从零开始卷量化(16).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ccae1da6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#pip install  matplotlib==3.2.2\n",
    "#sudo apt-get install ttf-wqy-zenhei -y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "94c13315",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting Portfolio Value: 10000.00\n",
      "Final Portfolio Value: 10000.00\n"
     ]
    }
   ],
   "source": [
    "from __future__ import (absolute_import, division, print_function,\n",
    "                        unicode_literals)\n",
    "\n",
    "import backtrader as bt\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    cerebro = bt.Cerebro()\n",
    "\n",
    "    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())\n",
    "\n",
    "    cerebro.run()\n",
    "\n",
    "    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ac6b88f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>outstanding_share</th>\n",
       "      <th>turnover</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-01-04</th>\n",
       "      <td>29.28</td>\n",
       "      <td>30.35</td>\n",
       "      <td>28.91</td>\n",
       "      <td>29.89</td>\n",
       "      <td>43601981.0</td>\n",
       "      <td>1.789981e+09</td>\n",
       "      <td>0.024359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-05</th>\n",
       "      <td>29.59</td>\n",
       "      <td>31.32</td>\n",
       "      <td>29.49</td>\n",
       "      <td>30.62</td>\n",
       "      <td>43608514.0</td>\n",
       "      <td>1.789981e+09</td>\n",
       "      <td>0.024363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-06</th>\n",
       "      <td>30.63</td>\n",
       "      <td>31.01</td>\n",
       "      <td>29.57</td>\n",
       "      <td>29.98</td>\n",
       "      <td>33244642.0</td>\n",
       "      <td>1.789981e+09</td>\n",
       "      <td>0.018573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-07</th>\n",
       "      <td>29.51</td>\n",
       "      <td>29.73</td>\n",
       "      <td>28.20</td>\n",
       "      <td>28.81</td>\n",
       "      <td>43046178.0</td>\n",
       "      <td>1.789981e+09</td>\n",
       "      <td>0.024048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-08</th>\n",
       "      <td>28.50</td>\n",
       "      <td>31.03</td>\n",
       "      <td>28.36</td>\n",
       "      <td>30.21</td>\n",
       "      <td>69925572.0</td>\n",
       "      <td>1.789981e+09</td>\n",
       "      <td>0.039065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-24</th>\n",
       "      <td>13.31</td>\n",
       "      <td>13.37</td>\n",
       "      <td>12.94</td>\n",
       "      <td>12.99</td>\n",
       "      <td>40061843.0</td>\n",
       "      <td>1.827237e+09</td>\n",
       "      <td>0.021925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-25</th>\n",
       "      <td>13.03</td>\n",
       "      <td>13.20</td>\n",
       "      <td>12.78</td>\n",
       "      <td>12.80</td>\n",
       "      <td>35072959.0</td>\n",
       "      <td>1.827237e+09</td>\n",
       "      <td>0.019195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-28</th>\n",
       "      <td>12.75</td>\n",
       "      <td>13.10</td>\n",
       "      <td>12.71</td>\n",
       "      <td>12.98</td>\n",
       "      <td>33790788.0</td>\n",
       "      <td>1.827237e+09</td>\n",
       "      <td>0.018493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-29</th>\n",
       "      <td>13.00</td>\n",
       "      <td>13.07</td>\n",
       "      <td>12.68</td>\n",
       "      <td>12.78</td>\n",
       "      <td>31143671.0</td>\n",
       "      <td>1.827237e+09</td>\n",
       "      <td>0.017044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-30</th>\n",
       "      <td>12.78</td>\n",
       "      <td>13.27</td>\n",
       "      <td>12.74</td>\n",
       "      <td>13.02</td>\n",
       "      <td>34915307.0</td>\n",
       "      <td>1.827237e+09</td>\n",
       "      <td>0.019108</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>300 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             open   high    low  close      volume  outstanding_share  \\\n",
       "date                                                                    \n",
       "2021-01-04  29.28  30.35  28.91  29.89  43601981.0       1.789981e+09   \n",
       "2021-01-05  29.59  31.32  29.49  30.62  43608514.0       1.789981e+09   \n",
       "2021-01-06  30.63  31.01  29.57  29.98  33244642.0       1.789981e+09   \n",
       "2021-01-07  29.51  29.73  28.20  28.81  43046178.0       1.789981e+09   \n",
       "2021-01-08  28.50  31.03  28.36  30.21  69925572.0       1.789981e+09   \n",
       "...           ...    ...    ...    ...         ...                ...   \n",
       "2022-03-24  13.31  13.37  12.94  12.99  40061843.0       1.827237e+09   \n",
       "2022-03-25  13.03  13.20  12.78  12.80  35072959.0       1.827237e+09   \n",
       "2022-03-28  12.75  13.10  12.71  12.98  33790788.0       1.827237e+09   \n",
       "2022-03-29  13.00  13.07  12.68  12.78  31143671.0       1.827237e+09   \n",
       "2022-03-30  12.78  13.27  12.74  13.02  34915307.0       1.827237e+09   \n",
       "\n",
       "            turnover  \n",
       "date                  \n",
       "2021-01-04  0.024359  \n",
       "2021-01-05  0.024363  \n",
       "2021-01-06  0.018573  \n",
       "2021-01-07  0.024048  \n",
       "2021-01-08  0.039065  \n",
       "...              ...  \n",
       "2022-03-24  0.021925  \n",
       "2022-03-25  0.019195  \n",
       "2022-03-28  0.018493  \n",
       "2022-03-29  0.017044  \n",
       "2022-03-30  0.019108  \n",
       "\n",
       "[300 rows x 7 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import akshare as ak\n",
    "wanmei = ak.stock_zh_a_daily(symbol=\"sz002624\", start_date=\"20210101\",\n",
    "                             end_date=\"20220330\", adjust=\"qfq\")\n",
    "wanmei=wanmei.set_index('date')\n",
    "wanmei"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "abdbbb2d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "今天是：2021-01-04，星期1，收盘价是：29.89\n",
      "今天是：2021-01-05，星期2，收盘价是：30.62\n",
      "今天是：2021-01-06，星期3，收盘价是：29.98\n",
      "今天是：2021-01-07，星期4，收盘价是：28.81\n",
      "今天是：2021-01-08，星期5，收盘价是：30.21\n",
      "今天是：2021-01-11，星期1，收盘价是：29.48\n",
      "今天是：2021-01-12，星期2，收盘价是：27.58\n",
      "今天是：2021-01-13，星期3，收盘价是：26.99\n",
      "今天是：2021-01-14，星期4，收盘价是：25.88\n",
      "今天是：2021-01-15，星期5，收盘价是：25.71\n",
      "今天是：2021-01-18，星期1，收盘价是：26.59\n",
      "今天是：2021-01-19，星期2，收盘价是：26.14\n",
      "今天是：2021-01-20，星期3，收盘价是：26.39\n",
      "今天是：2021-01-21，星期4，收盘价是：27.61\n",
      "今天是：2021-01-22，星期5，收盘价是：27.2\n",
      "今天是：2021-01-25，星期1，收盘价是：25.97\n",
      "今天是：2021-01-26，星期2，收盘价是：25.99\n",
      "今天是：2021-01-27，星期3，收盘价是：27.8\n",
      "今天是：2021-01-28，星期4，收盘价是：27.53\n",
      "今天是：2021-01-29，星期5，收盘价是：27.09\n",
      "今天是：2021-02-01，星期1，收盘价是：27.53\n",
      "今天是：2021-02-02，星期2，收盘价是：26.52\n",
      "今天是：2021-02-03，星期3，收盘价是：26.26\n",
      "今天是：2021-02-04，星期4，收盘价是：23.69\n",
      "今天是：2021-02-05，星期5，收盘价是：23.18\n",
      "今天是：2021-02-08，星期1，收盘价是：22.8\n",
      "今天是：2021-02-09，星期2，收盘价是：23.21\n",
      "今天是：2021-02-10，星期3，收盘价是：23.52\n",
      "今天是：2021-02-18，星期4，收盘价是：23.97\n",
      "今天是：2021-02-19，星期5，收盘价是：25.25\n",
      "今天是：2021-02-22，星期1，收盘价是：24.49\n",
      "今天是：2021-02-23，星期2，收盘价是：23.9\n",
      "今天是：2021-02-24，星期3，收盘价是：24.06\n",
      "今天是：2021-02-25，星期4，收盘价是：23.69\n",
      "今天是：2021-02-26，星期5，收盘价是：23.43\n",
      "今天是：2021-03-01，星期1，收盘价是：24.14\n",
      "今天是：2021-03-02，星期2，收盘价是：24.31\n",
      "今天是：2021-03-03，星期3，收盘价是：24.64\n",
      "今天是：2021-03-04，星期4，收盘价是：24.66\n",
      "今天是：2021-03-05，星期5，收盘价是：24.86\n",
      "今天是：2021-03-08，星期1，收盘价是：24.86\n",
      "今天是：2021-03-09，星期2，收盘价是：23.71\n",
      "今天是：2021-03-10，星期3，收盘价是：22.62\n",
      "今天是：2021-03-11，星期4，收盘价是：22.89\n",
      "今天是：2021-03-12，星期5，收盘价是：21.99\n",
      "今天是：2021-03-15，星期1，收盘价是：19.8\n",
      "今天是：2021-03-16，星期2，收盘价是：19.82\n",
      "今天是：2021-03-17，星期3，收盘价是：19.91\n",
      "今天是：2021-03-18，星期4，收盘价是：19.66\n",
      "今天是：2021-03-19，星期5，收盘价是：19.13\n",
      "今天是：2021-03-22，星期1，收盘价是：19.16\n",
      "今天是：2021-03-23，星期2，收盘价是：19.22\n",
      "今天是：2021-03-24，星期3，收盘价是：19.62\n",
      "今天是：2021-03-25，星期4，收盘价是：19.34\n",
      "今天是：2021-03-26，星期5，收盘价是：19.41\n",
      "今天是：2021-03-29，星期1，收盘价是：19.13\n",
      "今天是：2021-03-30，星期2，收盘价是：19.45\n",
      "今天是：2021-03-31，星期3，收盘价是：19.64\n",
      "今天是：2021-04-01，星期4，收盘价是：19.92\n",
      "今天是：2021-04-02，星期5，收盘价是：19.74\n",
      "今天是：2021-04-06，星期2，收盘价是：20.37\n",
      "今天是：2021-04-07，星期3，收盘价是：20.33\n",
      "今天是：2021-04-08，星期4，收盘价是：20.65\n",
      "今天是：2021-04-09，星期5，收盘价是：20.64\n",
      "今天是：2021-04-12，星期1，收盘价是：19.81\n",
      "今天是：2021-04-13，星期2，收盘价是：20.04\n",
      "今天是：2021-04-14，星期3，收盘价是：21.07\n",
      "今天是：2021-04-15，星期4，收盘价是：21.18\n",
      "今天是：2021-04-16，星期5，收盘价是：21.33\n",
      "今天是：2021-04-19，星期1，收盘价是：21.6\n",
      "今天是：2021-04-20，星期2，收盘价是：22.27\n",
      "今天是：2021-04-21，星期3，收盘价是：22.02\n",
      "今天是：2021-04-22，星期4，收盘价是：22.09\n",
      "今天是：2021-04-23，星期5，收盘价是：21.71\n",
      "今天是：2021-04-26，星期1，收盘价是：21.14\n",
      "今天是：2021-04-27，星期2，收盘价是：20.95\n",
      "今天是：2021-04-28，星期3，收盘价是：21.46\n",
      "今天是：2021-04-29，星期4，收盘价是：21.6\n",
      "今天是：2021-04-30，星期5，收盘价是：21.16\n",
      "今天是：2021-05-06，星期4，收盘价是：20.77\n",
      "今天是：2021-05-07，星期5，收盘价是：20.26\n",
      "今天是：2021-05-10，星期1，收盘价是：20.17\n",
      "今天是：2021-05-11，星期2，收盘价是：20.35\n",
      "今天是：2021-05-12，星期3，收盘价是：20.91\n",
      "今天是：2021-05-13，星期4，收盘价是：20.72\n",
      "今天是：2021-05-14，星期5，收盘价是：20.81\n",
      "今天是：2021-05-17，星期1，收盘价是：21.3\n",
      "今天是：2021-05-18，星期2，收盘价是：21.05\n",
      "今天是：2021-05-19，星期3，收盘价是：21.02\n",
      "今天是：2021-05-20，星期4，收盘价是：22.44\n",
      "今天是：2021-05-21，星期5，收盘价是：21.7\n",
      "今天是：2021-05-24，星期1，收盘价是：21.91\n",
      "今天是：2021-05-25，星期2，收盘价是：22.41\n",
      "今天是：2021-05-26，星期3，收盘价是：21.98\n",
      "今天是：2021-05-27，星期4，收盘价是：22.21\n",
      "今天是：2021-05-28，星期5，收盘价是：21.5\n",
      "今天是：2021-05-31，星期1，收盘价是：21.3\n",
      "今天是：2021-06-01，星期2，收盘价是：21.11\n",
      "今天是：2021-06-02，星期3，收盘价是：20.6\n",
      "今天是：2021-06-03，星期4，收盘价是：20.81\n",
      "今天是：2021-06-04，星期5，收盘价是：20.94\n",
      "今天是：2021-06-07，星期1，收盘价是：21.63\n",
      "今天是：2021-06-08，星期2，收盘价是：22.08\n",
      "今天是：2021-06-09，星期3，收盘价是：22.03\n",
      "今天是：2021-06-10，星期4，收盘价是：21.93\n",
      "今天是：2021-06-11，星期5，收盘价是：21.19\n",
      "今天是：2021-06-15，星期2，收盘价是：21.21\n",
      "今天是：2021-06-16，星期3，收盘价是：20.41\n",
      "今天是：2021-06-17，星期4，收盘价是：20.12\n",
      "今天是：2021-06-18，星期5，收盘价是：20.86\n",
      "今天是：2021-06-21，星期1，收盘价是：22.95\n",
      "今天是：2021-06-22，星期2，收盘价是：23.08\n",
      "今天是：2021-06-23，星期3，收盘价是：24.4\n",
      "今天是：2021-06-24，星期4，收盘价是：23.82\n",
      "今天是：2021-06-25，星期5，收盘价是：23.19\n",
      "今天是：2021-06-28，星期1，收盘价是：24.98\n",
      "今天是：2021-06-29，星期2，收盘价是：23.95\n",
      "今天是：2021-06-30，星期3，收盘价是：23.91\n",
      "今天是：2021-07-01，星期4，收盘价是：23.4\n",
      "今天是：2021-07-02，星期5，收盘价是：23.55\n",
      "今天是：2021-07-05，星期1，收盘价是：23.18\n",
      "今天是：2021-07-06，星期2，收盘价是：22.3\n",
      "今天是：2021-07-07，星期3，收盘价是：22.1\n",
      "今天是：2021-07-08，星期4，收盘价是：21.21\n",
      "今天是：2021-07-09，星期5，收盘价是：20.54\n",
      "今天是：2021-07-12，星期1，收盘价是：18.8\n",
      "今天是：2021-07-13，星期2，收盘价是：19.19\n",
      "今天是：2021-07-14，星期3，收盘价是：19.33\n",
      "今天是：2021-07-15，星期4，收盘价是：19.91\n",
      "今天是：2021-07-16，星期5，收盘价是：20.15\n",
      "今天是：2021-07-19，星期1，收盘价是：19.45\n",
      "今天是：2021-07-20，星期2，收盘价是：19.75\n",
      "今天是：2021-07-21，星期3，收盘价是：19.44\n",
      "今天是：2021-07-22，星期4，收盘价是：19.46\n",
      "今天是：2021-07-23，星期5，收盘价是：18.88\n",
      "今天是：2021-07-26，星期1，收盘价是：17.04\n",
      "今天是：2021-07-27，星期2，收盘价是：15.9\n",
      "今天是：2021-07-28，星期3，收盘价是：15.34\n",
      "今天是：2021-07-29，星期4，收盘价是：15.97\n",
      "今天是：2021-07-30，星期5，收盘价是：15.91\n",
      "今天是：2021-08-02，星期1，收盘价是：16.26\n",
      "今天是：2021-08-03，星期2，收盘价是：15.4\n",
      "今天是：2021-08-04，星期3，收盘价是：15.34\n",
      "今天是：2021-08-05，星期4，收盘价是：14.91\n",
      "今天是：2021-08-06，星期5，收盘价是：14.51\n",
      "今天是：2021-08-09，星期1，收盘价是：14.8\n",
      "今天是：2021-08-10，星期2，收盘价是：15.05\n",
      "今天是：2021-08-11，星期3，收盘价是：14.94\n",
      "今天是：2021-08-12，星期4，收盘价是：14.87\n",
      "今天是：2021-08-13，星期5，收盘价是：14.62\n",
      "今天是：2021-08-16，星期1，收盘价是：14.7\n",
      "今天是：2021-08-17，星期2，收盘价是：14.66\n",
      "今天是：2021-08-18，星期3，收盘价是：14.8\n",
      "今天是：2021-08-19，星期4，收盘价是：15.02\n",
      "今天是：2021-08-20，星期5，收盘价是：14.56\n",
      "今天是：2021-08-23，星期1，收盘价是：14.91\n",
      "今天是：2021-08-24，星期2，收盘价是：14.85\n",
      "今天是：2021-08-25，星期3，收盘价是：15.29\n",
      "今天是：2021-08-26，星期4，收盘价是：14.8\n",
      "今天是：2021-08-27，星期5，收盘价是：14.52\n",
      "今天是：2021-08-30，星期1，收盘价是：13.6\n",
      "今天是：2021-08-31，星期2，收盘价是：13.42\n",
      "今天是：2021-09-01，星期3，收盘价是：14.76\n",
      "今天是：2021-09-02，星期4，收盘价是：15.18\n",
      "今天是：2021-09-03，星期5，收盘价是：15.2\n",
      "今天是：2021-09-06，星期1，收盘价是：15.66\n",
      "今天是：2021-09-07，星期2，收盘价是：16.35\n",
      "今天是：2021-09-08，星期3，收盘价是：17.68\n",
      "今天是：2021-09-09，星期4，收盘价是：16.6\n",
      "今天是：2021-09-10，星期5，收盘价是：15.95\n",
      "今天是：2021-09-13，星期1，收盘价是：16.92\n",
      "今天是：2021-09-14，星期2，收盘价是：16.52\n",
      "今天是：2021-09-15，星期3，收盘价是：16.57\n",
      "今天是：2021-09-16，星期4，收盘价是：15.91\n",
      "今天是：2021-09-17，星期5，收盘价是：15.65\n",
      "今天是：2021-09-22，星期3，收盘价是：15.3\n",
      "今天是：2021-09-23，星期4，收盘价是：15.76\n",
      "今天是：2021-09-24，星期5，收盘价是：16.01\n",
      "今天是：2021-09-27，星期1，收盘价是：15.46\n",
      "今天是：2021-09-28，星期2，收盘价是：15.28\n",
      "今天是：2021-09-29，星期3，收盘价是：14.63\n",
      "今天是：2021-09-30，星期4，收盘价是：15.08\n",
      "今天是：2021-10-08，星期5，收盘价是：15.06\n",
      "今天是：2021-10-11，星期1，收盘价是：15.76\n",
      "今天是：2021-10-12，星期2，收盘价是：14.86\n",
      "今天是：2021-10-13，星期3，收盘价是：15.0\n",
      "今天是：2021-10-14，星期4，收盘价是：14.84\n",
      "今天是：2021-10-15，星期5，收盘价是：15.0\n",
      "今天是：2021-10-18，星期1，收盘价是：14.5\n",
      "今天是：2021-10-19，星期2，收盘价是：14.97\n",
      "今天是：2021-10-20，星期3，收盘价是：15.38\n",
      "今天是：2021-10-21，星期4，收盘价是：15.19\n",
      "今天是：2021-10-22，星期5，收盘价是：15.37\n",
      "今天是：2021-10-25，星期1，收盘价是：15.46\n",
      "今天是：2021-10-26，星期2，收盘价是：16.16\n",
      "今天是：2021-10-27，星期3，收盘价是：16.46\n",
      "今天是：2021-10-28，星期4，收盘价是：16.51\n",
      "今天是：2021-10-29，星期5，收盘价是：17.38\n",
      "今天是：2021-11-01，星期1，收盘价是：17.42\n",
      "今天是：2021-11-02，星期2，收盘价是：16.95\n",
      "今天是：2021-11-03，星期3，收盘价是：17.15\n",
      "今天是：2021-11-04，星期4，收盘价是：17.85\n",
      "今天是：2021-11-05，星期5，收盘价是：18.59\n",
      "今天是：2021-11-08，星期1，收盘价是：18.98\n",
      "今天是：2021-11-09，星期2，收盘价是：18.36\n",
      "今天是：2021-11-10，星期3，收盘价是：18.93\n",
      "今天是：2021-11-11，星期4，收盘价是：18.96\n",
      "今天是：2021-11-12，星期5，收盘价是：19.5\n",
      "今天是：2021-11-15，星期1，收盘价是：20.48\n",
      "今天是：2021-11-16，星期2，收盘价是：21.28\n",
      "今天是：2021-11-17，星期3，收盘价是：20.84\n",
      "今天是：2021-11-18，星期4，收盘价是：19.45\n",
      "今天是：2021-11-19，星期5，收盘价是：19.83\n",
      "今天是：2021-11-22，星期1，收盘价是：19.74\n",
      "今天是：2021-11-23，星期2，收盘价是：19.95\n",
      "今天是：2021-11-24，星期3，收盘价是：19.96\n",
      "今天是：2021-11-25，星期4，收盘价是：19.76\n",
      "今天是：2021-11-26，星期5，收盘价是：19.87\n",
      "今天是：2021-11-29，星期1，收盘价是：19.69\n",
      "今天是：2021-11-30，星期2，收盘价是：18.84\n",
      "今天是：2021-12-01，星期3，收盘价是：18.92\n",
      "今天是：2021-12-02，星期4，收盘价是：18.58\n",
      "今天是：2021-12-03，星期5，收盘价是：19.23\n",
      "今天是：2021-12-06，星期1，收盘价是：19.31\n",
      "今天是：2021-12-07，星期2，收盘价是：19.03\n",
      "今天是：2021-12-08，星期3，收盘价是：20.93\n",
      "今天是：2021-12-09，星期4，收盘价是：20.83\n",
      "今天是：2021-12-10，星期5，收盘价是：21.05\n",
      "今天是：2021-12-13，星期1，收盘价是：21.95\n",
      "今天是：2021-12-14，星期2，收盘价是：22.38\n",
      "今天是：2021-12-15，星期3，收盘价是：21.76\n",
      "今天是：2021-12-16，星期4，收盘价是：21.85\n",
      "今天是：2021-12-17，星期5，收盘价是：21.53\n",
      "今天是：2021-12-20，星期1，收盘价是：19.5\n",
      "今天是：2021-12-21，星期2，收盘价是：19.55\n",
      "今天是：2021-12-22，星期3，收盘价是：20.31\n",
      "今天是：2021-12-23，星期4，收盘价是：20.35\n",
      "今天是：2021-12-24，星期5，收盘价是：20.82\n",
      "今天是：2021-12-27，星期1，收盘价是：19.43\n",
      "今天是：2021-12-28，星期2，收盘价是：19.47\n",
      "今天是：2021-12-29，星期3，收盘价是：19.16\n",
      "今天是：2021-12-30，星期4，收盘价是：20.26\n",
      "今天是：2021-12-31，星期5，收盘价是：20.31\n",
      "今天是：2022-01-04，星期2，收盘价是：20.66\n",
      "今天是：2022-01-05，星期3，收盘价是：20.49\n",
      "今天是：2022-01-06，星期4，收盘价是：19.74\n",
      "今天是：2022-01-07，星期5，收盘价是：19.18\n",
      "今天是：2022-01-10，星期1，收盘价是：18.45\n",
      "今天是：2022-01-11，星期2，收盘价是：17.91\n",
      "今天是：2022-01-12，星期3，收盘价是：17.96\n",
      "今天是：2022-01-13，星期4，收盘价是：17.32\n",
      "今天是：2022-01-14，星期5，收盘价是：17.22\n",
      "今天是：2022-01-17，星期1，收盘价是：17.4\n",
      "今天是：2022-01-18，星期2，收盘价是：16.92\n",
      "今天是：2022-01-19，星期3，收盘价是：17.16\n",
      "今天是：2022-01-20，星期4，收盘价是：16.86\n",
      "今天是：2022-01-21，星期5，收盘价是：16.26\n",
      "今天是：2022-01-24，星期1，收盘价是：14.63\n",
      "今天是：2022-01-25，星期2，收盘价是：13.87\n",
      "今天是：2022-01-26，星期3，收盘价是：13.66\n",
      "今天是：2022-01-27，星期4，收盘价是：13.25\n",
      "今天是：2022-01-28，星期5，收盘价是：13.61\n",
      "今天是：2022-02-07，星期1，收盘价是：13.76\n",
      "今天是：2022-02-08，星期2，收盘价是：13.84\n",
      "今天是：2022-02-09，星期3，收盘价是：14.12\n",
      "今天是：2022-02-10，星期4，收盘价是：14.2\n",
      "今天是：2022-02-11，星期5，收盘价是：13.76\n",
      "今天是：2022-02-14，星期1，收盘价是：13.78\n",
      "今天是：2022-02-15，星期2，收盘价是：13.82\n",
      "今天是：2022-02-16，星期3，收盘价是：13.94\n",
      "今天是：2022-02-17，星期4，收盘价是：13.97\n",
      "今天是：2022-02-18，星期5，收盘价是：14.02\n",
      "今天是：2022-02-21，星期1，收盘价是：14.08\n",
      "今天是：2022-02-22，星期2，收盘价是：13.49\n",
      "今天是：2022-02-23，星期3，收盘价是：13.73\n",
      "今天是：2022-02-24，星期4，收盘价是：13.18\n",
      "今天是：2022-02-25，星期5，收盘价是：13.32\n",
      "今天是：2022-02-28，星期1，收盘价是：13.2\n",
      "今天是：2022-03-01，星期2，收盘价是：13.2\n",
      "今天是：2022-03-02，星期3，收盘价是：13.15\n",
      "今天是：2022-03-03，星期4，收盘价是：13.09\n",
      "今天是：2022-03-04，星期5，收盘价是：13.15\n",
      "今天是：2022-03-07，星期1，收盘价是：12.59\n",
      "今天是：2022-03-08，星期2，收盘价是：12.18\n",
      "今天是：2022-03-09，星期3，收盘价是：11.9\n",
      "今天是：2022-03-10，星期4，收盘价是：11.95\n",
      "今天是：2022-03-11，星期5，收盘价是：12.36\n",
      "今天是：2022-03-14，星期1，收盘价是：12.13\n",
      "今天是：2022-03-15，星期2，收盘价是：11.39\n",
      "今天是：2022-03-16，星期3，收盘价是：11.73\n",
      "今天是：2022-03-17，星期4，收盘价是：12.9\n",
      "今天是：2022-03-18，星期5，收盘价是：12.72\n",
      "今天是：2022-03-21，星期1，收盘价是：13.0\n",
      "今天是：2022-03-22，星期2，收盘价是：13.25\n",
      "今天是：2022-03-23，星期3，收盘价是：13.51\n",
      "今天是：2022-03-24，星期4，收盘价是：12.99\n",
      "今天是：2022-03-25，星期5，收盘价是：12.8\n",
      "今天是：2022-03-28，星期1，收盘价是：12.98\n",
      "今天是：2022-03-29，星期2，收盘价是：12.78\n",
      "今天是：2022-03-30，星期3，收盘价是：13.02\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<__main__.TestStrategy at 0x7f5fb042e5e0>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import backtrader as bt\n",
    "\n",
    "class TestStrategy(bt.Strategy):\n",
    "    def next(self):\n",
    "        today=self.datas[0].datetime.date()\n",
    "        weekday=today.weekday()+1\n",
    "        close=self.datas[0].close[0]\n",
    "        print(\"今天是：\"+str(today)+\"，星期\"+str(weekday)\n",
    "              +\"，收盘价是：\"+str(close))\n",
    "\n",
    "cerebro = bt.Cerebro()\n",
    "cerebro.addstrategy(TestStrategy)\n",
    "#\n",
    "data = bt.feeds.PandasData(dataname=wanmei)\n",
    "cerebro.adddata(data)\n",
    "\n",
    "cerebro.broker.setcash(100000.0)\n",
    "cerebro.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "42f16a78",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "buy3300\n",
      "100000.0\n",
      "2353.0\n",
      "2353.0\n",
      "sell3300\n",
      "2353.0\n",
      "96403.0\n",
      "buy3200\n",
      "96403.0\n",
      "3635.0\n",
      "3635.0\n",
      "sell3200\n",
      "3635.0\n",
      "86707.0\n",
      "buy3200\n",
      "86707.0\n",
      "1555.0\n",
      "1555.0\n",
      "sell3200\n",
      "1555.0\n",
      "90195.0\n",
      "buy3400\n",
      "90195.0\n",
      "2747.0\n",
      "2747.0\n",
      "sell3400\n",
      "2747.0\n",
      "96927.0\n",
      "buy3500\n",
      "96927.0\n",
      "502.0\n",
      "502.0\n",
      "sell3500\n",
      "502.0\n",
      "83592.0\n",
      "buy3600\n",
      "83592.0\n",
      "1368.0\n",
      "1368.0\n",
      "sell3600\n",
      "1368.0\n",
      "87624.0\n",
      "buy3500\n",
      "87624.0\n",
      "2819.0\n",
      "2819.0\n",
      "sell3500\n",
      "2819.0\n",
      "84474.0\n",
      "buy3400\n",
      "84474.0\n",
      "2092.0\n",
      "2092.0\n",
      "sell3400\n",
      "2092.0\n",
      "85426.0\n",
      "buy3400\n",
      "85426.0\n",
      "2058.0\n",
      "2058.0\n",
      "sell3400\n",
      "2058.0\n",
      "79034.0\n",
      "buy3900\n",
      "79034.0\n",
      "3608.0\n",
      "3608.0\n",
      "sell3900\n",
      "3608.0\n",
      "79502.0\n",
      "buy4100\n",
      "79502.0\n",
      "741.0\n",
      "741.0\n",
      "sell4100\n",
      "741.0\n",
      "80404.0\n",
      "buy4200\n",
      "80404.0\n",
      "58.0\n",
      "58.0\n",
      "sell4200\n",
      "58.0\n",
      "83764.0\n",
      "83764.0\n",
      "83764.0\n",
      "sell0\n",
      "83764.0\n",
      "83764.0\n",
      "buy4200\n",
      "83764.0\n",
      "898.0\n",
      "898.0\n",
      "sell4200\n",
      "898.0\n",
      "89938.0\n",
      "buy4100\n",
      "89938.0\n",
      "1829.0\n",
      "1829.0\n",
      "sell4100\n",
      "1829.0\n",
      "92398.0\n",
      "buy4300\n",
      "92398.0\n",
      "1410.0\n",
      "1410.0\n",
      "sell4300\n",
      "1410.0\n",
      "93774.0\n",
      "sell0\n",
      "93774.0\n",
      "93774.0\n",
      "buy4600\n",
      "93774.0\n",
      "1866.0\n",
      "1866.0\n",
      "sell4600\n",
      "1866.0\n",
      "97546.0\n",
      "buy4500\n",
      "97546.0\n",
      "1696.0\n",
      "1696.0\n",
      "sell4500\n",
      "1696.0\n",
      "102676.0\n",
      "buy4600\n",
      "102676.0\n",
      "1798.0\n",
      "1798.0\n",
      "sell4600\n",
      "1798.0\n",
      "104010.0\n",
      "buy4800\n",
      "104010.0\n",
      "2393.9999999999854\n",
      "2393.9999999999854\n",
      "sell4800\n",
      "2393.9999999999854\n",
      "102330.0\n",
      "buy4700\n",
      "102330.0\n",
      "810.0\n",
      "810.0\n",
      "sell4700\n",
      "810.0\n",
      "103928.0\n",
      "103928.0\n",
      "103928.0\n",
      "sell0\n",
      "103928.0\n",
      "103928.0\n",
      "buy4500\n",
      "103928.0\n",
      "103928.0\n",
      "103928.0\n",
      "sell0\n",
      "103928.0\n",
      "103928.0\n",
      "buy4100\n",
      "103928.0\n",
      "103928.0\n",
      "103928.0\n",
      "sell0\n",
      "103928.0\n",
      "103928.0\n",
      "buy4400\n",
      "103928.0\n",
      "1848.0\n",
      "1848.0\n",
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      "95216.0\n",
      "buy5000\n",
      "95216.0\n",
      "1466.0\n",
      "1466.0\n",
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      "1466.0\n",
      "101466.0\n",
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      "1678.0\n",
      "1678.0\n",
      "sell5200\n",
      "1678.0\n",
      "102402.0\n",
      "buy6000\n",
      "102402.0\n",
      "462.00000000001455\n",
      "462.00000000001455\n",
      "sell6000\n",
      "462.00000000001455\n",
      "96162.0\n",
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      "96162.0\n",
      "2942.0\n",
      "2942.0\n",
      "sell5900\n",
      "2942.0\n",
      "90911.0\n",
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      "753.0\n",
      "753.0\n",
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      "753.0\n",
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    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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Tv0RBfjZs2esv4ULF7L+qFGft27dYkJPNB7hdsqRJVEoFxcXdUT2/5paLNeR/V4e639nnP/V3Ip/x1rfbq/yPH5bcyPPx7c1H58zmk+Zw82buTIhRkbA9u1Ajx5AUhLw669AzeoKlMh8DGMFJ0yk8vSEeTEPJmZDYIXyF+n//5VFtdDWwcFAzZrA69ecQBFVmKAaoQULAlZWAOV6Jq3gFGstuzZFelAYUi/cRubY0dgV35TZs0oVoGJFQEgcC+0+AUknrsJ+wUgkHr6A1D8fwmnDNJg3zwa/2nMeUL0b0p+/h8v+xYgYvQiZvkFwO7EaxpVKSd4e/tW6IePFe5jNHI2kiQtYEmj+sCs50gXfe9WDKjmFjSes9xTEGTmifNDBj85BeZy//MIJUnV+NxPVlVfYPhnQxybLIfjLtSFu3ACjxhIFW0iPTb56DyGthsOgqDesB3ZAxODZMKlZCa77FkleS/zuk4gYMgemtX+CUfniiJm/CZbdm8FhwSjJYyJGLkD8tj9gM7YXkJ6JmMVbYdmzJRzmDZc8JqBGd6Q/eweXfYtgULVsnnJkU+88QdCvA6Cfzw1ed/dI9h27dh+iJq2Aecs60Hd1QOzK3bDq3w720weJHkMOpvCFO5A4fx1UNatDFRYB3efPMSR+Ku5Z12Ygie6tT82Fpn4pr5io1eSoofuYwJYYuZHflwSsaH+abxKvItGuUqWAgvmznV36hp9XY+hT3lWf8y78GscsWADQe/XJE83SS4cOHWKRyfPnzzNhI2EOaLdu3RAWFoY9e/YgPDycKfbOnDmTgUVqBH5JydfIyAj+/v5o0KABxo8fj86dO6svkaKfVapUYfmmVPqG759sTHTcjh07smPo/O3bt8fDhw+RP39+BAQEoHbt2qLbC9ILT6vx/TVp0gSTJ09mAJvvr0CBAmz8P/30Ezp16sTAtvB8Xl5eiIiIgL29PaZPN2TU4jFjzrLr0RZ7InsYZCWN07jJfkKxJwLFcvmdr3GH/4vnrFGjBqvnNGzYsH/tLP369cMPP/yAAQMG/GvnyGvHvGw3eXuoTpXcvk8L/Bc/ZN/nTHCjlufje569T5vDv/7iwBoB0vnzgdGjAQoSkEANtY7GhzHdfLHaIGkqQ/wcfRhxKksNI/32G7Bsmfhi+FuzJuVqLl/OgXYCWlWrcotyWrSbPb8Hg6hQqCiyecoau/wqw91TD5cugeWsarfIqasQt2oPrAa0R0ZAKJKPXYbN9EGw7d9O8rKDWw8HRfEc10xC4qHzSD53Ew5LxsCyc2PJY/wqtEWmXwjcTq1lQDb96Ru47F0I0xyiuH7l2iAzIBQuh5YipCW3JvD+cAa65uLpWCqlEu+dqrP9XP9YieCmg6BraY4rk04x8ShiGVKa2+3bAIkYUdOFAq/tNev9XEr/Cb3juVzRtWuBvn01Lyvp1DWEdh0PowolGJAN6zGRAXIC5lItbsMBRI5fBrNmtWBcrhinEty6LpzWTJY8JqzfdCQePAe7GYOgSs9E9Iy1sGjfEI4rxkvbuWJ75iRwPb4K+uWK5QnIpj19i8CaPaDnaIt8z6QTImMWbUX03I2w6NKEAVneAeKwaLTkeKJmb0Dskm2w+q0VMvxDkHz2T6yx8cGiN03YMZ6enMNp5EiggGZwXqNPitST4BRVN9m2DXj/XvOUPxo9xESbdTDSSWMb7utXwkplP8TEqMW1PxqjNnX9knkj5NswjilOE+ClvEcqC0rvl5zaf/F7Q3NCKt10/4u1qVOnMhDJA00CZJRDSoCwQlYxaIqYUnT2yhXOSSRsBDwpokv1VymvlG9Unobqr5IQkrD/CxcusLI4BDB5YPjrr7+yc02ZMoWJLNHaXmy7sH86D4Fl0qbhgStFhwlcU/SW+iP8cfHiRRb9pRI7/PkoWkvbqb+oqCjWz+LFtjh/PglxcRXYNr78DgUpixQpwnJlx4wZw6K6FIFesmSJRvmd6tWry0A258fr391KoJMkr2mSKaGabjy6uYk+8Lnt3wayb9++Rc2aNfHu3TuWaO3r68sSsukGvHPnjtrTSw8TPaCXL1/+3EvJ03H0Ajx48CCjLzx69AjOtCqR23dngf/ih+y7mwTBgOX5+J5njxu7cA79/AwQGvpx1IUiOlT6gKKvlSsD165lRw9o7USKs0VOLUeVgP2I1rOHpSIW+sjEb0abcT++IItSErj58IEDgcWLA8SEc7BXwSbOF7qZ6bkbUk8PNuW94eah96/TmEnZl1SBKVpC6sHarajeWxy36aHx5ynGszDzWjXkyyd+KcJyLekBoUjafRJWY3rCfpRmP8KjAxv2Q9q9Z3DeNptFZOnHbuYQWPeV/vZ/KNoYyqg4uF/disjRi5B6+zGcNs2AeRPporEfCv8KZUw8PK5tQ0C1bmySvJ4egb6TeEFTZWIyPnhzeaqet3fD/8cOIP5x/tDLH0VxKUJHqr+OpgkoNbwRO0Zn+CColqxESpHSONNiJVPfpZIzVN9W2BL2n0H4gJkwqVGRAdmQNiNgWKIAPC5vkbxfYpZsQ/TsDbDo+CuMyxcHRVtNG1aFy7Y5kseEdBmH5NPX4bB4NAOykWOXwKxJDThvmiF5jG/xZlBERMP90mboFvHKE5DN+BAE/0rtoWNmgvy+ZyX7jpq+FrErdrIoLAHZqEkrWXTWad0UyWMIvBOItx7aGZn+IexeMR4zCENutsOJExwrghpv6+rVgaenAlD8wmoYZSaxbW9REOPCBzOhLb6RuBWVAaKfgABgVMJ0NDM+pzGOUpFnkQIT9lwWKgT2DBAwJaYBAeFRL/viB11OeIxavNIc5aJPseguVUjJqi6Ffv2AxYsBCT2gb95xSpFocuRcvcoxV4iZkVOjdws5xhYt4hgcYk0byBLdt1y5cswWJIxEjcBi27ZtWS1WvlEAacuWLUwsiSKbpORLa3Bqfn5+IAxA9VpXrFihAWQJANJa+Tov1Q2w8jYknER/nz59Oouaim0X0pPpPKQ4PGfOHPZsCCPKixYtYthg9erVWL9+/Ufbly1bhtevXzO6M4FYAqvTpuljw4ZnaNduPZYvX86UjPlGgJzo1Xfv3mXR28GDBzNQK2wEwOWIbM734z+ylT6epDyYVQpJ3acQdBKfnG4Kkp1+8+YNu0G1G93gvGdDamD/FJCVOteoURyNh7jw1HggSx4ZqvvEg/AvCWTJbvQgkveGHky5fX8W+JrAiTzVFG2h8gvh4Zx3u3VrbmFOUQdapDN1z3f3YBbO1cXINDJFfMVaMLMzZjUcqUxEbo36u3OHiwKFhXGRK/qhj7v6X2MFPP1uwDj1Y+GF3Pr/J7fTRyYoMAhu7m5qgQbq38jVDtXHV4aB4cf5gv/k+akvWijv3s1FHKh8B/0rt7xbgJ6p5ctv4Nq1ajh6lJsve4NYLHRZBlu9OEAFPIl0wtTEEahR1wD79nEUYe0WPnQuEnadgO2EPkjYcwoZ7wJYtM6kcvZNT5EXYrcRWKY2wGQrRphJ5wpqn2NPahNMTvZB0aLAihVArSyGLS2Ejx/nAFOpP+aiVNJtdmiGjiHeNh2CruuqfASShH0/OuqHqAd+3Lcq3BTjD5RBWCS3SKTndtw4rtwJ9U/PefmkqxjkPwFJehZI1zWGTUYEdEcMgvc46ehqWP/pSDxwDnbTB4KAbMKGgywP02HqQMnJ8v+lKzJefmCRUgImCduPwXbsb7AZKV108r1HbahS0+H5YD8DsskXbsFh+ThYduBApHajNcV7t1pARia8Hh6Af9WuUCUmw+PWLhgW8BA9JjM0En6lWjDw6v32JD7kb8D28/Y/D10TceXizKAw+JVpDRjow3nbHIR2GA3DkoXgcWmT5PXHbT6MSJ/FMPu1GgOyQY36Q9/LBV739kkeEzVzHWKX7YBVnzaMWhzedxpMfikH10PLJI8JbjkUKdcewHHdFKjSMzgKc60f4bqXW7+Itff56kGVlMKAPDyc8gRkM8Oi4Feyea7U7QifxYjffBg2o7ozIBsxYgFM61eByw5pNln4kDlI2H2SPX8UkaV7hajStiO7M6BIsQJ6Zk6fzr6aYaYbMch0q8bl1Y3ZiQAdTxYdpXIwLVpksyfo2+TbygfKazcR06AtrM8cgI5Kibidh2FVwJ69e8VKAvlX7YKMV74wnT4ayZMXQKmjixKxl5GRwQFmqp1L9Hzqn1IP6PkufX8L6iUeZiWUlNDFLv1OOGrYCunpSXB3N4W9vS7s7MB+iPJMUebCBRRwMohhFGo9Y304FbH+ZDq11HzT2MiO2srQ9Pdz5zinF73f6He+UeoFsU9oTR8fnorMeC7twszRDJYORkyluH9/4N497jrIdnx5Jb4PbSB77do1FmGlMjh8IwBHtV2pfI2w0ff5wYMH+OOPP1j5GeusFzdRc4nK26VLFxYUE0ZkZ8yYgdu3b7MIL98o4nvmzBmcPXuWAUQCtSfIO5LV+O0EcLVbTv3R/rlt5/sTqhZLPpS5bJCB7OdaLg/H0aJ4/Hhg0yZugdCuHfcC+ekn7mAx0Eny0zt27GDhdIpmEk2YPB/0Q9LYdGPT9lmzZrGQfcmSJZkXgzw52n3SA0G0A/JkkAeHvDrDhw9nIX+KAJOnZ968eYwSIHUu7cskfj6BVEoip8YDWfLEkEw2JX2TN0kbyBLPnbwp5D2iJHZ60IheQPvy5yZwTH8jikWvXr0wn3huWY0eDOLHkzfHzc2N2YNoCjwAoiT1tWvXsgdVbt+fBb4EkKWPy/Tp3Eerd+JylMu4wwyVojDE9LiBuJVRXtJwDjqRuG7bSq3+STvOThyITamcu/XHH4E+fTjASzkx9PEmcZFf36+CTSq3ug9OscbYwAGIV0mrANYxvIq1lt+2M2a2yxL47K+AIkX+/n1Gc+HvD0SGZiL99kPopKVCqQAOPfTGmmNuGosHJyfufPRNJ6dtFYsnaJ28E/rg1DszK1dF8+0t/rEFzt+/uq/bw8qVCgwezIXCaAFIQj01Yv/ALAvN8iB7f1mC0XsrSNauDO05CUnHLsN+7nAGZNMevoTzrvkwq6up/ErOGYrGvngB9PkwET+nXUECzJEC6aoChkiDNeLwOLMYWsauZ2OlBR8x5UhIaMYMDhyb6STjkZ1mMdLjabVwuNw0RhEmASLKw7S3B374gYu2zh0Xh5kPW6jL21DfkxNH4I57C0yezEWi+ZIr/Ewl7D2N8EGzWKTQIJ8r4rcchY1PT9iOlo6uqqN+i0YjLSAU8Uu3w7xbMzgtlM7d5Cm/bmfWMSAbt3YfrAd3hN3k/qI3jSozE+9dOH5mvtcnQFHgpD8uwX72UFhllZLRPlCZmoYPHnW4Y96eREDVrlCERsL9/EYYlRZ/eNPf+iOgcidGJ8735oSaZuz1/A/oO3ClM7Rb+ssPCPilK3RtLBkg43JFXeF1d6/kAxCzcheip62BedsGsB7UAYHVukHX3hreL45JHhMxdgnifz8E6+FdWUQ2tPNYGJUrBvcz3H0j1gLr90Hagxdw3jGXAdmwnpNg/OMPcDu+StzOBP6JWp0VuVbZWuYJyAoj2d5+56Braizaf9jAWUjcdxq2U/pD380R4X2mwbhqObgdlgbj6udvzjAGZOPW7GU2s5uimdpF7An6vlGKwCTTJSj//hBiytaA+dtHMEiIgWrjWng1KiH5nAc1GYTUW4/gtHE6IkbMhzI+ER63dsKwgLQH0bd0KyiCw+F6ZDmCmw/hrvnSWVz40wTEjqW6xoSByMlF62Fq121awFkvUm2f55kF0TR2s+Qc0ob9Vv1Q1iBbtGy7VT8UndmJOZy1n+EcO9LaSOCU+jh0CHBzUWKM/Wa4IYjtFZRgiUl+PdUpFJQPTlFpynul4+idWlD3Aw5Z94ZJFh2bajtPzrcJEUbubC1AKRr0L+XTawNlsYgsCTSlp6erI7K07qXgkDAiK7wEApqvXr3Cxo0bGS6gdT4POrX7p4gs5ZcSYOYb5a7Smp2PyBL9WGy7dkSWjs+pP9o/t+3ZY8guv/MpcyfcVwayn2u5HI4jD++VJkuskOMsAAAgAElEQVTw4W4kpsQOQYgyawWWdQx9QOnj27p1dj4reViOHTvGkrYpNE+AlgAeJV8Tz3wx8TJAHp57IF47eU3IU7Nq1SrMnj2bRXEpsZsHx+SVIbD5yy+/gEAmNdqfksDJU0K0BOLLV61alf0udi7tskYEMM3MzNj4KDmcGg9kST26WrVqGDJkCFM90waydB1E+yWwS9x4GhuNkcApf26iB9O1fPjwgVGV6RrpeoheQDx4etjo9z///JPZgKjMNA6KyFLfdH6iPMjt+7PAvw1k6SPfuDEXfTFFMh7bay6KTynr4lnbycz7e/AgWJFuWlATWKPIjXfKCwx60AdpeiaINXaCU5IvLju3wRbrISxfjPrVbpUN7mG7laaoyOTUMdBt3hiVKoHVceSFM/h/S7/Yi4avViLW0BGB5oW/2kTShzotLRVGRsZqYOiZ8ByWGdEYlzAGx3Qao1cvzstOP5RjqO1xzmnwEREc7YponkRr/c1kF8aarVEfkqg0wc/RR1CjkSmoKgDZWKFVwWC1xXjUM8r+KFNNzgNDLmDSZM36k1/NiF/xxJQLV6qUilEJ27RRYto0XRYN8Z2+A8qV6xBfoAz0E2NgGuYHx43TYdFMOoktuM0IpFy+C8eVE5Cw9xQX4Vo/BRYtOJAk1oJbDUPK1fssB9SidT3J/VL+fIjgZoOhX9ATevt3MoBJC0VhI3JSx7oR6HWkJVS6ekjv0h1GW3/HNcVP6BHzcc1O/li+7mgGDBCvbwO7zHAE/dIGP+8bIrn4jdt4EJHjljL6qYGXS65iPHSuoBZDkXqdi/qlB4SwuqWmrevCJYfcTTXl9/o2JB65iJiFW2DZowUc5o8QtZUiLgG+BTnncf6giyxHlo+S2wzrIn5MZAx8i3EKovlDLiHgl27IeOvPQIdJlbKix6Q+fImgur2h5+qIfI8Oghd+8ryzBwbebuLH3HuGoIb9oO/pAuftcxBYvTt07azg/TI78qN9IOWJUr4oCS9ZD2wP//JtoWNsiPwBFyTvFXIwkKPBdlI/BmQJOBkU9oLnjR2Sx/ARQ9fDyxiQDWk3KsdosTI5FR+86rL+KJdYYWSQJyCrUijw3pmjeOd78Qf07MVBv1DkiyKyoZ3GwqhMUbif2yD9LLUdiZRLd+CwYjyjFscs2JyryFXYwJlI3HcGdtMGImHfaU68av9imNaoKHmegJo91XnXBGQzg8Lhdm4DjMsUlTyGIvbKhCR4/LmDOUoItXk9OQx9Z3uNY8gZtWULFwFuuKAedFNTkNa7H4w2rIXS2QVRG3bh8uWbKFKkMuLi9Jljin7oON/X6djwqjbrT6HSZc7ki+mV0Sd+PqM69+7NidMRRZq+w+TolKIwa18IMX46ZlVLKq3/DAetNRWwZ6UPh1XPlhg6lKNVUyN6MQWkfH2B1kYnMNdCM5o+LH4KjqfXYYJwFC2n7yKlXwgYs6wfqRxZWt8SoKVGwR2Kul6lk4o0Wi9TRJVyaLt3787WyBSYokbrdYVCwfJuSZGYQCqBYqF4UuPGjVkQjMZCFF1STBbbTrRj7ZZTf7R/btv5/uSIrJUV41hbWmqKTkg+dV9oA9HZnxVqDRedMIxzWo/Ba4qxPAZKsN+5k/PQkHfc3LwGAgNvw9jICOnpaUjPSMfMGbMwbvxYNlICeJSPSt4YnjpAoJaimETj5RtRailZm9TICOiRENPp06fx22+/wcfHh+1GkVyiHZBSGF/Lifj3lNxNwHTBgsvw8amJs2djULq0NfPqhb2MQeYjLv9Bx0AfDvXsUaJcQbXaGP2dB7I0RnqY6EGgPFrix/M5skFBQUx6my+4TMdRQjc9PBRhpeusVasWo1Tw4Llu3bpsvCNHjmQcecrHJQ8P3wgEFy1aFGPHjmUfmkKFCrFCySRLLtcV/kI3+j94mtyALAErciTSbU8fOAKX5EtJTweMnz+AxzvuRa/S0UNctUYoWL8AihXjPpxPn1L9Rg4wtW0LDG4fDpc+raDS00Ni0/awOLwTRrV+gvve7EUxlaEgDyr/QeRVNg2L5Yd5q7qInrkOFh0awXH5OEYT3riR8+oSjYhyY+ij5/biAkrvn4okBy9kmFjA2v8pTEf3g4uPdM3A6AWb86TG+Q+aXrQrsfnghVMOuA3E2EeaiT/VqnEAREwMh3tPUH1LLm/Kz49zFNB8UCNv9SyzuWiQfgKR+o6wyYyCHhRI3LwLpRtzFEgCs5STRd53+iGxHpORg2D26hFCf24G5z85gZUfIs9gxe+mLI9J2OidS+1TwPa/beN/q396VmrX5ujypUpF4N49axgaGrDTRc1Yi9jlOxk9M8M3iAnH5CYypM7n3MoBiaST10DiNKTSK9UC6/VhJVacd86FWb0qkvulPXmDwFo9oedkh3xPj7D9aMFLeZX0WacIL4lI0Q0UUKULi/o5LPZh4kCqUiXRNXUNo+tTihgtHCnq8+wZ916Y1OgBut4eysCORZv6iJ61nuVXOi7jvq9iLWbpdvV+Bp4unDBP58ZwXKKZlyU8NrBuby5KvXMu0ghojFsGk4ZV4ZpD7uY7ovymZzDKb8LhC1nRyfpwWiVe41VN3zU0QIGgi0z0iM+btJuopaSUNbgM32D4V2wHHVNj5Pc7B+E4peYk5foDBLfgbEYA0bdEMyjCo+F+cROMShUStVnypTsIaTsShsXzw3nHPPiXawMdI0PkD5QGpZETlyNu3X5YD+7Eoou+RTiRKwLcOhIhttAeE5F0/Ars541gkVgh4JaaT7+yrZEZGAa3s+sZkA1uPBAG3u7wvLNb9BCFEPyHXkamUpknIEudvfesA1VKGjzv7wPdO2JN7RRaPRH6ro4cGC/kBc8/pcE40a5T7z6F0+aZDMjmReQqpOs4JJ/icoMT9p7JUz61X8V2yPQNhtvJNQgfPo9Rhon6bvqLOFOJUdf56PWTw+z5ZFHcmzthWFA8iisE/K5HVzAnlq6tFdyfHpa0s3BOnNZPRVifqQh3LY0mQSvZWoAa5WDTt56+C/SOb9gQ6N1LiWoVU5gj1tBUH6Y2mtR4Ym3QGoHeGZSR1tzhBmxmjkWypRNSLB1hF/gExoN6wm3Kx2wMcqoSyNY7sA9JMzkValVqGns3vmg6CgveNmPMLHoHE0NEqCpNNGH6ITViCtLs27ePrclpjUvqxBQU2r17t1q1mAJN9HfKf6VAVv369dkal0rbtGzZkgWPKCBEa3Ba//KNgl9EFf79998Zi5FXGaZg2bhx4xjQJFamtmqx2PacVIul9s/pfML+ZCD7jQJZupEe/9ANZiHv4bR3McxrZXvB6KNL3iPK/wJqoIReMRy0fgF9HQV8FSnoGf8WbYfOxoJFAxjAI/os1ZbiG3HoCawKE54J8BEQJNBK20iamoAvgVe+mDF5W0hhTFjcmF5E5LFZvDgRffuSKBMtTLLPdcq6CwrpczmB1A6p6sAnairevn2HAgU0I7I82KaIL3l5iD7MA1mi+9K4KArMN3oIaczkNeKpxcKCzESpLlOmDAO7FH0lOjTvaaI+6EVA9GSiVcsRWanP+Lf3d7oFCCQS1Z48lPwLXgrIUtmLkyeBHTuA+/fFr+eqTSu46mXxlshjml4JPeM/LuNQty6Xb4f3WVQ4Wys4LBzF0c1yUcxMPH6FU9asWBLmreshcgzld1WH85aZkkamsg+8IAktWnhanN343pLHRE5akSvN8EvMqth8RPgsQvzmI7Ae1QOXC/ZkkvmvXnEfa/p+EvAn0GGpl4xizw/BKC2eUbCexLhj2iNS2NSMlJLTeepULic5rFcWfXXOMMSs2MXoarlFAwJq9ED6s7dMuTWk4xgWsq0SfQiROg5MWIQXVSf/18yZAL1G+5lsR3/T7dChBFHo4IJdKxAQIH09Ei76Vtvdu2ClNigthRZpOZXbIKcKRSmodumSJefRs2cNtbYCP4eUo0cCNUzRdfpAWPeXUCQBIMznTNhzmlEj7aYOYLmNUs2/cicu+nd0BUx+LiO5X4ZfMPwrZIMtfkeaK5oPXlciVRD1c1jiw0q3kFPJ4+pWFqkXiglRRIYRc65cRWi3CUwZl6LCTOincXU4b5Z+ZtVAv28b6Hu6ImoCp5LrvDFbFVT7Yvx/7oyMN34s0pkWEIKowXNg/Et5uB1aKnrdBKhY7ipF796cROKRCyzn1azRL3DeOlv0mPRXH1jEi4C89+sTECrZ2s8Rr1CgVtJ1sEW+50c1IscWLcWj6UlnbmhQdknsKeN94Ec50cJBJh67rH6HEoXXt/CvbDNFjnWyHCjaF0VAKWHHcdiO682ArNoeb09Cz0o89ULIDKAcWUaBtjKH99tTkveXOvJ9YzsTe8pNWZiouyw6bGKE/P7nP0mESCjGZVRMRN4aQGCj/ki7+xTOW2dB380JgXV+g56LA/I9PiR5DcKySwRk2TelQVW4bJcWueJZAgT8KCKbfP4WHJaOhWUnbm7EGj9+Egaj+eHFyMwa/iK6vwad2vcsAqp0zjWKK2QWeN7dyxwt0NeDh99ZnDp1ijH1tHVg6P6j+1DH1IR9b5nTpEQB2J3cwpyjGzaAlXkSNgNk4Jh1DxTU5/Lj01X6uFpnCnrvqqF2ZtI7kt6VBGYfPgTS/jiL8P4zYFKtPKPex67YBat+bWE/Y7CkzdSO527NoExJ42jjk/vBpHcn1i/pEpHQlbDRmlZbBZgYh7QOprU+MRr5OrKDBg1ipW2oEZAl0EgleIjB6erqytbABEr54JT2eYQ5srSNgC0Fwyi/lq/rSkrD1J+wjqz2dr5fEmKieSKmZ0798ftLnU84ThnIfsNANqjxQM4L9vt0mDfVpG3RR5YodXPm1ED1DHPMN4xTz+ucpA/YmVoccxafRenSl9GiRXMIAZ5YRJYik3Sz8xFZAr90sxN3niKzFLEm4EhCUpRXK2wkxU75CyrVZejpNYeTUyzL7zMzU+GBSU0WGQnTd4FTZgjuZ5REu7gLKFZsKZo3b8Qe1NKlfVG6tLc6akyKZ1RXivJhiQ5BD6dYRJbqZNGY+YgsAVcpIEtRYwLmYuV15BxZyXfsP7rhzz+5iJqrKxdxpHxF8n4SgKFol25KEkzePMn6RReWVUuicFlztm3vXg6IkodSIL6HiVar0NhAoPDIYQt1U6l0sD25BVancAIotLDt0oXLR6V8OIrymRirMPZETeipFPDPVxWevtcRZFYQXVSbWe4l30jggnJkieJD3m1eXMRh4WhOMTNrUSxlNGENQyr5wH/wXA+KL1apn+w8sPps0UIlFCx7tYTDXOkahuHD5iJh5wnYju8Nm+Fc7biv0cSArFpxs28b2M/Myociv8B7TsmRrxCgXa6Fxv9rzGa41ygIUtQkqihF1GkeeUCmXqSumsCALBPCObgEptUqSF6+X/m2LEJB5UhCOoyGMjYBq6ttx+JDHAeMKM8UUSfBDb6dtO6Kwvof1L+HKhxQNeYQc6oQNY0cLCTcRRHBMhL4i8D5o0dcbVESIyGhdPqhY/NSz5GiyxSZJro0LcDIGUDAum/8InhmvGd9pOmb4XLZIbD5wYMxES5ezL6Gn3/mRIrI009iKjyIo3kgAZL16zna+vz5ChQufFxjcaguRzJ9IAOy5JiwGd0Dtj5aIWyB1f3KtFIvUBN2n0L8pkNMlIjEiaSaOpJ3aTOMSn5cg5A/ThEdl6donDrqV6IgCMgG1evDcgy9Hn5c35TvW5jvatG2vlol13V/dikh7fFriPF4uqjrlrrskaYw+/7QEoqQCJZ7muofgsiek2BYrhg8JHI3FTHx2WAv+BISj17k3ifVK8D1QDbrSDi21AfPEVS/L/Q9nOH1YD9ilu3gWCE5lJJJufUYwU2yI5DCXF6paHrCwXMI7zddLaIUULsX0h+/Fs2J5scXv+sEIobOZSJKlCP73jUrl/fVcejZWoneIlSflijVvFLzOzomS5SK3pViTR2Z3DKLld/x+6Elu/lZFFfiwRNGvlVpGRwgMjdF/g9nRM+R9uI9l6+bRY3OjSkk7ET9Pjq9FsblS4j2T8rR6S/es3cbOTf5fGTvd9JgXPieI6BNIle55dWq5233AgaumCr2jMGw7tdW8pnlbeX51wFEDJ/HpROsmgCLtpzgl3YTCoORqjVdGy9gJhXFzQgMg3/Z1ixin+/lMbVCtvu7Uzh96YIokE179IoD/M72DMgGNeBo7F73s4XB6FtP62rKq6e0lQNLAtDhUBZnOGvgO1Oa42mjkcx5umoVsDqr0hO9Xyk1Jm7TYbWD2qh0YbVCdk4MDqHjmaLxlJpAOdzkrCbKMq1/SO34W288kKUUPTFQ/G+OXway3zCQDek0JlfaFkUpayUbotOHFNjMHIan89egp9+fiFF2Q7RqDTw9LyMsrDnu3YtFyZLcrUT0XQKK5BX58ccfGcWY+OiUI0tgj8+RJbpBnz59cP/+U8yZcwbKOBVGjKiM8vkrol3ljvCzqozrj2Nx4MBzKJUN0azZZVy+zIFJomXpp2fL8BNlinI54mzzodI7RygUpIDJfdg9PX3h758NZOlvND4qK0RCVHz5HYq+Er2BBJkoR5airBQhJpXh3CKyJEtOUWcCv5QHS9FY8hjR9RJFgSKylMRO/59EXDS5fZIF6GVLi2uKlNLcKzOp4Nx7qDIy2YJ4yZF82Hs053DVJsuRqGbIiSdRu55eEd3jFzMaqJbgHlt4UxTlmV1tGOnkXJ4jTGmPyWUPs6gdgVgScxE2YU4TLQ4oUsN/5Oi8dD2UN0P0Vb4lX7iNkPZcrpTDolHcAtHdCV5/HZC0W+y6/YiauBzmzWvBvE09LrepbDG4n5UWGuGjJgReqX9O3ESaPkgnFwp7UN3Ar9XEFnBq2mUWpVpjHpScs+LBA+DHxxtR6clWhNsWhnlyJExTo6G7YiG82/8oeTlqUZbtcxj1lafSmTfmalqKtQ+FGjHw6nFjO0I6+DBQ63xiLbbeK8EoqXx5FQKYFKFt0gSIr9ESqrAI6I0dAcXcxcgwMEE9/bOs/IR2o8UNUVaLhF1DsVCujl+GUg9rI5rjclixj/an1CRy8NA92kpxAMVT7jO/TLqOIY5Yd8Wz1ALMSUgLLe1WSO8DTtloOi5WJHfDsmQOLNJzRIwCin7TM0nNWicOu6wHw1U3jP0erbRGj7hF8FO6M5XnI0cycObMSY3FYUhHH3XNUop0sFIgWo4J7bF9KNBQTRkksSdeOdZ+VrYzQ/uY9151oUpOhee9vTDwcpWcQ+3opJ61eDQu8Y9LCOs1GcY/lYbDUh8E/NQJuhZm8H4vkGrVOou67mjTmrCgZ7bLOKZ26356neR4wgbMQOL+syzirO/lmqf6puo8wVs7GbU4vO2oHHM3qdaskH6rrqmaw9j41AaDot7wvLYNcb8fyrWUTNL5W5yCcKlC8Li4CUJ1ZakIfNzWo4gctVBd1iao2WCk/vkQFNkzb8HlKWq32PUHNCLXaoptDnNPjidhlFAYOTUsLF7nSB2ZPLCEAVm1onLAeegaf6yorH1vqdLSc1UWTr3/jANKWQ6DTwGyQuaCFJATgl0C7EwhOhcwLoz0ZgaE5Cmv1r9SB2R8CGS1cClXlthBNmN6wlaiJBTZ5r07N78kDBYxbB5H4547HFa9sgpKa028UBiMgLgw2mzWqJrovZL2/B2XQ21vzertsrxilQpujw7gzN1bokBWTXcv5MWALEsxsLaA95uTks+xOtfbxRHmPVshbtYaHEuvi+HxmjWHhw0j0SKuG6FziCKyLFc+FwaH0PFMEVmhs5ocirNnc+J3ec3Zlbygf3mDDGT/ZQNLdU8heBI3+hZzZGnM6o/GtIGwHiBO22J1ZK9dg74STOjAQqGDenrWqNb3CAaurYS0NKL7UsGqWBbxmDePWyRt3bqVqfbyqsVUm4kvoMwD2W7dhmHIEBV27CAVxPtYYVEJlQzuYX6SL65nxCJOqUIqSEymL7p0GYzu3S+jZcvsqGhmcDj8SrditA/68PMUmPdL56JVq9po2/Y9jh41QFgYUY81gSwVLi5dujSjH/BAlmgLRJOg34l23Lp1J3ToMAP6+ga4f+0kRo5vj+vbH8DAxhwFqjijbdtsajHZk6jFBFJfvHjBPEZEO6ZEeMqLJRBLwJ1oFC4UVpFbnixAwJUK1VOkUiikM8FsOXqY7Ff38TyzEJrHb2L10Gg/KklDwJeim0QnJWC6IqA1HBRhCNd3gWNmCELhiKqRXLSERGaITk+USHd3LnKVGJWG8GIcvS15+Rpk6umDHBZly5ZlOeA6kREwmeBDIVcU8NesbSe8OLVXWE8PHle3cB+5XOhm5J2mPBvjn8uwXL+8eMWjF21BzNzfWV4g5chSbo9BAQ943tolaWuhyiZFj4QLRKmDhJFJKU94nib3b+4ktoBTL55z+bjTAoD3TKfeeYLUG3/luBCmoaqpqEeWM0oXKy2ybCwsO4pT4Vh+Fqm4KhTwenyIAVlGM963CKY1K3GqtXM5BgDpVPCvBb60htvptWzBSs0r8BJevtFn+1LOFTEIDhzIdsDctG0GB93soqPkpBmQuZhFbukYypWi54FvJCb20K4BdHWy6zXsT/0V4xKzczMpgktC81WqcMqeZq8fwm3mYGTYOCC5YClY3b2It2VaYr/XcBb1pVIOVAKDgPCcOcCpU0CB4OtYbTZOY6b3eI5ApbktWE54ZmbGR3lnaqbQxulsoZtb3iizMy02s0RcKMrJIoE55JqSAywvUTl+4MKyMgYe4nXA43ccZ1Ei07qVGUXSr0QzrtQJ1TeVSHwmMSE+x5WoxXnJRxRGLQnIhrQeznI/Pa5oljLhx65tn9SAEIQ1GqAWSxJ7DNUqv1lRv+Rr9xHSchgMiuSD5/Xtok+uGuxWKAH3U2tZrjJTV65ZCa77Pk6joE4o4kmRT+PKpeH2x0qmdBy/NWcV5thVuxE1dTVz1jmtngS1Q36xDyy7UHrAx01t506/wnHpWPgWbwpFRAyrwyoVjQ9qOgipNzmFXPNmNaHOZT2zDsblioueRxiZNCpbNFdxJUVsAnwLZQtkEbDla+RKKQur5yLLYfApQDawQV+k3X/OBK/MGlQVvQYhfZe+CXkpb0QAk4AmlV0iZx27jwt6wvPmTsm3vHoOrmxh1OK4VXtgNaA97KeJl4RSRMXCtyg3v/RMRQyfz5X8mdgXNkM7i54n9a8XGswIIfXbop14FDfl9mONPGXeCeRyfRvOvXwsCmSFjh7nLbPyBP6Tr9zjnt1i+WHVty0ihs1FStmfUPXOAqb/Qo4+ov3WqJHNohHqB1BENnwgp16eE4ND6HgmlXBeidtp1QTG2KH+SReHGGHfcpOB7FeanW8dyKopSrlQsAggEnXCefcCxCzYpJaKz/ypCsvnIzonAQ1qRJughY9n6F00DN3K6JTU3rhXh1GP9ix/isAJ5d+SJ4hYxPSNJyXWrfFt4agIQaiBO5wzAhFnaI/DPQ+zxVTTph8XLBdSbNxPreOKfZuaIL/fWcbhJyBZoEB/9kIgVg9RT/myQmK3BBWUplp9RKWjfwkMMVlynXhcsWkNc93s/NlhydMRWrwmE86ha+DFfah//ofEsqjRh6ZHjx6M70/UY6K7Eu2PqHtENaFzUKSE9ndWBMMwlaNx2xRxgHcFrfDeV7qXv8ZpSQSPqC9BnNI8awRMyXO4SjkIZfEIcbCEFeKhhA7SL15GiVLStUPfe9dnNQqpLEdoRx9G37K+f4Yt9EkASJv5pU1Loig7Rdb5HBkN+l0OuVbpr7NFYCi3h9Xy09Xl6GYSC1x17mqDqixHVl3/L4dFceSUVYhbvQdWA9vDonV9LtcqK/dMav545UiNUgtVysLtyHLJKVcvhrbNhlRu0pe4X8QWcAn7z3D0zBwokDQ2tWLm1AEgIEsCGPYLR8GqWzPphRcvKnPhd8Su3JUrFU6ZlIIP+Tg1XFIXJSDLl46ghbFYE5Yw8Xp6hJt3ikCIUCDpfUXv3dQUJZrNq8GovwEl6sHj2VmkexVE/hub2XuFbxQlJdEvArXxr8OQf0RrKPX0EVa6DlwenEZsySqIHDuXgVIq4UDPmrAlnb7ORQzLFYN5s1p5EnSJ23UKkUNnQ1WmNPs46Fy8pEFJF5tDdVRr3yKW+5hb3qiGnX3PMgDF8sOb1IDzphmidtamzpJQYE7Nt3gzKCKi4X55M4xKiNOQY9fuRdSklcyJROJUHzw5JxhFZCkyK9Yip65SL+AtWtVFYO1ejJ6Y78lhyeGoFYjXT2GRZCGdV+wgbZVbohaHVO8OHStz5JfI3RTm+xI9Ug0IcmCFqJ+9rIW1Omc/h9z++O3HWBkVAv8uu+ZDaA8pQBM97/csBeXmcJg/EmF9pyHx0HnYzRgE637itXSjpq/RyCdURwOPrYLJTz+I2jqgVk+kP3nD1j1mdX7SyMOWimYKQaBhUW+oo/5397JSSdpNWyBLpVTmWk5I+BxSWZ9PAbLCmrVSOchqUPrXAei72OcKxjWcQq9PMCDL02xzuo+FziECsuSEtejSBI6LOfFP7ZYtDMat8SInLEfc+v2wHtqZaQiINTVLIMsBIyzTJRXFVbMEfigMjwu/g09bcDq1BheC3okCWWGKAOW3q50Rvmeha2YiOjZ13vaPP7A8V17fQn/zGqaVQO9g7SbUD6CILP8+zqm8k9DxTBFZobOaUlCoBBFVS6ByYt9y+xQgS867hIQEpnlDx1FgicSnKH+Wp/jz+5AGDv2f8p6JQUlBCr7RsRSInDZNHxs2PEP79htAQTnqh28khkVir6T34+DgwFIWeQFbfh/S/5HL7/xLd5e6eHfv1qzWm1Tzq9gemb5BTCkuev4m0bwEElUhjzwBNGobLUejhuEtdZdUdqJ4FCkEaoqpUOkQUoAk8MfTw5gwSrtRajEDqXEJ82soeiGlKti9O0WIuYR5yj0w8n0NY9+XDEAmZxrhROIvuHjLlCmVajcCl/3NHPIAACAASURBVKV1n2JNZn8ooIt0GMIEqViX3AkLkrUy5AUHU8RjldNsuOhzAj+RCnMsNZ+EkBQbdfFt7XNVNbiDLVYj1X/OUOlhZpk96DfVmeVHfOuNIj5E26Q8U6LLWoa/hfOH2+wlodG0f9X6/bmqKHa/rcCcHXQo3SPbt3N5gbywCr/Y5Snl1D+JkkjR/oQAgWieFBWllpMCpRCAkniJ9oJBo25iDuUMhPmuHte252mBK4w6OCzyydMxanGSsb+xaIVQEETq3lErRy4azSI0Qpqf1DH+VToj4zUnHCNVIuNL3KtiCzhtIRjJ6+48FslnbjB1WdIJ4Etm2AyRVmtW0xHv7mV0V0aFy6F+pzAST/cZ1ZRkCrw5RI60AdaHgo2gSk5BTqVFhFEd1z9WIrjpIDXtUOr60569RWANcnTYMIXV3GpXUj/CxZp589osgsADEKnzqOnuLWozwRje0WI/lYu6iM2hun7p6bUMyDLHRA5RB22HU+KBs7keoxZwyhLMye1+VQsK5QB8hGre9vNHcuJAlFP56CDLNRRrJIrDUyotWtXTcMZKjUntWN41n4GjgJ8750hjzAyP5qLD9L4Lu4LUgFAEV+AEbPIHi+duqqNFWZFe9bswB7pk3ObDiPQhgblqoKhU8uW7XG5/iQLwuLxF9HLU4L9FbcaIiF64GTHzNjFWCTFRxJq22JzQhlK01IjRC7l6u6O6w3ZML+Qlr1Z7ztXK2Dk48IQg0MDdCbk5QLS/MXS96nJCEuA34dB5jRzUTwGyIer33mhYdvlY0VsblOrZWOYKxrXfWZQjG/BTxxzzfLUp1Qn7zjDqN6XFOG0QR1Rq9XBHW0b5FZZHcpgnrumQdDJbTI1YAuFD5+ZaEirh8HmN2rk8Hdtx30JcjA8VBbLCklikOSNkiGiX+eHvaSGDw6p/O47xkBVll3r2hfoBRj8UyVPkWxiFV6akflQXeORITqOB14/I7V34tbZ/CpAlEEvqyDwwpWeEUhJJSJYHobQPVSGh0j96enoM+NJ+VFaUB7uUYkhis0uW2OH8+UTExlZAxYoVWUUTahSsLFy4MOrUqcMErUj3p2fPnqy0J6VNUqNSRZRu+H8BZGmxT/k6X6qR3D1FFaKnrwVRLKj+nlT7UKQxlNFx8Li+DdELtiDp6EXRIueU73fkCEdhq7imD8z9XyCifkc4nOEmfWDRM7j52JSJjlAEliK3I0ZwETah5Lnn7d1M8IB9eAMvsKR7sZZ09oY6F4NAthRVTChhTsXt79g20Yiu8qCUgmMknkKgkX5ofCQclHTuJovgGf5QmKk2kucQzZrgQX0fJiRElEDKb6QSKlSyg35c31zFGktNm45JGIuDaRwNkeirJEjE016pRmelVzvRIXotUmACPWTCEBn4LW4eLmf8zKLKVNaF8uFyawT+CARS5IUoKvQ7lX0gDx/Jv+fUCNyTOh5FKQk4aud70rG0D+VUUISbXoAkakQ1IbUdAaetO6sV+XIbs3A7OT0qRh9HksqU1UIj0THt+mZ8kXMqWUAUWlZSQOLDT30LP7ZE2eLr8IlFuvixqAFoPld43d0ruujmo7wet3bBsABXhkW7CfPA3C/8zuX5ZJW1kBINiZ6zETGLuRqG9nOHcfd2piLHRXHob1PUzyapFquVOWmxKhFxCmo+RE2r1XN1YJQq/Xxu8Lorrf4gFI4hr/DXamILuJQbf+Xp4x7UZBAXHf19OlJvP+E8+0M6wW6SuHNKm4pKQDZ25e4cFSO1F//CRYhU/p92OZK82FoIytwvbcpTbqbQTvbzhrO87dwWUcI8Q1pwsghCLkra5Pjka0rquzgies4GWGTRO+m+EZvDDwUbQhmXyOo+ZrwLyDVvNP2dP3fNluagPDhtiqvY/alWy81aFOd2DwvBo1ndyqK7awMs9Xfz2jZQdE6sCQWFLFrX1aBO6ghljgUHCwEW1ZHNTVBIrahqZoL8vmeRFhWDwKIciPGWyN1UA4CKJeF+cg2EaTxS4DdbOK4BiLao/f4Uu35t4KoGti3rwGndFFGbhY+Yj4Ttx5iQFwl6RU5eibg1e5mysN2UAeJ27j8diQfOsZqllEaVl7xabTGw4NbDkXLlHhxXT2SlkrSbGAjkgwCUB2ry48eRX7FId27gVx3Frl+FCVd9CpDNjl6Liypp1wImRWc1BViCjaCdT612LBGtPuyKqMiVtoBawv6zuYqW8fWc+XQZoVChVEkoofON6LfqKG4O73qhkr/LtjnqvFr736fjsipeFMjGLN6m8W4TvsMMC3mJ3pOxq/eoWS3EJMiLOrSQRk+1fVlZsFzeYULFcmJn8GtZijZTI1YlYS4K9ORFCDC3d+W/tZ2LoMbDwsJSUjiNP3dychJ0dHRZiiDfUlKS2X9NTGgRTH0lwsjIEIaGHG1JpVKyv5mYGMPAwBBKpYIBXTMzc4SH6zHcMnr0aTb/gYGBTJGZ9H9IQ4fSEqk0ETUqt0nVUKgyC7V27doxUP3dA1mquZRbHVllcgoCC0rLjv/TN4f72xNIOngeMWOWwKR+FThsFqdg0c0T4FkXUCjh+mAf4pdsR+L2Y7Aa3QNWw8WLnNNYg3/uzOp9OR5ehvB2o9jC3fXObiYoI9YIaASV4Gh0Hh9OI6BAI4aY3B4eYA+qWEs6dB5Rg2azMgKOexewY1QpqXC9uYOJYAjbxYs6mDtXFzZpYVjwpi0U0EOIqTfck9/iQ/4ayJw2BZUqqT6i01EfSQfPqcsVmNT/GTETV8CkcTU4rJ8qOS0RG08gZfIiJOcrCoWRCSxe/YXIjn2Aju0ZiOVpx8IOYmauR8LqPbDo05rVR0u9cg/Hyo3HmMsNkJ6uA1NTFQYPVjJhoFevdFjeZ9H8qaiUfhPGyhRWrOOveG9suFYcAQGakW/+PB4eKvzsGYCmGUdgoMpgx/g5lMMrl+qMznLlig7Cw7OPdXdXsfM0i9uBfnqboQslO2Z3ajNMT/rYC+rtrcIPP3B2HH+uPgwVqXjqUgsZejkLMfEv0JJB56CvzMDzGTtQtrErE6YRawGFfoUqKQUuN7YjvNUwKEKj4Hx6LXM2iDWqRxnycxfomBjD491JCI838HYTPSbl4m1EdB4Hg1KF4HJmHVswUF1jqh/My+8HVWjPyrA4nVzNisaL3qdHLiJqwEwY/VwGTgcWI7BUSyijYuF8YSPLjxFr0RNXIHHTYVgO6QTrsb0QWKI5lDHxcL70OwyLiC+KwzuOQerlu7BdOgZmLetwzy0AtyeHoWcnrswZUq8PMp6+hcPOuSxiFlqrl7pmntTNrbbdn9thkE/cdv/0+0p0TkXmI/3pW4TW68Nqfrr9lZ1DrX18SO3fkPHiPRz3LGDU4vjF22DetQlsJdSaaeEVVLIF937yO4v41XsQN28TzNo3hN1i8cgR5aKFNRkEPXcnuN3ZjehxS5G49Q9YDu8K69HdRU1E6quhDfpBz9kObg/2I6RmT/YucNy7EMa/lMv1GOdzGxBUihM+8Qg4BykwlHz6hlq51nb2UO6cLvZwE6hsap8sbtFW0I95lyYwbVKdEwwqkg8ulzZJTnfM5JVI2HgIloM6sIh/zPhlMGn0CxyySsVoP1Pse+NRl3v3/7Wfi8iSOFpBT7heFY/qUdpLWMP+rH+3e3uYYya8zUgmZuRyebPo2MiJEd5yOPTzu8P1+rZcb9ewNiOQduMh7FZPhFlzriyNdosauRBJu0/CamwvWA3phODKnZDpFwKnP1aw8jpiLbzTWKReugPbJT4wa1EbAfk4gOT+/CiLsoq1wNKtoIyIAc21vpcLAgtz9U3d356ErunH71mix4bW76t+JtJTUxGan8vLdHtyCHp21h+dJunAWUQNmQvj6hXguHs+E9LiwS99n8Wcy7HzNyN+6XaYd2sG2zlDQXm27H1iZw33J+KlW2Kmr0XC2n2w6NsGNlP6I3HnCUSPXgTjOj/BcZt4mZ/I/jOQfPQSrKcNgGXv1ohduCXX5zei2wSknLsJ2/kjYN65MdS/LxgB806c/bRbAGNDpMIl6z0X0WsyUk5dh83cYbAQqU9Mom6BxbnIt4fvGVbWJ6RuH2Q8ewuHXfMYq0C7id2r/NrJ6ehyGFXMUtAUHBi/4QBip6yGabOasF8zSfS7JHVDR41aiKRdJ2E1piesRPJKM4PCEVyxPWBoAE9fTjU5t/Go5zmr1ipR/QMLZTns356ArunH1FqWR/tTJ/X3OPnkVUT+NpVdL123WEs5fwsRXcfDsHQROJ9aw5wZbP3aoAocJFIIEjYfQcyE5TD5tRocNkyF9j0qdp74NXsRO2MdTFvXhf3yceC/q1aLR+GGJQnaZX//+eNjZqxDwpq9bO1mM3UAgip1gCIwDE7HV7FUDLEmHItF39bc+sTUGB5vpQWiwloMRdrtJ7BfN5mtdYIrd4aOsRE83ksrSgeVbQNFWBScz6xjDv+w5kOg7+0G1xtcrjut+xYskE7JkrqXvvTf09PTsGTJEgwaNFijzCVFU4V0YBrXjRs3mJ5Jx44dYGtrh7CwMFb3liKnJPBKpTjXrFmNXr16wckpW/Ng+/btcHJyQr169fDo0SOcP38eIylkTYU/mwLly2fC2NgYRBWmCitUO5eisgRc+Xbp0iVWtjM6OppFez09PTFixIjvH8hSGJr42Tk1nbR0lBgonZf2T980z1YNgeWj9/BYfxyJRTzgO1o8t0Q3NR3FB3HjerZqKByP3YTD6TuIrFseoe2ks8OLDlkJ/eRUvJneA/kW7oVBfDLeTumKVA9xipVBRCyKjNsIhZEBXqwaiqJDV0I/iY7vjjRX8TxR24t/wXXXBcSVL4yA/k1RZNRaGMQm4u3kLkj1FEdAxv7hKDh9GzKszBDatgY8NpxAYjFP+I6Ulny3vfAArrsvIq5CYcSXLcQdU9QTvqOkj7E/dQfOB68ipnJxKEyNYX/hASIa/YiwluL1zsi+rlvPwPbaE4Q1qwKj4EhY332FkPY18bhYNaxZUxpPnzp8dBv8ZrILY83WqP9OtciqRB9GipE5HB2TYWaWAaVSB8HB5khI4DxGC8xnooVxtrR/msoQpaPOIBNcboCxcSasrVMRGpqdB/CHdU8U13+jPk+M0hI9XLegSJEYuLsnwtk5CW5uCbC0zGD76GRkokR/ruzL8+WDoTT9WLFR7J4u7LMOhtEJeDehE1K8JUSxMhUo2Y+T8XuxdCC85++BcXAUPoxog6Ti4t5PY99QFJy5Axk25ni1oB+KjF4Hg5gEvJ3YGan5xMVbrG6/yHWuC0zdCpPACPgOb43EEuJKljaXH8Jtx3nEly0I/4HNUWjC7zAKi8H7Me2RXMhd9NF2+/0kbG4+R2iraohsWAmFx22AYUQc3o3tgJSC4uAx/5xdMH0XDL+BzZBQthCKDVwGvbQMvJrzGzIcPl6s0onV/Y7riEwbcxTxWQ+lni6erx0u7p5VKlGyD1ca5MWSAVBY5BLi/6dfXLn0x79HlIb6eL5avHYlu+6s+4zm3+xNEFz2XkJspaII7CO+qNXu1/biA7juuoi48oUQ0F88r9b8mS/yLTmAFHcHvJvaDU4Hr8Lh1B1E1imP0Pbi706zl/7wXrgPqS62eDujJ7zn7obZ2yD492+K+PLiThqzF37wXrQfqa52eDu5q8azoTAXz8+yvvEU7ptPI6FkPgR3qsPevbnZzHnPJdifv4+IBpUQV7EICs7Yrn6epKbFbdMp2Pz5jN3HGbYWWc+TB3xH5e17YxQWjYLTtyPD2hyvFopHy81e+MN70T7u+qf3QPazboFXC8Rz5ywevYPXisNIzueM9xPFhWKE1+S58ggsH75FUJe6iKleWvRyPdb8Aav7rxHcsRaia5VDgWnbYBIQDt9hrZBYUtz5pH5mBzRDQrlCKN5/KXQzMvFqXm9kSDifig9YCt30TO65trNCib6LQJpdLxf1R6bVx7m4pq8DkX/+HqQ52eDNrF5s7Bp9iLwbbC89hOvO84grVwgBA5oxR3bJvjk/9857L8H+HHd/hLWuBoPIOBQZuyHH+8p1+znYXnmEsKY/I6Lpz7C88xKe648jqbA7PviIC1B6Lj8Ey8fvEdStPmJ+KQW7M3fhsv8KYn8shsDe4sGAfAv2wvxVAAL6NEZcpaJw33AC1rdfIKRNdUTV/xhgQqlCyT6cQNWLxf2hsDSD+p3cuhoiG1T66B4wiIpHkTHrodTX496fFPGet5u9X/z7NUF8hY/ZKxYP38Fr5WEkezvj/QTuPsztm+Jw/BacjlxH9C+lENzt48hwTq9I5z0XYX/+ASIaVkJYq49Ve42Co1Bo8mZkmhnj5bJB3HimbYVJQITkfWzyLhgF5uxCur0VXs/tzShgJfrkfE8aB4Sj4DRuHfZqUX+YPfeD9+L9SHWzx9tp4k4+7e9xXr7P9idvw/nQNcRUKYmgHg3U9wqty4J6cc4c7eZ45Docj99CVK2yCOlYGx5rj8Hq3isEd6iF6NrizkTt+7jglC0wDorEh+GtkSSxLnDZdQF2F/9CeKMfEVWvAooNW8WG8nTdCEBPHFgK740UL6fsY+h+09cTvR7hOkA3LQOFpm5FpoUJXi4RF9X6wp/sPJ+OclmpfKd2mzJlCqjurbARDXn8+PGYP38+ow0TPXjWrFmM/kuN6L5VqlRBcHCwhvhq27ZtWbR37969mD17NhOtpRKhwkbUY6qx279/fwZ4vb29sW5dtso81aUlgVf6t1ixYixSS/38X0RkGbU45QtSi02MmSeYRZxKFoSLRImOzOAILp/GQJ95GeNX7kbcnI05RiKIJhzgWU8tWR7WeiQy3/jBcf8iGFcpy7wgxF1ftChbyVAdiXBxgNv9vdlewCPLYVTpY68k3Vhxy3ZwUZEOjWC3aBSCq/fQOI/YE5J6/YE6kmA9uR8iOo2FQYmCcDknXaIkbvE2xC3cwjy55P3LzWZ03thZ6xG/ag8sereCytwUiUu2w7RjIyYoI9Uiek9FyomrsJk1BBmvfbnozYiusB7VndGDt23TwYkTuqAoKdW4JHXefLsXoNT7Ewgz9oRNWigMVel4M2EdqvQqxGqaChsJUr1+rQNTnxGwefcXfPNXh9f7q0wkZn/Pw1Ba2bCodOXKKpaLSp66Z8+4yK9jn3bQDQ+H7tSxUE6dy8SKPPzPSooVkQeQPIH0QvbwP5crFYQfZ24ebNqP1AvVUSf/cwhvPQJpdzgvpWmTGqLmTb16H+HtR6sjSMKInHG18qLHJGw9iphx2REksYhsWMthSLv1GHZrJ8Osqfi56ZmJnb0BZm3rw27pGIQ27I/0R6/gsHUWTCRoihH/Y+8roKs69q83JBB34gIEKE5bKNIWl1KkRYpLcS/u7u5apDgULe4upVC8uFsIhBAS4gGS8K2Ze8/cc+bOnJO8B//2ra+z1luv5Nw5c2TOzE/2b++2w5G87xSL/rPM6ZqJVAtR1J5XbENrV0ktD9HwU0diibyFqCmZXv9jyyjJDMu6PNhHWcr5RiCfTwuaYImyzEyGd6b/8oei98FnTmWQ6rBPalPiL5LRJ3MnuvcU2FcqBZ+1k4RXxWe1WMbKjAYRdUraeQxRncbArnRR+G6djdi5v5rWzsbfwmummNAkae9JRLUbiewlCsFv5zxE/jgEKYfOwHNaPzg3ExteSbuOI6rjaNiVKgrfbbPBZ5JE16bO6pAsNHun5kySqM8rInexcT/cBrenc51mA8wIB+ma1noYkg/8QTNhJDP9stlAzXrLv0O239ja0Mx36uNnhpmKpL2/I6rdCPbMSBb3edkfkcXVCcG3dgovTUHz2JUtDt+N0wxn4quek5C46QDch3WEq4ThP5KQeR0/D8/Zg2iN+osfeuPN6b/g9fNwOEnIvfiM+9NiPyA9KgZ+h5Yge6E8Vtf1PpXsrWakxbWtVAM1LP93eB+fCP+TKylLOd+SD5/By5ZDNMiSJ0Xr0eAyyeqSGla+kb2L7GFODb+B12wTk3VYaA28T3mDgDNrqXwY3/hsn+ZbJHuAwNCO6jYeSVsPw31kF7h2agj+WkUvhl9zE9bsQvSAGXD45it4rxgnXhurd8K7q3fhvWoCHKqWQfSgmUhYtZPtr1brXEKSJdN9fy+yOtghevBsJKzcLkVUvL39EBGV2iGrhyuCrpsyNJEtBiHliCnj7ixgyU3cehivuo2HXdnP4Wtmdo74vjvenr+OHEtHw7GGdeCb7CVkT3FpXx8eY37KVEb29eSliJu9Fs5t68FzXHerZ/Xm0k28qNUNNoE+CDSXl7yo0wNvzl1DjiWj4FjL2vklcOuXTQcgW6FQ+B/6xTRXlPX191XIFmodrCW8BJH1ejFEBBvXjF4RvUQ+A0sy7CSzrmRoRX2UZ+Xcrj48x/4ENld0UIjRw+chYekWhoZS5rVzv1Y4U8BbmJFlKIFRXeDasSFe1O1pskkWj4SjRJ5Nvaa4dGiAsJwmYsBA83ctuh91ppfs6UZ9NOvF1a3Ux3hWqilglw0hEp1iw8Xwb/oByXzmyJEDYWFhGoSrnZ2dJkNLLo/IYPbv3x9Tp06lTiVRC+nVqxdmzJiBVq1a/evIZuYd/tNZizNSw8Jo+HO4I/fNnYhdsQ1R/aczQgfR8+DZXAkVu1pzsXXr1tSRJQXRSlNTkQefWImn1TrgzeVbIGQ+U/84iHHjxtGUvtKWLl2KKjejNJTtYTU6o96hdbiQGkehA2SMN2/eUEkdAhEgEG9/Nw+0jbVDy4rV4TW6q1Cfk7y3zp07Y9euXRRj37bAF2h/Iw7u3ZvDqVY53PqmPUa+D8fR1Nf0ODk/rw2r1PF4DGoHODkgZvg8CkcOWD5eOoUYG+WikRSWRfS+iE5njonyzFJE66FI3H2CErbErdyGtzcewH/TDDgKYEzKwGEV25hkQDZMo4yPis6lTBuP9FPYF9VESXrkSrx8Q0a/m4ywKr69H6Yhk2AEFtP7U5IQUWMaj6WLIXDXfLAaSbO0gqhPzMxVGsFxUS2SWgpDNraaMp/oWhrVWpFrUc8Fwi6ZoZquYvWR9vwlgg79AlK7qq6NEZEyUVkOVe0tcWQVzbyc17fDVgDpV4vFk/r1v7OJ3oeoTo2/Rp6ki0CLI1oNpfBPQggiaqymNF9OhPyxBow5VEenl9WyffMV/NdO1ojZE61BUYtbt0dTK5YRibS41Tvwss9UOJpr5jJSV6tmfiU6jEbvnVyrQgyWY2pfylrMarB1GLuZhMmS0bAN8bNab/l3yNYND1cQgjVeckMElSaMp2oZCkZupFOjZyEmqkB1H42aIlPl0acVPAebdHP5xpMBsbVhhphYh/Rntf4Hl8D+swIwYtPl5VpoDeOnP9DyBuW7569LLeUVuH0udXzuflYfdpGvqYanqHZTRKSjlkuxEzjZRC6MjOU1rgfcOzWkcixq3U8bN2uoNE8+xNdBip4zzybMkx+J+rC64h3z4PDlp+BZjPk+PIEYydK8GrPQpGncuRFyjLV2Apm+a4g/CNMzaRHtRiBxx1Ehpwg5zr7db8vCf/VE2sdI3oxJh/VqCa+hHTNVI8t0tiXSVLy0D72exv1Aymy85w6Ba5MaVo+XsVOXLEIJQem8LloPaRFR0jmZeOAPRDQfSMtxgg4uwdu7jw1Jy/iaWDZXdGR+Xg6cibhlW6B8txmZK0QySk3+p9Rgu3RtgtPFg4Q1srzmMNPCnjUIrs3FKAHedmAkX2fXQ1bupNYlJ/aaESs2T8RFShgf5TXLPenwzxith3/H8cz4U8HBwbRWlbAJK434EGvWrKG1qw8ePECePHko/JiomyitQoUK9N+EmXjZsmUUVkx8CaUR5Yr/b6HF/1QdWRJBDCv7I40gEqNB1JimVmgQCAkTz+gm6sOTS/A6byJHNmH7UbxobxKTD9w5T7OYT79xhkZU1Dh0Mq6apZWQPkwoXgW7rl3A6XexzJElRdaTJ0+mUZjQ0FAcGTkN9ccNxsLKDdBgyXQTS6SZBEO5F/JbgqknUZ3IyEhULlEKveCDdhNGgohoNyn8BV5lTcP2Z/focYK7Jx8JwcsrLaL1MCTuNol1v3d2oLW8JOoatFUOH1c7mOTdvBoxH84NqsH3Z61AtvqZM0Nx8SjErtoBknH2WTQSMmp9usmoHJ4XHUaZRMl12DiJ9tjDYJOUBBEiJ9q9pD6VzAdRtJX8Lvn0X5Q91UjHlJ8/GaHHT7l4Q2MQv+g2Hgkb98FzeGfIWGeZwWB2KozYG8l1vRq9wETo06Uxcpgj32r5HfIbNvaIzvDoLma8ZZT5/dvAc0BbRLQZZijkzrNqZsRh5omnjDQDeVmOrM6OVDMwPT4RwWfWInueEKvPWy0WTwJbf2eTkZwwduHzG6g8Cd/4QBsJslHdw09yIuTUGuEtqXUCiWY1c2x1dHrVZB7kG44nbLpdxupKA71euBGvhs+Fs5nFlTfERBcXM3ctJe1zblQdhPQkrHwrvL35AP6bZ8KxwhfC+4kaMhuxSzYz6QpGTnJ6LbLntX7v5CTqYIrTdxVMGrlkTdBh7A6r2Bpvr9+nwTXbYD8rNlP+HaoZvnOe3wie3VTESs5rB4vmNf8QYuasRfTYhXBpUgM+c4cYTuNX4xfj9azVcNNh+Gds3ltnw6FscbzoOhYJmw7Aa1RXuHczkRfyzeqbVaTufp0CEakUI9axz47QMFMg6UnZlrSOOsA8Lj8GY0c1r33kmd8u3YTCnv3XT4NjFWuER9SwOYhdtIkGb71GmCDdj0s2prwXgbsXUJIvvomM9/skUKbD3KzMKZ/FI+FSryreXLljkiDy9UKua5a6M/VYvLOvJn0kTpGoMQKlI8tgVzQfeF1Zvg9PIEaOqzV/fWYOtBqGD8aTHzCW3CEd4NHbYh8ondWSTb4LTfs8sx2m9IFbG1NdvrrxzLuZIXtSE7b5mevU1edmAboShUDWOXo9bYcjcecxGlAngXWr+bV+L152n6DRC1Zrm3IeeQAAIABJREFUbouCqIpD6VCuOAK2zAbP8K6wxqrHUhMgEpZixmKsM1fU8nIePzUD70CL5gpLDkztC7fWdaGwkRMOhTPl8wsd2fBaJhk3Qh7o/H2lDElCsfV0yWjK1mwUgNTokl/dCsKG/KhIXVr/Skgk7QT8IIRBWq1eoCZV1Vu3hR/R3/zHzDiyXl5e1CYn8F+lTZw4EcuXL8edO3eokgYha+rXrx+rgSXnJ7DhFStWoEmTJrh58yYKFSqE8+fPo0QJE2rvwIED+Pbbb63Inoi/oPCmEEjzli1bNGRPBBb9Pw8t/qc6sqnPXxoyHj7fehADmrXCUcQjLlsW5PMPwqyXzsj1WRFsql2EsnYRxi4yAXr37k2zk8TRePBNB4xKD8eRrAl4G58AvzQb/Nx7EKpMHQ7iyJKXTuiud+/eTSfUjPo/osAv++BojkwqDKxe43ti1rNrQkdWvcDGVS+FcoU/xWybnKj7+jJzZPlvL2b2GjQZ0AtFPi2GKQe2a8TISXSbTDhSoE2Kxb8gAlsAhhevhP1XL+LQstXIUvELeIUEYaNbMdR5eZ6ywRL4AsneHlfxlytssMSpJI6sAmEOkZCPkHEUvTLCxEsyEy97TIRjlTLwXz9VuoQoRgwxWgnbnl70l5yEfMDEKaXi5Rc2gkTRqUC6jqQAv8k8Kd4QqU9fIFBHGJ43/DO6BjIphUHt4NlXXCuTdORPKs+UvXBeBB9bbmEiVBldVu+dMHSP/pkZ+xlxQHl2TJHBkBEtO17nMLLXJMSv3Q3PwR3g0cfauKFzwSx5pWRM+A2Zvz/1BpXzxg7YensYRvZFWQc+Q8SPw4vFZ/S9fozfyQw4nm2UH5tnBs6IQcSzX/JSEKL7Y1mtNia9SyYNpJPFVUu4eE/th1cTllBkhmu7+vCWEFGxjL/ZyQqv3Y1KCilGleja+Pn0+ItGlJgocO9C2EuIidSBNsfKpZERxm71mpYtxN/Cyks0lG1trbJJSYf/xPMm/ZC9SD4Em0mk1HqT2YKt69lZlqlpTfjMGUzXOOpkp6Uhp9ng458Bk57r2BAEJWHUmOOrw/DPG6IsCCHRaRd9szwSg78uUSDJSBaGBUfMTMDku7lZ4Uc43X0KXwkihQWJVWsUe/8bp8OxknWNqDr7Tgxz0vgMEn8/LGC3djKcvvmKknuR7CkfXFb3Y9+32SnNCFM5n7kycugIgRjPIquWkiJSQXzjmZ7JcT5gxPeJnr6CqiCo5YbY3jSyC4jzxTe1beROiCHfvdPom+vN5bi1u3Vls1iwrXwJBPxmQsxF9piI+HV74DmsEzwEBFFq6RlFt1mNqHP65murS4pduZ3qmRIVCL+VE5CekGSovcrvte8ehhvKValRJMQpzUiA/dkPvZB84gJ8Fo4A0XZWvh/HupVxtnZxoSPLtK/NaDgm96Qjz8avp8yW2zILIp1i0TMyChgwdnaVnvyDXN8YJiKM1sO/43hmHFniYxAUJqldJdBiknklcjhEGocktkgj/z9p0iRav0rqXAmqkmjCktpWBf1Zo0YNmtRauHAh/c7atGlD/QJFfof4dvnz56e1sgMHDsS1a9foGISUSi2/QzK9/zqyH2nWZGTx+L50Wby+dB2zqjXAZzsX4ey6LbDpMQ0+uUNwfnBjlCpVCkFBQTh27Bj9wMnk+fyNLWbWaYH1iMHJsHt4N2Ul/lq4Gj5t66PYtCHUkSURix07dqBcuXIgkZLFM2fjaNYCTAroZb9piFu5neo0zkl8TLHtxPklkZaGDRvSSRfdcohJ03bBMDRdORc10l1Q5Mw9VIw5L3Vkw4fNRomJAzChfku02bDYClJHJnzx4sXppFWY0NaV/h6dz+1B+LaDuOPvjBKlSuGW19fIe2snbHJ4UCZbUiSuhiCwTMTG6Uh3smd1J7ku/yZ9m2poCa23aTkYdqrIqKijOtIct2q7RitP9HvCKPgwl6kWI/fD/SDyD0mHzsBbBwLDjCcvN+S+tQs8tEs0Dg+RzOgUZkZ5p4bIMU5sYDJUwFefgUDlmPGvoz3IDFczVNvIwCDXy2Bh5ki0yGBQy4sQx0PUGOxo9iC4NquFqJHzqZ6mnlzEwwK1kf4qFkEnVsKuYCgUaKN77x/hNaSD1TBpcQl4lMcE+1Ikq4wi6QzO5eaM3PdMrIeKZp7/bzPhWN46m6eWolLo+zP6bj/072QG3JMyzahsS8D2uXD4ygIbUsZnRqpfDuS6uhV81Fp0nSR7SeaM0/eV4Ld0DDKiQ8pLPWQECsdnwtR6wr4LhgsfIVsrzRn/jKAN+N9k5JtW67valyisCbzZfy5m5lScXYLeINBilsUla6eXu5URzsNgyQ0byX+InFLmQP2xBiL5CyMnk3/QGSmpUd8rQaoY6bSrv1lFBiei1RAk7jlJuRTcWlmTiCmBJLVElhEUVXGWXFp+B58ZA+gzv169HVyuPpSu+2pZIAITJo0FSJaNhbOAi4A5peumwqlqGdrn8ecNTEHPA4shmiM85JfXvM1CNPG4xkMw+e+Z/71I7zvu19142XMS5RsI2GBdI82XEpBzGjqBHMSd9DEKRDGIsxn1Q/q8HDADccu3Ms1b/n5Y5nvmQLi2qJ0pR1b0fanPzzuY5BgPZeavhw8k0blSr6cuOoyXaqLBJ98KlFdFFnziHeq0qBg8MvM1hEYcEzK0s1Ils1OaEdkt3glX3jth0j7fpKzQkWXzfN9CkLXRCLpOv40SjUDYmwPNfcJrdtGU4PHPWZR4elq9I95cvAm/1RPh9G1Zq29FBNU3yvx+6H36Q50vM44sSZIRH2Hr1q0UNUmSZU2bNsWIESOYTA6Zc4QoavHixVRjtmzZsliwYAHVhVUaYR4mybmdO3cia9as+OGHHzBnzhymRUt+R5xfAmE+d+4creHt3r07dWrVjbAc/+vIfqiZwJ1HE7m+sgW2/lpWXBKJ8PPzwwmPL5Cv7rcg0Ta9Woa6detSseAeBUtjQauuWPT+JdYe3IN8J25QsiTXVnXgPa0fdWRTUlIodJcueuHh1Bk+51kaubo0ow6Muq7wRbMqcHNzo5ORREtatGgBEuHofzMZhCTgRPsqWHvud2wo3wDXZi2VOrLkfhsWLI6nDx5i98RZ8OrbGg8/qUVlTUjtJ6k5OHnyJEgUhuhHKW3npzVQ78o+xB0/hwtZkvFthUq44vUlg1+SCfzll1+C4OeVps5spTva4/nXLXWjzJp6ort7aEb22XfdKHSXGIGipqlxvLwZcat2Mu1RmUC4WvONGE+kHiRh4354SqK/ZFw+4s0ilj8Ph0sDk1PMt9c/r88QNNpqU2SZU5MWoagxo9IczTWKrpNzMHhvv9bwHNgOzAE1Z8tE4zAD0awbKHKceCio6Dz8BsUblqI+9wMrU8mqkEubkS3IFwq0UZaZU2pXiWxCnvAj9JQs8yuBtbGarmA/5Lxokqox2kwzUlrwkZYrq9PKHNmn33Sk64Lfmklwqm6dDWB1YPlzIeT31dDUHUrqhngoIl97JCKViuw+AfHr97JMRkayuHwfvs5W9GxZhsZcm2iUvafvmcva8gafaBweds5nIfg+GgfC7LjyWVz+HTINR1XNoFo31aGMtRanCH7NnG4JaiQjsF/1/cT/dhCRncfAQZWpUh8XZVeN4Muib9YIKcIy1kXzIfiISfbIqBxDVCJxpU4Xyoqv1LPy704EE2a1knMGw7WpNfEY75SScxplmfjsqhEs/H16usnhAaAgT3jOBP5eNNqo5u87YecxvGg7XKqDzODKKvREwrYjNPBr/+WnCNwxz+oTiV22FVEDZ8CplqXu2mgO8PsSOanIuVUPptb+JiUImcnIGsGwWTlEw2+gBM6MAjKi40alMAwmrEKaPMxTg8o8BUvKG1hJzuQ+cGtbT1uDfX8vbFwtKgvK82JOqXkv4NE4onWOBULN9dQKvwYh7bvQobrQkeV1Yxm/hkozmx+L78MHvPnfi0oBjYJYonnMl0D8X+3X/+04mXFk/9uxPkb/fx3Zj/FUzedkjtzvq6z0Kc+ePYvyX5fFdffScGlRG6QuJPXFKzwuUpey1p6e1h4zZs7Eo0ePQOiuCSyXRCZGFSmHiIEzsCJnNuxJjcaTe/dROc0JY35oicJrp1FHVk32RKIhBM57zOMLFB3SFZ792sBS92Xt0JA6RZK+P5uzEl7ee4h62Z7g8MnjyLH7DK6MmSN0ZInT17VrV5zetB0r3udE7ukDaf0Dq7cxk16QjCzBw799+5ZlZNfk+grdnpxF5OUbuJGWiBLFi+Om19fIuW8RheGRLDTJEqszsmooU5qjHdPIDZUQo7DnSghKIo5R9tmwcj9STc/ct3cJZwCpZSTGJWm5Hx8EMXpfDZtD6y18l4wW9uGj16JaKL4jT+bAQ5tEAymRaCOyKr4vX88lOjcfAebJXkR9eHhvRhxQ5hCtnQQCjxIZDErmWRbZFxlzLLtXpzJEdUqammTzBq33PZAx3tx8gKflWyGrmZSN/C1q+FzELtwI9+7N4DXCUiuiPJ+ko2fxvFFfyloafMyk0fm8SX8kHT4Db4mxyovFf8SlyfDUMgOOkWlJAi38fBY5IfzgUaPmm4jlzJkTkZPG92G1VuZat4xkcfk+PEmZ6KEwY2beUIpoyQjagK+j5Y1EfhwhDPa7n0D0WGXwVMJa+yi/Sc4o9NlRWobBMhdmB5N/hzyhC+lLIJ5k3fIzw0/5axM57szJliALMkLEpB5HZBCqj4uyqxZCqfLwW2FN8ieCCRshL5gzZUajkGtgmaqhHeHRy1rbna/RJ8/8cuOeVOrNc1B7EH4JvolgwjxChe/D6vXMkF/67r7tZCpdkWSM+OwqDc76VaQ6wqLMnGbPe3KIsglr9s4Xx60Y8lnAIJst8jw7Si876dg5PG/YB9kLhSL4+Eqr+xeRAiUeOoOIpv2pfqcIjaKs0eQb9JlnCsLy9dsZmbsiuLG6H58xzIwjy4LSEj4AEcLIiCBKNGeNSOrYGqVCGBll70VOG6vBvrwZtoHWkos89DYj5HF8aYoyVwgr86U+9a0cWdGcFcGt1e+QBmTIPCcZ6GvbYOvrhRedxyDht4PwGvsT3Dtby5OlnL+O8BqdKWM4IxMzqF8WQcWNShEMN96/6Qf/OrL/PnjpE2C1UXt+hj0nvm3JyJZEwR6tkGNUNyhG9rO0FFSKu4R9+/ahYsWK1OkjGdlcuXJhRPBntO5DgTLdX7IeLbp1RsGQXFh277KuI/vppIEgdR88E6f6BsiYxBk+7VESfzx7hNZJt2jGlmQ10xKTEfs+FZ6enhQf36BBA1ozRRzsM2fOYLVvCdifvwVS40KimQyaYY7YKTWyRGdKKfAe7J4PhxMjcer+LbzL4QYPZxdaI1t1088UQjVt2jQKkz5x4gS9TJ4ciWjjPgmpRrX+ZGywfLRNU79I6skEECsWXXSwQ+iTQ4jftB+RXcdJswZ0A+ecl4xkB3miJFb/Yc5uiiYXbzxl9BNM2H0CL1oPpXNRYUDk+/IZBqMoM+nPZxMy5ICWbkprthQiLJHBwOqidBhveSgPX2/J35+GdZVAprJmhQL5cqxRFv6rTOyW6iaCHDLItRkJwfdhTpKZYI0cF0EK1f14SFhG3+vH+J3MgGNkKebIPT82gwhWLQP/dab6cyOSK8ZCPrAtDbSRZsQyyWc5M5LF5SF5IgIZ/n74rIOakZjU5ooaPydFNZHqfqKstRGEmdWwqcj0+Low/h0yKGbb+lBQJUZM5iI4LkMWrBgPZ4FkSEZYwDXf1x+X8axOdyl5XWr4Czz+rAHUiAijLG7ymSsm1E3uIIScNaFujKCoLENvZqgmfXgIO/++WfZ5dDe4d21CA3IXW/Wnmq9qMid1PxFMmCcZ4sdhtXcq1lW9oJIou0q/RZ3MnAheyZfLENI6dWNM2KqgMHMKVGgUdR8RmzCrr5SgpERZRrbWVyqFALO8jnocPnBFjhmhmVhGbdscECKlzDiyKZduIvybjrAN9EFOQZmTqOyFL6vg3zvP8kuOMxvBXO5g1UdBq6hIEllwTRJ8EjlgD/PXRnp0LIIFiRgyJk+GlBEmbUYWeGEjSF2/glyyCfbDXyNbWDmyohI9o+C6JiATdghZ7e2sUGP8M+O5QchxI74NEUqAD3x+jL35Y5zzX0f2YzzVDJzzf+HBh1Vqi7fX7krZC2vkLYyUJ8+xYMgo5B/xE/766y+k1+yJlymJqBV3mRZRFylShDq0xGkkBc7DnEOxb+4SBDX7HmXnjsarPcfRuEFD5PULwC9Pruk6ssUXjoVLo2+hzkScbVcV5cuXp/WxRJyYYN3LlCmDvttu4s3bt3DcO4/CohP2nMC1AZPRMPYKrl+/Tp1qR0dH6sT+/vvvOHLkCJLq99FI1IjgUoR9mEj1rFu3DhFPnqLyZyXQ2zEEvcMvUvhKg5wFEfX8BdYsWYrkr4pQ1uKxY8cy1mKeHIlAjh/krQnbpBQGYeanD0+iwzvDIukCZVOyCfBBrr9+A4OdmUmQRFNUMa6Izmgg0bYUwKH4foQgK3rcIla/bGRskf5GDpHs8xHVJlltgr0nI37NLhBpI0IIpRiE6roxvg/bBFeOp8zTGSGj4utURQZDRq6Xd3hEzJAaw+v+E4SVaY6sLk7I/WAfPcQgvV9/jsBt1szXotpVnuSFfyai7Dcj21I5bOp+ImMtA0vhR/mJzIAzIidhhuIP1aAwhfKZQv6CefguNZIMJCYsmURTRl8jDXR7F9UA5RvvQKRcvoXwah2gfOOiB8mIwczM4xlBGzDEiNnpYBnnrk2QY7RFskAZT5RNNoIwi66dkeCZWWr5d8iyO2ZpETI+c1TNLKL8MxDBoo0kQ5SaYBlrLz+GUW0dQ0SYeQRIf6MAm+ibNUJeiOauhVSsHryn9LGaIozwxlx3S575+Y5D4LPrDFzbiPuIYMJ6mX5Nhkkl3aVX8yvKrtLvyiwnFGiWJNKsjYpMi6quX1Nfac5uqfswJmxVJstIsUHkTBqRwokCCiJpGvW1ibKMRqgXPnOZGUf27Z1HCPu6pVSpgtXbq9Z/I74LEQu/0XrCMwOTZ2IUfBKxcxuR1LG9V6WwwJftqN+HSL5N/cyuTO1o5ciKgitG9oWorMAIwi2CtivSQDK+DWa7qdjZjZAVH2Wz/gAn/V/wp/Ru819o8QeYBLJT8IYF/7s7LQdg1ObVOGb/Fglp71CwYEHMinaDz+tkLG3wKRZvWo+0tDR8//33VLOV1NQOfueNdatXY4FjPJ4lxMIhW3aUSbLB+IJfo9jlbbqO7BfrZ1GjL+nEeTz/oTeyFciNQcGplPY6OTkZvr6+aNy4MYb1G4CIAibNUEJaRKKwhFr9fJOeGmjx48ePqUNLRJNJ1pgIQiP9PZo1aIglm9ZTOEejZbNQvsY3GLvdVLNLPphOnTqZdGTt7NEs2RHdnXMh1JwZvdtiAPpsWo5jWRLg4OpCi8FJEbnSeKOGbDR3P60Pu5dy3T7GaFq8IIL2L6anMtII4x3XjBi9rJ7UTFpjRP5AroPPgLJN3syCKZpbRrUbsvmowO1svD2Q68YO4c94EiNee1LUiYcYGTFd8hqrtgE+wsi3iBVQszGSIIYiU2J2XozGFr1HBmtT1capxxE5uqLMo7qPyFhj71ri0BgRf3zEpcrq1DIDzihDZclYWox4NTmbiJFVFPAyqjUSOQNG3zQvcZIRFldWHnJyFbIXyA0jtIFG0ubObth4uILXTOYftohQx2gusGyyCr5pBbfmGFdFNaIs4yORuBIxpCqBhxwTelLJHL4ZScnwv2eOvKM9Qh8ftDofkd4gEhy2uQKQ89wGetwogyeCr4rIdtSDiaCfjBDMLL/EXxzv6JPv5myPUfDbfIKxuPN9RDBhvXIRTVbq8UFkdTRpvivBDpEEkUw1QU//WrbH6TFoi0ooUp9FUhk52NqYYO9ZsmgegQjNIkIYqDuJOAmMIMxPa3bBm3PX4KtCDhhl8vlysMw4skY64AzeOqYb3Ls0obdnVN4gyvBFT1uOmMnLNGzM6mfFMwOTY0bBJ5Fest66LSsZ4QPU6usSoWbYPLW1wbWfe6FmrVpMaoX0ZY6uuwty391j+vZPXTJJupl1x63W0xv38bRCa6jtHBE0Xd1PhFI0Ql3xGvbkfEZZ3P/LPTwzY/3ryGbmaX3A3/4vPHg+Wmu1CTbsw5iBXRpWp4eZUyBhBeV1Y9/ee4KwL5sjq6szct83saPyjZcbMWIiFEmHZEQahNeYZMaYhA1WBEsyylrxTHFko7n1VTM4PoqQEtDECbTYjITueSgxY1+1z47cTw5Zbc7kmfOww4xAF3ktPNG18u/TYlyaZBUy2tSbhsjAoBueQo9vroHMCAybsTsfXQ67Inlh5ICK4Goig0FNnkXYgvkmqhM0yu6ogzghJ1eZNsY/r+BZ7W6QZZ1F0GMjQhMRBNVIK9HIqcjoe/4Qv5MZcEbQWpZZUmX9RDWB6msUGZx8lp+/JxHbLk9uw/fhoXKami6zZI26D82EkUCJqqbQKBuQ+jIGjwuZgoAK26elntNCVKMehyfIomvJpF+otqYsq8drg5M+/FrCv0PRfmS0RotYqo2g0ooxG2x2/o3mo+g71jwfRTZIFWh6c/0enlZsAxuV9IW6D09aR46JnFt1H5aBUdW9G2Xw+PIZ8sxPD5iAwDWHmPwJf/8iiQ494iLRfkzOqVdiwhwAVXaV9NEja0v+/SKe1etppfmsh45gjlipolQDlzRRTbPmOSs18d2a0JIq0owYlUXcEbwuMv+cRYRpRoidB0FVTPJ5ZiLAzDiymnksWE9EteMM0qqSxDJaG5k+riTYzfNPkPMZBZ9E5R96TNqyd8yCWIJyOlHASh2kuT6/J2rUq6NxZEW1q0b2qyjIZVQ+xOuSk2dmhL4RkYmJ1hCj9e+fcPx/wZ/Se07/ZmQ/4iwyYkkULThGBA4886nIcDIy4IyIUURRMBG8Sz1OevIbPAypSv+Uy0yiY8ReK6xjGrsQr+eshZtEg1Cp87Qz101SuYNqbeFy/ZGUREe08LNoo1mbjH9miq6dk5k0KCNySozav08reA5unyEBel6LjWWPPysAmQC93mahN53V70jJtFtt/lXa4e2VO4z8RfRe1X1odjWoiokF+OImEC1KNbSHytVwEXlRtkBkMBgZRBaWRAeEPj5AL0sdcAgNs3Z+RXA0o7ktql01ygaIMpdG9VBGMM+PuFRZnVpmwBnVmIl0Go1YNkXsq88a9UXy0bPwnjsErk1M0kfqxgxO85wjx/R0/0Qs8kZwZM38M5PfGGX83+pB180lB/y9iOakCOaq7ifKICg1eG5mB4F/hyKEkBGcna+DI9egZ6zR50xYwd+lIqeEJIa/fxHkUP0bEbLF6DsXadMqcGO7T/Mj6NAvVnNK5KAbMYnzyAHyzE+NmIbgX/YI+RRERDTkQvSIixTmYHU5BOmjx8BL9ObDq3eCbZAvcl7azO5Vj0GbOXkq5JLRd6VI7ag12Y0I3tTyf579TTXxRozKjCjPLLNG+hit2yKOEhY0KpAbSiBTeTgakjkzwiczjqymRlTA9CuqRzdKEPDEceRajdjWRckQveCTDD6ux/TL6ta5rDsrp9swDUQPW91EQWb12Lemd8E3TRtqHFlRxt9I41bIir31MF50HAV7FZGb+tpEgUPR3Fb3EZFuGWVx/y/38MyM9a8jm5mn9QF/+7/w4I3gYSLpA8WAI8x8hKGPbzw0yMgYEwnYiyjz1eOIIp0MLpTNFpQdmHdOIqLwuGg9wMbGBBPOkgUK1FbG9Ms2ThUNv1EdE6s9rPYl/H+dQiGpV+p2hfvZW/BSQXY0i9TEX6ykc3iaff458wubyGHj+/C1q0YOHekfzrGTimB0/DiMWl5Cpa/3mT0IroL3KW+Z08n/VgQLZE6DmaBB3UfjHD/YR2tPZfVZSj+WiVfVvIkMBpnRp5xHFJk1mtuizYltypK5LapblhmKyrXxUi/k70bkJEbEOx9w+TQ8lcyAMzKiRFkHkXOrvgCR9p5Sa+Q1viclqFM3GakInx3TzFO1xvOjA8jq5EAP65FKMWfJLjvVDybNkgkUw/OZ7JLKgWBlCpKsC7+mkXGMoOui4ErMjFWInrgELmZZCv4divRsjQjGRM9HL0Cp5h8gNehkPchI40lg1H1ETruGIEvAVi+qiRMFTtXjiLJWRs4vX3NKnvnJCXOQc9422HEOIRlLFhDVWxtkGSg9Bl4R8oSMr4cSE7Gwkj4ieLny3PiAr/J3Uf2kcow5AKr92ohRme2TS8fA+ftK9FRGwYyHBb9DetRrBB1fAbtCeWgftm4LiKhEgdNMObIkiEMQHGlpyCmQXBRlw43QS7y+NLkHo5IlEXRdL/gkha53HEXHEslIyeqgeXtG/X2JdFfJcYWA7M64tqjatoXGkRUhT4w0bhmarsIXCNg8k16CUeZbVKNuVIPNoyPJOEbcGRlZC/+O3/w3/tSkSZMwePBg9OzZE7NmzTJ9Zykp6Nu3L5UBJWWR1atXpzqypHxRaU+ePEGXLl1w9OhRqh3bqlUrTJw4kSmakN8dO3YMffr0obw8wcHBGDZsGC2fVLf58+f/qyP7MSeNETyMLbQnVsKuYCi9FBI1oouHwIAjx0WQOhFUSbkvkVNh5CCIagZli50yjsg5YQtKxZII2DTD6lEzGK3quJGhzEtIkI3mUvM+8Dp6Ge4SCDPLlPZtRSURSGPsq2b5Dv7iGGxE1ceIgIaH5RoxPpIx+WwU0xKWQMWNot1G85ndw+GlsCtmEadW+j3MVxPpr+M1xFkMsinoI4IeiyCZmg3NDOVVM4rKDAZ2PX+sQfZ8OTW3J4JkGj0fxfBSB1eMHG8R/NII0i9izDRiYTaSQjF6tx/yuOx9MMNCovfIYMS/jIFzHZPBKYIbq69VtH4pGQSFdEz9e5khw1hczdrE6j6ymkE9Afs3V+4QEN/8AAAgAElEQVTgaZV2sPHxRK7r2+npjIJTIvZLkaaw+tpEsDYjI0rkqPHkcvw7FAWp9KCz6m8p180dsMnhQS9bLyvPEEJmqTMRI7xonrLyhGPLYVc4r+YnIv1NI4kmkf6tURBCVKvNnF8Jmy7PAkye+fEZC5F72kZkM2spa+ahIrFHno9KzkaPUZ45AHlDEHJ6LTudntEsW2v0NH5FcGwyGM/2rb4fWbmEKJOv9JPJM1ngrb8ie55gzRwQEWcaQXn5UidyQuaACaT3eCJJEozPjCNLzq/H0M4zItP15NEzPCnZGFkcLagi9Y2LJBxFRGaa9TTnN3iflIyQcxuQLVcAPcQyha3rwHtqP82zFd03+QFjkzcTP6o7yZipRRrJSj+ZzNbjz35Aangk7g1rgcpd22ocWVGQTxPIvLsHNu4umvsRyfOIIMrqTiJ2aFkwSOknctqNApCite+f8Lf/1JE9d+4cGjVqBFdXV1SqVIk5ssRB3b17N1asWEFVTwjXTdasWXHq1Cl6u4T757PPPqO8P1OnTsXz588poWuHDh0wYcIE+puHDx9SstvOnTujffv2OHz4MHr16kXPSxxj0jZs2ED7/Qst/oizSGSgKMOpM3w5//oNhPCGNEatLmA2FZHkkD56rKCyOkORw6Jcm6iWyChiyuoS8gQj5Myv9FRG0WxRDYJR7SFfYK9liawLkSQGCw6M7Q73zo3otRkV5YuYVI1Ia5j8xfppcKxSmkoTPQyuaqq5UUEg1VOOGXBmfUCNkS6oszGqJzOazno0/LIAh7IB+2+ZBcdyJTRDyCKzehrKhDgsovlA2Kng0zKDQU/CSmb86RkTIqIMGSuocqOiEgG2+XMGqdJHBOGT1aApfUQIDaP3+bGOy96HyFFTX4MIsi8igGLrYFqaSfOPlCSonCUGkxUQY8lImkQMn8o4onp8cuxJuR/x7tZD+AtkKUTvyyigx6CoKggbgxtLglMM3quSxREFadTPWVSfxcNg+Xeo1AgHqQKnetBZGbRfJFPDnvP9MISVaaZhBc/IHBWRdyn9ZAFhlvVTGezsm+06FgmbDkBNhGRUc8+X7ZBz6WXMRGgn8syPzl+KPOPXCmVYFJhwFmdHhD7czx6NXqmCaL0kHfWCvjKJEtG8US5CRmylVxrACOw6N0KOsd3Z/ejB/GWOsV5QidekJwNpiNXu7YFafUAThLm1EzZe7vTa9OaAqCwgs46sXqBYxBitKQ0jgQ1OClCk5apHdCa7b1ZepWKTZ9+swlatIlQix0RyQUof2Xy1aMpbbC2lj4xoS7FJHvZtiAp9u2gcWVmJhai0RBmHIVNa1IbPzIH0zyxBwNWMK31YWY8qscErV/DrGC93Ro4z+7V0MQTump+Rpe8f8Zv/xJFNSEhA8eLFaaZ13Lhx1DElGdnY2Fh4e3vj119/pWorpN26dYuS2Z4+fZqqouzduxe1a9fGs2fPWJZ24cKFGDhwIF6+fIns2bPT/yZO67Vr19gzatKkCV6/fk2VXEgrXbo0SpYs+a8j+zFnkd5GI6tXZI4atzGQ65QZUaIPSrkvRmuvyiqQY3rMkiwyW0srNq/n/DISFJXmJ4uC5fRHzvMbrR61iDjGyNjnyaDIRvNnn7HwX38UMgiziPmPZwvmL47PrpLjbANeOAIuP1Szuh/RRqWXxdUEJsz1ZJpMg8qwVwZjRjxnCGV0HosyZkpfNSw3t1l/jd53zS4gcHPfZWPh/J3J6VCaDAqtN78YhE0F/ZEZDCI4pDK2rIZFifAGHlgM+88Laq5XRqmv5/yK4HhGNV2i7CqDCPp7I9eVLdbzp1AdpL2MRpAgK5XR9/uhfid7H0aRbV6+glyPXr2nSEOV9GEazCpjhK1pf90Geb423HPU0+K0zNNA5DxnYlCnc7tWV5BjorktyoqKnBf1MxdltYx4DBRZHA9zbT05nxGhichg5IMM6ndIWOVFtat62R0Z5J5JVQjqzdh1m2XLMjof9dAIMqZs3axfi0FI2n8K3jP6w7WliXxLNteUa2TkQJtnwrHCF/TPenwSorIK8swPLV2NT4YvR1aB0cyy/L5eyHVtm2UdPX8d4TU6w1awV8rkwRjEVCAbJpN+Y3W1AvtCRuQmqgVULlymacrrL6vngYgbhBzXc35lGXuRo0fOJdISpXMgOhaP8teml0NLoGxt2aWxd+OXA7mubjW9f47522g+6wVkWEmQCl2kx1shc9RlNh29v9h4PMpb03R/hJ/CLjv9b5YpNJdkqe9DVibDgr4CrXRZwkEkMaSMZSG909qVin3xuGsdlBvWU+PIysoYRMhEZRyRPFGqgoTImpUpZKifgSjwLApsqPs8LtEIqU+eI3DvQth/UZgeMuLOMJo/f9fx/8SRJVBgT09PzJw5ExUrVmSOLJHirFKlCmJiYuDubgogkZYzZ06aUe3duzdVItmxYwcuX77MjpMMbGhoKC5evIjPP/+cyoISR1mBK5MfLl++nJ6DOMtviTyooyM2b978v+/IEk1Sktb+J7aknccQ1WkM7EoVhe+22ZpLTHvxCuGfNwRssiL4yUFWcxo3bx1eT1gCp0bV4TXLFE1SWurTCDwr1Qywy4bgB/tYnxcN++DNqcvwmj8UTvWqaPqknLqEyIZ9YZsvJwKOL2fHIr7tTEl9vFdNgEPVMpo+sXN/RezEX+DU+Ft4zRzAjoWXboa0sAj47pwHuxKFNH0S1u9FdJ+psK9SGj6rJ9Jj7+6H4Xm5Vsji4oTg2zutXlH00DlIWL4Nrj2aw31QO3r87bV7iPimI7L6eCLosoWkQun8ssMoJO8+AY/xPeDSpi7daM6NmYWgpXthX74EfNZPtRonomYXvL18G94rx8Oh2pf0OLtHwXMmx59X7YB3N+7De+0kOFQqRftEdRqNpJ3H4THmJ7i0r68Zhxi4T/PUoPWnAX/+CttgP3r8eZX2eHfzAbzXTYGD2ThSOpLAxNNPTJtq0L09TFYhrMB3eB+XCP8TK5Atb4hmnDeXbuJFrW6wCfJF4Nl1mZ72L9sOR/K+U/CY3BsuLb/Tzq+wCDwr3QxZ7LPT+aW0yB+HIOXQGXhO6wfnZqZNUmnJh87g5Y9DkL3YJ/Dbt5D9XW9+xS/biphhc+FQuzy8F48yzZV373Dw4EFUq1ZNs5Hpze24JZvxeuQCONatjBwLhrGx9Z75q77TkLhuD9wGtoVbzxasT/gXTZD2LBK+exbQTLG6ia6BvO+wnN8AqWkIOL8BtgHemj7Pvm6J1Ifh8Nk6G/ali5ru8WE4nn/dElmcHBB8d7fVuwsL/dY0f87+Ctsg0/z5u5rsfby78wjPK7alWolB1y2GuHKdYfm/w/v4RPj/vgrZQoPonxPW7UV0X+3aoPw+1TznyJoWospQxf+yBTEj5sHxuwrIsWik5jGk/H4RkY36UXZV/2OWNS1m5HzEL/kNrt2awH1oR+08PXwGL1sOQbai+eC/f1GG5nbCr3sQ3W8a7KuWgc8qE9yJtKeF6yI9Jg5+R5cie/7cmnFE6wrhMaBzBUDg9W1Ukkfdon6agKQth+A+ojNczYiR1MfP8OzLFsjiYI/g+ybZCXWLbD4IKUfPwnPmADibuRTY2hDog8Bz6zXflE1qOl2fSAu6vZPVrr45ew0v6vaAbe5ABJxarRmDoC0iKrWzeteEhOtl80HIViQv/A+Y5MyUJns3VjfA/eFFo7548/sl4R72qtdkJG7cD7fB7eHWvRnr+ax8a6TeewKfzTMoiYu6vajfC2/OXIHXwhFw+t4UfCPZqrBgUwAy8OoWlqVT+oWXaoq0py/gu3s+7MwBMOL4hBepR39C92lbGzYMQc+EF/vBdOzpIZpNoxnZjVtQoP8iq72d/C7lzF+IrN8btqFBCPjdxJpOGnvWnm4IumZyopSWsHY3ovtPp3sX2cOUJlt7yXGZHRE7azVipyyHU7Oa8JqmhZjGjFqA+MWb4dK1CTyGWb6f6EEzkbBqJ1z7/Aj3ftr6tKhu45G09bBm7pLx2fucNxRO9bU2CXtvv82E/ZefsvuJqNEFb/+6LbRJwvLUpPJ+AafXwDanCS5LmvIt+h9bhmyf5GJ/J4iZZ8UbWb0Dgo4Ky23iHgm6tYOqPSgt5c+riKzXU/NuZOug5gWp/vG8Wke8u35PYzeQw5r94sIG2Pqb9gv6dzIn09MReGkTbHy92Nlkc+/do3A8/6olsjjaI/iedm1IffoCz0o1pTaiej1N2nUcUR1Hw650Ufhu1dqiKScuILJJfyrH6H9kKRs/bvEmvB71s9X+Sn7A7L1KpeCzdhLrEzNmIeIXboRLp4bwGNlF85hkc1JZy562+RYlR/XW7P+yNV20vyqDveo/HYlrd8NtQBu49WpJ/0wCBqL1T+kjsldIUDn80wZAliwIDjtolS1/WqgOLcPyP76cSgGR9t/aZ7J59bH/ThzZHDlyICwsTONPEWlN8j++kdrX8ePHg0CL7e3tNY4sycS2adOG1saqW6lSpSj8ePLkyejYsSOIfOf+/SpUSlISnJycsGfPHtSoUQOffPIJPQ+pv1UaOVarVi0kJSVRRzkwMBB//PHH/74jSx4a8cr/ic3p+iPknrkZKYE5cG+0dgOwe/YK+UYsR6qTPW7N/oldvsfxvxC4+iDiPs+LJ93qam7L/skL5B2zGu/cnHB7umWRCF6wHW4X7+JZ8yqIrvS5po/LxbvIuWA7kvIE4MFgixGQa/omON98jLB2NRH7pdYp9d18At77ziKqaglENDHVuZGWZ/QqOIRF4lGvH5BQRGvAee0/B/9Nx/G6TCE8bW9ydmzik1Cwt4mS/9rC3lRXTt2CluyG+5838bxhBbyqXpIeyvYqDvkHLka6rQ1u/NyLLiLqlmvaBjjfCkNYh1qILW3KtjlfuY9cc7YiOacv7g83LVzqlm/wL1Rn9v6gpkjOG0gPsef8WR48+clkqKhb/v6LkC0mHveHNkdybn96yH/NQXgd+wuR332JyDpfa36f5c1bFO42h/7txrweSLc3RUJzTd0A59thCOtYG7GltA5StqhY5B+0xOpePxm8BNlfxmquVxnM+dpD5Jr1G5KDfXB/5I9W1230h8AV++Dx+zVE1C+HqJpaVkHZ/Ar6ZQ/cz9zQvCdlHLczNyhDZ0LBEDzqa4Jt0/uevhHON58grH1NxJbRzi/vXafhu+0UossVxbNWploHWbPM7aqIrqQ1Vn22n4LPztN4VeFTPG9pyZDnnrweTnef4knn7xD3RX7NqYMX7oDb+Tt41rQyoqsUZ8fyjlwB+/AoPOzTEImFtLW4ecashsOTF3jUoz4Siplq2Ukr0HMebBNTcHdMa7wJyKEZp0Dv+bCNT8bdUa3wJshktGi+h8V9ABWMLEtqGgp3NhFT3Jj9E9KdTFqR/7RmGxNPjfT3WbPg+qI+2u8zPR1FOppq4W/O7Io0F9O67HrhDkJ+3oHEPAF4qFqDyDH7sEjkHb0KqS6OuDWzK7td91PXELR8H+IL58Lj3lqyJ9maxuZDxU/xvIUWMeH2500EL9mNhAIheNTPMk9Fa5ByEaI1jRxT1pMHA5siKZ9pPVGa7+bj8N53DlHVSiCisWXtLNhtNmzevMOdCe3x1scSpSb9QuZsgeuVBwhvVR0x5UxBj6yJKSjUcx797+sLe+M9t3aGTlgLxwfP8bhbXcR/bqopzf4iBp8MXYo0++y4Oa+H5rpsYxNRoO/PeJ8FuL6oL5DVtK7aPX2JfKNWItXFAbdmmqRQlOZw/xnyTPwVb3O44s4ki2PjeDccoZPX4Y23O+5ONHEOKM3l0l3knG+932h+JPhHyPxtcL10D+EtqyGmgsW5IT+V7W/sGfxUF/GfaetqZXuV3nso0GMebJNScGdsG7z1NzkUet9l9sjX+GTIL0izy4ab83uyu8qa/AaFus81vbsFPfE+ezZ2zPnKA+SaswXJIb64P8KyV2V7FYv8A817AdkrVc3rwHn4bzyG16UK4GlHU+CTNMc7YQidsgFv/Dxxd1xbTR+fLSfhs+dPvKr8OZ43sziSXgcvwH/DUatzkc4BK/fD8+RVvKj7NV7WNgV8SfPddBze+63nNDkWMncrXP+6j/Afv0FM+WKsT8i8bXC9fA/hLaoipqJ23c7ffyGyxSTQmsiUXJaAnXSvlKwrZLBPBixC9uh43B/SHMmhpn2atOwR0fhk2DKkOdjh5lwL5Bnv39N1NktaOm5N7YRUD0t95X+7t5Jxc09eB6e74VZ7T5Z3qSjcxUSEc2NOd6Q7WpyDgt3nwCb5LQjZ0Vs/T3YPzD7IZmuyhczNJi4RBfv8TP91bbHlWyb/tgt/iXwjrb9n5+uPkGvmZiQHe+P+yFaauaKsp/z67HHyKgJX7kdcsVA86aEN3HseuoiA9UcQ+0V+hHW2BMS9d56G7/ZTiC5fDM9+NAXvlKbMyagqxRHRtDL7e/DCnXA7f9tqTyY/CFy+Dx6nrO2VPGNXw+Ex2ZPrIaGYichLacI9/v17FOoyC1lT03B7cke889IGE/MN+QV2ka/xYGATJOUzBWD13hmdR51mIEv6e808yv78FUVjpDna4eYc1bzTXOE/7x/EMWzWzOIfKFc4cuRIjBplSjYojTi7X3zxBU08FCtm+ubVGdl/HdlMvF8lFf5PzsjyEXL17b05fx0vvu9OoUQBKgKHxO1H8arLWNh99Rl8N2sJklJOXkRkY+tMxKt+05D46x5NBEoZS5YNYdnFsT/BpZ12kYoeOBMJq3fCrW8r+j+lvfihN96c/gtePw+Hk5nIRTn2etJSxM1ZC+d29eE51uSYv09NQ1iIPAIe2XIwUg7/Cc/p/eHc1JQtkGUplXFYpvTXyXCoWJJGwH9fuJIaXDYh/gg8YyHDUPpYImcrkC2fKcPJIpSCbDk5HhZKsqtvEHBmLWxDTBvk6ynLETdrNZxb1YHnRIvhQo6xSGj2bAh+aMmWv2w/Esl7TsJjQk+4tK6jmeEkI04igTZ+Xgi8uIkdY5FpVQZZOZi45TBe/TQedmU/h+/G6Zn4Ykw/ZRHTzo3gMaKzpr8smxI9bC4Slm3VZM6VjqLsKjnGZ87VA8WM/hnxizbBRXUNssj3qz5Tkbh+r1U2ht6LkoH7qSnch3RgQ7AM8tS+cG5eS3OPkU0HIOX4eXjOHgTnhpaNNuL77nh7/jpyLBkFx1rlNX2U6K/vtjmwK1WEHQsv0xxpT57Dd8dcEDkodXuSqzqVJAo4u45KYNDvQZ0NuLmDQg+VlvYqFuGE9VuQ+cn0S/4AHWTvgxCYPc1neqZqFAH5N4lOk2+N3sOj/chiNuD1snSyDFXS3t8R1W4EspcoBL+dJodOaQkb9yO612TYVywJn18ns7/HLdqE16N/hmO9Ksgxf6imT/zK7YgZPBsONcrCe+kYdix6yGwkrNgO114t4D5A6wywNa1NXXiOtziGet8nywb0aw23PpZAU3iJxkh7/hK+e38GkX9Rtxd1euDNuWuauWeUPXxWrhVS74fBR5XV4udQ6vt0hnLA4+d4Xr41srg6IfiWBR0jy+CQ60s+dg4vmw1EtkKh8FfJ1by9+QARVdojaw4PBF35LUPvxmhKvuo5CYmbDtBMOsmoq1tk4/5IOXkBXnMHw0lV0kGySCSb5DVnEJwaaI1m2bdJUFAEDeW3fxGyF83HhqGZMbJXpaUjQJUxIz+QISXeXr+PiGodNOgh+t3sP4AiHU1rc+CV3xhJFvl34o5jeNV5DOy+/BS+v5kCV6SlxcQhvLApcB38+ACyZLNAXmNnrkbs1OVwblEbnlP6sD6y/YP8gK3Z3ZvBfbAl2CBDGZA+UZ3HImnHUbiP6QbX9qZMM2mxM1YhdtoKq/HJMWYTLBgGp7oW5ySqx0QkbT4I92Ed4dpV+z4Z4ujkSmRTkTq9bDUUyQdPw5NbtwlM+Gl+k7NEkWjmIDH59/NKbfHu9iP4bJgG+3KWwCR7Nv45EHhBW9YUVvB7vI9NsEI8Je0+gagOozQIusxmZCObDUTKsXPwnDUQzo0sQVq99T28RCOkPY+iiCaCbFIa+8683BF01VKKopddJOsIWU9scwUg4I817FxvLtzAi+9+EtpIbD3lsqsMUVimGHy3mJxwNickmf24X37D6xHz4VinEnL8PFzTx7LWtoT7AJPsEmnKmkkCKJ/NHqHJyMrsCIaSEmT8lT2eXxeeFvsB6VEx8Dv8C7KbyVWVa3hatD7SX722Oibax0mf9KRkPM1r3gfv7mYs+AxpmTWrKYvLJWI0D+Qf9I/MZGS3bduGevXqwcZGhU5JS6P3SgidSJa1atWq/0KLM/J+/xNMd0bO+yF/o8dsypiBi32C4MMWOIceTTgTHy9dDM0TrqNu3boUL65X7ykjnOJrTdX3zcvIKMeUWkHv6f3h+qOp7khprFZmQFso2nDkmJ5UzNManUEcet8V4+Fsdh5khFbKOHz9I61JWraGRl8JTCj3/b2a66LkB4QS//175LyxA7beJuZNPT05Tf2jSkJCJjVAzieradNj/pPVU+hpaIoY+TIzZ2NmrUb0+MVwaVYLPrMHabqyupeSRRC4xxTxJc1CtmJNpiVjrWS6dYPaw0MVDCHnExFtyWqRZDWt9DzdJyB+/V54DusEDxVMmDFzju4Gd86IYjrNqybAqUY5do8inULloEjGgRwTMWmSv8vkYcgxGUmFEXtlZt7xh/it7H3okb6JBO/1vg1yjDFZcrrJerXyiqyXovGs3K+I4VI5FjN7DaLHLYJL05rwmWOBKomkldiaNmA64pZvo/NXYTsnx/TYkRXZoBwTesKtgyWTLNKDVMZhhFMcmZoeiyurGTy6HHZFTNlInsk33dUE06pZsybSrt4V6orqyVWp9xs1cQkjzLHPDl6rmWklm/W3MzoXlTphEfO8SLaEnDei7XAk7jyGHJN6w40LxsrI5nj5OuX69GreWT2eSsaF9BPJ+SjfTdEe8/A+KUXDHEv6yOaoph6SY2Jl+ztHfCbTl9VbG1l9s4B1nOmGzhoEV1UAUKTDrjy3MEV3/NcpcDKX7ZBjItZoOkeJRA0hd0tPR86rW2HrZ0GyvOg8Bgm/HYTX2J/g3rkxmzoyxnHyA9l6LmN6Jn0ULguiJawOKokkkDJbI8sI5yb3gVtbC9KLSQU52CH0ySHNZyHSfSU/kPFP6D1DJvVVNB+Cjyxj4+ixNcu+WT3ZMBnJlx5r74tu40CcZjUBG7lAhVTqZfWSKLF8ssaRla21eprrTIZt9UQ4fVuWPQO9+mXZvvywQG2kv4rVSDiRE2rUGiKOMYc1I0oVGV0T/y9/lxl/Kj4+nsKC1Y1AgAsUKEAJmohMDiF7WrduHX74wRQQu337Nj3Okz0RtmIfHxPR7eLFi9G/f39ERkZSODM5F9m/rl69yoYiWePo6GgN2ROBLP/LWvwRZwsrMBdIESgEDg7liiNgi6VmgUk1hPgjJxdJZFIJ35ZF07DTzJFlRlqTGvCZO0RzRzJD7dWYhXg9dy3cOjVEjnFaGNqmig0x/Y+DuGn7jmZVCEsYaWr21jnR9yhbWXJyMr777juMsQ0B9vwOYsAtiLqLJUuWgGTL7ZLfobyNK+bv2Qq/yl9pru1O6caodn4HYh1t8To+nh27mr8Ghj6+gGO2SXBwcqLU3cOHm6J7D3JWQ1xCAiaV9cOeo4fh4OCAauXKY/TxCHqcJ3Agke6reatjROJ9HMueQn9PzjegbhM8rdyW1qR4/rGKUnzv2rWLHu/6Y2u0WPEHhUKHPjNp4pIm09kjx5hwd6FQBB9fye6FZ1lWPwARwyl9zp1GI2HLIasNnRwTse5mZgrHrtyOqH7T4FSzHPxWWur+yDlkRhYzZOpVga+5plUZU+ZoiggXlD6izV5mMDDSn5bfwWeGpV6bnEu2mcmMKNJHZsiKmK2V62Wb3KXNyGbOrpJjjDhryWhKNKY0PXIfGUmFjAQmM+/2Q/5Wz4ATkZaQsUVkKeTvFifdHqGPD2ouU/ZN6ZEdyeYEc7zKfIpALosrW+8YU2vDb+C7QJtBsMwJrWEtc1bJjTHDa/5QuDSy6IDr6SvKCOFExFlGc/JB7up4n5CE4DO/IkuIH3Nk3526jOcN+9BMRPAJy/okk9ih68Ha3XjZaxIcq5SBv4p7QE/DVRbYMpqbr8YvxutZq+HW/gfkmGiBUdJv9svmeHfvCQK2zYHD15bSGUbuNaQDPHpbst8aQi5Oz1Nm5KZGRuNx4ToUKh9KDFMV7F/EmEuuSyRTp3w3xQYvRfrLGASpAg2kD5P/Eqyl9wMrUxRHCLfOMKbh/m3gqUINaAhsVMY0XRvbDEPiruNWTr7ompV3IyMC1COtZM9mxzw4qOpd2b7XoQG1CZSmFzCQBddZQkBAniVzdPQUE2R7gIggK7OOrIjhnq6NN+7jaYXWyJrDHblvavlCLDq9k+H0jcVG0mOI52WflOcrI2JLfRaJx5/+AAi00nn9aeVcMoI8clxG8qW3BsvYrxWbJrrCp/hs3UyNIyv7XtlzHt4ZHj2aa5YXWWBAFhDTCzw/LtkEqY/CEbBrPhxKW6DzMhZkIzJAo3Xw7zqeGUdWdI1qaDE5TuR3iBNK5HcIh1H37iaYNalnJU2R3wkICMCUKVMQERGBli1bUpkdXn6nW7duaNu2LQiJVI8ePazkdwjp1L+O7EecOWpx+Fz398JGRSxgYQauAL8V49hV6C3aaoe10dUDzJFVnBPHGmXhv8pEtKQ0kYYqORYzdy2ixyyES+Nv4TNPC8Pb+WV93L52HY7t6mLIikXMkVX0IPeUC8XU80dx6NAhGk0hlNjut8IwPtETPguGIeKzUPp3oh91s1IrDDy9F56VSmPFXu0C3tErL67FR+GGfTpex8Wxa27gHYrI2Bhs2LEd8aF+FKZA6L1bNGpM5Wz6x99BYtmi2LB5M8LDwyk+f2CKB+rZ+yKXimqfnJCw/DYuVAJRWdKw42e44x8AACAASURBVPk9Gu0h5xvVpz8qjN9IWf1GVwnCixcvqHgzOV6lQkX0THBGg5CCTD+SnEtvYxFJFlHDZf46vBq1gMJYeUM5dukWRA2aCada2jmgl52IGjYHsYs2wb1Hc3gN10KDMzKV9XRAZdcat24PXvaYSEmvAjg4s8yYZJujIPPLGKFV7M8yg4FFi7+vBD8VJJTcK2ORXjwSLvWqsttXgjcio1jmNDC2RQ5RoLfJPRcwo5KLkElskGMyiZ3kU5fwrG4PShoRooKEZeSdfozf6BlwMrkvlkXl9DNJMOnRJyYYFg0MqWGTy7YiauAMq2+AEGM9KdVEqK/IpHm6NUGOUZa6ThZMKpwHwcdWaNfBftMQt3I7PLj3q2ekM2TEnMFwbWohOWMGt0Bf0WKUToLTN5Y6ej0JExKcE2XvZHJfIrZc5WbV78amaD7myL7Z+ztetBsB+1JFEbjbxFugNJkOuUhzmfTRZH5v74KNp5vl2xu9AK/nrYObQDZJb57q7UcyduKo4XMRu3Aj3Ls3h5eqTELPWWIM9lygQS+7ybKO66bCSUWMKMpuKt/NZ+PXUbK3gJ3z4VDGYgDrOfqKPFLw76s0JGIyhImeFJSIqZ88f1EWWXkvMoZ4xo4sYKkWIQOofaEgfzgEhJ7cjEzuJeXyLYRX6wAbARO2SDaFjK/HrC1zHC0a9d/C11yakFlHViZvRFj/CTuviJU6vG4PEFJOEiR2VpF1yhAR5P5ECgnk7zJpLBmLM+nDgnwck/Wbmw/wtHwrofPNsucc6smyBudFsIqIj+7XkvtU1hlSA15s2wKNIysLYjFt914t4cUR+8nmJPsmOJ1xvcCzDHGgpw2up+7xMfbqD3HOD+3IpqSkoG/fvjQrS0ifiO4rSXwR3Vi2Vz1+TB3eY8eOUZIn4pBOmjQJhGFfaeQYYTm+ceMGgoKCaEKrdWst39C8efP+dWQ/xCTQO4csyjq+XnPs2r0b2zsPZFA3Iu47ctgw7H7th+upiZhS2JG+QIJFJ87XmJDPkXXZTrh1aYwGJzYzR3Zhj4GYs2A+DtZozTIRRNOJwI5rnH5Ms3tXm5XHhNMHcefOHcr0Nfybuii55gQcvy0LfzPLsHIfSsTy3ogf0Xh4f+bIKhDT5nbhaNCrK/r1M7EeEuaycmW+xAWPUsi1broGYnS7bjcM2LcJr0J98fsNC0Tg/PnzaP5lRQx2zIVeCMPr2Fh6LlJ07uHsgg2uRVF17RwKOSaCySRbenjDb7hV5HsUf3UGp/48g5KlStEaWSKifHPDDvzqXBjBZ9Yiex4L02/0qQvwK1sSv31SCd/dPkzHoOfbvgPLbgPJ79NQIv4CFWomBeykje/SE9t/WYHNZeog5KSFWVJPPkXmcMkkYsg4ssySTAaB9JFFfDM6jxWRbz4zQzc0c1bEtV19eE+yEI4waaXiBRG0X8tSGtF6GBJ3H0cOlf4aOZdM/oEcY1IbKjiazGCI37QfkV3H0XrogE3amnGZ4WUxSKrDd76FzZiMzbQnz65HttwWoh6ZLIXeJscMzFFd4d6tKXsFeoaXTGYkcd/viGg5GHaCZ5zRd/shf6dnwDGZkk0z4FjRRNJGmkzXl4e8KpqOpI/M4E179RqPCpjq4niUhQy2rmdcyDLuesYiywZwMHQ9CRMWweccGFkGQQ9SKs34R0ThMamnJlISXCZOLcWWrVxx5sgmbzxgyq5WLQP/dVpmd5l+px4agjnf5zcgm4pFVq9kRW9+imSLlN/LHH0mzdG6DrynWhh4ZbA/cj5ZplJPNkhmgIskTZTv5vNZ2/Du2j34cc6vHhLqcfGGICzegfsWwr6EpeZeJP9F7kVP//ppzS607lpdtkP66OnisuwqN3f1JJoehFTF++Q3VhBqVgJTuwL8llsC9XoBKtn71CszUOCqniO7wOMnC1mNntxMeJ3uSPnjMnw5JI1I6iWzjqwMBs7KiARBtufNByLpwB/wnjEAriolAT3bQdF2D9g6Gw5lLbXBTOqsQTX4/jyCfXJ0rvhWoP9Wl1iRf8sy/nqau7Igrp7koiwgpNxnfNHcKLx/qcaRlQWxGNJQpb3N1ougKrS8J+TiJmQzq0fQb18pRZjYiyI/lKYXeJZpHusFTZksD/cdf8j9+UOf6791ZD/09WT2fP9fZGTfvycOUmYfzX/+e0KirNR4y+rrbg6Ygk+nDsK57qPw6RzTgkMEgsuULImm8w7hZmoCXNZPxleVK1FMeMOGDRESnYLRL+zgObgD6u1YxhzZRYNGYva06dj/1Q8MNqY4stX3XcfF/YfR/O0dbNm5g2YvSXq/VvVvsTl7fhT6uoyVcPOjwnWQFhmN+5M7oVGfn5gjqyySn8edw5bdu6hzTRpZ7ImA8U73z1D14BqqqUWYywhcl+DpHZAVy7r2R5P5Jpr21NRUlPriC/R/lI709+/RLUsYG+PSpUtUO+qW19fwnz2Y1uoQdrRGjRrhxemL2PdlfdR5fZmOSSI35P8JFGHG2PG46FGa1nbal7QQ8vyxcBW+7tIKD8q3Qu7jpiyNcr7z9p/iekqs5nzk+I6RU9By7BDc+K4LAreb2CfpfT55jiclGtEsLtFZVRfyM+eTM6r0HBSZPqKsBpBcg2zTy+hslcE/TRvaDMQt32pVE8jqjUKDEPKnVvJHttAz8XMOOk/GEWnMygwGVkP5eUEEcVIf7DzcO49bvQMv+0y1CtLoOlQzViF64hK4NK8Fn1mW2mGm2+vkgNBHBzSPWfa8lGABkTNQB0JIZ5FeHfm7nsOe0Xf7IX+nZ8CF1+6GlD+vWGmvMsNL4CwpkFcyfxRZHnK9MsOeSNY8CDCx/ua6s1sjWRPRfiQStx+B1/iecO9oqUN9e+cRwr5uiazuLsh9VytL8axxPyQf+RPeXHY16fh5PG/Q2wpyS8Zl2fPtc+GgkneR1duSPiyrdnIVshewMLvLvnUi4fKooIlvgDqlKgINWRaX3aeHK3Lf0co4KU6Xz+KRsK9dgTmyiUu34NXweXCuXxW+nJyRzCjWKw+Q6XqygMG4HnDv1DDDU1K2Xuh9s6zk4Ydq8F1oMdplsD9yMTIEiZ6zJDPaRRlr5bsp8csBKv/DO0uyNYNcm6yOWoRgUR4sy6ZzgTnZufRg/rJMVvLpv/Ds+5/od6te//XeDas35QKQzJHmdO3J/TA+Dw69lLj/FCJaDBIG+WTPU9lDRdryz5sNQNLB0/DmaoFFGeHMOrLRU5cjZsoyuHLaqyJNauUdijShyTE9NJIMcivTXSXnk63BTCd4TDe4d7EQc+mVELBgAJdFfnvrIcLK/Yisnm7IfXuX5vuXwXQVbo7EfIEoeHy1xpGVBbFkwWo9FKQsAKqXoJCVL+kFQGVImgwvhn/DD/91ZP+Gh06GzMyDT0wEnC0EoR/9ihMSACcn0zCyGhICZWw4ZwLKV62MMXs2U0grKZK+e/cuUr9uQ/Uk1RElwhTW58e2OGhXmGa/6qyczRzZJWMmYuaY8dhTsBoT8lYc2aobzmDQsR1wr14W87ZZ2PsaV/sWAX/cRO/iFayM7QfBVej4D+f1QoNO7ZiTqdRQfvLqFP48e5ZlMMl9Oma1xXLXQqh3YZcmI3qp83AsW7USTTu1x1czTcbGxIkTceevqxh2OAxn0uLRLf0RG+PkyZP4tnJVXHEvxUgBSMb3yy+/RPzJC9heoyXaxd9EYto7ei6y0cyePRuDBgzAba+v4bdWW2eyf9xM1B/eD3fr/cRqkZXz3fukJs48e4T2b+8jISmRzYujw6eg2riBeNpqqAb2rYFyPTrAmOpIR1ldZvKfV/CsdjfY5gpEznPrNXNPyejx0WTm1JQvgYDftGyBini47/JxcK5tirBmpukRtchqc1l9j5cbct/Sbk6yrCiL4nOkE+RaRUQsMoNBDwonI3SREZpoIK7hRxirLjUafvkNBK7k9F1F+C0byx6p3ib3atwivJ69hpL6qOvA9IyWiNZDkbj7BHJM7Qu31hZ5LZbB5jIYmXm3H/K3egacnBRmI14NnwtnzrEg1yWDwslqrajhpWR7uKyfjAyNZeJsbExZXBVjpJKh8ls5Hk41LazUetlzGdGHLHuoV5spM3Df3n+CsDLNqa5rbpV2M7l/GfpCRgJD+rD5NaUPHFvUZo5s/MzViJm6HK5coI30UUj3/LjMswxuT/e10k1p2QYPnWVzY/YguDbTMobrzU8Z6ZeeMS2r6dfLzLPSDA6OzFAnJQohaJ9FZ5i+hy5jkLD5ILw4GKUIJqx8N1+s/51qb3vPHAjXFhbJHD1EjWyOypwW+l0VqUtZmIOOLIOdioWZQcy5rJBe4ETmNLy5etfEJ8E5n5p38/QwDfAqLXHPCUS0GkrZ3IP2WvTF2XouCIoyDhCuREovKCpDR8TMXIXoCdaBSfo+O4yk0GM+ECYirMysIysrz5E59uR6FEJIQiinJkZk96BXnvPzcLioGLtl85vOlWL1KXM6T3IlC9TolRCwfZ8j+UoNf4HHnzUAsmdDnvAjmk+eJXVOrISdijVYyVYnB3kj/9kNzJHVC5So+WLUiEK9WncWmONLUk5ewPP6vZCNK4mh7+an8SDvzpOrxdUjFmR8CEvHUELJ5NOXP+TW/FHOlZSYhO/rfI8d23fA0clazjR7vpxM+/ijXMB/edL/LzKyf6cjK6uZIovp+g0bsNA5ETefhVFnjDirR48eBcmI3n8ejlmfuuPC7RtISEhAeno6bN+m4oJbSVpLUXv2WObILp02E9MHDceugDKMEU9xZCsvOohWF/biTJYk2DlYtClT375DnfeuGJ+3DHN+yVxS1wQ+Wj4YP7RoxpxMJQr1+euz2LpvD6pUMenTvUtOQXZHB5qRrXHvqEZoPnriLzg+eR76ZHmKhzFRuHfvHu13Zt1vSKrTG+cc09A59oYmI1uieAnc9PoKOXr/SOsfSC0uyUg/Xbsdh5v3RN3Xl/FWlZEljvGMcRPos/Hhap9OjJyGimP640mrIQhaYRKTV873V8FauHzzOurG/oW3b98ybP6Wjv3Q5pdZuNtrgoZgiBiqpEZXBFthm+PY7nDvbNGp1MsOyBwCPUIOGVFFRtcBjTP+5BCyOlj07GRZK0YUIXAQGIxm70KaiVearCZIxrgoMxhYnQ7nROuRKsjqdFhGXcC2Gr9xHyK7jbeCMMvqPsl9xsxZi+ix1nXmepAw2caoxyad0Xf7IX+nZ8DJMgiWbEA9eKtkQsh1yTJEesRmCjKEN9KZ48U5pRrGSC7QJMs6yjLumvn112+wDTAxK5LGaga//hyB20za0aTp1SzKUBYpF28I2YTJ+RROAveeLeA1rBMbR4/IRp1xdP6pKXNkY0f/bKqt5xw4clJZ3ajeuxGVB5BzhdfqStlWMxtoY1m/PMEIOfMru1e9b1aWFZGxwZOTypAzeogIWd2jyIlSvptSOy8gaftReHGZaXWgwa2NVr9c9h6elG1JJWZ4GCm5HxkTK6vT4+ptZfXVeqRfMjjwu6cv8ORzsdPCUCmcc6C3t8kcVpmDS9fg6Sspq75Li9rwmTmQzRsWZOzYEDlU0lnkB4w1nyMJE7HqZtaRlQW5GB+GIFDJCBO7N4PXiC6Wexi7EK/nrIWb4B5kmUIZ4oDOFWUecaRpsuwq6SMLJspg6GlxCXiUxySlGMoFN2Skicoa+NbLFXmvbmOOrB63AiPK5NZgFhgUKFjI5opSEmNXsgiCVGoNdA0ePIsGud25WlwZGoT0YRn/mQOR/ZOcFNL8T2/vCXldQgKcnJ1hojbVNttgP01A6p92P/9fOLJ/J7SYwYK4yBnJKsQcOY2vkv7CkZMn0KlTJ3Tt2pWycxFnpen5XShc6xtMWb4Y7u7u1Mlt1aARhc/6b5qBmqP6M0d246o1GNimAw55fkEhr1nt7WhRNSmcrjhlC4Y8PIfA5t9j6i+WSDOTyuDo4FlNYJYseLJ+FOrVr8+cTAWG1/TtHTQeMYAWc5P256EjKF+tKi56lUGhiBPIoirWJh/8wUET0DTuKpLfvMHatWsp5NjZ3gHpcQlIzZoFCemp8PT0pGxkRYsWhYerGza6FMFX7ZvT2qdp06Zhx44d2NVpIJ70HI8SMWfxx9k/UaJECZqR7dixI27uPYK1aSFWhsPTiYsQOqQL9jTvjqprTOzQyvnWORdGzNm/UCL2PP44c5qej7TRVepg94lj2DtyisaAJMdkUU0Ze6ImAk6yRKpnI5MOYBmFIF/kvLRZs2bIIH0ZXVg08kY8o+e3nUD05vislR6lvIzBVgbzlBn7MoOBSS9wDNJ62XFZRkavPkwGAZdlFsjzjl2+FVEDCFFRefiZgyTk768XmjOTIpbnIbMpZIx3ThjLp4BFPKPv9kP+Ts+Ak2XqGHxWQMDB4MhLx8D5exNkmG76TfsjSZC5IsdkRB8yp1QvuMFIvg4vhZ1Kq1FWi6s3v2Skb8ywFzCDyjIyeuQoslp5PfZ0NRGW29COzJGN6TsN8ev2wHNoR3j0aqmZKoyFmasdUxtk6qwi6SwjWmP105tnwrGCiXMgI032bb65fg9PK7aBjbcHct3YoTmVrO5QD/bHagg51IAeIkJGhsNgrf1aw3NgO3ptyndT+sgNqu3OZ9lkzirpy/gGOOkWJjl3cAnsPyugeQaiukM9CTsZakCPDEhG0MSCjAIYacqlmwj/piNsA32Q87JFa1iPbFAGIZZBjvXWWuaAkGC4SmOc9GHrFBcgEqFlMuvIygKisqAnuR7Ld64NAOqx78tqg2V1oGQcFgDkZGlktavU3ilUB2kvoxF0bDnsCptkvkx//x5phJWb+7ssIKIhTeSIT5Vgf6qjPULv7WGOrJ5kkSwgohcYlKGuGJll5dII2DBN832RREzMjJVw5WpxZfXcpLNaRorUj5PAJ7HZWb1hRhbE/+PfkBrqyJeR8PH20TC2k8tI2LQfJJjEl5X9H1+i7nD/Xziyf+cDZ5sTp3WnLCpjirvhRZZUnDhxgjLnuri40AWn1qG1qFL3O0zbsIYy8xJm4KtnzuGSZ2kKDanesxNzZO/euYOC+fNjjVtR1L12AHN+XYWhQ4dSXabyQ1fhevJrdLB9ivUbN6J8+fK0RvXciZNIbDQQeW0dNZEzEtF6XLoZ0lwc8WRRP1qbSqixabv5kG5OW+yTMC9rFGMtblynLlzO3MCUwOJUx3XhwoWoX78+ZS6+Mmc52vftBQcvDxyPeETJnEjNb+LhM3jZewqu5XTDwAdncf36dfp7UmvbpEwFRFy8iiVNOwDD2tNa3LFjx+L7+GyUAXiQZzwS8wRQRjSFtXh4icqoeT4cHiqjgm5aw+agw7RxSAjxweZzpxhrMTlftf3XKcnCsPzZEOtqT89HIN6VipdEL/ig/eQxVjqkrP5hwzQ4Vi7NppZUUzQ11aRjS2r9bu6ATQ6Tji1pMti5bpaISDS8S0XOy5thG+j7H01tmS6izHGgxo9gXD2yEZn0FIMecca+zGCQZdlYlphzcMkDkek3s1pfLutD+shYg0XagspDl2UQZDBS0s+iycsZLYpmKTd//6MX/AE66RlwMjjf/2PvOqCjqNbwt0kgEJIQCL3buygKYgH1CVKkiwhKkWJFBVEUsAE+FQW7PAsCKmIFaQpWugiIgAhWlN5rIISa7Dvf3cxkdnZmszOzOzsJ957Die7c+v937tzvr6q2+Ym7UO6+4JQIZr7dqgZPB3C5BDVdgu7iZRZ5mm3MIkaamU0G+eJqIvCGA6XqZalmFdRe/plK7XCgS72k63y9w0WENcvfGU67o02lUW7kgyqQ3XP7sEBQNoOcq2YaKrNgU1ywWU7xcCmDwm1LM8FqONcCM4FVOLM/syjV4fyezcxUjcCE8t5cvnQ9Dr49CRk6LZuZNQFpY/b+mAkL2caIR+H8BMU7cnoL5GVlo+aiD0CTQZZwuVrNtLjhIvGancHh8oya+SmHAw1mvN55/7MBwY0uxzjXahbV3kjIYBXImrmVqIBIF0iR8zGKlszfw5mhm/kGm0WrZn9mUXvN0kuJO4qJC4HiflZL5/bBNkYBFcOZtCsuIf4EH2pt+k7cAVnCCZ7NXLbCBdUys7pQfN31eck5BzNT8XAm3Fp3Gb4jJU6tiYrPFQTPjMLnOepd0OKT93wqwBI0qcc4ELOiZP3vYwlko051iz6ysRg/0j7VA1VnxqKYiP4ztAea3Xs7unTpIgIkiUtC54GY/9XXGJqahU379+DMM89E165dMfShR7AisyF4eDTtcYsKZNnm0Urn4q3da+HLSMP9D/TH5MmTcf/d9+DqxyaIPte9OxhPPvM0fv/9d7FRaXrcb/lenJtYBrVXT0VS5UxRj5e0ydfejK4HVocs8eha+nPdIvy53uveUM0j2/KKRhiybB8yTqmJ2ss+FWbA8+bNw6FDh1AuJRWNshMw6LImqDs3MBcW5YO28oJq6L38a1Xry2db3p2Mu+68C3PyspBSLkPkfX3iiSegmAsl9GiNIVtWqHlfCXRfObcxDrwyEYy42/2Xb9CoUSMMGTJEfAy2ffwFnqrjwzd//armkWV/yociaWB3DFoxW+2vR6XTcdeOxJDAMOJj0KEfDi9Yjkqa1DH8XfUB/OZtlLr4nCDamV1EzMy/zHw5w2mJIt2P4uN0RVcc/3tDSF5GMymrWJ+BBDY36yDWnx5IS6I3IzK7TJnl0zO7MJhpkMMFlTAD0WZgQnw0V/2Fzdf1FnmF66yeqpIzXMCNQ98swvZbH0Fy3bOEcEkpalqQe7sg88l7glhj9mE0C7hhha/RrBvuAmd2sTcDN5yXWYRn1eRYFwFZvGsdH8DhectC3AXM0sWwjVHEyHCBo9jG6OJVcIkK1QSa+bWqwhAjQcniVdjaui9KnFIDtZYWBEwLlzrNzERdBas6c0qupcBK4GpkjnlSBbK7ujwcoKUu9QTbmJk2mgnnwvFTPet+nIiSpxdEjy9sb+buzcL6swK+pNoUTWbvGOupbhu64F5mWle2UTWCulzDZv7ugqaK/7wuBZiReafy3lyxZicOvPQ+0nu2Q8XnA5ZLLGYm9nxmpIELZ0HDNkaBi8KBBvGOXHQjTmzZieqab1U4Fxgzd5ACy4TQdFdmkaPNUjpxXoq/ul6La5aWR/BzyvdggLFSl9dF9emvq3Q2szJgBTOhhZFZvFUgaxbN1izYm9hf707F7oEvhFj2hDNDNwuSF05QomprdcIsM8E252bkQmAm/FOIb+S3rZqnGwRN1N5raqydieSyaaIrM3cDPjNzOTJ7v9nG7PsfLjq7Gjiy2ZWo+kEgWCmLasJtYOGi8CatRxvkfPWDiJ+htUIq7CyMx3MJZONB9SIEZAty3QX7P6j+X7qE6SSn6puk8a/RSkX1OWnZxshnIZyUlW2MtBfhwoqbpSIJd9kwS6qtmgvpwsSLA8cEIBildlA+NFdtOoT9w94ICTSjaoJ0QTc4jtnHxcyvmW3MIqaa+ZKIi0P9m3Fi/dagpNrCBIeaWr8ftddMQ1Kl8uqbFKTp1AgZtD5JAjhqgtlYeQ3VgFHvPi3SG7GYaV2Vfo20tWZaFKWN6hPz86coUatq2I9TuAuDGnRHEyQiXBAtMxAdziTTLJpnuLyPZtE81Y/c4NtRbkD3INaYfRidRqO2wv9I6objh5mJlllaC45nlhvZLCeteNd6PoZDX8xDBY3JazhfPrYxihgZLpUP2xi5C6ig9PRaqPXjxCCSmQGFcAGDzAQvqslh5xao9NqQoHHMfLfM8uiyseo7dlU9VPp0lApkd9zQF0dX/I4qH4xAmWYF+W3ZRrUg0AWCMoourkzQyKzWDPBEst/MhA1m+bnZp1lwr3AaPDOz8HBmnGZWGaqgReM2pH6PNhzE/qfeCskfbpZih+tR3Qs0PpGFaVfV2Ayau0K4yMTirpDvK1n185eR0ijgTmNmCqzwbt1pLYQrUE2NgCKcCbeZ0DWcEEbV4pZNxSlrZ6nbJlzeZrPUQFQG5Hy/2FAYbSacVFNXffoCUq5tIMa3CmTNvkuq1YPBN8FMU2jmrsR5qd8lXZR9I94qhDQDX6p2VfOdVtpoo6ArudrDBU0U++vyW3F87UZU00R7Dxc0UXtuVF/xGUrVCOQaNQsAJ/hi4p9t9n1lG7Pvdbjz1CxwpFkaL8Gb/EBjpa6qJxQGzKertcRjHlQqrRTNM9swkwYDmmrL4cOHhavd7t27VUUPLQaZV5WKIga8Pe200zBs2DC0aROIfG9Utm7dij59+og2mZmZIhcrU1Yqhc979+4tnleoUCHkudTIRvIFs1nHStRim0NEpZmZmaF6eOhyXXFQNbjEw71QfmBPMY9wETn53CiyoZnUSlmY0UXF7MVlmyA/h7UzkZgvOTPzC2EbM6m5Wc5StjGLymnk/6F8aBofTMDeB55HaZ2fQ7gov3tHjce+58YhvXsbVHxhoMrvDZd2wokN20JS+QTx5sEewv+JJS/nCNbVbir++5R1XyMhNTjqm2oiqblEBmkgdBF02Y8akVeTxsMseqTVjWoE7sP5wYr9ZeA/a6bFVOZjFKzHzBc13IXBSEgTLuANxzcKLBEut62ZRsgsLyDHMDMlDeenZPZ+qSaC7wxHatsCH1KrvI1W/XD8MHvfjS6CynzMfI2MLshKGyOBQLgotmynjRipSMHDpVBim42NuuP4H+tQdfJLSGkc8OsM5xttBrpUX6trG6Dapy8EscJMqBjON9rM1NLMFJgDaoFalW/fVoHstkY9cPyfTUGXS2WCZibMZlGb2c5o3uGCXUWyL42EgYq2KkUXyVacu4cOY12d6wPnria4VzizP9UctlZV1P65IIq/asapy0catBd0wWDUM1Fj+q68N4325GLfIy9BP2+z9Ewcx8jSIUgIo0vPxDZqShENQApnkhl0lmuiVOeEidzKNkZRx1Uz4esaourHwbmJBThh3lIKan+dgqQqFQSfwuXRNXtHZzuFsgAAIABJREFUwgUdMwMnRueAsgfN0oQZmdhaBbJm32izSMlif81agO3dh4REeDaLJs42Zppts+jwbKO+F/ffiszH7xLkKMxaRU0B9uJApHcLgKVw+WXF/mp6O46u/ANVJo5AmesDQjNVMHhmbdT64YOQ4+Df01vAn5WNqvPfRco5p4nnquuOQfYGbVApJS6MoMvoj4T7WWqn0BzyijWY3t/eLC2POE+/X4JtnR9CyfPPQM0549R5hxMyKK4fSXWqoUSd6qhG/1hNIZBl3JuXXw7OSKEnysCBA7F8+XL8/PPPKpD9999/8fnnnwtXw2rVqom4MvxvZuI499xzDY/Zq6++WgDe1157DatXr0azZs0wbdo08HcW/j311FOFO+KuXbvQokWLoOdmQHb06NEYOXKkMEmuW7eu6L9Bg4AAyO0ifWRjTHE18Eu7/4icciyFSVm1Efcy/3ufaHPs93+x+erbkGCQAoXPjVJSmB3yypJVsxFNyhqzsOZKGyPpXThzIW3wKJESIz9PogrWNYBQGcPMzMnIrFf50FyTWBa7ez4ekmsuXJRfM82Skm+t5uKJQamEOL8CH8cCk7Fw/nSCNwY5LBXzRF9qCk5d93XILjSKRlnYZSPSrWx0aStMe6+uQZNWI1xEX87FiPZmQW/CXRhUQYDmwxguJQPHNjKFViMDd2mJSq8ODiKXmbmUkRWA0tDsgx4uoIvZh1EFgTrf60h5Gu164fhhpnlUtU1fv4VS9YI/qkYBW8wsD5S1GJloh4tiy3ZGAYpUbUC1SqjzS0HgGWUc1aRw3FNIbX2N+Dlc5Gk+NzJHVgGhQZAvM2FXuBQ3ZoIis6BAnJfiv8vLWrnnB4hLEIPYUciXt/8gahhYAKmApOnlqPrh8+pWUoVBBsJWoyjbhZ0hhe1Rozym+16biL3D30Rqp+aoPPrR4HeWYIlWLbm5QWBJdecxMPs79uc6bLqqOxJ0OXhVM+FRD6Fsj7ZB45jlhTbSfinvzdVHkrHn3qdRWncJ/4exBo4dR60Vk1CiRnCMAzWydetrUPmNQKRTnjGbLr8VPgbC2fBtCAmNQLv63deZsSuNjS7h4awJxFl+ZVcc/2tDUOTkcN99tll3anMwiJT2O6pqvg2++2YBpwrSwzyM9G6tg2hg9o4o6WGqfjwKKdcVxLJgY7OAU0aCV6tA1kxoZpahgPNR9lfJc05FzfnvqeszErApD818jQto/iFKnlYziFZGQaXCRQZmY9UlRJN6ysw9SN1fivvVW08irUMT8XNh+2v9RTcid8tOVJ75P6TWv0C0MQumyGdayxytRZvi/0wXs4ojgv1SzSzaVDP0Z/qJVHraYuYHriqODCxcFEEv85ln3NMZ5R4ItsqKBMjy3Ga9F154QcSp2b9/v+nxWa9ePeF+x0Cx+vLPP/8I10RqXStXDpw3ffv2FZlQ3nvvPSjPN2/eLKzy6CN73333qc8FHwx8ZD/55BN0795dxMO57LLLBCj/7LPP8Oeff4pYN24XCWRjTHHlQsQcVeldA4ewP+cI9j47RkQxO5VSVp1ztfLxNppaCQP/K3Hg3DkM2Z9/h3KDeiO9e+BDfHjuUuy8579I1gUYUQ+cfB+0UldejBK1q4mfj/3xL44u/93w4sDnRibRZtE1xVqPn8C/1fKDHWmCqdCvhf4tmU/di4y7bg5aqpoLDBCmwkqhtiFv3wFU1Vz2lQ/NfzJrYmf7fsLHkaaIStk1IP8Cp4uux+cKGCp53uko/0jgEPDn+bHjtsCFqc5fXyKxXHrQ3JTLhvhRMe1lWGwgxL9SaWiUh/DIsjXY0uIuJOk0A0obI18XJXF4qQYXoPqX/7O9c40ks4Vp75X9VfauTkjN/zhRyrp32BsoVf98ob3WF2UNlfPzqfF51tjJ2PP469AHVgh3YVCAYbmBPVWTL2rM9r/+EcrccHVQrl9lDhsb3iI0UPRlTr7oLPFz1v8+EdH3yppEBlY0QsxFrGoQnn4bh2cvCYmGzf602kHmmUNCIHD9gXFTcGLTdlTRBSniM7MPo2oFoEtjZJvJDhuG44ciXeferfz2k+pIWzsOgD87J+jiqjxUgrLQYqLK2OHiZ2rwNlwQSEFyii4VFH9TrFlS21+nWj/Q/JB+yUZRbNlGjRg5vC8y7u4s+jYDIsrcFPDLc4D+eSwEzNTSGuXE5XMjc2Sz1C6sLzRUNa4TIIZ7MjEzQ4xDf70jC5eH5LQUc9iwFRsvvRk+XWR5Mz990WbdFmxsEFi3UTECUIqJKH29K+UDKP+JXGxu3EN0UefvmUjMCPitKUWrdVC02DQ9pcWBHiSaTkb3wEh4F+5iyuaKe0yZVleL2A0s3J8nNm5DBV30Xz4zSyWm0lRz+VamZ2Z2a+Rrqhesljj7FFR6ZVCgq9w80EJI0NTg26LcFYzoZbbfFcEq156Qv6f8h4+I3LIlDXJ4s28j317V7eLqS1Ft0kshU1Au7hVffBil86NRUxCc9cYnIalvlMaKdjDtlhtEDlqWnG8X4diaf6DPnc5nWnDCIE0JKYF0gdxr4ix/+0ko5q3KGCpwTCmNWj8WaPpo4UKrKn2eY7ZTI95eeCZqfj9WXasiwGZ01hKn1hC/WwWyquUc73Y75qnuP+ECp6lBy3R3gXBuF0a+oOGCL3ItRsLEcJGB2cYo9VSB+XQ11P7pk5C9ou6vZ/urggfetXb1GxGS3k5pvLFxDxz//V9U+mQU0vKDaIZzu2C7AoVDAWhXXFjKDeiB8oMDFnNKCRKUaL43ZnnJ2U4VfJVNDRIybGl7P06s3xISZ0Tsr68WYnu3waCSglGQeV/TFgJUZuFgqVq1qgCgNBdWgiwxGCs1mwSH9F1t166dKZClqXHt2rWxYMECXHppaJT4KVOmCGBKoKqUMWPGiPg2K1asgPJ848aNarCnsWPHqs/F+2cAZAle69evj9dfD/ilc541a9YUYw0alH/eheyM2P0ggWzsaCt6Vuz8jYZJqJCBU36fEfKIprVbO/QXprz6og8DrjxXfJaMxil9Tf0Q8wbWU0z3jNpkGIStZz3F/yGlSUMkVgx8nPih56XPrI1y4BiNU/G1IUjvHMg7phSCX5rW8lJsVLTRFpUPTdMzzse2q28z5abWvEmppPgDGzZiztSts0OEDNTubGl1D/xHQnmTetP1qPy/0JxhSj5IxdREvPj7DoB9ldR9TJW5KBJc9qlotwh+syd/ixRd4AGrW1gJbsD9VyLfH4VmevTn0AejUffXIy/hwLjPDYdK0Wly1DXk+ykZNdKbc4e7MCh+yUb98JKkXhQ1FRQtrlEbfWRrpY4SpMJwn2o00eo+pZ9zraYCnBgVgnuCfG1RPowokRScd3fZGhGNuqYu76NV3karfjh+KFoQs7Fq/zYdSRULonOzniKEMWxjkK6G9RRrFqM2vGgapQNQLl4EZXy3WChUODz3J3GhMBIAKak6DPeKgeaI9ZSgPRyHkncWXrZPbN4RklpJ3V/ntUXuzr2GJNDnv2YlraCkDFMW5QvODs9fJs6PKh+NRJkmDYP6I2DePehlHF31pwDP+/ftQ0a5cuJCzSB0mU/fH+Jbr0T6NOOnsKTRpA1jPcX02qhNyXNPRc15BZqlSPekYpKYkJ4KX3IJ0YzCDqaw0OdxVPpUfKKNxjASJGnNn9O6tYYvMUE0PfTlfJFORGsOqfSp+G4iIUEIHpVCsAxe4DTRf1XBakY17Ow4wHTppxq4k9ASaUuzO4UWU1+MTCXFezV1Nmi2alSMtNisp0RbJjhOyAgIavOyDoq9WaZlI1R575mQ7pQ0gkbjULhZ4amA5Zi2KBZfRm0qvjoY6V0CgQK1RQkWZtSmqsZ3VeXBjj3YcH47UzrX0KXbYkVFY83vnza6+p5hbwh+au8KVoGsdn+Ve6SXaoGWNX4qcrftMnxnlW+CL7kkUq6/Ql0LgxPx21LzhwkoeWadoDUqlj2+UiXFN5uFQJb5hlmMBIOK/yj3MdsFGJ8n7jK8y9X5bVoIHRVTcApklNRPBOs8T/XmtkpjxeLLiCllWl+DKuOeCt0rLe/GUUb4Pf90JOXfKymUI1iklpQBk/RFESYy0JcixKJZfe7Wncgceg8y+nYJaiKAPi048vICv+sUEfq0g6yiWpmY7DB9jnOxv35Yga3t7heKDVrA+EokwVcqGQn5NKe5MEEfU07SJJgaVwJZ/mN59tlnsXbtWhBQzp071xTIHjt2DM2bNxd9UbtqVCZMmIDnnntOmBQrhZrTwYMHizGU56tWrVKBLAPFKs/ZRg9kOW5KSgomTZok5qaUHj16CMBNs2W3S5EHsnSETk8P1pq5TcRw4xGM7n9+PHK37w6plnJDI6S0DATb0ReaovEDHlQSfCEaQuX54e8XY/edw4W2N6iUSEK5p+5FWvdQZ3BKbQ9NnQ2/7iKeULoUynRsql7QtP3tvHkgjiz42XDO5Z8fgNSugciT2rLr9qE4/OX8kN9pLlVl1psocUZodEsGJjnKy72u0OegdNMCp3h+aOgoz8jF2cPexPE1/4S0KXnpeSj32B0hv/MA39P/OTAljL6kNL8K6X2NNRt5OYfhP3Q4uInPJyTiRgGYDo6fin2PvmpIs5S216JCvhZEW2HPgJE49HFBwAvtszJdWiLzhYcM+4vkx5wv52P37UMNq5K2Fd97OuTZ0aWrsffhF4Rfmrb4SpZAxqO3G+7jA2MmYf/QN4SfVFBJSkTma0NQRuMLqvCxadOmah45dW/P/UkE8tILdnylS4m9XeqKi0LmS5pnjXpXSPm1hZfkCmOGikjD+pL1ygfIfp+CpeD5JlQoh4rv/hdJVSuGtDn0+fc4Mu+nkN954U1/oFuIIIRaqy0XdTQUhPByUX3lJHCO8S7h+EFt3a5ejwtTQ30p1fBClH/p4ZD34MTWXdjOS/qeUBOp0i2uQsV8La22PwpWdnYbgry9WcHDJPiQfvfNKNuvqyEPs54r8GXSVkhpcy0qvBkqaCJPDn+3GP6jwQIJakJLX385ElJKh4zD9R/+6gdDNpV/YSBSuwQL51jx4NjPkf3xVyHvA7VVfB8SM8sG9ce9u+WCDsIk2KhUnTsOJXQX3CD65Z+NRu+Uth6B086bHhSAX19KN7sSmS8WxA9QnlPYeOjTrwT4Cz4QfOJ8LnluwM/NStn7yEvInhAq2GUfFd4ZanjGEAQc+W5JCE0TKpZDmRubwpeUGEzTvDxsPqct/AZgkRWrfPWmKgBRGvK833LJzcKHT198aWVQffmnSCgT2CPq96hRY+zrPRQnNmwNpWnTy1E+32VI/5Df4hABNr8turgLQXz+a71IpxNUkhIF0OAlWl8OvP4R9j8zxpA16fffioxBgZy42pI98Qvse+ot4HjweepLLS2+X0ZnML/hOdPmFACH/A4TypdF2h0dDd8r3kcOz1oYMn5itYrIGHJ7yHoorNl1yyM48uMvIW1oBVdl+msgQNQW7pnt14auUdRJSECNv2aocwt3DhoRkO/sJkby150lSt3KX44WFnLaQvPeLXVvBE4E01bUKZGEGr9MDrmLUYiy9fKuod9WWobVqIxqSz4MOYOP/fo3trfqKwSm+lK6+ZWoaAAwD46bgn2PvWa4V0o1aYhK74cKPQ5N+gZ7HnheWCAElYQElB/R3/iOeO/TOPz594bjZAzvi/Q+N4Y829G+H44u+dWwjdl5saPTQzi6cHlIG2pPq84eiySdub/Ir9r5YRxdsip0f519iuH+Or5+C7Zd0U0ITmmNJrZVagp8+WeEviNqRwkof/zxRwEueZcl2CXQJZBt37499u0LPmcJJpkdhJpQAk9t4Cht/9S49uvXD9S4KuWdd94RGleOoTzfsGGDALI0PyaAfuONN4RbCu+ztGLTpt+hmXL16tWxaNGioABVDz/8sAgYtWTJEkOexPLHIg9kGf2L0gFZ3KFAiV37kb78b/gUqVb+sLkppbD/8nPhLxmQpAcVvx+J2TrgR2Fgcgnj+u4sxbVRfCdykbp6HRIO67S4iQk4eF4d5JUJmFBpS/LW3ajw1U9IOBb80ckrmYTdzRvgaLVAuiRbxe9H6X+3IfGQTuiR4EPO6dWRp0hrbXUe3CiBmmvdXvEnJsKfr3GJwhBFrovkrXtA/urL0WoVnPHV65TIy4NPdxHmlKO5FxJyjiJj0Rok6iwm/IkJyLrsbBwvHx2hJ8+z1N82hOzt3JRkZJ93CpCv6XPKklIbdyBl7ZaQbo5VzED2Bac67d5b7fP8SN6+N4SmeaWTcTwzOnzjglP+2owyfxZc7BQiHKuQgayG5xRoajTUSTyYg5I7Q4UwxypliJzrRark+VF6w3b4dN8Wf4kkHK5TWYC5Yl38flScuQTJ20KtIw6dVRP7GgWbglqlRfqyP5G6JqAZ1Ra+s7tbNDDcXyl/b0apzbtC2hypUQk5Z1Q3nAL3Y4k9B0Lb1KyI3NRQ4RsrJuQcCf3u+3yBczHfNUbboe/ocWQs/g2JOcFKFZ6nBy45A8d1wjelre/Ycfh0QNafkGB61nNeaavXw6cTPOeWKons808B96a+JO07GDiDdYLy3NQUHLzwFON9nOcH32V9yStdMqp30Sofz0bFletQ9bsxQsjlp0BNJ1RT5kBTXwLZ+fPni780z01NDQizKUg5ePCgALUM8kSTY4LYW2+9FUePHhV+qcnJyaZblMGhGPl43bp1qu9q//79RZ8ErMpz+soqYJhBn/j81VdfRVpaGvI+ny2BrNVDINL6StRir2tkI12PrGePAlYlpvZGka1iTQHJx1hT2Fr/kh/W6OXF2pKH7nNF0tx9msdyRMnPWFK3oO/iRmdqzHe0vV+kf1JSOSmr/fTTT4VJMEEitZ7UrN5zzz1glOKcnBzs3VsgYKGWlqlyaBrMIErUkNIUmcGaZsyYgVKlQpUgeo4xKvEZZ5whgCn74djUxGqjFvP5kCFDQJ/bli1bCtDM50YaWWlaHMV3gqp2SinWrFnjadPiKC5ZdmVAATrGf//997juuuuQpPPjkgQrOhSQfPQWryQ/vMUPO7ORPLRDNWdtJM2d0c9rrSU/3eFIcaMzTd6zuj+KMldcDAap1BYCReIWrpnBnrp16ya0sEqwJ21dBnHq2rUraPrLsnDhQrRu3VpoYRPzM4Dw9wEDBuDBBx8UdRo2bCj+n4CXhabA999/vzAFLleunADMDDilFD7n+D/88IPIMzt06NCgPLNmwZ6oHWbKHRaaONeqVUtET5bBniy8M3SSjlfOIgvTlFUlBSQFJAUkBSQFJAUkBSQFJAUkBSQFPEuB9evXiyjI2mKWfofBnd566y01wjI1zX/88Yea5sfNRRZZH1lFI7tp0yapkXVzx3hsLJqkfPPNN7j++utDggR5bKpyOmEoIPnore0h+eEtftiZjcLD3Nxm6NYt1MdM3+dHHwEtQwPJ2hn6pG0j35vixXrJT3f4KensDp3NRqGrJqMfE1dlZARSwynFCMjyGVPvjBw5UgSJuuiii4TpMtPyxKMUWSCr+MhmZWVJIBuPneORMa2Gx/fItOU0dBSQfPTWlpD88BY/7MyGPJw69SvccUcrZGX5QoKHa/tkJgreX7ZuBSJwu7IznZOijXxvihebJT/d4aekszt0Dgdky5YtCyM8ZQZk4zvj4NElkPUSN+RcLFNAHoCWSebJBpKP3mKL5Ie3+GFnNuThwIGr8Morl0TcfMIEoGtoVqOI25/sFeV7U7x2gOSnO/yUdHaHzhLIxpfOIaNLjazHGBKn6cgDME6Ej/Kwko9RJqjD7iQ/HBLQA83Jw8aNd2Hp0qrIy/MVOiNmXWF++8mTC60qK5hQQL43xWtrSH66w09JZ3foXBiQ3TZzDtLLBOexz/luMXK+/gG1lnwU30mGGV1qZD3LGjmxSCggD8BIqOT9OpKP3uKR5Ie3+GFnNuRhvXpZWL26QsTNr7kGmDMn4uqyoo4C8r0pXltC8tMdfko6u0PnwoDsqrNbIi2xREi15IvORtUPRsR3khLIepb+cmIOKSAPQIcE9EhzyUePMCJ/GpIf3uKHndlIjawdqllrc+QI8NlnwNSpwJ49QLlyeahdewWeeupCpKWFXgit9S5rx5sC8hx0hwOSzu7QuTAgu2ftOqSnpYdUSyybCl9yyfhOUgJZz9JfTswhBeQB6JCAHmku+egRRkgg6y1GOJiN9JF1QLwImk6fDjAd4759AM2y8/L41y/MuDMy/Hj/fR9at46gI1nFsxSQ3yV3WCPp7A6dCwOyRTV4rjQtju/+kaM7pIA8AB0S0CPNJR89wggJZL3FCAez4TsloxY7IGCYpgSx9Cdm8ftDK/p8/NEnNLVt2sRmDkW1V70WOzMzQMubbvJexGz5XXJnl0k6u0NnCWTjS+eQ0WWwJ48xJE7TkQdgnAgf5WElH6NMUIfdSX44JKAHmis8zMu7ATfeGMgjawy6ApOdNg1SgxgB3wjEqlUD9u83pqfShUxpFEpMYy12QJtdrhzw3nve2oPyHIzghYhCFUnnKBDRQRdFHU9JjawD5sum8aeAPADjz4NozEDyMRpUjF4fkh/Ro2W8etLycNasEgZmsN4FEPGiWSTjMkVR9+6R1AzUkSmNAnQoXIsdqOclLbY8ByPf505qSjo7oZ7zthLIOqehrR6KOuFtLdpCo/79+2P//v149913LbQqelWjeQDecccdmDRpEkqWLImlS5fi3HPPxZYtW8BE0UWl3HXXXbjwwgtxzz33uDrlp59+Gjk5OeBfOyWafLQzvmwTTAHJj6K/I/Q8pCZx0iRgyhRg716gfHmgfXugY0fvmXR6mfo33hgAW9QiFlZkSqMAhYqqFlueg4Xt8Og8l3SODh3t9mIFT+Xm5mLo0KH44IMPsH37dlSrVg233XYbHnvsMfhohiIsf/x48sknMWbMGIFDrrzySrzxxhs444wz1Cnu3bsX9913H2bMmIGEhATceOONeOWVV5CaWpD+Z9WqVejbty9++uknVKxYUdR/+OGHQ5YpNbJ2Oe+wnZZZhw8fRlJSEkqUCEQ5bNSoEWbNmuVoBCdA1okPy9y5c3HttdeKTUlQqBQr82Ef7dq1Ey+AWVHGKVOmDPhiVapUCd26dcPw4cPFS2G1LFy4EG3atMG6desMgStf1IyMDLz88sshXZ955pn45JNP8Msvv4jnK1eutDp8VOqvXbtW0P6ff/7BZ599hjvvvFM9VAgySSulvPXWW7j11lujMi47yc7OxmmnnSZoUKVKFcv9yg+ZZZLFtIHkR0zJ60rnkoexITNTFM2bF3nfMqVRQCtdFLXY8h2KfJ87qSnp7IR6zttaAbLPPPMMXnzxRbz33ns477zzsGzZMvTs2VMoMe6//34xmeeeew7PPvusqHPKKafg8ccfx6+//orffvsNpUqVEnVatGiBbdu2gXdR8p991K9fHx9++KF4zjnxbt2kSRMMHjxYtO/Vq5e4Y1PppC0SyDrfA457uOaaawRwI9jTlxMnTiAxMVGVdEQ6mBXgqO3TqQ8LAWbz5s0FKP/+++/RoEED0b2V+UQKZEmzXbt2YebMmahZs6Z4Mf773//i9ttvDyITXxJFSGBGvwkTJuCFF14wBaFmQPaPP/7A9ddfj40bNwrtdzyB7EMPPSSWN2rUqKBlrl+/Xhwm+/btE2BcXxT6OBFgsE/SiBK3Rx99NNJtqtaTHzLLJItpA7f44XTPxZQIRbzzaPBQ8id0E0iNrPUXo6jSLBrvkHVqnXwt4k3nk/2cswJkW7VqhcqVK2Ps2LHqRqXiqnTp0kJLS20stbQPPvgglDspoyGzDe/InTt3xu+//y4sHqlpvfTSS0U/X331FVq2bInNmzeL9tTg8i5JrS+tJFkGDRqEqVOngvdubSnyQHb37t1ITw/Ne1SUjgJKHKgNVKQZZBoB0dtvvw1q2Si14Kbh/5Op1D6yrtZ8dMGCBeI3ghb2V65cOaGpVDYbtXTcWDSZTUlJEZINbgpqL6mFvPvuu7F48TLk5CQCOAfAtwBSgjeLiMRI87RctG5tEKoRlFTPQ8eOHYU5wKJFi/DNN9+INhybGlZlPjt37hSbnKCV5ghsQ0kPNXsEXUeOHFE1iDQ9uOqqq4LmooyzdetWfPvtt2jatCm6du2KqlWrCtBMSQ7NGkaMGIGDBw+Kl4P1hgwZItZ76qmnConRddddh9dff11IfHiY8mXs0KGDkCCxD86TLyfNGThP8qZWrVpC88hC8Lthwwa8+uqreP/998VfSqj0hXNgH19++aV41Lp1azz//PNijUePHsW9996LL774QsyhRo0aeOedd8QL/t1334l25Cv5RvDO+RoVHgycDwG9trCtshYCWWWenAPHufzyy1G9eiu88cZryMtbqaaQAC6iCAIZGT0wblwuSpf+TtDl77//FgcNhQbsQymkEw+fH374wfLrx3UrfCxM6GC5c9nAMgXc4MeMGT707p2I/ft96p7Tpi/hnmvVyvicsbygk7CBUx5K/hhvmg8+8KFXr0DwrEjK+PEncOutJ/c+btIkEfPnR24p1bhxHr77LjcS8prWCZjS+zB9eoJqSt+mTR46dvQjXykU0lbfhnmB69T5BU88cY7MC+yIG+EbOz2rnExNnnMB7WeFChWwadOmIDyVnJwM/tMW3tOJRXi3572Sd2Eqc6ilpZXfv//+K6zzVqxYgYsu4h0yUK6++mrx/zQfHjdunMAEVK4ohUo7amtpTdi+fXt0795dzIvAVSlz5szBf/7zH9AsmRhHKUUeyFINzQt+US6UOlx22WUCzLIQrJx11ll45JFHkJaWJjSyixcvFtoubrbVq1fjqaeewrBhw3DOOecI8EdVe48ePQSI/fnnnwVIoolyv379VKBE0EGQQ0DJ9vx/AkCCn+TkMli0aBJycmjeTCBGKUloAmSmFUhJOY7x479GyZKhTkJU/xMgEiDRX/OBBx7AxRdfLP6GxiVuAAAgAElEQVT/0KFDYj6U2HBtZ599ttj4BHKcL9fC/1f6UEwMjHirr0NwSrt9bv7zzz9fmNWSprSpJzDixufYnA+1xEuWLBHCgtdee01Iiqg9JmBWTId37Ngh+iA4oxk4Xz6Czj59+gRNhwC4U6dOYo36PrQVOQ5B8cCBA8XPNL0gGCTg//rrr8U/mkVzDIJzAmb6BNDcgmuiyTDBPUEp6aYvpOHNN9+MN998M8S0V78WznP06NGiPkH70qUVMXLkvwBeAaA1iw4AWZ+vB/z+VShVqhGGDBko6EuJGIHsyJEjUb16dTEdCl0oHNGalHvtvTx2LAE//FANS5ZURXZ2SaSmHsNll23DlVeS5hE4vXltQUV0PkuXVsGzzwasNfz+gF+NtgTSlwCDBy9Fgwbbi+gqi+60JX/MecczpGfPZuJbabR31ctVId/Kors7rM98xIj64swNRy8t3XgmDxr0k/WB8ltw/77yysU4dKgkeJZwXOVvmTLH0K/fcjRosCOofzttbE9QNvQEBeQ5F2ADXc9uueWWEJ7Qz5X3am3Jy8sTCiHe2YlNqDCjWTHvwixUYNEnlvdYKpaUwnsylUF0wyMYptnxn3/+GdQ3lXTENVSsERxTqUXTY6XQNJnmzPxLvKCeGX6iiiJYFFV4cdXIUirRtm1bU85QlU+NHTcPwRY3FR2jlUKQyk1BDSiBBYET1fhK4e+ffvqpAFDUzq5enYWVK18AUOCMHW5bmEmZFU0pTX4J3miyS9BI7auikaXGkuYJ3OiKPys1j9RKEiBp+zCbA+sQhDMQEyU5BIV8EfmCUUNKSRG1z4pEiOCaLxjBqlJoxtC4cWMBvvTaVL0Ws3fv3sIsl6BfKXv27BEvE6VYlFqZaWT54tNqYPbs2aqp9Y8//iheVJpckEbkD6VUBNlaH9/TTz9d+P5S+05ga1YYlIovPWlKYYe2GGlkqeVlXV7KatVKwv79DApmDGSB2wDcg+Tkkti1a6QqzSbApsBFMSWmppaHDPlsVbjkhkRWSl4jP+hjyQ9qPbjnsrKMQaz6cfL5wThrGzdSUhv53GXNAAXs8vBk5Y8VDd4XX/hw4420XgoviJk8WVoVkEZuarF5znfsWDhvtJZldtrIcyZ6FLB7VjmZwcl6zhnRzIpG9uOPPxYKGSoxeN9jTBhaQVIjS2WaBLIWdqUVm24L3calqt5HllILalXr1aunzmfixIkCRBGUEBhRgkJt3ksvvSRAEE10tQGiqA2lBo826dxwBHjaYD/sg36la9asEZrChg2HYt06mr1SO0Lg8gQAvSnQRACBAEJpabVx4MCaEHpp/VuPHTsmgA6lLwSzShRlgnTayVPbfPw4L1yMAEl5Si7Gj89G5cpz0alT4cGetD6yBKWKSariE0qgWZ6hOQEh4WGh6atSSCOCxv/9738h/q16v1IjH1kC0GnTpqkaSDMfWWpEGQCJZuHU/rLwvymt4jPOkYIISqoIiqmZp58rAeny5cuFtIsmFbVr1xaCC0q29EUJ5kQTcppNa4t+LZwnDx0KPgqCcBDIMpBVqEY2sB9uADAbKSnJyI9JJgQIBNkKTblnr7jiCqFht1pi7SNTFFM/WKVhNOvHkh9FNfBLNOnrRl92eXgy8sdObAjjNn7k5fmQkeHH++/7ZF7e/I3uVtRiO+NwijIvsBsnkvkYds8qJ7M+Gc85M3pZwVPEDVT+EH8ohdZ5VKhRESVNiy3sSiuEt9BtXKoaAVmtfTkDCRGc0BmadRnhmCCuTp06whSWgIoaR6rblUJgR43sm2++iwcf/BgfffQyLrxwMTIzaboM3HRTcMqFgkiMvwJoCmA0gBtN6WEWiVEfqImbm6YJzZo1E6bFBFE0k27Zsj2AbaCJPIMMM5WB8jc1dT78/jbIzg4ftbgwIKsNbkQwyMjEWrDPoFTUyBLk60GoHvxRa02tqjZq8U033STMs6mZZDEDshQa0Pd2/vz5wtyZhTQgLwlAtRpYAtsuXboISRc12kphH/QVIIh9+eUtmDOnMvbsQRA/L7zwTDE/8r4wIKsEpSoIwsEI00MA/KVpyujDI/IFG3cByECHDiMwebLxtuA+pP8uhRZWi50PWaQBGuxcbk52DaAdfkTK86Ia+CXS9Xmlnl0enmz8cSLk0qc0ysigT+UKDB9+oalPZaTnllf2UbTmQWMoxcjMyA4wP3MHpk1jDAl7o9oBJ5xLUYyobI9C3mxl96xyspqT7ZwLRysreCozM1O4lSnKIfZL/DF+/Hj89ddfarAnWmHSD5aF/ROP6IM90TrzkksuEXXoc8s7uT7YE+/EipKKd/XPP/+8+AV7omlmNIM9xeMjUxiQJUC94IILhPM0/RMJaBkciX6xBCT0/6RZKbV49KmkuTBNj6+8sjNWrHgX+/ZlA7gAwED4fL3g95dAevpaPPLINgwZco0wMR4/viG+/rom/P7NABoC+B8AY9PmcLnx9ECWAIz+ozR9pTkxN/KUKbno0OFyANcDeAQA80ZtBEAgzkBFtJs/F++9tw3du1cyfP+UcZSoxUYaWS2Qpf8maUiziBtuuAHTp08XwaHob0whQWFAlppQaq+pgaXGnNpmaldpTquY8rIPasj1QI7+rjRNpraVtKY1P0EwHeIZkIomx9TKkrfUohOsUpNNTTu1tKQbHdv/+9/ZePxx0mwHEhIyg8A//d4bN34QZ5yRIDTwkQLZAgHGWgD0vZ0DgLx5EQCjD4/JB7IrADRH3bof4+efGwttLLXFNLdWfBW490hLBoSyWqx+yKxoUOxcbrp2tbqC4lXfKj+srF6mL7FCLft17fLwZOJPtIVchdHcyrlln/PebRnr9dsBJ6SWzAsc3z1T2HsTi9mdTOdcYfSzAmRpnUhXQPquUuFCXEIsQmUP76ws/MtAq9r0O7QA1KffIUhlXBcl/Q7dJZXYOMR2vAfTBY8xdXhX5xi8Y8v0O2E4GutD1mzowoAs2z3xxBPCBJaO1TQ9pfkmzVUVDSGBHX1MqUmk72h2dnkR9c/nexcB6ec/AJhImBFljwA4TQDbadM644cfHsGYMRPzI4gxElgvAMPyzYyNZ01wYHTZN0qdQy0ogSbt56khphnPvn0780EsoyMfAFAr32z5vvwB74DP9znS00+IaL76qMVWgSw75TwISGn6QMDFl42aYpbCgCxNdgkw2ZamFTTzZnAmRotWCvsgmNMXmgXTTHzAgAFiLSzkIfugefVHH30k+iLQpeaWAbtorks/U/pJ09c3J+cYjhwhjZ4EEGpaTGm23/8XMjOvw7Zt/walGzIyLQ7VyHJWBK88iBj0iPnAqHplSiiaFgM+32yUK/c4/P7fhRaZ/sdPPz0Kf/11ESZNOoRZs05FkyYr0aVL1RCNf2EHqZUPmVUNip3LjZnWubB1FJfnVvhhdc2SH8EUi5Xw1C4PTyb+RFvIFY7mVs8tq+9VUamv12LT+6d9e6Bjx2ArMTvrsQNOeD86mfMCx+r8scI/u2eVlTH0dU+mc64wOlkBsszAQWXFlClThFsi49PQipAYRUmTQ2UNA0UxujFdCnl/J35h7BqlUAFHzMK4NbxPUvnGrB8MrqoUgl+aMDO+DxVGDN5KUKsvRT5qcbQ0ssXpI2NHysyN4YafiJsXh8JeXifP+UIxDY8ShdhJX4W1tcLPEiXuxMiRF+H++wM+wYUVJ/zQCn58vmfg9x9CQsLTQlNMDfF770VuIhbph8wKLZgyd+tWoHnzk/uiUtgeMHoeKT/s9O1kz9kZz8ttYik8tcvDk4k/0b7MmtHczrl1srs32Hlv7fCT45ysGtlYnj9W+Gf3rLIyhr7uyXTOFUYnK0C2sL7i8VwCWeonj7gD4txisN0X1A0fFjsfmnDasXgcgOQjJU1MZUTtbKyLXX5GMi+7e9+J4MdIAtyq1Qmkps5Cu3bNg7TJ0fj4TJlSNC4qXpCMK/SO5Xtld89Fsp+LUh0n71Ak67TLw5OJP3Y0eHPofWFSzGgeyzM8kr1wstSxQ+eT1Uc21uePlT1n96yyMoa+7sl0zhVGJwlkC6NQjJ5Hk/B2Dj8v+9A5AYuxltC5dXHQbjsvAQQ783LCz0heP6sCDCcfgHD7i/n9JkxIQPv2SabTtkMLBjdzEszDjf0T6/cukn2grRPri4XVPWfnvbG6ZjfrO3mHIp2nEx464U+k8/NCPTvniR3BarTH8QLtvDgHO+8V1+GGNZqX6GWHTrG0EHByVjmhq5Nzzo17gZO1WWkbTTxlZdxo1ZUaWcbmvbFoaGwiZbpTsBhLH5Zo07qwA9AtgGD1ULMyL6f8jGTfWJmPXcFP4RLgQErrqVN9aNPGeNZ2aDFrlv2LihW6REJnozqF0yXQiuZvZnSxO7ZZu8Leq2iMZ4e2dtpEY67R7sPuO2RlHk55WFxoHY5m0eaDGc3tnFuK5tfqt8XKHtHWdWscu/OLtJ0dcFJ4G36bfI4iKkc6fzfqOd330d4rTs8qJzSzc87ZaeNkjrFuK4FsrCls0n80Ce/kIxOn5YcdNtpgMZprdHqA6ufiheAaVg81q8DFLX5GKsCwM5+JEyMFk35kZPiEb6uRBNjO2NSgFH5RCewsbeoHq3yy8554TTKurMGti0Wke47zcoMfdnhoBwzY3cdW5hcNHlrhj5W5eaVutN8/M5rb5bfVb4tduro1jt35WW1nZz3GbYpnXmC7+1E5h2+7jQE7Q1MnWo2N4fb3xmwfWTnnisJ3yOr7Ek08ZXXsaNSXGtlipJGlzybzmqal3WNiSjkxPz/soqC9YxaBOBobTN+HWxeHaI9jRgurh5qdeX32mTPT2Gjz0Y7gp1ev6KzBiSDEyuXGDp/smF45WU+0+artLxogKJrzc4sfTuZsZX/ZeYfC+WYazdtrPHRC21i2tSPkMptPNH1k09MDOd9ZwuVddWqpYfUbFktemPZtQwVoBZwo4+rbRJIXOC70cDio3fMnVnulqJxVReE7ZGdrSCBrh2pRaBNNwsfrMsm0Oz/++KMIbsOw1RdeeKFIyaIkCLZLJr5sFSvORXY2v4L7TbthyhYlsqudS7jd+Xn14mDV79nOoWYHlDItgZd8eOxIc7lXohEZ0g7NtXs70suNW2eCHVq6kRrIaxcLt/hh90yzesFzg+9e46Fd2opojDw4eYDs2QNkZgYQ3k03Oc/Xkj8pK0KIcOuIVtTif/8FTj0V2L/fGMQqc3D6DXd6ntrmqZWG0WKOlTHz6xabd0i3djvnT+RWVdbvlUWFzl7/DtnY4qKJHTw1evRojBw5Etu3b0fdunXx2muvoUGDBnan4Kid1MjGMWqxNn/skSNHRI7Tzz77DJs3b3bEVDZ+5pm5ePTRdvD59oeV5mpNKR0PaqGDaH2bom3KZWEJsHOo2Y2gG03wb2WNRnXtrPudd6KXAscNWtj50NsBmHYl4055WFh7r10s3OJHYXQxem4HDNgRaFkVtHmNh3ZoK+zJ7dgx2gC/kQq57ABZtrFybhHAOglQFymt7ZzlVvdhpHMxrGdVQuRosNDGxeIdMqCJHb7HMrpzUaGzl79DTra+VSD7ySefoHv37njzzTdx2WWX4eWXXxbY5c8//0SlSpWcTMVWWwlk88lm5SPTurUtWoc00gJZPly9ejUuuOACIeFgntI5c+agdOnS6NatG4YNG4akpCQwiXDv3r0xd+5cMOnwaaedhs8//xy1a9eG0h/r16hRAwTHQBkxrs83C37/PwBeBrASpUu/hNNPn4FVq2ar8+LmZBLjP/74Q/z28ccf45lnnsHGjRtxxhln4JVXXsEVV1wRncXnCxAmTQII7vbuBewkRo9FcI1IF2jnUKNCwW7ydbt3ukjXE2k9Oxf3W2+NjkZWmWOsaeEYYEZ4kbazh+wA5kh5q9Tz2sXCMT+sEsBCfTuXQsdWFhHsL6/x0AJJA1XtgphYHw5hFlIYzSOdmlvnglvjWOY9G9j50ETZtKwwftpalwca2SFttL/hWjKY0jmCc85Ncnr5O+SEDlaBLMFr/fr18frrr4th8/LyRCpK4pZBgwY5mYqttkUeyK5duxZpaWnq4mmiW6ZMGeTm5gp1ub6Uozc6gIMHD+LEiRNBj+fOTceddyZj/34fEhICTv7KX/pKjBuXhxtuyMN+ikt1pWzZskhISEB2djb4UmoLwWipUqVw7NgxHDp0SH3Uvn17tGzZEg8//DBycnLE31mzZglQSqnGqFGjRBvW69ixI+699148/fTT+P3330UeU47J9VetWlWYJrNe8+bNceeddwqT5R49emDTpl34/PMDAjytWvUR1q17Cy++OBsNG2bjggvOwsqVK1GhQgUxp1tvvRWXXnqp2Ijz5s3D3Xffjffeew/nn3++mNeDDz4o+j2VNk/55giks7aQ9pwLQfThw4eDntGEOjU1VWz6rKysEBpmZGTA5/MZ0jAlJQXJyckhNCQPlyxZgmbNmgkT7X2MQABg0KBEzJvnQ14esGVLWRw/noiKFbPBFC/asn9/aRw4UAodOhzD6NHBc0pMTEQ6HZUAMV/OW1u6dMnA7NklUb58DtLTKTQoKAcPJmPPHtLiBKpVC+zDevX8KFsWmDvXh3XryovfqlfPQokSwTTcuTMVOTklUa5cDtq1O4wRIwqe+/0lMWtWqpDuA1miv6uvzsN11/lRsiRNegI0NNrfCg2PHj0q9pu2UEjC94jCkXD7m/uXe3LBAh8GDkwUXezdWxpZWaWRknIMlSpli99o8sYyahTQunUaPvjAh2HDDsLnC0QmVsrWrek4diwJmZmHkJZ2VP196NBctGtXEpwzecz1aAvfteTkspg82Yc5cw4iOzsviBbly6eK/cA9GBDoFJRIzohOnRLx008HQ3iza1cZHDqUjLS0I8jMDNAwIYE88OOFFxLE/uYF/OCwYTxkgqJhZGzYAF9aGrLGjsWxq64SbWfOJF0SsW9fCrKySon9yX2qLaQP6cTy7ru70aJF8D7kHuVeJU/JW23hucPzh2cSzyY9DXmGsOj3N2m+dOlSXH/99YL+ehryXSRvjM5Z7j/uQxaewdE4I5T3ed26DPj9CahS5SBKlQo+Z/fsScHBg6UEbzp2PBT03ij7m3NSzggtLRQaKvs7UhqS7n36lMP06T7UqJGFhIRg3mzbloajR0uoZ4SyV/hOL1xYCh07pokzomrV4P3t9/uwcWOAhpMm7cNVVxV8q3wLFiD9vvuQvG0bcsqVwxHykB3zfEpLQ8LQoSjTurXYC99++62QmHP9SnHrjNDS0OwbyDrac5ZnD88gHDuGpJYtgexspG/ZgiR+OzMzcVTzrWfb5IMHkZKbiyP//ouDx4+DtEkcODDwXubmImPjxsD+rlEDuaRB/sGUO3IkyrRo4eiMYL/6c1b73vB7oT9neSYlJaWCwqj58w+An0HtGV6xYuAe0aHDYaxeHXw/CXdG1K2bgM8+CwitVRpqGGB2Rtx9dyLmzCktzh++T3yvtCU3NwGbNgX2Yc2a+1G/fi7eeKPge8TzzuycdXpGJH/6KU488IDY49pS8vBhpO7YgbzEROzX5HHPHToU/hYt1G+g0V3M7B7B/o3OCOV+wXeofPnyYq/aOSPC3SP43eXYRue3QkOjb6CTc5bfwDlzUtGpE/l6IMRqb8OGAM25H1577SgaNfKDe2X5cp+41/B+w+81v9vawrOOZx6/8+3b7w3aK6yn3JP1NNS+N3z/+Vy8y/nfUfEub9oEf0KC4Lk/PR25Tz4Jf6NGYni7NOS7pnwDjb5V+v2tvVceOlQSu3Zx/+eKe5y+bNxYDm3a+DF27P4QrKHck43uYso9ubC7mBWsYXrO5k+a59jpp5+OTZs2qXdecb4mJ4t/2sL7H9+jSZMmoZ3ixA8IvMGzZxrNPF0uRR7Ijhs3ThBVKdyYfEn5ESHB9YUXOxZuIPHB1BRuoNzcEli4sDIWL66K7OxkpKYeRf36W3D55VuQmpok2ugviwrDebBwTD3g4SHFf7zQaUEutawEooqPLAFs27ZtMXz4cKGy54WDa1mwYIHQjr700ktCfb9q1Sr06dNHAMrAnAP9sj9KSQiO16xZI/xtP/zwQ/USSi0uAelzzz0n2hEUn3322WjTpo24yPbt21eYCFSuXBkjRowQdu+8yCrliSeeQJMmTdTfzGjIw54Hk15QoPAmmjTk3Eh35WXTX7j5vF+/ltixIw19+y5Go0Ybgng+adJ5mDTpfDz55Hycc862oGeF9fvJJ3UxdepZ6Np1JW644a+gtl9/fTrGj78EdersxYgR3wY9y8lJQq9eN4rfRo6cJT4k2jJy5FX4+efqaNv2N3Tp8mvQs0hpaMQbZR8a8UZZqx3efPTRBZg+/RzUq7cVAwcuNKThsWMJOHToGEqXDr6cDRrUFOvXl0fPnj+jWbO1QW25j7hP7b7LbM/3Qg+kIjkj5sypgczMfTjzzD1Bc3r99cuwcGEdXH/93+jVa3kIb2qtXImLX34ZU8aNCzl72t5+O5Kzs7HwoYew9ZJLgp5PmFAXX355Ni67bBMeeCA4GBvB25Ah1yMl5TjGjp0S0i/PCK7JaK0KDfVnj9KJch4avTekvRkNo8EbO2dEz54dcPhwCQwePA91624PosW4cfXwzTdn4Kqr1uPee5dYepcVGhqd3+FoyPfmqaf+g9WrK+Dtt6ciPT1YkPD449fh778roFu3FSFnBPtdsaImpkw5BU8+OSfkjLjvvtbo12856tbdGPKtunLUKNRYtgy/tW2LX7t0CWpbY/FiJKWkYFv9+mG/VW6eEWbfwEjO76aDBqH8+vX4uWdPrG3WLGitZ375JS6eMAELH3sMW84/P+hZ8oEDaHfHHeK3L19+GdlVqgQ/9/ngS062fUaws1h9A9esScFpp+0Nmu/771+EmTPPMjwjdu4sg1q1AgDT6F0Od0ZMm3Y2PvqoLs49dyeeeCJ4H+7ZUxp9+wZyoY0ePR2ZmaHC6VidEQ1HjsSBzEz80q1bEB2qLVuGRqNG4UhaGqaNGRNyHvIuYPUuFsk+dHJGhLufRHJ+O/kGhjtnV6yogHPOCXVl69q1I5KTc/HKKzPFHVhb3nrrUsyZcxquvfYf3HnnsqBnv/1WEcOH/wclSpzAhAmTo8ab9E2b0CJfQDV53Dic0Nz5OUisaWj0bV2woDZGj26IypUPCjrpS+fON6N//59x+eX/GGINL92TKUTpxYicukILzaFDhwb9unXrVlSvXh2LFi3C5Zdfrj6jIo4KMCqW3C5FHshGUyPrqpSEmtYmTdAqLQ2P8KUsXx5727bFT5mZ6NCpEzZsCAAuSvKWLVsmwOP69euFpOrFF18UgJRSlE6dOomNxouqkUZ2165dqraFYJia3NmzZwvNEU2SCWa5+fg7+5wyZYoAhdygnINWks+XmVpZAlqWaGlblE0fkUb2wAHkzJiBhPnzqUZCXno61laujLoPP4wSaWmqtoUyjJYtkyjQx+bN5hpZasH8/tL455/DOHEiWGNVmEb2yy/T0atXqYg1stQyUnPaokUS1qwpB2pdzDSyvKzXrHkYP/yQLTStSlG0iYVptWOtkVXmQzp/910Kpk1LQXb2MdSseShIQ6yl4fTpWRg4MEE0VWRIWo2sAgJGjswVEuBw0mirklTtwRqJRpZK3Pr1c3DsWG6QtFqvkaWCh0rYmTNPoExSHjLOOQd5Bw4gq1atkLOcEmVKlg9WrozjlSrhxMyZ/AIL7XafPqlCI0uwqtfI0pqAdJo8ORdXXbUv5KN4Mmhklfd5zZqyyMtLNNXIUvhYtepRLFlyIOi98aJGVtnfhw6dwLRp2Zg3L0GjofOjQ4eyIgWVes5qtJTUSJXMycHhsmVxWKexKkGN1dGjOPT33/h2wYIiqZFNHDQIPpoR5eUhfetWU41sqQMHUHr/fhzv0AFZN9wQ0ODkl4S8vFCNrOatLP3kk0i69VbbVhvsyo5Glt/ewrQtEycewrBhwdr9cBpZ3jVvuSVgmWZFI0uLkAEDykSskX3qqeNo0aJAARBLjWzpli1x7JdfItbI+uvVQ+4bb0iNbP4eD2cdp71H7NqVhe+/9wWdP40bp4Nm58ePF1guKtZDkWpkx4+n9VCwsigijeyRIzhKG15e3vIvConHj6Psli1iZftq14afH978jy+/o2mZmba02lbvEdp7ZXa2uUaWU9u3rxw2bjwRREPl+HEVa+QPamj5kv/MikZWAtkownSrNt1RHNp5V/mOMtfs24d2Ph/682XNNw3bUrYsamRlCT9ZakZZCEAJHv/6K1jrt27dOpFup2fPngJgan1u58+fLzStWjPRd999V2hcaU7MQrPLKlWqCGBLc+R77rlHlcrQRJlmA3fddZfz9UarBwMHI5qa+PLy4KdJ7fvv045VHS3Wfs92/Ex4MY31vKJF7lj0E85HjGa1EyYkoH37AjPIWMwh0j4t88mOs2R+5JRIfecinbvTel70DbPMD6dEiLC9A7ZHOEJ+NYsDnRg/Hl+WKycsdKhdL1LFjjMagyxEIzS6A0JF672x+22xOnW3xrE6L1HfAw680eKnrfV7rFEs90oQnT/+2J1IZzbp69XvkM3liGZW8JQ0LXZCaV1bK4SP4rDOu9IEsLjG7wcT5PTX9urz4T9+P6pfcw3e/OIL7NmzBzfccAM6d+6MRx99FF988QXOPPNMYc9OXy+a+t52223o169fEJBl9LBzzz0X27ZtU6OI6YEsh2XgqC1btoDAd8eOHaq/8YwZM9C/f398+umnqFevngC9NCWgKTIDSbleCgn8QQmdcMvUJdWLNUCwe6jFel6u88fCgEbRQVu3PoEyZWahXbvmnrp0W+KTw4tXNKKmWmBD2KpevcBZ4ke0iFFIP7G84AUNbXF/5bVpgxm33VY0gazFtYp0PE4i6UVpr0TzvbH7bbG6FLfGsTovW2kBohxSOZr8tLx+NvBYsKNY7ZUgOnfuHHeBVPcAFgwAACAASURBVGG88uJ3qLA5h3tuFU/RZ5ypdphyh4UWgrVq1RJxfGSwJwucsEp4C13HrqruxnMNEApkAdDz694SJTA3PV0EamEQpqeeekpc8KlRffXVVwXopFnPjTfeKH6jqYg+CvIdd9whzIfpI0EATDNsrUaWC6VZMdt16dJF+NNqC/1xn332Wfz777/CzJMbl7mjuGFdLQ5virEGCHYPtVjPy1UeORws7heGMPOPmE92tEhzgn3SHJIxas2LBT+iRo3CO4rVBS9oZIv7K69xY8wYMMBdIButi7dF7bMAPXZzmxXO3ohrRPu9sfttiXjC+RXdGsfSvBx+9y2NZVI52vy0NCdPMiUQTNxORqxwoPx4YiJmzpwZOKuaNrWf2sESgZ1Vjvhe4GwYV1pbxVPMcMLgTm+99ZbABcQVVHox44liSerKxPMHKfI+sgxSpESEc5Nwtsay83GOsoTR1rzj3agI0K04HWrxYHdcLwzRWrAdLZIbuXRsrK9Y8MPGuoOaWARlti94kc7T4v5yXSMbTQLYATFuJOcthFexeG9sfVss7l0uy61xIt3uop4rEiLzGcWCnxGt327qqYg6d17J8l4p5Gw4MXYsvkxICADZIqCRdU5Bb/VgFchy9ky9M3LkSOEGedFFFwkFGzW18SgSyLpJdYsXEWEu5dGLrptk84KvjKvrPQkHi9uFIZq0LgICl0iXWyz4EelijerZBGWWL3hW5mhxf7nqIxuLi7dVEGMH/BbHvKM2966VrSjqFrdxDAgQl3PQA/vY8l4I1yCCs4EhoZYOHox6Q4eihMd9ZKNKG490ZgfIemTqYhoSyLrJDYumYWB9j5oeukk2QQdGsIy0RINuNiTakU5P1gulQFwuDNFmRDG6gBQLfmj5a+V9juDiJbrW+eNHezuF9Gdxfx3fsAEzZ8+OvWmxxXlh61aIcMyRFKtgySr4jWQOFurE/b1xa++6NY5C+5hKiMwZHBd+WhRYCbN6r1ruRXg2MMbJ8ZQU+LZtC8TIqFaN4bcL0hsYsYihgZmv3Mp5YuFdPpmqSiAbJ24XScJLjay93eI23axenuytSrbSUCAuF4ZYcCDOF+loLanY8IMEsfI+R3jxEqkf4nGJsrC/jjdvXuB3FsuoxbG+eFsFMVb4Ha0XJr+fuL43bu1dt8aJMm/sdBcXfrp937FDmEjbWDwbaEWSRAdcC+ecNlOFmJYVoWWk6yjm9YokntLwRGpk3dygFl9qT0vaiivd3JY0u0lHD48VlwtDrOgRx4t0tJZUbPhh9X0uCmd0hPvLNR568eJtFfxG6cVxjeZG83Vr77o1TpR44qSbuPAzHhZoTogUrq2Fs4FaWX/btkhg0DarAkhlDhGejbFablHtVwLZOHGuSBL+JJJkRnVbuEU3t8aJKnGKR2dxuTDEknRxukhHa0nFgh923udbb/V86gdV6zBpUiBS7969AHOotm8PdOyomu26xsPidPF2+AK5RnOjeVoADSJvvd0YHG6N45AX0WgeF34WJ/paPBsYaT1B60Zm5TtqVWgZjQ1STPooknhKamTjuPucmEzEcdpxH7oQuql5ZKdNQ4ipSaSTP4kkzZGSxK16cbkwuLW4IjhOseCHnff5nXfc98eP0f5wjYfF6eLtkBeu0dxonhZBg+0YHG6N45AX0WgeF37aObe86iNr4WwI0chaYaAdoWWkfvpW5lFE60ogGyfGFWnCS/MHe7vGgG7+hAT48vLgz8iA7/337YNYzsjCoetIom1v9cW6VVwuDMWaos4WZ5sfXvJPsvM+k2wM4pSXVzgBnWi1Cu/dcQ3bPLQ6cnG6eFtdu66+azQ3mqed/W4nK4Jb4zjkRTSax4WfxQmUWTwbVB9Zq8yzOI502wsmsFM8lZ2djUGDBmHq1KnYs2cPTjnlFNx///2466671IGOHDmCBx98EB9//DGOHj2KZs2a4X//+19Q3tmNGzfi7rvvxpw5c5Camipy1T777LNISkpS+5k7dy4GDBiANWvWoGbNmnjsscdk1GKr70vU6lsxmYjaoMWgIx3d8jIysKJOHVw4fDhKpKU5W+BJJGl2Rqjot47LhSH6yyg2Pdrih9cEdHbe5169gO7dI+ejhyOG2uJh5CsvqFmcLt521q9p4xrNjebp1mXerXEc8iIazePGTyeWe14SJkZ4NgRFLbZzjzuJhCvR2Nf6PpwC2TvuuAOzZ8/GO++8gzp16uCbb77BPffcg88//xxt2rQRwxGgfvnll3j33XdRtmxZ3HvvvUhISMAPP/wgnufm5op8tFWqVBH5abdt24bu3bvj9ttvxzPPPCPqrFu3Dueff74AyH369MH333+P/v37SyAbsim8dAjoJxfjuVEacu6552LLli1ioxWFEtUPjTwM48byqPIxbqsoPgNb5ocX/ZPsvM8TJxab1A+Weehk+zq5eDsZ12NtXaW50f3AjbQlEYKTuEX2juKeiCs/7QgG7bSJIr0Mu4rgbGAe2SWDB+MS5pG1E2HdjtBSprZU2eUUyBJc3nzzzXj88cfVPi+55BK0aNEC//3vf5GVlYWKFSviww8/REfGcQDwxx9/4JxzzsGPP/6Ihg0bYtasWWjVqhW2bt2qamnffPNNPPLII9i1axdKliwp/ptgePXq1eo4nTt3LvpAdvfu3UhPT4/Kq+ibMQOJvXvDt38/VJNVjelq7rhx8LdqFZWx2EmTJk2wcOFCLF26FBdeeKHod//+/ahUqRL++usvIdlQSizmxo3BsSkFKaqFH5pvv/0WTZs2tXcAahbu++ADJFEjE2GhGYyfwWFkcUyBaPLR8WRkB7DEjyNHkFSrFpCVxQ+KKfUodUfZsjixcWPkeUQd8MLu++z74gskEgQHEq2HzECsgxLkyZOj+j1wsFTDppZ4GIXBY/GNisK0XO3CbZrrF+fW3nVrHFeZZzBYVPl55Ah8kyYhgWAzP0BbXps28GsCtIVMgW0mT0YCY38obdq2hZ/nk87HU7x/+SAh7Lk1aRL8rVu7StrCzoZjY8bgqxIlbN/jEjt1gm/6dOFmVljh3d7fpg1yP/20sKonzXMC2QoVKmDTpk1BeCo5ORn8V1ihRnbFihXCtLhatWqg+S81sQSdjRs3Ftra6667Dvv27UMG09bll9q1awuN6gMPPIAnnngC06dPx8qVK9Xn1MCeeuqpWL58OS6++GLRV7169fDyyy+rdcaPH1/0gSwRfkpKSmF0LvR5laVL0eDZZwu9vCwdPBjbGzQotL9IKjz66KOgFvTMM89UJRm0Ne/atSveeustVSoRq7m1a9cOL774otgosgAJx46hWc+eKJGTU+iFnMm7vx4/HnklS0rSSQqc1BSoMWcOLnnllYhp8HP//thMCXqMi5P3mWfuxa+8gpKHDkEEkvP71b/HypTB8n79sCNK34EYk8HV7knzaosWoerixSiRnY3jqanY1rAhtl5xhTwrXeKEW3vXrXFcIltMh4k1rZycdTFduKbzWJ4NXv0GuUVbp+Pk5OTglltuCenmySefxNChQwvtnj6vBLPvv/++8GelyfCYMWOEaTALcVrPnj2Fb6y2NGjQANdeey2ee+450X7Dhg34+uuv1SqcV5kyZUQ+dGp3iZXYz+DBg9U6fFbk88hGRSMbJ40CNbJXXXUVRo8eLWzJGzVqFKKR/eSDD/B8nz7YmJeHMwDwunhFPgv3A7gdwLcAqgC4p3Rp9Dt8GMeOHRM1Jk6cKGzNCZbLlSsnADI3pc/nwxVXXIFly5ahdOnSYtNRZU8VPTfKzp07hS06JSibN29WBQW0WT/99NOFtrh69epCAvPwww9j1apVKF++PB566CH07t270E0fzQpRlZhSA1NMtDHRpLEbfUWbj27MuTiPYYUfXpaGO3qfLWhDvLgXrPDQi/MvinPyDM3d2rtujROnzRANfrqhKbVrfRInsoYM65jOcbrDe4V+TudhRSNLXHHnnXeqQ9IkeMmSJQK4jho1CtSyzp8/X4DNKVOmCMtTCWRNOOTUpjuo2zgFL7jmmmtArejhw4cxY8YMLFq0SABZgk4Cyd9++w13dO2K6fv2gca/U/OB618AMgF0A7AHwEcAcgC0BfATAH++ORw32GmnnYYzzjgDv/zyi4gSRg3srfnmsAS0BKOKafH69etFtDFF/U+7d25GpT43KaUlNOXdvn07zjvvPLzxxhu48cYb8fvvv+P666/HhAkTBAB2q8TEh8WLfiZuETRO48SEj3FaS3EY1hI/vO6fdJK+z5Z4WBw2rQfWIGnuASZEcQqO+emWP7GdeAB2IlZHkbbarhzTmZ1F4IsrxnSSojFG6493t1bw1MGDB7Fjxw51ylRqMaYOQesNN9yg/s5gTFSEffXVV9K02IzBVghf6CaJ0yGgAFlKN6jppGaWvylAtm/fvrh+82b0o2Nzvu3/lQAY0JpGAKUBLAJwaf4CP/P50IkmcCZ+arRFP3TokJCcsBQGZJ9//nmxAbkRWerWrSu0rt26dROaXgJvbl6l0FSaAHfs2LGFkjxaFaJyABpNRkaVjhaLIuonZnyMaHRZSU8BS/yI0/lpiWsn4ftsiYeWiCkrm1FA0rx47Q3H/HRLSeJ1YWIh28IxnZX+T1KhpdO3zgmeUtoq5r/KXIhrqJBjBGMl2NNHH30kFF8sf/75J84+++yQYE+0/GScIJa3334bAwcOFFai9NWl5SjH+fXXX9Ul0yS6yJsWk0COgz3F6RBQgCwBJhlGB+YFCxYIp2tuAEo31v/xB0poHNiPA2BcsJ755sTbAVTOZ+kSAA01GllqT4cNGyZMgXlQ0D6dduYK+CwMyDJ6MTW0tFvnRrryyiuFJIY26wTZDLVN02SlMHw2zaO50dwqUTsA3ZqwHMeQApKP3toYlvjh1mXNWyTy/Gws8dDzqykaE5Q0Lxp8inSWjvnplpDPrXEiJZzFeo7prB3vJBRaWiR3SHUnQJadEcvQzfP1118XpsXz5s0T6XZoAcq/LPxLbMD0O8Rs9913n/idCjEWJf0Og0VRiUalGJVm1Ozq0+8Qf/Tq1Uso2pivVgJZUjBOh4AWyJKJNNWlwzOTBhPIMldSux07cNeqVapGVgWNhWhk6SdLzS4TDtP3ldIMAmaaDzOyGAt9YxkNzMy0mHUYDbh58+YipxPBLJ25WUaMGCGiizG5sSgxTg1k9qJG9QB0ehrI9rYpIPlom3QxaWiJH26Zz8VkpcW3U0s8LL5kcHVlkuaukjvmgznmp1tKkiIuTHRM55jvhOI9gFMgS9BJN0RqX/fu3SvALLEMoxFTYRaACEcEtqFWlko1ujoSnzBvrFKoNCPgZdRjKsx69OghsAYDSCmFz9gvXS9r1KghAuVKIEvqxOkQ0AJZTmPy5MnCiXrPnj0CyFJ93r9PH3y6cyfqATicb0p8NoAaALoyXQ+DOuU/a8dcXPkaWdqxM8z1tGnTRG4mOmO3bt1aBHlSgGzVqlWFBEVR9et9ZAOkmSDMiCltIYil4zYLtbUMh00f2TbcqL17Y83+/Tju86E+TZsTEgLgu1w54L33gBiFe5cHYPE4YCUfvcVHy/yQ/kneYiAgrHAoAW/ZsqXj1GSeW5xHJyRp7lHG2JyWY366pSQp4sJEx3S2yV/ZLEABp0A23nSUQDYgKgDcSCSu47YeyPIxEwMTdBLIMo/sZxMn4tkePfBvbi6YzYmJf0YDqAVgH4A+AL4DUBXAHaVLY3BurhrimsmEhw8fDqb04ViUkjBPlAJkaRrM8NoMca1ELdYGe+J86FNLiQmduRn9mFpcpTBQ1CO9emH5ypVg9q5zAAwHEBTqKV8aA2qB27SJ+n6XB2DUSRqXDiUf40J200Ft8UP6J3mKibZ46KkVFL3JSJoXPZ6Fm7FjfrqpJCnCwkTHdC5e28711Ugg6zrJYyRB8PIhEOHcPhowAE9Mm4a///7bHa7ESQCgXZw8AN1hdaxHkXyMNYWt9W+bH9I/yRqhY1jbNg9jOKfi3rWkefHisGN+un1HKqLCRMd0Ll7bzvXVSCDrOsljBGTZrZcPAYO5/e3zIcvvxyUZGVg7YgTavfoq2rZtqzpGx5w1bkobTRYjD8CYc9mVASQfXSFzxINIfkRMKs9WlDx0nzWS5u7TPJYjRoWfESoiopYWpggKE6NC51huhGLetwSycWJwzAjv5UNAN7eVCQno/Pvv2JSVJUx/O3ToIKJ9paSkuMMVt/w/wqxGHoDusDrWo0g+xprC1vqX/LBGLy/Wljx0nyuS5u7TPJYjRo2fXlaSxJKAEfYdNTpHOJ6sFkyBmOEplwgtfWRdInSxHMatiHwSyBbL7aNdlPyQeYvFkh/e4oed2Uge2qGaszaS5s7o57XWUeWnl5UkcSZ8VOkc57UUxeElkI0T14o64eNEtugOKzWy0aXnSdyb/JB5i/mSH97ih53ZSB7aoZqzNpLmzujntdaSn+5wRNLZHTqbjVLU8ZTUyMZ3/xTt0aWPbNHmn4dmLz9kHmKGTN3iLWbYnI18p2wSzkEzSXMHxPNgU8lPd5gi6ewOnSWQjS+dQ0Yv6hIEj5HT3nTcjshnMEt5ANpjnddaST56iyOSH97ih53ZSB7aoZqzNpLmzujntdaSn+5wRNLZHTpLIBtfOoeMvmfPHlSoUAGLFy9Genq6x2Z3Ek1nzhygb9/CFzx6NHDttYXXs1jjxIkTmDdvHq6++mokJSVZbC2re4UCko9e4URgHpIf3uKHndlIHtqhmrM2kubO6Oe11pKf7nBE0tkdOocDsg0bNsTu3buRmZkZ38nYGL3ImhZ/8cUXaN26tY0lyyaSApICkgKSApICkgKSApICkgKSApICkgKkwIwZM9CqVasiR4wiC2TXr1+PU045BUuXLkXVqlWLDuH9fqS0aoXE1avhy8sLmbc/IQG555+PnC++AHy+orOuOM2Ukrzvv/8e1113ndTIxokH0RhW8jEaVIxeH5If0aNlvHqSPHSf8pLm7tM8liNKfsaSugV9Szq7Q2ezUbZt24YGDRpg3bp1qFOnTnwnY2P0IgtkN2/ejJo1a2LTpk2oUaOGjaXHscnXXwPNm5tP4KuvgGbN4jjBojO09K0oOrwKN1PJR2/xUfLDW/ywMxvJQztUc9ZG0twZ/bzWWvLTHY5IOrtDZ7NRijSeAiCBbDz2j98PXHYZsHw5kJtbMIPERKBePWDJEqmNjZAv8gCMkFAeryb56C0GSX54ix92ZiN5aIdqztpImjujn9daS366wxFJZ3foLIFsfOkcMnpRlyDATCsrtbGWdpo8AC2Ry7OVJR+9xRrJD2/xw85sJA/tUM1ZG0lzZ/TzWmvJT3c4IunsDp0lkI0vnYsfkNVrZaU21tYOkwegLbJ5rpHko7dYIvnhLX7YmY3koR2qOWsjae6Mfl5rLfnpDkcknd2hswSy8aVz8QOyXJFeKyu1sZZ3mTwALZPMkw0kH73FFskPb/HDzmwkD+1QzVkbSXNn9PNaa8lPdzgi6ewOnSWQjS+diyeQVbSyP/0E1K8vfWNt7DF5ANogmgebSD56iymSH97ih53ZSB7aoZqzNpLmzujntdaSn+5wRNLZHTpLIBtfOhdPIMtVffcdcP/9wKuvAk2aeIzK3p+OPAC9z6NIZij5GAmV3Ksj+eEerWM1kuRhrChr3q+kufs0j+WIkp+xpG5B35LO7tBZAtn40rn4AlmP0bWoTUcegEWNY8bzlXz0Fh8lP7zFDzuzkTy0QzVnbSTNndHPa60lP93hiKSzO3SWQDa+dJZA1mP098p05AHoFU44m4fkozP6Rbu15Ee0Kep+f5KHkubuU6B4jSjfIXf4KensDp0lkI0vnT0JZPPy8jBr1izccMMNHqPOyTMdeQAWD15LPnqLj5If3uKHndlIHtqhmrM2kubO6Oe11pKf7nBE0tkdOksgG1864+jRo+KfUrZs2YJzzz0X69atQ/Xq1V2f3YkTJ3D77bdj4sSJGDFiBAYMGBCVOXzyySeYOnUqPvroo6j0F+1OFi1ahCFDhmDu3LnR7tpWfzwAv/32WzRt2hQlSpSw1YdsFH8KSD7GnwfaGUh+eIsfdmYjeWiHas7aSJo7o5/XWkt+usMRSWd36Gw2CvHUKaecgk2bNqFGjRrxnYyN0X1+P0Pner8MHToUw4YNC5noO++8gwoVKri6gGPHjuGFF17AkiVLkJCQgPvvvx/XXHON4zlQw3v33Xdj8ODBqFOnjuiPQJnjbN68GS1btkSfPn3CjtOuXTuULFkSiYmJ4h9B/pVXXinaJiUlOZ4jO3jsscfQunVrXHbZZab9HThwAATlS5cuxcGDB5GWlobzzz8fHTt2NBQ8bNiwAePHj8c///wj6n/wwQdITU1V+//+++8xefJk7N+/X6zrvPPOQ+/evVGxYkXTOXz88cdCY05+1a9fX9C2dOnSov67774r5rZ3716kp6fj+uuvF3OTRVJAUkBSQFJAUkBSQFJAUkBS4GSgwO7duwW2kEA2xtx2QyN76NAhAfaSk5NNV5OdnS0Az+zZs0W9Dz/8UIA6s7J27Vo0bNgQt912G0aNGhWWSl9++SWeeuopLF68WK33/vvvo1KlShg7dixq1aolAHS4QhBLgHbRRReBUq4ff/wRDz74ICpXrowZM2bA5/M55hTnRI0xQaJRycrKwhVXXIGzzjoLzzzzDM4880wowJag8r777gtp9ueff4LaXq61ffv22LlzJzIyMtR6BLplypQRQosjR46Ago2VK1eKNRlpZN977z0MHz5czJF9du3aFVWrVsWYMWNEn08++SQ6deqEs88+G3///bfg4SOPPFKooMAx8WQHhhSQEllvbQzJD2/xw85sJA/tUM1ZG0lzZ/TzWmvJT3c4IunsDp3NRpEa2TjRnxrKmjVrRk2CMH/+fFCbSQX1PffcI7SsBH/aQu0d/WEJNAmqpk+fjv/85z9hKfDcc89h0KBBQiPJ9uG0onfccYcAb88//3xInwTCfPbyyy+HHY9AdcWKFQLIKoXm1zTDpkaTmlk+J5j87bffhHazSZMmeP3115GZmYlp06bhgQceEJpRBfRyvWy3detWlCpVStD81FNPFevhuvSFmnNqQ3/99VfLWuD169cLE4d9+/YFAVntGIcPHxZAlmNQUDBz5kwxP61pcaNGjdC2bVs89NBDoulPP/2Exo0bizkrWlltnzQNp1SKIF0W9ykgfWTcp3m4ESU/vMUPO7ORPLRDNWdtJM2d0c9rrSU/3eGIpLM7dDYbJdp4yu3VFBnTYj1hokl4avWonaOmTynUthI8Upt5xhlnYPv27cL8lOCsXLlyQtMXzrRW6adNmzZCa8hCjePll19uyuMGDRrgrrvuQq9evaIKZNnZVVddJUyMCax/+eUXYb7L+RPY3XTTTUJ7Sm0lfX9pI0+QqJhL33nnnQKQjh49Wp0XAew333xjuB5qY6+77jqhXTYr1GTTt3jVqlVBVcIB2YULF6JVq1agxleZT8+ePQ2BbNmyZQVwJ0hn4UFJbTW1uHXr1g0ak8ILmh537txZBb5uv4gn+3jyQ+atHSD54S1+2JmN5KEdqjlrI2nujH5eay356Q5HJJ3dobMEsvGlc8jo0QKyEyZMAMFQbm6uMC/t3r27MAGmXyoLtZIdOnQQ4I/avypVqghTVvp7Flbo80ofToJFFmoqn3jiCdNmBMzPPvusoa+mE40sB7z55puFL6hiWqudBINLDRw4UJjYstDEdseOHcKPlOCea/7uu+9w6aWXqs3oe8u+qAnVF66DAgCCcqslEo0sNaf0jSY4Jxg30shS00weaudMLfrXX38t2mnLo48+iilTpgitLevI4j4F5IfMfZqHG1Hyw1v8sDMbyUM7VHPWRtLcGf281lry0x2OSDq7Q2ezUaKFp+K1ipNaI/vKK6+gf//+gvbdunUTfqg0T6WGbsGCBcLEl36rSmEAJgK60047LSJ+0XSXQYmUQnNXmjCbFbc0sgTkBJoEbvT5JeDmumnOy0J/VQLAbdu2CW0ywbVecxpOI0utMzWh4TSyZjSIBMiy7a5du4SmnPXnzZsXYlpMjeznn38uNMMs1DRzjXqNLLXCBOTsoyhGa4toIxaBSvJD5i0mSX54ix92ZiN5aIdqztpImjujn9daS366wxFJZ3foLIFsfOkcMroTCQKBKoP9KECrX79+ePHFF0UEYn1ZvXq1eMbgQ2+99ZalVD9vv/02aJZL4EufU5rDEixqo/Fqx4uVjyzB3jnnnCOAXYsWLQTIZAAmBmKi3y01stT4MiKwUqi1ZBQzBnVq3ry58JtVSmE+svRf/fTTTwX4tRopOVIgS39daoUJun///XdDH1n6PBOwsyxbtkxoYkl/xUeWIPbNN98UILZ27doe2+En13Tkh8xb/Jb88BY/7MxG8tAO1Zy1kTR3Rj+vtZb8dIcjks7u0FkC2fjSOWpAltpHBnJS/D0Z2ZbpZKIRzVc/SZop03T58ccfF+lkGHSJGl6tOS79PhmQiCB548aNItIuNaVK4QtOs2fmrCXoHDlypAjQZJYzVRvsiW0ZqIlaZ5o406+Xz6n5vfbaa4WmldHK6Bu6Zs2aICDLVDgE8NTecl7aNDeMCMygSEyJY1Tow8oxqI0mWDz99NOFTy7BbU5ODig40BcKFxiZmtGJGUmYPsnUqtJXmXPmfJgrluCVZs/33nuv8FfmP65LH+xp3LhxwpSbGnRGLe7SpYswkebvLNS2M8AVQSyDS8kSXwrID1l86a8fXfLDW/ywMxvJQztUc9ZG0twZ/bzWWvLTHY5IOrtD52gA2TfeeAP8R6UTC+/5dJmkkoyF7oj/Z+9K4Gwq3/937tiXLNkjoU1FGFKI7EJSSouKiqJFP0pFiy3qRyXTplCpSFlafpS1hEiY0SKVtebfwpAlycjM/D/fl3PduXPPPefee857zx3P8/nMx4z7vu/znu9zzrnnK/CBpwAAIABJREFUe56NDiTW2eEzfceOHfHSSy/lK54buBfDucjoSDrUWM+HOhh1aUdOutDiYcOGKQJHckQiwwrFbgkr+5K8Mi9z9uzZKoSVnk0SREMMsssCT/TgkvQxnNfIwaWnlMQxUHr37q3yV0MJj4seR5JdekNZxIn5sSR+BvkleaanmKSRnlm2piGBDvTIshUR29XQe0tPbqAwXJfrsU2OmezZs0dVFmYVZP7Otjkkz3xpwGNkf1x6hEmgKYYnNng94seQbpJfYsg9kuC2atUKY8aMUZWrmSNL7y+LaQW2BKJ+XkCscsz8Z74sMKosEyfiwQJQhjD026ylkFvniKx7DAH5IvPWmSD28JY9otmN2DAa1GKbI5jHhp/XZos99VhEcNaDs5mWSCJcyU/IL0gySUDJT+hgYzcUktoBAwYohx05Cp/VyRUY7frFF1+YHiSL0JKXcS06luj8o5OK6ZnslGIlJx2RpcFYjZdhxfTSuSX0dDLnkgZkOOuCBQsUoaxXr16efFMSMubNklAyTJahvAz1fffdd93amu11GRLNPGJWCjaEZPHBBx8EybAXRG6AXrBC7HsQO8aOoZMriD2cRDM+a4kN9eMumOvH3E2NYk830T2xtuCsB2cniGyoNcqXL6/I7DXXXKOiN9mVhL9TfvjhB5XauHr1alx88cX5ppMMV6tWTXlxjXaZjOpk+1OSYUaMWslJR2QJCN3dDFl1UxhGS+LasGFDpKWlqR6lDHGl0VhEiWGuFHob6RmlMGSWY7wgDAtg/1vm9vLti1dFboBetUxk+xI7RoaX26PFHm4j7P76YkP3MQ7WIJjrx9xNjWJPN9EVIqsHXWsthkeWHlCm7xlCnhSOKzHtcdasWWCUKD2yTAlkxCadd0yFNIQ1aJjiGFhrx/hs27Ztqo4Q5zdo0MA/h04+/k1nmpWclETWChQnPmcobGpqqnKrP//882rJRo0aKWPR28q+taykS7c5TwYKW8CwQFG8hW9P2DKIbn4WevKyyBeNl61jf29iR/tY6Rgp9tCBsrs6xIbu4htqdcFcP+ZuahR7uomuEFk96FprMYhs8EgWxWWKXrAw7JfdSZgPy+K19MCyTg3/ZTtTOgsDxajLwxDiYGGUJ3NiWcCV6YyGkCMxBdBOdKoQWWsbRzUiJSVFeWLp2aRnlsI8WBYtMvrJ0hNLj6whdK2zh62IfQTki8Y+Vl4eKXb0lnXEHt6yRzS7ERtGg1pscwTz2PDz2myxpx6LCM56cDbTEqlH9siRI6oILEOAWbtmypQpqnAq21sKkY3AlpEkJ0ewrCNDaWQWNGKbGv4Y/UlZwXfo0KHo1auXqmLM3Fi6zw1p2rSpqjIsYh8BuQHax8rLI8WO3rKO2MNb9ohmN2LDaFCLbY5gHht+Xpst9tRjEcFZD85WRDaQr0SyIxaFZXgwnXYSWhwBcl4msjwM5sLyjUVgf9I5c+aoBGi62desWaNa87BqcWCfWb7hKFGiRARInNxD5QZYMOwvdvSWHcUe3rJHNLsRG0aDWmxzBPPY8PPabLGnHosIznpwdovItmnTBqeffrrKZ2WxJxat7dGjh1LHIrZsqWlV7ImFnhiVSjlw4ICqFyTFnuJ7XoTUzhYxF154oUqCZg4q28ewzDRd8YsWLVI9XT/77DNVVVnEHgJyA7SHk9dHiR29ZSGxh7fsEc1uxIbRoBbbHME8Nvy8NlvsqccigrMenJ0gsowqZc9YEte//vpL5cUy95VtRtu3b6/a77AlJknoKaecgnvvvVepZS6sISS2bLdjtPDkfEasBrbfIV+S9jvxPS9Caj906BBKliypPsvMzFRhxowtZ84sDcakZrYFYq9VEXsIyA3QHk5eHyV29JaFxB7eskc0uxEbRoNabHME89jw89pssaceiwjOenB2gsjefvvtWLp0qeq+wj6x9evXx0MPPaRILIUFoOhZpVeWRZ86duyIl156yd+phWNYxIn1gvr06aPmMIKVhaVeffVV7Nu3Dy1atFBz2JbUjkixJzsoOTimRo0aYFg0307QcIsXL1ZvLuhKHzhwoDI6e86K2ENAboD2cPL6KLGjtywk9vCWPaLZjdgwGtRimyOYx4af12aLPfVYRHDWg7MTRDa+Ow2tXYisZqswlpzhw3ShM7T4p59+Un/zzQbb85QuXVr1YArXu5Whx2zTw75MJ7vIDbBgnAFiR2/ZUezhLXtEsxuxYTSoxTZHMI8NP6/NFnvqsYjgrAdnIbLxxVm5qAN7EzGf9LzzzsP27dvzNPCNZZtpve6znN5ounVz3nCL3HXXXSqcuHbt2tixYwdycnJUMjTjzRlPzguavWU//PBDtG7dOuRSrBDWrVs35cE92YV40avNsIbChQuf7HAk7PGLHb1lOrGHt+wRzW7EhtGgFtscwTw2/Lw2W+ypxyKCsx6czbSQT9WqVStPl5X47igy7QnjkWVTXuaSBgtJYYUKFSI7apPRVaYvxKFG55quVSLtB/zRq2PEur6u+DUmXzAZ/b7rh+2Tt6tQYoYYs9Q1Y8VnzZqFQoUKgbHne/bsQfny5TF16lT1WSh55JFHwFY9JLMigoAgIAgIAoKAICAICAKCgCAgCESKwO7du9G3b18hspECF+l4XR7ZatddYbq1ZYd229r29ddf7x+Xi1w0S26G9b71SMlJwdAPhuKaHtco4nr06FFFWv/44w81nuQ0PT0dN954o/IwsooXPzv//PMxYcIENGzYUI0L9Mi++eabSE1Nxbp16/w6GzdurLy1bO1jfN61a1e88sorSu8zzzyjetvSO8x83auvvhqTJk2Cz+dTa3APDz74IFg1jPtjWWySbC+KvMnzolUi35PYMXLM3Jwh9nATXT1riw314ByoRTDXj7mbGsWebqJ7Ym3BWQ/OZlrEIxsn/N3oI7um512oceOVpke09K9dKo81nKSlpeHmm2/2D1mIheiETv6/X930Ku447w7/32zFw5xYyqWXXoqVK1diyJAhePnllzF//nxccsklePHFFzF27Fhs3rxZ5dIG5sjSu/vcc89hw4YN/jUbNGig8mdZEYyf803Ls88+q4grc3MHDx6sikpRB18QkCDzdxJagzjzb/aB2rRpEzp06KB63rLRsddEciu8ZpHo9iN2jA43t2aJPdxCVt+6YkN9WBuaBHP9mLupUezpJrp5iSxbtnTu3FlSxPRAnkeLG3xK52EkTGhxMChuAO80kaU3timaIg1pyEY2kpGMBlkNkF4iXeXGUhg+/PPPP6tQ4wsuuAAbN24EPar8IZk05JxzzlFVjumtjZTIss0PS2VTjBZArIxMMkvp2bOnKnP9xBNPYPz48aqi8vvvv+/XzVBmElyGO3tN5IvGaxaJbj9ix+hwc2uW2MMtZPWtKzbUh7UQWf1Y69Ao15AOlKFqwwiR1YN1KC1u8CmdR3NSEVl6FcPJ2f9b7ahHNtgba+iuUrsK/th+LJz4tNNOQ//+/fHwww+D3tm///4bNWvWVE2F2ZvJkE6dOoEVjxnyGymRDfbYkjwzfJieWwo9t9TNcXfffbcqRlW8eHG/7uzsbOUt5o3GayI3QK9ZJLr9iB2jw82tWWIPt5DVt67YUB/WQmT1Y61Do1xDOlAWIqsHZXMtQmTjZIFogCeRDRcafHDki44R2WBvrAETvbIlO5bEgUUH1H8xDJke0Kefflr9fvDgQVXRmOG8gR7Zc889F48//ng+j+zs2bMxbNgw1cbHT5SrVFH5tUZocSRElvMYpjxz5sw4WTYytfJFExleXh0tdvSWZcQe3rJHNLsRG0aDWmxzBPPY8PPabLGnHosIznpwNtMSDZ+K747zaj/pPLK6iKyZN1bBfw+AF48ZYu7cuYrAVqxYUbUToteTntKtW7fik08+UQWgSGhHjRqlcmTpOQ30yG7ZsgUkuexFy3xa5sIyFHjy5MlREVkmfRs5s0ZVZIY780bTpEkTL527ai9yA/ScSaLakNgxKthcmyT2cA1abQuLDbVB7VckmOvH3E2NYk830T2xtuCsB2chsvHFOZ/2aN4g6PLI3nTzTXlyY4M3n5SahNz7ctV/s5jSuHHj8Prrr6scVFYHJqFlCPGTTz6pcluZOztx4kSVN0sJJLL8m+T1v//9r8q7ZbXiOXPm5Cn2FIlHlusx7JhhzSxcxTXr1q2riLQUe/LYRVCAtiNfZN4yptjDW/aIZjdiw2hQi22OYB4bfl6bLfbUYxHBWQ/OQmTji7NjRDbcYTBHNpz8dMUltlCodHOlPJWK8036BEDnY//LnNgSJUqo37/77jvUq1cPp556KtjXScQaAbkBWmOUCCPEjt6yktjDW/aIZjdiw2hQi22OYB4bfl6bLfbUYxHBWQ/OQmTji7MjRFbHIZjlxubRzQLCNYFitYrh0I+HkIQk9XFmZiYqVaqkfj9y5IiUIbdhMLkB2gApAYaIHb1lJLGHt+wRzW7EhtGgFtscwTw2/Lw2W+ypxyKCsx6chcjGF+eEIbJhc2MDj+IbAOWBBdUXoCOOtcFhGG+RIkXAKsHMVa1WrZrHUPfeduQG6D2bRLMjsWM0qLk3R+zhHra6VhYb6kL6hB7BXD/mbmoUe7qJrlw3etC11hJNqqb1qvpGnFTFntyG1fDGrsd65OBYn9hw4oMPKUjBGqzxe2WrVq2qerYyP5VFl7RJRgZdwvbV0XNcvbr98S6NlC8al4DVvKzYUTPgFurEHt6yRzS7ERtGg1pscwTz2PDz2myxpx6LCM56cDbTIkQ2Tvh7EfgsZKEmamIndtpGpQqqYAd2oCiKqjmsWPz111+risXsHRuVREpKy5QBmjcHdtrfN6pUAXbsAIoe23e8RG6A8ULeWb1iR2fxjHU1sUesCMZ/vthQvw0Ec/2Yu6lR7OkmuifWFpz14CxENr4459PuRSLLTWYgA5mw79mshEqojhOezY4dO2LRokV444030Lt378hRz8oCataMjJRWrnzMu5qezvhma50+H5CSAqxZAyQdy++Nl8gNMF7IO6tX7OgsnrGuJvaIFcH4zxcb6reBYK4fczc1ij3dRFeIrB50rbV4lU9Z7/zYCAkttouUpnHsKfv222+rdjpswROx5OYCTZsC69dHRkpHjQIuv9y+ugULgI7HcnvjKfJFE0/0ndMtdnQOSydWEns4gWJ81xAb6sdfMNePuZsaxZ5uoitEVg+61lqEyFpj5MqIRAfeDJQHHngAzzzzDAYPHqz+jUoWLgQiCUsmKe3Q4RgBTksDsrPN1SYnA40aecIby03KF01UZ4jnJokdvWUSsYe37BHNbsSG0aAW2xzBPDb8vDZb7KnHIoKzHpzNtCQ6nxKPbHzPn3zax48frzyxvXr1Up7ZqMTwykZKSu0SYI94Y4XIRnV2eHKSfJF5yyxiD2/ZI5rdiA2jQS22OYJ5bPh5bbbYU49FBGc9OAuRjS/O+bQn+hsEMzjffPNNlRvbrl07LF68OHrUoyGlAQR4WXY2ugPYd3wHlwHonpSE/zRubOqNZXGqgQMHonPnztHvO8KZiXgD7NChg3pZQRuLHEMgEe1YkG0n9kh864oN9dtQMNePuZsaxZ5uontibcFZD85CZOOLM7KystSPIeyzet5552H79u047bTT4ry76NSTyHz55ZcoXLgwkpKSUKNGDVx55ZV46qmncMEFF6gWPFFLbi7WXXghhv3wAzYAyAVwOoDBAPrw7+Rk5DZogOxVq/IUbEpatAiFunbFMhLXYCIL4J5585DLMOQgWbZsGR566CGsWbNG7Z85vhT2xD18+DBKlizpn/G///0PLVq0iPrQAifyBkjC3759e4WjmYwePRqvvPIK/vnnH3Tp0gUvvfQSSpUqFdX4WbNm4fnnn1fVpc866yysW7cuzzq33347Zs6cqXoCG8Iq1BdffLH6c/ny5bj//vuxdu1aRzAoCIvYtWNBONZEOAaxRyJYKfwexYb6bSiY68fcTY1iTzfRPbG24KwHZzMt5FO1atVCRkYGqnugrWakaCRMaPGIESMwcuTIfMc3ZcoUVKhQIdLj9sT4Rx55BE2bNkW3bt2Qm5uL9evX48knn1Tkr0yZMpg2bVrU+yRhu+PWWzHu8GHcfnwVElrWUzb8pauGD0dmcK/a3Fy0HDIE6Vu34urc3Dwe2Q4VKuD8yZNDViomcSX5JkkMlG+//VYd04wZM0Iey9GjR1GoUKGoj9POxKVLl+Kdd95R5w9xZe5x+fLlce+994acbjWeBPavv/7C77//ji+++ALPPfdcnnUmTpyoiHvfvn1Drk9b33nnnRg0aBDq1q1r5xBkjCAgCAgCgoAgIAgIAoKAIOAoArt371bPq0JkHYU1/2IF1SNLEstwXEOqVq2KPXv2wOfzYdKkSXjhhRfyePwaN26sxt9www3qDcr06dPRqlUr//x69erhscceQ506ddCyZUscqlcPyV9/jaSAAk6GN/b3Dz7AA0OGgN5UeoSvueYajB07FsU+/xwru3bN55G9ol8/DHzxxXzG4du0SpUqKVJHL3mgfP7552rdzMxjLYlGjRqlPM1860PPJsOo6RklOZwzZ45/asWKFTF79mz/sb377rvKy8sL7cwzz8Szzz6LSy65RIWkWnlkW7dujSuuuEIV0KLQg9qmTRvs3LkTxYsXz3c8dsczDDw1NTWkR7Zs2bJhi3XdcccdOPXUUxXJFzkWWmxlR8FJHwJiD31Yu6VJbOgWsubrCub6MXdTo9jTTXRPrC0468HZTIt4ZOOEf0HIkb3sssvQvXt3/Oc//0FOTg4YcnvTTTfh4MGDClV6+l5//XVs2EBf6jFp0KCBGt+nTx+wwjHfpLDnLGX16tXKI0pPIYk/yWzrunXRa8UKNAVQJcBWuZ98gktGjEDz5s3BsFt6cEk4GfI7etQoLKtbF91//PGYRzY5GZeVKIHuI0fiP4MG5bP4999/r7yxvBkls6pxgJAk8xj37TuWbUvP+hNPPAF60nmsR44cwbhx49QxfvDBB/6ZJIL8mxh9/PHHIPH76KOP1PHz//v164effvoJp5xyivqceblmocX0wpIkGzmp3CfDfqnzwgsvzHc8dscTd9oo0D5cjLbhXil8MXHbbbcp7ytfThhCrzD7BS9kLrOI5Mh67ByQnCWPGSSK7YgNowAtximCeYwAemy62FOPQQRnPTibaUl0PpUwocXBBkh04Hk8JGnMKS1atKginiR19Ig+/fTTiqDSe0kCZkZkN23ahIsuukgRV3o1Ga5KMkcvLmXLli14evx4LJ42DduzstAEwMs+HxqlpGDtCy+g0+WXK0+pQbDoEevfvz+2bt2KZePGoftDD50ILa5XD91vu02R6GChJ7Zjx45+Am5FZElEA4+J5DYckSU5Z4Gk++67z780CTj3ev3111sSWZJr4kxvtiEM/SWJDJWra3e8GZGlx5n5zgxfZh5sz549FZHljyGTJ08Gf7766qv43sE8ol2+yDxiiOPbEHt4yx7R7EZsGA1qsc0RzGPDz2uzxZ56LCI468FZiGx8cc6nvaAQWcMjaxBPhhrTe0lySo8ryaUZkeUchteSwJLQValSBZ9++ikasc9roCxciN86dcIQAJ8DyPjkE8z+6y81p3Tp0mokc1UNoUd42WefoXv79tjHkOQmTY55ZI97j4ONEalHlkTP8FhyLSsie/7552PHjh15PK688TGEmkWT7Hhk586di7Zt2/qPlYQ/nEfWzngzIhuMDwtLMQyZhb0MEY9sXpTki8xbN1ixh7fsEc1uxIbRoBbbHME8Nvy8NlvsqccigrMenIXIxhfnk4LI8iBJXkmQmCfLYkQLFixQIbSGkKyyKjDDVykM0WW/WZJZ/j9zTfPJ8bY6365di/oAdmdmYvOWLbjqqqsUYd67dy8qV66sCk6RZDLPVoUEd+2KfaefDqSm4rInnjAlsrwJlStXTnkXg3NkQ4UWB3tf6YFmmC1/KH///bci2CTl9FqzrQ9JND2wwWLnBnjppZeq+SS9FObI0hPL4w6VI2t3vF0iy1xnjg0ksqxszCJlRnVnj11e2rdjx47aN3USKxR7JL7xxYb6bSiY68fcTY1iTzfRPbG24KwHZyGy8cX5pCCy9Doy15OFl+jlfPjhhzF+/Hh89tlnyvPKAkesdMyQVIPIsnputWrVULt2bZWLaYTf/vDDD/jwww9x3XXX4fTTT8eBjz7CQ7feimWlSuHHjAxVGZlrMmSXOhmqSznnnHOwceNGrFixIk9ua2A+b6hToUePHqqA0t13353nYztEloSVbYcYhnvGGWeoNj4Mj2b1YOpl7jBDmt977z3lbWY+76pVq3DuuecqAk6CSg8v8Qslr732mqpYvGTJElWUioWy+EKA/x/NeGLHG+9bb72l9smwZdqMIeIU7pPkm2SclaiZe0xchgyhT/yY0F6sSk3SLCJ9ZL12DsiDhdcsEvl+xIaRYxbrDME8VgS9NV/sqccegrMenJ0gsixQyohFcgw6gpo1a6YcMuQOFD6HsxBtKOGz8bXXXhvyM3Ka4E4tTFmkM89KJEfWBKElWIKBGIhUpKId2lnhGNXnJGks0GQUKWKBo6uvvlp5RkmQSHxIuHiSsBgUqxUzZ9Yo9mQoJYFl9WJWHjNaEfF3jqOXkzcJkiqSVXptzz77bDV1165dijTOmzdP5eQaQt0M5w0s0mRFZElGuVZwb1Q7RJZ66YkmsSxRooQKNebfRrEnfs4Kx7yAtm3bpggjc4NffPFFVUyJlY+JGVvsmAnXZIgvSTArGLOnrBFWzbxkEnf2ejUk3Hh6V2+99dY8qmrWrOkn0qwW/c0336hwbfY4pveVx2PkIlMXve3BRaKiOokKyCT5IvOWIcUe3rJHNLsRG0aDWmxzBPPY8PPabLGnHosIznpwNtMSSaomnTRMS2zSpIl6xh02bBi+++475Xxj7Rk6eowuJYa+V199VTnljHo+ofZBIstOIixwawif9RntaSVCZEMglItcNEVTrMVaNEETrMEaJCHJCkvHPifZHDp0KHr16qXChq2ERaFInNiuJlB48jDkmJV+GTJMr2Eo4VsQnkTFihXD4cOHFcFjISmSMApJIgsj0RtKj6aZ8O0JyfPll19utWXHPucNMCUlReFUvz4Dp70vxInEtn379t7frKYdyheZJqBtqhF72ATKw8PEhvqNI5jrx9xNjWJPN9E9sbbgrAdnMy2RENngNUhayQvYapNOnFDSsGFDxR+mTp1qeqDkIKwPFNi9xC4qQmRDILUQC9EJnfyfLMACdERHu5jGPI6eQYb7MiSYbnozAkpFPIl4gtBLaBQzMjbAKrlsD0NhZWGGAIQSenwZxsx2OKx0zFxOEmDmdlJYqIheT4bI0jPqJZEboJesEf1exI7RY+fGTLGHG6jqXVNsqBdvahPM9WPupkaxp5vonlhbcNaDs5kWg8jSq2o4sDiWHlEjZc5sLjnDWWedhW+//Va14QwWptexY0g4DsI5JLIksWyNSS8sUxXZqvPUU0+1BEeIbBBEhjc2DWnIRjaSkYxGaKTVK8vwV7ZuoXeULnuG+YaSMWPGqHY9N998s590Bo5jBWTml1LCeXcNwsvQYHoLeQLRK8swAIYKMJeW5LZ69erIyMiwPKl0DpAboE603dMldnQP22hWFntEg5q35ogN9dtDMNePuZsaxZ5uoitEVg+61loMIhs8cvjw4SrVz0yY8mh0Wlm5cmXIYXfddZcqHkuSHE5mzpypUguZX8sWoAxZZltRpl+yJWY4ESIbhE6wN9b4WLdXlh5ZembHDRuGIT16WJ+JxgiG/lavrv5iBWGGCFP4loMkNFRoMOPd3333XUyYMEHl4fLtCnNR6eVlHHwgkabrv0yZMvb34/JI+aJxGWBNy4sdNQFtU43YwyZQHh4mNtRvHMFcP+ZuahR7uomuEFk96FpridYjO2DAAMVTSGLp6AoWOuVYx8ZolWm9kxMjyEHq1KmjirQGR5sGryNENgCRYG+s8VE8vLIsuMSCQJcVLozP/v3Xvv2rVGHZMGQXKqTebhw5ckSFKP/yyy/Ke8vc22BhISfGt7NYEkktPb2PPvqoqqhLIstqyYZYhQfY36gzI+WLxhkc472K2DHeFsirX+zhLXtEsxuxYTSoxTZHMI8NP6/NFnvqsYjgrAdnMy3R5Mjec889qjPK8uXLTasUs7MHi52y+GzFihUjPkjOYXgxUx3DiRDZAHTMvLHGEKe9smw1wxxWVgcOFuNtRKGkJLCecBn2grUSnw9ISQHWrMEvGRlgJV1WRGauK08mElquG+ymZxubH3/8UbX5IanlScexDBtgiDFb/Jxyyik4cOAAWECqX79+VjvR9rncALVB7aoisaOr8Ea8uNgjYsg8N0FsqN8kgrl+zN3UKPZ0E90TawvOenB2gsiy+CudbO+//74KGWYEp5mQT7CTSnAhWjtHS3JNHsK8WYYvC5G1gZqZN9aY6oZXNhyRpV6DYLIWse3gYvZc6thRkVLmurLVztdff63c/nv27FEnXqtWrfIgwrY/+/fvV32hjF5QXbt2xfz589U4hgaw91NqaqrqU2sUkLIBq+tD5AboOsRaFIgdtcBsW4nYwzZUnh0oNtRvGsFcP+ZuahR7uomuEFk96FpricQjy5zXGTNmKG+swReogSmH7CtrCItAkX98/PHHYMueYCG/YUvNq666CgcPHsTIkSPRo0cP1XKUObIPPvigcqKxiJRVwSnxyB5H18obaxjBSa+sFZEdPHiwylu9rUIFTN27F8jONj8jmQzdqJHyxiIpCZMnT8Ydd9yhWuHwROrSpYv6l/1T+f+GMIadIciUwPxXvm1hT1sKw5EZq963b1+0a9cOixcvtr4yNI2QLxpNQLusRuzoMsARLi/2iBAwDw4XG+o3imCuH3M3NYo93URXiKwedK21REJkzbqosP8rKw8bwmJNbIvJziu/7UJGAAAgAElEQVQ+RosGCdcx5pCHMDI1PT1d8ZBq1aqhQ4cOGD16NCpXrmx5AEJk2Sf1eN9Yo1KxGWpOe2VJZBmmO2fOHNX2htWBaVjmtbJyF8kk31ZUKVcOPffuxX4AbwC4CsCFAAJrifUHkNSlC16eN09tnxWIx40bp0IADE8q/x0yZIj6f0N4klEXe8geOnTI3+qHN3C+Tfnjjz9U5WS2+eH+6J397bffLE8sXQPki0YX0u7qETu6i2+kq4s9IkXMe+PFhvptIpjrx9xNjWJPN9EVIqsHXWstkRBZ69X0jxAiC8CuN9Ywj1NeWRJZvpVg1S/GgrMCGCsLv/baa4pckkTSE/r333+jV/nyKLR3L97IzQWp6kAAW0leARz2+VAlKQmLV61Ck4suUtuki37u3LmYOHGiqkRskFl6WUmcDWFpa/aX5V62b9+e5wxk+x269klomR9rVCtmiDLbA3lB5IvGC1aIfQ9ix9gxdHIFsYeTaMZnLbGhftwFc/2Yu6lR7OkmukJk9aBrrUWIrDVGjozIysoCfwxhQSK2lyH5CmzgG6kyemObJTdDelI6cpJyLKf7cn1omNsQq7JXIUnRyOiFSdKsxvXAAw+oRXbu3IkaNWqo/NbWrVtj165dipCuWLECHRo1QtW0NOWRZYDx6QCmA7gMwDsAxpx+OtK3bPFvJiUlRcWWM46d4cUky1deeSXq1asHNig2hInUPXv2RNOmTZWecHLmmWeq6seffvopWrRoEf2BOziTXzQMdW7fvr0qbCWSmAiIHb1lN7GHt+wRzW7EhtGgFtscwTw2/Lw2W+ypxyKCsx6czbSQT9F5RkdaqDY68d2dtfaE8ciyKS+TgYNlypQpqipWtPKv71/0a98P+4rts71E2cNlMXnxZBTOiY04May4d+/eeUghiyqx/Q0Tnav9XA1V762K9R+tV5XBGv/xB97++2/4cnLAJjq/A3jN50O7okVxxnXX4crj1Y9ZVeyGG27A4cOH8eKLLyqizxP17rvvViHEbLNjxLmT4DJvlkQ2VGueQFBGjRqFtLQ09O/fP2Tytm0AZaAgIAgIAoKAICAICAKCgCAgCMQVgd27d6saOEJkXTaDWx5ZbjsDGditmtzYk4qoiOrI3/zX3uwTo4I9svTA8m3I1m1bUad2HeBXoPqM6vi/If+n/r/1OefgzaVL1QKbATQCsI75soULY+v27ahUqZL6jCHJDFVmgjWrEbPiF/FjaDBb6tCryspgFL4cIHFmASj2rg0nDz/8sOopy6plXqlcLG/yIj3rvDle7Ogtu4g9vGWPaHYjNowGtdjmCOax4ee12WJPPRYRnPXgbKZFPLJxwj/RY7oJG/NS2dOV1YRJPEkQ2ed12OfD0KlmJ4AVnC4A0A2KlN5888144/vvgbQ0VcGYTXT2Fy+OWh07qsJQhqxcuRKXXnppvrxX6vv555/Bz5s3b66GM7SZvWHp8R4+fHhYa77xxhu49dZbVdgzw4u9IJLD4gUrxL4HsWPsGDq5gtjDSTTjs5bYUD/ugrl+zN3UKPZ0E90TawvOenA205LofCphQouDDZDowBtENrBq8cUXX4ypr01Fj+o9sH7peuQMyAFYIPhvKMLbq1cvTLvxRuB4T6Y3AfQGMHPmTFx33XV+iAzCGdwqh38vXboU/JwhzRTmzX700Uf52vKEOuHXrVuHJk2aoGLFiip/1wsiN0AvWCH2PYgdY8fQyRXEHk6iGZ+1xIb6cRfM9WPupkaxp5voCpHVg661lkTnU0JkrW2sdUS+CspHAbDN679Qha3OqFkTaNoUWLsW8886C1ds2QI2Fv7mm29QqFAhtddHH31UhQvT2zpp0iT//g3v62OPPQbmu1KYG/vVV1+polDdunULe6ysnlyqVCk1hkSWhDbeIl808baAM/rFjs7g6NQqYg+nkIzfOmJD/dgL5voxd1Oj2NNNdIXI6kHXWosQWWuMXBmR6MCHAsW0n+35AL4HPlnwCTp17AQsWYIj996LVklJ+HLTJrXU/Pnz0blzZ/U7Cz3RSzt+/Hh/RWT+P/9mEakbb7wR06ez5jFUSDMTvNesWYOLjrfuCWew2rVrK0LNUGY2MI63yBdNvC3gjH6xozM4OrWK2MMpJOO3jthQP/aCuX7M3dQo9nQTXSGyetC11pLofEo8stY21jbCtJ/t1QDeB/pP7I+XB76Mzz//XJFWekSZ80q55pprMGvWLPU7w38ZBhxMNtlXlu18SFhJXFndmIWgeLPmOiS1VtJjUA/MfW4uqtSqgi3fbkHJkiWtprj6uXzRuAqvtsXFjtqgtqVI7GELJk8PEhvqN49grh9zNzWKPd1EV4isHnSttQiRtcbIlRGJDnwwKKbeWA5kr52ngIoDKmLnSzv9/WuZF/vee++ppYoUKYLffvtNFYUiIT148KAKN2bfWEP494UXXohTTz0VLLf9559/qt8pbNVDUhtOuMfGfzVG2gVpwC/AwPsGYuJzE12xr91F5YvGLlLeHid29JZ9xB7eskc0uxEbRoNabHME89jw89pssaceiwjOenA205LofEo8svE9f/zaTb2xHDENQB8AbYAFSxegIzqqeWzfs2XLFhQvXhz//PMPUlNTVb7r22+/jbPPPhsbN270581yPMlt6dKl1dy9e/cq4nv++eejXLlyitRaiX+PCwF0gupFu2LFCn8FZKv5bnwuN0A3UNW/pthRP+bhNIo9vGWPaHYjNowGtdjmCOax4ee12WJPPRYRnPXgLEQ2vjjn057obxACDyisN5YDvwRwCYDTgCb/1wRrsAZ/HfhL9YWlsG0O+8HSu7pnzx7llf3iiy/AKsjBUrVqVdVnlqHH7DHbtm1b1K1bF9+zrU8YCd5j0m1JyH09V+lYvXp13M4OuQHGDXpHFYsdHYUz5sXEHjFDGPcFxIb6TSCY68fcTY1iTzfRPbG24KwHZyGy8cW5QBPZsN5YHvleAOWPQ3AAWFB6AYovL45WrVqhRo0aSE9PR7Vq1XDkyBE1aOjQoRg7dmxIi7Vo0UKRXBaDys7OVi197PSFzbfHbwHUB0qXL40Dew7E7eyQG2DcoHdUsdjRUThjXkzsETOEcV9AbKjfBIK5fszd1Cj2dBNdIbJ60LXWkuiOQQkttraxqyMMT+d6rEcOcsx1VWbPGyBpXRIapzTGDc/dgMGDBqs+sB988AGuvfZazJ49G/Xr11fhxWb5rn369MG0adNUe55ixYrh/vvvV1WOZ8yYYao7pMeY/W1PA+ADjv57FMm+ZFdxMltcvmjiArvjSsWOjkMa04Jij5jg88RksaF+Mwjm+jF3U6PY0010hcjqQddaixBZa4xcGeEo8BkZQGam/X1WqgRUr25/fJiRWchCTdTETuwMv15LACsATAeq3FgFbXu3xfQ3p6uQ4scffxw7duzA008/jUGDBqFOnTqma40ePVqNv/XWW1Vu7LPPPovBgwfjmWeeMZ0T0mP8z/H+tgDm7JuDq8uwtLINcRhr+aKxgXkCDBE7estIYg9v2SOa3YgNo0EttjmCeWz4eW222FOPRQRnPTibaXGUT8XhUMQjm5UF1KwJ7LQgkoHGqVIF2LEDsKjya9eeGchAJsIT6dH9RuODKR/grPpnoWXrllizdA2+++47pYKFm8qWLWtL3TvvvKP6yAbKf//7X9VfNpSEzd8tBiALqL+9PjacscFfTdl0Iy5gLTdAW2b3/CCxo7dMJPbwlj2i2Y3YMBrUYpsjmMeGn9dmiz31WERw1oOzENn44pxPu2NvEHJzgaZNgfXrgZwwob3GDnw+ICUFWLOGZXu1oUKP6QMPPIAzzjgDXbp0waRJk1SOa6REdtu2bTjnnHNw9OhRNZetej7++GNVvTiUhM3frQrgDwBpwIKGJ6opm4LiAtamN0CHPb/aDH2SKpIvMm8ZXuzhLXtEsxuxYTSoxTZHMI8NP6/NFnvqsYjgrAdnIbLxxdk9IsuVFy4EOnWyf4QLFgAdj7XA0SULFizA5ZdfjuTkZFxyySVYuXKlv0pxJB5Z7pcvAdiKh4WiSpYsac47kYumaIo0pCEbx0hzHjkPwCbAt9SHlDYpqppyEizIvcNYh7wBuuD51WXnk1WPfJF5y/JiD2/ZI5rdiA2jQS22OYJ5bPh5bbbYU49FBGc9OAuRjS/O7hJZw1OYlgYc93KGPNzkZKBRI8e8scxPfe6551RoMFvnPProo+jbty+WLFmCYcOG4aeffsJpp52GJ598Ep07d1Y/ixcv9m+tZcuWWL58uZq/ruw6DMRApCIV7dDOEWtZVlNuDmAVgNkAegALEIFX1iGsQ94AXfD8OgKoLGKKgHyReevkEHt4yx7R7EZsGA1qsc0RzGPDz2uzxZ56LCI468FZiGx8cXaXyHJ1u55Ch7yxJKkNGjRAWloazj33XOzcuVP9UNhWZ86cObjsssuwatUqFUrMSsQMAz7zzDPx228sGQwMGDAAL7/8Mv7c+yc6lu2ItViLJjjWZ9bSM2phT1vVlLsCmA9gMuDr60MKHPbK2sDa9AZo154GDjZ0eewSKFDbkS8yb5lT7OEte0SzG7FhNKjFNkcwjw0/r80We+qxiOCsB2chsvHFGVlZWerHkF9//RXnnXcetm/frryWMUtuLpKbNUPShg1ICuGVzU1ORm6DBshetcqR3NitW7eiYcOGeOONN1TIcPHixdUhDBw4EEWKFFEViA255ZZbVF7rI488ArbPYR/Yn3/+GSzcxNY5MzNn4voK1/vHzzs6Dx1yO8QECasp1ylUB7uSdpmvczOAtwGMAzAEqJxbGVuObkFRFA2v20GseQOkl7p9+/YoXLjwCb0WOoyBTts1JtBP4smmdjyJMYnnoYs94om+M7rFhs7gGMkqgnkkaHl/rNhTj40EZz04m2khn6pVqxYyMjJQ3aGOLDqPKGGqFo8YMUK1mgmWKVOmoEKFCo5gVjE9Hc1C6DAWXzV8ODIbNnREFxdhnitzX0lqzz77bPTu3RvTp0/Ht99+i0KFCvn15OTkKO9s//79MXHiRJXXet111+HQoUO48847UWt7Lfx8+s/I8eXAl+ND7f21MX75+Ji9spnFMnGg6AHT430/9X2sfH8l2t7YFp37dUaZrDKocNieLXRgbaXDLbs6doLIQoKAICAICAKCgCAgCAgCgoBLCOzevVulNQqRdQlgY1nXPbJUZOLFc9tr988//yiSvnDhQjRr1gxlypTB2LFjQyJ6++23q1Y7rGLM3rEkwNgLIKj7jhNeWSuTcs9jxozBHXfcgRdeeMFqeN7PHcI67Js8Bz2/kR2cjI4UAXkjGyli7o4Xe7iLr47VxYY6UM6rQzDXj7mbGsWebqJ7Ym3BWQ/OZlrEIxsn/B1rvxO8f7PcSodzKH/88Uf88ssvaNGihQolfuKJJ/DBBx/gtddeQ6dOnTBz5kywmBPb5DCPluS1bt26KrSYv7NI1PYd21G7Vm349vqQU/ZE66BkJKMRGlnmyi7BkpgKRHEPgwYNUt5h7jdicQBry9wKq1xZh+0aMQYyQSFgaUfBSSsCYg+tcLuiTGzoCqxhFxXM9WPupkaxp5vo5iWybAPJgqZ5UsT0qD/ptbjGpzQhmzChxcF4uAZ8cAVjhysVG8fB8OF+/frh+++/h8/nw4UXXojU1FT176efforHHnsMmzZtUp+xKBRzZvlvIJGdtmMa+tTqE9IjSz3hqggbxZxiKRA1bdo0tZ8OHToob3LE4gDWll80ZhWpXbJrxBjIBCGyHjwHLK8rD+5ZtpQXAbGh/jNCMNePuZsaxZ5uoitEVg+61lpc41PWqh0ZIUQ2FIzBXjwPeu0MImrW49XKKxvcWsdW65wgrD766CNceeWVaNKkiaqqHJXEiLWtLxoHPL9RHZtMso2ALTvaXk0GxoqA2CNWBOM/X2yo3waCuX7M3dQo9nQTXSGyetC11iJE1hojV0a4CrzhxVu7FmjSxLG+sU4CYdnj9biyUAQ1mARbkV6zfa9YsUKFP7Ml0ObNm6M6vH8OHULHypXR4OBBpEaBta0vGgc8v1EdnEyyjYAtO9peTQbGioDYI1YE4z9fbKjfBoK5fszd1Cj2dBNdIbJ60LXWEgmfevLJJzF37lz88MMPqtsK6/r897//VZ1VDGFx2s8//zyPYhamnTRpkulmcnNzMXz4cEyePBn79u1D8+bNVXvRs846y/IAxCNrBtGSJeyFA6SmAu3aWQKpc4CVN9bYixlBNSPBkXplv/vuO9SrVw+nnnoqWPUsGlm+fLnqm+sDsP+jj1DqiisiWsb2F02Mnt+INiWDI0bAth0jXlkmRIOA2CMa1Lw1R2yo3x6CuX7M3dQo9nQTXSGyetC11hIJkWUNn+uvv15FYrKGz7Bhw0AuwDRJdlShkMiyEO2oUaP8ykuUKIFTTjnFdDMkwyTJTFlkKyCmVzIFk+sWK1Ys7EEIkbW2sedG2PXGGhsPJKhmJDgarywrnbHnVHJysirWk5SUFDFW7KN76623qnnMDW7dunVEa9j+okkAL3tEB17ABtu2YwE7bq8ejtjDq5axvy+xoX2snBopmDuFpDfWEXvqsYPgrAdnMy2RENngNTIzM1GpUiXlgWWEpkFkWdOHBWHtCL2x1apVw/33348HHnhATdm/fz8qV64McgQS53AiRNYOyh4aYxDR9ViPHJyoVGy2RR98SEGKv4KxFQmOxCvLPrbGGxiedOHetpjt7/HHH8fo0aPVx6zc/Mgjj0SEdkQ3QA972SM66AI4OCI7FsDj99ohiT28ZpHI9yM2jByzWGcI5rEi6K35Yk899hCc9eDsBpHdsmWLCv+l9/SCCy7wE9mNGzeCBLVKlSq44oorlIeVXtlQsm3bNtSpUwfp6emqqK0hjNbk3xMnThQiG99TxFntWchCTdTETuy0vXAVVMEO7EARFEFTNEW0BaKCFeb+8guKnXkmjvz7L3bMm4eaVauG31OlSkD16nnG3HTTTZg+fbr6vy5dumDevHm2j4sD5QYYEVyeHSx21GsaXmfMR+HbTqYHBIvYQ6893NAmNnQD1fBrCub6MXdTo9jTTXRPrC0468HZisgyjPe0007zDytatCj4YyY5OTno1q2bymlduXKlf9irr76KmjVrKi/rN998g4ceeggXXXSRyq0NJatWrVI5sb/99huqBvCInj17qkjPd999V4hsfE8R57VnIAOZyLS9cCVUQnVUh5U31ljQllc2KwuoWRNVdh6j1OkATrxHMdlalSrAjh1AwIVxySWX4Msvv1QTypcvr3JtIwlRjuQGSA/y33//rXTRexzuArUNrgx0BIFI7OiIwpN8kWuvvRazZ8/Gww8/rPJSgkXskfgniNhQvw0Fc/2Yu6lR7OkmukJk9aBrrcUILQ4eyZfdI0aMMF1gwIAB+OSTTxSJZZqhmTBtsG3btqD3lp7XYBEim5ERFkBrE54cI2ItEJUPpeM5p3XXrsUPzG8FEDa71ecDUlLyVYBmDPyuXbv8y7MSWmD1Myvr2P2ieeedd9C3b1+QzFLKli0Lhj7wjZFI/BGwa8f477Rg7ODSSy9VXz58m/rhhx8KkS0YZs1zFHJN6TeqYK4fczc1ij3dRFeIrB50rbUYRDYSj+w999yjnh1YsJXFmcIJHUilSpXCggUL0LFjx3xDJbRYiKz1WQrY9sYai9nyyi5ciGadOmE1AAYMXGW1k6B+vAcPHkTp0qXVLIY3Msb+tdde8xd/slqOn9v5omGboHbt2uHIkSN5lmS4AkMXROKPgB07xn+XBWcHbJm1detW9XaUb0mDReyR+LYWG+q3oWCuH3M3NYo93URXiKwedK21RFLsiXmv9957L95//30sW7bMVnucL774Ai1atMDXX3+N+vXr59uQUeyJhZ5Y8Ily4MABVURKij1Z2++kGBFrgShTkHJz0aVcOXy8fz+mArjNbGByMtCoUT5vLIkrT2qGFNNbOm7cOPTr1w+Mr88jGRlAZuhQ6n+PHsUXK1eieYsWKFyo0LFpAbm4fEi/+OKLsWfPHlx99dWYNWsWbrvtNlXim0WmHn300ZPiHPD6QcoDg14L8e0o35IyjJ//sh9coIg99NrDDW1iQzdQDb+mYK4fczc1ij3dRFeIrB50rbVEQmTvuusuzJgxQ3ljA6Mny5Qpo54j+IKcn3fu3Fm15mSO7KBBg1TkbGBv2XPPPVelNV111TEXGNvvPPXUU3na73CutN+xtt9JMSKWAlFFYZ7oTfBuatMG0z/7DE8DOPYexUSCvLEcxQuhe/fuaNy4sapWzBOaVc9IcP1yPBcXO+0Xt/qqfHk8ULcutu3YoZLH+baHOngRsWra2LFjlb6bb74Zb7755klxDnj9IOWBQZ+FAiMhqDUtLQ0NGzYUIqvPBFo0yTWlBWa5bvTDrE2jXEN6oBac9eBspiUSImtWw+b1119Hnz59kJGRARZxZW9ZviSvUaOGeran0yiwswnXMeZwX3xOZ04uHVksHkUP7ksvvaT60VqJtN+xQqiAfB5tgSirw7/3nnvwwosv4pGkJDzBvNlgMfHGctiECRMwePBgFd6bmpqqynTz5N67dy/4dkeJ0f91/Xogx7rdUE5SElKKF8eG47mwXILkeNGiRf5qaCxyw2I3TZs29ReasjpO+dxdBOSLzF18A1ffvHlzni+Ht99+G7169ZIHcn0m0KJJriktMMt1ox9mbRrlGtIDteCsB2cniGx8dxpauxBZL1olgfZk9IG9C8CLZvsO4Y3lUMbZv/DCC/7KqczXY9L3woUL0aFDhxOrLVwIdOpkC5XZAK4FVO4tq6lxTcbZ+1hs6rgwXOHCCy9UBZ/+/PPPiKok29qEDIoYAfkiixiyqCcwZ9xoXM5Fhg4dqqIUAkXsETW8npkoNtRvCsFcP+ZuahR7uonuibUFZz04C5GNL875tEfiCvfY1gvUdgyv6g3ly2PG/v1AdvaJ4wvjjeUgxtCTbDKUgLmxDPWld2jYsGEYM2bMiXUMr2xaWt71g5DM9vlQr0gRbDp8WIUomJUNZ+XikiVLqtmZmZmoUKFCgbJJIh6MfJE5bzUWNytUqFCelzjU8t577+G6667zK7zyyivxwQcfCJF13gRxXVGuKf3wC+b6MXdTo9jTTXSFyOpB11pLovOphPHIZmVlgT+G/PrrrzjvvPOwffv2PA18rU0mI5xEgDmmLNTUMSUFCxj+GyRH581DbqB3NeBzhvz+9NNPqiR3mzZt8NZbb+H2229X+Xpr1qzJs1LSokUo1LVr2K2/DeBmAOXKlVPr+sOTQ8yip5ax/MybZS9bkfgiwAeGxYsXo3379ihcuHB8N1MAtDPPnKHzAwcOVAUUAoVREAzp5wsc9m1mBWMWVAgUsUfinwRiQ/02FMz1Y+6mRrGnm+jmJbLy/a8H61BayKfYQofPxOH6wcZvh+E1JwyRpXdt5MiR+Y5mypQp4lGL49lFwsnKY0zI/jInB2W2bYMvJwc5Ph/2166N5ePHA0lJ+XaYk5OjcmOPHj2KV155BewnywRvJotT2IaH1Yz9kpuLlkOG+NcPXnB/UhIaFiqE7f/+qzy7PXr0CIsKQ6IZYszwZjZqFhEEChICLKTGQgqMPODLpmRGRxwXvjCaM2cOmjVrBjYiZ9j9zJkzUaRIkYIEgRyLICAICAKCgCAgCFggwBfadEgJkXX5VBGPrMsAR7k88+1IBM866yx8P2FCHq9pOG8sQxlq166tQh/ZL4r/UvhwvW7dOkyePBm9e/fOsyszr+xfAC4H8AWgCkZt2rTJHzpsdlgksCTQDz74IJ544okoj16mOYWAvPl2Cslj6/znP/9RFf8oS5cuxaWXXupXwC8skttRo0bhueeeU3nia9euVXnjhog9nLVHPFYTG+pHXTDXj7mbGsWebqJ7Ym3BWQ/OZlrEIxsn/BM9pjtOsDmu1ugFW7FiRexii5ymTYG1a4EmTfL1jQ1Uvnz5crRq1UoVY2KvV0MMz/s111yjer7mkRC5soEklqHEDE9pQt0Wwgd49rai55ZVjEXii4DkIjmLf9euXTF//ny1KF/WsEebIZdffrkK52fUA39WrlyJ6dOn48Ybb8xDZD/++GOVxy6h3s7aRtdqck3pQjrvA7lcN/pxd0ujXENuIZt3XcFZD85mWhKdTyVMaHGwARId+Piets5pN+xAjyqLyyQtXQoMHAikpgLt2pkqeuONN3DrrbeqnEi2xjHkq6++Url97DfFcId8D9FBFYz7ApgKoGzJkli8bJnqF2tH+LDRpUsX1KtXT4UYi8QXAfkicxb/888/35/3yt/Z082QBg0a4OuvvwavARZ5YrE19lUOjEwQezhrj3isJjbUj7pgrh9zNzWKPd1EV14A6UHXWkui8ykhstY2lhFhEGDD41KlSqkRf/31l/93K9CMtj133nknJk2a5B/O3FmGB7Oa8LJly/Dzzz/jgQceUGGQ/fv3P9FXNi0NudnZqAJgF4APP/gA3a680kqt/3N6gRkOXaxYMdW0ObA9j+1FZKBjCMgDg2NQqsbivCZZndsQFsU744wz1J+8vnbu3In09HQwMuK+++5D9+7d8f777/vHiz2cs0e8VhIb6kdeMNePuZsaxZ5uoitEVg+61lqEyFpj5MqIRAfeFVDisCgfmosWLQre8H/55RfUqFHD1i569eqFGTNmqJBHhj4Gyi233KIqGNevX9/vLWWFVZLaEiVKAMe9sj8BOAdAkeRk7Nm3zzaJpi4WmSpevLj6l+uefvrptvYtg9xBQB4YnMOVJJVkNSkpCRdddJGqAM5KxXfffbc631nUidft77//rjy1jIpgvjrTBNT1BajrWUIknbNJPFYSG+pHXTDXj7mbGsWebqIrRFYPutZaEp1PiUfW2sYywgIBVhzetWuXClck+bQSPkSz5ce2bdswd+5cXHXVVXmmsILqDTfc4P8/EmUW+3rxxb7LH9IAACAASURBVBdx1113+b2yU9auRT8A5593HtI3bIg4l+/cc8/Fjz/+qPJq24UJg7Y6Hvk8dgTkgSF2DI0VvvzyS9VSimX0WdTsoYceAvNiSUxJXqtVq6YiEJgKwOuWf1OYHsDQfOaPN2rUSIiscyaJy0pyTemHXTDXj7mbGsWebqIrRFYPutZahMhaY+TKiEQH3hVQ4rSoQQgZCswCTlZiFHoqXbq0erBmi5BAYRXVqlWrqgdtFn9iGx72w6TXiMRTVThesgS9r7kGb+7fj2uvvVYVq/m88OcYiIFIRSrawTw/19DVrVs3/O9//ztBkK02Lp+7hoA8MDgH7TvvvKMKN7FS8csvvwz2a2YI/Z49e/DDDz8gJSVFeWx57VGGDh2qqhj/9ttv6m++1CHpFY+sczaJx0pyTelHXTDXj7mbGsWebqIrRFYPutZaEp1PiUfW2sYywgIBen/oBWKOHXPtrIS9YqdNm4bbb78d7AMcSsYtHYfnDz2P1694HZf8fQlq1qypHsTfffdd1X+WwgbOO3bswPDhwzHskWFoUbgF1mItmqAJ1mANkpC/f22gLubePvPMMypHkF4okfghIA8MzmE/ZswYPProo2CIPouq8QUQrxO+tKEnlkXOWPCJObKGMEqCLXhYaI09Z5kmwL+larFzdtG9klxTuhGXkHz9iLurUa4hd/E1Vhec9eBspkWIbJzwT3Tg4wSbK2r5sPvJJ5+oVh6sRBxOWBCK3iAWomHbj+bNm+cbnotcNEXTPKR05IiRGDlypPIm8QGb9mdeKx/M6Y0tfU1pdC3U1b/WAixAR3QMuxdWa2WxKSPs0hVwZFFbCMgXmS2YbA1in9ipU6eqFzyMaGCRNPZMZlQDe8XyBZLZOc/rKy0tTfWgZcixEFlbkHtykFxT+s0imOvH3E2NYk830T2xtuCsB2chsvHFOZ92IbLeMcjNN9+Mt99+W1UWfuyxx8JujGSXD9Jnn322CnNkQZpgWYiF6IROeUhpyu4URVz/+ecfvPfee6oYDQtG8cH70ccexRNXPIENvg3IRjaSkYxGaGTplWUodOvWrZVnl/m6IvFDwNUvsowMIDPT/sFVqgRUr25/vMdGtm3bFp9++qnyxvbu3Rtz5swB+zLXrVtXXTP01vKFE6/FYHnqqadUqDHXYH6tEFmPGTeC7bh6TUWwj5NpqGBesKwt9tRjT8FZD85CZOOLsxBZj+EfuB3Ds0lSuW7durA7Zd4ePbFjx45VD8zBYnhj05CWj5SOGD5CkeWKFSuqXNzZs2ersOCyPctiZLOR+day8sr+8ccfKheXZJoeYuYRisQHAde+yLKygJo1gZ077R9YlSrAjh1A0aL253hoJEOJ2W6Huei83vbu3QtW/WZrK4b+s3fssGHDwBDkYNm6dasqxMZIh9dffx3XX389+H982SPXh4eMbGMrrl1TNnSfrEME84JlebGnHnsKznpwFiIbX5yFyHoM/8DtsOcrCWF2drZ66OWDdCj56aefcM4556iHZObgnXbaafmGBXtjjQEkpZdlXaY8sBs3bvTPe2/WexjWdhi2l92O7KRs///b8coyL7BcuXLYv3+/avNTr149D6NcsLfm2hdZbi7QtCmwfj2Qk2MNos8HpKQAa9YAIaIFrBeI7wi21yHh5LWYkZGhKhdTLr74YtWGp3DhwiqaITU1VXlcQwkrF69fv16F3TNflmHGnTp1UukDIomDgGvXVOJAoH2ngrl2yF1VKPZ0FV7/4oKzHpyFyMYXZyGyHsM/eDvsRblkyRIwNJHtPkKJ0TuWxWbmzZuXb0iwN9YYEEhK1361VrUWoXeJMv336ehVpZcpOlZeWeMBn+HK11588UkVguqlU8rVL7LjfYdtH++CBUDH8PnVttfSPJBFneg9Za9YhuHzpRGFIf9PPPGEfzezZs1S4cahhL2dH374YVUdnMTYEBZ0YzEokcRAwNVrKjEg0L5LwVw75K4qFHu6Cq9/ccFZD85mWhI9VVOqFsf3/Ckw2idPnow77rhD9Z+kNydYGHLcpEkT9d/8nZ7VYDHzxhrjDFL64IMPYvz48aqtSNGviyId6cjx5fe22fHKGhWURz3+OB575ZWTKgTVSyefq19khlc2LQ3IPuG1z3f8yclAo0YJ643l8Xz22Wdo06YNzjrrLDACwhCj5ZXx94oVK9CiRYuQpwDzxevUqaM+IyFmb2hesz169FDh/CKJgYCr11RiQKB9l4K5dshdVSj2dBVeIbJ64LXUIkTWEiJ3BiQ68O6gEr9Vd+/eraoRM6Rxy5Yt/gdh7oghvHy4ZnElemVZGCpYzLyxxrhAUnok64hql1O8dXHcd9F9lgcdzivb96m+mDp0Ktrc2BpLNx88aUJQLUHTPMD1Bwa7XtkE9sbSZEYxtQ4dOmAhj/m4sCcz+zH//fff6n82b96scmHNhLm0JL8sFFWpUiX10oi55OzjTJIs4n0EXL+mvA+B9h0K5tohd1Wh2NNVeIXI6oHXUkui8ynxyFqaWAbYRYAPz4sXL8aTTz6pQhMNmT9/Prp27YqiRYuqB2H2hA0WK2+sMd4gpX7im5uWJzc2eN1wXlmucfYHZ2PLVVtQolEJHBw7B0mdLrd7uECCkx77B+r+SNcfGKy8sgXAG0srGSHEzG+dNGlSHsNdccUV/pB+tsEqVaqUqWFpD/ad5Rzm1RpzQ63r/tkhGqJBwPVrKppNFfA5gnnBMrDYU489BWc9OJtpESIbJ/wTHfg4weaq2ilTpqBfv35o2LCh6kVJoTeWvSu//fZbDBkyBOPGjcu3BytvrDEhkJQuwqI8LXqsDiyUV1aR5x86AXUBlAA+PjAfl18yAjgJQlCt8NL9uZYvMiuvbAF4MXHTTTepvsqhctVZ4IlVvklgSWTDSbA9GIrcsmVL9TLq559/RuXKlXWfIqIvQgS0XFMR7qmgDxfMC5aFxZ567Ck468FZiGx8cUZWVpb6MeTXX3/Feeedp9pMhKp+G+ftnpTq9+zZgxo1aqgCMatXr1Z5sJ9//jlYCKpkyZKqVyurBAfLoqRF6Fqoq23M/nf0fxjhG4H0pHTkJFlXovXl+tAwtyFWZa9CEo71rSV5bpbcDOlH05FTMgc4CtTbUQ/rvxuLwl2vsNzL0XnzkNuhg+U4GWAPAX6R0ZvPc4UeQFckNxfJzZohacMGJAXkyuYmJyO3QQNkr1p1olIxe8/u3m1/GxUreqL3LNtS8dojmb322mvz7J8ElDnsLJYWqtha4OBge/CFVLNmzVT++yuvvKL60Ip4GwEt15S3IdC+O8FcO+SuKhR7ugqvf3HBWQ/OZlrIp1gkMrDTQXx3FJn2hAktHjFiBEaOzN8rlF5A9kgU8QYCEyZMUOSV/Svvv/9+5YFdtWoVOnbsiAEDBuTbJAnlkJZDsLXsVuQm5VoeRFJuEmrvq409xfdgX7F9luONAWUPl8XkxZNROOcYSUqvmH6i9yw9sj8AWAQML/k47us9A2W2bYMvRLuWHJ8P+2vXxvLx4xOyPYttwMIMLJaZiaIHDtheKqtMGRz2yDVaMT0dzULcR1YNH47Mhg3VMfn+/Rft+/VDsX32z6/DZcti8eTJyHGLhNtAm1EP7A17+PBhVQwtVC4rW02xPQ89q5HKG2+8oXrQdu7cWRV2ExEEBAFBQBAQBASBxEaANW769u0rRNZtM4pH1m2EnVl/w4YNuOiii1T/SRZ3at26tfLQsuopq58GSxayUKdQHexK2mV7A5VzK2PZ0WU4gAP49+i/qj8m24IULmTuyauIiqiOYz01DW/shqQNx/JrrwLwAZA0MQmN7mmE1Z+MCOuVPam9sVlZKFSnDpJ22bdXbuXKOLplCxCGPGl7IxvklQ3pjTXGpKcjyUbv2VyfD7kNG+b16No+m2MfyFZUbJnDF338nX1gWaiJ7XOilVD2mDlzJm655RbVk5bri3gbAW3XlLdh0Lo7wdxBuD0QFSP2dNCeYZYSnPXgbKZFPLJxwl9yZOMEvA21bdu2xaeffoqKFSsiMzNTtflgjp2ZZCADmci0sfKxIZVQyU9Ko8mtyFdYaiiApwDcBeBFYMqPk9Gh5/OosXFj3nYtBaQgkG2gQw00iiaxxZINkgf2MWWrpTVrwnqwo7Fj1McRnCsbKjfWKp82WHkc82vffPNN9O7dW+2IIb8vvPACSpQoETU8nBjKHj/88APq1q2r1j5w4IB6WSXiXQS0XlPehUHrzgRzh+BmGhmLQu7caX/BKlWAHTvCvjC1v9ixkWLPSBGLbrzgHB1uTs1KdD6VMKHFwQZLdOCdOgG9uM7HH3+MLl26+Lf2zjvv4Prrr3dlq5HeAEMWlpoGoA+ANoDvWR9yL8pF9TIVsCMzEz4PERZXAIxmURdIXqR2jGbb/jkGGV+7FmBv41Ak26rKsbGYB15uDBw4EM8//7wqtPbqq6/GBI0xOZQ92FqrTJkyqoXP999/r0itiHcR0HpNeRcGrTsTzB2C26UXppHuTuwZKWLRjReco8PNqVmJzqeEyDp1Jsg6fgQY3si+k5s2bVLVTX/55RcUKVLEFYQivQGGbPOzBsDFAKoAqAFg7bGtbq5XD2d+//0xr6wHCIsrAEazqAskL1I7RrPtPHOWLAEGDgRSU4F27UIvZ5ewx+KNZfhcpv1oBFSqlK+o1A033ACG/T777LMYNGhQzNBwATN7NG/eXOW8sxc0e0KLeBcB7deUd6HQtjPB3EGo7d5/DZWx3IdNti32dNCeYZYSnPXgbKZFiGyc8E904OMEmza1c+bMUVVTWfyJLT/ckkhugKZtfljTJ38xZbw7bBh6jh17YusufFG6hYvr69p9yLCJWSR2dP3YDAVWhD3WlxsOhc+1a9cOS5cuxVtvvQW233FCzOxx7733qtDlwYMH45lnnnFClazhEgKevKZcOlavLCuYO2gJq/uvoSrW+7AQLAeNFt1Sct1Eh5tTsyLhU08++STmzp0LphoVL15cdTNgjY5zzjlHbefPP//E8OHDsWjRIuXEYoph9+7dMXr0aBXRZSZ9+vTBtGkMjzwhLBK7gM+QFiIeWSuE5POoEfjnn3/Uie6mRHIDDOmNNTZXFcAfx/+gZ/YP4Pqh1+GdJduAcCGobh6cl9e2esiI8OEiEjtqhcWKsNsk6iH37FD4HPs0f/PNN+qGzxu/E2Jmj9dffx233XabKuLGPHgR7yLg2WvKu5DFvDPBPGYI8y5gdf81RsdyHw6zZbGnw/Y0WU5w1oOzmZZIiGynTp1UqmCTJk1UIddhw4bhu+++U+lGbLPJ30lkSUzZIpVt//r376+Kvc6ePdv0QDl+586d4DOGIeyuEKplZ/AiQmTje/6I9hgRsHsDNLyx67EeOQjRe7Y1gGUAmgG4AcC9QJnLy2Dv4FlIGnhf+BDUGI8hYadbPWRE8HBh147asTIj7BESddN9W2EYPDEEptWqVcPvv/+ueryyT6wTYmYPViVv2LCherO6d+9eJCUd68ss4j0EPHtNeQ8qx3YkmDsG5bGFHH5hGunuxJ6RIhbdeME5OtycmhUJkQ3WyYKulSpVUm03W7ZsGXJLs2bNUtFirK9h1k2BRHbfvn2qxV+kIkQ2UsRkvKcQsHsDZJufmqiJnTCpgjgPwAsAngew+xih9VX14dBvh1AUkffc9BRI4TYTS46mgyTPrh3jgqsZ2YyAqJvu2+pBzZhoQpxzc3NVT1jixzCeGjWY5B27mNnjyJEjKF26NPjv1q1bUbt27diVyQquIODpa8qVI47/ooK5CzawetnnxH3YZNtiTxfsGWJJwVkPzmZaYiGyW7ZsUT3r2ceetXFCyZQpUzB06FDVxcRMSGRJYllPh17YNm3a4IknnsCpp55qCY4QWUuIZECsCCzBEgzEQKQiFe1gUlgnSiWR3ADttvk5dPAQWp7SEiQJf/zxhypYVSDFiRxNh0heJHaM1ha7du0Cc7fZoqZYsWL2lwkmm055Y40dWD2oGeNCPLDt378fZcuWVSMOHTrkWCh/OHukpKQgLS0NfMt6zTXX2MdRRmpFQMc1pfWAEkCZYO6CkRx8YRrp7sSekSIW3XjBOTrcnJplEFmGB5922mn+ZfmSnD9mwsKu3bp1U57UlStXhhy2e/du8JmBHtkxY8aYrsWClWztV6tWLfWSnCHLpUqVwurVqy1b/QmRdepMkHVCImCE9K7FWjRBE6zBGiTBuXBEt26A5557Ln788UdH8w49d4o4kaNpl+RZeH7/PXoUX6xcieYtWqBwoUIIVZ03VvyMNjW8mfImGSw9e/ZUN+N169aB4bp5xE7v2Wg3aOWVDUOcjbehzE05ePBgtDvINy/cdcU2P3zDSgzDfTE5thlZKCoE3Lo3RrWZk2SSYB6boT/88EP18vjOO+8Mf/81PnXRG0sVYs/Y7Gl3tuBsFyl3xhlENnh15rqOGDHCVOmAAQPwySefqOem6tWr5xvHfvPt27dH+fLl8dFHH6Fw4cK2D2Dbtm2oU6cOlixZgrZt24adJ0TWNqwyMBoEggssLcACdIQzBWnc/KIxWpo89dRTeOihh6I59MSYY9cbGO7BwYrkOeH5dQBNo7ov/128eHGeFXfs2KHeBFJ44+YNPI/Y6T0byx6t7GDywMa3lawaeMYZZ2D79u2x7CDP3HAPFi+//DLuuususOgDv8REvImAPBzqt4tgHj3mjJjhwzAxZMQHc/H9YveFafTqQ84UezoMqMlygrMenM20ROORveeee8AXT8uXL/c/OwWu/9dff6nik/Syzps3L7IouOMLseIxw4vzvdgKOhAhsvE9fwq09uB2N8lIRiM0ctQr69YNkOXEH374YVx33XWqR2eBFStv4PEDX+Dz4a7ChfHcu++i25VXRkbynPD8OmAA5nHQg8lwFRYqCiw6MG7cOP8LC+aZkhQm0xMKgOEzPp8PsNN7Ntp9Rhk+x7ecV155paog+NVXX0WrPd+8cNfVmjVrcPHFF6swZvaUbdCggWN6ZSHnEHDr3ujcDgveSoJ59DYdP348HnzwQbUAW3zw+zePWL0wjV616UyxpwughlhScNaDsxWRzcjICOlZDZzHlDu24Xv//fexbNkylR8bLPTEksQyLPnjjz9WZDZSIbk+/fTTVd4sw5fDiRDZSNGV8bYRMGt346RX1q0bIHtg8UJkbyz2yyrQYuUNBMDbyP8AlY/J8uqBeRQKGyuSZ0NHHowdDhkjGSXxYpEiSvAbf1b7TU9P929h/vz56Ny5s+qBzHLw9Hyef/757p4GUeQbT506FX379lV75Z6dknDXFbHs0KGD6l1LDwqJbb5QbKc2IutEjYBb98aoN3QSTBTMozMyH475Xbt582a1wGWXXYbPPvss72JuR8WE2LrYMzp7RjpLcI4UMWfHR1LsidFYM2bMUN5Yo3csd8NOBnzGIonl8wFrdpDsMu3JEHpYDQcB0/f4wuqqq65SaVEjR45Ejx49UKVKFZUjy5da9OqyiFS4PF2uLUTW2fNBVjuOQLA31gDGaa+sWzdAhjmxyBPbi/DCpBevwIqFVzbb58OpSUnYn52tIGBIKd+y8eHjp59+UnkMlrkPNj2/ucnJSGILmTVrAAdbuzDvqmpVNgs+Js8//zwYGkPhMfCGzBvsjTfeiLfeekt5Oa+++mr07t1bjXnssccwatQoR04BEkH+5CtDH0X4HEPfWQ2Q+3zjjTcc2R8Xsbqu6NFmSDNf8vAlAMOLAr+wHNuILBQ1AlY2jHphmWiKgGBuAo1FjYRl69ah9Z13okjhwjjy77/q++TPP//M/71r9cLU4XNT7OkwoCbLCc56cDbTEgmRNWu5xxf+rDxMLy37zIcSRroxDYrCdYw5//zzD7p3766cCSwcxRfjJMOjR4+2VWxViGx8z58Cq93MG2scsFNeWTdvgPQ6/vbbbyp88pJLLimwtlIHFsZjug5AE0ARlezsbBw+fFhVoPvyyy9VqC49gpMnT7bGx65X1mFvLDdmhMMam2RD73feeUf9yZvl448/rjzwzz77rPK8ktSysjH7nlFatWqlbtCxCqsMX3jhheohjUUQunbtqsLX/aE3EYbP3X///WrPDzzwABia55TYua741pQhxqxKOP6++/DALbfYU1+pEhCiMIS9yTLKLgJ2bGh3LRlnDwHBPARONmok3AiAd+M7ALB6AbP9/zd3LrpedZU94F0aJfZ0CdigZQVnPTibaYmEyMZ3p6G1C5H1olUSfE9m3ljjsJz0yrp5A+zSpYvyPL744ouquE2BljA5muOrVsWD//d/uOKKK9SbtsGDB+eBgqSPb9ose5haeGVzmIfasCF8a9c66o3lZt977z1FGBmikpWVpfbKvqsU9j7buHEjXnvtNdWap0WLFvjiiy/8nzGUmqSWbwqtQlyszpFXXnkF/fv3zzOMeSBPP/20amWj6nk3bQoQgyZNLD3Tt9xyi/IgM6fbyC+z2oOdz+1eV+OffBIPDhuGHgBm21mYY6pUAXbsAMKU9be7lIwzR8CuDQVD5xAQzENgaVEjYQ8A1ohn0gdfmk4BMAnAvffcg9Tn2dg9fiL21IO94KwHZyGy8cU5n/ZEf4PgMTgd3Y6VN9ZQ5oRX1s0bIKsVswgQ27ZMnDjRUYw8uZiJx/Tyxo2xYN06TJgwQWFx2223KU8sw1nffvttFVZq2yNo4ZU9Om8eCnXp4jg8RiERhgyzgh49yySy9JDWq1dPhbIxnJw5wCSGJIjM59iwYYMqZsRG3iwx37x585j2Rg8mvcMslsBG3yTPBqFmaA373Po+/RQYOBBITQXahe+7fPnll6sWUQYJj2lzAZPtXldLlyxBu/btURvAVjvK+bIiJcWSoNtZSsaER8CuDQVH5xAQzE2wDHPfJ1UdCKARgPUA3gdwNYCzzz5btcCLSCxCmPOtZREdIvaMCP2oBwvOUUPnyMRE51PikXXkNJBFDASsvLHGOKe8sm7eABmyydBN5k1Onz694Bs5RI7mvw0aoNwPP6gQW5I6hsUGCgsMMTz2lFNOASve8d+wYuKVZW7svlq1UGrjRhQuUsRxrEkcX3jhBZVPykJe69evVySceaXsU0ZvMysAU5i/yv9nOHndunVVAYK5c+eGrqQZwU43bdqE8847T4Ut84uDRQ1YEIEke+zYsaoQFUnuRRddZHvVxo0bq2Ph3nkMTond64oh0iTklH0s+GBnAy6EjttRe7KNsWvDkw0XN49XMDdBN0w0zvUA3gUwFsDQ5GTsr18fp37zjXrZyPQF3hMZ8cOXpUXCfTfYCGHOtzuL6BCxp5tXy4m1BWc9OJtpESKrCX+GA/LHkF9//VU9FPIGl6+CqqY9iZr8CCxKWoSuhbrahmbe0XnokNvB9vjggbwBsico8w0tCw5FqIWeudtvv12t7WRF2Ai3oXV40qJFKNT1hP1WjB+PlkOGKLLCa061oQkQkj6SW745JyFjlV8rCdZhjF81fDgaPPig43bk+qyMRxsyTJyEkqSWTbpJxJj7S6/yrvq7MCh5ECZkT0Db3BMNuFkYii80WOTKILtWxxjqc7aT4MsRhqyzml+g0BvLMHa7GBpzWfr+559/xooVK9CUIckOSSTX1Zlnnqm8yp/5fLgsJ8d0B3xZkdugAbJXrXI8dNyhwy5Qy0RiwwJ14HE8GMHcHHyz+/65AOh3XQCoDvOMymk1dqyqTVGuXDnVKo0yZswYDBkyxFxBbi6SmzVDUno6ksLch4wFcn0+5DZsGPZ+JPbUczEJznpwNtPCZ7tatWopZwQ7ESSaJIxHdsSIEao8c7BMmTIFFSpUSDTcC+R+6Y0d0nIItpbditykXMtjTMpNQp19dTB++XgkHcsO9JSsW7dONWOuXbu2IiAnheTmKuJabssW7D3zTNzbtKnyRjMkNl9fv+OA0MP50ksvqVDcSZMm+curmzOaYzrKbNsGHyv4+nzYX7s2lrNYkUWl4mKZmSh64IBtU2SVKYPDFSrgP//5D3bs2KGqD7NCHnNSDWFu6SXNLlHn7pZyW3Dm3jPznJP0CpDIsiATX24Y5eODNxFub/Qu9Bw9Gn/+9RdG9emDS+vVg7E3rsOQYq5NLzBD2u0K8375gu/ll1/OU5XZ7nwnxtGbzB62vEIGWSzIlxWZDRs6oVbWEAQEgURC4Ph3i3Hf59YPAmAMD58WfktKQrE6ddT3wLvvvecvxscX1CQ6fOHIGgPhOghUTE9HsxDPiWYwyf0okU4g2atbCLBgI4t2CpF1C+Hj64pH1mWAHVg+C1moU6gOdiXtsr1a5dzK2HJ0C4qiqO05gQPdfJO3du1alRPJYjzMCT1ZJGnpUiQPGoTsCRPQ6emnVb/Q5557zrTgFasYswUP80jZvJo9Ta0k+O384Q8+wEIgvGc9KwuF6tRB0i7751du5co4umULKlavrvJhGR7Nfmd8+0gZNmwY+JIsOJIgMFKAJLRSpUqqpxnD3BqGImIWe5sHgIG/FQH8HwAGTxt7Y9Ej5t+2adNGlZqnd9OsxH0grgxLZk4vhV9ElmHdVkYJ+DyS64pVn/lzU/nyeHP/fiQdb9MUqE68sRGA79DQSGzokMqTfhnBPPwpEHzfXw2gGQA2RvvtuDc2t0MHVa/gzjvvVIX4+BKyXbt2qiAfw4v54sxUDK/shg0h70PGPLv3I7GnnktacNaDs5kW8cjGCf9Ej+mOE2yuq81ABjKRaVtPJVRCdUQfyuBmbsW2bdsUQaMnzmjDYvvACsBAei4ZUsx/+RDBUH4zYVVnegVZkZf/mgmJ7jPPPIOxY8bg0gce8Ffn/XflSnz8ySeKBJuGiFtUv8yn83hhof2LFqFsuXLqY5JRvtFnlV+jCXeSLwlN0RRpSEM2shEqf9soqsSiXyx4lU8s9nYDgJnHPZbKtx9U9IgYk2DzfOZLE553VsKQYvZkY94YXybYIb9WaxqfR3JdMdyaRbQuOOMMfMtqcZ+uuQAAIABJREFUxGYiubF24XdkXCQ2dEShLGLZf/mkhygoV/YlAHcD4KvP+WGqtLNAH2sAsHo8749h08kcbPMm15CeM1Zw1oOzmZZE51MJE1ocbIBEBz6+p23B0e7mDfDAgQOKXFDo/SpevHjBAc7GkbC3Kj1t9EgzLDccUfrkOAllfkUoj2Jubq4K0+aalJYtW+Lzxx7zV+f9t1UrlSMalshyot2HFOP4FizAt9WqoX79+ionds8eNnvIK2ZVtgOraj/55JPKe8vCT7NnmzSaMdkbw+aqAKAfeQWAFgF7Q0dmhR0ThhWzN++0adNU1WQrYeh7kyZN1EMd74dOSiTXFcOReI4w5PqvBg1QfMMGINArm5wMNGoklYqdNJCNtSKxoY3lZIgNBARzGyAF3CfZN5YdyIcxBzbMiy5+f1x66aWqLRo9tUxhMRWLNm+I4H4k9rRhTweGCM4OgBjDEonOp4TIxmB8mRp/BNy8AfLLk31DqSNRcweitRA9sAyh5bGTuJHAhRN6BOm9JeFPT09XLWsMIY4kZqwSHCgsEMUWCxTbdrR6SDEUBDyszJs/X73N5/GkpaXl2YNZle1gryxDf/kgRW8u80FZzTifmOxtEwD6sosdr+y7ooMPA18ugtRaH6FdUnv/Mgybo7f6jjvuULlgVmK8PCDWxNxJsW0Phkjn5qr8aL4k+GriRDQJVfBLvLFOmsfWWpHY0NaCMsgSAcHcEiLeMI71yk5LQ5PsbNU7dladOrhm82YsSVqKgRiIVKSiHfK2Hlu4cKEquBfYA9xUm9ULT5v3I7GnDXs6MERwdgDEGJYQIhsDeLFMTXTgYzl2mXsCAbdvgNWqVcPvv/+ej5wVZBuwEjFJG6tGduvWTeW9Lg3zgGFgwcq7H374IUaNGqWKKhlCLyO9jYUKFVJv0tnKht5XFjV66qmnIiOyHG31kGIoPv6wwkrF99xzD7i/4GrBVj2PDa8s82RbtWqlPAIM5129erVqn5NPQuyNvoMBAFoDWAqg6Rpg7UVAEzTBGqzxFzrj3q6++mqcf/75+O677yxPsTfffFP18mVVbRbcclIiva46dOigqoe/MmkS7pg6VT2kKq9sBN4PJ/cva0XwckjAcgyBSK8bxxQn2kILF+Jop04oBYC9KDa/9hrq3NpHpXisxdp890YenpFKwZfLTMUIm0ph9sIzwvuR2FPPiSU468HZTEui8ynxyMb3/BHtMSLg9g2QIanffvutekhnwYmTQegVpHeQ3sfvv/8e1WtUD/uAYWAydepUVfmOfVBZFMkQVvxl1ecbbrgBM2bMUESWHl4SQXq6SXAjsmMYr+x6AOf4fCiVkuIPZSVhHjdunGoNxKJVhlj1PA72yrKgEgk5c7RSUlLw+eefq0qaeSTE3ow+iay53vRyHzp9fKJFTWD48s6dO/3kmG2B2HoinBh2cqPPcUT2ANRLCWKscqS7dwc6dTqx9WDvR0YGkGk/jx6VKgEJ2BIg3veKSG0Y7/0WBP2CuU0r5ubiu3r1UG/jRpT2+bDvyBEsTl6CTjhx3wi8N3JVRvsY91sW7rMsbmf2wtOmN5Y6xZ427RnjMME5RgBjnC5ENkYAo52e6MBHe9wyLy8Cbt8AWUn2s88+U60Arr+elKTgCkNE2eLKaHNlFDYK9loGP2AYiNBzTQ82hb+TqNK7Sw8mCSs9jvSKHjlyRPUqY5VjenDp9Y3YjiEeUtiH8HIAFwFYOW8eCnfpovZCu7377rsqbHfw4MF+A1p5Y42BgcdLEksyS1LbtWtXdUwk4nkkYG/MjyUifwD4DMCDa4C0xj5k+3JCFpViX1jqYM9bq+rPbIfEolXBBN2JMzRSe8ycOVO9qGAv2y9Xrz4WOrh2LRBcwIW9wGvWBHbutL9Ner5ZRKpodJXN7SsqWCMjtWHBOvr4HI1uzBkZwh7ZvLf16tUrPgcdpda3H34YN//3v2hxwQVY/u03lgX3qIYvV1l40VZBvOCXimbe2DAv1v49ehRfrFyJ5i1aoLBxn5cXa1Fa3Hya7uvG8QNI8AUTnU+JRzbBT8CTfftu3wB79uyJWbNm4fnnn1fhqQVVGKp199134/XXX1eHOHToUNWAnu19rSr6BmJCbyzbFtE7e9ttt6kQ3GbNmqkHEBJXVp2kGPmgzF1l1duI7RjC83ktAKMM06iRI/HY8cJSRhGlwFxfK2+scUyhKhgzVLp169aqUvCAAQPA0OU8YW4Be/spOxvnAKq51KwOSei2MH9/5UCi3KdPH1XsicWTuGbp0qXx6aefqhzUYKH3mzizINejjz7q6KkZqT2Y73zuueeqgmgsklZo2TJ/IS8ERjJEWXka9PBb9Bh2FIACsFikNiwAhxz3Q9CNOSMgmE/PXuebN2+Gj9XQI5E4RkcYkTr33nsvuqR2yeONNQ4h+KUp26ax8CDTXnhft5TgF57B3lh5sWYJoY4Buq8bHceUSDqEyMbJWokOfJxgK3Bq3b4BGm1lhg8frvqNFkRhiGy/fv38D0IvvfSSqgxJsVPRNxAT5scSK+ZMLliwAHxYmTBhAoLDXzdt2qTa+bDSLXOf2KfVVtXiQGUBDykHAFQGcPj45/SSMry5UaNGyktMDzEJduPGjcMel5l9gx+oGB79/+xdCbyMZRf/z72WkrJkS6Ksiew33ERfZKdFe9IelWjTjmylkNIi8VVfUlKkqBCRIrquaylL2YoKV0WklHvn+/2fe58x8955533emXdm3pl5Tj+/uPdZz3mf5TznnP+57LLLBNARraIPPPBAYNXCsRGRk8icbQH85WeNNVOUZdyrf2PyUcA4Nqa84SMA446lvJz6Pu2uK1reiQpNlz9/Pgcdj2qMs+82Ow/+6M5OzTHZ27Erw2TnRyzmF2ueE8COubFJfPDiA5syxVmJk95OU/47BZNumuRLf2a2N/Ln9Pgg2J705LGcq3w4C+Ydwsr6Yc2ShbEoEOt1E4s5JVIfia5PaYtsIn1teqxFOBDtDVCmoKG18oUXXkg6Ccg4S06MCh+VJiJDijMe3gBrbKgLhvwdFVQmsadiQyvh66+/LlLDEDCKipc/MQXPF198IdLa8JHAtiLrZ/mcmpcHJqype9xxaNS9u0BaJrIwQafockeFkzGoVJjlvLKRjXwci1c1E24a0tAczQOAmViWrtd33323sILQSkA0TR8Vjq33qlWY5vXimlrAW1vMPx9/UCm6QbNNuhcT6dks3QQt3bR4z5w5U4BEOUnhrCu6iM+ZM0fEyg4aNMh8OGEgT2trrH3phiND+73oGv4ciCXPGTPKOFEC0ZFsx8rHUYnjfkyU+99//x0vrH4B/Zuaezv5PyIynIP74uTJkwUegxItXBjcO0RW1g9rSmyMZqFYrptoziNR29aKbJwkl+iMjxPbkq7baG+AUlm58sorwTjAZCL/tCl0AyYgk8yby3laxZCaxcq+8sorARZCusfu3bvX51YseShBn3ih2bp1K5YsWWKdR9YogMJLSFcAnwAYeu21uHP8eNRtWBf79+73labLK2Or6K57BEdQAzWwB+pxmlVQBTuwAyWFk/AxIrozU/OQd/fcc0/A77zz5uG0Ll3wEwGoXgS29CuIjTVSMPdllqGCSquvWXodGU+7dOlSgTLtJFmtq4VYWCRNBi3vjEHu0qWLeJQISaqXRxvALE7OPxnaspJhMszRbXOIJc9lSjCi+B45ckSkiqPniRVIXADPVNehrOTQemT4BMMoOOaGBxpiTck1yEOBQu5Pxr2R5xTDXxj2wgdQR0g/rDnCxkgaieW6iWScyVo30fUpbZFN1i8zReYV7Q1w2rRp6N27N9q3b4+FfNlNIpIouVTuqORR2ZNkFUNqpnzJ+rSwStAoWkSNOWRZjpaE2rVrC2vmxIkTccopp1gqsnQro7VSugjTNWxfs2Y4Zc0aHAWwaeNG1D2zHhp92wjfPPsNTlh/AoptKgY+RPjnZt2JnciFOnJuJVRCNVQrIn3GTg8YMEDEazFuy5++/OILnNe2LYp5gKOHAJQK/fEYHwbk4UL3a8adlioV2EDZsmWFKy+t4IxPdZJCrSv5bRjTZNDFka6OjIcm6nLx4sXNh2R1ebSZJsPJuSdLW9HeG5OFT07OI5Y8l9409HTZvn071q1bhxcefBB3XnGF2pQIWnTqqb6criJdlhlFsB4J7sc9kns942G5X3G/JMbAdcOvw9TBUy3HK/dGiY5OTxg+nDlGqgq9Q4q8Y+NOkoZiuW6ShGWOTkMrso6yU72xRGe8+kx1yVAciPYGKJOwN27c2BeLlCwSIRoz45Rq1aolUCD9ycoaK8uaWWVp7eVlg9bZRYsWCcCnYERLJuNo6Qb8xBNPoFu3bqYKEK26BEE6evSocGGl5Y/08sCBuH3CBDSrUwfZ331XxJJsNkYn5Pjzzz8LBGbOl7G+HB//zrhVzp+XuDJt03BoMYJaY+UYgj0MsJ1TTz1VWFnogt2mTRvfkNkurRkkIijTqu0khVpXZijWdCcnKBWVWCUwFqvLo740RiTSaO+NEQ0uSSvHkud8nJsxY4bYN08oWRID77sPTQGsVuWtRAMnMJt/uiyz+mGuR+7/MnUdzxo+YPLxkvt37txc5KTlBLXGBtsbnxn3jAAKtO1GbcUTi4c1b3o6PM2a+VK6WTWnf2+PA7FcN/ZGlhqlE12f0hbZ1PhOk3aW0d4As7OzhfWPCgUXezIR0XaJxCyRg+XcrKyxoZQvf/7Q/fSuvLvwfPrz6IDgOXhpUaQieOjQIREnS3cxM0seXcroWkaidZKKOMvyUrNp0yaMGTMG991/ny2U5UjlyTle1O4iHF56WKTAoHsxkYyl9bf1Ra3x1WtfAaFTwvqGYVS6mVqD8cVjx44VCr8kIpTWrVsXJUqUABGnbaOVWkzcbF0Zvw2jAs5YXaYkUnL9M7s8RmD9iVSeyVQ/2ntjMvHKqbnEkudMa8bHMyqKjRs1QtVKlfCP14vNxAqwmhDRjWWubZZluqzVq+kmU7RmhOtx6tSp6NOHCAbHiGMfkz0Gl5cn1rwacW/c88YeXH/99bjwwguxYMECy4rffvutAMCiJZh4CSFJP6xZ8jNaBWK5bqI1h0RuVyuycZJeojM+TmxLum6jvQHyosBDl9YvKgwBaVYSnJsSkZn5SJ988knfbFStsbJCMIunmftpMJbR7Ywuukzdw7gvM0VWKnWMuT148KBQZgl4QmJs74YNG7C+6nqlNA5OiM43xxezgP5Aq1atcPnllwuFk+7Ao58ajXfufQerPavDBpWiXKjcMw0UQaAkEUTrxhtvFJbuZcuWOTGdgDbM1pUVirV0taYF5tNPP7Uel9nlMUzrj3WHqVMi2ntj6nBSfaax4rl/WMj+/fsF6FOz2rWRs3Ur5gDorjJk/zUWRSWOj3AEf6MLND1vGNP/wosvoG+TvrALuDds3jB07dIVqh5SBMqjV1CjRo2wdu3a0FwxeVjLp9LftCnSiHysU4CpfFm2y8Rq3dgeWIpUSHR9SltkU+RDTdZpRnsDZOwoY/5IVJ7k393OT+a+pfsWFTzGnhKJ2Kggnn/++WDqHaZ8ue6668SUnEL0NXM/Dca39evXi4sGU+bs3r07qJssHxEqVKggFFdehGj5pLWcDwtXX301mPanZq2atlGWI5Gjb467CfksmCcso3SxnTBhAm6767aIQaWYUoPx2TVq1BDylMR0SVOmTBEXRKIEO03B1pUKivWGbzcI1GrGWxORVLo/m47PeHmM0PrjNB8Sub1o742JzJtojT1WPGdoBVHCmcKMVkeSfOh73uNBf64rMwq2xqLoHcE9isosgeDotUIKF3BvVvYsZLbIFAj7P/1EGD1zYgwuzz4q+jwH+X9LMij0swEwudGg99/HCRdfbFldFwiPA7FaN+GNLvlraUU2TjJOdMbHiW1J1220N0DGKdLyx0ORgBq0zsacbCatX7BxIzr17h0wzGeffRYDBw4M+BnjGRlfuWrVKjSnm1kEFwx/RF8r91Mj/8hjvtRv3rxZIFISzdJITLnA1At0Q/7xxx9FHCatknQxoxJMsrIkOxkrW0SpOx/A5wWjpqWUaYyoZEcKKkWQJ4I6kUdU8itXZrZciAssQVOCpTVy4vsMtq5U+NvR2xFVqlQRKNXKaMpGa5C2xjohQkR7b3RkkEnWSKx4ztRmdN/nXvPqq68KLvJxj/v8/QDGWPE12BqLkncE3YrpXmzMtx3O3ujd6RU4BHyUJVJzKA8piYovWcGHNe6lIclPod+Tlwee9sxN3qVzZ8x6//0iyPtWbNa/V+NArNaN2mhSr1Si61MJY5HlpsU/kvgax8sclQvGL2pKTQ5wA6QLIxWakCipEbCnZs2aIj6WOTulwhdBc/aqHjmCYrVqwbN3r1I9JndpUawYco4eFa66BEZavXq1eL1nblVJubm5Yt3wIsAD3h8RlxeMfdin1B8LVUTFAETfBZ4F6F6sqHPb3KNzQUUnGA0dOlS4NxPsiTGWRqIbNC2Q/fr1E9ZOI1GxzEzPxBrPGuR5gqRx8KajibcJlucthwce5bmZFSwyR94lbwbqtayHVQtXWVsibYyAbnRUWnkxozJPJZ7KIon7IB8knCbjurLD32uvuVZ8a8zBzAu3JXm9SM/MRFp2NvKbN0ce0Z+1C58l26wKxGJvtBpDqv0+Vjzv2rWrQNFnbvPbbrtNsJn7IoGQepUti3cPHoQnSLwrQYu8TZoEX2OF69CzZo2oG7KsDcFyT+cZzf3bGCtroxlRlA/KdKMm8bEslGLK1GUffvihr4usrCzhkmxFngULUKx7dzxgeBCgVxPBtY477jirJvTvbXIgVuvG5rBSpjjvEWeccQZ27twpjAWJRgmjyPqn8/BnMjdHuhxq0hyIFgf40s0HE17MmxG5MJbk9aLtoEEou3UrPKHcxQrHxEy3VwPCtZOAQ9yYHn30UeGuSyuhpG+++UYoGbTw+aeliXRqVHgGtR2EbWW2Id8vZ2pafhpqHqiJMUvHBFUkGYtMizHdi5lj8IQTTvANha66N998s1C4qfAyxYuRcirmYFjmMMvhD10+FE1zi9a3rOhXIOgcvYBnoQdn1D8D47LHOaIsyy55QaWLMeNvmcqIFzJaY+he99JLL9kZethl7fB316u7xLfGmGHGX6tQxbVr0XDyZHxz663IVbhsqrSpy2gOJCoHjsvNRck//gg6fO6HPQcPxp9//41X7rkHdapVw5EyZbBkyxaMHj0a9atWxYaffzad+vKhQ5EbZA9lhYo5OcgcdmwfDVVWlbdEb2dYhFPnJ0NJGGpCsEIzIwY9WQgMyIdcianw8MMPoyVBrazI60WDe+9Fk+3b8SeAXpdeijlz5woEej6Y33nnnVYt6N9rDiQUB+iZd8stt2hFNtpS0xbZaHM4MduPxUse0wQQGZKurETIjTXJF2Kzfr8rTFFKp9OzADCRDhU+KrBEA+ZDDy8/dMmVljymhyHIEl/26Z7qFJlZY2X7ZlZZXhKYC5WWb7rKMXevJLo+E9SI8clMRWOMu7SyFsp20h2yyoY7x3B5TLASokszVdK8efOEXInQTPTOyZMnh9tsyHr+66pY8WIhrd1G/g56dxCuuuoqocjSvVhTfDgQi70xPjNzb6+O8NzCC2cbgFoASgBgempma/ZWroysmTPRsk0b4aGxu3p1SMuq5JaShTUK3hF0BWZYxMqVK4M+QtqVJs+Jbdu2YcmSJaZp3fg4S6RiWmDpUUUvH6Z64z6qQkP79MGT06ejSc2aGDpunHDTJ+Be+fLlxRmUTKCPKvyIdhlH1k20B5nE7WuLbJyEm+g+3XFiW9J1G4vYCr4AT58+XcQfGeNMY8LQEDnuvgIgM7TSL4EOwZUqVcLWrVt9wFQE3yEgCAFC6JpK4oHOF+0HHnhAxC45QVZpe4LlSpX9Uo4EnCIyL8fIsUqSY6WrGEGsjGQVu2ksH0msbCRzDJfHdCtmGAWJl0G6DzKvLL1RaKmOBvmvq8+KfxYUCdqs32eWP4N7z71XxJPTk0FTfDgQi70xPjNzb6+O8Fzu99nZQD6DRQKJzrIXAaCTLIGIUJhK5/d581C+MJ/0n7Nno1QwcCKV+POFC4EBA+irDHQInjZNVQJ8QGWKMOaO5WWZXiSRUuvWrbFixQoRakGAK/8zhOcHFVy6FDN8huBS7JdKrD/YVKgx0IuJZyatumyPD6dEYeeDMF2bmeqtXr16kU5D1/fjgCPrRnM0bA4kuj6VMK7FRgklOuPD/uJ0xQAOxGID5MsuY5HoijtixIhj/dsEYUKlSkC48QcmQBzMLPqM4ZvgWP3dnwieRHddunYNK3QbY249Hvi0MtOy5wSpKpTBFEnKUVqJefEh8BMVoeeeew50TSMFAzZyCmVZdf6RzFG1j2DlKCOiSzOnMd3CeaGigkvrRDRIrqsuXbugTfE2ttJkNNzeEOtqrkvKlFXR4HW02ozF3hitsSdqu47xPEQ6nFEAGHlOn5WpklHz5sHbsaNA5yW6/sYNG3Am93WZGzZOaOBUJvmwSqLXjRM4FsR74EMnra4yPpjtjx8/Xiirkhg/S6WTca30PmKO65kzZ5p+WvQEmjhxogA/JDVo0EAg49MLhp5LRI/nAyLLEWRLk3MccGzdODeklGop0fUprcim1OeafJONxQZI5Y8x2gQa4kEniMBjNWoAe/aoM5UAPV98AZjEPgVtSCq/JlZZ4vWuBzDF40GNOnWwf+RI9LrssgDXJ1peadWki/THH38sumFsLMEyGG9J5ShSsrJUyvbNrLJSjnwsoKLGV/AePXr4AKrIf7pLGyncNA7+KMuqc490jqr9BCtHdzZaAXhJJTHmmZfEaLm4SXm079oetYvXxh6of+eV/66MPccXlCcwVbly5SKZuq4bJgdisTeGObSkreYYz0N44RADgVgIowE8aFBQzz77bLF/fvLJJ+hMwLTOnY/xWsUa67BkOBaOifsV4/CcIMbyMQafj8r+YHI8L+bOnYuLL75YeKq0adNGgEHROssctgRqlEqqcRwHDhwQbsO0IJN4JlJR5th5ZlKRHTx4sPBeYv/RCulwgj+J2IZj6yYRJ++CMdtRZAnKSW8IPhIRi4VhX1wX/l4KfGi/7777hCcjw0I7deok8Dxk1oVgU2ZmBt7xuLaYKuvcc88V9+06depYckgrspYs0gXczIFYbIC0cNIqG+DaauH+VYRnhUnVsWuXfeWX+UNLlgQMr/S/FKYvJQYvMY0rmFxU6I7KeEXGTu3Zswe//vqrD+nWqdy4qpZKyRejVVbKkfFMVLr9Yyu5ITIm1ExpCyeNQzXYR+aLdI6RriPmYmRORhIvbf6InJG2bazvv652F9+NXOQqd1EJlXB2ubPFYUSXdukWHaoBHowEY+Eh1rZtW+W+dEFzDsRib9T8D+SAozw3sco2BMDMsR8B6Mru/fZ9qczRu6Uv0YwJbpSVBWRkMC7BGTRwG55Ii77+Gh1uvz0g322k3wz3CYJa8UyWCPa8BPN849nG846I/ZLWrVsnYmVDKdNff/21AIKi9XjNmjUi/yzJX558HKBCzFRxGzZsiHQaur4fBxxdN5qztjlgR5ElejcxMDIyMgSY2iOPPCIez7gmJEjn7bffDqZMpMcfvUR4p0tLS8OyZctMx0ZlmEoyvQeJoMyHo/Xr14t2rZDCtSJrW+S6gps4EIsNkK9KjJM9//zzsXjx4mPTD+H+FZRHn3wCDBkCmMQ+BVV+md9VXkAMr/R0K+sDgBlgV4W4qPB1jMiN3HSIHkmE4Hbt2qFGjRri35GSE+69/nIkcvH8+fNFfBMvJCNHjoya5VF17k7MUbUvs3J0zWPOXLpdP/300z6lNtJ2g9WPdF3JPLdMEUKXvFDEeO4mTZoIYDKus7feeqtocRuXZ1E5Ejf+aDA0Dm1GKsM4DDnhuzTleTjfL9MKUhGV7sF0zwVAPPejAH5IS0P15s2xcOUoDPAMxARMwOz+swX2AdHCeSmEg/GuQjg2PZG4kq8F8J927fDZkiWOyFe6EPMy/fbbb4s2v/vuO2ER4oWX1lWGp0jiv2WaHu4x/oj4sgzDNhi+wZAbIsRL8pcn25Gpzqgw04KryRkO6L3KGT6G24odRdbYhwwf+Pzzz8UjtFwnPMdp/CHRessHIKawpFHFSHyIYvw8jRbEACGxHVpwqQxzrYcirciGK3ldzxUciMUGyMs4YfcJAMEXIh+FcP8KYI6/+9eCBYHuXlZcNFpZ/ZRnKrFUZpng5EkLtzG6VTGfLPN70p2Yr1/+rsZWwwj1eyfce2Mhx3jPMZL+ZV1e2HhA0DIb7ELmRB9sI1J5UHnlhXDq1KkBCNTG8bGf8847T1hRSEynQbCVAOu7zcuzaIhu/NKTwSmmJFg7kcowwabriuEG5Xkk3y+VPz/3YJ4+DCdhJtX9nPG8T9Cy0xBkIQsZyMDlYy/HA4MeMH8Q8uMSL4+HDx8WOcSVQxRseiKN93hwr9crLqJS6YxUUG+++aYABiSKO7MJkHjZZdwq3YkZx2okKrK8GJt5iBAJ/oknnggMHwqyD1JZ5h5MaxPdjTU5wwG9VznDx3BbkYosrZ/+Ka0Y4mXMEmHsY8uWLcL9l3dj3pF57vP8Z7pE/zzPNJwQ74TpLI1EFPJatWohJydHPGpLosGF/yZWSijSimy4ktf1XMGBWGyAdDVi7lKmrmGsoiS66e6eNQuN77jDmhdS0QxH+WWsUyFYxvuzZqH9U0/h5HXrUDU/H7sBLKpXDxds3BjSbaxv375gGhduDDzoGQtES/OVV15pPXaFEpG698ZCjgrTCFkk0jlG2n8s60cqD140eeHkgwmRsc2IMTHDhw8X7ke8VLNfHow81Hxk8/IsUVwdc6WMJeMd7CtSGTo4lJRpKijPI/l+yTk/qyztj0wAR6T6ZRkZmL9yODp7uvj4+8i7j+CJK54QcWtmbnzokR8pAAAgAElEQVRE4qXlg+cXvXR4+SSgkVlO1iLCs+GJxEdWYuIT7Z+o/07QggULRMwd41fpNkyS5xsf+OitYiRehteuXWuqgPbq1UvE/RkzExjlSWWZSjMVX3oKaXKGA3qvcoaP4bYiFVljfZ7PxCcxI5HTumdPEUb05ZdfimJ8aOc6YWysP9G7jh4PwbJkLF++XMTE/vzzzz63ftZlyis+snHPCkVakQ1X8rqeKzgQiw1QLnK6vNK9ky9NXIzPP/+8SMw+vWZNXPnDD0BeXlGeBEOLVL0IGKysRGhkDGHdU0/Fiz/9hAsBHA/g9w8/RMkePULKg6labr31Vl8ZbjREX3QLxUKObplrIowjUnlQeWVcM19g6QoYjLiu+ErLw5DWGsai8/IdFBVUdc3IjuIAbOM2uUYqQ7fNJxHGY8rzSL5fv7qP0PuGihuAiYXW2NVYjTzkgUB6dbPqYuM5G4WbHtPO0OrK1Dc8u0i8MDJEhuP0Jz7UEpeA1heuQ6bNGjVqlAhJKUI2HmNvLFcOr+/bJ6ydjG11gmi1adasmXA7ZH5akgS5Yr5Ygj0ZibGtxBQg4Azj94xEhGJao6jQU0mWZJQnz1+ew0YXZCfmlcpt6L0qvtIP1yLLtcTYcSqx1QozcmhF1oYsI/HpttGNLupyDsRiA6SySvcrEmP/eMjzZ5LKlS6Nbw8dQgE8RBAyXqqtLgJBlF/mzWP+PEklPR4c8XrRuUwZfPL775YgHtKqzPqMVaB7cTRdU+1+NqHkuBALMQADRAxYB0SW19DuuFK1fKTrSsax0eJPy38wIiLhHXfcIb5rXrAJGsG4PqaLeu211wKrWK0ZWTpOaUbc+J1EKkM3zsntYzLleSTfr1/dnnl5YIbtF6pXR+0dkwKssYI3RP2rzOPAI86oBx98UCimXFNE26WSR0ssU9EQKIm5Uumlwzg3hs/w/zwrSFTW6EJLZNIipKiYd83IwCdZWQJl+KabbnJEfFTQeWlOT08XD8sELCQyOpV2KrbBkFFpEeZ8g+VNp1Wa5ztlR8wIPq5JMsqTrsm0YLM8rVBOpBNyhCkJ3ojeq+IrwHD0KQI4ffDBB+IBjOBMkrRrsQ1ZhsN4G83rognCgVhtgDw4eYBKIugOXSL5h7GnXcuUwdyDB+HxT2Af6lJtdRHwU3550NItgy/R3bp1E7nt5Ev0uL59ce/LL1tKi3xiXlYevoxH3N1wt6uUQzM5SpAlGQO2EivhQYGrtabocSDSdSUB0gj+QBCIYNS9e3dxUabySnAaWkMYt81DkTEzREIkAAtjanr37l0Etdt09toaK1gTqQyj93Ulb8sheW6150u2BPt+C+vyukh4vsVPP4UHBr0HaY2VVdO8aQINKv+vfBGrRuWUFll/ovWSD0elS5cWPyYAC5VW6QpIECPOgwoizxtaOYsobFaKeeHZ1zwvT5yPTIvDtpwgjlOimDKlD89DWlHlvhGsj2eeeUa4Uwd7WJMxflTYCQZFdFVJRnnSe4ToxzxHmcqH2BOaIueA3qsi52EkLdjRp/hgRMRw7gtLliwpkh5Hgj3Ry4ou+yQCVDLnvRXYE4GeuE5JfGQjirgGe4pEsrpuQnAgVhsgL9WE6KdCW716ddStW1cceHyhpZsTX4YnA7jFyDWzS7XZRSCI8ksXZiZ0Z+A8NwTmf+UrugSv8M/fFUpoVH6pFJ9a7VS0REsfQIgblEMzORpT3hjT9iTER5qAg4x0XVF5pQsjQSAIjmIkxsPyQkhEbca58XLNg4uWFV4Wf/zxRwFYQ1fjk046ScTNVqxQoQiKa0C72hobwI5IZZiAn23chxyS54rKX9DYbq8XB1u0wElEMAYwI/cdXFHBBN+gPmFCIc4lKpH8P12EuSa55uiN429BYXvvvvuuCD3hQxKBVYgySuWQ69M/zU0Ag60U83nzUO3mm8UDsFP5ymX/Erxp48aNIn6OcXzXXnutiMsPRox/5aWaiKm8TPsTlWymLWKKHmmNNlNk+XMq5MwtyxRAtHhripwDeq+KnIeRtGBHkaUXFd2HaY31v3sS50J6b9DlmGuESijPb+4hJD6gSaJiy0fsSy65RPyI4XpcU/7pd3g30Ol3IpGsrpsQHHDDBshYQLosnVK8OHbl5SGNVlmTSzU3ASq/3ATKEqnVP2G95Lif8suDlaiufCmmK2a/fv1EKQbFUzHlJcUuuVE5DCZHaY31jwFrhmZwg+Jtl+eJVj7SdSXTYdDqQ8uOkWiJpUX2tNNOE+mgJGoqc9PR0kEXyNmzZ/uq8SFHIBcqXJ7hF+OWaHx3cryRytDJsaRKW5Y8j+D7XTFhAloPHIhTypdHtV9rFbHG+njcGcD8YxynokaEXa4r5keVsWxGmdDS4o9eTOWWYCt01SXIYRFkY4vHWO+KFSh53HHCusuHKa51p4gPZHzconLOWF4CQNGF+s477wzaBa22LVq0KALYyMIyP3cwa20weTLOlv0QnEYC3Dg1r1Rtx3LdpCpjYjRvO4qsGcI5w4EYwkDiAxgtq7TK0oOCj2JcNwRMlcR2/Otw/yG4FEFJ6fFABHLWodHIijTYkxWH9O9dzQE3bIBcqHSBoEWJ6Z6JKCnIYI0laqKEFmd8wfMTJgRamAzKL+N1GD9IhZWuX59++qmIC4qE3KocBpOjUeH2sRXz0AnHADki4YeuG5wDka4rKq98iSXx79KNUfbGBx0+zPDlloeVJB5+dAOURAsRwSQIVkPrS22iGRtya4qy2hpbRJCRylCvDfscsOS5DU8cY+8SsK9Zx2ZYPb/AMhuU+NY5qeA3tHrw4dTfXVZ1VoyxpSWXrslMiRVUATZTzOfNw28ZGcICTOLF1iqNh+q4WI5KJK07jPVlSAI9PGh9JmhVMKILsswBy3lJ12SWpSWavB0yZAiGDRsWUD2YPMkLemXxIs54Y9munfHrsoEcsFw3mmFR5YAdRTaqAwmzca3Ihsk4Xc0dHHDLBki3Jrpb3Fe5Msbu2QNkZMDoIkawDYJekHixoKty8337Aq2yhcovD14e1rRs0e2SAfX+ObnC5b5blUOjHI0Kt5wvkTm1VTZc6avXc2JdUXn9888/xTdMC4okvrwSUIUXQmPsHD0VJOooL850padLoIyfpYXol88/R9fXX0dj43R0bKzlJVz9C9Alw+GA0roJofyF8iagex6tjpXvrYx94/YJpOKgRFhjwhtTn31lEm679bZwpiLqEAuC+SHpHUHk3yJkVMz9HpQ2btokwBF5bhHp30niHsG9QhJTB/HhV6IzG/vinkOlnPsREZRpIWboA62w9HiiZZXnN8MZ/MlMnvSEImaFv0XJyfmlWltK6ybVmBLD+WpFNobM9u8q0RkfJ7YlXbdu2QBlDM4ZVapga9my8Dz/PNDhGMLur7/+Kl60+TLNV2MeggRwemvaNEw57zzs2r0bzzZtipOzswUCMQ/YGTNmiJdfvjwr5/gLIWE3K4dGOZop3HJ6OlY2ukvZiXXl7/5H0CdJvBjzgkyrCNeFRATn73/77TdUqFBBIJBOmzYN11xzjbhI05OBsbOS6pQsic3//lsArqatsUE/BidkGN2vLPlaV+J5COWPe38w4nrgetq6dSvwLoDLQvCOKRevAlAR+OCHD9Dz+J5hM5pIw1TWHnvsMYwYMSJ4O0bFvPBBiUAw9CRiHB1jbp0kuj0znIf7At2mqdhaWUZlih05DgJY0cuDcbN8OA5m0TWTJ2Nyab1lfB/Pfk2RcUBp3UTWha4dggOJrk9pi6z+vBOaA/HYAIOlg+FLLw9Sui0FOxCZpJ3AEFRiGR/Iw90YO3hDx454bf58EcvEWEG6LrEt6Y4cqaDcrBz6y7FY8WICjMqIyCnnr62ykX4J1vWdWFcEJKMnARGM+TAjiRaRRx99VFxAuRaMRFdjApoxXkbG47AOLSbMj8m4OIKrbaTrpKysrbFF+OiEDK2/FF3CnwPKPDdR/sy4KR9/PCU9wD7AW9przvi/AdwLeC72oEXHFhFhCrz44otgGAxd/AneYqJlF7j7Z2XB26IFNr7+OurWq4eZM2fiqquuQijkcie+HtX0bCNHjgTPYYI6MQaPAI4dOnTAwoULxTCIQ2FMSWcmT57LRCzmIxwf4/xdlZ2YU6q1obxuUo0xMZqvVmRjxGjGIUp4eHZJJDyZ09MJa1WMpqG7cZgD3AAZO8o0A7HI6UarZmZ6JrLTstE8vzmW5y33pYOh2yNdsJj43T/WhkjBjFWiOxMTqjOlCC8ITCtC4kH/xRdfCCsUUyYQvGLRokUi5cirr77qCMfkuNd41iDPU9QlLd2bjibeJgHzcaRjxUb85bi4xGJ0L9bdsubco3PR0dvRspwuYJ8DTqwrutvTckIwNOZxJBFVlHGx3MvpJnnbbfbdHokayjU/plo13L9rF/KbN0ce0RBNrFn2Z58cNZyQYXJwInazUOa514v0zEykZWcrfb9UwpjqrUT3Evhnzj/KE6rsrYwtR7egJEoq1/EvyPAXgq4QA4KhAGZAL3kLFuC9W2/F6JIl8e2OHbj88suFpZMx7wwNIOhLNCjUeRyqvynrp+COFncAhe8BBKIS1m4DmcmTZ3XNmjXFPZQuzlT0NYXPAeV1E34XumYIDvA7JpK5aSy8y7mXMBZZ6cph5CeD9OmKpklzIBYcyKmYg2GZxwAhhi4fiqa5BQATtBSNHz9eoDMyZQ5dIelSRURFulkxRoffK0EveBAS/ImIkESSpGLLyznjifhazFgf/ixYcvdw5mkct1kb/vMJp59I6/BiMqjtIGwrsw35acdcSY3tpuWnoeaBmhizdIzOKxsp06NUn/Hgc+bMEW5/fLwhrL5EIqZb/aBBg8J6fGJcLddR09NPx5KjR/HNrbcit3GRiNkozUo3qzngDAcqrl2LhpMnK32/9957r8itfP0916NRz0bKAyhzpAwq/B3+/YgPTowb5VnGR9hg7rs8y3g/43nmT3SF/v7774XnRTgPViqTDHUem9WXZ8yW+7YArxWUopXWCPRk1f/LL78sYveJyMrHOU2aA4nKAbrWE8NFK7JRlqC2yEaZwQnafCxf8oxWTaMVk3ld6frIMRGoiUos3Y4k0dLKy3swYrmGDRv6yl9010XY/NxmjM8bj/be9hFJx8oaKxuPp1VWypFgxBcfd7HyfLVVVplVtgo6sa6Y1uKRRx4Rca60otJCS3rooYfExVcFSXWRZxHuSb8nYB3QclK/fn3x2MO0IMxfp6koB5yQoearPQ5Eg+cEMZJ5y3nRtIoFtRpxsDUVqg5daOnaTO+KYIBPBHPj2UWPqMGDB4vUcFTyJHGtcx9wmqzOY7P+FngWFHj87ALAzB5/QaTT4SO0kULJc/78+SL/LD0C+chgZq12et7J2F401k0y8ilac9IW2Whx1qLdRPfpjhPbkq7bWMZWqCD+Mjemf9wfrbB0reJlnvE4oQ47uhHffPPNIlVJ7a21sabSGmQgI6IYJwrcKjbW+FHEA0iJcvzo448wssdI5KTlIB/m1lg53jSkoTmaR8yfpFsUDkzIiXU1depU9OnTB+3btxdooStWrBBu94x3VSEJTpaFrCLrgIosH4oIiEY3Rk3BFVnGNdIiFouwCy0DiEdMp3n+7LPPijAUxpzTsycSCrWmzNrlmcSzyQzwiWm0mE6LKMCLFy8WsaYMpeHlmMS8kExx4zSpnMfGPo2Ah55xHngf9GLex/PQqWPRlG6h5Ek8DD6isQwVWbpmagqPA9FYN+GNJDVrJbo+lTCuxcbPK9EZn5rLxflZx2oDVEX83b59O3iBJ9ow0+YQKVEVCILuW7ww7K+7X7jXSopEsZTjzka2q5VDyvGDeR/gzu53Yq9nr/KHUgVVsAM7wo4BU+4oxQo6sa4IosLYdQKiMM9jiRIlRJy4qru88aLqvw7uv/9+jBs3Trgsv/766ykmHbXpOiFDtZ50KcmBcHhOpG6uj6B5WgGhwBI0jQqtjDUPl+Oh1pRZmwRfo8Wyc+fOIqezkS677DIB7MQ4XoK4kfhv/pzEGNKePcNHTg42LtXz2Fg3qPL7LzCvePDc5FbyzMzMxFdffYU33ngD1113XbhiSfl6VnxOeQZFmQGJrk9pRTbKH4huProciNUGaGXVtFI2VZEVjQd0pAi9R3AENVADe7BHWRDxUA6lHM/uejb2F9+vPNZKqIRqqKZcXhdU44AT6+rbb78VLoeSbrjhBpHKQ4Ws1gEtPxdccIFws9y9e7eSm7JKv8lUxgkZJhM/YjEXuzxnea4RWi+ZM1kCVxJRlzGp69atE9gLjEOlizHzL4dLVmvKrF0CPrVs2VKstT179mDlypXiMYoWyLy8PPFz5omlQkeAJxLHS28M4kPQLZlgUU5SOOdxOMqvlTwZKsQQCsYAT5o0yckpplRbVnxOKWbEYbJakY0D09llojM+TmxLum5jsQGaHYCSmVbKph13rnDcpayEuhM7kYtcq2K+38dDOYyFHJUZoAs64iJJS9PJJ5/s4yZzJ6umkrJaB/xeCPL3xx9/CJdlXrQ1BXJAr6nYfxF2ef7OO++IFDUkfxfcZs2aiVzjkhiWQjDASMhqTZm1zdznDJEh+j49jPhAReV1y5YtAsypRYsWOOmkkwS+A+PWJVGZ5R+VWHg78wr3PA5H+bWSJ63NBLNjBg3yRVN4HLDic3it6lqqHEh0fUpbZFUlrcu5kgOx2ACtDkDJGDOrrKo7Vzgvxq4UShiDioUcwxhWylZxQh68xB5//PEi1Y6Mn1NhqOo6IPDMhx9+iAkTJuCuu+5SaTqlyjghw5RimAOTtcvz1q1bi4cYEl1xCahE93taXqkA0irLx59GjRoFKIl2h6q6psza5RiMqMQjRowQ4QLMj07QI65Ff1L1QrI7l3DO43CVXyt55ubm+qzNVOTLly9vdzq6PKITW64Zq84Brciq88rRkonOeEeZkcKNWR00kbLG6gCU7ZtZZe24c1kd0Fbuy5HONZ71oy3HeM4tEft2Sh604GzYsEGk3QmGeBqMN6rroH///iJFFRFRiQiuKZADTslQ81WdA3Z4TgWWiqwkpl6jYkTlleBJRL7/8ssv1TsPUVJ1TZk1wRhQutBS2aaXBdcex0vQNboUG+N37Xgh2ZlguOex1fzlGIxnrIo8JfAcU40R7FGTfQ6o8Nl+q7qGKgcSXZ/SFllVSetyruRAtDdA1QPQ7CBUdeeyOqCt3JddKRwbg4q2HG0MRRd18IU8OztboAsTtVslPYWddTBq5CiR7oOoqswrq0krsvH+BuzsY8zPOn36dPTu3RvMjcz84VQKhw8fLkCVRo8eLaydkZKdNeWBx7I7xsUSyHDjxo2+sozp5aOVJFUvJMvODAXCOY87oiNaoiVWYzXykGfaZbAzVkWeRGTm/kNZUWaa7HNAhc/2W9U1VDmgFVlVTjlcLtEZ7zA7Ura5aG6AkSL+2nHnUj2gk9UqG005puziiGDi8ZKHnXWwc8pOkdaDOWqpCGjSimy8vwHVdcP7y+mnny7AkhgLS4+C9957T+QZp6s83fGNymG4c7OzpjoxkbcCUQGnIk6qUqWKyB0rH6rseCEpdOUrEu55PBzD0QVdlLvyP2NV5Pm///0PBLJz0oKuPNgkKajC5ySZqiunkej6lLbIuvKz0oNS5UA0N8BIEX+tLhDywLR6MZe8SGarbDTlqPot6XLHOBAPedhdB4PnDkbPHj3RvHlzrFq1SovPwIF4yDDVhaDKcyquzMsqc8PSnZjIt0zVRnAlIgJv3bpVyYshFM/trqmVWAm7Vll6W0ybNs03DFUvJLvfSjjncWVUFqj2OQgvN7mKPAl6VadOHREvfODAAeV0e3bnn8zlVficzPOP99y0IhsnCSQ64+PEtqTrNtobYLiIv1YXCH+ldAEWoDM6K8smGa2y0ZajMnN1QcGBeMjD6uHHKJrnsp7DwHMGipQlPA80BXIgHjJMdRmo8rxjx44ChZgx3oyH/eGHH4SFVtKAAQPw3HPPRcxOu2vKztnC+F2609KCzMckkh0vpHAmZ/c8LoMyOBfnhp1+TkWeBLU75ZRTRGoi8oSWWU32OKDCZ3st6tJ2OJDo+pS2yNqRti7rOg64dQNUvUB8gk8wBEOQjWzkI9+Sv2lIQ3M0h+rLuWWDLingVjm6hD0xH0Y05BEKxTQct8GGOxtiXfV1KF68uLBiOZ3mI+ZMd7jDaMjQ4SEmZnM7dwK5wdOZ/Xv0KJZRmWnTBsVlKhrmUK12LNc13YnLlSuHgwcPYs2aNWjcuLHgw5lnnilyyZKYf/XCCy+MiD/hrCmzs0UVgdjq3LOjKEc0eb/KdpVf//RzqmuIIFgzZ84ULuIEn9NkjwOqfLbXqi6tygGtyKpyyuFyic54h9mRss25cQO0ssZKYdEq2wRNsAu7wn4xThbBu1GOycLbcObhtDysUEzDchs8Uhl7jtsjprdv376AnLXhzDnZ6jgtw2TjT1jzOXIEqFED2FPw3SlRlSrAjh1AyZKiOJXXpk2bityrzLWcnp4ufj5w4EBh3Uw7MQ1z981FlxLqcZ3BxhHOmqqCKtiBHSiJgrGSrNausZwZqFIihsaorqFJkyahX79+Ip+1TKek9G3oQoIDqnzW7IoOBxJdn9IW2eh8F7rVGHHAjRug1au0kTVTMRVn4Sxljvm/GCtXcnlBN8rR5SyL6vCclocKimk4lpPGJzcWyoBTwDhRZWqMG3dahjEevju783qBli2B7Gwg39qDBmlpAN1uV64EPAWIwHQnZvoauhfPnz/fN88VK1eg9bmtgb5AxosZjnjdhLOmGFPqTyprl+VVz714WGXD/ZhU19Du3btRtWpV0M2YSgHDHTSpc0CVz+ot6pJ2OJAUiuzSpUsxZswYMFXCL7/8gvfffx8XX3yxjw9EZCMymz916tQJ8+bN8/2IlwkmpWcuLbp49erVS8R4lC5dWpRZsmQJ/vOf/4jcY+yDoAaSsrKycM4554h/ciNQoURnvMocdRlrDrhtA3TSnct69slTwm1yTB7OhjcTJ+URLRRTzuyss84SaUAWLlyI9u3bhzfZJK3lpAyTlEXhTYvKZ2d1TAPwntTpGBowwZHefvttDBs2DEOGDPGNQSiCv3UGTgJQDHCDwqe6du14ITVDM0eU9PCEZ6+WnTWUmZkp0ifJuGd7PaV2aTt8Tm1ORWf2ia5PCYssc5YtW7ZMBOxfeumlQRVZBrK/9tprPi6WLFlSxHlI6tKli1BQ6WLBj/LGG29ERkYG3nrrrQBF9rTTTsNTTz3lg27nL+mSwTH8+OOPWpGNzneatK26bQN0yp0raQVmMjG3yTHV+G+cr5PyiBaKKcd8wQUXYPHixQI1lQqCpmMccFKGmq9+HJBW2dWrgTzzvKSgy3CzZgHWWLZSo0YNcdfxf3xRVRhjLQfVtatqjZXjd4OSrsJLO2uIxqAHHngAHTp0EEBegkLEUwft3xBPrTLGZChjh8/JMF+3zSEpFFl/pjIXWDCLLJN1z549Oyj/+SLOl3FaVlu0aCHK0FrbtWtX4WZBlwtpkSXkPGMI5EL/66+/BOIbUfpGjBihFVm3feEuH48bN0An3LlcznbHh+dGOTo+yQRq0Cl5RBvFVFq3xo0bh3vvvTeBOBz9oTolw+iPNAF7ULXKGqyx8sLIuFjeqaTHmqrCGEtOqa7dZPZCsrOGZBqeYsWKYe/evShXqlTE8dSxlHc8+7LD53iOM1n7ThlFlkos82TRCstX8JEjR/rANV599VXcd999+P33331yPnr0qHAffvfdd3HJJZf4FFmi8jVq1AjfffcdqlevjjfffBNjx47F448/LsqZuRYzQTj/SPrpp5+E8rx9+3Ydj5Csq0thXtwA+ShChEeil2pKTA5oObpLbk7JY4FnAboX6246ublH56Kjt2PYkx80aJAIYaESO3r06LDbScaKTskwGXkT8Zy8XqRnZsKzZg08Qayy3vR0eJs0Qd7y5b7YWPY5Y8YM9O7dW4A9rWTcbCGYUmZ6JtZ41iDPc8zCm+5NRxNvEyzPW66U2zXiORkaUF279EKqVawW9nr2Kg+hsrcythzdEgAqpVw5hgXtriHK9dtvvwXvxL2vvbbgG8nJgUchntqblgZv06ZFvpkYTjduXdnlc9wGmqQdU59i7uqdO3eimh/CeqJMtwjYUzCL7PTp01GqVClfkm7Ci/MlkfEAfFl84oknRAythI6Xk69UqZKIA7n99tt9iiyVXbodc8EzPoRKMeNxqdSGUmSp6LItI02ZMgUVKlRIFH7rcWoOaA5oDqQEB2ipGdR2ELaV2Yb8tKLAOGn5aah5oCbGLB0T9kV91qxZeOONN3D++efj7rvvTgm+6km6gwMVc3KQGeROIke3fOhQ5DZtGjDYyZMn46OPPkK3bt1w6623it/lVMzBsMyidxtZcejyoWiaG9hOtDlgd+3mHpeLP0r+oTysMkfKoMLfyXdvY4gDjTf169cX9+Uf1q3D6F27YP6UF8iyYN+MMlN1Qc2BMDlA1P9bbrkluRVZI2+2bduGWrVq+WI87CqyX3zxhYCaZ4xIgwYNhPsxf6YtsmF+hSlcTb/kJYfwtRzdJUcn5GFl0ZEzjsQqSyWWBzA9MqggaDrGASdkqPkZggMmVtl8WtaaNEH+V18FWGPZEtOz5OTkYOrUqbjyyitFaptg1ljZa7yssrFYu4nwbdldQ5QtZexPrU44Acv//juo5V6WM7PgJwKPnBijXT470adu4xgHUsIiG0zgFStWFO7Fffv2FW4Uqq7FtMjSmkvQJyYAZzt0t6HrcihF1jiGRPfp1ovIGQ7o2Apn+BjvVrQc4y2BwP4jlUesUEyZvqRz584iXGXt2rXuYmKcRxOpDOM8/MTo3iRW9ujcuSjWrVvAHA4dOiSyNuTl5QmwJ96BVEGSYgmOFKu1mwgCtruGGBrHeyz3onbt2glPRWbx+NyPNe4AACAASURBVC0/H2WsJmyIp7Yqnky/t8vnZJq7G+aS6PqUkmtxMCWSrsBUPnv27CnSHzBeddWqVQL5mLRgwQJxwTCCPVGR5Wb+4IMP4umnnxZoxSynFVk3fM6JNwa9ASaezIKNWMvRXXKMVB6qF3Q563Av6rwwNmnSBAxjIbK+pmMciFSGmpcKHDAgGNOytv+MM1D6229RvESJgAaI5cDcsUQt3rFjh7DGtkRLrMZq5MEc/Tgd6YhlyppYrV0F7sa9SDhraCEWYgAGYAImoP+Z/UXI3fu1a+Pi7duDo1yboFvHffIxHEA4fI7h8JK+q6RQZPlSSMQ1EmNXn3nmGZHztXz58uIPY1OZF7ZKlSrYunWrgBg/ePAg1q9fD6bhITH9Di8SL7/8si/9DhGMjel3pCL7zz//4I8//hCAUYzL1Yps0q+VqExQb4BRYWvMG9VyjDnLQ3YYiTxiiWK6e/dugXpPqwfPFGI2aCrgQDgy5JnOOL+HH34YZcpY2pA0q8kBg1WWcY4Zjz5aBHyQGRtGjRqFPn36CEudGxXGWK7dRPh47K4hyb8sZCGD//XPwEsvvoQ7e/TAC3PmmE85ha2x4e5VifD9JMoY7SqyS5cuBdNNZWdni7Srxkw31OmCEY2XBGgMRsFwkOrVq4dNmzZZslFYZGVqHGPp66+/HhMnThRgTPT9J1w8U+nwVZGpcipXruyr8ttvv6F///6YM2eOuFRQ8Z0wYYIPXl72IRVZY19akbWUlS4QhAN2DxrNRHdyQMvRXXKJRB6xzKVMN02i6efn54sDlY+tmsJXZHluE0CLSNBMiadJgQPSKpuVhfzmzTHnscfQtVu3Iops27ZtBRYIASpvuvkmYY3NRjbyURQIzdhrGtLQHM2xEivDBkZTmAliuXZVxhPvMnb3QePjxJDZQzD8kuEQF/KTTgKMuYeDWWNTMPesXT7H+7tItv7tKrL0pF22bJnwwL300kuLKLJ8YPYnlr/55puFwbRmzZqmiux7770nsJMkMZWVCphvEdfiRBGQXcYnyrz0OO1xQG+A9vjl1tJaju6STKTyiGUuZSqv9AbiYyvdjDWFr8gy1phW2dtuuw2TJk3SrFTlAC9fAwbg6DPP4KMjR9C1a9cARfavv/4SIVX0GhCpB+tURw3UwB6ou8NXQRXswI6op6yJ5dpVZW+8ytnZB42u4nQJb7S/EdaevFY8tP04dSpOu+66olPxt8YyxWSNGoCdMAk+3u3YARR6R8aLV5H0a4fPkfSj6wbnQCT6VLBMN8ZeaAylF++iRYtMRUCLLA2aa9assS0mrcjaZpmu4CYO6A3QTdIIfyxajuHzLho1E0kejRs3xrp163x4C9HgRyK2aVeGBKo56aSTwFCj8847D3Qf02SPA2Y8//zzz0WKKLrBEyGUlz+tMNrjbTxK21lDZq7iZ7Y6E5tWbsJrr76KGyZOPGaVDWaNldb97GxAIfcs0tIA4tIwJ7GJO2c8+Ga3Tzt8ttu2Lm/NAanIbtiwAaeeeqqvAkNHZfioWStWiiwfmZmbluEU11xzTUhFlu7KDGk57rjj0Lp1azz55JMiNasVaUXWikP6967mgN4AXS0e5cFpOSqzKiYFE0kenTp1EuCCr7/+OhgOo6mAA3Zl+Ouvv/rcuJhNYO/evZqVihzIzc0Vij//EEfk7bffxoknnuirzVCsIUOGiJQ706dPV2xVF4s3B1TXkBlwF62ylQZXwi8jfxGX+Gl9+gCdO4tp7QOwbOhQ9BgyRITj+cgECduUF0kQX6vK53h/D8nav1RkjfMbOnQoaCkNRVaKLONiR48ejZ9//lkoqGZE92M+otINn2FCxGbio98333wTsJcGq68V2WT9MlNkXnoDTA5Bazm6S46JJA8qr8wny8OSaPiawlNkmXUgIyPDx759+/YJMEZNoTnw1VdfiVQrXDOSXnzxRdxxxx2+f3fo0EG41Rl/rnnrbg6o7oMhgbs+B3A+BLL67l9+gadVK/ySlYXzSpbE1iNHRPrKG2+88RgjDEjYphxKIrRjVT67+2tJ3NFF0yLLNKvM8/7888/bYhAxmYjwTvBhxteGVKYJ9mSrdZcUjsSn2yVT0MNwgAN6A3SAiS5oQsvRBULwG4JT8pg6daqv1euCxYc5MG2Zyu3uu+/G+PHjHWgxOZqwK8N3330XV1xxhW/yX375Jc4999zkYEYUZzF48GCMHDlSuM+dfvrpIN8yMzMFGAqJcbGMj2WcLK0LDRo0iOJodNNOckBlDVmlUUo7kgaUB/IP5+PWW2/Ffa1b49J+/bDhn3/EUAkCRtfzAFK1yiaBNZbzVuGzk3LVbQVyIBJ9KpRFluB2/L4Z98oQILvEh1U+AtLFOBRpi6xdzuryruKA3gBdJY6wB6PlGDbrolLRKXlQkW3WrBlWr16NaCmyfLG97777cNVVVwmXTk0FHLArQ7qA+Vu0Jz/2GG655BJrdlaqBFSrZl0uSUsQ2IlucbS28u9E5aR9gC7G/PuKFStEvBet23TXDnAjTVKeJMu0VNaQUhqlYQAMHpoSpI7fyg8//BAYC2hllU0ia2w4e1WyfF9umUe0FNkbbrhBPN7R28cu0c2Y8bF0bbZC0NeKrF3u6vKu4oDKQeOqAevBBOWAlqO7Pgyn5BELRZa5yq+99lqR+/yzzz5zFyPjOBq7Mrz99ttFHnhJ9wEYqzL+JEBNVZlmsDJUQqiQUEGlizHTUdCKsHbtWgwfPhy01j711FN46KGHRBpD5lvUlDgcsFpDVtZYOVPGytZZWgcl7iohgOmYUoTx1FxztMbKsAhe+Pnd8E8TIhcXxtMG5ViSWGO1Ihv/9WBXkaWSyVQ6pKZNmwr3X56/5cuX9z3I/PHHHwLcbty4cejXr1+RSbZv3x6XXHKJSNtKuv/++9GjRw/hTsx4Wsbn0pJLACpiNoQircjG/xvSI4iAA1YHTQRN66ox5ICWYwyZrdCVU/KIhSJL5ZWHYv369cWhp6mAA3Zl2KVLF8ybNw8tSpXCqsOH0Q3AXCtmJglqqtU0zX7PCxdRPtPT00V6CeY9HDRokMjDW6dOHWGpbdWqFRhvPGHCBNx1113hdqXrxYEDVmtIyRrrN+6Pjn6EvE/yhJslrU2TJ08Wqa7OPvtsodDy5zt37gTTYK3OzkZ6ZqZa7tk48MbJLq347GRfuq2iHLCryC5ZskQorkYiXgVBF0mvvPIKGO5D4CYiERuJYRi02EowKXpU8XGHoINUXNu0aYNRo0ahVq1aliLTiqwli3QBN3NAb4Bulo762LQc1XkVi5JOySMWiiyVV8YdMg7x999/jwV7EqIPuzIkKMfmzZsx5NprMXzaNDBt/VaVmSaRZUhluv5l5s6dK6wIDRs2FPl3yfOZM2cKcJLDhw8La+3u3buFpZaXtFKlStntQpePIwdCrSFpjc1GNvKRbznKNKShOZpjJVbCA48oz/2K3wjjqBlXvXz5cl87VARuZeqRYFbZJFtzdvcqS2brArY4YFeRtdV4DAoLRZYbLPP3ZGdnC+2Z7i90gyHxA3vsscfw8ccfY9u2bUKzZvAtXSGqVq3qGyK1a/r5+xMDdOlSQ5IaPC8b7MMfhjkrKwvnnHOOKKeKPZXojI+BbFOiC70BJoeYtRzdJUen5BELRZYuTPLF98CBAyIXqqCdO4HcXHXGJlmspx0Z5ufnCyXryJEj+Gr5crTOzBRX7cMA/BMm5AE4AkCoY0kWp6f+oRwryRQRtCj06dNH5EmUPH/nnXd88doEgfr666+Fm52mxOJAqDV0BEdQAzWwB3uUJ1UFVbADO1ASJX116F45e/Zs8W9a9Ikl8NprrwmU4++/+w4nXXhh6Nyzyr27t6Cdvcq9s0jckSW6PiUUWbq/EGGPr4aXXnppgCLLi8Fll10m0Nbo9sAXpIEDByIvLy8ggJeKLF8hWU4S86idcMIJAYrsaaedJmJGrr76al85+k9zDD/++KNWZBN3LcRl5HoDjAvbHe9Uy9FxlkbUoFPyiIUiy4lK4BQ+irZo0QI4cgSoUQNgnJkqJVmspx0ZShdZAhH9/fffqFS+PPYfOoS1ABr58a8tgO8B5JDn/HmSWYZUPxVZ7qKLLsKHH36IZ599VtyLJM9LlCghgJ9Kly4t7lZ0FdWUeBywWkM7sRO5UH8sq4RKqIZAYLT33nsPl19+uWAOXSkZK0hX4++++06Ar42mC6e/VTYJ15wVnxPvy0msESeFIuvPcqvktiwrLaj+SGtUZOkPzT/BSFpkad0lit+nn34qihGSni+VRKVi0nBtkU2sBRDv0eoNMN4ScKZ/LUdn+OhUK07JI1aKLCH+CfU/bdo0XHPNNXTtAVq2BLKzgXxrtz8kYaynHRlS2WJMEoE2duzYIdwcCV70jseDKwoz9NFpu3zhB/a4x4OhfDBYuRLwFLhJpiLxYZ6XQHq1nXfeeQFxycNmDcNb9d/CK41eQQd0SEX2JPyc7ayhcCdLL4jMHpnYUmELZkydgU7pnTBnzhz07NkTfBD5adcuVOjWjRdvgHmek3DNxYLP4conFeqlpCK7cOFCdOzYEUxYK924qMjyJZcfJIPYeZm45557hKsESSqyjMHh6yRfm1juzTffxNixY4V7Dl0szBRZLnb+kfTTTz/hrLPOwvbt2wXYgqbU5AC/Nz6KMOFy8eLFU5MJSTBrLUd3CdEpeUyfPh1NmjQR6IMEc4gW0avn1VdfFWEwQ4YMEd14FixAse7dlbs8OncuvB07Kpd3e0E7MiTyM4E32rVrJ/ZTelbRVZYZQ4YWTvQL5rws/DutsVvffx/FecFOUSJSMd2GSQQooQea5HmHCzug3XHtkJ2Wjeb5zbE8b7kvLjJF2ZWQ07azhsKdIGNtM9MzA74VeCE8JJm6hOA511aujPR77kHe+PHwtm8fbleurRcLPrt28i4YGPWpM844QwCNyT3NBcNSHkIRsCcriyyVVSZJJzAEX78lEX6Z+QIJv8yA9Ycffhg33nijgGUmSUWWrsn8OSGbeeG44IILRDwuldpQiiwVXcajGGnKlCkCylyT5oDmgOaA5kBqcoC4DlS8aBVjTllBXi/aDhqEMtu2IS2EVTY/LQ0HatbE0jFjUta6OGPGDFCZJfozkXUlPy8tXRrvHj4s+PcigIJECQV07733imT3qUrMjcw0KcQKeemllwLYkFMxB8Myj91Xhi4fiqa5TVOVVXreIThg9q288cYbmDVrlnhcolFIk+ZAtDhAVPVbbrklNRRZvpr06tVLuNJQMfWBagThLl/H+/btC+YbKlmyZIAiSxcwxpPQsku0SbbHn2mLbLQ+0+RtV7/kJYdstRzdJUen5BEriyzjFInlwAfSlXS9KyRVq2yyWWM5fTsyZAoQWn6Yu+/RRx8F0XiJl9HojDOwdvt2wU1mApwEoCyA/YBIK0OX2lQlAl7yMf7KK68EXeglzxd8ugAjuo/A2rS1yPPkId2bjibeJtoqm4Afip01FM70pDV2jWdNkW/li6VfCGBVpiKhpYzx68lK0eZzsvLNqXmljEWWH9oVV1whkIuZt+/kk08OycNvv/1WQNJv2rQJ9erVC1BkCYDA2BJadblI+RpM1LZQiqyxs0T36XbqA0z1dnRsRXJ8AVqO7pKjU/KIVYzsxo0bRagJzxaiGNOzSJCMlV29Gsgj5q6Bkhh5144M6Rm1ePFi0ApE1NTvv/8edevWFdkF/mjQAMXXrMG5eXlgcpBnTjsND+7eLRRleknRMslUM3y0oEdWqhAfTphqhxkfCNAjFdlRWaMCrLGSH/MwD53QKVXYkxTztLOGwpmwWR5afisX/HuB8DbkfkbU6wzGxyYpRZvPSco2x6aV6PqUkmuxVGJ5uPGwo/JpRXQ7JiQ9TdblypULUGSZgodobE8//bRAK+7cubNWZK0Yqn8flAN6A0yOD0PL0V1ydEoesVJkmYfx+OOPB9PIEIE3INXJ/PnBczH6NIx5QKfkUzDsyJDxUQR5omcUQZ/IR6b/YOznl+PGIfO++4Ql9g8A619+GU8uXSpckf3ppYcewu2F6Kshv+YET3P05ZdfCqTiSZMmCSVj0aJFIkSK9M+//6DBoQbYXna7sLBJSkc6mqFZQA5Rd614PZpgHLCzhuxyUOahXY3VyEPwb+WyXpcJ92I+GMnYf7v9JEL5aPI5EeYf7zEmhSJL998tW7YIXtI1i3Gt//nPf8TrKi8EfHnkqyvdjSpXruzjOX9PVDWiG9Kdi3UIeMB/06e/S5cuIm6J5B8jS0WWFw8eArTs8vVcW2Tj/SknZv96A0xMuRlHreXoLjk6JY9YKbLkXu3atbF161bx2Hr++ecfY6iZVTaJrbGcvKoMjx49KiyvTKnHC40ET2RKEKYGGfb447h+1iycvm4dins8+PPvv/H9li0ivUyVypVxwpo1+Oyff3AZgHdVPuMETnPEx3c+wkvioz6/Od57SB8d/Qjdi5kDjGmrrMoH4p4yqmsonBGbWWNlW/xWdk7ZKYDX6MbPe3WyUjT5nKw8c3JeSaHISiXTyJjrr79eoAnztTYYyQsDldw77rhDuBETWZjl6Z5EMAjGxwZTZI3taUXWyc8yddrSG2ByyFrL0V1ydEoesVRkqVjRw4eWMsZ8BpCZVTYJczLKeavKkJZYntk8q+kiLGPxyEeiQRPQadCFF6LH4ME4+4wzsG7bNtHFQizEAO8A9LvsEAbO2gkGG+0FEDKSL4HTHPGyR3drpgykks8YYnqT8WGeRAtbRn4GcpCD/LSiKZ+0VdZde5zKaFTXkEpb/mXMrLGyjPxWZu6aieqnVRfGntzcXMuQPrvjcEv5aPHZLfNz+ziSQpF1O5ODjS/RGZ+IPHfjmPUG6Eap2B+TlqN9nkWzhlPyiKUiSy+gZ599VqAWM6VbABmtsunp2N+oEU5YsQLFS5SIJivj1raqDOfNmye8p4hlwcdoSfTSqlOnjkhrRivkyJEjRVo9hg3Ji3gWstB8Xx1srvg9DgHIAdDEasYJ+njAx3mmCyQy9ueff34sDrtwvlYWNskWbZW1+kDc83vVNWR3xHa+lfvPvl+k4Xn77bejmsLM7hycLB8tPjs5xmRuK9H1qSIxsokirERnfKLw2e3j1Bug2yWkNj4tRzU+xaqUU/KIpSI7ceJE4RnUo0cPEcNYhPysshuIuluqFNpdcAHmzJkTK7bGtB9VGT7yyCN48sknQQ8sIhdLYk535of/8ccfUaVKFezevVuUe+ihh2C8iGecfgKyfvgT45iWx2yWCezKTbCdli1bCuU1KytL5Pj0J5+Fzbs6IDbWyAppaes/tX9AXlkqyZrcxwHVNWRn5FbWWNmW/FbaPdAOY8eMFXmeX3vtNTtdJUzZaPA5YSbvgoEmuj6lFVkXfER6COFzQG+A4fPOTTW1HN0kDfX4SqtRx1KRJegO01XQ/XPz5s1FhyatsllZuLp8eUz/7TcUK1YMBw8eFDGiyUaqa4p54Zn7nZdkXpb96aabbgq4PBMno2u3rmiJlpAgNbxwVx1ZDjsH70M3AHNDMTKa1tidO4HcXHUxEnSK34RFHSr0bW6+GcvXrsUNl1+O12bMKPpGgvnojM7Kfd+/8H7ccEoBrxmapRVZZdbFtKDqGrIzKFVrrGzzkXcfwRNXPAGuUwKNJSNFg8/JyKdozUkrstHirEW7ic74OLEt6brVG2ByiFTL0V1ydEoesVRk5ZlA5ZSxnnSJLUILF2Jz376ov307qKCQaGFr0aKFuwTgwGhUZPjnn3+KGE8CPjG1nhEPg27EvXv39o3mhx9+wMbqG4sqbfQpbgaUBvAbgCKcj7Y19sgRoEYNYM8edc4RuJLfwF5G9prTegCNAPCpY2vFiqhKhbkQ+4O1pIUtG9nIR9HYWGPLaUhDjX018OGeD4VVViuy6iKLdUmVNWRnTOF8K3WX18WmczcJ74jthTmd7fSZCGWd5nMizNlNY0x0fUpbZN30Nemx2OaA3gBts8yVFbQc3SUWp+QRS0WWKWOIHksl9rvvvhPxncGILrTMlyrp5ZdfRt++fd0lAAdGoyLDhQsX4sILLxR53amk+vLvFvZPd2KZyqhMmTL47fff0MrTymeNlcNMy0+D52Qgb38+iK3aKtj4/ayxjL9l20z1E5TsWleZErBXLyA7G8i3ViZB0KlmzQq6Zo7hEHVeBNAfwIUAFjCX58qVgMxTDOAIjqAGamAP1JXoMn+VweLti1HCW0Irsg5869FqQmUN2ek7nG+lwo4K2HfGPpEh5O+//y6yRu3079ayTvPZrfN067i0IhsnySQ64+PEtqTrVm+AySFSLUd3ydEpecRSkSUHmzRpgrVr14q41+7dC9Kg7N27V6AYV69eXaTlueKKK0SqGSpwn376qUhv8corr7hLAA6MhjL87H//wwWNGqF4sWJBWxz80ksY+d//onfXrpg6YgQQJMdrw4YN8e233wrXxsFfDjZ3oe0FYBYw0uPBo4XWbtGpwRr7008/4eyzz8b+/fuxfv16NGjQIHBs4VhXmdJn8mSgRw91zlGxJnUO7RJ8RWFaoZEAHjVxjd6JnchFLo7+exRfLvsSbc5tg2LFg/OcXX4x8wt0OLNDoR6tXYvVhRbbkk7tg/6jlt+K6kzK/lMWtUrWEsWJXFyhQgXVqglTLhp8TpjJu2Cgia5PaYusCz4iPYTwOaA3wPB556aaWo5ukkZixsiSg1deeSVmzJiBcePGifRvJKLtDh48OIDBnTp1wi233CLSqDRr1gzZtOQlGf176BDyTjsNx+3fbzqz8wAw6m4ygFtYKkiOV/Jx/Pjx6H9Xf6ycsLKINVY27nnRA29/L9jmUmOPhQog3bmZJolIyaRhw4ZhyJAhgaVlLLMd6yrBl1asAFq1KrCw5uWZS9NfsWapli1N69D5/BRA2FqXnnkmztuwIcAaa+xEdR+TDzysr12L3bvwVOUZ7RlUqlRJKLFr1qxB48aNo91dzNt3C59jPnGXdKgV2TgJItEZHye2JV23egNMDpFqObpLjk7JI9YWWSpGzH1+4uUnYtaMWeiADiIP6hdffCGQZplehnNbunQpeDmsWbOmiKU9dOiQcN1LJvr3n39wqEEDlN22DZ4grrN/AWAG1H8AfA+gtkmOV1pOX3zxRdS6pRaurny1OYuYXpbe3PnA7LQ0XMQ+DdZYWr793bhNHxHM8v6a9S4tpar1/C2rIep8B6AegJIA9n/4IY6zsPiqrhutyCbGSlOVZ7Rn07RpU6HEfvTRR+IhiLTyijt83bac8VK0hxDV9t3C56hO0sWNJ7o+pS2yLv649NCsOaA3QGseJUIJLUd3SckpecRakV2xcgVat2oNnAg039ccnx35DCeXP1mAGW3dulWkkaHSSiWW1sGTTz4Zv//+u7DIUqlKJqIMs0aNQuawYUGntRjABQCqAtgFwMNSJq6zqilDPA954H3KK6yY3wIo59cmgWroUkyAKabwefrpp8G4Zqb3YYxuABnz/vr98iCApwHcCKCmEUQqRD3RRDDQqRB1aKm+DUC7E0/EkgMHQlpj2bzqutGKbGKsNFV5Rns2DJOgEjt58mThSSIV2dOuuQg73/oAWpGNtgSSu/2kUGT5Oj1mzBhxmP/yyy94//33cfHFF/skxwN/6NChYhHxdZaxMszZ5w+m8dtvv+Guu+4SsUlpaWno1asXnnvuOZQuTRxDYMmSJfjPf/4jEBLZh3+6A6JGnnPOOaKcRJK0+mwSnfFW89O/V+OAWw4atdHqUmYc0HJ017fhlDxirch+kv8JulbtWuALugAYdmQYhvYYKiyvVGSNxHQ9TNtDSyFjZZOJhAw/+gg9Ro5E2po1RdxthwIYDoA21rcsUIWVU4bQzNsUwOYCRfNVP3Ak5vjlveG8887D4sWLRbwy04k8//zz6N+fcEoGMrGUUi1/nG7kAKazilH5trLKBlPWTeowu+ubAAZfcw2GT5tm+XmorhutyFqy0hUFVOUZ7cEyxp/3b3qb8C6uFdloczy12k90fUpYZD/55BMsW7ZMuF5deumlRRTZp556SiRC/9///ifg+RlvRJCGDRs2+BTSLl26CAV10qRJ4lXyxhtvREZGBt56660ARZYvr2zv6quPuSj169cPHANfZrUim1oLKNLZuuWgiXQeqV5fy9FdX4BT8oilIiuthqtuXQXvFC88/T2omFYReyfsBc8YKlFGevDBB4VlkO6uRC+OGdlF5Q0CwmQ1VinDbsWKoVgh8JV/nbYEHQLAWQvMZgtrrGp6Gc8yD7zneZmXBgufegrtH3gAR44cEejHtH4vWLBAAG2NHTsWgwYNErl/CbpVhEwspecD+BwA4W+2BEERFil1gsW9hlLWTerUAPAjgE8XLECHC4lbHJpU141WZK046Y7fq8oz2qOVIRP+wHR0LdYW2WhzPjXaTwpF1l9UhN/3t8hSsaxatSruu+8+3H///aLogQMHULlyZbz++uu46qqrsHHjRpx11lkB+fgI5kBffjKI9aVF9rHHHsOKFSt8B9dff/0lDrgBAwZgxIgRWpFNjXXj2CzdctA4NqEUbUjL0V2Cd0oesVRkfVbDOQB6AqgOoBSATcDMmTPFI62RCAxFgCg+un799ddADBRMhIvKu2NHQP5Sqy/GJ8MuXVCcaW78QJB2AqCSRjCj7WlpOJ1gSYa0MrL9cFKGlOpfCodfPIzWrVuLR3Lyn8Bap556qkjzk56eju+//x5169YF8/4SyIbeWkXIYCk9AqCMSHlTQAdmzsRJQeQKM6usibIuGjPU2QHgDADF0tOx/8ABnHDCCVYs167FlhxKrAJO7YORznrKlCnCY4R3aroYk7QiGylXdX3JgaRXZJkkvVatWsjJyRGpDSS1a9dO/Jvuw6+++qpQdPnaKokxSXQffvfdd3HJJZf4FNnNmzejUaNGIs8f0yG8+eab4mWWLhMsZ2aR5YsukQolyAAAIABJREFU/0gihD+VZ8bd8HDUlJoc4EHD13y+8BO0RVNickDL0V1yc0oe06dPF+cEgUr46BktojU2Mz0TazxrkPdXHsAMFXRzJaUBe3bvQbmyImIzgJjPlOdIyZIl8dsvv+D4M8+EZ+9e5WF6K1fG0SVLgD/+UK6DChWQfsUV8OTkBAVhMjbkTUuDt2lT5C1fbhmj6V/XX4YlFi8OsMo+wVQyjP1k2A91uK9G4u6Wb2J83ni097YvMhemDNmHfcpz9P7iRbu67cSZPX/+fHFP+Pjjj4UFdtSoUb52iMDKh3B6e/l7afkKeL1Iz8yEZ80aePLyBMIyUZElfbZoEdqc5/+Twt8Y6nnT0+Ft0iQ0Dw11/ufx4AavFy1bthRgYSqkum7kumCb0V4bKuPWZYJzQFWe0eYfDUM9e/YUiMUMxSOtuv5eVLuiG3bN+Agt/vdMtIcQ1fbdwueoTtLFjVOforftzp07Ua1aNRePNPjQioA9GS2yy5cvFzGxP//8sy8xOptiLj6Wfeedd/DEE0+Ig4hKqj8RUIMuEbfffrtPkaWyS7djorARdv+CCy4Q8bhUakMpslR02ZaR+FKVjHm1Eu5L0gPWHNAc0ByIEwdyKuZgWKbf+XARgA8LB9MKGDpuKJrmMngzkPhweu211+Lw4cN45plncMNLL6Hs1q3w+OdBNZmT1+PB/po1cfyvv4ZMcWOs/nfZslhz551o5afQWbFt+dChyG1adPxW9Xy/93rRdtAglClEMD4TABF5p3g8uKRWTbT82oMt5bag9u+1MWbpGHgKoJ8iIsYdU3nlQzgfnAns9MILLwRclGixp7WWuWR5xgd7jKyYk+MDrKIK/JjfqAh8I/MFGwfrX4+/U+GhrEMgrLsKAat4L7n++usj4oWurDkQCQe4fu655x6UKVNG3LU1aQ44yYF9+/YJEDGtyNpQZPm6OXDgQCxcuFAcYDRr82faIuvkp5kabemXvOSQs5aju+TolDxiYZENsMZ6CvOHvgrg5gKeeh7zoNmwZlietzyogtaxY0fx0MoX6avPOQd933lHeCWr0FGCGz7+uH3r6rJlSD/3XJ+l0ayvAEvirl3APnWr6NFy5bBgwwaft4pnwQJhlV0BoHWh1/VuxsmuGIZuLQsAZEgTt0/EuYfOjdhSyEvRmWeeKdxtSXTfppuxP/Hxm0CPDDG67LLLQMWWbscB5Gcp7ZyXRwwvVC5WDHuOHsUNN9wggLqCUmG9tOxs5DdvXsQaS0sw6zM++qabbhJN/LpvH24480zML7SwE6ySgFS/NPgF96TfY2qxlv2rrhttkVVZXfEvoyrPaI+UigZD9EgHDx4UHiTaIhttrqdO+0lvkXXatZgWWR4OBH3iIVexYkWRwH727NkhFVnjJ5XoPt2ps0SiO1O3xLBEd5bJ37qWo7tk7JQ8YhEjGxRRl6jFzAHDINClBf6o8zAPndCpCKN5/tBLiFZZ0inFi+O7vDyUDpJ71VfZHzhowQKgc2d1AYaR8/RI69aYXK0aLjl4EKqBNHR7nvvCC+h80UUFls5CQKPbV63Cy14vens8eKNFc7RcCaz25CAPeUjLT0P9v+tj+vbpyFmdg+uuI25v+CTRVtkCc9ESudhI0m2S3xwVSnpZ0dsrgObPx9HOnUXe2z+JWty7Nx5/803h2bWasb9mtHAhMGAAMGEC0KFDQKlrrrkGb7/9tvgZ/8/4w/bt22PVqlVgkErfiy7Coy+/jMpVKqMlWiILWchABlZipanFWnXdaLCn8L+pWNZUlWe0x0TPkeOPP1646tM6e/rpp+sY2WgzPYXaT3R9ytK1WII9EeiJcbCkP/74Q+ThM4I98QAg8jGJyISdO3cuAvZERZagDhItkmjFLKcV2RRaNQ5O1S0HjYNTSsmmtBzdJXan5BFtRTZkflMmGyWq0bNMH5qOZmhmqoQwt+mHH34oYjj5Ov1fAAU2uhAkFVKr3KWyiQhyngrU0mHD0A3AXKtx8fdpachv2hRzHnsMXbt187nsHpg1C6f36oX9ROIFkJc1Ep1b+DvrFjQ+acckHP/F8RErsrx088GaijSzEpQvXz7o6OlezHAluh8P/3A4BvcYHFjO60VWgwY4Z+NGlE1Px6pNm1C7Th2UKFFCWKj4fzu0Z88e8ZgurcUcH73DGK/KUKXPPvtM5LwlGR9KzB5EWFZ13WhF1o604ldWVZ6xGCFTiHE90ashMzNTK7KxYHqK9GFXkbVK2UpPF6MLfKdOncBHy1DEx06mgt29e7eIB2dqNpmaNVQ9ocgyQTxBL0h84WSsEHO+8tBh7CrT5YwePTog/c66deuKpN/h4cAUBlz8fOFu0aJFkfQ7UpH9559/hELMhPR8fdWKbIqsGIen6aaDxuGppVRzWo7uErdT8oi2Iquc37SQvaGUEBbhWffQQw+h5QknYMXffxfJvSqaCZbGxSp3qRRvGDlP8zp08AFxFAPwCwqwrKzo6Ny5+OjoUWFpZCgP8SyY751EOI/tLZoj82uPzxor20vzpqH+X/XxwMwH0Oe6PlbdWP6eQJF8SCDIoxnxQaLyHZWROzEXFW+viD0v7Sli9Rzbty8GvfIKerRqhQ+WL0e5cuVEBgUqn7z02CECTjGDAi9JvOO89957ovpJJ50kctw2a9ZM/Nv4UJKO0A8iqutGK7J2pBW/sqryjMUImX+Zbu70ICECuEYtjgXXU6MPu4qsVcpWKrLUB1977TUfA+kOzz3bjHg+9enTR+iQBNh79tlnBVgww09oOA1FQpGVqXGMBQlwQKsrrbJMwsxYlP3796NNmzZ46aWXBHS+JB6QTGo+hzFDaWno1asXJkyYINyISbIPqcga+9KKbGosGKdn6aaDxum5pVJ7Wo7ukrZT8oimIiuVDNX8pmlIQ3M0D+kaysOXqI1E3V8LwFT1MiqkVlZZsxymCjlP5xd6N8kvZKLHg36hwKgK+/r3yy/x8SefCJBGXgwklS1dGmNPPBHV5t6Fzs0eMf3w7l94P8Z0GBOTD1M8SMzuDFwCoC4wb3OBGzgt5YsWLRIXoOHDhwtcDWY5oHfY+eefj88//1zcUeyAMVG2tG4xhveNN94QSgH/MP3SrFmzBLilJLOHErMHEdV1oxXZmHxWEXeiKs+IO1JogGnCqMSOHz8ed999t1ZkFXimi6hxwK4i69+qESCYv6MiS12Rep0q8YwijgIBAUn0zqHXzF133SUel0NREddi1U7jXS4Sxsd77Hb656ubpJYzXrJTNSXKuumgSQmGR2mSWo5RYmyYzTolj2gqsuHkN62CKtiBHSiJkqacIegQXV37V6qE53/9NdAqW6gkPnPllXh7+nQ8+uijAnVfkJVVNkgOU55jX774Iq4YPZpZggKpsDxdbvkyTe+lX3/9FW0BfG4l13nz8O8FFwjUYOadnDx5ssijy1R5RD4N6ZJNz2RvGmr8WgNbK2x1BME41HB9DxL7s5F/cj6QDzTe2Rg51XLQ/87+4tHcn6hw8sJDFFe+2tPazP/Tw+vEE08MiK+ltxktAf5oyPLRnC7EVGaZJpCUl5cXADRlxqNQVlnVdaMVWasP2B2/V5VnLEZ77733CiWWYX50v9QW2VhwPTX6iESfMlNkuc8y5IOPkMxOM3LkSHGGBSN66JYqVUp4xvjOU0A8UFIh/uCDD0IKQiuyLv9Ok2mzigar3XTQRGN+qdKmlqMzknbq4cspeURTkSXHmN80F7nKzKuESqgmHGuP0UIsxAAMwARMQAd0EPgOjOcpc8IJ+PnPP1HK0PrnTz+N/zz4oC/nORVf5kmtesopAC2fBB/KK0RPZl0Tayy9mIgpsWPHDrx2xhm44ccfC+r5lc/dt0/kSac86O3Uo0cPMZof09JwWjAwKr+6/x49KhTyW2+9FVTo6BXF/O8kVZdsK1dsZcaHKBgwlnMAME3m68Dsy2bjulOuEzGwdP9l3BRDn+heWaxYMRHqxJf/tm3bCiWdF3y+6jPWmWFRjHNlJgR6jlH5lQBSRKlm7nHidDBkyoyseBSMN6rrJtqKrFP7gBPyTeQ2VOUZizmOGzdOfOMEKZs2bZpWZGPB9BTpQyqyGzZsEOeNJD4C8k8oCqbIEpWdiikzAWzduhWPPPKI8M796quviqLSAyK9K/tlutfWrYmpX0APPPCA8LpZuXJl6DHQtTgRZRXJC0IizTdWiiwPVkmRIlXGkr9uOmhiOe9k60vL0RmJOrVfOCWPaCuykXJNWt38EWm9+V6R+5QK5utnnIHr/RTMg40bo/HvvwvQlSZNmmD9+vXCkkeLH8Np7mzRAm3uv7/osAzWWLpNUSmlxZTU9uyz8fn69eLvPLKHZWQgs2dPocQ9/fTTQuElmKKMk6PDb5BeCvot7IsyHDBggIg5IuASLym8dFhZY+XgiWDcPC20K7ZT/F+N1QI1GQ8DGA14rvPg9A6nY/v124UbsMTw8EczJk5HsNhYgjTR9ZIIyUR5JWVlZQnMDsqUlyu2w4wMRH8NRlY8MrPKqq6bWCiyp11zEXa+9QG0J1f4X6mqPMPvQb0mlYOrr75aPEbxUcqpvV59BNEr6SY+R2+W7m1Z6lPGETKklPm9Q1EwRdZYXma/YWgIkeGNpBXZnTsDEqy791MJb2Sx2qzcfuE0457eAMP7rtxWS8vRGYk4tV84JQ+37ytmiLQ+MKB69bBy82afcPp26YJXPvkENWrUABUpvjYTG4IvyZImVK+Ou376qYh1FX4pZUaMGIEhQ4YIt1YqW3xP3taoEWqsW4emxx+PdX/9FfBB0L329ttvF262d955J5qVKoVsKmkhLL9016pXr55Q3qQLLhu1sjQav8RoWmWLjGURAGbJYcpMQnAsgYiNHTzYgGJciBDMV37Ok7gctLAyXvaXXwiHVUBMWcIctdIdU8qVrm6MvTUjVR4ZeaO6brQi68x+F+1WVOUZ7XGwfSLFUomtXbs2vv/++9grsjt3Arnq3i8gQE+1QO8XfY+LxZdivw+nLbLBRsBUq3QvZt5uI2nX4hRSZP2F7/QrayQXTn83Jo7R6bGFWpZuOmjsbx+6huSAlqMz34JWZNX5GAqRdu+evcKdlQfsyvr1RdqXRfXqoUOhUjt28Vj89/z/+tyRmcuUaP90+StZvDhy/v0X9eVQ/KyxVFiZYoCWUv6dqI5vvfWWcHV9vE8fNPnsM1y8a5eI9WzVqpVQtjwVPXhv03u4uOzFyM3NFeBNtALnAGhSROucB3QqyJVLF1xacKks88WbsUrRAMhS53hgyaBWT+rvBLYsMKQCHghFvEb1GkG76XBdByxZsAQj3hiBhzs9LB4WOnToIOrQs4hWb8YYEzSEPzvrrLMECib5TrfkYGRljZV1glllVfcxrciG+9XEtp6qPGMxKn7bVGL5OEMQtK+vvBMxs7rz0axGDWAPE3QrUpUqXLyAhWsqW3MTnxVnl1TFIvFwVbHIsn2ep4yb7dmzZ1DeMSyEKPJMuUOi1xLr8KFYgz0l+OfmfzHlVKK1cUWqyHJcpFi7MukNMME/8MLhazk6I0etyKrz0QqRlqkAuC9e16ED/rtrFxofPoyNP/6IO+68A1kv0Bk5CxnI8KEgUzFlqhvmymtRqhS+OnwYq+rXx3tduqDG6aeL3I+TJk0SwEskojES2f/NN98UShddaBnbSRfihx9+GKOeGIXmvzZHTnoOMsoe60eil7YpXRpLDx+Gh7GyQeJwiexL5fraa68VfZCiBZClzvVjJU2tnvQ8+6ywXAdg3qcFCMZG8rmF52chI+0YfwgOsnbtWqHE8yGCqRvoos04ZgJDURFgvC1T7QQjVWusrOtvlVXdx7QiG84XE/s6qvKMxcjoWcC4QxKzf2y+7ZHw74N2rasVKwK9egHZ2dQwrKeblgY0bw4wttHPE8Wsopv4bD255CthV5ENlbKVZxjznjPUpkqVKuJxkbGu3IMZiiNjbuliTAwDKqokpt8huBPPSCq09CIiSvemTZtQuXLlkEzXYE8u/ya1IhtaQHoDdPkHrDg8LUdFRlkU04qsGh/NrG5peR40T28hlNNVWavEgUrkRSLkMscs3aMmfjcRl5W9zNeRvyLz008/oWHDhgJpsWbx4tj2779FBsQXbMa9UtHk32ld4YHPywGJl1VaD1dXXI3O6FykHyLt1q9fX9R7nciOPo3qmDWWP7rooosE8BEVuJZfbvK1U3XGw6YAWUQ4ZjwtiReIbt26IRhAlhqXzUuFtHo+AeDRgrqeaR60uKZAHh6aZ/3IzC3c2CsfCajI8wJFN+6rrroKb7/9dtDBRWqxVt3HjIqsHIxT+BRO7QORyjnR66vKM1bzJOorQeK++eYbHBr2YniKbLjWVT7AFYLNKc03CEq7WT238VlpfklUyK4iGypl68SJEwXyMPOH8xysWrUqCLDHcBp/hZT4BPSK8Y/BZeodInLzoZEYFHzo9U8dZ8Zyrci6/GOMtSLLzdGfVNyE5RhZL1ktshoFMroLRR9kzvDXf7/4rscx9D+7F2Sn5BGJp4czHAneipXVTSqndO/1R0ycPGUyXrn5FUhwomDupXQVphWURBAoohrzQF+2bJlQUv/73/8Ky60/3XTTTb7k8UyzMXbcWLRES9N+eNjzlbtisWLYdPQoymdkFLF+EAiJcbxMXVD5zXlKl95oWwrlnEPyPxtACwBlCWfJQFfAGIsayi3cqPBSOe/evbuP3fy3kf/yl5FarFXXjZHPzZo1A93T7a5TszWiFVlndg9VeTrTm3UrvNzT24APVJWmfqK0pou0KnNX27WurlgBtGpVFJXd2IFZzuwQ03Mbn60lkVwl7Cqybpu9VmTdJhHDeOKhyNp1E04VRTZabt0u/wRjMjx9kDnDZqMiG+4F2Sl5uFGRtYqB9FdO35r2Fnr37i2EQ9Tb4SuHo2taoBLK3/krWnQxplsUc77269fPB0a4IH8BBnoG4nnP8yLNjz9JIBdaDYmIvO6UdQHWWFlW9kP5/L+9KwG3ctrf7z4npeQWpaI0GyOliaSBRinjLaq/uHJNGaLBkJuQLiVjg66LuEoZ41DULZLSJKSBBlHcRipE1Dn/57dOa5+111nft9b37eHss89veTzV/uZ3je96fwMtaikScf8jjsCT06YB7WPvWbFiRezevVssfH97YILTojcVRNZJ9XwFALnFNgeykIUmiI2ebDMLV7El82JSvMkck8yMX/j+BQwoNSDq36z3vHhSOrn2GyayiRnvkn0X1/pM9nvI+8sNL0pn0n3tT0592vhutpzX+kVSXXW9LoAaS49KN5xTVZ/p8pwSQWRJAv72228LYU7h7SlwRdu2bUWuH7VQZCoK+09FhrynyILfffddTJ4iijBIgRgoeAVN4F7h8PWHF3fg/RqwHjxJEii6JllkSk6s0lyFnuWqrjKRTZfhqPi+B09kiak7VyKrptuiJ+tKUKLqIx2JrE2NVUljuz/a4bjjjgOZDH80/yPccsYtUZVUnueVikWtUVOaH1U5JPJLSi3NhR07dYxRY72eQ6l7yPSX8u/RfKgWIm3kq0SF1OA119zpNHekgsjGq3p6bUT41QOtRyZOnIhbB9yKj8d8XMi/OTG9z31BHi+RtaXLY0U2MTWaqHEwMW8DPPPMMyIvdLt27TCy8olOfdr4bKnK6jmv9ZN1ddV2XQg1lolsolpH+PsUdz7lpMhSpEQimrKQfX6HDh0wd+5cQWLpf0o6TmHyZSETKhlMQRJZmqQphQAFspCFEpKTTTURXCay+ajoxJCJrHcHTdVEwwuD8IOky5WpqkeXdynO5wQhsqTWUjGZNCaqPtKNyNrUWBNp/H7z90LN++HUH4wqqbzGL02Nqz8n3ctGtOVzKHiGnGN37NgB8p+ThfyTqH5Jld22bRs+7X2L06I3FUSW3jEe1dMVH7Uf79mzRwQTqdK7Ci4sd2H0UKJTC7n2m0QQWT9rC56vEjOKu9ZnYp5mv8vKlSuFDz6tr9/v8n+o0+eifMHhkTuDp8ZZuRLoXOCD7/l0XV21qbIB1VgmsvZ6T/YZJYLI6iBSsvGcnByRy4qCVRCRJTMnMqcyFUlkhw4dKiaTr7/+Onoa5bmjKIzkCMxElols0A6bqomGFwZBaybY+amqx2BvVfzOZiLrX2c2EqRfLYmOjQD7qYFB/DmDPofScVBUSErTQ7lRZXn99ddF1EjaYKaN53QjsmF7VlB81OcEqYew7+c6jpVUIluUqfrC1KlrfYa5t+kaGz6UkoQsLchlYFL7S9H+xn7Y/OLraP7x9OCpcb75Bmjd2tvn1Utd9VJlQ6qxTGQT1XrC36fEEVnyN6EoVBSQguz0qRCRpZ0iMo8iXxTK3UYJzGWocElkFy9eLIIsvPHGG2jVqpXIc3fxxReDgi9QdEg/IkvRBul/WcjUi3LC0TVkWpVJZWnf21CjR1fxSZunvSP+Tn9SkX9vOmlMQj/55ZdfFpsRv4ycGPNsl+fo7+tyTaJeniYaysFIFgIUWCVZRX4j1UMqvy9Z35Nu901VPabbdyf6fdR2uq5Lc9GnP/vsMxGpVS2yv9NvpuOJqg/5HNMzEv3ttvsRkWmZ3RLLI8uRG7GnkMjKy0LjvMZYcGABZkVm4fxSBQGDvJ6Vsz8HHfM6xhx+P/K+8dog5+rPk9dSjlTKzUdRkGmDWZZHH30UQ4YMESloKB3Q5/2GOM0dtnZhwzjZx72w9MJH/T1IPYT9Dtd+o+Ps1U+93kPtV+o5sp+n63xlWyvQd8mij1lh6ySe61zrM55nqNfa8KFzKXDZ+++/j9ubtMYtQ+/E5qk5aLH2E0SWL89PxWUpeVlZyGvcGAcWLEBk1iyUUgKh6Zfuz8lBXsfY8YzOibz/vvE6r/Nt75RqnG3vU9KOE5+qU6cOKCJ+jRo1it3nO5kWq19FeX169eolTIGJ0FIh35NatWqJf1OURJpAiZjSrjAVSWTJ3GnSpEliN+nZZ58FOa6T6RPl62vcuLEvkaUQzZSbSC/kM1C5cuViBzy/MCPACDACjEDqEPgz609c0+Ea7Dp0l/NDK/5eERNnTcRdre7ChgobkJvlvVDMys1C3d11MWreqGiqGCLPg1oPKnRtkHP1l1WvnTZ1mkglQz5zlCNVFpqTyYeWVNlERcJ1Bi1JJ3ph6YeP9EMOUg9Jen2+LSOQEASI7NP/bdq0EWnBqBy1fDlaGtbHXg9cMGwY1tSsKaIff/D22+icm4uCLQQgNysLu+vWxbxRo8x5YPPy0HrQIFTYsAFZubn28xPy5XyTZCFArin9+vUrOUS2U6dOIq/e22+/7YnpnDlzQMlu161bh3r16sUQ2ezsbJEYnsySKYjGwoULsX//fiuRZUU2VpFVFdtEKISsyPoPEem6w52sgS3V9+Ud2cQgzoqsP47km7kDO2JOWjXsEVTpcLb4bdusj3Dy8Nujx4/CUVgVWeWkxsqLVKXVpiAGOVf/Mrp231v7BFk99dRTsYzSaRwslMePiCzFpBg9enRGKLI2LE34SHXcdq1JHQ/TI13HsUQqsqTmUlGtHtJ1vjIpjqoKS98h1en6MxZ7WhG4KJdh6k+/xrU+E/EsuofLd82ePVtYNh5z2F/wyX+mCmu9ps8/guyWLRH57DNElHg2+nvlZWcjj9wAL78cd9x5p4gWLMtqAPkZpPOLTV1VVdk8AF9NnIjKF12EChUqFNxk0yZgR+x4a8Jq/59/ijRnLbp1Q6natRMFJ9/HEYESpchS5OK6desKpZWSrXsVStRevnx5YdJExFdVZGmQatasmThO55G5MQ3ANkVWf1Zxt+n2a18uwZ6CpsixtWeOWuyPEPvI2lpQfMdT7YsU39um79Ul1Uc2njzPflHXnVLFKM1BTRVDP6u5YPVWo/rVynOXYRlyYTcPlM955btXULtWbeFW8csvv4hNZioNGjQQqXnIkolcgIq7j2yq6kHPQRu0p7uOY4n0kTUFbUvX+crU17ywOP7thZ4BylKVKcG1PoO2E6/zXb6LApeRJSO58i1/djL2zfgILaaNA2xBmA4+9MsJE9C4f38hIJHrwe+//44lS5ZgUCSCh8n/1dHXNS83F2tOOw2vf/klXjr0UKz+/XcRYG7p0qUidg7IFbBWrUC+u3lVqyJCGVLKlEkUpHwfBwSKO58KZFpMk+LTTz8t5OdSpUp5wkOJ38kHlvLXNWzYsBCRpSjFlLqH/qQ8e0xkY6FkIuvQ8w6ekqqJJl0XBu5IpfeZqarH9EYh3NupqTjUxd/X3c4UCwtTVGJbdNpE1UeqohbH0z/9Fo/xpIr5AB/4RjmWtU0BpdqiLWqhFrZiq3MjqIZq+CbvGxx95NEixQ657tBGMS1waaN47969GDdunDAZK+5ENlX10AmdnPE3nejab5JBZCl1nlqSlaovDEByjJLjE91DpvdjIluAqAuRpbNpXb1ixQo8M+QenLJhRz6RdUiNQ76xbcqWxUcffYSLLrpIiFLTp08HWXBUoZgsAESkEUPkYYqPQ2MMuQ/SnyRUUYwavaxZswYUxDX6PmQp4uK7G4kg7/TTkbVkidmcOUzD42ucECgxRJaipZEz8OWXXw5KmSMLRUycPHmyMHWg8P/UyMlunxyGZW5ZXZGlnSCaeGlXiQhxSSaypnyOTGSd+p44yXXh4H5H85nxLJTjfXZJuD5V9ZiJWKoLQZkHmhaJTGTdatu2eAyTKqY6qvuqsfLNVFV2MzZjO7a7vTSAKqiCGqgRzeP+/PPPo2/fviLdTlVSNiIRUEwLsp4q7kRWEB9sCoxPmHqIR5V1HceSRWRTkarPuYEqJ/pZfDGRDU5kZV7kI24+HMMrt8VN97yVfxOLKvvCwIHoO3q0CMS6evVq1KxZU6yhKDXm1q1b8QaAC5s1AxYtiiGTJE6Rr71OXMkChIK9UmAuGn/mzZuHMWPGRH13be+jtyUyZy7VNT/QKZfUIVBiiCxFSSMz4a9eJ9QXAAAgAElEQVS++kqE9JeF1Nk+ffqIEP9kKkwdgnZ6KNWOnkdW7hjr1VPSiaxuGsRE1r0Duy4c3O/IRDZerMJcn6p6DPNu6X4NE9mC3NtS5QlSZzYiG+Re8tywaX7CPIuiFT/++OMiajFFKyZ3nRYtWoho/mPHjhWbzGGIrKrwCcWnGJZU1gPB4zqOMZFlRdbUnVzHoucnPY+rrrwKOAU4cVplrDppW36AOZ/UOJ+feCI6bNuG7du346GHHsLgwYOjr0ABWinyedfy5ZHzxhtA+/bi2A8//IBB4wZh8sjJII+HI444Ak2bNhU++a1btxaxcMj6gwql3yQRq3379iKThCg2lfjgG5Dv7q46dVB+5UocsnVr8Jy4xTDSbjoNpyWGyKYT6PQuxR14iafJxC9RRNak9nrVI/vI+rdwVmSTOwK4LgCT+xbF8+5MZNOLyMbjzxlGDXzuuedEBgCKXEyBFilXOykkZ511FgYNGhQXkU0n89SgvTPV9UDvt7DXTdjWsz2qTJ2NMyc/6fnKTGRTT2TD+NGnel5yJbJTtkxBr+N7AT8DuBGY+dRMRM3iNVV2CYBhAGYcbI0nnXSSsIKU/vT089dffy3MgbOysnDTTTeJ9TW5pKgKbKUrKmHdE+tQsUJFY7uW9yB//R9//DFKcF1VWYqk3GzgQBxSv34gv1pUq0apUVLjV0vBq7a7W82gShWgGJDs4s6nAvnIBp1Iknl+cQc+VUTWFAjCVC9MZJnIJrO/2u6d6gWD7X2K0/HiQmRVTBOdEiaejSbXxaNrm4jHn7MMggc5IUsnGuePPPJIUBoFUlvuvPNOkSaP8szGo8gWZyKb6npgIuvdQ+I1LZZ3lpYBYfpsmDEi1fOSy3fJDZqlby5B3sWkegK1J9bGhms2FFJl/3PgAP5GlgKAIKk0HowcORK1DZGBSWEl31m10DW5jXKBIQB6AOTP7+VHTr75lImE3A0ptzVZcJJ1JpWcHTuQvXw5YIqonJ2N3EaN8PbQoWKsOqRVK8DRrxZZWUCTJoVMoV3H6iDnvfTss7h4wACU3bPH/bJUkmz3typ0ZnHnU0xk46j8RFyabEWWiWwiaik+xScxb5DZd0n1giGT0CxORNYr+FS89aEuUtV7uZjEuiweg75fGH9O8ncNUyg1HZn3UewJyu8+YsQIEZSRohVTPveSSmQJy1TUg2r5RCljWJEt3IrjJbL6hkqYPhsvkSXzfJ1Qh+mvfte4fFeMufwIAEPzIzQ9+cmT6H96f3H7vJkz8c8uXXDXwYdd2LIlRr/wAr6p9w1uxs14Ak+gPfLNh2Wh4KzkokAbYuQ7e8KJJ+CuM+7C53/5HAdwAKo/v5flyM0334wnn3wSf//734UfLpkbU5k3ejTOHjjQ89PJN/ad/fvzieycOUDnzu7QGgJTOV0cUF19bd48dHnmGZRdtQoRMpm2lRSSbNur2I4zkbUhlKTjxR14CQsT2fgaSKoIUJhJML4vK1lXp6oeMxFVJrKxG01BU5O5LB7Tvd2QzxrFqXj22WdBeTkppsW//vUvHHXUUQklsippS7Sqnu4Ye72f2v/2jJiQECJrw1mNBi43q9VAb/Su6aSmZwqR9cJUNVsm7F020EztyTYWSTX2U3wqyCWpsSDRczpwZM8jsePlHUKVHT9uHG648UbxiIHVquGhzZsRyc4SAeiWYAmaoRkWYVG+gutRvPzL/VTZ9957D507dxYba5QOTJbbBgzAI/PnA59+GqvKHkz18+f8+Xh3xox8IksZUVq0KHyu/p6OaYKMnxciNdBvFSpg24gRqNU/f7PApWx8/nlc/PjjLqcW6Tnnn38+7r//fpGRhgL1FrfCimwR15i+CJWvoy7GTJEIXRZrthQb6qezabF/Q2Aim9yOwkQ2PL5MZJnIkikxZRM49NBDUbZsWfz000+CzFIKnkQqsiqBYiKb32eTRWT9rBdciex/f94WHVjiqa8w/qWu6wuXqMVFpcjSu1HQUsrdasprq+LisiazjfI2Imskl58BaAygFDB502RcfMTFqFevHr7//nvcV7ky7pkyRQRv0q/1NRNGnjHquk2VpZy0pOj+9ttv4lNpg43SBNH7rH3qKUS6dCkMwcyZ+POcc/Duu+/mE9lDDrFGX47eJKwaK4NQBTBhXlG9Oh5p1w6DFi7ESevXI8svpdBBkv3cdddh2L33gpRqkVs3DQvFVaD2PX/+fCayqa6fTFRk1R1VJrJuLSpVBIiJrFt9hD0rVfUY9v3S+Tomskxkqf9cfPHFyMnJiTZVCr6yatUqJrJJ7rypIrJ68EZJdP0UWSKyiTDnj3f+Kw6KrEkFdyGykmQnm8gWUmPVdn0WgAVA5VvKYeSpj+OaftfgmGOOwYYNG1CmTBno19oIqS3atx8J7tatmxiHKKgUpeCkTCbk/rDiiy9wytVXFyitiqL65/79sUTWFu04HjVW4mZJVaTCe4By9x5zDFb98AO6nH463iVl2VZmzkTfyZOFMv3aa6/Zzi6y45RhhuqJiWwRVAET2QsE6n47rolQZGXV+pnK2HYRk9k8UkWA4p3Ik4lBJtw7VfWYCVjp38BENvFENlGmgqlsb6SGdO3aVUQuzs7Oxs8//yxUWVZkk1sLySay6turMS+YyOavgWTKLZ3o6wq0bQ43WRukE5H1JZeTAfQGUB2oXq46vl/7PR555BHcdtttAqMgZsK+hBmw+spStONRo0bh3nvvFZGQyWz1nXfewQMPPIC7mzaN9X89qKga538b0QyrxsoOZSPL8rzsbDxyzDEYSD61gLB4WV2lCmpt3uwZvAqnnw4ylz65QQOhxlIk6HQtTGSLsGaYyBYQWa8d10QQWRc/GyayRdgRMuTRTGTDVyQT2eQQ2UQoLOFrNdyVtPtPiybK9T5w4MCoyhE2j6w+/rNpceF6SQWR1UkrkQUmsoWJrF9wy1QSWRcBwNTDvdZSNnKJfeQUDeBgZhgy7/3222+Fr6rXtV6qrE2Nle/tpco+eX93jLlqPm57rhWar6iBLzo0FsGfmjVrhk8WLsRDtWrhy++/xwMNG6LOZ58BkYg5/7JPTlwiili0SFwbV7GRZQBfAWhUujR+/+MPYfZMa5V/dO+O4W+95f3omTOx4PDDcemll4L8hsnEWpannnoKzz//vDC57tKli4jwLAud//HHH+PXX39FpUqVcPXVV4OIplehPL/9+vUTiiqdf8899+Caa64Rp5NFDuUHXrhwIWiTs0GDBiJXMKVlUwsT2bhaUHwXM5FNLZH9utuZ0Qrz2umkE+TuaHy16351qgiQbRJ0f2M+04RAquoxE9FnIstE1qQgq33KRmRVNctkqiotcpjIMpENE8goFabFto172xyeSEXWRQAIQmSdyCWFKB6Zf9few3rjP/f+R/zddq1KSK2E+eBLe5Fgur7BuqpYXX87TvvpeEy49hzUfmIYjjn6aBGXqlmVGliybbO4y+HlymHshAno06ePiLge4yMrwfEimvGqsfL+FlX2z0gEZ5UujSX79uGUU05B06ZNBQk9o0ULLCQfWY/gVUSyRzz4oAi8R9GgKY2RLK+//rr49+zZs0W+XpXIErmlTUgyB6cI9BQ4i6LPE0am0qZNG+F/TJGiKdgfpTyaPn066PfFixeLfMGUAok2NigQIG1uUnqkypUrR29XYogsmQgMHz48BkcyGVizZo34jdj+7bffLiqNbOEJzHHjxqFq1ari+MaNG1GnTh1ReVQ51atXj97rf//7n7ChP3DggEi+bMpvZapAJrLhiawpcIPXRCMHZCKyXsovK7KZSI9S+01MZMPjzUSWiaxpDA5KZP0UPiay3v2TFVn72MVE1o4RnWHqx5JcLsMy5CLX+0bfATgewKFA4/WNsazSMnEuRSqORjnWrtYJqY306g/XVVn9+sdGdMUtd+egYeVqWLFzq7i8dFY2GpzWEJT/mgqZ6uZGcvFnuT/Rql0rXH3+1cJFghRGHCSaPy5bJoIrVUyEb6z+ET6q7GgAgwAR8Is4ULVq1XD55ZeLoHo/Tp2Kshfkr8NjykGS3aFDB2FaTQqsqRCvIqKpEln1PIogTIrtJZdcUoh/0XlESIn0kiorudaNN94ofHInTZpkfCYR2ldffRXnnHNO9HiJIrL08bSDIEupUqWirP76668XNvC0U1GhQgX0799fkFaSyKlIIkuElc6lCIuyUKTF8ePHC4LLRHZsNGS+a7Anv2AOXjuUpp1JJrL+E41tN9dtmuKzvBBgIhu+bTCRZSKrLoBfWzEW4+9ZhzH7x2DfO/ucfGRtUXCZyHr3Ty8im7WfQsTkF13F1OdmuYlAkXGpqBvH9O9MNC1W43uYfH/VKMEuUYuDKLJqbfq17bA+solUZPdhH2qhFrYinwj6lhUAygDVjq+GjdiID/ABOsOek5UIaUd0FKTXSpgPvkAWstAETaJpfKKE+8BS5GbnITs3C8dvqISV9bdiQKNWePzzBah2ZCU82Lgt/m/my3jooYeEHy2psXohfkGCWLt27TBryhTMXrYMpCGSmW+FRKmx8qEequyqSASnA9iXl4dnnnkGpUuXRuPGjUEEdcuWLXjzjTdwwYMPGoNXbd+xA6eddhqeeOIJYV5sKl5E9oYbbhBciiI/16pVC3PnzhVCoF7eeOMN4UZCop4slHKNRES5SaBeQ2ov9TMiyETIZSlRRJZ2DWj3QC+7d+8WueomT54crTBSailiGdlmn3HGGVEiS4BNnTpV2G7LQjsWPXv2FDmMmMgykbWN0/rxVBEgJrJBaybY+amoR1swkGBvnD5nM5FlIivHJ1pMdjjlCmHa1yS3CYa+PRRdz+sKF9NiVmTD9Wk/IutFaPyILF2jblBnMpH1I+jJJrIu/t/pQGSp/jdhE7ZLB9iDzXTFkJGo1rkNtsz8UPxJhf5+6kN3ogqqoDqq+6qxsrVLVXYe5qE2arsR5oMXV0M+YS6DMr4BpQ679HWsqHUkzjq1EX5798Poxg7xhzd/fBNX4krgBwAzgLo5dbHh8w3Gzvhy3brouW5d/L6x+t01VZa2oMiTdBFFK27YUHCf//znP4IIkp/pCy+8IMx9XyST387KRsFBkk3CHwV5IkJJfsrlypUrlH7HT5HNzc0F+cG/9dZbImBXxYoVC+FBbZM2A8ikWJZXXnlFCIXrCCOl7Nq1S/jGEqnWrWtLFJGlKGSktpKkfuaZZ2LkyJGoWbOmiJB47rnnirx1Kti0k3DrrbdiwIABUSJLNtsUQZF2Elq1aiXCPVPKAFJzmzdvzkR2ePKILKX2UYvXIC5TAInBc/L0qELMpsU3pFWC+XBLrvS9KlVE1i8YSPqi4/9m8RJZdWyQ6kSi6kNV+tQFeTw5LU1oqBtNqjWLPDdo1PWidJcI0w7l+35QZSl6tywIDjJswTDc3ezuuImsfCe/eSDMe2fCNUxk7bVosvhSyXpRKLLxEFnTWspkRRfUnzjIuOM15slnhjETPhknFyLMfrVLhLkGangGlMo6EEGT7KZ4okcT1Ox1obiVGkcl6pOb9ykORA4gOy8bp0dOx6Q1kzBl8hQsWrRIELBvPv4Yz7//Pnqdcw5e+u9/C78SRRTefjDSlb05AlWqADVqFJx5UJXNW7oUkbw8jIpEMDgvT5BQirZ8yy23RPNFEzml+YvMjb/fvBnlzz0XWLIEH55wAub27InbBw4UAZqIYBKhJWWViKxORm2mxfRyxLu++uoroQjrhXgUkWVSWGWh88aOHRujyNJmQceOHdGoUSNMmDChEKEuMUR2xowZwu6a1FPyaSVGT8mWqaLefvttXHXVVcI3Vi1ETMksgHYMpGkxNQCy3SZgyfH4b3/7m6jcK664Qkj2foos3V99Bj3/5JNPFteoPrcubTidziG/YmpgVH4ZORE1enTF5mnviD+pyL/Tn1T04x/8vF1cTztGl112Wcyned1bvU/TSWPENfJc+Q76s9d1ae75nKV9b4t5X7on/aYW+ZxEY08L7lmzZglzD5FIO0lFfiPVQ7K+JUmvXixum4p6VPuDqb8UC6AML+nVz/36rNc1sm0nqj7kc6Q1j9dYFS/2av80jZ1+fdZr/FLvk+59nr6heo/z0K3NLfjyL+uEaV9Wbhbq7q6Le3LuwXEzlkTnDtO3qPXkNx/5zTfx1mFxvV7tS3tG/Rs7LmmHyq/NBZkWy/lax1wfi2S/qD9jsbhGxZlwkcdl3VB/0n9T1w9yjk9UfcU7/5nWF+q7mb5LYqGugSSOap+l+8ii3kdfD6nf4LcGUucGem8iLHv27IHpfUxrMtP7urZt01jkda3XmEcYTXl5Cu7tci82VtqIvAiFWfIvWXlZaJzXGAsOLEAEwSMBvx95H+eXOt/zIWP+2Q2XnniDOK6uobyuy9mfg455HaP3I+tOCmBEfIHW/jFrvX37UKpePUS2bbN9ZvR4XtWq2E+qZZkyIrozcZnzsrNRunt3kKvxSQD2AsL0eW/LvXir/VvoPrs7+lTrA1JL27dvjx07dgiC+OZNN+GD66/HBVu2gPLhkl8r8Z9p06aJ9GfkZkn+vmSarBa6NwWCIkLqVR588EFxjw8++KDQKeQjS5yMfGSrEDEHhFsnpV2TPrLEtShgFFnI/vvf/y5EYukaIrJ0/wULFghSXEMl+M6IFu2Jkbw82ooIVkimJsV1zJgxwlE7CJGl/HYtW7bE2rVrcdxxxwnzY7KRtxFZU8ApemvagVAjcAX7Ej6bEWAEGAFGgBEo/ggsP2o5hreMDcpIX0WqbOPtjYv/B/IXMAKMgBMCf2b9iWs6XINdh+5yOp9Oqvh7Rfxr1r9wSG4wQYBU1UGtB2FDhQ3IzSocjEpuqI2aNyqGJHtdZzqfgsGS8EXEjNwQ1XQ2FBCq9aBBqLh+vVBTbSUvEsGuevUwb9QoYaJ89913Y+XKlSLf7aTVq9Fv/XoQtSSh7IERD2Bwm8FYd8Q61P+pPuQ3kHskpbohcY24C13/xx9/RB9NGypk3ksRhOk48SRZiO/Q/xQfiAg0mSwT2SWRkMyJSZQhBZfUaAosRT6zgwcPNn4WEWriUZQzmN6he/fugkCfffbZYvOlW7duqF+/Psh3Vo2crN6MuFVOTo64vkQRWQKBckIRiAS6q2kxKbJUwXQtSfaUK0mGiLYRWVZki58imwpFI1HKkW3wi3dH2nb/kn48FfXIimxBK4tXkVUtLvzUSldFNt66KemK7JK+A3D92PexssJ6HFAWk7QoPOn3kzCxX1sc2+P8GDVEHXOKkyJL76oWXXlLxliq4uNn+VRcFVmbBVW881+iFFm1buX6wkvZLcmKLOFdrVk1/Jj9o4hJ06ljJ2u3OApHCTPhoMWmxsr7vbjgAbTZ1iQ6Btmu01VZyo9KSiOZ044eTfGEC0rk/fdR6nxvRVj/pv05Ocjr2BGk45EQRiomlbaVquGDnVuQFYnglVdfxbbG23B9neujl4//ZjzO+uUsYQFJrpbkGkkkmwq5TRLxlG4zlEJn2L3DcMeQO2IeT8Txvvvui/mN1GYK8ETXUlAmUn2POeYY4YdLPq+ShFIKIPp37969xfWkThMu8+bNEyl21DyyhBWJjLp/LpkXy+vpHiVWkSUzY/KPpQrp27evCPY0ZcoUESaaCtl0n3jiiYWCPUkiS1GKaZeB/rzuuutEo7ARWb0hcvqdYOl3pO8r+SdQCesja/KnM/l1BPH1CDpwqucnypfP9g4c7MmGUHzHU1GPtqiW8X1B0V2dCB9ZfTyw1Ydff1DTe3lFX9V9ZOOtGy9/MZfoofpYJWtS9XkL6uuW6tbw+Ijzcevd+ZudpkJpMP7a4KYY/zQ9+JlfsCeJherXKCPs0vNSiU+8bSVM3fjlzw3iI6ti7ucXmsxgT6agd7b5Ot75L1E+suraxdQmTTEQ5PeqwaP81kCkisnxySvYkxxXTO+jxhYJ2i9s9aC2XT8f2VT1Ede8s+Qre+qe4/DOh49j8+S30Hza2EBpgei7KeAs5USlCL5kVhuJKCbQlnywUdy09D0Uffjoo48uNCSQefDDox7GZXUuw+pDVwulWW4KvvzNy1j+ab6fLJFPIpLkRknqKymv/3zon7jzjjsRKR1Bp/M64d033g1lrh1mnApzTRgfWSLO5L+7bNkyoSSTefSFF+b7QNPage5JeYE3bNggCD+JnqRAEzn3KrY0r37f5mRaTEl0SaImc2Kyxx42bJggn6tWrRIkllLq0EtTpZI/AYWEpkI211RUH1lSZElWJ/NksnenMNtMZCnIN6CSzUSn30kkkXUJhR9kQA7T+eQ1tgW36d6mPLq280wTXzzvzdfGIhCmHoNimKrJPeh7xXt+OhJZ0yKTvtMrF3W8dZNIIivHt+JCZGkx2WBdVXxdd2eMGivbFfm/nbC+EmZ9+YJYRJrSjah1I8mAaT7SiazLRkG87Vu/Pt62EuZ9EklkXSL1JoPIqt+tEz7bfF3ciSx9b5A1kMSKNuKkj6wpirK6LnAN9qRuJOgbel6baiZCnA5ENmhAqZcWPIB6j32PXdMucE4L1An5ajJZcJKvKVlnkklugwYNYruyTz7YmBOV9D0fffQRWrdujdq1a+Paa68VaucxlY/CvQ+OQF6HPFxb+9pCw8XTG59G2Y/KRjc7ZKBbSaxn5s1El3e7AJ8DR044El+t+gqVy1PyoPQsYYgsxU2i9KpNmjQRqrRKZMn8m6IjE8GnFESEDwXLIuV66dKlniAQkfVL8+qHnhORJRMNYuA7d+4UxJUiDo8YMQL16tUT9/79999x++23C1WWGhnlf6JcRjJXkU5k9RdiIpvZRFbNF2eKVuo3sNu6fhgC5Dop65NKUSzabN+fKcfD1GPQby+KBXDQdwxzfhAiKzdxpFJKz1MXeK5Ri22KLBPZMDUZ7hrXxSQtIg+srxnzEEmqmMj6Y58pRNZEomlOZiKLaFRaNXMDrV0SQWS9rFRsRNZvzeEXqV0d31WFOdwIY74qmjcWy5CLwr6x+lWRvAga7joO469th1umfQr67wAKci3r58u0QIuwKKpokh8rZTkh/nHXXXfFXmJTZTU1li6moLNXX321cJGkoEr/PvcSNL+iB5Zn7cPDlzyM1WVXIzdS8G20KXjSbydh8GuDccX/XVEImBiF+psDKHtWWSHw/bXjX9NWlQ1DZNUPJwKvEllTa1myZIkIgEWBtcia11SIyHqlebW1Wycia7tJURxPd9Ni3XxHYiQHLtuCsjgrsvJbTYtZLyIrd0zVtuRilhOGANmIrG6KRO8Uj7lQUfQP12e6biKYzNFcn+FyXph6dLmveg4T2YJ8q1LxYSJbgInez4uDIhtdTB5YKiIVexVp2ndbzt1ocnoTcRotcJnIuo0iehopdT4PalpclIosE9kLxFxOxcW9Kh4iq27gq2quKYWVSnRdlV0/KxR1fE8Wkd2HfaiFWoHyzh71+xEY8tgZGHjHDLeOB2AmZmLbi/kRiefOnYvnnntOROGl4EQx5sV0gk2VVdRYOv2OO+4QmVVuvPFGPPXUU9ENnUfLz8bo9rF+uOoLD5w9EKPajyr0DTGbinlA6Zal8fd2f8eoB0fhUBzq/M2pPDEVRHb27NkiwjNZ4tLGkKkQkfVK82rDg4msDaGQx/WJTzepk4OQ14IyKJHV88QSCfRSalwHcVMeWZN646VchiGyQRePYQiQC5FVTZH0BS5NROpCJmQTSYvL/JSGVJLAMPUYFEC9P8jrXTZMgj4rlecHVWSpj6ULkfXyGQyaZzZVpsWuGz+pqn9XNVa+Dy3Arjz6SvFPJrLutaSOk7pZLhNZO45F4SOrvlVQ02J17RJWkfUaY72IrMmlIYwiaxrf9bkuUePYJmwqlHd2xZCRqNa5jXjk4r0/iT9rzvtC/HbkvgroW/92fFV/p5OKm4UsNEET9H+xv9iA2zr0UXTLeQF79/+JsW2644YP8jclosVLlTWosXQNxfV5/fXX8dhjjwnzV5pHavTqjrNb3YBvK30bo8bKZ5AqW2tnLayvvL5QFOYWaBGrNN8JnPLhKZizYA4qo3JaqrIqkSV3UTWdKQWsov/9ik2RJYtdygVMcZNeeuklz1v5pXk9/PDD/d8hTPod+7CV/DOKgyJr2u1WFVm/BWUYIquTQCay5naYCCLr5euX/Jaf2CeUZCKbKabiNiKrb3IFJbKf9r7F2Oi88FM3trx8/dRgKl4qUZCWbiOyfptPto042tAz+ZUGJduJWjxKXMKY9tXeWRtvbX1LLKiYyLq3sHiIrKrM0RNZkS0cqNIv8JW6oU746YRPHWNM95GYB/GRTTciq7ZUORa5KrIm8cF13nfvIQVnmsZ/+Q77sv5A09Y98WPF35xvXQ3VMOKlEWjRqIVwgxn38ya8MDMH7arXxZzN6wvf56AquwkAUbD8DKsk7c4EOhVEbyYMKPUOpZwh10jy5yTlfP2t1dG75VDr+1EAvTM+rxmdG4ybiu8Bh111GKpVrYZykXIohVLW+6b6BErTQ+SV3Ef1QvGQSCkNS2RJoKDNAuJrlKvWS4013V9N80rm377vwEQ2Oc2mKBTZoETWNMGq/iE2RVZFzkS8i5Mia/JhsWGRLJOd5LRI811dJ7Rkm+UWhSKbSiKbTNNsFyIrv1UuBIMoskRk1cWjl2mebGHpSmS9Np9ciKz8NpOa4kpQXfuaa/8PY9pX4bcKmPvNXJTOK81E1hVoFPhPSvJPl8rx36bI6maeTGSZyHpZ6Mk1F7Uvdf2lrq/0dZfpGtv4nuixSH0nPyJL5y197yXUGH9rTO/b/+d+zP94Plqd1QqlDokle1VQBXNfnCs2gGhN9utZp+HcW69DdiSCbzdtEiQsJoDn1LH4oXFjnPD556DsrZ9mZaFGkybAokUib6wslJ6GsqaQYkjBanfs2IHj3l6A656egxUV1hlz4sprpavGhGvPwRnTxsMzevMvAJ6G2Dik1EY34+a0VNrf3D4AACAASURBVGUpCC9FFk6kIktruh49eojIxXPmzBGBuoIWmeZ15MiRTGSDgpeI84sLkdV3MG3kzWtXM92JrLrY1MPwy/rWibcNCyayiegp+fcoCUTWlBoiEQimC5E1+Xl5KbLqd6dKkY2HyEoi70VkXSw0krF4lKZ9ujkfmXGtWbMGhx12mFjo/f7Mq8K0b82PB9D+xPYC/kxQZE3p4BLRp/R7xKvImpRCPxUyWVGLS5KPrG4Rl46KrGxnekRkPyKrb0oWNyKrWrjI77fN/7pp+iV3D8Inq1bgH//4B4YPHx71bZX3vrdPHww/aMZ6NoA577yDUuedF9OtyZx4wIAByM7OFmlkvvjiC/z43VTfNGb6uECq7C1358DVxYP8fWUU5mSMU2HvGY+Fq8m0WJLYtWvXCr9mChIctKhpXil3sF9hH9mg6Dqez0R2ulBxqOiTsoRQNy/UiaOL76JtAJTPcjGzziQim2iViBVZx47vcZqOn94H4rl7OhFZP7M/+kZ1IU1ESv9NEqygZrsupsWJJrImMu733iYi69pPbe3DSwUnU666deti7/3jxXjspQ6a6iFM+p0YZWTaONtrhzru1d5d5otQD8xwRZYwkURKEigdS5s7jg1XnYjo64KiNC2W7y43qRIVtdjFR1Z+ty31oqurmSS1YRRZte8SJmH7k02RTQSRnT7/Q9zwyEhkV8tGznc5OKL3W1GrodNfelykCqX8pqS/Ugi8e4YOxX333x/TTCnVDuU2rVq1Kv773/9i2afL8M8zB2JNvR3Ii3gHzpM3oSjMJ66vjC/rb8EZOCNUFGZbv0nV8aBElkjmunXrxOs1btwYY8aMEbl0jzzySJGXl9Lv0Pyek5Mj8JWFjpcuXVr889xzzxV5gfv37y/+bUvz6ocFE9kktRQmst5EVo9QbJpATIOdqarSjcgmajKIt1m6qj9BzwtLNGzf41qPtvv4HS+KBbB8H53Iuih4rt/KRLYg8rCXaZ5JSZX4upgWmxRZvxgIprrzIrIubcFmmp5ORDbZJvtF0Y8zWZE1BTYsSUTWbwM73qjFJqKqjkXpRmR19zTXOUg9LxVEdt+ff+C4Gy/Ege25qPl4TUydfx5q9rpQmGN/99d2wqT1iMMOw6hy5dBv+3YR3Zh8NClnrCxXXXWVSI1DvrEUhGjRZ4swqGv/QP67R/5UFnc93TZwFOZ0U2WDElnCkoirXvr27St8auvUqWNsOqTOtm3bVhyj3L1XXnll1AfXluaViWyY3hjnNSYiGyToiusOnNx5M6mZNhXStDtvM6eN17SYYNUjCPoRWdsCzpUA2bBQF8BemPqZF3otisPuasbZ/KIRq23mz0xkCwL5xIu5K4lWTTqDKo9+BImOqf1T71eqb6ttx17tV64+siZV1M9E0kuRdTUX1TeNdDXYy8dfYqgHTaHfvfzSEk1k1Xp0JbJ+punFgcjaxnLX/pcoIhvkfbyIrHxnWTd7RkzAtp7tUWXqbGTtP+CrgqeLabFOZE153zNZkS1JRFYNeuflpyvHwbBrl1QQ2Q+qLEXvFUOB6wD8BRh+/bnod8YgMX7fsX21IK3du3fHgw8+iGuvvRYff/wx+vTpI9ZFsnTp0gUzZ85Ep06d8MgjjwgFscKCWSjTo7mItkzuGVTIRUO6asjf9k6cJlw19k1dhDsGvues4soozGpuXNdxL5nnBSWyyXyXMPdmRTYMag7XeBFZ16Ar8RBZdSIy7fjR63uZmaUjkfVbwBU3IpsoU0JbEwxKUF0JLz3Xdq7t3UzHXesxzL3lNbYFcDLrxlWRDaPoZ5oia4qyaar3MEpqmPRhJkLs5V/qalosN/RcNzX09qM/p7gQ2UT4idv6sesYYcNUvY8XkdV9TjOFyHqRHFdLKb0O0tm0uKQRWd29Q8+kEZbIyvlTNVP3E1rUNmKb/9X2Q+lxura5BV8c9jXyyAF2MfCXbmWw6m9vYt7459Hr/anIysoS5LRDhw5CdR09erRQCac07Rx97PXrPsHy5ctBKuKgQYPEuka+uy1Am5xH1k97HReOezGQiktRmDdiI8qImMrpUUoEkaWIUZRriXYmypYti5YtW4okwieccEK0Fkgu/vDDD2NqhXZCJkyYIH7buHGjaEjUwL777ruYXEVky37sscfiwIED+Oabb4TkbCvpDnxRE1l9gjUpqcVFkc00IuuiwNjav+04E9nCCNkWwDbM4vH/C0Jkg5p3MZF1V1J1xZpaie4f6KLsMpEtWPSp5MZPuQtCHP3GN1s/to2Npo0t2+YcE9kboj6IJqXOtgnIRHZsFL+iNC3Wny2tYkzjYFBF1q+Odb9j2QcliQ5CZGPS4ywD0CzfEfasTqdh7bx12Pbbr2hTvQ6uHjlcWP/Nnz8f119/PfLy8pBz/hVofHUvodxeNP9N4Uc7ePBgXHHFFaGILN1na6VfYlRc4kmUN5fKd60bxii7Xbt2BUVhpgjG6VTSnU/ZsHJSZDt37gyyX6ZQyPv378ddd92FL7/8UoRqpqiIVIjIHn/88bjvvvuizyxXrlw0b5AkskRYqVGRo7Us5HA9fvx4QXCZyF4QNW+TO2N+UepMO16mvGpMZF8UgxoVm3l0ok2LdRO2RBNZ0yLCRsr0xZw6odExXfFJ1CLUa0CyTWS2gczluG0BbMMsHvM6E5HVXQ1o4aCrjC6LCSay4YmsyT+wqIgsEWpZ9Hq39b/iqMjqi1mXPkzn2PpxmPswkc0nWlTU9YOu1nkpsraxk4lsehNZFz9pW78KQmTlGkiOebmlsoVJ/nnnnYdDDjmk0KPkvX8e/pRIj/NlhXU4kJWbfx7FChpbcEmFw8pj2n3/xNaj/hINLkiKLEUlfvDMjug7+DZ885830ObNZ4R4RoGKOnbsGJrI0pNVC0c/ZTcRrkS2eghzvEQQWR2Y7du3o0qVKkKBlc7TRGQpFxGFtDYVSWSHDh2KqVOn4uuvv46eRspuz549cf/99zOR7cVEVhJ4WszZFnAmAqQTRxo8vBY/chAK6yOrL8ZMRMRVjQszAKkLO3UxZltYeBFZnWSrWCbCLJCJbEHaE92MX2Ljp8iaTI8TSWTlO6gLi6LwkXUJGBSvabGXb35RElmv77aNg0VNZNV+rW68qsQ8UeNgECLrZ0Vhw1T9ppKqyEoM1PQwXoqsGvxMnxeZyGYWkfXbPNfVV5MPtkpkabz4dlqOE5Gd/eaQwulxdh8ks+WAfr82xZDzh6LcoYfGbMh88sknGDduHC47riEeefhhfDLxRVwy4yURQXfixIlo2rQpE9ljj8WmTZtQo0Z6qcUu62InRVa/EYVdPu6447BixQqccsop4jAR2ZUrVwr5vlq1aujWrRvuuecekCpLRRLZxYsXi12XN954A61atRKy/8UXX4x33nkHzZs3ZyLLRFa0F7nza1tseBFZnXQli8i6BEwIs4AzkXGvDm0irYkksrqZuk29CGOCW1IVWZMvvI3IqsqJbBN+0TFt1him1A/qwoKJbH4EdhqTvEzzXKws1D5J9ab7qvmRBds4WNRE1s9qyGssd8HMNOYFJbL65kCYzbmSTGRVIuKiyKpjkaw/r9Q2prlFJzmqj7rfxrM096dzTKb/YSyxMi1qsd/4ZTP/1dckpk1vL9JqIreqculCZBuf3hg9ypyDr+vuLFBjlQEiOzcLx2+ohFlfvoAIIjFElnLF9u7dGycfUQWznn0Br4x5Erd+9A7q168vctHqbc7VR9YUQJEVWRfqmdhzAhPZ3NxcEQ1s165dgoTKQrsalLvpmGOOERL+kCFDBDEl31qVyJJz9aRJk7B79248++yz+Nvf/oaKFSsKG3XKR+RlWrxv3z7Q/7J8//33OPnkk8X5lPA93crLL78sFOrPPvtMvBr9/ZeRE1GjR1dsnvaO+I3+/sHP28UxKupxOkaFztWvkb/RcXm9vFb9jZ5turfp2fJc9T7qs9d1ae75Der7qNfIb5Dv6IWFfm/53U0njYHEUeIj65mOUSECNGvWLOHUL01S1GvomWQWr98nKKYmLCRm8hn0Pkv73ibqS9aDfF9ZD6ZrTG3X9A1ebVxta/StVEy/+T1HrRv1e9T7qG1Jrwf13hIDwkzWE91HFvmO6jWmekx0n/ZqA+o7yj6r4ijfo/6MxdG+KK+hbzUVeVwe0+tTHQ/0fq72ff0+evuS72vq53591jbufPf6TOy4pJ3oV5/3GxL9blO/UbGQx/36vtoH6Nv9vkH/flM788NPvo8JC69xR/8GW9+X30Bjp1q82oDe1+T3m9qXqf2oz9Gxl+OOvCflkaWYE3sfeqbQfBOkHkz1qb6v33gqxwFTH1DHGr1u9TFG9jVZb3RcnTNNbUUdi+T95PXq/Oj1Hjr++jV6290z6t+i31R+ba6IWqzP8SrmpjlBYmqaM23P9ltfmNocfZtp3neZr/Wx3Gue8Op/ejv1w8J1DeSFj9o/g877hAX1oT179iBIe/db25nan23t57oelFh5je/6s01rMr1uTGsKddzWj5vWol7rU4mpOt+YTIupff3a6ldcX+d667LgxQUPoM22JtG1MX3jmWeeKcS37EgWVk15DQPvuhtvb1gFcpvs1atXdA7S+5/aR1zX03Se131Max/rB6XgBOJTFMOoxCiy5N86Y8YMQWL9JOg5c+aIhLek3tarVy+qyBKRpd0RChi1du1a0bgWLlwofG/9iCzlJho+fHihKn3mmWdQuXLlFFQ1P4IRYAQYAUaAEWAEGAFGgBFgBFKFQB7yMKj1IGyosAG50jfW8PCs3CzU3V0Xo+aNEqqsLGQp2q9fP+zcuRM33XSTMDMm/1iKzyNT6qTqW9LxOTt27BD4lAgi279/f0yfPh3z5s3zTHgrK+nXX39F+fLlo3mapGkxEVnafaPAUXScziNzY9rFYEW2QLF13YHLZEXWdVeTdkxJOXrttdcKqTupUmRpB04Wk3rhp8iqqp6uDuo7gqYdPVdF1u85XiqRuvNqUv1sKogJi2Qqsn7Kr0mRpf6jFlUdo9/VHWx1R169xk+F1Her1fr0sn4wKbKqsuTXvtSd/UQosqqyZFJGbMqun7LkpRLZVDaJvapOmyxBbBYlyVBk1bqT7cfUvvR+ZdvF97Mo8Rt3ioMiq46dJnVf/82rzYUZi9Rx2c+axaQ4mtTVkqLImixXgliHUJtVxwZWZP3Xfq7rwWQosqa6MY1f8rdkKLJ3fXgXRrcf7cwBSZXNW18zakVIF97z8Uz897t1iJSPIO+XPJx66ql46aWXolYJfmOwX9ume6trVdtY7vwRKTyxRCiytJtBuxjk10qJhklFtRVKQEw+sJ9//jkaNmwYo8hSo6AoxTfccIP487rrrrMSWf156R5ly+QPFcZXzdU/xMsHwS9Sb7qn39Fz3eqpM6RfgzT9oTZi8rmRbScZUYu9/Hnomabo0aa8kaZouEH8al19ZP2eI6MW6357Jky9cnGqfVQPmGOKhKmenygfWT/fYJNvnZcvjJ5PTvV7UQODqf3TL+qnqT69cjabfGTVujM9J1k+slWmzhYmkmp9mvyCqC5NvrZqvettydTm9PvIwDImv+t0C/Zkqk+v9mXCwiuHYdhgdYQvjY1169bF3vvHe+YOd6kHU5tTfXrj8ZE1+Qabxir5m4qpLeewa7+xBcpjH1lzsCIZhdWEj2m+tq1T1PnRtX3Z5lnZ19hH1t/HP0jd+I3l8QR7ovnmzMlPiqWBHPNJje017j1srLQReZE8G/VAJC+ChruOw205d6PJ6U2i89IzOW9i2L/z04EKYvuPe9CzR88Yf+qgeWTZR9ZaHSk5wclHlgjn5MmThRqr5o6tUKGCyCu7fv16cZyCOFWqVEn4yA4YMECYHsvcsroiS6bE5GdL/rGlSpViIuuxEGQiu82YNkcNWmAjsjq5DTOhqfVgCpigT7ouRFZNt2EKSKIGrHKJCOm1GJMjiWnBaAtAE4TIuqSJ8goUxUS2IKCQKZiTa/vyWzwGIaAy+EY6EVm9j5QEIitTNMkxRyf69G+/TaN0IbL0nuo3eBEWdePCq75TSWTVVZhfYCI5Vu8ZMUFEX1X7jS1wjAkLvw0geif1GpfNaq/NCnkfLxJjIoHq/MdEtnD/k2sFr3aajnlk/SILe61DvDa9E0lkaQzYl/UHGnXogz1l9ziToqN+PwL/fG00WjRqESWyz/04HUOvHp9/j87AwNsH4sqjr2QiS7F4Nm8GpUbNaNPiSKTA1lxtSc899xyuvPJK8fF9+vQRuWXJVJgAueiii0CpdmgipaITWb1F2kyL9fPTHXhWZPMX5jqh85sYbYpGWEU2nYmsSenyW/T5RYTUc8H6fbdcMBYFkVX7smtCdHmNKey/er9MUmTVxSwT2RuihE0nO1T/JmXctPlkU4lc7+MXFVV9n3gVWfm+Xovi4kJkdeua4kJkTYt4v99KEpFV82DbyBlHLS5e6XdcVW7bOCjv4xq1WFdk5Rpy2oHVqN6oOvZOnIZqnduIKX/LzA/F3+lPKvLv9GelfRWxenueEEHo2TV6dcd5Z92ML05cC/wIRD4Gah9fB29tfQvLP13OUYtLApF13gZJ4YlMZGNJos0sxGbWbNqZtS0ETYsom6klE9lPCw2aJtXdtovvRepV5TZdiayJjMu8pVLJoHZiy1eoqgEm5URPPl7cTIuZyE6PtgHVRJQWxVQkuWciG5t7XG036aLIuhJZtR+nUpG1kTKTAmr6raQR2bBuDvoGt2lzgE2LC1vp2Cz0gqrBqlJvW0OaSGsyiCzFLtDHdxMhtmGhXrP+1uro3XIo8CmAnwCcmz/SPL3xaZT9qCwTWSayKWSvyqOYyDKRdfWRLW6KrN+iz88X0m+ioa6jqjsm4ic3GcLcR1102FQi0zeoRLZWj/OjOTvle5pM2Py+QV2Y6uqzjoXfIspGJl02buR76s+x+cjanm3aNc8k02L6PlnU9mVSd1yVVFZkC1w1XPu56hPu1yZV03WTH7nNH91rQ09vA8kwLfbbGKTnM5EtrCjaiI+tr9lUPyayJZfIepk6e82ZfmuOn4c/heuenoMvK6yLyT9LEY5P+v0kDH5tsPCl9cv/6rKGNI2N+pinb64XDXsq/NR051M2nJx8ZG03KYrj6Q48mxazaXE8E3UyFdkg5o46ufUiga5+x3JBqN6HFrBeRNbkG+znqybfV19E6WTSZLJp81Uzmfe6EFmv92UiS9vjhQO02cxpmcgWkArbplFxU2R1P3sTafXzPdQ3vlyDPTGRzW9TVEz+uWFIaZhrONhTwbrJtjln6vuZosgmksjOfnMIbr37HU+aMnB2ga8sB3va5JtWtSi4nsszmci6oBTiHCayTGSZyJrbQBBF1iXAip95E03sfv5bNpXIpooykTUHY/NbFLsqgbZgKbaNAJtrRDyE2GZSZ1pQ2kzzTIsoG6lnImv2PTQp+UHNYNVNN1ZkWZF1VYiDkkl9U1eNWq8HcrOZ0wZ9drqaFieKyDY+vTF6lDkHX9fdGaPGyvEhKy8LtXbWivrKMpFlIhuC7oW/hBVZNi1m0+J83zhTFGVXpcu2uHa9T7IVWdegK16KrJdpEBNZc9qcdIhazEQ21h3ALzqtl/lvSVNk9Uiq8QRJYyJbYDERRl0Ncw0rsqzIko9soojsb2f/hmtrX2slGtJXloksE1lrY0nkCUxkmcgykWUiS2MKK7L5AcT0nX1dcSxu6XeYyDKRDWpazEQ2f06QSr3JTNhE0L38Xf02BtlHtgBnm0+4zXRdPc6KbGKI7Oyft+LhSx7G6jKrkJvtnX9W9ZU94e1PfPNt+20mso9sIhlesHuxaXEwvJzPZtNiNi1m02I2LTYp2rYI4SYTyHiUJVvEctMiihVZszLiZ/1gMnUO4o/OpsUFwW10IqZu0tg2OPxUPd0H1CV4nr5Zxul3zvRUzLxiIHD6HU6/4zevqfNNohTZR8vPxuj2o53X7OQre+nEX5nI1qjhjFm6nMhENkk1wUSWiSwTWSayTGTzfWhVXyz2kS0c5MorYib7yBb2wWYia46i7LdhZep/KkFnRbYgyJWOBZnn79mzJ5ruK9F+quwjewESTWTzkIezW92AjZU2Ii/ircbK5X8kL4LaO2tj8g2dULPXhdGAZ16bWLa+5mWizFGLk0O4mMgmB1cwkWUiy0SWiSwTWSayJgVPbxdMZAty4dpM4JnIMpH18gn362uucRyYyMZGrnYdv3QzdNX6wWujRBK+RBPZfVl/oFGHPthTdo/zCr/CbxXw9tU9Ua/HxUxknVFLjxMTTmTHjh2LUaNGYcuWLTjttNPw5JNPonnz/ATHtWvXxrfffospU6bgsssui0GgQYMGWLVqFZ577jlceeWVVnTYR5Z9ZNlHln1k9R1TfTLlqMWnR/MH2wiCujhk02I2LTaZnBdFHlnd/JeJLBNZJrKJ8c/N5KjF0w6sRvVG1bF34jRU69xGcIotMz8Uf6c/v2vdECeeeCLWrFkj/vzhsx9wxtSv2LS4pJsWT506FVdccQUmTJiAFi1a4LHHHsMrr7yCr776ClWqVBFENjc3FyeddBLee++9KFn95JNP0LVrV+zbtw9PPfUUE9nJ5kWU9BsyDeJBAi+Y/I9sfnt+gWNMgQ68Jho/omHzMfMKmCBNf/zULy/fHVdMTak8wvhiuUZl5Dyy5rQ5tjQYTGS902QwkY0l9Zx+Jz9ImJfZKRPZgiBqtnFHku09IyZgW8/2qDJ1NrL2H3BaFNvyV8czr3GwJ3PkZdd5n/Bj0+L8QIKuGQ5Ma9FUK7JearDrOi7I+ktfT3tZ19DvbFps1ShDnZBQRZbIa7NmzQQZpUKk9dhjj8VNN92EO+64QxDZyy+/HI8++ijWrl0rjlH5+9//jkMPPRQvvPCCIL+syDKRDZIPjYlsfvCNML6HrpOTaSPASxnxWyR4bSjklsqOLgBr9TjfmFZIn0xdzcg4j2wBuTVtYnGwp3x8qJjyAtsWP/rmiXofDvZUgKkt1ZXJ95CjFhf2p/YaB21+e36EmH1k2UfWJoa4rhWYyH4a9afWxzwmsqF4qvWihBHZP/74A+XKlcOrr76KCy+8MPrgvn37YteuXZg+fbogsrfeeivmzp0rCO/QoUOxd+9eHH300fjwww/Rtm1bJrK9CnyF9IVVkF1Er7yZXqoMK7KF/TlNCrFX3lbXqLKsyJpTxTCRLYjYylGL84mlzYTUq3+aSKnJooQVWVZkOWpxfhtgIstElomsNwENsp5mRdbKOxN+QsKI7A8//IDq1atjwYIFOPPMM6MvOnjwYEFSFy1aFCWyderUwe233y5UWQqKRCosVX7FihU9iSyZHdP/smzatAmnnHKKeB4R4XQrRNzJ73flypXi1ejvvz71Eo4+/xz8L2eO+I3+vvDXH8UxKupxOkaFztWvkb/RcXm9vFb9jZ5turfp2fJc9T7qsze2a+T5Der7qNfIb5Dv6IWFfm/1u73wkdfQPcuXL49ffvklirP63fLvNixsmJqwUO9de+5n0XoyfbesB79rvNqF7RtULPQ2Z/puFVP13rKd+v2mtlOvupHty4SpVz3kZmfhx/Na4sh3F6B6l7ai3evfRfc1YWF6X7Uvme4jj3thIetTbbumOnZt76Y26dXXTO3HtX2ZvjvMuPP9jA+i9ZF1IDembQcZv0x9P9725TdeeI1FpvErnvv4tTmv8cvW1/Q2l4i+RmMjWT79Nm5KofnGtR68+rHeJtV2YaoHW18zzXWmMcZlTpDjYDz9xjaPmMain8dPKdRvvL7bb07w6zde46BfP1fnXttYFGa+Vq8xrTlMfc10jev8aJtbbHOC3xylr6Xk+iKe9u46H9nWUrb1oDwepI/o61OvNaRt/PK7j9f6VGKqzjfku6qul73WuTYsTGtj13Wcrc/a+pppLCf8Lrgg3/In3cr//vc/tGzZUsQwqlmzZrq9nvV9ioTI9u/fHzVq1AD51A4bNgyXXnop6Dc/Invvvfdi+PDh1g/iExgBRoARYAQYAUaAEWAEGAFGgBFgBNwQWLx4sbCWLW4lYUQ2iGkxmRcPGjQIS5YsEUotqblHHHFEIEV2//79WL16tdhtzsrKKm648/smCIGff/4ZJ598soh4ffjhhyfornybVCPA9ZhqxP2fx/WRXvUR5m24DsOgFt81jHl8+KXb1VyfqakRxjk1OHs9heIZbd26FY0bN0apUqWK9mVCPD1hRJaeTcGeKNUOpdyhQuCQTE1qqwz2RCSW/icSSgSkZ8+eePnll8X5fopsiG/jS0oAApSovEKFCti9e7eILsileCLA9Zhe9cb1kV71EeZtuA7DoBbfNYx5fPil29Vcn6mpEcY5NThn6lMSSmTJVJiCOz399NOC0JLv67Rp00SepqpVq0Z9ZInIUtm5c6cIEFW2bFkmspnawpL8XTwAJhngFN2e6zFFQDs+huvDEag0Po3rMPWVw5inHvNkPpHrM5noFtybcU4Nzpn6lIQSWQKJUu+MGjUKW7ZsQaNGjfDEE08IpZaKjFosiawOKiuymdrMkvddPAAmD9tU3pnrMZVo25/F9WHHKN3P4DpMfQ0x5qnHPJlP5PpMJrpMZFODbuY/JeFENvMh4y9MJwQokvXIkSNx5513okyZMun0avwuARDgegwAVgpO5fpIAchJfgTXYZIBNtyeMU895sl8ItdnMtEtuDfjnBqcM/UpTGQztWb5uxgBRoARYAQYAUaAEWAEGAFGgBHIUASYyGZoxfJnMQKMACPACDACjAAjwAgwAowAI5CpCDCRzdSa5e9iBBgBRoARYAQYAUaAEWAEGAFGIEMRYCKboRXLn8UIMAKMACPACDACjAAjwAgwAoxApiLARDZTa5a/ixFgBBgBRoARYAQYAUaAEWAEGIEMRYCJbIZWLH8WI8AIMAKMACPACDACjAAjwAgwApmKABPZTK1Z/i5GgBFgBBgBRoARdLXwmgAAAVJJREFUYAQYAUaAEWAEMhQBJrIZWrH8WYwAI8AIMAKMACPACDACjAAjwAhkKgJMZDO1Zvm7GAFGgBFgBBgBRoARYAQYAUaAEchQBJjIZmjF8mcxAowAI8AIMAKMACPACDACjAAjkKkIMJHN1Jrl72IEGAFGgBFgBBgBRoARYAQYAUYgQxFgIpuhFcufxQgwAowAI8AIMAKMACPACDACjECmIsBENlNrlr+LEWAEGAFGgBFgBBgBRoARYAQYgQxFgIlshlYsfxYjwAgwAowAI8AIMAKMACPACDACmYoAE9lMrVn+LkaAEWAEGAFGgBFgBBgBRoARYAQyFAEmshlasfxZjAAjwAgwAowAI8AIMAKMACPACGQqAkxkM7Vm+bsYAUaAEWAEGAFGgBFgBBgBRoARyFAEmMhmaMXyZzECjAAjwAgwAowAI8AIMAKMACOQqQj8PwsbQkawSZpIAAAAAElFTkSuQmCC\" width=\"946\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[[<Figure size 640x480 with 4 Axes>]]"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import backtrader as bt\n",
    "import math\n",
    "class TestStrategy(bt.Strategy):\n",
    "    def next(self):\n",
    "        today=self.datas[0].datetime.date()\n",
    "        weekday=today.weekday()+1\n",
    "        close=self.datas[0].close[0]\n",
    "        if weekday==1:\n",
    "            self.order=self.buy(size= int(self.broker.get_cash()/close/100)*100 )\n",
    "            print(\"buy\"+str(int(self.broker.get_cash()/close/100)*100  ))\n",
    "        elif weekday==4:\n",
    "            self.order=self.sell(size=self.getposition().size)\n",
    "            print(\"sell\"+str(self.getposition().size) )\n",
    "            \n",
    "        print(cerebro.broker.get_cash())\n",
    "\n",
    "        \n",
    "\n",
    "cerebro = bt.Cerebro()\n",
    "cerebro.addstrategy(TestStrategy)\n",
    "#\n",
    "data = bt.feeds.PandasData(dataname=wanmei)\n",
    "cerebro.adddata(data)\n",
    "\n",
    "cerebro.broker.setcash(100000.0)\n",
    "cerebro.run()\n",
    "cerebro.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6adc8309",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "69769f35",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2021-01-04    0.000000\n",
      "2021-01-05    0.033990\n",
      "2021-01-06   -0.020426\n",
      "2021-01-07   -0.038119\n",
      "2021-01-08   -0.010500\n",
      "                ...   \n",
      "2022-03-24   -0.037912\n",
      "2022-03-25    0.003031\n",
      "2022-03-28    0.000000\n",
      "2022-03-29   -0.016834\n",
      "2022-03-30    0.018679\n",
      "Length: 300, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "import backtrader as bt\n",
    "import pandas as pd\n",
    "import math\n",
    "class TestStrategy(bt.Strategy):\n",
    "    def next(self):\n",
    "        today=self.datas[0].datetime.date()\n",
    "        weekday=today.weekday()+1\n",
    "        close=self.datas[0].close[0]\n",
    "        if weekday==1:\n",
    "            self.order=self.buy(size= int(self.broker.get_cash()/close/100)*100 )\n",
    "            #print(\"buy\"+str(int(self.broker.get_cash()/close/100)*100  ))\n",
    "        elif weekday==4:\n",
    "            self.order=self.sell(size=self.getposition().size)\n",
    "            #print(\"sell\"+str(self.getposition().size) )\n",
    "            \n",
    "        #print(cerebro.broker.get_cash())\n",
    "cerebro = bt.Cerebro()\n",
    "cerebro.addstrategy(TestStrategy)\n",
    "\n",
    "wanmei_btdata = bt.feeds.PandasData(dataname=wanmei)\n",
    "cerebro.adddata(wanmei_btdata)\n",
    "\n",
    "cerebro.broker.setcash(100000.0)\n",
    "cerebro.addanalyzer(bt.analyzers.TimeReturn, _name = \"TimeReturn\")\n",
    "cerebro.addanalyzer(bt.analyzers.TimeReturn, _name = \"TimeReturnBenchMark\", data = wanmei_btdata)\n",
    "results = cerebro.run()\n",
    "strat = results[0] \n",
    "portvalue = cerebro.broker.getvalue()\n",
    "returns=pd.Series(strat.analyzers.TimeReturn.get_analysis())\n",
    "benchReturns=pd.Series(strat.analyzers.TimeReturnBenchMark.get_analysis())\n",
    "\n",
    "print(returns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "de0b79d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_pct=[]\n",
    "bench_pct=[]\n",
    "\n",
    "my_pct=returns+1\n",
    "my_pct=my_pct.cumprod()\n",
    "bench_pct=benchReturns+1\n",
    "bench_pct=bench_pct.cumprod()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "54d875f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"740\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.font_manager import FontProperties\n",
    "font_set = FontProperties(fname=r\"/usr/share/fonts/truetype/wqy/wqy-zenhei.ttc\", size=12) \n",
    "\n",
    "plt.figure(dpi=100,figsize=(8,3))\n",
    "plt.title(u\"我的策略 vs 完美世界\",fontproperties=font_set)\n",
    "plt.xlabel(u\"时间\",fontproperties=font_set)\n",
    "plt.ylabel(u\"价格\",fontproperties=font_set)\n",
    "plt.plot(my_pct)\n",
    "plt.plot(bench_pct)\n",
    "plt.legend([u'my_pct','wanmei_pct'])\n",
    "\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6db94a2b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/ubuntu/myquant/matplotlibrc'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib\n",
    "matplotlib.matplotlib_fname() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c200281c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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