qPCR-analysis-220519-plate1to3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ec1f6d73-3ad7-4908-89d5-2f7ca6735fbf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mkdir: ../jupyter_figures: File exists\n"
     ]
    }
   ],
   "source": [
    "import sys, os, glob, warnings, logging\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from scipy import stats\n",
    "from sw_plotting import change_bar_width\n",
    "from sw_utilities import tukeyTest\n",
    "from sw_qPCR import *\n",
    "\n",
    "logging.basicConfig(stream=sys.stdout, format='%(asctime)s - %(levelname)s - %(message)s', level=logging.ERROR)\n",
    "# logging.basicConfig(stream=sys.stdout, format='%(asctime)s - %(levelname)s - %(message)s', level=logging.INFO)\n",
    "# logging.basicConfig(stream=sys.stdout, format='%(asctime)s - %(levelname)s - %(message)s', level=logging.DEBUG)\n",
    "\n",
    "# ignore warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# plotting configuration\n",
    "font = {'family' : 'Arial',\n",
    "        'size'   : 7}\n",
    "matplotlib.rc('font', **font)\n",
    "plt.rcParams['svg.fonttype'] = 'none'\n",
    "\n",
    "# Make a folder if it is not already there to store exported figures\n",
    "!mkdir ../jupyter_figures\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "efcf0422-23ad-4b71-b55b-26a6719ed5a0",
   "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>Well</th>\n",
       "      <th>Sample</th>\n",
       "      <th>Primer</th>\n",
       "      <th>Cq</th>\n",
       "      <th>plate_id</th>\n",
       "      <th>sgRNA_id</th>\n",
       "      <th>group</th>\n",
       "      <th>well_id</th>\n",
       "      <th>relExp_25</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A01</td>\n",
       "      <td>A-188-1</td>\n",
       "      <td>Rps29 v1</td>\n",
       "      <td>19.334721</td>\n",
       "      <td>220519-plate1</td>\n",
       "      <td>188</td>\n",
       "      <td>A-188-1___Rps29 v1</td>\n",
       "      <td>220519-plate1-A01</td>\n",
       "      <td>50.747984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A02</td>\n",
       "      <td>A-188-2</td>\n",
       "      <td>Rps29 v1</td>\n",
       "      <td>19.577852</td>\n",
       "      <td>220519-plate1</td>\n",
       "      <td>188</td>\n",
       "      <td>A-188-2___Rps29 v1</td>\n",
       "      <td>220519-plate1-A02</td>\n",
       "      <td>42.877475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A03</td>\n",
       "      <td>A-188-3</td>\n",
       "      <td>Rps29 v1</td>\n",
       "      <td>19.335932</td>\n",
       "      <td>220519-plate1</td>\n",
       "      <td>188</td>\n",
       "      <td>A-188-3___Rps29 v1</td>\n",
       "      <td>220519-plate1-A03</td>\n",
       "      <td>50.705404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A04</td>\n",
       "      <td>A-188-4</td>\n",
       "      <td>Rps29 v1</td>\n",
       "      <td>19.627998</td>\n",
       "      <td>220519-plate1</td>\n",
       "      <td>188</td>\n",
       "      <td>A-188-4___Rps29 v1</td>\n",
       "      <td>220519-plate1-A04</td>\n",
       "      <td>41.412722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A05</td>\n",
       "      <td>A-188-5</td>\n",
       "      <td>Rps29 v1</td>\n",
       "      <td>20.491257</td>\n",
       "      <td>220519-plate1</td>\n",
       "      <td>188</td>\n",
       "      <td>A-188-5___Rps29 v1</td>\n",
       "      <td>220519-plate1-A05</td>\n",
       "      <td>22.764959</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Well   Sample    Primer         Cq       plate_id sgRNA_id  \\\n",
       "0  A01  A-188-1  Rps29 v1  19.334721  220519-plate1      188   \n",
       "1  A02  A-188-2  Rps29 v1  19.577852  220519-plate1      188   \n",
       "2  A03  A-188-3  Rps29 v1  19.335932  220519-plate1      188   \n",
       "3  A04  A-188-4  Rps29 v1  19.627998  220519-plate1      188   \n",
       "4  A05  A-188-5  Rps29 v1  20.491257  220519-plate1      188   \n",
       "\n",
       "                group            well_id  relExp_25  \n",
       "0  A-188-1___Rps29 v1  220519-plate1-A01  50.747984  \n",
       "1  A-188-2___Rps29 v1  220519-plate1-A02  42.877475  \n",
       "2  A-188-3___Rps29 v1  220519-plate1-A03  50.705404  \n",
       "3  A-188-4___Rps29 v1  220519-plate1-A04  41.412722  \n",
       "4  A-188-5___Rps29 v1  220519-plate1-A05  22.764959  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read in data from different plates and combine them\n",
    "plate_ids = ['220519-plate1', '220519-plate2', '220519-plate3']\n",
    "dfs = []\n",
    "for plate_id in plate_ids:\n",
    "    dfs.append(get_plate_data(plate_id))\n",
    "\n",
    "df = pd.concat(dfs)\n",
    "df.reset_index(inplace=True, drop=True)\n",
    "\n",
    "# Add a few helpful columns\n",
    "df['group'] = [df.Sample[i] + '___' + df.Primer[i] for i in range(len(df))]\n",
    "df['well_id'] = [df.plate_id[i] + '-' + df.Well[i] for i in range(len(df))]\n",
    "df['relExp_25'] = [2**(25-df.Cq[i]) for i in range(len(df))]\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4e67a70f-7451-495f-b35f-93eadcf0659b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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odFzAe0DskXjOoX517r2/KiilTgLsI1MB59hXAfu8PP+02tuWIwmrB6bR6KZdgP19bcsDMS9Q2wByFUqp14AHtNZ5Ic63DdNoCOq7IEJyMM4MITJncP5TF1pRMyGbYoCv8I6ErgcWYeIln4Jp7DmAx5VSDbXW91b1BMp4VJ+B1wEPmPA6qzGVfSpmFL29tS8BeFsptU77OnH8CGiM6bRxj2jMxJjrgp/litVD/Ave0JMaWAKsxYzY97Z+YMy/5ymlTtRa5wS5lP9hfGDsCXPJRxvueY3nYkJeAnwH7LaWfeZFqsrhPAsx9/Eg5r6fgHlmX2CUiqAopUZgwm+6R7FKMHOp3YpxK2A4pryBaSRPUiYah32UJse2HMn7Ar7vTKsQck2AnzANAhemk2gjkIYJD+oeIRqFmVYQMD6xUuoiTBl1e1cvAeZhrrUh5jpbWvsfwMwnDzh6rZS6E+PV3M0BK1/7MD5POgFDMJFVwDQw92E6CoKhMB/BZgH2fWKdtynGQWW6tb3YuoYdmPeyK15rrM4Yi5Gu2vhr8effwE229WxMOSrAOFfth3kuU6zrC8QHmHsFcLpSKjXE+wlG8XB7l54cQLam6u8jzS+Y8tQVr+PBDXit4XzeQ6vum4nvO7AQ07BMw9ShDTEdY/Z6uRI1WH9D7X73/glcbS1vw7wvTitvXa3tjYFvlVJddABrIWXCD8+yyYNRzpZj6oZuVnoK01mywPpmZAZIqwu+oeUqgAWYcMAVmHdsmG1/a2Cy9T6FaoP8gcDTleZorXdZy68Cl9v2rcQ8r1LrPCdios4kAP9USh3SWr8f4BpOwryf7lFIJ6Y+2GLlfzSmbn8EY/VZCa31RqXUfMx3Iwq40MpfQJSxFBllrZYRfppnsHQceMsDHH7btSqcglGoojH13lzM93MwJqQgmG/dS0qpRYDb0moNpo3SADgN0/4CE8HiZ611pTB5NVlmQ/Atpm04CG89sARvm+u3KqRl5wLMN1Bh7tNs67+zlVcw9/AfSqn1WutKUzps19/ettkdxjcBU5aaYAYpQrUDahylVAzwPb6+0A5h6oVczDNzt727ATOVUgO11juofZpi9KFA1pWfWPl0P4NLgL+HSe8y2/KH/juVUi9iBpPcHMT7XjTHDA41xNTRnymlbtIBIrYopa7yy8t2jM6Sg6mTBlnpKcz778T4iqs76rrXIdIfRtlbgLfnZNNhpncOvj0xV/ntv8m2b3qEad5hO+Zbv31JhO9d8/+twuotr+K1tbenE4G8ffT5jgjkx/nl87zDfBb+110MXOknk4zvaIELGBYgrXdtMhMD7L/Ptv8AcFKQPJ2H8bbrlv1fEDn7+a4NIhOPaei45ZYAvQPInYhpwLjlvq7GvZxoO/7dw3ku1XyWPmWP4CPuMyOQGYBvz+/nQJqfTH9MR4F/GRrlJxeF+fi69/8ANA5wzoaYjgl7Wqf7yXS17XMCTSK4L3Yrn9ww90xj6rquAd4B/xGUzgHO1RXf0YoP8BvRwnyErsOMrrnlbg/yPIttMk8AMUHk5tnkSghgiUBlC5kszLuWhOkovQ9IsWSftsktCnSfMY0o+wjW4wFkxvud819Agp/MGGBPgOfQ3k/OPoJzXZhnvswmO76679CRfocDvJ8B6xF8RxODyTgwjXG33A786m3MO/d2gHtfKU1qsP6mhr97VB6BzMOMOCk/uevxtTh5IsC5FKaD0i2zOdC1YsINLrXJLQSiA8jZrVcWAW0CyMRhFGb7NfxfALmJAZ7Vc5hOxFTM+zbWkrXXlSXAGQHSS8d07rnltgW4Z0n4Wi2txG8k0kon0AjzRD+5m237Zod55rfbZL8+jPfpFr88BSy3Nfj+XhvgPvwHSPIrY3/3k3Fa5da/bKfh+77MOAJlNmg9HKAcTgxyH0bZZDIjLMtP42ephukk2meTmRvkfF/bZHKAc/z2x2Isev3PObM2y4N1brulmgt4CL+RZ0wb1G5J843f/nfD3fNInyGB2z3zMQMIiZjO+Ltt5a/UJlfJAtOWbmO8Vlxl+LUb8LXULMeEf4/zk2mAsaLVtnQG+8lEYb5nbpmHqFxvxWHqRvv7VanNdiR/dXbiahTYp/wKxzWHkVZrfM1KN+JX6QD32PZPjjDdG2zH/OK3b7hf/p2YGMFDMY2eZGAEplfKLrfQv0BGkA+flykCeXtlsMG/Iggg/71fHi87zGfr/+KPDyLnwPejPi+AzLu2/RMD7M+07b8kTL7utcnuDCJjP9+1QWRut8msJoRZNqb3d79N/sQq3suJtmPfPZznUs1n6VP2ODyl3/6sfwAcQeRa4PtBrpQmpnfbvW9vmGegMBYYbvlAjfKdtv2PhrknrfH9YJWGuWeZWIpvgLRSMKMPbtlbA8h8bdv/Xpi8nWGTPYStUWjtf9S2/8cwabXEt5Pm1AAy9vfPhd+H1E/WrmCPCCH3J5vc0gD77Z09r4dIpxe+HRyayg2VW237fgqRll3ZOUCAjpJI36GaeC+r+qPmlP4LbTIFhGjwYDqndKg0qcH6mxr+7lFZ6R8fIi17J8eSAPvH2/ZnYZleB0mrIWbk0y1/hd/+DNu+EqBtmOv80Sb/YYD9E/2u898h0rIr2G+FkEvB19S2j9/+u2z7dhGkoxUzEvuLX/4m+sk0xmuO65mGECQ9u6J7fjXfpb5+1/ZLddKp4jmv9bsHAacjYQYkcvxkLw4i288mUwRE1VaZtWSC1sMByuHEIOcZZZPJjKAs/zNEnq+2yTmpPF1rkN/+UN+sx/3OO7OWy0MjfDv47wohOxzvAKUL6Gjb9264ex7pM6Ryu2cXkBwiLfvAyf0h5Ox6mP/gayy+nRp/CJN/u945zW9fD9u+kIPQ+E5PuK02n3W4X1078osIpdSfMPM63PyCaSBUJ600zMfbbVbqwszT8g+fZ3dkUUJklNuWY/z29bUtl2J6wq/XWi/QWudrrfO01nO11ldiGrFuBmPmntQmb+DNe2fgDRXEiZkyTmHG+m2uyWkiX2mtvwm0QxvvyrdgnhnAcKVUoOkRAVEmVNoKjLnZFszIcShm2pYbR3qeANxiW/6b1jo/mKA2JpF2D/w3HsZ5j1ms99QdmUADt+gg3rW11ll4za6DkYapN7ZjPHWHegYaY6LnJtCzt5uE3q+UOjNQWkqpRIyFSqxtc7j35d9a69wgecvFt1x28DtfW7zmtuXAnaFOpLX+CTM6A+Ye+U8XcGJ63/dj/I6ESms3pgPVTbh3Zo7WelGI/Q1sywlBpczUjgcw5vT2uhOlVG+8Jqz5GOUhIFrr1YSPfvEJXodcY6wpCIGwmxd+prUuDyJX37Hfhxe01huDSpoOlcJgO2uh/q7N796aYN8xC/u+DgH2278ZT1vvVkCsuuxR2yb/b0ZrzEj6FuALrfX2EPmCqn/3QpnaRvQOW/XaLRgriDFUdoxnL0cPaBMmOVA6FXgb/cHOdRDTiQymg/fiQHKW4zG3h/4cTLuxSigTpnkyZuQSjOL156qmUwM8FmijNpFl7E4stxL8vVqB6RQF8yz9HVHWZJmtC5wYvy/B+BZvuXJQeQqvvYx+oLWeGyKtx4h82nBNMBbv+7eREN85rfWvGCUVjBVdv1rNmZe3dOipRHad79IQcqFM+y/CO8V2mdb6nTB5ehzvdM5TlYm448Zet8UE+3ZYPAzcBpyNaa/UGUe90m/NmbDPpdiL6RUMF14nUFppGDM3uwf4J7TW0wOIO4MshzxFiH2TMOaBf8E4hvgpmKDW+r/Af22b7ghToA4LqxFgr+yuAWYppc5SSqUo4z17oFLqbYxprBMz4uKmtAaz80aYvGZi5mG7OTvShLXWB7TW47XWvbTWHSMoQ3bFKzaoVAishoO7otB4FaxQ/GBbHlWd89YDzsLbqJ6nTZzjUPyPEOVQa/2V1nqM1rqd1vpvEZw/3LN/CTNSAaaD7zvLG25vZbyUN1JKXYAx0z8Z37m/4d6XmWH2Z9qWk/z2jcFbry8J1jj2I2h501o/prUeprVuprWeEkFaVXlnQjWKwNdb+ltKqdOVUpXqWK11jtb6Ka31p7py2Fd7+LtvQnX2WIRsBGit92O+IWDK5wVBRO2Nkmp1UB/rWPPvT7dtCnkftPF5MCnE/hqtv2v5uzczTN7s6fi8w8p4zj7JtiloW8GG/R0eqpTyKNha6zla69Ote3ZlBGlV5R3erbX2V9Dt2N/hy5SJqBDQc73W+h2t9Vta61/s76ky0VncvjvCzqvXWm/At40QCHtZDOgXhcodd1Vq51gdsNPxRugA03m9tirp1AAFhI6Otc+2PNfq9K6Etd3uL8Wj9NR0ma0j1usQkXis+sn+bvh/e+3fmnB1XTkB5prXIva8fRJB3XkZkK61TtNaf1mL+bITrj3wA97y10cFiKRg1RXucpiHN1Sym9Nsy2HLqNa6GN+6fKRteSPeTuO2wMfBBiG11jO01v/SWv8QqjPsSHBUO/JTSt2MccDkbujlYUbIs6qRVjpG4bIr/B9gzHsCYR9xiPQ+2eV8PhBWnidHmA6YeSB/tJabYkyH/B0R1SQTMcqp+0N3Ir6Vshv3aPsZeJ2VRGoJEQ4X4T/WYOYkjrCWe4YSrArKhGnsgnGodwLekWaofgfZENuyE3gxgN7ij72h1ToCh2H1kUG25VCjwQBorQuVUqv8josYq37ogWlcjsD341Dp2VvnG48JEdoG8+7/lcBWObswPczLrPVw70s4p5h2xdW/brKXt5aWQ9BwtLct9w4m5I/VEdkWYxY/ENNhYL//4d6ZcI3fVzHm4co6z0/AXqXUT9byNEsJD0VVy9EmpdQBvA7eAvEBxicMGOXe5x4rpfrjdWS1WWtdXcdSxzrd8DaMD2mtN0dwzG8EcSgZjmrW3xOpne/e4bzDffG1NLxfKRXJN7YM8+2IwZS/5REcg1KqMSZufD+MaW9Vvnvh3uGfMPeiE+Y9fgx4UCk1G9Me+0lrvTJMGm7Hb2AsKIrCyIMpRyeG2D8ZM4KXilE4MwJ0XlS7485ynDgNX0fNT0QwslgbZAZT5C3sVq7hFBK7rL0hc0TLbC0RiTPqfEyZAdt7q5RKxlgLuQn7raH6DgerQ3fbctjw6NrrhPNIErIu0VqXKaU+xeuQ91Iq62+X4K2zPrcsWezY20ejImwf2Z3He9pHWuscpdRHmKk0YNp4FyqllmMGBqYCv2qtyyI4xxHjqFT6rdGcJzCh7NzkYZzABPTKGia9bpgPeYZt8yeY+RzBKsMC27J/j14w7OYe4UaUQqK13qCU2oXXw2cfalHp11q7lIk9vRhjipISQGw9ZirELKWU3STOM5qolHqS8CaBv2mt3wuwfX8EI3Fg5uS4SQ8qFQKrkj4PMwrbDfNiVyutMNi9k0djTA+rSmN8PcYfD9jja0faM7qTCJR+qz64AKOodsKY1zYIdUigjdY7OhQTmitQ/GInxlTyFr/0w42+h3sH7L30/nmzl7e2VL28BXx3rTr5ZIyZYF/M+9KOytOYfA4Lc67sUDu11jOVUvdhHCu5P+TpmLmVVwNaKbUYYyr9vyAjjtUtR6GU/m8xIz4pwElKqZZ+vfchPQcfR9jvfaQd9TvDi9Rc/V1T370AVOUd9sc/osU1YdIKRLD3uC2mrhqKUVI6EDpyweG+w05l4pJPxVseYjHhRE8FnlNK7caYzn+KcRDn3yar7jscKl+lSqnPgP+zNl2CzepDKdUD7wBRJsZJaUQopYZj6gj7M3hea/1QpGnUMAGnigWhugM4tVZmjyCRtD2DfXvtZbQwjJm6m4jquhrC/nyqPGh6hAhZl1h8gFfpv4TKSn+4b6/9PpyAd/pOpPiX0dsw3x93OgozcNQfMyW9QCk1DWPS/7VlOVCnHHVKv2US+Da+vf2HMAp/2B6qAOmdhDEZtIfbeQe4XmsdymzfbsYUaWVkbyjuCyoVOTvxKv21XiFaH9t/KKXexPT298U4XNkFLNC+oaXa25btlcgVBA5XaCceE67Ln0g7Suw9/clBpYKglLoVM1cnVGNnLWau27VVTd+PUOeIlEg7neoT9ncp0ooy6Hxg8Ixo/QfTIxuMEkwIm3h8zRUDYlnwXGTN9ToT8144MXMjJ2utd1rntlukhPzohqmXwnG45a1SWVNK9cNMNxoQ4riDmIb9cMK//27CjthprZ+zRgXvxUz5sI8mKYzPk8GYMJ7vYuJ82xtcNV6OtNYlSqkvMJZYDkx5egk8nSN2c+HjWemv8XsPNV9/19B3z5+6fIeh8pSBBMw83usJHBYLvGH8cqnsvyAYkbzDqywl+l5MNIOWfiItrXxdD6xWSl2vtbaHtKuVcoRRIAIq/fgpD2FGyj0opS600o23bX5Ma/1IJMfXEv7+qmqD+tDOOZx3trbKaE1h1x8isZQ54kRiwaO1/k0p5bYc6qaU6qu1XgGglOqIaQuA8d00K0ASNdo+0lrnKxMK+gbr1yeA/HnW74BS6m6t9buHmYfD4qhS+q25Xt/gG0dyJ0bhr/I8KKsC/hDfhuLfMWEgwlXi623LbSI8pX3uVmaEx4TCblp3xExErNH2LwjicMJ6Tu2t1WJqziFJfHgRwBurHIyDsYhRSj2Fr1PIMkwIvVWYZ74G4wH8gNVQubYq6QfAXpHN0VqffJjpHS/YP5yhRuHtJAbbYY0MzsM3fvB+jGKwFvPsVwIrLTOy54hA6Xejtd6EmYoUDPvHYF2k6VYDe3l7XGv98OEkppQagPl42j92mzHvzDrrtwL4XWutlVILiVzpjwhLATjPqndOwyhmY/D6ygDTAfAHoINSaoxtzmKNliMbH+CdfnUpXieHw/Ga9M63ysXxSo3f+9qsv+vwu+eP/R3eobWO2FltIJRS0RhzU/u3JxdT963B3LdVwHKtdZE1rTJSpT8itNbZwH1KqfsxJrZnYuLHn4CvtVAvYJpSaoS7MU/tvcPzMJ2zGUA/pVRXrfXv1r4qd9wppW4D/om33aaBv2qtQzpArSfUaJk9BqmtMlpTFOJVeI+I7wRVe37IPsQ7wn8ppv3hXnbzvyA6XhHegcJTtNYzDjcz1iDNq8Cr1uDPWIwV00h8ByWbAO8opaK08dtWJxw1Sr9SKhUzB8punrsWOFNrvaMa6V2DGZ1yFzwN3KO1fiHCJNxOGmKAZkqpRlrrQ2GO6WFbXm3LSzTGpC4dY17yWoTX1MK2vCeiXB8ZRuI1bVppdwqitW5/GOk2sV6IcD2u9s6ViO+LpcDcZ9v0H0zoj2Dmb6mRph2Cg7bljkGlBH/sDnVaBZXyxX8Eyc7jeBX+PIyC+HWIzr/UCM8ZKaNsy8trOG07NV3e3sar8K8Brg4zxSq1Bs4ZEEsp+8r6oZTKwEQquAnvsx1pbZtkrdd0OXIzG6P0tQNOUEq1ser0496Bnw37vY/knoaUq6P6207Q714NY3+HWyqlEg7TLPRWvAp/OWa60Ts6eESJ1MM4V0is+naB9XtUKZWEaSBfBZxviSVhPLtPsNZr5R22Oik/xMTXBmOx84RSaiDe+dmLbB0BQVFKPYj5xrgpw4Tw/TjC/B7r1HSZPdawl9EEpVSa1dEVikjrxJrgIF6lv0UoQfDoLDpAW9zeXgqn1Ad02FkD2JX+i/B2Akfy7T2IVxHvCBy20m/H6uR/GXjZuofDrDz+EW8nz1NKqQ91FR2D1hRHhfd+ywHPT/gq/PMwcS6ro/BfgmmsugtlOXBVFRR+d+iXJbZNoZzCuEcB3KN5GtscMCut14EXMX4KxoQ7vzJe3+3Kba3N51fGK/YHSqmpSqlI5gBPsC1H4o0+UuLxdTgSjMG25apM+bgab6Ntrtb65hANRvD1AeE23a0qy23LLS0HPyFRxvP7H5RSo5RS7ap53mMduyOcgeGErWlBAZ3QWffvatumO7Tx5h/K2sf+7Cvdf6XURKXU50qp2UqpkA1Ry7TW7sW8Jt8Zf5bblkdFUnaUiThwqVLqBKVUM9v2fnhDjWrgvFAKv/UM7PfisMqtUipGKdVdKTUk0H6t9VZrFG0Qvk6A7COaVS1HrYhgbrhVdj6ybRqnlHLg9e1QjpmjfDyzHK9pcYryDXcUjFA+OWq0/j6Kvnv+rMQ7dziKCCyOlFLRSqk/KaVOVUp19Btls8+vflZr/UYIhR/C1H1VRSnVUik1RilVyZJPa12gtZ6ktb4A37Bywd7h7sqEQQ1HpA5d7cqBO9TpJUH2B0QpdRe+Cn8+xuH08aLwQ82X2WMKy6eL3d9E2G8N1XQ6XE3szjL7B5XycjFQopTaYlk9urFPFQn3HmaE2V8ttHEI63b43VEp1UMp1R1jJQTG0iuYZfhy2/LoIDI+WN+JCUqpvlYnpX1fqtVuau1/nNa6QpvIKbfhdfwLZuC3q7/8keKoUPqB9/H1qvgjcFoEPWWVUEoNxswXd19bMTBea/1R8KOCYg9VcXkY2Qvxmqn9qk0sWDt2pT1UjEk39liuq3Rkno+rSwpwJcZ0Nlj4GgAspcB+Lz6p4byEO38XvGWljMCeloNhV7gj8Zzq75wt0Ecp3GjPanynIEQSj/b/MJ1Wv2DKzdHyntYk4e7bVJvMMBUkFIqN8QT/CDXFd/Qq5LO3yri90RLouQ/GlI+TMGaqofgj3l7vhTp8+MHDwd5z3RLfUD3BeB74GHNfXrFtt78vB3ToGOtg5tzbn0G1G3HKOMMqwijzky2FOiBa6wLMN8ON3aTOHmZwnNXBHIpw9bwdu0IwDhP1we3Q6ccA34D6Rsh32JqjaZ8PH/K7ZymF54UQqen6+2j67nnQJlLLMtumSL4ZFwJvYqwl1+H7DkR836wOSnsY3MNSxJRS6zC+EabjGxElEPb48EnuThqr3nG3f2LwWgQEO2cLfENrBcVK2902G2Qd6y43FYR5zspEcLErRQeB0TpwGOh6Sy2U2UioLUub6mL/1oSr61Q4mRrGPr89lE8jN2dgLMEz8HXuaPe7VUnR9ePUyLJWLfy/vfZrCjUdx94+Ok+ZqE1BsZT8/wFfYzoMrrHt+w/G+eBvBI7a5EFr/Qu+1jBV9kVWU9S5MqGUuh7fSvxHYEJ1TIOsBp19Dn8ZME5r/WPwo0LyKd44jBcrpQJ+SJRSTTHmaG4CxZq3F8QzlVKnB5BxpzcMuN226e+RZbfaTMfrM2CkUsrfGYWd1/DOCfqhOr4WwvAXpVSHQDusnmC7UvKdjsxLqhu7OU2voFJ4rEUm+G0OFLO4PNR+ywT0ddumW6znG+y87TAOj9y8e5iO3Y5Wwt23bXjjqDqAl4KNWiszX/+ZQPss/M2ogj57yyTrv/j6AQn03O11yi0h8paB7whWxNZG1UFrvRrfeLcvK+PAMCBWo9Ueoss+18x+35qG+kBadeC//DaHi/EdiuW28zfF17FWIOyjFx5zXK31HLxWAMnAk8ESsHrr7w+23x+t9Xq8lkajMQqkm+PBtD/kO2xhr/vutuq3YDyOr8Ndf2q6/j6avnv+/Me2fJ4y/okCopRKwUS4cPOV34BJxPcN4+zPbv57OO8w+HYy3BrG8sj+Dm/0s8Syt6mesK45GC9Rtamr7ndVYSwx3SOUP+kQIUGtDoK38FpD5ABjtNZLgh1Tz6nJMhsJkdQ/RxJ7XXeNUirUSP7N1GC46Qj4AK/fgV5KqT8GE7QG1nzmx9uWN9iWz1LGwjlQGk2Ae6qZ10j4FG/dfS7eut6JGcAIxgd4Oy7igTdCDShgvknu9lMhvtZ79rrtMqsNFBBlLLfTbJs2BBGtfbTWdfbD9LTnYExHNaax1vAw0nvElpYG/q8G8vicLb2DwOl++zOApTaZVUBUgHSiMCY2brkcjLmsv9zFGCc7brmZgKpintvb70OEx7zj9xz6+e1vAnxmkykCutZQOdB+v63AID+ZRhjLC7dMCdAjQFrv2mQm+u27x+88f/a/t9Z5nsBUHv75ahLgfM/a9r8W5PoaATtscnnApQHkRmB8Sbjl9gGNq3gvJ9qOf7cmns/hlD1gVBC5T20y9wWR6Y35sLvl3gdS/GQ6Y8w//Z/VKD+5tbZ924OUnX4Yhdk/rckBZNMw9YFb5r/41V3W89xuk5leE+9ruGeMcSZnv2/rArxPDoyTswKb3Aw/meZ+78FP/uXRSmccxuGq/327K0DeMsOVDZvsv2yyBZjRWP/3NRqjyLvlSoGWfjJn+eXrOSDeT2YgJk6z/zW0D5PH22yyFdZ/NhBXU+/QkX6HrTzMDFXGAtzX1UB0ABmFaRy55TYDg/1k4jCddv73/l0/udqov9+x7T+s757fPbv2cJ4xRomxtyvKMHPzo/zkemMc8rnliv3zh7GGc+/PBU4McL5OGD8Y/vdsdQDZieHKhk12EGZE1i3/BtAogNzJmBCIbrk7/fYnYNoF7v2LgS5+MskYK0//a5gYJo+Nrftrf4c1cEmY4+xlx4VxOH3E39UgebvWlreZYWTfrcK9yrTJtq+tMmvJhayHMb5c3PunBMnvKJtM5uGU5QDXPyrAfnu7Zj+V9QUH8Be/chb2GdVQmXjM79ncBDj8ZPpj6mi33P/89rfD932eTOU22SBMXer/HvqXl/b2/dW4nq+sY+11/Y8RHHe3X76+oXKboSG+up8GHvaTScD4cnDvnwd0C3C+tvi2Ub+r7Wcd6lfXjvxuwjeEwj7g+SpMYZ6itZ4EnlH+22z7ioEBSqnXqpCfW7SZf2/nMYyn2d6YBsVPysSGXoNpFI/Ba9ZfAFyhA4zMahOv9kJMwWiCue6vLPO3xZjG6xB8nW+tAy7SVsmpZe7DmN+1wpgDLlZK/QZswcxxHYnXu74TuEZH4OCmGuRhKoOF1vk3YD7KY/B6RdXATbrqoy1vAndhRg7BeFv/i1JqJaYXrw3G8YbdUsSF97qbUjk2s73H7v+s3v8DmCke/wXQWh9SSl2EUZqSMRXKx0qppzGmhU6MLwP7SEcpcJmuvybC9vv2qFKqP6ZB/bXW+lsAbUI93YvX0uUqzAjCL5h7nIExr4/CG/7GXUb856w+hXdEpw2wSin1K6YhmYiJtWrveXfHYQdvefGgtc5WSt1uS/M6jPn4AkyHXk98n+cmjpA5n9b6V6XUXzBKs8Jc2yKl1FJMvdUAE36vve2w7fiOVKO13qOUegevl/rTga3We7kbU4/1x3cef8j7VkUexvTit7Xy/AnwtFJqDeZj2wjja8Uee/d+beZX2q/jR6XUvzANUDAf/euUUjMxvf7dMHHLFeYbZE8v1NxnMKMKf8fU325T6C90HTnpOcLY3+GewDyl1CogR2t9F5iWnDJOdd3fvQ7AAmWiPKzD1IWj8I6m2O+//72vjfr7aPnu+aBNBJGLMOFDW2DaGC8DDyil5mLqyk6Ycmv3Fn9DgPw9g2nDKMz3Z65SahGmgznKSsc+B7nG3mGt9WKl1L/xvnvXA5daddE2K++98foOAfNNfNUvnWKl1JUYU/AEK79rrXuxBVN+RuOdRhWqHPnn8aBS6kdMXeN+h/OBb4Mdo5Rqg29Y6QOYb1Oo6Sl2crXW94YXO3ao4TIbCfb65wyl1HTM93yT1jqU5V9tciumbHbE1Hc/WfXTckynyEl4v5cRl9Ea4lFMtIzTMM/mVcyzmYepP7ti6k+3AvY7vjoVWuttSqn38Zq5nw1kKhNWNw/TjnXXJSsw3+mgVs2HyQeY6WD2kfpIIm28gMmje0rXuRjr67mYdlBzjC5mtzr7CT8rQatOuhkzLUlhBlvWWPrhFowO2gHTRnHr2geAOyO8vtqhLnscMI7y/HuDqvJ7xpbWuMNMS+M3+mNLuxmmIgt17G4C9KAHSKsLZu5TuLx8A6RX8762t6dVheO6Y8L3hLvOM2u4HNjTPwPzwgQ7fzamIyRYWu/aZCcG2D8U3965YL8NluwM27ZrA6SXjGm8+B//QwDZXvhaewT7bQNOrua9nGhL5906eKfb+13LqCBybfG1aHH/Xg0geyfGsiPY/dqHGSmyW1MMDpDOY/j2Ugf7fWg9K/d6McHrhhsxHTSh0vsJaFpT72ukzxgzZ3JfBNc7B2gTJI0EzFzFcGmUYBSoa23bZgZILzNc2fCT74BpMIU7fz5wW4h0FEY5DzQC7P5twSgg9m1Bn5st7cl+x1Tr3a1ueail93hmhGVsUoD7WEDlEfj++Fox+f9cGKupx23bXglwvhqtv600a+S7Rw2O9NvkWmP8IoS73gPABSHSuQHvaHao3xRM3Wyv09r7pTUxkrJhk3dglL9I6t6vCWHdhpknnBXi+DKMovKBbdvdEeTxQr903g4jf2sE1xLqt6eW399rbeeaGUb2XZvsxDCymcHKRS2UWR3qXBhFanGAdNfaZEbZtmcGSKOqZdl+/aNCvNuB8mX/fYBpO7jXv6/N8mDLWyxmqlKo76DG1GUtgqSRQOVvnv/P3fHzRbBnyOGP9Mfia22ZDzSI8FgH5lsTru2mMdZJQS33MB0g+RGkswI/S7K6+NXtyU3v0uFUnHal399kozq/gA17K32F6Rn6BmPKWoYZ0ZuPaeymVuG63V6eP8MoeMWYXrL1GDPhUw7zvlb7ZbJe6D9bL/1BTA/kAYxTuduB5FooBz6VOyZkz4MYBbnA+i0CHiCAaaBfWu/a0poYRKYpprJfZD3DCowCut56JtcAMZbsXbb0ZgRJrxXG1G8nphLZQxATHtuz/wgz+ptvHbMbM0/8BiKsuIKkP9GW33eP1LscrOwRQrHDhLj83LpfZRiHT8GmSHTBKG1rrGdViDEpfgKrkYgxp3Oft3OQdIZhpglstt67Uuu4+ZiR8cE22VW29K4OcR0dMfNI11r5KsE0Dv5HBCaf/vesJp+x9S7dgjHx3WFdcxFGwf0Y01kacvoQ3rpvMqbBXWal43bQ9ShWpwGml9w9taACyPBLKzOSsuF3TDTGSuJz67kVWHnYjWlc3IefeV6ItAZiGj0brHTyMJ3P92IsPhr4ld/YCNK8xCafGe5+1nR5qI0fkSv9cZjOtN+tMpFtvTeVOqwx35ZbrLT3WO/eLus9GWbJPG8775NBzlmj9bctb4f13aMWlH6b/OmY+ePrrWsuw3TozbCuMeR30UqjJ2be9XpMPVVuXetSK+1TbbL2Rr2/WevESMpGgPP3w0QwWgwcss6fjanTXyXCzjLM1Kp7MXX2fqscZWIsQXpaMp/b8nh9BGnGWXlxHzMmjPwr+NYTVf3VW6W/psqs3/0KeC6MRcpLmBH+Esw7uxjLbJ06UPotuShMPfQjpo4rxXRWfgOcZcn82ZbWR7VZHgLkr69131bZns0uzBTa84jgG4YZIf8Sb7s3C+OA+Srb/a81pd9K4z+2NN6vxvFtMe2XX63nU4ZpE6zEvOMDIkynJUY/mWmlU4ppX2zGTPm4lADT3+rip6wMC0KdoZSyF8IMrXVmXeVFODaxnLGU4jWjaqiNV3dBiBgrSsQ2a/Wg1rpJXebneEMp9TbwB2v1Vq31v+syP8KxiVJqBt6QXOO01pPrMj+C4I9S6mG8DsD/rq0pUYJQm9T1nH5BEIRKWCGy7sD0lK7VWs8Lc8gQvPXZNlH4BQBl4vdegSlHy7XWy8IcMty2vLrWMnacYPm9iMJYlszQIaKtWJ7d7ZFN5P4LACilJmKsAzYD07TWZSFkEzBWBW6kHAm1jlLqaoxJ+2ZgttZ6X5hD5FsjHHFE6RcE4WikFOOtWwEVSqmWOkj4JEtZeMC26ecjkD/h2CAGb9k4YJWjgE6TlFKx+IYZknJ0+IzEmIuC6cT7ZwjZCzBOFcFMe1oQQlY4vjgXr2PU8zFz/4PxZ7zhsTaJ5aBwhOiHN177y/iG3fZBKTUYr4M7jZkmJwi1Tqj4hIIgCHWC1joXb6M/GvjEMr32wbIIeAc4x9rkxHxwBQHMCIrbm38T4D0rhrAPVhzdSXgVi3zMfFTh8PjJtjxRKXWWv4BSKsryzP6+bfPrWutif1nhuMVejv6llBrqL6CUildK/RXjENLNi7WdMUGwsJfRm5RSVymlouwCynAWZq6/20v+l1rrHUcqk8LxjczpF+ocmdN/ZFFKDcMbcqVG0FrfWJPpASilRmJ6wN0fTifGeZN7znVrjIfuONth92itn6/pvAjHLpZC+YFtUwkmdvxOjAfgtpjpIe5y5gIu11p/eiTzWVWqGI42Et7TWv9WkwkqpeIwjhLt4TA3YpxeZmPC4vXBN+zjYoxTN1H6BQCUUo0xDv/SbZtXYcpSPsaR1gC8oR8BvgMmaK1dRyqfVcUKZzksrGDkbNBa/6MG0xOqgFJqGibChJsdGKdw+zAOSHtgItK42Qqc4J4KcKy0zYRjF1H6hTpHlP4ji1LqWszoeI2htVbhpaqOUupcTESLcA7VCoC/aq1ldFaohFLqeuAfmGgGodgH/Elr/V3t5+rw8Ks3a4I/aK3freE0UUo1x3gwPjkC8c8w3taDzv0Xjk+UUl0w3sB7hxHVGM/bdwSbynO0oJR6l5pV8mZprUfVYHpCFVBKJWGiIVwQgfgM4EqtdZbt+Gs5RtpmwrGJzOkXBOGoRWv9rVKqEyYMzNmYUcHGmKlJ7nBPUzBxlQ/UWUaFoxqt9ZtKqe8woaxOx4y4pGFMLPdhRg0nY0a7xQlkDaK13gOMVEqdiQldNARogwmRWIhx8jcPc+8X1llGhaMarfUGpVR/jI+IC4FBGMdpcZjR/k2YkFlva63X1VU+heMX69txoVJqOKbNMhxoh+lsLgG2Y6wV/6e1Fp8xwhFHRvoFQRAEQRAEQRAEoZ4ijvwEQRAEQRAEQRAEoZ4iSr8gCIIgCIIgCIIg1FNE6RcEQRAEQRAEQRCEeooo/YIgCIIgCIIgCIJQTxGlXxAEQRAEQRAEQRDqKaL0C4IgCIIgCIIgCEI9RZR+QRAEQRAEQRAEQainiNIvCIIgCIIgCIIgCPUUUfoFQRAEQRAEQRAEoZ4iSr8gCIIgCIIgCIIg1FNE6RcEQRAEQRAEQRCEeooo/YIgCIIgCIIgCIJQTxGlXxAEQRAEQRAEQRDqKaL0C4IgCIIgCIIgCEI9RZR+QRAEQRAEQRAEQainRNd1BgShqiilUoCRtk07gLI6yo4gCIIgCIJQ/4kF2tjWZ2mtc+sqM4JQFUTpF45FRgLf1HUmBEEQBEEQhOOW8cC3dZ0JQYgEMe8XBEEQBEEQBEEQhHqKKP2CIAiCIAiCIAiCUE8R837hWGSHfWXSpEl06tSprvIiCIIgCIIg1HM2bdrEhAkT7Jt2BBEVhKMOUfqFYxEfp32dOnWiZ8+edZUXQRAEQRAE4fhDnEgLxwxi3i8IgiAIgiAIgiAI9RRR+gVBEARBEARBEAShniJKvyAIgiAIgiAIgiDUU0TpFwRBEARBEARBEIR6iij9giAIgiAIgiAIglBPEaVfEARBEARBEARBEOopovQLgiAIgiAIgiAIQj0luq4zIAiCIAiCIAiC4WDxQV5d/ipKKW7tfyspcSl1nSVBEI5xROkXBEEQBEEQhKOAnJIc/jT1T2zK2QTA1tytvHHaG0Q5ouo4Z4IgHMuIeb8gCIIgCIIg1DEFZQXc+PONHoUfYOGehbyx6o06zJUgCPUBUfoFQRAEQRAEoQ4prijmlhm3sObgmkr7XlvxGov2LKqDXAmCUF8QpV8QBEEQBEEQ6ohyZzl3zLyDJXuXeLZ1TOlItMPMwnVpF/fNvo/skuy6yqIgCMc4ovQLgiAIgiAIQh3gdDm5b859zN0117OtY0pH3jnzHf4y4C+ebfuK9/HgvAfRWtdBLgVBONYRpV8QBEEQBEEQjjAu7WLibxOZum2qZ1vrpNa8cfobpMWncXWPqzm59cmefbN3zub9te/XRVYFQTjGEaVfEARBEARBEI4gWmueX/Q8kzZN8mxrltCMN09/k2aJzQBQSvHEiU941gFeXPoiqw+sPtLZFQThGEeUfkEQBEEQBEE4gry64lU+XPehZz0tLo03Tn+D1g1b+8ilxafx3MnP4VCmyV7hquCuWXeRX5Z/RPMrCMKxjSj9giAIgiAIgnCEeG/Ne7y24jXPelJMEq+d9hodUzsGlB+YPpCb+t7kWd9VsItHf3tU5vcLghAxovQLgiAIgiAIwhHg8w2f88LiFzzr8VHxvHLKK/Ro3CPkcdf3vp6hzYd61n/K/IkvN35Za/kUBKF+IUq/IAiCIAiCINQy07dN5/HfHvesRzuieXH0iwxIHxD22ChHFE+f9DSN4ht5tj2z8Bk2Zm+slbwKglC/EKVfEARBEARBEGoRp8vJs4ueRWNM8h3KwfMnP8+JrU6MOI2miU15csSTnvVSZyl3z7qb4oriGs+vIAj1C1H6BUEQBEEQBKEWWZC1gKzCLM/6A0Mf4NR2p1Y5nRGtRvCHXn/wrG/O3cwzC5+pkTwKglB/EaVfEARBEARBEGqRrzd97VlumtCU8zufX+20bu1/K32a9vGsf7XxK6ZsnXJY+RMEoX4jSr8gCIIgCIIg1BK5pblM3z7dsz6u4ziiHdHVTi/GEcNzJz9Hw9iGnm32aACCIAj+iNIvCIIgCIIgCLXE91u+p9xV7lmf0GnCYafZKqkVdwy8w7O+OXczB4oPHHa6giDUT0TpFwRBEARBEIRaYtKmSZ7l/s36k5GSUSPpntz6ZJ/1xXsW10i6giDUP0TpFwRBEARBEIRaYP2h9aw7tM6zfl6n82os7WaJzWif3N6zvmjPohpLWxCE+oUo/YIgCIIgCIJQC9hH+ROiEzi9/ek1mv6g5oM8y4v2itIvCEJgROkXBEEQBEEQhBqmzFnG5C2TPetntD+DBjENavQcg9MHe5a35m6Vef2CIARElH5BEARBEARBqGF+2fELuaW5nvWaNO13Yx/pB5nXLwhCYETpFwRBEARBEIQa5utNX3uW2yW3o3+z/jV+DpnXLwhCJIjSLwiCIAiCIAg1yJ7CPfy661fP+oROE1BK1cq5ZF6/IAjhEKX/GEAp1VUpVaKU2hlGrrVSSkf4+1OIdIYqpT5TSu1WSpUppXYppb5SSp1S81cnCIIgCIJQv/h287doNAAO5eDcjufW2rmGNB/iWZZ5/YIgBEKU/qMcpVQc8DYQF4F43xo4353Ar8BFQAsgBmgJnAf8rJR67nDPIQiCIAiCUF9xaRdfb/Sa9o9oNYJmic1q7XyD0mVevyAIoYmu6wwIwVFKRQOfAsMjPMSt9BdHcMz2AOebALxgrW4EngR+BzoD9wE9gLuVUtu01q9EmCdBEARBEITjhiV7l7CzwGucOaHThFo9X9PEprRPbk9mXiZg5vWfmXFmrZ5TEIRjC1H6j1KUUk2AT4CqmNS7lf5VWuvlVTxfHPCytboZGKq1zrbW5yulvgJmAQOBJ5VS/7PtFwRBEARBEIBJmyZ5ltPi0hjVelStn3Nw88FepV/m9QuC4IeY9x+FKKXOBpbgVfhdER7qVvpXVOO05wFtrOUH/BV6rXUhcIO1mgJcV41zCIIgCIIg1FsKygqYmjnVs352h7OJiYqp9fMObj7Ysyzz+gVB8EeU/qMMpdSnwGSgLaCBJ4A5ERyXiDHDB1hejVNPsP6LgK8DCWitlwBrrNXzq3EOQRAEQRCEesuUzCmUOEs86+d1Pu+InFfm9QuCEApR+o8+hlr/mcBpWuuHIjyuF97nWZ2RfrcPgAVa67IQcnOt/yFKqYRqnEcQBEEQBKFe8vUm77hJz8Y96ZLW5Yic1z2v382iPWLiLwiCF1H6jz52A/cA3bTW06twXD/rXwPZSqnnlFJrrFB/OUqpeUqpm5VSlWzMlFIN8Jr2bwpznq3WfzTQqQr5EwRBEARBqLdsztnMyv0rPevndToyo/xu7Cb+Mq9fEAQ74sjv6GOE1jrSOfx23PP5ncBiwD4KH4cZyR8O/EkpdY7Werdtf0vbciWv/n7s8jtuVTXy6kEp1QxoWsXDOh7OOQVBEARBEGoauwO/uKg4zupw1hE9/+Dmg/l8w+eAd15/k4QmRzQPgiAcnYjSf5RRTYUfvEp/NFAG/BOYAuRhTP9vA3oD/YGflFJDtdZF1jFptnQKwpyn0LacUs282rkZeKQG0hEEQRAEQagTyl3lfLv5W8/6KW1PITk2+YjmIdC8fgndJwgCiHl/vUAppYA+1up+TLi9O7TWU7XW87XWbwGDAPfXqBfwN1sScbblEkJTHOQ4QRAEQRCE45I5O+dwqOSQZ/1IOfCzI/P6BUEIhij99QCttQa6AScBI7XWqwPIlAFXA7nWpj8rpaKsZbt1gQ5zOmVbrq5VgiAIgiAIQr3B7sCvZYOWDGk+pE7yIfP6BUEIhJj31xOsOfq7w8jkKqW+BK4DUjGm/ovxNemPD3Mq+/7Sque0Eq8Cn1fxmI7ANzVwbkEQBEEQhMPiQPEB5uz0Rlee0GkCDlU342oyr18QhECI0n/8sdK23Baj9OfbtjUIc7x9f/bhZkZrvQ/YV5VjzGwGQRAEQRCEuue7zd/h1E4AFIrxncbXWV5kXr8gCIEQ8/7jjyLbcqz1vxPj9R+gVZjj7ftDWhYIgiAIgiDUZ7TWPqb9Q1oMoWVSyxBH1C7+8/oX7llYZ3kRBOHoQZT+eoBSqo1S6lyl1J+UUq3DiNvD4+0Dz3z/Lda2cOHwOlj/5cCmKmdWEARBEAShnrAxZyNbc7d61id0mlB3mbHwmdcvzvwEQUCU/vrCqZg57m8CZ4eRHW79a2Cpbbu7K/gEpUJORBth/S/WWpdXNaOCIAiCIAj1hRnbZ3iWYx2xjGkzpg5zY7Ar/Zl5mewv2l+HuREE4WhAlP76wRzb8uXBhJRSnQH3xK5pWusc2+6vrP8UYEKQ4wcBPazVSdXIpyAIgiAIQr3BrvQPbzmcxJjEOsyNodK8/r2L6ygngiAcLYjSXw/QWm8CplurJyul/ugvo5RKBT4BojCj/E/4ifwAbLeW/66USvc7vgHwH2u1AHinRjIvCIIgCIJwDLKrYBfrDq3zrI9pW/ej/FB5Xr+Y+AuCIEp//eE2vF7431RKvaWUOk0pdYJS6s/ACmCAtf8FrbXdOgCtdQlwh7XaHliklPo/6/grgAWAu+v4Aa212IoJgiAIgnDc8sv2XzzLDuVgZJuRdZgbX2RevyAIdkTprydordcC5wD7AQX8EZgK/Ab8GxOeTwMvAPcGSeNL4G7ABbQBXreO/xDoaYm9qLV+udYuRBAEQRAE4Rhg+vbpnuUBzQbQKL5RHebGF5nXLwiCHVH66xFa69lAd+ARYAlm5L8UyATeBYZpre/WWusQabwADAM+BnZhvPQfxJj/n6W1/mstXoIgCIIgCMJRT3ZJNkv3ef0hn9L2lDrMTWVkXr8gCHai6zoDQni01qOqIHsQeMz6Vfd8CwnhEFAQBEEQBOF4ZuaOmbi0y7M+uu3oustMANzz+jPzMgFj4n9Wxll1mylBEOoMGekXBEEQBEEQhCpg99rfvVF3WiW1iug4Z34+uqystrLlg8zrFwTBjSj9giAIgiAIghAhReVF/Lr7V896pKP8B995lw0nDOP3oSew+8EHKV65khAzLg8bmdcvCIIbUfoFQRAEQRAEIULm7Z5Hmcs7Wh/JfP78GTPY9+yz4HSii4vJ/eJLMi++hK0TzuPQRx/hzMur8XzKvH5BENyI0i8IgiAIgiAIEWL32t+mYRs6p3YOKV+WmcnuewIGTqL099/Z+/gTbDx5JLvv/xtFy5bV2Oi/e16/GzHxF4TjF1H6BUEQBEEQBCECyl3lzN4x27M+ps0YlFJB5V1FRey89TZcBQWebUmnnIIjKclHTpeUkPv112y77HK2njueQx98iDM397DzO6T5EM+yKP2CcPwiSr8gCIIgCIIgRMCiPYvIL8/3rJ/SLrhpv9aarIcfoXTjRs+21Esvoc0r/6bz7Fm0eOopEvr1q3Rc6caN7H3ySTaNOYXChQsPK78yr18QBBClXxAEQRAEQRAiwu61v3F8Y/o06RNUNvvDj8ibPNmzHt+3D+l/+xsAjsREUs8/j/affEzGN9+QduWVOJKTfY53FRay/58vHlZ+BzWXef2CIIjSLwiCIAiCIAhhcWkXv2z/xbM+qs0oohxRAWWLlixh77PPetajGjWi9Usv4YiNrSQb37ULzR98gM6zZ9Hy2WeI7+PtSChetoySdeuqnecmCU3ISMnwrIuJvyAcn0TXdQYEQRAEobbQLhclhQUU5mRTlJtDYW4ORTk5FOZmU5STQ0lhPilN08kYMJjW3XsRHRNT11kWBOEoZfWB1ewr3udZD+a1v3zfPnb+5S9QUWE2OBy0+sffiWnePGT6jvh4UsaPJ2nMGDaePBJdXAxA9sef0OKxR6ud78Hpg9mauxUQpV8QjldE6RcEQRDqDYU52ayY9iNbly2i4NBBivJycTmdYY9b+uO3xMQn0K53PzoMGExG/0EkpTU6AjkWBOFYwW7a3yCmAUNbDK0ko8vL2XXHHTj3H/Bsa3bnHTQ44YSIzxPVsCEp48aR89lnAOR+9x3N7r6LqIYNq5XvQc0H8dkGk1ZmXia5pbmkxKVUKy1BEI5NROkXBEEQjnn2bNrA0inf8fuvc3A5K6qVRnlJMZsW/camRb8BkN6hExn9B9NhwCCad+iMcsiMOEE4nrGH6jup1UnERlU21d/3wgsUL17iWW942mk0uu66Kp8r7bJLPUq/Li4md9I3NLrqymrkGno07uGzvjF7Y6W5/oIg1G9E6RcEQRCOSZwVFWxcMI+lU74ja8P6yA5SioSGyTRISSUxNY3Y+AR2b1hHUW5OJdG9Wzaxd8sm5n/5MYkpqXQeMpxhF15Gg9S0mr0QQRCOerbkbCEzL9OzHsi0P3fy9xx6733PemyHDrR4+qmQIf2CEd+9Own9+1O8bBkA2R9/TNqVV1QrrdZJrYmPiqfEWQLAxhxR+gXheEOUfkEQBOGYoigvl5U/T2HF1O8pyD4UUCaj/yDa9OhNYkqqR8FvkJpGQsNkHFG+jre0y8XeLZvYvHQRW5ctYu+WTZXPmZvDimk/sH7eLE66/Br6nHKmjPwLwnHEjB1e0/4YRwwjWo3w2V+yYQNZDz3kWXckJtL6Xy8TlZRU7XOmXX6ZR+kv27KFogULaXBC5SkF4YhyRNEptROrD64GYEP2hmrnSRCEYxNR+gVBEIRjggPbM1n8/STWz5uFs7y80v7YhAR6jTqNfmecTVqLVhGnqxwOmnfqQvNOXTjx4isoyD7E1uWL2bJkEdtWLae8pNgjW1pUyM9vvcqamdM59fo/06x9hxq5NkEQjm6mb/Oa9g9tMZSkWK8y78zPZ9ett3kc7wG0eOpJ4jp2PKxzNjzjDKKeehpndjZgRvuro/QDdE7r7FH6N2ZvPKx8CYJw7CFKvyAIgnBUU1pYyM9vv8v6eVNA60r7E1Oa0WHQqXQcdDJJqQ3ROprCnFISk2NRjqqbwialNaL36NPpPfp0KsrL2bVuDSunT2HD/LkemaxNv/Ph/X9hwNjxDL/ocmLjEw7rGgVBOHrZU7jHozBDZdP+rAcfomzbNs96oz/8geQzzzzs8zpiY0m98EIOvvkmAPk//0z53n3EpDerclqd0zp7ljflbMKlXTiUWCsJwvGCKP2CIAjCUUd5qZPtaw+yYuovZK6YhHbmV5JxRLcjKr4/TpXBpqWKTUt9TVZj4qJo0jqJxq2TaNI6iSatG9KoVQNiYgPH1Q5EdEwM7fr0o12ffmQuX8LPb/+H3L17ADMtYMnkr9kwfy6nXHcjHQdWbwROEISjk6K8MvZuzeVX10zPNoViVJtRnvXiNWvI/+knz3rikCE0u/OOGstD6iWXcPCtt0yHp9NJzuef0/SWP1c5nS5pXTzLheWF7C7YTeuGrWssn4IgHN2I0i8IgiAcFRRkl5C56iCZKw+wfc1WSvOm46rY6iflICquN1Fx/XFEhQ6pV17qJGtzLlmbcz3blIKUZok0aWM6Ahq3SiI9I5mEpMpeuP1p328g17zwCgu++pRF337liRKQf2A/k557nE6DhzHmDzfQsHGTKl+7IAhHD1pr1v+2hzmfbqC81ElFTCo9Wp/I2vRf6ZfejyYJ3nf80NvveJZVYiKt/v4CKrrmmtexrVuRNHIkBTNnApDz2Wc0ueH/UDExVUrHPtIPxsRflH5BOH4QpV8QBEGoM8pLnayauZONi/dyYEcBWjtxliyhomQ+4Bt6Lyq2DW36XEBcQlPKiisoLa6gzP0rcUZ0Pq0hZ28ROXuL2LR4n2d7kzZJtO7WiNbd0mjZKZWYuMDWADGxcYy49Gq6jxjFtDdfYdf6NZ59mxb9xrZVyznx4ivpf9Y5OByRWxQIgnB0UFJYzsyPfmfzUm/9EF0ey8lbL6br/iG0bx/v2V6+axd5U6Z41tMuupDopk1rPE9pl1/mUfor9u0jf8YvRI0aw5yN+5n5+37KnC7uPL0rrVKDTzNqFN+IxvGNOVhyEDDO/Ea3HV3jeRUE4ehElH5BEAThiKNdmt8X7GH+pM0U5pYB4CrfSXnRz2iXr0f+6LgkBpx1BcMuHEt0TGBFWrs0ZaVOTydAUV4ZB3cVcHBnAft3FpCdVYjLWdkfgJsDOwo4sKOA5dO244hSpGck06Z7I1p3TaNZRjJRUb5zXxu3bssljzzN6lk/M/vDdygpMNMPykuKmfn+m+xYu4qzb7+bmNi4w7lNgiAcQXb9ns3P766lILs04P70gvYUfwpz929kyLgMst9/H5xWh2NUFI2uvrpW8tVgxAhi2rShfMcOAOb9/XVun+2kzOnyyKzcmcuPt59ETFTwefpd0rrwW9ZvgAnbJwjC8YMo/YIgCMIRZdfv2cz7chP7txtFWbuKqCieg7NsTSXZ3qecwUmXX0tCUsOQaSqHIi4hmrgE81lr3AradPea/zsrXGTvKeLAznwO7DQK/sGdBZQUVo4C4HJqsjblkrUpl4XfbSUmLoqWnVNp36cJ3YY193Q8KIeD3qNPp+PAocz+8G3WzPJ69968eD5fPvkwE+55iPgG1Q/ZJQhC7eOscLHwu60snboNbH2DCQ1j2N5hObHr00kptUz6NayYvoNNi/bQYcnvNAEUkHzmmcS0ijxqSCS4XJpVu3KZvm4vFa2HMs5S+ttvX0t65yx2NEz3yG7aV8DHC7dz9bD2QdPrnNbZq/SLB39BOK5QOoAnZEE4mlFK9QQ8bnRXr15Nz5496zBHgiAEQmuNKzeX8n37qNi3n0Nb9rN0jYNduV4l2FWxi7KCb0EX+xybgoOByc1Ib9yUqJQUHCnJRCWnEJWWSmy79sRltMfRoMFh5y//YAk7f89m5/psdv6eTXFeWchjktLiGDIug65Dm+PwG1HbsWYlP77yT/IP7vdsa9q2Pef/7TGS0kL7HxAEoW7I3lPItLfXejoh3bTt2YjhV2Rw5g+nUl7mZMCu0xiYdTq4fCOCND64mi4bP6P7R6+TUENtkcLSCv45bQPfrtjNvnxjddCwrJAPpzxOrMtMe5rUYQSv95lAtENR4TJt+dTEGGbdNZqUxMDz/b/Z9A0PznsQgCgVxYIrFhAXJdZIkbJmzRp69epl39RLa125t1oQjkJE6ReOOUTpF4SjF2dBIYXz5lEwYwYFs2fjzM6mPDqRzHZnsbPVSLRtnruzbDPlhZMB73z8KKeLznsO0f5ALuGCSUW3aEFcRgaxHTsS1yGD2A7mP6pJE5Sqeqg+rTWHsgpNB8D6bHZvyA7qKyCteSInTOhIRl/fc+Ud2M9XTz/CwZ3bPduSm6Zz4QOPkdaiZkcBBUGoPlpr1s7dzdzPN1JR5jWTj4p2MPyCjvQe1ZpfdvzC7b/c7tn3ztD/sfOHcnZtyPFJy6ErGHJeF/qd2pao6MMLg+d0aa55eyFzNx2otO+OJZ9w2o7FAFTEJxI36Ud2l8K17yzyyPxxRAYPndMjYNprD67lksmXeNY/O+czujfuflj5PZ4QpV84lhHzfkEQBOGwKN+7l4JffiF/xgyKfpuPLjcm8y4Vxa5Wo9jafiwVMb6j8rp4KeXFM41drEV6biE9du0noTwyp3wVWVlUZGVR+OuvPtsdycnEZWSQMHAgSSefROKAAajY8N75lVI0bplE45ZJ9B3TBpfTxb5t+excn83mZfs4sKPAI5u9p4gfX1tFekYywyZ0pFXXNACSmzTlkkef5etnHyVrw3oA8vbv5eOH7+GC+x8lvUOniK5NEITao6SgnF8+XM+W5ft9tjdu1YDTrutJ41bGGmnG9hmefS0btGRg114M7ArL/j2ZxctclMeaaUcuFc38SVvYtGQf597eL6JoIMF4YervlRT+BrFRnNS5KR0HXAMPG6U/uqSIpgtn0uXiixnZpSmzNphref+3TK48oR0ZTSpbQnVI6YBDOXBp08mxIXuDKP2CcJwgI/3CMYeM9AtC3aK1pnT9evJnzKBgxi+UrPEd6NDA/iZ92dxhPMWJ6b4Hu5wkFf3AgXLf+aQDBgylX8ceuPLycOblmv+cXJx5eeaXm4MrNw9nbq5xwV8FHImJJA4fRtJJJ5N08knEtGhRrWvevHQ/87/ZTO6+4kr72/ZsxAnjO9K0rVECyktL+O6fz7B12WKPTEx8AuPveoB2vftV+fyCINQMRXllfPHMYvIPlfhs7zumDSec18Hjs6PCVcHoz0aTU5oDwJXdr+TeIfeiXS62nHsuhZlZbO4wnt0tR/ik07RtQyb8tT+xCVUfV/txVRY3fbTUs962USKPT+jFCR0aERcdhdaazAsv8tS5cd27k/HVl2zaV8CZL83BaZn5n9YjnTevHhTwHOdOOpetuSYU6jU9ruGuwXdVOZ/HKzLSLxzLyEi/IAiCEBHlu3eT88WX5E6aRPnu3QFlcpMz2NTxPHJTOlba17ZnGtGOX1k726bwK8Wpf7yJvqeNjSgPrtJSyjK3UbZlM6VbtlC2Zav537oVXVIS+JiiIgp+nk7Bz8bRXlznTjSwOgCqYgXQaWAzMvo1Yf2vWSyavNUTdQBg+5pDbF9ziM6DmjHk3A6kNktk/F0PMvX1l1k724wWlpcU8/UzEznrlrvoOmxEsFMJglCLLP4h00fhT0yO5ZRrutO2Z2MfuYVZCz0KP8CYtmMAKJg9m7JNm4kBum34mF4T+rF4ZzqHdhcCsH97Pt+/upJxt/YlOjbysJ2b9uVz1+crPOvxMQ5ev2og3Vske7YppUi7/DKyHjDz8kvXraN4+XI69+/P5UPa8sH8bQBMW7uXXzcfYHjHJpXO0zm1s0fpFw/+gnD8IEq/IAiCEBRdUUHB7NnkfPoZBXPmgMsVUK4osRmZ/a9mT0xGpX2NWzXghAkZrPnlPdbOnuXZHhUdzdhb76LLCZErwI64OOK7diG+axfffLpclO/OomzrFsq2bKF49RoK587FmZ1dKY3SjZso3biJQ2+/jSMxkYannUrjG24krkPlvPsTFeWg50mt6DK0Oat+2cnSn7ZRWlTh2b9x8T42L91Pv9PbMvjs9px5019ITEll8XdfAeCsqGDyS89SnJdLvzPOjvi6BUE4fApzSlk719th2bJzKmf+Xy8SGlbu+Ptuy3ee5SYJTejfrD8Ah95+x7M9ulkzOl15Ju2cDib9c5nHGeDujTlMeWM1Z93YO6I5/vkl5fzfB0soLPNObXr2gj4+Cr+b5LFj2fvsc7jy8gDI/vhjEvv356+ndWHS8l3kl5j66PHJ65h86wiiHL7+TbqkdWHqtqmAMe8XBOH4QJR+QRAEoRLlWVnkfP4FOV9+ScXevQFlVHw80cNHk9nqVDbuiq/UH5CYEsvQcR3oMCCVyf98mm0rl3n2xSYkMP6uh2jbq0+N5Fc5HMS2bkVs61Zw0kkAaKeTkjVrKJg9h4I5sylZuarS1ABXURG533xL7neTSRl3Dk1uuonY9u3Dni8mNooBZ7Sjx4iWLJu6jRUzduIsNzfA5dIsnbKNLcv2M/rKroy88joSk1OY/ZGlLGjN9Lf/Q1FeDsMuvLxaTgcFQag6S6duw1lhVVQKRl7eNaDCX1RexPTt3hCcYzPGEu2IpnjVaooWLvRsT7vqSlRsLLHAuNv68vULS8neUwTAttUH+fndtZx2XU8cjuDvuMulufOzFWzZX+jZdt2JGYzvF9jxpyMhgdTzzuPQe+8BkP/jFCruu49GjRpx+ymdeeL7dQCsy8rjiyU7uGRwW5/jO6d19iwfKD7AoZJDNIqX6CKCUN85PBejgiAIQr1BV1SQP+MXdtxwI5tOOZUDr75aWeGPiiLp1FNo/vIrFDz+