plot_trees.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'calculate': {'analysis': True,\n",
      "               'friends': False,\n",
      "               'network': True,\n",
      "               'uniquetweets': True,\n",
      "               'uniqueusers': True},\n",
      " 'data': {'dates': ['2018-03-11', '2018-03-12', '2018-03-13'],\n",
      "          'eventname': \"Givenchy's Death\",\n",
      "          'phrases': ['givenchy%20death', 'givenchy%20passed%20away'],\n",
      "          'starttime': 'Mar 12 08:20:00 -0500 2018'},\n",
      " 'path': {'cwd': '/Users/lzhou/git/github/uclresearchanalysis/data/givenchy',\n",
      "          'networkx': {'all': '/Users/lzhou/git/github/uclresearchanalysis/data/givenchy/pickle/networkx_all.dat',\n",
      "                       'friends': '/Users/lzhou/git/github/uclresearchanalysis/data/givenchy/pickle/networkx_friends.dat',\n",
      "                       'potential': '/Users/lzhou/git/github/uclresearchanalysis/data/givenchy/pickle/networkx_potential.dat'},\n",
      "          'newcrawl': '/Users/lzhou/git/github/uclresearchanalysis/other/newcrawl.dat',\n",
      "          'pickle': {'friends': '/Users/lzhou/git/github/uclresearchanalysis/data/givenchy/pickle/friends.dat',\n",
      "                     'needcrawl': '/Users/lzhou/git/github/uclresearchanalysis/data/givenchy/pickle/needcrawl.dat',\n",
      "                     'network': '/Users/lzhou/git/github/uclresearchanalysis/data/givenchy/pickle/network.dat',\n",
      "                     'tweets': '/Users/lzhou/git/github/uclresearchanalysis/data/givenchy/pickle/tweets.dat',\n",
      "                     'users': '/Users/lzhou/git/github/uclresearchanalysis/data/givenchy/pickle/users.dat'},\n",
      "          'result': '/Users/lzhou/git/github/uclresearchanalysis/data/givenchy/result',\n",
      "          'twitter': '/Users/lzhou/git/github/uclresearchanalysis/data/givenchy/twitter'},\n",
      " 'save_to_file': 'False',\n",
      " 'timeframe': '1440'}\n",
      "Loading data file from path /Users/lzhou/git/github/uclresearchanalysis/data/givenchy/pickle/users.dat\n",
      "'Loaded 5011 entires'\n",
      "Loading data file from path /Users/lzhou/git/github/uclresearchanalysis/data/givenchy/pickle/networkx_all.dat\n",
      "'Loaded 5011 entires'\n",
      "Loading data file from path /Users/lzhou/git/github/uclresearchanalysis/data/givenchy/pickle/networkx_friends.dat\n",
      "'Loaded 5011 entires'\n",
      "Loading data file from path /Users/lzhou/git/github/uclresearchanalysis/data/givenchy/pickle/networkx_potential.dat\n",
      "'Loaded 5011 entires'\n"
     ]
    }
   ],
   "source": [
    "import math\n",
    "import numpy as np\n",
    "import networkx as nx\n",
    "import pandas as pd\n",
    "from collections import Counter\n",
    "import operator\n",
    "\n",
    "import config\n",
    "from config import load_users_dataframe\n",
    "from config import load_networkx_all\n",
    "from config import load_networkx_friends\n",
    "from config import load_networkx_potential\n",
    "\n",
    "# Plotting\n",
    "import matplotlib\n",
    "# matplotlib.use('Agg')\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "import seaborn as sns\n",
    "\n",
    "# Networkx\n",
    "from networkx.drawing.nx_agraph import graphviz_layout\n",
    "import dzcnapy_plotlib as dzcnapy\n",
    "\n",
    "project_name = config.settings['data']['eventname']\n",
    "timeframe = config.settings['timeframe']\n",
    "save_to_file = config.settings['save_to_file'] == 'True'\n",
    "window = 30\n",
    "unique_users = load_users_dataframe()\n",
    "network_all = load_networkx_all()\n",
    "network_friends = load_networkx_friends()\n",
    "network_potential = load_networkx_potential()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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>user</th>\n",
       "      <th>user_id</th>\n",
       "      <th>time_lapsed</th>\n",
       "      <th>followers_count</th>\n",
       "      <th>friends_count</th>\n",
       "      <th>mention_and_reply</th>\n",
       "      <th>source_candidates</th>\n",
       "      <th>source_index</th>\n",
       "      <th>seed_index</th>\n",
       "      <th>generation</th>\n",
       "      <th>time_since_seed</th>\n",
       "      <th>exposed</th>\n",
       "      <th>pos_x</th>\n",
       "      <th>pos_y</th>\n",
       "      <th>pos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>davelackie</td>\n",
       "      <td>100766356</td>\n",
       "      <td>0.00</td>\n",
       "      <td>143119</td>\n",
       "      <td>4643</td>\n",
       "      <td>[]</td>\n",
       "      <td>[3, 5, 6, 7, 10, 11, 14, 15, 19, 20, 24, 74, 8...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>(1, 6)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>alexanderskhan</td>\n",
       "      <td>3186545203</td>\n",
       "      <td>0.15</td>\n",
       "      <td>753</td>\n",
       "      <td>3428</td>\n",
       "      <td>[0]</td>\n",
       "      <td>[0]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>(2, 5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>consiglierela</td>\n",
       "      <td>4134992843</td>\n",
       "      <td>0.23</td>\n",
       "      <td>2161</td>\n",
       "      <td>396</td>\n",
       "      <td>[0]</td>\n",
       "      <td>[0, 12, 21, 32, 48, 748, 819, 972, 2358, 2778,...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>(3, 5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ImpactPrincess</td>\n",
       "      <td>1955472014</td>\n",
       "      <td>0.63</td>\n",
       "      <td>242</td>\n",
       "      <td>642</td>\n",
       "      <td>[0]</td>\n",
       "      <td>[0, 115, 577]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>(4, 5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>panagiota_karag</td>\n",
       "      <td>2938214163</td>\n",
       "      <td>1.18</td>\n",
       "      <td>250</td>\n",
       "      <td>493</td>\n",
       "      <td>[0]</td>\n",
       "      <td>[0, 20, 577, 1012, 1591, 1656, 1807, 1953, 320...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>(5, 5)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              user     user_id  time_lapsed  followers_count  friends_count  \\\n",
       "0       davelackie   100766356         0.00           143119           4643   \n",
       "1   alexanderskhan  3186545203         0.15              753           3428   \n",
       "2    consiglierela  4134992843         0.23             2161            396   \n",
       "3   ImpactPrincess  1955472014         0.63              242            642   \n",
       "5  panagiota_karag  2938214163         1.18              250            493   \n",
       "\n",
       "  mention_and_reply                                  source_candidates  \\\n",
       "0                []  [3, 5, 6, 7, 10, 11, 14, 15, 19, 20, 24, 74, 8...   \n",
       "1               [0]                                                [0]   \n",
       "2               [0]  [0, 12, 21, 32, 48, 748, 819, 972, 2358, 2778,...   \n",
       "3               [0]                                      [0, 115, 577]   \n",
       "5               [0]  [0, 20, 577, 1012, 1591, 1656, 1807, 1953, 320...   \n",
       "\n",
       "  source_index  seed_index  generation time_since_seed  exposed  pos_x  pos_y  \\\n",
       "0         None           0           0               0      0.0      1      6   \n",
       "1            0           0           1            0.15      0.0      2      5   \n",
       "2            0           0           1            0.23      0.0      3      5   \n",
       "3            0           0           1            0.63      0.0      4      5   \n",
       "5            0           0           1            1.18      0.0      5      5   \n",
       "\n",
       "      pos  \n",
       "0  (1, 6)  \n",
       "1  (2, 5)  \n",
       "2  (3, 5)  \n",
       "3  (4, 5)  \n",
       "5  (5, 5)  "
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_users.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading data file from path /Users/lzhou/git/github/uclresearchanalysis/data/givenchy/pickle/users.dat\n",
      "'Loaded 5011 entires'\n"
     ]
    },
    {
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WenLaKJS/kNbpYVJgYJJdSZ5I8s+S/GramI5buq9JgY37M9ph443l1r5Saq0npQUm5gMbN2Vhp5G5JA9nENj4cpJXMhipMh/cGO+SMZfkkQzGotyZ5MFSyu5a68YkV2R0PMqkzhl70jpn3Nedc2Pa6JYtSS6ecElvpwU8hkMbXy+l+B9NAAAAAADAQRPQgH3oflP+7QmbfqeU8sOHu56lqLX+myTf1z38i6WUX+mzHpg2tdYz0l6DP53k6iRHL3HXnWlBhH+c5H9PCyzckkFgYzh0MJcWNvhC9/WlVRbYmEkLPgwHNv5/9u47Sq77PPP8FzkQmcgkEZhJJCI2JIoyoR1J9JFNyQrWKFJxPLJ3z+54ju2ZPbPzzqs4kiU5aEzLXqeVrBlJtmWtpHWQxoYCZaFBZBAEQAAkAIIgiJxjo3v/eG/hhrrV6OpUHZ7POThmoX731q+CgRbuU8/7ENUjTs4R4Yds08YE8i0bD1EduLhEjFSpBDaagQPJaJRRwCLyTRvtNWdsA04njzE/WT+75GkdBTaQCW2Y2dGOvB4iIiIiIiIiIiIiIiKggIbITbn7daov7B0yszsasZ+bSS6MniYucrYBM8zsWGN3JTJ4uftc4K3AE0RQYEQHD71IhAeeBP6aCDk8mvxaTXVgYzP5wMbpru69O7n7GGAp+dEoc0uW7icf2NhBjFDJtmzcU3LcUdKwRjMRoDidPPYtyWNnQxt3l5zjHNGc8SxwHhgL3JusLzZ7ABwgH9rYaGZnar4IIiIiIiIiIiIiIiIyqCmgIXIT7n4KmJTcbAOGAFfNbFTtoxrL3e8Fdic3j5jZrEbuR0RCEqC6G3gn8B4iaDCsg4efI1ojfgf4PmlgY03y39ngRzawsZYIbPS54EDSNpINbKyiekTMNaLpIjsa5VSyttKy0QTcWvIQu8m3bGwzs6vJY08mPxplBXB7yTmOE+GLvURzxwRgAbCsZK+Vx6wENtYDW8zscrsvhIiIiIiIiIiIiIiIDAoKaIjchLtvAJYXf9/MhjRgOx3m7p8FfjO5+WUz+1gj9yMi1dx9KHGx/73AO4hGiWJjTy2nidDB54jQQrFhIxvYaKW6YaMvBjaGES0j2dEoDxLBuKzjpE0Z64gwxBTSsEYT0ZhRDNJdIV6HyrHrgefNrC15/FnkQxsrKQ9+HEoe8yARIJkMLEl+FRtSWoDtZEajADvMrOXmr4iIiIiIiIiIiIiIiAwkCmiI3IS7fw74jZK7bjezl3p7P/Vw9/2kIwSWm9mmBm5HRG4iCSgsBT4EPA7MpjqcUKYNOAk8BXyKGAvyKtLARhPVgY1NpIGNp/piYAPA3ScQQYls08b0kqU7yY9G2U2EXyrNHE3AfSXHHSeCGpWWjfVmdjJ57CHAPPItG8uB8SXn2UOMR3mZeD+mE+9lWcDkEhEUyYY29ppZazsvhYiIiIiIiIiIiIiI9HMKaIjchLsvJL79XGRm9vHe3k893H0ccIb4Rv4lYJwuAIr0H+4+kggXfBR4DJhGxwMbx4B/Aj4BHABeTRrYWEV1YGMj+cDG2a4/g+6XhCbmkm/ZWAaMLCy9CGwgH9q4SIQssk0b00oeZi9py0YzsNXMriSPP5QIemRbNh6iuq2jlQjKbCbei2HAbUTA486SxzyT7Dcb2jhUafcQEREREREREREREZH+TwENkZtILgaWhRq2mNnS3t5Pvdz9vcBXk5s/MrNHG7gdEekCdx8DPAz8W2ANMdajI1qBI8A/AB8nWiMqDRtriMDG8ML6jcBa0sDGuS4/gR7i7qOI8SLZlo27SpYeIh/Y2Eg0XWRbNpYDowvHXQW2kI5FaSYaLyqjUUYCC8mPR1lIhDLKzrOdGFEzkgibrARmlez3FfKBjafN7PhNXg4REREREREREREREemjFNAQ6QB3v0R6wa6N+Ab7OTOb0LhddZy7/wR4TXLz3Wb2Pxq5HxHpHsn4jzXArxDBjY7+mXSdCCt8hwhsXKK6YWN4YX2xYaPPBjYA3H0a8TwqgY0mql+f68A20sDGOuAF0tEoleDGA1Q3l5wiDWtURqPcCE+4+1iiWSPbtHFvyVbPE+NmdgLngLHAPUTYY3LJ+v3kQxsb+/p7ISIiIiIiIiIiIiIiQQENkQ5w9xeAecnNSkCjzcyGNmxTdUgq+S8QIZPrwCQzO9/YXYlId3P3W4E3EIGNlcTF/o5oIcag/BXwaeLPuWxgYyXVgY0NpIGNn/b1kEBmNEl2NMoiYgRU1mnS0MU6IoTRQgQmKi0bTcDMkod5nnzLxmYzu5zZwyRiHEs2tDGn5Dwnidd3LxGeGQ88mBxbfE/bgF3kQxtbs48rIiIiIiIiIiIiIiJ9gwIaIh3g7n8FvL3krtFmdqW399MZ7r6KuGAI8LyZldX/i8gA4u6zgF8APkyMACmO7qjlKrAP+BrweWAEaWBjDREsyI7vuE4EA35IGtjo8yEwdx9HjDSpBDZWUz5qZA/50SjbiIBGJbCxighwFMMTLcBWMi0bwHNmdmNslrvPID8aZSUwrWQPh4nQxgHgGtGusTj5NaLkcbeRD208a2Yt7bwcIiIiIiIiIiIiIiLSwxTQEOkAd/9l4Bsld73ZzL7T2/vpLHf/E+JCLcCnzOw/NXI/ItK73H0e8EvAE0QjQ/HCfi2Xgd3AnwP/DRhDjFR5lLRhIxvYaCHCBGuJwMa/9JPAxhDgdtLARhMRnigGWy4TY0myo1EOk45GqQQ3FlA9GuUMEdS4MR7FzI4W9nAH+cDGCsrH1zxPjJ45TDRpTAOWUj6S5VKy52xoY6+Z6QdBEREREREREREREZFeooCGSAe4+xjgYsld3zGzN/f2frrC3V8Bpic37zGzvY3cj4g0RhIEuBd4J/Au4B7yIYv2XAR2AH8I/AUwjnxgYwXVqM3j7wAAIABJREFUgY1iw8aFLj2BXuLuI4hRKNnRKPeWLD1CPrCxgQhJVBo6KsGN20qOPUC+ZWOTmd34OycZz3IP+cDGMqqDI63ATmAzcIx4D2Yne5hf8rink31mQxsvKbQhIiIiIiIiIiIiItIzFNAQ6SB3byG94NhGXHg7YmZldfh9lrvPJL5tPYT4JvdkXYwTkSQEsBB4LzHSaS4wtIOHnwe2AL8H/A0R2HgNaWBjOdWBjfWkgY1/6S+BDQB3n0LaklEJbkwuLGsFniENXqwjwhOzyLdsrCBer6zrxIiS9ZnjdxVGowwnGjqyTRuLgOGFc11LzrUdOAWMJN7bFcSYlqIj5AMbG8zsePuviIiIiIiIiIiIiIiIdIQCGiId5O7HgVuTm5WARouZdXREQJ/h7v8H8DvJzW+b2S81cj8i0vckAYClwAeAx4nmh+LYjFrOEBf3P2dmP3D3CaQNG2uIwEY2/FEJbGRHopS1FvVJSRvJ3eRbNpZQHZY4Rxq6qLRtnCBGkmRbNhZRHY45R7ymlZaNZjN7ubCP0cBDRPiiEtq4n+r37SIx7mQnEa4Zk+x/BTCp5Cm+QD60scnMztV+RUREREREREREREREpIwCGiId5O4/BV5dctfQ/thA4e5bgcXJzcfM7B8buR8R6dvcfRQRHvgI8BgwjY4FNtqI5oafAp8ys+YksFFs2MgGEq5R3bDRbwIbcGM01jLyLRtzSpa+QD6wsZkIdiwnbdloAu4oOfZF8i0bG4tNJMlrvYx808a8knNVxp3sBS4B44ngyDIiwJHVRoQ7sqGNrWZ2peS8IiIiIiIiIiIiIiKSUEBDpIPc3YD/UnLX/Wa2u5e302XuPpL45vQI4mLoODO72thdiUh/4e5jiVaMXyFaMaZ08NA24DgRvPi4mT3j7hPJBzaWUR3YaCYNbPysvwU2ANy9Mt6kEthYCdxSWHaVGBdTCWysI0IcM8kHNlYSIYqs4liV9cCzZna9sI9pRAAkG9qoNe5kA3Aw2ddkot1jMbVHqWRDGzvNrKX2KyIiIiIiIiIiIiIiMrgooCHSQe5+F/HN4qLPmdlv9fZ+uoO7vwGoNGdsM7MljdyPiPRfSchiDRHYeDUwoYOHtgKvAN8nAhvPJ+d6hDSwsZR8YOMq1YGNS119Dr0tGSPzIPnRKA9Q3UxyjDR0sY4IP5wjxpdUxqI0EcGJYYVjzxMhixtNG2b2UmEfQ4gRNtnARq1xJ/uBjcBhImwzlXh/2hulkg1t7OuPrVMiIiIiIiIiIiIiIt1BAQ2RDkouYF2n+gLUs2a2oAFb6hbu/rfAW5Kbv25mv9PI/YjIwODuU4E3AB8lAgRjO3jodeLi//eIwMYRd59ENGysIQ1sZP8srgQ21hKBjXX9MbABN4IuK8k3bUwrLKuMGMmORtkBjCRem0rLxirKx5kcJt+yscHMzhX2MQS4i3xoYxnV72MbsJto/ThKBGlmEQ0dZY99igiM3AhtFAMjIiIiIiIiIiIiIiIDlQIaInVw9wukF6faiAuEF82sWFHfbyQX4U4BE4nnNNvMjjR2VyIy0Lj7bOAXgA8TTQ+jO3hoCzFi42+AT5vZ6SSwUWzYKAY21pFv2Ljc1efQCMmf0fPJBzaWEmGMrAtE8OHGaBQze9ndZxBBjUrLxiriz/usNiLgcaNlA9hRHE+SNH48QL5lYwkxKiurBdie/DqV3D83WT+j5Gm+TL5lY4OZnWjnZRERERERERERERER6ZcU0BCpg7s/B9xT+O02Mxtatr6/cPe7gT3JzaNmVnYBTUSk27j7fKK95wPERf/iRf5argH7gG8AnzWzS+4+mXxg4yHygY0r5AMb6/prYAPA3UcRzzE7GmV+ydIXyQQ2iHEjV4i/x7ItGw8BwwvHXiRGmVRaNpqBF4vjSZK9LCbftPEA+ZE0AJeBzUTzxzlgDNHQsYLqwAjA8+RDG5vM7Hz5KyIiIiIiIiIiIiIi0j8ooCFSB3f/KvDekrsmmtnZ3t5Pd3L3TwP/Mbn5Z2b24UbuR0QGj6Ql4j7gHcC7iQDBsA4efgV4DvgL4PfNrCUJbLyWNLCxhOrAxs9IAxvN/TmwAeDu00lDF6uJ4MX4wrIWYBv50MYeYBTRyrEqc447Sx7mCPmWjQ1mdqZkL+OIcSgrSEMbd5Wc7yzR+rGXCHCMA+5P9jKmsLaVCHdkQxvbzOxKyXlFRERERERERERERPokBTRE6uDubwK+V3LX+8zsL3t7P93N3Z8n/Rb2ajNrbuR+RGRwcvehwCIirPEOYjxGR5uKLgHPAn8E/KmZtbr7FKJhYw1pYCOrEthYSxrY6NcX/t19GBF2yI5GWUj163iKNHCxDlhvZifdfSr5sShNwOTCsW3ALvItG9vN7FrJfqaQD2ysBGaXbP0YEdo4QIyqmUR8FhZR3fJxDdhKPrSx08yu13hZREREREREREREREQaSgENkTokVe5l37L+vpm9sbf3093cfTxxsW4YybeZdaFLRBrN3YcDy4H3A48Dt5FvxGjPBeIi/peAb5hZm7vfSn4kSjGwcZnqho1+HdiAG80WK0hDG6uBmSVLnyMNbDQTrRstwN3kWzYeAkYWjr1MjFJpzvw6UByNkuxnNtWhjSkl+zlIjFt5mWjSmJo89n1Ufw4uJI+fDW08X/b4IiIiIiIiIiIiIiK9TQENkTq5+zXSb/G2EReHjpnZ9Mbtqvu4+7uA/57c/KmZvaaR+xERKUrCck3AR4A3AvX8+VsZq/EF4O8zgY3sSJTFhWMuA/9CGthYP0ACG0OAO8i3bCwHRheWXiYCEtnRKIeIcMYS0sDGKmI8TdFR0oaN9cTrd7rGfuaTD2wsB24pOedzwJbk3EOBWcRYlbkla08S7/mN0IaZHS5ZJyIiIiIiIiIiIiLSoxTQEKmTu79CejGwEtC4bmbF6vV+y91/CPxccvMJM/tKA7cjItIud78FeA3wUWKMSVkLQy2niLaMz5jZU8n5ppIfibKocMwlqgMbVzv9BPoQdx9BBFQqgY3VlIcuXiYf2NhgZheSUSaryDdt3Fpy/G7S0EYzsK3sNUxGtdxHPrRR1txxHdgBbCfe0xFE+GQF5QGew+RbNjaY2cmSdSIiIiIiIiIiIiIi3UYBDZE6ufta4oJd0fCBMg4kuSB2FhhL1MlPNrOzjd2ViEjHuPtEIlzxb4CHgQkdPLQNOAH8CPikmW1JzjeVfMNGrcDGWiKw8fRACWwAJA0jlcBFJbgxqbCslQhHZEej7CJe0/nkWzaWAaMKx18BNpO2bDRTYzSJu48k3oNKYGMFsJBo0iiecwuwEzgHjAHuTNaXfSb2kQ9tbDKzC6UvioiIiIiIiIiIiIhIJyigIVInd/8N4HMld600sw29vZ+e4u7LiUp4gINmVlYbLyLS57n7NOD1RGBjBeUjM8q0EiM0/ifgZrY3c75sYGNh4bhLwE9JGzYGWmBjKNGqkQ1sLAGGFZaeJcIWlcBGs5kdSwIWi8m3bNxX8lAnyLdsPG1mJ2rsaSywlHzTRlnzx3liXMte4n0alzz2UqpHu7QCz5IPbZQ2fYiIiIiIiIiIiIiIdIQCGiJ1cvc7gIMldz1pZr/W2/vpSe7+ZeBXkpu/bWa/2cj9iIh0B3e/DXgT8GEiWFBsc6illRiN8XfAx83speR804ixUI8mvxYUjrtIPrCxYaBd5E8CEsvIj0a5vWTp82QCG8AWM7vi7pOIUEWlZaOJ8tEke8m3bGwxsys19jSJCOSsIA1t3FGy9DgR2jgAXAMmEqGbRVSHTq4CW8mHNnYNlAYtEREREREREREREelZCmiIdIK7twJDCr+9x8zubcR+epK7vwzMTG7eb2a7G7kfEZHu5u7zgV8CngAeAEZ08NAW4EXg28RIlJPJ+aYTDRtriMDGg4XjKoGNykiUDWZ2rUtPog9KgjCVhozVRFBibGHZVWK0SSW0sQ7Yn9w3l3zLxnKqWy6uEWNMKoGP9cTfx6U/4Lr7DPItGyuBqSVLXyJCG4eJYM5UIsxT1vRxHthEPrTxQq09iIiIiIiIiIiIiMjgpYCGSCe4+zmiFh2gjQhrXDazMY3bVc9ILjQeIZ7jOWCSmbU2dlciIj3D3YcA9wPvAN4N3E11i0It14AXgG8CnzGzi8k5Z5AfiVIMbFygumFjIAY2hhPNFNnRKA+ULD1GPrDxtJmddfcRmeNXZY4vBiZPEUGNSsvGejM7VmNPQ4ggSLZlYwUwvmT5XiIMcix5zJlEa8ickrUniDFhN0IbZvZy2R5EREREREREREREZPBQQEOkE9x9B9UX2DCz4kWiAcHd/1fgS8nN/8/MfqGR+xER6S3uPhRYTIQ13k5czB/awcOvAnuArwJfrIQuksBGdiRKMaRwAXiKNLCxcSAGNuDGGJKVpIGNJqobLdqAZ0kDG83ADjO77u4TiWaNpsyvmVR7gbRlozIa5VKNPQ0F7iXfsvEQ1e0drcm+thOhkBHEWJcVwLSSU79EvmVjg5mdKtuDiIiIiIiIiIiIiAxMCmiIdIK7/zHw0ZK7ZpjZ0d7eT29w983EBSqAx83su43cj4hIIyQtDsuB9wOPA7OpbnCo5TKwE/gT4MuVNiJ3n0k+sHF/4bjzVAc2Wjr/LPqupNHiTvItG0upHjtznmiouNG0YWZHkuNvJw1rrKJ8tEoLsJV0LEoz8FythqjkfV9APrSxiOp2lavANuJ9PkeEOubTfitHNrSx2cwulO1BRERERERERERERPo/BTREOsHdHwXWltz1a2b2ZC9vp1e4+0jiYtNI4sLWeDO73NhdiYg0lruPIoIEHwIeA6bXcfhFIiTwJPA1M2tLzlkJbKwhAhv3FY6rBDbWEoGNTQM1sAHg7qOJgGAlsLEamFey9CD50SibzexSMlplAelYlKbkdjFYc4YISVRaNtab2Svt7GtMsq/saJRiuAaiEWUTEca4RIxIu5cInowqrG0FdpAPbWw3s6u19iEiIiIiIiIiIiIi/YcCGiKdkIQVrpTc9WMz+7ne3k9vcfd/BfwgufmsmS1o5H5ERPoad78FeAT4CBGwmFLH4eeIC/lfBL6bCWzMIt+wURbY+AkR1lhLBBMGbGADboyJqYQtVhMBiWJDRQuwhfxolL1m1ubu40lHo1SCG7eVPNQB8i0bm8zsYjv7mpCcN9u0Mbdk6SlgY3L+q8BEIjSykOpWjitEkCcb2thtZtdr7UNERERERERERERE+iYFNEQ6yd2vUl25ftLMbm3EfnqLu/8V8Pbk5n8ws882cj8iIn2Zu08ighr/Bng1MKGOw08ToYDPmtmN1iZ3n00+sHFv4bhzpIGNHzI4AhvDgAfIj0ZZSHVLxknygY31ZnYqOcdt5Fs2VhBtF1nXge1kWjaAnbVGoyTnnUbasFEJbcwoWfoyEdB5iWjSuBVYQvX7CxHK2Ug+tLG/EuoRERERERERERERkb5JAQ2RTnL3l4DZhd9uNbPiN18HFHcfQlzgmgS0AXPM7FBjdyUi0j+4+3TgDUTDxkpgbAcPbSP+7P0J8Ckz25A552zSsMajwD2FY8+SD2xsGeiBDYCkJWMF+dEoZcGI3eRDG9vN7Foh9FEJbiwChhaOP0cEJCotG81m9nI7+xoC3E6+ZWMF0aJR9ALRAnKUCJvMJEaj3FGy9jiwgUxow8yO1NqHiIiIiIiIiIiIiPQ+BTREOsnd/wF4Y8ldowb6rHh3vwvYm9w8AUzTt3ZFROrn7rcDbwI+RLQljOrgoW3AMeCfgI+b2a7MOW8jGjbWEIGNuwvHVgIba0kDGwN+XEYSjJhDPrCxjOrX/BLRTlEJbKyrBBGTETbLSFs2migPSxwi37Kx0czOt7O3ocT7lG3ZWAaMKSxtA3YCzxCBnRFE2GM5MLXGPrItGxvM7HStfYiIiIiIiIiIiIhIz1JAQ6ST3P1jwJMld70uW0U/ULn7fwEsuflVM3t/A7cjItLvJQGC+cCbgQ8Q7Q3FUVq1tBIjMv6RCGwcyJz3dvIjUcoCGz8mwhprga2DIbAB4O4jiWBMdjRK8fUBOEwmsEEELi4k55hFNGxUWjZWUj3KppUIVdxo2QCebe91dvfhwIPkmzYWA8MLS68RY1d2Ee/laOJztAwYX3LqPeRDG5vN7GKtfYiIiIiIiIiIiIhI91FAQ6ST3H0GUFYd/hdm9sHe3k8juPse0gtZj5jZU43cj4jIQJIENh4A3ga8mxhd0tExWteJ9oTvEIGN45nz3kE+sHFX4dgzpIGNHzKIAhsA7j6VCFtUAhtNVI8fuU6EIrKjUXabWWvShnE/aWCjiQhWFN+7C8RIkhtNGzcbGebuo5NzZUMbDxDjT7IuAZuAfcBFYBzx+VkKjCx5LjvIhza2m9m19vYiIiIiIiIiIiIiIvVTQEOkC9y9leqLIvvNbH4j9tPb3H0ccJq46HQFGK8LOiIiPcPdhxEX598FvB2YCwzt4OEtwH7gr4HPmNnZzHkrgY3KSJQ7C8eeJh/Y2DbIAhtDgXvJBzbKAhdniIaMSmCjuRKMcfexRDiiiTS4Ma/k4Q6TjkVpJkaSnLvJ/sYTbRmVwMYKqt/Dyv42AgeAq0To5EFgIdWfoyvAFvKhjd1m1treXkRERERERERERESkfQpoiHSBu5+husb8ipmNbsR+GsHdfxn4RnKz2cxWN3I/IiKDhbuPIC7Gvw94HJhNdWiwlqvAXuBrwBfM7ErmvHPIN2zUCmysJQ1sDKoL9+5+CxGKqIQ2VgO3lSzdR340ylYzu5qcYwYRqKiEPlZR3dTRBjxLpmUDeMbMWm6yv1uJz0a2aWNWydJXiKaNw0STxq3EyJeyMS/niIBHNrRxwMz0PyZEREREREREREREOkgBDZEucPctxIWMoqGD6YKFu/8T8Lrk5kfM7E8buR8RkcEoGX+xGvgg8BgwvY7DrwC7gD8D/iDbkOHuc8kHNootUadIGzbWEuMxBlVgA8DdbycNW6wmAhJjCsuuEIGI7GiUA2bWljR13EO+ZWMJMKJwjotEUKLSstEMvHiznzvc/TaqQxuTS5YeINozjhGBnxlE+0dZAOUYMablRmjDzF5pbx8iIiIiIiIiIiIig5kCGiJd4O6/C/zvJXfdaWYv9PZ+GiWp3T8LjAVagWlmdrKxuxIRGdySMVSPAB8mxpdMqePwi8AzwB8CX8kGLpLAxqOZX/MKx54CfkQ6EmWwBjZGEONDKoGNJuD+kqWvkA9sPF0Za5KEbh4i37JxVzvnqLRsPG1mZ26yvyFEO0o2sLEMuKVk+W7i83ASGA7cDiyn/DP1IvmWjQ0324uIiIiIiIiIiIjIYKGAhkgXuHsTcUGl6LfM7HO9vZ9GcveHgM3JzUNmdkcj9yMiInnuPpkIanwEeJjqEV3tOU/8Gf97wLeybQ3uPo9o2FiT/JpTOPYk+cDGM4MxsAE33oOV5EejFEMObcAO8qGNZyutJu4+lQhqVFo2VtU4xy7yLRvbzezaTfY3DHiAfNPGEmBkYWkLEdjYRYw+GU0EdWoFPJ4jH9rYbGaX2tuLiIiIiIiIiIiIyECkgIZIF7j7cKDsYkezma3u7f00mrs/CXwsufn7ZlbWLiIiIn2Au88AXk8ENlYSLUgddYa4+P95M/t+4bzzSNs1bhbYWAvsGMSBjSFEI0Y2sPEQ0VKRdZ4INlQCG81mdiRzjrtJAxtNyTmKoYrLpONVKsGN/R0YjTIKWES+aeNBYGjJ+bcA+4gGlluIkS1lAY/rRMAjG9p45mYBEhEREREREREREZH+TgENkS5y98vAqORmGzGv/YyZTWrcrhrH3Q8Ds5Kbi81seyP3IyIiHePudwA/T4xEWUL6d9vNtBFjTX4KfNrMbjRLJeGBeeQDG8WGpRPkGzYGbWADwN3HAEvJj0aZW7L0AGlgYx3RSnE5Occo4j2sNGw0EWGJomPkWzaeNrNTHdjjLckes6GNu0uWniVCIQeBq8BEoqGjvYBHNrTx3GD+LIiIiIiIiIiIiMjAo4CGSBe5+wGqvx3cambDGrGfRnP3acAR4sLLBWCCLq6IiPQvmWaHx4EniIvqIzp4eBtwnGjH+GQ2qJcJbKwhDWzcXjj+OPnAxrOD/e8Rd59JPrCxiupRIteIgEN2NMq+SkOGu08hghRNmXNMLXm450gDG+uBrWZ2tQN7nEx+NMoKqt9biFDIZuAw0aQxBVhMfN6KzgIbyYc2Dt6s9UNERERERERERESkr1JAQ6SL3P3bwJtL7hpnZhd6ez99gbv/KvAHyc3vm9kbG7kfERHpmiRY8SDwVuA9RFtCR4OIrURw7wfAx83s+cJ555OGNdYAtxWOrwQ21pIGNgb1D7DuPox4P7KjUR4kWryyTpAPbKw3s9PJOSqvfbZlYxnVzSlXiEBFtmnj+Y68B+4+i3xoYyVwa8nSQ0S45GjyHGYQY1pml6w9Rj6w8bSZHb3ZXkRERERERERERET6AgU0RLrI3Z8A/qLkrjeb2Xd6eTt9hrtvAJYnN99mZt9q5H5ERKT7JAGBJcA7gXcQIziKIytquU60J3wX+ISZHcmcdwhwJ/mRKMXAxjHSho21wM7BHtgAcPcJRBgiG9qYXrJ0F/nRKM+YWUtyjpHAIvItG/eXnOMEaWBjPRH8ONGBPVYaVLKhjeXA+JLle4BngJPAcOJzsIxo3Cg6SD60sdHMztxsPyIiIiIiIiIiIiK9TQENkS5y91uJb/cWfdPM3tnb++krkos854CRQAswabA2ioiIDHTuPoK42P4eolVqNtVtDrW0EBfYvwV8qtLwkJy3MmrlUdLARrFV4RjpOJQfosAGcOO1m0s+sLGM+Hs56yKwgUzThpm9lDnPJOK9rbRsNFEe/NhLvmVji5ld6cA+hwL3kW/ZeIjqJo9WYAcRMDmb3D8PWEr1uBeA3eRDG1vM7NLN9iMiIiIiIiIiIiLSkxTQEOkG7n6d6m8OHzKzOxqxn77C3dcA/5zcfM7M7mvkfkREpHe4+2jgVcAHgMcov6BfyzVgH/B14HPZi+qZwMYa0sDGrMLxR8kHNnYpsBHcfRTRfFIJbDQRr2fRIdKgxTqikeJico4hwBzyLRvLgTGFc1wjxpZUWjaagT0dHI0yElhAPrSxkOqxOleArcTn5SIR1Lg7eY4jCmtbiEaObGhjh5ldu9l+RERERERERERERLqLAhoi3cDdTwKTC799zcyK31IddNz960QFPsB/NrNPNHI/IiLS+9x9PPAI8GEiVFH8O7M9V4DniHFiX8peUE/CAneThjUepXZgY23yf3crsJFy92lEyKIS2GgCJhSWXQe2kWnZIIKXrck5RhABimzLxgNUt6icIoIRlfDHejM71sF9jiWaNSqBjRVE80bReWAz0cpyGZiY7OUBqsO0l5O12dDGnsrzEhEREREREREREeluCmiIdAN3X09cLCgaNtj/kT+5eHaC9GLcfDPb37gdiYhIo7n7ZCJQ8VHgYWB8HYdfIkZd/N/An2T/nk3+zrmH/EiUmYXjXyFt11hLBA30A3EiM3IkOxplEdXhhtNEM0YlsNFsZicy55lAhCiaMr+K7wXAC+RbNjZ3dBSJu08k2juyTRtzSpaeIIIYLxNNGlOS53RnydozwEbyoY0X9RkRERERERERERGR7qCAhkg3cPdPA/+x5K5FZvZMb++nr3H3ecDzxDdpTwG36kKHiIhUuPsM4PVEw8YqYGwdh18gRml8Cfhm9u+XJLBxL2lg41GqQwJHyI9EUWCjwN3HEUGISmBjNdVNJQB7SQMb64BtZnY1OccQ4HbSsShNRICj+F63kLZ1VIIbuzsaeHX36eQDGyuBaSVLDxOfm6PEzyfTiYaOsud1lHxg4+mONn+IiIiIiIiIiIiIZCmgIdIN3H0psKnkro+bmfX2fvoid//PgCc3v2Fm/7qR+xERkb7L3ecAPw98CFgCjKrj8LPABuALwN/XCGxUxqE8CswoHP8y+cDGHgU28gphi0rTxgpgdGHpFaKNIjsa5WDl9XT34cCDpA0bq4AFVLd1nCEdjbKeaOt4pY693kE+sLGC6jEuAPuIdpaTwDDgNmAp5SN5DpAPbWw0s7Md2ZOIiIiIiIiIiIgMXgpoiHQDdx9GfOOzaIuZLe3t/fRV7r6buDAG8L+Y2T83cj8iItL3JRfY7wZ+EXiCuKA/vI5TnAJ+BnzGzJ4qOfd95Bs2agU21ib/d68CG9XcfQQxNiQ7GuXekqVHyAc2NpjZucx5xhNtHZWWjSYiKFF0gHQsSjOwycwudnCvQ4lROCtIQxtLgTGFpa3ATmAXEfwZBcxN1habP9qA3eRDG1vM7HJH9iQiIiIiIiIiIiKDgwIaIt3E3S9R/c3R82Y2vhH76YuSivRTxIW1q8D4SvW5iIhIRyShigXAW4F3E+GNYR08vA04AfwI+ISZbS059/3kAxvTC+c4TNqusRbYp8BGOXefQj5osZrqNopWorUiOxpll5ldz5zntsx5VhGBinGF81wHtpNp2Sie5yZ7HU58rrJNG4uoDgNdI0aw7CPG69wC3AUsBkYU1rYke8qGNnaYWVmoV0RERERERERERAYBBTREuom77wPuLPx2m5kVa7oHNXd/G/DXyc2NZraikfsREZH+LWmxWgr8MvAOYA7VIzJqaQWOAj8gAht7CueuBDayI1GmFc7xEvmRKAps1JBpQ8m2bCyhOgRxjjRksY4YaXI0c55hwAPkwx+LqH7fzxHjbiotG+vN7HAd+x2d7C8b2rgfGFJYehHYDBwELgMTk3UPlKy9lKzNhjb2mllrR/clIiIiIiIiIiIi/ZcCGiLdxN2/Dryz5K5bzexkb++nL3P37wOvT27+mpk92cj9iIjIwOHuI4kL6e8BHgdmU32RvJZWoiHj7wAvXsxPAgYPEEGNSmhjauEch8gHNp5XYKM2dx8DLCMNbDQRIZui/eRbNjab2ZXMeW7JnKcS3Cg7zyHFpACAAAAgAElEQVTyLRsbzex8HfudkDxOJbCxAphfsvQ0EcQ4TDRpTAEW1lh7hgiSZEMbh/S5ERERERERERERGXgU0BDpJu7+DuCbJXe918y+1tv76cuSb76eIWrB24CZ2W/GioiIdJckAPAq4AngMapHlrSnBXgR+DbwyWLgMglsPEh+JEqtwMba5P++oAvv7XP3WeQDGyuJnxmyrhEBiBstGxTCMO4+k3zLxkpgQuE8lRErN1o2iDEkHRqNkjzOVCKokW3amFmy9AiwlWhtgfgsLmlnbS60YWbHO7onERERERERERER6ZsU0BDpJu4+CThVctd3zezx3t5PX+fui4mLFAAvA7fpgpWIiPQ0dx8PPAJ8CHgdMLmOw68BLxCBzP9qZhcK5x5KdWDj1sI5XiRt11gL7Nfff+1z9+HE65odjVI2PuQ4+cDGejM7kznPUOA+0sDGKmAx1SNWLhDhiErLRrOZHapjv0OA28gHNlYAk0qW7weeAU4k+5hNjOyptTbbsrHRzM51dF8iIiIiIiIiIiLSeApoiHQjd28BhhV++4iZzWrEfvo6d/994H9Lbv6hmf1qI/cjIiKDj7tPIcaVfAR4GBhfx+FXgT3AV4DfNbOrhXNXAhuVcSg/R3Vg4yD5kSgKbHSAu08kgg/Zpo1phWVtwC7yo1F2mFlL5jyVESvZpo15JQ95mDSwsZ5otOhwOCIJbdxFPrSxDBhbY8+7gLPAKGJUy1JgTI212dDGVjO73NF9iYiIiIiIiIiISO9SQEOkG7n7MaqrzVvMbEQj9tMfuPsh4lumAMvNbFMj9yMiIoNbMhbj9cCHiYvoxQvo7bkMPAv8KfBHxTEZSWBjARHWWEMENqYUzlEJbKwFfmhm++t9DoNREoCYTz6wsRQYWVh6kQgy3GjaMLPDhXNNJw1srEp+FRst2oj3+kbLBvBMNvzRgT0PJ5pAsuNRlgDFnxtbgO3APqLd4xbgTsrbP64la7OhjWfr2ZeIiIiIiIiIiIj0HAU0RLqRu/8EeE3JXaOK36qVkMxtfwUYSlw0maiLCCIi0le4+1zg54EPEhfPR9Vx+EVinNcfAl8zs9bCuYcCC0nHoZQFNg6QGYliZgfqfAqDlruPAh4iPxplfsnSF8mPRtlkZhcz5xkK3EO+ZaMsSHEJ2Ega2FgPHKynESXZ82LyTRsPED8nZV0GthCfjyvABGJ8y/1Uj365CGwmH9rYq6YWERERERERERGR3qeAhkg3cvf/BHyi5K5Xmdm63t5Pf+HuvwJ8Obm51sxe18j9iIiIlElaGu4BfhF4H9GGUWwwaM85YBPwReC7xQvkSRBgEfnAxuTCOfaTGYmiwEZ9Mu0YldBGE9VjbVqAbeRHo+zJvl/uPpoIf1RaNpqIESZFr5CGNZqJ0Shn6tzzOKINJBvaKHusM0Ro43DyHKYQn9F5JWtPAxtIAxvrzeylevYlIiIiIiIiIiIi9VNAQ6QbufuDwI6Su75oZv++t/fTn7j7euKCA8C7zOzrjdyPiIjIzWRGlrwVeBdwNzCsjlOcJi7+f87M1tY4/yJiHMqjRGCjOGrjBfKBjYP1PIfBLnmN7yffsrGQ6saKU6TNGM3EaJSThXNNJX6WqQQ/VlHdiAKwi3zLxjYzu1bnvqeQH42ygnRkXNZRImzySnJ7GtH+MaNk7cvkWzY2mNmJevYlIiIiIiIiIiIi7VNAQ6QbJf/If73krmfNbEFv76c/cfeRwFmiOv46MMXMzjZ2VyIiIh3n7sOJpoN3AG8H5lJ9ob+WNuAk8BPg02b2dMn5h5E2bKwBXkvtwMZaIrDxYr3PY7BLGitWkAY2VgMzS5buId+ykQtaJI0rd5EPbCwFRhbOc5loVqm0bDQD++sdQeLus8mHNlZSHhA5CDwDnCAaYGYl+5pYsvZ58qGNTWZ2vp59iYiIiIiIiIiISEoBDZFu5u4XgLGF375oZrc0Yj/9ibs/Avw4ubnPzO5u5H5ERES6IgkfrgLeDTwOzAaGdPDwNqL9YC3wcTPbWXL+YcBi8iNRihfZnyffsKHARp2SoMUdpIGNJmA5MLqw9DKwkTSw0Qy8WBiNMoposKiMRWkixuYUHSMNbKwnRpCc6sS+55MPbCwHyn4mfY5o9jhDhGXnJPscU1jXCuwkH9rYZmZX6tmbiIiIiIiIiIjIYKWAhkg3c/fdwL0ldw2t95uQg5G7f424kAXwSTP7vxq5HxERke7i7mOBVwHvBx4DptdxeCsxguIfiMBG1SiTJLCxhDSw8VqqAxv7yAc2DtWxB0m4+wgiHJMdjVIWtHiZfGBjQ7GBIhlXUhmNUgluTC0513PkWza2mtnVOvc9DLiPfGjjIapbPa4TLRv7gAtEqGM+0eAyvLD2GrCVfGhjp5mVtcqJiIiIiIiIiIgMagpoiHQzd/9z4AMld83Rt1ZvLvm253HSSu57zGxvA7ckIiLSI9x9AvAI8CFiZMnkOg6/DhwCvgN8wsyOlZy/EthYQxrYmFBYtpd8YOOlep6DpNz9VtKAxerkv4vvaSsRfMiORtllZq2Z81SaL7ItG8uIZousq8Bm0paNZqKBrN7RKCOJ4EV2PMoCYFhh6RUiiHGAaAuZSISS76O6GeYCMbYlG9p4XmFlEREREREREREZ7BTQEOlm7v4m4Hsld33MzL7c2/vpj9x9LvAC8Y/9Z4Ap2QsXIiIiA1FygX8N8GHgYWB8HYe3APuBvwY+Y2ZnS84/jGhLeJSbBzbWAj9SYKPz3H0o0aqRHY2yhOrgw1nSgMU6oLkYuMmEKLItG/eXPOxJ8i0b683sRCf2PhZYSr5po6wh5BywBThMfAYnE+GOuTX2toFMaMPMDte7NxERERERERERkf5MAQ2Rbubu44l/aC/6gZm9obf301+5+/8JfCq5+S0ze1sj9yMiItLb3H0W8HqiYWMVMKaOw68SYYuvAV80s8sl5x9OdWCjGArZQ75hQxfUuyAJPiwjDWw0AXeULH2e/GiULWZ2pXCuSUTrRVPmV9nYnH1kAhvJuao+Dx3Y+yRgOfnQRtnejwPbgFeAtmRPi2vs7TD5lo0NZnay3r2JiIiIiIiIiIj0FwpoiPQAd79G9Xzu42Y2rRH76a/cfSfpt0MfM7N/bOR+REREGsnd5wGPAR8kmhiKIy/acxnYBfw58KSZtZScvxLYqIxEeYTqwMZz5AMbL9exBynh7rPJt2ysBMYWllXGmWRHo+zPjgxJRqPMIQ1rrCICFcVgzzWi9SLbtLG3M21l7j6DfGBjJTC1ZOlLxGiXE0SDyCzis1ZscIEIlGRDG5vM7EK9exMREREREREREemLFNAQ6QHufgSYUfjt62ZWDG1IO9x9HHCKCLtcAyaa2aXG7kpERKTxkovx9wK/CLwfeIDqcGh7LhIXzJ8Evlp2cT4JbCwlwhpriMDGuMKy3aSBjR8psNF1yeu+gDSwsZp4f4uOkW/ZeNrMzhTONQJYSDoWZRXwIDFGLus0aWBjPSVjVjq490pIJBvYWEH5uJ69RGjoDBE2uoMIHo0urGsFniUf2thmZlfr3Z+IiIiIiIiIiEijKaAh0gPc/Z+A15XcNU7fAKyPu78F+Nvk5lYze6iR+xEREemL3H0ocSH+LcC7gbuJpoKOOk80NPweMVqs6n8kJMGBZaQjUdoLbKwlAhtH6tiD1JCMF1lJvmmj2FTRBuwk37Kxw8yuF841gXQ0SiW4MavkYV8g37KxuTNB2eSzeS/50MZD1A5i7CM+j2OBO4nPdfGzfBXYSj60sav4XEVERERERERERPoaBTREeoC7/zrwhZK73mBmP+jt/fR37v73RKU7wL8zs99t5H5ERET6ukyY4u3AO4hWg6F1nOIMcXH+88APagQ2RlAd2LilsGwX+ZEor9SxB6khaaq4k3xgYykworD0AhFeuNG0UWw5Sc51O2lYo4kIcBTHrLQA28i0bAC7OzkaZQTREpINbSyiPIixDThIjOkZT4Q97is57QVgI/nQxgtln10REREREREREZFGUUBDpAe4+93AnpK7/sjM/m1v76e/c/dhRPX2OOLbobeb2eHG7kpERKT/cPdRxAX4dwFvJhoTimMuamkjRo79FPiUmTXXeIwRwHLSwMZrqA5s7CQ/EkWBjW7i7qOJZorsaJR5JUsPkh+NsqnYjJEEfB4k37KxgOqQz1nSAEgzsL6zrSnuPibZ/wrS0MZ9VH9OLxDtGS8RoZHJyV7nlJz2BLCBTGhDY3hERERERERERKSRFNAQ6QFJlXML1f+gvMfM7m3Alvo9d18IbE9uHgVm6huRIiIinePuY4GHgfcRLVXT6ji8DTgG/Aj4hJltL1tUCGysIQIbxVaGZ8kHNo7WsQ+5CXefQdqKsZoIPYwvLGshAg/Z0Sh7iz9nufs44v2snG8V0bxRVAmAVJo2NprZxU7uf0LymNmmjbklS08STRtHic/nVGAx5Z/rl8i3bGwws1Od2Z+IiIiIiIiIiEi9FNAQ6SHufo7queyXzWxMI/YzELj7F4F/l9z8UzP7SCP3IyIiMlC4+0RiRMkHiTDF5DoObwVeAf4RcDPbX+MxRhDtCI+SNmzUCmysBX6swEb3SlrJHiA/GmUh1aHik6Qhi3VEM0ZViMHdZ5Nv2VhJ9c+/14FnyIc2dprZ9U4+h2nkWzZWAjNKlr6cPO4JYnTKTKKhoxhQAdhLPrSx2cwudGZ/IiIiIiIiIiIi7VFAQ6SHuPt24h+8i4Z1Zla33JiRfgC4I/mt1bVq1kVERKTz3H0qEdT4IBGkKLuoXct14DDwXaJho3TkhbuPJB/YeJjqwMYO8g0bx+rYh3SAu48n3odKaGM15YGH3eRHo2w3s2uFcw0D7idt2agEQIYVznWOGD1SCWw0d3Z8XfLz4e3kAxsrgIkly18AdhGj80Ylxy1J/jurlfjsZUMb283samf2KCIiIiIiIiIiUqGAhkgPcfc/AH615K77zWx3b+9noHD3W4n66qHAJWBi8eKAiIiIdK+kKeH1wIeIi9/FIEV7WoiA5d8CnzSzMzUeYyRxcf1R0sBGsXnsGdLAxo8V2Oh+SeBhDvmWjeVUhxguARvJjEYxs0Ml57sFWEa+aWNOyUMfIglrJL82mtn5Tj6HocBd5EMby6j+PLUBO4F9wHnicz0fWEB1qOQqsIV8aGN3Z5tARERERERERERkcFJAQ6SHuPu/An5QctdvmNnne3s/A4m7fxT44+TmT8zstY3cj4iIyGDj7vOBNxINGw8BI+s4/BrwPPDfgd82s0s1HiMb2FgDvJragY3KSJTjdexDOih5LxaTBjZWA3eXLD1MvmVjQ9moEHefSRrWqIxGmVBYVmmxuNGyAezowmiU4cCD5Fs2FgMjCkuvEZ+rA8Bloj3mHuDektOeJ0Iq2dDGfjPT/8gWEREREREREZFSCmiI9JDk24Jl3/r7sZn9XG/vZ6Bx958RFwcAnjCzrzRyPyIiIoNV0rhwH/ALwPuIi+DD6zjFFWJ8xv8DfKlWM5a7j6K6YWN0Ydl28iNRTtSxD6lDMganErJYnfz3pMKy60TY4UbLBtE6kRv3lzRe3Ee+ZWMx1Z+jC0QgotKysR441NlAhLuPTh4n27TxADCksPQSsJUIoFwDJifr7qDaCfKBjadrjfkREREREREREZHBRwENkR7k7lep/lbeKTOb0oj9DCTJNznPEBdmWoFpZnaysbsSERGR5GL7IuAtwLuIpoXiuIj2XCKaE/4Y+LNajQlJYGMVaWDj1VQHNraRH4miwEYPSd73e8mPRllM9Xt/hrQRYx3QXNZ84u5jgKWkLRuriPEjRS+Tb9nYYGZnu/A8xhPjUFaQhjbuLFl6hvh8HSFGpUwjPvdTS9YeIh/a2GBmpzu7RxERERERERER6b8U0BDpQe5+CLit8NutZlbPRQqpwd0fBp5Kbh4ws3kN3I6IiIiUSEZLLAfenvyaAwyt4xQXgC3Al4Bv1mpLSAIbTeQDG6MyS9qoDmwo3NmDkka5ZeRHoxR/NgbYR340yhYzu1pyvulEUKPSslHW2tEG7CTfsrHdzFq68DxuJR/YWAnMKln6CtEYcoIIpswkQirjS9buIR/a2GxmFzu7RxERERERERER6R8U0BDpQe7+d8DPl9w1xcxO9fZ+BiJ3/yrw3uTmb5vZbzZyPyIiItK+TJDiXwOPA7OpHinRnrPABuDzwD+0E9gYTXXDRq3AxlrgJwps9Dx3v520FWM1EXwYU1h2BdhMfjTKgeJ7nbR23E2+ZeMhqhvsLpGORqk0bRzs7GiU5LFvozq0Mblk6QFgF3AaGEmMRVlE/rMIMQ5mB/nQxvZaI39ERERERERERKR/UkBDpAe5+8eAJ0vuequZ/W1v72cgSubeHyWtk15gZs82cEsiIiJSh6Rl4WHgPUSwdVqdpzgF/Az4jJk9VWtREtjINmy8iurAxlbyDRsK1PawpGFlEfnRKPeXLD1KPrDxtJmdKznfaCKkUQlsNAF3lZzvFdKwxvrkfJ0eO5L8THon+cDGMuCWkuW7idaQc8BYYB6wgOpmmStEe0w2tLHbzFo7u08REREREREREWksBTREepC7zwX2l9z1VTN7fy9vZ8By9znE6zyE+IfuybXm1YuIiEjf5u4TgdcCHwDWUN5KUEsbMV7iR8AnzWxLO48zmggEPEoa2BhZONcW0sDGTxTY6B3uPpkIOGRDG7cWlrURjRPZ0SjPlv0M6O5TM+erBDemlDz0LvItG9u60mDh7sOIsEk2tLGE/OcMoCV5LgeIto8JRDPIPSWnPUe0gWRDG1XtIiIiIiIiIiIi0jcpoCHSg5Jv0l2nurZ7v5nNb8CWBix3/y3gvyY3v2dmv9jI/YiIiEj3cPdpRFDjg0TTxvg6Dm8lmhf+J/BxM9vTzuOMIW3YWEMEA4qBjc3kAxudblyQjkt+pr6LfGBjKTC8sPQ8EVioBDaazezITc5XadlYSnVw4jLxnjeTBjde6OJolFFEY0glsLGC8vaMy8B24CXgGjAJeAC4veS0x8kHNp42s1c6u0cREREREREREek5CmiI9DB3P0N8Cy7rqpkV505LF7n7DuDB5ObjZvbdRu5HREREup+73wa8nmjYWAWMqePwVuAw8HdEYOOldh5nDPmGjfYCG2uJwMaZOvYiXZA0oCwlDWysBuaWLD1AvmVjk5ldLjnfKGAx+ZaNe0vOd4wIatwYj9LVZpVkzM9S8k0bd5csPUuENo4Qn79pwEKq20UAXiQf2tigz6eIiIiIiIiISOMpoCHSw9x9E/EPrkUju1KZLNXcfRwxh344URU92czON3ZXIiIi0lOSJoT5wBuJwMZDVLcgtKeFuJD9bWIkysl2Hmss1YGNEZklrVQ3bOiCeC9y95mkAYvVRNBhXGHZNWAraWBjHbCvrBXD3ack56i0bDQBU0seeg/5lo2tZnali89lMtGusYI0tFHWnnGMGI9ynGjhmEkETYrPG+A58qGNzWZ2qSv7FBERERERERGR+iigIdLD3P0LwK+X3LXczDb19n4GOnd/HPh/k5s7zGxhI/cjIiIivScJbNwPvAl4PzESojgGoz3XgBeArwOfM7ML7TzWWOBVpIGNJqoDG5tIAxtPKbDRu9x9GNGulh2NsoDq8YMnSAMW64hWjKrxNcnnax75lo1lwOjC0qtEWKfSstFMjRBInc9nJvmWjZXUbs/YBZwhPpO3E2NViuGl68Az5EMbzyhELiIiIiIiIiLScxTQEOlh7v4I8OOSuz5uZtbb+xkM3P17xIUZgP9gZp9t5H5ERESkMdx9KNEm8BbgXcTYiKF1nOIq0Trwl8DvtteKUAhsrCEu3hcDGxvJBzbO1rEX6QbuPoFopciORplesnQX+dEo282speR8I4jPWLZl4/6S850kMxaFCIEc7+JzqQRGsi0by4HxJcv3APuAc8RYoHlEeKX4/w+XgS3kQxvPmVlrV/YqIiIiIiIiIiJBAQ2RHpbML79Yctd6M2vq7f0MBsm3JU8R/zjdBswzs4ON3ZWIiIg0WnIxfTnwNuDtwFyq2xTacxl4FvgT4I/N7Ho7j3UL1Q0b2TaPSmBjLWlg41wde5FukIQc5pIPbCyjum3iIvF+3RiNYmYv1TjnRCIsUWnZaAJmlCzdR75lY4uZXe7i8xkK3Ee+ZeMhYFRh6XVgJ3AAuESMRLk7+VV0lnju2dDGwa42goiIiIiIiIiIDEYKaIj0Ane/QvU/8p41s4mN2M9g4O4LiMpmiJnc0/WPyCIiIpLl7qOJi+fvBN4MzK7zFBeA7cB/A/5Hey0DSWDj1aSBjVXkAxvXqW7YUGCjAdx9FLCE/GiUu0qWvkQmsAFsNLOqYHYSAplDPrCxnGiyyLoGbCUNbKwH9nS1vSIJJi0kH9pYCAwrLL1C/Pz8EtEeM5loA7mt5LTHyAc2njazo13Zp4iIiIiIiIjIYKCAhkgvcPf9xDfzstqAYQoN9Bx3/zzw75ObXzGzJxq5HxEREenb3H0c8DDwHuAxYFqdpzhHhCx+B/huez/nJYGNh0kDGyupDmxsIA1s/FSBjcZx92mk4YrVyX8Xw9bXgW3kR6OUjgdJQhMLSMeirCJGjhQbXU6TjERJztdsZse64fmMJZo1VpKOSLmvZOl5IrRxhGh9mUqEO6aUrD1IPrSx0czOdHWvIiIiIiIiIiIDiQIaIr3A3b8F/FLJXbPN7OXe3s9gkXxb8QXScMwjZvZUA7ckIiIi/Yi7TwJeCzwBvA6YVOcpThMX6j9rZj+8yWONI23YWENcMM82HFQCG5WRKD81s/N17ke6SWaUSLZlYzEwtLC0ErC4EdowsxM1zjmBCEtUgiBNwKySpfvJt2xsMrNLXXtGN0azLCfftDGnZOkJYAfRUjcUmAksAm4pWbubfGhjS3fsVURERERERESkv1JAQ6QXuPsHgT8ruet9ZvaXvb2fwcTdpwKvEP94fAWYaGZXGrsrERER6Y/cfToRnvgA0X4xvo7D24CTwE+AT5nZhps8VqXN41HSho1iYONp8g0bCmw0UNKKspw0sLGa8rE5e8m3bGw1s6sl5xtCjBfJtmysoDoI0UI0d9xo2QB2d3U0SrKH6eRbNlYC00uWHgZ2EYGUEcDtRNPGiJK9PkM+tLHDzK51da8iIiIiIiIiIv2BAhoivcDdbwMOldz1N2b29t7ez2Dj7h8A/jy5uc7MXtXA7YiIiMgA4e63A68nAhsrgTF1HN4GHAX+GfiEme28yWONJx/YWEE+sNFCdWDjQh37kR6QfEaygY3lVH9OrgCbSAMb64CD/z979x0lx3mf+f6LnEEiERkESIIkQJDIGFgkJYK0RWUrU1kbzl4f22eD1z57d6/37m9/VrIsS5bXWltOWlmrlWxLXq2uJcuWLEOWFTDIgSAYQAQCIHLOmHT/eKtZ9VYXMN09M909M8/nnDlUo19WvT2a5sF0PfX8ikbkuPtwwiiUbMvGA5Q3d1wg/DyUWjZazexYL7yeIcBc4paNVcDEguUvJl+XCK/5TuD+gr1eA7YRhzZe6I2AiYiIiIiIiIhIs1FAQ6QOkg8y2yn/MPKImc1pwJYGHXf/MaE2HOD/MrM/buR+REREZGBJ/r53F/BaQmBjGTCyikN0AkeBvwV+w8xe6uZ8E4BHSAMbKykPbGwkDWz8RIGNxnP3EYRxINnRKPcVLD1OHNjYbGYXb3LM8YT//7NNG0W/Y7xE3LKxtTd+JpJxLwuJWzaWUx5E6SSMPDkAXCU00NxNeN/knQe2EIc2DhWFVkRERERERERE+hMFNETqxN1PA5Nzf9xuZvnaX+kD7j6KULk8mvDh8EwzO9HYXYmIiMhAlQQ2FgFvBD5AaD0YXsUhOggNbN8EPmpmJ7s530TKGzay4eBSYGM9aWDjShX7kT7i7pMIoYps08ak3LJOYDfxaJQ9ZtZxk2POIg1rtBBCE+NzyzoI40Zeadm41TGrfE3DCc0e2aaNByl/D7Qle3gZuAHcTmjZmFlw2BPEgY1N3b0vRERERERERESajQIaInXi7hsIH47mjTWzq/Xez2Dk7o8Q5r5DuOAxT3fhiYiISD24+zDgIeAtwHsJjQP5drVbaSc0D3wN+E0zu9DN+SZS3rCRPV8b5Q0bCmw0gSTccw9xYGMp5eGGi4SgQimw0Wpmx29yzGGE4EM2tPEgcesKhHEkm0lbNlrN7OWevypw99HJ68iGNu4HhuSWXiGENo4RgilTCWGPfGgF4CBxaGNLd+8NEREREREREZFGUkBDpE7c/aPArxc89Woz+6eCP5c+4O5fBD6cPPxdM/t3DdyOiIiIDFLJqItVwNuBdwHzKL9QfSs3gL3Al4HfMbNr3ZzvNuLAxgrKAxutpIGNnyqw0TzcfQzh/7PsaJR5BUsPEI9G2X6znw13H5ccsxTYuNkxj5AGNjYSxq1c6sHLye5hYrKH1aQjUhYULD1HaBA5Rfi5nQ4sAcbm1nURxqhkQxs3/R6IiIiIiIiIiNSbAhoideLuLYQPSfM+bWa/Vu/9DFbJHYnHgWnJHy03s+0N3JKIiIhIqV1gLfBu4OeBWVUe4hrhwvSfAn9gZu3dnK8U2FhHCGwsJw5s3KA8sKHWtybi7jOJAxurgXG5ZW3ANuLRKPtu1iLn7jNIAxtrkq+JuWWlcSulsSitwDPd/cxVyt2nkoY1Sl8zCpYeA54lhDdGAHMIo4TyIyTbgV3EoY3dvbVfEREREREREZFqKKAhUifuPorwwXneDjNbVu/9DGbuPo9wd+EQQo3zZDNra+imRERERDLcfTwhQPE+4PWEMQ/VKI2J+APgS2bW2c35bqe8YSPb6JENbKwHNiiw0VySMSYPEIc2FlPezHKKNFixAdhoZudvcsyhwH3ELRsPUT5u5TKwhbRloxU43BvjBJOA9Wzilo3VwO0Fyw8ALxLGv4wB7kz2n/8eXCUEV7Khjb3dvU9ERFkZJAYAACAASURBVERERERERHpKAQ2ROnL3q8Do3B9fNrPxjdjPYObuvwZ8Knn4XTN7spH7EREREbkVd58EvBr4EPA4xRenb+US4YL0Z4FvdHfhPAlsPEoa2FhOeWBjA3HDhsZINJmkKWUVaWBjLWmTXNYe4paNp2/WMJGMW1lO2rLRQvFYkqPELRubzexCT15PZg9DgLuJWzZWUDzy5HlCcOMqMCH59+YXHPY8sJk4tNErIRMRERERERERkRIFNETqyN33Ej4QzBumu7Xqz913EWZXA7zLzL7eyP2IiIiIVMrdpxPGk/wz4GGg2sDvecLF808Bf19BYGMSaWBjHbCUOLBxnTiwsUGBjeaTBBvmEwc2lgMjc0uvEMIKpcDGBjN7+RbHvYMQkii1bKyhPETURRoEKQU3dvXiaJThwCLilo2lFI88eQY4TBgBczuhZaNojMpx4sDGJjM71Rv7FREREREREZHBSQENkTpy968A7y146h4ze7He+xns3H0ccJbwoW07MPVm9c4iIiIizczd5wJPAP+ccGF6TBX/ehfh70Q/Bj5hZj+t4HylwMY6QmijKLDxU9LARqsCG80pGcW4jHg0yl0FSw+TCWwAW83syk2OOQRYSBzYWEZ5WOIqsJW0ZWMjcLC3WiuS1/YQcdPGImBowT52EwIZHYSRQou5+RiVbGhji5ld7I39ioiIiIiIiMjAp4CGSB25+3uBrxQ89Utm9gf13o+Au78J+Ovk4XNmdn8j9yMiIiLSU5nxD08CHyaEJ/INCbfSBZwkBCs+YmZPV3DOycQjUW4W2FhPGti4XsWepI6SRow1pIGNNcDE3LIOYAfxaJQXbtYM6O6jCSGN0liUForbBU8Qt2xsMrNzPXxJ2X2MJ7SGZEMbRfs4T2jaOEX4WZ4BPEB5+KkLeJY4tLFDgSQRERERERERKaKAhkgdufsMwizmvO+Y2RvqvR8J3P2bwFuSh//FzD7SyP2IiIiI9KYksLEYeAPwQUKDwPAqDtFJaBb4O+A3zGx/BeecDLyaOLCRdY3yhg0FNpqUuw8F7icejbKE8iaKs4RgRSmwsdHMTt/iuFNIAxulf04uWPocactGaTTKjR68pPw+JhOPRlkFzC5YeiLZS6mFbzbhvZV/P7UBu4hDG8/01jgXEREREREREem/FNAQqTN3bweG5f74uJkVzTyWOnD3YcAZwl2BXcBCjZwRERGRgSr5u88y4M2E8Xv3UH6h/VY6gCPAtwgNG8cqOOcU4sDGQ7kl14CfkAY2Niqw0dySJopVpIGNtYSWibwXiEej7DSztpscs9T+km3ZWE55A8x10tEopaaN/b01GiXZyyzi0MZqisMjLwEvAhcI7Rp3AvcSN8gAXAG2EYc29vbmnkVERERERESk+SmgIVJn7n6SMNM4q8PMqrmLUXqZuy8mzJ2GENaYdrN6ZhEREZGBxN1HEC4+vx14B+ECc/7i8q20AweBvwI+Uck4ikxgYx0hsPFgbkkpsFEaibJJgY3mloQr5pIGNlqAlcDo3NJrwBbSNowNwKGbBRXcfSShgSXbsnFvwdJTpGGN0miUMz17VdE+hgALSBs2VhNe3/iC5XuBA4RQxnhC6OTOgnXngM3EoY0jCm2IiIiIiIiIDFwKaIjUmbv/kDCfO29Sb85Wluq5+yeB/5A8/Asze08j9yMiIiLSCO4+GvgZ4N2EMXCzqjxEG7AP+Arw22Z2pYJzTiVu2MgHNq5S3rDRayMupG8k4Z+HiEMbReGKY8QtG5vN7NItjjuJEJBoyXzlQ/AQ2juyLRs7ejPok7TR3EfcsrGM8saPDmAPcBi4AUwifB+mFxz2GHFgY9OtxsSIiIiIiIiISP+igIZInbn7rwMfLXjqjWb2N/Xej6SSu+L2AfOTP/pZM/t+43YkIiIi0njuPgF4BHgf8CQwrcpDXAeeA/4M+FwlwQp3n0Yc2FiSW3IV+DFpYGOTAhv9g7tPJjRhlAIbLYTAQlYn8DRpYKMV2HOzhrvk7/HziVs2VlDe3nED2E7asrGRXh4zkjR+PEg8HuUBysdcXgeeAY4SXu8UYDFwW8Fh9xOHNrbcKsAiIiIiIiIiIs1LAQ2ROnP3FYRK37w/MLNfqvd+JJbUbR8nfIB6g9Bs0u1dnyIiIiKDRXKB/dXAB4HHgdurPMRVwmi5PwT+h5l1VHDOacBrSAMbD+SWXCEObGxWYKN/SMIVC0kDG2sJrRv5EZAXCOGEUmCj1cxO3OK4IwhBiWzLxv0FS88Qghqllo2NZnaqBy+paC9jgeXETRsLC5ZeJIQ2ThHGDE0nhDbG5NZ1ERo5sqGNXm0HEREREREREZG+oYCGSJ0ld1QVfXD2rJktqvd+pJy7f4hwhyeEu9NWNXI/IiIiIs3M3WcA64APAw8D46s8xGVCq8HvAV+7WUtC7px3EEIi6wiBjcW5JaXAxnrSwEZblfuSBkkCDSuIR6PMLVi6n3g0yvZbhRTc/TbS0Silpo2iMSP7iFs2tpnZtVpfz032cjuwkji0UfQaTxEaaM4SQiuzgUWUB1jagJ3EoY1nKglAiYiIiIiIiEj9KKAh0gDufhkYm/vjq2aW/zNpEHf/IfBo8vBfm9nnGrkfERERkf7C3ecBTwD/jHARPD9mojulpoTPAN+pZPyEu08nHomSD2xcprxhQ4GNfsTdZxEHNlZT/jvVDWAb8WiU/Tf7GUraO+aRhjVaCKGJfGNFG7CDtGWjFXihkjBRNZKf49W5r6kFS48AewmNG6OT17CQ0LqRdQXYShzaeLE3R7qIiIiIiIiISHUU0BBpAHffQ3G97ggza6/3fqScu48i3KU2hlAhPMfMXm7srkRERET6l+QC+D3Ak8CHgKXAyCoPcxb4CfBJM/unCs87nXgkSr6p7jLwI9LAxhYFNvoXdx9OGHWTHY1S1Eh4kjiwscnMzndz3CXELRuLKQ8/nCMEHl5p2rjVyJVaZAIk2cDGSmBiwfJ9hEaRK4QWm7uTfzfvLLCZTGjDzI705r5FRERERERE5OYU0BBpAHf/U+BfFDy11Mx21ns/UszdX0W40xLgKDBbd5uJiIiI1C654PwA8AbgAxSPariVLuA08I/Ax8xsW4XnnUE8EiUflr5EeWBDwel+JhkbUhphUgpu5BsouoA9xKNRdt9qFIi7TyQEI1oyXzMLlh4gHYvSCmw1s6u1v6LCvQwF7iW8zlXJP5dT3lTTSRiNcpgwYvP25N+7o+CwR4lbNjaZ2Zne3LeIiIiIiIiIBApoiDSAu78N+N8FT/0HM/tUvfcjN5cL03zezH6xkfsRERERGUjcfRjh4vJbgKcIbRtDqzhEF3Ac+B7wUTN7vsLzziBu2LhZYGM9IbCxVYGN/icJBN1FHNhYDozILb1MaJV4JbRhZke7OfYc4paNVcC43LIOYCeZlg3g2T4YjTKCEHzKNm08CAzLLb1BCKccJQQ4phBCUjdr5NiU7HkT4T1wuTf3LSIiIiIiIjIYKaAh0gDuPg0oqr/9BzN7ot77kZtLPtQ9CkxP/mi1mW1u4JZEREREBix3H0m4uPw24J2EEQ350RK30gm8DHybENg4XOF5ZxIHNu7LLbkE/BMhrLEe2KbARv/k7qOBZaSBjRZgQcHSQ8QtG7dsw0jCRoszx1xDGJWSDxxdIA0+tAKtZnasBy/pZvsZQ3idpZaN1YSf6/z76TIhtHEyee6O5HUUNXI8k+y9NCJlp5ld7+29i4iIiIiIiAxkCmiINIi7t1N+R9NpM8tX8EqDufs8Ql3xEMJM50lmdqOhmxIREREZBJKLzK8C3gW8GZhV5SHaCRfavwF83MxOV3jemaRhjccIoyGyLpIGNn6AAhv9mrtPJwQqSqGNNcCE3LJ2YAdpYKMVeOFWIxDdfTxhNEqpZaMFmFOw9BBxy8aWvmiryIxqyTZt3Fmw9AxhPMpZwgii2YSWmaJGjp2kLRubCA0hNx0XIyIiIiIiIjLYKaAh0iDufhSYkfvjTjPLf+glTcDd/z3w6eShmk5EREREGsDdJwCPAu8BXg9UG25uA/YDfwH8lpldqvC8swgNG+sIgY2FuSUXiAMb2xXY6L+SNoz7SQMbawkjRPJtGGcI4YRSYGOjmZ3p5tiziAMbq4HxuWUdwNOkgY1WYE9fBB+Sdsdsy8Zq0vbArKPAXsLP+mhCu03+fQChkWMLaWBjM7DvVkEWERERERERkcFEAQ2RBnH37wE/W/DUzL6ouJWec/cdwEPJww+Y2f9q5H5EREREBjt3n0wITnyQEJ64vcpD3ACeB/4n8LuVjmtw99nEI1FuFdhYTwhsqFWgH0vCQatIAxtrKQ4yPE88GmWXmbXd4rilMEipuaMFeJDytopLhLDDK6ENMzvSg5d0s/0MIbR8ZAMbq4DbCpYfSL6uAOOAu4C5BevOkAY2NgGbzOxoL29dREREREREpF9QQEOkQdz9V4HfLnjqKTP7y3rvR7qXVBSfAUYQ7mq7o7s75ERERESkftx9BvA48CHgYcqbCbpzDXgG+BPgjyttwXD3OcSBjXtySy4APyRu2FBgox9LggzzSAMbLYTxIaNyS68SGiWyo1EOdzMaZSywgrRlYw3Fo0iOkDZstAKbK22FqYa7DwXuJg5trADG5JZ2EQIqh4HrhFDHvcC0m+w9G9rYot+tREREREREZDBQQEOkQdx9CbCr4KkvmdmH670fqYy7vwH4dvLwRWCh6npFREREmpO73wk8AXyYcJF7dJWHuAzsBP478FUz66zwvHNIwxqPES5uZ50nDmzsUGCj/3P3kYTGvexolHxYB+Bl4sDGZjO73M2xZxB+hkstG2uAibllnYSAUSmwsRHY3Rfjdtx9OLCYtGFjNeG1j8gtbQOeI4xI6QAmA4uACQWH3Usc2tjW3fdFREREREREpL9RQEOkQZIPtIqqbl80s6IP8aRJuPs3gLcmDz9mZv+5kfsRERERke4ljQcLgScJI1GWAiOrPMxFQhvC7wB/XWlQ193nEho21hECG3fllpQCG+sJgY2dCmwMDO4+lTRUsTb53/lRPB3A08SjUZ67VSAoabW4l7hlYykwPLf0CmE0SrZp45YNHrVy99GEkEa2aWMRMKRgT88CJ5Pn7kjW5dtHOoHdxKGNXWZ2o7f3LiIiIiIiIlIvCmiINJC7X6S8dvm6mVV7Z5/UURKuOUU6h3mRmT3bwC2JiIiISJWSC9wPAK8HPkC4QJy/uN2dc4SL6b8F/KCKwMY84pEo+cDGOdKGjfWEwEZF7R3S3HLBilLTxkPAsNzS86Shig1Aq5md6ubYY4DlpIGQFmBBwdJjxC0bm8zsQo0v6ZbcfQJhHEqpZWM15T/vEF7vc4SRksOBWcB9lH9fbgDbiUMbzynQJCIiIiIiIv2FAhoiDeTuO4EHC54aa2ZX670fqZy7LyLUB0P4AH1aX1QHi4iIiEh9JCHc5cCbgfcQxpIMreIQXYSLyz8EPm5mm6s4953EgY38RfWzxCNRFNgYQNx9LLCSNLDRAswpWPoi8WiU7d21Sbj7HYRQRLZpI9/g0QXsIW7ZeNrMihofe8zdpxAHNlYDMwuWHieMPblAGE80j/JxQQCXCM022dDGAY2iFBERERERkWakgIZIA7n754BfLnjqZ8xsQ733I9Vx948D/yl5+A0ze3sj9yMiIiIivcfdRxIuZr8NeAfh4nB+VMOtdAEngO8DHzWzPVWc+07SsMZjwPzckrPAP5IGNnYpsDGwuPts4paN1cCY3LLrwDbi0MYtgwmZUT/Zlo1lwIjc0qvAVtKWjVbgYF+FHpLXmw9tTCpYegjYD1wmtFEuoDjMcpo4sLHJzI71/s5FREREREREqqOAhkgDufsbgG8XPPUbZmb13o9UJ/lwcy9pRe8bzOw7DdySiIiIiPSRpOXgVcA7gbdQfMf/rXQCR4G/BT5iZgerOPd8QsPGuuRrXm5JqbljPSGw8bQCGwNL0vCyhDSwsRa4v2DpCeLARrfjS9x9FCGkkW3ZuOcWxy4FNjaZ2blaXk93kt+17iIObKwAxhUs30sIblwnjKFcCEwtWHeYOLSxua/2LyIiIiIiInIzCmiINJC7Tybc2ZP3EzN7uN77keq5+1TCDOdhQBsw2cwuNXZXIiIiItLX3H0i8ChhHMrrKL4gfCsdhAvG3yQ0bJys4tzzSds1bhbYKDVsrAd2K7Ax8Lj77aRNGKXgxpTcsi7CaMZSYGMD8IyZdXRz7CnJsUvHX1NwbIDnSMeibCSM37nl2JVaufswQiglG9pYCozMLW0HngdeJrzPpgD3ARMKDvsCcWhjm5ld6Yv9i4iIiIiIiIACGiIN5+43KK+TPW9m+bnA0qTc/UPAnyUPd5jZskbuR0RERETqLwnuvgZ4PyE0Ue3f59uBA8BfAp/srvUgc94hhBEoj5EGNubmlp0mHomiwMYAlPws3E0c2CgaX3KJEEZ4pWmju/EfmUaLbMvGCsrDEdcJo1FKLRutwP4+HI0yCniQNLCxCngAGJpbeo0QJjmRPL6DEPYYlVvXAewmDm3sMrO2vti/iIiIiIiIDD4KaIg0mLsfBmbn/rgLGNZXH2JJ73P3HxA+kAf4VTP7TAO3IyIiIiIN5u4zgceBDwCPAOOrPMQNwuiGLwOfNbOrFZ63FNhYRxrYmJNbdoo4sPGMAhsDk7uPBpYTj0a5s2DpQeLRKFvN7Fo3xx5JaLAotWy0APcWLD1FGtjYCGw0szO1vJ5KuPs4wmvONm0UjWy5QAhtnCGEWGYS9j8st+46sJ04tPGc3jMiIiIiIiJSCwU0RBrM3b8FvLHgqQVmdqDO25EaJXdunQHGEgI2C6qZKy4iIiIiA5u7LwCeAD5IuKA9uspDXAOeBb4AfL7SO/qTwMYC0rDGOsoD4qXAxnrSwIY