17_DL_linear.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f26969a4",
   "metadata": {},
   "source": [
    "# Deep learning - Linear models "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "04150fdd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import tensorflow as tf\n",
    "\n",
    "from tensorflow.keras import Model, Sequential\n",
    "\n",
    "from tensorflow.keras.optimizers import Adam\n",
    "from tensorflow.keras.callbacks import EarlyStopping\n",
    "from tensorflow.keras.losses import MeanSquaredError\n",
    "from tensorflow.keras.metrics import MeanAbsoluteError\n",
    "\n",
    "from tensorflow.keras.layers import Dense, Conv1D, LSTM, RNN\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3353f47d",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams[\"figure.figsize\"] = (9,6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fb0ccd5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(42)\n",
    "tf.random.set_seed(42)\n",
    "tf.keras.utils.set_random_seed(42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a767c1fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df = pd.read_csv('data/train.csv')\n",
    "val_df = pd.read_csv('data/val.csv')\n",
    "test_df = pd.read_csv('data/test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f1d76f34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>HUFL</th>\n",
       "      <th>HULL</th>\n",
       "      <th>MUFL</th>\n",
       "      <th>MULL</th>\n",
       "      <th>LUFL</th>\n",
       "      <th>LULL</th>\n",
       "      <th>OT</th>\n",
       "      <th>day_sin</th>\n",
       "      <th>day_cos</th>\n",
       "      <th>year_sin</th>\n",
       "      <th>year_cos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.588227</td>\n",
       "      <td>0.454943</td>\n",
       "      <td>0.599461</td>\n",
       "      <td>0.473673</td>\n",
       "      <td>0.556576</td>\n",
       "      <td>0.613765</td>\n",
       "      <td>0.691018</td>\n",
       "      <td>0.866025</td>\n",
       "      <td>5.000000e-01</td>\n",
       "      <td>0.010486</td>\n",
       "      <td>-0.999945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.585130</td>\n",
       "      <td>0.459449</td>\n",
       "      <td>0.596738</td>\n",
       "      <td>0.471006</td>\n",
       "      <td>0.550279</td>\n",
       "      <td>0.620783</td>\n",
       "      <td>0.636233</td>\n",
       "      <td>0.965926</td>\n",
       "      <td>2.588190e-01</td>\n",
       "      <td>0.009770</td>\n",
       "      <td>-0.999952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.572743</td>\n",
       "      <td>0.436920</td>\n",
       "      <td>0.591319</td>\n",
       "      <td>0.465748</td>\n",
       "      <td>0.512595</td>\n",
       "      <td>0.586144</td>\n",
       "      <td>0.636233</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.440628e-12</td>\n",
       "      <td>0.009053</td>\n",
       "      <td>-0.999959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.571194</td>\n",
       "      <td>0.450437</td>\n",
       "      <td>0.591319</td>\n",
       "      <td>0.468414</td>\n",
       "      <td>0.515693</td>\n",
       "      <td>0.599955</td>\n",
       "      <td>0.581468</td>\n",
       "      <td>0.965926</td>\n",
       "      <td>-2.588190e-01</td>\n",
       "      <td>0.008336</td>\n",
       "      <td>-0.999965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.577388</td>\n",
       "      <td>0.450437</td>\n",
       "      <td>0.596738</td>\n",
       "      <td>0.473673</td>\n",
       "      <td>0.521990</td>\n",
       "      <td>0.599955</td>\n",
       "      <td>0.519656</td>\n",
       "      <td>0.866025</td>\n",
       "      <td>-5.000000e-01</td>\n",
       "      <td>0.007619</td>\n",
       "      <td>-0.999971</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       HUFL      HULL      MUFL      MULL      LUFL      LULL        OT  \\\n",
       "0  0.588227  0.454943  0.599461  0.473673  0.556576  0.613765  0.691018   \n",
       "1  0.585130  0.459449  0.596738  0.471006  0.550279  0.620783  0.636233   \n",
       "2  0.572743  0.436920  0.591319  0.465748  0.512595  0.586144  0.636233   \n",
       "3  0.571194  0.450437  0.591319  0.468414  0.515693  0.599955  0.581468   \n",
       "4  0.577388  0.450437  0.596738  0.473673  0.521990  0.599955  0.519656   \n",
       "\n",
       "    day_sin       day_cos  year_sin  year_cos  \n",
       "0  0.866025  5.000000e-01  0.010486 -0.999945  \n",
       "1  0.965926  2.588190e-01  0.009770 -0.999952  \n",
       "2  1.000000  7.440628e-12  0.009053 -0.999959  \n",
       "3  0.965926 -2.588190e-01  0.008336 -0.999965  \n",
       "4  0.866025 -5.000000e-01  0.007619 -0.999971  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5302ea2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def format_timeseries_data(df, input_length, output_length, target_names):\n",
    "    \n",
    "    if target_names is not None:\n",
    "        target_indices = {name: i for i, name in enumerate(target_names)}\n",
    "    col_indices = {name: i for i, name in enumerate(df.columns)}\n",
    "    \n",
    "    total_length = input_length + output_length\n",
    "    \n",
    "    input_slice = slice(0, input_length)\n",
    "    output_slice = slice(input_length, None)\n",
    "    \n",
    "    data = np.array(df, dtype=np.float32)\n",
    "    ds = tf.keras.preprocessing.timeseries_dataset_from_array(\n",
    "        data=data,\n",
    "        targets=None,\n",
    "        sequence_length=total_length,\n",
    "        sequence_stride=1,\n",
    "        shuffle=False,\n",
    "        batch_size=32\n",
    "    )\n",
    "    \n",
    "    def split_to_input_output(x):\n",
    "            \n",
    "        inputs = x[:, input_slice, :]\n",
    "        outputs = x[:, output_slice, :]\n",
    "        \n",
    "        if target_names is not None:\n",
    "            outputs = tf.stack(\n",
    "                [outputs[:,:,col_indices[name]] for name in target_names],\n",
    "                axis=-1\n",
    "            )\n",
    "\n",
    "        inputs.set_shape([None, input_length, None])\n",
    "        outputs.set_shape([None, output_length, None])\n",
    "    \n",
    "        return inputs, outputs\n",
    "    \n",
    "    ds = ds.map(split_to_input_output)\n",
    "    \n",
    "    return ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3f866f18",
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_model(model, train_ds, val_ds, patience=5, max_epochs=50):\n",
    "    \n",
    "    early_stopping = EarlyStopping(monitor='val_loss', patience=patience, mode='min')\n",
    "    \n",
    "    model.compile(loss=MeanSquaredError(), optimizer=Adam(), metrics=[MeanAbsoluteError()])\n",
    "    \n",
    "    history = model.fit(train_ds, epochs=max_epochs, validation_data=val_ds, callbacks=[early_stopping])\n",
    "    \n",
    "    return history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "af9bf579",
   "metadata": {},
   "outputs": [],
   "source": [
    "MULL_max_train = 7.568999767303468\n",
    "MULL_min_train = -5.934000015258789\n",
    "MULL_max_test = 4.690999984741211\n",
    "MULL_min_test = -3.3399999141693115\n",
    "\n",
    "OT_max_train = 46.00699996948242\n",
    "OT_min_train = -4.079999923706056\n",
    "OT_max_test = 17.165000915527347\n",
    "OT_min_test = 3.025000095367432"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3e14e70",
   "metadata": {},
   "source": [
    "## Single-step model "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "aa3e897d",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_ds_ss = format_timeseries_data(train_df, 1, 1, ['OT'])\n",
    "val_ds_ss = format_timeseries_data(val_df, 1, 1, ['OT'])\n",
    "test_ds_ss = format_timeseries_data(test_df, 1, 1, ['OT'])\n",
    "\n",
    "ss_sample_batch = next(iter(test_ds_ss))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2059d5b1",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "382/382 [==============================] - 2s 2ms/step - loss: 0.1654 - mean_absolute_error: 0.3268 - val_loss: 0.0671 - val_mean_absolute_error: 0.2249\n",
      "Epoch 2/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 0.0419 - mean_absolute_error: 0.1686 - val_loss: 0.0297 - val_mean_absolute_error: 0.1544\n",
      "Epoch 3/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 0.0187 - mean_absolute_error: 0.1104 - val_loss: 0.0132 - val_mean_absolute_error: 0.0984\n",
      "Epoch 4/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0128 - mean_absolute_error: 0.0890 - val_loss: 0.0051 - val_mean_absolute_error: 0.0576\n",
      "Epoch 5/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0104 - mean_absolute_error: 0.0780 - val_loss: 0.0041 - val_mean_absolute_error: 0.0496\n",
      "Epoch 6/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 0.0087 - mean_absolute_error: 0.0696 - val_loss: 0.0047 - val_mean_absolute_error: 0.0526\n",
      "Epoch 7/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0073 - mean_absolute_error: 0.0634 - val_loss: 0.0041 - val_mean_absolute_error: 0.0493\n",
      "Epoch 8/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0062 - mean_absolute_error: 0.0588 - val_loss: 0.0032 - val_mean_absolute_error: 0.0439\n",
      "Epoch 9/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0054 - mean_absolute_error: 0.0551 - val_loss: 0.0026 - val_mean_absolute_error: 0.0402\n",
      "Epoch 10/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0047 - mean_absolute_error: 0.0515 - val_loss: 0.0022 - val_mean_absolute_error: 0.0375\n",
      "Epoch 11/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0040 - mean_absolute_error: 0.0480 - val_loss: 0.0020 - val_mean_absolute_error: 0.0353\n",
      "Epoch 12/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 0.0035 - mean_absolute_error: 0.0445 - val_loss: 0.0018 - val_mean_absolute_error: 0.0333\n",
      "Epoch 13/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0029 - mean_absolute_error: 0.0411 - val_loss: 0.0015 - val_mean_absolute_error: 0.0310\n",
      "Epoch 14/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0025 - mean_absolute_error: 0.0379 - val_loss: 0.0013 - val_mean_absolute_error: 0.0284\n",
      "Epoch 15/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0021 - mean_absolute_error: 0.0349 - val_loss: 0.0011 - val_mean_absolute_error: 0.0258\n",
      "Epoch 16/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0018 - mean_absolute_error: 0.0322 - val_loss: 8.7467e-04 - val_mean_absolute_error: 0.0234\n",
      "Epoch 17/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 0.0015 - mean_absolute_error: 0.0296 - val_loss: 7.1501e-04 - val_mean_absolute_error: 0.0211\n",
      "Epoch 18/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0013 - mean_absolute_error: 0.0271 - val_loss: 5.8000e-04 - val_mean_absolute_error: 0.0189\n",
      "Epoch 19/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0011 - mean_absolute_error: 0.0249 - val_loss: 4.6851e-04 - val_mean_absolute_error: 0.0169\n",
      "Epoch 20/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 9.3886e-04 - mean_absolute_error: 0.0229 - val_loss: 3.8049e-04 - val_mean_absolute_error: 0.0152\n",
      "Epoch 21/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 8.1608e-04 - mean_absolute_error: 0.0211 - val_loss: 3.1382e-04 - val_mean_absolute_error: 0.0137\n",
      "Epoch 22/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 7.2068e-04 - mean_absolute_error: 0.0197 - val_loss: 2.6332e-04 - val_mean_absolute_error: 0.0125\n",
      "Epoch 23/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 6.4817e-04 - mean_absolute_error: 0.0186 - val_loss: 2.2484e-04 - val_mean_absolute_error: 0.0115\n",
      "Epoch 24/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 5.9441e-04 - mean_absolute_error: 0.0177 - val_loss: 2.0320e-04 - val_mean_absolute_error: 0.0109\n",
      "Epoch 25/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 5.5563e-04 - mean_absolute_error: 0.0170 - val_loss: 2.0628e-04 - val_mean_absolute_error: 0.0110\n",
      "Epoch 26/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 5.2844e-04 - mean_absolute_error: 0.0165 - val_loss: 2.2475e-04 - val_mean_absolute_error: 0.0116\n",
      "Epoch 27/50\n",
      "382/382 [==============================] - 1s 2ms/step - loss: 5.0973e-04 - mean_absolute_error: 0.0162 - val_loss: 2.3362e-04 - val_mean_absolute_error: 0.0119\n",
      "Epoch 28/50\n",
      "382/382 [==============================] - 1s 2ms/step - loss: 4.9662e-04 - mean_absolute_error: 0.0160 - val_loss: 2.2154e-04 - val_mean_absolute_error: 0.0116\n",
      "Epoch 29/50\n",
      "382/382 [==============================] - 1s 2ms/step - loss: 4.8686e-04 - mean_absolute_error: 0.0158 - val_loss: 2.0022e-04 - val_mean_absolute_error: 0.0109\n",
      "Epoch 30/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 4.7927e-04 - mean_absolute_error: 0.0157 - val_loss: 1.8344e-04 - val_mean_absolute_error: 0.0103\n",
      "Epoch 31/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 4.7350e-04 - mean_absolute_error: 0.0156 - val_loss: 1.7430e-04 - val_mean_absolute_error: 0.0099\n",
      "Epoch 32/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 4.6929e-04 - mean_absolute_error: 0.0155 - val_loss: 1.7036e-04 - val_mean_absolute_error: 0.0097\n",
      "Epoch 33/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.6621e-04 - mean_absolute_error: 0.0154 - val_loss: 1.6938e-04 - val_mean_absolute_error: 0.0097\n",
      "Epoch 34/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.6380e-04 - mean_absolute_error: 0.0154 - val_loss: 1.6978e-04 - val_mean_absolute_error: 0.0097\n",
      "Epoch 35/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.6180e-04 - mean_absolute_error: 0.0153 - val_loss: 1.7025e-04 - val_mean_absolute_error: 0.0097\n",
      "Epoch 36/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 4.6009e-04 - mean_absolute_error: 0.0153 - val_loss: 1.7021e-04 - val_mean_absolute_error: 0.0097\n",
      "Epoch 37/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 4.5860e-04 - mean_absolute_error: 0.0152 - val_loss: 1.6982e-04 - val_mean_absolute_error: 0.0097\n",
      "Epoch 38/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.5723e-04 - mean_absolute_error: 0.0152 - val_loss: 1.6935e-04 - val_mean_absolute_error: 0.0096\n",
      "Epoch 39/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.5591e-04 - mean_absolute_error: 0.0152 - val_loss: 1.6882e-04 - val_mean_absolute_error: 0.0096\n",
      "Epoch 40/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.5459e-04 - mean_absolute_error: 0.0151 - val_loss: 1.6815e-04 - val_mean_absolute_error: 0.0096\n",
      "Epoch 41/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.5330e-04 - mean_absolute_error: 0.0151 - val_loss: 1.6738e-04 - val_mean_absolute_error: 0.0096\n",
      "Epoch 42/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.5204e-04 - mean_absolute_error: 0.0151 - val_loss: 1.6664e-04 - val_mean_absolute_error: 0.0095\n",
      "Epoch 43/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.5082e-04 - mean_absolute_error: 0.0150 - val_loss: 1.6599e-04 - val_mean_absolute_error: 0.0095\n",
      "Epoch 44/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.4960e-04 - mean_absolute_error: 0.0150 - val_loss: 1.6538e-04 - val_mean_absolute_error: 0.0095\n",
      "Epoch 45/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.4841e-04 - mean_absolute_error: 0.0150 - val_loss: 1.6477e-04 - val_mean_absolute_error: 0.0095\n",
      "Epoch 46/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.4723e-04 - mean_absolute_error: 0.0149 - val_loss: 1.6414e-04 - val_mean_absolute_error: 0.0094\n",
      "Epoch 47/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.4609e-04 - mean_absolute_error: 0.0149 - val_loss: 1.6353e-04 - val_mean_absolute_error: 0.0094\n",
      "Epoch 48/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.4498e-04 - mean_absolute_error: 0.0149 - val_loss: 1.6296e-04 - val_mean_absolute_error: 0.0094\n",
      "Epoch 49/50\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "382/382 [==============================] - 0s 1ms/step - loss: 4.4389e-04 - mean_absolute_error: 0.0149 - val_loss: 1.6242e-04 - val_mean_absolute_error: 0.0094\n",
      "Epoch 50/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 4.4282e-04 - mean_absolute_error: 0.0148 - val_loss: 1.6187e-04 - val_mean_absolute_error: 0.0094\n"
     ]
    }
   ],
   "source": [
    "ss_linear = Sequential([\n",
    "    Dense(units=1)\n",
    "])\n",
    "\n",
    "ss_linear_history = train_model(ss_linear, train_ds_ss, val_ds_ss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9720af27",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_history(history):\n",
    "\n",
    "    fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2)\n",
    "\n",
    "    ax1.plot(history.history['loss'], label='Train')\n",
    "    ax1.plot(history.history['val_loss'], label='Validation')\n",
    "    ax1.set_xlabel('Epochs')\n",
    "    ax1.set_ylabel('Loss')\n",
    "    ax1.set_title('Loss')\n",