Ob/Ejuf3Hb4Kf0xcFEPGZXDlY8No36cBXz7xgI/Cn5iSysWPPFNjCn8wVFQUCX360PSWP5Px6ad0njeXls8/R/K4cUSlpfkKu1zkfvMtm88+h9333U/Z9u2BE/UjvkEMw87rxJWPDaPnSS1RtsZ9zt4ivv77MmZ+tJ4+p43nzJv/inJ4P7u/ffExsz74b41cqyAIoSnMLWXNHO8of6eBzWjUInDYz+nbp1Nc4fXdMa7jOAAOvfO2Z5sjMZG0S7ye8BOSYjn39v40bBzv2bZp8T5mffw7ofxn/WfWZqau9dazQzIacf/YbiGvJfVS73l1eTk5X34JwNXD2tO+caJn3/M/baCgtMLnWLvSD7AxW0z8BeF4QJR+QRCE4xxXSQkH336HTaecys6bb6Zg1qxKZvzRLVvQ9Pbb6PjzzxRe8QDf/hLHgu+3+4S0Uw5Fr5NbceXjwxh8dgbFeQf55OF72LPZ26hMTW/BZY89T3pG5Tn/tU10o0akjBtHq+efo/PcObT/7FNSL7sUYmwxrZ1OcidNYvNZY9n9wAOU7dwZUdpJaXGMuqIbF/9tMM3aNfTZt2bObj6eOJ+ElD6Mv+tBomO9cbGXfD+JpT9+55+cIAg1zPJp2z3WOACDzmofVPa7zd53slNqJ7qmdaVs507ypvzk2Z560UVEJfua3yelxTH+L/1ITPZaD6yds5vfvtocUPGfvWE/L0z93bOenhzHvy/vT0xU6OZ5XEYGDYYP96znfPIp2ukkNtrB/WO93vgPFJTyn5mbfI5tldSKxGhvx4Ao/YJwfCBKvyAIwnGKLi8n+5NP2Hz6Gex77rnAo/qnnEKbN16n07RplJ16GV+/vZ3p762jILvURzSjbxMue3gIIy/vSmJyLAd37eDjh+4iO2uXR6ZZ+45c+thzpDavuvf8msZtBdDikUfo9NMUUi++GKJtM96cTnK//IrNZ55F1kMPU75rV/DEbDRpncQF9w7ixAs7ER3r/cQW5pbx42ur2LgkgXP++jCxCd5G98z33mTzkoWBkhMEoQYoyitj9WzvO9yxf1NPWD5/9hbuZcGeBZ71czuei1KKQ++97+0MjYqi0TVXBzw+pWki597ej7hEb32ybNp2lv60zUdux6EibvtkmWfGUUyU4tUrBtKsYTyRkHb5ZZ7l8l27jM8V4PQe6ZzQwWuu/+acrew4VORZdygHndK8oUPFmZ8gHB+I0i8IgnCcoZ1Ocr/9ls1jz2bPxEep2LfPZ390yxY0ue1WOs2YTptX/o2rx2B++u86vv77Up9Y9QDN2idz3p0DGHtTH9KaG1PZorxcvn72UQqyD3nk2vbqw8WPPE2DVD+z+qOAmJYtafHYo3ScMoWUCy+AKJvH7YoKcj7/nE1nnkXWo49SEcAxoD8Oh6LfqW257OGhtOnue72bl+7nlw9z6XvG/3lM/bV28f1Lz7F36+YavS5BEAzLf95ORZl3lH/g2PZBZX/Y+oMnjr1CMTZjLM6cHHK++MIjk3zWWcS0bBk0jcatkhh3az9i4rx1yfxJW1g101gOFZc5ueGDJeQUlXv2PzKuJwPbRV4/Jo0aRXTz5p71nE8+NXlWiofO6YHbVUhZhYtnp6z3ObZLmtcR6oZD4sxPEI4HROkXBEE4TtBakzdtGlsnTGD3PfdSvmOHz/743r1p/Z9X6TRtGk1vvhmd0pj5kzbzv4kL2LzUt2MguUk8p/+pJxfeO5CWnVM9250V5Xz3z6fJ3bvHs63LCSM4775HiUtM5GgmtnUrWj7xBB2n/EjK+ef7Kv/l5eR8/Albxp5N7jffhJyj6ya5SQLjbuvHKdd09xn1Ky2qYNUsB03ajfMmX1rCpGcfJf/ggRq9JkE43ikuKGPVLO8of0bfJjRt0zCovN1r/9AWQ0lvkE72J5+ii71z/Btf94ew503PSGbszX18vPfP/mQD6+dn8cDXq1iblefZftHA1lwxtG2gZIKioqNJvfBCz3rh/Pm4ykwY0Z4tU7hoYGvPvskrs1iyzdsJ2znVO69/c+5mnC7vNC1BEOonovQLgiDUc7TWFMydR+ZFF7Pr1tso3eg7xzOucyda//tftP/sUxqOHg3KwfrfsvjokfksmWLzdg3ExEcx7LyOXP7ICXQelO7jeV5rzc9v/Yeda1d7trXr05+zb7ubaPu8+aOc2DZtaPnUk3T84XtSxo8Hm/M9Z3Y2u++9j+1/uI6yzMywaSml6DasBZdPPIHOg5r57MvP6UhMwmDPekH2Ib5+7jHKiov8kxEEoZqs+HkHFaVepXZQiFH+3w/97jPHfVzHcbhKSzn04YeebYnDTiC+R4+Izt26axpnXN/Tx8Hn9PfWsWJhlme9d6sUHp/Qq1pRPJJGnuxZ1iUllKxa5Vm/6/SuJMZ6Oy4fm7wOl8t0Vtqd+RVXFLOzIDLfJYIgHLuI0i8IglCPKV6xgu1XX8OOP/2JktWrffbFtGlDy+efI2PSJBqeeipKKbI25fDFs4uZ/t46inLLvMIKup/YgisePYEBZ7QjKqby52PpD9+w+pepnvW0lq055y/34rCPmB9DxLZrR8tnn6HD5MkkjR7ts69o/ny2nDue/a++6hldC0Viciyn/6kXZ9/ch6Q0ryM/R9wIHDHeBvj+zC18//LzuJwy8iYIh0tJYTkrZ3oV2va9G9OsXXJQebsDv4ToBE5teyp5332H84DXAqfxdX+sUh4y+jbllGu6g1un13BuYSxNnYq0xBj+c+UA4mOqV0fGd++OI8nrm6BwgdcXQbPkeG4e5XWYumJHDt+uMNEL7Ob9IM78BOF4QJR+QRCEekhFdjZZDz1E5iWXUrRokc++6PR0mk+caEayx41DRUVRkF3C1LdW89ULS9m3Ld9HvmXnVC6+fzBjrupOg5Q4ArFl2SJmfeANZxXfIInz7n2Y+AaBnWUdS8R1yKD1q6/Q6l8vE93MO1qvy8o48PK/2Hre+RQtXhxRWu37NOGyh4fSe1RrlDKWADENzkRFeefmblm6iJnvv1Xj1yEIxxsrZuygvMQ+yp8RVNbpcvLD1h8866e0PYWEqHgOvv2OZ1tcly40GHFilfPRdWhzRlzs7dyLRjG8JIZ/XTaA1mnVn/akoqNJHDTIs160wNch6J9O6kCr1ATP+rNT1lNc5iQlLoVmid66TJR+Qaj/iNIvCIJQj9AuFzlffsWWsWeT8/kXPvuiUlNpdu+9dPxpCmmXXoKKiUFrzfr5WXz86AI2Lvadt9+wcTxn/l8vJtzRn6Ztg8+BPbBjG9+/9Bzacn7liIpi3B1/I615cEdXxxpKKZJPO40OP3xP2pVXgs0Ut2zzZrZdeRW7H3wQZ05O2LRiE6I5+dIuXHT/YNIzklEqhtik8eDwjkAum/IdiydPqoUrEYTjg9KiclbO8I7yt+3ZiPSM4KP8C7IWsL94v2d9XIdxFMycRdmWLZ5tja77Q7XM8AF+T4IlsRWe9S7lUfRKPnw/J4lDhniWi5cvx1XqjawSHxPFPWd29axn5Zbw5hxzPT7O/LLFmZ8g1HdE6RcEQagnlGzYwLarribrgQdw2rzMq/h4mtxyCx1/nkbjP1yLI96EhCrOL2PK66uZ/u46ymyjYdFxUZwwoQOXTxxKxwHNQjZyi/JymfTcY5TZnFydct1NtO3VpxausO6JSkqi+YMP0P7TT4jr3t1nX+4XX7J57NnkfvddRI7+mrZtyAV3D2T0Vd1IaJhKbNIEwBvfe9YH/2X+Vz/X8BUIwvHByl92UlbsVbIHnx18lB/g2y3fepabJjRlaIuhHHrba70UnZ5Oytix1cpLSbmTF3/ewIL4cpx464bl03eEOCoyEod6lX5dWkrxihU++8/t25L+bVM962/O3kJZhctnXr+E7ROE+o8o/YIgCMc4rsJC9j73PFvPO5/iJUt89iWNHk2HyZNpesufibLN/dyyfD8fP7aALcv3+8h3GZrOlY+dwMAz2xMdZp5pRXk53/79SXL37fVsG3DWufQ59cwauKqjm4Q+fcj4/DOa3XMPKsFrPus8dIjdd9/DzltupeLQoRApGJRD0ePEllzx6An0GtWHmIbjsE/+nffpv/n6hSnkHyqpnQsRhHpIWXEFK2wKdetuaTTvkBJUvqi8iBnbZ3jWx2aMpWzdep9pO42uvgoVGxvo8LD8b8F2dueWUOiAtbHeDtb1v2VRlBfeJ0go4rt1w5HstWDwN/FXSnHPGd086/mlFazYmePjwX973naKysWBqCDUZ0TpFwRBOIYod5azM38nS/YuYca26cz/5CXWnnW6GZGyO39Lb0r0cw/ifOYeDqQqiivMSHxpcQXT31vLj6+tojjfGyM6oWEMZ93Ym9P+0DPovH07xlP/K+xav9azrX2/gYy8qmpOro5lVHQ0ja/7Ax2++44GNi/aAAXTp7Nl/HgK5s6LKK34pBhGX9GNSx64gLTWZ9v2VLBl8Tt8/Oh0Ni/bF/R4QRC8rJy5k9Ii2yj/OaFH+X/e/rOnjgTjtT/nk088647ERFIvvrhaeSksreCVX7wRU7Jbx3uWneUuVs06PM/5KirKd17/woWVZAa3TyMpzhs29LfNB33M+zWaLblbKh0nCEL9ITq8iCAIgnCkyC7JZkvuFvYW7mVP0R7zX7iHvUXm/2DJQQCa5mium+pi4GZfM/IKB0weovjyxEOUZj8Dk7z7Mgp6cfLGS0go8Z3XGteplDZnQ2GTPRwqiSItLi3svNUlk79mzUyv6XmjVm045/Z7jllP/YdDbOtWtHntNfJ/msqeJ57wePp27j/Ajj/9iUbXXE3TO+7AERe+MyU9I5lrn7+Br58rI3OZFQlBF1Kw/wt+fC2G3qPaceKFncJaYQjC8UpZSQXLf97uWW/VNZWWnVJDHmP32t8lrQudYlqycfL3nm3J544jqmFwvyaheGfeVg4WekfzbxzfjcJpWWxbbery1TN3MeCMdsTEVv+dbjB0CAUzjKVC8fLluEpKPNO4AKKjHAzNaMT09abj8LfNB7lp1ECiVTQV2nSObMzeSK8mvaqdB0EQjm5E6RcEQahjdubvZPr26czYPoNl+5ahCT4fXGnN6Us0V8x0EV/uu29tG3jrjCh2NvVV2KOcMQzdfg599ozy2V4aVcy8jC/Z0GQR2AaHkmOTaZ/cnvYp7WmX3I72yea/XXI74qPj2bxkIbM+8nq0jk9qyHn3PExcYoNq34NjHaUUyWeeQeKQwWQ9+JCnAQ5w6L33KfxtPi2ff574rl1CpGJwOBTn33MLk17IY8uS+QBo534qimexetYpZG3K5Yzre5LW/Pi934IQjNWzdlFaaBvlD+GxH2Bv4V4WZHlD3Y3rMI7cb75F2/yUpF16abXyklNUxuuzvSPog9unMapLU3YT41H6SwrLWf9rFr1Hta7WOQAShw71LOvycoqXr6DBCUN9ZIZ1bOxR+pdsz8bpctA+pT2bcowVgjjzE4T6jSj9giAIRxitNRuyNzBj+wymb5/O79m/R3Rc0xzNTT+46LXNt1MgNxE+GONgdi/l41UeoFl+W0ZvvoK04uY+23em/M7Mjh9TEJeNP3lleaw8sJKVB1ZW2te5oiXDfonFYTmqU1EOxv31flKbt4joGuo70Y0a0fqVf5Pz6WfsfeYZdImZi1+6YQOZF11Es7vuIu2qK8NaUiiHg3P+cjefPHwP+7ZuBsBZugJHdDsO7urEZ08tYuRlXek2TO67ILgpL3WybJp3lL9FpxRadkkNecwPW3/wdLQ6lIOzMs4i+z7vNKWEfv2I79Yt2OEheX32FvJLvB0Qd5/RDaUULbuk0qxdQ0941OXTd9Dz5FY4HNWLDBDXpQtRKSk4c3MBKFq4oJLSf0KHxp7lsgoXS7dn0zmts0fpl7B9glC/EaVfEAThCODSLlbsX8H0bdOZvn06OwtCz+NUKJomNKV5g+akJzZjyMJcen28hCibl32ApIsuoMVtN/BEwyQqXBU4tZNyVznFBaWs/+kQO9YU4GM4EO2iaGAmJe020Lm0PQeKkzhYfJCiivBOnBJKouj7q8JR7k1wbo/9fL36z/Ta04veTXrTq0kvejXpRaP4RlW6P/UJpRRpl15C4pDB7L7rbkrWGr8HuqyMvU89RcGcObR86kmimzYNmU5MbBzn3H4PH9z3F8pLzKhjedFPOKKbUVGWzPT31rFzfTYnX9aF2Hj5nAvC6tm7KCnwmkANPjsjZAeb1ppvN3u99g9tPpSGa7dzaNNmz7a0y6o3yr8vv4R35m31rI/s0pQhGaZeVErR77S2TH1rDQB5+4vZsmw/nQY2q9a5lMNB4pDB5E8zU64KFyzEv3bp0SKZlIQYcovN/Zm/+SBdWnThx60/AmakX2td7ZCEgiAc3UgrQRAEoRYpc5bx+YbPeXvV2+wrDu6ILUpFMaj5IE5pewojWo6geVJzYhwxlGdlkfXgQxTO+81HPqZVK1o8+WSl0RytNRsW7GHel5k+jvoAmrVP5tRru5PW/NRK5y8qL2J/8X625W0jMzfT/OdlkpmXyb6ifcSUK05b1IykEu9nY037PDa2KYBSmLtrLnN3zfXsa5XUil5NetGzcU+6pHWha6OuNI5vfFw1KOM6dKD9Jx+z/1//4uBb/wXLOqJwzhy2nDueFk8+QcMxY0KmkdaiFaf+6WZ+/PffzQZdSlnBD8Q2vBilHPy+YA97tuZyxp960bRt9eYcC0J9oLzMd5S/eYdkWndLC3nM79m/e0a6wTjwy371U896VEoKDc+sXjSSf8/YREm5y7N+9xldffZ37N+Uho3jyT9orIGWTdtOxwFNq11HJg4e4lH6i1euxFVcjMMWWcThUAzNaMTUtSbaym9bDnJrD+90o+zSbA6WHKRJQpNqnV8QhKMbUfoFQRBqAZd28cPWH/j3sn+zq2BXQJn4qHiGtxzOKe1OYWTrkaTEeUNKaa3J+epr9j71FK6CAp/jUi++mGb33ENUku+c7oO7C5j98QZ2b8zx2R4V7WDQ2HYMOKMdjqjAQVsSYxJpF2Pm7Z/c2tcTfX5xHl8+8wgH873mn/tbahZ3rzw1wM2ugl3sKtjFT5k/ebY1im9E57TOdE3rSpe0LnRJ60LH1I7ERlUvDNaxgIqNpdmdd9JgxEnsvvdeKvbsAcCZnc3Om/9M2pVXkn7vPaiYmKBp9DhpNNtXLWfNrOkAaOducC6A6GEA5O4r5ovnFnPiBZ3oPar1cdWxIghuVs/aRbEt/F24UX7wdeCXEJ3AqAb92Tn1Ac+2lPPPj8gBpz87DhXx8UJvB8TZvVvQq5VvyEBHlIN+p7ZhzqemXt2XmUfWphxadg7dUREM+7x+ysspXraMBsOH+8gM79jYo/Qv35FDmwZ9fPZvyN4gSr8g1FNE6RcEQahBtNbM2z2PF5e8GHCufsPYhoxqPYpT2p7CsJbDSIxJrCRTvm8fex5+hIKZM322R6en0+KJJ0g6aYTP9rKSChb/kMmKn3fgcvnO92/bsxEnXdKF1GaVzwNQ7nSxeX8Ba3blsXFfAUVlFZRVuCitcFFa4aSs3En68kk0yvIq/NkNWpDZ+SrOSY2jYcoeyqMz2VO6kbUHV3uiCwTiUMkhFmQt8HGaFaWiyEjJoEtaF/o07UO/Zv3oktaFGEdwJfhYpMHQIXT4ZhJZEyeS/+MUz/bsDz+kZP06Wr/4ItFNgje2x1x3I7s3rCc7y3QglRbMp3mXruTsM+bCrgrNnE83smtDDqdd10O8+wvHFcUFZSz+IdOz3qx9Mm16hJ5iVOGq4IetP3jWT217KqXf/gjlXguptEuqF6bvxZ83Uu50+wmAv54W2IFn9+EtWTh5q8fx4LKp26ut9Md17kRUWhrObNMZW7hgYSWlf1hHbx1T7tTs2B9Lw5iG5Jcb3wIbszcyvKXvMYIg1A9E6RcEQaghVh9YzT+X/JOFeyrHSe6a1pVb+t/Cia1ODKnQ5n43mT1PPIHLcsjkJuW880i//z6ikr3h9rTWbFm+n7mfbaQgu9RHPiktjhEXd6ZDP6+5aHGZk3V78lizO4+1u3NZszuP9XvyKatwEYyh2QvpnuN16JcTncIXjc+gZHs+87fnYz4jnYhydKZj04s4sXk5yalZOGO2s79sE5tzN5BXlhc0fad2silnE5tyNnka4AnRCfRs3JN+zfrRt2lf+jbtS1p89RrCRxNRKSm0+sc/yB05kr2PPY6ryPhRKF68hK0XXEjrl18ioW/fgMfGxidw9u338PGDd+KsqACtyd/7LX1PuZMVvxz0+G3Ysmw/P762mrNu7CWKv3DcsOi7rZQVex3mDTuvY9hR/gVZCzhQfMCzfk7GWHImTvSsNxg+nNj27aucl4178/l6mddnywUDWtOpWVJA2Zi4KHqPbO3psMhcdZBDuwtp1LLqkTmUw0Hi4MHkTzWhPosWVv4OdUlPonGDWE8IwflbDtE5rTNL9y0FxIO/INRnROkXBEE4TLblbePlpS8zddvUSvtaJbXilv63MDZjLA4V2LQewFVczJ7HHif36699tkc1bUKLRx+j4ZjRPttz9xcz59MNnrBPbhwORYcRLWg4oBHLCsv4bvpGth4oZM3uPLbsL8AVPBpgJXrmrWVIzhLPerEjnm+bn01JVEIlWadLs2FvARv2AjSyfv1okRLHiAxFq2bZxDXYx76SrWzI3kBmXiYuHbizobiimMV7F7N472LPtvbJ7T2WAAObDSQjJbzp7tGIUorUCRNI6NOHnX++hbKtxtFXxd69bLvyKtIffoi0iy4KeGx6RkdOvvKP/PLu6wAU5hxi35avOfe2W/n5nXUUWabN29ccZMrrqznrht5ExQQvc4JQHzi0u5DVc3Z71jP6NqF11/CdhN9t8Zr2N0toRq9NFeza5Z2KlXrpJdXKzz+mbfDUszFRittP7RxSvveo1iybuh2n1fm6/OftjLm6e7XOnTh0iEfpL161CldhIY4G3g4EpRQndGjM96uyAPh180EGDfQq/eLBXxDqL6L0C4IgVJNDJYd4ZdkrfLnxS5za16t+WlwaN/S9gYu6XBR2znrp1q3suv0vlG7wHWVJPucc0h/4G9Fp3gZsSWEZc7/dwoa5WWinrwa/Px5+jC1h78rNsHIzVUEpyGjSgCYN4oiNdtD40CbaZM7x7NdRMThO/xNXtmhPlMPBjkNFrMsyUwKcIXoSsnJLyVoOkAC0o3lyV07ocDkXdkmiedM8Clzb2ZC9gdUHVrPm4BrKXeUB03E7FXR72m4U34iB6QM9v86pnYlyHDsj23EdOtD+88/Yfd99FPxszdUvL2fPQw9Tsmo16Q8+gCO2crnpf+Y5bF+9nM2LzRSJrcsW0673HC6870wm/WMpeQeMU7Btqw/y4xurOOv/RPEX6jfzvtyItuogR5Ri+AWdwh5TWF7IjO0zPOtjO4wl97+fedajmzUL62QzECt35vDj6j2e9SuGtqN1WuCpVW4Sk2PpOqw5a62Oi98X7mHo+A40SKm6L4EG9nn9FRUULV1WaTrYCR29Sv+qXbmcP6qjZ9/mnM1UuCqIdoh6IAj1DXmrBUEQqsGyfcu4a+ZdlTzyJ0QncE3Pa7imxzUkxQY26bSTN2UKWQ88iKuw0LPNkZyM6477Wd37BH5cnc3O7N1sP1BIzNZCOh9wkaB9R7gLlWZWQjlrYpwQweB3bJSDrs0b0rNlMj1bJtOjZQrdWzQkMdZ8EvZs3sinj35FhTUSr5SD8XfcR6dBQyulVVLuZNO+AtZm5bF2dx7rsvJYm5XnE5vazp68EiYt382k5WY9PbkhJ3Q4nXM6XsY/Tm7MrqKNrNi/ghX7V7B833L2F+8PmM6hkkNM2zaNadumAcZXwoBmAxiYPpBB6YPo1rjbUe8XICopidYvv8zB119n/8v/8nj3z/nsM0p//51WL79MTLpvCC+lFGfceDvv33MrBYeMlcfsj96ldfdeTLhjgK/iv+ogU95YxZmi+Av1lG2rD7J9zSHPep/RrYP6L7Hz87afKa4o9qyf0+AECma97VlPvegiVHTVm8gvTPV23CbERHHz6I4hpL30P7Uta+fuBm38c6ycsZNh50V2rJ3Yjh2JatwY50FTNxQtXFhJ6R/WobFn2enSlBele9bLXGVsz99Oh5QOVT63IAhHN6L0C4IgVAGtNR+s/YB/LvknFdqr2EaraC7ocgE39r0xIu/HuqyMvc+/QPYHH/hs39qkHRMHXMG+5TGwfAlo6FThYGRxDI1cDuxavUazItbJnPhySgLodFEORcvUeFqnJtKtRUN6tkyhZ8tkOjVLIiaIF/+cvXv4+tlHqSj1+ggYc92NARV+gPiYKHq1SvHxTK21ZldOMat35bFk2yHmbznEmt25AacW7M0r5Zvlu/lm+W4SYqI4t29LrjhhPNf0vAatNVmFWZ4OgOX7l/P7od8rWVUA5JflM2vnLGbtnAWYzpf+zfozuPlghjQfQo/GPY7K0SvlcNDkppuI79GDXXfdjSvfONQqXrGCrRdcQOuXXiRx4ECfYxIaJnP2rXfz2WN/Q2sXLmcFk198liufeYnxf+3PpH8s84QBy1x1kClvrubM63uJ4i/UK5xOF/O+8JqjxyfFMGhs+4iOtZv2d03rStrUxRx0WdONoqJIvejCKudn/paDzN7g7aT8w4ntadYwPqJjU9MTyejThK0rjI+BNXN2MfCsdsTGV63OUkqROGSwx1lo4cIFlWQ6Nm1As4Zx7Ms3dfyOvb5RBTZkbxClXxDqIUdfC0gQBOEopaCsgId/fdgzuuzm5NYnc8/ge2iX3C6idMp372bnX/5KycqVPtu/6TCCt3qdQ4WlnKZXKEYVx9DWWdlsPTPayayEcqIbxdGnUUNapyXQJi3R/Dcy/82T44kOotwHojg/j6+efoSi3BzPtiHjL6Tf6WMjTgNMw7N1WiKt0xI5s1dzAHKLy1mceYj5Ww6yYOshVu+q3AlQXO7k08U7+HTxDvq0TuGKoW0Z17clZ2WcxVkZZwFQVF7E8n3LWbx3MUv2LmHVgVUBpwQUVxTz6+5f+XX3rwA0iGnAgGYDGNJ8CINbDKZbWrejajpA0siRZHzxOTtvuYXSjSZuuPPAAbZdcy3pf7uftMsu8/Fh0LpHL0644FJ+++J/AOTszeLnt15h7K13MeEOP8V/5QGj+P9fL6KiRfEX6gdrZu8me0+RZ33ouAziEsNb9+wp3MPCLK+Tu3PbjSXn+Xc860mjRxHTvHmV8qK15vmfvNFakuOjueHkqo3U9z+trUfpLy2qYN28LPqe0qZKaYAx8Xcr/SWr1+AsKPQJ76qUYljHxnyz3EwnWLK1mJYtWrK70KxvzN7Ime3PrPJ5BUE4uhGl/xhAKdUVWAEc0Fq3jkD+UuB6oD+QCOwCpgL/1FqHdc2qlBoK3AmMAJoA+4EFwCta6+nVvQ5BOJbZmL2RO2beQWZepmebQzm4fcDt/KHnHyJyKqe1Zs2kn3A+/hCxRQWe7UXRcbzU7yJmt+4HQEOX4qTiaHqWV66iHamxtBvTkrH9m/FkWiKxNaTElZeVMum5xz0h4QC6jxjFiEuvrpH0UxJiOKV7Oqd0N6akeSXuToBDzNt0gDW7fT38r9yZy8qdq3ji+3VcMKA1VwxtS+f0hiTGJDK81XCGtzJhpUoqSlh1YBVL9i5h8d7FrNi3ghJnSaXzF5YXMmfXHObsMn4KGsY2ZGD6QIY0H8LQFkPpnNq5zh0DxrZrR/tPPmH33x4g/6efzMaKCvY+9jjFy5fT/OGHiUryThk54YJL2LF2JTvXrgZg/bxZtOvTn16jTmWCe8T/kE3xf0MU/+OFvAP7mfO/d8ndvxeFQjkUWP++66YspKa3YODZ40lr0apO8x0pJYXlLJy8xbPeqGUDeoxoGdGxH637CI07nJ6DMdsakr/f68U/7dLLqpyfX37fx5Jt2Z71G0Z2JCWCDgg7LTql0rxDMnu2mLpw+fTt9BrViqgqdNwCJA4Z4l1xOileuoSkk0/2kRnWwav0r9mdy2ldO3qUfvHgLwj1E6V1FVw5C0ccpVQcMAMYDuwKpfQrpWKA/wHB7NKKgGu01l+ESONO4Dkg2Ffmea31PZHkvbZQSvUEVrvXV69eTc+ePeswR0J9Z/KWyTz222M+c0Abxzfm+ZHPM7j54LDH788v5b25m+G9tzhr+RQceOvdzIbpPDHkGnY1bEZybDQXJTSk8c7SSk76EpJjGToug+7DW+CoYiMwHBVlZXz34jNsWeId/Wrbqw/n3/8oUdFHZl78uqw8Plqwja+X7qKwrLL5PsCQjEZceUI7zuzZPGhnR7mznLWH1rJozyIW7VnEsn3LfJ5bMJomNGVYy2EMbzmcYS2H0Sg+dIzv2kRrzaH//pd9//gnuLwRDmJataLl88+ROGCAZ1v+wQO8f+9tlOQbRSE6Lo6rnnmZRi1bkXegmK//sZSCQ96pGhl9m3DG9aL412cO7d7FF088SP7BwP4wghHfIInz7ptIyy7dailnNcfczzayYsYOz/q4W/vStmfjEEcYDhQf4Kwvz/J0DI5uM5o738+naP58AGLatqXjlB89nSGR4HRpzvnXXNZlmXewSVIss+8Z7fGRUhW2LNvPj6+v8qyfdl0PugyputXBxpNPxml1ZDT643Wk3323j8y2g4WMfH6mZ33C6BVM3/MxYCLOTLlgSpXzfjywZs0aevXqZd/US2u9pq7yIwhVQb76RzFKqWjgU4zCHwnP41X4pwHjrWPvAnIwo/4fKqUGBjpYKTUBeAFTLjYC1wLDgKuBtZbY3UqpP1ftSgTh2KTMWcYT85/g/jn3+yiOA5oN4PNxn4dV+HOLynn+p/Wc8/h3tHzqPs5e/qOPwv9zm4E8cNpfGXRSP14Z35sH4hvRaFuJj8IfHeNg0Nj2XPnYCfQ8qVWNK/wlhQV8+dTDPgp/k7btOffOB46Ywg/QvUUyT0zozYIHTuWp83rTo0VyJZmFWw9x28fLGP3CTP63YDtlFZVD/sVExdC3aV/+1PtPvH7a68y7dB7vn/U+t/S7haEthhIXFdgj9v7i/Xy7+Vvum3MfIz8dycXfXcxLS19i0Z5FlDsDRxSoLZRSNP7Tn2jz5htEpXjn25bv2sW2K69i30svoctNnho2bsKZN93ukakoLeXHV/6Os6KC5CYJnHfHAJIaea9564oD/PTmapzOwOEShWOb/du28unEe6us8IOpCz5/4gEyVyythZzVHNl7Clk1c6dnvV2vxhEp/ABvrXrLxxLo5rQJHoUfIO2Si6uk8AN8smi7R+EHuGV0p2op/ADt+zYhpZk3JOqyadup6uCcUooGg72j/UULF1WSadsokZYpXn8DBflNPcu7CnZRWF5Y6RhBEI5tZKT/KEUp1QT4BDjFtjnoSL9SqhdmCoAD+BK4SNserlKqG/AbkArM1lqP9Ds+DqPotwE2A4O11tm2/Q2AWcBAIBfIsO8/kshIv3Ak2F2wmztn3snqg6t9tl/b81puG3BbSM/whaUVvPtrJq/P2kx09kGe/vV12uZ7vfyXOaKZN/ZaOlxzOaO6NWPv7zlMe2cNpYU2j/cKug1tztDxHUhKi8wZVFUpyD7EV089zP7tmZ5tDRs35bLHn6dh4/DOCGsTrTXLd+Tw4fztTF65m9IACn6r1ARuGtWRiwa1Ji46svn5Zc4yVu5fyaI9i1i4ZyEr9q8IGibQTUJ0AkOaD2FYy2Gc2PJE2iW3O2JTAcqzsth9730ULVzosz2+Vy9aPv8ccRkZAMx453WWTfE6Jxt24WUMv+gKAHL3FzPpH0spyPaO+Hfo15TTr+9ZZdNh4ehl94b1fPXMI5TaIoG07tGLpm0z0Fob5VFrQKNd2pi4a03+wQM+ir4jKpqxt95J12En1cFVhOf7V1eSudKMYiuH4tKHhtCoRYMwR5m5/GO/Gut5309rdxr3/taMQ++9Z9KKjaXTrJk+IVLDkVNUxugXZpJdZNJs3ziRn/56csT1USBWz97FrP95/QOce3s/2nSvmuVR9qefseeRR8yKw0GXBfOJatjQR+aOz5bz1VIznatjy3z2pTzp2ffBWR/Qr1m/6l1APUZG+oVjGVH6j0KUUmcDrwJtrU0ujDIfSul/DbgBKAc6aq13BJC5EzOSDzBIa73Etu9S4GNr9VKt9acBjh8ILLZW79Ja/72q11YTiNIv1Da/7vqVe+bcQ25prmdbUkwST5z4BKe0OyXocaUVTv63YDuv/LKJAwVlNC3K5ul5r9Oq0DtftDy9BW1ffpnUvr1wuTSLJm9l8Y+Z2AwAaNwqiVOu6U7Ttg0rn6SGyM7axRdPPkze/r2ebY1ateGCvz1GcpOmIY488uQUlfHl0l18NH8bWw5UHoFqmRLPTaM7cXEVlH83xRXFLN6z2OP0b0vulrDHtEpq5ekAGNpiKA1ja+85AWiXi0PvvMu+F1+Ecm8HhUpIIP3ee0m95GIqysv48N7bObTbjIAqh4PLHnueFp27AqL413e2rVrON88/QXmpdxS724kjOfPmvxIVJvSc1pp5n37Agq+9cepRilP/eDN9TzurtrJcLXasO8S3Ly33rPce3ZqTL+kS0bGP//Y4n20w16hQfHn6x7gm/BFXrqnnk88dR6vnnqtSfh75ZjXv/bbNs/72tYMY0y09xBHhqShz8v4Dv1Kcb971ToOaccafeoU5ypeyzEw2n+l9dq3/8yoNR4/2kfliyU7u+nyFteakUc+Jng6Rh4c9zEVdLqr+RdRTROkXjmXkS3+UoZT6FJiMUfg18AQwJ4JDx1v/swMp/Bbv25bP99s3wfovAr4OdLDVSeCu3PyPF4R6wY9bf+TP0//so/B3TuvMJ+d8ElThr3C6+HTRdkY/P5NHv1vLgYIymhce5Pk5r/oo/ImDB9Pzu0mk9u1FcUEZk/+1nMU/ZPoo/N2GNeeCewfWqsK/d8smPn74Hh+Fv0WXblz62HNHncIPkJoYyx9HZPDzHSN59YoBdE33vTe7c0t4aNJqRj0/k/d/y6SkPLBPgEAkRCdwUuuTuHfIvXwz4RumXTiNx4Y/xhntzyAlLiXgMbsKdvHFhi/468y/ctInJ3H1j1fz2orXWLl/JU5X5OeOFOVw0PiP15Hx2afEdvJ6BNfFxeyZOJGdN92Myi9g7K134YgynR7a5eLHV/5OeYlRAlOaJjDhjv4kpXlN/bcs38/UN9fgDGBFIRw7bFq8gK+ffdRH4e972lmMveXOsAo/GHPwEZdezcir/ujdqDU/v/UKC77+rMrm5bWFy+li7ufeEH1xidEMOTsjomN35u/kq41fedbPyjiLpvM3ehR+gLRLL61SftbvyeOD+V6Ff3TXpoet8ANEx0bRfXgLz/qOtYdwBYp3GoKYdu2IbtbMsx7IxH9YR/uUiCiaxHkjBWw4JM78BKG+IUr/0Yc7GHYmcJrW+qFwByilOgBuTy+zg8lprfcDbpuxkX673X4DFmity0Kcbq71P0QplRBCThCOOT7f8Dn3zr6XCu01sz+347l8NPajgOH4XC7Ndyt2c/o/Z3Pvl6vYnWsa3a3y9/H8nFdJL/bOgGlw4om0eeN1opKT2bM1l8+eXMSOdd79UdEORl/ZjTFXdycmtvZCyW1buZxPH72f4jxvYzej/yAuevAJEpJqd8T6cHE4FGN7t+DH20/iP1cMoFtz3/xm5Zbw8DdrGPX8TN77tWrKv5vmDZpzXufzeGHkC8y6eBb/G/s/bul3CwOaDSBKVX4uTu1k2b5lvLL8Fa744