+LBig3H0GaaBiLSHAkA8QtQE7iEejvNjdz4W7T0qOV2rZaAGmFSx9gbhlY4eZXa/xJXUr2deq5KsU2sgHlwBOAi8C5wnv0bmE5pC8i8AW4tDGQb1vREREREREpDsKaIg0mLv/MvC5gqf+pZl9od77kdq5ewvhg0sI1bkzdVeViIiIiOQloYl7gScJDRtLKR8V0Z0rwC7g88D/NLOOKs59F/FIlHxg4yTlDRv68GCAcvdhwGLi0SgPAENyS0+TBio2EJowznVz7FKjS7ZlYwXlAaUbhJaKUstGK7C3L3/ukqDK6tzXlIKlhwnjhy4D4wiBp/x7BkLQKRvY2GRmx3t94yIiIiIiItKvKaAh0mDufh/hTri8r5vZu+q9H+kZd/8j4F8lD79gZv+ykfsRERERkebn7kOBJcDrgfcDi4DhVR7mErAV+F3gG5Ve2E4uoN9NHNiYlVt2kjSs8QNgjwIbA5u7TyS0TWRHo9xRsPRZ4tEou8ysvZtjjwAeJA1srCH8zOedJW7Z2Ghmp2p5PZXIhEmyLRsrgQkFy/cBhwjjTyYCCykOdxwiDm1sNrPzvb13ERERERER6T8U0BBpsORupTbK7056ycyKZgNLE0s+XD8CzEj+6BEz+3EDtyQiIiIi/Yy7Dye0DLwJeA8hQDG0ysOcJ1zc/hTw9zUENtaRBjZm5padIB6J8qwCGwNb8nNxJ3HLxgpgVG7pFcLoj1dGo5jZkQqOfxshEJFt2phesHQfmcAGsM3MrtXwkiqS/H53H3HLxjLKX3cn8DxwFGgHJif/Xn50DMm6bGhjm5ld7Yv9i4iIiIiISPNRQEOkCbj7ecJdN1ltZlZtzbE0AXefCxwkhG6uApP78kNDERERERnY3H0U4cL1zwPvBOZRHvDuzhngR8AnzewnVZx7CHAPaVjjMYoDGz9IvtYDzymwMfC5+0jCeJ5sy8bdBUuPkAlsAFvM7Eo3xx4CzCVu2VgFjMktbQN2EDdtvNCXoyaTBpAlxKGNJcCw3NLrhDDGieTxHYTQRv73/A7gaeLQxtNm1tYX+xcREREREZHGUkBDpAm4+xbC3Ud5t5nZhXrvR3rO3f8d8DvJwx+Z2aON3I+IiIiIDBzuPhZ4GHgH8BbKAxPd6SKMLVkPfNTMnq7i3EMI4xweIw1tzMgtO048EkWBjUHC3aeRtmCsTf73bbllHcAu4tDG892FKpJmmSXELRuLKQ8rnSOEHEotG61mdoI+lLwnl5EGNlYRwhh5lwihjTOEQMcswvsp35BzDdhOHNro9nskIiIiIiIizU8BDZEm4O6fBv59wVNPmNk/1Hs/0jvcfSuwPHn4z83siw3cjoiIiIgMUMl4iEeBp4DXAVOrPEQncAz4LvARM9tXxblLgY1Su8ZjlAc2jhEHNp5XYGNwyIwIyY5GeYjyQMJ50gaMDYRQxekKjj+BEIYotWy0EEIPeQeIWza2ddfi0VPJ+3IlcdPGvIKlp4G9wAXC6JS5wIKCdRcI42OyoY2X9F4SERERERHpXxTQEGkC7v6zwPcKnvq0mf1avfcjvcPdxxM+bBtJ+NB7Zl/fuSUiIiIi4u5TCUGJ9xGCE7dXeYgOwliKvwY+ZmZHqzj3EOBe4pEo03PLSoGN9ck/X9BF5sHD3ccRggvZ0ShFoYq9ZAIbwA4zu1HB8ecQt2ysAsbllnUAO8m0bADP9nVDhbvfQdqwUQpt3FGw9CiwH7hM2Pt8ir9HJ4kDG5v0O6eIiIiIiEhzU0BDpAkkd9acK3hqq5mtrPd+pPe4++uBv0keHgQW6MNnEREREaknd58FPA58AHiE8ovV3Wkn/F32fwMfN7Oi311udu4hhAaFxzJf+cDGUdJ2jfXAXv2deXBJQhXZwMZKYExu2XVgK/FolG4bJNx9GGEUSrZlYwnlLR4XSUejtAIbqwkn1SJ5f8wlbtlYBUwsWH4AOET4PkwE7gEmF6x7iTi0scXMzvf23kVERERERKQ2CmiINAl3v05oWsi6ZGYTGrEf6T3u/nXCfHBQK4qIiIiINJi7LwB+Fvgg4YLw6CoP0UZoN/hzwt9vL1dx7iHA/cSBjXyDwMvEI1EU2Bhk3H0E8CDxaJT7CpYeJw5sbDazixUcfzywgrRlowWYU7D0EHHLxpZqft5rkYyFWUjcsrGc8sBKJ+F9+DKhEWQyob2mKID1HHFoY7uZXe2L/YuIiIiIiMitKaAh0iTc/QBwZ8FTI8ysvc7bkV7k7sMJ1bOlaumlZrazgVsSEREREQGihovXEho2lgEjqjzMdcIF4C8Cv29m16s8//2k41AeA6bllh0hDmy8qMDG4OPukwgNGKXARgvlDRKdwG7i0Sh7zKyjguPPIm3YWEMIRuRvmOgEniZt2aj4+D2R/E75AHHTxoPA8NzSNuB54ATQRQg/3Uv5zSDthNeRDW3sNrO2PnoJIiIiIiIiklBAQ6RJ5FoWshab2Z5670d6l7svInxQOAS4AEzVh18iIiIi0mySu/cfAl4HvI8wGmJYlYe5Svi77x8CX6wmcJ4ENhYRghql0MbU3LJSYGN98s99CmwMPsnPyj3ELRvLKA8tlEaXlAIbrWZ2vILjDyOEh0qhjRZCKCL/frgEbCbTtGFmR2p7VZVz99HAUuLQxv2E3zmzrhBCG6cJ35uZhO9bfsTLNWAbcWjjBTPr7KOXICIiIiIiMigpoCHSJNz9XwF/VPDUvzWz/1bv/Ujvc/ePAr+ePPyWmb25kfsREREREelOcuf+SuBNwLspvrDbncvAduD3gK9Vc8E3uQi/mHgkSj6wcZi0XWM9sF+BjcHJ3ccQxoGUAhtrgXkFSw8Qj0bZbmbXKjj+WNLRKKXgRlET5hHSsSil0Sjdjl7pKXefmOyvFNhYBSwoWHqOMB7lPDCKMN5lfsG688AW4tDGIb2/REREREREaqeAhkiTcPd7gBcKnvobM3tjvfcjvS/5cPkF4O7kj95qZt9s4JZERERERKri7qMIF73fQmgAnEf5HfvduUC40Ps7hN93Kv5gImn4yAc2puSWHSIeiaLAxiDm7jNJGzDWEoIL43LL2gjtEdnRKBU1s7j7dOKWjdXAbbllncAzZFo2CCNF+nycqbtPJQQ1sk0bMwqWHgf2EwJVYwnBjqJ1J4gDG5vM7GTv71xERERERGRgUkBDpEkkHzS2U/7h5lEzm9WALUkfcPcphA++hhH+/55qZucbuysRERERkdq4+zjgYeDthNDGzBoOcxb4KfBJ4J9qDGyUxqG8hvLAxkvEgY0DCmwMXsnokgeIR6Mspvx38VOkDRgbgI2V/O6W/EzeS9yysZTy0StXCO0UpXNspA7tFMmNA7OJWzZWA7cXLD9EeP9cAyYSGnQmFaw7SBza2GJmF3p98yIiIiIiIgOAAhoiTcTdz1D+YUeHmeU/yJF+zN3fD3w5ebjbzJY0cj8iIiIiIr3F3W8DXk0Yh/I6yseRdKcLOE0IUnzMzLZXef6hhIvvjxFCG68BJueWZQMb683sQJV7lAEmGQ2ymng0yrSCpXuIWzaerqQFIxm9soy0ZWMNcFfB0mPELRub6hF0SEIbdxO3bKwgNGlkdQEvAi8TbjiYTAijFK17jji0UdEYGRERERERkYFOAQ2RJuLuPyV8EJQ33cxO1Hs/0nfc/fvA48nDXzezjzdyPyIiIiIifcHdpxHCEu8l/P03P/qhO52EkQrfAz5iZkVjIW91/qHAEtJxKEWBjYNkGjYU2JAksDCfOLCxHBiZW3oF2Ewa2NhgZi9XeI5ppA0ba5Kv/A0bXYRQSCmwsRHYZWZtVb+oKrn7cGAR8XiUpcCI3NJ2wijPE8l+pxFCG0XrdhGHNuoy5kVERERERKSZKKAh0kTc/ePAfyp46q1m9s1670f6TjK7+wzhTqMu4F4z29vYXYmIiIiI9C13n00IarwfeAQYV+UhOgl3738b+KiZHa7y/EOBB4kDG/mL4geIAxsHq9yjDEDJ73ClFoxScKOoBeMwmcAGsNXMrlRw/CHAQtLQRktyvnzQ4SqwlTS00QocrMfYnuR78BBx08YiYGhuPmmVswAAIABJREFU6TVCaOMUYbznTMJ4lPwYmavANuLQxl4z6+yjlyAiIiIiItJwCmiINBF3fw3hQ8C8z5vZL9Z5O9LH3L2F8IEdhA+uZphZRwO3JCIiIiJSN8kF6QXAE8AHCRd7R1d5mHbgEPAN4BNmdqrKPZQCG+tIAxu355YdIBmHQghsvFTlHmWASlowsoGNNcDE3LIOYAfxaJQXKgkh5EIhpeDGPQVLTxAHNjaZ2bkaXlLV3H08oV0kG9q4u2DpecJ4lHPAKGAuMO8m6zYThzYO1yOAIiIiIiIiUg8KaIg0EXefABTNl91tZkvqvR/pe+7+eeAXkodfNrMPNnI/IiIiIiKNkgQ27gdeC3yA4nEK3WkD9gF/CXzKzC5WuYdhpA0b64BXUx7Y2E/asLHezA5VuUcZoJLAz/2kgY0Wws9TvmHiLCFQUQpsbDSz0xWeYwohBFE6/hpgSsHS50jHorQCO83sRpUvqSbuPpl4NMoqYHbB0pOE99NlQrvkAuCOgnXHiQMbm6oNY4mIiIiIiDQLBTREmoy7X6X8rrGrZja2EfuRvpV8gHeYUPkKsM7MftC4HYmIiIiINIfk78pLgSeB9wGLCeMSqnEDeB74EvB7Znatyj0MI4x0eIy0YeO23LJ9xCNRFNiQVyQNEytJQxtrSX//y3qBeDTKTjNrq+D4QwijVrItG8sJLRVZ1wnjREotGxuBffVqpnD3WcShjdXA5IKlR4CXCGNSJhLaOPIhKQjNNtnQxpZqA1kiIiIiIiKNoICGSJNx970U14GOqfbDROkf3H0u4cOloYQPzaaY2eWGbkpEREREpMm4+wjChe43Ak8Rfm/KNxN05xrwDPAnwB+bWXuVexhGCI08lny9mvLAxovEgY3DVe5RBrAkUDGHOLCxkvIbNa4BW0gDFRuAQ5UEKtx9JCFYlG3ZuK9g6SlCUKPUsrHRzM5U/6qqlxlxlA1srATGFSzfTwhutBNCHQuBMbk1XcCzxKGNHfocRUREREREmo0CGiJNxt3/F+HusLzVZra53vuR+nD3fwP8bvKw1czWNnI/IiIiIiLNzt1HEy5uvxl4BzAPGFLlYa4AO4DfB75qZh1V7qEU2FhHGtiYmFtWCmysJwQ2jlS5RxngkvBRKVBRCm7cW7D0GHHLxmYzu1ThOSYRQhCllo0WYFrB0r3ELRvbzex6Na+nVsn76T7i0MYyYGRuaUeyz+PJ42nAPZSPRGoDdhGHNp6pNpglIiIiIiLSmxTQEGky7v4h4M8Knvp/zOwT9d6P1I+7bwFWJA9/0cw+38j9iIiIiIj0J8koiYeBtxNCG0VjJLpzkdBa8BngW9WOf0guMC8jhDXWAY9SHtjYS9ywocCGlHH3yYQwRSmw0QJMyi3rBJ4mDWy0AnvMrLOC4w8B7iRu2Shq8rgBbCdt2WgF9tZxNMpI4EHi8SgPUD7u6DphTMzp5LmZhNEv+dDWFcKol2xoo26vR0RERERERAENkSbj7gsIM4zz/sHMnqj3fqR+kg+UTxPuDuoE5prZy43dlYiIiIhI/5Q0BrwaeCfwemBKDYc5R7jw/VuEMEW1gY3hpIGNx5L9TMgte4E4sKHfAaRMEqhYSDwa5SFgeG7pBULooBTYaDWzExWeYwQhDFEKbLQAiwqWniUObGw0s1NVvqSauftYYDlx08bCgqWXCA025wi/Z88B5hasOwdsJg5tHFFoQ0RERERE+oICGiJNJvnQpZ3yWcqnzKyoflQGEHd/LfB3ycPDwDx9KCQiIiIi0nPufgchJPFeQrvFbVUeogs4A/wQ+ISZbaphD8MJF5YfS74epTyw8TxpYOMfFdiQm0mCCiuIR6MUBRD2E49GqXhsibvfRmivaMl8TS9Yuo90LEorsM3MrlXzenrC3W9P9plt2ij6XpwmfD8uA2OB+RSPejlGHNjYZGane33jIiIiIiIy6CigIdKE3P0kMDX3x53AcF2sH/jc/WuEu/wAfs/M/k0j9yMiIiIiMhC5+xxCUOP9wCPAuCoP0QWcAL4PfMzMnqlhD9nARmkkyvjcslJgYz0hsHG02vPI4OHus4gDG6sJQYSsG4QxH9nRKPsr+bwhualkLnHLxsqCc7QDO8i0bADPVzJ+pbe4+3Tilo3VlH/WAiGMcRC4RghM3U1xgGs/cWhji5ld6v2di4iIiIjIQKaAhkgTcvd/JFTf5s03s4P13o/UV/Ih7QnS+cKrzWxzA7ckIiIiIjKgJRed7wKeAD5AuJA7usrDdAJHge8AH63ld7fkd4EVxA0b+cDGc8QNGwpsyE0lP1MPkAY2WoDFBUtPEgc2NpnZ+SrPUTr+muTxkNzS84SgxivjUSodv9Ibkvf5POLAxirKW2wgBDaOEIImkwmhjTG5NV3AHuLQxo5K20lERERERGRwUkBDpAm5uwH/teCp95vZV+q8HWkAd18E7CZ8oHUZmKIPeURERERE6iO5kLsI+DlCw8YyYESVh+kgjC38JvBxMztewz5GUB7YyDd9PEsc2DhW7XlkcEnGlqwmDW2spbxZohQ+yI5G2W1mHRWeYwIh/FBq2WgBZhUsPUjcsrHVzK5U+ZJq5u5DgXuJQxvLKA9odRLGuBwnfG+mEUIbw3Pr2oCdpIGNjcCeSr9vIiIiIiIy8CmgIdKE3P1VwI8LnvqSmX243vuRxnD33wD+3+Th98zstY3cj4iIiIjIYOXuw4ClwJPAewkNBMOqPEw7YUTC14BPmtmFGvYxgjBO4rHkq2g0SymwURqJUnUwRAaXJJC0gDiwsZzyUNJlYDOZ0EY1DS7uPps0rNFCCHDkf347CAGHV1o2gGfrPBplBKEBJBvaeJDy9/wNYC9wBhgKzATmU94cchnYSvjelYIbL2qErYiIiIjI4KSAhkgTcvdxQNEc071mtrDe+5HGSD4kew4o/X/+HjP7iwZuSUREREREeOUC7irgDcBThDvph1Z5mNLF3S8DnzWzqzXuoxTYWEcIbIzNLdtD2rDxg3qOlJD+y91HE5okSoGNFkKII+8QccvG1kp/lpPg02LSsSgtwBLK30sXCaGGV5o26j3ax93HEL4fpbEoq4H7KA5jvEgY5zISmAPMLjjkWdLAxkbCSJmX+2TzIiIiIiLSVBTQEGlS7n6F8vmm182s2jnI0o+5+1TCHOvhhDvuZpjZ6cbuSkREREREspKL2T8DvBl4OzCP8gu33blGaL/4AvB5M2urYR+l4MhjpA0b+cDGM8QjURTYkIq4+x3EgY01wITcsnZgB2lgoxV4odK2CHcfTxjrkw1tzC1Yeoh0LEorsMXMLlf5knrE3ScSAlLZpo07C5aeI7TnXCJ8zjOf8pEyAC8TAhuvNG2Y2Zle37iIiIiIiDSUAhoiTcrd9wD3Fzx1Wy1VuNJ/uft7ga8kD58H7lcVqoiIiIhI80ouMj8CvI0Q2phZw2GuAE8Dvw982cw6atjHSOLAxsOUBzZ2Ewc2TtawVxmEkgaM+4lHozxAeQPGGUKQohTY2FhN8MDdZxIHNlZTHgzpJLxfXmnZAJ6p5X3TE+4+jbhlYzUwvWDpCeAgIZg1gdDCk39NAPvItGwQGkrqGkQREREREZHepYCGSJNy9z8F/kXBU68xsx/Wez/SWO7+98ATpYdm9l8buB0REREREamCu08CXgO8E3iS4rvnu3MJ2AZ8Fvg/ZtZZwz5GEi4YP0Ya2Mg3N5YCG+uBHyqwIdVw9wmEcEK2aWNGwdLniUej7Kq0NSYJhtyXHLsU3HgIGJZbeonQRlFq2Wg1syNVvqQeSUaXziFu2VgF3Faw/DBwBGgDJhFCG/kW1U5CC062aWOnmV3vi/2LiIiIiEjvU0BDpEm5+3uArxY89TEz+8/13o80VlKZfAoYl/zRYjPb08AtiYiIiIhIjdx9OiEg8RTwOMUXa7tznnDR+dPA92pp2csFNtYBr6I8sPE0ccPGqRr2KoNUElCYRxzYWAmMyi29CmwhHo1yuIrRKGMJo1FKLRstFI8beZm4ZWOzmV2s7lX1jLsPJYQvsqGNFZS/97oIo1GOJY+nJv9ePohyA9hJ2rKxCXi23u0hIiIiIiJSGQU0RJqUu88j1F3m/dTMXlXv/UjjufsawodIECpip5tZewO3JCIiIiIivSD5/W8d8F7gUcrHkHSnCzgL/Aj4hJltqHEfoyhv2Mjfwb+LNLDxQwU2pFpJMOgh4tDGwoKlpTBFKbCxuZrxHkkQqhTYWJN85cNQXYTWmFdaNoDd9f5d292HA4uJWzYeAkbklrYRxp6cIoySmQnMLzjkZULgZVPma7/GpYqIiIiINJ4CGiJNKrnLpI3yOyPOmdmkBmxJmoC7/z7wi8nDr5nZuxu5HxERERER6V3J74J3E0Ycvp9wUTnfNtCdLuAkYUzJx8xsV417GZWc/7Hk61WUBzZ2Egc2TtdyLhnc3H0K4WetFNhoAW7PLesgNLpkR6M8V+m4n6S54l7ilo2lwPDc0iukbR6l4MaheocbkibNh4ibNhYBQ3JLrwIvElp1RhBGqswqOORp0rEom4BNZna0TzYvIiIiIiI3pYCGSBNz92PA9NwfdwEjVFU5OCUfKB0i/bDlSTP7bgO3JCIiIiIifSgJbDxACGx8gHBBOX9XfXc6gePA3wIfNbN9Ne5lFOGi9mOkgY18eKQU2FhPCGycqeVcMrglv/suJA1srCWEFfI3sZwnhA1KoY1WMztZxXlGA8tJAxtrgLsKlh4jbtnYbGbnq3hJvcLdJxDGoZRaNlZTvN8LhKaNS4RGnjuBKQXrjhC3bGw2s7O9v3MRERERESlRQEOkibn7d4GfK3hqkZk9W+/9SHNw97nAAUKd6Q1gar1n5oqIiIiISGO4+zBgGfAkYSTKIsovWneng3Bh9q8JDRs13UWfXNwuNWysA36GOLDRRXnDhgIbUhN3HwusJB6NMqdg6T7ilo3tZnajivNMIx2JUgpt5JtMu4BnSQMbG4FdZtZWxUvqFUn7SCmsUfqaWbD0JPAScA2YACxI/pm3lzi0sa2a0TIiIiIiInJrCmiINDF3/4/AJwqe+gUz+6N670eah7v/a+C/JQ+3mtnKRu5HREREREQaw91HEC7IvgF4N2E8ytAqD9MOHAT+CvjNWu+gTwIb2YaNosDGDuLAhu7Wl5q5+2ziwMYqQmNE1g1gK2lgoxU4UOnIkqTF5h7ilo1lwMjc0muE0SjZpo2D9R6NAq98X/KhjaJxuS8DhwkjdicR/vuRb8XpBHYThzZ2VRN6ERERERGRlAIaIk3M3VcTfrHP+7qZvave+5Hm4u6bCB+4APyKmX22kfsREREREZHGc/cxhGDEm4F3AHNrOEwb8CLwVeAzZnapxr2MJlw4f4w0sJG9qN0FbCcNbPyTAhvSE+4+HFhCPBrl/oKlJ4gDG5vM7EIV5xlFCGmUWjZaCCGOovOUAhsbgY1mdq7S8/SWJGRyF3FgYwUwrmD5AcJIpE5gavLv5Vt6bhDeu9nQxnMaxysiIiIi0j0FNESaWPLB2pWCpw6a2fw6b0eaTDJ79iTh7pYuYIGZHWzsrkREREREpJkkvzc8AryNENqYUcNhrgPPAf8D+AMzu17jXsYQBzbWcuvAxg8bcTFbBhZ3v500SFEKbkzJLesCniEejfJMNYGDZNTIatKWjaLzQHgvZVs2djaijSIZl3Q/cWhjKeXNIO3AfuAUoZ1nBnBnwSEvERpEsqGNiptKREREREQGCwU0RJqcu1+i/I6GdjMb0Yj9SHNx99cCf5c8PArMMbPOBm5JRERERESamLtPBl5DaNd4HcUXkLtzlTDy4A+BL5pZe417yQY21iX/O/u7bhewjbhhQ4EN6ZGkTeJu4sDGMuKfPQiBg01kmjbM7FiV57mLuGVjOeUjRK4Tfs5LLRutwL4GjUYZBTxIGthYBTxA+dika8A+4Bwh0DEbmFlwyNPEgY1N1XwPRUREREQGIgU0RJqcu