MontainCarContinuous-v0-Done.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import json\n",
    "import os\n",
    "import seaborn as sns\n",
    "from numpy import median\n",
    "import numpy as np\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## RESULTS USING THE SIGNAL OF DONE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2150, 17)\n"
     ]
    }
   ],
   "source": [
    "env='MountainCarContinuous-v0'\n",
    "df_comper = pd.DataFrame()\n",
    "for i in range(1,6):\n",
    "  path ='COMPER_DDPG/data_using_done/'+env+'/train/trial'+str(i)+'/progress.json'\n",
    "  aux = pd.read_json(path,lines=True)    \n",
    "  df_comper = pd.concat([df_comper,aux])\n",
    "df_comper[\"Method\"]=\"COMPER-DDPG\"\n",
    "print(df_comper.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2059, 17)\n"
     ]
    }
   ],
   "source": [
    "df_ddpg = pd.DataFrame()\n",
    "for i in range(1,6):\n",
    "  path ='DPPG/data_using_done/'+env+'/train/trial'+str(i)+'/progress.json'\n",
    "  aux = pd.read_json(path,lines=True)    \n",
    "  df_ddpg = pd.concat([df_ddpg,aux])\n",
    "df_ddpg[\"Method\"]=\"DDPG\"\n",
    "print(df_ddpg.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Trial</th>\n",
       "      <th>LogCount</th>\n",
       "      <th>Task</th>\n",
       "      <th>Time</th>\n",
       "      <th>TotalItr</th>\n",
       "      <th>TMCount</th>\n",
       "      <th>RTMCount</th>\n",
       "      <th>e</th>\n",
       "      <th>Ep</th>\n",
       "      <th>EpItr</th>\n",
       "      <th>Done</th>\n",
       "      <th>EpRew</th>\n",
       "      <th>AvgEp</th>\n",
       "      <th>Avg100Ep</th>\n",
       "      <th>AvgLast50Ep</th>\n",
       "      <th>AvgLast10Ep</th>\n",
       "      <th>Method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>12-09-2023 21:27:33</td>\n",
       "      <td>200</td>\n",
       "      <td>0</td>\n",
       "      <td>191</td>\n",
       "      <td>0.009941</td>\n",
       "      <td>1</td>\n",
       "      <td>201</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.169679</td>\n",
       "      <td>-1.169679</td>\n",
       "      <td>-1.169679</td>\n",
       "      <td>-1.169679</td>\n",
       "      <td>-1.169679</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>12-09-2023 21:35:10</td>\n",
       "      <td>400</td>\n",
       "      <td>0</td>\n",
       "      <td>380</td>\n",
       "      <td>0.019882</td>\n",
       "      <td>1</td>\n",
       "      <td>401</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.480935</td>\n",
       "      <td>-1.325307</td>\n",
       "      <td>-1.325307</td>\n",
       "      <td>-1.325307</td>\n",
       "      <td>-1.325307</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>12-09-2023 21:42:47</td>\n",
       "      <td>600</td>\n",
       "      <td>0</td>\n",
       "      <td>564</td>\n",
       "      <td>0.029822</td>\n",
       "      <td>1</td>\n",
       "      <td>601</td>\n",
       "      <td>False</td>\n",
       "      <td>-2.088349</td>\n",
       "      <td>-1.579654</td>\n",
       "      <td>-1.579654</td>\n",
       "      <td>-1.579654</td>\n",
       "      <td>-1.579654</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>12-09-2023 21:50:37</td>\n",
       "      <td>800</td>\n",
       "      <td>0</td>\n",
       "      <td>720</td>\n",
       "      <td>0.039763</td>\n",
       "      <td>1</td>\n",
       "      <td>801</td>\n",
       "      <td>False</td>\n",
       "      <td>-2.483504</td>\n",
       "      <td>-1.805617</td>\n",
       "      <td>-1.805617</td>\n",
       "      <td>-1.805617</td>\n",
       "      <td>-1.805617</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>12-09-2023 21:58:15</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>890</td>\n",
       "      <td>0.049704</td>\n",
       "      <td>1</td>\n",
       "      <td>1001</td>\n",
       "      <td>False</td>\n",
       "      <td>-4.329440</td>\n",
       "      <td>-2.310381</td>\n",
       "      <td>-2.310381</td>\n",
       "      <td>-2.310381</td>\n",
       "      <td>-2.310381</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Trial  LogCount                      Task                 Time  TotalItr  \\\n",
       "0      1         1  MountainCarContinuous-v0  12-09-2023 21:27:33       200   \n",
       "1      1         2  MountainCarContinuous-v0  12-09-2023 21:35:10       400   \n",
       "2      1         3  MountainCarContinuous-v0  12-09-2023 21:42:47       600   \n",
       "3      1         4  MountainCarContinuous-v0  12-09-2023 21:50:37       800   \n",
       "4      1         5  MountainCarContinuous-v0  12-09-2023 21:58:15      1000   \n",
       "\n",
       "   TMCount  RTMCount         e  Ep  EpItr   Done     EpRew     AvgEp  \\\n",
       "0        0       191  0.009941   1    201  False -1.169679 -1.169679   \n",
       "1        0       380  0.019882   1    401  False -1.480935 -1.325307   \n",
       "2        0       564  0.029822   1    601  False -2.088349 -1.579654   \n",
       "3        0       720  0.039763   1    801  False -2.483504 -1.805617   \n",
       "4        0       890  0.049704   1   1001  False -4.329440 -2.310381   \n",
       "\n",
       "   Avg100Ep  AvgLast50Ep  AvgLast10Ep       Method  \n",
       "0 -1.169679    -1.169679    -1.169679  COMPER-DDPG  \n",
       "1 -1.325307    -1.325307    -1.325307  COMPER-DDPG  \n",
       "2 -1.579654    -1.579654    -1.579654  COMPER-DDPG  \n",
       "3 -1.805617    -1.805617    -1.805617  COMPER-DDPG  \n",
       "4 -2.310381    -2.310381    -2.310381  COMPER-DDPG  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_comper.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Trial</th>\n",
       "      <th>LogCount</th>\n",
       "      <th>Task</th>\n",
       "      <th>Time</th>\n",
       "      <th>TotalItr</th>\n",
       "      <th>TMCount</th>\n",
       "      <th>RTMCount</th>\n",
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       "      <th>EpItr</th>\n",
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       "      <th>EpRew</th>\n",
       "      <th>AvgEp</th>\n",
       "      <th>Avg100Ep</th>\n",
       "      <th>AvgLast50Ep</th>\n",
       "      <th>AvgLast10Ep</th>\n",
       "      <th>Method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>03-10-2023 15:11:02</td>\n",
       "      <td>200</td>\n",
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       "      <td>0</td>\n",
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       "      <td>-0.886030</td>\n",
       "      <td>-0.886030</td>\n",
       "      <td>-0.886030</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
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       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>03-10-2023 15:11:28</td>\n",
       "      <td>400</td>\n",
       "      <td>185</td>\n",
       "      <td>0</td>\n",
       "      <td>0.019882</td>\n",
       "      <td>1</td>\n",
       "      <td>401</td>\n",
       "      <td>False</td>\n",
       "      <td>-2.731218</td>\n",
       "      <td>-1.808624</td>\n",
       "      <td>-1.808624</td>\n",
       "      <td>-1.808624</td>\n",
       "      <td>-1.808624</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>03-10-2023 15:11:55</td>\n",
       "      <td>600</td>\n",
       "      <td>275</td>\n",
       "      <td>0</td>\n",
       "      <td>0.029822</td>\n",
       "      <td>1</td>\n",
       "      <td>601</td>\n",
       "      <td>False</td>\n",
       "      <td>-3.107946</td>\n",
       "      <td>-2.241731</td>\n",
       "      <td>-2.241731</td>\n",
       "      <td>-2.241731</td>\n",
       "      <td>-2.241731</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>03-10-2023 15:12:22</td>\n",
       "      <td>800</td>\n",
       "      <td>317</td>\n",
       "      <td>0</td>\n",
       "      <td>0.039763</td>\n",
       "      <td>1</td>\n",
       "      <td>801</td>\n",
       "      <td>False</td>\n",
       "      <td>-3.694801</td>\n",
       "      <td>-2.604999</td>\n",
       "      <td>-2.604999</td>\n",
       "      <td>-2.604999</td>\n",
       "      <td>-2.604999</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>03-10-2023 15:12:49</td>\n",
       "      <td>1000</td>\n",
       "      <td>349</td>\n",
       "      <td>0</td>\n",
       "      <td>0.049704</td>\n",
       "      <td>1</td>\n",
       "      <td>1001</td>\n",
       "      <td>False</td>\n",
       "      <td>-4.229462</td>\n",
       "      <td>-2.929891</td>\n",
       "      <td>-2.929891</td>\n",
       "      <td>-2.929891</td>\n",
       "      <td>-2.929891</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Trial  LogCount                      Task                 Time  TotalItr  \\\n",
       "0      1         1  MountainCarContinuous-v0  03-10-2023 15:11:02       200   \n",
       "1      1         2  MountainCarContinuous-v0  03-10-2023 15:11:28       400   \n",
       "2      1         3  MountainCarContinuous-v0  03-10-2023 15:11:55       600   \n",
       "3      1         4  MountainCarContinuous-v0  03-10-2023 15:12:22       800   \n",
       "4      1         5  MountainCarContinuous-v0  03-10-2023 15:12:49      1000   \n",
       "\n",
       "   TMCount  RTMCount         e  Ep  EpItr   Done     EpRew     AvgEp  \\\n",
       "0       96         0  0.009941   1    201  False -0.886030 -0.886030   \n",
       "1      185         0  0.019882   1    401  False -2.731218 -1.808624   \n",
       "2      275         0  0.029822   1    601  False -3.107946 -2.241731   \n",
       "3      317         0  0.039763   1    801  False -3.694801 -2.604999   \n",
       "4      349         0  0.049704   1   1001  False -4.229462 -2.929891   \n",
       "\n",
       "   Avg100Ep  AvgLast50Ep  AvgLast10Ep Method  \n",
       "0 -0.886030    -0.886030    -0.886030   DDPG  \n",
       "1 -1.808624    -1.808624    -1.808624   DDPG  \n",
       "2 -2.241731    -2.241731    -2.241731   DDPG  \n",
       "3 -2.604999    -2.604999    -2.604999   DDPG  \n",
       "4 -2.929891    -2.929891    -2.929891   DDPG  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ddpg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Trial</th>\n",
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       "      <th>Avg100Ep</th>\n",
       "      <th>AvgLast50Ep</th>\n",
       "      <th>AvgLast10Ep</th>\n",
       "      <th>Method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>12-09-2023 21:27:33</td>\n",
       "      <td>200</td>\n",
       "      <td>0</td>\n",
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       "      <td>False</td>\n",
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       "      <td>-1.169679</td>\n",
       "      <td>-1.169679</td>\n",
       "      <td>-1.169679</td>\n",
       "      <td>-1.169679</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>12-09-2023 21:35:10</td>\n",
       "      <td>400</td>\n",
       "      <td>0</td>\n",
       "      <td>380</td>\n",
       "      <td>0.019882</td>\n",
       "      <td>1</td>\n",
       "      <td>401</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.480935</td>\n",
       "      <td>-1.325307</td>\n",
       "      <td>-1.325307</td>\n",
       "      <td>-1.325307</td>\n",
       "      <td>-1.325307</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>12-09-2023 21:42:47</td>\n",
       "      <td>600</td>\n",
       "      <td>0</td>\n",
       "      <td>564</td>\n",
       "      <td>0.029822</td>\n",
       "      <td>1</td>\n",
       "      <td>601</td>\n",
       "      <td>False</td>\n",
       "      <td>-2.088349</td>\n",
       "      <td>-1.579654</td>\n",
       "      <td>-1.579654</td>\n",
       "      <td>-1.579654</td>\n",
       "      <td>-1.579654</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>12-09-2023 21:50:37</td>\n",
       "      <td>800</td>\n",
       "      <td>0</td>\n",
       "      <td>720</td>\n",
       "      <td>0.039763</td>\n",
       "      <td>1</td>\n",
       "      <td>801</td>\n",
       "      <td>False</td>\n",
       "      <td>-2.483504</td>\n",
       "      <td>-1.805617</td>\n",
       "      <td>-1.805617</td>\n",
       "      <td>-1.805617</td>\n",
       "      <td>-1.805617</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>12-09-2023 21:58:15</td>\n",
       "      <td>1000</td>\n",
       "      <td>0</td>\n",
       "      <td>890</td>\n",
       "      <td>0.049704</td>\n",
       "      <td>1</td>\n",
       "      <td>1001</td>\n",
       "      <td>False</td>\n",
       "      <td>-4.329440</td>\n",
       "      <td>-2.310381</td>\n",
       "      <td>-2.310381</td>\n",
       "      <td>-2.310381</td>\n",
       "      <td>-2.310381</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Trial  LogCount                      Task                 Time  TotalItr  \\\n",
       "0      1         1  MountainCarContinuous-v0  12-09-2023 21:27:33       200   \n",
       "1      1         2  MountainCarContinuous-v0  12-09-2023 21:35:10       400   \n",
       "2      1         3  MountainCarContinuous-v0  12-09-2023 21:42:47       600   \n",
       "3      1         4  MountainCarContinuous-v0  12-09-2023 21:50:37       800   \n",
       "4      1         5  MountainCarContinuous-v0  12-09-2023 21:58:15      1000   \n",
       "\n",
       "   TMCount  RTMCount         e  Ep  EpItr   Done     EpRew     AvgEp  \\\n",
       "0        0       191  0.009941   1    201  False -1.169679 -1.169679   \n",
       "1        0       380  0.019882   1    401  False -1.480935 -1.325307   \n",
       "2        0       564  0.029822   1    601  False -2.088349 -1.579654   \n",
       "3        0       720  0.039763   1    801  False -2.483504 -1.805617   \n",
       "4        0       890  0.049704   1   1001  False -4.329440 -2.310381   \n",
       "\n",
       "   Avg100Ep  AvgLast50Ep  AvgLast10Ep       Method  \n",
       "0 -1.169679    -1.169679    -1.169679  COMPER-DDPG  \n",
       "1 -1.325307    -1.325307    -1.325307  COMPER-DDPG  \n",
       "2 -1.579654    -1.579654    -1.579654  COMPER-DDPG  \n",
       "3 -1.805617    -1.805617    -1.805617  COMPER-DDPG  \n",
       "4 -2.310381    -2.310381    -2.310381  COMPER-DDPG  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.concat([df_comper,df_ddpg])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Trial</th>\n",
       "      <th>LogCount</th>\n",
       "      <th>Task</th>\n",
       "      <th>Time</th>\n",
       "      <th>TotalItr</th>\n",
       "      <th>TMCount</th>\n",
       "      <th>RTMCount</th>\n",
       "      <th>e</th>\n",
       "      <th>Ep</th>\n",
       "      <th>EpItr</th>\n",
       "      <th>Done</th>\n",
       "      <th>EpRew</th>\n",
       "      <th>AvgEp</th>\n",
       "      <th>Avg100Ep</th>\n",
       "      <th>AvgLast50Ep</th>\n",
       "      <th>AvgLast10Ep</th>\n",
       "      <th>Method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>5</td>\n",
       "      <td>247</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>04-10-2023 00:15:45</td>\n",
       "      <td>49200</td>\n",
       "      <td>15979</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999</td>\n",
       "      <td>2</td>\n",
       "      <td>9936</td>\n",
       "      <td>False</td>\n",
       "      <td>-159.297384</td>\n",
       "      <td>-225.415867</td>\n",
       "      <td>-262.224560</td>\n",
       "      <td>-71.862668</td>\n",
       "      <td>-133.669135</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>5</td>\n",
       "      <td>248</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>04-10-2023 00:16:11</td>\n",
       "      <td>49400</td>\n",
       "      <td>15983</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999</td>\n",
       "      <td>2</td>\n",
       "      <td>10136</td>\n",
       "      <td>False</td>\n",
       "      <td>-161.179071</td>\n",
       "      <td>-225.156848</td>\n",
       "      <td>-259.923544</td>\n",
       "      <td>-74.989636</td>\n",
       "      <td>-139.346456</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>5</td>\n",
       "      <td>249</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>04-10-2023 00:16:37</td>\n",
       "      <td>49600</td>\n",
       "      <td>15985</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999</td>\n",
       "      <td>2</td>\n",
       "      <td>10336</td>\n",
       "      <td>False</td>\n",
       "      <td>-162.441780</td>\n",
       "      <td>-224.904980</td>\n",
       "      <td>-257.627073</td>\n",
       "      <td>-78.035952</td>\n",
       "      <td>-145.087001</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>5</td>\n",
       "      <td>250</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>04-10-2023 00:17:03</td>\n",
       "      <td>49800</td>\n",
       "      <td>16027</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999</td>\n",
       "      <td>2</td>\n",
       "      <td>10536</td>\n",
       "      <td>False</td>\n",
       "      <td>-165.686367</td>\n",
       "      <td>-224.668106</td>\n",
       "      <td>-255.361442</td>\n",
       "      <td>-81.063723</td>\n",
       "      <td>-150.866840</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>5</td>\n",
       "      <td>251</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>04-10-2023 00:17:28</td>\n",
       "      <td>50000</td>\n",
       "      <td>16169</td>\n",
       "      <td>0</td>\n",
       "      <td>0.999</td>\n",
       "      <td>2</td>\n",
       "      <td>10736</td>\n",
       "      <td>True</td>\n",
       "      <td>-174.670526</td>\n",
       "      <td>-224.468912</td>\n",
       "      <td>-253.179333</td>\n",
       "      <td>-84.153550</td>\n",
       "      <td>-156.905478</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Trial  LogCount                      Task                 Time  TotalItr  \\\n",
       "246      5       247  MountainCarContinuous-v0  04-10-2023 00:15:45     49200   \n",
       "247      5       248  MountainCarContinuous-v0  04-10-2023 00:16:11     49400   \n",
       "248      5       249  MountainCarContinuous-v0  04-10-2023 00:16:37     49600   \n",
       "249      5       250  MountainCarContinuous-v0  04-10-2023 00:17:03     49800   \n",
       "250      5       251  MountainCarContinuous-v0  04-10-2023 00:17:28     50000   \n",
       "\n",
       "     TMCount  RTMCount      e  Ep  EpItr   Done       EpRew       AvgEp  \\\n",
       "246    15979         0  0.999   2   9936  False -159.297384 -225.415867   \n",
       "247    15983         0  0.999   2  10136  False -161.179071 -225.156848   \n",
       "248    15985         0  0.999   2  10336  False -162.441780 -224.904980   \n",
       "249    16027         0  0.999   2  10536  False -165.686367 -224.668106   \n",
       "250    16169         0  0.999   2  10736   True -174.670526 -224.468912   \n",
       "\n",
       "       Avg100Ep  AvgLast50Ep  AvgLast10Ep Method  \n",
       "246 -262.224560   -71.862668  -133.669135   DDPG  \n",
       "247 -259.923544   -74.989636  -139.346456   DDPG  \n",
       "248 -257.627073   -78.035952  -145.087001   DDPG  \n",
       "249 -255.361442   -81.063723  -150.866840   DDPG  \n",
       "250 -253.179333   -84.153550  -156.905478   DDPG  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='TotalItr', ylabel='AvgLast10Ep'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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/hd1D7fVhx9GOlVBYG3YSzTsNVvwNZp8AHz8Ja5+CY38OxZMSxzKDmK/8gsAHj+BqWdO3eaUyk3nWUISb8Y85/7OoH/0tduOkA9n5mUeoKHASCFmsb+zE0BQEYSnLUBVClo1l2+iKQncwhK4q+IMW+U4NVRFsa/Vy8YPv4g+a/PKsPbnl6Y9ZWd+O21CpLXbxjcNmoKuCgGmjKwLLhn2nlrCqvp3pFXnUFLkGnnz79vB7omYPfBveYPP/HmamNxzzr7bqeMLcl3LRionKp3Y1j5jLOEj5kLnKJhwEabXzKBKdnKy+RrVoHuBkknS4LngOxWVVfKn1Tl635rJUWUWB6A67OpddERbMWzbAR/8HSy8BVzFM2AuaP4W8irBz0FUUvhaUhe/tO7q62bBuFXd8AM+s2hFzvjnVBcytLmBLSzelHoOP6tsocRsgBLNcbZyyVx2Vahdrffk8+OQLfOItQMOkSHQCgpX2JOLF2Uxz59l7cfzC6qyMnW4MIVNfxyB3vrCeHe1+bnl6bb9C3Qsf7+S8+97mu8fM4uJDUghvvSIdhNM4H/pc+Pdr2hL3DQXgprqwXfc76/utC5YOw6lxdcvTa+lsWsFPT1mAlUJqLuxJl4xn1fawU+KFNTs5cVFN3/b+JOtXPmnkl89+wjlLkwQYkCDSAZzymzf535dKGIxBPZVIB6BiDmKkwTPaIh2AIPyf0E6KenW7MaO9AihFOokkQqht22hPQSKRSEaOrib43+3QtC4ssgzE498M//vEFZFt2z+AK3qEuJZNsPox7E2vIT5+EhWIl3ikSJeaBJEOYNOrHH7D43Tgzsg5zrv/7b7fuwMma3d08o2/vjeoMfLo5gvut/i+dW/S553AzKjHc5TNzFE2x+zzNe0xJogmJNnjav0BaAMEHK2+E3miYQX8/dzYnf95UVpj5gMLgd8COMMuVZ0QOyjmscb9qdrVzM3BMzlJ+ye/0Z6D7qiDe94C04Bje46Ppt4u4VHzQNz42WUX8hn1ZX4ROp21di2HKB9wn3kMAbS++8qwr3Jwwt4fX9+YNaEuXaRQNwYx1IHfaB9ubeW8+8IX2J//92M+s1ctlQWDcMHdfwIc8M2wlRrCKlbrprDl1tsc/lcZuqsOQB+GUBey4M9vbA4LdSmUOo1Qv2NYccpcf+bSc34frrn2zqZesWRgI6qFwk//9T7XDrhnenR5R9eCP5J02GmsyEkkEsloIZMRJBLJeMe2oX0b/GJeZsbr2M4BNz3PmXtP5NJXlgDZ9sSMX5rtPEp6ajxHM1XU84GdaM5QsDhLfYHXrLlstLMvPtSJHdyn/zxcrsUa3lhSpBsf9KaS17KLi7Vwmu9p6qtDGqtGNPP1njF6ucP4dd/vV+p/TXnsFquc74cuQMPChZ8XrD3wR1Un30Osw0Jg28VDmlsmkULdGMTjGPi/7danY1eh9r3hOV789iFMLkvTqbTxlfDPNW1Q/z78+TSYc1LUDsO/SUlHcExF9Nl7Bbda0ciPtT9yb+gE3rZnoyX9ZojUMTDjBL7BvCI1jW8dgU1ze9fgOhMM85xjnd6Vj8CgfIgSiUQysgh7/F+PJRLJbswnz8CDp2d82G2tXn79wjoulXegwyJVnDwthVB3kfoY39X/xi67gKfMvSkXrXwleDnZkEqPVN7ht8ZtGR9XIskEE5VGHjRujNnWYufRhZNasQsIu//Otx4ajenFMLzcRcmokOeMfLulcoF1BxLdZE+tbIjdYKWZSvnoRdDdBMvvG/yx/TAcR100vULdL/Q7OVJ9l787rgOSC1vR2+KFuniHHYT/vk2diU42LY00VAUro+La7iHUhdlfWTmq85BIJBKJRCLZLWn4KCsiXS8uKdING4Ng0u3TlPqk28/WngegTLTzee05jlKXM1NszeicHAS4Xf+1FOkkY45i0dkn0kHY/VcVHP0SJ/JSOQbJi3LUdQfMWIedbYOvle5AopDUFb8tkLyGWwKhJMXrh+gmCJmR44Yn1EVWgKyeISdEfcAguZimYWISbq5h2XZM2myyDNqb/ruGe15KrD+nD5BWC6Bgo4uB90sXTWS3Rl2uUEkzs5UtA+8okUgko4W9e1yPJRLJbsbqf8PDn8/qKVwqZLns8rgnWdorwEyxjTLa6MJBlWihzfZwsPJBjAjRy4PGDTxjLqZKNPOctRcPmkdQRhudODlVfZUq0cxcsYkj1Xdpt13cFTqZ/ZWVFIsOdtmFqFhMFg0E0bARTE8hEkokY5Eqc/Tfz1KoG4M4tIjA1e4Lxgp1/74Mlt/PVNeNrCS28UGXP040CnYzILad3D03RKHOF4oS6rQBhDor9TnsaKGuxwlnxRlE1STCVqyjLtZFl8ydmEykg3SFOist5126ZLuZRC4gsMnrp6GGRCKRSCQSiSQLvHE3/Pd7WT+NQ7GlUJcljlSXc6S6PK19y0Vbn9PuMPV9XPj5of5g0n0LhJfv66OfCiiRjBRl5s7RnoJMfR2LRJnSaPfGCUbL7wfgC77Ei2mCUJeOo87fAVYSUSpeqOvaBb8/Ct59IOkwT61sYN3OTvxBk95qcJqSui6CbdvJz5uEPqHOjh0vlaOuF9O2Me1oR136VerSSn0VmRXqktfcG3+IDNQ/lEgkkmwia9RJJJLxQiBoEnr06yMi0mmE0BUZ5+UieyjrRnsKEknOIHIgc0IKdWOQaHGp3RepURCIcqsFrUQRrHMoQp0VAitJHYT4m5SXfgZb3oTHLknY9bX1u/jqA8s54raXcD79XV40LsdD/66pL/7hLex+hLrev4Bt25g9DxIcdUmELSVqm2XZMaa9wTTx09OqUWentV+67C6OOkUKdRKJJMeRnQolEslYxrZtAoEgv/7jX/H9tBbtgz+PyHkL6ULJgRtgSSJyoVwiiWIwwkCWkELdGCS6rlq7NyKifborUq/An0SoS6hbl45QZwaTOtuu//dHeKPH62esVfXtfb97PryfycoOTlNf6dfB9sonu+j0JqmN10Nv6mvAtPpSVi3ScdRFCXUJjrqUp0sgndpzCnZGxTXpqJNIJJJcYfe4HkskknGAZcKWt8HbQuuK//LVH1xDyzW1GDeUccmGiygQaZTCyRCFoitm0VySO8gFKIkkihzInJA16sYg0d1Kox110amkZhINdkiOOjOQtEbdP9/bSn7Zp1x6+IzwBkVNOYSRpBadQTCh62o8ShofEF/Q6hP87LivmORdX6NSXy07Zg79CYdO/Fyl/YWnrCX8z1qQdtfX7DjqxreQJR11Eokk1xE5sNIqkUgkKbFMePMeWPE3qH+vb3MRcI8+arOikC78lIzeBCQpkQvlEkkUORDnSUfdGCRaUIquURcIRbbHC3XVNHFA2xMQ8kc2BtNJfU3uqFOw2dYSlb6qpNZ8jSTdXQ3MyPs/xQfBTpZy2/tcjyjnD5l9NfvihboBa9RZsV1f+/t+ulB9gi9qz/CgcSOQfuprZmvUmWmfe6wisGWgIJFIcp8cWGmVSCSSlLx5Nzx1ZYxIlwsUis60FuIlI4901EkkEewcuE5JoW4MYqZIffUFI4JavFD3pONKvtl9B7x6e2RjWo66UEqhTkRf0ZXUy3PJHHUaocjrSNZVFrDMgdNLrfoP+VrXbyihPSH1NVnaqSqiU19j6/2Z/SjnE0VjwvwHQsFCSyNFNl16HYIOAhkbMxeRQp1EIsl95HVKIpHkKJ2N8NRVoz2LpBTShZJGDC0ZeWT8LZFEyAXhWqa+jkGiBaW2KKEu4O3o+z2+sUKx6Klf9+mLcEhPV6e0mkkEw3Xq4ogWvID+HXVJhDpdhCLOwKRFZW0sM7VzrFe0qvrrkZwEaHpjgjiZrKZbtMPNsmMddaF+UnHjxzbSEursjNaV00R47g5SOw3HOtJRJ5FIxgIy9VWSTWzb5u/vbGVOdQELagtHezqSsYRtwx+OGu1ZpETWqMtdZPwtkUTIhc+DFOrGIFaKGnWmtzPZ7rHozsjv6TaTSPJGFfFfstE16mybaLudx5H4NotJfU3iqHMQxE4iEPYS75abJbbgx4jdRyRx1EXN27Rim0mEzNSBQzpptfFkOvU14qgbv0Id5MYKhkQikfSPvNGUZI9X1+3iu498CMDGm44f5dlIxhQf/BWaPx3tWaSkkC5U2fVVIpHkOLkg1MnU1zFItJ4UXaMu5I10V00p5ujuyO/BNLo8JUl7hSQF/9Wo1Nc4gc2tJzaa0AhFRLIk53AQ6Df1Nd6pFkJN0vW1f0ddfDOJ/ppbhIh9DVoSETCecDOJLKS+ivEr1Aly48IokUgk/SEddZJssqXZO/BOEkkcVncL/PNroz2NfikUXYmL/ZKcQC6USyRR2BbBfkw8I4EU6sYg0S6wGEedP5L66kxVx0wbiqMukQShLrpGXSg2wFSUxEu/Tv+pr06SN7HoJd5RZyYR6pLWqEtIfY08FzQznfpqZdhRZ/acezwLdbbs+iqRSHIeuaAgySZF7khMFQhJUUMyMD6fF/PnM0Z7GgMSdtTJ93RuIr/XJJJeLNsm1I82MBJIoW4Mkir11fJHUl+dIiLUxTQf0F2R3wNppMqayQW/hPoSIuqtFPQNOKyOSd/LsBK/sJ0igNVv6mu8o05Jy1EXfVzQjE19NZPMo5f4mn+jkfqq7TaprzJQkEgkuY68TkmyR3TJkOau8d1ASjJMvK10v/d3gjdNRR8D8aEmTFmjLkeR8bdEEiEXPg+yRt0YJMZRF5X6avuSO+oKiDjnTKFFkjgD6aS+pumoi94vzlGXLENIJ0TQSu2ocxDE6kc4i68/F0KNkelURaRw1EXGDJlWxNXH4Bx16Ql12XHUjWehTjaTkEgkYwGZuiXJJtGxSVOXn6pCZz97S3Zb1r8AD5yCe+A9cwpVdn3NSWTqq0QSIRcyvKRQNwaxUqS+4o8IctFCXZGIbA8G/FFCXRqpr/7krruE1bDoNNV0HHXRXV+TpLg6CfTbTCJZjbroD5SqiKQiWfS2oGnFdX3tz1EX+/WVTu05BTutWnbp0jv38VyjDhLdkhKJRJJzyBp1kiwSHZs0dUpHnYTwNad1E3hbw2VpPnoE3vzNaM9q0AhsGeflKNLpKJFEkQNxnhTqxiAxqa/eILZtI4SISWV14e/7vZDI9lAgyu0WTEOo87Ul3ZygMpupHXXJ0GJSX5PVqAuAmVrkSqhRZ6sQJYrZto0qkqS+CqsvYykQl/oaStJMQojw5zQ69TXdJhEKNnpWur6O36BdQNL/N4lEIsklZDMJSTaJjkdk6quEzp3w0Nmw9e3RnsmwEYCQNepyEumok0gi5MLnQQp1Y5DoBiSWDV0BkzyHhghG16iLCGfRjjozEOV2S8tR1550s4JFIGYiUYJUcGChziAUERyTpb6KIFaKtFtIXqMueiXItpOnp0ZvC5lWTKfXZAUjdUUhYFqEooQ6g2B6XV9FZlNfe885nlNfQa7oSSSSsYAU6iTZI3pBdlenv589JeOe/3x/TDrnUhF21GUuNpZkDll6RiKJkAslTmQziX646667mDJlCk6nk8WLF/PKK6+M9pSA2NRXCLvqANRg8tTXwqgadVZ0Wmo6Nep8qYQ6G390J7JoUS2lUBeZd0zX1xSOOjvJ9l7ihToTFTtK+7ZsK7mjLiH1NWqMJI46TQ2PacUJdek45cI16jJXh6P3Nafj5huryJQIiUQyFsiFAE4yfol2+0tH3W6Arx02vxmbamWZ8Ku9xpVIBz21iKWjLieRQp1EEiEXHHVSqEvBww8/zGWXXcYPfvAD3nvvPZYtW8axxx7L5s2bR3tqCYJSW49Qp0Q76qJSX4tEZHusUJdG19f+HHXRQl1M6mvyGnXRAkx6qa+pBal4p1oIBcsWMc8nd9RFdX21YlNfg2Zi4KApiR9TB6H0a9Rl8Gau9/VkcszcQwp1Eokk98mFAE4yfjFljbrdA38nrHsObpoIfzgKPnw48tzy+6F5/ahNLVsI0mvIJpFIJKNJLgjXUqhLwW233cb555/PBRdcwJw5c7j99tuZOHEiv/nN6K9smSkcdVoo4pAzhNnnHiuISn2NEdHSSX3tp0adP2Rh2zYX/PEdXlu3I/JkCkdddF07I7qZRIqur3aSJhO9JKa+ajENHzQ7lKLra5SjLjRw6qumKj1zj5zPIJhm11c7w4668DnjO96ON3LhwiiRSCT9IR0hkmwSI9RJR934w9cG//4W3DgB/nxaZPv7f4n8vvHVkZ/XiGBLR3KOIkvPSCQRcuF+VAp1SQgEAixfvpyjjjoqZvtRRx3Fa6+9lrC/3++nvb095ieb5PsaWCw+pjeVtC2JUAeR9NeiqGYSdiiq1kkwndTXVEKdRSBk0tjh59nVO2hoiXLnpXDUKfGOut5ANFnXVxHA6sdRFxbqokQ21Jj0VK1HuosnxlFnWjFpxMmaSfQ66qKP00Uo7dRXPaNdX62EuYw3BLLrq0QiGQuMfgAnGb/ECnWyRt24YNc6ePwyWP8C3FQH7/whcZ+e7JSgadHSlTyWHg+oSRboJaOPdIpLJBFyQaiTzSSSsGvXLkzTpLKyMmZ7ZWUlDQ0NCfvfeOONXHvttSM1Pfbf+VeudDzCh9YU7gsdw3/e0FjoaUELdsTs5yRAFy4Koxx1oleos6xhCnVhR11vQ4kYh1lKR12U2EUo4gxMmfqaummCJmJTW0MoMTXqdMwUjrrIHEKWHeuosxIFIr3HURc9lkEoLadcuEZdJru+mglzGY9IoU4ikeQ6tmURNK2+7wiJJJMMNvXVHzJpaPMxqdQz8OCdjaC7wJE3nClKBsIyYdP/oGkdfPoirPpXePvy+1IeYob83P70x9zx/Dru1hs5Rh2ZqY4kAls6t3KUXBAmJJJcIRc+D1Ko6wchYtcWbNtO2AZw5ZVXcvnll/c9bm9vZ+LEiVmbl2WD39ZZqGzgF8ZvaNz8F17+6yHMDzTG7Bdx1EWEOiXUDd5WUNL89u9uSrpZwSYQsvAGeuumRYlHcY46u0eQUxKaSfTukCr1NfUXuYqJESWWmagJjr1kzrNokSsQsmI6qyV11KmJjjqDILpIr0ZdJkW1iKNu/Ap1MoCTSCRjAtsiZNro4/BGWjL6RJc4aezw0+UP4XEkhuxd/hAuXeWiB5bzwseNPPSV/dhvamnqgbua4JbpkFcF3/44G1OXWBa89kt49ppBH7p6axN3fLoOGL+LsuHMifH52sY6ihh9YUIiyRVywWEqhboklJWVoapqgntu586dCS47AIfDgcPhGKnpMevcO1m58WKmr/sTyup/UW628hn/vxL2qxFNbLPLYxx1iumDLW+BkqYLwNucdLMiLPwhi+4eoS4mFTQ4cDMJHbNPwCOJIOcQgaQpsdFjOaI625q2EtPlVRfJHXVaVCpqKK6ZRKifZhLxjrr0Ul/ttPZLl14Ba7w7zsb765NIJGOfRbWFoz0FyTgmehHRGzTZ0NjF/Lj33Jbmbo647SWOnlfFCx+HF2rvfGFdcqEu6IPNr0F3T0zX2RDuMJpk8VkyDII+ePB02PjKkA6PblSm5ICbIxvIBdncJRccRBJJrpALtTRlzkYSDMNg8eLFPPPMMzHbn3nmGfbff/9RmlWEmiIXe+2xhIJTb0U//7+8PeUiVtuT+p5vt10A/Na4lf2UVRRG1ahT7SA486F1S3onS9Fworfra69QFy1keb3Ju8mKOEed2V+NOgLY/aS+qlgxjjogRqjTUohpakKNushzSZtJKL2pr5HjHCLdZhKZTX3trXc3vh11spitRCLJfaaVufsc1xJJpol3+K/d0dFXj7iXO57/BH/I4rEP6vu2fdqYoknYf74LD5wKj10a2ZZO+RNJ+uxYCddXDlmkg9j4brwuWgpkjTqJRJL75EKEJx11Kbj88ss555xzWLJkCUuXLuXee+9l8+bNXHTRRaM9tQiqjqNmDgtOvpw33lnGfa+9hxbs4NAjTmDRG5dR4V3Pn/QbYw5xW11Yr/8GpbguvXP008HVHwziDYbFsujgorWtHStJmkZMaqowB0x9bWr3MjnFtDRMDBEJWlVhxdXAM5N2R9WGmPoaLUTqhGJWPVMR7vqa+WBkvAZvEBZzx/Prk0gk4wOPoYCsTyfJEmZcPLKjw8e2lm4KnAV9JViSiXLbWpPHbLz7x/C/wahjfO1gpFHTTjIwa56Ah84e9jBGjKNufMZCAhvFDuXGXbAkBumok0gi5MLnQQp1KTjzzDNpamriuuuuY/v27cyfP58nn3ySSZMmDXzwCOMsqmT+nktxGQpOp4uZ06exk2/j/+RBHFsj7d39to5DBGF1YppsSuzkgYKCjT8QpK21FYgVwMzuVj7Z0cHcmkIMLXIjo0a94Q2C+HrceKmaSbR2pl7tjXfUhd1rsc0qkgk+Mc0kQqEBm0loPTdisTXqBtH1NQ1Bb7CMZ0cdxDojJRKJJCdJ8d0oGVvcdddd3HzzzWzfvp158+Zx++23s2zZstGeVkxHegCBYFurj7I8BxUFTgA27Erunkuop7xzdfKT+NuB6kxMd/eiYwd8+BDsXAMn34nZsQM1AyIdEFP/eLwuWooM12+WZI5cECYkklwhF1JfpVDXDxdffDEXX3zxaE8jLUpLSmiZujcBvxetoBLP5D0IFXnYpZYxYdM/6bYd7Ou/k+Pdq7ms6kPKmt5G87fGjLHamsgcJZISawuBsJNftAUWvpDNp5+uBZSY2m8FoV2sbG1HUQQzKvJjjunFQZCmbn+4a16y1FcRQFdSf2GEa9QFYx4nNpPo31EXDPgwWyMpI8lSX/XeGnUiukZdeqmvAjsrolMyp+B4QdYukUjS477Q0XxqV/MT/f5+9/tJ8PMsVj7hOPWtkZmYRDJGePjhh7nsssu46667OOCAA7jnnns49thjWbVqFXV1aWYdZIl4h393IISuCD5t7CLfUNC7t9PUlbwb7Efb2lkQXc/urv2Sn8TfkanpZp6gD3Rn4nbLgg0vQfUicJeM2HS6/CF2dfqZtPxGeO2Ovu1/Nw/iva0d3JCh80Qv7o7nRUshFzpykvFaF1EiGQq5YPqVeRvjBCEEk6tLmVRbg65plNXNQa1eSHDm8dxZ/D2+Z1xJB25etPegdfGlvLvsd3y814/YfOwD2IpO1+wzODbwM47y/4yPxAxWLvg+7bPOTHk+FYugJfD5wo0joh1marCDCaKF+lYfH9W30R0I9R3Ti4Mgnb4Q21q6kzoTHASTOu0i5zcTHHVqGkJd9Cpe0ASrfVvf42TNJHoXpeMddVoaXV9VrIw2k+glWTfb8cR4XUWWSDLJKnsSD5hH8ZPgF3jFnJ9yv4fMw3jJWjSCM9tNkDeaY57bbruN888/nwsuuIA5c+Zw++23M3HiRH7zm9+M9tRiynIArGnooNit09od4JX7rkT71UKOUt5OeuyzaxrY1NSVMEYCvrZweZNQEsGvnxrBWefJ78AN1dC4NvG5D/4KD5wC9x6SlVP3/s3u+98Gfv38JxDohk9fZMuNS7jvtu/HiHQAj7+7gY07WzJ2fn23SH2VXV9zFemok0iiSGFWGkmko24coasKem/NHCFQS+rIq27jvGWCV7xTePzxHXSHFJzeBgzdTahgAuvVyWw45XVCzVuBbtbaEznRey1/LhH4/LXU1bVRtuVpEAJhxXajMm3oVAqAUMyXrmIGcHdtYUJFOfVdAXZ1+PqO6cUhQqjYNH38BrUrf5bwRnQSQNipxTANCyPOURffVTbZylC0yBW0BaazBAgHWSF/N5ghUCOz6Y1zY7q+imBCI4tkhGvUZT71dTwHOEKAkgMXRokk17Hs8LX+9+Zx/N48ji9ZTzFLbOZs7YXY/RAy+M4G/s6wmKHqoz0TyRAIBAIsX76c73//+zHbjzrqKF577bWE/f1+P36/v+9xe3t7VufXu27oMlS8AZOnV+1AAMctqObkHb8D4Bb9Hhb694470mbTrm5Wb2/HGzCZ6glgpDqJtxXq34eQDxwFULUANCPstNv+IagG5JWDuwwceUN4DTaqMghPQsgPj14EK/8PgG2P/4QJX34gdp9V/wz/27ppUHOxbZuAaeHQ1ITnOv0hnlsd/vu+9uhvOOGIw7j2iXCtv4veOxmtYxuzgWv0DQnHBtFwktzZOBSiY8vxu2gpMydyFemok0gi5MJ1SjrqxjG6plJWNxeluI4il4IA2oOCf+yoxBYamquAqgI3eS43bb6I+GMDW7sVivMMdk7/LMv3v5NtU86IGbv3Yt7Zo5XFOMdsEyXUjaNzKxV5Dpq7w0GMImK/AAwRYvEzn0GrT1wVdhJEC6ROy1CEFa63FzWf2GYVyRs+RO8TtGzMKFEoFPRD0yfh1Irel9LzvBrvqEunRp3IbNfXXsazo06mvkok6RGK+/r+o3k0V4Uu5BlzMY12JO3NTlOo28t3d8bnOK4JdI6u60gyLHbt2oVpmlRWVsZsr6yspKGhIWH/G2+8kcLCwr6fiRMnZnV+IthNCe2cMr+UL+xTgyLgqVU7uPGJj/r2CRIrOp2hvsgnji9S3vgaZXkONjZ1s2nt+6lP0ro5/D4OecHbHO4C274dtr0Lm98Ib2tYAVvegO0rwrXZNrwMbdtSj9nDbc+sZY/rnmZ9Y2fS5x94fSM3/WdN7MYnrugT6QDe2NCceKCSnr8gaFo0dkSE1csefp8F1zzNjnZfwr7fe+RDvvnQ+zz8twe4SdzBgc+d2vec1tH/aw3Zasyi8XDRdwOhTjYNy2WkUCeR9CJTXyXZRzOwK+bhKZnAmUvCgeWdb3fyZMdUuisXE3KVYjgc4VXTKNa1hm/vXIZGSX4eOxdfwXtL72CdMReAAhEuYtwZ6BWyIoKUMIOEnMXonfU4gu249XBgFS/AaJafVDhEAN23M/XLwowJjuJTX3XMpIFAdC29kBlxzAGE0KBpPbRs7LO79j6dkPqaVjMJOwupr+O/CK8M4CSSgbFSfH1fGLyCA/2/7HscQE9rlbyZgozNbfdA3tCMB2KaLpCkEUMPV155JW1tbX0/W7ZsSdgnk8zY+R9ed1zCZzf8kC/wX360t8ChQmHXp337hJ1ckffhzfq96MLkc81347K8VOXp+BvWJBm9h47tPVkEjvBjKwjN6+BPJ8Hz13H9615aHTWguaBtK6z4O/zxRLh9fjhtNq4B10fb2tjS3A1rnqTu5SsI+rr49fPrEk5r2zY/+tdK7n5pPR83dIRdfW/9NpzWGr1fsmuckuiI62PHKnasf481De2cde8b7H39s3yyI7zg+6/36wmELB56K/H/7YkPtwMwS2xNPXYKTJSYesnDRY1a0B6vi5YCsJM0b5OMPrkgTEgkuUIuZKPI1NfdAM3pprxE45ylDnZ2+Hn+453c/tw6PI457D3ZBULBqxUBkSDlL2tsJrkdHFjhw1JdOBwOjMopfGrMZHpgFd/THuIVcwGdwbDAFy1cCSuArbnA34besRmXHhYIE4W61OkCToJ0kzogi69RF99MIp2urwErnL7bS9AW4CqExjXhdKaiiX3p6TGpr6Sb+mplXFRTyY5LL3eQK60SSTqE+rk++jHYy3c3FiKloCcZJjJFf0xTVlaGqqoJ7rmdO3cmuOwAHA4HDodjpKZHTccKHCLEnt434MM3mOKpYZ+ph/DvTZHPvUf4uXHOZl7prMEwu6HHgNZqOlC3vEW+O4/CjpWpTxJM0jV2/Yt9v768ZjvtopCfHVEEhhvWPR1+wrZg0+vgLISCavCUU9+tcMIdrwKw0Xk2p6uwzS6jQb884RTe5m2EBUZByLLg3oOTTs+yk8gGyRx1XbtoaO2m6rdLqQSW+f5IgHBK+iPvbuP7x87u29XsRyCKdymnS3R2RyYZr7GQzJzIXXJBmJBIcoVc+DzICH43QFcVKguc6KrCWftM5JBZ5ZiWzU3/WcOKra0ABELhL82qAifTyz10BW1++KbGHR8Z+KI0qUfyPscqaxJlop3fGL/E5w8HKHqcow7AdJaid29H84Wjx/igQ+3PUUcA7NSC1EA16jTMhFTb3u29BM3YBWHTssHIA8MVFus6dkQ56qKFuvQcdSoWRoY7tGopnILjCRnASSQDM5AA10wBrYS7bq+yJo3ElHYzRj+AkwwdwzBYvHgxzzzzTMz2Z555hv3333+UZhVhx8E3c2ftzXxceBCm4sDRVc+8LX/he0pszbazNv6QG11/5mdl/+nb5sLP5a87aO/24m5KLdRZ/qi01O5mePyb8MotfZsK6WJNU5QIFV2PsW1rWOjb/iFsfoN1a1cljD9TbCHPEbeg8MHDuO+Yx/e1hwAw1NTXMTuZvydOqOtub4Kbp1H12wV926JrxvXGtr3Ed9ONnoPZz+JHKjTMjDrqohmvsZDAHtclXMYyuSBMSCS5gsAa9RIn0lG3m6EIwTcPm0G33+Stjc1c/dhKvnHYdJx6OEApz3dw+ZEzePjtrfx3ZQOPbNB5oxG+e6SXuQ7osh18NXgZjxs/ZE9lHWf7H+JKPo8aJUgpVvhNbas6luZCb94CaAlfAJrlTTlPhwgi+hHDDMXCEHFdX0W0oy75sdEil03YVddLXzznLIKuRmhcg22KhOMMEYxJoU1FNpxvepoi4Vgl3A1MBnASyUAMxv3xnj2D8wNXsMmuZI7YzDp7Aieor7PKmszn1We51zwhizMdp8iur2Oeyy+/nHPOOYclS5awdOlS7r33XjZv3sxFF1002lPjqAU1LJv+RTZtWka79xOM9U+hbXwJR2c4ddPc92KsT19Cb1xJ4eZYsbFO7MRqq+fy1ybwH2VHynOENr+N/snTiIKacCprV2PM84Wii5gt0cJe506oXQzuUgh0onbUE7/2X0gXeY4oca/+PXj0KwBcpD3OTaHPxdQJjsfqFeoaVsCLN8FhP0oQ6q741QPE9+iNzmTwh2LjJTOJUOfUFQKmhRk1fxE5e7+owsqaUDeeY6HxKkKOdWQzCYkkgrCtcEkInKM2BynU7YZoqsJ3j5nFLU9/zBufNvOLZz9hapkHAIemoKkK5x0wmX2nlnDH8+vY1hngO4+t55tLHARNwRa7km8HL+J3xq18znqCJ5UFsY66qJRW01EEIrmjzuFrSjlHJwFEPykKk9xBHG2xjrqYZhIpUlPjRS5/KFqoi/qCcpdB2zbsUDjVJVqY0wmllfqayQLDvWiYMYLkeEQGcBJJhDbbTaHoTthuDtIQ/5y1GIB1di0Aq0Nhl90T1n59+5wX+A436b+lUrQOcba7ETL1dcxz5pln0tTUxHXXXcf27duZP38+Tz75JJMm5YYDVTMMimumkKfXoldOIjjrKHZueBcz4KX6gEtRpxxIqKsJ+/W70Het7jvOI3y84LiCtd4J6ErqWr9GZ0+jhKbEOnIAeymf8Cz7RDb4ozrddkalDBt5iDwdiI3pCkUX7uimyPceknCOkJn6c2Qjwp+z3x8VbnSxYyVMOqDv+VufWoO3u5P4trbR8Wg6jjqXodLuC8VcUx0E0xItVKy04sGhMF6FOkF2FrIlw0fWqJNIIuSCw1Smvu5GuB0alm3jDZg4NJUrj53DZ3saTHy6K1yrxKFF3hJLJpVw5+f2YsmkYgKmzc1v+nh/e7hj1rPWYv4UOhKA2/Tf4CGqk1acTdQ0wkXK44MeI5S8Gxj0pi6kDlIULGblR1JnVWHFWOlTOd7ia8b5zVhHXVNXgO1tPhAC8sqxe15LtHgUTn0dODDLxiqrjjmuAxzZDUwiiXBf6GgO8t/Od4JfSXhuKGlaA/GCtSf7+u/iMXNpWvt/aE3hf+a8jM9jbDD6AZxk+Fx88cVs3LgRv9/P8uXLOeigg0Z7Sn30lS1x5UPVfPS6xZTNP4LiPU7qa6qgFdWin3InoQOvoP3QG9h50A20F83BEiozlW1Jv0/NglpM1dX3uKl8H1or9qF5r29gFk/Dqt4TgK9pj3Nbx3fCzR4AfFFCXUdsbT8lyR1+oejC7GiEFY8kFekAzK4knV17sBHhWnjBnoWKlg1sbonEmve+sBoXibWOo7MtAp1N2DvXRs7n94adgVYkjnL1ZJSE7Mg11UkgJoU2FRomDjHwfkNhikjsPjweENgo43zBeaySC8KERJIr5MLnQTrqdiNqCl34gibrdnZRphg4NJVz9pvE4knF3P+/Daxu6KCu1A1EarflOTV+dMJcHn7zU/7yzvYYYev60OfZW1nDHCW2i5ZtBmnzWxQ6YnXgeKGuP2eYg2DYcpoK2+KYGj982jt2fDOJ5GJWfF2MhvaI2OcPWazd0YGhKhS6dNyGA1soQKwI6CCYllimi8yvsoZr1I1zoU4GcBJJH23k8XfzEBwE+al+X9/2wTrqBsO3ghdzR+hU8unmM+or1IpGDlY/TNjvntCJrLNreEr9ftbmkrNIR51kJFFUKKxFcZfiDPnBkQ+V88Nd6tu3oVUvpKBsJh1dNltDhRQWleLf9BafrnyLl4Nz2N+xiVOscDOIUMkM1i+5nrnPfwmArpmn0qFXsCN/Np7SQ+lWCnlz82/5mvYYk6wt8O/LCE47CqV9e9/yQKC1nq7uIJoqMFQlqVBXQBeNjdvhnS8nfUkCC3PbeylfsopJZ8sO8nrPic7L61v4Qs+di5MALhJrHUdnMwT8PkK7Pul7HGrfDpubQXNCYS24inH2jBcdozoJpOmoM7PiqJsmtiWtszweCNeoG79x7FgmF4QJiSRXyIXPgxTqdiMURTClLI+gabFpVzc1RS6EEMytLuCGUxewsr6dY+ZXsqszwJaWbgKmRZFbRxGCz+1Tx8wi+PlLDXQHbarzFLZ3Gnwx8H0eMn7KNGV733k0TK59qYMbDivAqUWit/iURqOfZhK6MFGt1I40YVsYUZ228lQL1YoW6pIHTvEiV3N3ZL+QBUUugxavnzZvELeh9hRsj+3eaohQSiEwmmwEb5oIjfsivDL1VSJJ5M/mkTTZBfzG+CUApp15R10vJiqf9KTIvhuaCdh4gj6OU9/kYOUDTlDfBMJBTDYFw5xGCnWS0UB3hX8AiidBXiW0boHWjeGnVQVh23QLF84Zh1FSMJcX3yrgH10BTnGGhTrb8NBVMo8Ne36PvEAjtqMIt65RWeBGQWdju8Ld5kn81TyMa1x/4xT7OfT1T8dMw+rYzprtbShCQdMEm1oTPw8Fwku7L/X3eRnt7OpMff1wigBdptIn1HXZjpjUPCcBXEncbNHxX7els8X0AC0A+IUL2/AgQt3h2neqgavHXRe9uOoSgbRu0jSyU6OuVuzK+Ji5hJoDN8CSRHJBmJBIcoVcSAXfTSPs3Re1R6wr8hg0d0UCHCEEVYVOdFVlVlU+C2uLcGgKDW1eWroDoOgsnj2Nm0+YxLV7dfOPzxSzX7VCI8WcFfghnZ46fM4KLBHWfuta3+Sm170xhXvjBRiXnVh3KRq9n2YT2CbCigRVEz1mQtfXZNSJnTFpq9GdE00bNFXg0jR2dfoJWnZU19fo1NdgSiEwmmylvo5vR50sZiuRpCIUle5qjmgIIejCxd/NQ7gk+E3a7LDz+i1r9oDdZ8cvckFBkgPoTiifAbV7Q2Et5YV5VJYWEWzahNnRRI3H4ufHVFNZEEl1bQyGP7/tVUvZuedl+ErnYer5oKhoqsDf89ZuI49rrC/z8b434SuYEnNah7+ZcrdCkdvAoapYPbFeQnyipPYDVIpmdrWlLoHiIMjmjkg80I0jJvZyCT/OJI666H3afCHWNETO0eINsa4lSBv5YUeduwSXI1zkLjpudBJIK4ZTsHCkkSI7WNKJMccq4RIn4zeOHctIoU4iiSByIM7bXSPs3RqnrjK1zEPQsvEFE78shRBUFjjZc1IR8yYUogjY2RGuC1Lq1ti3IoRLCXHpXhrnztc5cGYlXQdfy/IDf0vz3HAqxY/0B3h/Wwd3vefrK+UTXytlIKFO68dxJ2wrRqjThRUzfrzjrcnOB2B/dRUPGT+lqqfocSAqlbf3V7eh0ekP0eENRs09tplEOl1fsyHUaZjj3lEna9RJJMmJ7kOYjRp16bKv/06W+H7DTopjxMPdCnk/I8klXEXgLEAUTaRq/iGUTN+XtiDYpklVvs7Np87q2/WJLQY/enor967SaArpBAon461cjK2Gm2d1+iPxTWcAugpn8umBt9G18Fy2TjoF08hH2Ba1r34fR3c9Dl3B4wgLcvFxj8tsJxVVogVXPyVCnAQ446lINwqfbcS63ggkr1EXJXIFTBtDi4iF3pDFrk4/6xs76fCboOq4ejI/osWxwdSoy3z2hJ2VZmS5gqxFnLvkgoNIIskVckG4lkLdbkp5voNJJW6au/0J7et7cWgqtcVu5tYUYmgKTZ1+TKOAgLsapbMBxQ5x/FSNi/dyoigCFJXm2WcRdJVTJVr4hvYoj30S5B8fh4Od+De8yxrIUedL/WScUKcIG7eauuvrm9YcLghcQbvtZomyliccV3GAsoJondKywbZtFAUUBE1dgShHXVTqK+mlvmZjRXT8O+psmfoqkaQgxgE8il/fPhzsohBg93XU9VdDVSIZRRRnPhOmzESftA/1zqlYmptCT8RR91r3BNbs7OaJj9u54IEP+N0rn9LSHcRWNEKuCtqj9CnTBp8JKCr+qUexefoXqN/3akzNjbNlLXUvXErBxqf74rt4d5k71JpynlWiGWGmFsOccWKVN95Rhx+XSOaoi+r6asZ2evWHoNhlEAxZbG3pJmja9PSSiBXqRABnGk0iVCwcIrOiWnbEv9xiPMexY5lcECYkklwhF4Tr3TTClgghmFruYVKJJ5zmaaa+6SjxGMyuCndubQ+At3gWZmEdDm9jws2KrTponnUmABdq/2G62Mob9eGAY0J+7FveOWyhLhIchRtPRKWnxq3SWig8ay3mhMD1rLQmUSo6eEC/ic90PhgTWIZ6hvA4NNq8wb7UXWUIqa/xc8gEGuO7Rp1caZVIUmNn0FF3+sIyrtzPxaHTCjlgwtDL1bbYeQPvNC6RNzSS3EVXFaZWlxEsmkobeaDovLDPvVwXPIeXrYVAuNtpwLT41wf1XPDAO/z+tS00ihLag7HXls5A7Hu9q+YA6vf7Md2l81FMH5Xv/4q9Vv8cD94ER11+P0JdpWhB6SdzwiECMc4yL0aMgOUUyR110a67oEXMgmyvWbDIbdDSHWTdzk7afeH9oxdkHQTSSmlVsTLufnMQzEozslxBIDMnchUp1EkkEWTqq2RU0VSF6RV5TCp1s6srdbAEYQfetIo8hABbNTBLZxE0itD9rQn7essW0lm1Hyomvyn4E703NEqcqOf19VODDjD6EeqEbUJ0swnbihEN41MWelPGNtuVnBa4lr+EDkURNif5HuMJ4yrmiE1AJP3VoSsEQlbfSqwWJwKm07EqW6mvahppt2MZGcBJJMmJFeqG/vX9+bkGVx1Rx2GTdW49eRrXLHPz7wvm8bNlKtOLBjdWFy5O9V/LpYFLhjyfMYlsJiHJcYrcBlPKPLT5ggRNi9aqA/mDeSy9PoFzlk7i2hPnMasyn0DI4p/v13PBn97hxfUtMeP4OtsSxjadJWw78Hp2zT0XW2hU73qN/zN+zCxla8x+ZWZDyvlV0Yxipo49nQQpILKg67f1GKHOxcA16nyhsFjXN0ZPkKcoUOjS6fAGCfVsi3biuQgkOPqSoQoz47GeQTAr8WOuIDMnchcp1EkkEaSjTjLqaKrCzMoCZlTk4TL6d2hMKHIxqdSNpgjQHHTnT0KxArGCWQ+NCy7EUgxm+D/iO+VvAeBQY78A8shc6iu21eOqC+OKC96iazv5MbgqdCEXBK6gWRQxXann/4wfc5LyP6KNhYaq9DnqosWxcOprGo66bDSTEOa4bmsfbiYhAziJJBnR17HQML6+z13oTNhWU+BgQZnCHYfq/PyEKdTkpR+ivGfP4DFrf74W+Cb/MA8a8rzGFvKGRpL71Ba7qSly0tjpw6HFfqZrCp3sNamYm09fyDUnzmNmZR6BkEV9a2zs1W6q6N0NieneQqVl5ulsXXYTPqOYWcpWfqvfErNLRSi1UFcpWlCTxI+9OAhQKCKNIHRhxqW+Ju/6Gh17+UI2wajUV19U+GRoCsV5RtT4Q6lRl/mur440szbGKgLGdWbIWEY2c5NIIuSCcC2FOgmqIphWnsfMynw8jtRinaIIppXnM7U8nOrkd5YTcFWgexPbyIc8lbTMPAOArwT+xBdn+DhjthGzT7EYQKizB2gmYYeiHseKVwuLYgPNZO6TZ63FfMV5Cy+ai3CJAL8y7qRoy7N9z3sMrc9hF9/1NR2xLBtCnYY57h1n4/31SSRDJVqoy2ZtuCNmFvPHE/IHfdx/rH15xFyWhRnlINJRJxkD9MZ3+Q4dbyA2bqkqDAv2QggWTyrmltMX8YPj5lBTGCvk/2FdHu+0FyACHUnP4SuZzVtLbuVdazpGnOO/0tyecm5VonmA1NdYR51OKLaZhPAP2EzCG4qUNIFwjbp4ep+O6fqado06EyPDNeoMERrXNeqEsFGFjPNykVwQJiSSXCEXPg9SqJMA4UCtPN+Bpvb/ljA0hRJPj+AmFLz5k7FVJyLYlbBvy4zPEMirRfe38HXzQWYVx4qAk12Jx0Sjmf2lvloY0WKZFRsc1rligz87xVu9yfLw5eB3+H3o2PBxK+/C0boufH5N9N2LRRe+dRJASyPIyF6NuvHrqEOmREgkKYkW5zLWbbWngDxKYp26+8+axYnT9SQHpeZ1ay5XB7/EH0NHZmZ+OcvoB3ASSTp4HBrTK/PQoxx1Ll0lz4j9zAsh2G9qKT8/fRG//tyeXHfSPAxVYUOzjytftTju6SKu/l+Qf65uj2k4ARB0lnJW4Ec8HDokZnu1WZ9yXlWiBbXf1NcABSJWqDPiOrPGZ0/07tdLwIrUpYNI6ms0vXGeHhfnpeOoU7PgqEu3DvJYJVyLeDzHsWOXXBAmJJJcIRc+D0OvIC3Z7bFtm4Cej694Bnkda4iPaWzVYMcelzDx1e9TWf8c3sLimOdLlf4ddf0X8rVR7UhwpNixQY0S10nMtJMLdQEzfPP709DnmSQaOIL3qH7zerYcfBumMzLfaHEsWZexZGQl9XW3cNSN/oVRIsl1huOoC7kqQHOF/9XdhDwGqImfu4U1HiYscfH4usFcywR/Mo8GbN63pjNL2cpF2uNDnmvOIru+SsYQFflO5tYU9j0uyzfoDpqEOv0UuQ1UJSLiqYqg2GOwz5QSXIbK39/Zylsbm9neFb5GrHurmd8rbg6o7eaE6QYLy8OLBgF0vhe6kEfMZUxX6rlB/z3FdmJ9u14KRDeOUHKXHoTFskIiC7o6Zkxqngt/UtebHufq64hqhuFPog9ZfUJdbFptOnVA1Sx0aHUQzLhLL9cY73HsWCUXanJJJLlCLnwepKNOMiQKnDpFboMOX4iQu4pQ0VQskei88JXNp3XK8QC4Vv8j5jk1FGkmscUqH/wkQhHBTMQ56kRc3RMrxcett8iwjcLlwYvxuqrRvY1MeO2HKIH2vgAuOqjIo5/aeVE4srAiqjHea9TJlAiJJBVW1IJDKMXiQzqEPFVguMP/qj3XbUUn6CwHJdGpd+dpU/jWEiNhe/8IHrWW8bPQmZwb+A5fD1wKwCpr0pDnnVPI9QTJGGNKqafv98mlHhZNLMLj1Gho99KZLCeUcMOFC5dNYXKpmwKnxvELq5labBC0BC9uDvHt57v51nPdvNvQG5cI3rLn8LB5CC+ZCwecU1FwR8rnHAQpEBGhLt5p5krDUQfQHifU2XFp61ZfiZPIcQ4xmBp1A+83GBwEx3XqK0ihLlcRQn6xSSS9iBxYkJWOOsmQcOoqU8o8tHuDIARqxUy6vc1YdmK9ul1zv4Sz4R2c3tiATAmFHXXbCvfiDO9V/Cv/Ziqb3kx/EtEpE1aco86KDZyiV4ujCUSlQbTj4f1FP2bv96/C0b6JCa9dTYH9XXaQFxNUuNMU6rLnqBvPQl1utMOWSHIRK0NdX5Oi6oTcFejB9oSnagoMJk/W+cU7g78htVF40doTgGd9e+HHwCCIkwBHq2/jws+3tEcojioaPzaQ1ynJ2EKNKm1SXeikssBJsdtgW0s3m5q76fQHKfU4Eo5zaCo3nraA2mI3q7a3c9HSGrasX8l/1nbw3606K3eZrNwVG5eYqJwX/C43Of7GGaHHU6YQFQVSN5vQhUkJEcedIUKIKJHNKQID1qiDWEedZYcXaKNvflKlvloiHUedhSPD7jeHGN9CXTj1VV4/c5FcSPWTSHIF6aiTjGnK8xzUFLlQFUGBy8DjNPAGE0UkW3fzyfxvJmzvTVfNc7v5+ckzcR72PbYu/QkdSy5JbwKhfoS6+LonKQKuuNrKdLmq2bb/TwkZBThb1/E7+8dMFDtixLF06tMBGQ/eoLdG3fgNcCZ4ZAAnkaQiOoQ2M1WjbhD87UtzuHRxYsfYdPETduUF0GnHw9/NQ/iTeTR7+u/J1BRHDtlMQjKGqSp0AeG6w1PK89hzYjEV+U4aO3x0+hJFIl1V0HuFPt1F3fT5fHO/Iv56WBenzdRI1ofMQuEX1pks3+d2ti9KjAEBivtx1AFUiJbIHAjFpLU6CSQtRRK/SNoet0t8+mtvxDGUrq/ZSH01CGVloTdXkDXqchcp1EkkEXLh8yCFOsmQURTB9Io8akvcOHWVkjyDDlMHRIJw1lk4E9+sk5OOY6s9KVWqga90Lt2Lvkz9pFNSpqv2ES3UxXV9VeJSX5dUaxQ7bJxxwWQwThMKWRAoqGPbgTcRdJUzie08avw4oZNZOmSjGLAmTNQhzGWsMLXAZl7x+H19EslwiL4iZtxRB9iKRtAdVb8ursHEguo8Tpwx2BTYdBAc47+JX4dOZq01IQvjZwEp1EnGMAfPjC03UujWWTChkPm1RRi6GNBJYGtOfCWzKS4u5dKZrTxwgpszZ6nccEgeZ8+wOH1+EQLY3i343KtlXNt8BKf7r+bq4JdixsmzEh280VSI1r7fDUIxjRtc+JOKaf2lvgL4QqlSX6NFwGBaKa2ayHwzCQeBGHffeEMgU19zlVxwEEkkucPox3ky9VUyLJy6ilMPq1+lHgdbHCWE7BLsrmZMdzmaGrnsdy++GKV8FhtKljHhpSvIa1sLgKXG3fgJhR0Tj+F3zYtQmtfxQ/3B5Cfvp1uYiEt9LXZpvHiKzbXLFf5vXeSDlyDU9TwVKKhjy0G3EHjqx8wWG/v5C6QmG6kLOua4dtQpAibnmdB/7C6R7JZEF1LPjlCnE3RXRtWvi5wv+tY936HSkawq+zBYY9exJlTHL/kMVaIJv20wRTTwsOMnGT1P5hi/12HJ+OW5Kw5ma4uXxZOKE55TFMGEIhd5hka7L5iyZEgvtubCVzIH566VVPh3curUfKZWOfjMBJtPjTIWF7Tx4BqTj5oV/vtJBzCbd8zZPGou4wDlI36t/2rADIVooU4nFONwcIkUNepE3EJxvFAX76hLkvrqEv60OmurmBmvUWcQGtfNJGTqa+6iyP8XiaQPJQeEOumok2SMQpeOyzCoFxV0e720dnljdxACu3IBQU81n86/DJ+nBgBTz0863hbHdH5nHs8p/uv4lfh84g5m6kAmvusrQiAEaAO8400r6kbYVcqXuYaHQocAELBVfhg8L+0i7tlIXdDGeY06QDpVJJIUKFE3tdkQ6tLlv19ZwMMn52Vl7CAaW+xKdlLMm/YcDvbfxpn+H3FZ4GJ+GTo1K+ccEvIyJRmDTCvPS3DTxVPo1plY4kZVBIoikpY06cXSPfjK5hHMq8UItCD8kS6vc0sFN+wT5Jb9fMwud/Vt78DNf619OCZwE2uMBVhKYiOyXspEZDydUFwzCX+KGnWx8x3IURepUTf41FcNc0gZF/0R3zRjvCGFutxFOuokkgi5kPoqHXWSjOHUVUo8Bk1WGaVaDTsbd2FZbpQk95Om7mHTHt+msv55ds7+YtLx9J7j3ren06jN4tK5Fmx4Gdq3DTiX+NRXS/OgKhr7VMKr9YLuoEVrEkOeGRc7+DH4fugr/MfaF4CXrEVssSu4Q7+DAtHd7xwynQ4BvTXqxrFQZ9uQA112JJJcRMQ46ka+Rl0vLl2hxDUyQuEmu4pNVIWFMQt22CU4CXC1/sCInD818jolGd8UOHWml3tYt7Or3/0s3YOvdC6dQSciuAW0yGdDCFhcZjFj9iTWt1tU08jP3wzi7e5kTUstx7RfyR7FAQ623uI472PMUrbGjF1BpEadQ4RQoptJEEBJ0qUyMfU19nl/fOprz3VVi2smEUzjFsmdxNE3XBwiiGMcC3UQLuMiyT1yQZiQSCQRpKNOklEml3nYo66cqroZeJQg3f7UYlXIUUzLjM/gL5iU9HlDiXxh6Apw1E/hzD+DMbCTI77rq+XIB0VjzwrBf84qY+/q5AGYGfcd1fvwJWsRL1mL+n7f238Xf3QlFxh7SbfpxGAId30d3zeIudAOWyLJRbKd+pp4Qp2QqwJLc4Zr18XVrLv79Bl8fa+hN5cYCn8xD+cP5rHM9t3HdN+fuD10Gu9bU0d0DoB0/krGPYoimFTqYW5NAYVOHSHAtm1C8SuaAELB564hVDwNtMRrghCCIpfOggqdv5wzh6v3VTi0yo8mbN5vMfhl24EcHfg556vX8yvrs+zSwxkX8W616GYSHuFLOu8Ba9SlSH01olJmHSKYlqPOnaSZxXAZ/80kZIpl7iK/1ySSXnLhOiWFOklGyXNoFLp19Lxy8gpLCPnaBj4oBUbUu7OvVooQsOhzgx7LjnurT8hLbvAOxX0mU92L+TH4j3E0nzCRT0aw+LmGOb4ddUhHnUSSiuigYUSEOlUn5KnC1tzh2nVqbIraPnX5HD45ddpaNvHhIITG7aHTOTvwQ14z5/K4ud/ITUAKdZLdACEENUUuZlTlU+TWqS50saPDl0KsE5hFU7CLJ2Or/Qv4RQ7BJbO7OLgmdpzjDj+co045B8dh3yPkKOp3jDnu5MVs40Wu+LguVeprvKPOKQYW6lwkFwuHQ7iZxPh11MnU19xFpr5KJBFy4fMghTpJdtCduMsmogW7sIb4faxHZXbp0e/UvS+AGUdHHhdPHngwEftWP2m6ztTCxI+gGXfz1d+tWBdOTrVv4dzAd2m1PQPPIQPoYvw76qRQJ9kd6LBdA+8Uh+jn0YjQ47CLdtblG4KfHjuZE6ePjmAH0I2Ts4M/5BvBS9nbdxf3h44agbNKoU6ye+HQVGZX51Nd5GJHhx9vIMmioaJil83CdBalNaauxD8WqIogVLsf25ZeQ+fU42iYcGTSY41QZ9Lty6pCzCzRmFqU/BYnlaNOi6t/l46jzpOF1NdwM4nxK9QhhbqcJRccRBJJ7jD6cZ4U6iRZI7+0BsNw4PP2X98kFdGOOi26+5gQsOc5sOcX4KDvwsl3gaei/8HihDpdFXxzr8Qby/hF4v4+opYNlmWzjXL28t/D7/Iv7n8OGUAjFJP6MS6RQp1kN+DMwI8GfYwY7SC6x2EX76w7bk4JJ043Uhw0sjRSxM9CZ3FT8Kzsnkg66iS7IQ5NZU5VAVPLPLT7grR0pRazbKEmNvaKI0GoUyOxnq25aZ99JuvnXsKWqWdixy1OaKHksWWBHuLvp5XwkwNc7FmReJuztcPCjvr89qW+xjvq0hDqXFlIfXWI8d5MAinU5Si54CCSSHIF2fVVMq7RPcUUllUT6mrqC4QURVCeb6AoA38d6FE16hK6tQoBs46FRWeBpwwOuQoKa2HygaAm3jDaQgFFRfO1Itq3oAQ7KXcLblpmcNxkmFYUtu+F4j+T/XxGLTviwLNQeNVxEJ8e/Sfeqhp8am66ZKNBRe4xehfGlVbyeokSSaaZN7WWvX13cVfopLSPyeUgekqRyrcOmsDiqsw0uVhUrjK/bGhjeXFyt3kSP8uqWDf6AZxEMhoYmsKMyjwW1BaiKLC9zYtpJX4e/Pl1WEr/n+H42E5Tk1/lNs26kKalP8SqmE936fx+xxRWWHArcSl8bx+DWw52cs48jeOmOQB4aHWAy5/rZuWusBjWKxlFO+qcIohDDBxvubOQ+moQHOc16mzUcV3CZewiHXUSSYRcaK4ihTpJ9hCC6inzqCgqwGmFVz51RVCe50RN1go2jmhHnZ4ieOsjvxKO+Rmcek/YYVc+K+Zpj8uFqJhFd+VirLI5aMFOdH8L8507+Prsbmpc4aDozfpQzEpr/446O8aBZyPwli/k4+KDabCLB3x9QyGdFd4xzSh3fX1s8f2jdm7J7sWEfJVGirgzdDLPmXumdUzOBNFJUmABzllSycETM5MCe9osnV8cMbySAnebJ3Cc/wauD56dkTnFIJ2/kt0YIQSVBU4WTiyiNM+goT1RrAs6S/EWzsDWUzcAi3fUGWrq2DBYOIXgsu+z+dA76C6dl3I/V/Nq3C9fS8XK31G1+XH2CL7PGbWt/OAAD6dMV3Go8NEuk8ue7eaaV7rpCiTv+ppWM4lspb6Oa0edTH3NVXJ5MVAiGXmkUCcZ56ieYmqmzmeiM4RDGdwKWnSNuoF0uhhKpoQ7xO7z1b5NeU4DraCKkLsCq3gq3sKZgMCbP4XOsoWcvSAPBZunNwR5Yn1kJXPA1Nckol6nXsqJ/p+y3JoxiEmnhzONFd6xjT2qXV+/urR61M4t2b2YVhz++u3CBaf9lrbSRQMe0zZCtTAHJEUKLEBtfmbCilbf8AMkG4VV9mR+a57AHr57eNlckIGZSSSSXgqcOvMnFFJT5Ep6k+931+AvmoqlJ792RWdOQBqLsgCKxqYDf86mGecS1PNjnrIRqMFO9M2vULrhX0xeex/T372OhS99hZr/O5Wftv+QF6Y+yA+r36JGNPG/bSFaerS26LpwzjRr1GWj66uDwLgW6kCmvuYuoy9MSCS5Qi6kvmoD7yKRDA+1pI4KXzN07hzUcTGOujRSZWMQClRGrbhGO/iEwJ9fR7tdgMNdgKoqLN6jis9uep2HPja5810fU4sU5pZp/ZYhCgt1kcd21C+NFHNW4EfsIdZxhf539lNWD27+KRj3jjqQThXJbsGcUp07Tp1IXqCBRRPyMEtnQ9MHMftU5BvQEnn8jj2Lu0Mnst7OXUF5QYXGdcdM4u/Lt7KicejpTS0ZEOqiaSWfi4LfYon5MX8yfjb8AeV1SiIBeurWVRfg1FQc8bmsQhByV2GbFuBNONZI0kwiLYRCS+VSWovns+itbwPgK5xKcL9L6dy1hSLFT3fTNujcjru7HkdXPUrIS177J+S1f8IFwAUO2CnKeS44n1esBTii4itDmGhpfMazkfrqECH0cdxMQtaoy12ko04iiZALnwcp1Emyj6JC8aQeoS588yWAoGmDlvpjENNMYrhlj4SCpgoqChzhGihCYOp54Vp3AJqDQ/ecw7au1byy1eTaV73cdbSnXy09FJfm0Svq9W4NovG2PZsLAldwoPIRdxu3Jx1no1XJQ+ahfF9/aMCX4dgthLrRX8GQSEaCA6YU0lTfCEDzrDNxFtfQ6J7GpBcuAeDwWWXsu6OENzc09xwhuCmUvRqYmeKEuaWs2Lh9WEJdkpJXw6YbJy9bi9hpF1EhWoc3mLxOSSR96KrCzKqwuy1pN1jAVjRsT2VMynx/zSTSQkQ3GlOx86roVitwl1Sws9VLmy+IoSrYdpDpjjZ2blxFaeda3M2rcbRvoMJu5HPaC3yOFxKGVsTAn3FXFlJfHbtBjTptvDdFG6PkQk0uiSRXyIXPg0x9lYwM7lIoqALCDSUqi5wAdPpCKe93YptJDFPXFgq6qlBZ4ERPVQNFc/CNoxYyKV/Q7LP5yf+8CV1gowmasRO34oS6Xjpx819rH34Q/DJttjthnFet+dxtnoRpD/wapaNu+Gw94Aa8S77OzgVfidnuL5gCQHfRrGSH5TQ7F3ylb/6SMYKI/bzbqoFv8VcJFE6O2f6NQ6dz1XGzB38Dm2FEstOnqFUHkOySndAUKAWzSxTOXZC9LrLH+6/n0sDXhznK6AdwEkku0rsoqiqCkGXT5g1i2WArOnZ+dUzKfPw1IWV8lga26OdYRcMqrKO56kB2zv8qWw79JeuPf5htS6+lYdKJ+PPrAAgozkGd08iC4BRuJjG+HXU5U29VEkMupPpJJLnD6H8epKNOMjIIAYV14GsHoMxtoJa62dzYhi9ogki0zBlRm+JXXdM8adSv6VnyXG4PPzxmOpc9upaVu/oPwBIcdb3/pvhcP2gewV/Mw7hOu59ztGf7tps9ermJMmAnLKcY30KdIPvNJLzlC/HWnEZb/Tq0pV+nacdGKq1dNFp5FANb9voOhdv/h3vOUYRWPIKzpBb9wwcxpx2J2Pwaor0egwCNdgF5+HDlwP9J46KLUYNdONo3jPZUJGmTnvDm0FX2qivmH1/dn78v38ILHzeyrTUxhWxU6KtVl3jRO32WwYtbbBZXQLvtYlllgD2mTeSLD32Cv5/L3NRSJ3ccaVDqgp1ZepmNFPOYdQCTgjs4T/svJaJz8IPI1FeJJCm9i6Jbmrvp8pvoqk1zdyAi9is6QVc5dnvT0GrUpSLNOK8XW3PRXbmYtvyFtLt06sxNbLPK6Vj/BrUbHqYssG3ocxkGDoLo41qos9GkUJeT5IKDSCLJFXJBuJZCnWTkcJdAYS1o4RXLYrdOu9tgh9/E6UwMsKLFOTUDjrp0qaqs5Kv7NnPb/5r63S8YF2ekctRFY6Pwo9CXuSF0NqudXwbgA2ta33MMJNRJR11m0RwgVEITD8CqXweA6SikZfJxGFULaLLyKa2ZzrbqIyitmU5T/TpKyiewc/27GBP35sONa9m7qJPtG1dz7dsqNoK1Vi1VooUnHFeN3OsAcmHlRzIYBndNm1ji5sy967jo4Gm8/mkT3/nHh1maV2Yocio8eeF8mrevp7RmOts3r8WrCA6oNXh+U+rrWPyVujzPoLEzO9e9O8zT+LV5ChucXxj8wfLjJpH0y+QyD4oQeIMmH25pRe+1z6k6gbxaQq07cFqtQGHfMboihixR9euoSwdXCVaogMnLzqZ14mzuW+3ld+sL+YL6DF24+L72V/JFN2qWP/wOEcQxjmvUhaNdKdTlIlKok0gi5MLnQQp1kpFDCCidFracqQb42ihw6aT6vo5tJjHMcyuDW2k9ZNFMnvvkbT7YmTpYik997atRl8bn2ouTI/w/Zy/lEx61DgQizrr+cI7juiVA+I+X404VobvQCiop9hhYxU5CNfPxm6W89mZH3z5NdiGH+m9lptjCPSlqE2YcWTNrt8BtaMyuKuCP5+3D06saePDNzaM9pZQpsCJJvuwPD/Cw97RKXlmzldfqE9+z8cc8/tXFbP10Bac/OgTXWxrYKBzo/yUzxFbuM24exJG5fZ2SSEabsjwHAP6QSYFLxxuMLETaik53wVRUY03MMbo6WKFu8JkT6XLmPBcVtZU8sOp0dCvAvk0HYugaD+2zgW2tXvZbdzsFojuj54TsNKjIJQSgDbAoLRkdckGYkEgkEWSNOsnIIwRUzAF3GW6HjseRPLgado266EOiVlo1VVCe76C/UihCUbn4sNn9Dp8q9TVd1tm1/M08tMdJB1YaDpvdwVEnclyoS4ZLE9x31kyuPsDVt22DXc1T1j60n/oX3jT269v+rcDX2GaXjsY0JTlEGiUp+2XBhELO2ruObx4+gwUTCgc+YJiI/q5PfSmweup9esh3KJy7TxVX7qPy60MHrm1naAqFjuyGKlvtcl6w9uTCwOXcFjw9vYOkMC6RpIVDU6kudKLFifBBowgrvypmW9Zq1A2RaSU63ztiCrcekY9mOOkIKpz+1gz+3L4HS/138K3A13jEXMafQkdm7Jx5Sbrjjjekoy43kUKdRBIhF65T0lEnGR1cRVCzB462rRR589jVFcTyVGB31/ftEl2jLt0i5CmJChB1VaGiwMmmpq5+D6kpK+JHR05C7W7gmv8ldvZKbCYRfjzUr7kWO5880f9K6nivURdmbAYKi2ryqEXnj5+rY9WGTfzsjfD/Zah6L+7L+wqdjX4eMZfxpLUfbwdm89z8p3F88kTGzt9VvR+lH/81Y+NJsk1mmkN8aelkjphTyZMfbWfDri4MVWH5ppbcqWOXAlUIphXBkTOLeGZta992JcWizFNfWcCaT9fzzWcz72Dp5RlrCc+whHfsmUwV2/mpfl/qnaVQJ5GkTVm+g5buJPGLqwyIlBkZbKxnR19HB5k5MRhKXQq/PGUKtzy7gTXNFi9vsQAXj1rLeNRaBsAtoTMoEl18SX2aIBoXqv9GTaNzbDz5Irev3cNF1qjLXUa3ZZVEklvkwudBCnWS0cNwQ/lMStt8tAe7sAuKCHXT58owohx1w254OMSUiMnV5UworOYq7VNW7Azw+OrWvufidLoBm0kMxAXBK6gULfzJ+FnKfRzj3lGX+6mvA7Gg2kONbVBZUYMnsAOALjWP84Pf6dtnq11O15G3wo5Vw2oA0V06jzbPVAD8RdN4/bC/sXjtLzC2vj68FyEZATIbAhw1t5KgaTGvupCV9e189t7we6Asz2DXMGu8JUthTUo/XWBT8dNjp3Dq5LVc/HR44STVfXp5no4oVTl8RhHLN7fR6h/chfbMPcp5+P3GtPZ9zZrPa8zjh5NW4Wx4F6xkJQekUCeRpEuBU2dKWR55hoY/FPmO16KUOV0ZxLUmCdlw1EVTVWBw7QEG/2ko4M/LdxKKC1XayaPdzuMnoXOAsHA3S2zhBPUNlikrmK9sTOs8491RJ7BRpVCXk0hHnUQSzeh/HmTqq2TUKXLr5DlUHE4HJdWTUN2FmKoLpxlxTsSLYukRXbsk9q2uCFCEwLTSGFjVOefwvfjCstn9rvb21agbwkwBPrbreNlaxC9Dp/KyuSDpPrtD6utYF+p6OWR6EVOLwgJxhTv5G6d+6Y/x7vVVQnr+kM6x5aBb2TzzvL7HXk8tvlmnDGmsePzTj2PHHpdkZCxJErK4VOcyVP7x1aXc/fnF/OfSg3js6wdk72TRDCIFthddFcwoiSyk5CdpLNSLEIKbT5zKjw90pdwnFd87bOIgjxA0Hf8HOO2e5E9LR51EMihKPEaCY1aLWoXVFDEokT+BDNeoS4YqBGcsKuPXR3rYv7L/anohNFbaU/hZ6HOcEriO/Xx3cGvwdD6wpvZ7XC50ks8mgtxIKZMkIoU6iSRCLnR9lUKdZNRx6irzJxTicWhUFjjRdSd+V2WMKJWOntYvcSkRLl2lyG3Q4Uu/bLHb0PjVcZVctiB5EDXsOfbwi9AZfCP4jaTPGWKcF+C1GTdCXTTnzHNw7Oxi8o3Y7SFXGd79vsX6Zb+gfsHFdO//PUKO4kGMnKj2hKr2xHfec+yaM4ROltHj1O5H54SDhjWGZGSJNqNMLc9jQrELVRHDcqkkGzsb3Hj8ZGYUK/zgiLoB951TqjK/yj3oc1y3v8q0QZTzE0JAyVRYcj5M3Dfu2dEP4CSSsY6uRNUP1tQEkV9TBYoQBMyB44JsO+qimVascvkCPw8fp1HuHHj/EBoNlHKHeRonB37KxYFL06+HOc4Q2OjjPZYdowwlVVsiGa/kgnA9boS6jRs3cv755zNlyhRcLhfTpk3jxz/+MYFArKiyefNmTjzxRDweD2VlZVx66aUJ+6xYsYKDDz4Yl8vFhAkTuO6667Dl6nlWib+RDDpKsB15fY/N4f794wI4IQSVBc6Y1dx02H9SPouKk3deHW7qazRt5HGa/xpuDn52+IONIXSVcelU8RiC64+bwj7VyZ1GpqOQttpD8e1xHhuO+ROtZ/+XHXt8g2DN3v0PnEI9sQvraJlxBh3H/BpbDM2hYCvpu6IkQyGzytdY+dikmubRs0q46+g8JhQ6BhxDVQR/Ons23903jTvkKJZUKvz6sCG8rw+9Co65CZZ+HeacFN42DhcUJJKRQFMF5QUGmiLQlOjUVyUhfb7AoVFd4MLuuXIoiqAsz0BVBUHLil0gHQFHXTxzSgSvfAY+v1fFoI570tqPX5mnsch3L3v77uQpcwlvWbOyNMvcQrrpJBLJ2GD0A+txI9StWbMGy7K45557WLlyJb/4xS+4++67ueqqq/r2MU2T448/nq6uLl599VUeeughHnnkEa644oq+fdrb2znyyCOpqanh7bff5o477uCWW27htttuG42XtdsSMgoIOYr6HqexmJqISJ36CuGU2wLX4G7arPxq8vPyk9phrWGmvsbzrj2Te8wTeNOazWor1mWywy7ir6FDM3Sm3EFXlTHZ9TWjCIFVNJn2yUfTcfIfWX/832j7zN9oWHxFkn37uYQrKsGpR7DloJ9j5tWkdWpv0QxCe5yDt3QugRnHkwtfUuOXXChTmx6DnukQatUNhYPrdGZXDD4N9sbjJjO1aODwJ0YHFwIOvBymjb/rrkQykuiqQl2Jh/J8B75gxFmlqQLNMCipnoRmOACBsILUFDupKHAiRHgxryzPQYnbQanHQZ4jco0ZSUddNELAWXtV8NdzF/HFuYObQxt5NFLMV4OX89nA1dwdOgGvbQx84BhGQ7rpJBJJ7pMLqa/jppnEMcccwzHHHNP3eOrUqXz88cf85je/4ZZbbgHg6aefZtWqVWzZsoWamvCN66233sq5557L9ddfT0FBAQ8++CA+n4/7778fh8PB/PnzWbt2LbfddhuXX355RlKIJGkgFAKuKmArMNQaddHjJa60OnWVynwHuzoGUQ9Ec+KpnMqpU9fwyKexH5++GnUZ/FyH0DgzcDULxXoec/yob3uznc+VoQv5h3kQfzFuwCGSu/zGHPbYbybRH9GXD00VlHiM/l2dQsHS3ZiV0+kw3RSFdmFu/wjPzuUAmLoHaO/3nP7imbR98Xkcj5yDZ8fbKfdrr9yX7fv+kLqps9m68WNK1fF9szDqZOm7JCe+ovpq1WU3yDFUwV++MIdb/vsRf1kVvo6fMLeEf69q7ve4o2eXsKSgmSMf6v+zI5JJlMWT4YRfQCixE7hEIkkPVRHMqsqnsSPS6V5TBLqqUODSCQYryauaitK9CV1VmVbmRrEiC6tlHgdl5R4sf+Qzaug6oVG6/ilCMKsyD/cMhYVlgu++Yg6hHIrgptDZ3B06kRPUN2izPdym/4Zm8qkUrVmY9eigivEb40kkkvFDWnXss8y4cdQlo62tjZKSkr7Hr7/+OvPnz+8T6QCOPvpo/H4/y5cv79vn4IMPxuFwxOxTX1/Pxo0bk57H7/fT3t4e8yMZOg5dwaErtGmR/7thf1hS3L2W5TlwO1SUQdzdhtyVSdMc7Lh/M8lH9hTetGb3PTYJC4/L7VnM8d/Hd4MXZuGso4PYTdIidFWh1GPgMlSK3XpCke1kdB9wJfX7X0v7KX9m64E3YmuutN9vDUu+Teeh16feQSg5ovJIhkpSYSljY+cun5llUF1gcOYcg+uOmcy+NemtQf7giDpmFEfCoK/uX825CwZIvXUVh9Nf6/YbzpQlkt0ep64ytyZSNFJTlb6FK103KJuyCL1sOigqbkPFaSTeskTHbk5dQ1NH97ZGVwTzShX+9sU5fHb20Ba7Wsnnz+aRPG7tz1z/fezrv4sD/b9koe+33BD8HN8NXkir7cnwzEcO6aiTSCRjgVyIe8etULd+/XruuOMOLrroor5tDQ0NVFZWxuxXXFyMYRg0NDSk3Kf3ce8+8dx4440UFhb2/UycONjucpJonLpKeZ6DbjPy9rRU56A6CSagJK9dUuwxmF2dn5ZI0ocQUDaLbx0xM2ZzplNfY8ZG4cuB7/C2FT5nF86Y5/5mHspC371ZOPNIM84ddUm26YqgLN9BWV7EXTeg227i3rgmLSbPUAGbDu/AjkpL9xCY8xk6S5N3FE6WNmSpA9cLk+QGo7/uN3oUOBT+ff48LlgUvi5eutjJfpMG7qT8mYVl3HV0pBaqAIyorwqpW0sk2aXEExGz1B5HXWSDDpXzwg1dUhL1IVWUhKcUMTquiKmlLi7cw8lVR0yk2iNw60O73Qr2JD5ttctpx8O95on8zTyUPfz3coj/Vh4IHcHfQgdncupZRwp1EolkLJAL9TRzXqi75pprEEL0+/POO+/EHFNfX88xxxzDGWecwQUXXBDzXLLUVdu2Y7bH79PbSCJV2uuVV15JW1tb38+WLVuG9FolEcryHbj0yB2TqTpgOMXt+6ld4tDC5xGC9JuGCMGCCYX8/OQZ3HBI+IbQyqalDujCxbmB7/HL0Gn8PHhmwvPt5HFF4KIkR44xxrFQlwpdEZS6w+66kh6XXanHiL1pid6/x41XV+piWnkepm3R0hlI6623da/vsGXx9xOfSPYZUTRaP/8UDXt9a8Bx2057iHUn/IPmr65g/XF/pWvZD9mw9AZ2TT2ZjhN+S8vUE9OYnSQXGQuCVfT3c4VH4a7PzODwSeHvjIn5/Yc6E4vCYsExs0v63U8ikWQWI+o7zkoWf6kaaEb4ImRZ4Z9UCBVVERS7DQxdUFEQXgDzBmOFoZGU7U5fWM6fTsxn37qBFw4Gh2CjXc2PQl/mu6GvMs/3e07zX8ODocPptAfXZGekkUKdRCKRpEfOC3WXXHIJq1ev7vdn/vz5ffvX19dz6KGHsnTpUu69N9ZhVFVVleCKa2lpIRgM9rnmku2zc+dOgASnXS8Oh4OCgoKYH8nwKHTpFEY1ehhSM4loBigy7DZUHLqSENANRHGei6ryMgDWtVq8s6Ujq0FgFy5+ETqd5Xby7mCPWAcxzfdAFmcwAoyV9pVZQFdEWKBL4fCMd9oJBOX5DuZWF+I0lLRq4liai86KxQRr94/ZnqoQt1U4ie7yRQOOa1btga2Fna+WkY9/wRfwFs2gcdYXCNYtY9fCr+Jd8vUx69JrP/H3oz2FsUdvUwnNRdBVgZ3l5hLxXLrEyZWHT+SWw9z97vfLU6by4AkeZlXE7jcG9Mndjuuvv579998ft9tNUVFR0n02b97MiSeeiMfjoaysjEsvvZRAILYW7YoVKzj44INxuVxMmDCB6667Lv2FOknGSDubIa8S8ivBjKsNGdPwRUVXBCVuHZceXuyqLnKR7wxfd3RVId+h0dLtx+sfWbHox0dP4ldH9n8dGg5duHjXnskPQuezn//XnOj/KSf5f8IPg+dl7ZxDRQp1EolkLCByIFcl54W6srIyZs+e3e+P0xlePdq2bRuHHHIIe+21F/fddx9KnA1+6dKlfPTRR2zfvr1v29NPP43D4WDx4sV9+7z88ssxQd3TTz9NTU0NkydPzv4LlgDhgKqyIHJDb1pWOA0ir2oQzrrorq/JU197ceoqRS6DrkEGb7aiM3f6FA6bWYJlw03Pb2N96+g6wkxUVlqTRnUOQ2acN5MYLr1Ounghr9itM6U8j7J8B0KItBpVdBx/N5sO+VVkg1BSChOmq4yO4+9J3nl2EHj3+QbrT/jbkI+3dQ/+gskANNjFI+ocCE08YMTONRyy1vBoKOP2NpUw3ATdlViaC9NTmfVusL24dcEZi8opcfUf6uiqoMyd8+GQBAgEApxxxhl87WtfS/q8aZocf/zxdHV18eqrr/LQQw/xyCOPcMUVkWtXe3s7Rx55JDU1Nbz99tvccccd3HLLLdx2220j9TIkSehXJ9VdUDEPCiamvhbFp74CLl2lssCBLhR0VWFGZT6TSz14gyaB0MjFGgVOjTmlGjefMIWTZ+jkObJ3venEzQp7Kh/a0/izeSR7+e7mcP/NWTvfYNFyIJ1MIpFIBkIKdRmkvr6eQw45hIkTJ3LLLbfQ2NhIQ0NDjDvuqKOOYu7cuZxzzjm89957PPfcc3z729/mwgsv7HPBnX322TgcDs4991w++ugjHn30UW644QbZ8XUUKC+I3IS7DS0s1BVUh1MhBssAjjoIp9sGh2DdE0Jw4bLJzK9w4g1aPL1p5FYLi53J35OfC/yACwOXj9g8MooU6vpIqzNsD/kOjXnVhRS59Igzr7/C2qpBoGgqocqwW65p6in9jh+cdDAdEw+l9XNP0jT784N5GbEIlbbT/07j/PMHfWjL+W+x+bBf03LuKyz138EC/+/4cdWv8c05g7aqpQD4px1DZ+XeQ5+fJGvYio6VVwW6m6CzPGXt0JxBfuXnHNdeey3f+ta3WLAgea3Np59+mlWrVvHnP/+ZPffckyOOOIJbb72V3/72t32Nvh588EF8Ph/3338/8+fP57TTTuOqq67itttuk666UcQe6KbIkQfVC8MLtn0MvCBblu+gJM9AUxR0VVBd6KI0z6DDN3Bt10xz+MxiLlnsYr+6kcu8aaaA9fYEFvh+x76+X4/YeVOhERrtKUgkEsmAKFKoyxxPP/0069at4/nnn6e2tpbq6uq+n15UVeWJJ57A6XRywAEH8NnPfpZTTjmFW265pW+fwsJCnnnmGbZu3cqSJUu4+OKLufzyy7n88jEqeoxh8hwaN5++kHk1BVx1/JzhDZbGDWG+U0PXxJBWWTXdwSVHzqWueGRrgyybmFy0bCePZ6wlNNt5SZ/PWcb5TdJgtf5ewa23dt1Agp2hikGfo/2UB9h4xD201xyY1v5W8VSaZ56Of8YJWEN0RpkVC2idfiqh4umDO7Dnc2y7y7FRsFFo0irpPvQnbNvzctYe9ju6jr6d7Ut/TNvp/6B55meHNL+xyGAEhooCB05DSfqvmiQVLVPdZPvem6pOMK+GgKdmxNx1kt2D119/nfnz51NTU9O37eijj8bv97N8+fK+fQ4++GAcDkfMPvX19WzcuDHpuH6/n/b29pgfSWZJ6xJmuEHvibOsOMEnxYKsoSrUFrvoXbcSAirynSjK0OK9TPDdwyZwxKSRvQXrwM0OSpjj+wNzfX/gGXMv/m3uO6JzAFDF+I7zJBLJ+CAXHHXjJkI+99xzOffccwfcr66ujn//+9/97rNgwQJefvnlDM1MMhzOWDKRM5YMsYtutGKRhnqRZ2jkOTS6AiEMzRhw/3g8Do0fHzudbz/yES3+gffPBOcvdLJkWg03PLMJXxIj31H+m9lLWcu9xi9GZkLDxZa1S5LRK9gxmO7E6aIaBPMmDO4YRafryFtonXoGk17/IS21hw9p1af9s4/SsmUl0548awhHJ2I6CiO/V8ynaa6T/O6t6Ftfo+vga+lqaaB04xOo7Zvp3u9yvK0NlK75S9rj2yiIcZC2U9njVnYbWsy/FfmCdm923A5CEFPF3VZ0gu5K0B3hOnY5KNhlSqCUjBwNDQ0J9YSLi4sxDKMvw6KhoSGhlEnvMQ0NDUyZMiVh3BtvvJFrr702O5OWAINcp8uvhM4GCLZGtiVJfU15uFOjzGOwo92fdHEi2xiqwvkLNObXlWAE2vj5m94RO7eX8PX/wuC3Abg62E4IhVv0e/jEnsA56jME0SgVHSM2J4lEIsk1ciECzL3IWCLJBgPUqINwUePyPAdrd3RSPMSavxVFHq4+vIo/vrmN95uyn9blUOGEuaVMUHbxp481XlrfFvP8Lgp52tobr23gEoEUo+QQMu01owwmdXYox5iuUtq+8Awt9esoHcoEVR3LyKPl/Ldo2/Q+k5/9ylBG6ZeOE39Hy6YPKZ68B23169D2/zrNW1dTUreA5vp1KEu/QfOOTZR5DJrbWim3m2kOapR5N9EiCijf+TqNlfvjArYdeD017/2C9sJZ5O94G9X0ZXy+o4mmhjslJvu/z1rA0lvHTh39lUvJ6HDNNdcMKIK9/fbbLFmyJK3xkpUpsW07Znv8Pr2O1FQlTq688sqYzIr29nYmThziIqJk+HjKoHIe7Fwd2ZZGnIdtheuxCqgoDJcrafOOXmy0qNrNNN3L8/Uay7PcjCwVzYTTcL8SDNdxvDX0WWxgkfiUbhx8S/sH+XRzoLpyFGYnkUgko4PIAfevFOokYxPbYlARTRo16gCKPQYOXaG1O0CRe/CuOhSdyRMn8iNzM2c+rRKKmqOuCh44wcNZ/+oc/LgDUFeg8ouTp/HzJ97noY8Txa4D/b9kuqjnYcdPMn7ujGJJR10m6XXiefurVReFEJFjgmmm22YC21FAMK8G76LzCLZsoWDzs+kfO9B1QChYRlQKuKJha67I8a5iLKMJs3w6oeA6AjX7469fh2/uMXTXr6Nzr8/RXb8OF+AtW0Drl16mYcMKhG0x840rUVs/HdyLzWHCTXyceAPycwhD658hGTyXXHIJZ53Vv6s23WZeVVVVvPnmmzHbWlpaCAaDfa65qqqqmPrFADt37gRIcOP14nA4YlJlJZln0PUB86tiYzuhAgJ8bRDsBtWI/AgBXbvC6bLuUjA85Bkas6ryafMGwwsRo6TXCSH409mzeH3Fas5/smt0JhGF1eOPf98Ol6b4WvBbgM3kUAMldPA17XGOVJeP4gwlEokk+8jUV4lkKHjKoaAGWjamf0yaQl2R22BWVT4r69uHXmhYqJiak/sP93LN2w7W9ZjcbNumdIDug8PlnDkKx09R+NVKF29viaQtNFFIk13Yz5E5wjh31I3WfX9aLrk4VWKwIl8m8B7wPZrq12EeeSMd6/9H3YuXjdi5B41QaD/1QXwr/o/qd3Kno142kIKVJJuUlZVRVlaWkbGWLl3K9ddfz/bt2/tqFD/99NM4HA4WL17ct89VV11FIBDAMIy+fWpqatIWBCWZZ0i3RJ7yyO+uIqiYDWYQgl4IdIb/9bWHFwHzqsCRD7vWhmNC3YXWW1YC8PUIdaoqKHQb+PwhgpaNZWX/Zk0IQV2Byo2H5PHU2jZerM+1RjuCjXY1G6nmwuAVlAbb2Fv5mDzh5RTlVem2k0gk4w4p1EkkQ0F3QeX8cGH5NAW4wXQXrC50EQxZrNregTqUO1Sh0F0wnb0dG/n3BJPZfwy7U4bQUHbgU4n4x4IyF9x+yjTeWrWWv6xVYwS7B0JHcLj6LjWiOfOTyQSyRl1WGI7oNpDIN5T02oGwHfn4i6bTftJ9dG1fQ/XbP8M0Rq5LXrrYrmI6aw+mvXYh9vsPUrjxv6M9pYzQXwrscEnpmlH0nKtVJ/XJ3GPz5s00NzezefNmTNPk/fffB2D69Onk5eVx1FFHMXfuXM455xxuvvlmmpub+fa3v82FF15IQUH4GnL22Wdz7bXXcu6553LVVVfxySefcMMNN3D11VenTH2VZJ9h95JyFkJhbew2MwQhb1i8cxb1nMiEpvXh+NGRB4YHhIKqCoqdBk5DQ3eqBDRBlepk0wg67Y6d5mCRO5iDQl0sTRTyX2sfAP5hHsyNe3RT0fwOh2+7e5RnJpFIJJkhF7q+5k5ELJEMBt0JVQvDvzetG3j/dAW9HqqLXNS3+djeOrQaVCGjAKt0Fmr7Vi5b5uSe17dzy0nTgZ1DGi8VqW4pXLrC/HKNOxdMY826T/jiv8Pptj8KfZmrQ+eywfmFjM4jY0hHXVbRVEGxW6fdl37DgIFEPl1VKMiS8y5Uu5ROpZzWmYezq62NkoyfITOEavamiWL08hnoHz2E7m0c7SkNi1FJgZW16iRpcPXVV/PHP/6x7/Gee+4JwAsvvMAhhxyCqqo88cQTXHzxxRxwwAG4XC7OPvtsbrnllr5jCgsLeeaZZ/j617/OkiVLKC4u5vLLL4+pQScZeeyh3BRFC6vJRH5VAzU/dlvZzLBo190EXY3Qvh0UFd0OUeZxQH4FdFditG5maoUH4fWg+0fOWe7S4JsLTH65InfFuhPmllBIJxccPJv6rZ8yZ8ZeNNVX0XLE2bRvep/a5T9D7dg22tOUSCSSISMddRLJcBiESy6tIsNR6KrChCIXuzqG3r7Vzq/GdhawzOriiIp2aiYV0FSfWaFuIDRFUJ2n8I8vzeH11RtY2+Xm5XUtIzqHQWGNb6FutNEVQbHboMtvDtoJlw3nXLpYhXXYXWkI8qOMb++vs63mKMrznHRteJ2yHa+hbH8PvXvHaE9t2IyY0ajXWae2A6PbrEOaq3KP+++/n/vvv7/fferq6vj3v//d7z4LFizg5ZdfzuDMJMNl2I66dGNCRYWC6vBP0AfelnAH2a5dgADDHc7aQODQVGZX5cMug/ruYc5vMKRx7TlvnsK8UsHeC+bz9qpPWDhzGq+vWkfdhIm8+NEmCotLefnjHby/M7MLLvcc42HJnEk0b19PoUsj5ImImLangkDRVNrO/i/NW1cz7cmzEON8AVYikYxPciEElEKdZBwgSF7dJOojNkhHHUB5voMitz7kWQHheih0oWTpji/dNJ2ppS4Kpxp8vmYyO+cFeab1UbZvXsMXN16ZlXkNGRnQjRi9TrjephG+Ab6SRqPJxJhECKzCiXRX+Ona47M0bVvLjH+dNFKnzii9KbC7Ov2YI1CnCehz1pl5NQREDi8qSCSSjDLsK8xQ0uZ1J+g9op2/I7Koa3igehEgwg0oALeu0m5a6KbFEFqNDYp0LuXHTFYoMAT5DpVFlRqlHp39J+iU1uRRi4PSmipOnNDJkQ+19x1TV6CwuT39OGtyocLcmiKeXB0plzK1SB049lR1bN1N+2f+xq5OP3Uf/AKrqwlH+4a0zy2RSCSjiWD070mlUCcZ++iuHoEn/UL56eDUVaoLXYPvRBaHrWgE3blTe0lVBIvnz2FXkQobY5/rOuQ6WoIapf5tdHq7KV9538hOTgp1I06vAOezdLrTaDg3Gk0mxjRCoeWLL9G+dSWTnr94tGczKHpTYFu7g5gj3ZFZc2A5CkHRwg47zTXiNeykFC2RjBw1Ra6Bd+qPISzIxuCIS5HVerr8mgLyqqhVnISaHWzu8DMxy19/A117rjl6EvlG/aDGdGoKvzvWw3qzkq6met5sduOxOninPkB1vsYzGyMN1OaXqVx7wizc3VuorJ3MGxuaaR6KwVlzYmsKHZ99hKYN7zL57Z+ib5cdY8cjltDwF0zB1fbJaE9FIskIuRAD5oZyIJEMB90dDtD6u5EcYgA3qdSNZTMsN4mt6ATdldAjbFx3zCT+8vZW1jSNbuMEoSg8M/9m9J0fcMjOPwPgn3ky3p1b8NacRmv9Oozph9LS2UXdaz/gra5K9lNWZ3dS472ZRC5c9VNQU+zExJP2/qOZChuNQ1NHfQ4DYedVEijoIDDlSIwNz4z2dMYWvbXrDJesYSeRjEP+euF+3P3Seq49ad7wBsqWiK/qUFCNEehmUqmbrm6D5l1+hplv0S8DrS2fMLeEnRsHJ9T5QhZCCPatK6BJ28lhe9bRVL+Ob+0BO4MOLj16ISfeExHRppQ4afKFJ3LoRIVHPrGYW+ke7EuJoOh0H3QtvjX/oWzjv1HbNg19LElO0XHU7WyzirB1D1VVtfhW/B8FTh39vfswuraP9vQkkiEha9RJJJnAcIPmBF9r7PboQGeIQp3WI65lsqj6CXNLWVrUEpOOMFosPuhE2tcWwrNhoS4hOjQ8BPNLaL3wXc76+Wt48LJHlc6D+22H/34v8xMaadeOpA+BQFPSF7x6nXXEHTPSAp5DV3AZ6qCbZIwGlqtotKcwZEQuq8wZJNpALTuASiTZZ+m0UpZOKx3+QIOpWzwUVB1HUQ0zCg02dm7F78ve9aG/kctcIivlVPr7/v/iHIU5JYIjFk8n2Lxx6CcRgu6qvemavC87RAlTX7wUtfXToY8nyQmC04/B2rAiXIjIVUxn7cE4aqZTX7Y/5W4N38fPUL7uH1KclYwppFAnkWQCzQmaC2hNvc9wUyIyQW+R9J5V30uX1fDYhw1s67QJmqN3MQh6KjEL6ggKDZQUa8Q9QWEXLrzosOB0sILw2q/DRZgzhUx9HfNkswtsynMqgrJ8B4am4DQUSjxG37+57rYbC7h0lUAoRz6bcdfRjNFzjRv9sEwikQyJQTYNGzQ9zro8M8ikSVNpCHagCDsrF43+vrV+dMAwU4RT0N86na4KDqgRFDg1mjJ0vpC7krYvvUD38r9Q+2qO1UuWpI2/YFK/z1tFk+mYeCjGki/RuvlDalfei7LjQzR/68hMUDKuCboq0L07CeRNQAt20lZ7CHn+RhoL5+NpXok661hY8286pxyNe/OL6HucwcfvvMCft5axSKxntWMhLt9OOnHhJEA+3egiRAHdeHFw3ii/PinUScY+QoCrqH/BKBeEut4Urp7UrXP3Dhf6PecJLw0dwQEOziJCpe3s/9C0fT2laazS9sWktUvgjPvhr2eCry0zc5FCXdZRVUGxR8+4gDXaqbC6Iih1G6CruD2Rf3ubX+wOwl22XG+1xS4qChzD78qYCXqvo7qW9Zp14/edIpGMQ7LtqOtF1ckvr8Ppa0Tv2IbfzsJ5U1x8ztqjnLll/syfj9FzEHvLFtB84Xt0rXmGCe/chOJtHvggSU7Qccwd7FTKKE5nZ9XAdBTRefw9NG1bS03zWwS3fUDRhv47dEt2XwJ1B+MPmShTDqTD68dTNokWv0lhWS1NXQGK6hbStHMLZcWl7GreRWnNdJq2r8eumU7rhhW01R1J5ZQFNBXtgVUwkbaKvZkwaSbLGybwj01e/sHBVLsNtpuBlHOQQp1Ekgkc+UncYMPr+hpNb/fDjNzkxzlCCpza6Ap1EA5w0/wbJdysn/Mv+OAv8Na9w5/HOBfqcuHGv0/QGkSaa9rjJkmFzTYH1Dr6fb5vXgMId71CY1YFvVEUulL1xk4HRRE4FXXYJQAy+heNW/iQSCS7OSPcsEuvXgCeEuyW+vC5FZ2gsxwjMHyhKdW18oR5pWAOvomEr19HdPhs0V/dI67Z6S58pXNpPfd/hF79BRUrMhBPSrJKR83+BKceiVW/bnAHCgGKin/hOTSVLUWbvBR//QpKP34oOxOV5Cy2oiOsIN69LyHQuA72vZjOze/hnnscLdtWUzR1H5rq11FaM52O+nUYNdPx16/DrJyOWb+ur+GP7SoG0TQKF67sI4U6yfjA8EQ6dOluaK+PKzY0PKGut/thRmrVxd1gXnfMJD5Yt4kbX/cOf+wRIOG2uGgi7HE2vPMHsIZZI0zWqBs3aKrIat24v5yUR6tezbE1nYM6LpVw5zJUCqK2Zyd1d/cVlcSwpMI0ULLgsBt/MZ9EMn4Z6cwJzYCSKdjuGqxdPlB1gnk14HcO+zqU7NKjCJhb6aZpcDodHmMgoa7nnFE3uaPmnhaCtmknoe/9ZdwPn4pDNiLISVrOfZVdLc1koLIkgTmfoblwEcbk/ehu+ITKD+7MwKiSXMDSXKA5aa07Co/ZRkPxYpydWzH2v4i2LR9RVDmZXS0tlEzfl6ZNKygtnU63X8HlyMd0lozIHHM9zJNCnWR8oLtAd4Z/L5kSTsUMRN3A50LqawpmlrspDepjRqhLyQXPwerH4ZVbhj7GOO/6mutfCJlEVwTFboMuf3b+T8vdCntOLkJ0dw1rnOE4AQdK9x3tdOBohBj+zVdGncWZZhgpsdF/l91XSpVIxjgj7KjrRdN1KgpsNFVgKzpBdyVkYaHnK3v07x5PhdtQaeoeeMEs2owy2rkNtrOITftcS8GOt6ha9btRno2kl2D1Epor9kV3l0Fra2bHnnYM7a7pOGcfRWvjNmrfuRG1fUtGzyHJPJarhFc6awmi0lq6J0trDdTKORRNmM2WVi+lE2bRtH091Eyna8MKusv3oNJZTNBTDUJg68PoJD1EcjCCTYkU6iTjA80ZdtJBWLSrmA3+jsjzSmaCpt4b1YY2X0bGi+alixeyZcunnPtEFyErd28XU97sF9bCnBPgk6egYcUQB89+eLi71CvLBbJVD28kSEdk622ckSqdNr6xhsiyTaE/138mHG0ZdRZnir5SAjoQymhK7Nh710okuzEjVaMujt7rYtC0qChw0NyVut5RuiS7lh9cl6LZ1wCUeXS2tA5c1y6mk2wOhKAhZzEtk44mr2oqxhu/wujOYOMyyaAJGQV0nPpn2uvXZcRJlwqzdBYBv0rbF57h0Nte5qf6H1gk1lOnNGbxrJKB8C46j0DbdsSis2jftRXPrMNp2rmVktq5fOn29wHByXk6U+ZOocJuxC6ZCu0fj8t01JFECnWS8YEQkF8NRo9Y5yoOi3WRHTJymt6ArKkz88V8850alR6Fw6YX8vTa1oyPPzQS/24Dxm9n/w0aPoS/nDn4042AUJcs7XEsCkljgd56eGPx79zrtEtn7vHptCPZ8TZdRJYzT0eNPmGuR6jLIDK+lEjGEKPkqOtFVxUq8p20e0PDTsWPv/S8cskifLs2DGmsHx9Vx2X/t4bzl04EWlKfM1uOumFeSAOzT2N7wUKmPfUlFG+mes5KBkPrOc+FUxRH+Lxt5PGN4KW48XGW+gITxU7O054a4VnsXlieCkKo+A/4Hr5tH6Iuu4LmbWsomTivr16cV6zD7SzG1pp6FkjCn/G+EHMMxZojXFZ70EihTjJ+KJwQ+9jIi/yew6mv8Xx5n8ocEuoSGdAUpBqQVwlCzflU1sGIMZKhM5b/zr1zH4z4ltqNN4ail7FOXNMeiUQyzhGj46iLpq88gK5mrDv14ioVj6Ey1DyOumInvz02j9KaUprqkwh1PUJa9DecnRMtvmNp+9y/6fr4BWr/d9VoT2W3w8qfgN0xeuV5unHyB/NYAH5vHkchnVym/R/TxDamKtJpORy6i2dhqU52LL4cvXkdJft+ju1bP6W0Zjqt7umUKiq2ml7afe5dNWIZO3ceEWQEKxm/RK/ijVJKRL/03khqrphArsyjc9Rkhac3jnaVkOSkfSH++lvQ8AH848vZnE5GGIoYMxR2d4fOWBbsBlNvLnXdu1wPY7LPiN3/DTUFNroH0ZgM6ySS3ZQciPMSygMM8ToUHSv8YP+RqeEU3UwiF6uv2M5ivOULCU7YF33bm6M9nd0C37yzaFcKc0os2GqXs5VyLgxegU6IWWIzpaKDs9Tn2WEXc7T6DtVi+J2XxyvttYei1SxkR+ECistqqG/pRAiBWTodv15MyW63uJnbcd7u9r8h2V3JRUddbwBnuBICuc/N1vi0Q9DlD7K9M7cEu7RXWl1FUDIV3KXQPTbSFbLdqVQSZiwKdtFzHux7pFfki74RGunXnUmROKebSkgkkt2THBDqUhLn8LUVDb+zHDvFTfExEy1+9p7K0inF5Bsjk5mQYyXqUtJx0n20bF7BtCeGUF5FMii6D/oxbdvXZ7Um3XAIovGRPRVseMlaBMA1oS/xvX2cPPP2CrbY5Tx4pEXx1ufYtH4VS5S1ozzjkcfUPARnnciuovm45xxD064GSmumE6pfh1U8FVrDNcUzsTCZg0bcAcl1A4UU6iTjl+grRi4KdfH0BHKaouHUBFceWoPub+KLj7eP9sxiGPR1+KuvQNM6+NNJ2ZhORsl2p1JJLGNVsBvse6T3dVpRl6FsODj7++tloplELznZVCIVw0iBzfUATiKRRJFDTpCExYy4rtSq5sLvqkQzk9c7LnHCo1+YSm11Fc2bPxqROSs57qjrQyhYugf/zJNQtryG7t012jMav4zJL0FBp17Ku/ZMAHyF+WyecA2nr17F8cobfH8fndqVdyOCXaM8z+zxp9CRHL33XBxzj2NXWwcldfPx1q/DHV0SKguMxXdLrpM732oSSTYZC0JdTyCnCrNvpTUXdYtBx2+aA5wFULcUtr8PwdGrc5EOY7lT6VhlpFKPM8VQ3yPKID89QpDVLoK7BRnsAiuRSHIQRwH426Fy/mjPpI+Uixk91yOHqgI+bEUj5Em+kGBoSowLO9vkelH1eLqO+DlN29Yy41+5vwgsGVmiPzaCiID0hLUfF9Xm49n3SzQ1bGRC4/+zd+fxTZT5H8A/kztN77uFQgsoVwGhVSi4FpRTQF3xQDyoB6siyoqogAqIAq4iHqir6wG6uqL7A1bFC5BDEZBbuQ+hlKPlKNCWnmkyvz9CQpMmbZImmUn6eb9efUEmTyZPJpPJN9/nWosSowIJh79CjaBF2OntEtS26ao63Y6KWhEj9g/EySoFKqBDTutIxEW1hlh+UOrqyZrcL3tM1FHoMtcJkPyQqPPbZLtKNar1SVAYKxEfpoBWJaC6VkY/Mr2tym3/Bk7vAT4e7tPq+Jp1pdJgSRqFEk/mgZOS9Rzx9y8bpSBcWkWwieR9ROWj7uWNx4woCEzcD5hqLA2CQUZUqGEyRAGSjtq1XOnkPkedU4IC1e1vhHBsEzTlJ6SuTUip1QV6jVffsRtQBScNlUoNIChQdcV9uHDiILRX5qH4xEEkROhx7uQRtDj4OS6c2IvYqqOBrLbbTNEZqNQlwDj4NZwvPICotr1QfOIgzh+oQAWkm7onWC4bdcm9EZu/RCl0iXXmdvNxok6nVgIKwOznAfmRWgV++FtX3NlZ49fnccnJFczrVywIgDYCGPUlcOUDTapWsJL7F4LUrD3r9EE0FLYpApqY9MNTBNVcdQo1jLoEec9jRUSeU+sBXZTUtQh6ddudfBva+vf7ofy6f+Bo7hy/PkdzVBPeQuoqeE2s80tFENw/A80RLVAblogLg+dh0eVzMKZmAqYaR/unkl4oT+yB05eNRMWd36Kw11SIYXGo1cdLXS2boEzUSV2BRrBHHYUuu0Sdbz+KGfEGxBm0OF9ZA4PWPx8jUaGCOSwJydFhMKjlcylpcgDXIguorQY2feCT+vhLsPTuCkXBOHedWxw+PME25NdRUM1Vp1SjNiwRamPDc37atcSHyGlHRNJwbMyw3q42yu+aWfdyJ68lzBpnVkdIXYWgVDr8Q0R+c7/T+4yG1ADXJjDc/Vo3KTRYbs4GAIwaOggtFGehXfsSNBeO+a9yruoSmYbShB4oumoSxLLTSJNrg2MwZupkjok6Cl12iTrfXtQEQUBUmBpRYWqf7rcuUaGGKTwOUJqQm6bGv7Y7n3Q40HxyHY5OA/pOATQGYPVswFwL1Fb5Ys8+4zKJolB5PTk9eSZkE3b+0kBmyRcrehERkfscGzPUSgUi9WqcOO9irl6lDoLJCCkGPAnBsuyrM4IAsy4GiqpzAX3aiqseQ0XZecTv+SSgz+s7ruOCc5ffguAbTH6Rw9BXb/RuoUK8QY32UbUQlSoYM/qjSJeOBB1Q+/uXiD3yPRQVp31SXVeqO4xAZXU1xH7P4czZ0xBV+gbLN7VxMZQbJ0W4OBdk/pr5S5NCl6FOd2CNQbp6+ECiQYFfRxkwc20ZvisIzt439bTuDajDgMd3A/u+Bf73sNQ1AhRqwJAEVBa7LsPJ6QMu2Hue2bjojsrem4EhKlQwhrmfZGdyk4h8odFpAi6uTm2OiofpTBFgKgtc5ZxUKdh61EmlKnsszp04CMXVj6P4VAFSz27GDwUCog59AwHAdcptfn3+11JexoPpp1CsSkSs+SyK1cmIM51BsTIeCRf24xSiEVW4HuHVJ6E6s7v+DpxMC3Sq21iornoAxtOhMeefINgnod2N3PVqAd+PycSp/B12282x7XCu/W1QXD0eZQfXIaH8Tyj2L4XufNMXbTifeg1M2igor34c54oOI+qyPig+cRBxuigA/k0K+iJJFwy/igQ4zkUs7ziPiToKXSot8OQhy9VHrt2EPRCuEaBUSH8Z9Pm0fEo1kNABaNUbKFjn4517UZeIZKC6xLbJl0kUeX8dyF+oJrQCkYiUQ0up1HUQFWoYw5KAYE/4ElFQsfasc8naAKjVoyYqA2L1n4GrnBN+nn459Kj1gKBEdZc7UXBuN94wdgAg4vc7wnH+1BGk7vkItTWV0J/b59OnLdK1QVX3G1B14iCqU9uh+sRBVKcORvWJg6jsNBjlh3egIqE72u7/AHCaqKu/yRiWBJU6zKf1lFLdVV8Bz5JJSoXgeuVltQE1URmo6jgAxan9kXp2M2oLNiAq/weP63ik35uITL8ShUXHIABIikhFbVmFx/uROswLlstGMF3fmKij0GaIC8jTaJQKXDD7f6WdUZeZ8U2+tElHv1zfBAHo85j0iTonQqY3VwgIqaGw4cmWxHCA+PNIubOohODYjClTdlUM4tOLiIJTbVgiRE0lxFqVraddoKfaEIPpl6xsCTDFt0dNjRJlIxai+PgBJIQpUXx0D2KPfA9d0uVQ7/gPVNXnvX4GdxeeF11O/1M/rjWGJaLhAZbBJxCNhNWZI1Ecmw1VWjYMv7wIADh6zSswXN4PZ08eRXyEDsXnzyHl/O8oVsYh7ZenAADG1KtQE9UGoj4GQMPz34midRVbBie+IvdDyUQdkQ/EGjQoLPH/HGtJYcA1KWb8XChd0shv4Zs6DLjxLWDj+0Dh7/56Fq+Fam+uYGRN2LkdpcpGnU9PZApgMtol7KznmLekOhpBtagEEZEciC6WoxQUMMV3hKmkSrKpNpim8wNBgDmmDarPl6Mo80EkZXTBsRZDEJeQgvL9qxEZk4AFi/6H/oqt6Kw44tYu3f4l4GSIq7VOjmrDEt3da1Co9xL9fXIrL8VwJm00oAmHqFTDHJ0Bc4UJVVfci6oTTR8m64wckk4yqIJH5F5fdhEh8gGDVgWFAJjM/g9vJM9N+LOlNSIFuOZJYOTn/nuO8GRLUtDDHk3W5JCaPevIaw6fHaXakrBTWM5DWwLSD9gCW4ebvVR4xIjIHwwaFZRKAUaTi9ngHK/X1muWSh+QHna+DGXFQF1IZfId51EtBAHQhKMqtgNMLXritdpbMbxmJjKrPkDJrYvxn9p+DT7c7d8DLnvU1d+BqNS6uVP5sp+DzPuhr+QZdsT1Pf7iJPIBg1YJvUaJKqMfepRYAzRBig6wTr7EA/G0aT2Bp48AD/wEjPovYPBhC19kCqAJs/xrTdh5kbgj8pirKEapdnr+BVtyzZ0hsLJg7aWiDkOtPhEiV3AmogCK0KkQoVWh2ujmsg3Wa5Ym7GIPO1/GKk7ivGD8wR2Ula7PDAUuIAymhE74xdy1wbIKd2MEhfs96kJB3VNBEOx7rgbyLBH90Nzn37csNM+Hhsj9I8BEHZEPaFVKROrU/knUWQO0iz8mpb6oBKDToIVSY1kEpEUPYOgrQJfb/PAcavvEnVJ9KWnimMSz/qtgMo98zKFnnW1zA591T5NigbhuWIfABk2vU9u1Ve18BJrMAzgiCk4KhYCkSK3LEYlSC42UV/BrLNHj/ggbVyda8/iSE6TK1AWc9++nb8+EkD7IASXTrwii4BMTpkFVrf/naJL6a1WSRsvwJCD7PuCGt4Golv59LsfkncO/Ko3GkiBRa+yHojgOSVGo6g1R4Q9/8hVPk2I89YiI5CNKr0G4xsvevAo1jLoES2OmHwSsQZaaxFVHOUeii/PEcbtZF93EGsmD4+kb2CmD/P9kco3neNnwPY73IPIRg1YJpULw34VKECCIZgAhuOqru9oPBpI7AytnAgeXS1IFa4LEaDIjNqU1VGrlxSEp+ovD6S4m6NRhqDVoLt1W6SEqwwCUNP4kCudDISnYNfLpsfbm9BITwb7Fw0lE/hKhUyFc6+XPMKUaxvBUoFrnl/nqgvIHdwh+ATb2Prg9y4Sbc9TVXH6jmzsMLonhalyZooReH44wtZvDzWVIbOSMCL1PgH/Yz2Eo76PGHnVEPmLQqqBVKVHhp5UPxbAEKMxGv+zbo3pIXQEAuOkdYNSXklbBZY8m2yptavvbmjCI6rBL5RQq18k4a68+zp0XWhrrjmp9360USp/N+xZs890REYUylVKBhAgtFILg1XVeVKhhDEvyS3wQlNO9BWWlG+Ojoa8uv/8vbT/d+T5U9Jrg5g6DiyAImJVrwOs3tQ1wLNS84q5g/AjKPTRmoo7IR3RqJZIitSit9E8yzRyehFptrOSXfd9eiL18NYICCE8ERv7HP3PXecDrRIo67NK8ZAqVZXivY2LOxdxl1EwICltCWK9RNilhF8jrRtAsKnFR3VbqepNQU6OOHj2KY8eOSV0NoqDTKi4MLWL0TbvOu7mKtUtOrnMc+hoc3E7UuTo36jy+pM0wQBX8K74CgE7VPNMbUocswXjZkHuU1zzPZCI/aR1nQGy4xj8XS4UKNZGt7CalaFJwFgrSegI5Y4FuowBdlCRV8HoC/bqt4AoVEJFsv6iFY1n2rGvWmrxQQwCjkWBbVEJUqGBs7tdSD9XW1uK5555DVFQU0tPT0bp1a0RFReHZZ5+F0Sh9z2+iYKBWKqBVKe1uu3PttDaGKBVC/V78PuDbH9wB+vKROkvhB429D+6u+iq6WrVErquZNFG7eB1uuEyNcVenSl0VPwi98zxQrB+XYOr5x6iUyId0aiXaJoQjv/iCX/Zfq08AlEcBVFtuG5IBpR+vOE6+D2R5gRv4AnDVA8DWT4FjvwEnd0ldI/e5k4Sz9qwzGZ2vRMsEXrPRUG+1hubaYGjXAIUatYYkQGk/jw+PmWvjxo3DkiVL8PLLLyMnJwcAsH79ekyfPh1nzpzBu+++K3ENiUKXWqlAYoQOpZW1lzY2tWedHTkGesHBl/lCn6366jIhF5rfckqFgEez9IhLTUbxiYPSVSTAyeOmPlsI5rqdspujTuavmYk6Ih+LD9dApYhAuEYFkygiMVKLs+U1vtm5QglRGwngtG/254XGJjOVjKAArn0GKDkK/KtvwJ/ereF+zu5ynJesIXXLasIu/euYwGPiTp58kOW29rggktLnn3+OhQsXYsiQIbZtXbt2RatWrTBy5Egm6ogCzdqzTl1/xXlPcehrcGjyYhJyz1J4oVOcAtlpESgpOiV1VXzOGkL6420LwVMhJIRmn1ciCQmCgBiDBgqFYGv1VLm7hrqb+5eSLHvUORq3BfjrewF9SkmH+1kTeJowzmkna77/8NgNgaKmUahhUhtsNxm4uqbT6ZCenl5ve3p6OjQaTeArRBSCvJrv0wdDYYMizmsG/N+jru724H/TH7gqCXOvM0DVTOMhqWOW4D+D5IeJOqJgZx3uoNLDqEsAFK6WYfeNoLgQ66OBhPZAxxssizTIRPMMHcjGD79+rAniME3DvSekSPAH26ISUKphVofbbgZJrSXxyCOP4IUXXkB1dbVtW3V1NWbOnIlx48ZJWDOi0NGkBkC3h8I6WUzC82eji3z5Nd/4HHVu7sjV74K6jw+B7Oxd2UmSN1o2llwlGQiiRcM49JUo2FlbTzV61IYlQm0s9fET2F/EguqrfNhrwIEfgf+NDdhTyiI5YZ33jkNhm412ieEwXwy0nZ1/UpyN1h+ZlTUmSx1kHhCR+7Zt24affvoJLVu2RLdu3QAAv//+O2pqanDdddfh5ptvtpVdvHixVNUkCko+iSNsPes8j9pCIGfTLLibk3K5mIR9pq6p1ZFMr9YRmHoVEKlToVjqytjxfczTcBjFEVeekntUykQdUZCR+rdu0F2IEzoG9OkckxOScJzLrqZCurpQQCgVApQXQw5n55/U141gJKg4hNOV6OhojBgxwm5bWlqaRLUhCi0+nYvUi0UmOEed9wK7mISbT+ZijjpRE16nTHCmBF67Lgy53S6TdtEIIj8Jzk8lUTPW0MqOgRB08ZtEGQpnLeLsUdTcBe7TYz3/dBoFEiO1kp571rqcLqtuvLCccK5Hl+bPny91FYiaDW962Nkeo1Z63bPONxj3eKuxRJ37i0k471EnaiJwoudziIhPgxiEIy/GXZ2KzIQLUlfDNT/FXa7iuaY+XWh/UkUn/5P/aw7JOeqqq6txxRVXQBAEbN++3e6+goICDB8+HAaDAfHx8XjsscdQU2O/IueOHTuQm5sLvV6PFi1aYMaMGRCDrhsRkZ/wo+AWSReXIHkK4PdI3bnrkiJ1kgYj/lhUx1/4Xd+wU6caXkmvtrYWGzduDFBtiJoH6/Vcr1G6nbBrSgzCHnXBoclz1EFEeUpPGFtf46sqBRWVUkCsQRM88+j6VdOPgQhR9pkvx2Sm3PtPyD9q9sJTTz2F1NTUettNJhOGDh2K8vJyrF27FgsXLsSiRYvwxBNP2MqUlpZiwIABSE1NxaZNmzBv3jzMmTMHc+fODeRLoBAiiznLvFa/zj6N3+R+hfSB4H7/KVQ0g4+a71nnegzCngb+kpKSYpes69ixIwoKCmy3i4uLkZOTI0XViEJe3eSb17GFQuUwFNbPcR55zWeLScg9eyIRtVKBOIPGo2S2nJN78qsRNVXIDX39/vvvsWzZMixatAjff/+93X3Lli3D7t27cfToUVsi79VXX0VeXh5mzpyJyMhIfPbZZ6iqqsKCBQug1WqRmZmJ/fv3Y+7cuZgwYQKHrpHHZDFnmQ+xw4lnQu39p6aQ7sMj9ZD5YGH3DlnneuQcjzaOPQ6PHTuG2traBssQke95HVtYF5lQX0zYCWcB2H+G2aNOLhqbo869vYiuetQF+bX66oxIwBjYoa9qpQKRBg0q3UjuBffRDV1iEL0zIdWj7uTJkxgzZgz+/e9/IywsrN7969evR2Zmpl1vu0GDBqG6uhpbtmyxlcnNzYVWq7Urc+LECeTn5zt93urqapSWltr9EflNA1/MokIFY5hnkwZ7Kngub/KiUgoI07gafuBn7BnU7EndxqRRKZAUpUVKlI8mSCfZ8leDZn5+Pu6//35kZGRAr9ejbdu2mDZtWr3pSzjFCZEbrAk7P8aLnpJzbyU5crtHnctVX4P7mnd5Qv3f+qGuobdc6jjP+hUaTGeV3DtgeXV1Tk1NRd++fdG3b1/k5uaiffv2vq6Xx0RRRF5eHh566CFkZ2c7TaoVFRUhKSnJbltMTAw0Gg2KiopsZdLT0+3KWB9TVFSEjIyMevudPXs2nn/+ed+8EKImEBVqGMOSAM6LJjtqpQJhGokCYmvPIJMRMCQBlfJawJ78Tw6hSGKEJUlnNLF3KXlu7969MJvNeO+999CuXTvs3LkTY8aMQXl5OebMmQPg0hQnCQkJWLt2LYqLizF69GiIooh58+YBuDTFSb9+/bBp0ybs378feXl5MBgMdlOhEAWDpk6vIeqiYZTJACtrbyWjRomYMDVKq2obf1AI8/eqr8GVUrGnl8cpW5/deyKHyCtwguVsqtsmJ/d3yKtf86+++ioiIyMxd+5cdOzYESkpKRg5ciTeffdd7Nmzx6cVnD59OgRBaPBv8+bNmDdvHkpLSzF58uQG9+cscyqKot12xzLWVlZXWdfJkyejpKTE9nf06FFPXyY1A76aqyzwFxWHz0PQXIrlp+4lRJIWY6UaiHDRgq5grzu/Y48dCnKCIKCsrAylpaUoKSmBIAi4cOFCQEYUDB48GPPnz8fAgQPRpk0b3HDDDZg4cSIWL15sK2Od4uTTTz9F9+7d0b9/f7z66qt4//33bXWrO8VJZmYmbr75ZkyZMgVz585lrzoKOm4vNKFQX5ybzv473hzdGiZdbABqWp+1B51Oo7DrSadWCIiP0CI+vP59oczxFfpsjjqXiToKJn7/epJ577LmyKt89B133IE77rgDgGW46apVq7B06VI8+uijMJvNMPmwtXzcuHEYOXJkg2XS09Px4osvYsOGDXZDVgEgOzsbd955Jz7++GMkJyfjt99+s7v/3LlzMBqNtl5zycnJtt51VtaJkx1741lptdp6z0vkyBpMGU1m/y8uYAvIfN/kxN8xviHZarCuhsEq1YD+Yq87JuxCjty798sFL28NE0URl19+ud3t7t27290O5LlWUlKC2NhLSYbGpjjp16+fyylOJk+ejPz8fKcjJ4jkrtE566xDXZVqOM5J51cNXA+sPeigViLMoLHLPKkVAuLCLt3nzpxgwU4QPIux3V/11cWx4xeefwlC0Aznlnft/EfuobHXv+IvXLiAtWvXYs2aNVi9ejW2bduGLl26IDc315f1Q3x8POLj4xst9+abb+LFF1+03T5x4gQGDRqEL774Aj179gQA5OTkYObMmSgsLERKSgoAS+urVqtFVlaWrcyUKVNQU1MDjUZjK5OamlpvSCyRN5q6uIBb1xRbQOb7b2F+rwe5usNgXSXsGrqfmoCfHuBS7+Kz5TWNFyZZWbVqldRVsPnzzz8xb948vPrqq7Zt/pripLq6GtXV1bbbnIuY5ErOK80rlQKiw9RQwezxY4Ml4dEU9XvU+WgxiRAc+jquW3D0EvRk8YlgVPfzGIwdOeR+NfEqUdezZ0/88ccfyMzMRN++fTFlyhT85S9/QXR0tI+r575WrVrZ3Q4PDwcAtG3bFi1btgQADBw4EJ06dcLdd9+NV155BWfPnsXEiRMxZswYREZGAgBGjRqF559/Hnl5eZgyZQoOHDiAWbNmYerUqeyRQLLj92DM6VBx/z0dBRATdvKnCffZrlKjdTh+vtJn+2sKtVKBxAgdSivlM/+QW1/vHB7u88ZYwDLFSWPz/G7atAnZ2dm22ydOnMDgwYNx66234oEHHrAr648pTjgXMQULa2OwnFiTbFq1GeF6tV3S211qhYC4i/PXhWrCTiEAJg9ibLcPgavFJII4oL+2VTAkvvxwjjYQrEjxiag7Oqju2dQcEuuB4FWi7sCBAwgLC0ObNm3Qpk0btGvXTtIknbuUSiW+/fZbjB07Fn369IFer8eoUaNskxADQFRUFJYvX45HHnkE2dnZiImJwYQJEzBhwgQJa07kXFN65lHgyfLrypqQa+z+morA1SlUuRsUD3sN2LkY6POYz5567m1XYOpXOzHmL218tk9fknMvEBvr8HB+FnDhwgVs2bIFRUVFEAQBSUlJyMrKsjWSesLdKU6sTpw4gX79+iEnJwf/+te/7Mr5a4qTyZMn28WBpaWlSEtLa/iFEQUzhcoyhYpKD6MuAZqas17vyjbEtbbpvaibQ8LOylc96jhHHQWa9XMq+56EMr98eJWoO3v2LP744w+sXr0aK1aswLRp06BQKJCbm4t+/frhoYce8nU9PZaenu50UuBWrVph6dKlDT62S5cu+Pnnn/1VNaImkbpnZxA3wFFTuJrbrinYQ8m57Pssfz6UFhuG+fde5dN9NoVjYk6tVCBSr5a+4YHXtwYZjUZMnDgR77//PqqqqqDRaCCKIoxGI3Q6Hf72t7/hlVdegVrt/mfa3SlOAOD48ePo168fsrKyMH/+fCgc5l7y1xQnnIuYmh3rFCoaPWrDEqE2ymu4t2PCTi6aEqF7Gt67veqrqznq+IUXVBpfzE/mWSeZCKaz3us0Z9euXfHYY49h0aJF+P777zFkyBAsXrwYjzzyiC/rR0QOpL4M+/QCJ/WLIfdZe9YpfJhU88c+ZS2YwgP/sg7PkmxRFU/4I0kdpCZOnIhFixZh/vz5OHv2LKqqqlBdXY2zZ89i/vz5WLx4MZ588km/PPeJEyfQt29fpKWlYc6cOTh9+jSKiorsesfVneJk27Zt+Omnn5xOcaLVapGXl4edO3diyZIlmDVrFiZMmCB5QxiRr7ndW9kP38NKJRBrUPu115s1YRcKn1zHb0Ofrfrq6ue+ko0P5Jw3Q1cbO1+VAKL1/r0euCOYOpx41aNu27ZtWL16NVavXo1ffvkFZWVl6NatG8aPH49+/fr5uo5EISkohnoB9Zr4guj6Rv7ApIX3gik6kIgU18VG3xbH4eHN+DPwn//8B1988QWuvfZau+3R0dG4/fbbER8fj5EjR+L111/3+XMvW7YMBw8exMGDB21zD1tZR1BwihMie24vYOaH65lKoUC4VttAjy7fkUuOvSnf8p73qHOvnKiwH/o6vmYsBmeo0FMbAeCkZ08qA6M7BUEDnwSa+hmo+3B/LIKhVAqIMWggBkMDrUx4lai78sor0b17d+Tm5mLMmDG45pprbC2VROSepq7+ahXoH7bMNXhPLoFkkzjOWWcdvqoOs/+3GSYxqOl8dV30q8bmdQxhlZWVDQ5TjYuLQ2WlfxYtycvLQ15eXqPlOMUJkQ8o1AA8W/DHaS+ckAh8AsPTI+X+YhL2ibqvzFejdbQOPT18Pjn4+r7OUJ3bL3U13OOHc99fnyaf7Je/D33O6znqmJgjkge3fthaJwVWePWRt8PrMNmxTrAPAJqwS/+ajIAhCagslq5ussNPjyO59SzmO9Swfv36YcKECfjss8/qLbxw8uRJPPXUU/V62xGR9Dy+1irdT9RZE3R6jdLnvXCCTZO+yRwe7LvFJOq/H8H6XRes9Q4EX0RRzub3d/uxPnj+QPCknlLHpl79ao+MjMT58+fxf//3f/jzzz/x5JNPIjY2Flu3bkVSUhJatGjh63oShSyPgycXxaz7OVvuZFUt66TAyqZfRptyEW/umtX8R0o1EJ0GqPXsZUcuWRsaHMktgUcW77zzDq6//nq0bNkSmZmZSEpKgiAIKCoqws6dO9GpUyd8++23UleTiBz4o7eyY4LOg0nT/CD4vys8TW+6fbgVobPqqyiKUAKIrDPXmTfzqQWGb+pjfX3Vzek3hEyoAzBsvyFeJer++OMPXHfddYiOjkZ+fj7GjBmD2NhYLFmyBEeOHMEnn3zi63oShSxPgyfBxYVfrVQgMUKH0krPhio09myOmKYjt9UdImjtZdech8cyye0263XRaDIzYScjaWlp+P333/Hjjz9iw4YNtoUcrrrqKsyePRsDBw6stxIrEQWfhhpLVGo1ohPToNdpvUrQKZQC4sN5XXfkt1VfnfSoC1Yi6s91Zp1PzboCsE6jsEvcyTeR5x7r6ztVZV9/6+uyvl5BqJaohhYifNshIdjfN1/wKlE3YcIE3HvvvXj55ZcRERFh2z5kyBCMGjXKZ5UjIhliroEA7ybUd0zcNWVf1CwExZx1zYxCocCQIUMwZMgQqatCRB5yt7eyWqlApF7t9Nqr1mgRGRN/aa5aD6kFBRIifL3IRCgEpwLqvg5fDX0VQylRV+dtdkzkWFcAhlqJsDqJO2uPT+ttvyZ+xLrvn39ZE3jW11s3SSZJgsvHL9gfC1o4ctX5RS68StRt2rQJ7733Xr3tLVq0sLWuEpF/NKmxQqFu8lx1oRAKkQ/4ckJ9676sPe6sCTtFiCXw2KPOa4EaCsuh/e45cOAA1q1bh6KiIgiCgKSkJPTu3RuXXXaZ1FUjogZ40/ihUKkRGd8SKrV738XWBIpS2fwaWJoSo3s6ctjbxSSCmbLOQbIl5lwcOMf7rbcDkrCTQN1XE+dFgosja+XHq1/rOp0OpaWl9bbv27cPCQkJTa4UUXNk/SF6odqXQ1cd+GCuOp/9jG2G3wjN7xV7yHFFWetCFY5DZrnCbLPDobDyUFJSgnvuuQfffPMNoqKikJiYCFEUcfr0aZSWlmL48OH45JNPuOAYUQhRqbWIS4wDjC560Dk0qtkSJMaqANYy+L8TPH0FTVlMItBHy3GYpuPwVMdyrr7jFT6YB9Exgedu3dypp1D3V5I/Vn318S6t8/1VKgXIPa3elKGwwdoG61VfwhtvvBEzZsyA0WgEYBmPXFBQgEmTJmHEiBE+rSBRc2H9IerTiSttPeiaksiwvyAG68WOgpg1gacJc/6vOgyIaAFEtWDyLsTZrpPNeFVBKT366KM4fPgw1q9fj3PnzmHfvn3Yv38/zp07h3Xr1uHw4cN49NFHpa4mETXC3V7KduVcxZTW72hnsWbw5888EsgY2ZvFJJ4x3uefylzkKuml1ygRZ9AgTG3/r+N3uVqpcLrdSqmwzE+n9GFjnTVx51g3vUaJeIMacQZ1vc+J9TFyikW8SeJZ5/tTOyQtvUqGOfzra47nhjd1dZxDT5T5ODGvetTNmTMH119/PRITE1FZWYnc3FwUFRWhV69emDlzpq/rSNTsiKLocty8R5dOWw86NQDf9NST9yVN3jQq+XyhhxSlGohpdel23YUrZJWw46fHV7gqrDS+/vpr/Pjjj+jZs2e9+3r27In33nsPgwcPlqBmROQJd3sp263MrdEgNqU1VBqN851KOt9s8H+/etpZzJsedZ+Z+gPwbzKl7rxptn9dVNYxsVd3AQhHPVto0CFRD8VZTUDebrVCQGKkDhDhcrisY7LIfl5B38YngUgCqy4mw7xZwdnT6qkUgtNFP9xdDMRxERF348Fg6nDiVaIuMjISa9euxcqVK7F161aYzWb06NED/fv393X9iJqdKL0aOpUSpVVGp/dLPWI0mC5wcvPA1W3w464iDO+aKnVV5M0Xwb7jvHeuhs0GsgcePzw+4zjPEhN3gdPQqm6+XPGNiPzPkznr7JJ2zjhOX0F+5e6qr2IA5qizDqH09DvYcQGIuvPJ1TWofQzeG6SX7EeQq/nwHOe9U1+QpHoA5Nl5tW7yzdYT8uI2rVqJcK3SNpdevSSvw9yCjc1FWHfV35gwNUqrnHdQqRuJh+RiElbXXnstrr32WtvtrVu3YurUqVi6dGmTK0bUXEWFqdEiRo+yIueJOnc0+qPV7UUl6j+eqQbvRYWpsezxXKmrIX/+WKgCuLTSrLN/HRN6fknc8dPjLw2tUEi+M3z4cIwZMwYffvghsrOz7e7bvHkzHnroIdxwww0S1Y6IvOWsp1CjXDWqWbeXHvNhDRsjjx/cvlxMwlervjqbo84brno2qZQC4iO1iNSr6yXYfEXu0ZMtmVRnKGxMmOeJy2BmbYsO1176bVkvESsCsG5zWOW4qeo+lzpCC41KYTv+BrUS1U4eI/e2RY8/ucuXL8eTTz6JKVOm4NChQwCAvXv34qabbsKVV16J2lo/ToRP1Ey0iNEj1qD1+vGNzuNkNyS2aXMSEIUEx3nwGuqBZ0gClE1q5yKZYqfHhs2bNw+pqam46qqrEBsbiw4dOqBjx46IjY1Fz549kZKSgjfffFPqahKRh5zNFdYo6/ems0RdZIobjcFUl78WkzBFp3taFaesc4Tp6/Rcqjv/nFruWY9AqBNExBq0Ppn7zW0BOPyNvY72SREXk3DSUisExIVdOleTo3XIiDfUK+dur1SpeHQF/fjjj3HvvfciNjYWZ8+exQcffIC5c+di7NixGDFiBH7//XdkZmb6q65EzUaYRoW2CeFQN/GC7u5wMGt3Y0+X8iYKWQ31xItOA9R6mc1/R+R/0dHR+P7777F3716sX78eRUVFAIDk5GTk5OSgQ4cOEteQiGQjqlXjZcjG05yB253XNOE4NOQz1Ea1AhYctTyXZ09lx9VwVX8K9kY0x+GZVgpFcHSUsCbo9Bplg78XvZn+wtMkpifl7Xo6KgSISgFhmkvprwCcuk3iUaLutddew6xZszBp0iR8+eWXGDlyJF577TVs27YNbdu29VcdiZql5CjLPCD1h3K5f1Vxd7JgIvKA4zw8CrWb894FeaQpQ5ybThodOnRgUo6IGmaIs/zLOevc4vgtJoo+GvoKwKSNglkT4XmlwFE3nmk4zrMlji5SCrAl8OINl0Y5eaMp8625eqxjgg4N9BD0NsJVKzxbwKKxOesae2y41v9zNvqKR91n/vzzT9x+++0AgFtuuQVKpRJz585lko5I5lwOhbXOVafSWxILTocp8IuZyCnrPDzW4bKO/zom7jyfbYIa4Xhta2rijqnUpjl37hw++eQTqatBRHJi/a7kUNgGedoZyV95M8ckjHXIq7/mn6NLK8wmRujqDS22vg++HqWpUgq2BR4ULsJTa1LM8b13tl2tFJjM9TGPfjWUl5fDYLCM71UoFNDpdEhLS/NLxYjIOZ9eqK1z1V1MLKg0GvsWEoUCxrBEHz4hUQhxNT+P4/3WxJ0ieFrxglWj83OSXxUUFODee++VuhpEJCd1vyuNFYBolrpGsuSvOeqccdYoVbf3VN256OSQfBGDsRnNyx9s1iRYmFpplwzLiDMgIdz7+cutHN9ntSAgKUqHpAhdk5KxGqUiKJK5wXQmedy08eOPPyIqKgoAYDab8dNPP2Hnzp12ZbjiF1FwUqu1iEtqhUpYumWbEjrDVO5kVR6fzM0l/4s5ETUPl4Z9BFMIF3ilpaUN3l9WVhagmhCRrwmCn+cCi2oJ6KIsiTqtd8MwQ5ljXqext8Kb+cCccTW8sSlDDH2tW2o4gOad4NWpFNCFqWF0MRTZ1elgfX/rLv4R6fC+KgUBkfqm9Xhl9OR7Hr8jo0ePtrv94IMP2t0WBAEmk+OcWkTkLcehXH79urS2elZWWYbEKtQAnKzkrOAk+kQeC/bZkIOY9Tp6trxG6qoEtejo6AZ/HIqi6LMfj0QUWApBgMmf31NhsZY/K85dZ8dy7bx0/EUfR/xKwXlPc+uCcnJIyLnyt5wUoPy41NVonN3nxz/H09MEqu399fPiHwxxfc+jRJ3Z3Lwz2URSsA7lqr+oRH3uzs/UaLmLQ2JVGg0SI5VQKfjZJ2o6RjGB4niNUysVSIzQobTSScMDuS0iIgLPPPMMevbs6fT+AwcO1GvAJaLgIN80jTz5epEFfx//5MhLwyaD6b3ulqSGVsXpLBrj+J5yERDngimhyFk9iUKINannTrlIvbrR5J/Lcko1YEgCKoubUl2i5iWYooMg50kDB7mvR48eAIDc3Fyn90dHR0PkeU4UlBSCk6lOyCXrEEKjj+Zy83c6ReUwdysTOaHF8V0M9NBlXjl8z+tE3b59+zBv3jzs2bMHgiCgQ4cOGDduHDp06ODL+hGRA1mMKlKqgYhkoLpE6poQEfkMc0wNGzVqFCorK13en5ycjGnTpgWwRkTkM4GOL62rwfpk3uPAUzvM5WbUKBGu9b4PjKdz1AHuJduclQnTKp3OVUa+FNjjKvXvw2CJn4KkmgC8TNT93//9H+644w5kZ2cjJycHALBhwwZ06dIF//nPf3Drrbf6tJJEdIkQVB3WiYjkwdWQ/2AK2qQ2ZsyYBu9PSkpioo4oSAU8X2OdFzlE5qpTKwQYnCTq6ibKlAAi9ep630MqpQCVh29A3YUBrL36rAsG6DQKxBssCVBnCTmDRhUUK3RS8JBlLKW42BigDvOuUUDiRgSvEnVPPfUUJk+ejBkzZthtnzZtGp5++mkm6oj8wPojs1NqJJZsD4IJVYnIgSzDmJBWNznH4bBERK4ppOqSE+Q96+qqewTrzpEaadCgUqmAUikgxqCB0iGxptco7RJ17gxHjXO2Qqt1wQC1EmGROkvYwYRc4NTtVhbww8732UahAvRxgCYM0EdZtmnCPG8UCMZEXVFREe6555562++66y688sorTa4UEdVn/ZE58so0nCqrwvVdUqSuEhF5IljGBYQQd+ftJM+8+eabTrcLggCdTod27drhmmuugVKpDHDNiMhbkibqQqRnXd1vebXS9QII9RJrCsEun6bXKH2+6itRs6FQWaZocpJosw/F5f0Z8ypR17dvX/zyyy9o166d3fa1a9fiL3/5i08qRkTOqZQK3NCtBdolhktdFXuK0GkRJaLQ1dCq10yluue1117D6dOnUVFRgZiYGIiiiPPnzyMsLAzh4eE4deoU2rRpg1WrViEtLU3q6hKRG6Se46q5q3v8OSz1kkhNsK742rzmqAt4AOX4u9Ob36EKeTcmenXm33DDDXj66acxbtw4fPrpp/j0008xbtw4TJo0CX/961/x9ddf2/6IKMRZL4yaMEuLqIKJOiLnmAaSA2svu4Z6O1DDZs2ahSuvvBIHDhxAcXExzp49i/3796Nnz5544403UFBQgOTkZDz++ONSV5WI3CRZjzqrEBoC6w2p8yxy8/aQGFzRwoBZ10ZJXRWSI2tPXOvvTsfbbpH3p86rHnVjx44FALzzzjt45513nN4HWIZAmEycC4bIlxrqDSIJpRrQezMMVyb1JwoUDn2lEPHss89i0aJFaNu2rW1bu3btMGfOHIwYMQKHDh3Cyy+/jBEjRkhYSyLyhNR5ulAYAtuUQyg4vAHNfejr0Mv0GJp9OVByVOqqeKDuHHUB7lEX0GerT5SqMTqEE/xeJerMZrOv60FEbmrKnEsBSfKF8AWTiEKH9XpYWFIpdVWCTmFhIWpra+ttr62tRVFREQAgNTUVZWVlga4aEXlJ8h51zRxHu1Iwk6wp2prgd1MwtZl7NO7j+uuvR0lJie32zJkzcf78edvt4uJidOrUyWeVIyLfcnfIV5MSel51PSZqDoIoOmgGrNdDlcJyPVQpBeg18p6vRC769euHBx98ENu2bbNt27ZtGx5++GFce+21AIAdO3YgIyNDqioSkYdkkyhSqgFDEqD0qj9J0JLL4acmsMsCNbM56uQihDqMeJSo+/HHH1FdXW27/Y9//ANnz5613a6trcW+fft8VzsikgTncCLyg3YDLP/qoiWtBtmzXufUSgUMTNS55cMPP0RsbCyysrKg1Wqh1WqRnZ2N2NhYfPjhhwCA8PBwvPrqqxLXlIjc5Tj0UjJKtWXFRoUniTqZ1L0J5HL4ibwhm55q1g4j7iTqZP6Z86ipQnR4BxxvExERkQtXPw7EtAYyrpG6JlRHRrwBVbWW+XQZ1rgnOTkZy5cvx969e7F//36IoogOHTqgffv2tjL9+vWTsIZE5CnZ9Kjzijwu3k1Jtjk+tLnPUUeekfpskccnsBFKNURtBICSRovKQfPqU0xEXnE6BDaEuhYTBYRKA3QbKXUtyIFGpYBGxd7DnlizZg1yc3PRoUMHdOjQQerqEJEPCJL/1K8jSGPMpjT2sEcdkZ8p1YAuCsAxqWviFo8iU0EQ6nWLlk03aSLymLtz0TkdAutJ12IiIgoZAwYMQKtWrTBp0iTs3LlT6uoQkQ/I6iddCMx3rFIKiDVo3J7vWU6Hn4JPs8nJKIIzie8Nj4e+5uXlQavVAgCqqqrw0EMPwWAwAIDd/HVEJH9NWUGWiIiapxMnTmDhwoX4/PPP8fLLLyMzMxN33XUXRo0ahZYtW0pdPSLyQnCv+iq/uqsVAuIMGtuYYpVSQIxBA6WLxJ3j8efQ12BUp0tlUH+ePOf3qUOsCTpNGKCP8no3dadue+HGTNz67jqUVtVfxV4OPOpRN3r0aCQmJiIqKgpRUVG46667kJqaarudmJiIe+65x191JSIiIvKboJhjRQbi4+Mxbtw4/Prrr/jzzz9x++2345NPPkF6erpt1VciCi7NLK8QcNbEndrFgebxp6aQ+vTxefxkTcypwy4l6Hw8kqt9cgS2Tx3os/35mkc96ubPn++vehARERFRkMnIyMCkSZPQrVs3PPfcc1izZo3UVSIiL8iyR53bc9XJo5nFl4tJUDCqex7yHfWKs55zmjCf7d7xSqGQ8So6nD2ZiCQi3wsjERE17tdff8XYsWORkpKCUaNGoXPnzli6dKnU1SIiL8jy92oIzFXnLscknzxSj0TuafLQ17oJOs6BDoCJOiLylyBdsYuIiBo2ZcoUZGRkoF+/fjhy5Ahef/11FBUV4dNPP0VKSorU1SMiLwT3ZPTBXHeL4H8FdTSjCf/tiNLNURe0H18lE3SuMFFHRP7RjFpBiSg0+H0y5BCxevVqTJw4ESdOnMC3336LoUOHYsGCBcjKykJWVpbU1SMiLwTtD/0Q4dij0a+LSWgjvU+IuJOE428AakxECqDSXTpXApSgczfOm31zF/9WxA0ezVFHRERERM3bunXrAAArV67ERx99hMWLF6N169YYMWIEPvjgA4lrR0TekOUcdW4L/lYWTw7/EaSgdVOeTB/lfRJNqQb0KUBNRVNqQCHG7U+gNdEbFgtEJPmzSl5Z9HBvXJEWDaUM5gJgoo6IAqO5doMnIgohx44dw4IFCzB//nxcuHABt912G4xGIxYtWoROnTpJXT0i8pIMfpc2a+4e/peNt2Ft2HX42q+1cYJxPDWFQgXo4+wXiZChrNYxUlfBhkNfici/HOcesC6zrWQ7ARFRMLn++uvRqVMn7Nq1C2+++SZOnDiBefPmSV0tIvKBoOhR5zJZFAR1b4TjHIGuhr6+bxqGYkVc057Mm3kefDFEkck+v5H1x1ehBiJbAtFpkr/3wdT3lr+Uici/rF/sjrfLiqSrExGRE2JQhXCBt2zZMjz22GN4+OGHcdlll0ldHSJqbkJ42KW7PRoFiPUX/giWBFgIv38WdWMIOWfOfM9p7rfuSq4y7kUnVyHXo+7bb79Fz549odfrER8fj5tvvtnu/oKCAgwfPhwGgwHx8fF47LHHUFNTY1dmx44dyM3NhV6vR4sWLTBjxgyInGGaiIiImrFffvkFZWVlyM7ORs+ePfHWW2/h9OnTUleLiHwgKHrUyVxTjqAnj1VaCyscRq0EcvEGZZAkB5sJQeLEoF1Dp+N5GSTnyDt39pC6CnZCKlG3aNEi3H333bj33nvx+++/49dff8WoUaNs95tMJgwdOhTl5eVYu3YtFi5ciEWLFuGJJ56wlSktLcWAAQOQmpqKTZs2Yd68eZgzZw7mzp0rxUsiIiKiAGGbXMNycnLw/vvvo7CwEA8++CAWLlyIFi1awGw2Y/ny5SgrK/Pr899www1o1aoVdDodUlJScPfdd+PEiRN2ZdggS+Qd5umk5Xj8XV2RBIiXkqruDEd11tuu7pNZ77dNTeNmUsX63OowwJDEKW0Ahw51zfADFQQJuoa+69snRwSwJo0LmU9UbW0txo8fj1deeQX333+/bXv79u1t/1+2bBl2796No0ePIjU1FQDw6quvIi8vDzNnzkRkZCQ+++wzVFVVYcGCBdBqtcjMzMT+/fsxd+5cTJgwoX5XYyIiIqJmJCwsDPfddx/uu+8+7Nu3Dx9++CFeeuklTJo0CQMGDMDXX/tnmvN+/fphypQpSElJwfHjxzFx4kTccssttlVorQ2yCQkJWLt2LYqLizF69GiIomibS8/aINuvXz9s2rQJ+/fvR15eHgwGg13DLVFzI+sedc2g95YnvWdcvlXKOkk3QxJQWXxpuKnJ6Lxs3WGJmjDPh6Uq1Za5x9T6kH5/qGGiQhO0Q1xXT+yL0xeq0TYhXOqq2AmZHnVbt27F8ePHoVAo0L17d6SkpGDIkCHYtWuXrcz69euRmZlpS9IBwKBBg1BdXY0tW7bYyuTm5kKr1dqVOXHiBPLz850+d3V1NUpLS+3+iKgRMo4HiYjIPe3bt8fLL7+MY8eO4fPPP/frcz3++OPo1asXWrdujd69e2PSpEnYsGEDjEbLD1Brg+ynn36K7t27o3///nj11Vfx/vvv22Kzug2ymZmZuPnmmzFlyhTMnTuXveqoWZP1qq+OPcdCMHHnbmcQExRQuiprPU6aMEvyLLKl/TFzVtYXx9C6r0AOvZWlZjZHXZ33W1Sqg/bzmB5vwJXpsVJXo56QSdQdOnQIADB9+nQ8++yzWLp0KWJiYpCbm4uzZ88CAIqKipCUlGT3uJiYGGg0GhQVFbksY71tLeNo9uzZiIqKsv2lpaX59LURERERyZlSqcRNN93kt950js6ePYvPPvsMvXv3hlpt+XHABlmiJpBzjzpHwZQYcnOhh/pDX+u/HxvMHVELlXtJVW8TcXV75YVYMjSUSfLx5bnhV7JP1E2fPh2CIDT4t3nzZpjNZgDAM888gxEjRiArKwvz58+HIAj473//a9ufs9YKUbRfPafe8tgXW1hdtXRMnjwZJSUltr+jR482+XUTERERkb2nn34aBoMBcXFxKCgowFdffWW7jw2yRN6TdY+6YOZmUrH+4a+/ZavZstq20NQ3q6Hew3V75QVLMlSOginx7a4G5jNkh3Tfk32ibty4cdizZ0+Df5mZmUhJSQEAdOrUyfZYrVaLNm3aoKCgAACQnJxcLwg7d+4cjEajLUhzVubUqVMAUC+wq/s8kZGRdn9ERERE1DB3G2StnnzySWzbtg3Lli2DUqnEPffcYzdklQ2yRN6R9Rx1oUKhAsKTnPZE8iT3plAo5dnbLQSHJAeLgHx6HZO4Qfg+B1NCUfaLScTHxyM+Pr7RcllZWdBqtdi3bx+uvvpqAIDRaER+fj5at24NwLJa2cyZM1FYWGhL7C1btgxarRZZWVm2MlOmTEFNTQ00Go2tTGpqKtLT0/3wComIiIiap3HjxmHkyJENlqkbf1njwssvvxwdO3ZEWloaNmzYgJycHCQnJ+O3336ze6yvGmTrDpUlCkXsUechb4aGKlRARLLTu9w5/B/WDrHsRiFYEiXe8iQp60nyzZrIcXxscxlGG0xZIE+4MXw7WF55QkTwfJfLPlHnrsjISDz00EOYNm0a0tLS0Lp1a7zyyisAgFtvvRUAMHDgQHTq1Al33303XnnlFZw9exYTJ07EmDFjbL3gRo0aheeffx55eXmYMmUKDhw4gFmzZmHq1Klc8ZWIiCiEcTGBwHO3QdYZ6/tVXV0NgA2yRE3B3zke0oRZ/kxGWzJK0EUBOO/V7urPUVevBIphWVHT5WIS/uCYfPP2sZow39WJ6vHrKWFdOTgEDO+Wiu1Hz8ty8QhHsh/66olXXnkFI0eOxN13340rr7wSR44cwcqVKxETEwPAMtHxt99+C51Ohz59+uC2227DTTfdhDlz5tj2ERUVheXLl+PYsWPIzs7G2LFjMWHCBEyYMEGql0VERETUrG3cuBFvvfUWtm/fjiNHjmDVqlUYNWoU2rZti5ycHAD2DbLbtm3DTz/95LRBVqvVIi8vDzt37sSSJUswa9YsTJgwgYkKatbYo85LdYcD6qMvbfewF1mjl58Ghu8TSS5IGjqVCgHTb+iMoV3ln3gMmR51AKBWqzFnzhy7xJujVq1aYenSpQ3up0uXLvj55599XT0iqiuhI6BQWloiiYhkIDjCzOZJr9dj8eLFmDZtGsrLy5GSkoLBgwdj4cKFtmGp1gbZsWPHok+fPtDr9Rg1apTTBtlHHnkE2dnZiImJYYMsEQAhMLNcNR/WHndu8uToM6kqV9JFET79/Lq5UnFdjJ98L6QSdUQURNQ6y79M1BERUSO6dOmClStXNlqODbJE3lGE1DgrmXMyd1u9RW4aSLwomakjf7IOda2pkLomzRoTdUQkLWuwUlMOmJm0IyIiIgo0rvoaQI5zt9VU2PeSUzTckynoh746LlDhRQ8uWZJw+KdPTokmvA9BMvI1qLDthIikZQ1WFGw3ICIiIpJCUCZ/rAmfYKx7XUo1BJXu0m1nQ2avftz236DvUGeL/dXOb5M0rO+DN4k6Dn71OSbqiMgtwR4DERE1hi3CRNRcDe6cDABIiNBKXBMPNGVF0kBz7EXmcJ+ibnJOqa4/9LXfM5fuDvpM3UUNHROiZo5dWIjILQL8PFGoQg2YTf58BiIiIiJyYuSVaUiN1qFLiyipqxKaGksqNpZ7Uygv/TdUWs+DKdFKFGBM1BGRWwRB8G93k8gUoOyE//ZPRERERE4pFAL6tk+UuhrNlierdgblMOVmIYi65SvUQEQLS4LYVY9GD3o8ckSC7zFRR0Ru8XtIYEgEwuKBymJ/PxMRERERhQx5JK6akj9zHM1ql/d48Be7+5TyeLm+x6GwXvP43FOqgZhWlv+7Wt2VPR4lxUQdEcmDUgXEtAaMVVLXhIiaKU6GTEQUjIL/2t1goiW5i93NJg99lWv3J2tiyGT03aqwgVxRVk7HNcAr6crppYcKLiZBRG4JSC97QyJgiLMk7YiIiIiImoEGh746BOEhP/TVl6vCNpMVZeudEa5et58SeMzT+R5/DRORWwT/LydhSdCldLX831U3bCIiIiKiEKJw6D5Tb9XXOpRN7WoTLIk+fwyFDXBPM9lRqgF9Sv1tTTwmIrvU+RwTdUTkniD5TiciIiKi5iT4g1THXnINJepCZtXXxvhjjjRroirEOgS47GVpTcKpw1wn4zgXnSwxUUdEbmkmIQERNWNsECYiIik4xtlHxQSXZZtNoq4hzb1nnLvqJuE0YdLWhTzCRB0RuSXgMQFXfiIiIiKiRgV/K4tjnF0FLbpV/Qu1UGKXQ1mF4xKxzYVSDRiSgMrikO0Z561mekaENCbqiMgtDU5y6w/WFqC6X8BsPSMiPwr+n3pERBSMHHvJCQJQIoa7KBuIGsmQUg1EpwFqPX8LUMhjoo6I3CKLXvZsPSMiIiKiumQRpDatUdvxkQ0t4dbUoa+JEdomPV5SruZTk0VjvnTNfVJ/BDh1iO8xUUdEbpHs+l+3mzsRERERkR15JOqawnExAEEQXGY/vE3KvHd3Fn4/eh4DOyV5twM5Y2P+JRIkLEWOSfA5JuqIyC0uVxPyN6UaiEgGqkukeX4iIiIikq8Q6M7jGGY3FHV726NuUOdkDOqc7NVjZUtOc1pLeB4KguLSDa7gGhKYqCMitwR/WyURUcNC4LceEREFIcdhsw3l4pRSj3OUE1dDYZsdac8Jxk++p2i8CBERpL3+y6m1jIiIiIjkIwQSV/V71Ll+TQr+gnetufxmsM7Jpw6z/CvxZ4B5Ot9jjzoicoukl3+2lhERERFRiPJkJVfJpqMJBtbfDKE+V511Tj4A0IQBQoG09SGfYz6eiNzCoICIiIiIZCcExt3Vi7M59LVpQrVnnYvVbaU+JcQQ+AzKDXvUEZFbpP4CICLyPwaaREQUeJ4tJuHXqoQGx9E4vkzcuUiWeRxDCAr362R9Tk0YoI/y7Hn8SKkQYDKLyGodI3VVQg4TdUTkFsYERERERCQ7MmlNbko1PFlMgqNcvODLaXSsw06bPLxWcH+Ybt2hrjKy/PFr8N2OQozunS51VUIOE3VE5BYGBUREREREvufJYhJKdqmTJ38M/3TZe08e2iSEY9y1l0ldjZDERB0RuYUhARGFOk6xQkREUnDMvTXUPm7Q8id8kykdVk2VaSJMrj3pyP+4mAQRuUVWHepCdYJYIiIiImp26g19dVLm+Rs646qMWIz5S0ZgKhXKrENhNWGWfxW++E0hXWsfRz6FHqbjichNMvoCaC5LrxNRQLFHHRERScGd0ayje6dzLjB/kVsnAJkPeSX/Y486InJLUDXU8MuNiIiIiIKF4LiYRDAF3iHA2gnA2rNOoQYMSYBSon5N1vq4+VuGZ0voYaKOiNwiyy8AV61fjl+2REREREQy5dij7u6c1gCA3MsTJKgNQakGIpIBRYATdexsQBdx6CsRuaVTaiRO7TstdTXscQgsEREREQU5xznqJgy4HH9pF4/urWIkqhF5rCnzZyhUgD7OMmeePsrjh7MDZuhhjzoicssrt3TD3b1a47vH/iJ1VYiI/EKUcCJoIiJqvkZktQAA9GkXBwBQKxXo3S4eeo1Symo1P3VH6wRy3jqFytKDjz3p6CL2qCMityREaPHCTZlSV4OIiIiIKKS0jAnDrucHQa9mYk5S1tE6VpEpgMloSdipw/yTuPNBQpAd6kIPE3VEFPzktlITEREREZEHDFr+NJelusk7TZh/9090EYe+ElHw4+IRRERERM1UgPsTtcoJ7PMRNYKrBIceJuqIKHSwZx0RNUFT5oEmIiKpBPjifdM/nW7OTo8NbD0ouDG5Rg1g/1oiCh3sOk5ERERE/vL3nUB0mtO7WkTr8ctT/RAVxgbjZsHTDgKKi+WtBN/1mWLKL/QwUUdERESEgPfJICKiYOMiSWeVFuuHOcxInqwdBGoqLLdddcu3Jug0YYA+KnD1o6DGRB0REREREREFqQD1J7rvx8A8DwUXa886RZ0ecnVXiQ1Ago6jaEMPE3VEFLqUDl3MiYiIiCjEBKg/dKtegXkeCi62Re3qpFb8uUosNQtcTIKIQhfnrCMiIiKipvr7DqlrQHInKKV8cgmfm/yBiToiIiIicNVXIiJyIrEzEN1K6lqQ7DGIIN9hoo6IiIiIiIiClJ97E93zP//un5onH7YOco660MNEHREREREREZGjh9cB4YlS14JCycCZgC4aGDpH6pqQjDFRR0RERERBo7q6GldccQUEQcD27dvt7isoKMDw4cNhMBgQHx+Pxx57DDU1NXZlduzYgdzcXOj1erRo0QIzZsyAyHHPREHMD5/fmz8AJuwFkjr7ft/UvPUeBzx1GEjs6LNdskNd6OGqr0REREQARM4vExSeeuoppKam4vfff7fbbjKZMHToUCQkJGDt2rUoLi7G6NGjIYoi5s2bBwAoLS3FgAED0K9fP2zatAn79+9HXl4eDAYDnnjiCSleDhHJUddbpa4BhTIF+0tRw0LqDNm/fz9uvPFGxMfHIzIyEn369MGqVavsyrCllYiIiCg4ff/991i2bBnmzKk/ZGjZsmXYvXs3Pv30U3Tv3h39+/fHq6++ivfffx+lpaUAgM8++wxVVVVYsGABMjMzcfPNN2PKlCmYO3cuYz2ioMX+RCQDEn6HPHbdZQCAUT256EmoCKlE3dChQ1FbW4uVK1diy5YtuOKKKzBs2DAUFRUBuNTSWl5ejrVr12LhwoVYtGiRXQuqtaU1NTUVmzZtwrx58zBnzhzMnTtXqpdFREREATC4czIAICFCK3FNyJmTJ09izJgx+Pe//42wsLB6969fvx6ZmZlITU21bRs0aBCqq6uxZcsWW5nc3FxotVq7MidOnEB+fr7T562urkZpaandHxERkVxktojCnhmDMeuvXaSuCvlIyCTqzpw5g4MHD2LSpEno2rUrLrvsMrz00kuoqKjArl27ALCllYiIiFwb0CkJi8f2xorHc6WuCjkQRRF5eXl46KGHkJ2d7bRMUVERkpKS7LbFxMRAo9HYGm2dlbHetpZxNHv2bERFRdn+0tLSmvpyiMinfPwbTQiZn8gUUNLmCvQapaTPT74VMlehuLg4dOzYEZ988gnKy8tRW1uL9957D0lJScjKygLgv5ZWIiIiCn6CIKBHqxhEhamlrkqzMX36dAiC0ODf5s2bMW/ePJSWlmLy5MkN7k8Q6g+BE0XRbrtjGWtDrLPHAsDkyZNRUlJi+zt69KinL5OIgsmDv0hdAyJq5kJmMQlBELB8+XLceOONiIiIgEKhQFJSEn744QdER0cDcL+lNT093a5M3ZbWjIyMes9dXV2N6upq220OiSAiIiJq3Lhx4zBy5MgGy6Snp+PFF1/Ehg0b7BpSASA7Oxt33nknPv74YyQnJ+O3336zu//cuXMwGo22WC45Oblez7lTp04BQL0Y0Uqr1dZ7XiKSEx/PUacx+HZ/1Dxw9B35kOx71Lnb0iqKIsaOHYvExET88ssv2LhxI2688UYMGzYMhYWFtv35o6WVQyKIiIiIPBcfH48OHTo0+KfT6fDmm2/i999/x/bt27F9+3Z89913AIAvvvgCM2fOBADk5ORg586ddnHfsmXLoNVqbaMrcnJy8PPPP9stJLZs2TKkpqbWa6glomYqtn7HDCKiQJJ9jzp3W1pXrlyJpUuX4ty5c4iMjAQAvPPOO1i+fDk+/vhjTJo0yW8trZMnT8aECRNst0tLS5msIyIiIvKRVq3sV7ILDw8HALRt2xYtW7YEAAwcOBCdOnXC3XffjVdeeQVnz57FxIkTMWbMGFtsOGrUKDz//PPIy8vDlClTcODAAcyaNQtTp0512SBLRHLnw55MuZN8ty8iIi/JPlEXHx+P+Pj4RstVVFQAABQK+06CCoUCZrMZgKUVdebMmSgsLERKSgoA5y2tU6ZMQU1NDTQaja1MQy2tHBJBREREJC2lUolvv/0WY8eORZ8+faDX6zFq1CjMmTPHViYqKgrLly/HI488guzsbMTExGDChAl2Da5E1IwxYU9EMiD7RJ27cnJyEBMTg9GjR2Pq1KnQ6/V4//33cfjwYQwdOhQAW1qJiIiIQkF6erptapK6WrVqhaVLlzb42C5duuDnn3/2V9WIKOD4G42IQovs56hzV3x8PH744QdcuHAB1157LbKzs7F27Vp89dVX6NatG4BLLa06nQ59+vTBbbfdhptuuslpS+uxY8eQnZ2NsWPHsqWViIiIiIgo1GXeInUNKGhxMQnynZDpUQdYVv768ccfGyzDllYiIiIiIiKqJ76d1DUgIgqdHnVEREREREREXrl8iNQ1oGDmZDoGIm+FVI+6YGMymWA0GqWuBoUgtVoNpVIpdTWIiIiaLcZ55C+M8/zk5vekrgEREQAm6iQhiiKKiopw/vx5qatCISw6OhrJyclcBIWIiCiAGOdRIDDO8wNdlNQ1ICICwESdJKzBW2JiIsLCwvgFSz4liiIqKipw6tQpAEBKSorENSIiImo+GOeRPzHO85Or/iZ1DYiIbJioCzCTyWQL3uLi4qSuDoUovV4PADh16hQSExM5PIKIiCgAGOdRIDDO84PLB0tdAwp6nKOOfIeLSQSYda6SsLAwiWtCoc56jnF+HCIiosBgnEeBwjjPx9jzlYhkhIk6iXAYBPkbzzEiIiJp8DuY/I3nmI8ldZG6BhTsuOor+RATdURERERERNQ8GRKA8ASpa0FEZMNEHQWNvn374u9//7vP9zt9+nRcccUVPt8vEREREbmHcR55ram9C2961zf1ICLyESbqyCfy8vIgCAIeeuiheveNHTsWgiAgLy/PrX2tXr0agiDg/Pnzvq0kEREREXmMcR7JWlOHHF7W3zf1oGaOQ1/Jd5ioI59JS0vDwoULUVlZadtWVVWFzz//HK1atZKwZkRERETUFIzzKCTd/L7UNSAiqoeJOvKZHj16oFWrVli8eLFt2+LFi5GWlobu3bvbtomiiJdffhlt2rSBXq9Ht27d8H//938AgPz8fPTr1w8AEBMTU6+F1mw246mnnkJsbCySk5Mxffp0uzoUFBTgxhtvRHh4OCIjI3Hbbbfh5MmTdmVeeuklJCUlISIiAvfffz+qqqp8fCSIiIiIQgvjPAo5f30P6Hqb1LUgIqqHiTryqXvvvRfz58+33f7oo49w33332ZV59tlnMX/+fPzzn//Erl278Pjjj+Ouu+7CmjVrkJaWhkWLFgEA9u3bh8LCQrzxxhu2x3788ccwGAz47bff8PLLL2PGjBlYvnw5AEtgeNNNN+Hs2bNYs2YNli9fjj///BO333677fFffvklpk2bhpkzZ2Lz5s1ISUnBO++8489DQkRERBQSGOeRLHk7R51K59t6EBH5iErqClBoufvuuzF58mTk5+dDEAT8+uuvWLhwIVavXg0AKC8vx9y5c7Fy5Urk5OQAANq0aYO1a9fivffeQ25uLmJjYwEAiYmJiI6Ottt/165dMW3aNADAZZddhrfeegs//fQTBgwYgBUrVuCPP/7A4cOHkZaWBgD497//jc6dO2PTpk248sor8frrr+O+++7DAw88AAB48cUXsWLFCra2EhERETWCcR7Jkjdz1F0+GOgwzPd1oearqXMlEtXBRB35VHx8PIYOHYqPP/4Yoihi6NChiI+Pt92/e/duVFVVYcCAAXaPq6mpsRs24UrXrl3tbqekpODUqVMAgD179iAtLc0WvAFAp06dEB0djT179uDKK6/Enj176k2EnJOTg1WrVnn8WomIiIiaE8Z5FDJGfSF1DYiIXGKijnzuvvvuw7hx4wAAb7/9tt19ZrMZAPDtt9+iRYsWdvdptdpG961Wq+1uC4Jg26coihCcdH13tZ2IiIiIPMM4j4jIGfaoI9/hHHXkc4MHD0ZNTQ1qamowaNAgu/s6deoErVaLgoICtGvXzu7P2kKq0WgAACaTyaPn7dSpEwoKCnD06FHbtt27d6OkpAQdO3YEAHTs2BEbNmywe5zjbSIiIiJyjnEeyY6nidr7fvRPPYiIfIQ96sjnlEol9uzZY/t/XREREZg4cSIef/xxmM1mXH311SgtLcW6desQHh6O0aNHo3Xr1hAEAUuXLsX1118PvV6P8PDwRp+3f//+6Nq1K+688068/vrrqK2txdixY5Gbm4vs7GwAwPjx4zF69GhkZ2fj6quvxmeffYZdu3ahTZs2vj8QRERERCGGcR4Fte53Aa16SV0LCkWco458iD3qyC8iIyMRGRnp9L4XXngBU6dOxezZs9GxY0cMGjQI33zzDTIyMgAALVq0wPPPP49JkyYhKSnJNryiMYIg4H//+x9iYmJwzTXXoH///mjTpg2++OLSHBS33347pk6diqeffhpZWVk4cuQIHn744aa/YCIiIqJmgnEeyYonCZKrHvRfPYiIfEQQRaZ+fa20tBRRUVEoKSmpF8RUVVXh8OHDyMjIgE7HJcHJf3iu1TE9qs7/S6SrBxFRIxqKIUgeGOeRHPBcq2NOe+BCUePlhrwM9GSijvzkx2eA9W9Z/s/fG+SCu3Eeh74SERERERFRcHJnjrohrwBXPuD/uhAR+QATdURERERERBS6ev5N6hoQEbmNc9QRERERERFRcGpsJqcHfw5MPYiIfISJOiIiIiIiIgo9sW2BlG5S14KIyCNM1BEREREREVFwamiOujE/Ba4e1LxxjU7yISbqiIiIiIiIKLQ8uhXQx0hdCyIijzFRR0RERERERMFJG1l/28Prgbi2ga8LNWPsUUe+w0QdERERERERBadbF1j+1UVbetFNPQskdZKyRkRETaKSugJEREREREREXknqBEwvkboWREQ+wx51REREREREREREMsBEHXmsqKgIjz76KNq0aQOtVou0tDQMHz4cP/10aVWldevW4frrr0dMTAx0Oh26dOmCV199FSaTyW5fgiBAEARs2LDBbnt1dTXi4uIgCAJWr15dr7wgCIiIiEB2djYWL15su3/69Ol2Zax/HTp0sJXp27evbbtGo0Hbtm0xefJkVFdXN/i68/LybI9Tq9VISkrCgAED8NFHH8FsNtuVTU9Pt5XV6/VIT0/HbbfdhpUrV9qVy8/Pt6tnTEwMrrnmGqxZs6beMR8/fjzatWsHnU6HpKQkXH311Xj33XdRUVHRYL2JiIiI3MU4j3EeERFJi4k68kh+fj6ysrKwcuVKvPzyy9ixYwd++OEH9OvXD4888ggAYMmSJcjNzUXLli2xatUq7N27F+PHj8fMmTMxcuRIiA5LV6elpWH+/Pl225YsWYLw8HCndZg/fz4KCwuxadMmdOvWDbfeeivWr19vu79z584oLCy0+1u7dq3dPsaMGYPCwkIcPHgQL7/8Mt5++21Mnz690dc/ePBgFBYWIj8/H99//z369euH8ePHY9iwYaitrbUrO2PGDBQWFmLfvn345JNPEB0djf79+2PmzJn19rtixQoUFhZizZo1iIyMxPXXX4/Dhw8DAA4dOoTu3btj2bJlmDVrFrZt24YVK1bg8ccfxzfffIMVK1Y0Wm8iIiKixjDOY5xHRF4SuZgE+ZBIPldSUiICEEtKSurdV1lZKe7evVusrKy0bTObzWJ5tVGSP7PZ7NFrGzJkiNiiRQvxwoUL9e47d+6ceOHCBTEuLk68+eab693/9ddfiwDEhQsX2rYBEJ999lkxMjJSrKiosG0fMGCA+Nxzz4kAxFWrVtmVX7Jkie12TU2NGBYWJk6aNEkURVGcNm2a2K1btwZfQ25urjh+/Hi7bTfffLPYo0ePBh83evRo8cYbb6y3/aeffhIBiO+//75tW+vWrcXXXnutXtmpU6eKCoVC3Lt3ryiKonj48GERgLht2zZbmWPHjokAxHfffVcURVEcNGiQ2LJlS6fHXBRFl++hs3Ot2ZoWeemPiEjGGoohSB4Y5zHOY5xHRPV89zR/b1Cj3I3zuJiEDFQaTeg09UdJnnv3jEEI07h3Gpw9exY//PADZs6cCYPBUO/+6OhoLFmyBMXFxZg4cWK9+4cPH47LL78cn3/+OW6//Xbb9qysLGRkZGDRokW46667cPToUfz88894++238cILLzRYJ7VaDZVKBaPR6NZrcOb333/Hr7/+ivT0dK8ef+2116Jbt25YvHgxHnjggQbLjh8/Hi+88AK++uorPPXUU07LhIWFAQCMRiOKi4ttLazOjjlgGSZCRERE8sQ4j3FeXYzziEIVe9SR73DoK7nt4MGDEEXRbh4QR/v37wcAdOzY0en9HTp0sJWp695778VHH30EwDLk4frrr0dCQkKD9amursaLL76I0tJSXHfddbbtO3bsQHh4uN2fY2D1zjvvIDw8HFqtFldccQVOnz6NJ598ssHna0iHDh2Qn5/faLnY2FgkJia6LFteXo7JkydDqVQiNzfXdszbt29vVy4+Pt722p5++mmv601EREQEMM5rCOM8IiIKJPaokwG9WondMwZJ9tzuEi+Ou3enZU90MUZfFEWnj7/rrrswadIkHDp0CAsWLMCbb77pct933HEHlEolKisrERUVhTlz5mDIkCG2+9u3b4+vv/7a7jERERF2t++8804888wzKC0txT/+8Q9ERkZixIgRAIBffvnFbn/vvfce7rzzzkZfr7stns7K9u7dGwqFAhUVFUhJScGCBQvQpUsX/PbbbwDqH/ONGzfCbDbjzjvvbHRyZCIiIpIO4zzGeYzziIjIE0zUyYAgCG4PS5DSZZddBkEQsGfPHtx0001Oy1x++eUAgD179qB379717t+7dy86depUb3tcXByGDRuG+++/H1VVVRgyZAjKysqcPsdrr72G/v37IzIyEomJifXu12g0aNeuXYOvJSoqylbm008/RefOnfHhhx/i/vvvR3Z2NrZv324rm5SU1OC+AMvrzcjIaLRccXExTp8+Xa/sF198gU6dOiE6OhpxcXG27e3atYMgCNi7d69d+TZt2gAA9Hp9o89JRERE0mGcxziPcR4REXmCQ1/JbbGxsRg0aBDefvttlJeX17v//PnzGDhwIGJjY/Hqq6/Wu//rr7/GgQMHcMcddzjd/3333YfVq1fjnnvugVLpugU4OTkZ7dq1cxq8eUOtVmPKlCl49tlnUVFRAb1ej3bt2tn+HFtpHa1cuRI7duywtdQ25I033oBCoagXAKelpaFt27Z2wRtgCWwHDBiAt956y+kxJyIiIvIFxnnOMc4jIrdw1VfyISbqyCPvvPMOTCYTrrrqKixatAgHDhzAnj178OabbyInJwcGgwHvvfcevvrqK/ztb3/DH3/8gfz8fHz44YfIy8vDLbfcgttuu83pvgcPHozTp09jxowZTapjbW0tioqK7P5OnjzZ4GNGjRoFQRDwzjvvNFiuuroaRUVFOH78OLZu3YpZs2bhxhtvxLBhw3DPPffYlS0rK0NRUZFt0uS//e1vePHFFzFz5sxGW4Lreuedd1BbW4vs7Gx88cUX2LNnD/bt24dPP/0Ue/fubTDYJSIiInIX4zzGeUREJD3598MnWcnIyMDWrVsxc+ZMPPHEEygsLERCQgKysrLwz3/+EwBwyy23YNWqVZg1axauueYaVFZWol27dnjmmWfw97//3eUcH4IgID4+vsl13LVrF1JSUuy2abVaVFVVuXyMRqPBuHHj8PLLL+Ohhx5CeHi403I//PADUlJSoFKpEBMTg27duuHNN9/E6NGjoVDY572nTp2KqVOnQqPRIDk5Gb169cJPP/2Efv36efR62rZti23btmHWrFmYPHkyjh07Bq1Wi06dOmHixIkYO3asR/sjIiIicoZxHuM8IvIWe9SR7wiiq9lgyWulpaWIiopCSUkJIiMj7e6rqqrC4cOHkZGRAZ1OJ1ENqTnguVbH9Kg6/y+Rrh5ERI1oKIZo7tLT03HkyBG7bU8//TReeukl2+2CggI88sgjWLlyJfR6PUaNGoU5c+ZAo9HYyuzYsQPjxo3Dxo0bERsbiwcffBDPPfec24sFMM4jOeC5RiQz3z0JbPyX5f/8vUEuuBvnsUcdEREREQWFGTNmYMyYMbbbdXtGmUwmDB06FAkJCVi7di2Ki4sxevRoiKKIefPmAbAEyAMGDEC/fv2wadMm7N+/H3l5eTAYDHjiiScC/nqIiIiIHDFRR0RERERBISIiAsnJyU7vW7ZsGXbv3o2jR48iNTUVAPDqq68iLy8PM2fORGRkJD777DNUVVVhwYIF0Gq1yMzMxP79+zF37lxMmDDB7V51REREdjhQkXyIi0kQERERUVD4xz/+gbi4OFxxxRWYOXMmampqbPetX78emZmZtiQdAAwaNAjV1dXYsmWLrUxubi60Wq1dmRMnTiA/Pz9gr4OIiIjIFfaoIyIiIiLZGz9+PHr06IGYmBhs3LgRkydPxuHDh/HBBx8AAIqKipCUlGT3mJiYGGg0GhQVFdnKpKen25WxPqaoqAgZGRn1nre6uhrV1dW226Wlpb58WURERER2gqZH3cyZM9G7d2+EhYUhOjraaZmCggIMHz4cBoMB8fHxeOyxx+xaWgHLBMK5ubnQ6/Vo0aIFZsyYAcf1NNasWYOsrCzodDq0adMG7777rr9eFhEREVGzNX36dAiC0ODf5s2bAQCPP/44cnNz0bVrVzzwwAN499138eGHH6K4uNi2P2dDV0VRtNvuWMYaB7oa9jp79mxERUXZ/tLS0pr8uomIiIhcCZoedTU1Nbj11luRk5ODDz/8sN79vppA+PDhw7j++usxZswYfPrpp/j1118xduxYJCQkYMSIEQF9zUREREShbNy4cRg5cmSDZRx7wFn16tULAHDw4EHExcUhOTkZv/32m12Zc+fOwWg02nrNJScn23rXWZ06dQoA6vXGs5o8eTImTJhgu11aWspkHREROeAcdeQ7QZOoe/755wEACxYscHq/ryYQfvfdd9GqVSu8/vrrAICOHTti8+bNmDNnDhN1RERERD4UHx+P+Ph4rx67bds2AEBKSgoAICcnBzNnzkRhYaFt27Jly6DVapGVlWUrM2XKFNTU1ECj0djKpKamukwIarVauzntiIiIiPwpaIa+NsZXEwivX78eAwcOtNv3oEGDsHnzZhiNRv+/ECIiIiKys379erz22mvYvn07Dh8+jC+//BIPPvggbrjhBrRq1QoAMHDgQHTq1Al33303tm3bhp9++gkTJ07EmDFjEBkZCQAYNWoUtFot8vLysHPnTixZsgSzZs3iiq9ERNQ0XPWVfChkEnXuTiDsWKbuBMINlamtrcWZM2ecPnd1dTVKS0vt/oiIiIjIN7RaLb744gv07dsXnTp1wtSpUzFmzBh8/vnntjJKpRLffvstdDod+vTpg9tuuw033XQT5syZYysTFRWF5cuX49ixY8jOzsbYsWMxYcIEu6GtRERERFKSdOjr9OnTbUNaXdm0aROys7Pd2p+vJhD2ZpLhxl4HEREREXmnR48e2LBhQ6PlWrVqhaVLlzZYpkuXLvj55599VTUiIiIin5K0R924ceOwZ8+eBv8yMzPd2pezyYG9mUDYVRmVSoW4uDinzz158mSUlJTY/o4ePepWnYNNXl6ebQU2tVqNpKQkDBgwAB999BHMZrOtXHp6uq2cXq9Heno6brvtNqxcudJuf/n5+XarusXExOCaa67BmjVr7MoVFRVh/PjxaNeuHXQ6HZKSknD11Vfj3XffRUVFRUBeOxEREVEoY5xHREQkD5Im6uLj49GhQ4cG/3Q6nVv7ysnJwc6dO1FYWGjb5mwC4Z9//hk1NTV2ZepOIJyTk4Ply5fb7XvZsmXIzs6GWq12+txarRaRkZF2f6Fq8ODBKCwsRH5+Pr7//nv069cP48ePx7Bhw1BbW2srN2PGDBQWFmLfvn345JNPEB0djf79+2PmzJn19rlixQoUFhZizZo1iIyMxPXXX4/Dhw8DAA4dOoTu3btj2bJlmDVrFrZt24YVK1bg8ccfxzfffIMVK1YE7LUTERERhTLGeURERNILmlVfCwoKcPbsWRQUFMBkMmH79u0AgHbt2iE8PNxuAuFXXnkFZ8+edTqB8PPPP4+8vDxMmTIFBw4cwKxZszB16lTbsNaHHnoIb731FiZMmIAxY8Zg/fr1+PDDD+3mQPE5UQSMErUYqsMADyZP1mq1SE5OBgC0aNECPXr0QK9evXDddddhwYIFeOCBBwAAERERtnKtWrXCNddcg5SUFEydOhW33HIL2rdvb9tnXFwckpOTkZycjPfeew8tW7bEsmXL8OCDD2Ls2LFQqVTYvHkzDAaD7TFdunTBiBEjbMOSiYiIiGSJcR7jPCJqBni9It8JmkTd1KlT8fHHH9tud+/eHQCwatUq9O3b1zaB8NixY9GnTx/o9XqMGjXK6QTCjzzyCLKzsxETE1NvAuGMjAx89913ePzxx/H2228jNTUVb775JkaMGOG/F2esAGalNl7OH6acADSGxss14Nprr0W3bt2wePFiWwDnzPjx4/HCCy/gq6++wlNPPeW0TFhYGADAaDSiuLjY1sJaN3iriyu0ERERkawxzrNhnEdERNS4oEnULViwAAsWLGiwjK8mEM7NzcXWrVs9rWKz1qFDB/zxxx8NlomNjUViYiLy8/Od3l9eXo7JkydDqVQiNzcXBw8ehCiKdq2ygGXIdFVVFQDgkUcewT/+8Q+fvAYiIiIiqo9xHhFRI9gDmHwoaBJ1IU0dZmnxlOq5fcBxdV1PyvXu3RsKhQIVFRVISUnBggUL0KVLF/z2228A6rembty4EWazGXfeeSeqq6t9Un8iIiIiv2CcxziPiIjIA0zUyYEgNHlYgtT27NmDjIyMBssUFxfj9OnT9cp98cUX6NSpE6Kjo+1W1m3Xrh0EQcDevXvtyrdp0wYAoNfrfVR7IiIiIj9hnMc4j4iaAfaoI9+RdNVXCg0rV67Ejh07Gp3H74033oBCocBNN91ktz0tLQ1t27a1C94Ay+TDAwYMwFtvvYXy8nJfV5uIiIiIGsE4j4iIKLDYo448Ul1djaKiIphMJpw8eRI//PADZs+ejWHDhuGee+6xlSsrK0NRURGMRiMOHz6MTz/9FB988AFmz56Ndu3auf1877zzDvr06YPs7GxMnz4dXbt2hUKhwKZNm7B3715kZWX542VSqFHpgNoqQFBKXRMiIiLZYpxHROQlXZTUNaAQwkQdeeSHH35ASkoKVCoVYmJi0K1bN7z55psYPXo0FIpLHTSnTp2KqVOnQqPRIDk5Gb169cJPP/2Efv36efR8bdu2xbZt2zBr1ixMnjwZx44dg1arRadOnTBx4kSMHTvW1y+RQtG93wPLngUGvCB1TYiIiGSLcR4RkZeungAU/g50uVXqmlAIEESRy5P4WmlpKaKiolBSUoLIyEi7+6qqqnD48GFkZGRAp9NJVENqDniuEREFn4ZiCJIHxnkkBzzXiIiCj7txHueoIyIiIiIiIiIikgEm6oiIiIiIiIiIiGSAiToiIiIiIiIiIiIZYKKOiIiIiIiIiIhIBpiokwjX8CB/4zlGREQkDX4Hk7/xHCMiCl1M1AWYWq0GAFRUVEhcEwp11nPMes4RERGRfzHOo0BhnEdEFLpUUleguVEqlYiOjsapU6cAAGFhYRAEQeJaUSgRRREVFRU4deoUoqOjoVQqpa4SERFRs8A4j/yNcR4RUehjok4CycnJAGAL4oj8ITo62nauERERUWAwzqNAYJxHRBS6mKiTgCAISElJQWJiIoxGo9TVoRCkVqvZwkpERCQBxnnkb4zziIhCGxN1ElIqlfySJSIiIgpBjPOIiIjIG1xMgoiIiIiIiIiISAaYqCMiIiIiIiIiIpIBJuqIiIiIiIiIiIhkgHPU+YEoigCA0tJSiWtCREREwcQaO1hjCZIfxnlERETkDXfjPCbq/KCsrAwAkJaWJnFNiIiIKBiVlZUhKipK6mqQE4zziIiIqCkai/MEkU22Pmc2m3HixAlERERAEASf7be0tBRpaWk4evQoIiMjfbZfch/fA2nx+EuP74G0ePyl5+/3QBRFlJWVITU1FQoFZyiRI3/FeQA/41Lj8Zce3wNp8fhLi8dfenKJ89ijzg8UCgVatmzpt/1HRkbygysxvgfS4vGXHt8DafH4S8+f7wF70smbv+M8gJ9xqfH4S4/vgbR4/KXF4y89qeM8NtUSERERERERERHJABN1REREREREREREMsBEXRDRarWYNm0atFqt1FVptvgeSIvHX3p8D6TF4y89vgfkTzy/pMXjLz2+B9Li8ZcWj7/05PIecDEJIiIiIiIiIiIiGWCPOiIiIiIiIiIiIhlgoo6IiIiIiIiIiEgGmKgjIiIiIiIiIiKSASbqiIiIiIiIiIiIZICJuiDyzjvvICMjAzqdDllZWfjll1+krpLs/fzzzxg+fDhSU1MhCAL+97//2d0viiKmT5+O1NRU6PV69O3bF7t27bIrU11djUcffRTx8fEwGAy44YYbcOzYMbsy586dw913342oqChERUXh7rvvxvnz5+3KFBQUYPjw4TAYDIiPj8djjz2Gmpoaf7xs2Zg9ezauvPJKREREIDExETfddBP27dtnV4bvgX/985//RNeuXREZGYnIyEjk5OTg+++/t93P4x9Ys2fPhiAI+Pvf/27bxvfAv6ZPnw5BEOz+kpOTbffz+JNcMM7zHOM8aTHOkx7jPHlhnBd4IRvniRQUFi5cKKrVavH9998Xd+/eLY4fP140GAzikSNHpK6arH333XfiM888Iy5atEgEIC5ZssTu/pdeekmMiIgQFy1aJO7YsUO8/fbbxZSUFLG0tNRW5qGHHhJbtGghLl++XNy6davYr18/sVu3bmJtba2tzODBg8XMzExx3bp14rp168TMzExx2LBhtvtra2vFzMxMsV+/fuLWrVvF5cuXi6mpqeK4ceP8fgykNGjQIHH+/Pnizp07xe3bt4tDhw4VW7VqJV64cMFWhu+Bf3399dfit99+K+7bt0/ct2+fOGXKFFGtVos7d+4URZHHP5A2btwopqeni127dhXHjx9v2873wL+mTZsmdu7cWSwsLLT9nTp1ynY/jz/JAeM87zDOkxbjPOkxzpMPxnnSCNU4j4m6IHHVVVeJDz30kN22Dh06iJMmTZKoRsHHMYAzm81icnKy+NJLL9m2VVVViVFRUeK7774riqIonj9/XlSr1eLChQttZY4fPy4qFArxhx9+EEVRFHfv3i0CEDds2GArs379ehGAuHfvXlEULYGkQqEQjx8/bivz+eefi1qtViwpKfHL65WjU6dOiQDENWvWiKLI90AqMTEx4gcffMDjH0BlZWXiZZddJi5fvlzMzc21BXB8D/xv2rRpYrdu3Zzex+NPcsE4r+kY50mPcZ48MM4LPMZ50gnVOI9DX4NATU0NtmzZgoEDB9ptHzhwINatWydRrYLf4cOHUVRUZHdctVotcnNzbcd1y5YtMBqNdmVSU1ORmZlpK7N+/XpERUWhZ8+etjK9evVCVFSUXZnMzEykpqbaygwaNAjV1dXYsmWLX1+nnJSUlAAAYmNjAfA9CDSTyYSFCxeivLwcOTk5PP4B9Mgjj2Do0KHo37+/3Xa+B4Fx4MABpKamIiMjAyNHjsShQ4cA8PiTPDDO8w9+vgOPcZ60GOdJh3GetEIxzlN5/AgKuDNnzsBkMiEpKclue1JSEoqKiiSqVfCzHjtnx/XIkSO2MhqNBjExMfXKWB9fVFSExMTEevtPTEy0K+P4PDExMdBoNM3mPRRFERMmTMDVV1+NzMxMAHwPAmXHjh3IyclBVVUVwsPDsWTJEnTq1Mn2xcLj718LFy7E1q1bsWnTpnr38TPgfz179sQnn3yCyy+/HCdPnsSLL76I3r17Y9euXTz+JAuM8/yDn+/AYpwnHcZ50mKcJ61QjfOYqAsigiDY3RZFsd428pw3x9WxjLPy3pQJZePGjcMff/yBtWvX1ruP74F/tW/fHtu3b8f58+exaNEijB49GmvWrLHdz+PvP0ePHsX48eOxbNky6HQ6l+X4HvjPkCFDbP/v0qULcnJy0LZtW3z88cfo1asXAB5/kgfGef7Bz3dgMM6TDuM86TDOk16oxnkc+hoE4uPjoVQq62ViT506VS9rS+6zrgbT0HFNTk5GTU0Nzp0712CZkydP1tv/6dOn7co4Ps+5c+dgNBqbxXv46KOP4uuvv8aqVavQsmVL23a+B4Gh0WjQrl07ZGdnY/bs2ejWrRveeOMNHv8A2LJlC06dOoWsrCyoVCqoVCqsWbMGb775JlQqle218z0IHIPBgC5duuDAgQP8DJAsMM7zD36+A4dxnrQY50mHcZ78hEqcx0RdENBoNMjKysLy5cvtti9fvhy9e/eWqFbBLyMjA8nJyXbHtaamBmvWrLEd16ysLKjVarsyhYWF2Llzp61MTk4OSkpKsHHjRluZ3377DSUlJXZldu7cicLCQluZZcuWQavVIisry6+vU0qiKGLcuHFYvHgxVq5ciYyMDLv7+R5IQxRFVFdX8/gHwHXXXYcdO3Zg+/bttr/s7Gzceeed2L59O9q0acP3IMCqq6uxZ88epKSk8DNAssA4zz/4+fY/xnnyxDgvcBjnyU/IxHkeLz9Bkli4cKGoVqvFDz/8UNy9e7f497//XTQYDGJ+fr7UVZO1srIycdu2beK2bdtEAOLcuXPFbdu2iUeOHBFF0bJcc1RUlLh48WJxx44d4h133OF0ueaWLVuKK1asELdu3Spee+21Tpdr7tq1q7h+/Xpx/fr1YpcuXZwu13zdddeJW7duFVesWCG2bNky5JfLfvjhh8WoqChx9erVdktmV1RU2MrwPfCvyZMniz///LN4+PBh8Y8//hCnTJkiKhQKcdmyZaIo8vhLoe5qYKLI98DfnnjiCXH16tXioUOHxA0bNojDhg0TIyIibN+fPP4kB4zzvMM4T1qM86THOE9+GOcFVqjGeUzUBZG3335bbN26tajRaMQePXrYlj4n11atWiUCqPc3evRoURQtSzZPmzZNTE5OFrVarXjNNdeIO3bssNtHZWWlOG7cODE2NlbU6/XisGHDxIKCArsyxcXF4p133ilGRESIERER4p133imeO3fOrsyRI0fEoUOHinq9XoyNjRXHjRsnVlVV+fPlS87ZsQcgzp8/31aG74F/3XfffbbrRkJCgnjdddfZgjdR5PGXgmMAx/fAv26//XYxJSVFVKvVYmpqqnjzzTeLu3btst3P409ywTjPc4zzpMU4T3qM8+SHcV5ghWqcJ4iiKHreD4+IiIiIiIiIiIh8iXPUERERERERERERyQATdURERERERERERDLARB0REREREREREZEMMFFHREREREREREQkA0zUERERERERERERyQATdURERERERERERDLARB0REREREREREZEMMFFHRCQj6enpeP3116WuBhERERH5GOM8InIHE3VERE4IgtDgX15eXqOP/9///tfkejgGdL7aLxEREVFzxTiPiORMJXUF9mTHcwABAABJREFUiIjkqLCw0Pb/L774AlOnTsW+ffts2/R6vRTVcovRaIRarZa6GkRERESyxDiPiOSMPeqIiJxITk62/UVFRUEQBLtt//nPf9C2bVtoNBq0b98e//73v22PTU9PBwD89a9/hSAIttt//vknbrzxRiQlJSE8PBxXXnklVqxY4XadXO13+vTpuOKKK/DRRx+hTZs20Gq1EEXRF4eBiIiIKOQwziMiOWOijojIQ0uWLMH48ePxxBNPYOfOnXjwwQdx7733YtWqVQCATZs2AQDmz5+PwsJC2+0LFy7g+uuvx4oVK7Bt2zYMGjQIw4cPR0FBgVvP62q/AHDw4EF8+eWXWLRoEbZv3+7DV0tERETUfDDOIyKpcegrEZGH5syZg7y8PIwdOxYAMGHCBGzYsAFz5sxBv379kJCQAACIjo5GcnKy7XHdunVDt27dbLdffPFFLFmyBF9//TXGjRvX6PO62i8A1NTU4N///retDBERERF5jnEeEUmNPeqIiDy0Z88e9OnTx25bnz59sGfPngYfV15ejqeeegqdOnVCdHQ0wsPDsXfvXrdbWhvSunVrBm9ERERETcQ4j4ikxh51REReEATB7rYoivW2OXryySfx448/Ys6cOWjXrh30ej1uueUW1NTUNLk+BoOhyfsgIiIiIsZ5RCQt9qgjIvJQx44dsXbtWrtt69atQ8eOHW231Wo1TCaTXZlffvkFeXl5+Otf/4ouXbogOTkZ+fn5Hj23s/0SERERkW8wziMiqbFHHRGRh5588kncdttt6NGjB6677jp88803WLx4sd3KXunp6fjpp5/Qp08faLVaxMTEoF27dli8eDGGDx8OQRDw3HPPwWw2e/TczvZLRERERL7BOI+IpMYedUREHrrpppvwxhtv4JVXXkHnzp3x3nvvYf78+ejbt6+tzKuvvorly5cjLS0N3bt3BwC89tpriImJQe/evTF8+HAMGjQIPXr08Oi5ne2XiIiIiHyDcR4RSU0QRVGUuhJERERERERERETNHXvUERERERERERERyQATdURERERERERERDLARB0REREREREREZEMMFFHREREREREREQkA0zUERERERERERERyQATdURERERERERERDLARB0REREREREREZEMMFFHREREREREREQkA0zUERERERERERERyQATdURERERERERERDLARB0REREREREREZEMMFFHREREREREREQkA0zUERERERERERERyQATdURERERERERERDLARB0REREREREREZEMMFFHREREREREREQkA0zUERERERERERERyQATdURERERERERERDLARB0REREREREREZEMMFFHREREREREREQkA0zUERERERERERERyQATdURERERERERERDLARB0REREREREREZEMMFFHREREREREREQkA0zUERERERERERERyQATdURERERERERERDLARB0REREREREREZEMMFFHREREREREREQkAyqpKxCKzGYzTpw4gYiICAiCIHV1iIiIKEiIooiysjKkpqZCoWB7qhwxziMiIiJvuBvnMVHnBydOnEBaWprU1SAiIqIgdfToUbRs2VLqapATjPOIiIioKRqL85io84OIiAgAloMfGRkpcW2IiIgoWJSWliItLc0WS5D8MM4jIiIib7gb5zFR5wfWYRCRkZEM4IiIiMhjHFIpX4zziIiIqCkai/M4+QkREREREREREZEMMFFHREREREREREQkA0zUERERERERERERyQATdURERERERERERDLARB0REREREREREZEMMFFHREREREREREQkA0zUERERERERERERyQATdURERERERERERDLARB0REREREREREZEMMFFHREREREREREQkA0zUERERERERERERyYBK6goQERGRvYqaWhw9W4mWMXocOl2ONgkG7C0qRWllLTqkRCAlSi91FYmIyBPGKkCtC/xzmo3AuXwgoQOgVLssWmsyQ6Ws04fDbAYEwfJnNgOKi/eJomWbsRJQagBjBUpqtcg/W4H2yRHQqZVO932huhbRYRqnzy2KIkQRyC8uR5XRDBWMSIgMR0VNDcI1Khw+W4lIpRGHD+1DTIvLEa+ugT48GjVQoUW0HjVV5dDow/HnyRJo1GrsOlGKXm1iIdRWIyoyAiZjDZRqy3Obqi7g6MkzaB2lgCCKgEoHhCcCohkQFEBNOaDS1jtWlTUm6FQCLpRfgFqlQvHJY0hpdRkqK8pgVFje13CtCkqFAJNZRHWtGQat5ae2ySyi0mhCuFYFk1lEcXk1ACAxwn/ng9FkhsksorTKiDCNCmFqJRQX66ZUCLbjXlhShbhwDUora5EQoUWV0WR7D8uqjPjzdDk6p0ZCffHcqPt4u32ZzRAuniOiKAKiGYJCCVEUca7CiNgwNapNZigEwbYvo8ls+7/1HFAoBIiiCEEQGnx9JrMIBUQI5lpApbGdr5VGMzQqBc6cPApDRAzOVivRKi4MpgtnoAiLxcXaAhXFlve9tsby+Lqs57grde4/V16Dkkqj5XiLou09DdeqcOjMBaRE6XG+ogatYsNwtrwGceFa1JrMqDCaIIqWqgBArdny+JpaM6LDNAjXepCmMdUCosly3jrUsazKiKNnK6FRKdAuMdz9fTYg/0w54sI1iNCpUVFTi/V/FqNPu3jo1EqcKq3C6QvVaJsQjpJKI5IidTCbRQgCUGsWbe+3t6znnChaPmNVRpPL64qzxwKwnbOOii9Uw6BVOb2GSYGJOiIKCaIo4otNR5EWG4Y+7eLr3W82i/hi81GolQpsLTiHKqMJS7fm41n9IiQpy3BMkYrMlHCknFiORFMhysIzEF1RABMU0CgAhakKCIsDOt4AhCcAh9YANRcsAZ7Z8uUohsWhrPgE9LEtUHruDMIzsqEqOYIjpnjUVF5Ai0gliqsEnDGHoyTiMpxIvhbVtWZE6dXQqBTQKBW4UF0Lk1nEVRmxaJPgmy/UQKqoqcV/fivALwfOIFynwpTrO6JFtPdJpePnK7Hu4Blcc3kC1v15Bn3axeOX/WcwsHMSInSuf3D4xYltwK9vWH6YnD8KmGqA+MuAjsOBzfOB2irLNqUG6H43cL4AOHcYaJEFRLUEig8C5WeAlG6AoEDhmWLURLdDTdFuFF0wYWlNNkSFEmEnt+Kz44kwNvAVfWfPVthbVIYtR87h5u4tkBKtw4O5bREZ6GNCRESN2/oJ8PWjwIgPgS63BOY5TbXA612A8lOW270eAQbPqlfs840FmP3dHpRW1WJ0TmtMMPyAqLUvWO7MyMViYy8MPDYPyru+hL5NH2DBUKBgnd0+loqD8Ez1aPRpF4fPHuiFF5fuxgdrD+P+qzPw3LBOGPX+b9h+9DxWP9kXqU5igns+2ojDB3djrfbvtm1LTH1wlWIvTogGnBYTcIVyC9oAWGy6Gj2Ua7HFfBm0MKKFIh9KUcC3CffimtOf4xPTAPRXbEW04hgAYHPGw+h26F8ouHoWMoQiKNe+hnTHClw+GDi1GzAkAKf2WL6385YCsCSTbpy5EP8yPYeWwhlEXHxICwCLTH/BXxVr8YRxPH4wX4W+iu2YovoMTxv/hm3iZXjxpkzc1as17vjXBuwuLMVt2Wn46NfDAIDoMDU2P9PfPjnakJoKYP4QoHVvYPDsBotW15rQ/tkf6m2fcn0H/OvnQ+jfMQn7T5Zha8F5u/uvuTwBP+8/jWeHdsR9fTIw8LWfUVhShduyW+LlW7ph1nd78PnGAtyenYYP1lpex4O5bRDz51cYefZdROUthNCqF7577UH8pex7vH35R3jv9xp8oH4F3cJLMLR6Fi5PisCnwrM4UJuEYSfyMDWzGAP2PocpNffiV+VVeOAvGfjstwI8N6wj/tq9pa1uW46cxdSvdmFIZjKWL/8OX2mnXqp47tPAriU4XB2BfqefQDKKsUH3KI6J8bim+k28/5dyDNg0Bj+HDcQ1mr2W+AwArnoQ2Pwh8Nf3AIUK+O/oesfsN8O1OF4bjv6KbYh8bC2g1gPv5QIJ7XHm+n+hz0srUV1rrve47sIBzFZ/gKdqR2CM6jv8bLgSz50bipw2cVh/qLjB9y8mTI1tUwc2WMamvBh4pY3l/4YESxxaVQIA2NZjNv66rjUAYIjiN7wT+wWEC0W2h5oEFW7S/Asv5w1Ax5RIt55u5/ESDJu3Flemx+C/D/XGhC9+xw+7ijCiRwuMzknHDW//CsCSxxRF4JnrO2Lu8v1Iidbh2LlKfD2uDzoku/dcjj7fWIDnv9mFO3u2xpebj6KsqhbhWhXWTb620fjXZBZx3auroVYqsOzxa+olgk+VVeGqmT8h1qDB1ucGeFU/XxNEURSlrkSoKS0tRVRUFEpKShAZ6d2JSBS0di0B9n1v+SIzmywtrr0eBv5caQku0q+2lBNFYM0/IG75GFVD34Qpox+qjSbEhWvtdmcyixAAmEQRJrOIcxU1mPjf35HVKgZvrjzodTU7C/n4VjulCS+06f40p6AGarQRTuB901CkCMUYoVyLP80peEY7GQtvMAAXTlla/VK6AZ1ukLS+rry96iBe+XFfg2XCNEpU1Jjqbc9sEYmdx0sBAHEGDYrLawAAHYQC9FTsQTvhOG5U/goVzJhWOxrlog4dFAW4TrENMdHRuN84EZrwOJwurUJhSQUeUH6HmPAw3DvsGmD/cmzML0ZV9/sh7v4GyTHhqDp7DF9qR6Dfuf/iglFAqq4Gu9NHI2b7u8hOC0e7wqUwd7wJMFVDFJRQ7rME6ubLBkNxoH7Q6y8La/tiUu3fPHrMiB4tEK5V4+P1+QCA1CgdTpRUQakQ0CE5Am+P6oGECC2+/v0E/rv5KEb1bI0P1x7G2L5tMTgzGeaLnzEAthbPei2fZjOw/3tAGwFUnrf8mNkyH6guA6LSLOfp+SNAqxyI5/JR2fJqCAoVzlXUIC5cgz9PlSNCp8KUJTtw6HQ57s5pjZe+34v4cC