QpGfjaSO2feycfrP2Zj9kZcuuYU6vju3cn44gvSrr7KZ3vBzJlsOXc8idt3ekz6AbKzdjPzg7c86ylNEwMr/m+J4n+ssm7uTL79+5M4bRYgg8dfyCl/vLnKc9MHnXMeZ9x4O0p5j5v7yfvM+uC/aFfdl4+187I4tNtr6TP47AzikyLzO/L6ytc99XqUiuKmvjeR/cnHnv1xXbqQ0L9/xHnRWjPx2zWesKMxUYqHzukR8fHhaNfLq5CXFlWwLzMvhHRllFIkDh3qWS9asKCSTKvUBNo2SvSsR1d4IzdszNlYSV4QhGMbCdl39LEbeAV4WWtdGk7YortteVMY2a1AV/sx1nx9dxdvJMeDKTudgFUhZAXhmOG9Ne/xwuIXfLbdO/heruh+RcD527/vyef+r1aydHuOz/Z2eVk899ubJJd4G2lJo0fT6sV/omJjWTVzJ3M/34jL5qyvYeN4zrqhd62O7gOs/3U2P/77H7ic3k6NHieP4fQbbotoRPBoweFQnNW7BWf0bM7UtXt5afpGH0dae/JKeOTbNfxrxiauHd6OK09oR2pibJXPE+WIonfT3vRu2psb+t5Aflk+C/cs5NddvzJv9zx2FeyqdExuaS5Tt01l6rapAKTEpTCg2QAGpg9kUPogujbqSrSj+vfaER9P87/9jaSTR5J1//1U7DcO25wHD7LzxptofeEFtOjYmazNptG+8ucpdBgwhI4DjWMvt+I/6R/LPKb+W5bv56c3V4tX/2OMFdN+4Of//seap28Ycdk1DJ1QfbPsXqNPIy4pie9fes7TkbDk+0mUFORz+g23eSxJjjSlxRUs/M479SY1PZFeoyILL7gtbxvfbfb6uxjXcRzNdxWxdcVKz7a0yy6tkp+OH1btYf6WQ57160Zk0KFpUogjqkZ6hxRi4qMoLzEdl9vXHqJ5h8CWR8FoMHQIed+Z6y5Ztw5nXh5Ryb4OUod1aMz2Q0UAZOc0Bss1wsbsjWit6zyMqSAINYd83Y8+Rmitn6+Cwg9gD067PYysu5XayHLeV93j/Y8ThGMSrTX/XvZvH4XfoRw8OeJJruxxZaVGT3GZk2enrOfsl+dUUvhHqoO8suhNkou9CmjD00+n9UsvUqGjmPb2WmZ/ssFH4W/XuzEX/21wrSv8y6Z8x/cvP++j8A8ad35Ec36PVhwOxZm9mvP9rSN4/aqBlTz+Hygo5YWpGxj+zAwmfruGHVbjtro0jG3IKW1P4aFhD/Hj+T/y/Xnf87ehf2NU61EkRAc2fMotzeWXHb/wwuIXuPT7Sznx4xO5cdqNvLXqLZbtW0aZM5RhVXCSRpxIxrff0PC003y2533xJd1n/Ep0lPeZTn39ZYpyczzrgUb8PV79ZcT/mGDhN1/w81uv+ij8p1x302Ep/G46Dx7G+fc9SmyCt0yvmTWdb//xNBVl1Suvh8uSHzI9c9wBTrygU8S+KP6z4j84tVGeo1U0N/S5gexPvG6LVGIiyePGRZyX4jInT36/1rPetGEct47pHPHxkRAV5aB1V69Dwe1rDlY5jcQhXg/+aE3R4sWVZOwm/vsOes+XV5bH3qK9leQFQTh2OTZbevUYratlC2p3NVsQRtbuBSsF2HeYxx8WSqlmQFUnEXcMLyII4XFpF88teo6P1n3k2RbtiOb5k5/n1HanVpKftWE/D01a7RkZcdMqNYH721fQ+e//xpWf79mePG4cLZ9+irzsMr5/dRXZWd7XRykYcm4HBp7RDuWovdEUrTW/fvYh87/y9c158pXXMXhc/XDN4XAozujZnNN7pPPzun28NH0Dq3d5O16Kypy8+2smH8zfxtjeLbjh5A70anV41ZdSirbJbWmb3JbLul1GubOc5fuX8+vuX1m8ZzGrD66mwlVR6biiiiLm7Z7HvN3zAIiLiqN3k94MSB/AwGYD6dusLw1iwnsiB4hOS6PVyy+R+9XX7H3ySVxFplzG5+TRfatmVVszp7coN4epb/yL8Xc96OnEMor/AB/nfm7FX0b8j1601sz95H0WTvrcs005HJx581/pcdLoEEdWjba9+nDxw0/z5VMPU5xv3qXNi+fz5dMPM+Huh4lLTAyTQs2Ru7+IFb94XRW17pZGu96RhejbnLOZH7b84Fk/r/N5tFCpbJw82bMtZdw4opIiH6X/z6zNnqlcAPef1Y2kuJpvTrft2ZitK4xPmH2ZeZQUlhPfIPIwqjFt2hDdogUVWVmAMfFvOGaMj4xd6XeVtvDZtzF7I80bNEcQhPqBKP31A3vg6ZKgUoZi23Kc3391jz8cbgYeqYF0BKFKOF1OJv42kUmbJnm2xUfF89LolxjeariP7P78Uh6fvJZvV+z22R7tUFx/cgf+LyWPfX++yaN0AaRceAEtHn2U/OwyH1NqgISGMZz2x5606Va1MExVxeV08vN/X2XV9J882xxRUZxx4+30OHlMiCOPTZRSnNYjnVO7N2POxgO8MXsLczd5HSk6LR8M363YzfCOjbn+5A6M6tK0RkxYY6JiGNx8MIObDwZMVICV+1eyZO8Sluxdwor9Kyh1VjbgKnWWsnjvYhbvNaNwUSqKbo26MTB9IAPSBzCg2QDS4oOHEFNKkXrB+SQOHcK+Z58jf9o0AFpn57MvOZG9qUaZ2bx4Aat/mUbvMad7jjXO/UTxP5aY+/F7LPzmC896VHQ0Z//lXjoPHlbj50rv0IlLH3uOL554iPyDZhrJzrWr+eb5x7nooSer7DOgOjidLn75YD2uCmPRoBSMuKhzxO/sq8tfNaEJgRhHDP/X5//I+eQztK2uTrsscgd+Ow4V8dqszZ71AW1TmdAvsmkGVaVtD+/3QWsTuaDzoMgdBSqlaDBkMLnffAtAYQBnfunJ8XRo2oAt+wvRFQ2JIYlya+xnQ/YGTmp9dIZtFASh6ojSXz+wWweEc/Fq/1K6/P6re7wgHFOUO8u5d869TNs2zbMtKSaJV099lf7NvM6cXC7Np4t38PQP68gr8R217d82lafP702brWvYcfOf0cXe/rC0yy8n/cEHKMgpY9I/fRX+5h2SOeP6XiSlxdfiFUJ5aQnfv/w8mxd7HTj9P3tnHR7V0fbh+6xm4+5O0ISQ4C5tca+7K3X76u7yVt66y1sXpEBpobgVDZBAIECIu/vq+f5YOJslIQQIEpj7unLtmTkzZ+eEsHt+M8/8Ho1Oz7QHHiMmuf9Jfe/TjSRJjOwWwMhuAaTlV/PZ6kwW7CjE2swBe93+ctbtL6d7kAc3Do9mcmJoh67WGTQGBoUMYlCI3UzLZDWxs3wnW4q3sLl4MynFKTRYWm43sMpWdpbvZGf5Tr7dZU+40sWrC4NCBjE0dCj9g/u3GgmgCw8n/L3/Ur9xIyWvvkbTrl30ziulys0Fo9Z+X8s+fY/ggCACevdR+inC/+2t1FU4hP9fn6Yx4VYh/M8k0lcvdxL8Gr2eGQ89RVRi0kl7T9/QcC5//nV+f+kpJR1k7q5Udq9fTc9hh/sBdzxrf91HfkaVUu41PBS/sPatyu+u2K14awBc0u0SAiVP9n35pVJn6NsXlx492j2elxamYzq4BUaS4LlpCahOUqSWp78B7yBXqortnxM5u45N9AO4DhykiH7j7t1Yq6pQe3s7tRkS60dmaT0ggSkEdHY/EGHmJxCcXYhv87OD5iH5R1MSzc8fUiIn2l8g6DQ0Whq5e/ndToLfR+/Dl+O/dBL8GcW1XPrJeh6bneok+D1cNLw4I4Hfbx9K+N7t5N52u5Pg973xRoKeepKGGjPz3k6httwRPBObFMCMB/qedMHfWFfLby8+5ST4Xdw9uOSpl856wX84CWFevHt5MisfHs2Nw2JwPSwzwp7iWh75PZWBL/3Dg79sZ/3+8mNOj9UedGodyYHJ3Nz7Zj6+4GPWXrGWn6b8xMP9H+b8yPPx0R95NX9/9X5+2P0Ddy27i+E/Duf6v67n0x2fklaW1iJFoNvAgUT/9ishr76Cq58/vXNLlXMWWeaPxx+i6J23sdU7tpp4BRiY+UBf3H0dwVtZO+zCX+zxPzMoztzH4k/eU8oavZ6Ln3jxpAr+Q3j6B3DZc6/h4efYibfmx29O+v7+XWsKSF2Rp5S9Ag0Mmdn+3X0fbPtAOdar9dzc+2Yqf/oZa7ljf7z/rFntvt6avWX8tbNIKV8+IILe4Se8y7FNmq/25+4sP+b0ic0d/JFl6je1nbqvvs7xb7y3Uoh+geBsQqz0nx3UNjs+2mbQQ+dloOoE+gNUHrFV+/kQ+PWorZzpAszrgPcWnGPUmmq5a+ldbC3ZqtQFugby2djPiPWOBex7Zj9csZ+3l2RgOUz8TU4M4ZkpvQj0dKExNY28e+5Fbvbg6z/rDvzvvpvGWjPz3kmhutQxGRDd249xN8ef9JXTmtISfn/5aWVVDsDDP4CLHnsev/CINnqe3YT7uPL01F7ce35Xvt+YzVdrsyitdcxbNpis/L41j9+35hHha+DivhFc2DeMCN+Ts3dZo9IQ7xdPvF8818ZfiyzLHKg+wJaSLcqWgKL6ohb9LLJFOf9eynt46b0YFGyPAhgSOoRQ91AklQrvGTPwHDcO7y+/onT+b2R72z+6q1z1bJr9C91/m43/7bfjfeklqHQ6PP3twn/OW44V/0PCf8ItCai1Yo3gdNFQXcW8N1/CYnZ81kycdT9h3Xu20atjcfX0YvgV17Lo/f8A9s+ZrYv+YOD0i0/K+xXsq2Llj3uUss5FzeRZiehd27enPa0sjRW5K5Ty5d0vxw839n3xhVJnSErCbdjQlp1bwWy18ez8nUrZw0XDQ+O6t6vviRAZ78eO5fbP8vpqExUF9e2OdADQhYehDQ3FXGDfmtawcROeh5l/Do5tvq/fsYc/szoTs82MVtV+HwGBQHDmIkT/2UF2s+OjbS47dL5UlpVk5HmAFVAfQ3+wpxc8IWRZLsFuJthuRAoZwfFQY6rh1sW3srPc8eAW7h7O5+M/J8zd/mdtsdp4al4aP27Mdeob5m3gxRkJjOlhN0Yz5+eTO+sOpxX+gPvuw//222isMzHvnRQqixyh2xG9fBl/CkKlS3OymP3y09RVOlJJ+UdGc+Fjz+Lh639S37uz4OWqZdboOG4aHsO8lAK+WZ/FzgLnHNi5FY28/U8Gb/+TwdAuflzSP5wJ8SEYdCcvXZkkScR6xxLrHcsl3ewO7AV1BWwp3sLGoo2sL1jfqpv24SkCw9zDSPRPpHdAbxIDEul5xy1Mmj6V7x67n1qzXczvDfbFf28+1hdfpPzLLwi48y68pk9ThP/ct1KorbBHqGTtKGPRJ6lMuC0Bjfb0pGs7l7FaLMx/+1VlTz3AoJmX0W3w8FM+lp7DRrH1zz8ozrSvAG+Y8zMJoy/A1cu7Q9+ntqKJvz5JdWQ5kWDsTfH4BLfP4BLg/W3vK8cGjYEbe99I5Q+HrfLfdVe7nye+XZ/NvhJHUOQDY7vh594RtkZtE9rNG7VGpUTcZO8sPybRD/bV/uo5cwC7md/h+Lvr6RbkTkZxHdYmh+i32CwcqD5AN59uJ3AHAoHgTEFM3Z8dpDc7PlrsW+zhfWRZNgGHEuC2t78Z2NfeAQoEp5MGcwN3/HOHk+CP847jm4nfKIK/yWxl1vdbnQS/WiVx26hYljwwUhH81tpacm+/A2upwyDO79Zb8b/9Nprqzfzx7jYqChyh02HdvZl4e++TLphyd+7gp6f/z0nwh/dK4LJnXxWCvxX0GjWXDohg4T0j+POeEdwwLBpfN12Lduv2l3P/z9sZ8NI/PPDzNn7amMPe4tqTsgXgcELdQ5naZSovDHuBJRcvYd6MeTw68FFGho88YorA/Lp8FmUt4vVNr3P1n1cz+IfB3LLjMSov7WHfhAzIksT2yEAsKglLQSGFTzxB5tRp1CxahIevnhkPJOPh69iCkp1Wzp8f7sBssrb6noKTx4pvPycvPU0px/YdwNBLrzwtY5FUKkZfe5NSNjU2su7XHzr0PcwmK4s+TnVKzzd4eizRvdv/GZZSksLa/LVK+eqeV+Ntc6H8OFf5y+qMvLMkQyl3C3Ln6sFR7R7PiaDVqQnt6thCkLuroo3WreM6yJG6z5iRgaWi5TWGHFzttxmDQXZMhIgQf4Hg7EGI/rMAWZYLsK/WAww7UjtJkgKAQ1O26w47vfHg62BJktr6uzi0vLBZlmVzG+0EgjMCo9XIPcvuYUfpDqWul18vvhr/FYGudiFf3Wjm2i83sniXYyXV21XLL7cN5rGJPXHV2YOiZLOZ/Hvvw7jX8SDkOWkiAffdi6nRwvz3tlOW61gNCunixaQ7EtGexBVigD3r1/D7y09janREF3QbNIyLHnseF7djWxU6F+kV6skzU+P597Hz+fjqvlzQMxD1YeZcdUYLs1PyeXR2KmPfXkXfF5dw49eb+GD5Pv7NLKfxJAtiSZKI9Yrlqp5X8cH5H7D28rV8Of5Lbul9C/F+8Ui0vmJptpnZUbaD7yr/YGtXx46sehcdqeEBinOr6cAB8u9/gAMXXoSU+i/TH0jC098h/HPTK1n4/nZMTS3TEApODqnLF7Ptb0dqOZ+QMCbd/RAq1emLuAjvmUDXgQ6xvOOfvyjPy+mQa8uyzPJv0ynNcew47No/kL7jj01gv5/iWOV317pzXfx1LffyH8Mq/xt/7aHW6Pi7f2ZqPFr1qXt8jox3hN8X7KvCbDy2zxq3gQOdyg2bNrdoM6TLwUkVWYfN7PAR2FO5p0VbgUDQORHh/WcPc4C7gbGSJIUenAg4nOuaHc897Nxs4CrAC5hxsOyEJEn9gV5H6C8QnHGYbWYeXPEgG4ocIY3dfLrx6dhP8dLbV09Kapq49suN7C5yPGiGeLnwv5sGEhfoodTJskzR8y9Qv84xX2ZITibklVcwm2wseH87JVmOMPHAaE+m3NUHncvJ/Zjdumg+y7/51J7T6SDJE6Yy+rqbT6s46IzoNComJIQwISGEktom5qbk8+vmPPaW1LVoW9VgZtnuEpbttu9O0qgk4sO86B/lQ0KYJ4EeLvi56/Bz0+PjqkXTwSKheYrAe/reQ1VTFZuKN5Famsr20u3sKt9Fk9U5A2tqbDVhpS4EVdrFfKGPB7Jkom92ldLGuHs3eXfMwpCUxPhb7mHxCoPiTZGfUcWC97bb/64N4vHhZFKQsZuln3+olHUGA9MffhK9a/tD3E8WI666nv1bNmKzWpBlGyu/+5ILH332hK+bsjiHvZsdu/0CIj0Yc23PY9rSt7FwIxuLNirla3tdi4dVe9x7+bfnVvHLFkf018SEYIbFndrIqYhmZn42i0x+RuUxRT5oQ0PRRkRgzrXfR8OGDXiOH+fUZnCsL5Jk/xqxNgWj0tknSDIqM1pcTyAQdE7Et/bZw6fYc97rgY8lSZopy7IyHSxJUnfgiYPFDbIsbzys/59ADhAJ/EeSpLWyLBc36+8GfHSwWAd8dXJuQyDoGKw2K4+tfoyVeSuVumjPaD4Z+4ki+A+U1XPNFxvIq3TszY8LdOfbGwcS6u0cPl3xxRdU/erwnNRGRBD+wftYJQ1/frCdwv3Vyjn/CHem3n1yhZEsyy1ydgOMuPJ6Bky7SHhfnCCBHi7cOrILt4yIZUdeNfO2FbAxq5z0wlqn1H+HsNhktudWsT23qsU5SQIfVx1+bjr7RIC7ngB3Pf7uOiJ8XYn0dSXKzw0fV+1x/7t5u3gzNmosY6PsJl1mm5m9lXvZUbqD1LJUdpTuIKsmi5VJZUxdG4LBZJ8QKvT25asuFiZvqSPQ8SdM47ZtNN55I7FJieyNupW6avu4CvdXM+/dbUy9uw8ubsLg62RQV1nBH2+9jNXiWF2edPdD+IWdGUacPsGhJE+YzJaFdj/dAymbydqRQnRi8lF6Hpms1DLWz92vlA0eWibe3vuYoqRkWXbay++p8+TqXldT+d3xrfIXVDXy+JxUZT5Vr1Hx+KRTZ554CN8QN9x99Erq15ydFcck+sEe4l99SPRvOvzxD7xddfQM9mRXYQ02Ywhg3wq3t0KE9wsEZwtC9J8lyLKcJknSh9hX+6cCqyRJ+g9QCAwGngK8se/Fv6uV/k2SJD0A/AZEA5skSXoR2IF9n/9jQPzB5k/Islx6+DUEgjMFm2zj2fXP8nfW30pdmHsYn437DH+D/WEpNa+a67/aSHm9wxG7b6Q3X14/AG9X573dNX/9Tcmb/1HKKi8vIj75BDy8WPRRqlMeab8wN6bfm3xSBZHVYmbxJ++xa9UypU5SqRh/+73Ejzr/pL3vuYgkSfSJ8KZPhDcA9UYL23Or2JxdyebsSlKyK51Cf1tDlqGi3kRFvYm9bdiWeug1RPq5EuXnSoSvK1G+bkQdLId5G45pQkCr0tLLrxe9/HpxOZcDUNVURWpZKtvCV9L0/b+obCAh4VsVwDNXWui/z8RF62x4Oywp8Nm2g6Sdj/HvwHuxaEMAKMmqYd47Kfa/c3ch/DsSi9nMH/95ifpm3hxDL72KLv0GtdHr1DPowsvZuWIpTfX2KJiV//uCyNfePa7ooorCepZ8sZNDe01UaomJt/V28pVoDyvzVpJSkqKUb0i4ATeLmsJjXOU3WWx8seYA/126l0azI5T+9lFdTlo2j7aQJInIXr7sWlsIQM7O8qP0aInbwIFU//Y7AMa9+7BUVqLxcU4TOqSLn130N4UodSWNJVQ2VeLjcuSUogKBoHMgRP/ZxYNAKHARMPTgT3OMwHWyLLfc0AXIsvy7JEkPA68BEcAnrTR7R5bl/3bckAWCjkWWZV7b+Bpz981V6gIMAXw29jOC3ezOxGv2lnHb/zZT32wf9pjuAXx4Vb8WDu2N27ZR8MgjjgqtlvD3/os2KopFn6Q5GSv5BLsy7SQLoYaaaua/9YqTuZdW78LUBx4jJqnfSXtfgR03vYahcf4MPRjia7XJ7C2pZXNWJVuy7T95lQ0cj89frdHCzoKaFtkEwO4xkRThTVKEN8mRPiSFe+PVzvRlyjVcvBkRPoIR4SNIc1vC3x+/C4DWqmJiWjQrR9exIrGQCVtkpv9rw/3g7gCduZbBG99mW+Ld1HnYV5vLcuv4+tXlXHBnV+JCYo79ZgUtkGWZpV98ROFexz7qrgOHMnjmZadxVK1jcPdgyMVXsPybzwAoy8kibfk/JJ4//piu01Rv5s+PdmBqcnwWj7y8GyFx3sd0ndzaXJ5c+6RS9nXx5coeV1L5v2Nb5V+3v4yn5+10cuoHewTY7aOO5nN88ojo5aeI/urSRqpLG/AKaP8EhGs/5++GxpRteJw3xqluSKwfX6w5gLVZ2j6wh/gPCjmzJp0EAsGxI0T/WcRBY72LJUm6DLgZSAY8gWLgH+ANWZZ3HeUab0qStAq4DxgJBAI1wAbgPVmW/zp5dyAQnDjvpbzHD7sdjtI+eh8+G/cZEZ52sbJgRwH3/7wNs9Whyi7sG8ZrFyW2MGcy5eaSO+tOZKMjn3voSy/iOmAAy75JJ2uHw8HfK8DA9PuScfVs6QDfUZTn5TDn9eepLnbkbzd4enHhI88QHCfSKp0O1CqJHsGe9Aj2VBy9rTaZqgYT5fUmymqNlNWbKK8zUl5norzeSGmt/bWouomimqbmdgxHpKrBzIo9pazY4wiyivV3IynSm+QIb5IifOgR4tFug7GEMWMpzcli65/2EG1NjZkbMgcw7J5Z7LggjRVZG3D7fSmDVpfiagSduZ7k7e+yLfEuaj2j7fdZpuHH19ezbdCj9I9JYlTEKAYEDUCrFqv/x8P2JYtIW75YKfuFRzJh1n1IqjPTc7nPuEmk/L2AqiK7GF33y3f0GDoCnaF9YtRmk1nyxU6qSxzbq3qPCiN+xNEyBzvTYG7g3uX3Um107E+5O/luXMyQ185V/pKaJl5cmM4f21vaIV3cL5zHJ/U8qSk7j0ZETx8klYR8cDYxZ2cFvUe3X/RrQkPRBAVhKbbv2mxM2dpC9A+M9UUlgc3sg2zVI6nt33tC9AsEZwdC9HcCZFkefYztfwZ+PoH32wicnpxAAsEJ8Hnq53yW+plS9tB68PHYj+nibV+h+d/6LJ7+Y6eTyLptZCyPTuzRYvXHWl1N7m23Y22W3sj/rrvwmjaNtb/vY/e/DuHt4evC9PuTcfM+eXmbD2zbwoJ3XnNy6PcNDWfGI0/jExx60t5XcOyoVRJ+7nr83PV0C/Jos22T2UpeZSM5FfXklDeQXdHgeK1owHQwP3drZJbVk1lWz+yt+YB9z3GfcG/6RfvQP8qHflE+LbaqNGfU1TdSnpdD9g57SHRO2g78Zi9kwg23MSFmAox5htKiA2R8/B/c565E19RI8vb32J44i2ov+/8p38ZgBq2Zyeya9/lh9w+4a90ZHjac0RGjGR42XPHPELRN3q40ln/tCK7Tu7kx/eEn2y2gTwdqjZaRV9/IH2++BEB9VSWb/vidYZddc9S+siyz9re95DSLlArr7s2wS7se0xhkWebJtU86pZabGTeTi7peRMVXXx91ld9itfHN+mzeXpJB3WHbdHoEe/DijAT6R/tyutG7agmK9qQo0z6xkbOrgt6jw9vdX5IkDMnJ1P5lX7dpSElp0cbTRUvvMC+251VjMwajds0GYE+FcPAXCM4GhOgXCARnBd+nf8+7W99VygaNgQ8v+JBefvaEE4tSC3lq3k6nPo9P6sGtI1uGbMomE3n33IspM1Op85w2Ff87Z7F1cTbbljhSVLm4a5l2b9Ix7z9tL7Isk/LXAlZ88xmy7BCAUYnJTLnvEZGSr5PjolUTF+hOXGDLf0ebTaak1sjeklq25VSRklvFttwqKpr5UDTHaLGxMauCjVkOIRUX6K5MAPSP9iXaz1URPiq1min3PsL3T9yvrNam/DUf/8goEs+fAEBAcAwBz76P5d5Kyr/+mvJvv6XPjg/Y0ft2qrzt0SVulkCu3XgPK6LfJz2ikr+y/uKvrL9QS2r6BfVjdMRoRkeMJsLjzDCiO9MozT7AvP+8hM1qD3GXJBVT7vm/TjGZF9d/MOE9E5TtRpsXzKX3+RPw9A9os9+GPzLZsSxPKXv4uTD+lgTUx5jl4rPUz1iSvUQpJwYk8uTgJ5EbGyk/yir/5qwKnpyb5pS5BcBdr+GBsd24dkhUh2fdOBEi430V0Z+3pxKrxYZa0/7xufZ1iP6m1DRkkwlJ5zwpOLiLH9vzqrE2E/3CwV8gODuQ5PbEFQoEZxCSJMUDyobmtLQ04uPj2+ghONuZs3cOT697WinrVDo+uOADBocMBiCztI5p769VVnI0KonXL07kwr4tV0pkWabwiSepnu3IWunavz8RX37Bns1lLPt2t1Kv1auZ8UAygVGeJ+W+rBYLy7/+hO1LFjnVJ42fwpjrbkGlFin5zjVkWSa3opGU3EpSDk4E7Cqodtqu0hb+7jr6RvowpIsf4+KDCfM2UJ6Xyw9PPoCp0R5mrVJruOSpFwnvmdCiv6Wykoovv6T0x1/ZHnsNlb4ON3OXxjL0Fe8yd1A1eyJa7puO845jdMRoRoWPord/b9QipSTl+bn8/OyjNNY4QtNHXnUDA6ZddBpHdWwUZ+7ju8fuU8q9Roxh4l0PHrH9poUH2Dj/gFLW6tVc+HA//MOPbQJzZe5K7l52N/JBB8AAQwD/m/AD2Lyo+vorVB+/p7Tdds9zZEX3pqrBTFWjifI6E5uzK1tcc3pSKE9M6kmg58mZxD0RirNq+O1VhyXT9PuTCe/efoO9xtRUsi65VClH//wThj59nNqs2FPC9V9tQuv9Ly4hcwH79+mGqzagUYl1wp07d5KQ4PS5mCDL8s4jtRcIziSE6Bd0OoToFzRnWc4y7l9xP7aDq+AaScPbY95mdMRoABpMFmZ+sI49xY7VnHcuS2JGcuv7Rqtmz6Hw8ceVsi46muiffiQn28yijx3pm1Qaial39SG8x8kJ/Wysq2XB26+Qk7ZDqZNUKs67/jaSxk8+Ke8p6JwYLVZ2FdSwNaeKLdkVbM6qpKTWePSOQEKYJ+N7BZMkFbDx0zc59Adu8PTi6pffxjMgsNV+looKSj77klUpBsq9mwv/Uvpue4f9QVXMHqoiNVqy5yw8DG+9N8PChjEybCTDwoadk9sAqooK+fnZR6hr5tTf+/zxjL2lfSnlziQWvf8fdq1erpSvevltgru0DNXf+nc26+c4UvNpdCqm3pNE6DEa92VWZ3LVwquoM9sN91Ro6GJ5mF1ZPsiNjXy15BV8jPZz6T5RPDDyrlb/Dg8RF+jO89PjGdrl2FLhnUpsNpmvHl5DU70ZgL7jIxkyM67d/WWzmT0DBiI32R06Ax95BL8brndqU2+0kPjcYmR9Fm7RHyn1c6fPVbbJncsI0S/ozJw5cUsCgUBwjOws28mjqx9VBL+ExMsjXlYEvyzLPDEnzUnwXzck6oiC35h5gKIXXlDKai8vIj79hOJSmb8/a+YFIMHYG+JPmuCvKMjjxycfdBL8ejc3LnrseSH4BS3Qa9QkR/pw0/AYPryqHxseP5/V/zeGty/rw1WDIukR7HFEvZOWX8N/lmRwzeI60sNGKPWNNdXMffNFzAcFwuFofH0JfeQhZr5zCcGGKqW+yRBASp97iSvy4qmfbLz7gwsD94J02AJDlbGKhZkLeWT1I4z8eSTXLbqOL1K/YG/lXs6FxYiashJ+eeFxJ8Hfa8QYxt58Z6cT/ADDLr8Wjc7habLyf1+0+HfcvjTXSfCrtSomz0o8JsEvyzLb8wu5YeEsRfAD1BdMZ+teL5rMNiYfWK8IfoDveow7ouA3aNU8OrEHf94z4owW/AAqlUREL8d3TvbOijZat0TSajH07q2UG1vZ1++m1xAf6omtFQd/gUDQuRGxOgKBoFNSWFfIXcvuotHicH5+ashTTIyZqJS/35DDnJR8pZwU4c0Tk3u1ej2byUT+gw8iNzquF/LqK9SofFj4wVaszQzVRl3Rnbh+ra+AnijZO7Yx/51XMNY7kqX7hIQy4/+exje0/cZNgnMXSZKI8HUlwteVmcn2v5nqRjMpOZVsza7k38wKNmdXtEgr+I+mF5JbIT3q7aZopVmZfPfGq1z7+NNH3GutDw5kxuszWPjeVnIz7KkGG10DSUm6l+Rt7xCSU8NDOWCMCmbtBcF8H3KAWmu90zVsso2tJVvZWrKVd7a+Q4hbCCPDRzI+ejz9g/p3ShHcFnUV5fz6/BPUljkyMXQbPJzxd5y5Tv1Hw9M/gP5TZvDvbLuHcF56Gvs2/0vXAUMASFuVz5pfHWZ7Ko3EpNt7H3Xi1GaTySyrY2tOFev3l7N2fwm1np+h8XB8rpsqhmCpHgCA3mLk4n0rlHPpPlHsjehFuJsOb1ct3gYdXq5avA1aQr0NzEwOI9Tb0FG/hpNOZC9f9m6yO/CX59VRX23Ezav9BrKGvn1p2LQJgIaUrciy3OL/14BoX3bkVWMz+aLS2ScWMioznL5bBQJB50OIfoFA0OmoM9Uxa+ksyhodKfNu7n0zl3S7RClvz63i+fmODJU+rlo+vKovuiMYH5W88SbG9HRH+2uvwZYwiD/e2OqUQ3rQtBgSRh5bSqn2YGyoZ92vP5Dy13xkm2OCISI+kakPPIbBvW0XeIGgLbwMWkZ3D2R0d/tkVXmdkaXpJfy9s4jV+8rsWQIkiWX+o/ExVxFksgvSirTN3HPvU/S88DouGxBFgEdLgaHWqph0dzJ/fpRK7kE39gbXIFL63Evy9nfRm2rQZxdx3hdFjI+MpOaKS1je08rKojUcqD7Q4nqF9YX8vOdnft7zM5EekczsOpMZcTPwN5zZK7HtoaG6il9feIKq4kKlLrbfQCbd/VCn9+gYMP1iUpctpr7Kvld+1XdfEps8gD0bSlj5g8MBXqWSmHBrbyLj/Vpco6LexLbcSifjytomh6u+LuBv9B4OXxVLfQzG4ikYtGoGxPhyaeZKp1X+8159nAtHjTwZt3taaL7SD5C7q4IeQ0La3d+QnKQcW0vLMOfnowt3nkweEO3DF2sOYDUGK6JfOPgLBJ0fsadf0OkQe/rPbcw2M3ctvYt1BeuUugnRE3ht5GuoJLugr6w3MeW9NeRX2VftJQm+vXEgI7q27ihdu2w5ebNmKWV9z54EfvYtc97ZQU2ZI7w5cUw4wy/t2qErj7LNxq7Vy1n1/Vc0VFc5nUs8fwLn3Xg7ao2YnxWcPOqMFlbuKeXvnUUs312Crb6Kywp+x83qSA+5x60rK4LOY2xCGFcOimRIrB8q1WHpz0xWFn64g7zdDoM0N2MJyZv/g65ZKDaANioS/zvuoGZUEquL1rI6bzUbizZitplbHaNaUjMqfBQXdbuIoaFDO6WpWGNdLb8+9xilOVlKXVRiMjMefgqN7sipFTsTO5b+zZJPHQZ6fafczq51rhz02kNSSYy/JZ4uyYHIskxqfjVbsysVgZ9d3nCEK4PGIxVD+PeOss2XS0Le5PxusSRH+qAxNbFv7DglTZ+hTx+ifvrxrIsU+fmljZTl2v8/de0fyLibWxpuHglrVRUZg4co5dDXX8Nr2jSnNmV1Rvq/+A86/yXoA5YCEOQaxD+X/NMBo+/ciD39gs5M5/vWFAgE5yyyLPPyhpedBH9SQBIvDn9REfw2m8x9P29TBD/A/Rd0O6LgNxcXOxn3Sa6u+L/0Ogs+3uUk+LsOCGL4JR0r+Isz97H0q48pzNjtVK9Sqxl19Y0kT5x21j2wCs483PUaJieGMDkxBJPFxrr9ZSxd5YFp2efobPb0gN3r96IvNLLIOo6FqYVE+7lyxcBILu4Xjp+7ffVfo1MzaVYiCz/YTv6eKgDq9YGkjnuJvmkfIGU79gWbs3MofPQxdNHRTLlzFldO+oBGm5F/C/9lVd4qluYspcpYpbS3ylaW5S5jWe4yAl0DmRk3k5ldZxLm3vFRNycDY0M9v7/0tJPgj+jVm+kPPXHWCH6AhDEXsOmP35QUkNv+WoDOw+4YL0kw9oZexCYFsGRXMe/8k8HOgpp2XVftUoRr2G+H5g7Qq13435SP6ennMJEsfvM9RfAD+N/V+QwR20NkL19F9OekV2CzyS0m4I6E2tsbXZcumPbbvRUaUlJaiH5/dz2xAW7kNDkiCIobiqk2Vp+ThpsCwdlC59w8JhAIzkm+3vk1v2X8ppTD3cN597x30asdIcfvLdvHygzHXtnR3QO4a0zrDsey1UrBQw9jrapS6gIef5Kli2ooz3OsTEbG+3L+dT2R2vlgdTQaa2v45/MP+O7x+1sI/sjeSVz7xvv0nTT9rHxgFZzZ6DQqRncP5IVbJnHdi6+jcXOko4xuzGF60QJ0ViNZ5Q28smg3Q15Zxt0/prBufxk2m4xWp2byrD6EdvVW+lXXa9gx/HF8X3wNXXS00/uZsrIoePj/yJw6DfPfyxkTNopnhz7L0kuW8uaoNxkSMoTDKWko4ZMdnzDx94ncuvhWFmctPmKEwJmAqamR2a88S3GmY097SLcezHjkabT6My813ImgUqnpM3aSUrZZ8rBZy0CCMdf0IMsNpry3hlu+3dym4A/w0DOuVxD/N6E7n17fg7iEX5ElR0aK54c+5yT4K3/5hYqvv1bKhj59cBs+rGNv7gwhspdjW4Sx3kJpdm0brVvSPMS/cWtLMz+AgdG+WJuEmZ9AcDYhVvoFAkGnYHHWYt7a8pZS9tR58uEFH+Lr4tjjuDKjlHeWOh5MwrwNvHNZ0hFXQco++UQxNQLwnDKFNHMvCvY6TKKCYjyZcGtv1EfwAjgWbDYrqUsXs+anb2mqc35Q8/APYMy1txA3cIgQ+4IzgtAucVz78pv89uJT1JTazcNCjUVcVDSPeUFTaNC4YrLamL+9gPnbCwjxcmFy7xCm9gll8qzeLPhgB4X77Pnny/PrWaEKZtrPszGtWEzphx9izs5R3suUmUnBQw9R9tFHBNw5C48JExgfPZ7x0ePJq81j7r65zNk3h5KGEqWPjMz6wvWsL1xPoGsgl3W/jIu6XoSfoeVe8dOF2WRk7usvUJDh8AsJio3joseeQ+fSeQzkjgU3vyTsj5f2vfhW43aCx17NQ5v3tyr09RoVvcO8SIrwJjnSh6RIb0K9XJAkibSyNB5e+TAF9Y7P5Bvib2BSrGNioX7dOoqed2RdkVxdCX7u2bP2czS4ixdavRqz0e41k7OrnKAYz6P0cuCa3Jfq334HwJiRgbWuDrW7u1Ob/tG+/LTJF9mmQ1LZo30yKjMYEDygg+5CIBCcasSefkGnQ+zpP/fYUbqDG/++EaPVvtKjUWn4dOynTg8g+VWNTP7vaqoa7Ct+OrWK3+4YQmK4d6vXbNi6leyrr4GDpnnayEiMj37Mil8cxmLeQa5c9HA/XNy1J3wPBRnpLP3yY0oO7HeqV2u1DJh2EQOnX3zWrfoJzg7qKsr5/eWnKcvNVuqaDD787DeJGm3rYiPS15UpPYMI2V5LTZ7DrT8g0oNp9yah10tUz19A2UcfYc7JadFf3zUO/1mz8Bg3DumgwZ3FZmFdwTp+z/idlXkrscrWFv20Ki0ToidwZc8rSfBv/17nk4GxoZ75b79K9g7Haqp/ZDSXPv0yBo/2i7RDyLJMeX49+XsqaawzYTHaMJutWExWLEYbFpMVs8mKxeQ4dnHTEtHTl6gEP4K7eB0xC0NHUJpby/o5+8ndVYG5/m+sJvtWZ5tKy6cR12JWOW9jCPLUM2t0HJcNiMBF62xiKMsy/9v1P97e+jYWm8PIb2joUD48/0PUKnt74/79ZF1+Bbbag5OoKhXhH7yPx5gxJ+0+zwQWfriDrB12I9vgWC8u+r9+7e5rzDxA5iTHpEnE55/jflhURE55AyPfWI5r1IeoXe3/Py/seiHPDX2uA0bfeRF7+gWdGSH6BZ0OIfrPLfJq87jqz6uoaHLkJH5p+EtM6+LYh2i0WLn0k3/Znlul1L08szdXDops9ZrW6moyZ87EUnDQQVujwe2db1g4txqbxf6ZqHNRc/Gj/fEJdjuh8RsbGlj9w1dsX7KoxbnYfgMZc+0teAe3331ZIDgdNNbVMue155y2o+g9vakbfSO/ZFqpqDe12k8nwzVGA74Oewx8Q92YeFtvvINckc1mqv+Ybxf/eXkt+0dH43fLLXhNm4qkdUy+lTWWMW/fPH7N+JX8uvwW/QAS/RO5vMfljI8ej059avfNl+fnMu/Nl6gscNyTb2g4lz7zCm7ePu2+jqnJQt7uSrLTyslOK6e+ynj0TkdA56ImoqcvkQl+RMX74ebd/lRvbVFT1siGPzLJ2Fis1NksxZhqHaZ7K/xGkOppF0ttiX2AqqYqnlz7JCvzVjrVDwoZxFuj38JTZ58wsVRUkHXpZU5/N0GPPYrvddd1yH2dyaStzGPlj/aoNkmCG98cgYtb+yanZVlm75ChyrY2/zvvJODuu1q0GfzKUqpcf0TnsxGAeL94fpryU8fdRCdEiH5BZ0aIfkGnQ4j+c4dqYzXXLrqWzOpMpe6OPncwK2mWU7un5qbxv38dq5AX9g3jP5f0aTW8U5Zl8u+5l9olS5Q6z/seYUlWV6cH6kmzEolJPLEUYfu3bOCfzz+krqLcqd47KIQx199KbF8RKinoPJibmvjjrZfJ2r5VqdO7uTH1oafJVAUwf3sBi3cVU2e0OPXTyXBpnZ4Qq2OVWdKqSLo4lkEjIlCrJGSzmaq5cyn/6GPMBQUt3lsTGoLfjTfhffFFqFwcETFWm5U1+Wv4YfcPTgafzfFz8ePibhdzSbdLCHILOtFfw1HZv2UDf773JqZGh5mod1AIlz77Ch6+bX+myLJMZVGDIvIL91Vhs56c5zT/CHei4v2ISvAjKMYT1TFGATTWmdjyZzapq/KUyVLlnCRTW/sDnmb7RECF1od/el7LrDFdjyj2AbYUb+GRVY9Q3OCYQFBJKu5MupObEm5SVvhtRiM5N9xI41bH36L3FZcT/PTTZ21Yf3OqSxv57qn1Snn8LQnE9Qtsd//cO2ZRt3w5AG5DhxD55Zct2tz5w1YW587GJXgeAHq1ng1XblD+Dc5FhOgXdGaE6Bd0OoToPzcwW83c8c8dbCjaoNRNiZ3Cy8Nfdnqom7ctn3t/2qaUewR7MGfWMAy61h9MKn/6iaJnHSGKhuEj2NrjNmXvMcCAKTEMnBJz3GNvqK5i2defsmfdKqd6jU7P4Asvo9/kGWeVY7fg3MFqMbPo/bfYs361UqfR6Zn24OPEJPWjyWxlxZ5S5u8oYGl6MU1m+/YZvQ0urtcTanUWlltcrdR3cyMxwpve4d70DnTFe9XflH/2easr/2o/P3yvvw6fK65osQ/5QPUBftr9E/P2z6PeXN+ir4REcmAy46LHcX7k+QS7BbdocyLINhv/zv6Zdb9+71Qf3iuBqfc9iquXd6v9LCYreXscq/m15U2ttjuEWqPCO8iARqdGo1Oj1avR6FT2Y60Kjd5er9GqKMurI2dXOcZ6S5vX1Lmo8Y/wwC/cHf+DP76hbmhaEedmk5Udy3LZ+lc2pibnLRYWSWaLzsIGvYXohgzGlS5Vzk1//AXi+iS3+v5Wm5XPUz/nw+0fYpNtSn2gayCvjXiN/sH9lTpZlil4+P+oWbBAqXMbNoyITz5GOofSm3739HqqS+wTSz2HhXDeNT2P0sNB2WefUfofu0eOytWVbps2KttoDvHNuiyeX7IQ1+iPlbo/ZvxBjNfxfzd2doToF3RmhOgXdDqE6D/7kWWZJ9c+yR/7/1Dq+gb25bNxnzmF6e4rqWPa+2toMNkfPD30Gv64ezgx/q2H5DdlZJB1yaXIRvuKvtrfn4Kb32fnv46V+Jg+/ky8rfdxOfXLsszuNStY9s1nNNU6G1ZF9k5i3K134RXYsUJDIDjV2GxWln35CduX/KnUqdRqzr/xDnqfP16ZlKs3Wli6u4T52wtYuacUq8XGmEYtySZnYZalsbLA1UTjwfkATxcNiaHuTC5JJWHFXDR52RyOytMT36uvwueaa9D4OIfL15nqmJ85nx93/8iB6gMt+h4iMSCRsZFjuSDqAsI9wo/31wGAqbGBRR+8xb5N/zrVJ0+YyqhrbkJ9mBitrWgiO7WMrLRy8nZXYjXbaAsPPxeiE/yITPAjrLsP2iNMaraGzSZTklWjTCqU5rTP7V1SSfgEu+If7o5fuDsB4R7UVjSxcX4m9dWHbeeQIE1nYbXeTN3Bf8dgNzWX7vsauelgTvlBQ5n2wOMcTlljGY+ufpQNhRuc6keGj+TFYS/i4+L871v6/geUvf++UtZ3jSPqhx9Qe3i0677OFlb9lEHqCvvEmJu3nuteGdruKIeGzZvtnjYHiZkzG5eezpMGuwpqmPT+Ejy6P6vUvTHqDSZETzjxwXdShOgXdGaE6Bd0OoToP/v5YNsHfLzdsboQ5RnFdxO/w9vFW6lrNFmZ8cFa9hQ7HmA/vrovExJa3x9va2oi65JLMO7dp9QZH/uEtesdK2DeQa5c8mh/dIZjXy2qKSvhn88+4MC2LU71ejc3Rl9zM/GjLzgnwk4F5wayLLPu1+/593fnPb5d+g9m3G134+rpnM+7utHMkl3FrN1XRvWuShKLbWhx/H+okWzMczNRpHF+JpFkG0MKd3Jd5nIiy1oa/kmurnhfeCFeM2fg0quX0/8xWba7+/+4+0dW5q5E5sjPOz19ezIuehwXRF5AtFf0sfwqqCzMZ96bL1Ge5xifWqPhgpvvJGHMWABsVhtFB2rITi0nK7WMioKWkQjNUaklQrt6E5VgD7/3DnLtsM+P+mojOTsryE4rJze9AlNj21EAR72en5afTbWUqx2/37G9gvjPpX3YPvt7Ns6zp1mVVCpuef9LPPwcWxzWFazjsdWPOXm2aCQN9/W7j2t7Xdvinqvnz6fg4f9Tymo/P6J//hldeNgJ3UNnJCu1jIUf7FDKlz81EL8w9zZ6OLA1NbFnwEAw241vg55+Ct8rr3RqY7XJJD2/GFvYS6h0lQDc0vsW7ul7TwfdQedDiH5BZ0aIfkGnQ4j+s5vZe2fzzLpnlLKP3ofvJn1HpKezKd///badXzY7wn9vGBbNM1OP/HdQ8tbblH/6qVKWrr6bFUW9sFoOuve7qLnkOIz7ZJuNbUv+ZPUP32BuanQ613XgUM678XbcfXyP0Fsg6Nxs/XMey7/5zKnOzduHCXfcR3TSkR3Fs/dVsviznZiarRhbkFlqMLNDZ4XD9a0s07ckg8szltK7PJPW0HftiteMGXhOnYI20Hl/c3F9Mf/k/MM/2f+wpXhLmxMAcd5xDA4ZzJDQIfQL6oeb9sifCQdSNrPwv29gbHCIeHdfP6Y9+DiB0V3JTi1n39YScnaWY2xoW1y7eesVkR/ewwedy8kPVbdZbRRl1lB8oIay/FrKcuuoLGpAth392dA7wp2FUiPrauqUOpUED43vzu0ju6BSSdSUlvD53TcjHwzZH3zRFQy79CoyqzP5MvVL/tj/h9O/RZh7GG+MfIPeAb1bvF/D1q3kXHc98kGhKul0RH37DYakpBP8LXROzEYrnz+4SvFTGHpRHMljWzevbY0Dl11G03b7pIHnlCmEvflGizbXf7WRf+vfROthTzk5Onw0753/XgeMvnMiRL+gMyNEv6DTIUT/2cua/DXctfQuJRWXi9qFz8d/Tp+APk7tft+Sx4O/blfKfSK8+fW2Ieg0rRtRNaWnc+DiS8Bqv67UewD/drmV+iqH4Jh0R29i+gQc03irigr566O3yd+9y6ne1cub82+6g26Dhh2hp0Bw9nBg2xb++vBtGqqrnOqTJ05lxJXXo9W17hLfVG/mn693kZ3qbHRJjBs7AlVsya+mrK6lW318+QEuy1jKgOLdLc4BoFLhNnwY3jNn4n7eeaj0zu9f1ljGspxlLMlewqaiTa2m/juERtKQ4J/AoJBBDAoZRJ+APujUOmRZZuO831jz07fQ7DkqtFtPhl9xD1lpjWRsLKapznzEayNBcIwnUb39ie7th1+Y+xkRDWQxW6ksbKAszz4JUJZn/zkUEeAd5IprPz+e3pJJbTPTRl83Hf+9PJnhXZ3NCue+8QL7N9tD93WeHuy/LJBl+ctbTLyMjRrLs0OfVdz5m2PKzSXr0suwVlYqdWFv/QfPZqnnzkXmvZNC3m777yS8hw/T72vdM6E1il99jYqvvwZAGxZG3NJ/WrT5YPk+3t36Hnr/ZQCEuIWw+OLFJz7wTooQ/YLOjBD9gk6HEP1nJ+nl6Vz/1/U0WBoAu+nW22Pe5vzI853aZRTXMv39tTSa7Q/qni4aFt4zgghf11avK1ssZF12OU07D+aM1urYfekHFOU7BP+AydEMnBp7TOMtztzH7y8/TeNhe/fjR1/A6GtuxsW9fWGWAsHZQENNNYs/+a8i7g7hFx7JpLsfIjC69f9fsk1m86IsNi44QHMN6B/hzvib46nRSGzJqWBLdiVbsqvYU1TDoUXoLlX5TMtczYj8HRisracMtLm54zVpIr4XzsSQlNRCVFc1VbE8dzlLspewvnC9U0741nBRuzDIkEi37WrMe5yzDIT3GoGsGkl5fuMReoPeVUNEL1+ie/sTGe+Lwb1zGHrKskxtRRMmo5VvduTx3or9Tuf7hHvx4dX9CPM2tOh7YNsWZr/iiN5akVRKVmiDUtapdDwy8BEu6XZJq5Me1qoqsq68ClOmI8Ij4L578b/99o64tU5NyuIc1s22b1lTaSRuenNEuyNEav5eTP699yrluJUr0QY5R8hsyqrgiu8/xRDuMKdce8XaVidmzgWE6Bd0ZoToF3Q6hOg/+yioK+CqP6+irLFMqXts4GNc2dN5j2G90cL0D9ayr8QRTvrZtf0Z2+vIabjKv/yKktdfV8o5M59jX6VjJSo60Z9Jtx+bcV/erjTmvP6cU0ouz4Agxt56F9GJ7V9pEQjOJmRZJnXZ3yz/5jMsRscKvVqjYfjl19Jv8gwkVevRONk7y1ny5U4nl3lJsv//7D0qnPAePkgqidomM9tzq+2TADmVbM2uxFJfz9CCNC7I3Uyf0n2ojhC63+gfjHrESCInj8d70AAkrXNe8xpTDavyVrG+YD3/Fv5LSUOJ03m3RjV99nkRl+eOSm7mHSCp0LqNQaN1jkg6hIefC3F9A4lO9CM41uuYU+OdKVTWm7j3522syih1qr9iYCTPTO3VIg2f1WZlSc4SvtzxBT3m1ODVYP99F/k08deQYrQqLTPiZnBD/A1EeEa0eD9ZlqlZsJDi117DWub4bvCaPp2QV185I6IiTjflBXX89PxGpXwsqWbNJSXsGzlKKYe98w6eE8Y7tTFarCS+9D26aEfo/9cTvqZf0JG37pzNCNEv6MwI0S/odAjRf3ZRbazm2kXXklntWMW5Pv56Huz/oFM7WZZ58JftzE7JV+puGRHDE5N7HfHaptxcMqdOQ26yp8AqTZhMqr8jHNQ7yJWLH+2P/hiM+zK3bmL+W69gMTtWFnuOGMPYm+9E2yx/uEBwrlJRkM+f771JceZep/rIhD5MuPP+I+aqrylr5K9P01p1l/cOciVhZBjdBwfj4uYQ62arjZScKlZllLJqbymFGVmcn7uF83M2E15f1uI6h2jUGSjpkYRm2Ahip4wjJja0hQlgVk0WGwo3sGnvWhrXphOdpUctHyY0JTd07lNRaUKdqlVaiE0OIGFYOKFdvY8rG8iZgtUmM3trHm8u3kNxjWMyR6dR8eKMBC7t7yzYjVYjf+z/g6/Tvian1m5u2OuABwPTHd4m0g2DuGbk7QS4tr6lyph5gKIXnqdhvXM2BNf+/Yn48gtUIuUpYP87/fbxddRV2v9dEkaGMerK7u3uv++CsUpqTN/rriXoscdatLn44zXs1t+DpLJvVWltQv5cQYh+QWfm3EloKhAIzjhMVhP3Lb/PSfBPiJ7A/f3ub9H2l825ToK/b6Q3/zehxxGvLcsyRc88owj+OrdQdgVNgoPbd7Uuaibd0fuYBH/66uX89dE72KyOPcB9J05j9LU3H3EFUyA41/ANDeOKF95g/W8/snHur4qJW07adr596C6GXHIl8aPOR+/qbJDn6W/gwof7svbXfexcnd98qzxVxQ2s+XUv/87dT7eBQSSMCicg0gOtWsXAGF8Gxvjy0PjulNcNYM2+MSzaU0LBus3037OOUXnbcLc0Ob2XwdRI1I71sGM9DR+9wdyAGIp69Uc7fCTdB/Wmf7QfgbI3Qf/WEPFPHlbz4RN6EmpdPBrDUCSVYytPoUcmewI2sN8/BUkr0y+7H0PNQ+nq05Vwj3BC3ULRqrV0FtbsLeOlP9NJL3TexhTuY+Djq/uREGbP0mCTbWwp3sKCzAUszlpMnbnOqf2+8Hr6ZvigsdonPxLzfFsV/LamJso//ZTyzz5XDPsO4TZ8OGFvviEEfzMkSSIywY9dq+1bTbLTypFlud1REIa+yYrob0jZ1mqbgdH+7MoKRm3IBSCjMuPEBy4QCE45YqVf0OkQK/1nBzbZxqOrHmVR1iKlrl9QPz4Z+wl6tbPxVnphDTM+WIvxoNO+j6uWhfeMILSV/aOHqJozl8KDqxZWlZat571ErcUhMibe3pvYpPYb96X8vYBlX37sVDf00qsYfOHlIsxUIDgCeelpLPrgLWpKnUPlNXo9PYeNos/YSQTFxrXoV1vRxK41BexcU0BjTev79YNiPOk9OpwufQPQaFvmrbfZZNKLalizs4DiJUvx37GRvgW78DK1nS4v18OXnWEhWPUmJGyHnZVQ6XqicRmESm3PH290qWOn3zr2BGyk2lDa8oJOvSWC3YIJ9wgn3D3c6TXMPQwfFx9U0umfQNxTVMsri9JZsafl/YzqFsA7lyXh46YjszqTBfsXsDBzIQX1Ba1cye7If0P8DXguL2DXiqUAaPUu3PbxN04TP3WrV1P0/AuYc3Od+msCAgh6/DE8JkwQn7WtkLmtlEUfpyrlK54ZhG9I+7LQVP74I0XPPW8vaDR037QRlcH5e3X5nhJuX/QoOp9NAHTzjuf36T8dfqlzArHSL+jMiJV+gUBwWnhn6ztOgj/GK4Z3x7zbQvDXGS3c+f1WRfADvHVZUpuC31JWRvGrryrlzIQrnQR/3/FR7Rb8siyzYfbPrP3lO6f68264jeQJU9t1DYHgXCW8ZwLXvv4eS7/8mPTVy5V6i9FI6rLFpC5bTHBcN5LGTabbkOGK07+HrwuDpsXSf1I0mSmlpK7Mo3BftdO1iw/UUHxgF8u+lfAPdycw2pOgaE8Coz3xCXJFpZKID/UiPtQLxvbEapPJKKgiY8W/NK5aSUDqJkIrC5CBep2WGlcdVa4u5Pp6YlM3tcgaqNJ2R2MYgkrti0olEZPkT69hoYT39KXCOJR/C/9lXf461hWso7zpsIwEB5GRKawvpLC+kE1sanFeQsJd646n3hMPnQeeutZfg1yDiPCMINw9HFdt6yamx0NJTRNv/5PBz5tyOTxrX6SvK49O7MHALloWZv3C/Mz57Crf1fqFgG4+3bgp4SbGRY9Do9JQ4pKpiH6zsYmdK5fRd+JUzMXFFL/8CrV//+18AZUKn6uuIuDee1ALY9QjEt7DB5Vawma1/4Pl7Cxvt+g39O3rKFgsNKWl4TpggFObflE+yKZgpXygeh9WmxW1quVEm0AgOHMRol8gEJxyftz9I1+lfaWU/Vz8+OiCj/DSezm1k2WZx2anklnmWJm7Y3QXxnR3dhg+nOKXX8FWbRcIZX4J5PoOVM4FRnkwcFpMu8Yp22ys/O4Ltiycp9RJKhUTZ91PzxFj2nUNgeBcR+/qxqS7HqTboGFsmj+bgj3OQrFoXwZ/7ctgxTefET/6AvqMnYhPSBgAao2KrgOC6DogiLK8OtJW5bNnQxEWo2OLjc0qU5JdS0l2LWkr7VuAtC5qAqM8lEmAoGhPDB46Itx06OOjKDYMo7RHCOuy9lJTmoetDdd+lTYOjWEoKrU/+qYKPAv+oZQKdrl0o8Yjkf7efYkJ9WNK7BSmxE5BlmUyKjNYV2CfANheup1Gy5Ed/ZsjI1NrrqXW3NLX4EgEGgIJ9wgn0jOSSI9IIjwj7K8eEXjoPNp1jQaThc9WHeCTVftpMDVPYWjD072e6QO1dAktZ0HRrzyesu6IaQ699d5MiJ7A1C5T6e3f22llPjA6ltBuPSnIsOd83754AVHF5ZT99z1sDQ1O13FJTCT4macxiCi+o6Jz0RAS503+Hnvqvuy0cpIuiGxXX31cHCp3d2x19u0YDVtTWoh+Txct4a5xHIr5MMtG8uryiPKM6rB7EAgEJx8h+gUCwSllafZSXt3oWIU3aAx8cMEHhLmHtWj7/YYc5m93hIwOjPblwbHd2rx+7fLl1Pz5JwBGnSe7e9+onNPo1Yy9KR51O9yzbVYriz95j50rHbmLNVodU+5/hC79Bh21v0AgcCZuwGDiBgymNPsA25csYtfq5ZibHGK4qb6OLQvnsmXhXCJ7JxEUG4dO74LOYEBrMKBzMRDV00B0vA/5GfXsT6mkpswKshVZNoJsRMYEshGL0UT2diNZ2+xlWTYiWyuQreUoxh5HQaWNReNiF/t+5TsJK/gFv4pdSIeyA+xfCX9CAxIrvAIxRsbg3asHsQP7EN2rO916XssNCTcgyzIVTRXk1eWRX5tPXl0eebV5ymtRfVGLnPXHQkljCSWNJWwt2drinKfOk0DXQPwN/k6vAYYAAlwDsJg82H7Ayier9lNuykelL0XnWYpKV4paX4rWpQwrJuYWAoWtv79OpWN0xGimxE5heNjwNj0L+oybpIj+ioJ8dq3+L/4Njr8BlacngQ/cj/cllyCpxUpye4mK91NEf8G+KkxNlnal7pPUagx9+lC/di0AjSkprbYbFNaLBc1sHTIqM4ToFwg6GUL0CwSCU8bfWX/z6KpHsR009lJLat4c9Sbxfi1Xc1JyKnl+gWNF0M9Nx3+vSEbThmC31tUp+xNlJHbH34AJx3aBkZd1xTvw6KGwFpOJhf99g32b1it1OoOBGf/3NBG9eh/9RgUCwREJiIrhgptnMfKq69m1egXbl/xJWU6WU5uc1G3kpG475WOTVF5I6mA0Ln1x844gNtSIR9EGbPvW4F6R1WofNTLB1cWQWgyp/1L+M5QDVq0OVXQMXr164NKtK126daNX175oYiY6rYCbrWYK6gvIr8unxlhDjcnxU2uqVepqTbXUmGqoNlZTY6ppdSyHc+g6+6r2td0wHFoLCG9reqRfUD+mxk5lbPTYo+ZtN5eUUDN/Ptq5c9BprZgOejBk+3niX2cX/V7TpxH48MNo/NuXck7gIDLBl3Wz7cc2i0z+nkpi+rRvC5shOdlJ9Ms2Wwtj2mFdIvljoxcqrT2CbmvRTsZGje24GxAIBCcdIfoFAsEpYf7++Ty59klF8AM8OfhJRoaPbNF2Q2Y5N32zGdPBffySBG9flkSwV9sp8UrfehtLUREAeeGjKfdyRAV06RtIjyEhRx2n2djE3DdedBIcBg9PLnr8+VYNxwQCwfGhM7iSNG4SfcZOpGBPOtsWL2TvhrVYLUcOte84JCSVL5ImELUmEJ1rKAbPEFzc3XH3caH7oGBi+vij1qgAu7ixVFZSs2ETecvX0LR5E24F2ajaMENWm02wdw81e/fQXKKrPDzRd++KvmtXXLp1Q9+1K+FduxIV2v6V0zpTHbm1ueTU5pBbm2s/rskhpzaHkoaSo1/gOHDTutHFqwujIkYxOXZyq9FZzbE1NVG7dCnVc+fZRaXN/nkeEezL/iC7CWKJlxvWrl2IeeIp3AaLCKrjxTfEDXcfvZK6L3tnRbtFv2vfZOXYWl2NKSsLfWysU5sB0b7YVoU4RH/hkb0cBALBmYkQ/QKB4KTze8bvPLf+OacQ1kcHPsrF3S5u0Xb57hJu/26Lk3Hf3WPiGNmt7QeYhq1bqfzxRwBq3cLY32Wmcs7dR8/oq7of1fnZ3NTEnNefJ3fnDqXOwy+Ai554Hr+wiDZ6CgSC40WSJMJ69CKsRy8aam4lbfkSsrZvpam+DnNjI6Ym+4/FaDz6xewXRG9wRefqit7VDY3OBdDh4u6DX3gMAdGxBEXH4Orlhs5FjVqrapcrvMbHB98J4/CdMA6wi9qK9D2kr91G8fad2DL3E1Kej39TdZvXsdXW0Lh5C42btzhfPygIfY/uuPToiUvPnrj07IE2IqLVdKDuOnd6+vWkp19PZFmmtM5IbkUDuRWNZJZVklGRTVZ1NtnVBVhVNag0NUiaGiRNLZKmBpWmocU1DxHsFkyMZwwxXjHEesUS42U/9jf4t/l7shmNmA4cwLh3Hw2bNlGzaBG22pbeBJHlNewP9AZJQpYkqq66VAj+E0SSJKIS/Nh5MHVfzjGk7nNJ7AMqlTIp07h1awvRH+TpgrsUSRO7Aciq3d/BdyAQCE42QvQLBIKTyo+7f+TlDS8rZQmJp4Y8xSXdLmnRdv72Au7/eRuWZrbRNw2P4f6j7OO3mUwUPvU0yDJWlZZd8Tdik9SH3pALbuiFi1vbubHNTU3Mee05cnc5Uh/5hIRy8ZMv4unftnGgQCDoGFw9vRg4/WIGTm85IWizWTE3GTE1NWBqbMTc1IS5qRG1Vove1Q2dwRW9qytaF8MpSe2mcnHBP7kPI5L7AHbj0cyyetZszSRj4w7q0ncTVllIdE0h0TVFeJjbNvOzFBdjKS6mfuUqpc6sN1ATFk1teAx1EV1oiIylITSKkiYbuRUN5BwU+o3m1gLxow7+tHLGT0u/Lhq6hcoE+5rQayHKM4poz+ijZgOQTSaMB7Iw7tuLcd8+TPv2Ydy7D1NOjiIcW0WScBsymNAZM8hJT2H/Vnv2gtRlixly8RWoNW1/RgvaJjLeIfprK5qoLGpol4u/2t0NfffuGNPtXgsNKSl4X9zy/183n27sMC+2t7GVUGeqw10nsioIBJ0FIfoFAsFJ45ud3/Dm5jeVskpS8cKwF5jWZVqLtj9tzOGxOak0j5a9/4Ju3HN+3FEf4Ms/+RTTfvvKw74uM6l3daQX6jc+irBuPm32NzU1MufV58hLT1PqfELDufTpl3H38W2zr0AgODWoVGr0rnZhfyYiSRJdAtzpMj4RxifSZLayKauC9fvLmZNdSe7ebALLC4ipsU8ERNUUEVlbjL6NzAFaYyN+men4ZaYrdRZJRanBm2q9G9U6d/ur3t1xfPC1Su+OUa1Fa7Pip1cxMMKD/qHu9Al2J9BVjWw2238K1MhGE7aGDJoaUmiob8DWUI+toQFbQwNyQwO2evuxpbwcU3Y2WNtnhgigi47Ga+ZMvKZNRRti32KVHB2piP6G6ioy1q8RGVFOkBNJ3eeanKSI/satrZv5DY1MYEezBf7txekMixjQaluBQHDmIUS/QCA4KXyy/RPe3/a+UlZLal4d8SoTYia0aPvZqkxe+jPdqe7pKb24cfjRU+s1ZWRQ9umngD09X37YKOVcYLQnA6a2fQ1TUyOzX3mW/N07lTrf0HAufeYV3LzbniwQCASCI+GiVTOiawAjutq3Jlmsg8gormNrTiUpOVXMyakkq7SWkPpyoqsLiakpJKa6gC7V+QQ1Vh3xuhrZRkhDBSENFcc1rkYg+7h6thNJQhsejtuwoXjPmIFLnz4tJm4jExLxCQ2nsiAPgM0L59Jj+OhTEqFxtnIiqfsMyX2p/MG+Pc504ACWyko0Ps7ff2O7xvPRXg2Syj5JtfzAdiH6BYJOhBD9AoGgQ5FlmfdS3uOz1M+UOo1Kw5uj3uT8yPNbtH17SQb/XeZwllZJ8OpFiVza/+h76G0mEwX/9wiYzRh1nqT3uEY5p9WrGXtjrzbT85kaG5j96rPk726WJSA8kkueekkIfoFA0KFo1Cp6hXrSK9STqwfbw+4r601sy60iJaeSXYU1ZJltLLHZ0DXUElCcS3BJNsGluYSW5RBUWYRabiN8/jSgDQtDHxeHvmscurg49HFd0cfGoDpKNIakUtFv0jT++fxDAEoO7Cc/fSfhvRJOxbDPWo43dZ8hOdmp3JiyDY/znCMvugZ6obIEI+vsEzUpRcLMTyDoTAjRLxAIOgxZlnlz85t8u+tbpU6v1vP26LcZET7Cqa3NJvP8gl18vS5LqdOqJd69PJlJvY/usg9Q+u67GHfvRkYivcc1mLWO/YUjLuvWZno+Y0MDs195RskZDULwCwSCU4uPm44xPQIZ0+PoviE2oxHj3n0Y9+zGUlqKpaICa3kF1soKLBWVWCsqsFRWgtl8XGOR9HpUrq7OP25uqNzsx5KrK2p3D3QxMei7xqGPjUXl1r7w8dboNfI81vz8HU219twGmxfOEaL/BIlK8GPdbPsk+rGk7tOGhaIJDMRSYs/80JiS0kL0S5JEgC6GEuyiP7demPkJBJ0JIfoFAkGHYJNtvLzhZX7e87NSZ9AYeO+89xgU4uzMbLHaeOT3VH7fmqfUuWhVfHJNf0YdxaX/EPX/bqDiy68AyA0fTYVvL+VcXL9AegwJPlJXjA0N/P7K0xRm7Fbq/COiuOSpl3D18m7X+wsEAsGpRKXXY0iIx5AQf8Q2sixjq6uzTwBUVCCbzEg6LZJWh6TVIGm1zj+ag3U6HZLm1D4SavUuJI2dyL+z7d8Z+7dspKIgH9/QtlMBCo6MT4gr7r566iqOLXWfJEkYkpOp/ftvABpStrbarqdfd0rKV9vbkEej2YxBKwwYBYLOwJHjXgUCgaCdmK1mnlr7lJPgd9O68fEFH7cQ/EaLlTt/2Ook+D30Gv5306B2C35rdTUFjz4Kskytezj7Y2co59x99Iy68sjp+YwN9fz+8lPOgj8ymkueflkIfoFA0KmRJAm1hwe6qChck5NxGzQQ1+RkDAnxuHTvjj42Fl1EBNrgYDR+fqi9vOyr+KdY8B8iafwU1IfeW5bZuuiP0zKOswVJkoiK91PKh1L3tQfXvo4Q/6bUNGSTqUWbYZG9He+lMrFi/54TGK1AIDiVCNEvEAhOiGpjNbf9cxt/7Hc8rHnoPPhs7Gf0Derr1Lai3sS1X2zk753FSp2vm44fbx3MgOj2u+QXPf8ClqIiLGo9O3vdiKyyPzRKEoy98cjp+Zrq6/jtpaco3Ot4UAmIjLav8Ht6tfv9BQKBQHDiuHn70GPYaKW8c8U/NNbVnr4BnQVENhP9tRVNVBY2tKtf8339stFIU3p6izZj45Kcyssytx/fIAUCwSlHiH6BQHDc5NTkcPWfV7OpaJNS56P34YtxX9A7oLdT273Ftcz4YC0bDjgcp4M9XfjltiEkhLVfcFfPX0DNwoXIwJ6ul9PgGqSc6zcxmtCure/Ht6/wP03RvgylLiAqhouF4BcIBILTRr8pM5Rji8nIjiWLTt9gzgIOpe47RPbO8nb1c+nZE8nFRSk3pLRM3efv6otWdnzH7ihpOTEgEAjOTIToFwgEx8XW4q1c9edVZNVkKXXRntF8N+k7evr1dGq7fE8JF364jpwKx4pDbIAbv94+hLhAd9qLOT+fouefB6AoeDDFwQOVcyFxXgyYHN1qP2NDA7+/dJjgj44VK/wCgUBwmgmIjCYq0bHKnPLXfCzHaUYosKfuC+3qrZRz2in6Ja0WQ4LDSLFxa0vRDxDk4kiDW9CQic3Wvu0DAoHg9CJEv0BwEvh5989c+MeF/Gfzf2i0NJ7u4XQ4CzIXcPPim6kyVil1A4IH8N2k74j0dOQFlmWZL9Yc4KavN1FrtCj1I7r6M2fWMCJ8207r1BzZaqXg0cew1dZS7xrEnq6XKuf0bhrG3RSPqpX0fKbGg6Z9+xwh/YHRXbjkqZcweHi2+/0FAoFAcHLoN3mGclxfVcmedatO32DOApqH+Bfstafuaw+Gvo4teQ0pW1v1A0gI6KEc27QFZJSI7RgCQWdAiH6BoIMpayzj1Y2vsrdyL1/v/JorF17J/qqzI7WNLMt8uO1DHlv9GGabYyVmepfpfHLBJ3jpHavmJouNx+ek8sKCXTRfCLhuSBRfXT8AL8OxOf5WfPUVDZs2YVVpSet1Eza1Xjl3/nW9cPdxadHHLvifdTLtC4iO5eKnXsTg7nFM7y8QCASCk0N0n774hTsmjLcsnNtuAzpBS5qb+dmsMnm7K9vVz5CcpBxbS8sw5+W1aDMswrF1T6UrZ+3+/OMfqEAgOGUI0S8QdDCppalYZMes+r6qfVyx8Arm7uvcDzFGq5FHVz/KR9s/cqq/t++9vDDsBbRqh4ivrDdxzRcb+HFjrlKnVkm8OCOB56YnoGllRb4tmnbtouTd/wKwN+4i6t0dKZ36nBdBTKJ/iz7mpiZmv/ocBXt2KXUBkdFc8qQQ/AKBQHAmIUkSfSdNV8ql2QfISRMmccfLodR9h2hviL9rcrLdEfcgDRs3tWjTfKUfYFVW2nGOUiAQnEqE6BcIOpjdFbtb1DVaGnlq7VM8seYJGsztc9I9k6hoquCWxbfw54E/lTq9Ws+bo97k5t43O6XH21dSy4wPnQ37vAxavr1xIFcPjjrm97Y1NZH/f/8HZjMlAckUhI5QzgVGeTDkwi4t+piNTcx57Tnyd+9U6vwjorhYhPQLBALBGUmvEWMwNPNY2bJw7ukbTCfn8NR92Tvbl7pP7e2NvodD1Ndv+LdFm2ivaFQ4UjzuLEvv1AsaAsG5ghD9AkEHk17hcLNtHu4OMD9zPpctuIw9FZ0nt21GZQZXLbyKlBKHqY+viy9fjP+C8dHjndqu2FPCzA/WkV3ezLDP3425dw5jWFzL1fj2UPKftzDt20+jix/p3a9S6rUuasbdHI9a4/wxZjY2Mff158ndlarU+YVHCtM+gUAgOIPR6HQkjZuslA+kbKY8L7eNHoK2aL6vv67C2O7UfW4DHQa5DRs2thD0GpWGENdopVxryyWv8uzzLhIIzjaE6BcIOpjmon908HTeP+99J/GfVZPFlQuv5Jc9v5yxs+MVTRX8uPtHrvrzKi764yLy6hz7+uK84/hh8g/0Ceij1JksNt5ftpcbDzPsGx5nN+yL8Xc7rnHUrV5D5f/+h01Sk9brJqwag3JuzNU98ApwNgI0m4zMfeNFctJ2KHW+oeF2we/lfVxjEAgEAsGpIWncJNRax1axrX/OO42j6dwcb+o+10GDlGNLcTHm7OwWbXo3C/FXuRSxfn/7ri0QCE4fQvQLBB1IVVMVRfVFSvmntVbW7Ajg+4k/0zfQ4Yprspl44d8XeGjlQ9Sazgzn20ZLI39m/smdS+/k/F/O5+UNL7OjdIdTm6GhQ/l24reENdtT/29mOZP/u5o3F2e0MOz7+oYBeLkem2HfISyVlRQ8/hgA+2OnU+vp2BrQa3goXfsHObc3mZj3xovkpG5T6nxCwrjk6Zdx8/ZBIBAIBGc2rl7e9BoxRinvWrWMhprq0ziizsvhqfuy09op+gf0B5VDHtRv2NiiTe8AR1petb6Qv3YWHv9ABQLBKUFz9CYCgaC9NF/lB7A2hfLZ6gOs3uvBfy59m6VF3/F56ufI2NXx4uzF7Crfxa2Jt6Jv5kZ/omhUGjx0Hs4/Wg8nsz0Ai83CxsKNLDywkH+y/6HB0nr4n0bScEXPK7i/3/1oVfZrlNUZefnPdGZvdXbuVasknp0WzzXHsX//ELLZTMGDD2ItLaPML4HciPOVc76hbgy/tKvzfZjN/PGfl8je4diC4BMSyqVPv4y7j+9xj0MgEAgEp5Z+k2eQumwxABazie2L/2TIxVec5lF1TiLj/RTn/sJ99tR9Ope2H/3VHh64xMfTlGrfItew4V98LrvUqU03327KsaQ2siZzLzVNyXi6HN8kv0AgOPkI0S8QdCDNRb9sdUE22wXn7qJaZn6wgf+bMIWPzu/P42sfo6LJbnSXV5fH0+uePiXjc1G74KHzwF3njofOg4K6Asoay47YPjkwmSmxUxgXNQ5vF28AbDaZHzbm8Ppfu6k5LPdvj2APXr6wN30jj39lXZZlil5+mfp162nSe7OrxzXKOY1WxfibE9Dq1Eqd1WJm/lsvc2DbFqXOOyiES55+GXdfPwQCgUDQefALjyQmqZ/ymb5t8UIGTLsIjU53mkfW+YiK92Pd7/sAR+q+2KSAo/ZzGzRQEf31Gzchy7KTYW83n25O7W3afJallzAjOQyBQHBmIsL7BYIOZHe5w7nf2hQKOL4kTVYbLy5M58O/VHww+jsGBQ9q5QonlyZrE6WNpRyoPsCO0h2tCv4YrxjuTr6bRRcu4tuJ33Jp90sVwZ+WX83Mj9bx5Nw0J8HvplPz5OSeLLh7+AkJfoDK776n6sefsEkqdva8AYvWXTk34vJu+IY6+wOs/O5LMrc60gp5BQVzydMv4+F7fMaBAoFAIDi99Js8UzluqK4ife2K0zeYTsxxp+4bNFg5tpaVYdq/3+m8r4svga6BSlntms2fqSLEXyA4kxEr/QJBB9J8pd/WFMr1Q6Nx1an5aOV+Dnn2rd1XzpUfVfPizGcYFPIXP+7+UVn17yissvWY2vsb/JkYM5EpsVPo6dvTaUYfoKbJzFuLM/h2fZbTvn2ASb2DeWpKL0K8DJwodatWUfzKKwBkxkyn2jtOOdd1QBA9h4Y4td+zfg0pi+YrZc+AIC59+mU8/Y++kiEQCASCM5PI3n3wj4ymLCcLgC0L5pIwemyL7yZB20iSRFSCPztX2bfhHUrdd7Tfo2vfZNBowGKf3K//dwP6uDinNgOCB7AwcyEAatf9rMwopd5owU0vpIVAcCYi/mcKBB1Eg7mB7BqHy621KZS+UT5M6xPK6O6B3P/zNvKr7Gltapos3PPjDmYmD2Du9Os7fB+cxWahzlRHramWWnOt/fXgT42phjqz/ZxKUjE8bDiDggehVjlC5muazBworSezrI79JfX8sjmXklqj03tE+rry3PR4xnQPPPztjwvj3r3k3/8A2GzkhwwlJ/IC5ZxXgIHRV3V3elCpLMxn8SfvKmWti4ELH3sWT/+OGY9AIBAITg+SJNFv8gz+/ugdAMrzcsjevpXopH6nd2CdkKh4X0X011UYqSisxy/Uvc0+Kjc3DL1705hi98lp2LAB36uvcmozMHigIvpVLgU02OpYvqeEKYmhJ+EuBALBiSJEv0DQQeyp3KMY9AHYmsJIDLOn6hsY48ui+0bw7B87nYzv5qTks/FABTcNj0Gr6bjdNmpJQq9RodOo0Wt80WsDcNeo8NOr0Lup0WtV6DUqjBYbB0rr+WJfFpml9WSW1ZNZWk9ZnfGI19apVdw+KpZZY+Jw0aqP2O5YsFRUkHvHLGz19VT4dCej2+XKOY1ezfhbE5zMh8wmI/PffhVToyM38Lhb78IvLKJDxiMQCASC00uPYaNY8+M31FfZjeg2L5wrRP9xENbdB5VGwmaxP5/kpFUcVfQDuA4e5BD9Gzci22xIzVz9BwQPUI4lSUbjeoBFqV2E6BcIzlCE6BcIOoj08mYmfjYNbqpgovwceeQ9XbS8dWkS5/cI4vE5qVQ3mgHIr2rk+QW7Tvl4j4dhcX68MD2B2ICjPzC0F5vJRN5dd2POy6PeNZi0+JuRJftkgiTBuJviCYjwcOqz/KtPKM0+oJT7jJtMj2GjOmxMAoFAIDi9aLRaksZPYe3P/wMge0cKpTlZBERGn96BdTJ0LhpC47wVF//sneUkj4s8aj+3QYMo/+hjAKzV1Rj37MGlpyNVX7h7OKFuoRTUFwCgdtvP8j2JNJqsGHQdsyAgEAg6DmHkd5YhSdLVkiTJ7fyJO8I1LpckaakkSRWSJDVJkrRfkqSPJEnq1lp7gZ3dFQ4TP5sxhMRw31b3zU1ODOHv+0YyPO7MN5pTSfYw/jHdA/jgyr58d9OgDhX8sixT9NRTNG7diknrzvbed2DROCZKhl3clZhE59/TzpVLlXROAEGxcYy+9uYOG5NAIBAIzgwSL5iARucwolv6xUfYbMfmWSOwp+47ROG+KprqzUftY0hKQtI6th7Wb9jgdF6SJKfVfrVrJg0mKyszSjtgxAKBoKMRK/1nH32Ot6MkSVrgB+Diw07FArcD10qSdJ0sy7+dwPjOWpqLfmtTKL27ex+xbbCXC9/eOJBv12fxv3+zqag3dehYLDYZk8WG0WJrV3sfVy2xAe7E+LsRG+BGrL87sQFuRPm5otecvBn78k8/o3reH1hVWnYk3EaTwSHwE0aFkXheuFP7stxs/vniQ6Wsd3Vj6v2PotGK3MACgUBwtuHq6UXv88cphq35u3ey6Y/ZDJpxyWkeWecipo+/U+q+fVtKSBjZdno9lYsLhuRkGjZuBKBhw0b8rr/eqc3AkIHM2z8PALVLEZK6jkVphUxICO74mxAIBCeEEP1nH4dE/2rgnqO0zTms/AYOwb8EeB8oBYYCTwLewHeSJB2QZXkLAgWz1czeyr1K2dYUSmK4V5t9VCqJ64fFcP2wmJM2LlmWMVnt4t9otmG0WJ2OJUkiytcVH7dTn/+4ZvFiSt9+GxmJ9B5XU+MVq5yLjPdjxKVdnSIlTE2NzH/7VSxGh9/AhFn34xUoHi4EAoHgbGX45ddyYOtmqortKeHW/fId0YnJBMW2GqwoaAXvQFeCYjwpPlADQMbGoqOKfgDXQQMdon/TJmSLBUnjkA4Dgwc6tVe7ZrI03RujxXpSFwwEAsGxI8L7zz4Oif71sixvO8qPsrwsSVICcPfB4u/AeFmW/5Bleb0sy/8BhgBVgB546xTeT6dgX9U+LLIjb721HaL/VCBJEnqNGk8XLQEeesJ9XOkS4E6vUE+SI31IivA+LYK/MW0nBf/3CACZMZMpCeyvnPMLc2P8zfGo1I6PJ1mWWfLp+1Tk5yp1/abMJG6AI5ewQCAQCM4+dC4GJt71oGIiZ7NaWfjem5iNTad5ZJ2LbgMdE+SF+6qpKWtso7Udt0GDlGNbXR1N6elO54Pdgon0cPgDqN0yqTNaWLO3rANGLBAIOhIh+s8iJEkKBg7lK9t+jN3vwv73YAbul2XZKRu7LMu7gRcPFkdKkiQsdJvRPLRfllV4qSMJ8z7xvPVnI+biYvJmzUJuaqIwaBDZUROVc66eOibf2QedwTkIKXXp3+xeu1Iph3bryYgrrjtlYxYIBALB6SO0Ww8GX3iZUq4syGPld1+dxhF1Prr2D0SlckTPZWwsOmofQ2IikouLUm44bF8/cNi+/v0A/Jl69GsLBIJTixD9ZxfN9/NvO8a+0w++rpJlOfcIbb5tdnzhMV7/rGZXucN932YMJDHMv1UTv3MdS0UFuTffjKWkhErvruzufqVyTqNVMfnORDx8XZz6FGfuY9nXnyhlFw9Pptz3CGqN2J0kEAgE5wqDL7yckLjuSnn74oVkpmw6jSPqXBg8dETG+yrlPRuKOWx9pwWSTodr375Kuf7flqK/eYi/Wl+KpKlhya4iTO30FBIIBKcGIfrPLg6J/iZgT3s7SZIUCxyK+1p1pHayLJc2u67Ij9YMJ+f+MyS0/0zDUllJzvU3YNy7jwZDIKnxtyCrDgp3CcbeGE9glKdTH2NDPfPfeRWr+aDTsCQx+a4H8fA78zMfCAQCgaDjUKnVTLz7QbR6x8Tw3x+9S0N11ekbVCej2yBHiH9VcQOlObVH7ePaLMS/YetWZLOz8//AkJb7+muaLKzPLD/B0QoEgo5EiP6zi6SDr2lAP0mSvpEkKUeSJJMkSSWSJP0hSdLkVvr1bHa87yjvcSg5es82W51DWG1Wdlc45lisTaH0DhOivznWqipybrwJY0YGJq2bPTWf1k05P2RmF2KTA5z6yLLM3x+9S3WxI0xw8IWXEZ0kdpYIBALBuYhPcChjbrhVKTdUV/H3J/896oq1wE50oj9aF4fB3p4NRw/DdxvkEPVyQwONqWlO5/0N/sQ2M+I9FOK/KLXwRIcrEAg6ECH6zy4OrfR3B/4FrgUiAC0QAEwFFkiS9D9Jkpq7t4U2Oz7c0f9w8g+++kqSpG+zZTuQJClQkqT4Y/kBupzo+3YkObU5NFkdhjg2YyiJ4d6nb0BnGNbqarvgT0/HotazI+F2Gl0DlfO9hoeSPDayRb+Uvxawd+M6pRyZkMiQi684JWMWCAQCwZlJwuixxA0YopQzt2wkdenfp3FEnQetTk2XZhPsezcVY7O2HYbvkpCAys0xSd+wse19/Rq3TAD+3lmE5SjXFggEpw4h+s8SJElyAbodLHpgF+cPYw/DHwU8gT39HsDVwEfNuvs0O647ylvVNzvuiOXsWdgjE47lZ14HvG+HkV7u7Gbro4kmyPOE50POCqw1NeTcdDNNu3ZhkzSkxt/ilJovvIcPI6/o1sL/oDQni1Xff6mU3bx9mHT3w6hUIgWQQCAQnMtIksTYW+/CzcexP335t59RUZDfRi/BIZqH+DfWmslNr2yzvaTRYOjviLBrbV//oBDHFgCVrhxJU0Vlg5kNByo6YMQCgaAjEKL/7CEeOORstg5IlGX5TVmWVx38eRl7+P/+g21ulCTpgoPHzRXq0XLgNM/xIpQth+3nN/nRJzRYmPgB1ro6cm65haa0NGySip29rqfS17ErxC/MnQm3JqBWO38MmU1GFr77uvM+/nsexs3bB4FAIBAIXD29mHD7vUrZYjSy6P03sVosbfQSAIR188HN2/H41q4Q/4EOUd+YkoLNZHI63z+ov1NZ7XYwxD9NhPgLBGcKQvSfPWwD4oCxwAxZlltM3cqyXADc1KzqnoOvzeOvjrYxrrmaFXFbQHqFY6Xf2hRKb2Hih7WuntxbbqVp+w5kJHZ3u5LSgGTlvFeAgWn3JqF31bbou/r7rynPc+wyGTj9YiLiE0/JuAUCgUDQOYhO6kfyxKlKuWj/Xv79/cfTOKLOgUol0W1AkFI+sK0UU1PbkyWugx2iXzYaady2zem8j4sP3Xy6KWXNwX39f6UVY7UJvwWB4ExAiP6zBFmWrbIs75dl+Z+DLvtHarcSx2r/aMm+JN08pN+lZS8nmp83Ht9onfgQSDjGn+mtXuk0IMsyO8uapetrCqXPOb6f31ZfT+5tt9GYkoIM7I27kKIQx/5Ldx890+5LwtVT16JvZsomUv6ar5SDYrsy9JIrW7QTCAQCgWDEldfjF+7whNkw51fyd+9qo4cAnEP8LWYbB7Yd8bERAJcePVB5OrLrNBwtdZ/bfkCmrM7I5iwR4i8QnAkI0X9uknrw1QP7fv7mOVvcWjZ34tB5Gag60YHIslwiy/LOY/nBMWlx2imqL6LWXKOUrU2hJJzDzv22hgZyb7udxi1bAMiKmkRe+HnKeRd3LdPuTcLTz9Cib31VJX9/9K5S1updmHzPQ6g1LaMBBAKBQCDQ6vRMuvsh1Br77kZZtvHn+//B2NBwmkd2ZuMf7o5fmONxb8/G4jbbS2o1rgMcZn31rZj5NRf9Km01ktYu9helHX37gEAgOPkI0X9u0vzbUAdkNyuHHaXvofOlsiyf85vnmof2AwToYgnwODetDmyNjeTeMYuGzZsByA0fw4EYR4ZInYuaafck4RPccl7Jnp7vHad8y2NuuBWfkKP9OQoEAoHgXCYwOpZhl1+rlGtKi/n9laepqxQrzG3RbaBjtT8vvYL66raDN90GNdvXv30HtsZGp/P9gvuhkhyyQuN2KMS/CJsI8RcITjtC9J8lSJLUR5KkiyRJul06uovcoXwtVqACaK5cj5YO75D1enqbrc4RnEz8zB70CQ0/jaM5fZhyc8m5/gYaNthn/wuCB7M37mLlvEarYvKdfQiI9Gi1f8pfCziwbYtS7jpoKAmjx57cQQsEAoHgrKD/5BlO3i+FGbv5/rH7KNy35zSO6sym28AgxaVJlu3p+9rCtZnox2ymYetWp/OeOk96+PZQyuqD+/qLappIya3qkDELBILjR4j+s4cHgN+wp+LrdqRGkiRpgUM2q6myLJsOGvzlHawb1kbfgGbXXnekducSu8qb7+cPI/Ec288vyzJVv//OgekzaNy+HYAS/yR2d79KaaNSSUy4rTehXb1bvUbZYen53H39GHvr3SIDgkAgEAjahaRSMenuh5z299dVVvDzM4+QtuKf0ziyMxd3HxfCujmy4hzNxV/fNQ61j6N9w4aNLdoMCnZMDGjdMjnkDb0oVbj4CwSnGyH6zx5WNTtuy/nsGuz7+AF+aVY/5+DrWEmSQo/Q97pmx3OPaXRnKTvLmjn3G0PpfQ7t57dUVJB3990UPvEktoP7J8t9erAz/kY4FOInwQU39iIqwa/1a5hMLPzvG07p+Sbe+SAG99YjAgQCgUAgaA13H1+ufPFN4gY4jGOtFgt/f/QOy77+RKTza4Xugxwu/mW5dZQX1B2xraRSOa32H4rsa86AYMe+fzS1qHR2g8BFaUXIsgjxFwhOJ0L0nz38hj1UH+ABSZL6HN5AkqRE4M2DxVLgk2anP8Ue7q8HPpYkSX1Y3+7AEweLG2RZbjnFe45R0VRBWVOJUrY1OUS/taaGmiVLMBcUnK7hnVTqVq4kc9p06v5ZqtRVe8aQljQLudmfzugru9O1f1BrlwBg1Q9fUZbrsJQYMO0iIhNEej6BQCAQHDs6gyvTHniMoZde5VSfsmg+v7/8NA011adpZGcmscmBqLUOKZBxFEM/t0EOs77GtDSsdfVO5/sG9UXd7BlAfXBff35VI6n54ncvEJxOhOg/S5BluRq472DRHVgtSdLTkiQNkyRppCRJL2IPyffBLu5vlmW5oln/NOzp8wCmAqskSbpQkqQhkiTdD6wHvAEzcNepuKcznd3lu53KgfpYfNx0yCYTWVdcSf7d97Bv3HgKnngCU27uaRplx2JrbKTwuefIve12rGVlSn1V1EC2D3wIq+z4sh96YRzxI45sxHcgZTMpi5qn54tj2GEPagKBQCAQHAuSSsWQi65g+sNPoTM4MsXk7tzB94/fT0lW5mkc3ZmF3qAhJtFfKWdsLEJuw3TPaV+/1Urjls1O5920biT4Jziu735AOf4zVbj4CwSnEyH6zyJkWf4fcDdgwZ6O7zlgDbAS+yq9G/b0fFfLsvxHK5d4EPj94PHQg8frgLewTxYYgWtkWd7cSt9zjubO/bLVQFKw3eOwYcsWTPsPZhW0WKj+fTb7J0yk4LHHMWVnt3apTkFjaioHZl5I1Y8/OdXXnHct2+Kup3nkZL+JUSSPi+RINFRX8ddH7yhljf5Q2iWRnk8gEAgEJ05c/0Fc+eJb+IQ4dizWlJbw41MPs3vtytM4sjOLboMcLv51FUYK9lUdsa0uJgZNQIBSrm9lX3/z1H069wOADYC/0gpFiL9AcBoRov8sQ5bl94He2A399gKNQB2wE3gdiJdl+acj9DXLsnwxcDnwD1COfWU/D/ga6CvL8s8n+x46C+nNVvqtTSH0ifAGoG7lqpaNrVaq58xh/6TJFDzyKKasrFMzyA5Atlgo/fBDsq640mnckqsrtbe/zmZ5EDar44s8eWwkg6bFtnKlg9eTZf7++F3n9HzX3YrvOZr5QCAQCAQnB7/wCK586S1ikvopdRaTkYX/fYNV33+FzWo9jaM7M4iM98XFzTHhntGGoZ8kSc77+v/9t0Wb5vv6zdSi0tu3QWaVN5BeWNsRQxYIBMeB5nQPQNDxyLK8G5h1Av1/BoS4PwqpZc2d+0PpHW7fz1+3erVSrwkOxlJaCoceLKxWqufNo3r+fDynTMb/9jvQx8ac0nEfDUtlJU1paTTu2EHjjh007UjFWlnp1MYlKYniaY+wZZVzHuQhF3ah77ioNq+f8tcCMrduUspdBw6l93njOu4GBAKBQCA4iIubOzMeeZq1P3/Hxrm/KvWb/vid1OVLiOs/iK6DhhKZkIRGe+5Fm6nVKrr2DyR1ZT4A+7aWMuLybmi06lbbuw4aSM2CBQA0padjra5G2b2pRwAASKZJREFU7eUwMU4KTEKr0mK22Q16XTwyaTDaown+TC2kV6jnybwdgUBwBIToFwiOg3pzPQX1OUrZ2hRGQpgXprw8R2g/EPjQQxj6JFL2ySdUz52HEgNvs1Hzx3xqFizEc9IkPM4bAx2Zok6lRuVqQOXigmRwRWVwQWUwIBkM9le9HkmSsBmNGNPTDwr8VBp37MCck3Pk66rV+N95J+k+Y0hd6TAplFQSY67uTs+hR0r8YCdrRworvv1MKdvT890l0vMJBAKB4KShUqkZccV1BEbH8tdH72AxGgFoqq0hbfkS0pYvQWdwpUu/gXQdNJToPn3R6l1O86hPHd0GBSui39RoITu1nC59A1tt6zZ4sKMgyzRs3ozH+ecrVQaNgcSARLYUbwEgMDCXrIMWQAt2FPDguG7iO18gOA0I0S8QHAd7KvY4lUMNXfB00VKxqllov0qF27ChaHx8CH3xRfxvv4PyTz6has4cZ/G/YIEya37KkCQkgwHZZIJ2pjHSRUcT9OprrNuiZm8zwa/Wqhh/czwxfQLa6A3leTksePtVZJvt4BBUTLzzAQweYtZfIBAIBCef7kNG4BMSxoJ3XqOyMN/pnKmxgfQ1K0hfswKNXk9sUn/iBg0lNnkAWhc9psZGTI0NB18PHjc1Ymqwv5qNRty8ffAJDsUnNAyDh2enEbdBMZ54BhioKW0EYM+GoiOKfm14OJrQECwFhQDUb9jgJPrBvq//kOhvUO3Fvq9fRVZ5A2n5NUpkpEAgOHUI0S8QHAdOJn42LUnB3QCoX2UP7ZcBVdJgVF7eSjtdeBghLzyP/+23UfbpZ1TNng2H8tOfamQZuaGhzSZqX18MvXvjktgbQ2IfdMn9+fvL3eTscrj26wwaJs/qTWhXnzav1VBTzZzXnsPY4EjvM/q6W4hMaJFZUiAQCASCk0ZgdCzXv/Uh+ek7ydiwjn0b11FX6bxVzWI0krFhLRkb1tqj8I7DgE7v6oZPSCjewaH4hIThE+J41bu6ddTtdAiSJNF9YBCbFmYBkJ1WTlO92Wmvf/O2bgMHUT13LgAN/25o0WZA8AA+2v4RAI3WOtzci6mvCwFg/o4CIfoFgtOAEP0CwXGwq9wh+m1NISTG+WAzGqn/919kIC3+Fko9k9jw5DoSR0fQa3gIelf7l6c2LIyQ557F/7ZbKfvsM2rmL8BWV3ea7sSO5OKCS3w8ht69MST2xiWxD9qwUGWVoqnOzB8fbKf4QI3Sx9VTx9R7+uAf7tHmtS0mE/PeeJHqEkf+36TxU+g7cerJuRmBQCAQCNpApVITEZ9IRHwi511/K4X79rB343r2bljr9F0FHJfgBzA21FO0fy9F+/e2OBcQFcPgiy6n68ChZ0w0QLdBwYrot1ll9m0pIWFk62l3XQc7RL8xIwNLRQUaX1/lfJ+APujVeoxW+zaKbtHFpKTZRf/CHYU8OqEHKtWZcd8CwbmCEP0CwXGwo8Rh4mc1hpIY7k3Dxk3ITU3UeERTGpAE2NPfrJu9j40LD9BzaAh9zgvHK8AVAG1oKCHPPEPIM890+PhksxlbUxO2xkbkQ6+Njfa6hkbkpkZsjU0gSbj07IG+a1ckTesfB7UVTcz/7zYqixyRAZ4BBqbdk4RXgKHVPso4Djr1F2Q4Jklikvox5rpbOuZGBQKBQCA4ASSVitBuPQnt1pORV91ASVYmezesY++GtVQU5B21v0arQ2swoNHqqK+qaFdGgNLsA8x/6xWCYuMYftk1RPXpe9rFv3egK0ExnsrkfsaGoiOKfrdmDv4A9WvX4TV1ilLWqXUkBSaxodAeBaBzzwSSAMivaiQlt5J+Ub4IBIJThxD9AsExYrKayKnNVMq2plDiQz2p/dG+n/+Q4G+OxWgldXkeqSvyiEn0p8/5EYR29T5pX/KSVotaq0Xt0fYq/JGorWjiwPYyDmwvpSCjCpvNsdLhF+7O1Lv74OalP+p11v/2o1M+ZP+IKCbf+wgqdeuuwAKBQCAQnC4kSSIopgtBMV0Yfvk1lOflUHxgP2qNFp3BgM7gis5gQG9wRWswoHMxoG42YW61WKgpLaayqIDKggL7a2E+VUUF1JSVtogaKM7cx++vPEN4zwSGXX4N4T3iT/UtO9F9ULAi+gv3V1NV3IB3kGuLdtqQEHRduijGxdXz5jmJfrDv6z8k+rPq0/BwuYjaJvv9z99eKES/QHCKEaJfIDhG9lXtw4ZjJj/M0AU3vYailauQgZJmol9n0GBqbGaUJ3NQTJfhH+FO0vkRxPUPQq1RnbobaAVZlqkoqCdzWykHtpdRmtN6Lt3Qrt5MmpWI3nD0j470NStY/9sPStnVy5uZjzyD3rXlA4RAIBAIBGcafuGR+IVHtru9WqM5uG8/DJKdz1lMJqqKC8lL38mGub9QV+7wx8lLT+PnZx4hJqkfwy67hqDYuI66hWMirn8ga37di81qF+epK/MYcWm3Vtt6TZ9O6VtvAVC/di3mwkK0ISHK+YHBA5XjBksDQ3o2sjjFnhFhwY5CnprSC7UI8RcIThlC9AsEx0h6s/38sqwiKbgnpuxsTNnZ1LmF0WRwuNifd00PPP0NbF+ay97NxcoXKUBZbh3/fJ3Oujn7CeniBXTcl59KLaEzaNAb1GhdNOgNGnQuanQGDToXjf3VoKa+ykjmNvuKfk1ZU5vX7DogiPOu7XHE3L3Nyd+Tzt8fvaOUNVodMx5+Cs+A1t2ABQKBQCA4m9HodPhHROEfEUXC6AvYvmQRG+b+QmNNtdLmwLYtHNi2hW6DhzP00qvwC4s4pWM0uOuI6x9Ixga7r0H6ukIGTYtF59JSLnhNn07pO++AzQayTPW8efjffrtyPt4/HoPGQKPFnhEgIDAPsE9mlNUZ2ZBZztA4/5N+TwKBwI4Q/QLBMbKzuYmfMZDkbgHUHXTtbx7ar9GqiIz3Q6tXc8ENvRgyswupK/NIW5WPsd6x+t9QbWL/1tJTNv72IkkQ3MWL2KQAYvr4K14ER6O6pIh5b76ItVkqwAl33k9I1+4na6gCgUAgEHQaNDod/SZPp/f549j65x9snj/bKbtNxr9r2LthHb1GnsfwK67F3efUhcInjolQRL+5ycru9UUkjglv0U4bFIjbiOHUr7Rvbaz6fTZ+t96KpLJHLmpVWvoG9WVt/loAik1p+Ln1orzeBNhd/IXoFwhOHac3plgg6IRsL96pHNuaQukd7kXdqkP7+R3xfJEJdsF/CDdvPYOnd+G6V4Yx6sru+ASfeWHuaq2K6ER/zru2Bze8PpwLH+pH0gWR7Rb8TfV1zH71OaeVi2GXXUP3ISNO1pAFAoFAIOiU6FwMDL7wMm5673MGzrgEjd7hlSPLNnau/IevH7iDbYv/RLbZTsmYgqI9CYrxVMqpK/KQba1nMPC+8CLl2JybS8PmzU7nBwU7DP+2l25jfIJD5C9KK8JsPTX3JBAIxEq/QHBMWG1WDtQ40u/IxnB6eGvJ2bCBetcg6t0c+9m6JAe0dgm0OjUJI8OIHx5Kzq4K9m0twdxkabXtcY/TImNqtGBqsthfG62YGi1OhnyH0LtqiE70J7ZPABG9fJ0mKo7tPS0seOc1KvJzlbpeI89j0MxLj/s+BAKBQHAQmw1K0yF/C/hEQ8zI0z0iQQdhcPdgxBXX0XfiNDbM+YXtSxZhs9qfC4wN9Sz94kN2rVrK2FvuIiAq5qSPJ/G8cJZ8Yc9SVFXcQE56BVHxfi3aeYwZjdrHB2tlJQDVs+fgNtCxl7/5vv4maxO9YqrA7u1HVYOZNfvKGNNdbPsTCE4FQvQLBMdAdk02ZtmolMNc47ClbEE2mSgNTlLqVWqJqN5th61JKomoBD+iElp+kZ4MZFnGarZhbLRgbrJibLQgSeAf7o5KfWJBP7Iss/zrT8jekaLUhfWIZ+ytd5/2NEQCgUDQKbHZoDgNstdC1hrIXgeNFY7zPabAxNfBq/W0aoLOh5u3D+fdcBv9p8xk1Q9fs2fdKuVc4d49/O/Re+k3eQZDL74SrYvLSRtHl+RA1nrto6HaHoqfujyvVdEv6XR4Tp1C5bf/A6Dm778JevJJ1O5uAPTw7YGH1oNas90cuEreSbBnT4pq7B5C87cXCNEvEJwiRHi/QHAMpFekO5WTgnpSt7Jlqr6Inr7tcrg/lUiShEanxs1Lj3eQK0HRngRGeZ6w4AfYvGAO25csUsreQSFMe/BxNFrtCV9bIBAIzglsVihIgXXvwQ+Xw+vR8MkI+OtR2L3AWfCDve6DQbDhU3tfwVmDZ0AgU+79Py56/Hm8goKVetlmY/P82Xz90Cz2b9l40t5frVGRMNIxmZSdVk5VcUOrbb0vvNAxvsZGav9yPAuoVWoGBA9QyqvyVjE50RERuXhnMU1m8bcrEJwKhOgXCI6BnWW7lGObyY++4cHUrVpFo4sftR6OtD6xRwjtPxvZs34Nq777Uinr3dyY8cjTuHp6ncZRCQQCQSfBaoGVr8PrMfDpaFj8JGQsgqbqo3bFVAuLHoYvxkFR2kkfquDUEt2nL9e9+QGDZl6GSu1YSKgpLWHu68/zx1svU1tR1sYVjp/4EWGoNI5IvdQVea22c+nRA5devZRy1e+znc6PiRyjHKdXpDO4m+OadUYLK/aceUbGAsHZiBD9AsExsLXZQ5W1KYxEqjHn5VHqn6TUSyqJ2D7nhugvyEhn0Qf/UcoqtYbpDz5xytMMCQQCQaekKge+ngzLXzqyyFfrIHIojHwYrpkL96VBnyuc2+Rvhk9HwT/PgrnxZI9acArR6vQMv/warn39v4T16OV0bu+GdXz9wB1sXfQHtg6O9nD11NG1f5BSTl9fiKmxdf8hr4scq/2NKSkYMw8o5VHho1BJDrlRZNlMhK9BKc/fUdCRwxYIBEdAiH6BoJ3Issz+6gxHhTGUoPStAJQ0C+0P6+aNi/vZH9ZeVVTI3NdfwGo2K3Xj77iXiPjE0zgqgUAg6CTsmgcfD4fcf53rNS4QPQJGPQrXLYBHc+DGRXDek9BlDHhHwMyP7RMAPs1M3WwWWPM2fDgE9i8/pbciOPn4hUdy2TOvMu62e3Bxc1fqTY2NLP/6U2a/8iyNdbUd+p7NU/WZm6zs/rew1XZekycj6XRKuXqOY7Xfx8WHfkH9lPKynGVMTQx1lNNLaDB1rJmxQCBoiRD9AkE7KawvpMlWp5TD3bpiXLMao86LGq9YpT426exf5W+srWH2q8/SWFuj1A295Cp6jRjTRi+BQCAQYGqA+ffBL9c6r+77xcE1c+wi//oFMOYxiBkBWkPr1+kyBmath+EPgKqZh0zlAfjfDJhzO9SXn8w7EZxiJJWK3ueN44a3P27xfZu9I4UfHn+AspysDnu/wChPgmMdW/V2LG89fZ/a2xuPC85XylVz5yJbHEL+vIjzlOOtJVsZ1dORBrjRbOWf9JIOG7NAIGgdIfoFgnZyuIlff69YGjZtptS/j6NSOvv381vMZua9+RKVhflKXfyo8xl80eWncVQCgUDQCSjeBZ+dB1u+cq5PuhpuXQldzgONvvW+raE1wAXPwG2rIKy/87ntP8IHA+yu/4KzClcvbybe9SCXPPUSXoGOEPyq4kJ+ePIh9m7suH/zxPMcq/3VJY3k7KpotZ3XhRcpx9bSMurWrFHK50U6RL9NtlFg2kKXADelbv52EeIvEJxshOgXCNpJWmkzEz+zJ6Nqy5HNZqfQ/pBYL9y8juGBrZMh22z8/dE75O/eqdRFJiQy9ta7RGo+gUAgOBKyDJs+h8/GQGmzCWSdB1z0Bcz4APTuR+5/NILi4abFMOlN+zUP0VAO318CuSfP6V1w+ohM6MNVr7xDZO8kpc5sbOKP/7zMul+/R7bZTvg9YpMDcPNyhO7vWJ7baju3IYPRBDsyDVQ3M/QLdQ+lp29PpbwsdxlT+zhC/FfuKaW60bFVUCAQdDxC9AsE7WSw7+XUZ95LY8ElmMrOJ2rfdkxad6q8uyptzvZV/rW/fM/utSuVsl94JFMfeBy15uz3MBAIBILjoqECfr4aFj4IliZHfVg/uH019L64Y95HpYaBt8BdG6HHFEe9qQ6+uwjyt3bM+wjOKAzuHlz02HP0mzzdqX79bz/yx1svY2psPdVee1GrVSSMcqz25+ysoLKovkU7Sa3Ga+YMpVy7YgWWCkdUQPPV/vUF67mgl49SNlltLN5ZdELjFAgEbSNEv0DQTtIL6rAZQ7BU90NVOxjt5n8p80+EZq60Z7PoT12+mA1zflbKrl7ezHzkGSdDIYFAIBA0I3ud3axv94JmlRIMvx9u/Bt8Y47Y9bjxDIXLvoOh9zjqjDXwv5lQuKPj309w2lGp1Yy+9hYmzLoftdYxCb9v07/88ORDVBadWPh8/IhQ1BrHs07qivxW23nPnOkomM3UzJ+vFJuLfqPVSJF5O71CPJW6+TtaNwkUCAQdgxD9AkE7iQlwZ0ZSKLEBboxxqcNSWOiUqi