Human Activity Recognition with SmartPhones.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2b51eccd",
   "metadata": {},
   "source": [
    "## Importing Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "25906839",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler,MinMaxScaler\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34d028ea",
   "metadata": {},
   "source": [
    "## Loading the data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "d6385278",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_data=pd.read_csv('train.csv')\n",
    "test_data=pd.read_csv('test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c10fd03e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "429e1ccf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Count')"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=train_data.iloc[:,-1],data=train_data)\n",
    "plt.xticks(weight='bold',fontsize=8,rotation=45)\n",
    "plt.title('Distribution Of Data',weight='bold',fontsize=16)\n",
    "plt.xlabel(\"Activity\",weight='bold',fontsize=16)\n",
    "plt.grid(alpha=0.5)\n",
    "plt.ylabel(\"Count\",weight='bold',fontsize=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "9ce5a307",
   "metadata": {},
   "outputs": [],
   "source": [
    "features=train_data.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21b2de0b",
   "metadata": {},
   "source": [
    "### How data looks like"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "236f530b",
   "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>tBodyAcc-mean()-X</th>\n",
       "      <th>tBodyAcc-mean()-Y</th>\n",
       "      <th>tBodyAcc-mean()-Z</th>\n",
       "      <th>tBodyAcc-std()-X</th>\n",
       "      <th>tBodyAcc-std()-Y</th>\n",
       "      <th>tBodyAcc-std()-Z</th>\n",
       "      <th>tBodyAcc-mad()-X</th>\n",
       "      <th>tBodyAcc-mad()-Y</th>\n",
       "      <th>tBodyAcc-mad()-Z</th>\n",
       "      <th>tBodyAcc-max()-X</th>\n",
       "      <th>...</th>\n",
       "      <th>fBodyBodyGyroJerkMag-kurtosis()</th>\n",
       "      <th>angle(tBodyAccMean,gravity)</th>\n",
       "      <th>angle(tBodyAccJerkMean),gravityMean)</th>\n",
       "      <th>angle(tBodyGyroMean,gravityMean)</th>\n",
       "      <th>angle(tBodyGyroJerkMean,gravityMean)</th>\n",
       "      <th>angle(X,gravityMean)</th>\n",
       "      <th>angle(Y,gravityMean)</th>\n",
       "      <th>angle(Z,gravityMean)</th>\n",
       "      <th>subject</th>\n",
       "      <th>Activity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.288585</td>\n",
       "      <td>-0.020294</td>\n",
       "      <td>-0.132905</td>\n",
       "      <td>-0.995279</td>\n",
       "      <td>-0.983111</td>\n",
       "      <td>-0.913526</td>\n",
       "      <td>-0.995112</td>\n",
       "      <td>-0.983185</td>\n",
       "      <td>-0.923527</td>\n",
       "      <td>-0.934724</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.710304</td>\n",
       "      <td>-0.112754</td>\n",
       "      <td>0.030400</td>\n",
       "      <td>-0.464761</td>\n",
       "      <td>-0.018446</td>\n",
       "      <td>-0.841247</td>\n",
       "      <td>0.179941</td>\n",
       "      <td>-0.058627</td>\n",
       "      <td>1</td>\n",
       "      <td>STANDING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.278419</td>\n",
       "      <td>-0.016411</td>\n",
       "      <td>-0.123520</td>\n",
       "      <td>-0.998245</td>\n",
       "      <td>-0.975300</td>\n",
       "      <td>-0.960322</td>\n",
       "      <td>-0.998807</td>\n",
       "      <td>-0.974914</td>\n",
       "      <td>-0.957686</td>\n",
       "      <td>-0.943068</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.861499</td>\n",
       "      <td>0.053477</td>\n",
       "      <td>-0.007435</td>\n",
       "      <td>-0.732626</td>\n",
       "      <td>0.703511</td>\n",
       "      <td>-0.844788</td>\n",
       "      <td>0.180289</td>\n",
       "      <td>-0.054317</td>\n",
       "      <td>1</td>\n",
       "      <td>STANDING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.279653</td>\n",
       "      <td>-0.019467</td>\n",
       "      <td>-0.113462</td>\n",
       "      <td>-0.995380</td>\n",
       "      <td>-0.967187</td>\n",
       "      <td>-0.978944</td>\n",
       "      <td>-0.996520</td>\n",
       "      <td>-0.963668</td>\n",
       "      <td>-0.977469</td>\n",
       "      <td>-0.938692</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.760104</td>\n",
       "      <td>-0.118559</td>\n",
       "      <td>0.177899</td>\n",
       "      <td>0.100699</td>\n",
       "      <td>0.808529</td>\n",
       "      <td>-0.848933</td>\n",
       "      <td>0.180637</td>\n",
       "      <td>-0.049118</td>\n",
       "      <td>1</td>\n",
       "      <td>STANDING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.279174</td>\n",
       "      <td>-0.026201</td>\n",
       "      <td>-0.123283</td>\n",
       "      <td>-0.996091</td>\n",
       "      <td>-0.983403</td>\n",
       "      <td>-0.990675</td>\n",
       "      <td>-0.997099</td>\n",
       "      <td>-0.982750</td>\n",
       "      <td>-0.989302</td>\n",
       "      <td>-0.938692</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.482845</td>\n",
       "      <td>-0.036788</td>\n",
       "      <td>-0.012892</td>\n",
       "      <td>0.640011</td>\n",
       "      <td>-0.485366</td>\n",
       "      <td>-0.848649</td>\n",
       "      <td>0.181935</td>\n",
       "      <td>-0.047663</td>\n",
       "      <td>1</td>\n",
       "      <td>STANDING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.276629</td>\n",
       "      <td>-0.016570</td>\n",
       "      <td>-0.115362</td>\n",
       "      <td>-0.998139</td>\n",
       "      <td>-0.980817</td>\n",
       "      <td>-0.990482</td>\n",
       "      <td>-0.998321</td>\n",
       "      <td>-0.979672</td>\n",
       "      <td>-0.990441</td>\n",
       "      <td>-0.942469</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.699205</td>\n",
       "      <td>0.123320</td>\n",
       "      <td>0.122542</td>\n",
       "      <td>0.693578</td>\n",
       "      <td>-0.615971</td>\n",
       "      <td>-0.847865</td>\n",
       "      <td>0.185151</td>\n",
       "      <td>-0.043892</td>\n",
       "      <td>1</td>\n",
       "      <td>STANDING</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 563 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   tBodyAcc-mean()-X  tBodyAcc-mean()-Y  tBodyAcc-mean()-Z  tBodyAcc-std()-X  \\\n",
       "0           0.288585          -0.020294          -0.132905         -0.995279   \n",
       "1           0.278419          -0.016411          -0.123520         -0.998245   \n",
       "2           0.279653          -0.019467          -0.113462         -0.995380   \n",
       "3           0.279174          -0.026201          -0.123283         -0.996091   \n",
       "4           0.276629          -0.016570          -0.115362         -0.998139   \n",
       "\n",
       "   tBodyAcc-std()-Y  tBodyAcc-std()-Z  tBodyAcc-mad()-X  tBodyAcc-mad()-Y  \\\n",
       "0         -0.983111         -0.913526         -0.995112         -0.983185   \n",
       "1         -0.975300         -0.960322         -0.998807         -0.974914   \n",
       "2         -0.967187         -0.978944         -0.996520         -0.963668   \n",
       "3         -0.983403         -0.990675         -0.997099         -0.982750   \n",
       "4         -0.980817         -0.990482         -0.998321         -0.979672   \n",
       "\n",
       "   tBodyAcc-mad()-Z  tBodyAcc-max()-X  ...  fBodyBodyGyroJerkMag-kurtosis()  \\\n",
       "0         -0.923527         -0.934724  ...                        -0.710304   \n",
       "1         -0.957686         -0.943068  ...                        -0.861499   \n",
       "2         -0.977469         -0.938692  ...                        -0.760104   \n",
       "3         -0.989302         -0.938692  ...                        -0.482845   \n",
       "4         -0.990441         -0.942469  ...                        -0.699205   \n",
       "\n",
       "   angle(tBodyAccMean,gravity)  angle(tBodyAccJerkMean),gravityMean)  \\\n",
       "0                    -0.112754                              0.030400   \n",
       "1                     0.053477                             -0.007435   \n",
       "2                    -0.118559                              0.177899   \n",
       "3                    -0.036788                             -0.012892   \n",
       "4                     0.123320                              0.122542   \n",
       "\n",
       "   angle(tBodyGyroMean,gravityMean)  angle(tBodyGyroJerkMean,gravityMean)  \\\n",
       "0                         -0.464761                             -0.018446   \n",
       "1                         -0.732626                              0.703511   \n",
       "2                          0.100699                              0.808529   \n",
       "3                          0.640011                             -0.485366   \n",
       "4                          0.693578                             -0.615971   \n",
       "\n",
       "   angle(X,gravityMean)  angle(Y,gravityMean)  angle(Z,gravityMean)  subject  \\\n",
       "0             -0.841247              0.179941             -0.058627        1   \n",
       "1             -0.844788              0.180289             -0.054317        1   \n",
       "2             -0.848933              0.180637             -0.049118        1   \n",
       "3             -0.848649              0.181935             -0.047663        1   \n",
       "4             -0.847865              0.185151             -0.043892        1   \n",
       "\n",
       "   Activity  \n",
       "0  STANDING  \n",
       "1  STANDING  \n",
       "2  STANDING  \n",
       "3  STANDING  \n",
       "4  STANDING  \n",
       "\n",
       "[5 rows x 563 columns]"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "47633cd1",
   "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>tBodyAcc-mean()-X</th>\n",
       "      <th>tBodyAcc-mean()-Y</th>\n",
       "      <th>tBodyAcc-mean()-Z</th>\n",
       "      <th>tBodyAcc-std()-X</th>\n",
       "      <th>tBodyAcc-std()-Y</th>\n",
       "      <th>tBodyAcc-std()-Z</th>\n",
       "      <th>tBodyAcc-mad()-X</th>\n",
       "      <th>tBodyAcc-mad()-Y</th>\n",
       "      <th>tBodyAcc-mad()-Z</th>\n",
       "      <th>tBodyAcc-max()-X</th>\n",
       "      <th>...</th>\n",
       "      <th>fBodyBodyGyroJerkMag-kurtosis()</th>\n",
       "      <th>angle(tBodyAccMean,gravity)</th>\n",
       "      <th>angle(tBodyAccJerkMean),gravityMean)</th>\n",
       "      <th>angle(tBodyGyroMean,gravityMean)</th>\n",
       "      <th>angle(tBodyGyroJerkMean,gravityMean)</th>\n",
       "      <th>angle(X,gravityMean)</th>\n",
       "      <th>angle(Y,gravityMean)</th>\n",
       "      <th>angle(Z,gravityMean)</th>\n",
       "      <th>subject</th>\n",
       "      <th>Activity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.257178</td>\n",
       "      <td>-0.023285</td>\n",
       "      <td>-0.014654</td>\n",
       "      <td>-0.938404</td>\n",
       "      <td>-0.920091</td>\n",
       "      <td>-0.667683</td>\n",
       "      <td>-0.952501</td>\n",
       "      <td>-0.925249</td>\n",
       "      <td>-0.674302</td>\n",
       "      <td>-0.894088</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.705974</td>\n",
       "      <td>0.006462</td>\n",
       "      <td>0.162920</td>\n",
       "      <td>-0.825886</td>\n",
       "      <td>0.271151</td>\n",
       "      <td>-0.720009</td>\n",
       "      <td>0.276801</td>\n",
       "      <td>-0.057978</td>\n",
       "      <td>2</td>\n",
       "      <td>STANDING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.286027</td>\n",
       "      <td>-0.013163</td>\n",
       "      <td>-0.119083</td>\n",
       "      <td>-0.975415</td>\n",
       "      <td>-0.967458</td>\n",
       "      <td>-0.944958</td>\n",
       "      <td>-0.986799</td>\n",
       "      <td>-0.968401</td>\n",
       "      <td>-0.945823</td>\n",
       "      <td>-0.894088</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.594944</td>\n",
       "      <td>-0.083495</td>\n",
       "      <td>0.017500</td>\n",
       "      <td>-0.434375</td>\n",
       "      <td>0.920593</td>\n",
       "      <td>-0.698091</td>\n",
       "      <td>0.281343</td>\n",
       "      <td>-0.083898</td>\n",
       "      <td>2</td>\n",
       "      <td>STANDING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.275485</td>\n",
       "      <td>-0.026050</td>\n",
       "      <td>-0.118152</td>\n",
       "      <td>-0.993819</td>\n",
       "      <td>-0.969926</td>\n",
       "      <td>-0.962748</td>\n",
       "      <td>-0.994403</td>\n",
       "      <td>-0.970735</td>\n",
       "      <td>-0.963483</td>\n",
       "      <td>-0.939260</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.640736</td>\n",
       "      <td>-0.034956</td>\n",
       "      <td>0.202302</td>\n",
       "      <td>0.064103</td>\n",
       "      <td>0.145068</td>\n",
       "      <td>-0.702771</td>\n",
       "      <td>0.280083</td>\n",
       "      <td>-0.079346</td>\n",
       "      <td>2</td>\n",
       "      <td>STANDING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.270298</td>\n",
       "      <td>-0.032614</td>\n",
       "      <td>-0.117520</td>\n",
       "      <td>-0.994743</td>\n",
       "      <td>-0.973268</td>\n",
       "      <td>-0.967091</td>\n",
       "      <td>-0.995274</td>\n",
       "      <td>-0.974471</td>\n",
       "      <td>-0.968897</td>\n",
       "      <td>-0.938610</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.736124</td>\n",
       "      <td>-0.017067</td>\n",
       "      <td>0.154438</td>\n",
       "      <td>0.340134</td>\n",
       "      <td>0.296407</td>\n",
       "      <td>-0.698954</td>\n",
       "      <td>0.284114</td>\n",
       "      <td>-0.077108</td>\n",
       "      <td>2</td>\n",
       "      <td>STANDING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.274833</td>\n",
       "      <td>-0.027848</td>\n",
       "      <td>-0.129527</td>\n",
       "      <td>-0.993852</td>\n",
       "      <td>-0.967445</td>\n",
       "      <td>-0.978295</td>\n",
       "      <td>-0.994111</td>\n",
       "      <td>-0.965953</td>\n",
       "      <td>-0.977346</td>\n",
       "      <td>-0.938610</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.846595</td>\n",
       "      <td>-0.002223</td>\n",
       "      <td>-0.040046</td>\n",
       "      <td>0.736715</td>\n",
       "      <td>-0.118545</td>\n",
       "      <td>-0.692245</td>\n",
       "      <td>0.290722</td>\n",
       "      <td>-0.073857</td>\n",
       "      <td>2</td>\n",
       "      <td>STANDING</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 563 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   tBodyAcc-mean()-X  tBodyAcc-mean()-Y  tBodyAcc-mean()-Z  tBodyAcc-std()-X  \\\n",
       "0           0.257178          -0.023285          -0.014654         -0.938404   \n",
       "1           0.286027          -0.013163          -0.119083         -0.975415   \n",
       "2           0.275485          -0.026050          -0.118152         -0.993819   \n",
       "3           0.270298          -0.032614          -0.117520         -0.994743   \n",
       "4           0.274833          -0.027848          -0.129527         -0.993852   \n",
       "\n",
       "   tBodyAcc-std()-Y  tBodyAcc-std()-Z  tBodyAcc-mad()-X  tBodyAcc-mad()-Y  \\\n",
       "0         -0.920091         -0.667683         -0.952501         -0.925249   \n",
       "1         -0.967458         -0.944958         -0.986799         -0.968401   \n",
       "2         -0.969926         -0.962748         -0.994403         -0.970735   \n",
       "3         -0.973268         -0.967091         -0.995274         -0.974471   \n",
       "4         -0.967445         -0.978295         -0.994111         -0.965953   \n",
       "\n",
       "   tBodyAcc-mad()-Z  tBodyAcc-max()-X  ...  fBodyBodyGyroJerkMag-kurtosis()  \\\n",
       "0         -0.674302         -0.894088  ...                        -0.705974   \n",
       "1         -0.945823         -0.894088  ...                        -0.594944   \n",
       "2         -0.963483         -0.939260  ...                        -0.640736   \n",
       "3         -0.968897         -0.938610  ...                        -0.736124   \n",
       "4         -0.977346         -0.938610  ...                        -0.846595   \n",
       "\n",
       "   angle(tBodyAccMean,gravity)  angle(tBodyAccJerkMean),gravityMean)  \\\n",
       "0                     0.006462                              0.162920   \n",
       "1                    -0.083495                              0.017500   \n",
       "2                    -0.034956                              0.202302   \n",
       "3                    -0.017067                              0.154438   \n",
       "4                    -0.002223                             -0.040046   \n",
       "\n",
       "   angle(tBodyGyroMean,gravityMean)  angle(tBodyGyroJerkMean,gravityMean)  \\\n",
       "0                         -0.825886                              0.271151   \n",
       "1                         -0.434375                              0.920593   \n",
       "2                          0.064103                              0.145068   \n",
       "3                          0.340134                              0.296407   \n",
       "4                          0.736715                             -0.118545   \n",
       "\n",
       "   angle(X,gravityMean)  angle(Y,gravityMean)  angle(Z,gravityMean)  subject  \\\n",
       "0             -0.720009              0.276801             -0.057978        2   \n",
       "1             -0.698091              0.281343             -0.083898        2   \n",
       "2             -0.702771              0.280083             -0.079346        2   \n",
       "3             -0.698954              0.284114             -0.077108        2   \n",
       "4             -0.692245              0.290722             -0.073857        2   \n",
       "\n",
       "   Activity  \n",
       "0  STANDING  \n",
       "1  STANDING  \n",
       "2  STANDING  \n",
       "3  STANDING  \n",
       "4  STANDING  \n",
       "\n",
       "[5 rows x 563 columns]"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "068ac288",
   "metadata": {},
   "source": [
    "## using label encoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "00cd4b54",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_data.Activity=train_data.Activity.map({\n",
    "    'STANDING':1,\n",
    "    'SITTING':2,\n",
    "    'LAYING':3,\n",
    "    'WALKING':4,\n",
    "    'WALKING_DOWNSTAIRS':5,\n",
    "    'WALKING_UPSTAIRS':6\n",
    "})\n",
    "test_data.Activity=test_data.Activity.map({\n",
    "    'STANDING':1,\n",
    "    'SITTING':2,\n",
    "    'LAYING':3,\n",
    "    'WALKING':4,\n",
    "    'WALKING_DOWNSTAIRS':5,\n",
    "    'WALKING_UPSTAIRS':6\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "fdce0b86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 3, 4, 5, 6], dtype=int64)"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.Activity.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c1ef249",
   "metadata": {},
   "source": [
    "### How big is data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "8b621c8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7352, 563)"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f844c05",
   "metadata": {},
   "source": [
    "## Without using feature selection, Training Logistic regression on 563 columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "d8659c64",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "lr=LogisticRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "a5061294",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train=train_data.iloc[:,:-1].values\n",
    "y_train=train_data.iloc[:,-1].values\n",
    "x_test=test_data.iloc[:,:-1].values\n",
    "y_test=test_data.iloc[:,-1].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "7574f57c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(7352, 562)\n",
      "(7352,)\n",
      "(2947, 562)\n",
      "(2947,)\n"
     ]
    }
   ],
   "source": [
    "print(x_train.shape)\n",
    "print(y_train.shape)\n",
    "print(x_test.shape)\n",
    "print(y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "86c1645b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\suhaib mukhtar\\AppData\\Roaming\\Python\\Python39\\site-packages\\sklearn\\linear_model\\_logistic.py:469: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-5 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-5 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-5 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-5 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-5 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-5 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-5 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-5 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-5 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-5 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-5 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-5 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-5 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-5 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-5 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-5\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" checked><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LogisticRegression()"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea2bf5ad",
   "metadata": {},
   "source": [
    "## prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "21b858c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred=lr.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "37f51c33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 1, ..., 6, 6, 6], dtype=int64)"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "274c9a8b",
   "metadata": {},
   "source": [
    "## Evaluating the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "0072c3a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import accuracy_score,confusion_matrix, classification_report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "aa2cbb83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9524940617577197"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_test,y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "36a94729",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cm=confusion_matrix(y_test,y_pred)\n",
    "sns.heatmap(cm)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "755014ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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WLMvSU0891Wibqqoq3XffferevbsSEhKUkZGhuXPnqr6+vtF2mzdv1vXXX69gMKj27dtr6NChWr16dZOf+fjjjysrK0uBQEBdu3bV1KlTVVZW1qr7CQAA4kdMw9HWrVu1evVqderUqdn1kUhEY8eO1aJFi3Tw4EGlp6erpKREDz30kKZMmRLdbtu2bRo+fLjy8vIUCATUqVMnbdy4UWPGjNHKlSuj2z3wwAOaPn26du7cqZ49e6q6ulqLFy/WNddco8OHD7f27gIAgDgQ03B0xx13qLKyUqtWrWp2/SuvvKINGzZIkkKhkD744AM99thjkqQXXnhBW7ZskSTNnj1bNTU1SktLU3FxsUpKSjRo0CBFIhHNnDlTklRWVqZHHnlEknT//fdr165d2rRpkyzL0q5du5rMWAEAgHOTP5Y/vHPnzidcf2zWJzExUWPHjpUkTZgwQdOmTZMkrVq1StnZ2VqzZo0kadSoUerQoYMkady4ccrPz9eOHTtUWlqqtWvXKhwOR9uQpCuuuEKZmZkqKCjQqlWrdP/99zfbj7q6OtXV1UWfV1ZWSjo6sxWJRFq07034zf4qIn6/HNtWxHC7MrW/rchvmd1nv+WXLdtou8bGTSszOXz8/ohs25Hfb3bf46OUho9v+eXIVsT0KTwOiuk3fE7z+/2ybdtou/FyfJsUiUTkOE6b3/dT7V9Mw9HJ7Nu3T9LREGXbRye5unXrFl2/d+9elZeXq6amRpLUtWvX6LrPb3esrea2Kygo0N69e4/bjwULFmjevHlNlhcVFSkpKel0d6t5EyeaaaeBY9uqyMpSoSTbccw1XFBgrq1WMrGb2VraspWVlCVJcmSmlgVxUEfJ7LC0bUdZWRWSCuU45iat46KU7Qwf37JV4Ws4vg2NSUlxUcyJhs+Vtm0rK6vh+DZ0royX49skx3FUUVGhwsLC6N/rtqi6uvqUtmvT4ch13RMusyyr2W1asp1lWcftx6xZszRjxozo88rKSqWmpiojI0PBYPDEO3GqcnPNtNMg4verUFJmKCRfw4yZEUuWmGurleS+aLaWx2aMQgdDCrtmarmkd9uvo2R2WB6dMSpUKJSpcNhnrN04GJLSVsPHtxqO7/qQfDJ4fMfBuMw1fK48NmMUCoWiVxfO1JK4GJRmRSIRFRYWKjMzUz6fuePbtGNXfk6mTYejHj16SJLKy8vlOI5s29bBgwej61NTU5WcnKzExETV1NTowIED0XWf3+5YW5J04MABZWRkNNouNTX1uP0IBAIKBAJNlvt8PnODwGSAaWA7jnzhsNlw1IYH/TGmAoyXI0dhN2ys7bZ88vAyPSwdx1Y47DMajuKjlK1wfMuRT2Gz4SgOimkqwHg5jqNwOGys7Xg5vk2zbdvs38VWcKp9a9PhaPTo0frNb36j2tparVixQuPGjdOyZcsarff7/crJydGKFSuUl5enqqoqnXfeeVq+fLkkqV+/fkpJSVFOTo78fr/C4bByc3M1ZMgQbdu2TYWFhdG2AAA4Z6zbbK4t15Vqq6SyKukEV2JO2zVfMdfWaYjphcFQKKTMzEyNGDEiumzOnDnKzMzU5MmTNX78eA0bNkzS0evMffv2jV7emjRpkgYMGCBJmj9/vhITE7Vnzx6lp6crLS1Nb7/9tnw+nxYuXChJuuiii6LvXHv00UfVp08fDRkyRK7rqnfv3rr33nvP4p4DAIC2KqbhqLKyUkVFRdqzZ0902aFDh1RUVKT9+/fL5/Pp1Vdf1bRp05ScnKzi4mL16NFDc+bM0eLFi6Ovyc7O1rp16zRy5EjV1taqoqJCQ4YM0WuvvdZoRujHP/6xHnvsMfXt21clJSU6//zzddddd2n9+vU6//zzz+auAwCANiqml9WmTJnS6MMcmxMMBrVo0SItWrTohNsNHDhQeXl5J9zGsixNnz5d06dPP92uAgCAc0Tbfb8dAABADBCOAAAAPAhHAAAAHoQjAAAAD8IRAACAB+EIAADAg3AEAADgQTgCAADwIBwBAAB4EI4AAAA8CEcAAAAehCMAAAAPwhEAAIAH4QgAAMCDcAQAAOBBOAIAAPAgHAEAAHgQjgAAADwIRwAAAB6EIwAAAA/CEQAAgAfhCAAAwINwBAAA4EE4AgAA8CAcAQAAeBCOAAAAPAhHAAAAHoQjAAAAD8IRAACAB+EIAADAg3AEAADgQTgCAADwIBwBAAB4EI4AAAA8CEcAAAAehCMAAAAPwhEAAIAH4QgAAMCjReEoPT1dEydObLL8wQcf1G233XbGnQIAAIiVFoWjkpISlZaWNln++uuvKzc394w79XmHDx/WD37wA/Xp00fnn3++gsGg+vXrp4cffliRSESSVFVVpfvuu0/du3dXQkKCMjIyNHfuXNXX1zdqa/Pmzbr++usVDAbVvn17DR06VKtXrzbeZwAAEJ/8p7Pxc889F/33oUOHGj0/fPiwdu7cqYSEBHO9a/Dd735Xzz77rCQpKytL1dXV2rFjhx588EG1a9dOM2bM0NixY7Vhwwa1a9dO6enpKigo0EMPPaTCwkItXbpUkrRt2zYNHz5cNTU16tKli4LBoDZu3KgxY8ZoxYoVGj16tPG+AwCA+HJa4WjKlCmyLEuWZam4uFhTp05ttN51XV1xxRVGOyhJGzZskCSNGjVKq1at0meffaYuXbqoqqpKe/bs0SuvvBLdJhQK6YYbbtATTzyhadOm6YUXXtCMGTP0b//2b5o9e7ZqamqUlpam7du3KzExUcOGDVN+fr5mzpxJOAIAAKcXjqSjAciyLLmu22h5YmKi+vbtq8cff9xY5465+uqrVVRUpLy8PF122WWqrq5WVVWVhgwZov/3//6fHnrooWgfxo4dK0maMGGCpk2bJklatWqVsrOztWbNGklHQ1aHDh0kSePGjVN+fr527Nih0tJSpaSkNPn5dXV1qquriz6vrKyUJEUikehlvTPmP+1fxQlF/H45tq2I4XZlan9bkd8yu89+yy9bttF2jY2bVmZy+Pj9Edm2I7/f7L7HRykNH9/yy5GtiOF246GYfsPnNL/fL9u2jbYbL8e3Pvd3/ExEXFeO6ypisM2jDZs+X5xae6c1GhzHkSTZtq3Bgwdr48aNp9+zFnjqqafkOI6ee+45/f3vf5ckJSQkqH///kpOTta+ffskSZ07d5ZtH72Nqlu3btHX7927V+Xl5aqpqZEkde3aNbru89s1F44WLFigefPmNVleVFSkpKQkA3soqZkb3M+EY9uqyMpSoSS74fdmREGBubZaycRuZmtpy1ZWUpYkyZGZWhbEQR0ls8PSth1lZVVIKpTjmHujbFyUsp3h41u2KnwNx7ehMSkpLorZ3JuBzoRt28rKaji+DZ0r4+X4Vm2VsaYcuaqIfKbCuirZsoy1a3pMVldXn9J2LYrKa9euVTAYbMlLW+TRRx/V888/r6FDh+rll1/WoUOHNHz4cP3iF79Qu3btmsxiSWq0rLmZruNt15xZs2ZpxowZ0eeVlZVKTU1VRkaGuToYvpE94verUFJmKCRfOGyu4SVLzLXVSnJfNFvLYzNGoYMhhV0ztVzSu+3XUTI7LI/OGBUqFMpUOOwz1m4cDElpq+HjWw3Hd31IPhk8vuNgXJp+08+xGaNQKKSwoXPlkrgYlJLKzIWjiOuq0K1SZqCDfMf5W9oivXuba0v/uvJzMi0KR9dcc4127dqlX//61zpw4ECT4DFnzpyWNNusI0eOaPbs2XJdVxMmTFBycrKSk5M1dOhQ/fGPf9Trr7+uq666SpJUXl4ux3Fk27YOHjwYbSM1NVXJyclKTExUTU2NDhw4EF33+e2aEwgEFAgEmiz3+Xzy+Qyd5E0GmAa248gXDpsNR6b2txWZCjBejhyF3bCxto2Nm1Zmelg6jq1w2Gc0HMVHKVvh+JYjn8Jmw1EcFNNUgPFyHEfhcNhY2/FyfMtkiJFkW5Z8DQ9jDNfyVH83LQpHTz/9tO69997jTkGaDkfHBuyWLVskSbW1tXr//fclSeeff75Gjx6t3/zmN6qtrdWKFSs0btw4LVu2LNrG6NGj5ff7lZOToxUrVigvL09VVVU677zztHz5cklSv379mr2kBgAAzi0tuvA/f/58RSIRua7b7MOkLl26aPjw4ZKkpUuXqnfv3kpLS1NRUZEk6a677tL48eM1bNgwSUevR/ft2zd6GWzSpEkaMGBAtN+JiYnas2eP0tPTlZaWprfffls+n08LFy402m8AABCfWhSODhw4oI4dO+rdd99VfX29HMdp9DDtlVdeiX4IZGlpqT777DMNGjRIS5Ys0Xe+8x35fD69+uqrmjZtmpKTk1VcXKwePXpozpw5Wrx4cbSd7OxsrVu3TiNHjlRtba0qKio0ZMgQvfbaa7yNHwAASGrhZbVrr71WO3fuVL9+/Uz3p1kXXnihfvrTn+qnP/3pcbcJBoNatGiRFi1adMK2Bg4cqLy8PNNdBAAAXxAtCke33HKL7rnnHt12222aPHmyLrjggkbrj10GAwAAiDctCkdTp06VZVnKzc1t8rZKy7Ja5d0EAAAAZ0OLPxLU9I3XAAAAbUGLwtHu3btN9wMAAKBNaFE46tmzp+l+AAAAtAktCkff/OY3j7vOsiz99re/bXGHAAAAYqlF4Wjx4sXNfg+Z67qEIwAAENdaFI6GDx/eKBx9+umneu+99+S6rq6++mpjnQMAADjbWhSO3nzzzSbL/vGPf+iqq67SDTfccKZ9AgAAiJkWfX1Ic770pS+pf//+euKJJ0w1CQAAcNa1aOboueeea/Q8Eolo165d2rBhgxITE410DAAAIBZaFI6mTJly3Buyr7nmmjPuFAAAQKwY+4Tsrl27KicnRz//+c/PuFMAAACx0qJw5DiO6X4AAAC0CS2eOZKk2tpavf/++5Kkyy67TOedd56RTgEAAMRKi9+t9vDDD6tLly668sordeWVV6pLly76yU9+YrJvAAAAZ12LwtEzzzyjH/3oRzpy5Ihc15Xrujpy5IgefPBBPfvss6b7CAAAcNa0KBw9+eSTkqSbbrpJf/jDH/SHP/xB48ePl+u6evzxx412EAAA4Gxq0T1HO3fuVFpaml566aXosltuuUW9evXSzp07jXUOAADgbGvRzJHP51Ntba3C4XB0WX19vWpra+Xz+Yx1DgAA4Gxr0cxR//79tXHjRg0fPlw333yzLMvSSy+9pIMHD2rIkCGm+wgAAHDWtCgczZw5U+PHj1d+fr7y8/Ml/etDIX/wgx+Y6x0AAMBZ1qLLauPGjdNzzz2n1NTU6LvVevTooSVLlujGG2803UcAAICz5rRmjkpKSrR+/Xr16dNHt99+u26//XYdOnRIklRYWKiCggLt3r1bvXr1apXOAgAAtLbTmjn66U9/qqlTp6qysjK6LDk5WcnJyTpy5IimTp3KB0ECAIC4dlrh6I033lAwGNSoUaOarMvJydEFF1ygN954w1jnAAAAzrbTCkcffvihevTocdz1qamp2r9//xl3CgAAIFZOKxz5/X7t2bNHjuM0WReJRFRSUqJ27doZ6xwAAMDZdlrh6NJLL1VVVZUefPDBJutmz56tyspKXXrppcY6BwAAcLad1rvVbr31Vr399ttauHChVq1apauvvlqWZWnDhg165513ZFmWbrvtttbqKwAAQKs7rXD03e9+V0uWLNG2bdv07rvv6t13342uc11XAwYM0He/+13jnQQAADhbTuuyWiAQ0BtvvKFvfOMb8vl80Q+A9Pl8mjRpkl5//XUlJCS0Vl8BAABa3Wl/fcgFF1ygpUuX6pe//KV27dol13X1pS99ScFgsDX6BwAAcFa16LvVJCkYDOorX/mKyb4AAADEXIu+Ww0AAOCLinAEAADgQTgCAADwIBwBAAB4EI4AAAA84iYcHTp0SP/1X/+lnj17KiEhQV26dFFOTo6Ki4slSVVVVbrvvvvUvXt3JSQkKCMjQ3PnzlV9fX2jdjZv3qzrr79ewWBQ7du319ChQ7V69epY7BIAAGiDWvxW/rOpvLxcgwYN0u7du5WQkKA+ffrIdV299dZbKi0tVc+ePTV27Fht2LBB7dq1U3p6ugoKCvTQQw+psLBQS5culSRt27ZNw4cPV01Njbp06aJgMKiNGzdqzJgxWrFihUaPHh3jPQUAALEWFzNHP/rRj7R7925ddtllKikp0Y4dO/T+++/rk08+0cCBA/XKK69ow4YNkqRQKKQPPvhAjz32mCTphRde0JYtWyQd/XLcmpoapaWlqbi4WCUlJRo0aJAikYhmzpwZq90DAABtSJufOXJdVy+++KIkKTU1VSNHjtTu3buVmZmpH/7wh/rGN76hlStXSpISExM1duxYSdKECRM0bdo0SdKqVauUnZ2tNWvWSJJGjRqlDh06SJLGjRun/Px87dixQ6WlpUpJSWnSh7q6OtXV1UWfV1ZWSpIikYgikYiZHfWb/VVE/H45tq2I4XZlan9bkd8yu89+yy9bttF2jY2bVmZy+Pj9Edm2I7/f7L7HRykNH9/yy5GtiOlTeBwU02/4nOb3+2XbttF24+X4lusaayriunJcVxGDbR5t2PT54tTaa/Ph6NChQ/r4448lSStXrlRKSoouvPBCbd++XZMmTVK7du20b98+SVLnzp1l20cnw7p16xZtY+/evSovL1dNTY0kqWvXrtF1n9+uuXC0YMECzZs3r8nyoqIiJSUlGdhLSRMnmmmngWPbqsjKUqEk23HMNVxQYK6tVjKxm9la2rKVlZQlSXJkppYFcVBHyeywtG1HWVkVkgrlOOYmreOilO0MH9+yVeFrOL4NjUlJcVHMiYbPlbZtKyur4fg2dK6Ml+NbtVXGmnLkqiLymQrrqmTLMtau6TFZXV19Stu1+XAUDoej/7700ku1bds2SVL//v21c+dOPfnkkwoEAk1e53rSq2VZjZ6faLvmzJo1SzNmzIg+r6ysVGpqqjIyMsx9p1xurpl2GkT8fhVKygyF5PPU8IwtWWKurVaS+6LZWh6bMQodDCnsmqnlkt5tv46S2WF5dMaoUKFQpsJhn7F242BISlsNH99qOL7rQ/LJ4PEdB+My1/C58tiMUSgUavT35kwsiYtBKanMXDiKuK4K3SplBjrId5y/pS3Su7e5tvSvKz8n0+bDUXJyshISEvTZZ58pOztbCQkJkqTs7Gzt3LlTJSUlGjlypKSjN247jiPbtnXw4MFoG6mpqUpOTlZiYqJqamp04MCB6LrPb9ecQCDQbADz+Xzy+Qyd5E0GmAa248gXDpsNR6b2txWZCjBejhyF3bCxto2Nm1Zmelg6jq1w2Gc0HMVHKVvh+JYjn8Jmw1EcFNNUgPFyHEfhcNhY2/FyfMtkiJFkW5Z8DQ9jDNfyVH83bf6G7Hbt2mn48OGSpO3bt6u+vl719fXavn27JKl3797Rd5nV1tZqxYoVkqRly5ZF2xg9erT8fr9ycnIkSXl5eaqqqlJ9fb2WL18uSerXr1+zl9QAAMC5pc3PHEnS/PnztX79ev39739Xenq6XNfV/v375fP59MADD2j48OEaNmyYNmzYoIkTJ0bfyi9JkyZN0oABA6LtrFmzRnv27FF6eroSEhJUWloqn8+nhQsXxnIXAQBAG9HmZ44kadCgQXrjjTc0YsQIVVRUqLa2Vtddd53++te/6tprr5XP59Orr76qadOmKTk5WcXFxerRo4fmzJmjxYsXR9vJzs7WunXrNHLkSNXW1qqiokJDhgzRa6+9xmccAQAASXEycyRJQ4cO1dq1a4+7PhgMatGiRVq0aNEJ2xk4cKDy8vJMdw8AAHxBxMXMEQAAwNlCOAIAAPAgHAEAAHgQjgAAADwIRwAAAB6EIwAAAA/CEQAAgAfhCAAAwINwBAAA4EE4AgAA8CAcAQAAeBCOAAAAPAhHAAAAHoQjAAAAD8IRAACAB+EIAADAg3AEAADgQTgCAADwIBwBAAB4EI4AAAA8CEcAAAAehCMAAAAPwhEAAIAH4QgAAMCDcAQAAOBBOAIAAPAgHAEAAHgQjgAAADwIRwAAAB6EIwAAAA/CEQAAgAfhCAAAwINwBAAA4EE4AgAA8CAcAQAAeBCOAAAAPAhHAAAAHoQjAAAAD8IRAACAR9yFo1tuuUWWZcmyLH3961+PLq+qqtJ9992n7t27KyEhQRkZGZo7d67q6+sbvX7z5s26/vrrFQwG1b59ew0dOlSrV68+27sBAADaKH+sO3A6nnnmGeXm5jZZHolENHbsWG3YsEHt2rVTenq6CgoK9NBDD6mwsFBLly6VJG3btk3Dhw9XTU2NunTpomAwqI0bN2rMmDFasWKFRo8efbZ3CQAAtDFxM3NUVFSkadOm6aqrrlL37t0brXvllVe0YcMGSVIoFNIHH3ygxx57TJL0wgsvaMuWLZKk2bNnq6amRmlpaSouLlZJSYkGDRqkSCSimTNnntX9AQAAbVNczByFw2FNnjxZtm1r6dKluvbaaxutX7lypSQpMTFRY8eOlSRNmDBB06ZNkyStWrVK2dnZWrNmjSRp1KhR6tChgyRp3Lhxys/P144dO1RaWqqUlJQmP7+urk51dXXR55WVlZKOzlhFIhEzO+k3+6uI+P1ybFsRw+3K1P62Ir9ldp/9ll+2bKPtGhs3rczk8PH7I7JtR36/2X2Pj1IaPr7llyNbEdOn8Dgopt/wOc3v98u2baPtxsvxLdc11lTEdeW4riIG2zzasOnzxam1FxfhaN68ecrPz9eSJUvUq1evJuv37dsnSercubNs++hkWLdu3aLr9+7dq/LyctXU1EiSunbtGl33+e2aC0cLFizQvHnzmiwvKipSUlJSC/fqcyZONNNOA8e2VZGVpUJJtuOYa7igwFxbrWRiN7O1tGUrKylLkuTITC0L4qCOktlhaduOsrIqJBXKccxNWsdFKdsZPr5lq8LXcHwbGpOS4qKYEw2fK23bVlZWw/Ft6FwZL8e3aquMNeXIVUXkMxXWVcmWZaxd02Oyurr6lLZr8+Fo8+bNWrBggW6//XZNnjy52W3cZpKqd5llWc1u09x2zZk1a5ZmzJgRfV5ZWanU1FRlZGQoGAye0n6cVDP3Up2JiN+vQkmZoZB84bC5hpcsMddWK8l90Wwtj80YhQ6GFHbN1HJJ77ZfR8nssDw6Y1SoUChT4bDPWLtxMCSlrYaPbzUc3/Uh+WTw+I6Dcdncfadn4tiMUSgUUtjQuXJJXAxKSWXmwlHEdVXoVikz0EG+4/wtbZHevc21pX9d+TmZNh+OduzYoUgkotzcXL388suSpCNHjkiSXnrpJSUlJemWW26RJJWXl8txHNm2rYMHD0bbSE1NVXJyshITE1VTU6MDBw5E131+u+YEAgEFAoEmy30+n3w+Qyd5kwGmge048oXDZsORqf1tRaYCjJcjR2E3bKxtY+OmlZkelo5jKxz2GQ1H8VHKVji+5cinsNlwFAfFNBVgvBzHUTgcNtZ2vBzfMhliJNmWJV/DwxjDtTzV303c3JBdW1urw4cP6/Dhw9HZnnA4rMOHD+uGG26IbrNixQpJ0rJly6KvHT16tPx+v3JyciRJeXl5qqqqUn19vZYvXy5J6tevX7OX1AAAwLmlzYejKVOmyHXdRo+ePXtKkm677Ta5rqvx48dr2LBhko5ej+7bt2/0MtikSZM0YMAASdL8+fOVmJioPXv2KD09XWlpaXr77bfl8/m0cOHC2OwgAABoU9p8ODoVPp9Pr776qqZNm6bk5GQVFxerR48emjNnjhYvXhzdLjs7W+vWrdPIkSNVW1uriooKDRkyRK+99hqfcQQAACTFwT1HzSkpKWmyLBgMatGiRVq0aNEJXztw4EDl5eW1Us8AAEC8+0LMHAEAAJhCOAIAAPAgHAEAAHgQjgAAADwIRwAAAB6EIwAAAA/CEQAAgAfhCAAAwINwBAAA4EE4AgAA8CAcAQAAeBCOAAAAPAhHAAAAHoQjAAAAD8IRAACAB+EIAADAg3AEAADgQTgCAADwIBwBAAB4EI4AAAA8CEcAAAAehCMAAAAPwhEAAIAH4QgAAMCDcAQAAOBBOAIAAPAgHAEAAHgQjgAAADwIRwAAAB6EIwAAAA/CEQAAgAfhCAAAwINwBAAA4EE4AgAA8CAcAQAAeBCOAAAAPAhHAAAAHoQjAAAAD8IRAACAR5sPRz/72c80YsQIXXzxxQoEAurZs6fuuusuFRcXR7epqqrSfffdp+7duyshIUEZGRmaO3eu6uvrG7W1efNmXX/99QoGg2rfvr2GDh2q1atXn+1dAgAAbVibD0dPPPGE1q1bp4SEBF1yySXau3evnnvuOQ0dOlSVlZWKRCIaO3asFi1apIMHDyo9PV0lJSV66KGHNGXKlGg727Zt0/Dhw5WXl6dAIKBOnTpp48aNGjNmjFauXBm7HQQAAG1Kmw9Hd999t/bs2aM9e/aouLhY9913nySprKxMa9as0SuvvKINGzZIkkKhkD744AM99thjkqQXXnhBW7ZskSTNnj1bNTU1SktLU3FxsUpKSjRo0CBFIhHNnDkzFrsGAADaIH+sO3AyDz74YKPnV199dTT8BAIBvfzyy5KkxMREjR07VpI0YcIETZs2TZK0atUqZWdna82aNZKkUaNGqUOHDpKkcePGKT8/Xzt27FBpaalSUlKa7UNdXZ3q6uqizysrKyVJkUhEkUjEzI76zf4qIn6/HNtWxHC7MrW/rchvmd1nv+WXLdtou8bGTSszOXz8/ohs25Hfb3bf46OUho9v+eXIVsT0KTwOiuk3fE7z+/2ybdtou/FyfMt1jTUVcV05rquIwTaPNmz6fHFq7bX5cOQVDof15JNPSpLS09OVk5Ojxx9/XJLUuXNn2fbRibBu3bpFX7N3716Vl5erpqZGktS1a9fous9vd7xwtGDBAs2bN6/J8qKiIiUlJZ3hXjWYONFMOw0c21ZFVpYKJdmOY67hggJzbbWSid3M1tKWraykLEmSIzO1LIiDOkpmh6VtO8rKqpBUKMcxN2kdF6VsZ/j4lq0KX8PxbWhMSoqLYk40fK60bVtZWQ3Ht6FzZbwc36qtMtaUI1cVkc9UWFclW5axdk2Pyerq6lPaLm7C0eHDh/WNb3xDa9eu1UUXXaQ//elPCgQCcptJqd5llmU1u01z2x3PrFmzNGPGjOjzyspKpaamKiMjQ8FgsCW701Rurpl2GkT8fhVKygyF5AuHzTW8ZIm5tlpJ7otma3lsxih0MKSwa6aWS3q3/TpKZofl0RmjQoVCmQqHfcbajYMhKW01fHyr4fiuD8kng8d3HIzLXMPnymMzRqFQSGFD58olcTEoJZWZC0cR11WhW6XMQAf5TvD39LT17m2uLf3rys/JxEU4Kisr0w033KAtW7aoT58++vOf/6z09HRJUo8ePSRJ5eXlchxHtm3r4MGD0dempqYqOTlZiYmJqqmp0YEDB6LrPr/d8QQCAQUCgSbLfT6ffD5DJ3mTAaaB7TjyhcNmw5Gp/W1FpgKMlyNHYTdsrG1j46aVmR6WjmMrHPYZDUfxUcpWOL7lyKew2XAUB8U0FWC8HMdROBw21na8HN8yGWIk2ZYlX8PDGMO1PNXfTZu/Ifv999/X4MGDtWXLFl199dV66623osFIkkaPHi1Jqq2t1YoVKyRJy5Yta7Te7/crJydHkpSXl6eqqirV19dr+fLlkqR+/fod95IaAAA4t7T5maObb75Ze/bskXT084yO3XQtSd/61rc0depUDRs2TBs2bNDEiROVnp4evd47adIkDRgwQJI0f/58rVmzRnv27FF6eroSEhJUWloqn8+nhQsXnv0dAwAAbVKbnznyvkts27Ztys/Pjz4+/PBD+Xw+vfrqq5o2bZqSk5NVXFysHj16aM6cOVq8eHH0tdnZ2Vq3bp1Gjhyp2tpaVVRUaMiQIXrttdeis08AAABtfuaopKTkpNsEg0EtWrRIixYtOuF2AwcOVF5enqGeAQCAL6I2P3MEAABwNhGOAAAAPAhHAAAAHoQjAAAAD8IRAACAB+EIAADAg3AEAADgQTgCAADwIBwBAAB4EI4AAAA8CEcAAAAehCMAAAAPwhEAAIAH4QgAAMCDcAQAAOBBOAIAAPAgHAEAAHgQjgAAADwIRwAAAB6EIwAAAA/CEQAAgAfhCAAAwINwBAAA4EE4AgAA8CAcAQAAeBCOAAAAPAhHAAAAHoQjAAAAD8IRAACAB+EIAADAg3AEAADgQTgCAADwIBwBAAB4EI4AAAA8CEcAAAAehCMAAAAPwhEAAIAH4QgAAMCDcAQAAOBxToajF154QQMGDFBiYqI6deqkiRMnqqCgINbdAgAAbcA5F45+/etfa/LkyXrnnXd08cUXKxKJ6KWXXtLQoUNVWloa6+4BAIAYO6fCUV1dnR544AFJ0oQJE1RcXKydO3eqQ4cOOnTokBYsWBDjHgIAgFjzx7oDZ9PmzZv1z3/+U9LRcCRJKSkpGjx4sFavXq1Vq1Y1+7q6ujrV1dVFn3/66aeSpI8//liRSMRM53w+M+00iPh8qoxE9LHPJ5/rmmv444/NtdVKfHVma+mzfIrUROSr88k1VMuP46COktlh6fNFFIlUyuf7WK5rruG4KOURw8e3fKpsF9HH9T75dI4d34bPlT6fT5FIRD7fuXd8q7rKWFMR11VlXbU+Dks+yzLWrukxWVlZKUkn/12755Df/e53riRXkvv6669Hl99+++2uJDcQCDT7urlz50Zfx4MHDx48ePCI78e+fftOmBfOqZkj9zhJ8dhy6zhpd9asWZoxY0b0ueM4qqioUOfOnY/7mlirrKxUamqq9u3bp2AwGOvuxDVqaQZ1NIdamkMtzYiXOrquq6qqKqWkpJxwu3MqHPXo0SP67wMHDkT/ffDgQUlSampqs68LBAIKBAKNll1wwQXmO9gKgsFgmx6o8YRamkEdzaGW5lBLM+Khjh07djzpNufUDdkDBw5U586dJUkvvfSSJGn//v166623JEmjR4+OWd8AAEDbcE6Fo4SEBD388MOSpFAopPT0dGVlZam6ulpdunTRD3/4wxj3EAAAxNo5FY4k6Z577tGSJUvUv39/lZaWyrIs3Xzzzdq4ceNJr0HGk0AgoLlz5za5HIjTRy3NoI7mUEtzqKUZX7Q6Wu7x7lIGAAA4B51zM0cAAAAnQjgCAADwIBwBAAB4EI4AAAA8CEcAEIeqqqqi3xMFwCzC0RdETU2N3nnnHR0+fFiSdPjwYf3mN7/RokWLtG/fvhj3DoBpKSkp6tSpU6y7EVdKSkq0ceNG1dfXSzr6eXdf/epXlZ6ertGjR2v9+vUx7iHaCt7K/wXw3nvv6atf/aoqKirUtWtXvfHGG7rtttv0/vvvSzr6ce6bNm3Sl770pRj3NP7dfvvt+uijj7RmzZpYdyUuVFdXa82aNQoEAsrJyVG7du2i655++ml9+OGHmjNnTgx72PZNmjSp2eW5ubmKRCK67bbbZFmWli5depZ7Fn+uu+46bdq0SZ988olyc3M1efJkSf/6fk2/36+NGzfqK1/5Siy7GRccx5FlWdHvF3333Xf1v//7v9q7d6/S0tJ03333qW/fvjHuZcsRjr4Abr31VuXm5ko6+uW5vXr1UnFxcXS9ZVm64447tHjx4hj18Iujd+/eKi4uViQSiXVX2rzdu3dr2LBhKisrkyRlZGToT3/6UzSkX3XVVXr77bep5UnYtn3CL7h2XVeWZVHHU5CcnKyLLrpI7733nvr376/t27fr0ksvVXZ2trZv366///3vGjVqlFauXBnrrrZ5Pp9PgwcP1l//+ldt27ZNQ4YMUV1dXXR9UlKSNm/erN69e8ewly13Tn3x7BfVW2+9JZ/Pp1mzZunhhx/W7t279fWvf12zZs3Sq6++qgceeEBvvvlmrLsZF37961+fcD33eJy6efPm6aOPPoo+LywsVE5Ojv7617+qZ8+eMexZfLrkkkvk8/miz/fu3StJ1PI0VFZWRr8JobCwUN27d9e2bdvUrl071dfXKz09XVu3bo1xL+OD67rRGbcf/ehHqq2tlSR17txZ//znP1VdXa358+fr2WefjWU3W85F3AsEAu5ll13muq7rZmVlubZtu/v27Yuu79Gjh5uQkBCr7sUVy7Jc27aP+zi2HifXs2dP17Zt93vf+54bCoXca6+91rUsy7300kvdjz/+2B08eDC1PAUTJ050Lctyhw4d6paUlESXJyUlUb/T1LNnT/e8885zy8rK3Msvv9zt3r27Gw6HXdd13XA47KamprpJSUkx7mV8sCzLveqqq1zXdd2LL77YtW3bzcvLc13XdfPy8lzbtt309PRYdvGMcEP2F0BiYmL0+2w6dOggSerevXt0fceOHRvd64ETcxv+j6i5B05dWVmZevXqpZ///Oe66aabtHr1at1www36xz/+ofHjxzeagsfxLVu2TL/97W+1fft2ffnLX9bvf//7WHcpbt14442qq6vTyJEjlZqaqv379ys7O1uTJ09W//79tX//fl155ZWx7mbc+eSTT9S3b1+NHDlSkjRy5Ej17du30cxxvOGeoy+A/v37q7y8XB9++KH+9Kc/6eDBg/qP//gPSVJ9fb0uuOACpaSkqKCgIMY9bfu6du2qzp07N3vPgeu6uvbaa7V3717u7zgFKSkpCgQC2r17d3TZkSNHNHz4cL3zzjvcK3OaioqKNHnyZP3tb3/T7bffrmXLlqmuro76nYby8nJdeeWVKikpaXIfl+u6SkhI0Nq1a3XVVVfFqIfxw7ZtJScn62tf+5pyc3OVkpKiDz74ILq+V69eqq+v14cffhjDXp6B2ExYwaRHH33Uvemmm9y6urom655//nnXsix30qRJMehZ/BkzZoybkJDg1tbWNrs+IyODSxmnaMSIEU0u8bqu63700Uduz549uUTZAuFw2P3Rj37k+v1+6tdC5eXl7r333ut26tTJtSzLtSzLDQQC7siRI938/PxYdy9uHKudt4affPKJ67quu3fvXte2bXfkyJEx7mXLMXP0BVdRUaGqqipdcMEF6tixY6y70+b95S9/0datW3XnnXfqwgsvbLL+5ZdfVmVlpe66664Y9C6+/OxnP9OTTz6pe+65R7NmzWq07v3339fNN9+s+vr6Ru+sxKnZsmWLduzYIUmMxTNw6NAhhcNhJScny+/n/UmnY968eU2W3X777crIyNDChQv1y1/+Ug8++KC+9a1vxaB3Z45wBAAA4MEN2QAAAB6EIwAAAA/CEQAAgAfhCAAAwINwBOCc9uabb0a/QLOkpOSUXzdlyhRZlqURI0a0Wt8AxAbhCEBceOaZZ6Ihxrbt0woy0vHDTDAY1KBBgzRo0KDoJ82fioyMDA0aNEhZWVnRZSNGjJBlWZoyZcpp9Q1A20I4AhAXFi9eHP2367rGvtBywIAB2rRpkzZt2qSLL774lF83e/Zsbdq0Sb/4xS+M9ANA20E4AtDm7d69W3/5y18kSV/5ylckSc8++2yj77urqqrS97//fWVkZCghIUGdO3fW6NGjVVNTo7S0tGiYWrduXXQG6s0332xyWe13v/udLMtSu3btVF5eHm3/v//7v2VZli655BI5jtNkJsqyLK1bty7at2NtFhQUyLZtWZal119/PdreH//4R1mWJZ/Pp/3797dq/QCcHsIRgDZv8eLFcl1XF110kX77299KOhqY1q9fL0n67LPPNGLECP3sZz9TcXGxUlJSdOGFFyovL091dXX68pe/rC5dukg6+uXMxy6jBYPBJj9r/Pjx6tixo8LhsF566aXo8j/84Q+SpDvuuEO23fTUOWjQoOgXP3fp0iX6M5KSknTddddJkp5++uno9qFQSJJ03XXX6ZJLLjnjGgEwh3AEoE1zXVfPP/+8JGnSpEm64oor9OUvf1nSvy61/f73v9fWrVslSY888ohKSkpUWFio7du3q3379nr55Zf1ta99TVLjy2gDBgxo8vMSExN1yy23SPpXIHr33XejX6p5vK/r8Lb3ta99rdGlum9/+9uSjn79zCeffKJwOKw//vGPkqQ777zzzAoEwDjCEYA27c0339Tu3bslHZ218f43NzdXhw8fVn5+viQpEAjoe9/7XvS1l19+uRISEk77Zx4LQOvWrVNZWZl+//vfS5KuvPJKXXrppafd3rhx49S9e3fV1tbqhRde0BtvvKGPP/5YHTp00E033XTa7QFoXXzTHoA2zXsj9rH7eyKRiCSpurpaubm5jba3LOuMf+awYcOUkZGhoqIivfjii3rxxRclqcXvQvP5fLr77rs1d+5cPfPMM9EZpltuuUXt27c/4/4CMIuZIwBtVnV1daP7fj799FN9+umnqq6uji5bvHixBg0aJEmqq6vTY489Fl23c+dOffbZZ5IUDSGHDx8+pZ997HLXggULVFxcrEAgoK9//esnfM2Jfsbdd98tv9+vzZs3a+nSpY1+BoC2hXAEoM1atmxZNGhs375drutGH0888YSko5e+Bg8eHJ2Nuf/++9WrVy/16dNHl19+uY4cOSJJ6tu3ryRp8+bN6tevnwYPHqyamprj/uw777xTlmWprKxM0tFLYxdeeOEJ+3vsZ4RCIQ0YMECjR4+Orrv44ov17//+75KOhqe0tDQNHz78tGsCoPURjgC0Wcfeft+7d2/169ev0bqbbrpJlmXJdV397ne/09q1a6PBaP/+/frnP/+p6667LvrBjt/85jc1YcIEdezYUTt27FB+fn708lxzPh9ejncjttf3v/99XXfddWrfvr3eeecdbd68udH673znO9F/33HHHUYuAQIwz3K9HxQCAGg1ZWVluvjii6Off5SRkRHrLgFoBjNHANDKysvLNXnyZF1zzTWSjs56EYyAtouZIwBoZSUlJerVq5fOO+88jRgxQs8995ySk5Nj3S0Ax0E4AgAA8OCyGgAAgAfhCAAAwINwBAAA4EE4AgAA8CAcAQAAeBCOAAAAPAhHAAAAHoQjAAAAj/8PtZtoPdzyKjEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_data.Activity.value_counts().plot(kind='bar',color=['r','g','b','orange','k','pink'])\n",