+8i1HPm3WFmJ+u9H2k+7v4XhFnTAH9kZr/QyP2IiIiIiEj/4e4zCAGJp4DHgYk1HOYyofni94Cv1Road/exlDdsZC+ad1Ie2Dhfy7lEspJxPMuJQxvzC5YeJB6NstXMrlVxnpHAQ8QtG/cVLD1N3LKxycxOV3qe3uTu4wjfm2zTRtE4l4uEpo1LwBhCy8bkgnWHiUMbmxW8EhEREZHBRAENkSbn7r8P/GLBU28ws+/Uez/SfJIZu8dJP/h42Mx+0sAtiYiIiIhIP+XudxLaLN4DPAqMreEwFwgXXj8N/G2tTQBJYONnSAMbLdw8sLEe+JECG9Jb3H06cWBjDTA+t6wN2EE8GuXFan7m3X0SoamiJfM1rWDpXuKWje21jhvqqcyes00bcwqWngZeIrTuTAAWUP49BHiBOLSxzcyKRv6KiIiIiPR7CmiINDl3fyvwjYKnPmtmv1Lv/UhzcvdFhIrhIcAVYKqZXW3srkREREREpD9LRjTcAzwBvI9wgTo/nqESZ4GfAJ8khCh6GthYRwhsrKE8sLGVuGHjQi3nEslz92HAItLAxlrC+I8huaWnSZsvNgAbq2mISN53d5KGNdYAK4HRuaVthOaa0rk2Ai80YjQKgLvPJA5trKZ4hNIx4AhwA7idMAYm/9+VDsJnHNnQxi4za+uTzYuIiIiI1JECGiJNzt1nE+of87aa2cp670eal7s78F+Sh+vN7PFG7kdERERERAYWdx9KuCD9BPB+YClxQKISXYQL2D8APm5m23qwn3GUN2wMzyzpBLaQBjZ+pMCG9CZ3n0jaflEKbkwvWPoscWhjl5m1V3GeEcCDpGNRWoD7KQ+HnCVt2NhICIc0ZDxuEjSZTxzaWElo0sh7iRDc6ASmEpo2huXWXCcEUrKhjedqHakkIiIiItIoCmiINLnkF9obxB8yAVwys6JfamWQSn5WngXuTf7ow2b2pQZuSUREREREBrCkUWA58CTwXsIF4/xF1e50AieA7wEfMbMXerCfccCrSAMba4h/l+6gPLBxsdbzieTl2i9KgY0VlDdEXAU2kwY2Ws2s6OacW53rNtJwSCm4MaNg6T7S0EZpNEpDGjeTkNd9xC0byyj//nQC+4FThBDKDGBewSEvEt7T2dDGwUa1iIiIiIiIVEIBDZF+wN2PALMKnhrdqHmj0pzcfQrhrpPhhA8fZ5vZ8cbuSkREREREBgN3H0m4UPw64CnC6IKhVR6mE3gZ+BbwsWovWuf2Mw54mDSwsZriwMZ6QmDjxwpsSG9L3hdLiUej3F2w9AiZwAawxcwuV3GeIcBc4paNlcDY3NJ2YAdpy0Yr8HyjmiiS788S4qaNJZSHvW4QwibnCM09sykOpJwiDmxs0uciIiIiItJMFNAQ6Qfc/VvAGwueWm5m2+u9H2lu7v4U8OfJw33APbp7RERERERE6s3dxxAaLd4MvI3iO+C700EYf/AN4BNmdqoH+xlP2rCxjnAhOHsRuIPQavAD0oaNS7WeT+Rm3H0qaYhiLSFUcVtuWQewizSwsYEqgxTuPpwwlijbsvEA5aNRzhPCDKWWjY2NDDW4+1hCs0YpsLGK0LyRd5nQtHERGENoL5lUsO4QcWhjs5md7/2di4iIiIh0TwENkX7A3X8F+EzBU79qZkV/LoOcu/8d8Nrk4SfN7D82cj8iIiIiIiLuPhF4BPh54C0U3/3enTbCBdk/Bz5tZhd6sJ/xlDds5AMbm0gDGz9WYEP6Qmb0Rza08SDlLRLnSUMUpdEop6s81wRCs0ZL5quotfUgccvGVjO7Us25elMy0mUl8XiUotDXWUKo6yowHlgAjCtY9zxxaGNbo0a/iIiIiMjgooCGSD/g7suAbQVPfdvM3lTv/Ujzc/fRwEnChxEAS81sZwO3JCIiIiIiEklGNL4GeDvwemByDYe5QbjQ+iXgcz25wJpcuM4GNlYRXyBvJw5s/ESBDekryYieUpBibfJVFKTYSzwaZYeZ3ajyXLOJWzZWUx5qKDV6vNKyAexp1GgUAHe/gziwsRqYVrD0BHCY8N+LSYTQxsjcmg7gaeLQxtNm1tYnmxcRERGRQUsBDZF+wN1HEZL/+QrKo2ZW9Mu5CO7eQviABsJdNndU+yGNiIiIiIhIvbj7TEIw4l3AE8DEGg5zDXgG+BPgT3pycTUJbDxCGthYSXFgYz1pYONyrecT6Y67zyENbLQQQkRjcsuuA1uJR6O8VM3oU3cfBiwibdhYQ2j0GJpbepF0NMpGQqPH0epeVe9x9yHAXOLAxiqK/1tyGDgGdAJTgfmUv75rwHbi0EZVY2ZERERERPIU0BDpJ9z9AjAh98cdwIhqfsmWwcXdPwf8cvLwm2b21kbuR0REREREpFLuPh9YB7yHEJQYW8NhLgM7gf8O/LmZdfRgPxNJGzbWEQIb2Qu67YSL1D9AgQ2pA3cfASwhDWysJYxKyTtOHNjYbGYXqzxXttGj1LQxt2DpYdKWjVZgSyPfB8n4mIWkYY3VwHLKgy2dhLEuJwnv6+kUv74LwBbi0EZVARgRERERGdwU0BDpJ9x9C7Ci4Kl5Znao3vuR/iH5IOIgMCf5o7ea2TcbuCUREREREZGqJXfGLyQ0a7yPcJF1VA2Huki4uPo7wLd6cid8EtjIN2xkAxttlAc2rtR6PpFKuPsk0gBFKbiRHx/UCewmHo2yp9oAU9J6UzpXaTRK/uaiTsLokFdaNoBnehKW6il3Hw48QNy08SAwPLe0DTgAnAVGEEbMTC845EniwMYmMzvRF3sXERERkf5PAQ2RfsLdPwv824Kn3mVmX6/3fqT/cPe5hA8UhhI+XJhuZmcbuikREREREZEeSMLoS0gDG8sov7haiXPAT4HfBtb35C54d7+NOLCxguLARmkkyk8V2JC+loSb7iEObBS9X0rjSkqBjVYzO17luYYC9xO3bDxEPBoIQrPNZtKWjY1mdriac/U2dx9N+L6UWjZWE15LftzwVWA/4fs1BpgH3F5wyJeIQxtbzOx8n2xeRERERPoVBTRE+gl3fyPwrYKn/sjMfqHe+5H+xd1/iVDpC7ALWKr6TRERERERGSiSO+KXA08CTwGLicMRlegCzgA/BH7TzDb2cE+3AY+SBjaWUx7YaCVu2Ljak3OKVMLdxxB+HrOjUeYVLD1A3LKxzcyuVXmuscm5Si0ba4D5BUtfJm7ZqHoMS29LWnJWkAY2VgELCpZeILSXXgHGJ2uKRjI9Rxza2K73vIiIiMjgo4CGSD/h7tOBYwVP7TazJfXej/Q/7t5K+CAE4P82s99q5H5ERERERET6iruPJFwMfh3wLuBuagtsnAC+D3zczHb3cE+3Exo21pEGNrJ3598gDmz8VBdvpV6ScSWlEMVaQiBhXG5ZG7CdNLCxAdhX7Q0gyWdca0hbNtYAt+WWdQHPkGnZAJ42s/ZqztXb3H0qccvGamBGwdJTwGHC+/p2QihlZG5NO2H8Sza0sdvM2vpi7yIiIiLSHBTQEOlH3P0GYeZl1lUzK0rli0TcfQJhLuoowgcd95rZ3sbuSkREREREpO8ld/G/CngT8HZgDuWjC7rTCRwFvgN8zMwO9HBPt1PesJEPbGwgDWxsUGBD6sXdhxGaaLItG4spf9+cIg1RbAA2mdm5Ks81FFhI3LJRNIblCrCFtGWjFTjUyIbQZITMbOLAxiqKx568TLj5qgOYCtxJeXDsGrCNOLTxgpl19sX+RURERKT+FNAQ6Ufc/SDFlZMTzOxSvfcj/Y+7/xzw3eThCWB2o+8+ERERERERqbdkdMGjwM8Db6b4DvjudACHgP8P+ISZFbVeVrOnScSBjWUUBzbWkwY2qho3IdITyftmNWlgowW4o2DpHuLRKFU3X7j7aEJoqdSy0QLcVbD0GHFgY7OZna/mXL0tCW3cTRzaWEH52JMu4CXCzTRDgOmE8FjeeUIwJRvaaGgwRURERERqp4CGSD/i7n9FuNMn72Ez+0m99yP9k7t/FXhP8vBLZvbhRu5HRERERESk0ZKxBa8h/M79JDClhsO0A/uBrwGfqrZFoGBPk4BXkwY2lhIHNq5T3rChwIbUTRJEmE8c2FhB+SiPK8BmMqNRzOzlGs43jTQgUmramJRb1gU8SzoWpRXY1eixIe4+HFhE2rCxmvCezjfltgMHgLPJc7MoDsGcIA5sbDKzk32xdxERERHpXQpoiPQj7v7LwOcKnjIz+41670f6p+RDgWOkHzg+bmbrG7glERERERGRpuLuswihiHcBjwMTazjMDWAv8GXgd83sSg/3NJnQsLGONLCRdR34KWlgo1WBDak3dx9F+NnMjkYpar44TCawAWyt9j2SBETuIQ1rtBCaZ/IBkWvAVtKWjY3AgUY3UCTfq4eImzYWUTz25ABwERhNaNe9reCQB4lDG1vM7EJf7F1EREREaqeAhkg/4u4PAjsLnvoHM3ui3vuR/svdFwG7CXdfXQOmaUyOiIiIiIhIMXdfQAhGPAU8QvmogkpcI9zZ/4X/n707j7PjLu98/9FubdZiWbtteZVlW17klloGgyyDwRizGkMyCxPuJLkZhiQ3meVmXtzMk2fCxJBgSBgISZjwYkkghIQhIRC2IAw2WItlyfImS7ZsWbssyVpaS6uX+8evSqeqTnWr+5w6a3/fr1e/RPf59fk9fdApq6u+9TzAn5tZd5U1XUR6JEo2sHGa8sDGmWr2FKlE1Pki7nqxkhCmyIaeeoHNpEejbDOzvmHuFQdEkl02rs5ZepB0l431ZnZkOHvVgrtPIXQhibtsLCeMS8k6QQhknASmAJeRP0JlK+nQxiYFt0REREQaSwENkRbi7uMId8SMyjx00Mzy2h2KDMjdDfi96NOfmdlrG1iOiIiIiIhIS4ju2r8GeAPwi4QLqBMqeKqTwBbgs8Bfm1lPlXVdRHokyo2ZJXFgYw0hsLFOgQ1pBHcfDVxLejTKUso7RxwhBCjiwMY6MztUwX4zCUGNuMtGJ/mzAi72AAAgAElEQVRjjJ4j3WVjc7VBqiJE9ScDG8sJo0+yDhM6k3QTOmwsIn+EyhbSoY2nqj3+iIiIiMjQKaAh0mLc/QgwPfPlfmCcmfU2oCRpUdFJxacJJ0UAftXMPtfAkkRERERERFpOdLF5KfBGQmDjJmBsBU91gjCG4VPA/xlu54CcumaRDmwszSw5DfyMUocNBTakYaLOEbeSHo0yL2fpNtKjUZ4ws7PD3GsUcDnpLhvLKA9anQEep9RlYy3wQqNHo8C5MUzZ0MbMnKX7gL1AHyGUchnlN36dIvycydDG9mqPQSIiIiKSTwENkRbj7o8SfnnMWmxmz9W7Hmlt0Qm7vYSTh33ApWa2u7FViYiIiIiItC53H0u42Psm4BeAJZR3BhiKo4QLwh8HfljtReEhBDZOUR7YaHj3ABmZohDFQkqBjU5CIOGCzNLTwGOUAhSPAi8P9/3i7uMJXWeSXTYW5yw9RCmwsY4Ku3oULRE6SQY2bgUm5yx/mTDiZRQwG1iQs+YosIF0aGNXM4RTRERERFqdAhoiLcbd/xD4LzkP/ZKZfbHe9Ujrc/f3AX8TfboTuFx3SYiIiIiIiBTD3ScQLvbeDdwPXEn5HexDcRh4GPgo8GgBgY2LSQc2bsgsOQU8QimwsV6BDWmkaPTvUtJdNq7JWbqPdJeNDWZ2ooL9ZhBCIZ2Jj4tzlm4n3WVjUzN0o3H3MYSQSTK0cTMwPrO0l3A+6DDhBp4FwKycp9xPOrCx3sxeqUnxIiIiIm1MAQ2RFuPubwK+l/PQX5nZv613PdIe3P27wJujT//YzH6rkfWIiIiIiIi0K3efDLwGeCvwbkKXgOEGNvoJd8D/GPiImW0poK6LgVWUAhvXZ5YosCFNx91nUup6EQc3ZmSW9QFPUgpsrAWeGe7NKVGXissojUXpJHSpyHb1OAtsohTYWAdsa4buE1GnkKWUAhsdhHBWtsvPGeAl4Bjh57sUuDDnKV8kHdp4zMyO16J2ERERkXahgIZIi4lakh7MeWi7mV1d73qkPbj7BcABYGr0peVmtqGBJYmIiIiIiIwI7j4NeB3wduBtwNwKnqaPcHf7dwmBjRcKqGs2ocPGakJg47rMkpOkAxsbFNiQRotCFFeTDmzcROgMkXSMECiIAxtrzexABfuNIwQc4g4bKwhjjbKhqyNEI1Gi/daZWd75vbpz90nALaQ7beSdY+widNroAqYQwioTM2v6gWdJhzY2m9npmhQvIiIi0oIU0BBpQe5+GpiQ+fIZM8sm9kWGzN1XEE4SABwHZusXaBERERERkfqKbsy4A3gXYSzKzAqephfYDXwLeMDMdhdQ1xzSI1HyAhsPkw5snK12X5FquftEYBnp0SiX5CzdQXo0SkWjSqLQVQelLhud5AevdpDusvG4mZ0a7n614O7TCT9DB6XQRt5r9irwMtANTCOENsZl1pwFtpAObTxtZj01KV5ERESkySmgIdKC3H07YWZt1iwzO1TveqR9uPufAL8RffrPZnZPI+sREREREREZ6dx9PqGLxf3AnZQ6Hw5HD2Fcwd8DHzOzwwXUNYf0SJQlmSVdhA4bawiBjccU2JBmEb2v4vDESkIQYXJmWTfwOOnRKDuGO6ok6uqxkHSXjQ5gUmZpD7CZUpeNtcBzwx3FUivRe3555mNWztIDwF5CUOwiwniUbEeRk4TXNhna2N4MY2BEREREak0BDZEW5O5fBX4h56G7zOyH9a5H2oe7jybMD43vinivmX29cRWJiIiIiIhIkrtfTghqvA+4nfIRA0NxFnge+ArwSTM7UUBdc0kHNq7NLOki3WFDgQ1pGu4+Frie9GiUvFElB0kHNtab2dEq9kt22bg+Z7+jhPBC3GVjrZntH+5+tRAFTy4j3WWjg/wQ2W5CcGMUMAeYl7PmVWAD6dDGboU2REREpN0ooCHSgtz9l4HP5Tz0h2b2/9a7Hmkv7n4poc3maMLdG/PM7JXGViUiIiIiIiJZ0QXSxcAbCDdyrADGV/BUZ4CtwBeAzxYx7jIR2FhNCGwsziw5QXlgQyMPpGlEo0qWkx6Nku0Y0Q88Q3o0ylNm1lvBflOBWyl12egEFuQsfYl0l42NZnZyuPvVQnTjzzWku2zcDGTHMvcBO4HDwFjCz3lRzlPuIx3YWK/uwSIiItLqFNAQaUHufh3wVM5DPzez19S7Hmk/7v4fgD+NPn0WuE53LIiIiIiIiDS36OLojcAbCYGNmwgXP4frFOG8w58DXyyi04W7zyPdYSMvsPFTSoGNjQpsSDOJAlGXk+6ysQwYl1naRegEcS60YWZ7K9xzAekuGx3AlMyyXmALpcDGOuCZJhqNMo7QHSQZ2lgKjMks7SaENo4RAh0LgQtznnIH6dDGY0V0ARIRERGpFwU0RFpQ1Aaxm/K2h6+a2YwGlCRtyN0fJfzyD2Bm9j8aWY+IiIiIiIgMT3T+4FbgLkJgYwmhW+JwdQGPA58G/q6S7gA5tc0nHdi4JrPkOKHDxhpCYONxBTak2bj7BEKHiGSXjctzlr5MusvGRjM7VcF+Ywjv4ziwsYIQdsi+r48TwgvnOm1UGhKpBXefSHjdkqNRsmORAE4SQhsngcmEkSp53TieIT0eZbOZnalJ8SIiIiJVUkBDpEW5+yvkt/6bYGbd9a5H2o+7XwjsJ/zi2w9cb2bPNLYqERERERERqVR0MXklcDfwHuBKym/+GIpjhIugDwLfLaLjYhTYuCPxcXVmyXFKHTbWAJsU2JBm5O6zKQUoVhJCFFMzy3qAzZQCG2uBbZW8l9x9MiGIley0cUnO0l2ku2w0VeeJ6DzUraQ7bVyWs/QY4Wc5Q+iwcRnlnYLOAk9QCmzEXUWqDpeJiIiIVEsBDZEW5e4PAa/PeehmM9tc73qkPbn7XcD3o08PAfOKaG0rIiIiIiIijRdd2H0t8FbgXYSRApUENo4APwP+EPhpQYGNBYQOG6sJgY2rMkuOkR6J8rguvkozirpeXEt6NMoNlHe9OEwIEsSBjXVmdrjCPedRCmysIIQdsuNC+oAnSXTZAJ5upvdRFHbpiD7i0MacnKWvAHsJ415mEgIq2WNZF7CRdKeN5zXSV0REROpNAQ2RFuXuHwE+nPPQh8zsM/WuR9qXu38F+MXo06+a2b9qZD0iIiIiIiJSG+4+nXAzyNuBe8m/EHo+/YSLpQ8BD5jZxoJqW0h6JEpeYOMnlAIbm5rpQrNIkrtPIYQOkqNR5uYsfY70aJQtldw44+6jCSGRZJeNG4ExmaVdhABD3GVjrZntGu5+teLuowhBsmSXjQ5gWs7yvcCB6H/PIf/1PUIpsLEOWG9mewouW0RERCRFAQ2RFuXudwL/kvPQN8zsvnrXI+3L3ccBe4BZ0ZfuNrPvNbAkERERERERqQN3v5gQhngnYSzKzAqepp8wPvP7wB+Y2daCaruEdGDjysySo6RHomxWYEOaVRQ8uIR0YGMZYexs0mlKAYo4uLGrwtEok4BbKHXZ6AQW5SzdQ7rLxgYzOz7c/WolCp9cRbrLxjJgYmZpP/AyoVPJWGA++ce0PZQ6bKwn/LwVdTIRERERyaOAhkiLcvcZhF8osnaaWd58RpGKufsS4ClCe8gzwBwzO9rYqkRERERERKSeoi4Wq4H7gDuBqRU8TR/hAug/ETps7CyotksohTXuAK7ILDlKusOGAhvS1Nx9PKHLRXI0ytU5S/eQDmxsMLOuCvecQwg4xF02VlDenaIfeJpElw3gSTPrqWTPWnD3scB1pDtt3EgIZiSdJYQ2jhLCMAvJP649Tzq0sbHS11hEREREAQ2RFubupyhP0vcA4zU/UYrm7v8d8OjT9Wa2opH1iIiIiIiISONEd/xfTghqvBe4nfI71oeiF9gJfAP4mJkdLKi+SwkdNlYTAhuXZ5a8Sjqw8YQCG9Ls3P0iQmgiDmx0AtMzy/qALZQCG2uBZ82sr4L9RhNCIckuGzcB4zJLTwKPUQpsrCPcRNY05yfd/QJCSCMZ2lhCuBkp6TThmHQSmARcBkzIrOkjhFSSoY0nzKy7VvWLiIhI+1BAQ6SFufszhPmRWZc003xIaQ/RybenCL+8AvyGmf2vBpYkIiIiIiIiTSL6nXEJIbDxPsLF3PEVPNVZYAfwVeCTRXVvdPfLSI9EGSiwsYZSYGPYF7RF6ikToIhDGzcBYzJLjxJCBOdCG5WGoaKgw82UAiKdlHesgTDaKA6IrCPc7NNU3VjdfSphHEoc2Ogg/2c5DuwidJWdBlxK+WvcDWwmHdp4VsEvERERyVJAQ6SFufsXgH+X89A7zewf6lyOjADuPgvYS2gJ2QdcaWYvNrQoERERERERaTrRheObgDcCv0D+eIGh6AaeA74EfMbMThZU3yLSgY1FmSVHKHXYWANsUWBDWoG7TyKEDuLAxkrC6I6sFygFNh4FNlXaASI6XxR32FgRfczMLOsHnqXUZWMt4X11tpI9ayXqUtJButPGvJylhwnnyHoIP+slOWu6CJ1FkqGNHc3UWURERETqTwENkRbm7u8Hvpjz0KfN7NfrXY+MDO7+XuBr0ae7gct0N4CIiIiIiIgMxt3HAbcCdxE6bCwBRlfwVKcJ3R3/EvjLokYKRIGNO6KP1YQ75JOOAA9RGomiwIa0DHdfQKnbxUpCAGFSZlk3sJFSYGMt8GIlYYKoo85VlEIbnYSuG9muOqcTe8bBjYr2rKXo9Ys7bMShjRk5S/cDB6L/PRuYk7PmELCBRGjDzPYWXbOIiIg0LwU0RFqYuy8mJM+zHjezZfWuR0YOd/8O8Jbo08+a2QcbWY+IiIiIiIi0lmhMwkrgzcD9hLECoyp4qi7gCeAzwNfMrKeg+hZRCmuspvzu+MOkAxtPKrAhrcLdxwI3kB6NsiRn6QHSgY31Znaswj0nELrqxF02OgnjWbIOku6ysd7MjlSyZ61EAZQrSHfZWAZMzlm+i3C8GEvoxJEX7NhNusvGhmb7mUVERKQ4CmiItDB3H0NIt2fvODlhZlMbUJKMEO4+kXBXQPz37HYze6SBJYmIiIiIiEgLc/cpwGuBe4B3kT8uYCiOE0YKfBL4pyJCE9HF2EWkO2wMFNhYQwhsPKXAhrQSd59OCBokR6NclFnWDzxNejTK05V2VnX3mdGecZeNFcCsnKXPke6ysbmo7jlFic7TLiHdZeMmyruG9BBCG0eBC4AFwJScp9xOOrTxuJl11aR4ERERqSsFNERanLvvJ7TMy5qif7RLLbn7CsIvxRDuWJpd1CxgERERERERGdncfQbweuBtwL3kjwoYileBnwMPAj8qYnRCIrCxmlJgY2Fm2SFKHTbWEC5iK7AhLSPRJSIZ2LgZGJdZeoIQIDjXacPM9lWx5+Wku2wsAyZklnYDj1PqsrEWeKEJR6NMAJaS7rRxHeU3250BXiacX5tMCIBlf+Y+wninZGhjS7MFVUREROT8FNAQaXHu/gPgjTkP3WZmj9a7HhlZ3P1PgN+IPv0XM8v7uygiIiIiIiJSFXefTQhDvBO4m/wxAefTT+h08RPgAcIYgaICG5eTHomyILPsFdIjURTYkJYTjSa6hfRolEU5S18iPRplo5mdrnDP8YSQQ7LLxrU5Sw9R6rCxDlhnZocq2bOW3H0y4TVMhjauylnaRei0cQa4kBDaGJNZ0w1sIh3a2FppRxMRERGpDwU0RFqcu/8u8D9yHvodM/tYveuRkcXdRwM7gEujL73fzL7cwJJERERERERkBHD3SwhBiPuiPysZ9doPHAD+BfifZvZ0QbXFnQfuoBTayAts/Jh0YEMnaqXluPsc0oGNFZSP7DgLbCYd2the6d/5xDiWuMtGJ/kdhrdTCm2sBTaZ2ZlK9qylqGNQcjRKB+VdeSB0BNpLGJMyk/LjCoSOJo+RDm28qOOLiIhI81BAQ6TFufvrCHd+ZP2zmd1T73pk5IlOir1IaM/YCywws/0NLUpERERERERGjEQg4k7gfuB2YGIFT9VHuPj5HeABM9tRYH1Xkg5szM8sO0josLGGENh4RhdUpRW5+xhgCenQxg3AqMzSuONFHNhYZ2ZHKtxzFOHmoc7Ex63ABZmlZwkdJ+IuG2uBbc34XnP3eaRDG8uBi3KWHiQEzQAuJj+ocoh0YGN9pWNoREREpHoKaIi0OHefRkhPZ+0zs3n1rkdGJnf/NeCz0afbgMXN+MutiIiIiIiItL/oYu11wBuA9xIubI6v4Kl6CSMG/g/w0aJuRkgENlZTCmxkz+EcpNRdYw3wrH7Pllbl7lMJYYM4sLESmJOzdCulwMajwBYz66lwz3GEYEjc1aOTEBzJBkWOEEILcZeNdWZ2sJI9ayk6biwi3WXjVvK7B+0hhDLGEo4t03PW7CId2thgZnnnmEVERKRgCmiItAF37wImZb7cB4zTPFOpF3f/OeEXbIA/MLMPN7IeERERERERETh3R/9NwBsJgY2bCBcuh6uHMObz68DHK73bP6e+UcBVlMIad1Ae2DhAeiSKAhvSshIdL5KBjWXAhMzSU8AGEqNRzGxXFfteSAg2JDttzM1ZuoN0l43HzexUpfvWSjR6eDHpLhs3U/469hECGUejxxYAk3Oechvp0MbjZnayJsWLiIiMYApoiLQBd99CSIRnXWNm2+pdj4xM0S+5+ym1j7zZzDY3sCQRERERERGRMtGd9cuBuwgjUZYQxnbm6af8jvtYN7Ad+CvgU2bWVVB9o4CrSY9EyV5EjgMb8UiUrQpsSCtz9/GE8FRyNMpVOUt3kwhsAI9V+t6L3msLSXfZ6KD8Rrge4AkSXTYI77mmuzEueh1vID0e5QZgTGbpWeBloIsQ1lhIeaehXuAp0qGNLWZ2tlb1i4iIjAQKaIi0AXf/HPDLOQ/9azP7Sr3rkZHL3e8Cvh99+iow18zONLAkERERERERkUG5+wXAbcCbCIGNKxg4lDGY08CzwF8Cnyvq9+HoIvI1lAIbd1Ae2NhPeiTKcwpsSKtz91mE4EQc2OgEpmWW9QJbSI9Gea7S8IS7jyWMSIr3WwFcT3mI6yghsBB32Vhb1Bikorn7JEJnjWSnjWtylp4kBGBOAxcSQhvZYMcZYBPp0EZThlVERESalQIaIm3A3X8B+GrOQ583s39f73pkZHP3LwP/Jvr0G2Z2XyPrERERERERERkOd58C3A7cA7yLcJGyEieBJ4HPAn9lZj0F1RcHNuJxKHcAczLL9pEeiaLAhrS8aKTHNaRHoyylPERwlFK3i3g0yqEq9p0K3Eqpy0YnYUxI1s7EvmuBjc06IsTdpxPGyiRDG5fmLD0G7CV03JgJzM9Zcxx4jHRo4yUdc0RERPIpoCHSBtz9KsKMwKynzez6etcjI1vUKnY3cHH0pXeY2T82sCQRERERERGRirn7DGAVcC/wNmB2hU91AtgIfAr4ppn1FlTfKGAxpXEod1Be417SgY1tungq7cDdJxPCE3FgYyX5IYLtpEejbDaz7ir2XUApsLGCEHCYklkWd/eIx6KsBZ4t6r1fNHefQ3o0ynJK5/eSDhG69hA9nrfmFdKBjfXN2mFERESk3hTQEGkDUXq8m/K0+Ckzy85MFKk5d19CmFE5ivB3c56ZHW5sVSIiIiIiIiLViy5i3gG8A7gbmFHhU8V3+T8I/KCowEQU2LiW9EiUgQIba6I/tyuwIe3C3RdSCmx0EkIHEzPLzhACU8nRKDsrfR+4+xhgCaXARiehu0d2NMpxYAOlLhvrzGxPJXvWWnQsuYR0YKODMP4kax8huDEGmEf5KBqAl0mHNjaY2dHiKxcREWluCmiItAl330P4x2/WRbowLo3g7v8f8PvRp5uAZTrZIyIiIiIiIu3G3S8ldK54d/Tn1Aqf6jDwMPAx4OcFBzaWkA5sZO9430Opu8Ya4Hn9Di/tIur2egPp0Ma1OUv3UwpsrCV0fThexb6TCWNE4rEoK8gfI7KLdJeNx8zsRKX71lJ0o+DVpAMby4ALMkv7CB12jwITCCNh8m4kfI50aONxMztVk+JFRESahAIaIm3C3b8DvCXnoTvNbE296xGJTgBtAeIxO//VzP6ogSWJiIiIiIiI1FT0u/CVwJ3A/cBrKb9zfyj6gYPAj4AHzOyJgmtcQmkcyh3ArMyy3aRHoiiwIW0lGl20nFJgYyUwM7Osn9AhNtll45lqRpS4+zxCUCPusrGc8o4UfdG+57psAE818WiUsYTzf8lOG0uBsZmlZwnHlhPAZGAhMC6zphd4knRo40kzO1ur+kVEROpNAQ2RNuHuvwM8kPPQ75vZf693PSIA7j6LcBfOOMIvtYvNbFtjqxIRERERERGpjygMcT3wBkJgYzkwfoDl/YRRoXn6CCMEvgf8gZltL7jG6whBjdXAKsoDG7tIBzZeUGBD2kkiXJUMbNxMecjgOCE0EAc21prZ/ir2HQ0sJt1l48acfbsIo1HiLhtrzWxXpfvWmrtPBG6i1GVjOaFrSfYYd5pwfDlDCKosoHwszGlCd95kaOM5M+urVf0iIiK1pICGSJtw99uAn+U8tMbM7qx3PSIxd78f+Nvo033AJWbW08CSRERERERERBrC3ccQLvq+EXgv+RdiY4MFNnoJd6L/I6HDxp4CaxxNKbARf1yUWRYHNtZEf+5QYEPaTRQyuIX0aJTLcpa+SCKwQRjTcbrKfZdR6rLRCSzKWbqHUmBjHVWOZKk1d7+Q8HMlO20syll6HNgL9AAzyB/rfQx4jHRoY6eOQyIi0goU0BBpE+4+lfAP06xDZpa960Gkrtz9n4C3Rp9+3sz+fSPrEREREREREWkG7j6ecJHyLuA9hNEj2bvHY4MFNnqAl4C/B/7IzF4psMbRhC4gd0QfqygPbLxMqbvGGuBFXSiVduTuc0kHNlYQxnUknSV0fEiORqmq64y7zyYd2FgBTMss6weephTYWEsYD9K0N0q5+8XAraRDG3Nzlh4GDhB+xosp7/IDYSxUMrCx3swO1KBsERGRqiigIdJG3P04MCXz5X5ggub0SSNFyf99lGZq3mlmaxpYkoiIiIiIiEjTiX5/vg14EyGwcQUDhzIGC2ycBZ4HvgL8cZF31ScCG6spBTZmZpbtJDESxcx2FLW/SDOJuuJcR3o0ynWUvzdfIRpNQghsrDezV6vYdzRwNaWwRidhpMi4zNJThE4T8d7raOJOE9GomQWkAxsdwPSc5QeAQ4RQ2zxK5x2TdpIObTxmZkeLr1xERGToFNAQaSPuvpHQdi/rRjPbUu96RJLcfQXhF0EIvxzOaea2iyIiIiIiIiKNFnVMfR3wFuAdwCWDLB8ssHEG2Ap8AfgzMztVYI2jgRsIYY3VhMDGjMyyl0gHNl4san+RZhON8lhOutPG7Jylz5AejVJVtwt3v4AwQinZZePKnKX7SXfZWN/MoYUotHEl6dDGMmBSZmk/YezLUWA8IegxMecpt5IObWwq8pgoIiJyPgpoiLQRd/8M8MGch37VzD5X73pEstz9k8D/E336UzN7fSPrEREREREREWkl7j6TEIC4N/rIu+g7FKeAJ4HPAV8osvNqFNhYSnokykCBjTWEwMZLRe0v0myigMEi0oGNZYQQQdJJYAOJ0ShmtqfKvWcRghpxl40VlHe8AXiWdJeNJ5q5I7O7jyWMhEp22cjrINID7AZOEEbRLBhgzZOkQxtPNfPPLyIirU0BDZE24u73AX+X89DfmNkv1rsekazoJM0LwGXRl37FzP53A0sSERERERERaVnuPpfQteJtwN2UByGSBuuw0QU8Dnwa+Dsz6y2wxtHAjaQDG9lxBS+S7rChwIa0NXefQAgUxIGNTvK7XewiEdgANprZySr2jbtRJLts3EJ5WOQ0sJFSl421wIvNOhoFzr2mN5LutJE3buYMIbRxmjAWZT5hTErSacIxMRna2GZmfbWqX0RERg4FNETaiLsvAvJmem43s6vrW41IPne/lPD3dDTQCywys12NrUpERERERESk9bn7ZYTAxruAO4EpgywfLLBxjHBB8hPAd4u8KOnuYwgdNlYTAhuvpzywsYN0YGNnUfuLNCt3v5gQmEiGNi7MLOsFNpMejVJVcCARFom7bHQCeeeSD1IKbKwD1pnZkUr3rQd3n0LoVhJ32VhOfhCmizAepYcQdJubs+Yo8Bjp0MbLzRxaERGR5qSAhkgbiRLQ3cDYzENngQn6x6I0C3f/v4E/iz7dAVylBLqIiIiIiIhIcaLzRFcRghr3Aa8DLhjkWwYLbBwBHgH+iDCytLBzTFFgI9thY1pmWRzYiEeivFzU/iLNKuo+s5hSYGMlIdyU7fZwhFJw4lFCcOJQlXvPJIQZ4i4bncCsnKXPUQpsrAU2m1l3NXvXWvSzxWGN+GN+ztKjwH7CsXEWcFHOmgOkAxvrzexgDcoWEZE2ooCGSJtx953AJTkPLah2ZqFIkdz9EeA10acPmtl/bmQ9IiIiIiIiIu0suth7PfAG4D2Ei5LZsQax+KRxXmCjHzhECEw8YGYbC65zDOFu/jsoddjIBjZeIN1hQ4ENGRGijhC3UgpsrATm5SzdRrrLxhPVBCeiwNflpLtsLAMmZJZ2E0aDJEMbzzf7jYPuPp/y0MbMnKWvRB9jCF02puaseYl0aOMxMztWg7JFRKRFKaAh0mbc/ZvAO3IeutfMvl3vekQG4u4XAvuAidGXlpvZhgaWJCIiIiIiIjJiREGIW4A3AvcTQhFjBlh+vsDGfuD7hMDGszWo8ybSI1GyYx+eJx3Y0ChVGRGi4MRCSoGNTkLQINst5zSwkVJg41GqHM/h7uMJHT3iwMYK4NqcpYeIRqJEe1fd4aPWEoGUZGDjVmByzvK9wKuEwNt8Suc6Y/3AVtKhjU1mdromxYuISNNTQEOkzbj7bxHmg2Z9wsz+U73rERmMu99FOIEDYb7tXDM71cCSREREREREREak6GLrCuAuQmBjMeWjFGKDjUPpA3YD3wY+amYvFVznGL0emh8AACAASURBVOBmQlhjNWF0SzawsZ10YGN3kTWINDN3H0cITiRHo1yTs3Qf6cDGBjM7UeXe0wlhhmSnjdk5S5+P9o07bTR9YCE69iwmHdq4mfJORL3AHuAEMAlYQPlI8h5gC+nQxlNm1lOr+kVEpHkooCHSZtx9BeEftlmPmtlt9a5H5Hzc/YvA+6NPv21m9zayHhEREREREREBd59IGE36JuA+4AoGDmUMFtjoAV4GvgH8oZkdKLjOsZQCG3cQOmxkxw7EgY01wEMKbMhI4+4zKYUm4uDGjMyyPuBJ0qNRnjGzvir2HQVcSrrLxq2Ud5k4C2yi1GVjLbC9mr3rIdFFJA5sdAA3UB5u6yaENk4RAmXzKT9mniKMh0mGNpr+NRARkeFTQEOkzbj7JKAr56GjZja93vWInE+U6t9FKU3/XjP7egNLEhEREREREZGMaFTp64C7gXcSxioMZLDAxlngBeBrhI6vRwuucyxhdMsd0cfrKA9sbCPdYWNPkTWINLsoOHE16cDGTZR3ejhGCArEgY211YasonOBN5DusrGE8mPGqyTGokR7H6xm73qIzs/fQrrTxtU5S08RQhtnCWGZOTlrjgIbSIc2dlUzmkZERBpPAQ2RNuTurwLTch6abGYn612PyPm4+xLgKcIvYmeBhUXfUSMiIiIiIiIixXH3i4BVwFuBe8kfYxAbLLDRDTwHfAn4UzPLu/GomjrHAstIBzamZJY9RzqwsbfIGkRaQdQ1ZxmlwEYnoftF1g7So1E2mdmZKve+kNB9Iu6y0QnMG2DvZJeNx1thXLK7zyB0Dkl22rgkZ+kxYD/hmDkLmJmzZj/pwMZ6M3ulBmWLiEiNKKAh0obcfS3hH7JZnWa2rt71iAyFu38Y+Ej06VPAUqXBRURERERERFqDu88DVgNvI3TZGKyT62CBjdPA08DngM+bWXfBdSYDG6uB2ykPbGylFNh4SIENGami93Wyy8ZyYHJmWTdhNEdyNMqOas7rRR0+FpLustEBTMos7QGeINFlA9jaCmNB3H0u4WdKdtqYlbP0UPQxmtBlI9sRCOBF0qGNx8zsePFVi4hIERTQEGlD7v7HwG/mPPTbZvbJetcjMhTRL16bCXMbAX7XzD4yyLeIiIiIiIiISJNy90WEAMS7oj+zIYikwQIbJ4FNwJ8CXzOznuKqPDduIdthI3sBOg5srCEENvYVWYNIq4gCTtdRCmysJH88yUHSgY311Y4zSuyd7LJxPSG4kHSUEFI412nDzPZXs3c9ROdGLyMd2uggP5CxnzACZjyh08gFmcf7gWdJhzY2m9npmhQvIiLDooCGSBty97cD/5Dz0D+Y2TvrXY/IULn7xcBuYBzhF4mlZvZUY6sSERERERERkWpEFx6vAe4E3k3oWpG9oBiLT1gPFNg4DmwA/gT4VtF3ykeBjVspBTZupzyw8SzpkShNf/FXpFbcfRohTJDstHFxZlk/8Azp0ShPmVlvlXtPIbxf4y4bKwidN7J2UhqLso7QYaLpR4G7+2jCsTPZZeNmyo+ffcBewvFxEjAfGJtZcxbYQjq08XTRoTcRETk/BTRE2pC7X0L4R2fWy2aWNzdQpGm4+/3A30afvgIsKLqdqYiIiIiIiIg0TnTR8QbgDcB7CBcdxw2w/HyBjVcJF3s/Dvyo6HGpUWCjg3RgIztm4RnSI1EU2JARKwpkXU46sHELodtDUhchbHUutFHEOCF3n086sLGc8g4+vYSwwrkuG8Cz1QZG6iE6Jt1AutPGUmBMZulZQmjjFKELxzzKj6MnCeNpkqGN7Ro7LSJSWwpoiLSh6B/BZyj/xbYXGN8KM/hkZHP3bwH3Rp/+tZn9m0bWIyIiIiIiIiK1E40uWEbosHE/cBPlFxtjgwU2+oHDwE+AjxLGKtQysLEaeC0DBzbikSgHiqxBpNW4+wRC54fkaJTLc5a+TLrLxkYzO1Xl3mMIY1jisSidhIBD9hgTd+eJu2ysNbM91exdL+4+kfD6JkejXJuz9BSwD+gGZgCzc9a8Sngd4sDGOjPbXYOyRURGLAU0RNqUu79A/j9yrzKz5+tdj8hwRL9U7AWmRV96i5l9t4EliYiIiIiIiEidRBdzVwB3ETpsLAZGD7D8fIGNA8APgQdqMUbV3cdT3mFjYmbZ06Q7bCiwISOeu8+mFJhYSXjPT80s6wE2UwpsrAW2VRu8cvfJhFBY3GWjE8jrPL2LdJeNx8zsRDV714u7X0gY/5Icj3JZztITwH7CmJRZhOBG1l7SoY31ZnaoBmWLiIwICmiItCl3/zrhF9is95rZ1+tdj8hwuftywi9AAKeBeWb2agNLEhEREREREZEGcPdJwGuANwH3EW5KGmjkSf8gj/URLjR+hxDY2FFwqXFgYzmlwMZrKQ9sPEU6sHGw6DpEWk3U6eJa0qNRbqA8nHWYcM4wDmysM7PDBew/l3SXjeXAhZllfYT377kuG8BTrTAaBc6FYuLRKPGfc3KWHiGMnh4dPZ4dEQOwg/RolJYJr4iINJoCGiJtyt3/I/DpnIf+3Mx+rd71iFTC3T8B/Fb06aNmdlsj6xERERERERGRxnP3acDrgLuBdwILBlk+WGCjlzBS4R+Aj5rZviLrhHOBjRWkAxsXZJY9SSmw8RMFNkQCd59CCBIkR6PMzVn6HOnRKFvM7GyVe48mdO9Jdtm4ERibWdoFPEapy8Y6YFfR45VqIRqVvpB0l40OSl2Nkw4Qxp+MB+YBEzKP9xHGOyVDG0+Y2ZmaFC8i0sIU0BBpU+5+K6HtWNYmM7ul3vWIVCJKzm8HFkVf+nUzywseiYiIiIiIiMgI5e6zgFXAW6OP2YMsHyyw0UO4K/xvgU8UcVd+VjS+Je6wsZrQGWSgwMYaQmDjlaLrEGlFUaDgEkqBjU7CGI/se+g04dx4cjRK1aGJaCzzLYm9Oymdt0zaS7rLxgYzO1bN3vUSBVOuIt1lYxnlnYD6gX3A8eix+cCYzJqzhBE1ydDGM63ScUREpFYU0BBpU+5+AXCS8l84u8wsryWZSFNy90sIJ0fGEJLYV9WiBamIiIiIiIiItAd3n08IP7wduAuYMcjyPspHKMS6CTeOfBn4dC3a90eBjWSHjbzAxhbSI1EOFV2HSKty93GEzhbJLhtX5yzdQzqwscHMugrYfzbhPRx32VgBTM8s6weephTYWAs8aWY91e5fD+4+FriOdKeNvG4iPYRwyilgKqHbSdn1CWAj6dDGC63QcUREpCgKaIi0MXc/BMzMeWimmR2pdz0ilXL3XwX+PPr0ZeByJa1FREREREREZCjc/XJCYOOd0Z+D3bw0WIeN08CzwOeBz5nZ6SLrhHM3XWUDG9lRAk+QHomiwIZIgrtfRCkwEQc3sqGJPkL4KQ5srAWeNbO+KveOO1DEHTZWADcD4zJLT1EajRIHN3a2SlAhOlbdSDq0sYTy4+cZQmjjLOH/g4tznu4woePJudCGme2pTeUiIo2ngIZIG3P3hwlzLbPuMLOH6l2PSDUyf58/Y2YfamQ9IiIiIiIiItJ6ohEJi4E7gXcTzjVkO1bE4pPnAwU2ThIu8P4Z8NdmdrbAUoFzF0E7KQU2biMd2OinPLBR+GgWkVYWhSauJh3YuInykRxHCQGBc6ENMztYwP4XEEIacWCjE7gyZ+l+0l02NpjZq9XuXy/uPpUwDiUZ2rg8Z2kX4WftA2ZRHp6B0PEk2WVjg45tItIuFNAQaWPu/ofAf8l56HfN7CP1rkekGu4+jZC2jucd3m5mjzSwJBERERERERFpcdGF26WEwMb9QAfld7rHzhfYOEFo3f8p4Ju16P45zMDGGuCnuqgpUs7dJxHCBMnRKAtzlr5AKbDxKLDJzLoL2H8WIcCQ7LSR1w37WdJdNp6oRRisVqKf81bSoY15OUuPAq8Qjq9zgMk5a54nHdrYWMSYGhGRelNAQ6SNufs9wLdzHvq+mb253vWIVMvd7wK+H316AphXi/mvIiIiIiIiIjIyuftYwsXEO4H3kH+Xfex8gY2jhAuqnwB+UO3ohDxRYGMl6cDG+EyNm0l32NDoY5Ec7r6AUmBiJSGwNSmzrJsQxIoDG2uBF6sdTRJ197mSdJeNW0i/nyGMWnqcUpeNdcCOVhmNAude5zis0RH9OSNn6SvAEcJrMJfycU99wNOkQxtPFBGgERGpJQU0RNqYu88Hduc8tN/M5ta7HpEiuPsXgfdHnypsJCIiIiIiIiI14+4TCBdK30gIbCwGRg+w/HyBjcPAT4E/An5Wiwuq7j6RdGBjJeWBjU2UAhs/VWBDJF8U2LqB9GiUJTlLD5AObKw3s2MF7D8BuJF0l41rcpYeJAQ14i4b61rpfR2FU64g3WVjGfldNPYBxwldludRHqDrJoTSkqGNZ2vR0UhEpFIKaIi0segfNqcpT9n2AxNaqRWaSMzdxwEvE1rdAbzfzL7cwJJEREREREREZIRw98nAa4G7gPuARQwcyBgssNFPuDv8X4AHzOyJYisNMoGN1dH/To5w6Sfcjf9jSoGNV2tRi0g7cPfphABBcjTKRZll/YTODsnRKE8XERJw95nR/nGXjU5gVs7SbZS6bKwFNrdSZwl3H0MIwyQ7bdxE+bWOXkJo4yQwlXDOOHvMjcdPJUMbLdV1RETaiwIaIm3O3beSn6pdamZP1rsekSK4+7WEX3JGAT3AZWa2p7FViYiIiIiIiMhI4+7TgNcDdwPvABYMsnywwEYf4SLj9wiBjW1F1hlz90mUd9gYKLCxBnhYgQ2RgSW6P8SBjXg0ybjM0hOEYMC5Thtmtq+g/Rcl9u4kdJ/IjgPppjQaJe608XwrhRSijiJLSXfauI7yrkbdhONpNzCd/ADLIWADidCGme2tTeUiImkKaIi0OXf/CvCLOQ99wMy+UOdyRArj7h8GPhJ9+hywpBazXEVEREREREREhsrdLwZWAfcA9wIXD7K8j4HHpfQSRhf/I/AxM9tVZJ2xKLBxG6XARifpC8t9lHfYOFqLWkTahbtfANxMusvGopylL5EejbLRzE4XsP84SqNR4k4b1+YsPUwprBGPZnml2v3rKepqdAvp0MZVOUtPAfsJx9ZZwLScNbtJd9nY0EqjYkSkdSigIdLm3P1XgL/IeejLZvb+etcjUpQoHf4EYQ4kwB+Y2YcbWJKIiIiIiIiISIq7LyCMFrkXeDPhbu6BDBbY6CFczP174ONmdrDIOmNRYOM1lAIbKygPbGykFNh4WIENkfNz9zmUOlysJAQJpmaWnQU2kw5tbC+iy0U0mqWDdKeN2TlLnyfdZWNTEaGRenL3GYSfNRnayOtudIwwamoUYTTKpJw120mHNh43s64alC0iI4gCGiJtzt1vJqTcs54xs+vqXY9Ikdx9NrCL0omCZWaW9/ddRERERERERKTh3P1y4E7COJQ7gcmDLB8ssHGWcCH1K8CnahWSiO5OjztsrCYENsZmatxIGIfyY0Jg41gtahFpJ+4+BlhCKbDRSbgRLTsC6RAhLBEHNtYV0dUhuvntUtJdNm4FJmaWJkMjcXBjW6t1Mnb3eZSHNi7KWXoYOEI43zwXGJ95vA94inRoY4uZddemchFpRwpoiLS5aC7bKcr/YXcGmNhKM+ZE8rj7/cDfRp8eBha0WqpbREREREREREae6ALptYSgxjuB24ELBljeH30MFNg4A2wFvgD8mZmdKrTYSBTYyHbYyAY2HiPdYUOBDZEhcPephBBBcjTKnJylWykFNh4lBAR6Cth/HHA9pQ4bK4DrKL+28CohqHFuPEqtuvrUSnT8XUQprNFBCKhku5pAGI1ynBBemQuMyTzeDWwiHdrYama9tahdRFqfAhoiI4C7HyTMVcuab2Z7612PSNHc/R+Bt0Wf/p2Z3d/IekREREREREREhsvdRwM3EgIb9xEuGo4bYHl8Yj974TR2CniSMPr4S7W6u9vdp5AObCwnHdjopTywcbwWtYi0m0SXi2RgYxkwIbP0FLCBxGgUM9tVUA0XEsILcZeNTmBeztIdJAIbhFEgNQmK1Up0DF5MusvGzZS/3n3APsLrPoX8EM0JwrEvGdp4UTfMiggooCEyIrj7jwgtCLPeYmbfrXc9IkWL5qPuAaZFX3qXmX2zgSWJiIiIiIiIiFQlupv9VuANhMDGjZTfuR07X4eNLsIY5E8Df1/E3fZ5osDGa0kHNpI19xIuJP84+nhEgQ2RoXP38cBNpEejXJWzdDeJwAbwmJl1FbD/KGAB6S4bHZSPa+oBniAd2tjagqNRxhNGzyQ7bdxA+bH4LKHTxhlgOvnjU14hHP/OhTbMbF9tKheRZqaAhsgI4O4fAT6c89BHzey/1bsekVpw9+WEf+iPIvxDeKGZvdLYqkREREREREREihGNMl4JvJEQ2LiWgTtoxBdBBwpsHCNcOP1j4J9rddE0GtkQd9hYTbi4mRfYWEMpsHGiFrWItCt3n0UISsSBjU5KN7LFeoEtpEejPFfEe9/dxxJGocSBjU7CqJTs8ecYIZgQBzbWtWJAIbpZ8GbSnTauyVl6CjhAOB5fBFyYs2YX6S4bG8zs1RqULSJNRAENkTbn7hOBjwK/McCSPuD3zez36laUSI24+4PAb0efbgQ61DZORERERERERNqRu08GbicENt4NXM7AgY3zddg4AjwC/BHw01qdT4kCG8kOG3mBjfWkO2wosCEyDNGojmtIBzbyOvAcpRSWeJQQmCjkhreom86tpDttLMxZujPaP+608ZiZnSyihnpy9+mE8TPJ0MalOUtPAAcJx+LZwMScNdtIhzYeb8XXREQGpoCGSBuL2o0doTwtm7XJzG6pQ0kiNeXuYwj/gL08+tJB4GLgKTO7oWGFiYiIiIiIiIjUWHSB8PXA3cDbCWMIBtJHCHPkBTr6Ca34HyLc+LWxhoGNCykPbCRDJD2UBzaqHtMgMtJEga5llEIbK8k/RmwnPRpls5l1F1TDfNJdNpYDUzLLeoEnSXTZAJ4xs94iaqgnd59DOKYlQxsX5yw9En2MA+ZGfyb1Ak+RDm1sMbOztalcRGpNAQ2RNufuO4FLzrdMHTSkXbj7pcAOyu8ImWZmxxpQkoiIiIiIiIhI3bn7bELo4W7gbcCsQZafL7CxD/gB8ICZPVtspSVRYON2SoGNWykPbKyjFNj4mQIbIpVx94WUOlysJIQJsh0dzhA6FSdDGy8VEdqKbra7lnSXjaWUd/o4ThiFFHfZWGtme6rdv96iG2ovJR3a6CB/9MlBws99ATCH8tfkDLCJdGhja63GVYlIsRTQEGlz7n4lsJXy/4AnLanlL1Yi9eTuXwL+bc5DK8xsfb3rERERERERERFpBtHF2NXAvcCbGbzrbh8Dj0PpA3YD3yYENnYWWWdSIrCxmhDYWEZ+YGMNpcCGRgGIVMDdxwE3UApsdBICFFn7SQc21pvZ8YJqiDt9xF02OskfFbKbdJeNDa04DikaR3M16S4btxCCGUl9wAHgJKHryOycpzsOPEY6tFFImEZEiqWAhsgI4O4fAD4/wMNngIn6j7S0C3fvAiblPPQBM/tCncsREREREREREWk60Z3cVxCCD++I/pw8yLcMFtjoBXYC3wA+bmb7Ciw1xd2nke6wkQ1snKW8w4YCGyIVcvcZhNBAcjTKzMyyfsIIjjiw8SgFjiVx97mUAhsroo9s14m+qIZzXTYIY69bcTTKWOB60qGNpcDYzNIeQlimG5gOzMh5uldIBzbWm9n+2lQuIkOlgIbICOHu6wj/Ic961syW1LsekVpx9w7gW4R5fUnfMrO3N6AkEREREREREZGmFgU2lgB3Au8CXgtMGGB5f/QxUGCjB3gB+C7wN2b285z95hLCFT8ws7NV1D2ddGDjFsoDG2spBTZ+PlBgI3quM2Z2qtJ6RNpddKy4knRg42bKwwPHCYGAc502igoGRF0nFpPusnFjTg1dhI4SyU4bu1rxZlV3nwjcRHo0yrWUj6U6Q+i00UsYazUl5+leJh3a2GBmR2tTuYjkUUBDZIRw9/HAw4R5ZVMII0+OAKtq2YZQpFHc/X7gC5S6abxoZpc3riIRERERERERkdbg7mMIFzzvBO4jXAwcN8Dy8wU2eoFngC8CnyWEJo4SWvi/CtxgZrsLqns68DrSgY3kBcw4sBGPRPm5mZ1y96nADuAUcK+ZbS6iHpGRIAoP3EJ6NMplOUtfJD0a5XEzO514nhmE0UkPAx8eTngrU0Mc3Mg7F7yXUlhjLSGccCzzXB8mBL8+aGY7hlpDvUUjoJaR7rSxKGdpF6GTxijCaJTs+BSA56LH9wC/RwjUpMJq7r4c+H3gE2b2/UJ+CJERSgENkZHkoQ1XAX9NmCM3jvAf3D7gMPAp4NOs6ihkVpxIM4gS3Z8E7l6xYNEH3nL19b9JOLEA4ZfwTxL+7scJ61GUTipA+sRC3terXdtKe7VSrdqr8d+vvVprr1aqtV33aqVatVfjv197Nf77tVdr7dVKtWqvxn+/9mr892uv2uzVR7g49wjwEvA08LXhnAd093FLZs198+2XXPnRiyZPuXbc6NFjsmt6+vp4/vBBvrP9SU50d6ceGz9mDNfPns+cyVNYOHVG3/SJk0YDdPf2MmoU/ZPGjn9+/Nixfwb8Bas6jvPQhnmE8zZ3Rk+xHlhIuGMc4Engfazq2A7AQxumAr8C/BJhVMujgJ3sPvO+0aNG/9rYMWPmjgo3rI3K3m6eeK2SD/WNHj26n/LX9SzhIvPnztVa2v/9wFuj5/kn4EuFnmsN53a/SjiPNQY4DXwP+BCrOvYWto9IAaIuOcnAxgrKxyidBTZRCmzMAR6MHnsIeK+ZHUh9R/577RuE9/6vAxcT3re9vX29z/zjs0/8rycO7Lk0UcP0+Hg0c+IkDp862f/0gb1bz/T2/DyqYUO09+Qp4ycc/uVbbnt62sTJNxFuAoyPBz3AMUInis3Af2NVx96otvcBVwHbGeZxtgjufjEhUNdBKbSR7TQNISR3hHCdaDblAbxewnH2XKeNmRMn/c7rLrv6vRdNnMQoRm2cM+XCe8eNGXMC+BDwQcKNwUcIr8tJ4uNgkH5dgtoeM0WamAIaIiPFQxs+Dvyn86zqBt7Aqo6H61CRSP08tOE/AH/a6DJERERERERERJrAKcIFxnuGfB5wiOdW4usN39n2JBv27ATgkmkz+NdLlzOaUYwbO5b+/n5GRTGJnP99GvgM5z+PGXsQ+CbwA/LvCq+l08Bd0f/+HqUurrGTwJsLOdd6/nO7H2RVx2er3kekRqKuPNeRHo1yHeUjOpIOAu8xs58A8NCG28l/r53Pg6zq+M/uPvr+65e9b/FFcz7fT/+YsaPHjOvu6aGffv56y3pePnrk3Dd0zL+Ue66+AeDcMeq8e8CvEkIckwldK/oYznG2BqIbGBeQ7rLRAUwfzvNkX4/EteWeUaNGZUfLJJ0mvA79lF6XUYTXKXvMLu6YKdLkFNAQGQlCunrbEFd3AXNZ1XGihhWJ1E+442JPo8sQEREREREREWkyx4H55z0PWMG5lf7+fj7+sx/S09fLb9/2BiaMHWg6SiG6KL8zv17i127KII/Pq+pc69DP7c5lVcf+ivcRqbNoREcHpdDGPYQux1lL7Y63vgTsBqZWuN0VhE5Cuc/R29d35sGf/fAfTvWcXT1l/PiLf/u2Nw41mHE+QzvO1lEU2riKdJeNleS/9n8344JJY3698453FfR6nE/1x0yRFjBYqklE2scXh7F2IqHd1F/WqBaRenug0QWIiIiIiIiIiDSh0QztPGBF51buuuJadh47wuA3yBdiuHfTF2kipREpecZR/bnWoZ7b/SjwgSr2EakrMzsG/Aj4kbtPoBR4SjpJGMfxPmB8Fdt9GfgC6bFF54wZPbrnv97+pu/7j7999A1XLPmVKvbJGupxtm7MrJ8Q+tpGGJuEuz8CvCaztB/41m+sXH1nHW/2L+KYKdL0cg9EItJ2Fg1j7eiHdz7/51GKUqQdLG50ASIiIiIiIiIiTWgycOUQ1g373MqoUaOYM+XCritnzNo4YWzN7xNt5HnMMQx+I+wEhvYaD2bRENddU+U+Io3UA2wldOv5CvDLhPfOFDN7mdDxYUIVz39Z9BwDdduJj4cvzpo4ub/AbhFDPc422iHCKJK1wP8EVgMTzexLwOI6dc+AYo6ZIk1PHTRERoYXgflDWdjX38/hk11jgD53h5CS7Ae6zOzCmlUoUjtbCS3aRERERERERESkpAt4fgjrKjq3Mm/qtK/PmzrtEeCPqe0Ikn4aF9LojfYf6FrLGYb2Gg/mRYZ2bve5KvcRaRgz6wVuGGTJdsL7qdKQxkvRcww0EqkLeN7M/rL/x+uvAf5dhfvkPm9Bz1VL7wbGm9nJnMfqeX69iGOmSNMbVce2NCLSKEOfU0h3Tw8f//kPOdvbO9iyfkKacouZ3VJAhSK1U8GcVBERERERERGREeA4MJ9VHXljBUoqP7cylzCeYDcwtYLvH6qBLrjWQ/zaTRnk8XnnfY0HM/Rzu3NZ1bG/4n1EmtlDG6ZS3bHkCuCVQZ6jdDws9nzy0I6zzay+59erP2aKtACNOBEZCVZ1bAceHMLK7vFjx77ubG/v5wktxQZKcI0itO+72d37o48+dz/r7q8vqGqRYqzq2At8sNFliIiIiIiIiIg0iVOEi4b3DOkiWGXnVj7Iqo79rOoI+4T9zgzh+04ztPOYsQeBu6Pvq7fTwFuij7y7zk8Cb6n6QuPQzu1+UOEMaWulY0nee+18HmRVx47M8agreqyL7PGwsmPeg+d93lY1+OvRc57vPk34/yz5upwk/5hdzDFTpAWog4bISPLQhsuBrxJahY0nBC36CPPF/gT4zED/8XP3g8DM6HuG2jKwHzgLXGBmOthIYz20YQ6hpead0VfWAB8H/hS4ERgXfT35dzX5dz3v69WubaW9WqlW7dX479derbVXK9Xaf0AZ7gAAIABJREFUrnu1Uq3aq/Hfr70a//3aq7X2aqVatVfjv197Nf77tVdt9uoj3Dn+MKHN/zPA14Z9ESycW/k08CbyO1acAr4LfKgsLPDQhinA+4ClhFb5V0S1xTUcA74AfC66gz17HmctcClwbfR9TwDvZVXHjsTz/wrwAWAS8Cjwu8A7gV8FLiOc+4lfp0r/P+gBdgB/ca7W0v7vB94arf028KVCLzSGc7tfI5zHGstgr7dIu8p/r/098EvAbwIXE25O7yF7nEg/x/uAKwnjNPKPh+XHvPh40EM4Zu2M9vgdVnXsH/LztqrwenwUuIYwUul3CIGL/wh8iPAavUoYy3SK+DgYpF+XoLbHTJEmpoCGiFTE3UcR/iMbBz2Gqg84bWaNajsoIiIiIiIiIiIiIiIiIlJ3CmiISGHc/U8Ira7GMPTQRn/08S9m9qZa1SYiIiIiIiIiIiIiIiIi0kgKaIhITbn7fmAWoa3YUPUDvcBbzOyHNSlMRERERERERERERERERKSOFNAQkbpy94nAEYY/GiWe8TjJzHpqUZuIiIiIiIiIiIiIiIiISK0ooCEiDefu/xv4JUKXjeGENvqA42Y2vRZ1iYiIiIiIiIiIiIiIiIgURQENEWlK7n4QmMnwR6P0A98zs3tqUpiIiIiIiIiIiIiIiIiISAUU0BCRluDuC4HngXEMfzRKH/AeM/tmLWoTERERERERERERERERETkfBTREpGW5+9eA+xj+aJR+oBeYbmZdtahNRERERERERERERERERCRJAQ0RaRvuPgo4BExjeKNRIHTZOA7MMDMdGEVERERERERERERERESkUApoiEhbc/cO4GfAWIbfZaMf+KGZvbkWtYmIiIiIiIiIiIiIiIjIyKGAhoiMOO7+z8BdVDYapQ/4v8zsS7WoTURERERERERERERERETakwIaIjLiRaNRXgWmMPzRKP1AL7DAzA4UXZuIiIiIiIiIiIiIiIiItAcFNEREcrj7O4CvM/zRKBBCG0eBmWamg6yIiIiIiIiIiIiIiIiIKKAhIjJU7v4IsJIQ2BhuaKMP+ImZrS68MBERkf+fvXuP934d6Pz/ug/7iO0YKTSiMqEDv2ZCjZFOk6joSCUp5BBha9PO5WKca5PDiEokfiOMicp0UMr0UzQp6UhMsQs574297ftea/5Y989Dxrb3vtd3rc93rfV8Ph7+dF3v/+7v+uz343oDAAAAALD2FDQATtKc87TqvdWVOrlXNjarB44xnrHqbAAAAAAAAMB6UdAAWKE5532qp1dHOrnSxkb1RWOMv191NgAAAAAAAGA5ChoAO2zO+WfVzavDJ/F/36wuqK4xxji+0mAAAAAAAADArlHQANhlc85rVv9YndEVf2Wjtl7ZeP0Y41YrDQYAAAAAAADsGAUNgDUw5xzVuZ38NMpmNccYj151NgAAAAAAAGD7FDQA1tCc81D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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a290c0780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "unique_users = load_users_dataframe()\n",
    "unique_users = unique_users[0:5000]\n",
    "for index, row in unique_users.iterrows():\n",
    "    source_index = row['source_index']\n",
    "    if source_index is None:\n",
    "        unique_users.loc[index, 'exposed'] = row['time_lapsed']\n",
    "    else:\n",
    "        unique_users.loc[index, 'exposed'] = unique_users.loc[source_index, 'time_lapsed']\n",
    "\n",
    "\n",
    "unique_users = unique_users.sort_values(by=['exposed', 'time_lapsed'])\n",
    "\n",
    "max_generation = max(unique_users.generation)\n",
    "unique_users['pos_x'] = range(1, len(unique_users) + 1)\n",
    "unique_users['pos_y'] = np.add(max_generation + 1, -unique_users.generation)\n",
    "unique_users['pos'] = list(zip(unique_users.pos_x, unique_users.pos_y))\n",
    "\n",
    "DG=nx.DiGraph()\n",
    "DG.add_nodes_from(unique_users.index)\n",
    "previous_index = None\n",
    "for index, row in unique_users.iterrows():\n",
    "    if row['source_index'] is not None and row['seed_index'] == 0:\n",
    "        previous_index = row['source_index']\n",
    "        DG.add_edge(row['source_index'],index)\n",
    "pos = {index: row['pos'] for index, row in unique_users.iterrows()}\n",
    "attributes = dzcnapy.small_attrs.copy()\n",
    "nx.draw_networkx(DG, pos=pos, with_labels=False, **attributes)\n",
    "plt.axis('off')\n",
    "dzcnapy.set_extent(pos, plt)\n",
    "dzcnapy.plot('Tree plot', [30, 30], save=False)"
   ]
  }
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