8g0gNPvyMYLnVysnak8M9nHyhljU7PzP972mkvoUAgEAgOIst2J/2vJ0NNM4HkHmQ367vgWVCfxAgpSYKxz8OgOxx1TVV2g7/iXUfqJejkxI86n8uffQ13Xz+lrjwvh+8fv5+sbVuO+7oGDx1dBwQq5d3rCzG2kr5PFxmJ64ABSrnq99nIst34r6t3VyI8HOl8l+YsdQrxX7uvjIp603GPUSAQtI0Q/QJBOxnVLYB3Lk9m2YOjeT64BrPGQIVPd+V8l75n5yp/aU4W8996BZv1YA5gSWLyPQ8THNft9A5MIBAIzkQaq+CnK+GfZ0Futqc6bizcvtbuun8qkCSY8Ar0v9FR11AO306Hsr2nZgyCU05wXDeufuUdQrs59tAb6+uZ/epzbJrvEOHHSuIYh2A3G63sXneE9H0XXeh434wMmnbaJ5kkSXJy8V+Zt5IJCY7nJqtNZlGaWO0XCE4WQvQLBMdB45o1lPslIDdLk9QlObCNHp0Pq8VCyl/z+eW5x5z2BI657hbiBgw+jSMTCASCM5TC7fDpKNjzp6NOpYFxL8GVv4D7KZ4cliSY9B9IvtpRV18C30yFisxTOxbBKcPN24dLnn6Z3uePV+pk2caq777k74/fxWazHvM1AyI9COnSLH3fitbT93mOG4fKzeHMXz37d+X4/ChHWr9aUy1Fpp0kRXgrdcLFXyA4eQjRLxAcI9a6Ohq2bKGkWWi/b6gb3kGOvLOmpkby0tOoLul8xjSyLLNv8wa+efguln31CU11tcq55IlT6Ttx2mkcnUAgEJyByDJs+QY+HwuVWY56j1C4/k8YeheoTtMjl0oFU/8LiZc56moL4ZtpUJVzesYkOOlotFrG3nIX5980C5VardTvXPEPf3/4znEJ/95jHIZ+NaWNZO8sb9FG5eqK56SJSrl6wUJsRiMAif6J+Lr4KueW5Ti7+G84UEFxTTOzS4FA0GEI0S8QHCP169ZhkdVU+PZS6ro0M/CzmM388tzj/Pzso3x+9818ed+tLP3yI/Zv2YCpqfF0DLndFB/Yz68vPMG8N16gsiDP6VzP4aMZfe3Np2lkAoFAcIZiaoB5d8L8e8BqdNTHjILbVkHkoNM3tkOo1DD9Q+g1w1FXnQtfT4Hq1k3ZBJ0fSZJIGjeJS558CYOHwzRv1+rlxyX8Y5MDcPN2pCXesTyv1XZeFzpC/G01NdT+8w8AapWaMRGO7S3LcpcxMSGIQxl/ZRkWCkM/geCkIES/QHCM1K9eTYVvL2xqR97a2Gah/alL/6I407FfsrKwgG1/L2Tu6y/wwY1X8Mtzj7Fh7q8UH9jfITl0O4LaijL++vBtvnvsPnJ3Ors7+4VHcuFjzzHp7odQqdRHuIJAIBCcg5Tvhy/GwrbvnetHPmw37DvV4fxtodbARZ9D98mOuqpse6h/beeLShO0n/BeCVz6zCu4enkrdbtWL+evYxT+9vR9YUo5d1cFFYUt0/cZkpLQxTgyU1T/Pls5bu7iX9JQQoUlk4HRjtX/+TtEiL9AcDLQHL2JQCA4hCzL1K1aTYn/JKXOK8CAX5h9/5rZ2MSGOb8csb/NaiF3Vyq5u1JZ8+M3uHp5E9U7qcNd8NVaHa5e3rh5++Dm7XPw2Bu1xtkt2tTUyKY/fmfz/DlYTEanc65e3gy79GoSxox1Cg0UCAQCAbDrD/sKv7HGUWfwgQs/g65jT9+42kKthUu+gp+vhr2L7XUV++2h/tcvPLMmKQQdin9EFJc+/TK/PP84DdVVAKSvXg6yzIQ772/3pH788FA2L8zCarEvWqSuyGPUFd3/v737jq+6uv84/jrZCYEkkLBBZAuoUAdUQMRRF04UXNXan22tVquttnVUK85qq1atv9b+1NZabd2jTkRlqCgiDqbsDUnIICRkn98f53tX9rq5yc37+Xh8H99977n3cMj9nO8ZIdcYY0ifeTbZf/gjAMWffELFjh3E9+/PpH6T6BbfjeIKV1kwb8s8Zhx6Jp9uzANg2ZYCtuaVMKhnCiLSdhT0izRD2bffUpazhz0jxvmPDftOFsZrm/blu29SXJDvPzdp5nnsy8tj09dfsG9Pbq3XKyksYNWiD8Oebp+k1O7+yoCUtHS2rfwmJL0AcfEJHDbjTI484xwSkvVHV0QkRGUZzJsDnzwSerz/d2DWPyB9cGTS1VRxiTDrn/DsbNjwoTuWuwaeOBG+/xJkDIlk6iSMeg0cXDvwX/Qh1lpOvvIXTargT+6ewIgj+/hH71+9eBeTzhhKYkroQ4Uep59O9gMPQlUVWEvBK6+QdcUVJMQmMHXAVN7e9Dbg+vU/fvzl/O61FVR5AwO+8c1OLp82rO0+uIioeb9Ic+ybv4D8jNFUxSX5j/ma9peVlPDZqy/4j/cbPoqjzr2QEy+/mh//+Ul+8MdHOebiyxgy/jDi4hNqvXZ7KN1XRN72rWxd8TVrPl5QK+A/aOp0Ln3wL0w572IF/CIiNe1eAX87tnbAf8Rl8MO3O37A7xOfBOc9CwdMCRzLW+8GItzxZcSSJeHnAv/Qpv6rP5rPm4/8MTA1byMOOSYwoF9lWRWfvb6x1jXxvXuTOnWqf7/w5Vf8XRqDm/hvKNxAUdUOjhrWy3/slWXbWzy1oIjUTU/6RZph34L5ZGdN8O+nZiTS+4DuAHzx1quUFgWaeU6e/X1/CwBjDL0GDqbXwMEcduqZVJaXs231CjZ99QU7Vq+kokbT+taqKN1PcUFBrSb79RkweizHXHwZfYeNaNN0iIhEheoq+OTP8P7tUFUeOB6f4o2Mf27k0tZSCSlwwX/g3+fDxgXuWHE2/P1UmPUUDD+u4ful0+o1cBCzbrmb5+bc4H/iv+Zj92/glJ/9stEn/lmDuzNwdAbbVrsHB19/uI0RR/Sh79C0kOvSZp7Nvg8/BKBi61ZKPltCt0kTmTpgKnExcVRWVwLuaf8Z409k4VrXInL1riJW7NjLuAGhryciLaegX6SJqvbupfjLr8mdGJj2aOgE17R//74iPn/9Zf/xQWMOZvDBh9b7WnEJCQw5ZAJDDplQ7zWtZa31gv98igsLKCnId9sFBZQUuu3YuHgOmnoMw4/4rr+CQkREguRvhld+Cps/Cj3e52A3MF7v0ZFJV1tITIULX3Sfb7nXUq18HzwzC05/BMafH9n0Sdj0GjiIWbfezfNzbvS3+lvz8QKw1g3c20jgP+38Ufz79s9c334L7z+1itk3HUlsfKARcfdp04jNyKAq373+nscfp9ukiaQmpDKx30Q+2u7K1Ptb3uex4y/hlleXU1LuWhu8+MU2Bf0ibUhBv0gTFX/8MQXdh1EZ381/bJjXtH/pf1+mfH+J//hRsy+KeBBtjCEhOYWE5BQy+g1o/AYREQmwFr58Bt76NZQXBY6bGJh8DRxzA8RFpqtWm4pLcIMP9ugPHz/kjlVXwiuXQ9FOmHItqFI4KvUaMIhzb7krNPD/ZCEWOLWRwD+9TwpHzBjC4lc2AJC/q4TP397ExNOG+q8xCQmkn3suex57DHCzHxUv/pRukyZy3ODj/EH/17lfU1yVx8nj+vHiF24awFe/3MENJx9EQpx6Iou0BZUkkSba//U3ZGeN9+8n90ig77A0SgoL+OLN1/zHh4w/jIGjx0YghSIi0iaKc90I969eERrwZwyBS9+C42+NjoDfJyYGvnc7nHQPEBTgz7sN3rzedW+QqNRrgHvi3y0jMG3et58s5I2H7qOqsrLBe8efMJjMQan+/S/e2kzutn2hr/8/PySmRw//fvb992OtZfqg6Zigf2sfbPmAmYcFHlDkFZfz4ZrsFn8uEQmloF+kibKuu4784cf494eOzyImxvDZqy9QUVbqPz551kURSJ1IB1RdBVUN/2gU6XDWvA2PToLV/w09/p1L4PJFMHhSZNLVHib9FM55AmKDKjSW/A2evwQq9kcuXRJWPfsPZNYtd5MaHPgvXsQbf7qXqsqKeu+LjY3h2O8fhIlxwXt1teWDf66iujowCF9sWhqZP/6Rf7/0668pencumcmZHJoV6AY5b8s8Jh3YiwHpyf5jvqf+ItJ6at4v0kS71hewvyTwtGPYhCyK8nL56t03/ceGHzFJg+FJ52MtlBZASZ4bpKy60luqoKoidL+6EqoroKwI9ueHLiV5QfsFUFboXt/EugHP4pMgLtmt45MD23HJkNQD0g+AjAPc09SMIdC9HzRx7miRVivJg/duhS+eCj3eLQtOfxhGnRyZdLW3cWdDam949oJAGV71OvzzLDjvGUjp2fD90in17D+AWbfezXO33cC+/DwA1n72Ma8/cA8zrvkNcfHxdd6XNbg7E04YzBfvbAYge3MRX7+/lfHHB2ayyLjoIvL++TSVu3cDkPPAA3Q/7liOHXwsX+Z8CcCSXUvYV1nE2d8ZwMPvrwPg/dXZ5BWX07NbFLWqEYkQBf0iTbR+WY5/OzEljv4j0/ng73+lssIbydkYjtJTfulIKstgz3o3FVdxDhTvgZJc13S5OAdK9rjtkj0ukA8XW+WaSAc3k26KmHg3BVrGkEBlQNpASEh1c43HJdWx9rZjE8FWByosbFVQpUVQBYathuQMSOmlfstdVVUlLH0SPrjTVVgFGz0DTvsTdMuMTNoiZcgUNwXh0zOhaIc7tuUTeOIkuOiFzjM1oTRLRr8BzPrdPTw350b27XEj6a///FNev/8uTrv2BuIS6g6+jzh1CBu+zKFgtxvb6NNXN3DgoZmkZbmpf2OSksj82ZXs+u0tAJRv2kTBiy9x7MnHcv/S+wGotJUs2LaAmd+Z7g/6K6osr325nR9MPjCsn1ukKzCaB1M6G2PMWGC5b3/58uWMHRv+PvSFOSWs/yKH9V9k03NAKoef1JMnrvkJ1V7z5VFHHc2Mn/8q7OkQqaViP+SuhZw1kLPaW9ZA3gYX7Erj4pJdhULaQEgfBGmDvH1v3WNAdPXhFmfDh/D2DZC9MvR4Qnc4+fcw/oKuXRlUuA2ePgdyVgWOpWTCuX+HA6fWe5t0bgW7d/HcnBsoyg087Bgy/jBO/+WNxCck1nnPjrX5vPzHZf79AaMyOOOa8f5BjW1lJRtOP4PyDW7gv7isLIa9+w4z372AdQUuyD/hgBO4/5j7Oed/P+bzza4C7uABabx+1ZSwfM7mWrFiBePGjQs+NM5auyJS6RFpDgX90ulEKugPVl1Vzdy/PczyD+Z6aYrhB/c/Ss/+A9s1HRJB1VWuOXBJbmDebmsB663xtr01uFG/YxO8JT5oOy6wHRPnXrtsr3vqWFroLQVuvb8gcKxoJ2SvgvxNgfdoL7EJkNzTPSUPWdJD92PioLLUVUz41hX7oXI/VJRCRYk7XpwLBZuhYGt4Wx20mHGfJ7G764qQ6Ft8+90D+3GJgW4RVRXu81R53SKC9221+3cQExf0byLetXCo+e8i5N9LPdsxsVBe4rpelO11S6m3Livytr1z4L2v7/3ivHV86PGEFJfPKT0D+e3b7syVIHkb4N3f1u63DzDie3DKH1zrEnH/D/37wtApC02sG/hv0hVdu1IkihVm7+a5OTeyN2e3/9gBh0zgjOtuIj4xqc575j+zhuULtvv3p39/NGMm9/fv7507l+1XXe3fz/rFL3j2iFIe+9qN7p8cl8yC2Qt4+YtsbnjpG/917157NCP7dG+zz9ZSCvqlM1PQL51ORwj683Zs5++//Cm2uhqAsdOO56QrrmnXNEiYVJS65vB5G6E4O9AUvjgndLskj3YPtFsjIdU1Ye+W5Zoqp2S6dfB2Sk/X9z4mzgWQMV4gGLwfG+9+8MfGh+fHfnUV7N3hKgDyN3mLt12wGfbtbuQFpN0kpHoVAhmQlAbx3dxYDfEp3joZEmocS+wOGQdCr2HuXHsrK4IFf4DFjwYq63x6jYCT7oYRJ7R/ujq6ilJ49UpY/kLo8XEz3XgHkchLCbu9udk8P+cmCnbv9B8bPO4Qzrz+FuKTagf+5fsreXbOp+zLLwMgITmOC26dSLd01zrAWsvm885n/1dfARDTvTuVzz3EeQsCA/09cuwjTMg6iiPueI+ySvcb6ydHD+WGUw4K2+dsKgX90pkp6JdOpyME/W88dB+rP5oPQExsHD988C+k9e7brmmQVrAWinbBnrWuWXzu2sB2wRY6VTAfwri+tr0PgqxRkDXarTNHumArGlRXubEKKksbX/srLmJdRUVMXNAS49YYV7lTuM21Mijc5i1bXOVDtWYfCJseA6DXcMgc4da9RkDmcNeloq0HcKyuhq+egfduc/kdLCkNjrkBjrjMVWZJ3ax1lSXv/ja021DvMTD7aVeRI1GnaE8uz99+I/k7d/iPDRwzjrN+fSsJScm1rt/0TS5v/Plr//6Bh2Zy8uUH+5v5F3/2GVsuvsR/vucPL+WioXPZVbwLgLOGn8WcyXO4+tllvPaVe8+s7ol88ptjiYuN7KRjCvqlM1PQL51OpIP+3C2b+MevrvI34T70hFM4/rIr2u39pZkqSmH3CtjxBez80m3nrmv+oHIdQUIqJKW7ICUpzT2ZzxwZFNyP0BO3tlRd5VoWFGyFwq2umbO/yXxRjWbzQc3pqypqNJevp/m8ifG6AJS75v5V5YEuAP5uABWBGRWazYR2O/B3S0h1lSAh3Q7K6+6CUL7PtWqpKG7zr7desYnQc6irAOhVY2nKgIuV5a5VyJ71sGeda7mz5VPIrvHb3MTAYZfC9JugW6/wfZ5os3EhvHCpa/Hkk5gGM/8GI0+MXLokbPbl7eG5228if0dgCr0Bo8dw9m9+R0JySq3r3318BWuXBFplnfijcQw/rLd/f8tPfkLx/AUAmIQE3r7nNB7PeRWAjMQMPpj1AYvW5XHJE5/573ny0iOYPirwGpGgoF86M43eL9JMHz33L3/AHxsfz8SzZ0U4ReJXM8Df8ZUbgKqlT2sTe3hN4LNqNIvPCjqe6UaM9/EHJKb2tm8KvKpyb6kICriCjpuY0OA+OcOlJVb/ZbermFjo0d8tTIxsWqyt/W8nZLvMBenxyYHgPiHVtWhoC5Vl3pSMeUHTM+YF1qWFgTEaKvZ765LAGA7BxxtTVebKbfDgcT5Jaa5FgK8SoOeBLj3BAX7+5sYHsBwyFU66B/qOa/g6qe3AqfDj+fDcxbD9c3esrBCeme1aTBx9fdv9u5MOIbVnL2bfejfP334Te7ZtAWD76pW8cNctzLzhNhJTQiubp84awdaVeZQWu/FZFvx7DQNHZ5DUzbWk6f2LX7BxwUKwFltezvS5OTw+3t2bX5bPsuxlTBl+GH16JLJ7r+sq8OLSbREP+kU6M/2CFGmG3RvWsW7JJ/798d87he49u9hUTh1J4XY3uNTmj2Db0pYF+HFJgWbFmSMD272GR0+TeOn8jHED50Vq8Ly4ROjRzy2tUV7sBtHLXeuCdN96z7rAAIMNKS10gaYv2Gyu9APgxDvdVHwagK7l0gbApW/CW7+CpX/3Dlr48C5X6XrWX92gnhI1uqVnMOuWu3j+9pvI3boZgJ3frua5OTdy4uU/p/eQof5rk7snMHX2COY+4WbF2F9UwUfPr+W4H4wBIGnUKHqcNoO9r70OQMI7ixh9YHdWp7kWRe9teY/D+x7OWRMG8pf56wF4d+VuCksqSEtRFxyRllDzful0Itm8/6W7b2Xjl0sBiEtM5EcPP05KWnq7vHeXZ61rsrvpo0Cgn7+p6ffHJkCfsdDvUMg6KBDk9xiop1IikWYt7Mv2KgB842x4T+/zN7a8tU5SutcqYBgMOhLGXwTxdY88Li209B/w5nWhAyP2HOr6+fdp3/F2JPxK9hbywh03k7N5Y+CgMRw8/QQmz/4+3dIzADdo3xuPfs3mb/b4Lxs8tidjJvdnyCGZVO3awfqTT4EK1xpgy4R+XHeS6zKSHJfMG2e9QeG+JI6/f4H//jvPGseFEyM3q4aa90tnpqBfOp1IBf3bV6/k37f+yr9/5JnnMvX8Sxq4Q1rFWvdEcNNCL9D/GPZua/w+8AL8cdB/PPQb79ZZB3XuKcZEuqqqSq+P/roay3rYu93NDNBrGPQcFtT/39tO6Rnp1HcN25bCc993+eETEwcTL4dpv3LdMiRq7C/aywt3/pbsjetDjscnJTPxzHM57NQziUtIoCivlGfnfEpFaWh3m+Tu8Yya2JesFa9T9ezf/Mdv/n4s3w50LXDOHXkut3z3Fs54ZBFfbSsE4DuD03npislh/nT1U9AvnZmCful0IhX0v3LfHaz/fDEACckpXPbI4ySnqvl3myrb54L8de+5palP8jNHwQHfhf7fUYAv0pVUlodv+khpnn05boC/TQtDj6dkwnG3wISL2n5WBomYitJSPn3lOT7/78tUeU/rfXpk9eHoCy9l5KTJbFiWw9wnVlLlTb9XU1rRJvptX0jvnGXkHtiNq88pBGOINbG8dMZLfLQyht++Goir3//lNIZmpYb1s9VHQb90Zgr6pdOJVNBfVlLM0jdeYekbr3D4jLP57jnnh/09o561kLMa1s51Qf6WT2rPnV2LcU1GD5gMQybD4KMgNatdkisiIg2oqoQP7oCPHqo9mGK/Q+Gk37sKWokahdm7WfjM31nzycJa5waMHsMxF/+I1J6DWb14J6s+2sHe3NI6Xye2spQ+2Z/z3thPWTDaDRZ47KBjuW3SfRx55zzKq1ylwZXTh3H9iaPD94EaoKBfOjMF/dLpRHrKvv1Fe4mNj69zftoQRbvctFgpvdRn3Ke8xD29z1kNGz6EdfMab7JvYqDvITBkigv0B09Sk10RkY4sezW8/RvY8EHtc+NmwglzIG1g+6dLwmb76pV8+NTf2LV+ba1zY44+linnX0xqei+2ry1g5aIdbFiWU+/T/7W9lrDowJcoiy/hqZOf4rF3q3lr+S4A+qclsejXxxIT0/6texT0S2emoF86nUgH/Y3atRxevxq2uwH/MLFuarfU3pDaB7r3cevUPu5Yt97tOLBUHX8krQUs2Gq3bauD9qv90xMSl+TSGZfs1vEp3rHk0Cab5cWQt9H1x89b7603uv63RTualsweA2D48W4ZOk39QUVEOhtrYc1b8M6NbjDGYHHJMOVamHy1+xsiUcFWV7Nq0YcsfPYf7MvbE3IuPjGJU3/+K4YddiQApcUVfPvZLlYu2sme7ftqvVZxfCHzh/2HjJFx/GDIH7jsqaX+c/+6bCKTh7f/zEkK+qUzU9AvnU6HDfory2HR/bDgD27u9a4kJt4L/uPcnN3NFZsABxwVCPSzRquProhINKgsg8WPur+N5TWCu7TBcPilkDYIuveF7v3cOrGRPtvWwv58KNhSe6kqg+QMb+npWoaFrL3jSWn6OxMmFaWlLHn9RZa89hKV5WX+4yYmhhMv/zljpx3nP2atJXt9Hp/+9kl2dBtDVVzoQ5A1WZ9y4gWHceuLhtx9rvvfWRMG8MDs8e3yWYIp6JfOTEG/dDodMujf8SW8eiXsXt7opeLJGALDT3BB/pApjf/IExGRzqtoF8ybA1/+q/FrE7p7lQBBFQGVpaHBfc0KhOaKTXBTC/pnfBgOmSO8WR96qUKgDRTtyWXhM39n1aIPQ44fc/FlHHbqmSHH9s6dy4Zf/pbVoy5gT6+QwJrSxCLKDhnAY2t3A5AcH8uSm48nNTEunMmvRUG/dGYK+qVOxphk4OfALGAkYIGNwAvAQ9baggimreME/ZVlMP9eWPRA6KBFJhYm/9w1TS/aDft8S3bQ9m73pCKapfZxP6rqWpJ6RDp1IiLS3rYthbd+Bds/j3RK6peUHqgE6DkM0gZ43fO8SojkDFUKNMOX77zBvCf/EuguCEw8axaTZ38fY4xrKblxAdkPPkjuvPXs7DuJtcPPoSoutOvH1wmVfJBcQbmBe885hFmHD2rXz6GgXzozBf1SizGmPzAXGFPPJZuAU621K9stUUE6TNC/fSm8ciXkrAo93nssnPln6D+h8deoLIPi3Mh1B7DWDZRnYrwfMCawbWIC+1j3lKWiFCr3B629pbLUravK3TgFPYdBzwMhUVMaiohIDdXV8M3zsPRJN7jrvt3eeDItlJIJ6YMhfRAkpLoK9ZI8192sJM/t15xNoDViEwKVAKl9vNYIfSBzJPQ9GNKHaADfGlZ/vIC3Hrmf6qpK/7FDDh/LcUMLiVn7JpQWYi1s/ziDoq3JlCams3rUheT1DP0putdU83ZKBX1GpvPcT9p3JggF/dKZKeiXEMaYOOAT4HDc0/2/AM8D1cDZwM+AGGA98B1r7d4IpDGyQX9FKXx4F3z8cOiPlJg4mPpLmHqd5ogXERFpqqpKKM6Bop2uG0Ct9S6IjYeMA1xwnzYI0g8ICvS7Nfz61kLZ3qCKgHw3sGzuWjfI7J61bsDZtqqAT+jugv/gpfdBEJfYNq/fSW1auphXH7iHyopA4D+yew4n919DXIyLR6orYfP7mZTmJWCBHf2OYvXImRgT2tf/y4RKbrzhuxzYr/0eLijol85MQb+EMMb8FHjU273aWvtwjfPnAc96u3Ostbe2Z/q8NEQu6N/yqeu7v6fGlDR9D4YzHoV+h7RPOkRERKTtVFVCweZAJUDuWtizzrVEKNrV+gqBmDg3SK2vAiBzpFvSD4DY9u2bHjbWaxVYWgile711IZTkwtq58O3b7Cg0vLxlLKXV8f7bBqfkc8bAVSSk94akNCq3fMvGuZlUlrjvZX9iT+YddREpdlTI28UkVXHWVYfTd1hGu3w8Bf3SmSnolxDGmFXAaGAV7j+zWu3tjDGvAzOAfKC3tbay5jVhTmNkgv55c2Dh/bgGEJ6YeJj2a5hyjXsKISIiItGlutp1ESjaCft2ubF6ina6bglFO91+4bamT0sbLCbejXOTOcJbRkKvEZA53I0d0JGUFUHOGsheCdmrIPdb13rCF9yX7XXd/BqRW5bCi1vGsa8y0PKh76D+nHXzvaSkp8Oe9ZS+9xSb73ye6nL3m6vSwJMzpjK0+ExMtXvqH0sZsy7vSc/xE8PycWtS0C+dWZRULUpbMMaMxgX8AM/UFfB7/oEL+jOA6bj+/9EvKY2QgL//BPd0v099Qx+IiIhIpxcTA916uYVx9V9Xkge7vgldclY3PJ5AdQXkrnFLTfHdID4J4pJc1wD/Ojl0Pz7ZLXHeOj4J4lNqHEtxx2MTQpc433aie3gRm+C6Lu5Z6wL74KVwS6u/SoDMPpmcd/h4Xnx/N/m5bprfXVt38J/bfsPMm+bQI3MYSbNvY0C/49h6+U+hupo4Cxe+u5B7Zq/m7N3nkFc2jrGpL7Gux90c2SapEoluetIvfsaYHwKPe7vTrLUL6rmuL7DT273TWntze6Qv6P0j86S/ugoePwF2LYfpN8B3r4qeJnkiIiLS9ipK3YC/wRUBud9CyZ5Ip6wdGdea4aDTYMwZ7qGJMZQUFvDi3beSvXG9/8rUXpnM+PmvGTDqIADynv4Xu++4w38+Ow2eOqc71+YNJH1MH/pe8GfiYttn0EQ96ZfOTEG/+Blj7gOu83YHWGvrbadmjCkBkoGXrLUz2yN9Qe8duT79uWtdn7Wske3zfiIiIhJ9ivcExg7I/dYbQ8AbULAtZxoIh5g41w0hazT06O9aQialQWKPwHZS0HZC93pnMygrKeHV+25n68pvQo6PnjyNqRf8gB6ZWey6407yn37af27NABjyxOOM731Qu3aBUNAvnZkeU0qw/t66ksCT/PrsAIYF3dM1ZI6IdApERESks/N1Fxg8KfR4ZTnkb3SVAPvz3cB4lWVumtzKsqB9bx08ba5/Gl3fdolraVBV1rI0mhj3hD5rNPQe4wYg7H2Qm5a3jWYpSkxJ4ewbbuONh+5l3ZLF/uOrP5rPuiWLOeL0szn82mso3riO8o/c+VHbYeVvrueQfy1EEyOKNI2Cfgnmqy4tto03ASn21mmteUNjTG8gq5m3DWvNe4qIiIh0SHEJkDXKLW2luipQOVBV7ioLqircdpW3HXysutJNj5g50o0HEGZxCQmcdu0NLHn9JT596T9UlJUCUFlexicvPMs3H8xlygXnU7x1Hd235AIwZlken991HUfefH/Y0ycSDRT0SzDfMKqlTbh2f417WuoKoN2n/RMRERHpEmJiITHVLR1UTGwsE888l7FHH8uifz/Fivnz/Of27cnl7cceps/48fQtXsSAPe5naven3yL/8BPIOOnkSCVbpNNQqxgJ5hutvykDPZga94iIiIiItFhqz16cdMW1XHjn/fQbOTrk3O7NG/lq4ACWDc6iNC6Wbw4wLBvYrrNGi3RaCvol2D5vndSEa33XtLCjmIiIiIhIbX2Hj+T8OfdxylXXkdorM+TczowefDB2MNXnXczUEd+LUApFOhc175dgRd46pQnXdvPW+a18z0eB55t5zzDg1Va+r4iIiIh0UMYYDppyDMMPn8SS119kyWsvUVnunjVZYtj+9iI2jZvGiCO+G+GUinR8Cvol2GZvnWCMybLW5jRwrW/U/nqn9WsKa202kN2ce4wxjV8kIiIiIp1efFISR517IeOmn8DCZ/7B6o/mAzDwoHEMP3xSI3eLCKh5v4RaFbRd7wj5xph+gG8411X1XSciIiIi0hZ6ZPbm1Kuv57zb7qXv8JEcc8mP9CBIpIn0pF+CfRa0PRlYXM91U4K2Pw5fckREREREAgaMHsMFd/xRAb9IM+hJv/hZa9cB33i7F5v6/ze9xFvnA/PDnjAREREREY8CfpHmUdAvNf2vtz4EuL7mSWPMbOBUb/cxa61G7xcREREREemg1LxfanoM+BEwAfi9MWYs8E+gHDgLuMq7bhNwdyQSKCIiIiIiIk2joF9CWGurjDEzgHnAaOBibwm2HZhhrS1s7/SJiIiIiIhI06l5v9Rird2Be9L/a+ALoAgow43UfzdwiLV2ReRSKCIiIiIiIk2hJ/1SJ2ttKXCvt4iIiIiIiEgnpCf9IiIiIiIiIlFKQb+IiIiIiIhIlFLzfumMEoJ31q1bF6l0iIiIiEgXUMfvzYS6rhPpiIy1NtJpEGkWY8zpwKuRToeIiIiIdFlnWGtfi3QiRJpCzftFREREREREopSCfhEREREREZEopeb90ukYY9KAaUGHtgLl7fDWwwjtVnAGsL4d3lcapnzpmJQvHZPypWNSvnQ8ypOOKZL5kgAMCtqfb60tbKf3FmkVDeQnnY73H2y796EyxtQ8tN5au6K90yGhlC8dk/KlY1K+dEzKl45HedIxdYB8WdaO7yXSZtS8X0RERERERCRKKegXERERERERiVIK+kVERERERESilIJ+ERERERERkSiloF9EREREREQkSinoFxEREREREYlSCvpFREREREREopSCfhEREREREZEopaBfREREREREJEop6BcRERERERGJUgr6RURERERERKJUXKQTINKJ5AC31diXyFO+dEzKl45J+dIxKV86HuVJx6R8EWkBY62NdBpEREREREREJAzUvF9EREREREQkSinoFxEREREREYlSCvpFREREREREopSCfhEREREREZEopaBfREREREREJEop6BcRERERERGJUgr6RURERERERKKUgn4RERERERGRKKWgX0RERERERCRKKegXERERERERiVIK+kVERERERESilIJ+ERERERERkSiloF8EMMZ8zxjznDFmqzGmzBiTY4x50xhzWgP3DDTG2CYul7Xn5+msjDF/b8Z36ls21fNa5xlj5hlj8owxpcaY9caY/zXGjGznj9XptUW+qLyElzFmkDHmAWPMKmNMiTGm2Biz3BhzjzGmTxPuV3kJg5bmi8pL+BhjDjDGPGyM+dYYs98Ys9cYs8gYc4UxJqEJ96ushEFL80VlRaRpFPRLl2aMiTPG/AN4BzgXGAgkAJnAycBrxpi/GmNMHbcf2n4plQaUB+8YY+KNMc8DzwLHAhlAIjAUuBxYZow5p91T2fWU19hXeQkTY8yJwHLgGmA0kAykAGOBXwPLjTFT6rlX5SVMWpMvqLyEhTHmPGA18DNgBJAEdAcmA38GlhpjBtRzr8pKmLQmX1BZEWmSuEgnQCTCHgMu9raXAX8E1gMjgZtxf3x+DKwF/lDjXt8fmv3AUY28z5a2SGwXcAvwYBOuewT3Y8ACv6hx7j7A98NrrndtDi6PbgbSgaeNMRuttUtbn+QuoS3yReUlDIwxw4EXgW5AFS4P3vJOzwCuwFVivm6MOdRaW/O7VXkJgzbIF5WXNuZVwvwL98CrGvg/4Hncdzwd+BUwDvjYGHOktXZ3jZdQWQmDNsgXlRWRprDWatHSJRfgOFxwYoF3gcQa59OBjd75QiC5xvn/eOc+jfRn6UoL8D9B+XZfjXPjcD+wLfACYGqcHw3ke+fnR/qzRNPSUL5451VewvO9Pxn0vc+u4/wlQef/WuOcyksHzBfvvMpL2+ZHAi7gs96/+bPquOZg72+9BZ6scU5lpQPmi3deZUWLliYsat4vXdkt3roQOM9aWxZ80lpbANzt7fYAjq9xv692+atwJVBCGWMGAfd7u6twT1eC/Qz3tKACuNZaa4NPWmtXA3d4u0cbYw4LY3K7jCbkC6i8hMtJ3nqZtfY/NU9aa/8BrPR2T61xWuUlfFqTL6Dy0tZOBwZ5249aa1+ueYG19hvgVm/3EmPM6KDTKivh0dp8AZUVkSZR0C9dkjGmPzDV233AWptXz6WvAU/hAprcoPtTcE3/Ab4MUzKltgdxFTAAV9asqAHO8NYLrLVb63mNp4K2z27DtHVlD9JAvqi8hFWWt17fwDWrvHXfGsdVXsKnxfmi8hIW04O2H23guqe9tQFmBh1XWQmPVuWLyopI0ynol67qBNwfD3BN9epkrd1lrb3EWvtLa+0nQafGESg/ql1uB8aYaQR+SL1orf2gxvmhBH48L6jvday1OcAab3daW6ezq2ksXzwqL+Gzy1uPauCaYd56h++AykvYtShfPCovbW+wty621q6q7yJrbS6BCv6JoLISZi3OF4/KikgTKeiXrupgb72fwNMWjDHJxpgR3jRLdY3Y7zPeW1sg3xhzrzFmhTd9T4Ex5iNvmpn48CS/S7rLW1cCN9Zx/qCg7XWNvNbGOu6RlmksX0DlJZz+660PNsbMrHnSGHMWge//paBTKi/h1dJ8AZWXcEj01vuacG2ltx7urVVWwqc1+QIqKyJNptH7pavy/UHebq2tNsaMB27H9cP0lYudxphHcYOS1WxG7utDVgV8jpuKyScRN4LsUcBlxpgZ1tqaT3KkGYwx0wmMyvu8tfbbOi7rH7Td2Ai92711T2NMYh35K03QxHwBlZdwmoNruTQUeNYY8xBuYNJq4Hu46eLATR13e9B9Ki/h1dJ8AZWXcPA9Je5ljEmy1pbWdZExJgk3qwIEnu6rrIRPa/IFVFZEmkxP+qWr6uWtC4wxFwCf4aZRCq4I64f7MfaeMaZHjft9f2jicDXMDwAnAt8FfgR8452fALzj9TuTlrsqaPv+eq7JCNpu7KlBcdB2WotSJNC0fAGVl7DxfsROAZ7Afb+/BN7BTSl2PRCPG3NhqrV2T9CtKi9h1Ip8AZWXcPjMW8cBpzRw3QkEfgf4vleVlfBpTb6AyopIkynol64q1VsPxk2ttB+4GhfoJ+Nqhn19k6fg5o0FwGv2f4i3mwNMtNb+wlr7rrV2sbX2/4DDcYMAgutzVl+zZ2mEMWYwboRfgIXW2s/ruTQxaLvOpwVB9tdznzRRU/NF5aVdHIH73urrkjQD93Q5mMpL+DU7X1RewuZ5oNzbvs8Y