Stock-Trend-Prediction-LSTM.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c448eebf-9d5a-47aa-9b92-6fe76b211cb2",
   "metadata": {},
   "source": [
    "### Import Required Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a650ed37-1c9f-454d-89cd-5e5dd48c4b18",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import yfinance as yf\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2bb7872-257d-4cf8-8ded-9f97b31c3de9",
   "metadata": {},
   "source": [
    "### Scraping Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "08f1c5f9-f23b-4a02-be59-faa947a66b1d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[*********************100%%**********************]  1 of 1 completed\n"
     ]
    }
   ],
   "source": [
    "data = yf.download(\"HBAR-USD\", start=\"2019-09-17\", end=\"2024-03-31\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "17a7db47-587d-4e03-89ca-c945e0fe5a19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        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>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-09-17</th>\n",
       "      <td>0.416009</td>\n",
       "      <td>0.416009</td>\n",
       "      <td>0.087753</td>\n",
       "      <td>0.090177</td>\n",
       "      <td>0.090177</td>\n",
       "      <td>10855378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-18</th>\n",
       "      <td>0.090519</td>\n",
       "      <td>0.100272</td>\n",
       "      <td>0.080045</td>\n",
       "      <td>0.086921</td>\n",
       "      <td>0.086921</td>\n",
       "      <td>14772274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-19</th>\n",
       "      <td>0.087702</td>\n",
       "      <td>0.087721</td>\n",
       "      <td>0.054469</td>\n",
       "      <td>0.057924</td>\n",
       "      <td>0.057924</td>\n",
       "      <td>27324784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-20</th>\n",
       "      <td>0.058087</td>\n",
       "      <td>0.059061</td>\n",
       "      <td>0.047800</td>\n",
       "      <td>0.052490</td>\n",
       "      <td>0.052490</td>\n",
       "      <td>15814443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-21</th>\n",
       "      <td>0.052402</td>\n",
       "      <td>0.055408</td>\n",
       "      <td>0.045456</td>\n",
       "      <td>0.048021</td>\n",
       "      <td>0.048021</td>\n",
       "      <td>13144171</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Open      High       Low     Close  Adj Close    Volume\n",
       "Date                                                                   \n",
       "2019-09-17  0.416009  0.416009  0.087753  0.090177   0.090177  10855378\n",
       "2019-09-18  0.090519  0.100272  0.080045  0.086921   0.086921  14772274\n",
       "2019-09-19  0.087702  0.087721  0.054469  0.057924   0.057924  27324784\n",
       "2019-09-20  0.058087  0.059061  0.047800  0.052490   0.052490  15814443\n",
       "2019-09-21  0.052402  0.055408  0.045456  0.048021   0.048021  13144171"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fa10f0bf-dd84-4743-b411-7fbeebed7546",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-03-26</th>\n",
       "      <td>0.117147</td>\n",
       "      <td>0.130246</td>\n",
       "      <td>0.116938</td>\n",
       "      <td>0.120330</td>\n",
       "      <td>0.120330</td>\n",
       "      <td>163477891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-03-27</th>\n",
       "      <td>0.120330</td>\n",
       "      <td>0.121382</td>\n",
       "      <td>0.112298</td>\n",
       "      <td>0.113734</td>\n",
       "      <td>0.113734</td>\n",
       "      <td>108853536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-03-28</th>\n",
       "      <td>0.113734</td>\n",
       "      <td>0.117463</td>\n",
       "      <td>0.111356</td>\n",
       "      <td>0.116196</td>\n",
       "      <td>0.116196</td>\n",
       "      <td>64238270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-03-29</th>\n",
       "      <td>0.116196</td>\n",
       "      <td>0.117743</td>\n",
       "      <td>0.112648</td>\n",
       "      <td>0.116099</td>\n",
       "      <td>0.116099</td>\n",
       "      <td>54339428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-03-30</th>\n",
       "      <td>0.116099</td>\n",
       "      <td>0.116458</td>\n",
       "      <td>0.112933</td>\n",
       "      <td>0.113619</td>\n",
       "      <td>0.113619</td>\n",
       "      <td>44790919</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Open      High       Low     Close  Adj Close     Volume\n",
       "Date                                                                    \n",
       "2024-03-26  0.117147  0.130246  0.116938  0.120330   0.120330  163477891\n",
       "2024-03-27  0.120330  0.121382  0.112298  0.113734   0.113734  108853536\n",
       "2024-03-28  0.113734  0.117463  0.111356  0.116196   0.116196   64238270\n",
       "2024-03-29  0.116196  0.117743  0.112648  0.116099   0.116099   54339428\n",
       "2024-03-30  0.116099  0.116458  0.112933  0.113619   0.113619   44790919"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "459a44eb-8ba6-487b-be81-47187e5c12c4",
   "metadata": {},
   "source": [
    "### Data Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "38393766-e848-4602-bd2e-247eb691e549",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ebcfaefa-a85f-4ef7-89de-5df837d83a02",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.drop(['Date','Adj Close'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fdfcd18b-1fab-4e1c-88e8-eaf225165ea9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1c7f25b0390>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(data.Close)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "872d2f52-89c9-4d75-9c6c-c05767316e73",
   "metadata": {},
   "source": [
    "### Moving Averages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c9fca18a-5cce-49a6-a818-b0ccd581fc95",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Moving Avg 100 Days\n",
    "ma100 = data.Close.rolling(100).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "cf812c23-463c-411a-b73e-fb2dd29e5a9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0            NaN\n",
       "1            NaN\n",
       "2            NaN\n",
       "3            NaN\n",
       "4            NaN\n",
       "          ...   \n",
       "1652    0.093735\n",
       "1653    0.094078\n",
       "1654    0.094424\n",
       "1655    0.094715\n",
       "1656    0.094939\n",
       "Name: Close, Length: 1657, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ma100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8e4c95e8-e659-4092-95ac-3d8dff62ba15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1c7f2641a90>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "plt.plot(data.Close)\n",
    "plt.plot(ma100,'r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "93b426ae-a9bf-4d12-a3f2-d2a9f5b92ae7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Moving Avg 200 Days\n",
    "ma200 = data.Close.rolling(200).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "98774857-4d09-427a-b3dc-d4b4e89f3437",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1c7f26fe310>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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iOkejiSyqlpZ/c311+LyNyuB+FMu//b+GpdV2z7FVoZGZUnMz+XP/nqzwK/+W3iuFmWoiIqKkF9fu32VlZRgzZgxmzZqF7OzssK+bPHkySkpKPP8OHToUx1kSESW/CGNqn220AnWuJn/y8m8xe2xX+BpWWrxBtcXm/7o00Bbf45Dvd707v9yTvRbXUlvs3o7fZmaqiYiIkp4+kpOzs7Oh0+mQn5/v83x+fj6aNGnid/7evXuxf/9+XHbZZZ7nnO6/9PR6PXbt2oV27dr5XWcymWAymSKZGhFRnaaNIVOtVLpMyuTl38Ey1RVWb/CrmKm2e58TS/DlDc++3HwE6SbhV7G4ltoivY5VBkREREkvoky10WhEr169sGLFCs9zTqcTK1aswIABA/zO79ChA7Zt24bNmzd7/l1++eUYPHgwNm/ezLJuIqIwBVpTXW1zKJZ3S4Mxln+HT75PtadRmcIbE5XW4JlqaVZaDMrl4xwuqsLfeWUAvOXfUg6uhyciIkp6EWWqAWDSpEm4+eab0bt3b/Tt2xevvfYaKioqMHbsWADATTfdhObNm2PatGkwm80488wzfa6vV68eAPg9T0REgSllqsuqbej13HJ0aJqBr+452+c1aSDN8u/wiTGv+PUWy8CVmr1VWLyZamnJtkj6dbe6s89WSVMyeSm4GFRf1rUZHvl8qzAfviFCRESU9CIOqkeNGoUTJ07gqaeeQl5eHrp3746lS5d6mpcdPHgQWm1cl2oTEZ1ylBqV/b6vEFaHE1sPl/i95lP+zcAsbPJMtZg8VgqqfTLV9uBrqsWgWsxUN6+Xgv0Fvh3DM1MMAITmZGMHtsaHv+1nUE1ERFQLRBxUA8A999yDe+65R/G1VatWBb12zpw50dySiOiUplT9HSzgcjJTHRVPozL3F1zMWMuDaqfThUrpmmqFoFr6dbc5nJj2/U68+/M+AECTLLNfUJ3lDqoB75puln8TERElP6aUiYhqAaXyb2lQ7ZIFX9xSKzri100s+xa/7vL3JapsvuXeiuXfdu/Xvdrm8ATUAGDS+3f19gmqxbJzfu+IiIiSHoNqIqJaQKlRWbASb2kgze7f4fOUf4trqt1fd3mmukJS+g34ln+fKLOgoNziU/59qMg3K23QaXD72W18nss0e4vHxKCeRQZERETJj0E1EVGSkmaflXbUcjh9y4ulfPapdjIyC5dTlqkOlDGutMgy1e7u39U2B/pMXY5ezy9HtSSbve9Ehc/5Bp0WT1zaCWe3z/Y8p5d0/xaD+tm//YsHFm6O5VMiIiKiOGNQTUSUpKTZZ6VGZdI4WlpqDLD8O1piUt+bqRbXVPueJ89Ui1npk+UWz3OlVTbPsTyoNhuE8m+TXvnXsFZSmrB40xGUSMYiIiKi5MKgmogoSUmDYaU11T5bNsky1b5bajGoDpe8+7c2QMMw+ddUXFMtffOjWrLO+khxlc/5YjAtBtdyelm9/6aDReF9AkRERJRwDKqJiJKU3Seo9n9dWl7sV/4tXW/Nhblh83T/lpV/yxvByb/eYvm3lHQf63KLb2ZbDKpvPbs1AOC8Mxr5vK6TfcPlmW4iIiJKHlFtqUVERPEnDYaVMtXVtsBrqn0albH8O2xiRlos/xa/7Kt3n8SWQyV45KIzYDboYJNtoSVWCki/Z9J9rMuqfcu3Te4Mda9WDbD60cHIyTT7vC7/fssrEYiIiCh5MKgmIkpSoYLhqmCZasm12w6XqDuxOsxb/g33oxDcfrbhMACgcaYJdw5q5wlyNRrA5fJmqqVl4eWSTLX8W2mUNCVrUT/Vbx46WR2Z0j7YRERElBxY/k1ElKSk2Wb5lk4AYJEE1dYgjcqW7shDUYU1DjOsezz7VMsalYkOu7fGEoPndJPw3rS4ftou6bReKSv5lgrUoEzkl6lmUE1ERJS0GFQTESUpafZZ3igLCJ6plnf8LqxkUB2OQI3KRHqt8GtT/Ho3cZdtl1TZUGGx+3Rhr7D6brslZTIE//UrX1PN8m8iIqLkxaCaiChJSQNjhZg67EZlgPKabPLn8Nun2vd1g054Xvx652Sa0STTDJcL2Hms1GdP8CprsEy1ctdvkV9QzUw1ERFR0mJQTUSUpKRrqpX2mq6yBdtSy/dcedBNysQvk3yfapHeHWWLQa5Bp8GZzTMBANuPlMDuCDNTHaL8Wx5UWxhUExERJS0G1URESUoaoCmtqZZ2mpbvmywPwhlUh8ev/FsW3Bq0YqZaOM+g06Jd43QAwP6CyoDdv+VCln9zTTUREVGtwaCaiChJSZteORUy1dJMtnyLJ/m+ynaHQv04+QnVqEzMVItvUhj0WrRumAYA2F9QAZvTv/t3syzf7bIAwKgLXv4tD+a5ppqIiCh5MagmIkpSvplqpdeD7FMtD6qdDMrCIc9U62RL0fWyNdVGnRatGgpbYh2QZaor3N2/G6Qb/e4TsvzbL1MduJSciIiIahaDaiKiJOWzplqp/Fvyuv+aann5NzPV4RC/zmKDMnmmWgx2xa+3QadB22yh/PtgYSXKqr0l33uOlwMAGqSZ/O4Tafdvfv+IiIiSF4NqIqIkFWqfaunr8qBLfj7Lv8Mjfk095d+y4FZ8I0PcOsug0yIn04TGGSY4nC5sOljkN2bDNKVMdYTl31xTTURElLQYVBMRJSlpKbHimmqHNKgO0f2b5d9h8S//lgXV7q+5Z021TguNRoPuufUAABsPFvuN2UAxqI6s/Hv1npPYfqQk9CdARERECcegmogoSfluqaX0euA11fIgXN7IjJT5NSqT/ZZ0uL/mYvm30R0cN0wXSryLq6x+YyoG1RGWfwPAw59vDXoNERER1QwG1URESSqS8m95ebB/ozKWf4dDfG8iUPdvsbu3dJ9qADC6H6sU9qaunxp5+bdSUF1tY7MyIiKiZMSgmogoSUmzz0pBtXQdtUUeVHOf6qi4XL7l3/KgWizJl5Z/Sx+VguoUo/+vWmOo8m+Fl4OWjFdUAAo/I0RERBR/DKqJiJKUNJAOlamWB3NsVBYdefdvecbY06hMFlSL+1dXKmSTzXodPr9zANJNes9zodZUy4N5ADAZZNntf/4BnnoKOPNMID0d6NED+OSToOMSERGR+hhUExElKWlcHGpN9Zsr92Db4RLJ+dynOhry7t/y2NbbqEx4NLqDabH8WylZbDJo0bt1Awzp2Nj7XIigWmkcs/SaL74AunYFnnsO2LFDeG7LFuC664BFi4KOTUREROpiUE1ElKSkcfG/J8v9Xpevk753wUbPMfepjk7I7t+yRmXimmqDUr22m7h+Wvr9CrWmWmkNvN59L2zbBoweDVgswKBBwLx5wL59wLhxwuu33w589hnLwYmIiBKEQTURUZKSlnD/vq8Q6/8t9HldXtItbVbmX/7NTHU45N2//cq/xUy12KhM71v+rcTs7vQtfaNDDMYDzkOhsqDC4gCcTmD8eMBuBy67DFixArjxRqBNG+DNN4HevYGiIuDaa4FzzwWWLAl6HyIiIoodg2oioiQlzzN+seGwz8fyku4Uozf76bdPNTPVYRG/pGIwrfHLVCuvqQ4WJCtlquXjykm/fx/e0gcAUGGxA++9B6xdC2RkAG+9BegkGW+jEfjhB+Dmm4WPV68GrroK+PPPoPciIiKi2DCoJiJKUq4Q22LJS7ylQbU8U23jmuqwOGTdv+UJaJun+7dsTXWQNdLi+mn59yuceQBAw3RhSy7ziXzgsceEJ6dOBVq08L+wfn1gzhxg3TphzbXTCTz+eNj3JSIiosgxqCYiSlLywNivpFsWpKUavN2l/RqVMVMdFnmjMnkXbvF1q7z7tzayNdWh5+F9EyTN3TV8wtdvASUlQJ8+wIQJwQfo2xdYvBjQ64Xs9S+/hH1vIiIiigyDaiKiJCXvMxUqUDb7lH9zTXWknJKvWaB9qm0Oefm3xudRibimOpLvgVnSyCzdpEe/g9tw8Y6f4dLphBJwXfBGZwCAtm2FpmWAkNkmIiKiuGBQTUSUpOSJTYdfpto3SEuV7GNskwVwtgiypKcq6ddXFyBTLX7NPUG1PnT5t5hpjiRTPbRTDi7slIPJF3dAmlGHyas+BAAcu3YMRq6txPYjJSFGcHvoIeFx+XLgxImw709EREThY1BNRJSk/Mq/I1hTXVxl83mNmerQpF9PsZpbvqba2/3bd021vPz7wk450GiAu85r5wmq5d+/YPQ6Ld67qTfGD2qH1CWL0f3YP6gwmHF5wwuw4UARrnvv9/AGatcO6NVLWFu9eHHY9yciIqLwMagmIkpSwRqVuVwuv47eZkmmurjSCgDIMAsBHbt/hyZ9E8NT/i3fUkueqQ7Q/XvMgFbYOuVCPHpRB89zUVULWK3QPv4fAMB7fa/CybT6AIAyiz38Ma65Rnj88EPuXU1ERBQHDKqJiJKUPP6RZjpDxWeFFUJQ3TjDBMC/HJz8+WSqA5V/O+SNytxrqmXl3/VSjMgwG2TjR/E9ePddYO9enExvgFl9R0R+PQCMGQOkpAC//859q4mIiOKAQTURUZIKtqZaup46J1MInKVBd1GFUP7dOMMsnM9MdUjSmNezpZa8UZlsn2pxLbVBVv5dL9U3oAai+B64XMCbbwIA5g8dg0pjis/Lf+4vDG+cZs2ABx4Qjh99FLBaI5sHERERBcWgmogoScnXVEszqdIAbXSflsJzktcL3eXfbRqlAQAKKhhIhaLUqEwWU3uyzfJ9quXl34pBdaTl3+vWAf/8A6SmYu1Zw/1efuLL7eGP9eijQKNGwnhnnAHs2BHZXIiIiCggBtVERElKHoJZ7N5UqjSoNrm3bBKDcJfLhSJ3EN2tRRYA4FBhZRxnWjf4NipzZ6pla6qrrA4AgM0uW1MtKf826DRIN+khd8tZrQEA553RKLwJfSh0/MbIkdBmZoZ3TSCZmcCcOYDBAOzfD1x1FXDsWGxjEhEREQDA/7c+ERElBXmjsvX/FqKwwgqzQYuz//uT53mTe09jMRNqsTs9x52bCUH1wcJKuFwuaOSpV/IQ35SQxtHyNdXFlUJZvVW2pZa0/LtRuknx63xDv5bonlsPp+Wkh55McTEwf75wfOutSD/o/+u6XaMwxpEaPhzYvRs46ywhY926NXDJJcC4ccDFF0c2FhEREXkwU01ElKSUtmBat68Av/xzEmXVQvdnrcZbeiyeb7F5M9rtGqVDowGqbA6cLGcJeDBiUC3NTsu7fxdVWuF0uiTdv8VGZd7zGrmbw8lpNBqc2TzL8yZIUHPmAJWVQOfOwKBBiplvi90Rehy5Vq2AH38E+vQR1lYvXiwE2++8E/lYREREBIBBNRFR0lJagWt1OJGZ4g2wnC5vNlVsXiYGWzqtBilGHdKMwvkVkWzDdAoSy7+l2Wl5ozKnyx1Yu7853jXVkkx1gKA6InPnCo8TJgAaDcwG/1/X5dF+Pzt1EtZr//47cOONwnP33w/89Vd04xEREZ3iGFQTESUppb5Wj36x1W/Pab07myrumiWuvTa5S5PFzGvEjbJOMWL3b59MtUK1fF5ptefYs6Zaq2JQvWcPsHkzoNMB117rcx+pSmsUmWqRRgP06wd89JFQ+m2xAI8/Hv14REREpzAG1URESUq+phoAqm1OTP/xH5/ntJ6g2jdTLQbV3qCbQXUwYvdvaXZaXv4NAMdLLZ5jb6Myafm3ObaJfP658Hj++UB2ts99pFSpPNBogOnThccvvwQ2bYp9TCIiolMMg2oioiQl31JLtO94uc/HnqDZfXq1TcxUC2t39e51v+I6YFLmKf/2yVT7B9X5Pplq4fWcDDPOOS0bfVs3wNU9W8Q2kSVLhMeRIyX3UQqqY8hUS3XoAFx3nXD87LPqjElERHQKYfdvIqIkFSCm9gm2n7/yTE+5sjdT7Q6qDWKmWut+nZnqYJQalSnEsp7yb4NO4+nyrdVqMO+2frFPorAQWL9eOL7kEs/TRp1/cF9hVXGN/BNPAAsWeLPVPXqoNzYREVEdx0w1EVGSEmPgq3o0x1U9mnue926XlYkb+7eSBNXillq+5d9cUx0epUZlwTLVStnjmC1fLizu7twZaOHNeAcq/1ZaIhCVjh2B0aOF4/vvD/yODhEREflhUE1ElKTEzKlep/EJqsTgT+9+TlwDLD4//QdhzbW8/NvO8u+gxK+fNH5VDqqFNdVxCaqXLhUehw3zeVrcD1vK6fJWJahi2jQgNRX45RehgRkRERGFhUE1EVGS02o0nsAY8DbUEtdSSzPVpdU2/HmgCABQ6S4PjrZR2R/7C7H/ZEVsk69FnAqNynQKjcrilql2uYBly4Tjiy7yeSnQvVQNqlu1Ap56Sjh+6CGhFJ2IiIhCYlBNRJSknO4gWKPxDarEylwx+JMG1dKO0GLApXOvqY6k/HvH0RJc885anPfyqqjnX9soNyrzvl4v1QDAG1QrrXOOyfbtwNGjQEoKcM45Pi8FupdVzaAaACZNEkrPT54E7r6bZeBERERhYFBNRJSkxBhYo9F4ukxL6WSZarvThfJqb1BdbRPWVovX2p3hB2Dfb8uLas61mVKjMmn5d8M0IwDgZLkVgHJJdkzELPV55wFm3225AmWqrWqX9BsMwPvvC3tkf/IJ8MEH6o5PRERUBzGoJiJKUmKQp9UoB1ViSbgYBO44WoqiSpvn9Sqrw+d1uyP8rOOu/LLoJl2LifGptPxb+nVvmGbyOV/18m8xqJatp1a6lxj329TOVANA//7A1KnC8cSJQN6p9wYLERFRJBhUExElKTEE1kDjaUomJc9UA8Cz3+zwHFe6M9X6KLp/S/diPlUolX9L17Knm313oVQ1qK6oEBqEAcpBtSwrnmYS5qJ6plr08MNAv35AVRXwxhvxuQcREVEdwaCaiChJuaSZaoWGWZ411ZLM6vYjpZLrhUd9FGuqpWXPP/9zAtsOl4Q/8Vrqxe93+j0nDZzTTb5Btaprqn/+GbBahWZhZ5zh97L0Xg3SjEg1Cp3dVV9TLdJqhcAaAObMAewq7olNRERUxzCoJiJKUmL5t0aj8cmeisQMtT5EcCe+7ohgTbU0+33z7PW47M3VYV9bW21xv3Gw53i55zlDojLV0q20FLbxkt5rVJ9cGN2Z67hlqgHgssuA7Gzg2DFvaToRERH5YVBNRJSkxEyz0l7JgDdYDvT6Nb1aAPAGyDaFNdWl1TZMXLAJ32075vO8LsCYdZUzQBZfzPIDQIYpjkF1gK20lO7VvF6K5+NQa6qLK60Y88E6fLnpSORzMhqBG28Ujj/8MPLriYiIThEMqomIkpS3+7e3FFxK3CpLGviJmtdLwXNXnunzutI+1c99/Re+2nIUEz7eKBv71Aqqq9zrz+WkVQBp8qBare7f+/cD//wjdNw+/3zFU4ySe2WmGGDUhZepfvXHf/Dr7pO4f+Hm6OZ2663C41dfAcePRzcGERFRHcegmogoSUnXVCttF6xXaFQmuqRrU5gNOp/zlNZUL9uh3Nk5VEl5XVNhVV4zLM0QG/VaTzALqLim+uuvhcezzgKyskLOI9Os9wTZthBB9bGSwA3nDhZUorTaFvB1AECXLkCfPoDNBnz0UfBziYiITlEMqomIkpQYAms1GigVJ4tl30pBtTT404n7VCsEYNKu4kqvnyoqLcqZamkwq9NokOJuECZ/LSaLFgmPI0YEPEX6/cwwSzLVIcq/A2WyDxRU4NyXVqL/CytCz2/cOOFx1izld3eIiIhOcQyqiYiSlGedbxSZamnAJ3YOVyr/zpA03yqosHqOT7XYqdyinKnWS762Gg08XbcBlYLqkye9W2kFCaoNeu88slL0nntbAgTVLpcLmw8V++xbLrV6z0kAQKVV+c0EH6NHA+npQom6OFciIiLyYFBNRJSknJJGZS6FXLWYgVYKqqXl2+Laa6UAShponyizeI6V7leXBQoufTLVWo36QfXXXwNOJ9C9O9C6dcDTpOvmM80GSfm38vfpqy1HceXM37DlULHi60pvsASUkQFcd51w/MEH4V9HRER0imBQTUSUpJxhrqlWamImLRcWz5v+4z+YuXKPz3nSNbknyr1BdQS7b9UJFYEy1ZI3JzQAUo3ezL5Rr8Ka6sWLhcerrgp6mvT7lGE2eAL6QOXfC/84FHS8iIJqABg7VnhcvBiorIzsWiIiojqOQTURUZLTQDl4EzPUSiXA0mBQevzSsl0+50kzndLtmZynWP13wEZlkgyx0wWfNdXGWDPV1dXA8uXC8eWXBz21QZrRc2w2aGEK0ags1Pcv4qC6f38hk15eDnzzTWTXEhER1XEMqomIkpRPplrhdXEv6ex0k99rBoVMtRJpUCYNtJTup5QRryvCyVQ7XS6kGFQs/169GqiqApo2Bbp2DXpqTqYZs2/pjc/vHACNRgODe16BMtVKlQYrduZ7vodKneCD0miA668XjtkFnIiIyAeDaiKiJCUG1RqNBhef2cTvdXFNdaMME168qovPawaFNdVKfIJqSdCsFEDX4ZgaFWF0/3a6XDAbJA3gYt2netky4fHCC4WgNYTzO+Sgd+sGALz7Vgfq7u1Q+GbdNvdPrNp1Qng90qAaAG66SXj8/nvgyJHIryciIqqjGFQTESUpMS7SaICOTTPx8jXdfF6XZqAv7dbM5zWf7t9B9lOWln9LAy2lmKsuloT/e7ICt8/9E38eKFR8Xfq1czjh2ftbeE2loHrYsIgvDbWmOtD36tfdQtdvn6qEcL+vZ5wBnHOOkAafOzeC2RIREdVtDKqJiJKUtPs3AIzs2RztG6d7XpdmoNNNetx7fnvPx3pZ12rF8Z0un+Bq1a4TngBLMVMdxeeQ7O77ZBOW78zHd9vyFF/XaHzLv8166ZrqGBqVHT0KbNsmvGMydGjEl4fKVDsDZKJTjMJ19hBvoAR0223C4wcfnHrd7IiIiAJgUE1ElKRckjXVgBDgXd2rhed1+Vrpto3SPMcGyWuB1lTbZEHR4k1H8PXWYwCUA606mKjGkaIqv+dG9c5VPNfplJV/x5Kp/uEH4bF3byA7O+LLjSEy1Url3wBQWCHsW+2QfO8DNTtTdPXVwhZb+/YBP/8c/nVERER1GINqIqIk5S3/9gbFxiAZaOlexj6NygIEf0p7HP/4V7773v6v1cXyb2k3bwA4v0NjTJOtTxc5XC71yr9jKP2W3tseaE11gDj5eGm1cJ1Tuew/pLQ0b8My7llNREQEgEE1EVHS8jYq8z5nMgQOqn0DaU3A80RKAZmYwax74bOyVFlQ3bxeCrRByuVN0qA62kZlDgfw44/CcZRBtfj9tQUIiAOVfx8vs8DlcuHdn/d5nou4E7hYAv7550BBQWTXEhER1UH6mp4AEREpk6+pBnwz1fKybmlTrWDniZTW44rZa6WsdB1MVCPV6PtrMNAbEICQqU4zqrCmeuNGIRjNzAT69YtqiJCZ6gDfrGqbA6v+OeF7bqRBde/eQI8ewKZNwNSpwPTpnpdsDhvWHVmHH/f+iG3Ht0Gj0UCv1UOn0UGv1SPVkIpBrQZhSNshaJTWKLL7EhERJSkG1URESUq+phqAT6Y0eKY69NpfpfJvcX2tUkxWF8u/5ZlqbZCtrZwu+DQqM+l1Ac8NSiz9vuACwGCIagjxjRK7wvcQCJyptjqcOFFq8XnOHmnDMY0GePFFIcs+Ywac99yNL6o2Yv62+Vj570qUWcuCXv7uhncBALmZuRjSdgguan8RruxwJYw6Y2TzICIiShIMqomIkpQYFmkQXgZaWvLtk7UOUKaslOW0ezLVgedTl8iD6mDLpIVGZd7zG6RFGQTGuJ4a8L5pEqj8O1Cm2mp3+iwhAKLcs/rCC4ELLsCuzStw05xzsF53zPNSw5SGuKDtBRiYOxAGrQF2px0OlwN2px355fn4fs/32HFiBw6VHsKHmz/Eh5s/RE5aDsb3Go/xvcejWUazIDcmIiJKPgyqiYiSVKg11fK1v4YA2elAQbVS12cxa6m4pVYdzFSn+JV/B46qnS6XZ0sqAMhON0V+w5ISYO1a4TiGoFosPbcF6P4tzWA3zTLjsYs74L5PNsNqd6LK6gh4brhcLhfevq49Huq/AlW6Y8g0ZuLefvdiRIcR6NG0B7SawF/Hly58CaWWUqw7vA7L9i7D/7b9D8fKj+HZX57F1F+n4ooOV2B8r/EY0nZI0HGIiIiSBX9bERElKaU11SZpsCxLqwYKqk0Bgmqr3T+Y+n1fIVwuV4Dy77CmXavIs/3BMtUOp+/XNTsjikz1Tz8JjcpOPx1o3Try693ETHWg0m1p9rl1wzR0aZ4FQMhUl1vsAc8NpcpWhflb5+PcOefi7sPvosoADN0L7Gj6HJ4//3n0atYrrEA405SJoe2G4uULX8aB+w9g4dULcXbLs+FwObBo5yIMmz8Mg+cOxoHiA2HPjYiIqKYwqCYiSlIuhUy1tKy3X5uGPudLA0R9gKZlUoECsu+35ymvn66DQbU8W68LsqZ6QLuGPlneBqlRBNUqlH4D3u+10rp4wPfnJCfT5KlWsDicKKv2DapDdf+2OqxYumcpxn01Dk1faYoxi8dg9cHVMOqMeFVzEZbOB1p89GXUn4tBZ8C1na/Fr2N/xba7tuGePvcgzZCGXw78gm7vdMMb696A1WGNenwiIqJ4Y1BNRJSkXAqZ6i7Ns5Bh1uOc07LRsmGqz/nSMm+DNnj5t8PpQkG5cqDy9Zajyt2/62BULS99VtpOa+3k8/Hh2D4Y0rExKiRZ3kD7fwfkcgFLlwrHMQbVhhCZammpfuNMs+dnwGr3D6oDZao3523GmMVj0Pilxrj444vx/qb3UWIpQet6rfHsec9iz717cP8t70ILDbByJbB3b0yfEwCc2fhMzBg+A1vu3IJ+zfuhxFKC+5beh97v9camY5tiHp+IiCgeogqqZ86cidatW8NsNqNfv35Yv359wHMXLVqE3r17o169ekhLS0P37t0xb968qCdMRHSqcCp0/66XasSGJ4Zi9i19/M6XZqoNeknJuEKX6tHvrcXYOX8o3ler1SiGz3Wx/FselCptP9Y0KwWDz2gMjUaDIZ1yAACdmmZGfrNt24ADBwCzGTjvvGim6yEG1QEz1ZJv1pXdm8Ok8/4MFFX6vpkiz9YfKjmEMYvHoMe7PTB/63yUWErQJL0J7up9F3666SfsnbgXTw56ErlZuUDLlkLTMgD48MOYPiepdg3a4dexv2Lm8JnITs3GtuPbcM6H52DH8R2q3YOIiEgtEQfVCxcuxKRJkzBlyhRs3LgR3bp1w7Bhw3D8+HHF8xs0aIDHH38ca9euxdatWzF27FiMHTsWy8QSOCIiUuTJFstKko16reI2WT5baoXIVP+xvyjgfXUajeKa6rrYqEwelCplqqVa1E/Fn08MwZd3D4z8Zl9+KTwOHQqkpUV+vYRY3h9wn2p3UP3+Tb3RqVmmz89AYYVV8VwAeH/j+zjjzTMwf+t8AMDoM0dj9djVODLpCN665C0MbjPYf830bbcJj3PmCOvFVWLQGTChzwT8NeEvDGo1CBW2CtzxzR1wuiLcAoyIiCjOIg6qp0+fjnHjxmHs2LHo1KkT3nnnHaSmpmL27NmK55933nkYMWIEOnbsiHbt2uG+++5D165dsXr16pgnT0RUl3nLvyO/1hhG9+9AdFpNgPLvukde+hxsTbUoO90U8dcUALBkifB4xRWRXysjbpkWKFMtflrtG6cDQNCg2u50weF04OEfHsa4r8ehyl6Fc1qegz/H/YkFIxdgYMuBwZuPXX450LAhcOQI8MMPMXxWyhqlNcK8EfOQbkzHmkNr8P7G91W/BxERUSwi+qvAarViw4YNGDJkiHcArRZDhgzBWnGLkCBcLhdWrFiBXbt24dxzzw14nsViQWlpqc8/IqJTjVL372CkpwVrVBaq23OV1RGg+3fdC6v9GpVF8w5GOI4cATZuFL5Jl14a83BiJYLStmiAdOmA8PnotBrP51ZQbvE593hFHq5ceCVeXvsyAOCZ857Bz7f8jF7NeoU3GZMJuPFG4fiDDyL6PMKVm5WL5wY/BwB44qcnUGmrjMt9iIiIohFRUH3y5Ek4HA7k5OT4PJ+Tk4O8vLyA15WUlCA9PR1GoxGXXHIJZsyYgaFDhwY8f9q0acjKyvL8y83NjWSaRER1gqf7d5jnp0n2XPYJqmVZ1UCBmKi4ynrKdP+Wd76OW1D9zTfCY79+gOx3aDQ85d8B3iAR3ziRbrstvrlytKTa85xF8w9u+uZ8fPPPNzDpTFgwcgGeGvQUNGG+keMhloB/9RVw4kRk14bp7j53o3W91jhReYLZaiIiSioJ6f6dkZGBzZs3448//sDUqVMxadIkrFq1KuD5kydPRklJieffoUOHEjFNIqKkIoZL4Waq66cZ8d+RXfHqqG4+zcnk+1SHDKorbafMPtXyNclxD6pVyFID3gA50Jpq8U0R6ecjf3OlXLcSeaZHcbIqD50adcLvt/+O0WeOjm5CXboAvXsDNhsQp2akBp0Bk8+eDACY+utUFFcXx+U+REREkYooqM7OzoZOp0N+fr7P8/n5+WjSpEngm2i1aN++Pbp3744HH3wQV199NaZNmxbwfJPJhMzMTJ9/RESnGqfCPtWhXNsnFyN6tPB5Th5MVVqDN5M6WW5RbEpWF7fU8mtUFmmGNhyVlcDy5cLxZZepMqQ+RPdvpaUD4s+BCw4U6eegwPgKoLFhQLMLsfa2tfhtZzoW/nEw+kmJ2eoPPoDiuzIquKX7LeiQ3QHHK47j8RWPx+UeREREkYooqDYajejVqxdWrFjhec7pdGLFihUYMGBA2OM4nU5YLJbQJxIRncIiXVMdiHxNdbnFHuBMwclyK6rt/hnQOrik2r9RWTwy1T/9BFRXA7m5QkZXBeLWX4GqDjzl3xrftfVOVOKE8XmUGj4HAGTarsH5jf6L4yVavLRsFx79Ylv0k7ruOiAlBfjrL2DduujHCcKoM+Kt4W8BAN7+822s2LcixBVERETxF3H596RJkzBr1izMnTsXO3fuxF133YWKigqMHTsWAHDTTTdh8uTJnvOnTZuGH3/8Efv27cPOnTvxyiuvYN68ebhRbGpCRESKXFFkqpXIM9UVQYJqMaiUd4gG6mijMmcCyr/F0u/LLov9m+kmbp+mtKbaKXlO+vnYtceQZ3oQVbo/oHEZkW19GPXtN2P+74dRWm3znBeqkV1AWVnA1VcLxwF2BFHD4DaDcUv3W+CCC1d8cgXWHgrdKJWIiCie9KFP8TVq1CicOHECTz31FPLy8tC9e3csXbrU07zs4MGD0Eo6o1RUVGDChAk4fPgwUlJS0KFDB8yfPx+jRo1S77MgIqqDXGplquVraYME1bn1U7C/QLmzcsQxtcsF/PknoNMB3bv7ds1KEnZZ+XQ4W2pFxOXyDapV4t1Syz9TLX3zQ/x8VuxbgY1Vd8GuLYPO1RCNLE/A5DrNc570s7bYHUg1RvzngeDWW4U11Z98Arz6asz7cQfy9iVv40jpEfy470dc/snl2HbXNjRJD7wMjYiIKJ6i+gvnnnvuwYEDB2CxWLBu3Tr069fP89qqVaswZ84cz8fPP/88du/ejaqqKhQWFmLNmjUMqImIwhDNmmoleln2tbzaN6iWjt8ky+zzmtkQZSBcWSkEkX37Ar16ARddJDSxSjJxb1S2ebOwnVZaGnDeeaoN68lUK6ypdkjf/dC4MGPdDAybPwx2lMHoPANNql/1Cajlqm3BG9kFNWgQ0K4dUFYGLF4c/TghmPVmLB61GN1yuuFk5UmMWTwGNkfy/XwREdGpIfnSBkREBEAaVMcW6Mmvr7D6BtUpBm+ncHmGcv5t3jdNwy7/3roVOOcc4Ntvvc/9+CPwyCNhzjhx5OXTWrWDavFrMGQIYDYHPzcC3i21FDLV7qecqMI934/DxKUT4XA50NJ8EZpYpkGPBn7XSL8O1bbgjeyC0miEtdVAXINqAEgzpuF/I/+HFH0Klu9bjtu+ug1OVwxvCBAREUWJQTURUZLyln+rO265xTdoSjV6g2qDzvdm9VINSDfpfeYT1J49wLnnAhs3AtnZwOrVwJIlwmuvvw7s2BHT3NUmD6rlWf2YLV0qPA4fruqweq23+7e8U3uVrRoV2t9w1HQP5m/7CBpo8NLQl3Beo6ehgREA8MzlnX2uka6ztyg0qYvIiBHC49KlQFVVbGOF0KlRJ3x2zWfQaXSYt3Uexn89Hg5nDG8KEBERRYFBNRFRklJrTTUA/PjAuZ5jeaMys0EaVMt/LWg8621DxtR2O3DttUBJiVDyvWEDMHAgcPnlQim4ywUsWBD15xAP8jXJqm6pVVIC/P67cDxsmDpDVpdg2Z5leOvPV3DS8CqOG59Ft3e6I3VqKlq91gpnzz4bbWe0wEnTNDi0+cjNbImVN6/EQ2c95PN9Ht0312fcMsmSgJgy1QDQowfQqpWwBODHH2MbKwyXnH4JPrziQ2g1Wry/6X08/OPDcb8nERGRFINqIqIk5Sn/VmGs03IykNsgBYB/UO2bqfb9taDVeCcQsvz77beBTZuA+vWBr74CWrb0vib20vjyy2imHzd+jcrUzFSvWAE4HMAZZwhBZgxKqkvwyppX0Oq1Vrjo44vw9C+Po0K/AlW69dh2fCuq7FU4WHIQvx36DSWWYmhdmci0XY1td27HoNaDAAAmvff7bNRpsWjCWZ6Py9XMVGs0wKWXCsfLlsU2VpjGdBuD+SPmAwBe/f1VLPl7SULuS0REBETR/ZuIiBJDDPdiXVMtMrhLhuXdv5tkpeCf/HLhHFn5t1aj8WRvg8bU+fnAk08Kx1OnAs2a+b4+fDig1wvl37t3A6cFbpSVSPI1yX6J+liI66ljyFJX2arw+rrX8eLqF1FiKQEAtMhsgf7NB2DZtmpoXRl4+9qR6NX8TBRUFuBQ6SGk6hri7jmV0ECLTHO6ZyyTpAu8RqNBz5b1odNq4HC6fJrXxZypBoQ15DNnAsuXxz5WmK7rch02HtuIl9e+jIlLJ2Jou6FINaQm7P5ERHTqYqaaiChJiZlhtZKnYnMrMVPdJjsNs2/pjY5NMjznyDPVGo20O3iQqPqxx4Ry5549gTvu8H+9fn1v9+skyVY7nS7Y/DLVKv1atNuFbD0AXHFFxJc7XU4s37ccHWd2xOQVk1FiKUGnRp3w3qXvYd/Effj0moXIcd6JevbrMajlxTi94ekYkDsA13a+Fv2anw2N+9e79A0Zafm3yOj+fpdJ9qmOOVMNAIMHC1uo/fMPcPBg7OOF6ZnBz6BlVkscLDmI/1v9fwm7LxERndoYVBMRJSmxh5ZamWqxuVWVe8uk1g1TcX6HHJ9Q2b/827um2hkopl67FhC3UnzzTWFfaiVXXik8JklQXamQkVVtn+rffgNOngQaNBAat0XgYMlBnD37bAydNxQHSg4gNzMX80bMw7a7tmFcr3Ew6AzQaDTIMBsA+K6HBrxvxshL2U16/1/54h7mZRaVM9VZWcJ2akBCs9WphlRMv3A6AOD/fvs/7Cval7B7ExHRqYtBNRFRsopTptriDprErKy0e7RR75+pDlr+7XIB994rHI8dCwwYEHgCl18uPK5dC+TlRfEZqEu+XzcgJFdVIW4nddllQtl7mAoqCzB47mCsPbwWqYZUjOs5Dpvv3Iwbu94IrcZ3chlmYVxplhkAHO53P+RvEHRunul3P/H7Lf1abDpYHPZ8gxo6VHhMQLMyqas6XoUL2lwAi8OCScsmJfTeRER0amJQTUSUpJwqdv8GvNtFVbvLe5W2j5KvqdZoNJ7yb5dS+ffy5UKX77Q04MUXg08gNxfo3VsIxD//PPJPQGXlFlvok6Lhcnmz8WJ2PgxOlxM3f3kz9hXtQ5t6bbBjwg68d9l7aJDiv6804A2qb569Hp+sPygZR9zf3Pf8K7o1x+SLO+CLu7xvfHjLv71B9Ts/78W+E+VhzzugIUOExx9/FBq2JYhGo8EbF78BvVaPJbuW4Pvd3yfs3kREdGpiUE1ElKQCBUfR0rsDqGpPpto/A63U/VssP3fKl9pWVAATJgjHt94KNG4cehI33ig8fvhhZJOPAzGQzDSr3LNzyxbgwAEgJQW48MKwL5u+djq+3f0tTDoTFo1ahNb1Wgc93+zu5l1hdeCxRdtwpFjYE1r8PsnLv7VaDcYPaoderbxBulgSLm9e98SX28Oed0ADBghr6QsKgDVrYh8vAp0adcJ9/e4DAExcOhEWuyWh9yciolMLg2oioiSl9ppqg1/5t/Dx2LPbwKjXYnSf3KBrqv0y1Q8/DOzZA7RoATz7bHiTuOEGwGAANm4Ugs8aJAaS9VKN6g4sZqmHDQNSw+s+vebQGjy2/DEAwOsXvY7uTbqHvKZUVvYtfl8dLuXybyVKa6oBYM3eAlRZY8wuGwzerbVqYB39lEFT0CS9CfYU7sHr615P+P2JiOjUwaCaiChJudReU60VM9W+5d/N66Vg+9PD8OLIrp5yYJEG3ky5z5rql14S9qUGhKxzvXrhTSI729sNu4az1RWeoNrgfTLEVtxhibD0u6CyAKM/Hw2Hy4HRZ47GHb0UuqcrKK5ULl+PpMLBE1RX+49VUqVCebz4NVi8OMSebOrLMGXgxQuEJQnP/fIcjpUdS+j9iYjo1MGgmogoSYkxiDdXHBtPptrum6kGvMGV0ppqcU33D3/lC09u3w48+qhw/OKL3rWz4br1VuHxo4+AysrIrlWRWP6dleINqmMO+/bvFzLwWi1wySUhTz9UcgiXLbgMh0oP4bQGp+HdS98NuzKhWBb0ituDOZ3K3b+VmBQalYlUCaqHDRPK4P/9F9i8OfbxIjSm2xj0bd4X5dZy/Oen/yT8/kREdGpgUE1ElKTE8t50ldb8ikGWuA+xXucfdBn0/muqj5VUAwDeWLEbAGB9bLIQ8V91lTe4jsSFFwJt2gBFRcD8+ZFfrxKx/DtTElTHTMxSn3OOkJUP4HjFcczaMAvd3+2OtYfXIsOYgU+v+RSZJv8O3YGM7NnC52ObQ/i+OgJsqaXEKFtT/dCFp6N1Q6FkXZWgOi3N++bCBx/EPl6EtBot3rjoDQDAnM1zsP7I+oTPgYiI6j4G1UREScjpdOF4mdBcqUmmWZUxAzUqk5KvqZZnTW2/rIbx229g12hhe+756Cai0wETJwrHr76a0M7QUmJ2Nt3ofdMi5gpl8U2Cq67yebrKVoUZ62Zg+MfD0eyVZsh5OQd3fHMHCqsK0btZb2wavymsddRST1zS0edjMagWG5WF0zVeLPevdK+fNul1nsy9KkE1ANx1l/D44YdAWZk6Y0agX4t+uKnbTQCAid9PhNMl77hHREQUGwbVRERJqKDCCofTBa0GyE5Xp5GWQdxSy7Om2v9XgHybLZ8PXS64/jMZAPB5lyEoa9Uu+snceqvQGfrvv2ssWy1WAmSmSILqWArAt24VthczGIDrrwcAnKw8iam/TEXbN9pi4tKJ+H7P9zhWfgwaaNC5UWf8d8h/8dutv6Fdg8i/lmkmPRaM6+/52O4u+3Z61uKHn6kWpZp0nsy9akH14MHAaacJpf5ffKHOmBF68YIXkW5Mx7oj6zB/a81VRxARUd3EoJqIKAnllwol19npJk+GOVaeTLV7TbVS0OWUxZTSTPWgfzfC+NtqWHQGvD7wOtj99tiKQGYmMFkI0PHUU0B1dfRjRUkMGqVrqlONuqjGKqwqxJsf34dLrgfaPmxA1vvtcPqM09HqtVZ4YuUTyCvPQ+t6rTH9wulYc+salE4uxfYJ2/HwwIdh1EX/psmAdg1xWuN0AJLy7wjWVKeZfJcWpBrjkKnWaICbbxaO585VZ8wINc1oisfPeRwA8OTKJ1FtT/zPGxER1V0MqomIkpC4jjlHpdJvwNuETCxxVlpT7ZRF1Z6Y2uXCpF+FDN9HPS/BscxGsNpjLKO95x6gWTPg4EFgzpzYxoqCNKj+z/AOuK5vS/RsWT/s6x1OB37Y+wNGfz4aTV9pintTV+G704F/jZUotZRid+FuVNoq0TWnK+aNmIdd9+zCAwMewIDcAUg3pqv2eYgl+55GZWKmOozf8NnpJp+PUwx69YNqABgzRvhhWrVKaOZWA+7rdx+aZzTHwZKDeOfPd2pkDkREVDep0/2GiIhUtXr3CQDAGU0yVBtTXu6tlMl0yBYVi9ns8/f+gW55u1FlMOPt/tcAQOxBdUoK8NBDwKRJwPvvA3feGdt4ERKDxswUA8YMaB3yfIfTgdd+fw0fbv4Quwt3w6w3o9RS6nm9Wx4w5t9MdH79f2jZoA1OVJyATqtD/xb9odfG79et2FzOLq6pjqD8u2Gab5Y81ajzrOE/UlSl3iRbthTKwH/6CZg9O/x9zVWUYkjB0+c9jXFfj8PUX6fith63IcOk3n9fRER06mKmmogoCa3dVwAAuLBTjmpjyoNo+fppwFs6LNJqALhcuP+3/wEA5va8BIWpWQC8XcRjMmaMsAZ5wwZhK6oEKqkS96kOXX7tdDkxdslYPPTjQ9hxYgesDitKLaWob66Pe/rcg43bB2LzO8CDPSbgojMuQadGnTCo9SCc3fLsuAbUgHetvLf8W3heF05QLctUp5l0aNMoDQDwxcbDOFluUW+i48cLj++8UyPl/gBwS/dbcHrD03Gy8iRe/f3VGpkDERHVPQyqiYiSkBiwNlSpSRngvwe1UqbaKctUa6BBj6O70DVvDyoNJrzX19vVWpWgOjsbuOIK4TjBWy6VKqypDuT9je9j3tZ50Gl0eOOiN7Dhjg1YPmY5jj54FDN6Po4ei9YKJ44dG88pKxLL+P3Lv0MH1ekm3zXkKQY92mZ7S9Pf//VftaYpdERv2RI4cQL4+GP1xo2AXqvHs+cJWfIZ62dwbTUREamCQTURURISM8bhlPCGP6bvx0qZ6ub1Unw+1miAa7YtBwAsO22AJ0sNABabSlth3Xab8Pjxx4BNxXW8ISg1KlNSUFmAySuEpmovDX0J9/a7Fz2b9sQFbS+AWW8GliwR9rHq0wc4/fS4z1vOu6Za3FJL/NkJfa1f92+jDm3dmWoAWP9vgUqzBKDXA/feKxy/+qoK+5dFZ2SnkWiZ1RInK09iwbYFNTIHIiKqWxhUExEloUg6OIerShYE6xQ6WZ3fobHPx9qCAlztDqo/6TbM5zWrPEqP1tChQKNGQGEh8PPP6owZgsPpQrlFKP/ONAcvz35g2QMorCrEmY3PxL397vU/YdEi4XHkSLWnGRYxqLa7M9WOCNZUD2yf7fNxqlEHs0GHe89vDwBIN4fO4kfk9tuBtDRgxw5g+XJ1xw6TXqvH3X3uBgC8sf4NuGoouCciorqDQTURURKKR1BdLQuqlTLVGo0G489t6/lYu+onGJ127GzUGutadvE512JTKajW6bwl4GKAGqNth0s825IpqbTaPcfybaWkvtv9HeZtnQcNNJh12Sz/9dFFRULzLQAYMSKmOUdLLOu3RrGllkmvw4dj+3g+TnFvKSZ2QS+sCL2mOqKgtF49YY9yAHjttfCvU9ntPW9Hij4Fm/M249eDv9bYPIiIqG5gUE1ElITEdbGqZqqtvkF1oDW30r2ptStWAADWtOrmd54qa6pFYkD65ZdCKXUMdueX4bI3V6PfCyt8nre49+curbYhv1QIFnVaDUx65V+FTpcTDyx7AADwQP8H0L9Ff/+TvvkGsNuBzp1rpPQb8O4/Lnb/3nyoGED4Swek56UahTcNGri7gheUW4NeO2XJdvSftgIF7oZmJZU2XDrjV7z64z+BL7rvPmFdwXffAX//HdYc1dYgpQHGdB0DAHhj3Rs1MgciIqo7GFQTESUhT7ZRxTXVlWFkqgHvWlyt0wHN118DAH5u09PvPKtDpTXVAHDBBUBGBnDsGLBuXUxDbT1c4vfcgvUH0fmpZVi2Iw+9n1uOIdOFMvNUo87nTQSpn/79Cf8U/IMMYwaePu9p5Zt99ZXwWENZagAwyvapfm35bgDAjqP+XwclGZLyd/FNHE9QXWENmIl2uVyYu/YA8kst+GrLUQDA6yt2Y/uRUry+YnfgG7ZrB1x+uXD8+uthzTEeJvabCABY/PdiHCg+UGPzICKi2o9BNRFRErI7w+/gHK5qq3xNdaCgWnj+zPy90OTno9SYirWtuvqdp1r5NwCYTMAllwjHixfHNFSapKO1+ObE5EXbYHe6MH7eBp+14GnGwKXfb/3xFgDg5m43K+9n7HAA7ky+Z+41QHxzxOZ0+pT4O8Osyu6RWw839GuJ/wzv4HlO7DpvtTtRaVV+8+SP/UWeY5Ne+Jr/eaAwvJvef7/wOHcuUKBiM7QIdG7cGRe0uQBOl9PzvSYiIooGg2oioiTkjEOmWlwvKwqVqT7rwFYAwO+tusKm829YJZZ/V9scKK1WoWv3Ve7tuhYvjqkzdIokUC4LMa9U2ZZSosOlh7Fk1xIAwF197lK+eNMmYU11ZibQu3d0k1WBwV2+brO7cLioKuLrNRoNpo7ogjvObed5TgySgcBl/te+u9ZzLK5R//dkRXg3HTQI6N4dqKoC3n034jmr5b5+9wEAZm2chQprmHMnIiKSYVBNRJSEHHFYU/3M5Z19Pg40tlgOfdaBLQCANS39s9SAd43ywBd/QtenfwgZwIZ08cVCxnrPHmD79tjGchO3zQok1agcVC/YtgBOlxPntjoXnRp1Ur5Y7F49eLCwXVQNMbi/j3anE4eLKlUZU6fVeH4+bGF0eX/+252osNhhDXedvUYDTJokHM+YAVhCN0SLh+GnDUfb+m1RVF2Ej7fVzN7ZRERU+zGoJiJKQmKvLjWD6tbZaRjRo7nnY70ucPm3wWFDn8N/AQDWKJR+A/AEUAUVQjOr7UdKY5tgejpw4YXCcQwl4HZJEBg6qFYOhr/Y+QUAYHTn0YEv/vFH4XHo0MgmqDJxS60ZP+3BLR/+odq44lrtQIGyvMHbV1uOesrtwzJ6NNCiBZCXB8yfH/TUKqsjsrHDpNPqcG9fYZu0N9Zxey0iIooOg2oioiQUj0w14N1+SRhb+VeAVgN0P7oLKXYL0Lgx/slupXiexe5UPwgRG37FsLWW2LALAIorgwfVaQqZ6sOlh7HuyDpooMGVHa5UvrCyEli9WjgeMiTaqapC7P6tNvFnRSlTbbU7/crCtRrvz214NzB411a//HLAru8HCirQ9ZllePjzLeGPHYGx3cci3ZiOHSd2YMW/K0JfQEREJMOgmogoybhcLk9WLtxtkcJllGQXA66p1mow0F36jfPPF0p1FVjsTk9DNdVcfrmwb/WWLVGXgNud/pnqQNtmpSrsUf3Zjs8AAGflnoWmGU2Vb7JiBWC1Arm5NbaVlsgQoOIgVuLPivRNClGFxe73nNXhinwp/Lhxwpr0v/8G3J3m5VbvOQmbw4VFG4/gSHHka8ZDyTJn4ZZutwDg9lpERBQdBtVERElGGqcGCnyjZZBkNQMF7BoNMMDdpAznnx9wLJvD6ZPFdEGFALthQ+Cyy4Tj99+Pagi7JAgUg+rsdJPiuakG/0z13C1zAQDXd7k+8E2+EMrDMWJEwDcdEsUQt0y1GFT7Z5DLFYLqUlmpvTOcN1wyM4G73I3g7r4bOHHC75QUyffo72MxLjEI4J6+9wAAvvnnG+wt3BuXexARUd3FoJqIKMlI146quaUW4F0nCwQO2A1VVehxdJfwQZCg2uF0wWaPwxrUceOEx3nzgOrqiC+3KaypDpSpTpNlqrfkbcGW/C0w6owYfWaA9dRWK7BE6AyOkSMjnp/a4h1UWxWC6rJqIahulGHCrQPbAIBfB3hbgHJuP48/DpxxBnDkCHDddYDdN2CXlplXq7mNm8QZ2WfgovYXwQUX3t8Y3Zs5RER06mJQTUSUZJySGlq111RLy791AcqG26z9CUanHYeycoC2bQOOZXO4fAKucGOokIYNE8qqCwu9GeEISEvSxexpoG2hGqYZfT6e+cdMAMBlp1+GBikNlG+wciVQXAzk5AADB0Y8P7WlGJR/lX9254CYxvWsqVb42omZ6gyTHpkpwhsTheVWn3OUysYVZWQI3+fUVKGsfsIEn8DaItl7W7oPt9rG9RTezJmzZQ5sDhW2iCMiolMGg2oioiQjzVSruU814JvVDJSpPuMHoUnYos6B11MDgMPpW/4ddmYyFJ0OuO024fi11yLes1qp+7e4/ZdcTqbZc3y84jg+2vIRAO/+xYo+/VR4HDFCmGsNk+8/DgC3nNUafVoHeFMgTN7yb/+vf7lF+Lqmm/XINAt7mB8v890WSykYD6hzZ+Djj4Wft1mzgP79gVWrgIoKVEvGWbojD5M+3Rz79m0KLjv9MjROa4y88jx8u/tb1ccnIqK6i0E1EVGSsfuUf6s7tjSoVsyCV1Sg6abfAQBfdTw36Fh2p8snqA57j+JwTJgApKQAf/4pZIYjYJOtqT5UWImTsiyqqHGmd6314yseh8VhQZ9mfXB2y7OVBz96VAj+AOD6IGuuE8issC5cjeZl3kZlgcu/0016ZJiFTHV+qW+pfsRvslx5pbC1VlYWsGGDsP93o0boO2MqmpYKa61//CsfizYewUdrD0T42YRm0Bk8DctYAk5ERJFgUE1ElGSkDZ70KkfVvt2/FcZesQJ6qxUHs3Kwt2GLoGPZHb5BtVLwFbVGjYBbbxWO33wzokul3b/3F1TinP8GDsobZwiZ6mV7luH9TUIg9dLQl6AJlKF/+WXAYgHOPlv4lwSU9tpWY5st8Q0YpdJ5sfxbCKqFTPUJeaY63PJvqeuvB3buFB4zM4GqKvT84kMsnvcgcspOek6TN0VTy209hQqJ7/d8j8Olh+NyDyIiqnsYVBMRJRnpXr8qL6mW7VOtMPg33wAAfmrXJ2RXa4fTBaukUZmqQTUA3HGH8Pjtt0BRUdiXSYO5nSG6RWdnGLG7YDdu/vJmAMDEvhMxqPUg5ZMLCoB33xWOn3iixrt+i1KUMtUq/OAE26fak6k265HubvZWUCFbUx1t5ULTpkI1QHExsGgRyho0QpPyQixY8B80LisAANRLNQYfI0qnNzwdg1oNgtPlxIebPozLPYiIqO5hUE1ElGScnj2qEThjGiWz3huANa+X4vuiywV89x0AYGW7PiHHssvXVKvdCbxrV6BLF6Hb9uefh32ZPYwM6cD2DXHHuW2RlaLBtZ9fi/yKfHTL6YYXLngh8EVvvglUVgI9egAXXhj2fOItxej/q1zNTLXillrV3kZlSmu6Ad+KgahoNMCIEXjvhbk4nNkIbYuO4r3FU2GyW1Fl9d/SSy2397wdAPDBpg/gdMWn2zgREdUtDKqJiJKMuKZa7c7fAHB+x8a4qHMTvHl9DzTJMvu+uGULcOQI7OYU/N6yS+h5ysq/LWpnqgHgxhuFR3EdcxjCCeaevqwz/jO8Ix784UFsztuM7NRsfHfDd0gzpilfUFEBvPGGcPzYY0mTpQaU11Tr1VhTHcY+1elmPdJMykG1VYU3WUqqbJjxrxPXj34BxeZ0dD/2D15YOiMujcpEIzuORD1zPRwoOYAV+1bE7T5ERFR3MKgmIkoyjjgG1dnpJrwzphcu7drM/0V36fexPgNh0Ycur7U7fbfUirrcN5jrrhMC2J9/Bg4dCuuScNbymg06fLz1Y88WWnOvnItmGQpfE9EnnwhbfLVrlxR7U0sprak2qLAW37tPtf/X09uozIBUg//9ARUy1QDe/XkvAOBg/aaYcMVjsGu0GLljJXp8MSfmsQNJMaTgxi7CmzniOnsiIqJgGFQTESUZcZ9qtbfTCulbYRuhYwMvCOt0h9PlE8CqvqYaEParFveCXrw4rEvsAeYhXXu87uhK3P61UOb75LlPYvhpw4MPOneu8Hj77UmxjZaU0ppqNd6QMYjdvxUblXm31EoNkKlW4+ehqNK7TntN6+547gJhL+lLPn4N2LQp5vEDEUvAF+9cjBMVJ+J2HyIiqhsYVBMRJRkxU62NQ6Y6oBMngHXrAAD6Sy8J6xKbw+kTcMUlqAaE/aABTyY9FOmWZKJLujbFoglnAQCsmn24ack1qLZX44ozrsCUQVOCD7h3L/Drr8L+ZmPGRDT1RFBsVKZC+XewRmVi+XeGSY/UAGuq1Sj/Fpugieb2vBTfn34WdA6H8L2org5wZWy6NemGPs36wOa0Yd7WeXG5BxER1R0MqomIkownU53IoHrpUqFRWbdu6DmwC168qgs+u3NA0Esc8dynWurii4XHX34RGoWFoBQE5tZPRXa6CQ6U4LjxeVTZqzC07VB8es2n0GlDZJ4/+kh4HDIEaN480tnHnTlOjcqCrqmW7FMtbX4npUb5d7rJ4PuERoPHh92NoowGwI4dwIMPxnyPQMRs9fsb34fLpXITPiIiqlMYVBMRJRlPo7JEln+LWeBLhCz16L4t0ad1g6CXyNdUK629VUWHDkCLFsL+0L/+GvJ0pe7fmSl61EvVIqvFm3Boj6N9g/ZYePVCGHUh1o6XlQHvvCMc33xzNLOPO6NCAK1XZUutIGuqJY3KtFqNYrY6XpULhalZeHHUo8IHb70lrHePg9FnjkaqIRU7T+7EmkNr4nIPIiKqGxhUExElmXg2KlNkswHLlgnHl4RX+g2IW2rFeU01IDQqGzZMOF66NOTpNoUMaYZJjwd/eBA7CtYi3ZiOL0d9ifop9UPf+8MPgePHgfbtgauvjnTmCaHRaNC6YarPc4Y4b6lVaXEAANLcTdKUgmqr3YUKi93z8xyNartD8fmVrXsCjz8ufHDXXcIe4irLNGVidOfRANiwjIiIgmNQTUSUZMSYMGFB9Zo1QEkJkJ0N9OsX9mVl1XZ8+qe3I3fcyr8Bbwn4kiVCmXoQSpnq3/O/wIz1MwAA80fMR+fGncO77wcfCI+TJgHG0B3Ra8qPkwZhRA9vaboaW2oZ9O411Qrf1yqbEOyKe1QrdSA/UW5B5ynLcMXM1VHPocrqG1Snue9XbrEDTz8t7GVeXAw891zU9whGLAH/dMenKKkuics9iIio9mNQTUSUZBzuoFGbqPJvd9dvXHxxRJ2tDxRUYv2/hZ6P45apBoCLLgLMZuDff4X9tIOQr+W1aHbhvW3/AQA8PehpXNHhivDueegQsHWrkCm/9tqopp0oBp0WmWZvYKtXYUstkztTbQkrqPb/uZm7Zj8AYPuR0qjnYHFnqh8cejpWPXQefpw0CABQaXXArtECr7winDhzJrB7d9T3CaR/i/7o1KgTKm2VWLhjoerjExFR3cCgmogoySS8/Pv774XHMEu/pcGblFLwpZq0NCGwBoAvvgh6qrQk3Y5CnDBNhd1pxZUdrsSTg54M/57i16V/f6Bhw0hnnHDS5mRqdP9OcWefK2XZYofT5alKEDuPt6if4nf9nuPlMc9BzFSnGHVonZ2GhuneaoEKi0NoHjd8OGC3Ay+8EPP95DQaDW7pdgsA4H/b/qf6+EREVDcwqCYiSjJiUK1Gs6mQ8vKA7duFbOyQISFPn3JZJ7x+XQ/F18RtluJm5EjhccGCoCXg4j7VLthw0vgCHJpCtK13Bj668iNoNRH82hOD6uEh9rBOEtKSbzW6f6e595+usvl+X6tt3iBbDKr7t/W+6dAow+Q3ltMdiDsjXF8tZsRN7vuY9DoY3ftnl7n3ysZTTwmPc+cCq1ZFNH44Rp05CgDwy4FfcKT0iOrjExFR7cegmogoySR0n+qffhIeu3cPmY3VaTUYO7ANstP8gyYAKKu2qTw5mSuvFDLWe/cCX38d8LRqmxBUFxregUX3N7SuNMwctgAZpozw72W1AsuXC8fieu4kZ5CUfBtU+NkRA+YKi2+metPBYs+xyR3g9mzlbfrWMM1/7XlptQ3nv7IK1767NqI5iN9L6V7cYqWE502cfv2A224T3mi58UagsNBvnFi0zGqJgbkD4YKLJeBERKSIQTURUZLx7FOdiDXVK1YIj2FkqcXZBCpL/31fIb7dekyliSlITwfuuUc4fuQRoWu5zNq9BVi7rwDluhUo1y8DXFpkWx9Bx0anR3av334DysuBnBygh3JmPtlIO36rk6kWgld5s7AbP1jnORbf+Dmtcbrnue659fzG2pVXhsNFVfjzQBEKyi1hz8GzdlsSVKe751VWLcmgv/YacPrpwJEj3gBbRdedeR0AYMH2BaqOS0REdQODaiKiJJOwTLXLBfz4o3B8wQUhTxdj/GCdpe/+30Y1ZhbY5MlCl/Jdu4B33/V7+bpZv8OmOYJCw9sAgCz79Uhx9lLsTh2UuB/2BRcAKjT9SgTf8m811lS7M9VWb/DqChCsZpgNnuOsFAO6tcjyeb1KUjK+K68s7DlY3NeZDd7vQbqYqZYG1enpwrIAgwH48ktg6tSw7xGOazpfA51Ghz+P/ondBeo3RCMiotqtdvylQER0CvE2KovzjXbuFDpcm83AueeGPF3jjqoTstY7kKws4JlnhOOHHwYWLfK85HS64EApjhufg0tTjWxDD2TZrwHgXR8ctnXubGz//mrMOiGkzcnU+B6Je1BLM9Wl1YHXzV/XNxcmvRbX9slF/3a+SwlKqrxVBX9HEFSLTdLMSplq+Rr+nj2FLuAA8OST3jXxKmic1hgXtBXeeJq3dZ5q4xIRUd3AoJqIKMl4g+o4/y9aDDoGDQJS/Ls3y4lhmhrbNcXkzjuBK64AqquBq68G7rgD5SXl+HLLXhw3PQO79jB0zmxc2fJFaCAEY2Z9BEG1y+UNqiPYt7ummSSfoxrfo1SFTHVhhTXg+S+M6ILNT12Ido3Sfcq1AeDD3/Z7jsPNVNsdThwqqgQANMkye54Xx66WlaUDAMaNA+66SzgeP14o4VfJ2O5jAQDvb3wfNkec+wcQEVGtwqCaiCjJODxrquN8o6VLhUdxq6oQxPJvnWxi2enKjcviRqsVttW6804hAJ41C78OuQTXL74CVu0uaF0ZyLE+h27N2kguieCLuXcvUFAAmExCA7da4sLOOTAbtDDqtD5BaLTE8m/pllrBgmqNRuO5xiwLqjcfKvYc/50X3r7V+05WoNrmRJpRhzYN0/zm9dexAOO8/DLQurVQhfH002HdKxxXdbwKjVIb4Vj5MXy16yvVxiUiotqPQTURUZJxJmKf6qoq77rhCy8M6xKtO6qWd5aeEWCLrbjS6YC33wa++w4Ogw6vd/gFFt1f0LjS0NjyDAyuXFzTOxe5DVJw8ZlNIht7rbtDdY8egNG/k3WyapqVgvWPD8HKh89DA4UO3JESy7/Lqu0oqRQys3vD3HtanqmW2pVf5tnnOpjtR0oAAJ2aZfq8KSJWHcxZsx/LduT5X5ia6i0Df+01Ycs4FRh1RtzW4zYAwDsb3lFlTCIiqhsYVBMRJRkxU62NZ/fvNWsAiwVo1gzo2DGsSwJ1/xbLhAGgmQoZ0ohcfDGe+e8lWNYeSLUCl+wdDZNL6PSdnW7Czw8Nxls39IxsTHGbsTDWmSebTLMBzeuFLuUPR4rk+/rGT7vx8z8n8MgXW8O7NkhQXW1zYu2+gpBjbD8iZKI7N/NtemaWzOujtfuVLx4+HBgxAnA4gPvvV60b+Pje46GBBsv3LWfDMiIi8mBQTUSUZMQ11Wp0cA5I3IN5yBBvXXcInkZlsg5qKUYdFowTGnqZggRT8fDd7u/wXIlQivve18A7S75CmkVYh6vTaqDVajzzDovLBfzwg3AcRkf0uixNErx+vuEwXvh2p8/rPVrWC3ityRD8z4uNB4pC3n/7USFTfWZzWVAtWTuuQZDv7SuvCCX8K1YAixeHvF84WtdrjYtPE/Ytf+dPZquJiEjAoJqIKMlY3KWxhni2/5YG1WHybKkly1SnGHSejswWm0LzqDjZX7wfNy66EQBQzzoM5xzMQfOyE7jvtxj2Et64ETh6FEhLq5WZajXpdVp0aJIBABjYvqFPB/XhXZpg7q19A14bLFMN+G6xpaSk0oZNB4XAW77vdYrR+99F0PdL2rQROsQDwIMPCkseVHBXb6ER2pwtc1BlU2dMIiKq3RhUExElmTL3tkXSvX9VVVgIbNggHEeQjQ1U/m0yaD2ZyaMl1Rj17lpY7PENri12C6797FoUVRfB6DwNmY478dTQOwEAt/65BD0P7wwxQgBLlgiPw4YJW42d4m4dKDR7q7Y5fcrBR/ZsgcwgP5/Sc5VUKXXulvh59wnYHC6c1jgd7Run+7wmzVSHXCLx2GNAixbA/v3A9OnBzw3Txe0vRsusliisKsSnOz5VZUwiIqrdGFQTESWZUveevplmfXxu8NNPQplzp07Cmuowic2vTHrfXx2ZZgOMkqz6un8LseNoeB2eozVp2ST8cfQPpBuy0Mg6GRoYsKpdH3x7xkDoXU4s/O5FYGt46389nE6hqzgAXH65+pOuhcT1y1VWB06WCZ2/G6QZMej0RsGvCzNT/e7PezH9h11+r+/JF7bd6t26vt9r0oA9ZC+/tDTgxReF45deAvIUGptFSKfVYXyv8QCAGetnwKXSem0iIqq9GFQTESUZMVOdmRKnTPV33wmPYXb9nntrX3RrkYV3x/QGAL81yia91m8NbXUcy8BnbZiFt/58CwAwss2L0Lsae157aPgDcHXrBkNRATBggDfzHI45c4C//gIyMoDLLlN51rWTWMZdZXMgv6waALBgXH+/dfWBrgukyuZAabUN077/G2/8tAfH3WOL/i0Q1sW3lmylJZKu2w+rmd911wmd3EtKgFtuEd48idG4nuNg0pmw4dgGrDm0JubxiIiodmNQTUSUZEqrhUx1Rjwy1U6nN6i+5JKwLhl0eiMsuedsnOFeXyun0Whg0vsGUZWW+ATVvx74FXd/dzcAoL59DFZtyQUA1EsV3oCoMpqhWboUGDoUqKwUOkA//DBw4kTwgY8eFdbdAsCTTwINGsRl/rWNGByXW+wodm+r1TA99HZdoTLVFpsDeyTbc1XIfl72n6wAALTO9g+qpVb8fRw2R4ggWasF5s8XyvmXLQOefTb4+WFolNYIN3S5AQDw+rrXYx6PiIhqNwbVRERJpqxaLP+OQ6Z60yYgPx9ITwfOOUe1YeUl4RVWIdtuDxHwRFI6e6D4AEZ+OhI2pw2p9nOQYbvW81r/Ng29JzZpIrxxMH68UOb+8stCprIoQMdplwu4806guBjo3Rt44IGw51TXiU3BjhV7G3LVC6OCwiypXLi+X0u/16tsDuzJ9wbV4s88ANgcTuw+LpR/t2uU7netuI+7aPbqf0POB506Aa+7g99nngH+97/Q14RwX//7AACLdi7CwZKDMY9HRES1F4NqIqIkU1olNiqLQ6b6m2+ExyFDhO2GVOIXVFscmLxoG3pPXe5X2iv637qD6Pncj9h2uCTk+OXWclzxyRU4UXkCPZr0QEPbfT7bKT007AyM7NkCb17fQ3hCrwfeftsbSB05Atx9t7BvsdxbbwFffw0YDMDs2cK1BMCbca5wNxYz6rQhS78B3/JvpXXPVVYH/i2o8Hxc7l7yAAC78spQbXMiw6xHW4VMtUMWVC/edCTkfAAAd9wB/Oc/3uNd/mu5I9E1pysGtx4Mh8uBmetnxjQWERHVbgyqiYiSjFj+HZc11V9/LTyqvGZYHmhVWu1YsP4giittmPPbfsVr/rN4G4oqbXj48y1Bx3Y4Hbj5y5uxJX8LGqc1xhfXLIYW3s7cGg3QskEqXrm2Gy7tKmm8ptEAEycCv/4qHC9YANx+O2C1es/5+Wdg0iTh+KWXgC5dIvq86zr52mhrqFJr8TpJMzF5EAwAGw8W4y9JM7tSd1Dtcrkwc+UeAEC3FvWgVYjInbLqBqs9gjXSzz4LnHceUFEBXHMNUK38hk+47usnZKtnbZyFCmtFiLOJiKiuYlBNRJRkyi3uTLVJ5Yzp0aPerbSGD1d3bBnpGtnKENsnKQVdIpfLhfuX3o9FOxfBqDNi8ajFqG9u6nNOToYZRn2QX2dnnw3MnSscz5kjZOjbtxe2WjrvPCHIvvxyIQAnH6G2xgpEuu2VzaH8/f35H+86d/Fn/svNR/D9dqFDt3x/alGnZpk+H1siCap1OqH0u3FjYNs24L33wr9WwaWnX4o29dqgqLoI87fOj2ksIiKqvRhUExElGZs7SAgaKEZj6VLhsW9fYd1xDPq4tzpq3TBV8fVKq7ecd86a/UGbSQVr4Dx97XS8+ceb0ECDj678CGflnuXpji4Sm5QFNWaMN7AGgL17hZJwnU4IqOfNCz6RU1SoLt6BSDPMdocTs27qjQ5NMvDfq7sqni+uqX7vF+/66DObZyqee1a7bAzpmOP5OKKgGgCaNvU2K5s6VchaR0mn1eHevvcCAN5Y/wa31yIiOkUxqCYiSjJ2d+ZWF3IT3gitXCk8Dh0a81AzruuJO85ti3m39fM8N/+2fmiUIazTFjOPordW7g04VqBtkZbtWYZHlj8CAHjlwlcw6sxRAOAXVOdkmv2uVXTTTcC33wIzZwKffy68yVBUJGy7lakcwJ3q5F28z8hR7gAfjM3pwtBOOVh6/7no2bKe4jnl1Xa4XC6cLLd4nhvYPjvgmPddcJrnOKrt2269FWjbFjh+HHjzzcivlw7V41akG9Px14m/sHzf8pjGIiKi2olBNRFRkhHLoQ1hNIQKm8slrB8GhJLnGDXJMuM/wzsit4E3U332adm445y2AICiSqvP+d9sPRrR+DtP7MToL0bD6XLi1u634v7+93tek3aKBoDm9VPCH3j4cGDCBGDkSGDYMGFPagpI2oBuRI/m+OCW3hGPIe0AH2irrVd+/Ad7T1TgRJkFJr0Wfz93ETKCdL/v0iILL4wQ1r9XWu2RZ4gNBmDKFOH49dcBmy34+UFkmbNwS7dbhKG4vRYR0SmJQTURUZIRS6VVzVTv3w8cOiR0th4wQL1xZVJNQtB0oszi87wjSNCjkWWq88vzMfx/w1FcXYyzcs/CW5e85XOOPAt+04BWsU6bAtBoNJhyWSdMPL89Xh3VHS3qK5f7B2OXrKmW72cuNeuXfQCAni3rh9znGgAu7SasrXe6wm+g5mP0aCAnBzh2TKhWiMHEfsJ6/G93f4vdBbtjGouIiGofBtVERElGzFTr1QyqxSx1nz5Amv82RWppmGYEABwqrPJ5Xl6yHUilrRKXLbgM+4v3o32D9lgyeglMet+tv8SxerWqj18fGYwOTVi6HU9jB7bBpAvPiPp6acDbKMOEIR0bK5638M9DAIARPZuHNa50vfenfxyCxR5hGbjRCIwbJxzPjG1LrNManoZLTrsEAPDGujdiGouIiGqfqILqmTNnonXr1jCbzejXrx/Wr18f8NxZs2bhnHPOQf369VG/fn0MGTIk6PlERKc6cU11OPsBh00MqgcNUm9MBY3d65vzSn23KiqtClxeK7514HA6cOOiG/HH0T/QMKUhvrv+O2Sn+q+rLawQSsubZJl9ys8pOdll3b+fv9K7bdniCWehS/Msn9cv79YM4TDotDDohJ+eJ5fswLs/74t8cnfcAWi1wKpVwF9/RX69hLi91pwtc1BUVRTTWEREVLtE/BfbwoULMWnSJEyZMgUbN25Et27dMGzYMBw/flzx/FWrVuG6667DypUrsXbtWuTm5uLCCy/EkSNHYp48EVFdZI9HpnrVKuFRhfXUwTSRNQ0Ts4kWuzPgfsJiZffDPz6MxX8vhlFnxJejv8RpDU9TPF8MqsWsOCU3u9P3+94ow4R2jdJwek46uraohwqrbxVDOKXfImm2+qstka3bBwDk5gJXXCEcv/VW5NdLDGk7BF0ad0G5tRwvrXkpprGIiKh2iTionj59OsaNG4exY8eiU6dOeOedd5CamorZs2crnv/xxx9jwoQJ6N69Ozp06ID3338fTqcTK1asCHgPi8WC0tJSn39ERKcCl8vlKf9WbU31wYPCmmqdDjjrLHXGDKBRhslnZ6rGmd7SbWmDMene1BoN8M6f7+DV318FAMy9ci7Obnl2wHsUeIJqU8BzKHnUS/V980On1WDp/efiu4nnQKfVoLQqvKUBSqT7aO85Xo6SShuOFldF1rhswgTh8aOPgLKyqOei0Wjw3ODnAAgNy46UMnlARHSqiCiotlqt2LBhA4YMGeIdQKvFkCFDsHbt2rDGqKyshM1mQ4MGDQKeM23aNGRlZXn+5ebmRjJNIqJaSxpsGrQqlX+Lpd+9esW927VBp/UJdtNNeqSb9ACAUsm6aun61xL735j4vdDo6YXzX8DoM0cHvUeBe9ulBunMVCez98b0Qv+2DfD05Z39XjPotJ7lDeec5i3xf3hYZGu35duxdXv2B5z14k/4bMPh8Ac5/3zg9NOFgPrjjyO6v9zlZ1yOs3LPQqWtEvcvuz+msYiIqPaI6C+2kydPwuFwICcnx+f5nJwc5OXlhTXGo48+imbNmvkE5nKTJ09GSUmJ59+hQ4cimSYRUa1llwTVOp1KmeoEracW1U/1boWUatQhwywE1dJMdbVNKAl2oAwbyp+CzWnDVR2vwmNnPxZ0bLvDiR/+ygfA8u9kd2HnJvjkjgFoXi/4lmdPXtoJEy84DV/dMxATzmsX0T2k+1pLPfL51vAH0Wq92eqZM4Xt56Kk0Wjw1vC3oNPo8Plfn+O73d9FPRYREdUeCe3+/eKLL+KTTz7B4sWLYTabA55nMpmQmZnp84+I6FQgDapVW1Od4KA63R1EA0C7RunIdO83XFIlDaodcMGJAuN0VDnz0K5+O8y+fLbf9lpyP7oDaoBBdV3RIM2ISUNPR9cW9UJ+/+VsjugDYB833wykpgLbtwOrV8c0VLcm3Tz7qt/z3T2otFWqMEEiIkpmEQXV2dnZ0Ol0yM/P93k+Pz8fTZo0CXrtyy+/jBdffBE//PADunbtGvlMiYhOAQ5JkKDKmuriYmDPHuE4zuupRRlmb6b6yh7NPeuqDxd5t9mqtjlQqv8CVbo/oIUBn1/7ObLMWX5jyR0r8XYV79w89Pl06rJHsnd1vXrADTcIxzFurwUAT5/3NFpktsC/xf9i6i9TYx6PiIiSW0RBtdFoRK9evXyajIlNxwYMGBDwuv/+97947rnnsHTpUvTu3Tv62RIR1XHSTsmqZKq3ustgW7UC6tePfbwwZEgy1c3rpeD0HGEd9z/53iZQq/b/jGL9PABAPet47DwYuM+GVKW7U/ToPrmetdpESvLLlEvDA7rrLuFx0SLgxImY7p1uTMeMi2cAAF5a8xL+OhHbdl1ERJTcIi7/njRpEmbNmoW5c+di586duOuuu1BRUYGxY8cCAG666SZMnjzZc/7//d//4cknn8Ts2bPRunVr5OXlIS8vD+Xl5ep9FkREdYRd0vk70lJYRVu2CI/dusU+VpikbwY0SDPiDFlQfaD4ACatuBnQOJFmH4x0xzBMXrQtrLErrEKDs1QjA2oCPrylD85q1xCrHx3s99qx4iqFK4Lo0QPo0wew2YC5c2Oe2xVnXIHLTr8MNqcN478ZD6crgsw5ERHVKhEH1aNGjcLLL7+Mp556Ct27d8fmzZuxdOlST/OygwcP4tixY57z3377bVitVlx99dVo2rSp59/LL7+s3mdBRFRH2NXeTmvzZuExgUG1TVJ2m2rUoWk9oYfGkaIq3PDBzzj3g+EosRTA6GyHBra7oYHwuVbbHIrjSVVahEx1min8vYyp7hrcoTH+N64/WtRPRdtGaT6vHZUsFQjbuHHC47vvAo7QP4/BaDQavDn8TaQZ0rD64Gp8sPGDmMYjIqLkFVWjsnvuuQcHDhyAxWLBunXr0K9fP89rq1atwpw5czwf79+/Hy6Xy+/f008/HevciYjqHHFNtUGtoLoGMtVWu3QPag3MBiEA/regHF8eeBwHy/9Cur4hGlkfx3W9T/OcWyppZBYIM9UUyLs39sJ1fXM9W3QdKoyiQdj11wvLJPbsAb7+OuY5tcxq6dm7+pHljyCvPLydUoiIqHZJaPdvIiIKTlxTrUqm2m4XuhkDQPfusY8XJpusQZRJL/yqKdZ/iErdb4BLj+HNXoLe1Rits9OQlSI0NiutDh1UV3mCamaqyddpORmYdlVXDDq9EQDg8w2H4XRG2B08LQ24807hWKWKunv73YueTXuiuLoYDyx7QJUxiYgouTCoJiJKImL5t16nwv+e//kHsFiA9HSgTZvYxwtTr1a+DdFMeh3KdN+h1LAYAJBtux9GZycAQKMMkyeoLlHIVMs7OFe4G5UxqKZAruvbEmlGHf49WYG/jpVGPsC99wIGA/Dbb8DatTHPR6/V471L34NWo8Un2z/B0j1LYx6TiIiSC4NqIqIkYneouKZaLP3u2hXQJu5/93ec2xb/Gd4ByyedCwDYVbgZhYb3AAD1bDchzXEeiiqtAIS9pjNThFJueVC98u/j6DxlGT7785DnuUqLkKlOY+dvCiDNpMfA9kIJ+Mq/j0c+QNOmwI03CsevvKLKnHo164WJfScCACZ8O4F7VxMR1TEMqomIkojDqeKa6hpYTw0AZoMOd5zbDu0bZ6DUUor7frgF0NiR4hiATPs1AICiCiGAbpBm9GSqv9lyDFa7NzN99/82wmJ34uHPt3qeY6aawjG4Q2MAwMpdUQTVAPCAu0x7yRLgeJRjyDx3/nPIzczFv8X/Yub62PfCJiKi5MGgmogoidjENdU6FYLqGuj8LeVyuTD+m/HYX7IPOmdjNLTe5+n0XVghZKobpBmRaRaC6kWbjuCLjYc919sV1sNWWpmpptDOO0NYV73pUDHK3R3jI9KlC9C7t9CXYMECVeaUbkzH0+c9DQCY/vt0VNuj6E5ORERJiUE1EVESETPVejXKtcVMdQKblEl9sOkDfLL9E+i1ejSyPgId0j2vVbm3z6qfZkSnppme53fnl3uOTQrrysUAKcXATDUF1jQrBdnpJrhcwN7j5aEvUHLzzcKjCntWi27seiNyM3ORV56HOZvnqDYuERHVLAbVRERJRFxTrY+1/DsvT/in1QJnnqnCzCKz/fh2TPxeWEP63HnPw+Tq4HeOVgOkGXW45/z2OKtdQwCAC97stEHv/RVldzjhcrlQUimUjddPM8Zz+lQHtG8s7Fu9J9qg+rrrhIZlmzYB27apMiejzoiHz3oYAPB/v/0fbI7QHe+JiCj5MagmIkoiqm2ptXGj8Nihg7BNUAJV2iox6vNRqLJXYVi7YXjk7IcV3yTQa7XQaDTQaDSeoFpsRCZ3styKCqsDVnc38AapDKopuPaNhcqIvSeiDKobNgQuu0w4nqneGujbet6GRqmNsL94Pz7Z/olq4xIRUc1hUE1ElES8W2qpFFT37BnjjCI38fuJ+OvEX2ia3hQfjfgIWo3Ws1e11N2D23uOU4zCGulKd1m4w+lCsbtDOCB0Bp+7Zj8AYd/rFDYqoxCy000AlLdqC9t99wmPc+YA+fmxTwpAqiEVkwZMAgBMWz0NTpczxBVERJTsGFQTESURh0OlNdUbNgiPvXrFOKPIfPHXF/hg0wfQQIP5V81H4zShC7NJYQ309f1aeo7T3EFylbu7d2GFFdI+ZaXVNry0bBcAwGJnEEKhievuq6zK1Q9hOeccoG9fYb/3N99UaWbAXb3vQpYpCztP7sSXf3+p2rhERFQzGFQTESURT6ZarfLvBGaqCyoLMOG7CQCAyWdPxvltzve8ppSpzk73lnCLmecKd/n3yXKLz7lHi6tUny/VbeK2a5WxBNUaDfCwsAYab74JFBWpMDMgy5yFe/reAwB44dcX4HL5d7onIqLag0E1EVESUWVN9cmTwMGDwnGPHirMKjyTfpiE4xXH0alRJzw16Cmf1+RBtUEnrKUWpUrKvx1OF1bvPulz/q68sjjNmuoqcUmB2Gk+aiNGCM3+iouB116LeV6i+/vfj1RDKjYc24Ble5epNi4RESUeg2oioiTiUGNNtZilPv10ICNDhVmFtnTPUny05SNooMEHl38Ak97k87pJrwv6sVj+veVQMR5fvA1Tv9vp8/o/+d6g+gZJ2ThRIKlGFcq/AUCnA6ZMEY5nzgQqK2OcmSA7NRt39roTAPDET08wW01EVIsxqCYiSiJ2NdZUJ7j0u8xShvHfjAcgZN/6t+jvd47J4Pv5GGWZa2njsU/+OOR3/dq9BQCAZllmPH1555jnTHWfuKa60maPfbARI4A2bYCCAlX3rX7s7MeQbkzHhmMbsPjvxaqNS0REicWgmogoidjcW0YZYslUJ7hJ2bM/P4uDJQfRpl4bPDf4OcVzUmXduo06rex1fdB7VLizjVf3agGDjr+6KLQUNdZUi3Q6YJLQsRuvvAI4VBgTQKO0Rnig/wMAgMd/ehx2pwpvABARUcLxLxMioiQi7sMsz+RGJIGZ6r2Fe/H6utcBAG8OfxNpRuU9sTPNBp+P5Z+fUiMzAGjZINXn49vObhvtVOkUo1r5t2jsWKB+fWDvXuDrr9UZE8CDAx5Eg5QG+Pvk35i7Wb0sOBERJQ6DaiKiJGJ1bxclz+SGragI2LdPOI5zkzKXy4V7vr8HNqcNF7a7EBe3vzjguWaDfE217+fXJMuseF2X5lme44ZpRmSlGhTPI5ITg+ryajssdhUC67Q04E5hDTSmT499PLcscxaeOOcJAMCUVVNQaVNnzTYRESUOg2oioiQi7sEcdaZ60ybhsW1bIasWRwt3LMTSPUth1BnxxkVv+HTzlpN/PvKPzQYdPr69n991nZpleo5zZVlromDEN3LKLHac//LPnjesYnLPPYDBAPz6K/DHH7GP5zahzwS0ymqFI2VH8Ma6N1Qbl4iIEoNBNRFREok5qBbXU8e59Luoqgj3Lb0PAPDEOU/gjOwzgp4vXwet9Pl1aZHl8/ETl3T0CaRb1E+Jdrp0CpKu0z9SXIX80urYB23WDLjuOuFYxWy1SW/y9CN4cfWLKKgsUG1sIiKKPwbVRERJxFv+rQtxZgDieuo4Nyl7dPmjOF5xHB2zO+LRsx8Neb5R1nhNqbw902zAvNv6AgC659bDrQPbIFVSNt4gzRjjrOlUIm+OV25RqQnYA0JjMXz2mXc/eBVc3+V6dM3pihJLCaatnqbauEREFH8MqomIkog11kx1ApqUrT64GrM2zgIAvHfZezDqQge78s+nYbryNeec1gj/ThuORXedBa1W47PVVropeIdwIimTXosrujfzfFxWrVJQ3b07cP75QgfwN9Qr1dZpdfi/If8HAJixfgYOFB9QbWwiIoovBtVEREnE6t6qJ1A37KBKS4F//hGO4xRUu1wuPPzjwwCA23vcjrNbnh3WdVd0b+457twsE09c0inguRqNBlqtkNmWBtUZZjYpo/BpNBq8ProHurqXFZRbbOoN/uCDwuOsWcJ/dyoZ1m4YBrceDKvDiqdWPaXauEREFF8MqomIkkhMmerNm4XHli2B7Gz1JiXx7e5v8fvh35GiT8Fz5yvvSa3kzOZZ+Pnh87Dz2Yvw7cRz0KxeeOujU32CamaqKXJihYNqmWoAuOgioEMHIaCePVu1YTUajSdbPW/LPGzN36ra2EREFD8MqomIkogYVEeVqY5zkzK7045Hlwvrp+/tey+apDeJ6PpWDdN8Ms/hSDV4A2kG1RQN8edG1aBaq/WurX7tNcCu3th9mvfBNZ2ugQsuTF4xWbVxiYgofhhUExElgcNFlbh59nqs+Ps4gCgz1XFuUjZ702z8deIvNEhpgMfOfiwu95AzG71fBwbVFI10k7BsQNWgGgDGjAEaNgQOHAC+/lrVoaeePxV6rR7f7f4Oq/avUnVsIiJSH4NqIqIk8MSX2/HzPyc8f/grdccOKY5Nysqt5XhqpbDG86lzn0L9lPjugS2Sbosk35aLKBzimzGqrqkGgJQU4I47hOMZM1Qd+rSGp+GOnsLY9y+9Hw6nQ9XxiYhIXfwLhYgoCZwos/h8HHGmuqIC+Ptv4TgOQfUb695AfkU+2tVvh7v63KX6+IGkSLbU0mk1Qc4kUhaX8m/RXXcBOh2wciWwbZuqQz8z+BnUN9fHlvwteHfDu6qOTURE6mJQTUSUBORrqCMOqrdsAZxOoFkzoElka51DKa4uxktrXgIAPHPeM2FtoaUWaSDdLCu85mZEUuI6/kprHLK9ubnAlVcKx2++qerQ2anZeG6w0Azw8Z8ex4mKE6qOT0RE6mFQTUSUBEx63wZeEZd/x7FJ2bRfp6G4uhhnNj4To88crfr4ocy/rR9eH90drbPTEn5vqv3M7v+2LO4mgKqbOFF4nDcPKCpSdejxvceje5PuKK4uxiPLH1F1bCIiUg+DaiKiJGA2xJipjlOTsgPFB/DK2lcAANMumAadNrLu3Wo4+7Rsn32uiSJhdi8hqLbFaV3yOecAXbsCVVXABx+oOrReq8fbl7wNAJizeQ5+PfCrquMTEZE6GFQTESUBeRAddVCtcqb63Q3vwuFy4Pw25+PS0y9VdWyiRBCXVsQtqNZogHvvFY5nzgQc6t6nf4v+GNdzHABgwncTYHOo3HCNiIhixqCaiCiB3vxpN95etdfveXn5t/zjoKqqgB07hGMVg2qL3YL3N74PQNiXmqg2EjPVcSv/BoDrrwcaNAD27we+/Vb14addMA3ZqdnYfnw73lj3hurjExFRbBhUExElyKHCSrz8wz/4v6V/o0rWNEle/i1vXBbUtm1CdqxRI6C5emXSn//1OU5UnkCLzBbMUlOtJf63ZLE5cKS4CtuPlKh/k9RU4PbbheM31A96G6Y2xH+H/BcAMGXVFBwqOaT6PYiIKHoMqomIEmR/QYXnuKzat4RTXu5dL9UQ/sCbNgmPPXsKpagqeevPtwAA43uNh16rD3E2UXKSZqoHvvgTLp2xGocKK9W/0YQJgFYLrFgBbN+u+vA3d78ZA3MHosJWgfuX3a/6+EREFD0G1URECbL3eLnnuMziu2eu0+V7boO0CLatisN66s15m7Hm0BrotXrc3vN21cYlSjSxCkS6pnpXXpn6N2rVCrjqKuH45ZdVH16r0eLtS96GTqPDop2L8MFGdZuiERFR9BhUExElyP4Cb3asrNo3qHY4fKPqFEMEa6rjEFS//