    "plt.xlabel('Activity',weight='bold')\n",
    "plt.ylabel('Count',weight='bold')\n",
    "plt.xticks(weight='bold')\n",
    "plt.yticks(weight='bold')\n",
    "plt.grid(alpha=0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "e4ee1558",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train=pd.DataFrame(x_train,columns=features[:-1])\n",
    "x_test=pd.DataFrame(x_test,columns=features[:-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c4171e4",
   "metadata": {},
   "source": [
    "# Applying Feature Selection Techiniques"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6235692d",
   "metadata": {},
   "source": [
    "## 1. Check the duplicate features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "2debb9c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['tBodyAccMag-sma()', 'tGravityAccMag-mean()', 'tGravityAccMag-std()',\n",
       "       'tGravityAccMag-mad()', 'tGravityAccMag-max()', 'tGravityAccMag-min()',\n",
       "       'tGravityAccMag-sma()', 'tGravityAccMag-energy()',\n",
       "       'tGravityAccMag-iqr()', 'tGravityAccMag-entropy()',\n",
       "       'tGravityAccMag-arCoeff()1', 'tGravityAccMag-arCoeff()2',\n",
       "       'tGravityAccMag-arCoeff()3', 'tGravityAccMag-arCoeff()4',\n",
       "       'tBodyAccJerkMag-sma()', 'tBodyGyroMag-sma()', 'tBodyGyroJerkMag-sma()',\n",
       "       'fBodyAccMag-sma()', 'fBodyBodyAccJerkMag-sma()',\n",
       "       'fBodyBodyGyroMag-sma()', 'fBodyBodyGyroJerkMag-sma()'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.T[x_train.T.duplicated()==True].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "b871b33d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7352, 562)"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "163d5d75",
   "metadata": {},
   "source": [
    "## 1. To remove the duplicate features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "35743b1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train=train_data.loc[:,~train_data.T.duplicated(keep='first')]\n",
    "x_test=test_data.loc[:,~test_data.T.duplicated(keep='first')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "b29122c8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(7352, 542)\n",
      "(2947, 542)\n"
     ]
    }
   ],
   "source": [
    "print(x_train.shape)\n",
    "print(x_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "990da359",
   "metadata": {},
   "source": [
    "## 1 Variance Threshold method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "d36b441f",
   "metadata": {},
   "outputs": [],
   "source": [
    "columns=x_train.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "97068ec9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_selection import VarianceThreshold\n",
    "sel=VarianceThreshold(threshold=0.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "c22f14f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-6 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-6 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-6 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-6 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-6 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-6 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-6 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-6 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-6 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-6 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-6 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-6 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-6 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-6 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-6 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-6 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-6\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>VarianceThreshold(threshold=0.05)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" checked><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;VarianceThreshold<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.feature_selection.VarianceThreshold.html\">?<span>Documentation for VarianceThreshold</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>VarianceThreshold(threshold=0.05)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "VarianceThreshold(threshold=0.05)"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sel.fit(x_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8bb4c92",
   "metadata": {},
   "source": [
    "### To know features whose value is less and greater than threshold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "a4a7edc0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([False, False, False,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True, False,\n",
       "       False,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True, False, False, False,  True, False,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True, False, False,\n",
       "       False, False, False, False,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True, False, False, False,  True,\n",
       "        True,  True, False, False, False, False,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True, False,\n",
       "       False, False,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True, False,  True, False,\n",
       "        True,  True,  True,  True,  True,  True,  True, False,  True,\n",
       "       False,  True, False,  True, False,  True, False,  True,  True,\n",
       "        True,  True,  True, False, False, False,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True, False,  True,\n",
       "        True, False, False, False,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True, False, False,  True, False,\n",
       "        True,  True,  True,  True,  True,  True,  True, False, False,\n",
       "       False,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True, False, False, False,  True,\n",
       "        True,  True,  True,  True,  True,  True, False, False, False,\n",
       "       False, False, False,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True, False,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True, False,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True, False,  True,\n",
       "        True,  True, False,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "       False, False,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True, False,  True,\n",
       "       False, False, False, False, False,  True,  True, False, False,\n",
       "        True, False,  True,  True, False, False, False, False, False,\n",
       "       False,  True,  True, False, False,  True, False,  True, False,\n",
       "       False, False, False, False, False, False,  True, False, False,\n",
       "       False,  True, False,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True, False, False, False,\n",
       "        True, False,  True, False,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "       False, False, False, False,  True, False, False,  True, False,\n",
       "       False, False,  True, False, False, False, False, False,  True,\n",
       "        True, False, False,  True, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "       False,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True, False, False, False,  True, False,\n",
       "       False, False,  True,  True,  True,  True,  True,  True, False,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True, False, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False,  True, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False, False,  True,\n",
       "        True,  True,  True, False,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True, False,  True,  True,  True,  True,  True,  True,  True,\n",
       "       False, False,  True,  True, False,  True,  True,  True,  True,\n",
       "        True,  True,  True, False, False,  True,  True, False,  True,\n",
       "        True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True])"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sel.get_support() #false: < threshold and true:>threshold"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58d3de2a",
   "metadata": {},
   "source": [
    "## Columns which pass variance > thereshold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "ed1f383f",
   "metadata": {},
   "outputs": [],
   "source": [
    "c=x_train.T[sel.get_support()].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "c6a1f87d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['tBodyAcc-std()-X', 'tBodyAcc-std()-Y', 'tBodyAcc-std()-Z',\n",
       "       'tBodyAcc-mad()-X', 'tBodyAcc-mad()-Y', 'tBodyAcc-mad()-Z',\n",
       "       'tBodyAcc-max()-X', 'tBodyAcc-max()-Y', 'tBodyAcc-max()-Z',\n",
       "       'tBodyAcc-min()-X',\n",
       "       ...\n",
       "       'fBodyBodyGyroJerkMag-kurtosis()', 'angle(tBodyAccMean,gravity)',\n",
       "       'angle(tBodyAccJerkMean),gravityMean)',\n",
       "       'angle(tBodyGyroMean,gravityMean)',\n",
       "       'angle(tBodyGyroJerkMean,gravityMean)', 'angle(X,gravityMean)',\n",
       "       'angle(Y,gravityMean)', 'angle(Z,gravityMean)', 'subject', 'Activity'],\n",
       "      dtype='object', length=351)"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7cb40c1",
   "metadata": {},
   "source": [
    "## To get rid of features less than threshlod"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "19d577a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train=sel.transform(x_train)\n",
    "x_test=sel.transform(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "b43201f1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(7352, 351)\n",
      "(2947, 351)\n"
     ]
    }
   ],
   "source": [
    "print(x_train.shape)\n",
    "print(x_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "ec744c4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train=pd.DataFrame(x_train,columns=c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "247b38bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_test=pd.DataFrame(x_test,columns=c)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ab8762e",
   "metadata": {},
   "source": [
    "## Correlation Method"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33ed1cf9",
   "metadata": {},
   "source": [
    "**This method uses Pearson's correlation coefficients for finding the Linear realtionship b/w two features or realtionship b/w the feature and output. Helps to reduce the multicollinearity, which inturn reduces the number of features**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "22386c37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ED5ZNgKYmJHZaEWiJaxsjCaWgYQAKia5XELaLSOfjEgNSUBca4dnGsG8YZUqBiK3DoG7qCwFKEcZTqqTelDL3ohTC8Uw7p/OITJpSydxPW6rOcC1Fm1sH2zOGve2a69lxvThpSGUpSWhRUKs4ZmKYMXWv/RpqrN+MrVrZ/JbrMNtHzUtedE1F1AroLevRWqE2Po2cPg/SObRfi8udMmW2HFPeoI5GoGpJdwRgxBYoQAcR2te0RAoZ33urCHG0RbRuFYQ+asNTEPioDU8iembGdbgW0dYLwxuNcdnaBulcYtzranF8vFSLpu9XRk2buY1n1Igx8NN5M/GMAoSXRdfKCDc1Xv8i7mNBnZSwKEkox80XoSgoHyVB12oIv4Ye2QhuCpFqMeeolRGpPMKywcsi3LQZD/muZKItLBsyraYs9TKitRsy+fE+61dNW2plDHClwLLRvgJbJmOjWnIZsgWOGxEFkqxSCCArzPMt0gLR2Yn2q8b5IST4VXP/AO1TEOk8lCrUhY2tNbYWZgIdT2aFivty4Js6TecRXhYfDV7c36L4OSClKXdYR6RbknqN6hJHm8kGlm3azbIRtjfeZ90UNSRePsR2FdaQuRc/tJLnQQSITBpRrVEWFn81xJOl1wIv997zPG8He//P8XJ2z0u3v5Jt9Hqgadw3sR1c1yWK/vuBZVkWYRji+z4tLS1MnjyZe++9l4MOOijZ57777mOfffYBYO7cufzwhz+kWq0mBuqf/vSn7c572GGHkc1m+e53v8utt946IVj28ccf5+GHH+bOO++c4HkfHR3loIMOYtWqVcyZM4d0Os3vf/97jj/++O3Ov9dee/GDH/yA4eHh7bz3tm0nE5iXYuHChSxcuJDFixez33778aMf/Yh99933Zetr7ty5rFu3jk2bNjF58mTABNVsC9d1mTt3Lk8++eQEnXswQcSO47DHHnsAMGPGjO3Kc8cdd/CDH/yAe+65h/nz53PRRRdxyimn8I53vGOHqwqe5233UKu9OIqqg/CryK5pRBueHP++8Wnj2QREazetXgYhBEOxx04PbQYpUbERJjunEq1Zia6VQUgcaUO9TgpBZBzqpIVNNTZu020B6RHJKA5RED/o/JCMcCkTof2IjHCoEKHrAVlhvMtlHdEiFbrq4yBwNIjWLGkNlcg81vyKjScUkRZoJRitpOhsrbB2zLT5rt01amMO0tJESqLG+s2LPdNmvkPytx7eCMVB8LLk3TSOdCgF5oZ0aRi18RlEz3RTT6m8MXwaVpabxpMODoKscBBAVQcUJTjbtENFgg4VengjsnMaWiv0yEZkl2l7HYXGK9kxGWplOpw89ShIDFo9tB7ROc28FKMIXa4g8nU8IdGVanKdnDLXCnUEWhlzT2lc1/Rht25eTHrLC5DOG+9nrQyxt0+NbjGTwVQWPbiBTq8FX4V0ePmkr+ixfmjpRBX6EdKJy5/CQSRGQ4iCapU6ilBIVCDoTFVR8YxHVcbGjXvLMUaOdIyh8hLoIEKXhqHh6VfKrBgA2vYg5eMJCVqjgCiQ4xOBxv4NAz/2yOtiKSmLLRQ+EsdW0Jj4RaExShv3DAitsIEIgSUVujBk+gIg23qJNj+HCurISTOJNj6NqBaTMQNA4CP7diF67P5kfCnHw5q9N2pog7mOVohMq1kRUBEilUVpCGJr2HI1FsawH5Ha9KnQTCCd2OhozdRw6w4MbgKl0PUaRCG6WjKTFkCvfhJl2bBlHSrbhtx9PzOJjes/mZCkW1DFQQh9RLbdjJ2GkZppRY9tTSaeujJmxkrXVHQ8ORRedsK9eFi4GjYJM35cYZOTLmUVQL0OhWEzIRjaiiqOmnrza6hyAdEz3Xjvq0X08EazyqTMedTIJmT7ZLMaMtZvnBnSSVYQVP9qRGsPenQzZNrMZKNeBlsQbDAzp1BAGElGpMa2lXFOxG3emTPn8UMLunrje1JoKdH1snkmAqJaRAPRYIGa6KJVRzhao0sj6EafFBY6qIJfQ5fHEKkWdBTiIEBt4zhqPGO0MkZ7UEfHRnEUSDJqeyeT1hENk1L7NSTgl2xCXyIYd4409klrga5UEdk0rdQhXi36v4SXe++9Vujt7d3OA9/f349t23R2dr7iPi/15r+WaKrlNLEddtppJx544AHWrFnD4OAgKn44Dg0NsWXLFjZs2MCtt97KFVdcwaGHHkpLi/GenHHGGVx66aXceOONPPPMM3z5y19m5cqVfPGLXwTgIx/5CFJKjjvuOJ588kl+85vfbKeMA2bScOyxx7J48WJmz549gc6ydOlS9tlnHw466CDmzZuXfN7ylrew3377sXTpUlKpFGeddRZnnnkm1113HS+88AJ/+tOfWLp0KQDHHHMMvb29HHHEEfzxj3/kxRdf5KabbtrO+G5g9erVLF68mPvvv5+1a9dy++238+yzz7L77rsn9bV69WpWrlzJ4OAg9Xqdt7/97ey666584hOf4NFHH+Wee+7hnHPO2e7c73rXu7j33nu3237PPfdw4IEH7nCVoVAocNxxx3H66acnqwcnn3wye+yxB4sWLXr5ht0BrKlzsabORbhpog1PYk2dC45HtG4VVs9M4/FxXNTQBoaqRWqhT0/sWbb2OhRrpwXmhW/ZROtXQRgvRdfKSAREETU07lQHd6qDh0WfzJBRUCvYjImIDoKJZULQjTEyBIJOHIQQWJhPj3DZRAphmUeYL0APFyhJyFghGSsk11VnGIe851Ov2fT1FNg4kmcnq8xOVpmBtXm0EkSBJO0GWD0zk+V8q2cmVs9MZEsP+FWzNN7WC1pRCmqUggqe5eBZDiLXgeiaiuyZich2GFoSGMNPSIhCIhRlFEIIHK3pkRm6IugMzUcB7RHoUCNyHajBtVAeQ+S7UINrUYNrjXHrplBbTf6D4aCIK2104KMD39AOhjea5fkgRGQzEIa4SAgj88F44lIKJlk5KBWxMSsktbpNrW4jgGikYu63WkS09CQTCmplRGsPor3XGB1dUxkNSqQtl7GgnPQV0TEZ6mVTnxiDAq3IYOHKCFdGtFtpsG1yWOSUJvIFxbpLGEnCSCIzreZa+S5EptXUb2s3aJX0A6LIGB+hMvu19phPS6fx2Kay5hjLpqYjEAIXhbR0Um+6MmomAuUxdFiPvc81sCxa8jVa8jUGq2m6nBrFmmvaNKibyUHog5cyn3hykFJgoXFSEbJ3FiKdN6sNw5uwps8DyyF68c9YfXMQXha15UWsGXsZmo6OiJ76I3R0JeNLZFqJHv0vZMdkZMdkREsPBIYOh+WgAx9HaFLdilS3ws5rIjTdoWYXH2TawcpJRizJmCUYswRry3nWqgzWG94JbV1YC98Bnb1Y899mDPMohL4ZiHQLdPYiUnnUH28hevg2okduJ3rkdmT3DGS+C/yqGTstPeh6Gdk9I2kH/Bpyym6mb1ZGx8dK51TTXvkucy9exqykKMWY9vE0TIkkUyKJwkxWplhZRHs7dPQiZy6Ajm5E7wxE7wxo7zGGfUuPmVgKaVZFNj2HLvQbOk6+CzW0Hvyq8d6ve9pQoGLIzmmmv7f1medZFJjVEVvizsjgzsiQU5qWthqzfahWHGp1mxHLZkxarCvlWVfKs6mWQT+1Ku6HXUkflr2zkb2zEa3dCMvG2qmXNhVSF4K6EIjWHmT8Ea3dpm7SOWTnNPO3lzF9vu5D3UfXArMiUBlDVwvosX4zIYjbz82FSXsT1CHwTX8NfEP/CeugFSkitAatBL6SKC3w7IhICyIt8IUGpVD9o4RavOzk+nWBVq/d53XEfvvtt50S3u23387ee++N4zivuM/+++//upWradw3sR1OP/10LMti7ty5dHd3I2MPy9vf/nb6+vrYaaedWLRoEYcddhg33nhjctzJJ5/Maaedxmmnncaee+7Jbbfdxs0338ycOXMAyOVy3HLLLTz55JMsXLiQc845h0svvfRly3Dcccfh+z6f/vSnk22+73P99ddz5JEvz/c78sgjuf766/F9nyVLlnDaaadx7rnnsvvuu3P00UfT32+8sa7rcvvtt9PT08Nhhx3GnnvuySWXXIJlvfySYyaT4emnn+bII49kl112YdGiRXz+85/nxBNPTK777ne/m0MPPZTu7m5uuOEGpJT8/Oc/p16vs88++3D88cdPkOJs4IQTTuA3v/kNY2NjE7bfcMMNnHDCCS9bHoBTTjmF1tbWCTxCKSXLly/nv/7rv7juuut2eOxLocb6UQ1PViqfUAdEpjWh5YhcB8LLYkuLaugbr7JWqA1Poka3IjvjF3a2A/LtiGwHwktTV0FMy4FwMCAcDBjWNUZ0nYajPoU0nk5HYzk6pt+E1FAI11B0qpil8YL2KWifKooWFYFrE6FRaLAsrG0cVbWCQyshxbpLJu9TKqRocXwKgUshcMlkfSxHIaQ2tJxq0Szn6yjhEhMbHLowNG7UAYGKxqViVWQ4rzE1AUgMOpHOI9wUoYpwERRUHV8IijqgLmDUMh9bG1qOcM0Su8i0GU95/D35eDlEJg9uComgGvmIVNZc13bNPrkOSHlopSGdpqBDREsO0WJWParSeO6HVBXyrfgodDj+AqwLgdWeMffe4JPbnvne8LbGy/pEIVprdMPfZznm46bN/2AoBekWRDrPGCGVyKYS2RSjOliGVlWRAidraDmeE+E5EVorM6Hwq4ayUBg0HPN0nhBlPP+WRVkoZNqBKDBUCL9q6A3x5MrEhcS0HCBEIqRO6k2kWwwvO5U19+WmE1rOWMF8utJVxgKPlB0mE9nk/uJ7FtKBbCulOKahWnITSopI58GyUSNbkO29xotdGkHk2s2EbXgTaniTMYzbuqFSNgbVOmMkkjG0HO3XEI5rJkuWk/SvCEFQgKAAYckUa8AWbLUFOohQNUV7pMhHkI+g06rTrkKiNY8ZOs6ax4z3e90qZM9MM5FyPDPBkxLR3gsdXZBvg2wLZFvM+HA8U87KmJlsRKGZANouwjbl1IXB8RiUKDBjxa8hLBth2WhljGhSZlUgJSzGLChK8wl1xJiqM6Lq6ErFeLOH1ps2cNNJPxVO2pzTy5qy2C60dCaTCEPpMv0Qx0O0TzJGc1xWpIzvJzLniM+jSgG6HqLrITUhKBU8BmJajmtH5JQipRV5EZIXITkRIXq6jeFdK5t6qpfNxHt4I7peMdcpVagJiaU1Fhive9zGOvRNvw98dHnYULIsx1DoPBc8F+Ga+xcpM77Itpoyx/0tqFg4GhyNoQjK2NnguMnYEG6KChZeLsLLhVhCYwnzPGx812CeH1nP0HLEX8lsVOq1+/wPUCqVWLlyZULPbTju1q0zMTyLFy+eQH096aSTWLt2LaeeeipPPfUUy5YtY+nSpRMkqb/4xS9y++23c+mll/L0009z6aWX8rvf/W5CstDXGk1aThPbYZdddtnOi/1q+PJSSs4991zOPffcHe6z7777TuC07+jcmzdvxrbtCYPIdV0GBwd3eO5TTz11Aq/unHPOeVlvORiay09/+tMdnmtbTJo06RUTTnie97Ln2mWXXbjnnnsmbHvpve622268733v4zvf+Q6LFy8G4Ne//jWWZfHBD35wh9fcUeKu2bNnUy6Xd3jcy6ERsKmCuqHirFs1/n3Dkwm9QbR0JrSc4XrJBKwNbDRGS4OW0z2d6MVHzBK0ZWMLC4KA1Dac4JSwKauAQICXC/GGBEVtvwwtJ5xIywki0hg+aVGHZIVEV32sbWg5WQW+MpM0v25hC0WoJSoSjFY9+jqKrB4xhsa8njq1MRshY1pOod/QMtJ58z2G8LLo4U3m5Wi75JwUjnSoRcbQ16UR1ObnEN3TzYsw/RJaju3hSHsCLaeifMYsksmIElABUBo9utkEoipDyxGd0+KdlKHltPWi62Xa3Ty1bWk5I5vMvlEAUQTVKgQBjhDoullK1xhaTkmCrwx1wtByIOWZv11/G1pOJm9oCrVKQsvRDVpOOo8a3kin10KgItqcHLpaMPuM9RvP6Vh/MhHQKsJGINmGllOvG1oOhpbT7tVpDBFdLSaBmVi24ajbXsL5BgzfGNCRQpdG4slGTJFr0GUsG9IthpZjbnV7Wo42vG+tI6SMJwqVcYqQlJo6AteJxuMxosAcUx41f6cjhDSs9kAIbDtCFQcRjfHT3ova8gIqCpC9OxtaTr2M7JhMtHplfM4QOXk3wpX3jdNy3NREWk6jT1aLxhB104RaENXjiZc0baqA4QYtRxFzu03ltrdW8SrROC3Hj2k5lRKqwYVf87T53r8RlXsauft+xpjchpaTlKU4iA7qhtJW2IaWk8qjG3+n8+jymBkrXVPRYjz2IaHluGkcJJ6GjTKmiQmbrHAo621oOVEIwwPosulv1GuoSgnRMw3ROsnU3egWMx7icaiG1iM6ppjVmsJgEqTaiGVQW1cj2noMDS3XYSYNUYCwJcEWM34CAUFoJbQcgLRWWGjat6XldE4yQbSNfuVXE3oW1QIISTRYoCK66NDhOC1HNWg5hqffoOWQHk5WrCZARRMn3FGY0IyiQJKLXvJulWYlsREP1Lh3v2wRBTIx5pUWWDF9ztMCXaogsmny+q9Hy9Gvs8d9R3j44Yc59NBDk78bNsUnP/lJrrnmGjZv3pwY+gAzZ87kN7/5DV/60pe48sormTx5Mt/61rcmOCH3339/fvzjH/OVr3yFJUuWsPPOO3PjjTfy5je/+XW7j6Zx38TfFer1OuvXr2fJkiUcddRRrysn7e8Fl112GTfffHPyd7lcZvny5RMChl9PWH1mZUWVRog2Pm0UckojCUVHDRiVHjW8idF6mbTt0uZlwU0jd9/fBPiVTFCwCdALIZVBl8ewhIQwxEfj9JgXSuZZmw7LxYvAr1iMiYgWEaJV/OKyzX5tOCBNuGcHDsKxkHEAUhsOm4TFXl6NCE0gQG0ZYcDuYNfYU9PSXeOZkXameWWqJZepk8Z4cUsHO7vGtbn1xRZa2quGN2tHWJN2NjzvatEorBAbmNUicuruZvm7Xma0XibjeLjStI9o6UJ09BkFkIZBmspiWM4Y5Rg0VRSWkNha02Nl6IwMPQZgnQM5Dapm6CUNo7jx3TSUbdRzRrcg8l0M1sewpEQH5mUr8l1moqYiCELI5UAp0ljmbwzFKQI8DT12FsqGloMtqNW3CVAfqyI6JpvJROe0CQGBon0K2C56eBOyd2dG/RItTpYRv2g42YDonGZoGG19hrcct0kaScoy5W2RKXAdMkjaopiW47ukrbisXtYEt2plvMCprDHqqsXEyNFhhIeEUCFauow3smHMxUa4bOuFKDS0HMCJKTOJEo9fHfdGRiG6XkomDe2tJq5i03CebrtOqeYaY9SvGm+zVklgbiMwM70NLcdqKChhJjxW3xxUcYho9Qqs6fOMsTuwDjllN1PmofWoZ+5HtLYhsq3I3feHepnoiXux5plYJu3XDOXJyxgvr1Z4QuG1b2MMbYDOSNPZCAVS0G9bSZDqCyOt1IRk7h4HoDY9h5w2F7XleWTfLuhBM97pnWYM3PZuhJdDPfhbo5YTG//WG96V9HfZM9MYp9WC+d5Qh6mXzTnH+k1/6JxmxkrPzISDTr1svOmxWk6NiJSCafH4ibTCFpI+mTXBpD2GAqfUCkTHtmo53Yi2PnOdTJsZD0Prk+Be0TrJ9OdUHpFtQ296HhwXOctQx2TXNHS1MD5BVpFZOUtZOFPN2Mg9omntqDJ7KIdftwhDiwHLxtWaesmo8kRCsMuLzyIWvsMY0pYNhcEksFpk2yAKsKZ1065CisKiIiWiYzKiMeGUlpkQjA0YSmC+E6RlgmPj+C6tDOUkUcspD5uV07j/p1oDRgbiZ6oYX3VDyPFgVSFx4sm21hAqmajlVHyzMlUV2tAshwuAl8Rk/KPikEMOeUVnZiNJ5bY4+OCDJyT0fDl88IMffEWH3WuNpnHfxN8VbrjhBo477jgWLFjAD3/4w791cf4qmDFjBl/4wheSv4866qi/6vUbMpYi12EkDke3mO/VopE77DYBndGGJ/EsB0tILGEZqsSWF6C9d1wRJKjG6jE5I+WGBjvmcRfMC6WofQLsRPGkVVtoIoQcf6AqIEAjpHk5BWhQmih+6PpCkVUkRqODQKQ9ukMSj1O9ZJPVERXfoaWlRqmQotWpM+obI2yntlFUJOKAWmECAR3PGG6FeIUo/luPbDKesfIYmdiIs2Pj3qxSOMaD63hoFRjTs2Ewxi9bF0lVBSigokMCAWG8S35bJ1XD6ExlExoQxB7SKARqhr5geRSC8vhLO64L4eXAsc15HIcqUWJ0Q2DiEwQmQDEOMtM1hSUbdSuM+gyM83O3LVcUmHvya4YvLQSOsMxEblvpyihMvNtYEqRFFZWsrNRlkAQH1qVA2hqlwWmo5YT1xLOohTSTBDcNtjtRLQeF8GzTDg3jSI8vx+vKGMQe4YZhFNZfhoKn1QQ+sfBcCkVjyHakawxUM3R4xsNN6Jv967XxlYRYXaUsIa8E9aqNGhswhiuY8RSPLV0ZRY1sMYaekOjGGMy0QXEEXauaCdWWFxCT54BtJxPopI+GvqG1aEWEQMUOVRWaSVxBikSNCSCvdEJNahUhtrZRm56Dagm16Vnz/+ZnkW0mGL/hiddSmlWbdMYY9nEd6cKgKUsQjxfLMWVufAezyjHWb46p18bHSnxsso9fNcpKUYiHpCQNfQzAEpKS8tFSQxBAuYAe2pCspJl+IJPJFlpt46GW432/YdBaTsyntxG59nEPcWws41cn9ANVCpA5cz91IahVHMNjj+FpjdSa1oZaDgI8z0xwwrq533oZGu0XhWZ1b7RIVWTJaAWKiQHhUsYTp4rpG0Ii0nkiNMhtGvXlKCfxcyeobENTDOumPZUaj6mIURMSJ22ev5YcV8txLVNfDSUyHJsa1nhM0euN/yGdpomJaBr3Tfxd4dhjj+XYY4/9Wxfj/yvoWrxcrBWitdss/yuFaOlEDW8y1BxM4K1nOVhSEunIeA1LI+ClEpUHkWlDjfbHRp+FJyyo1vAQ6Nj4yAuXKDbPbFdhAQJtqBIAfohDCgloP8Qxvll0EOHEnnsBeGh03ShIWBqQglCQvJSiQGLHhr6KBEFoZBbD+Dq2F6FCSRRItBamHmpF4wVr1Ekt5uEXB9HCBIyaCY6F31hCr5cNbSdeghe2ZwyExsvJcUkJo5aTky5KCCwhCTQ48Xs6EJBRIGxhPHBtfbFiy6Ch6IAx9KtFyLWja0VydopKVBs3YouDiM6pxpBQGspVyFdJYaHLMW0Ki7QWlBr2QRAghUC4IqHDeFqDbRk6hW0boyP0E6NBl0eMZrZlo8f6ydlpAh3R4mSNoQemnJZt9m3QL7QihSRoyMQhoFoz8n6ACgVZO0ykMHWtPE4BiKkNDeM91QgXq1RJawddD5MVggYtJ9FRr5cRQEqYFYwIYSaSjfZJDDlpJjMtnrleoUSozHUyVmCOExrdmOw06j2+jpASHVNjHK1QkTQ0pXiCJtJ5ozCjFLKlxyjMRCEi24ra/Jw5p47MiskzK8z4KgxBJo/smzOhT2K7xpBWKjGSw9galrbGRmADJQHaVyjfKOV4cRunnQACoLCNQRn4pv4a/PjNa9HpPIwOGuWZaXPMSkrDuK8ZLrmwPTOB0grctNnemGg6adN/tIJUxpR5eBN0TIZGX3nJvdgxLWcs7heOtGmRHgqNLlcRtYqhWhVGklUronBcRjLTmuR8aKw6AeP692HdBIP3TI8DTWN63Vi/eZYVB03MheUkhmzYb/ax0JRrLlULhAAhNO0qxEKRTZmyhJFEzNh5fMUqCs39NSbqdTMhVyMVNNvkw/BrE2k5oQmC1WHd1JWUZsWqoYCjjEfdSFu64/Kj8ZiJAklaGcrfBEN5W7qLX8XSmrAuCWoWtlT4sVSt3IaWQ2Am4i0yGL+P1xt/I1rOPwqEfrXi40008TpjzZo1zJw5kxUrVrBgwYK/dXF2iGOPPZbR0VF+8YtfvCbnW7p0KTfeeCO33347YAKafd/nW9/61mty/v8OXspwuh1p0+plGKoWsaVFq5dhtF5O9Nw9y2Hd879CjWxBj26m7cAvkffSVIJ6sk/eTWMLG6UjUpbHI1d/kGNPvo+r317m6jvMEvpnTs2iqzWqd6/h/hWTOfQjZVb/XPNMrQWAFZ7m7BNs9MgY//LTDOceb6EGx7jsFy2cdWJsWAwXGLyjxA9Guzn9gC0IKTjvnm6+sudmVq9oB+AZlWPfjgEGhrMUIwcfyYxskWrdlLUc2owK871H1HnryEO4lk3G8RiNKQONv6uhj2vZ5OwUzzx0tfHmx8ZW+36fozvdQn9lDM92SNsu9XCi+s+mGz9PdOddyDk7sfXKVUz61CwKP3sGEbvWvMkWUSFi6WPTuGz0ITzLIYhCFDqp21BFeJaDKx1KQZXVd/wLuGkmHWBWfdK2mXhorTkoP4eyDhhRVX79qQ5O/aG5zrl9Q3gtEVpB9p/34v0XPsMtp87gW1dUOaBuDJmdpo1w9UAv3xl+iBY3y2i9hBSCrGO82IV6Bc926PJaGaiNsu6eK4xhlG9n8oFfAkAKQcb2KPpV3NgYDFTEuhPn8uJPzUt7zgXz+OiSJ7j2PT7lJ2v87vmpzPfGKMftc/DwQ9jSMvr5gCMtIq3IOB5rvrgQgFOvi7jsXQWuuK2Li/rvTWhbAkFn7DEfirnO/d84nEUXr+crXo3Hi+0cXzQyvKm4fhWanlQblbBGJazz7vY9+FjVlH1SumKMNgHvGH2KrJMi0gpnG93vWhSgtGLlnn3USzaPb+nig6P3Ysf85ozjUayb+mhP5dhSHsGRNjk3RSU2mNK2y6R0O21WhgeGnqXNyxJpxcxcL8+MGc69EIK07VL0q8m57+may31RTPvQ8LFFmtFbNyOE5gcbJ9OuBB+auQE7bepyeF0aLx2y/+rNtLk5huoFWpwsY36JVOwNz9sZBmqjdKfa2Fob4Q0ts6gon7o2RvRjw6uxpUXOTTFaK+PZDjknxXCthBOXK+ukKPgVMo5H3smwuTxMd7qF4VoJK15xytgeo/UylpBIIdjy9fdS/MljOOZxQPqzH0K/+AwUSnz0ykGeqm1hpF5kcrqTQmgM97TlUgwrCW2wGvqkbZeMnUom4ZWgbsZmFNDiZmlzstRVwPrSwITxUwnrSZ/TWnNq55uT4P/jOrby2KZu9p69heee78IWihk7jaBCQWnUTLKkpTmn6vCrrStxLTvps3bcV8pBDaU1x/TszWlumVQmwM2E7LzixWSsREqRdTwmpzsZ8McYrZWJtGLg82/gy/9p2ieDZNnwn0nZLkEU0uJmKfhlgniF4rLWN3PEwvWgYP79Q3jSTZ7L5bjexvwKD0zelUeL7XhaM90pI2K5T0vG4/S9dU6/LU8bNp9OjfKewS28OLiC1xv++kdfs3O50+a/Zuf6v4KmWk4Tr4hDDjlkQkT3mjVrEpUQIQSu6zJ79my+9rWvveokVa8HLrroIizL4pJLLnndr3XFFVe8LO/uf4N6vc65557LkiVLkm1nnnkmy5cvZ/Xq1Ts87tFHH8XzvAlcfYCbbrqJVCrFqlWrXnUZsk6KrGMUXYQQ5NwUGp0YEY60cKSFJWWi9oFWxkhx8+ScFFII88F4pYWQE2gaWmlcDe62Es2hURXRoULHajGBMJQc4bkQqxcJx0E4RhVHeK75zZZEoTQJVqQACVkkVsZ45107whdg2YpASTyhUMJ4o5QWKC2QAsLYGJRCk7Zd/ChEYO47bbtEWiEwhmolqBvqQIMjHCsxWEJSCmoJXUcgsKRMxogVUwR0EJoVkW1osCqQqEAibLMxAiMfiuEaN743/raEMXaVViAthO0hEdvt1/jLFTZYhquriJ1hjad+gzb0Ei1sIWP1oUY7xeN62+s0FHKEEImnPFHQgQnPCCEEMjbcsKxE6jLxRMaoS3C9kDjHVjyRsZM+mI6DmW1hoYMAHQSGahMqs3oT9zlLSCwpsYWNLWwsaf4mCHCFUcoJBdvVm0QkBhgQy21qLEzAtZQT62Q8UY3p7437lrbZbmlNxvYIVUSoIiRmbDXaNRlz8fesk0JhqDM5yzMTbDcXq1NpXMs2xmLc5xqGvSWMfGGjjU1ljgc9ughSjaJLJrz12908nnRod/OkLZdWN5eUtxxWqUUB1cinGvjoWJWq8S9tu0n5k+9CkLIcAhURqAgpBDknhR8/BxpjxbXs8XoRIpkMCCGgXJ0oyBKM30tWOHjSIedkKEf1eCJWoxLVKQc18+xBmARBCLRWE64DxnA2al+aaBvvcKJ+BUmfEUKYANP43qWlsbRG2ppAS3y1vQnViB1yLRvPNn04Y3uk448dP0vTSLQGaSukrZM6ADM5Vmgz4cHUjyUkSEGNKP5s79lW6PFnsTbPWN1I/aAjFNrkt0i6g0BaiqoUVGVjbJuAWil10ucDNAEax4nwpLPddV8XqOi1+/x/iCYtp4n/FX73u9+xxx57UK/Xuffeezn++OPp6+vjuOOO+5uUZ/ny5Zx55pksW7aML3/5y6/rtVpbW//ic/i+j+u63HTTTeRyOQ488MDkt56eHt75znfyve99b4dSofPnz2fJkiUsWrSIAw44gM7OTvr7+znppJM4//zzmTdv3qu/H9dIVebdNEPVIj2ZNvJOmuF6iTYva/j1YKg4o5uJRjZizXojGcejxY6zfMbGYCmo0um2EOjIbCsWyAobVQoTA0OXqwjXRqagYBnFm86+ELnGuOrSWqDHCsiOVtLaRxdKiLY8KR2hR+OEQB2tFAohOWE0zlXF6MgHw4q2LhMEmdvYQujLWDlE42lNPbDJeMaTN1jxcGIZRlsqsm6KNi/LUK1Ii2fqpE1YDNWKdKVbyTsZBmtj6NIwenhTksmz4WEbDopYwmK0XkrqFKAa+VAuQi2AYhEVCUilsPOaII47VJUIp9cj8yi0e3nG/DK2tGhzcxTjZFmWkLQ5WTZVh3AsGz20CTonJ96+Tq+FSmi87ylhoYEAhS6UaY2X/4WE6qBtsgFLaYzZOJFVUcce9pqFrQWT0u0M14u0eVkydorhuqn7Fi9Dq5Nl1C/R7ubRA+sQrd3okS3JKkOn18JQvUDeTePGxoCvAnS5RjWI60YpUlhgS4SEXKRZN9JCp1uL69VMGoUQBFFIynaxhGXoPHGAsIWDVhpHQy4O9AQzwUpbsYfT9oxxX6thYRKapZVO6q1hJIcqMoYympTt0opNMbYyJ6dKVGsOYWSM6oZRGOiIVjsVHx/iWS61go3lKMrSIu+mk2zO/ZUxJuc6yTtpRutlWrwMOSfFQLXAjHxPUu7RoMQcr4u07Zrxle3ixdKW5DwtbpahmqnbhhyqFJqW2IYZtUDXfaSlEdJQcRxtaE86NIMwiulo7XaWEJVMahxhJSsZ3XaelOXR5eSxhGRdfYgxv2yyTgNZN0VLvNLXkcrhSIfB2hh5N027NKsmg9UxutKtdHgtDNbHSDsuU9NdDAdFWjH9YLheIu+mE8NfV6oEFQu3K35glIvo0QIincIVkrR0Ca2IbidP3TXXkQg6nBxjYYWRepGM49Hm5qhEtSTOoMNrYcQv4lo2bU7O9CsV4dnx6l2qjf7aKC1uNumvli0pC8XUBlXFNtmUnVZtaFoI7FSECiRj5TjQWGjqVpAE3UdS4cnxINR0vDLSgmXifQJJWNdkHC8pK5iVKk86ONIh45gM0Lpcw2qM5XhC6wgLLPO3ZznJhNUXEFWFSdysFJYlk37b+D9lu0ShJKs0rtbmPMJk2dWNZHLVgBwWRSJKRS8ZV687mrScvwhNWk4TO8Sxxx7LtddeO2Hb6tWrX5Y687a3vY3ddtuNK6+8EgClFF/72te46qqrGBgYYPfdd+eSSy7h3e9+d3LMgw8+yIknnshTTz3FvHnzOOecc/jnf/5nVqxYwfz585kzZw4nnXTSBL3YVatWsddee/Hcc8+x8847A3DXXXfx0Y9+lNWrV7PTTjtxww03TMiSq5Tisssu4+qrr2b9+vVMmjSJE088MZHJ3LBhA6effjq333479Xqd3XffnSuvvHKHMlUvpeWUy2U+85nP8LOf/Yx8Ps/pp5/OLbfcwoIFC/jmN78JmERXxx9/PM8//zw///nPOeKII7j22ms5/PDD2XXXXbnssssmXOPaa69lyZIlEyS3Xoooithvv/2YNWsWP/7xj/mnf/ontm7dyj333LNDzf6XQ7D5qeS7rhZNsFdDY9xNJwGV2q/RutdHEqrK+ud/beTjWnuSB7GulU3CGCeNrhXY/wNXcO9X38i/XjzIF/fZCMCnH8hjC8nBKs8HejdzxUAPh1Uj5kwfAqDtzR6fvSVFXthcekSVk3/h0oLD1w4b48RfmxdoXth8oGpx4IcKfOuWdiSCkz/h88NrXBbGqXD7Jo/x/PpOMlZIT2eJStml5tsUAvNymtk7guWYLJNDA1nm3f81I4FYLZqAYjB/1ytxMqoAXSsy6S1fxJFWYhSue/KnqP7VJglOFKBr5fEgyhh7v/lzHJKaznNRgePCDq5xRnmfbk9+H5WQVfDxt2wkfcGFps5jjf0koNX2TIKl0CSs2mW/z1IOamx68iZT942APCmJbr8RkctBRxcnfekhvvs5MyH92eU+VWk8vDeJQX757bdy7Mn3cdVBRdbda4ytp2stvPvIEdzPn4Uujxit86Ce0JBkS49RDhrZguiayqz9P0/eyVAMKrz48NK4U9VNQqN8l+FCa4VwU3zxkH/lIzXTV862RvjtV/fi/Iu2sFtgcdicDTz/dBcZ10y+5j1y+TifPQ62RCsI6hx3qFmh+/4XOjj/22W+ctgo3le+vk2G2gg1ssmUt30yWA5H7H8WP128M388r59dpgzRd/PlSZ9vBCXr/tVGcSTbSnTLcp7/pjlHPbCpRjY5x2eP/zrLKAcJOSEWQcT6+Ncf/G26QsWe3YNM/e3l2wy0epxHQaHLY8hGMOdL1HpUoR/97CPYhxyDGlhnuPqbn0PGqlZmLFaNOlDMpb7vjRcwb8G4fOuXnu7koChDIODjHxgmGqhyx92TKcfe2TlRjYq2OPD2T6K3rkFOnmOC5+MJK2D+njYXteYxrJkLiJ66DzK5ZIVGzlyQjA+RaTW88kbissYzIx4LulpE14rIrhmowbVGwahxL9ViIkuJUhy5/2Leo9sYi6vk+tpzzPA6SQmb/zh3F5i1G7JzmpHU7IiDf0sjJglUW6+pm4YcrV9LNPaF7Sarbmp0CxRHIJVB9u1izlEcNMdm2ozcZ6wLX7vgrKSsN986ib1zw9xZ7eDQ7BBRIHmy0oajNV3EXHcEb7p0Z+x3ftL02UZwbEMSNd8JjkfwvX/hjqskKa2oCMn7HjprPCBcSHS9YvIcdE01fdjxOH3/C7j4hHiFrFbDPvZU038aajmpfKLeNPixs7h1nYnX+eivP2K4/pZj4mXy7cnYuHOff2WPWf2EdcnGza3IWN8+io37X7kpFp/ooAslHlhmc8BvP05qwft4veGvefg1O5e7096v2bn+r6DpuW9ih7jiiit49tlnmTdvHhdccAHAy2qoP/zwwzzyyCN88pOfnHDsv/3bv/H973+fhQsXsmzZMg4//HCeeOIJ5syZQ7lc5n3vex9vfetbuf7661m9enWSyRbMEumnP/1pli9fPsG4X7ZsGQceeGBi2IPhrB9zzDE4jsMxxxzD0qVLJxj3ixcv5uqrr+byyy/nLW95C5s3b+bpp58GTMKKgw8+mClTpnDzzTfT29vLI488kmTlfTU444wz+MMf/sDPf/5zent7Ofvss/nzn/+8XdzAZZddxpIlS/jKV76SbLvnnnv46Ec/ut0599lnH9avX8/atWuZMWPGy17XsiyuvfZa3vCGN/CRj3yE3/72t6xcufJ/ZNgDJmEKoDY+jR7ajLXXoagNT6IHNiJ3398o4mBeoHkvTbubp8VOo7auRk6aia4WiV74sznZ8BaolNH5VqiUmeN2oZ5fQ07nkTnzuNlZ5mjXkraIJIg2JaPkuyrW6ROt5LVEjQ3TQ442bRGN1Zks2gBo0ZIRS6CKdXJaEAJqqIjQnUkgmJNSVLHocGpUyi5t3RVWrJ3E7BbjLu8fyNPZVsZyFOlUEGtjx5ruDbWP+G8xaabRd/erdKVaSVlO4u3Uw5tMdtNMm0lS41fNOeT4kv0Mt5MUkulWDi9QzJUtdNU16bifFVIWrQrCYYUeXGvyB6QyiHy7+Q4mC6qQJsCxezI5O02n24Ja+5j5XSn08GaTd2DtJkR3O2JklJ11ivB5c46M6sTTAktrFqTaUatWMU2kiUojSUCtqzX158o4QxvGk3dVi4lai1LKqJ0MbwEvRbubp902BpSOZVOJQqOWpBV684vGCPVSzNAuec9ok88TnehNW+hRFn1hSHnIJUJQiiX41MBakzwL0GEd0dqDHhtErXuCScJsV5v6mRq1EGys4I5sGdcVD+vowVgX3kmjhtbTJjz00AhZGRL6Fmq9oa7pSnE8wU//BnRnLwxA+MRqWjtM+zy2qZuZmSLDlbRpn+LIuCJLI9DYcaFSojeIEGgsx0yQ1dB683t5DGvnN6LWrUJvXYt4wztR/avRowNYu5os09HzD8O65yGdNRKZk2YSPf8Q+ukV6Ea233rJBF+ObELXTaBl2oqQjYULCZOEx5QgJEOEGqsTVRRlKRLu+AbhEUiB1TeHcMOzyN6dk/EcPvQrs5PjmrFfGkX1r0b9+SFEeys6VlgSk2aix7YaA7pnJnpovclKLaQJxgajJjR5jskEWy6gY8Up7aTNRBXMvRQHE/pNXji0h5r2eCVihtfJLJmnS9voUgkRB/vz9AMQq3RRGAbbM/1tZItJDhb46M2rTSAvIHpnmLGUbzMqNM89ichkDMUN4oRRY9A1NVEQw7JN9uOUeXa1qoh8Z41dXvSpCJdImQywnhL4epyWFj3+FHL/EWOsS8sk9mrpjPvbmNHSty068CnFkp8mSVscfN1Q2CmOIhoyo5VRJmkbtd7UraqHWJueM+PSTcHYILq1K3G0WJ4yifE0ZixUSyYYulxIJhrRaD85GVAa8Qh8C19JUlaE54QUa7G0qxaozUOosSoWHei1T8JfwbhvquX8ZWga903sEK2trbiuSyaTobfXeFrWrFkDmKQMUkp83ycIAhYtWjQh4dTXv/51zjrrLD784Q8DcOmll/KHP/yBb37zm1x55ZX8x3/8B1EUsWzZMjKZDHvssQcbNmzgM5/5THKOT33qU5x77rk8+OCD7LPPPgRBwPXXXz/By10oFLjpppu47777APjYxz7GAQccwL//+7/T0tJCsVjkiiuu4Nvf/nYy+dh55515y1veAsCPfvQjBgYGeOihh+joMN7a2bNnv+o6KpVKLF26lOuuu453vOMdgPG6T506dbt93/rWt06YqIyOjjI6OsrkyZO323fKlClJfe/IuAfYfffdOeWUU7jkkku49NJL2WWXXV6xvPV6nXp9otqB1BLPc40qi5QmFXznNCMV56agPfayeSbwr7HsK1p7Ek+/7DJBudrx0FGAcIwU3Nboj8jenSiJanK9IXzKwqJHuoZziuG8yzgpjEw7jBEihI3MuhQwfFmZsRkj9swKm7QSyLRDPebp49qGtx/FqiGOIhQiMfbDukVKK2pxwGbaDZCW4dEGgWWyvDZ0srfxvDeMEJHrgNIwpaBCJZQJfUHkO2OPX2xoVEYRnekJdTwQlpjpZhnWPmCzFZ+6SFOLJ2KWNvdgtYjY8xmajJNu2nwHI0foV03ioNYealFAJawhOkz/0X7VtIzjIjrbEO1tiEyGIbEaq8eUrS4FNSGwEGzQZeTUGQzwHFbOThI2RYAz2THtGwXmvrxxVQ+R6zDeyHoFkWmjEJRxpU09MisKpjCG9iMybTBpp7jJPEbEXdR989rZYFcQ7VMpiiJDlk0qH2ANaKPkAhM8wDiuiVfwsohJO1HDJIcT2RQFqbFajKzhuFxnGlpjr3+2Fel4VHWIyKTxVR3LVmZFAswKScNA92umH6TzWDN6CP5ogi0zWuEHFhbalCuWvdR+daLOfXsvJfkQGW1WhEhlE7Uj4eUQbgrROTW5rskZ4CWKN6JrqlGAqZYQLV3JKpJu7xj3QLspdK1oskDH9RNuy/1WMEZITZggctnqYYUqSWwFkFOKqpRG5ca2jYyrNAm5EiM0qEOu3RimuQ5EdweipQ2cuN97mfHxkspCxxQoDcfZeOPJcXkY4WWRHVPQbtpIT/pVUy8NKczK6HidakVZBwRCUI0nIoNhmTbHIxAK0d5uylkrQ2uHmfAC5Nogk0dk203iqXyXuY5fRcReapHvMipe+S6z8jKpF/JtiJZ41SBWxhFeFhHL/5pnoIVwYmoigrAuGRU23VYVkHihUSJqjbndChDtraadQhOPoa36uJSplzV6/56L0j6REERCxFr/cV+S8XGpDFoFyFw7pLJUhEZ2mmeTqNZNNnDbZKrVgGjpNFK4QKzUixZmDGjLNpMGx02eb6Ktl1BLMnmf0Jf0lzMoLeLg8VimVoBszYBSKASiawp/Dfytklj9o6AZUNvE/wo33ngjK1eu5NFHH+XGG2/kl7/8ZcJ1LxQKbNq0iQMOOGDCMQcccABPPWUoIE899RTz588nkxnnJu+3334T9u/r6+O9731vko31V7/6FbVajQ996EPJPj/60Y+YNWsW8+ebaPgFCxYkNJXGder1Om9729te9j5WrlzJwoULE8N+W6xbt45cLpd8Lrroou32eeGFF/B9f0LZOzo62HXXXbfbd++9Jy4NVqvG+EilUtvtm06bh3ylYigme+yxR1KO97znPcl+pVKJG2+8kUwms1023JfDxRdfTGtr64TPJf/6byZQNt9ppCyHNiDbJhmN69IIItOaGHie5RDFSZnQiuiFP6O2vIDs3TlOttJltLvTeXBTVFQA2TQWEPYHhP0BA6rGgK5RF2A5JhjSV1YsLQfYkoIOqKLAtijqkBoK4ViMap9R7VMholVHJrA2vjfh2NjEEwWhKW5N0S3qDFbTtHRUGRnO0J2qMlBPM1BP09pRxUmZo+uBPZ5p1K8a71plzCzPh75Zsg/r44l3MDr3trSNFntYR5eGTRr7KDSGWOPjeIQ6wkVSUD41IRlVdYoWDNnmY7Kaxie2bPPSzrQm38m3mxdyKk4vb3tIIfBVaIwRL2voEtlWQytIe7H8YJph7SNaWxCtJqahKk2G2kFVhZY2Aq1QtcjIgWpBVUqs9kwc8asM9UTKJIA40d4PfHS9jC3tOMDTHtcZb+iPB3VTXs8YzKOEFCKHQuRQVDWwbQKhqUhwskavPeWGpNwwoTjpWtnIQsYrJyLTRoWIChGkUhSEQrZ6Zp9qMaZjjE8mdXkMYbsmWFJK/NhTmtRbKm/K6KaNB9RNmb9zWQZHzWdStsyInzKUIaWM9KtWE3X9AZHKM2oJHK2pFF2TCTW+DlKihjchW3uMnGmc5Ve4adTA2oQWIzomQbkEUUD0wp/NpCXbMkG2kaCOsGzTJ2yPQAvqQ5L6kMQfEWg0Gx3JWlei6yGqougJwzixlWaSU6VH+0TPPgj1mlkxqJSIXnwE0bszondnCH1TVr+GyLUjuidBa7vxfOfbxjOuhv7EsdPIzhxTjvSo0WlvtCNh3VD+GsGOsca9cFwQkpSwGbFgOP6EOmJI1RjQdfTYGFRKZiUg8Mc12/3auJfcTZvkU5aDaOsxk6Bsh5lwZFvNmLRd6JqMaO022+PJSLIak8rGfSFNOFgnGqkRjdQoWJKRoQwbHYmXCvCckI4opF1FtFg+LZZPXoTIaVOSBF+6XkYHVdTgetTgeqgWEbaLGh5jTDh4WpsMtfWy8ag3jquMmlWNoU1mkiekeSY6tvlYJqBeZDtMH863m3uP+3BlyCGl4kR5cW4GHdbN98ZYdjwq2sL2FLZrkqFZQuNHFlZMzwHM8yPt4SMnZIhu4u8XTc99E/8rTJs2LfFw77777rz44ossWbKE8847L9mnoTzQgNY62fZqQz2OP/54Pv7xj3P55ZezfPlyjj766AkTgmXLlvHEE09MyOaqlGLp0qUsWrQoMZJ3hFf6ffLkyaxcuTL5++UmAP+TkJVsNjvh787OToQQjIyMbLfv8PAwAN3d3QD85je/IQiC7cp8xhln4Lou9913H/vttx/XXXfdhBWUl2Lx4sVJOu0Eax541ffQRBNNNNFEE687mrScvwhN476JV4TrukTRfy8lZVkWYRji+z4tLS1MnjyZe++9dwL3/b777mOfffYBYO7cufzwhz+kWq0mxuqf/vSn7c572GGHkc1m+e53v8utt97K3Xffnfz2+OOP8/DDD3PnnXdOMLxHR0c56KCDWLVqFXPmzCGdTvP73/+e448/frvz77XXXvzgBz9geHh4O+Pdtu3/lqIze/ZsHMfhT3/6E9OnTwdgZGSEZ599loMPPvgVj3Vdl7lz5/Lkk0/yzne+c8Jvq1atwnEc9thjD4CXpebccccd/OAHP+Cee+5h/vz5XHTRRZxyyim84x3voK+v72Wv6XkenudN2FarF9B1UFGI7JxKtH4VSilk93SidauSxEQi05YodJSCqvFiD29BO14SoyAnzyF67gGTzMkxMo0ojYMgNIsQOEiKKiAQJolVSgtq2jIqMgBKkxKW8cwqTUpIaih0pMgI88gqE+EIiQ4iBGBrQ9FIbfM+CEMr8TxpJRipe8zsHeGJAePBfkN3QGXIRith1CEK/XGadstwicFoAFmO0XGPqRtZJ40r7URPWpeH0VsM11wLmWTq3DZJkhQSD4ErjPhjWQeUBTRu2dJQkHESq7F+QxmJQpN4p0EfiUITBJhtRQdVo9Md+UnyHj26BdHWO55IKowgisw9NFQyEHgaqgJqymTp1BhOkOeY88hQGwWigbVmGX+s32S39GJlpOKgoRikMujRflrtDKGKyNtpk7SJOMAxlTX0By9rAmphgnhfXUcQhgRoI+MYCDwZEcUUE10tGm8mIIRlPJluGuFlCeL7Ea6NJoBQmWttk2AnoUEASBln2owlIyOR1FuCbfUXlYIgSMriuBGViqTPCdH1EkJYZh8hk+uIdB4cU0c1IU2wdnFwnO6Ra0cNrjX0q56ZJjlc6Bv607qY/y8s5LR5hCvvM57fwU2oVBY5fQ/TBxuw7KRusBwiZDJ+dBDfo4B++fIGUldXmVrFgaGtpl/VKiZ7b7VkElcBbFqLyrbC8ABqywuIOW8wq0ON4OPGeLEc871BVSpsW8547Chl+kNl1IyV7nBCFljdSPhk2ThILA1Dcvy94wqLgqqbZEqjQ6ZOi2NJBmOqVfNdqSS7tkkG1zsuxzu6OabmxEmsWrqMtz9e5VEDaxGZvCmv7jT3GvoIWxAOm7IEAoLQYtTW2DGNMEOEFJCLk1gFoQVtneNJx8Bco1oy5agVwE2hhkuUZIZ8FOJoYShSjf5r2aZNAt/EKpSNs0cD2HFMlR2vpjVie9z0hOyzUSDJqYaOGXFbxXXeOCYyydmiQJikf1IlgbQNOqPUoCtVRDaFw/arVa8bmrScvwhN476JV8ROO+3EAw88wJo1a8jlcokRNzQ0xJYtWwjDkMcff5wrrriCQw89lJYWYzidccYZfPWrX2XnnXdmwYIFLF++nJUrV/If//EfAHzkIx/hnHPO4bjjjuMrX/kKa9as4etf//p217csi2OPPZbFixcze/bsCfSXpUuXss8++0yYQDSw3377sXTpUi6//HLOOusszjzzTFzX5YADDmBgYIAnnniC4447jmOOOYaLLrqII444gosvvpi+vj5WrFjB5MmTt6MJvRxyuRzHHXccZ5xxBp2dnUyaNIlzzjkHuU0w5SvhXe96F/fee++EXAJgAm0PPPDAHa4sFAoFjjvuOE4//XT23dcE45188sncdNNNLFq0iFtuueVVXR9IjA/tVInWrIQwRLtVohcfMXzv+CGrRvuNbriQdLot5iVeKRuKQmxQRs89gDXnzWZSMLyJsbCCyGSoiBF0bHzUdIgjTBbKasGlPdaFrlXiFO+rK7TTSq+28VcP0EaePmVRf7FGG4Y/26ttPFnBX1ejM4Kc0hBF5JQklzYvWa3BkoooEliOwhaawLdMBlYgrAqkpamVLSqRbYL/HBc9shWRjfnzjmsCZus1E5g30o8bk1lbnXgFqUFDCPw4a+sAYuru46THKKSmfCoo/Fhj2kGS1tAwRdMx51772iTI2vycMYaCOjrOXipSWWMEjWyFti5cYZussLExpYO6CYC0bEinEKk0ZOLVopjbrwSEQKVBwJbScIRtwWjF0MNaGpMSKdGDG6Gty2Qh7TeBobR2xcGnG6HDrCx1OjnKKg5IBFMPAxuhpQOZaTNlio2CyjZa8mA07WvSSDVa2xijujwyTvewHNMurd2Q6yBsTBMch4AKIuMaKsM2dBxqZjapLRuR68BCgu8TIbC9aLzeyqNmEhMFUBpFj/RDzzTELrtR1o8AMNkzmW0hnjQUR809+bWEpqCVQnROpSRhMtrci19Dx6pKemN8PbdsxhagLQe9btU22XRLqGfuhzAy6ke1Kro8hn5hFUwxSjbC8Uwfy3cl1JcxYaHC8ZXSLarCXFKktMDaqRfZOkbmgSiZb9ZrNrW6DbVqbBBGSTZVPWbiDAiCpD11eQz92J8Qnjeef2LGbuPjJZ033P3hzYZO1qiT0U2G5mQ56MGNiM4+0Apdr45PFkcHEKmWOI6jTBC3bbs2A8hXIaGOSAnb8P1r1aR/0ogfatBpotBMRLKthga0yYwjwHDGi88hMnkziSkMQyY3wVjV/esh24K0J8fnVKiaxsrE+vca/MgibZlnh4w0btxnLStWDNMC/ezTiPZJSeZu/Br0b4rbP2VoQkpTktDh1CjXXagUx/eX0vTfStn0gZYO8LKGnujFtBg/RI1uNhMayzGTQcdNJHrDUBq6D6BHtprnUyPnRpywTrT2MGJZZKcqokrEC5sdclaABuz4vqZFAjU8RrixiEX3Xy9D7f+n+vSvFZrGfROviNNPP51PfvKTzJ07l2q1miRWevvb3w4Y47uvr4/DDjuMCy+8MDnu5JNPplAocNppp9Hf38/cuXO5+eabmTPHyLnlcjluueUWTjrpJBYuXMjcuXO59NJLOfLII7crw3HHHcdFF13Epz/96WSb7/tcf/31nHXWWdvtD3DkkUdy8cUXc+mll7JkyRJs2+bcc89l06ZN9PX1cdJJJwHGe3777bdz2mmncdhhhxGGIXPnzk0kPV8NLrvsMkqlEocffjj5fJ7TTjuNsbGxV3XsCSecwBve8AbGxsYm6OffcMMNnH/++Ts87pRTTqG1tXXCPlJKli9fzvz58/9bes4ExPrgRr6yDF5q/HsqkwRoEfioWL8+0JHZJ99qAuMaHiEhidatwpo+j8ivkrU8iEI8Pe4YLSufrHSxNESRYERqUiKitSeOQdirk/VPVolEGm9eFxsfq6JkivT8NtY/awy2SKRZr9PssVcna59SuFqgxioEojV5yQaBhWtHVEILJ2NeFA1vVFxUgpqFZWk6UrHxbjnGMGlopluO4efaLsJLo2sVAmXqIEnm4qbjY+3xT+NYUxJsYeEiqCo/SdQF4/a/AioCRErGHs6iWf1w0xMNVss2L3DLoRTV8NW4B9SUbxs1K8eBKGRY1xAtxhsbiCoS8DRmomHZSRnysedxYy2FLseyjW7KGEdCjveTVNbw7T0P0jlqKqCuQmqRnxhsYNRjhJc29acVuGlGdJ1MbLTVVQBSmuQ42qh7FAKXNlFP+iO5uHRSGu9nXM/1bYx7Uy8WOF4SpImK0LGntBHgWdYBpFK4lE2wa6Pe3LQJYLTseOXFTozThtkn4jaz3cjUS8pM5LDt8RUaNwXSoiw0CpMoDTdl+PbEAapSmnHDmPktbt8JQbmN+3XTkM2b/tCo90YfaPRPNw1BnS7GMyJrDb0yQ0VrBBA+v4mwP0DQneyjIoFSAvItxoDM5aFaNZPBRv/NmbgZPM+U86U0CS9lgoHd1PjYsYvj38H0VS8OWHbcZKwk/aJRbzHfXmAmviVJEktjCUlB1WmRnpmEeJ4pW60K6bhO/Bqkc+ZcUWDGa4qJ4yGVSX4jlTHGbuCPBzO7abRbi1dgPGNcummsjEwGalGCS0RdaFQkCEOLIW3uI1UzvcWPTO4Isq2IhvfZr6LjyabI5E0ArNIEcTbYQAtTL9vWr+Ohh7ZCJotIZRFumqIOIRcHVitt+k0UPwNC16w2xPcThZJACFOPqcw4Vz4Mx7/bLiWL5P7a3Rp+ZGFLlejcP+GEWDtNRjj9FO+xzcS2ib97NI37Jl4Ru+yyC/fff/+Eba+GZy6l5Nxzz+Xcc8/d4T777rvvBE77js69efNmbNueYKy6rsvg4OAOz33qqadO4Jafc845ia79SzFjxgx++tOf7vBcL8VLs9Pmcjl++MMf8sMf/jDZ9utf/3rCPg2VoZdit912433vex/f+c53WLx4cXKsZVl88IMf3GEZGkHGL8Xs2bNfVq70lZB4W2PNbl0pJi8MXR5LAueEsEhZHpaQJkdlrWA89+Xx5WTheOjhTUR+FWv2m8hIF10q42mRrLK2Wuk4xyXYtiKtBSM4SWZHXa7RJrImAVPVp02kiQBdqtMmzEQjQNGiInSxSlqnSWmBcC08pSlX45etG+IHFmmt8Es2Kp5gJAG4lkYrk6FRazHR61zeZnImpfH0+SYANGubZDNJdstaGcaG0dskUdLlbSghQpKVHjaCFitF2tdIy5TDirt7ElAbavTogPGuNbx3DVpBOpe8WLVfpcWKDcKGd7U0YoyVVAZ8E/hJtUqnSKGHTHkcbZbZJZCWDtQqWEi00th2vKqgtQmwHRswXtby2HgQXqO/1GLt/2qJfJzILGW548ZUrWICT8tjxqCL66FNuGSEuU5aulCr4WGColUgaPfq1MPY010rjHtVRVwXtocuDZNpvLqqNRwEutoI0mx4T6Nxz321CI5HSlhQ95EYmhbFkaQuk3auV8zKVWEIKmXapDGaK0WXjFaEvmXusaG5H4bmmPh4XRqmQ5mAVseNzLVjqdmkX22rfR7Gqz2FuL/51XgVKDC65JWy6Q/p9HifjGU7dWXMTBZsb0KSYSHAQ5LVgorQSQbisrapxTNsx4kIQ8sE7ga+Wcp5iYqWHhtFpLNQLqELQwjHAddLJlRGQrQcq+zsYOw0nidaxVSTeKzY7jg1JK43pBUH1EpaIhiMf85YHq1WylD8gsAY9Y5rJiWxBxptVu60m4rlUC1TP/UauiU+UbUYU38cI505NgKdk4zuO5g2b/Tv1KCZBEQhIiWJCqYfZjSkvQAZjSd5qsR16jqxA0Fq1PAYsjpOy9F+NekHul6FyiiEJsEYgBQYec5tsseaQOE6OI7pc84YKSGT7MM6CMa1/C0bKiV0KmPODaQyAZRiuz0KTTs3cjM0qFWVMTIKVE2jfIiUyXa8rfpSDgs9PAZSkNfb9PfXG01azl+EZhKrJv5uUa/XWb9+PYsWLaKvry+h9PxfwCGHHDIhidUrYe3atdx888184QtfAOAnP/kJM2bM2GESrdca+005FIBAhTjSRiKoK+NtbmTsBPCExa1XvjPmfhc44Mv3MsftYmtUMqo4mEyRY2GFrOWRkS6/f/RqJu/8HtZ965+47hyjO/6JS0z8QOWGe3no4T7eMG8zxa0pBoaNR2qTSvHWt23B3xJx15NTecdBm6hv1dz/9GQOfZfhwgdbQp55tJutuOw9dSu1ssO3q6181i2yfsx4qVusgLqymNo9xn1DPbypZYinR9t54wyjYf27DZPxtGaqqtPXUeSEgiLSihYrRVmZF2ioFa1WCoUm0poW6XLdZW80xkTRGDHvOe8xJlk5BqMKgY5osVKsrg8m2SYtIXno4e8T3bYcXI+R7/2J9pP2pfrz+xIXflAAKwW/fHwa1+jNuMLC14YIYsXGQ6QVjrDISJeiqnHr+Qsgk+Wg0/4AYFZDkAghmG7lKeuQovb56Rk7cdzXDSXgitnGoHV7LbwPHMI7v3QXvz15Otd8O+AQ1/xmOYqfVzu5I+qn3UoxquporWm1zORlLKphCUmXTDOkavziwgXo4WFELssHzn8SMBmBW6THWFRjICwSaYUlJH/60m7032D6waRzD+WkU//Mv7+rRNhf4877pzDTLSc6918SW5P+qNC0yRQl5bPVH+PRbxrFqPd/+UFu/vxkTv9umVXBUFJXADlpPJgV5bM1KPDQvx7CkUse43s9dR7eMImLpSlHWjhEaBwhSQuHtHTYGpZIS4drp5p+fce6ybxnzgbuf3oy33GGSQsbBThiPOtngGJ1bZA/vbeF4UcET27p4hK7n7qODUPpUNdRMs5M/4pICSfx2Po6whEWezqdPOL3M8NpY0TV6JQpNobjxmLO8lhdG8QSEktIfrenw32PG4lCRysOvWZ//J/cjEw7fOk3WTpw+Iguk/JMWV4YayVNxA9SARlhUdYhWWFT1KHhtgO9VoaNUZmpVo4NUYlJMkOUTMuhf5v+Xohq8Zgb/974u6qCpP1GVY0eK8uQqib11iI91vkjKDSOsLj77D2p/dcT2D2mv3mnfxX14K2gFced8yRZYVPWIRlhlLSAuOwBW8ISGelSUb5ZBRAWUTzIIq3xpE1VBaSlgysstNaU4rHuSZu8cClqn/6gQKQVAsHp9uwkNuYDe66nsMGjc0HEbb/rxQKmxjK/taiR5VdzQ8risWAwoRh5wmKSZRwTW6MSA0GRk9w5fPLd/TxwczstVsDZspQ8a8GM++lWngjNhrDISFTh3lPmcPJ3TT/IYPF4OByrl4Ed94UtvnkuXedOwnUiLEvx5br5TWuNJQRRbPa96A/xX290+M/HppFSME+U0NrQ4xrxJt3dJW4ankR3BG/KDPPRUoFHNt/L6436E79/zc7l7fHyann/yGga90383eKaa67huOOOY8GCBdx8882J9vv/BfxPjPu/NSrfPNF8yWSM9y6KzPcgMJ5Je9xL+ql/N6slWWHz7S9PQT2/BtnbDdnYO6s0IpMxnudSmRlfvZNNL9zKbrt9kBVHGlrASbdlsBAcoDIcnBrmkXIHfZFPT9Z4hLpnFLn2xWm0RvBPu67nuuem0arg8NkbWL7aaIS3KdjF95k3byu/f2oqCsG7F67nnj9PYaptztOSr7F1JIcjFW25GsWyh2NHDNeM0TC9cwwnFVEYSTNQSbPv2R2GN1woIjLx/bgOetQEiQrHQY8V+OR1NSwk2Ti499un9aCHRhAtOfA8dKGInD593PMURUz7ws84oG0XMsLmSD/LL90qbwszidHQEmmGbME/77Ke3BF7mDZoqE1t+4hWCl2tI7JpTv7mEDWtuOrL8bio+zFvOkJtHgTPQWTTnPEDn8s+bQzm//y+wNOaTbbgYVFi6TkzOf2ijVyw61aeedS0T1nb7L3/ZlKH7I4ulkxdWBa6GNNccllTjtEioiXHif8+TE4Yqsy3T+lMiqpLZUQmjejpMR5DrTj7Ky/wjthRvixV4drj8ly5VNAZwdt7trBhUxtZzxhbuyyeCbVaLNnnoEfGzPl6J3HWV54H4OJP23xlWcR5hw7ivGGXpI6QEj1WSMoruro44ZynuOqzrfzkWwHvm7eezBF7mf39IOYiR+hCCcIIMakLXSjywDdNYWd0j7FqsJNd8qPM+MwUdN1HSIkOgm0y1NqIqdNYeuYLTA4Ue0/dStfH5xgaCUAlTmzWGGdgfqtWwffHx2AQED7+Ivbeu6FeWIec1InqH0HOmpqMMV0oIqdNTdp7xdkvMHXKKAC1ssO3qq0sDB2qAo7ebT1BWbLyhUmJ535Oukg9sNj1gxEyn0aXa4hcxgROtht6oB4tIrvaUKMFZEcr0cYBhC2T+5V9Xaa/jxYQbS0gxfj3Rh8YLRiPv2Ojx4qI1rxpx/bWce/xWMHcC0AYcukFm5kTCEbi0IyrgxfZ0+vFEoIr/zlAZFOmDsII4ZoxqMMIkU6Z89Z98NykbpIVAscx9e44UPdN20FCWTMxBlVE2kN0dSXyr2M/uD+hFN79zBSmUOMxO80h6WG0hs2FHBJN2jJe91BJ9vxAEXv3ncb7YrWGHjCTZzm9D9HRQfmG+/jto9PYSdWoaYv9zm6fkPiOKEKt2wyeg+ztRrS0cNr5a/jXD8bZf0t1rN1ioQUh4rgJjeidBMDqr65kTSmPRnDIKS4TlndiyGlT+PHi9bx/r/VENXjh6S6cOKi2IUbwFFnev/8GwlHNQ4/1cchXOsh84Tvbneu1RtO4/8vQNO7/RlizZg0zZ85kxYoV22UybWLHEELw85//nCOOOOLv4jwvxTPPPMPBBx/Mc889Rz6f51e/+hVLlizhz3/+86sOsv1r47wZ4xlyUwhqsfcohcBHJ15FD8FJb9+KVhpVCrniwSnktKAkNI0QSQdDBfA0eFrwuX+ZyrzTbufpp3/KQfOPA+DWt0BUUgRFwQPPTmbP7kFKRY8wTj5V8F126hvFr1tsGG5hZu8Ift1m80iOnfpGAfDrFoViikLg0pWuYluKJypt7NU6TLlsaDkjforudIWq7xAqiSWNhnMjaLMaOIxqhy6rTntrhRsrxjBt3FMDOS2ox5WQVfDJwwbQfoSKl+q/8/AUUlrgCwjRtGjBwDaBoRLB4q/vDm1d+Nf+J2NPQW5KSHG9g5DmOkHNJooET4508LgnSGtheL1xvQMEcbu0KkFRwmf23YhISa6406jpWHH9K6AzMslnNPDh3dbzn0+bJGPvm7SZ8phH96wyVk7wvYen8pn9N/KLu6ewT8oYH2EkecJvYY0jyCujiQ+Qi2+pKE0QbHsEIxactO9GwoLCygmuftAYaSquq5KEOppQaGwt+MysDRS3mslV13yf5X+cwkd2Xk91xOXpzZ1M8qqM1U373ZlyaUQtqPjeIjR1AV/cw3jdr3t8Gp/abyM/vm8KQ9LUVyNWOBPTJnwBZaE48x2DXHl7D8dO28gv106hP657J14ZsGIlIQmUhKZVCfbHeElroU3GDagFNvfamYROISDpGxIYkopFXVsZG8qwpppjhSeT+IoMgkrchpl4nKmXbLcwGUHbFWy0NBltssp2RbDeNvvYGrJaMCwVFgKp4Sh7lHUlY6SmiFjw9iGGHnUQQvOHkR48BW/MDiNjHli57GJbittVK5lYPUliqGKNuNwWZRSccsq0eddL4hu3WMaHn9WCsjDPiRYtGBF6PI5DC2rx+doVDElNSgtGpImTIT5+JB4vthZ8bpcNDK/P4KXM+Op6Twv+04OoGvx+5VTWuqadHD2eG0JqU+6S0KS1oBqP34wW1OLv6iV/tyhBVY6PK4lI6qIiNAqNRPD2ms9YTAPbtX2ESsWlta3Ki1s6EGjavTpakySBk0LzqMqzyTbHh2g8BOm4I4xIjS80u/uSvVuGqFRMW/xCtYzH4AMugvbIBJuPCXPMl/bcyK1/NmPZ0Zq1rhiPTYjroRD363fXa7Sk60ih+b3fjhXXgc14LMmg1HwsO8jzQ+04aHoyFSp1B8eKkvtJuSGrK3lSWtGdqvKfIseFa37E6436qjtes3N5897xmp3r/wqaxv02eKm3tWGAN+A4DtOnT+fYY4/lnHPO2U7H/X+Cv8S4v+iii1iyZAkXXnhhkjjq/xf8T43y8847j1/84hfbcfu3bNlCe3v7drKQfyk++MEPMn/+fJYsWZJse8Mb3sCpp57Kxz72sZc9plQqMX/+fD7wgQ/wjW98I9m+Zs0a9tprL77xjW9sJ+M5ODjIvHnzOPnkkzn77LMn/HbUUUexevVq7r///gn6/zvC2CeNVyMaDYkq4E51CAcDVA2cHouoEEs++nDtU9NwNaQ0fHC/DchcTC/oN16wsAI6Eg1HLb98cSrHvHeAd/3K5+5HlwLw63lfIasjisLiwD03cvsT09jDKRgJOcwy8MNbe5Bas3DSAA/39yCAvSf18/BWk01Sao2nNXN7B3l+SwdlYbGTV2JF2EJfnNF1l55hnu/vYGquyGglRWdrhY0jebozxhtbrLm0ZQyFYLSSYvf9h9ChJqqA3RLz/7f5W/kaVYMbn56WBKUC/NMb16NqYOXMPlHFUGxEI0Okggse7+P2yossdnYho3RyD90Yj21Z20zyqqRTAT17lAlGBE6rsTRD44DGzoEOoTZs4bVF/GTVNCLgIwuMio2QEFVApqC43sVyjDXx2Loe5vaaFZcXt3TQ7tbYGGSoC8n+Mzdx15rJHDp7I5vXGI9txXeY0jtGbpJPbdQi3RWhQ6gXTPukuiJUDSpDDrm+gJtXTqM1UgzZkg/sasoibQjKEq9ToWpxwtoU3PvQFKa7hpf/eJTnrVM3cef6yewmS7S1VBkczZL1TF+atk8J3fA2KhNsrH2FP6h59Ekj9Tqrc4RnhjrYo2+Qlpn+BK1NFbNDZBwK8R+PTOOYeet5ZkU33e0lOmdXk37daCcVghXHGvY/n0smnIPVNFM7CmwazrP73H6CipX0ca8l9thWJU5e8eAjfeyUK1Kseux68AiqppLyOL1mbEUVcHskqmLqx5lspjHBloCgKJGOwu0SyJxNNBxQG5CkusdvTtVAZsbLDlDeGnuxlWDVxm7aRIBnm7EQKskLZBLSh6M1oRC8//0DDN6n6dpHU1gVkZ8rCQdN/UcV0+ca1672W0hLJwtS6SkaHZoxIVOmLGEF3A6BDvX4OdoEUUFTL1ikeyNUBewOifYb+xg1Gq2MZNSVK6fy5tr4TOJZ16Y71OSUYveeIdKtAU5eURu2SLU16l4gHY2dMxQ3p80c6w/F4wgzHoMRgdNurlMbkLitanyc+uY8Tl6jxxNhs/GJFtq7zWrg0+u6aHfqlAKHVGwAjygXwfiEBmDeTv1kpyvTb22BqimEa54pQgqiiqnEgWeyPFzqQAl43z7rk/YULqgKRHWB5WmsFhPRffcfJzMna2g3Sgt6ZhZNJloJUc08AxqrDJufa+GpegtKwME7bTLiAY4iqFl4WXODbqti9WMdlENTCZbQpO0QrUVi3G9WKd4wdStaCYqjKaYsLNF+05283qg/9tvX7FzeXu96zc71fwXNgNpXgd/97nfsscce1Ot17r33Xo4//nj6+vo47rjj/iblWb58OWeeeSbLli37P2fcB0GA01C4eBXbXy/09va+5ufcsGEDN99883ZUnE996lP8+7//+w6N+1wux/Lly3nb297GP/3TP3HggQeiteZTn/oUBxxwwMvq83d1dXHVVVfxoQ99iPe///3sueeeAPz0pz/llltu4ZFHHnlVhj3A5+40Rt2orpMWNt6zFsO6RkrYZJ61KcZvnLxwuerUWPmjXOVj38+zs8wxhM9AbEk5SGo6pKx8Wq00P7lkBsedU+bWt/j8et5XAHjvqq8R3nEt5WvuZMXKXt46ZyPFIY+nRkyegV+Mpjn78xbRmi1ceEcX556oCFf3c9ldkzj7FGN5Ras3M/BHxVVj3Sw+YohwS43vrpzKe+0CG0NTxtbpdVYWbPZ9e8iy37qcvesgt6zo5ISDTODc5Xe2sHslRbuKaLV8Tv1zJwrIY1OOfVuNvxvc2SwWX/u8gw4jqBjj8PP/0UUvHltiDZcsFs9HhYRT7AqLn104kwv+MEj6gjMIlv8rcsY06rc9kBg45Q2S7HTFz+6fyq2P2OSFQ0VHKHSi7W84+II24VDYFPL9kyTCc/not1qS62SERag1GWGhgFHtc903d+EjZxlKzdULtlDa6jJz5zFSnziM931ugF9+ssYvr53KzhgDpq+7wO8HJ3HvaJV2HEa3hkRoOmI/+thmUzfdOAwNB1xxokYNFpBtOb54naH2RGjacBjbEPJcMIIVO0JuvXQ6W77xZwA+dN5+nP2lkAuOGMJfW+GeP09hdmZ8kvep+3PY23DoO4TLqA5YHYxw13cNpeZ9J9/JzSdqzr6uk8KKIIlzAMNJBqgQsS4qcvM5nXz0ojG+3lXkxYE2znrU3I8dB4g7SFLCIovNFl1lJKrxs7cZ4/GWO1s4aVaV+wpd/MfqHjJYhqePINiqk3t+LBjkt5+os+XXIbrq8fn72qnEfSmDDU/CkKqSlQ7u8xZFHZARNu7T8SRCVclJlz3J8cSLZaaJNAP4dOIwsskY3XWtaBUOL0ZF6jrAFTb/ZjsJe6vqOxz8aR9r9kzU+o38cKlFHuiJAlosc47nRIa8Unzttx3ktaT4e0VOSwpbFRu16dc7iwxrdI3ZpHlhY5VuMTEz6cgmU98ZLIqEKK1pFw5jq813gFbhmHwVQCs2Y5tDJuGyFT/h7uexWa3KSRv88KiGHrwp64H7LkTu/U7Uiv/iq4ufJV+QVGIPfWGrGWOtWjImFOt1lXzMyQ/jsdOQnw1QtAiX8uoQCeSEQ7hJUYt/TwubXHwvLwSjiXDAKWEesd6sirz1Q6MUH6nSemgXv12aIqMV0zMlLKnYXDKc+pSI+MGWPp7dUsEIrwpsBH3CzDIHtM+GqMgXw27esUjx3FURrYScvmJczUijsZFMwkEi2ECdIVXjhi/nOe2bcZwBFlufd6kSIhBIBClhsToYBeDGmSX8NUYx7JJNPVjxqp4FhGOm7p9ZX+A/31dh+a3dZBQsxNS9bSn8eBy+7YhhTr2tg520yz+7I5zx5y5+QBN/7/j75An8DXDsscdy1113ccUVVyCEmOCV7+zspLe3lxkzZvDRj36U/fffn0ceeST5XSnFBRdcwNSpU/E8jwULFnDbbbdNOP+DDz7IwoULSaVS7L333qxYsSL5TWvN7Nmzt9N5X7VqFVJKXnjhhWTbXXfdRbVa5YILLqBcLk9I6tQoy6WXXsrs2bPxPI/p06dPkKjcsGEDH/7wh+no6CCbzbL33nvzwAOvnKF02bJl7LHHHnieR19fH5///OeT39atW8cHPvABcrkcLS0tHHXUUWzdujX5/bzzzmPBggUsW7aMWbNm4Xlekqn2e9/7Hh/4wAfIZrN87WtfA+CWW27hjW98I6lUilmzZnH++ecThjtOmnHWWWexyy67kMlkmDVrFkuWLEkyuV5zzTWcf/75PProo0mbNpRuhBD84he/SM7z+OOP89a3vpV0Ok1nZyeLFi2iVColvx977LEcccQRfP3rX6evr4/Ozk4+97nPJdcCEwg7f/58pk6dOqGMhx9+OA8++CAvvvjiDu/joIMO4gtf+AKf+tSnKJfLXHHFFaxcuZIf/GDHj9HDDz+cj3zkI3ziE58gCAIGBgb47Gc/y8UXX8zuu+++w+NeilSsUJESFlUdkhYWGWECz1JxOviUsIlQhjtarSFcG1tI2rUkhUVKmE9Fh1hCkpVu8vK2EEQlRVZHZHVEeMe12O/4JJnDdmdrLJmntUCikWiT0GW0iEi7eEh0oYzMunja6C2r4TFEzqNc8shoQTRYBwkB5qWUJiJNRHXQoieEYFONXmVhdTiMSoVszyDbM4yJCE9rQsxSehqLFBIHQRqLNBZu/HceGw9JGsOfpVZD+yHaD0lhkdMi2d+k7hJJsKMQArRGVyKi/7qB0h82YL3to7hv3gVnRgvOjBa0EomhnxWmTiSQEUaqUgIifnlLBI4Q6FIZHQTYQmLH7dcwbj1M0iYPC/w6rrBwhUXkg5OOYi+pMmVTmrRSqNhbZ3sRBUlyz3lsWrFJIUkhyWHRio2DoA0HXayg6wGqUCaLTRabPDZubPi5wsKOP7pSRog4nCAKEYCuh6b9hJFn9EMLPzTHpTAfD4tM3M88YZt4kCAw5Y9516m4/RofB4ETl8FCQq2GLaRRR0Ik9eYgcbGwkVjxMW5cbu0rtK+MUos0lJgMFh6CDDK+R0km7hsmsVqIkMazmhUWGWwy2ChMQra0dCgqE8iaETY1HSbjJyVsxlSdFAIXM77y2BSJkj6ZF3YcLCpxhW2MRzuiVHcp1V2yKRMPED2/GrnrLgQY+kpKRLi2+QzYMGxJ2rXpu61a0qoF7VqSFjZpYdOuJC3CJq8FeWEzoH1GCBglZJSQbNwHUkgymImlQJCNv2eEhRXXvxebGikkOS3IMd62LhIbgYVIJoHRQAnZnkO2G4NZ/fl3yDe+gxBNuzLlzcblbdeSTHwPWWGSYDX6zrbICgcZP49cYRGiCLVO6j4XlyWPTVq6OMLCEw4prcjpiJyO0NUAaWuQgroUVISkXHco11xqSPPRFoEwE+wUtrlHYdGizSclrLjdjOKNozUW2vTvuO+m4zpztaBVmTp0hDRxLBAnhNN4QmLF9ScBF0lKOqSkQxSIxAOfivtqCoG37RgRElUK8LTp2zAuF6zjj6oGtGNTEdrkBfkrqdhoHb1mn/8f0fTcx7jiiit49tlnmTdvHhdccAHAy0oKPvzwwzzyyCN88pOfnHDsv/3bv/H973+fhQsXsmzZMg4//HCeeOIJ5syZQ7lc5n3vex9vfetbuf7661m9ejVf/OIXk+OFEHz6059m+fLlnH766cn2ZcuWceCBB7Lzzjsn25YuXcoxxxyD4zgcc8wxLF26dEISp8WLF3P11Vdz+eWX85a3vIXNmzfz9NNPA4b+cfDBBzNlyhRuvvlment7eeSRR5LEVC+H7373u5x66qlccsklvOc972FsbIw//vGPgJmUHHHEEWSzWe666y7CMOSzn/0sRx99NHfeeWdyjueff56f/OQn3HTTTVjW+AP3q1/9KhdffDGXX345lmXx29/+lo997GN861vf4sADD+SFF15g0aJFyb4vh3w+zzXXXMPkyZN5/PHHOeGEE8jn85x55pkcffTRrFq1ittuu43f/e53ABO05BuoVCq8+93vZt999+Whhx6iv7+f448/ns9//vMTZC//8Ic/0NfXxx/+8Aeef/55jj76aBYsWMAJJ5wAwN13383ee++93flnzJhBT08P99xzD7NmzdphXV900UXceuutfOxjH+O3v/0tV1111X8bRHzFFVew55578i//8i889dRTzJs3b0LfejXYOzIeJUWKuoBMCIHwCAR40cSsotW716BDswx/sJpGWwQ90qUee/UCYegqljYvhsoN93KAmkZQHKYYJy8qX3Mnmf6tOB89kysuPZYDih71mk1r7OFcUHcYvdssPb+h1sLIPWWE1OxZ14zeOZqUJQjz7BloBp5M4bgRC+satz2kO/Y89m/KMyeqsfmJPPPrAQMPWLy5phm+2/y+f72FTupoIbAtxV6RixO/4BpcXit+6SkBUlsoAbWH1hNWxukbC8JptChNl3QTus5O1nhgqdRQ/dn9VPstop/cj1+yie78MWLufIJ7ngGgXvYoPekxLQjZn3RSBkdDvDpOGJ/b1uALh9IfN2BnBzlYGQ6up03GWwW0RuPfR69+gPcHph9Vhsv0D+SZJkbQP7iVI5hG7bH1BGIqqZjCUSl4TA407dLB05q6sNGAG9eNH+uRp5WmLiXF+0cJ6xInXWdhEAdjYspelxa7CkOlUgLG/mMVtYq5v8q1d7BnMI3qCwGjWzJ0qJBS3U0C+Q5UueQFpeL7C7F5g5Wm8F2jEHSMnkrp9+t5kz+NckNZkXFucePYObIT//5neXc0hcCvs9G2OVgZb2yjji0d1yFQlzYZlWXzw8MAvLnms/mJPNNVnTDw8LTRspdogtgglRpm2L0M372FQiFLVdm8IXQmtJ/hO5txlo1tjgBww0bdevgCZtYVOSdDSwS90mFb94bEtO3uuEm9lqulRJqxUPUYvn2YoGaR+eNdzPL7cNDkvAA7zgGxsFLHERpXp3C1xhfmXjoRdMaqSL2Bos12aY00bZYZ4xLYJhwlmXgGwsJTpiyBGJd4bcRANJ4JJUk8VsZXabWAGcTPZQ2F+zZSLbj49xnnSvese4l8SN/5APvVu/EFtEWQUyqp+zh3Kz1WKqkfEbdro+68bcZ2Y5w3AtoBUqoRd2AxR46P3xZZTbK2brnPwq97BLcNMUUZzn0j2VO7NCucltDsGjhMF6mk7YU2MSgAfdJjnvRwdMjGn1focjxsSzE/bJnwrJVAJt6Qkw67CYfqPes5uG6cR47WjNgpAjHeJp6GvWKVqP5NRRw7QgrNfN/C1holGs8PM1imW+1sflCzm19HCvDSEfXAAk0yDodXSvapSzQwWMuyr5Pir4KmFOZfhCbnfhvsiHOfTqeRUuL7PkEQsGjRIr7//e8nx02ZMoXPfe5zE7jP++yzD29605u48sorueqqq1i8eDHr168nkzFZLb/3ve/xmc98JuHcb968mWnTpnHfffexzz77EAQBU6ZM4bLLLksmEoVCgb6+Pu677z7mz5/PypUrOeCAA9i8eTMtLS0Ui0W6u7v59re//bJUjquuuorTTz+dNWvW0NHR8arqZMqUKXzqU59KPOvb4o477uA973kPq1evZto0Y2A8+eST7LHHHjz44IO86U1v4rzzzuOiiy5i48aNdHePLzsKITjllFO4/PLLk20HHXQQ73nPexK9d4Drr7+eM888k02bNiXHvRLn/rLLLuPGG2/k4YcfBnbMud/2PFdffTVnnXUW69evJ5s1lI7f/OY3vP/972fTpk1MmjSJY489ljvvvJMXXnghmaAcddRRSCn58Y9/DMCCBQs48sgjJ/DtG3jD/2PvvMPsqsr9/1m7nX7O9MlMMiQkAdJJpEtXpCtNVECEC4iogAgoFxQFG4IK0lRECJcOShWkN+kIEggkQCBtMpneTt91/f5Y++yZIUG5V/SWX97nmWfO2XudtVff73rX9/2+H/sYBx100AduUmry0EMPse+++7Lffvvxpz/96W+mrcnjjz/O3nvvTSqV4vXXX2fq1Kkf6nc1WfMxFZBMBoJEnUs1r9SiWNrDKY9txgwr4JWVk5TTlq6xy+QefFdTkWBDfLdhBVTyFr4vMIyAd/oamJrN806hjo/P7wJgyeuT6NVNLmUtz71+HX+c910miTGObVMLcHydgjRoNGzcQKMYmOR0ByekZytJg+kNIwyPJrEMH8fTaW0psLq7Dj+0EuoEtGZLrMtnmNowymsjjewyYz1/Wq0U3YO37mTVa/XELY+BUoKpk0awKyaG4Uf1cWwDXQvQdInr6hhGwLKBBpIyoBo+Z1bzEOWSRSpt43kaUgqs2MTTptd6mylqGukgoKhpLLV87im/y2VCbdyLQmPLZJ4gEGRyVRX9Upd4jhaVRdMlvqsRhBrJip5GykJjm46QHrSqY8Z9NEMy2pdANwN8V6OnmIr8DIYrcSY35VnZX4eDxqzmIZYNNLBoai/93UrZrWHuKyUzjAMgJxD2hAcRUVyCvmISXUiqUmdKtjAhjaZLDCNABmpsvNXdSKOh+rrLT7BVZoTXi/VMFRVSMRfD8MmXlPLQPnkcXzogtDBwkK3zVp9av7ZsHOadwXrmTh7Ac0J+/ICwzCL6rpsBjw+2sv+0LnrWZhFC0tiijDfBOA1PBiqaceAL+vvS5F2lQDcnK5RtE8vwicdcfH/s0Nu0QtiHo5NMOSztb2LLzAhDhSSTJ41G+VtJj8AXyEAQz7lUhi0CXxDPuHiOFvWxmfQZ7UkQS3hRGyfqHYr9ql18X6AJiWEFSKnaengoiRnGKWieWuC1ZW3oSKpobJ7O4wca/eVEFGXXReALwfxJA4wMJ6hvLFMYiZPO2sTSauz2dmaobywz2J+ivqFMdoqD9MAPceHlIQvXUXMCVIRp3QwwTR/HNqK2EUJSKsYQQpJMOZSKMdLZKr4bcu7H/ahdhCZ5qa8FU0pGdXW/yffRJAwaOtuGTt9WzGNwJEUy9M/wA2WlzuUqUTsCaEYQfXbKBkJT8yrwhZorusQuGVH5tTD2xfj5OzIyFpht2ImjE1BGp05z8aWymAshSZhhPAoJrVMKeLaauzIQaIaMIgjX6u05GoMjKUq+gUQwrXkk0mdr/hygToAMI0Boktd7myPMPSguezPuR/OzWjLRw/p2DWQRSHwpaEmX8XwNTZO4nk48bDcr5tM1MMZuZIhgA7YcQw9U3yUdklkHM+nT+sRT/LOluuS+jyyv+MIDP7K8/rfIJsv9h5DbbruN2bNn47ouS5cu5dRTT6W+vp6f/vSn5PN51q9fz8477zzhNzvvvDOvvfYaAMuXL2frrbeOFHuAnXbaaUL6trY2DjjgAK699lq233577rvvPqrVKocffniU5uabb2b69OlsvfXWgFImp0+fzq233sqJJ57I8uXLsW2bT35y47RPS5YsYdGiRRtV7NeuXcucOXOi7+eccw4nnHAC69ev/8D8li9fTkdHR6TYA8yZM4e6ujqWL1/OdtttByjL9XjFvibvt3K/8sor/OUvf5kAI/J9n2q1SrlcntB+NfnDH/7AL3/5S959912KxSKe55HNZjdI97ek1j81xR5U/wVBwNtvv01rq6IWmzt37oSTh7a2NpYuXRp9r1QqxOMbt2okEgnKZYVpPumkk7jxxhuje+PhP9dccw3JZJKlS5duELX2g+QTn/gEO+64IwsXLvy7ir1t29jvC1bz88H6KIJqYlhjVPjE0YgNCkaFT06qOuvAN48sID0VXOoHj4TOrSjGEYC4FNQHKupsQgq+NK+TR5Z3sFNzHw+/qcbJJ7boYh6wcyHGH+d9l0+/8SPW7vFVbi+oMWJJ+OKWnWgG/MfbHRy9xTqELrlhRQdfnDHmsNm9IstLepJPN/RSv0hyz8OT2DY9zEBpbJyUKhbN8QprhnLMsIq8+24jH88oa+xfXm5j50NGeOuPCd4zY9w32qTgELYgL9SbNY7AkoKiCIijYUj45meHka6PdJQy9dMnWkhLwWhBpTEluGNU32gSTt1hnXLgywQMrEqxd0eJkwbqcJ0RACZ/sYXum1xeGGnm3RHFmuGJsYBThN8TUjG72ALO/Ew/aIIfP6T6ISU1yCtr6cerPv26QbcBh03q5eU+lWZWIo8QkqZYlY65I9z6RgeHz+7kpeXtrDdUP29nFljW3cgrcR0DQckPiIVKDEBFSGJSEEOxCp2xbw/Sk2hpk4sfbIrGihamTUtl9SuVA/6teZCV/XUA7Lp9F3/8awefnNKNW9V5ZqiFeV4hYjO6tL8FfxzvtwAMFPziuC3UZv+hVZPZc3IPb3Q180xCsekIlB03F0bCLYbsLWfusI5bXprCdkGJim9wS7+a7zXISIBi9AFlgV7oSRrGRX71Ao2k7nKbU8947yCtIqLfk4fPJPLYjoEQkstGGqP8zYKggJpbiUHBiPCJoRHLq3mmxptGTqox1FvxI5ag+mGNwTCNgSAmBXZ5jMnqE7ZH3lGv83eXZ5mVG6FQijE5ZTOYTxIzPGbN6EcPj1+GupJouuSKkSYmSZ2eoRRNUmdgxMccUbk2SY2BoTQtQqNvNMWkYW1ca0CP5hNDYIbzI4mG6UGhGmCFJbNsdS8jFUxquOCTlRqjo+lozTBLgooIMEJQ2Rkf72JweQwzruqbmeriDivz9B3vdjCqQdEPaDE0Qr9ULKlYkSqFNJoEO8Tk6xCVuWa1toViIYpJgSegEM71mFTPLwtJ0hbIcPzu4CorOUAKjyo6MxtGIiVaN9QmazTcBAgB93W285Yx5rcTC1lzCMdmHI3JvsY832bLaQMIDS7tbkVnbCwZCNJSoySCiLXstJndPLmyXY0DCUt90PKqbmZ46lSbp9tI5YAc+IJbSk2KbcqXxBGUQwig68KndfVeqs27QAp8XyceUtJu9rFR7nupg0oBti8V+IOWYuwN/U+Uv4Eo2CR/XzYp9x9COjo6mDlzJgCzZ89m5cqVnHvuuZx33nlRmvcz59Rw5bXPH0ZOOOEEjj76aC655BIWL17M5z//+QkK7bXXXsubb745wVEyCAKuueYaTjzxRBKJxMayjeRv3W9vb59g3W5oaPi7Dq7j6/i3ro9XmsfL+68HQcD555/PoYceukHajSnNL7zwAl/4whc4//zz2Weffcjlctx666384he/+Jvl/rD1gIn9+v72EEJMgDQ1NTUxPDy80XyGhoaiDc4PfvCDCfCrmtx2223ce++9PP/88xx99NF885vf/MBItO8XwzA+lAPtBRdcwPnnnz/h2rGp2RyXVhu7EUwa8PARFKRBVnjI0CFOIFl1l7KINrZ57F/xiWvq2NcJlGJYDTcCceEzjEmhN06b71AsxJhrKtqXwmAMKQV21WCSsFm7x1fZ7Mlfc8jHlS+Hafm8uqyNYV3n4Lp+Xlk+iWHd4JDGvoglZVTTqWiCg9q66V6f46FHkiDgSaeemSHVxbSGEVYO1bF5ehSqCSzTJ+9YkTXUIqDzEZ3Zn/dpeqyXLXtzmFrAkG+RESoPUwsY8S0sApK6TX8QY/X9Op5vks0qDX6/qktM8yO6zbxvERc+InyZ+1LQtzyF4+hRZNDhriSBL3Bd1V5dN/bRfnCa9msdtsBj2LcUlEJ3GfWtqP3rDIceP05cBrz3UAJDD9i7osZgWrcp+QYeGgnhMdn3afZ1RkcSTEaVVUoYHEqRiLn0vZNmjuPQuypLR6zEnIza9L062ES7VuWAoEKnm6IBh5Tp0umq+dqEg6X7dPoJWnF465EcLc0FSgWT3UInyDrLpstN0hC6IlelTlz4jPpxmmKqLOvfyDLNs+ntzmAZPrs09PHwSAt7JNXm68BREyfETdfYSIIwiJJdVGO9zlfsHxYB+1d9ZUkV4ElBTKiyBIBE0PN6klmOAwYkdI+9KzU1KAxyNM4Z1yDAR5ALFZyRSoymTJmBQpJdpYcdYpx9BNnwOVWpK2u5YZCIuTiBxiFVL1K2hsbNrVEM6lD3atcBbKlREjp1uLhSI675eFKjW1jsGI5rQwSMBCZxAgwhsaVGe67IlBByUyrFyDRWSaQdqmWTtVqMIIjTtTKJVvODkao9P29UKXgmSd2j7BvENZ9SoNq23ixTtE0Suo8d6PQJi/Ho5R2kO2G+WFrAoG+RFj4xTaUc9C1ywsPQAoZ9izh+lJ8RKtUjgUlGqLawpUb3khR+oOEHqr7V5SaBr06QtvHLlBwDDUnK8CJGl/HSF8RISZ+k7lHwx9bsrO4y6FvECUjqHk6gY0st6p96q0qnm6IeF4GkIA2S+GgCsnE1NyxDMeRUKybrKikkgnrNwZcigu74aMwRVaa7ekQkHIS0pwAxJOAzOTdCur3Ky2smYUrJ/kw87QMVudaWGiYBmlBr5+Qw6JaOJFcxMMKcJQKBpDbi2pIl3u1T0KFtwvPM91NhmkjSWZv+QgrdH4MYCSGxXTUO/vz8ZLbPDpFrqbBuVR072/8ipXsTLOcfkk3K/TixLAvf//vOF7qu43kejuOQzWZpb2/nmWeemYB9r8FrQFmzb7jhBiqVSqRgv/DCCxvku//++5NKpfj1r3/NAw88MMFZdunSpbz88ss8+eSTEyzvIyMj7LbbbrzxxhtsscUWJBIJHnvssY3CchYsWMDvfvc7hoaGNrDeG4YRbWDGy7Rp03jsscfYc889N7g3Z84c1q5dS2dn5wRYzujo6H/KobMmH/vYx3j77bc3Wo6NybPPPsvUqVP5zne+E11bs2bNhDQfpk/nzJnDf/zHf1AqlaINx7PPPoumaWy55ZYfuvyLFi1i2bJlG1yvVqu89957LFq0CICWlhZaWlompOnt7eXrX/86P/rRj1i0aBHXXXcdO+20E4cffjj77bffhy7D35Ozzz6b008/fcK1nt0OJqaNYMQC/BBsrptSOWSFR+WgjpNf6WvBFaCtzvLxzRQsRzOCKN5S4AuqZZNcSwUZCNasrKclVcZx9Sji4fLhBjQkOTwMEXB7oZlDPn4yM567AgDniu9wxXUSnYDPfK6BK6+TmPgcfFgjl19Xc9IN2MHWaDy4jd/9TlLA47NVj1VaHDsszGg+QWusQu9IminZAgOFJC3pMl0hq8XmjSO8M1hP/Uu9tJ44l9hNb6IZkmkQHaELDaYCvquUiw4peHJNO44AMaxgLPvM7EIzJJ6tIcKj7BrtXC2P91Y1ko3ZrMznaDUrdJZTNBs2/Z7Cx446OssXS/Y6RaPn1lEagxJm3Md3Neo91W6xhIdb1Wm2ihgxn1fXtOIjWNAyED5HYldM4kmXYj5Gpk5BH9b152jOKAjKQCFJXPeRUrCinGXBpH5e721mQWs/2SlKaWjod3nbSLD3lPW0m6PIQBD4gnZTwQFkIPBdwWaJYXxH8PSqdlb0KyPEJ7dQ0CvP1miL5ZGBgh8EnoaV9HjnvSbaGxR0543hBubkRliRzxF3A5raiywYqPBsWa1Ne2/WHY1RoSlIkqZLhCZZuUZhomckCqwfyjIlW6CutRKN1VoZAYxYgFvReXNtM9NyeYplC12TbN4wthGXUqDpQQQnMYwAw/KpFNXGasCO43k6lhYwc/qgcqoMxS6qDYiV9HHKOuvX5xgtx8laDs2TitE4mCZFBNXwXQ2hSXRTMjVQ4wUURMUpj8Hi3IqOEfOZUjYiuMwYzETBsIQGpSGLkbx6txh6gF006O7P4kpBUkh8JK1aNZqDuVSVIBCk0g5T6hyqBYN4xqNaGFMJdDOgBYjnPOy8QdNQHMPyI4t1POOimwFTA6GgUIZkajh3au0z/vs0beyzZ2tRPWrjRWgSocG6NXXYgY5eqbEQCYpSRwO2aB5mszqHwBdYaZ/qSNhWWY/AFVTzJm3GqHL8LJjUeTrxZLjJ8wUtISzHrhiUyxaZjI2VGFOqJ4UGiPH9YxcN7Kp6jl01SCYd3hmsxxcCH8F6FLZ+q3j420Cj6JjMmd4fjcGaQaHWf5ohGe5N0tOVVXS4AqbPHIzGb03cio6Z8Ak8BTtatrKZ6c0j6jm+oCPlUila6FqAF9bViKn3XbVgopeTBMA2s3siJwShS3xbi9pkzep6WuuKyEAwWoyjCYll+NghW85DcY+9PmNCYFBaYYSbk3+BBP9/OsJ+VLJJuR8n06ZN48UXX2T16tWk0+nIKjs4OEhPTw+e57F06VIuvfRS9txzzwj+8a1vfYvvf//7zJgxg4ULF7J48WKWLFnCTTfdBMCRRx7Jd77zHY4//ni++93vsnr16g2YcUBtGo499ljOPvtsZs6cOQG6c80117D99ttP2EDUZKedduKaa67hkksu4ayzzuLb3/42lmWx884709/fz5tvvsnxxx/PEUccwU9+8hMOPvhgLrjgAtra2nj11Vdpb2/fACZUk/POO4+TTjqJlpYW9ttvPwqFAs8++yynnHIKe+21FwsWLOCoo47il7/8ZeRQu/vuu2/UsfTvyfe+9z0OPPBAOjo6OPzww9E0jddff52lS5duFPM/c+ZM1q5dy6233sp2223H/fffz1133TUhzbRp01i1ahVLlixhypQpZDKZDbjtjzrqKL7//e9zzDHHcN5559Hf388pp5zC0UcfHUFyPozss88+nHDCCfi+PwG+88ILLxCLxT6wjQG+8pWvsNVWW0WK97bbbsu3v/1tTjzxRN54440PBc/5MBKLxTaov9glPBUxdHDCF51lqM/GOMYJx+PVB5UFKiEF++8QIyjYaAkTjND+FUjsVWXiCxqRpSrr342z89RBli9riQJQ3T2SwJQaC22TyVoFSyprvXOF2qRZJ/+Y+6/8HO2xOqyTf8t9Vx7O5Fg91sm/5YFffR6ASVYON9bEwV8+n5t+eQQSyaHGDFaZkh1DXvG8ZzGtfoRVAym2aK2wMp+jIzPKaKg8JXIudcMugS/w33yPzPZphCYISjYiEVrLNYEshyBjQyMoObze7aOF0AiA9LZpZKGKSMVUlM6Kg4iZUR74Pis6Y8yowosJjR0qCZbGdWbbGmVd5ZEMlGNm5elOWvZIgReAZk7sEwykH4ReigZ/6dVwkXxy97FlXLo+BILEiiKxVgH43PKCxdc/pjYA3U+mGfFNUmWfFxLwiZ0NVt6n8TEroDKg+rpbt9gpNUR2uyRBoYqWskDTCArK4q5l4uD5+KM2ei7G0vWStFRBmQ5aGJ4OahqyZCNSMYSlI4s2WnM9z3dZ7FdWVtAX4pI9Zpd4/K8NTHPUiVCPjDHbV7jpuh1iqh3CtpcVFUlWJCyWd6kxfOjMPlYuzbBZyiW9bXpsrAYSWVH9JhIWImay/DaD7eeWGHkxjqF7NNfazQuUiTQQ+MNVRFxDS1k4nVXefknBjDqyeQYKSZqzZdIL4iHDj0B6AYna2NcMUjGTJ+9IMg2bQSfOFjv5KqorY9SOWAZUXbAMhKEhq67qV0AIHen6OOsdYltlCYbLCMvAH3EwWpPRPJUVh7SuIXI58AKMJUMMjKTC6mikfcEyIx45VbsCMrZJKXRqb40XqFZNmhZ5SA+SRqD+W0HkQS8DiRbXkY5BfLpOcn0RYak5AWB0ZDaYL7LiqPYO0wQlG2HqY+MhE58wV2q/0bLJaK48tzqBpylIGsCILug0AhJSsG1HFaNOC2MegNVe628DYWmkUjGk7SJMnVw4H0RY57E1TVOwuqra8Gq5cMx6PkHFRUuYiKSFdHxEKob7yEi0aX/bzjKparMiZjDfdnBChhxXCCqOOiWwA505i/qIzUip5+tq3ZCOali9Po5IWojn8ry7solOTTlRL9g2PRZFVhNqjg1XEYaOlksgYiZda00Wtql5GLiC5Kw4dVKxXklX1ZvwlLv79wbDmoErILGFhfQCtZ4FMuofkYlTWmnQEIgIt+8GE0kUr17/LJcc9nNk13voNy9hUuhXs0n+Z8sm5X6cnHnmmRxzzDHMmTOHSqXCqlWrANhrL+VwqOs6bW1t7L///hNw4aeeeir5fJ4zzjiDvr4+5syZw7333ssWW2wBKB7zP/7xj5x00kksWrSIOXPmcOGFF3LYYYdtUIbjjz+en/zkJxx33HHRNcdxuPHGGznrrLM2Wu7DDjuMCy64gAsvvJBzzz0XwzD43ve+x/r162lra+Okk04ClBX74Ycf5owzzmD//ffH8zzmzJnDlVde+YFtcswxx1CtVrnkkks488wzaWpq4rOf/SwwRid5yimnsNtuu6FpGvvuuy+XX375f6bZI9lnn3247777+MEPfsBFF12EaZrMmjVro6cQAAcddBDf/OY3Ofnkk7FtmwMOOGADuNRhhx3GnXfeyZ577snIyAiLFy/m2GOPnZBPMpnkoYce4hvf+AbbbbcdyWSSww47bEJAqQ8j+++/P6Zp8uijj7LPPmNBM2655RaOOuqojfoMAFx//fU88sgjLFmyZEIU2+9///vce++9E+A5QoiN1uEfkW/cp8pVkh5JYaEjKISfYYwtxyTOpV82EDELOZrnpOvjtIkco3jkpVJc4kKnnhydyyrUiRQ/+2QPv32mg8+19UYBqM45WUeOFBj58yhr1jTwxS07eXVZG1eEVvn7r/wcby6/He/xG5k7+3MsW/776POby28HwHv8Rqq3Pc5Wc7/AsofPJ3jkLv58cYXTj/EZfqhfldsX/Hl9G/tu3clNyzvYr2GApT1NbD+lB4A/r2nDF4I3OxOUu2CJVsGTkoyIUwoBCH74HVT02TRZfvz1hOK5Lyqs6tdussiRpICHKyUpEacgPVzGMNK/PXCAkVdcttu3kZFHB9hthxSjz5cwYuGRenhCctVbU3j37SoCgSsDDCEQhI6UyIia00Xyy6NdRDbNiVeo+6YQEZf1NBnDXq2irp71JZfv36DiOpza0aecoAPBdw+u41s3ZPjpPn3c+ac26kMF85NbruPpFZO56F6bDGlKKJ77DEp5LOKjI6injgI+Pz9WIvN5RCrON25IRmVNkaKMH3K5pyjIKtd/weOdm5Vi8f0va1x8zRRO2W09w2/o3LWunU+391AaVYr71/4YJx4qZh4BCdL4SArS4zf79QFw+cNT+PLcddzzdgfP3F2JKEMlkjiqLDYBFelx1T59XPzwFA618hSqMb76RyNqN8X/LWignjI+FXw6aOD4ycpZ+fX1zWyeLNAzmuLnf1K0hbXfuBEsQsUVuGJhJ+uXZbFiHqfem4x41FNCtV9BeqSEqqOink1F+PO8dMkKk81ljDeXlWkVLQzi0IzFQIgeV22boCA9KriYaBxuT2Z2ZgSAoUKSQAo+f0A//oBN16tpTMunz0nRZCnF8N3BelLC44anMxjheNLD/0Phc5ox6Quf3Y/DJJpCWJSS/lccPClJizhV/DDGQ4IKPl6oKWZEHIcgjBeRZgSXHEmK+JE/RYoEw9IJ/QsMLv94F35xzNkktnkSraUOmS9yyR1TKAuJTYCJiqBN2A8OAaN4WCSoSh9TKMiNO87SbBLHlgHJkFLWQ0b9ExOK0rNCwIh0iGHh43O43RpBdz6x3TqG34tzzNaDvPlEI1nDIZO2MYyA0VE1D5Mxl18un8z65U4UVTlJlkSYyyAuJemxjzeZT0zppr1sYCU9Tr27bhzmnpBqNocPDOFSlT6XzVNrGSiM/curq9GYiKPhIymF8K2zTY8dmnswYgHnPNISRa/WIcL/D0mX85tHeK+/PoL9mXoIwwyNF8XHfkp69zPZo3UeF8ctHq00MIt/gWyC5fxDskm5Hydbbrklzz///IRrHwYvr2ka3/ve9/je9773gWl23HHHDRhbNpZ3d3c3hmHwpS99KbpmWRYDAwMfmPfpp58+AWrxne98ZwJUZbxMnTqVP/zhDx+Y18bkK1/5Cl/5ylc2em+zzTbjnnvu+cDfnnfeeROU7Zp8ULvus88+ExTjv/e7iy66iIsuumjCtdNOOy36HIvFNlrf9+czf/58Hn/88Q987nhKzJq8P1iVruucc845XHzxxVEd+vv7+cMf/hCx92xMvvSlL03o75pYljXBYXf16tUYhrGB8zYwgXr0Pyu14ERxoVHCpxGTuNAp4VGHOS48O8jhUaSuozXkyIgSGakhhEEspFYr4zNJGvgigUuA0+OT88GxdbSwzf3VPZGlryANNAOGdT1Ul6A9Vof3+I0Yn/gi7bE/4z1589jnx24AwPjk0bhXPcZm8Ub8O25AWzAPn7cIRgrktlMv2bfvtpgaVBlYlWKm7WPkAmyhYVghu4cQtHkeD1uwpW+QxQQBDgF1YZvIUJHIhcjWAEkwMAK+j0gqi18KQRbF8e0LiUtAg7Aipc9F4g1W8RwTf/0wxeEYWQhhUCFzhq2RqHdpDATDukWVgJKQNGLhhPkU8GjCpIQ6OQgG82imSSYMcpVCx0WSxyUjReTU6PeM0CLVxsqtGpRLFobhIz2fOCay6mNI6DZVWYQusYWgGZMqMuKsr44LOpRGw0aSQSfoGwHLQI6WSYYbgAQaFQLS6JhC8XRrAoKBPAOOgtRsZTtkZUzxyOsaCQl2xYigCTlhjtUh5JYPUBtIe7XC5Tf5Ajtv0OwFpAwdEy1SP42aUyeaUuCLLkkEnq9haEHUbuY4hUo9Q3HfT/IFQwOqPpP0KsWqRVz3SWJihB4VOkLFEgj7uV5YlHoNDEMxxtRh4obPKePTgIklNCr41GOSFCpoUmtIaxkXOmV8UgGkdYOc1AiEySgedeHrWqI2LA3Cohr2uS8EvflU2FYaQ6NJ0kuHidVL6prLmImAWNyLoD3Fd00Shke9jCsu87DNAgR+WN56qeMKk4zU8IRJAT8a0wBZTKSQuEg1dwgDRYXzqPY9E5bbRZJCJ4sebUJVeSV1NSpdApxBqOZN0pPDzcxglaDSj16fpD4QaBqKgz50IK2JI1RsgDI+mlCxGOxwPgA0YqmAWmJszevFIR3Wtw6DEj4ZdLTQyOEjqWgajX4Y6bcI6wazNMeHycRtLMunoaOM0KCzPwwm5wWkLI2MMMYp9xpmqCynhIEllHP+YF+aSZvl0cyAzICxgXKfkJqiF0Wtsb4tiI9zIk7relROC3WSZ4Vr8VBF0hwrohkyivlQy7dmskkJnUrZxCCI/DEgjEMRfpVr3+FTrQt4pPd1UlvOwxzhXyObHGr/IdlEhfk/RGzbprOzkxNPPJG2trYI0rNJ/neJ53lceOGFnHrqqWQyGV566SVWrVrF5z//+X8479/85jcsXbr0b560/FekcNqnARREIGSAEZauPmsiOsKVjseP7lPwoITUOOOQPMFoRcE2avCdQOKsKhCb14SsODx4W5bd56zjjTda2XySwjj/ZrSJGBofq0om6xWe0lMcnO6n7XMKa22d/GPmzlawnEeW/JY5sxUs55Elv2Xu7M8BagOwyGjiohfPZ9ZcBcu5xdqcp8wk21cV7MNBZ4tJg7zU18IeW3XxwlvtLJrSy7PrlRV7j+nrWfVeA1OnDZNdFEPETQW1KNqIZAipqcFyNKGgBRWHHz2ilNN4aIn79qEFghBqUIPxiKQFMTNqk5tuSrKF6/B4wmCnimRJXGOuLSmFJzXpIMARgj0XriO2VVbBBzQxEZajiRB2IxG6xoUPNuAi+e7Bxeg5OB5SSqrvVrGaNISlcemfJ3HqxxW7zCuPt1AWGinp82BC59wDR/ndvQ18trU7Uqqf6mxnm/QQk/fXJ8KNQliOCGE5waiNlovx0/vqSEuNipB86zOjY2WtwXJiJrJURWvI8sv/0DkAdax/o0hxzqL13PpyB1Mdn4XTe3lx1aSIFnX+5x1VpyBQUJSSjdA1RNLiut8rReqIBZ089cpktp3SS8Nu73PQL6l8RMJCJCyuuinBcTus4+1nG4ibHjMOCV99nh+1X1BwwBBoKQu3q8RLzykH7mm5PH35FC3ZEpP3JoLl4AURJE0IgUha3Hlblmm+jS01djyiPAbLGT+3qi4YOsI0kLY7Voawj931VWJb1SlYjqnjD9vobQp2FEHFLAMtl0R6PuWXBli5fIybvT5b4cliY8Tp7gqY7bgUw5OQeU2DOLZO+8dtpCcRloZ0AoQ1dnIonQAtbSKrHlrCxO2uIKyx9cCYnInmh4iHm+Ha2K+tGUUbavdKNlomPmGuRL/JJaP2vP/GJF7Iuw8wrAs6dQXL+fq8deh1eggXCsCoOftIhKWrsep4CoITzodaWUTcVO0ewnOCilL69fpkWF8PWXGjMYvvI1JxBh8YpFpSdXh1pJF2afOyFWeRbeOgUxYKlrOZUHAyJ9CYs00/1hbZCNooKw6yqvpYq08gEhb5p4d5671m+jUTWxMc+vn8hPErvYBguKLGYwjLue2mJAfNV4xhgQOJ2SlVT00gbQ9h6tHa9ebNOl1BHFcI9vvMwBjkJ0wPCpL03A0JptaPRph7X4qIDhNg14EXKTylYDl/Ofk1WuuKbPXWA/yzpfrCbR9ZXvEd//H37/822WS5/x8it9xyC8cffzwLFy7khhtu+O8uzib5L4phGBNOTbbffvvIsfoflRq8apNskk2ySTbJJvk/LZtgOf+QbLLcb5JN8v+5nDBN+VCUpR+FkFf4e53xy6uJ4OITYgjTROaLnHxTQAsWeXwKIc4zLjTqMOmSFeqExQU79PO75ydzWP0Y1/r+XwmQ+RLDT5foXFfHjK0GeWX5JB4J/druK61QOPsnb2bBV++a+PlNFTDMe/IWqr9/nI89Pszyh88nePxenv15iY+fGiP/gLJsVQuGstrPWscd73bwicQQK0ezzJ40CMArfS1UhaCkQVVTmHuFG9aphAf+CoOvbCB+CCv40VdDzH1ZWepOvklBD4r4uDIgLQwK0gtRyKCj8au9i4wu8anfq46Rx4fJ7ZBk5PlKhLmvyXWdk1khqiHNoiK3q9lSxzD3Gi4BFx8FIpvmq7/Oh89RmHuJZHMZoyIUb/uZR1b5wS3Kmvf1hv4ICtRyYIZzbjH40SeHuOPBVppCVqntZ3Xz57cn80DMJhfWyw/hOQAlPHQEdRjk8fn5lzSCfAktFecbN9XgHZBGp4gfjaWi9Fh8OLx1q7IIzj4hwS8Xa3z94+sZesPkTyMtfKa1m+KwglX9zI8TjyAvAUl0PCQlfC7bfQSAq55s45jN1/GnFVP4s1kJmdKV1E5WHALK0ufXnyhw2eOtHCQU5v63cRmN6zHMvUGFgCI+02SMo+sUtn95TyNTEiVGqnFuiEMSHTkOp67qLMlLj1/OGaT7LYW5/1k1RTVUUhK1CM3SIyUMJDKac2ZY1oL0yAqDadLiTVGhFYshXBoxGZyAuTco4VGWPiYaBzsJ5iRVmwyXEjRmy7Tv6uINOPQuS2GaPn3DadIhtWd/JUlC8/hjTLHwe0i0EN4xHBIlNmHSj0MDJkO4TEJRYdYgPP240ZyoEkRjpIQXrRsZDKrhXEphKMgYBuUJmHuDIVmjdxRc+rFBvLyKZQEQ2zyB1pghKFS47J4cxRAKpDjsxyBYVQIKeFhoOAQhUE6MKw0Y4b1kCICRKLgUKPhWEgWLyksXK8Swf9Yeo5DefZsuBlcmaFlg8+ZTjSRMl3TaRtcl+Xzo+2L43B7k6GYMc59CjzD3fbhUpM8nvSR7NCmfDjPu873eBsbOTcBEI4uOpIa5D7hky0Fue6sjrAu8rFej+RZDw0NSCX0IzpA+zW0FjFjAT9a2ToCS1aB+w9Ll3GSZ1UN1EeZ+PN89wLxbDiP9yX9n95a5XGLEeM7PcVLnjfyzpfrsR4deiO981EeW1/8W2WS53ySAYpU57bTTJuDVN8m/VnbbbTdOOukkjjzySGzbZosttuCuu+5im222+ac+t4Y/TYZ43wYMEkKLMMLjMffBwCjCNBB1GbI41EkdTQjiIc6zSkBboBNocXzA7pXkAhXptaZ2eav60FIWQpMUAxOhS4Z1AzN8yU6O1UeY+8mxJxXmfo8j1ecnbgbA2PNI3KseY2qiGf/Om9AWzAOWIYdHyeyoIBtrbtaZKir0r8kw0/EQKYVNHo+5b/I9/mrBVp5BnRayXYzD3AchBr/2kg1gDHOfUi/zFEaEI/ZDxaPx/Zj7ARu3GsNfP0JxOE4uCDBiAd44Srp4zqU+gCbdxEZSwqMB9RnGMPdlAjQ0gsFRNNOIlO5UiLnN45ENBDFRw9yP0hooKJJb1alUFHUengq6FVR9TAldZgitEgpz34rC/mfQiaFRDuuTwSCFhoMki07QNwyWQVCokEJBR5Jh+gwG8dBRURcCf3CEAVcx0MiKTVomVQAsXZKQKsJmDR6U9U1iobruohFDI0A5s1bXqLHS4kE1b9Di+aRMI1LUYQxLb6JhCQ1Z9klKgePrCnMf9vF4zH1CavgC6hC0+YKBAVWfSVaFQjVGTPNJYkXPMUIsMygF2RAmpV7zfZh7VZ/3z626EHNfDK8DJIRGlYBkAJlxmPtCmF6VU+IgqcckIULMPdBTrGHuBeSTpN8YIpaFXHMFIxFgJT2spGq34gqLpOVSLxMRbl0p7YIg3MzmpBZh7lUZlAJfU+5rfihu6JPy/rlT+54N73nhpiSLHimaqrySOmFGn51BRWmZblUKvzdYRSu5aPUJcoFA0wQ2EpMxzL1AGRbi4bjTQj8YB8lo+KTa3AGi9u7FIRVuIOsxKIZ1MYXACB1uy5pGU4i5dwuCdUNZWq1BsgkbK+bRsFkFNFj/qqLGtTydpCnICDVvXFQgtxrvWEboJIT63tefYdqWQ2imJNNrRGlkOC5TUsMTas5ZIsCraMTChjMlpPQxXL8VOhgnapj7qklbbBShy2ic1vKteStnhIFdNbFCPn8hZERr/EGYe32ETfK/QDZZ7v/Fsscee7Bw4cINnDHvuOMOrrzySl599VVs26ajo4Odd96ZU045JeJH/2dKf38/qVQqYnQRQnDXXXdx8MEH/5fy23vvvXnsscd49tln2XHHHT/Ckv7flPvuu4/TTz+dt956K2LMueyyy7j33nt59NFHN0h/ww03cNJJJ/Haa69NiAuwfv165s6dy3nnncc3vvGND/Xswkn7qg+Wwv8KISK6OGHqEVZTuj4/f6RZMTNIwWkHDOGP2mhJQ6UDpB9gr6yS2LoOWbR57O4Gdpq1nuXLmyMqzN+NNBOTgvm2pE2r8oyR5JBcH62HKczw38Lcz5+jsJNtVh0LjEZ+Pg5z/zt9C/4cN9mxWov26dPeUGD5cAPbbt7D0pUtbNkyxJJ+pVxu19FL57o6hbnf2lJY3BpWPDEOc1+yle9BSGn306cUe0aNCvObB41OoIxUVJhGhEMmkPz+tiwzfJvHYxbbVQPejOtsZQdUwzdpUga4CHad30V8i2REoYcmIppEALwgorK7+NEWXCH5932Hxsrq+kgvoPKeR6wVCOA3L0/hpO3XAfDqn1uooJPA5/GEwbf3GWTxA80cOg5z/2RnO9umh5i8N4rqNKUw1EFBYdi1jKKorFFh/uKBRpKhw+03DxgrS1ByIn8MWbLRmjJccXOCfVEnDbeJNN/auovb/9rBNMdj/vQ+Xlw1iXZNWSPnHlwZ8zEwdYWR1gRawuT2e9VYOXALFV13XusATbuPo3gNAkWdCYiEibAMrvlDlqMXdfLOXxoV5v4ANxqztX7yhxxFhZk2cdZWefWvalM0OV1kuJSgIVNmyicDAttT2HcviDD1aAIRM7jnzgY2C0LM/WH5yB9lwtwK8dE1WkzpjsPcOz7Oeo/47AzBcAVhaXhDDmZbciyN7Sn/g0wCZEB16QjvLR3D3Dc1lHhypJkAsIXC3M+1PYqh4jevfgi7atLx8RJ4UmHXA6n8bsZhs0WIbdfiOs56B2FAqPtjTk6Njff3UWHWRFackAozHA8h5r42V2ppanSU0gt46LYsPkSK7rAu6DRUxNkvz+oco8L0xigdZaD8BrSUNda2MNaugIgZ0T1FhRli4HOxaG7VqDCJm+B4iFScoSfyEeb+9ZFG2qTNX804c52QCjPE3HeEmPuqrzNvYR+xzRNqnFg6Qd5BeuEpQ2Mc4iaFl4qsWtmoYnNo8LmDh5gggQypMDW0XAxhGdx5W5Z9Z4WYe1eQnB0bw9xX1bNETHXQ23dbrPJTeAL236d3DGs/HnOfsnjp9xnaQ3rLfGlDzP0uAy9SfOIiZPcqXj55CU2ZMrNX/Il/tlSf/ujgyfFdj/7I8vrfIpuU+3+xbEy5P+uss/jFL37BqaeeyiGHHMKUKVNYu3YtzzzzDM888wwPPLBx5xXXdf9uFNn/qvwjyv3atWuZO3cuxx13HOVymauvvvqjL+D/APko23/vvfdmzz335Oyzz46uDQ4ORpGDNxYU7NBDD6W3t5enn3462hAceOCBlMtlHnvssQ+Muvt++bdpipK1IF1SwkRHkJcOCQw0IfDDJcIUgiu+klZUmCMFvvwfNu0izigeI+GxelIoa2WnLFMnLC7ZfZhfP9nGF+rHqDD3P80iGBpl5MkRVq1pYMvZ/by2rI0HwtPvB8rvsXTZbXiP3cDWJ/+RN9+8Be+Jm1l0yn0sXaacrGpUmNs+lefNh76H//BdPH6pw55HVxl4RDmYmgmfh9e2c9C2nfxuSQeH1/XySl8LO01TwZEeW9uOJqGiQVmDv2oVAilJCyM6qvfHwXJqzB8//npyAiznpOs9csKkFFFh6uSlG9HNGQh+e4DN6Cs29fu0MPJIH7mdM+Sfy6PXqDB9gdDgd6sm846oqqNzGaCLMViOJyUxoUWwg0u/ZCAySU64Qjkqx4QW0UBOlfHIYnzOsZJzQ5rR05r6IyrM1sMaOfM6nws/NcKdf2qJqDB32HI9T6+YzJ9iVbKYFPCQ42A5xTDaZQOKxeXi49R4EKk4p9xQo4Ucg46MSpckBiXpcsNRFituUlbQLb+S4+Lf+pyySzcjb+rcN9jKp5vHqDB/5FkRC1OAgtm4IdXf7z6txtsv/ljPyXPWcfsbHTyvlTHGjfkapMcmoCQ9rt63ws8fauKzKFjOlWGwH1NoBFJiCEEdpkqPzxRinNSsYBOvdLayVWaE9fkMtyT8CCJUg0ipOsOQdPj1wmG6XlewnJ9Wk5QjKkzVfnnpkBIKiFOUHklhYIW9PCxt6oTFDBnnTcpMEjH6cWjEZCSEy9RgHnnpUZIultA5wk4yKzsCwFAhwaSmAs27G/j9Fda+mMY0fbrzabKmardeN0EKjz8llOVXWcIVxKhXqk1cu4jRg0MrFr04ESynJv040fwo4xOEn0vhZ1CW4WrYPml0RvEi6I43Ls2gdAjC9rxy+2GC8hgVprV5RlFhjpa45PbkRqkwzRCWMyxdYkLDjmhkFaVsTUyh4ciAhNAjy3wNxmKFJ0xVfIakE8FcjrBT0UZj1x26GFoRp3kbj9cfqSeu+2QzVQwjYHhELWCW4XM7Gbqwx9Gy6tEJwRAuBelygJfhU5utpzAYJ5Zw+cFoNoKVSSQGGvXh6cggDlXpc8WCYa5/bYwK8xVdrUGelMSFPoEK87uaT66xjGEF/GT9RCrMWrsNSYcfZUu806cgQfWGjRASTcgIljP35oPJ7PUdPtE6n5/rJk/5OU75F8ByKn++7iPLK7HbsR9ZXv9bRPv7STbJRyXHHnssTz31FJdeeqliVhCCF154gYsuuoiLL76Yiy++mF133ZXNN9+c3Xffne985zv86U9jO+TzzjuPhQsXcu211zJ9+nRisRhSSh588EF22WUX6urqaGxs5MADD+S9996LfrfTTjvx7//+7xPK0t/fj2maPPHEE4CC5dQ2HNOmTQPgkEMOQQjBtGnTWL16NZqmbUDpePnllzN16tQJ1JKLFy/mwAMP5Ktf/Sq33XYbpVJpwm9GRkY48cQTaW1tJR6PM2/ePO67777o/rPPPsvuu+9OMpmkvr6effbZh+HhYT5IHMfh29/+NpMnTyaVSrHDDjtMoIa87rrrqKur46GHHmL27Nmk02n23Xdfuru7J+SzePFiZs+eTTweZ9asWfzqV7+K7q1evRohBLfffjt77LEH8XicG2+8Ec/zOPXUU6O2P+usszjmmGOiTdH1119PY2Mjtm1PeNZhhx0W0V8ODAzw6KOP8pnPfGZCmsbGRj7+8Y9zyy23bLTeV111Fe+++27Ex3/dddfx9NNPs3jx4g+t2APUYVKHSaOI4UtJHQbNQlHk1aGoFjPCIIGOHMoT9A8hMkkywiArNXIYNIsYzSF39yRp0C4SSlno8agLxqgwNSnxV3VDiO8uhVSYo5oeYcYnWTkFy/nk0YoW88lbMPY8kjZLUWTWIDvOkGSzeCPeH25Amz4dF0GQL9OwDTRsA/3r00z1HIZWxJlpB+hmgC0ERtzHiPuUNWjyPZYbHjGpYAb1wiRAksMgh0Fd+F1R+CnlLBgaRQ7lQddB10kLgxw6mSg91AuLuvAvLnT8wSpuVcfvHaY0oiybeiwgcDUCV8Mp62impD4QiooUDV2ozwl0Eij4UyMmGoryLxjKI22HlDBICYN6TNIhoWhaCtJSIykFQc8wLdKgRRq4VYNSIaYibvo+cTRkBMvR6DI1hEZIhanKmcGIPoNS0pqx8EKFP+hTczMoVEiikwzv137bICwahElWswiGigzYcQbsONgOaSnAk+hmMIEKU2iSnDDJYER/qbCNG4WFs6aEs6ZEUyBwRjWaPbUpG0trEEfBNNLoZISBLHsk5BgVZq3dUuH9BDoWAhONDAaTfI3h/iTD/UkmaVWK5Rhx4RMPIVgxFLSiVmcLjTphUu7RMQwf19HJYob1t3BlQB1GNM+ymDSFn+sxqMegRcTDkzFFU5iVyocljxeNyRyGmpvCpFGLERc6nhD05VP05VNUAoPBoRTlN8oETkBdU5m61grTWkZo68jT1pEngU9C96mXOkkpyIVjJSs16oVJvTCpkzp1mKTDMozgMYIb/Y2fH7mwnyVj86hemMhwDGQw8EJIVQ7VLrU0hHVpCOeKOyQp9xnRKYE/WMbvVLEr6gJBWgqSaKSlRk7q5KROWip8elNIYRkTmqIajdRyaBIWsZAWtQGDDDoeASmhkxI6zSGcqDZms8IkJ0wqmkZCBiRkgFeE9UNZhKWRiTlkUjYNHWVyk6vkXYu8a1G0LRJSkBo3FlPoxBHEEaTRqRMWhoShnhTp+irxjBelH/vTSUqNOELRzwqToAoxqf4SEhLhnMgIg3Q4DuuESZ0wGanE0E0V9be2tuoQ0WKaCJJCx64amMho66aNh+YAdL7Hp1oX8HjvUtIZe1yLbpL/ybIJc/8vlEsvvZR33nmHefPm8YMf/ACAH//4x6TTab72ta9t9DfvV9Leffddbr/9du64444oCmqpVOL0009n/vz5lEolvve973HIIYdEQZGOOuoofvazn3HBBRdE+d122220tray++67b/DMv/zlL7S0tLB48WL23XdfdF2nubmZvfbai8WLF0+IPlsLqFTLV0rJ4sWLufLKK5k1axZbbrklt99+O//2b/8GQBAEUaTbG2+8kRkzZrBs2bKoLkuWLOGTn/wkxx13HJdddhmGYfDEE0/g+x8civrf/u3fWL16Nbfeeivt7e3cdddd7LvvvixdujQKJFYul/n5z3/ODTfcgKZpfPGLX+TMM8+MKEevvvpqvv/973PFFVewaNEiXn31Vb785S+TSqU45phjomfVTlkWL15MLBbjwgsv5Kabboo2Bpdeeil33303e+65JwCHH344p556Kvfeey+HH344oJT5++67jwcffBCAZ555hmQyuVHr/Pbbb8/TTz+90Xo3Nzdz1VVXccQRR7D11lvzzW9+k0svvZSpU6d+YFttTHa2VdunA8hqAevRyQaQEhrrhU4qNHzFkAw8UsT3NPJ5j4PsBMO6IBEIcqGVxxQaMa1Mp0yQDXzefq2ZLaVDvhAnFm4A+58NKBUDXC/D9IYRuldkqWiCHUL8uRtronrb47hXPcYio43q79XnBUYb1dtULALn14/R8PvFbLbtt5DDJYKVK/nUFwoMP+PxYpeCUrRLm6ypnt2Mw8rOBhalh3lzmYo6vFt6GBGXHFGO8Y402NUz0KUkKQVFTbWJEX4f1DVigSQmJYMPKbrHalnBR/ap1qugsejoSJISXATV0OpsSsnaF9MUbQteyFMuJ1hxO5SdZozQeW3Aj9ExUGS+W6XZi1EXSFIarEcnF8IksrqkL1BwIB3Iv1KlMDjE5yoK61sQGmkZ0Bzz6Le9iPJy5BWXmY7Kw/M0ilWLXKrK2luL7FPJ0vMXi3rfY3I4x/rWZNgmNYQoNVDvexQ0nUBAvR9i/zUdT0DWFwzrOvlXqlQLJrGUyyeqqiy2Jmj0JUWh4QqDTOBTFTHyS4Zpiql267mzymy7np5XE4wW48ylTCzhRdzyB9pKaQVCR0CJLiW+0OldprDw8xyb3nVZ2qXNPlULN0wvgGwYvj6vGRhSZ3CJzvZVl0q4ATu8UnPWrf1GkhYenhRU0AmEjyNVGl1IdC3A9Qz2qo6pNyIcIwCu0BBoVAsmMhD0lZLsqukRfCsjJUNCIyMlWd2nU+okAkGdCBgIy9BEQMzwGXA9ZgqDvCbYxQ9oSVVZXlE0tGqMqsBQjrDQkXSZgnpHjbfGeIW3nQzmKh93hc6MbYeQAZRHBHZRvfIzhksgBZu5SlG0hSAmla/FgaGT5krPYKfAZ0ho1MmAqc15PE+LHLLfLNdhSgXRq82XbBBu1MM2ScqAchhMKimhLDQCwBc6ZpgmLgOqQovacs1bDcQtjxVrlSW8KVEhW1dlaDBgoVulV8RwhSAWjBmUNMATAh+d+nC9yms6ucCjzlDpVgc6dYE6HRgSggbp0pSyWVVWY7YsNOoDyaimAzrJIFCKfeAzHNZvYHUaHcnS+3NkEzaBLxjqTKJrAbNmqA2I0MBcVUeXn4j8jAwpcaNXuVKz67FxPY3SaAwhJHvYxoSTEQ1IBgFFTUPHQJOSUr/F9JAa10TS4ql2DBAYKN8UV9TGrE1xWBlcPlFV0CFNSgIhiIWnGQEWeqKoDCNoGHqAlFB0THJxZZCS/X0cQCOfbdmT0dECe6U/OObORyr/jTz3v/rVr/jZz35Gd3c3c+fO5Ze//CW77rrrRtMee+yx/Md//McG1+fMmcObb74JKMNbTQcaL5VKhXgYUfijlk3K/b9QcrkclmWRTCaZNEkpIO+++y7Tp0/HMMa64uKLL54QEKurq4tcTi3sjuNwww030NzcHN1/f6Tba665hpaWFpYtW8a8efP4/Oc/zze/+U2eeeaZaIDefPPNHHnkkRMiotaklnddXV1UToATTjiBk046iYsvvphYLMZrr73GkiVLuPPOO6M0jz76KOVyOQri9MUvfpFrrrkmGtiPPvooL730EsuXL2fLLbcEYPr06dHvL7roIrbddtsJVvO5c+d+YJu+99573HLLLaxbt472dhWL/Mwzz+TBBx9k8eLF/OQnPwEUhOY3v/kNM2bMAODkk0+ONlgAP/zhD/nFL37BoYceCsDmm2/OsmXLuOqqqyYo96eddlqUBtTJxdlnn80hhxwCwBVXXDHhtCWRSHDkkUeyePHiSLm/6aabmDJlCnvssQegTgVaW1s32heTJ09m9erVH1j/gw8+mM997nPsu+++HHjggX83cq1t2xucIuxx8AAxXY/4mOfrZYW/rzgsiFWjRVbaHhc90owPpIXg1MOHFSY7YUZc39L1cdZWmbugEVmo8Mid9ewyr4s33mhlziT1UvjtaDNJKZjvStpGdV7SkxzU1k3jwYpT/OAvn89Wc7/AZvFGHnnlfLac8zmmJpp55BWFrwfYLN7IZtt+i9+9/DNmbnUwuujlcn0Wr8Sz7BIoLLWNRmu2wutDjew4vZvX32slnnTJl9Rcm1lfpXt9js2mDzNroT2GjR6HuReGpni5x+GGf/KEmh8pqer8zS/kJ/LBh7+PsMe+z2235thC2iwebWGHEHM/G59ymEdSBLxjZ9lj0ToWzkhFPOrzYzay4kR9NZtiFEb+54+14SP598PCU60Qiy0dn/a1I8QmaRDAlS+08/U9FM/9Xx5vwUVQyps8ntD598OG+d19jRw+bT0yUNrHc+smMSee5zOfHVFxDDIx0DSCUQUB0DIK51vD3F/4p0mkpUa1IDnj0BA3bOgRtlokYshCBa05y2XXt7NvyHP/22IDZ+24nlv/2sFUX/HcP7e6jfYQFrLb4aPKx0CGmPuSg9AEIhXj5jvrATh0QSfPLp3MovY+Fuw2xmpCIJWvBES85Vff1sIxH+/knRcbycZcFu6nThSlHyCEQEqJP2QjLA09Y+H2VnjluYmY+9ZsiW0+JaP+qfWFqrOGSFjc8ftmpnk2GpJ9Dh+NMPlByNNfm2dzEo4aXyV7jIM8xE5P6xsmtlVW8dxbOl6fzdSOIGpbWbIVp3kuCV5A9Y0h3n1NYe5t12Cb+gGeyjeDgL/8NaV47sdh7ufWDePYBgfu0h35DchAIgwRYcOnU1C89yEPvr3WQbOIzvs7NhcT4hlEcyc15vsgS7bCgGtadG+DNBUHrS4VzZUHb8ngV8EMYWUrvBydIxnSmsYJW3cyv0FDxHXlK1BbMgMQlqbyH4fzl7YXte2slBvdk35AUHQhkExtHFMiaz4mImkhHR+RijH86AhORa0Zrw420YrNEjPOnLKOi8AOMfftw2pT5AQacxf0MWuc70xQchUvP6A3xhFxk/wLBd5d2cSK0TS2Jjjk8JGx8asJ8Hz8QeVzoeUSCEvn97e08umFCnPvO5DcKqF8RkJfDWHp0brz9h90lo424Ao44IC+sfYOxnwVRCbOs7fUMb1hBCkFI/kEvhTEdV8ZI4Dst++j+OxlyDXL+evJS4iZHv8S+W+iwrzttts47bTT+NWvfsXOO+/MVVddxX777ceyZcvYbLPNNkh/6aWX8tOf/jT67nkeW2+9dfS+r0k2m+Xtt9+ecO2fpdjDJuX+f4S83zp/3HHH8ZnPfIYXX3yRL37xixMgL1OnTp2g2INScM8991xeeOEFBgYGCEJlbO3atcybN4/m5mY+9alPcdNNN7HrrruyatUqnn/+eX7961//p8p58MEHc/LJJ3PXXXfxhS98gWuvvZY999wzgvGA2lh8/vOfjzYrRxxxBN/61rd4++232WqrrViyZAlTpkyJFPv3y5IlSzaYFDW56aabJkTKfeCBB+jp6UFKuUF+tm3T2DjmYJZMJiPFHqCtrY2+PrXg9ff309nZyfHHH8+Xv/zlKI3nedGmqibjTy1GR0fp7e2dwGOv6zrbbLNN1AcAX/7yl9luu+3o6upi8uTJG5x2/K3deyKRoFwuA/D000+z3377RfeuuuoqjjrqKM4991yuv/56zj333I3mMV4uuOACzj///AnXPpmdz151C3BD3C0oXG8t8mFNTARn7rI+ciS87I/tpKXAFhNZKxp9WLM8ICETHD2lh8eWT2FuIs+7PSpI1dkHD+IP2PQvi1Mqxfh0Qy/d63P87nfqWTf98giWPXw+/h03MGvuESx/+Hz8O29i1twjePMhten1/nADcrjEzK0O5t2376b6va/T+VCeHWYW6VmhLHENk0o8vGYyB8zv5I63OtgtPcyqvnrmNCgF9I3OZjLCY+mKVpavNSiGysT7662THWsDCefs3q2cDkOl4bK72knKHFVRS6/ao4a5l8CJ09cxsC7N6TsMMLLcYMcOh8F3ExhGaEHzBWbc5w9vdDC8TOURULNYM+H5tZF1+k5diLjGFfe3RW2vAbqEZh/y7yqr7Nd2WMeNz0wBYO+GATQh8Tydb21T4ar7JnPMVkpBbgipFrdr7mdkJMGV92SIyTqqQuVtyjoAnDAwkglUBJy5YxeBE6BZGlfeP3lCWR1BOK5SVITktIWdrHlV5XPOrn3c/kQHh23RydC6FC+vmsT87DCBrxrysj/Wo4dUoD4qIqcEykLy9UVKwfnDqx3sN6WbF7sm8c5dY+2kIbDCLqwKxSbztdmd/P4vHWynFyjbJlfcn4v6qybpQDmf2kJZoT/RoDakq4fqmJIusD6f4Z77TUw51jdRpNWwrv82tYuhnhRSCq64p26c70UWgZpbiuEkZNghi1nzYQ3bttGHNcskWZnDQ0EwRpeMlbP23KIIMKRgnpNk+8k9APR2ZxnJJ/jsJ7sprQio5C00PeDtnkaawj5eM5wjLnyefDKnKCXHBbvSa/sMVDuYUv2vC8AL6wkw+rpi2KnNFy1EjNc+18akpHbCAbZQJ2HVca88HaLoxwDHTu5BCKITgmSjQ2wzE3/I5a5XOiIHYVNOXHdcAVUxNv9qzwz3rJGTbu1/jXWmNu9NRNQGVWRU9kV2C/FQ0dxxWjfVgslWbf28u6yJtJCk4g6m5ZMvqDU8YXo8sKyDrnfG+ikmifq4qCnM+7bVJHMnD9AwEse0fC67p4HxoiHIBGP1cpEcN2U9Dy7tCNtN0rlSoMmxceMKInatT+sFFmYH0HTJbx9pjU4RNMbGbFVIPls/ROdQDoEkY7hYho/j6cSNMJrxs5cxda/vcGT9Qj4tNQZKSf4l8t9kub/44os5/vjjOeGEEwAVif6hhx7i17/+NRdccMEG6XO53AQ94e6772Z4eHgDS70QYoKx9J8tm5T7/2bZYosteOaZZyY4Z9bV1VFXV8e6des2SJ9KpTa49ulPf5qOjg6uvvpq2tvbCYKAefPm4ThjFr+jjjqKb3zjG1x++eXcfPPNzJ07l6233vo/VVbLsjj66KNZvHgxhx56KDfffPMEx+ChoSHuvvtuXNedsHHwfZ9rr72WCy+8kEQisZGcx+Rv3f/MZz7DDjvsEH2fPHky9957L7qu88orr0TQnpqk0+no8/sdX2uWOiBSxK+++uoJ+QMb5Lmx9n//5uz9PuqLFi1i66235vrrr2efffZh6dKl/PGPf4zuNzU1faBPwdDQULSZ23bbbVmyZEl0r7VVwUtqG6nxpz8fJGeffTann376hGuXzvsKErXo1xQyGHtZ1BR+XaromGgQlBXdnId6UYwdP0M6kFhSEJeCaslUR8Z6QCk8LvZ6qqCBafk4ozr1iyQPPZKkEDoMSiTBI3ehLZiH5F2Cx++NPvsPKw1OX7iAYOVKdNFL9XtfJ/6DK4n9+auYkwzkO6o0b77XwjbJUVYva2CuX8VI+1TRMC2lElSFxvRsmRdKDQwLxZstgXhYb8Z9d4RSZBIIZc0MJEFelTeAiP87AOJS4AqJHSoNMSkIPIX1lp6kmI+RCRw0ITHjqiyVoolb1WnyJIMWWCH0pipUWxL2j49Sqj2A0Mo6nrlOl0oJTgaSsqaUKOnJaKG3qyam6eN5KnqtKxSuOQDe05U1dXrSY6AvgROXpKQgCJXjGsigisQWEA8U9aeIa1ANQIvY83DDtqqGbWJJGBEqzWhoERSWFhleY3EPtyjINlXoWlOn6muMORPXRABxBMUuNZ+bvYByPkZD4BGMe50FITXg2HfVgFaoaVZ8HfE+X3hNqvYLwgfFA6hWVKKs7lCqWpji7yscvqshwz4LximtVjiOtEiJlNH1msKsybENnOKfV22aDmA4ZDNS7SkIwrw0YMAQ/HWdWg+mGGVWBCmsp3yapxRp3NpFWBrbDXSjxdWDlj7djKX5eKEGG6DGvMfYZsdn7LoEsr7EEWMUloOanDBffCQZKSiGnwFSUlAN65lAUGHixhfUfCkLpaDGJDhlA90MCHzV+15Fw8x7yECN66Kh1h3EmJLKuHxrbVPbfNWU6nxtLtU24WFbl3V1wUUx8lRFzYFbMCoCfISiFwVKozH6RlJk26pMmTyCYQUEvkDTJY6txp9p+ujFsf5U/TRRBDBgGKzqqmfewj41B994v3I/JrW1xYgF0WZFl2wgmiRyKi/YFo0tJTRDIkYn5jchb1+E402gawqW837c/aH1C3jZ7eeUFp3VfXUbPvh/uGzsxDoWixGLxSZccxyHV155ZQMfxb333pvnnnvuQz3rmmuuYa+99toAHlssFpk6dSq+77Nw4UJ++MMf/lOZEDcp9/9isSxrAn78iCOO4PLLL+dXv/rVh6YuHC+Dg4MsX76cq666KoLcPPPMMxukO/jgg/nKV77Cgw8+yM0338zRR/9taijTNDeKcz/hhBOYN28ev/rVr3BddwJEpQY3ufvuuyf85rHHHuOCCy7gxz/+MQsWLGDdunW88847G7XeL1iwgMcee2wD6zJAJpMhk8lMuLZo0SJ836evr+8DMXF/T1pbW5k8eTIrV67kqKM+fLCLXC5Ha2srL730UvRs3/d59dVXWbhw4YS0J5xwApdccgldXV3stddedHR0TKhDT08Pw8PD1NfXT/jdG2+8ES0AiURiAu3lf0U2tqB983PqZAChIXKpyFlU5FIEPcOIRJheE5x7WzMpNEoE/OhLDsFgASwDYaqlRKTi4PsEowpOcM4fcnx/USeP/3UKW8QUHOPXS6bgAotsydaT+rnn4Ukg4LNVpSwfaszgzxdX8HmLW6zNefbnJWAZv9O34PFL1YbV5W0+9YUCl+uz6HwoT+zPX2WzJ3/NwMHHY5pq3K40TT42L8+Nr3VwzC5dXPP8ZI7faz2XP6Ms3d84aID+Z2Fbb4RppQTbHFIgqLjqaDuk0qt9J5AEZQ9hCC5+dBLJkGEE4LT9BnF7K5htyTEavpBKr9ZuF97XRoev8eiLWbZyfO58I8dmnsANI85rKGXy4y297L2jhoiZiIRyQI0gQqkYcrSsjvoTFr++p528CDj7SyEf+LohtJSFlkthL+tDOmBtnuK6ezr43AxlKHhjeStloRGXAX94Msdpu6znvic6mGsVovHw7upGFi3oZvsGRTlIANIJEMlQ7QsksjqmVv3uicn4QikWX/uksh7Lso+WNpCBRIsZiHQMWXX5w10dTEWV91ePtnLMtC6efmsKPrBN/QCD3WMb8lO/aCunZUC6CkJRG4tnXadO5X56dIWrbmvguF3WsV1TSAsYSEU36fjhsBaITJzf3dnBcZ/o5vVH6knoPqd8McQU2040/jE0cBWUw+su8PgTaqxs19HLK52tzKkf4qs7DkcQi/EiNIHWmOTPt7TQpNt4gcapX8hHJzwiFVN56zoimyboVxt6LZtCVkIIUSIGMQv39U6MjiyyaEPcRMsk8PuUr0cNfqHVpaL8brolRWPYrromedJwGPBz5DuznLY3yEqVwrJhvNC/ZqtZ/bgVjeMXlvB6qphtCbz+KkZzHK2lDoDKi93E59dReW2E+NwsWl1a1aWG1+7PR1SPQgj8gqM2bDGDoBTSkFoawtTxh+2QqtLE7a1gtMTH+sfQFHQnkGDoXHJPE9M8RX8JMFoMaOjSKYiAM7ZbhzAEep1JZaWDqYqKXwQ9CcakuIIrWYaC08WMKB5FMFJS9+Im/mBJjctMAmmHwcEGy2hpE7xAQbkSFrge794BeVuNu5fzjbRJh3ve7uBTTb1UqgalooWmSXKNah0NPI0DtunC2Kxe9afvg2kiC+E66/uIRIyee/LcUWhmVkXgVnS+se/AhDErnYCg6qt2S5sIU+fmu6dw6JxxVJgLM2rtlUE4L92ovs9cH6M4EsP3NU7Ys5ug6CMsgV8MMBrUeq3VJ3n2liyT4mWCQOAHGroWUPV1ciH8puvffstpcQ3iFqv6sux0+r/Icv8RwnI2dmL9/e9/n/POO2/CtYGBAXzfjwxnNWltbaWnp+fvPqe7u5sHHniAm2++ecL1WbNmcd111zF//nzy+TyXXnopO++8M6+99lrkF/hRyybl/l8s06ZN48UXX2T16tWk02l22GEHzjjjDM444wzWrFnDoYceSkdHB93d3VxzzTUIITaKxa5JfX09jY2N/Pa3v6WtrY21a9dusOsEZXE+6KCDOPfcc1m+fDlHHnnk3y3nY489xs4770wsFouUztmzZ7Pjjjty1llncdxxx02wtF9zzTV89rOfZd68eRPymjp1KmeddRb3338/Bx10ELvtthuHHXYYF198MTNnzuStt95CCMG+++7L2Wefzfz58/na177GSSedhGVZPPHEExx++OE0NTVtUM4tt9ySo446ii996Uv84he/YNGiRQwMDPD4448zf/589t9//79Zz5qcd955nHrqqWSzWfbbbz9s2+bll19meHh4A0v3eDnllFO44IILmDlzJrNmzeLyyy9neHh4A2v+UUcdxZlnnsnVV1/N9ddfP+HeokWLaG5u5tlnn+XAAw+ccO/pp5/mhz/84Yeqw39VrrldbZh0qY7/i1oWXUIqgH6jgeZQR/UEfHdRJ3pSwx0KuOG6DoRsxBVjC0k8gHSg4YocsUDytewIT78ymQV1QzxXUArZAUYeQw+w6j1Wd9exbXqYJ516VmnqpbTKlJx+jE8wUuDX99Tx9a9ryOFRfv77NGeGG5EgX2b4GY9X4ll2mFnEnGQwcPDxNN19DZmfnAZA9x0So8HABfxyqJCUfepD05ezusrjIx0KBiF8rnxAja+EVHATGLPc18SUcNpu6xXmvKjyvPIBlYcvxuAj1jg4AMBXJ6+nWjARQjI4lOKL2RKDQymCMFFrS4Gevgwv97Ww9gF1TTnIJSP7s4KZJCIL5wkf60SLayy+TkFhqmISAnVvqttOXtPZckmJ/XL9PPuW8keZHi/SokmEkHxeD3jk8TZ2n9LNc+sm0YHCDE/vGOKpN6bwriVIBQqS4QnVLqC+6xJSIVzjuB3WEVQlwoCrHlebVp8xi246gGQAozoc1NzLe93KQnlEYw8PrZrMro39rOnP8epwE4vqB6IImTdcnyLtKytnWVOUgHW+JC4le4X25d4Hysy1Ywy/Y3H7y80RDEOTYxZoV0AigEMae3nm4RZazQq2Z7D4+tomNxZBRzrcgNVWAk3CXnFvzEFXk3hCEEt4XPX4JBKBapPa6RYoa282gB0So/iBhil9fntnLrKSJiS4qHIlg4BBPRc6TYIf0mQmAohLn1jQxhpLIyEz2AJyPgzoY3DMWAiL0qXaGKYDeMdQ8yfnxvh84FISPjEpKT7eg9Al2YVxhfkH7Pcc9ITPbfe3R1Cc8fNY1acDfxlAhuBtmORKXCGicd1jNIWBv8bmy/jP4+tcK3NFU8/yx6WJhWlEOOa/1NBLT1+GrcIfTpk6QmnEQkrBIy9Nod8Q4+z+YVnF2Ana2FmrgtMZ0bgd487RyESW+0L0eq0jJlW/JoOxOZzzJaOGKvDHtAKjvsVcv6IYwIQklXbUqULjGBb99093ROO1rOm0eD4jujr1HdIhE8Co3qz6bltVzl/dkUUbVzF9XPvZ4YHDjl6VFW+EQeCk4OWV8QieFJeQ16AhtMkJA3b6uNo0XvdEG/o4KFltzJoSpuEpR1pNIMLfWlqAH6iGadrG43tPNRNHcIDwuPNSly+exT9fPkJYzsZOrN9v5BovGzuN/zAMdDVmvvdTiO+4444T4v3svPPOfOxjH+Pyyy/nsssu+xA1+M/LJuX+XyxnnnkmxxxzDHPmzKFSqbBq1Sp+/vOfs/322/PrX/+aa6+9lnK5TGtrK7vtthvPP/882Wz2A/PTNI1bb72VU089lXnz5rHVVltx2WWXRc6a4+Woo47igAMOYLfddtuoY8h4+cUvfsHpp5/O1VdfvYFT5/HHH89zzz3HcccdF1175ZVXeO211zbKaZ/JZNh777255pprOOigg7jjjjs488wzOeKIIyiVSsycOTNySNlyyy15+OGHOeecc9h+++1JJBLssMMOHHHEER9Y1sWLF/OjH/2IM844g66uLhobG9lpp50+tGIPyrKeTCb52c9+xre//W1SqRTz58//uxF7zzrrLHp6evjSl76EruuceOKJ7LPPPhvAebLZLIcddhj333//BhNf13WOO+44brrppgnK/fPPP8/o6Cif/exnP3Q9/iuyo6cUZgmUfYOkrl5STqCzVRCg1+ADus+qV+uxDJ+6pjKL/DKakLi+hibG3krphIOuB5QqFp2jGaaYZUolizYvtAR5KRL4NMsKPgrDOVN62OHiuWM1YPihfnLbxdm+apN/YIDMjll2rPoRh33DNvBi1yR2CVx6VmSQ7whM0yfzk9OInfNLABp//z38vKK5FCFkRIxXDDSY5Pm8HtPYWi+TqqrFPi8MMnLs1GpU6DThEkgoo7P+BbWhTWaUpXRh1Qvj14bpNYMOUYmU1KJrsmZ1PZqQFHzFby6GJSXPiNp2eChJXbpKedRgmu+S9yxsBI26Q8lXy3RJ6EzSq/R7MWJIVr5STyZt8zEvdHQVEjfQGMJi82SBqmPQ1FTi5d4WFjUp7HjvYBon0AhCqMHMWJHRwQS5wGc4pK9s9zTSgc/OtkePUJAXUwT0CnW/LvBICp/1IkardFjzUpb6xjKl0Rhzw8BAGeHRKywygU97okSgCVxPZ2lPUwSLWNVVz3RhMzySICYCdCnJF+LELTVOtglKxMLPjqfjBRrJmEsq7XBfXim6u0yuMjqok2qy+VifF7KCg0Rghw+KIckaDu91N7BZsojraSRMl21DXv8an7cvBfXJKulSioTm0TStxJp31EZkn2mS8jrlFzHb9gnGQX4SoYWxIjSmxooscXMsNEcp2hY7UYkgOgVpUK8rhnEn0JklfQIpKAYm9cYYZCBAoBsBTY5JQvcoeCYFYTDNc6M0o8Kkwyyh6RLX0+kKEjSH9RnVdPo1Ex0VAGp2Sa1FzpKx36enaaDBtlqBbjtBi1mlz4nTbNiUvNCqK5QxvYqORYCHhi1EVPcp4XweP19GhU5O+tRmWV4YZKWHj2BUM8gFHhKBQYAWphkVJk04CCGpBjpdPTkGsEiGeb63qpFRDBpwmYJNxjGIIXERWGF/OyiIV1Z36A9ixGVAneFQ8Q0KUtWnSbcZ9q2Izx2gy08wPXxObUw3Bi5NiQqOp2PoAevdJA2hotlLggHdYLPAJvA1fKkiAEspWP92NhpP84MyAsgkbWzXIJOrRpj8kquYaN6xsyyzwOstIp2AbaqJkMh2orhh3eLC5z09zi4NylfM8zTmDelkDQdfCgwtYNSO0RhX68HTQZbqGp/AE0xzxtp7vDQKh+VmghmWom71A4EWMkN5ISxq7Z+T7GrrvGFBU6qMUf7vY7H5r8rGTqw3Jk1NTei6voGVvq+vbwNr/vtFSsm1117L0UcfjWVZfzOtpmlst912rFix4u8X/r8om4JYbZL/tPz4xz/m1ltvZenSpf/dRfkfJ0EQMHv2bD73uc9tYHH/1Kc+xezZsze6U+/t7WXu3Lm88sorEVbv8MMPZ9GiRZxzzjn/1DJ377InAG5VwykbpJtsqnkTx9bJNlcj+jzf1Xh+sAVHKFz9DpN7MOMBmhlQ6FUvLs/TkRJcV0fTJKWqRX2uTOdQjs1bFAwht5lNZUCnb32GvGOhCZhUX2A0r5TmvGexRccAfT0Zhtw4W0wapLc/Q9XX2WL6IKA47Eu2hS01Zs3o5833WlhpmnTrksbQtHjSqz8g0b4r5dUP07rlQaz/zec59Oy/cud5in3p6B+8w8nVGGnTpeyZzN2mD71OR1YDgpA6Uk9rBNUAvwhmk4afD/j96x3kNWVlBfji9uvQm2K466pocYWDr/SNbe40XbJsRQsp3aWlsUhumk3/2ykyjdUoTV9XBtPw8XyNxpYSQpP4roY2DlirsNwQzyj88eOrJ2NKybaNSnGPpVwCX+DZOt39WepTFQZKSWbP72P5UhVArD5RpaucosmsMmlynv7uDAN2nOnNIwwMKcuiHeh0tI5Qt6U7BmrWiFhUhCbGopgCi1/pwJJKZz9qRwX/qaUFGF4RRwjFZW8lfdyqUhqKw3GaphXpW5Uh11ihMBQnX4mRS6l2SeXsKOCWGfcRmqRaMBkeTTL7i6qPL7k1wQkd67ljzWSOCqPwooF0JEHYvHpWUOkSDKxP01lJk8Jji+mDVAsKTy/CDZamS4YGkzQ0lgl8wXODLRz6nToATv5ZD5fsOsxlf57Eydt3jUVG9SR+Wf3eyGoMvmmRm1zl1SWTmDujLwpSBuBVdaXAFkzsqkHD5DK+I3CretTPw/1JPF+jrq5CqskmcDVkAIWhOI2bq024FgfpQLnPiH6rGQGNhymn6cqfV1NYbzHp9G3w33ibx25IIIGbYiUyoaNBEyYmgq+29pDaLKC8TiM5JaDaLeheo5TU6bvkGVlu0LhHnPyLJTrX1JG0XKzQZ6V5i1I0P2QARoNBUPYJqhI9G8KpqgF+WWJOMpFln8AJMFriaq4kQ7+EqsQrCETYBl0r6pi2wyjukPr+9pvNzJw5iO8KqgWTxrk2QVUS2yKH16XgZHpbGllxKC+30UyJb6vYEbV5AxBLe2i6xHcFTtmIMPL1kxVrkpGGMP4TI2viaLok8AVNi1z03Bg0sQb9+o/7m0gHUNXUiWV3aCqNS9iDAq1T8hSG4sTiHoXReATbsZI+xYEYTVs7WLsv4Ls/7SWJxumLuhDG2LgShsAdklhNGn45wC/D4Noxny8hINdSYaQ3gRXzqZRNmjcrMtKj1tGO07bkhz/tJykFJ2/bhbDU2qTFdfzQX6jar6HHAgbXphGaZLiYQBOSdNxhqBxSkabKvFmuY5pWZtCLMattkGlLHuGfLZWHrvjI8krsc/KHTrvDDjuwzTbbTGDsmzNnDgcddNBGHWpr8uSTT7LnnnuydOnSDdAL7xcpJdtvvz3z58/n2muv/dBl+8/IJuV+k3xoKRaLLF++nE9/+tP88Ic/nMAs8/+rrFmzhocffpjdd98d27a54oorWLx4Ma+99lrEWz80NMTDDz/MUUcdxbJly9hqq602mtc999xDQ0MDu+66K7Zt87Of/Ywzzjjj7zoh/6Nyf6s6FUngExMBQ5jk8DBEwKC0SIWWLUNIJjfl0Y0Az9FYO5ijguIibxbKElbjA7dCRbXoWggkubhNT0W