    "    ax1.legend(loc='best')\n",
    "\n",
    "    ax2.plot(history.history['mean_absolute_error'], label='Train')\n",
    "    ax2.plot(history.history['val_mean_absolute_error'], label='Validation')\n",
    "    ax2.set_xlabel('Epochs')\n",
    "    ax2.set_ylabel('MAE')\n",
    "    ax2.set_title('Mean absolute error')\n",
    "    ax2.legend(loc='best')\n",
    "\n",
    "    plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2a19bc3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_history(ss_linear_history)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9d33e9a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_predictions(model, sample_batch, model_type):\n",
    "    \n",
    "    inputs, outputs = sample_batch\n",
    "    preds = model(inputs)\n",
    "    \n",
    "    if model_type == 'single_step':      \n",
    "\n",
    "        fig, ax = plt.subplots()\n",
    "\n",
    "        actual_scaled = outputs.numpy().flatten()\n",
    "        actual = actual_scaled * (OT_max_test - OT_min_test) + OT_min_test\n",
    "        \n",
    "        predictions_scaled = preds.numpy().flatten()\n",
    "        predictions = predictions_scaled * (OT_max_train - OT_min_train) + OT_min_train\n",
    "        \n",
    "        ax.plot(actual, label='Actual')\n",
    "        ax.plot(predictions, label='Predicted')\n",
    "        ax.set_xlabel('Time steps')\n",
    "        ax.set_ylabel('Oil temperature')\n",
    "        ax.set_title('Predictions on a sample batch')\n",
    "        ax.legend(loc='best')\n",
    "        \n",
    "    elif model_type == 'multi_step':\n",
    "\n",
    "        fig, ax = plt.subplots()\n",
    "        \n",
    "        actual_scaled = outputs.numpy().flatten()[:48]\n",
    "        actual = actual_scaled * (OT_max_test - OT_min_test) + OT_min_test\n",
    "        \n",
    "        predictions_scaled = preds.numpy().flatten()[:48]\n",
    "        predictions = predictions_scaled * (OT_max_train - OT_min_train) + OT_min_train\n",
    "\n",
    "        ax.plot(actual, label='Actual')\n",
    "        ax.plot(predictions, label='Predicted')\n",
    "        ax.set_xlabel('Time steps')\n",
    "        ax.set_ylabel('Oil temperature')\n",
    "        ax.set_title('Predictions on a sample batch')\n",
    "        ax.legend(loc='best')\n",
    "        \n",
    "    elif model_type == 'multi_output':\n",
    "        \n",
    "        fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1)\n",
    "        \n",
    "        OT_actual_scaled = outputs.numpy().flatten()[0::2]\n",
    "        OT_actual = OT_actual_scaled * (OT_max_test - OT_min_test) + OT_min_test\n",
    "        \n",
    "        OT_predictions_scaled = preds.numpy().flatten()[0::2]\n",
    "        OT_predictions = OT_predictions_scaled * (OT_max_train - OT_min_train) + OT_min_train\n",
    "\n",
    "        MULL_actual_scaled = outputs.numpy().flatten()[1::2]\n",
    "        MULL_actual = MULL_actual_scaled * (MULL_max_test - MULL_min_test) + MULL_min_test\n",
    "        \n",
    "        MULL_predictions_scaled = preds.numpy().flatten()[1::2]\n",
    "        MULL_predictions = MULL_predictions_scaled * (MULL_max_train - MULL_min_train) + MULL_min_train\n",
    "        \n",
    "        ax1.plot(OT_actual, label='Actual')\n",
    "        ax1.plot(OT_predictions, label='Predicted')\n",
    "        ax1.set_xlabel('Time')\n",
    "        ax1.set_ylabel('Oil temperature')\n",
    "        ax1.legend(loc='best')\n",
    "        ax1.set_title('Predictions on a sample batch')\n",
    "        \n",
    "        ax2.plot(MULL_actual, label='Actual')\n",
    "        ax2.plot(MULL_predictions, label='Predicted')\n",
    "        ax2.set_xlabel('Time')\n",
    "        ax2.set_ylabel('MULL')\n",
    "        ax2.legend(loc='best')\n",
    "        \n",
    "    plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "45189ab0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_predictions(ss_linear, ss_sample_batch, 'single_step')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "101f78a2",
   "metadata": {},
   "source": [
    "## Multi-step model "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "fb0a1626",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_ds_ms = format_timeseries_data(train_df, 24, 24, ['OT'])\n",
    "val_ds_ms = format_timeseries_data(val_df, 24, 24, ['OT'])\n",
    "test_ds_ms = format_timeseries_data(test_df, 24, 24, ['OT'])\n",
    "\n",
    "ms_sample_batch = next(iter(test_ds_ms))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "00a1f809",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "380/380 [==============================] - 1s 2ms/step - loss: 0.2100 - mean_absolute_error: 0.3621 - val_loss: 0.0767 - val_mean_absolute_error: 0.2417\n",
      "Epoch 2/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0488 - mean_absolute_error: 0.1815 - val_loss: 0.0281 - val_mean_absolute_error: 0.1357\n",
      "Epoch 3/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0263 - mean_absolute_error: 0.1277 - val_loss: 0.0245 - val_mean_absolute_error: 0.1241\n",
      "Epoch 4/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0205 - mean_absolute_error: 0.1114 - val_loss: 0.0286 - val_mean_absolute_error: 0.1375\n",
      "Epoch 5/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0171 - mean_absolute_error: 0.1023 - val_loss: 0.0291 - val_mean_absolute_error: 0.1407\n",
      "Epoch 6/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0144 - mean_absolute_error: 0.0944 - val_loss: 0.0255 - val_mean_absolute_error: 0.1319\n",
      "Epoch 7/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0123 - mean_absolute_error: 0.0876 - val_loss: 0.0209 - val_mean_absolute_error: 0.1187\n",
      "Epoch 8/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0107 - mean_absolute_error: 0.0819 - val_loss: 0.0170 - val_mean_absolute_error: 0.1065\n",
      "Epoch 9/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0095 - mean_absolute_error: 0.0770 - val_loss: 0.0141 - val_mean_absolute_error: 0.0965\n",
      "Epoch 10/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0085 - mean_absolute_error: 0.0729 - val_loss: 0.0118 - val_mean_absolute_error: 0.0881\n",
      "Epoch 11/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0077 - mean_absolute_error: 0.0693 - val_loss: 0.0099 - val_mean_absolute_error: 0.0802\n",
      "Epoch 12/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0071 - mean_absolute_error: 0.0662 - val_loss: 0.0081 - val_mean_absolute_error: 0.0724\n",
      "Epoch 13/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0066 - mean_absolute_error: 0.0636 - val_loss: 0.0066 - val_mean_absolute_error: 0.0651\n",
      "Epoch 14/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0062 - mean_absolute_error: 0.0615 - val_loss: 0.0054 - val_mean_absolute_error: 0.0588\n",
      "Epoch 15/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0059 - mean_absolute_error: 0.0596 - val_loss: 0.0045 - val_mean_absolute_error: 0.0534\n",
      "Epoch 16/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0056 - mean_absolute_error: 0.0581 - val_loss: 0.0038 - val_mean_absolute_error: 0.0491\n",
      "Epoch 17/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0054 - mean_absolute_error: 0.0567 - val_loss: 0.0033 - val_mean_absolute_error: 0.0455\n",
      "Epoch 18/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0052 - mean_absolute_error: 0.0555 - val_loss: 0.0029 - val_mean_absolute_error: 0.0426\n",
      "Epoch 19/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0050 - mean_absolute_error: 0.0545 - val_loss: 0.0026 - val_mean_absolute_error: 0.0403\n",
      "Epoch 20/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0049 - mean_absolute_error: 0.0536 - val_loss: 0.0024 - val_mean_absolute_error: 0.0386\n",
      "Epoch 21/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0047 - mean_absolute_error: 0.0529 - val_loss: 0.0022 - val_mean_absolute_error: 0.0372\n",
      "Epoch 22/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0046 - mean_absolute_error: 0.0522 - val_loss: 0.0021 - val_mean_absolute_error: 0.0362\n",
      "Epoch 23/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0045 - mean_absolute_error: 0.0516 - val_loss: 0.0020 - val_mean_absolute_error: 0.0354\n",
      "Epoch 24/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0045 - mean_absolute_error: 0.0512 - val_loss: 0.0019 - val_mean_absolute_error: 0.0349\n",
      "Epoch 25/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0044 - mean_absolute_error: 0.0507 - val_loss: 0.0019 - val_mean_absolute_error: 0.0346\n",
      "Epoch 26/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0043 - mean_absolute_error: 0.0504 - val_loss: 0.0018 - val_mean_absolute_error: 0.0344\n",
      "Epoch 27/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0043 - mean_absolute_error: 0.0501 - val_loss: 0.0018 - val_mean_absolute_error: 0.0343\n",
      "Epoch 28/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0042 - mean_absolute_error: 0.0498 - val_loss: 0.0018 - val_mean_absolute_error: 0.0342\n",
      "Epoch 29/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0042 - mean_absolute_error: 0.0496 - val_loss: 0.0018 - val_mean_absolute_error: 0.0342\n",
      "Epoch 30/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0042 - mean_absolute_error: 0.0494 - val_loss: 0.0018 - val_mean_absolute_error: 0.0343\n",
      "Epoch 31/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0041 - mean_absolute_error: 0.0492 - val_loss: 0.0018 - val_mean_absolute_error: 0.0344\n",
      "Epoch 32/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0041 - mean_absolute_error: 0.0491 - val_loss: 0.0018 - val_mean_absolute_error: 0.0345\n",
      "Epoch 33/50\n",
      "380/380 [==============================] - 1s 1ms/step - loss: 0.0041 - mean_absolute_error: 0.0490 - val_loss: 0.0018 - val_mean_absolute_error: 0.0346\n",
      "Epoch 34/50\n",
      "380/380 [==============================] - 0s 1ms/step - loss: 0.0041 - mean_absolute_error: 0.0489 - val_loss: 0.0018 - val_mean_absolute_error: 0.0347\n"
     ]
    }
   ],
   "source": [
    "ms_linear = Sequential([\n",
    "    Dense(units=1)\n",
    "])\n",
    "\n",
    "ms_linear_history = train_model(ms_linear, train_ds_ms, val_ds_ms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5f6c222c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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cdna2ce+99xqtW7c27Ha7ERsba3Ts2NGYNGmSkZ6efsrPbdWqVcZFF11k1K1b1wgPDzcaN25sXHTRRcZbb73l28f732D//v3FXp+UlGRcdNFFJR77u+++M4YOHWrExsYadrvd6Ny5c5H/FoZxfHXNE88n1ZPFMAwj8NFSRERERERE/EGra4qIiIiIiIQQhTwREREREZEQopAnIiIiIiISQhTyREREREREQohCnoiIiIiISAhRyBMREREREQkhKoZeArfbzZ49e4iOjvYVjhYRkeBnGAaHDx+mUaNGWK36HbMsutaJiFQ/5b3OKeSVYM+ePSQmJprdDBERqaCdO3fSpEkTs5sR1HStExGpvk51nVPIK0F0dDTg+fBiYmJMbo2IiJRXVlYWiYmJvu9xKZ2udSIi1U95r3MKeSXwDluJiYnRhU9EpBrS8MNT07VORKT6OtV1ThMWREREREREQohCnoiIiIiISAhRyBMREREREQkhmpMnIiHN7XaTl5dndjOkioSHh2Oz2cxuhohIUHG5XOTn55vdDKkCVXWdU8gTkZCVl5fHH3/8gdvtNrspUoVq165NQkKCFlcRkRrPMAzS09PJyMgwuylShariOqeQJyIhyTAM0tLSsNlsJCYmqjB2CDAMg5ycHPbt2wdAw4YNTW6RiIi5vAGvQYMGREZG6sevaq4qr3MKeSISkgoKCsjJyaFRo0ZERkaa3RypIhEREQDs27ePBg0aaOimiNRYLpfLF/Di4uLMbo5Ukaq6zumnbREJSS6XCwC73W5yS6SqeUO75p+ISE3m/Q7UD5mhpyqucwp5IhLSNHQl9Oi/qYjIcfpODD1V8d9UIU9ERERERCSEKOSJiIS48847j4kTJ5rdDBEREb/Rta4oLbwiIhIkTjU849prryUlJeW0j/v2228THh5ewVaJiIhUHV3rAkMhT0QkSKSlpfnuL1q0iPvvv5+ff/7Zt8274pZXfn5+uS5odevWrbpGioiIVIKudYGh4ZoiIkEiISHBd4uNjcVisfgeHzt2jNq1a7N48WLOO+88nE4nb7zxBgcPHuSqq66iSZMmREZG0rFjRxYsWFDkuCcPYWnWrBkPP/ww119/PdHR0TRt2pSXXnopwO9WRERqIl3rAkMhT0RqBMMwyMkrMOVmGEaVvY+7776bv//972zZsoVBgwZx7NgxunfvzgcffMD333/PjTfeyKhRo9iwYUOZx3niiSfo0aMHmzZtYsKECdx888389NNPVdZOEREJPF3riqrJ1zoN1xSRGuFovot2939syrl/nDGISHvVfN1OnDiRyy+/vMi2O++803f/tttu46OPPuKtt96iV69epR5nyJAhTJgwAfBcTGfNmsXKlStp06ZNlbRTREQCT9e6omrytU4hT0SkGunRo0eRxy6Xi0ceeYRFixaxe/ducnNzyc3NJSoqqszjdOrUyXffO1Rm3759fmmziIjI6dC1rvIU8kSkRogIt/HjjEGmnbuqnHxBe+KJJ5g1axazZ8+mY8eOREVFMXHiRPLy8so8zsmT2C0WC263u8raKSIigadrXVE1+VqnkCciNYLFYqmyYSTBZM2aNQwbNoxrrrkGALfbzdatW2nbtq3JLRMRkUDTtU68tPCKH2Qezeem179mbMpXZjdFRELcGWecwYoVK1i3bh1btmzhpptuIj093exmSQ3w5obtjHvtK95N3W12U0QkxOlad/oU8vzAMAw+/mEv//tpHwWumtElLCLmuO++++jWrRuDBg3ivPPOIyEhgUsvvdTsZkkNsHVvNp9s2cfWvdlmN0VEQpyudacv9Ppzg4A97Hh2znO5CbMpS4vI6RkzZgxjxozxPW7WrFmJy1PXrVuXd955p8xjrVy5ssjjbdu2FdsnNTX19BspNZqzcP7N0XyXyS0RkepK1zr/UfrwA/sJoS6vQD15IiISeiLtnpCXk6eQJyISbBTy/CDMZsVq8dzPVcgTEZEQ5F1J75h68kREgo5Cnp84wjwXP/XkiYhIKHIW9uQdVU+eiEjQUcjzE++8PPXkiYhIKIrQnDwRkaClkOcn3pCnnjwREQlFCnkiIsFLIc9PvIuv5Bbo4iciIqEnUsM1RUSClkKenzjC1ZMnIiKhSyUURESCl0Ken3h78vJUDF1EREJQhHryRESClkKenzg0J09EREKYSiiIiAQvhTw/0eqaImKG8847j4kTJ/oeN2vWjNmzZ5f5GovFwjvvvFPpc1fVcaR68IY8FUMXkUDTte7UFPL8RHXyROR0DR06lAsuuKDE59avX4/FYuGbb745rWN+9dVX3HjjjVXRPJ9p06bRpUuXYtvT0tIYPHhwlZ5LgpdvuGa+C8MwTG6NiFQXutYFhkKen6iEgoicrrFjx/Lpp5+yffv2Ys/NnTuXLl260K1bt9M6Zv369YmMjKyqJpYpISEBh8MRkHNVN3PmzKF58+Y4nU66d+/OmjVrSt137dq19O3bl7i4OCIiImjTpg2zZs0qsk9KSgoWi6XY7dixY/5+Kz7ekAcatSIi5adrXWAo5PmJr4SCFl4RkXK6+OKLadCgASkpKUW25+TksGjRIi699FKuuuoqmjRpQmRkJB07dmTBggVlHvPkISxbt27lnHPOwel00q5dO1asWFHsNXfffTdnnnkmkZGRtGjRgvvuu4/8/HzAEy6mT5/O5s2bfcHC296Th7B89913/OUvfyEiIoK4uDhuvPFGsrOzfc+PGTOGSy+9lMcff5yGDRsSFxfHLbfc4jtXqFi0aBETJ05k6tSpbNq0iX79+jF48GB27NhR4v5RUVHceuutrF69mi1btnDvvfdy77338tJLLxXZLyYmhrS0tCI3p9MZiLcEgDPs+D8htPiKiJSXrnWBudaF+fXoNZi3hEKuJqSLBAfDgPwcc84dHgkWyyl3CwsLY/To0aSkpHD//fdjKXzNW2+9RV5eHuPGjWPBggXcfffdxMTE8OGHHzJq1ChatGhBr169Tnl8t9vN5ZdfTr169fjiiy/IysoqMqfBKzo6mpSUFBo1asR3333HDTfcQHR0NHfddRcjR47k+++/56OPPuKTTz4BIDY2ttgxcnJyuPDCC+nduzdfffUV+/btY9y4cdx6661FLuyfffYZDRs25LPPPuPXX39l5MiRdOnShRtuuOGU76e6ePLJJxk7dizjxo0DYPbs2Xz88cc8//zzzJw5s9j+Xbt2pWvXrr7HzZo14+2332bNmjVFhiNZLBYSEhL8/wZKEWazYrdZyXO5OZrvoo5pLRERH13rdK0rpJDnJyqhIBJk8nPg4UbmnPsfe8AeVa5dr7/+ev71r3+xcuVKzj//fMAzfOXyyy+ncePG3Hnnnb59b7vtNj766CPeeuutcl34PvnkE7Zs2cK2bdto0qQJAA8//HCxuQX33nuv736zZs244447WLRoEXfddRcRERHUqlWLsLCwMgPGm2++ydGjR5k3bx5RUZ73/uyzzzJ06FAeffRR4uPjAahTpw7PPvssNpuNNm3acNFFF/G///0vZEJeXl4eGzdu5J577imyfeDAgaxbt65cx9i0aRPr1q3jn//8Z5Ht2dnZJCUl4XK56NKlCw8++GCRcHiy3NxccnNzfY+zsrJO452ULMJuI++oW4uviAQLXet0rSuk4Zp+ojl5IlIRbdq0oU+fPsydOxeA3377jTVr1nD99dfjcrl46KGH6NSpE3FxcdSqVYvly5eXOuzvZFu2bKFp06a+ix5AcnJysf3+85//cPbZZ5OQkECtWrW47777yn2OE8/VuXNn30UPoG/fvrjdbn7++Wfftvbt22OzHZ/b1bBhQ/bt23da5wpmBw4cwOVy+S70XvHx8aSnp5f52iZNmuBwOOjRowe33HKLrycQPP87SUlJ4b333mPBggU4nU769u3L1q1bSz3ezJkziY2N9d0SExMr9+ZQGQURqRhd6/x/rTO9J2/OnDn861//Ii0tjfbt2zN79mz69etX4r5vv/02zz//PKmpqeTm5tK+fXumTZvGoEGDiuy3ZMkS7rvvPn777TdatmzJQw89xGWXXRaIt+OjEgoiQSY80vMro1nnPg1jx47l1ltv5bnnnuPVV18lKSmJ/v37869//YtZs2Yxe/ZsOnbsSFRUFBMnTiQvL69cxy1pBUTLSUNrvvjiC6688kqmT5/OoEGDiI2NZeHChTzxxBOn9R4Mwyh27JLOGR4eXuw5tzv0vjdP/izK+ny81qxZQ3Z2Nl988QX33HMPZ5xxBldddRUAvXv3pnfv3r59+/btS7du3XjmmWd4+umnSzzelClTmDx5su9xVlZWpYPeiStsikgQ0LVO17pCpoY872T0OXPm0LdvX1588UUGDx7Mjz/+SNOmTYvtv3r1agYMGMDDDz9M7dq1efXVVxk6dCgbNmzwDVFZv349I0eO5MEHH+Syyy5j6dKljBgxgrVr15ari7eqqISCSJCxWMo9jMRsI0aM4Pbbb2f+/Pm89tpr3HDDDVgsFtasWcOwYcO45pprAM+8g61bt9K2bdtyHbddu3bs2LGDPXv20KiRZzjP+vXri+zz+eefk5SUxNSpU33bTl4BzW6343KV/Y/6du3a8dprr3HkyBHfL5yff/45VquVM888s1ztDQX16tXDZrMV67Xbt29fsd69kzVv3hyAjh07snfvXqZNm+YLeSezWq2cddZZZfbkORyOKl8RzlnYk6eFV0SChK51utYVMnW45omT0du2bcvs2bNJTEzk+eefL3H/2bNnc9ddd3HWWWfRqlUrHn74YVq1asX7779fZJ8BAwYwZcoU2rRpw5QpU+jfv/8pCyRWNQ3XFJGKqlWrFiNHjuQf//gHe/bsYcyYMQCcccYZrFixgnXr1rFlyxZuuummUw75O9EFF1xA69atGT16NJs3b2bNmjVFLnDec+zYsYOFCxfy22+/8fTTT7N06dIi+zRr1ow//viD1NRUDhw4UGSel9ff/vY3nE4n1157Ld9//z2fffYZt912G6NGjTpluAkldrud7t27F1vZbcWKFfTp06fcxzEMo8TP+cTnU1NTadiwYYXbWhERhYuMqSdPRE6XrnX+ZVrI805GHzhwYJHtpzMZ3e12c/jwYerWrevbtn79+mLHHDRoULmPWVUcCnkiUgljx47lzz//5IILLvCNbLjvvvvo1q0bgwYN4rzzziMhIYFLL7203Me0Wq0sXbqU3Nxcevbsybhx43jooYeK7DNs2DAmTZrErbfeSpcuXVi3bh333XdfkX2uuOIKLrzwQs4//3zq169f4tLWkZGRfPzxxxw6dIizzjqL4cOH079/f5599tnT/zCqucmTJ/Pyyy8zd+5ctmzZwqRJk9ixYwfjx48HPMMoR48e7dv/ueee4/3332fr1q1s3bqVV199lccff9z3qzbA9OnT+fjjj/n9999JTU1l7NixpKam+o4ZKJF2z4Ag9eSJSEXoWudHhkl2795tAMbnn39eZPtDDz1knHnmmeU6xmOPPWbUrVvX2Lt3r29beHi48eabbxbZ78033zTsdnupxzl27JiRmZnpu+3cudMAjMzMzNN4R0W9tOo3I+nuD4zbF3xT4WOISMUdPXrU+PHHH42jR4+a3RSpYmX9t83MzKz097c/PPfcc0ZSUpJht9uNbt26GatWrfI9d+211xrnnnuu7/HTTz9ttG/f3oiMjDRiYmKMrl27GnPmzDFcLpdvn4kTJxpNmzY17Ha7Ub9+fWPgwIHGunXrTqtNVfFZjU35yki6+wNj/obtFT6GiFSMrnOhqyquc6YvvFKRyegACxYsYNq0abz77rs0aNCgUsecOXMm06dPP41Wn5q3Tp5KKIiIyIQJE5gwYUKJz51cEPi2227jtttuK/N4s2bNYtasWVXVvArzLbyinjwRkaBi2nDNykxGX7RoEWPHjmXx4sVccMEFRZ5LSEg47WNOmTKFzMxM323nzp2n+W6K89XJ03BNEREJUZqTJyISnEwLeRWdjL5gwQLGjBnD/Pnzueiii4o9n5ycXOyYy5cvL/OYDoeDmJiYIrfKUgkFEREJdaqTJyISnEwdrjl58mRGjRpFjx49SE5O5qWXXio2GX337t3MmzcP8AS80aNH89RTT9G7d29fj11ERASxsbEA3H777Zxzzjk8+uijDBs2jHfffZdPPvmEtWvXBvS9KeSJiEioiyhceCVHwzVFRIKKqSUURo4cyezZs5kxYwZdunRh9erVLFu2jKSkJADS0tKKVJ5/8cUXKSgo4JZbbqFhw4a+2+233+7bp0+fPixcuJBXX32VTp06kZKSwqJFiwJaIw9UJ09EREKftydPwzVFRIKL6QuvnM5k9JUrV5brmMOHD2f48OGVbFnlqE6eSHAwDMPsJkgVc7v1vRosIuyea90x9eSJmEbfiaGnKv6bmh7yQpVv4RWtriliivDwcCwWC/v376d+/frlWrVXgpthGOTl5bF//36sVit2u93sJtV46skTMY/dbsdqtbJnzx7q16+P3W7Xta6aq8rrnEKen3hLKOQW6MInYgabzUaTJk3YtWsX27ZtM7s5UoUiIyNp2rQpVqupMw4EzckTMZPVaqV58+akpaWxZ88es5sjVagqrnMKeX6iEgoi5qtVqxatWrUiPz/f7KZIFbHZbISFhenX6iChnjwRc9ntdpo2bUpBQQEul/5/GAqq6jqnkOcnDs3JEwkKNpsNm81mdjNEQpJvTp5CnohpLBYL4eHhhIeHm90UCSIa6+InKqEgIiKhzuntydNwTRGRoKKQ5ycqoSAiIqFOwzVFRIKTQp6feHvyCtwGbreWcBcRkdATWbjwinryRESCi0Ken3hDHqiMgoiIhCb15ImIBCeFPD/xrq4JkJuvkCciIqHHWbjwytF8F4ahUSsiIsFCIc9Pwm0WvCuf5mpJWxERCUHenjzD0EJjIiLBRCHPTywWi2rliYhISPOGPFAZBRGRYKKQ50d21coTEZEQFmaz+n7QzNHiKyIiQUMhz48cqpUnIiIhzhl+fF6eiIgEB4U8P1KtPBERCXURdhVEFxEJNgp5fuQbrqkSCiIiEqK88/I0J09EJHgo5PmRd56CSiiIiEioiigsiK45eSIiwUMhz48c4d6ePF34REQkNEVoTp6ISNBRyPMjlVAQEZFQ552Tp+GaIiLBQyHPj+xaXVNEREKcd06eFl4REQkeCnl+pJAnIiKhzukNeerJExEJGgp5fuRQMXQREQlxkYXDNbXwiohI8FDI8yO76uSJiEiIUwkFEZHgo5DnR76FV1QnT0REQpRTxdBFRIKOQp4f+ebkqU6eiIiEqAjNyRMRCToKeX7km5OnOnkiIhKiFPJERIKPQp4faeEVEREJdZEarikiEnQU8vzIrpAnIiIhTiUURESCj0KeH3kXXlGdPBERCVUR6skTEQk6Cnl+5AhXT56IiIQ2lVAQEQk+Cnl+5OvJUwkFEREJUb6ePIU8EZGgoZDnR95i6CqhICIiocrbk5ej4ZoiIkFDIc+PjpdQUMgTEZHQ5O3J03BNEZHgoZDnR8dX19SFT0REQpOvTp568kREgoZCnh+phIKIiIS6E4uhG4ZhcmtERAQU8vzKG/JUQkFEREKVd7im29D1TkQkWCjk+ZFDPXkiIhLivMXQQfPyRESChUKeH2nhFRERCXXhNivhNgugMgoiIsFCIc+P7DbPr5vqyRMRkVDm1OIrIiJBRSHPjzQnT0REaoITF18RERHzKeT5kebkiYhITRBpV0+eiEgwUcjzI5VQEBGRmsCpnjwRkaCikOdH9hMWXlHtIBERCVUR6skTEQkqCnl+5A15oHl5IiISujQnT0QkuCjk+ZHjhJCnMgoiIhKqvHPyVCdPRCQ4KOT5kd12QshTT56IiIQo75y8HA3XFBEJCgp5fmSxWHxBT8M1RUQkVGm4pohIcFHI8zOVURARkVDnXXjlmHryRESCgkKen6mMgoiIhDr15ImIBBeFPD9TyBMRkVDn7cnTnDwRkeCgkOdn3pCXW6ALn4iIhCb15ImIBBeFPD/TnDwREQl1ESqhICISVBTy/MzXk6c6eSIiEqK8JRSOarimiEhQUMjzM28JBfXkiYhIqNJwTRGR4KKQ52fH5+Qp5ImISGiKtKsnT0QkmCjk+ZkjzHPhU0+eiEjNNWfOHJo3b47T6aR79+6sWbOm1H3Xrl1L3759iYuLIyIigjZt2jBr1qxi+y1ZsoR27drhcDho164dS5cu9edbKJN68kREgotCnp+phIKISM22aNEiJk6cyNSpU9m0aRP9+vVj8ODB7Nixo8T9o6KiuPXWW1m9ejVbtmzh3nvv5d577+Wll17y7bN+/XpGjhzJqFGj2Lx5M6NGjWLEiBFs2LAhUG+rCKddIU9EJJgo5PnZ8ZCnC5+ISE305JNPMnbsWMaNG0fbtm2ZPXs2iYmJPP/88yXu37VrV6666irat29Ps2bNuOaaaxg0aFCR3r/Zs2czYMAApkyZQps2bZgyZQr9+/dn9uzZAXpXRfl68vL0g6aISDBQyPMzh01z8kREaqq8vDw2btzIwIEDi2wfOHAg69atK9cxNm3axLp16zj33HN929avX1/smIMGDSr3MatapEooiIgElTCzGxDqHOEarikiUlMdOHAAl8tFfHx8ke3x8fGkp6eX+domTZqwf/9+CgoKmDZtGuPGjfM9l56eftrHzM3NJTc31/c4KyvrdN5Kmbw9eTl5BRiGgcViqbJji4jI6VNPnp/5SiioTp6ISI11cugpTxBas2YNX3/9NS+88AKzZ89mwYIFlTrmzJkziY2N9d0SExNP812Uzjsnz23oeiciEgzUk+dnKqEgIlJz1atXD5vNVqyHbd++fcV64k7WvHlzADp27MjevXuZNm0aV111FQAJCQmnfcwpU6YwefJk3+OsrKwqC3renjyAY3lu38rSIiJiDvXk+ZlKKIiI1Fx2u53u3buzYsWKIttXrFhBnz59yn0cwzCKDLVMTk4udszly5eXeUyHw0FMTEyRW1UJt1kJs3p6EbXCpoiI+dST52fqyRMRqdkmT57MqFGj6NGjB8nJybz00kvs2LGD8ePHA54ett27dzNv3jwAnnvuOZo2bUqbNm0AT928xx9/nNtuu813zNtvv51zzjmHRx99lGHDhvHuu+/yySefsHbt2sC/wUIRdhuHjxUo5ImIBAGFPD9TnTwRkZpt5MiRHDx4kBkzZpCWlkaHDh1YtmwZSUlJAKSlpRWpmed2u5kyZQp//PEHYWFhtGzZkkceeYSbbrrJt0+fPn1YuHAh9957L/fddx8tW7Zk0aJF9OrVK+Dvzysi3BPycvIKTGuDiIh4KOT5md1XQkG/bIqI1FQTJkxgwoQJJT6XkpJS5PFtt91WpNeuNMOHD2f48OFV0bwqEaEyCiIiQUNz8vxMJRRERKQmUEF0EZHgoZDnZyqhICIiNYHTG/LUkyciYjqFPD/TnDwREakJIu3HC6KLiIi5FPL8zKHVNUVEpAbwDtfUnDwREfMp5PmZ6uSJiEhN4LR75+Qp5ImImE0hz880XFNERGoC38Ir+breiYiYTSHPz44XQ9cvmyIiErq8c/K08IqIiPkU8vzMt7qmevJERCSEHS+hoIVXRETMppDnZ746eSqhICIiIUwlFEREgodCnp95e/K0uqaIiISyCLuKoYuIBAuFPD+zq4SCiIjUACqhICISPBTy/OzE1TUNwzC5NSIiIv4RoYVXRESChkKen3nr5AHkuxTyREQkNHl78nK08IqIiOkU8vzMEXb8I9biKyIiEqpUJ09EJHgo5PmZd+EVgFwNYRERkRDlHa55LE/XOhERsynk+ZnVaiHcZgHUkyciIqFLJRRERIKHQl4AqCC6iIiEuki7d06eQp6IiNkU8gLgxBU2RUREQpFKKIiIBA+FvABQrTwREQl1J5ZQUMkgERFzKeQFgLeMgkKeiIiEKu+cPJfbUMkgERGTKeQFgIZriohIqPPOyQMtviIiYjaFvADwLrySW6CLnoiIhKZwm5Uwq2c16aNafEVExFQKeQGgnjwREakJIlRGQUQkKCjkBYDDG/JUJ09EREKY07v4inryRERMpZAXAOrJExGRmkA9eSIiwUEhLwAcKqEgIiI1gHfxFdXKExExl0JeAKgnT0REagJvGYUcDdcUETGVQl4AeOvkKeSJiEgo03BNEZHgoJAXAN4SClp4RUREQlmEd7imevJEREylkBcA3uGaufplU0REQph68kREgoNCXgD4Fl5RT56IiIQwb0+eQp6IiLkU8gJAC6+IiEhNEKGFV0REgoJCXgAo5ImISE0QoRIKIiJBQSEvAOyqkyciIjWAt4TCUfXkiYiYSiEvAFRCQUREaoJIzckTEQkKpoe8OXPm0Lx5c5xOJ927d2fNmjWl7puWlsbVV19N69atsVqtTJw4sdg+KSkpWCyWYrdjx4758V2UTcM1RUSkJohQT56ISFAwNeQtWrSIiRMnMnXqVDZt2kS/fv0YPHgwO3bsKHH/3Nxc6tevz9SpU+ncuXOpx42JiSEtLa3Izel0+uttnJLD5h2uqYueiIiELpVQEBEJDqaGvCeffJKxY8cybtw42rZty+zZs0lMTOT5558vcf9mzZrx1FNPMXr0aGJjY0s9rsViISEhocjNTL6ePJVQEBGREOa0qydPRCQYmBby8vLy2LhxIwMHDiyyfeDAgaxbt65Sx87OziYpKYkmTZpw8cUXs2nTpjL3z83NJSsrq8itKjk0XFNERGoA9eSJiAQH00LegQMHcLlcxMfHF9keHx9Penp6hY/bpk0bUlJSeO+991iwYAFOp5O+ffuydevWUl8zc+ZMYmNjfbfExMQKn78kmpMnIiI1QaRKKIiIBAXTF16xWCxFHhuGUWzb6ejduzfXXHMNnTt3pl+/fixevJgzzzyTZ555ptTXTJkyhczMTN9t586dFT5/SVRCQUREagKniqGLiASFMLNOXK9ePWw2W7Feu3379hXr3asMq9XKWWedVWZPnsPhwOFwVNk5T2a3qSdPRERCn4ZriogEB9N68ux2O927d2fFihVFtq9YsYI+ffpU2XkMwyA1NZWGDRtW2TFPl6PwoqeePBERCWUR3uGa6skTETGVaT15AJMnT2bUqFH06NGD5ORkXnrpJXbs2MH48eMBzzDK3bt3M2/ePN9rUlNTAc/iKvv37yc1NRW73U67du0AmD59Or1796ZVq1ZkZWXx9NNPk5qaynPPPRfw9+fl68nT6poiIhLC1JMnIhIcTA15I0eO5ODBg8yYMYO0tDQ6dOjAsmXLSEpKAjzFz0+umde1a1ff/Y0bNzJ//nySkpLYtm0bABkZGdx4442kp6cTGxtL165dWb16NT179gzY+zqZb06eLnoiIhLCvD15BW6DfJebcJvpU/9FRGokU0MewIQJE5gwYUKJz6WkpBTbZhhGmcebNWsWs2bNqoqmVRmH6uSJiEgN4O3JA8/iK7ERCnkiImbQt28AqE6eiIjUBOE2CzarZ4VslVEQETGPQl4AeIdrug0oUG+eiIiEKIvFcnxenhZfERExjUJeAHhDHmiFTRERCW3eeXlafEVExDwKeQFgP2HiuYZsiohIKItQQXQREdMp5AVAmM3qm6OgxVdERCSUeUOe5uSJiJhHIS9AvL15ufkKeSIiErqcds3JExExm0JegNh9ZRR00RMRkdAVEe653mlOnoiIeRTyAsRbRkELr4iISCiLtHtK8CrkiYiYRyEvQOyqlSciIjWASiiIiJhPIS9A7OrJExGRGsAZrhIKIiJmU8gLEO/CK+rJExGRUBZhL5yTp548ERHTKOQFiKPwl02FPBERCWUqoSAiYj6FvABxeHvyVCdPRERCWIQWXhERMZ1CXoAcn5Oni56ISE0zZ84cmjdvjtPppHv37qxZs6bUfd9++20GDBhA/fr1iYmJITk5mY8//rjIPikpKVgslmK3Y8eO+futnJK3Jy9HwzVFREyjkBcgDq2uKSJSIy1atIiJEycydepUNm3aRL9+/Rg8eDA7duwocf/Vq1czYMAAli1bxsaNGzn//PMZOnQomzZtKrJfTEwMaWlpRW5OpzMQb6lMqpMnImK+MLMbUFOohIKISM305JNPMnbsWMaNGwfA7Nmz+fjjj3n++eeZOXNmsf1nz55d5PHDDz/Mu+++y/vvv0/Xrl192y0WCwkJCX5te0VE2Avn5KknT0TENOrJCxCVUBARqXny8vLYuHEjAwcOLLJ94MCBrFu3rlzHcLvdHD58mLp16xbZnp2dTVJSEk2aNOHiiy8u1tNnFs3JExExn0JegHhLKCjkiYjUHAcOHMDlchEfH19ke3x8POnp6eU6xhNPPMGRI0cYMWKEb1ubNm1ISUnhvffeY8GCBTidTvr27cvWrVtLPU5ubi5ZWVlFbv4QoTp5IiKm03DNAHGEa7imiEhNZbFYijw2DKPYtpIsWLCAadOm8e6779KgQQPf9t69e9O7d2/f4759+9KtWzeeeeYZnn766RKPNXPmTKZPn17Bd1B+vpCn4ZoiIqZRT16A2G2FdfJUQkFEpMaoV68eNputWK/dvn37ivXunWzRokWMHTuWxYsXc8EFF5S5r9Vq5ayzziqzJ2/KlClkZmb6bjt37iz/GzkNvmLo6skTETGNQl6A+Obk5SvkiYjUFHa7ne7du7NixYoi21esWEGfPn1Kfd2CBQsYM2YM8+fP56KLLjrleQzDIDU1lYYNG5a6j8PhICYmpsjNH5zqyRMRMZ2GawaIb3VNly56IiI1yeTJkxk1ahQ9evQgOTmZl156iR07djB+/HjA08O2e/du5s2bB3gC3ujRo3nqqafo3bu3rxcwIiKC2NhYAKZPn07v3r1p1aoVWVlZPP3006SmpvLcc8+Z8yZPEKmFV0RETKeQFyCqkyciUjONHDmSgwcPMmPGDNLS0ujQoQPLli0jKSkJgLS0tCI181588UUKCgq45ZZbuOWWW3zbr732WlJSUgDIyMjgxhtvJD09ndjYWLp27crq1avp2bNnQN9bSTQnT0TEfAp5AaKQJyJSc02YMIEJEyaU+Jw3uHmtXLnylMebNWsWs2bNqoKWVT1vyCtwG+S73ITbNDNERCTQ9M0bIKqTJyIiNYHTfvyfFhqyKSJiDoW8APHWyVNPnoiIhDK7zYq1sDrEMQ3ZFBExhUJegPjq5KmEgoiIhDCLxaLFV0RETKaQFyDeOnkarikiIqHOW0YhRz15IiKmUMgLEM3JExGRkPLDUvhgMvzycbGnVBBdRMRcCnkBotU1RUQkpGxfB1+/Aju/LPaUd4VNzckTETGHQl6A+IqhF+iCJyIiIcBZ2/P3WEaxpyI0J09ExFQKeQGi4ZoiIhJSIup4/h79s/hT4RquKSJiJoW8AFEJBRERCSkRtT1/j2YUf0oLr4iImEohL0CcKqEgIiKhpMzhmoVz8tSTJyJiCoW8APGWUFBPnoiIhIQyhmt6SygcVU+eiIgpFPICRHPyREQkpJQxXDOysCdPc/JERMyhkBcg3pDnchu43IbJrREREakkb0/esQxwF/0BM0I9eSIiplLICxBvnTzQkE0REQkB3jl5hhvyDhd5yhfy1JMnImIKhbwAsSvkiYhIKAl3QpjTc/+keXlOu3ryRETMpJAXIGFWCxaL536uCqKLiEgo8C2+klF0s3ryRERMpZAXIBaLxVcrT4uviIhISCiljEKkSiiIiJhKIS+AvPPyVCtPRERCQillFJwqhi4iYiqFvACyh6lWnoiIhJBSyihouKaIiLkU8gLIoVp5IiISSkrpyYvQwisiIqZSyAsg33BNhTwREQkFmpMnIhKUFPICyK6QJyIioaSU4ZpODdcUETGVQl4A2X3DNXXRExGREFDacE0tvCIiYiqFvADyllBQT56IiISEUoZrRmi4poiIqRTyAsgRrhIKIiISQk7Rk5fvMsjXNU9EJOAU8gJIxdBFRCSk+ObkZRbdXNiTB+rNExExg0JeANlVQkFEREKJd7jmST15dpsVq6XwKYU8EZGAU8gLIBVDFxGRkOIdrpl3GFwFvs0Wi+V4QXQtviIiEnAKeQGkOnkiIhJSnLHH7x8recimevJERAJPIS+AVCdPRERCii0MHDGe+ycN2XSqJ09ExDQKeQF0fOEVXfBERCRElFJGIVI9eSIiplHICyAN1xQRkZDjW2Gz5DIK6skTEQk8hbwA8oU81QwSEZFQ4Qt5GUU2+4ZrqidPRCTgFPICSHPyREQk5JQyXNO38Ip68kREAk4hL4BUJ09EREKOt4zCScM1vXPyVAxdRCTwFPICyLvwinryREQkZGi4pohI0FHICyBH4QVPPXkiIhIySunJ8y68kqPhmiIiAaeQF0AqoSAiIiGntDl56skTETGNQl4AaeEVEREJOaWVUPDOyVNPnohIwCnkBZBKKIiISMjxDdfMKLpZxdBFREyjkBdA6skTEZGQc8rhmrrmiYgEmkJeAKmEgoiIhJxTLLxyNK8g0C0SEanxFPICyKGePBERCTXeOXkFxyD/6PHNGq4pImIahbwAcoR5LngKeSIiEjIcMWDxXN9OnJfnq5OnhVdERAJOIS+A7Fp4RUREQo3FAs5Yz/0T5uVF2jUnT0TELAp5AeSrk6ehKyIiEkpKKKOgOXkiIuZRyAsg9eSJiEhIKqGMglPF0EVETKOQF0DehVfyXQZut2Fya0RERKpICWUUfAuvaE6eiEjAKeQFkLcnD9SbJyIiIaSEMgreOXnHNCdPRCTgFPIC6MSQp1p5IiISMnxz8jKObyocrpnnclOgHzZFRAJKIS+AvAuvgMooiIhICPEO1zyhJ887Jw80L09EJNAU8gLIYrFo8RUREQk93uGaJ8zJc4RZsVg89xXyREQCSyEvwBwqoyAiIqGmhOGaFovFN2TzWJ5+2BQRCSSFvABTT56IiIScEhZegRMLouuHTRGRQFLICzBvGQXNyRMRkZBRQgkFUK08ERGzVCjk7dy5k127dvkef/nll0ycOJGXXnqpyhoWquwKeSIiQe3LL7/E5ToeSgyjaF3T3NxcFi9eHOhmBTffcM2iPXne4Zo5eQUBbpCISM1WoZB39dVX89lnnwGQnp7OgAED+PLLL/nHP/7BjBkzqrSBocYb8lRCQUQkOCUnJ3Pw4EHf49jYWH7//Xff44yMDK666iozmha8fMM1M+CEUBzhq5WnnjwRkUCqUMj7/vvv6dmzJwCLFy+mQ4cOrFu3jvnz55OSklKV7Qs56skTEQluJ/fcnfy4tG01mne4puGC3MPHN3uHa2rhFRGRgKpQyMvPz8fhcADwySefcMkllwDQpk0b0tLSqq51IcgR5rngqSdPRKT6snhrA4hHeATYPP8uOHFenhZeERExR4VCXvv27XnhhRdYs2YNK1as4MILLwRgz549xMXFVWkDQ423ILpW1xQRqTnmzJlD8+bNcTqddO/enTVr1pS679tvv82AAQOoX78+MTExJCcn8/HHHxfbb8mSJbRr1w6Hw0G7du1YunSpP99C2SyWEssoRGjhFRERU1Qo5D366KO8+OKLnHfeeVx11VV07twZgPfee883jFNK5puTpwueiEjQ+vHHH/n222/59ttvMQyDn376yff4hx9+OK1jLVq0iIkTJzJ16lQ2bdpEv379GDx4MDt27Chx/9WrVzNgwACWLVvGxo0bOf/88xk6dCibNm3y7bN+/XpGjhzJqFGj2Lx5M6NGjWLEiBFs2LChUu+7Ukooo+ALeVp4RUQkoCxGBScWuFwusrKyqFOnjm/btm3biIyMpEGDBlXWQDNkZWURGxtLZmYmMTExVXrsG+Z9zYof9/LQZR34W6+kKj22iEhNVxXf31arFYvFUuK8O+92i8VSZAXOsvTq1Ytu3brx/PPP+7a1bduWSy+9lJkzZ5brGO3bt2fkyJHcf//9AIwcOZKsrCz++9//+va58MILqVOnDgsWLCjXMav8WvfKINj5BYyYB+2GAfCPpd8xf8MOJl1wJrdf0Kry5xARqeHK+90dVpGDHz16FMMwfAFv+/btLF26lLZt2zJo0KCKtbiGUJ08EZHg9scff1TZsfLy8ti4cSP33HNPke0DBw5k3bp15TqG2+3m8OHD1K1b17dt/fr1TJo0qch+gwYNYvbs2ZVuc4WVUEYhUsM1RURMUaGQN2zYMC6//HLGjx9PRkYGvXr1Ijw8nAMHDvDkk09y8803V3U7Q4ZKKIiIBLekpFOPskhNTS3XfgcOHMDlchEfH19ke3x8POnp6eVqzxNPPMGRI0cYMWKEb1t6evppHzM3N5fc3Fzf46ysrHKdv9xOLKPg3aQSCiIipqjQnLxvvvmGfv36AfCf//yH+Ph4tm/fzrx583j66aertIGhRj15IiLVU2ZmJnPmzKFbt2507979tF578mqc3iGfp7JgwQKmTZvGokWLik2FON1jzpw5k9jYWN8tMTHxNN5BOXjLKJywuqZTxdBFRExRoZCXk5NDdHQ0AMuXL+fyyy/HarXSu3dvtm/fXqUNDDW+1TUV8kREqoVPP/2Ua665hoYNG/LMM88wZMgQvv7663K9tl69ethstmI9bPv27SvWE3eyRYsWMXbsWBYvXswFF1xQ5LmEhITTPuaUKVPIzMz03Xbu3Fmu91BuZS28kq9rnohIIFUo5J1xxhm888477Ny5k48//piBAwcCngtMVS9UEmochRc8lVAQEQleu3bt4p///CctWrTgqquuok6dOuTn57NkyRL++c9/0rVr13Idx2630717d1asWFFk+4oVK+jTp0+pr1uwYAFjxoxh/vz5XHTRRcWeT05OLnbM5cuXl3lMh8NBTExMkVuVKqmEgrdOXp6Ga4qIBFKFQt7999/PnXfeSbNmzejZsyfJycmA5wJT3gtfTeXtyVMJBRGR4DRkyBDatWvHjz/+yDPPPMOePXt45plnKny8yZMn8/LLLzN37ly2bNnCpEmT2LFjB+PHjwc8PWyjR4/27b9gwQJGjx7NE088Qe/evUlPTyc9PZ3MzEzfPrfffjvLly/n0Ucf5aeffuLRRx/lk08+YeLEiRVuZ6V5h2ueuPCK5uSJiJiiQguvDB8+nLPPPpu0tDRfjTyA/v37c9lll1VZ40KRd+EV9eSJiASn5cuX8/e//52bb76ZVq0qv+z/yJEjOXjwIDNmzCAtLY0OHTqwbNky38ItaWlpRWrmvfjiixQUFHDLLbdwyy23+LZfe+21pKSkANCnTx8WLlzIvffey3333UfLli1ZtGgRvXr1qnR7K8w7XLOEOXlaXVNEJLAqFPLAMx8gISGBXbt2YbFYaNy4sQqhl4NDq2uKiAS1NWvWMHfuXHr06EGbNm0YNWoUI0eOrNQxJ0yYwIQJE0p8zhvcvFauXFmuYw4fPpzhw4dXql1VqoQSChG+hVcU8kREAqlCwzXdbjczZswgNjaWpKQkmjZtSu3atXnwwQdxuxVeymLX6poiIkEtOTmZf//736SlpXHTTTexcOFCGjdujNvtZsWKFRw+fNjsJgYn38Irx4eVqoSCiIg5KhTypk6dyrPPPssjjzzCpk2b+Oabb3j44Yd55plnuO+++6q6jSFFdfJERKqHyMhIrr/+etauXct3333HHXfcwSOPPEKDBg245JJLzG5e8PHOycvNBLcn1PlW11RPnohIQFUo5L322mu8/PLL3HzzzXTq1InOnTszYcIE/v3vfxcbdiJFqYSCiEj107p1ax577DF27drFwoULy1XjrsbxDtcEOObpzfOtrqmePBGRgKrQnLxDhw7Rpk2bYtvbtGnDoUOHKt2oUOYroaCQJyISlK6//vpT7hMXFxeAllQztnCw14K8bM+8vMi6J9TJU8gTEQmkCvXkde7cmWeffbbY9meffZZOnTpVulGhzNeTp9U1RUSCUkpKCp999hkZGRn8+eefJd4yMjLMbmZw8pVRyACOD9fMK3DjchvmtElEpAaqUMh77LHHmDt3Lu3atWPs2LGMGzeOdu3akZKSwuOPP35ax5ozZw7NmzfH6XTSvXt31qxZU+q+aWlpXH311bRu3Rqr1VpqPaAlS5bQrl07HA4H7dq1Y+nSpafVJn86vrqmftUUEQlG48ePJzMzk99//53zzz+fV155haVLlxa5vf3222Y3Mzj5yih4Vtj0DtcE9eaJiARShULeueeeyy+//MJll11GRkYGhw4d4vLLL+eHH37g1VdfLfdxFi1axMSJE5k6dSqbNm2iX79+DB48uEi9oBPl5uZSv359pk6dWqQ+34nWr1/PyJEjGTVqFJs3b2bUqFGMGDGCDRs2VOStVjmtrikiEtzmzJlDWload999N++//z6JiYmMGDGCjz/+GMNQb1SZfGUUMgDPD5ve6YtafEVEJHAsRhVesTZv3ky3bt1wucr3Rd6rVy+6devG888/79vWtm1bLr30UmbOnFnma8877zy6dOnC7Nmzi2wfOXIkWVlZ/Pe///Vtu/DCC6lTpw4LFiwoV7uysrKIjY0lMzOTmJiYcr2mvL7edojhL6ynWVwkK//v/Co9tohITeeP7+/t27eTkpLCvHnzyM/P58cff6RWrVpVcmwz+eVat+ga2PI+DHkcet4AQLv7PyInz8Wau84nsW5k1ZxHRKSGKu93d4V68qpCXl4eGzduZODAgUW2Dxw4kHXr1lX4uOvXry92zEGDBlXqmFVJJRRERKoXi8WCxWLBMAzVgj0V75y8Yxm+TSqILiISeKaFvAMHDuByuYiPjy+yPT4+nvT09AofNz09/bSPmZubS1ZWVpGbv2i4pohI8MvNzWXBggUMGDCA1q1b89133/Hss8+yY8eOkOjF85uThmsCOLXCpohIwFWohEJVOrnWkGEYla4/dLrHnDlzJtOnT6/UOctLdfJERILbhAkTWLhwIU2bNuW6665j4cKFKplQXt6FV04Ieb5aeerJExEJmNMKeZdffnmZz5/OktL16tXDZrMV62Hbt29fsZ6405GQkHDax5wyZQqTJ0/2Pc7KyiIxMbHCbSiLt05erkooiIgEpRdeeIGmTZvSvHlzVq1axapVq0rcTytslsBXQuFP36bIwpB3TD15IiIBc1ohLzY29pTPjx49ulzHstvtdO/enRUrVnDZZZf5tq9YsYJhw4adTrOKSE5OZsWKFUyaNMm3bfny5fTp06fU1zgcDhwOR4XPeTpO7Mmril5LERGpWqNHj9Z3c0X5Sihk+DZpuKaISOCdVsg7nfII5TF58mRGjRpFjx49SE5O5qWXXmLHjh2MHz8e8PSw7d69m3nz5vlek5qaCkB2djb79+8nNTUVu91Ou3btALj99ts555xzePTRRxk2bBjvvvsun3zyCWvXrq3StleUd04eeAqiO8JsZewtIiKBlpKSYnYTqq8S5uRp4RURkcAzdU7eyJEjOXjwIDNmzCAtLY0OHTqwbNkykpKSAE/x85Nr5nXt2tV3f+PGjcyfP5+kpCS2bdsGQJ8+fVi4cCH33nsv9913Hy1btmTRokX06tUrYO+rLI4TQ16BQp6IiIQQ35y848M1I9STJyIScKYvvDJhwgQmTJhQ4nMl/ZpanrJ+w4cPZ/jw4ZVtml94h2uCFl8REZEQU1IJBe+cPPXkiYgEjGklFGoqq9VCuM0z10O18kREJKR4h2vm50BBrmeTXT15IiKBppBnApVREBGRkOSIBQoXrSmcl6fhmiIigaeQZwJvGYU8lVEQEZFQYrWCs3Al7sJ5eb6Qp+GaIiIBo5BnAvXkiYhIyDqpjIJ3uGZOXoFJDRIRqXkU8kzgLaOQW6BfNUVEJMScVEahbpQdgP2Hc81pj4hIDaSQZ4LjIU89eSIiEmK8K2wWDtdsWjcSgO2HckxqkIhIzaOQZwJvrTwN1xQRkZBz0nBNb8jbdegobvepyyCJiEjlKeSZQD15IiISsnzDNT09eQ1jnYRZLeS53Ow9fMy8domI1CAKeSbQwisiIhKyvD15hXPywmxWGteJAGDHQQ3ZFBEJBIU8E9g1XFNEREKVd05e4XBN0Lw8EZFAU8gzgSNMdfJERCRE+Xry/vRt8oa8nQp5IiIBoZBnAu/CK7n5KqEgIiIh5qQSCnA85O1QyBMRCQiFPBP4hmuqJ09ERELNSSUUQCFPRCTQFPJMoBIKIiISsk4qoQDQNK4w5GnhFRGRgFDIM4EWXhERkZB1YgkFw1MXL7GwJ+/gkTyycwtMapiISM2hkGcCbwkF1ckTEZGQ4+3JcxdA3hEAYpzh1IkMB7T4iohIICjkmUDF0EVEJGSFR4LVE+hKLKOgIZsiIn6nkGcClVAQEZGQZbEUHbJZqGlcFKCePBGRQFDIM4GvJy9fIU9EREKQr1Zehm9T07oRgFbYFBEJBIU8E6iEgoiIhDSVURARMZVCngmOr66pYugiIhKCSiijkKiQJyISMAp5JlCdPBERCWklzMlLKpyTt+vPHFxuw4RGiYjUHAp5JnBodU0REQllJczJS4hxEm6zkO8ySM86Zk67RERqCIU8E3jr5KknT0REQpJ3Tt4JwzVtVgtN6hQO2VQZBRERv1LIM4EWXhERkZBWwnBNOHFe3pEAN0hEpGZRyDOBr06eevJERCQUlTBcEyBJi6+IiASEQp4J7JqTJyIioayEEgpwYhmFowFukIhIzaKQZwK7VtcUEZFQVkIJBThhuOZBDdcUEfEnhTwTaHVNEREJab45eRlFNqsguohIYCjkmUDF0EVEJKT5VtfMBPfxHzSbxnlC3p85+WQdyzehYSIiNYNCngm8JRTUkyciIiHJ25OHAbmZvs21HGHERdkB2KnePBERv1HIM4HjhBIKhmGY3BoREZEqFuaAcE+vXallFFQrT0TEbxTyTOAtoWAYUOBWyBMRkRBUWhmFOM3LExHxN4U8E3jn5IGGbIqISIg6ZRkFhTwREX9RyDPBiSFPZRRERCQknaqMgkKeiIjfKOSZwGa1YLNaAIU8EREJUSqjICJiGoU8kzhUEF1EREJZKcM1vXPydv95lAKXroEiIv6gkGcSu68gumrliYhICPL25J00XDM+2ondZqXAbZCWeSzgzRIRqQkU8kyiWnkiIhLSfMM1i/bkWa0WmtSNADRkU0TEXxTyTGI/oVaeiIhIyCmlhAJoXp6IiL8p5JlEc/JERCSkeefkHcss9lSSQp6IiF8p5JnEXlgQXcM1RUQkJJUyXBNURkFExN8U8kxiV0+eiIiEsvIM1zyokCci4g8Kef7kyi/1KQ3XFBGRkFZKCQWApnHqyRMR8SeFPH/I3A2PJMHMRDCMEnfxhTyXSiiIiIS6OXPm0Lx5c5xOJ927d2fNmjWl7puWlsbVV19N69atsVqtTJw4sdg+KSkpWCyWYrdjx4KoJIG3Jy//CBTkFXnK25OXeTSfzJzSfxAVEZGKUcjzh4janrpABUch93CJu/hKKOSrJ09EJJQtWrSIiRMnMnXqVDZt2kS/fv0YPHgwO3bsKHH/3Nxc6tevz9SpU+ncuXOpx42JiSEtLa3Izel0+uttnD5n7PH7J9XKi7SHUa+WA4Cdf6o3T0Skqink+YM9CuzRnvvZ+0reRSUURERqhCeffJKxY8cybtw42rZty+zZs0lMTOT5558vcf9mzZrx1FNPMXr0aGJjY0vcB8BisZCQkFDkFlSstuNBr8R5eZ5aeds1L09EpMop5PlLdLznb/beEp/WnDwRkdCXl5fHxo0bGThwYJHtAwcOZN26dZU6dnZ2NklJSTRp0oSLL76YTZs2lbl/bm4uWVlZRW5+5yujkFHsKdXKExHxH4U8f6lVdsjz9uSphIKISOg6cOAALpeL+Pj4Itvj4+NJT0+v8HHbtGlDSkoK7733HgsWLMDpdNK3b1+2bt1a6mtmzpxJbGys75aYmFjh85dbGWUUmsZFAQp5IiL+oJDnL7UaeP4q5ImI1HgWi6XIY8Mwim07Hb179+aaa66hc+fO9OvXj8WLF3PmmWfyzDPPlPqaKVOmkJmZ6bvt3Lmzwucvt3KUUdipkCciUuXCzG5AyDpVT57NUwxdwzVFREJXvXr1sNlsxXrt9u3bV6x3rzKsVitnnXVWmT15DocDh8NRZecsl7LKKBSGvO2HjgSwQSIiNYN68vzF15NX8sIrjnDNyRMRCXV2u53u3buzYsWKIttXrFhBnz59quw8hmGQmppKw4YNq+yYVcLbk1fCnLykwlp5ezKOka9FyEREqpR68vzllD153uGaqpMnIhLKJk+ezKhRo+jRowfJycm89NJL7Nixg/HjxwOeYZS7d+9m3rx5vtekpqYCnsVV9u/fT2pqKna7nXbt2gEwffp0evfuTatWrcjKyuLpp58mNTWV5557LuDvr0xlzMmrX8uBI8xKboGbtIxjvgLpIiJSeQp5/lLOhVfUkyciEtpGjhzJwYMHmTFjBmlpaXTo0IFly5aRlJQEeIqfn1wzr2vXrr77GzduZP78+SQlJbFt2zYAMjIyuPHGG0lPTyc2NpauXbuyevVqevbsGbD3VS6+4ZoZxZ6yWi0k1o3k133ZbD90RCFPRKQKKeT5y6mGa6pOnohIjTFhwgQmTJhQ4nMpKSnFthmGUebxZs2axaxZs6qiaf5VxnBN8MzL+3VftlbYFBGpYpqT5y/enrwj+8FdfEim6uSJiEjIK2O4JqhWnoiIvyjk+UtkPcAChhtyDhZ7WiUUREQk5JVRQgFURkFExF8U8vzFFgZR9T33S5iXpzl5IiIS8soooQAnlFE4qJAnIlKVFPL8qYzFV1QnT0REQt6Jc/JKmGfoXWxlx8GcU85DFBGR8lPI86cyFl/xzsnL1cIrIiISqrxz8lx5kH+02NOJdTwh73BuAZlH8wPYMBGR0KaQ50/enrzD6cWe8s3Jy1edPBERCVH2WmDxjFwpachmhN1Gg2gHUMWLr7hdsOV9eP0yeH9iiQugiYiEMpVQ8KcyevLsKqEgIiKhzmLxDNnMOeAZshnbuNguTetGsu9wLtsP5tCpSe3KnS/vCGx6E76YA3/+cXy7MwYGzKjcsUVEqhH15PlTGXPyVEJBRERqhECUUchKg0+mw5Pt4L//5wl4ztrQaaTn+c+fgs2LKn58EZFqRj15/lSOnjyVUBARkZB2qjIKcZUoo5D+Pax/Dr57C9yFc/rqNIfkW6DL1WCPgpjGsPZJeO82qHcGNO5egTchIlK9KOT5k3ryRESkpvNHGYU/1sCaJ+D3z45vS+wNfW6F1kPAaju+/S/3wb4t8Mt/YeHf4MaVEJ1weu9BRKSaUcjzJ1/IK6EnTyUURESkJvAO1zyWUeLTpz1cc9vn8NpQwACLFdpeAn1ugyY9St7faoXLX4JXBsD+nzxBb8yHEO48rbchIlKdaE6eP3mHa+ZmFls62hGuhVdERKQGONVwzcKQl5Z59NQ/fBoGrLgPMODMwfD3TTDitdIDnpczBq6c7+lV3P01fDCxxLp9IiKhQiHPn5yxEFb4S+FJvXl2m+ejd7kNChT0REQkVHmHa+YcLPHp+tEOnOFW3AbsySheS6+ILe/D7o0QHgVDn4I6zcrfjriW8NcUT0mHzQs8c/lEREKUQp4/WSylLr7iXXgF1JsnIiIhrF4rz98flkL2/mJPWyyW4/Pyyhqy6SqA/0333O9zK0THn35bWp4Pgx7y3F9xH/z6yekfQ0SkGlDI87dSFl8pEvI0L09EREJV+8shoaNnTt7ye0vcpVzz8ja9Dgd/hcg4SL614u3pNR66XgOGG966Hg78WvFjiYgEKYU8f/OFvPQim8OsFqwWz32FPBERCVm2MLj4KcAC3y6E31cV26Vp3SigjDIKeUdg5SOe++fc5ZljV1EWC1z0JCT28syZX3AlHMus+PFERIKQQp6/lTJc02KxqFaeiIjUDE26w1ljPfc/nAwFuUWeblo3AoAdpZVR+OJ5z4+ltZOgx3WVb0+YA0a87qmhd3Ar/GcsuF2VP66ISJBQyPO3MmrleRdfUcgTEZGQ95f7PNfEg7/C2tlFnvIWRC9xTl7