YfQcXhkx5Fokq7uvtdEiST2JyiXvJGljddfPw8/LDx+/DFw+LDqw3fJ6YKnz3saAHDXt3dh9cHVqt+DiIgix6CaiChBSqu8Jd9jP1wPl8sbSNucvk2UNOGWcdtswNatwnGPHjHPEQCKqoowf9t8AMCEPhNUGZOopoiZ6pPlVs9zWhWXSfjo2xcYNAiw24HXX4/LLf5zzn8wsuNI2Jw2XL7gcmw/rn6pORERRYZBNRFRgpRKstNFlTYUVnj/yLfLMtVh+/tvwGoFMjOBNm1inSIA4PlfnkelrRJdc7rinJbnqDImUU0xK1R92KL97y0cYrb63XeBEvWbomk1Wsy9ci4GtBiAouoiXDjvQuwr2qf6fYiIKHwMqomIEsDmcPpkqgHfclSHfFF1uMQsddeuqtS0nqw8ibf/FEq/X7zgxfAz5kRJSqmTflW89qwGgIsvBjp3BsrKhMA6DtKMafj2+m/RpXEXHCs/huEfD0dJdRy6mhMRUVgYVBMRxZnV7sQFr/yM9fsLfZ4vkQTZNoe3/PvhYWeEP7g0qFbBm+vfRJW9Cj2a9MBF7S9SZUyimmRSyFRXW+MYVGu1wEMPCcevvw5YLHG5Tf2U+lh24zK0yGyBXQW7cP2i6+FwxvHzIiKigBhUExHF2b8nK3BQYQuf0ipvptruzlQ/f+WZuHtw+/AHVzGorrBWYMb6GQCAx85+jFlqqhPke8ADQKXVrnCmiq6/HmjWDDh6FPjii7jdpmlGU3w56kuY9WZ8t/s7PLXyqbjdi4iIAmNQTUQUZ7oA/6ctrfbPVKcaI+j6DagaVL+/8X0UVhWiXf12GNlxZMzjESUDo8J/gFU2p8KZat7UCNx5p3D81ltxvVWvZr3wweXC9lovrH4By/ctj+v9iIjIH4NqIqI4qw7wB7y0/FtcU63TRpAdPnlSyIQBwJlnRj0/ALA5bJj++3QAwMNnPQydNsLgnihJaTQaNMow+TwX1zXVottvB/R64LffgC1b4nqr67tcjzt7CUH8mMVjcKLiRFzvR0REvhhUExHFWbXsD/hhnXMA+G6xJXb/NgRKayvZtk14bNsWyMiIaY6fbP8EB0sOIictBzd3vzmmsYiSzS8PD/b5WP7fZFw0bQpcdZVw/Pbbcb/d9GHT0blRZ+SV5+G2r27z2bKPiIjii0E1EVEcnSiz4I55G3yea5qVAkDWqMy9T7U+kky1SqXfLpcLL699GQBwf//7YdabYxqPKNmkGHWYdVNvz8dV8WxUJjXBvc/7/Plx2V5LKsWQggUjF8CoM+Lrf77Ggu0L4no/IiLyYlBNRBRHU77a7rMfda9W9ZFu0gMAKhS21NLrogiqu3WLaY6r9q/C1vytSDWkYnyv8TGNRZSshnbKwSMXCZ31E1L+DQDnngt06gRUVAALF8b9dl1yuuDJc58EAEz8fiLLwImIEoRBNRFRHG097JudmntrX8++uVbJNlo2d/m3PpK9psV1mjFmql9f9zoA4OZuN6N+Sv2YxiJKZuIbWtI3uuJKowFuuUU4/uijhNzy0YGPomtOVxRUFeC+pfcl5J5ERKc6BtVERHFisTtwrKTa83HHpplIN+lhdu+bK21gZncH2GFnqm02YPt24bh796jnuK9oH77a9RUA4N6+90Y9DlFt0D23HgDg930FiVlXDQA33CDsXf3bb8CePXG/nUFnwOzLZ0Or0WLB9gX4etfXcb8nEZ3aKix2TFmyHb/vKwCAU7KnA4NqIqI4OVZc7SnrBryBs8m9b67F7v2jXtynOuxM9a5dgMUiNChr3TrqOb65/k244MKF7S5Ex0Ydox6HqDbo0jwL2ekmVFod2HE0vmucPZo1A4YOFY7nzUvILXs164WHBjwEALjz2ztRUp2gz5WITkkfrT2AuWsPYPR7v+POeRvQ+/nl+G3PyZqeVkIxqCYiihNpeTfg3YtaLP+2SDPVzggz1WLpd7duQhYsCiXVJXh/4/sAgPv6sUyU6j6NRoOOTYVO+f/klyfuxje7O+p/9BHgjPMe2W5Pn/c0TmtwGo6WHcVDPzyUkHsS0akpv9Rblbd0Rx4KKqz4v6V/1+CMEo9BNRFRnFjtvn88i9lok14o/7bYpeXf7i21wg2QN28WHmNoUvb+xvdRZi1Dx+yOuKj9RVGPQ1SbnJ4jBNW7ExlUX3GFUFWyfz+wenVCbpliSMH7lwtvmr2/6X188883CbkvEZ16MlMMfs8dLqqqgZnUHAbVRERxYpNlqsXAWcxUr95zEqXVNve5EXb/3rhReIxyPbXNYcNr614DADw44EFoNfx1QKeGM9xB9V/HElgSnZoKXHONcDx3bsJue26rc/FA/wcAALd/dTsKqwoTdm8iOnWUVPo3fyyssPolF+oy/hVFRBQnYqDs/Vj45SI2KgOABz7ZDEBS/h3OPtVOJ/Dnn8Jx797Bzw3g0x2f4nDpYeSk5eCGrjdENQZRbdTN3axs2+ESn54HcXfTTcLjF18A1gR1HwfwwgUvoGN2R+RX5OOBZQ8k7L5EdOooqrQpPn+y3JLgmdQcBtVERHEiz1TL11QDwIq/j8PmcKKkSviFlJXqX0LlZ88eoLQUMJuBzp0jnpfT5cR/1/wXADCx30SY9eaIxyCqrdo3TkeaUYcKqwP/nkxgCfjZZwNNmwIlJcCPPybstma9GR9c/gE00OCjLR9h6Z6lCbs3EZ0aihQy1QBwooxBNRERxUjeqOzO89oB8Hb/Fu0/WQGXCzDqtchOM4Ue+I8/hMcePQBDGEG4zKKdi7A1fysyjBm4s/edEV9PVJvptBo0SDcCAEqr7Qm8sQ64+mrh+LPPEndfAANyB2Biv4kAgHFfj2MZOBGpqjhApvo4g2oiIoqVzb2W6MzmmVhy90Dcea47qNbrfM4b+uovAACdRgNtOOXfYlDdp0/Ec3I4HZiyagoA4IH+D6BBSoOIxyCq7TzNAm0JXu8nrqv+8kthS7wEev7859GufjscLj2M27667ZTcR5aI4kPsD9MgTXjDsl2jNADA8bLqgNfUNQyqiYjiROz2nWrUo1tuPU/AbDYo/6+3yuZQfN5PDEH1wh0L8deJv1DPXA8PDOD6Sjo1iUsw5NUkcTdwYI2UgANAujEdC69eCIPWgC///hIvrXkpofcnorqr0ir8/TJ3bF9sfHIo+rVtCAA4XspMNRERxUhcQ22QdfSWZ6pF489tG3pQux3YtEk4jjCotjvteObnZwAADw14CPXM9SK6nqiuMHr2ig/zjSy1aLXeEvBPP03svQH0atYLb1z8BgBg8orJWLFvRcLnQER1T5U7qE4369EgzYjGGcJSNpZ/ExFRzMStJAw63//VShuVST144RmhB92xA6iqAjIzgdNOi2g+H2/9GP8U/IOGKQ096yuJTkU1lqkGgGuvFR6XLEl4CTgAjO81Hrd0vwVOlxOjPh+FA8UHEj4HIqo7XC4XKq1Cf4pUo5A0aJwhNEA9ISv/drlcnsasdQ2DaiKiOBG31PIPqv0z1dnpJk/2LCix9LtXLyHrFSaH04HnfnkOAPDIwEeQYcoI+1qiusZYU2uqAeCss4BmzYQO/suWJfz2Go0Gbw1/Cz2b9kRBVQFGfjoS1fZTZ90jEanLYndC3J0wxRNUK2eq31q1F92f/QErdx1P6BwTgUE1EVGciOXfRnlQrbCmOtOsD2/QKNdTf/3P19hbtBf1zfVxd5+7I7qWqK4RM9UWew0E1Vqtt2FZDZSAA0CKIQWLrl2EhikNseHYBkz4dgIblxFRVMTSbwBINQhBtbjDgnyrrZeW7YLLBUz7bmfiJpggDKqJiOIk8JpqLZpm+e4NHfa6oyiD6ld/fxWAUPqZZkyL6FqiukasCrHaE7ymWiQtAa+qqpEptKrXCgtGLoBWo8WHmz/Eexveq5F5EFHtVWm14/vteQCEv3X07iRCplnY7rO0yrttodPpfeMuKyXy7UCTHYNqIqI4sTqU11RrNBr8/PBgpBi8ZeDlljD2y62uBrZtE44jCKo3HtuIXw78Ar1Wj3v63hP2dUR1VY1mqgGgf38gNxcoLweWLq2ZOQAY2m4oXjj/BQDAvd/fi98P/15jcyGi5FZcacXMlXtwtFh4I/CP/YU4c8oy/Gex8HeJuOQN8AbNJVU2LFh/EABwuMj7BuIf+4uwbEdeoqaeEAyqiYjixO7+BaPX+f+v1qjXYsEd/SMbcPNmoft3o0ZAy5ZhXyZmqa/tfC2aZzaP7J5EdZDY12Da93/7ZE8SRqv1ZqsXLkz8/SUeGfgIRnYcCZvThqs/vRr55fk1Oh8iSk5PfLkdLy3bhetmCW++vb1qLwL97zNDsqRt8iIh6D5R7tu7Yfy8DT6l47Udg2oiojjxrqnWKL7ePbcePrq1Lww6DZ678szQA0pLvzXKY8oVVhXi0x3Cus0H+nNfaiLAtwP/jztrKIgUg+qvvwYqKmpmDhAqZz684kN0yO6AI2VHMOrzUbA56mZ3XiKK3i//nAAAHCioRLXNgb+OlgY812zwbchabXOgoNzqd96mg0XqTrIGMagmIoqTQOXfUuee3gg7nrkIY/q3Cj1gFOupP93xKawOK7rldEPvZr3Dvo6oLpMG1aU1tb1Lnz5AmzZAZSXw1Vc1Mwe3DFMGFo9ajAxjBn4+8DMeXf5ojc6HiJKLw+ny2aHk6y1HkVca/q4BhworUVDhH1Sv+7dQlfklAwbVRERxYrO7t9QKsVVWWFtpAVEF1fO2zgMAjOk6JuxriOo6p6TTdbopzM77atNogBtvFI7feqtm5iDRIbsD5l45F4CwZGTBtgU1PCMiSgYulwtXvfUbTkoyzQ9/vhUA0K1FVlhjPP31DuSVCEF4mlGHG/u3xIgezdE9t57q860pDKqJiOLEFkamOmylpcCuXcJx7/AyznsL92LNoTXQarS4rst1sc+BqI6okKzjC/tNrXgYPx7Q64HVq4WeCTVsRMcRmHz2ZADA7V/fjm3522p4RkRU0yx2J7YcLlF87eIuTfHhLcIb/Vf1DNyz5bc9BXh9xW4AwI0DWuH5K7vg1VHdMbhDY/UnXEMYVBMRxUmoNdUR2bgRcLmEjsE5OWFd8vG2jwEAF7S5AM0ymsU+B6I6olLSbV/87/RwUSUsid5iq3lzYORI4XjGjMTeO4DnBj+HoW2HotJWiRELR6C4urimp0RENUhcyqakaZYZgzs0xrr/XICXru7m89rjwzsqXtMwzajq/JIFg2oiojgRt5dQJVMdYem3y+XC/K3zAbD0m0hOmqmutjnx6Odbcfb/rcQts/9I/GTuvVd4/N//gIKCxN9fRqfVYcHIBWiV1Qp7i/bixkU3wumqoa3HiKjGWYNsPZjp3jorJ9MMndY3gTDu3La4sb//TiVtstPVnWCSYFBNRBQn1TbhD/eaCKrXH1mP3YW7kWpIxYiOI2K/P1Ed4pKsqf7fuoNY+OchAMDafTUQ1J51FtCjh7AP/fvvJ/7+ChqmNsSiUYtg1pvx7e5vMWXllJqeEhHVEHlQPXXEmUg36ZFh1qNnbv2g12aYDX7PdWyaoer8kgWDaiKiONl3Utgmp2WD1NgH27hReOzVK6zTxdLvKztciXRj3XxXmChaj13cwXO8fn8Nd5/VaLzZ6rfeEvaiTwI9m/bErMtmAQCe//V5fLbjsxqeERHVBHlQ3SO3PjY8OQSrHz0fWan+QbOUdL9qUfN6KarOL1kwqCYiigO7w4m9x8sBAGc0ifFd2bIyYO9e4bh799D3dtqxcMdCAMANXW6I7d5EdVD7xhkY3qWJ4mtLNh/BQ59tQWl1ArfaGj0aaNgQOHiwxrfXkrqx6414cMCDAIBbltyCLXlbanhGRJRo8jXVqUYdTHodslKCB9QAkGb0BtWDTm+Ej27tC41GhT4zSSiqoHrmzJlo3bo1zGYz+vXrh/Xr1wc8d8eOHRg5ciRat24NjUaD1157Ldq5EhHVGgcLK2F1OJFi0MX+ruxWYesKNGsGNGoU8vTl+5bjeMVxZKdmY2jbobHdm6iOMgZYlnHfJ5vx+YbD+ODXfxM3mZQUoRM4ALz4otCUMEm8OORFXNjuQlTaKnHFJ1fgZOXJmp4SESWQPFPdONMU9rXS+Pm9m3rh3NND/w1TW0UcVC9cuBCTJk3ClClTsHHjRnTr1g3Dhg3D8ePHFc+vrKxE27Zt8eKLL6JJE+V3hYmIagu7w4nvtx3D8dLqgOdsP1KC8fM2AABaNUyFVhvju7Jb3NmhMLLUADB702wAwKjOo2DQhX4nmehUFKrXwfGywP+Nx8V99wnB9R9/ACtWJPbeQei1enwy8hO0b9AeB0oOsHEZ0SnG4g6qTXotfn1kMFKN/iXdgUjfHzTpdWpPLalEHFRPnz4d48aNw9ixY9GpUye88847SE1NxezZsxXP79OnD1566SWMHj0aJlP472wQESWjT/44hLs+3oiLX/814DmXzliN3e7S71w11lOL+9d26xb0NAA4WnYUi/9eDAAY13Nc7PcmqqMMIfanTvgfgI0bA+Pc/81OnZrYe4dQP6U+Fl27CCn6FCzbuwxTf0mu+RFR/IiZ6hb1UyL+mybmpEItElFQbbVasWHDBgwZMsQ7gFaLIUOGYO3atapNymKxoLS01OcfEVEy+G2PUPpYUGEN6/zc+ioE1RFkqmdtmAW7046BuQPRrUnoIJzoVBWo/Fv0xcbDPl3CE+KhhwCDAVi1ClizJrH3DqFLThe8fcnbAIApq6Zg+b7lNTwjIkoEcU21MYo3Gi/v1gxNs8y4tncLtaeVdCIKqk+ePAmHw4GcnByf53NycpCXl6fapKZNm4asrCzPv9zcXNXGJiKKRaOM4BU3TqfvH+G5DWJcT+1wANu2Ccchgmqbw4b3Nr4HALi7z92x3ZeojjPKMtU5snWCZdV2fLP1WCKnBOTmAjfdJBy/8EJi7x2Gm7vfjNt63AYXXLhx0Y04UXGipqdERHEmZqrl/88MR1aKAb89ej7+e3Xdf5M/Kbt/T548GSUlJZ5/hw4dqukpEREBABqle//wrrD4b32TL1uHGXPn7927gaoqIDUVaNcu6Klf7foKR8uOonFaY1zV8arY7ktUxxl03rLETLMe3048B3Nv7YuPb+/neX7B+oNYues4rn1nLfa7t8irtjlgsTviN7HHHgO0WuDbb71LP5LIjItnoHOjzsivyMftX9+e+Gw+Efmotjmw8u/jqLLG5/9LYlBtClHdE8ipUgIe0VcnOzsbOp0O+fn5Ps/n5+er2oTMZDIhMzPT5x8RUTIwG7zlT/1eWIFyWWB9tNg3qO7cNCu2G4p/VHftCuiCl17N/GMmAGEttUnPHhZEwUgblTXJMiM73YRBpzfCwPbZuO+C0wAAu/LKMPbDP7B+fyHu+2QTqm0ODH55FS6bsTp+wWT79sCoUcJxEmarUwwp+Piqj2HUGfHVrq8wZ/Ocmp4S0Slt6rc7MXbOH3hqyfa4jG91CMF6NJnqU0lEXx2j0YhevXphhaQrpdPpxIoVKzBgwADVJ0dElGxsTm/X23KLHT/s8F36svJv704IjTNMyEqNsfu2uJ46RJOynSd2YuX+ldBqtLij1x2x3ZPoFCD9A1G+rOPG/q0AAIWV3t4JWw6XYMuhYhwrqcY/+eUoqYrjPtaTJwuPn38O7NoVv/tEqVuTbnhu8HMAgEk/TEJeuXpLAIkoMvN+PwAA+GzD4biMH0v5tyKnE/j0U2DIEEDFnlw1LeKvzqRJkzBr1izMnTsXO3fuxF133YWKigqMHTsWAHDTTTdhsvjLAEJzs82bN2Pz5s2wWq04cuQINm/ejD179qj3WRARJYjd4ZudWrO3wHO84UAh3lwp/L+tTXba/7d33+FN1d8Dx98ZTbr3pgtKyyx77yWgoCgOVFzgFieuL+4tPwcO3BMVREQBFRFlz7L3LKOlLV2U7pk0ub8/bps2tIUWWlbP63nu0zS5yb3pbca5n/M5h/+eGHDuG6wYqT7DfOovtnwBwNXRVxPmEXbu2xXiMle1UJmHk/3JL28XA1pN9XbRh08U2C6nnaat3jmLiYFrrlF3YOrUxtvOOZjcezJdg7qSU5LDw4sevtC7I4RoJLag+izTv+1s3Qr9+qnZOMuWwYwZ5/6YF4l6/3XGjRvHe++9x0svvUSnTp3YsWMHixcvthUvS0xMJDW1srBHSkoKnTt3pnPnzqSmpvLee+/RuXNn7rnnnoZ7FkIIcZ6UlVfBbO7rAkDskZO2NNA/d6TY1usU6omns+HcN1iHkepiczE/7voRgAe7PXju2xSiCaia/u3uaB9U67QavF2qT6H4cf0x2+W03EbuY/388+rPmTPh2LHTr3sB6LV6vr3mW/RaPb/v/515++dd6F0SoknIyCvho6WHWB13olpx1MZgKh9MOKeR6m3b4MYboXt3dXTa1RVeeqkyK+cyUPfu3VU8/PDDPPxwzWclV65cafd7RESEFLEQQlw2zOUfYL1a+JCcXcTxnGKaT1nEAwMjSa3yJdvaEO97GRmQmgoajTpyVYvf9v1GTkkO4R7hXBF5xblvV4gmwOE0I9WgpoRnFpTaXXcwPd92Ob0xR6oBevRQ0yOXLoV334VPPmnc7Z2FjoEdeabPM7y19i0mLZrE4IjBeDl5XejdanTpeSW8sGAPd/WJoG9L3wu9O6KJSMkpZuaGY3y28ojtuhdHt7Vd1jdSQbBzSv9OTFSLL86eXXnd+PHwzjsQHNxAe3hxkBnnDSSr0MTbi/bz+C/bL/SuCCEaUcVItbujnp7NfWzXf7HqCEfLqwMDFDVEFc6KUeqoKPWsbi0q2mjd0+UetBp5WxeiLqp+QXSvJag+nVOLEjaK555Tf37zDVyknVBeHPgirXxakVaQxoN/P9gkBlKen7+bJfvSGf/Nxgu9K6IJee+/g3YBNcDrC/fZLjs51L+PdF2cdVD9/ffQrp0aUGs0cOut6veamTMvu4AaJKhuMHqdhi9XH2XBjhRyqhQ2EUJcXszlaVB6nYZbetjPXT52sjKodjE0wIdbxXzq06R+x52MY23iWnQaHRM6TTj3bQrRRHhVKSLo7lg9cS/sDD3m96bkNfg+VTNoEAwcCKWllengFxlHvSM/XPsDeq2eOXvn8P2O7y/0LjW6bYk5F3oXRBN0MC3/tLeXWqyNclKrooVgnedUKwo88QRMnAgFBdC3r5r+PWuW2snkMiVBdQNxd3QgxEv9AN6fevp/eiHEpausvPq3XqslwN1+JKsi4G4T5M6Tw1ud+8bqUKTsp50/ATCi5QiauTc7920K0URE+lVmf7jWEFS38K28/dae1Yv/7UzOafxRWY0G3ntPvfzTT7BlS+Nu7yz1DOlpqwb+8KKH2ZW+6wLvUeM4drKQ6z5bR1Zh5eDJ0RMFtgwmIRqLoigkZhUB8PEtnbmibUC1dUxlVpbtz6h2/bnKLh8s9KxrN5NXX4UPP1Tfv954A1atOmOx1cuBBNUNqE2Q2k97X+p5OHsthLggKqp/O+g0uDlW/4CJ8nfln8f6E+rtfO4b27pV/VnLSLWiKMzcPROA22JuO/ftCdGEVH2N5hWXVbs92LNypPrxYVEseWIAt/UKY80zg3Fy0HEiv5QNR7Maf0e7dYPbb1cvT55cvST5ReKZvs8wsuVIisuKGTtnLDklORd6lxrcR8sOsf2UUeoh76/i1m82YjkPBaNE05VVaCK/pAyNBoa3DeDrO7rxw8Qe1dZbsON4g287I0+tLeHv5njmlWfMUINqgE8/VTNsdI2Tln6xkaC6AVVUA07JKb7AeyKEaCyV6d9a3GoY3Qr0qMOHTl2kpqr9aTUa6NOnxlXWJ60nIScBV4MrY1qPaZjtCtFE6LQaInzUwLp/VPViU31b+hDh48w1HYPxd3MkKsCNN66NIdRbvQ5g2f7087Ozb74JTk6wZg18++352WY9aTVaZo2dRYRnBEeyjzB+3njKrNVPVlzKXAw11/fdFJ/FloTzcIJFNFnJ2WpsEeDmiGP53Ok+kT7V1jtwhhTx+jqcUcCyA+ro95nqTLB8Odx7r3r5+efhwabVjUSC6gZkLJ/AL2lAQly+KtO/NTUH1e4NFFSvWKH+7NwZvGqupvvTLjX1+/o21+Ps0AAj40I0MQsf7c+qpwfRwq96IUA3RwdWPj2Yj2/pXO22VoFuAKQ2dgXwCqGh8Npr6uXJky/KFlsA3k7e/H7T7zjqHVl0aBGT/p50WRUu052muvKRE4W13ibE2TqeU0yRqYzUXDWoDvKs/I7hoNPywbiOGPRaXhvTDlCnI5SYLSzdl85PsQnnvP2HZm21XfY/XVC9fz+MHQtlZXDzzZXvV02IBNUNSK9V/5xmSQES4rJVmf6trXHUIqChgurly9WfQ4bUeHOxuZhf9vwCwB0d72iYbQrRxLga9YT7uNT7fhUZKY3eq7qqJ55Qs1by8+Hqq0k8kEDskZPnb/t11CWoC7PGzkKr0fLVtq94ZeUrF3qXGkxhqTry/uiQltVui0uXejqiYSVlFdF36nLGfLLO1rIz6JRsuOs6h7D/tZHc3iscN0c9VgWW7c/gnh+38OIfezl0jv+XcekFtsv+7rUE1bt3q+3/cnPVomTffw/aphdiNr1n3Ij0OvUMprlMRqqFuFyZyzNR9DoN2hpGLU4tXnbWKkaqBw+u8eb5B+aTW5pLhGcEgyIGNcw2hRB1ckGCap0OfvwRAgNh927MAwfzyIf/XJRpx2PbjOXTqz4F4LXVr/H55s8v8B41jEKTGlT7uBp5/qo2jIoJ4vmr2gAwY30CGecrc0E0CSvjTgBwKKPAlv4d6F69K4FOq0Gj0RDqpWasPVqlve/hjIJq69dV1ZFuX1djzXOqV62C/v0hJUVtn7VgATg20ODCJUaC6gbkUB5Ul8lItRCXrYrXt76WNMDmvrX3k66zhAQ4elT9Et2/f42rfLf9OwDu6niX9KYW4jyrGC1Kzys5vwWqIiNh5UrMgUFEZiQwe/ZzLFqy/cz3uwAe6PYArwx8BYBJiybx277fLuwONYDCUrW1kLNBx70DWvDp+C5c1SHI9v3vl80XZy9xcWkyVukLvb48K+XUkeqqKroQVX1PenDWNn7dksSJ/NJ6bdtssdp6Yt/Trzmbnx9affrD3LkwYoQ6Qt2vn1rzwbd6fYqmQr6JNSCH8v5tZplTLcRlyzZSXUNqk6+rocbCIfX233/qz+7dwc2t2s0JOQksj1fTw+/sdOe5b08IUS/+bo4Y9VrKrApJ5W1uzpf7N+Uz7JpXSXHzJepkEnc+PwHleMNX/G0ILw18iQe6PoCCwvh541mZsPJC79I5qUj/djVWTv1p5unEm9fFANgKOgnRELKrtG7bX95ZqGOoZ63rh3jVXFvlmd92ceMX6+u83b92pvDC/D2k5pbg62rg6ZGt0GiqBNSKAu+8AzfdBKWlcO216veWWuq/NBUSVDcgva6iUJmMVAtxuSqzVf9WP2A+ubUzV3cMZs59vVjyxMAaU8Lrbe5c9eeYmit6f7nlSxQUhrUYRoRnxLlvTwhRLzqthugA9YTXgbTz10azsLSMf/emc8wrmHG3TiXZ3Y/wE0mY+vWHv/++6NptaTQaPrnqE8a2GYvJYmLML2PYmbbzQu/WWSsoD6pdjPb1NLqEeQJwKD3/sirMJi6sk1WC6goV/2s1qRiprknCyaI6nQBMzi7ikdnbmbNFzbq4tWc4Rn2VllhFRXDbbfDss+rvjz4Kv/2mdido4iSobkAO5V+mZaRaiMtXRfXvisyU0R2CmX5LZ3q28MHLxXDuG8jMrJxPfeON1W4uLSvlm+3fADCp+6Rz354Q4qy0Lq8Avj+1cQtUWawKq+JOUGQq4589abbrkzwDeXrSxyR5BGBMiIfRo6F3b1i2rFH3p750Wh2zxs5iYPhA8krzGDlrJPHZ8Rd6t85KkUlN/3Yx2vfdDfdxwUGnochk4bi0VRUNJLPAPmX7hVFtbAN4NQn1th+pjvSzL8K4+3juGbe5N6XyJKGDTsP4nmGVNx47phYi+/ln0Oth+nT46KOz7kN9IPPAZXUSSoLqBmRL/5Y51UJctmx9qhtiRLoms2aBxaK20oqMrHbz3H1zySzKJMQ9hNHRoxtnH4QQZxRW/gU2vZGLUz01dyd3freJ1xfu46m59qO8rz8+musnfsQXPcZidXSCjRvVKrw33QRpabU84vnnqHdkwc0L6BDQgbSCNIbPHE5G4aWXKl1Yy0i1g05LZHlbtj11CFyEqIvEk+rI8qvXtOP3B/twd7/mp13/1JHqcd1D7X5/aNY2vllz9LSPMWNdAgBaDXx9R7fKjiYrVkC3brBjB/j5wdKl8PDDdX8yVaTkpzDxj4m0/bQtc/fNPavHuBhJUN2AKtJBpU+1EJevU0eqG5TZDNOmqZfvu6/GVaZvmg7Ag90eRK+t3tJLCHF+eJZnpmTVkKJZcf25jsIUmyzM367Ol569qXoRrJb+rnToGMnUwROZPWelmoqp06lTSNq0gW++AevF8Z3E09GTf8b/Q4RnBIezDjPq51Hkl14abaiO5xQz4ftNtnRcN0eHauv0aqHW05gybzcm6QIjzkF8ZiFXfrSGLcey0WpgSGt/uoZ72c9rrkHVoPrrO7pxR+8InhoezdguzWzXv/H3fhIyC9mSkMX2xGyOnqisDr5kXzqxR9WCaC+MasugaD/1RN2ECXDFFWomXZcusGULDBxY7+eVW5LLi8tfJGp6FN/v+B4Fhc3HN9f7cS5WElQ3IClUJsTl79Q51Q1q9mxITAR/f7izegGyTcc3sen4Jgw6A/d0uafhty+EqDMvZzWwyiky265TFIX1RzJ55reddHl9CW8t2l/nx1t7KJPdyfajnHWZr92+mTsAW0sMairm5s3QtSvk5MC990LPnrBuXbX7rT+ced77XAe7BfPvbf/i6+zLlpQtXP/r9ZgsNZ+UuFik5hbz0dI4Vhw8YbsuwK1668RhbQIAyC4y8+/es88SOHKigF82Jda7WrO4PMRnFjL4vZW2wmSdQj2rpXXXxs3RgXbB7vi6GujX0hdHBx0PD4nizt4RdpW7f4w9xg1fxHLdZ+sZ8v4qVpW37pq3LRmAYaHO3Lb7P/V9pFcvmDFDzaC77TZYuxbCwmrafK3ySvOYunYqLT5uwRtr3qDIXETvkN7E3h3Lu8PfrddjXcxkmKMBVQbVkv4txOXqdNW/z+2BzfDqq+rlJ56osejHJ5s+AeDm9jfj7+LfsNsXQtSLt7M6Up1dZMJqVdBqNczccIwX/9hrW2d9HYPWoycKuO3bjQDseOkKVsWdoGdzH575bVe1dd+4tj37UvO4qZua2tku2AOAfRVzITt3hg0b4OOP4ZVX1FGlfv3UGg3/93/QvDmFpWXc+o26vf2vjcTJcHZzIs9GtE80i25dxOAfBrPk6BLG/DKGmdfNxMe5ATonnIXDGfks3JXKPf1b2FX1BkjKKmLEh6ttc6kr1DSvtW9LHzqGeLAzOZdN8Vlc3TH4rPbnjm83cTynmAD3OFY9PRhHh/N3bMSFtz0x2+73IM/6FQBbMKkvZovV7jXdMdSTbS9ewRsL9zF3azLfrbOvafDp8sMMDHEhfOVipq/7lyuPbUVfXF7UzGiEcePggQfUmg31kFWcxccbP+ajjR+RU5IDQBvfNrwx5A2ua33dGUfeLzUSVDcgW/r3RZJqJYRoeBV9qh0aeqR6xgy1N7W/PzzySLWbMwozmLN3DgAPdz+7eUxCiIbjWR5UH8oooMOr//HamHa8s/ig3TrZtaSGn2pLQuUX6U6vLTntut0jvLmtV7jt94qR6kMZBZSYLWoQptfD5Mkwfjy8+CJ8+62aEj5/Ptx5J/mPP2u7f06xCSfD+a3c271Zd+aNm8eYX8aw+PBiOn3ZiTk3zKFPaJ/zuh8ALyzYw4ajWaw/cpJf77cPGn7ZnFgtoK6NRqPhgYGRPDhrG1uOZZ/5DjWwWBVbobP0vFL2puTRNbxptylqao5nn1Lorp7jdA46bY3T0zycHGhRPu+/gs5qYeDRrdzw10qUp7byv8LCyhtbtlQD6bvuAp/6nfAqLSvlo40f8cbqN8g3qVM8Wvu25rl+z3FrzK3otJfniSJJ/25ADuUjV+YyGakW4nJVmf7dgG+fOTnqiBLAc8+Bi0u1VX7Y8QMmi4nuwd3p3qx7w21bCHFWvFwq59UWlJYx+dedFJntA7CU3BIOpp153vCO5JzT3t4jwtt2uaW//RfjQHdHvF0MWKyKbVu5RWY1qyYgAL76CrZvh+HDoawMvv0W/24xvLV4Ou3TDpNbbOZCGB45nI33bCTaJ5rkvGQGfD+Ad9e9i1U5vwMTG45mAbApPstu+p7VqrBkX3q19W/pEVrtugoxIWrWwP7UPJ6eW//WYXmnHIvk7PPbA11ceCm59kF1hG/dUr/rIjpAfe/wK8jmiTUz2TfjXr77/TWu2rcaTWEhye7+fNFjLNkr1kJcHDz5ZL0CakVRWBi3kHaftePZpc+Sb8qnQ0AHfr3hV/Y8uIfbO95+2QbUICPVDapi5MosI9VnlJ5XwherjnBbr3BbxUwhLgV5JeqXHldjA34wPPEEpKRAVBTcf3+1mxVFsbXRuq9rzQXMhBDnl5dz9RZ6lhq6f4z/ZgNbXrjC9nuJ2cLjv+ygX5SvbcQ5+dTRqXJaDex7bSTHc4p5bt5uHh0aZTc3EtQR0pZ+rmwqzGLMp+uY0DeC2ZsSGdzKn89v66qu1KED/PsvrF8Pzz2HdtUqbt35L7fu/Je8/XPg9VfUquENPa3lDDoEdGDLvVu4b+F9/LLnF55Z+gwrj63k3Svepa1f2/OyD+2bubPnuJo6v/LgCd7/7yAHajkR8sSwaO4f2KLWx2pWJVV37tZknhrRqrJ6ch1sOGo/XaCm/4uZG46xeE8a02/pXNnGsaAAEhLgxAnw9lY7R7jKd6tLUUWLvqtiAjHqdTwwsHoXkLM10JTOzxu+ouvaRRgtaiX7LBcP5rUZxF9tBrAzKBoHvZb7BvSBeqZmb0jewP+W/o9Vx1YBEOgayNShU7m94+1oNU1jDFeC6gZUMXJVJnOqz+iJOTtYf+Qkv29NZtcrIy707ghRJyVmC/kl6geRn1vdvyid1sKFauq3RgPffw+O1R93XdI64k7G4eLgwrh24xpmu0KIc+LooMPX1VitlyzAbw/05oYvYgHILLBPAf9jx3EW701j8d40W1CdUd6Wa2znZswrr/YNEOThhKODjkg/V+bcX/t8xiDPyveN78tb4lTtaW3Tpw+sWMHmmX+S9tb7DD8Ui/umWBgxAkJD1dvbtFELEQUHq/Oz/Ru3foOb0Y2fx/7MoPBBPLb4MRYdWsSiQ4u4osUVTOw8kbFtxmLQVT+B0VCKSiuzC+79cctp1x3eLuC0c5w1Gg3XdAzmz50pAKw/ksl1nUPqvC8Pztpm9/ue47koimKbe7r+SCYvLNhDUN4JPp/1JU/rj+OwY5talflUoaEQEwMdO6qVmvv3B+eGG/U83xIyCzFZrEQHuF3oXWk0m+Kz2JGUA8AjQ6JoE+TeMA+8ciVMnYr+33+xTbDo3RueeILFgZ144+8426qtAt3Q1qNl6Mbkjfzfuv9j/oH5ABh1Rh7r+RgvDHgBN+Ple6xqIkF1A3KQllp1trP8TSOvPEAR4lKQkad+eTbqtbg7NsDbZ1ZWZeusyZOhb98aV/tmmzpKPa7duCb3ISXExSzQo3pQ3SnUk24R3nw+vostSCo2WWyFg7IKK1N8C0vLKCwts42M3jewBaUWK3/vSgWq952tTZBHzetVFFCzo9GQ2LYrT455lsC8TH7MWkX04nmQlARz5lR/kDZtYMAAtYp4ixZqOqizs1pM0clJvezgUO+RLftd0nB/t/vpE9qHV1a9wvz981lydAlLji4hxD2Ex3s+zr1d78Xd2EBBRhX5pXX/HuLrWr3q96mmXh9DWm4JmxKyqs+PRS12WdOc15racP2zJ42vVh/lxm6hxKXn89mHv/PRstmMPrAG3alp8l5earp/Zqa6JCWpy6JF8PbbYDCoJ02GDYNRo6BTpzo/7wut2GRh0HsrAdj1ynDca2hpdilQFIXU3BKCPBxrLNK19rB6cmRku8CGCai3blWnlP33n/q7Vgtjx6rfN8qLjt0KXN+7Bf/3z0HWH8nknes7nvFhzRYzv+//nY82fsSG5A3qQ2u03NnxTl4Z9AphHvWrDn65kKC6AVW8SZpkpPqMDHothXUs/iHExSI9Xx1N8nc3NkzVysceg9RUaNUKXn+9xlVyS3KZu28ugLTREuIik5pTUu26CB91NHBk+0DcHfXklZRxNLPAVqX7eE7lPNmEk4U8+Wvl3NsAN0eeGt6qSlBdt5HF2gondn1jCUNaB/D+TfZflCumsaS5+7Ji3PNEz/gMVqyAPXvgwAE4flxt77d/f+Xy5Ze174BWqwbYrq7QrBmEh6sjpB07Qtu2ajCuP/NXzpiAGH6/6Xfis+OZsWMGX237iuS8ZJ5a8hSvr36dB7o9wP1d76e5V/M6/V3qoqAOJ/enjo2h0GTBr4ZWWqdyNujpHemjBtU59kH1d2vjeePvfYxoF8iAaD+u69zMNvJ96tz2/13Zmqn/HODT5YdY+/18JqyZw8yjlSPpG0PbU3z1tQyaeK1aVMrDo/LOWVnqMdu5U22xtmyZGmCvXKkuL7wA3bqphahuvbXGbhMXk4pgE+C3LckEezoxsn3gBdyjs/P7tuM8NXcnz4xsxUODWla7fesxdX5/vyjfc9vQwYPw0kvw66/q7w4Oanu9J59UX4unMOp1vHT1madbZBdn89XWr5i+aTrH89WMGoPOwC3tb+GZvs+ctykbFysJqhuQg1T/rjODvmnMrxCXl4qR6oCGSP1esABmzlS/jM6YUeuXml/2/EKRuYg2vm3oFdLr3LcrhGgwT49oxf/m7ba7LtxHLTSo0WjoFObF6rgTLNyVSpS/G3tScpm5IdG27qyNiXbzdz2dHXB00OHmqCe/pIxOoR7URftmles9eUU0Hy8/hNmikF1k5vdtybx8TVvb6J7VqrB0f2UBru2JOTAwEq68Ul2qysqCNWvUPtebN6u1H7KyKMorwGg2VY6WWq1QWKgu6emwbZtaabyCwQDR0dCunTpSdt116hf9WjT3as6rg1/luf7PMXPXTN5d/y4HTx7k/9b9H/+37v8Y0nwIEzupqeFODmcfEJZZrBSbq5/gD/V2IilLDYhXPjWICN/qxSNPp1l5hsHsTUm0C/bglh5hlFmtvLZwH6COQP+zJ40p83bz3o0duaFrSLWg+t5OfhR99Akj1/1B2wy1BZJFoyVuwAheb3s1693DuK1XGIO6xtg9n/jMQlr6e6Hp27cy+0lR4PBhWLpUHbVctEhttXbPPWqRzLfeUivFn+c59XW1I6mymnrF33Dp5IHVivZdzDLyS3iqvHjdO4sP8tCglnaZJEWmMjaXdwHo1cK71sc5rT171OM5b556zDUa9bi++mqNwXRdmCwmNiZvZO6+uXy3/TsKzWqF8ACXAB7q/hD3d72fANeAs9vfy4wE1Q2oom+tzKk+MwmqxaXoWJb6YRJcz76R1WRmVhYke+op6FV7sFxRoOyeLvdcdj0dhbjU3dQtlJgQD/7cmcKXq44CEO5TObp8a48wVsed4POVR/h85ZFq9/95Y2WAPfmKaDQaDU4GHfMe7ENWoYkezev25Xp42wA+urkTHUM8ifB1Yc6WJLsiVx1f/Y/Fjw2gVaAbn686wrrDlQWxFu9NI7OgtObUZm9vGDNGXapo+7+/QVEwWMrY8lRfnM2l6E2lkJcHyclw5Ihacbxi5LuoSL28Z4+aYh4UBA8+CA8/rKYt18KoN3J3l7uZ0HkCC+MWMn3TdJYdXcby+OUsj1+O92Jv7up4F/d3u59on+g6/a2qKiytHlC7GHRc0SaQ79bFo9VAmHf95yFXvc8LC/ZQZrHSupZ03qfm7mRAtK8tqA7KO8Hskk3owm5lcp5aQK1Eb2Beu8F82fN6Pnz+Bkal5rF+/h7Scu0zJd5adIDv1sXzwbiO9nO5NRq1EGZUlPp3P3FCreExfbp6vO64Az74AN57D4YMqffzbWzZRdUr1B9Iy7uog+q8EjMrD55geNsA9FoN136yzu72O7/bRFx6Pj9M7EF0gBuLdqdhKrMS4uVU/wK+hYXw/PNqb3qlPAYZM0bNgIuJOf19q1AUhZPFJ9maspUNyRuITY5lbeJaWyANEOMfw5O9n+Tm9jdj1J85c6MpkaC6AVX0qTbJnOozMjRkOyIhGoGiKBzNLKS5j4vtTPLe8gqxbYPPca7TCy9ARoY6V/HVV2tdbWfaTrakbMFB68DtHW4/t20KIRqcVquhXbAHLf1dbUG1p3PlCOywNv54OTvUGBRUcDPqWfH0ILugNqqexZg0Gg1jOjWz/R7s4WQXVCsKjPhwNR1DPDhyQv2CHOHjTEZ+KUUmC8/+tov/u6EDvq5GLFYFrYZaT+IVV0zd0mgw6R3o8OEmfF0NzLynJ60jI9XiZqijplYFikpMjH76Z1pmJvKk60li/pmrTnt56SU1iHv0UXj88dO27tFqtFzT6hquaXUNx3KO8cPOH/h2+7ck5iYybcM0pm2YRv+w/kzoNIEb2t5Q59oT+aXqcTHqtWg0UGK20quFD/cPbIGvm4FrOzWrV9GmCt0jvJnQN8JWNO7rNfHc2K32gmVXPvc7/RN38uX+NQw7shmdtfxvXB4EG++4g5GObrQ5WUjnMC+yyvufb07IpshUhrNBj6nMynfr1BHttxYdOH2BND8/eOYZeOQRNRB76y31JMjQoTB6NLzzjvr5dAFl5JXwy+Yk7uwTQW4Nr59ZGxIxW6z1KgR3Pk1fdoiv16jH44q2AaSccgJkVdwJAJ75bRcvjm5rG8W+KiaofifQly9XMw7i1W1xww3qaHW7dqe9W1ZxFrvSd9ktcSfjyC3Nrbaun7MfQ1sMZWKniQxrMUxO8NdCguoGZLBV/5ag+kwM+su3T524PHy7Np43/t7PhL4RvHx1OxRFYWd5L9l25xJUx8XBN+roM198UWO1b9s+bP8WgDGtx+Dn4nf22xRCNCqjXkfP5t4kZhXRq0VlcKjXabmuc4gt2Knw3FWteWvRAQC6RXjVqQBWfYzvFcb+1Dz83I10DfNi7tZkAHYmV35h/mFiD9799yALd6Wy7EAGHy87xPC2gdz9w2aCPZ348+G+uJ1SEGrFgYwaeydnFphYuDOVQ+kFWBWF5Oxivlsbj5NBxxPDokn2CCDZIwB9G3+++fJ9+O03tXjWnj3wxhvw4YdqgDd5Mviefj5puGc4Lw18ief7P8/iw4v5YusX/B33N2sS17AmcQ0P//Mw17e5ntHRo+kf1p8gt6BaH6uim4OrUc8PE3vwU+wxnhwejb+7Y41zXutKp9Xw8tXteHZkazq/toTjOcX8sinJdrtXUS69EnfTK2k3vRJ30yoz0f4BBg1S579edRVotWgAb8C7vIVW13Av3Bz15BabafvSv9W271bXQppOTvDsszBxIrz2Gnz+udqR4p9/4O671bofbc/fPFmzxYxWo0Wr0TJl3m6WHchgVdwJHB2qD8TEHj1J7NGThHo50y3iLNOlG0lqbrEtoAZq7HdeYUdSDtd/vt72+209w+u2kbw89cRIRa2DsDD4+mu1H/0pTBYT21O3sz5pPbHJsWxI3kBSXlK19Sq08GpB75De9A7pTb+wfsQExDSZtljnQqMoykWfq5yXl4eHhwe5ubm4uzd85ceGklVoosvrSwA48tZV1XpJikpjPllr+3BPmDrqAu+NENVFPb8Ic/lUjoSpo9h6LIvrP4/FyUHHpueHVvuyWWfjxqnFQ0aNUr+81CKtII2WH7ek0FzI4vGLGdFSWs8JcTGzWhXKrEq16U0FpWW8vWg/w9oEEJeeT7cIL1yNDoz4cDUAN3QN4b0bz1xx91y8uGAPP204Zvu9Q4gHf0zqyx87Unh8zg7b9a0C3DiYXjnHe+sLw/ApD/jXH87k1m82nvO+7HttBM4GvToPe8ECNZjbWV6szcUFHnpInRZTj1ZeyXnJzNw1kxk7ZnDw5EG721p6t6R/WH8GhA+gf1h/Wni1sGtRdevXG4n0c2HZk4Pq9TyKzcXklOSQV5pHXmke+aZ88krzMFlMeBg98HT0xNPRk9fnHyY9No52J44Tk3aY3om7bHOkq9rvF8HSlj3JveY6XvhfZetERVEoLiu2bafAVECBqYAfNxzgj11HUSjGSilgRYMe0OHt7MhLozug1+pxcnDCw+iBu9EdD0f1p5vBDUd9DRWoDx6E//1PPS4V+vSBu+5S58KfJpvgVIqiYLaaKSkroaSshCJzEan5qSTlJZGYm0h8djzxOfEk5SWRVZxFVnEWJWVVRnMVLRr0aHDGSeeOucwJreKKVnFBi7N6GXeujenIg/16EeUdhZdT7VMJzqen5u7kt/ITWbUJ9Xbi9l7htpNrAH8+3JcOIZ5n3sDixWrnkKTywPjBB2HqVCiPkfJL81mXtI6VCStZm7iWLSlbKLVUb/3X3LM5HQI62JY2vm1o7tUcZ4dLt/VaY6hrHCpBdQPKKzHT4RW1bP2B10eetpdhU3fjF+ttBRnqElQvP5DOvG3HefO6GDycLs1WCuLSEvPyv7ZWKwlTR/HZysO8s/ggozoE8emtXc7uQbduVSuuajSwYwd06FDrqpP+nsRnWz6jR7MebLh7g6RbCXGZufKjNexPzePL27syol3jVzJetDuVh8pbfP32QG+6RXijKArTlsQxffnhGu9zS49QXr66HX/tTOHp33bZ3Ta8bQCR/q4oCnyxqvp88dpUZP/YKAr89ZcaXG/dql5nMKhze0eNUtORIyLq9NiKorDx+EZm757NqmOr2JW+CwX7r7lBrkH0Du1NhEcEWfnO/LE9nXAfV27pGUixuZjismJKykoos5ZRZi3DbDFjtpYvFjMnik5w6OQhUgtS6/ycAYxl4FmiLm6loHFyoszVlXQcyNYaKNNqAAVvFwM+rnoKTYW2QNqiNHy3FJ1Gh6vBFTejG24GN1wNrmg0GqyKFUteLtYT6Vjz8rBowKoBixa0Rkf0zq7o3TzQu7qj1xuwKBZKykooNhfbAuiKv6H11LZfjUiDhq7BXRkROYKRLUfSs1lPHHTn//vi6U4+7X11BO1eVjMLvrurG0NaB/DqX3tZcSCDBwdFMq77GVpR5eWpGQwV2W4tWsC338KgQeSW5LLgwALm7J3DkqNLKLPaV7X3cfKhT2gfdQQ6tDddgro0Sou6y1Fd41BJ/25AVecJmyxWCapPo+qZ/Br7aJ5i4owttvtNu6lTY+6aEAAYHXS2oLqwtIx3FqujHy3rW0CkgqLA00+rl8ePP21AfSDzAF9t+wqAd4a9IwG1EJehX+/vxfbEHPqfa/ucOurb0hc3Rz1GvY7OYeqInkaj4c4+EbUG1bM3JTF7U81porf2DGNQK38UReFwRoFdRXGA1oFuxDTzYO7WZJp5OuHu5MD+1DxbVW0bjQauuQauvlqtSv3aa7Bpkzoat3ixmhbevr3aX3nwYLVntqdnjfuk0WjoFdLL1ikhpySH9UnrWXNsDasTV7P5+GZSC1KZt39e5Z0MkJ0PO5bW4Y94Cq1Gi5vBTR39dXDFPd+EQ2o6eeYCchwhxxHyjKBooFQP6a7qoiouX+ylF6tLteeGxi4AdjW4osMJTyc33I2uOOj0mK1m4tJyOHQiFwULUEZ0oJEy1AA9tySXfJOaiWBRLOSW5tY4hxYAp/LFTom6FGZCYfW7nI6j3pEAlwBC3EOxmL2JCYiiR1hrwjzC8HX2xdvJG3ejO4qisC0xkwkzNoKmDCuFWDWFWCko/1lIuxA9cSfSKTBnYtFkUKbNwKLJYkvKFrakbOHNNW/ibnRnaPOhjIgcwYiWI4jwjKjfDp+lKfMruwEsnTyQD5bE8ffuVKZc2RoXo55+LX1Jyi6iT6T6un/56nb2J5lqoijw++9qQJ2YqL5mHn2Ugpen8Ffycub8ci3/HP4Hk8Vku0tzz+YMihjEgPAB9A3tS0vvlvJdopFJUN2AjHotLgYdhSYLGXmll2xz+vOh6gmIYrMFF2Pd/hVPNy9FiIbkZKj8H/1o2SHb5bOpBAvA33+rfWCNRnUOYS1Ky0oZP288ZdYyRkePZmDEwLPbnhDioubm6MCA6PNXK8HDyYH/nhiAg05rNz3Nx8VAlL8rhzIKALWdz8/39OLzVUd4/7+DWKsM9N7RO5wHB0USf6KQPi3VoECj0fDZ+C4cTMunXbA72UUmvJwNWBU1Hb53pA8Dov3YkpDNAzO3klVYPQ21/IHUkemrrlIrhi9cqC5r11ZWDv/wQ7XtU+fOaoBdEWS71nyy09PRk6uiruKqqKsANWV70/FN7EjbQVJeEisPH2Z/ajbhPk50jwjASe+Ek94JR70jBp0BvVaPXqvHQeeAg9YBB50Dno6eRHlHEekdiZejFxpFgR9+gClT1HZiADqdehJg7Fiyu3Rn8N/x6AylfHBzFGiLyCvNQ4MGjUaDBg1ajbbaZVeDK+5Gd9vi7OBc53mt05bE8XH555ZHgTPLnhyIQ/n3LqtipdBUSL4pnwJTAfml+bbLiqKg0+rQarToNDrb/GadVoc2PQNl2zbKtm2hbMdWyrKzMOtAZwXHMnVxcnLDsV1HnDp2xbFzD5x69sXRJwCjzmgL6Gz7luXIZ1cPRl9D4dqvV8WhxwdbkkF5d6iRbQPJLynjmzu74eigIyWnmD5TlwNQxkmev97M6sSlLDmyhJPFJ5l/YD7zD6it3aJ9ounZrCfhHuFEeEYQ7hlOuEc4ga6BtlH6c2G2WDmYls+xk2rNATdHPS39Xfn4ls7cO6CFrRbLT3f3wKpQtymiiqIWInvxRYiNBaC4ZTj/vH03vyi7WfhZc4rLKs/AtPFtw83tb2Zcu3G08m11Ts9H1J8E1Q1Io9EQ4uXMwfR8jucUX9Sl/i+0qm+i8ZmFdj02T6eiqIg4e4qiMGXeborNFqbd1Enm/tfCsUoxvR2JObbLQR5n0aPabK4cpX78cQivuRBJoamQG+bewLbUbfg4+fDFqC/qvy0hhKhFkEf1doAajYa/HunH3pQ8vlx1hHsHtECr1TBpcEtu7