9mJbEDVo82MKv0pApU6pYDLhxWmPK4pTNVnl+qJmpQZUpraO81NfCVFGhIVfm2bw6kp7qOWRNh7pshWdGm9nGGqV9Xh6jwYheXC33v0tl/dNKwV/5IJ/e6dvc/aOtOfxctSm9/ZyZrP7Zu5SqFomYy9JqjqImMCTEw2WxrIkQoiQZ0QWJAPboWE8s6xOEZ9sPrJjCsA6TPMUTrgEtnhfBMVwErWYFL9B4lyT9Bkx3AgqaFkEcpvk2ttSoN22G3Rg+AhMZOfIBGAQYQjKMiSEls1sGCXxB71DIcy8NdCQxEdCSLTFajNPUUOLefDOfTisO7rWDOaY05BkYSfG2lmAbc5RACgarCRpC/nldC1hfSdFjGBswwsAE9kEMCZ/aqhOkwHcED61RECEzhDcYEjYPVIxSXwresmI0hYq/KSVVIdSpga4zOXBImw7DzhhzlCkCBJKq1PERZDWXhkyFSx2Fzb9o/wJ/uKeRgz++jj8+N2VCuWpxFYqaiE6N5m7Wz+hgguWVHJNCyk0ZxhF1pUZzskJ/OYEpAuZs089X3sgBcP3XGrnkVw6n7NXHHQ+2Rv2mvW+szPKq/NWMs1d8iCWlehLBmMOzGVr4c8LD0n3W+wlMGRALnSUBJiWVAthfTlAQBlrI7Z8RHuvDIHF2OCZbfJek8HGlYECzeDIWnni4JulAcpUxwBy9jjMa1Ia4+UszkEMKtx+MFMHxePauOrpMgzbXo9s0mOT6TE0phfl5p44tXJtn4xbbVH2mpIpUHQM7tOyv1WJURRgYSUpGdeUonAwkxXDzY4Tf+w0RBV8a1KHdlVTGpckEyvU4AHLS54W4QVOI3ZnvV/irkSAVwAzfZoURIx7ASlPSHqbp0RULz0zHx0Vx9ifwkYjIGl5FxxUCU0qSwsfS1MlJn1TtWtI0NCSGhA5RifDnLxrJCGo0JFTgNx/J6fO7cEcFekziVTQSoRtVUA5Y/dc6epwEjbqDHehkLEcFbkM58jdrNi/rSR4RI9z0WUW3e+/9LRFcpsbqkw7XnXQgSQQSU0oadTVu/UBjRJq0GFUcXydhunS6KdrDqLUXGj6L93MISi53Pt6GE8Ku3BB2BGqdWmMazPPUHE1bruK5dy3qE2o96CqnWDS7h+5VWWKWR3c+zSd6b+efLZUHPjq4SmK/Uz902ttuu42jjz6a3/zmN+y000789re/5eqrr+bNN99k6tSpnH322XR1dW0Arz366KNZsWIFL7zwwgZ5nn/++ey4445sscUW5PN5LrvsMm644QaeffbZCWx7H6VsUu43yYeWY489lltuuYWDDz6Ym2++eQPoyf+P0tnZyRe+8AXeeOMNpJTMmzePn/70p+y2225RmmnTpjE8PMy5557LmWee+d9Y2o3Lq5sdBEDFNfClIBNzKNgWEkE2ZlN2xmhFatAPDaUExk0PTUgGKmMbEB9BWegkZMDMliH6BtPqiDqhXkpT9vJw11fpfjNDdylFc7xCIuHSO6IUtgFMdtu6i4FVKV4r1LPHrHX0r8nwXjnLrjt0ATC0Ik6+EGe1m2LX+V2sXtbAc3oKlzGKu6+8eDbJaXtHCn7hqqM4/Ptv8vvvqc3VkT9YwSl2gqTuUfYNJtcXiMWVgmRXlQJjxTyEgErJJJlx8Byd1f11FIQeKW3zmgZJNdiM9CQxLR8hJEPDyQiOYegB8ZiL72u0zS2gZ3Uqa6RisQitlYNrU1gxn/UDGeK6j6GPHYvX4D2ur+NLQTZh43o6ZUdh+L2QKz9tOgRS4AUaPUGcBly6NIv99+nl4QfVkfKC3BBrh7O0pUq0zy/wwgtttMUUhKgQwpJ0LSCXqhKLK0un56iotXpI2+mFwZIMS23ylg81EKAC42w1SSmSvquhmwG+q7FuMIsmFHXf3D0Hya9Qv7eSPuVhC02XWEmPvq4MrqeTSalxMlKM4wYaEkFC9xBCUnRNejWLT5+mjr2/++sK58zu5uplHXwuEwYREsri6nlqfYolXAYHU7S2FXh0fRszfJup7cOsXV+nxjRKqTS1gEE/RotRperrPB+Lc/K3VZqv/6ybX+45yqWPt3J0XV9kaZeBwAmdVK2Yz+ruOhbuMcCSJ5uYOW2Q4b4U/jjniyAQ5B2LABFBP2rjBGC9n8CQklazgmWoTbXnazi+Tl1aKVtGeH1gJEXV1zGFZEr7CA27KOWx+Fd18pP7+p4Er7/Bn65VvEF/itnUhUjcBBpxKTggKNLUWmSoP0V9Y5nRoQSrwkBkC9v76OrOsdXHBlj1Wj0Dbpw4PlY4HhtzZaxwQ+HYBom0gwwE1bIZzSOAatkkXV8l8AVu1SDVYDPal4gc3wGKhRhCqL5Lphyad9Zwu5WSOrQiTvN2Hv6Ix3svN9DSWsCt6tTPqJJfG3KxT3FwRjV6OzMRlWPVVbA3vzYPtYCY6eN6GlXPwJMaAklduC7F4qFjraexPp9BJ8BHY8GCHsXvD8S2yhGMVhAJk5vuaSDnKz+ERCDpCa3ucQkzXIc6y2bYiRMXPqPSoMUM+08PGKwmmDenh+xR2/CjH/WQlhqHp/rRzRo1roamB1G7VooWjm1Q31JizZqGaJ7GTY/BagJL+FSlzqRkme6yMqLscnaOSy4pkpSCQxp6QwYigW4GOGU1DoaGk2y+aJhVryrYoOOrdS0ZcxmuqPG02aQRHhxsZUvHwRQBcd1nu667+GfLf5dyDyqI1UUXXUR3dzfz5s3jkksuid7pxx57LKtXr+bJJ5+M0o+OjtLW1sall166UaPnN7/5Te688056enrI5XIsWrSI8847j5122ukfqtffkk3K/SbZJP+fy1tbKt+EWMJFBgK7apDMOAS+oFK0iCfVSy/wBasG64iF1tTJzXnKpfDl2qBexDJQLw8z6eMUDZ7qamPb9BCD+WQEf7gzZjEp0NnadpnaMMqaIWUdnZJVFsO61gq3r53MTNtn29nd3PHeFGY6HnOn93HTeuUYOtMOaMZhxvRB7u2czFy3yvzdB/HLAWGcHmY81kXvW3eRnL4vlfVP8/ltTuPGszfnixesAuDGb2/Gml+uxHYMYpZHpWpS9dQGJ2WqOju+jhtopC2XohPi5YUkabmRn0HFMRn1LZpjlQgb3lxfjO67rs7yQh1JGfBKXCmCTb6KKFmz2Ha4KqLsnOwImh7gOfq4F71SGjRdYpo++XycmOXRX0jhScH0NgV3qpbNMF1AptGmMmqSbbf52dvtnDEjDGL1RjvTs6Osy2d4OW7ypfb1vLWymZxpEwuVLdvVqXgGlhZgBzqJ0Aej6quyx/WQvtM3SOjKGc/QA6qOgRs64Vm6j+0ZWLrPpPY8gS+QgeC64RbmheQ0PYZggWvTpVn4CLZAWa2LvqrH5i3DaLpEaBK3quMHGom0Q6rV45SQNvDqLxpce32MY/btY/n9anMoUSdItfHm+DpNdSWeLjRxyDaddL2eZXUlzfwwqFrgiwgGlaxzyA8kiCVcmnbSOfEBpeD87sQsF//W5xt79fHGn7LRhkogo/ZwfJ2OKcPc1N/GAWKUd+wssxKj6LrqR9/XMIyAZNZGBoLSaAzD8iNFDiA3qYJX1RntU5vlQApMyyfwBVVbtYvna/hS0NxQwkp4eI7Ga73NvBPTorkxaGjcSh+zjXrOae/DdzUa9m7AHwjpmTzFxNL9UpzufJpJ6RJ9xSRNqQpNU5Rfy4p3mpjcnOeVgWYW5IaIJ13cqh5tmsoVE8cP+8V0Kbmm2nxaDtXQuu9JjYzlMGqrDU1K9xj1LZqsCm44nrxAoz5VIZCCIBAst7O8EguYHKj7LZ7kVSugSeocaAzTV0yS0H1Wy0TkBN5FnFzg05HNU7VNYqaHFfPwAy0aB1Kqtc2yfAzDj2A3lYoVjXs/0IiZHs3tRXxXoJuSP69poyavWAGNUqcoAr4xows7H9bT0Ui3hKxVFY3yiIXnaaFBQCOe8cb61BfkWio8t7qNm808/7GPjT/i8O5z9dFGRITtYmgBFV8nazlYps+LTh27ZtS49T0FWcs0VKPN9MhAksY21X/fXd/IL7YbwC9K3n61GVcKNAGu1Ehoak431ZV4oNTE7iIfOfcHUlDxjGjT84adZd+duhh6O8boaJxkwmXWO2OBGv9ZUrn/lx9ZXokDTvvI8vrfIpuU+3+yTJs2jdNOO+3vOmZukr8tNTzb8PAwdXV1/+35bEyuueYabrvtNh5++GFAOU87jvNP84b/qGTl/L0BpRyOlOO0teQp5uOMVGJMaR2lmFcKjutpdDvJkK1F0p4qUtdcxrN1hocUPdqwHcMIX6aBhLb6IvlCXDkrZtUGoHmrMnqDSf+LOq8ONzHDKGKZPsNl9Zy8NNmiYRjDCFja38RW2RGEJlk1nIssw7oZsLKzgSo6m6ULGJbPH0shi0RYr6//ZCoHn/1X7v7BfI467y1ue+WXJNp3pdL5OADZaXvzWJ0KSlYJDOZs0YfQJGZOYg+GypsGVi7AGdUQmsRqlDz2whQcISiGm4iDZ67DzI3h7GNZn/VvZyO2iUTcpWobSClonZJHjwVoBpgtOnpGKRZrHjao2Eo5qktXkVL5L1gxL8IMe76GEJDOqpf5m0ONJGRAk6XaNZ22qVZM/ECj106QER4DWOy+ezdPPqUUlGmxIp6vkUnbNM8u88JzbUyyKiTiLuvzymKbM200IZmy5Qh6HPwadj1Ey4T+1+hxCBz401sdlEMfhE8vCKNnVtV9vyJY9U5D5Di8+YIhvFKIKw4E1YKBDATxjMsb77XSlixRdZTClIqrkwgplbN0LOEyOpKg007xiZNVW3//dz5nz1/PNa93cMzm60BIhKZoAmuY60S9R+97GVIZm2f7W5kuK7S35hkaVGPW0AMCKbAMn55iivZckapt8ITM8pWzFUvY1y9czyU7D/ObZ9o5YU4nIbkN0gM3pFux6gPefrmJOXsM8dzjrWwzu4dq3sBzQuy3L9B1SaEQo7+aYIu2IRxbp1oZs3T3jaToETHmJkdIpB2spI9T1unrzzBl6kg0Z82kT+/KLFXHwNAD6hvK5GaoDanRlmTkRZv6T+TQd9iWh772BgBLYiLiXvoLBTLC5PsNI2Q6XErrDVLtHuUena7OOgBmbD3I0OoEzXOqDL9j8ZeBZhoCj1SoGE7bfAihgZkJcAsamiEx6yV2v5orqk1khOu2GgTOIJg5da12YhGr8xlanUBKQSzuYVcNmmeX0bOqkTufTtA6o4DVbrDmqSRTts4jPdCSAj9f841RfiCjKy10M8CtGtgVQ22EwnmYSVcjPnrH0RmpxjFEwOQ2BVWKpT2ELglcjbUrlSU7kIJZnxqLMiwDiV6fBE3w+1syJANJjymIBzAQnuYkpWCe7TK9eYTR0TiW6VOsWkxqUcYLKaGvP8PMRYMkDvoYP/5JL0kpOGHzrugkT/oCzZRURwzS03yq3YLyiIVh+fT0KJ8ITUiamop092VJmB5Fx6Rj0ig9fWoeLzirhYsuLpCWgmPndqJZarxqcYEXttvA6hQts0qsfa0uOr3TtYBswmawpDYjrfVFVg/V4SKoEy4xw2PbdXfzz5bKfRd/ZHklDvxgxrv/q/J/RrnfY489WLhw4YSgSgB33HEHV155Ja+++iq2bdPR0cHOO+/MKaec8k8NIFCT/v5+UqkUyaR6kQghuOuuuzZgTPmwsvfee/PYY4/x7LPPTqBW+r8u/xWlfGNjwnEchoaGaG1t/VDUVh9WbNtm+vTp3HrrrRHnfV9fHzNmzOD1119n88033+jvXnvtNbbffnt+//vf85nPfCa6fscdd3DUUUfx8ssvb9Q5Z4899uCpp576wPI8+eST7L777h+q7I+3fg6AjOGSzVTpGs5EePY1g3XkTGXBsQwfTZNoQmK7Bn4g6PYSxGVAc8jQkKur4DqKIk5o8MZAI1NjRVxPp+Apy+NfYxYjWsAOVcm2M3t4991GfCloSSutMZlxWNrThC00tp/cwxudzfhCMLd5kL8OKJYUWwgWJYaJJ11W9dVTRWPnvXoJyn7klHbkCwnuDDH2t58zk+ypf4ggOgCVzsd5c/tvoQmJZfm8na9DAkVNIxPUWFcUFjcVBATAqK6xa64/cg4FeHHVJEZ1jRbPJxDq97OMYgSnKTsmJd/EFAHv6TECAWUBeU1G0TH3qvikdZeE5UZh3+OGR8U1McJ8LMPHDwSjbgxL+DRnyzjOGDRutBojYXhYhk8mV8WuKDjEjT3tHNXSDcDqznosLWDYt1gSNziyuZvV6xoQSFrqlGPhSD6Bqfus8NIRRhmIaCFrWHZHCDQku0zuwUz4eLbGU53qZMWSKuBRTErmpoeRgSCQgifcuoiqr6zBVNejKDSKusbHc/30DmWw9InxNUQIF6gEBg2xKq1T8py9XlnurzwCrrkpwbF7dvPYQ60EYZAlU8ooqmhB09lcL7HKT7H7nHV0rahjrZNi87hStmqbJs/XaKgv0zuYJmF6TN+9yIl/VorStSdmufK3AV/ZrZv7HmubEHQqGY6Voq6xfWqIu+0GDk0O8NJoEy2+hxXGUTWFxJWCXMyhvqHMiu4G4sInE3MohX3eVFeirq3Me281UQ10SkInKQPa0kXeK42xplWFFm2Kg0Cwqpqh01QK6LAmme4KXrRcXnUHuLldKZS5+SIKvBbbdStkvsjTV/p0hVj7PkOnyfeZkVLW/Zer9WzuV3nLiDPDdZg7p5fKsBVB1t4aqQ/7UZAMFDylqAnq/SCKHFvUNep9n6rQKGqCnB8wqms0+GPsLXlNZ1ro/VyVOlU03onpjIZzY/uqz0rLoEcPONgrs1SmMSUUdUiHD6oo8h+muS4ugjg+Cd3HDCFuACPVOJ4UxDUfS/fJpNW6tnZYtWtB6ARCYEjJVpkRfF9D1wMetBuww/52kFSEpErAv2/ejVvWSTT5eGWIb6baJSj6DC6PsW4wS0Oiiu0apJM268LNs46kLVvkhXID9+qjXL+/i19wePyxSfhizHLvA5lA9U+LF1CPS7ewmBNX/SMlDFQStGWL2I5BMumwZihHR06N6x/Zca78RJ6g6HH/s1MiHxhbU34QANOp8JKeZMeghC8FcdMjCAQjToymhFrTOytpZrcMopsBo0NK4V+weiwI4z9LNin3/5j8n1buzzrrLH7xi19w6qmncsghhzBlyhTWrl3LM888wzPPPMMDDzyw0bzGR4v9qOUfUe7Xrl3L3LlzOe644yiXyxulnfyfLI7jbEARJaXE9/2/G131o1Lu/1ly8803c/755/P2229PuH7YYYcxc+ZMLrzwwg/87Y9+9COuuOIK3nzzTRobG+nr62Pu3LmceeaZnHXWxgmFh4aGJkQgBtW+BxxwAPF4nKeffpp4PL7R375fXp5yMABlz6RPWEzTS+Rdi0HNZIZRZMRRWGwPjXrDJpCCZMylv6xeLFXbpN9Wi36/bkTKnw/svFk376xuos6yMUPM9ma7ldHqkwz9ucKjfZP4eGIIGQi6igpWMaoZbD+5B8MKeGp1Ozs292FYAX/pbGWHzRVFmRH3eXNZK3lhMKd+CNPyuXGkhfpgjOryhPMmcfj5y/n997biqB++y20v/YxExyeorH8agET7rjzVsBOuFLhoTE4X0XRJLOFSKapxqukSK+bh2AZCkyTSDqvXNeBKLaJanFE/SipnM9KfRBOSWMJjZX9d5AybFD4drSPYFZPmLUoEDliTDERcV4GNgO6HXMpli6FqnLjmKwiB1EjqXgR1qUodk4Cs5eD6Cv6TMF36HNX29aHzXlnqFDSdZBDQb+gcsncP9z2kwp4viI1iuzp12QotO0vuvb+F7XMD5AtxBlw1XlpjFYqOSXtTAd0I8L0Q+z8Ocy80Bf+RgeCtvgYcoWFKyZwI6qKgJq6j8/ZwfcTf/fHduimvC080Jvmsfy1Dw6QSRiLgL2+002aVI2rKoqvW4ABBTAQkTJdhJ87/Y++84+yqyr3/XWu3U6fPZNJDIEgJvXcQlCJiwfICIkhTuV5EQBQRUFTAioCCoCSKiMCVKxYsIEjvJUgJLaQnk+mnn7PLWu8fa599ZpJguZbr1Tz57E/O7Lrq3s/zrN/ze153HI4705T1nG8VuWSPIa56dBrv9cYQMYe/imRi+GQyPitG2tnmTYP899IZ7BjWmNpX5OUBk3fBiUeMIxSDwmWGqFGJHB5I2Zz7ceOU+cSV43x5r2G+8/B03t+xzuDDpYF1NFlXUpmAZ9b0cdBb1vHYnb1sO3eQoTU5ghjG4kcWrhVRDF3WWg7b2iUaocV45NImjdd9UHusciS7xTSzuUyDesNhlZ9JlG4A241YOdpOHYmF5k39IwksxG4zHvLcPr3IXXbi5//xAhbwuivIxTiwx6wa7dicKqp09VcoDKZp6zGMRUuLRtndbtYQa1a3M3POGAMr23iUPO0RZGNjZstswaxmeRF+w8KyFV46pFpyk5gEL2X+dr0QJxVRK7vkOuuURlPoGAaSygQMDOeN594O6esv0ba5wuo2fTz2uE9+swhnZhtP3+Qxd/YIUSDxcmHC5GXHrESDq/NYUtEIbOpxjIofs9u3W745FtoEWlAQpudnu8aozcaxHloLXhnvQGoIhWCfHVZj5UxZrS4XpEB25fjJDWlySlOSgpTWvB6rDBktmOsr+mWdQuTiElESNjM985wwkqwOM+w2dy0dx8/na5eNktWCt6VGk3iKJJlU3aFzSpXicIpiJcXsLUb5w8tmLltoOt06q4MMKW0ygM/xyixrmPfoW/7T5qrrFFkFRzYx96HE9iIaFVPY1cNtzN9jkFef6MaSCj+ysIQmP8FzP7O/wNMDvTSkYLryqWuLt667mb+31H7+tb/ZvdJH/fPFuv295Y2zI/0fkhNPPJH77ruPK664AiEEQggeffRRvvKVr/CNb3yDb3zjG+y3335sttlmHHDAAZx//vn86lctzNjnPvc5dtxxRxYsWMDcuXPxPA+tNb/5zW/Yd9996ejooLu7myOPPJIlS5Yk1+21114bJIwaGhrCcRx+//vfAwaW01Qu58yZA8C73vUuhBDMmTOHZcuWIaXkySefnHSfq666itmzZzPR9lq4cCFHHnkkH/3oR7nllluoVCqTrhkfH+e0005jypQppFIp5s+fzy9/+cvk+EMPPcQBBxxAJpOhs7OTQw89lLGxsTds10ajwbnnnsvMmTPxPI958+Zx/fXXJ8fvu+8+dt99dzzPY+rUqXz6058mDFuBVAceeCAf+9jHOOuss+jp6eEtb3kL9957L0IIfvvb37LrrrvieR4PPPAAWmu+8pWvMHfuXNLpNDvssAM/+clP3rBsIyMjHHPMMcyYMYNMJsN2223Hj3/84+T4xsZEMwhGCMH4+Hhy7m233ca2226L53nMmTOHr3/965OeNWfOHC655BJOOukk8vk8s2bN4rrrrpt0zs033zzJ896Uo446alK5NibnnXces2bN4j/+4z8A+PCHP8y8efP+aPBtV1cX/f39k7YvfOELDA0N8dOf/vTPVuw3ySbZJJtkk2ySfzrR6m+3/RvKv0QSqyuuuIJXXnmF+fPnc/HFFwOGiz2Xy3H66adv9Jr1IRmvvfYat956K7fddlvCAlOpVDjrrLPYbrvtqFQqXHjhhbzrXe9i0aJFSCk57rjj+OpXv8qll16a3O+WW25hypQpG4VEPPHEE/T19bFw4UIOO+wwLMuit7eXQw45hIULF7Lrrrsm5y5cuJATTzwxua/WmoULF/Ltb3+brbbaii233JJbb72VD33oQ4DhVz/88MMplUrceOONbL755rz44otJXRYtWsTBBx/MSSedxJVXXolt2/z+978niqINytmUD37wgzzyyCNceeWV7LDDDixdupThYeOZW716NUcccQQnnngiN9xwAy+99BKnnnoqqVRqUkrnH/zgB3z0ox/loYceQmudJIc499xz+drXvsbcuXPp6Ojgs5/9LP/93//NNddcw7x587j//vv5wAc+QG9v70bbsl6vs8suu/CpT32KtrY27rjjDo4//njmzp3LHnvssdEx0dvbOykZF5jkW+973/v43Oc+x/vf/34efvhhTj/9dLq7uznxxBOT877+9a/zhS98gc985jP85Cc/4aMf/Sj7778/W221FWAyyR533HEblHP33Xdn5cqVLF++POGvX18sy+IHP/gBO++8M8ceeyy//e1vWbRo0V/ERnT11Vdzww038Pvf/54ZM2b82dcBSdKgzo4ab+qtM7Q8T1dnlfl9Dda93sacjnEAbC/i9ZVdSAHDVY9t+ocZHMqTdgPeNN2Mi517A8KaQEgQluZXL81k324Dt6jHFIiX39tGQUTs3WjjnTuv5Iknp+Ki2KzbPCfdHnD/8qnUheCwuat5aMk06kJwwMy13L3CwD6qEvbPjbFFZ53nV/ZSF5KPv2MYf1k9cVkcf3GRWz+zBcde/Co/+tRs2ua8ldrKe1qwnDUPsHjXjye83aWKZzx9xWwSRKq0wC9KHGlw2ZWxNvJWQM7ykbE7eqyYZslYO31OHa0FY5U0W04fSXDHQd3m8cE+8iri1891kVOw+hVNKDT12Gt8UM0kfpreWUIrEXtEQxo1Jwm29NIhoW9RKbukUwFj5TTjvsc2Mw1LTHksRbcX4mZCnJQibEjSPSGX3zODj25pOOAXL+4lbUW8MtLJ9XdJztp2JQ8/N53ZXpl5HcbQXzeSoydfZeVQGwqBLbSh9o5XIibGVCgEMzMVHMcEfS4f6AAMHXiojcd9l7kDSVDwtY/PYIs4h8DrawT7B1WeXN5BIOCQ/nWMjGQTjPSsPoOFbga71moum3ePsvPmAadcZSAh3/1QiqsWTufjbzUBtc2AREvohG1m3WiezfrH+MXrMzhmr1Use6yd59f1sMNMkwyoGdOgIsmWXQ3G1maYkimx+34OH7vSeHOvOk5wzQ+n85F9VrPonh4iWgG1noipFscs9pi3lqvvn84720Z5eNlU5rklsinjUe+MV4B682V2nO6z5sU20qmA6e0FKgWzgrNZ3ygHzhasesSsAhUqKTJuwC5zB1i9vCOZs0FVsvnUUZx0hFbwzPIpjA2b90VDmCnw7LKARd+/m5s3Mywpb54WEcbO/xMOmIEeL7H4FptFr0+hx2qwdFkb3VaD7WaZ8fSHFX1slivy1Ov9zE6VOXaP1YTjijDmhVy5pNOwM5UkrhXhRxaNUUneDpJ+qI9Z5JyAkUoaX1vkrIDXC210W34ScD5SSdPXUTHMT77FQ2v6WTkkGInTpW7nW6wcgrVPBHyss8Czy6bgYjzVTehVEzI2O1UmUpJsyqfdjbAsjRPHM5THUigtaMvXkUKzRT7AcjRDq4yne2jM/C+EZpe5A2gtEELz2+dmUopfxQNS4yFYKwI+s/kq/KqF7SqCusUR28UrlsWQ8kqbSsFjanuBoG6TygcMrjawnJQbsvuctTzy2lRuuWwl1x1YIiqGvPJYdzL2Rczyk7Iilr8+hT67Tnuuzq+XzODA/nXJeK1WXHaesY6gZuHlQtatzLPHFgaC96nv9vGF3dcRlTV/eHoKEQILjY8kE7ft9J4iP3p6Jvs5JqA24wYoJRgoZxNYztMDvew+ewAnEzG0PE+urZVw7e8qf8MMtf+O8i8Lyzn88MNZs2YNzz77bHLON77xDS688MLk79WrV9Pe3s7nPvc5LrnkElavXk1vb+/6t05kaGiIvr6+JEnB0NAQ06ZN45577klw1nvvvTf77rsvX/nKV4ANA2o3Bsu59dZb+chHPsLatWvxPI9nn32WnXbaiddffz3x9t91110cd9xxrFmzBtu2+eY3v8lPfvITHnzwQQDuvPNODj/8cBYvXsyWW265QdmPPfbYBJL058grr7zCm970Ju666y4OOeSQDY6ff/753HbbbSxevDgxQK6++mo+9alPUSgUkFJy4IEHUigUeOaZZ5LrmvCa22+/nXe8w1AwVioVenp6uOeeeyZRQ51yyilUq1VuuummPwuW87a3vY2tt96ar33NLOdtDJaz/n2OO+44hoaGkiBYMIbHHXfcwQsvvACYPtxvv/344Q9/CBhDq7+/n89//vN85CMfYXx8nM7OTu6///5kHDSlWCzS3t7+Z2HgzzvvPC677DK+/OUvc+655/7RcyfK/fffzyGHHMLVV1/NKaec8kfPbTQaNBqTX85r930XnpQJVVqT8UZrE/TYVMyEgEUDvYQxDnunGevwq7ZhcUlFcdsYKEtQt9BK8NhIL3v3r+P51b1sljOaxXPVDjyt6cYnbYe86cg6K++yWFY2H78OGfC6SNMThbRt5DdATxQyu61IsZLCV5LetiqOG3HPeC/9YZwlVYf05aoMlLNMbSszVk6TcYME35xPNdj6ySsYefdJPPrKNHaYMpTUt8lUAyTJpLQWRJHgxbEuHK2TrLRv6h/Bb9gJbWYUStx0SPPNqpXg0bVTyClFTUo6VUhZWHTGWW+T5yCZ3T2Olw2TtjfPbd3HJOExyaz+sK4XDewyc11yD61BhRInHdEo21QrLs/WO9inz5yzbG0HaSuiELkECLbpH+blgW5mZMu8VDOsRWml2Ly9gJcOkrobCEpL8RBSE/gWlqV5achg9jWCrftMwHPzfGmZ2ATjQBM8vKqfHmWUraqQbNs7wtLBziSId9hP01z7mz9zCBXKSXUTwgRTP7HSUHvuMm2Ql1f3MKu9mLA9NZ/f/K21wEmFvLiyly37Rlk91EYqZvGZKFpD2DAsRdLS1MoOK2Mmp6m5MsWahwB6u8sxw45xCooJ699eNuDZZVOY6lYJIospfaXEyFORSMrf7CdpG2hTs6zNY5WCRybvE9QtnFSUzMGkrEpge1Hye1VM6wmGqWiZMnCirIp4U+8YWkGt5ia0nEoJIiXpbK8mEJDm/6m8gQhViy6pbEB5LGWoLEPJ+trCxPmilSAMJY4bJfVRkUjmThhKHCciCEyg+Pr902yH5wZ6EmgfwJiMA9VjLLwQJIxSXjqmrq3Z2G5EKhugQhPQ25w7zec02XGav7VmUqK45rtPWhonHREFgiiQjI9lEtz+s412pkSmfbboHyUKJKVyDB9qtDKgbtZvDOWJ8K2mEWm7CmkrCiMZVlazzEhXiJSkxi81ngABAABJREFUvb2VzViIVpsBOE6E5SiWr+mkJ2tik5QW5Dvqybuq2RfN+ryyooeUiIgQTO8pJg5spU1gN4CTCnltZTdtjp/0BbQgZACeE9IzrUxxOE215tAzpcysJ+/m7y21n172N7tX+l2f/tMn/YvJvwQs541kfe/8SSedxKJFi7j22mupVCqTIC+zZ8/eQLFfsmQJxx57LHPnzqWtrS0JilyxYgVgPMFvectb+NGPfgTA0qVLeeSRRzbqwf1j8s53vhPbtvnpTw137IIFCzjooIMSxR4ME8v73//+BJt+zDHH8NhjjyUY70WLFjFjxoyNKvbN4wcffPBGj/3oRz8il8sl2wMPPJB4jt9IIV28eDF77bXXpDbeZ599KJfLrFq1Ktk3cTViokzc/+KLL1Kv13nLW94yqRw33HDDJBjURImiiC996Utsv/32dHd3k8vluPPOO5O++XNl8eLF7LPPPpP27bPPPrz66quTVjW233775LcQgv7+fgYHjeevVjMejo1BYZoJqKpV80Ledtttk/odfvjhyXnlcplbbrmFTCbDAw888GeXf8WKFbznPe/htNNO+5OKPcCll15Ke3v7pO2aQUMNOfHD0PwINj92Ez+MttZUZcsIaBoFKhKoUFItuqjIfGBnqAbFsTQ9Vsug6FQRrlZoBCk35KVfpJn1Doud5q1jp3nrmD1njJqEO9Mwe84YlQm/a5LkWLnqMWvuGDVt82ili1rVwdHwB0/yB0+ScwIqdZeMFdKIGVhkHNQYaIHrRoy8+yS6/3sBe229OqlLKh8kv5t/C6mxbIXrRSiMp7AgLQrSeO68VJh8tJuZYpvKiuUoelRImwjIqYisZZSDMPbMNakULQyNZ1C3CBsWtmc8gkHdJqjbyd9aGwXB1ib5UbPtg7qFX7VxMyHlMS9RtKZHDcpFj3LRwxKatBvQFXNuR4FEAalUwN6brWHvzdZQlZJ6w0YIcDMhthchhFEEnFTr71Q2MAnNhMAXkkAYhbOpdDqpEMsxKwhhw5S7VwXM6Cwyo9Mo1o26TR1JI7Tp6q4i0EjMh0krYZSz+DUthPkd1C2m4DMFn8JompwMKFddbNf0l+0ZmsNmWZqKI0AYStJ2SKTFpHYL6tYED77Ar5kMps2yrijnac/WDT2hF8WrIwZHbtkKy1Y4qZCwYTHFqVEJHBwrShR70x7RpLnVNEDWNyTDhpUYVM1jlqNiHnjiYO4wyd4rLU1PR4X2TN1sbTW2ShWZKWrGUB7q4PWRTtZWswzUMwzUMwz6aQZDk4XVknG72SrJTRAFEssy5Wvy12vNpHkhLb3BfMm0+RvMHScVYbsR2fYGthcl+ROa57jpcJJxk9chbZZPSkSkRESXCulUERYG3++4ZkvnfGNoChML43rRJMXer9n4VTNvbM/kZGgaIo2K8ay7GdNHJlaDJBNyFLQU/ba2ejION1N1Nu8bw0eyal07K0baeSXI8VqQoytVpytVp8NtUCq0Mtw2FXshiTfTrtlcgzm5EgO1LEONtBmvrtksR8XvG0PpmYwDNJEyDEAqfr80Kg5+1aZWdtBKJP03s6tASdsmViceq04qwkuHyXMAOtzWuznSJvDdkopICyIteLnRhuUpph9hMeanKI/9gyCfm2A5f5X8S8ByNibz5s3jwQcfnBQc29HRQUdHxyTlsynZbHaDfW9/+9uZOXMm3/3ud5k2bRpKKebPnz8pkPG4447j4x//OFdddRU33XQT2267LTvssMNfVFbXdTn++ONZuHAh7373u7npppsmeZtHR0e5/fbbCYKAa665JtkfRRELFizgy1/+8p/MYvrHjh911FHsscceyd/Tp0/nd7/73R+9n9Z6A+OpaSxN3L+xdl1/v4qX3+644w6mT58+6TzP89iYfP3rX+fyyy/nm9/8Jttttx3ZbJYzzzxzgyDTPyV/rB4TZf0AayFEUu7u7m6EEBuNXxgdHQVIDMdf/epXBIFR7ib2ySc/+Ulc1+Xhhx9mr7324oYbbuCDH/zgHy17rVbjXe96F9tuu+2fHTR83nnncdZZk5kDXtnu/1Ect/DDmLPaDZLfTYYWMF6dPmE8rLZUjAxlSacCgsCiEZhXSaQF1cimK2UgKlO7SpOyooIJbJNCY1uK4UqaJY5Hz93rmHLatuYeLyyhuhq2jGzadvKor4Y3hTZtO7hUTQ4rtoxsXtE2W+3YYPEKmzGhmVNJ0y0idrCMIVUKXboyNQYrGdqzdZOF1a0R1Fo+jUdfmcZe7/0QXf+1kMW7fjyhXmwy3TSXySf+PQUzxpqhuyODWSxpPIHNxFPNwDQwnrLp7caDWyylsC3FLAwMoZkgrI5Fj1NHCM3IaNYkChvRWHHSMAA5av5ufny7rQa2VJOo8fzIwho3EKKUHaK0IGuHLXpJJ0ioMHVJMDKepc+pUyylEo/tLFHjsaiNPcZI2qLZLhPbQmmBFJou/CRZ0OhQNhkrWoOUhlmpGfybtVoxOf1WnbFyOqlHuejhoKgK0yYjQ9nEY9p8ltKCILSSMvih8TBKoRkZzCZQj/X7rhHYdNsNiqUUltSEiqTdwLAiiQm/if+2fPOcNmnGuWeHjAzmEu50KXTS51Jq6kGrnYu+ixzRSbtFytBtNuJkcRk3SKgaHbuZY8AcSzsh1apLyguo1Fz8yCLjBq3yaoEfWjixYdjeXme8aN4nxZrHzBnjBAM5/MhiVNpISDLyAuQ9M4brVUOdagcRYWhh2xFjZXOfnOfTCGxSbkgjsCgHDs6E/AHN8qw/Rpq/m8eaCdma11lST0rspbWY9I7pSJnEeRnb3L/LDanUXSypqMSB7rZlVhomGn5g6Hqb3PaRkoRKIsZiWk4rIlQyGav1yGKolE2e00x+1eyjJj2qbSn8OCg6n2pQLKbolD5D2kML6FEhCpK5rLWg4ttgXv3J2G2O5UrZTRiatIasMAnaxoczTJRmG9qWQilBGEk8O6QS5ztQWuAPW/iRYSeLlJzENGVJRSrmLRodas2N5n1Ne1nmPvFccaRK8kQ03zuLPM3BHeC/WiRrObxY7WAb/gGyCZbzV8m/jHLvuu4kT+sxxxzDVVddxdVXX83HP/7xv/h+IyMjLF68mGuvvTaBWmwM0vLOd76TD3/4w/zmN7/hpptu4vjjj/+j93UcZ6M491NOOYX58+dz9dVXEwQB7373u5NjP/rRj5gxYwa33377pGvuvvtuLr300sSDvWrVKl555ZWNeu+333577r77bj7/+c9vcCyfz5PP5yft22677VBKcd99920UlrPNNttw2223TVKOH374YfL5/AYK+p+SbbbZBs/zWLFixZ9N3/jAAw/wjne8gw984AOAMRBeffVVtt566+Sc9cfEGz17/X59+OGH2XLLLf9szLvrumyzzTa8+OKLvPWtb5107Pnnn8dxHLbd1iiuG8Pd33XXXXzve9/jgQceYIcdduCSSy7hzDPP5C1veQtTp07d4PymnHLKKYyOjvLb3/72T7INNcXzvA0Mph0eNQHEulFBFQax+jZD10qo4iDWlM1RBbNCoeslOvY8nbTtknVTvP6HH6NrJUQqi66Mm3OKg9CoQyqDrhQ44gM/5o7PdPH1bzh8bG+jmZ/1VDdpbLaPXA7tX8cvCz1sua4d70cGBpXfPcciWaMNB5FyWCRrdEgHXJunZUy5ic1+oQ22RVloLGCXd5X49q97yMaZVnfYdR13PjODnTtHqVRctpk3yOOvTWVezmC5SxWPHaYM0SjZLN7142z95BXoegVdKyE7++M6V9CNCiKdR9dKUK/QvsuHSNsurmXafNWzv0CNrkF29pvz/fpkb5GQHHjg+ezv9PO6XeXEeoZb0z6H+SlUPHfWeuDpHMfPLzD9ojPNM20PLBvdMIHzwnLMbxUhMh1svt/HiZRi2VMLzHPisgKou34K7W2IfBvnn/8qXzjOzINfLnCpSgEluMuucP2XtubU8xdz9SEllt9jFPMVOs0xhw/iffpiqBQQ7b0QhehqjIHPd6NrJXRxENE5nVm7nkTG9qiGDVY+dpNpt9CHegWR60SXRsyH2k3xucOu5Z0xGuYLdoNbPzuXL315hB0bgn2nraHwWopplunj+Y980bSjisByIArMfSsFLjzq+wBc8O4KV93Wxkf3Xk32iglB7lFIFK9IWf2boysFjjvoS3z/tHYevrLB/HmDdP3g0qTdkMatqla/jOjsR3hZwtsWMPoLEyP0hxV9pFVILbTZ49FPoysFsGzw62hllEOR7YJGhV+85fsQwh6zBui/4zvohjE2da1k2qNWQo+uxpo134yX8hgibd6/qjSMXrcMxoexD3g/qjgCWqGWPI21Q7zyGjTQjSrCy6BDHyEkT+97GVvuMZJU/4vPTOWgQCA1HHrgGhqDip+/OpN6rNdNb7g0pODdd5yIDhuIVB5CH7wsemRl0oaiox9dGUW09aEe+gV0doEX5wfY46hkfsj2PnRlHN2oIrummbkSzx+Z60SVx6BWQvbPbc0Vv56cI9J5iOEuJ+//RY4QKaqxufW9xmo2cxzahcvXz+7BOuhdiPY+1IrnIduetInIdJh56tfid1IBXR0Hx5vUP7hpdGEdenAlpDJYW+6R9A9+DZFpR/s1kBYIiX/VJSDN/Ln35hw7b7aOJ5b2M8cro5TgGZ3H0dAdQ2iUgIM/047zvotQ1QLCTaMLg2a8ACLXBVFA8KMref7bZVYJj5oUHPf4ZRDFxq+U6HqFaPkfsGZsY+qlFRfs/UUuPCnm3K/UcE45F10aTp4huqYlOLHqBRdx46MzEMCpv/2YeacICx3UEJ6Z6yLTzmN7f4UtthghbEhWrOxECI1nmxgKMIn2vF1mogsVxp90OfInh7FJ/vnlXwaWM2fOHB577DGWLVvG8PAwe+yxB2effTZnn302Z511Fg8++CDLly/n0Ucf5frrr0cIgZRvXP3Ozk66u7u57rrreO2117jnnns28HiC8UC/4x3v4IILLmDx4sUce+yxf7Kcd999NwMDA5M8vVtvvTV77rknn/rUpzjmmGMmeXWvv/563vOe9zB//vxJ20knncT4+Dh33HEHBxxwAPvvvz9HH300d911F0uXLuXXv/41v/nNbwDjsX3iiSc4/fTT+cMf/sBLL73ENddckwTIbqycJ5xwAieddBK33347S5cu5d577+XWW28F4PTTT2flypX853/+Jy+99BI/+9nPuOiiizjrrLP+aLtuTPL5POeccw6f+MQn+MEPfsCSJUt45pln+Pa3v80PfvCDjV6zxRZbcNddd/Hwww+zePFiPvzhDyfBuhPrMHFMqI14As4++2zuvvtuvvCFL/DKK6/wgx/8gG9961t/lKlmY3LooYdu1Ph74IEH2G+//d5w5aRYLHLyySdzzjnnJHkLzjjjDLbddltOO+20N3zeV7/6Vf7rv/6L73znO4RhyMDAwKStCRX6c0TXSubDZntGkagWzAdRTfgdfyBdy6YW+jjCMsrW+Fp0vWKUL8sxHxbHNb+BSCuIDQ8danRooCQRGkdDo+aQQuBIhbQ10tYIKQibLjkpkiyuSIHSGhUfsyassGhA1VqeTQCrw6IsTWKcemioLDUkMKNIt6AzSgujZKSyoJVRWpp/RyG6OGw+sEEN17Kpho2EhQmtELkuc76bNkqKZSNs12yWjdYaGSPTHUwd7AkLRJ4GJ65jIuvPoya4W6tEUdDoDc+XEqRA2BZISYiGtGc2DKwpFBCgwHFRE++BOSYsaRQGHRklx00bBV0psBxTT6VASvwoRArL3EdaIC2E7ZpySsuU1bLBcggmPCuIAesifqblKeraSjLeEgVmbDaq4NeMceHXQEocBA4C7YdGBVSmXXTomy1qrRDoKATLxkFCECQUpZNEKaNYRWGiZOLYCcTBRSUe+kkg++bfQpp2t+yE4z0KpFHo3RTCTYGK0JVC0jbmWDr5rWslhOWYdvMb6ChEj68110ahMUImjjGtzL2a3Z+SyJREx1V3tEYJk3gJLQgE+PFmYTj69dgAVArosTXo6jh6bHWrWvkecNOIfI9RlqMIgsAYAaGfGPZEofmd7TB1rJUQ6XyisOtaCZnrjBslNHNlYruEDVPn+B1jC2OUNDetNRptxpdS6PIoemwA0d5nFPpMByLXhWjrMX2wHgxDSAchndb8iOdOs7+S82wX3ez75rusOZfSLiLtYmmNCgXhhNVeKy6nQCMmjG/dMP1l+raILgyarV4x4y0wWa5DIYgEybjVUYgOfNPngWln7ddAxfkDHBscG+HFfb+eIyF5F2MMjeY5Qlgb1BkpCbTEySvcnFlBmLj6BZh2j8d8Q0hTln+ENN83f4vt31D+ZZT7c845B8uy2Gabbejt7WXFihV87Wtf46abbuKZZ57hyCOPZN68ebz3ve9FKcUjjzxCW1vbG95PSsnNN9/MU089xfz58/nEJz7BV7/61Y2ee9xxx/Hss8+y3377MWvWrD9azq9//evcddddzJw5c4MkWieffDK+73PSSScl+5566imeffZZjj766A3ulc/neetb35rQU952223stttuHHPMMWyzzTace+65ied6yy235M4770ySJu2111787Gc/+6Me32uuuYb3vOc9nH766Wy11VaceuqpCf3m9OnT+dWvfsXjjz/ODjvswEc+8hFOPvlkPvvZz/7R+r+RfOELX+DCCy/k0ksvZeutt+bQQw/lF7/4xRsmf7rgggvYeeedOfTQQznwwAPp7+/fIHfAxsbE+rLzzjtz6623cvPNNzN//nwuvPBCLr744klMOX+OnHrqqfzqV7+iUChM2v/jH/+YU0899Q2vO/PMM2lvb5+0oiKlZOHChdxzzz3ccMMNAAmFZ5Ptp7nCc9hhhzF16tQNtltuueXPLruuFsw2PoDIdEClgBpdbT7OtVLyURLSIeN4dKZyjNRjg6BeNUrB+Fr0+FqQFro4YjxVUtJmpdBFkyUxqkJUhTw2mZh72rYjXC0YjVpKiqo0yAsbH4UuN8hi0UChKw1ywiYnbBooMtrssxBktUC4FmkNRWFTFDa6rhIFOtICp11TlhIvHeClA3xltYIBtTCrFaNrEs/jxL+JQvToGmTPbDKOR1cqz1i9zFi9jPbrqOHlrfPb+9ClYVRxEFUcRPs12qwUGS1oEy4WGidWarNKkVWGh2ZMgvaV8cRZjnlmaRghLPNhbhoZ+R7w6+TtDLa0jMLr10ybxx963fDR5QrUa3RpGzU4jhocB6Av1OSUxsOCcgkLAbYJdnSciLTSqEaILgwiO/qNR3Z0DaK9F9Hei64WUMVBRNd0dHmUvJum4JdJWxP6cHyg5aUuDaMro+jSMO1akvECMl5ASlhQrRrDDEF1xGV6e4mq71D1ncSTSr1iPPaxEqnLo+S0JKcluhaQ1hCOK+MJDhpmi9sEv2Y83aURssJG1xoGtxyI1vGmUi8lBD44HjqooUfGyfb6ZHt9RqWdwCqQFiLbbuZHtj1RdoVlo0vDdKqIhhCk2gLTVqNrUKNrEG096Oo4amyN8ZBXzDGR6zTtUzFKK7YLjbgO9ao5Z9oW6IbxkqvxAdMv5TF0YSgxZFRVoaoKu8smE3/aOwhQdU3YkFjaLNXbmMRTNSmS1RjdMMojjbrxeFcKqIEl6LHV6Gb5OzphykzE1M0QUzdD1yut+VKvoIZXIntmJr+TvxsV1MgqZO8sdBSauVKvoMYGUGMD5vpYYQfIYpPSGleDqyFnebQJhxQW+M3Azwg1uhq9bqnZxgdQg0vRxZHYe183q4jSQqvAbIVB8LJmrhRHTF9LaQylKDDtmu8x78LSMDQq6PIosqsNPVZBj1WwgVRHiMbAb5QWFCwoWobtKi9C8joErdGBbxR8vwZ+PTYUJIQN84xyFdsyybykxozbsLXpKEyMHh366GrB9GsUQRShgyAesw102EAHsZFUK0GthNXhJn0uMu2QbUdk2hGpvPk/046uV0jJiKgmCOuxp15PNn6zWqLLFYRr064DKI//2d+Wv0qagQ5/i+3fUP5lYDlbbrkljzzyyAb73/e+9/G+973vj177uc99bhJ9Y1MOOeQQXnzxxUn7NobHPuKIIza6H9iAevHtb387b3/72zd67tq1a5k/fz677bZbsm+XXXZ5w3sD/PznP09+d3V1sWDBgjc894ADDuChhx56w+PrSyqVSvIEvNH9Hn/88Te8/t57791g34EHHrjR+gghOOOMMzjjjDM2eq/1r+vq6toAprS+bGxMzJkzZ4PnH3300Rs1npqyfh+CCVCeKFtttRVHHnkkV199Needdx5gYggsy+I973nPG977jfpriy22mJTHYNmyZWyxxRYJ5Gnp0qVveM+/VGS3oc7cGCxH9m0GRbO6o+slxusV0rZLm5cxy8uWYz6mTSWhsA6RbQc3ha4UqCgfkUlTFiXsNvPRqBCSxiKIgwOLQpEXISqMAw3TLhUiOnAQGZda83fapRr7RduxKUsLkXaJ0AQChGNRE5DXceCir0lpTaNuk3UCGiMm82wzQVXaCpNgYEuqBFajxgYmwXJUYRDR3meUq/EBCo0qKcuho7m07WUQqXxiFKjymIEAND1qQlJSDcqWoqQD6jhEhATCZBoFqAvIKxC2QOR7ElhO8zcYWI5o60GXRxGZDiphjUgp41WH1rlKIRwHUilwPQoiQuZbK0cFy3hGFRo8z/gaQ0UQmHYJhEDYEtJ5dGHIwHLctIHXAKK9z3hoR1cjumfSiALa3CyVoGYgNBjoga4UjDc19jripqgKTTXGDEd2A9IpoIKtNV4uZPVAe4IbFm09RuEB44lM5xFBA10eYyym8pPtaWoC7A6J8DIt4yYKEV5MbeimIdNOUQeItjagYRyRcbs1VyAASGVM+3lZRC5DfbwMQG6i9y8KDCynaQzE3nMd+IhMB2Uh8bTGr1rI7hktWE55DNk7O4HlyP7NE1iO7DNODFUYhHXLIN9mvN/9myewHDkBlqNKIwYeFU6IMYqrEBVDKigCIShqBysncaqGvLMZ3+spDRLk9DehwwZyAiyHJixHK0S2y8Bycl3oUhHsAXTF4Kqsubsk80N29k82jusxPCxW3lV5DDW0Atk/18yVCbAcVRgyBmvsNR/XAVVpU4/rU1E+JRkihYBc1njp890G6jMRlpMyqwXJilu+B10rtuAw+R4Dy/GyiHwnul41Rl3s5Ra5LnS1YBRh2zVGnMiihguIjOnjhhD4ZQtL69jLDTkFjoainuAtF8LAkaRsra7Ec13kukx5uzvww5Lx+gvi1RFjqInm6pDtmlXAdD723GsI47EYxl5pN20gfPHKB64JeI3GfTQQEjtwGhWQDrpRhnTs2Eyb5GGRLww7kBZJrFBTakIjsml0oUIdD9H1xlDRTfLPI/8yyv3/ZSmXyyxevJirrrqKL3zhC//bxdkk/0P56le/OsnYqlQqLFy48M/Gw/8x+c1vfsMll1zyd8mc3MTH0oSk1EqJ4qNrpdZHo17CtWx8FdIxAZYDJB8wDZNgOaFW4MaBZjHPvQICNJYGv2EnsJzm90xIQaQ1WmiIITpKAPF+MB9QW2ujhNKC5Uz8LFk5SVUKXC9krJg21IXQYgSa4KGKlEyUAl0tJMpJ8nd5FJHtQJWGcaRFPQrw7LgvtEJkOwwOOp03/0+ASwCTYDkuiiiG5TQZDlPaQHMAA2UBo5Q0fzf/FhK0gf0oNGrikrxlT4AexEvwtm2gMDEkR6KpCfAAn2gSLKdp84axoSS8LKo0jJCW6c/yWLODYshOzDGuIiwhW7AcjEKdjCvLBmHgPI0JIKCJsBw1AZaTtWOFNcaWQwyZiI2cJiwHQPst+A1aGTiDlC3sMi1YjoWAyFADivUUGMAoSk12DSnBcwl9056p9WE5WoGw0ToyqypxubBsGlLgKd2C5aTiIOPKeALF0U1YjpdF6xFjLADCjo2tCbAc2bdZC5YDZp5WCy1YTlxXmTLli8oxs4rWREIYOJwyYy22n3GIYWljAwbfXSuZelXHkzEkUh1GcdQdBj6jFYQhWLH3PIbf6Gqh9bs82lKuwfxdKSAz7UTlUQPLyXYkdTf9E7RgOUEDaz2Cg0grNNrAy8IIXR41fZXrRDSV1KBhjMHmvRKolGUgOWBWVpr9JMzcWB+Wo2pFM7Ks1jWmwWK2LY1RgkUc4I3A0Qaa06TGRQvTpo2KWfl00wb73zQQ3bS5bxAaWA4xLCfwW8apkGbcRqHxxNvmnRqiIf4GCHfC2E8qIZOyg5lXUsdju/mCnXBcWCZbr5NVWK4J2JdCx7Szzfe1jt8nwsBywk089/8XZJNy/08gH/vYx/jxj3/MO9/5zkmQnE3yf0tmz57Nf/7nfyZ//6kVo79Ebr7575fuu+l1p1pAZDrM3+Ux8/Ft4j0xClvG8RAIA8tpVFuwnKYH0XLQo2tiz5ek3Uqhx4sJLAcMLMdBYGvD6OBqwXjkMjspj09epIwiWPXJi7yB6FQa5GOe+wBFRgtUqY5FGykNwrVIaSjEypaqK6zYKxYoiduuqEiJ65mPol80eOqEo79RQVcLxtPYDCJu/j2wxMBUOqeZgGIhGasbr64O/BjG1GaW8btnEK15OWlfkcpPguVIwI2V2qZHuGhJRizQvjarH7muFiynqcAohS4OI6dsBqFP3s5Q1JXEu62LgyZuwrLRDR9RLoPj0IWNGm7CxdqYEmpCASnLhmrFKL1SJMm80nWNboTo8QFk57RWoGFzNaNWQlfHEd0z0dVxck6KsUaJlO0mCkQTxqPrFQNxAAjSdGqLrGc8tKloMiynNuYwra3EaCmTPId4XGkVmfYIG1CvkNPxc9aH5agIIsy5QTxuowBdHjOwnEoNC8co7c1VAa0gUmbMxp547dfQQ2Nke8zzRwdtuqw6RMbQEbnOOL7ES+onbRc1spLuKGLIsk2+gmY8C2YlQg0tN8w8qTYDf4mDbFUc/GtgQa7BtjdhOWMtWA4AjYpZSRpdYxSgZjBu1YylFixH0U6IqmuihkTo1ge/KmQCyxFt3ehGDZHJG1hO2BxPI2bVxo/3dXRBzzSzMgdJXIrsmoYaG0BXxpG9s83v+J0ie2aaOlcLZkUwCs1c8bKJAS27pqFG15g2yrSTxyatdBIb0WalWrCcehyEqyMojqCbBmesTAvbM+POr5t+acaNxPND5M1qkC6OQBga+Fu82qSKTRhawQSd2h5aKWRXHjVgnuPgkmoPUauNQ0BpQUGaeJlZcf6GZgIvHfgmuBcMyYATG/xhw7xrSgaWQxgr4FEwySilCcuxXfN+bVRJaxM3AqDDyBgsYQNt2egoMM+Kx9skWE6u00DHhDRzuem8qVdIWRFRQxA2pIEaMVmyWkK5irAtA8spjfMPkU3K/V8lm5T7fwL5/ve/z/e///3/7WJskn9TEfluAHRppAUXKI4YjPmMrdFja+Ljw9RCn4zt0ZNuN17XKZslxwCDa23UjaJUKyd+2oYggeUEKFLYxqtkacpCGW92MNlj146dBJi2YU0KNs1jM2JJhGMUeV9AMyNUD+bjF5UhqzS1ikPODfALkqxS+A3z2nOkShJuWVIZz2NxGLVuqYGeYDyPamAJsn9z1Lql6MIQCo0tBH2ZGBIQNoxH0nbRQQM18Lr5MDcV3XqJSCvqQuNrRSM2boxSa6QoY899DBdpxiwYOMyEoHcp0cOrIJOnHjVIWZ7B84LxyFUKRpkJAmjLxe3dWuFoem4DIUgJiW40SAkLVQ0JAuPdV4AqhyagengFIttpfg8tN+Ml02685OuWIrqmIYSg08vTiHzjVQWDcR5ZlbDANANWA0FCy5myNUiJpwU5ZTjPmzSMzfo0vdzCstGRh/BtdL1CKc4KK/IpqgLsLtli1WkG8jY93aZAVHSIyGaQhFiObhkOzQDBKDDlrBbMypXnEFTN+HInBm+XR9H12NPd9KwCOvYQV4VMzhe5rlabDK9C5ntQpWHU6GqszXcx42tklVE6MUYRY4OQiSFfUzYzxvPyF5E7GyYuXSsZj7tlg/KNsk8LBRaNh4RxUrGGbvGrTwywk4CtQU6dhw5qRqn1a4iOqeiVMRS1OX6DBkIp9No1iEYDHbNtyelboctjqKHlBhJWGESteRURY+gB1MASY7yMDxCtfB45ZfOW9z5m2FLDqxKvva4WqBMRCDsJBtVaE6DJYBRa0nlkex/R0IqWoRE0jMLquCbeI4ap6OJwshIhu6ajR1eD45lxNbzWGAG9s5P6qvEB49RQyrAISccYxq4Zsw0hCGuSnFIJLMfBwHKGMMq7kgJdLCfB+c1A3aaR3lyFEimHWhDhxn010aOOtEyHKmXqZdlopagJlbzniCJjRAW+6Su/bv6O6xuN+sk7RheG0I0y2nJMLEETUuimqUdWEjjeFNeJqASmPH7Tg1+oEJEH7x/Ec79J/ir5lwmo3ST/GFm2bBlCiA0w5/8K0gxaHR8f/98uyp8l99xzD1tttVXCAvStb32Lo4466i++T+Jd9CbCclJGkawWjDfM9kBIXMum6Fexm7Cc0dXGw9hkRBESUhmElwYhibQ2+G8MBl755kPho5AagsAihSRjhQmLDbZheFEAUhLFnDDCkgQoAhQKHeOGjQag0KhqHFiozeb0SMYtQSbvU/YdkykSkqQ1TV7uJgpA10pmaV+rJHhRZDvMPdctRU7ZDB3UsISkHNQntaHsnmG8azEcQThphBtvtodCGw855qUbrcdQk9aQUYCiBfNw0wZS0NTOvKzxNALYBk7TUH4rUC9eLTFKjgMxW04DhfBchOfiKU1RCiKgoRXC8whRCHsCREkIhCtNXZoKc6yoNOETBk4SmftHAZaQBM1zLccoSFqZlYQmHth2DRxLKiypqOsQhDDMPULgpBUVZeNakcHdR0GLcSTwW6tIlo2jBY4W4Ic42qx4GA98YMocNFpjMmYX8oRE1+pETE4cRTzOkvrFEAbhOHECLomn44zNiIQiMekLx42haDbYHg0hsHScpblaSJhjtI5aDDkYmE4CTYnHW3Kfqomd0KOrDU3lREaddL7l4XVTIKThJs9IrIxMlHwXZbzf0oz5xgS2nGaGZTW+Fl0aNUZF0Rj3zfEkuqchvByya7ox6KDVPkolqw5EoZkrTYO4UTG4+FxXMq9kW1+ivMruGQm7jsh2tOqSypqxgzBQrXiLYhM4QiOkhOKICfDtmYFo60O09SG7piM7p7UgU46XwNREKmsU7RjmJpy0geQ4jomxiOeXYSEyRrmwPTP3mnh910K4lolViQRBDMsRwij2Uhuok4PG1ua9pP2aYclpVKBaMPSbhXWJManDCEvoePzTYg1KxrFK2k+HZp5rSJivRNqbwOhjxQxdXsIOpJWhCE6UPMuZ9J5owsgCJF5bRKotNLFHQqOUSJLJmWstsC2qIo4z+UfIpiRWf5VsUu7/BeTAAw/kzDPPTP5uKuDNzXVdtthiC774xS/+0eDcv7dccsklWJbFZZf97dJKg1n56Ojo+Jve8/+CnHvuuZx//vkJ9eipp57KE088sVFKzj8mujJmtrHVhsUjZs4h9jA12XKQkpydYkqmk+F6AV03ypYuj6LHB9HjBsrC2CB6dB1oRZt00YUiWQWqbrYsFnksg5u3DaPNkPLixEcCVfHJYagVdc0ni2U+9BWfPDZ5DHbW0xpV8XE05LRA2Ab/WsWiikVUVKQVhL5lHOLdmoIlSed80jmfirKJYtB7pCTUK6jBpYiO/oRxQo2sNCsbUWg4p2dvT9py6Um1U/JrlPyaYctZ+2rMGjQQB6IOoscGzFYdp016eBrywsZBk4pV/Yw2rD+OhmFLo+q6xYldr7Q8+FIaj9v4EOQ7wa+RtzNkrFSiGOqxAaN01StQraHHi+hqhW5tEQ0XiYaLKCGYEirySpMSFrpcJoWFDltKd0YponJo4EH5HqNUj69FZDuNF79SiJl0pqKrBdqcLAW/QqrpNdfKsCtl2k2bFAaNB7U4QruWpNyQlBuSFQ66XI2VI01p0GNGW4lKaFMJ7db4alRM3cOGKUtxhAyCDGasZDREZZ3kGDBbLVGGm9CgFBY0AmwUQc1qKdRRDIGBFqtJo4IaLpDpDsh0B4xZhqKzSXUovCzYrlG0G3WzSYkuDNKpIrMy0haia0XUyCrjnc91JWNEOB66XjKQm1QeSmNQGkOPrTNzshFDN/waemwNondmiy1nZJWBnpRHzXiLDB1oWFSERYXVZpHVkghBh+WjqhDULLw4rsPTUJaSuhAQB8cmCqdfM/sqRfTa11Hja2PWnDWITAY6e6F3mtnqFeO1j+eLGlxqoFu1Emp4OWrYHNPNY219yVyhXkGNrDTzq7PfMCqNroYoIIeFpxU5ZVid8jJFLn5n6HIr7kKvfR01uNRsA0vMHCwOIlJ5o1TH7DtN+JBp97QZV+NDhpEo8FvsNOMDiGynOV4aRteL6NIwsj2LKtRQhRoOGq/NAIaaMTvjEirSGEyO1rhNZbLJYtWoGCabpvh103elGpY07z9joNYnbYSNhL2J+D2bQkLDh4afxJvoeiWBcOmwYcZYdRyrLTZMNJDKGkeDl02Mc+Fl0Y0KKRERVCSNcostR4iWcZXWAl2uIqQwTEClyYxwfzfZRIX5V4nQ/5va3ib5m8iBBx7IjjvumGQpXbZsGZttthm/+93v2HbbbWk0Gjz44IOccsopfOtb3+Lkk0/+Hz+ree9nnnmGHXfc8S+6dt68ebznPe/htttu45VXXvkfl2F9+f73v8+ZZ575V3ncgyDgoYce4qCDDmJsbOyf3lh4+OGHOfzww1m3bh2pVGuZ9Oyzz2bVqlV/ERVmZ26L5HfeTSde6ZyTYrxRIRMH1HqWw6tPfM98rMqjTDnoXHpS7ZSDanJ91knjSptARWRtj8euPJzjP/kkCw5rcMOvTJbekz7moGt16k+s4eGnpnHgewosu8PiDw3jHfyDG3HRf6RRw+NcfIvH5z6aQg2P86X/SnPBf5i6qtECI78tcPVoL5/ZbxDhSr7xuz7O3Hctax41ntH7/U6OnLaGl5f1kpYhq0mxU+cwa0bN8rgrIwZUCgVMwefg8cdxLZuM41GIAzkdaZGOveSWkKQtl1de/ilqeGWCge7e63Q6UzmKjSpCCDK2Rz30sWKjS2nN6htOJrz7fqw3zWHttUuYesJ0xn+6FMs1r19vigl8/O6TM7i88DSWlOiY0795H1Nm4/1sRD5Lfn0hpLLM2P8sAFK2iyUkEsGB+S0o6YBx1eD296f49E9Mu316yhBeW4RWkHv7Vrzr6yv46Sdm8LUrqhzUMArIZrNHuWZdP9eMPEHeTVMJ6iityTnmHuWgjiMtOr08Bb/CsvsvR1dGIZ1n6r5nAmBJScp2qQYNPMtBCoGvQl4/fnNe+7mpw1YXzeP4i19h4dtDik/VuXvFNHZyC0kGzkOLz+JICyEEfhSStl0EAikEL71/JgCX/aaLT+4zwHUPTuOiwQcAkEIQKcXUrOFWH6mXsIRk9cUHcfaVBc7OFHig0MsnS4/HfWwn+QKmpbspBFWqYZ23dWzD2+sGarF15yhjhQyeE/Lm0cVkHI9IKRxpYUujRFWCGlJInnhTP0Hd4pl1vXyw+IhheQHStkugIqQQtLlZhmsFLCHJOF4rd4OU9Lrt9Dp5Hhp5iSmZTmphg5mZXl4cN1S+rmXjWQ6VoG6oUIG7O7fhMd1KRHjc0QVG7q0jpOb24X46Izh0y5XYBqnF+NIUTirk8JVlapGPLSzqUQNHOlgxHCdtuYz4RXJ2moJfYae2OVSVTyPGsD8zsgTXsknbLkXf5H/I2B5j9XKS4C3jeNRCH9eyydkpBqrjdKfzjNRKrXNsj6JfxRISIQRrPr0X43eswWszz8l++FD0sqXoYpnTv+9zd/FlQhXR47XjqxZGvaF8SnE5/Cgk43g4zfwLQDVsYAsLpRXtbo6cnSLUEctKxqDybIe05VKLWp5prTUf6do1+ftDuRGeHe5m99kDLF/ehSUVs+eOEQWC8piZH9JSfLrqcvfIC2Rsj1BH5J1M0q5jjRKRUhzTszMnhT7904s4acWcx5YmY0VpTcpymJXrY119jLJfR6MZOG07zrrdPCeDxU1jz5hnKPOMgl8hjPvnwrbdOHbHlaBg/kNDpCyHSCsc6ZgVP6Di13mgbyuebHTgaNjGLqG1cXY0qV+3OCrg47/M0IHNR9LjvGNklMWDb8yS97eS2g8+/Te7V/qEv61D8f+CbPLc/x+XE088kfvuu48rrriilVQnlu7ubvr7+5k9ezbHHXcce++9N08//XRyXCnFxRdfzIwZM/A8jx133DFJetWUxx9/nJ122olUKsWuu+7KM888kxzTWrPFFlvwta99bdI1zz//PFJKlixZkuy77777qNVqXHzxxVQqFe6///5J1yil+PKXv8wWW2yB53nMmjWLL33pS8nxVatW8f/+3/+jq6uLbDbLrrvuymOPPfaG7fKLX/yCXXbZhVQqxdy5c/n85z9PGLY+BEIIvvOd7/COd7yDbDbLF7/4xQ3uUavVeNvb3saee+7J6OjoRp8zNjbGcccdR29vL+l0mnnz5rFw4UKgtYJy6623JomsdtttN1555RWeeOIJdt11V3K5HIcddhhDQ0PJPZ944gne8pa30NPTQ3t7OwcccMCkfgMTYPvWt751kmIPcNRRR3H77bf/RUmsXMvGjdlXHOngxAqDE/PaN8USlsHlZtrBNwpeynKQQiabK1vJlQQCtMZCov0oWebVoeFpDqvGc62DiDCSCWRAIpJzmHB+81odRi06OEArjVaaDKKFRyXGsbdFlIRFxg3whYFjBNokbnGtCEfr5CWYtl0aUYBAkLIcUpYTK2OmXrXQN8maYv7upggExUY1UbQsKbEnZDeWcaIrQgVRROBb6DAi9CUqFKjQKPbK1zQwyrwrHYQQyW83VrpcaeNKO1EGUQpbWtjSQiJwpZMomwqw4tpFaCIM7ClZpW56tJTeIK1TC0JkFGUgeb9obRIKCYRh65HSBCfGZW5uTWVGTvxbSiIliGJAtUCgGwaSFQhwnFZGaSeuly0sHGnhShtLSiwh0ZFCRyY/gJDCsJUIc0wgcC0bKSxkDHFqvhctBJEywczNdmve25U2rrBJWWYONOFgGtDawDDWT/AjhKD5r1lXrQS2a9rMtWwirYi06SfXMn3nSQfPdibtdy0bicCTDnZcl7TlEqgQT9ikbIeU7eBHoRlj8XhrKoQNYbZmERt1k4SrmQzKSoF0hdksheVoXGGTsTxSlkPWTpOynKQdy2GdSCnGGiVCHZERpn08YeEJK5kvUkhSlkMjDJBCJPubcK2U5VCLoRyWkBQbVdK2ix+FSV2a7w0Zz+EoEEQNswEQhBBFKK3NipWdYqRRpBrVqUZ1xvwSxUY1GTNSCBxhxcaKhSXMOHItOxmLpp2tZBxYQiZzRyISY8NHU0FRQRFFAiXEJHy6tDWWo5GWMu1qabLYOPHYssXkzRLS9B8xLFACQidjV8TPbraLJSROXD7hGEO0+c+8ExwzhqSNjOtmCWlYr+KXrhTCJBQElI6QCFNHKbEsRVVCVRKz5Jig4OZKXnPe2AgcNyJrTc5wvkn+OWVTQO3/cbniiit45ZVXmD9/PhdffDHAJH70pjz55JM8/fTTnHDCCZOu/frXv861117LTjvtxIIFCzjqqKN44YUXmDdvHpVKhSOPPJI3v/nN3HjjjSxdupSPf/zjyfVCCE466SQWLlw4KaPrggUL2G+//dh8882Tfddffz3HHHMMjuNwzDHHcP3117P//vsnx8877zy++93vcvnll7Pvvvuydu1aXnrpJcBQhR5wwAFMnz6dn//85/T39/P0009vNOMswG9/+1s+8IEPcOWVV7LffvuxZMmSJNvrRRddlJx30UUXcemll3L55ZdjWdYk7vhCocCRRx5JKpXi7rvvJpvNbvRZF1xwAS+++CK//vWv6enp4bXXXttAsb7ooov45je/yaxZszjppJM45phjaGtr44orriCTyfC+972PCy+8kGuuuQaAUqnECSecwJVXXgmYxGdHHHEEr776Kvm88c7df//9HHPMMRuUZ9dddyUIAh5//HEOOOCAjZZ5ffFiLKxnOZSDKp7lkLJd6lEDV9rJB89XgVmyrhYQfZslilfKaimUgYpodzJ40igulApkhY0qhi2qx2oN7YdYLtRjxb+trY4YM3XztDDsDJm0WYau1hDZlNlfjRlQsinq1bphclAaVQxpoInKikzeKBLpEVCBUbuk0JQluJmIRlMRkwZ3XBaGpNK1bDzbYbReSjjsPdthrF6mL9NOu5thtG4wtNHql7CmbwUYZb471UYtbGBJo7x0pnJJ+1bDBpRLqEaILFcM5aQyeN0gJvN2/RC7w8ZDkLFSiWctY6UIVMyOoTVpabypjrQMj7xlJ0p0xk6htCZQATYSD0kgLFShRgcxtlsbVhrLMYF5bqz8NoSmrs3vsGFha7NyUwpqZBwPW1pU4hWdlO2SshzG/TIp2zU0f23d6HoxqXPeyVCKx1LGNgZoKEJUqU41NB51HUV4WAjPRquAzlCxspCnxzPPcWJlvkkhKoTAFbbxvpZNm6S1QFUjsprk3OYqS1PptYQkbbvoag037nsnNgagpfiHKjLKnAqxpU0bDmNW3LZ5n5FCBi/uh3rox9mSFW0x1atCk7FT1MoOuc4GZUviWU4yvwqNKr3pNtKWSzWq41kOrrQpNqpMyZg2sYVFQwV4tAybdjfHmsbYpHk6Vi/T4WURQlAPfbSOMxwDoxZQDxACKmUvDvjUoEjoaN1MhO0pPOkQRBG2sAiIEkMKoN3OMC4tBIJQR4xFdUbDCpXIrPA0DZLmfEnZLsO1Ih1eNqGJHa4V6Um30ZXKMVQrIoWgJ91OLWwknvuRWmu+VcMGulY3YzA2kKhW0BXzzrCFWbkRCLq9tqQPGyog0gpfBcZDLy1SlmdoNGOlNmOnqIZ1LCHJWh4OkpIKk3GStdOUgyppy6yABTrCxaZAyJQ4WFZrQcES2J5RfC2hcTo12tdUVnjx+0AlSnbzvehKO1GubWnhCJsUkkDFRoIWSbs3pTkum6t3trDQlToW5t1iYQxto8ybfmrOEYCy0OiYcKdpaBkyACuh0LWlRRAYyFbKeAMQwsQjNWFHuhaQwaKOolxMkZb/IJjLvymc5m8lm2A5/wLyRrCcdDqNlBLf9wmCgNNOO41rr702uW769On8x3/8B5/5zGeSfbvvvju77bYb3/72t7nuuus477zzWLlyJZmMoaf7zne+w0c/+tEElrN27VpmzpzJww8/zO67704QBEyfPp2vfvWriSFRLBaZOnUqDz/8MDvssAOLFi1in332Ye3atbS1tVEqlejt7eVb3/oWp5xyygb1u+666zjnnHNYtmwZXV1dGxxfH5az//77c/jhhyfJpABuvPFGzj33XNasiSnXhODMM8/k8ssvT8659957Oeigg3jppZd4//vfz+abb86Pf/xjXHcyZ/lEOeqoo+jp6dloMqpmP3zve99LoFA333wzxxxzDHfffTdvfvObAbjsssv4/ve/nxgz60sURXR2dnLTTTdx5JFHAtDR0cFVV13F8ccfv8H5XV1dXH755ZMMuaY0Gg0ajck8xWLoVTzPNVjpsklYg4rQ5TGTNKnJOtKo0LHbKebj6HisXHyboTzMdycJaXRl1ODV3TTUKxz2/oX86lNbcvnXCnx0x1UAnP1sDyksdgxdDukY4nvlbg6vB8zbwrDC5HbN8bHbXbJYfOXddf7zvx2y2Fx6VIXTf2b6IidsDq3bHPz/Slz50zYUcObhI3z71z3sWDcrNHvsO8DPHp3Bfp1DDI9mmbPlKA+9NI1tOwyt3VgxzZTeErarGBnMsu0TXzdt4NdNQiQg4U5v0gP6dbp2/IDxrsVwmeFld5nMsdn2hJt6Yop2YdkcsM8nOdCZymu6wsn1NDemfN7up5M09oO2WdU4YZ/VpD//BYMDbwZsJomcbMOGYdmIdBub7/kRGlHA6md/ZMpWKyVZN6Nf/xja2xH5Nj5z3st88Xjzofzl9xzKcRKrX9klbrhsR0769LNc+9YqK+42bbu41s5h7xjBO+8Sw9mfaTfBrXEfi3TeYNkro4h8D9N3+iCe5dCIAta+/DNTlkYlTiSVNWw/cbKdC99yFe8NTdtcIBrcdv6WfOGyIbb3BQfOXcPy1zuTJDo7PPHFFhbe9gwuOjDsMBcfaVbHPn1UkW//rIMP776K3DULElpDohA1Ysab7JuDrpU4Yf+L+d6pOR66KmTbuYP0/vgrSZ+aiknUqheR3TPBTRHeeh1jd5g8Ds8um8JUt0olcNjj6c8nhpX2awnrjsh3o8tj3HHw9URCsOeMAfp//q1kHCRjQiuTDbVvsyQwlQk4bTW0HAZXYx90LGpwGSLTTrTieawtWskNCRsT+PYlT+/1Rd60T2t18QtP9HNwTSDQ7H3gOhqDip++NpNa7Aif7StqUnL0L+IEe3FeBmE5xliL20Pke9D1EiLfg3rkFwZznzJzw55vnAc68BGOa+ri10zwajMYNIyZXOLxIzv7TfxFaoKzJGi0xrqUnLr3hRzRSFGNg+Wv1auY63SSFzaXf3IKct8jTPxCk9kGDBtNpiMpR5MpRwc1E0AL5plRiHBThp5zzCTcs+buDICqFpLjzXwJQkj8ay5N+ue+H2bYafMBHlo6jXluCaUET+k8joZp8cpwCBx4YQ/2uz5q3qFuyiTCa64itfeCVgQ3fpPF3ynzsspRl/DBpy9qBRdLk3cjWv4H5PStEtapi/b+Ep89JTYIag2cUz9l7h0zbInu1opi7XOf5QcPTENq+PB9ZxgYoeUYFqn4fsJN8cQel7DFVsOEDcmypV0IoUk7IVXf9MkvUy6fPdVGlys8uMDhgP86jPT+J/L3ltr15/zpk/5MSZ/8tT990r+YbPLc/wvLLbfcwtZbb00QBDz33HOcccYZdHZ2ctlll1EsFlmzZg377LPPpGv22Wcfnn32WQAWL17MDjvskCj2AHvttdek86dOncrb3vY2FixYwO67784vf/lL6vU6733ve5NzbrrpJubOncsOO+wAwI477sjcuXO5+eabOe2001i8eDGNRoODDz54o/VYtGgRO+2000YV+43JU089xRNPPDEJ1hNFEfV6nWq1mtRn11133ej1hxxyCLvtthu33nor1gR4xeGHH84DDxhc7+zZs3nhhRf46Ec/ytFHH83TTz/NW9/6Vt75zney9957T7rf9ttvn/yeMmUKANttt92kfYODg8nfg4ODXHjhhdxzzz2sW7eOKIqoVqusWLEiOadWq20AyWlKOp2mWq1u9Nill17K5z//+Un7zj/t//HZDx9jkhatftmwUNgeau2rJhth/OHVo2voTbdRDupMS3cbbu5KIVZwYuV3YLn5EKYyUBhlipVDj4yR0hYq1qH68chpQZvSVCsuOS3wZIS0jVKnS3XaydCGhSrVyZNOfrcL8zFvj4NsdalORrcTAcG6mvHIxhhbq8djzIJsV4MlQ5047SagNttuyrpkrJ3Oho0QIZbUhoEj12WC/FLxxy/bgRpdDVFoWD5GVyf4+u6Uwe7r4nDCYS68LKo4CM0MphhYR7+Vo1NLpogUGRExW6ToUmGSobakLRNUFxqee10pGMYh220lOLKcloLY0UfGSpGxUglFJVqhS8ZwUcPjiDCCWo0ebaFGzD0yuoMyFq6G2SKDXrWSbuGh/RJ6QlKvcKSO69fRhXUtSsRia4wSNky9nTS2tGhzsoxpk50XMMpctQC5LtTAkljhcunWVoLlnS6y6JExOrWkLTJxAMXIpS1OkqQGl7YMmySRWgVdHGFmnFAqWF6iM+ogGNVGmYvCOHNswwQjAyqdR4+spF+kiFYOIegw3slmuzWDaAEGVqIsG+F4RCuHcNKmrA0hsC2F71vo8phRgKVjuPQnGF9qYAk5rSgKQy+ohlYkWVT10PKENUgvf9EwN6Xyhi4yrp+OAlj2CjoIUCOrTB3SeVi1BN1lslOTbY8DaYOEjtMSGpky76qoHNKrbXqsKpZUhOOKoGrmSxNM0pCCQIAeGzBGaWXcGG3+WMIdL+fuDI0Ksq3P8NMvW44oFRExTaeaNq81X7ysMQDiAOEmU44aWWngWu296LHVKCmR7X2GbjZuFzW6hiafO1FILy55FZGJx+M0r41+4dGrbfTQiDH4KgXDlBNnYxVaITLtqMFl6FrR5JwoDRtK3+Y5cbCvdtPowhCsXYFOZ1Bd0+IxawKgyXSY9gW0ZUMUIbLmHnkRYrmaft0gjKThupcmQVgx9rxrQK8bRo+uMcHkbsoESjfHgQrMOK7UyGV8dNnAplRhqGXkxXz0FEehPzT38Wu0aYkuGGeLrjVQ4wPowRUmiH9snRlfzQR8roxZfECVho0RGhtayfs6CrClQljaZOsGHGGC65t+84wW6PESqlilLHtg2cvQWnTfJP+kskm5/xeWmTNnssUWJlhy66235vXXX+eCCy7gc5/7XHLORIw+mCXn5r4/d1HnlFNO4fjjj+fyyy9n4cKFvP/9759kECxYsIAXXnhhUqZWpRTXX389p512Gul0emO3TeRPHV9flFJ8/vOf593vfvcGxyYqxG8EtXnb297GbbfdxosvvjhJCf/e976XQG6amWIPP/xwli9fzh133MHvfvc7Dj74YP7jP/5jUhzCxKyyzbZdf99EiNGJJ57I0NAQ3/zmN5k9ezae57HXXnvh+61Ar56eHsbGxjZa/tHRUXp7ezd67LzzzuOss86atE+MLEF6LtQriL5ZyL7NDFVd7yxk7+yEjxqtGKwWyDgeo0EJ2T0TnekwrCjlCTEJgW+8zG6K4ehBRFsvvqhh5UzdB2iQFhY90iWba1AoKUJlKAcBRNajRGiWmbMeZSIsBDLrUiHOxglILETWoy4MJMKZmkkyvgIEq+r0h5rxgQy9Xo3aoEVfGDE+ZMZmn1PH9UIsx9Acys7+OLtmHhl/8E3W2baYm7oKqWyCr6/FH0iRbUcNLTdtVR5FZDog1QpuRFoMRhXGnDzrdJ2SzrCKBqMyRRCPh4qANCBsYa53WvSjTcVWSAcaZeNd9LIEKsBXIaIjTgff9MwJiejIIzraEPk2RsQ4stMs5deFNBmCBQzoBmLKHMb1ywkPflOsjni1yvFijvkw8YAKxyR5EjHdYBO2IRDGc4pRcAw7RwYRt6Vw04wJRSPmuV9n1xFdUymKEYqW4WPPijDB/8ue2S3PfdNQikJI51lqGSPb3bydwiJwOoRRFps0fW464f8XXha6Z7JON7Bm9iIJCH05ud1MA6O7xwxFo5fFmtqFv8jEwnhaEymJKyKTFbZJk6gmZDkVEtEzg1oT7iM1snfWBIOs33icayWYMtt47v0asmdmQjWpSsPoaWVEYdRQS1qO8eZ29iZJxAgakO003tpYYYu0ICq3YooGRcig8pARbNFTJEWEt7qVVyGttMFi92+OrhUNz32jgmifktRHx8xRTQYp2d9nElnFyrLs6EeHPiLTgWzvTbLOyva+VuK7lOGkV+Ux8LLIjJkror0vUTBFOh+vDpnyD+gGY1bG5K4A1oYlMrZNTSjEtOlmTOY6UatfRscKM37NGBTpPEJI4+luZmWNqUdFpsP0WyprjL/uKmTbEq+4rlcQXs4wyzQVfstB+yFamfqUdI6gJhnCZW5shLox200mXjXSCERXu6mjmzaZb910y3Pf1o2OQmRHG6WKwtGaUMTjtzlWLMfAibJtSfZdoSIaGKpgAGzL1Kl7wtxM5aE5loqtlQRhewmdJn5o6gmQ70EDjaKdZGMGCCOZrKDVhUa0Z5GYOorNtuEfIv+mFJZ/K9mk3P8LiOu6RFH0J8+zLIswDPF9n7a2NqZNm8aDDz44CfvehNcAbLPNNvzwhz+kVqslCvajjz66wX2POOIIstks11xzDb/+9a8nBcs+99xzPPnkk9x7772TPO/j4+Psv//+PP/888ybN490Os3dd9+9UVjO9ttvz/e+9z1GR0f/LO/9zjvvzMsvv5wYNn+pXHbZZeRyOQ4++GDuvfdettnGvMymT5++0fN7e3s58cQTOfHEE9lvv/345Cc/uUGQ8V8iDzzwAFdffTVHHHEEACtXrmR4eHjSOTvttBMvvvjiBtcuWbKEer3OTjvttNF7e56H500OiPLLbww72iSbZJNskk2ySf7RotWf51zcJBuXTcr9v4DMmTOHxx57jGXLlpHL5RIv8MjICAMDA4RhyHPPPccVV1zBQQcdRFubgRN88pOf5KKLLmLzzTdnxx13ZOHChSxatIgf/chgeI899ljOP/98Tj75ZD772c+ybNmyjSqtlmVx4oknct5557HFFltMgu5cf/317L777pMMiKbstddeXH/99Vx++eV86lOf4txzz8V1XfbZZx+GhoZ44YUXOPnkkznmmGO45JJLeOc738mll17K1KlTeeaZZ5g2bdoGMCGACy+8kCOPPJKZM2fy3ve+Fyklf/jDH3juuec2yoqzMfna175GFEW8+c1v5t5772Wrrbba6HkXXnghu+yyS0I5+stf/pKtt976z3rGG8kWW2zBD3/4Q3bddVeKxSKf/OQnN1i9OPTQQ/nBD36wwbUPPPAAc+fOnRTM/KckgX3EOFhdKSBSWbO8XCu1IBFCJgwf1sQkVtBKzCNkK3kQEOgIPI+QapLASmGypkogDCUppMkQ26T5kIJAayKhEVIQaEUkNEhJEK8mKRHDb5IkVqAbIRNNXJkSNIRheCiUU8l1TcaTZgIrrY2nStcrxhtaHjP1JsaXl0cNT3UTsxszT1gTvMnCyybxCnpoeeItNA9VSTAdmORCakI9ALIaPIVJxmTZEMoEB00Ye9QcF0LHLK/H7EZRk60GJiUSE7aV7KujTOIbQKDjlQ6oEybZJnVoVi/AZLEVnm2wx0UDcxFOFlUxqzMi9obqwIQmh9oEYk4Ukcq22tD2jBfOcmigiGK4ha8nOySko2hoSd6NYS5hI6EbxXKMx1orhLBwYv9+k+tb2MJ49ZtY9KjlxSZsIIQ0DEBKEyBMsrQJFKMJfr0plg2uTaNixnGWED9s1VGrwCRUisJWP8V1rUqTcbdRs00bNPHl5TETjO5l0FImnm6USqAwwvYMFKRWNTCROGO0iQWJveFuOsmia7KfttoAQFVbSlEgBNpXRH48R+L9rlYoJVHDK2NvbhwzU6+0ViJSWTOO42RsCGm84XE7ab9m5ksUxF7vrJk78X7AZLAtj5l5VBpO5gp+rfVeafaV40EUYDUDnJvJ5ZQmQhGioWYgOQrASyUrHia5k/Haa0gSNCUrYM0+lRPeT26qlXgvHmNalRDKjFVUZFZzgggZZ6hVAoK6lSSxkkLjKrC1TpSpEA2plOHWrxVNvEi1gG6ytbkpExPQ8ON6CrPiGDRafamUgc8EvllRCfJg2YSilRSQULViTJpjWcoWjC6coBxHYetcYmgQIKQJ6nXSBhbZ9NarCRA9BSaJlRREQph8E5vkn142UWH+C8g555yDZVlss8029Pb2JkmNDjnkEKZOncqcOXM47bTTOOKIIybxn59xxhmcffbZnH322Wy33Xb85je/4ec//znz5s0DIJfL8Ytf/IIXX3yRnXbaifPPP58vf/nLGy3DySefjO/7nHTSSck+3/e58cYbOfroozd6zdFHH82NN96I7/tccMEFnH322Vx44YVsvfXWvP/9709w6K7rcuedd9LX18cRRxzBdtttx2WXXZbg4ZVSkyA/hx56KL/85S+566672G233dhzzz35xje+wezZs/+idr388st53/vex5vf/OY35OV3XZfzzjuP7bffnv333x/Lsrj55pv/ouesLwsWLGBsbIyddtqJ448/njPOOIO+vr5J53zgAx/gxRdf5OWXX560/8c//jGnnnrqX/bAOGGTLpgEMMTp7UU6b7ChpWF0aRhhe6Rtl4ztMd4ox0mDaujqOGpsDWpsjflAllu43TYrhS6WaNOCqApR1SSxMolqjILtaIO1boqu+WSFRYBCV31ywiZoJrQSFllh0cAkf9KVBhZxEivHYMkL0qYgbXRoDAghNKEyWRjLUuKlQ7x0iB9ZRKE0ih4msFIVBpFd05JEMmp8HbJ7hvk4xjjfjO2Rd9MUG1WKDaOEqeKgOb8Jz4kTf+nCIIQN2qwUGS3ICwcJeELiaE0uUuSi2Bi3YlrP0rBRjrRK2l3YXqwEjpqkQYFPxkoZtpCgYRSDUmt1Rzd8KFegWqEHBzVcQA0bI64n0uQUuFhQreAIAVLguhGuG+Epja4F6NKIiTPw6yZpVec0ZGfcNpVRU89GhbTlMtowDD7NDLV6bMAkJ4rP1dVxdHmUDm1oSTNuQEpYUGkFHtcLDn3ZKuWGS7nhtgKEA98oOrGCqyujZLUkqyW6YViYglHVUo6iEB2F6KBmMPFKoasFcsJGV2pYaMKGlbRbotzFmG/hpCHwUYPj5Psa5PsajAoHx4pMhlo3jWzrQ+Q6EW19SeIukTLBw91RRFFapLImw64uDidxGbo6jhofMNmg4yRlIteZJB7S4wOxcRea+vg1EzA5da7BUtfN/UR7H7paMFjqRNk2rC1Wh0UGg7du0yGqqgnrMSQk3qrSoiol1MqtWI44QFhXCmYbWWPiLCoFE0fS2QV9MxBTN0NM3QzdqKJKIzGkp2qChLtnmN+FwWQu4dfQ4wPI3tkQBWauxLkymuNZVwsm0FYp8tiklUns5mjIWR454ZBGgu8nCqyultAjq9Ajq5LEaro8Ztoz8E3ZJxheSfxCFKKLI6bPJlD96sqoyaQbJ4zCr5tkUD1tqEoDVWngaE2mM0AJwwWvtKBkQdESpEVIWoRkmi4GrYwhHoXGOWDbZovfJbpYTqgmAbN/wvhtBiU34Ve6VjKMYVGUbMJNG6W9CesUMkl2ZnUZE9jGQIFE+xQTp5DrQuR7TIK6oIErFVFgYJF6AktOU9IxS5mwLbI6ShKf/d1lUxKrv0o2ee7/BWTLLbfkkUcembTvz8HLSym58MILufDCC9/wnD333JNFixb9yXuvXbsW