OIfj8qePHCHNUTXui4+HKNz0LpP264vh8PxGREKCQ52+l9OQB2MNUK09ERGqIiNow6GHP/TVPwMHffE955+TtPJSDcXJpgzVPQG6WZ15fhyuqtk2NusKwwlU2P38Kdn1dtccXETGJQp6/ldGT5/AN19QQERERqQE6XAEtzgdXrmfYZmGga1LHE/Kycwv4Myf/+P4ZO+DLlzz3L5jmKWxe1ToOh85Xe+6vuF/180QkJCjk+Zsv5BXvyfOGPPXkiYhIjWCxwEVPgM0Bv6+E75cA4Ay3kRDjqSu7/eCR4/t/9jC48qD5OdCyv//a9ZepnmGb2z+HXz7y33lERAJEIc/ffMM19xb7ddC78Irq5ImISI0R1xLOudNz/6MpcDQDKKGMQvr3sHmh5/4F0zwB0V9im0Dvmz33VzzgqcknIlKNKeT5m7cnz5XnqRF0AvXkiYhIjdT3dohrBUf2wf9mAJB4wrw8oHAhFAPaXwaNu/u/TWdPgoi6cOBnSH3D/+cTEfEjhTx/C3OAs7bn/klDNlVCQUREaqQwB1z8pOf+13Nh19ckxZ3Qk7dtLWxdDtYwz4qageCMhXPv8tz/7GFPbT4RkWpKIS8QSll8xa6ePBERqamanwOdrwIM+GAizerYAdi47RDGigc8+3S71jO8M1B6jIU6zTzX6/XPBe68IiJVTCEvELzz8g6fFPJsCnkiIlKDDXjQM9ol/TsGZr9LlN3GGYdWYtn9NYRHwrl3B7Y9YXbof7/n/udPQfb+wJ5fRKSKKOQFQik9eY7COnm5WnhFRERqolr1YYBnTp5zzSPc0NHGXWGLPM8l3+opWB5o7S6DRt0gLxtWPRr484uIVAGFvEA4xXDN3HzVyRMRkRqq6yhI7A35R7h12620tKZx0Ijmt1bXmdMeq9UXPNn4Khz41Zx2iIhUgkJeIPjKKJS88IpKKIiISI1ltXoWYbGGEXYkHYBnCi7j5a8OmNem5v3gzAvBXVC4yqeISPWikBcIWnhFRESkdPHtIfkWAHJrNWG+qz9vf7ObQ0fyzGvTBdPAYoUt78HOL81rh4hIBSjkBUIpPXmqkyciIlLo/Kkw6GHs1yyiTZN65Ba4efOL7ea1p0Fb6HqN5/7y+8AwzGuLiMhpUsgLhFPNyVPIExGRmi7MAcm3YEnowNizmwPw2vrt5BaYOG/9vH9AWATs/AJ++tC8doiInCaFvECITvD8zTkIrnzfZodKKIiIiBQzpGNDEmKcHMjO5f3NaeY1JKahbxgpnzxQ5BouIhLMFPICIaIuWGyAAUeOTyTXnDwREZHiwm1Wru3TDIBX1v6BYeZQyb63Q2QcHPwVvplnXjtERE6DQl4gWK0nzMs7PmTTVyfPzKEoIiIiQejqnk2JCLexJS2L9b8dNK8hzhg49x7P/ZUzIfeweW0RESknhbxAKSHkqYSCiIhIyWIjwxnevQng6c0zVfcxULcFHNkP6541ty0iIuWgkBcoJSy+ouGaIiIipbuubzMsFvjfT/v4fX+2eQ0Js0P/Bzz31z0NWSbOExQRKQeFvEApcbimVtcUEREpTYv6tejfxnP9nPu5yb157YZBk56QnwOfTDO3LSIip6CQFyi+nrzjtfJUQkFERKRs1xeWU1iycTcZOSYWR7dYYPAjgAW+XQg7NpjXFhGRU1DIC5SShmuqhIKIiEiZklvE0a5hDEfzXcz/coe5jWnc/XiB9P/+H7i1cJqIBCeFvEDxDdcs3pOnkCciIlIyi8VyvDj6um3mXzP7PwCOWEjbrJIKIhK0FPICpYSePG8JBa2uKSIiUrqhnRtRP9rB3qxcln1n8qInterD+VM89/83A47+aW57RERKoJAXKGXOydNwDxERkdLYw6yM7p0EwMtrfze3ODrAWeOgfls4egg+e9jctoiIlEAhL1C8IS8vG3I9y0A7NFxTRESkXP7WOwlHmJXvd2fx5R+HzG2MLRwGP+q5/9XLsPcHc9sjInIShbxAcdSC8CjP/SOe3jzNyRMRESmfulF2Lu8WJMXRAVqc6ymrYLhh2V1gdu+iiMgJTA95c+bMoXnz5jidTrp3786aNWvK3H/VqlV0794dp9NJixYteOGFF4o8n5KSgsViKXY7duyYP99G+XgXXznsmZennjwREZHyG3t2MwBWbNnL9oNHzG0MwMB/QlgEbF8LPyw1uzUiIj6mhrxFixYxceJEpk6dyqZNm+jXrx+DBw9mx46Sl0j+448/GDJkCP369WPTpk384x//4O9//ztLliwpsl9MTAxpaWlFbk6nMxBvqWwnLb6iOnkiIiLld0aDaM5rXR/DgLnB0JtXuymcPclzf/m9kBcEwVNEBJND3pNPPsnYsWMZN24cbdu2Zfbs2SQmJvL888+XuP8LL7xA06ZNmT17Nm3btmXcuHFcf/31PP7440X2s1gsJCQkFLkFhZPKKHjr5BW4DdxuDfMQERE5lXFntwDg9S+2s+7XAya3Buj7d0/Yy9oNa2eZ3RoREcDEkJeXl8fGjRsZOHBgke0DBw5k3bp1Jb5m/fr1xfYfNGgQX3/9Nfn5+b5t2dnZJCUl0aRJEy6++GI2bdpUZltyc3PJysoqcvOLUnryQGUUREREyqPvGXFc3q0xbgNuXbCJ3RlHzW1QeAQMKlxh8/On4VAQ9DCKSI1nWsg7cOAALpeL+Pj4Itvj4+NJT08v8TXp6ekl7l9QUMCBA55f89q0aUNKSgrvvfceCxYswOl00rdvX7Zu3VpqW2bOnElsbKzvlpiYWMl3V4qTQp63Th5Abr5CnoiIyKlYLBYevqwj7RvFcOhIHuNf38ixfJNLEbW5GFqcB65c+HiquW0RESEIFl6xWCxFHhuGUWzbqfY/cXvv3r255ppr6Ny5M/369WPx4sWceeaZPPPMM6Uec8qUKWRmZvpuO3furOjbKdtJwzXDbcffS65LtfJERETKwxlu44VrulMnMpzvdmdy3zvfm1s7z2KBwY+BNQx+/hB+/cS8toiIYGLIq1evHjabrViv3b59+4r11nklJCSUuH9YWBhxcXElvsZqtXLWWWeV2ZPncDiIiYkpcvOLk3ryLBaLb4XNo3kKeSIiIuWVWDeSp6/qitUCb23cxZsbSl60LWDqt4Ze4z33/3sPFOSZ2x4RqdFMC3l2u53u3buzYsWKIttXrFhBnz59SnxNcnJysf2XL19Ojx49CA8PL/E1hmGQmppKw4YNq6bhlRHtDXn7fJua1/PUzvtlb7YZLRIREam2+rWqz/8NagPA9Pd/YOP2P81t0Ll3QVQDOLgVNrxw6v1FRPzE1OGakydP5uWXX2bu3Lls2bKFSZMmsWPHDsaP9/wSNmXKFEaPHu3bf/z48Wzfvp3JkyezZcsW5s6dyyuvvMKdd97p22f69Ol8/PHH/P7776SmpjJ27FhSU1N9xzSVtyfvyD5we+bgdWwcC8B3uzJMapSIiEj1Nf7cFgzukEC+y2DCmxvZd9jEurjOWLhgmuf+qkcha495bRGRGs3UkDdy5Ehmz57NjBkz6NKlC6tXr2bZsmUkJSUBkJaWVqRmXvPmzVm2bBkrV66kS5cuPPjggzz99NNcccUVvn0yMjK48cYbadu2LQMHDmT37t2sXr2anj17Bvz9FRNV3/PXXQBHPb82dmriCXnf7s40q1UiIiLVlsVi4V9/7UyrBrXYm5XLLW9+Q76ZK1Z3vgoa94C8bHjnZt+PuiIigWQxTJ2pHJyysrKIjY0lMzOz6ufnPdYCcg7Czesgvj2pOzO49LnPiYuy8/W9F5S56IyIiJTNr9/fISbUPqvf9mdz6bOfczi3gDF9mjHtkvbmNWb/L/DSuZCfAxdMh7MnmtcWEQkp5f3uNn11zRrnpMVX2iREE2a1cPBIHnsyTRxiIiIiUo21rF+LJ0d2ASBl3Tbe/maXeY2pfyZc+Ijn/qcPwu6N5rVFRGokhbxAO6mMgjPcRuuEaEDz8kRERCpjQLt4/v6XMwCY8vZ3fG/mVIhuo6HdMM8Ujf+MhdzD5rVFRGochbxAO6knD06Yl7dL8/JEREQq4/YLzuS81vXJLXAz/o2N/HnEpFIGFgsMfQpiE+HPP2DZ/5nTDhGpkRTyAu2knjyAjo1rA/CdFl8REQlJc+bMoXnz5jidTrp3786aNWtK3TctLY2rr76a1q1bY7VamThxYon7LVmyhHbt2uFwOGjXrh1Lly71U+urF5vVwlMju5IUF8muP49y24JN5BWYtPhJRB244mWwWGHzAvh2sTntEJEaRyEv0E7Rk6d1cEREQsuiRYuYOHEiU6dOZdOmTfTr14/BgwcXWT36RLm5udSvX5+pU6fSuXPnEvdZv349I0eOZNSoUWzevJlRo0YxYsQINmzY4M+3Um3ERobz4qjuRITbWPvrAe58azNut0nX16a94dy7Pfc/mAyH/jCnHSJSoyjkBVqtBM/fE0LemfHR2G1WMo/ms/PQUZMaJiIi/vDkk08yduxYxo0bR9u2bZk9ezaJiYk8//zzJe7frFkznnrqKUaPHk1sbGyJ+8yePZsBAwYwZcoU2rRpw5QpU+jfvz+zZ8/24zupXtokxPD8Nd0Is1p4b/Mepr//g3k/pPa7E5omQ95hWDIWXPnmtENEagyFvEArYbimPcxK24aexVe+3Z1hQqNERMQf8vLy2LhxIwMHDiyyfeDAgaxbt67Cx12/fn2xYw4aNKjMY+bm5pKVlVXkFurOa92AJ0Z0xmKB19Zv56n/bTWnIbYwuPzfnmLpuzfCZw+b0w4RqTEU8gKthOGaAB0Lh2x+p8VXRERCxoEDB3C5XMTHxxfZHh8fT3p6eoWPm56eftrHnDlzJrGxsb5bYmJihc9fnQzr0pgZhTXzZn+yldfWbTOnIbUTYejTnvtrZ8Hvq8xph4jUCAp5gebtyTv6JxTk+jZ3Klx8RStsioiEHovFUuSxYRjFtvn7mFOmTCEzM9N327lzZ6XOX52MSm7GpAvOBGDa+z/wbupucxrS/lLodi1gwNKb4MhBc9ohIiFPIS/QIuqANdxz/8QVNgt78r7fnWne5HAREalS9erVw2azFeth27dvX7GeuNORkJBw2sd0OBzExMQUudUkf+9/BtcmJ2EYcMfizaz8ed+pX+QPF86EemfC4TR471bQgmsi4gcKeYFmsZwwZPP4BaZVg1o4wqwczi1g28EjJjVORESqkt1up3v37qxYsaLI9hUrVtCnT58KHzc5ObnYMZcvX16pY4Y6i8XCA0Pbc0nnRhS4Dca/sZGN2w8FviH2KBg+F2x2+HkZfPVy4NsgIiFPIc8MvsVXjs/LC7NZad/I86uq6uWJiISOyZMn8/LLLzN37ly2bNnCpEmT2LFjB+PHjwc8wyhHjx5d5DWpqamkpqaSnZ3N/v37SU1N5ccff/Q9f/vtt7N8+XIeffRRfvrpJx599FE++eSTUmvqiYfVauHxv3bmvNb1OZbv5rpXv+Ln9MOBb0hCRxgww3P/46mQ9m3g2yAiIU0hzwylLL7SqUltQPPyRERCyciRI5k9ezYzZsygS5curF69mmXLlpGUlAR4ip+fXDOva9eudO3alY0bNzJ//ny6du3KkCFDfM/36dOHhQsX8uqrr9KpUydSUlJYtGgRvXr1Cuh7q47sYVae/1t3uifVIetYAaNe2cDOQzmBb0iv8dBqELhyYcFVcLjiC/GIiJzMYqj6djFZWVnExsaSmZnpnzkL7/0dvnkNzvsHnHe3b/OSjbu4463N9GxWl8Xjk6v+vCIiIc7v398hpKZ/Vpk5+Yx4cT0/7z1Ms7hI3hrfh/rRjsA24uif8MpAOPALNOwC1y3zDOcUESlFeb+71ZNnhlJ78goXX9mTiUuLr4iIiPhNbGQ488b2pEmdCLYdzGH03C85dCQvsI2IqANXL4bIOEhLhSU3gNsV2DaISEhSyDNDdMkhr0X9WkTabeTkufh9f7YJDRMREak54mOcvDG2F/VqOdiSlsXIF9ezL+tYYBtRtzlcuQBsDvj5Q1hxf2DPLyIhSSHPDCWsrglgs1ro0MjTm6d5eSIiIv7XrF4UC2/sTUKMk637svnri+sDP0evaS+4dI7n/vpn4atXAnt+EQk5CnlmKGW4Jhyvl6cVNkVERALjjAa1eGt8Mk3rRrL9YA4jXlzPb4EeUdNxOPzlXs/9Zf8Hv34S2POLSEhRyDODr4TCvmJFUL3z8jbvyghwo0RERGquxLqRLL4pmTMa1CIt8xgjX1zPlrSswDai353Q+WowXLB4DOz9IbDnF5GQoZBnhqjCkFdwFHKLXkA6NvaEvB/3ZJHvcge6ZSIiIjVWQqyTRTf2pn2jGA5k5zHyxfVs2vFn4BpgscDQp6BZP8g7DG+OUGkFEakQhTwz2CPBUbjk6Unz8prFRRHtCCO3wM3WvVp8RUREJJDiajmYf0NvXx29a17ewPrfDgauAWF2GDEP4s6ArF2w4ErIOxK484tISFDIM4tvyGbReXlWq4UOjb3z8jIC3CgRERGJjQhn3vU96XtGHEfyXIx59Us++2nfqV9YVSLrwt/egoi6sGcTvH0juDW6R0TKTyHPLGUsvuKdl6cVNkVERMwR5QjjlWvP4oK2DcgtcHPj61+z7Lu0wDWgbgu4cj7Y7PDTB/CJSiuISPkp5JnlxMVXTqIVNkVERMznDLfx/DXdGdq5Efkug1vnf8NbX+8MXAOSkmFYYWmFdc/AVy8H7twiUq0p5JmlrJ68xrUB2JKWRW6BK4CNEhERkROF26zMHtmFkT0ScRvwf//5lsc//hmX2zj1i6tCp7/C+VM99z+8E354JzDnFZFqTSHPLKUURAdIrBtBbEQ4+S6DX9K1+IqIiIiZbFYLj1zRkZvOaQHAs5/9yrjXviLzaH5gGnDO/0H36wAD3r4Bfl8VmPOKSLWlkGeWMnryLBbL8Xl5WnxFRETEdBaLhSlD2jJ7ZBccYVY++3k/w55dyy97Dwfi5HDRE9D2EnDlwcK/wZ5U/59XRKothTyzlBHy4Hi9vO+0+IqIiEjQuLRrY5bc3IfGtSPYdjCHS5/7nP8GYkEWqw0u//cJNfSGw8Hf/H9eEamWFPLMUsbCKwCdmtQGtMKmiIhIsOnQOJb3bzubPi3jyMlzcfOb3/DYRz/5f55euNOz4mZCJziyH16/TMXSRaRECnlm8fbkHdkP7uKLq3iHa/6y9zDH8rX4ioiISDCpG2Vn3vU9GXd2cwDmrPyN61O+IjPHz/P0nDFwzRKo0xwytsMbw+GYfhAWkaIU8swSVQ8sVjDccORAsacbxjqpV8tOgdtgS1qWCQ0UERGRsoTZrNx7cTueurILznArq37ZzyXPreXndD/P06vVAEYthagGsPc7WHA15B/z7zlFpFpRyDOL1QaR9Tz3S1l8xTcvT/XyREREgtawLsfn6W0/mMNlcz7nw2/9PE+vbnNPj54jBravhSVjSxwZJCI1k0KemcooowDQUfPyREREqoX2jTzz9Pqe4Zmnd8v8b7hnybccPubH4ZsNO3nm6Nkc8NMH8MEkMAJUv09EgppCnpl8i6+UvMJmJ62wKSIiUm3UjbLz2nU9uencFlgssPCrnQyatZrVv+z330mb94MrXvZMAfnmNfjsIf+dS0SqDYU8M52qjELh4itb9x0mJ68gUK0SERGRCgqzWZkyuC0Lb+hN07qR7Mk8xui5XzLlbT/26rW7BC560nN/9b/gixf8cx4RqTYU8swUXfZwzfgYJ/ExDtwG/LhHi6+IiIhUF71axPHRxH6M6dMMgAVf7uTC2WtYu7X4YmtVosd1cP69nvsf3Q2bF/nnPCJSLSjkmekUPXkAHRvXBjQvT0REpLqJtIcx7ZL2LLihN4l1I9idcZRrXtnAP5Z+R3auH0bonHMn9LrZc/+dm+GnZVV/DhGpFhTyzHSKguhwvF6eVtgUERGpnpJbxvHR7ecwOjkJgPkbdjBo1mrW/VrFvXoWCwx6GDpfDYYL3hoDf6yp2nOISLUQZnYDarTy9OQVhrxvd2VU7ByGAXnZniCZvbfwb+F9w+0Z3lG7acWOLSIiIuUS5QhjxrAOXNg+gbuWfMuuP49y9csbuKZ3U+66sA0xzvCqOZHVCpc84ymQ/vOHsOAquPY9aNytao4vItWCQp6ZTlFCAfDVyvv9wBEOH8sn+lQXgd8+g6/nwuF0T5A7sh/yc0rf/+u5cPm/4cyBp9t6EREROU19zqjHRxPPYeayLby5YQdvfLGDj75P546BrRnRIxGb1VL5k9jCYPhceHM4bFsDb1wB138E9VtX/tgiUi1ouKaZvMM1czMh/2iJu9Sr5aBx7QgMA3441eIrG1+DNy6HLe/Bri8hY/vxgGevBXVbQGJvaHsJnHUDNOwCxzJg/l/h04dURFVERCQAajnCeOiyjrw5rhct6kdxIDuPKW9/x9Bn1vLF7wer5iThTrhqATTqBkcPwbxLIWNH1RxbRIKeevLM5IgBZ6xnSMXbN8CwOeCMKbZbx8ax7M44yne7MundIq74cQzDs2SytzZOxxGe5ZSjGniCZK0GYI8q/rqCXPj4H/DVy7D6Mdj1lafWTlS9Kn6jIiIicrK+Z9Tjo9vP4fUvtvPUJ7/wY1oWV770BRe2T+AfQ9rSNC6ycidwRMM1S+DVwbD/J0/Qu/6j4z8yi0jIUk+emSwWGPwvsIbDlvfh5f6w/+diu/nm5ZW0+IrbBR9OPh7w+t0Jl78EbYdC015Qt3nJAQ8gzAEXPeEZrhkeCb9/Bi+eAzu/qqp3KCIiImWwh1kZe3ZzVv7f+YzqnYTVAh/9kM4FT67i0Y9+qvwqnJF1YdRSiG0Kh36D1y+HoxlV0nYRCV4KeWbrPBKu+y9EN4IDv8C//wI/vFNkF98KmycvvpJ/FBaP9syrwwJDHof+93nC4+noNALG/Q/izoCs3Z5f/Da86OkhFBEREb+rG2XnwUs78N/bz+HsM+qR53Lz/MrfOP/xlSz+eidudyWuyTGNYPQ7nhE+e7+D+SMhr4z5+iJS7SnkBYPEs+Cm1dCsn2clzLeuheX3gcvz65138ZVtB3PIzMn3vCancHz9Tx+AzQEjXoOeN1S8DfHt4IbPoN0wcOfDf++CJWMhN7uSb05ERETKq3VCNK+P7cm/R/egWVwk+w/nctd/vuWS59ayZut+jIr+ABvX0tOj54yFnV94fiQuyKvaxotI0FDICxa16sOod6DP3z2P1z0Nr18K2fupHWmneT3PkMs5q36FzF2e3radX4Aj1vOl3W5Y5dvgjIG/vgaDZoI1DL5f4ulZLGEIqYiIiPiHxWJhQLt4lk86l6lD2hLtCOP73VmMeuVLrnh+Hat+qWDYS+gAV78FYRHw6wrPegAuPxRlFxHTWYwK/yQUurKysoiNjSUzM5OYmOILofjdD+/Au7d4evWiG8GIeXz4ZxNumf8NrSy7eK/2E0Qc3et57pr/QHz7qm/Dji88RVQPp0F4FAx/BVoPrvrziIhUIdO/v6sRfVbVx4HsXOZ89htvbthOboEbgC6Jtbm9fyvOa10fy+lO0/j1E5h/pWfkTofhcNmLnrILIhL0yvvdrZBXgqC48O3/GRb+DQ5u9SzMMvhRXv89kkt+nEysJYfcOq1wXLsUaif6rw3Z++A/13tq7FjDYeTrCnoiEtSC4vu7mtBnVf3sO3yMl1b9zhsbtnMs3xP2OjeJ5e/9W/GXNg1OL+z9tAwWjwJ3AXQaCZc+D1abn1ouIlVFIa8SgubCdywL3p3gWXkTMCxWLIabje5WzIh+gNdvu5CYUxVHryxXAbw9Dn5YWhj03oDWF/r3nCIiFRQ039/VgD6r6mv/4Vz+veZ3Xl+/naP5nhq3HRt7wt4FbU8j7G153zNqx10Ana+GYc8q6IkEufJ+d2tOXjBzxsCI1+GC6VAY8PJaXsidzhlsPmhl8qLNlVttqzxsYXD5y9DuUs+wjsWj4Jfl/j2niIiIlKp+tIN/DGnLmrvP56ZzWxBpt/Hd7kxumPc1Fz+zlvc37yHf5T71gdoOhSteAYsNNs+H9/8O7nK8TkSCnnryShCUv27u+hr2/Qidr+bbtGyGv7CevAI3dww4k9v6t/L/+V35ntU2f3wXbHa4cj60GuD/84qInIag/P4OUvqsQsehI3n8e83vzFu3jSN5np69+BgHo3oncVXPpsTVcpR9gO+XwJJxYLih27Vw8Wywqh9AJBhpuGYlVIcL3+KvdnLXkm+xWGDumLM4v3UD/5/Ule+Zo7flPU/ZhivnQ6sL/H9eEZFyqg7f38FCn1Xo+fNIHq+t38YbX+zgQHYu4Cm2fknnRozp04wOhSWZSvTdfzyrbRpu6HE9XPTk6dfdFRG/03DNEDfirET+1qsphgG3L9jE9oNH/H9SWzgMnwttLgZXLiy82rNCl4iIiJiuTpSdiRecybp7/sLskV3o3CSWvAI3/9m4i4ufWcvw59fxwbelDOXsOBwufQGwwNdzYdn/gfoBRKot9eSVoLr8uplb4OLKl75g044M2iRE8/aEPkTaA7AEckEe/Oe644XYr1oAZ/T3/3lFRE6hunx/BwN9VjXDph1/krJuGx9+m0ZB4Tz+hBgno5KTGNEjkfrRJw3lTJ0P70wADOg1Hi58RD16IkFEwzUroTpd+NIzj3HxM2s4kJ3HJZ0b8dSVXU6/Xk5FFOR5VuT6+UMIc8JVC6Hl+f4/r4hIGarT97fZ9FnVLHuzjvHmhh3M37CdA9l5ANisFvq1qsdlXRszsF0CEfbClTW/eR3eu9Vzv/ctMOghBT2RIKGQVwnV7cK34feD/O3lDRS4De67uB1jz24emBMX5MFb18LPyzxB7+pF0OK8wJxbRKQE1e3720z6rGqm3AIXy75LY9767WzakeHbHmW3MahDApd1bUyflvWwbXoN3r/d82TyrTDgQS3GIhIEFPIqoTpe+F79/A+mv/8jNquFN8b2IrllXGBOXJAHi0fDL/+FsAi4aj60/Etgzi0icpLq+P1tFn1W8seBIyzdtJt3Nu1mx6Ec3/YG0Q6GdWnEdY5PabR2qmdjxxEw7DkIs5vUWhEBhbxKqY4XPsMwmLQolXdS9xAXZWfBjb05Mz46MCcvyIVFo2Drx2ANg4tnQbfRgTm3iMgJquP3t1n0WYmXYRh8syODpZt28cG3aWTk5Pueu6XOl0w+9gw2w4XR/FwsI18HZxmrdIqIX2l1zRrGYrEw8/JOtG0Yw8EjeQx79nPe/mZXYE4e5oCRr0PHv4K7AN67DVY8oIKqIiIi1YDFYqF7Uh3+eWlHvvzHBfx7dA+GdEzAHmbluT97cl3unWQbTix/rCJ99l/4IvU7cgtcZjdbRMqgnrwSVOdfNw9k5zJxYSprfz0AwMgeiUwf1h5nuM3/JzcMWPkIrHrE87jtULjsJbBH+v/cIiJU7+/vQNNnJaeSeTSfj79PZ/mPezn065e8YH2UBpYMdhtxTOAfND6zK/3bxHN+mwbUjdIwTpFA0HDNSqjuFz6X2+CZT7fy1P+2YhjQJiGaOX/rRov6tQLTgG8Xw7u3gCsPGnX1rLwZnRCYc4tIjVbdv78DSZ+VnI6jeS6++TaVVivG0CB3B5lGJDfm3cEGoy1WC3RPqsN5rRuQ3DKOTo1jCbNpsJiIPyjkVUKoXPg+//UAty/cxIHsPKLsNh65ohNDOzcKzMm3r4dFf4OcgxDTBK5eCAkdA3NuEamxQuX7OxD0WUmF5BzCmH8lll0bKLCE81jkZF462LnILlF2G2c1r0tyiziSW8bRvlEsNqtKMIhUBYW8SgilC9/erGPctmATX/5xCIDRyUlMvagtjrAADN889Du8OQIObgV7LRg+F84c5P/zikiNFUrf3/6mz0oqLP8oLBkHP30AQEa/abwXeRlrtx5gwx+HyDyaX2T3aEcYPZvXJbllHL1bxNGuYQxWhT6RClHIq4RQu/AVuNw8ueIX5qz8DYCOjWN57upuNI0LwFy5o396Siz8sRosVrjwEeh1k//PKyI1Uqh9f/uTPiupFLcLProHvnzJ87j3BBj4EG4s/JiWxRe/H+SL3w+y4fdDHM4tKPLSaGcYXRJr0zWxNl2a1qZLYh3N6RMpJ4W8SgjVC99nP+1j0uJUMnLyiXaG8fhfOzOofQDmyrny4YNJsOl1z+OzbvCEPVuY/88tIjVKqH5/+4M+K6k0w4DPn4JPHvA8bnuJp5ae8/j/nlxugx/2ZLL+t4Os//0gX/1xiCN5xVfmTIqL9IS+xNp0bVqHtg1jsIdpXp/IyRTyKiGUL3y7M45y6/xv2LQjA4DLuzbmnsFtaBDj9O+JDQPWPe0prYABSWfDJU9DXEv/nldEapRQ/v6uavqspMp8uxjemQDufKjT3DM9o3G3EnctcLn5Kf0wm3ZmkLojg007/+T3/UeK7WcPs9KuYQztG8XQrlEM7RvF0jo+mgh7AKabiAQxhbxKCPULX16Bm8c++olXPv8Dw4BajjAmXtCKa/s0I9zfq2H9+B4svQnycyDMCefeDX1uA1u4f88rIjVCqH9/VyV9VlKldmyAJWMhcydYw2HADOh9M1hOPfcuMyef1F3HQ1/qzowiBdm9rBZoUb8W7Rp6gp/3b71aDn+8I5GgpJBXCTXlwpe6M4MH3v2ezbsyAWjVoBbTLmlP3zPq+ffEh/7wDN/8/TPP4/iOnl69Un71ExEpr5ry/V0V9FlJlTv6J7x7q29BFs68EIbNgai40zqMYRhsO5jDt7sy2JJ2mB/TsvhxTyYHsvNK3L9+tIMz42vRqkE0LRvUolXhLU7hT0KQQl4l1KQLn9tt8NbGnTz60c8cOuL58ryoY0OmXtSWRrUj/Hdiw4DNC+HjKZ6LgsXqmbR9/j/AHuW/84pISKtJ39+Vpc9K/MIw4KuX4eOp4MqF6EZwxcvQrG+lD73v8DF+3JNVGPo8f/84cITS/iVbN8rOGQ1qcUZh6DujQS2a14uiYWyESjpItaWQVwk18cKXmZPPrE9+Yd76bbgNiAi3cetfzmBcv+b+Lbdw5AB8NAW+W+x5XLspXDwLzrjAf+cUkZBVE7+/K0qflfhV2rfwn+s9ZZQsVjj3HjjnTrBW7b8pcvIK+Dn9ML/uy+bXfdls3ZfN1n2H2fXn0VLDn91mpWlcJM3iIkmKi6JZvSiaxUXSLC6KRrUVACW4KeRVQk2+8P24J4tp7/3Al9s8dfWaxUXywND2nN+mgX9PvHUFfDAZMnd4Hne6EgY9fNpDPESkZqvJ39+nS5+V+F1uNvz3Lkh90/M46Wy44t8Q08jvpz6a5+K3/d7gd5ite7P5dX82Ow/lkO8q/Z++4TYLiXUjaVInksa1I2hSx3NrXDuCxnUiaBDtVAgUUynkVUJNv/AZhsF7m/fw0Idb2Hc4F4CzmtXhxnNa0r9NA/8VMM3Nhs8egg0vgOGGyDi4YDp0vkrlFkSkXGr69/fp0GclAbN5kWcufv4Rz7X90ufhzEGmNMXlNtiTcZRtB4+w7WAO2w4cYXvh/R0Hc8hzuct8fbjNQsPY46GvYayT+BgnCTFOEgrvx0XZVexd/EYhrxJ04fPIzi3gmf9tZe7nf/h+9WpZP4ob+rXg0q6NcYb7aRjnro3w3m2w7wfP47ot4Jy7oONfFfZEpEz6/i4/fVYSUAd+hf9cB+nfeh63v9wzYiemobntOoHLbZCWeZTtB3PY/edRdv2Zw66Mo+z+8yi7M46SlnkMl/vU/2wOt1loEO0kPsbhC34Nop3Uj3ZQr5ad+tEO6tdyUDfKTpi/VzWXkKOQVwm68BWVnnmMlHXbeHPDdg4fKwCgXi0H1/Vtxt96NaV2pL3qT+rK9/TorZ0FOQc92+q2hHPvgg7DFfZEpETB+v09Z84c/vWvf5GWlkb79u2ZPXs2/fr1K3X/VatWMXnyZH744QcaNWrEXXfdxfjx433Pp6SkcN111xV73dGjR3E6y1f3NFg/KwlhBbnwvxnwxRzPiB17NJw/BXreVC2u6y63wd6sY+z68yi7MzxBMD3rGOmZuezNOkZ61jEOZOeWOhfwZBYL1I20F4Y/B/WjHcRF2akTZadulJ06kZ6/daPCqRvlIDYiXENFRSGvMnThK9nhY/ks+monc9f+wZ7MYwBE2m2M6JHI2LObk1g3supPmpvtWaVr3dMKeyJySsH4/b1o0SJGjRrFnDlz6Nu3Ly+++CIvv/wyP/74I02bNi22/x9//EGHDh244YYbuOmmm/j888+ZMGECCxYs4IorrgA8Ie/222/n559/LvLahISEcrcrGD8rqSHSNsOHd8CurzyP4zvARU9A097mtqsK5Lvc7DucS3rmMU/wK/y7/3Au+7Nz2X84lwPZeRw6kks5OgWLsFigdkQ4dQoDYGxEOLUjwomJCPfcj/T8PfF+jDOcaGc4znArlnLULJTgp5BXCbrwlS3f5ebDb9N4cfXvbEnLAjwFSod0bMg1vZPo2axu1Y9Fz82Gr/4Nnz8NRz2LwhB3hmcYZ4crFPZEBAjO7+9evXrRrVs3nn/+ed+2tm3bcumllzJz5sxi+99999289957bNmyxbdt/PjxbN68mfXr1wOekDdx4kQyMjIq3K5g/KykBnG7YdPr8MkDnlJKAF2ugQHTIcrP9XqDgMttcOhIXmHoy/WFwD+P5HHoSB5/5uRx8Eie73FW4UiqigqzWoh2hhHtDCfaGUYth+d+jDPM89gZRpTDsz3SHkYth40o3/0wohw2ouyefexhGmJqJoW8StCFr3wMw2Dtrwd4afXvrNl6wLc9PsbBxZ0acUnnRnRqElu1vxyVFvb63eEJe2EqfCpSkwXb93deXh6RkZG89dZbXHbZZb7tt99+O6mpqaxatarYa8455xy6du3KU0895du2dOlSRowYQU5ODuHh4aSkpDBu3DgaN26My+WiS5cuPPjgg3Tt2rXcbQu2z0pqqCMH4X/T4Jt5nsfO2nDBA9BtDFgVJrzyXW4ycvI94S87j8yjeWTk5JN59Pgt42g+Wd77hc9lHcsv9/DR8gqzWogItxFhtxFptxFhD/P8PWFbpN2GI8yGM9yz3Rlu9d13nHDfGW7DEWbFEW7FEVZ4P8yKo3B7mNWiHsiTlPe7W90fUmEWi4V+rerTr1V9ftyTxWvrtrHs+zT2ZuXyyto/eGXtHyTFRTK0UyOGdm5E64Toyp/UUQvOngRnjYMv/+0ZxnnwV3jnZljxAPS43nOLjq/8uUREKunAgQO4XC7i44t+J8XHx5Oenl7ia9LT00vcv6CggAMHDtCwYUPatGlDSkoKHTt2JCsri6eeeoq+ffuyefNmWrVqVeJxc3Nzyc3N9T3Oysqq5LsTqQJRcXDJM9B1FHw4GdK/86zEuekNzxDORuX/4SKUhdusngVboh1wGv/EMQyDI3kuDh/L5/CxgsJb0fvZuZ77R3ILOJJXQHauy3O/8PGRXBfZuQXkFXhWHi1wGxzOLeBwbuV6F8vDagFHmA17mNVzs3lC4ImPS7sf7rtZjt8Ps/ieC7NZCLd6/obZrIRbPX9P3B5usxBmtWKzeo5hs1oIs1o8r/G+1mop3H78+WBYXVUhT6pEu0YxPDq8EzMubc/qXw7w3uY9fPLjXrYfzOHZz37l2c9+pXV8NEM7N2Ro50YkxUVV7oSOaOg3GXre4Al7X74Eh9Ng1SOw5gnocDn0ugkad6+aNygiUgkn/xJtGEaZv06XtP+J23v37k3v3sfnL/Xt25du3brxzDPP8PTTT5d4zJkzZzJ9+vQKtV/E7xJ7wg0rPfPwP3sIdm+El86H9pd6pmbEtzO7hdWSxWKhVuEwzIaxlTtWvstNTq6Lo/kucvIKyMnz3ndxNM/F0fwC3/2cPBfH8l0cy3dzrMB7v/Bxvud1x/Ld5Oa7yC1wk1vgIjffTW6Bu0gZC7cBRwv3r2684c/mC4HH70+/pAMXdij/HOoKnd+vR5caxxFmY0C7eAa0iycnr4AVP+7l/c1prPplHz/vPczPyw/z+PJfaJMQzdln1KNvq3r0bFaXKEcF/6foDXt9boMt78GGF2HnBvh2kefWpKcn7LUbBrbwqn2zIiKnUK9ePWw2W7Feu3379hXrrfNKSEgocf+wsDDi4uJKfI3VauWss85i69atpbZlypQpTJ482fc4KyuLxMTE8r4VEf+zhUHv8Z5gt/w++G4x/LAUfnhHYS8IhNusxEZaicW//55yuw3yXO7C0OcJgccKw2C+y01eYRDMKzh+P7fg+ON8l5sCt+G777l5jlngvX/CfvkuNwUugwK3mzyXQUHh43x34fbC/VxugwJ38celKSjj+VPVY6wKCnniN5H2MIZ1acywLo3JzMnn4x/SeW/zHtb9doCf0g/zU/phXl77B+E2C12b1vGEvjPq0blJ7OnXjbGFe+bkdbjC8+vfhpfg+yWw60vPbfm9cNZY6H5djZjQLSLBwW630717d1asWFFkTt6KFSsYNmxYia9JTk7m/fffL7Jt+fLl9OjRg/Dwkv9xZRgGqampdOzYsdS2OBwOHA7NW5ZqIDoBrvg3nD0RVj0KP76rsFeDWK0WnFZbYT3m4P6B3jBOCH+Fwc99wn2XYeAqDJBuwxsSDZrUifB727TwSgk0Gd2/Dmbnsu63g3z+6wHWbD3A7oyjRZ6PdoTRu2UcZ59Rj14t6tKqQXTF6sIc3gsbX4WvXoEj+zzbbHZoPcQz9r/l+WD1U0F3ETFFMH5/e0sovPDCCyQnJ/PSSy/x73//mx9++IGkpCSmTJnC7t27mTfPs/CEt4TCTTfdxA033MD69esZP358kRIK06dPp3fv3rRq1YqsrCyefvppXn/9dT7//HN69uxZrnYF42clUqK9PxwPewBYFPakxtLqmpWgC1/gGIbBjkM5rP31AGu3HmDdbwfJPJpfZJ9Iu40OjWPpklibzk1q0zkxlsa1I8q/2lJBrufXvw0vwJ5vjm+PbgRdrvbc4lpW3ZsSEdME6/f3nDlzeOyxx0hLS6NDhw7MmjWLc845B4AxY8awbds2Vq5c6dt/1apVTJo0yVcM/e677y5SDH3SpEm8/fbbpKenExsbS9euXZk2bRrJycnlblOwflYipVLYE1HIqwxd+Mzjchv8sCeTtb8e4PNfD5C6I4MjecUn29arZS8MfJ5bx8ax1I2yn/oEad9C6pue+XreujwASWdD17955u7ZK7kojIiYRt/f5afPSqqtYmEPaH6OZ0pGm4shrBz/HhCpphTyKkEXvuDhchv8vj+b1J0ZbN6VweadmWxJyypxImu9Wg5aJ9TizPhoWsdHc2ZCNGfGR1OrpEVdCnLh52WeJZp//R9QeDx7NHS4zFOQtclZqtEjUs3o+7v89FlJtbf3B1j5CGx5H991PLKe50fbbtdqlI6EJIW8StCFL7gdy3fxY1oWm3dmsHlnBqk7M9h2MKfU/RvXjqB1YeA7o0EtmsVFkhQXRb1ads+Qz8xdsHkBbHoT/vzj+AujG0HbodDuEmiarPl7ItWAvr/LT5+VhIyMHZ5i6t+8DtknrEyr3j0JQQp5laALX/VzJLeAX/dl8/Pew/ySftjzd+9h9mbllvqaKLuNpLgokgpDX7O6EXRw/UCLnW8T8dt/seRln7BzfWhzEbS9xHPRUDkGkaCk7+/y02clIcdVAFs/hq9fhV8/Qb17EooU8ipBF77QkZGTxy97PeHv5/Qs/jhwhG0HctiTeZSy/pdfy1bARVE/Mdj2JWflbiDKfdj3XIEjloIzLsTR8VIsLf8C4c4AvBMRKQ99f5efPisJaaX17jXsAm0vhjZDoX5rKO8ibiJBQiGvEnThC325BS52HjrKjkOe0Lf94BG2H8ph+8Ecdh7KKTLnL4wCkq0/Mtj6JQNsX1PfkuV7LgcnP9o78nutbqTH9SK/XjviajmJq+WgXi0H9WrZqVfLQWxEONaKlIEQkdOi7+/y02clNUJpvXsAdVseD3yNu2sevlQLCnmVoAtfzVbgcpOedYz0zGPsyTxGeuZR9mR4Hu/NyKZBRiq9cz9nkO0rGlkOFXntn0Yt1rvbsc7dnvXudvxmNAIs2KwWYiPCqR0RTmyk52/tSLtn20mPo51hRDu9f8OIsocpIIqUk76/y0+fldQ42fs9i6799AH8vhJcecefq5UAbYZ45u8166c5fBK0FPIqQRc+OZW8Ajf7snLI2paKddsaotPWUf/Q19hdRReA2UcdPne1Y727HanuM/jNaISL01vAxWKBWvYwX/ir5Q1/jv9v7+6Do6ruPoB/7923bEKIgYRsIhgjoLzKMxKlCWItTNPEqQOIY+pQJ7QzOEFgpOi0pUqhdjrQN2o7SFpadOrINAyjWEagGirE8vYIlpcUog+VQFASY0DySja7e8/zx7n7lmzCkre7e/P9zNy555579uacnLA/fvfevWvFCLtcJzkscm2X60S7FSMcViQ6LEiyW5Fot8BptyDRbkGC1cKkkUyL79/R4++KhrWOZnll7+N3gP97D+gMfiwDjhTgztlA9mwgOx9w3QtYIjypm8gATPL6gYGP+sTnAa6cAmoOAjUfALX/C/jCH/zisySgJWUSvkyejCvOibhgm4gLyjhc6xBoavfg+o1OtHR49cUDj29w/nk6bZawxM9pt8JpU5Fgs8BpsyAhsITWqXDaLHDYLHBYVTisFjhsarBsVZFgC6m3WGC3qrBbVViYVNIQ4ft39Pi7ItJ53TJuf/wO8PFeoK0hfL89GbjjazLhu/NB+bk+XukjgzDJ6wcGPhoQng7gsw9l4Lh0BKg7DYQ+sdPP4gAypgJZ/wNkzgDSJwGjJ0I4U+H2iUDC1+oOJn/NHV60u71o6/Sh1S3LrW4f2txetHV65dot993w+NDe6UWHRxvyX0FgiKoCu0UNJH2Bsr62WRTYAuWQbYu+bVVgVeV+q6rAalFhUxXY9G2bRYVVf43NIttaVXmbrM0ik0yrv96iyGPoZYuqwKIogTYWfZ9c6/v1NrwCGvv4/h09/q6IItB88oTtpUPAxcNA7THA3RTexpYov0s3e7b8LJ9rGjAigw9xoSHBJK8fGPhoUGgacO1TGTzqTsmkr+404G6O3D7hNiBtIjB6QnBJmwiMuguwOfvw44We8Plwo9OHdo83WO70ocPjww2PD2593eHRAnUdHi2k3odOnybrvD64PRrcXr3s1eD2aOjw+np9emk8s6oy2bMoSqAcWmdRFSgKwhJDVQFUJZgwKooCi17n329RFbmtBLcVJfhatcuxlEC9f9tfF2yvKIACvY2qQAHC2vn3QT+Of1tRgu0UhLf3/x8mePzQtvJYSrf98rXwt/G/xr8v5NgjHFbMm5zR5/nh+3f0+LsiioLmA774j0z4Lh2WJ21vXOveLjENcE2XCV+Gvk67m1+5RAOOSV4/MPDRkNE0+QXsgaTvDNB4Hmj+rJcXKUDKOCA1Gxh5O5AyNnwZeTuQYOzfrRACXk2g06vJxSfX7i7bsuyDxyfg8Wly8Qp0+jR4fRo8Pln26O29mmzn9Ql4NQ2dXrn2hrzeq4nAfq8m4NMEPD4Bn+Z/nZDH1gQ0TQTa+BevpkHju6Jh7kpLwvvPP9zn1/P9O3r8XRH1gaYBjZ8AFw8BtUeB+irg6n8BEeFuGYtd3p3jmi6/rmHUXXJJzQHsiUPfdzKFaN+7+SlSIiOpqvxi1tHjgWmLgvWd7cC1C8DV8zJ4NP5Xrq+eBzqagKZaufTEkaInfbcDyS4gaQwwYgyQlBZSTgecqYNye4miKIFbLpMcA374QadpAj7hT/rCk0BNT2BDE0RNyMRSE8FtWUZg26cfU9MENAHZJrQc8hpNCAi9LNC1nUyi/WX/cYSA3IfubUTIdmi7YH3o62Sd6FoX0l4A+nFkGWH7g2VN3ynrwl/r3wbCX+NK4fdOElEMU1VgzGS5PLBU1nW2Aw3VwBdVQP1/ZOL3xVn5MJf6M3LpKjlTT/pygsnfqLvkSdxBis00vDDJI4pF9kR5q4drWni9EED7VZnwXb8MNF0Gmj8Hmj4Dmj6X2x3X5ecHGpqAhrO9/xzVKpO9pHQgcTTgvE0Gl4TbZDlB3w6UbwMSUgD7CEC9taeExhNVVaBCgc28QyQiooFiTwTGzpSLn6YB1y/JWz3r/yPj9rUL8mMbHU1AS51cLh3ufjyrU56gHZklk8GRmUBylr7WlxEZgI0nxahnTPKI4omi6Ffj0uSTviJxt4Ykfp8BrV8ArQ1A25dyaW2QTw7raAI0bzDQ3Cpbokz2HCP0dXL4tn2EDEA2pwxYtpAldNuaAFgd8rYWq0M+iMZql2uLjWcziYgo/qiqfpUuB5j8aPi+9mvAtRo96bsgP7Zx7QJw9VOgvRHw3pB1X9X0/jNsiYBzlDwZm5iqn5QdBSSOCpadtwH2JD0uJ4WUR/AJoUNBCHkrr+aVi88jP+dpTxr0JJ1JHpHZOEbIe//T7+m9ndcdkvR9KYNOx3XgxnXgxlfBcoe+7S/7vzzW0y6Xro+aHlBKSPJnl0mfapPfV2SxB8uqTd9nDa4Vi7zaqFrD14q/bAUUVa9TZH1gWw3ZVmU/FFVf9HK3OkWvi3INhCSwodtd90X6tfQx8Y32I9iBdiJCXUj9Ldf1tq2XHSOB6Y9H108ioniUqCdioVf+/DwdwZOvzVf0dR3QciW4bqmXsdgfh3v9HH8vVFtI0peon2QNWXra9sfQwGKJsG0JiZVKL2U9nokI8aFbWU+Yui1d6jWfTKiET15RDZS9+j5fyLY32D6sHFrXZfH1UB9xvyfy7/7xV8M/pjMIDE/ytmzZgl//+teoq6vD1KlT8fLLL2POnDk9tq+srMTq1atx9uxZZGVl4Yc//CFKS0vD2rz55ptYu3YtPv30U4wfPx6/+MUvsHDhwsEeClF8sTqCD2uJlhAyOexsBdwt+ro18nZnqwxW3huAJ2TxduiBSV97O+QxfZ1yLXyhP1B+12CX7xskExs9gUkeEQ1ftoTgFcCeaJp8MveNa/IkbPtX+slY//a14HZHE9DZpsflNrl4O/TjeOTJ247rQzEyCqX5bt6mnwxN8nbs2IFVq1Zhy5YtmD17Nv70pz+hqKgI586dwx133NGtfU1NDR555BEsXboUb7zxBg4fPoxnnnkG6enpWLRIZsNHjx5FcXExfv7zn2PhwoXYtWsXnnjiCRw6dAizZs0a6iESmYui6LdgJshbRgeD5tOTPjfg7Qxf+zwhtzt4wrd9ncFyr2fsQm6bCJz58+lPEvGFbGvB1waeLtLlrGG3s4pdrkxFWoc9gS3KK12h+vtA5IhXASPUhbVTbr4v4lXJXrZ7apPs6qHjREQEQN5h4rxNLn3h8wKeNv2krJ4Aetpl7A3EX3eX7Q4Zi70d4bcfRrwapm+HxcqucTM0PurC7nhBhLLaZempzn9lUQ0pW7rcwWPR7/zpehUywpVJRQ3eSRS632KL0N4WYX+kRe3b3N0CQ79CYdasWbjvvvtQVlYWqJs8eTIWLFiADRs2dGv/ox/9CLt370Z1dXWgrrS0FKdPn8bRo0cBAMXFxWhubsa+ffsCbQoLC5Gamoq//e1vUfWLj5UmIopPfP+OHn9XRETxJ9r37sFPI3vQ2dmJjz76CAUFBWH1BQUFOHLkSMTXHD16tFv7b33rWzhx4gQ8Hk+vbXo6JhERERERkZkYdrtmY2MjfD4fMjIywuozMjJQX18f8TX19fUR23u9XjQ2NiIzM7PHNj0dEwDcbjfc7uBnfpqbm291OERERERERDHBsCt5fkqXz4cIIbrV3ax91/pbPeaGDRuQkpISWMaNGxd1/4mIiIiIiGKJYUleWloaLBZLtytsDQ0N3a7E+blcrojtrVYrRo8e3Wubno4JAGvWrEFTU1NguXz5cl+GREREREREZDjDkjy73Y6ZM2eioqIirL6iogL5+fkRX5OXl9et/XvvvYfc3FzYbLZe2/R0TABwOBwYOXJk2EJERERERBSPDP0KhdWrV+Opp55Cbm4u8vLysHXrVtTW1ga+927NmjX4/PPP8frrrwOQT9LcvHkzVq9ejaVLl+Lo0aPYtm1b2FMzn332WTz00EP45S9/ifnz5+Pvf/879u/fj0OHDhkyRiIiIiIioqFkaJJXXFyMq1ev4qWXXkJdXR2mTZuGvXv3Ijs7GwBQV1eH2traQPucnBzs3bsXP/jBD/DKK68gKysLf/jDHwLfkQcA+fn5KC8vx4svvoi1a9di/Pjx2LFjB78jj4iIiIiIhgVDvycvVvG7g4iI4hPfv6PH3xURUfyJ+e/JIyIiIiIiooHHJI+IiIiIiMhEmOQRERERERGZCJM8IiIiIiIiE2GSR0REREREZCJM8oiIiIiIiEyESR4REREREZGJMMkjIiIiIiIyESZ5REREREREJsIkj4iIiIiIyESY5BEREREREZkIkzwiIiIiIiITsRrdgVgkhAAANDc3G9wTIiK6Ff73bf/7OPWMsY6IKP5EG+eY5EXQ0tICABg3bpzBPSEior5oaWlBSkqK0d2IaYx1RETx62ZxThE83dmNpmm4cuUKkpOToShKn47R3NyMcePG4fLlyxg5cuQA93BomWUsZhkHYJ6xmGUcgHnGEu/jEEKgpaUFWVlZUFV+IqE3/Y118f63EopjiT1mGQdgnrGYZRxAfI8l2jjHK3kRqKqKsWPHDsixRo4cGXd/PD0xy1jMMg7APGMxyzgA84wlnsfBK3jRGahYF89/K11xLLHHLOMAzDMWs4wDiN+xRBPneJqTiIiIiIjIRJjkERERERERmQiTvEHicDiwbt06OBwOo7vSb2YZi1nGAZhnLGYZB2CesZhlHDT4zPS3wrHEHrOMAzDPWMwyDsBcY+kJH7xCRERERERkIrySR0REREREZCJM8oiIiIiIiEyESR4REREREZGJMMkbBFu2bEFOTg4SEhIwc+ZM/Otf/zK6S7ds/fr1UBQlbHG5XEZ3KyoffPABHn30UWRlZUFRFLz99tth+4UQWL9+PbKysuB0OvHwww/j7NmzxnS2Fzcbx5IlS7rN0de+9jVjOtuLDRs24P7770dycjLGjBmDBQsW4JNPPglrEy9zEs1Y4mVeysrKcO+99wa+IygvLw/79u0L7I+XOSHjMNYZxyxxDmCsi8V5MUusG+5xjkneANuxYwdWrVqFF154ASdPnsScOXNQVFSE2tpao7t2y6ZOnYq6urrAUlVVZXSXotLW1oYZM2Zg8+bNEff/6le/wqZNm7B582YcP34cLpcL3/zmN9HS0jLEPe3dzcYBAIWFhWFztHfv3iHsYXQqKyuxfPlyHDt2DBUVFfB6vSgoKEBbW1ugTbzMSTRjAeJjXsaOHYuNGzfixIkTOHHiBObOnYv58+cHAly8zAkZg7HOWGaJcwBjXSzOi1li3bCPc4IG1AMPPCBKS0vD6iZNmiR+/OMfG9Sjvlm3bp2YMWOG0d3oNwBi165dgW1N04TL5RIbN24M1HV0dIiUlBTxxz/+0YAeRqfrOIQQoqSkRMyfP9+Q/vRHQ0ODACAqKyuFEPE7J0J0H4sQ8TsvQgiRmpoq/vKXv8T1nNDQYKyLHWaJc0Iw1sUqM8W64RTneCVvAHV2duKjjz5CQUFBWH1BQQGOHDliUK/67vz588jKykJOTg6+853v4MKFC0Z3qd9qampQX18fNkcOhwNf//rX43KODh48iDFjxuDuu+/G0qVL0dDQYHSXbqqpqQkAMGrUKADxPSddx+IXb/Pi8/lQXl6OtrY25OXlxfWc0OBjrIttZvz3G2/vqQBjXawZjnGOSd4AamxshM/nQ0ZGRlh9RkYG6uvrDepV38yaNQuvv/463n33Xfz5z39GfX098vPzcfXqVaO71i/+eTDDHBUVFWH79u14//338dvf/hbHjx/H3Llz4Xa7je5aj4QQWL16NR588EFMmzYNQPzOSaSxAPE1L1VVVRgxYgQcDgdKS0uxa9cuTJkyJW7nhIYGY11sM9u/33h6T/VjrIsdwznOWY3ugBkpihK2LYToVhfrioqKAuXp06cjLy8P48ePx1//+lesXr3awJ4NDDPMUXFxcaA8bdo05ObmIjs7G3v27MFjjz1mYM96tmLFCpw5cwaHDh3qti/e5qSnscTTvNxzzz04deoUrl+/jjfffBMlJSWorKwM7I+3OaGhZYa/DzPHOjPMDxBf76l+jHWxMy/DOc7xSt4ASktLg8Vi6XYGoKGhoduZgniTlJSE6dOn4/z580Z3pV/8T00z4xxlZmYiOzs7Zudo5cqV2L17Nw4cOICxY8cG6uNxTnoaSySxPC92ux0TJkxAbm4uNmzYgBkzZuD3v/99XM4JDR3Guthm9n+/sfyeCjDWxdq8DOc4xyRvANntdsycORMVFRVh9RUVFcjPzzeoVwPD7XajuroamZmZRnelX3JycuByucLmqLOzE5WVlXE/R1evXsXly5djbo6EEFixYgXeeustvP/++8jJyQnbH09zcrOxRBKr8xKJEAJutzuu5oSGHmNdbDP7v99YfU9lrIvNeelqWMW5oX7Si9mVl5cLm80mtm3bJs6dOydWrVolkpKSxMWLF43u2i157rnnxMGDB8WFCxfEsWPHxLe//W2RnJwcF+NoaWkRJ0+eFCdPnhQAxKZNm8TJkyfFpUuXhBBCbNy4UaSkpIi33npLVFVViSeffFJkZmaK5uZmg3serrdxtLS0iOeee04cOXJE1NTUiAMHDoi8vDxx++23x9w4li1bJlJSUsTBgwdFXV1dYGlvbw+0iZc5udlY4mle1qxZIz744ANRU1Mjzpw5I37yk58IVVXFe++9J4SInzkhYzDWGcsscU4IxrpYnBezxLrhHueY5A2CV155RWRnZwu73S7uu+++sEfOxovi4mKRmZkpbDabyMrKEo899pg4e/as0d2KyoEDBwSAbktJSYkQQj7GeN26dcLlcgmHwyEeeughUVVVZWynI+htHO3t7aKgoECkp6cLm80m7rjjDlFSUiJqa2uN7nY3kcYAQLz22muBNvEyJzcbSzzNy/e///3A+1R6erqYN29eIPAJET9zQsZhrDOOWeKcEIx1sTgvZol1wz3OKUIIMfDXB4mIiIiIiMgI/EweERERERGRiTDJIyIiIiIiMhEmeURERERERCbCJI+IiIiIiMhEmOQRERERERGZCJM8IiIiIiIiE2GSR0REREREZCJM8oiIiIiIiEyESR4RRaQoCt5++22ju0FERDRoGOvIrJjkEcWgJUuWQFGUbkthYaHRXSMiIhoQjHVEg8dqdAeIKLLCwkK89tprYXUOh8Og3hAREQ08xjqiwcEreUQxyuFwwOVyhS2pqakA5O0lZWVlKCoqgtPpRE5ODnbu3Bn2+qqqKsydOxdOpxOjR4/G008/jdbW1rA2r776KqZOnQqHw4HMzEysWLEibH9jYyMWLlyIxMRETJw4Ebt37w7s++qrr7B48WKkp6fD6XRi4sSJ3QI1ERFRbxjriAYHkzyiOLV27VosWrQIp0+fxne/+108+eSTqK6uBgC0t7ejsLAQqampOH78OHbu3In9+/eHBbaysjIsX74cTz/9NKqqqrB7925MmDAh7Gf87Gc/wxNPPIEzZ87gkUceweLFi3Ht2rXAzz937hz27duH6upqlJWVIS0tbeh+AUREZHqMdUR9JIgo5pSUlAiLxSKSkpLClpdeekkIIQQAUVpaGvaaWbNmiWXLlgkhhNi6datITU0Vra2tgf179uwRqqqK+vp6IYQQWVlZ4oUXXuixDwDEiy++GNhubW0ViqKIffv2CSGEePTRR8X3vve9gRkwERENO4x1RIOHn8kjilHf+MY3UFZWFlY3atSoQDkvLy9sX15eHk6dOgUAqK6uxowZM5CUlBTYP3v2bGiahk8++QSKouDKlSuYN29er3249957A+WkpCQkJyejoaEBALBs2TIsWrQI//73v1FQUIAFCxYgPz+/T2MlIqLhibGOaHAwySOKUUlJSd1uKbkZRVEAAEKIQDlSG6fTGdXxbDZbt9dqmgYAKCoqwqVLl7Bnzx7s378f8+bNw/Lly/Gb3/zmlvpMRETDF2Md0eDgZ/KI4tSxY8e6bU+aNAkAMGXKFJw6dQptbW2B/YcPH4aqqrj77ruRnJyMO++8E//85z/71Yf09HQsWbIEb7zxBl5++WVs3bq1X8cjIiIKxVhH1De8kkcUo9xuN+rr68PqrFZr4APfO3fuRG5uLh588EFs374dH374IbZt2wYAWLx4MdatW4eSkhKsX78eX375JVauXImnnnoKGRkZAID169ejtLQUY8aMQVFREVpaWnD48GGsXLkyqv799Kc/xcyZMzF16lS43W688847mDx58gD+BoiIyOwY64gGB5M8ohj1j3/8A5mZmWF199xzDz7++GMA8mlg5eXleOaZZ+ByubB9+3ZMmTIFAJCYmIh3330Xzz77LO6//34kJiZi0aJF2LRpU+BYJSUl6OjowO9+9zs8//zzSEtLw+OPPx51/+x2O9asWYOLFy/C6XRizpw5KC8vH4CRExHRcMFYRzQ4FCGEMLoTRHRrFEXBrl27sGDBAqO7QkRENCgY64j6jp/JIyIiIiIiMhEmeURERERERCbC2zWJiIiIiIhMhFfyiIiIiIiITIRJHhERERERkYkwySMiIiIiIjIRJnlEREREREQmwiSPiIiIiIjIRJjkERERERERmQiTPCIiIiIiIhNhkkdERERERGQiTPKIiIiIiIhM5P8Bc462NlJap+8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 900x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_history(ms_linear_history)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2b777950",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_predictions(ms_linear, ms_sample_batch, 'multi_step')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5a02317",
   "metadata": {},
   "source": [
    "## Multi_output "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f6ce1498",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_ds_mo = format_timeseries_data(train_df, 1, 1, ['OT', 'MULL'])\n",
    "val_ds_mo = format_timeseries_data(val_df, 1, 1, ['OT', 'MULL'])\n",
    "test_ds_mo = format_timeseries_data(test_df, 1, 1, ['OT', 'MULL'])\n",
    "\n",
    "mo_sample_batch = next(iter(test_ds_mo))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "90b83dd3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "382/382 [==============================] - 1s 2ms/step - loss: 0.2673 - mean_absolute_error: 0.4178 - val_loss: 0.0487 - val_mean_absolute_error: 0.1801\n",
      "Epoch 2/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 0.0541 - mean_absolute_error: 0.1802 - val_loss: 0.0206 - val_mean_absolute_error: 0.1121\n",
      "Epoch 3/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0334 - mean_absolute_error: 0.1403 - val_loss: 0.0152 - val_mean_absolute_error: 0.0962\n",
      "Epoch 4/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0259 - mean_absolute_error: 0.1244 - val_loss: 0.0172 - val_mean_absolute_error: 0.1038\n",
      "Epoch 5/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0216 - mean_absolute_error: 0.1133 - val_loss: 0.0200 - val_mean_absolute_error: 0.1137\n",
      "Epoch 6/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 0.0185 - mean_absolute_error: 0.1043 - val_loss: 0.0199 - val_mean_absolute_error: 0.1143\n",
      "Epoch 7/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0159 - mean_absolute_error: 0.0969 - val_loss: 0.0170 - val_mean_absolute_error: 0.1058\n",
      "Epoch 8/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 0.0139 - mean_absolute_error: 0.0907 - val_loss: 0.0134 - val_mean_absolute_error: 0.0933\n",
      "Epoch 9/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0123 - mean_absolute_error: 0.0852 - val_loss: 0.0103 - val_mean_absolute_error: 0.0814\n",
      "Epoch 10/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 0.0108 - mean_absolute_error: 0.0802 - val_loss: 0.0081 - val_mean_absolute_error: 0.0719\n",
      "Epoch 11/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0096 - mean_absolute_error: 0.0755 - val_loss: 0.0066 - val_mean_absolute_error: 0.0647\n",
      "Epoch 12/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0085 - mean_absolute_error: 0.0711 - val_loss: 0.0055 - val_mean_absolute_error: 0.0589\n",
      "Epoch 13/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0076 - mean_absolute_error: 0.0670 - val_loss: 0.0047 - val_mean_absolute_error: 0.0541\n",
      "Epoch 14/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 0.0068 - mean_absolute_error: 0.0633 - val_loss: 0.0040 - val_mean_absolute_error: 0.0500\n",
      "Epoch 15/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0061 - mean_absolute_error: 0.0599 - val_loss: 0.0035 - val_mean_absolute_error: 0.0466\n",
      "Epoch 16/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0055 - mean_absolute_error: 0.0569 - val_loss: 0.0031 - val_mean_absolute_error: 0.0437\n",
      "Epoch 17/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0049 - mean_absolute_error: 0.0540 - val_loss: 0.0028 - val_mean_absolute_error: 0.0414\n",
      "Epoch 18/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 0.0045 - mean_absolute_error: 0.0514 - val_loss: 0.0026 - val_mean_absolute_error: 0.0393\n",
      "Epoch 19/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0041 - mean_absolute_error: 0.0489 - val_loss: 0.0024 - val_mean_absolute_error: 0.0376\n",
      "Epoch 20/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0037 - mean_absolute_error: 0.0466 - val_loss: 0.0022 - val_mean_absolute_error: 0.0361\n",
      "Epoch 21/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0034 - mean_absolute_error: 0.0445 - val_loss: 0.0021 - val_mean_absolute_error: 0.0347\n",
      "Epoch 22/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0032 - mean_absolute_error: 0.0426 - val_loss: 0.0020 - val_mean_absolute_error: 0.0335\n",
      "Epoch 23/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0029 - mean_absolute_error: 0.0408 - val_loss: 0.0019 - val_mean_absolute_error: 0.0324\n",
      "Epoch 24/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0027 - mean_absolute_error: 0.0391 - val_loss: 0.0018 - val_mean_absolute_error: 0.0314\n",
      "Epoch 25/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0025 - mean_absolute_error: 0.0376 - val_loss: 0.0017 - val_mean_absolute_error: 0.0304\n",
      "Epoch 26/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 0.0024 - mean_absolute_error: 0.0362 - val_loss: 0.0017 - val_mean_absolute_error: 0.0295\n",
      "Epoch 27/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0023 - mean_absolute_error: 0.0349 - val_loss: 0.0016 - val_mean_absolute_error: 0.0286\n",
      "Epoch 28/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0021 - mean_absolute_error: 0.0338 - val_loss: 0.0016 - val_mean_absolute_error: 0.0278\n",
      "Epoch 29/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0021 - mean_absolute_error: 0.0328 - val_loss: 0.0015 - val_mean_absolute_error: 0.0271\n",
      "Epoch 30/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0020 - mean_absolute_error: 0.0319 - val_loss: 0.0015 - val_mean_absolute_error: 0.0265\n",
      "Epoch 31/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0019 - mean_absolute_error: 0.0312 - val_loss: 0.0015 - val_mean_absolute_error: 0.0260\n",
      "Epoch 32/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0019 - mean_absolute_error: 0.0306 - val_loss: 0.0014 - val_mean_absolute_error: 0.0256\n",
      "Epoch 33/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0018 - mean_absolute_error: 0.0300 - val_loss: 0.0014 - val_mean_absolute_error: 0.0253\n",
      "Epoch 34/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0018 - mean_absolute_error: 0.0295 - val_loss: 0.0014 - val_mean_absolute_error: 0.0251\n",
      "Epoch 35/50\n",
      "382/382 [==============================] - 1s 1ms/step - loss: 0.0018 - mean_absolute_error: 0.0291 - val_loss: 0.0014 - val_mean_absolute_error: 0.0249\n",
      "Epoch 36/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0017 - mean_absolute_error: 0.0288 - val_loss: 0.0014 - val_mean_absolute_error: 0.0247\n",
      "Epoch 37/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0017 - mean_absolute_error: 0.0285 - val_loss: 0.0014 - val_mean_absolute_error: 0.0244\n",
      "Epoch 38/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0017 - mean_absolute_error: 0.0283 - val_loss: 0.0014 - val_mean_absolute_error: 0.0242\n",
      "Epoch 39/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0017 - mean_absolute_error: 0.0280 - val_loss: 0.0014 - val_mean_absolute_error: 0.0240\n",
      "Epoch 40/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0017 - mean_absolute_error: 0.0278 - val_loss: 0.0013 - val_mean_absolute_error: 0.0237\n",
      "Epoch 41/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0017 - mean_absolute_error: 0.0277 - val_loss: 0.0013 - val_mean_absolute_error: 0.0236\n",
      "Epoch 42/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0016 - mean_absolute_error: 0.0276 - val_loss: 0.0013 - val_mean_absolute_error: 0.0236\n",
      "Epoch 43/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0016 - mean_absolute_error: 0.0274 - val_loss: 0.0013 - val_mean_absolute_error: 0.0237\n",