h7KDV/EklVo4q+H+xFW3i7s1Mcx6LXEhKif4xVzsLVo0OtgbBe1OnNFka2KytW10mjUytNt2qjvmydPqv2VV6xQl7g4NU1861a1erijozrSff/9aoGv0/RadnJwYmDEQNvJynvTtpBpTueeti2ZPPwsgpBdu9Q54OvK2yWFhqoj6xMm2AqueQEbO3VAg+a8tRN9YlgUQ1r7c+vXG0jMKmLWhmPc3jsCnVYN2t2MbnWukG4TDvS4Qb2sKHD0qJpRsGkTbNyo9iYvzYe4tTB/rbqeg4Oavj9xolpAy2Dg9/K5xqm5JayKO8HQNtV7HOdV6dndr6Uvaw9ncnff5rww2r5oWrCnE9/d1Y2JM7agx4dgh07Mvv5uLFYL21K38e+Rf/n3yL/EJsUSdzKOuJNxNT41R70jwW7BhLqHEuYRZre08GpBc8/mZ0wlf7u8nRmAs0HH9hevANTguVOop209jUaD7kxfu4qK1NZzn3+Osnkzh3xgfXcHFo2KYrEhify9L9lWjfSKtAXS7f3by2j0BSRBdQNr5uWkBtXZNeTuCBtrlVPfczYn1Tmorrjv2bS4ELArOYcJ32/mZPmXmtt6hdP9IquaebGoOn3DWqX0RMcqH4519vXX6siLr686mlGD+Ox4rp1zLbvSd+Hs4MzcG+fSzL1ZjesKIURDcnTQ0TXci6/u6GZ3vY+rkWWT1QD0XD936xxUn8rHRy3wOK68eNfx45UB9vLlkJCgFn/89Ve1//Xo0Woq+ZAhauGzGhSZyvgx9pgt+61i3+rs5El4+WW1WrbVqm7nlVfUatkO1YMv43nueKLRqIHcqJgg5m5N5pW/9mFR4O5+zTlyooC8YjMt/V1xNerVedRWhQU7jtM13Itwn5r/ZqdsACIj1eWWW9TrzGb1JMPGjbBhgzqyevgwzJ+vLkYj1i5dmFAWwLbg1uz3b860xa4Mae3Pkn3p/Bh7jNfGtCMjv5QDaWqK+vyH+tAp1JOsQpPtZM2phrQOoFu4F1uOZbMlIZsxnZqh0+ro3qw73Zt154UBL5BbksvKhJUcyDxAQk4Cx3KPkZCTQGJuIoXmQkrKSjiafZSj2Udr3IZOoyPCM4JWvq2I8Y+hQ0AHIr0i8XcJxM85gPf/O2JrnwYw/ZbO6uCR2QzHjqkZDHl5kJ8PmZlqX2mdTj0BpNFAWRnW0hKyclJJj9/D/vhN7HYrZltL2DAYMp0BzMA+MEGYRxg3tb2Jm9vfTJegLhJIXyQkqG5gzTzVs7fHc6q3nBCVyqoE1ceyilAU5bRvCka9ltIyteBFZmEp/m5nMVrYhO05nsunKw7zz540u+uX7k+XoLoWVVt4HD6hpkUufKRfnacq2OTmql++QP3S5WF/AslsMfPxxo95ZdUrFJgKCHAJYMHNC2xzAoUQ4kJqqJPYPuWBa15JGWaL1ZaOXG/NmsFtt6mLoqgjpN9+Cz/9pPa//vprdTEa1VTy229Xfxorg7Ip83bzx44U2+91SsM3mWD1anUE8eef1dFEgBtvhGnTIOTi65f86NAoWzu11xfuo8Rs4d1/K6uj927hw4S+Eczfftz2/eCJYdE8NiyqTo+/NyUXDRraBLmhcXCArl3V5aGH1BX27IHvv8f8w084nDyBNjaWe6rcv8DgxJqPW7MjLAYH/+Y8GLuFFHc/MKqBfTMvJzQajX1AXVKinkiJj7ctH8UdY8uhDFwWWrH85I/O1UU90eHqCi4ueLi4MDCnkOGFeTgVWiDXDXNuBNpCX0pK80i35JFCPomGYpLcFRI9NCS6Kxxzs3DE1UyR3sKR7CMcyT7CokOLqv0d3EsNeJqM+BQ5EIORpW8qrCwsUoPoKt93TTooMKhLoUGdc5/hoi6ZzmBxAdqXL1UYdUa6BXdjUMQgro6+mu7NukuLq4uQBNUNrJlXeVAtI9WnVWatrAi5Ou4EV328lh8mdMffvXqwrCgKpiq9v1NzSiSorqfX/trHpoSsatd/ueooXcK8zkvl2UtN1ZHqnCI1FS3Eq3rq5Bm9/bZ6ZrpVK7UFRhXLji7jkX8eYX/mfgD6hPZhzg1zCHG/+L6cCSHEufBwckCrUWOM7EJTjZ/3VVmsCgUlZXg4nybtVqOpDOQ++ABWrlQrif/9txp4VYySenurI9jDh6N0787CbUmgVd/j9782EidD+fu9xQLJyWpq85Ej9j8PHlSDpAodO6rB9JAh5/aHaUSh3s4sfKQfo6er6dhVA2qo7PVc1QdL4+jZwtuu33pNsgpNXPvpOswWBV9XA7FThpJdZEJXNQhu3x7ef59WDoMJy0qhS8oBOqccpH9OAsHJR3A1FTMgYTsDErbbPXaewZkTnv74xYapI/8Gg3qCOj5ePXFyimblCwB7a95fz1N+r/ivcgFalC81UYBUNzjkDfv8YHcA7PaHJA9IcQOzDvKMJvKMJhI9YHstj1NXnhonWrpHEBPRk46BnegV0ovOQZ0x6OqZTSHOOwmqG1jFl+5kCapPq8xi3+Jif2oeHyw9xNtjY6qtW2K2UrXxW2puCR1DG3sPLy+5VeYnATwzspWtmvX9P221/1IhAPuUb1DnDNa7nVtCglpYB+Ddd21pgRmFGTy86GHm7psLgK+zL1OHTmVC5wly9lkIcVnSajV4ORs4WWji2d938c2d3avV9CizWMktNuNs0PPG3/v4ZXMSs+7pecYAD1BHokeMUJfp09VU5JkzYdYsNRD78Uf48Uc0wH6tniTPQLyim+M0fgZkZ6tVlRMS1JTd2vj7q6nld9wB/furQf1FrlWgm+1kBsDQ1v60C3bH1VFv1yPZzahHp9OQU2Tm5q820KO5N69e0442QdVbCJWWWejy+hLb75kFJqKe/8f2+83dQ3nzuhh0Wg2lZRasaEjwbkaCdzPmtR9K7JQhmB20vPfhfLy2bqDdkZ10KM1Em5SEe2Eu7qYi3DMSICOh5ifl5gbNm1cuQUEsPJDJxuR82ga5cVNbX+KOpKIrLqKlMyzdEk+2GfIcXcgzupBvdKHQ4EiRgxOFBkdG9mrJrD0n0Tg58+nNHQl11UNpKZhMaEpLCTaZCC4tZaDJRGlRMa/M3Y5DkhmdxYxVW4CDp5ngUC1Wfy3pzhYyDGYUR0fbSHnF/4mD1sFWud3F4IKH0QN/F3/8XPzwd/HH19lXgudLmATVDawy/VuC6tOpmv5d4UBaXo3rFprsi5Ol5l68f9utx7I5nJF/5l6D55mLUQ2Y2zdz538j29CzhbctqAZo89Ji3rmhAzd1k7MVFUxl9v01A9yN9Zu3VFamFs4pLVWL54weDcDu9N2Mnj2axNxEtBotD3V7iNcGv4aXk1cD7r0QQlx8vFzUoHrFwRP8FJvA2sOZRAe4EebtTN+Wvrz6116W7s+wu8/EGZuZfktngj2diPJ3JSWnhFBvp9O/H2s06khyx44wdaqatv3vv7B8OWW792AoKSYyKxk2JFe/r8Gg9sWOjFT7AFf92bbtaQuhXYwcdFpWPT2YpOwiAt0daVGlLeTYLiE8Ons7RSYL39/VnV3Hc7nzu00AbIrP4sqP1jC2SzNeHNUWryrzzv/de/pOLL9sTmJomwCuaBtA4snK6ZAt/Fx4dEiUrdDdc8/dDNxsf+fCQkhKUuci5+WpJznMZnB2rgyivb2rndBQdqbw02x1nHhKNuCttqm6om0AS7xOv78rTwAB6mfwzesLeOO69nRr64VbDV18vllxmNmd1OJq397ZjQ1HT/LI0Cjp+CMkqG5oFenf6Xkl5zZn6DJXU1Bd9Y23qsJS+6D61b/2kVVo4smzqdTZyK7/fD2gplxV9CC8GGSXpy+/OKotPcvP+C97ciBD319lW+f7dQkSVFdhOiWbot5TDp5+Gv77D5yc4OOPQaPhz4N/Mn7eeApMBUR5R/Hrjb/SKbBTw+20EEJcxKq203zlr30AtiDaoNPaTfWqUGSycPcPW6pd//qYdtzeO+LMG9XpKttvAa/P38WSJVt5qJnCbeEGyMkBLy91rnZkJAQHq/e5jIR6OxNaQztIX1cjP99bWb9jYLQfa58dzPxtx3l/iVope9624xzJKOCPh/vZ1lt5UD1m/Vr68sLoNoz8cE21x/5mzVGCPBy5ozxIj2nmwV+P9Ku2XjUuLtC6tbrUw4h2gYxsF8jivfa1YyqK0XUL9yLY0wkfVwMPDookLbeEB2dusw2ChXo7kZRVzPGcYiZ8vxmDTsu0cR0Z3SEYs8XKP3vSOFlQakuhf+/GjgxtE1Bj9XLRNElQ3cD8XI3otRrKrAqZBaU1tq8QYKkyp9rbxUBWoYmThSamLYnjsaFRdilhhaWWavefvvzwRRdUF1QJ/vel5F1UQXVFtdWqFU4j/Vw5/OaV/Lkzhcm/7mR/ah5/70rlmd92cnf/Fky+IvpC7e5F4dSRan+3miuP1uibbyrTvn/8EUu7try64iVeX/06AEOaD2HujXPxdpIicUKIpqNqPZVTVQTU4T7O3Nk7gj0pubT0d7XLqqrqxT/20tzXlX5R9fusjU3IJsXdH6+ru0CHoHrdtykI8XLmkaFRBLg78trCfRSUlrEzOZebv4qlY4gnU65qw9EThQDc0iOM1oHuTL4immlL4vBzMzL73l4Mm7aKjfFZtrncAOO6N+5Je4NeywfjOuHx516OZhbw+rXteW7ebraVt8Ts1cKHp0ZUfm/0d3Nk3f/s58On5ZZw+7cbOZRRgMli5eGft/Pwz9vRaLCbhhjgbuS6ztKdQ9iTYdQGptFo8CwvqlFR3EhUVzGn+qe7e7D5+WG23r8fLztk62FYoch0afSmji//kAF44+/9fLT0ELnFZg6Wt4bIyCth4a4UlPJ35k3xWTzw09YGnypgsSp8vfooK8rPJFfMUYPqbUP0Oi1ju4TQLlidMzXp520Umix8vOwQv2xKbND9utSYyuxP5lT0Zz2jefMqK5+++irZo4Zy9eyrbQH1oz0eZfH4xRJQCyGanFPrqQBse/EKvKoUI3vuqjZM7NecaTd14sGBkbxydVs+HNeJdsHuDIj249Nbu9jWffnPPbbP1LqIS88nLr0AvVZDv5YXz4nvi9FN3UPZ8+oI27TGDUez+HL1Udq8uJgdSTmAms4NMLFfc/7v+hj+fXwALf1dGdyqspp6myB3fnugN7f1Cm/0fXYy6Pi/Gzow94E+tA50574BleXHRrY/c0HWQA9H/nmsP7tfGY67Y+W446n/YkPbBFSrByCEjFQ3Ag8nBzILTGQX1bMXYxNSkf6t12rRaTV8Nr4Lt3y9gRKzlblbk7ipyhnN9LxSAFyNervR4MZWZCpjw9GTDIz2r9Ob59HMArvfP1gax9rDJ9ickM3VHYP5a6favsPhdi0j2gVy/09byC4ys+5IJrPv7UW7YPdz7jVotSp8s+Yob/+jFh959Zp2vPynWgpTq6HWQlvPj2rDrV9vxLsol/DsVEJz00k7thruGa7OX2rWzK4dSVNwahpiZJV5aLWaORPuugssFpTbxrP69gFM/LobR7OP4qR34qurv+K2Drc1zg4LIcRF7tT31V4tvPF2MTCmUzNmrE/AoNMyuJW/7XaNRsNdfZsDcG2VkcH+0cPp8toSjpwo5MfYY9zYLQQNGpbuTyevxMw1HYOrzYdNyipi+AerARjUyv/0VcWFTbcIL47vqDz5X2xWTzhrNdDcVw2qXY16u1oyb4/twNR/9nNLjzDblLMLYUS7QN64tj2Rfq60b+Zx5jugDja46bT8+kBvpi87zN+7U+kf5csLo9ryxt/7OJiWz4MDIxt5z8WlSILqRuDlbAAKyZWR6lqVlX+wOujUILJzmBeLHu3PkPdXsTM5F1OZFYNeTaQ4Ut4j+Mr2gXi5GPhq9dHzso93fb+ZTfFZvH9jR67veuYWRzVVfN+ckA1gC6hBnd8zuJW/bZ5zfkkZo6ev5e2xMdzS4/QFzrYnZtMq0A1nQ+VLt8xi5dctyeSXmEk4WcTsKiPMFQE1wLjuYeirzvHPyIClS2HTJnrt2s22jVvxLsq13+Av71Re9veH8HA1yG7RonJp0waCgi6JKqj1cWr6d+AZ2r/w5Zfw4IMoisI/Dw7jra7xrPtRncMX4RnB/HHzZf60EKJJu6lbKNOWxNElzJO7+jand3nA9czIVhj1Wga28rN99p+Ou6MDEb4uHM4o4OU/9/Lyn3vtUnTXHzlpN6INsGx/ZbGqZ0ZeXNPHLmb3D4jkn91p1U6IvDqmvV3ryaoCPRz58ObO52P3Tkuj0Zz1CHnrQHc+Hd+FKdlFBLg74qDT8tPdPRt4D8XlRILqRlCR/p1dQ1D93940diTl8NTwVmibcOpIxUh11RHg5r4ueDk7kF2kpkzHhKhnFSsKYkT6u3Jz91BbUH3jF+t567oYogLcGnz/8krMbIpX+zo/OXcnw9sF1FgFsqqKquSPDGmJg07LtPIiH6DOO6oIdn/bmszCXSnV7v/ZysNcFRNUbTT5ZEEpHy49RGFpGfO2H2dUhyDbl4XDGQVMmLGJpKzTp5B39YA3Isrgq69g40Z12VsZcGuBimRkJSSE7TpP8rRGemnzcExOVCtYZ2Soy+bN1Tfg4aFWRW3XTv1ZsYSEXLLBdkVQ3czTCSeDjh7NT5OuPW0aBVOe5LeO8OFoX3bql0IyGHQGJnSawJtD3sTH+cKdrRdCiIvBAwMjiQ5wo1cLbzydK6cjORv0TLmqTb0ey8Vo/xW2aoru37tSeetas91o9PbylOVHh0YR3QjfGy5XbYPdWfbkQLIKTYz5dB0Au14Z3mSqXYd41XHql2jyJKhuBBUfFDnF9unfiqJw309bAXWOydUdg8/7vl0sLOVBddXq6BqNhhZ+rmw9lk1SdhExIR7sSMqxFZnoFOppdwZ7c0I2V3ywmt8f7IOzQVdjL8WzlZBZaPf7lHm7+eSUs96nSs0pASDIw4lbe4YR4G5kzaFMXrmmHb6uRjqEeDBl3m5A7b0NcG2nYF4d056B764gKauYZ3/bxRe3dwVg+YF07v1xq+1vVeHvXalE+sVxR+9w7v5hc2VArSj4FOUSnZnIXV5FtMtJxuXwQTwSDqM9cQKeq77PSqeOxA3uyPoIHbGu2ewwJ5FfVkhOvhP5ha4MiupG3+ZheFgc8Mg3YziZDenlwXV6Or7HMojck0JIbi7a2FiIjbXfgJubOpLdsqU6mh0YCGFhasAdHa22LrlIVQTVs+7pSZi3c40nwRSrlQ0vTeDb3T8y50koMAJk4uLgwoPdHuSJ3k8Q7NZ0X+dCCFGVQa+t09zWuhjXLZSd5YEyQIiXE6ueHsyoj9dwIC2fhbtTGN9THaVUFIXN5SfKu0dI+8L6qqge/uPEHni7GJpMQC1EfUhQ3Qi8qhQq25Wcw53fbeLZka0ZVGWe0NZj2bQOdGuUUdZLgdlSfaQa1A/FrceySc5W22ttO6amT7cLdqdXCx9b2nhVFW2sDr4xEqO+YdpgZBaU2v2+cFcq+SWbeGxYFF3Cav5Arig4FuSppgmP6x5mN8fo1BFofzcjz13VBg8nB36Y0IPrP1/P4r1p7E7OpV2wOxNnVG8horeUEZKbzrZvtpM27QRj807QsjSLfppcLHv34V1cc69vQG0Z0qULlp7dWd/Wjd+c4vk94R+O5/8I2aiL3cbg7/gV/B1fw2O5ly9RwDBw1jkSqvPGq1SDd4EFt+winLPycTLl41S2CafUTRiTQauAzqr+1Gq0aP380AYEoQ0KQhfUDG1wMxwCgzEanDHoDBh1Rox6Y60/T11Hp9WRX2Imv6SMQxkFbD2WzeNDo84qK6SofN6YQa+tdn+TxcTMnT8xbf4z7HXIgvLzLS29WzKx00Tu63qfjEwLIUQjuqVHKINa+XHTl7GUlln557H+6LQaru8SwpuL9vPd2nhu6hZKmUVhT0ouKbklGHRauoVLkcizNSDa78wrCdFESVDdCCoqJe5PzeOfPalkF5n5X/kIZYUZ6xOYsT6B92/syMj2gRw5UUC7YI8mU02woqWW/pTnW/G3q5iffChDrZw9pLV6QkKv06LVQA1trtmemEOvBiqIkVlQvcjcqrgT7Dmey4bnhmJVFIzFRRSvWMXun/8kIrIZpfkR4OxLWA29IMnMZFjWIZ4xxdEywI3IHjF4dO2Ar7sjFBXR0ZLDPT7FrN+VyJvP7MLJXMo1pUU0y8sgNCedvto8grNS0CcnobFUbzFWwarRYIlojkP7dnbp2OaoSFZlbmH+/vnMOzCDtMOVfRyNOiPdm3WnT0gfujfrjpejF/8e2MfX67djIZuBrZ3JN+WyMyUFo14t2KXXaVAUhfTCdI5mH6XIUsJBSwpoALfy5fTTwwErkF6+7IBU1OUc6DQ6FMUBFD0aHAAtb2834unkjI+TD77OvnZLTdd5OXmxdN8JWyqhQa+ltKyUI9lH2JG2g+2p25m9ZzbH84+DHpzMcJN7b+4e93/0C+t3zsXmhBBCnJlGoyHY04mFj/TDYlVsU7TG9QjlkxWHOXKikKjn/7G7z4BoX5wMl1cPaiHExUGC6kbQv/xM3sajWdUKO5zq7X8OMH35IRJOFnFVTCCfje9a67o7k3IoLC2jVwsftiZmU1haZjf6fSmpaKthVziLyrkr8eXp13HpapGylv6VlZcddFpKy6r/XX/bmnzGoDohs5BAD8dai2tUOFkeVLs76rl/YCSb4rNYFXcCY2oyWydNweGvP+mcfggni4Ue5fdZAWQ7e+D5RxA4O6vzkE0mOHkSsrIwAA9V3Yizs5oefeIEWK3877R7VMnq5MRxzwAsIWGEdm6NLiwMIiKgbVu0rVqhdVb/hsfzjrP06FKWHP2ARUsXkV1SORTtYfRgTOsx3NDmBq6IvAJHvX0RrsERQ9h+YDWHMgrwKPElITkHjxK18vrxHNjz6ghcy+ezmS1mjmYfJbUglezibLJLsskvzae4rJhiczHFZcUUmYswWUxYFattsRTkYc3JxpqbgzU3B0teLpb8PMxYKNWBSQeleiit+OlsoNSox2TQqddZTZRa7DMKLIoFsKjBfbnMYnU5zOE6/oVBhxsaoxsGvYbm03MpMBVUWycoHybHwr0TP8Hj7kl1fmwhhBANp+rcbFCLmI1oF8CvW+zbc0b4ODP1+g7nc9eEEE2IBNWNoIWvS63tnzqFenJrzzByiky8tegAmQWlVHRiWrovgxKzpcaAL6fIxLivYikxW2kd6MaB8t7HCx/p1yCtmM63ypZa9vvdMVQtTrbmUCb931lumy9ctahITQE1wPztx3nj2tqrUa44kMGEGZu5vVc4r1/b/rT7VzGn+pYeYUwa2IJJZfGse/8teu+LRUvlMHmiRwCbQtsTlpNKt+T9eBXlwoHcmh80LEydU2yxwL59UFSkLgCOjiguLpyw6Cg2OOLu40GpozPerSIxRLdUK263bAmRkWgDAwmt4XjnluSy6tjS8kB6CQcyD9jd7ufsx5hWY7iuzXUMazEMg672+cxarYbrujTjncUHWXs4s9rt7V/+l7XPDibEyxkHnQOtfFvRyrcBqqlarXDsGOzZA9u2qUXRNm9W53BjKl/KdepE4qARPGkJx6lTG967qT0fLN3LjxsPA2YUzChYAYUXRkcS4mMlvSCDtUfj+WPXQSyaPPT6AtqGaMgsyiSzKNN24sFCPmjzKbNWbtLFwYWOvu3pdKyEPn/t5IZ9YPzsS7j7vnN/3kIIIRrMmE7NbEF1oLsjt/cO54auIfi6Nq3WkEKI80eC6kag0WjwdHaoFlT/en9vuwrCy/ZnsLG8cAao/Rt3JNWcwvzI7O224lYVATXA6Olr6RjiwY8Te15SPRcrim/pdfbBYdsgd3xdjWQWlNoCaq0GWvi51OkxD2cU1NiL8I8dx3nslx0A/LThmF1QbbUqtjmzFqvCvpQ85mxJQmu10DP2X3jqeti/n77l628Ibc9fbQawskU3jntUZgr8r28w94Vq0eZkQ3Gx2tfZYFBHo6Oi1JHpCmYzxMerQXVAAAQFoQH8FAWLVak2gl+TQlMhscmxrEpYxbL4ZWw6vql8pFalQUO34G4MazGMkS1H0je0Lzpt3dPeBkb78d6/B22p9q+PaceLf1RWDB89fS1/P9rflrJfm/2peew5noufm5FjJ4sY1jag9vtoteoJhObN4eqr1esUBZKT1eB6yxZYswbWr4cdOwjbsYO5QLxXENr1Y0jPD8IvMIocJ/uide/+BVH+7hzK0APBeFUcTTOsuutKW8G8MmsZK+KOcOcPy/F2K+Xz8V0JdAnALy4Z9zkL0L4/C7LKX7PvvQf3SUAthBAXmz6RPozt3Iy9KXnMub9XtdFsIYRoaBpFUWqYnXpxycvLw8PDg9zcXNzdG67Cc2O6evpadh+vHLH8+JbOXHNKte+VBzO463v79kSB7o68NqYdw9up1TH/2pnCI7O3n3F7V8UEMu2mTmdMa75YNJ/yN4oCm54fir+bferx2M/W2Sp+gzryv/ypQbbfI/73t+3y7leGsz0xh7cW7bedbHA26Hj/xo5cGRPE+iOZvPn3fvam2BfwenhwS+4f2IK3Fh3g710pzL6vF5F+rjw0axsbdh3j+j3LuGvrX0RmHVfv4ObG+v5X82Jwf474hALwwqg2uBr1+LkZCfN2btSic4qikJibyMbjG9mYvJH1yevZkrKFMqv9iZso7yiGtRjGsBbDGBQxCG+ncyvIkl1oQq/TkJ5XakvBf/a3XczZkgSAj4uBf58YUOvZ/zKLlR5vLSOrsHKEOcLHmcWPD6jX/6rFqqDVUJmRceIER7+bzdGvZ9I/YTtGi/3f4YSXP45tWqOLjuKjBAvH3f3JcPXGrNVj1unp1NyX2KR8zDo9Pz/Uj1lbU3Fzd+LWvpG8+d8h/tqVyhUeZUx3OAo//AAHD1Y+eHQ0vPkm3HBDnfdfCCGEEEJceuoah8pIdSPxcqk8K+rtYqgWUAP0j6qsonhz91D+2JFCWl4J9/20lWk3dWRsl5BqAfU713fgmd93AeDmqKdXCx+W7Etn0e40NhxdzpInBuBzrulN2dnw2GMwdSoEN3w7ILPFaisCZdRVD6yq9p7sEeHN+F61V7xyc3RgQLQfyw9k2ILqIpOFD5bGodHA5F93UmSqXtjrkxWH+WRF5Rzb0R+tZlDqPq7csZSPDq7DzVTepsrLC558Eh55BLc8heNfrsfLQceaZ4fY5hQ3pNKyUo5mHyXuZBxxJ+M4lHWIuJNx7M/cT0ZhRrX1Q91DGRgxkEHhgxjWYhjhnuENuj8V/8dVe3S/PTaGUG8nvl0bz8lCE9+vi6elvyt/7Uwl1MuJR4ZG2YLsA2n5toDaoNdiKrOScLKI1i8upmOoJx2aeZBdZOLGbqEMrKWqaH6JmVEfryUxq4iPbu7E8LaBOPr6cr9DRw7dEIlLaRH9EnYw5MhmuifvpUV2Cn7ZGbA+A9avZsqZnuRX8GyVX98tX+w4OcG118L48TBiBOjlrVMIIYQQQqjkm2Ej8aqSiu1ZS1q2Tqth+i2dWbwnjRdHt+W2XuGMnr4WgFkbE9mcUJkabtBrWf30YPzdjPyx8zi7knJ578aODG3tz8B3V3I8p5isQhMLdqRwd7/m57bzEyfCggUQFwcrV4Kj45nuUS9Vg9yaqnBOubING46u5fZeEbx0ddtaH6dqpfSHh7QkyMMRX1cjT87dSVx6AQ/M3Ga3vqODFj83Y2VfZyDqxDGu27eCMXtX0Sz/hO16S2RLdI8/BnfeqaZvAzHusOKpQWjQnFNAbbFaOJZ7jEMnD1ULno/lHsOq1DxnXK/V0yGgAz2b9aRXSC8GhA8gwjPirPfjbGm1Gh4eEkWYjwuPzt7OpyuO2N3+Q+wxXhrdlghfZ1YdVP+mA6L9+HFiD75efZQ3F+0H1MJ7FT1GF+5K5ebuobw9NsY2Gr09MZvZmxLxdjGSmKXOPa9I4R/TKZhDGQU4Omh5YWxPpsxzJn7AcFqO7QAeGnXO+uHDcPgwJ3ftpzQ+gaCSPDRms5p6bzaTk1uI3mrBwVKG3mpBd8rfvcxgRN+1C9x7rzoq7dY0298JIYQQQojTk/TvRvLigj38tOEYAB1DPfljUt8z3EMVn1nI4PdW2l3Xq4U3M+/uWes829TcYt77N47ftyXjbNCx+LEBhPnU0Napro4cge7d1RHrnj3hu+/U9kwNJD2vhJ5vLUOn1XD4zStrLLJWWFqGo4OuxhZjFenfrkY9e14dUe32p+bu5LetaoGStiGl6Lx/5P4uj3Fl1EB0Oi3Ficc5+c0MdLNmEXR0v+1+eUYXjLeMwzjxLujbV53fW09mi5nUglSS85JrXVLyU+zmPp/KzeBGtE80UT5RRHtH2y7H+Mfg5HD6+cvnU4nZwvWfr6+WWl+TF0e35e5+zTFbrMzZnMSi3amsP3ISACcHHcXlPaEnXxHNzd1DOXyigPt/3Ep+DcX+qhrUyo8ZE3qQmltMoLtjvQr2VZ1GEB3gSo8wT3bGn+B/wyIpKS2jT6fmODVCNoIQQgghhLg0SPr3BebvVpmCvTs5p873C/d2xkGnwVzecmps52ZMG9fptPcJ8nDijWvbczSzgO2JOXy4NO6M9zmtyEj4/Xc13XXjRoiJUYtG3X8/DB8ONaRs10dx+Ui1k4Ou1iDIpQ7BjKNDzUHvlCtbU2Qqw9Wox+Q6g482/sHCQ3/gpnUitECHIbcAByvoB4PDQNB6+JDn4Yd7aCierlk4pE3HYcEX6LV6HLQOaDVaW1uo2hazxYzZaqbQVIjCmc9TGXVGWnq3VANm7yiifSqD5wCXgEuimrujg46v7+jGVR+vIcDNkfmT+lBksjD8g9V2c6hdjXrb9AcHnZbbeoXTKtCN9UdiGdzKj/dv6sTAd1aQX1rGtCVxTFsSV21bA6P9GNTKjw4hnny24jDLDmSg02q4o7ea7h7kUf+TDVPHxjBtSRzf3dW9xuJ2QgghhBBC1IWMVDeSpKwi+r+zAoBJgyN5ekTrOt835uV/bSN0h9+8sk6VoAG2JGRxwxexuDvq2fbiFbXeb8XBDII8HGkdeIa/ZXIyTJoEf/5ZeV1wsJoO+9BD4H92PbL3p+Zx5Udr8HU1suWFYfW+f8UIY4iXE2ufHVLzSqWlsGULB1bP4/3jc/nJK4nS83QKyUHrQDP3ZoS4h6iLW0jlZfcQmrk3I8g1qF6VuC9muUVmHPQanA3qHzgtt4R/9qQyqJU//+xJZWC0H+2Cqwetx04WEuThhEGvRVEUpi4+wPdrE6r1dv/iti6MaBdod6JhX0oens4OBJ+h8rgQQgghhBBnq65xqATVjUhRFHYfzyU6wK1elY6/WXOUD5bE8dHNnRnWNqDO97NYFbq9sYTsIjMf3dyJMZ2aUVBaRnJ2kS2A3nM81zZv+8hbV9WYXl3N/v3wxRcwaxacVFN2MRrhjjtg8mRoXfcTBgBbj2Vz/efrCfN2ZvUzg+t1X6gMqqP8XVkyeaB6ZW4uxMaq7ZbWrIFNm9TAulypDg63DSRtzBDKhg3BHBRAmbUMs8Ws/rSa7S5X3Ga2mrEqVpz0Tjg7ONe4ODk4YdAZcNA64GJwwd/FH62m/qnjAkxlVrIKTXy5+gh5xWVMuaq19BUVQgghhBAXhATVlziLValbwHuKD5bE8dGyQzg6aPnz4X5M/nUHe47n4WrUs/ypgczbdpyp/xwA4Os7unFFPYJ2Skth/nyYNk3tGQyg0cB118Gzz0KPHnV6mHWHMxn/zUZaBbjx7xMD6vsUmTRjI3tidzGtWQFdE3arAfS+fXDqv7KfH/TvD/36qT+7dDmredJCCCGEEEKIpkeC6iaqtMzC+K83suVYdrXbQrycKDFbyCyonO/6zg0duLFrSP3m8CoKrFsH775rnxres6eaFn7TTaetGL50Xzr3/LilXgXcAHUk+rPPUBYsQFNQUP32yEj7IDoqSg36hRBCCCGEEKKeJKhuwvYcz2Xs5+sxldXcmulU7YLdmTGhB35uZ5Fmu28f/N//wezZaqsiAB8ftS3XPfdAdLRt1dVxJ9BrNZwsNPHI7O30auHNL/f1rvlxFQXy8yEpCdauhTlzYMWKytsdHaFDBxgyBPr0UauVBwbWf/+FEEIIIYQQogYSVDdx8ZmFbE7Iomu4F5F+rrYiZgAPDopk+f4MDqbn29a/p19zXhh9Dm2z0tPh22/hyy8hMbHy+g4d4IYbKOjTn67/ZFOqN/DkFdG8vySOIa39+e6u7nD0qDoPevNm2L1bbemVkVEZpFfQ69V53HffDb16SSq3EEIIIYQQotFIUC2q2Xj0JLuP53JH7whbxeWFu1J5ZPZ2mnk6sfbZwefeysligUWL1MJm//0HZZV9hkt1evYEtGRXUBR7AyIZpstl5MF1EFe9hZKNm5samI8aBbfeCuHh57Z/QgghhBBCCFEHElSLOikxW2j38r9YrAqdQj356vau+LvXPh+6XrKy4I8/YOFCSleuxpiVWfN6er06H7tHD+jcWU0ZDw5W08idnRtmX4QQQgghhBCiHiSoFnXW5fUlZBVWFi/r2dybn+/tdVbVx2vz+YrD/PLLCrocP0D79CO0Sz+C3t2Nbi89DiNHghxXIYQQQgghxEWkrnGo/jzuk7hIPTW8Fc/N3237fWN8FkdPFBAV4NZg2zh0ooBjXsGUNY9kfk4xAIse7Q/BEkwLIYQQQgghLl0SVAtu7RnG1R2D2Hosm+fn7+F4TjG7knMbNKjenJAFwJvXtaddsAe+roZzn78thBBCCCGEEBeYlE8WALg5OjColT9XtlfbUr38516en7+buCoVws9WWm4JSVnFaDXQNdwLPzejBNRCCCGEEEKIy4IE1cLOfQNb0DHEg4LSMmZtTGT09LXEZxae9eOVmC08NGsrAG2D3XFzdGioXRVCCCGEEEKIC06CamHH382ReQ/15bPxXTDotJjKrHy+8jCgBsgnC0qr3afMYmXrsWxbsbMT+aX8uiWJ3GIzT8zZwbbEHAC6R3ift+chhBBCCCGEEOeDzKkW1ei0Gq6KCcLX1chNX8ayaHca9w+MZOKMzSRnF3N3v+YY9VrWHc7k+q4hfL7yCMnZxYR5O/Pk8Ghe/WsfWYUmnvltl+0xB0T7cf+AyAv4rIQQQgghhBCi4UlLLVErq1VhyPsrSThZdNaPYdBpeWxYFJMGt2zAPRNCCCGEEEKIxlXXOFTSv0WttFoNT1wRbfvdx8XAo0Oj0FfpX63TavB1NfL6mHa0b1b5j/bejR1Z/fRgdr0yXAJqIYQQQgghxGVLRqrFGSVlFZFwspAOIZ54ODmQlluCVVEI9nSisLQMnVaDo4MOUEe3M/JLCfRwvMB7LYQQQgghhBBnr65xqMypFmcU6u1MqLez7feqAbOL0f5fSKvVSEAthBBCCCGEaDIk/VsIIYQQQgghhDhLElQLIYQQQgghhBBn6ayC6k8//ZSIiAgcHR3p2bMnmzZtOu36c+fOpXXr1jg6OhITE8OiRYvOameFEEIIIYQQQoiLSb2D6jlz5jB58mRefvlltm3bRseOHRkxYgQZGRk1rr9+/XpuueUW7r77brZv3861117Ltddey549e85554UQQgghhBBCiAup3tW/e/bsSffu3fnkk08AsFqthIaG8sgjj/C///2v2vrjxo2jsLCQhQsX2q7r1asXnTp14osvvqjTNqX6txBCCCGEEEKI86lR+lSbTCa2bt3KsGHDKh9Aq2XYsGHExsbWeJ/Y2Fi79QFGjBhR6/oApaWl5OXl2S1CCCGEEEIIIcTFpl5BdWZmJhaLhYCAALvrAwICSEtLq/E+aWlp9Vof4O2338bDw8O2hIaG1mc3hRBCCCGEEEKI8+KirP49ZcoUcnNzbUtSUtKF3iUhhBBCCCGEEKIafX1W9vX1RafTkZ6ebnd9eno6gYGBNd4nMDCwXusDGI1GjEZjfXZNCCGEEEIIIYQ47+o1Um0wGOjatSvLli2zXWe1Wlm2bBm9e/eu8T69e/e2Wx9gyZIlta4vhBBCCCGEEEJcKuo1Ug0wefJk7rzzTrp160aPHj348MMPKSwsZMKECQDccccdNGvWjLfffhuAxx57jIEDB/L+++8zatQofvnlF7Zs2cJXX33VsM9ECCGEEEIIIYQ4z+odVI8bN44TJ07w0ksvkZaWRqdOnVi8eLGtGFliYiJabeUAeJ8+ffj555954YUXeO6554iKimLBggW0b9++4Z6FEEIIIYQQQghxAdS7T/WFIH2qhRBCCCGEEEKcT43Sp1oIIYQQQgghhBCVJKgWQgghhBBCCCHOkgTVQgghhBBCCCHEWZKgWgghhBBCCCGEOEv1rv59IVTUUsvLy7vAeyKEEEIIIYQQoimoiD/PVNv7kgiq8/PzAQgNDb3AeyKEEEIIIYQQoinJz8/Hw8Oj1tsviZZaVquVlJQU3Nzc0Gg0F3p3apWXl0doaChJSUnS+qsJkuPfdMmxb9rk+DdtcvybLjn2TZsc/6ZBURTy8/MJDg5Gq6195vQlMVKt1WoJCQm50LtRZ+7u7vLiasLk+DddcuybNjn+TZsc/6ZLjn3TJsf/8ne6EeoKUqhMCCGEEEIIIYQ4SxJUCyGEEEIIIYQQZ0mC6gZkNBp5+eWXMRqNF3pXxAUgx7/pkmPftMnxb9rk+DddcuybNjn+oqpLolCZEEIIIYQQQghxMZKRaiGEEEIIIYQQ4ixJUC2EEEIIIYQQQpwlCaqFEEIIIYQQQoizJEG1EEIIIYQQQghxliSoFkIIIYQQQgghzpIE1Q3k008/JSIiAkdHR3r27MmmTZsu9C6JBvD222/TvXt33Nzc8Pf359prr+XgwYN26wwaNAiNRmO3PPDAA3brJCYmMmrUKJydnfH39+fpp5+mrKzsfD4VUU+vvPJKtePaunVr2+0lJSVMmjQJHx8fXF1duf7660lPT7d7DDnul66IiIhqx1+j0TBp0iRAXveXm9WrV3P11VcTHByMRqNhwYIFdrcrisJLL71EUFAQTk5ODBs2jEOHDtmtk5WVxfjx43F3d8fT05O7776bgoICu3V27dpF//79cXR0JDQ0lHfeeaexn5o4g9Mde7PZzLPPPktMTAwuLi4EBwdzxx13kJKSYvcYNb1fTJ061W4dOfYXpzO99u+6665qx3bkyJF268hrX4AE1Q1izpw5TJ48mZdffplt27bRsWNHRowYQUZGxoXeNXGOVq1axaRJk9iwYQNLlizBbDYzfPhwCgsL7da79957SU1NtS1V3ywtFgujRo3CZDKxfv16fvjhB2bMmMFLL710vp+OqKd27drZHde1a9fabnviiSf466+/mDt3LqtWrSIlJYWxY8fabpfjfmnbvHmz3bFfsmQJADfeeKNtHXndXz4KCwvp2LEjn376aY23v/POO3z88cd88cUXbNy4ERcXF0aMGEFJSYltnfHjx7N3716WLFnCwoULWb16Nffdd5/t9ry8PIYPH054eDhbt27l3Xff5ZVXXuGrr75q9Ocnane6Y19UVMS2bdt48cUX2bZtG/PmzePgwYNcc8011dZ97bXX7N4PHnnkEdttcuwvXmd67QOMHDnS7tjOnj3b7nZ57QsAFHHOevTooUyaNMn2u8ViUYKDg5W33377Au6VaAwZGRkKoKxatcp23cCBA5XHHnus1vssWrRI0Wq1Slpamu26zz//XHF3d1dKS0sbc3fFOXj55ZeVjh071nhbTk6O4uDgoMydO9d23f79+xVAiY2NVRRFjvvl5rHHHlMiIyMVq9WqKIq87i9ngDJ//nzb71arVQkMDFTeffdd23U5OTmK0WhUZs+erSiKouzbt08BlM2bN9vW+eeffxSNRqMcP35cURRF+eyzzxQvLy+74//ss88qrVq1auRnJOrq1GNfk02bNimAcuzYMdt14eHhygcffFDrfeTYXxpqOv533nmnMmbMmFrvI699UUFGqs+RyWRi69atDBs2zHadVqtl2LBhxMbGXsA9E40hNzcXAG9vb7vrZ82aha+vL+3bt2fKlCkUFRXZbouNjSUmJoaAgADbdSNGjCAvL4+9e/eenx0XZ+XQoUMEBwfTokULxo8fT2JiIgBbt27FbDbbve5bt25NWFiY7XUvx/3yYTKZmDlzJhMnTkSj0diul9d90xAfH09aWprd693Dw4OePXvavd49PT3p1q2bbZ1hw4ah1WrZuHGjbZ0BAwZgMBhs64wYMYKDBw+SnZ19np6NOFe5ubloNBo8PT3trp86dSo+Pj507tyZd999126qhxz7S9vKlSvx9/enVatWPPjgg5w8edJ2m7z2RQX9hd6BS11mZiYWi8XuixNAQEAABw4cuEB7JRqD1Wrl8ccfp2/fvrRv3952/a233kp4eDjBwcHs2rWLZ599loMHDzJv3jwA0tLSavz/qLhNXJx69uzJjBkzaNWqFampqbz66qv079+fPXv2kJaWhsFgqPalKiAgwHZM5bhfPhYsWEBOTg533XWX7Tp53TcdFcerpuNZ9fXu7+9vd7ter8fb29tunebNm1d7jIrbvLy8GmX/RcMpKSnh2Wef5ZZbbsHd3d12/aOPPkqXLl3w9vZm/fr1TJkyhdTUVKZNmwbIsb+UjRw5krFjx9K8eXOOHDnCc889x5VXXklsbCw6nU5e+8JGgmoh6mjSpEns2bPHbl4tYDdvJiYmhqCgIIYOHcqRI0eIjIw837spGsiVV15pu9yhQwd69uxJeHg4v/76K05OThdwz8T59u2333LllVcSHBxsu05e90I0LWazmZtuuglFUfj888/tbps8ebLtcocOHTAYDNx///28/fbbGI3G872rogHdfPPNtssxMTF06NCByMhIVq5cydChQy/gnomLjaR/nyNfX190Ol21qr/p6ekEBgZeoL0SDe3hhx9m4cKFrFixgpCQkNOu27NnTwAOHz4MQGBgYI3/HxW3iUuDp6cn0dHRHD58mMDAQEwmEzk5OXbrVH3dy3G/PBw7doylS5dyzz33nHY9ed1fviqO1+k+5wMDA6sVJy0rKyMrK0veEy4DFQH1sWPHWLJkid0odU169uxJWVkZCQkJgBz7y0mLFi3w9fW1e6+X174ACarPmcFgoGvXrixbtsx2ndVqZdmyZfTu3fsC7ploCIqi8PDDDzN//nyWL19eLX2nJjt27AAgKCgIgN69e7N79267N92KD+W2bds2yn6LhldQUMCRI0cICgqia9euODg42L3uDx48SGJiou11L8f98vD999/j7+/PqFGjTruevO4vX82bNycwMNDu9Z6Xl8fGjRvtXu85OTls3brVts7y5cuxWq22Ey69e/dm9erVmM1m2zpLliyhVatWkv55EasIqA8dOsTSpUvx8fE543127NiBVqu1pQXLsb98JCcnc/LkSbv3enntC0CqfzeEX375RTEajcqMGTOUffv2Kffdd5/i6elpV/VVXJoefPBBxcPDQ1m5cqWSmppqW4qKihRFUZTDhw8rr732mrJlyxYlPj5e+eOPP5QWLVooAwYMsD1GWVmZ0r59e2X48OHKjh07lMWLFyt+fn7KlClTLtTTEnXw5JNPKitXrlTi4+OVdevWKcOGDVN8fX2VjIwMRVEU5YEHHlDCwsKU5cuXK1u2bFF69+6t9O7d23Z/Oe6XPovFooSFhSnPPvus3fXyur/85OfnK9u3b1e2b9+uAMq0adOU7du32yo8T506VfH09FT++OMPZdeuXcqYMWOU5s2bK8XFxbbHGDlypNK5c2dl48aNytq1a5WoqCjllltusd2ek5OjBAQEKLfffruyZ88e5ZdfflGcnZ2VL7/88rw/X1HpdMfeZDIp11xzjRISEqLs2LHD7ntARSXn9evXKx988IGyY8cO5ciRI8rMmTMVPz8/5Y477rBtQ479xet0xz8/P1956qmnlNjYWCU+Pl5ZunSp0qVLFyUqKkopKSmxPYa89oWiKIoE1Q1k+vTpSlhYmGIwGJQePXooGzZsuNC7JBoAUOPy/fffK4qiKImJicqAAQMUb29vxWg0Ki1btlSefvppJTc31+5xEhISlCuvvFJxcnJSfH19lSeffFIxm80X4BmJuho3bpwSFBSkGAwGpVmzZsq4ceOUw4cP224vLi5WHnroIcXLy0txdnZWrrvuOiU1NdXuMeS4X9r+/fdfBVAOHjxod7287i8/K1asqPG9/s4771QURW2r9eKLLyoBAQGK0WhUhg4dWu3/4uTJk8ott9yiuLq6Ku7u7sqECROU/Px8u3V27typ9OvXTzEajUqzZs2UqVOnnq+nKGpxumMfHx9f6/eAFStWKIqiKFu3blV69uypeHh4KI6OjkqbNm2Ut956yy7oUhQ59her0x3/oqIiZfjw4Yqfn5/i4OCghIeHK/fee2+1QTN57QtFURSNoijKeRgQF0IIIYQQQgghLjsyp1oIIYQQQgghhDhLElQLIYQQQgghhBBnSYJqIYQQQgghhBDiLElQLYQQQgghhBBCnCUJqoUQQgghhBBCiLMkQbUQQgghhBBCCHGWJKgWQgghhBBCCCHOkgTVQgghhBBCCCHEWZKgWgghhBBCCCGEOEsSVAshhBBCCCGEEGdJgmohhBBCCCGEEOIs/T8qKMYErie5DQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "plt.plot(data.Close)\n",
    "plt.plot(ma100,'r')\n",
    "plt.plot(ma200,'g')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "531470c8-f518-4b7e-be98-8cf88955fd7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1657, 5)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "476d9f11-4ecc-4415-97f2-35a60deffaf4",
   "metadata": {},
   "source": [
    "### Train Test Split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "fcae2ff8-2d22-4923-8f2f-73125ff95820",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Train Test Split\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c85e72e3-89ac-4cab-b23f-0496d125dcf5",
   "metadata": {},
   "outputs": [],
   "source": [
    "price = data['Close']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "d5b6438b-4968-416c-a98a-a50cf00b01e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "training, testing = train_test_split(price, test_size=0.3, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "233526df-f71f-4ad5-957e-1e99428e38e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1159\n",
      "498\n"
     ]
    }
   ],
   "source": [
    "print(len(training))\n",
    "print(len(testing))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee48e04c-e282-414c-9546-3997c31cd9df",
   "metadata": {},
   "source": [
    "### Scale Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "5a0771cd-f5c2-46e7-907e-4ecfb7df0213",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Scaling data\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "scaler = MinMaxScaler(feature_range=(0,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "1aa7b8f7-82cd-46b7-8056-d508c274d4c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "training_trans = scaler.fit_transform(training.values.reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "aa76fcae-5b2e-44a4-b6b1-1bf3c00c851d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.16153703],\n",
       "       [0.15497043],\n",
       "       [0.09649022],\n",
       "       ...,\n",
       "       [0.07670372],\n",
       "       [0.07740152],\n",
       "       [0.07728656]])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "training_trans"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "288de8aa-8189-4e05-a6a6-3fec067e1c03",
   "metadata": {},
   "source": [
    "### X,Y Split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "32ee1ab5-90b1-4a2c-9469-eba5dbd20a61",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "x_train = [] # Steps, Features\n",