27b54Ac/mOxzXXcDOMlEOeussybhv88//3zOP//8jZ47e/ZsfvKTn2z02ODgIP39/ZP2HXrooRx66KFv+OyN1eHAAw/cYP+VV16ZUFJuTD772c/y2c9+dqPH5syZs8H9NvaMJqSnKTvttBNPPPHEpHPe8573TPq7s7OTj33sY3zjG99IGJCef/55Fi1axK233vqG5d2oxJ5F4WWMQuWmEkYUUtkWB7pfoxEGWFLS7mZi5b+K6E5DPpucI2aYlQtdGWNpYxg5a2eG5BKsONzhtaiIQDDH6sb1QoI6JktiUwHxHEo6pEu4iIxLSYd0Cxfh2RS18Th1CpcAgUi7JphWaEg5uBpmCqMwGox9yOhYht7OMmtebmMru8zrQx0AbDl9BGlpokDiRxbNtPXRuiWIrIF/CdslWvNyovTpgSXUQx/bshK6Sx0H+JHKg5s2zCaz5huFFEApVjRGGM508Ho4Tkn0sSQcZY0zJfGkKmEC32TG4Gi1XzNBipmOxFMm3DQia4L9RL6HUBve76aXlInn9vUisjnomcJi/SrWVnMBKMkRKtJg7l8LRmHOlgyrF0Fp6o14tUUIZI/xFEYrnkd2TTcrBasWm3t39BtmmZWLEX2zAJP8qRzVjYIG4LioVS8i2vqQ08yql7BsXqXGaN0MhGViFaJvO6osZcyyyfYGrFrTQVfeBIOLdB6N8f5je0YRTLch+jbjFWHeBfYW01l9V53UvIzBFEdh0qbN9tehj+ybw7KohJy1OT4jeLmw5V2ulWKufh9SGdT4WmT3TOz992TFbU8BMC9dYrCaodOto8cHjCFl2SYzbexYUEphzd6eF7xfsJmvjAFhe0nQpy6PmmDTdN4Yv27arI7USgY7DcarWxpG27GXuV6FdtCDKxBz4vgfy0ENLcea/iZjuGhFpCRRHEMfFCNW0WClm6YiLHbtd0H6ZJZDFC8+zBQ1KpFtrh9cCZkcujQOqQyirduUd3AldPYbhTnfaQyO4ig6Vu5Ex1QzP9YtMeV300RrXzXY91hpjta+ajz1lo1a/RKid7aZK17WeLQBtW4JVvOdEYUM6BqDThtD0vTk8uowkadwhIXommnKlS1Ao46OV56aWXrpnWWCerNdiGyX8VDHzxFuKomJEW3dpt8tu8UCJR1DIpDvMaslGEOosWYMEa8QDls2g8vzrLYFO6UCwlDSV1VYgBsr6r6KV85UlNRdZDvQw4a9SeR7ED0zwLJYEaTo0BFlLc34TTzxmPeRX0cNLEFOfxOyo5/XRR0xc4a5T7ligtbdtBmLqQz4dcP2BFRejkjrONPswJKESUsHDROsD8jZ27NCp5nXP4KqRrjrImqRjaVaXvyG0IhcFjVaIMRFTPufwV3/YtmEuf+rZJPnfpP8VdJoNHjttde44IILeN/73pewwfwjpFqt8vTTT7Nw4UIOOeSQf9hz/1nk/PPPZ/bs2Um8xZo1a7jhhhtob2//n91QWpNfqBOZG5pL8tBKoASToQ3QWraXTU+hSO4jbLNFWiUZQZsiMGwNlqMQaZcARYACzyGKf4uUQ4gmRBOgqQuJSLuEaGpCgx8auM6E5CsSkgREkTLwnwhBhEBInUBRmh8y0fTiajW5LeIETECSPXZy263XDk0qS8uZvDsOntug6XUc+CbF5Hutf99mG/8x0crcJ1Y6Q60QtoWwLWNExEXX6JbXGiYnaVLN9rAmnfOGZWK9cdEso5STIAM+ColGNiFFtKAiWhlFJIokUSRb4y55bgsWE2pNqLWBC5jCm//XL+vE8gFYFhYaFW3YB5OfZcodaUGkhWHXweRGSM6dMCYmSiBagatvKM2xtf6cm3isWQ7YeJ+rFiRLCJ3MLx2JJAlZJEDVI1TdlCsEmoAlzYSxJlp9tNFNSINfa86LN1K8mnNdyNZcmnj/N5IkoZr5P5hwyARsKxQa3YwtExPKPbEvJnLFS7nxdptY9mYbrtePzbILIeO5JMGWBPGwUTGcT6k4qRUkY0UjDF5cWpPH8ITfzfuHQqBEDM/bWBtNrB9m3E+qh5BJoO6kektp2JqIx+JE2M56ZWms9z7y5GS4XAMNjo1wbXOvTbCc/xOyyXO/Sf4q+fGPf8zJJ5/MjjvuyA9/+MN/6LOvu+46Lr74Yg455JA/uvrwryrt7e2TchS89a1v/etuGAXGCxTFmU+aWOnmxzBmQpFCTErRbq6NVQYrXnbG0PRZQsbZZUVyG1dYCGG41sEotlEzUyNAFGEjCNCgTIbb5m879keEGJYJoghNnPgqVvDKgVGopWXw1balCAKLdCpgvGyoKAGCuo3tRoYCTovWhzeVn/ShFak8uh57kD2TKEoKYZJTYTzSBudrgVItpg7VonG0hDRwHGnjRBqJmPTyDYiVXIm5R9Mw8Gutj3fTUHBTSfnU+oqKkIbGNIwMbjcMSQsbXasnbW0LsLVJmGQ83RrhWi3FdaKkMhN+Zzd6TKGpq8AYC028dhSasTQB/66jkKywE0PKIYbVxbfTClJWNImSM5GJylcUQ3ow8CMrznJr+iE0jdjETYMpk1YGyx0EhoJyYqbZ9fDKonldo0HWM2pmreHgoAijOBbCTZvzJ7S/sD10FNKmQMXZkJOKYVh7tF+bjNOPArO/yfIThRPK7bRiATKtpGjNezXbVFj2pDazswaO5mjIqZiBaT29saGsJJlb0mcT+w5MG0Zh0n64nunzZtk3Ml9Ept1AQ5p1TrdYo0Smw5R1Ai48uT5+nnBckyFag82EJGTSwUIYRbuJnbftCUZS0wiKDIStqdg3MfZxP5h5FV8X515oKtoakjHepFQ1MQI2OjDvjJTWeKkAqwI6DphpCDOXXcucI9V6CnhcromKdZJYS0X4QhIlhtYEZ0DTYLHsxGjx4vepuaee8L6l1Q6xQePmJuxvMm8RGxYT4Eg5ZazqZlE1TMpYbYF5puPgMOGef2/ZFFD7V8mmJFb/IGkmNGomf/pXkmbyp7GxMTo6Ov63i/M3lZdeeokTTzyRRYsWsdVWW7Fo0aKN7gMTPHzLLbdw5513AiYWwvf9Pwrr+WeQXafuBxiPuieNpzxUEY60J3nYU8LhzuveHmNGS+zxiTuZ7XYzFJYJ4+BIKSR15WMLi6z0uPuxbzJtm6NZueCDfPqc5wG47OLNQGtq//0I9z82nf33WM3g4iyDRfNhfdX2eN+Rw4QjdW59ZAbHHD5IONzgZ4/P5D3vGDFlHamz4rEcT4TtvG3uKlQouHrNVD46dYDly0y2z5qyaXcaZNM+i0sdzPXKjNTTzO03gaGPD5o4hh4VMr29xIcqNbTWtFkpSrFi3vw7ij2HbdLj5iv2NV/CslH433zeo/RbOQajCpFWtFkpVjRGknazhGTRCz8mfPR2KBUoXHMf7aftQ/1nDxGVTftGdbBc+OkLM7lerSIlberKfEibWWQDFJ6wyEiXQlTnd1/eC1Jp9vnP3wDgSQcvPncLu4OSDqnogFs/OZsPfc0kb7tqizF0JPCmS7x3vZlDPn4Pd505h+9e5bN/DIHJ5+rcUunht+EAnVaascjAnNots5Q/HtVwhUWXlWY4qvKrr+6NHh5CtLdz+GcMnExpTbuVZjyqMRqWE6/+U5+cz8rrTWKoWV8+iFPPeJRr3uHTeLnE3X+YwZvcEpWGUR5PZw2uNFSbGk1OetRUwHhY4ekv7gvA+7/4Kjef0s5nF0Q84g8kGUsB2qRRYIqqwUhQ4pkrjuAd5z7Gdd0RTw/08kWxImk3rTWOsMhJk510OKzQY2f5VpdRuh9b18feMwZ4YUUvX3ZGyErX0K8izQoTZlVmeWOYx9/ewdBjkleHOrnQWpvMjbR0k0yqnnTwdYjWGk+2FDqFxhM22zhdPNFYy3Sng7Jq0GNlWBW2sM5Z6bKqMWqSqQnJf7V18XTFQMk8rXnb1+bS+OWDiJTF138/hW4leHv7IG7GjKnly7tIOwFfEIpO6TGi6nRJj2HVoBZD33plmoGowgwrz6qoxHQrT4CZBwADYZlAR7RZKYpRPRkjhagVR9FmpagoH4mg3UoxFtXos7IMR9XkPjnpsco3c9IWFo9+cU9qdzyF3WcgN6lPfYHosTsgCjnx/BfIC5tR7ZMXDsU4k3NOOBS1z7qwTFa6VJSPEAJPWASx1hroKDmWkQ6eMO+6Ztkz0iEnPYpRnZEJY/ZMd8uElvOYbVYyvDTL1D0a3H9XH47WzMiWAWMAAjh2xHUixdP+IFE8NlLCoccyxvBAVGY8qPDB9JZ8eOeVLH+qg0zG56RSyyNuxoHFDKuNAMWqsEghrPL4OdtwxrfNOMhi80wwRIROzgdY55vj35OzmN5fQEjNR4ddHGTMYy+TYPaljWHu2zHFz16YSUrB1laplZk2/n/WlqNc+/oMOpXgYHeMD1QLPL32Qf7eUr3q9L/ZvTL/efXf7F7/V+Tf2nP/Rpldm+I4DrNmzeLEE0/k/PPP34AT/h8ll1xyCRdccAFf+tKX+PSnP/03u+/6mV3/L8lrr73Gl770Je666y6GhoaYNm0ae+65J2efffYbJqf6n8hFF11ENpvl5ZdfJpfLveG+RqPBhRdeOCmY9txzz2XzzTfnE5/4xKRxtb7MmTOH5cuXv+HxZcuW/clg4IceeogDDjiA+fPnbxAj8adkT89wOrsIHAQVVPK7hsKNveUOguje+9BBCPWAA1OzSCHZzM0m53gIqvH1NoLoNwvZp2NL6OjhzurrAFz8+2F0NaI2aFGWkvqQxPct2jzzcdu8DuNPBYS+w7zAp7AoIqh7bB41KDxlzgnqNuWGyzzdYHhVjjCSzIwk9ZKTQEuyVkCoDMQjo5UJ3hWKRs18hPPKBEi6IkJIzf5OPxJBRgvKVhPWY/6uC42FwNMQ3n0/hArVMIrSgc5UOrVkzDEeyIwWDDcx1BhnfPjo7dh7vpP6Z09HK0Hw+8eJipqR5eaD73ohpUKKOUHAvumptGnJuG1WPHLatG1ZKDwE7Voy5ijCB5+ClMOBnsHg2ghSSOooZkUWZQkI8B9czN7a0LhWhivUqw5dVLF+9yAHOf00Hn+d9mhG4mkuVzxmhoJD7H46lWCd04atBe3xx37EacPTgl4lWGPn8O98iHAwwO5zONgysLwIyGvBqNNGw+mLFRCoP7yESsW0Tfj7B9hNtxOsHGFkeYZ2FRGEFo24vvulZybwkrgqaEC5ED5laGB3Ez34z65mhprBQe60SeO6mQSpbmnKTh/RoufY3uqkVCiT1xEHpky7pWOlRwIWJsC76rbTqSUqGkzGSmEkTUZEHGL1kdOCEPMBLTdXIoRgdaadYGAt60Z66LYb7ONMTergICgQ4mEYoiqYFarmnAPIIMloSV4JMt4MHASObKNdS7Z0jPEboklryXCmI2ENiqIynbEHNxIC9dLL1FdrokDRGwnyCoLAQlfM+W3pBo4TsZnfxi6+zTOuw/zA4kXHTcrbrSQjdoaZkWS1naJdt9rJjIMMEoGnBTVLYcdzpWgpZHyPjBaULEVGS3JaMOS00a0thp1c4h1Oa8lYuj3pZ7VqLfV1ErtolG77ju8TPr8E7Ufsq/rJKVhnp+gMYSw2OHMK6iLDkJsnpyUF27Rnm5YURWt1pTmvHARtWpq+ixfGHARtSjDuKKpOb+LW2KIWMCaNquSXJI4bUV8ZYWmzQuIHFhNVA6UE2+CScvtpRoBYCDJxy20uc/iOoieE+jqzLwpk/P4h6WMPSbsyTDpznDR1R9N4/HX2Cs249RR0Ov00hI4NTYGtBYVMDwDtsky96iAtxcF04WkD0/KUyasBsGU6T2VomHlhA1soHFtRaThYQierW4PL2tjGh7SKGPQz7JaesJr395R/00DYv5X8Wyv3byS/+93vEmrDBx98kFNOOYWpU6dy8skn/6+UZ+HChZx77rksWLDgb6rc/y0kCII/fdLfSHzfx3VdnnzySQ4++GDmz5/Ptddey1ZbbUWpVOJnP/sZZ599Nvfdd9/f7JlLlizhbW972yTlemP7brvtNnK5HPvtt1+yr6+vj7e+9a185zvfeUOWIYAnnnhigzwF4+PjHHzwweyyyy7MmjXrj5axUCjwwQ9+kIMPPph169b9pVVktTKReBUdkBUOQgiKqkFWOFhCUotp03LSRc6ba166pRKvRmuZZeUY1X7iQXOFha8jasqnzUqBO5uMsPF/8F+c52wJQPriTxLd82OiWx8ht1Th5hWOE/F60XzgH0tLdjusm2jNGNffbbP7IR1Ea8a54V6XXQ413vZo3Rg8WmRhoY+z9hhGh5rfPdaGEJpSZJT3zfvGeHikj8O3HeFnf2jnQ9OLLFo+nW3nGYXt1891MTPQWMqmWErxul1Fo2kTLqXYe9n824+9f3lhY71pjoEalQ1N42v3lJgiUqzT9fgch9fDcaLY8+dJG0oF6p89ndQXr8b+2dUgJerOJ+hxTds3RiQdW5R46tF2XlJj5IVDQyt8HZEXpj6BNlkju4RLQQdYW80Gx+ElZYwmB0lWOGg0JcvELZR0iPf2vbnv0ecAOLbPR62VuN1gH7IvD/3yPs7bqo/GI1CqG0/3tCkFaiNtPEeZXstjRPsoND2xJ3xUm77ut1IM6QbOdpthrRtBdrWz+J5xU1YUPdJjVPssD8YTj3r6XXuTe+kZAOyD3syrtz+FM7uNjrESjfFO0l6QxEssifxJFJvtwqWkfdaGJZw99wDgiV+/iDO3k8GnIl7X1USpbPYVQEmHrA1LWFvuxKvqJdK5gKCa5SVVTNoNzApLFhtPSNapOhrNyXPibMbjNjvPKPPSq+0spkZaWmiMwRfFClyA5mV/BG+bLrqXVBkrplmuq9S1UbqzwiHUiqJqJKsKFR2YeRWXuaQC8tJhK5njNVVmmkwzqn2mihTrdCNp27xwWBEW8XWEKyzqZAniNs7oCF1rkD90FmrdKPkV0BYzMrlpU5bXhzrIypC6p/iDG1EhYrEDBUJG4ueUZJoBXUNZWZboCjNFJqbTNPVdO2G8F7WfjM3x+DdAh3CpxPXvki6j2qciPEZ0I1F824XDiqicrIToRoa2A7pQo8YjLnp68c4+FvXoHSz9/VIcyxhDBdtiOEbn91gOowSsUTXahUtFBYRo8sJJvNRVHdIhPCoqwBKSduEQak05nuuusGiTDkUdsCosIhEoNLtbU6nGkL/c1jaNJxWZ+RlSixUZK6QtX0damkLBGBqOHbFWKZaqSlJHR0h6henzEd1gXVhhJ6aS29pm5TILxzbjtynNtuiXHhpYo+uMqTrevlvx+BNmVTCLxUpdw4+DcB0hsZCsCsy4/linQxhKbFuxWNZjz70Zs80eei0cp3MXye3DHhkFu4RhAi+KlBlPsw9p8L27Ivq0xbvdChV/45nRN8k/l/zbKvcnnngi9913H/fddx9XXHEFAEuXLgWgu7s7YV+ZPXs2CxYs4Omnn06Ue6UUX/ziF7nuuusYGhpi66235rLLLuOwww5L7v/444/z4Q9/mMWLFzN//vxJLDBaa+bNm8dHPvIRzjnnnGT/888/z/bbb8+rr76a8JTfd9991Go1Lr74Ym644Qbuv//+SZzxSim++tWv8t3vfpeVK1cyZcoUPvzhDyfPW7VqFeeccw533nknjUaDrbfemm9/+9vsscceG22XX/ziF3zuc5/jhRdeYNq0aZxwwgmcf/75CdWkECJJVvW73/2Oc845h4MOOmjSPWq1Gu95z3sYGRnhV7/61UYTT0VRxGmnncY999zDwMAAs2bN4vTTT+fjH//4pD4aHx9njz324KqrrsJ1XZYuXcqJJ57IvHnzeOCBBxLaT4Add9xx0vXPPfccH//4x3nkkUfIZDIcffTRfOMb30i87WAMp6985SssXbqUOXPmcMYZZ3D66acndQV46qmnuPjii7nooov4/Oc/v8G+z33uc9x8880cddRRG9TzqKOO4oILLvijyv362WSVUpx44om0t7dz4403/skVow9/+MMce+yxWJbF7bff/kfP3Zic4BuPcyAEAnC0xhd5Q6OmdfKhVkKw7tvPIwSoSHBy2IsXKMCmLkybNksaCEj7mrHvPMrR/jQKi0tkYgxlsPArlH+/Cr9sU5aS4aVZwtBiimOW8/eopRn/3TDlMY+9aprxe8Yoj6XYra4Yv8so5pVxl2o1zR51xfhim3LR401+xMhoNlGU2uc0GCqA1WYURMtTJngthjfnFHSqkKwVYFuKE+sZHDQWmnqMfXVRSKARo/0dNGuvXULgW0kw7sn1NjIioqQzyfkl0ZcEzjqRpnDNfWglsH92NfY7Tmfs/R9CSCgNmA9+EFgUhwWbRw1OUB04cbsrIZATkJNKiDgTps26ha8jLc2HAuMtt7ROzm+eVxcutdse5J2hYdAorG6wfKQD2x1BLbyLD+mZjPx6Lb3hFDzbKGGlQoqtwwabBWnSIqSmY3hEHKtQ1ykU0CYDKsplxXdW4/sWrruOk+tmLEUIXCLqpCjI6Ul8Rf0Xj9CIz6l+7w6Oqk2l8XKRtUvb6RWNSV7Qk4PWe6PVBimqsoP6rx4H4HA9g8KDa9g6yHJQ2MotECFwEt+rTVlkqPzkCQ7XMxkvlumyfD4UdDJRLK2xiLnh8QxtpDQKZkpDdczF04oP1R1cEdNiAoGOxxeKdXI6/murWDvWR397hQ8V21ETDA4NNEQbMgJXayJib3V8vCYlMtJMjXx2E21INEFsfrhxPzQ/2mXRSyAEFqBllVluJXnO6L1l2t5UorEmYmaYxUKxdixHutjKolpXFofWbbrwGcchr0NKwqYQGx59UciYzLOlU2apn0ueZcd94WgzXwQanywuCgdFhWzS9s25lCbCE4qSTsVzJZ3kePC0piZMX0s0hXvXkdtSUH4lDup+7n7yuz9N/YUib6v1I1CESKZmSqyumtWMHqdKLbQZoQ1XKwKRwhcCa72542lFQJooHmSmz027ZnSEBAJSFGTrPTI/N0alZqBi/hqfTKeg/rKPLcyz147mcaRKlGE7tJiPYDeVTzJQN9+rpu0dajLPPFnGX+PTUBa67nJC1DLyVNzPIs4HUidNKDKUbl/MO2oms7KDpi4ylKXE1iYvQHsUUbBMufJTVvHi8324UvEBZVYtFeDIiHpMmzQu+qi9uoad/AYWGjulqPkOaTcwDGLA0COCvRsWXSpkuJHhvfyDkh5uQoz/VfJvq9xfccUVvPLKK8yfP5+LL74YgEqlssF5Tz75JE8//TQnnHDCpGu//vWvc+2117LTTjuxYMECjjrqKF544QXmzZtHpVLhyCOP5M1vfjM33ngjS5cunaR0CiE46aSTWLhw4STlfsGCBey3336TEhBdf/31HHPMMTiOwzHHHMP1118/Sbk/77zz+O53v8vll1/Ovvvuy9q1a3nppZcAKJfLHHDAAUyfPp2f//zn9Pf38/TTTydJrtaX3/72t3zgAx/gyiuvZL/99mPJkiWcdtppgIGiNOWiiy7i0ksv5fLLL8eyrMQoAuNFPvLII0mlUtx9991ks9kNngNGgZ0xYwa33norPT09PPzww5x22mlMnTqV973vfcl5d999N21tbdx1111orVm0aBEvvPACN9100yTFvilNzH+1WuWwww5jzz335IknnmBwcJBTTjmFj33sY3z/+98H4Lvf/S4XXXQR3/rWt9hpp5145plnOPXUU8lms5xwwgmsXbuWQw45hMMOO4xzzjmHXC7HRz7ykQ32gUkeddxxx21Qnt13352VK1eyfPnyP5tn/9Of/jSPPfYYjz/+eJJw7I1k4cKFLFmyhBtvvPHPTtC1vtziGY9RWYfUdECfzFDSAVXl02dlqMaeN0tIjvjQXHNRKsX3L3mNbWQb6/AZjzHqFR0k2E5pwaEf2ZOfXfAyb54egsl3hZw9k84ffpro3pt57rOv89aZFcZWZ1gZf6ifS1nsv0eWNuAnP5Xsv0eGdqX4+S8sDtjHKIbtwKu3wgspiz1n+uSVz38/384H2iqIMfNRGHo5y1xfUVuu6YkE0oaqALffvPZWv6LpCy3KymIWFW5N+yitcYQkigPHIq1xhTSQJDQpLL5ywnR0GCUBX1+6rsxskWIVDZTWeEKyJBxN2lci+OVp+xD8/nGQkrH3f4jOWxYS3n8zzn/dBUBtZYDbrnjo2S5+Y5VwkNR0iC1k4lmuaRMcmxIWFR2y4Og+RFuOG75hGjYjbBwkdUKmiwxVImra57BDd+TOp1cCcGhfg3mZYbJTQzInvIUbPvEARx/aRXWhpBaaduntK/ObkXZeEXUyWFTjtkjF+IUqIQ6CDA51FF87th1drCCyOb72w9YKVCq+9vVwGIFJ/PW2fbfCedZg3TPHH8wvn3uBvWanmR4WuO/5GcxWLe/lD5wCnpDmWjTdwqOoA9aEJY4+zEDvfv3YS5xwSA8v/jDid7afJEAyzzftVkexIixy2FHbc+eLy3lLvsGSoU5u8AzvvyfMeLUQZIRNCsmIbqCA/Y1ujwIynf7/Z+/M4+yoyrz/PaeWu99e0+lO0iSQQCRhCYgoIA4KA7IojgsoirILzoAMIg6DIOICCCo4rgyLigziKyojiiKKLIJsJkAghDV7d3q/+63tnPePU7duNwmIM+jMaJ7Pp5Lb91adOmvV8zzn9/weglHBjZkogaHZiEQxjxCsDIY5bCDL4Kwym8YK3JTyTLKweC6lhUVFB9SUT7+Vo65DGjqkVxrDpKx9mjrkTU4vj1FhB5FjDB9fK5OPgDZjymZVN0nigCvtNJsauaSuOx5ooWtNCq8b5JlnaxQi2C1VIpszlu3IWApXa36fhqJOMyUiOnWKSRGxQZv34M5OludFk6d1nhfSHk0dmeDr2FhJCUkYt6kZe79tIVD4CV7d/N2GPAUEzCPFEH6y4+Ei2RCVkvN++JYewnUTdB5ijFa5eCcIfIqnvpVb3vp15mmXklCkVZFmxpSR1jnqtmaNruMKK3lm2YjkczpeHzVtArJtJE2iZLenEP8eEPFCOIHCBL6fUp1FKm7Pos4S5Q0OfX+fpvS4TSqyGCyWEQI2lWIHh9asTGme13W82Ni3kMwRxogY1T4bowof0rPZsa9CSkbk0j7fUDOdOBLowyWFZC1NRlWDgw4c5Kcv+Em/jeomzZhXXwJpx2ZjZGJn9lifo7+jhm1HfKnegWztUGEncSJPR+P8XQ+stlM4GnaLAhwrIozae2A9S31WPKABi2NEnS8rnyP5C8g2WM5/S/5mlfuOjg5c1yWbzSZe+jVr1gCw7777IqXE932CIOCUU06Zwd9++eWX84lPfIL3vve9AFx66aXceeedXHHFFXzta1/jhhtuIIoirr32WrLZLEuXLmXDhg2cdtppSRnHH388F1xwAQ8++CB77703QRDwve99j8suuyw5p1wuc/PNN3PfffcBJnHRfvvtx7/9279RLBapVCpceeWVfPWrX02Mj4ULF/LGN5pgs//4j/9gdHSUhx56KPGeL1r00hy1LUx/q6wddtiBz3zmM5xzzjkzlPtjjjlmRrKqlnK/efNmjj76aBYuXMiNN96I6760he84TuIFB9h+++257777+MEPfjBDuc/lclx99dVJWS0O95fKGNuSG264gUajwXe/+93EwPjqV7/K2972Ni699FJmz57NZz7zGb74xS/yzne+M6nDk08+ybe+9S0+9KEP0d/fj23b5PP5ZI7k8/ktvpuammJqaoo5c+ZsUY+5cw3W+ZXg5sGwD33pS1/iZz/7WZJM7KXkmWee4V/+5V+45557ZiTx+lPlkDCOGxBQkdAbms8lC3oiEvq3QEP5R6sREuyC5gg9SK+n8USGSox9rQmI37dEQOPH93FgOEhlfTnxvnq/eAB3chKxZHduqd/OqWOdqEgwyzYGws6epHR/DTulWOoVmLq/gZ1SLPYU5fvMlrOVUtT9WexMxPizGaTQbBcKxidy1GIldaCnTKUqkbbJHun0WZSf1oi0UVJDoekiIIypDt/qp7G18bK12tz6u+VDEsDUj18g9GXiYX6b30+3CpmQ5uXtaM0mp00Ja4MJni1r1O0PISSEd38f+03v5c7THgNg6dwxxjflGAxC3kqBMK5DLgIvtmFDIKPA0qY+U7dtIlWMOEQbr3w+gqY0yl1egcImEuDf9Rj7R2YeVkZqTJay9KkKzm13cbiYTfmujXRHs3HjOINaKcX2vmYn7WKh8YSNrfW0XRnzt4Umwmbkx6NEgcTN1jis2W63jM8dts06CSX4963G981882+7mzd5s/FeaDC+NkeXCvG1lewgHK472x0PZBU0RIqKlSd85AkAXiu68R7bwFw1yGuDtuc+FAJ3mudvs50h/MNqljGLiUmLLtvjEN1p6qnbOHJLt+ptvNfSLSVj6FXN7s1hTTfxTCtEkhXZQbOTO0A4uoGxiW46Mx4H+x2J8t+UkIrHc9KCgdBgoKsSijEJSU3mKEnNUk8z1y7SEWk8kWbMhr5Az6jvqJ2lxeipdJk+1+x8+ZFF/eFx7CJgb2JukMfRmkrTJYizHSsEPhav9QSzdZNhkWK29hgRLgts87xc7AcM2hkWRk22l2nWOwae3qJS7Q90UpdQQCo2dj0psKezomK88wKoS0FvFDJmpZLdHCWgLHuSOdNcsR4dgkgb+In/xF0IV+Ks38ibPJs+7VHVFh0ipKbNWk+LiEBLNtpmbrXWrydIxqcQmf4OBFgKk6lZQDE+oSNSKCHQwLDdThq4g6xhx2vDH1FkOgKC9T4pncVGUaqlTabmljGpYDCSLFJ5atLMnQDoiu8TCpuSlWWnoEFUDqlGDn5dcphoM9goYcY5pTVpHbGzlaYqM/iPbmCfYF4yVwNhU7Laz4QOBZNx4G5H30bWPt+FLRWHhGbNhvHuRTOGrO3mzMIf38COgYcjNNLWhJHEmsacNfGkw56eyfY9HGV5szuT3neb/O+Uv1nl/uXkpptuYueddyYIAh5//HHOOOMMurq6uOSSSyiXy2zatIn99ttvxjX77bcfjz76KACrVq1i9913J5ttB57ss88+M84fGBjg8MMP59prr2Xvvffm1ltvpdls8p73vCc55z/+4z/YYYcd2H333QEDO9lhhx34/ve/zymnnMKqVavwPI8DDzxwq+1YsWIFe+yxx1ZhMVuTRx55hIceeojPfe5zyXdRFNFsNqnX60l7Xipg9aCDDuJ1r3sdP/jBD5LssQCHHnoo99xzD2BgTk88YV7M3/zmN7n66qtZu3YtjUYD3/e3YBLaddddZxgJLXKnPwZVaY3B9J2D/fbbD6UUq1evRkrJ+vXrOfHEE2dkdA3D8E/miW80zEs1nd4Si5jJGIWjXjceyaVLlybBs/vvvz+33XZbcu7y5cs58cQTueSSS142AReYcTnmmGP49Kc/zU477fSK6+p5Hp43k6c40hGOsNDCELHZ2igcloa0MkoZgCNAWBoVSIJS3D6laFoWXjwckQCP2FOnAWW+E1IzC+Nx0r5GrRsiuGc1XxELCfwpgsBiNDQvt7olsFMma2JNSuyUIvQkTSGwUuYlqwKJLRV1bTClTjoiKJtgNmsazaFq1RmwCi5VoRE5c58mGqUha4XUfQclBL6AnFI0Y/xyJAxVXEtBy2qF5WqEVATNmJZTCJpCEsSc1U70YhZ/iKomeLbXrVMZTuH8v19x52mP8fdPfB6AZ15/Oo4boWqm3yzAjQ2LtGr3rdSQUxpPCFQoCGoyUbbABMspYcpoOQKjskoe9EJCyglJ5UNU1ShhTk4RCMPpDmC7EapuKP4KSmFj7pdvcZALQSAEaWWUIWlpAl8QNNuvk0AIslqZRGPxfECbTLKztzcGWjQVz8myRdfcGs+UO+jL1Bmvm3UkHJIkPKZtmkgKQgHRZIz31gIdmvaGQiSQEVtrGjFOOqUMtKG2KmDHAHpnVVm+eRZOAgtpBxoGAvJKM2UJqtKwGBHPZRErPGZuGx+2hSISbYVZAo2NRkH0AgupIZDtsbEwRpqjzTqLhLl/62npCdNegRnr1vrqiEjgPUq0oTHE56ZTIUFgSunoaKICQTClcQZCqtLMEU9LUr5RzJ5PSTJasp0fMiFccipiQjhklEJOoyiVQCVWoPPKwJNairtCJOvDExJPQlZpIkQy93JKUYt3WM38MWuldS1AQSnK8VjZGhpjFkJC9aGYTWe2RrgR4tlNaGYzgYODpqLtZG6UEpLceLyFMNDAaesATP08IRIolK3bxkoUG4QRJLsTEijkPHw/ZqyqW6hQEJXDOP5AsEnFe1rxfRxtDFGpTZ+17tUbBzxPWhZSC3wliaqYNaIliLaRKeO1LzDQppYRVXnBSjJaWxhjKatMELgnTPuqcV/6dYty5GJHZg1b6ASm1IIIWRqqYykCJJEGPBdbKlw7oDUrnXSEJwSO1vSmmrjqL6Tcb6PC/G/JNuV+KzI4OJh4uHfeeWeef/55zj//fC688MLknBcrl1rr5LtXyi560kknceyxx/LlL3+Z6667jqOPPnqGQXDttdfyxBNPzPDKKqW45pprOOWUUxLF8aXkj/3+YlFK8elPfzrxZE+X6YrrS0FtDj/8cG6++WaefPJJdt111+T7q6++OlGAHcc8GH7wgx/wz//8z3zxi19kn332oVAocNlll/HAAw/MKPPF92opsqtWrXpZStHp4/FiEUIk0KR///d/3yL+YLph8kqkp6cHIQSTk5Nb/DYxYeAZLVz9z3/+8yQIefr4jI6O8o53vIN3vvOdM6BaLyWVSoWHH36Y5cuX80//9E+AGT+tNbZtc/vtt/OWt7xli+suvvjiGTsmAG8p7spBnbslCsYGx7z0lIB1DhTiN2ggIDXHQtgCVY+YWgvltJV4O8G8LFoKmQSCMhQjTdC0Ey9bbYNEr6vh1VJUhWTuB/rY+L0RSvELNKs0WglCTyYKpYqMsqhjjSBoSsaiFFmhUJGgUTXgldl9FSYnzBoa2VhgQeQxvs54xNfebnNQI2Lol6b/3xwz9jUjiyYWQymjaE1akmY8ddIaypakLE27HC15w2yBDjWub17WIyNQ0RY1ATkNdSkTzxsYr13UNIw43rgkCCwa6wOWzh3jmdefDsCOD/wbI287id80BdtFUJdGSXA0SV0sTP1GbfMyz/aHSFdQMogb8goasYIwNwgpSQtPCiZfSNMXGrdhGEqUFoxtyFOsN+iNNLVRhw4dUNZmbeYbDoM0edzKsMmxcbS57yYnftnH9Vrn2GQ07Dc7oJgNQcL6B2RSl2HZnhsRxrs7uSHDZMmMz5y5JTRQHksjhFF65oaSXZaZuIrfPzXI5hjZHmGYmCwgp8AbMp3bqYwyOD+IeNa1DOe4NnO1N/aUTsZavJVS1KWgWk7TqUOetdpOA6khsEy9xy2j2r3Gi3h2lVm3u9hVxjbnWZCqcpcuEiITj+z09WFpmNqcpZjxGK7m2JBmhvHlC7ZYZwCT8SNeABktmLQEozaM2lZSv5Y4gKUFnmi/wCu1VGKcDdVz7JwZpV5xqU+E8XhpBp1aksugMzD5Bu5K5chrqApJXkNZmsBggJTtsNmGCJtR27TNe9Ej1QEmtcQTkNaCkiWoxgYLQMmS1AUUlGDKMgxOOW1RndYPk1rix/O2Cbj5iPJQmlxMQ6pC8KcsrMmIhhSMS9P2jqhdH1ebvvUFePH4ZbSB4bVUUUvDWBw3kInb4uh23+e1oBEr/pZue/+fKXeQi+FP0UZJGElyE36yU9KhBaGSZF3zXFFaMBIWWeO0dndM29a0xhLIaigJh+Fni/Q6TSypeVDMxNw7GnJaUJZtliIVygQiZKFZ7dhI3TboK1Ik7d2wqZN5eQPRuS3oSoyM1LRxlECt6tKbamJJk8dBaUHdd0jZps1ezXSQozV+aDE2fUL/OeV/MEPt17/+dS677DKGhoZYunQpV1xxxQyyjOnSogJ/saxatWoGwuDmm2/m/PPP57nnnmPhwoV87nOf4x/+4R/+bG3YErT8NySu627BUrI1sSyLMAzxfZ9iscicOXO4996ZPK/33XcfO+9sUmgvWbKERx99NFFoAX7/+99vUe5hhx1GLpdLAlSnQ10ef/xxHn74YX7729+yYsWK5Lj77rt56KGHWLlyJTvuuCOZTIZf//rXW633brvtxooVKxIF84/JnnvuyerVq1m0aNEWx9bw7S+WSy65hA996EMceOCBPPnkk8n3c+fOTcppQVPuuece9t13Xz7ykY+wxx57sGjRIp577rk/eo9ly5axZMkSvvjFL241dqBF67lkyRJWrFgxI47id7/7HVJKdtppJ2bPns3cuXN5/vnnt2jry9FWbk1c12XJkiUz2tySlStX4jgOS5cuBczORes+LchOEAS8+93vpq+vj6uvvvoV3bNYLPL444/PmBunnnoqixcvZsWKFS8ZMH3uuedSKpVmHP+QX0p3ZLxNYKA4WW0Uio7Y8yQxv0fliHAixOp0ySnoD835eWUOMC+QuoBJCVYaxm1BFAlmpxrMTjXIbafIzTGexp2yZYZu2Mycd+TIKk1WaRPYKzWZrgA/NtDSHYHxcEnjfc50hQxmqnhC4qQjpNCkFQyPFMikAzLpAMeO8LTETUXUhaThOeStgHrdpV53KYiQKH4E9jpNUtooAhVplPp0rNSWpfk/rWBSanSoUb7G7rSxO+0kYVBGG+9sNX5xJsqGMBz2lVKazIAxXNwORWUqnWTlHXnbSfT99GoGIyvpx1Ts+Wt58FLaQAiasfIV1UE1NRll4Dp5Zc7JaNjo2IzbgpKEzvlNNtkWm2yLdDag7jvkix75uSFjlkm2JAVkRZQk+NJa4GoYkYaN3NYwLhXjMZONDYxJRQToEOy5eYiNi0ZLaRLGY16Wpt8CAT07NAiVJFSS3JwQTwjS2QBpKfZwS1QDl+aURXPK9ENOC/JaUNCCjridVdnOrWZpk6ysKUxQYQtG1YKPtPSQFqeXpSGKXbmtfpvuJW2Nuw08m7IItCCIMxy7TkTdd6gLKEnNpNBMSYUWoOPvSlJjuxG9C6pssF2KyoxHJlY+++J1ZmljmKS1MXoGQnO0xjCnNClt1lcxng8WbQOvImPjOV5rjajtAEqLiEbVId/loZVgnmgwx2ogBFhSz4BcDAaasjT3qQrzf28k6I2MEtwZz7+iMobrdJ9tKl4ftXh9ONqseYf2UZKQjw28CYtkrTi0+6URQ1da3uepTRlsV9EoOTRKDtKG3HYKt0PRFUVUpxnOrjaHRVtprguNG3vPrWn1zCnwhDbJvaJ2XyftUSTzuy7NZ0/AJtsiRBIi6ehoMBylyXc1kwDawR0nmb9D27EjhSanNNnWvI2PrvjIabP7NNeuU+ho0ght/NDCjp+5ctruiBX/7+h4zuwcst61WO9ajNg2ATppXypW8ktCUxI6caZAPF/j+TkmNRVhjpLQ9C8s83hUYLVXJIhamcXNOomUwEmbZ0LVkmy3wySLXpS/8K9NbrrpJs4880zOO+88li9fzv7778+hhx7KunXrXva61atXMzQ0lBzTYbX3338/Rx99NMceeyyPPvooxx57LEcdddQWzsxXU/6mPfcLFizggQceYM2aNeTz+URZHB8fZ3h4mDAMefzxx7nyyit585vfnAQ3fvzjH+dTn/oUCxcuZNmyZVx33XWsWLGCG264ATCY9PPOO48TTzyRT37yk6xZs4bLL798i/tblsVxxx3Hueeey6JFi2ZAd6655hr23nvvGcGzLdlnn3245ppr+PKXv8wnPvEJzjnnHFzXZb/99mN0dJQnnniCE088kfe97318/vOf5x3veAcXX3wxAwMDLF++nDlz5mwBEwK44IILOOKIIxgcHOQ973kPUkoee+wxHn/88VccrHn55ZcTRRFvectb+O1vf/uS2PhFixbx3e9+l1/+8pdsv/32XH/99Tz00EN/VLEWQnDddddx0EEH8aY3vYl//dd/5TWveQ3VapWf/vSn3H777dx11128//3v51Of+hQf+tCHuPDCCxkdHeX000/n2GOPZfZsgwu+8MILOeOMMygWixx66KF4nsfDDz/M5OQkZ5111itqb0sOOeQQ7r33Xs4888wZ399zzz3sv//+L7uLcuaZZ/Loo49yxx13bDXnQHd39xbxC1JKdtlllxnf9fX1kU6nt/h+uqRSKVKp1Izv3r+vSSok0xY6VOhQI1wJSqOabQNK2IJ/f3CQCMg+Ch9640bCCYVVFDPO0b5GpCWEmpt/N8g7F6/nvifm8pqiaduP7jeY0cEgpD9T4/dTs5hzrc9Bp8eBo/es51tPzaNHCd69bD3//uQgXQretet6rnraXNulBLsGTQ7YYwM/XDlIb6jZt28zD4/0US+Zx1p3ukmX47FprMCS4pTJTusGjDXMWMztqmBJZQwGoTl2lxJIgfYVwm63Sfs62VtXTc2/PzyIl/CpwCn7bTR9FrddK43MWiabJoCEH/x6kAVBwCO/72Bh5PG7R7sZDEJUbHv+pikY3OMCTl1+EVPvOx6702TjDCYUdty/whb4Ywq3T4IU/L+7BilLOGHvDQCEZY1Mg0wLqmssMt1mZ+He5XM5YnuTxOoPL8xmlvR4eqiH4VGb9+2ynp+uHOSgwSGCpnmxrxrpYU6qzpF7jGJ12mhfEVUVdqcd94ciqivsbhvdVHzvvkEqT4OrOzl1f3OfcCLC7rYgNH0nbDO2v/3VXObaBqL240cGOWyHjTzw7AAC2G/3jTRX2vxkk4ld+cAbN7YxOfFukbAFwpX86jfGMD54+43ctWYO+w5spmNxhLAlWmmENNAJM68lwpXc8ptBDt1pPaue7KMvV2ePPUaS8UGZ/g0mFMIGmQbVhLHnzM7haDmLH1lIoTntjZtmzI9oKr5PViJsyfLbu1kz0cl+s0bp3tkzawlAabRv5sZLrTMrb/rb26xJDQjCCYXdLVF1hcy2ysFcm5bJHFt7TzbBhQM8O9EJExAIyWs6J1GRoNZw8cJ4dybto5TgLTtuwC4KwrLGLgqiqsbKmzKjusYuxv1pC8Ip0zetPGEyK2eulxd9BtDN1t+010hoxqflWlRNhcy2d0vv+M0AGaVoxA6lykS7r9+6aCNvnG2Ma5kWqKaOxziGLNU1VqcFSuOPKOwiyLj/wymF3Wk+e5s1Vsq0tTWWYVlhd1tJG0TalFN9WhPFbvxNmzpYVCjx1PpZdDtNgsji4SfnYKHpdQyGS2vBG+YN8/eLzBi3RNVjj3vezMfRR2zWD3eQtiIiLTj574bQMRRFxH0Z1RUyLZBpYxn9/FdzOHyueV6HvqRrSdh+RsdzWObjZFYPOmyaKKAQfOytw2ZM4vJb9RKu5IGfD7DfrFHCUDJZzuBHFlnXOAEA7hjp590HDhGMhDy4YoADlmzgLyKvIixna3DUrb0LAb70pS9x4oknctJJJwFwxRVX8Mtf/pJvfOMbXHzxxS95j76+vpdM4nnFFVfw93//95x77rmAcbLdddddXHHFFdx4443/xVa9vPxNK/dnn302H/rQh1iyZAmNRiMJDD3ooIMAo3wPDAxw2GGHzcChn3HGGZTLZT72sY8xMjLCkiVL+M///M/EUsvn8/z0pz/l1FNPZY899mDJkiVceumlvOtd79qiDieeeCKf//znZ3jtfd/ne9/7Hp/4xCe2Wu93vetdXHzxxVx66aWcf/752LbNBRdcwKZNmxgYGODUU08FjEf59ttv52Mf+xiHHXYYYRiyZMkSvva1rwEGxjEd8nPIIYdw6623ctFFF/GFL3wBx3F4zWtek0zyVypf/vKXZyj4W8OEn3rqqaxYsYKjjz4aIQTve9/7+MhHPjIDg/5Ssvfee/Pwww/zuc99jpNPPpmxsTEGBgbYd999k4Rk2WyWX/7yl3z0ox/lda973QwqzJacdNJJZLNZLrvsMs455xxyuRy77rrrFgr6K5GTTz6ZPffck1KpNAOzf+ONN24Bg3mxfP3rJnve6173uq3+fuedd3LAAQdw4YUX8u1vfzsJ/H61JPuZuH5OCj2xEZHvBjuFnhpCFHqT9Oa6NsFlf/9JJIKuVIFTL7oSPbbWnBOneNelEbTfQKRz6KlRvn3vzbzvHUt5/NkSb1pqNNnb/mCTEw77kmHHjibPThXZkZDh75cA6Dsgx7Orm0xaLqnFRZ5Z1aTXckjvmOXpZ8wLtMdymBWmWLYwx+STMO7CwW+QrLtNsCAyftqevhpPreul0/aRlqIz32SikiEtY++0EqQKIUHTYnwix9xPnWm+r4yZNgFIC13aHKept9ClEb78touxpCRrGajaRz99Bbq0GZHtBMs212c72+nmleKaX32GN2YGeEpN8iHVyS+sCm+lkHjmtos9iVPvO57OG68jev4RcDPk5i0hemG5OclyyBR6URufQhR7OeeWsyimspx+mdntEbkOorWPgVK4d/4c0dWJ6Ojkpn95lIOPNs+myctqjIgsngU/F5O858QD+c3HV/APOygeu8vE5lSlZNFhHu5Zn0NtfArZMwiZAmroadMl3XNBSNS6JxB92/G5A/+VuZkeJoMa/3RuTPnqZlDDz5pzlUKrAOFkuOWeb3Bc0ygN/2GP8L6jd+bhL06xUyBpTNhUQoc3Zcw8yFz0OfAbxkVvu+A30SoAIfnN774NwGEH97P6Ojhsd0if+xmI2nk39IQxNERnP1g2P7n7i7z78B0JnqxQ7G6Qu+wL5jytEEKi/QapdU8g5+wIqRzhDf/G1KNGIehIe4w1MvRmGmQ+8Ql0ZcyMtd9AWLE/O51DOBlW/vZ6FvkhUSTIfu6z7bVRGUOkcmZtja1F9AyaMkojyTlohd68htSmdcg3vRM98gKi2Id6+iHkjq+N54GNrk4gOmaDikArSm/+GjvvPtoqgn97JseeoYutYfYeTYIxxUNPdlOPdegdaw5NJDue/y4oTyC6ZqOrk4hiT7u+9QqydxC1fhVyu6Wo+38GuQLE0Eq5y/7J+hCFXlP30ojp79YYlEfMWlAKNbEROWen9lqJ14eujCG6jLFG6PGje7/Cm1SORqzT/0e4jn67SEE4HH3k9ojd9kR0zEKPrEf0m51gPT6E6J2Ltd0uRBtWIbId5GbNJ3rmATN3AGv+bkRrH0NkO8l1zyH8wy/BcbEWmRgy7TfQo+sQHX3guOa5Z9moCz6NzJs++fFIljcHAWsdm912mCL0JBvXmuR3E4F5HgQIlp4wD+vN7wa/mTwTCIzLW3TPAcum/7orWf1th/HIpSYle5z30eRZi5Ror4Ze9xSiZ8D0qZPiwbu+ytuPNFSYutbA+dAZYDmmLxsVwzATj598zxcYslwiBPuedgq6WUNYDtqrIXIdydrwbruKbKdPFAgmyxksodHxbhXA87bCXjyA7CmRXRFR/NSH+EuIfhXZcrYGR23RWE8X3/d55JFHtsgndPDBByfEJi8le+yxB81mkyVLlvDJT35yBlTn/vvv55//+Z9nnH/IIYck+sqfQ/6mlfuddtqJ+++/f8Z3rwQvL6Xkggsu4IILLnjJc97whjdskSl0a2UPDQ1h2/YMNh7XdRkbG3vJss8666wZnuXzzjtvBo/+dJk/fz4//OEPt/rbyMhIwvjSkkMOOeRlgzm31oYDDjhgi++/8pWv8JWvfOUly0mlUlx33XVcd911M76fbhm3KCu3JjvttBPf+c53XvJ3MMG4v/nNb172nGOOOYZjjjnmJX/fWrbXrX33mte8hiOOOIKvf/3riXX+s5/9DMuyePe73/2ydXilMRpr1qzhgAMOeMnfL7zwwi0eVq9EdMXMNZHtRPYMosbWIrKdiO65RvGIRXQOkIoVmZJfg9BDj26EMIRCV3xOP3roGXS9AlGIKyyIIjJaEEyat3UrKRMYSIUEJiOXnpYbO1QIBE0U+CGSFB4aHURJ9swmik6l0V4YB58KRMqUWw7Ny3xAmuA+21KEvpUERLbSqgupEyrlQJmXKYDIFJPPACLfbYwWgHQWS0pc6eC1CPOjAF0rgZOCUJrz/TYkT1gOaWlT1JKCcHC0SVAT0sYd16U57E5B9PwjWDu8FjW6NvkMoIafQw8/h7XodaixtWyX72OkOZW8zKNnH8ZatBfRxtWmnWPjiGyWWSKFHjewgaxyqEhBIOPkTb6HIwzGo5UheMh3wZbo0mbk3Neg61NQHkEOGCNd16egXkLMWQT1Ep1unqHmBAUnCynj6dZTQ+b8RgXtGT5JLSTdmORcgElQ5fkGT680lqNITcsmit9ABw1QCqEUulk2ioyKKMY9p8s1UhTR9QgCz2i2ShllJ1YOdOghtKJDOOhmkwhBFMik31p+YZEpgGUjsh0mydhYiaxr7hMpSbPlas51ICwbpEREoekPQOS60LVJ8goq0kr6StjGOygKvejRtYh8N6Jve6MIp3KIjj7UupXmnGIvcmBHoudXQxCvr1QOudPrTF8AeDVwM8bwmabMRTGQWitDk5jSZk5FVYVftcgonQTldjgebmjDxhegswe9eS3kikZh7jPsS5Qn0IVuY1R5NcTS10GmkLQnWS/ZTnTTKJYi29k2wlq/VSdMvxZ7Z66VVr+nizOMuA7hkFZQjRdHWjgUhINEoCt1MxcaFQh9dHk8nitNdHWSaONqrDmLUaURomcfwtrx9ahhA/eM1j+BNX831MQmwtX3Yy19o/mtZcxMbkL0L0SXRyD0EG4G7TeQWQtVNUr33EDjWxaRgKnhLCoS9BJgC5VMpEgL5F4HxP1WNU4Tv5Eo9wQNhE4RjZSx6CVoXRj66NCsQSGddp8oZeYwht5VV8zOl641EbnOWGm30ZaNyObQdWMc53s9oqn4WdfZD17NjF19qu28ANJa4VVtQl9iCU2kBX5oJesipY3HX6QcAmTbAPk/JOeee+4Wu/Fb89qPjY0RRVGyu9+S2bNnMzw8vNWyBwYGuOqqq3jta1+L53lcf/31HHjggfz2t79NkBfDw8N/UpmvhvxNK/f/k+J5HuvXr+f888/nqKOO2mLg/5xSr9d56qmnuO666zj00EP/Yvf9a5fLLruM//zP/0z+rtVqXHfddf8tmsrpctddd3H33Xe/KmVNF5GK+ZkzBePFTBchUzAvazsF6TioOfAIopBIK2xpGQUjnTXKTtrwzxOFiHQOhERLabJDCmGwrh1Gk663ksUIo9yHwtAItrCdSIdAK2pCgzQc5zVChCWTTLGR0OQkIEXMUQ4i4xrKwvi1FAUSB0Ptls0qfM8mbYdM+eah7qZC473Ph8hxbdoqzcurpcBg2eZlJqVpb7OG1hpfTcvMbDmIVMZcY7uglfHQTvu9qUKm7AgvzjLb0CGBMHhhIAlaFVIYr/foWuSs+UReDTW61nRL/0Ki6gRq5AVkZz+hjphsVk1CAYB0DjW6DmtgR5TjQDYD6YzJktli/8HgctMKynhQ6KCiA2TWJpMxbZI+iFzaeGUnNhqDrTaJnjJwANExG10vocc2IHrmoNH0pIpM+VWjkIC5tjJmdoF0hBCWqR+agmXuU1UeODZNFGXLxskpUnaYBH2SziFaQXWWDSpjlB6gFuN1RD6LRwxvcVLm/pZtlKJUzLpjOZDKUdcRwjFm1fRYe92otNeCmzF/Wzayu0ikTHu0hryI8EPLzIHYc9/yzALoZgWRyqGBrFJoLRBOpr1+wCjH2Q506CNc85sQ0ii+gEgXjCLtOPHvWXN+bTLxQItUzij1qZxpp5C0iUoNO5SPSjzfdqdNKg7+brkRGqFtWHAKHVArQ64IzTpk8onipyc2m3vHBo8qjxklMogV0HinKlkvQiZrRcTUuEShab+Q8djEa0U67d2KKDRrCxCWTUkHRMJNWG48HeITIRCIYt70uZs218d9gu0i7BTCTqGmhpGd/UT1EmrTM2YnBog2PoWa2ITsnoOe3GR2JLZfBrFCney6tZ5llo1wMwYOFsOMmkKQTQVMhmDbEYG22CxcBLBrh4ltiwKJXrsKsXQ/0Bkz/9wMOlaKhTR/Wz1mXghM8q4koAjM8yb+W/sNZFyGQiPiwFxcG12bMkZBFJh5O93YC2TSh7oyBs062raN46U1VzqM3mGnIoTUqCmRUP9OZx3DshCFLA4eIlvgLyKvIiznpSA4LyUvR5jyYlm8eDGLFy9O/t5nn31Yv349l19++QxY9Z9S5qshf9MBtf+TcuONN7J48WJKpRJf+MIX/qL3vuqqqzjooIPYfffdX3b3YZv8aTJ//nxOP/305O+jjjrqJQNb/yvywgsvMDg4+KqVt022yTbZJttkm/yvlFbU/KtxvELp7e3FsqwtPOojIyN/kgP2DW94A88880zyd39//3+7zD9Vtin3/0Ny3HHHEUURjzzySMKa8peSM888k4mJCX7wgx+8Yg78bfJXLG4a3DQ6CtHj6w3eVCn05EbzOfAMRKAyhkJjCUmnmzee/UKX8TDGD1FdGUs8ezTriT9RQUK7o9C4wsLRJihMashbAVEgDVzCtrCFoAcXbAuBoBsHpMAS5ujBYRNpRMqkE2oKjZqoEgA9lk+P5SMtA8tJmpkKaQQOWSska4V4DQdpabyqoQXEMtGCulE2ny3beKDrUwZzLx0I2tk3s1Y6wd1ju4nXTVcnjDey9WKJvdkSga8jlBDYQpKbxoTT4sYOJhTWvCXoyhjRhieTz7oyRrRupfGil0ZQk5sYqk8wO9eZjI81uBRdnyJa+xg6CMB1IAiY0gGis4DoLODFHshIQFa64DVJY2AHQ5N5hibzhr+7VDcwkkYF/Kb5XCsZSIXfQBT7jKc3Cin5NVLSIWW5SZtFodf0g98wsQoqAL/BFCG+svCVRUYarHAuhpA0p2yqgYNSAqXEzAyVQiKkg1YBWkcoNCr2Q8vkH+Ixi72egW8OISEKiFAgBQKNtJUZoyg0UB8nZeZvo9L+Thp4gh9aBtqlBa4dta+LQnQUbPF3QxqaQtGaU7Ho0ojZGQh99OjaxOusJjeZz7aLDgzuG8tGRyGi0GXKXfskwnKMF9iyDdwjCgzmPvQQxAGiKY20zZyyMQwwWmm0MnkLWgxOvraMtz/fCW4ake8yuwSFLnR9ysz5XDHBnROF8OxK9HMr0WtXodeumrk+4n7X9SnTlnj96GYZIR0zBxoVU9/W71Kaa5rlRAFrQX0C0WaA0Wg8rZJMzbhpgxm3bES2YDzJUkI6i5y1Hbo6gZoaxtpuF7NuXlhO9MJyrIEdzTNsZA3WgmXo8jjRk/eYeabMnKVWau/Uhb5ZW4DIWoisxbhtIFq9ERT6PIq9TSytsbVm7WQHayc7WFMtoDdPU+RETO+UPFOk6QfLirny4xwGUia7D1h2MidbO6FoZWhKMynIpBCZVIzBypgdETtlYD1xe5oVx8DdNIl3nzB+LvlNc0QBPiaXiOW011vKjgiUJFAST2jQCjVWQgrQzTZk8c8qSr96xysU13V57Wtfy69+9asZ3//qV79i3333fcXlLF++nIGBgeTvffbZZ4syb7/99j+pzD9VtsFytsmrImvWrGH77bdn+fLlL8s//9cq3/72tznzzDO3ynbzcjI+Ps7OO+/Mgw8+yIIFC3j88cc59NBDWb169UvmE3i1ZQbmvnd+G3PfMzgTc989N8HcV4L6y2Pu/QZEIZaQoA2zTFg25WSFoY/UAkPDCJQil65Wtiw/RJDGfzHmPlKJDtdE0aE0uuG3MfcZsz1ei2Y+1ixpuPC1EthS4ccUdtJSaG0w+DMw96n8TMx9pmgUbCEhlU4w90ELmhN4MzH32c4EOwsghIUrLPIx5l7GmHtPthNUNQV4Foax5IXlW8fcb34BPboOa4c9UZObGMzNmom5f+5hrIV7EW2KMffjk4hcnm7hoicNDjerHEqW4QmXAEFgMPdAR8pggjcHrtnyL21G9i80SlmpiuxfaMr1agZz378A/Aadbp4Rb4qMlUrgFebaRQbC4sXQIenQiU1McIJEQBAQoMnEmHspaMNy/EairMzA3AP5Fua+XsehgPaVUcSiEN2CAbUw9zHGOScctOejX4y5bxkDlg2OaxTdGHOfctpzycdwgJPOGZNRSgPpiI03kS6gmxUyCupCoiJpoDotOEahFz25EZGLMfe1CUQUIjr7UesNja4o9iLnLjaY+yiYiblvzSmvFs81fwYMI2y0MPcCG2ESFElQ1YigJklrbeoPdLlNGoEDm9dDroAe2wjprMHczzZBqgnmvlk3UKFdXm+M3Bdj7lsxKkpBOmc+t7ylqVyi/ItMwYzPizD3pHLteAnLJidsUgrKcde7wm5j7qs1MxdqJVOvFua+WTeY+6FnTJxIC3O/eJ+ZmPvtdkFNDhM+8wDWbm9GbXyqDauaGkbM2s48D0MnNsQ8k9cjxtzPCTT10CGwYGo4g4oE/cIzQahxcwIlkfscbAxLv4HWyjg8/JhNx28YqsmRMtDGvhOF7TEWEmIlWgdebMBBBokuxd/XmgY25TcRjov2bUS6wwTWApmiTxAzDRljvGLgS3Xb/B1LGkM7GviGDaqFuW/BcmZg7vVfvz/4rLPO4thjj2WvvfZin3324aqrrmLdunUJUcm5557Lxo0b+e53vwsYJpwFCxawdOnShAzl5ptv5uabb07K/OhHP8qb3vQmLr30Uo488khuueUW7rjjji0o1V9N+esfqb9hOeCAA2Ywv6xZswYhRHK4rsuiRYv47Gc/+4qDOl9tWb58OUcffTQDAwOkUinmz5/PEUccwU9/+tP/sTr9V+Too4/m6aef/pOvu/jii3nb297GggULABMEvPfee/PlL3/5Za+78MILZ4zli48/xtAzXUQqb3D36ZzBhaZy5ogVB5HtMEGGgUeoIrwoINIK7JTBNec6TGBgKpdg7oWTgkzenIdJjGPnwc6Drw32PKSNuRdoUpmQVMa8RCM0FcIEc1/BfB9qTag1NSKKVhv3LgGRS+FqqAmLmrCIAomNIogsc59I4toRTW3R1BapjMHcpwsBUmjjGW0FP8ZeUuFm2jhYN5MEk0U6ItLKtM+yzbkyPh+D3W4dpHMEKKpCEcRY8YYOCTEe9EiQJNYRtgDLQQ0/h5w1H+wUavMLqM0vIGdvD7aNGluHyHWj0ZT9ensgbRc1/DzWnMUGs53PJbjzlrRWVF5BVfmQzRnMfd4mm/XJZo2xJHKxJ3tq2IyrVujyiGE/ieeGnhxOlPlOJ48XGWWmFQioK2NmV8iJYxHcNBJB0fIpWj4NFYCU+GgmLIGTU2TtabEM8W5J4sl0M4mHu46ijkJkUsabKUVbWRcxJtlxjbIuHbBd/Bhz3+4MlXjrdb2EblSM9zP+LLvyyS5CGEmyIiKMjNKlaxNGaa1Mtr32zQrCycR8+cZwFHZs8LgZYwykcgaDrlWCvRZCInId5kjlEsw9jllfIlOYGaDtxHMy7lOc1AzMvZVShOgkyZXVaeN2mHmn4qMWOJS0DZkc1KumnGbdeO/z3SZWAmOwtBRz7TeMQR+YQOdkfUB7nIRECCvxQAthJZ5lUzmzVhDTvNRg2hr3U02HM+oaabNuPCIzp/2mGbtpuHScabsFk8Mx402KaONTyP6FxjC1bIO57+pHWA5qzWPI7XZp77wAujZpnofxnBOpnKG3Dc3hCUEh4zEptaHRFbCJNOt1hlndNWZ11+jrrKGffyzxvgvpmOehmGZE2i5WV9Y8t4gx99MkmcMAoW/+dlLm6WHL+LDQ1UkTtN6omKDmRiW5j4oT/ilhmM50ZQLK4+jKZLIb2Hq2WY7CcU3MUwtzL4U2z0VIMPeuiMxOwl9C4h2IV+X4E+Too4/miiuu4KKLLmLZsmXcfffd/PznP09y9AwNDc3gvPd9n7PPPpvddtuN/fffn3vvvZef/exnM5KB7rvvvnz/+9/nuuuuY7fdduPb3/42N91006sK232xbPPc/w3KHXfcwdKlS/E8j3vvvZeTTjqJgYEBTjzxxL9oPW655RaOOuooDjroIL7zne+wcOFCxsfHeeyxx/jkJz/J/vvv/5K8sX9MgiBIsuH+JSSTyfzJGYEbjQbXXHMNP//5z2d8f/zxx3Pqqady7rnnvmS23LPPPjvxJEyXc889l5/85CcvywD0YmmxcIgabYVMWMnnViAYjQopy8ESFp1O7JGLA+V0i/axMmk8d5YNlSmc6R7UuBiBIC0sUtoEfWW0oNP2E551HSlcJL046KCafCZUpOKXUQ8OIwp2poqjTaCoLtWBDP1Wi28a7NgT5TgRvmebpCyxgh36Fm4mTGA5LU+kLo8lAY4IiS6PmS1zpdBTo7jSwZU2GWlgFbpeMoqPV4XQMTSFuc4ZfZwSFilM8K8SgoywkwRK0E5Q5Y8pMoVe9PBzRNUJsxMyal4kUXkEa8fXEz50K7o2RVammJvrRVeM91Kk8qipIdTUEGJgAPXMs4h8zgQj54sAeCJIkgV1WWkoT9EtXIKRKcZLrXOE6ctUDr0hNlizHehNz5rPsYeWoRfQlo2nAmY5BeNZjZljcDPozWuMRzYOUtZ+g0oMywHocNPg+fRqi5yCxqSB5bT42nV9yniplWoHy07zVLekpdbqeqkdHMnMQFlUDoFAKxPQLC1tFKNWe8BAfiaGjKKYMUGDtcA8Q3pyDSb9NCknMrCVymQ7oNaNDajAg3RAU5oAcTDebdEqvzZhoDfVCQPRyXUiAFUZa9NC1ibQ40PoMDKwJiHN/HphJWKeCQzVlm3q3tVv6q4VFhoZZ+zSyjAhSQAN2lfoMF4jcXdI4jpaNkRRMkZAe7dOKzMGzbrp22dWotOZhAqT7ZfGgdMTCbWiLo9DsScJ8tblsbbHvjxuzvcbiEYF3fKYVyehywQGE/qkhNnVaiUgc4RFhCaHjfZ8sxOiFDQa7Qxf9aoJBs52ooefM4ZWrgs1/BxR7N0X/QuTdUW+C73+KaJHf40cNMknyRTQI+sg12GOqtlxMvkIzCxrSPBDi95IJDZ/RikEmvWjZv0ESAY3D6PnTxk4jGUbKEszNsQbFePNVwY2KNFILQwcMPTbY+w3oF4zc6ZZBhUQoc1OE6ClSJ61IjAQIq2ipO9rJWM4KTDzNQ6opVlvP6/dDE0k0tKo0GTX1cATMstrrXJ7/Xg+aqyEJm92Tf4S8ioG1P6p8pGPfISPfOQjW/3txSx+55xzDuecc84fLfPd7373H2XOezVlm+f+r1SOO+447rrrLq688srEm9uSnp4e+vv7mT9/Pu9///vZd999+cMf/pD8rpTioosuYt68eaRSKZYtW8YvfvGLGeU/+OCD7LHHHqTTafbaay+WL1+e/Ka1ZtGiRVsk7lq5ciVSSp577jlqtRonnngihx9+OD/72c84+OCDWbhwIXvvvTcnnXQSjz76KB0dHa+oLDCR6N/85jc58sgjyeVySdKtb3zjGyxcuBDXdVm8eDHXX3/9H+27BQsW8NnPfpYPfvCD5PN55s+fzy233MLo6ChHHnkk+XyeXXfdlYcffji55tvf/vYMQ+TCCy9k2bJlXH/99SxYsICOjg7e+973Uqm0FY7bbrsN27a3SCh2yCGHMD4+zl133fWSdczn8/T39884fv3rX3P99dfz/e9/f0Z2vD8mujZlDq+K6J5jsNXNsqFP85vGG9SoQL4LVzoIBJsa4+ZFNDVmXtqVSXPkOsyLNn6RZaWLbnh0KEFzwqI5YdEpHLKYjIwqEig0w1Ea21XYrgKlcRDUiOLPkjrmZegicZHUUKS0RodGWXMAHUQoAaNhitEwRboQMolDMeNRLqfJF5uUghRF16fo+tSqLlEgDUuEFgYHGwXGy6eiBM8sZ2+fwDzE3EVJv437Zcb98kzWD69mPO5+w2yrN2ugIrLSpUNLuoVLVkWkhYWlIa80eaWpSnje0bh90nDLb7/MsGMMPYPcbilyu6XgZggfuhX7dUcgMgV8HRLqKPFYqpEXkH3bI5wU0WNPGM9eENBPCrV5HLV5nJQ2EBiANDba85AIrKykK9+gK98gpxQ6iKBewtp5X+Mhrk5iLX4D1uI3GE9xbQq52wFg2WQsl8dLa2koH9E5gOgcgMokcoc9zbnNmoEWRCGzcbGFwhYKV1joMCLCpLYH6Ex7eIGNF9ht5h2IFT+j1OlmjT5t06dt1GiZjBZE5ajt3W8dLa9dbBh0CAddrmKhjVezhYHOFCCdQ8Z8+KKzH2GniDZNMqe3wpzeCpO1DBHCeON7BpEL90Rutwty0V7JDo3s2x5dr9ATajZbDvnOOFbFq5q11TNoFFmvZvj//Ub8/Tz0xGZz1CuIzlnQSrgzNQZ+A7nT69r1DX2Te6C1S9KK9YgEOhJIG/JIipGZW/6Ioj7uJMwpgGkLAkY2QfcsmBqHYjeUJowXuFExsJJm3ez+NGuww2sQOy1DLN4Lsdhww6Mis6OkTQyD7F9olMs4DkT2bW+UVKUMdWqL3aZlTEShWS/x2sF26cGlI9JJBtusdM26ERa6XIVCp+mHbA68pjlSaWOMjK01a8d2URtXYy3YzTB6pbPo4eeQC+M5ueFpxOBrzG/xTqUuj5nfLdtg7+N2ONsXTVIrWzAniMhmfXIK6jWXpmcTxu9WR2gcoUkJhdhxSUzbqtrPhngnCSkh8IhGa2SIiBBmbNxMe9e0teuXSiG6ZydluQi0H6L90EAWu+fEbDxpc01nG+fdu7COEibbrVywG3LHvZCL9kJuvzty+2XI7Zch7BQOJmt2FEqkMM/C19klk43ZN5EOOggQuTRNbUFl6hW/W7bJ/5xsU+7/SuXKK69kn3324eSTT07SIUdRtMV5Dz/8MH/4wx9mbA9deeWVfPGLX+Tyyy/nscce45BDDuHtb397Ev1dq9U44ogjWLx4MY888ggXXnghZ599dnK9EIITTjhhCw77a6+9lv3335+FCxdy++23Mz4+/rIWb8so+WNlteRTn/oURx55JI8//jgnnHACP/7xj/noRz/Kxz72MVauXMmHP/xhjj/+eO68884/2n9f/vKX2W+//Vi+fDmHH344xx57LB/84Af5wAc+wB/+8AcWLVrEBz/4wZeFDj333HP85Cc/4dZbb+XWW2/lrrvu4pJLLkl+v/vuu9lrr722uM51XXbffXfuueeeP1rPljzyyCOcfPLJXHLJJS+bp2BrIrvnIrvnGlq0wDefi30Gb1roNcpOZz+EPtWgQTWoY0vLBKDNmoPonYfo6DNb4VpBZ69JhlPopKKaiFyGioRUZ0SqM6KsQ2qE+C2qO2FgDHYqwk5FIAUBGgUISxKgYo+VwEfho0xgb/wdQIihwkxpSKFJYYIIba0JQouUGxIFEldEBJFFEFk4TmS8+64yW+zZToNFDXzzufV3FEK2YDySgYcX+YbnPxaRKSI6+wycobPfXF/oTfpEZDspRU0mhaKkDeykpkM0xkvuCYGjoaCFCfgs9qLG1iI7+83nyU2oyU2mLrmiweRvvwfVsEkj9MyL33JMYp/KGKLYhyhkEYU8Ys4gzRi+IjIpQgENKbA1VLSP6OikTmSyyApztPqdbAdqfL1RvvJdST1kzzzD5b/5BeTATtTDJv3ZbjbXJ9uTqtBl6hK3oQX18FC4VoRrRVSVjyjm8YQ2SoirUEq04QCFXjMG+W7j/S10QbEH0dnHuIgYFxGiK0dDaKyiZcYhhocJJ5MEW4p0AVHoZUqb+4Hx3Lf6Da9mFO1ayexU1QzUxprfR+BbBL7xhOZEaIyOKDCwhvqU4URvKW2hj+jswxOCrFLGcCz0tg2eKED2DJq15TeS34hCRP8Cc3T2ob0GIm+80MyaY5JYTWxM4HOi2GfiCoqt+dVh6GDjgFqAChGBEEQI3D5Jticgoh1QG2iJJwT0zzPK8awBo8z39CPyXSbuoKffrOlM3szrqTH05Gb0xCb0xCYzNnGSO5HrRnTEz4x0of3MiEIz/h19Jri6tVbSRdP+Qi86ChC5LtOeTJFR/LjuZrehrJpUdGgodHs7IQzbNKE9A4ieAVPHjlkGrjY1bJ5hhS7U6FpEx2zzbCv2oMc2ILvmGE7/zWvMDl0c2NvKZyF6Bk3d4nbomoc1K4c1K0cgBLatDJQwxqRXpKRkWQhhgqgtNHrNM2bO5rviOdyFyBTMEc9pe6BAaCJPkDqG8rXmbwu+NY3+VOS7DRStkI0PQ9uqvVrbCePVTL3TBaKmCUz2JPFu0Wb01LDZHSqNmB0aN00IpIqhSWQ1LXmVJXSCuxe2BdI8q+icFifw55T/AbacvyYR+v8SsHmb/ElywAEHsGzZsiQLWivoNZPJIKXE932CIOCUU07hW9/6VnLd3Llz+cd//Ef+9V//Nflu77335nWvex1f+9rXuOqqqzj33HNZv3492WwWgG9+85ucdtppSUDt0NAQg4OD3Hfffey9994EQcDcuXO57LLL+NCHPsSll17Kv/zLvzAxMUFXlwnGfOihh2Zkdfv+97/PEUcc8UfLAmMInHnmmTOw6vvttx9Lly7lqquuSr476qijqNVq/OxnP3vJfluwYAH7779/4uUfHh5mYGCA888/n4suugiA3//+9+yzzz4MDQ3R39+/RUDthRdeyGWXXcbw8DCFgtniP+ecc7j77rv5/e9/D8A73vEOenp6uOaaa7aowzvf+U46Ojq2MGq2JiMjI+y111686U1v4nvf+97Lnru1NNxL5+9jcL9C0O0UmAgqJgutW2DMK5G2zPZu3k5z33/+s9mqHt/Ea973TfJ2hmYUIGPvVaeTwxU21ahJ0cpw+0V7cPpn1nD568f5j/sMK9SHTpXoao3q78Z5bHU/b3j7BM/9MsMG38ylh9KSTxwboMYrXPrzLs59v/n8xdt6+PiHjIGqJsqUH2nyraEBznr9JrAFV907h5OWref5R8x8ekrl2bdnhKHRIhGCSRwWF6cYL5v7CKEZ1SlsremxPN7dNBCUgp2lFhqvsUJTsLM0Iy/5/PAt/wyQbE/v+J6vkLXSBCpAoclaaeNRnyaPffmthPc+gvWa+Wy+7nn63tXH1G1DqND0W7Y/JKrDLasHOWfq92yX7yPUEUP1CQZzs8z90GRlCl+HVMMmT6z6AeHjv2Hxu640YxsFzMn0YAnJ+5z5/JYpNJqbTurkzGvNdv9F80zwtJVS5A/dkaO/Msz3Tyhw1bUWB2B2lTq76vxocjZfqiynL9XJVFAl0BGzXAO9mAqqKDQDqW5G/TJP3H4heuh5RLGHnd9hdtgirehyC1TCBrawsIQk1BErTtmBp683dVn8rwv48MXr+epbypRXah5aP5udC1NU62a+vavxLEIIJIJIKxzpIIXAFhYPfcAk37vwRznO33+Eb9w9wFcrK5L+lgj6Up1mfXhTWELyxL+8lo99rcrpVo2nah2c4T82Y4wkgvmZPjb7JTzl847CEt7dNFCVnBMgpcYLbN7rPUfaSqHR2MLClWbnphI2sITk7l2zVDaneXKsm9P8x5PyC3aWetREIpiV6mRTczxeM3l8Ze6Tthz6nQ7y0uWB8nN0unmaUcDibD+rahuTvs3aaRPjAAgh+VFukAciAwuxgaOPKlO6v0oUCG7dPEBHBActXo9tpj5Ta9M46ZAjNzRJWy6VsEHGcqlHHtl4vXsqoBkFdDt5Rv0yb8pvT0UHSRKy5dU1AOTtDPXQQOEKTtYE28eSszN4KkAg6HCyjHhTZK00zchLdpOzVpp61EzGYOVHd6Fyx8YEZlQ46QD05mH0+CRnXa9Z7o9QDuv0OAXGg3jO2jkmgiqjjSn6s900I4+SX2dhYYBQmbW4prqZublePBVQCersXlhAhOKJynoAHGnR6eYpBTWseM5GWnFqbinNGND04e038uiqfpYsGOHhtf04WvPaxWYde7U4M6yl+exEF7eVV+FKh0hH5O02ZLMaP1veW1jKCekp3FSIm414/eqRWNU3z52UdBlMdzPsl5L+feKDC/jET0xZaSQ/KK80sCWtSFspIq1ohfZebu/M67cfRgjNW56t4kobpTWOsPBjjGQ9bHLnYB93j84mozSLnCqREjwo8hzgGmN93kEh5/+yiw4s3p+e4KSKzz0bf82fW2rnvedVKyv3uf/3qpX1f0W2ee7/BuWmm25ixYoVPProo9x0003ccsstSbrlcrnMpk2b2G+//WZcs99++7Fq1SoAVq1axe67754o9sAW0JKBgQEOP/xwrr32WgBuvfVWms0m73nPSy/Y3XbbjRUrVrBixQpqtRphGP5JZb3YC75q1aqXbccNN9xAPp9Pjume8t122y353OKi3XXXXbf4bmSkzSbzYlmwYEGi2LfaMf38RqNBOp3e2qVkMhnqdfOS/PznPz+jntODeYIg4N3vfjezZ8/m6quvfsm6tOTiiy+mo6NjxlFqjqLQ1IImQ80JtNZUwyZDjQkUmnJQoxzUGPGmzNZvuoDomUMtaJKSDkpH1MMm9bDJ5uYkpbBOI/IpRw3I5mhqhUjLxBMnUi6imMfOaepCgjRZZCOMpzFAI4p5ZH/3tM9dBEInXivZ301lPG08+mnzGCsLhUxLCnmPQt7D0QZ+IYQm1IKMVvi+RcYJyDgBTWUl3nNbKiKlCFVEJawTqMgcUUg5qCHjF6iv4qQ8bgZR7EEUe/Ai4433VYgXBZSDWrzDYY6yX4N0BtIOOIZ+UxTzpIoRdkphpxTSFVhpKEsoprKMNKd4rjREwc0w0pwyf5eHmAiqTAU1KkGd8PHfYO/6Fkp+nZJfJ+dkGPVLPFcZYrmoUxCOyegbBNgYBhUVCaSjsNIgerqpKg9RzFMVmpLnUvJcnHTEiIxIWS61yKMSNHCERTlsUA4bVIIGKenGyp9nPIbpLBS6aEQ+jcjHljaV0LTdUz71qEnZrxnMdOzhFF3dhCisnhx2SlG2JJ5vUwvN0Yh8QhUR6AhfhYQ6xItMWVgWWJYJprUFEmPcRMqMY6AiqlGTatQk0op66IFlEaKN1x6o+U1qfpMgCgmieOyiBrWwgRcFtPlPDP1ha0ehGQWESZ0iKmGDStjAVwH1sBmTvigsrYmUohn6NEOfCa+M1ppK0GBTcxytNc3QZ7Q5lQRnT/gV1jTH0FrTCH1cYVMLG7zQHCPQpi8irWhEHvXQoxH51IIGUmhs4gBaDaQc7HREKh/REMaDG3kS5YPyoVF3CJo2jrRxkKSlgy0sUtJhxJtixJsiJR0qQZ0IRS1ssNIf5WlvlOfjI1KKIAqphg0T9KoiqmGDQJm+8VVILTRsMYEKqMT9CkZ59aIALwqohQ3qoWlPJWiY54MEu2gOUikQApHPEcRUvCnpJLS8lpBEKKQQ5Nw0k36F4foUHW6Wzc1Jnipt4KnSBgpuhjGvxPrKKJ1uno3+JI+W1yTj40iHatjEiwJ8FVANGtSCBpYGB4GDIPIFLhG5eYqsVqRRhJ6h8N08WmDzaIHRkTzPhlNmLuqIUJkxS+qqzZxI4h8ssx5C1aZ4bflcPR1hx8+eRuQnMEVzCIIoTJ47QTz/GqFnDhlTXLoaX4XJ80th5nAzCqiHHl7TJqM0jtZEMXbrjVaJpm/T9G2EEFQIGSNARYJSNC2If5v8r5VtAbV/gzI4OMiiRQY7vPPOO/P8889z/vnnc+GFFybnvFw2tVe62XPSSSdx7LHH8uUvf5nrrruOo48+OjEIWpjw1atX84Y3vAEwWeRa9fpTymrJ1qgjX64db3/722fAkabnG5gejNs6f2vfqZeJxH9xQK8QYsb5vb29TE5OvvgyACYmJhLI0amnnspRRx2V/DZnzpzk8xlnnMHTTz/Nww8//JKGwnTZWhpuNqwglXLNVncUoAPfMCLEn1vBfihF3x7HIhG4ls2mJ29GrX0M0T0nyciqo9BAFWLc6v7v+RZ3nb87l1+S4R+XGQ/Z+79SxBaSv1ODHDk4xOd+2cfBDcVufcarfODf2Zzy1TQFYfOFdzQ47Rs+BWwufmuJk75qvFY5YXNUo8C/vGuSr/5sAAGc+0Gf6749lz1jz9hePWMMjxWIEOwwMMnEuJkvI74pY8ngqIGhRILh4SJrHjHGI34jYYEBDH7YbxpObq/GvDedhS2NZw9g46M3mO3/zoEETyumXw+8Yb+zOCA1j6fU8xwfzOa7X9rIIXowCRosrYeMghP23sDpl12dcIgTeDO50ivjMfbaYcc3nEbJv5ixNYY/WU1sQsQB0NEt10AmjeifyylnPsi3PmK87rdc6TBpGcjDTx5dwc+/fgjHnX4v33pjmRfuMYbo/esGOP/9VS468UsmIDTbaTjVA+MpJlMwQYG1Cch2sNObP0HKcvEin7WPXNfuwxbzUqzQCTfD6W+5jKObZu0cdNZd/Opfl3DBZePsHBY4fOEGnnu6l56s8VJufOSHbbrFVlCitEBITvv7LwHwbx9O8dlv9XHuW0c589wbzHxt9VXZGNKi0ItIZTl6/09xw8fmcu/nLfYcGGXkjtvNec1azD2uTNxCzzxwUgRXf57Hv2nqnkv7rKsWmJutsebua03QtLBmUp5mCmA5fPst32ROGLFjR4m1v/h2m/Zx+toKPJMN2s2AipKgaFI5aFRQj92NdcDnzfrq296wFBWmwSECz0Bn4gy19+59CUfsvCGuiOb0G3t5XTRIIODkQ0YIhj3ufHge1RjGtpQaY7UMd33/PQZXnyuafAYZA0UB4niPXVAvrEDusCdq41Om7nF7WueZOeq0czrE2a2TeRD3rfZqyO45CVQmiUj1G6Ytsbz/TZ/mzWoe43G0+Q/vv5VBtwsHyQ1nzUEseQui2IMe22ggOZhAXtE1G9k739zPTpm5K2T7+QUxW41jICkxn73smWfaOx73n+0alpv42vonPp5cfvPv5rJnqsK1D83jXQObiULJyjV9SKDXNc+dILL4+TVvw9p5X0NTabsmaLo1l7vmItw0/r99mju+14UzqalLydpHLk549bEcMw82rkZ0zTZQITfNx//uC3z+hDhYudbgM/90U8yZ7xi2p2nPik3vPI/frp6LErDqt+eZgF0nBbVSMpdExyzu2PsL7LNgiKBpMTaWJ9ICHYiENvWyX/Twbx+2oVrngavzPPjzU/hLiP4TWW62yUzZptz/FYvrulvF2b9YLMsiDEN836dYLDJnzhzuvffeGamTW5AYgCVLlnD99dfTaDQShpgW1GS6HHbYYeRyOb7xjW9w2223cffddye/HXzwwXR3d3PppZfy4x//+I/W8eXKeinZeeeduffee/ngBz84ox0772zYEQqFwgzP+l9a9thjj5eE0axcuTKJrO/u7t5qsrGrrrqKa6+9ljvvvJN58+a9ontuLQ23pwNoBkkSqxYOVk9uMi+BFttHZYxMjAHtSRUNm4dSScAcGK5oHXiIVAZdnSQnXfBiesUWQYOwEracoGmR05K85SFk22h0hCCHBUpjIchhPPwttpwCFpXY69+ibgs3TNAU/QlmNJULqIza9LkNmnWHfN5j82SeLssogNXJNIXuJlFgvLLESp4uTVOkLDs2Vgydoq5MkLZdJIKsbYwp3agYxSZmrtCVMch2tjtYKVLSwUbgILG0Jits8tOWZl6ZIyxrRK6D6NmHIZ3DGlxK9FwcuG27hhFneDWiYxZeFNCTLqImNgEgu+cQrb7f1MnzEZk01OIAbtna7jf851JAXrrQqOEiITSeewAlQVeNkqHHNsAsiUjlUKNrTVGzDCWcHh8yiguaHqfABFUzJzCKvBpdi+wZNAmsojDh+bbj8clJkywti8TREDSsJGgVYpxwizPdTsW5EwKwnITnnmqdrHZR1aCdgErEwZr1uO2pHDoKTABvvWESPjkKNRknGmopoIGPHl1nYg4yBQgjbGnmtRfYpImIlDB4+/KYUaj8Rtv4Cr3EKHS0Rkht6tRiQCltNpzwURAbEYPoVrK4FiWk30APPQ/NRrK+8Gro5x6DOIhV2Ckzx2KlGa1whEpgLAA5DBtTHlD1ENWEphAEsa+jHLhm10wpMy6ZPHhNtJuG2ChKErq16rBqOeTyCb2q2KWQrA+RM88nXRmboVDryljCPKTLY+hMwYxns9bml6+MzQhKT2ES3HXGXuSMdHGQ5IUDYWSMzBaDV0taiqCTMkZIvhvZM4/wmQcSQ1tut4sxlnLdiO45RI/clgSiJsWMrUd09SNCHxUFCMtBK41VNI6ahgDbUnQGkO3xUYGgPtYyUkw5IaBXP4Ee3Bnt1dC2a4yJluGZyoGfAscmqxVVEcc/NCrtdkjfGI6NKjpXNOxCoUcKkaxlYVuGjhYSx4OOKUbBsIUpYda8nhxuz9VWQitASsOq5GSUYcwZNc9Tx46o+6bNCg1BiKo0sEWmfc8/t/wPsuX8Ncg25f6vWBYsWMADDzzAmjVryOfzidd4fHyc4eFhwjDk8ccf58orr+TNb34zxaLBbH784x/nU5/6FAsXLmTZsmVcd911rFixghtuuAGAY445hvPOO48TTzyRT37yk6xZs2YLNhswRsNxxx3Hueeey6JFi2ZAd/L5PFdffTVHH300hx9+OGeccQY77rgj1Wo1YeaZTgP5cmW9lHz84x/nqKOOYs899+TAAw/kpz/9KT/60Y+44447/uud+irKIYccwrnnnsvk5GQSdwAmNmLjxo0cdNBBL3nt7373O04//XQuuOACdthhhy1SW2cyGTo6Ol5RPXQtVshaiasmNrY/xwmuAETPvCSJVT1sGnq7iSGjXMdUeKKzP6aiq0HgY2EUCAdBazc3K0zW2UiAk46gbBJPeQ1Ttg4irBiegx8mn3UQIWgF0GryWqG9EImBIsicSWIVxEmqVCQMM0rsgWo2HDJ2SD2M6Q1ToXkBRgI/stqJq5xU+3PsBTTsGRJhOVjCJLFqZaol8GNqRCdhbJnu0UVIUsIijSQnHJQwSn5TmgyiYJQGJUGmIVr7GNaivVCj64jWrMBaaJQ6Nfw8amoIOW9ndGWMOZkeRv0SIqZijFbfj7V4H6K1j4HSJolVNkdB2IZlBMgpm6qUNEScRMprkhISrTR5x7zwN0cu2LGR0z3HKJyNCqLXGJA69IznumMWulGh2y0wFdZwZcxhjqFTTBT7mPVGWzY5LKpxtwkEeD4BmqwCO2WywDpObPWEfpyoKTIQhpYSHnrGIAF0o4FNqj0O06kwW3EPMQtLVlgQRWgEQdNCODGVaWucY9YRUTBBlmpkCjB9a1uKJhZaC6M8pXMmiHm6V9jNQOBhA4EQBL6ZU0kSq1bAZrbTsMjUJk0Sq2JfkmhJFLoR83ZCrXk2WV9kC4hFy9pGgldrGyMqMHz5QOTFa8OTcf9CSYKqR0SeCfJVsXE8K1On4TswNmSoLSeGzdydHIG+QdOe8oQJIq9MGa/7bm+I+eSdmfWwU4ZjXUVx9txpSawsG6qTbX776WulldIgVjhRhrs+LSS2hkYrXYGyyIn4nuUqIvRNvEulhI7HkFoZbdkoIU3iteok0drHsBfvQxT3rdr4FHJwl3aCq2UHoTasSgwLNbER0dVvdqVa69hvoENNOGH6flaomQpSeA6Uh9JESrLAqSGlphmYcgIlkQe8zczFWIkmCpPxw2+ggWi4REhvwnWvQ2+m575FOek3TV4BDM5eTxiKSlXzsDMFY1TaKYgCk3grXm+2q0zmWzBzCMBx0bVwBlWvi6IykiIILCypiJSkGdg4sWHramHYjlzL6NvWNrXx/4Jsw9z/FcvZZ5+NZVksWbKEWbNmIeMX0UEHHcTAwAALFizglFNO4bDDDuOmm25KrjvjjDP42Mc+xsc+9jF23XVXfvGLX/Cf//mfCZQmn8/z05/+lCeffJI99tiD8847j0svvXSrdTjxxBPxfZ8TTjhhi9/+4R/+gfvuu49sNssHP/hBFi9ezFve8hZ+85vfJMG0r7Ssrck73vEOrrzySi677DKWLl3Kt771La677joOOOCAV3T9n1t23XVX9tprL37wgx/M+P7GG2/k4IMPTpJmbE2uvvpqfN/nk5/8JAMDA1scH/3oR195RVqsIZadvKBx3CS9vXAyCCdjPEPaYEN9Fadob2X1jBPS6CD2Dglp2CyEgCgy3OJpc4RaE+iYb9w2rDghknQ2IJ0NQJnvygRorU2yJkJ0aILFNJoSIbNSDbQfYWlwNciOHCkNE7hM4BJ6FimhCJVEWual5doRdW1R1xZuNkSFkmynjyVbHjO55cvLso2iaNnoKEiC3gJlcK7Jtn8rSU3riKXlSWsaNC1Sa5qEMee9OSTG0yLT5kUabVxt4AJKEW1aTbRpNbJ/BwCzo5LtxBKSmt80Oy6t5FprH8Oav5vZ0Ui5IAQpJLoZoJsmhZaroTOCug4hlaamQ2TWorPYoLPYMF7nXNooNtWJWBHzjZIWK2oEPro6aYwdJPk4iFj7DaNcBH47D8K0vkkh6bF8eizfBB1rRYBmzBbYGUWn6xGGFmFota+NoTgtOBJCEqCN8Zcy2OvEyzeNIaOViAxMUqDWJr8g9qoHvjlqE6adzVrMKz9lPNAdWSypsaQmCE0Sq0gZbnFdrxj62HoF7TXQXsN4XqVFWrWpPVvzJ1kTydoK279JC5HKIFIZ87dXI07Va5RiJxNTTQbJzkVLwRbSaXvAlcnC7OYjJAZn7wBW3sbOzfSCTjXTjEUpo9g3GgaK4jVjiskOc0RhnDjM1KHl7U1oYlvjKqeNUytZVZKwyTHtBbCnrSsVtc+Jedlb7fV0opLG42UkjJli8JoJpCahO23VQSvU1LCB+UQh0bqVWP0LsfoXmt/G1xvmnigkevZh5PzdEtpOw51faUPiWuMDqKY5AiFMzoN4l1FFgufDPM97efr7KvT3VZg7q4xe/ci0BrzomSIthLCQHRnsuH221ub+rYRaWplnjlJtj39rN0RptDLwUpNMrWTWWnWyvYsYG1c6PqjHidpqJWMIxfTHKIUtzE6WYQ+Ld/i0SGJjXMxcFMU8jtBbQA7/bKL0q3f8Dco2E+yvWHbaaSfuv//+Gd+9Ery8lJILLriACy644CXPecMb3sCKFSv+aNlDQ0PYtj0DGjNd9tprL/7f/3tlkewvV9ZLteu0007jtNNOe0Xlt2TNmjV/tPwFCxbM+O64447juOOOS/6+8MILZ8QwAJx55pkzMgYDnH/++Zx99tmcfPLJSCnxPI9vfOMb3HjjjS9bx+uuu+4VMem8ElF33GI+pFMmoU0QzvzsxI8JpXlTYUfjQRIW0e03odZuQvR0IjLToD6ZGPvvB2xnFVBDY/RERSrrzUs+KyxSSDoiKI1k2LcZkREh1bIpI/NMlQU6RUELms+Osb3upagEjedC5mtTdl4LRr2QOeummBVBVmm8J0eYH8xh+6yBYwyNFukr1niq3Mn8nkmen+hkcf84Fc/sUDlphYo0lYk0SgvUr34MUhhISytewrLQng9BYBSheoMDCiYuxI59I9FtN6LGphCdBbNV7vmIvlkJTacKIxbZnWwXWVQsFyUEc0WWvIqDH4G5QchGx6a6xsK90yQ1U46DDtoZW5XjIAYGCB97AlHI8j5nPst7Zhl8PQaKg9JE8se4J3+K2ukn4uwW4aHMWGISaPWFEeO2xVwrh3rmGXYmR/25ElPlONusDvFWjpPuvBOqdchmjLJZj3nnsxnjAZ+qIIp59krPoYCFjyb65c3JXMHzIZNCzhmAMERHEXUUjcgoTvPcAsGT6+hX/fSEmskNGYKovVsX/eoHBoYR48p1uWoCqvv6DDwB0JUGeZ1BNRXRL2+a8SLXDQMDEpk0oqeLflyi9aNYdKAiSfTTeP0EcfImpcwOR6iQfV3I2T2siylPd5s9yshwhtn5KtEvfgTNOKg3CM3/ALaFXLAdYzbMisCyFOrXP2knfQojwxeezZjroghSBpqk474V2Qza81FrN4P3fdS6IVTnI+haI6HxbM+xXvM5bnNpxIyfigSztU1TGMXR2xQS1C1m41MITV37OmoUPZvwt/eZPnZtCCOEayOKD5lyRqaQT65CTZSRK59AT1VMW+N5Lbs7kvXRokpM1k58jvb8tpHm+YhC1qyVYh7hxkZJw0P0dJlrlGYpWSIBXbH9sMjpwkGQxSV4ch3yhSFE2kGHCmG3FV7h2MjeTnQYoVKuWTtKo1K3xRMqMknMUq4Z5yhC3X83Io5V0s2mmbMpF7ndoFnzQGO4PSfHbRivZUi5wkC7tKBDhWgEU5OZeDpZ9N7xO+x1a9tz0Q/Rk8YTL3o6ET3dTP2uzgtOB/vYJRq+Y54/00SHEXp8ylwzqwtRLBChzXhhdjij28y7U0hp5nvKNesN2Lixg9mRoUCNfvWzOFmZQIfTMjVvN4fnrBQ79/lEnqBcSRNFFt9KwQV5MyfnTOYJnxsmmgpp6n7CW38E+72fP7v8jVJYvlqyTbnfJn8W8TyP9evXc/7553PUUUcl7DL/02X9b5PDDjuMZ555ho0bNzI4OMjatWs577zztmD5+XOK6GlDgnStjigWjMLQaEA+3/Yy1hrUYp52DYaLe1YXoquz/SAOI0Qri6VS1PQwpBw8YVKcg+FR91BE8Xejls3cKKLQaZSx1GyBt8Z4jNxeSeM5TUoIUrMhWGcUmQBBXUhS/ZLys1CXAu1DWVo0ffNY68o1KFXTdBPQKDkURIjXcMjG8LTQkwaeITRpO4SOolFSqjVoBSdLiahWoZg3SaGkoKInUUCqtfHZ0YEII0SnMRoEIHL5xFMplKKi11KVEKDIqgjDQWIniYVK0sITkOkOEV2d6LFxyGYQuQx6PA66zqRN1tmYw/63bKCAkxhTIpM2UBzbpXb6ieT+7RqaF/4TkkJifNWlwNGCqsQwDRXyTIkpnEL7RRohjD5dLKCD0CiVUqJjA0HkczFWO0T0dDGl12OLFBUdIrJdSb/pUtkospls0i8WQ/gxXt7XAVZvARVz76dzAeGkTJR/USi07yljrHEmDbk8zdgPLzIp6gKsog3TYWjT0853FKHQwRTrkZ05ZIunpGWESj+pH0qjqzWwLERXFwVtFDKv4WChDXd9LgMtZTaMEsNJpNOQLyTzM1vwzdxoKbqNJqIYx/hEVURnV7xTUEf0tA1ilAbXRhQKiFlNhG0ZBbs7bp9lI+p1RKFo5ieGtz6ViZloIslYNaIHmwBw+yRWOaL5vIXfgjPFXSBnd6MnS4ieTmOsdRYSY0d25REpF9mZNzkSXtiMzDim7XG/zlgvrbWSzZrvAcoV089KQ73eXivFQmL0CKuK6OhIYiUmxDiDyqLSKkL7FIVLnQhZSCNSDqIjh/DDpC5CKWModRQRpbIJJs+k0aPj0HI85IswPgmOg+gsojYMm92t1vpJuWbOdnUadqtsDoIAJxsRJ6OmuM70dUGZnRIAB4UURqk3U0jgr/OwX9eRzEERBMkzUhQLiEKRdGdINAxSarNz2NXJdBFBYIzIlIvo6kTk83iMt42iIDJxNWFk+kGpuD1mvaWdkPEoRSgEIjfN+RJGifFFroAvRhDStCeILGyp+ExvhbUbzFoedUGkbWRWYaHa8/DPLX+jHvdXS7Yp99vkzyI33ngjJ554YpKl9X9LWf8bZTqEZqeddmKnnXb6y1YgFysc6Qyi4JkkMZmM8Vwp1fY8FhpMqjW4wiZAQXcvYnIKkc2alyEYRSebMwZBo2ESJeW6mf6YntI+KQxMIgokQzbMiiyioAVlMZh7AOFK7HirmGmOHIUmpyNQkNLQFOBun2OnFTV6e423dd1wJ3N7yzw40cuSOR6Pj7rM75pgtGaC/zK9IaXVGRw3MtvQLWXJssGNX4a23W5/vC0+pYaxkASipYQWodEw/7eu7Z1mgIahMYoEVHRIU7g0tE80DXvgScNgAyA6Ott9GgTGUABIpRH5nPH+zhlEs56aDhD9MctTrYLI5kAInN0imhf+E+kLv0rz1nOSNli6peDDxqiK6NqJGuMIG9JubMQFKaSLUbgwSrZJ9BOPSS5vtEOtEdksDR1SQtIkQkyLHcG2zLmtjKKBj49uhcIyqhogc0wKRcqSaCVI2SEFO+6Jrm5EGJp7WSa4WuTy0NVHNe4t0ZHDQyNcy/T/dGkpU4UidM0ytKquTYDAdqN2vzXbjC6iXjPKdt9sCEPKwrwid+zwmKp0sWPBR3R3m3NsK14jZnaLdNpkecXAN6JAIjo620psK79EKgXxXMNxEPmCgZoAdKcR9ZrxIHd1m/XV1YmldLt9Qpr+6I0ZZ7QCViXJtlrSosBEQUwjn2RTbZGICduCeMeJYt54dGMlU4+MGcN/fBLR1Yk9v2Hqa0+b97bdXi8yrlc6k6wVIWTSfm1Z7bXSUubBXNPZkyj3AS9Qlab+ADUVIKQgjWUU+86CUcStoG1EKB0rwd2QiQ1K3zPrKBuzqCllnmuZLNSqSMcxv7fWV6Nu2pfJmERN0yB63lS7b7NWyHrbRkUmq2sTCzTMn22M8KBpkd6t24x9SwI/2QkQhQL0mOeDAsJI4oW26ZvpDDFRaAwiIRH5PHT2UOJpRI8pV6ZqiFl95lwpEYFv1kqPYTEKQosuaRJT0TU7cdIIpdu7TZ09wHPIbMtI0URKsnmoSGfGzFcZpWco2uJFRsg2+d8p25JYbZNt8jcuH1lgaDYrOiQlJC6Ssg5xhCCDRSNWpNJYXH4sZiu+XOMff+SwUKcZFxETOg72i8uc0E16RJpvnd3P2V8c49M7bubBxwyF51uu2Al8j6l/f4BVz8xi+/5JSlMZyp5RqO9JuZz5wYBoeIorbp/FWcc0iYZLfP03/ZxxfAwvGZ5k6pGA747085G9NqJDzQ1/GOTQwigrJg3Tzd/tsoHvrR7khAOH+fydszj39cN88/dzOe0tJvj4y7+ZzY6BYG7kkbNDbnRShGi6tU1JmPsEaLqxCdB4KHq0xUffY4JTVclsW3/qV930aotxEdFE0YvDKl0ljJXLjLC5+uwB/HtXkXrbvjRuvpf0Icvw73qMqGzOmXwhTef8Jvcun8tNqTqzhKnLlA7oFm4yVjVC+knRRPHZE4xyeep328whBWGTQuKhkAiaRHzj4S8we3uTtXj9x/fmuWvLbPf6KqljDuWd/3QnPzhS8KsfdrJDyrSrUPC4Z3IWjzohs7XNhIgI0PRpo+iMx30zoCzGpOK8d1YJN1aQRYfP/aoHAB9Nr7aYFIrHokkywkYBN//+UoaOMMZs3yffwsVnPcHZh4zhPd9kxWP9zO8uUa4YT+rXbCuBPgF0YVMi5IWowi0X7gLABy96hmsP9/n8z7tMJt5p8zoTX+uhWaNrfOeUTj7y7zXOFj51z+HfWsgrIVBakxKSNCbwebP2mNQeN51m5tJHv1Xji2+e4tu/7mdYKrJaoAELaMTsPxLBQ9EEN//rItZf+SyNhsPVImMyAAN5rGRMU0KSwaKiQ7LCwonrOqUDBLBMZ3laeszVLuMiogMrMWhCNEUsntN16jokLWz+ReuE3aSQ9tj+HSBnGUPrx19T5JWiT3jkU2adPhB2UIw0q13oVoIJqZP/R4SZT7O1zagI2SlyeMYKySKZbj7UUTPWSzTtcxA/CXq1TVlERBDPh4ieeF60zunRFs/QIEKTFhZXHlZLYDcA1i47InpnQbXCZeevo1eZnaesgpEY19YfCcak5gXRZBYudRSj2qNn2tqZ1D79Ik2diLIO6BEpXASN2GvgIunVFiWheCKaIiMdIq34Jy+HjmfW/p+fR+2HD5F5/Rx+8O8WHZFigVPDthTVmG0q6wb8JwWGRYAfl20hmKvN72MiZL2qc5qXY7+TIu652qIoA36YcmYksbIRdGmLrIa1MmScgK8f53Lut02ZOSxKhEzpdhxQp3B4XhlY4o0H+qy8rZOME/AzmUdijAkHkSTlWkWNaz/o8r3rXDIaFut6En8UxsQEOx9Y4sJ7ZtGtLY4pjPGNajeXr3l52OirIZUz3/aqlVW44qevWln/V2Sbcv9/TFpZZluZYLfJn1e01nz4wx/mhz/8IZOTkyxfvpzdd999i++WLVvG+Pg4O++8Mw8++CALFizg8ccf59BDD2X16tVb5eD/3yK1C98HgCjmDfY3jMxnz4cgNFu9GF7ls75rgmM7sLnoHzOEz27E6utAdMReRa0MpKFYQI9PcuLXJ7n6xBzf+XfBod2bAThrMo0rLN4W5Nk9VeKpZpG5NOmKMZ4Dezb47AP99GmLU/bdyOfv72e2sjjh9Rv4zEPGK9WnbRb5moMO2MT37p2LDfzDwg387qk57N5rOMM3jhWZ011m+WQvf7dkA/c9MZfXDm7m7o0Gk3rQThtoTDlUyymavs3OH3IgkzJY40K8E5FJocZKCFsiUi7RWJl//WUnEZrOeOPzk8eGqPEKsiufnG+9ZofEq6gbTY6/fBP76jx3iTLvCIvcbtfZP8omW6d9YcQm2+KIwU10Hb2jgeIIiegsJFhdMJAYtXkckUlx5g1gI/jiafHckgJdrqKbAUSRgeI4NoNffJjNL/wSgP12O57v5nPc2uzm13qcH120K+d/ej0fnTXCuvVGGSxpm712GSL35kHUhjFEVw6RSaM2mX6VPQVwbKL1Y8jeAv98k8WgdqkJxfnviyEuKRc1PInsKSB33glir/XcM2/hOznD/vN1Z4r/d0yGr38/S08E+xfG2DBRpOiYMpZ8tDuJI8CyDHwkn0XOH+SMT78AwBUftPjSdyzOOGAYe/6sGThdXWth7lOI+fP4589v4EvHCu67SjC/u8S8E+J8Ecpwgya4aKWRs3sgm+Grlxtmkg+/ZZjr7+jnHXM20XlAJ9oz3mQ9HRpiS6zdlnDmBc9ykOeyR9cYA+/uMkGgGKYXszby6IZnxiibMWuu5dXtKKI9n2Dlepylc02MQG+RaKSE1RfDIVIuaqKMtXDQQE8aTZ76wkZyOdNv9brLT4XxRvtCc9rAMF7VZsNoB3Vt6vqagXG8ps3A/hGqGiDzjvm/6CK7zbVqoorVWyTcMIE9r5torMx0sXqLpi5jJWRH1nwemUo+g8Hti1zKzIexErIrjxqvIDqyyXNFjZWwFg3Gwb1NvvhvDbK6Tdv5MGU8rUgLi2ve2kRN+Yis2cmRBeMQUCUP2ZHCmt+PGpk0Y97dgZ4otXdwerpQm8dMDEYmhZoogRcguts7ImrjKLIrj9xpITqes2NXPZa0+drRfvbwNI+lBO+yp/BDi4lmGo0gHRu9TW3x2oNGcXac3YYw+SHRkGEls/o6EINzGL3qCf7fWD8HUqHuOyw7sU1z2ZqX0UgJ3Yywt+tGzOrmnCumuOR9cYxIpYHs6zLQNzAxBZ6PnGueb7eft4msjggQ7H+0MdyRog3jAazX7MCnLxnhnF03EVZhzeoeY7QKnSj5d4oCp7xjimhzjTvunsOhJ/h/kYyvlTOO+OMnvUIpfOXWV62s/yuyTbl/FeSAAw5g2bJlXHHFFUBbAW+J4zhst912HHfccZx33nlbJFb6U+S/qtwvX76cSy65hLvvvpuJiQn6+/vZdddd+fCHP8wRRxzx36rT/4T4vs8VV1zBDTfcwDPPPEM2m2Xx4sWcdNJJfOADH9gigdR/VW677TaOPPJIfvvb37LDDjvQ29vLr371qy2+s22bs88+m8nJSa655prk+ne+853sueeefPKTn3zJe1x44YV8+tOfftnfP/WpT23x/Zo1a/jMZz7Db37zG4aHh5kzZw4f+MAHOO+883BddyslbV1umPOBrX6vYYYnVKJ50/yhVnwjd66dQ1YpvGkvpAiBiuEAjoa3vmY9P39qkLcMDPHMeuMF3X3ZMJEP9QmX9Zs76co00RpKTfOiDrRk0eA4QdNmzWgni+aOEzQt1o13sGjQKJhB0yYMJesmi8zvLuE1HUbqWXrSjWkeTJ/Reoa5XRWenexkbrpGxXOT7ebxuvEQW0KTcwKeCfNb9EHLbxwKSCmNEoI3bDeEtHTCLHHvmgGyWtEUMumvihQJnl5qOPw166mNueT7fEob0xT6PCojqQSZEIaGLeixTbOYtCyyShNh4DrZeEtcY7LpprQmFHDADptQkeDuteZlrhDklIpZeAR1aTjt33Gq5s3fNAl6fvfYdRy6x2l8d9DH7VB8f+Ug712ynt89OpcdMsbj1/RtKqHDkOWS0jqBC7W8ttProYADXrMBr2IjLc3v1g0k50qtiYRg3BbGY6jh/R/Ps+5r6wDo3b7GrSsHefPsYeyUYvOGAlN+it6MMfIe89vYXiUgo0y7y1Lw9gUbAfj183M5YHAT968bSNiHWn2RiSEOgRBULcHbFq/n16vmsXtmimdqHdTjeRsIgdTm2q4oIkLQkIJJS3Bgzsy3p6c62X3eCI9u6KMuZHIfMPUi7pNJW/CO7TcQBZLb180hrfWL9hO2Lq04AIVAoskoTU3KpA2terb6QmoTp9CCdu2ma4h4ByFUkoF+o4hHgeSFkS4coUjJKFHY/MjCEpqNKk1K62Q8PSGS+/SqkJKwsDCZpa147NWL6tNuQ6vvX9w2cLXGF4JQQF4p6kImECFbazwpkuv27xol8C3sGJ5VmN2EeK09vMrMr9a1mVhxrwuJozXjtpXMk0AI8pEiis9tSEEmZuIKhSCvFBHQiCFEgYC80gQCJi2zdmxMsHsu3s2YN7vE5ESWzs4GI+N5LKHJZ83zpNYwz1wpNGXfZaOVmgFHzL5oPu4cNZg3d4o1G7qxhWKtSM+YK615oDDPAU8IjthlPb963FDSOtrkLpj+nBGQxCrsa5WIlMSSilVeMekziaaVUqRsCY5cvJ77nphLWiv603WUMtTArZoUc01WVzpJa8WCjjLLq128b9MN/Lllm3L/35NtmPs/o9xxxx0sXboUz/O49957OemkkxgYGODEE0/8i9bjlltu4aijjuKggw7iO9/5DgsXLmR8fJzHHnuMT37yk+y///50dnb+l8oOguBVU6T/mGitiaIIpRSHHHIIjz76KJ/5zGfYb7/9KBaL/P73v+fyyy9njz32eNV2NZ577jkGBgbYd999X/a7RqPBNddcw89//vMZ1x9//PGceuqpnHvuuTN4+6fL2WefzamnnrrF9+eeey4/+clPOOaYY7Z63VNPPYVSim9961ssWrSIlStXcvLJJ1Or1baad+ClpNkisxAmkZJ54bU/+/FTPqMFqWIEEhpjNg0JKS1oCkEjLiOlTRIXCckLJKU1tVKKLtd4UqubXZxMxMhogbm9ZYTQjE/kSFvmZT4VOUSBpF4ziXaiQNJouDRo4/IbdYdq0yVAIIXGcSLqQtInNX68nbyxnmOH7inWTnSwQ7FEreHiSoUXmHHIxPfLuAFhJKlL046+UFOyYoVAwOzQNGTUlswOFalihFbQmDTzvmoJqnEMQVNAb6SpSZLss7YAHQmadQc1JFk73smO2TEmS1lSjlEalBaMl7LMkh4jIjvDOGjVBeIydVuxstMRk/HvloaqlLja7AQ42ij4z11b5rt5490/dI/TuG35N3jitWfS1azTH2qGnymwtHucas0YVx3FBpsmMzQlZEJN1ZIEAroi06CqFFhANlKM2xYqkKhQYjlRYujVJfSERnlo9YMCfnFxme1dJ5kHOaUZHi6igU0qzWvnjrBqozECG46ZT61rQ2EUaAk0K+bVVVCK6mSafu3xtJ3G0eZcCZStNqQnEDC1KUNeKcJIMteu83Ds3c4qU7atYaNjkVVmLQwGEbWaUdg6CRja1MHSWePcN95HVhml0dE6uY+lzbH+uS4CJXlDfoLf17vxWnHXkaYuxRbrrBgxzdCAlBLkUTSl4RifsgR9oUrGOQS6I01TgtCG2jTthkw1zPgVUj6WoxjZVKCzs8GYtLGAQRpE8dqoKgeBJpKCujDZI+qibewAPO8YsFBKmXr2hAqLtpFXkgJfQE9k1ktDQH+oqVptr3tvqKlIQdkSzA2M8VC3LSxNYph0hZrxuP0ZBW4mZGIyS7HQTMavMeVgp6JEeQczF4ZjxbyoNKPS8OP7QiTPtEm7PQcUQNz/EqhLSUqTGK/QNlxb4xMKmJ1qUI0dBus3d9KZblKtpBiPUsYoKqdRAnpEOzvyBitFGN9HYZ6BrZo0YkNmRKdwhwsUXHOdFwns1nwXoLWpa0prAmE+b3iqg2LUNp+8+J2iAIT5Px3/XApSpK0IPzQGWkq1CQ1UYljBoyv76RE+WggqnkvGDnGtKMkP4qYirIomKyKE1IxPex79WWVbhtr/lmzjuf9vynHHHcddd93FlVdeiRBihge8p6eH/v5+5s+fz/vf/3723Xdf/vCHPyS/K6W46KKLmDdvHqlUimXLliUJnFry4IMPsscee5BOp9lrr71Yvnx58pvWmkWLFm2hyK1cuRIpJc899xy1Wo0TTzyRww8/nJ/97GccfPDBLFy4kL333puTTjqJRx99lI6OjldUFoAQgm9+85sceeSR5HI5PvvZzwLwjW98g4ULF+K6LosXL35Fga/f+9732GuvvSgUCvT393PMMccwMjKS/P7b3/4WIQS//OUv2WuvvUilUtxzzz1cccUV3H333fz617/mH//xH1m2bBk77LADxxxzDA888EDCx+95HmeccQZ9fX2k02ne+MY38tBDD82ow5NPPslhhx1GPp9n9uzZHHvssYyNjSVje/rpp7Nu3TqEECxYsGCr34Hx8Nu2vUVyrUMOOYTx8XHuuuuul+yHfD5Pf3//jOPXv/41119/Pd///veT9rxY3vrWt3Lddddx8MEHs8MOO/D2t7+ds88+mx/96Ed/tO+3yTbZJttkm2yT/7Wyjef+vyXblPv/plx55ZXss88+nHzyyQwNDTE0NEQURVuc9/DDD/OHP/yB17/+9TOu/eIXv8jll1/OY489xiGHHMLb3/52nnnmGQBqtRpHHHEEixcv5pFHHuHCCy/k7LPPTq4XQnDCCSdswXd+7bXXsv/++7Nw4UJuv/12xsfHOeecc16yDS2j5I+V1ZJPfepTHHnkkTz++OOccMIJ/PjHP+ajH/0oH/vYx1i5ciUf/vCHOf7447nzzjtftu983+czn/kMjz76KD/5yU944YUXZnDFt+Scc87h4osvZtWqVey2227ccMMNHHTQQeyxxx5bnOs4ToJvP+ecc7j55pv5zne+wx/+8AcWLVrEIYccwsSEwT4ODQ3xd3/3dyxbtoyHH36YX/ziF2zevJmjjjIBpldeeWVifA0NDfHQQw9t9TuAu+++m7322muL+riuy+67784999zzsn0xXR555BFOPvlkLrnkEg455JBXfB1AqVSiu7v7T7pG6raXvS7bUJyqjD1I8VGNiTl0aLKJKsDSekaQXUNAyTLleBLcfotNtmDWDjU2Blk2Blk6FgZk+iMGF0zy/GgnpVKGTCog7Yak3ZCcjtBKYNuRYcQBLKnIECWJeixL0ZFrkkLHSY8kaa0QwsAgFIJep8nYVI6BXI0N5QKFvMdk5CbJmsYjl1Lk4odWgld2tPGetvokpUm2+F1ttvOT5JuOwnIUUhMnLjJeVIXxXNZlfAhIzZV0z63Tvdhj0dxxcgMhfbMr9G1nDttSzJldphy5eALKlvHQegLK0hwq/nvKMsw6VkphZ42HMcKMUT1+oo/bFhsdSVUKtnt9lVub3dza7Oa7gz5PvPZMlj5yBR2LI551BQNLKzwy2Uuh4FEoeEShxNZtOEDr1Ri02Ffi+9Vjr6l0FHYqMunrIZ4Xpt8AJiWMWqYNb95vEwteX2LB60t07aoYtwULFo8ze1aF7ew65ckMRRlQlEFSVkQLDmLqUpKQ6/XJ9fpMWJLO/jrPWWkDraFdP1uTeEIbArrmNZi0LKTUTARpAkyS1JI0c7ZsGS9+EM/1NY7F3EVTzF00xRNOmkV7GK99KAyUwxMGvtOaK5GAcQt2PKDEvLlTPFA361BoczSFSPIaVFt5nzBecUebI2ytO0SyvmwNFSmTnQGb1i6G2XWrShJIDhhYSKY3om9OhXyfh0U7qZZjRTiWwWFrzM6Do01iNSs+WuNcjAx8Ix3XYdKWlCxJRZqjVf/Weml5waVu72IEwnj68/HAaMxama5utSA5rZ0MaWt6umuk0iGpdIjbKyjO98n0RXRFkaGaxdSrqMxhawOp8WSr/+K1Ik2fhrTHtfXbpGW+8+JnFRivusTM1812u2+b2qKpLebPmWTu0jK9c6q4KDri55OjNY5UOFKRtkPGW6lB4jZHM+A28c4WPnMXlKj45hlEPK6haHnX22WAmV9zFpUYtS1GbYspy9CFTlpm/k5aZj4M2+YY6K6YJFR2lMzVmpR40uzo1aVgwoI99xpmApe6tiikfCIlUdrsiEqh8T0LqSHUAq9pb1Ma/4/INljOf1M6OjpwXZdsNkt/vwn2ayVB2nfffZFS4vs+QRBwyimnzEjAdPnll/OJT3yC9773vQBceuml3HnnnVxxxRV87Wtf44YbbiCKIq699lqy2SxLly5lw4YNM5IyHX/88VxwwQU8+OCD7L333gRBwPe+9z0uu+wyAJ5++mkAFi9enFzz0EMP8eY3vzn5u5UN9o+V1ZJjjjlmRpbYY445huOOO46PfOQjAJx11lkJRGb6fV4s08vYYYcd+Mr/Z+/N4+woyv3/d1V3n/3MPpPJJJOFJEACQoCALIJBFhVcQK/gcoEgiuASuSgqCAiICAIXIgqCSJBFwAVBEERURCEsshMIJED2yWT2s5/TS9Xvj+rTZ4YEwa+gv3svT17nlZ5zuqtrear7qac+z+f5/vfZY489KBaLZDIN/PM555zDQQcdFP29atWq180yWyqVuOKKK7j22mt5//vfD8CPf/xj7r33Xn7yk59wyimncMUVV7Drrrty3nnnRdddc8019Pb2snLlSrbddluy2SyWZUVjC2z1uzVr1tDT07PVukyZMmWribG2JgMDAxx++OF85CMfmbCQeyPy8ssvc9lll3HxxRe/5jm1Wo1anZIvlDusMSxhMaqq+Dpgkp1hWFVwlU+XnaakGomUFn1kpygr5a++vYL5iVY26BJDyuCkq8oDBa4OSEqHT354IY898ASfzghqIcA8cfQhJnHP1XfjIundYYyBlRlWlU1g28NJOP0wk4xm6U0WZ34gC77iZ7+wOfWjho2FIGDdzUX+lLQ4ZbcKIib55Z+bOdJS0Yu0e0qeezf08OF3DHHHUy3sNrfMr59oZ+99jGnxk3sl76poNntJdEFwr13CQxG3LJP1FHAJSFg2CSGjoL5DPrh9yKNuzrnrskGmixT9ukYVn5hl8ZI3gg7LsIXFZw4/AOsPD2Af+C7U0ntJHXMQzt33o4qmrk3lCpkpPv2DNneJURwkeWqkRCx6mRZxabUSJLApaJcj3z8H0d7GbU8/BUBGxpAIytJnipUmQLMxKPKfn3w/f1xmFtqLmhWt1XLEg3/utAP48ue+xOpnnmDSoOn/3s48L8QtnhJlsrZNiQClNZmQt7+ofWwhaMKhhM9HD5xuONITDvdtMHqgtCZlW5R1wHNuYzfu80ccxPqzTGK9mX+6hF/ucRLH/OfupP62nId/k2Y7v2io+4BbxTAJ2YAddMoEo6rGy+4QXzj63QDcdsZyPvbOVpavC1ivK1jjjKh4qG81rXjJG+FzH9qBu1f2sbulsFHcpk294tJGa40tLOK2JC0cBoIyY6rKou1MsOL61QqZMLCtB+wKKYyOWIiI9UWjebS6kS/Nm4P75Ga2VRUuiflRbgiAtHAYCSq4OmCSnaagPAKh6LTMfYZVlary2C8xiafUKPMSTfTpMgodMaLUCIhbFqv9MVztYyF5t5WNGF0K1TiJ3SaTAIjHGH5R0RJA3PHJZs3cXzGSpUkFPJTQNGlJXiiatCQnFKu1ib2YKzK8pEvMFile0WU81ATDzkJGdVFoAjQxSxKgDVUukAhhIwGauC0p64BekWSzrkVMMgnbYp2fR6MRCI45sAM1mEc0m0Bka+89I9rMe5/9Gz3aoiCUydcgTBkpJGUUL6siMWlFfW4hyGHgPVmRwBGSvKqRFg4OkjFRIykM5KbNieMgqGnFCncw1DvNdD2NDmHKa3tXguITAa1feBeFr7xMSitmZvJYjuKxvHk2NXkBqxIe/aJCTZs+s4RkujDt6dNlVnujTBFTmb8gg79KkJKK31slxouFoFPEyGDxii6zKSiy6IPb88eXTN0ywmazrlJUbqT3GRnjZdfEiRzT6zCaS2HJgL/EajiYsYmFtLUAz3hDfG67ZtY8K0kpSatnR0Z9PaHc7PdU+dE9GonkGC24Txb4PP8C+T/qcX+z5G3j/i2UW265hblz5+J5Hs8++yyLFy+mtbWV888/n3w+T19f3xbJivbZZx+efvppAFasWMHOO+9MKpWKfn817GPy5MkceuihXHPNNeyxxx7ceeedVKtVPvaxj71mvXbaaacou+ycOXPwff8fKuvVHuoVK1Zw/PHHb9GOJUuWAHDjjTfyuc99Lvrt7rvvZt999+XJJ5/krLPO4qmnnmJkZAQVYuzWrVvHvHnzXvN+WuvXDQB++eWX8TxvQv86jsMee+zBihUrAOMhv++++yYsJMZf/4/wzVcqFRL1xEevkmQySblcBuC8886bsJh4/vnnmTZtGmDiF/7jP/6DSZMmcfXVV7/hewP09fXxvve9j4997GN85jOfec3zvvvd724RvHvaR/bj9P9YaPjutYJiAbJhMGOpYHi5TQX5wFceBIzBevsP3oNavhw5dTo0tZhzLLvBD10tc/AX7+Web+3Eku8McsxMEwT5gS8MIoTgMHp5f+cgNy/vZZ7rslO3eWm9Zx+bU67PksDh7A/kOO2mLAkkp793mK9ea+qVQPLeShPf+OgoV945BU/ASe/q494/TWZ2SOk4uCnLbk6Ohx+ezNHb9PHwssl8sncTv/mtCco7eYf1FAdiBJ5keCzNT74zF5yYaX+9zU4MyiV0rYaIx9HFIod/zzC1xEKe+59fsBt6w3rEpBkQT0C5BDO2bfB4Bz4HHn0z+zvdPHjn/Ryre7nuv/7KoWJS5FnuCDRDmwWf2HE9HzvuAHBrZgxq1YhJhVQa8mOmLs0tHHHK3yiqtdx1ebi7UymZ8+MJ1KpViGwG0botH/nifdx6zjsA+MmZfXT7mpeGBedOO4DRdX9k5rYf4oXPbccrN5ndi2eH2vnMQZuIHbQHenQU0dICQqBzOQBEU5PJODsygmhr4+Nnv0CLjFPSVa4/pzFvdT5vzp3+AcPDLSyO/NQtLK6ZMdxl1vsZXvYDDv/gD9lbtvPp6ZvYsLYlCni+7dL9TV+CYcsZHkQ0tUDvLD571G8AuGlxN2f/oMSZ7x3BWbhnI+EaoItGD0QmA1NnseiY37D0Sx08eGGBWV2j3HnugebEWtXorOehC3mTW2BSN9Rq3HqKGesvz13PHQ/3cmDHZv7zpF3Q5bJhHnG9KFkZjoPc4XDO/NSd7F1tZ8e2Ya775h4NnvU613m22cyzcsnMucCHgulbMllQiuBvT2C9cx/UiheQ3VPQxWIjh0Cok0yfbeaZUjxz1O+Y3jNq1M2TfP26ViZpm5rwOekdG6mNWTy2upuiZxZwu2VGKFcczvx0xiTXSidNFtxMGtltYIBq7Qbk9Fmo9RuRvduY8besBod9c7PR9/p8sWxTr/oxmL9t24xfuYxIZ9B9GxFd08F2Gnrbu03E2f+Vz/2FWaqDXLid+Pvr7yIpDU3kb47vNIn2sinD6hUmoNKVKiKTRvRub/IWpDNhorVa41lWqzb+LuTC8xrJtCjkTR2zWeg9JJq/pe/+lCCE01/7617muWlu/+ZKvtCSx3MtXi41oRC8I2HGsObZXPApGzlv5zA/hIRqBdW3CQA5ZSZMmUn50hu5/le9zJcVRrwEPzm/sTtu9MVD9fVDECBnbAedkznhxPu58kttoX6XkHN2btTf84wuTTPjt/xTd9AfJAgCwSVntJn+CPU8yr2w/UFc+um/cMI7NxAUNS8/3W6w9koiw92g//5dB9/5eAVd83j0phTXfW8m/wp5m+vln5O3jfu3UHp7e5k926Sqnzt3Lq+88gpnnHEGZ511VnTOq43U8YbrG1Xuz3zmMxx11FFccsklLF26lCOPPDJaENTx2i+++CJ77rknAPF4PKrXP1JWXbZG6/j32vGhD31oAhxpypQplEolDj74YA4++GBuuOEGOjs7WbduHe9973txXXdCWa++37bbbhsZ6K8l9b77e/VSSvHBD36QCy64YIvrJ0+e/HfLf7V0dHQwOjq61d9GRkYiWNMJJ5wQwX6ACd7+xYsXs3LlSh577LHXXChsTfr6+th///3Za6+9uOqqq/7uuaeeeionn3zyhO9O2PEojn/sWdzQM2cjJxzXRQrBHSdPNx4VrVi0eBm9Iskgq/BCrIpGRwGNFpJ7Fk/jq+dt5Ly9B7n7ftPW24+pgtJUn1nPQ0/28LG569m8uolnNncC8MqdkvPfO4CuBlz9m8mce9BmVDVg6d09XPBe423V1YD+v8W4+s52jtluPcKGO+/r5d1TN5EbNl7QTaU0nYkKk+MVXnilk+5YhTUb2tij1cRULHt2CnFt4EVdTpXPfnNF5I2tz7z63wlh4aNIYPHr/5o6wav06W88TbuIM6ZfBMARgiH1fPS7RnPvSTOoPfoKp27fxfDdm/joe9vI378RJ236rTToYDmKO5b38qdTnsIRkoL2SGDhhEZGIeS8lwjKrOPmT2cRTZNZ9KUHAMPTHReSkvaZS5oxMUaJYX7+YcEZZ68H4Bvz+uhflWX/HQp8+XNfYua2H2L1yt+w246f4kfCjM9OnUNc9+fJPPbXlaSwqDFkOMhDXfAwY5DCokqenx3fYgxDO8EJ3zKQQhnWJ2CAYfUcKtSLn30gYMO9xjM8dPPpzH7PN1j1i8W4N/yc++7upltWGa0Y3V+0eBkpYSEQuFrRJGxcNjGsnmLpvsboX3JZiq/v2sdNv+3lz797GmucvibDxVdFB+T00/zsQ4qLL6vwseYCTw128M3Fy0y/CQulNbYQpEONH9V9ZIXNCTGzE7F8+STe1TXAiv52zjn7ZWwkGk2DmRxcFJvVKn4yp0BpKMbjA12cddpzkRe7Pp98FAKBhcCve6/DuvpaI4Vglk7y3M2P0iuS5FhLCosxzOI30BpHCMbUi9EO01m2xTN9naHOCs49oJ/yao0V09z5TC8ZpdmlYwgnYRY/m/qaScY8zrlGoYkBAYoYEo8Chs2oE4dB1oWe3rW0hPke6po/qPvDPMtRzl8EdQiV+abuUZb1QGgd0C7i5PRKgvCcuJCMqVXRfLvu3RXyL0C8ydT16wfOQA+PgZBccA2UiRPghzpvvPIVFIIiw/ppHCGo6oCYsHAQ5EIvfgILO/wtLWxSWAzqGiKsY0pYWAgC+hlUz0ZwmI8EvRFj1Ycm9zOwOcs5e43xxJ86cYRiXscIQmhWDrSFdVJ8/4YYL4jncRDh3LEi6tx+VjKmlvM+1cvBTYNUqw4d8RKf/ebEd5olBG0YI3xIv0hRL+fad5c57wfG8ZDUkpdE4zljZopgQD0LwBf9NNu1jSKF5ssXeluF0/Sr3/DDyWVuXzYVR8MOTh4VZqqtG/eL529gyc1TcUhxULzA4m+9zI+P2Uphb8v/r+Rt4/5NkFgstlWc/avFsix838d1XZqamujp6eGBBx5gv/32i85ZtmwZe+yxBwDz5s3j+uuvp1KpkEwag+Xhhx/eotxDDjmEdDrNFVdcwd13381f/vKX6LeDDz6YtrY2LrjgAn7961+/bh3/XlmvJXPnzuWBBx6YADlatmwZc+fOBQyMJZvNTrjm8ccfZ2hoiPPPP5/e3l7AxCW8EfnkJz/JaaedxpNPPrkF7t73fWq1GrNnzyYWi/HAAw9EbDOe5/HYY49x0kknAbDrrrvyq1/9ihkzZmDb/9xU2GWXXbjhhhu2+tvy5cv5j//4DwDa2tq2iom/6qqruOaaa7jvvvuYOnXqG77vxo0b2X///dltt91YunQpUv59RGQ8Hide90qHcvm+hcYfSiNsaRLIKMAW6GrIEx0TfH+J0UMJXLVfgaA4ipWxUdVQ/xUIO1ycKs21P0hxzrzN3PaXXt4329Ax3v7TqSSVwhNT2Wf6Jh5d0UNvvMROk4zxsmtMcetdk7E1/MeUTfzqd5NxNHxkyiZuvcssuhwNrYHPx2b08eCzU1DADrECyzZ006xMXeZ0jrJmsIXOZJlmp0Yy4VHynChJ0vR4EdtSJBIe+UKCyw8M+8GW4I9japACVfYRtkD7mouWOAigFr78rjy4jHYLjX6TYmJGx5jFjy9zaQ6mUnsIOv1JlJdK2oJJeKHh3qw9pIADezdx+DYKJMiUjSo2PNEyY+MNjGGlJEi46popFEWZK99laA/xNVppZMqi/HIOJ6sQNtz7yyl8udfkGHjw6Sns0DbMHx6byupnnuCFz23Hbjt+iseX38hzu50EwJqBFj44eTNH76IhZAqaYBnU8dNhGy/7cQ+2TiKA7x/QH9WlLvU+EVJw523dTNfGIPv+sb/nxS/MY5dP/Jjz5Ry2y47heRZ22PdX7VcweqWM7mlfR/r1tz+YzJwfaR3moWU9HNy9mU/sKRv9rnSkkzJlo92A39w6mWN6NrFhYwvzmsa4YvfqFnX1RhRWCmRKUutXDKwxnm5baPqHsmzXOcqluwfRfUydQkdCzAC6H/h9D2l8dmwe5aC9JkLgtK+jcRKxcZ0a1kFVFdoHvwyJGQ7B2CjCFqiyxu6wI32cAFmQgpW/zzK/N1z4avjTH7vpwCMuA/bMjOB5FsuH2iNmmKwOGK7E+PqefciERFUVMmOhygG67luRIGywmmxUOaC6SWAnjU4BxHpiDV52VW+TtcXcMc+S8Dcp0FUzV8ZzutcTVglb8tvfdtMeBNihoq1cGZANsiSV4sTZfaRmykj3VNG0yO6Iocp+pGfYIpo7MmMqrKtB9HuQ91FVcHoaTG861Bft6+gagOrqDcRCNOBjD0yiM1HhD3/uYZtYES+weH6ojQDBtJhZcFZ9m6N7+kjP0KiyMuNX1VGsjt0kETFJ/oUywwNpBqtJvJLg8g+NNPotbF+Q95ApyzxblObPd0/i89uYHYDAk2S31dHzWSuNkALZZOo++IjHK8OtKOCi9w2G5Zpx1X5DZ5++u519OwbRCjaPZLGkImYFESznj49O5bg5G1G+ID+U5NyeHP8SeRuW80/J28b9myAzZszgkUceYc2aNWQymQheMjw8TH9/P77v8+yzz7JkyRL2339/mprMC+OUU07hW9/6FrNmzWL+/PksXbqUp556ihtvNByyn/zkJ/nmN7/Jcccdx+mnn86aNWu2SnFoWRaLFi3i1FNPZfbs2ROgO5lMhquvvpojjzySQw89lMWLFzNnzhyKxWLEzDOeovHvlfVacsopp3DEEUew6667csABB3DHHXdw66238oc//OE1r5k2bRqxWIzLLruME044geXLl/Ptb3/7DfQ2nHTSSfz2t7/lgAMO4Nvf/jbvete7yGazPPbYY1xwwQX85Cc/Yf78+Zx44omccsoptLW1MW3aNL73ve9RLpcjKtIvfOEL/PjHP+YTn/gEp5xyCh0dHbz00kvcfPPN/PjHP35N6sqtyXvf+15OPfVURkdHaa1vn2Ow+Bs3buTAAw98zWsffPBBvvSlL3HmmWeyzTbb0N/fP+H3ZDJJc3PzFtf19fWxcOFCpk2bxkUXXcTg4GD02/h4gNeTNQ8YWJIUmlgsoFozj4VE3Kdas7HC7XGtYZ+aMYgK2mbdAym0NjSOdc73uOMzVk6QTbjYdsDC2CgvPt3JHulRNq0xbZhFGSUECdtncFOWPttiXrZG01RjVVSGLFoDxSZHIqSmIwjY6FgIqWkNaeA2OpIpgQmwbcPjZcssWHqpMkqYCXIkTVu8SqEapylZoy+fZWprntWjph5zWkZ5criDvbv7SGQ91v7J7BA5ToDnxaI2x2IBnmfKt6Ri/zBmoRomBFr3x1jU/vr51Zodeb6k1OxHActRFKpx4rZPxbeJWSrCl+e1Q4oAr2rxzP1tNMVrJJMem0ZbaA6ziqZSLsO5JlozFYSAhRTIVWOs/qtZOOdqMTKOR0tThbG8WYQlYj7bxItRgqptkgWKpTgL2oeYNNjEKze5/Ej0REG2AHfteDqjIymG7hVkUi6+L6m6NpmUqYfvS1zPBCEHnmShV6YQOFho1t9vFk6VmkM2XcP3JX4g0Vrg2AFzZImubrOIOnJ9G8t/EvAjMYOYqDHtmDYevMwnGXKKr/1rCscxBlcQGEPYthWua9Fim7rkCwkmORVGR1KU7p3oYKmPiRAapQQzdYWhzRmSjk+umKDyV2PYBcrob9zxkVLj+RaubxGzA5IJ4/X1ypLWZJX+oSyV+6tYlkIrgbQ0rmtF46yUoCdexvUtcsUE7v2NZ0g84VOpONE8q19X/z46L+bjeRZyrUYpM47pjEv5+UbuCscJorlpSUV7W4niWDzqqwVTNzMymKbm2TyfbzH6E+5SASREQBzBuqeasS2FUiKqf50Csa6/Qhi9TmdcRK6R36H8QiyqixfSy46fO2a8AoJw/BvHjbn16uul1GxDhUCKiNL2naJARdv4SDavz2L3NRYPStXH2PxdqMZoSVURUrMp30ZLrBYFyw+NtdCUrGHbARvyHTRZHntp63cAAQAASURBVB0bS5SKpj5+IEmnXTzXwg9k1Ld2zKb4sunb6W050i0uI68keFJnURKckPIyFupqzAnYtL6J1ICHkDrSk6jOgYgCVm1LYaFxUKz749Zyk8SRQkfP2A5cBjZmw/4TDA9oap6NJRW+kqTjXtSvmWwtzEir6VvWcOhoJRDhMz0IJHEZMDpm9CwW0gN7gRXlRCCA0kiclulV+l7OMJxPMWkrNX3T5W3j/p+St437N0G++tWvcswxxzBv3jwqlQqrVxucZt2gsyyLyZMnc8ghh/Cd73wnum7x4sXk83m+8pWvMDAwwLx58/jNb34TQWkymQx33HEHJ5xwArvssgvz5s3jggsu4KMf/egWdTjuuOM477zzJgSp1uXwww9n2bJlXHDBBRx99NGMjIzQ3NzMggULomDaN1rW1uSwww5jyZIlXHjhhSxevJiZM2eydOnSvxv02tnZybXXXstpp53G97//fXbddVcuuugiPvShD73u/eLxOPfeey+XXHIJV155JV/96ldJpVLMnTuXxYsXs+OOJjX9+eefj1KKo446ikKhwIIFC7jnnnsi47unp4cHH3yQr3/967z3ve+lVqsxffp03ve+972uB/zV8o53vIMFCxbw85//fEJ8wU033cTBBx/M9OnTX/Paq6++Gtd1Of3007ea7OqYY47h2muvjRKY3XfffSxcuJDf//73vPTSS7z00ktbePv/EbziS655WdSEIFbToVdaEHPDoNLwzRnXmnf29iOkxqtaPDbQRSxMclRPBCN9TZNSbKwmcLRmbssoJW2TDWSUXGpyZx47HlDOxxnOp9jdKfDkcAdtg8aQ2mTFOGDbDQhL84cXezlw+w0gNPe+2MuB2xrvv5AwsDbLsg3d7N45yDYpn5fWtLNN7wg9vqnLuv4WktLDCrntm50aY/kkk+IGarF5OENSKR5c3cM0UWGdTuILSFZ0xPXtC0hWDaQkEIKUUuw8w3jB/ZoxSP62uSvqS19AvKq3SPCzW+sQxVKcnkk5CrkEnV1FSrk4dsy8TDOhcbdioJ2ilGxyY0gXlITNobFk5cy4DBTiKGCXSYN0Jgo8FCaOUhI2BzGckRQt2jeBxV6cbTrH6KsaaF3MDWhuquDWLHo78zw71M5OnUOsGWjhrh2N7h2y/FyunX8m7b5C5lON5Dd5U4YSwrCrjKXRwPzuQSZpY2A9FvaFBqx8kkCErC9A4Jl+2LzJODemd4/xzOZOtm0ao1J1uPuHmvcfr3j6aqN3L9aacKo67Fdzzzpv+LYps1sxVErSnqqSr8R52c9EEBnNxARsAbCgfYgXBtvosqs4VsDLXib6DcCqQbPyyUkbDfS4NQqu6fv2RIVCNUZTssYLleaITcgad70SBs41N2k8m34gebHWFLEGxasmCdqr51m81pir9XnXrAJGpUVCa4pS0jQUUBWNZ5JT0fjCsCZJYFLJxQ+N7pTlU+23SSddMuka8ZKPJTWBEpHBnqvGTeKkWibqq/r/dc79pNJUpMlTUBOCpqEgSvYFUBXScLiH82X83Kmb3ybhmmGPGj+vxotTNfz3hP25U8swgd9oaywe0GIZZqoX1ndSDpPFvbosHerGxjA5nZkPDk7oaA4EUI0bHZIwhE3/UIJqWI6jNXIsHelaXc9bij522G+pwGPD2ha6MyXa/GrUnwBOrMHs9XK5icBvJP6yMExE9X4LhKBF+WQtj8lNJjZkebF1YtJAraP+c8M+3Sk7yqZ86IxBMyhjpq9N+hFENYkM79NZjbNN2xhSaJaPtE8ou15rTwhmO0UKbgwLjS0VUmhScS/KB7L3jE3ct7YHfxQWpMdYXZ64C/9WiX7buP+n5O0Mtf9L5MEHH2ThwoVs2LCBSZP+uXX1m1nW/yW56667+OpXvxrlBqjVasyZM4ebbrppi8Dp/xf585//zOGHH84rr7wyYXfgn5X8cYaJSDYb700wWsZqDQ25XAURD30AtsWFv2lGobG14CsfHKW2qoTT40Tn17fXdamGqgb86IEejt91Pfc8MpW9ugxs4I9Dk8hL6PE075w0wPOb2mmRHi9Kc/+90iM8W2ilJgQLMlsegzE2dkuP4PsWni8ZcpPsstMm7l8+lUwIy9mue5gX+9uZ3pRnqJAi7ZjFQ8kzhnRHtowQUK3ZPBI08Yn3DyAsiar5BjYACMdC13xU0UfEJEHR5+Inp2DRSDjzX+8fxh+uYrXEEHEbXfGQHdkJnqclP0/R65tEP3P9Gg/H48x0dWQE9VJFa0Eq5jH7kBrYEpFOoHNliJn+F+k4OldGewHCklx1VwcDMuCM/zDB2rrYuK62fBitQMbgN4/1csj2BnO/fPkkCsLG1poX4hafefcmrvvzZD7YvpnRETOGj6ksi546h8qpJxCMuciEhUhYqLzpP5EwfeOP+MiE4EePTiWrjPG0KITlCFuiih4yZSPScRP8mHC4/eYmZmqzuFrmJPn0Luv5yyNT8IVgn1l9rH2llXd8wRgvatMQKmd2SURMhtAoiczGuOfXBtq214xNLFszmd0nDdC+p4X2QlN7HOQDpZGtKW65OcsHZm/guRVdTGktMOUQZ4LO4geokotI2Ii4Q/nZAqtfNHiMuB1Q8w2CfPuDcqhiYOAWrsKqwz6UxupM8+BNadrtGralmHVQ2bQfQClUyTVzRQrUaPhbeAxgtafRSlNbkSc+K0Xt5TKxGQkDexkHXdHVAKvTnIvSPP/LGB1tBhbi+5LH8u10Bx45YbHLpEHcms260Sa80MRrs1yqgcUOOw0gbENvK2Pm//hcs/iqPJsnMTtBMFTD6ogjhDBOg/GQM8dCVbwIZqPdAGFLRJjYS9X8CXUWKZtgpIbV5CCckAmp4mF1ZqKxuPFXzWzv1tgszcJqdUzQGRhay2N2WD+xvuHQyYSBbTmTkuhAmWeWryDhINOhsT9sdoxEKoYqVBHpOLIpjRoy1r8quWjXFGh1psE3utT3JyIv9urhFjoTFTZW08xqzqE1jBaTWEKTTTYgWL0HBaiKh/YNVEZVA9yhMMagx8JqTVB+rkTfyy301cwCev9DByODVkiBdpWBD7kGAiWyCe69Ocs+2/eZ+vqC9A4xRDLWgImValG/bvijpC+fRQEL9tsc1UUrHUEn7Ukpnrs1QWdbCa3MTligJG5gkQyfl0UvxvSeUZxEwOpX2pn/WUn62z/nrZbcsa+92/2PSvPS10YR/G+Vtz33/8OlVquxfv16zjjjDI444oh/yhh/M8v6vyiHHHIIq1atYuPGjfT29rJ27Vq++c1vvimGPcDvfvc7TjvttDfVsAeIf/U0cxBLovtfxmnpjo5FWyPgV+cHuPzabwEwKdnKqV/8Hs7wBkRzV8QsoQbXGmaUWBKdG+Te+3/D4oVzWfNEkYMmme3xB8YqZLFplQ6VksPjCYtDVYWDp5qXVtPuKb73mxqdOHz4EIvv3VZjEjE+fDBccKeBBXUSQ5Ta+NB/jPHD27O4Cc0ebZKXYoJ9QoOiZVuP/iGbbRM+sZJi6rZj3Pf8VBZ0mIDa9YNNTO8eI5HyeOcoxL9xTljvAUga75SIp9Fj/YZpIpFG5zZzxXu+AUDGMUbDN079KTHX1EvEEujCcIMtJJR7fnYuB9rdPEuRmV6SlaLKtjoWeSyftZLENHx4l0FiJ38HndsM0kJkO8wxGEsmnoZyDlLN/PctpxC3Ypxz3H83xig3gHYrJFruQzRlEc3NPP30y3xsfxPXsmmF4cJWwFOiTOygPXjsrys5ehfN0L2mLu2+onLqCSS/+yOCdcuRLd2Ipg6CDSZ4TzZ1IZJZgjVPIVp7OHv+UfRmOyl4ZU485+aoH4L+lxGZNijl0MpD2HGevPUaZoY20F8Z4/Pv24lnnhphOxf8miRQkuU/NJ7M+X/6OrhVtA7MuNRKUdbK5397CwAH7+SwdqPgwDke8VMviNhytFboEcPOJNt70b7LX355CR/fpxN3haS5q4Lz2TD3h+caFhGlUGueRXT1IjJtyNt+Sveo6ftVm9rIWh6BFiTPuRBdzoHlQLWE9k2DZEs3qjDE6M9vpBwk2W3SAPGvn4WIhcblSB8ilgQ7htr4Is6U7RCxJGporSmrPoarl2PvUkS+6zCccA6qJ/6E3O3AsG+TqPwAIpGN9EL/8jLa5pp6aFfzzNMttFYEGa1onuFSG/Z5pdgeZW7tdSUVS/LOb3zKsO8AwokbFqSwPU1HdyHsONqrIFLNBL+5DlpbEGGwv9znwxPmi4gl0aP9kG427Qz1ETtm6jzah2yfivZc0Aphm/uqwhAi1WLGIPB58rYlNFsxVLgQucvfxBQ7S6eIkzpgDnKfA8z8dCuIdMgcUy0gQr3UI30QS0Dgm7kbijNlOzMGdhxdzaM3rQYhcXZaaE6IJVF1nVWB0SUp6Yn9d7RAWHs1tHeV6FuXIldMEGjBSpk0PPulcJyBGTPjxD50tNETOwb5YRJ1PWnvBSeGvOFy/JU+RSmpSEHim99B11crAG7F6OPkbUz/WDaP3LaE9x5k2NUoV7CP+bJ5PoTjIDsbO8Tdw2fzh4fbEMB+53yrwSRVZ80BiKcp/WIJ286qoqqw+eksQmiSjkfVN8+wuxMOpx82CTUwytjLDnLPBjnGWypve+7/KXnbuP8fLjfddBPHHXcc8+fPf0NZYf9VZf1flS9/+cvR8bbbbvsP0Wm+npx//vlvWlnjJXoBWjYks+ZvKSGVRReGjPEDYNs0xQwufaRWQJdG0flhdOBFRpewHPTQRnQsAVrRaiXQhSJZBdUx41FqxSGOJK4NHtVGsN5L0xPun6tClSwZqmh0oUozaaooVKFGE8arWEPTGvioXIW4biGtBSIhSSvoF8ZTumOYLEdampqysBJmG9qyTV0VgsCTxFK+wRGXcqjiCLKlG50Lea4LQ8jWHtTQOqgVEdkOsrEkEkHBMx5oXSubF6wTR+d9ZPtUgnXLESEDCokUrVaSViXotOIkhU8KCwtNNuy3PsdmjVRYLTZq4wvIKdujRzaa4+5Z0TjpDSux5u6NGl5PV7yFUlAzRi+ghzaYxZhbgWIZ7ZmX+SRtozaYBU1ct5P0NTUpyNo2enSUFBb4OsLUy3yKYMwlWLcca9qOqL5VqLF+rGkG7qb6X0YNrcWaMZ9gw/P0ZNpZVxigJ90WLfKiazevQQ2vD/UnTpe2yCbMfZpUDD2Sw0EgMVCvbKJGX8XomC4MmQWNUujAN+0KfHSlQFuIDVFjLgkN7pAmVRkXGB6eZ8anhM4N0IaDKhSxSFPJObS4ZvyEsNCBh4inwa2aRVythP9yP82zTB9uHnBoESbBD04c2T7V1C3bHi16SKTRq59iqqrxnJMg0eyhC0PosE9Epg3V/xLCiSPCuaWlhUi1oDa+2Kh7IoUe3AyVAjpvFopim3mNcS7nzKJveH1jwQeocshQk5G0aAsHj4QIcEcF1YJhAXLq8cbC9DnD/YgZc9H9a6F7Onpkc2OB5LnoRMiU5lYQU3qgczIiVafJDedLcxcqN4DWysyd/DCqYPRNtnSjBteipYVs7UG71YYxGt5HNHeZhZhWiFQLnThklKIc9lurnaRTxEki0aM5o2OBjy7l0OXxY+6hhxVy2o7mnpvXGHravOF9V+tXIHvnooY3GMM+lmjoFqDXLTfX9r8MpRykzALCmtxBsNoEscZEhlS3j14nsKRCakFBmuR1k0JSDY2AVBLtVqBcgHjCGPnx+u5mDcpjBAM5HDuB8gykRof6bTpOmvEOfIQdB7eC9ms0aYkeC/W6VDXOBLdqFoeBD0KaeQPYkw1MzdEYfQ0XK7paihZfanAdSelTG5Z4VRklQzNxFmEODi3ReZPHwhcCRhuxXW+pqNc/5W15bXnbuP8fLosWLdpqVtd/d1lvy/8cER2ht0dK9Fg/osvwGOuxTYj2Xgg9Tro4wlitiNaalnga0dINQpqXvW8MNp0bgJYORCKNLuUYUzVEKklRVkh2mJff2GafLDY1YSMtTSlQtOGiQ4NNpmOUMOeIdJwiAVksZDpGIaTAy2JTkBYyG6cqQAnDpFIT0KYaDDMW4LuSpOUTVA2uto7ntYWOAt0sqRDNnQhpoUtjiGZDKyikha4UEOlW8wKtFCh5VQKlSDlmESFSzaYfQo5/7VaRbVMaPPfAaFBhs9PEsHap6ARlfGrCxg7Rr46GnkCiXWU8zeUxREs3ItUSGamiyeDZ1fB6ZOd0xrwiBa9ivHoAndIYYZk2SCURTRlENsuIGEa0GgMwAIqWoS4sESBaWqhhjAE/7BdfCGTCMoZZ3ypkzxx0fsgYPYDsnoUa6SNYvxyrd0cKXpkpmQ42FocaOtUyGTW0ATlpBlqZxZ+Ip8kLhRfeJy9cRFszHiOklMJJBBSHYjTJEP7TNsUYJCoIjZeQxzuRpt+qwyeSVAU4LcZ4JghzAgQ+or77Eo7PoHaRLRkkGicRIJJmoUi1hKgbR+kmU1cnid3TyujzxjBsDQKsmEIFFgQ+Kj9k6lQrQWgoUS0h2nvoF3HafY1btJGtPZGXVJdyyG5DQawH1yLapiAsG5UbQE42cVbaq6A3vYJIZxDZdsSkGWZRsOoxZDgvhTCGn2ibYvomFJkKFzxVxagwGH2tBbF2jVY+ariRYdhgyiViyixj7E2eCb6L6J5hDFKAbKvZuSqOIJonoZ/7GxTG0GFQveydG9aljAx373Q5h2hqN/0JZi61TAYpzUK5Pi+kRITzQ9dK0TkA/biURTzC1I8EFdLCoUPEEC0mF4dIhJ77FkMcoAtDiNYp5jg3gGzvRQU+1EpmZxHAiaGLo8j2qahqCT26GdJNkaFL2xT0SB+ye5bx/gsJ2Q6CTUPIqR0AVLQxhC1MoicFJLTJhFyoL+bBcNNnO9CWY/RDyGh3RmQ7IPCwJrdR89wojkEksxOMeyzHLK6ENL9pRV4oRLpBk6w91+y8WHb0vKk/D4LBEp5oMbEIY5vBq4XPp0qjzcksFWVjxUM4pTaLlvEZj4tCITIpdLFs4ks6/zGa6Lfl3yNvZxL+XyZr1qxBCBElqfq/JgsXLoyoLv+nyFFHHTUhsdXuu+/Orbfe+q+rgF+LDHiqpXHHZeMtVcZ7iu8ihcCSkpSdMC+LSsG8kCwbLBvt1Yynqe5d09okvsHgZLVvslXqkC9ba4hrQdrxDItEIEDWMykKkIYnOk6I6Q3/xREmsE+a4LoA0K7CF+AIhSMMnaRigo09QZQGITXKN+nW654v3Ko5jv6umO+0QlfzqDBXgi0tbGlFBqUOfPMCdyuNZF71D2BrEfF/m79NIGFNCOIaMgqCojKQg8BHl0YhkQ6NWg9dGoFUM7hVVG4ATwdknWT0u4inTZ1LOYM5D+/toRHJRJTwxxNhinttomADNEioujZVN8T3JyxEUwfar6HzQ43j+t+ZVvBc1Fg/RbeKLSxaExnjSdYK2dxpzi3ljD5Ik6Coiqbq29GWf33rvRj2UaAFjlQ4Upm2VEvGg+lW0NWCORaSmBbEtIgw9sIWDeM/8A28QVrmE/ggLSwhIAjwEFiOjvotksA3u1S+MYKIx/CqFl7VIoHCDSxTrzpkI/DMrlXYZq0VhEGmltYEnkT7jZwdulYycwbQ1cYxtVLUt0Coa9rco1Iw9xsbNufXrw+9+EirATx/lci6qr2GB1SiTT0gWkBSLaHr7VIq6jtUgB4eRY8Mm7qMDRt9l1Z4TXjsudEuXtSWwDMLX9+dsPiK+iXaQTHPDKs+t8dJxK5fXxB4lSiBF0o1DNtkFjzXLEjC+aBLI+jSiIHs+DWzG+LEzHWlfGP+ZFrRbgVdHDVQGq3Mb0pDpQaVGgIzrgoIlMRXkrg2nnsL8wFMQrSa0V1dyaMrBQOZyw2YMQ11xpIKJcIA18BHj/sQeKYtXiXSI4kA2wo/Zk5FD7hwjtXnvfY1tg4Dy71aQ78hTKgWwqPQWAkiAx8MC5EQ2jBNAdgWuuoR1xr8xti9laJDetU34/N/Ud427v8F8mqDs26A1z+xWIzZs2dz7rnn/tuysj355JMceeSRTJ48mXg8zvTp0/nABz7AHXfc8S+p04wZM7j00kvf8vv8/02eeeYZfvvb3/KlL30p+u6MM87gG9/4RkSpujV5tQ69+jNz5sw3XIf6S0ePGbyszg2gRzea49IIOj+Azg+AkKSdBFknaWA51QK6OGrgIkMbDCwknkSPbDJeMd+nOYTlZBTU8ha1vEUbDmksYqFaSWC9l8ZyDCOGgeXYESwni005hOVkscPfFK1BgMpVcDQ0a4FIWSQ1bBYxNotYxOVs2YpqMBGWY9kKhUAFEmkrtBbocg490odo7jTH0d9dxigoDCGausg4CbKxJCWvSsmrGqhB3ry01fB6RLYdPdLX+JRzNFtJmrWgQ8RJiIBEmN4noxQZpShKeNlR2C02atNK46VXAapvJSLbYbx9gO57yXh5fZfOWDNSWNGLWm180SwMpIRyBT06hi7k6dI2qm8Y1TeMBbQGmozSZISNzuWi5FSZlEsm5Rqvbt4j2PA81rQd0eWcOZ46D2vqPHSlYOBC03dCl3NMTrexvjhI3HKiRV6w/jmsyXPMuUPr0WNGxzq0RSbukom7ZEUMnS9ghTrgu5Js3GXMjzHmx9DFEXStaAx7r2IMFLeCHu2nVQlalUDlG7AcXSsb48ytmAVWtWQMT7eCHttkYDmlKhaaasFuGDgh3r6O0yaeRvs1/NWbaZ7h0jzDpd9ysITGUyaeRLb1IFu7DcY5NDDreO8eXWPQlsQzPro8hsoNoHIDBkoz1m92xNLN6NKowYCn26L5o0f7IZ5CVyrGMCyOGr2btaMxlN2qwdtnO9Bjm9AjGyNDX5U1qqyRCUmzljhoEiLAyxlYjo3ZIXLGP85HBxCJNORHwDaebSpFqBSN7uYG0KUxdH4AMXUqYvosxMx5iJnzDGxotN/sclUKqJGN0dxRIxsbf4ftlK09BuqTH4BqCZUfQOUHjIc7P4Aa7QOvRkcIy3G0xtGaFitJu4iTQKJz+cio1+VCY45VCqaMvhcQHVPBd1GbVkWYfAC18UVTB+UZGFIi1TDylUJteN547ctj6OENEZxLTmpDjRZRo0XiQpHs8NEY49cSmryEsoSMDsjogKwOIGsWGVRLoS6WGw4Q5aGLIwQDOexwB0qAMeDruutWohgT4STBq6GLIxEsR48V0LkyIp4KF02hM8JyomeXPcnAgBwNsmMqoq0H0TEV2dyF6Jhq+smtkLZ8aqOSyqhjjHktIliO1sLcM1dCJByz6MqPvuF3yz8lYbD4m/L5Pyhvw3L+jfKHP/yBHXbYgVqtxgMPPMBnPvMZJk+eHPGw/6vk9ttv54gjjuDAAw/kpz/9KbNmzWJ4eJhnnnmG008/nX333ZeWlpb/p7I9z8NxnNc/8Z+Uf9V93mz5wQ9+wMc+9rEJSb4OPfRQPvvZz3LPPffw/ve/f6vX9fb2smnTpi2+f+yxxzjssMP4whe+8IbrIMIgLCEkaqw/+luP9Zut7rpnujRKvmZYPZriKWRTF0opA4eoexQLQ9DcgOXkgioiM5mCLJEIYTm5TT4BFq6QCAEVoekYD8vJJkIojo3IJiKIjswaiA5ABiuC5bgCqpiHeE1ASwjLEVJERmPCCvDLITWf24Dl1LefLakQ2fbo5Rht5QtpYDmpZnDiUMpR9KporUmEAYER/MOJGZiCWzVwgXF0qmNBhWGniRHtUg1hOZ6wI+iBo6G7Dstpm2JgOc2TEMmmyHgzBr+KAhPrsJx68K/snG68v5lWA8vJpBHpDMNiCNkecmMDxZBJpqh9RFOTyTirGrAcJUz8gmzqQvW/bAye/BBq82pzn0kzUSN9qE0rkVO2p+CV6U610F8ea+hUSzdqeAOyc5qpkzawnIJQuL7xb+aki2hpwmOEmDZQmbLr0GQZfZMt3Q3Pt2VH3nJiSTbXYTnt42A5qWbze7ibouvjkm4BaY2D5RgIUL3fqJVM+VpByuw+1GE5+eUmsVBr4CNCq1j7Lro0FsFyhB2y4VRLiNZu+kWctkDjVSUyhK5BiJWvQ96G1xvIjmWjc4PInhCW41YMVjyTQWTaEJ3TENkO1CtPRPNSWrbRyZbJxqsvQ474CbAcRU0IlLaItYNWHv54WE59nKbMgloVMWm6gTJ1TjOeZTCBsfE0FEcQLZPR7t+glEeHnls5bQeow9ay7Q1IW3gMhPXsNvOiOBoF6AvLRtThStVSBK8B2BTCcmqhno4FFbLCARFDtDabeqbbIFFpzNPiSARb0/khY8j6NXQYJwNEixfZ2oMq5YwHP5kx8xoQrSEsp2umWWQBZDtQg6PIbrNIKOuA2pjJYW3oRSGpwdJQDGE5GsDzEE3tRq/C8iNYTrrNeO0ntVLzGjs7Ipk1C0yIYDw6noh+E2QNLCeTis7RvmsClu04Ogzir8dEBMOViIZV5QbNokFItF9rwHLiaUqBgeUI2YDljJe8UIhsCp0vGnrd9reJNv4nyNue+7dYFi1axP3338+SJUsir2pd2tvb6e7uZvr06XzqU59i77335oknnoh+V0pxzjnnMHXqVOLxOPPnz48ST9Xl0UcfZZdddiGRSLBgwQKefPLJ6DetNbNnz94i8VWdqvHll1+mVCpx3HHHceihh/Lb3/6Wgw8+mFmzZrHHHnvwmc98hqeffprm5uY3VBaAEIIf/ehHfPjDHyadTnPuuecCcMUVVzBr1ixisRjbbbfd6wbs5nI5jj/+eLq6umhqauI973kPTz/9dPT7WWedxfz587nmmmvYZpttiMfjW91h+N3vfkdzczPXXXfda95r4cKFfOlLX+Kkk06itbWVSZMmcdVVV1EqlTj22GPJZrPMmjWLu+++O7omCAKOO+44Zs6cSTKZZLvttmPJkiXR79VqlR122IHjjz8++m716tU0Nzfz4x//GDDj+4tf/GILbn/LsjjkkEO46aabXrPOlmXR3d094SOE4MQTT+TjH/84X/3qV/9O775KSjnDaFIrofND6OKI8Xjmh4wXq2q89JQLxG2HmGXT7KSNh6h+jme8q7o42tj+rZaxhPGKCkBVzQfqqdIbsJyYFRB4gsAT4AdYCDLI6DiNBF8hMQ+tNJZ5cSkdeSJ1VWFpSImAlAhecztWyMZOdh2WAyE0wa2Y9pTMJ/q72vjNkRa2ZZGwHBKWY64LISjarZrdDr8WeZG1WyEmLOJhgJpJLCOwdQhNwhj3SQ1BOdxmL+dMwGR4bP7eYIJ2S2PGuEbTFm8yxlg9eLQ4gh7aAEFgPJJRpiAbHJuaEBF0wBZiwha761m4nhXxZItk1nieR/pMsGh5LPpbtvUYb+lIHzXfI27FaEtkzHeVAsI2nnc10mc8i54J/PXR+CGcwRFmfB2gKgQ6TCYVhB/jgRwz+lgpoHObzbFfi2A547Oh6krBeO8rBQM3qZlPfVwdIdCVGh4CO66iftN+zehurQTlopkLXgUsi8CTBJ7xggdKYokQyhJ6WbVfi/pFu2Z3wRUCR9epCUOdcKtmbEojpk65QdO+WtkE1oZl4FaMZ7RWMzpYNOczuKlRX7dqAjTdiqlHHVrja/NRRr+sMC+A+c4sdKUeB9cBExAfQlW0WzHzORxD3Ir5P4QHqb5+9OZNMNQPQ/3mvPr8qBTMGJdz0bH5e8z0p+82zvNr4bXViW3xalAtGQgexmC2NNhCIhE4CHTNRdfL1aqxUxP44NcQTizacav3vxpajxpaHy7cx1DDG8zcKIzBSD+6WgqDTBMGQpMLM/164e6PH6ALZXShTAyF8k1f1nyLmm+bOmqiuawAnS+aXZfSSDjuucYOaXkshJsZw97WYUBtqLe6WkLXQkhkudiA97gVA6EbD8sJddHsbIWe/3BHSrvm2WiBGcvAixbaUb/5NVwkdgbsZEg0oAXjX6UWmD4o1oxeV4pbfa6+6aLexM//QXnbc/8Wy5IlS1i5ciU77rgj55xzDgClUmmL8x577DGeeOIJjjnmmAnXXnzxxVx55ZXssssuXHPNNXzoQx/iueeeY86cOZRKJT7wgQ/wnve8hxtuuIHVq1dPYGsRQvDpT3+apUuXTjD2rrnmGvbdd19mzZrFr3/9a4aHh/na1772mm2oL0her6y6fOtb3+K73/0ul1xyCZZl8etf/5ovf/nLXHrppRx44IHceeedHHvssUydOpX9999/i/tprTn00ENpa2vjrrvuorm5mSuvvJIDDjiAlStX0tZmvCgvvfQSP//5z/nVr3611WyyN998M8cffzzXX389H/7wh1+zfQA//elP+drXvsajjz7KLbfcwoknnshtt93G4YcfzmmnncYll1zCUUcdxbp160ilUiilmDp1Kj//+c/p6Ohg2bJlHH/88UyePJkjjjiCRCLBjTfeyDvf+U4OOeQQPvjBD3LUUUex//7789nPfhYwkJyxsTEWLFiwRX322GMPvve97/3dOo8Xz/P46Ec/Snd3N1dfffUbvg5C+kow+PVEGj24ziS0qdPKuXWL3KYj3oxGM+YWjXdrpN+8iOoeqEQKBjai4wZ33yGT6LECrYFNedh4rjpxcBAklTE64gjWB0mmJc12b5Cr0UoLNTQqV6OFZlw0Qa5GGyHPPYqmQBDkajhAIvT6pzX0hWw5czHPdTumqAQ2VsIk5JJW/SUGnmuRSHvmhZYfQCuFaJsS0ShqrRDtvejNq1H5IWTLZFrjWQSCMde85Ax0aQjhxNFeDdk5HbV+RaODEynarCSdStBtJWiSHilMRtdECL1a59gMSYXdZqPWPYfomW1gGiObTZAjmP7etBq500L05tVMjrdRUyEWH9DDmwwMwq0aRg3XB62ZrCyC9YbSMa67SAWKspQ04aBHRkhhoZWOMnlaY2n8EZ9gzVOGEWf9cvTgWuT0nUy/bVqJ3/8S9rz98J//C1PSHawvDtKTbo/w1sHaZ7CmzkMNrDYQLaXAidGlLJpCPvC2IIkeHsXBQqKpFB1a0xVWlYznUYVjENGQ1g3NapmOcLyD0RopDe6wIBX2Q/0aHbKkEE+j80O0E0MXxrBwqOadqN+wY6bcZBZKode6MIq/dpCW7Ux7Ng46NGkPS2iDH2/rAaWQlo3/4kOAoZLUm9cyQ1V51kmQavcjIxMMK4zqfxktJcRTUftEugW97gVzklbgOOhCweyCDfWh3CpMnRWxoKCUKWtovfFip7JmoRxOQZkStGpJnICECKgOSir5MBFavXvqlerfANO3haGNMKkXRvqhErJAlfLGkyyN111O6oCuHhN0DBHLlmjpNnCj+lwZ29RgwmntQQ2sRggL0TltwlyJGLbaeswzSClEupnJOmTLCT377VaSLhEzbDkj+UgHdDkHYyFzSxgoilLI3nnogdXowY2Irt4G89XqpwxbzuBa2LQWHMcsbsOdsWDjC4bhadMqs0BNZlFuBWt6N/5LZqziIkt6qg/rwJYKS2hyFsRfzZYDZjGTHzZ9mB8xz0aAcg5VqxD054g7aXDNgkuXxybGK/i1BlFBcQR8l+bxbDll1+z8lAsIpQxtbOBF7ED2lAyONkaeaOsx58hwQRDuJqj+l0iF0C23bEU7mXLcCrBJS9TIGMRsA8sZnJhB/a2S/6tY+TdL3jbu32Jpbm4mFouRSqXo7jZbj2vWrAFg7733RkqJ67p4nsfxxx/P0UcfHV170UUX8fWvf52Pf/zjAFxwwQXcd999XHrppfzwhz/kxhtvJAgCrrnmGlKpFDvssAMbNmzgxBNPjMo49thjOfPMM3n00UfZY4898DyPG264gQsvvBCAlStXArDddttF1/ztb3+bYHTXs9i+Xll1+eQnPzkhu+0nP/lJFi1axOc//3kATj75ZB5++GEuuuiirRr39913H88++ywDAwPE4/GoL2677TZ++ctfRt5w13W5/vrr6ezs3KKMyy+/nNNOO43bb799q/d4tey8885RdthTTz2V888/n46OjsgQP/PMM7niiit45pln2HPPPXEch7PPPju6fubMmSxbtoyf//znHHHEEQDMnz+fc889l89+9rN84hOf4OWXX+a2226LrlmzZg2WZdHV1chwWpcpU6awbt06lFJvKFvuF7/4RV566SUee+wxEonEa55Xq9Wo1WoTv+yYTjwWpoQf2oCcsp1hBBnZaGgYvQYTzmB1DCEErbGswWzGE4bRpU7TNzYAbZ1mu7tSZFhVEU3tjFpVMpMN3GJ4xKMFh1rYrqLQTMIlcMMslc1xCnWGnOY4eQKasLCa4+TGseWMWua7ioAgfCnVBEzSja1uWzfYcpQbBhHWaRQRWJbx3EuhDQRJShOM194blaHLY+blKA0bSM4tobRqwHKyHQYXa9nGyKqVEF3TJnTxUFCmz84wqGuUVIwqigAbFS6ck3W2nKoy15ZziPYeY8jUAw5bu9GWjep/CTl5WwbdPNWgZoJswXjLKwXDVtKUQbS3IlIphmTBJNXCGHXDtjHxSviItjaq5AEIvHAHA5MUSLT2GKx9746osX7U5pAtZ8r26JE+/Of/gj1vP/LehUzNdNBXGo6gSLK9FzXWb5h16pCXWJKcfJByzSzyRiwX0T2FKkNkVUAi7bF+NEOnCPnA63h2rUzfplrQOoBKgT7rMaMrnUnKAmLt2sAv6gZMPbC4Pj6xJJt1DdmeRQJ2PIj6Dd9tBN42tYaLiRT2tHZGf28M6k4/wIkFFL2YMVyHNhgGGLeCSIfluBXEpOn0icdp9TW1vEV2UiP2RRdHzNzSysCdps4N50w/Yvo8c1KlgN74MqK11cButEIkmlAvPILY6d2NsqoFZEdvZAzWxwxAVTXDIqCKBA3xdgW4qLEGLEcJgUIgttnBwDSmb29YVKbOQYcGs2idZKAkJQNTC555HGENRAsgsWDHqM4iZMHRpZFoHkVtbu9tMHF1To/mStSWWmkCP/t64TJXxiJIyXBQIWHZdNXZciwbsq0mCLY1hPPkhyPIjy4MGfiTCGkfW0MYScj8IzunGyadwT6zUAmpRGVHr4G8TZ1r8P8YaJi7/jasaaaMsq5R6bdwxrHlxMM4hpwcZ05JYcYvnjaQmVijzSLVgtAKe2ob1XrSNeosOuFOmpBmhyeZMbofcu/nhEKkko37+K6B2DixBgywySReCzaXKMsWs6swtMGwVkGDACGsS1Vb2ElNPdeyFAZyVJecUMjmNCpXMknQuhq5T96W///K28b9v1FuueUW5s6di+d5PPvssyxevJjW1lbOP/988vk8fX19WyRA2meffSJ4yooVK9h5551JpVLR73vttdeE8ydPnsyhhx7KNddcwx577MGdd95JtVrlYx/72GvWa6eddorYdubMmYMfbt2/0bJe7YlesWLFBHhKvR3jYSzj5fHHH6dYLNLe3j7h+0qlEsF/AKZPn75Vw/5Xv/oVmzdv5oEHHmCPPfaIvv/rX/86AcN+5ZVX8qlPfSpqc10sy6K9vZ13vOMd0Xf1hF4DAwPRdz/60Y+4+uqrWbt2LZVKBdd1mT9//oS6fOUrX+H222/nsssu4+6776ajo2NCe+Lx+ASoVl2SySRKKWq1GoODg8ybNy/67bTTTuO0006bUI9rr72W++67j6lTp25R1nj57ne/O2FRApBNdNKU7CJQivZ4E2Oeobtsjzcx5haj+mXsJOv+ugStA/TgOrbZ+4u0xrLkvRJ2+GJrto0uVpVH1k5y//l7c/wZL3LZnqP8+gFjMC/5nEYXyhQeGuPFVR185X39vHBvM39dbV4az/ZpLlqkUQNjnH9nKxcdrVADo1x8dzv/HYajqIFR8o9XueCubr6650ZEQnL1fVP49Ds3sPZR41lc+ngv/7ndeh5d0cPUWJm7XujlgCmbeHad0ZneVIkXBtvwhaANl2kLPo0b+GRjSWphnIGnAjJOAiEEtcCjyUmz5i+XGGMlxJhP2eVobGmARr4OSFqxCf2r0Kz64Udxf/8gzjtmsu5HG7nok80M/HowouLcZ5KH9uGGZb1854DTaIll0GhybomWWCYqq6Y8klaMsl9lxb3fhkqBbff/enSftlgWC8mCRA9jej0V7XPzf1j81y1mkXzu9htQnkQ6io8eOJ2Pn/0CPzu+hct+3MNCz8RTzO8e5EePTuXs+UfRk2mn4JUpulUmh8GJBa9MzfeYku4g713ImlV3EKx4ELKtdO/8n1Fd2hNNlLwKCTuGLWx87bP8qOm88AujKzd8bRrHfXctP1pYIP88PL5+EtNjpch7uM3eX8SWFhKBq3ziVgyBQArB4x8ydbn4ji6+/M4NXPdIL2fPPwoZ6qolpIEsAUO1HLaweOnru3PalTW+0DbGn9f3cFrYb1HmVWCb1CQGvQJlv8rB2W05qGZo/3ZqGyZfSJCNuUze9Rhilo3WGseySVlmMT3qFsg6Kf4yqxWtBH9ZO5mT9zgeXxujqclJ4ykPhaY73sqm6gi+CmiNZwlCxpuYtJkcayEpHB7N3UZHopmiX2FeagrPFE3iLl8FpOw47jjK1zuzs7nmb2buxzWc/uERNv3RBIrf9FQvrQF8dOf1yHDdX1jr4CQC9j7iyuje9f8zYXtGvCKBVkghcJXHwdntGNWbqYbt+Vvulmh+1AIPN/Bpiqeo+i5uaKRmY0kUOpo7Obc4Ya4AZOwElcBFhyxUL3/pHYz8rh/LMfU57MsL0evWogZG+eKPPf72/R9RCVwsIakpN+w3h4JXpuK7tMUzeDpAYpwQdaadvvJw1Ndx6TAl3oqvA5bnLweg6ntMSrVS9s1OpSMtAq34RPNOeJj7fC5T5C9rJ7Nb2zDFYhxLaj663XqUD5XRcLEvNadc2cbt3/scCSuO0gFpO2kgisCYV8RXAUc2v4P/tFzeOakfJ6GYumtj1x7AFhYz0pPor45E/fPSsXP48nVmLidI8MurF0d6lXVSDNfy0fP6K5n5HL3zerQP0/c7KQRCghwHD/YCnwenTOem53tJaFjgmIVbvhInFTPPwK+/t8DXb2yhhRY+3TnEwSfezV8/9A/APv9f5f8onObNkreN+3+j9Pb2Mnu24T2eO3cur7zyCmeccQZnnXVWdM6rDb/6A7B+/EbkM5/5DEcddRSXXHIJS5cu5cgjj4wWBHPmmECuF198kT333BOAeDwe1esfKasu6XR6i+v+XjteLUopJk+ezJ///Octfhsf2Lu1+4DxmD/xxBMsXbqU3XffPbrPggULJlCEjs/A++pgXCHEhO/qZdQZbH7+85/zX//1X1x88cXstddeZLNZLrzwQh555JEJ5QwMDPDiiy9iWRarVq3ife97X/RbR0cH5XIZ13WJxSYahCMjI6RSKZLJJD09PRPqXYclATzwwAMsXryYyy+/nL333nur/TFeTj31VE4++eQJ3+095yCkkARa4Sqf9lgTGo2nApqcNE4YKObpIMKjiuZOsk6KVjtNTNrRi8tXAe1OhlpoeOiRETLCxs8rmoMQDjOUR9c8/FqIYfY1XZ0FVg0aPcpogc7nIWaT0RKVL0DMJoVAjxkvs4jZVAuO+d1VUFUEwngtW9uNkRobbAJtPJS2pShrcJIBblhXxwkw5JoCS2hSdpyMkyLnFqNkXZaQjNYKtMazJK04Obdk4By+H3nI4pZDk5PG1wG2sBip5elJNhamVeWhhwbxBzyszcO4roXOlwg8iRfuVjSlfOwpGQorYUqynU3VEdrjTUxNdTBQGwOgxcnQ6WR5NreW7lQbetMrkEgRDxcT7U6WMb9ExkqQxcIWcXJI/I1j9Grjua8VbJQvseMBeqxAi4yjSxVsnaQQGH2fpCGroDfbybrCAFMyHbTGsqwvGo9ud6qF9ngT64uDTM10EKx4EGvuPgQhPAWgJ9XOxtIQHclm2hyzOAm0wt9YoBKYxZUeHaNFxNCuQmtJTCvKrkN3hzEwmsJkVlIIbOUTlw6WkMSlg9tnjK1WLQiKmtYAUk4j7kYIES2yklaMrJNCbR6hmSZUIMkoFfWbr3yEtKj4NWLCjhYS03SMtY4Zn30nVRnNpbAtH18FlL0aQgiUVsxuNvV0A5+OdBMjm9P0bJcnv0mQdRrPxpJfoSveQoDC1T5NThqNpha49CSMvig0vg7IyCQJO0abncESkj4vF9U3bVvkvRLt8SYEwkCzNGTC10FVmmBKFSSp1mzaA01zEKAaG1qI0DM7yc7yUnWAqfE2NtRG6I61YIfzoz2WDcvWBFaMIVVlKChTUmZnJWXHkcKK5ktTzMyVrJOM5s9orUBnooWMrRmtFaK5UlMedvhcybnFCOpWDWr4G0ZwKzaODp8hA5tRm4fRxRrttOIqH0tIMnaCJpKRbtnCoj0uWF8cZFKqlXYny6Cbpzkcg95UJxsqQ3TEm+mONeMq3+hWGPzbm2lhXXGAnnQ7KStOJXCJSZscPlN0qCuBZMgKY0OUSfpkZUBUoVYNveFCU9BGhzJ2woynlaAWes5j0iFjJ+nSNhXPMcw0yizsxr8THWEWtp4OiFsOMemgRstkMX2bQOKrgEQYqBsT5v4Z2/TJgFSgQPswVi1Fi9i47eCH+RG6ks1UKjFaA0hoPSEKsx5Yq4oeWSwCTELAFmvczsFbKG/Dcv45eTug9l8gsViMIAhe9zzLsvB9H9d1aWpqoqenhwceeGDCOcuWLWPuXLOdO2/ePJ5++mkqIUYS4OGHH96i3EMOOYR0Os0VV1zB3XffPQEyc/DBB9PW1sYFF1zwhtry98p6LZk7d+7fbcerZdddd6W/vx/btpk9e/aEz3jP92vJrFmzuO+++7j99tsnUEwmk8kJZY1nqPlH5a9//St77703n//859lll12YPXv2hF2Funz6059mxx135LrrruNrX/sazz//fPRb3cs//ru6LF++nF133RVgi36oG/fr16/nox/9KMcffzyf+cxn3lC94/E4TU1NEz7ytYjg35a35W15W96Wt+XfIf/GgNrLL7+cmTNnkkgk2G233fjrX//6mufeeuutHHTQQXR2dtLU1MRee+3FPffcM+Gca6+9dquU1dVq9R+v3BuUtz33/wKZMWMGjzzyCGvWrCGTyUTe3+HhYfr7+/F9n2effZYlS5aw//7709RktpNPOeUUvvWtbzFr1izmz5/P0qVLeeqpp7jxxhsBg2X/5je/yXHHHcfpp5/OmjVrtmCzAbNoWLRoEaeeeiqzZ8+eAN3JZDJcffXVHHnkkRx66KEsXryYOXPmUCwWI2ae8cGqf6+s15JTTjmFI444gl133ZUDDjiAO+64g1tvvZU//OEPWz3/wAMPZK+99uKwww7jggsuYLvttqOvr4+77rqLww47bKsBqK+Wbbfdlvvuu4+FCxdi2/abzqE/e/ZsrrvuOu655x5mzpzJ9ddfz9/+9rcJ/PI//OEPeeihh3jmmWfo7e3l7rvv5lOf+hSPPPIIsViMzs5Odt11Vx544IEt4Dx//etfOfjgg1/z/tVqlcMPP5wpU6bwjW98g/7+LYOc6jEeryfDNeMNV1rTFs8y7Jq/W5wMo24h8so3OWmTtdKOo0f7KYQwjlrgRrCcrJ2kpFyqgUvCiiEyaWoMY2UEw3aIx27JoPIlnGSNqraQGYdSobFLUkUj0gl0rkxFaGQ6gSpUou8BVKFCPO1RLWhkTII0QWnChlIupLYDAlcQ14qqa5ME/JqMmExUIKLgt0ALyn4NhfHglzyzYFYYysta4OLVvWTJLEI66Go+bL/HqC5E295xy6EYVE2SKEwCHtHcjN3lINuaicU2I9IZYqkSXujtQ4K/sUhMtzDqlcg6KcbcInErRtIy7cl7JSSCSalW+ssjhmov20otMC7ZEYrEpE0xqOJivIdVAmSTQ0mYZ460NJYTIC2NSDiUdBVhJxCARd3rDYEw8JuedBsbi0O0JjJ0hRj1/vIYbYkMPel2g7PPthK8+BDWdntFnse8V6I1kWG4mjceydArK1MdjfukkozpIsKWVIoxPCFJOl5EyZn3QgpQIQiUoiJrocc2SWyqqcvgCoWVEuQlEZTKdKeIPKW1wEOICrKzlQIuKjCJw+r9VtfdmGVTVR4CgRfim7cJ4xDKow4asKQmZtmknQQajS2tCB6TsBwKfoXmbofqmEVGmTbUdxNSdpxhN49C0xVvYdDNodFknRT94e5MTNp0x5opa5+q77LZzVHyK2yT6magOhbpU9xyKPoVJI3EaOEmkGGZaU3gxAK0hpwyoyskyHCDUAgD6+7zcmTtJP1ujqQVY9DLkwxPyvsVPOWRshMUvDJz45NIyZhJBgZs9Iei+VH2qwRakXYS4TyqRm0u+RWzCxhLM1orRHOlDpept6Uu9tQ2nGeHsWNhwG1rKyJfRPujlDCwt7xXoqYscqGOZO0Uo24BW5pkakOVHJaQpO04hbBsX/lknRQjtTxJK0arlaKgapEXO++V6Eo2s6k0QleY5bXq1WhN2mwURlccJ6DVNYH4ShvWHFUF5UIq29gaiVckJa9CoAN8FRA4Ci+8T9mvErNsNgufpGN2XYTE7CRQjwcyNDd1qFQt8PBVgMzGJ9iqjrRRWkfniXF63a4kIoTityYyWFKitSYm7UhnPR0Qi/uG0GpcuePvIVMmz0gGs+M3FlT43yy33HILJ510Epdffjn77LMPV155Je9///t5/vnnmTZt2hbn/+Uvf+Gggw7ivPPOo6WlhaVLl/LBD36QRx55hF122SU6r6mpiRdffHHCtX8vPu6flbeN+3+BfPWrX+WYY45h3rx5VCoVVq82fNEHHnggYAzmyZMnc8ghh/Cd73wnum7x4sXk83m+8pWvMDAwwLx58/jNb34TQWkymQx33HEHJ5xwArvssgvz5s3jggsu4KMf/egWdTjuuOM477zztuppP/zww1m2bBkXXHABRx99NCMjIzQ3N7NgwYIomPaNlrU1Oeyww1iyZAkXXnghixcvZubMmSxdupSFCxdG5yilsO36tqbgrrvu4pvf/Caf/vSnGRwcpLu7m/32228ClOb1ZLvttuNPf/oTCxcuxLIsLr744jd87evJCSecwFNPPcWRRx6JEIJPfOITfP7zn4/oMl944QVOOeUUfvKTn9Dba7DmP/zhD9l5550544wzop2S448/nmuvvZYvfvGLUdkbN25k2bJl3HDDDa95/0ceeYTHH38cICr/1fJGYVuvPGQwp3Ued5PO3EFX8o2spxhquJ59/wswL+Q1j1+DHlxrAsHCl4uu5E1W0ngSXS3x4aN/yW1fmc4PLkmwaLv1AHz5uk7SpNnFa+adTSP89+862K/qccAcw0jx4flJvnx9ihRpvvOhHF++MUGaDOceOsKXrjdb0ilSvKea5SsfGeGHv52CBj5/QD9X/qmXHarmJfqp/TZw27KpLOzezKaBJj44fz33PN3L3t2GOWZtfwtzu4ax4wEjg2nWP/KziDOc8EWMtExgXnHEBBdqRfeuiyZsn29e+RtUcRThhJaT5aDzQ40Otmzee+C3OcCaxIo/jXFcNctF1wccUm3o8vpHJBUBJ+zbxxdPvcAE+bmVKBAViKg4RYvBgW+/1xeoBC5rH19q+r44grAcQ5l3z68QqVZEaytnnbmGMz5hXvi/vXYyNSlQwH0bKlx/zjxO+NYqvn9AP+vvNy+axzZ3seh9/Zx4zs0NztAwqDXSrUohCl6t4+yFEGxebTxWujRm9Ekp1PB6Exhqx/n2B5byEccYZJ+6tJ8bT+nlexfl2MGFd07tZ/OmJgbGzBi/8uiPG9mS7bg5Dnx0rcTFH/kFAF87eJAf3zOVRfPX87mrbotYWgi8RlBkey+6UuDEgy/lsk8JHrw6y97T+ll184/Dc8NMxFKiXnrMBLpaNt5PLqX0mGHUeWjFFKZYFfKVOJte+Z0JPrXsMIGZGWvZMZVg44v88f03MWxbHDC9j7U3LDXsOmDqFjKV6NxmRMvksIyKyUZc79vhPuhfj7X/d1AbX0C0TUH1rcSatiPjRfuu0VPL4cl3X8R/7rUh1Fk4764e9q0o4mg+tmA9lSGLW1f0Ug2Hc4pnsiM/fON+iJYuKBdMkGq11GC+SmURiawJEE81ox65G1o7IrYca/aCifMlzGRr6tBwCOlqybRTh4m+SrmoT8y5ssGuY9mctPB77F/rphbOsau/8Qi9VhOtIsXFX0gjD/iGKac4gkiGzD21kuG5l9I8s/yaydlhx6PMvyKRNWxgnmvYdKolkBJ7exPXpso5RMicpCuFSN/9n12B9szz7ZFrshw0bz2PPd/DJKeC1oJfLu81eSrC4Fgl4PtndXH5wV9DFYYQsaRhFqoHsYb5CbylS1j5M/hr32RcARuf+34jg6+00NUSat1yZO88RCwBSnHOey7lvEV1mtUKZ3/5FtTQWkQ8bRJudc+Ksg7XLv4OP7nH1G3dih8Zfaln3B73THlk7+9xyA7r8SuSNavNrnAm5lGoGqfC9+7Nct4ijS5V+OP13fz+J404trdSXiPx8lsu//3f/81xxx0X7YZfeuml3HPPPVxxxRV897vf3eL8VzsOzzvvPG6//XbuuOOOCca9EOINO9zeDHnbuP8XyLbbbstDDz004bs3YnhJKTnzzDM588wzX/OcPffccwIe+7XK3rRpE7ZtT2DjGS8LFizgF7/4xevW6fXKeq12nXjiiRNYfMZLEAQMDw9PUPxsNsv3v/99vv/972/1mrPOOmtCbEJdXo3Tnzt3Lps3b36Nlmz9GmgwGo2X8W2Lx+MsXbqUpUuXTjinPvm33357yuXyhN+ampqihV1djjnmGM477zweeuihaBfk0ksvZdGiRX83OPbd7373m5c5eNxTVOcGDOuELc3xONYYKoUoGKs93tRIaa6VoRMEw3Nff3FXy5FXUQF1MokAHf4zHkQLaInV8GuNNOoBmiQSQkM0FR7XvX0ppElyEzK/eGh0OSAAsiJcjPiG5znwpOHRr0JMa1QQ7iAIgz0OPGmyMfouwo4ZoyBjXnIiljQZMJUXvUAtKRGigafWtZJJmgTGeBjtb2S+BMM8pDUB4KFMIphQ6kmsMgpaNfgjAcSS6LFNIC2TiTS3uTFOsSR682rjLdeKlJ1osOnEkiYmwnMNz2fInuGiEfEGFWJZGu9ufWdBAviaSshiowFhS0QsQbBuOaJlMrK5k2D9c+Y+Ld0IO0aw9hnDioOmJ9VuvNSlMXNOusVc29yFEFZkvLloqr5RBOXUojrVNbAS2GSc0LgMPENvqBUi8I2RVqfarHdgmOhIxoThAq8bplo1FqXVEqigrnGmflJH/abdiqmjDqBWNWwrmTZEOkFx0Cx4WrRHECb40fkhY7RZjhn7UN9VbhCkNDSjgaJacCYwk+ixfmN4Ajo3aBbFlm0Mv3qiIyENbWIQNPjbVQAbV6O7Q7phJ27mZqrZtNOd6EnVriZAEwiBp0HEwHJ0xHMPYGsdMefo/JBhZCmMGkM7DHQVQjbKTzWj+zdDrYZIGKpFPW1HRCwRzRdhx1CjfYadKHweqLF+w+Zi2ejh9YiO6WZcAy9qsx4bMImdpGG38dC44xbPSmv8uoYIaXjzwVD0hh52vDBRWiwdGbvCCY3qcB6Ipi6TEdiOm/k5vMncM8wRIWJJVP9LZlykNOVbNmooh8iG2H4E1Zwzrm6CbGD606/HwgEUG/kVtFboWqXBhBMy6IiYTaA0MtRLQ/XaMO5NhuWymf/ZjigJFnWIr1aGHtWtoENmIF3KRc9zf6gW4a7V4DrDhS+kuUc9cVeiAU2Vto6SWAVKRIHtAYBtoSs1HB2fkJzvLZU30bjfGktcPB6P2Pjq4roujz/+ON/4xjcmfH/wwQezbNmyN3QvpRSFQmFCbBxAsVhk+vTpBEHA/Pnz+fa3vz3B+H+z5W3j/n+51Go11q9fzxlnnMERRxzxD3m+38qy6rJhwwauu+46giDgXe961z9d3v80SSQSXHfddQwNNTy9XV1d/1gSqn9SdDHk+3bi0NRuAkarDiLTZhhh6i8lyyZlG3af4VreGFOVwoSHveHJ34gOjdsmGUcXS6QVeCVzXgsOMQSONjmWJLDRSzE5bmAuulQjTZoKCl2qkSFFGYUquaQxL6MyivZAowpVkwAKgczYJDRsFsaw2BHwBViOMslmXsVz72uBCiROwjdJW6oltC4gm7vMSxLjoRbNnSYdfZi5NmHHsISMYEk68M1vsaQ5v7UbtWFcHEUsSbOVJKsFHTJOjIAEFhJIhS/ifmkxKjR2mxVRXerCkDnuNsHtujCE3rwGuc2u6MIQrbGsgRyE46MG1xovdXkMai46lwfbokNbqH5jkEndRrtv+iVlW+h8nlhoAmTTobGdT6KKHkH/y4b3e2gDwaZVWL07mPsMb0CNbDQ89mP9tCea2Fgy0J260RCsW26uHVyLGtsU6VebtiIWjjQOulhCYgx8rQTZmMtoLTT6qoWGgQ5RhlpdytFcTwiWd4lr8Ma0MezrxtF4ozfw0IUhmnBQpRIWKdyyHZUtwsBOEUsaMyvVgg48/LWDNPea8h4b7mAbUaYS2IhkFumYPA4i9BCDyQyq+lYySbussuPE0x66ko+STImmLpOYzIkjmtrDJFYlk4G2P4zXkRLSTeihQZMEqlIwtKjbzIvyTdSv0WObTDvj6TBJnDHGrIwkqyWONsncvDGoFe2on2Gc3ZQfQUyeaXIRdEwx/4eiPReyrWaRURpFTJsG7ZOijMy4JvFXfb7oIGeyCofHALLZGNS6VjIc+OPnSj3zcrajEagfT9OGHfLch8HmVoJ2ESeBROeLEGZt1W4Fwr7XXg0KQ+jcZkPVOtpv6EYnzYxYrdTml5E926HG+tED60024nFSn3dqeL1JHBdPQzWP7G5D9ZtnZAyLVLuH31dnntEUJMSVoCNklVOAaG0xY1PPsOy7jeyzWplkWoN5HDsGXrjkHLcgRauIulLEM9GOVUZLdMnogSrVzA7GWL+5Viuz8AvzITiTU8jxPPduxSyyQg5/MIvMpO1Ty9v4rgkQVlogRcNxlNECXSgjknECIUzyr/9hsjWWuG9961tbOAiHhoYIgmAL22bSpElbhb5uTS6++GJKpVJEiQ3G2Xfttdfyjne8g3w+z5IlSyLmwzoS482Wt437/+Vy0003cdxxxzF//vzXzQr7ryyrLvPnz6e9vZ3rr7/+X7pl9f8nefe73z3h71NOOeVfen/RNsX8LyQq3/DW69yA2UIODSZdGqXgVozXOpZEZjtQWiFSLcZzhknoRFObgeWUcuSCKiI1iaKshHzbkNvgk8KiJi2kpakITRtetIEg0nHKBGSwEOk4RQKy2Mh0jNI4nvuikMh0DFcYnL5WxhuZVZFfF3u8574iiGuN5xoTJy5UZOhLqRGZVrMdXikgmhqB27paMi9DO44uj1EO2xqvp5OPpyHThoinGueHEAFzgmQsqDDiNDGiXaokKOPjCdvwRmM86V1agK+RbVMMd3imzXg968ZhutUYfPkBREs3Bb9C3i01eLrbe41BkMxCMo5IJRHpDKNiCNluXuaBEOQtc8+yDhBNTQQYw6qOdQ+EQKYMt7bavAY5aYbJ9Dm4ztyncxpKSNTAamT3LEpehY5kM8PVfCMxUXOXWWx0Tm8YcfE0BaHwPNP/BctDZNIE5LC1xo4btpym0HMvm7omQE+M8eOBHWcwZPKw2pNUBdhNJulaZNwHPjrsF5HMgrQY0a6J90DhJIKo3yZ4vuMJtA4Qdhyru5ncs2MANKsAYWmDFPfdyNuNW0XIcMejVkK0dLFZxGgONH7NQobeecAYtfW5NboR2dI9LkGUidXRfg29eQ0ik0GkWxAdUxHpNtTQBsPdDkghzb2aJ0VwGI1JXgWgqoqcUHhCUNQWsQ4B2kMNNXY8LMIYlckzzc5F1zTD098xNUrqRDwdGYGiqQvt1qCUj3Zh5LQdGvMl09poYziPwMCzRLPJ46GLI0a3Q4hXPZDftKWR62MAl7JMRLtauaDKiIiBiCHaWkzirnQbJNJmngGURozHXUiTJKu5CxFmHRZ1774dM33d3IUq50yCqWRjQSqaJ6HH+pFtU9CWY7zcmTbUwCiyw8R4lIHqmI3EcMEHChLKPGeq4SJZCdCeZ3ZWwvuaDgsXkek2CDxkVwu1eg4RMM+P6FyTRluH/PUimUWQpShUFHckpTALsFjS7EbYcVBB5I0Phqso80gxWXJrpcZuU30RkUhT9h3suELIhud+vJSFRqST6EIZhYCW1ye1eDPkzYTlbI0l7tVe+/Hyj7D7jZebbrqJs846i9tvv31C/po999wzYiMEQwW+6667ctlll70mOuGflbeN+zdJ1qxZw8yZM3nyySe3CI78d8qiRYtYtGjRW17WwoULmT9//j8cuDreY/3/VznrrLO44oorGBgY4Ne//jWHHXbYVr9zXZd58+bx05/+lH322YeBgQF22GEHnnrqKaZMmfLvbsZrS7gtreNpY6iUciZo1I6bF71oGKkxy9C1xaRjvHCbXoFJMxrevHgamWoxL6lYkkG/gOjqosYaVEgMsMobJSYsthNd2LYydJaYZFMAImZR0B6OEIi4Q0n7JIQE2yKnjfFmCYEnbEQyjodJJiPjNhkFPUljnIyuSjBTVdkw3MSsaSOsXtnGDplRXhw1hshu2/SjtcCvSWqejS4MG89WuNVtbmQ3MoPaBg4RtxykEAYSA6GH/WXjHbPj6NIIsmf7hnEf+Iz4RWpOF2u9MXJyCq/4Q/Tb3RFARwJ5GR4oha4VQQcGLlIL070rzxiDpTGwbGxhkXYSjcWX8qJ6y57JkExBtoVngieRc3cDYNhei6NhVMJz7gBM/wDD6jm0r/BDuJLCLLAo5VDD6w0kyY6bjKgYAxTfRY9uRlm2oWx0MsSkbbyeGG+4GtuErpWwps6L8M3PqDzv8UNMvd+HyMxjWIyw2bax4+FCK/Qa6noCL6XAUSbba7oZ2TWTVdrsmlhzptEnx3CmN5lxqhstECWx0nYc0TGVAVVBdPcSsNnAcsYtBEy7AmNQDa5DdM3E2u/dvHSNYfma3T7KyuFWelMl08ZSzoxFrbEwENU81vSdWBGDuXV0UKXQwDd7rvkkswZeVf9NKQOZAJPgKdOKXv8KulIw86u9Yozq+g6b5aDLY8jJ25qFQ+CjtMAbMf3mVyQjeKyIJ/DQ7B2TCCugKdAQLuymxUoUXQe9ea2BIqVGzM5APBVh6ulfC5NnGi+3GdQGHh8mzpdUi+m7+hjUFzSFIWN0WjY6N4C24yZjbVtPBDPRhSFkz3ZhIjGPqg7YaAuKoR4MVvJ4OmCzjEG8C71+FTo7aCAr9SzEtSq6MGow5+Ux4ykPISi6DlsTYW4Krcxvlm36PuxXXSuZhYFbwZo8J1rEqJKLrpj7vBKbxOTNGZ6KS+bEPTzPIlk1kKcWEQZwawmeZ3ZmAs9khtUK3R/2o2UjO6ajhnI8L9qZ7rvkRfj8qUP56hl3S3nU+hWIntnIlm5e1mXk9G1MffMF056wHTgxk9wsXAQOPxejKQgXG8Mb0F7NZEf2XIiZZ76cOZ/lTpydpgtUMSC2ISDQAqUFrjLPAw+NyKTB83C0auxAvNXyJhr3W4PgbE06OjqwLGsLL/3AwMDrIhVuueUWjjvuOH7xi19E8ZSvJVJKdt99d1atWvX6lf9/lP/VHHgLFy7kpJNOiv5es2bNBBqiWCzG7NmzOffcc988/PI/KE8++SRHHnkkkydPJh6PM336dD7wgQ9wxx13/EvqNGPGjDedSeZfIVprrrrqKt75zneSyWRoaWlhwYIFXHrppVtg3f8ZWbFiBWeffTZXXnklmzZt4v3vf/9WvwO46qqrmD59epR4rKuri6OOOopvfetbf/cer0WTVf8ce+yxW71uZGSEL33pS2y33XakUimmTZvG4sWLyeVy/1gjlZqQ9lzroOE2UVs+YeusMOhx19XLqAdejk+MIyS+0NHOsTUuiYpWxmtV1RbKlyhfoos1UsImhYUuVUkJKzyukcIOPxZZFaALFRwEWS0QmTgpZXCwShvMqMLAslVguOy1EkhtvJYqEGGdBL6SE/uhfjz+b103PsVEL87488a7m8Z9bzD3GktI5Lg+rNvzASE23paN7XhhmWNpRYG9kfGqVMRiFMn47JZ+A0qVFDbUalCrRe9LP1pVSBMXIQ13t9bCQDf8oJHRUqkoKLEx7kHUJ3bIry0QETxg/Pm6WkIk0qAUKWETIAgQ5vxwAeQJQGiE0IbJRWxFv15DNCCkmHiOUibZmm7s4siw7gqi5GHAFufVvwOzuxMXCt83MKpAmfvowJugE+PrGAvH1o4HDbhEPeB8/Nwa973pz63QJY8z9qLz1Zb39LWcUFxVBzjasAbJjIPd1NC1LV76Wk/UYSkbWX7HF1r/vv6pXyPkxL549dypt3V8nbWaeH29DzA2nfOqulpCbjnntDJ67o+r5/jFXR0SM7499UDfKIB3XH6T8ZCYwDdBv1qB0mhfoX1FMlSb8X1o5rPhhbekwhEqigXaqkTtN4XZQkcMXlucUz8e14damV1KlI7aHOnVuD63Yya6R+pX9bmeODcsTdhG8+wE0FqQtn3Stm+gQJUaqlAxbXVe30j+nyqxWIzddtuNe++9d8L3995779/NI3PTTTexaNEifvazn3HooYe+7n201jz11FNMnjz5n67za8n/Sc/9H/7wB3bYYQdqtRoPPPAAn/nMZ5g8eTLHHXfcv7Qet99+O0cccQQHHnggP/3pT5k1axbDw8M888wznH766ey7774Tkjb9I+J53haJmd4K+Vfd59X3O+qoo7j11ls5/fTT+cEPfkBnZydPP/00l156KTNmzOCwww57U+5X567/8Ic/HL1ctvYdwGWXXbYFhu/YY49ljz324MILL6S1tXWr9zjyyCMnJLeqy+WXX84FF1zAZz/72a1e19fXR19fHxdddBHz5s1j7dq1nHDCCfT19fHLX/7yjTcy9MQIJ4YOEgitELEE+lXMF0IbOjcpFK7yDINDPGE8/KF3UoB5ScaSIKQxQLXC1iLKjlkXJcCOKUplRUIExFLhdn9nKwVdRQqQbU0UdQVLCGRHlpI2L2xLCKoijuxsoiI0Y0Khqx45Czzf1NdyFIEWOKFRD42XV120EkhbkXQ80w+WA7V4wztlOeAlTZvsGCLMDGoJiR8G7hKmfzeBg46BN1h2ZLhGHsBx9w20wpeEYHJjbCfqwZ5OEi2kgR24FQhhH8QSYfCnRMSS+DqgWk8/D+BW0ZZtPKhBGLbruROp83RoPIX3FcIynnopcGwz3oEHIuFEW/0ino7wvGDgNRpMUGIsia99Aq2oBjVzTXSz8NowUFIk0oY6UYT3USq04kNcsDSUpPVAvgk6aDmmPxzT1si40hoLgfaVGYdxdJiREeLEEJZNgDZeU8zCLuq3wI+MVe3EwmDHJLqUZ9xtjLEpdEPfZUhcWN+hCdmBNGBpbXD9saSZJ4BWQTS38JKmf+ptrC8uYglIpE2Aazi/iCUhkYrajpTgG2+4EBKtFTEZRAHrOtAkhBXplsq7BncvRBREGyhBoIW5n+dCImX6IZ6I+kXHEga6FO7CkUobz37IahbNF69ijqVl+qB+DEZ/6v3sxMNPzLSlHnjvxRsBxUoRYBZg9QVoPfA7qDsOnJjpl7C+kcQS5qMN5EoohbbsKIg57BzTJicGwbj+BTNvx+usVgg7hrAbpryCSD9VIAiUCfg3C79woaolIhY3z4v6DoFfi+paDzAWqRgJrSlqi7KUpp8jbKI0dQ3bWp+LFnKCsS+cJEjfeO3dysT5h1k0KzBlhLqj63UI/45rA+Uan+TM9LsZgGERIDJZpFaA/y8LqP13seWcfPLJHHXUUSxYsIC99tqLq666inXr1nHCCScABuKzceNGrrvuOsAY9kcffTRLlixhzz33jLz+yWSS5mYDzTr77LPZc889mTNnDvl8nu9///s89dRT/PCHP3zL2iH0v8tl/RbLokWL+OlPfzrhu9WrV28VOnPAAQew/fbbRx2tlOLcc8/lqquuYnBwkLlz53L++edPMMAeffRRPve5z7FixQp23HFHvvnNb/KRj3yEJ598kp133pk5c+ZwwgknTAiMXL58OTvttBOrVq2iu7ub6dOns99++3HrrbdutQ31oXm9smbNmoUQIkos9Yc//IGvfvWrnH322VxxxRVcdNFFrF+/npkzZ3L66adz1FFHReXMmDGDk046KdrhyOVynHLKKdx2221Uq1UWLFjAJZdcws477wwYiMptt93G4sWLOffcc1mzZg1BELD//vtPgOX87ne/48gjj+Syyy57TYae3/3ud5x77rksX74cy7LYa6+9WLJkCbNmGVaIOtTplltu4fLLL+fhhx/miiuuIJ1Oc+SRR3Lbbbfx4Q9/eIs+y+fzNDc3v6Fx3LhxIyeffDK///3vkVLyrne9iyVLljBjxgzOOuusrQbhvPo7rTVPPPEEu+++O6Ojo1GegrrMnDmTM8444w1ThwLcf//9HHjggVxxxRVvOEEVwC9+8Qv+8z//k1KpFFGLvp6cPOPjABQIcBCksMjhYyNIIqmE5mECybf/owKW8ah/7c4M03WMUREwxkQDdlTXaBExvn9ilm9eUeEbMzfx8AoDTTr4gmnoconcjct5etUk5nSOksslyLsGb/pQIs6XPl5GDRW47A9dfPljRYLhElf8qZsvfjLknx8pkn/K4/r+Hj43fz1IuP3RXvbv3Myz/QYTumB2P7evncLH37WRS5f18MV5G7hpeS//uaehDLzy0anMdDWdyiNt+dwWMzCGZi0phy/wGopWbeEJot++8MER4/EuGJzRefd10q4tRoWihqJFW6yiQt2sTgubH3yhieqyl0kevjfVOx4i/q7tcZe9iDdizhndkKR9mwoPPD6F2xMubTgoNGP4tIQ+GImggM8kYtRQnPkpH11z+covG9mN01jEkZRRWJjdgP9edibd2x0GwIZzD+B3382z/z59JI7Yn4+f8jdu+EDAnbe1MUcaOFNLU4VHxjp5MhbQpS3yQlFF06FDrLxQ+Gi6lEVOak45LI+/sYBMWVx4v9m6dtG0aYuCUDyj8qSEjULzs8cvYd1Cw5rVc8beXPS1lZz0/mHKL1RZsaKT7uYS1Zpp75UigTOOWagJixKKNarEjSf3APCFS4e4dP8cl/xpEhWhIp5wgGRonFSEZr2ucuVxSU66xuVLVKm4DtfEGt5VBcSRZLGwgEE8hnWNnx5j4ii+fp3m3L0GuOGBKQxY2hhEgI3Ao/EKfVznuOm0Way/dCXlcowbZYpyiHRPYaHQ5PFxkCSRlMLg6nhY71w4j3YM4rxk+UzWNqMiIDNOJz00TVqyWlQp64CEsDjR1ZQD029Njsucg4rYU9vQfsB9S2OkdUBbokomDJp+fLSDjFI8m7BoUTAmif4fCRdfbdpiRARsE1istgKSWkZeajBY7PqcKApFANHcqfdJs5ZUhcZH0xLqUquW5IXCHXfOOuHioYkjOX//Eaz2NLoYBnhvPx3RMwXyY1z27QFaAyhKSCkYCHdgugLBiAXrhEsbNjU0w7i00nA8jeLRRYwqmhI+LTgkEBTCeeogaNcWRaFYHuoswCdrjYysB3yzlcKtz5Hes4P7r4nRJDw6m8rYdkChaIz3ZMLjtlobA8LHRUc7dd3alDcqAjboKsdWY+z5iTKP35SgKebyC2tixnUJtCpjfPdZiiE8Ll1kc9q1ps2ZcJ7n8KPFbhM2a0LI2k/2yLPmkWYScY9b3dYoJ4I1TmdfpMKVxyW5/seClIJ5ohjd3w8XK9vvP8Z5D04iqyVHpob5Wbmds9beyFstAwe8+/VPeoPS9cf7/6HzL7/8cr73ve+xadMmdtxxRy655BL2228/wNiWa9asiVj2Fi5cyP33b1n+Mcccw7XXXgvAf/3Xf3HrrbfS399Pc3Mzu+yyC2edddYbyhP0/yr/a437XC7H+9//fnbccUfOOeccAEqlErNnz55g3D/22GMcdNBBLFmyJDJCL7nkEs466yyuvPJKdtllF6655houueQSnnvuOebMmUOpVGLmzJm85z3v4YwzzmD16tV8+ctf5pVXXonKPu+887jxxht57rnnojqdfPLJPP7449x///38+te/5iMf+QgPPfTQhECLrcnrlQUmAKSrq4vvfve7Ea/7E088wZFHHsmll17KgQceyJ133snXvvY17r33Xvbff39gonGvtWbfffelra2NM888k+bmZq688kquvfZaVq5cSVtbG2eddRYXXXQR73rXu/jud7+LZVm84x3vmGDc33zzzRx//PFcf/31Wxjf4+VXv/oVQgje8Y53UCqVOPPMM1mzZg1PPfUUUsrIuJ8xYwYXX3wxu+yyC/F4nBNPPJEXX3yRF1544e/22+uNY7lcZv78+ey7776cdNJJ2LbNueeey+OPP84zzzyD67r88pe/5Nhjj2XTJsP4kclktviuu7ubSy+9lCuvvJIVK1ZsUY8jjzySVCq1BW3ma8natWvZfffdOeKII/jBD37whq6py9VXX82pp57K4ODgG77m4Z6PAFANLKSAmAwoByZoLGEFuCqkm9SSzmQZP5BUPAcFZOMuNc8mHzReomVhkQqZOqZ053h+Uzvbto9GL7+W1jJCQLXsUCjFGfNjdMSrpEPDo1yOoZRgyE3SlTD3G/ISdCfK6NBgG6ol6Ig3svvlajEUJilVOdzm33nqAI9u7GaPKf08urGbd83ZyB9fmsrC6Yb//KE1k2lVPlNbjYd2LG9e4qm4R3kcLWQ67lF1bSypSMR8ap5NoARl35yTsj1sS5nvtSAV8xipJkKKO7CEpqulRKkUI5OpUas6OE6A61pMmmnuvebFdnwlids+Zd+hpiVZy8NVFtXQqG6yXFxlYQtFzAqwpIGxjFRNv9rCeAHbLZdKYOFiYaGZPWWYZ/o6AZjTlKNSdZjxzhyDyxOsH2mmp6nAaDHJ1CljAGze1IQXvtizCRfPl1R9m0zcuPZc38JXkqZkjXLNQWtBJbCx0GYHBKj6NqmYh+db5P0YAYKECJjSkWfan68A4OW9v8hIIUkq5tHSWqF/IEvC8cnX6knItIFShUF+tlRUfJu8dthllvGOLVvdwy7tQzw71M4UqxJ5VaHhSXWsgKIXoy1VYaCUoiNZoew6kTFsxlngCIWvzf9VbVEQFgv3MrkXfvp4L0ftsJ47n+llJ1nADgOxhSDSFccKGHYTTG/LEfiSDfksWcuL6hGzDJ65ft+05eMqiSNV5CXNK4cAQat0kUKTcHzKrmN2DGhIMuYxUklE+jV1Ui7anbLjAXZM4buSeNbnnpUmiNfShrIRYMwyCZgWyAKBEtiWibmwLRXpU2u8RtF1yMZdSrUYZW2REkEUcFmvz/j5kk64lKrjFpsJN6JYTSdcyjUH21JUPXvC9WMVM+YxqXCsgEymFlHWAth2gJCweTiDIxWOHSCFjuJEZBgMWnYdA48RmpJvU8KmVRq99bU5Ny4DKoHFoIwxhcYzRApNzDILmzE3HunE3HcMMPiKYdaJxX269tEMPChYPtKOAJ6JC+II5lfNwsxCM2DZbEMFX8mQWlKSDueP51sUfIee5iLt00v8eflUHK2Zak+Ek8qQuSYR86m6Nm5gkYm7lF0n6n9fSUrazD0PQVb4lMPnxfyd+ln27BTiWtGTLDEe1VTvt7LrkE3Uor8rnkPc9ifUww0spNC0NlUoFOMMeQnet/lm3mrZvP+bZ9xPuu8fM+7/N8j/WlhOc3MzsViMVCoVsbDUucv33ntvpJS4rovneRx//PETvMsXXXQRX//61/n4x41H84ILLuC+++7j0ksv5Yc//CE33ngjQRBwzTXXkEql2GGHHdiwYcMEHvdjjz2WM888k0cffZQ99tgDz/O44YYbuPDCCwFYuXIlYBIt1eVvf/tbZHQDUQKp1yurLp/85CcneIc/+clPsmjRIj7/+c8DZkHw8MMPc9FFF024T13uu+8+nn32WQYGBqLgk4suuojbbruNX/7ylxx//PGA4YK9/vrr6ezs3KKMyy+/nNNOO43bb799q/cYL69OtvWTn/yErq4unn/+eXbcsZGw5aSTTuIjH/lI9PeqVasm9NtryeuN480334yUkquvvjqC1yxdupSWlhb+/Oc/c/DBB0ewqPFMPlv7bs2aNfT09Gy1HlOmTOHJJ5983foClMtlDj/8cHbYYYd/OBZieHiYb3/723zuc5/7h6472zLe8KJw8VG0WkkKooaPokkmqMkQA47grnMWRBCGg099lB1FOxvsMgVpjNRaCC+oKY//j73zDpOjuNb+r6q7J25eabWr1UpCARACIRFkgsFgMDnZJpiMicYBY5MsRBLGZAyywZgkmWSCMdk2yRgDxiSRJBBJcaWVtHlnd1KHqu+P6unZlUS4F+zvXl+d55lnZ3u6q6tOVXWfOnXO+yZljGcu2J0zf/Iyt27p8tLzZrwcctH2EPjkbn+a91+rYafpK2lbUMWCnjoAXk5oLjxJsknR5cK708w6EXS+yC/uq+C8k80ja+Oiy+oHC9w8UMe5O7UjYpLfPDOCw+tXs2SlCX8a6EngaE0sFbDaFmglyElINpo6Lm4TTCpKPuytodEq8HO7iKcVicAisM1Co/R/wtYUdEDaj3HbhWZnSYd409/++fs0izRr7AKuDkhoi6ViRcQa6WDx0hUH4v/tBexdv07u1j+ROno33L88T9Br+mBkcx/pkT4PzWvh93Y7trAYUEWSjhN5o/PKozqWICYsBpTLw+dugqitY/efmhdXWsYQCHwdMCpWias9OlSex877Or/5saFPv3OjHANrYsiExUbPXsu08XvTee95/Oq7T3FYq9H/mMZe/tgzghfopUrFyAgXnIBKbYy2PuniWJK6IEm35XLX2aPRPb2IVJIjrzNGt3KKpHHotzyTOIthmX3j/H1ZtIMhbBv/0vUcN+V4/nbDAeRveYRX1iTZWA9EDLYzrB4SYUhSoBXDrBS9IsvyYhfzjjEer/suW8pee8S5+UHNO0FhSB5CMgz7yGuf5bTz8lnb8PPLW7nICejPp7jINgvghLAJUMSETVo4xITFmqCXQGu+njDlFUPDSAI/F4qktg1DrZb4Thj3DrytFvHmUZux6u41pETALCtPftD8SUibjDBMyFUyQS5kPq2xzcJyQGXwteIrTgPz/E42FbWsdvLYQuKGc8vVATFlsVKuxtU+AsHc7uG0esbzm9SKHU8BnTO7bN5HUOsrptR1kaw2dXljyQiq8bklEadSWmQIqLQt+glYHTfPg2aZYmUsx2iRZnksS0xYEW8FmLh+VwfRfAm0IuHbeOF3gIRvoyyPAE3Ct8iKIs0iTZddpBjuaCSUTZvsJEAhEPztpFGotiIkjJFqf2M3E6PhFrj6p29RQzzaZRywyrsiWeGz3BkgJiyyysWKSSSCbBhvkhA2MWGRUUUqYvFwHhWj+VVtJYgjKeiAjzDIUFprznpvYuQZ/+Y3Oul53Wfkjzbjg4s6SRJwRGUflq34aJWZP2nL4/mY5o4gTxDuLMRsiyZhdoFWWTlagzWckR3HgaNcRr+bpzJV5OzBFLGAhaDRSuKoOMtklg7Vy7Onb8IJ1xq40grhsCIYIK8Nq7JEkJQOS4oGAODRVTVsUtWLbQdckE1haYEGHCEohLsz77OK5w+o5daHK0kp2MrKRvcvOVK2+Haecx6vwClUc5zMc3Mix7pBpBvkf5r8xxr3nyb33XcfkyZNwvM85s+fz2mnnUZtbS2XX345mUyGtra2KCmyJCVMUjBJlltuuSWpVCr6fe3tlaamJvbdd1/mzJnD9OnTefzxxykUChxyyCGfWK8pU6ZEhFQTJ07ED5PiPm9Z22yzzZD/Fy5cGBnkg9sxe/bs9d5/3rx5DAwMUF9fP+R4Pp+P4swBxowZs17D/o9//CNr1qzhxRdfZPr0MovdCy+8ECWdAtx0000ceeSRLFq0iPPPP5+XX36Zzs5OVBhLuHz58iHG/drt+jywVJ+nH+fNm8fHH39MZWXlkHMKhcKQ9n4eyefzn0glnUwmoyTfu+++e4jx/Ze//IWddtop+v+EE06gp6eHp5566nOH1YBp77777stmm232qQm86yPz+P1ZGxF3LBMbms+bmFrLMkmYMSdK/CJf4Mjz38VCkMDiyQunoNtWI2pHleNwS4mcUkKhwPd+Oo/bT6jk5lurOGSU8Zif+xMfAWzhtbBdZTePvdHCWL/IZtW9AOwyKcsvbxtFlY5z7tatXDd3FBU6xVnTWvnlzYbYq0LbTCrWcs52bdz/txYkcOzYlTy5pJlxwrRv2NgB5r9XQ64nxhSvSKHfZozn0/a26e+dvRwNwwcoFmx6BpLcf944E+uay0Ey7MvS/1KCEOiBHEdf/CECQTxEDf/jzI3RXT2IujA5KptHNGwxRMcnnfYy2+pqPnp4Hgfkm3h8/rvsXCyjL2iguFKwz7iVHH7YJCi64IRx+16J2EYa/Ho/QFRVcMplrfgs4+lzNzO/K2Wu0wrvveVYwypBprnsp+/yhyOM8fjAXfWklaarS/DA9NPpeul6Jnz9Z3zwg81YcJt54b+zZjjHf6WV7+81Bd3dh6irNgl3mZDsp6bKJNx29SAamznhsmXUiBi9eoC7zyqTnumBLKIijajYLNLf1Wd/yG6uqctxU47nhXfmcOBWP2SGO5xth3fQ0VVBZcL03xM/29yMQTDjMDNgdFKxKbf93Bjmt+yQ4e77mzl97Eqqj5oyJFBX92ai+orKqVx43mJu2SPHy4/WMXlcO08ftVlpUpRj7nv7QQpEbSPBkpW0PWHG885ung/eHM5GFLj77GZwDRqL9gbF+CcTiLrNePBnraRVPdPHreKPR29eji0fPLcKBYjHynOutIEuBDqXR7W2Y03d3MyvihGojm7k6FC3UpgxNnzzKCn1/Vkfse04s5OoAsGNvxvJZsUkBSHZZ8JKigM2/2gfgRfm2o/VRQpYXHVkgFYuwgkJtxwb7BDCMV9E1AxHZwYQ1SMIlrYhEk6UACvHjS7Pj9K7cPD30v+OY/Q7kIWqCjOmahojAjLTls3MNojWXHfBCjYr1tEfxnY/+dDzDA+5K648IIdIxxHJhBnrITkbngeptIHuzeYhnQTXM/1UyglzHNPX8TjkC+iBLNg1iPowF8oPzJitqULENonGRPaB17BCmNF5Dw1nRFWWBRd10GAXEUIzv7PeLEjD5rhBnCt268SeOtEQTlkW5PLmfoAY1oKomEThiddZ+GQdXUGcldkE91849L2LH6DbO8GSiOFjERUVXH1BKzfvH8Jn5rPYW4wDPzAJ8UUXEY8hqicB0Hf76zyxaBQSuPX0WPQc10ohSsReTZP4y9nLOGLTFfhFw1BrSUXcDiiG0Li3P1LHZbusIsj4vPxyE3edM/R9+S8T/env+A3y6fJ/0rhvaWlhwgRDDDNp0iQWL17M+eefPyQZ8tNwTj9vJNOJJ57I0UcfzbXXXsvcuXOj8AwgIi744IMPorCceDwe1eu/UlZJ0un0Otf9V/BalVI0NTWtl7F1cGLv+u4DBrP+jTfeYO7cuWy77bbRfbbZZpshLLolSKn999+flpYWbrnlFkaOHIlSis033xzXHZrZs/b9Nt544/WGv6xPPq39Sim23npr7r573fjB9S1ePk2GDRvG/Pnz1/tbd3d3VN4BBxzAV77ylei3wRCZV1xxBY8++igvvfQSw4Z9fizh/v5+9tprLyoqKnjooYc+NcF5fWQeO1dvztdqpuChKaKowIq+pwbhQrhobt877BtbMuvS1TQoi37RjzcoHliEf+NIfr3nADfcluTY8a08/YExTi4+qAtd9Mkv8njug2Z2G7WKNasq+ShjjIpn36jjRzu3oV3FPS+38IOvrkT7mvtebuFHO5sFAr5m9ZtJ7n2jhW9PNBBzL7w/ip3qO+jpNcZj+5JKqlWAtDQrZYxRSjAgJHWN5iX7+rIasu0OBST1VpFfXNGFoJSHGL6Iw//jWuALk4g6d38fXfQRcfP4/PnlHWEccVekqxxLIh+nAm480MVr7cIZU0Xxgwzbj0lSXJKnmDELhExngkTK45WPm3j9ml4CoIAijYziY90w7j0AiqKX67+ewapPc8FV5r6p8FwPTaNqRAnoEYoZe3bym3vN+DtsxGpWr65i5wldHHvUtnxz/xv46A+nMe3wW/itGAvAxlW9PP9KM++81Y2DwKMbKBMgeXTjYHYkCnTy21360a5C2JIrr+6LzjUoQH10ie5IL5fs3cuivxiD7G83HMCBW/2QR964nsc2P49sex31dpGiZ/Q66/L2KOZeAwkt8IRLLxlmbWe8l3e+NIpDJ6zg0Y9HsfjyjiEoJonQOCiKLrJ0cOGO7dz25Eh2S/bx/uLh/CXUmxPGItsIEtrsG2RFH0ldxUkjjcE8v6+OrUe082p7A3/9ZX8UyW0hon72GWCN6OWSr7Wz9KVKli+t5TdXdEXY8gGaRNhHpbllWItNDD2AG8arj/PrWfxnM79yIk9AEugx4yl8pA2wNCr7qEDy7iKDqy2B46a2ImxQLsx7p4kEAVNSfcQTZjHS1l1JteVy652G6Mgkr9oooBDO5SoVp1cWqVExemUeqC0zAwO+6Brkx89ihXrUZKOQGx3qqMSMWxRd4VzpZvBbtMgy0zY0M6esQrugQj/BgZukgDzaC7j7oQbywiSKVqg4+WhHJYYioEeaOnlkiSEIgBzGsVIZ6rtIPzXawheSAXwcjKe7KoTklXSzRhhOXIVm78LIiFX6q1utpK81wU6HDfDqfWkSImDTql6kpfio2ywS0vj89pkRZP7aG8W5x7QgFe58DYh++kQve+cb2WLiGsTiWuKOzy+uYB29VYTXZEQ3BbqYOX0VNz9qHBxJDW1/7cdDR7sPSe2zWpg5eHoyweZigJgdcO31VdFYtQAvzO3oFEs4d4tV/H3BKJJK0ZzIopTADyRWOA6+s3krt/69BRvYkiI3XZfnJz/lXy7/vxJq/1PkP9q4j8ViBEHwmedZloXv+7iuS1VVFSNHjuTFF1+MEigAXnrppcgbvdlmm3HnnXeSz+dJJo0h8fLLL69T7j777EM6nY4SXZ9//vnotz322IO6ujquuOIKHnrooc+s46eV9UkyadIkXnzxxSEhRy+99BKTJk1a7/lbbbUVq1evxrZtxo4d+5nlry3jx4/nmmuuiWL+S/HiyWRynUVLV1cXCxcu5Kabboo81y+++OLnus8RRxzBd77zHR555JFPTaj9rH7caqutuO+++2hoaFgnCfa/KtOmTePGG29c7+JpwYIF7LLLLgBUVlaus1MAJrl45syZ3HPPPVHy8ueRTCbDnnvuSTwe59FHH/3E3YOSrI/M4+FNTsZxoSAkvpBUKE1OSnwkNYGmKMvtyb5nYlSFhE29Opp8ny7LjtgkFVCQxggOAL+9QH0A+Z4Ym0qTrOUuy4GE3tUpxog8XsEiZgckPPM0H+tqehZYSEsyxg3oXuAgLc1Y16f33TISTt9AgjFBQPeKNPGETwAs66gmLkw5I5r6mV+oJpbyTcx3pcdAt8ROmt89AdVOkYRvY0vF1KIx4BUiik1W4f8VypACSa3JzCsgLR1BRU5xa6kKAjJW2bTssYY+Wosf9NO1LEVNTz+rllTT7PfRtSxNbXO4iBDguRYC2NiTxJUmY9nENSRDj1u3JUgrcLRGCUFmgcaOZ5jkm/HkaJNk2GlL6n1NXgrilqS42PQBgB03gRW57hip1xawg6zHvet+LpcTiYU7HvmCgy8Em7gg0aSUYkDKyHCOaU1BCCSaShWQeQ+0luQHYkwO134KY0TYWrPGtvGEednk3i9QU2sqk7/lEWa4w3ls8/PYf8ElPD95BoWgnOS6KRaJElJK2AdZKWm3HVTOHC8Z2SkFU1yBPchiLKGtSC3osW0GPoZGX0MMktJnsmee3YNBCxVQEyh6LYtWW6PCQjwBiUofv0Mw2R0c/z7U0VNrO7S/FSeVcmnvTrFFUZCXgxcoQ+dWXgoCYYiQAHLSoK+M8BVJbdHg+/SHyDMlW8cPny/9lh0dq6vtIZkz49EPJEFR4PVK7Lii07KJawty4ISx7X3CoRBYbBKYueGEMdsWmtXhLtzEoMAqEUdqReN6HULCMD6jscMEY19IYlqXoVYh6hNzLlQFATkpccMyY1qTsWTUluwqm4GeBOlqMx7FRzmUJ7CSmmG+JqUCHDR90qYunIPd0iGlArotG0drPCFRwsydrrA9FYGZO0VpIzWklGKlYxMOR+LhWLO0ptYxOUUaqKHA6JG9APQuS5DPx/BX9eNRAdqibyCBJRWLwwTtlLbYpuCyJoLZNO0cFpTqatNl29i4qECQCRycwGKqHKpjAcR1QFxr+qTFgJQMLLUY5Zl6SqA6kGZuhQu0pNLUhkRYWgu6vQTC02wiSyMwhI4N79Fg2fSsSBIPLemCZ2MJjSUVbjgXu5cm2bQY4AlBTaJIRfCfC4X5nyT/0cb92LFjeeWVV1i6dCkVFRVR2EdXVxerV6/G933mz5/P7Nmz2XXXXSMD76yzzuLCCy9k/PjxTJ06lblz5/LWW29FHt4jjjiCmTNncsIJJ3DeeeexdOlSrr766nXub1kWxx13HDNmzGDChAlDQncqKiq49dZbOeyww9h333057bTTmDhxIgMDAzzxxBPR9Z+nrE+Ss846i0MPPZStttqK3Xbbjccee4wHH3yQZ555Zr3n77777my//fYcdNBBXHHFFWyyySa0tbXx5z//mYMOOmid8Jj1ycYbb8zf/vY3dtllF2zb/sS48draWurr67n55ptpampi+fLl/OxnP/vM8gEOPfRQHnroIQ4//HDOP/98vvGNbzB8+HDmz5/Ptddey49+9CMOOuigz+zHI488kquuuooDDzyQiy++mFGjRrF8+XIefPBBzjrrLEaNGvW56gOw6667ks1meffdd4eEFOVyOebNm8ell176idd+9NFHHH744Zx44onstNNO6xBoxGIx6urq1rmuv7+fPfbYg1wux1133UUmkyGTMaEIw4cPHzJ+SrI+Mo9vjDdeUDupUJ4gcAVOuvxdhm9n5Que+XgURQkVgWafTVaQ7YqRqPRw0mZuKU+gfIEVN9c/989mdh+5moUrhzGh3ngeX5jXjCcEdcqnIZXjxe4GvlrXzrCRxvjXWvDQipEkNew1rm2d72C8VpPJMXXcGl5f0og3INi6tpM3e4ZhhS/p2u4EzcqlfWUlE8mxYNEIdqjv4LUFpozdG9fQ052iubGPgUycr45sw4orcl0x4hVhclxcke9xsByFk1T0t8f56/KReMLEMQPsMqEt4sWRjqLQ55AeXmbc1Qr++s4oqlVAsbeW4aLI3xeMolb50W5Fj2UxLdbHjluuJN9tm/ulFYVe8x3ASSvyPeaRbccULy9uImNJ9h1v0H+8vIUdV9hJRc+KJIm0h1aCt95pZKc6451cs6KSNpXA7lK8/Gia48es4m9/aWSTyl5GH2vG2F9u0Ow4vg2/KPEKlmFzpUwy5iQCtBLkBxwSaY95rSOIaYUnJF8ZVR67WglTn7gyGPYS3lvQQCKMk35lTZJth3eQba/j+ckz2Pndy7hj6gXsmDKe/omNnVGSKIBXkDgJhXQUL80zffiNYR28ubCRHRrXkKj0B927HDMshMZOKl5bMJKt67ro7E1Tkyqwd7Px3PtFGdXXckwiqh1TeAWLzjUmkXKMLtCzKkVD4LFxcxeBV17IlfpHK0Gq3uX9dxsYXpklIQJ2Hr8GKyTn8nIWQmgzt3xQnsSKK4KijMaKk1ZoBf1rEqTriuR6YqTrXdysVSb5sjX5XodkrYu0zZxrX1YZRfYUPJt3FzbgCEUXMaamelFKMFCMGfhLYJOqXnxfkkq7SEujAhH9nTYsXOT1xJhQ4xG4AitmeCqUL1CBCNuto/kRSwVYcUW2M0ai0o/aXJpL0lEMdCRI1bhD5krpPql60xY/L3jpw5EMw+PDrJkb/iqBozWuEGw/ehV+0UIFZrFe6odSHwSeREiNk1S4WQvLUcQqw/t020hb46SCqM5OWuH2y2h8l8aAYWw1+lz0QT1dHWb3WGlBoCTPvzCSkXYepQWxEEJ2J1GGTm0cl2HSoLGrFQYaFYil/FBXcZYuqSMtfQIt+Or4tnW81V7BIvAkiUoPK654970RbDO8MyozlvIjzgYhTf+UxknPqhRJ4aMRbDWsI5oPQMTMnaz2aFtSzUYpE3KXLzqGH0SLyHP/dm89u261giAvWPRBPftPXMG/QwbP/Q3yX5f/aOP+zDPP5Nhjj2WzzTYjn8+zZMkSgIg9zLIsmpqa2GefffjFL34RXXfaaaeRyWQ444wzaG9vZ7PNNuPRRx+NQmkqKip47LHH+N73vse0adPYbLPNuOKKK9ZJEAUTQ33ppZeuFwbxm9/8Ji+99BJXXHEFxxxzDN3d3VRXV7PNNttEybSft6z1yUEHHcTs2bO56qqrOO2009hoo42YO3du5EUGE5pSiu0WQvDnP/+ZmTNncvzxx9PR0UFjYyM777zzZ7KzDZZNNtmEZ599NvLgX3PNNeucI6Xk3nvv5bTTTmPzzTdnk0024Ve/+tWQun2SCCH4/e9/z80338ycOXO45JJLsG2biRMncswxx7DnnnsCn92PqVSK559/nnPOOYdvfetb9Pf309zczG677fZf9uTX19fzrW99i7vvvpvLLrssOv7II48wevToIXH1a8vvf/97ent7uemmm7jpppvW+f1rX/taFColhGDu3Lkcd9xxzJs3j1deeQVgnZ2RJUuWfO7dl48+NiFAnpbUJ/L0F2N4WlIbL9LvxqKQ+7Tts2W8j1jcZ3lPFR+/P4wAgdWho23ruDRoGhkvRm28yEaxLCvaahgRz9PZa16QE1KZyNiw7YDN/X6e6m1gSqdJ5Fut4+w/cjXFvM0rSxo5YNQqClmHV5Y0sv9IYzwW8zbxpM9LS5vYoqqHqmF5ulZVMK22k0y/2b3I5ONUOG6Ee9+UyrKmu5KmmNmm7+pK0+0l6FqVwEHR93GCgrZoru5n5WpjWBS0FaHJZJXNqKp+psX6cJyA1j7jMV+2uJZMECMtfIpa0pDOsaKtJvJEJqyATWL9eL5FMu7hehZjVA5XWzQkTV2afUlPPkFhgU2/7xjyJNtnwHOi0OSU7THgOdQkiiglmFTZS9G1WfSh6b8Aga8FNbEiXmDh9xj0nTF1fazoLo/nrZvbyfQk2cQfYMWyGhplAc+z+MevjXG898mK+bfVEihJZaLIQKcxCitDtI+caxByatN5WnsqGBPLknMdko7HmlXmPvnApjI2CNlDaAIthkBdbqwH6OiqoN4uUggs7ph6Ace8dTH/3Pwc0z+ZVKTDEmpOgMAWijEJsxDs6E7TEMuzYk01VvtgYiqBHaK6BCE5V4NdoLM3jSMNMsxHH5ZD3zSCmAwi1BpXSapiLqlk6G0tJkh6NrVOkfY1lcQdwworhSYfttGSiuLqamqTBbr7U4xu7OWjj4fhhSE3I9JZunNJPC2pixfod808a0jlIrQYT0sqbY9AC9Z0VeBrSbFdMro2w5rWiuicEeksK1dXEyBIWn7kZQUYVpOFTJKYFTCiYgC3aCOlJhUr5we09ZmyZDaJI8z8tQjncQi01a9tYqtUdLwxlcNxAsPuC7T3pvG0pKlqgBVtKXLaoqW6nxVrqnFDxJbm6n7a1lSRVTajazPRXEkKP9JLU9UAraurCbSgwvGYkOhHaUEV5dygmB0QKEl7WyUF30YKTa7dJh/uu1QKnwFtUSECkpYxlrOBgyMUFY4Zt71unJRlxnh/iO7VmMrRH6L7BFpQEfPod2PYwiDu+EoyrCZL/4Dpn0TMx7YVTj4g75kyBooOFopR9WXj/t0PRpAQQTR+PwkZPul4yFCfiz+uj9CeSghRJfPW7wjRq2yPTKa8O1vstSKUMzAIU0447qvTBZIh8k0mk8CS2vA1SB09E9s7LAItiDmBmV9aIMJxXeK92K5hNS++2UxCKzZp7GLxR/WUoST+dbIhLOeLyX8sFOb/FPnHP/7BLrvswooVK/5LBvK/uiyAIAioqqri9ttv5+CDD/7C5f1fl/nz57P77rsPSdKdPn06p59+OkccccQXLn/p0qVMnDiR9957L1qgfBny+qiDAPMCVdrEW8adAK2h6NnRQz5mB2TyBpHbsQKEgAHXIe14JGLmJRIRufgSN7DwlKQy7tJbiFOfMiE9fiBx/UG7UlJRkXL5R854jicFeWpSBYTU9Awko+992QRVyXCrXmoKRYec61Cbzkfwe+lEOV9DSE1bptIY632VVNnmt9ILNFCSriCGBIpCMtLKY1uKnOtEkHiOHZAtmrJjVkDWtyPPczzUix9I81LEQBQOFGPUVuQJQng5rQWZfJyiltTEighhrhFCMxAaCJtPbafQa/Fw20h2tkzMrJQapUT08i/dq+gZ4wYg69uRXrUGxwnwfQvPl2TcGHXJwhBdx+yAtnyaKmkMyJpkkZ58gpTtkfeN0W0JzZY/TLPghgF6ghhV0sORil7f6KHKMtd26DjDRZFUzKOysojvS9rDBVza8eh141Q5BtLRsM6aOpegLi00lQkTY18ILIZX5WjPpNl+wRUAvLv16REMJBiv6WAYRIDeQiKCIvUDGY2/UltLOkvE/CHwpgnHx5KlcWCMmaJnE3d8AiVNvxdiDIRGYEOqBAFr42vJgLawAQ+zaCj1RV2yQM51qKkoRGOuNH8833ju4475v+CauaWUiBYViZiPZSkGcnEsqch6Zn4BeKEB71gBWc+hJllEayJo2hIMaa8bJy4Utek8mXycuG3msjdoARB3fANh6tkUlIUjDOGbJTQ14RzrL8RIOj5F3yJmBSQTHp5nRTouQWeW5sva34Hof8cO6C/GSIRwoJbQQ86pSprkVM+3yHs2NalC1F9uYEWwqo4dkCnG8bUgZfmR3qxw8ZiwzULH3FNh2+Ww3KJro0LYTyk16coinmvRF0LglhYEMRGQtP3IwF7ppajD6DYdd+kqJElKn8qEixCaiirTD8W8E83DmhF5liyqi+AspdDRgiIlAlIxL2p/JlzY2bKMRVTO/YFs4FBhecQdP9I7GKhMN7CoShYJlMS2AzLZRDQ3CoFFfdrsLizPVoRjX0RoVAD1dpFk3OjWChe9SguKvh2NJykN3K5GkLY8aqvybPL+X/hXS9sOn46291+RkS/97Usr63+L/Ed77v9/SrFYpLW1lfPPP59DDz30CxnjX2ZZJVmxYgV33HEHQRDw1a9+9QuXt0Fgiy224Morr2Tp0qVsscUWtLe3c/DBB3P44Yd/KeU/8cQTnHzyyV+qYQ+w5TxjTKEUKteHTFWjtULn+w1bo29e9rqQpWrqUcQth7STYPnHj6M6liEqh0XMoDrfj872GJbVQoavHvgrnp+xFVde1snp08128nf/WUHMEeykKjiwcRWzOxrYr89hj9EmebHmK3G+/1iCauFw2WE5Tns4QVXgcMlBfZzyJ+O1qhYO+xUtdj6kj189Vou0BacdVeTOO9JsrUwc+4imDGQq6R1IsFFDD4WcYwy20KAe3dBHU9yEmHR1pNn8n5dA4Jl2V4VeXa+IzvcbJs7AQxf6GfHVH+NICyekBF323h9Q7UuQw8aAb84XycoIVQRg26/8kJ2SLSwKXE7w6rjd6WNfXYMIw3Jffr+FCgVHfXUlyYt/AW7eMJUqZb4DxJLoXK9h0qwcxsQdfkg+cFk5z7AR64Fu8A2KS/D0/YjKSqit4/s/nccNPzA7EQ9e65J3QGHzoOji4et25bjTXuLmnftZ9oJJ0P+gWMUWqzqZ+uw56P5ORF2zobgfMOEysqYRnetDda9EDh/DuB1+SFU+TcbLsvjVW0xdQ13JqgbD0Bsys/54lys5IvRnzrB6eOJnmzPr8nY2xWJiYyddmRTvbn06AJPnXQde2XtbYvrFzXPCrpcDcNOZ1cy6Pst5+/QSP+9qg/gCoAJUj0m+lrUjwXI4aIdzeGDGeP55UTtNjRmaHr02GrPRPTqXQaoakaoh+NPtfHydKaPg2uQDmwrHZXKoFyzb9E2JwTmehniau3b9DcMyCbZo6KTlqdnokgvSzRt2X63QmU5kdYP5rZAtM7R6RVRPG3rJAuydDkF1t5l+b/sI2TIpmqe6mEVUN0TtfXnbSxi9Wa8Z18BP3q9n52ItgQVHHtBN0JHn6edHkg1dvBOLBbLa5mtPfxe1ehGyeRMzhhvHR2WqzlZk86ao5QuQY6eg3n0R0lWGNRWwxm1dni8VdeDmzffqhvIzI/xNZ3vRuT5kw0aozmXImrLvN7omDJv99g4z2NetpTdci9zlfcxoXUfKhjsv2BjGbYocPgbV9hGidkQ49nsQ1Q1mbBaziFS1eRYVsxFDrYglzb3S1aje1ehMJyKRRjZtHM0fXcwi0nWGYRrAshl/0dkRS+1jf2pgm9ounhuoZ5d4jsCTvL6mAVtr6jHOg0ALxp67Odvu9V0zZqU0Y6wQ5tdU1IITx7v5Ep75rSCuFTkh2e+Vc8oMy0KiiznU8gWIYaPMGHbinLnDxVx2ajhWcnns435idG3HzVxNVUfss51HncNflhvAhiOfOgLy/WbMFnKQNs8DWT+K56ZfyeRx7fhFycpV1RHef2k36HErwYzTHXRvP6/8zmHq74/j3yGDw4g2yH9dNhj3/yK55557OOGEE5g6dSp33nnn/5iySjJ16lTq6+u58847h+C1b5AvJscee2z0vaGhgbPPPvtLK7tEf/1ly2CjCTePTlaaF1EhC/E02g2JXnwXW1pYQiKFQLt5sOPGoA1fXLqYRWd7oUJC4BsDuFDAAXQY32MLSQwZPXwCNO7gtEZfkRAWMQQoHTF4ai8gHhrMDsIkFvrKoHEAWBYVAcRLuwiexBEKT0kTT7yel4XyJVpjvGhaoYs5YyCHRmXpfxFLov0iCIkjLaOHEg27mzfnu3l0MQuei6Z/iHEfkzYWAluYdsaFBG1yBwDWoCkKYbIS3TzayyNCo1CHhpIIfChmo74QQhCTtrlnqHv8cOfCD9BBgPB9bCS6WN7RKLGrJqQFuSwpYaEKAU7oUXYKGtVXBLdg9sYD34yF0gLOd6M6oRS2HNx3od7cvFkQ+K7Rj1JoZbDJS7G8CWmgCR0ECa3RyiSTlkJ58Iplo1cFEPgIy0a5efxSwIMd3lsKc5+SzrUyxgxAVVgPAKXL+DalRVOpLZZjoFwDP+xTLyL+MTsz4Rgqna+VMezDcrQdQxSzETKMtLQx3ku/ey7EkkaXbiH6TftuBE042AjUgW/q5BXRgRcZv9p3o0WfDnyEkChdDmMQEmxhkosloL0A5Q6NcfC00TVWCLdq2eZCy0Hn+srtc/NmTLl5Mx7igxL2tTLPBq2Mke/m0X4REXjlZ0bgm/oXs0ZvgVeeW6Vz1mqLE86NKIFb2jhIYljoXM6Eqli2qU/07CqYOvjuoHFXgGK2vLginEtuwbQnP2D6ZNigMavC50Bp0Rb4CCnQfrkM21ZmDgUm/r4ozIgqhGR/GoHO5cCyEaXxC6bvSx0UGHbpgkhQrYMo9HEdUQphx42OvSJFVBlCVIqorgJC/Q4a64Bcu1xpoXUQhfto3zXPHUyM++BdFc8rM2OTL4LnExArP4P+xbIhLOeLyQbj/l8kxx13HMcdd9z/uLJK0tnZ+aWWt0E2yAbZIBtkg2yQDbJB/v/LJ+V5bJD/YbJ06VKEEEPw4jfI/y5ZvXo13/jGN0in0xFvwPqOATz77LNsuummEcLT9ddfzwEHHPDvqaga5DJZy32iQqjPzyIRK4lEDC3vv1kXYW6+zs9a6yEPscG10sp4WzUCEdLTC6FRCMOFubZbSwVD7jn0PoYsiMA37Q8ZISWfogetoo9Y67zS/yr8CAY9jEv3GqyD0v+DvkvW6getym2IoHrCNio9RH+DWy4QZZzFIW0OwvsF5vtgKdVDK6OHtcdE6f4qWEefOkxw/SSRQkdxw5GUPLTyE15ZcpDHfm39rX0qZpdAa1Xu11JdB5cxSIbUVg26hxqkl0HXSDTrZLN9kitSBes/vta1UX0/raxBP5XARoQQCGlGnK3NxxKD5o1aq0whyzsgIZHT4F2odeo9+Pq167X2OI4qF+pOBUP6q9S+T2xdqT5qPX1cGv/hb9GYHTRWo3qXjkm5rl6jOgXhIb3ObQYfkSG3hww/Al32rg/W09r1xPSRJbTxsg6u15B6lOsmw93M8mc9bQz1OmSOaTVUP2vNE4Mu9Qkq16Ui/r3pmVqJL+3zf1E2GPdfQHbZZRdOP/306P+SAV76xGIxJkyYwCWXXPK5ia/+FXLppZdiWRaXX375l1ru7373O4QQ68XNv//++xFC/Lfw8v/dsnr1an70ox8xbtw44vE4LS0t7L///vz1r3/9Uu9z7bXXsmrVKt566y0+/PDDTzwGcPbZZzNz5kxkaLScdNJJvPbaa0O4AJYuXcoJJ5zARhttRDKZZPz48Vx44YXrkIB9bgm35YFoq17YsfLLPnzB+yrAC7fQoxAFaYG0EMJCWCEjpZCGrj7EjI4sWczLcfCrWaAR0nywJT7KEObYFh7KkGM5VlSECssQjiF1CgDteeQkuL6F6xsIx4K2SFq+gXR0TBxpXCjiQkUwekKYZE0sx7Q3kTZ6KP1vx0wMbiyJiCVxAx9P+bjhBztuwkdkqD8nZo6VPrEkmrIxJbUmWAsfPSjpwxbmfnbchB6E36P/HVMelk2gFb4KEJZtPqV6hH0mpDDsmGD+WlaI229EhcddrRAxQRBIgkDiC4GISRO7G0uGegjLdkw9RCyJSKTBsiM9BEpFbY7qW9JH6TsmgdqSikAriDloiNCWrLWNehWUw3O0MuFf0sJGYiMNOyeA60e6Lv81fUeon9JC00Nix8t6M21yyiFAod4BbDvAtgN8Vcb5J5ZEOMlB+rHDuRLqJmyPtLSZI4PHUmhQRqy1g+9bmnehASss24SxSCuai6VP1C/hvaUAYZc/FgJHg6VBBwrtm7CvvIS8BFdbeAgTpuLETJiXHS/HfJeeBwCJVDi/w2dAeE8sB+GU60IsaeLbw7aaeiZASlN2Il2eK6UxVOonJx5dIzGcDTL8lN6dGm30UgpvSaTK+oolymXHEggnnEPhWBz8PRrH4bgs6zWcO5YTlSUsGxm3EbZE2BKJNv0aPjdEiDT0icszrxiFN+nwE+nOtkgpTb+2yUirPLfDT1k3g+oECNtC2GY+mzo65TaV6m8Z+F4lzAJC2HGIp025ibQZv04S4cSQOoQ1dQxCUGkGlhbhvtBgWwhbmmRc698T8KH1l/f5vygbwnL+BfLMM88wefJkisUiL774IieeeCJNTU2ccMIJ/1/qM3fuXM4++2zmzJnzubHkP6+k02na29v55z//OQR7f86cOYwePfpLvdeXKZ7n4TgOS5cuZccdd6SmpoYrr7ySKVOm4HkeTz75JD/4wQ94//33v7R7Llq0iK233npIQuz6jr300kt89NFHHHLIIdGxeDzOEUccwa9//esoAfr9999HKcVNN93EhAkTWLBgASeddBLZbHa9vAufJbqYQ+d6ERW16EIWnetDJ9JRjKV28zjSImnHSNgxEyNbSoQbMBj2OteL7lljYloLOWpkAt3Th4NAJIyxUCdipLCIa4NoU/J6lYxtnfdIUmHi7LNFUqSII1F5j0RoYsVC1AeVdYmVHt5KGyKdEM1DSPPiFUITKEk86ZHvq6Q2ZmJ98/kYFU4BIYy3mMAzscGBD8nKUCfmfx3ETfyuXyRpx4hJu+ypLi1wIHqZ64HuKNESoEIalKFqYYzGehEnpSAeesPiCJIaVC4w8diFDKgkQjrmO5iXvpsH30dLiSMdhBDlfIcwZwLLRmcGjPdQaWqx0T0mjjqpKiKiruEyge7qoErYaL/8BpRao3K+abubN3rx8uXk1sBH5zMmOTFVQ9yKEZcOeVksx9yH8b9ohe4OWYUTaaqwsKU5Z5iVgswACR2ShBUkuhQLThhzXvLY+y4iWWkSM7tXUhtmIuuePmp1nKAvvHfJEzn42sBH9XeSFCb/Iy4Ubs4ekicihDFedTFrEl2LWYJlq4nFQ2SbjEW1UzRJhm7e9EkYDx/NH78Ife1UKG2IxgKBDvzoPvhFRCJt5la2G1HdUI6xrx4e1UX3h3PJLSAqh5lzAt/kf4AxwAPfGIuBhxAWtlCI8G0ubEhhkQzrUdqxMWRTZswWMLHisqaRoHMFoqYR3bO6fD8w8eJCghc6C4pFiLvlXZLAM20LfGNcF8z8EH4xygMh8EFUmvFTyA4aH2455yHw0ZlOSgD4FtIQsoVDstJKUCPjVA4yV0S62tQrNHjLsff5KF5ee3nI9qHDPAFh2ehCv1lGunnIZkI9FiLdo5XJIQrnr7ZstBdEnnhHG0z9qkDh+9Kgy4TQNsWITVmYnJcwDwDLQXuuWQyX6pjtAyGp0AFFDDmeybVxy3XN95v8ACFN3oKbpx4b1dFt7pNzjc7zGdMX2V5jeIe6EBJ8wrwL1+gCJ2buHRroui+gSnhku2P4voHFLO2aldCtklqg8wV0wQMS5vp/g/xf9bh/WbLBc//flOOOO46///3vzJ49e50whfr6ehobGxkzZgxHHnkkO+ywA2+88Ub0u1IqIk2Kx+NMnTo1Iq4qyauvvsq0adNIJBJss802vPnmm9FvWmsmTJiwjgG3YMECpJQsWrQoOvb3v/+dfD7PxRdfTDabXYfZVinFFVdcwYQJE4jH44wePXoI5v+KFSv4zne+Q11dHel0mm222SbCVgewbZsjjjiCOXPmDLnmueeeWwf+cdGiRRx44IGMGDGCiooKtt1223UItVatWsW+++5LMplko4024ve//z1jx479RDKskpxzzjlsvPHGpFIpxo0bx/nnn4/nlb1QF110EVOnTmXOnDmRh15rzfe//32EELz66qscfPDBbLzxxkyePJmf/vSnQ1iHly9fzoEHHkhFRQVVVVUceuihrFmzZkgdHnvsMbbeemsSiQTjxo1j1qxZ+L550I4dO5Y//vGP3HHHHQghOO6449Z7DODee+9ljz32WIdt9oADDuDhhx8mnzcvxb322ou5c+eyxx57MG7cOA444ADOPPNMHnzwwU/V1TriFcErGu+VdCJPqbDjxkga5KEMwu1rS1jGcOtrNy/Kkpc0lkRUD0dU1CIqahlQLiKVJECjXYV2Fb3aozskQFeBwMYYdNIyXjGkIMAY6sKS+GizAyAFHhoPTYBhkhQySo9EJOPUBAbPOxXzKPQ7VEmDDZ+scOnrTVIXL9DjJuhxE1RWG8Pe2D8iSkTTpQRZb5ChGhpSFLKIkFLeEhaWsMwLuZCNUGG0m0ckqxDxdPTJKw8N9Gtzj4z2yAvDSJqTAgvjvRe2MMy3lmMM+/A7lhOy1JRDJ6QQxqsZ7poYL680OyiVKUgmEOkK+vARFSlERQpfQFEIXAE9qoioqsFFgTKJgratTGiBLaMwJAJ/6PeSdzfww+Q8gSUkVpgoWD7fM590NaSrEYlKsijyvk3et+lVRXAMe21WGoKqgBDuMsTqFpZtvMMqQGd7EekaRHUD3dqjW3uImkr6hMKqTxpD2nfDpEovCj3QvouIp3F1ALEYvg5DsgbtNkVix6LFlNUygv7+OP39caqdIjnfMfUa0j5/6Keilv7QEAy8cGer5F0uzbWShzbwooRW7RaMMe8kDdKSNiEXuq89SpSMwliUMmMyHFsk0rhKEuQgyIHXCwMEZCxBhy0RjoWICVJKR59a6VKjfVTvaijk0L2rDbpMX3tZbyXDPTJSQz2Vwl5815zn5aPvkYFaOsfNlxNnPTeaK5EOw3OG7EihKEjICfPJa4+McunVXoQ8o/rao4RZ8wm/Dw6/CXyw7fIOWuCH7FnSJE7HEuYzKHyOMHFZJKsQiUpEPI0qBGjXfDwBhZxDnyWj8LHSIqpCBAZnn6Cc6B3uykSLutJzIpFGF13aLZsa6VGjfaMb3yxSo6R1pdD9nUa/lkOGAJFKmk/CoZTULUQ4joU09U5U4hcNaIGtMca/DqIFdxQuGE+T0Q7xtE885HQQmOFXap/C7BZgW2YB82/y3G+QLyYbeum/KbNnz+bDDz9k88035+KLLwYgm103i/z111/njTfeGIKiMnv2bK655hpuuukmpk2bxpw5czjggAN49913mThxItlslv3224+vf/3r3HXXXSxZsoQf//jH0fVCCI4//njmzp3LmWeeGR2fM2cOO+20E+PHj4+O3XbbbRx++OE4jsPhhx/Obbfdxs477xz9PmPGDG655RauvfZavvrVr7Jq1arIWz0wMMDXvvY1mpubefTRR2lsbOSNN96I4sBLcsIJJ7Dzzjsze/ZsUqkUv/vd79hrr73WgewcGBhgn3324ZJLLiGRSHD77bez//7788EHH0Re/mOOOYbOzk6ee+45HMfhpz/9Ke3t7Z/ZH5WVlfzud79j5MiRzJ8/n5NOOonKysohaDUff/wx999/P3/84x+xLIvu7m6eeOIJfvGLX5BOp9cpsxQDr7XmoIMOIp1O8/e//x3f9/n+97/PYYcdFpFLPfnkkxx11FH86le/YqeddmLRokWcfPLJAFx44YW89tprHHPMMVRVVTF79mySySSu665zDOD5559fL3zmNttsg+d5vPrqq3zta19brx76+vrWy2b7aaJDr7tIVhqvb3+X8Vw7MYM4EoYoAKScOFJIE6ftFVHL30WMGItIGV2JeBoq6kw5A92scfsQjSMoiqW4ncYMX+L1EBc2W1lJ/KJFtZYmMj4M7hTJGP3aJyEsRCpGloAUFjLpkNVmsZQQkkBYiHScnNAkQq9ZQmvSFcaA7u5JUVeZ5+3+WrYY4fP2ijRbj1vN68uNV36r8R4Dyy28gmVIXbJ95sXv5iOdIKUx3AtZ06ZsH1KYWPsS8g3FLDpjdCaEBcUsomGjsoIDj14/i4rBKr+fnKyhze+n3zJedIC0ggEJIhaGPpRiadeOdbZstJdFaIUtLFwhyudYTui9DhANDZCugNoGlgSvIcdMASAj25BAn4RFbie0jKdLvYWwBa5r2qMAWRlS2Of7TTiFkGWPXSxpjINCDvL9SCGIS4cKO1n22II5344jB+liqcqS0QZze3mxCyo2pZcM7baDdBS2UBEuPG4eVfLuSgvdvdLAHQ4fw8og9C6PnEwHC5FNw8xYHfRs0sXw2nwGOXyMWWhWVeHTaxhNB+u2FMstJbq/B5mqQWyzPUuLzwGwzZjV/HN5E1vVZtDFgTA8KPRqh4a7AKxxm7DM1tSGjK8621dGSQn8aG4JO27GWKRb440ViUpIVUIui3YLqBULEXVNxgAv9JfHRCGLGDbGeHgDnxwWhT7zOle+pEsVWGzHyKMQlUlk0acWj35lzhnZlCGfddCt70N/H2rZu5DNoAIfUVVv7tO1Gl1Za3aS+juNxTcYoaY0XwpZkGE4n1sw/VBazBSzZvGtzYJElOZKIm0cCQD5fkTdyAhFJtCaLqnJCNOX3a4hLEsIB6wW6OkwhrDnortWRffVmS4Dy1tamEfhQ4PMnBLqkG2b8J1Ysrz7ooLIoy6bNy2PI1cRrslZbQs6e9N8nFDsVlvAK9hU5wMEmrq0GW8lgijd31keY24Btdo43UTDaKymiQSr+/jISTItnieXdyDfH+UJCBHubBRz6DXLwIkjaxpp03nkaENYqDP9xuFQej4nUmaHa/gY032r0jR6Ab4Q0S6AtswiVOfMWJJNG7M4ZrHjOEUw4JPoNFwnXmBFeSYFoREVaUS+iA0mDOjfIBs8919MNpBYfQHZZZddmDp1auRVXrp0aRT/LKXEdV08z+Pkk08ewjza3NzMD37wA84999zo2PTp09l222254YYbuPnmm5kxYwatra2kUgZ7+re//S2nnnoqb775JlOnTmXVqlW0tLTw0ksvMX36dDzPo7m5mauuuipaSGQyGZqamnjppZfYcssteeutt9hxxx1ZtWoVVVVV9Pf3M3z4cK6//npOPPHEddp38803c+aZZ7J06dL1Goy/+93vOP300+nt7WXatGn85Cc/4eijj2bixIn88pe/ZPHixVx33XUsXbr0E3U4efJkTj31VH74wx/y/vvvM2nSJF577TW22WYbwBjkEydO5Nprrx2S3/BZctVVV3Hffffx+uuvA8Zzf+mll7Jy5UqGDzdb4K+++ipf+cpXePDBB/nmN7/5iWU9/fTT7L333ixZsoSWlhYA3nvvPSZPnsyrr77Ktttuy84778zee+/NjBkzouvuuusuzj77bNraTFjCQQcdRE1NDb/73e+ic9Z3rKamhl//+tccffTR69Slrq6Oa6+9dshisSSLFi1iq6224pprrllvf4LhTCgWi0OO/XiLY7GEVWYDRURQgxblMIkEkquOkWjPA8/n1D9YjBBxCihyYdSppxU+iiKKFDa3XDqZc2Z+yIWTVzPv9SYAdrpxCngemRv/xryFjUybuIbigM3y1TUALLTjHL53O8WlRe57v4Wjv76KwrKAxz8exaEHGSPIXZZlzXsVvFCs5eBprQysdLiqu57dCxbLYuaFesLhOc66z+aaU9Oc+JtebjkpzfdvzXPjD2sBOPHXXRxcTDICF0sqHorFcRBUaEmPCGEhw//7hcLRghSCU/fuRAcKNWA8XVf9s4mWQLLEMlCPaS35UOTxw0drQljMPncU/rz3cLbbksKfXyWx1zb4894l6DFezeIqjVbwwkfNPBv3qMIii0KhqQhhQnNhTzRomy4R8Itv5cCyOO0P5vcKLGJIPDRxBAUUAwTccP5YTvv5MgAuHtVJod8mPcyl8pjtOemCD7n+q7289sxwakKSr2Tc4/18Ne/FoE4JVluKmBbUhi/bNeH/w5SgzVKcvVsHbptLbFScXz9l5lYAVGtBh1R8pE04iQRu+8kIeu83uSU1x0zhtl90cdR2K1A5zUvzRkbMswBXaScahzaSWuHQrT1WBv089ZZ5nla17Er3TUdw9Pnvsokwi4aSSZAMQ1CKApZR4MYzRnDkVa2cG9hUpIpc6SXDcW2ZnRgELopGYnTgsTwY4IGTzHPvrDkel+7YydwXRlIQkAjhRCVQCG8Y0/BPkeH2YxJ8eLuZY7fJBCVqIgdJP77ZldLaQJACNoJCNH/MuZuTYrlwo76PYXatSpLWkg/J42GgYK/dqIdsV7gg04KRP9nCnBiPc9Z5H1OJRXMgqQnXTfNjAVVa0ikCprsWr8UCtnZt3owF0VzeLIix2PLZ1rV4M6ZQgBXWF4j+T2tJrwiII6nQgi5h5gFAhZZ0i4BKHf4mFaMCSatVZl+t0JIloogC4kiuONFB9+cQcdMeufF4SCQhCLj4nA+YWhS0OoIxnma5Y0oZ5Wk6bMGHlkedtukWPkUUldgUKCXpmhC1HkIHAdLk7YT1SCGpUZIOGbBU55FhG89RZRjdTY+2CNp6sccMZ+5cm7SCytBznwt3bJJK83FM8oEs0qkKxISFqwNapHmX51G0qzw/LKb56r3fYPZxz1EbwHK7rBMNOFpQrQVxDa2Wohefq493uCLcJE9pQacI6MbDCqED6nFYHM63Oft7PPnHWlIqYGHcJqbBFwZ+dyC80XuywOx9sjz5UB0pFdAUz5t8JSuISM/GTe7itx+OYpQv2JwsNzoWc5Y+wL9almz5jS+trI3efvpLK+t/i2zw3P8L5L777mPSpEl4nsf8+fM57bTTqK2t5fLLLyeTydDW1saOO+445Jodd9yRt99+G4CFCxey5ZZbRoY9MCSeHaCpqYl9992XOXPmMH36dB5//HEKhcKQOO3f//73jBs3ji233BIw2Pbjxo3j3nvv5eSTT2bhwoUUi0V222239bbjrbfeYtq0aZ/LE1zaSRg9enTkob/++uuHnJPNZpk1axaPP/44bW1t+L5PPp9n+fLlAHzwwQfYts1WW20VXTNhwgRqa2uj/7/3ve9x1113Rf8PDBhj4IEHHuC6667j448/ZmBgAN/3qaqqGnL/MWPGRIY9lBO1Pgv5ZeHChbS0tESGPcBmm21GTU0NCxcuZNttt2XevHm89tprQ0KagiCgUCiQy+WG9OVnST6fXyckpyTJZJJcLrfO8ba2Nvbaay8OOeSQTzTsAS677DJmzZo15NiMXacwc7ctywgPQQCWhZAS7ZfjTcnl+ekdAQ42Fg43/agC1daOSCeM1wgQMRscx3zyBfb/2as8ctIwbr61hf3rDa/9fqc9hxCCw/UovlbfwZNLmqkJFOOTxpv0rQnt/PqpUQwLBIdv2cpNz7XQ4MN+G7dyzWOjABim6tjcLfKtKa088GYLw33F5UfnWfOXHF9tNgbztfeO4sp9uznvRsktR9lceGvADYfDmdebsItbvpug89F2+rqTuL7F+d/Kol0fnfeQ1cbwK/0vKhPg+qisy+VPjDBstOEL/2cH9uEt6yc2vtqcX/SxJzRHYQy66HLYJR+xrRjGa395j731KP7yyvtsLeqoDMuoUSb5cY+NVrLPHo3oTBZRkYISZjYm7AhAdXQhatNcdE8aD82vTwnjjgdy6Hwe4g66P49IxhHVaY65+CN+d6xpz0O3NlOpFN2dkofPX8A9pzUy+9cpvlXbRabfjLnObJLtx61ijykOqtfFGp40WOkZY/xb9UnwFUFPEWt4kmsea6BWCzoWKs7ew/QxUqAyLlZ9EmtimHujNT+4rpN9iyMBuO+ypdyyQ4Y7XxqFA3xjWAcd3WncEC/8pjOry+ENfoDu6UPU1CBGTqaqZVcAMq1/Y+rkw3lt1nYE75XDEQF0NuQHSDpYYxo54eo27j53HPMuWonbn+L6H4e7dV6J+EqBHUOt7kYOq0Y0bsysy82u4RUH5Lj14ZEcPbmV2Kg4ujAohdIu5V5oTt1uErOu6mLvYowKx+OK4wSR+RgEUJE2IQ6AzhejvAgc0z/CNqEV3ttLsMc3oHoHTOiZ65swDACl0TkXa+MWM8aCgIeuTtMUlBPpz7n4Q2JYFAi449ug+gvkPnApZEwZ+2+pCDI+sfE1ZOf1sv+0arJv9nHgtOpw3EFxfiuxCXVkX+th/22qy/cuYb7LMLY87yFrU+iCh8q6WLUptBsSYWVdrPo0qr+AzvnI2iTesn6cMZXRLovKutjjQ64V1+esW11qSUSL2feCNwjC7w8daJFbkCPeLCm0KhLN4QJulSZWD7FNh6N6upG1FeDY6IEcIhXunCBQvRlkTYXZScjny6FGgM4WUP1FrPo0cszI6PiHv2yLstAvuydOY9DEMivg7I1b8fOSXG+MQElSlUb/viv52sYesamjEXWN4Hpg26gVZpdBVFUg6kfRdt177HP0fTywpYvbJ6nYatDusRTg+gRdBZSriG1Ujair4sxbXa7YzewqqpyPPaoGUVdlxhage/uRYwxx1Y1XZTiwtgPPs9hxhyLaVQhbonIBssqYfs6mLVz7mzhHNa3BK1is6a4kHrL82mFo3KMLWzht11UU23yWLKzn+lMr2SD/82WDcf8vkJaWFiZMMFtnkyZNYvHixZx//vlcdNFF0TlrG5Q6hBgsff88cuKJJ3L00Udz7bXXMnfuXA477LAhRuScOXN49913se1yNyuluO222zj55JOjMJBPks/6fbAceeSRnH322Vx00UUcc8wxQ+5ZkrPOOosnn3ySq6++mgkTJpBMJjn44IMjdJdPavfg4xdffPGQUCSAl19+me985zvMmjWLPffck+rqau69916uueaaIeetHXozceJEhBAsXLiQgw466BPbNrhvPum4UopZs2bxrW99a53zPslQ/yQZNmwYPT096/2tu7t7yAIFjGG/6667sv3223PzzTd/atkzZszgpz/96ZBjV25+MlctCigOSqDKCtMncaQhTgGS2uGqvTrBV2ilmXW9YFRQRUZqMiIkOMLDwxijDoJHfziSmTfmuXD7NfzjOfMCf/QUDTGbgb+2Mu+9JnZtXo1XsGjrNouxxfMrOWnyCooZm7/Pa+bYTVdQyNi8unAkP5y2AgC3T7JmRRX/mN/M3qNWkcvEuem+OiYX4/R1mRf2iePbeOCRZs6d0sqcO1qYMbWV2+5u4dLtVwLw67nNbFUYRoX0iFkBv/5jVWi0Q35Qdye1if0tJfmdtXMbQgqT/Arc8MgoaoMa+t4y58c1rHy6EF1vIbj3xGrct1fijKul78U2jt19GMV3VhBGGZHvtJCW5u9LR/LBXIhTRTFE2HEwL1MvhNxL6mHkheb8nVeDLbjkpgYAUjqGTdx4+3WSnIAimjn7uvzyduPV/m5LGwM9CWoacxzylVpmXZ/lnK3a+OdLIxnhmLCC+lSBl5Y2sWylIKHLnulEOA1L/6dCvfz4KysIBjRWSnDLk6OidsfDa9tkLzrUw3W79tH5mlmQ77VHnLvvb+bQCaZP31zYSEMsHxkVs64fGuZYq+P0iQIdLKT7JpPPM3Xy4bz17j2M3/hAvl+5ZeSJ1ZQTMosCOkWem/cu8LPLV3Puxp2880Ejl9zkhf1jxODhaKpVHX1S08tqLthkNQB3PtTCkRu38te3RrHiXRG9OAejqSoBS1/o5LzJq+hclKK9N801t1tR6JWtLRQ++XBuJbXEE8ZbGwsHQmnejfObWPmCZnhQTVaasZcTpcRYiGtB2xP9UXt/3NhJV0fIxCrgd4cIVM8AIh3nlgdqSOoqmr2AePgsXdlhPLndr0OFqmTgY0jpKnIfQ0/YqBa/hdVvQKOfZvUSUwcoe7pdQTRfcuv5Tvh/UYDUlSS0CT2rDWrofqt8TlpB299MnztYXLpjO35ngFVhzoht0YQuugjH4fa5NklVh/uxGV/FxeWxVvwY1ryuSVBPMczLcahgEP4PCWoooLGwcIgN2Q2JkyIezv120Rvpdr9CAicMETp905UUMxapkQHP/bMZC6g1uENkemrC8aRZ2WWz5DWfAp1YmLk7Upn3aa/06KWNwwqVPHaUxwP3jCCpNItbyw8dhSauBZXK9Hf7G5oBobh8127ueqoxanObpSkIb5C+K2gXZnfzzBEdLFpehyU0T/2tDqnNGHU0eOEFbX8rcNambbz4djMJrRiZzJJ3HQOVGo63r9et4cFnm6gOFKPtHD+/schl5/Avlw1hOV9MNhj3X0BisRhB8NkYxZZl4fs+rutSVVXFyJEjefHFF4fEvpfCa8B4he+8807y+XxkYA9O7izJPvvsQzqd5sYbb+Qvf/nLkGTZ+fPn8/rrr/Pcc88N8bz39vay8847s2DBAiZOnEgymeSvf/3rer29U6ZM4dZbb6W7u/szvfd1dXUccMAB3H///fz2t79d7zkvvPACxx13XBQCMzAwMCRkZ9NNN8X3fd5880223nprwITl9Pb2Ruc0NDTQ0NAwpNx//OMfjBkzhpkzZ0bHli1b9qn1LdV5zz335IYbbuC0005bx/jv7e2lpqaGzTbbjOXLl9Pa2jokLKevry+CAd1qq6344IMPokXdF5Fp06bx3nvvrXN80aJFFAoFpk2bFh1buXIlu+66K1tvvTVz586NoDM/SeLxOPF4fMixs7/RBYCIG2QI7Stk0kEHCnyFiIfICkWf2U804IQwe+ft14W3ModVZSOrwzJ9hUjFwLLQ+SJn3hhw2a7d3PNMM3s1mQTkc++oB3y2dVvYqXk1C1YOJ4ZiVJXx3I9OezzygfHGbzNqDX/+aBQNfsDmjZ3cv8Dof7ivGamLTBvZzisrG6lTPsd/dQU9H8ZIh4yTf/i4hSN3WMFvX23hB3u189unWjhl11X86jnjlfvxHu20/d1mIBdDCs2pO6wEBX6vwq4p69HvVdh1Eu1qggHNzS+2YGlIh3bBKdutwOvWODUCYQu8bkViYira8dBFn/Pm1DFKjaJ9XsAkL817dwY0K1MOwBgvoCAkOzStYZ8tQecCE38vTcwvEJUXZAKsKosbnx+JBGbsZbzlpTAhlEYVFFaVjYhZXPrnYfxsF2OkPvVUE426yMvZOhYsD7hgz27u+VMLezSuoafbOAYy+TjbNraz+0QPt1Pj1JhE31LOhFNjbuN2CWL1mjteaaE2gIyE46a2mqrGBF6vxq4CZ0xVxPJ5zSMjmFo05dz8oOb0sSt59ONRpBTs0LiGFWuqqYwbA/e8fXpNm6U0Xsy+IlZ9Etk0jKPPfxeA12Ztx/iND