      "Epoch 44/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0016 - mean_absolute_error: 0.0274 - val_loss: 0.0014 - val_mean_absolute_error: 0.0240\n",
      "Epoch 45/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0016 - mean_absolute_error: 0.0273 - val_loss: 0.0014 - val_mean_absolute_error: 0.0243\n",
      "Epoch 46/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0016 - mean_absolute_error: 0.0272 - val_loss: 0.0014 - val_mean_absolute_error: 0.0246\n",
      "Epoch 47/50\n",
      "382/382 [==============================] - 0s 1ms/step - loss: 0.0016 - mean_absolute_error: 0.0272 - val_loss: 0.0014 - val_mean_absolute_error: 0.0248\n"
     ]
    }
   ],
   "source": [
    "mo_linear = Sequential([\n",
    "    Dense(units=2)\n",
    "])\n",
    "\n",
    "mo_linear_history = train_model(mo_linear, train_ds_mo, val_ds_mo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "0bdb5cd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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jPPbYY0bbtm0Nm81mREZGGp06dTIeeOABIz09/Zzf2/Lly40rrrjCqFevnhEQEGA0btzYuOKKK4yPP/7YtY/zv8GhQ4dKfT4uLs644ooryjz25s2bjauuusqIjIw0bDab0aVLlxL/LQyjuLrm6eeT85PJMAzD86GliIiIiIiIuIOqa4qIiIiIiPgRBXkiIiIiIiJ+REGeiIiIiIiIH1GQJyIiIiIi4kcU5ImIiIiIiPgRBXkiIiIiIiJ+RIuhl6GoqIgDBw4QHh7uWjhaRER8m2EYHDt2jPDwcCIiIvT7fQ7q60REzj/Ovq5Ro0aYzeXn6xTkleHAgQM0bdrU280QEZEqysrKIiIiwtvN8Gnq60REzl979+6lSZMm5b6vIK8M4eHhgOPL0z8SRETOD9nZ2TRt2pS9e/e6fselfOrrRETOP86+7lz9nIK8MjiHrURERKjjExE5z2ioZsWorxMROX+dq59T4RURERERERE/oiBPRERERETEjyjIExERERER8SOakycifq2oqIi8vDxvN0NqSEBAABaLxdvNEBHxKYWFheTn53u7GVIDaqqfU5AnIn4rLy+PXbt2UVRU5O2mSA2qU6cOsbGxKq4iIrWeYRikp6dz9OhRbzdFalBN9HMK8kTELxmGQVpaGhaLhaZNm551wVA5PxiGwYkTJ8jIyACgYcOGXm6RiIh3OQO86OhoQkJCdPPrPFeT/ZyCPBHxSwUFBZw4cYJGjRoREhLi7eZIDQkODgYgIyOD6OhoDd0UkVqrsLDQFeBFRUV5uzlSQ2qqn9OtbRHxS4WFhQDYbDYvt0RqmjNo1/wTEanNnL+BupHpf2qin1OQJyJ+TUNX/I/+m4qIFNNvov+pif+mCvJERERERET8iII8ERE/N2DAACZMmODtZoiIiLiN+rqSVHhFRMRHnGt4xi233EJSUlKlj7tw4UICAgKq2CoREZGao77OMxTkiYj4iLS0NNfz5ORknnjiCX799VfXNmfFLaf8/PwKdWj16tWruUaKiIhUg/o6z9BwTRERHxEbG+t6REZGYjKZXK9zc3OpU6cOH330EQMGDCAoKIh//etfHD58mBtvvJEmTZoQEhJCp06dmDdvXonjnjmEpXnz5jzzzDPceuuthIeH06xZM+bMmePhqxURkdpIfZ1nKMgTkVrBMAxO5BV45WEYRo1dx8MPP8x9993H1q1bGTJkCLm5ufTo0YMvvviCn3/+mTvuuINRo0axdu3asx7npZdeomfPnmzcuJHx48dz1113sW3bthprp4iIeJ76upJqc1+n4ZoiUiuczC+kwxOLvXLuLdOGEGKrmZ/bCRMmcN1115XY9tBDD7me33vvvXz11Vd8/PHH9O7du9zjDBs2jPHjxwOOzvSVV15h2bJltGvXrkbaKSIinqe+rqTa3NcpyBMROY/07NmzxOvCwkKeffZZkpOT2b9/P3a7HbvdTmho6FmP07lzZ9dz51CZjIwMt7RZRESkMtTXVZ+CPBGpFYIDLGyZNsRr564pZ3ZoL730Eq+88gozZsygU6dOhIaGMmHCBPLy8s56nDMnsZtMJoqKimqsnSIi4nnq60qqzX2dgjwRqRVMJlONDSPxJStXrmT48OHcfPPNABQVFbF9+3bat2/v5ZaJiIinqa8TJxVecYOsk/ncPvdHbk1aV6OTUEVEztS6dWuWLl3K6tWr2bp1K3feeSfp6enebpbUAh+uTeW299bxWcp+bzdFRPyc+rrKU5DnBkVFBku3HOSbbRkUFinIExH3efzxx+nevTtDhgxhwIABxMbGcs0113i7WVIL/HbwGF9vzWD7wRxvN0VE/Jz6usrzv3yuD7BaTK7nBUUG1poboiwitcSYMWMYM2aM63Xz5s3LHBlQr149Pv3007Mea9myZSVe7969u9Q+KSkplW+k1Go2q+M+cV5h7ZjfIiI1T32d+yiT5wYBluKvNV+dn4iI+KGAUzc08wrUz4mI+BoFeW5gNZ+WySvUcE0REfE/NotjmIoyeSIivkdBnhtYTgvy8mtJmVYREaldXMM1lckTEfE5CvLcwGQyuYaxKJMnIiL+yNnPaVqCiIjvUZDnJlaz46tVkCciIv4oUJk8ERGfpSDPTZwVNjVcU0RE/JGGa4qI+C4FeW7irLCpTJ6IiPgjLaEgIuK7FOS5ibPCpuYqiIiIP3LezFQmT0TE9yjIcxNXJq9ImTwREfE/NosyeSIivkpBnptYXdU11fmJiOcMGDCACRMmuF43b96cGTNmnPUzJpOJTz/9tNrnrqnjyPlBc/JExFvU152bgjw3KR6uqUyeiFTMVVddxWWXXVbme2vWrMFkMrFhw4ZKHXPdunXccccdNdE8lylTptC1a9dS29PS0hg6dGiNnkt8lzOTp2kJIlIZ6us8Q0GemxQP11TnJyIVM3bsWL755hv27NlT6r133nmHrl270r1790ods0GDBoSEhNRUE88qNjaWwMBAj5xLvE+ZPBGpCvV1nqEgz02sWiRWRCrpyiuvJDo6mqSkpBLbT5w4QXJyMtdccw033ngjTZo0ISQkhE6dOjFv3ryzHvPMISzbt2+nf//+BAUF0aFDB5YuXVrqMw8//DAXXHABISEhtGzZkscff5z8/HwAkpKSmDp1Kps2bcJkMmEymVztPXMIy+bNm/nTn/5EcHAwUVFR3HHHHeTk5LjeHzNmDNdccw0vvvgiDRs2JCoqirvvvtt1LvFtCvJEpCrU13mmr7O69ei1mHMxdA3XFPERhgH5J7xz7oAQMJnOuZvVamX06NEkJSXxxBNPYDr1mY8//pi8vDxuu+025s2bx8MPP0xERARffvklo0aNomXLlvTu3fucxy8qKuK6666jfv36fP/992RnZ5eY0+AUHh5OUlISjRo1YvPmzdx+++2Eh4fzt7/9jcTERH7++We++uorvv76awAiIyNLHePEiRNcfvnlxMfHs27dOjIyMrjtttu45557SnTs3377LQ0bNuTbb7/l999/JzExka5du3L77bef83rEu1zVNdXPifgO9XXq605RkOcmAa7CK+r8RHxC/gl4ppF3zv3oAbCFVmjXW2+9lRdeeIFly5Zx6aWXAo7hK9dddx2NGzfmoYcecu1777338tVXX/Hxxx9XqOP7+uuv2bp1K7t376ZJkyYAPPPMM6XmFjz22GOu582bN+fBBx8kOTmZv/3tbwQHBxMWFobVaiU2Nrbcc33wwQecPHmSuXPnEhrquPbXXnuNq666iueee46YmBgA6taty2uvvYbFYqFdu3ZcccUV/O9//1OQdx4ozuQVerklIuKivk593SkarukmmpMnIlXRrl07+vTpwzvvvAPAjh07WLlyJbfeeiuFhYX8/e9/p3PnzkRFRREWFsaSJUtITU2t0LG3bt1Ks2bNXJ0eQEJCQqn9/v3vf3PxxRcTGxtLWFgYjz/+eIXPcfq5unTp4ur0APr27UtRURG//vqra9uFF16IxWJxvW7YsCEZGRmVOtf5YPbs2bRo0YKgoCB69OjBypUrK/S57777DqvVWubk/wULFtChQwcCAwPp0KEDn3zySQ23+uy0hIKIVJX6Ovf3dcrkuYnVouGaIj4lIMRxl9Fb566EsWPHcs899/D666/z7rvvEhcXx8CBA3nhhRd45ZVXmDFjBp06dSI0NJQJEyaQl5dXoeMaRunfI9MZQ2u+//57brjhBqZOncqQIUOIjIxk/vz5vPTSS5W6BsMwSh27rHMGBASUeq/Iz26OJScnM2HCBGbPnk3fvn156623GDp0KFu2bKFZs2blfi4rK4vRo0czcOBADh48WOK9NWvWkJiYyFNPPcW1117LJ598wsiRI1m1alWF7nTXBGcmT/2ciA9RX6e+7hRl8twkwKx18kR8isnkGEbijUcF5iicbuTIkVgsFj788EPee+89/vrXv2IymVi5ciXDhw/n5ptvpkuXLrRs2ZLt27dX+LgdOnQgNTWVAweK/wGwZs2aEvt89913xMXFMXnyZHr27EmbNm1KVUCz2WwUFp59iF6HDh1ISUnh+PHjJY5tNpu54IILKtxmf/Dyyy8zduxYbrvtNtq3b8+MGTNo2rQpb7zxxlk/d+edd3LTTTeVeQd6xowZDBo0iEmTJtGuXTsmTZrEwIEDz7lOVE1yZvIKiwwKixToifgE9XXq605RkOcmruqa6vhEpJLCwsJITEzk0Ucf5cCBA4wZMwaA1q1bs3TpUlavXs3WrVu58847SU9Pr/BxL7vsMtq2bcvo0aPZtGkTK1euZPLkySX2ad26NampqcyfP58dO3Ywa9asUsMAmzdvzq5du0hJSSEzMxO73V7qXH/5y18ICgrilltu4eeff+bbb7/l3nvvZdSoUa45CrVBXl4e69evZ/DgwSW2Dx48mNWrV5f7uXfffZcdO3bw5JNPlvn+mjVrSh1zyJAhZz2m3W4nOzu7xKM6nJk8UIVNEak89XXupSDPTZzDNZXJE5GqGDt2LH/88QeXXXaZa0jf448/Tvfu3RkyZAgDBgwgNjaWa665psLHNJvNfPLJJ9jtdnr16sVtt93G3//+9xL7DB8+nAceeIB77rmHrl27snr1ah5//PES+1x//fVcfvnlXHrppTRo0KDM0tYhISEsXryYI0eOcNFFFzFixAgGDhzIa6+9Vvkv4zyWmZlJYWFhqc4+Jiam3H+0bN++nUceeYQPPvgAq7XsWRXp6emVOibA9OnTiYyMdD2aNm1ayaspSUGeiFSX+jr3MRllDVyt5bKzs4mMjCQrK4uIiIgqHWPC/I18mnKAycPac3v/ljXcQhE5l9zcXHbt2uUqdiH+o7z/tjXx213TDhw4QOPGjVm9enWJYZd///vfef/999m2bVuJ/QsLC4mPj2fs2LGMGzcOgClTpvDpp5+SkpLi2s9ms/Hee+9x4403urZ98MEHjB07ltzc3DLbYrfbS9yJzs7OpmnTplX+vgzDoMWkRQCsm3wZDcJ9f3FgEX+ifs5/ne2/bUX7OhVecRNX4RU/KyAgIiIVV79+fSwWS6kMW0ZGRplDeY4dO8aPP/7Ixo0bueeeewDHmk+GYWC1WlmyZAl/+tOfiI2NrfAxnQIDAwkMrLlAzGQyYbOaySsoUoVNEREfo+GabqJ18kRExGaz0aNHD5YuXVpi+9KlS+nTp0+p/SMiIti8eTMpKSmux7hx42jbti0pKSmuypkJCQmljrlkyZIyj+lOgc5lFDRcU0TEpyiT5yZWs+bkiYgITJw4kVGjRtGzZ08SEhKYM2cOqampruGYkyZNYv/+/cydOxez2UzHjh1LfD46OpqgoKAS2++//3769+/Pc889x/Dhw/nss8/4+uuvWbVqlUevLcBqBjvkq68TEfEpXs/kVWaB2IULFzJo0CAaNGhAREQECQkJLF68uMQ+SUlJmEymUo/y5ii4i6priogIQGJiIjNmzGDatGl07dqVFStWsGjRIuLi4gBIS0ur9AK8ffr0Yf78+bz77rt07tyZpKQkkpOTPbZGnpNNmTwREZ/k1SDPuUDs5MmT2bhxI/369WPo0KHldnYrVqxg0KBBLFq0iPXr13PppZdy1VVXsXHjxhL7RUREkJaWVuLh6QmpAaquKSIip4wfP57du3djt9tZv349/fv3d72XlJTEsmXLyv3slClTShRdcRoxYgTbtm0jLy+PrVu3ct1117mh5WfnrLBpV5AnIuJTvDpc8/QFYsGxuOvixYt54403mD59eqn9z1zk9ZlnnuGzzz7jP//5D926dXNtN5lMxMbGurXt52I9tRh6vubkiXiVCgj7nyIVtPIZzvnnGq4p4j36TfQ/NfHf1GtBnnOB2EceeaTE9nMtEHu6oqIijh07Rr169Upsz8nJIS4ujsLCQrp27cpTTz1VIgg8U1llpavLtU6e/o8n4hUBAQGYTCYOHTpEgwYNMJlM3m6SVJNhGOTl5XHo0CHMZjM2m83bTar1bFYLoOGaIt5gs9kwm80cOHCABg0aYLPZ1Ned52qyn/NakFeVBWLP9NJLL3H8+HFGjhzp2tauXTuSkpLo1KkT2dnZzJw5k759+7Jp0ybatGlT5nGmT5/O1KlTq34xZQgwq7qmiDdZLBaaNGnCvn372L17t7ebIzUoJCSEZs2aYTZ7fVp5reccrqkgT8TzzGYzLVq0IC0tjQMHDni7OVKDaqKf83p1zTPvOBiGUaG7EPPmzWPKlCl89tlnREdHu7bHx8cTHx/vet23b1+6d+/Oq6++yqxZs8o81qRJk5g4caLrtXOB2OpwrZOnIE/Ea8LCwmjTpg35+fneborUEIvFgtVq1d1qH2HTcE0Rr7LZbDRr1oyCggIKCwu93RypATXVz3ktyKvsArGnS05OZuzYsXz88cdcdtllZ93XbDZz0UUXsX379nL3qekFYuG0dfI0XFPEqywWCxaLxdvNEPFLrkyegjwRrzGZTAQEBBAQEODtpogP8dpYl8ouEOs0b948xowZw4cffsgVV1xxzvMYhkFKSgoNGzasdpsrw6rhmiIi4uecSyiouqaIiG/x6nDNyiwQC44Ab/To0cycOZP4+HhXFjA4OJjIyEgApk6dSnx8PG3atCE7O5tZs2aRkpLC66+/7tFrKx6uqY5PRET8k+bkiYj4Jq8GeYmJiRw+fJhp06aRlpZGx44dz7pA7FtvvUVBQQF33303d999t2v7LbfcQlJSEgBHjx7ljjvuID09ncjISLp168aKFSvo1auXR6+teLimMnkiIuKfAnRDU0TEJ3m98Mr48eMZP358me85Azensy0W6/TKK6/wyiuv1EDLqsdqVscnIiL+TZk8ERHfpPrTbmK1aE6eiIj4t0AFeSIiPklBnpsEaDF0ERHxcxquKSLimxTkuYmzuqbWyRMREX/lqq6pIE9ExKcoyHMTZfJERMTfaU6eiIhvUpDnJpqTJyIi/k7DNUVEfJOCPDdRdU0REfF3yuSJiPgmBXluonXyRETE36m6poiIb1KQ5yZW55w8DdcUERE/5czkqciYiIhvUZDnJs5MnoZrioiIv3LOybMrkyci4lMU5LmJJqOLiIi/cy6hkKe+TkTEpyjIcxPnOnkarikiIv6quPBKoZdbIiIip1OQ5yauTJ7WyRMRET9VPGpFNzRFRHyJgjw30Tp5IiLi71RdU0TENynIcxPnOnkFRQaGoUBPRET8j9bJExHxTQry3MRZXRO0Vp6IiPgnFRkTEfFNCvLcxLlOHmjIpoiI+CdnJk9LKIiI+BYFeW7irK4JKr4iIiL+SUsoiIj4JgV5bhKgTJ6IiPg5m9VxQ1PDNUVEfIuCPDexmE2YTiXzCtT5iYiIH7JZLIAKr4iI+BoFeW4UYHauladMnoiI+B9V1xQR8U0K8tyoeK08dX4iIuJ/nEFeQZFBkW5oioj4DAV5buQsvpKvOXkiIuKHTl8uSMVXRER8h4I8N3IWXylQdU0REfFDzkweKMgTEfElCvLcqHi4pjJ5IiLif2ynVZLWvDwREd+hIM+NrM7CK7q7KSIifshkMrmGbKqvExHxHQry3MjZ8RVoMrqIiPgp14LoyuSJiPgMBXluZLUokyciIv5NyyiIiPgeBXlu5KyuqTl5IiLir5xFxlR4RUTEdyjIcyNV1xQREX+nTJ6IiO9RkOdGVovWyRMREf+mIE9ExPcoyHOjgFPVNTVcU0RE/JXNNf9cfZ2IiK9QkOdGrnXyNFxTRET8lCuTV1jo5ZaIiIiTgjw3surupoiI+DktoSAi4nsU5LlRgKu6pjo+ERHxT85Mnl1BnoiIz1CQ50auwitaDF1ERPxUgEatiIj4HAV5buQcrqlMnoiI+CtV1xQR8T0K8tzIZlF1TRER8W/FQZ4Kr4iI+AoFeW5kNTuHa+rupoiI+CctoSAi4nsU5LmRVZk8EREBZs+eTYsWLQgKCqJHjx6sXLmy3H1XrVpF3759iYqKIjg4mHbt2vHKK6+U2CcpKQmTyVTqkZub6+5LKcVVXVNTE0REfIbV2w3wZwEWVdcUEantkpOTmTBhArNnz6Zv37689dZbDB06lC1bttCsWbNS+4eGhnLPPffQuXNnQkNDWbVqFXfeeSehoaHccccdrv0iIiL49ddfS3w2KCjI7ddzJlXXFBHxPQry3MhqPjWERdU1RURqrZdffpmxY8dy2223ATBjxgwWL17MG2+8wfTp00vt361bN7p16+Z63bx5cxYuXMjKlStLBHkmk4nY2Fj3X8A5FFfXVJAnIuIrNFzTjZyZvHzd3RQRqZXy8vJYv349gwcPLrF98ODBrF69ukLH2LhxI6tXr+aSSy4psT0nJ4e4uDiaNGnClVdeycaNG2us3ZWh6poiIr5HmTw3cq6TV6BMnohIrZSZmUlhYSExMTEltsfExJCenn7WzzZp0oRDhw5RUFDAlClTXJlAgHbt2pGUlESnTp3Izs5m5syZ9O3bl02bNtGmTZsyj2e327Hb7a7X2dnZ1biyYgryRER8j4I8N3IN19QQFhGRWs1kMpV4bRhGqW1nWrlyJTk5OXz//fc88sgjtG7dmhtvvBGA+Ph44uPjXfv27duX7t278+qrrzJr1qwyjzd9+nSmTp1azSspLdCqvk5ExNcoyHOj4sIryuSJiNRG9evXx2KxlMraZWRklMrunalFixYAdOrUiYMHDzJlyhRXkHcms9nMRRddxPbt28s93qRJk5g4caLrdXZ2Nk2bNq3opZTL2dcpkyci4js0J8+NnEsoaJ08EZHayWaz0aNHD5YuXVpi+9KlS+nTp0+Fj2MYRomhlmW9n5KSQsOGDcvdJzAwkIiIiBKPmuBcQsGuTJ6IiM9QJs+NnIuhK5MnIlJ7TZw4kVGjRtGzZ08SEhKYM2cOqampjBs3DnBk2Pbv38/cuXMBeP3112nWrBnt2rUDHOvmvfjii9x7772uY06dOpX4+HjatGlDdnY2s2bNIiUlhddff93j12ezWgBl8kREfImCPDdylpUuUCZPRKTWSkxM5PDhw0ybNo20tDQ6duzIokWLiIuLAyAtLY3U1FTX/kVFRUyaNIldu3ZhtVpp1aoVzz77LHfeeadrn6NHj3LHHXeQnp5OZGQk3bp1Y8WKFfTq1cvj1+eqJK1MnoiIzzAZhqE00xmys7OJjIwkKyurWsNZPli7h8mf/MygDjH8Y3TPGmyhiIicqaZ+u2uLmvq+PkvZz/3zU+jTKooPb48/9wdERKTKKvrbrTl5bhRwqrpmge5uioiInwrUEgoiIj5HQZ4baZ08ERHxd86pCRquKSLiOxTkuZFVHZ+IiPg552LodmXyRER8hoI8NwpQdU0REfFzziUU8nRDU0TEZyjIc6PidfIU5ImIiH9yZvI0akVExHcoyHMj15w8dXwiIuKnnHPyVHhFRMR3KMhzo+LqmsrkiYiIf1J1TRER36Mgz42cmbx8LYYuIiJ+qni4pm5oioj4CgV5bhRgUeEVERHxbxquKSLiexTkuZFVi6GLiIifc2by8gqLMAzd1BQR8QUK8tyoeLimOj0REfFPziAPtIyCiIivUJDnRs4hLMrkiYiIv3Kukwealyci4isU5LmRVYuhi4iInzs9yNO8PBER36Agz40CXIuhq9MTERH/ZDabXDc1FeSJiPgGBXluZFV1TRERqQVcNzU1PUFExCcoyHMj15y8IkMVx0RExG85i6/YlckTEfEJCvLcKMBc/PUWqMKmiIj4KdcyCgryRER8goI8N3IO1wQN2RQREf9l03BNERGfoiDPjU4P8lR8RURE/NXpC6KLiIj3KchzoxLDNZXJExERP+XM5Gm4poiIb1CQ50Zms4lTVaW1ILqIiPgtZfJERHyLgjw3s7rWylMmT0RE/FOARevkiYj4EgV5bhZgdq6Vp45PRET8k6prioj4FgV5bubK5GlOnoiI+Cmb1QIoyBMR8RUK8tzMOYRFZaVFRMRf2dTXiYj4FAV5bmY9VWFT1TVFRMRfqfCKiIhv8XqQN3v2bFq0aEFQUBA9evRg5cqV5e67cOFCBg0aRIMGDYiIiCAhIYHFixeX2m/BggV06NCBwMBAOnTowCeffOLOSzgr51p5WidPRET8lZZQEBHxLV4N8pKTk5kwYQKTJ09m48aN9OvXj6FDh5Kamlrm/itWrGDQoEEsWrSI9evXc+mll3LVVVexceNG1z5r1qwhMTGRUaNGsWnTJkaNGsXIkSNZu3atpy6rhACLMnkiIuLfnH2dMnkiIr7BZBiG16KP3r170717d9544w3Xtvbt23PNNdcwffr0Ch3jwgsvJDExkSeeeAKAxMREsrOz+e9//+va5/LLL6du3brMmzevQsfMzs4mMjKSrKwsIiIiKnFFpQ16eTnbM3L48Lbe9Gldv1rHEhGR8tXkb3dtUJPf1+RPNvPB2lQmXNaGCZddUEMtFBGRM1X0t9trmby8vDzWr1/P4MGDS2wfPHgwq1evrtAxioqKOHbsGPXq1XNtW7NmTaljDhkypMLHrGlaJ09ERPydllAQEfEtVm+dODMzk8LCQmJiYkpsj4mJIT09vULHeOmllzh+/DgjR450bUtPT6/0Me12O3a73fU6Ozu7QuevCGd1Ta2TJyIi/soZ5Km6poiIb/B64RWTyVTitWEYpbaVZd68eUyZMoXk5GSio6Ordczp06cTGRnpejRt2rQSV3B2VrOzrLQyeSIi4p9UeEVExLd4LcirX78+FoulVIYtIyOjVCbuTMnJyYwdO5aPPvqIyy67rMR7sbGxlT7mpEmTyMrKcj327t1byaspn3O4ZoGqa4qIiJ+yqfCKiIhP8VqQZ7PZ6NGjB0uXLi2xfenSpfTp06fcz82bN48xY8bw4YcfcsUVV5R6PyEhodQxlyxZctZjBgYGEhERUeJRU4qHayqTJyIi/ql4Tp76OhERX+C1OXkAEydOZNSoUfTs2ZOEhATmzJlDamoq48aNAxwZtv379zN37lzAEeCNHj2amTNnEh8f78rYBQcHExkZCcD9999P//79ee655xg+fDifffYZX3/9NatWrfLKNToXQ9c8BRER8VdaQkFExLd4dU5eYmIiM2bMYNq0aXTt2pUVK1awaNEi4uLiAEhLSyuxZt5bb71FQUEBd999Nw0bNnQ97r//ftc+ffr0Yf78+bz77rt07tyZpKQkkpOT6d27t8evD07L5Km6poiI+KniTF6hl1siIiLg5UwewPjx4xk/fnyZ7yUlJZV4vWzZsgodc8SIEYwYMaKaLasZzkyeqmuKiIi/0hIKIiK+xevVNf2d1aLqmiIi4t+chVfU14mI+AYFeW4WoOqaIiLi55TJExHxLQry3Ezr5ImIiL9zZvLsmpogIuITFOS5mWudPAV5IiLip5yZvHxl8kREfIKCPDcrrq6pjk9ERPyTllAQEfEtCvLcrHidPGXyRETEP2lOnoiIb1GQ52auTJ7uboqIiJ8KdA7XVF8nIuITFOS5WXF1TWXyRETEP7mGayqTJyLiExTkuVnxOnnq+ERExD9puKaIiG9RkOdmAaquKSIifs4V5OmGpoiIT1CQ52audfJUXVNEpNaaPXs2LVq0ICgoiB49erBy5cpy9121ahV9+/YlKiqK4OBg2rVrxyuvvFJqvwULFtChQwcCAwPp0KEDn3zyiTsv4ayc88/zCoswDN3UFBHxNgV5bqZ18kREarfk5GQmTJjA5MmT2bhxI/369WPo0KGkpqaWuX9oaCj33HMPK1asYOvWrTz22GM89thjzJkzx7XPmjVrSExMZNSoUWzatIlRo0YxcuRI1q5d66nLKiHQYgHAMDQHXUTEF5gM3XIrJTs7m8jISLKysoiIiKjWseau2c0Tn/3CsE6xzP5LjxpqoYiInKkmf7trUu/evenevTtvvPGGa1v79u255pprmD59eoWOcd111xEaGsr7778PQGJiItnZ2fz3v/917XP55ZdTt25d5s2bV6Fj1uT3dTKvkPZPfAXAL1OHEBpordbxRESkbBX97VYmz820Tp6ISO2Vl5fH+vXrGTx4cIntgwcPZvXq1RU6xsaNG1m9ejWXXHKJa9uaNWtKHXPIkCEVPmZNcw7XBBUaExHxBbrV5mZWrZMnIlJrZWZmUlhYSExMTIntMTExpKenn/WzTZo04dChQxQUFDBlyhRuu+0213vp6emVPqbdbsdut7teZ2dnV+ZSzspqMWM2QZGhCpsiIr5AmTw3cy2GrjkKIiK1lslkKvHaMIxS2860cuVKfvzxR958801mzJhRahhmZY85ffp0IiMjXY+mTZtW8irOzllh064gT0TE65TJc7Pi4Zrq9EREapv69etjsVhKZdgyMjJKZeLO1KJFCwA6derEwYMHmTJlCjfeeCMAsbGxlT7mpEmTmDhxout1dnZ2jQZ6NouZ3Pwi9XciIj5AmTw3c2XyNCdPRKTWsdls9OjRg6VLl5bYvnTpUvr06VPh4xiGUWKoZUJCQqljLlmy5KzHDAwMJCIiosSjJmmtPBER36FMnpspkyciUrtNnDiRUaNG0bNnTxISEpgzZw6pqamMGzcOcGTY9u/fz9y5cwF4/fXXadasGe3atQMc6+a9+OKL3Hvvva5j3n///fTv35/nnnuO4cOH89lnn/H111+zatUqz1/gKbZTSwZpTp6IiPcpyHMzZ+EVVdcUEamdEhMTOXz4MNOmTSMtLY2OHTuyaNEi4uLiAEhLSyuxZl5RURGTJk1i165dWK1WWrVqxbPPPsudd97p2qdPnz7Mnz+fxx57jMcff5xWrVqRnJxM7969PX59Ts5Mnm5qioh4n9bJK0NNrh303e+Z/OXttVwQE8aSBy459wdERKRKfHWdPF9V09/XoJeXsz0jhw9v702fVvVroIUiInImrZPnI6xmzckTERH/55qTp+GaIiJepyDPzayn5ijkF6nTExER/6UgT0TEdyjIczNV1xQRkdogwHlTU/2diIjXKchzs+Lqmur0RETEfwW6llAo9HJLREREQZ6buTJ5Gq4pIiJ+TEsoiIj4DgV5buack6fhmiIi4s+KF0NXfyci4m0K8tzMWV1T6waJiIg/C1AmT0TEZyjIczNnp1dQpDubIiLiv1RdU0TEdyjIczPrqTl5hUUGWndeRET8lTPI08gVERHvU5DnZgHm4q9YFTZFRMRfqfCKiIjvUJDnZs5MHqjCpoiI+K/iwivq60REvE1BnpudHuQpkyciIv5KmTwREd+hIM/NTh+uWaC7myIi4qdc1TXV14mIeJ2CPDczm02cWkVBFTZFRMRvqbqmiIjvUJDnAc67m6o4JiIi/kpBnoiI71CQ5wGutfI0J09ERPyU7dQcdN3QFBHxPgV5HuAsvqLqmiIi4q+UyRMR8R0K8jzAanYO11QmT0RE/JOWUBAR8R0K8jwgwJnJU5AnIiJ+ymaxAMrkiYj4AgV5HuAcrpmv4ZoiIuKnnDc0lckTEfE+BXke4FwrT5k8ERHxV5qTJyLiOxTkeYCr8IruboqIiJ9yBnmqriki4n0K8jzAVXhFi6GLiIifslmUyRMR8RUK8jwgQJk8ERHxcxquKSLiOxTkeYDVoiUURETEvxUvoaC+TkTE2xTkeYDVrMXQRUTEvwW4hmsWerklIiKiIM8DnB2fqmuKiIi/cs3J09QEERGvU5DnAa518tTxiYiInwrUnDwREZ+hIM8DnNU1C1RdU0RE/JRzTl6RAYXq70REvEpBngcEKJMnIiJ+zjk1AZTNExHxNgV5HqDqmiIi4u+cmTxQkCci4m0K8jwgwKx18kRExL9ZzSZMju5OxVdERLxMQZ4HOAuvaE6eiIj4K5PJVLyMgoI8ERGvUpDnAcXDNdXpiYiI/wq0qMKmiIgvUJDnAcXDNZXJExER/+Wcl6ebmiIi3qUgzwNcmbwidXoiIuK/ApTJExHxCQryPMA1J0+ZPBER8WPOTJ5dQZ6IiFcpyPOAAOdi6Bq+IiIifkzDNUVEfIOCPA9wZvLyVV1TRET8mIZrioj4BgV5HuDs9JTJExERf+bM5CnIExHxLgV5HmBVdU0REakFArVOnoiIT1CQ5wHF1TUV5ImIiP/SnDwREd+gIM8DbK7qmur0RETEfwWc6u9UXVNExLsU5HmAK5On4ZoiIuLHNCdPRMQ3KMjzANecPC2GLiIifsxmtQAariki4m0K8jyguLqmMnkiIuK/nMM1lckTEfEuBXke4FonT3c2RUTEjwVquKaIiE9QkOcBVvOpTJ6qa4qIiB+zWVRdU0TEFyjI84AAVdcUEanVZs+eTYsWLQgKCqJHjx6sXLmy3H0XLlzIoEGDaNCgARERESQkJLB48eIS+yQlJWEymUo9cnNz3X0pZ+WcnmBXfyci4lUK8jxA1TVFRGqv5ORkJkyYwOTJk9m4cSP9+vVj6NChpKamlrn/ihUrGDRoEIsWLWL9+vVceumlXHXVVWzcuLHEfhEREaSlpZV4BAUFeeKSyqXqmiIivsHq7QbUBgGqrikiUmu9/PLLjB07lttuuw2AGTNmsHjxYt544w2mT59eav8ZM2aUeP3MM8/w2Wef8Z///Idu3bq5tptMJmJjY93a9srSYugiIr5BmTwPsKq6pohIrZSXl8f69esZPHhwie2DBw9m9erVFTpGUVERx44do169eiW25+TkEBcXR5MmTbjyyitLZfrOZLfbyc7OLvGoac7hmsrkiYh4l4I8D3BV11QmT0SkVsnMzKSwsJCYmJgS22NiYkhPT6/QMV566SWOHz/OyJEjXdvatWtHUlISn3/+OfPmzSMoKIi+ffuyffv2co8zffp0IiMjXY+mTZtW7aLOQtU1RUR8g4I8DwgwK5MnIlKbmUymEq8Nwyi1rSzz5s1jypQpJCcnEx0d7doeHx/PzTffTJcuXejXrx8fffQRF1xwAa+++mq5x5o0aRJZWVmux969e6t+QeVwzcnTcE0REa/SnDwPKF4nT0GeiEhtUr9+fSwWS6msXUZGRqns3pmSk5MZO3YsH3/8MZdddtlZ9zWbzVx00UVnzeQFBgYSGBhY8cZXgc01XFP9nYiIN3k9k1eZstJpaWncdNNNtG3bFrPZzIQJE0rt44tlpV1LKGi4pohIrWKz2ejRowdLly4tsX3p0qX06dOn3M/NmzePMWPG8OGHH3LFFVec8zyGYZCSkkLDhg2r3ebqcM3JUyZPRMSrvBrkVbastN1up0GDBkyePJkuXbqUe1xfKytt1XBNEZFaa+LEibz99tu88847bN26lQceeIDU1FTGjRsHOIZRjh492rX/vHnzGD16NC+99BLx8fGkp6eTnp5OVlaWa5+pU6eyePFidu7cSUpKCmPHjiUlJcV1TG8pXkKh0KvtEBGp7bw6XLOyZaWbN2/OzJkzAXjnnXfKPa6vlZUuHq6pO5siIrVNYmIihw8fZtq0aaSlpdGxY0cWLVpEXFwc4BilcvrNzbfeeouCggLuvvtu7r77btf2W265haSkJACOHj3KHXfcQXp6OpGRkXTr1o0VK1bQq1cvj17bmYqXUNBNTRERb/JakOcsK/3II4+U2F6ZstLlcZaVLiwspGvXrjz11FMl1hY6k91ux263u17XdFlp5/CVgiJ1eiIitdH48eMZP358me85AzenZcuWnfN4r7zyCq+88koNtKxm2bSEgoiIT/DacM2aKCtdFl8sK209tRh6YZGBYSjQExER/2TTEgoiIj7B64VXqlpWujy+WFbauRg6aAiLiIj4r+LhmgryRES8yWvDNatTVroyfKGstLO6Jjg6PmcnKCIi4k+c0xPsyuSJiHiV16KNqpaVrixfKCvtrK4JqrApIiL+y6YlFEREfIJXq2tOnDiRUaNG0bNnTxISEpgzZ06pstL79+9n7ty5rs+kpKQAjuIqhw4dIiUlBZvNRocOHQBHWen4+HjatGlDdnY2s2bNIiUlhddff93j1+dUIpOntfJERMRPabimiIhv8GqQV9my0kCJKpnr16/nww8/JC4ujt27dwO+WVbaZDJhMZsoLDKUyRMREb8VqMIrIiI+watBHlSurDRwzuqUvlpW2noqyNPdTRER8VcBWkJBRMQnqAKIh2itPBER8XfO4ZoFRQZF6u9ERLxGQZ6HWE/NyytQJk9ERPzU6dWjVXxFRMR7FOR5iLPCptbJExERf3V6oTEFeSIi3qMgz0OcHV+BqmuKiIifci