    "y_train = [] # Prediction Output\n",
    "\n",
    "for i in range(100,len(training)):\n",
    "    x_train.append(training_trans[i-100:i])\n",
    "    y_train.append(training_trans[i,0])\n",
    "\n",
    "x_train, y_train = np.array(x_train), np.array(y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "25a2ffb9-0474-4a96-8ba6-aff43694bb28",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1059, 100, 1)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a609adf8-b6ff-4751-a2ce-fea5cce80980",
   "metadata": {},
   "source": [
    "### Model Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "03c2b75d-8d7a-49bd-af65-24982048fc35",
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.layers import Dense, Dropout, LSTM\n",
    "from keras.models import Sequential"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "acb4148d-73f8-4510-a754-65ffb528bd28",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E:\\PROJECTS - AI\\ml-stockprice-prediction-lstm\\env\\Lib\\site-packages\\keras\\src\\layers\\rnn\\rnn.py:204: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
      "  super().__init__(**kwargs)\n"
     ]
    }
   ],
   "source": [
    "model = Sequential()\n",
    "\n",
    "# Layer 1\n",
    "model.add(LSTM(units= 50, activation = 'relu', return_sequences=True,input_shape=(x_train.shape[1],1))) #1 bcz 1 column price\n",
    "model.add(Dropout(0.2))\n",
    "\n",
    "# Layer 2\n",
    "model.add(LSTM(units= 60, activation = 'relu', return_sequences=True))\n",
    "model.add(Dropout(0.3))\n",
    "\n",
    "# Layer 3\n",
    "model.add(LSTM(units= 80, activation = 'relu', return_sequences=True))\n",
    "model.add(Dropout(0.4))\n",
    "\n",
    "# Layer 4\n",
    "model.add(LSTM(units= 120, activation = 'relu'))\n",
    "model.add(Dropout(0.5))\n",
    "\n",
    "model.add(Dense(units=1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "9376c412-7974-4b69-8a8e-d0b0f9da6019",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_1\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_1\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                      </span>┃<span style=\"font-weight: bold\"> Output Shape              </span>┃<span style=\"font-weight: bold\">        Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━┩\n",
       "│ lstm_4 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>)                     │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">100</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">50</span>)           │         <span style=\"color: #00af00; text-decoration-color: #00af00\">10,400</span> │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ dropout_4 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">100</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">50</span>)           │              <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ lstm_5 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>)                     │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">100</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">60</span>)           │         <span style=\"color: #00af00; text-decoration-color: #00af00\">26,640</span> │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ dropout_5 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">100</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">60</span>)           │              <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ lstm_6 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>)                     │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">100</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">80</span>)           │         <span style=\"color: #00af00; text-decoration-color: #00af00\">45,120</span> │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ dropout_6 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">100</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">80</span>)           │              <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ lstm_7 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>)                     │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">120</span>)               │         <span style=\"color: #00af00; text-decoration-color: #00af00\">96,480</span> │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ dropout_7 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">120</span>)               │              <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ dense_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>)                 │            <span style=\"color: #00af00; text-decoration-color: #00af00\">121</span> │\n",
       "└───────────────────────────────────┴───────────────────────────┴────────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                     \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape             \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m       Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━┩\n",
       "│ lstm_4 (\u001b[38;5;33mLSTM\u001b[0m)                     │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m100\u001b[0m, \u001b[38;5;34m50\u001b[0m)           │         \u001b[38;5;34m10,400\u001b[0m │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ dropout_4 (\u001b[38;5;33mDropout\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m100\u001b[0m, \u001b[38;5;34m50\u001b[0m)           │              \u001b[38;5;34m0\u001b[0m │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ lstm_5 (\u001b[38;5;33mLSTM\u001b[0m)                     │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m100\u001b[0m, \u001b[38;5;34m60\u001b[0m)           │         \u001b[38;5;34m26,640\u001b[0m │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ dropout_5 (\u001b[38;5;33mDropout\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m100\u001b[0m, \u001b[38;5;34m60\u001b[0m)           │              \u001b[38;5;34m0\u001b[0m │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ lstm_6 (\u001b[38;5;33mLSTM\u001b[0m)                     │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m100\u001b[0m, \u001b[38;5;34m80\u001b[0m)           │         \u001b[38;5;34m45,120\u001b[0m │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ dropout_6 (\u001b[38;5;33mDropout\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m100\u001b[0m, \u001b[38;5;34m80\u001b[0m)           │              \u001b[38;5;34m0\u001b[0m │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ lstm_7 (\u001b[38;5;33mLSTM\u001b[0m)                     │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m120\u001b[0m)               │         \u001b[38;5;34m96,480\u001b[0m │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ dropout_7 (\u001b[38;5;33mDropout\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m120\u001b[0m)               │              \u001b[38;5;34m0\u001b[0m │\n",
       "├───────────────────────────────────┼───────────────────────────┼────────────────┤\n",
       "│ dense_1 (\u001b[38;5;33mDense\u001b[0m)                   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m)                 │            \u001b[38;5;34m121\u001b[0m │\n",
       "└───────────────────────────────────┴───────────────────────────┴────────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">178,761</span> (698.29 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m178,761\u001b[0m (698.29 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">178,761</span> (698.29 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m178,761\u001b[0m (698.29 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "0cd3975d-9cbd-421d-8fad-7335c04162bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m13s\u001b[0m 173ms/step - loss: 0.0618\n",
      "Epoch 2/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 162ms/step - loss: 0.0119\n",
      "Epoch 3/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 180ms/step - loss: 0.0110\n",
      "Epoch 4/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 171ms/step - loss: 0.0089\n",
      "Epoch 5/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 165ms/step - loss: 0.0082\n",
      "Epoch 6/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 187ms/step - loss: 0.0081\n",
      "Epoch 7/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 170ms/step - loss: 0.0076\n",
      "Epoch 8/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 177ms/step - loss: 0.0058\n",
      "Epoch 9/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 157ms/step - loss: 0.0066\n",
      "Epoch 10/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 164ms/step - loss: 0.0076\n",
      "Epoch 11/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 158ms/step - loss: 0.0066\n",
      "Epoch 12/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 169ms/step - loss: 0.0059\n",
      "Epoch 13/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 158ms/step - loss: 0.0066\n",
      "Epoch 14/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 212ms/step - loss: 0.0056\n",
      "Epoch 15/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 205ms/step - loss: 0.0056\n",
      "Epoch 16/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 200ms/step - loss: 0.0063\n",
      "Epoch 17/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 193ms/step - loss: 0.0063\n",
      "Epoch 18/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 198ms/step - loss: 0.0060\n",
      "Epoch 19/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 192ms/step - loss: 0.0086\n",
      "Epoch 20/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 208ms/step - loss: 0.0066\n",
      "Epoch 21/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 243ms/step - loss: 0.0050\n",
      "Epoch 22/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 213ms/step - loss: 0.0058\n",
      "Epoch 23/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 267ms/step - loss: 0.0064\n",
      "Epoch 24/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 316ms/step - loss: 0.0051\n",
      "Epoch 25/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m18s\u001b[0m 223ms/step - loss: 0.0050\n",
      "Epoch 26/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 161ms/step - loss: 0.0045\n",
      "Epoch 27/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 168ms/step - loss: 0.0043\n",
      "Epoch 28/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 158ms/step - loss: 0.0043\n",
      "Epoch 29/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 172ms/step - loss: 0.0042\n",
      "Epoch 30/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 160ms/step - loss: 0.0047\n",
      "Epoch 31/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 167ms/step - loss: 0.0054\n",
      "Epoch 32/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 164ms/step - loss: 0.0044\n",
      "Epoch 33/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 179ms/step - loss: 0.0043\n",
      "Epoch 34/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 215ms/step - loss: 0.0045\n",
      "Epoch 35/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 177ms/step - loss: 0.0041\n",
      "Epoch 36/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 191ms/step - loss: 0.0032\n",
      "Epoch 37/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m22s\u001b[0m 543ms/step - loss: 0.0045\n",
      "Epoch 38/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m16s\u001b[0m 376ms/step - loss: 0.0044\n",
      "Epoch 39/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 215ms/step - loss: 0.0039\n",
      "Epoch 40/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 201ms/step - loss: 0.0043\n",
      "Epoch 41/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 227ms/step - loss: 0.0034\n",
      "Epoch 42/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 202ms/step - loss: 0.0037\n",
      "Epoch 43/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 206ms/step - loss: 0.0043\n",
      "Epoch 44/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 209ms/step - loss: 0.0049\n",
      "Epoch 45/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m14s\u001b[0m 414ms/step - loss: 0.0037\n",
      "Epoch 46/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 241ms/step - loss: 0.0040\n",
      "Epoch 47/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 219ms/step - loss: 0.0037\n",
      "Epoch 48/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 317ms/step - loss: 0.0036\n",
      "Epoch 49/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 216ms/step - loss: 0.0032\n",
      "Epoch 50/50\n",
      "\u001b[1m34/34\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 205ms/step - loss: 0.0036\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x1c79242e790>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.compile(optimizer='adam', loss='mean_squared_error')\n",
    "model.fit(x_train,y_train,epochs=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "b73f6450-1816-4904-af65-ff3433afb9eb",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:You are saving your model as an HDF5 file via `model.save()` or `keras.saving.save_model(model)`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')` or `keras.saving.save_model(model, 'my_model.keras')`. \n"
     ]
    }
   ],
   "source": [
    "model.save('kerasmodel.h5')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24abbab1-ebde-4bd9-8eac-d96b6ae82f5a",
   "metadata": {},
   "source": [
    "### Create Testing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "05c1b07f-2065-4536-9488-50d350747c9a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1059    0.080932\n",
       "1060    0.082877\n",
       "1061    0.081149\n",
       "1062    0.078958\n",
       "1063    0.077842\n",
       "          ...   \n",
       "1154    0.047194\n",
       "1155    0.049078\n",
       "1156    0.048113\n",
       "1157    0.048459\n",
       "1158    0.048402\n",
       "Name: Close, Length: 100, dtype: float64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "training.tail(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "e4a80e55-f5c0-43cf-aa97-6f8036be4e17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1159    0.048729\n",
       "1160    0.046154\n",
       "1161    0.045090\n",
       "1162    0.046487\n",
       "1163    0.048417\n",
       "          ...   \n",
       "1652    0.120330\n",
       "1653    0.113734\n",
       "1654    0.116196\n",
       "1655    0.116099\n",
       "1656    0.113619\n",
       "Name: Close, Length: 498, dtype: float64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "8ebe95cb-0357-4428-ad60-5f6c2bc40262",
   "metadata": {},
   "outputs": [],
   "source": [
    "past100days = testing.tail(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "c5e50d85-bd1e-4ddd-9f0b-99d878767803",
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df = pd.concat([past100days, testing], ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "c55fcd23-d377-457d-8be0-40dd10fb246e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.090911\n",
       "1    0.091231\n",
       "2    0.090313\n",
       "3    0.092499\n",
       "4    0.089798\n",
       "Name: Close, dtype: float64"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " final_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "9916e054-ee52-4e0f-b720-3f0f22e5de6e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(598,)"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "cedaacf1-0c22-4f49-90e6-a2b653ec0f0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       0.090177\n",
       "1       0.086921\n",
       "2       0.057924\n",
       "3       0.052490\n",
       "4       0.048021\n",
       "          ...   \n",
       "1154    0.047194\n",
       "1155    0.049078\n",
       "1156    0.048113\n",
       "1157    0.048459\n",
       "1158    0.048402\n",
       "Name: Close, Length: 1159, dtype: float64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "801787a1-1cdf-4988-ad7e-0abd38bf9185",
   "metadata": {},
   "outputs": [],
   "source": [
    "input_data = scaler.fit_transform(final_df.values.reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "e6bbd714-66d1-42aa-ad4a-303c4a71d726",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "       [0.81697738],\n",
       "       [0.79154618]])"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "d4801a93-a40e-4a61-8183-d62bc63e15fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(598, 1)"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "5188a39f-05c6-43cf-9cee-628a946d78ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_test = []\n",
    "y_test = []\n",
    "\n",
    "for i in range(100,input_data.shape[0]):\n",
    "    x_test.append(input_data[i-100:i])\n",
    "    y_test.append(input_data[i,0])\n",
    "\n",
    "x_test, y_test = np.array(x_test), np.array(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "dda53c67-a873-46e7-bf01-e2cf982dfb3f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(498,)"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2e63a3f-a58b-4d8d-b832-5af1460a8aea",
   "metadata": {},
   "source": [
    "### Making Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "d6b1053d-aab7-479b-a83d-14a2be15d76a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m16/16\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 158ms/step\n"
     ]
    }
   ],
   "source": [
    "y_predicted = model.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "93bdc945-9fc5-48d2-9740-009950b3c136",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(498, 1)"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_predicted.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31291ebd-d455-4356-8dff-e8c478adee40",
   "metadata": {},
   "source": [
    "### Scale Up"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "b36108b3-19a5-48a4-8ae1-071472497b6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "scale = scaler.scale_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "e0ec917d-f910-4b7d-a3bc-767a2db9f445",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.254517035740408"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scale[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "c3730de8-ff23-4ab4-80cd-3f6bff85becd",
   "metadata": {},
   "outputs": [],
   "source": [
    "scale_factor = 1/scale[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "ca121258-549b-4a24-801b-57884b0a9e10",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_predicted = y_predicted * scale_factor\n",
    "y_test = y_test * scale_factor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "a86a6f56-9005-48f8-b553-cfbddbb84318",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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++eSTgK/zzTff0K5dO5KTkznuuOMCxlmUGjVq0LBhQ9q1a8cLL7xAcnIyX375JWAV+wcffJAhQ4aQmprKtddeG7S1fsGCBZx22mmkpqZSo0YNjj76aJYvX+67/9VXX6Vjx44kJSXRoUMHXnzxxZDGJiIiIiJSmTkV+erV4fDD4c03oVkzu23ZMjs6bfWgIF9WVFIsC16vTQCpaCkp7qmtUkhOTmbbtm2+65MmTSI1NZWJEycCkJWVxcCBA+nXrx9Tp04lLi6O//3vfwwaNIi5c+eSkJDAyJEjefPNN3n99dfp2LEjI0eO5PPPP+f4448v9OsOGTKEadOm8eyzz9KtWzdWrFjB1q1badq0KZ9++innnnsuixcvJjU1leTkZABGjBjBu+++y6hRo2jbti1TpkzhH//4B/Xq1aN///6sWbOGc845h6FDh3LttdcyY8YMbrvtthL/ncTFxREfHx/QkfDEE09w7733ct999wV9zrp16zjmmGM49thj+eGHH0hNTeWXX37xTVt47733uPfee3n++efp0aMHf/75J9dccw3VqlXjsssuK/EYRUREREQqC6ci79+AW68eLFmiIF+eFOTLQnq6nYKqaHv3upNNSsDr9TJp0iQmTJjAjTfe6Lu9WrVqvPrqqyQkJADw7rvvkpuby6uvvoon74TBG2+8Qc2aNZk8eTInnXQSTz/9NHfddRfnnHMOAKNGjWLChAmFfu0lS5bw0UcfMXHiRAYMGABAq1atfPfXzvufXb9+fWrmbTKZkZHBww8/zPfff0+/fv18z/n55595+eWX6d+/Py+99BKtW7dm5MiRALRv35558+bx6KOPhvz3kpmZyciRI9m1a1fAiYjjjz8+4KRA/kr/Cy+8QFpaGh9++CHx8fEAtGvXznf/fffdx8iRI31/Ry1btuSvv/7i5ZdfVpAXERERkSrNvyLvqFfPjgry5UdBPop89dVXVK9enaysLHJzc7n44ou5//77ffd36dLFF+IB5syZw7JlywrMbz9w4ADLly9n165dbNiwgb59+/rui4uLo3fv3gXa6x2zZ88mNjaW/v37hzzuZcuWkZ6ezoknnhhwe2ZmJj169ABg4cKFAeMAfKG/OP/+97+55557OHDgANWrV+eRRx7h1FNP9d3fu3fvIp8/e/Zsjj76aF+I97dv3z6WL1/OVVddxTXXXOO7PTs7mzT/32giIiIiIlVQYRV5UJAvTwryZSElJXDzxIr8uiVw3HHH8dJLL5GQkEDjxo0LLNZWLV91f+/evfTq1Yv33nuvwGvVc/53lpDTKl8Se/P+br/++muaNGkScF9iYmKpxuHv9ttv5/LLL6d69eo0aNDA133gyP/3kl9R35Mz9tGjRxc40RAbG1vKEYuIiIiIVA5FVeTXrrWjgnzZU5AvCx5PqVrcK1q1atVo06ZNyI/v2bMnY8aMoX79+qSmpgZ9TKNGjZg+fTrHHHMMYJXmmTNn0rNnz6CP79KlC7m5ufz000++1np/TkdAjrPhJNCpUycSExNZvXp1oZX8jh07+hbuc/z222/Ff5NA3bp1S/T3kl/Xrl156623yMrKKlCVb9CgAY0bN+bvv//mkksuKfXXEBERERGpjIqqyDtNuv5BvlYtOyrIHxytWi+FuuSSS6hbty5nnnkmU6dOZcWKFUyePJmbbrqJtXmn126++WYeeeQRxo4dy6JFi/jnP/9Z5B7wLVq04LLLLuPKK69k7Nixvtf86KOPAGjevDkej4evvvqKLVu2sHfvXmrUqMG//vUvbr31Vt566y2WL1/OrFmzeO6553jrrbcAuP7661m6dCm33347ixcv5v333+fNN98s778iAIYNG8bu3bu58MILmTFjBkuXLuWdd95hcd5+Gw888AAjRozg2WefZcmSJcybN4833niDJ598skLGJyIiIiJSXpwgH6wi7whWkd+5E/xqd1JCCvJSqJSUFKZMmUKzZs0455xz6NixI1dddRUHDhzwVehvu+02Lr30Ui677DL69etHjRo1OPvss4t83ZdeeonzzjuPf/7zn3To0IFrrrmGffv2AdCkSRMeeOAB7rzzTho0aMCwYcMAePDBB/nvf//LiBEj6NixI4MGDeLrr7+mZcuWADRr1oxPP/2UsWPH0q1bN0aNGsXDDz9cjn87rjp16vDDDz+wd+9e+vfvT69evRg9erSvOn/11Vfz6quv8sYbb9ClSxf69+/Pm2++6Ru7iIiIiEhVVVRrvSNYRR4szEvpeLyFrUoWxXbv3k1aWhq7du0q0FJ+4MABVqxYQcuWLUlKSgrTCCXS6edMRERERKqCm26C556D//wH/vc/u+3PP8F/pu2oUXDdde71GjWskr9kCbRtW7HjrcyKyqH5qSIvIiIiIiIipVLSijy47fU7dpTfuCKdgryIiIiIiIiUSlGL3TkKC/Ja8K70FORFRERERESkVIJV5BMTA4O9gnzZU5AXERERERGRUglWkQeoW9e9rCBf9hTkRUREREREpFSCVeQhsL1eQb7sKciXkhb7l/Kkny8RERERqQoKq8j7B/n8C7A7QX7btvIbV6RTkC8hZ2/w9PT0MI9EIpnz8+X8vImIiIiIVEbFVeQ9noL3ORX6XbvKd2yRLC7cA6hqYmNjqVmzJps3bwYgJSUFj8cT5lFJpPB6vaSnp7N582Zq1qxJbGxsuIckIiIiIlKo4iryqakQk698rCB/8BTkS6Fhw4YAvjAvUtZq1qzp+zkTEREREamMcnJg/367XFhFPv/8eP/bFORLT0G+FDweD40aNaJ+/fpkZWWFezgSYeLj41WJFxEREZFKz6nGQ8mCfM2adlSQLz0F+YMQGxurwCUiIiIiIlHJCfKxsbZ3vL9u3ezYqVPB56kif/AU5EVERERERKTEnLb65GRb1M5fjx6wdCkcckjB5ynIHzwFeRERERERESmxjAw75q/GO9q0CX67f5D3egueBJDiafs5ERERERERKTEnyCcllex5TpDPyoIDB8p2TNFCQV5ERERERERKrLiKfGGqV3er8Dt3lumQooaCvIiIiIiIiJRYaYN8TIztLw+aJ19aCvIiIiIiIiJSYk5bfEmDPGjBu4OlIC8iIiIiIiIlVtqKPCjIHywFeRERERERESmx0i52BwryB0tBXkREREREREpMFfnwUZAXERERERGREjuYIF+zph0V5EtHQV5ERERERERKTBX58FGQFxERERERkRLTqvXhoyAvIiIiIiIiJaaKfPgoyIuIiIiIiEiJadX68FGQFxERERERkRJTRT58FORFRERERESkxBTkw0dBXkREREREREpMQT58FORFRERERESkxLRqffgoyIuIiIiIiEiJlVVF3ustuzFFCwV5ERERERERKbGyWLU+K8ut7EvoFORFRERERESkxEpVkc/MhIcfpkaf9lzoGQOovb404sI9ABEREREREal6Shzkf/kFrrsOFizAA7zO5SykPbt2dadhw/IaZWRSRV5ERERERERKLOQgP2MG/OMfcNRRsGAB1K0LffuSzAE+4Tz2bNh70GMZORJee+2gX6bKUJAXERERERGREgtp1fo774Q+feC99+z6lVfCokXwzTdsjD+ENiwnccK4gxrH2rXwr3/BDTdATs5BvVSVoSAvIiIiIiIiJVbsYncvvgiPPmqXL7kEfv/dyuZ16kDt2vxY93wAqs/66aDG8fffdszKgj17DuqlqgwFeRERERERESmxIlvr58+HG2+0yw89BO++a5V5Pwvr9weg9ryDC/KrVrmXo2XhPAV5ERERERERKbEig/wPP0BuLhx3HNx1V9Dn/934KHLxkLZhMWzaVOpxrFzpXt65s9QvU6UoyIuIiIiIiEiJFRnk586141FHgccT9PneWrWZRxe7MmVKqcfhH+RVkRcREREREREpRJGL3c2bZ8cuXQp9fkoKTOEYu/JT6dvrFeRFREREREREQlBoRT4nx+bIA3TtWujzq1WDn7B58mVVkVdrvYiIiIiIiEghCl21/u+/IT3d7mjTptDnV6sGv3CkXZk/3y3xl0BODqxZ415XRV5EREREREQkiNxcyM62ywUq8k5b/aGHQmxsoa+RkgIbacj++Brg9cKKFSUex4YNtu2cQ0FeREREREREJAinGg9Bgryz0F0R8+PBKvLgYWP1vKr9smUlHod/Wz2otV5EREREREQkqCKDvFORL2J+PDhBHtYll12QV0VeREREREREJAj/6ezx8fnuDLEin5JixzXxre2CgnzIFORFREREREQkJDNmQL9+MGmSXU9KyrdN/IEDsHy5Xe7cucjXciryK2JLX5FftcqOrVrZUUG+grzwwgu0aNGCpKQk+vbty++//17k4z/++GM6dOhAUlISXbp04Ztvvgm4f+/evQwbNoxDDjmE5ORkOnXqxKhRo8rzWxAREREREYkKH3wAv/0Gr71m1wu01a9aZQvXVasGDRoU+VpOkF9GXpB3TgCUgFOR79bNjpojXwHGjBnD8OHDue+++5g1axbdunVj4MCBbN68Oejjf/31Vy666CKuuuoq/vzzT8466yzOOuss5jt7FALDhw9n/PjxvPvuuyxcuJBbbrmFYcOGMW7cuIr6tkRERERERKq89HTb3t3rdW/buNGOGzbYsUCQd5J1y5b5SvUFOUF+cU4b97n+S9CHYNMmO3bsaEdV5CvAk08+yTXXXMMVV1zhq5ynpKTw+uuvB338M888w6BBg7j99tvp2LEjDz74ID179uT555/3PebXX3/lsssu49hjj6VFixZce+21dOvWrdhKv4iIiIiIiLgeeAD69wf/BmcnOBca5J0t5Fq0KPb1nTnyKw40guRk2xTe6ZUP0e7ddmzWzI4K8uUsMzOTmTNnMmDAAHcwMTEMGDCAadOmBX3OtGnTAh4PMHDgwIDHH3HEEYwbN45169bh9Xr58ccfWbJkCSeddFKhY8nIyGD37t0Bf0RERERERKLZlCl2HDPGvc0J8k5gLrQiH0KQdyry+/bHkNPSFrxb/UPJ5snv2WPHpk3tqNb6crZ161ZycnJokG/eRIMGDdjo9Gvks3HjxmIf/9xzz9GpUycOOeQQEhISGDRoEC+88ALHHHNMoWMZMWIEaWlpvj9NnZ8CERERERGRCPDRR7BgQeiPz80FZwbzzz/Djh122QnyjiJb64vhC/L7YG2itddPfCn0IO/1uhV5J8Lt32/f62GHwZVXwvjxIb9clRL2xe7K2nPPPcdvv/3GuHHjmDlzJiNHjmTo0KF8//33hT7nrrvuYteuXb4/a9asqcARi4iIiIiIlJ/58+GCC+DSS0N/zurVsHevXc7JgQkTIDsbtm4NfFxSUr4nlqK1PicH1iZaRT5lY+gL3h04YGMCOOQQ9/b774c//oA33oDTToMtW0J+ySojLlxfuG7dusTGxrIp3ymdTZs20bBhw6DPadiwYZGP379/P3fffTeff/45p556KgBdu3Zl9uzZPPHEEwXa8h2JiYkkFjiVJCIiIiIiUvU5EWrt2tCf47eeOABffWXz5f0XvoOyqciDrVx/JNBw15KQx+hU4z0eSEuD6tXt5MPChe7tOTn2vRx3XMgvWyWErSKfkJBAr169mORsQAjk5uYyadIk+vXrF/Q5/fr1C3g8wMSJE32Pz8rKIisri5iYwG8rNjaW3NzcMv4OREREREREKr/9++1YkoXgnCDv5PFvv4X16ws+LiDI79sHzg5kIVTk4+PtD8D8zHYAND1Q8iBfvTrExFiY93fssXZctCjkl6wywtpaP3z4cEaPHs1bb73FwoULueGGG9i3bx9XXHEFAEOGDOGuu+7yPf7mm29m/PjxjBw5kkWLFnH//fczY8YMhg0bBkBqair9+/fn9ttvZ/LkyaxYsYI333yTt99+m7PPPjss36OIiIiIiEg4OUE+M9Pa0UPhBPkrroCaNWH7dpg4seDjAoK8s+J8WhrUqhXS13Ha66fvbA9AC+8K9u3IDOm5TpBPTbVjzZrufc2bQ69edtmp0EeSsLXWA1xwwQVs2bKFe++9l40bN9K9e3fGjx/vW9Bu9erVAdX1I444gvfff5977rmHu+++m7Zt2zJ27Fg6d+7se8yHH37IXXfdxSWXXML27dtp3rw5Dz30ENdff32Ff38iIiIiIiLh5gR5sKp8gXntQcybZ8fu3aFLF5g6FX78seDjAoJ8CVasd1SrZmOauaExe6lGdfaxYcbfVDuxQ7HPzR/k/SvyHTu6e8sryJeDYcOG+Srq+U2ePLnAbYMHD2bw4MGFvl7Dhg154403ymp4IiIiIiIiVZp/FX7XLsi3EVgBWVluO3qXLhaIp0611evzCwjyzkJ3IcyPdzjz5NP3e1hCO3ryJ+mzl0AIQd7Zei4ag3zErVovIiIiIiIirvwV+eIsW2Zt+NWrQ7Nm0KmT3Z6eXvCxAdX9UlTkndZ6gMVYe332gsUhPbeo1vqOHaFD3rmAdevcx0YKBXkREREREZEI5h/kd+4s/vFTptixc2dbRM6pbAcTtCJfwtZ6xxJswbvY5aUL8v4V+U6dbJq+030QaQveKciLiIiIiIhEsJJU5L1eePllu3zeeXZ0KvKOGjXcywFB/u+/7diqVchj8w/yTkU+ZU1oK9cXN0fe/6ggLyIiIiIiIlVG/jnyRZkxA/780wL6ZZfZbU2aBIZ3/wq9L8h7vdaTD9CmTchj82+tdyryNTcfXGt9/fpQu3bgWCNtnryCvIiIiIiISAQrSUX+pZfsOHgw1K1rlz0ed745BFbofUF+61Zbfc7jKdVid+AG+dT9m0OaA1BYkPc/0aAgLyIiIiIiIlVOqEE+OxvGjLHL+Xfv9g/v/kHZt9idU40/5JDQ9rfL4x/k95DKBhralSXFt9fnD/Knnw6DBsG//lVwrJEW5MO+/ZyIiIiIiIiUn1CD/LZttjK9xwN9+wbe5wTimBho18693VeRX77cjq1bl2hs/kE+JgYW57anERttUvthhxX5XCfIO23/TZrAt98GPqZnT3jrLTj00BINq9JTRV5ERERERCSChTpHfts2O9asCXH5Sr5ORb5uXahXz73dF+RLMT8eAufIt2oFC8hL3PPnF/vc/PvIB1O7NgxpNple2dNLNK7KTkFeREREREQkgpWkIg9Qp07B+445Brp0gSFD3IXkoGwr8h07wjy6AJA7d16xz83fWl/AzJlw3HH259ZbbUG+CKHW+qps40ZYs8bOetWqFe7RiIiIiIhIJVQWQT4tDebOtcubNrm3H2xF3j/It20L0z1dwQveOXOLfW6RQX77dgvwe/ZAQoL12GdklGj+fmWminxVdsYZNm9kypRwj0RERERERCqpsgjy/vxriAdbkfdvra9XDzbU6QxA7Mb17oAKUWSQf/llC/GdOtlJhuefj5gQDwryVVuTJnZcty684xARERERkUph50646CL48kv3tpLOkS8uyCckQPXqdjkpCUvUW7bYDQfRWl+7NlRrlMoKWtgN84pury80yGdmwnPP2eU774SmTUs0pqpAQb4qU5AXERERERE/jz8OH35ozbuO4iryO3fa9PFQgzy48+QTE3Gr8fXqFb3yXBD5g3z9+jCXrnZDEUE+O9tW2IcgX/KDD2DDBmjcGC64oETjqSoU5KsyBXkREREREfGzY0fB2/yDvBPaHd9/b63yDz7oBvm6dYv/Ok7hvXFjSj0/HgJb6+vUsVDuC/Jz57J3b/A16pwV68Hdfs7n3XftOGyYtQ9EIAX5qswJ8uvXh3ccIiIiIiJSKQRbA9s/yGdlBbbaT5hgx59+KllF/p137CRAjx7A+PF2Y5cuJR5v/op8Soq7cv3+P+ZRrx5cfnnB5zlBPikpX1bPzobffrPLp51W4vFUFQryVZkq8iIiIiIi4sd/azin9dw/uENge/1ff9lx9eqSBfkmTeCEE7BEPWaM3fiPf5R4vMGCvFORj1s4j4wDubz9dsHvodD58fPmwd69dkenTiUeT1WhIF+VNW5sRwV5EREREREBkpPdy5s329G/Ig/Bg/yaNbB1q10OJcj7fPQR7NsH7drBUUeVeLz+rfW1a9v4l9GGrNhE4jPTacFKwDoG/DlBvkBb/a+/2rFfP4iNLfF4qgoF+arMqcjv2mX/eUREREREJKplZ7uXN2+2685tzkrzTpDfuxdWrrTLGRnuVPeQgvwLL1hJ/n//s+tXXgkeT4nHW7++tcY3aGChPiUFcohjS822ALRnMeB27zsKrcg7Qf6II0o8lqpEQb4qS011/zeqKi8iIiIiEvXyB3n/anyjRnZ0gvyiRYHPzcqyY7FBfvx4W0juhx/sTEBsLAwZUqrxpqXBlCkwaZKdB3A6CjakdgCgAzbIb78NfF6hQf6XX+wY4UE+LtwDkIPUpAksXmxBvl27cI9GRERERETCyAnjYEHef255/fqwdCl89RXMnRt8YTwoJsivXevOhT/3XGjWDA47zD1LUAp9+7qXnVb7tdXa0wu3Ir94MaxYAS1b2v1Bg/y6dbBqFcTEBL5oBFKQr+r8g7yIiIiIiEQ1/4r8pk1uRT4xEWrWtMvPPmvHZs0KPj85OXCefYCsLLjwQlsVr0cP2+YtKamshu77+gArkwMr8gDffQfXXWeXgwb5adPs2LVrkMnzkUWt9VWdVq4XEREREZE8+SvyTpBPTrY2dn+rV9vRPwwXuYf8PfdY63pqKnz8cZmHeHAr8n/HFwzyixe7j9uxw44B39O8eXbs1avMx1XZKMhXdQryIiIiIiKSp7A58snJVqF3+GfwAQPcy4W21c+dC489Zpdffx1aty6T8ebnVOSXxrQHoCGbaFlrJ2Bd/Q7nJETTpn5Pdpbgj+Bt5xwK8lWdE+TXrw/vOEREREREJOwKmyOfnAwDB9rlHj3gxhvdx518snu50CD/5pt2PPtsmxtfTpyK/PasGmxPtu22TzjESvFr1riPc1bbb97c78lOkO/YsdzGV1lojnxVp73kRUREREQkT2Fz5JOS4J//hBYt4LTTYPt2yHzxVZqm7ebwphcAViAMGuSzs+H99+3yFVeU5/B9QT49HdZW70Dt/evpm7aIV+kbUJFftcqOviCflWUr+YEq8lIFqLVeRERERETyFDVHvlo1GDzYLjdZ9ztP77uG29bfxqEnN+XfPAIUEuQnTrSzAnXrwqBB5Tp+p7U+PR1W5S141ynW5slv2GDnFLKz3TZ7X5Bfvty++WrV8vXbRyZV5Ks6J8hv2AA5ObaHo4iIiIiIRCX/ivyWLbBvn10usBL9u+/asXZtPNu38wh3sZj21KlzdsEXfecdO150EcTHl/mY/TkV+f37YUWyzZNvlr6Y2FiLO5s22TEnx4bi2/Vu4UI7duhg289FuMj/DiNdw4Z2zM52l24UEREREZGo5F+Rz811l9IKCPJZWfDhh3b53Xfh5psBeJshtMpdFviCO3fC55/b5UsvLZcx+/OvyC+MORSA2qv/9M0oXrPGbatv1swvs0fRQnegIF/1xcW5G0Ju3RrWoYiIiIiISHj5B3lwQ2/ATnETJ1q5vl49OPFEePxxFtQ+mhrs5fhf/xf4Au+9Zyvmde4MvXuX69ghsCL/h+cwcoghZdNKetS3qcRr12qhO1CQjwzORJZt28I7DhERERERCSv/1npwQ29ARf699+x44YVWGIyPp9arjwPQ7Of33PTv9cLo0Xb5mmvA4ym3cTuccWZkwKb0GsylKwDHJvwCWJAvsNAduK31qshLlVG3rh1VkRcRERERiWqFVeQDgvzUqXb020au8dl94YQT8GRnwxNP2I0zZ8KcOZCYCP/4R/kN2o9TkQdbWf8XjgSg14EignxuLiyyBfFUkZeqw6nIK8iLiIiIiES1Yivy+/e7G7Lnr17fdZcdX34Znn8err/erp93HtSuXR7DLcD/hEN6uhvk22+xIO8/R94X5P/6y76vpCRo1apCxhluCvKRwKnIq7VeRERERCSqORX5tDQ7bt9uR98c+b//tmNqqpsjHMcfbyvTZ2XBjTdaRb52bbj77nIftyMmxhoAHE6Qr7d+NtXYG7wi/913duzf36YKRAEF+Uig1noREREREcGtyLdvH3i7r9K9LG9V+rZtC85593hsFft//9t9kenTK3zeuX97/RqakdvkEGJycziM31m9uoggP3BghY4znBTkI4EWuxMREREREdyKfIcOgbcXCPJt2gR/gZgYeOQRe9ycOYU/rhwV2PP+yKMAOIfPWLvWFsKLiYFDDsFa6n/6yR530kkVOs5wUpCPBKrIi4iIiIgIIVTkly61Y3EBvXXrwB73CuRfkY+Ph5hrrgLgWl6hFcsBaNECEhKAn3+27fGaNImaFetBQT4yKMiLiIiIiAhuRb51a4iNdW/3zZH3b62vpPwr8ikpwIABMHAgCWTxMHfTpw98+GHeAyZMsONJJ1XI9niVhYJ8JFBrvYiIiIiI4FbkU1KgWTP39pBb6ysB/4q87/Jjj+H1eLiAj5je9hL6pC6GL7+EF1+0+6NofjwoyEcGVeRFRERERAS3Ih8XZ1V5R3Iy1oK+erXdUNWCfNeueB56CGJi8Lz/vi0CcMYZNkd+0CA455ywjDVcFOQjgVOR374dcnLCOxYREREREQkbpyIfHx8kyK9YAV4v1KgB9euHZXyhKNBa77jrLvjtNzjmGHf+/hVXwLhx9g1HkejYZC/SOUHe64WdO93rIiIiIiISVYqsyPu31Vfi+eRBK/KOPn1slfqcHNi7F9LSKnRslYUq8pEgPt79AVZ7vYiIiIhI1HKCfP6KfFISVWJ+PBRRkfcXGxu1IR4U5COHU4VXkBcRERERiVpOa31cHLRq5d6enIw7P75lywofV0kUWZEXQEE+cjgL3mnlehERERGRqFVYRT45Gdi82a40aFDh4yqJkCryUU5BPlKoIi8iIiIiEvX8K/I1akD79na5USPcIF+JF7oDVeRDocXuIoUq8iIiIiIiUc+/Ig/w/fe2uVW9elSZIK+KfPEU5COF9pIXEREREYl6/tvPARxyiP0B3CBfr16Fj6skVJEvnlrrI4Va60VEREREop7/9nMBcnNhyxa7XMkr8v7hvVq18I2jMlOQjxRqrRcRERERiXr5K/I+O3bY3utQ6Svyaq0vnoJ8pFBFXkREREQkqnm9RVTknWp8zZqQkFCRwyoxtdYXT0E+UjhBfseO8I5DRERERETCIjfXvVygIl9FFroDVeRDoSAfKWrXtuP27eEdh4iIiIiIhIVTjYcgFfkqFORVkS+egnyk8A/yXm94xyIiIiIiIhXOP8irIh/ZFOQjhRPkMzMhPT28YxERERERkQrnLHQHqshHOgX5SJGS4i5aofZ6EREREZGoo9b66KEgHyk8Hs2TFxERERGJYk5FPjbW4kEAJ8hX8q3nQK31oVCQjyQK8iIiIiIiUcupyBeYHw+qyEcYBflIoiAvIiIiIhK1nIp8gbZ6qFJBXhX54inIRxIFeRERERGRqFVkRX7LFjtWgSCflAQNGkC1alCnTrhHUzkFO1cjVZWCvIiIiIhI1HIq8gWCfFaWmxGqQJD3eODXXyEjQxX5wijIRxIFeRERERGRqOVU5Au01m/daseYGDczVHKtWoV7BJWbWusjiYK8iIiIiEjUKrQi779ifYwiYCTQv2IkUZAXEREREYlahVbkq9BCdxIaBflIoiAvIiIiIhK1QqrIS0RQkI8kCvIiIiIiIlFLFfnooSAfSRTkRURERESiVqHbzynIRxwF+UiiIC8iIiIiErWc1npV5COfgnwkcYJ8ejocOBDesYiIiIiISIVSRT56KMhHktRUiI21yzt2hHcsIiIiIiJSoQqtyG/ZYkcF+YihIB9JPB6oVcsuq71eRERERCSqqCIfPRTkI43myYuIiIiIRCXNkY8eCvKRRkFeRERERCQqBa3I79tnf0D7yEcQBflIoyAvIiIiIhKVnIp8QJB35scnJkKNGhU+JikfCvKRRkFeRERERCQqORX5gNZ6/7Z6j6fCxyTlQ0E+0ijIi4iIiIhEpaAVec2Pj0hhD/IvvPACLVq0ICkpib59+/L7778X+fiPP/6YDh06kJSURJcuXfjmm28KPGbhwoWcccYZpKWlUa1aNfr06cPq1avL61uoXBTkRURERKSKysiAvXvDPYqqq9iKvESMsAb5MWPGMHz4cO677z5mzZpFt27dGDhwIJudH7Z8fv31Vy666CKuuuoq/vzzT8466yzOOuss5s+f73vM8uXLOeqoo+jQoQOTJ09m7ty5/Pe//yUpKamivq3wUpAXERERkSrqsMOgXTs4cCDcI6magi52pyAfkcIa5J988kmuueYarrjiCjp16sSoUaNISUnh9ddfD/r4Z555hkGDBnH77bfTsWNHHnzwQXr27Mnzzz/ve8x//vMfTjnlFB577DF69OhB69atOeOMM6gfLT+4CvIiIiIiUgXt3w9z58KGDbBxY7hHUzUF3X7OWewuWvJQlAhbkM/MzGTmzJkMGDDAHUxMDAMGDGDatGlBnzNt2rSAxwMMHDjQ9/jc3Fy+/vpr2rVrx8CBA6lfvz59+/Zl7NixRY4lIyOD3bt3B/ypshTkRURERKQK8v/4qvb60lFFPnqELchv3bqVnJwcGjRoEHB7gwYN2FjIKbiNGzcW+fjNmzezd+9eHnnkEQYNGsR3333H2WefzTnnnMNPP/1U6FhGjBhBWlqa70/Tpk0P8rsLIwV5EREREamCFOQPXtCKvIJ8RAr7YndlKTc3F4AzzzyTW2+9le7du3PnnXdy2mmnMWrUqEKfd9ddd7Fr1y7fnzVr1lTUkMuegryIiIiIVEH+H1/37QvfOKqyIivy9epV+Hik/MQV/5DyUbduXWJjY9m0aVPA7Zs2baJhw4ZBn9OwYcMiH1+3bl3i4uLo1KlTwGM6duzIzz//XOhYEhMTSUxMLM23Ufk4QX73bvufHPC/WERERESkclJF/uCpIh89wlaRT0hIoFevXkyaNMl3W25uLpMmTaJfv35Bn9OvX7+AxwNMnDjR9/iEhAT69OnD4sWLAx6zZMkSmjdvXsbfQSVVs6Z7eefOcI1CRERERKREtm1zLyvIl06BirzX6y52V7duWMYk5SNsFXmA4cOHc9lll9G7d28OO+wwnn76afbt28cVV1wBwJAhQ2jSpAkjRowA4Oabb6Z///6MHDmSU089lQ8//JAZM2bwyiuv+F7z9ttv54ILLuCYY47huOOOY/z48Xz55ZdMnjw5HN9ixYuNtTC/c6ed1lQLjYiIiIhUAWqtP3gFKvJ797rpXkE+ooQ1yF9wwQVs2bKFe++9l40bN9K9e3fGjx/vW9Bu9erVxMS4TQNHHHEE77//Pvfccw933303bdu2ZezYsXTu3Nn3mLPPPptRo0YxYsQIbrrpJtq3b8+nn37KUUcdVeHfX9jUru0GeRERERGRKkCt9QevQEXeaXNITISUlLCMScpHWIM8wLBhwxg2bFjQ+4JV0QcPHszgwYOLfM0rr7ySK6+8siyGVzXVrg1//60gLyIiIiJVhlrrD55TkS8Q5OvUAY8nLGOS8hFRq9ZLHq1cLyIiIiJVjFrrD55Tkfe11m/dake11UccBflIpCAvIiIiIlWMWusPXpEVeYkoCvKRSEFeRERERKoYVeQPXoGKvIJ8xAr7HHkpBwryIiIiIlKZpKfDunU2T7tNm6AP0Rz5g1foYncK8hFHFflIpCAvIiIiIpXFL7/AIYdAu3bQti1cconbA+5HrfUHr8D2c06Q1xz5iKMgH4kU5EVERESkMpgxA045BXbsgGrVICYG3n8fLr8ccnN9D9u/3/441FpfOgUq8s5id6rIRxwF+UikIC8iIiIi4eb1woUXwu7d0L8/bN4Mn35q5eL33oPXXvM9NP/HVlXkS6fQiryCfMRRkI9ECvIiIiIiEm6//w7Ll0P16jBuHKSkwFlnwWOP2f333utL7AryZUNz5KOHgnwkUpAXERERkXD75BM7nnYapKa6tw8dCq1awcaNMHIkUPBjq1rrS0dz5KOHgnwkcoL8jh0Bc49ERERERCrCLz972fT8x3Zl8ODAOxMSYMQIu/zEE7Bnjy/I16tnR1XkS0dz5KOHgnwkqlXLjl4v7NoV3rGIiIiISNT56oGZNDiwisy4FLwDB/Hii/Djj34PGDwY2re3xD5mjK9w3KyZHffts4+yUjIBFfmMDLe1QUE+4ijIR6KEBJuLBGqvFxEREZEK12LWZwD8Xv80/lycwtChMGSI3wM8HrjqKrv86qu+j6xOkM/NhQMHKm68kSKgIu+cHYmJgbS0sI1JyoeCfKTSPHkRERERCYP0dDh0+xQAvuVk5syx29eutQXsfYYMsdLx9OnEL54P2HbzDrXXl5xTkQ8I8nXqWJiXiKJ/0UilIC+l9J//2B8RERGR0lg4J5PezADgiy1HMH++e9/SpX4PbNAATj8dgC6/21Z09erZ4vbgt+Ddr7/C229r7acQOBX5uDg0Pz7CKchHKgV5KYVt2+Dhh+3Pnj3AqlXwf/8HL7wACxeGe3giIiJSieTkwDffuHlx1SoL6uu+nk0SGWyjNguy2jJhgvucJUvyvcjllwPQY9nHeMildm2oVs3u2rsXeOcdOOYYuOwyuPvu8v6WqrxCK/IScRTkI5WCvJTC+vXu5d27gRtvhPvug2HDoGtX+OOPsI1NREREKpfPPoNTT4WmTeH++6FtW+jeHbaMmwbAbxwOeFiwwH1OgSB/0klQvTp1DqyjD39Qp4671FPCFx9b+31Ojt3w6KMwalQ5f1dVW0BFXkE+oinIRyoFeSkF/yC/b/U2+PZbu9K5s53i/ec/3TdTERERiWqLFtnxwAF44AELkenpUG2eBfnpnn4FnlMgyCcl2dkA4Bw+81Xk48ii6fN32GOuv946BAHuvNMtO0sBQRe70x7yEUlBPlIpyEsp+Af5+K8+szfK7t1h4kRITYUZM+CVV8I2PhEREak8Nm1yL8fGwtln2+V+WJBP7xZCkAc45xw78Bm1a3mpXh0u4gOSN660SfMjR1pbfa1atrWyOgQLFbD9nCryEU1BPlIpyEspbNjgXq75zQd24cILoWFDeOghu/7f/9qbqIiIiES1jRvt+NxzNiXv44+hT5P1NGc1OcTQ+qLDfI+tX9+OS5YE2R/+lFM4QCJtWUbDLfNIrZbD3Txs9912m61+FxsLJ5xgt02cWL7fWBUWUJHfssWuKMhHJAX5SKUgL6XgVOQbsZ6acybblQsusOP110OHDnZ2d+TIsIxPREREKg8nyDds6GbtuwZYtXx54qF06FPD99hTT7Ud0Hbvhs2bA19nf2x1vuVkAOq/9Rinb3uDDiwmI6Um3HCD+8ABA+yoIF+ogIr82rV2pUmTsI1Hyo+CfKRSkJdScIL8AL7H4/XCYYdBixZ2Y1ycW5V/8snAfjoRERGJOv5B3nFaS1vZrsbR3Wjb1r29Rw9o3twu52+v37ED/sc95OIh4aP3uGr+rQD8dsI9NrXPceKJdvztt7ztdcRfbq67Q198PLBmjV1p2jRsY5LyoyAfqRTkpRSc1vqO5G0117t34APOPhv69LGNXe+7r2IHJyIiIpWKc06/QQP3tvilfwHQ6PhONG7s7gnfqRO0a2eX8wf5bdtgFr34KHEIAMnZe5lFD6b2vDnwga1a2Z/sbPjpp7L+dqo8/zUA42K9bkVeQT4iKchHKgV5KQWnIu8L8h06BD7A44EnnrDLr7wCf/5ZcYMTERGRSmPv3rx93gmsyPv2muvUiZgYuPlm6N8fjjjCDfK//hr4Ws7H1ReaPAzVq5PrieFaXmHP/riCX9ipyk+aVGbfS6RIT3cvJ6dvs+0EQK31EUpBPlL5B/kCK4qIFOT1uhX5DuTtJ9OxY8EHHnOMLYDn9do+8/r5EhERiTpONT4lxd33nZwcd0+6Qw8F4OGHYfJkSE727TLH66/bHvQOJ8jnNGgM06fzylW/M5PevhMFAQ4/3I5z5pTltxMRdu60Y3IyJG7Oa6tv0AASE8M2Jik/CvKRygny2dkE/y0oEmjbNlvpNJ5M2rDMbsxfkXc8/ri9c//yC3z1VcUNUkRERCoF//nxHk/ejStXWhU4KQlatizwnIEDYfhwu3zZZW7ntxPka9cGOnVid9tegM3kK6BzZzvOn18W30ZEcYJ8zZpofnwUUJCPVMnJ9ksU1F4vIXHa6luznDhyOBBXvfBWrEMOgaFD7fIzz1TMAEVERKTSCLbQna+tvkMHW8I+iEcftYXv9u6Fb76x25ztzp06lFPhD1qLcroFt2wpuPx9lFOQjy4K8pFM8+SlBPLPj19bo4PfKfYghg61fWQmTdJZcRERkSgTNMj/ZQvd0alToc+Li7PKPMCMGXYMqMhTTJCvVs0WvAP3xIEAtvo/KMhHCwX5SKYgL4Xwem0amz8nyDvz41cmB5kf7695c1vFHlSVFxERiTJOkPdfsT6UIA+2AQ7AH7blvO+jap06dqxWzY6rV8PWrUFewGmvV5APoIp8dDmoIJ+ZmcnixYvJ9t/rQCoPBXkpxDXXQKNG7uJ24F7uFm8V+eVxhcyP93dz3rYw772ntRhERESiiLPYXdDW+ryF7grj7G47bx7s31+wtf6QQ+y4cCE0a2aL5QVwXl8dgQGcIF+rFm6Qd/4yJeKUKsinp6dz1VVXkZKSwqGHHsrq1asBuPHGG3nkkUfKdIByEBTkpRCvvWZTyx54wL3Nqch3SbCK/GJPCEH+qKOgdWt7Fx43rhxGKiIiIpVRgdb63FxL3lBsRb5pU6hf37oD58wp2Frfty98+im0b1/IRwxV5INSRT66lCrI33XXXcyZM4fJkyeT5CyoBgwYMIAxY8aU2eDkICnISzFmznQvW5D30jLDgvy87GJa68Hm0F90kV3+8MMyH5+IiIhUTgWC/MqVlroTE9057IXweALb6/MHeYBzznHX1c2rGbr8K/LaBtfHV5FPy4V16+yKgnzEKlWQHzt2LM8//zxHHXUUHr/FsA499FCWL19eZoOTg6QgL8XwD/KLFkEjNpCcvZccYlhwoHXAY9evt1Vmb7st34s4QX78eP2siYiIRIkCQd6ZH9++va1oVwynvX7GjIJz5B3NmtmxQJBv395Wxd+5020pFF+Qbxy7yfYUjomBxo3DOiYpP6UK8lu2bKF+/foFbt+3b19AsJcwU5CXYni9Ni9t2zYL8q2xE3Gracb2vQkBj/3Pf2D2bHjyyXydbJ06Qdeu9obx+ecVN3gREREJC6+3iCBfTFu9w78in3+OvMMJ8qtW5XtyUhK0bWuX1V7v46xa3zgnr62+UaOQTqpI1VSqIN+7d2++/vpr33UnvL/66qv069evbEYmB09BXoLI34E2bRr89ptdPrLh3wAspzUZGZCZabfPng1vveU+Z8SIfC964YV2/OSTMh+viIiIVC47dtj5e7C57kDIC905DjvMjgsXWkc+FAzyzZvbcfNm9zE+WvCuAF9FfrdNk/SdCZGIVKog//DDD3P33Xdzww03kJ2dzTPPPMNJJ53EG2+8wUMPPVTWY5TSUpCXIDIyAq//+qv9AejXwCryy7G2+j177PY77rATAM6b7gcfQMAsmrPOsuMPP2j1ehERkQjnbAlXo4YVx4ESV+Tr1YPDD3evx8RAamrgY2rVcreiW7s23wtowbsCnCDfetq7duHEE8M2Fil/pQryRx11FLNnzyY7O5suXbrw3XffUb9+faZNm0avXr3KeoxSWk6Qd/qVRIADBwKv//KLG+QPTcxrrY9zg/zatTBxoi1M88EHcPLJtjDtG2/4vUiHDrawTWYmTJpUAd+FiIiIhIvz0dI3p91/xfoQK/IA553nXq5d28K8P4+niPZ6VeQL2LkTmrKa2n9+bzdcfnk4hyPlrNT7yLdu3ZrRo0fz+++/89dff/Huu+/SpUuXshybHCznt6uCvPjJ35o2daqFeYDGByzIb0hxg7yz5cvhh1tWP/ZYux7whurxwGmn2eWvviqfgYuIiEilUGCV+dWrYd8+iI+3bWlDdM457uX8bfWOQhe8cyryf/1lJxKEnTthCG/j8XrtA1vLluEekpSjUgX5b775hgkTJhS4fcKECXz77bcHPSgpI3Xr2nHrVm3NIT5ORT4lBa6+2n40srIgLQ2S11uQ31zDDfJjx9rjne75Ro3suGFDvhf2D/J6QxUREYlYBSryJVyx3tGyJTjNvIUFeWeefIEg36aNnTjYuzfIndEnOxv27cnhct60G664IqzjkfJXqiB/5513kpOTU+B2r9fLnXfeedCDkjLi/HbNzoZdu8I7Fqk0nCCflATPPONOZTuhz248eZPetteyIL92Lfz4o91/5pl2dHYxKRDkjzkGqle3ZWxnzSrH70BERETCqcB2cSVc6M6f017vFAryK7QiHx9vU/sgqtvrc3Nh+nT7+HU5b9KG5Xhr1oRzzw330KSclSrIL126lE5BFrLo0KEDy5YtO+hBSRlJTnZXCHFWJZGo57TWJydbVf7zz+H88+HeS/JWr6tXj9iaNQD46CM7D9Shg51khyIq8omJMGCAXf7++/L9JkRERCRsCmwXV8KF7vzdfDM88AA8+GDw+wudIw9a8A4YM8amP95y9V7+xz0AeP77XzcDSMQqVZBPS0vj77//LnD7smXLqKYfmsqlXj07KshLHv+KPEC7dvYm0K16XpBv3ZoaluP59FM7OtV4cIP8jh1BtoJxJtBPmVLWwxYREZFKokBFfvp0O3brVuLXSk6Ge+8tvJhfaGs9aME74Pff7dh94uM0YiMrY1vD0KHhHZRUiFIF+TPPPJNbbrmF5X77Ty1btozbbruNM844o8wGJ2XAf568CAWDvI/z/7lVK1+Qd5x0knu5Zk0rvoO1cQU45hg7/vyzlfJFREQk4gRU5LdudVesP/LIMv9aTkV+zZogS/CoIs+yZVCdPQzLfQaA5xqPcD+oSUQrVZB/7LHHqFatGh06dKBly5a0bNmSjh07UqdOHZ544omyHqMcDAV5yce/tT7A8oIVebA1a/z3efV4imiv79rVVs3bswfmzCnLYYuIiEglEVCRd7a+6djR/dxZhpo0sW3pMjJg8+Z8dzoV+YULIcj6XdFg6VK4htHUZBeLaM8fzTQ3PlqEvqykn7S0NH799VcmTpzInDlzSE5OpmvXrhzjVOOk8lCQl3wKrcg702Vat6bGHvfmPn1sLr2/xo1h5cogQT42Fo46Cr7+Gn76yV2KVkRERCJGQEX+x6l25eijy+VrxcdbAWHdOqvKN2zod2fLllaZ2L/fPse0bVsuY6iscnJg9fIsbuUpAJ7gX6TVKvXu4lLFlPpf2uPxcNJJJ3H77bczbNgwhfjKygnyW7aEdxxSaRQa5J1VZFq0CKjIB/uvXWhF3v8JmicvIiISkQIq8lPLN8iDu+STcwLBJzbWXWBv/nz27IFvvomeXXDXrIHzs9+jKWvZQEPe5R/UrBnuUUlFCbki/+yzz3LttdeSlJTEs88+W+Rjb7rppoMemJQRVeQln6BBPjfX3g0AmjcnNdW9q3//gq/hBPn164N8AecJU6bY68bozLCIiEgk8e0jn7TP3XK2HIO8s6hegSAP1l4/cybMn8+lb53NF1/AJ59Ex+5ry//K4H7uB+BJhpNBErVqhXdMUnFCDvJPPfUUl1xyCUlJSTz11FOFPs7j8SjIVyYK8pJP0DnyW7bY5DOPB5o0YY9fa/0RRxR8jSIr8j172ovv2GETt5x960RERKRSy8mB0aOtua6wneSysvB9Tmiw7Bdb3LZpU3d5+XLgBPmgH2fzFrzbM30B476xm/76KzqCfOKbL9OCVWyIacwLubZSvSry0SPkIL9ixYqgl6WS0/Zzkk/Qiryzp0vjxhAfH/AmkJZW8DWKDPLx8dC9O0ybBjNmKMiLiIhUET/8ADfcYM11kycHf4zTVp9IBjX+d4ddOfHEch1XsRV5YN9v8/F67aYCu+pEon376PbV/wCYdOR9HPg5BbwK8tGkxD2vWVlZtG7dmoXONhNSuakiL/kEDfLO/Pi8s+nXXAO33FL4NPfGje0YNMgD9O5txxkzDmaoIiIiUoGc93Vn/dsAXi/8+COeh//H8wzl0/gL8MyZY581H3qoXMflfJwNGuTzKvJ1ti0mnkwgSoL8G29QY/8WltOKvYOv8K3zpyAfPUq8an18fDwHnCQglZ+CvOQTtLXeqcjnbdZavToUMYOm6Io8KMiLiIhUQbt323HDhiDL3Pz3v/DQQ9QHhgJk5d3+2mv5lpIve0VW5Js2JSu5BvH799CWpfzFoZEf5HNy4MknAVup/uz28VxyCTz9dPApkRKZSrUK1dChQ3n00UfJzs4u6/FIWXOC/PbtNodJol6RrfV5Qb44TpDfsgUyM4M8wAnys2ZF7b6uIiIiVc2uXXbMzs5XA5o2DUaMAGDdEYN5iLsZV/dKGDUKzjij3MdVZJD3eNha39rr+9dZAERBRf7zz2HFCrZSh7e4jLZt4d577d+sQ4dwD04qSqn2kf/jjz+YNGkS3333HV26dKFatWoB93/22WdlMjgpA7Vru5e3b4f69cM3FqkUimytDzHI16kDcXH2Rr9pk61xE6B9eyvr790Lixb55q+JiIhI5eVU5MF2pqlfH/vgcNllVqK/9FK+O+5t7vkVTu4DZ1xXMeMqcrE7YH3tzjRa9RtHps3npW3ns3GjzQTweCpmfBUurxr/AkPJSUjxfQ7TRkHRpVT/3DVr1uTcc89l4MCBNG7cmLS0tIA/UonExeHbh0Lt9UIxrfUhrjgbE+NW5R980F34xic21lavB/jjj1KPVURERCpO/iAPwLhxtgtNw4bwzDO+qrh/rai8FVmRB1ZVt4JBN+9sANLTrZbgk5sLn34Kzzxju/RUZQsXwrRpZBPLS9zArbfax32JPiX6Z8/NzeXxxx9nyZIlZGZmcvzxx3P//feTHJAIpNKpW9e2AlOQF8qmtR7gggvgiSdsm5o//4Tff8935rt3b1stb8YMuPzygx22iIiIlDOntR78gvyYMXa8/HKoVct38t4J1xWhyMXugNnVjuQcoO36ydSunsn2vQls3Ag1agALFsBFF8G8efbgN9+EDz+ssrvqZIx6g0TgG07hunsbcv/94R6RhEuJKvIPPfQQd999N9WrV6dJkyY8++yzDB06tLzGJmVFW9CJnwJBPj3d/dkoQZB//HGYONF2m5sxA1auzPcALXgnIiJSpRSoyO/ZA9/kbc5+/vkAYa3Ip6e7nYX+Znl6sYn6JGbs4dS0n4G8efLZ2W6IT021F5o9Gw47DL7/vsLGX2ays8l+8x0AJh5yJfffH8HTB6RYJQryb7/9Ni+++CITJkxg7NixfPnll7z33nvk5uaW1/ikLGjlevFToLXeqcanppZ4z5IBA9y8PnVqvjudO2bPhqwsREREpHIrUJH/8kurALRtC927A4SlIp+a6raPB6vKb98Zw7ecDMCpfA3kBfnnnrMQX7s2LF4Mc+fCUUfZGYuTT4YXX8S3+XwV4B0/gWq7N7KZerS95VSF+ChXoiC/evVqTjnlFN/1AQMG4PF4WO/rvZFKyQnyW7aEdxxSKRSoyJeird7f0UfbscCe861bQ1qazUVbsKBUry0iIiIVp0BF3mmrv+ACX+k3HBV5j8f9es7XHzcOhgyBfftsBunXnArAUbstyO9bsBLuu88e/MgjNse/cWOrxF98sVXrhw61in0V2Vp726iPABgTczGXXB4f5tFIuJUoyGdnZ5MUMLHW9pXPUrWtclOQFz8VFuRjYtReLyIiUoX4V+S3rU2HCRPsSl5bPcC6dXZ0Zm5WlPzz5B96CN55B8aPty6B7zgJb1wcTfYs5jh+4OQXTrOpAYcfDldd5b5QYiK8+y6MHGll/jFj4M47K/abKY3cXBJ/HA/ArmPPrNCOCKmcSrTYndfr5fLLLycxMdF324EDB7j++usDtqDT9nOVjLPl3ObN4R2HVAoFWuudye0hrlif35FH2pnypUutja1hQ787e/eGSZMsyF99dWmHLCIiIhXAvyLfYuVP1lXXrBl07gzYSvBLl9r9XbtW7Njyr1zvHNets4p8FmlkHHY0Sb/+yA+cAFthc1xjPjz6Y27Kvy+bxwPDh9uUgTPOsNXsTzvN5gxWVn/+SY30zeyhOq0uPTLco5FKoEQV+csuu4z69esHbDX3j3/8o8AWdFLJNGhgRwV5IUhF3gnyLVuW6vVq1YIuXexyofPktQWdiIhIpeb1Bgb5w3d8axcGDfK11c+da49r1Mj9eFlR8gf5nTvtuHy5uxRP7qNPsK7TAHKIYQ/VGZT9Jc99fkjhL3r66XDDDXb5iisqdYt91pf27/E9Azj8mIQwj0YqgxJV5N94443yGoeUJ6civ2lTeMchlUKhQb5Fi1K/5jHH2Jv71KkweLDfHU6QnzfPvnC+qTkiIiJSOaSnQ06Oe30QeUH+5JN9t/35px179KjAgeVxgvzWrXYywZkG8NdfdoyLg+QjezL58Yl0PXUbHrxsoy7VNgS+zpw5Nt++adO8G554Ar76CtasgTfecIN9JbP/s2+JB36pMYizSld7kQhTooq8VFGqyIufAq31K1bY8SCCfN5Ctr52O5/mze2dNyvL3b9VREREKh2nGh8TA0c2WEZblpEbGwfHH+97jBPke/as+PH5z5FPT7e16sAN8rVrW+NAw4awnTpsw56wb59NCQDL6ocdBiec4LdYfUoK3HGHXX7sMfeFK5Pt26k+/zcAdh5+slarF0BBPjo4FfmtWwNPtUpUCqjIZ2TkLUvLQQV556z22rX57vB41F4vIiJSBTgV7tRUODPJFlXb3vEouyHPrFl2DGdFfts2t60e3I8xtWrZMWCtnjwb8qrys2dDZqYVHhYv9nvAVVfZ5+WVK+HDD8t24GVh6lRivLkspAPtBpRucWKJPAry0cBZVjQ3N/jmmxJVAoK8s2J9tWruqe5SOCRv+lmBIA9ukJ85s9SvLyIiIuXLqcinpsKJ6V8A8OHuk31brWdmwvz59pjKFOQdTpCvX983pd93dIK8f+fgjz/6PTk5GW691S6PGGGfmSsR7+9WDPmNw+nXL8yDkUpDQT4axMW5v/00Tz6q5eTYGzHkBXn/tvqD6NNygvzOnW77mo+2oBMREan0nCDfvNpWum61lPvU6nMZOhSmT7cW9qwsqFnzoJr4Sq24IO/sMx8XB/ffD9dcgy/0OkF+2TL38QFBHmxufFqafaPjxpXhyA/egakW5GfF9PF9rBJRkI8WmicvWCe9IzmZMlnoDuzsfY0adtnZX9bHecdZsMCdoC8iIiKVitNaf0rmWGK8Oexu04MmR7cG4OuvAxe6C8ccbadxcOvWoivyAPfeC6+84hYaNm60o39FfvJkv3nyYCF+6FC7/PDD+e6sOAcOwO23w88/593g9eKZZcWQPR36uGscSdRTkI8WWrleCNxVJSmJMgvyUER7fZMm9vOXk2NLxYqIiEil41TkT9z1MQCpVw7m6qvttq+/hs8/t8t9+4ZhcLhBfsuW4oO8o1EjOwaryG/ZYjWGADffbJWOP/6ASZMOdsil8vnntpD+KafAkiXAihUk7dtOJvE0P71rWMYklZOCfLRQRV5wC+KxsdZ6drB7yPsrNMj7L3inefIiIiKV0q5dUJttdN+WF2DPO8+3hfyff9oObQCXXx6e8TmL2O3e7VbY/Tmt9f78g3xGhrs0UNe8PFygvb5+fevJB6vKh8Hff9txzx7b0jfjZ2urn0M3TjglMSxjkspJQT5aqCIvuBX5stx6zhHSgneaJy8iIlIp7d4Nt/IUsd4c21e2bVvq14c+fex+rxcGDID27cMzvtRUSMzLsQErzucJVpF3wv/GjfaRJzcXqle3gAyFbKjzr39ZtePHH+G338pk7CWxZo17ee5c+Op+G+TsuD4cfniFD0cqMQX5aKGKvJBvxXqomNZ6gF697KggLyIiUinFrVzG7TxuV+67z3f7qae6j/nnPyt4UH48HvfjbKhB3r8i78yPb9PG/dhTYF0fsD11hwyxyyNGHMyQS8XpGjjrLDvWXWFBft+hfUhIqPDhSCWmIB8tnN98qshHNae1Pikp74rTm1ZRFfm//oL09IP+WiIiIlK2Tvv+FhLJZHmbgXDmmb7bzzoLYmLso8Lpp4dteIBbYV+0yI7x8e59xbXWO/Pj27a15XugkCAP8O9/25mDceOCnzUoR05F/oYb4Owzc+nJLADqDupToeOQyk9BPlo4rfWqyEe1gNb65cvtSo0awd/9SqjIIN+4sb2b5ubC7NkH/bVERESkDM2bR9c1X5NNLL9e8EzAsvRdu8Ivv8BPP+WtrxNG+RtM27Z17yuqtX7rVqslOM9xgvz69YV8oXbt3FaEV189qDGXlBPkmzaF5/61ihrsJYMEDrs0THMapNJSkI8WqsgL+VrrnX1kunUrk31kigzyoPZ6ERGRymr0aAC+4Exy2xYMjIcfDs2aVfSgCnI+zjo6dHAvBwvydeq4Jx9++cWObdpYfQFsQbk9ewr5Ys6S/W+9BZmZpR5zSeze7W4D2LQpNNkxH4DMVh1od2h8Ec+UaKQgHy38K/Jh2hdTwi+gtd5ZQb5nzzJ5bSfIb90auM2dj1auFxERqXz274d33gHgFa4lNTXM4ymCU2F3dOzoXg7WXBgT4z5n4UI7tmtnC94532eh7fWnnmrdhFu2wBdfHNS4Q+VU42vVsjEybx4ANfp1qZCvL1WLgny0cIL8gQNFnHqUSBfQWj/L5lz5KuUHqVYtdzX8oG+KWrleRESk8vnkE9i5k7XxLZjIiaSlhXtAhctfke/Uyb0crCIPgeG/fXvo29cuFztPPi4OrrjCLr/2WonHWhr+bfUAzLeKPJ07V8jXl6qlUgT5F154gRYtWpCUlETfvn35/fffi3z8xx9/TIcOHUhKSqJLly588803hT72+uuvx+Px8PTTT5fxqKuYatXsD2iefBTzBfnEXLe1vowq8h5PiCvXL1oEe/eWydcUERGRg/TeewC8n3w1XmKqVEW+c2e45BIYOtRvR558nAXvwBahd1rti50nD3D55Xb8/nvYvr00Qy4RZ8X6AkG+iyryUlDYg/yYMWMYPnw49913H7NmzaJbt24MHDiQzYWEzV9//ZWLLrqIq666ij///JOzzjqLs846i/nOD7qfzz//nN9++43GzkSYaKd58lHPaa1vlbPUwnRycuAEs4PkvPE429MHaNjQ3jW14J2IiEjlkJ3tmzz+ebYtSV+VKvK1asG778Lzzxf+HCewH3GEu6UbuPPkC63Ig62M16UL5OTAl1+WZsgl4lTkmzUDsrLc5flVkZcgwh7kn3zySa655hquuOIKOnXqxKhRo0hJSeH1118P+vhnnnmGQYMGcfvtt9OxY0cefPBBevbsyfP5/gevW7eOG2+8kffee4/4eC0OAbinMZ0txyTqOBX5jul589S7dy/TJWgPPdSOQc6rGbXXi4iIVB7z5sHevXjT0vg93d7EK3NFPn+Qr1mz+OcMG2ZV+zfeCFzbt9jWesc559jxs89CHWapBbTWL1liYb5Gjcqx0qBUOmEN8pmZmcycOZMBAwb4bouJiWHAgAFMmzYt6HOmTZsW8HiAgQMHBjw+NzeXSy+9lNtvv51DnWRRhIyMDHbv3h3wJyI5vUVF9hBJJHOCfJvdefPjy6it3tGtmx3nzCnkAU57vRa8ExERCb+ffwZga9sjyCWWxo3dZZUqI//W+piYvAXhinHooVa1b9cu8PZgQX7RIrd70efcc+04YUK5Tw0MaK33nx9fBrsLSeQJa5DfunUrOTk5NMh3eq1BgwZsLKRqvHHjxmIf/+ijjxIXF8dNN90U0jhGjBhBWlqa709T38SUCOP0EG3YEN5xSNg4b06td+RVxMtooTtH1652nDOnkM0RVJEXERGpPPKC/G9xRwG2UHtlzow1arhz4WvWPLixOh+LnfrWp5/aKvjO+nY+nTvbnnUZGfDtt6X/giEIaK3PW7FebfVSmLC31pe1mTNn8swzz/Dmm2/iCfF/91133cWuXbt8f9Y4/4sijSryUe/AAejEAtpsmGI3HHlkmb7+oYfaGfItWwpZisE5cbB4sXZPEBERCSevF6ZOBeDdlRbkTzstnAMqnsfjVuUPdi6/f0U+Jwf++1+7/tFH8Pff+b5oObfXHzgAb75ZSEVeC91JIcIa5OvWrUtsbCyb8n3i37RpEw3zL0uZp2HDhkU+furUqWzevJlmzZoRFxdHXFwcq1at4rbbbqNFixZBXzMxMZHU1NSAPxFJFfmot2cP3McDxOC1N6X8fWYHKSXF1oWBQtrr69e3dyev1101X0RERCreihWwYQPeuHjGbexDYiKccEK4B1U8pzE3lPnxRXGC/IYNFt6dfea9XnjxxXwPdoL8V1+58xTL0JAh1gmQmWkL+B1yCKrIS7HCGuQTEhLo1asXkyZN8t2Wm5vLpEmT6NevX9Dn9OvXL+DxABMnTvQ9/tJLL2Xu3LnMnj3b96dx48bcfvvtTJgwofy+mapAFfmol7h0HufzsV25//5y+RrOPPm5cwt5QDS117/zjs03eOklO90vIiJSWfz6KwDrG/fmAMkcd5y7U3FlVlZBvkED6yLMybHt6wCOPtqOr70G+/b5PbhPH0v+e/dCvhwSVG4u/PADPPkkvPVWIfMNzfLl8PHHVvi/7z5bRig+c5/bFqAgL4UIe2v98OHDGT16NG+99RYLFy7khhtuYN++fVyRN0FlyJAh3HXXXb7H33zzzYwfP56RI0eyaNEi7r//fmbMmMGwYcMAqFOnDp07dw74Ex8fT8OGDWnfvn1YvsdKQxX5qHfGrPsBWN13cLm1avnPkw8qWoL8/v1w6612Rv2f/4QBA2z1WRERkcrgr78AmE13AAYNCuNYSsBp2j3YIB8XZ3kbYMcOqF0bxo6FVq1g50677BMTA2efbZdDaa+/4gprb7jtNtuL/sEHC33oqFF2HDTIaiwtW+L7t6FBA6hXryTflkSRsAf5Cy64gCeeeIJ7772X7t27M3v2bMaPH+9b0G716tVs8AueRxxxBO+//z6vvPIK3bp145NPPmHs2LF01tmq4jkV+W3bbMEOiXiTJsFhh9kuc5m/z6b/1s/IxcOGa+8rt6+plevzvP++/V+rW9dKHJMn24q3IiIiYZSbCw89BCsnLgFgYa4Vutq0CeeoQud8nK1d++Bf67DD3MsTJ9prOtMLli/P92Cnvf6LLyA7u/AX/eILePttC//OTlv33QevvFLgofv3g7Pj9j//6XeH01av+fFShLAHeYBhw4axatUqMjIymD59On379vXdN3nyZN58882Axw8ePJjFixeTkZHB/PnzOeWUU4p8