06vmBcaYVAIz9oCrmAGVlXBqcb6orIg0j4J+6ap8TcB642qHj7fWPuwN3FfqDdr3PeA977pzjTFHAXhT9YzGjf4/zVq7vOaLW2vLgYtx0wECXGmMiQ3fx4lqPwV8311DT5Org7ZtvVc5wT/Cq+u9ShrSpHxReQkvY8zVwCvAkcBi3NSi3XBPGWfgBrcaDvzHGBPcMkPlJYxami8qL+Fhrd1O4P+pocBiY8xMY0wPY0yKMeZ7wEJgLIGBFX3BqMpKmLQmX1RWRJpHQb90VcG19X+11i6peYG1thK4NujQBUHndlhrFzUy2mwh8KK3m45rXibNN8tbFwBvNHBdcLPLpEZeM/i8+ly2TFPzReUlTLy5wB/EBRof4H74zrPWllhr91pr38A1c/3Yu+VBY4zve1V5CZNW5ovKS/j8FnjO2x6Om7mnENck/x3coHD34MZeACjx1ior4dXSfFFZEWkGBf3SVRUFbb9W30VezbFvTt4jWvA+XwdtD673KqmTMWYMrvYf4HVrbUUDlwfnabdGXtp33uKCVmmGZuZLc6i8NM9PCDxZvNx7qhXCWrsf+LG3GwNc7m2rvIRPa/KlOVRemsGryD8P912vrXF6MXC6tfYGAn34s721ykoYtSJfmkNlRbo8jd4vXdWuoO3GRnPdBgwiMHJsc5QEbSe04P6u7rSg7ZrTWtW0OWh7QCPX+s7neD84pHmaky/NofLSPL6KyHUNzJyAtXaFMWYd7imab45rlZfwaU2+NIfKSzN5TcL/CvzVGNMX9+R3h7V2b9Blo721b/o9lZUwa2G+NIfKinR5Cvqlq1oOnOFtZzR0IYE/EAUAxphBuOZhvYG3rbXbGrg3K2i7JbXTXZ1vNN8SXDO/hgQ37xvWyLW+p9T1NgmUBjU5X1Rewsr3VLGgCddm44JL30wkKi/h0+J8UXlpP9baXYQ+AMAY0xMY4e1+5a1VVtpRU/NFZUWkedS8X7qqz4K2j6zvImNMDDDS293krY8HXgX+BpzayPv45jC3wBfNTmUXZoyJJ5A3S7zmsPXypsjy/dGf3MDrZhHI04/ru07q1tx8QeUlnHxzXA/x/q9qiP8JJKi8hFmL8wWVl7AwxowwxtxhjHncGDOkgUtPIfDbeB6orIRTa/IFlRWRZlHQL13VOwRGc/2fBkZzPQ3o7m37+v4vDDp/AfUwxowATvJ251prC1qW1C7rYAKDIn3axHte9tYnGGP613PNJUHbr7QgXV1dc/NF5SV8FnnrTGpPyednjJkEHFDjHlB5CZfW5IvKS3gkATcBPyQw1WgIbwq4a7zdHcCHQadVVsKjNfmisiLSDAr6pUuy1pYBf/Z2xwG/r3mNMaYf8CdvNwev77K1dh2BmuajjTH/U8e96cC/cVOaWeCONkx+VzEuaLvW7Ar1eAyows2P/JealTnGmFG4HxgAn1prP0Oaq1n5ovISVn8DfP2G/2yMqdXf2Hv6+IS3W4krIz4qL+HR4nxReQkPa+03wHpv93pjTFodl90JHOZt/75Gn3yVlTBoTb6orIg0k7VWi5YuuQDJwDe4PwQWmAvMxA2o9FNccz7fuVk17h0D7PXOVQP/B5wATAKuxA3847v33kh/1s64ALcHfYcTmnHfQ0H3fQScjZse61ogzzteDhwe6c/YGZeW5IvKS1jz4+ag7263tz8d15z1F8D2oPM313G/yksHyxeVl7DlyUVB39u3wKXev/WZwNtB594HYuu4X2Wlg+WLyooWLU1fIp4ALVoiueAGd1kc9Eeh5lIJXFnPvUfjBoSp795q4D7ARPpzdsYF9xTM911mNeO+eNw8v/XlSykwO9Kfr7MurcgXlZfw5cnvvO+voe/2d/Xcq/LSMfNF5SU8eXJPA9+pBd4CetRzr8pKx8wXlRUtWpqwGGstIl2ZN9DSxbja5kNwffi3AfOBP1nX/Ky+e3vhapNPxw3gkwDsxPU5+4u1tql90aUGY8zzwDlAmbU2qbHr67h/NnAZbnTfHrinbe8B91lrV7ZlWruS1uSLykv4GGMOBn6Ge5o80Du8DffdPtzQ/2Pe/SovYdCafFF5CQ9jzPHAVbinyRm4WRaWAE9Ya19owv0qK2HQmnxRWRFpnIJ+ERERERERkSilgfxEREREREREopSCfhEREREREZEopaBfREREREREJEop6BcRERERERGJUgr6RURERERERKKUgn4RERERERGRKKWgX0RERERERCRKKegXERERERERiVIK+kVERERERESilIJ+ERERERERkSiloF9EREREREQkSinoFxEREREREYlSCvpFREREREREopSCfhEREREREZEopaBfREREREREJEop6BcRERERERGJUgr6RURERERERKKUgn4RERERERGRKKWgX0RERERERCRKKegXERERERERiVIK+kVERERERESilIJ+ERERERERkSiloF9EREREREQkSinoFxEREREREYlSCvpFREREREREopSCfhEREREREZEopaBfREREREREJEop6BcRERERERGJUgr6RURERERERKKUgn4RERERERGRKKWgX0RERERERCRKKegXERERERERiVIK+kVERERERESilIJ+ERERERERkSiloF9EREREREQkSv0/L8rwUpPqGrYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 840x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plate_id = '220519-plate1'\n",
    "primer = ['Itga9 near sg v1', 'Itga9 near sg v2']\n",
    "# df_annotation = get_annotation_data(plate_id)\n",
    "\n",
    "plot_melting_curves(plate_id, primer, save_fig=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c4c82282-37d7-48e3-870c-7a0f420f172f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sg1 = get_expression_data(df, 'Serpinh1 sg1 v2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "697fd19e-be65-4465-847c-fe2eed124674",
   "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>Sample</th>\n",
       "      <th>Cq_ref</th>\n",
       "      <th>relExp_25_x</th>\n",
       "      <th>Cq_test</th>\n",
       "      <th>relExp_25_y</th>\n",
       "      <th>deltaCq</th>\n",
       "      <th>relExp</th>\n",
       "      <th>Group</th>\n",
       "      <th>sgRNA_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A-188-1</td>\n",
       "      <td>19.308192</td>\n",
       "      <td>51.709623</td>\n",
       "      <td>24.121491</td>\n",
       "      <td>1.838877</td>\n",
       "      <td>4.813299</td>\n",
       "      <td>0.035567</td>\n",
       "      <td>A-188</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A-188-2</td>\n",
       "      <td>19.454663</td>\n",
       "      <td>46.797256</td>\n",
       "      <td>24.288221</td>\n",
       "      <td>1.639209</td>\n",
       "      <td>4.833557</td>\n",
       "      <td>0.035071</td>\n",
       "      <td>A-188</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A-188-3</td>\n",
       "      <td>19.239314</td>\n",
       "      <td>54.277856</td>\n",
       "      <td>24.143611</td>\n",
       "      <td>1.810665</td>\n",
       "      <td>4.904296</td>\n",
       "      <td>0.033393</td>\n",
       "      <td>A-188</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A-188-4</td>\n",
       "      <td>19.452289</td>\n",
       "      <td>46.958306</td>\n",
       "      <td>24.888545</td>\n",
       "      <td>1.081469</td>\n",
       "      <td>5.436256</td>\n",
       "      <td>0.023095</td>\n",
       "      <td>A-188</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A-188-5</td>\n",
       "      <td>20.507010</td>\n",
       "      <td>22.668028</td>\n",
       "      <td>26.952580</td>\n",
       "      <td>0.258375</td>\n",
       "      <td>6.445570</td>\n",
       "      <td>0.011473</td>\n",
       "      <td>A-188</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>A-228-1</td>\n",
       "      <td>19.869762</td>\n",
       "      <td>35.150132</td>\n",
       "      <td>26.942180</td>\n",
       "      <td>0.260256</td>\n",
       "      <td>7.072418</td>\n",
       "      <td>0.007430</td>\n",
       "      <td>A-228</td>\n",
       "      <td>228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>A-228-2</td>\n",
       "      <td>20.397910</td>\n",
       "      <td>24.297695</td>\n",
       "      <td>28.012417</td>\n",
       "      <td>0.124185</td>\n",
       "      <td>7.614507</td>\n",
       "      <td>0.005103</td>\n",
       "      <td>A-228</td>\n",
       "      <td>228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>A-228-3</td>\n",
       "      <td>20.466661</td>\n",
       "      <td>23.163913</td>\n",
       "      <td>27.626942</td>\n",
       "      <td>0.162221</td>\n",
       "      <td>7.160281</td>\n",
       "      <td>0.006991</td>\n",
       "      <td>A-228</td>\n",
       "      <td>228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>A-228-4</td>\n",
       "      <td>19.722219</td>\n",
       "      <td>38.821736</td>\n",
       "      <td>26.797408</td>\n",
       "      <td>0.287744</td>\n",
       "      <td>7.075189</td>\n",
       "      <td>0.007416</td>\n",
       "      <td>A-228</td>\n",
       "      <td>228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>A-228-5</td>\n",
       "      <td>19.968454</td>\n",
       "      <td>32.746717</td>\n",
       "      <td>27.165812</td>\n",
       "      <td>0.222870</td>\n",
       "      <td>7.197358</td>\n",
       "      <td>0.006814</td>\n",
       "      <td>A-228</td>\n",
       "      <td>228</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Sample     Cq_ref  relExp_25_x    Cq_test  relExp_25_y   deltaCq  \\\n",
       "0  A-188-1  19.308192    51.709623  24.121491     1.838877  4.813299   \n",
       "1  A-188-2  19.454663    46.797256  24.288221     1.639209  4.833557   \n",
       "2  A-188-3  19.239314    54.277856  24.143611     1.810665  4.904296   \n",
       "3  A-188-4  19.452289    46.958306  24.888545     1.081469  5.436256   \n",
       "4  A-188-5  20.507010    22.668028  26.952580     0.258375  6.445570   \n",
       "5  A-228-1  19.869762    35.150132  26.942180     0.260256  7.072418   \n",
       "6  A-228-2  20.397910    24.297695  28.012417     0.124185  7.614507   \n",
       "7  A-228-3  20.466661    23.163913  27.626942     0.162221  7.160281   \n",
       "8  A-228-4  19.722219    38.821736  26.797408     0.287744  7.075189   \n",
       "9  A-228-5  19.968454    32.746717  27.165812     0.222870  7.197358   \n",
       "\n",
       "     relExp  Group sgRNA_id  \n",
       "0  0.035567  A-188      188  \n",
       "1  0.035071  A-188      188  \n",
       "2  0.033393  A-188      188  \n",
       "3  0.023095  A-188      188  \n",
       "4  0.011473  A-188      188  \n",
       "5  0.007430  A-228      228  \n",
       "6  0.005103  A-228      228  \n",
       "7  0.006991  A-228      228  \n",
       "8  0.007416  A-228      228  \n",
       "9  0.006814  A-228      228  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sg1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4b470502-bb83-4815-97e9-a9dd204d42ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Group', ylabel='relExp'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(data=df_sg1, x='Group', y='relExp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b96876ad-46e2-446c-8b58-5947c1b37e2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Group', ylabel='relExp'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data=df_sg1, x='Group', y='relExp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b6c69dab-e451-4279-9b6f-bf2f39fc6943",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sg2 = get_expression_data(df, 'Serpinh1 sg2 v1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "2be6a5c6-2e38-43d4-860e-c0236f6253de",
   "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>Sample</th>\n",
       "      <th>Cq_ref</th>\n",
       "      <th>relExp_25_x</th>\n",
       "      <th>Cq_test</th>\n",
       "      <th>relExp_25_y</th>\n",
       "      <th>deltaCq</th>\n",
       "      <th>relExp</th>\n",
       "      <th>Group</th>\n",
       "      <th>sgRNA_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A-188-1</td>\n",
       "      <td>19.308192</td>\n",
       "      <td>51.709623</td>\n",
       "      <td>24.375034</td>\n",
       "      <td>1.544511</td>\n",
       "      <td>5.066842</td>\n",
       "      <td>0.029835</td>\n",
       "      <td>A-188</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A-188-2</td>\n",
       "      <td>19.454663</td>\n",
       "      <td>46.797256</td>\n",
       "      <td>24.565618</td>\n",
       "      <td>1.351385</td>\n",
       "      <td>5.110955</td>\n",
       "      <td>0.028937</td>\n",
       "      <td>A-188</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A-188-3</td>\n",
       "      <td>19.239314</td>\n",
       "      <td>54.277856</td>\n",
       "      <td>24.470453</td>\n",
       "      <td>1.443624</td>\n",
       "      <td>5.231139</td>\n",
       "      <td>0.026624</td>\n",
       "      <td>A-188</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A-188-4</td>\n",
       "      <td>19.452289</td>\n",
       "      <td>46.958306</td>\n",
       "      <td>25.152901</td>\n",
       "      <td>0.899671</td>\n",
       "      <td>5.700612</td>\n",
       "      <td>0.019228</td>\n",
       "      <td>A-188</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A-188-5</td>\n",
       "      <td>20.507010</td>\n",
       "      <td>22.668028</td>\n",
       "      <td>27.132403</td>\n",
       "      <td>0.228081</td>\n",
       "      <td>6.625392</td>\n",
       "      <td>0.010129</td>\n",
       "      <td>A-188</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>A-229-1</td>\n",
       "      <td>20.070591</td>\n",
       "      <td>30.472156</td>\n",
       "      <td>27.268291</td>\n",
       "      <td>0.207599</td>\n",
       "      <td>7.197701</td>\n",
       "      <td>0.006812</td>\n",
       "      <td>A-229</td>\n",
       "      <td>229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>A-229-2</td>\n",
       "      <td>20.670557</td>\n",
       "      <td>20.111401</td>\n",
       "      <td>28.247522</td>\n",
       "      <td>0.105413</td>\n",
       "      <td>7.576966</td>\n",
       "      <td>0.005237</td>\n",
       "      <td>A-229</td>\n",
       "      <td>229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>A-229-3</td>\n",
       "      <td>19.766588</td>\n",
       "      <td>37.625153</td>\n",
       "      <td>27.228276</td>\n",
       "      <td>0.213472</td>\n",
       "      <td>7.461688</td>\n",
       "      <td>0.005673</td>\n",
       "      <td>A-229</td>\n",
       "      <td>229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>A-229-4</td>\n",
       "      <td>19.765525</td>\n",
       "      <td>37.658369</td>\n",
       "      <td>26.545040</td>\n",
       "      <td>0.343046</td>\n",
       "      <td>6.779515</td>\n",
       "      <td>0.009103</td>\n",
       "      <td>A-229</td>\n",
       "      <td>229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>A-229-5</td>\n",
       "      <td>19.735918</td>\n",
       "      <td>38.466698</td>\n",
       "      <td>26.342547</td>\n",
       "      <td>0.394739</td>\n",
       "      <td>6.606629</td>\n",
       "      <td>0.010261</td>\n",
       "      <td>A-229</td>\n",
       "      <td>229</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Sample     Cq_ref  relExp_25_x    Cq_test  relExp_25_y   deltaCq  \\\n",
       "0  A-188-1  19.308192    51.709623  24.375034     1.544511  5.066842   \n",
       "1  A-188-2  19.454663    46.797256  24.565618     1.351385  5.110955   \n",
       "2  A-188-3  19.239314    54.277856  24.470453     1.443624  5.231139   \n",
       "3  A-188-4  19.452289    46.958306  25.152901     0.899671  5.700612   \n",
       "4  A-188-5  20.507010    22.668028  27.132403     0.228081  6.625392   \n",
       "5  A-229-1  20.070591    30.472156  27.268291     0.207599  7.197701   \n",
       "6  A-229-2  20.670557    20.111401  28.247522     0.105413  7.576966   \n",
       "7  A-229-3  19.766588    37.625153  27.228276     0.213472  7.461688   \n",
       "8  A-229-4  19.765525    37.658369  26.545040     0.343046  6.779515   \n",
       "9  A-229-5  19.735918    38.466698  26.342547     0.394739  6.606629   \n",
       "\n",
       "     relExp  Group sgRNA_id  \n",
       "0  0.029835  A-188      188  \n",
       "1  0.028937  A-188      188  \n",
       "2  0.026624  A-188      188  \n",
       "3  0.019228  A-188      188  \n",
       "4  0.010129  A-188      188  \n",
       "5  0.006812  A-229      229  \n",
       "6  0.005237  A-229      229  \n",
       "7  0.005673  A-229      229  \n",
       "8  0.009103  A-229      229  \n",
       "9  0.010261  A-229      229  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sg2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "67053bf4-dc70-423b-beab-9025898c0df9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Group', ylabel='relExp'>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(data=df_sg2, x='Group', y='relExp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "9c68a898-c7f6-47ab-9684-32ff9fc44529",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Group', ylabel='relExp'>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data=df_sg2, x='Group', y='relExp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "90a8c40b-f26d-49a2-a900-ff29038991f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sg3 = get_expression_data(df, 'Serpinh1 sg3 v1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "cbf8acb1-bbed-4b32-a3d3-28554c7fbb4f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Group', ylabel='relExp'>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+ktQg4y9JDfo/kvZbyn8cNjIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(data=df_sg3, x='Group', y='relExp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "b67385e5-eda6-496e-a542-8fc2579aeb4b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Group', ylabel='relExp'>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data=df_sg3, x='Group', y='relExp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "290aa8ee-5268-4e3b-9673-2c2f8d0ee91e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}