6hAJqXJyLiTQryPMQ5J0+ZPBER8Vcmk8kV6KnQmIiI9yjI8xDNyRMRkdrAOXJFmTwREe9RkOchAWZV1xQREf9n01p5IiJepyDPQ5yZPA1fERERf+YK8tTfiYh4jYI8D7E618nTnDwREfFjWhBdRMT7qhTk7d27l3379rle//DDD0yYMIE5c+bUWMP8TYBZ1TVFRM4HP/zwA4WFha7XhlHy5pzdbuejjz7ydLPOGxquKSLifVUK8m666Sa+/fZbANLT0xk0aBA//PADjz76KNOmTavRBvqL4uGayuSJiPiyhIQEDh8+7HodGRnJzp07Xa+PHj3KjTfe6I2mnRdsqiYtIuJ1VQryfv75Z3r16gXARx99RMeOHVm9ejUffvghSUlJNdk+v+EcvqJMnoiIbzszc3fm6/K2iUOga05e4Tn2FBERd6lSkJefn09gYCAAX3/9NVdffTUA7dq1Iy0treZa50esZmXyRET8hclk8nYTfJbm5ImIeF+VgrwLL7yQN998k5UrV7J06VIuv/xyAA4cOEBUVFSNNtBfqPCKiIjUBs45eXYFeSIiXmOtyoeee+45rr32Wl544QVuueUWunTpAsDnn3/uGsYpJTkXh9VwTRER37dlyxbS09MBx9DMbdu2kZOTA0BmZqY3m+bznEGeRq6IiHhPlYK8AQMGkJmZSXZ2NnXr1nVtv+OOOwgJCamxxvkTq1mdnojI+WLgwIEl5t1deeWVgGOYpmEYGq55FhquKSLifVUK8k6ePIlhGK4Ab8+ePXzyySe0b9+eIUOG1GgD/YWzumaBFocVEfFpu3bt8nYTzmvFSyio8IqIiLdUKcgbPnw41113HePGjePo0aP07t2bgIAAMjMzefnll7nrrrtqup3nvQCzs7qmMnkiIr4sLi7unPukpKRUaL/aKFBLKIiIeF2VCq9s2LCBfv36AfDvf/+bmJgY9uzZw9y5c5k1a1aNNtBfFK+Tp0yeiMj5KCsri9mzZ9O9e3d69Ojh7eb4LNdwTfV3IiJeU6Ug78SJE4SHhwOwZMkSrrvuOsxmM/Hx8ezZs6dGG+gvAlRdU0TkvPTNN99w880307BhQ1599VWGDRvGjz/+6O1m+SxV1xQR8b4qDdds3bo1n376Kddeey2LFy/mgQceACAjI4OIiIgabaC/cK2Tp+qaIiI+b9++fSQlJfHOO+9w/PhxRo4cSX5+PgsWLKBDhw7ebp5PK66uqf5ORMRbqpTJe+KJJ3jooYdo3rw5vXr1IiEhAXBk9bp161ajDfQXWidPROT8MGzYMDp06MCWLVt49dVXOXDgAK+++qq3m3XeKC68oiBPRMRbqpTJGzFiBBdffDFpaWmuNfLAUXL62muvrbHG+ZMAVdcUETkvLFmyhPvuu4+77rqLNm3aeLs55x0toSAi4n1VyuQBxMbG0q1bNw4cOMD+/fsB6NWrF+3atauxxvkT1zp5qq4pIuLTVq5cybFjx+jZsye9e/fmtdde49ChQ95u1nkjUMM1RUS8rkpBXlFREdOmTSMyMpK4uDiaNWtGnTp1eOqppyjSnLMyaZ08EZHzQ0JCAv/4xz9IS0vjzjvvZP78+TRu3JiioiKWLl3KsWPHvN1En2ZTJk9ExOuqFORNnjyZ1157jWeffZaNGzeyYcMGnnnmGV599VUef/zxmm6jXygerqlMnojI+SAkJIRbb72VVatWsXnzZh588EGeffZZoqOjufrqq73dPJ/l7O/suqkpIuI1VQry3nvvPd5++23uuusuOnfuTJcuXRg/fjz/+Mc/SEpKquEm+gcN1xQROX+1bduW559/nn379jF//nxMJpO3m+SzbFYLoEyeiIg3VanwypEjR8qce9euXTuOHDlS7Ub5I+edzXx1eiIiPu3WW2895z5RUVEeaMn5SUsoiIh4X5WCvC5duvDaa68xa9asEttfe+01OnfuXCMN8zeuJRQ0Z1FExKclJSURFxdHt27dMIyyR18ok1c+501NZfJERLynSkHe888/zxVXXMHXX39NQkICJpOJ1atXs3fvXhYtWlTTbfQLrsXQNSdPRMSnjRs3jvnz57Nz505uvfVWbr75ZurVq+ftZp03ArVOnoiI11VpTt4ll1zCb7/9xrXXXsvRo0c5cuQI1113Hb/88gvvvvtuTbfRLwQokycicl6YPXs2aWlpPPzww/znP/+hadOmjBw5ksWLF5eb2ZNiGq4pIuJ9VcrkATRq1Ii///3vJbZt2rSJ9957j3feeafaDfM3ziUUlMkTEfF9gYGB3Hjjjdx4443s2bOHpKQkxo8fT35+Plu2bCEsLMzbTfRZzpuadmXyRES8psqLoUvluDJ5urMpInJeMZlMmEwmDMPQWrAV4FonT/2diIjXKMjzENc6eVpCQUTE59ntdubNm8egQYNo27Ytmzdv5rXXXiM1NVVZvHPQcE0REe+r8nBNqRzXOnkariki4tPGjx/P/PnzadasGX/961+ZP3++lkyoBJsKr4iIeF2lgrzrrrvurO8fPXq0Om3xa845eRquKSLi2958802aNWtGixYtWL58OcuXLy9zv4ULF3q4ZecH13BNBXkiIl5TqSAvMjLynO+PHj26Wg3yV8XVNZXJExHxZaNHj9Y6eNWgTJ6IiPdVKsjT8ghVV7xOnjo9ERFflpSU5O0mnNeK5+TppqaIiLeo8IqHFFfXVKcnIiL+K+C06ppaV1BExDsU5HmIa06eym+LiIgfc2byQMsoiIh4i4I8D1F1TRGR2mv27Nm0aNGCoKAgevTowcqVK8vdd+HChQwaNIgGDRoQERFBQkICixcvLrXfggUL6NChA4GBgXTo0IFPPvnEnZdQYc7CK6A+T0TEWxTkeUiAqmuKiNRKycnJTJgwgcmTJ7Nx40b69evH0KFDSU1NLXP/FStWMGjQIBYtWsT69eu59NJLueqqq9i4caNrnzVr1pCYmMioUaPYtGkTo0aNYuTIkaxdu9ZTl1Wu04M8FV8REfEOk6EB86VkZ2cTGRlJVlYWERERNXLM/UdP0vfZb7BZzfz29NAaOaaIiBRzx293Tejduzfdu3fnjTfecG1r374911xzDdOnT6/QMS688EISExN54oknAEhMTCQ7O5v//ve/rn0uv/xy6taty7x58yp0THd+X60fXURBkcH3kwYSGxlUo8cWEanNKvrbrUyehwSYlckTEalt8vLyWL9+PYMHDy6xffDgwaxevbpCxygqKuLYsWPUq1fPtW3NmjWljjlkyJAKH9Pdiitsqs8TEfGGSi2hIFVnPTV8pciAoiIDs1lrMImI+LvMzEwKCwuJiYkpsT0mJob09PQKHeOll17i+PHjjBw50rUtPT290se02+3Y7XbX6+zs7AqdvyocFTYLsWu4poiIVyiT5yHO6poA+aqwKSJSq5y5uLphGBVacH3evHlMmTKF5ORkoqOjq3XM6dOnExkZ6Xo0bdq0EldQOVoQXUTEuxTkeUiAufir1lp5IiK1Q/369bFYLKUybBkZGaUycWdKTk5m7NixfPTRR1x22WUl3ouNja30MSdNmkRWVpbrsXfv3kpeTcU5i69ouKaIiHcoyPOQ0zN5CvJERGoHm81Gjx49WLp0aYntS5cupU+fPuV+bt68eYwZM4YPP/yQK664otT7CQkJpY65ZMmSsx4zMDCQiIiIEg93CbQWL4guIiKepzl5HmI1a7imiEhtNHHiREaNGkXPnj1JSEhgzpw5pKamMm7cOMCRYdu/fz9z584FHAHe6NGjmTlzJvHx8a6MXXBwMJGRkQDcf//99O/fn+eee47hw4fz2Wef8fXXX7Nq1SrvXOQZAiwariki4k3K5HmIyWRyBXrK5ImI1B6JiYnMmDGDadOm0bVrV1asWMGiRYuIi4sDIC0trcSaeW+99RYFBQXcfffdNGzY0PW4//77Xfv06dOH+fPn8+6779K5c2eSkpJITk6md+/eHr++smhOnoiIdymT50FWi4mCIkNzFEREapnx48czfvz4Mt9LSkoq8XrZsmUVOuaIESMYMWJENVvmHjYN1xQR8Spl8jzIWXyloEiZPBER8V8Bp+ahK5MnIuIdCvI8yFl8RQuii4iIP7NZLYCCPBERb1GQ50FWV0lpZfJERMR/aQkFERHvUpDnQQHOwiuqrikiIn7MZj01XFNBnoiIVyjI8yBl8kREpDawaQkFERGvUpDnQZqTJyIitYGqa4qIeJeCPA9SdU0REakNtE6eiIh3KcjzIGcmTxPRRUTEnwVouKaIiFcpyPMgzckTEZHawJnJ001NERHvUJDnQTbNyRMRkVogUJk8ERGvUpDnQdZTc/LyNSdPRET8mGu4pm5qioh4hYI8D1J1TRERqQ2cwzXtyuSJiHiFgjwPct7ZLNCcPBER8WPFc/LU34mIeIOCPA+ymk9V1yzSnU0REfFfxdU1C73cEhGR2klBngcpkyciIrWB1skTEfEuBXkepHXyRETEbxgGnDgCuVml3grUcE0REa9SkOdBzuqaBaquKSIi57vP7oHnW8C6t0u95Ry5YtdwTRERr1CQ50EBqq4pIiL+IrS+42/OoVJvRYcHAnDgaK4nWyQiIqcoyPOg4uGayuSJiMh5Liza8TfnYKm3WjUIA2D/0ZOczFM2T0TE0xTkeVDxcE1l8kRE5DwXeirIO146k1c31Ea9UBsAOzNzPNkqERFBQZ5HFQ/XVCZPRETOc2fJ5AG0ahAKwI5Dxz3VIhEROUVBngdZLao2JiIifsIV5GWU+bZzyOaODGXyREQ8TUGeBwWcWgxdwzVFROS8Fxbj+Jt7FArspd52BXmHFOSJiHiagjwPUiZPRET8RlAdMFsdz8uYl9cqWsM1RUS8xetB3uzZs2nRogVBQUH06NGDlStXlrtvWloaN910E23btsVsNjNhwoQy91uwYAEdOnQgMDCQDh068Mknn7ip9ZVj1RIKIiLiL8xmCG3geF7GkE1nJm/noRyKtD6siIhHeTXIS05OZsKECUyePJmNGzfSr18/hg4dSmpqapn72+12GjRowOTJk+nSpUuZ+6xZs4bExERGjRrFpk2bGDVqFCNHjmTt2rXuvJQKCdBi6CIi4k/OMi+vSd0QbBYz9oIi9h896eGGiYjUbl4N8l5++WXGjh3LbbfdRvv27ZkxYwZNmzbljTfeKHP/5s2bM3PmTEaPHk1kZGSZ+8yYMYNBgwYxadIk2rVrx6RJkxg4cCAzZsxw45VUTPE6ecrkiYiIH3Ato1A6yLOYTTSvHwJoXp6IiKd5LcjLy8tj/fr1DB48uMT2wYMHs3r16iofd82aNaWOOWTIkGods6Y45+RpCQUREfELzuIr56qwqXl5IiIeZfXWiTMzMyksLCQmJqbE9piYGNLT06t83PT09Eof0263Y7cXVwbLzs6u8vnPRtU1RUTEr4SVPycPSs7LExERz/F64RWTyVTitWEYpba5+5jTp08nMjLS9WjatGm1zl8eVdcUERG/4szklTFcE06vsKkgT0TEk7wW5NWvXx+LxVIqw5aRkVEqE1cZsbGxlT7mpEmTyMrKcj327t1b5fOfTYBFmTwREfEjZ6muCRquKSLiLV4L8mw2Gz169GDp0qUlti9dupQ+ffpU+bgJCQmljrlkyZKzHjMwMJCIiIgSD3ewmpXJExERP3KW6poALU8FeYeO2ck6me+pVomI1Hpem5MHMHHiREaNGkXPnj1JSEhgzpw5pKamMm7cOMCRYdu/fz9z5851fSYlJQWAnJwcDh06REpKCjabjQ4dOgBw//33079/f5577jmGDx/OZ599xtdff82qVas8fn1n0jp5IiLiV85ReCUs0EpsRBDp2bnsPJRDt2Z1Pdg4EZHay6tBXmJiIocPH2batGmkpaXRsWNHFi1aRFxcHOBY/PzMNfO6devmer5+/Xo+/PBD4uLi2L17NwB9+vRh/vz5PPbYYzz++OO0atWK5ORkevfu7bHrKk/xcE1l8kRExA84h2vasyA/FwKCSu3SKjqU9Oxcdhw6riBPRMRDvBrkAYwfP57x48eX+V5SUlKpbYZx7gBpxIgRjBgxorpNq3EarikiIn4luC6YA6AoH44fgjqlC5e1ahDGd78fVvEVEREP8np1zdpEwzVFRMSvmEznnJfnKr6SoSBPRMRTFOR5UIBzMXQN1xQREX/hDPLKW0bBVWFTQZ6IiKcoyPMg66nF0POVyRMREX8R6szkHSzz7ZYNHGvl7Tl8Qv2fiIiHKMjzIFcmT3PyRETEX4Q518o7VObbsRFBhNgsFBQZpB454cGGiYjUXgryPKh4uKbuZIqIiJ9wLqNQznBNs9nkyuZpXp6IiGcoyPMgZ+GVvAIFeSIi4ifOMVwTiufl7cw87okWiYjUegryPCjArMIrIiLiZ1zVNcsergmqsCki4mkK8jyoeAkFBXkiIuInwiqeyVOFTRERz1CQ50HOIC9fc/JERMRfOIdrHj9LJi/61Jy8Q8cxDN3oFBFxNwV5HuQcrmkYUKghmyIi4g+cmTx7NuSfLHOX5lGhmEyQdTKfw8fzPNg4EZHaSUGeBzkzeaC18kRExE8ERYLF5nieU3aFzaAAC03rhgCalyci4gkK8jzIuYQCqPiKiIj4CZPptGUUzlZ8pXjIpoiIuJeCPA+ymoszeQXK5ImIiL8IdS6IruIrIiK+QEGeB1nMpw/XVCZPRKS2mD17Ni1atCAoKIgePXqwcuXKcvdNS0vjpptuom3btpjNZiZMmFBqn6SkJEwmU6lHbm6uG6/iLJyZvHKGawK0VJAnIuIxCvI8yGQyEeBcRkEVNkVEaoXk5GQmTJjA5MmT2bhxI/369WPo0KGkpqaWub/dbqdBgwZMnjyZLl26lHvciIgI0tLSSjyCgoLcdRlnF3Yqk1eh4ZoK8kRE3E1BnodZnQuiK5MnIlIrvPzyy4wdO5bbbruN9u3bM2PGDJo2bcobb7xR5v7Nmzdn5syZjB49msjIyHKPazKZiI2NLfHwmtAKrJUX7cjk7fvjJLn5hZ5olYhIraUgz8Nca+VpTp6IiN/Ly8tj/fr1DB48uMT2wYMHs3r16modOycnh7i4OJo0acKVV17Jxo0bz7q/3W4nOzu7xKPGVGC4ZlSojcjgAAwDdmWq+IqIiDspyPMwZ4VNVdcUEfF/mZmZFBYWEhMTU2J7TEwM6enpVT5uu3btSEpK4vPPP2fevHkEBQXRt29ftm/fXu5npk+fTmRkpOvRtGnTKp+/FOdwzbMEeSaTyTVkc6cqbIqIuJWCPA9zVthUJk9EpPYwmUwlXhuGUWpbZcTHx3PzzTfTpUsX+vXrx0cffcQFF1zAq6++Wu5nJk2aRFZWluuxd+/eKp+/FNcSCuUHeaAKmyIinmL1dgNqG1cmT3PyRET8Xv369bFYLKWydhkZGaWye9VhNpu56KKLzprJCwwMJDAwsMbOWYJrTl75hVegeF6egjwREfdSJs/DrKquKSJSa9hsNnr06MHSpUtLbF+6dCl9+vSpsfMYhkFKSgoNGzassWNWStipIC/vGOSdKHc3ZfJERDxDmTwPKx6uqUyeiEhtMHHiREaNGkXPnj1JSEhgzpw5pKamMm7cOMAxjHL//v3MnTvX9ZmUlBTAUVzl0KFDpKSkYLPZ6NChAwBTp04lPj6eNm3akJ2dzaxZs0hJSeH111/3+PUBEBgO1iAoyHUM2bQ1L3M31zIKGccpKjIwm6s+ZFVERMqnIM/DNFxTRKR2SUxM5PDhw0ybNo20tDQ6duzIokWLiIuLAxyLn5+5Zl63bt1cz9evX8+HH35IXFwcu3fvBuDo0aPccccdpKenExkZSbdu3VixYgW9evXy2HWVYDI5hmxmpTqKr9RtXuZuTeuFEGAxcTK/kPTsXBrVCfZsO0VEagkFeR7mWkJBwzVFRGqN8ePHM378+DLfS0pKKrXNMM5+I/CVV17hlVdeqYmm1Zyw04K8cgRYzMRFhfJ7Rg47DuUoyBMRcRPNyfMwLYYuIiJ+yTkv75wVNp1DNjUvT0TEXRTkeViAs/CKllAQERF/4gzyzpLJA2jpKr6itfJERNxFQZ6HOTN5+VoMXURE/EloxYI8VdgUEXE/BXkeZlUmT0RE/JErk3fwrLu5hmsqyBMRcRsFeR6m6poiIuKXXHPyzr0guskEB7Pt7M7UkE0REXdQkOdhrnXyVF1TRET8SQWHa0YEBdC/TQMAPl6/192tEhGplRTkeZgyeSIi4pcqWHgF4IaLmgLw8Y/7NH1BRMQNFOR5mLO6Zr46NRER8SfOIC//ONjPPt9uYPsYokJtZByzs+zXsw/vFBGRylOQ52FWZyZP1TVFRMSf2MIgIMTx/Bxr5dmsZq7v0QSA+es0ZFNEpKYpyPMwrZMnIiJ+yWSCUMdcO3LOnZ0b2dMxZPPbXzPIyM51Z8tERGodBXke5lonT3PyRETE37gqbJ57Xl7r6DB6xtWlsMjg3xv2ublhIiK1i4I8D3Otk6fqmiIi4m/CYhx/z7FWnlPiqQIsyev2Yhi6+SkiUlMU5HmYqmuKiIjfqsRwTYArOjckLNDKnsMn+H7nETc2TESkdlGQ52HOdfLyNCdPRET8TSUzeSE2K1d1aQRA8rpUd7VKRKTWUZDnYVZl8kRExF+FncrkHa/4sgjONfMW/ZxO1ol8d7RKRKTWUZDnYQFmzckTERE/5crknbvwilPnJpG0iw0nr6CIzzbtd1PDRERqFwV5HubM5Km6poiI+J3QU9U1KzhcE8BkMrkKsMz7QQVYRERqgoI8D9M6eSIi4rdOH65ZiWDt2m6NsVnNbE3L5uf92W5qnIhI7aEgz8OchVfyi3SnUkRE/Iwzk5d/AvJyKvyxOiE2Lr8wFoD5KsAiIlJtCvI8rLjwijJ5IiLiZwLDICDU8bwS8/KgeM28z1MOcDKvsKZbJiJSqyjI87Di4ZrK5ImIiB8KO5XNq0SFTYCEllE0rRfMMXsBizanuaFhIiK1h4I8D7OaTxVe0XBNERHxR2GVL74CYDabSOzpyOYlr9tb060SEalVFOR5mFWFV0RExJ+5grzKDdcEGNGjKWYT/LD7CL8dPFbDDRMRqT0U5HlYgBZDFxERfxZa9SAvNjKIQR0ca+09/9WvNdkqEZFaRUGehxVX11QmT0RE/JBrTl7lgzyA/xvSDovZxNdbD7L698wabJiISO2hIM/DlMkTERG/5hquWbnCK06to8O4uXczAJ7+ciuFmsMuIlJpCvI8zDknL19z8kRExB+FVq3wyunuv+wCwoOsbEnLZsGGfTXUMBGR2kNBnoc5q2sW6M6kiIj4ozDHnLqqDtcEqBdq494/tQbgxcW/ctxeUBMtExGpNRTkeViAqmuKiIg/C2vg+JuTAUbVb2je0qc5TesFk3HMzlsrdtZQ40REagcFeR5mPTUnL19z8kRExB85h2sW5IK96ssgBFotTBraHoA5K3aQlnWyJlonIlIrKMjzMGd1zQJV1xQREX9kCwFbuOP58aoVX3Ea2jGWnnF1yc0v4oXFWlJBRKSiFOR5mKprioiI33MN2ax68RUAk8nEY1d2AGDhhv1s3pdV3ZaJiNQKCvI8TNU1RUTE7zmLr1RhQfQzdW1ah2u6NgLg6S+3YFRjnp+ISG2hIM/DAlRdU0RE/F3oacVXasD/Xd6OQKuZtbuOsGTLGdnBoiLHmnxpP8HvX8OJIzVyThGR85nV2w2obayu6poK8kRExE/VwDIKp2tcJ5jb+7Xkg283cPjTSRRtLsCckwbH0h2Povzineu3hTu+BVtojZxbROR8pCDPw5xz8vJVeEVERPxVmHNB9JoJ8gDGXdKSS76/lYvyf4ZtZ75rcmQP809A5q/w1SS4elaNnVtE5HyjIM/DnOvkGQYUFhlYTlXbFBER8Rs1PFwTIGzbx1xk/MxJw8ZLRTcwZujFNGnWCsJjHZlDSwDsXA5zh8OG96DVpXDhtTV2fhGR84nm5HmYc508UPEVERHxU3WaOv4e2AiFBdU/3vHDsHgyAF/WG83b+Zdz+7pG2GO7QWQTR4AH0PIS6DfR8fzz++FoavXPLSJyHlKQ52HW0zJ3Kr4iIiJ+qXl/CImCnHRHMZTqWvIYnDwC0RdyyS1TqRdqY2taNq8s3V563wGToMlFYM+CBbfVTJApInKeUZDnYQGnZfIKlMkTERF/ZLVBlxsdzze8V71j7VwOmz4ETHDVTBrUCeOZazsB8NaKHazbfUY1TUsAXP82BEbA3rWw/LnqnV9E5DykIM/DLGYTplPJvHxV2BQREX/VfbTj72+LITutasfIz4UvHnA8v2gsNL0IgMs7xnJ99yYYBkz8KIUc+xnZurrN4aoZjucrXoBdK6t2fhGR85SCPC8oXitPmTwREfFTDdpCswQwCk9l4qpg5UtwZAeExcLAJ0q89eTVHWhcJ5i9R07y9BdbSn+24/XQ7WbAgIV3aP08EalVFOR5gdbKExGRWsGZzdvwvmPR8so49CusesXxfOhzEBRZ4u2IoABe/HMXTCaYv24vX5+5SDrA0Ochqg0cOwCf3e0obS0iUgsoyPMCZ/EVVdcUERG/1mG4Y27cH7tgz6qKf66oCP4zwbHI+QWXO45ThoRWUdx2cQsAHln4E4dz7CV3sIXCiHfAYoNfF8G6t6t4ISIi5xcFeV7gLL6i6poiIuLXbKHQaYTj+Ya5Ff9cyr8gdTUEhMCwF3BNZi/Dg4Pb0jYmnMycPCYt3IxxZrauYWcY9JTj+ZLHqj4/UETkPKIgzwucwzXzCpTJExERP+ccsrnl84rNi8s5BEsedzy/dDLUaXbW3YMCLLyc2IUAi4klWw7y8fp9pXfqfSc0jYeCXPhuRuXaLyJyHlKQ5wVWszJ5IiJSSzTsCrGdoNAOP3109n0NA76cCLlHIbYz9B5XoVNc2CiSCZddAMDjn/7Mpr1HS+5gMsGARxzP1yfBsfTKXIGIyHlHQZ4XBLgKryiTJyJSG8yePZsWLVoQFBREjx49WLmy/JL+aWlp3HTTTbRt2xaz2cyECRPK3G/BggV06NCBwMBAOnTowCeffOKm1leTyQTdb3E83/De2YufrHoZtn4OZitcNRMs1gqfZtwlrbi0bQPsBUXcPvdH0rJOltyh5YDTsnkzK38dIiLnEQV5XmA9NSdP6+SJiPi/5ORkJkyYwOTJk9m4cSP9+vVj6NChpKamlrm/3W6nQYMGTJ48mS5dupS5z5o1a0hMTGTUqFFs2rSJUaNGMXLkSNauXevOS6m6Tn8GaxBkbIH9G8reZ9si+N+puXPDXoDG3St1CovZxKwbu3FBTBgZx+zc9t6PnMg7bf08kwkGPOx4/uM7cKyMapwiIn5CQZ4XBAU4vvZSi7eKiIjfefnllxk7diy33XYb7du3Z8aMGTRt2pQ33nijzP2bN2/OzJkzGT16NJGRkWXuM2PGDAYNGsSkSZNo164dkyZNYuDAgcyYMcONV1INwXWgwzWO5xveK/3+wS2w8HbAgItug563Vuk04UEB/POWi6gXauOXA9lMTN5E0elTI1peCk16ObJ5q2dV6RwiIucDBXlecEFMOAC/HMjycktERMSd8vLyWL9+PYMHDy6xffDgwaxevbrKx12zZk2pYw4ZMuSsx7Tb7WRnZ5d4eJSzAMvPC8CeU7z9xBGYdwPk5UDzfnD5s9U6TdN6IcwZ1QObxcxXv6Tz0tJfi988PZu37p+Qk1Gtc4mI+CoFeV7QubHjzuzmfQryRET8WWZmJoWFhcTExJTYHhMTQ3p61Yt/pKenV/qY06dPJzIy0vVo2rRplc9fJXF9oF4rRzD3y0LHtsJ8+Gg0HN0DdeJg5FywBFT7VD2b12P6dZ0AeP3bHSzccFrFzVYDoXFPKDipuXki4re8HuRVZjI6wPLly+nRowdBQUG0bNmSN998s8T7SUlJmEymUo/c3Fx3XkaldGpSB4Cf9meVXs9HRET8jumMdd4Mwyi1zd3HnDRpEllZWa7H3r17q3X+SjOZirN5zjXzvnoEdq8EWxjclAwh9WrsdNf3aMJdA1oB8MiCzazfc6S4Hc5Km+v+6ViyQUTEz3g1yKvsZPRdu3YxbNgw+vXrx8aNG3n00Ue57777WLBgQYn9IiIiSEtLK/EICgryxCVVSIeGEVjMJg4ds3Mw2+7t5oiIiJvUr18fi8VSKsOWkZFRKhNXGbGxsZU+ZmBgIBERESUeHtf1JkflzH3r4L+PwLq3ARNc/zZEt6/x0/3f4LYMuTCGvMIi7pi7nr1HTjjeaH0ZNOruyOZpbp6I+CGvBnmVnYz+5ptv0qxZM2bMmEH79u257bbbuPXWW3nxxRdL7GcymYiNjS3x8CXBNgttosMA+GnfUe82RkRE3MZms9GjRw+WLl1aYvvSpUvp06dPlY+bkJBQ6phLliyp1jE9Iiwa2g51PF97qq8f+HjxthpmNpt4JbErFzaK4PDxPMa+t44jx/POyOa9Dccz3XJ+ERFv8VqQV5XJ6OVNNP/xxx/Jz893bcvJySEuLo4mTZpw5ZVXsnHjxrO2xRuT0Ts3OTUvb7/m5YmI+LOJEyfy9ttv884777B161YeeOABUlNTGTfOsdD3pEmTGD16dInPpKSkkJKSQk5ODocOHSIlJYUtW7a43r///vtZsmQJzz33HNu2beO5557j66+/LndNPZ/iXDMPoOMIuHiiW08XYrPy9i09iQ4P5LeDOfzl7bX8cTwP2gyGRt0g/wSsftWtbRAR8TSvBXlVmYxe3kTzgoICMjMdd+HatWtHUlISn3/+OfPmzSMoKIi+ffuyffv2ctvijcnornl5Kr4iIuLXEhMTmTFjBtOmTaNr166sWLGCRYsWERcXBzgWPz9zmkK3bt3o1q0b69ev58MPP6Rbt24MGzbM9X6fPn2YP38+7777Lp07dyYpKYnk5GR69+7t0WurklZ/grbD4IKhMPw1R1bNzRpGBvPh7fHUDwtka1o2N729lj9O5MMlp7J5P/wDjh92eztERDzF6u0GVHbieFn7n749Pj6e+Ph41/t9+/ale/fuvPrqq8yaVfa4+0mTJjFxYvGdxOzs7OoFegV2OPizY6HVdsPK3KXLaZm8mpiALyIivmv8+PGMHz++zPeSkpJKbatIUa4RI0YwYsSI6jbN88wWuHGex0/bOjqM+Xf05oY5a9mals1f3l7LB2MvpW7DrpCWAmtehcumeLxdIiLu4LVMXlUmo5c30dxqtRIVFVXmZ8xmMxdddNFZM3k1Phn9WBr840/w8S1QVFjmLm1jwwmwmDhyPI/9R09W73wiIiJyTq2jw5l3e2/qh9nYkpbNze/8QE78g443lc0TET/itSCvKpPRy5to3rNnTwICyl5XxzAMUlJSaNiwYc00vCIim4IlEArzIKvsEtWBVgvtYh3BpIZsioiIeEabmHDm3R5P/TAbvxzIJnFZHQqiOznW71utdfNExD94tbpmZSejjxs3jj179jBx4kS2bt3KO++8wz//+U8eeugh1z5Tp05l8eLF7Ny5k5SUFMaOHUtKSorrmB5htkC9lo7nmb+Xu1unU0M2FeSJiIh4TpuY8FNz9Gz8knaMp09e53hj7Rw4VvVF6kVEfIVXg7zKTkZv0aIFixYtYtmyZXTt2pWnnnqKWbNmcf3117v2OXr0KHfccQft27dn8ODB7N+/nxUrVtCrVy/PXlyUYwFWDpcf5HVu7JyXd9QDDRIRERGnC04FelGhNpIOXcAWa3vHunkrXjz3h0VEfJzJqMjs7lomOzubyMhIsrKyqj4/b+mT8N0MuOh2uKLsDuOXA1lcMWsV4UFWfnpysIqviIhUQ438dtci+r4cfjt4jBvnfE+bkynMtz2NYQ7AdO+PULe5t5smIlJKRX+7vZrJ82tRrR1/z5LJuyAmHJvVzLHcAvYcPuGhhomIiIjTBTHhJN8Zz96IHqwo7ISpKJ8ji57ydrNERKpFQZ67uIK8HeXuEmAx06HhqeIrWhRdRETEK1pHh/PJ+D58Uu+vAET+toDV33/n5VaJiFSdgjx3cQZ5WXshv/wlEjo718vbd9QDjRIREZGyREcE8fT4W1gf3BeLyeDol1N4f81ubzdLRKRKFOS5S2h9CIoEDDiys9zdOjepA6jCpoiIiLeFBlrpMvp5ijAxzPIDyZ//h+n/3UpRkcoXiMj5RUGeu5hMFZqX58zk/bw/S52IiIiIl1kbdsTU+c8APGT9mLeW7+T+5BTsBYVebpmISMUpyHOnCgR5rRqEERxg4XheITszczzUMBERESmPacAkMFsZYNlEvOVX/rPpADfM+Z6D2bnebpqISIUoyHOnChRfsZhNdGx8qviKhmyKiIh4X72W0G0UAG81+pLIICsbU49y5aurWL/nDy83TkTk3BTkuVMFFkQH6NS4DqAgT0RExGdc8jewBBJ56EeWXJ1P25hwDh2zc8OcNXy4NtXbrRMROSsFee5UgeGacFqFTS2jICIi4hsiGkGv2wGI+eE5Ft4Vz7BOseQXGjz6yWYe/WQzeQVFXm6kiEjZFOS5U71TmbwTh+HEkXJ363QqyPvlQBYFheowREREfMLFE8EWBuk/Efr7F7x+U3f+b0hbTCb4cG0qN/7jezI0T09EfJCCPHcKDIPwRo7nZ5mX1yIqlLBAK7n5Rfx+SMVXREREfEJoFCTc43j+1SRMuVncfWlr3hlzEeFBVtbv+YOrXlvFhlTN0xMR36Igz90qMC/PrOIrIiIivuniCY6ROTnpsOQxAC5tG83n91xM6+gwDmbbSXxrDf9ctQvD0FJIIuIbFOS5WwXn5XU5tSj6ZgV5IiIiviMgGIa/Dphg4/uw4xsAWtQP5dO7+7rm6T31xRbG/Ws9WSfzvdteEREU5LlfBYM857y8n1R8RURExLfEJbiKsPD5/WB3TK0IC7Ty+k3dmXr1hQRYTCz+5SBXvrqSn/Yd9V5bRURQkOd+Fa2weWoZha0HslWtS0RExNcMfBIim0FWKvxvqmuzyWTilj7NWXBXH5rWC2bvkZNc/8Zqkr7T8E0R8R4Fee5Wv43j7+EdUFR+8Na0XjCRwQHkFRbx28FjHmqciIiIVEhgGFw9y/H8hzmwZ3WJtzs3qcMX9/ZjcIcY8gsNpvxnC3d/uIHsXA3fFBHPU5DnbnWagdkKBSfh2IFydzOZTK718lR8RURExAe1uhS6j3Y8/+xuyDtR4u3I4ADeGtWDx6/sgNVsYtHmdK6ctYqNqr4pIh6mIM/dLAFQt7nj+bnm5TV2Lop+1L1tEhERkaoZ/DSEN4QjO2HZM6XeNplMjL24BR+PS6BxnWBSj5xgxJtrePV/2yks0vBNEfEMBXmeUNF5ecrkiYiI+LagSLhyhuP5mtdh3/oyd+vWrC6L7u/HlZ0bUlhk8NLS37hhzhr2HjlR5v4iIjVJQZ4nuIK88hdEB+h0ahmFX9OPkZtf6OZGiYiISJW0vRw6jQSjyDFss8Be5m6RwQG8emM3Xh7ZhbBAK+t2/8GwmSv5LGW/hxssIrWNgjxPcC6Inrn9rLs1igwiKtRGQZHBtnQVXxEREfFZlz8LIfXh0FZY/ly5u5lMJq7r3oRF9/Wje7M6HLMXcP/8FCbM36iiLCLiNgryPCHKWWHz7MM1TSaTa728FE3SFhER8V2hUXDFi47nK1+CnxecdfdmUSF8dGcCEy5rg9kEn6YcYNjMlaz+PdMDjRWR2kZBnic4h2se3QMFeWfdNb5lFABJq3drvTwRERFfduG1EH+34/knd0Hq2rPubrWYmXDZBXw8LoGm9YLZ98dJbnp7LZMWblZWT0RqlII8TwiPhYBQx9j9P3afddeb4+OoHxbI7sMn+Nf3ezzTPhEREamawU9B2yug0A7zb3RU3TyHHnH1+O/9/bk5vhkA835IZcgrK/j21wx3t1ZEagkFeZ5gMhXPyzvHkM2wQCsPDr4AgFnfbCfrhO7siYiI+CyzBa7/BzTsCicOwwcj4cSRc34sLNDK09d0Yt7t8cRFhZCWlctf313HxI9SOHri7KN+RETORUGep1RwGQWAP/dowgUxYRw9kc+r35y9WIuIiIh4mS0UbkqGiCZweDskjzrn9AynhFZRfHV/f267uAUmEyzcsJ/LXl7BVz+nu7nRIuLPFOR5iivIO3fQZrWYeXRYewDeW7Ob1MNaU0dERMSnhcfCXz4CWzjsWQX/uQ+Mii1+Hmyz8NiVHfj3uD60ahBKZo6dcf9azx1zf9S6eiJSJQryPKW+s8Lm2dfKcxrQNpp+beqTX2jw3Ffb3NgwERERqRExF8LIJDBZYNM8WPFCpT7eI64uX97Xj7svbYXFbGLJloNc9vJyXv3fdq2fKyKVoiDPUyo4J+90jw5rj8kEX25OY/2ec4/vFxERES9rfRlc8ZLj+bd/h58+qtTHgwIs/N+Qdiy6rx+9W9TDXlDES0t/Y8gMFWYRkYpTkOcp9U4FeTkHITe7Qh9p3zCCkT2aAvD0l1sxKjjsQ0RERLyo51+hz32O55/edc419MrSNjac+XfEM/OGrkSHB7Ln8An++u46btcQThGpAAV5nhJcB0IbOJ4fqdiQTYAHB19AcICFjalH+XJzmnvaJiIiIjXrsqnQ6c9QVAD/Hgs/vlPpQ5hMJoZ3bcz/HryE2/u1wGI2sfTUEM5Xlv7GcXuBGxouIv5AQZ4nOYuvZFZ8yGZ0RBB3XtISgOe+2oa9QGPyRUREfJ7ZDNe+BT1vBQz44gFY+XKFi7GcLjwogMlXdOC/9/cjvqVjCOfM/23nkheW8f73e8gvLKr59ovIeU1BnidVYhmF093RvyXR4YHsPXKSuau1QLqIiMh5wWyBK16Gfg86Xv9vKix9okqBHsAFMeHMuz2e12/qTvOoEDJz7Dz+6c8MeWUFX/2cpmkdIuKiIM+TqhjkhdisPDS4LQCvfrOdP45rkVQREZHzgskEA5+AwU87Xq+eBZ/fC0VVG5ljMpm4onNDljxwCVOvvpCoUBs7M48z7l8buP6N1azbrUJtIqIgz7OqGOQBXN+jCe1iw8nOLWD6f1WERURE5LzS5164+jUwmWHj+/DxGCiwV/lwNquZW/o0Z9n/DeC+P7UmOMDChtSj/PnNNdz23jp+3p9Vc20XkfOOgjxPcgV5Oyo9VMNiNvHElR0A+OjHfTy/+FcFeiIiIueT7qPgz++BxQZbP4cPEytccbs84UEBTBzcluX/N4CbejfDYjbx9dYMrnx1FWOT1vHTvqM103YROa8oyPOkei0AE+Qdg5zKr3XTp3V9nhp+IQBvLNvBjK+313ADRURExK06XA03fQQBobDzW5gzAA5uqfZhoyOCeObaTix5oD/XdmuM2QT/25bB1a99x61J69i092i1zyEi5w8FeZ5kDYQ6zRzPD1ctQBuV0JzHT2X0Zv5vO699o0BPRETkvNLqUhjzBUQ0cSyr9PZA+Onjmjl0gzBeSezK1xMv4brujmDvm20ZDH/9O8a8+wMbU/+okfOIiG9TkOdp9ds4/lZhXp7T2ItbMGloOwBeXPIbby2v+Lp7IiIi4gMad4c7l0PLAZB/AhbeBov+BgU1U1ytZYMwXh7ZlW8eHMCIHk2wmE0s+/UQ185ezQ1z1vDttgxN+xDxYwryPK0axVdOd+clrXho8AUATP/vNt5Ztau6LRMRERFPCq0PNy+Efg85Xv/wFiRdAVn7a+wUzeuH8uKfu/DNg5fw5x5NsJpNfL/zCH9NWsflM1by7/X7yCvQOnsi/kZBnqedXnylmu75UxvuG+jIDE77Ygvvr9ld7WOKiIiIB5ktMPBxuHE+BEbCvh/grf6wa0WNniYuKpQX/tyFFX+7lNv7tSAs0MqvB4/x0Meb6P/8t8xZsYNjufk1ek4R8R4FeZ4W1crxt5qZPKcHLmvDXQMcx3z8s1/4cG1qjRxXREREPKjtULhzGcR0ghOZMHc4fPP3Ghu+6dSoTjCTr+jAd4/8iYcvb0d0eCDp2bk8s2gbfaZ/w1NfbGHP4eM1ek4R8TwFeZ7mzOQd2QWFBdU+nMlk4m9D2jL24hYAPPrJZp747GfsBVVbZFVERGre7NmzadGiBUFBQfTo0YOVK1eedf/ly5fTo0cPgoKCaNmyJW+++WaJ95OSkjCZTKUeubm57rwMcbd6LWHsEuhyExhFsOJ5mHMJ7N9Q46eKDA7grgGtWPnwpTw/ojOto8M4Zi/gn6t2MeDFZdyatI7lvx2iqEjz9kTORwryPC2iCViDoCgfju6pkUOaTCYeu6I99/7JEUDOXbOHEW+sIfXwiRo5voiIVF1ycjITJkxg8uTJbNy4kX79+jF06FBSU8seebFr1y6GDRtGv3792LhxI48++ij33XcfCxYsKLFfREQEaWlpJR5BQUGeuCRxJ1sIXDMbRrwLIVGQscVRfXPpk5Bf80F8oNXCyJ5NWTKhP+/+9SIGtG2AYTgqct7yzg9c9vJykr7bpaGcIucZk6HSSqVkZ2cTGRlJVlYWERERNX+Ct/pD2ibo8Ve4akbNHDPvBHw3k0M71rN+3wlyCi0YFhu9WscSF10XLIEQ0Qi6/gUC9I8AEfE/bv/trqLevXvTvXt33njjDde29u3bc8011zB9+vRS+z/88MN8/vnnbN261bVt3LhxbNq0iTVr1gCOTN6ECRM4evRoldvlq9+XnOZ4Jvz3Yfj5347X9S+A4a9D015uPe3OQznMXbOHf6/fR47dMeooLNDKtd0ac2OvZnRopP+9iHhLRX+7lcnzhj89AZhg/buw8YPqH2/fekfguPxZGuxbyuV8xwjLCv7M18T9/i9Y/SqsfBG+nOgY9nEgpfrnFBGRc8rLy2P9+vUMHjy4xPbBgwezevXqMj+zZs2aUvsPGTKEH3/8kfz84mxKTk4OcXFxNGnShCuvvJKNGzfW/AWId4XWhxH/hBs+hLAYyPwN/jkYvnrUcXPXTVo2CGPK1Rfy/aMDmTb8Qlo2CCXHXsD73+9h2KyVDH9tFfN/SOW4vfrTTkTEPazebkCt1OYyGDAJlj3jCLxiO0LDLpU/TmE+LH8eVr4ERiGEN4SEe8BkpjA/l+9+PcBPezKwUUDjMBOXm9diObTNMezjkofh4olg0f8ERETcJTMzk8LCQmJiYkpsj4mJIT09vczPpKenl7l/QUEBmZmZNGzYkHbt2pGUlESnTp3Izs5m5syZ9O3bl02bNtGmTZsyj2u327Hb7a7X2dnZ1bw68Zh2V0BcH0dwt+lD+P512PKZoypnp5Fgds89+7BAK6MTmnNz7zi+25HJ/B/2smRLOpv2ZbFp32ae+mILV3dtxI29mtGpcSQmk8kt7RCRytO/8L2l///B/h9h+xJIHgV3LIOQehX/fMY2+OQOx7BPgE5/hmEvQHBdACxA//6Qt+UgD368iayj+TQNuoZ/xSQTd3ApfPt3+PW/cO1b0OCCGr88EREpduY/fg3DOOs/iMva//Tt8fHxxMfHu97v27cv3bt359VXX2XWrFllHnP69OlMnTq1Su0XHxBcF659AzpeB188AFl74ZM7Yc1rMGgatPqT205tNpvo16YB/do0IDPHzoL1+5i/bi+7Mo8z74e9zPthL+0bRnB998Zc3bUR0eGaFiLibRqu6S1mM1w3B+o2dxRgWXgHFFVgMdKiIlj9WvG8vuC6jsnZ17/tCvBOd1mHGL6872K6Nq3D3twQLtkzhhfD/o8CWwQc2ABv9YPv36zYuUVEpFLq16+PxWIplbXLyMgola1zio2NLXN/q9VKVFRUmZ8xm81cdNFFbN++vdy2TJo0iaysLNdj7969lbwa8QltBsE96+CyKRAYAemb4f1r4f3rIP1nt5++flggd17Sim8evIT5d8RzTddG2KxmtqZl8/SXW0mY/g1/ffcH/rPpALn5qvQt4i0K8rwpuC6MfN9RbfP3pY5SyWeT+j28dyUsmQyFdmg9CO5a47irdxZN6obw73EJTLmqA+GBAbyW2Y1+x/7Ob2G9oCAXvnoY5l4N2Qdq8OJERMRms9GjRw+WLl1aYvvSpUvp06dPmZ9JSEgotf+SJUvo2bMnAQEBZX7GMAxSUlJo2LBhuW0JDAwkIiKixEPOUwHBcPEDcF8KxI8HcwDs+B+8eTF8Oh6y9rm9CSaTifiWUcy4oRs/PDqQp67pSLdmdSgsMvj210PcO28jFz39NQ//+ye+33lYSzGIeJiqa5bB4xXHUubBp+MAE9z0EVxw2oT7oiLHkM7vZkCqo6oaAaFw+TPQ/Rao5Pj3jGO5PLtoGws37gcMbg/+lofNH2AtPAnhjeAvHzvmCIqInGd8tVpkcnIyo0aN4s033yQhIYE5c+bwj3/8g19++YW4uDgmTZrE/v37mTt3LuBYQqFjx47ceeed3H777axZs4Zx48Yxb948rr/+egCmTp1KfHw8bdq0ITs7m1mzZvH+++/z3Xff0atXxSov+ur3JVVwZCf87yn4ZaHjtcXmmKvX516IbufRpuw8lMMnG/ezcMN+9h896doeGxHEsE4NuaJzQ7o3q6P5eyJVVNHfbgV5ZfBKx/fFRPjxnxAUCXcsh8gm8PMC+G6mY40ccPxod7kR+k10DPOshrU7D/PEZ7/w68FjNDel8X7IDJoW7sWwhWMa+R60Hlj9axIR8SBfDlpmz57N888/T1paGh07duSVV16hf//+AIwZM4bdu3ezbNky1/7Lly/ngQce4JdffqFRo0Y8/PDDjBs3zvX+Aw88wMKFC0lPTycyMpJu3boxZcoUEhISKtwmX/6+pIr2/ehYT2/PquJtbYY4gr3mF1f6xnB1FBUZ/LD7CAs37OO/m9M5dlolzsZ1ghnWKZYrOzeicxMVbBGpDAV51eCVjq/ADu8OcxRjiWrteJ11ar6ELRx6/tUxJCOi/KE4lZVfWMTcNXt4ZelvmO1HeStgBgmWLRgmC1w1A1P30TV2LhERd1PQUjn6vvzY3h9g9SzY+gVw6p95jbpBn/ug/dUer6xtLyhkxW+ZfPnTAZZuOcjxvOK5ek3rBXP5hbEMuTCWbs3qYjEr4BM5GwV51eC1ji9rv6OgyolMx+vQBhB/F/QcC8F13HbajOxcZv5vO5/+uIunzG9xncVxB3Bn+3E0HzEds0VTN0XE9yloqRx9X7XA4R2w5nVI+cAxBx+gTjPoPhq63ASRjT3epNz8Qpb9eogvfjrA/7ZmcPK04iz1w2wM6hDD4A6x9GkdRaDV4vH2ifg6BXnV4NWOb+86x8LlbQZD15sck6s9JD0rl3+s2EHUuhcYb/4EgK8DBnBy2EyGdYnT3TUR8WkKWipH31ctcjwTfvgH/DAHTh5xbDOZHcsudLsZ2g4Da6DHm3Uyr5Blv2aw+Jd0/rctg2O5xUM6Q20WBrSLZlD7GC65oAF1Q20eb5+IL1KQVw21veM7nGPnh4UzGbRjOlZTEWsKOzA1ZBJDL2rPyIua0DDSc4GniEhF1fbf7srS91UL5Z1wLKK+8V8l5+0F14XOiY6AL7aTV5qWX1jE2p1HWPxLOku2pHMw2+56z2yCrk3rcGnbaC5tF82FjSI0j09qLQV51aCOz+H4L0sIWDgGW+FxdhfFcG/+vfxCSy5tG80NvZpxadsGWDWUU0R8hH67K0ffVy13eAekfOh4HDttCaUG7Rzz9jpcDTEdPVqsxamoyGDz/iwW/5LOt78eYmtadon3o8MDGdC2AQPaRtOnVRR1QpTlk9pDQV41qOM7TfpmjA9vwJS9jwKsTM9P5J3CoRiYiYkI5M89mjKyZ1OaRYV4u6UiUsvpt7ty9H0JAEWFsONb2Pg+bPsSivKL36vXsjjga9TdKwEfQFrWSZb9eohvt2Ww6vdMTpxWuMVkgk6NI7m4dX0ubl2f7nF1CQrQXD7xXwryqkEd3xlO/gGf3wtb/wPA75F9uOPYWHaeKB622aVpHa7s1JBhnRvSuI6Gc4qI5+m3u3L0fUkpJ4/Cb4sdQzp//xoKi4dMEtnUMXev9UDHcgy2UK800V5QyI+7/+CbbRms3H6I3w7mlHg/KMDMRc3rcXHr+sS3jOLCRhEadSR+RUFeNajjK4NhwI/vwFeToNCOERbL2m7P8vruRnz3eyZFp/2vqFuzOlzRqSHDOjWkkQI+EfEQ/XZXjr4vOSt7Dmxf4gj4ti+F/OPF71lsENcHWg2E1pdBdHuvZfkOZufy3e+ZrNqeyarfM8k4Zi/xfliglR5xdendsh69W0TRuUkkAQr65DymIK8a1PGdxcFf4OO/QuavgAn6/x+Hekzgq62O9W/W7jrC6f+L6t6sDgPbxzCwfTRtY8I1UVpE3Ea/3ZWj70sqLP8k7PjGEez9/j/ISi35fngjaHUpxPWF5n2hTpxXgj7DMPg9I4eV2zNZvSOTH3YdIfu0ip0AwQEWesTVpWfzuvSIq0vXpnUIDwrweFtFqkpBXjWo4zuHvOPw1SOwYa7jdeOeMGgaNO9LxrFcvvo5nS9+SmPd7pIBX6PIIC5tF82f2kXTp1V9gm0aMy8iNUe/3ZWj70uqxDDg8O+O4Zy/fw27VxWvwecU0cSR6WveF+IuhqhWXgn6CosMtqVns3bnEdbuOszaXUc4eiK/xD4mE7SNCad7XF16NHMEfnFRIbopLT5LQV41qOOroJ8XwH8mgP1U1atWf4I/PQ6NuwOOIRRLtxzk220ZfLcjk9z8ItdHA61m+rSK4uI2DejbOkpZPhGpNv12V46+L6kR+Sdhz2rYtcLx98AGKCqZPSM0Gpr2giY9oclF0KibV+b0FRUZ/JZxjB92HWH9nj/YkPoHe4+cLLVfnZAAOjWOpHOTSDo1rkPnJpE0jAzSv1PEJyjIqwZ1fJWQnQYrXoAN7xX/qLe7Ev70mGOM/im5+YWs2XGYb7Zl8M22DPYfLfmjGhVqI6FVFH1b16dPqyia1dNdNBGpHP12V46+L3GLvOOw9wdHwLfnO9j3Y8kCLgAmC8R0cAR8zqAvqg1YrB5vbkZ2LhtS/2BD6lHW7/mDzfuzyCsoKrVf/TAbnRpH0rFxJO0bRtC+YQTN6oVgMevfKuJZCvKqQR1fFRzZBcufg5+SwSgCTNDpzzDgEccwjdMYhsFvB3NY9msG3+04zLpdRziZX1hin8Z1gundsh494hxDJ9pEh+uHVETOSr/dlaPvSzwiPxcObIT9P8K+dY6gL3t/6f2swRDbEWI7Q8Mujkd0e7AGerS59oJCfkvP4af9R9m8L4uf9mXx28FjFBSV/udycICFC2LDaR8bTvuGEbSNDadNdBhRYZ5ts9QuCvKqQR1fNRz6Fb79u6MaF4DJDC0ugc4jof1VEBhe6iN5BUWk7D3Kd79nsmbHYTbu/YP8wpL/swwPtNK1WR3HZOm4enRpGqmJ0iJSgn67K0ffl3hN1v7Tgr71kP4T5OWU3s8cAA3aQnQHiLnQ8YjuABGNPDrHLze/kG3px/hp31F+2Z/NtvRsfj14rMQ0lNPVDQmgVYMwWjUIo3V0GK2iQ2ndIJzGdYN1w1qqTUFeNajjqwEHUhzB3vYlxduswdB2KHROdKyzYyk7SDuRV8C63X84xsvv+YONqX9wPK+w1H4t6odyYaMIOjaOpGOjSC5sFEHdUJubLkhEfJ1+uytH35f4jKIiOLIT0lIgbVPxI/do2fsH1TkV8LWHBu2KH6H1PRb8FRYZ7D58nG1px9ia5gj8tqUfY98fpef4OQVYTDSpG0KzeiHERTn/hhIXFULTuiEqSCcVoiCvGtTx1aAju2Dzvx3DOA9vL94eEgUXXgtthjgqcAWGlXuIgsIifj14jA17HIHf+nImSoNjmOeFjSK4ICacNjFhtIkOp2WDUIIC9MMp4u/02105+r7EpxkGHE11LN2U8Qsc3AIZWyBzOxilb/wCEFzvVMDX1vG3fhvHI6IJmD2zNt7JvEJ2Zubwe0YOOw4dZ0dGDjsO5bAz83iZc/1OVy/URuM6wTSqE0TjOiE0qhNEk7rBNIwMJjYyiPphgcoEioK86lDH5waG4RiTv/ljR9B3PKP4PbPVsQxDi/7Q8hLHJOxzjME/cjyPXw5k8fP+bH4+kMUv+7PYffhEmfuaTdA8KtQV9LWoH0rz+qG0qB9K3ZAAFXgR8RP67a4cfV9yXiqwQ+ZvjqDv0FbI2AaHtsEfu4Fy/klrDYb6rR3FXepf4Aj8olo7agaUMY3EHQqLDNKzc9lz+Diph0+w58iJU3+Ps+fwCY6dsZ5fWcwmaBAeSExEEDERQcRGBBETEUj9sECiwgKpH2ajfpjjtbKC/ktBXjWo43OzwgLYtcwxb2/ncji6p+T71mBoFu94NOoGDbtCeMw5D5udm8+WA9lsOZDN9owcth88xm8Hj5VaCPV04UFWWtQPJS4qlBZRITStF0KTuiGn7pwFYbV45s6fiFSffrsrR9+X+JX8k44s36FfHUHfoW2O9fwO74Ci/PI/FxbjCPjqtTwV+J0K/uo2h4BgjzTdMAyycwvY/8dJDhw9yf6jjr/7Tv1NO5rLoRw7hWUUfylPqM1C/fBA6obYqBdqo05IQInn9UJsRIYEEBkcQERQAJEhAYTZrJiVKfR5CvKqQR2fh/2x27G+zs7ljr+nZ/mcwhtBo67FQV9sJwiPPefYe8MwyDhmZ/vBHH47eIztGTnszjzOnsPHOZCVe9bPWswmYiOCaFw3mCZ1g2lcxzFcomFkELERjiCwjjKBIj5Dv92Vo+9LaoXCAsfN5Mztjgzg4e2O54d/h+OHzv7Z8EaO4K9ei1N/Tz2vEwfBdTzSfKfCIoPDOXYOZttJz87lYHYuGdm5HMy2k5njfORxKMd+zmGh5TGbIDzoVOAXbCU8MICwICvhgVbCgqyEnfobHmglxGYlNNBS8q/NSkighRCbhSCrRQGjmyjIqwZ1fF5kGI67b7tWwP4NjknYh36lzCEYgZGOIRcN2p4ad9/WMQyjbvMKrbWTm1/InsMn2H34OLszj7P78HH2/XGSfX+cZP8fJ8krPPePZKDVTGykY9hEdHggDcIDiQ4POvU30PW3TohN4+hF3Ey/3ZWj70tqvdwsR6bv8A5H0HdkhyMAPLIL7Fln/2xQHagb5wj46jY/9bw51GkKEY3PWmvAnQzD4Ji9gMM5eWTm2DlyPI+jJ/I4cjyfoyfy+OPU8z9O5JF1Mp+sk/lkn8zHXsXA8GwCrWZCbBaCAywE2YqDv6AAC0EBZgIDnK/NxdusFmxWM4FWx/NAq9n12mY1Y7OYCXD+tZy+zYTV7HhutZgIsJgJsJj88ka8grxqUMfnY+w5kL7ZMacvLcXx9/Dvp9bjK4PZ6viBrdPM8eNbp+mp580gsqkjA3iOOX9FRQaHcuyngr4T7PvjJGlZJ0nPyiUtK5f0rFwOH8+r8CWYTbiGSUSF2YgKDXQ9rxdqIzLYMYyibohjGEWdkADCAq1++eMk4i767a4cfV8i5TAMOPmHo+LnkZ2OoM/5/I9d584AAgTXdRR8iTztEd7QMf0kvKFjmGhQpEeXgjib3PxCsk/mk53rDPwKyLGfeuQWcMz5NzefHHsBx/MKOeH8m1fAcbvj74kyqqF7k8Vswmp2BH1Wi+O51Xzac4sZq9mE5bSH1WzCbDJhtTj+WswmLKbi982nvTabTJhNjvOYTCYsZrCYHM/PfM9swrVtaKeGtG9Ytd9dBXnVoI7vPFBgd9x5y/zN8Tj066nn26Gg/PLFLkF1HMFeWLTjhzYsxvE8pD6E1HP8OAfXczwPqlNmZtBeUEhGtp20rFzSsk6SmZNHxrFcDh2zl3hUJhg8XYDFdGrIhGO8fESwc+y81bUtLMhKhHMIxalhFBFBjgAxJNBCoFUTr6X20G935ej7Eqkie46j8ufRPY4pJ3/sKX6etf/cWUAna9Cpf4vEQlgDR+XxkPqOv6Gn/j3i/HdJUCTYwj1WJbSqiooMcgsKOZlXyIm8QnLzCzmZ73h+8tTr3IJCcvOLHM+dfwsKsecXYS8oIq/g/9u7/+CoynuP45+zu9klCSE38iMhl9SmSlVwoFewTFC0lTYFO44wdOQ66GA7oxMEBmQ6VqoUaqcT+mMoepG0TKkzHZ2GYRTLVGkJrY0FcQqUSEaof3QQqJJGRMgmIT92z3P/OLtnd5PN5ocJG3bfr5kz58fznLPPfic5z/nuefasrc5QuNdyd9hZ7w4bdYVsdUXWu0K2Qrbd6zeWR7Pn/vdLuv9L/z2kfQd67u5/TBswGvkCUvE0Z4pn21LwI+nSOecEfPls5ER81tl2+ZwU7nJ+e6fjkjM0dCAChVJuoTMPFEhjxikQKFBZYJzKAgXONv9YqThfKsuX/NFpgrq9ubocytHFTq8+6fLq4w5Ln7R162Jbly60drnDJy61O8MnPm3vdk9iF1qdOkOV47WU53cSwDy/V3kBn8YGvMrNiaz7nWET0eVcv88ZVhEZOpGb41UgOozC51Wu3xsZQuEMs/Bn8HAIAACSCoxNfg0S1dEitXwoXf63c91x+d/OFDwvBf8jtTY5Q0VDHZEk8YMBvrAlBcY5CZ87jXOuP/z5Trv8kSm6nJPnPECm1zwyeQPDmjh6PM51R57fp/HDdtSBMcYoZBuFwkZdYVuhsHMt1R22FbKNwpFEMGw725y5kR3ZL2zbCttS2I7Wj03ROnZ0m3ESWtsYhY2JLDvfnTTRbUayjZFx6zrrtjEqn5A/4vEgyUNm8XhiwyKur+hdHh2C0dostf4nbt7kLLd/IrVfdOpcueichCXnU7mBfjLXQ46kCZHJ5RvjnFx9uVLOGGc9LyCNGyP5Agp7/OpSjrqUo07jU6dy1GF7dcX26YrtUXvYp9aQV+1hS21hj9pCHrV2exQMeRTsstQWthSSV93Gp+4Or0IdPnXLqw551SqvuuVTyHgVUu+pW14ZDfyEb1lyx85Hx8b7fU7y5+8xbj46Rt7n9bgJYnTZ63GGRuR4nOVomS8ydMIbN6TCl2RYRfxQi/hhFZY7pEJuPU9kSEV0OIUztMLpnKL1LHdYhbPNkiXLEylTrI4VKYvfj6QXALLYmHHONOmWvut0tTvXH8EmJ/lr/8SZ2i7EluOncJckE7seGdolSXJev3M94gvErkl8gdg2dz2uLCc3th7dJ7qtZyLZM8H0jRmRYaqW5Vw75HilXI3ASCbblrrbpa42qavVmXe3R5bbY2Xd7c7TXruvOIl8KDLvjp8/KenO4W9jnLQnedu3b9fPfvYznT9/XtOnT9fWrVs1b968PuvX19dr3bp1eu+991RaWqonn3xSVVVVCXVeeeUVbdiwQf/61790ww036Mc//rEWL1480m8F1wLLigx/uE6adHP/9cMhJ9G7clG6cknqbHGmjhapMxhZDzrr3W3OP3myf/7uK5ETdESow5n0adKX9UrKjUyD5o1Mn4EtS7a8CsurkDyxJNB4FJZHIeNsC8ursJxt4bBH4XBs3TYehWXJjpbLI+MuW+6yHaljm8hclowsd7uRZMujkKSuuHUjybhzK25uJZRJkjFWrzpS9HE+sTIlOVZ8vfhyJakTv+6KJIVOh2bFbbPc41pWZNly9rcix3L3jTuuZSn2Gm65+2LO/pbTHrfM6p20u+8meqjIq0Zfw4qLTrS+lbC/SShTX/uYxG09jx87trMeGPtfqlr1VK/2AkBG8edFntpZPrD63R2R64/LkelSZN4Su+boDCZeg3QGY8lGQuLR45ok3OVMnSPyTpOwnITPH03+8uOSwGQJ4xgn4fTmRCa/8/wFrz+2nipptO3Yewx3S+HO2HKoMxKb9kiidsW5nuu+Ermmi8Syq83ZPlz+56HhO1Yf0prk7dq1S2vXrtX27dt1xx136Fe/+pUWLlyokydP6nOf+1yv+qdPn9a9996rRx99VC+99JIOHTqkxx9/XBMnTtSSJUskSYcPH9bSpUv1ox/9SIsXL9aePXv0wAMP6ODBg5ozZ87Vfou41nl9Uv54Z/qs7HDiCTZ60g11RpK+zripI7YtemJKutzdYx5/Ags5vw0U7o7MQ055dNmOlCd5gI2TjoXkU0gJj6ixeswxspJ9veDa+crBkJzrLJVEkgcACXIid8zGThqe44VDkTtMkWuO7o64a4/IerhnWWfvOqErsXmoM/EOlptYtvf4sNtEEqlhTJquKivuazn5TpLqz4skrvmxBDZ+tFZC4porlX155FuZzgevzJkzR7fddptqamrcbbfccosWLVqk6urqXvW/973vae/evTp16pS7raqqSu+++64OHz4sSVq6dKlaWlq0b98+t86CBQtUVFSk3/3udwNqF19GR1ax7UjCF4olgCbsrIe7I9vDsXI77CSG7j7x5eHIvtG5HTuWsWP7Rid3PewMpXXLTGI9mcTtCesmst5zHimX+iiPzBWdRZfjyyUjO7LJGWfvnjKNkZGTIBvb2SexzMSOGz1Wj/Y4xXZcG+y4piS2I7Ft0dZGXy8uUe91Rrd7F8XXifv00xj1+DQ0MZs38fUjdaN3HGP1Lee9x91tNL0+HYg7bvzrS7LHlmji0v/r+SYGhHP34BAvAFdVNLGMDm2MJn9dbXF30HokjtEEs/tK7IPr6Afbdij2AXeqdMaynO8e+gKxO3/uPJB4RzGarEWHlgYKYslb9LuPOblpfSrqqH/wSldXl44dO6annkr8xLayslJvv/120n0OHz6sysrKhG3f+MY3tHPnTnV3dysnJ0eHDx/WE0880avO1q1b+2xLZ2enOjtj96hbWloG+W6Aa5jHI3n8kvzpbsmo1HOYIgAAGAKvT/JGHlaHEZe257BeuHBB4XBYxcXFCduLi4vV1NSUdJ+mpqak9UOhkC5cuJCyTl/HlKTq6moVFha6U1lZ2VDeEgAAAACkXdp/bKPnU+iMMSmfTJesfs/tgz3m+vXrdfnyZXc6d+7cgNsPAAAAAKNJ2oZrTpgwQV6vt9cdtubm5l534qJKSkqS1vf5fBo/fnzKOn0dU5ICgYACgUCf5QAAAABwrUjbnTy/369Zs2aprq4uYXtdXZ3mzp2bdJ+Kiope9ffv36/Zs2crJycnZZ2+jgkAAAAAmSStP6Gwbt06Pfzww5o9e7YqKiq0Y8cOnT171v3du/Xr1+vDDz/Ub3/7W0nOkzS3bdumdevW6dFHH9Xhw4e1c+fOhKdmrlmzRnfddZd+8pOf6P7779fvf/97HThwQAcPHkzLewQAAACAqymtSd7SpUv1ySef6Nlnn9X58+d166236o033tD1118vSTp//rzOnj3r1i8vL9cbb7yhJ554Qi+88IJKS0v1/PPPu7+RJ0lz585VbW2tnnnmGW3YsEE33HCDdu3axW/kAQAAAMgKaf2dvNGK3w4CgGsP5+7BIV4AcO0Z6Lk77U/XBAAAAAAMH5I8AAAAAMggJHkAAAAAkEFI8gAAAAAgg5DkAQAAAEAGIckDAAAAgAxCkgcAAAAAGYQkDwAAAAAyCEkeAAAAAGQQkjwAAAAAyCAkeQAAAACQQUjyAAAAACCDkOQBAAAAQAbxpbsBo5ExRpLU0tKS5pYAAAYqes5uaWlRQUGBLMtKc4tGN/o6ALj2RM/Z0XN4X0jykggGg5KksrKyNLcEADBYZWVlunz5ssaNG5fupoxq9HUAcO0KBoMqLCzss9wy/aWBWci2bX300Uef6ZPglpYWlZWV6dy5c1xo9IEYpUZ8+keMUsu2+BhjFAwGVVBQoHHjxnEnrx+fta/Ltr+voSBG/SNGqRGf/mVbjKJ9XWlpqTyevr95x528JDwej6ZMmTIsxxo3blxW/MF9FsQoNeLTP2KUWjbFJ9Wnmkg0XH1dNv19DRUx6h8xSo349C+bYjSQvo4HrwAAAABABiHJAwAAAIAMQpI3QgKBgDZu3KhAIJDupoxaxCg14tM/YpQa8cFI4u+rf8Sof8QoNeLTP2KUHA9eAQAAAIAMwp08AAAAAMggJHkAAAAAkEFI8gAAAAAgg5DkjYDt27ervLxcY8aM0axZs/S3v/0t3U1Km7feekv33XefSktLZVmWXnvttYRyY4w2bdqk0tJS5ebm6itf+Yree++99DQ2Daqrq3X77beroKBAkyZN0qJFi/T+++8n1Mn2GNXU1GjGjBnu799UVFRo3759bnm2x6en6upqWZaltWvXutuIEUYCfV0MfV1q9HWp0c8NHn1d/0jyhtmuXbu0du1aPf300zp+/LjmzZunhQsX6uzZs+luWlq0tbVp5syZ2rZtW9Lyn/70p9qyZYu2bdumI0eOqKSkRF//+tcVDAavckvTo76+XitXrtQ777yjuro6hUIhVVZWqq2tza2T7TGaMmWKNm/erKNHj+ro0aO65557dP/997sn7myPT7wjR45ox44dmjFjRsJ2YoThRl+XiL4uNfq61OjnBoe+boAMhtWXv/xlU1VVlbDt5ptvNk899VSaWjR6SDJ79uxx123bNiUlJWbz5s3uto6ODlNYWGh++ctfpqGF6dfc3Gwkmfr6emMMMepLUVGR+fWvf0184gSDQTN16lRTV1dn7r77brNmzRpjDH9DGBn0dX2jr+sffV3/6OeSo68bOO7kDaOuri4dO3ZMlZWVCdsrKyv19ttvp6lVo9fp06fV1NSUEK9AIKC77747a+N1+fJlSdJ1110niRj1FA6HVVtbq7a2NlVUVBCfOCtXrtQ3v/lNfe1rX0vYToww3OjrBof/wd7o6/pGP5cafd3A+dLdgExy4cIFhcNhFRcXJ2wvLi5WU1NTmlo1ekVjkixeZ86cSUeT0soYo3Xr1unOO+/UrbfeKokYRTU2NqqiokIdHR0aO3as9uzZo2nTprkn7myPT21trY4dO6ajR4/2KuNvCMONvm5w+B9MRF+XHP1c/+jrBockbwRYlpWwbozptQ0xxMuxatUqnThxQgcPHuxVlu0xuummm9TQ0KBLly7plVde0fLly1VfX++WZ3N8zp07pzVr1mj//v0aM2ZMn/WyOUYYGfxNDQ7xctDXJUc/lxp93eAxXHMYTZgwQV6vt9cnmc3Nzb0+WYBUUlIiScRL0urVq7V37169+eabmjJlirudGDn8fr9uvPFGzZ49W9XV1Zo5c6aee+454iPp2LFjam5u1qxZs+Tz+eTz+VRfX6/nn39ePp/PjUM2xwjDi75ucDhPxdDX9Y1+LjX6usEjyRtGfr9fs2bNUl1dXcL2uro6zZ07N02tGr3Ky8tVUlKSEK+uri7V19dnTbyMMVq1apVeffVV/eUvf1F5eXlCOTFKzhijzs5O4iNp/vz5amxsVENDgzvNnj1by5YtU0NDg77whS9kfYwwvOjrBofzFH3dUNDPJaKvG4Kr/6yXzFZbW2tycnLMzp07zcmTJ83atWtNfn6++eCDD9LdtLQIBoPm+PHj5vjx40aS2bJlizl+/Lg5c+aMMcaYzZs3m8LCQvPqq6+axsZG8+CDD5rJkyeblpaWNLf86lixYoUpLCw0f/3rX8358+fdqb293a2T7TFav369eeutt8zp06fNiRMnzPe//33j8XjM/v37jTHEJ5n4J44ZQ4ww/OjrEtHXpUZflxr93NDQ16VGkjcCXnjhBXP99dcbv99vbrvtNvcRwdnozTffNJJ6TcuXLzfGOI+83bhxoykpKTGBQMDcddddprGxMb2NvoqSxUaSefHFF9062R6j73znO+7/08SJE838+fPdjs8Y4pNMz46PGGEk0NfF0NelRl+XGv3c0NDXpWYZY8zVu28IAAAAABhJfCcPAAAAADIISR4AAAAAZBCSPAAAAADIICR5AAAAAJBBSPIAAAAAIIOQ5AEAAABABiHJAwAAAIAMQpIHAAAAABmEJA9AUpZl6bXXXkt3MwAAGDH0dchUJHnAKPTII4/Isqxe04IFC9LdNAAAhgV9HTByfOluAIDkFixYoBdffDFhWyAQSFNrAAAYfvR1wMjgTh4wSgUCAZWUlCRMRUVFkpzhJTU1NVq4cKFyc3NVXl6u3bt3J+zf2Nioe+65R7m5uRo/frwee+wxtba2JtT5zW9+o+nTpysQCGjy5MlatWpVQvmFCxe0ePFi5eXlaerUqdq7d69b9umnn2rZsmWaOHGicnNzNXXq1F4dNQAAqdDXASODJA+4Rm3YsEFLlizRu+++q4ceekgPPvigTp06JUlqb2/XggULVFRUpCNHjmj37t06cOBAQsdWU1OjlStX6rHHHlNjY6P27t2rG2+8MeE1fvjDH+qBBx7QiRMndO+992rZsmW6ePGi+/onT57Uvn37dOrUKdXU1GjChAlXLwAAgIxHXwcMkQEw6ixfvtx4vV6Tn5+fMD377LPGGGMkmaqqqoR95syZY1asWGGMMWbHjh2mqKjItLa2uuWvv/668Xg8pqmpyRhjTGlpqXn66af7bIMk88wzz7jrra2txrIss2/fPmOMMffdd5/59re/PTxvGACQdejrgJHDd/KAUeqrX/2qampqErZdd9117nJFRUVCWUVFhRoaGiRJp06d0syZM5Wfn++W33HHHbJtW++//74sy9JHH32k+fPnp2zDjBkz3OX8/HwVFBSoublZkrRixQotWbJE//jHP1RZWalFixZp7ty5Q3qvAIDsRF8HjAySPGCUys/P7zWkpD+WZUmSjDHucrI6ubm5AzpeTk5Or31t25YkLVy4UGfOnNHrr7+uAwcOaP78+Vq5cqV+/vOfD6rNAIDsRV8HjAy+kwdco955551e6zfffLMkadq0aWpoaFBbW5tbfujQIXk8Hn3xi19UQUGBPv/5z+vPf/7zZ2rDxIkT9cgjj+ill17S1q1btWPHjs90PAAA4tHXAUPDnTxglOrs7FRTU1PCNp/P537he/fu3Zo9e7buvPNOvfzyy/r73/+unTt3SpKWLVumjRs3avny5dq0aZM+/vhjrV69Wg8//LCKi4slSZs2bVJVVZUmTZqkhQsXKhgM6tChQ1q9evWA2veDH/xAs2bN0vTp09XZ2ak//OEPuuWWW4YxAgCATEdfB4wMkjxglPrjH/+oyZMnJ2y76aab9M9//lOS8zSw2tpaPf744yopKdHLL7+sadOmSZLy8vL0pz/9SWvWrNHtt9+uvLw8LVmyRFu2bHGPtXz5cnV0dOgXv/iFvvvd72rChAn61re+NeD2+f1+rV+/Xh988IFyc3M1b9481dbWDsM7BwBkC/o6YGRYxhiT7kYAGBzLsrRnzx4tWrQo3U0BAGBE0NcBQ8d38gAAAAAgg5DkAQAAAEAGYbgmAAAAAGQQ7uQBAAAAQAYhyQMAAACADEKSBwAAAAAZhCQPAAAAADIISR4AAAAAZBCSPAAAAADIICR5AAAAAJBBSPIAAAAAIIOQ5AEAAABABvl/GjM0uow/IFEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 900x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_history(mo_linear_history)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ec316e57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_predictions(mo_linear, mo_sample_batch, 'multi_output')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a06177f7",
   "metadata": {},
   "source": [
    "## Evaluation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "c276e874",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "55/55 [==============================] - 0s 908us/step - loss: 0.0022 - mean_absolute_error: 0.0318\n",
      "53/53 [==============================] - 0s 923us/step - loss: 0.0235 - mean_absolute_error: 0.1229\n",
      "55/55 [==============================] - 0s 889us/step - loss: 0.0049 - mean_absolute_error: 0.0495\n"
     ]
    }
   ],
   "source": [
    "mae_linear_ss = ss_linear.evaluate(test_ds_ss)[1]\n",
    "mae_linear_ms = ms_linear.evaluate(test_ds_ms)[1]\n",
    "mae_linear_mo = mo_linear.evaluate(test_ds_mo)[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9766bcb5",
   "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": "3.9.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}