/ZUrV3LLLbeUw8irmNq1ISHBLmsv+Yj39NP2/vHHHxaq99/5AABjuIDqfYvflrG0nIr8/Pn2oeDTT/M9wAnyS5bArl3lNo6w8nrtHwDgzjvhmmvs8ttvh21IIiIiAC+/DPfcA3tmLAZgzn5bLyf/Hu2V1WWXwYUXwg03HPxr/d//wdVXw9q17o68TsW/wEflo4+2k/PbthXeXr9zpzuw22+3swP35RVPbrsNtm8PePjYsXZT8+Zw8sl+d/hvPSdSiEoR5KWCeDzuaUy110e8n35yL3dhLmk/jiWHGB7gvnLdI7ZpU3uDjYmxs9kPP5zvAXXrgrPwZKQuePfTT/YmXK0aXHWVrWIDdpZ+x47wjk1ERKLWnj1w773gIZe2LAVgxm4L8pV5/3h/LVvCBx+UzQ66AwfC6NHuwnfgBvkCu+/ExdkHHGDTo2/w2WewdWu+x/zf/9ln7Hbt3AB/333Wrrh3r3uSP8/Spe44YmP97tBCdxICBfloowXvosbu3e7l67EJWJ9yLktjOpRJO1phPB57g3Uy+qJF7hw0H+fd948/ym8g4eScRTn7bJvE1727tcdlZsKYMeEcmYiIRCGvF777Di66yMJnU9aQRAa5cfEsyWoBVJ0gX94KrciDb5P5tB/HcvW526lf3+a45+bCbWcsJfuZ5+1xzz8Pycl22eNx97Z75hmr2ufZts2Oderk+zraek5CoCAfbbTgXdRwgny7xnv5B+8CMIrrqVs331nfctKxo528Tk+3PVoDONNn8lbMjTjOmfQePezo8bhV+fffD8+YREQkao0ebVXfr7+26+2w+fE767Qhl1hSUyEpKYwDrESKDPI9erC7VTeSyOAiPsDrhccftwXqj/ryDuJys9h7zClw4omBzzv7bDj0UPtw5re3ndNpHxDkt251v3inTmX2fUnkUZCPNmqtjxp79tjx+pofksoeVsS14UeOq7A5cPHx0Lq1XV60KN+dxxxjxylTgpTrI0CwRWqcRXJ++y3fnjYiIiLlyynwHnMM/PwznNXRgvyqxKrVVl8R/IN8gV3jPB7m9bKq/O3VXqR2tQz+/humDhnN2Ywlm1jGHvl4wReNiYE77rDLL7/s25LWCfIBnZLOP1arVlC9etl8UxKRFOSjjVORV2t9xLOKvJdzt1pb/YvZ1wKeCn2z7tDBjosX57ujZ0+bP759OyxYUHEDqgj798OyZXbZP8i3bAnNmtkWdL/8Ep6xiYhIVHLmcp99Nhx5pFuRn3tAQT4/p+CRnm7T2vP7ofE/2E4tWuz7i0+b3MjpjOPuDbYN9r38Hx/NL6SKPngw1KoFq1f7drFxWusDgvzvv9vR2QZIpBAK8tFGFfmI5PUWPGu8ezecwCSabZ7JfpJ4k8uBin2zdoJ8gYp8fDwccYRd9l+VrwrxeuGNN+x9uXt3+OabvDv++su6DOrWDVwC2OOB446zyz/8UNHDFRGRKOYE+bp17dgsw4L8b9ur1or1FaFaNahRwy4Ha69fuLkOF/M+Xo+HY5eMZhxnkkgmX8adzQjuYvJkO2dfQHKyLbkPVpWnkNb6KVPsePTRZfHtSARTkI82Wuyu8ho1yrYq+/rrQt4BCnfnnfYm8Pffdj0nB/bt83IftuXcy1zHVuoBFftmXWiQB+jf345VNMgvXgxXXgmffGLb+w0ZAps3E9hW7/EEPskJ8j/+WKFjFRGR6JY/yDfcZUF+QbYq8sEUNU9+5UqYwCDmXfIoADtiavMS17PkP29Rp46HPXtg+vRCXvjaa+341Vewdm3BinxOjs19AHcaokghFOSjjVrrK6fp023f0UcfhdNOsw3g09NDeuratfDkk7armbOt6d69cCyTOZqf8SYm8hh3+B5fkW/W7dvbscggP2VKkElold/mzXZs1Ai6drX2uBtvJPj8eIcT5GfODNxWQEREpBxt2WLHunWBjAxSt68EYAkK8sEUFeRXrbJj5s23w6pVzPhyI3Ovf4lrb6vBCSfYfd9/X8gLd+xoAT03l9xXX/PtSOuryM+fD7t2WUuAWuulGAry0cbZKHPrVsjICO9YxDVypB07dbJf3lOmwPnnh1SZf/55yM62y86by+7d+KrxXH0N+1Ib+x4fjiC/bp27+J5Pnz62RO7mzYUk/crNWa+ucWNrsY+NhY8+gl2/FBHkmzWzFQBzcmDq1IobrIiIRC2vN19FfvlyPN5cdlODTVibnlrrAxUW5DMy3FpYixZAs2aceEo8L71kH9+cIF/kUjjXXWfH0a8S47UPcLVq5d3ntNUfcYRt/SNSBAX5aFO7truv5dq14R1LFPB64bnnYNasIh60YgV8+qld/uADa61PSrLjffcV+fp79/qmWQG2fgpA9qSfOJafyCABz53/5pBD3MdUZJCvXdv9egUWvEtMhH797HIVbK93FsCpXt3W7nM64BIWFRHkwa3KT55cruMTEREBa/A7cMAu160LLLG2eqvG2xQwVeQDFRbk16yxY0pKkL3fcacUOoWVoM49F+rUIWb9Wk7mW6pXh4SEvPucIK+2egmBgny08XigaVO77Pw2knIzcSLcdBP06lVE9/gzz9jiaCedZD3aRx8Nb79t9z36aBETrWx+9s6d7nUnyNd+/v8A+KjGVXDIIb5GDKj4s+6FrlwPVXqevBPkq1WzY/36UIvtJO/Ke9c/9NDgT3QWr9HK9SIiUgGcanxiYt57VkCQN6rIB8of5DdvhhEj4M8/7XqLFgWXwQH3I/bq1UV87ktMhMsvB+A6XnZPCHi9breegryEQEE+GinIVxhnEROAGTMKedB339nxhhvc2wYPhksusYB/2WWFzqdevtyO3bvbcdUqYPp00mb+QCbxvNvkToCwVeQB2uV9Tsj73BDIP8hXsXny/hV5gHr1oCUr7EqjRoXv/XrUUXacMcO2qhMRESlH/m31Hg++N+SVCe19j1FFPlD+IH/ffXD33XD11Xa9efPgz2vSxP6OMzLcdQmCylv07hS+oVfKQrtt4kTYtMl69Hv3PvhvQiKegnw0UpAPi08+CXJjVhYsXWqXe/UKvO+552wC9uLFhc6Xd7Yt6dnTjmvXQu6YjwEYwwWk120GhDfIt2xpx6BtZn37Wj/Zhg3u3utVRLAg34KVdqVFi8Kf2LKl/btmZbl7xYqIiJST/CvWO0F+S223Iq8gHyh/kHd2jXXqKoW9zSckuBtEOV2SQbVrx+reZxODl+t3jLDbnnnGjldcYVMsRYqhIB+NnFSnIF/u/Auun34apOi8bJmtVFe9emDaBlv55IsvbCLWhAkwfHiB13cq/oceaoutZWdDzrivABjLWaSm2v1Oa3316vZyFcl5s1u5MsidyckW5qHKtdfnD/L164cY5D0etyrvbDEjIiJSTgoL8nsbWZCPi/NbbE2AwCC/cWPBrsKi3uabWQ2l2I/Zvx77HwCO3/Q+jBsH33xjnxFuvLF0g5aooyAfjVSRrzD+QX75cttvPMBff9mxY8fgk61697YF8MCWp8+3QJoT5OvXt/MAbVhK/PLF5MTGM5ETqVHD7nfOEYTjjHuRQR6q7Dz5UlfkQUFeREQqTECQ37XL2reB7JZtAftsEOwjSDRzgvymTe7Hk/h49/7CWushcJ58URZV68V4BhLrzYEzz7QbTz0V2rQp3aAl6ijIRyPnN4xWrS93+beC//LLfA9wgnynToW/yBlnuFuVXHttwNkBp7W+dm17UzmVrwFY1fwY9pDqq8j372+LpYfjJK+TadeudbfJC1BF58kHC/LNyZs/UNQ7PLhB/tdfbSs6ERGRchIQ5J3pfA0bktbUPiSorb6gevXs5EZODrz1lt129dXu23thG9OAW5EvLshv3w7/5lE218kr5sTGwp13HvzgJWooyEcjVeQrTP61zGbPzveAhXkLnHTsWPQLPfqoTbpauhSefNJ3s1ORr1PH3jhOw9rq5zc/DcAX5KtXt/ldt9xS8u/hYDVsaHPGcnIK+ZHr18/6+tasKaJsX/k4+8iXqiLfpYstZrN7N8yfX15DFBERCQzyTo94u3a+udxasb6g+Hh3k5lvv7XjCSfAjz/CpElF119KEuTn0o137/4L9uyx8v+RRx784CVqKMhHIyfIb99esGQsZcoJ8s6Z27lz8z0glIo8QFoaPPGEXX7qKV+K9K/It2+wk/5Y/9cfDSzIO6314RQT457BXrECXnrJCtE+1apBnz52uQq11+fffq5eXa8vyGc1aVH0k+Pi7AQGqL1eRETKVUCQd/aCbdeOk06yk9BOV7cEevnlwDXnjj7a1qs9/viinxfqHHmnGFO7NvZhItjG9CJFUJCPRmlpbsJTVb5cOUHeWc9t+XI3AJKTA4sW2eXigjzYyvWtW9tv/tGjycy0E7hgv/uP2vI58WSzskZnlntsfpVTkQ83Z+X6V1+Ff/4TLrggXxd9FZwnn7+1vnbMTlKxf5CtKc2KfwHnVL+zZ2xpPPOMnRA44gh4/PHSv46IiESswiryPXpYEdh/91txdegADz9sl7t2DX0KQqhz5P2LMSKloSAfrdReXyGcIN+smbWYe72wYEHenStX2kajiYnFt2KDVXH//W+7/MQT7NiYAdi0qrQ06Dz/QwC+TLnQF/ArS5B3vj1nC761a+2khk8EBPmY1SsB2EgDtuxNLv4FnHnyU6eWbm2AWbPg1lvht99g2jS44w6YPr3kryMiIhHN2c+8Xj0CKvKgRe6Kc/PNMGaM/QmVU5HfsMGWNjrrLPu4l5//9EiR0lCQj1YK8hXCmbmQnGxncwHmzcu702mr79DBFjgJxZAhtgf5unXEjHgIsC1jYrdtps6cSQC8vu8C3z6nlaG1Htwgn5Xl3haQ2Y880nrwV6yoMj+T+YO8M79/JS3YvDmEFzjsMDs5s349rFpVsi+emwvDhtkJgNNPh7PPtttvvtnuExERyeOryNfOdTsBi1ubRwD7aHL++fZRLVR167ot+aNH207CX3xR8HGqyMvBUpCPVgryFcKpyCcnB5knX5o308RE5l75NAB1Rz9MD2bZG8Cnn+LJyeEPejN7bxvfmnGVrSLvb8oUvys1akDPnna5ilTlCwT5vDC+kha+6keRUlKgVy+7XNJ58u+9Z1X46tVh1Ch44QW7PH26u12hiIhEPa/XDfIN9q+0DyaJidCqVVjHFck8Hrcq73j99cDrOTmwc6ddVkVeSktBPlopyFcIJ8inpLgVeV+Q37DBjs4m71jF+qWX3LbzxYvh998DX3PwR4P5iMF4cnL4mMGcFTMOHrLq/Hc1LwDceVmVMcgnJtoxIMiD214/eXIFjOjgFVaRX0Xz0II8lG4/ea/XdjEAuPtu69Bo1MiddvHKK6G/loiIRLRdu9xdTmtvzOsEbN/eOsKk3DhB3gnp330X+JF75053Vl2tWhU6NIkgCvLRyvkNU4W2+6qK/Cvy/kHe68VWmIGAfV8+/tgWg7vlFnvMccdZ1nPmUYF1Yg/lBTYkNqc1f/P4kjNh3Tro0IHZva4K+PqVpbXeWewO4JprbCbBypX5FoJxloGdNKnS7yfv9Rbcfs6/tb7EQb7AWY2Cpk2DCROwfQQXLLAVbv/5T/cBQ4bYcepUQuvtFxGRSOdU46tXh4SleYv0hLLArhyU44+3zzovvWR1Cq/X5sofdpi9nzsFm7Q02+pOpDQU5KOVk6xWrAjvOCKcf5Dv2NF+qe/YkXdWNkiQd/aZnzfPAvuGDVald87iZmRYJXgr9ejL7/zIsXZHz54wZQpNuwae1q0sFfkGDezvAOCcc9yO8oD8eswx9m62ciX8/XdFD7FEMjMhO9suH1RF/phj7Idi4cIi/y9u3Wr71556Khx47Bm78fLL7ROAo1kz6N3bPi2MG1eSb0dERCKU0+TWqBHu2jyHHhqu4USNO++0OfCDB8MVV9hts2bBH3/AbbfB22/bbQMHhm+MUvUpyEcrZ27U6tVuz5WUOf/F7hIT3e3SH3iAoEF+4UI7rl4Nf/7pvo5TkfevzK/JqM+JTOSZc6dYa3a9egVOsleWIO/xwFNPwfDhll2PPNJunzHD70HVq7t7q3//fYWPMRQHDljB25nXBnn7yHu9vtPry2kdepCvXdv+QiD4Sjh53nzTTgo1y/mbxIlf2Y033ljwgc6id599FuIAREQkUu3YYTOwAK67DjfIqyJf7jwe9zPYxRfDPffAXXdBQoJV5F991e676qrCX0OkOAry0apxY6t+ZmVZW7aUC/+KPMDIkfbL/fXXIXNtXvuzX5B33mO9Xvj6a/d1nADvtMg5cohjV9ejfV8g/3tzZWmtB/sQMXKkFaCdZQEKBN4BA+w4cWKFji1Ujzxiufu55+x6UlLehgNbt8LevXg9npK11gOceaYdx44NenduLrz8sl2+gjfweL1w0kk2xzG/c86x4/ff28RIERGJWvffb++zHTvCTcNyVZEPk/h4ePBB25P+kkvstowMaN7c/dgjUhoK8tEqNtZ+g4Da68uR/2J3AEccATfcADHkELvTWUa2ge+x/v8U/t3RwSryDv/VTv0XwE9Orrxr2dSta8f8JyY48UQ7/vBDpewUcTr+f/3Vjr62+rw7MuodQiaJpQvyU6cG/Qf+4QdYtgw85DKEvF48p08vvw4d7IcgKwvGjy/BIEREJJJ4vdbNBdYRF79htbUJJiRA69ZhHVs0Gz7cvXzFFba9nUhp6ccnmmmefLnLX5EH+yVel63Ekmvl+bxUu3hx4Bpv69e7lwuryEPg/qO1akHDhna5srTVB1NokO/d2+Z979hhk8kqGWeBuyVL7OgL8nlt9TnNbMpKiYJ8ixa2EmJubmAbRp6nn7bj6dUn05zV7ItLY2f/M3nnHXfl/ACnnGLH774rwSBERCSSbNwIu3dbUDzuOGyRVNCK9WHWubMt+tu6NVx7bbhHI1Wdgnw0U5Avd8GCfN260ACbH++tW9f3hurMjw+mqCCff/9Rp72+MrXV51dokI+Lc1ev/+abCh1TKJzg7MxGyV+Rj2vfipgY+/f64YcSvLAzt92ZNJfnt98s28fGwqMd3wTg6xoXcP+jyQwZYqvhFnDSSXb87rtKv/q/iIiUD+eEc8uWVoT3BXnNjw+7V16xTrtGjcI9EqnqFOSjmYJ8ufJ6Axe7c6SmQuMYC/LZdQrOj3dCrr9QK/LgttdXyYo8wBln2LGIxd/CxanIO/JX5BM7tOL66+2mG26wOXAhueYa+6Q1dWrAnvL33GPHGwdvpN28TwB4ad9lvq75gO37HEcfbSsrrl0LixaFOACRyKRzWRKtFi+2Y7t2eTc4q8t26xaW8YhI2VOQj2YK8uXKP8T5B3mPB1qmWJDPSKvvu92pyDs51l+oc+TBPdnuvzNZZeME+fR092SHz2mnWS/gn38WklTDp9Ag70yeb92ahx+26Q1LlthCQyFp0sS2kwNbDQf48UeYNMkWyXkg8SFiDuznNw5ncmY/3we07duDvFZysrsSvtrrJYqlp1tmufDCcI9EpOI5FXnfuqi//WZHZ3cYEanyFOSjmYJ8uXLa6sFd7M7RPMmCfHqNBqxZA+++604JP+MMC/v+8lfkmzVz78tfkR88GAYNgmHDDvIbKEc1alhAhSAnJ+rWdfenq2RV+fxBvlq1vAtOkG/VirQ0eP55u/rII/DhhyG++B132AmMb7/F+8OP/Oc/dvOdF60i9X1btv6lQx4C3B+OoEEeAtvrRaLUtGkwbx58+qkq8xJ9nCDfrh02H2zNGnuP6d07rOMSkbKjIB/NnCC/fr1tkC1lygnysbFuaHU0ibet5/YkN+CGG+DSS93zKT17uhsKOAvL5g/yhx/uvnb+Fvp69eDbb92dyCojvzX+grfXOyu5l3eQ37ULpk8PPOtShKAV+QMH3EnzrWyxu3PPhX/9y266/HKYPz+EF2/dGq68EoDMcy5g7bTV1E3ay3+WX2Gr0J9wAtu6HR/wlEKD/MCBdpw8uQT9/SKRZeZMO2ZnazdGiT4BrfVONb5rV79WMhGp6hTko1ndulZS9Hph1apwjybiBFvoztEwb478joQGvjfb2FgrRB9yiNsKd8QRdswf5E84wdaFa9OmYPW+qggpyP/0UyEPOEh//WVb3dWpY2dFWrWCZ56xleOLEDTIr1xp/4dq1AhY4OCRR2x/2IwMeOedEMf1zDN4u3cncdcWZtCbhUndSfzlR/t/+vjjtGkT+PBCg3znztbfn54Ov/wS4hcXiSzOlGAo4U4SIlVcVpbbKNa+PW6Qd6oAIhIRFOSjmcej9vpyFGyhO0f9XAvy2+IasMkuMn++rXPm8dgWdYMGwY032n07d9q26k6g79rV3pcnTCjf76E8FRnk27Sx1oTs7BL0pofoxRehRw/4/nv7S61e3fbpueUWK59nZwd9mtdbcLu36tXxLXRHq1YBZ1ViY93t3kP+d0pJYc2zY1nDIdRnC3V3LreTDT/+CD160LZt4MMLDfIej9rrJeopyEu0WrHC3spSUqBxY2yeCWh+vEiEUZCPdk7vthNGpMwUVZGvnW3pfXVGA/bssdv8tyE56SRrj+/Rw657vba1uhN669aFXr3cFvyqqF49OxZacL/sMju++WbZfdGJE23xgMxMOPVUWLrUzo48/7wl73fesa8bZEJtZqblfn/VqxMwPz6/AQPsOGeOnSvIz+uFxx8PnEEwZ2dz2rOYq1v/CM89B7//Dn36APZv7v+lduwooolAQV6i2LZtgeeng/6eycmxqWWLFhX8zy1STnJzy3/NBmd+fNu2EJOd6c4zUUVeJKIoyEc7Z18S57e+lBknyOdf6A4g7YAF+bmbbPu5xMTg28XFxbmrz69f71aEg21RV9UUWZEHuPhiW1xg5syQJpm/+ip8/nkRD9i0yRYj8Hptu7cvv7TKf0ICDB1qK2LFx8P778Prrxd4ev62esgL8s7YfHv8uOrXt8YCsHMI+U2damvcXXCBG/QXLID9pLC/77F20sHvBMHhh1sud7K511vE3F/nLMKff8LmzYU8SCQyObnFUaAi/9ZbdjaxSRPbs7N2bfuP6OwDKlIODhywnWXOOivfHWWc7ANWrJ81y75w7doUaOsSkSpNQT7aKciXm0Ir8rm5VNtnwWrGGgvyDRoUPtfd2V7O+SeKja3cW8uFqtggX7euVc2h2Kr8X39ZNh8ypIjPQ9dfb2G+c2ebD5//L/zMM+Ghh+zyLbfY3Hc/hQZ5JzE45fJ8iiqMO+E+IwOeesouL1hgR2cbwfxOPNEaaZwV8wttr2/QALp3t8vff1/Ig0Qik39bPeQL8jfcYNNoduywVbxTUmD3bvjoI+jSBe6+W8vcS7lYsMAWofv227wfsXfftcVx0tJsXZNrry34w1sKixbZsW1b4Ouv7cqAAVV3UR0RCUpBPtopyJebQufI79hBbK7Nw5651vaRb9iw8NdxgryzKF6dOpHxXlxskAd3b/W33ipyZwVnDvrevYH70mdlWUs8n38OY8dai8P77wef7wC2OMGRR9oL/fOfAXcFC/KpSZm2vxUUGuSdBeS/+65g9+6kSe7lF1+0XOEE+UMPDT5Eh7PtYKFBHtReL1HLOb/m/Ff3BflZs2DUKAvwDz5ov1d277bdK845x/qeR4yAhx8Oy7ilivN6i5ymsWaNHWOz9pN76WXWJfbrr7Bnj51oHj3aplKdc469Z23YYB1VmzcX88s+0Jw5duzSBfjqK7ty2mml+55EpNJSkI92TpBfuVLbVJWxQivyeW3O26lFFgmAFU8Lkz/IR0JbPbjfR5GLUJ16KjRtaml/zJhCH+bftr5jhx29Xvs81KfDHrzOqoF33JH3yaYQsbHWVh8fbyUTv1XqggX5hlvn25mCWrXchSPzOeIIqFnT/tkff9y9ffdum/4O0KyZnTt44QVYuNBuK/MgrwqjRBGnQ/6oo+zoO2H42msA5J43mDea3MPy1fH2//6ww2x6zTPP2OPuuQfefrtiBy1Vl9cLb7xhC9vExdkZ3CAnUC3Ie3mNq4h97207oXTffTZFa+JEuOQSO1P/+edw9tm2Ul2DBvanTh37zHb77UXup5idDXPn2uU+jdbC7Nn2moMGlcu3LiLhoyAf7Ro0sG2zcnPdRbukTBQa5POWnt+Km8ijOcgXWZGPi3Mr4889FzSMZmTYdukOJ9ju3GlVidNWPItn3TrrR7/nnuIH1q6dzU0HuO023yr2zvoEToAGaLh+ll3o2bPQNomEBHjySbv83/9a4Q9gyhQr3LRuDf/7n932xBNWIExMDLp2XoCQgvyRR9oP4IYNIW5mLxIZdu+2o7OV55Yt2C/l994D4I8uV3HllXDTTfmeeNNNcOeddvnaa+GPPypkvFLFvfYaXHmlWwr/7jsL8zfdlNcWZtas9nIrT3ExH+CNi7MTxvffb2duBwywVvt582zLmmBvAkuX2htFjx7umeB8liyx95Fq1aDFgry2+sMPd1eYFZGIoSAf7TwetdeXk0IXu8sL8ttxE6GCfBGuusqS7cyZQT+4/Pqr+3cNbkV+40ZIYR+38DQA889/gGMGJoeWZ//7X0vKCxZYGy5uRb55cyvYA9Remde/66xoV4jLL4fzzrNzAkcdZZ/3XnnF7jvhBDj3XFvs0CmydOhgRcKihBTkk5Lg2GPtstrrJYo4J96cRpktW7Aq565d0Lw5s+ucAFguKuChh+D00+0s4TnnaO86KVpGBvzf/9nlYcNsgdGhQ+36c8/ZZ6xbboF//YsbXuvNk9wGwNpbRrpdU/4OPRSefdZ2E/J63T+7dsEnn0CLFrYlw3HHBZ1PP3u2Hbt1g5hv1FYvEskU5EVBvpwUWpHPS17bqOO7KZQg74S8OnUKf2xV4h/kJ092P3wUUK8eXHihXX7uuQJ358+nTpDftAmu5lXqsZVddVvxf4suYOpUmyJfrFq1bP4s2MJX69f7gnz16m73ZO0VRS905/B4LLgPHGhh/o03bNF8sCJMSootmO0orq0eQgzyoHnyEnW8XvfEW4sWdtyyBdteEuCKK9ixyz7+rF8fpNEnJsYe264drF1rJxM1NUUKM3q09cw3aWLzp7p3ty1Nv/jCflGvWmVTNkaOpOWOWRwgkUf4N3+femPJvk5qqp31/fNPOwOcnm7Tz/J1U/75px1PaPk3jB9vV04//eC/TxGpdBTkRUG+nBS62F2Qinwoi905mjQpg8FVAs73lZVlhYV+/dx5fQU4re4ffWQJ3c+PP9oxJu+3mS/Ir83iXzwBwIRu/2b+ojjAPlOBrS1U5NbR110HffvaA2+6yRcMqlWzz0aL5mWRsDBvwMUEebBzA+PHWwfBtdfaZ72jj4aTT7b7nXX9oPAV6/2VOMhPmRLYuiASoTIy3P/bTkV+5+ZM+z8AcM457NxpF/ftc9vwA6Sl2e+bhAQ765bXmSMSICvLXRjxP/+xLijHGWdYwP/4Y5si9q9/8d/az3MIa7mLR9i9p5Sr1tasCZ99ZiX3zZvtTSTvcwW4J8UvXX6/nTk+6aSi14YRkSpLQV4U5MtJcRX53fElq8iDrXtz7bVlNMAwyz/l4MABKzYE3fK8d2+b45eVZdWPPLm57tRvp7vdCbap331CU9aykQa8F3eZr4V25Upru2/cuJgiRWysldFjY+HTT2k49WPAKvK1akHrzdMsMaSl2UT3EPXrBy+/bFWTKVPytrDLu71jR7scwnmB0IN8x4529ufAAdu4XiTCOW314FbkO+//3c6u1qsHnTv7gjxYVT6obt3g0Uft8m23wbJl5TBaqdKmTrU1SOrWtc6N/FJSbF7VCy+Q88jjPLJ7KNvy1scJegIpVKmp8M03thjskiV20mDvXrxee285lPm0mf6uPVY7MIhELAV5UZAvJ8UtdncgJbQ58occ4l7+4gto1KiMBljJNGtmn5MbNLDW8hUr8j3AqcqPGmWBHit27Ntnc9Z797a7d+wAvF46f28bs7/AUCb9nOisWceqVfDbb/Zh/+efixlU167WWg8c8+ENNGCjb/9238bvgweXyX6AHo/9+771lrtlXVFCDvIej1v2//TTQh+2b59vXT+RKs0J8snJVryMj4fj+cFuPO448Hh8nTsA69YV8WI33WRtzPv3w9VX29lDEce4cXY8/XTr3sjnzz/dJRY2bQr8HXtQQR7sbPS339oP+a+/Qq9ebP1gIr23jWc8g/B4vXZ2PJQzwyJSJSnIC7Rta8eNGwkoU8hBKa4in1k9tIr8kUdaZvz1VzesRopLLrGK9C+/2DpUTkv5X38FFN7NeedB/fr2qXvsWMDdqq1dO3dB3h07gN9+o+mGPzhAIi9zXcDWcevXuwsL79ljf4p0zz3QvTsp6dt4jauonpJrJ72++MLuv+22Un73BbVtC0OGhHZeIOQgD3DRRXb86KOg20zu3GknUgqsuzR9uq2i/MMP2p5SqgwnyFerZv+X6tWD48ibg3PccQChVeTB5uyMHm2V1Z9+snYaEbB1E5z3gTPOKHD3okXWKXb22Xbd2UPeUVSQL3Lal79DD7U5W02awJIl1LvkJMZzMoewzlZNdbZMEZGIpCAv1hrsTLx2Nt+Vg1bcqvU5aZbEEhLsn6AwHo8teNuvX9mPMdzeecc+RB9xhH3gWbDAciNY8ThgfanERJu3DraQEO6Pa8eO1u4OeUE+b1G897iELdQP+Jpeb+C+80VW48D+gd5+m6zYRE7lG86Y+z+bC+n1WhWmQ4eSf+NloERBvn9/+z++c6e1Y+Yze7a9zs8/5/2dp6fbnM7DD4dLL7WK5GGHFZN4RCoHJ8g701YOqbOffkyzK0GCfLG/A1q2hBEj7PLdd4ew1YZEhXnzbK5WUhKceGKBu51F56ZPt/Og+YN8YSeRn3vOTkJ99lmI4+jb185O/+MfbK/RnJ2kMa3dZbbLS7NmIX87IlL1KMiL6dzZjgsWhHccEaTQxe7ykpe3tlXkGzYsk87sKsnjgRo1Am9zOhSXLAlyXum662zO+pQpMHeuryLfqZMbbNM37/VV7EdxfdCv+9tv7uWQsmmXLow54lkATvrlPtsCCOD220N4cvkoUZCPjYWLL7bLefto+3OmMWRlwY6tOXDmmfDSS3bjUUfZWZK5c+2MS4E5DyKVi/8OEwDHxE8jiQzSazX2TSULuSLvGDrU5szv3GldOiJONf7EE3HnXLmcxeSzs+29LJSKvNdrC9xnZNjbXcjnjOrUgXfe4fhWK6nFTlb/35sF31xFJOIoyItx9rsKaZNtCUVxc+Rj6loSK6qtPhqlprrFjQIViSZNbF9ngOef9wV5/4p8lxXjYP9+VsS2YQa9Az7LOPu/+7ctFluNyzOh2TW8zaV2pV07+PBDW3Y+TPyDfEg7Y/3jH3b88ssCKwr6Z/PsR56A77+3D6YTJthiTjNnWt//qlW2T15mZtl8EyLlIH9F/pj0bwFY1ep431nTkOfIO2JjbW9vsEUwnXKrRK+vv7ZjkLZ6CPy9OmeO7WQI9qMEwYP8vHm2fTxYiB8+PPThbN3qThs79tjQnyciVZeCvBinIq8gX2aKmyMf18Aq8gryBZ17rh2Drs2Wt+id9913WTffPo37B/njNn0AwHu5FwEe+vZ1nxosd4ca5Pele7icNxlzzzwrr/hv/B4GTpDPzg5cpbtQXbtae3xmptsmnMf5wNmbP6j7TF618bnn3EnzLVvCpEn2l/zHHza1QKSSCgjyXi9HrLcOmlnNzgK7qWSt9Y5jjoELL7QXuPFG7S0fZfbvt3XjzjsPvDt22u9CKHR1Uv/t3efMcSvyzrJEwYK8857XqZOdc3rnHXctmOL89JMdDz1UnytEooWCvBgF+TIXNMgfOODrua/f0ZKYs2mAuM44w9aYmjPH1mAMcPTR0LUrnv37OXvXG8TE2N9hrVpQi+0ctW8CAO95bYG3ww+3p8XHw/HHF/xa69bB0qVut3xh9u0DLzFktuvsllTCKDnZlg2AENvrAf73Pzu++CKsXu27ecUKqM4e3udiYnKy4fzzAze2B9vm6I037PITT9gKhSKVkP9id8yaRZ3dK9lHCr+m2e4N+/f7Nr4ASrj0w2OP2cInv/wCH3xQZmOWym/OHJg1y8L2wpcm2w4G7drZ78Yg/Cvyc+e6v3KdBsjdu219kv/9zz4agBvk//1v9zyqU/gvzIoV9iv9Y9shNej7nIhEJgV5Mc5y4Zs3u3ulyEEJutidk7hiY7n4ulS++ALuvbfCh1bp1anjriE3c2a+Oz0eX1V+KC/QqkUuyckW5M/nIxLIYn/7biyiI7Vru6/Tti20aVPwa61fb+u5DR7sVjSCCQgHlYDH41blQ17aYsAA67nMzLQVFPPSzKq/c3iBobRlGbtrNbMt/oIt3HDmme5eyTfcoP3qpFIKqMjnpZuvOZX1O+2XsX9bPdg24CGvEt60qW9LSm6/nYAtMSSi+Qfz1W9MAiD3+AFBH5uVFXCulOnT3QL+UUfZcc8euOMO+O9/7dzookX2uzwuztaKOeUUe1yQ9UkDXHedLeEwZoxdz1vPUUSigIK8mGrVrH0WtOBdGQm62F3e/Hhq1yYxycMZZxS9Yn00c7a+LRDkAS6+mAPJNWnN31xa1+a/1q7l5Z+8CMCyIy4DrL3w1FPtQ9E990CLFu5LNG9ux+XLYcaMgl9r4UKrlDi7rjmf1ytLkAfL1WAf4kLak9jjgUcesXaHzz+Hk08m65GRjN1wGEN4hxxi+PDUd915CsE88oidQZg3z7c7gEhl4lvsrprX12rzCef5zlE7bfVpafZfISenhOevb7vNfpmsX+/Om5eI5x/kmy/7HoBL3hgQ9CPTmjVWsE9MtAauffvs+oknQo8e9pjdu93XfPFF+L//s8sDB9qvYCfIT51a+O/3Awds7VdH9eq2SYmIRAcFeXGpvb5MBW2tdyrydeoUeLwEcoK8E7IDVKvGtE5WGb7m7zshM5PkGVPpyjz2kcL3Ta8AbEeAmjVh3DjbSt0/yDvth3PmuNU4/7mIN95olRJnO7zKGOQfe8zOv61cWYLt7Pv2tVX9U1Jg0iTi7/oXvZjFTtK4kteZnlDMAn5161qYB7j/fm3FJRVqxAh4/PGiH+NU5E9b9AQsX05OYjLfcEqBIF+3rjuX2H+e/KZN9nUKTOtxJCW5qevRR0swt0WqMmfOexPW0pFF5BDD+IxjmTzZfczcuXZi9fff7XrLloHT5266yRZ0Bdi1y/2527DBnalx//12bNPGnpudbeuPBvP773ayuUED243l11/dTi0RiXwK8uLSFnRlKmiQ96vIS9GKrMgD7zS5iy3UpdHW+fDQQ/DUUwC8yz+Ys6omUHDBn/r17TM4BJ9H6AT57GyYNi3wtvxbWlUGNWrAa6/Z5XffLUF78Omn2xzfq65i3fH/YAR30o4lvM1lbNoUwvOvugq6d7cykRNoRMrZzp3W1X7HHQU2Xgiwdy9czHucNuUOALbcOoJ9VPcFeae1vlYt2wgDAufJP/20fZ0nnihiMBdfDF26WBpzTmxJRHOq5/cfZW31s+N6s5NaAYvaPfywVdfzZn/RqpXtWgjQurVV2Z0gv2mT+znBcdFF0Lu3e92pyhc2T96ZDta/v52j7dKllN+ciFRJCvLicoL83LnhHUeEUEX+4HTvbp3g69cHr4wt3FyHW3jarvzf//n2jn+Bob7w3bBh4HM8Hrj2Wlu8/cwzC04DX7jQFqKeO9edGrF0qR0rY0Ue7ANcSoq1WDpjLc66dbC/fXd49VXGnfcOdzOCXQn1AUIL8jExMHKkXX7pJViypFRjFykJ//b3Qnd/y8zkzB9v4T3ytlu86SZib70JsACfleVW5GvWhMaN7fIzz7hbdzm/P4psTouNdXd/eO45d28xiVhOkD89Oa88foLNj/cP8s5l55x9y5YWzlNS7HxzTIwb5HNz7Vitmp0gTkqyx/g77TQ7vvWWOwfen3+QF5HooyAvru7d7ejfayylkp3trkLrv4+5KvKhq169iAXvsM/N73MxO/qfZTc0aMCHjW9lHl19H8SDbcHzzDO28FCNGgXv377dwoJTjQdYtszCfWUN8jExbhVm7lxbWH7QoMLbgmfOtA+Xxx1na945H06dDoiQgjxYS8Opp9oP+333HdT3IBIK/w72QoP8vfcycNEzAMw5/lZ48klq1/H4Ttpt3x4Y5E891S5PmmQn+DZvdvfxXrSomAGdcortonHggNsPLREpO9tZvM5L3dkW5HOOsyDv/LxA4AJ3YBX5M86wLhFnx1InyPs/ZsYMWxHfWarIcfzxcNll9pHs4osDK/OZmdZKDwryItFKQV5c7dtb+XjfvtBLexLUnj3u5YAgr4p8iRTWXp+d7bTCejjw/mf2KWnjRt7r+STg/v071bbCOG214O4usHCh++EI7EPa/v3uua3KFuTBtogHOwf33//ChAmB3b4ffmjtmn/+aVN6s7LsZMaDD9r8enC36du0qQTbYz/8sB3HjNGUHCl3znlQKCTIb98Ozz8PwGW8ydzLn4TYWGJj3XOnW7YEttZfe62dADvkEAtGM2e6VdXVq93OnKCcxSPBzqCFuuG3VDlr19p7QLe4v4jdshGSkqh1Sj/Afl68Xjufk/9EqBPM/bu/EhMhIcG93qSJffzq2LHg1/V44PXXbTfQ3Fz3Vy5Y+N+/39Z6cDYeEpHooiAvrthYtyo/a1ZYh1LVOSvM5n/DVkW+ZAoL8hs32oeauDho0NDjS9f+i60nJMDJJxf9+k7QT0tzKxoLFwZW5DMyYPFi93plDPLOHMxPPnEXTxo92n7ccnPhzjvt7/Dcc919isE+FH71lV3u29eOmZk27TckXbvai3q9misv5c4/yM+eHeQBzz4L+/axNKUbbzMkYD2LevXsuGVLYEUerKOln2UyfvjBDe9ebwjntI84wkquubm2zYVElD174P333XM059ay+fEcfTTN2iXh8VjtY8sWW6keID7eDe6tWgV/Xf8T/P4nlIOJibFZHLGxdpLZ6RRxNkw49tjgu4WKSORTkJdAPXvasdC+RQmFE+Tzt9CpIl8yzrIN+T9MO9NRmzSxDzkO/yB/3nnuh/fCOB+gevZ0Kxo//mjt5h6PG/SdubMJCXbyoLJxKvL+U9XT0236+o8/wqpVdtuKFZY3TjoJhgyxy/v3WzfC0UcHLsIUMqet/uOPVZWXcuUf5JcudVenB+xKXrJ5pe7dgKfYIO//++LQQ+04blzg1/Q/iVcop63+ww/VzRZhRo6ESy6x9naAAeTNjx8wgMRE6+QAq8o7bfVt2tjzbr7Z/d2cn/9ng+KCPNh6L87Cd2+8YV1XY8bY+99dd5X8+xKRyKAgL4GcIK+K/EFxWrsLBHlV5EvE2et91arAdm+n8tG0aeDj/UP99dcX//rOfr4DBrhtjXlr5tG5s3u/U/2rTCvW+8v/YdH5b/zkk26R0OluABg+HF591T4MTptmf5+NG7trBpQoyHfpAuecY/9ARS7zLXJw/IO81+ueYANs8vCOHdC6NWNjzwUCu2ecIL91q9ta71TkwQ3y+ddtDCnI9+hhk+1zc7WCfYRx1v7dsgXiyKL7zsl2wwCbH+9U3P/+2z1h2qwZ3Hqr7X5QWKW8pEEe4ArbVZXRo90TCzfd5P6+F5HooyAvgfyDfMgTZSU/VeTLhhPU09MDP8Q7FXmnGuLwb1c86qjiX//qq+2D2h13uEE+M9OOQ4ZYZQXcwFAZ2+rBpgY4Jz3AFtHu1csCi7PH8UsvwahRFuxPOsnaP086yebGO+eVShXkwf4CAd57L3BDbpEy5P87API1jn33nR3POovd+2IBQm6th4JzjJ0AVuyCd47//MeOb7/tnmmUKs9ZDBSgH9NIztpj79950xD9g7xTkW/WrPjX9f9skP99rDCnnmo/xzt22O/oVq00o0kk2inIS6BOnax/eOdOdxUsKbFCg7wq8iWSlORuIedUO8D9nJz/A9Ctt1rVYvr00OYMOiu+x8XZsWZNC8XvvAO33QZt29rjnIp8ZQ3y4Fbl09JsvvuECe7c+c6dbbG7666zvFHY302pg3zfvnDMMbaK3jPPlGr8IsVxzoM6AdwX5L1eN8ifdJJvhwn/IF+3rh0La61v29ZObjmcxR9DqsiDTbI/9lhbiTNvwT2p2rzewK3lTiVvyfhBg3ztX8Eq8v4nVQtTmop8QgJ88AHccovN2581K99iuiISdRTkJVBCgruXldrrS80J8gFvsl6vKvKl4N9e73Aq8vlb62vVshV+Dzus5F+nRg1rq121Cv7xDwu7TkXe+eBfmT80OdMAjj/eFkWqU8e21LrrLptTGcqJDSfIF7Z1XZGcqvyoUSVYLU8kdM550OOPt6MvyC9aZL8UEhPJPfLooEHevyIfrLU+Ph7atXOvO/ORFy8uQXParbfa8ZVX3P0qpcrascN9L+/bF0735K0M6mzuTtlU5EMN8gAnnABPPWV706elhf48EYlMCvJSkNNe//vv4R1HFRZ0jnx6ui2BDqrIl0CLFnb0bxAprCJ/sOrVC/xw5FTkHaHMuw+Xm2+2P4895t5Wp46tTN+7d2iv4XQ//P57KWbWnHyyTTTes8eCjEgZc4L8CSfYccGCvKkwEybYDcccQ7o32ff4YEF+69bgFXlw58mDTTuJjbU19GyryxCceiq0bm1f4O23Q3ySVFZONb5hQ5j8xgo6ef+yH4qBA32PKW2Qd04KJybqvL6IlJ6CvBTk9BROnx7ecVRhQVvrnWp8QkLl7tGuZPwr8kOHWgerszB0/op8WWvWzM65eDw2x/zKK8v36x2M2rVtcSWni6A0zj7bKpMTJ8KLL5bwyTEx8K9/2eWnn3ZPWomUESfI9+plJ9wyM/O2BfNrq3dWsvd4INnN9L4gv2mT2zDiX5GHwCDfoYPt7Q32e+fAgRAGGBtrq4+BraCvdWaqNGd+fMuWkDQpr63+yCMDzgA5QX7t2tK11jdurK3jRKT0FOSlIGdD3T/+sPl+UmJBg7z//Hi9c4fM+VA0Z46F6d9+c/8qy7oin19cHEyZYue0KnM1vqx07uxW9IcPh88/L+ELXHyxfTJdv94mcYqUIef/vd9aY8yekQ0//WRXTjzRF+SrVQv8NevMkV+0yPJ1UlLBxignyNeta7+7R460iukXX8AFF4Q4yMsvt/0cFy2yX1ZSZTlBvlUr4KuCbfUA9evDEUfYz1RWlv3MhdIq73w2KElbvYhIfgryUlD79lbuSE+HefPCPZoqKegcec2PLxUnyE+ZEljgiotz53SXp0MPhT59yv/rVBY332yV+cxM21Xunnvc+4otMCYk2EpMYBM5VZGUMpKR4U47r1PHXRNi4w9/2XtVjRrQpYsvyOffKtKpyOfk2PGEEwIXtwObe9+pk9t5M2gQfPut/ViPGxfibLPUVBg82C6/9lqJvkepHN54A+69F5Yts+vtm+yFH3+0K/mCPNj6ns5Jo8aNC/5cBdOokR0PpoNKRERBXgqKibGVXUAVhVIqtiIvIXOCvJMJnQ/krVoF7hsvZcPjgTFj4Pbb7fpDD9lUhieftFblX34p5gWuvtoqkvPmuXvfiRwk5zxoTIydZ3aCPH/kpevevSEmJuhCd+D+3nCcemrBr1Grls27f/RR97bjjnOr8c89Z8di2+ydMwFjxuA7syBVQnY23HADPPig/fMBHLF/kp3ZbNnS5lzk07s3XHWVXW7ZMrSvc9FF9vOk7eNE5GDoY7AE57TXT5sW3nFUUUEXu1NFvlTyzzd88klrsX/jjfCMJxrEx1uL/aBBdv311y3QZ2SEUGSsVQsuu8wuays6KSP+50FjYtwgX39lXpDP26qisIp8YmJgh1SwIF+YG2+045gxcPTRdiIhYA/7/I4+2kqte/fCJ5+E/oUk7Fatcpf3cE7Id/w7b378aacVOi3u8cft5+R//wvt61SrBsOGlf86LyIS2RTkJThnwTtV5EtFFfmyU6NG4OrSxx1n89WPOCJ8Y4oWF19sx8cfd89DjR8fQse8s+DXuHGBGzGLlJL//HiwwmhiIvTICh7kg60n6syT79w5tJXFHX362LntrCz4+Wcrzn77bRFP8Hjgiivs8uuvh/6FJOyWLMl/i5f6M/yCfCFq1rT1Dfv3L6+RiYgUpCAvwTmt9UuX2n49UiJFBnlV5EvMqcq3bq3FgSrSWWdZO70zrxhgw4YQls7o0MG2aPJ64fnny3OIEiXynweNj4c+nfbRmfl2QzEVeXDb64vIY4W6915bl8M5GVBkRR6sKyUmBqZODZYOpZJydkRx9ImbTdym9XZmSCldRCoZBXkJrlYtW/UH7IOIlEiRi92pIl9izl7yxx4bzlFEnxo14Mwz7XJcnLvo3/j/b+/O42Su/ziAv2Z37S7W7mLZXfc6Iqz7iFLJah0pUSQhKeUoV4RCN4oOJVeF+smRIikkIUmyborchHVml2XPef/+ePvOd4c9Zs+ZWa/n47GP78x3Pt+Zz+x+d+b7/hzvz0oHDh40SLeffWbONSHKorg4HRGy53q8nrodtFPYdnghBZcKh9pa+DIK5Lt00Z747Cwj2aaNnsbz5+v9HTsyOaBsWXNuCucBuQ2jzcX4zukRuExvtG6tQ0CIiFyISwTyU6dORaVKleDr64umTZviz0xSw3799deoUaMGfH19ER4ejh9//NH2WFJSEl566SWEh4ejaNGiKFOmDHr27IlTp07l9dsoeIyoiQmrsizNOfLskc+2bt30urhvX2fX5NbTv792LPbuDfTsqfscCuQjI4HbbtNWrblz87SOlH/ye0XSjz4CRowAxo3T+6k/Ph8M0WuF35KaID5B5y6nl+wOAIYN0znQ1aplry6+vuaydwcPmg226TJaDObO5VKubsLokR89GpgwXtDH53+6o1Mn51WKiCgdTg/kFy5ciKFDh2LcuHHYtm0b6tati8jISJw9ezbN8r///ju6deuGPn36YPv27ejYsSM6duyIPdeb669evYpt27ZhzJgx2LZtG7799lvs378fDz74YH6+rYKBgXy2iKQztJ498tnWpQvw77+20bOUj1q0AKKjgU8+Adq21X2//QacOJHJgR4e5lz5KVMAqzVP60l5b+NGHaUxZkz+vea2bfb3UwfylS9sAQD8ntzENmc9ox753BAUBJQrp7d37cqkcIcOesDp08CqVXlTIcpVRo/87bcDL93zB4qcPKjD6h9+2LkVIyJKg9MD+ffeew/PPPMMevfujZo1a2L69OkoUqQIPk8nQcyHH36INm3aYPjw4bj99tvxxhtvoEGDBvj4+jzMgIAArF69Gl26dEH16tVxxx134OOPP8bWrVtx/Pjx/Hxr7s+YD7Zrl9mbTJmKjzc7X9gjTwVBqVI6tL5KFU2fkZSk17XXrmVyYM+e+k9w4ICD3fjkysaM0c+3Tz91IOFhLilSxP5+6o9Py/Wl5/5EE3z1lZ6Xy66PhA4Ozrs6GRnzM50n7+1tZoz88su8qxDlivh4HbEB6GAi20iiRx7Ju5YhIqIccGogn5iYiK1btyIiIsK2z8PDAxEREdiUzrJnmzZtsisPAJGRkemWB4CYmBhYLBYEBgbmSr1vGaVLA7Vq6e1ff3VuXdyI0RtvsdyQOZk98lQALFigwdTWrcDQoZkULlbMXGCZS9G5tS1bgLVr9XZ0tDlnPU0ieoLs2JHjiP/cOfv7ttW/zp+3rYgQhUb4/nugRw9g5079iH322Ry9bIaM4fWZzpMHtFIA8N13QExMHtWIcsPhw3q6+vsDpYrFmwvJG3OKiIhcjFMD+fPnzyMlJQXBNzSdBwcHIzo6Os1joqOjs1Q+Pj4eL730Erp16wZ/u+5RU0JCAmJjY+1+6DpjeL1xBUeZMk4fPz8dXQxArw64jjwVAJUqmR1VCxc6EKcNHKjR108/AX//ndfVozwycaL9/Z9+Sqfgli3AnXcCjRpp13WVKsA332T7dW8M5Bs2TPU6AKR6ddS/NxAJCWbcNXmytkPnFaNH/rvv9HXeeCODwg0b6jjt+HiuKe/ijGH1t90GWJZ8C1y6pAu9M8sqEbkopw+tz0tJSUno0qULRATTpk1Lt9z48eMREBBg+ylfvnw+1tLFGV9gv/zi1Gq4kzQT3V2+bI63Z488ubmICF3+67//gKNHMylcuTJg5Cj56KO8rhrlgZgY4Ntv9fYzz+g2zUD+3DlNcrhpk2aGK1wYOHJEhyaPH5+t3nlj9dNvvtE4uHXr6w9cT4pradIEK1cCb72ljaedOunKb3nJ6JG/cEHfspHJPk0Wi9mjy+H1Li11IG/7rOrbN1WLPBGRa3Hqp1NQUBA8PT1x5swZu/1nzpxBSEhImseEhIQ4VN4I4o8dO4bVq1en2xsPAKNGjUJMTIzt50SmWZxuIS1b6pfY3r3AyZPOro1byHAN+cKF9YfIjfn4AOHhenvrVgcOMJaimztXo39yK0ePagxeqhQwZIju+/XXNHIkDB+uf986dXSc8rlz5t9+9OhMuq7TZvTIh4cDnTunGlpvrG7TpAl8fPTpY2I02LeVySOVKmkCzjp19P7Bg5kkpe/eXSu1fr0DLV/kDN98A8yYobfvKRoF/PGHtlYaLVdERC7IqYG8t7c3GjZsiDVr1tj2Wa1WrFmzBs2aNUvzmGbNmtmVB4DVq1fblTeC+AMHDuDnn39GyUyGMvv4+MDf39/uh64rWdJMFc5kVQ5hxnq6FRhDnB0K5O+9V6Oeq1d1XXlyK0bbdvnyQI0amrU9Ph7YsCFVoQ0btKHGYgFmzgRCQzVJyAcfAJMmaZlx4/QxB8XHm1noS5VK9YCIXSBv8PDI+yAe0NdYuFCT3fn6apI9I0lamsqX10ZxAJg3L+8rSJk6cwZYvVpPpSVLdNDI4cNAYCDQOXqqFurSJW+zJhIR5ZDTxwsNHToUs2bNwty5c/H333+jX79+iIuLQ+/evQEAPXv2xKhRo2zlBw0ahJUrV2Ly5MnYt28fXn31VURFRWHgwIEANIh/5JFHEBUVhXnz5iElJQXR0dGIjo5GYmKiU96j22vTRrcM5B2SYY8858dTAdGggW5vXB4sTRaLuRTdxx9zTW03YwTyFSron/K++/T+77+nKmQE608/rUsbpDZsGPDKK3q7Xz+NnBxg9MYXKgQEBKR64OhRHXNfqBBQt25W3kqu8vAw16Q3hmWny0h698UX+Zfyn