2MJjPm33sl2sQboFMrUWMy41RpFcI0KqiUll4AsQYNLlTV2lpxFQoBCkGAQaNstPU9WDCGkD++R+Sx6VF1/l8SmOc8sh6YP9ihHvWfO33St7b/CzDjsO4up7sri+2CiLs+Ad7s7vT+9Kr/IDFCi1+e7meXJNo9YxA6Tf0RAPDGyCtw4xUt7B5XfKEaWS+uwKvqdzBCudatl+aNGqihgdH9B1w8Vj/sLELNF3m4QbneZdED5hYYUPMK8nWjAAAbze1xW800DOuagudv6IysF1c4fdzO5we533Nq04fAtxPs6ubKjmMlGP5W047llmf72+qd1ToGix7ubXeu1GV93caYyyCM2wjVCzEAgH/VDsW7tcOxVfcQAKBf9atoKZzGvzUvAbCcM9bHWm/b7felobb/Z0z+FtasxWbtQ4gXSp3WJb3qPxil/Amz1B/abn+rmYzOiiOuX2xkC6D0uOv7rW7+ANBFAv+5DQCw5d7DGPFP5+fFPu1oaAX7883x9TWk7mtv0NrXgRXTXN5tfc531a9hsHJTvfs/r+2HzV2fx6u3dXPr6R769xb8sKvIVse658QbI6/A+IXbG3z8k4Pa45F+7dx6Lkeuzr8f/v6XRpN/x89Xos9LKwEAu54fZOvtavXV9uO2urt97L3kbgzBHnVE5J5v/m75QV6HObkbFEW/N/7Ynf9n/ziVDoraKgCAAEC/8BYcE+PxRM3D2KbsjL+0i8evf57GPaqfUFFjwiExBd2Fg1hp7o4blOvQHzXQ51cjX7ca82sHoZVwCtHCBRSJMdCjBtcqt2O5KQsDlFt89OL9o62i0Pb/caqv7LYvND4GLHL92GeM9+EzU3/Mz7sS/TokAsV/Ats+BXLGAYY4f1YbgCWwLiypwqKtxzD/1/xGy9fUVON+5Y8wQYmhyg3YYm6PclGLc0UReFPzPdooigATgAZGgbyi/pf9htIj+Id5KlIqipEglF56bDWARR8AAHIB4OfvLNvPWP7phf9d2scFIHfn95Zvw4tvh2JPnfsvCmSSDgBGqlZDLZhQLaoQKVRAhIAvTX3xi7mry8dsPXIeh4vLbbdPlFg+YyaziF0nStF3zmr78hdb0h/9fBsAEfcol2GC6v+ghBnvm4ZAAyN6pqqQnzIUV1csR+KBLzx6DQKAfHNr/KN2JMpFLToojuKsGIFCMQ7nEY4+ir3Y/aMGVysisfZCFwDAze+sa3inTaBUCPj3/Vchp02cXVJPFEUsWJeP57/Z7dZ+UqN0WDYh17NhKUTUfJw5CPz+uWUoZeoVgMqhB1lNOVBx1tLzJbaNpVzl+Qa/u0urjCg4dhxtdr4B/e8fo6DdXdio+wtMGgO6J4g4bugCZelRHPtzB2pLCmFQGDG8eD7qNn2KYfEwHlwDTWwaisqMuGDW4GipGZ2EfIxUrkKcUAIDql3WIeLsDlz4bDRc9fUfq/wKmy60x5bVZchRHIBZVEApmLDhvW8wTlmLQ2IKXv7GMjTQOvKstKoWC9ZZemYlwL8JTI+SdAAq//sQtH/+gCtq9UhWnmiw7GWK48hR7LLd7igUoI1wAid27Me9h/ehtVCBclGPKOECDKhCZ0U+DKgCitsCJ9Zbzok2uZaEkT4GMBkvDb0VBMvwzB3/vfSEm+cD5lrLOaSNBFr0ANRhyDdGYeWOApw1XTrnBFh6e0WhHFcq9kGPahQjEqfFaOwX01y+puW7T178n4jtR87gXz//Wa+MALPd+6Y+dwC7/zcbnS7e/pvqW2QIl3pwPaH6EpGosN2+S7ncbn83KNbhmBiPzop8nBMjcH79GZQpIiGqdLgCByAKAswQXCbpAOAx5WLcoVppu/2h+pWGk3SAe0k6AJU7v4FacSmBsuynFWgrnIcZChihRBiqoUMNTFDUS9IBQBQuoIVwBjVQ4ZCYCnOd5QJ0qEa6YDnme8U0zPx2N8prTGgdG4Y/jpcgIVyLQZ2ToTKW4njRSRQcO4oru2ehbNMONNT3rrtwADVQIwxVTu9PFYqhVSuwt6gUu46XIjZcg/KKSmS1ScS5sip8tekA1IIJJRfKIarC8MOucxcfKeLKSZ9BiQiYIUCEAjPqxVEiElCCC9BBjVrECmU48WcNznSNQVy4BiaVAaqaEkATDrGqFMeqdIjUa3D0XAW0KgVOlVaiqLQGF6qMcDFaFQCwZt9plFbWQqkQkNkiElqV/dDVhRsLsPbgGdvtK2YsQ682cUiI0GL38RK0S4rA0j8u/Sb74JdDuDU7DVF6aUepsEedH7CllWTHWAmcOWCZv+DkbmDtXMtcJaUngBNbgYgU4Po5lt4wBeuB7yYCvR8FOt+MEqMCyp//gfDdn/u9mv+qHYpZtaPwpWYGrlI03EOLLMm6meqPgJQrLPPPVJ233DGpAFg64VKCVBsF3PQO0HGY8x2ZzYCxHPjjS+DX1y1DfE9su/jYSKDng0BiJ2DVTMvwTScmGR+AAVV4Tv0pjKISaqF+7znyjXJRC4Ng+TF1WoxCqRiGMuihUSnRyXwA35quQoZwEh+ZBmO9qRNWaSdA08D7cVKMxkFzC/RR7nJZJhCmGkeju+IgvjL1wWpzN1hSfSIuF47hedXHWGAahMHKjThgboEPTdfDDAXMEKCCCbVQwgQlBJghBmCdrMeubYcJA9v7Zd+MIeSP7xG5VPwnMK+Hd48d/Q2QcY3Tu/q8tBJTymdjqHJjEyonvfdqh2J27Z31tkeiHH/oxkhQI5nTxwDDXnc6JLMho2qm4HnVxyiDHpcLxxAuOE/SWFl78Q9WbERHRQFKxTBECxfwg+kq2+gTkyhAKTBt4CtLTH3wuPERAEAb4QRWaic2WL5M1CNCqPRLXS6IOqwxd0WcUIZeij2Nlq8VFVAJl4b7/m5ugxtrXgAuzgDYRTiEb7TPelyPlaYrYIYAHWpwtUNMWvf8+5+pN06L0Zhbewsq67TwZwiFuCspH6LKgAfOvGT3+v5S/TrmqefhauUuHDInWzoI1FEhahEmVMMsClht7oZVbZ/EC3kufjc1kbsxBBN1fsAAjiQhisDuryxDJVtmAzsXWYaexrW1JN6CwPu11+NTU3+s0U6QuipB7YyhHeLL6yfUxGnnUWk04f+2HMPUr3Zhxo2dcXd2MvBqewjWJJ8Tlaoo6Fp2gZDvvyEpRI5eNt6Op9Se9eIDgFJRj+XmLLxROwIlogGrtBMQK1wAYAn0ziLC0gPzovWmTni6dgxmqj7EV+Y+yBQO46wYiTdNN8Myy3P9ZtzROa3x/I2Z3r60huvPGEL2+B6RS8unWuYy9UabvsA9Xzm9K33St/hV+yhaCA3PbSV3dZMTdW3UjkWicD7wFSKby6o+wQHdPVJXo1mxDkutO/w3WF1V9TZOwTLkOVCv5x/Gkfin6dK0QA097wFzC1ymcK/nJAD8JGbjuud/alL9XOHQV6LmxFgJvJYJVJxpvKyMCRChRq3U1Qh6zpJ0ANBt8n9RCoPt9nff/BcDf3gbyY0Ex1VGE/44dAY9/d9RicjGmyQdAEQKlRihXOt0riOlICIB9kNmcpS78bPycQDAX5Q7bdsnqO2H7Ft9b7oSG80ve1U3IgpBZjOw+3+WBtK9S73fj8k+/qkymlBeXWubXkKB4O9bIbh4DUzSSa+7cEDqKjQ78ShBGbxfcE1OblKuxW4xHWVi4F5PpFDeeKGLPEnSAbAMTZcYE3VEwc5kBF7vGvRJOqvQmA5eWsViBOKEsnrbWwsnsUO0rAw1WLER72ped3ufCtRf0YqoORqi3ISzJesAeDm8jYhCy88vA6sbXoXTLWYjft5/Gheqa9E+VsDmfz6IaOECbhAKca+21On3erCxxnhTVJ/hbyrnE8OTNP6i3CF1FZqdzbqHpa6Cz0xR+3+KJEcPq75BlmK/X6ZLKkAyskzm+ouqBRATdUTBbs3LQPkpqWvhEwKYEPKFSmgB1A/o04Ui7BDb4BHl//Ck+ku39+d88B9R86U1VTReiIj8ShRFiCJwvtKIippaVNeacb7CiKzWMYGtiC+SdABMtTW45yPLHHRPqRZirGq1T/YrJ9YedUzSyU+GUNh4ISKZ8dec5kWIQ61JhFrZeFl/YaKOKJidOWBpyQ0RljWDgn9oh9T0LlZtu0/1A/qLW3Gj0rOVNUUILoerEDVLIhdLIfK5XUuA/421rHw5+hsgMsVpsY/WHkar2DAs2XYcfxw/j6Nn7SdYv+OqNPx+tASf/60XovRq/Ht9PlbtO4137uwBnS9+da19HTi9F7jxHcvKmz5SWXlpqFWaEBoNsM4xnpAjxt9El8ihgwITdUTBShSBt7KlroVPCRCZEPIBV8NjuisOojucz1/XECbqiOwJInv+kn8VX6hGhE4NjaqZTA5qrAL+m2f5f/EBSy+1G96sV2xT/lnMWLq7wV19vvEoAGDBr/kY3/8yPPfVrovbC3Bvn4ym13XFNMu/V9wJ6Hy3mMjpkgu2/4fqd64AEUqOnJClUD3niLyhEKS/TjWTb3+iEOThUu3BgoGC/HDoK5EDkdcp8p/CkkpkvbgCN//zV6mrEjiHf7a/Xeu8Z/j+k+7P01ZeY9/braTS6HG17NRUABvfv3TbVA3UuD+ZeWNE06X6hWoyS0DovrZg10PBxSSIrJQy+D3KHnVBShRFCAJ/Oocak1lErdkMjVJx6f0t/AM4vhnIuhebjpzDnsJSdLvwK7rt/krayvoJu97LEXvUEdUlcOgr+dGafacBADuPl8JkFqFUNIN4b9939rcdYtyikircu2ATjOeOQYFwmN3oa2A02SeEzOYmfo8t/Tvwx6XVqA+frUFGnO8mMFLj0nUllGMhJXj9lKMkrrxLZCOHazATdUHo6NkK3Pj2r7irZytMGNhe6uqQl6prTXjlh324tkMiOqRE4uN1+Zi38gDMIvCXy+IRo1djyOkPMeTcpwCASd8cwsLqHADAMs3MkOwPa5mjji2t8iT9FxaRbHDoK/lRUqTO9v/j5yrRKi5MwtoEyIHlDhvsE3WP/GcrYk/+is80s7FcnYUxxica3WWtyf57y+RmT9gdx0pQVWvClemxtm1mswhFnSQdADy1ZA+uTFHiKbf22jiV0BwSdSJUjPOISObYo4688uHawzhbXoM3Vx5koi5I1ZrMePQ/27Bs90l8sPYwAECFWpgvfiSPHtyBCep/orvi0nxil5kOArAk6kI3gOMQS3niIh9EdXGOOvInU52eXwdPl/k2Ubf7KyA8CWjVy3f79IWyE/a3hUutkWaziC1HzuEj9fcAgAHKLYAbo1hrzfafU5MbH1uzWcTwt9YCALZPHYDoMA2e/d8OLNt1EhsdypqgwKGic4Cm8f26Q4VLQ3WFEE1msUGWiIKBIEj/u4eJuiAUqePbFsy+2n4cn6w/gi1HzkGHalwmHMdVir2YpPocd9Q8A4NQjY81/6j3OHWdAC5UgxwGcPLFoa9El4Tqj2iSh7pDNg+cvIBrOyT5Zsen9gJf3mP5//QS3+zTF8ym+r1U67TarT9UbCnmYVOe0aFHneiiR115dS0MWktsbayT3Csur0F0mAafbiiAFjWArv5jNe5kDN3UHIa+CgBUHPpKRDInh7k0mfEJQgl1hkSUVhkRqVNLWBvyxM6jZ7H1v//AvYp9GKSKw99U39rd/3/aGS4fa5+oC90Ajgkh+RHAno5EdckhgKPQVVMnUXfw1IUGSnro9J5L/zcZAaVM4kdTjZONl751lu0qAgC35qWrq9bk2KOufnzx5aajeGrRH7glqyX2FJZi4qBLI1Xqfu8lC2frPVYJM7SCLxN1l+K8UL7G/D975x0nV1X3//et02d7zSabTho1QAhFCAqhyENRBBEkCihiw4D+BPVRUMSCqKAi+ChgBRU7vUgTBEINBEivW7O9Tb+/P2Znd+ruzO6dmbu75/16hWXm3jnnTLnnfs/nfIvYkBUIBFZHFh51gomgK6OmQ3O3D2+tRQwtQUaauof40WOb+eje67hOe3xCbWgJuUump5EjidwllkTCEAKqQBBHKBwmGI6gKdMwWaig6ARCuQl1/f4Qbb0+5le5058QHILtT8HA/tHnBjvBY5Kn3mQJp4pdnQMBQr0+qr12+nxRASuco1AXjIyfo+5L970BwJ9f3gvAx+58KW1btjSec4oUSfv8RIn3NJuu91xh5wkEgqmALxAavjeZVzAoV4SFOQWJd+Vv6h4q4kgE2RCOGBz9nSfY/cojrOiemEgHSR51FlD584UsCQPOigiPOoFglEjQRyiQzgtIMJX42c9+xrx587Db7axcuZJnnnmm2EMCEu28d1v76Brwp5zjD4X59gNv8/jbrVzzl42c+IOneOKd1vQN3n8V/OE8eODq0ecGO9KfG4nAUFf0bzy+Hrj1cHj4K7m+nfFJI9Q9vKmNI78dtZlCw4JbZqHO4E7tu/yf9n3iCx8FQ5EEL7pcq77Gn51WqCOMHmebTZbE0NfpaQtJRAVOgUAgsDIyBkTM24iZ2BgEU454o6OpRwh1ViQSMTAMgz+8uJur//Q6ACfLGybV5kzJUSdyl1gP4VEnECSiRAJFN+AEk+Pee+/lyiuv5Ctf+Qqvvvoqxx13HKeeeiq7d+8u9tAIhEbvg4OBMM9u7aBzIFEYvvXxrdzx9HYuuXsD/3w9Wojha397K7Wxx74Br/0u9fnBDuhtgoEOCMeJTU/eCP/4HOx7JeqBF/SBYcAbf4SOLfD8T8x4i4mkCX2Nv+OER4S69J4N1XSzRnmd9ymv4mVw5PlQxEjI95ejThetGjvYyXXqnRwpv5NyXCViao66+E3Y6ZriBKICp0AgEFgZK6y1RejrFCTe6BAeddYjEjH4n58+iyLLvL6ne+T5Cql3Uu3OhNwlEtP3vU19pu+iQSDIFSFcT31uvvlmLrnkEi699FIAfvSjH/Hwww9z2223ceONNxZ1bMlFELa39+N1qCys9lDnsSH7u/n9i6mC4r7uIboGA5Q5h8uQGgY8+8P0nbS/G/VkCw2BsxxqDow+9/T3osfnr4GBVlAd4KyIthVjnPx2W9v6eHbLfi5Y1YiupvoErP/ja+zcP8AfP7kaVZHTit7GsC+BYYyKbZk86rQEr7Y4j7pwJMFmThf6qilSyucd/3rjka9ysfpo2uMyEVM96uKZrl5nYkNWIBBMBawg1AmPuilIKN6jrttXxJEIAK7+0+ucceuzI8Zga5+PN/f1Joh0h0mbOVN5blL96DPEo07stFoPiem9uy8Q5IrYUJjaBAIBXn75ZU4++eSE508++WSee25y92ozCCQVQXj4rVY2t/SzcW83f/rxlfC9eRwx9J80rzT43X938fqeblp6fPhat2bupGc3hPyg6ODvjwp2b903elyzg7saVB26dyWGyva1jDn+9938NN/45yZ+98KulGORiMFfXtnHK7u7ebNpeAMzTehrjKFgeMSjzsiQhEGNy+EbHz4aChtRr7i4vpOxqZnzD4UiRrRSbgZUwtik/ITAT9fNAAlD2BMCgcDyWGGeEkLdFCQ+9HVv1+AYZ0bZ2tafOW9JMlsehc7tEx3ajCAW1hrjzy/vZeO+Hv67PWrE6mmSi9+h3zzpftWE3CXFnzzyhVgAW5PpumgQCCaCZIh5aiqzf/9+wuEwNTWJxRRqampoaUkVofx+P729vQn/8kllx8tcqf6ZtdrrlNHHpuZebnjgbb7199c4r/duAL6t/V/Caz6iPMbbto/Rv+kR9vf7eX1vF7tefSxzJ76e6F8pzmbZEZejLzAAsgq6KyrYde8ZPdYWVz12mH+83jRiB8V4qyn1c4oVhgBwaAo8dyvcsSblvJjNs6N9gH7/cDEJI96+it6TTpFfZI38WsrrIGovB+Ny7aXznLOl8fgb6cHXA107Mx7Pp0fddLXzJBAedQKBwPJYYQ4Woa9TkHg3/l0dg/QMBilxJoYg+IJhfvjYZtYur+Xcnz9POGLw20tWceyiyvSNhoOw50X43Qejj7/Rk6/hT2lC4Qin3fIMlW4bv7/sqATBTpGiO73pLuvKSYa9AmhSvEdd8SeP/GAIoc6CSBn9GASCmcl0Lugzk5CkxJnNMIyU5wBuvPFGrrvuukINi3n7/8156l+iDxRoVWr4b2AhPUPOEcu9QurjE8o/eTpyMF2Gmxu0XwHw3vZf8/KmBRzf6KCq+d+ZO/H1DnvUqdEN2n9+Hnr3jR4PxFWbVW0Qjitosee/UD4fyueBrLC1rZ/P/eFVAHZ+voFLlAe4M3wKXntqeGzX4KgHmiwBj3w17fBiNs+GXZ10D0U97uJDX1XC1Eqd/Fz/Uerrhi9PfziS4FHnD6UKROlCc2Msv+9EJF+GohuYn6MunukaOQHT+70JBILpgWSBeUoIdVOQeKOjYyDAOy29HDKnNMF9/zsPvsNdz+3kzmd3jnjg3ffK3vRC3Uu/hIevhdqD8j72qYovGOatpl40RWJzaz+bW/uJRIyE8BR12JMukpQD5Vh5oyljmBmhr8KjzoqUSgN0Gp5iD0MgsAyy8Kib0lRWVqIoSor3XFtbW4qXHcA111zD+vXrRx739vYye/bsvI2vq2Ilj7TtZaW8mYpQKzXhVs5UUiMjrtX+wLX8gbCkjohTC9nL06/8iXvfquMqZYwiVm/9JfpPd0eLOSQXdEj2JAvGRXD0Nke96kJ+qF5Ka29cGpbb38PXNPCj4bEfkNJtTHSD9B5uMWI2z0AgPLIpGi/U2QgyW2pPeV186KsvEE4S6lKv27E86nTf/ozHIGqvCI+6XBE56gQCgfWxwhwshLox+NnPfsb3v/99mpubWb58OT/60Y847rjjij2shBx14YjBtuEkw4trvChydCf4jxuiIQrxQlJ8zrQE7h82Pve+OPpcOBTdZRUAcNUfX+f+jc2csrx25LlAOIIvOGpsxD77uCgLSujnt7o5SakTq74Wf/LIF9NVhJzqzJfHzkkkEMwkrLDTKpg4uq6zcuVKHn30Uc4+++yR5x999FHOPPPMlPNtNhs2m61g41t77mUEw5fQ2d3FkK8JY8d/MPa+hNT+NlIkjHr6dwi+ei+2rneRW99CifN2K5P6uUr7M0Qgq59pvOccgK0E/D3w8l3QsxdWfRJcVRAcGD3H3wvuSujeCXYPiuxKafZI+R22YdDnC+LSVeRhG6k7zqNuc2svyzIMK2bzhHrbiQzbspEkoc5Oan64eBFoKBhOsIPTC3WZc9SNh0IYmyQ86nJBEpETAoHp9BpOthr17DJqaDNK2W7U8375eVbKW3BK/vEbEKRghbW2UGIycO+993LllVfys5/9jGOOOYbbb7+dU089lU2bNjFnzpyiji2UlGQYA3Z3DqJIMgur3UQMg8FA6m7V9v0DBEJh9Hij5J+fT9/JUBe4q0wctYkYBqQJTQGiCY7dNZmP58iru7v4v2d3cP/GZgAeemtUrPCHIviCqcaG4+XbuELZxM/CZ3GE/K4p44CZUvVV7LQKBALrM10X0TOJ9evXc9FFF3H44YezevVq7rjjDnbv3s3ll19e7KEBoCkyNRUVQAXMOhBCH4OhLiLhELKzHM1bB4P7YaiHUNOr9HsWMISN8Bt/wR4eYLBzLy5fC09HDmSJ1srSSLSwRGDWKlrLj2L2xh9HO1rxQfDUwsp10Q3b2UfDY1+Hd/4JWx+DHU/Dig9EQ2VjDHaCagfdCfs3owTmp4zfzRC7OwfZsLMTh65S4dJprHCxv3900ThWQbSYzRPwDRAJR+2CePvARhBbmrDTeA+3oUCYUNzuqT+QKuzZtJj4Z3CJ8gAbI/N50VhKNpXOFSmfoa/FXyTmi+lqwwoExeCCwLVsiBxAgMRUA/eG1+BmkOu1u9gcaeDj6kNUS93FGeQUxAopToRQl4Gbb76ZSy65hEsvvRSAH/3oRzz88MPcdttt3HijOR5SEyWUVLXqpV1dnHf4bLbt72f7n7/Kift/zzLpG2wy5qa89sE3WzhhcXU0p104FN0xTcfg/milL9UR/RvDMKLhEWrhdpZHCAzCA1fDrufgE0+CozTx+MY/w32XwKrL4dTvmtLl2T/LXP3NHwozFOdR59r3LDzyI0r2beBLGtwTPhEn5u1iJBaTmJ5GjkTU8BUIBAIrI4qrTH3OO+88Ojo6uP7662lubmbFihU88MADNDY2Fnto6VFt4Kkd9SmrXhJ14Q/0o9YfQqnmwD40QItkZ1d3D86FYbYOqVy/oZTuwSA77BcCEHFV07L4IyNCXWv5SlzV83A7SqF6GWh2tjSez8uh4zi3926U1o3w+h8SxzLUFf1rL4X+NpSuLSnDdUtDSJKE164z4A+xq3MQRZa4/anRgmVamuJbI8eGBbehkEFsfzpBqJMCGTzqRoW6wUCIvsFRMdA/0AvtW6B8LijRRW0s9PVE+VW+pv0OgLm+32cV0qoQwZan0NfpKmYJO08gMBefoaeIdDH6cbI+eAUAPw+fweXKP/mydk8hhzdlsULkhBDq0hAIBHj55Zf58pe/nPD8ySefzHPPpQo3fr8fv39UkMl3NbDY7qAqS4QiBn99dR8b9/Vw9Lxyrt9/FwBfVO/lY8H/N/KaWbSzVtnAC1tqKXVqNJY7qRnagiNTJ71NMLAfjEjUQ61yMcgyDLRD+zvgKAdnBchK1NixeaOVw7LwZHtzXw8b9/Vw/hGz0yZtbu4ZQkKitsQ++uSOp+Gej0TDLYD//PkWjrnofxNf+Ojw4xd+Pq5QF58wuq3XR68vyMLqsXNwLZD2sdeowk9UuAx178PobuNI6W12GTUseeQzCecrRLBJqUbkRNHjiklM10WiCIkQCARTgens7TKTuOKKK7jiiiuKPYyJI8tg90b/AXZnOXNKalHbO9jT1ILbtp/vvb+erz68j5jj1369AUPR2XLUd9EC3XSES1Db+3G7B2iQI9iAM/5p4AvXs+Owb3HN8g3w7xui9mCMoU4C4Qj+YISwXEaQPkgSrDwMEQ5H0FUZWVLpGAxw8a9eZE/X0Mg5kUhmD/qYzTMQNLBHBgAbqpToUWdPY2PFi3m+YJht74zmCfZHJGh/O2rLempAd6MPi0aNUmIOQCeZvf1iKHksJjG97TwROSEQmMW7Rrb5UiV+Hj6DpyMH0SC18z3tDkqlgfFfNkOxgp0nhLo07N+/n3A4nJJQuKamJiXxMBS+GthhLX/mDP0hBmuP4B3nEfxkWyVb2/pR2zfBsKNbpZRYtfUx2xdxSAHu3uNEPeRLvNPSR3DXMyzK1EnHViidE/Wg622GktnQ1wS/P4+hkMEf536TCw/YGc3LJsvD3m5XwcqPwXFXge5KEO22tvVR5bFT0voCf/zFH/l1+GRqvXbWLKlO6NYXDLP6xieir7nhVNSOzdC9C/7yiRGRDuDf77RwTPKY5TF+zvu30hnWMVw1fOv+t3l9Tzf3f+44HLrCkd9+HIDnvnwi9aXppcvV8lv8Qb+BtyKNnB6IelTW//IwAP5og1ajNOU1EgYOEz3qZkqOOiHUCQQCq2OFnVaBIB2yqtFQV4vDU8aW1n7kQIjvnl3Kf/98KCvCb3N923HUKX0cVLGKxUsbcAT7CfTtZ3tngMFwH3WaH9+wjvLc3gDGMe8Ffx/Sf3400kdksIu39vUQCBlEMNjTl2qTuBnC8PclPBcv0gFIofFDX1d2PcR3gr/kC/KnEuwgnVBajzo9rupr2IBAbxsQFTL9ERm8deDriQp2hoEtGPWoCyYsiQxcWQl1+chRZwDSNI6cMFCn6XsTCArJ/wtexv3hVQxkdrtJg8QmYy6bjLk84j+cBVITFyqP8TH14byNc6pihbW2EOrGINnbK94LK55CVwNb3vs0B8jvQNs7rOE3fMxVxVPGYXQOjBosS6Q9XOB8iQeDh1Af2otjeNexoedlQvteZUGpk/LmZzJ30rMHvLNAG/Zq83XDc7dA5zYcwA9f7MfuaeC85S4IB2HDndFQiGdvhsajo7u77hqwl7CpE0679Tnsmsw7yvlcr8Feo4qdHcsT+xzqpnvD33DiYRA7Q8Ewnp+tSju8+ITCIyhp3H43/Z1N+0Mse+LjlBMNZ4jxyKYWzjxk1sjjN/Z2ZxTqzpafBWC5vCvt8Zo0Mf9aBiNyosTvEk9XMUvstAoEgqnAdF1EC6YPFW4bEQNe29NNmcvBxhN/ycf/9RqDu4Hde9AUicuOc3DK8loUezk14QC9nX66WkY9LAKhMG829eCqfh81B3Yw1LqNyrbnkCMB9EAvTncFsgyd/lSxyiUNwVAPcqAPlNRiEwDaQHPG8cdEuXO7fwnAD/XbeCB85MhxG4G0OeqS89z2q+XEvP18wQjdPgNVLcHtrIi2Y+sA/ATilkQO/FklYM+HR51KmBCqJRaJ+ULMnwLB5AkYKv04J9GCxDZjFteFLubRyEo+qjzKSfIGFAvkZrMCChFUxZyc9xNFCHVpqKysRFGUFO+5tra2FC87KHw1sFcO/DrPv/l3TlFeorrvbey+dtbycMK3qUlhvh35Idc7SgjrHhgu6lVq9HDho0N8esUAn+h6M2Mfgbat6B3boWQW9LfDpr8mHK+SeniluYbzlhMVyOIrxPYOG1797SArPPN29LPxBSMwXMfiMHkLZc643HdDXfCrU6ltf5vva0fy6eCVhMKZJ4oIwxfOYGc0LPaAU0HRE875y1//yDmvX5axothQIIxhjPYRGKO/UJIwqGWRk0SVwthNNOASPOqm6SQqSaAYwoATCATWRhbzlGAKUOHSqfbYaO/zY9M1BhlNKRIMG/zsyW08t62DdUfPZUGVG2/VHHa17o87J0K/L4QiSfgXnMrmah3vC7vR+/cy980f03TU1wANu5a6eephiHDQj96zg0DpUvzBMAukfXxDvZtbQufwkrEEZ/fWjGPXkgS3sCElPGeTxq/6CjAYHh3bYDDC2y292FWFhTVuPLbRarQGowsyD0NZe9Rlk8suF3RChFCncehr6nckEAhy5yVjiWltPRdZwXORFXjp5wBpLwfL2zhNeYGbQh+imm5+pP/MtL6mChIRNDlzHtVCIIS6NOi6zsqVK3n00Uc5++yzR55/9NFHOfPMM4s4sigfPPk9dB69inJliOD+bUTefQB2v4DW9gYSYJz5U0Kv/h7bvv+i+rpRA6NhsCvlLbwgfZJXNi1CVTLvZOpbHxxzDGvkVxkgrspXcHD0/3t2Q92B0f8PB1GMzpTXV9Iz6jkVDsFtx0LvXgBOV17k00EI+odSXhdDIRL15Lv7f6B1I5xwbULo659f3suWDU+QnFtTIoIxLLoNBcP4Q6OLrZRqunEEky6VbHKXqIRxmFgS22xj0KpMV29BgUAwfZiui2jB9EKWJRrKHLT3+UcEqRjL6rxsbu3jtT3dXHnva5x1yCwuXt1Ih18ZOad7KIKDAPHGVNOq/2XOvz+Dq+0Val75Ma0rrxqRuOJDwjUpTFDSUAdbUVwNtPfD97Q7WClv4TjlTeb6fk9YHu0rmWRPtUHsCYUiMuWoS7aVBoLxG7JQ5tDpHgrQ1DXEgmr3SJhsvHeeRxqMegSOg5oHj7rYpqyZ9qOVkDCER51AMAl+GTqVO8OnsNeoMr3tXty8ZCzhpfAS/i98+sjzS0J7WCbt5D3KxjFePb2wglezEOoysH79ei666CIOP/xwVq9ezR133MHu3bu5/PLLiz00NEWmpsQBOMBdDrWLobeZwf27COmleGsaUW1OCH4Y2rcQ2fww/tIFBPv249r7DN7IICcor6dtO+yqQRkYTag75GpACQ6ArKAFuokoNpTgANdqf6B310MYL74fadkZBPv2j5pxnTtGG1Q0FJsL6E24MVdKPbQ3vUtk1/eQ3/4bJOUxAQi3v5PxM3DgJ9y+OVqNDBh6/T5ahyTmDh+/+k+vc5WaamTZCOIbTuTn6+tiqHXUwAr6BiHkjwp+kVA0d4kq4w9FCCVdKm6yMeDCpoa+ZuPFN9URxSQEAsFUwAoGnECQDeUunbpSO/u6BxOeP3dlAw1lTn77wi6e2tzO317bx5a2Pg6dXTZyTldAxvB1I6vGyIrBV7mC9oM+RfXrP8G790kGqw+F0hOAVJHMGLalMAzae4ZSNjmlSGa7Jr6AFsAQtsSqrwSzCn0djDslOGxelDp0Ogb82Ltk+vzRfuLttRIGsvSoi6Qdw2SICX/1Uuom93RB5KgTCCZOP468iHRj8Z3QhwH4tvF/HCRvZ4W8s6D9FwMr2HlCqMvAeeedR0dHB9dffz3Nzc2sWLGCBx54gMbGxmIPLRV7CdhLcJY1QiQcLeQwS49WbtXdyBULcNQfQmtrJ5t3nUmlHqZ/3yZ2bn+Xf/oP5Qzlv7xf+S8AgYWnssOzkiXPX40hKbQd8SXC9nJa3cswOrawZ0Ci7bnfc77yb6rCXfDabzBe/x2qNLor2t+yhb0tfWiKhE1VGAxEjaZ4A61S6uGV9m7knb/J8KYMere/TF2Goy7JR/vOt6gdfvxmh4EBzB32UJWIpBXT4oW6gc59+FolGN4LHmjdBjv3RYtjRMKAgVs18IcgyOj7k4lklbvEbKFuZuQMEDnqBAKB9REeIYKpgiRJLKhysy+pkEN9qYPaEjtXn3wARy+o4EePbeGtpl7eahot3GUAe7T5LA3sAk2F4ar3Q5Ur6Fh6IZWb7qbqjTvQVx0I2FM2FB3hPsANQHvvEPuMSpayZ+S4HMlsIyW3NWjY0OKqvupkCn3N7FEXjETzTauqjMemsa97aMRGjS/+5ZGGcGZRDEwhnCIoThad0LQuViM2ZAWCybEhsrhofV8buhSZCH/R/5dD5O1FG0chEEKdxbniiiu44oorij2M7NHiCiE4y6P//HNhqBN0N5VeHyGnyn6/imvRe1kw+wiUHXV85d1lI0LdnnAFzeVHIB37Q+w2FxHVDrKCx6ljC7nY0KNyc+hD3BI6h4+4NvAFz+OUdL8Fcfl6bD078PV10ad6CBl+OgeiRky80VMrdREgMadcPJX0srdriAMyHHfi451uZUSo6zccCbuaTvxphTo7AWKBwHuHbOwNu4BuAHb0yeztC+HWZdwOG6oi4dT8dPggFCfUOfFltdOqEU4bljFZprOQJSFCXwUCgfURoa+CqYRdU1gxq2TksdumAgadAwHKnBpHL6iksdzFjQ++za7ORM+7R/fpeOc3MtC7h383hynv7WeeITN/wdm4m5/H3rWZpW/fgszVKR51zsioUDfU08Y8aTT3s04wmsIkA8lC3RB6okedFExbcTVZOBsMJV6rwUh08WPXFey6giSFACPBXvMwiEvKwqNOMj/0VZdCzKHN1DatxnS2YwWCfPFKZCG3hM7mmchBRR1HBJmzAt/kePkN7ta/W9Sx5BMrbJgIoW66Y3NH/wFum4fZTi/q7u20t7dQapP47DE1HDWvHJ6Mnv6d1zSe2LCdSlcFaw6oYc3iKuaUKBiKRshRTZc/6oofROVvoaM4/cg11AR2Ub31T/QHoazjVbRgLwc980m65/8PXQvPxmvXgTDOOKOnVupCCmferZwrNWMzMh93SX4ueVJj23Be5H4cCQaiCx/uNPlF7FJgJB9J51CYLe39I8c6hgz2DEgwYOAeDFHlseHQZCCckGTYhS/hvWRCNbnqa4z3yG+Y3qaVUKXiT4wCgUAwFqKYhGCqUekeLXrWWOHkoNml7OoYpLl3iGq3nVllDm4692BufWILL+7sxGvXaOvz88+NzTz4lkQo4gTCwH7AwdIKP5c2foaze66iovM1rlfv5CehsxL6dIb7YDg24pqWL1Avjwp19dJ+5MhYQl04QdBJH/qaRTGJpC4CYYjb1iZWU8wR15ZHGswqF3G06qvZHnVBqqSe8U+cokgYqJIQ6gSCXNljVPNk5NBiD2MYiaciB/HL0KmcKL/CPLl1/JdMMYRHnaCwKBq2sgZme+vx7Wthb2s7JbKHQ+dr9DxfR4m/mRdDCwHYPxDmT6808adXmlhY5WbNkires6iKDl/XSHM9fggbBv7ShfQdchmbA5XMDu6gZsP3sPXtoXzzvZRs/xdHVp6JjZNTwggq/LszDnWe3IIcdmQ87sRHGaMi26Bhp04ezefhkQYzhr7G6A+AhALDRtZQyKDSbSMSgQF/iO37+0c8BeN3TN1SdtXANCmcYPiZReU0N+BESJlAILA6VthpFQhyQVNGNxxnlTqoK3FQ4tDY0tpPc4+PCpeOXVP41AkLuSwSodZr5/antvHU5v209/tH2lhSqfNOu4+3O8Jc1VHJK65P801+zIXq4ymilTsymn+4PtKScKxB2o80hlCnE8LLwMhjn6HjlUa9/WwZQl9TQmaDiYutQCTxcexKjm/Lw2BWKU6iOerMtfM0Qqa3aSXKbCAPFX8BLBBMNZ4IH1LsISQh8c3QRTwuH8rv9W8XezCmYwWhrrg1ZwVFQVFkFs6qpWbWXNp80BeAv66+j4N8v6AfJwCnrajliLllKLLE1vZ+fvHMDi6+80X+vW1UJDKAwd7OhLDXoaqDaT7yqzQdeS1+byNKaIDVLb/nUf2LnKa8kDCOev+2jGOcJ7UghTIXbHDhSxCsVCnRsHEzhCedR13cOf1Bg0DcWiu26yrL4HGoVLntI5doclhttkmG8xH6Op2rv0oYKbvhAoFAYDXEhoJgqiFJo0JdfWl0I9Spqyyt8zK/0kX3UIDuwajNIksSJQ6Nk5fXcuqK2pHXHdRQyvdPqeOeNUN8eJmOW4PfDRzJ/wbXAfAh9amEPvVgH4GQQSRNwbAGqR1lnBx1pdKoUKdIEea4Ru2fWpufcjWdUJdoQwwkmUyBJBMjptslhL5muSGrEkY32TtMJzSt7bxqR0TYeQJBDuyI1PDRwP/j75Fjij2UtDwXWcG6wJf4Teh9xR6KqVjBzhMedTMUVZE5oNaL26ayvX2AgGSnF9fI8TMOrqehzEnPUJBntrTz73fb2NzaT58v0Xh4aJ+DC/RmSt2jBiCSxED90QzUHYVn71O437iLOcF2PiP/PeG1Df7MSSjnSi0oIW/G404pUaizE8CehddbvOA2EAR/nK0wEEpVzmMhESkedUUKfVUIm54PxUpIWGNiFAgEgrEQOeoEU5mldZ6R/9dVmUU1bjwOlW1t/ezv91PuGs0hvLx+1BY7qKEEQ9Epd8Ily+DDSz3cvy3AHzadzPLQTj6s/juhHyPQz9P//heXSJ9IGcMsaT9ypDrjGGXJoJzRwhYaIVzKqNH2/lmDuLuHIEkDXFUd5pfNo4+TPeqC4cTHMTsv3l7zMpAi+KXDkUXBiVzRpZDplWSthEczWHdACKZ3HnqBwDS68PB05OCC9XfBMp3/WTmfjdt2ccNzmZ1m4nkycgj/iayg1SijDyfXaXfneZT5xwp2nhDqZjCKLDGnwoVdU9jdObprWerURoy0EofG+w+q5/0H1bOrY4B/vtFMny/IQCDE63t6+ONWiT9u9XBAqYGuDXBEA6x2yzS6DCRJpm/2Gp6WDqftv/dwmXI/trgkv3MCWzOObZ7UwmBoTsbjLvxUEi/UBZM86sbPUdcfNAjEGWxDaeyi2OH4hMUufFnlLtFMrvoKUcFwOu+0AqhCqBMIBBbHCgacQJAr15+5nJd3dXHOYQ0Jz0uSRF2JA49dY+f+AXzB8IgHXq3XzrI6Dz1DIQ6ZXUrI4SLgnYutZxsOZw0fXGLj1AU6/3xrHf0t7+D2japks9RezuGJtGNpkNqRI2Vjjjc+V9tcZxDZGBXPpEgIOZJqD9nlzFVfgYRICojPUZdY9TWbTcNswmNzRSeInqZIxnRitlN41AkE2fK3cOE86T54UCUfWxagospJRVDLWqiDaP76n4TPBuAP4RORMFgrv8RpyoucoryUryHnDSsUNxRCnYBqr52l9aPVwBZWu+keCtLvC+Gxazj0aMXTxgoXFx3ViKpIVHtt3PHUdp7e0k5Tt493uyUgzMb2Xn6Fk3J7P6vqVU5s1EBzcFPoPP4YPoGLlUdwM8R56pNURvZnHFOj1MqWcObJwZkU+mojgD3OsHEzlFWOuniPusE0+lcsJMIWJ4458WXpUWe+UGcjOM096kSOOoFAYH1EMQnBVOSjq+fy0dVzMx5321SW1XkJhCP4gxE0RWIgEOb6M1cwq9TBG/t6QJIIlMxDDg6iDbYRdNfi0iTet9BNYNGXMf79/5BCURvpxMruaO2JNDRI7bRFMo8F4MoDOmFH9P89ahDCo0abHAkipQmdbXSHOWqWxq7uEM0DRoptlxL6Ovw3PirDwyDEFRHLRD486qI56qavnQckpMwRCATpuTt0Eg9FjuS/kaV570tTJM5apLJ+TQP9raPurlef0MCG7S08uTs3J5EAGgD/iBzDQ5EjOSL8DucqT3GW8pyp484nslT8DVkh1AkAWFA5GvZ65NxyDpldSmuvj87+AJ2Dfrx2Dbdt9OfitqmsWVLNexZV8cv/RK2o+ZUudrd28EbzIJ0+eHB7kAe3B3EMv2y3UcM3QxehEkKRInxQeTrjeJySH6+/OeNxl+SjUhoNibBLSR510vg56sIG9PhHL8LBNKGvo0JdfOirL+vcJQ6Td1t1QgnefdMNkaNOIBBMBcSGgmC6IssSdlnBpsosrSthe3s/iiwhSRIRw8AfCmNTNQIlc1H9nUihIQw1mvMuVLmEwGm30N7RTsN/voKrb0fGfhqk/bzRP/bib5YyuiErRUKQ4FEXTFs11quGuP3UMr7xVBd/3RIklHSpBjKFvsblqPNKg4QMZcyxQZ5CX6e7UGcYQqgTCLKgBxfPR5bnvZ/jGyQuXD2fOqMFj02NK9UIFxxWzdraXp7c3Zvx9eMRQOM/kQN5PrKcn4XO5BHb/5v8oAuAFSInhFAnAMBt10b+/4BaDzVeOzVeO32+IPv7/OzrHqKpZwhZkvA6Rs916ArfOGMZpU6dt5t7qVvVgNGzl807dvHvPWGeatHoDybuSoZQuTp4OQ+q7+VLZU8x17cJ22BiNTCAKl/mBBbJHnXJOepcabzpgJTiDp2+OKEujV0USZOjzkX2SYZN96iTAtM+9NUKrsYCgUAwFkKoE0x3JEmitsSO16ESDBkgQY3HTs9QgM5wgGpPCUFXPXrvLoJux+gLNQeDNUcQ1EvQ/F0Z26+hC59vaMyViOxPEuoi8R516UNfpeFzHGp6j7hgcujr8F97fOgrQwSk8ZdIeQt9nc5CHUKoEwiyIVKAmp/zS+DLR6gEPTqMocVdvrqO13e38/y+ia9BI8hsNmZztv86zlf+zXnqkxNuqxBYwc4TQp0AiCYTtmsyvmCEoxdUjjzvsWt47Bq1JQ5ae4fY0zWEKo8RDiCrSGVzWeqq4MAF7Xy2p4mX9g3xWKuT1bOdvLy3H5u7jPvf7uLxoUU8PrSIWm2QkyLPUkY/n1H/igRoUhh3qDtjNy7JTxWjx+0EEjzN0nnTASm7lB1xJeKDkWiSYU0ZfX+RNDnq3JIPZzahr1I4QTw0g2g1sOlrwIliEgKBYCpghZ1WgaAQOHUVhmtLHDqnlF5fiK1tfbT2DVHnrEMbaEYODgKjHmhhWynbVn6VhRuuQw32p21XlgxWaM2MdSnJgbiVY7JHnZE+9BUjupB8z2yVP70bSBHmkj3qRqq+xheTkAYYMmyZBzZM3opJTOPICSDhexQIBOkJG/kV6i47ppHVlT6Qe8Y99xOr62hu6Of0P6VW8M6VV41FvBpaxG3hM1gtb+Ia9fd4M6zbi4lsATtPCHWCEZ764hqGAmGqPKnGiUNXmFvpptprJxgy8IfDRAyDYDi9qBLRPQR0D7KzhqO1jSwv3c/cuRV8bH4vW/RqTipv56kmiSebFFr8Tn7DyQD8PHwGK6QdfFv7JUvkPWOOd7bUNvL/Xmkw4ZiXweTTAVI83OI96iCadLg0jVAXL4458eHKwjizETTd2JruOerAQJWEUCcQCKyNJDxCBDMQSZIocWgsrfPydnMvrQMSNvcs7N3bgIqEc/3u2ew45Es0bPsDjs6307a3UG5irGwXSrJHnZHkUWdk9qhr9CpccqDKz19PPGckR50RQR3az9LQHhbK+ymXRhegHgaRsshP5Mxb6Ov0jpwQ86dAMD759qj71JrFbG/tIuB3ISnquFk5dUXizvMX89LmXfzslcnPfTuNOnaG67g/fBSzpXbOUJ7jGPlNDpR3TrptMxBCncBS1Hjt454T21n1BWVmlTpo6fEhjXFlRzQXvvIlhPteRu5vgeFQhDkeuGRpmCuWh3kysJg3WwaZr/fys1dhl20Zpwx+h1XSOxxka+FQNrHGeAlHUthqg9Q+8v8lJO7YVkvdacczlkcdwEAQSuM+hshw8hJbUuhrNlVf0xWzmCz5EP+shCgmIRAIpgJWMOAEgmLh1FUWVnl4ZaiTXnUWqq0Dra8L8CSc53PPpuWwqyDQz7ynr0xppyacmvYknpTQ1yxy1EmR0MjVecJslR098PDOqPAlE2F+x5PManoaW9dmlNAgP4QRj8EY2dpvZuchhlgxCXPTplgJSYS+CgRZkU+h7rLj5gNgyBpBZw26kd1cdnC9m0C3CiZuUvTi4i3DxVuhuQCcIL9GndTBjdovTetjIkgWWI8KoU4wIeyawor6Emq9dpAgEIoQihgMBkJRMS+OiK2UvrKlGLZWiCQKaooMhzV4WFzj4WDFz9pGg0HXHG59dBPPtS3hBd9S4ARsBDmvejezfFv5kPEIZcEWdGnUYLNJibuP9XJH2nHbknPUpQh16UMi4vPCuSUfrixcdN15cOOdCTutopiEQCCwOlYw4ASCYlLi1KgrcbCrcwB36Xzkng0QSr+J2TfreJ4+4xlWNf8W24bbR55Pvt8byPjKl2Dv24UUHEDxd48eTBLl0ol0AJIRTpDRP3GQxtmLZN7a+Aqndf6WpXt3jzYpq7Qa5ewOl9NilLMxMo+var9DkQxKMkRmxJOfYhLBaZ+LOD7XoEAgSE8oT0LdC9e8l7a+xLnLkFWCzmqQx5eG5pXInLG8nP9u76J9yPxNyycjhwDwcPgIZAy+pf2K2VIby+Vdpvc1FlbYkBVCnWDCyLJE9bAXni8YZn6li5YeH92DQcqcOg59NF9JSC8lWFOD4WvGGNIzNYkiSdR7dT673Ed/WOHFNgWQ8KNz0vtOpzbSjKydSe/zP8Hd/B+kcCjtgmmx3kG6CNGF7iBxqe1SXplJqIvf3cw29DWbghO5okvTO/RV5KgTCARTATFPCQRQX+agpddHj1xOxFWPPNQBevqlRUj3Elz+QSIHf4Td29+lbNNv8La9iN3w8fvQGhxSgKozvkmNPsict36Obcu/ol50wyTnhZQyCHXJIpCrdxuLNt/FKd1vggyDkpPBA85hoO5IAp5GLn9kkG3dsbYNzlGeZVmWC8K8hb5O48iJ6Nco5k+BYDxCjF95eiJoShoBUNYIOWtBcxByjC3YSZLEdWvncs9/BvneC+avdWN04gXg8uAXALhQeRQXPq7R/pC3PuMRQp1g2mDXFJbUeakvc7CvazAq2A0FqHDZ0NXhCUFzYniWEGnpJaLYUAIdoDoztmlLmkd0RYYIGO5aupZcQN8B57JLqmPJ69+mvP2lhHO1YPpkl8fUBPnzieW80TLA917w40va1PvDJj/9AYPVs1RUWSKWc1iXEj3qsikmkZw3zwxs03ynVcJAtcDEKBAIBGMhGWKeEgi8do2GMgfb2vsxHLMx1CCExygdKEngqSOsN7Nn3of4q/QR3tjVxhvGfEDit45SCA8yuPoqaHkdW1/mXMVKKL2NJRkhMAzsXe9QvfWvVLQ+B0BY1vhl4GR+GjqTj2uVnFYS3TROvJQlLg78P27Sfs7xyhvjvn97HgQ1TZreRcPAgIgQ6gSC8ciHUHfeEbPHPkHRCLlqQRnfxhkr9VU++G34JAAejxyKjMHd+nepkzrz1p8Q6gTTDq9dw1tXQl2Jg92dg7T2+rGpSYqbJDFQsgitH2xj5PfQk+YnmyoleMkZqo2w5GTTYdexfOBFvE3P0KNVUf7uPRnbdLW9wkHqj5gtl3D08lK2+MrYHvDSr1Vy1xY7r7bCq61DVDokzlysj1QLS85Rl423XD5y1OkEU/LsTSckQBE7rQKBwOKI0FeBIMrcCheGAbs6ZELeBRh9W7J+bUh18oaxYOSxKhMtLqE5aTvks9Rt+B6yvydtmGsmoc7RuwPpX5dQ0hMNcTWQ6Kw/HvXIS9j+mo2ed0L85GUfB5QrLChTRiInYrRTyrrglzg9/ALz3UHWB36e9fsxAxuhaW3nASJHnUCQBWGThbr/fvm9tPdn6QUsa+N61h3ToFHnjdDcW9icmluNBgBW+2+lkl6+qf2KNfJrpm+cWCFyQgh1grxQ6tTx2jWqPD7eae4llGQJhXUPg+UrsAXbMBQdgqkXuS1pfrInC35xhErnEqpZQJu2iD5nIxXb/4q7Z3PKedpQO2x7iBqgBlgSd+wau0ybVs8rgUZeC8xh48b5hCOLAS1JqPMVUagLoU/nkAhAETnqBAKBxbHCTqtAYAVURWZBlRu7puCwlYDsxxgcvzgZgCobSY9HXTTCtlLaj/s2u/0OlrzxfUq6Ej3c1HB6oU4ZjBYai8g6HdWr2T//bAa9jcx3uzhzYR87egxeaA7zgxeHuPUkV9or2UDmX5HVLFBUNjqXsasrwK+077PTfgArK8P4Bnqp6tmY1XvMFW3aC3UGkiHsPIFgPIImC3X6GOvoFGKedZqaUbBzqBL/vGQ5v37mbW7ZkL8Q2MxI7KeETwW/QBm9fFK9nxPk11giZ/bEzgUh1AmmNbIsUVfiwDBge3t/yvGI6iDgXogRCkOaCle2JLdbmypnFfTZW7OK7pIDcOzfyOI3fwhAf+1RSIvXMtDTjpchBrqakQbbsQV70fxdaIFu5EiI2uBeTpP2cpr2HwAGDBvPRZZjjxtfmdSPJo1vZOSjmIRt2ueoM4RHnUAgsDzCo04gGEWWJWaXR1OZDGmLCbel2nzpUJNCp+KFOohGToQML28e+T0O3PkrPNv+gTRcsEJK55XlKANPHcFFp7PdfThdYS2aNmVYjpMlic8fbucTDw2wpSvCXzYHGCuKPWzANhrYbfg4IXAzR5QrfOPEJTS//RzHb/hsVrZgrkSLSUxfOw8QHnUCQRaEDXOKSax/32LmVbrGPCdjGOs4obCyJHHqfI1dQy4eeLtjJBKt0HTh5TuhD/MTzuRU5UW+r90x6TatsCErhDpB3qkvdaAqEl67ltEgMmSViKsaY7Bp5LmUHHVZCnUxQpo3sf3yRfR5lmErq6Cpa4A+Xwi7piBLMKfMwY5du6gN78PWuwNb93YcHW/h8ndxkvJKQrtlUnYGaL5CX6d7jjrhUScQCPLBV4If58/h9+DAz0p5M01GJUfJm9hnVLJKfocOw8tB8nZWypupknrGbCutSCAQCHIi2cFDVdKvFg1ZZWDeKdiWrGVPuIQFD3w4tZhE2Vw47SZQNNC9ePv99Hamet2V22U+eaidH7zo4+6NfkJjXMrhiEFEihmu0kiYbL+jnvMCX+Mn+i3Um5wjafoXkzCKItT5DryIQX+A8s33FrxvgSBbdqy+kXnPXwPA+w+s4ZktEu2DkxOMLjyqkX3dk1yTjhEKq8oSX1/byIm1Pj7/+MDk+pkk/Tj5U/gEAG5U/w9Vmvhck1zAqBgIoU5QEKo90TCIYDhCtddGny+ILxjBbYteBIasYXgbCA0yMgmketRJ5FKeIf7VhjyO+7AkEbBXMOipZ7D2iOEXRfA3b6Z+4A1Cu16iTallafeTKFJ2F24+iknMhJ1WxQITo0AgmB78J7ycW0Ln8JbRSD9Rjx8/Oo9HVgLwdrgRgEciw/N+OBp6phHiFu1WDpc3UyqlGp5WMOAEAiuiKhLVXhttshKt2ppBfINUjzpNHjs7uazbKfXMJrzmq6hPfgvCcfaQrCW0U+7UaeoeIt2lunaexhO7grzaOvbGYNiAUNwOc0yoMwx4xVjM6f5vc47yLF/TfjtmO7kw/YtJAEUIfR087it0NG1FOnY9Xc1bqWt5kv5AmMp3/4AUMn9jXSCYCIY0ul49orGM3y/1cNI9YxToKRRZFJlYUqHwyw8u4OXtTfzsleg1Nb/CzvaOwofF/il8An8JH8ciaR/nKM/wCfX+nNsQoa+CGYemyNSVOJAliS1t/TT3+ChxDBtXI/HwIUKqG4fkA6LHNDnqXpsTcecbskrOxWkkmUHvfHpmL6V+6cl00cCb295H46afUupvGvfl+fCosxGc1jutEqDkIZREIBDMLO4MreUv4ePYaMzP+bVBVIKoXBr8IjpBnrZdSa3UlXCOFQw4gcCKaIpMjddOc8kc5MHuMc9N9qhT5PQSeNgwkGXQFKh022DRSaCo8MwPYGjYoy2NjSghETGMlEOSJPGloxx86qEBuv2ZF57hCIRJFepif7vw8svwabwQWcJ3tV+wXN415vvNhuleNAyM5FK7he3dXkLYVsLQ6qvobtqK8p6r6X/x19S88xuCqz6Lf++ryMeup6tpM81SLVveepF1u79StPEKZhjxc9Wwk8n/njyHP7+8j00dua2PPrNmIQ1ljiy7NaeEq9eucN4yOyvmNVAdaWb+vMWsvPmVomxthlF4x5jDt0Mf4fnIMj6oPMXpyotZv16EvgpmLDVeOy6byvb2fvZ1DeLQR3+Khu6it+IQjM59QAeQWgE2O+ImHcmcn3rjIWvoqqjisTff4fE9BrdpP8x4rkMyvwqOTQpN69BXRI46gUAwQbZHavlV+FSejyxjmzHLlDYDaBzjvwUHfp60rUcniFcaKupCUyCYCpRUNdA0NEiwd3fGxYaWHPoqSykSVShioNkkXHpSK5UL4ZTvwl8viz6WEhvTFZlSh8reLh8ue6oRWemQuWa1g//3ZOboh7BhpPeoSzrvTWM+pwdu5Br1d3xyAp4bCeNmutt5WKuYhCTTX72SgeqV1Mw7kE7vCirsJYTtZSytn021zU/voXfj2/4crooGBvdt5IG3u1gpb2GFvLPYoxdMO+LmseEIs7NWVHJceTcv9lby4o4O/v722Kk5Ynz8mHmTD3lNGd741WBVWWLNolL27mwF4AcnOrn1tQg7OotRcCLKvyOH8u/IoWw1/swHlKdpkPaP+xoh1AlmNG6byrI6Lx6bSsdAIGHH01B0FEcpMaHONkboRDZMyKMuE5LMIUsPoG/efD7wyhKc+Pnm0A00yPtR85xfbbqHvoocdQKBIBcihsSLxhKuDFxBJ14CaOO/KEfCKPTjZJX/pxwpv8Mf9BsmlfdEIJgJzKty47UvY+ceJ+1BnXRZhlNy1KUR6gzDoNxpwyWNl8IksTFJgiqPnc6BzDbTYbUqX1ipsadf4s/vpm6uhiNRoTBGfOhrOm4MXcDvwu/Db2icpLzMt7Q7xx5zGqZ9jjqYcsUkQrNW0SNVoNYvpLv0UGoOqOGf725j7uZ1uKXiiQ+CaUj8YjhJDDtyXgXzZ1WzdG43G3Z28tjbbRmb+cL7FuVnfFmEwCZzYLXKfesWsvrHr+Av8hLvh6EP8sPQB3jL9nFckn/Mc6UsU13lEyHUCYqKqsjMq3JTVxpGkaN5TZThHCVanDinqwqojmEVf/T1kYhB2gQkSRjjGXgTYHGljU+dtgrXUBMn/O2H2PHzzeonqZe7Oab776b3B8Ohr9N8p1V41AkEgvHYHJnFm8Y8rgleih8NzNuKyUgYhe2ROr4evJhD60pZm/ceBYKpTYXHTqhhLu27u9N6ialJC6Hkqq8ANk2h0qOTJlVkIlJqhUSPXaXKY6NzMHOEwzGzVLwOLYNQZyQUm0gOfU0zCHYbNQD8NnwSXYaHj6kPcbi8eZzBjxINfTU/IsMqSIYBkalt5x05x8Nc2cVF7b+lsv9dfhESobGCyREuncu++edhkJi2KRlJgnNXNnDMgkrqSx3s2D/A7DInL+/q4t3WvpHzTlxSk1P/kjRG5dd0ZPCsG6uNH52g8qnHrbCGlVjl/ykVUi9P2dZnPMsKKU6EUCewBHYtKqTVeO0EQhEq3HpCuIGmaaA7oyr+sLuqKku4NZVAulrQhgEJk535XhYxFleoXLaqml+92MYX29aiyxEulLx8Xr2PEpMLSsyEHHWqBSZGgUBgTR4PH8p2o44bQhcWpf9Wyrk7vBbVaxNCnUCQBZVuG1Uene7+EIarJmFhl03V1xK7RqlDh3RCXfzpaYQ6gGqPjWA4Mm6e4wo7JOc8DxkQihOVMoW+ZuL+yFHcHziK+/Vrss5fp037FCdAge28rgVnmt6mIkv834eX09ls5/U932HHu69yVr+oKCuYGD0XPET/jo3Y+veNPpnkZDJafzo6l1353sXs6x5iVqmDLW19nHfHfws0WibkWdfolTi0SuLV9uJ7qvXjpN9w8trh32PWwJtUvf3rlHNE6KtAkAZdlVleX8KO9oGE5+KRIiHK7CoVdaX4/AHsfd1EwlF/WpdNoaM/Qvz0Nm7V10ly6tIyGrUevr8hRI8PfsWp/DV8DMfLbyAT4cvaPXgZwD5Jkc0lTe/KVBKGJXYwBAKBtbg1dBadhoc7w6cWeygCgSAHFFlidpmTQMjA8HhR8VPq1PD3Jgp1sjRaNEyVJUqcGpqm4vE403rapZBBiHPoCguq3AwExxa/njgHNg2U8uG/d488F44YhOM96oYXbrmmqDwncB21Uie3aT9m2TiCnU5o+heTiEyPFCfS8G9u9qqzeEs5gM8+W8UyeRefUv9Z5JEJpizJoa9ZzjXO5ByehSKNZ50xxgTZ6Rs99q0TPGxs9XPv28XzIG6vW4NDWsLbb77KYfKWhFB2IdQJBBnQVZnFNZ64x6NCm2HzEvA0YOhDaKqCJqkwIBE0oMKj47E5kPw2BgdHJzuHTcdQJPJp+yyvVPjxWXO44aGtbOk26MLL3yLHAvAX/3HYCLJY2su5ylN8VH10Qn3ko5KslZBEMQmBQBDH5YEr6TC8vGQsKfZQBALBBKlw2xgKhrGpMlpEpsyps18GLW5NGu9MpyoSHocerexqHysiIqFEYuazstD5bApUOCQcmsRQMLpAS86nlKtHXQw/OruMWr4evJhD5K18Rft9xnPtBNCk6SFkZUKaYjnqsuGIeg3ttI/w3Lt7uHzbAj6v3sdSeU/e+vOfeQfNAwYlsw9Ee+hq3M3P5a0vQeFICX3NYSpwaApDwYnNHRITrPyao2fdrtHoXN6/yMGqWon3HbqYp1/fzG/eKpJgJ0l8NPhlyujjVfvlI087lOLPU5nvagJBkXHYRsU5j03FrstUe23YvGV4FxyJMnc1eEcr+2myTJXbhl1TqC914HGMGndOux1dUyhz6uiaRJlTR5ZiOe7Mo8qtcdMJNv7fQYOU2+OPSPjR2WjM539DH2OJ704eCx+ac/ueae5RB4hiEgLBDKfJKOdE/00c5/8hD0WOtKZIV/yNVoFgyqDIEo0VLmxqYnRDvEddchhszshjN6ArMjZVxpe0kFX93Wj9+5CQMRSNH5xSz+dXpE8yHvOui0yw6vNLxhJ+EX7/mOe4pn1xAmPKFZPIlvcuLmO2V+WhyJFcFryaUNVy0/v474n30H72vUTmrSHonoXhKKftoE8SnHUUEcU+fgMCixPvUZffaLBicFRt9P1dtFwfeW7l7BI+eqCd2z64kE8daivsgKTR/+nCywf8X+dzgU8D4M5f1qysER51Asvi0OKEOruKU1dHXHujfzPfkGyqTEOZc/QJWUUDyl0aaAo1JXb6fCG6Bv2oirmXgU2ROKo6xPHzFW5/I8Lft6cadD5sXBa8Ck9wiDfsl2Xdthdzc95ZDQlRTEIgmInsiNTwirGYbwU/QhceClEcQiAQFAFFw3BVg7QHJUmoUxWJcpeeNlfduGTIURdDV2QqXDb2dg/gGl7+SOEAStiHr2YFkYbZBLojHF3WySx/kB+/mbpgNGtv9wP+r9MgtfNj/WcpxzzT3M7DAIzpvyG716ii99z76H/rfhpe+g7yYLsp7Q66GzHsvQnPhR0V9J15F127Xqdu/39xvvBDU/oSFIExqr7GQkozeQjnVAyiSHz2UIUP2xpZakutWLtqjpeFqg1vWTUbd7bwwPbJh8F9+ph6Tqrp46vPhXmzZfy59WXjANoppVWupsbtnXT/k0UIdQLLEi/UacoYBpikRPNdGIn5R+QxJjtNllhU46Z70MZQIISmyGiqTL8vhNtuzmXR6JX47nEyAc3Ng+/2pBw3kOnFxUrfbdRIXfxGv5EKqS9NS6PMiNBXSQh1AsFM4UHjaJ4KLeMf4aMZHGPzxWoIhzqBYIIoGnhrQdWRQ34g6ragSBKaIuN16eN6x40SZ+eNI9QBlDo1WnplgqEImiqjDu3H56xDdzeA3QtyP4buwqPLHFgWYmNXoj0Ys04mK9i9bBzAy8YBvOZfyEJpH7/UfzBybLrbeUARPOqKp2D4yw6g++Kn6dn+ArUtT9Gu1uJp24Ct4WDUjX9AMcIoAy3jttM763iCnoYxz4loLnwrPymEuinGrjU/IZbsyYibxwxJJRdrYzK/8pyrviYjawSd1RiGOmatmHK7xNJ5JXQ0ZRauzzukivdWddOHg67eAd7cPzFh//b3qhx+UA2dzf187/1zadm3i48/mFiVSEoT8LvbqOFjnjt44AOlE+rXTIRQJ7AsDj0uL91YE1XpHFBt0LsvUZBLSF2S+lNXZYlKtw5E3W8bK5zs3D9Any+ExySxDuCSI6s5e26Ql3q8/OK/qTfjDkroMEq4Lngx8+UmrlT/krEtj8lVZK2I8KgTCKY/3bNOoKvxFA5YdCq739jOQU0q/9019kaFQCCYHjhdXiobDmB35xsjz0069DWLZarbplLi0OkZ8FMp9xJRnfhcc9DjF8f2UgzdwzcPaeVjz1fT5UtT9dUkpX6XUUurUZbwnCJN720ARWZ6Fw1L9zOUJEKOSoaO+X/079jIQPVh1Mw7kI6aE6ionUfPjpeo9u1Ceus+nPvfSNMAtBzxJSSMrArmthz2BWpfEWLdVCA4axWBkrlxzySHvoZAVgk5qpFkdUwxTSqmS52iEXLWYAz1m1LUWZIkfnzWQjqatuKsmk9X8za+87JEODDI8/uyq4o9xyuNfCaaIlPvkXnk8gP55v1v88yesdswa46fLCJHncCy2OKstjF3L1UdSmdDw5HgronuqoZ8iZsQWYS3VrltzKt0A7C/3084bM5VKksSDR6Zy1fXcc+Z7ozn/SNyND8KfZDfhd7LK5GFac+Z7jut0WIS0z8kQiCYiYRVF/2HXY7vow/TdOCn8JUsoNRl48RGjVvOXsjdp7s5uN5V7GFmxTN7pnNVRoEgz0gSdfOXUd04mn9SV6TcQ17jT8/Co06SoNwO6sA+QooTf/lSwpon8SRZJeSqpcIhceVRJdjT2KJmruF82DjW/yPO8X9j3HNvDH6Yc/zf4NbQWSaOoLCoEshWWQVbAVkh5KjEv/w89h37bfrf9326552ecpohZ58wq2/Oe+m87GValnzUzJEKCkKaaLCRgg0WSJo2DoasEnZVp3WQmSgOTcamStxy9kKuP87JfeuWcer8sT+LKw9Ln9+v1qNzZN3o2DJpmxPNQ2o2wqNOYFnidwayul5ioRJlc8HfD4OdcY1l91OvdOvYdZmmLh9dAwEC4YhpDvOSJFHhkLnj3EX89eWdPJgh9v4roUsA+JJ6D0ulXaxRXh85ps6AsFDhUScQTC+eDS+np/Ekao66gEatC3f5fGh/LeEcVZao98jcce4Ctm7fQr0b3tpv8N0NYfZ0WS+5+pYuMU8JBJNBkhUa5i8BopEGNlVCkydhcWUh1BEJURLupLlyAc32RsqcXuhPLRwRtpUR0d0ssGl858xF2AeauPyhPvoDBv3+sGm56mLsNarZSzX3hE7gfPXJtOc8E17B7eEzAHgltJiT5JdZkseqonmlwDnqeue8D8/4p1mCwOIz6HAvRVl2JoP73kCVJIa6mgg5q9H792bfkOaic94Z9Mx+Hwc8KgS7KUP82jc5R11+OzZlvWvIGuEcqsBOhHnldi47xE5nyM4Lu1MjMf77uUPo3PPWpPqwioUnhDrBFCGHC95ZDvUHQzAuTDTmURcJga8bAoMQiYDNBfaSBAPPravMr3Qw6NbwG2BXFczM7Xv4bA/zFAfdYQfP7+rNeN73QucDBl83fk2p1M/Zyn/MG4RFkTBQLTM9CgSCydC1fB2fe7WWZyIH8bkSGzVZLKQ1RaLaJVNuhwMq4M+XHETT9jcZcs5iz97d/O8zQ/hN8nYWCATFRddGlyHqZEQ6GD+vnRGBvla0knqqnItpah7EE05vb4RtXsK6F4Lg0hUW2VXKHApdQ2G+9egeTpubnznoy6HLeMuYy1fV32KTRkOzVvtupY3ShHMvDvw/zlf+zRe0+/IylrxSwBx1hmJLCi2cGgQb30OvVo9UMof2fVuYaFr7iOogWH8EWtNLpo5PkC8y51cf95VToJiEWXh0ids+uJBNWzZz44sR3lMfZn/Ew/vqhtBzyKMgkT5kWHjUCQQ5kPP1Yi+B2gNHHzsqo3nsAr6oOFc2DzQHdO+G3iZAiobQqnaIhFD9/XhlNTrraRUEZYkK5wQrkWXg1nMWsHvXVj79mJ/m3kCGsySuC12MlwEOlbYyV241rX+rMq1zlwgE05yw5qb/zLvo6B8kUnsoz7y8cVLtaYqMW5dorHZSFVJ58tMH07J3Gx97cIjuoezylAgEAmuSUChMVicQ2iVl+P84DAMG90PQH93IrV5Cleamsj9M12CQtPqgJBPyziHUG8aQVfTSWr5xagXX/GMrG1sG2ZQ3U0ziN+GT+Xv4GCJI3KD9isfCh9FMRcqZrZTz4/AHuER9EO+Uyl9sFFaos5cUrC+r0nf67Qy8/Qh6706q3robOZyfNDotS9ZhW/Vx+na+RP07v0ZtfX38FwmSiFvwSqnhm2OtQq2i0xkAskbIYW4IbDpqXDK/+chiOpq2UlE/h46mraa0axGdTgh1gqnBhJTt+MnBWwc1y6NGoM076mHnqYOhTggOga8H/H3RibHu4FEhr78NLTxEpduGL2BeXiJZkvDoEh84qJJnN7fyWlvmUIBeXJwWuJEvqH/m48qD0zbZcNSjbmbmqOuvOAh3R/okwgLBVKDr48/T0d5MefUywqGteUmCa1Ojwt3DnziQzuat3Pyawpv7emgemJ5zokAwndHjhDpDViGHPFwpZPLY9fdE2521HFzRTVsFmF3upHOgm7CRfnkbctYQ9PswMIi4K5hf3cOXjtT55vMB8u3U20s0V+fng58Z99z3B27gbPnZqeNZZxgQKaCdZ5UVdzHRnPgqV9Azdy3djacwp8xJz1uPUBpsR97+GOElZxJsfRebqxSj+TXsPdty7iKke+madzo1rmr8ZQfQe9Zv6NvyNI1PjP8bFsQR/3tV9GGxSwNGNybz4TknSSY3HMurp6kFEewmSqa3HDY7v8EEseanJhAkMaHLJf7qUzTw1KSeo9lBqx99HA5Fd/rUaCVYnJUw1AX9raC7INA9kZGMycePrOXMhn5OuidzGCzAIHZuCF3ILaFzsBHkW9qveDsyh4vUR3k7MofjlDdNH1uhkZh5HnW+gz7KnrJVhJzV1JU4Cb/2e7zdm9BaXi320ASCcRkqX4bvzF/S2bqLMnsZhtIxejCNBWSW6aMpEqos8d33z6dlzxb+7x0b21u7xtzwEAgE1kKLi1KIGEbUVnPXQjjbTdG4OSbTisvfD9XLoGRWwtOVLhvVHjs79g+AxzZuT4assnh2LReGAtz9YkuW48s/u40afhz+AJoU4jPq34s9nOwooEddoYU6q3g1pUNCAknBKJtL3+wT0OsX0jH/XCrqFw57JEX/Nuz6OwN+P2789Mle3GqYwaFBKt69B7+3Eal8AVLrG2hD+4GoHbu39PDEzhSdgHcu3Rc9weC7j1G94x+o7RNbp9wXPpbO2uP4oHcTZdumyG98woxeG4ZqI+TyDnsah8b9KRe16msmRgphWEP4yhar6PtCqBNMCSZ9wWQbTpFcHVaWwVUR/QcwOIBsRIgY5odcXfmeWWza08YjO8Y2UPtw0gdcHvwCAD8OnwNIOII+yujnQ+qTHCO/yRHyZtPHmG9mUo4630EfpaVqNd4D1hDcsREJiJQvoHPJh5Fq59G98xUaNv0f+u6nij1UgSAtXeueYX93DxWOMiJ6R8rxeJMxn0aPpkh89aQ5tO3183x3OY9v2seze0VYrEBgdZT4uFODqK3mrRtOSZIjacLECA6BYot60iUhyxINZQ7a+1KLSaRF1gg4ajjnkDC/39BCsIimyj0XLeH837yT8NxNofO4JXQOm+0XF2lUOVBIoS7PKfinHFmIOUOrr6KraSty/UK6m7ai1C+ks2kr8tGfY39nOxWzDqBz95vU9b5Bm2M+JQuOIjBsxyYT8dQzUH80vYd9hK49bzJrx59h3ytZe+0t9/2SAeyc4iznhBVHIx3xCVrbmihpfh7bUZfRs+cN6nb9E9uWfxGYu4ZI9x7s3eaEP+aDwdVfpEOrZvbTX0x7PKI6Rh8oerwj3bgUW6azok44USziUCeEOoG1saky/lCE4xalGlnjE+9Rp5syHqN0DkPlQ8g9u0xpL56PHl5De10vT+wKEcpphoi+zyHsDGHnR6EP8hPOYr7UzKXKA3xInTpCjywZyNM0rDfG3aGTuC/8Hu469lyCmXIpyAphexn9p/+czj1vUTvwLn999N9cpD5W2MEKBGno+dDf2d/XT5mzCrp7Mp6XINTlf1gossSZKyo4wtvJM52lPL6piQ0twsNOILAq8R4giXOElLu6ny701dcDntpoypM0lLt0akvsOYU5KbLEb85wc9uLXTzVPIlQ3UmwuMrJ949TuGNjhC3do2MPoPFyZBEr5S1FGVd2FDZHnRDqRpmskGI4ykHqjP6/ase/4gJC2eYEkxUimovBE75JR9NWZjU/Rmjfq3j3jr1GGSAqXBkAkkSkfAHhnkG65p5KjaOMoHsWA+/7PvsWfpjSeSvpaNpK3eAWwpsfxjjmC/TueZMyt5OB1q2UDu3BP9CNd9ejhJzVUDYXuXUjSqhwOR59h16Cb4zPLKK56TvtZ/R2teNQbZC0jzDmdzjJ7zevOpusEbRXoQc689lLVmTzPkUxCYEgCx6/6nie39bBWYfOGv/kZOJns8nkPYlD1VTKGhbRZi8nMARGJELEVQP9pjSPLEmcvaKcP72R6p2SCyFUNhuz+VLoE3wzdBEXKI9zrvIUC+UJ7FIXkOkc9hqYczy/6T+MbzYdkf2LJAlDtRNY+gG+9uA83jYamSO1cbn6z/wNVCDIQOC0H7PXqKS08gAigfGN82LtrtpUifMOqeK48m7eGKzgwTf28ozwsJvy7Ny5k29+85s88cQTtLS0UF9fz4UXXshXvvIVdH10M2737t18+tOf5oknnsDhcHDBBRdw0003JZyzceNGPvOZz/Diiy9SXl7OJz/5Sb72ta9ZM3RohmDEL4xsbtCd4Ose+0UJtSSSvrtIOPrPU5dxMpIkiXmVLgYD2Qv6hqxSUl7LZ1bsp2lIY8s4Q8wXyytlblkjc+pfE6Mwzgt8jSp6eN7+2eIMbDwMA4xC5qibmnalqkiUu3R6TSxiZyV8Ky+no24r6qzDMHY8havtlYTjgXnv5UvvHjDyeEzZRJII20aLhgQWnkqHcxEVJY34B4IE6xfSp8+Ohvo2bSW89nt0tO6Kegbu2cTszXfT6VmMx1tBB26qhnbRhYuqpn+j7zLH2SEw5zh6XfOyyt0bnHsig/pWHClHop+ClAdJLe+/MkUj5KxGC46d5imfpK0blOGdW0Woy0euZ4HANBrKnJx7+OzEymBZE+9RZ44mrSkyNV47utNDEAVJ0Ym4azFMEgIBLjuqlqPqzLo0Jfpwcnv4DN4XuIluw2VSu/lBm4aFJALzT6blsC/Q//7becVx9KTa+n34vXwn9GG6z/8X5we+atIIBYKx2X34texc/W3Ci05NMIbHo1Chr5mwqRKnLCnny6sd/PyDi/jS4Qq1zsKPQ2AO77zzDpFIhNtvv5233nqLH/7wh/z85z/n2muvHTknHA5z+umnMzAwwLPPPss999zDfffdx1VXXTVyTm9vLyeddBL19fW89NJL3Hrrrdx0003cfPPNxXhbgmESpgibB0pm5yayJHvU+brBUQrO1Iqp8bhsKlVZ5KgbQY7mXAray/nOkX7muLN/aT740pqGhMchVJqp4LbQGeyMpMnNbAWmcY46s9AUmQqXjmby5oHVZD/fyk/SsvKqlOf7T/0pf4scO/LYMPN7VO0jofKGojPw3u/S33A8gSVnEfDOxXfoJQzWHE7/6bez9+DPY2QqVJMD/e//BV0HfGjS7YyFGd+tqZ9zctuyStBp3cIS8YjQV4GgkJgopAE0Vrio8tgJRSKUODT2yCoBexWaCZOPLEl89jCVWbtcEBzkvnezzJ+SBUf7b6Vc6uVZ25WmtWkmyjQS6kJVK+jzLsRY+x36mrYy9lIhNyLlC/lvpJe1/u8wp8zB1w/tZ393L4e89V0TexHMdAKNx7Nv8UV0VxyKrX9f7i5yFvFO0hWJI+s9zAnLrJkt0+NewF83bMfpKeMfG9voGEpvkZXYFYxIhN6ARSy2Gc4pp5zCKaecMvJ4/vz5vPvuu9x2223cdNNNADzyyCNs2rSJPXv2UF8fLRT1gx/8gHXr1nHDDTfg9Xr53e9+h8/n46677sJms7FixQo2b97MzTffzPr164VXnVXw1kPP3nFOylBMwohE89NVLck+R3GO+FwNrCjx8ehZEQ74bV66yIrzD61mTVUPt7yh8uA7XSPPfzf0Yb7Lh9lpv6B4g8tEIau+TgNCYYPWniEcQ35CtomLnFad2SK2ErrWPUvH/mbqO16kUy7BKntqvfXH0le7mgbasD37HfSB3CKTfMvPp1cpMU1wyYc33Ujbef6BGLJG0FkDE3K+yQ+SRFp3Tavo+9b5pAQCs0kIfTVXk7ZrCuUunWqPHZuqYMgaAWeNaYKgLEmctqSUDyyxm9JejEHs7DWqOd1/Ax8PXG1q22agTJPQ154576P33D+z/8BLE543+yb4rjGHFrmGnnmn01Z1NIt9d7PQ92u+GbyQBxquJGIvNbdDwYyha+E5DJx4Y7Ra1wQpdI66bFlc5eTSg+189thZ/OF/3Fy3djYfWpKax/R3Fy7htrXW9kKe6fT09FBeXj7y+Pnnn2fFihUjIh3A2rVr8fv9vPzyyyPnHH/88dhstoRzmpqa2LlzZ9p+/H4/vb29Cf8E5pKyMLK5o1518nCRiEgk+i8T8cUkhrrBXgquapNHOUpI8xDxzsFQVC5aWTjPtf89JjUgTpUlvnXqXP54Vqp7303Bc3k0vLIQQ8uS6Z2jbrJmXizkVY0LebVrMvVlDhpKHZS7bIlFWHIdn5S+j2JjOCsxVAe+Qy9hqOqQYg8nEVkhuOBkdp10BwPHfoWQrTTrlw6uvpqe+Wfkb2xxTGaTyawNqqmwz5XNGA2LWK1CqBPMDEwKfc2EJkv4Q+YbHrO9MsfNL2ES9+S0vGXM44nIYfwqdAobIovNbXwSqNPEo6574VkF6yu2uJGlaCLpECq/DJ/GtvL30P2x59n5vtsJzDkOX8n8go1JMHUZKF9Oz7l/Yf+Kj0cTR0+CBAeXSY4rX0iSxGENbi45yMbznz+UU+aNbrbIkmT63Cswj23btnHrrbdy+eWXjzzX0tJCTU2iaFJWVoau67S0tGQ8J/Y4dk4yN954IyUlJSP/Zs+ebeZbEZBhYVQxH8rnR8U63RXNWyenqe4K0dBXSQFfLwQGoawR