9LVpw9w//3ArFnAu+/qvp49gaO/HkfJVV/pjuvXlURErsrpgXzXrl0xadIkjB07FvXq1cOOHTuwcuVKW0K748eP4/Tp07byzZs3x1dffYWZM2eibt26WLx4MZYuXYratWsDAE6ePIlly5bh33//Rb169RAaGmr7+d3uqoMcZgTyq1fzAtwBxhz5YsVS7WSPPBUwqXvkHYpLHn9cG7KOHQOWLs3LqlEuM1ZuNdLHNGqkW9tojP/+g20hd6PB5kavv67DlK1WoFs3HWaeCSOQDwq6oad940bd1q2r8zyc6LbbdLt/fyYFO3fWaVX//GOOJiCnSEkxT78XX9SUDoUKAe+8AwR8+DqQmKgjKO64w7kVJSLKhNMDeQAYOHAgjh07hoSEBGzevBlNU7Xmr1u3DnPmzLEr/+ijj2L//v1ISEjAnj170K5dO9tjlSpVgoik+XMvM49mT6NGegEeE6PzxihD7JGnW0F4uK4tf+GCGehlqHBh7Y0Fsp34jJwj9dB6wGzEsY3G+PZbHV9eu7b+pMViAT75BOjYEUhI0ASIO3dm+LpGIG83rB4wG4IiI7PwLvKGEchn2iNfrJhm4gOY9M7J9u0zp2wYDe+PPQYExx4AjOvNt95ySt2IiLLCJQJ5cnGenjoGDQB+/NG5dXEDnCNPtwJfXzNmc2iePKCJz4oU0QiQU3XcRuqh9YB2hFsswKlTuqa8LW37449n/EReXsBXXwEtWugHZZs2wIED6RY3MtbbBfJXr5q9/0Zg7ETVq+s20x55wBxeP3++9vqSUxgDIgIDzX2DBkGnf6SkAO3bA+nkaSIiciUM5MkxDzyg22XLnFsPF3fiBHD2rN5mjzwVdMYQ62nTtJP1u+80AVi6goLMXvk33mCvvJu4cWh90aKa9A4A9v582lye9LHHMn+ywoX1eyQ8XFsB7rwTiIpKs2jqofU2P/2kwXzFiuaC7k7kcI88ALRqpUkAL140GyMo323Zots+fXTGx/jxQMP4jcCiRdpCxd54InITDOTJMe3aaW/K3r261g7dZP58vbb89FO9bxfIR0frlhlwqQAZMEDjsp9/BsqW1VHTRptful58UbvzN23iCB83YLWaK48agTxgDq+P+2aFNsg0bgyEhTn2pIGBmnOlQQON1u+5R9eNu0GaQ+uNBe07dcqfFPWZMAL5f/8F4uIyKezlZY5a+OKLPK0Xpc/okW/aFBgzBhg5wgoMHao7n3rKqQkUiYiygoE8OSYwUJeQArTbjeycOgX072/fwZj6ohdGwsbQ0HytF1FeqlcP+PprnX1jDDo5dSqTpeJDQoDnn9fbI0YwgaaLO3NGp797eNh/fBmrFgREXV8O1oH56idPmh+FCA4G1q3TaVtXrwKPPgqMHGk35PymQP7iRXNUmAsMqwd0kJUxYyqDWQKmnj11u3y5OeWK8k18vJmawbZy4fz5Gt37+QFvvum0uhERZRUDeXJcx466Zcbpmzz3HHDpkvZSrV2rnS2PPJKqgHH1GhLijOoR5Zn27TUmefVVcwj04cOZHDR6tEY/f/0FfP55XleRcsAYVl+2rHYoG7RHXlDz1M+6IyIiw+eJidGOznr1zDwiKFYM+OEHszd04kSgeXNbFj27QF5El7aLidFucBeaw2zMk3doeH2dOvqLSEzUodyU5+bP1znwiYkaxCcn6zlVoQK0EWnkSC04ahS/o4nIrTCQJ8c9+KBuN240J4ITDhwAvv9eL3LnztWBCz162F/0skeeCrI2bYBx48xhxpkG8oGBOqYV0KDemHqSTXFx2nhmZKKm3HNjxnpDvXpAOPaglPUsrnkUwS9XM16qa9kyHbVx9uwNo8q9vIDJk4HFiyHFi2vmxIYNgY4dEf7XQpTGGYT6XdYga8kSXSfsq690GIiLuP123RpzrzNlJL1j9vo8Fx8P9O0LTJmiszKMlQsbN74+M2PyZJ0XUaECMGSIU+tKRJRVDOTJceXLa3YrEXOe4i3q2jVgxgwdQvzTT7qvRQugVq00Cl+5YkYYDOSpAKtcWbeZBvIAjj/QH7u96ml017dvjhLfvfEG0KsX0L078+fltvQCeX9/4I2WOqx+nfVuPD0g4/XcU0+Bnzo1jb9T586Y1m83vsQTsMICfPcdXv/nMZxBCB56MlB76wFgwgRzgr6LMGYVLF3q4Pn3+OM6V+H335lzJo+tXm1+/X77LbBwod6OjIQON5kwQXdMnKgJP4iI3AgDecqarl11ayw3dIv65BMdTt+3rxnIt26dTmGjN75oUR1KSlRAZSWQnzrLG48nf4EEeOuQlk8+wZEjwPDhwOzZWXvdJUt0u2wZ8M03WTuWMmYMrTeWnkvtoSI6rH6dRyscOQIcOpT2c8TGAqtW6W1vb13H20h0bzh/Hhj5UVn0xJcIx25MxAj8hdthhQUWq1WHe3zxhUv2mrZpo+/r4EHg778dOCA01PzCYK98rrh4EZg37+aUG6k/D5Yt06nwnp7XL2VeeEGH1t91l3ltQ0TkRhjIU9Y89piOR/v1V7Or5hZkLLG1ZAmw5nqup0wDefbGUwFnBPLpBXSGhASdGr8H4XgZutST9fkX8GLVpZg0SZeF2rPHsdc8eNB+bnLv3kCVKtfXhaYcS69HHsnJwPr1AIAL9VoB0NUL0rJ8uf7Nq1cHnnlG9739tn3v9bvvApcv65D9u/rWwkhMRC38haKIw4UthzWfQo8eLpGp/kb+/rqyHJCFFDJG0rsvv+QwklzQrRvwxBPAnDnmvqQkMzeij4+eg4CmcwjetFQT93p5AdOnu+R5RUSUGQbylDXlygF33623Fyxwbl2caP9+3aak6PzckiUzWNKYgTzdIqpU0W1GPfLJyTrE9fx57cWcjGH4zPI0PMSKedbHMMjvM4gIRo927DV/+EG3zZvrXOUrV/T1p0zJ8dT7W961azr6G0hjZblt2/SXXaIEKj6oy3WtXm0+fOWKBlKAOYDrkUc0r52vr/bIz52r+6OjgY8+0ttvvql/u8BAvR+PwgisH+ZSc+LTYuSCdXhRl44ddYTWkSOavZ+ybft2c2Tchg3m/rVrdfpb6dLAs8+a+3s+fNlcOWP48HTmxBERuT4G8pR13brpdt4859bDSUTMQN7QqlUG15lGNMFsuFTAGT3yx4/rEvHPPadJxg1vvKG5yp54Qu+/9BJQqZIFz8o0LEZn+CIBH1x5Gj/gAcj332PjopPAtWvYvOIidv94Qv/xtm0DoqJsE1+NQP7hh3Wg0MqVQM2aus8YLUNpi44GypRJf7T6jBnaDlmhQhojjq73xqNFC7SO1EuJX34BZs7UKez+/ppYfvNm7ZG3WPTvXrky8NpreuiQIfr8b7+tjQZ33AG0a6e9p0bwX726y8fwADQXrMWiQ7cdakAqUkSTOgD6S6NsmzTJvB0VpdukJOD11/V2x45Aly56u3Bh4JHd4zTBXVgY8Mor+VpXIqJcJXSTmJgYASAxMTHOroprOn9exNtbBBDZts3Ztcl3p07pW/fwEAkK0tuzZmVwwEsvaaEXXsi3OhI5Q0qKiK+vnu5Fi+p27Fh9bONG/Z/RpjARPz+REydEpk3T+y8NTxEZP17E09MslMFPisVDdheqJ69bxko9bJO/9lpt9Rg+XIs9+aToP+zcuSKDBon07Cny3HMi06eLHD/ulN+RiL502bIiI0Y4rQoiIrJwof6evL1FYmNFli4Vee01/TteuSJSunQGn2/t2+uD770nSUkiAQFp/6mKFdNt167moUlJIg0b6v4GDcyvk59/tn+JLVtEDh3Ky99A7rr9dn0fK1c6eMDWreYf4OxZh1/nyBGRxMRsVbHAOXrU/iPDw0Pk8mWRUaP0vr+/nkNWq8iMGSK/fbzd/CBascLZ1SciuklW4lAG8mlgIO+Arl31i7BfP2fXJN+tXatvvUoVkR9+EOnfX+Tq1QwO6NlTDxg/Pr+qSOQ0NWvaB3KlS2vbX5Uqer9HD5G9ezW+FtEL7AsXUj3B3r1yrf8QiS5cUZJgXqEnoJAkFAkQKVNGkoNK3xQxWitU0Mayb7+Vba8tk1F4SzZ53y1WiyX9BoHHH9eoKJ9NmaIv7+UlcvKkyKVLTqmGfPCB+auYMUOkSBG9/f33Zh0rV04jaExO1ggJ0GBURDp21LsWi8jrr4t8+aX53BaLyJ499k+xf79I8eJmmXvv1XPBnXXqpO/l/fezcJDRojFpUqZFrVazXTg8XGT3bsdfZvRo/R80/u/c2V9/aVtcfLxIr176+4iI0MYxQOTDD83zatGiVAdarSItW+oDjz7qrOoTEWWIgXwOMZB3wM8/m83dV644uzb5avp0fevt2jl4QOvWesCcOXlaLyJX8MADN8fL5crptnx5DVodYbWKfDknWfo/ESOPdU4UQNvERETmzRMJwSkZUeYLOdrwYUnxLZxxD36TJtojP3GiRjTNm5uPFSki8s03efb7SEuPHubL9+8vUrGiiI+PjlDIT0ZQaIyQMG737q2/MkAD+ptERemDAQEa1IvIb7+J3H23yHffmcX699di3bql/fpr1mhjBiCyYUOuv7189/LL+l769s3CQTNmmC3D13+X6Rkxwv609vG5uYEkLQkJ5t935sws1M1F3XmnvpeWLbWRCBDZvFnkoYfsz+XUo0BERGT5cnMExNGjzqg6EVGmshKHco48ZU/LljrZMTYWWLTI2bXJV8b8+OrVHTyAye7oFmLMky9USFd3AnQ6qp+friUeEODY81gswBO9PDH1S388078QAF3CzGrVpGrRCIV074GKUd/C48J5zTLWuzfQuDHQqBE2lOqEgfgIs189phO1P/gAGDECeOstYONGYOtWoEULXX6qc2dg8uTc/2WkY8sW8/YnnwDHjmlG7Y0b860KAMyPJsBcaxvQj/Q//9Slzo25xXaM+fF33WWbwH7nnbr7wQfNYlOmaK6EWbPSfv377tN59d99p0/l7m6/XbcOLUFnePxxzex36JCZ8CENR44A77yjtydM0NM8IUETR2bmjz/Mv6+x4oq7Skgw/3/WrtUmja5dgSZNNDcDYL5X4/MHgGamHTHCfKBixXyrMxFRXmEgT9nj4WGuI/TRR7fU8jkM5InS16SJbp94AhgzRpOe+fpqwjPjsay66y5tCDhzBtixw8yObkvAVqSIRpCff64R6JYt2PTiN5iKgZi3IY0F0AGgQQONIo3s1S++CLz3XvYqmAWxseZnSFCQ/WP5HWTdmJQtMFDrFBen91u1AoKD0zjQWAT+nnsyfH5PT6BtW6Bo0fTLtGhhH/y7MyPJ4l9/ZeEgPz8zpXoG59/mzbpt3FiTRD72mN6/8ZxJ66vYyOieVnl3s2sXkJioCREtFl354u239bFGjcxy4eGabNFmwQL9wxQvDoeXxCAicnEM5Cn7nn5aU8Bu325e2N0C9u3TrUOBfGIicOGC3mYgT7eAbt20Z3baNA0Kd+zQ6+dMYr4MeXub63S/+y5w8qReyGfUi/voo7r95RddC33zZnMpNRsvL+02NtJbDxuWfvdxLtm6VYOtihV1cEDhwsD99+tj+R1kGW2MRgD67LPmMmqAuUCJnWvXzM/7yMi8rJ7bqV5dg8sLF4Bz57Jw4MCBei6uX5/uSfDnn7o1GsOM5U5TF585U1e0mz3b/tjUgfzOndo57aj4eHMZQVdg/B5attRf14YN5iggo0ceAPr1S7U0fEqKrmsI6P948eL5Vl8iorzEQJ4A6PItEydm8aCgIOCpp/T2u+/mep1cUUICcPSo3nYokDe6vLy8gBIl8qpaRC7DwwO4+24NtAFd4emmNcizoV073S5YoNsWLTQITk9YmDYeiGhn+1136TFGIGDnlVeAUaP0dr9+Oh48jxjDghs3Bvr21d5vox1h+3at7z//AMnJ5jEpKcAXXwAdOmhP465duVMXI5D/7DOd9vDGG0CnTrrP21uX9LvJunUazJcrp5UhmyJFzBHbWRpeX66cOYfBCDhvkPq8AYB69XR79KiulR4fD4wdq+fT008DS5fq4xcumEuyeXvrn+7G5VPTc/KkVi0y0nUG3aVu0GjRwn6UT+nS2hBVp465xCUAPbn37dMhJwMH5mNtiYjyFgN5wsGDwPDhwMiRejtLhg7VK/dVq7Spv4A7dEjn6BYr5uCy8MaVckiI/p6IKFuefBLo1cv8N3rgAceOAXTOd3Ky/u/27q1Bjx2LRbvHn3xSo+YuXXS9+lw0ZYoGRZ9+qveNgMxi0XjYw0N7cV95RRsJP/jAPHbRIn3vy5cDe/YAffpkrVc1LYmJwPnzertKFU0TUKiQjg4YPVqD+8DANA405nG3b5+qy5MM2ZonDwAvv6y/z2+/1WEbqSQnm6ejcd4ULw5UqqS3d+wA/vc/nXpiseh5/vDDmregc2cNwmvXNo+dMgUoWdJ+/fW0fPaZNgSsXWtOZ3G2G0cm3GjJEr0UKVbs+g6rVVuoAGDwYMeTdBARuQFGFoTvvzdvr12bxYMrVzZ7El5+Odfq5KoOHdJt1aoOXsMa3ffly+dVlYhuCd7ewJw52rG2YAEwYEDmxzzyiDk/OzRU53v/9Rdwxx3a8W43/Nli0bHJrVtrt2b79pqFLpd89JH2cB44oPeNoArQnlxjhM+ECbr99VfzcaM3tnVrjUOionRq/wsvaAd5dpw5o1svLw3qDJ6e2qZh16NpEDEDeWOIBNnJdiBfsybQvbveHjPG7qG//9acjMWK2Y8EM4bXb91qBuUTJ2qjj8WiU0mMvIQdO5rlZ8wALl7UgXTJ8ck6xOPnn/VkOnECEIHVaj9E3xUG3cXEmFPbUv//ZGjJEmDvXk3WYZf9jojI/TGQJyxbZt7O1lT311/Xq8EffshGS4B7OXxYt1WqOHiAkfXImIRKRDlSrZpmqfbyyrysn58G/EWK6ND0GTM0UN25E5g+PY3cYoUK6TDcOnV0WkzbtjpuOYeOH9fRTh4eOuXA398+MRdgBllWq26NzxpAe+EBfd9GYq9p07RxwMiTllXGrJ8sDRbat08bJ318zKQFZMcI5HfuzHw4+u7dwPz5wIoVwOXLAF59VU/QFSvsusCNhpyGDW2LBAAwz5lJk3S4fEAA8Nxz2uD17796vn/yCbBypQ67N8oDgnuwDlPOdgUCA4C6dbWVqGVLoEIFoEwZnH64P0KP/g6/ogJPT43zc3mQSpYZUwQqVdJh9JmyWs15Ky+8wLnxRFTgMJC/xV28qMliDMZyLllSrZp5NTl8eM7HfLow4+LaSK6Tqb17dctAnsgpJk7UnryICOChhzQWNZJWp27EtPH310bJsmW1K7RTJ02OkQNGA2njxjqqx27o73XGnGfD4cPmZ7ERyNeqBTzbVzDs/t14qfxXGI538cg/b+HyKxOBefPMSfYOyNZiGv/7n25btsw4Ff0tzEi4tm6dzi0/ezbtckePAk2b6upz7dpdTzJYpYo51KR/f9scEGM4+Y290EZgboyuGDfOPK/KlNEcDP36aT0KFdKFGhphC9aiJdahJbpiEbwSrgL+/rhQNhz7cRuS4QlER6Pssmn4HXdir28DTG00Gz6Ix9Chzv16N5L2Obz6xfff62gDPz9gyJA8qxcRkdPkw7r2bicmJkYASExMjLOrkiMXL4o0ayYyfLjeP3tW5PffRaxWs8z//icCiFSvLlK4sN7euzcbL3bmjEixYvoEH3yQK/V3Re3b61ucPt3BA26/XQ9YsSJP60VEjrt4UcTTU/81t20T6dxZ5P33byi0Y4f5mda9u/0HZxY98YQ+zejR6ZdZvVrLeHmJeHjo7ZMnRS5c0NveiJdrr04QKV9ed6T3U768yJgxIpcuZVin6dO1eIcODr6Jq1dFSpbUg7791vE3fwuaNEnEx0d/VU8+af/YqVMiiYkiDz+sj5crJ1KokN7esEFEYmJEQkN1x7hxIiLSqJHeXbTI/rlOnjT/7J07Z3KKXrsmKcOGSwosIoCkePvINDwrdxWOkvFvpYhFd4svrkprrJLZ6CVxKGx7gXMIkg/wgnzZ//cc/S9k15UrIsWLZ+H0s1pFGjTQA0aNyvP6ERHllqzEoQzk01BQAvkpU8wv+XffNa8NOnUSOXdOy3TqZF5gRkTo7Y8+yuYLTpumT1C4sMjBg7n2PlyJEZf/9JMDhRMS9KocEDl+PM/rRkSOu/deM5ACNPCKjb2h0KpV5v/wyy9n63WsVvOzd82a9MslJYk8/bTI1KkiYWFa/tdf9SccO+WwV1XzA93XV+Tuu2Vzte4yE0/L5tt76hsqWtQsU7KkyGefpRt0jRunxfr2dfCNfPaZHlCxolaWMrRmjf66ihbVIFRE5LvvdF9QkG49PUX27BF55hm936bN9YMXLbK16lj/2Cx+fnr3r7/sX8NqFenWTaRVK43/0xUVJVKzpnludO8u1mPHpXJl+zagXr3MYiEhIt/OOi8ycaJIhQp2BeNDK2oPwZYt+RbUf/KJvnzlyiLJyQ4csHy5+QcwLniIiNwAA/kcKiiBfPPm6Xfa3HabyL59Zq/Uzp0ib72lt6tUyfiCM10pKSItW+qT3HGHSHx8rr8nZ0pJ0etnQOTQIQcO2LNHCxcr5pQeDCJK3+TJN38uzp+fRsHPPzcLzJyZ5df56y+zoeDqVceOadVKj5kzR2TRyCg5jxK6IzRU6xMXJyJaX0A7HkVEX2DBApEaNcw6d+iQZiDz7LN2nb4Zs1pF6tTRA955x7E3cYuzWvW7FBD58kvdd/fd9ufb4MG6/+BBcxRGVNT1g7t0EQEkqWJlKYYY8fDQtuEsV+K998wv+uBgbU247uuvRRo2FGndWr//U1K0QWDx4hsatZKSxLr8B1lXsYfEws/+TYSFiYwcmaeN9ykpes0CiHz4oQMHWK0iTZroAcaQRCIiN8FAPofcJZDfvVuv2aKjb37s2DH9DrNYRGrVMjtSfvjB7B0qW1a3rVqZxxg9BYDI999no1KHDokEBuoT9O5doAJYYxijp6cOjcyU0avStGme142Isuaff+w7uI3RSiJp9PiNHWv+8//4Y5ZeZ9YsPfTeex0/pm9fPWbywMMS56Ofp8dCm+qcgFROnNByHh43B14ycaKIt7c57GDTJrtjH3wwC9OEjDdRpMhNdaD0vfaa/tpatxbZv9/8W82aJTJ+vK09RkREHn9cH+/X7/qO//7TL21AvkVHqVbZkW7oVK5d0y524yR/5JEc90zHxIiEV70qnbBY1gZ3EWuRIubzWyw692zFCo28c9HmzWab+E2jZtJi9MYXLpz2BRIRkQtjIJ9D7hLIG/Pm0pov9u67+tg992gA+vrrIkeO6GNGfGn8/PCDedz58yIdO5pz7gx79oj06SPy228OVGzlSrN7YezYAhPM//qr2QHhEGPsau/eeVktIsqmli21k3LpUjOgb9lSA4Z33001gtxqFenZ0wxm161z+DWMNoBnn3W8XhMninghUQ6UbCoCyGY0lq9mpB3BVKqkz79qVRoP7txpdmV6eWl35vXP48aNdXeqDtq0nTolEhCghSdNcvxNkBw+bMa4bdvq7fbt0y67cqXZaW5rSNq0SZK8dLL94rBhjr/wqVPagGy0HHzwQa59D+/da+bT+fHrKyILF4o1so39RUWtWnqhkUsB/cSJ+rQPPeRA4eRkkfBwPeDFF3Pl9YmI8hMD+Rxyl0C+e3f9rho//ubHjCD/k09ufsxqNefD16hx83et0frt7689z4cO6cWFcS04derNzxkbK/LcczrXLz5e9ILR+FIfMSLXW+idYc4cfTsREQ4e8OijvPglcmEpKdpxmXoYdOqfjh1TFU5IEImMNHv6fv7Zodcw5j+/+qrj9Vq8WORNjBYB5JIlQCriiGzblnbZHj30+UeOTOfJYmJsw7QFkGsPPiozJ8VIieuj9f/8M4OKJCWZEWijRpwbnw0PPGB/Ti1Zkna5xEQzmdv69eb+L9t9ZR78yiuZB+Rr15rD7ooXdzChS9aMHKlPX6eOtm/5+oq81n2/xD0zyEwQCYjUrq3j93P4/d+unT7de+85UPiLL7RwQIBmiiQicjMM5HPIXQL511/X76sbs+LGxIgtA+2pU2kfe/SoyGOPaS/zjVJSzCH2S5eKVK1qBvbG93Pqnvk9e8wGcECHCFqtot+6xs4HHnD7L1WjZ83h5FBG1qAsDsUlovxn/H9Xr67TwI2PrtTDn+XaNc1IBmiq8XnzMn1eI5CbMcPxuuybv02SoPOaH8Ei8fRMf379vHn6/DVrZvCEVqtmP72eHn0fbpMm+EMAkdOnMzhmwABzqMLOnY6/AbK5ckXbsj09dXBERtOynnxSf90DB5r7OnQQGYZ3zRPy2WfTPhkuX9b54MZouFq1RA4cyP03JPpVbgzSSP3j6ysysPtFiRkyzv6CoXbtbPfQJyebT7V1ayaFY2PNxHxp9XAQEbkBBvI55C6B/MKF+n11xx32+9eu1f0VKmT/uY3lkozG9YoVdYh+1656f8AAnXpm9OwDIqVKmQmejd6nlE8/F6uxDk9wsLaWu2nvvPE7mTDBgcJXrpi/jGPH8rxuRJQz165pw6UxB9dI9bF79w0F4+PN0TaAyEsvZRidGStgOZxzJClJkuvqQQvQRQDNZp+e//4zP2oyi9u2T9skx6DL16XAInsjnk973vS1ayL9+5vjwhcvdrDylJ5z5/RvlRFjandoqPk1acyM+Pv5qeY5V62ayNy5+qW8b59+KRlJb4zWfSNVfh55802z0//jj83ccoBIixaiuRTGjbMP6GvW1JYnh9LOq61bzQ72TA8zMjhWqnRDCxwRkftgIJ9D7hLI79xpfpGmHm1nzI83Ejdlh9HLY1zHGT3wP/5oXmgYvQceHjoE9cQJc4UiDw+d81e/vsi9gdslqWp1+/lzc+ZkIwWvczVrptW/cS3fNBmLQpcrV2ByBBDdSowAPM055CkpOv/W+Exr1kyHOaXBGOUcFeXgC0+YIALIf5ZACcZpKVUq88FMRpb7yZMzL1cC52VTtR5m3f38tGX2xx9F/vhDs9/Vrm0+7lCacMoN8fFm3PvHH9o+ZDTSnDgh+jcqU+bmrnDjp1KlbGapzbrkZO1MMNqprVZzyT2LJVWjhRHQp+7Cr1ZNz6tLl2zPl97XpDGwL73cAjbGxQkg8ssvOXtzREROxEA+h9wlkL961RxCf/asud/oNX/77ew/9/nz5nO/8IK5PyHh5iF1N+Z96tbt5uuL9ycm6AVq6vlz5crp/HE3yIJstYptTml6c1XtvPKKFn7iiTyvGxHlPqPTPcN5uYsXmx+IgYG6HlyqiCQ52RzpnN40Jzs7dtiGv78X/rkADo3elylT9DXuvjv9MsZSdYUKXW9z+OknbWlNLygsWVIzkFO+6tRJf/1vvGGurFCkSKqBbP/9p4Gx0dhSrJg2JM2e7fj6hnmo+vU2+2XLbnjg0iXtxje+SI031revfP70RinsnSxr1+rlwKOP6tsR0QR3QCarHq5aZWbgSz0vgYjIDTGQzyF3CeRFbKvT2M11r1xZ961enbPnHjtW5OGHdepdasYQc0AzPN/o3DmR0qXNlnlApG7d6w/+95/OXTOy56X6Mpddu3JW4Tx08KBW1dvbwYEEd92lB3z6aZ7XjYhy30svORgXHDliZgg3PhT37BERDd6NEUqZDgu+etVMNvLQQ3LurDXjRHSpHD1qvs65c2bM9PLL+jk+cGDaDbOSkqI9mX366BjuSpV0YfFJk+xbhynfTJtmNsp8//0N3583csHkg8bo9iFD0ikQG6sZc40cMtd/TiNYlpR+RmY/+I1UwFEJLm2VlBQz7v/jjzSe68oVkTFjzGUW27XTaSFERG6MgXwOuVMgbyRRnjVL71+4YH435lVHt7FUU0aNBRs26LK1P/9s62Cyz5V07ZpWOnWWPEAXW1682OUuUIzerMaNHSgcF2deWORRsiEiylszZ+q/cNu2DhROTNTEIMaC9J6eIi+8IDtXnhJAJCQkk+OTk7XVFNBkI2fOZLm+xlSAjz8WGTQo7U72fv2yND2ZnMBoNC5USGS0LlwgXbo4u1aOW7BA61y/vk6ve/fdtGPrxASrXF2xTjZU7C7/IeCmk/U8SsiZ2vfJbPSSSYVekuTJH2jD+MyZIm+9pb+U1MMDu3Rxu+l6RERpYSCfQ+4UyL/wgn6HGculrlql96tWzbvXjI8Xad1alz1yZPq3cX2a5pKuVquOze/cWS9+jS/l8uV1bkBaiZicYOhQrVb//g4UNiYKli3L+fFEburnn/XfuHp1+/3//KPzmNPscTxyxPzAAyTZy1tm4mnpWHN/+i+UkKAjkowhP6nXHsuC9983e2+N+KZ7d/3M6ttXc6Px48g9hIWZIyyAtJd8dVWnT5uj8Yz6N22qeflERP79V3vtU8+yK4QEGV5/tXyEAbIddSURXulP+bjxJyxMG/95chNRAZGVONQiIgKyExsbi4CAAMTExMDf39/Z1cnQJ58AAwYAHToAy5YBb78NvPwy8NhjwPz5zq6dWroUePhhoHRp4PhxwMcnnYInTgDTpwMzZwLnz+s+Hx+ge3dgyBCgdu38qvJN7r4b2LABmD0bePLJTAqPGwe8/jrw+OPAvHn5UT0iymVHjwJhYYC3N3D1KuDpqfvfegt45RXAzw+4cEEfv8nPPwOvvgps3AgAsMICj/tb62fCvfcCFSoAKSnA+vXA6NHAn3/qcfPn64d3Npw9C5QtCyQn6/3KlYEDBwAPj2w9HTnRs8/q1yAAhIcDW7cChQo5t05ZcfvtwL59etvDA7Ba9X3s3AnccYd5uhv69AHGjgWqVNHzt9VdCfjvtz2ojT0IxWl0bnYajctHA9eu6QFBQUClSsD99wONG5v/nEREBUBW4lCvfKoT5ZHq1XVrfGn+9ptuGzd2Tn3S0r49UKYMcOoUsHAh0LNnOgXLl9er5DFjtOBHH+kVzOef60/r1hrQR0bm69VpSgqwbZveduj3+sMPum3ZMs/qRER5q1w5wMsLSEzUz67y5XX/unW6vXIF+P13jctvEhEBRERgdp/fEPT5RHTAcuCnn/QH0OhfBEhK0vuBgfoZ9/DD2a5v6dJAu3baoAtoMMgg3j21bm0G8tOmuVcQDwBt2ug1SUSEfo03bgzs3g1MmaJBvLc38OOPuj8mRhugPDz03L14EShVygeRkQ2xDQ0BAB3eBXCnc98TEZEr4te8m6tRQ7eHD2vvkHGR2bq106p0k0KFgIED9fYHH+j1a4Z8fYFevYAtW7RlonNn/ZZfvVqvVGvVAmbM0G6yfPD330BcHFC0qPn7TtfBg9r44OkJPPRQvtSPiHKfl5d2+gHAoUO6TUy0dbIDAFasyPg5Nhe6Cw/ie3w48ICO1GnUyGwdSEoCSpYEnn5auypzEMQbevXSrbc30Lt3jp+OnOSBB4Bu3YBJk4A73TCAffVVHVzy3Xf6nfn447r/xRd1++CDQKtWgL+/NpAZDU5t2+oAvGbNzE72woVdq2OCiMiVMJB3c2XK6BDKlBTtrL52TVu3nTgKPU19+2p8vn27OWogUxaLXsUsXqwB8pAhQLFi2tT/3HN6BTBokF4E56EtW3TbsKEDI/gWLdLtffcBpUrlab2IKG9Vrqzbw4d1u2WLOboXAFautC9/9SowZw5w6ZLeP31atz61qmp0s2ULEBurc4yOHgWio4FZs3SofS546CFg1Cjgs8/48ePOfH2Br74Chg1zdk2yJyBAZ4gUKaL3+/bVrTHtI7NGpmLFgPr19XazZulMXyEiIgby7s5iMYeqf/mlbtu00f2upGRJs1X+66+z8QRhYcB77wH//gu8/752lV28qGP16tXTKPvDD80r51z066+6dahXYOFC3Xbtmuv1IKL8VaWKbo0eeWPEU8uW+hm7axdw8qRZfsIEDVIefFCDFuPjqEyZVE9auLA2QlasqL3zucjTU/OkPPFErj4tUY40bGgG5qGhOrU9Mx062G+JiOhmDOQLgBvnnLdp45x6ZKZRI90eP56DJ/H3BwYP1h76FSuARx/Vsfvbtun+cuV0zN5nnwH//ZfjOl+7Bnz7rd5+8MFMCu/bp1f2Xl65MkyWiJzLCOT37NGtEcg/8gjQpIneXrXKLL9kiW43bADeeEPn1gMavBDdykaO1O3gwY61X40apaP3XnghT6tFROTWGMgXAGFhmlUd0B6ZiAjn1ic9ZcvqNnUPVrZ5emqLxaJFerU8ZYqOwbNagV9+0XmnwcE61nThwmzPp1+2TEfCVqwI3HVXJoU//VS3kZFAiRLZej0ich2tWul21Srg2DFzfvy995qfudu36/b4cTPgBzSQNz7rGMjTra5LF83jM3y4Y+ULFdKZdUzYSESUPn5EFhB9+uj27rs1AbIrKldOt//+m8tPHBQEPP+8ppA+fFjHltaurcmkli3TyXqlSwM9egCbNjmQbc/0v//ptnv3TC4orlwxA/l+/bL/XojIZdStC9SsCSQkAB076gidWrV0ea3bb9cyxoohxmIVd92lc5uNjxmLRdsUiW51JUq43rQ/IiJ3xkC+gOjRQ+eez53r7Jqkz+iRP3PGXHUp14WF6Zi83bv1Z/Ro3RcXp1F58+Y6xn/2bCA+Pt2n+d//dNS+kcwq0zmnX36p6+hUraqpd4nI7Vks5v/+jh26HT5c9xuB/N9/69YI5Nu312zjW7ZoL+TLL7vf8mFERETk+iwiWeievEXExsYiICAAMTEx8Pf3d3Z1CgyrVbPxJiXpMNVcStScORHgjz80O/RXX2n3GqDjXV98URdcLlrUVjwxEfDzMxsb7rhDO/LTZbVqN92+fZpwj5P6iAqMY8fMZejKltVBP97empm+eHHdf+aMlrl2TRfRqFPHSZUlIiIit5aVOJQ98pRvPDzM7M25Mk/eURaLzp///HMd1z9xoo7zP31ax8BWqqTD8WNiAABHjmgQX6SIdrQvXZrJ88+erUG8vz/w5JN5/GaIKD9VrAjcc4/eHjrUXAorMBAICdHbM2dqEF+uHBAe7pRqEhER0S2GgTzlqxvnyaekAPPn63LKmTl92sxZt2SJdnwbnesOCwoCRozQ9aRmzdK01OfP6/jXihWBMWNwNOo8AOC223RYbYbzW//7T4fyA8C4cRrME1GB8sUXuj78oEH2+43h9Z98otvISM4BJiIiovzBQJ7ylRHIGz3yEybo+vLG0jRpEdE5p+XLa3A9frwu//TRR+bScFnm7a2Z7fft0wnxNWtqj/ybb6LlU5XwDoajUblMWhesVmDIEODcOb2if/75bFaGiFxZhQpAr166WEZqRiBvrBffunX+1ouIiIhuXQzkKV8ZCe/+/VeHon74od7fvfvmsteuaQDfvLkmmEpJ0QaA0aM1hgZ0veYc8fLSlPS7dwPffAPUrw/vxDgMxyRM+7GCPrZ69c3Z+RITgb59NbugxQJ8/DEzWhHdYmrUMG9bLOZydURERER5zcvZFaBbS+oe+dmztTMb0ARSN3rqKWDBAr1dqBDwzjvAmjXA8uWaHP7gwVwI5A0eHkCnTsDDD+PlBivQfsebaG7dpMnxvvoKCAgAGjTQ+fTx8cBPP+miuB4eOub2vvtyqSJE5C6MHnkAaNhQZ+4QERER5QcG8pSvjB75Y8eAP/8091+6pD+BgXp/xw4N4i0WYPJkHUpfvrzOiz9wwEw0tWePTlM3skfnmMWC+THt8DbaYdvMKNSPmqUT8s+dA9autS8bGqo98Z065dKLE5E7SR3Ic1g9ERER5ScG8pSvjB55Yzm3EiV0e/Gi9srPmqXT1o2kdo89ptPQDR4eQPXqert6dWD/fmDjRuCBB3KnfomJ2sgAACEPNAKeaaSZrHbu1J/oaB2OHx4ORETobSK6JZUpo4N1YmKA++93dm2IiIjoVsIohPKV0SNveOYZYN06YPNmDcinTzcf8/QEXn01/ee66y4N5DdsyL1A/vBhnX/v52cuLQVPTx1W36BB7rwIERUIFgvw6afa+GgsUUdERESUHxjIU74KDdWLXxHdPvec9oBv3gwsXqxlSpQAihXTLNG33Zb+c7VoAXz2WS7Ok4fOuwd0Dj6XkSKizDzyiLNrQERERLciBvKUr7y9gdKlgTNngA4dNHdc5cr6mBGQd+ig+eMy06KFbqOiNMN94cI5r9+BA7qtWjXnz0VERERERJQXuPwc5bsGDbS325j7HhamWxHdNmzo2POEhekc1aQk7dHPDUaPfLVqufN8REREREREuY2BPOW7L7/UrPT33qv3jUDe4Gggb7GYvfK5Nbx+3z7dMpAnIiIiIiJXxUCe8l3JkkCdOuZ9Y2g9oFnp69Vz/LlyO5DfvVu34eG583xERERERES5jYE8OV358poYHgBq1gSKFHH8WCOQ37QJSE7OWT3OnNHl4i0WrQcREREREZErYiBPTuflpcE84PiwekOtWrqO85Urusx7TuzapduqVbPWmEBERERERJSfGMiTSzCyxDdqlLXjPD2BO+/U2zkdXs9h9URERERE5A4YyJNLeO01XVO+R4+sH2sMr1+zJmd1MAL51PP3iYiIiIiIXA0DeXIJzZsD06bpMPms6tBBt6tWAf/9l/06sEeeiIiIiIjcAQN5cnu1amnwnZQELFmSvedISQH27tXbDOSJiIiIiMiVMZCnAuGxx3Q7f372jj90CIiPBwoXtl8Oj4iIiIiIyNUwkKcCwQjkf/kFiI7O+vFr1+q2dm1zKTwiIiIiIiJXxECeCoTKlYGmTQGrFVi+PGvH7t0LDBumtx98MPfrRkRERERElJsYyFOBce+9ut2yxfFjEhKATp2AuDjgvvuAkSPzpGpERERERES5hoE8FRjGGvRbt9782PvvA08+CVy7Zr//iy+Af/4BQkOBBQsAL688ryYREREREVGOMGyhAsMI5Hft0p52Hx+9//ffOnReBLj9dmDECGDnTuC224CJE7XMSy8BpUo5p95ERERERERZwR55KjAqVgRKlNBl6Iw14QHgtdc0iAeA8eOBLl2A+vWBsmU1W31QEPD0086pMxERERERUVYxkKcCw2Ixe+WjonS7ezewcKHerlgRiIkBFi/W+5cu6XbwYKBo0fysKRERERERUfZxaD0VKI0aAT/9ZM6TnzpVt488Ajz1FNCuHeDtDcybB5w6BRw9CgwZ4rTqEhERERERZRkDeSpQbuyRX7dOtz16AG3bAqtXA2XKADVrOqV6REREREREOcZAngqUhg11u2eP9rbv36/377xTtxERTqkWERERERFRruEceSpQypcHwsKA5GTNRA8AtWoBJUs6t15ERERERES5xSUC+alTp6JSpUrw9fVF06ZN8eeff2ZY/uuvv0aNGjXg6+uL8PBw/Pjjj3aPiwjGjh2L0NBQFC5cGBEREThw4EBevgVyERYL8PjjenvRIt22aOG8+hAREREREeU2pwfyCxcuxNChQzFu3Dhs27YNdevWRWRkJM6ePZtm+d9//x3dunVDnz59sH37dnTs2BEdO3bEnj17bGXeeecdTJkyBdOnT8fmzZtRtGhRREZGIj4+Pr/eFjlR9+729xnIExERERFRQWIRMVbYdo6mTZuicePG+PjjjwEAVqsV5cuXx/PPP4+RI0feVL5r166Ii4vD8uXLbfvuuOMO1KtXD9OnT4eIoEyZMhg2bBhefPFFAEBMTAyCg4MxZ84cPPbYY5nWKTY2FgEBAYiJiYG/v38uvVPKTw0bAtu26e3jx3XIPRERERERkavKShzq1B75xMREbN26FRGpMpB5eHggIiICmzZtSvOYTZs22ZUHgMjISFv5I0eOIDo62q5MQEAAmjZtmu5zJiQkIDY21u6H3NsTT+i2UiUG8UREREREVLA4NZA/f/48UlJSEBwcbLc/ODgY0dHRaR4THR2dYXljm5XnHD9+PAICAmw/5Rn5ub1nntF1499/39k1ISIiIiIiyl1OnyPvCkaNGoWYmBjbz4kTJ5xdJcohPz/gs8+Ajh2dXRMiIiIiIqLc5dRAPigoCJ6enjhz5ozd/jNnziAkJCTNY0JCQjIsb2yz8pw+Pj7w9/e3+yEiIiIiIiJyRU4N5L29vdGwYUOsWbPGts9qtWLNmjVo1qxZmsc0a9bMrjwArF692lY+LCwMISEhdmViY2OxefPmdJ+TiIiIiIiIyF14ObsCQ4cORa9evdCoUSM0adIEH3zwAeLi4tC7d28AQM+ePVG2bFmMHz8eADBo0CDcc889mDx5Mtq3b48FCxYgKioKM2fOBABYLBYMHjwYb775JqpVq4awsDCMGTMGZcqUQUeOsyYiIiIiIiI35/RAvmvXrjh37hzGjh2L6Oho1KtXDytXrrQlqzt+/Dg8PMyBA82bN8dXX32FV155BaNHj0a1atWwdOlS1K5d21ZmxIgRiIuLQ9++fXHp0iXcddddWLlyJXx9ffP9/RERERERERHlJqevI++KuI48ERERERER5Se3WUeeiIiIiIiIiLKGgTwRERERERGRG2EgT0RERERERORGGMgTERERERERuREG8kRERERERERuhIE8ERERERERkRthIE9ERERERETkRhjIExEREREREbkRBvJEREREREREboSBPBEREREREZEbYSBPRERERERE5EYYyBMRERERERG5EQbyRERERERERG7Ey9kVcEUiAgCIjY11ck2IiIiIiIjoVmDEn0Y8mhEG8mm4fPkyAKB8+fJOrgkRERERERHdSi5fvoyAgIAMy1jEkXD/FmO1WnHq1CkUK1YMFovF2dVJV2xsLMqXL48TJ07A39/f2dUhShPPU3IXPFfJHfA8JXfA85TcgSuepyKCy5cvo0yZMvDwyHgWPHvk0+Dh4YFy5co5uxoO8/f3d5mTjyg9PE/JXfBcJXfA85TcAc9Tcgeudp5m1hNvYLI7IiIiIiIiIjfCQJ6IiIiIiIjIjTCQd2M+Pj4YN24cfHx8nF0VonTxPCV3wXOV3AHPU3IHPE/JHbj7ecpkd0RERERERERuhD3yRERERERERG6EgTwRERERERGRG2EgT0RERERERORGGMgTERERERERuREG8m5s6tSpqFSpEnx9fdG0aVP8+eefzq4S3UJ+/fVXdOjQAWXKlIHFYsHSpUvtHhcRjB07FqGhoShcuDAiIiJw4MABuzIXL15E9+7d4e/vj8DAQPTp0wdXrlzJx3dBBdn48ePRuHFjFCtWDKVLl0bHjh2xf/9+uzLx8fEYMGAASpYsCT8/P3Tu3BlnzpyxK3P8+HG0b98eRYoUQenSpTF8+HAkJyfn51uhAm7atGmoU6cO/P394e/vj2bNmmHFihW2x3mekquZMGECLBYLBg8ebNvH85RcwauvvgqLxWL3U6NGDdvjBek8ZSDvphYuXIihQ4di3Lhx2LZtG+rWrYvIyEicPXvW2VWjW0RcXBzq1q2LqVOnpvn4O++8gylTpmD69OnYvHkzihYtisjISMTHx9vKdO/eHXv37sXq1auxfPly/Prrr+jbt29+vQUq4NavX48BAwbgjz/+wOrVq5GUlIT7778fcXFxtjJDhgzB999/j6+//hrr16/HqVOn0KlTJ9vjKSkpaN++PRITE/H7779j7ty5mDNnDsaOHeuMt0QFVLly5TBhwgRs3boVUVFRuO+++/DQQw9h7969AHiekmvZsmULZsyYgTp16tjt53lKrqJWrVo4ffq07ee3336zPVagzlMht9SkSRMZMGCA7X5KSoqUKVNGxo8f78Ra0a0KgCxZssR232q1SkhIiLz77ru2fZcuXRIfHx+ZP3++iIj89ddfAkC2bNliK7NixQqxWCxy8uTJfKs73TrOnj0rAGT9+vUioudkoUKF5Ouvv7aV+fvvvwWAbNq0SUREfvzxR/Hw8JDo6GhbmWnTpom/v78kJCTk7xugW0rx4sXl008/5XlKLuXy5ctSrVo1Wb16tdxzzz0yaNAgEeHnKbmOcePGSd26ddN8rKCdp+yRd0OJiYnYunUrIiIibPs8PDwQERGBTZs2ObFmROrIkSOIjo62O0cDAgLQtGlT2zm6adMmBAYGolGjRrYyERER8PDwwObNm/O9zlTwxcTEAABKlCgBANi6dSuSkpLsztMaNWqgQoUKdudpeHg4goODbWUiIyMRGxtr6y0lyk0pKSlYsGAB4uLi0KxZM56n5FIGDBiA9u3b252PAD9PybUcOHAAZcqUQeXKldG9e3ccP34cQME7T72cXQHKuvPnzyMlJcXuBAOA4OBg7Nu3z0m1IjJFR0cDQJrnqPFYdHQ0Spcubfe4l5cXSpQoYStDlFusVisGDx6MO++8E7Vr1wag56C3tzcCAwPtyt54nqZ1HhuPEeWW3bt3o1mzZoiPj4efnx+WLFmCmjVrYseOHTxPySUsWLAA27Ztw5YtW256jJ+n5CqaNm2KOXPmoHr16jh9+jRee+01tGjRAnv27Clw5ykDeSIiKvAGDBiAPXv22M2TI3Il1atXx44dOxATE4PFixejV69eWL9+vbOrRQQAOHHiBAYNGoTVq1fD19fX2dUhSlfbtm1tt+vUqYOmTZuiYsWKWLRoEQoXLuzEmuU+Dq13Q0FBQfD09Lwpw+KZM2cQEhLipFoRmYzzMKNzNCQk5KbkjMnJybh48SLPY8pVAwcOxPLly7F27VqUK1fOtj8kJASJiYm4dOmSXfkbz9O0zmPjMaLc4u3tjapVq6Jhw4YYP3486tatiw8//JDnKbmErVu34uzZs2jQoAG8vLzg5eWF9evXY8qUKfDy8kJwcDDPU3JJgYGBuO2223Dw4MEC93nKQN4NeXt7o2HDhlizZo1tn9VqxZo1a9CsWTMn1oxIhYWFISQkxO4cjY2NxebNm23naLNmzXDp0iVs3brVVuaXX36B1WpF06ZN873OVPCICAYOHIglS5bgl19+QVhYmN3jDRs2RKFChezO0/379+P48eN25+nu3bvtGp1Wr14Nf39/1KxZM3/eCN2SrFYrEhISeJ6SS2jVqhV2796NHTt22H4aNWqE7t27227zPCVXdOXKFRw6dAihoaEF7/PU2dn2KHsWLFggPj4+MmfOHPnrr7+kb9++EhgYaJdhkSgvXb58WbZv3y7bt28XAPLee+/J9u3b5dixYyIiMmHCBAkMDJTvvvtOdu3aJQ899JCEhYXJtWvXbM/Rpk0bqV+/vmzevFl+++03qVatmnTr1s1Zb4kKmH79+klAQICsW7dOTp8+bfu5evWqrcxzzz0nFSpUkF9++UWioqKkWbNm0qxZM9vjycnJUrt2bbn//vtlx44dsnLlSilVqpSMGjXKGW+JCqiRI0fK+vXr5ciRI7Jr1y4ZOXKkWCwW+emnn0SE5ym5ptRZ60V4npJrGDZsmKxbt06OHDkiGzdulIiICAkKCpKzZ8+KSME6TxnIu7GPPvpIKlSoIN7e3tKkSRP5448/nF0luoWsXbtWANz006tXLxHRJejGjBkjwcHB4uPjI61atZL9+/fbPceFCxekW7du4ufnJ/7+/tK7d2+5fPmyE94NFURpnZ8AZPbs2bYy165dk/79+0vx4sWlSJEi8vDDD8vp06ftnufo0aPStm1bKVy4sAQFBcmwYcMkKSkpn98NFWRPPfWUVKxYUby9vaVUqVLSqlUrWxAvwvOUXNONgTzPU3IFXbt2ldDQUPH29payZctK165d5eDBg7bHC9J5ahERcc5YACIiIiIiIiLKKs6RJyIiIiIiInIjDOSJiIiIiIiI3AgDeSIiIiIiIiI3wkCeiIiIiIiIyI0wkCciIiIiIiJyIwzkiYiIiIiIiNwIA3kiIiIiIiIiN8JAnoiIiLLkySefRMeOHZ1dDSIioluWl7MrQERERK7DYrFk+Pi4cePw4YcfQkTyqUZERER0IwbyREREZHP69Gnb7YULF2Ls2LHYv3+/bZ+fnx/8/PycUTUiIiK6jkPriYiIyCYkJMT2ExAQAIvFYrfPz8/vpqH19957L55//nkMHjwYxYsXR3BwMGbNmoW4uDj07t0bxYoVQ9WqVbFixQq719qzZw/atm0LPz8/BAcHo0ePHjh//nw+v2MiIiL3w0CeiIiIcmzu3LkICgrCn3/+ieeffx79+vXDo48+iubNm2Pbtm24//770aNHD1y9ehUAcOnSJdx3332oX78+oqKisHLlSpw5cwZdunRx8jshIiJyfQzkiYiIKMfq1q2LV155BdWqVcOoUaPg6+uLoKAgPPPMM6hWrRrGjh2LCxcuYNeuXQCAjz/+GPXr18fbb7+NGjVqoH79+vj888+xdu1a/PPPP05+N0RERK6Nc+SJiIgox+rUqWO77enpiZIlSyI8PNy2Lzg4GABw9uxZAMDOnTuxdu3aNOfbHzp0CLfddlse15iIiMh9MZAnIiKiHCtUqJDdfYvFYrfPyIZvtVoBAFeuXEGHDh0wceLEm54rNDQ0D2tKRETk/hjIExERUb5r0KABvvnmG1SqVAleXrwcISIiygrOkSciIqJ8N2DAAFy8eBHdunXDli1bcOjQIaxatQq9e/dGSkqKs6tHRETk0hjIExERUb4rU6YMNm7ciJSUFNx///0IDw/H4MGDERgYCA8PXp4QERFlxCIi4uxKEBEREREREZFj2ORNRERERERE5EYYyBMRERERERG5EQbyRERERERERG6EgTwRERERERGRG2EgT0RERERERORGGMgTERERERERuREG8kRERERERERuhIE8ERERERERkRthIE9ERERERETkRhjIExEREREREbkRBvJEREREREREboSBPBEREREREZEb+T8j8fWykaS5ywAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "plt.plot(y_test,'b',label='Original Price')\n",
    "plt.plot(y_predicted,'r',label='Predicted Price')\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Price')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0baf4a09-ec85-43dd-8b77-50f58fce79a3",
   "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}