1OwLiamKRLXXlpN4EfE2gKOc8w6r5Y8fP4QLl+Z3WXX56jqOm51+Q1iSJMrsMofUJ24u/CR8NpcFU0MLi4oIfc3ISMjr8M2n0mtjSZ2XJTUeZpc7OWR2KeVOfURss+tyzqKbpkjRPizk2TQeVvka/QddxI5TfkP3BQ/RcuiV+A84M7FSaxwD1StBn0BsvKwSclSnOH/EPoN8imEF+ZhlLfr+pOIU44kn00dpldDXqXOFCgSTIc/x8LPLncgyDPrNTViuyhJ3fGgxlx2cQ/6UHLg+9FEuCHwlL21PhFrH9BDqCmlRZOpJkyWQJILuWfS//xfsOf6H9HzgXvYe/PmcdgMFM4OI7mbvwZ9j96pvEK5aZkqbCQaQYVh+p7XUodLgFWZRofnGN76BJElj/tuwYUPCa5qamjjllFM499xzufTSZM/l1B+aYRgJzyefE8vLk8mr4JprrqGnp2fk3549eyb0XgWZSXvblJWo2OZtgMajYc5q8MYXF4sPfZWjoa6zVkL9weDOzRs4loM4J/FCc2DUHoRh87CwysU5C2WuW51BSDQBuzb+2O740GJ+/z9uLltVS6MV57NCF5Ow7DZRdthVGY9tdA2jyhKSFLXxKlw6Tk2hwqXj0JVxBTur34PHwlLfoiQRKZ1LX+P7GHjvd9l22j1pc5W3HfypibWvRPNg5hq2b5Wvd9wlUOz92TwFGc9YZLomcqkEnk9EjjrBzMDkHHXJVLhtNJa72NrSic1RhdE3uaqtyZw6X+efWwM09Zs/cQTQWOr7FXOlVh60XWN6+7ngVIRQl3tXsQVm4vNqsn0uK4RrDqZ3UKav7hhq6xsZ3PQApbqB+tqvsfXuLMh4Bdajv/ZIAmffRe/Ot0w19KbiokDK8P+C/PGZz3yG888/f8xz5s6dO/L/TU1NrFmzhtWrV3PHHXcknFdbW8sLL7yQ8FxXVxfBYHDEa662tjbFc66trQ0gxdMuhs1mSwiVFZjPmLdNWQY5vdfKCJIcLR6hFzi7VdxGsF2VOLJWYv3xtdz81D7Tu7Kl3NhTUWWJKqfMp46p50PzBjnpnmiY9rH+H7NAauJu3QK5bAvoUSdZxRUrz8SEu2CcYKcAXoc24nXXmaebsqpIlDk1en35q65u6a9RVuj6+PP07HmTeQ+viztQWCtiMl+vRH7z36Uj4m3AHyxyNZ4MWESnE0KdYBoTn6w2T8mE45lT4aTXF6S5R6ZCcUKgL5pjxQRcusQDH3Dy9ad6+ftO83drh7DzttHIxwNXE0HiLv37pveRFWPln5lCSAXMtRe7lySb72NuvEsShr2EwdojcNQvpKn8SIL9nfzpwUeZLzVzludtPEPmLzIE1iLoqGLgzDtpHwxRYUJVs1RGjT6L2Dy5I9S6vFNZWUllZWVW5+7bt481a9awcuVK7rzzTmQ58Xe7evVqbrjhBpqbm6mrqwOiBSZsNhsrV64cOefaa68lEAig6/rIOfX19QmCoGAKkKCsF9l7TNYI2qvQA51cuLKG91b3cvqf+kztwp6FUJeJNrman55cCv82bzwTwogUVnWxtMJjPvGCXaXXhtehoWkKTpeOarPT3mO+IKMpMmVOnQF//jbbrZIzLCO6m5CjEv8BZ2F792/R5/IkjOaj1boSO0PBcGHDoSUJQ7XHhfrmT5bKVM0202eZz+q3uWBBn2iBwCQiwdH/L0ApaE2RmV/pxqHr9JctwXDVJCY3niSSJHHhAfkVgJ6IHMaTkUM5wHcXi3y/5rbQGTwbXp7XPuORChoOkUdyvCFMqqsMjedqzw+WL+PO8Kl8LfRxHj3kJ/St/RHtKy4lYisxY5gCi9F75l3sXnMLkfKFeZsfp7rGNdXHP91oamrihBNOYPbs2dx00020t7fT0tKS4B138skns2zZMi666CJeffVVHn/8ca6++mouu+wyvF4vABdccAE2m41169bx5ptv8te//pVvf/vbouJrkZn0wqjY352iEXJWY0jR+VRXJI5qNDe0y65O/D2GIwbOkgr8i86IVl6MP6Y6CCxYy9/CR092iONT0EISMIW3iSZFTLDT4q6LErvKwmprejBNF0J1+Svcks9fsqrIVHsnV8BwwrPTBEN9J4JEduMUHnUCQb5xVUeTeEoK2LwF6bLEqTGv0sXuLplITSUMtEKPeRNPhR3eOyvC4/vyq7H7iXoZfDf0YTRCnB95gq3GLC5WHmHI08iZkceQfd3mdzxthLrCewYm75CqOWbBT1jjSBLBBafQ7ViIcszn6Ny3mbkvXo/csRk57DNhtIJi8f3ghzj/xCNwzTqKSNPWvPaVUEzCiP21iPUjmHI88sgjbN26la1bt9LQ0JBwLPa7UhSF+++/nyuuuIJjjjkGh8PBBRdcwE033TRybklJCY8++iif/vSnOfzwwykrK2P9+vWsX7++oO9HkMikZwabtyALvbEwZJWgc9Qz5MdnLeTtrVv43oYIm1oHJ91+NjnqMhEe/oAHTvo+3dtfYv5DFwHQe8b/0WaUUr7gCK787n+4KXQeB9rauI0bJj3etExzoa7YenEuWLH6a0amiOlgFHGLb8pvNMWKTBTAuWaEDJ+ZEOoEgnyjqPDFbdGLUC6c8+isMicgYXfYCdvcGH3pq8hNlELPw0FUfhM+GYDnI8t5j0vl+A9+k843H6Zyxz/4a88iDu15jEPkbZPuSyqCwGU2ofLF+EsXUqg9y9jNJPlnMQl7PhFFx1Dt9H7gXjqatjJ7x5/w97RQsusRkzoQFIIvBy9lc6SBV4zFnFXhxTX+SyZN/G/SIjbPuMTPr1Pd5p1urFu3jnXr1o173pw5c/jXv/415jkHHnggTz/9tEkjE5hBThq+JEE4RMIsY/OYItTFqr/2DAZyfq0ha1FvteHwMU2RmOWRqfeq5gh1kwh9jSdsL6P7/Pvp6mqn3O7BCIxWx91rVOGTqun8xBv0vfsks976OWr7JlP6BSCSvzxmaSnw5tBEuyuGaJac124iFWQLxVSxIRIpcI46E9uaSBXsSTPiWVf8bztikU1lIdQJpjfa5Nx4J4IiS8ypiCYzDoYjVJa46A3XFHaHII8YAJJEwD2L5gM/xYl1S/nHhrXUNPqxb7qHsm1/n3Db0yH0tfe8v0Hz9oL3mywqTCbNRFqBQopWkR089lo6mrYirfwYfS1bmfXc1ybekSDv+BefSa9Wzj0vn1jwvoXQJRAIsiWnHFTeOuhrgcHO0edkc1KNxKq/DvhD0cXaZOax4dxLXz+1hHMXvMMnHxqY1NiyKSaRLZHyBYR8BuAn+U0aAIpOoHQ+vef+ha43/kXVlj/ibX1x8h0XekN2imwAa4qM16VDjtEQpvQ9LNgxnMvOisKdNWSTHDHZCIppR5k858zsTVNkvA6NocDUX5eNRabPzCoedSJHnUCQRzRFprrUA+4600IyinG7/NhRs0YfJE1eHrvKKfN1bLMPZf+Bl9F36k/pbVgzsY4i0+CGUOCE1pk96ib+S8lmIylUeyiD1YfSednL7HzfHYRL5xPWRO4TqzHw3hvpXvSBIvUeV0zCIkZPbhR/cSIQzBRymiMcZVC1OLFgl8n3XpdNBWmCE1cshEtzEnLV4nLYmV86eSFxIqGvbj331yR/F35PI/sO+yI9595H7+z35txeAtPBzhuDXLUZK4afxoQ7p6ZQ4dJxxFWSLRbnHlxVtL4nylQ0eybrSWedX/HkEB51AsFMoxix9yZx8aoG7vxvtAroeHuTwXnvpcPWiF4+G2XLQ2hDbVn3Mx086grN6A5b4vO5brxP+OaquQi66+m54AE697xNTWAXXX6J6v0vsF+twdvyX6TDLiKw9Snk1Z+md/dreGcfxOCWJyljAGP7k7haX5po74IMdF/0BPu7OikvYiXEhBx1RRvF5JguRqdAYHVyniO8syAYlzPV5LnObVOxqQp9vgmEaiYkRx99/WOXH8g727dz7dM+en252zt2VY5vLivcNpX+QO5hvOkIVy2nY+UXkFdfjvL6b3G8O4EIikILdRb3qCumJ122FDtEtsIhcfRcLx1NieuJmMhpJc+/YmJGjrqYR7GlyGNV2Ewf2RFzzC0ENFGmnmIgEEwxRnYnNMUysffZ8qmDFRZX2hIXq1kOf/DYa+mYdy6L/n5G9h1a3KCyIrGvw8wcdRO91xuKRnDBKfibtjK4bC29OzbSV3c0NXMPpFOfQ4WrmkDJfAx3LYM1h+OoX0hHzfFUOVX69r5J3aZfEhnqRtGdBA0Z28A+pODk8/rMJPxrf0BzyInXU4/RV9zPbqqbzCJ0VyDIP+cdPpt7N+zhC+9bnNsLJQnK58U9Nif0NYZTV3DbVHqHgqa1We7UOKBcmfDcOJHQV49NoaUvt9eMZ+Yp9YfgKK2CFf8DG/8Imx/OofFCb8ha0+a2oifdeGQKkVUViXx+q9XOxN+9AngdGg5diYqcVgrZTazMlt/mTUCV8/E7NPmaK3DuuisOd7PuuIUQbi1If2MhhDqBIM/EdidG4vwn6VlXyMXj5QeptAXViXvGSBIDx3yZ8J4NeHc/Nv7pFjWorMyIUJfiUTd1jL9I6Vx8gyF6z72PjqYtVNQvoqNpGxW1jXQ0b2f2lt8xGAxTvvUvxR6qZempPxZfyUI8S84guGuz6e1PZN4RQpdAIBiPG885kCvWLKCxYiIlbvJX/UWSJKo8Nlp6za90fuQcD49u7s75dXZNHjeqIZn/PXkOl977LpcfPQvITrHLOupr/glQsQAqFsPb/4DuXVk0XmiPOmvalVPBk248RoQ7Ob9CXfI3qCgSZS49JcXLWEJiUTA7R93wJ5Gp1Yl0pyoy1V47WobE1kUpKpGJPESmpXtXXzraC24dekzrZsIIoU4gKDST3BkoxFR5z0VLUPv3AsGUPnNNsOk/eB0dVcdmJdQJcsfIkKNONde5oDBIctQrQpKjFoeig6wyuOab0QIW7/kSHe37qOt+le6gQs32vxIKDGHv3lLskRcNQ9borzuKHcfchD7YitdC6lhC1ddJ5mSfMLGQCdVBwFmHLBnpjbw0n5t1PkmBYPoiy9IERbrkhsy/6XnsGk7d/HavOn4WO9t72NKVm0FlVyVy9ZNeXuvi7x/wUN1QQ0dTjq512XLslXDgB+COE8Y/t8DCmdgAnrmMF7KbHDprvideFu3EXQ+GpBC2l4OcGDKfL7IR4VKcTYqJharCFgoh1AkEBSJlQoztDKiOnHYI8rV4/MOZbtyVjQQ6dzGvyklHcHR3xYy8B31rf0xgx3NUbL530m0JRhm5XSV9RbmGvprxHecbw16KoezHf+CFDDZtpfewD9OxbwtVDomOvZsp3/UAtlkHoW78A4rmQOkufPXdQhJ0VNH/oT+zv6cPw6RiNWYi5TkEJC1xwtxoMncddAdB96yoHqfZEs4xMsy9U+CSEAhmNvEXaR7ycbptKk7d/KWSXZP50hEq33lZpmsgQKcvu4WnTZVzFuoAlBy9tia8DP7kM9D6JvztUxNtIS9MtRDTqUjUy02z5OecydMuOXQ29ncog3dZ3pFVgs7qlNyW8Uhj2FK5fvKxyq5mYdo6Is853RNuG9b7uSYghDqBoECk7ErEdgZ0R047BGZNKref4uKTDw2MPK50yFSU2OgYSL1BJXjGTLC/4IK1dNrnUbL/VdRO80PzZiqxzbjkb20qhb5OCkkiUr4Qf88QLSs+Sc28A+moPZGKugV073yF8vIqhjY/jrt6PoFtT+F0ugk3vUHkiMvoa99NidNGf08HVdv+QjgURO/fW+x3lBV9p/2cFm0WFa4a6MmTl4SJGPn2aogJdHHCXLpk7kDq3CvyIAoEU588CHW6KlPu1HMWulJIs/B06xJfObGeSqOD//lzb3bN5GtVmdTshJ3evPXR0NajPgV7XoJ9GyY9NDOoKKb4MkPQZIkKpwXCTbMgPmS36Jh4TWcrlE0knLWgIbDZes7lWmTC6qpcGoRQJxAUGKvE+zd6Zb54QgPff3IvVxxdBwxkPDchR91k1tuSTO95f6Pv3SdpfOKKSTQkSCb5/jOZYhIWTemSG5JE2FZCpGQO/bOOw1a/kE5tFlL9QjqatlJRv5BBpQZH/UL6mraiH3kpHc3bqNbDdHZ3UL/9z/TplZTvepiuhhNx2u20VazEs+h4Ot59hrI9j1LW9gJKX1NB39bAe75Oq2MepXOPgqatowcs/qXlbXjJAt0YO9GZMGSVYBpjb+qZdALBDMbkYhIxFlS7kYD2Pv/EG4ktPLXofKVK0blGkiRcqoTHptDnt0Bo2TCTnq6PuxqaX4ffnmPGcEzBKsUbYoUQij2OfBETwfIljKrD+ekUi3x+yeGzSl+O7lo5GEcjqW4m+NZj60+HruTsSRdzNgmGI4Vbw45scGSw65Lm1Xx54BWT6feOBAKLY4V4/yevOIhg507OP7SKg9zdLFtUS2fztoznx+/STNozRpIJeOcweOTnCe97Bc++ZybX3hRiMps5spQ+P2Cmb8MiNszUYfjLCVceQCiwlYGTb6araSvy8dfQ2bwNqX4hgaatoGgEHVW0L74Aec1XGHrrfkrcbuRX78K5f2Pehjdw/Ddo1+rxLn4P4XiBrmBY9Ac1svM68ZwuhqQRctWAkrrQt+i7FggEkPfQV8g9bHTsxobnKzkw8pSuSPzx4mU8+MoWbtmQuXDFMbMKuWQzYWdFtU++DRPJt4CULZkKIUw38iWMjhThsMje5Mh4hsNmQwnv11rfsRmhrgVdw2Zr303j3HVCqBMIrMLwzoE6zo6AGdO+167SQVSAq3XL47pL5+NWE5y7hvaqY3GE+wn5+md0QYBsyPQdjIS+xq9XmNziYgp6h+ePsT4M3c1gzUoc9QvpcB1AtS2C/52HKN/3JOr+TaZ037T8E/TVHU3V4qMIFkWgM5cJm1HJuedGcnvmMemyuBAEgqlDHopJ5AtDVvHbq0byY84tt7OobOzx29XCzUemeEDrTjjx69C3D176PxMaNAereNZNd5ILOUylz3syv5H4y7TUmYXnZI52xlinT51POE9kmdsuPs/fWDn/rIAQ6gSCIpESAju8I6AakwivyIKzF+s5v8a00NckDMVG73l/Y3DDb2n4z1fMa3gaIksQHsOjLv5WM5UMoulEuGIxPfNk1NWfpmv3RqrDrfj3vErlprvGfW1EsSGH/QyVL8PRGRX5fMvPp3vOScU3I0wQrCYu0Gnpc8+NlYPOLPIUSicQCPLAVBLWFQ2/owY1PGrvHVAu89EVdp7aNciuvlSvr0I6YJlm5jWujn4v5Quh7S149TdmtTxhrOJZN1OYqGCXcF6BU3vEj7nSFfVAm0hF2PJsfmcju+3RFByZilvFk9G5wgJTYFGn4WnoWSeEOoGgSGRyH07eaU1mspPgJw+x5fya+JtCuvDLyeIrX0LYMwulb5/5jU8TMn3vo/bL6AnTPaTC8sgKEd1NsP4QuhwLUA7/GN3NW5j36KUjp+w7+no81fPoGAxS2rCc/R2tVFbWsn9/K4v+fsZwO9ar5DpRcrazZQ0ImhLaOlEkdfp8/gLBtCdPoa/xDAbCBHt9lJpYKTGGJEmsX+WiTOrjxxtT30v+9t8KYC+svBg2P2gJoS5GfG6xMqdGr6+w95eZRq6CnWYBIVWTJaq99qhynVQxNjvhLodrS9EIOmsmtcbL9FKr5EY3jfFy18kaQXsVeqBz3Kasvr9T/KtAIBAAoxOpouv4HTUYGRbpk5lTTlhQkmNIpDTpPrPBUGwMvOdrhGxlee5p6pJpsh7xqIv7kkzNqSOYNIa7hpCrlqHDPjHy3FD5UkL1RxByVmPYS0CSMWxe61sNEyRXnS5cNp+ApzEvY8kaSSNkryzuGAQCQXbk2QO21KExp8JBtcdG56A5kQ+GrBJyJYZqralPn/upkLpFXvxRShuhYlE+Wp4QMeHIqSmUOXUUk+690/MObh6xz90xBUNiIfF3U5E212D81ZPFeyuAzRdzDCmU+Jl3B8iEDdwMx53VGNLU90cTQp1AUGTiq/DUeO1ocvSyNGSViLPGtEqEJ83V+PZp8yb02vj7UL7mX8NZRfPhXyRUuSRPPUxtxvOoi5/MVSHUWROLV2Ydi4LphyNVXF1EbCUF6nSU+K9IUjXCzuqCj0EgEEyAPHvUzalwsWJWKXMrXegmLXgNWSOctOAsscH5C1PFuoLe1jPcqiaV301W4KTrwVkxubFNYaxWsbSYxAQvK3jOmUqCESGlVIVNuXZytAvH9N8r4Eav1b30DFkl6BzdBMn0KVtz9KNMs6tDIJh6ZNrpMGSNsDt1x2Ai8/DcchtXHWnHrk3skk+o+ppHrSHomc3QMV9msOqQ/HWSR1oP/vSYxydzQ8go1KVp3Ko3TkE85n9H08IZb7yd0jwzdaVUgWCGU6BiEiUOjRqvPa9JyG1p3opZHl/ZkGke1BQ5gxfRWMSd66yAE64BT/1khpcbVeNv/kYrsWaR+H+SjHx+0+JmbQ7Zir9TpwhI4tWT4oGXtNaTJLJ+X+Otvwr5yRTaSy9XDDkaSpy6hk6cua1+KVrz0xUIBKPEYvEn6MJ70lyNP1+8zLRwyEIsZPcd/U2CdYcXoCdz6Z13at7aHjf0Ne454VEnMBMzfk1T0ZlQGvmPQCCwPAXIURejrsSBx2FiWFW8nWdE0p8yFYtJpKN0Dpx2ExxwWj57GeWcX4x7iiZLVDinbjjmVGasUNjPHOEG4JOH2icoEluPmOAYQ5Jk0zwLrS46FYXhuTWbIh1WZNoIdTt37uSSSy5h3rx5OBwOFixYwNe//nUCgUDCebt37+aMM87A5XJRWVnJ5z73uZRzNm7cyPHHH4/D4WDWrFlcf/31GFNxlSGYHox4mOhIkdyS3a4/fhZfXGVHNnH2LsSlEPTMpu9D9+ErtU4+k2KT6TuMzU3xh4VQJ7AaBowtesVCXi1UQEMYvQLBFKKAQl2pU2NWqQOnbpIX37CdZ7iqAAkpjVhX0PmoEEueZWcWoBPAm7333rQNx5wCpBPsrl7t5fWrV7KiamqKLOku2tj7HCXHi00YJrkRW0NbyLbMhSn6y0/lnXfeIRKJcPvtt7Nw4ULefPNNLrvsMgYGBrjpppsACIfDnH766VRVVfHss8/S0dHBxRdfjGEY3HrrrQD09vZy0kknsWbNGl566SU2b97MunXrcLlcXHXVVcV8i4IZTsRTD217kLKY1B/+xArk3t1U1NfQ0dQ38U7T3BBMtd/GueE0H3ktdXsfwr7pXjN7nZJk0t7SedSJYhJTAGFsJVLE6q4jyBoRzQ2YkyheIBAUkAIKdZIkMbvcCcBQIH3xh4lguGsJlC5Ekvem9mlaL8kN59nOy8T8E+DSJ+CBq6HplUL0mDWTCbMUt/bJMSJkDduxTtsU83I0cismYe7vZYp8RoKsmTZC3SmnnMIpp5wy8nj+/Pm8++673HbbbSNC3SOPPMKmTZvYs2cP9fXRHZYf/OAHrFu3jhtuuAGv18vvfvc7fD4fd911FzabjRUrVrB582Zuvvlm1q9fX9BEjYKZia7KSEAgkrijariqCHjmIEktY77+rpNVqtw6Hb35GV8hnUtDzioGT7iOcOtbuDreLFzHFmS8YhKJQl3ehyOwJPm7P0225bDmiib1tbJzuqIR1jxAR7FHIhAIcqWAQl3ekCQC3kYi9n6gJ/lQwSjYNF29FNZcA8//FBxl8NZfC9XzmMTEoiFhTBWdZOFuupHLL8zAGDM3ppAoMmOMRG0kFWi0+Ic2rWegnp4eysvLRx4///zzrFixYkSkA1i7di1+v5+XX3555Jzjjz8em82WcE5TUxM7d+5M24/f76e3tzfhn0AwUao9NhrKHGnDrYPeORiaPeNr7zxZpcaV30mnGOvsPYdeRdOBVxShZ+uQ6Vsd8aiLO2Gq5/CYCApQ6sh/MujJkdtO63QirLow0oUeWDDkVSAQTEEKVEwi70gyhqM09ekCDqGg2X5cVfCBX8Ixn4cvbIIP3gmL1oKnroCDSM/UKWAgsCaF/d0k91aIyqzJfVhW+FI0Qq7h4hIWHWI6pq1Qt23bNm699VYuv/zykedaWlqoqalJOK+srAxd12lpacl4Tuxx7JxkbrzxRkpKSkb+zZ4928y3IphhyLLE/Co3NV5Hyu6IodjAUZ72dXedf0DeRToojlAX0dz0NKzBv7BAyYfzxGSqxGUMfU3jUTcTc9RFq7ZZPLfMFM11mle7q8hVXsdiXINTiIsCgXWYDh51w6SzFWbEbV21Qfk8OOtncPbt0aITRcSsnHVC8JuhZPN152hg5XJ2ISqzWr3663hY/Yq0/Kf6jW98I1pKd4x/GzZsSHhNU1MTp5xyCueeey6XXnppwrF0hrdhGAnPJ58zmqw9/dd5zTXX0NPTM/Jvz549E3qvAkEMu6awtM5DhVtPOSbLo5ft+5eUUO3W+dbJ9RzUUFKQsRVTaxh43/fYdeJPijeASWJMQuYc716eUExCGINTwDC26rjyQ/Iv35AUQo6qqS12WVBcFAhmLNI08agj/f1+Woa+joWqQ80KWPcAHHLBxNuRNXBPbjNosvbEdKlYKsiCHHPUgQTuWlRNp9prm1SOaas4s1li/siErBHRvcUeRdZYPkfdZz7zGc4///wxz5k7d+7I/zc1NbFmzRpWr17NHXfckXBebW0tL7zwQsJzXV1dBIPBEa+52traFM+5trY2gBRPuxg2my0hVFYgMAOPPWpUJCcq/sRx83nq3XbOPnQWZx06i+tLHezrHgIlH1NjkZIMZ0JWCXjnMrj6auwv/gQ57CvmaApKpl2VWCbDhBx1VrlbFxFNkfGOkWOm2EKekYdurfy1p8wbskrQWV3c4hFpiBfTJWaanCoQTGGmkUddOqZs6Otkb0xVB8CRn4D6lfDqb6D5tdxer2jgqINwMCrYac6chTuRs06QPblePBJ469CAao9K71Bme8gwGHMimEzUzoxB0QjbSoFWwNp2M0wBoa6yspLKysqszt23bx9r1qxh5cqV3HnnnQmeRwCrV6/mhhtuoLm5mbq6aO6DRx55BJvNxsqVK0fOufbaawkEAui6PnJOfX19giAoEBSLGq+duz52BA1lzqhAV2gsEL7nO/RS9lUfx6K/n1nsoYwweMRnxj1nMjfRcYtJxOeom4j4ZPW7lcmMJ+QJkpjs7yN+2pBVgo5qDNk6JsjM+vULBNOQIgl1hcgDBQUW6grYV9YsPwsaVsIdJ0zs9YoG3uG8d7oTAoM5N1HsDT7BFCMbuynunELNJfkgNvam7iGcujW9m6Wkv1OBabNCaWpq4oQTTmD27NncdNNNtLe309LSkuAdd/LJJ7Ns2TIuuugiXn31VR5//HGuvvpqLrvsMrzeqBvkBRdcgM1mY926dbz55pv89a9/5dvf/rao+CooGukm7mL+FiPjn1IYJIX+932fgZrDiz0SAAzdY3qb8UZhxhx1w39neo46s8ivIT5zi0kkhH0rGkFnTfriEhZC3PIFgimEXJwlTT5yNKWbegzdlVKxMH+9WZgP3gkHnTf5dpTcQ2LNylknmMbkGvoad35sLnHoSkbBzqp2SWzsy+tLmFXqKPZwskay0IZxOqw9uhx45JFH2Lp1K1u3bqWhoSHhWCzHnKIo3H///VxxxRUcc8wxOBwOLrjgAm66aTRZaUlJCY8++iif/vSnOfzwwykrK2P9+vWsX7++oO9HIIgRm/ySQ2CLhbkOdZO74wQWn0GHeymL/vZ+k8YzGczfg455fQV1ZVh8S+3DMKClZ4iyuN+HkuFcwfjEf+Zi5zyKGeEUhgGGrBK21QznpQtOfmACgUAQY5qHvhqaGzTncJXs/C7fku08BfBapar6vPdEC07IGux6Frp2TqydmIddOAiuGhjqyPqlwrNOkE8yrfvGteot8HPU1Sk2DwuhrjCsW7eOdevWjXvenDlz+Ne//jXmOQceeCBPP/20SSMTCMxhKrtE55veM+8msOVxKjf9umhjkExUMJONQE2Whndwo/6Mdn30RihLEktqPLTsHfUeziTqCbInLzlpck4yPL0wZI3IJJN65wMDY1SMjPuKRL4XgWAKMY2KSaRDkqS4Ktn5vb8ntz5SVd1K3vonXQc9eyYeChtD0aB0NmiO0fx1yX+T7lkiZ50gMzlem2O4yOW67os/S6wXs8TiH5GYYQSCKUI24RWjlRRN0uDTTGARC+o/oVmr6Fr8oeIOwjAvKDhdhbB4+9ipjS5IDGBWmYP5le641+d+57H4vcoyqIpEmVNDttKCZRjrjWjqYcHpTSAQZEORPepii+rJVG0ci4RmZY2gvQrk6S1OZsWlj8H7fzi5NmLedboz/d9MAp7FvXEERSabONUxNvknE1Zvdjj+tEVSo17KFkV8gwLBdCKhkuLMo/sjD7Pn2O8UexiZmYT9Pp7tX+Yc/c5jHnl2Xc46PKPUkfibydTGTA/50BSZMqc++cq6U+zjm+xwDYqbW3NCSFNwzALBTKXIQp2myFR77Kgm5MpLN+8kPKdohJzVGJIQiiibB/WH5rePDEKequtj20OyWpBQZYGVMD9yYnQTYGxPfyuZK1aOAov/nKSYl7JFETOHQDBdkLXRSoqyljfjwMoeJ5GSRnyVRcp9ZYJH3VgiWKYbcDoPR33YIw9NwRmXb82uy5Q5NXp9qeXfa7z2hMexXG3JbTh0JedqqTNd3BvFyldPfjGSdo1V2fq/CeuOTCAQpOCx7mLLDMR8NA6OchjqLGiXmmajomYOQ7IranOrDgzdC/iiJ4yEKo9hL8m5F7UQWJh4WyfHqq+ZiHnWtff5x8wTbqV0HVbLrz5VEUKdQDBdGK6kKEmYnMckceI3t5hEfui+6N/0b/sPDc99tWB9BuccB4HJtTEijqVxn8tk5qX7OpLzyMTyqaApaB4buiqPeMql87rz2FOTRo+0Iaf3rBvLiy/2vpLFPbMEPHU4f46iSKRKkIUnu/dlHYNqPCa8Sxu3UeDUlYSQMFWRqU4ShwUCgSBnPvJnGGiHigXFHolppJ1y83XLmDq3Iusx7GmnhiOU1zWiagphvQRoix6XNRjPKlE0cNRBYDDfoxVYkRwWVY0VTnqGMjsjWMmjzmpk+pit/pkJoU4gEOTEFNDpiHjqGKo8kIjuQQ70FaTPcOUSaNo65jmZ7gfZVFSTM9xN0nnUjdWOJktUOEc95Ub+xokopQ513KTRMeEu2dMu1t6QIqe8r2QxL/aaeI+/XEN2IU7gNIAcBMR8kUmYlPIQEpHYgcUsjjgPAYeumhISlm8SviGLfZwCgSANi04q9ghGMCvcK93ck8kGsD5TddzZk8l7SNV1qr0KqpJGrMvkSSc87AQZ8Ng1PHYt9Xc2PO9YEauFwFpjFNmTV6Gura2Nd999F0mSWLx4MdXV1k3WJxBMNaw2+VkOWaH7Y/9h8M1/0PCf/HrWRVRHVudlEjmzqaiW6VBySCHEqr4WhmRPu5ExKBKVXhtehzbyvuI9++LFwZTn04TsjvU3wXsvaTzJbcfaLPZ1Y4Ux5I2RvDzpFxrJc5eYx6yJsOEEgtzIZ7iXmCGtj6pIeJ2jS2tNkfE6NAgHR4tQuGpgqGPUky6ZZA+7mHCXZUXaEWRttC9BAcnzhiypNlTsd2ZFMd/qIbBWChdOR16Eut7eXj796U9zzz33EA5HvxhFUTjvvPP46U9/SklJST66FQhmBLEJ2qEreB2pOysJxHLVqY4J5qxLncBMDX3N9/yo6AxVHpjnTihIPHCm+2+6rgsp1GViRCCbxEeTScAbyxsw6zaTQngL4nEX91lUuG055fkrNjnZfyOh96MLCFmCmhIb5U4dddhwi1HjtRMMRywn2FndgMsXwoYTCKxH8hxsxIqHiUIFlkFTZLz2NMJZrBgFRHMp+nvGb0wZFuh0JziG51zdmfo3U8isomXfl8A8CuCWHxO/ku0mC+p0UxMLebTmZZVw6aWX8sILL/Cvf/2L7u5uenp6+Ne//sWGDRu47LLL8tGlQDBjyKlcd2zBrDtTFs4TZfIlEwqMpBR7BCOku4fG51cbi0yH0+lgVhDqpgox4c6pKVSM49WYL6ZrsY3492MYRCsiZpi3YvOaQ1csJ9jNNIQNJxAUl3SzX3IlWEOO5iVGc4rKolMJJcvQ1pi4l815FhIWBIVLEJS8HhRWU+6kFTe9dRkjQgpNXmb1+++/n4cffphjjz125Lm1a9fyi1/8glNOOSUfXQoEgmwwoxrsVEhSV3Am/qEk5Fcbg0wu7elepgihzjTSedyZ7cCfKaddrhT9Wx8OeVU1nWqvjEMfFcmzvUIy7RQXjDgX1Zm6Oy1sOIFgckw6NUmaySfjbd3U4mFTGAvO12m//3jvOjOItRcLrxWCnYUwp+qrYOaSF6GuoqIibWhESUkJZWVl+ehSIBBkw4QMuqRdXHNHND0oQOhrJiM9bTEJWWIy35TXNnVCMvNNurx61sy0UXxUXae8rhGHQ8ebJDrmeolYPa/JdEbYcALB5MjP/CXKvo6JBY3TrCJfzCIm2InqsdYhGxFOMu83YsUcdTFimxedA4FiD2VKkZcZ5Ktf/Srr16+nubl55LmWlha++MUv8rWvfS0fXQoEglyYhGddOmFIYK0cddoEd/F/cFIpXzpxNosrxI7sWESLf2gTyGs38d+JFcNjR7wN7Tql1bNx2O0Zw/INK66iBGkRNpxAYD2sM/ML8kIhQ1hFZdn8UYCN+0xIFo6m0RSZ+lIH9aUO7Lpc1BQn8WkELKxtAnnyqLvtttvYunUrjY2NzJkzB4Ddu3djs9lob2/n9ttvHzn3lVdeyccQBIIZQ2yXIjbxZbVbka1nXdoZTCy4U8n9M8lVeMlY9TXNcxMNff3AUieU1EPPngm9fqagyRIVzszVaTN+p5Mw4MwKjzWD2G/XoSvRsG27A6e3ouBjELns8oOw4QQC63HgrOIUcck2j64gSnIuwawxKyQ2XvALBzOf4xDed/mhiEJd0XrODi2ukJhTV0XERBbkRag766yz8tGsQCBIQ/zEV+2R6B0KZf/iCXjWmbZZZPU7Sp4ZyU2XpaiWi41cjIIIM5l04bGQmt/OzIVOOqE33zuDKQJdDr+zic4bmQQ5TZHHr3o9AQpQsM3yCBtOIDCHiW4oJJ99z2VH4bIVp1hEtnl0M1KoeXSGztcpJAt+wnPOWsS8GQWWQGJyqYLyTV5m/a9//ev5aFYgEJjNBHLWWXc6Kx5Slh/KZOzIXHZphZeRNUgV8BKPTyactZAedjUeGz6/PPp+YgJdAcJnCp2rLl5QlGboyk/YcAKBOUx0/kq+3S+u8bCve8jEkQlmBCJvnfWIeTPmgZm6uTidMdXCf/HFFwmHR29GRtIWut/v549//KOZXQoEAjMYy7MuaeYvYvoFCxPJew+5OMmpwqNuShATvjJ5QEoylDk15CJ9nzEhscylM6fcmXpCbBGQhVCXbA9MZCz5DHUVBq6w4QQCq5PVPDhcfXsiOYinNMI2FViBYuaoK1rPU4OYnSelec6qmCrUrV69mo6OjpHHJSUlbN++feRxd3c3H/7wh83sUiAQmMGIZ10WC+4CDGfKUYAPRQh105+YMBZDkSQqPTYq3YUtIhEf4ppWSJyAJ91kL5GYZ0ohq+hJ0swyfIUNJxBYg0zzTlbzYA72nEAgMBuxShKYh6kWb/Lua7od9MnuqgsEgswkF5bIeXGf4lmX+npxBacj86cSn6fMrskJz+dCLpO1CH2dmoyElg4jSdJI4QotKe9dPr9jTZHH9PTLxZMuhlm3flFEIn9MJRvO7/dzyCGHIEkSr732WsKx3bt3c8YZZ+ByuaisrORzn/scgUBikaWNGzdy/PHH43A4mDVrFtdff71l3ptg+mHpecvqLiWTRQiWowUmNKfIWZdvxH1kSpFx9itkFeYxKLhf9ISr4QgEgnGZdEWdLHLWiXtQKlIaoS4l8b6mYNeUkeO5FnzIZu48dp6XF3f3cvLiMgg059S+oADkePGkW9Ml54mL/c4GjcnfWxXA69CsuZgcJn6OyzfW/RSKh1VsuC996UvU19fz+uuvJzwfDoc5/fTTqaqq4tlnn6Wjo4OLL74YwzC49dZbAejt7eWkk05izZo1vPTSS2zevJl169bhcrm46qqrivF2BNMcs3NtxoS/zoFA5pMmUCxsSpNpairwQtsaM2QS8QUm9DRpLLKlAHlpBRPHKvfnaYFZVZgnyQyZvQUCQU7EDDw6Ug4JnS6VlkOvJOYHNZnKmGORTTO/+cgSAp17sDlUGMN+F0wfYsJdy+DkHORVRaLSa8Pr0DKLyJMw0g0Lzxxi82Fq8eCDD/LII49w33338eCDDyYce+SRR9i0aRN79uyhvr4egB/84AesW7eOG264Aa/Xy+9+9zt8Ph933XUXNpuNFStWsHnzZm6++WbWr18vFjuCojPeb1BTZKo9dnqHQplPmkCxMIFgTGKFEERxitwpgMgp7ly5Y/XbvelC3aZNm2hpaQGiIRLvvPMO/f39AOzfv9/s7gQCQT6IGXi+HiBxB1gsalPRlp2GXZfHFegmcz9Ibu6cJQ7+8s4QHz1odHdUkiRsqsXvOoK8UOXRCQXUCYfGxqrIjqmnTaJa2VScN2aiYGN1G661tZXLLruMv/3tbzidqZ4hzz//PCtWrBgR6QDWrl2L3+/n5ZdfZs2aNTz//PMcf/zx2Gy2hHOuueYadu7cybx581La9fv9+P3+kce9vb0mvzPBTCDmCecPju1ZN/NmHhOYgveYopMcEpuP0FjhhRclj9VeY0w1k2XS6ZpmAKYLde9973sT8ny8//3vB6IGr2EYM9LwFQgE6Zg+c0HFcGir00QPumQ+cqCTh7b5OLwu6rt344mlnHfkXA7zdOelP0EeyKNaVe22QdgOwx52QV3JSrDLStgzwdDO1zu3dO6nKYiVbTjDMFi3bh2XX345hx9+ODt37kw5p6WlhZqamoTnysrK0HV9RIBsaWlh7ty5CefEXtPS0pJWqLvxxhu57rrrzHkjghlLLAS2qXto0m2JuU8wadKFxOpOcz3mZpwXnlCMs2XS6ZpMQFVkSl3WDTA1dWQ7duwwszmBQDBJJm/IiWISVuG4OXae/szB1BptANhUiVWNXujpKfLIBFYkFhI7lKY6YKy4SdYh2ibsBOdLozQ791NyQYGZtLdYLBvuG9/4xrgi2EsvvcRzzz1Hb28v11xzzZjnphMTk0XG5HNi33smIfKaa65h/fr1I497e3uZPXv2mOMQCCZMFvOO2XNf/ijQJDqD5uqCI7zipgSSuAjGIL0RqipSwfIeTwRThbrGxkYzmxMIBJPENENOHr05T8UQtqIgm19la06ZHXrEjVgwOQrhAZqKmDisTrFsuM985jOcf/75Y54zd+5cvvWtb/Hf//43IWQV4PDDD+cjH/kId999N7W1tbzwwgsJx7u6uggGgyNec7W1tSPedTHa2qIbIMneeDFsNltKvwLBZIgYEIlE0h4r7IJb2BSCcUjerLNIRUxLUsxF0jS5lPPpLZy8F2d1cTMvvn5btmzhueeeo6WlBUmSqKmp4eijj2bRokX56E4gEOSbuJuxWG6PQ0yg053gKIk+pzshHATdBQwUdXiCmUUstHVCiF30GUmhbbjKykoqKyvHPe+WW27hW9/61sjjpqYm1q5dy7333suqVasAWL16NTfccAPNzc3U1UUXlo888gg2m42VK1eOnHPttdcSCATQdX3knPr6+pSQWIEgH5S7dGaXOdnTNflwwJFFLf70J0yw+utE853OdGaEF3YsZHbGhLNOggLaUdPlp6cpMl6Hljdv4al0jZoq1PX09PDRj36Uf/7zn5SUlFBdXY1hGLS3t9Pb28sZZ5zBr3/9a7xer5ndCgSCcTBzd8JAytngm1FkChNUtGGhTjBzKbzMHQuBnRAmJj8WnrjWx+o23Jw5cxIeu91uABYsWEBDQwMAJ598MsuWLeOiiy7i+9//Pp2dnVx99dVcdtllI+O+4IILuO6661i3bh3XXnstW7Zs4dvf/jb/+7//K/IoCwqCXVNYWuelzKWjp0lPkAsjkRNDDAtyGhBXDXaC1V9HCgwVzOtaYBmy9ZgTnnVpSLrOClBEYrpQjLybybf8I+eWF6zvbJjc3SGJz372s+zYsYPnn3+erq4u3n33XTZv3kxXVxfPPfccO3bs4LOf/ayZXQoEgiyIGXIOXclpEjRsHgKehsTnkMVNeYIkfOriMxRYlTzsAOdbqDOrethM1hOngw2nKAr3338/drudY445hg996EOcddZZ3HTTTSPnlJSU8Oijj7J3714OP/xwrrjiCtavX5+Qg04gyDeKLDGr1EGVZ/yQ6qwWsCOCnLAtBJMk5jE3XuqW+PNcNaCITfxiMtX3mWJrVW1486IYwt1Hj7ZWGjdTr6h//OMfPPzwwyMhCPGsWrWK22+/nVNOOcXMLgUCQQ7kmrMuUjafSFJ1soiFl7LJoRqTCvvLlpO/Nf45wyR8cjEDKGbgDHWYPjSBxbC6W5msgqMiMWzbJIw8zxtmVQ+z+DeUV6aaDTd37tyU4h8Q9bz717/+NeZrDzzwQJ5++ul8DU0gmBTJC+5YKJhAUFDiq8KOd17pbNAcpuZlnpIU0c6zer61XClEwRyrf2KmS99jhQ2IkAKBYBpgoZVssjAXC9WIVbocCd3IJ4vWQnAgdy+keAMoZuDkatiIHGICM5FV8OTn92R1jVIQRdhwAkHxycuVNsFcdQJBVsTbtLpzBuevK6JQJ27R0w5TQ1/POOMMLrvsMjZs2JBybMOGDVx++eX8z//8j5ldCgSCCTAZd+LYLciQFEKOqokbfVneUVRFosypIctSWmGuwqWPuEkXhdj7iBkpY4gcGd9x7LVyjgLJRF8nEBSYqarTTbcd6rEQNpxAMI3JGBo7c+a4QiDEkmGS89clPxYbzQILYPUNSFNXt7feeiv19fUceeSRlJeXs2TJEpYuXUp5eTmrVq2irq6OW265xcwuBQLBBEjOA5ALI54xskrQWT3pm2xMfFOSEhbHnnfoCmVOHUWSMgpzxa1OZu1JXmAlpqpcJZgJCBtOIJj6FCOv09hYZRyCgpK8eZ28sZycBy/5rxDwcsbimtOEMSsHcYz4CI/klqy2OWuq/3NpaSkPPvgg77zzDs8//zwtLS0A1NbWsnr1apYsWWJmdwKBYJJMxKBLyTU1TjhFprxxuhQYEeK8Lp3goEypU0M2IkBixbHxshOMVLac6tXJzNpxFDuVglzJ82+m0KGvE16szmAtVdhwAkFxSJ6vJrPgjuWzy2deJ4HANJJDZmN/w8GpKdyJHHWmY1YO4qlIXhIVLFmyRBh0AsEUIDb5BcORrBe1hgGqplNeM5uww43dYaO8rhG7EhXe7Lqc8DcmxKXkjQuEceg6yMPPyzLlTo2gP0Slp1jecRPAzPL0MYMlZqDEkvrnmusjVg5+xuYIsShFNeDG0aBiv5k8ke9iEslMZG7LlSkzR+WIsOEEgsJSiKTpI4hcdYJikq3NnCzgxQt3U6UA21QSGGcAaYVMi5txeZ+lX3vtNbZs2UJdXR3HHHOM5WOBBYKZSC5GogFouo262fNHnnPqKoQVnDVzQLfjdOmgKdG/OXq5aTJUu+0jAl46ihvqmoScZVWsXMi20pZAMFUokkaZzwVwUXNjFoGuri7++c9/8tGPfrTYQxEIpjmTt20yehXHctVpalSwkzoxFGXS/QkEWTFR+zZdATarh80KO14wSUy1Mi+44AL6+voA6O/vZ+3atRx22GFceOGFvOc97+HII4+ku7vbzC4FAkGBMTJ5BSXnm8jjjTIW6qplEAEtJeTFMel9ChHSOsWxYFxlgX5TxX7nsUVrci7MGNM1ZMRMdu/ezcc+9rFiD0MgmPaY4dMwbi7iYcEuXL0Cf8nCyXcoEBSK2HpDd6b/a1XhLs/MFF8oM3PWaRZbJyZjqlB37733MjQ0BMB1113Hli1b2LBhA36/nzfeeIOBgQGuv/56M7sUCAQmkrwDm25HdtzoPQtUIh1PyDOVQtwZY6ECyUbIDDE+BHkki2rFZpBR4C8QmiJT7bGjjuGpC8UXFItJb2/vmP9iG7ECgSA/xGyuZNMlr5uOqg1k4VFnFmLTxwIkC3mFFO6KbOvMBGKbEE5dnXBhxPi2rIypoa/xhviDDz7Id77zHQ477DAAVqxYwU033cSVV17JzTffbGa3AoHAJJLDxDIlJbaap9q0JzlUQITGCnJEkpLsR+GdmR0zaKorLS0dMz2JYRgifYlAkEdiNpiStKFQkMVk0uaqsPMmRqHzsQqyYKx8d6YLeEXMRSzuz1kR/w1ZXVg3PUdd7EfS2trKihUrEo4tX76cPXv2mN2lQCAoIAZZGo3jJozNfnJUFIkyl2ZRwzH7MeXtJmpmQQvBtCTll5fn4hHJWHnpYuWxFRKPx8NXvvIVVq1alfb4li1b+OQnP1ngUQkEMw8zLYWsK2An2Q8FiUgQCIpBtpVmNSd4ZkUvyGxFPeFRJzAR04W6r33tazidTmT5/7d35/FR1ff+x9+TbRISskDIBoEEomAIICaKEX/EsKpApdoiQilxQRGpSKBeQQW0AlbBBZVqrYJWr9h7gVal2oRFEEGhLJUdLUtEElFEgiJJSM7vD26mTPbAzJwzM6/n4zEPmHO+c873nDOZ+cznfJcAlZSUKD093bHu22+/VUREhKt3CcDFGgrsmtyFrfqL0AUzjwYH2NS6RfMnpvCIZiTf3Nb9z4XnGu7kvwEcsav1VfeAyMnJqXN9dHS06V2YAX8Q6MKbkp6YARv/YfUWOmhAnQm89v9Z31hSLyKhwYnw3M1f33l1/WYNCmjiWOUWP2kuTdT16dNHe/fulSSlp6frwIEDTuv//ve/q2vXrq7cJQA3qA7s6sLPNAur2bKOlnbWYuIfj+3cvq8mvCe85XPDnxNRI0eOdIwzXJeEhATNmDHDgzUC/FOgG1rfN3sGbJd9R3jql7DFf3HDt9TXKs/E8bn9tedrzc+2oECbkmLC1Co8RGcqz8Z0TQ3trHYOXZqo+/DDDxtcP2rUKGYMA7xcs3/HVieLXN+A1xqCQppc1O3jR9Q3lh0t7XAuE8Y3tEICrMldwPzU2LFjG1wfHx9Pog7wF143aZX53zGAbLSoM0t1jBcWEqjIsLOfW2cqnW9M2Gw2p3jUaom5mtzybnr99ddVVlZWa3m7du20atUqd+wSgFV5aFZJU/S6WwqLMbsW8BpmDjJs2q4lWeMnVPVd1+oxNquDOotP+uVx9cVw5eXlev31102oEeBfzv28fvOOuseMPF/NGrMuMtHUFkKA97FCtOOfasZ40jlxnpfeoHVLeHrrrbfqxIkTtZafPHmSFnWAnwoKbOJ4Ad7kusfNrkHT0AUWJkuopyu9Gc696xofGaqgBsaU8aFPqyYjhgOso3dabJPKNTUBV9eP2QYFBkvh8VKgj/aKAHwEs77WVv15V1+cZ/Uz5pZPXcMw6nyzHD58WFFRUe7YJQCLCw4IUOtwi04I4evO7QIbECSFtfbCbi24EGb91b2al6W/bTuiif0vMqkGtTU0BieI4QBv5LbPtcBgqWWCVHbibOs64gbAkvh1Vb/kVmE6/mOF2dVoNpcm6nr27CmbzSabzaZ+/fopKOg/m6+srNSBAwd07bXXunKXALwFrbrMFxgsRbaTwmPP/v/cmau4Lr6p+oeVrURmdMno2yVefbvEe3y/58sCQ+mZhhgO8B/NGrOzOn4LaSGFRVl03FtrpClo1OTnTAwieO/Vzx4UqISowFqT6Vi9FaJLE3XDhg2TJG3btk2DBg1SRESEY11ISIhSUlJ00003uXKXALxFzYkNrP3Z6JtqTjZx7jISdu5nRgAXGCyFJUra5vl9e4mU2HCd+Mn77rS6GjEcYA2e+PFY3QKvorKq8YRdXbGD5fjxXRZYCO9Dq/OmG7IuTdRVzwaWkpKiESNGyG63u3LzAEziU+PKmcjSZ5GEnW+p0UXJ0u89k0XYgxRhD6p1p9XfEMMB/qc6Yefvn3+ASzQ1C/T/JksfzZMGPOLCnRPpNSYo0KbIsP+kv6x+xtwymUTfvn31zTffOJ5v3LhR9913n/74xz+6Y3cA3KzJgw43haMLLAMTWxIzvbmRB2/j+fJsy3ArYjjAXGb8eHTbDVmLdy0DTNFvuvTQN1LbTJdtkj+1xgUHBiiqRYjZ1WgytyTqRo4cqdWrV0uSSkpK1L9/f23cuFHTpk3To48+6o5dAvAWjkSQlyfqhr1odg08i0GkvRoBXOOCAm1qYQ80uxqmI4YD/E+zbshacsxhvuTgZYJcmzDiL6D5asbGVjuHbknU7dixQ1dccYUk6S9/+Yu6deum9evX67//+7+1aNEid+wSADzr0lvMroFn0dLOO5BQPW/BgQFqEfKfGwihIQFqE+l/3T+J4QBzWf7GSnU8wOzxQA3mDYB2yxXtJUk920ebVgdvYHjRIHVuadJSUVHhGNtkxYoV+tnPfiZJ6tKli4qLi92xSwDeJtAuhYSbXQvUx5J3zL2cJ4IDx+QRzmyWu09ofS1CghTX0v8SdcRwgH+y2Zr5NVVzkjBTbxR5z49v+DATk0C5XeK0eso1ahsdZlodvE3N2DijbZRJNambW1rUde3aVS+++KI++ugjFRYW6tprr5UkHTlyRK1bt3bHLgF4m/h0KaaD2bVAfeq7Y04CzytZvoUGLIMYDvBPF/w1Qct7wFSpseEKCXJLescnVcfG/3yov1bk91FyqxbmVqgGt1zJ3//+93rppZd0zTXX6JZbblGPHj0kSe+8846jOwUA+B1vTJbUnJSAQPwCcMff6gyuETEcYDKzQgXb+d7RscQNvDrqHtnO47XolXr2ZkZYMOOd+idiCG8UG2FXWlxLs6tRi1u6vl5zzTX69ttvVVpaqpiYGMfyO++8Uy1aWCtTCQC4AIyJBl9CjE0MB5jsvBNmF7rf831h9Q08q7n7Y4/vMiEqVJ9O66eWoV4+YRoA07mtbWRgYKBTgCdJKSkpiouLc9cuAXij6juxAb5/9/H/pbUxuwquU33dQlrQwq6pvGgAW/g3YjjA//jcEAlh0absNj4y1GliIvgR4jy4kNs+Rf73f/9Xf/nLX1RUVKTy8nKndVu2bHHXbgF4m+o7sd8fMrsmbnf1RbH6y13ZSon1gVYp9d1Bp4WdJfna7y+4FzEcYJ7AAD6xm48ECYDmsfrNCbe0qJs/f75uvfVWxcXFaevWrbriiivUunVr7d+/X9ddd507dgkAXuGK1FaKaxlqdjVcr2YLu+AWUni8FMhdZSswqyuVt/PH80YMB5jrxsvaqnN8S439f6ke3a9bZgf3v49Q+DUSxnAdtyTqFixYoD/+8Y96/vnnFRISovvvv1+FhYW69957deLECXfsEgBgpromnYhOPjuYM63r3I+WjC5BiE0MB5itRUiQ/jGpjx4cnO7ZHXt1Us2rKw9fQddXyzv3Ernl5oQLuSVRV1RUpKuuukqSFBYWppMnT0qSRo8erbfeessduwTg7YJbSFVnzK4FXKk6eRfcgiSSu9VMlNZg7VAEVkIMB/gnl31POGaBpUU9AJwvtyTqEhISdOzYMUlShw4d9Mknn0iSDhw4IINMM4C6hEVLlSTqfFLNhJ2/Ju74/oMXIIYD/JPLevpXf+cHkKgDYF1WH93ELYm6vn376t1335Uk3X777Zo0aZIGDBigm2++WT//+c/dsUsA3i4kQrK5bSJqWEF18H7uOHauTtj5WxfQph6vxYMRWAcxHOCfrN4NDAD8iVtudfzxj39UVVWVJGncuHFq1aqV1q1bp6FDh+ruu+92xy4BeLuQcCk4TCr/weyaNK7jNWbXwDdUJ+4qK5yTTReSbAsMlsISpfJTrq2rS7igNVLNc1N9vHAJWowRwwH+yuqtSwDLI4awPOOcWNzqH3luSdQFBAQoIOA/LWOGDx+u4cOH6/jx43rrrbf061//2h27BeDNguySPdI7EnW/Wmp2DXxLzYRdSAspLKp2As+fBQQ7n5tmJiKtHozAOojhAP/k8u+JhO5n/z1T5uotAxZFog6u49F+ZkVFRbr11ls9uUsA3qRFK8nmBWOa0EXXPeqaOZbJKM6q69w045zYaCrRJDVvhnPW/oMYDvBtLv+eCAg8+wAAi3Ca9dXisbEX/CIG4DfsLc92f7U6i3+w+5yaLe68NnHnwjut1ecEAAAXILIBAOsgUQfAOqrHqQPqcm5yKqQFXWObgdwyAKBB7vqeqG4BXnrETTsALIIx6ryK1UNj+m8BsI6gUCk8VgoONbsm8AbVibsAL0nUEcBZHlcIgL9y249Wx9ANtA+BryOKsDpvCsVd+ok5f/78Btd/9dVXrtxdvcrKytSrVy/961//0tatW3XppZc61hUVFemee+7RqlWrFBYWppEjR2ru3LkKCQlxlNm+fbsmTJigjRs3qlWrVrrrrrv08MMPW74fM+D1bDapdaez/7fkrJ3wWxcyE60F8O2FxlglhgNgDn7nAPAnVv/Ic2mi7umnn260TPv27V25yzrdf//9SkpK0r/+9S+n5ZWVlRo8eLDatGmjdevW6dixYxozZowMw9Bzzz0nSSotLdWAAQOUm5urTZs2ad++fcrLy1N4eLgmT57s9roDsLjItmbXAGYIDJbCEkkgw2dZJYYDYA7P/Gj1ouYsAHyON30CuTRRd+DAAVdu7ry8//77Kigo0JIlS/T+++87rSsoKNCuXbv05ZdfKikpSZI0b9485eXladasWYqMjNSbb76p06dPa9GiRbLb7crIyNC+ffv01FNPKT8/n7tNgL+77gmzawA0G99d58efTpsVYjgA5nH7x11YK+n4IU/sCTCHN/WrhOVjY58ao+7rr7/W2LFj9ec//1ktWrSotX7Dhg3KyMhwJOkkadCgQSorK9PmzZsdZXJycmS3253KHDlyRAcPHqxzv2VlZSotLXV6AAA8JDBYCo9vePwbS3RdNS+As3YoYh3E2AD8ldt/tEbESaFRklHl3v0ApiGIgOu4ZVTP+sY5sdlsCg0NVVpamvr06aPAwECX7dMwDOXl5WncuHHKysqqM6lWUlKi+Ph4p2UxMTEKCQlRSUmJo0xKSopTmerXlJSUKDU1tdZ258yZo0ceecQ1BwIAaJ7AYCk6+eyMwfUl4qq7rrpzptjzTQbW9zpbgNSy7dksm5eOjQfvY0YMB8B8br+hE2SXopKl8pPu3hMAeD23JOqefvppffPNNzp16pRiYmJkGIa+//57tWjRQhERETp69Kg6duyo1atXKzk5ucFtzZw5s9Ek2KZNm7R+/XqVlpZq6tSpDZat626RYRhOy2uWMf7vFnt9d5qmTp2q/Px8x/PS0tJGjwsA4ELVs8o1tZw7EnaNjWNXX3Ot+l5nC5BiGBMMnuXKGA6A9/BIL7CW8dLJYg/sCABqM7yo64Rbur7Onj1bl19+uT7//HMdO3ZM3333nfbt26devXrp2WefVVFRkRISEjRp0qRGtzVhwgTt3r27wUdGRoZWrVqlTz75RHa7XUFBQUpLS5MkZWVlacyYMZKkhIQER8u5asePH1dFRYWj1VxdZY4ePSpJtVrjVbPb7YqMjHR6AABMFPh/rdSCW9SdkKtO2NW33goCaLEEz3NlDOcOy5cvV69evRQWFqbY2FjdeOONTuuLioo0dOhQhYeHKzY2Vvfee6/Ky8udymzfvl05OTkKCwtT27Zt9eijj3pV8A64hwcydSHhUquOkr3lf76nrfj9C5wPvkfgQm5pUffQQw9pyZIl6tSpk2NZWlqa5s6dq5tuukn79+/XE088oZtuuqnRbcXGxio2NrbRcvPnz9djjz3meH7kyBENGjRIb7/9tnr16iVJys7O1qxZs1RcXKzExLMtLwoKCmS325WZmekoM23aNJWXlyskJMRRJikpqVaXWACARZ3bwi6k9piltcq5s0vs+bK57l6axcfLtQyD8WVcGsO52pIlSzR27FjNnj1bffv2lWEY2r59u2N9ZWWlBg8erDZt2mjdunU6duyYxowZI8Mw9Nxzz0k62+thwIABys3N1aZNm7Rv3z7l5eUpPDxckydP9vgxAVbhse+Jc1u/RzKbOnwJMQRcxy2JuuLiYp05c6bW8jNnzjhaqyUlJenkSdeNUdC+vXP3oIiICElSp06d1K5dO0nSwIEDlZ6ertGjR+vJJ5/Ud999pylTpmjs2LGOVnAjR47UI488ory8PE2bNk2ff/65Zs+erenTp1t+ZhAAwHmyQsKuunWBW/D9haYxI4ZrijNnzmjixIl68skndfvttzuWd+7c2fH/goIC7dq1S19++aVj4rB58+YpLy9Ps2bNUmRkpN58802dPn1aixYtkt1uV0ZGhvbt26ennnpK+fn5xHrwW7zzgQtEizq4kFu6vubm5uquu+7S1q1bHcu2bt2qu+++W3379pV0tttBXRMzuFNgYKCWL1+u0NBQ9e7dW8OHD9ewYcM0d+5cR5moqCgVFhbq8OHDysrK0vjx45Wfn+80Bh3gj/jtAr9gZpfYpo6zB7epGWPb/PCnq1VjuC1btuirr75SQECAevbsqcTERF133XXauXOno8yGDRuUkZHhSNJJ0qBBg1RWVqbNmzc7yuTk5MhutzuVOXLkSJ0TkUlSWVmZSktLnR6AryHOA+DrvCmV6pYWda+88opGjx6tzMxMBQef/ZFz5swZ9evXT6+88oqksy3e5s2b547dS5JSUlLqHG+kffv2eu+99xp8bbdu3bR27Vp3VQ3wSjaZ+OEWECSFtbZWt0T4Nne0sDPxTis/wNBUVojh6rJ//35JZycZe+qpp5SSkqJ58+YpJydH+/btU6tWrVRSUlJrPOGYmBiFhIQ4WgOWlJTUGsqk+jUlJSV1JiDnzJnT6MRmgLfzxxsTAGBVbknUJSQkqLCwUHv27NG+fftkGIa6dOni1D0hNzfXHbsG4IsCgqSW7uoSCDSAVm7wM56O4WbOnNloEmzTpk2qqqqSJD344IOO8fEWLlyodu3a6X/+53901113SVKdXVcNw3BaXrNM9Y3d+rq9Tp061alnRWlpKTPeApZCkhFW4E3ttWB1bknUrVmzRjk5OerSpYu6dOnijl0A8LAAm01VZo+9YIUZwmia5N8Cg6XweOmnY+fxYhNb1Jm2Z3gbT8dwEyZM0IgRIxosk5KS4hgTLz093bHcbrerY8eOKioqknQ2yfjpp586vfb48eOqqKhwtJpLSEhwtK6rdvToUUmq1Rrv3P2c21UW8EXeHd6QIIEFmP07CT7FLWPUDRgwQO3bt9cDDzygHTt2uGMXADzMEgFcdeumABMTdR16m7dvmC8wWIpOliLbXfg4dgEWSDwDNXg6houNjXUkBet7hIaGKjMzU3a7XXv37nW8tqKiQgcPHlSHDh0kSdnZ2dqxY4eKi4sdZQoKCmS325WZmekos3btWpWXlzuVSUpKqtUlFvAnpoV5VrgJC8A/eFEu1S2JuiNHjuj+++/XRx99pO7du6t79+564okndPjwYXfsDoAHeHzsEisGbuFxUli02bWA2aoTxiEtLmziierteOA9bolEO7yCVWO4yMhIjRs3TjNmzFBBQYH27t2ru+++W5L0y1/+UpI0cOBApaena/To0dq6datWrlypKVOmaOzYsYqMjJQkjRw5Una7XXl5edqxY4eWLVum2bNnM+Mr/J5p738r3IQFXMKLskB+yvCia+SWRF1sbKwmTJigjz/+WP/+979188036/XXX1dKSopjxjAA3sXj8ZsVA7fgMLNrACtqasLt3C4RHk5CM0g4msrKMdyTTz6pESNGaPTo0br88st16NAhrVq1SjExMZKkwMBALV++XKGhoerdu7eGDx+uYcOGae7cuY5tREVFqbCwUIcPH1ZWVpbGjx+v/Px8pzHoAABotriuZtcAPsQtY9SdKzU1VQ888IB69Oihhx9+WGvWrHH3LgG4AQ0NgCZqSmtQJqiwpJqzxfv7557VYrjg4GDNnTvXKfFWU/v27fXee+81uJ1u3bpp7dq1rq4e4NVM/7y7oJ4UZlcekJR1m1Txo5SaY3ZN4APc0qKu2scff6zx48crMTFRI0eOVNeuXRsNngBYk6Va5FixWyxQrbqFXa0usc1sbu/CQYlN/wEGr0MMB/gX078nLqgnhfd0Z4MPCwySrp4ktb3M7JrAB7glUTdt2jSlpqYqNzdXhw4d0jPPPKOSkhK98cYbSkykFQHgjQLMDuDOZVa3WNOjWHiVmu9Tm1vvjcEF+KlHDAf4K0vdkAUAN/CmiXnd0vX1ww8/1JQpU3TzzTcrNjZWJ06c0KJFi/TKK69o27ZtqqysdMduAbgRg2xLumig2TWAN6puAdrcRJ0L/+b460VTEcMB/smnwrw7VpldAwC4IG5J1K1fv16StGrVKr366qtaunSpOnTooJtuukl/+tOf3LFLAG5myfjN011g+z/imf3At1S3rKNFHbwAMRzgnywT5wUGS+Hx0k/HmvGiGrUP4PsWgHdzeaLu8OHDWrRokRYuXKgffvhBw4cPV0VFhZYsWaL09HRX7w6Ah1jyTmt1AqT8lGf2F9LCM/sBXIwWsWgKYjjAf1nmeyIwWGqZIJWdMLsmAGAal95uuP7665Wenq6dO3dq/vz5OnLkiJ577jlX7gKASSwTwDUkgEkmAJw/bxq7xNWI4QD/Zqkor9k9Jvz4wxtAk3nTJ4VLW9QVFBTo3nvv1d13362LLrrIlZsGYDJvyNMpMFgK82ALO6A5/DkLBMsjhgP8nJXiPE/3mAAAi3Fpi7qPPvpIJ0+eVFZWlnr16qXnn39e33zzjSt3AcAkpsVvnh6HDnCbJibqki47+2+PES7bs1ck2mEqYjjAv3n314R31x4AanJpoi47O1svv/yyiouLddddd2nx4sVq27atqqqqVFhYqJMnT7pydwA8KMCsX/rVd1UbStSRzIMvub1AmrxXSurpsk1OyE2TJA3pnuiybcK3EMMB/s0rhjgBAD/hlilxWrRoodtuu03r1q3T9u3bNXnyZD3++OOKi4vTz372M3fsEoCbWTp+a0oy70Ix4ysuVFO7vlYPpO1CI65or9VTrtGzI1yX/PNFhleNXuIexHCAf7JkmMeNWAAu5E2j0Lh97urOnTvriSee0OHDh/XWW2+5e3cA3MaSIZzndPul2TUALkhqbLgCA/z87xjNQgwH+A9L3pCtvhEb0FiiruavbyseDAA0ndsTddUCAwM1bNgwvfPOO57aJQAX8vvf95aMYAHA/YjhAN9nI7kFwMd5U88JjyXqAHi3bm2jzK4CALhVzS4R5OcB+AtLf9412gXWypUHgOYLMrsCALzD73/RXc+v+kIjrkg2uyomIQjEhfKeu3gAAFhGdRfY8lNm1wQAPIJEHYAmiY2wa+bPuppdDQBwG1KpAPwVs74CgHXQ9RUAAE/wpqmmAAB+xSvSdMwCC+ACeFMoTqIOgO9xRyDHnWZcMC+KDgAAfsUrwpwmzwILAN6NRB0A30MgBwAA0GRekahrKp86GAD+iEQdAACAvKtLBAD4LbrAAjgP3hTmkagDgCbh7izgb2z83QPwE171eUfPCQA+jkQdAN9VfcfVVdsCLgTNtQAAFkVvUQA+z4ticRJ1AHxX9R1XV2jRyjXbAQAAsBjydABgHSTqAKAxPUaaXQP4BO+5i+e/uEYA/JQ3Nqmr7jnhjXUHgAaQqAOAxhAAAn7Bi3pEAIBLeWWk48qeEwBgISTqAAAAAMCP+dY9SZ86GAAu4k33Y0nUAQDgCTTXAgBYlHentry79gBQE4k6AAAAAPBjNt9qUgcAXo1EHQA0Jvses2sAn0CLOqtraqPHD6dc49Z6AICnkaYDAOsgUQcAjYnvanYNAFhEemKkUmLDza4GALgUDeoA+DpvGoWGRB0AAJ7gTdEBJElGHa0gE6JCTagJALiXzZvb1JFlBOBjSNQBAAA0Qf9L4jT7593MrgYAuJ4357q4EQbAxwSZXQEAAAArqKsF3bn+NOZyD9UEADzLm/N0tdDCDoCXo0UdAABAHby6KxgANAO5LQC+zvCi1rck6gCgIal9zK4BfIb3BAc4q7EWdgDgK7z6xkTNLGN0B3PqAcDSvCmqo+srANSn90Tp/002uxbwFV50Fw8A4F98pkVdRIIUGml2LQDggtCiDgDq0/VGKTTK7FoA8BByqQD8lVcn6s798I5MMq8eAOAiJOoAoD5eHbXCesgCWV1DV+jtO6/0WD0AwNO8uusrAPgYEnUAAACNiIsMNbsKAOA23JsE4Ou8qecEiToAAIA6BAX8J0xqFR5iYk0AAPUiywjAxzCZBAAAQB0CA2z6x319VFFZpaiwYLOrAwBuYyPZBQCWQYs6AKgXQStcyJva2/upui5R54SWymjLpDIAfNutV6VIkq5OizW3IueD71cAPoYWdQAAAADgx3K7xGndf+UqgfE4Afgob0rpk6gDAAAAAD/XLqaF2VU4P3TbBeBj6PoKAPUh8AMAAAAAeBCJOgCojy3Q7BoA8CDDqzpF+J99+/bphhtuUGxsrCIjI9W7d2+tXr3aqUxRUZGGDh2q8PBwxcbG6t5771V5eblTme3btysnJ0dhYWFq27atHn30URmMcQUAACyCrq8AUJcuQ6S4S8yuBXwJiQDgggwePFgXX3yxVq1apbCwMD3zzDMaMmSI/v3vfyshIUGVlZUaPHiw2rRpo3Xr1unYsWMaM2aMDMPQc889J0kqLS3VgAEDlJubq02bNmnfvn3Ky8tTeHi4Jk+ebPIRAgAAd/Gmm3K0qAOAuox4k66vgJ+56bJ2kqQuCS1Nrglq+vbbb/XFF1/ogQceUPfu3XXRRRfp8ccf16lTp7Rz505JUkFBgXbt2qU33nhDPXv2VP/+/TVv3jy9/PLLKi0tlSS9+eabOn36tBYtWqSMjAzdeOONmjZtmp566imvCuABAIDvIlEHAIBHkASwut5psVo1OUd/vae32VVBDa1bt9Yll1yi119/XT/++KPOnDmjl156SfHx8crMzJQkbdiwQRkZGUpKSnK8btCgQSorK9PmzZsdZXJycmS3253KHDlyRAcPHqxz32VlZSotLXV6AAAAuAuJOgAAgP/TsU2EQoMZn9JqbDabCgsLtXXrVrVs2VKhoaF6+umn9cEHHyg6OlqSVFJSovj4eKfXxcTEKCQkRCUlJfWWqX5eXaamOXPmKCoqyvFITk528dEBAAD8B4k6AAA8gW51QC0zZ86UzWZr8PHPf/5ThmFo/PjxiouL00cffaSNGzfqhhtu0JAhQ1RcXOzYnq2OIQsMw3BaXrNMdZfXul4rSVOnTtWJEyccjy+//NIVhw7AVfh+BeBjmEwCAAAAppgwYYJGjBjRYJmUlBStWrVK7733no4fP67IyEhJ0oIFC1RYWKjXXntNDzzwgBISEvTpp586vfb48eOqqKhwtJpLSEio1XLu6NGjklSrpV01u93u1FUWAADAnUjUAQAAwBSxsbGKjY1ttNypU6ckSQEBzp1BAgICVFVVJUnKzs7WrFmzVFxcrMTERElnJ5iw2+2Oceyys7M1bdo0lZeXKyQkxFEmKSlJKSkprjosAJ7E5F8AmsCbGt/S9RUAAI/wougAsJjs7GzFxMRozJgx+te//qV9+/bpt7/9rQ4cOKDBgwdLkgYOHKj09HSNHj1aW7du1cqVKzVlyhSNHTvW0Qpv5MiRstvtysvL044dO7Rs2TLNnj1b+fn59XZ9BeBN+K4FULeAAO/5nidRBwAAAEuLjY3VBx98oB9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      "text/plain": [
       "<Figure size 1500x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(nrows=2,ncols=2)\n",
    "fig.set_figwidth(15)\n",
    "fig.set_figheight(10)\n",
    "sns.lineplot(data=df, x=\"TotalItr\", y=\"EpRew\",hue='Method',ax=axs[0][0])\n",
    "sns.lineplot(data=df, x=\"TotalItr\", y=\"Avg100Ep\",hue=\"Method\",ax=axs[0][1])\n",
    "sns.lineplot(data=df, x=\"TotalItr\", y=\"AvgLast50Ep\",hue=\"Method\",ax=axs[1][0])\n",
    "sns.lineplot(data=df, x=\"TotalItr\", y=\"AvgLast10Ep\",hue=\"Method\",ax=axs[1][1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(50, 6)\n"
     ]
    },
    {
     "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>Trial</th>\n",
       "      <th>Time</th>\n",
       "      <th>Task</th>\n",
       "      <th>Int</th>\n",
       "      <th>EvalAvgRew</th>\n",
       "      <th>Method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>13-09-2023 00:37:51</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>5000</td>\n",
       "      <td>-0.002435</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>13-09-2023 03:59:29</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>10000</td>\n",
       "      <td>-0.000137</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>13-09-2023 07:23:37</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>15000</td>\n",
       "      <td>-0.000136</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>13-09-2023 10:50:36</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>20000</td>\n",
       "      <td>-0.000083</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>13-09-2023 14:16:39</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>25000</td>\n",
       "      <td>-0.000164</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Trial                 Time                      Task    Int  EvalAvgRew  \\\n",
       "0      1  13-09-2023 00:37:51  MountainCarContinuous-v0   5000   -0.002435   \n",
       "1      1  13-09-2023 03:59:29  MountainCarContinuous-v0  10000   -0.000137   \n",
       "2      1  13-09-2023 07:23:37  MountainCarContinuous-v0  15000   -0.000136   \n",
       "3      1  13-09-2023 10:50:36  MountainCarContinuous-v0  20000   -0.000083   \n",
       "4      1  13-09-2023 14:16:39  MountainCarContinuous-v0  25000   -0.000164   \n",
       "\n",
       "        Method  \n",
       "0  COMPER-DDPG  \n",
       "1  COMPER-DDPG  \n",
       "2  COMPER-DDPG  \n",
       "3  COMPER-DDPG  \n",
       "4  COMPER-DDPG  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path ='COMPER_DDPG/data_using_done/'+env+'/eval/progress.json'\n",
    "df_comper_eval = pd.read_json(path,lines=True)\n",
    "df_comper_eval[\"Method\"]=\"COMPER-DDPG\"\n",
    "print(df_comper_eval.shape)\n",
    "df_comper_eval.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(50, 6)\n"
     ]
    },
    {
     "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>Trial</th>\n",
       "      <th>Time</th>\n",
       "      <th>Task</th>\n",
       "      <th>Int</th>\n",
       "      <th>EvalAvgRew</th>\n",
       "      <th>Method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>03-10-2023 15:21:13</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>5000</td>\n",
       "      <td>-0.031264</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>03-10-2023 15:31:59</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>10000</td>\n",
       "      <td>-0.008570</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>03-10-2023 15:42:46</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>15000</td>\n",
       "      <td>-0.000978</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>03-10-2023 15:53:49</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>20000</td>\n",
       "      <td>-0.001195</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>03-10-2023 16:04:54</td>\n",
       "      <td>MountainCarContinuous-v0</td>\n",
       "      <td>25000</td>\n",
       "      <td>-0.000072</td>\n",
       "      <td>DDPG</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Trial                 Time                      Task    Int  EvalAvgRew  \\\n",
       "0      1  03-10-2023 15:21:13  MountainCarContinuous-v0   5000   -0.031264   \n",
       "1      1  03-10-2023 15:31:59  MountainCarContinuous-v0  10000   -0.008570   \n",
       "2      1  03-10-2023 15:42:46  MountainCarContinuous-v0  15000   -0.000978   \n",
       "3      1  03-10-2023 15:53:49  MountainCarContinuous-v0  20000   -0.001195   \n",
       "4      1  03-10-2023 16:04:54  MountainCarContinuous-v0  25000   -0.000072   \n",
       "\n",
       "  Method  \n",
       "0   DDPG  \n",
       "1   DDPG  \n",
       "2   DDPG  \n",
       "3   DDPG  \n",
       "4   DDPG  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path ='DPPG/data_using_done/'+env+'/eval/progress.json'\n",
    "df_ddpg_eval = pd.read_json(path,lines=True)\n",
    "df_ddpg_eval[\"Method\"]=\"DDPG\"\n",
    "print(df_ddpg_eval.shape)\n",
    "df_ddpg_eval.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_eval=pd.concat([df_comper_eval,df_ddpg_eval])\n",
    "df_eval.rename(columns = {'Int':'Itr'}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Itr', ylabel='EvalAvgRew'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lineplot(data=df_eval, x=\"Itr\", y=\"EvalAvgRew\",hue='Method')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## USING ROLLING AVERAGE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>TotalItr</th>\n",
       "      <th>EpRew</th>\n",
       "      <th>Method</th>\n",
       "      <th>EpRewRolling</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>20000</td>\n",
       "      <td>-270.931678</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-131.071602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>20200</td>\n",
       "      <td>-271.988001</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-133.779785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>20400</td>\n",
       "      <td>-272.833587</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-136.493311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>20600</td>\n",
       "      <td>-273.631443</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-139.208742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>20800</td>\n",
       "      <td>-275.745171</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-141.941359</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     TotalItr       EpRew       Method  EpRewRolling\n",
       "99      20000 -270.931678  COMPER-DDPG   -131.071602\n",
       "100     20200 -271.988001  COMPER-DDPG   -133.779785\n",
       "101     20400 -272.833587  COMPER-DDPG   -136.493311\n",
       "102     20600 -273.631443  COMPER-DDPG   -139.208742\n",
       "103     20800 -275.745171  COMPER-DDPG   -141.941359"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_comper_rolling_avg = pd.DataFrame(df_comper[[\"TotalItr\",\"EpRew\",\"Method\"]])\n",
    "df_comper_rolling_avg[\"EpRewRolling\"]=df_comper_rolling_avg['EpRew'].rolling(100).mean()\n",
    "df_comper_rolling_avg.dropna(inplace=True)\n",
    "df_comper_rolling_avg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>TotalItr</th>\n",
       "      <th>EpRew</th>\n",
       "      <th>Method</th>\n",
       "      <th>EpRewRolling</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>20000</td>\n",
       "      <td>-413.868835</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-203.917559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>20200</td>\n",
       "      <td>-413.899070</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-208.047689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>20400</td>\n",
       "      <td>-414.047415</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-212.160851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>20600</td>\n",
       "      <td>-416.912915</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-216.298901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>20800</td>\n",
       "      <td>-419.419068</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-220.456143</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     TotalItr       EpRew Method  EpRewRolling\n",
       "99      20000 -413.868835   DDPG   -203.917559\n",
       "100     20200 -413.899070   DDPG   -208.047689\n",
       "101     20400 -414.047415   DDPG   -212.160851\n",
       "102     20600 -416.912915   DDPG   -216.298901\n",
       "103     20800 -419.419068   DDPG   -220.456143"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ddpg_rolling_avg=pd.DataFrame(df_ddpg[[\"TotalItr\",\"EpRew\",\"Method\"]])\n",
    "df_ddpg_rolling_avg[\"EpRewRolling\"]=df_ddpg_rolling_avg[\"EpRew\"].rolling(100).mean()\n",
    "df_ddpg_rolling_avg.dropna(inplace=True)\n",
    "df_ddpg_rolling_avg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>TotalItr</th>\n",
       "      <th>EpRew</th>\n",
       "      <th>Method</th>\n",
       "      <th>EpRewRolling</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>20000</td>\n",
       "      <td>-270.931678</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-131.071602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>20200</td>\n",
       "      <td>-271.988001</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-133.779785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>20400</td>\n",
       "      <td>-272.833587</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-136.493311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>20600</td>\n",
       "      <td>-273.631443</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-139.208742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>20800</td>\n",
       "      <td>-275.745171</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-141.941359</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     TotalItr       EpRew       Method  EpRewRolling\n",
       "99      20000 -270.931678  COMPER-DDPG   -131.071602\n",
       "100     20200 -271.988001  COMPER-DDPG   -133.779785\n",
       "101     20400 -272.833587  COMPER-DDPG   -136.493311\n",
       "102     20600 -273.631443  COMPER-DDPG   -139.208742\n",
       "103     20800 -275.745171  COMPER-DDPG   -141.941359"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rolling=pd.concat([df_comper_rolling_avg,df_ddpg_rolling_avg])\n",
    "df_rolling.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>TotalItr</th>\n",
       "      <th>EpRew</th>\n",
       "      <th>Method</th>\n",
       "      <th>EpRewRolling</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>49200</td>\n",
       "      <td>-159.297384</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-262.224560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>49400</td>\n",
       "      <td>-161.179071</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-259.923544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>49600</td>\n",
       "      <td>-162.441780</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-257.627073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>49800</td>\n",
       "      <td>-165.686367</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-255.361442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>50000</td>\n",
       "      <td>-174.670526</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-253.179333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     TotalItr       EpRew Method  EpRewRolling\n",
       "246     49200 -159.297384   DDPG   -262.224560\n",
       "247     49400 -161.179071   DDPG   -259.923544\n",
       "248     49600 -162.441780   DDPG   -257.627073\n",
       "249     49800 -165.686367   DDPG   -255.361442\n",
       "250     50000 -174.670526   DDPG   -253.179333"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rolling.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='TotalItr', ylabel='EpRewRolling'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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t4NtXnVlwDdvl45WVnw7s/2/P92veBwZOdS739Qv+1+u5nC8afoqq64mKQBWyVYXjyHJEpC5qW0ZJHCUQDgdDS6cN3cyOI20WaHjAqPPzE/kTRGrFHPnLKnNYnan//mg5JK9nJBV9Soqjhh3y7xvekX/3FDjf/wkw5QcWRr6W84XDuU8HmzpRGrx10qAhy5GqqP3wIIhYonZMI4mjBMWo5ZFt0sFmkQ/R0GVzoNMmwuywwxUC3WG1Q7CJMABhF4Fss9rAWexIj7bD/ixHDltgwdZ9XC6OpDFTDgUrMHsKtGAiktf4z8ALE4fdglvfWY8V2xuwP0BVg2SDxJG6kDgiUhm13cYkjpIMq42hqcOKNJvNLY6Otnahsa4F6ejCQNERcpQ9Y8Chpm5kdtuiF0f+cFiDxEF53OBj5VbzFG9BxZGgmDj7ZvcRrLA1BG+YZJA4Uhe1Hx4EEUvUFv+UrZakiI4e95OW56ATeHRaHBDDCMhut9rR0hUgWDoc/IkNhzVIBt2JC8BuAQ59DzTt75nV2eg9wG2keLr9gmX18RrFxJkmRbO6BBJHqqL2w4MgYona5zdZjpIUTvZwZzBoBfBGbVA/bXu3HWlpOvAAjnfY0G5xAErUWYxUHLnEnGh3Zo817emZV7vZqZ0KhgAZRc7YnSM/OQev1ZmcgofXANo05/dAsU2cx7xg7kcFxZEOCmbdJRAajgKy1UTthwdBxBIOOGG9D3BfjyEkjpIV0U8qfxCLyO6GdqQZHTCldeFYhwVgoRsP7SIDDw68r0X8WayCudWYh3AQJKek3QJY25wXiMMGHD/orJnksPSIHcacYklrBIw5QE65UygBTgHkEkxeMUfBxRFzWBVxXWhSVByR5UhdyK1GpDbsRCazOoGa5FZLViQPd+kbJBckliZdr0GXTcSO+lZ0WOwwaENT5YwBNY0dONLW7adBlJYjX9+Z2BMr5LABHUec60ovADL7OD9ZfZ21hpgdaPrZaX0CgO4WZ02i4zXOZT0tR8EGyuUEvP3fXYHbhEiqxuZQnSN14aiUApHCqJ2t1mvF0csvv4yKigoYDAaMHTsW//1vCCnZiYRUcDDR998+0AgczAYNijONKMwwuENxWrrsaOywotNPRe52i3N+Y4fFtyEokDgK5MLyFE7S9YRaBFKjBwxZTqtTd6tzmqXNWUOp9gegZp1zgFwpQd1qAnbVNoW2/SCkqoggyxFBELFCbbdxrxRHH3zwAX7zm9/ggQcewKZNm3D66afjvPPOQ01NjdpdCx2JQpFZjsI5oSR2+aNt3dhe14qdR9rQZrGjrdsGm9izrmPtFljsIjosDnRYfYiWgJajAILNU6REIo5caIxAV5Pz2HQdBzRawFzkXKets6dd8/6gafr//LFBMYtPqlqONGS5UBVyqxGpDIkjFViyZAluvvlm3HLLLRg6dCj+8Ic/oLS0FK+88orP9haLBa2trbKP2nDSWJ1gLqIQ0Qk8LDYR3TYRBxu78ePBFhxp7UZDmwWNHVZkGrVwiCJau3ykuPtzndmDuNW8LEeS7+GKI63RORSIpdUpkrRGZ2C1IdP5v4vDG4GuxoCrauoWFQukpmw1IhbwJE6JFEZt8d/rxJHVasWGDRswdepU2fSpU6fi66+/9rnME088gczMTPentDQB6hzHYMgQznU6MsAmOtBtc+BwSxd+PtoOm8MBg1aAUatBU6cVds/7cqRuNSUtR4LOGcTdcRSwdTmz2NxILjVdWtAx6BzgoVVIHKVstho9nFVF7YcHQcQSshzFmWPHjsHhcKCwsFA2vbCwEPX19T6XmT9/PlpaWtyfgwcPxqOrgZGKCoUsR56kGzTISdMjL12PvHRnxoBRK6DT4vCOTVLKrSYVLWFW+3YHUFnanRYrQVKjQFIEcnWNiG4vdSdHSXGUqtlqqbpfyYLaDw+CiCVqn9+9NpWf8ygKyBjzmuZCr9dDr9fHo1shUdsmokT0na0WawSBgwgGkTHYRBHHWrohtFuQ4xB9n0xBA7JF/9/DtRwBzuBsWye86g1IxNEtK+x4VefAlACvBg4I0HJKiaPUdD8JVOdIVdR+eBBEKtPrLEd5eXkQBMHLStTQ0OBlTUpEPv+5GzM+a8eHuyUTY2Q5CoaDMRxq7sLhxi4c7/CT4h80ld9DgEQTcwQAWkNPvJF0tRLhq4U9aMkDB3joFBI1qetWS03RlyyQW41IZdSOqet14kin02Hs2LFYvny5bPry5csxadIklXoVOn/Z6hyI9ufj0mw1dU8iOxPBHH4elEGLQHrWOYpWHKU53Ws6+Whx3x/tOdV1sAWtocGBKehWS00Rkar7lTyQ5YhIXdQW/73SrTZv3jxcf/31GDduHCZOnIjXX38dNTU1uO2229TuWlD4E2eMIBVEKlmOpPirJWm1WsBsNvh1SgYMyI7g4cvxgLmP1+T9rRzGnzjbdXDIj58PBIiKxdSk6jAbJI7URe2HB0HEErXdxr1SHF111VVobGzEokWLUFdXh6qqKvz73/9Gv3791O5aUIQTd0T5g1t9ceTPTWXp7sLRpnb097egEkUgA7D9mA3PfduGKRKBooU96IXHQ1TMcpSqqG327u2o/fAgiFiitvjvleIIAGbPno3Zs2er3Y3geIgO/kTsjDyN+sRNUk0LUoBsNbs9gMhQMpXfB1f+/RjarAznaiXiiLOHZDnSpWh9IqVI1crfyYLawysQRCzhOErlJwLhKY5O/GLSAnycSxQFG0w1BH4+LmLe6m4cag9Tt/sRR7xogxDoJGcONHda0dJlAwPzijlyiM7MuEhpszqXlYpJLexBM614BWOOUpVgApOILWQ5IlIZtc/vXms5ShY83VUut5r8rZ2daBu9OHrgKysAYHeTDq9V+G6zqsaBdrsdp0uS+zg/AoYXbQEzwzq7raht6UITWtDX0ol+ouhW7FarFQeOdSDLbEW+KZK9kfRD8iDXwxbUJURuteAoVeqAiAy1Hx4EEUvUPr/JcpToeAge4cQJI3BSy5HzQc9FEsDsh/ou36fGjkYH/vijHbO+8BibzI8w40RrQNHWbbXB4WBgDufgtnZHz9AkbV3daO60wiEZ480mimjssMImMjAGWOwi6tvs+O2KZqzd34mj7RY0d9rQaXXALllOGjyshT1oMLFA4igoZDlSF7VjMggilqgtjshylOB4Wl00J1xUvixHYLF/mB/t9P1A9FdOIJjlyCWcXDUamUPS1mGHlpc/Ahwi0NxthSmNodVqQ01jJ576zoJ1tQ78bVsX3jtfB57noOE5aIUegSd4uNWC1R4SoNzYaqkKZaupDVmOiNRFbfFP4ijB8RJHvPO7r1R+JS1H/tD5SdkPFHMUKBbKSzhJvkstTjZRRGuHFXq7CKtNxPSPj2FgjoCL+zMcautZxqjTIEOvgd3BYHOI4DlAZB7iiHMEtQrxEOnhHwSyHKmL2m/WBBFL1D6/SRwlOl4xR64AYx/DhygQcxQMndCj52WB0n5jjqwBLUdf1zFwOTzSs4F9rRxqDzkw7cS8brsDjRYOjUe6kGlpxaED3Xhxo4AjXXa024CNR+y4dIAOvOcrBgdoNBw0GgFaHrA45AHsOthDEEeMYmqCQOJRXShbjUhlSBwRAfGM19FCBMDLH0xMuYDsYEgtRzaJ5vEngJxuNf/9Otop4vUf0nBPth33rDPgboG5z8qtjRx+VZ8F4OCJD+DL2OoljiT0iKOe/ulggy6I8BE4Zd1qPESIKRbiR+KIIIhYobZbLbXu1qmIn5gjja9stTi41aQxQBZZF/xvm3dY/M7TQERtJ4/mbgccjJNZeFzWncc1b+BP2qd8xjUxxgKexBpX6QMuvJgjpbPVUjG4m8SRuqj9Zk0QsUTtYbHIcpTgeFpdfIqjOFqOJF41pzg6IT4Cuc54h59BaeHcDwbO7ZXzDJwGgOmaVQCAKvt+bGHyWtt20TmUmt/18xwA5pWtFkysKJ2tpocNFugUW18iQDFH6hKwfhhBJDlkOSIC42k5OvFAkqXyux5SClSUDgbnKY5cBCjUKAQSRyf2w6c44hyytwc9rF7L28TgbjXP9eq4UGKOyHIUDA1VECcIIkaobRklcZTg+MtW0/jKVgtgvYkFVsmzMZAJNJBbzeVGcy2t8Qiclu6nrwFcQxdHUstRKNlqDFoFH/462DGVX6/Y+hIBgdxqBEHECBJHREC8K2S73Go9D3cujnWOpAYiueXIvzgKaDlCAMsR7LL99FXV2i4GNr+6Y44kF5oONuiDBWQrXOdIx9lwKr9VsfUlAhpyqxEEESPIrUYExjPmCN5jhcWzzpEUa8gB2YHEkXM/2Il9kIojDRyyYpe+Bjq1OoJZjrgT6+1ZNg3+++PuM0SZMIsWLezQwxa8YRJBAdkEQcQKshwRAfGukO1yq8VmbLVwkFqO/I2tBgQWR55uNc+sMqmoKeCaveKO7CILLI5OlB6QHi8TF1wcOQOylTueethh4LxjppIZcqsRBBEryHJEBMZzbLUA4igeRSClKOFW03q51Txjjnq+/5/2dfxbN1+2vC1otprzf6lLLg3+Y6DcfVbarQZbylmOlBSPBEEQUiiVnwiIv7HVpCIiFgPPhoIsIDtQKr89mOWI4cx9z8KhMXhkq9mh5+SCYgBfJ/seakC21A1pCtGtpnS2WqqJI7IcEQQRK9S2HJE4SnA8RYfruzyTKn5uNanzzOKQfouszpGWc2AMtxsnHfsCJ2mAzx3je+bBjny0eC3DQYSr9KOnOHJ4uPdc86SlD0xcl9/+uNBxdvAK1pHRcXYYfJQiSGaozhFBELGCYo6IwHiII8a8B551x/vEoc6RlNDdaoFT+cu5evf3bK7d/bcWdhRwzV7LpEssPzaH/CS2e+hDX1lw6SFYjnzVVIoGZ4ZcalmOqM4RQRCxgsQRERBPa5DLciTPpFKnzpElVLdakGy1/hJXWQ5a3X/rYEcBd9xrmXT0WH7sHpYjm59uSMVRWggB2Uq7wFLRrUbZagRBxAq13WokjhIdP5Yj30Ug42s5skq7FkgcBeiXBnYM5g65v+dyPeJICzsKfVmOJG4xmyh/u7B7dMOdBSeLOQoekK20C0wPcqsRBEGEClmOiIB4xRG53Wo+stUSNCA7EBqIGMzVuL/ncm3uvwWOoZhr9FomA53uv20iINVHnmLJVxacCcFjjpR2gek4ylYjCIIIFbXFEQVkJzpeAdnOE0Yry1YLLSCbKWyoDDXmKBAZXCf6csf8zvc1L4PrcutBT3HkaTlyzZJlq4XgVlPayqOFd+ZdskPZagRBxAq1xRFZjhIcL4uMT8vRiVT+YNlqgQoCRUCoMUeBCCSMAKCPj/nSmCObA3DILEfytr4CskNJ5TcobOXRpaBbjWKOCIKIFSSOiMD4iTmSpvL3ZKsFe1gp+3O7xBFv74pZAUpf4kkecxSqOOrpnzGEStVKC5lULAJJMUcEQcQKtQOyya2W4PjLVpM/mOI4fAhzoBBNzj9tJhTtfg+lP70a9moc4PA/cQRycRzHWCZspRNRcegTryKPvpDGHNm93GoeMUcn/tVw4T3IlaxxBDgtR6nmVqNUfoIgYoXaliMSRwmOP7eazKXhHng2WLZaeCebprsR5gPLwNs7oe2oh7azHv07juA8g3M7joOCzCJjNZWgKX0gVh3mUcdy0ZLWD7cX/AjwWljM/fBM8xnYvW8f9rA+KDdzONipQdeJLt+am41b9p6BCfx2FKMRczT/8CuUzhO+gw52tMCEwe0m6O1GcFwW9rEi2EW9fI8ZwKt8kQEn4qRSDHKrEQQRK0gcEYHxk63me2w1Zd0cfTY+jazaL72m2xkPDkxWdbp+xO1oKz8XW2zFWHBgFwBgmI5HbcVA8JwAXqdHS0smtrFyAIAFvGyQWWdlaw7fiMMAAKuso3G58CXOF75FEdeEPpKstbH8bozldzu/NJ2YeEITid8LwCYtbKZiWMzluNRagny+SJkDEgVmdKjdBcWhgGyCIGKF0tb7cCFxlOCEEpDNRVnniLN1IuPIcmQc24M/a2tQwdXDxHUhq9ZZrbqtz+nozB8Fm6kYu2z5uOVLI2YL/8Q92r+51yFqjADHwSYJAPL0GXsONiJIQqBsDvmF0IJ0vOk4H286zgcPEVP577GN9cM4bicq+HoUc03IQCf6Gbog2DuQIzYil2sDDwfgcEDfug/61n24CcBNuogOi6Kkp6DliFL5CYJIVUgcJTqeqfzwTuV3xxwFDcj2VuJlu99B0f6l4ERnPEyh4L1Ua9nZ6CwcBwDobnJARAdEj+BupjEAAKyOnv56bk067BljAM9x7lZWh/+3BBE8vhBPBgDUsELZMG6Ti3jsbWE40MqQgU7MGyVicl8GXdsh6Fr346dde1Biq0EFVxd23JGSSOOkUgUKyCYIIlaQW40IiLflyCmAZC4NV5swArJ1rTVIP/wlivb+DRwYLBllaMoZjT/sKUA1/wPOF77rWT2v9Vre7iGORMHp17IHEDlScSQyee6cv2E/giENyG5DGlo1OtjSDbCl90FH8Sl48kA7tneI0MIOAQ68pn0WE/mfoItzMLGZI3FEEAQRKiSOiIB4V8h2njDSooZcqNlqEnVS/M0jSD/SI4AOn/YEjtmM+GBnt2wgWEAujlxrcEBuYhI1RgByy5HX5iUnO2NMduoHshwFwiq64pWc2DwPl2s6NLBBgxm2+6GHFX25ozg5z4rJxz9Gf64OlXxtRNsPlVS0HMnH9yMIglAOSuUnAuNVIVsED1EerBZinSMODCXrFkKwtEBjbfGa79qSw9NlxnufJnYPccQEp1vNc/gOWRtpl+Ex7EeE4sguMoiSQ+Rv+BApFujwM+sDHfT4q+1uZKIdZVwDlow5ipymTcit8w5Cj5bUzFYjyxFBELFBbcsRFYFMcLytQcwrhTpkyxEAfVuNT2EEjnOLFW9x5O1W82zjcqtJRY6nMJEFZDPAIREykVqOPItAeg8f4n+9rm22IB1bWH8cGHAt9oy4B7db78T34qCI+uOPVLQcqZ1NQhBE6qJ2CRayHCU6PixH3vVlQq1zFAjObYFxMA+rUBDLkchpAd753RbIrcbkwsmhgOUo6PAhAZa12OVzRcYgAvhMnIDPrBOQjVY4IOBMfjOuFlZjkrAtoj4CQHoI47kRBEEQTtS2HJE4SnA8A7J9iiPGwDms4G3t0WwpgFvNV8xRTxuH0FN4UWY5gn8Xlwil3GpBBp4NsFqLh5BziJCpqWaYAQCfiKfiX+JE5NjaUMHVoYKvx/9pX4+ovwRBEEQokDgiAuGjzpGnODK2H0D/z64GL8rHA9s78Cbk5OSgvuAMDPnXxYG3w3FwaYWQYo4k1iV/4sgT6RzGALvM4hNNQLakXz6HD/GNT8uRnwUYeDQiE40sE987huBTxwQIEDFP83f0447gbGFTRP0nCIIgvKGAbCIgnnFEEy3/xUjtStk0/kSNIrs+G115I3Bo0qPQtx/EPqE/jKYWOGzeMUOeMIQbcyRxq50IxgYCu9WkwkNk8u+RxhzZRbmg8TfwrC+8xVHo7ypdcO7zIvsNABjK7A0Yx+3ErZpPMZg/FOJaCIIgCF+QW43wi9DdDF2HPMX8ZNt6uHRJjX4ghPLTwJgD9tKJcOiywAFwGPPgsLUi3Exrlz7xLPCIIHWOQrUcSaWHpziKOOZIBKR6zNOtFsgg5SnIAlmOAsOhhhWihhXiY+sZOJvfgNH8HvxK+DTu9ZQIgiBSARJHhAxtRx3S9y9Daf16mNr3u6c7sithd9jwXXcpVndU4AexPwZUjMJ1ZVbA3gVjRh54a7sfU0kIBkpJtppXmn4wyxHfI45kFbI9s9UCuL8izlZzIKDlKBCeW4zQs+fFSnEsVopj8YL9FzDAiiXaVzCZ30zZXQRBECFCbjXCSWsddB9djz5Htsgmd5n7ozVrGPST78Xxwzvx3PdZ+L7V6UbrCw0Aq4+VRQIH8YR6CRhz5BZQUstRj1stYIVsyd8eHi3FUvk9Y5fCETyRW458Y4EOFuhws+23KEAzTuG34xgycQn/P7zouBQAhwaW5RzEFyK6ocNwbi92slJkoAuNMCMXrRjMH0QuWrBeHAIN58AjmrcxWfhBuY4SBEEkGLzKddRIHCUK6QXg2o+AcTw6CsbiSP4kcKXj0Q09bJ0tKNM7M6ekD29HqE9yLjTLkUtkSMUR4wSfy0stR1K3mlWWrSYnUFZZNG61gNlqYaxLFOXlBpSkAdn4lzgJALBOPMlvux9YJQCgG85jehRZOCpm9TRgwI22+5Bva8Z1mpW4lP8K/fiGmPSZIAhCLTg4Y1iNKm2fxFGiwAuwTv09jhxrQmfWILR225Ct1wEWeWVlUfK49xQC/gnFQOnbcuQrUw3wqHMkizkK0CmJ8PDUddYIQ3OsDrkACqfOkSciC1QyMrE4imw8a78cL+JSlHINuFpYjVP47SjlGpDDRVPSgSAIIhGgmCPiBKx4NMS29QHbiLLgY+VOHgbOPUaZtAikP3Ekq3MkiTmS9smzd4F6G6nlyHMpu++h6ELCwZSLO4oXNmiwl5Xgcfu1AJwDEjNwuFxYi71iMU7hd2APK8Hp/BZYocV4fgeG8/vV7TRBEEQQOKgrj0gcJRlSw0jI4igktxp8pvIzTn6KuLYor3PUE3Nk9Qwmki4bRuZYpNg9NhKOOEomy5E/XO7ODx2TAQDfO4YAAP4jnuxuU4xGaDg7fqP5CNlox1nC5rj3kyAIIhBcwMGfYg+JoyRDnvEV4jIhudV4iCcKTspS+UOwHMncalLTlseZLQZQKpEWgfRazwnLkUNkqGkV0e1DdPVLF9FlBxq65YHnH24+hjF5iZF6f+NJPC4cPwRrt+zF1ZOGoL3hZ6w7noNV2w5j7cFohokB6pALMOBu22wAQIGtGTYIOJP/AWP5XbhQ+AZZXIcSu0EQBBERaqfyJ83As4sXL8akSZOQlpaGrKwsn21qampw0UUXwWQyIS8vD3feeSesVnk215YtW1BdXQ2j0Yg+ffpg0aJFMQvCjQURBWRL8CuUuJ6sL3sIMUehDB/ivW3/KOXOqmkTMW9lBy79qA2/+qIDTSeGNBuUxTCtMg1fXpeNP55hxauntuPe0/Nx3TAtLjkpBwDwY10n3t5iUaYjUfDgKQKuHCSgIseAiwbqYNDy4DgOF52Ui3snGHHj+EJMKFHuvaYB2WiGGUvF0/Gg/WaMsbyGe2y34q/2yYptgyAIIhx4MHCheD1iRNJYjqxWK6644gpMnDgRb775ptd8h8OBCy64APn5+fjqq6/Q2NiIGTNmgDGGF154AQDQ2tqKKVOmYPLkyVi/fj127dqFmTNnwmQy4e677473LkVEoMyskOAEgPmyPPiukO3pVnNv26NCtmsJaUC2GpKzxQJsOeq0/qRpgD4ZHEYVavHI6C4c1OYgU9sFGw8IHDC8yIiJuR0oKivFaXlt+L4lE+v3N2HvcXVTSItN/m8IOoHDHaf3QcOhThzTlGDlD7uxdI+I4wpquvw0AaecPRO21iNoLZkFx5a/IXvPUuU2QBAEEQS1LUdJI44eeeQRAMDbb7/tc/6yZcuwbds2HDx4ECUlJQCAZ555BjNnzsTixYthNpvx3nvvobu7G2+//Tb0ej2qqqqwa9cuLFmyBPPmzVNVpYaK1AsbSSo/4wVwDt/iyLU+aZq+f8uRJOaI10vEkf8+xTLYWeCAqRUaOERgeIEGQ3MFlJp5tHXZYTZqIfBdAZfvm8Fj2MAC3DLEippjrTgp24F1dRw6DMX4395GjO5fjPV76rF8vy12OxEGAs9hWJEJOV0CrhjIY6u9FN/tPoy/7wyv7tWYQgGnDypCGVePA63AladVofPoXuT1yUZjbSPsxWPQ6EiDrmgYmlvbUbjrPWgsTV4DIhMEQSiJ2k/jpBFHwVi3bh2qqqrcwggApk2bBovFgg0bNmDy5MlYt24dqqurodfrZW3mz5+P/fv3o6Kiwue6LRYLLJaeV/PW1tbY7UgQ5NWgI3CrcRoAPswMnB/LEe8ZkO1s5Dl8iKuGti1AnaNYuS8rMjnMHJmG8QUcuu0iMgzRndZpGg5aHji/HNjGDBiTZUBRWT4m57XgV2dUYse+/Xj0627FgsijheM4nDMoG6PTG3H7KA2OdYq4fbWIhnanUOI5IN8IVA/Mx+HGZtwxuRKdjQcxtHIg2o78jLw+hajf14BhuUCaTkCX50sCJ8BePAYtGUBr2dkoddQgbcV9EGwUl0QQRKygmCNFqK+vR2FhoWxadnY2dDod6uvr/bZxfXe18cUTTzyBzMxM96e0tFTh3oeOPOYo1KUkDzte8JrrikMKRRy5tx3BwLNKnur5aRzevdiM16Zo8fjpWkzrrw++kAIMyDNiQh8t1t4+Eq+fa4rJNqI5TjkGDtkGDo9dNMg97exSDm9P0+L+s0ux8LQ0DMpPQ6lZgF7DR2QttZeeisMTF8FaPhlWU0nwBQiCIMJEbbeaquJo4cKF4Dgu4Of7778PeX2+bvSMyYO6PNu4rBmBHhLz589HS0uL+3Pw4MGQ+6Q0gcYn84/ErcZ5iyMXvsSRv2w1u586RzJrSjiFjkLkwnIRr56twTvnm1CeKcCsV8f4qtfwqMgS8PUdo/D7M9OQZfB/XNUg1h5iUWdG9+hbsH/qn9A19la0F0+I7QYJguhVcFDXtaaqW23OnDm4+uqrA7YpLy8PaV1FRUX49ttvZdOam5ths9nc1qGioiIvC1FDg3PoBU+LkhS9Xi9zxamJ1C7jiMBN5VMcnXiSunSNGEJAthRptlqgsdUijTkaVWzE9FPK0MeyF8MzO3HIorY3ugeDlseYIg1W/now3ly5Ga/8KIZYOsE/0XsfOfDxip/jOHSdtgCNB7Yg38ij8Xgzjh3cjVO2LozP9gmCSEl69dhqeXl5yMvLU2RdEydOxOLFi1FXV4fi4mIAziBtvV6PsWPHutssWLAAVqsVOp3O3aakpCRkEaY2EdU54gK71Vz63J3KH0KFbAN6ApOlbjVrgGy1cEp6TR+RiY7jRzAi24YpEyqRX1CIw9v3hbx8vOE4DueW8xiU6cCyo1mwdXdizUF7xJW/o0UNk7CY3R9i1x4cKjmXxBFBEFGh9itw0gRk19TUoKmpCTU1NXA4HNi8eTMAoLKyEunp6Zg6dSqGDRuG66+/Hv/3f/+HpqYm3HPPPZg1axbMZuegrdOnT8cjjzyCmTNnYsGCBdi9ezcef/xxPPTQQ0mRqQbICylGMnxIIEuQ75gjuZhybb6GFaCbaWHXmGQCKmCdoyDdzdGLeLGag06rQ15RDpr27QcHQCckT2hcvhG4amQuSjiGX1X3xQ+79+GxrwNnysWC2JzPyXGNEASR/PAcpfKHxEMPPYR33nnH/X306NEAgNWrV+PMM8+EIAj47LPPMHv2bJx66qkwGo2YPn06nn76afcymZmZWL58OW6//XaMGzcO2dnZmDdvHubNmxf3/YkUMaKYox48xQ4At1vNd50jrXd7ABboMNryGi4ekI3LcdjZlrHAY6v56G6BkeGekzrAcvtjKPajIteIhgRym0VDVbEJWRYtzunLsLehBTetCc01W6xAnDev4iHMNibNbYUgiARGTZtF0tzF3n77bb81jlyUlZXh008/Ddhm+PDh+PLLLxXsWXyRCoyIstV8BmS7xJGrzpE0IFuSlcYY2qw9HeiCAYfaOXxq0SPXJCDNJK+f1GZleHu3Ht12HtlpPNos3vWVeDAMyXKgxawF1xbq/iQX2QYOFebgQjZNA/xr1ghY6rdHvU01xdHIkthk8REE0ctQcfSKpBFHhBPvgWdDGVRWXgTSEwYO7VaGug7vIpDrG/X4/bJ2HOlgaLUyr6Dq/9V04n9wPQzl7qNjXcA/D0itJd4FFJPEmxkXTFoO2UYN/BeVCB013cTJ4qImCCLRUU8cJU8wBwEg/OFDHCLDX74/6v7+03FvN5lF5DD9X234YKfTsiO1HO1u12Fnk4jjFm9hJKUiQ8SQHAH56VqUmem0igiFNAXj1LUcEYmNNb0vusb+Gp3ZQ9TuCkEERsVK/GQ5SjI86xx9XQvUtPDo4rvR1iWixQIcte9AR5cFFrEDWXqG+lYLnjqRUNbh0AAexiORAZ025xAcQ3N5/KrMAGxzzhuWw+N3A43ok84j08Dhw+1WLN3lPUTF5f0dmDokC/v5vrA1HcTs/4TmI6NneA9KHguy3hC+aJ75PxxrPobcPoNRnz8Z2u4mFGvaIO74FOZDa9XuHkHI4MitRkgRGcOxToaadjsOHhfR0aVBlbYNa7bo0GbtUdLddoYnNzA4f0apYDkxFD0caLUAWsljd2gOgBb59lxzs/QcHpygwyBB5xZHVXk8ikp7rE1aP0Yh6bM4nOQyeoT3oOSxIMsR4QuWlgscb3Z+4TjYjbmwVpyJxvShECc/jNaDP6L0fw+Ao6FhiISAxBEBoN3qQLMFmL26wx3/40QH7DgIwHfmWLaeYVp/PcyCDZlahvSi/jBb63HXyk4A8tMrTef9kwtwjmLveqAyzn8qvz+kpd6FIFYLDS9xCdJD3I2Sxp64FYEkUgYxowSWrE403/wt2nauRt/1T0Bor1W7W0QCwzgBDn0meF4As3WDZZWhw1gMQ5oZx7RFMLQfhH7AGbD/vAYt+eOQ1rYPmRVjMesftRjL78RGcSDKuAb8JJZjFL8H+1gxhnI1sEIDBg7zAozoEGtIHCUQE1/ZBZvDBJec6ZPBw2IXcSxImZziNIabRxrAW+3gGNCZbwbXfNR3Yx9iR885Y43c1gZpG963IPNE+ijWBLEcpWkFtFocXsv1dpR1q/n+m+iddI35FepzT0ZmKI15DayZFWi5YRWatnyOnJplyDnweay7SCQotqIx6NLlQNNnFJo5MzLTM3DYboLW0oqsERegsXYPcksGoPHwLuT2HXLieyVa9m1BK4DCiuFoTB+KdkMxurvqkF4xGGvF9VgrjpRtZ4NjMABgFca4p80L8eU8FpA4SiCkz7BsA/D2Ben448Z2fLgrcFCaLzEiXReTja3m/yd3P0SlliMP5R6KkVPweBjreQaL6JyoEwCdhgMs3v3s7SgnYrjYHNcwOni85HRk1f43Fr0gIqC7ajrsre1hL2dN74sjw26CZuwNsG37FLk73otB74hEwJreF6zvyajPqALv6IJp7NU4XrMVWQNOcQuezto9MJZUwrFvC0R9tvOewHHOZ4af0RSSldTamyRHZn058SAK5XnkKUYAecyJTBwFUOKuVlJB5G/4EK9lZTFH8g6laRgsVuc0g8DJ3G5k1ZCi3MFQ3q0W3vpqR9yBhiE3YNCqWQr3gwgHW59TcHD4HGSlFwGteyJej71oNJrEDOgGVMO2eyVydn2gYC+JeNFaMB68aAVGXovOhj3Qjp6O5qOHkWsU0CCakdvvJHTs+g4cAJPWBIcxV9X+qplYQuIogZCeBy5rUCixzcHEkXwj/sURH4LlyO+yAfpj1ADNJ+LF9RpA46vDRFB3ZDioLjo5Dg59FlovfANsy4fIPLBM5Q71Pmz6bHRUL4Sj06HcOvudgUZtCTRDz0fnwR9QtHGJYusmlGG32AfNSEfZ0JPBGbORNXACDnXwyC4dhvqaneDgdHW1ZOxBbnoRHK3tgA6AhUqwSCFxlED4ituJ1HIkVdxSV1ggseNLHMn+DkSAbDWj0NMDg4ajNHM/FJoS2XIUGfay09DI58J8YLksaJ+ILe15I3Fw3AMozKoAOiO3GPnD3ucUtHG50I29HnNe+hse1byFAXyd4tshfOMwl6I9awh0OaWoN/QH77AgY/RluPSV/6HGlg0A+GjkIJit9TD3GQxx/05A0Knc6+QKoyBxlEDILEcn/g4lJdtf6jwHpzAK160WSBz5Kzsh7aYvy5ELgwDYpW41v73pfRSZlHtzSxBt5ITXonnWRti/+yMKfnhZ7d6kPO1nP4VDXEF8TgKtEV+LVTjb+gzO5DfhF8L/cInwdey328uwlYxDN3RwVD+I40cPwTzoDHccUNe+LeAAZGgMOIZstbuaMpA4SihccqZH8IRyexP8jF7Mc4DDY1YoAdmymKMQ3WoyceSh6DwtR12SPiXUQ1xlitOVE0eJYjlyozWipXwaMrSA8XsSSLHEOvhiiCcemPFkjTgaa8TReMN+Pkq5Bjys/TMKueNx7kVq0JE1BO15oyCUT0A7M8I8uNophrL7w9blP0Enwa76pIbEUQLhM+YohLNd46cN59Zakga8/wdwTyq/1HIU2uUmC8gOYDkSuJ5gc4+e9XqUE0dcYhaB5AR0nXwnrA27kFmzQu3epCTNAy5RuwvYwvpjC+uP/1jGQ4CIXwufIItrx42a/6jdtYSlK2cYHKNuQGt7GwyjrsChmv2wpPdFKQ7B3q1czBgROiSOEgi5a4rzmuYPfw9CTmKJ8r0Vj/W4m0gDssN/YAeKORKZt2WJcFKaoaRbLXGP8dERt0JTdgpMXy1WuyspRdOvNqOx4RDUzS/qwQEBDgh4znEZAOAp+1XQQMQI/meMSG9Hn85tqGV5+HV5LTIO976yD8cqLoEtrRD6U29HY8NB5JZUoqN2DwwaQ8Qm9cS96pMPEkcJhC/LUSjXiL8sp3Cvr5724QdkB4o5koolBrk4oou5h36ZyhU8i43+VGalTGOEZcT10K1/BVpLkyLrJABoDGr3ICBdcPbvf+Jw1GsN+Nk+EQDwi/FmPHj8YrQ0H8XT2leRx7Wq2c2Y0l01HcfMw5BWdREaDu5yZo5p9IqtP4HfiZIOEkcJhM9stRCW85cZ7/sBGcBy5LqyZFeYR0C2n2XdNZJ4DThjIYDjPrcoMkAvFUd0MQMAso3KXorSmCNFxm6MwQ+1b+LjMDesR9G2NxVfN5HYeJ6SuzUDsU3sg3GWV7B8WjMy675GdtcBaA/+T5X+KcUPaZPwVWseXrdfiI8uz0FOWRW6avcgLZggcsV/xr6LhB9IHCUQvqwvIWWr+Y058narsQDr8zUrVLcaz2wAL4DxWiAjG8BOn+3IcuQbpvDo01Itk6g3WLsxF839ziVxpAB2fXJnKUnvCLa0QjQO+AU05VVoOrQdBVoLWo/8jLymzUDdZhiOK1+aQEna80fDcfp9ON7UgDcODMS/mpwD/bK4WPZ8hVIQkUDiKJGQPNHCqnMUIJU/1KmAbyHm0GUE7wAAhyEH1owyoMs7pkha34Yx//3tzYhK3s84TnnLUQxpufxvsG7/N/J/ekvtriQtNlOh2l0IC89bjc/7HMeBCTrYi4ahS8xA58jL0Xh4Fwq5Vixd/TUuOP5uwrjgGHhYL3weBzp0cBiyUVg0HFZxD3CQXv+SFRJHCYT6brWevw8M/RW0Gg1sGaUh9ACwmcsg6jKAri6v7XKsJ/WUMQZNMrvVeA3sxgLFxxHKMCg7wKL0uAYemU99HAXDcdyqIXEUBba0IrW7EB84HvaScfguTYOHj5yKM/kf8HzlRphVzH7ces570Ou06Fs5Gvadm1W1hifb7TSRIXGUQMgDsp1fonOrRb794wWnAPlDkHl8W2gLS4pLchwHDc/BfsIcwqMnFdXBayEISXzaCVrYTUWAoKw55pmL+wO2WsXWJzXOJbrlCADAa9XuQcJjSSuGvtN3FWprRmlIQw0lCtGekmYdAHBYI47CkTFngBt6EWx7v0TO7o8U6F1odE66D0cNpejKGgydrT5u2yXiQxI/pVIPXzFHIWWr+SkC6XNs9gArjOatw3NbgkQcAcCpZUb8r6YLl42rwHf7myTLMbCkMx8pz6D8NDQqp43kbjXlVhtTmDYNnK0zLtvqnHgPjrM05B7fAtRugr51f1y2GwtsJeNxfMAlyFG7I2HgKdjDLT1x2UAe+1sZLhjVD0ATbAOmodE4APy4m9F28Ef0/WYhOHu3ch0+gc2Qi+4zfofW1mYYR14Na93PJ/qv+KYIlSFxlEBEOvCsv7qO4V6w0aR/e25LFnTN8ZhzahEe/EVf2B0MG2qa3fNErQmdmcUQBaOzrb0bgHKprb0WqVstWdRRHHFk9kOHoQKGMdPRWLsHBZouPLm6DkVHViMfLZiuWRWT7T7GbsIdV1+K5mO1yM7Ow7EOC/JMetQ3t8B4fA8yB5yMrt1rUbTpDz6W9v4hjw27AfyZC8BqEztI2ZNoxUSalsNDEzQorMhBY23Py5aY3R/dXSKab/kerXv+h+Kaz6Df9UnE23GkF6O18GRoKs9Grd0EUWdGYcVwdNbugTEBFZG0S4nXu+SCxFEC4TPmKIoK2dHEHPmDs1t8rsNzijSuCJwAaA3ok2XEgcZOecwRr0F3ehlEhwNd5gEQ09rBTowvwjEW3RXOGHh7N3hLJ8DbAGXDehKaWFiOmG9bZErgKBiOBg3wV/sVAIAx59+MPpoWiD/9AxkNG8F3HVNkO7VcIRy5g2Cz8HAUVEKs3QNHQSUcHVvQUTAG6XlD0WbV+hRHvgbutRvyoP5wouHjZTlSegO8Brb0Pug45ykcyj8N5vpvkf+z3OUmGrIhgoOm23etrcOTFsE46kr3GGaOCIZkifSKcS9FLzaqQeIogZCalt2p/CFcXIrFHAWayRzQdjQASAtpXVLLEeN5iEKPNUjjS4XxArrTS+EoTkd3UztM9mY4NAYIDh+mccYA0QY4GHhHNzjRDq7bDsFigcbOIIAHb7c4++HgwLh0MFMhRIcBQDc4lurl+OXDhyRFzBGA+L7r+hD40mMm6GArPwuNujI4isrRdHgXipu/R3t7K3Jr/gOu9RAEe5cCW40OuzFJxZHHUz+WRhiLuQLHzBUwVkxA+orfAgAOnPUiMgafhca6vcjLyUXD/i3IOPYj8jp2Q/ezc5iTzvyRMMauWzEhVV9e1CAicfTjjz/6nM5xHAwGA8rKyqDXk2skGpRI5fcprAKs0O8wJA4btJ0NsKUVwGY0AfB+i/aMGRBk47MJYLxOMi9AthovgAk6OAzFaMnTQGNrQ6FBXsNF230MEHQQeB14m8WZOcbrIGoEOCBC1OpgSy+FqEtHi1UHmDPBisywN7RD1KaBNdQCCCKQmIhkNjVxiqfyx+O2G08V570tv8eJ14AJOlhG3IDW2j3QTpqD+r0/wNB+CLkl/fHae+/jCmENKvgjwTcblSXUe5LdmBfFCtVDbRsk4zTu6v/MkA2HPhstfaqRfcSm6HaiiuOkkkWqEpE4GjVqVMAAOq1Wi6uuugqvvfYaDIbELmmfSMjcaq6x1RTOVgt0rfnblqbzKKwZpbBkVYIJvqOGA7nVGK+VrVxeBNL/Djo0aXBo08B0JoDnnCn0jlrYDEZYswZAk5GB49oOMF6Loj656GjtRqfVAU1ajxATRYts28xUiO7sgbDb9oHxGliN+c7hLAz5EDUG2I0FENttAO8A06QBdmVu4ry9G0D8rgWp0E30VH5ViFYxcjwsGWVw5A3Fy45L8KrjIuhgw8qLbeiz7Fd+F+OjMpH4cKsZE2UktfDwshyp1A+C8EdE2Z9Lly7FwIED8frrr2Pz5s3YtGkTXn/9dQwePBj/7//9P7z55ptYtWoVHnzwQaX7m9JEGpAdnlstgOXI4zvjODj0WejOOwndOUMDV3gNEJDtmaYt+IsgD4SghS2jFGLuQHTmDofdkAOmM0HUGMHCrDlkM/VBZ1YlbLpMWNMKAV0aLMZCQJMGu6kIHZmDYOszAaxkNByGHNjSCgCN8UR9I617n+xGyXSNEda0YnQbiyBqDLBJ5olZ/dGVPyr8fY4C6c+RPG615EUEj27o0VUyEYdYIGuOsjKACUlqoQ99PGzlkEUrh7LB6DsV75jtBIwRT1oishwtXrwYzz33HKZNm+aeNmLECPTt2xe/+93v8N1338FkMuHuu+/G008/rVhnUx1ZKn84bjV/4sjnxR0gld9jlkOXhS5TnkwU+Vva841YFnPkUdcooFstELwAMbMMzNoe3W2L42DT+098ZrwGTJcOGHRgQgtsJwSUs76RFoC9p96Rzuj+35reB928FQaNALsp270MMxthE7sA7Pe7TY3AIcekg8bfjxn2LvasJ3my1eJ5Z4/NQQm6BwpbjlIFtd1sPaTuMSbCIyJxtGXLFvTr189rer9+/bBlyxYATtdbXZ3vgmWEb3xajkLJVgsnlT/A+rxM/hwX8XhAXtlqfuYlyi1RbbQCD7NJh64YjK1Ct3tfeB8VRd66g6wk3Ho+qQqdk7GBzi7liOhOPGTIEDz55JOwWq3uaTabDU8++SSGDBkCADh8+DAKC5NrvB+1kb49udLzQznZ/RkbRJ/+lOCWI85h9dvO303Ns7XUOiTyOr/zyA4MPHdRX2WHI/E4pMnjVkuajvol2NkcTS0xT1gSPwo9e37d2AIAwOn9zfHvjAzOz9/Rry0+CxJKEdEd+aWXXsLFF1+Mvn37YsSIEeA4Dj/++CMcDgc+/fRTAMDevXsxe/ZsRTub8kguCJeACM2t5vuh4ggzEpcHoLEeB2cX0G3qAyGMeIZARSClQ4sAflL5ezE5+SUn3HWxQTHJkUpCNkY6LPgRUu4Ytl7xd0DZ5CrVmFyZhXcvSsfgAQNw9MBWFXuS/AKdUIaIxNGkSZOwf/9+vPvuu9i1axcYY7j88ssxffp0ZGQ4R3G//vrrFe1ob0CqGZRwq9l9Bpv4X6HG0QWOAbb8KnR1ZCA9ioehEMB1Fmheb4TjOGegd3oRNIIW2WlatHbbFVt/8sQc9QKiEZgSE2DjkGvB5Z8EJFllbBe+TslCEy9/qYopIWxHiZcBusHJSKb3q4ht+enp6bjtttuU7EuvR57K7z3NH/7uJ44wn4pMo0drzkAUZ/QBOtvCWta7zpHUdQa/85LpYokVBRl6aHQ6wFgMrcOGrPy+aK89pNj6k6bMURyfJL6qTSuyXg5gjPO7K8pFlCW34j25LAMHmi3IMyXagMPJfUOi+6lyRCyOdu3ahTVr1qChoQGiKPffPPTQQ1F3rDciE0e89zR/+Bs+xJc4CjTIq0OfDbsuMp9/oDpHnpko5FaTU5qTBq0rEFvQAhlFAB/hKN8+ft/kiTmKIzE6KMHO7GgeXjJBl+Q/an66Fn//RTr6llairWGv2t0hCC8iEkd//OMf8etf/xp5eXkoKiqSWQ04jiNxFCG+hg+JJpXfEeb9k+MjrwgdeODZAPMi3mLqYNR5xGRpdcgqKIVGq8xbdfK41ZKmo/4Jmq2mfDZiMjIkPw2Z+g7o/MUExJo4mVjiXaKA7qfKEZE4euyxx7B48WLcd999SveHOEE4MUf+sr99u9XkK1ynm4j320eHvK1QCVToUTqPUpu90er0yC8pR1dHeK5Nf6SA5IgBKh0VpU53lrx1z387lsepFWY01R2N85aT8F5DF69qRCSOmpubccUVVyjdl16PvM7RiWy1EJYLy3LkIUb+L3MBNra2+ZoVFp41kgLVMopf0GWS46rCHWWaf/JYjlKjCGTgIXqUCchO1itobCGHs8oE1V+KlCyDEGhX4l4hO76bS2kismleccUVWLZsmdJ96fVIT2whHMtRNHEMEjN/uOM+BYodCuRW01BAtptMo3/XmUanQ05xP2gMJkVEEhF7gp3P0blZmJ+/k4e7xiTvYM5JQS+/nypJRHfbyspK/O53v8M333yD4cOHQ+sRG3HnnXcq0rnehsxyFE7MURRue6k4CmVbTPL2yvOc2ywRSAB5XrEUc9TDH28Y53eeVuBRaDagy+o4MXRJZA9E5SxHwewiSYSPgGYlzsW4HaEkc6tVl2rw+KVVaDn0k9pdCYKyv14051Rvf3FUm4jE0euvv4709HSsXbsWa9eulc3jOI7EUYT4ylYLRfdo/BSBDL4VubUo3LdaDc/BVSPdc9lAAiiQcIo1GoFDvlmH413WsEsdxILRZVmhNw7JzeYjWy3sXhHREMhlE607yaExQrB3oaNoPExRrSl+/H3GUGRaDsOo5dGidmd6EySuoiIicbRv3z6l+0FAfuPUhDHwbFghPB5vnNL1hxsKFCh2KNQ6R/FGK/AozDBg37FOOERH1OvTCBwKzHoYdDxKsoxwMIamDivyM0KrLq4Nx+znGuw2TAuSMhqQ7rShEOx6jfbU33PmyyjKyUK3VZs04qh/rhGNtWr3IlToPCecUBBDAiGLOQrDrRZWNiyvAQPnrpniWYYhHEKOKwpjuXgiLc8lMoYjrd1wMFFmTdPwHHJMOhh0vFsESf836gSYT8QNledpkJ+hx4GmDmgDZOuFi0uAaVwnRZiB2izJa+LEhJgdEy5wsG+UqfyiNh2OvKFJWxk7GjSC81rURBNk6cbfOhR2q1FAdtISsjiaN28eHn30UZhMJsybNy9g2yVLlkTdsd6OS1yEcisN515hM5XgUPWzKF37G9SdvAD84Z554V7IAheZAIp1zJHIGOwOBrsowupjgDmO46AVONgFDiadBmk6Af1OFGI0aAXoNTyy0nRwiAwagUeB2QCjTkCaznm5eP4vxaTXYFhxJhhj6LYpExcijT0CELYFiaRR/IhlEcje/ktqBR5mkw5d0QRZJhkszN+cxJFyhCyONm3aBJvN5v7bH2qnaCYz8lR+72n+CEcciboMHB/4S7T2mwJRlwGudod7XijZatJLNbDrTHoDC5Dmr/Dp0tZtQ7fNAa3AQSvwyNBrka7XyKwvAs9haLEZAsfBqBXA8xyy0nRe63KLkQjgOM7b4qM0vBY2Qz501qaAzchw5IvYDR8SeH7k5wKXhD/kyALf2WnKWoEiWL/f3yExnl/xLh5JeBOyOFq9erXPvwnlkMaGuD0oISwXzv3FNXyIqHMOECzTN1HEHAUaIsQ7INu/cAoXkfW4jfpkG1GUaUCaTgO9hodW4KEVOPcDqdBscC9nNsR+TCeXxcfmEFFgDi0GKRBeYkvQwpZeAlgMEheb9/FMrrymOBFDoRGzOkdJyGvnZ/kUKLG2Avlef+of+152esWUpLBP7t+/HzfffDMqKipgNBoxYMAAPPzww7BarbJ2NTU1uOiii2AymZCXl4c777zTq82WLVtQXV0No9GIPn36YNGiRQkTk2GTVG0My3IU5FeU35vkK5TerMOtcxTIdcbHya2m0zgFSGaaFsWZRvTNTkOOSQeTXgOdhk+Ih5FLJCm1HmkQN+O1sKUVOsdk84Map7cAIMuojZ3VLEEJ6laLSy8ShyKzPrykgxQjGgtQbztXEo2QLUe//OUvQ17pxx9/HFFn/LFjxw6IoojXXnsNlZWV2Lp1K2bNmoWOjg48/fTTAACHw4ELLrgA+fn5+Oqrr9DY2IgZM2aAMYYXXngBANDa2oopU6Zg8uTJWL9+PXbt2oWZM2fCZDLh7rvvVrTPkeBg3uJIiSKQQoDU+Wjeq0JP1w+wXBR3gOw0HcxGLbLTdFR12xWkzTUBsMtmKSaOuNCr+AgCh2yTDoJOiKn7JHKSz61GJB/hxgwRiUPI4igzMzOW/QjIueeei3PPPdf9vX///ti5cydeeeUVtzhatmwZtm3bhoMHD6KkpAQA8Mwzz2DmzJlYvHgxzGYz3nvvPXR3d+Ptt9+GXq9HVVUVdu3ahSVLlmDevHmq37jsEsuRO1sthOU0QRpppG9uHm3DthxJrnV57JD/OkeeRCtkXBlk6QZNUr+VPnf1qIiW8xnL5ArS7m6FpzhS062m5TnkmnSwJZxIUidbLbp7DD1oicAkytWVCoQsjt56661Y9iNsWlpakJOT4/6+bt06VFVVuYURAEybNg0WiwUbNmzA5MmTsW7dOlRXV0Ov18vazJ8/H/v370dFRYXPbVksFlgsFvf31tbWGOwRYJcEHbluopHUOWK8xmlFgLOfgYouRhNzJC8gKSeQVSkay5FG4FCSbUSOSZfUwuipy0bgklF9IlrWK3tNgpheCBvk0xWxHPn4oQQeyEkLTfC4RFJvyjTyTRSPrwRx/6cG8ZERFFidvCTlnernn3/GCy+8gNtuu809rb6+HoWFhbJ22dnZ0Ol0qK+v99vG9d3VxhdPPPEEMjMz3Z/S0lKldkWG3ccrfijWHKe3QwRvawfjeaeLxVTkni8VI8xjfZxMHIV3IWsCZKtpAqguTYBAbikiA8QTgtFlLTHqBK+4m6QkRvdMll4EhyFHNi1WliOB55FniiymRCNwyE7TymLT4kqMhEasi0AmE4PzjWp3IQLCPy9i6XAgPaweIVuORo8eHfLDc+PGjSG1W7hwIR555JGAbdavX49x43rGn6qtrcW5556LK664Arfccousra/+McYCFjp0BWMH2rf58+fLaju1trbGRCDZfZQyDuWIc6INuvZ62A05sGRXArw8fVYj8JInpKflSOpWC6+/IVuHAsxzzXSIDHotJ+sPA0OWQQejVlAsqDlRUOJ+6hKMTR1W75l8T4B2It5gtQKPvAw9dBo+gVxt0RNsT8JNekhmhhSmqd0F1Yn05473coQ3IYujSy+9VPGNz5kzB1dffXXANuXl5e6/a2trMXnyZEycOBGvv/66rF1RURG+/fZb2bTm5mbYbDa3daioqMjLQtTQ0AAAXhYlKXq9XuaKixW+xvoKKVvN0QVLTiWsmZVgmh4BcfGIEnzyYy1+XT0AWOFeo9/1hyR+JU34ABagkMXRCbptDvTPN0F3IhLdbNRiZN8s5KbroNeoM5J3LOsUKRHfphV4FGQY0Npl954pyV5LgCHkfKLlOeSm9cQjpQIcF3hstehUcYL+kMlIgtc5ItQnZHH08MMPK77xvLw85OXlhdT28OHDmDx5MsaOHYu33noLvMfwDBMnTsTixYtRV1eH4uJiAM4gbb1ej7Fjx7rbLFiwAFarFTqdzt2mpKREJsLUIhLLEQegwzwQhuzBXsNJXDCiGLefNQBd1h7HikNv9lheYjkKpZN+ArIDu9U85/Fes3LS9eiTleYWJNkJEFMUS2tVPG/BjBO8rIlq4as4nyseicX1oKgjNNRO+iCSiIhOldAzShOBRO5tVE+fDRs24N1338V7770XsGp2tNTW1uLMM89EaWkpnn76aRw9ehT19fUyK9DUqVMxbNgwXH/99di0aRNWrlyJe+65B7NmzYLZ7BQE06dPh16vx8yZM7F161YsXboUjz/+eEJkqgH+Yo4CL8PzHLoyK/2Os2XQOh+KO8ctQvPAy9Ha71zZfKnG5ML0qwW2DnkLIH/LaQUBZdlGGHWCz1o+qYhSp1so1i2R42E1lYQ8FpsSfco26SD4Kv53QghpfZxrqRC8GvRlJoofvq7qtuCNEoiTihJsaFyZyz5Om4zTdpKVBHjs+iWiu2VDQwOuvvpqrFmzBllZWWCMoaWlBZMnT8b777+P/Px8RTu5bNky7NmzB3v27EHfvn1l81wxQ4Ig4LPPPsPs2bNx6qmnwmg0Yvr06e5Uf8BZjmD58uW4/fbbMW7cOGRnZ2PevHlBx4qLF74u2GDnjsBxIZ1hdZXXwJo+08f6w7QceW7btR6PLgihBmRzHMpz01CYmTrxRKGg1E0hUOaaC8ZwolBkfASnqzpxwr4SAu6Bl5VZV8+uBhM/kfzum8X+uMb6ID4qykiah+3sMXpcPTofsNSp3RXFifXQJ9GQyGIj2YhIHN1xxx1obW3FTz/9hKFDhwIAtm3bhhkzZuDOO+/EX//6V0U7OXPmTMycOTNou7KyMnz66acB2wwfPhxffvmlQj2LPcEtR8qtP9y3WsFD5EgJNHyIdDmDlkdhZupbijzpn5cet23FS6Mk8kPDGwXFERe6l47jIjvPu5BcLw+/GJS6lbE9hyYJdLbHW6wkw5WXLEQkjr744gusWLHCLYwAYNiwYXjppZcwdepUxTpHBL+4hCivPnkRyODt5QPPhu468zfP5UrrbYwszVJ0fYHca7EOr3GJIqNOcFqMelO+OrzP70AB2b0pW80TV/mG1m4fCQRxR/3fQYAz8STQy0QCG18VQf1fwT8RiSNRFKHVeo/lpNVqIYo0zKWSBJMN0VabjqbOUYDC27J+iR6XuF4rGRss1a/+OBGwMKQyVSD9b5vnkZtsosjHMYkqfTpky1Fk20gFkqN8Q+TXSrjizzXEDlPw5TBRj6o/wrl24k1Ev8pZZ52FuXPnora21j3t8OHDuOuuu3D22Wcr1jkC4IOU8Iu2iB4fIG4oGALvXx1J3WpagUeWUQu9hkeBWY90fY8m91W+gFAWEqCxJZzLJrKrNdkeef5xlW/wFZAPxLE4qOdwR3AOlByNZU/Lc85xHhNEASdCklEwgvVQTREdkTh68cUX0dbWhvLycgwYMACVlZWoqKhAW1sbnn/+eaX72Kvhmf9AW0AJt5rk7zCXDVTpWmo5Ks81oapPJvRaZ3Vro64nrVwZqwYRCObvGLuGmQkzi00jcMg0an1moyUP3sck0lPR8xKM3dhqyYM09ixQLJprnkHHu12zaggMlxXHs0SM0oQTl9dbzpVAaGP8ewQiIrdaaWkpNm7ciOXLl2PHjh1gjGHYsGE455xzlO5fr4dndgDeLkz3/GgtR9JstShS+RljaOqwQmQMHAdoNT0ntU7D+12uN1mOnrliJO7+2w949NKqmG3DV+yRX9uja7BaIfhvIPAc8s16QHTAoBWgTdMklxvNEwVPu3COQm+JOZK6WV3lG3ydL+55WgFprjYCh2yT1i2YXP/Hx4qg7P3IU+B4BnMDCicyhLiK5EqeUIeoCp9MmTIFU6ZMcX/fuHEjHnrooaAZY0ToCAgsjqK2HEl0SygaXXrrkIqp1m47skw69M/PRH6GHnqJIPLsorQIpK/Cl6nKZWP74vzhxTLLmdL4ij3yazlywWthM+RDZ23yepN3/a/XOpBuMALMntyiKAaE5VaL4NAdZVnhL6Qw8XyYulxvbsEkFU6KoeC6olyVr0GZXS+t0caU+t2mD5GmBon8rhD2kVm+fDl++9vfYsGCBdi7dy8AYMeOHbj00ksxfvx42O2JkImQOnBiYLda1Kn8kis7moFn7Q4Reek6lOakwaAVArrcpNd7b3OrxVIY+cPfIXZZmQxGPfKLS5GTkQajTkCuSYc0rfx/bYQp6ImLcgHZng/HgGd0BMfxQduNYS8TDv4EsUHHu+N/tIIz6D4RMks1Aoc8kxa5EutSKKIt4LAubpR9Wke6No2GQ3GmEVlG/y/GSm4vFKQC2RWjFa11L4G1UXiWo3feeQc33ngjcnJy0NTUhDfeeANLlizB7Nmzcdlll+GHH35AVVXsXAa9ESGImVfJmKNQXlJEiaVHK7kQGAfZGGiyNH+P9UpFWG9yq6mFS4D6iu8wG5z1c9JyMwFDOaBNjTHO4kk4ciESQ8AR5IS/UAi4UsndJRg8LTVaAdoIssvumdwXAZy5UaPlORSYDU4VeqKvrvH5PB/SsgyywO+ZCUemUQuNhUe2KXC6v5RInwaCAOSkB44Lc50nNp2APLMeZqMWWo9zRm1LlJKEJY6effZZPP7447j//vvx4Ycf4uqrr8azzz6LTZs2YcCAAbHqY69Den4Gs+ZEa3aVZ6v5X5dDZGjutKLb1nOH0QjyOkfSC0sTYr+o8kNs8LzJFWUaYDQIMBeWATrDCTeF5EYmaAFzMWDtjHNPU4AwLsF4B9n6c4dpBK7nARfgWnW7uHh5cLU/S8E/r8rDyEF9gJaDyu9MAHzGLp2Y7iofILTEtUsAoncbuY6/UqLDs7aS6/d0us19b8dd8d4zhszHe630/Mgzad3TkpGwxNHPP/+Mq666CgBw+eWXQxAELFmyhISRwrjPJSYGfdNUts6R93yRMRzvtKHL5kBuug656T2WBfkwIPJYokBFIKU4eplbLV5I3R+MAX2z05xfdEEEkKAF0ouc//esIbHt3xGh7PAhIbcN8WnJwCkyxIlnbIlXwc4wN+EpQmwquInDxSUw7B0910RWWmoGI3sN48RxcsHiIYjdv6etW5Hty86PE9a9ZLUmhdXrjo4OmEzOwQR5nofBYEBpaWlMOtabccUyc6LDae8MQLTZL9LlPdfV2mVHXUsX9FoeI/pmYnRplixmRiqAtDwvc7N5Cid/9KaAbLUIK67LZUHSpvkQSSmEgqLc8/QOnMof2jqtgy8GAGzlB4XdH1+1gqSiyN/Av5Gg1HrigfSe5DoW7tgqPwMlJzODCjNQlpvmFiw98YPqWC+1Gm+5kcjZm2Fnq/3nP/9BZmYmAGel7JUrV2Lr1q2yNhdffLEyveulCNyJG7doA+MC/0SKWo4k0zUaHgIHDMpJR0GGwSsd39nPniUEXu5mk1uO/PdRJHEUc7yOsE/rkI82vczNFnE8dhgLhnq5dpzxMJpNAzB/2wggyE/gK5bM6BErFCidvrfi5YpjgENym1OiHpGaR9ukE4Au9X9v13HOzMiAqE8DlyQiNGxxNGPGDNn3W2+9Vfad4zg4HEkW+ZZguM4djtkBPvCbe9QB2ZLL1y46axQZdTwGFabDbNDCoPVvuZK+aQk8L3szk91UAnSRArJjj5eRxCV8QsElpNpqg7dNKnwUgYx4XVzIS4ccc6RNQ1vZWWjbbgFgCdzUFRMijbfxiBWKF8njJfd9XKR3u1xJoLfaLrhAGYWu2B6Djo/6ZdmVCehan5L7ruE551t0kgj0sMQRjZsWHzS88w7DiQ5wGgMAm9+2UReBlLwpmfQCBuSbYDbqQrrINF5uNanlyP+gtFJ6Wyp/0iFogYxioKNB7Z4kLJ6XSuCBZ8OLv2CJOvBUMhLBvcZl9bDphLgFGPsKoveyckn/l2TuhZoI4w8tz3tlAsZSzCSwVy26IpBEbHBbjkQbmJCNQOIoGstRu8Uus9wMKsxARX56wGWk9xfptrVa+VuLPOYocBYckeC4fr+0nNQRSTGMOVKqbTKS9Feznx9IVj4gRmLBK1g+gu2k+vkVTyISRyUlJTjzzDNx5plnorq6GoMHD1a6X70ajVscOQC9EUCr37aRFIHstNrR3GmDUcejT5bRPT3cAoVSq5U+wBAhlK2W5HAcUDLaGX+UKuLIVxHImK1Zso1EflXuTSjwM7jEjKDTIlujB+Aaoy30ukRSFIkLo9NLMSLKsXvmmWdgNpuxZMkSDB06FMXFxbj66qvx6quvYvv27Ur3sdchcACYAwAHCIGL8oXjY27psuHw8U502xzon2fC2H45KJaIo3CtUNL2Ro/YpFCz1chylESEEsjdCwnnsjHpNVG7ZRJ5XKxheb3n3HCJmf55JmSnaXumpfVkwvm7P2tODHSbahlyqURElqNrrrkG11xzDQDgyJEjWL16NT799FPccccdEEWRArKjROABTrQDPAMX5EEUaipkm8WOHJMOQ4oykJdhQLpec2L5njbhvtXKLUdycSSEKI7sDhJHSYMrkLuj0fk9ia1+Ahd6NlIwwllDukEb8RAcnhWtEyVY2MWDU8qg1yTL8FGxPWYu4aQReuJ0pb9VoEKK0ZAYZ0LoBO2vii9iEccctbe346uvvsLatWuxZs0abNq0CcOHD0d1dbWS/euVaHgOOkszWEYGRK0xYNtQLEcmvYAhRRnucc9ky8vqHIXXT6kw02rkC2tkAdkBUvmT+AHba9EaAX0m0F6vdk8ihufgNdhnpCiRyu8SPoEyhPwW8EuQ7J9og4FjT/zvNdL7ayL9VolCyomjU045BT/++COqqqpw5plnYsGCBTj99NORlZWlcPd6FyVZBtQe78apfQQADJbMAWC6jIDLhOIKG1jofx2crFZRmJYjSXOtx81cai4mt1qKoUsDCoYA9i61exI1SriowlnSn6VXOOFmMXiMUSV9sYiFpYFILZJOenGhl8GINxGJo927dyMtLQ39+/dH//79UVlZScJIAT781UR8+mMdJmUcQafVBD69BJw98Injmcpvd4josDrQabUDXGCrDRCdW82zQrZsXojrIstRkpJeAOQNAsTkdqFLU7UN2sisSN6neqBU/tDW6RJtHBe4xhERBrJ7jZ8fgm5HsUdau4/jEctBiqMhortBU1MTVq9ejVNPPRUrVqxAdXU1ioqKcNVVV+HVV19Vuo+9htx0PU6tzIOYPQAd5soTJ05gXCKk2+ZAfWsXGjus0PAc+uebMKYsG8VZhsDLS+7W0bjVdAFjjiiVPyXJqQDyKtXuhSJoec6rCnygwnvS4Tk4j2VCrXMkXb9ncK7bZUYQyQ7vkciRJAkdEcccjRgxAiNGjMCdd96JDRs24MUXX8S7776Lv//977jtttuU7GOvgwk6gLeG1JbnnVloosjQJ8uIokwjzAaNbCiPgMsHGFst+LI9f3uN+i2ZyQJYh0gcEWoQbFDXXFNP4LOvwntayfAc0jM/WLC13BXtUdnaR5eSzk2SLPi71yX5AU+YUhG8FjAVAl2NTjFk9D0UUYL01icRiaNNmzZhzZo1WLNmDf773/+ira0NI0eOxNy5czF58mSl+0gEIF2vwajSLGSmaZGh10SVcRZKzJH0/i1tr/N4KEjfggMJINJGhCoEcecWZBgCmlJdKds2nXDiOnCuL1jsEhemedbTIktEQwg3G6WzxxL56R9LBC2QUQRYWtTuScREJI7Gjx+P0aNHo7q6GrNmzcIZZ5wBs9msdN+IEMgx6VCakxbx8vKYozCX9TeWGuSWo0ACyE5D0iQ/vbj+kZbnPIbRCRbjl7pPy0hjtgjlSN2zK/5EJI6amppIDCUIWk10N6To3GrSKtge2WpScRTIckTaKPlx1T/yYTZPXHxVyI7s0eJ52QQyPvCRlLRPcO6bYMRXB234xfA8oOOw2t2JDoXVRbzFStJp7wTub0RXqtlsxvHjx/HGG29g/vz5aGpqAgBs3LgRhw8n+cWRKDCgudOKxo7A2SrR1hbho0jll2akeV6U0jpH9gDiiCxHhCqoNLZauJdrMjzsfj3GiPcuNnsNIUQQyUxElqMff/wRZ599NrKysrB//37MmjULOTk5WLp0KQ4cOIA///nPSvez19FpsyNfb0BFSWbAdkKUb6LSm7WSN27pugKNn0YxR4SbZFACPgin2xzHJfTwH72GJD3XghHTvfLMOgtGkrvbI3qyzps3DzfeeCN2794Ng6EnVfy8887Dl19+qVjneismnQbDijMxqiwraDxR1JajEFPuXUh1TiCXnHRdgdxqRIrCa4D0wvBujHGteRU7y1GgVH6B491p+sHik4CkHqEl8VDhWMY7eyymm3O5z/kwxJG5OGnFUUSWo/Xr1+O1117zmt6nTx/U1yfvkAKJQmluGoy60LJUon37lLnVoigCSVWwCRm8xpmtkqgoqTrCuG5o9AgipQnTupTIl0NE4shgMKC1tdVr+s6dO5Gfnx91p4jQiT7mSPp35GUAAi1JVbCJVMbT/B4wIDuRnwYpTwgVshWm1/zcLlGkSwOMgUNBpCRMXSYfRORWu+SSS7Bo0SLYbDYAzh2sqanB/fffj8suu0zRDvYmNAKHArM+LGtQ9DFHoVl/fC/b8zdVwSZ6K2ENPEsxy4kN3arCQyqKgrnQkiwGKaJL9emnn8bRo0dRUFCArq4uVFdXo7KyEunp6Vi8eLHSfew1aAUehWZD0Cq7UqK1HAlhFoGULcuFZjkKFJBNpCBS03o4N8Q4vkUqacEJK1uN1FGCECfLUeIaRqLDFVMYiihykWQxSBG51cxmM7766iusWrUKGzduhCiKGDNmDM455xyl+0cEIVxB4wkXtlutR+jwIcYcUUB2L8M1XICLUGsgxVFEK5koFs4lSG61BCfJf5+4dF/QAua+gCkvaYROJEQ8thoAnHXWWTjrrLPc3zdu3IiHHnoIn376adQdI0JDSctRNAPPBnarhd0tgogxSgZkh9403KSHlLU8EMmLywKkABwHfDx7En758teKrE9JwrbxLl++HL/97W+xYMEC7N27FwCwY8cOXHrppRg/fjzsdrvinST8E63lSJaOH65bLcSzx5db7YNfTcDAgnT8ddaEsLZJJClJEG8Q6ZUUTip/uGKHPNIKIj2YcRKdKVEhO9z6RmEypiw7JuuNlrAsR++88w5uvPFG5OTkoKmpCW+88QaWLFmC2bNn47LLLsMPP/yAqqqqWPWV8EG0qfzSpaMZPiQQvtxqp/TPxfJ51WFtjwiP7DQtmjttanfDSShDjMTTTBLDCtmBxFEqj61GpBgRZqClCmFZjp599lk8/vjjOHbsGN5//30cO3YMzz77LDZt2oS33nqLhJEKRJutJiUUw5G/IpCBoFR+dfjLzadgeJ9MvHfLKWp3JQFR7pwMR/CEkWtBxJR4BWTHuQikEiuJJNg6QhL5VSEsy9HPP/+Mq666CgBw+eWXQxAELFmyBAMGDIhJ54jgRBtzJCXcCznUhwJlq6lDVZ9M/OuO09TuRugk6XkSVip/7LpBBCU5z69wCPlc9OUq4/heE2wdCmGJo46ODphMJgDOlFSDwYDS0tKYdIwIjWhjjqJZV6hGq3RdVHH/RCqRKLFHag08S6n8RCLgyih1ubkzS4H0fEWDraNhYEE6Fl2iricq7KfWf/7zH2RmOv2Poihi5cqV2Lp1q6zNxRdfrEzvCBm3VvfHa2v3yqZFazmSp/KHt2ywzJunLhuBf2+tw02nVUTQMyIlCRR7lKTxOJ7dDlghOx6ikNcCpkKgqzH220omZAHZyXmuBYML11HlellJIEvR7y8bjqvGl6ndjfDF0YwZM2Tfb731Vtl3juPgcDii6xUh47sFZ6OmqRNj+2VjRJ8sDC3OwPVvfofDx7swrl+OYtsJN1g0N10fcP6V40tx5XiyLBKpTahXzVmWp/G2ENqYie51R/IMF7TOce0sLREsTPQqVLYU+QrlSJQhRcISR6JIBWvUoMBsQIHZAAC4YITzRF59z5mwOkSk65VzWYUijs4fXoz31x9EcaYBlQXpWHTJScgLIpIIwgtBZeuGkm61EO/le1lJ2NbZqLsZ4zTs5MXPD6FwWFKCPOd74DWAMTdhzgefhydBQsMoGCRJ0Wl46DTKxi+EcuM+Y1A+PrvzNPTLdcae3TCxXNE+EL0EX9aNZA3IDmGKi5im8kuFkONECQdXbInDFplISrCHKRGYgKcXnxzB1heOVD/mCYhCHO3cuRMvvPACtm/fDo7jMGTIEMyZMwdDhgxRsn9EjJGaMEM1Z55U0vtqXhCphrcQi1S3hLOc4Ap6VRJf9WgcHvWtQqkz5XPdGqeI7S0orF0TynDkOaxPAiLwHNISJIEnItPD3//+d1RVVWHDhg0YOXIkRowYgY0bN2L48OH429/+pnQfiRjSP8+E0wfm4eKRJYpmvhFE2KhZBJLXAlpjRKvytAYFLAJpLnJuSwnCGRGdQML4a2KI7MxLIpfqiL5OUX/B8MQRbxGJo3vvvRfz58/HunXrsGTJEixZsgRff/01FixYgPvuu0/pPgJwZsCVlZXBYDCguLgY119/PWpra2VtampqcNFFF8FkMiEvLw933nknrFarrM2WLVtQXV0No9GIPn36YNGiRWBJas5XAo7j8JebT8Hz14xWuysEoR6CFtCmRbRoWKn8vhrzWiCjD5DZx/tBJm3vaqNNI1FEBMd1figlxmOA673i7RtPxlOXjcDjvxyubockRCSO6uvrccMNN3hNv+6661BfXx91p3wxefJkfPjhh9i5cyc++ugj/Pzzz7j88svd8x0OBy644AJ0dHTgq6++wvvvv4+PPvoId999t7tNa2srpkyZgpKSEqxfvx4vvPACnn76aSxZsiQmfSYIIgCq1jzyfiGK5TvSXtHpmhJ4rme/pSInuwzIKuuZ5j4mEnXkaqOEKAokyFKWFE/l57WAoOv5nhS/q/N3yDHpcOX4UkUTjKIlop6ceeaZ+O9//4vKykrZ9K+++gqnn366Ih3z5K677nL/3a9fP9x///249NJLYbPZoNVqsWzZMmzbtg0HDx5ESUkJAOCZZ57BzJkzsXjxYpjNZrz33nvo7u7G22+/Db1ej6qqKuzatQtLlizBvHnz/MbcWCwWWCwW9/fW1taY7CNB9CoijYNJMELxRt9gm+9s6xJHrvRpnYe1KtbHRPATn5Qk7hciAIIWnEYXvB0REhGJo4svvhj33XcfNmzYgAkTnKOqf/PNN/jb3/6GRx55BJ988omsrdI0NTXhvffew6RJk6DVOi/odevWoaqqyi2MAGDatGmwWCzYsGEDJk+ejHXr1qG6uhp6vV7WZv78+di/fz8qKnwXK3ziiSfwyCOPKL4fBEEkDrEMyD7E8gEkwMCzvurapIhIDY94ja0Wh41QRmFMiEgczZ49GwDw8ssv4+WXX/Y5D1C+IOR9992HF198EZ2dnZgwYQI+/fRT97z6+noUFhbK2mdnZ0On07ldffX19SgvL5e1cS1TX1/vVxzNnz8f8+bNc39vbW2lYVMIIqmJ3fAhgdYcrKp8UpIsD+dQfvJkDD91ZRQm+vFPMiKKORJFMaRPMGG0cOFCcBwX8PP999+72//2t7/Fpk2bsGzZMgiCgBtuuEEWTO3LLcYYC5iu7lo+UBq7Xq+H2WyWfQiCUAiXqyeeic9ceJWqAfjN/vEePsT/fsRNG8Uznsv1cE7gwF+1CHs4j3DxOCd9nl+JMp6hDxL5XSEscXT++eejpaWnaNvixYtx/Phx9/fGxkYMGzYs5PXNmTMH27dvD/ipquoZfC4vLw+DBg3ClClT8P777+Pf//43vvnmGwBAUVGRVzB4c3MzbDab2zrkq01DQwMAeFmdCIKIE2oMYcBr5EHRoTw4XP30EAHB7u+fl/UkhcStXIarr+E8EBP4Iao4/p7KCfyw9kkov3Mk50KMmX3mAADAwxeFrhfiTVhutf/85z+ywOTf//73uOaaa5CVlQUAsNvt2LlzZ8jry8vLQ15eXjhdcOOy+Lj6M3HiRCxevBh1dXUoLnbeaJctWwa9Xo+xY8e62yxYsABWqxU6nc7dpqSkxMvdRhBECsNx/oOiAUAI/dYYzDpw3Fjes9pEflXulbFHSYbLUuRH1MfcUqUQ9547BLdWD0CmMXEEmydhWY486wHFqz7Qd999hxdffBGbN2/GgQMHsHr1akyfPh0DBgzAxIkTAQBTp07FsGHDcP3112PTpk1YuXIl7rnnHsyaNcvtBps+fTr0ej1mzpyJrVu3YunSpXj88ccDZqoRBBEiSW55kN0CzH1DtirJlvPRVpQUl0yK20yS/46JhOK/t0vA+innkBTn1wkSWRgBEcYcxRuj0YiPP/4YZ599NgYPHoybbroJVVVVWLt2rTvzTBAEfPbZZzAYDDj11FNx5ZVX4tJLL8XTTz/tXk9mZiaWL1+OQ4cOYdy4cZg9ezbmzZsnC7YmCCJCEtB875dgL3bSB5CnSHINmnvCuiR7IPHaIDFHSfD08uU+jEQwJVyF5mSMtj5Bwh3L1Ccst5orSNpzWqwZPnw4Vq1aFbRdWVmZLIPN37q+/PJLpbpGEIRixFM4hFEE0jMmStACWaXO4Ua0aeA0egAWPwsDYrI+k6WCKBKXm2ssr17splPsjA5xXLRk0N7JQljiiDGGmTNnuq013d3duO2222AyOUdol8YjEQRBhEUy3dglgskpjiTTPYgo/MAlTDgVC86qESgfS2S/QzKdbIQahCWOZsyYIft+3XXXebXxNawIQRBEUOJpYVEwXlJW2FHQeu3GYeNgAIfCW6lbmOyOsneEmsTbkpMsAdnJQFji6K233opVPwiCIFQlJhWyTfmwcxQnknAkg/+JPxHb1tWodk96JYkzyhtBEETcUNJMFeBBy/EQ45TVGxcoky32uIKvdWnO42xpCb4MoThJka1GEAShKIq61TxWLRVLQy5QclPq46cQJqEgUWR9JoNBLFkgcUQQRGKQpDf2gA+kqYvjVg8uriSlBYkCsonQIXFEEERiEFcN4WtjkT0wAwbB6tLgSFVx5KsGFCEjpFI3QapeE+pAMUcEQfQ+FBQswZ5/SVvnKBSk6f4Om7p9CYdE8j9Jaxh5DmUTpoUuKYqMJgkkjgiCIABEarriPR5InhWyU9KtFohEreacjL9DqtWaSiJIHBEEkRgk60tvMMuRGJ9uJAwhVnPuDcT7lE7WSygRoZgjgiB6H0q61Ty+r3GMAgB0804XSUql8gci4YO0U/93IK+acpDliCCIxED1Z1eEAdkeT6Q/Os5HLctB5tDJWIQUjzmSQi4gL/yKFSrwmPCQ5YggiF5I7Ooc2aHBP8XTcFyT79xSb7EcBcMlCIQUfScPZf+kBR4zigA+RY9FCkDiiCCIxCBJXQLBut1r3GrBELSpLQh87J/XuRFFgUcivpA4Igii96FoKr9veeTaQjRutYcuGgYA+PWZAyJfidpIY5ESPi4phnjudwyORZK+XyQkKSrhCYIgAhG7gGz3Fk4IsGgsR5MG5GH7onNh1AkRr0N1PGORzMWAtTP+/VDbgucZjxWDGC2qc6QcZDkiCCIxUPnZFfFzxc9yrt2J9pmc1MIoGIlaE0khOD6Ff7sUhyxHBEH0PnwolkhFTMDhQ0AxRz4RJIHJxkx1LEnxgIuvOCK7kXKQOCIIIjGI6509dtlqnpsgceQDSvsnEhxyqxEEQUSB5/AhLhhcMUfx7E2Sk+zp/ioHnFPIkXKQOCIIovcRh4FnXZugOkdhoFS6v69Ypnj8Di6LGK9WDBWpI6UgcUQQBIHI37qDLUeWozBRwvqitkg5sQ+cEN+Yo7OGFAAA0vVJanlLIOgIEgTRC1FSsfhxq53YhIPUUXA8ayGZiwGHTVkXldI+p0CZdq594PYqu80gXD2+FAUZeowozYzrdlMREkcEQfQ+4uFWQ/R1jnoNvgK0XdOUymRT+ncQtIAxcP/iHQPE8xzOGVYY342mKORWIwiCiAL/RSCd/2cY6B2UIJINumoJguiFKJnKH3j4kAcvGIbDzV2YeWq5YtvsVSiWAUYWPCJ0SBwRBNH7iINbzUVJlhH/nHOaYtvrdcQqBilSPGONevN4cSkMudUIgiCiIJhbjVAINTPQpPWXXP2QiiPpdyIlIMsRQRC9ECUtR77l0Yi+lDEUM3gNYMwNT5BEo1YFLZBVCmiNYW2TBoJNXkgcEQTR+4ihW+0/vzkDa3Y2UIxRLOE1zmKR8YSGPOlVkFuNIAgCkdcWPrk8R/Z9cFEGbq0eAL2GRmSPCUkU40N2o+SFLEcEQfRClLMcnVtVhFeuHYOTSsiNFhekFhyHLbbbClTokUhpSBwRBEFEAcdxOG84uVtSElehxwihkKPkhcQRQRC9j5N/pXYPCCUIy8UWwFroCvDmJK5Qshj1akgcEQTR+yga7jUpx6RToSNEVCgxxAivBcx9AVMewEnCcCn4uldD4oggiAQhTj6Im5f7nHxr9QDsrG/DBSPooZh0hGRB8mM5krrOOGWD6MmrlryQOCIIIkGIQ9XE858GSk/2OStdr8HrN4yLfR8I5VGqijZPCdyEExJHBEH0HirPUbsHRCzxVYvIVzwREJdMNCoCmbyQOCIIonegMQI5FWr3gogngiSeSCqC0osAXRpgpPILhG9IHBEEkSDE+C37ju9ju34i8ZBakqSWIwq2JoJADlaCIFKf9CIgs6/avSB6GeRVS15IHBEEkSDEMCD7yndit26CIFIOEkcEQaQ2Of2Bsglq94JIBjhlH4lkOEpeSBwRBJHa3L5e7R4QCUEIlslTfu0M4D51buy7QyQ0FJBNEESCoPB79vQPgYozAIFuc0SImHKBu7YqFyxEQUdJS9JZjiwWC0aNGgWO47B582bZvJqaGlx00UUwmUzIy8vDnXfeCavVKmuzZcsWVFdXw2g0ok+fPli0aBEYi0PxOYIg4sugaYDWqHYviEQh1Ps8CRoCSWg5uvfee1FSUoIffvhBNt3hcOCCCy5Afn4+vvrqKzQ2NmLGjBlgjOGFF14AALS2tmLKlCmYPHky1q9fj127dmHmzJkwmUy4++671dgdgiDc0EsKkVqcVpkHAEjTKTssCRF7kkocff7551i2bBk++ugjfP7557J5y5Ytw7Zt23Dw4EGUlJQAAJ555hnMnDkTixcvhtlsxnvvvYfu7m68/fbb0Ov1qKqqwq5du7BkyRLMmzePqpkSBEEQilGRZ8J/752MbBrUOOlIGrfakSNHMGvWLPzlL39BWlqa1/x169ahqqrKLYwAYNq0abBYLNiwYYO7TXV1NfR6vaxNbW0t9u/f73fbFosFra2tsg9BEEqj4MsJH7shIQgiHEpz0pCuTyo7BIEkEUeMMcycORO33XYbxo3zPTBkfX09CgsLZdOys7Oh0+lQX1/vt43ru6uNL5544glkZma6P6WlpdHsDkEQseaurWr3gCCIJEZVcbRw4UJwHBfw8/333+OFF15Aa2sr5s+fH3B9vtxijDHZdM82rmDsQC61+fPno6Wlxf05ePBgOLtJEES8yShSuwdEwkExbUToqGrrmzNnDq6++uqAbcrLy/HYY4/hm2++kbnDAGDcuHG49tpr8c4776CoqAjffvutbH5zczNsNpvbOlRUVORlIWpoaAAAL4uSFL1e77VtgiAIgiBSE1XFUV5eHvLy8oK2e/755/HYY4+5v9fW1mLatGn44IMPcMoppwAAJk6ciMWLF6Ourg7Fxc5BBZctWwa9Xo+xY8e62yxYsABWqxU6nc7dpqSkBOXl5QrvHUEQqjB1sdo9IAgiyUmKmKOysjJUVVW5P4MGDQIADBgwAH37OgeTnDp1KoYNG4brr78emzZtwsqVK3HPPfdg1qxZMJvNAIDp06dDr9dj5syZ2Lp1K5YuXYrHH3+cMtUIIpXQkJWX8AHVsyPCICnEUSgIgoDPPvsMBoMBp556Kq688kpceumlePrpp91tMjMzsXz5chw6dAjjxo3D7NmzMW/ePMybN0/FnhMEQRAEkUgkZX5heXm5z6rWZWVl+PTTTwMuO3z4cHz55Zex6hpBEGqjM6ndAyIhIcsRETopYzkiCIIAAAy/Qu0eEASR5JA4IggitRCoACRBENFB4oggiNTh1Llq94AgiBSAxBFBEKnD2QvV7gFBECkAiSOCIFIHnm5phB8olZ8IA7qTEASRGvSfrHYPCIJIEUgcEQSRGvQ/U+0eEASRIiRlnaNkwOFwwGazqd0NIgXRarUQBEHtbiQeVOWeCAi51YjQIXGkMIwx1NfX4/jx42p3hUhhsrKyUFRURMPeSCmbpHYPCIJIEUgcKYxLGBUUFCAtLY0eXoSiMMbQ2dmJhoYGAHAPspwSRHutlI5Xph9EakIB2UQYkDhSEIfD4RZGubm5aneHSFGMRiMAoKGhAQUFBanjYovm4TXiauX6QRBEr4cCshXEFWOUlpamck+IVMd1jlFc2wkuek7tHhCJDlnxiTAgcRQDyJVGxBo6xyQYswGtQe1eEIkOudWIMCBxRBBEYhCp4PvNVmX7QRBEr4fEEZEQnHnmmfjNb36j+HoXLlyIUaNGKb5eIkEw5QP6dLV7QSQFZDkiQofEERGUmTNnguM43HbbbV7zZs+eDY7jMHPmzJDWtWbNGnAcR6UOCG8icXuMv0X5fhAE0eshcUSERGlpKd5//310dXW5p3V3d+Ovf/0rysrKVOwZ0Ws5cz5wxm/V7gVBECkIiSMiJMaMGYOysjJ8/PHH7mkff/wxSktLMXr0aPc0xhieeuop9O/fH0ajESNHjsTf//53AMD+/fsxebJz/Kvs7Gwvi5Moirj33nuRk5ODoqIiLFy4UNaHmpoaXHLJJUhPT4fZbMaVV16JI0eOyNo8+eSTKCwsREZGBm6++WZ0d3crfCSIhKHfJIBPkTIGROyhgGwiDEgcESFz44034q233nJ//9Of/oSbbrpJ1ubBBx/EW2+9hVdeeQU//fQT7rrrLlx33XVYu3YtSktL8dFHHwEAdu7cibq6Ojz3XE8K9jvvvAOTyYRvv/0WTz31FBYtWoTly5cDcIquSy+9FE1NTVi7di2WL1+On3/+GVdddZV7+Q8//BAPP/wwFi9ejO+//x7FxcV4+eWXY3lICCUJNyA7f2hs+kEQRK+HikASIXP99ddj/vz52L9/PziOw//+9z+8//77WLNmDQCgo6MDS5YswapVqzBx4kQAQP/+/fHVV1/htddeQ3V1NXJycgAABQUFyMrKkq1/xIgRePjhhwEAAwcOxIsvvoiVK1diypQpWLFiBX788Ufs27cPpaWlAIC//OUvOOmkk7B+/XqMHz8ef/jDH3DTTTfhlluccSiPPfYYVqxYQdajVOQ3W4D0fLV7QRBEikLiiAiZvLw8XHDBBXjnnXfAGMMFF1yAvLw89/xt27ahu7sbU6ZMkS1ntVplrjd/jBgxQva9uLjYPUzG9u3bUVpa6hZGADBs2DBkZWVh+/btGD9+PLZv3+4VND5x4kSsXr067H0lVCAct0cWxbkRBBE7SBwRYXHTTTdhzpw5AICXXnpJNk8URQDAZ599hj59+sjm6fX6oOvWarWy7xzHudfJGPNZ+NDfdCKFueAZtXtAEESKQzFHRFice+65sFqtsFqtmDZtmmzesGHDoNfrUVNTg8rKStnHZfHR6XQAnOPQhcOwYcNQU1ODgwcPuqdt27YNLS0tGDrUGXsydOhQfPPNN7LlPL8TCUyoIpfS94mIoIBsInTIckSEhSAI2L59u/tvKRkZGbjnnntw1113QRRFnHbaaWhtbcXXX3+N9PR0zJgxA/369QPHcfj0009x/vnnw2g0Ij09eBG/c845ByNGjMC1116LP/zhD7Db7Zg9ezaqq6sxbtw4AMDcuXMxY8YMjBs3Dqeddhree+89/PTTT+jfv7/yB4JQh3k71O4BQRC9ALIcEWFjNpthNpt9znv00Ufx0EMP4YknnsDQoUMxbdo0/Otf/0JFRQUAoE+fPnjkkUdw//33o7Cw0O2iCwbHcfjHP/6B7OxsnHHGGTjnnHPQv39/fPDBB+42V111FR566CHcd999GDt2LA4cOIBf//rX0e8wkRic/CvAXKx2L4hkhVL5iTDgGKMzJlxaW1uRmZmJlpYWmUjo7u7Gvn37UFFRAYOBBsIkYkdKnmu/Lwe6mv3Pf6Ae0Brj1h0ixfjyaWDVo86/F7ao2xdCNfw9vz0hyxFBEInP7d+RMCIIIm6QOCIIIvHJH6x2D4ikh5wkROiQOCIIIrGZf0jtHhAE0csgcUQQROJy+3eAPkPtXhAE0csgcUQQRGJw7pM9f5/9MHDvPnKnEQShClTniCCIxGDk1UDlOUBabviD0BIEQSgIiSOCIBIHU17wNgQRCRSPTYQBudUIgiAIgiAkkDgiCIIgegFkOiJCh8QRQRAEQRCEBBJHhIz6+nrccccd6N+/P/R6PUpLS3HRRRdh5cqV7jZff/01zj//fGRnZ8NgMGD48OF45pln4HA4ZOviOA4cx+Gbb76RTbdYLMjNzQXHcVizZo1Xe47jkJGRgXHjxuHjjz92z1+4cKGsjeszZMgQd5szzzzTPV2n02HAgAGYP38+LBZLwP2eOXOmezmtVovCwkJMmTIFf/rTnyCKoqxteXm5u63RaER5eTmuvPJKrFq1StZu//79sn66xoVbu3at1zGfO3cuKisrYTAYUFhYiNNOOw2vvvoqOjs7A/abIAiCUB4SR4Sb/fv3Y+zYsVi1ahWeeuopbNmyBV988QUmT56M22+/HQCwdOlSVFdXo2/fvli9ejV27NiBuXPnYvHixbj66qvhOVRfaWkp3nrrLdm0pUuXIj093Wcf3nrrLdTV1WH9+vUYOXIkrrjiCqxbt849/6STTkJdXZ3s89VXX8nWMWvWLNTV1WHPnj146qmn8NJLL2HhwoVB9//cc89FXV0d9u/fj88//xyTJ0/G3LlzceGFF8Jut8vaLlq0CHV1ddi5cyf+/Oc/IysrC+eccw4WL17std4VK1agrq4Oa9euhdlsxvnnn499+/YBAPbu3YvRo0dj2bJlePzxx7Fp0yasWLECd911F/71r39hxYoVQftNEARBKAwjwqalpYUBYC0tLbLpXV1dbNu2bayrq8s9TRRF1mGxqfIRRTGs/TrvvPNYnz59WHt7u9e85uZm1t7eznJzc9kvf/lLr/mffPIJA8Def/999zQA7MEHH2Rms5l1dna6p0+ZMoX97ne/YwDY6tWrZe2XLl3q/m61WllaWhq7//77GWOMPfzww2zkyJEB96G6uprNnTtXNu2Xv/wlGzNmTMDlZsyYwS655BKv6StXrmQA2B//+Ef3tH79+rFnn33Wq+1DDz3EeJ5nO3bsYIwxtm/fPgaAbdq0yd3m0KFDDAB79dVXGWOMTZs2jfXt29fnMWeM+f0NfZ1rBEEEYM3vGXvY7PwQvRZ/z29PKJU/xnTZHBj20H9U2fa2RdOQpgvtJ25qasIXX3yBxYsXw2Qyec3PysrC0qVL0djYiHvuucdr/kUXXYRBgwbhr3/9K6666ir39LFjx6KiogIfffQRrrvuOhw8eBBffvklXnrpJTz66KMB+6TVaqHRaGCz2ULaB1/88MMP+N///ofy8vKIlj/rrLMwcuRIfPzxx7jlllsCtp07dy4effRR/POf/8S9997rs01aWhoAwGazobGx0W0x8nXMAaerkSAIBWAUkE2EDrnVCADAnj17wBiTxe94smvXLgDA0KFDfc4fMmSIu42UG2+8EX/6058AON1m559/PvLz8wP2x2Kx4LHHHkNrayvOPvts9/QtW7YgPT1d9vEULS+//DLS09Oh1+sxatQoHD16FL/97W8Dbi8QQ4YMwf79+4O2y8nJQUFBgd+2HR0dmD9/PgRBQHV1tfuYDx4srwKdl5fn3rf77rsv4n4TBEEQkUGWoxhj1ArYtmiaatsOFXbirSoUSwXz8wbGGPO5/HXXXYf7778fe/fuxdtvv43nn3/e77qvueYaCIKArq4uZGZm4umnn8Z5553nnj948GB88sknsmUyMuRjb1177bV44IEH0Nrait///vcwm8247LLLAAD//e9/Zet77bXXcO211wbd31AtOL7aTpo0CTzPo7OzE8XFxXj77bcxfPhwfPvttwC8j/l3330HURRx7bXXBg0kJwiCIJSHxFGM4TguZNeWmgwcOBAcx2H79u249NJLfbYZNGgQAGD79u2YNGmS1/wdO3Zg2LBhXtNzc3Nx4YUX4uabb0Z3dzfOO+88tLW1+dzGs88+i3POOQdmsxkFBQVe83U6HSorKwPuS2ZmprvNu+++i5NOOglvvvkmbr75ZowbNw6bN292ty0sLAy4LsC5vxUVFUHbNTY24ujRo15tP/jgAwwbNgxZWVnIzc11T6+srATHcdixY4esff/+/QEARqMx6DYJgggVcqsRoUNuNQKA0yU0bdo0vPTSS+jo6PCaf/z4cUydOhU5OTl45plnvOZ/8skn2L17N6655hqf67/pppuwZs0a3HDDDRAE/xatoqIiVFZW+hRGkaDVarFgwQI8+OCD6OzshNFoRGVlpfvjaXXyZNWqVdiyZYvb8hSI5557DjzPe4nL0tJSDBgwQCaMAKdonDJlCl588UWfx5wgCIJQBxJHhJuXX34ZDocDJ598Mj766CPs3r0b27dvx/PPP4+JEyfCZDLhtddewz//+U/86le/wo8//oj9+/fjzTffxMyZM3H55Zfjyiuv9Lnuc889F0ePHsWiRYui6qPdbkd9fb3sc+TIkYDLTJ8+HRzH4eWXXw7YzmKxoL6+HocPH8bGjRvx+OOP45JLLsGFF16IG264Qda2ra0N9fX17gDzX/3qV3jsscewePHioJYtKS+//DLsdjvGjRuHDz74ANu3b8fOnTvx7rvvYseOHQGFJEEQYUAB2UQYJI04khbec33uv/9+WZuamhpcdNFFMJlMyMvLw5133gmr1Sprs2XLFlRXV8NoNKJPnz5YtGiR3xia3kZFRQU2btyIyZMn4+6770ZVVRWmTJmClStX4pVXXgEAXH755Vi9ejUOHjyIM844A4MHD8aSJUvwwAMP4P333/cbm8NxHPLy8qDT6aLq408//YTi4mLZp1+/fgGX0el0mDNnDp566im0t7f7bffFF1+guLgY5eXlOPfcc7F69Wo8//zz+Oc//+klUh566CEUFxejsrIS119/PVpaWrBy5cqwA6gHDBiATZs24ZxzzsH8+fMxcuRIjBs3Di+88ALuueeeoBl9BEEQhPJwLEmUQXl5OW6++WbMmjXLPc2V0QMADocDo0aNQn5+Pp555hk0NjZixowZ+OUvf4kXXngBANDa2opBgwZh8uTJeOCBB7Br1y7MnDkTDz/8MO6+++6Q+9La2orMzEy0tLTAbDa7p3d3d2Pfvn2oqKiAwWBQaM8Jwhs61wgiTFY/Aax90vn3whZ1+0Kohr/ntyeJHyksISMjA0VFRT7nLVu2DNu2bcPBgwdRUlICAHjmmWcwc+ZMLF68GGazGe+99x66u7vx9ttvQ6/Xo6qqCrt27cKSJUswb948qilDEARBEETyuNUA4Pe//z1yc3MxatQoLF68WOYyW7duHaqqqtzCCACmTZsGi8WCDRs2uNtUV1dDr9fL2tTW1gasY2OxWNDa2ir7EARBEASRmiSN5Wju3LkYM2YMsrOz8d1332H+/PnYt28f3njjDQDOwTs907Kzs7Oh0+lQX1/vbuNZKdm1TH19vd907SeeeAKPPPKIwntEEARBxI+kiCAhEgRVLUf+RlmXfr7//nsAwF133YXq6mqMGDECt9xyC1599VW8+eabaGxsdK/Pl1vMsyifZ5tQih/Onz8fLS0t7s/Bgwej2m+CIAiCIBIXVS1Hc+bMwdVXXx2wjb8xsSZMmADAOexFbm4uioqK3BWHXTQ3N8Nms7mtQ0VFRW4rkouGhgYAgYsB6vV6mSuOIAiCIIjURVVxlJeXh7y8vIiW3bRpEwCguLgYADBx4kQsXrwYdXV17mnLli2DXq/H2LFj3W0WLFgAq9XqTilftmwZSkpKIh6YlCAIgkgCkiMxm0gQkiIge926dXj22WexefNm7Nu3Dx9++CFuvfVWXHzxxSgrKwMATJ06FcOGDcP111+PTZs2YeXKlbjnnnswa9Ysd7re9OnTodfrMXPmTGzduhVLly7F448/TplqBEEQBEG4SYqAbL1ejw8++ACPPPIILBYL+vXrh1mzZuHee+91txEEAZ999hlmz56NU089FUajEdOnT8fTTz/tbpOZmYnly5fj9ttvx7hx45CdnY158+Zh3rx5auwWQRAEETfIckSETlKIozFjxuCbb74J2q6srAyffvppwDbDhw/Hl19+qVTXCIIgCIJIMZLCrUYQBEEQ0UGhE0TokDgiAAAzZ850l0/QarUoLCzElClT8Kc//QmiKLrbSce4MxqNKC8vx5VXXolVq1bJ1rd//35ZSYbs7GycccYZWLt2raxdfX095s6di8rKShgMBhQWFuK0007Dq6++is7OzrjsO0EQvQFyqxGhQ+KIcHPuueeirq4O+/fvx+eff47Jkydj7ty5uPDCC2G3293tFi1ahLq6OuzcuRN//vOfkZWVhXPOOQeLFy/2WueKFStQV1eHtWvXwmw24/zzz8e+ffsAAHv37sXo0aOxbNkyPP7449i0aRNWrFiBu+66C//617+wYsWKuO07QRAEQbhIipijpIYxwKaSBUSbBoSRhafX691j1/Xp0wdjxozBhAkTcPbZZ+Ptt9/GLbfcAkA+xl1ZWRnOOOMMFBcX46GHHsLll1+OwYMHu9fpqkFVVFSE1157DX379sWyZctw6623Yvbs2dBoNPj+++9hMpncywwfPhyXXXYZkmRMZIIgkgG6nxBhQOIo1tg6gcdLgreLBQtqAZ0peLsAnHXWWRg5ciQ+/vhjtzjyxdy5c/Hoo4/in//8pyyLUEpaWhoAwGazobGx0W0xkgojKVRegSAIglADcqsRQRkyZEjAgXkBICcnBwUFBX7bdXR0YP78+RAEAdXV1dizZw8YYzIrE+AsDJqeno709HTcd999Cu0BQRAEQYQOWY5ijTbNacFRa9sK4Dk+XTjtJk2aBJ7n0dnZieLiYrz99tsYPny4e6gXz/bfffcdRFHEtddeC4vFokj/CYIgKCCbCAcSR7GG46J2banN9u3bUVFREbBNY2Mjjh496tXugw8+wLBhw5CVlYXc3Fz39MrKSnAchx07dsja9+/fHwBgNBoV6j1BEARBhAe51YiArFq1Clu2bMFll10WsN1zzz0Hnudx6aWXyqaXlpZiwIABMmEEOAO1p0yZghdffBEdHR1Kd5sgCEKOoFO7B0QSQZYjwo3FYkF9fT0cDgeOHDmCL774Ak888QQuvPBC3HDDDe52bW1tqK+vh81mw759+/Duu+/ijTfewBNPPIHKysqQt/fyyy/j1FNPxbhx47Bw4UKMGDECPM9j/fr12LFjh3vAYIIgiKg55Tbgp38AVb9UuydEEkDiiHDzxRdfoLi4GBqNBtnZ2Rg5ciSef/55zJgxAzzfY2R86KGH8NBDD0Gn06GoqAgTJkzAypUrMXny5LC2N2DAAGzatAmPP/445s+fj0OHDkGv12PYsGG45557MHv2bKV3kSCI3ooxC7g9+DBUBAEAHKNiMmHT2tqKzMxMtLS0wGw2u6d3d3dj3759qKiogMFgULGHRKpD5xpBEET4+Ht+e0IxRwRBEARBEBJIHBEEQRAEQUggcUQQBEEQBCGBxBFBEARBEIQEEkcxgGLciVhD5xhBEETsIHGkIFqtFgDQ2dmpck+IVMd1jrnOOYIgCEI5qM6RggiCgKysLDQ0NABwjkJPI8sTSsIYQ2dnJxoaGpCVlQVBENTuEkEQRMpB4khhioqKAMAtkAgiFmRlZbnPNYIgCEJZSBwpDMdxKC4uRkFBAWw2m9rdIVIQrVZLFiOCIIgYQuIoRgiCQA8wgiAIgkhCKCCbIAiCIAhCAokjgiAIgiAICSSOCIIgCIIgJFDMUQS4CvC1traq3BOCIAiCIELF9dwOVkiXxFEEtLW1AQBKS0tV7glBEARBEOHS1taGzMxMv/M5RuMQhI0oiqitrUVGRoYiRR5bW1tRWlqKgwcPwmw2K9BDwh90rOMDHef4Qcc6PtBxjh+xPNaMMbS1taGkpAQ87z+yiCxHEcDzPPr27av4es1mM110cYKOdXyg4xw/6FjHBzrO8SNWxzqQxcgFBWQTBEEQBEFIIHFEEARBEAQhgcRRAqDX6/Hwww9Dr9er3ZWUh451fKDjHD/oWMcHOs7xIxGONQVkEwRBEARBSCDLEUEQBEEQhAQSRwRBEARBEBJIHBEEQRAEQUggcUQQBEEQBCGBxFEC8PLLL6OiogIGgwFjx47Ff//7X7W7lDB8+eWXuOiii1BSUgKO4/CPf/xDNp8xhoULF6KkpARGoxFnnnkmfvrpJ1kbi8WCO+64A3l5eTCZTLj44otx6NAhWZvm5mZcf/31yMzMRGZmJq6//nocP35c1qampgYXXXQRTCYT8vLycOedd8JqtcZit+POE088gfHjxyMjIwMFBQW49NJLsXPnTlkbOtbK8Morr2DEiBHuAncTJ07E559/7p5Pxzk2PPHEE+A4Dr/5zW/c0+hYK8PChQvBcZzsU1RU5J6flMeZEary/vvvM61Wy/74xz+ybdu2sblz5zKTycQOHDigdtcSgn//+9/sgQceYB999BEDwJYuXSqb/+STT7KMjAz20UcfsS1btrCrrrqKFRcXs9bWVneb2267jfXp04ctX76cbdy4kU2ePJmNHDmS2e12d5tzzz2XVVVVsa+//pp9/fXXrKqqil144YXu+Xa7nVVVVbHJkyezjRs3suXLl7OSkhI2Z86cmB+DeDBt2jT21ltvsa1bt7LNmzezCy64gJWVlbH29nZ3GzrWyvDJJ5+wzz77jO3cuZPt3LmTLViwgGm1WrZ161bGGB3nWPDdd9+x8vJyNmLECDZ37lz3dDrWyvDwww+zk046idXV1bk/DQ0N7vnJeJxJHKnMySefzG677TbZtCFDhrD7779fpR4lLp7iSBRFVlRUxJ588kn3tO7ubpaZmcleffVVxhhjx48fZ1qtlr3//vvuNocPH2Y8z7MvvviCMcbYtm3bGAD2zTffuNusW7eOAWA7duxgjDlFGs/z7PDhw+42f/3rX5ler2ctLS0x2V81aWhoYADY2rVrGWN0rGNNdnY2e+ONN+g4x4C2tjY2cOBAtnz5clZdXe0WR3SslePhhx9mI0eO9DkvWY8zudVUxGq1YsOGDZg6daps+tSpU/H111+r1KvkYd++faivr5cdP71ej+rqavfx27BhA2w2m6xNSUkJqqqq3G3WrVuHzMxMnHLKKe42EyZMQGZmpqxNVVUVSkpK3G2mTZsGi8WCDRs2xHQ/1aClpQUAkJOTA4COdaxwOBx4//330dHRgYkTJ9JxjgG33347LrjgApxzzjmy6XSslWX37t0oKSlBRUUFrr76auzduxdA8h5nGnhWRY4dOwaHw4HCwkLZ9MLCQtTX16vUq+TBdYx8Hb8DBw642+h0OmRnZ3u1cS1fX1+PgoICr/UXFBTI2nhuJzs7GzqdLuV+K8YY5s2bh9NOOw1VVVUA6FgrzZYtWzBx4kR0d3cjPT0dS5cuxbBhw9w3eTrOyvD+++9j48aNWL9+vdc8OqeV45RTTsGf//xnDBo0CEeOHMFjjz2GSZMm4aeffkra40ziKAHgOE72nTHmNY3wTyTHz7ONr/aRtEkF5syZgx9//BFfffWV1zw61sowePBgbN68GcePH8dHH32EGTNmYO3ate75dJyj5+DBg5g7dy6WLVsGg8Hgtx0d6+g577zz3H8PHz4cEydOxIABA/DOO+9gwoQJAJLvOJNbTUXy8vIgCIKXom1oaPBSv4Q3rmyIQMevqKgIVqsVzc3NAdscOXLEa/1Hjx6VtfHcTnNzM2w2W0r9VnfccQc++eQTrF69Gn379nVPp2OtLDqdDpWVlRg3bhyeeOIJjBw5Es899xwdZwXZsGEDGhoaMHbsWGg0Gmg0GqxduxbPP/88NBqNex/pWCuPyWTC8OHDsXv37qQ9p0kcqYhOp8PYsWOxfPly2fTly5dj0qRJKvUqeaioqEBRUZHs+FmtVqxdu9Z9/MaOHQutVitrU1dXh61bt7rbTJw4ES0tLfjuu+/cbb799lu0tLTI2mzduhV1dXXuNsuWLYNer8fYsWNjup/xgDGGOXPm4OOPP8aqVatQUVEhm0/HOrYwxmCxWOg4K8jZZ5+NLVu2YPPmze7PuHHjcO2112Lz5s3o378/HesYYbFYsH37dhQXFyfvOR1W+DahOK5U/jfffJNt27aN/eY3v2Emk4nt379f7a4lBG1tbWzTpk1s06ZNDABbsmQJ27Rpk7vUwZNPPskyMzPZxx9/zLZs2cKuueYanymiffv2ZStWrGAbN25kZ511ls8U0REjRrB169axdevWseHDh/tMET377LPZxo0b2YoVK1jfvn1TJhX317/+NcvMzGRr1qyRpeN2dna629CxVob58+ezL7/8ku3bt4/9+OOPbMGCBYznebZs2TLGGB3nWCLNVmOMjrVS3H333WzNmjVs79697JtvvmEXXnghy8jIcD/HkvE4kzhKAF566SXWr18/ptPp2JgxY9zp0wRjq1evZgC8PjNmzGCMOdNEH374YVZUVMT0ej0744wz2JYtW2Tr6OrqYnPmzGE5OTnMaDSyCy+8kNXU1MjaNDY2smuvvZZlZGSwjIwMdu2117Lm5mZZmwMHDrALLriAGY1GlpOTw+bMmcO6u7tjuftxw9cxBsDeeustdxs61spw0003ua/3/Px8dvbZZ7uFEWN0nGOJpziiY60MrrpFWq2WlZSUsF/+8pfsp59+cs9PxuPMMcZYeLYmgiAIgiCI1IVijgiCIAiCICSQOCIIgiAIgpBA4oggCIIgCEICiSOCIAiCIAgJJI4IgiAIgiAkkDgiCIIgCIKQQOKIIAiCIAhCAokjgiAIgiAICSSOCIIgQqS8vBx/+MMf1O4GQRAxhsQRQRBJB8dxAT8zZ84Muvw//vGPqPvhKZaUWi9BEOqiUbsDBEEQ4SIddfuDDz7AQw89hJ07d7qnGY1GNboVEjabDVqtVu1uEAQRALIcEQSRdBQVFbk/mZmZ4DhONu3//b//hwEDBkCn02Hw4MH4y1/+4l62vLwcAPCLX/wCHMe5v//888+45JJLUFhYiPT0dIwfPx4rVqwIuU/+1rtw4UKMGjUKf/rTn9C/f3/o9XrQkJYEkdiQOCIIIqVYunQp5s6di7vvvhtbt27FrbfeihtvvBGrV68GAKxfvx4A8NZbb6Gurs79vb29Heeffz5WrFiBTZs2Ydq0abjoootQU1MT0nb9rRcA9uzZgw8//BAfffQRNm/erODeEgQRC8itRhBESvH0009j5syZmD17NgBg3rx5+Oabb/D0009j8uTJyM/PBwBkZWWhqKjIvdzIkSMxcuRI9/fHHnsMS5cuxf9v5w5VFgmjMI4/E0REgzaLaJgyisGJThEMpgEFMXsB1rF5BSpiNBnsEzSJmBRvYYzehGVA3SbjrvvtygfLKv9fe1/OnDPx4cDMcrlUr9f749zf9ZWkMAy1WCzuNQD+b2yOAHyUIAjkOM7DneM4CoLgy+fO57P6/b6KxaLS6bRSqZSOx+Nfb46+ks/nCUbAG2FzBODjGIbxcL7dbr/c/czzPK3Xa41GI5mmqUQioXa7rTAMv/0+yWTy2z0A/DtsjgB8FMuytN/vH+4Oh4Msy7qfY7GYLpfLQ81ut1O321Wr1VK5XFY2m9XpdHpp9rO+AN4PmyMAH8XzPHU6Hdm2rXq9rtVqJd/3H748KxQK2m63chxH8XhcmUxGpmnK9325rivDMDQYDHS9Xl+a/awvgPfD5gjAR2k2m5pOpxoOhyqVSprNZprP56rVavea8XiszWajXC6nSqUiSZpMJspkMqpWq3JdV41GQ7ZtvzT7WV8A78e48cMNAACAOzZHAAAAEYQjAACACMIRAABABOEIAAAggnAEAAAQQTgCAACIIBwBAABEEI4AAAAiCEcAAAARhCMAAIAIwhEAAEDED4DF+afyuBmEAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.Figure()\n",
    "fig.set_figwidth(15)\n",
    "fig.set_figheight(10)\n",
    "sns.lineplot(data=df_rolling, x=\"TotalItr\", y=\"EpRewRolling\",hue='Method')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>Int</th>\n",
       "      <th>EvalAvgRew</th>\n",
       "      <th>Method</th>\n",
       "      <th>EpRewRolling</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10000</td>\n",
       "      <td>-0.000137</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-0.001286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15000</td>\n",
       "      <td>-0.000136</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-0.000136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20000</td>\n",
       "      <td>-0.000083</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>25000</td>\n",
       "      <td>-0.000164</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-0.000123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>30000</td>\n",
       "      <td>-0.000142</td>\n",
       "      <td>COMPER-DDPG</td>\n",
       "      <td>-0.000153</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Int  EvalAvgRew       Method  EpRewRolling\n",
       "1  10000   -0.000137  COMPER-DDPG     -0.001286\n",
       "2  15000   -0.000136  COMPER-DDPG     -0.000136\n",
       "3  20000   -0.000083  COMPER-DDPG     -0.000109\n",
       "4  25000   -0.000164  COMPER-DDPG     -0.000123\n",
       "5  30000   -0.000142  COMPER-DDPG     -0.000153"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_comper_eval_rolling_avg = pd.DataFrame(df_comper_eval[[\"Int\",\"EvalAvgRew\",\"Method\"]])\n",
    "df_comper_eval_rolling_avg[\"EpRewRolling\"]=df_comper_eval[\"EvalAvgRew\"].rolling(2).mean()\n",
    "df_comper_eval_rolling_avg.dropna(inplace=True)\n",
    "df_comper_eval_rolling_avg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>Int</th>\n",
       "      <th>EvalAvgRew</th>\n",
       "      <th>Method</th>\n",
       "      <th>EpRewRolling</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10000</td>\n",
       "      <td>-0.008570</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-0.019917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15000</td>\n",
       "      <td>-0.000978</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-0.004774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20000</td>\n",
       "      <td>-0.001195</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-0.001086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>25000</td>\n",
       "      <td>-0.000072</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-0.000633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>30000</td>\n",
       "      <td>-0.000151</td>\n",
       "      <td>DDPG</td>\n",
       "      <td>-0.000111</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Int  EvalAvgRew Method  EpRewRolling\n",
       "1  10000   -0.008570   DDPG     -0.019917\n",
       "2  15000   -0.000978   DDPG     -0.004774\n",
       "3  20000   -0.001195   DDPG     -0.001086\n",
       "4  25000   -0.000072   DDPG     -0.000633\n",
       "5  30000   -0.000151   DDPG     -0.000111"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ddpg_eval_rolling_avg = pd.DataFrame(df_ddpg_eval[[\"Int\",\"EvalAvgRew\",\"Method\"]])\n",
    "df_ddpg_eval_rolling_avg[\"EpRewRolling\"]=df_ddpg_eval[\"EvalAvgRew\"].rolling(2).mean()\n",
    "df_ddpg_eval_rolling_avg.dropna(inplace=True)\n",
    "df_ddpg_eval_rolling_avg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Int', ylabel='EpRewRolling'>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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y8nLS6TQAX/nKV/je9763x/vuK0mGhBBCiHY7RpF6MxLR04iT53nd3v7zn/88119/PWs/WMNDv3+Yn//ou13qhDr73BcuRNM0UqkUsViMH373Lk4/7dSO66dMnsyTf328y22KiiJdfv6fz53Ht6/7f7S2tfK9H/6EaLSIz3zqkwC8+p//cvrZn+o49v5f/pL/mT9/j4+3tyM03R171FFHoaoqyWSS6upqHnroIWbMmMGiRdlaqI8e/8Ybb+C6Lv/zP/9DJpPp1f32lSRDQgghBlzQ0Fh+26l7PnCA7ru39t9/fxRFYcWKFXzyk5/s9pjJkycDsGLFCo466qhdrl+5ciXTp0/f5fKysjLOOussvnjJJaTTaU4//XTa2uLd3sdPfvA9TjrheKLRIiq6GT3y+QwmTZq428cSi0Y7jvnjQ7/lgEOO4LcP/p4vXnQBRxx+GO+88TrggWtTOXL0HvsPrVixgvHjx+/2GICGhgbq6up2Ofaxxx5j+vTpFBcXU1ZW1nH5pEmTUBSFlStXdjl+woQJAASDwT3e576SmiEhhBADTlEUQj49J197U29SWlrKqaeeyr333ksikdjl+ubmZk455RRKS0v50Y9+tMv1Tz75JGvWrOFzn/tct+e/+IL5vPzKv/nC589H283UVFVlJZMmTew2EeoLwzD41nXf4Du33EoymSQYDDJp0kQmTZrEpP0nUxT07bZ+6MUXX2TZsmV85jOf2eN9/exnP0NV1V2SyTFjxjBx4sQuiRBkk8STTz6Ze+65p9vf+WCQZEgIIYTo5L777sNxHGbOnMlf//pX1qxZw4oVK/j5z3/OnDlzCIfD3H///fz973/nsssuY+nSpaxfv57f/va3XHjhhXz2s5/l3HPP3fXEjsVpJx5L3eZ13HbzjfsUo23b1NTUdPnavn37bm9z/rzzUBSF+371665XKGq2x5GdAc8lk8lQU1PDli1bWLx4MXfddRef+MQnOOuss/jCF77Q5aZtbW3U1NR0FIRfdtll3HHHHdx5551MmjSp14/nvvvuw7ZtjjjiCB577DFWrFjBqlWr+OMf/8jKlSvRtAHoyt2JTJMJIYQQnYwfP57Fixdz55138vWvf51t27YxYsQIDj/8cH75y18C8NnPfpaXXnqJu+66i2OPPZZUKsWkSZP49re/zde+9rVdR6NcF+w0iqJQPmLfR3veX76C6rFdp8n8fj/p1sYeb+Pz+bjyy5fz/R//hMsvu6RTjyOytUueBa7DggULqK6uRtd1SkpKOPjgg/n5z3/OBRdcgKp2HUO56aabuOmmm/D5fFRVVTF79mxeeOEFjj/++L16PBMnTmTJkiXcdddd3HDDDWzevBm/38/06dP5xje+wRVXXLFX59tbirc3aw6HodbWVmKxGC0tLUSj0VyHI4QQeS+dTrNu3TrGjx9PIBDIdTi553lgpbLTUAO23UZ/8Nq3BPGBEcxuGJvndvdc25v3bxkZEvsuXguZOIRKIFBcEH9AQggxaByzABIh6Og/5JjZaTPdn+uABo0kQ6LvXAea1kP9GnAyoPkhXA7RkRAqG1Z/SEII0S2nfS+w9n3H8l7n+qFe9h8aCobHoxT9z0xmk6DmjRAqBl9l9o8n2QCt28BflE2KIiNktEgIMTy5TjYRgh77CeWlHfVDdhqUULY54xAnyZDYe4kGqFsBqSYoqmwf+iU7EhSpAM/NTpvVr4bGtdlRoh2jRUb+1g94nofjeuja0P/DF0IMMM/LfkB0nZ2vkYVE1XeOahVI/dC+kGRI9J7rQsumbJLjORAd1f0fiKJCIJr9sjOQaoR4DfjaR4vC5dnRojz5tJEyHZqSJrWtaZKmQ2U0QHnETzS4d/1JhBCiQ0edkE5BTI/tYnjVD0kyJHrHSkPDB9kaIX9RNtHpjW5Hiz7sNFpUnpPRItN2aU6Z1Mcz1LeZJE0bv65haCof1LWxvjFBWchHZSxASchHYC862AohhrkudUL58aGvT4ZR/dDQfWSi/6SaoG5VdtVYpKJvnxB2GS1qgvh28EWgqDp73gEeLXJdj5aURUMiQ21rhnjGRlUUIn6d4liwYxQoFjTI2A6NCYua1gyRgE5V1J8dLQoYqGohfsoTQgyKQq0T6skwqR+SZEj0zPOgdQvUrc7+IURHtn/S2Ucdo0UemHFo/AAa10G4NDv1FirLzlH3A8/ziGdsmpMWNa1pWpIWjusR9utUFAXQekhs/LrGiCIN1/NIZGzW1iVY35CkLOyjSkaLhBDdKfQ6oZ4Mg/ohSYZE92wzW/zc+GH2yR+t7v/7UJTslJu/KDsvnW6Btu3ttUVVEKns82hR2tpRB5ShKWGSdhyCuk5p2IexFwXSqqJQFDAoChjZqbWkRW1bmrBP76gtigVltEgIwRCoE+rJ0K8fkmRI7Crdmq3tad2aLXbup1Ga3dJ8EB7RabToQ2hcn23kGB3VqzgsJ5usNMQz1MUzJE0bQ9UoCuiUGfv+x+vTVcojfjzPI5FxWFufYENDkpKwQXUsSGlYRouEGLYcOzsqVOh1Qj0Z4vVDQ/BfTOyTthrYuiS7+itaPTiJUGc7Rouio7LTZpk22PoObFgItSuyy/pdt+Nw1/VoTpp8WBvnrXVNLNnYxOamFLqqUh0NMqLI3+8JiqIoRAI6I9sToLaUzbLNzby5vpHVNW00JkxcV3a5EaIQXXjhhSiKgqIoGIZBZWUlJ598Mr/73e9wO732jBs3ruO4YDDIuAkTOfd/LuDFl1/tcr716zeg+MMdXyWVozj2xFN45d9dj6upqeHqa7/BpGkzCERLqRwzjqOPP4lf/fo3JJPJQXnse6RogJedLuv0uxgKJBkSWY4N9R9kEyHHhKKR2WHRXNJ82RGh2CjQtOy03aZFsOkNErXr2by9nsUbm3hrQxMf1LXheB4VRQEqowEi/sFZFm9oKmURP9WxILqqsq4hweINTSze2MSW5hQp0xnwGIQQ/eu0005j27ZtrF+/nn/9618cf/zxXH311Zx11lnYtt1x3G233ca2rVtZtewdHv7NfRQXF3PS6Wdx53e/v8s5n//X02zb8CGvPL+AaFERZ3zi06xbtx6AtWvXceiso3j2+Re56/ZbWLLoNZ7/19Ncc9WVPPWPf/L8Cy8N1kPfM1UH184mRENoa9OhNc4l+sZMZKfFWjZDsAR84VxH1FX7aFFGC9OWSNG6tYZE4gPS+CFSRUVJNUq4tH+Ku/scYnZVWsSvYzkurSmLZZubCfl0Kor8jCjyUxzy9ViwLYTIH36/n6qqKgBGjRrFYYcdxuzZsznxxBN56KGHuOSSSwAoKiqiakQpFAfZb8wojp17PNXV1dx06+189lOfZMqUyR3nLCsrpaqqiqqqKu6/9xeMnrA/zz7/Al+69ItccdXX0HWdt15/lXB45+vvjAMP5DOf+iT5tZ/60KwfkpGh4S5RD1sWQ/PmbMFyniVCtuvRlLRY35Bg+dZWVtenqXeLUKKjKY0VMcLeRlH9EkLb38Zo24xi5X44ecdo0chYEJ+msrExyZKNzSze2MTmpiRJ097zSYQYajwv+8ErF1/9kEyccMIJHHzwwTzxxBM7L3SdnXVCSvbt9Oorr8DzPP7+1NM9nisUypYfWJZFQ0MDzz7/Al+5/LIuiVBnedf8tXP9kDM0Xs9kZGi4cl1o3pBtpOi52amoPPmDc11ImDatKYvGpEkik/1jCxk65RF/R5guYVwjDK6FZrYRqH8PzwhiBSuwQxU4/uKcjxaF/Trh9tGitrTNe1taCfpUKor8VBQFZLRIDB9WEu4amZv7/tbWfvmgN3XqVJYuXbrzAtcGPFB2vpWWlpZSUTGC9Rs2dnuORCLBDd+5GU3TmHvs0Xzw4Vo8z2PK5MldjisfuR/pdLZf0Vcuv4zv3XXHPsffr4ZY/yFJhoYjK92+yeqGvesmPcBSpkNr2qIxYdKWsXEcj4ChURLy7/7vTDVwAqU4fg/VTuKLb8KIb8L1FWNFqrEDZXhGaNAeR3cMTaU07MPzPFKWw+amFJub0sSCesdKtLBf/hyFyGee52VHaTwP8LIfJLuprew4rpOj5p6Iqqokk0mqq6t46Df3M+PAA1n0xpsAKB9Ziv/Gf17BdV3+58KLyWQyA/aY9skQ6j8kr77DTbIx2006Udf3btL9yGwfMWlMmLSmLDK2i09TKfIZ6Ppe/mEpCq6xY7TIRjNbCdS/3z5aNKJ9tKgk56NFIZ9OyKdjtz/25VtbCRgqI4r8VEQDFAcN2SxWDD1GKDtCk6v77gcrVqxg/Pjx2XoZz2ufGuv6OtXQ0EBdXT3jx43tcvljf3yY6dOmUlwco6ysrOPySRMnoCgKK1evAj7ecfmECeMBCAYHeUXvXlGyS+yHQP2QJEPDRUc36VXZhoqxUR1z3IPNdj3iaZuW9mmwtOWgoRD0a0SD/dS1VdWzo0UBUK0kRnwzvvgmHF8JVqQaJ1CaTZpySNdUSsI+SoCkabO1Oc2W5hRFAYNRxUFKwj4iMlokhgpFybuaxL3x4osvsmzZMq65+qpsrQwK3TVW/Nk996GqKp88++NdLh8zZhQTJ07Y5fiysjJOPvEE7vnl/Xz1ii/3WDeUvzr3H1ILtvO2vNIOB7bZ3sRwbfYTUrRq0EPwPIibNm0pi4aESSLj4OERMjTKwv4BHV11jRCuEWofLepcWzQCJ1iBHSjJeRuBHaNFjuvRmrZ4f2sLAUNjRCQ7WlQSktEiIQZLJpOhpqYGx3HYvn07CxYs4O677+asM8/kC587h2ydELTF49TU1GBZNuvWr+eP//sov3nwIe6+41YmTZrY6/u77+c/5WPHn8gRc47hlhu/xUEHHoiqqrz59tusXLWKww89ZMAea7/oUj+k5nT0va8kGRrq0q3Z0aC2bYPXTbqTlOV0TIO1pS2s9jqg4qCBpg3y/LKq4wRKcAIlKFYSI74FX3wzji+GFRmJ4y/F9UUGN6aP0FSFkpCPkpAvO1rUkh0tigYNqmMBSsM+igKF+clLiEKxYMECqqur0XWdkpISDj74YH7+s59xwf+ch+paoGb/Bm+69XZuuvV2fD4fVVWVzJ45kxcW/IPjj5u7V/c3ceIElix6jbu+90Nu+M7NbN6yBb/fz/RpU/nG167missvG4iH2b866ocyBVk/pHj51cAg77S2thKLxWhpaSEazY9C417xvGw36bpVYCWy9UGDNPphOR5taYumhElz2iJjORiaRtinYeh5NrrhOmhmK6qVxDOC2IFy7NAIHH8xnpYf89+Om/19JkybgKFRHvFTEfVTEtq7fdaEGCzpdJp169Yxfvx4AoFArsPpH3YGrFT2dTRHJQb5z80utTeCg1Y/tLvn2t68f8vI0FDk2Nld4Bs+AN3I7jY/0HfpQjxj05oyaUiYpEwbVVEJ+TWifiN/9yxUtS6jRXpiG0Z8C64RxgpV4ATKcr5EX1MVikM+ikM+UqZDTUuarc0pogGDqpif0oifokHquC3EsNSx75gqidBu7agfShdc/ZAkQ0PNjm7SzZsgVDooBYttaZuNjUniaRsXj6CuURYJFNooKZ4RwjZC4LmoVgJ/yzq8lvW4/ih2qAo7UILri+Z0+Dfo0wj6NBzXI56xWbmtjYCRpDTioyqa7Vvky7fRNyEKmevu3HpCLZw395xRtGzLgQKrH5JkaCiJ10HdSki3QFHVoGXl9fEMrSmL4pAPfbDrgAaCouL6inB9RR1F1/7Glfg0H44/hh2uwvEX53Q1mqYqxIIGsaBB2nKoa82wrX0lWnUsQFmRn6jUFgmxbzwPnEy2uWIBjXLkXAHWD0kyNBS4DjRvzDZSxMtOiw3Sky9juzQnLcJ+fWgkQh/VuejayaCaLQRSdXh6IFtfFCzHCZTktL4oYGgEjJ2jRau2x/E3JKiMBqiOBSkOGTKFJkRf7HhDV3Xyd64/HxVe/yFJhgqdlcruNt+8IdtJ2l80qHfflrZJWQ4jIvn/ZN9XnubHCfpxIFtflKzpqC+ygxXYwTIcfyxny/Q/Olq0pTnF1pY0IyJ+RpUEKQ35UGXrDzGICnp9zo6d2RWpE+qbwakf6q/nmCRDhSwPukk3JU10VRl2H5q61hcl8bWuw9e2DseIYoc71xfl5kU0YGhUGUFM26WuLUNtW4aysI9RJUHKwj7pWSQGlGFk3/iSyWSed1Dugedmty3yPJke2xeDUD+UTGY3597xnOsrSYYKketmu0nXr8oOQ+aom3TKdGhJWYR8w/hppKi4vki2P5HroFlt+JtW41N1XH8MK9ReX5Sj/kU+XaUyGsBystOZdW1pSsI+RpeEKI/4pdhaDAhN0yguLqa2thaAUChUOFO1nte+G7uZHeW13FxHVOA8cDOQscEI9FsJh+d5JJNJamtrKS4uRtP2LdEqmHexpqYmrrrqKp588kkAzj77bH7xi19QXFzc422eeOIJ7r//ft5++20aGhpYsmQJhxxyyOAEPFDsDDS0d5P2hyFUnbNQWtMWpu0S668tNAqdquH4i3H8xSiOiWq2EUjW4+l+7EBZ+95oxXj64PddMbTs3meO69GSsli2pZlYIDtSNKLIT8AojBUfonBUVWU73e9IiAqGa2drhRS1IAp/C4LngeeA6svWEvWj4uLijufaviiYZOj8889n8+bNLFiwAIDLLruM+fPn89RTT/V4m0Qiwcc+9jHOOeccLr300sEKdeCkW9q7SddAZATk4E11B9eFxoSJT6ZbuuVpPpxgWba+yE6hp2rxJbbi6GHs0Ihs4bU/NuhLdTVVoTTsw/UMWlMW729tJRLQGRULUBENEJa90EQ/URSF6upqKioqsCwr1+H0TroVti8Hg2wNpug/ZhKsJqiYDuHSfjmlYRj7PCK0Q0G88q1YsYIFCxawcOFCZs2aBcADDzzAnDlzWLVqFVOmTOn2dvPnzwdg/fr1gxXqwPC87HYadauyfYSiI3PeuyFh2rRlbIp8Miq0J54exNaD4HmoVgJf20Z8rRtwfEXYocr2xo6DW1+kKtlGjrGgR1vaZtX2NjY2JRkZC1IZC8iyfNFvNE3rtzesAWWb0LYOvAQUDXyj2mFHj0A8Ca0fQlEs7zbtLYhk6PXXXycWi3UkQgCzZ88mFovx2muv9ZgM9UUmkyGTyXT83Nra2m/n7hPH6tRN2petD8oDbWkL2/HQdRlG7jVF+Uh9URx/8wd4yjpcXxQrUt3evygyaMPziqIQDRpEgwbxjM2HdXG2NKWojPmpjgWJBWVZvhgGPC+7mXXb9kHp2D9shUdAy5ZsG5iqGTn/UN9ZQSRDNTU1VFRU7HJ5RUUFNTU1/Xpfd999N7feemu/nrPPMvHsaFDrFgiVgS+U64gAsF2PhoRJUOpM+k7VcPwxHH8MxbFQrTYC9e9l+xf5S7DDlTj+kkGtL4r4dSJ+nZTpsKmx07L84iAlsixfDGWtW7N1mOHyvHqDHnIUBYoqszsk+KNQNiHXEXXIacHHLbfcgqIou/166623ALr9dOp5Xr9/ar3hhhtoaWnp+Nq0aVO/nr/X4rWwdQm0bYVodd4kQgDxtE0i40gy1E88zcAJlGIVjcIxwujpeoK17xKqeQN/wwr0ZB24g1dzEfRp2VGhgEFta4YlG5tZurmZ2tY0jlvAfWOE6E66BepWZzslGwXYBqDQaAYEY9CwJrtrQp7I6cjQlVdeybx583Z7zLhx41i6dCnbt2/f5bq6ujoqKyv7NSa/34/fn8MGgq4DTRuyTxSA6Ki8W9HQmrbw8NCGYsfpHPP0ALYeyNYX2UmM+CZ8bRtxjSKscCVOoBTHFx2UT69+XaMyqmE5Lg0Jk9q2TPuy/CDlET+GFM+LQmeb2dF3OynTY4PJX5RtGFy3MvtBPw/qh3KaDJWXl1NeXr7H4+bMmUNLSwtvvPEGM2fOBGDRokW0tLRw1FFHDXSYg8dKZT+hNG/MZs6D3E26N8z2N8aQjAoNLEXBNcLZ/c88B9XcUV+k4vpiWJEqHH/JoNQXGZpKRVEAx/VoTpq8u6mF4pDRkRTJsnxRkDrqhGqyo+9icHXUD62Gyhn9vuR+bxVEzdC0adM47bTTuPTSS7n//vuB7NL6s846q0vx9NSpU7n77rv51Kc+BUBjYyMbN25k69atAKxatQrI9r/oj74E/SrZCLUrIVmfnVPVfLmOqFvxtE3atCmL5G5Z/7CjaLj+GK4/Bq6FZsYJ1r+Pq/ux/aU4oQrsQAmePrBD/JqqUBbJ9ipqTVu8t6WFooDBqOLssvxh3XxTFJ62bdnFKeHynG2hM6x11A9tBn8s5/VDBfMMeOSRR7jqqqs45ZRTgGzTxXvuuafLMatWraKlpaXj5yeffJKLLrqo4+cdU3I333wzt9xyy8AH3RuuC62bs0O1rp2zbtK91ZQwURQ132buhg/V2LlxrJ1GTzdgJLbhGWGsYBlOcES2seMAJtOaqlAS8lEcNGhN26zc3sbGxhQjiwNURgMUDcSy/D3tP7TH/YlyffsCMtB/3Pnwu7IS2ddc3S91QrmkGRAqzpaFBKLZxDRHFK+gd9IbeK2trcRiMVpaWohG+7kJl21mlxg2r8/OmwaK+/f8/Sxtuby/rQWfpsrUSD5pry9SzTYUz8M1ItjBMryPJNVKx5961/9nL+/8MuB95MePXt/1HJ7nkTYd4hkbv65QFvJRFvER8WvtW9Z95LadX3K6nPsj97PbV6YBTk72OTnat7vvk+H+AWWvfuceWMm8aVUy7DVvhqoDoLR/R4f25v27YEaGhqT49uycdY67SfdWW9rCtByifmnIl1c+Wl9kJTDaNpF9d1B2OXYPJ+vx2F3fa3ZeHwEifoWM5VDf6NDcDLGgn9KwjyK/vuuy/F3i+Oj1e4htr67r7v724KPH783vba+vz7fPowMRT75lagoEi3MdhNghD6YaJBnKJc/NrgoqgETI87Lbb+iqln+va2InRcP1RXF9udlKQA9ADDBtl9q0TW0LlIR9lBf5iAV8yAI0IUQ+kmRI9ErSsmlNW4Rk7yrRCz5dpTTiw3Y8mhMmDYkMsYBBRTRALGRgSANHIUQekXc20SttaRvLcfHp8tFe9J6uKZREfDiORzxjs6a2jYhfpzIaoDhkyEa/Qoi8IMmQ2CPXhYa4SUCXp4voG01TiIUMXBcSGZsPatsI+3QqogFKQj4ChiRFQojckXc3sUfxjE08bRMNSuG02DeqCkVBnYink8jYrKuPU2PolEf8lEV8hHyySlEIMfgkGRJ71JKycHHRZfsN0U8UBSKB7MawSdNmU2OC2rY05RE/pZHsCjQhhBgs8oojdstyPZoSMkUmBogCIb9OyK+Tthy2NqeobUtTFvZRHglQFNDzYdWtEGKIk3c4sVvxtE3CsikN5XDzWjEsBAyNgKFll+W3ZaiLm5SEssvyowEDXVagCSEGiCRDYreakyYK2VoPIQaDT1cpi/ix7Z3L8osCOhVFAWJBA7+saBRC9DNJhkSPMrZLc9KSDThFTuh6dlm+62aL+D+sbSPg0ykP+ymJGETkeSmE6CfyaiJ61Ja2SVkOIyIyRSZyR1UhGtTBay+2bkqyvVWlNGxQGvYTDRgycimE2CeSDIkeNSVNdEWR7TdEfuhUbJ2xXOraTOraTKJBnfIiP8VBH4aseBRC9IEkQ6JbKdOhJSXbb4j85DdU/EZ2u494xqYpGSfi1xhRFKA4aBCUfkVCiL0g73SiW61pC9N2iUmjRZHHdE2hOGTgednO1usa4vh1jdKQj/KIn4hfluYLIfZMkiGxC9fN7lAv+0aJQtHRxBGdtOlQ05qmti2TXZof8RENytJ8IUTPJBkSu0hYNm0ZmyKfjAqJwhPwaQR8GpbtdizNj/h1Kor8FId8sjRfCLELSYbELtpSFrbjoevySVoULkNXO5bmJzI2H9bFCRo65REfJRGfLM0XQnSQVwPRhe16NCRMAoYUoIqhYcfmsEWdlubXtKYpCfkoi2SX5suMsBDDmyRDootExiGRcSiWwmkx1HRamm/aLg1xk/q4STSgMyLqJxY0pE5OiGFKkiHRRUvKxMNDk34tYgjz6SqlkezS/ETGZs32OGGfxogiPyUhnyzNF2KYkWRIdLAcj8aESUimyMQwoWsKsU5L89c3JNjWkqY07KMs7KcoIEvzhRgOJBkSHdrSFinTpiwSyHUoQgyqjqX5AZ20JUvzhRhuJBkSHZqTJoqiyidhMawFDI2AoWHbHs1Jk4Z4mkjAYET7lh8BQ+qKhBhqJBkSAKQtl+aUTdgvU2RCAOi6QonevjTftFlblyBopCmP+CgOZ5fmywcHIYYGSYYEkJ0iS1s2RX6ZIhOiM1WFooBOkV8nZTpsbpal+UIMNZIMCTwPmpIWhqrJDvVC9ESBoF8j6Nc6Lc3PEG2fQouFZGm+EIVKkiFB0rJpSZmyQ70QvbRjab7jeMQzNh/UtRE0dm75EZKl+UIUFHn3E7SlbSzXxSd7NgmxV7SOpflGx9J8f0ua0rBBaThAkV9HlT8rIfKeJEPDnOtCQ9zEr8lTQYi+2nVpfobaVpPikEF5kZ9o0MCQpflC5C15BxzmEqZNPG0Tle03hOgXHUvzHY/WlE1jIkMkYDCqJEhJ0Ccr0ITIQzKAO8w1Jy1cXHTZfkOIfqVrCsXt02UZy2XN9jibm5JYjpfr0IQQHyHJ0DBmuR5NCZOALgOEQgwUVYVYyCDk09jUlOTDujhtGTvXYQkhOpF3wWEsnrZJWDalIX+uQxFiyAsYGj5NoymZIWHajCkJUR72S4G1EHlA/gyHseakiQLyYizEIFFVKIv4UVH4sC7O+oY4acvNdVhCDHsyMjRMZWyX5qRFyJCngBCDLRLQCdgaNa0ZEqbD6JIQJSFZxCBErsiYwDAVz9ikLIeANIcTIid0XWFExE/acllT28amxhSWK8XVQuSCJEPDVGPCRFcUWeYrRC4pUBwyCBoam5sSrK2NEzeluFqIwSZzJMNQynRoTVmy/YYQeWJHcXVjMkPSdBhdEqRMiquFGDTybjgMtaYtMrYrjRaFyCOqCuURP/G0zQd1ceIZi5HFIfyyTY5oZ7keGdvBtFzSlkPCdCgJ+SiP+HIdWsGTZGiY8bzsFJnsri1EfooEdPy2yraWdLa4ujhEsRRXDzudE5+UmU18kqaN6bjYjpddCawoNCdNVDVCaUgSon0hydAwEzdt4hmbiE9eXIXIV4auUh4J0Jw0WVPbxqjiIBXRALrsbzYkWY5H2nYwbZe06RDPOCQtG8txcdqL6g1VxaepFPmNLjsGtCQtNtQn0UeoRIPylt5X8psbZtpSFpbjoevyoipEPlMUKAn7SJkOGxoTxDPZWqKQrAAtaB9NfNraV/ZmEx8XULKJj64S+Eji051YyKAxbrKhMcGEEWHCPnlb7wv5rQ0jjgsNCZOAIS+mQhSKoE/Dp6k0xHd2ri4Ly4avhcByPNKWQ8bO1vi0ZSzSpovpuLje3ic+PSkN+6hPZNhQn2RiRUTqzPpAkqFhJJ6xSWQciqVwWoiComkK5UV+2tI2H9S20RYNMKokKLV/ecR0XDKWS8bO1vjEzU6Jj+uCkk18/LpK0DDQ+nNzbAXKwn7q4xk2NCQZXx7GkM2394okQ8NIS8rEw+vfP0IhxKApCuiYtsq2lhRJ02FMSUjqRHJgR+KTtp3sVFfaJmO7mLaLS7a42dA0fJrS/4lPDxQFSkM+6uJpdBXGlkWQXLn35K9omLAcj8aESVCXKTIhCpmvvbi6KWGyensbo0qCVBQF5I1vgOxIcnqT+IRCvpz2htI0hdKgn+1taQxNZVRxSHpV9ZIkQ8NEW8YiZdqURQK5DkUIsY8UBUojPlIZh3X1CeIZm9HFQYJSXN1nnpcd8THb63tSlkM8bZO2XayOxEfBp6kYukLIl9vEpye6rlDk97G5OYWuqVTH5DW/NyQZGiaaEyaKokrRpRBDSNCvYegq9fE0iYzNmNIQpSEprt6THYlPtsYnm/jsGPHpLvEJ52ni0xO/oeJ6Ohsbkuhadg88sXuSDA0DaculOWUTlk+NQgw5uqZQHg7Qmrb5YHuc6uIA1bGgFNB+hOdB0rJpS9s0JUySloNle3ieh6Io+HQVQyu8xKcnQZ+G43psaEiiqyol0rhztwrmn7ypqYn58+cTi8WIxWLMnz+f5ubmHo+3LIvrrruOGTNmEA6HGTlyJF/4whfYunXr4AWdJ9oyFmnLliX1QgxVCkSDOmG/zuamVHbFWVo2fPU8SJoO21vTrNrexvKtrayti5PIOPg0NbuVRZGfsoiPooBOwNCGRCK0QySggwfrGxLyfNiDgvlnP//883nnnXdYsGABCxYs4J133mH+/Pk9Hp9MJlm8eDE33ngjixcv5oknnmD16tWcffbZgxh17nkeNCUsDFUD+aAoxJDmN1TKwn5aUzart7dR05rGcXMd1eBLmQ51bRnW1MZZvrWVD+sSxNM2IZ/OiKIAsZAx5BKfnsRCBqblsr4hQcp0ch1O3lI8z/NyHcSerFixgunTp7Nw4UJmzZoFwMKFC5kzZw4rV65kypQpvTrPm2++ycyZM9mwYQP77bdfr27T2tpKLBajpaWFaDTa58fQraYNsP09iI7s3/N2kjBtVmxtyzZuk0ZcQgwbibRN0rKpKMr2JAoO8ZHhlOUQz9g0JSxa0xam7WBoGiF57QMP6uMZikMGE0bkYVPGli1QOR1KJ/Traffm/bsgaoZef/11YrFYRyIEMHv2bGKxGK+99lqvk6GWlhYURaG4uLjHYzKZDJlMpuPn1tbWPsedD9rSNqbrENNlvliI4SQc0PEbGrVtaVKmw6jSICXBoVVcnbbcbAKUNLMJkOWgqxpBn0ZMmsvupEBp2E9DPM1GLcm48jCG7HPXRUEkQzU1NVRUVOxyeUVFBTU1Nb06Rzqd5vrrr+f888/fbYZ49913c+utt/Y51nziutAQN/FrBfHPLIToZ9mVRAFaUhZrtscZGQtQVRws6DfCjN2eACVMWtM2GdtGU1SCPo2o35BygB6oKpSE/dS1ZdBV2K9UmjJ2ltNfxS233IKiKLv9euuttwBQuvk4s2MVwJ5YlsW8efNwXZf77rtvt8fecMMNtLS0dHxt2rSpbw8uDyTad6gf0I0dPZdAw/soVnLg7kMI0XdKtm4k5NPY1JTkw9o4bZnCKqbN2C6NCZO1ddkaoFU1bTTETYz2lXQlYV92gYgkQrulawrFQYNtLRm2NqfI/yKZwZPTIYMrr7ySefPm7faYcePGsXTpUrZv377LdXV1dVRWVu729pZlce6557Ju3TpefPHFPc4b+v1+/P6h0ZOhOWnhem6fN//bI89jxNL7KV73DzJFY9h8zA9wfZGBuS8hxD4JGBo+TaMpmSFpOowuCVIe9udtEbHpZEeAWpImzUmbtO2goBD2adm+OZL49ImhqxQFdDY3JzF0haqoNGWEHCdD5eXllJeX7/G4OXPm0NLSwhtvvMHMmTMBWLRoES0tLRx11FE93m5HIrRmzRpeeuklysrK+i32fGe5Hk0Jk4A+cP/EZSv+QPG6fwDgb9tE9aI72HrU7XiazNULkY9UFcoifuJpmw/r4sTTFqNKQnlTUGs5XjYBSpk0JS3Spo3aPgVWFvYPqXqnXAoYGq7rsbEx24OoPOLLdUg516d3yqVLl3Z7uaIoBAIB9ttvv34dXZk2bRqnnXYal156Kffffz8Al112GWeddVaX4umpU6dy991386lPfQrbtvnsZz/L4sWLefrpp3Ecp6O+qLS0FJ9vaP/jx9tXkpSEBmaUq2TNXyhd/TgAjft/lti6fxJqeI/KJT+l5vCvg5IfL65CiF1FAjoBW6OmJU3CdBhdEspZUz7L9YinbdrSFo0Jk5TloAAhQ6csEpAEaICE/DpO2mZDYwJdVSge5k0Z+5QMHXLIIbut1TEMg/POO4/777+fQKB/huAeeeQRrrrqKk455RQAzj77bO65554ux6xatYqWlhYANm/ezJNPPtkRb2cvvfQSxx13XL/Ela+akybAgAyBR9cvoPz9hwCoP+BCmvb/LMkRhzDq9Zsp2vwKVnAEDQdc2P93LIToN7quMKIoQHPKYk1tGyNjQSpjgUEprra7SYA8IKhrlIbyd+puqCkK6DQnLNY3JJioRSjyD9/FNn3qM/T3v/+d6667jm9+85vMnDkTz/N48803+dGPfsTNN9+Mbdtcf/31nHfeefzwhz8ciLgHTSH2GcrYLsu3tqIpCkF//xZPRza/QtVbP0TBo3HyOTRMv6DjuqKNL1C1+CcA1B58BS3jz+jX+xZCDIy05dCWtigL+xldGiTs6/83Rdv1SGQcWlMWzUmThOng4RHQNUI+XRKgXPGgMWESDmhMHBHJTT+qQu0zdOedd/Kzn/2MU089teOygw46iNGjR3PjjTfyxhtvEA6H+frXv17wyVAhimdsUpZDeT9vzheqeZOqt3+Mgkfz+DNomPaFLte37XciRrKWspWPMOLdX2EHykhUz+rhbEKIfBEwNAxVpTFpdhRXl/VDcbXjQiLTPgKUNElmHFzPI2BolISGxh5gBU+BkrCPhkSajQ1Jxo8I4xuGa+779IiXLVvG2LFjd7l87NixLFu2DMhOTW3btm3fohN90pgw0RWlX+fag/XLqH7jbhTPoXX0XOoOupzu7qBxyjxaxp6CgkvVW9/H37S6/4IQQgwYTVM6PkB9UBdnQ2OcjL33e3m4brbZ69bmFMu3tbBiWysbmxLYjkcsaFBe5CcSkJGgfKIoUBoK0JDIsLEhieUOvzX3fXo6Tp06le9+97uYptlxmWVZfPe732Xq1KkAbNmyZY/L3kX/S5nZYej+nB7zN62heuFtqK5JvGom2w+7pucCaUWh9uArSFQcjupkGLnwNvRE7xpjCiFyLxLQiQUMtrWkWVPbRnPS2uNtdiRA21rSLK9pYfm2VjY0JLEcj2jQoDwSIBLQ0QaqzYfYZ6oKJSE/tW1ptjSlcIfZnnZ9mia79957Ofvssxk9ejQHHXQQiqKwdOlSHMfh6aefBmDt2rVcccUV/Rqs2LO2jI3puET7qRW9r3Ujo16/Gc1OkSw/iJojrwd1D08bVWfbkdcx+j83EGj5kFGv38ymY3+A6+vnmishxIAwdJXySIDmpMma2jZGFQepiAbQOxVXex4kLJt42qYhbpIwbWwnWwMUDRgD199MDBhdU4gFfWxtTmKoCiOLg8NmNV+fN2qNx+P88Y9/ZPXq1Xiex9SpUzn//PMpKirq7xhzqpAKqD0PVta0ksg4xPphmaSeqGHMq/8PPd1Iunh/Nn/sTjwj1Ovba+lGxrzydYxUHanS6Wz52O142tBoaCnEcJEyHRKmRVk4wKiS7OrgtrRNY3sCZDkufl0nZGjo+jB55xzi0pZDIuMwvjxE5WA0ZSzUAmqASCTC5Zdf3tebiwEQb99+oz9WgmjpRkb99zvo6UYyRfux5ahb9yoRAnACpWydcyuj//1Ngo3LqXz7x9QceZ30IBKigAR9Gj5NpSGeIZ6xcVwXy3XxqRphn46RJw0bRf8JGBqOk23KaGgqpeGh3ZcP9iEZWr16NS+//DK1tbW4H5lcvOmmm/Y5MLH34mkby/H2+cVJNVsZ9d/v4EvWYIaq2HLU7X2e4jKj+7Ft1rcZ+fpNFG39L/Z7v6V+xqX7FJ8QYnDtKK5OWQ5+XccnCdCQFw7otKZs1jdku1RHg0O7B1GfHt0DDzzAl7/8ZcrLy6mqqurSgFFRFEmGcsBxoT6eyW5WuA8UK8mo12/B37YRO1DKlo/dgRPct21MUiMOYvth11D91g8o+fDv2KEKmid+Yp/OKYQYZEp2lEgMH9GgTlPcZENDggkV4QHpP5Uv+vTI7rjjDu68806uu+66/o5H9FE8Y5PMOMT2oXBacUxGLrqDQNNqHF+ULUfdgR2u6p/4Rs+lPllH+fKHKF/2G6zgCBIje95XTgghRO6VhH3UJzKsr08ycUSEgDE0RwX79Kiampo455xz+jsWsQ9aUiYuXt+Xrro2VW9+j1D9Uhw9yJY5t2JG9+vXGJv2/wzN489AwaPqrR8SaFjRr+cXQgjRzxQoC/tpSZlsbExiOkNzzX2fkqFzzjmHZ599tr9jEX1kOR6NCZOg3schbM+lcvFPidQswlV9bJt9E5mS/fs3SABFoW7Gl4hXHonqmoxcdDtGfEv/348QQoh+oyhQFg5QH0+zuTGJPQSbMvZpmmzSpEnceOONLFy4kBkzZmAYXadmrrrqqn4JTvROW8YiZTmU9mWHes9jxNL7iW5+GU/R2DbzBlLlM/o/yB1UjZodPYia1zDytZvZPPeHOP7igbtPIYQQ+2RHU8aa1jS6pjK6ODSkuoj3qc/Q+PHjez6horB27dp9CiqfFEKfobV1cWrbTMoie7/8sWz5w5SufhwPhZojvkF89Nx9iqW3tHQTY/79DYzkdtIlk9n8sbvw9EHoZyGEEKLPTNulNWUytixMdayfmjIWap+hdevW9Skw0f/Slktzyibch1UeJWv+Qunqx4HsLvODlQgBOIEStsy5lTH//iaBptVUvfVDts26ARRZrSKEEPnKp6tE/AabGlMYmsqIoqHRSHcIDXINT20Zi4xt7/WS+uj6BZS//xAA9QdcSOv40wcgut2zikazdfaNuKpBpGYhI5b+OttGWwghRN4K+DR8usqGhiRNvdi7rhD0emTo2muv5fbbbyccDnPttdfu9tgf//jH+xyY2DPPg6aEha5osBdDlZHNr1Dxzr0ANE4+h6b9PztAEe5Zumw62w//OlVvfo/idf/AClXSvP+ncxaPEEKIPYsEdFqSFuvrE+gVEYoChd2DqNfRL1myBMuyOr7viTJcdnXLA0nLpjVlEdqLHepDNW9S9faPUfBoHn8mDdO+MIAR9k581NHUp+oZ8d5vGPH+77CD5cRHH5vrsIQQQuxGLGTQGDdZ35Bg4ogIoQJuytnrZOill17q9nuRO21pG9N1iOm9a7QYrFtK9Rt3o3gOraOPp+6gL5EvWxI3T/okerKWkrVPUrn4x9iBUtLlB+Y6LCGEELtR2t6UcUNDggkjIvgLdKuWwoxa4LrQEDfxa73LZ/1Nqxm56HZU1yReNYvth12ddxum1s/4IvHqOaiune1B1LYp1yEJIYTYHQVKQ36akhYbGpNYTmHWffZ6ZOjTn+59HccTTzzRp2BE7yXad6iPBvY8KuRr3cCo125GtVMkyw/K7hyv5uH8rqJRc8Q3GPXfbxNsXMmo125m09wf4QRKch2ZEEKIHqgqlIZ81Ldl0FUYWxpBy6/P2nvU63fEWCw2kHGIvdSasnA9F30P22/oiRpGvXYjmtVGumQyW2d9B0/b+35Eg8XT/GyddSNj/v1NfImtjHz9FjYf8108PZjr0IQQQvRA0xRKgj5qWtIYqsroklC+VGH0Sq+ToQcffHAg4xB7wXKz228E9N3/82mpBkb99zvo6UYy0bFsmXMrnhEapCj7zvXH2HrUrYx+5RsEWj6k+s3vsXXWjaAWbnGeEEIMdbquEA342NycQtdUqmOF00i3wAayBEA8bZMwbUK+npMh1Wxl1Gs34kvWYIaq2HLU7bi+okGMct9Y4Wq2zr4JV/MT3v4WFe/eJz2IhBAiz/kNlbChs7ExSV08k+tweq3XI0OHHnpor5fNL168uM8BiT1rSZkAPe4Lo1hJRr12M/62jdiBUrZ87A6cQOkgRtg/MqVTqDnim1QvuovYhmewQpU0TTk312EJIYTYjaBfw/E8NjYk0VWVklDvVjznUq+ToU9+8pMDGIborYzt0pSwCBnd/9MpToaRi24n0LwGxxdly1F3YIerBjnK/pOonk3dQZdRsfRXlK94GDs0grYxx+c6LCGEELsRCeg0Jy3WNyTQ1fxvytjr6G6++eaBjEP0Ujxjk7YdysLd7Afj2lS9+T1C9ctw9CBb5tyKGd1v8IPsZy0TzkJP1lL6wRNULv4ZdqCU1IiDcx2WEEKI3Sju1JRx0ogIwTxuyrhPNUNvv/02f/zjH3nkkUd225Va9J/GhImGsmuVvudSufgnRGrewFV9bJt9E5mS/XMS40BoOOBC2kYdg+LZVC+6E1/L+lyHJIQQYg9Kwz7iaZv1DUkytpvrcHrUp3Gr2tpa5s2bx8svv0xxcTGe59HS0sLxxx/Po48+yogRI/o7TgGkTIfWlEXwo9tveB4jlv6K6OZX8BSNbTNvIFU+IzdBDhRFZfth16Clmwg1vMfIhbew+dgfYgfLcx2ZEEKInihQGvbTkEizsVFhXHkYQ82/Nfd9Ghn66le/SmtrK++//z6NjY00NTXx3nvv0draylVXXdXfMYp2bRkb03F32aG+bMXDFK/7Jx4KNYdfS7LqyBxFOLA8zce2Wd/GjIzGSNUz8vVbUK1krsMSQgixG6oKJSE/dW1pNjcmcfJwgKhPydCCBQv45S9/ybRp0zoumz59Ovfeey//+te/+i04sZPnQUM8g/GRJWQlq/9C6eo/A1B7yFeIj56bi/AGjesrYsucW7H9xfhb11P1xt3g2rkOSwghxG7omkJx0Me2ljRbm1N51ymlT8mQ67oYxq5L5QzDwHXzMOUbAuLt22903hU4uu5flC9/CIC6Ay6iddxpOYpucNnhSrbOuQVXCxCuW0Llkl9IDyIhhMhzhq5SFNDZ0pxke1s61+F00adk6IQTTuDqq69m69atHZdt2bKFa665hhNPPLHfghM7xdM2lu1itO8IHNn8SrYRIdA4+Vya9/9MLsMbdJniSWw78jo8RSW66QVKV/5vrkMSQgixBwFDI2hobGxM0pAwcx1Ohz4lQ/fccw9tbW2MGzeOiRMnMmnSJMaPH09bWxs///nP+zvGYc9xoT6eIdDecTpc8wZVb/8YBY/m8WfSMG1+jiPMjWTVkdQefAUAZav+RHTDszmOSAghxJ6E/Dq6orK+IUFLKj/KHPq0mmzMmDEsXryY5557jpUrV+J5HtOnT+ekk07q7/gE2d5CyYxDLGgQrFtK1RvfRfEcWkcfT91BX6KgdsPrZ63jTsNI1lK6+nEq3rkHO1BGsvLwXIclhBBiN4qCOk0Jk/X1cSYFHcI5jmef+gydfPLJfPWrX+Wqq67ipJNOYvHixZx11ln9FZto15oycfEIta5h5KLbUV2TeNUsth92NSiyvVzDtPm0jj4exXOpfvO7+Js/zHVIQggh9qAk5CNlOWxtTpGynJzGstfvpM899xzf/OY3+da3vsXatWsBWLlyJZ/85Cc58sgjse38GPIaKizHoyFhUpLawqjXbka1UyTLD6LmyOtAze/25oNGUdh+2FUkyw9CtVOMXHgrerI211EJIYTYnfYeRK1Ji6aEldNQ9ioZ+v3vf8+pp57Kgw8+yHe/+11mz57NH//4R2bOnElJSQnvvvsuCxYsGKhYh6W2jIXbsoVJb92CZrWRLpnM1lnfwdN8uQ4tv6gG22Z9m0x0LHq6MduDyIz3eLjreSQtj7qky4YWh+X1Nm/X2NQmZDWkEEIMFkUBVVXwyO2K4L0aWvjJT37CXXfdxfXXX8/jjz/OvHnz+MlPfsKSJUuYOHHiQMU4rLXVb2P6ktvQM41komPZMudWPCOU67ByxvM80g4kLY+E5ZG0dn6fsAy0im/x+cQNRNs24jx/O9+LfotWRydhdb5N9nY9/emNi6nMGqkzs1rngHINLQ+7pQohhOg/iuf1vkFLUVERS5cuZfz48biui9/v5/nnn2fu3KHb6K+1tZVYLEZLSwvRaLR/T960Aba/B9GR3V6dbmvCe+pqgvGNmKEqNh/7fZxAaf/GMEg8z8N0IGnvSFxoT0p2JjWJLj93Osb2SJjt/7fA3cMzdpqygcd9t1GkpPg/5yiusa7A62EQVFUgbCiEDfBpCpvb3C7njxhwRHU2MZo5UifmlxotIYToT/HaDVRMOpRREw7o1/Puzfv3Xo0MJRIJwuFszbeqqgQCAcaMGdP3SEXPzCTaM9dhxDdiB0rZ8rE78jIRclyP59dbbG5zuyQ1O0dg2pMa26M/9+hTFQjpEDIUwoZCqP0rbEDYmMSj9je4ePtdfFJ7jTHVVSzdbz4hXSHsUwh3up1PA6XTarw20+OtbTaLttq8uc2m1fR4eaPNyxttFGBqmcaskTqzRupMLFa73FYIIURh2usK3GeeeYZYLAZkO1G/8MILvPfee12OOfvss/snuuHKzuA98y2MxtVYRhFbj7oDO1yV66i69bulGR5f2fvGWQoQNCCsK50Sma5JzY6Rmq6JDjuv1xUCOntIRGZRt+GrVC35KYfXPsGY6ipaRp+xx/iKfArHjzU4fqyB43qsanRYtDWbHH3Y7LKiwWFFg8NDyzKUBRVmVmcTo8MqdYKGJEZCCFGI9mqaTFX3PEWgKAqOk9slcv1p0KfJXBuevQk2voajBVk/5w7c8in9e7/9ZHm9zTUvJHE9OG2CQXmwa0IT6iapCeqgDuJoSunK/6Vs5f/iobJt9ndIVM3s87nqky5vtI8aLd5uk+60cNJQYcaI7KjRzJE6o4u0nk8khBCiQ8FNk8m+YwPMc+Hl78LG1/A0HysOvh5/niZCGdvjh4vSuB6cONbg6zODuQ6pW41TPoeerCO28Tmq3vwem4++m0zJ5D6dqzykcsZEH2dM9GE6HktrHRZts3ljq8XWuMfi7Q6Ltzv8ckmGUUUqs9pHjWaM0DA0GTUSQoh8JY1q8oXnwX9/Bh88j6dobDzsOjKlB+PPdVw9ePi9DJvaXEoDClccFsh1OD1TFGoP+Qp6uoFw7WJGLryNTcf+cJ+nHX2awhHVOkdU61xxqJ/NbW7HdNqyOoctbS5PtJk8sdokqMNhVTqz2ouwy4JShC2EEPmkT8nQyJEjOe644zjuuOOYO3cuU6bk5+hFQXnzN7D874BC+ujrqQkcStSXn1Mty+tt/rIqWyf0tSMDRP15Puqh6mw78npG/+d6Ai1rGfX6LWw69vu4vv6Z9lQUhTFRjTFRjc9O9ZOwPBbX2Lyx1eaNbTaNaY//brb57+bsvNr+JSoz24uwp5RqgzptKIQQYld7VTO0w5/+9CdeeeUVXn75ZVavXk1lZSVz587tSI6mTZs2ELHmxKDUDK19Gd74dfayY77OlqqT2NCYYERR/o24ZGyPLz+TYFOby0njDK6bnZ/TY93RUg2M+fc3MFJ1pEqns+Vjdwx480rX8/igKTtq9MZWi1WNbpf+RsX+7AjTrJE6R1TpRHySGAkhhpd8qBnqUzLU2fbt23nppZd4+umneeyxx3BdVwqoe6tpQ3Zq7K3fZn+edTn2jPNYsbUV2/WIBPJvFvPX76T580qT0oDCA6dH8n9U6CN8rRsY/e//h2YnaBt5NDVH/r9B3d+tKe3yZnsR9ls1NslOHehVBQ4o37l0f2xUlu4LIYa+fEiG+vxuG4/H+c9//tMxQrRkyRJmzJgxpBsw9rtV/4S3fpf9/pDPw8HzaEtaJEybklD+VQstr7f5y8oCmh7rhhkdy7ZZ32bUazdRtPU/2O+VUz/jkkG7/5KAyinjfZwy3ofterxfly3CXrTVZmOry7I6h2V1Dr95N0NlSOmYTjukQsevF97vWwghCkGfRoZmzZrF0qVLOfDAAznuuOM49thjOeaYYyguLh6AEHNrwEaGVi2Ax/4nu5R++ifhY1eDorC+IUFNS5qySH4lQ4U8Pdadok0vU/X2DwGonXEZLRNz3xtrW7x9Om2bxTvbHaxOizf9GhxSqXesUKsISxG2EGJoKNiRoTVr1hAKhZgwYQITJkxg0qRJQzIRGlCb38gmQmOPho9dBYpCxnZpSliEjPybHvt9oawe66W2Mcehp2opX/4wI5Y9gB0sJzHyqJzGVB1R+eRkH5+c7CNle7yz3W6vNbKpS3kdq9V4W/ZPE0KI/tTnmqGlS5fy8ssv88orr/Dqq6+iqipz587l+OOP5/LLL+/vOHNmwEaGPA/eeACKKqF4PwAaEiart7dRFvaTT6Uiy+ttvvZ8Eg+47Zggc0YZuQ6pf3geFe/eS2z9AlzVx5aj7yRdmn/F/57nsb5l59L95Q2O7J8mhBgy8mFkaJ8LqAHefvtt7rnnHv74xz8OWAF1U1MTV111FU8++SSQ3fLjF7/4xW5HpG655RYeffRRNm3ahM/n4/DDD+fOO+9k1qxZvb7fwexAvaY2TlPcpCQysCuc9kbG9rj8mQSbh8j02C5ch+pFdxDZ/iaOL8qmY76HVZTf++21Zjze6rR0v83c+Se8Y/+048fqnDbBR1DqjIQQeS4fkqE+zccsWbKEl19+mZdffplXX32VtrY2Dj74YK6++mqOP/74PgW9J+effz6bN29mwYIFAFx22WXMnz+fp556qsfbTJ48mXvuuYcJEyaQSqX4yU9+wimnnMIHH3zAiBEjBiTOvkqZDq0pi6A/v3oLPbQsw+YhND22C1Wj5sjrsj2Imj9g7ItfIVE1k5axp5KsPAyU/Pr3AIj6FU4Ya3BC+/5pKzvtn7a20/5pf3jP5FOTfXxif19BFrsLIcRg6dPIkK7rHHrooR29hY499tj+HzXpZMWKFUyfPp2FCxd2jOosXLiQOXPmsHLlyl43fdyRJT7//POceOKJ3R6TyWTIZDJdbjNmzJgBHxmqbcvwYV2c8jwqnH6/3uaa9umx248JMnuoTI91Q0s3UfXW9wnVL+u4zAqOoHXsybTudzJ2KL+S557UJV3+u9nmb6szbI1n/7QDOpw50cdnpvgYEZIpNCFEfinYkaHGxsYBTX4+6vXXXycWi3WZ3po9ezaxWIzXXnutV8mQaZr8+te/JhaLcfDBB/d43N13382tt97aL3H3ludBY8LE6MVGuINlx95jHnDyOGNIJ0IATqCELUffja91A9ENzxLd+AJGqo6ylf9L6cpHSVQeTuu400hUHgFq/o0W7TAilC3C/vgkg1c32zy6PMOHzS5/XWXy9zUmJ40zOHeqjzHR/H0MQggx2PqUDEWjUZqbm/nLX/7Chx9+yDe/+U1KS0tZvHgxlZWVjBo1ql+DrKmpoaKiYpfLKyoqqKmp2e1tn376aebNm0cymaS6uprnnnuO8vLyHo+/4YYbuPbaazt+3jEyNJDipk1b2iLsy59VZJ2nx748FKfHemBGx1I/41Iapl9AZOt/ia5/hlDDe0S2v0lk+5vYgVJaxp5C69hTsEO7PifzhaYqHLefwdwxOm/VOPxpeYZldQ4L1lo8s9bi6NE686b7mVwqSZEQQvTp3Xfp0qWceOKJFBcXs379ei699FJKS0v529/+xoYNG3j44Yd7dZ5bbrllj6Mwb775JkC3nXg9z9tjh97jjz+ed955h/r6eh544AHOPfdcFi1a1G1yBeD3+/H7B3eqKp62sWwXI0+mMN6vt/lr+95j1xwZoGgYbhHhaT7axhxP25jjMdo2E9vwLEUbn0dPN1K26lFKVz1GsuIwWsadSqJqJqj5k8h2pigKR1brHFmt8369zaPLTRZutXl1c/brsEqNedP9HFKhSbdrIcSw1adX8GuvvZaLLrqI73//+xQVFXVcfvrpp3P++ef3+jxXXnkl8+bN2+0x48aNY+nSpWzfvn2X6+rq6qisrNzt7cPhMJMmTWLSpEnMnj2b/fffn9/+9rfccMMNvY5zIDmuR30iQyBPRoWG2/RYb1hFo6k/8GIaps0nvO11YhueIVT3LuHatwnXvo3tL6F17Em0jD0VO1yV63B7dEC5zu3H6qxrdnhshclLGy0Wb3dYvD3J1FKV86b7OWqULhvHCiGGnT69A7/55pvcf//9u1w+atSoPU5bdVZeXr7bKasd5syZQ0tLC2+88QYzZ84EYNGiRbS0tHDUUXvXKM/zvC4F0rmWNG2SGYdYMD+Sjh3TY2XB4TU91hueZhAffSzx0cdixLe21xY9j55ponT1nyld/WeSIw6hZdxpxKtngZof/6YfNb5Y4/o5QS6Y4ecvqzIsWGuxstHl1v+k2C+qct40HyeMNdClkaMQYpjo07xMIBCgtbV1l8tXrVo1IEvWp02bxmmnncall17KwoULWbhwIZdeeilnnXVWl+LpqVOn8re//Q2ARCLBt771LRYuXMiGDRtYvHgxl1xyCZs3b+acc87p9xj7qi1t43oempb7Nx6ZHus9KzKShgMuZN2pD7LtyBtIVByGh0Ko7h2q3/wu4xdcSNl7v8OIb8l1qD2qjqh89fAgf/x4hM9N9xE2YGOryw8WpfnC03H+tjpDyt7nNmRCCJH3+pQMfeITn+C2227DsrJbbiuKwsaNG7n++uv5zGc+068B7vDII48wY8YMTjnlFE455RQOOugg/vCHP3Q5ZtWqVbS0tACgaRorV67kM5/5DJMnT+ass86irq6OV199lQMO6N/le31lOh7NKYugkfsi1o9Oj80amZ+jGnlHNYiP+hhbj7qN9Sf/hobJ52EHStHNFko/eIJxz3+JUf+5gcjmV1AcM9fRdqskoHLxQQEe+XgRlxzspySgUJf0uG9xhvlPxfnje5kujR2FEGKo6VOfodbWVs444wzef/992traGDlyJDU1NcyePZt//etfhMPhgYg1JwayA3X95tVsXP4G4fKx5HpV/a+WpPnrKpOyoMIDp0dkVGhfuA7h7W8SW/8Moe1vo5DdcdUximjd7wRaxp2W112uTcfj2XUWj6/IsC2RfXkI7uhVNNVHeTA/Cv2FEENDPvQZ2qftOF588UUWL16M67ocdthhnHTSSX09Vd4ayGRo6/pV1Kx6k6LKsf163r31Xp3NtS9kmyvecWxQRoX6kZ6sI7rxOaIbnsVI1XdcniqbTsvY04iP+hielj+NNjtzXI9/b7J5dEWGtc3ZhM5QyfYqmuZjdFHuRzSFEIWv4JOhj1q8eDE33XQTTz/9dH+dMucGPBla/SZFFblLhjK2x5eeSbClzeXkcQb/b6jtPZYvPIfQ9sXE1j9DePsbKN6O0aIwbWNOoGXsqZixcbmNsQee5/HGNpvHVpgsq8vuO6gAx4zRmTfNz/7Sq0gIsQ/yIRna69Vkzz33HM8++yyGYXDJJZcwYcIEVq5cyfXXX89TTz3FySef3OfAxeB7cFmGLe2rx4bk3mP5QtFIVh1JsupItFQ90Y3PE1v/LEaqluK1T1G89ilSJVNoHXcabaOOwdPz599CURRmjczWkb1Xl02KFm61+fem7NfhVRqfm+bnIOlVJIQoUHuVDP3+97/noosuorS0lMbGRn7zm9/w4x//mCuuuILPfOYzvPvuuxx44IEDFavoZ+/V2TzRafVYROqEBoUTLKdpyjyaJp9LqHYJ0Q3PENm2iGDTKoJNqyhf9gBtY46jZexpmMUTch1uFweO0DlwhM7aZofH23sVvV3j8HZNkmllGvOm+ZgtvYqEEAVmr6bJDjnkEObNm8f111/P448/zrx58zj00EN5/PHHmThx4kDGmTNDdZosbXtcLtNjeUNLNxHd+DzRDc/iS2zruDxdvD8t406lbdSxeEYohxF2b1vc5c8rs72KrOzMH2PbexUdL72KhBC9kA/TZHuVDBUVFbF06VLGjx+P67r4/X6ef/555s6du89B56uhmgx1Xj32m9MjMiqULzyXYP1SYuufIbL1dRTPBsDVg7SNOpaWcaeRKZ4EeTby0pR2eWKVyZMfmCSzHTeoDCl8dqqf0yYYBPT8ilcIkT/yIRnaq2myRCLRsWxeVVUCgcCAb2Iq+p9Mj+UxRSU14hBSIw5By7RQtPEFYhuewRffQmzDM8Q2PEM6NiFbWzR6Lq6RH20sSgIqXzw4wLxpfp76wOSvq0y2Jz3uXZzmkfczfHKyj7P390nLBiFEXtrrAupnnnmGWCwGgOu6vPDCC7z33ntdjjn77LP7JzrR79K2xw/fyDZXPGW8NFfMZ44/RvP+n6Z50qcINrxHdP0zRLb+l0DLWgLv3kf5e7+lbdQxtI47jXTJlLwYLQr7FOZN9/Opyb5sr6KVGWoSHg8ty/D4igxnTfLx6Sk+yqRXkRAij+zVNJnai86AiqLgOM4+BZVPhto0mUyPFTbVbCW68SWiG57B37ax4/JMdCwtY0+jbczxuL5IDiPsynE9XtmY7VW0rmVnr6JTxhucM9XPqCJJioQYVB1v+V77187/db5M6eYyuqQLXS9Turms68m9jxy787JE/WbK9j+CkVNm9uUR9ShnfYaGoqGUDElzxSHE8wg0rsjWFm15FdXNTnu6qo/4qI+RLp3W4+06/dD9911eEXb+oPCRl4oejut6rp3fb2xxWFLrsD3houChKDAhpnFwhUZ5SOndOb2er1N2eSnrPo6erlN2ua4Xt/c6/356vq5f9MvI376fY6i8YSh44Lngue3PHa/9e7fT9x7QwzHt1+1yTMftvfZzuTu/b79O+egxnS/v8r3X9fLO97nj3OxIXDonHez8nm7+dvNQ24FfoOizv+jXcw5onyFRmNK2xw8WyfTYkKEopMumky6bTt2MSyna/BKx9c/gb11PdNNLRDe9lOsIdzECOByg81MvAazLSThCiDzh9UOSvq/6nAytWrWKX/ziF6xYsQJFUZg6dSpXXnklU6dO7c/4RD95aFmGrXGX8qDClw/Nn4Z+Yt+5vggtEz5Oy/iz8DetJrrpBfR0c5djvC6vNUr33/c48tD9Mbt+1uzpvN0f02bCuhaHmoTXMYhSHFAYX6wxIqTueuNu41N6vM7r9rqPHrfr+bsb6+ndfXfzuxnMOq5BGOTP/VtWf/HwFBVQQNHwFKX9ezX7vaIC6kcuV9v/PbP/99qP2fn9R2/ffnmX79uPYce5Oh2jKDsv73xM+312vf3O++j6vO38nPzIv1any7xuLuv++d7p+G6e57tepnR6rel07m4v23meHavJisidPiVDf/nLX/jc5z7HEUccwZw5cwBYuHAhM2bM4H//938555xz+jVIsW9k9dgwoShkSqdQVzol15H0WiXgtLk8vjLDs+ssrDgQh3GxbK+i4/aTXkVCiIHXp5qhCRMm8PnPf57bbruty+U333wzf/jDH1i7dm2/BZhrhV4zlLY9vrQgwda4y6njDb4xS5orivzUkMr2Knr6A5Nktr0SIyMKFx8U4Ngxumz1IcQQlQ99hvq0lKOmpoYvfOELu1z++c9/npqamr6cUgyQB5funB67XKbHRB4rC6pcekiAR84u4qIZfor9ClvjHne8luLq55O8V2fnOkQhxBDVp2TouOOO49VXX93l8v/85z8cc8wx+xyU6B/Lam3+tlqmx0RhifgUzj/Az8NnRZh/gI+ABisaHK55Ickt/0myuXXotO4QQuSHPtUMnX322Vx33XW8/fbbzJ49G8jWDP35z3/m1ltv5cknn+xyrBh8nZsrnjreYKasHhMFJmgofGFGgDMn+Xh4WYYF6yz+u9lm4RabMycZzD/AT3FA+hQJIfZdn2qGetN8EYZGA8ZCrRn65eI0T6w2KQ8qPCDNFcUQsL7F4TfvZli0NTtdFtLhvGl+Pj3FJ3ufCVHACrZmyHXdXn0VeiJUqGR6TAxF42Iadxwb4gfHh9i/RCVpw4PLMlz0jzjPrDVx3PxvLCeEyE97lQydccYZtLS0dPx855130tzc3PFzQ0MD06dP77fgxN6T6TEx1B1SqXPPKWGunx2kIqRQn8o+5694NsFb26TIWgix9/YqGXrmmWfIZDIdP3/ve9+jsbGx42fbtlm1alX/RSf2mqweE8OBqiicOM7gwTMjXHqwn7ABa5tdbnglyfUvJ1jbLKPSQoje26tk6KPlRbKtWX6R6TEx3Pg0hXOnZVeefXqyD12Ft2scLl+Q4AeLUtQl3VyHKIQoALIUY4joPD12mkyPiWEm6lf58mEBfnt6hGPH6HjAs+ssLvpHnN8tTZOw5IObEKJne5UMKYqySxdY6QqbH37XPj02QqbHxDA2skjlxo+F+NlJIQ4o18g48KflJhc+Hefva0xsKbIWQnRjr/oMeZ7HhRdeiN/vByCdTnP55ZcTDocButQTicGzrNbm/9qnx752ZICwTI+JYW56uc5PTtT47xab37ybYUubyz1vp/m/1SaXHOznqFGyvYcQYqe9SoYuuOCCLj9//vOf3+WY7rbpEAMnOz2WkukxIT5CURSOHm0we6TOPz60+ON7GTa3udzynxQHlmtcdqifaWV96jsrhBhi9uqV4MEHHxyoOEQfZafHPJkeE6IHuqrwif19nDTO4LEVGf66yuS9eoernksyd4zOxQcFGFkk5ZNCDGfyClDAOk+PXTMzKNNjQuxG2FC4+KAAD50Z4ZTxBgrwyiabL/4rzi8Xp2nNyMozIYYrSYYKVKrz9NgEgyOrZbhfiN4YEVL55qwgvzw1zOFVGrYLT6w2+cLTcR5fkcF0pMhaiOFGkqEC1WV67BCZHhNib00s0fjucWHunhtiQrFKwoIH3s1w8T/ivLDewpU+akIMG5IMFaClMj0mRL85olrnvlPCfGNmgPKgwvakx3cXprjy2QTvbJftPYQYDiQZKjAp2+NHb6QAmR4Tor9oqsKpE3w8eGaEi2b4Cemwpsnlmy8l+c6/k2xoke09hBjKJBkqMDI9JsTACegK5x/g56GzInx8koGqwKKtNpctSPCTN1I0pKTIWoihSJKhAiLTY0IMjpKAylVHBPnN6WE+NkrH9eCfay0u/Eech5elScn2HkIMKZIMFYiU7fHDRTI9JsRgGhPVuOWYED8+IcTUMo20DX943+TCf8T5xwcmjmzvIcSQIMlQgfjd0gzbEjI9JkQuzKjQ+flJIb5zVJDqsEJj2uOnb6X50oIEC7dYeLLyTIiCJslQAZDpMSFyT1EU5u5n8JszInz5UD9FPoUNrS43vprimy8lWd0oRdZCFCpJhvJc5+mx02V6TIic82kKn57i5/dnRTh3qg9DhXdrHb7ybILvvp6iJi5F1kIUGkmG8tzv3m2fHgspfEn2HhMibxT5FC49JMCDZ0Y4cWx2g+QXNlhc/M84v34nTZspU2dCFApJhvLYu7U2/7emfXrsyCBhQ6bHhMg3lWGV6+cEueeUMAdXaFgu/HmlyQVPx3liVQZLtvcQIu9JMpSnUrbHjwpkekyxkmiZ5lyHIUROTSnV+MHxIe44Nsh+UZU20+OXSzJ88Z9xXtkoRdZC5DNJhvJUoUyPKY6JnmlBcWxUK5nrcITIKUVRmDXS4NenhfnaEQFKAgrbEh53vJbiqueTvFcn23sIkY8kGcpDnafHrs3n6THPwUjWYRaNxiwag5ZuAk+KR4XQVIUzJ/n4/ZkR5h/gI6DBygaHa15IcsurSTa1ysozIfKJJEN5pvP02BkTDI7I1+kxz8NI1GKFKjCLJ2EVjcHxF2cTIiEEAEFD4QszAjx0VoQzJmS39/jvFptL/pXg52+laErLhwch8kGevtMOX799N90xPXZZHk+PaekGXCNCpmQynuYHwIyNJ1j/Lq5j4mm+HEcoRP4oC6pcMzPIp6b4+O27GRZutXnqA4vn11ucN83PZ6b4COh5OgI8xLRmPNY0OSiApoCmgqpkR/M0JXuZ2n65pigdx2QvVzq+33lb+XcbCiQZyiPv1tr8fY0F5Pf0mGrGUTxIl+yP6yvquNwOVWCFR2HEN2NFRuYwQiHy07iYxu3Hhnhnu82v30mzpsnloWUZnvrA5MIZfk4eZ6Cp+fl3X+hqEy5PrDb5x4cm6X4s3VLonCztSJKUXRKmPR/Tnnx9JNnakZB1SdDaj4n6Fc6Y6KNIGvHuM0mG8kShTI8pTgbNbCNdOhU7VPGRK1XM6Fj0dAOq2dYlURJC7HRIpc49p4R5eYPN75am2Z70+NEbaf66yuTSg/0cWa2jyIhDv9jQ4vD4SpMX1lvs6HJQFVYI6gqOR/bL9dr/D+6OyzwP16XjmJ62ofMA2wV7l0t393P/+ddai9uOCbJfVBuw+xgO8vMddxjaMT1Wkc/TY66DnqzHjI3HKhrT/SG+IjJF4wg0Lsc1QqDIH6gQ3VEVhRPGGRw9Rufva0z+9/0M61tcvv3vFIdWalx2SIBJJfL301fL620eW2Hy2padacohFRrnTvNzRJW218mm53k7EyW3U8LU+Wc3e1l3iVXnY9wdx3S5bafz93Cc2zlx8+CVjRZb2ly++lyCb80JMmuk0d+/xmFDkqE88O72TtNjM/N0eszzMJLbscNVmLEJoPRce28VjcRI16GnGnYdPRJCdOHTFM6Z6ufU8T7+d3mGJ9eYLNnucMUzCU4cZ3DRDD8VYVnr0hue5/FWjcOjyzMsrcuu2FOAo0brnDfNx7Syvr/lKTvqh6D9PzvOnjvnTPVx+39TLKtzuPHfKS452OWcqT4ZVewDSYZyLGXDD9/eOT12eFV+/pPo6QZcI0qmeP89F0erBpnoOIK176DYaTw9T0e6hMgjUb/C5YcG+MT+Pn63NM3LG22eX2/xykaLT0/x8blpftmkuQeO6/HKJpvHVmRY25xdoaercNJYg3Om+YbsFFJJQOV7x4W4d3Gaf3xo8cC72cd/zZEB/FKQv1cK5uNGU1MT8+fPJxaLEYvFmD9/Ps3Nzb2+/Ze+9CUUReGnP/3pgMXYF39cG6Qmz6fHVLMVUEiXTsb1RXp1GydQhlU0Gj3VCNJ5V4heq46ofPuoEL84OcyMEdntPR5bYfIF2d5jFxnb46k1Jhf+I87dr6dY2+wS0OEzU3w8fFaEr88a+rU0hqZw9REBvnp4AFXJ7o/39RcT1CelbcPeyM9hiG6cf/75bN68mQULFgBw2WWXMX/+fJ566qk93vb//u//WLRoESNH5tcKp8VbkvxrczYBytfpMcVOo5kJ0mXTcYLle3FDBbNoP/RUA5rZguMvHrAYhRiKppZp/OiEEK9vtfnNuxk2tbr8ckmGv68xufigAMeOGb5F1nHT48k1Jn9bbdKcySaHMb/Cpyb7+PgkH1H/8Pq9KIrC2fv7GBNVuf2/KVY1unzl2QS3HBPcp6nB4aQgfksrVqxgwYIFLFy4kFmzZgHwwAMPMGfOHFatWsWUKVN6vO2WLVu48soreeaZZzjzzDP3eF+ZTIZMJtPxc2tr674/gG4kMjZ3vVwLwJkT83R6zLXRU42YsQlYkVF7fXPPCGHGxhGoW4ZjREDNw8coRB5TFIWjRhnMqtb511qLh9/LsDWe3d5jWpnGZYf4OXDE8Pm7qk+5PLHK5B8fmCTb66IrQwqfnerntAnGsO/VdGilzr2nhLnp1STrW1y+/kKSa44McPJ46fu2JwUxTfb6668Ti8U6EiGA2bNnE4vFeO2113q8neu6zJ8/n29+85sccMABvbqvu+++u2MqLhaLMWZM96um9tX3F6xka5tNud/h0kPycHrM8zCSdVjhKjLF43dbML07VqgKK1yFnqrv5wCFGD40VeGsST4eOjPC59u391ixY3uP/yTZPMS399jc6vDjN1J84ak4f16ZTYTGxVSunx3kobMifHKyNK3coTqi8rOTwhw1Ssdy4fuL0vz6nTROT70BBFAgyVBNTQ0VFbuuSqqoqKCmpqbH233ve99D13WuuuqqXt/XDTfcQEtLS8fXpk2b+hTznnz6sNGML/FxxbRkXk6P6ak6HF8Us2R/UPdhuaaqYUXHgWqgWol+i0+I4ShkKFwwI8CDZ0U4fcf2Hpuz23v84u0UzUNse49VDQ63/SfJxf9M8K+1FpYLB5Zr3HFskF+fFubEcQa6NKncRchQuPnoIP8zPTsi9OeVJje+miRuSkLUk5yOr95yyy3ceuutuz3mzTffBOh2btzzvB7nzN9++21+9rOfsXjx4r2aV/f7/fj9/l4f31cHjynm4XPGUPfB9gG/r72lZlpA0ciUTsE1wvt8PidQjFm0H/6m1bh6sM+jTEKIrPKgyrUzg3xqso/fvJvhjW02T66xeH5ddnuPTxfw9h6e57Fku8OjKzIs2b5zxGv2yOzy+OE0LbgvVEXhwoMCjC/W+MGiFG9uc7jquQS3HRNk9BAvKu+LnD6rrrzySubNm7fbY8aNG8fSpUvZvn3XpKGuro7Kyspub/fqq69SW1vLfvvt13GZ4zh8/etf56c//Snr16/fp9j7Qz623VfsFJqdJF12IE6gtN/Oa0VGoafq0NJNOMGyfjuvEMPZ+GKNO+eGWLLd5oH27T0ebN/e44IC297DcT3+szm7PH5NU3aES1XghLEG5071Mb5Y3sD7Yu5+BqOKVG56NcmmNpcrn0vw7aNCHJmnuxzkiuJ5+b/uecWKFUyfPp1FixYxc+ZMABYtWsTs2bNZuXJltwXUDQ0NbNu2rctlp556KvPnz+eiiy7abdF1Z62trcRiMVpaWohGo/v+YDrZun4VNavfpKhibL+et89cGyO5nUxsImbx/tDPK1X0RA3B+nexA2WykasQ/cz1PF5q396jNpl9WZ9QrHLJwYG8fuMzHY/n1lk8vtJkazybBPk1OH2ij89O8VEpDSf7RVPa5db/pHi/3kFV4NKDsxsE58OKxHjtBiomHcqoCb2r7e2tvXn/zt+/kE6mTZvGaaedxqWXXsr9998PZJfWn3XWWV2SmqlTp3L33XfzqU99irKyMsrKuo5AGIZBVVVVrxOhYcVzMZK1WOFRmLHx/Z4IgWzkKsRAUhWFE8cZHDNG5/9Wm/zv8mwDvm+9kuSw9u09JubR9h4Jy+PpD0yeWGXSmM4mb0U+hU/ub/CJyT5ifkmC+lNJQOX7x4f4xdtpFqy1uP+d7PPja0cG8Gm5T4hyrSCSIYBHHnmEq666ilNOOQWAs88+m3vuuafLMatWraKlpSUX4RU8PVmH4y8hs68F07vTsZFrI6rZiuvr35E2IUR2e49zp2WXmj/yvsmTH5gs3u7w5WcSnDTO4KKD/IwI5S7RaEy5/G21yVMfmCSyuxAxIqjw2ak+Tp/gI5iHC0qGCp+mcO2RASYWa/xySZrn1ltsanO55eggZcHhnXwWxDRZLg2HaTIt04zieaTKD8IJlAz4/RmtGwg0LMcKV4GaP59UhRiKtsXdju09AHwafHqyj3mDvL3H1jaXP6/K8Ez7qjCA/aIq503zcfx+BoaMTgyqxTU2d7yWpM2EsqDCrUeHmFKWm9djmSYTOadYSRQ7Tbp8xqAkQgBWZCR6qh49LRu5CjHQdmzv8ekpNg+8k2FZncOjK0z+tdbi8wf4OXPiwCYiHzQ5PLYiw7832exodTOtTGPeNB+zR+moeVCzMhwdVqXzi5Mj3PRqko2tLte+mODrRwY5YdwAzQzkOUmGhjPXQk83kynZHztUNXj3qxqY0bEEa5tkI1chBsm0Mp0fnaDx+pb27T3aXO5dnOZvq00uOdjP0aP7b3sPz/N4tzabBL1Vs3N5/JHVOvOm+ZgxQsuLwt3hblSRys9PDvPd11Ms3Gpz98IUa1scLprhL5hViP1FkqHhynMxEnVYRaMxo2MHpGB6d3Zs5OpvWYcZGTno9y/EcKQoCkeNNpg5UudfH+7Y3sPltv+mmF6e3d7jgPK+vy24nsdrW2weW55hZePO5fFzx+icN82fVwXcIitsKNxydJCHlmV4dIXJYytM1re43DA7OKjTqLkmydAwpSfrcAKlZIon5WbPMEXJFlOnGtAyzYM2RSeEAF1V+Pj+Pk4cZ/D4igx/WWWyvN7ha88nOWa0zsUH+xld1PvExXI8Xthg8fgKk01t2STIp8Gp4w3OmeqnOjK8i3PznaYqfPHgbIPGH72RYtFWm68+396gcS+eB4VMkqFhSEs34Wl+0qWTczpF5elBzNh4AvXLcFxr4FaxCSG6FTKyXYrP2t/H75dleHadxaubbV7bYvPxST4+f+Dul7gnLY9/fmjy11Um9alsQVDYgLP39/GpyT5KApIEFZITxmYbNN7yapJNrS5ffTbBdz4Wys+NxPuZPFOHGdVKojgmmZLJuP7iXIeDFarEClVipBpyHYoQw1Z5UOXrM4P86tQwR1brOB783xqTLzwd50/LM2TsrouOm9MuDy1N8z9PtnH/OxnqUx6lAYXLDvHzyNlFXHxQQBKhAjWlVOOeU8JMK9OIW/CtV5I8sSrDUF94PvTTPdFBcSz0TDPpkinYoe63MRl0qoYZG4eeaUK1Ev2yF5oQom/GF2vcNTfE4hqbX7+T5sNml98tzfDUGpMLD/IzY4TOX1dlWLDWItNeFz26SOXcqdkpN2neNzSUBVV+eEKIn72V5tl1Fr9ckm3QeNURQ7dBoyRDw4XnYCRryUT3wyzaL68Kll3/jo1c18hGrkLkgcOqdO47NcwL6y0eXJahLunxg0XpLsdMLlWZN83PUaP0YbfyaDjwaQrfmBlgQrHKr9/J8Mw6i02tLjcfHaR0CDZoHHqPSHTLSNZhh0ZgxibmZaNDq2g0TqAYLd2Y61CEEGS39zh5vI8Hz4hwycF+wu0lfYdVanzvuBD3nBzmmDGFsxGs2HuKovCZKX7uPDZExIDlDQ5XPptgdaOz5xsXGBkZGga0dCOuHiJdktuC6d3xND9mbDzBundwnQye5s91SEIIwK8rnDfNz5kTfTRn3GGzukjsdES1zi9ODnPTqyk2tblc80KCb8wMcvzYobPoRUaGhjjVjKO4DpmS/fN+LzA7WIEZGY2elGJqIfJNxKdIIjSMjY5q/OLkMDOrdUwH7no9xe+WpnGHSGG1JENDmOKYaJlWMrFJ+VMwvTuKglU0Fs8IoZqtuY5GCCFEJ2Gfwm3HBDl3qg+APy03ufnVFAmr8BMiSYaGKs9BT9ZhRvfDio7JdTS95voiZKJj0TJxcIfevLQQQhQyTVW49JAA180OYKiwcKvN1c8l2NrebLNQSTI0FHkeRqIWO1SJWTyx4FZnWZGR2KER6GmZLhNCiHx00jgfPz4xTGlAYUOry5XPxVlcY+c6rD4rrHdJ0StaugHXiJAp2b8wC5FVAzM6DlBQ7FSuoxFCCNGNqWUa954aZmqpSpsJN7yS5P9WmwXZoFGSoSFGNeMoHtkO076iXIfTZ06gFCsyBiPVCAX4hyWEEMNBeVDlRyeGOWmcgevBvYvT/OTNNJZTWK/bkgwNIYqTQTPbyBRPxA6NyHU4+0ZRMKNjcHxRtExzrqMRQgjRA5+m8P9mBbjsED+qAv9aa/H/XkrSlC6cOiJJhoYK10FPNmBGx2IVFU7B9O7s2MhVtdPgWrkORwghRA8UReGcqX5uPyZIyID36h2+8myCD5oKYyGMJENDgedhJLdjhysxYxMKrmB6d2QjVyGEKBwzRxr84uQwo4tU6pIeX3s+wSsb8//D7NB51xzG9FQ9ji9KpmQynubLdTj9q30jV081UM14rqMRQgixB/tFNX5+cpgjqjQyDtzxWoqHluV3g0ZJhgqcaraCopIpmTJkd3zfsZGrlmkFr3DmoIUQYrgq8inccWyIz07JfkB/5H2T2/6TIpmnDRolGSpgip1GMxNkivfHCZblOpwBld3ItVQ2chVCiAKhqQpfOjTAN2dlGzT+d4vN1c8n2BbPvw+1kgwVKtdGTzdgRsdjRUblOpoBl93IdSyKa6M4mVyHI4QQopdOGe/jhyeEKA0orG9xufLZBO9sz68GjZIMFSLPw0jWYYWqyRSPB0XJdUSDwg5WYEVGoadkdEgIIQrJ9HKde08JM7lUpdX0uO7lJE+uMXMdVgdJhgqQnqrD8cfIlEwG1ch1OIOnfSNXVw+iZlpyHY0QQoi9UB5S+fEJYU4Yq+N68Iu30/z0zRRWHsyaSTJUYLRMC6h6duWYEcp1OIPO9UUwo+PQzIRs5CqEEAXGrytcPzvIFw/2owD/+NDilnciNKVy+3ouyVABUewUqp0kUzwZJ1Ca63ByRjZyFUKIwqUoCvOm+bntmCAhHZY3G9z5cn1OY5JkqFC4FnqqkUxsIla4OtfR5Jaqy0auQghR4GaPMvj5yWEmR22+9rHcfsCXZKgQeC5GohYrMiqbBAyTgundcYJl7Ru5NslGrkIIUaDGxjS+e3gbo6O5rX+VZKgA6Ml6nEAZmZL9QdVzHU7ekI1chRCi8OXD53tJhvKclmkGzZctmNaDuQ4nr3h6kEyxbOQqhBBi30gylMcUK4liZ0iX7I8TKM51OHnJDlZkN3JN5rb4TgghROGSZChPKY6Fnm7GjE3ADlXlOpz8pWqYsfF4mk82chVCCNEnkgzlI8/FSNZiFY3GjI7NjwnVPOb6Y5jRsbKRqxBCiD6RZCgP6cla7EAZmeJJUjDdS1ZkFE6gFF02chVCCLGX5J02z2jpJjwtSLp0Cp4eyHU4u+V6HvG0TTxjgwKaohDyaQQNDV0b3Dw7u5HrOAJ176A4GTzNP6j3L4QQonBJMpRHVCuB4likyw/E9cdyHU6PUqZDa9rCdl2KAgYTK8KEfDrNKZOmhEVDwsR2XXyaRsinETA0NHXgp/rs4AisyCh8bZuxIsO8MaUQQohek2QoTyiOiZ5pIV0yBTucfwXTluPSlrZJWTYBQ6My5qeyKEBxyIdPz44CjSwOYjkuiUx2tKghbtKatmiLW7ieh1/TCPl0AoaKMhB1UO0bueqpBtRMS14nlEIIIfKHJEP5wHMwknVkovthFu2X62g6dJ4G01SFWMhgwogwpWEfYX/3Tx1DUykO+SgO+RhdEiJjOx3naEhkaEvZNCUdFEUhYGRHjvy61n8x+yKYsfEE69/DNCKg9t+5hRBCDE2SDOWYAtmtNkIVmLGJefHmnTRt2tI2jusSaZ8GKwv7iQUN1L2c7vLrGv6IRlnEz36lIdKWS1vGoi2VTY7iaZsGJ4OqqATbkyNjH+uNrHA1erIOPVWPHa7cp3MJIYQY+iQZyjHVSeMaJWRK9s9pwfSOabC05eA31G6nwfaVoigEfRpBn0ZFEYx3wySt7MhRS8qkMW7RlDKxbQ9dVQj5dIK+PtQbqTpmbBzBTBOKlcQzQv0SvxBCiKFJkqEcs40omZLJuL7ooN93d9NgEyvClIR6ngbrT6qqEPHrRPw6VbEAjusRz9gkMjZNCZOmlEV9PIPtevh1taMYW+1FvZETKMWKjMHf8iGmHpReTUIIIXokyVAOeUaYeGx/fKGKQb3f/pwG60+aqhALGsSCRkcx9o5krTFh0pKyaElZeB6d6o16LsY2o/uhp+rRMs04gZJBfjRCCCEKhSRDOeQGS8mEBuefwHJcWlMWadslaKhUxQJUFPn7dRqsvxmaSknYR0nYx5jSEGnLIZ6xiact6uNmNklKuqgKBPTsSrXOj8XTA2SKxxOsW4rrWHiakcNHI4QQIl9JMjSEfXQarDhkMCkWGLRpsP4WMLLTZOURP2PLPFLt9Uat7clRS9rEsl00NVuMHfRpEKrECldjJGqwIvnXskAIIUTuFd47otij7qbByiN+ooHcToP1J0XJFliHfDoV0QATyj0SZjbxa05aNCVMGpPZ5o9BtYoRbj1GJg7+SK5DF0IIkWckGRoiCnEarD+pqkJRwKAoYFAdC2I7LomMQ9y0aUwESdqj0etXkAqqGLqB31Dx65rUVQshhJBkqJA5rpft9mxaaKpKcbCwp8H6k66pxEIqsZDBqOIgZvkMUutSZJLNNBLsGEUC8GsafkPFp6nZxk9CCCGGleH9jlmgPjoNNmlEEWUR35CaButvPn8A36gpsHUxFUGDDGGSpkMyY9OcskiZDi2OhdK+4ayuqqgKaJqCrqhomiKjSEIIMURJMlQgup0Gi/opDg6PabB+EamA2BhoXIe/eDR+XaUklF3Gn7YckpZD2nTI2A4Z28WyPSzHI+1aOC54eIAHKGgoqKqCpiro7f/XVBVV/imEEKLgFEwy1NTUxFVXXcWTTz4JwNlnn80vfvELiouLe7zNhRdeyO9///sul82aNYuFCxcOZKj9pqMJoUyD9Q9FgZJxkKiDVDMEizsu3tEZm/DOw10XbM/Fdjwc18NyXRzHw3Y90raDaXlkbAfb9cjYLo5r43pu9oRetsh7Z6LU/qVk/y/TcUIIkT8K5h31/PPPZ/PmzSxYsACAyy67jPnz5/PUU0/t9nannXYaDz74YMfPPp9vQOPsD52nwYpkGqx/+SNQOgG2Lc1+r/b8J6Cq4EPFt5vt4jwPbNfDdrNJ047vHdfDtF0ytkvayiZMluViux6u57XfOJswaYqCpiloCmiq2pE4ybScEEIMjoJIhlasWMGCBQtYuHAhs2bNAuCBBx5gzpw5rFq1iilTpvR4W7/fT1VV7/vLZDIZMplMx8+tra19D3wvfHQarDoWYIRMgw2M6CiI10KiHor2rfeQooChKRiaBrvp6Wi7XjZZ8lxs28PxPCwnOxWXsR1M28VyXEzHxbHcTtNyWdkRJTWbMLXXMamqItNyQgjRDwoiGXr99deJxWIdiRDA7NmzicVivPbaa7tNhl5++WUqKiooLi5m7ty53HnnnVRU9Lz9xd13382tt97ar/HvjuV4bG1JdpkGKw37CPkK4p+mMGl6dnQo1QhmEnwDv5Gr3l5bBCr0MDjpuGRHmFwXx9nxvYdlZ5OktO1g2dmkKuPaOK7XZVpOVXZOx+maQkDXZDpOCCF6oSDecWtqarpNYCoqKqipqenxdqeffjrnnHMOY8eOZd26ddx4442ccMIJvP322/j9/m5vc8MNN3Dttdd2/Nza2sqYMWP2/UF0Q1MVSsM+Kor8Mg022MJlUDwW6leDkR8buWpqdprMT8/DPR3Tco7bPiW38/vsCFP7/x2XtrRFyNCz9WW5f3hCCJG3cpoM3XLLLXschXnzzTcBut2M0/O8HjfpBDjvvPM6vj/wwAM54ogjGDt2LP/4xz/49Kc/3e1t/H5/j4lSf6uKZhsj6prMdeREydj2YupGCJXlOppe6TIttxspy6EpYbK9LUNdPEPQ0Aj79XzI+YQQIu/kNBm68sormTdv3m6PGTduHEuXLmX79u27XFdXV0dlZWWv76+6upqxY8eyZs2avY51IKiqgiof2XPHCELZRNi6BBwTtPwvru+toKERLA5SFvHTmDCpbU1TH08T0LMjRVJrJIQQO+U0GSovL6e8vHyPx82ZM4eWlhbeeOMNZs6cCcCiRYtoaWnhqKOO6vX9NTQ0sGnTJqqrq/scsxhiIlUQHQmtW7KF1UOMX88W45dFfDQnLba3pmlIZPBpKkUBQ5IiIYSA3RQn5JFp06Zx2mmncemll7Jw4UIWLlzIpZdeyllnndWleHrq1Kn87W9/AyAej/ONb3yD119/nfXr1/Pyyy/z8Y9/nPLycj71qU/l6qGIfKOqUDIe9ABk2nIdzYDxaSoVRX6mVkfZvzJC0KfRmMzQnLCwHW/PJxBCiCGsIJIhgEceeYQZM2ZwyimncMopp3DQQQfxhz/8ocsxq1atoqWlBQBN01i2bBmf+MQnmDx5MhdccAGTJ0/m9ddfp6ioKBcPQeSrYDGUTMg2YnSdXEczoAxVYUTEz5SqIqZUFlEU1GlJmTTGTWxbkiIhxPCkeJ4nr4C70draSiwWo6WlhWg0mutwxECxTdjyNmRaINL7OrRC57rQkraoa8vQlDABiAR06W0lhBg08doNVEw6lFETDujX8+7N+7e84gkBoPugbBJofmjeBOnm7Dr2IU5VoSRkMGlEhKnVUcoiPhKmTX08Q8Zycx2eEEIMioLoMyTEoIiMAOPIbHfqlk3QsjnbkDFQDOrul7IXOlWFWFAnGohQmbGpi6dpjFu0ZUwiPoPA7vYkEUKIAifJkBCd+SPZr+hISNRC80Zo25Zddh8sAW03e24MAYoCRQGdokCEEUU2jXGT+niGtjabiE/PbmYr3SCEEEOMJENCdMcIQPF+UFSdbczYsim7lxlAqBT0wWnMmUtFfp0iv86IIj8N7UlRXSJNUNeJSFdrIcQQIsmQELujGdlRokglJBuhdTO0bQfPhkDJoOxrlmshn0aoNEh5kU+6WgshhiRJhoToDVXL1hSFy6G4CVq3ZqfPUo3gj4K/KC/2NxtInbtaNyVN6loz0tVaCDEkSDIkxN5QlOw0Wag0O43Wtj1baP3/27u32CjKPgzgzzuzh9btsrRCWdbySVU00VJiwECJERAjGsCgN2oIYrzSWMBoYiJelBgTiIkmeqMXJgRv5IZDSDyEglBiKIdQGlpUQgICYksVe9hSut2Z+X8XszvtbJdDP7/uaZ5fsiw783Y72/925+k7M+/b/4d9rlFZBFClnQqCPg3RKWWoCo2Oav3PUAJ+jaNaE1FxYhgi+l+VTbFvkfuAwVQoGvjTHs26fCqglfavV3pU68pQAH1DI+gZSOCfoQR8SkNFmQ8+vbR7yoiodJT2pzVRLgTuAapq7bnNbvTY4xQN9tiH1sorS2oC2GzSo1pX3RNE/80R9MQT6BtKQgGYUuaHz8dQRESFjWGI6P/FFwAiNfbkr0N/2z1Fg38BsOxQ5C/P9xZOKl0DqkIBTC0PcFRrIioqDENE/2+6DwhHgVA1cLMXGLgKxLvtq9HKI0CgIt9bOKnSo1pPLfdjYNjAX/Fh9A6NYGBYEA76EfQzFBFRYWEYIposmgaE7h1zsnWXfU7R0BWgLAwEIyV9BZpSo6NaDyYM/D04jOsc1ZqIChDDENFkU8o+obp8KhCZ5bnpPlyjWk8xcD2eGtV6IImKoJ+jWhNR3jEMEeVS1uk+uu3BHT0w3UdFwIeKezNGtR4cRrmfo1oTUf4wDBHlw62m+1AAykt/uo/0qNbTw0H8cyOBa/EE/r6RQJmPo1oTUe4xDBHlk2u6j+upk629M91HmV9DLGNU6+s3hhHQ7Z4iDuBIRLnAMERUCDQdqKgGQtPHT/dRlroCrYS7S9KjWt8bskNRelRrn6YhoCv4dA26UtA5kCMRTQKGIaJCMm66j26g/6p9C4ZKfroPv66cUa37h5L4ezCBRNLEsGHCMAWWiNNWh4Kua/BpgK5p0DUFn6Z43hERTRjDEFGhcqb7qPHcdB9+TWFaRQDTKgIwLcCwLCQtC0lDYFgWDFMwnApJyaQgYZowkwLTSoUlATSV7lECdF3Bp2kMSx4nApiWO1QXOw0KmqagKfC9/S+U7qcpUanw+HQfeqrnJwgNyPJSLQt2ULIsGIbAsARJ00LCMJFIChJJE0lTMJxMwjAltcMQaLB7k3RNwcewVHzGBBtTBGIBpggsASwrtQxjQo8IlNKgaXZQLpUyWyKwLPt+9EUJAAU9HZQ0BQ2Anv6/St1Kt5N5whiGiIrFLaf7ELunqMSn+7gVTQOCdxGW7B4lIGna/x8xLNwcsUOTkQ5LlgAQiACassORE5aUBl1XpXzqVv4IXCHGEruXTyQVcCyBBUnv4x2aUtDVaM+IT1fw6xr8ukJA1+yewdTOX9dSbXXY95NcyFx1PokIjFQgMsWCadk/O9MUjKR6UZOGfW9YAsu0RgMU7Pe7/UQKStk/x/TPS1NwhSddK933P8MQUbFxTffxj30+0eA1z0z3MVGusJSFSCosmYKkaR+GS5oWkoaFm8kxYclKwrQAgeXsONLnKY2GJq1kdxYTke6psFJBxrQEFuywY1kCExlJIXVYU9NGd766puBPnTwf0BUCPh2aGj0/bGywsR9r0NnTcUsiSIUmGQ1M1mjwNEWQNCT1x4IgYZiwLIFhCkwZDVAilutiDgV3INWVgtJGA6deJL2tDENExUrTgNA04J57geF+93QfwYoxJ1pP4JNosvbkE3re3H5yKtgdSgEA0FM3/+haEZ9z6M0wBYYoGKbds5QwLAwnTRiGIJnauYw9NKOnDr3pJXJYRpAKORgNNqO9C6OvUIO9Q7QPzyj4lB0Y/X7N7r3R7CsDnV6b1OErX2qnmg477reNmXE/ZqMyFk3sFWF8N47zWLK0vdXXZukKylyXtbvoFs+T+X2yts14Vyl3s8xVdxzSVQfgU873SB+CtCzAtCxYMnoo0rQASZ/LZwoMw4JhWjAtwIK9fkQEIpbrpShlByhN01LnOwGWmRz/WnKMYYio2GWb7iN+9c799NnW/9u+/Ql9fXGcxJreifjTQQkq/R8Aqb+4rdSJ3el7w0LSAoZHDLtnyRLIZB83yVGXlA5lD3fgSx+Ssq/oGz20opxzU9I9Br5xwSZTliCQs7dHasOybWDmHxQq/U/qptSYrxvzPCqjTXq9a92YZbdtl/m8GP89s76su3k/3L6NBtzl4cTRNqakDsdZ9r3TCyV2oDItwYhh/zExYlpIpK8SDU2/i+8zeRiGiEpJerqPqlr38rveEU9gD5TX5ywcTli6TRvDsiAl0TcEJ+BMmly9B7IFimzBxrWc7sT5m+EuSeownT6Z76m7wDBEVIoyP7z5YZ5X/KAlyk4p+wKFfOPpZkRERORpDENERETkaQxDRERE5GkMQ0RERORpDENERETkaQxDRERE5GkMQ0RERORpDENERETkaQxDRERE5GkMQ0RERORpDENERETkaQxDRERE5GkMQ0RERORpnEz5DkQEADAwMJDnLSEiIqK7ld5vp/fjt8MwdAfxeBwAMGvWrDxvCREREU1UPB5HJBK5bRsldxOZPMyyLPz5558Ih8NQSuV7cwrSwMAAZs2ahStXrmDKlCn53hzPYz0KC+tRWFiPwjKZ9RARxONxxGIxaNrtzwpiz9AdaJqGmpqafG9GUZgyZQo/XAoI61FYWI/CwnoUlsmqx516hNJ4AjURERF5GsMQEREReRrDEP1rwWAQTU1NCAaD+d4UAutRaFiPwsJ6FJZCqQdPoCYiIiJPY88QEREReRrDEBEREXkawxARERF5GsMQEREReRrDkAcdOXIEq1evRiwWg1IKe/fuda0XEWzZsgWxWAzl5eVYunQpzp4962qTSCSwYcMGTJs2DaFQCC+88AL++OMPV5ve3l6sW7cOkUgEkUgE69atQ19fn6vN5cuXsXr1aoRCIUybNg0bN27EyMjIZLzsgrV161Y88cQTCIfDqK6uxpo1a3Du3DlXG9Ykd7788kvU19c7g8A1NDTghx9+cNazFvm1detWKKXwzjvvOMtYk9zZsmULlFKuWzQaddYXbS2EPOf777+XDz/8UHbt2iUAZM+ePa7127Ztk3A4LLt27ZKOjg55+eWXZebMmTIwMOC0efPNN+W+++6T5uZmaWtrk2XLlsm8efPEMAynzXPPPSd1dXVy9OhROXr0qNTV1cmqVauc9YZhSF1dnSxbtkza2tqkublZYrGYNDY2TvrPoJCsWLFCtm/fLp2dndLe3i4rV66U//znPzI4OOi0YU1yZ9++ffLdd9/JuXPn5Ny5c7J582bx+/3S2dkpIqxFPp04cUJmz54t9fX1smnTJmc5a5I7TU1N8thjj0lXV5dz6+npcdYXay0YhjwuMwxZliXRaFS2bdvmLBseHpZIJCJfffWViIj09fWJ3++XnTt3Om2uXr0qmqbJjz/+KCIiv/zyiwCQY8eOOW1aW1sFgPz2228iYocyTdPk6tWrTptvv/1WgsGg9Pf3T8rrLQY9PT0CQFpaWkSENSkElZWV8vXXX7MWeRSPx2XOnDnS3NwsS5YsccIQa5JbTU1NMm/evKzrirkWPExGLhcvXkR3dzeeffZZZ1kwGMSSJUtw9OhRAMCpU6eQTCZdbWKxGOrq6pw2ra2tiEQiWLhwodNm0aJFiEQirjZ1dXWIxWJOmxUrViCRSODUqVOT+joLWX9/PwCgqqoKAGuST6ZpYufOnbhx4wYaGhpYizx6++23sXLlSjzzzDOu5axJ7p0/fx6xWAy1tbV45ZVXcOHCBQDFXQtO1Eou3d3dAIAZM2a4ls+YMQOXLl1y2gQCAVRWVo5rk/767u5uVFdXj3v+6upqV5vM71NZWYlAIOC08RoRwbvvvosnn3wSdXV1AFiTfOjo6EBDQwOGh4dRUVGBPXv24NFHH3U+iFmL3Nq5cyfa2tpw8uTJcev4+5FbCxcuxDfffIOHH34Y165dw8cff4zFixfj7NmzRV0LhiHKSinleiwi45ZlymyTrf3/0sZLGhsbcebMGfz888/j1rEmufPII4+gvb0dfX192LVrF9avX4+WlhZnPWuRO1euXMGmTZuwf/9+lJWV3bIda5Ibzz//vPP/uXPnoqGhAQ8++CB27NiBRYsWASjOWvAwGbmkrwrITNY9PT1OCo9GoxgZGUFvb+9t21y7dm3c8//111+uNpnfp7e3F8lkclzi94INGzZg3759OHToEGpqapzlrEnuBQIBPPTQQ1iwYAG2bt2KefPm4fPPP2ct8uDUqVPo6enB/Pnz4fP54PP50NLSgi+++AI+n8/5WbAm+REKhTB37lycP3++qH8/GIbIpba2FtFoFM3Nzc6ykZERtLS0YPHixQCA+fPnw+/3u9p0dXWhs7PTadPQ0ID+/n6cOHHCaXP8+HH09/e72nR2dqKrq8tps3//fgSDQcyfP39SX2chERE0NjZi9+7d+Omnn1BbW+taz5rkn4ggkUiwFnmwfPlydHR0oL293bktWLAAa9euRXt7Ox544AHWJI8SiQR+/fVXzJw5s7h/PyZ8yjUVvXg8LqdPn5bTp08LAPnss8/k9OnTcunSJRGxL42MRCKye/du6ejokFdffTXrpZE1NTVy4MABaWtrk6effjrrpZH19fXS2toqra2tMnfu3KyXRi5fvlza2trkwIEDUlNT46nLVEVE3nrrLYlEInL48GHX5apDQ0NOG9Ykdz744AM5cuSIXLx4Uc6cOSObN28WTdNk//79IsJaFIKxV5OJsCa59N5778nhw4flwoULcuzYMVm1apWEw2H5/fffRaR4a8Ew5EGHDh0SAONu69evFxH78simpiaJRqMSDAblqaeeko6ODtdz3Lx5UxobG6WqqkrKy8tl1apVcvnyZVeb69evy9q1ayUcDks4HJa1a9dKb2+vq82lS5dk5cqVUl5eLlVVVdLY2CjDw8OT+fILTrZaAJDt27c7bViT3HnjjTfk/vvvl0AgINOnT5fly5c7QUiEtSgEmWGINcmd9LhBfr9fYrGYvPTSS3L27FlnfbHWQomITLw/iYiIiKg08JwhIiIi8jSGISIiIvI0hiEiIiLyNIYhIiIi8jSGISIiIvI0hiEiIiLyNIYhIiIi8jSGISIiIvI0hiEiIiLyNIYhIippr7/+OtasWXPX7ZVS2Lt376RtDxEVHoYhIiIi8jSGISLyjKVLl2Ljxo14//33UVVVhWg0ii1btjjrZ8+eDQB48cUXoZRyHhNRaWMYIiJP2bFjB0KhEI4fP45PPvkEH330EZqbmwEAJ0+eBABs374dXV1dzmMiKm0MQ0TkKfX19WhqasKcOXPw2muvYcGCBTh48CAAYPr06QCAqVOnIhqNOo+JqLQxDBGRp9TX17sez5w5Ez09PXnaGiIqBAxDROQpfr/f9VgpBcuy8rQ1RFQIGIaIiMbw+/0wTTPfm0FEOcQwREQ0xuzZs3Hw4EF0d3ejt7c335tDRDnAMERENMann36K5uZmzJo1C48//ni+N4eIckCJiOR7I4iIiIjyhT1DRERE5GkMQ0RERORpDENERETkaQxDRERE5GkMQ0RERORpDENERETkaQxDRERE5GkMQ0RERORpDENERETkaQxDRERE5GkMQ0RERORp/wXHQL66IZTjsQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_eval_rolling=pd.concat([df_comper_eval_rolling_avg,df_ddpg_eval_rolling_avg])\n",
    "sns.lineplot(data=df_eval_rolling, x=\"Int\", y=\"EpRewRolling\",hue='Method')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7f1bc5999d50>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.catplot(data=df, kind=\"bar\",x=\"Method\", y=\"Avg100Ep\", hue=\"Method\",\n",
    "    errorbar=\"sd\")\n",
    "g.despine(left=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 654.75x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.lmplot(\n",
    "    data=df,\n",
    "    x=\"TotalItr\", y=\"Avg100Ep\", hue=\"Method\",\n",
    "    height=5\n",
    ")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "results_analisy",
   "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": "3.1.0"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}