2TRh48wcOrxCFtE8TLBgIrqYjeluPaxen7xzQyP3j+K7YZ3sF24eardIKqfsCVeu4vTEMNqrueG2814O3mHlfzxHy3st2krdgWocO2mFchBb9HEFjVc/4cWdiwWqIh5/PjrvSY5GeNplQkLkXQMAouvwJbogh9dLyvj4CuKS/LERsXwO11kQuJnFHZdKaFVEwwoYuOrELZE+4qn722gTpv+VwgueECSIk0Bzcxw8VXstXBzpoytRroEBXCqwO0RxGo1Xp/AqdZYoVe3sMIn3ijJt0KyBVROmVzVcDhaVbI8P2ok2tf4vRpnmIzO8XsVVpVA+xqvRxAfIXA7FbGGoefExiaivrjx2ZGkFdGiaPk8HzA7DjM2bkV5Aiuu8bISJ20K8fMSO6mINdoEAz4yZSFiEl0IIv1jC9SA6QPA7EAoop0XXVBmkVolcFrKu77v3y8NgzVw7/stpDT0rILDN2rDL0qKeRsVSEbGjC3g+5JtxuSIjYohq5PonIuoTOIvXxPVwx5Vw8K7NKc94HDNdivwejV7DtKJmfcaP2PC9WINElkV44YnGjllKzPHghw4wySywokQkdSAjx3W/Z57m/haXSeBLzlibEcJjAjlCWS4UkuMTzLnzy18q2UVXsGio6sCxzLtcMOwnLfXDGe/LVoZaI/R1ZVmxm4d/Dvk07gwNshnywbj/gvI2LFjeeWVV1i6dCkVFRVRomlXVxerV6/G933mz5/P7Nmz2XXXXaMwkbPOOosLL7yQ8ePHM3XqVObOnctbb73F3XffDcARRxzBzJkzOeGEEzjvvPNYunTpeqENLcviuOOOY8aMGUyYMGFI6M5tt93G9OnThywgSrL99ttz2223ce2113LOOedw9tlnE4vF2HHHHeno6ODdd9/lhBNO4PDDD+fSSy/loIMO4rLLLqOpqYk333yTkSNHrhMmBCYG/ze/+Q319fXr1deECRN48MEH2X///RFCcP755w9Jzt10003ZfffdOfnkk7nxxhtxHIczzjiDZDL5qaEzEyZMYPny5dx7771su+22/OlPf+Khhx76xPMHy29+8xt22GEHpk+fzsUXX8yUKVPwfZ+nn36aG2+8kYULF7L77rszZcoUjjzySK677rooofZrX/talBtwwQUXsN9++9HS0sIhhxyClJJ33nmH+fPnc8kll3yuupRkzz335Pbbb1/n+AsvvMC4ceOihOm2tjZ22WUXRo8ezdVXX01HR/mh29jY+Lnvl5j1S/MlhHAUlcMMusJAD6JqWBnKr5jl0t+fiCUkFbEEPzrvAWI9qw10ZglOLtttEuycOBSyLHhoDs5Wm9D1bB9VG4VIMW96JLDISvBdixeTgn0KATUjjOe4YpsKXnw4T9q22H3nNM8/mCft2Oz8tTj/fMTsClTEbfYsxJiyc5IPHwKFzbbD4tz/+nC2ajfG0pFfXcFjL43i0NoOFv6pgmM3XsFfnxzJIVVmV2ThnypoGN5PurpIV3ua9OybQ7SbAiKeKuvELUSEMrqQ5cJpxxh0mHAhdcKNT6MznYh0tUHC8IpDKOCFZfPPP53JrrGRLNY5dvWTPGO7bO0l8cNx/XHMwtZQvUlAYsbPy6gqUE74s2x0zsDYiWQV12/3PYqBx+kzzHND5/sj2MLgyfuguhpRWUXh6Q+wx5jdHgV8aCeQGlp1HmeX7Xjuibc5fDtJ9mnzUl/kVzBlO4v4jCtI5fsRFXUQeKRCKEaRqkbn+0llzViZNfVoUk6cYuBxys0Pm7oUswb+L1lpEguVgliS/KO/ptkyY+WdoED1UVNYfHkHU1xBotLHatf4gdFr/Lyry3CJdtygiAQ+5PvZ5Ja5pp3vLeL7lVsycOrxVNw4p5yIHPioLrMjIBvGovP9LHzsYuSwaoYHPolKj8SMK01dQ+x8hESteI9Y3UhEPI1//80c0WjyZf7xXCPTYv18uHA4X3ljFjrbZ5JZ3TyEfS0qatH5fja+6xZWizhfaeghdWk5NFEXsybpOfBQvatNorFSEfRkaY6pjmXY7Suxdz0C1bEckawkWPYO1sSvlM/zi8ZSCy22kfdfwiY7dkc/P/ZaI9vndcgfIQgKmsdWjIx2pMasUeSl5NuPHUwKoqRMYTnoXK/Rv5CIymEkCv2IymGofz4GNfVRCJ49Zbeh8yWE5xTJyijpNkLC8YroYg5ZN5JUptMkEpfEzZuk4zCheeEOF7CPn4hi2O/zVzPOqaVS2FQcPAW5w96Iijp072qTwA8GEjRVg4glDDpSLInOdKK9vMF4BwMSEPgIO4bqakX3rEEkK7EmmGe4yvWZ32MJk7ArJUJINpW/oLTPsPLOgGnjV/PSkpF0tFWglGCersTRMLLPtNkHWn40Hvubp5px4sRQfe04YQK+qB4OWrFZ5XWcemOWP/9zFAUJx9xz4RCyNl3IEix7B9m8KTJVjdaKzJO/IL5tGB6aL+KcdA6qr920t68dUV8OHT1k5Uxu/0czUsPJv73A6FlIk/Qc6l/EU2zz8KXE0gHS1vgdkkALErYf5Rm8koBv7DKG5ECWD+Y4TD72IDbI/3zZAIX5BeTMM8/Esiw222wzhg8fHnlNd999d5qamhg7diwnn3wy++yzD/fdd1903WmnncYZZ5zBGWecwRZbbMETTzzBo48+GmGdV1RU8Nhjj/Hee+8xbdo0Zs6cyRVXXLHeOpxwwgm4rsvxxx8fHXNdl7vuuotvf/vb673m29/+NnfddReu63L++edzxhlncMEFFzBp0iQOO+ywCJ0mFovx1FNP0dDQwD777MMWW2zB5ZdfjjUoTnGwJJPJTzTswRA21dbWssMOO7D//vuz5557DomvB7jjjjsYMWIEO++8M9/85jcj1JtPC2058MAD+clPfsIPf/hDpk6dyksvvcT555//iecPlo022og33niDXXfdlTPOOIPNN9+cb3zjG/z1r3/lxhtvBEwI1cMPP0xtbS0777wzu+++O+PGjRvSp3vuuSePP/44Tz/9NNtuuy3bbbcdv/zlLxkzZsznqsdgOeqoo3jvvff44IMPhhy/5557OOmkk6L/n3rqKT7++GOeffZZRo0aRVNTU/T5L8lgGLgSnKPvlqHjSpCGShmkmNJCqwSrFvjmxRFCSOqSQaaUgUeEISRWYi2+1gBNEMITlhBzTDhKCYVERAl6thDYwvzvrb3gU9owcKKw18dxKTRKlO8TaMNeqIIytrMuQQ6W4AA91/xfgqIchBQRMdSqwMAwegbhItJdCeov8CM9lBhtrbDuttbYWlMUJnxB2LIM4xhizEcwi27BGHWlvgLsEIpTe+ae2i8afO9BbJJiUB+XtuUFJkyGwMdCrnO+9oJBOPHeUCjGUv3CPo4gOUP9RboojZtonHghq65GCG10og30pj0ovCVQkkDJ8viDMppNSa+DREPosQ/KsKCh4R2NRa3wB4Vg2HEV1TXSZ2kslz5SRNxtpUWYhLLhGsIQar8YwRYS+ChhktDtmBqik4jt1xs0PiIdmU/ED1DqMyiPp6jBqgz5OIR5tfyxMOzMEtC+RgdD54oSZQjZEppMhIISItEQ+NHCxSDQeAwe16W2RQvfki5D3USsrxE8ahDNFVGCdR3MvBy2x0IMMUwsIctzLV8IYR9DTozAM4gxJb2U6lcijyrxAbj5SN8RbKfnhlwBfpkXYTCDqwrbsNb7Tkgzb0sSCPPxEOYjJHieqWNI/CWEVUbuKfFfuMaAtrU2O3glIqu1SNVELBmhDxVQiHjMJBs79rrjYPAHEzYmBle8REY2aCwVtUSGJFYlbHsZPh+Dkvc8MDtNqjQ+/g2ydnO+yOf/omzw3H8B2XjjjfnnP/855NjniZeXUnLBBRdwwQUXfOI52223HW+99dZnlr1q1Sps2+aYY46JjsViMTo7Oz+x7J/+9KdD4q5nzpw5JKRlsIwZM4YHHlh/Zvxxxx0XYbOvT04//fQhCDdjx47l2WefHXLOD37wgyH/NzU18ec//zn6f8WKFbS3t39muMuVV17JlVdeuc79S3LRRRcNyXlY+57XX3/9OgnAg2X06NE88sgjn1qHPffckz333PMTf3/44Yc/17Ha2lp++MMf8stf/jJCWVqwYAFvvfUW999/f3TeZ+n/i4rWAWLQkzGicx8s66OlX1uUWq8XQRI6HhnK1g6Epkl5vH+u57PSDAnTDHe5Rci6KGRoCK7Fgirkp8xZKQ30yyA9lBY3alD9ohemMN6+EvxfVJHPEDt8CUcU70qViWYieLz1L6oHNeQz72Pq/QVlEDkXnxEG9qXJWga9WPv72o1azxu9tLAS6M/9wh88VoQYehshJFqtOyek1gSfkaRvTgzHFgzVqfoclVuf3j/j0CeWqhTCdoaMuU+VkvK0MjqQ/8Vxub66r6dDShoszTMB6xjanyile6jAGMH/XVEqTHouORr0pz8v/otSwpFfX4lisN7CMTFkVEVtHGTglxa4pnCUIAr9+8Q6DLq71mbxLddmio7O/feJ2hCW84Vkg3H/v1SKxSKtra2cf/75HHrooetgyv9vlWeffZaBgQG22GILVq1axdlnn83YsWPXG170nywzZ87khhtuIAgCLMuira2NO+64g+rq6i//ZiUDpeRJG0xBD0NevAJD2CZKHmu/CMF6Eq9VUF4MSLlew0JhiKs04IdedPODHmLYly9QQ64V4bkyJJXCloauvsQU6RpPvgoEltAoT4TMoeYVZQnzoo7uO4isSQ9iNzVeXCsicAqUImbZkTeeMBTHEBMNunY99QYIwvr5QkQeQE+YxE5RWuXIMORCfYJRrxRybdr7z7iv0Zvxiq5jkg7y3GsAKYzXMmy/HuwCC7yyhzPclRAh9j+Dvail6z+hLmuLVmGcbcmwKO2grO0lXvs6CCmOB3m8B+2waN8tLzBVyFosP6FOg48pwzJriteG2GdQvfRabSt5qpUwOtZarOPNFoP7aNBvQ+ZcaZciJKsSaxvcgWe835ZtyizZ2m6oN1nSi8BHhwtGQcgPBxjPsyWIxq32iwZ7v0S6Vaof4Tnx9LpGebgrZcZDrFyvtdiBgbJnXBuv+uDxZNrihH0bRAZkENVVRknSlMAXSnOuNAfD3Rdd0lXpWSatcp8OXkCEIUBDjpf6VZeMZEz5nh8hBGkSKF8MeZ5Z2nxKeyG2xuQcldps2cZRUhq6Jax9rVBaGO+6KN+/JFFoXwnLXpllTgmJiKJb3h0p7RIMFl+XE77VWnNx0DNfIVA+KF9Ei9lAyaGGvCw5NPj3Leg3yBeSDcb9/1K55557OOGEE5g6dSp33nnn/+/qfGnieR7nnnsuixcvprKykh122IG7774bx/n3EGf8T5Hq6uohPAh77LHHv+xeqtNAkSKkIVLxwtjMbB+qxPqIiZ+tT1ZiC5ukFUP1tKE7V0B1PipLD/QYwp38ABRyVMg4ui9DSosoCTGFhYNBHNFaUK0lceERhBAOOu+SIGWYa7NFEiRwEOi8RwKD+uIgqFIBOlskpg0OuHYDLMo08KoAca3xfQshNG7OIqFVRNYUswO0EghHmVCQ9iWmgm4eEa8ot8nLmzyCkBK+KV2LFFbZg9+1ImTqLZTPH2ysWQ5VMk5KCyqFjYMmgSSmNfnwpTksMOEyQcZHd7cZnccTZgu8ZJw4MROf3d8DqUoa4jUMBAV0JiR5yxkSHGE56HwhMiCSSHTWxMsnlU3GkjjaxFTrgQGSwjIsnLrk2Q7b3b0Sne83MdTSMjoAdLKyTNyV7aMuXkXSilFUHqrHxKiXQrV0PA3ZPlMvJ05SCxNyAyQtG92bIaEFvjBjwZaKWEhipXraDCESGOOmFDJWzEcwpDpbJKVN8qzqWlEOwwGs0ZubqixfAIFHjYih+3NI4hQHrLLeSoRUAL2d6FgC4ll0bz9uzrwiE6Ehpkr16u8xcdFeMQpnKYV/OGGoVbY3Rn37krI33M2HCxELnek0hpJllxlbMWEmZDPovl5Ux3J0x3KoqjcEU2sGQX16RbQTN4voUn/55b+J0BwOBm03JDXR95hWKCXRnSvDOBPblDPYSCzkTBt7O6IwFnLlug6eLxGxmZsnGOguG6lu3iy0VACFHCrwDeNqrq/cFjePLhF9SYmDcQaUPM4pGSMlDIeD9gPUqo8gWQGZbvMXTPhQqt/kA2iFtuPoge4whr4Ea5s39Yol0T1rovapboOeRSlnJZ4YEhIWdAxExq1FGjdnEwiB1gKlBVWBxgIqQuvd1wKCALVmkWFVduLoTBc6ZCsX9U3mWeIHWFIhA7MgCNo+KOeYWA7k+qGzjSDwEVXDQEiatI1aGSbQ5z2s7pXmmRtLmvlYysPAzIlYqEPdviQi4qOYQ6SMk0gnUqQsn0KfQ+AZ1l2lBX4gsULUqpQWkC+iPR+HGPT38u+QDQm1X0w2GPf/S+VfHZLx/0s+K7Rlg3z5EjGIekW0HUdUDzf055aNrGksv4iLWbry/VhSkrLjyNqRaCdpEkmz5Ze1tmyTSJnvJ6dcREUaV2SRYdpELmScVZj30EC4NW3Hw63nZIwiihgSkYzhonCQiKQTwXI6CDLSRqTjFEJvk5ACT0A8NHesKsGAFMSTHt39SZK1Pv0rLVIp4xFb011JlTYGuSUVVuP4yCMYGQSBjxjkjdaFLF0hU2gUR98wFpU0VPX4RYRSQxJqsWwyqkjB0vRrHwYR68RDj3lPSMYjExJR0xh6bE2cv/byYfvCBa4TRyQqaS/2EmhlEqDBeFdDhliRTEB1FaKyiiKdEUZ+KU/BF1DUClFRQV4HyJQ9NFxJaWR9C7qYNYZAGLsMINI1ZpERTyMqh9FZ7DPGfeAhw4Q+XchC4JlxYMfNgsGJkRc6QuPIax9RU0VRdCHDcIAgNCwAZO1IqPIjHZqcAhfyGYrhe18kHQO1GBPIhrHlMei7xqjHGPk600mvdhHpJAKFk1CIqhB1K56NjFrd34OorEPE04iaShKVpq+zHRbDSvkg9S3oVI1JbHbzESuvrGpAD/SggZyUpGtcM7d0eXEsLDvK45Ajxhtv8+CE2lwfOj+AqK5BDh8dxWnrTFd5nqpyPoQOQ2MAZCpcnEkRwj1qYlojbLNTMSCJ9JaVFkUhEE3jzIHBCbU9BlmJilqTTJ2sRCQq0UIaMqmUMaitho2M5zicLzrwzfiPp8seZa9oDNVw4SPrRqLS1WauDDknNEWkRRGFRTkEZEAVyckklhCGKXXEWETlMHR69RD2bJGsisaJsGPGwC9kTDI2mLaUEtW9Irq9FewYss7gwpuE9KJJNi0lsUsLa2SNQTbCrI0SVR7Oah2Gr0CPbdDDkl7IECwA3/SvzvWZBN5kZTR/RVW9ea7EY0AeX4Q7d00TGSzacwkCD2vsFNMGregUAdZGJqdK5ouIGvNdxCtMeFV1Q7QosetsCjLcVWjYCOHmy6zKMfMwFrEknpKk6j2CosDrkFhC49gBbtHoNic0xGMI1ze7jqkK/h2yAQrzi8kG4/4/VEpsuSVG2w3ynyfnn38+a9asibDtDz74YHbYYYd1cOw/U0ovslgSEm6ENkGyyhgRoaE7+FFrSZNcqrpakU7ceHfBIExU1EUJYWu8DGLYMLKibMAsD/qxkEyU9ViOCtHFBV4+RJOIO+S1jyMEIhkjpwNiQiJiNtnQPSmFwQ0XcYeAMEynMkFSQVXItJpfKWjyfbq60gyrybJmUSUbWVmWdxmv1UaNPViOQitB0bPNAsWy0f1dEHq2sGzjGdMq/K0zCkNJhoaFzveju1qhvsXEIOf6hhiaaEWX18+A08Aqv58BkWK5n2GNnRyy9e2Bgb+0bJPrEE8bA1mHaB92DFTaePekxBKSYuBFyD4lKnohLER9LVRWQ+1wluq3EWMMwtKA1YEnDJb3x143jBpPn34b7Qao8GUagCEl8l2zIxEm4kWebmkZYy3TiYglsYVFpZNCiHzZUFWBQcmRFmKYwb4Xlk2rLjDgGb0tpx1ROZUsHfTYNnZSobUgESsZ9E60SBJaofo7EfE0cvgYlhEuysY00iny2E0pc+9Bib6l3ROd6URUDaNLFRCNYwhYY3I9QgNHB14YvhEYz6+bh3QtctNNWH2LweQfGx+gu5CgJlZEZ3vR2R5jSLpDd63kiLEsiUlaPG3Gs1+MjEsTVuEjEmmoqCv/ZjnmO6EBqhW6YxU68M38qms215ZQq6TZYZMNY6NkaaUFwUCY1OxrunBZ5iQpSJheYWEN+KRUFDrOSF0kq2x0bzvkB6CiBoo5dLLC1A/QXasgWYnuXIFoHA+VVeCUjWmd7y/Pj6RvFkeZLqgoh7yUvMoAOtuDTlaauVLbHIUb6YEeZOO4aK70apd2O0FXuJhqz/XhCElM2IjkKPSqxdDfY5wOJc+9WzCLkeFjTJ/YMdM/8XS0UC95tYUdMzsFNcNMW0uLd6+IzvUipETWNEa6Vt1l1uROO03PqhSLYpKN7QA/kFS7JvylJuT68LSAqspobGitDBJTryGxkok0smYEuuiywk9RgdGXzvcPCQvTbh6KOVTrQsTIicjKetp0EVEbAiZYZryLZJVpb8oQg8k6U/fcEkWiFJHU31lGWBqEliNrG1kh40yuMLlHMWlCfzy/TGLloRGpFHieiVSqHsqz8q+Sz0n3s0E+QYT+vIxJG+QLyy677MLUqVO57rrrgLIBXhLHcRg9ejTHHXccM2fO/Ezm1E+T/65x/+abb3L55Zfz/PPP093dTWNjI1tssQWnnHIK++233xeq0+eRsWPHsmzZMu655x6+853vDPlt8uTJvPfee8ydO/c/ctfivyJr1qxh4sSJvPPOO4wdOxaAd955h1133ZUlS5asw877abLf6H0BE08fF5KCDoZ8L6HWJITFbTPGGNSMQoGDf72aGhE3HthBaCIWkqz2SAiLOy/ejJMu+JDf7DHA7U8YT+kJM+uhUMD954f88R/NfOsrK1j9ToplGVPnhXGbE/ZsRw143PaPZk7cbTU6F3D7P5v57t5mS1rnfLresnikr4GjJ7WChDvfbeGbdWtYtKoOgOHJHG35NJNHd/DUqia+Xr+G19sb2Gmi2YZ/bPEoWkJ20nq7yJW22SFIC5uMLhEcCdLCLCriQpLA4prTwi3tnHl5n3jLAI0iwRpdxEJQIWyWBv1RXK4lBH+8YluCt+ZjbTyO7AOvkTpgCv4bH5BdGN4n3LV44v0WHrYzVAuHnA4IUKSF8fi5Yb9UC4de7XLbD+vAsjjyOuNpjQmLlDA7Io3E6MU3DLYnpfjpLaauPx/fTm9bktpRedIHTOa7V7dx6/4ujz5Yx0banDOifoDneofzvJ2nDocO7WIJQV2INd6hXRwhqCfGGl3kt9+rRK3pRg6v5Ue3mPAfjaYKh27t0q7yYZy/5qGT6lnyO7PLM+6sjbjoik7O3XENAx/D20tH0GAXokS6WXaZCEwiSAobVwcMKJfHzjEJ9idc3cbNexe49i/1LCSLjw6RVaBGGEO0V7t0qQJ/evM3bLrpwcy1x7PYivOIZephD0IySgmLBBbd2iWG5IpmA5v6t6XN7NiwhvdW1fNg0icRUl9JGILC82HQx0P7S5Y9YbEiW8GN8YEokTchLPq0i4WM5paFICYsCmF+io0gISxGiyTvq37SwsFCUCscOnQxuk9S2KwMsmg0FoLLpMOyYhiyphU7H+fiL+9BxCT3/rWJKqXZurqLRNqMt6Ur6khaPtfaMIkUC8mxMSk+JBfVt1HEWa2LjBUJlukCdSJGECLwANF4TwmLXu0Sw6JS2HRrFzssoyIcqylhU4lNly5Gc6UkaWGzUmXD+Sa59+gk7ocdER59bL+dob8PnS9w3jXd1GiLlcJlRDjGAaqw6EexUueoETH6tU+AolI4FMMFX4Eg/M3DRlAlHDx05DBICItKbHq1R4cqL9qO9+sitKS9tm6l/f00TVvlmfdcA45QDK80dc/mzXizLcWjVDJP91HQJofAEpIaYRZ5OXwyqsghejiH7biSj16sIZ1w+bnv4IVPjUBrEsJinEjRR0CbzpNXHg/dexQXHPk4ALXa4l1yFAnQaGJYOEKyOjBz8LqEwLIVtq34ZX8tFoIATQyBG47ZRUGGe75a4PG/N5NShqTKkhrXL+f5bLx9N9e/3kxSC3YXGX6B4A/LPh1c4suQhRP3+dLKmvTRnz/7pP8w2eC5/x8gzzzzDJMnT6ZYLPLiiy9y4okn0tTUxAknnPBvrccjjzzCoYceyu67787tt9/O+PHj6erq4p133uG8885jp512oqam5r9Vtud5nztuvqWlhblz5w4x7l9++WVWr169DtHU/1W57bbb2H777SPDHgzp2NixY7n77rs59dRTP3dZ958VwnUqZdwlay/gSkRtns/Jl7USExILwQMzxqO7egy9e4QWI0zSWyIBRZdvn/8OD/xgBLN/k+KkzQ35ypGX9mELyV5BM/uMXck9r45iU9dlbHUGgOmTs/zyqVGkEJz0lRX86tlmUlrw3WmtXB0yoCa1YHrB49gdWvnDay3ENBz/9VW8+FQDo1PG07Y8V8GU0e0809bEN7dp5c+vtbDHZq088KEJHTl8+xX0vB/D9yWZ/gS/O7kaPA+dLyJKi6MgQGfziHTKxLEXC5zxK2P0x0ID5taTKghaO7Bahptk4GweOXp8GdnD8zjw7FeYYtXykXqfvXULT723jKkMZ2LoNMxJk/C498atHLzvRHShgHAck9haDL3XjoNWCp0ZQFRVc8YNA/ho7j4jDCvI5aO+Clo7kDVpRMzm+7dk+c3Rpi6P3jaKCqXoyQzjLx+2MfdHw7jm13mOHbmKzjXGOHy/o479Jq3gOzsOR/UPIGsqTAxxNgw/qalA54vo/l5kfSXn3lSkmir6cfn1kaWxI1DZLLKmAtHYEu18/PjSFRyeNzsNP7+8lVv2yHHbkyNp9DVb13XR2ZvGCsODHpgxvpzoqxQUChCLIaqqOOLChQDcfe44fnb5an7xzQxy2KBkc6XR/SEufzqJaBzDppsezPvvP8At0y5gc6/I3Wc3Dx3fShsdeh6iqg6dzfP7W80539yylaffHsV2je1ct08VFEOvrNKIEhqLVsiNN+PqX7SzY8GnIZbnntObojZoz0NUVQ6FgNQ6RKkZlDStNf67S7AnjTH1CcdUNCa1gnwRMWpC5I2eN2sVk+sMGV2gJD+7r4oamnDRnL1FK26f5OPFwxjoNvfZZHgPxbzNLd+txZu/EmeLZrx3V+JMbo7qopatQbY04L61nNgWzehsfgislUhXgB+Y+VJTaxI8swVEjZlHQPhbDeTypg01lQQrO7Gah4EfROfI0WPD3ZaAM37Vx0jdHDFmv/zcSySEjYXg7oMl3rIMzkbVeEs6sFvMjqHf2o89Iok1ptHUM5k286U0j8AkuQ5kEekqo9N8wew0xk0ZeiCLzhcQVRWIhjJefPtvy4SCv3u7hQmu4sGXazmsvhPPs+juN+O5MmEWLK5vcfqe7dhbjDPPQa3M/brMQlFUpBBVlWTueoNfv9zMftYAPdkkt/6wDPcsHAc9kMVf0Y5MOiYUJ5XisMPv4fYdzTwMBhSJ7cYg0uHOhB+Y9oY7ZU9f1EGFDvAQXH5kLiJp0zkXUWEWGnKj8cy5vJf9GtbgFi26+1K4IQBBKeb+rldH8eM91qAGfD54oZbbz/43ee43hOV8Idnguf83yXHHHbcOMdGSJUvW613fbbfd2HTTTbnhhhsAUEpxySWXcPPNN9PR0cGkSZO4/PLL2WuvvaJrXn31VU455RQWLlzI5ptvzsyZM/nWt77Fm2++yZZbbsnEiRP53ve+x5lnnhlds2DBAqZMmcJHH31EY2MjY8aMYeedd+bBBx9cbxtKQ+Wzyho/fjxCiIg595lnnuHMM89k1qxZ3HjjjVx99dW0tray0UYbcd5553H00UdH5YwdO5bDDz+ca6+9lo8++ihihD355JNJJBLccccdXHfddZHn/pe//CVz585l8eLF1NXVsf/++3PllVdSUVGOC7zlllu4+OKL6erqYs8992SnnXbi4osvHsJ8u77+6u3tZfr06cyePZtischPfvITZs6cyYwZM7jttttIpVJcfPHFQzgGVq5cyU9/+lOeeuoppJR89atfZfbs2ZER/tprr3Huuefy5ptv4nkeU6dO5dprrx2C9y+E4JZbbuFPf/oTTz75JM3NzVxzzTUccMAB0TlTpkzhlFNOWQdKdNasWfz1r38dwlb8WfLsiEMB8MNEthgq+u4M8koGCEZXZyKEmda+StLSx1USN/RkqvC8GCbcZmJLJ8+uamLPjVay+GPDgdA4rB9pKTzXIpuNRzHWpZhvX0lSMQ8/kLiBRSrm4fpWdBzADyR5z8GSilgYw531HJK2H8G4ZdwYw9J5unNJapMF+gsxko5PPoyNTTo+A665xpKazmKCAIG1Vput0FsZILBRjK7vi5JCAZb1VEeY4l54vouMylHAZk1d9PclSCZdejNJamvydPekGDbMLEQGMgkCJegtxPGQBKH32QCCll9yCqJymysGkJZmeZ8x+krnijDeWqLxkDSmcqzOpaJr/EAipcayFCsylbRU95ucBMePdNvvO1EbBrcLGPK/BFrq+lCBRAWCFQOVUV0tdDQeVHjdyGQ2+t1xAlozVTSGxwaKMRypImztbOCEejXtiAuFrwU+klrbGFKFwGLixp389eNRDA/j0AU60t/g/1MiYIET56Q3L+bgrU7jB8XyM6KkVwdFgMQLx3A8hKJJOiH7qxZ0e4OMsMEwggh8oN5yqUwWWT2QRiMidCQRlu+G+SZOWC+AWIhf5CFxkdRKl6yySUufvLIjPQ7Wbel/CdTaxYhRNG77JGI+2UKMVNwjk48PaQOYuQLgSEV3EKPOcukOYtRIj4KyovZAeQ6U+nAwUowe9FvpPE0ZTWbw+Cm1V6x1joPGG9S2hliegm+TsE1/ptMugSexHMXKnkoKSFIEuFjRmCyVW6qTGHR88Dj4pN8G92epvqX21tvFaDfJ4A5B3PFNKF94ndJiCHxkf+CEu5imlVKU521BW3gIaiwXpQUxyySz9/qxIXNdoEmIAE9LChj0mmFOgZxfdpIV9LpIWiW9poVP2vEQAjqLiXXKLumg1nIpKguBjp6FQPRctqQi6znEpCLu+LQVUuyz5t517vtly4Jx+31pZW2++PEvraz/LbIB0+jfJLNnz2b77bfnpJNOYtWqVaxatYqg5DEaJK+//jpvvPEGX/nKV4Zce80113D11VfzzjvvsOeee3LAAQfw0UcfAZDNZtlvv/3YZJNNmDdvHhdddNEQw1sIwfHHH8/cuXOH3GvOnDnstNNOjB8/nqeeeoquri7OPvvsT2yDEOJzlVWSCy+8kAMPPJD58+dz/PHH89BDD/HjH/+YM844gwULFnDKKafw3e9+l7/97W9DyhoxYsQQltZcLsd99903xIguiZSSX/3qVyxYsIDbb7+dZ599dkgb/vGPf/C9732PH//4x7z11lt84xvf4Be/+MUntnGwPPvss7S1tfH888/zy1/+kosuuoj99tuP2tpaXnnlFb73ve/xve99j9bW1qieu+66KxUVFTz//PO8+OKLVFRUsNdee+GGEG79/f0ce+yxvPDCC7z88stMnDiRffbZh/7+/iH3njVrFoceeijvvPMO++yzD0ceeSTd3d0A9PT0sGDBgogdd7BMnz6dV199lWKxuM5vG2SDbJANskE2yAb5z5cNnvt/o3xSzH0ymURKieu6eJ7HySefHJEXATQ3N/ODH/xgCDTi9OnT2Xbbbbnhhhu4+eabmTFjBq2traRSxkP329/+llNPPTXaFVi1ahUtLS289NJLTJ8+Hc/zaG5u5qqrruLYY4/liiuu4Gc/+xnd3d3U1tYCxsu86667Rve899572W+//T6zLDALgdNPP51rr702un7HHXdk8uTJUQIowKGHHko2m+VPf/oTYDz3p59+OhtttBFnnHEGH330EXfeeSfXXXcdb7zxBjU1NUM892vLH/7wB0499dSIxOs73/kOAwMDPP54eeV+1FFH8fjjj3+m5/65555j8eLFEfPwpptuSkNDQ+QVD4KA6upqbr31Vr7zne8wZ84crrzyShYuXBjFoLuuS01NDQ8//PB64SyDIKC2tpbf//737LfffpHuzjvvPH7+858DZvFWWVnJn//8Z/baay/eeustpk2bxvLly6OdjZK88847bLnllixdunS97LjFYnEdw3/NLgcSD9sYeBJphQyunsRJBPjFMNFVal5dNQJfQFJppo1sx3ctLLvsy1OBwI4biEmtBG+sHs7OW67kgfda+HqF6ZNl3dVoBCttm2l2hkwxTtLysa0QLUdossUYdugpWvs7gC0VrpLUJIvkig75wCJpBfhKRh7KEaP6eWlpE9Ob1vBO23C2aOzk7dXDmTLCxO0vWDOMRqsQeYrHjOsJdSAi+GwhNL4rsUIGRy9v8UxbEwIDXQmwy5i26DxpafyiRbzCjzDShdC8vLiJynCLvM5yyQQxau0irSFHQE0Y99uQzlFVlyfwJEKAtBWBV/bBSMtgr0tLM6/N5DBs1WjaYzkKr2AhZBnL344FrF5dRW21CVFZ2FNHs52j20tgoxjb0MtbHcPYrKqXvgHjkXasgHTapbohT77PwUkEWI6m0G92PJxEgB1XFDIOdjzgudaRVChFUQh2GLU6GituzsZJBAipo3qvbK2JvJ39gcNm4zp4f/FwktKnJlXAD2TkJa2tD+P3lRlTbs5GSNMP2T7jje7uT5HVNuOH95Co9AzzrMlfpDhghfU1x55a1sy4oMg1sTwPvPErVu5+iik/jETTGjzXQgqNkwhQgYgi1OavHsaEyj7WZNKMa+keErlW6h/LUViOYvnSWgIlmbBpJ15eRmMp8MpcDqW5Vfo++C2sAonvS9LVRYpZB8tWuEWLitrioHPMGNBaoBV0rKokETfjvlB0cH2L4fUDuEWbQtFGa0FHMRl5bJ3Qvzuyrp+K2iK53hgVw4pku+NRTnIp2Txd75LvdchnHYQok75V1hVCAmuBFU4Gvyix4yo6xy+Gu3LSfI+lArQCaetIL15eRtdrBWtWVFFZUcAP475LO4RSaCoSLsPH9FPst4mlAgoZ48VO1bt4OQutwC9aSNvUPfBkVBc7pqI5qpXALZq+jqfDJH3bJEHb8cAwEwuj3541KWLxEjqRwLYV2YEY/YU4llS4yhqykyLQDK/Kka4uRvcfPIfteIC0NP3dCWLxgLZOs9s1YUIXdjJE5QmROAfa4ySrvWhO3b10FN9pNnCzbs5CWjq6hwoklq1wkqVxJfi4tR6JZlxLd9TuwfVxEgEfLx5Gy4heAk/Sm0niKxmFxgG4gUU67uIHkgHPYaPmHsa88Qz/apm/0f5fWllbLHnsSyvrf4tsiLn/HyD33XcfkyZNwvM85s+fz2mnnUZtbS2XX345mUyGtrY2dtxxxyHX7Ljjjrz99tsALFy4kC233DIy7AG23377Iec3NTWx7777MmfOHKZPn87jjz9OoVDgkEMO+cR6TZkyJWLJnThxIn6I0/t5y1rbs7xw4UJOPvnkddoxe/bsde697777csopp/D8888zZ86c9XrtAf72t79x6aWX8t5775HJZPB9n0KhQDabJZ1O88EHH/DNb35zyDWlOgMsX76czTbbLPrt3HPPjRZRkydPjgx7MDsKm2++efS/ZVnU19fT3m5QRObNm8fHH39MZWU5NAGgUCiwaJHBqG5vb+eCCy7g2WefZc2aNQRBQC6XY/ny5UOumTJlSvQ9nU5TWVkZ3SefN/G+iUSCtSWZNMZiLpdbr74uu+wyZs2aNeTYzB+dwPk/PtGgSgQe2nMjFIkhhExKceK0o5EIYpZN66N/QLUuQNQ0Gmg7DHSkzrQbpIr+Hi477Bb2OmhL2t/vpn6Cqfc5bzvYQvI1VUl9Q5Z7OtLskZdsVGeM6+Ffszn1MZtKYXPlQR4/fFhTicNl++Q55U/mhZ8WNofkLabuneX6P1UjHPjRUUXm3hFnmyBMoOt3aNRFlrfVsEVjJ91dKTZK9PPBahMetGVLu2EdDQSrV1dRd/tlpp0l3O6SeEWDow3oYpazdj0bW1oRFOaSe25HdSwzsHRSDoHSLMklO/6UXRKjeF9l+K5Xyx3xPvbUNYQImHxsxUgqmDatnfRVV5ahAUMSHHNzZdBHLBssh9O2+x5Zt0D7M0+Z7ulZjXBiBkLvsbmQTCAam5l5+qvcfPxIAOZdW+R1UYEXg4d1O49fsjszT3uJG7ctkH/BGEqLvAr22qcf56SzqXHzBo0j8Mq088lKw4eQ7YZUNefueg5xK0YxcPno3lvKOgz8CPEHDOzez79+FYflTaMvsjt4+qjN+MtVXUz2kuzd3MVHHw6jJmmM2KZHrzWoPFoZCMlC1qDaCMn3vnENANf/OM0lN3lstyMkZlw5hFiqhO4jqhoQsQSP7HQhd5/dzA8u7WXl7qfQ/IxxoGg3b1COAh/VvgRZPwqcON6tlzL/t2bMjk9nWJapojmVZcR9v0APdBvYyEFoOSJZCZbDo7v9lialGLY6yUZ/nmWgF2HI3CrdEydujg+YsU8sCYUs6p3nsXb5jplfw8agM+1lyNNwTIqKWkormY+nX8bIcSEcrdD8bMkwtu1twBPw3W+swWt3WfR6BQNhzPxksmR9m5bfHAxugbpUNbqYpSZZaeAUAbV6EXL05qglb1EzbivUivfCNprxKEIIyQheMuQ2IFlZzikowS8qhS5mDRRmaa6UxM2btoTy451nsWv/cHpCo/x+sYQWpxYHyd2nNSM2n2bgJNtbqak35ehMF6J2RBkuNOybISyvUg5CfuoMydkCrPAa1bXCnGfHDNxsCI+annFWFOvyx380s5Xs5zkq+WbjGgJf8lFHLRaaWseMW19JxszeC2vSDqa/Q0QhXTA5RaK2GRFLUPPrWTx1Vw1xrclJyfTbLysjl1kO5PupXPURono4or4FEUuw/GtXUrN32OZsntiPZpWRvPL9Q9rb9q2ZdMj/x96bh1lSVOn/n4hc7la39q6u3rvpZmuQRVBZBhRlx3VGUUEFBREdBxAVZRQVRRQEBBfEhV2+wjjKoqIooiyC7AjN2jRN79W1V909l4jfHydv3qruRvEnOM7Y53nyqVs382ZGREZknjjxnvf1MAr2vuLT2Nqk3KfKRNqXVMcMHnn1ubh+Qtc6hVu+Ocn+Zdbn9A8VoFzl3h8oZn7/o/w9bGvY+W+zrc79P4DNmzePJUuE/WHHHXfkueee44wzzuALX/hCesymLDXW2vS7F7v4cvzxx/Pe976Xr3/961x++eW8853vTCcE224rHLtPP/00e+21FwCZTCYt119zrqZtKfn1z9Vjqrmuy3vf+14+//nPc++993L99ddvdsyqVas4/PDDOfHEE/nSl75Ed3c3d911F8cddxxhM6FrC+ef2l6zZ89OJzAA3d3d6edNE4CVUlv8ziQvMmMMe+yxB9dcc81mZZ0xQ5KQjj32WIaGhrjwwgtZsGABmUyGvffeO4Xt/LlrN6/T2ysP5rGxsfS8TWtCdzb9vmmnn3765lSZz9wuQkNNsarq+HQRmqY5LtlEsMfVjlBAVkvikEylcKuMC+91UCOnPAhCEaFKqugqEarxrDjWmU2RvJHBUwoPBVGMh3y2scFLXl4eijD5rok6lcTTTPpSUsq2MMGxwnUMUazTPII41Lj+lMh4k2qwqVSbVsi0nDgT42kXTzut8RfUhV4u4TtH6enc5VqT0R45dMo8lFGippuZMnQbCtAJdzlNqkEP1aQVbFLlZTLptfym05vcKwvidIcR6ADqNRyl0qTOUCnyBiY0ZLQLjTq+ciCyxFOoMG0kokVKtcSr0qTpRgVrEtXMKEApRWQiXO22+NeDmvw2cfKtbXGzNy2rXGg08FA4tKK8zXLYWkno+4zBehnh3E/UeptsNYQRDmCDWNphqgpps9yZCjYOhRUngUJaS4u3v0n16rgiINYzV5ykRtDqS1ois64ryrxNDQLlZmS8gExkwkrazq4rDm1zYojSrbFl4paCKaTnUMaIrkEYYhsVbLWEalSEpjPtg0bas1FNlFSdqXmuYBVZHMF8WzDliKjMNM3n2CoMCqrlFg0jiT5BNmm3MJA2DAPpb6las077W1MoraVkHKOm3gdjsGGYUpNuNlZIqEin1CWv3ASvLpXKaGEMcpWWpFyTCGrFETZJbJYy1lvKvc1770wZi9mC0GAm5bM2lknqFAEx5Sb9zBrh9QeUqzH1RFgtKXNz1W5qd2vmPERWt9oy0QuxjXJrcpxMWG25ARRQTTT8lCACVtSJCYNUHMxaI8rdzWeTsSjPTycs6bmT6wQNh6y1xBaZkHkZqZ/npxM0G9QJVGt1Y9qzM/nsWiUqvUFEjI+tjLPV/vFtK+b+72i+728RZ7+pOY5DFEUEQUB7ezuzZ8/mrrvumnbM3XffzY477gjA0qVL+dOf/pRGdEHYZTa1ww8/nEKhkCa6To2GH3zwwXR3d3POOee8qLr8uXO9kO24445/th6b2gc+8AFuv/123vKWt6RQoan2wAMPEEUR559/PnvttRfbbbcd69evn3bMDjvswH333bfZ75rmui5LlixJt6nO/V9rr3zlK1m+fDl9fX3TzrlkyRI6OoTJ48477+Skk07i8MMPZ6eddiKTyaQQohdrixcvpr29nSeeeGKzfcuWLWPu3LnpBGBTy2QytLe3T9sy2ay8sHUzsdVpybor3do2teZvmqqWyaYcLz1XjBWu6GmJh8kS/CZzOmtF9RE9Xd592mdrMVMmZ5tN3DYpokqS/ZQW5cUXYnK1zfpsWrdNv2u+YDc1PaW9tvB7a+1mddJArGTTNtERMGw52jj1u6kexabX0pscq7W0l5Z21VaubVQyyW3uZ0r7T/mttXHrvE2WlxRn0oQq2FaZk7I2nfBNy2mQhEdJNDVb6BuSmDg1OXFav0zPY6f9TmnVcnA2bZepzk/S9kpJO09r6ymqpKnzk7TJZv0mcWqntc+UOmprW7dpyv2bNram9q3mMVO+a0aOp6qObva7pF5mky7ZbBvp18npp+yXeaSdVu4tlmVqv27e/6lsP5uOj+bf5Bw2ofjc7LhNnyfNe6SkP05P2p3aF6bfCOV4qUIwOrmfU8u2aXtOud4W+6g1m31vN2lca5PEWi3QIs0WHCmtN++PU9ttS8/T5vd/bl96bt06J8jEaAumm9SlybVtHLYmZFbGX8pv9QLPRqOYzpK0pXZ7GcwkCsAvxfbPaFud+7+jLVy4kHvvvZfnn3+e4eHhNBI7MjLCwMAAa9eu5Ze//CUXXXQRBxxwQMpV/slPfpJzzjmH6667jqeffppPf/rTPPLII5x88skAHHXUUWitOe6443jiiSe4+eabOe+88za7vuM4HHvssZx++uksWbJkGnSnra2NH/zgB/ziF7/giCOO4JZbbuG5557j0Ucf5dxzz01//2LO9UL2yU9+kiuuuIJLLrmE5cuXc8EFF/DTn/50WvLvVNtxxx0ZHh7eLHm3aYsXLyaKIr75zW/y3HPPcfXVV3PJJZdMO+Y//uM/uPnmm7ngggtYvnw53/3ud/nlL3/5svD1H3300fT29vKWt7yFO++8k5UrV3L77bdz8skns3atLPkuWbKEq6++mieffJJ7772Xo48+OoXSvFjTWnPggQduNlECmTxsCdv/osyY1kvDTnHimi8CWk5D1HyZTHX0koh3+gLRWiLtsfB5N0/jIVSaTXl502Q3cQzaEdo4p8mmsclnVylc1cK2NldhtLxtUUhUMraCSQ6tFgaWUOMnojOeMnjKYGLBOiudRM6adZki1IMxLUEcmAbXiUws7TDVsU2WyNPofzLGPeWkfNeOta2opJEtVLIpV02DehDUprW/NaGILymd8pGn10mimUo56SoMxpBRGhtI5M0okbr3LLjKgTBM2zPjRWQ8iYQTJRHqTKHl2PlZ2Zp9JFdM616LGsRTHF1rY2lHPcXBM4YMrfb3lQvGpJzo1ih8HdMIXRoJoxFJhBzHnTbJcFDShsagUbLSoLQc39yaprUowqKS/mTFQYsjidqauAUtaTr1tRLWGHJeSM4LCQJhE4ljLeJL2QL4uRSOJmV1sXFIxiaRe9+0+kQCLUoqylRLvyeJYk911Jq/dzOpWi2ASoWxpP9pBSgLyqIcK2PMgm/BRjLRiBGn1MI0hiua0d/kfqX9rdmvHDd1BPEEsoKXafV7129NwNzMNOdU+blW/5n6m6lOd6K+2qy3q0Txtek0O8hzxEXJykuzHRwXa2PpX837FkdyHa1bKwvNto2C1OG2YU0i482yNMvj51oT2Wb3ybui8usqcgayfoQHhHWHMHCoKk1V6emT40a95ag3+2MmK1uzPUFWnZqZEM2giG7+xpXfT33+QOu+JPfERkl0v16Z1u+zhZCy1lS0TvuqyrVLHTMF2WgFROy0OVTrH22R54GWSXk6nl9ma7bnS7H9M9pWWM7f0T7xiU9wzDHHsHTpUmq1GitXrgTgwAMPBMRhnjVrFocffvg0RpeTTjqJyclJPv7xjzM4OMjSpUu56aabUihNW1sbP/vZzzjxxBPZfffdWbp0Keeccw7/9m//tlkZjjvuOM4+++wtRtrf9ra3cffdd3POOefwvve9j9HRUTo6Othzzz3TZNoXe64t2Vvf+lYuuugivva1r3HSSSexaNEiLr/8cl73ute94G96enpecN9uu+3GBRdcwDnnnMPpp5/O/vvvz1e+8hXe9773pcfsu+++XHLJJZx55pl89rOf5ZBDDuFjH/sY3/rWt15Umf8ay+fz3HHHHXzqU5/iX//1XymVSsyZM4c3vOEN6UTtsssu44QTTmD33Xdn/vz5nH322S84uflzdsIJJ3Dcccdx7rnnpnkB9Xqd66+/nltuueWvOpcZFrYf5WXEOY8asnzbhFI0XyxhQF+2E1cJ3twOroTBtdigjvWn4P/L47Kk3aiSUx52skzGKkyCysgqBwdFxibJksnDN2jIdeKxOt10kUFhSgHduOSsJh4N6EyElHwUbSoiHm3QZgR+gKuZFxq68iJ+NDqSZ0a+xupqG/M7x1i9ooMFMyZ4eERWNbbrblAdaznyZt3TUt8wEKVSkJdmGLRepkGd2bkeUctMnGKz9gkYWIPtSXDTcdT6PYDStGlfBLFwcYC8cnGsOPQgop5ZC+GoIbP6cVGp9XMCKUgmG8rNYEc3EK99BvwsC3J9TMY1zKA8R+zQanG+lcZOlmXZvlohi4MdEzx2V5xnnefQZiDjamxpkgIu4ahBJ0vzHSbCVALM848JhKLQnk4cAJGfr5ahUoL2LrbJz8RXLnUTYp5NVsUadXEaMtnUobOeTxGHKPEiCsrDjpfIWiEMdDxRWm3SndrhVRC1oDy2UUkdyaAZ23V9wAp0Yu0TrTIaA+OyImZLY5DNk1cOtlrDQ2hY03YbXZ9OINydX0f02G3JOSyTgbT97O4SYV2jlSVefh+UxmVchEFrdcZfBYV2HAtFE1Mt+ZiBFdOj1nEk9zXBVivHw9gY6kmOjOdDUMdOTmI2LIfBtZgogMoktqnGCgKZ6pyROqENq6lPeEl3s8nKBgQKnHYPLwjoMjGZBDJSzAR4oYHRIWyljOrohHIJiu0CnQFY9zzGcbGrVmA8H4Y2YCdHW/ezvbs1Pjxf/oaB9I/mfQiDVjsFdWxPf2usNCc5USQY+sRpVEx3xtqcDDlcmYQGEax8ClvswA4PoTrHkns8CR0jKQRHZQqiYOu4MiZA+rLS0v5jG+X62TxmxUNJP9ggzy3Pl/GbrF7Unm0lMiugHrhESX8FKNoYhaWrTSblsdEwuB7btUJgSsqRvluZTPujyhYwtZC6UswixDMOZtWjrXZzXBljg+uxk2PYnpmQzZNDYycFcmQqDaLHfteagNXKUvakvvWKR1sTMrrsDqjXRMOgVsW2d8p1uvrwrJAAmFjjOTGxkWT+ZlJth1WY0RK2EdKmlfT9/+N28cUX87WvfY0NGzaw0047ceGFF7Lffvu94PG33347p556Ko8//jizZ8/mtNNO48QTT5x2zE9+8hPOOOMMVqxYweLFi/nyl7+8WT7gS2lbnfu/o2233Xbcc8890757MXh5rTWf+9zn+NznPveCx+y1117TsOMvdO4NGzbguu40B3iq7bnnnvz4xz/+i2X6S+d6oXp9+MMf/rMCS88///yfveamDDcf+9jH+NjHPjbtu6m8+QAf/OAH+eAHPzjt/xfKJWjaFVdcsdl3v//97/9iefv7+zfTM5hqu+++O/fff/+0797+9rdP+39LbbdpvQ8++GDmzJnDddddx7vf/W5AhK1e85rXpDkTL9ZUPkkAzhRkibs6Dn4OrT3BijatPUM1khe/waIK3diefkm+neLc27EkoTaKyGkPohiNi5P40QVcPBQxrRfktPJkNVViYcp3FTUMsZLvGzRXEDSRVShfE6oEuhNGPO/naKtIRGrxrFGe29BFn1tncjjH7I4yG0famKvkJTy2IU++GGBiiZyprn5J/kwmOVKZJHJfnUhXIybCKlnHI0hmK7pnHsZxUYVOKb+XS6XmQRw4R0mOQUZpQqXIJrzVbcmS/4gjLo1yQc/eFpXvkAS5OEqTDW11Ajwf1dmPrYyxMZigEtUkAZQEblLsFfx2ZESUp1oli05xGzGCuQ+VONdNSXknL5LzABPaRWVdEfLJFqTeUSON9GENVJLkTWMYCksEJkKh0HMFYmdLw6h8p0RWh1ZLO7gZHMBLuON95STRQOiMhckEaGkI5DvE2UlWQ3RHH7Y+iS2N0Y90JjMwSofpJhwM8LtnT8P1NyecqtgNQU1w+mFIjDjpzXaj+ReIHrsN9xWvx04OU37oajqzAqcrlzMUbUQ9cNFzdxRnLUmepukMt3Vhh1aTMy1tAtXe24pqezlsaViw3yBldX20m8EMrZJjMjlwM9hMBtXRh61X0DMWiOPbXNGxRiK0YQOIwPPJq5hse8Lz71iKww4FAwUgHAxojGgmtEMtgVeM1zPUcaCjC9XRJeO3swdcH9XZl1zGoPsXY8rj6L5FGNeXZ0Vz1SAtS7JS1Vz9EGoc2e8m+SFRBK6LKnS3xkqSaI2bgaghWHovI6s7FhLiGHzlkFWO5N2EIczbBtWeBH1mCluYGh2A3tno7jmyohTUUGFfmvwNCAQlSRwmn6w6NSromULfbFxXxk+jInlDSRTc71bYqAVzch1DIZTAhLEq4feHsYqs6sUoWLwU2nskX8KVpGnVmyQgN8vnO8wwIcPKo+EoEZ9q3mPHw/rjktMya1GamN5uNaaUPIOrEc6SPVPn3tZKoB3siARr/ExMXQlMTG2zizzD/Bx2chjVLQn2BDXaVUit4hFFDrHRxFahjEpZxEIFKuejXE1gpkOdXk77n0qove666zjllFO4+OKL2Xffffnud7/LYYcdxhNPPMH8+fM3O37lypUcfvjhfPCDH+SHP/whf/jDH/jIRz7CjBkz0gDrPffcwzvf+U6+9KUv8ba3vY3rr7+eI488krvuumsa7flLaVud+38SazQarFmzhjPOOIMjjzySmTNn/kOc6+9h5513HgcddBCFQoFf/vKXXHnllVx88cX/08X6m0wpxfe+9z0effTR9DvP8/jmN7/5158r3ykfckVh4ci2y+c4TJM55UBNNXlpZ10fCh0wJL9TuWSCYAz0zQPPx06OsDEqo2bOp6zG0tMM2Bo+Dg3tYmIlUBFEJh1AF3xqxHhodMGnTEwnCt3mUUnEfoooajg4RV8SURVgLNpCTouTY2KFpwz12KE3FzIxLkJNow1x+mbmS0JdGSRUn81l6rDWgltoLTCZJrygUaEa1QlNKAmkAH4W5WXkN0mUUvfMm/YSHI4qVP0ONpo6lgwjtkGoMow7TYhRgr3PIi9ynUBRmjABkP9zRYn+ejkaJiC2JmVjUbliCqvQfV3gOKi+mWy0A+iZ4gzVdEBDQVnDYFxFzexnzK5H53UqOW8BlfFQbd2SXOjlxClI7r3yctgCkETEq1GdjOMTmhY8QrV1pwmKqm+RRDD9HEOEqfDOxngc1dVPRU0w7ji4vtCbtrtxq182YUmuL05ZpoDOdzLEb+T29HYwoS1eny/tPzVpN1Np3ddCF6M2QLV3E1IVGspmuyVR+zSpdHIY1d5L/tV9lB4TD2NGe5UNQZ5+f8pK1iYwLuV4qL5FjLh3kQ0VjpfAmppQrjiUOiXOHR6yLw5RhY7kHrYnbe7Jcc37Pjk6jS3HBjVhq0mgLOFUlpNQMU5E2XEIAafdwavHONaik+PavBAnsnJus/kEO72u1uL4Oy40qtI3vEQxubM/HR8qW4RMwgKUK4JpjaW0HrXS9LEytS5T2HPKNqKqfWpJ8w6FZTxXk1UuujPJvYoi8DOpA26T86YTUDcjyeiOi50KI0v2qUwhZfBJ2YxyRYFFuX5r/Cagep1N4GcaGqFLWQulJcizS9NSdDVGy8qKnwPlSNvlG2mSr/Zz0NaN8hzGlUvWGox1pEy6qaabwIzGBmVlo5gDv5thFePMkbGsy1WZ5PnJmEOgR6pHJjxBw6FgYuImBDVNEM6kqyaqYyaT1mNRd52o4VAfktWhqVCWKhZVzGPHS4RoWcn7O9j/FFb+ggsu4LjjjuP4448H4MILL+SWW27hO9/5Dl/5ylc2O/6SSy5h/vz5KcX5jjvuyAMPPMB5552XOvcXXnghBx10EKeffjogxBa33347F154IT/60Y9elnpsde7/SexHP/oRxx13HLvtthtXX331P8y5/h523333ce6551Iqldhmm234xje+kQ7c/8226667suuuu6b/b0oz+mIt+tkPAVD5HLZUFqcwn8NWEzaRjDgvdrLMoV074aDowCX+2eVEj6/EWdCHakteqmGI2m4H+VytkNMedrJEh1EMPisvjrFYGFrypsDQYBu7RQkTiS8vy2BNnXl00x8rwnUVFtouZsWKYHWduSQqt7HGqJhwY412A1kD0YYSB2YjehfKS/SWx+dx2B5ruHTZPD68d5kbbm7nA6/dwI13SDlevZ/Hht8agoagvqOfXAaeix0ZR7UlsJqMjx0ag4yH8jzM8ARHdC4lxtKeQISi//oe8ZohnFnd4LuYwXHc/fdqOeWNBr1ugS6rU73ZpjtVTg7ZoRHzbMbB1CG65puY4Ql0d7skFw9LlFx3Sbnj9WM4C/p4a3EpFkv4g7OTGxljBsdRHXn0zB5UVxdEEWO2AXlxMMeckHlhzPOew7ipQ6NBUbk0Bgx+4lTPDhpUHyuhb7iSaMUA7uwuyPhEKzcCyP+OQ7RqCHd+DwcXt2O+9ZlQhvDSC6XPFLJEq4Zw+jtw9n+t9J/KJCO2QUkl9bCWeOU6cradNa4lrDu0+wGVuvS3+BdXQthSVY1XDeDMm4nac29Wx7KipPq3Y5wBnDk9RP/1vVbin7HY8QSi0VlE77A9PsK24mMwsWq1WyOhOTWS71F+6Gryr+7D/9g5/OGHslp64qtGue2Obl6zpEz4gwuw9VDub4JFloZxcA8/jOVOxOxQk82HRDdcicpl0vFDxpexVa6CVqhcVr5P8plUIYedLBOvGsQdHiF6dh0q5xOuKZHZNYm2egJncl65S8Kc1GBceaxbIROEMHao+4ZnnIgIi9ORARrsWBynVpc+O3/pOI1Jh/CnPyceD3DaPeLJEKfTR+Wk/aMNZdyZeWwYozK3EawsiX+Y9NnMrrNlfIyMo9rbpo0dlZMJtBkalbHkOtjRSVRnsTVWkueKGRrDfcX24LrYRoPZKkNVQRPZ3esUqCU6EGZolOCSH6PzDrrNw5Slf+g2T/IpFvRh1o+ge6UtzPBE+hnflX19ndhGgBmcRPe1o9wk98BxiNcM4/R3ovfZN2WuKT/vpFHkYQfWNXKs9CJcP9EBcCJiq5i/UAIYYd1h8NM/pfffZsuzM47BcQgfExiYO78HvesubPy94ZZsyJd3HKQ+6hD9+AdpP0hznNYOE5cCvMV96PmzWWtrqBmJtknGJ/jWmWn5bRRLftPrZLw9PN7DHj3DhKFD+N1vguskOUQO1KXd3P1exa05y2v3bcNM1Nj4y2QFUVncBJbTZxTxyo0E6wMcZmJ+/xvY/1hebnspsfJb0nfJZDJkMplp3wVBwIMPPsinP/3pad8ffPDB3H333Vs89z333LNZntshhxzCpZdeShiGeJ7HPffcsxnC4JBDDkknBC+HbRWx2mpb7Z/cntnxUECgB8Yq2ot1JiZzGKvo6qgyWZIXdWQ0pdjDwVJSLouyJTq6a4R1h+Fxce5jo6lYwaR26pAFC8d4+rleOv1GKlK14LVVbGDY8ECODZNtaCwdmYBcVl44qyfa2X7OMKPDBTY2cmzfP8LwcBvjkc8O8wVHPTaUJ4gcxsIMC7onqNc8nq0XCZVilS8vhY+e1sn7zl3NVafN57hz13Lpp+fx/q+u4fKThSb0o98Y4+iaw9yuSUrlDDNnlYhDTWFGQH1c4h5RoCn0ikBO1NDke0LufmwOFhhzxMs5aO56vJwhqDg0Ki7Fvgarl3ely9qFTEixo46JFR0LG4JaKIP2IU4QHc8+OYPQKvo7KoyXs+T9kNhIND3jJY6NUVRCj9m9JcLAYWhSJiBeEjF0k7+OtqwOChRtxKRyOehkj29fIq7SW3IjVCo+c5aMk98+x0039fIKfwKlwPPkmMHJAr6O6e8r0bE4pLJWE9YdOhaKs1NZ7xKHms7tI8rPK/64eharPMXsyPL67SVxvDyUpWNeneqQy7NresgkUJzdTnBpPCaQJZ3VbHw4S1tXAxMphje2kcuGrJuQCOuMXDVl8HDdGD8TUypleL7RxkEfkR1fvMzwye3Xc9lT8ziqf30qPmRiRVCVe5gthgysaad/3iS/WD2HpVGdOf0TDAzKdUySdJfzQiYDn85sg1LD5w+ZLB9/8IsAdM5/PcPffDsnfmkl5y4axusEGwmManKlOKltMwMefWQme53exe++Msk+/7KBsWd86lVxqDO5iDBwmChniYxmZneJatVPxwXAQLlAHc2i9kk8L8bLCnY/ihw6ElGvONTku0LWreigFnrkvJCu7irF2UHSrlK27F4LUK7DzRcGaGt5OqMpJpd6zonIoflA2widC+pMrvVpnxtQ3uCxen2njNO5Y4wP55m94ySDz7Sxulyk0wnIJv2xp68iZekJaEzKKlxhRkht1E3pZZtjyVrI90TUx510rDRhWIXegOHn24hiTT4f4OcjOl6hMJNyncpaTXEHgcasvLPI/F3HMXUZP5WNco/zMyKiimJoTZGOnirVyQwjk3lcbaYlh7YX6zTqLuP1LCXr0qUD+rpkoqgdS7G/QXXEY8W6bgqqA3VgAAEAAElEQVRORMM47HrYGNGgPJuy+yxAL1yAeeppfnClT3sMz3qGotW0J23bZiBvLLt1DTNZyuK5hmrDo2+GTDZNrBkYLrL9rkMU3rEHF3xpI+1G8a9zRQxPjlHJqqKmMCuiOuBSHs/QPbfC40/ISrmnDH2dFVaMdZDFUMNhQaHExgSWuO/P3s6F77iRTgNHvnKNJOtHFuUq4rJcZ2B5kQVvhMd+nMFRlsholLK0ZQJKdXF8ezsrPDneRZ9qMGk8er06e669gZfb7p/z0uHRf/HBXTfTd/n85z8/jW4cYP369cyZM4c//OEP7LPPPun3Z599NldeeSVPP/30ZufebrvtOPbYY6eJjN59993su+++rF+/nlmzZuH7PldccQVHHXVUesz/+3//j/e///0vm5r8Vuf+H8yaqrVNZdl/NttUxXervXCfOOOMM9i4cWOq+Pv2t7+dffbZZ3Me+79gv58p4mOd2QZaWYZrOXpzNbS2DFdydOfEA23yxMdGk8uGlCoZBuIseWuYWZBouefH+JkIpaBa8rmv3sV+XUNsHGmjbiTCdE/WQ6N4TT1gRl5WB8ZrmRSuMbe9xLOlDvqdOsVCg+cm2un3a2T9iGcqEoXr13UcZSlkA9aWi7Q7AXPmTKC0pW2hPNJOvbeHb324yL9/Z5JvfbDAR79f4VsfLHDq9+WaFxwNq66tsrpcpF2HjBkfH8OodtNEtGzyv28tGWsYcxz26BjBWkW+KM7Uo6v7aChFxloKRIwqj21zpfRFXWt4PGfyFE3MCt8lm9BRupAyBu2symhlqYQeHdkGsREmn6mOXxRrsn6UYntznkwAClkpRyN0cR1DGGm6uqs0ah6FjgZnDnVx/gHjANzxyxl0EvK4l2WNYzh58TqWLZuJq4RZCKAnW8NaxXAjy0bHoyuOyWIYSCAQXXGEh2Wd6zEjitm2e4yOmXWqYx5/2igTp04bslH7dJiYJT1jRJFEP78dFlls5DwNBfsHNdaTJVSwwNapGZe+vDix9cAV/C8ysaxbhw6vQf+cSc7eKBCVc95c5errOzlqn3X84ff9RMlsQGPJJtHPinJYmCnzeNjOIbuuYfWyTtaFeRYXJMFRaYtSEAQO2VxIuZwhnwvpf1WdOdc/J/1z9W3ssvRdPHjma/jVmSPUtEYnLE8zE+z4hHbZrWuYL1fbOMlEPGCKLAxDik6iHBsLH313vobrGtZPtNHuBTKJS/IMZnWX8LIxq9Z3YSyUlEuPCvCdmOEwURDGMqZdlvglMn5EI3BZ1WhLJ5sNBXUNT+uAEMsXZo1gIkVxG0M0KW2S2baIbYTcfUMXw45LVxwz4jp0xTFLirJStHKynT6vznJTYBE1Zs4oUSll0tyM9Y08PoZx7ZI3JimXQ5sx+MnaVHMsNfflrSFExkrzmHHtMk/VcJSlFrsM4/FMRpNLxkZXDGtci0ZxUFxmmW1LeeZ7EhjWiOOSM4Y5us5k7JFXMR35Oq5rCIImXaiiHro4ytKWb9DW2WBiJMdYVdo1tJpR7dFuYhZ2j4v6tmf4TaUnddwf8SJWmDLb6iKf3nE9UUWR397HTIaEo3JQWJH78MyKXtr9gDB2yPkh62uF9P7Nbi9xd62bW50y39lngmjccM/Ds0V7IOm/MQrPWoZchxlRTJcOeNLJsV9RAhxxpBkr55g9c5IoEMXjkaECnZ3yfDt6NOQXrzbEZfj14/OwkCrpZhO3b6FT4Sa3wDvUJNa2oDDVwEsT20frWRb2jTM6liefCYlizS7Pv/yKr/fO/teX7Fy7rfzRi4rcN537u+++exoD4Je//GWuvvpqnnrqqc3Ovd122/H+978/hdwA/OEPf+Bf/uVf2LBhA/39/fi+z5VXXpnmxwFcc801HHfccdTr9ZeqmtNsKyznRdimDmfT2Wqa53nMnz+fY489ls985jMvC83iX7KHH36Yr371q9xxxx2Mjo7S39/PK17xCj70oQ/xxje+8WUv08KFCznllFM45ZRTXtbrfOELX+DMM8/kkEMO4Ve/+tW0feeeey6f+tSneO1rX7vF5Nf/S7Zx40YuuuiiaZj7z33ucxxwwAEcf/zxKTvPi7E2r/UQD9D0enWGankaKGa4DYZqEiGOUfT64vTX6h612GVRvkQQOmm0qFrVxAl1Zd4aDttxLX98ajYLMmV68zIBOHGbGmjY8HiRSt0nMpreYjWVmx8u5VmUL1Gu+wxOFpibq1CqZ6iFHtsXxwEoV0X6faySY25biUrd58E1M4mUorpW+vrXX7+Br1+c4cLXT3DB97J8/V/G+Pb3cpyzj7wcv3P1HP4lilnQPkkYOuRMRBRrep3WwzaKNd3J/9bCbMcwNpFHK8vIhLTLLL+K65g00r7QCRis5luCNxj2mT/AxEiOV84tUx3zyXcFNMpuKh4zvLEN34sJYofhWo46mjYVEwWKIMFB5FXMWJAlRlFQEVpbXCdidVki0Fli6jjkVczgQA4Hy3ipi/MP3cjVt/YD8Oa5G9iwvoN37LIGnVX87I/z+Je+QQaGi3Qlk7hS3UcrS9EJ6VQBjm8IYoftVIK19iyx0bTbEM+PmSxlGZvIY4E5TsIYYhXbqCrKsTwz0pXSGp71+o1E460Jy9MPz2CPmYNkixFjG/LkQpcoTvDNsdskCUQDHV6DauRxz+pZnP16if7/4IbZHL3dGn7yh3ns7icwHMU0R6VXW0brWfadtZHf/Gku2ztllhQnWDXZnvZrEGrVsK4p2ogNQZ7b7uhm+JuvBGCXpe/i0SeuZfF2b+HH2W3T8mtlMUneRDshz450cf4+G6gNOOy9MaaOSy2S16ynLL4Ts6FSoK40/W6dcuhhUBRdGYPPjHRR1Q4L3YqMi2yNiWqWiTBDr9fsh4pup85IPUdYF5G2XfqHmGptfQFen4PSil/fOgvHWsY2aLJJ0w8/LhPL1xXG6Y81btYw3yqUsqyflP7U79eohB47ZScp1TMs29iLZ4VKFGB2pkpsFDOcGsYoYqOZkUxGm/ewOZaiWNOtLI4WbHpsdCpWNsOpUWn4BChcZVhaHGef/pbCtokUfodBaXjiwRm8ujAm/OVGpdeZ68WEkUM58MiqGKUsg5U8JeVSTCA9GkuIJqtiJieLjJa76DFhmuCddyIKRDieYflol1DtonhdYRwvgQwesbiK1+8TDpb4xUPz8Kyl/JxQdzYnHBlr8ayl36kzGfg4ylKp5ZiZqaVtsWqynYPmbeDIPT2u/fkccgZ28kubJZG6jmGRY6gHLrXQ49B563nkOYncO8gE6aGBGXhY6krTYWKeH5Jn8a+PnOSa6zvxLOyiKrJCRZLfk/T5ydDnwwvX89yzAnd0tZAdO8pSDWQS3pursXqwg45MQLXhUQ6nCyy+XPZSRp235MhvyXp7e3Ech4GBgWnfDw4OvmBuYX9//xaPd103Zft7oWNeznzFrc7932C33norO+20E41Gg7vuuovjjz+eWbNmcdxxx/1dy3HjjTdy5JFHcuCBB3LllVeyePFiRkZGePTRR/nsZz/LfvvtR2dn5/+vczcxYy+3/TXXmTVrFr/73e9Yu3Ytc+e2mC4uv/zyLWaz/1+0Sy+9lL333puFCxem3+2yyy4sXLiQa6655s8yEm1qTWXFTr+B5xpKdZ8uv47vxZTrPt0ZeUE3VQutlZdqmxcwWhUnsnnMrGTJ3vVjosDhnqdms31xnIlKlvFRebjePdmLa2G+aVD0A/JOyHApj5/ASma0VxmYKJB1YvraKwxOFsjomPZCPXU8siomjFxmtldYP1nEU4alXaNkcpEkSwLfuGM2Jx84yIW3zuSUAwe5+NbZfHj/DXznDmGtOHHfdTx9exejpTwZN0qdMOJNRFriZqKpQoWWYiZAK0vzVTFRzxAEDr6S6zaMQ5dfT6klo1jz+OoZ5FXMU8s7yFhDOKSmiYwszJSZrGXQytKbEycgiBx8N06d1CjWZLwYa0m54LWyzEkmTbGRexMbxcy2MnGo2bYYcMVv+/m32SLu9vCqmew0Y4RfPjyPmoYDezfy5EAP288YY2BY2rY916Da8EQvwGhM7OBpSUxumqMsjrKUQ5+iH+A6EY62TNakVRxtUud8Xr5CbESc6od3zaEtcTA1sIg69w32EQ0p+uKQLq+R9sc2L5iWVBfEDjkn4pVdk1x+p+DP37vTGn77yFzeuMMannlyRqp13PzbtE6/wRMbetirf5CRkQIbJwtpu7lJrkEcC4tOPXDp9yNes6TMiV+Se/Hgma9h8XZvYcUzN3LfzqelqzKW1iTCWsXsXIUf3z+P/sgwQzWwVqX9WitLbBW9mToZL2K8mpXEVm1pJBPbubkKmWzE2KSszoxWc/g6pscLqDRatK312KE7U8d1DNbCso29qcPmYKkOatZ4Cg94Y88Qcazo6K8RJyrAmR6DjeDJh2ekzD7GSvpAly9juRz6ZHTMcC1H3olYnJtMV5Sa/V46ZquddexMa3c26TNxpAisg6dMOnGzkSKjY3wlQnODkwUeLHfjJxfKG1kxU8B2ToWBcgGNxaBSXHgYaBxMGikHmJGv0acsQSj/a23TZ1dXps4c11Cre+kEIbaKKFlFWdwxQRRpXNcwOFmgXJFz/OyxHnhMaGuP3GENUZL1K5HzJHJf10yO5ijXfToyAbFRdLhxCnMBmFsoc9+6fh4dhpN2WkNUUyx/pjeln7TJRCsKhRXMU4asE3P/yn527BJsv4kV9YbH/LYJgoZLNh8yMlpgYbv02c/c1MEX91lHXDY8/VBvCk9qOu8AXZkGd6yYzTaOTKbUlOs3c3CGanlmtZXTlUE/foEE7P8D5vs+e+yxB7/5zW+m0VT+5je/4S1vecsWf7P33nvzs59NX8n49a9/zZ577pn6NHvvvTe/+c1vpuHuf/3rX0+D/rzUttW5/wt27LHHcvvtt3P77bdz0UUXAaT89D09PfT3S0RswYIFXHbZZTz00EOpc2+M4ayzzuJ73/seQ0ND7Ljjjnz1q1/l0EMPTc9/33338aEPfYgnn3ySnXfemc985jPpPmst2267LSeeeOI0LvRly5axyy67sHz5cvr7+znuuOM44ogj+OlPf5oes3jxYl796ldz/PHHY619UedavHgxSqlUdfbWW2/lE5/4BGeeeSbf+c53OO+881izZg2LFi3is5/97GaUk1NtYmKCT37yk9xwww3U63X23HNPvv71r6cJoF/4whe44YYbOOmkkzjrrLN4/vnnt6je+6tf/Yp3vvOdfPOb30wpN/v6+thjjz248sor0/a6++67GR4e5h3veMc05db777+f//zP/+Thhx8mDEN22203vv71r/PKV74yPeapp57i+OOP54EHHkgTbg866CCuv/563vrWt26xfr///e854IAD+NWvfsWnP/1pnnrqKfbee2+uvfZaHnzwQU499VTWrVvHEUccwaWXXko+n0/rc9ZZZ7Fs2TIcx2HvvffmoosuYvHixS+qTzTt2muv5UMf+tBm37/5zW/mRz/60V/l3O9x20flQ5O2rske0qgI40NTiTRqMHd/gfy42mHV/Zdih1cJi0cCY7GNMrY8JlzS9QqnHPtTbvjwPC6+sMZ7txeKtmtW9pHHIQozvCZT4bqgi/1sxJJtRgBo2yXLeTdb8nh8+eA65/8c8vic9YYq5/9K+kgWhwPrDnscZLnxF/IA/fBeY3z3tn52bMgxH91vHT/51Vze27uRZTe3c/xua/j5b+fxzhmSGPrIbb3M75vAzcSMDLbxmj9+mlQps0nTl4jQ2PJoKoAza4/3S10T52PjMzdKnd3E+fJz2PEpURrX59ADz+JAp48nqfH+usePcjGH1/3Uwb/dtlP14cP/sp7cpz4lTET1SsKZnyQr1yvY6riwYcQhO+x7EvU45Pk7LpPylIaFC79RIf7VT1GFHKq7m4HPraLzdZ0AVK/S3D3SR6TgLrfGe07ZnS+euYILXxVTu12cuqdqHRx08AC5L35NmEQSoSeVsL7YKMDWK8JEEkfMeuUxRCbGd1w2PCeraXZyGJUrYqMAM7JGBLHcDP/95qvYB8E4f0kZrjltDr+9oMROgWW7OSMMbiwSJfCgnW77lFAqGiOsMkEN4gjbKFN/+/XS1HMzrH1c4bbBax46cwrPfYwZkwmN7pmHrYxz8aHf5MLD21l+mccO84aYeV2iJZL0XeW4xMvvEzpPxyX8wQWcG8gqz6/OzPDj7Lbct/NpvHrZuUL7qDU2DLATg3KdGfOJ1zzO2sOvZdB12XP+GL1XnTVdpKo6Icw/lTEZN44LYUMoMpvHjG1k/sAanNe+A7P+aVTXbMzgSvScHdJjlEpYnBJazOrrLmD7vUdlp4bz7p/NvrWYDJaOeXXqow43LJ9HPelwc1ZaGkrxrz/8F1RXv1A/tvdCrdTi4M8VUZk2YY/Kd2Du/zV0z0jZUpxFu20+XhxPPqdiVY6wEDmusBJlC9jy2DRRJuW42DBIP5/6+vN5XcNST1abv+0NscDtoAOXt324E33Q26RvlYaF2YuE4arYKzz2ydgx4wPCdx82iQEKCRVmFbtxpbSf1rg77CvdoCz88zaoCbNPUsZ5130PW5M2yVxh2XnpAPc9OZvVT3dhreJBXcCzMCtMnpMoDjizD+egd0sZvRx2crDFJNU5C+KQhZd9g22uNdzy2DwCBUff/8lpzx3bqGLWPIGetxTlZ7FxxI1v+AYHHdmR9KUa/qlnYwZXSj0nBpk7a1vpY8BZF36VS385B8/Chx45Q9q4Ke7VZHCqV6jucy7ztxslbmieX9kNQM6L0sj973IOp7+3HVup89urcxz8gz35e9j/FFvOqaeeynvf+1723HNP9t57b773ve+xevXqlLf+9NNPZ926dVx11VUAnHjiiXzrW9/i1FNP5YMf/CD33HMPl1566TQWnJNPPpn999+fc845h7e85S3ceOON3HrrrVsUonypbKtz/xfsoosu4plnnmHnnXfmi1+U5KpKpbLZcQ888AAPPfQQxxxzzLTfnn/++Xz3u99l991357LLLuPNb34zjz/+ONtuuy2VSoU3vvGNvP71r+eHP/whK1euTFVnQegOP/CBD3D55ZdPc8gvu+wy9ttvPxYvXsz111/PyMgIp5122gvWoQnJ+UvnatrnP/95vvKVr/D1r38dx3G4/vrrOfnkk7nwwgs58MAD+fnPf8773/9+5s6dywEHHLDZ9ay1HHHEEXR3d3PzzTfT0dHBd7/7Xd7whjfwzDPP0N0tD5Bnn32W//qv/+InP/nJNPXbpl177bWccMIJXH311ZvNmj/wgQ9w2mmnpY7vZZddxtFHH73ZOUqlEscccwzf+MY3ADj//PM5/PDDWb58OcViEWMMb33rW5k/fz733nsvpVKJj3/84y/YlpvaF77wBb71rW+Rz+c58sgjOfLII8lkMvy///f/KJfLvO1tb+Ob3/wmn/rUpwDpO6eeeiqveMUrqFQqfO5zn+Ntb3sbjzzyCFrrv9gnAMbGxli2bBl77rn5Q/bVr341X/nKV2g0Gi9qGRJoORZNdcOw0aJiC2opawRAwctirSW2BlsZFYGgpiotiDR5aRybFdGjnHKxjUBUO6tyj/M4ZBLcbRxrPKCBQrtJ1KgRkcfBRaWfPRQm+QykCq+2EaXL4TYw5AwpblVpodnUjiWyGuUK3WQToRajMXFyrLLYhLtdFTrSz1iDauvC1kviOGQK5BPqvHrSLrYyIdzy2sOaEN3eJ23adHD8HAXt02YVOS0Rfh+Nh8VJJggRmpqSZDdbGhaHpzQstJfN+5S0t5qxAFspkXUyuNqViQfiUJMtYKslqNeFoaRaJW8VtiH3x6gceWOoaU0e2e8mPPhOAqlwrcWUY2x1At0zFzOZlKM7ce4r49InumfD8Fp8x6UaNqRvJDzdpjSM9jJSpsqE9A8/R2ZKHkHOuhAEeCRQgVCT8SKGosz0fmkNKo6w9Unpa/UK2eY9r8e4gKnTumfJbyglAkf5TmxlTHjuGzXAE+hO0m7K8eS82YL03UYlOXeI1ymnqzW56pVt8bkjTrapJE5192xsZRwPS0NBpj3GVkZb9IZ+VuqU0KXaRCRJaQ87OdIqd72KrVax1QkZX026yiZfuzHYXBFbGRMqzOakK9Ey0K4maxUeFl/FxDVF1Eii1812SzYmR6G9R4SJckUpRyOB/8SRiGu5orxL0GgpUcMWx8u0sdP8vzwqdWjrlr5QHUfp1iqtLXRIOwF4OYo4ZKwhbsLRtE8eh2zCdkTUwNaQNgyTPqK1jEEQB706IX2vvXWfyYpTa8ujUs9mPZoUqNVx0eyoleRcSWBDGI2kT/hK47YJ9MZa4blvqOmrRACUSnK/aiVRQq6WWpPj2iREAbZUQ6kMrrXESqVUmWk/aGoomFjKGAbTr6ESnYV6Re5nvSKCgo0mBazXggs5Xkob2hTnAjCNCnXr4Phg4xYQpknrCZCxClupYcNI+kxpyjh7Ge1/Sln2ne98JyMjI3zxi19kw4YN7Lzzztx8880sWLAAEH2f1atXp8cvWrSIm2++mY997GN8+9vfZvbs2XzjG9+YJiK6zz77cO211/LZz36WM844g8WLF3Pddde9bBz3sNW5/4vW0dGB7/vk8/k0St8ULtpnn33QWhMEAWEYcsIJJ0wTdDrvvPP41Kc+xbve9S4AzjnnHH73u99x4YUX8u1vf5trrrmGOI657LLLyOfz7LTTTqxdu3Za1PX9738/n/vc57jvvvt49atfTRiG/PCHP+RrX/saAM888wwA22+/ffqb+++/f5rT3VSX/UvnatpRRx01TXX2qKOO4thjj+UjH/kIIDPbP/7xj5x33nlbdO5/97vf8dhjjzE4OJg6mOeddx433HAD//3f/51SNgZBwNVXX82MGTM2O8fFF1/Mf/7nf3LjjTdu8RpvfOMbOfHEE7njjjvYY489+K//+i/uuusuLrvssmnHvf71r5/2/3e/+126urq4/fbbeeMb38ivf/1rVqxYwe9///v0/n75y1/moIMO2uyaW7KzzjqLffeVyM9xxx3H6aefzooVK9hmm20ASXL93e9+lzr3m6oGX3rppfT19fHEE0+w8847v6g+sWrVKqy1zJ49e7PyzJkzh0ajwcDAQPowmmpbogSzMWR8T8Samoq0zQic47WUJI0Rp765Lt98SThuiw+/qZaYSKwbSPbFqa8bJ8hPQ+vhPU0WRQtm3yafbaK2qbQieb2kzn1TBKlp0Yt4HzRx7s0qpDaVv7xZH5VIwCudvhzjpupj0g7KccWBa7ZDk6M+jV5qDJYIsLQEjoD0s0vL8Ur5xZvlmcpz33T0lNBqxtbIhApaMvdaC6WeVihXENJKt64ZK2kzg03bF0SUBxIxLFe17n3TKUjL4SXRfBH1staiVIJQbkYnHS9dAUJrFF7SDi2z2E1ugETr0pdS0ocEZ6OTcoSbnadpynGx1khUO442b7fNjp/q7GzS9kkfSODa6Km9bKr2w9T2cdzWOQETIU5seh+dKWMrSqLZjpwvPWeTi9xp3Us3A5RabeVMqdeUfjnVxHlX0r+U3Wx/as1+qvWU8rmtfZ4/pe03sWY7Tf2s9OZt7biid6C0lH1qm5DoDGhPhLocN1HXnTJGbEtxF62mPXeY8tyZOmFI20VPaR/Hk77huOBOKePUPpv8lmb/VVooUqcGnzbpfNpu8vwCOV5NaZMpfUYpR8qgN3lYTe1XzT6fPoemPg+m/E470/rrtHtiBD+f+shmysp4U9tACZyp+ZhrwoGmRs2bz+H0GfJ3ErH6n7SPfOQjqb+zqW1J4PK1r30tDz300J8959vf/vbNBCtfTvu/f5deRrvuuut45JFH+NOf/sR1113HjTfemPKjTk5Osn79+tTxa9q+++7Lk08+CcCTTz7JrrvumkI2gGkZ2iD48iOOOCJ1Wn/+859Tr9d5xzve8YLl2mWXXXjkkUd45JFHqFQqRImE+4s916YR4SeffPLP1mNTe/DBBymXy/T09NDW1pZuK1euZMWKFelxCxYs2KJj/5Of/IRTTjmFX//611t07EGSmN/znvdw+eWX8+Mf/5jtttuOXXbZZbPjBgcHOfHEE9luu+3o6Oigo6ODcrmczryffvpp5s2blzr2INHvqXbYYYelddhpp52m7Zt6zZkzZ5LP51PHvvnd4OBg+v+KFSs46qij2GabbWhvb08Ts5vleTF9olaT6Gg2m2VTy+UkOlStVjfbB/CVr3wlbYfm9rVLr5MIUKMiDn0UJJ8jgUU06rKFAZ5y8LUrq0GRROdtUJOoUb0iS/pBXfZFEZ7S2DAUgRUjm5cIzE91mOKpL/PI4KDEgU8+uyhsZPDQCNdOU7TF4ADNV683xY+xkYhaWaMkOS6SF7GJFSZOvjOyXysr5Q7q2CiQKFkYiFrllHpiDZ528B0XTzt42pH6h8nWqMjyd6Oeno+ghocWdpzUmZfJjUpcsBCImnjXBH5CUJdzRw0RkGqeEyAKcJN70dxvg5osuYcBhBE2irFhiAPYIMIGUdJGkhTpoCAI8dDSVo5sDmACI7AgY6BRkXrFkTjNjYrAIBwXG9TwHBdjDa52JHLYjB5G0hdsoyZlCwNcFCpZPXHRSfmmTPKUJUQRolIYDnEokeOwkd6XZoIukNzjVrvJ3xAbNpL+KO2ikeh2ivUOaq3fxKE4P2GQRExrEMXi9LjSP7WyaGXl/pq4NflNzm8bVWxyHQ1oV6BsNmk/4jC5hzURYWr2mzhM60VQB2tEibVZ/0ZFvmve51Dql163qWpqZLOR3MO0nrHaLFGzOX4Ig1Y0vlmOoNV3m2M7VU6dasmxNo6mj5UoSOts46Se9ZLAuZp1Tuoh9Y+kTkENgjouatqzwVVO8jwAwigtb/rMqVfkvI2yKGqbuDUewkbrPge1tDyEUk6a/XVKxNtGzfsfpEq7thGmq1+bek1mSwGFZjmtkXadqpxspC/bUPJndNKHpX8nW/M3UXKOKEjhRcTxlC1s1aWpEpzcg/Q+W6S/JkEaO2UlliggRhNVIazpFHM/lT7USa7ZXBnabAXhZTLzEm7/jLY1cv832Lx581iyZAkgqmTPPfccZ5xxxjTu1E1ZappRrubnF2PHH388733ve/n617/O5Zdfzjvf+c7U+dt2W2FuePrpp9lrr70AyQxvluuvOVfTCoXCZr/7c/XY1IwxzJo1a4uMNVMTe7d0HYDddtuNhx56iMsvv5xXvepVL3idD3zgA7zmNa9h2bJl01Yaptqxxx7L0NAQF154IQsWLCCTybD33nsTBMFfrEfTfvCDH6QO9aZJv1P/V0pttl8phZmiAPmmN72JefPm8f3vf5/Zs2djjGHnnXeeVp6/ZL29QgM4Nja22eRodFSWoLc0aQLBC25KlWkf/XkrQliZgExWcOaVcVlKThQ4m06EUpoON9uKaDfxmyB4Ws9PnMKqKKgqTUMZMu2JmuZGi4ciVArPj9E1RbsKaZTFRc+5mhBDBgdcTYgcr5LvATwcXGsFejOlLqGCXPISi6uWrLUEDYesExOWNHkjolUAGSUMHDZh3bAmwQqPD8gqBkmUrTQsS+yejx2ewNUuCkW7n9zrKGhBmVxfIAbu9EdriKGsLDGW0ErSYQzESZStaKDNauLxCOV4AgtwRFwrdaxcV6AdAyvA8/G1SyNqiTxNi7g6jrz8jaWmrAjXADljmXQ02kKIBTe5hrEpZWAMOG0yaYjXPiHwBGswAzIxV24G6hWip+9BFTrIO1mWdBQITCRQiKQMZnygFU1NIoshlmojEf/yEmejWXzPUAs8+txkAqOdVt3tlLusNfXmkHUT6kBX7kNTRRdjWuqlidMWYVGetFGThx1IIFVajtNaHFvPB61SDvuZcYhxBIZhJwYFipM49s62srQer14GCMSsK7ZMrs/QZk0L4lYelfM6rsA0snnZV52AbD4tN9UyRLE4/UpLX5xcA21dabvYyVbAIHVAE//RRnLPAzTWKryixUQRmRasn7yJ0UpLfxrZIGUaH0rUVNtabehlBBqULcjEqFpp5df0JuWbGEyjuXZ8YFpUPs09MTF2ZA2q0C1jpdknADu+IYlAO9ioQYmYunIJk+dyZGPi5vpSLoOdGELlO6BWRiVtYmsl6aeOm+Za4LgQ1KW/Jtezk4OtFQpjwPdl8iSdAjPwrOw3Rvqe0phVG9P61KxLZYNLVQkzUGwUfZHFtUKbC8lqXD6XTF4aMr7iKMXCq0wWjEEXs5KwjkwQbL3UmgQkatjUytjhtZKDAxSsxkxUkzoHmPEBuUbSb21lLB0z4boKGoHAxmsel8m640q+THI+gDYnpFESbQKtZC2xEbotxV0Az4WgIfSy+S2/t19qm7rCudX+etvq3L8I831/i8mem5rjOERRRBAEtLe3M3v2bO666y7233//9Ji77747jQwvXbqUq6++mlqtlkZc//jHP2523sMPP5xCoZAmut5xxx3pvoMPPpju7m7OOeccrr/++r9Yxj93rheyHXfckbvuumsa5Ojuu+9mxx133OLxr3zlKxkYGMB13WlsLi/WFi9ezPnnn8/rXvc6HMfhW9/61haP22mnndhpp5149NFHp4lDTLU777yTiy++mMMPPxyANWvWMDzcesvtsMMOrF69mo0bN6a0VPfff/+0c8yZM+evrsOWbGRkhCeffJLvfve77LfffgCbJdS8mD6xePFi2tvbeeKJJ9huu+2m7Vu2bBlz585NJwCb2pYoweptkpSmvFyyBCs4YHKxYIubCYdaU0+w9ZGJJGnW81vy7UgSnjVGJOu1OOPKd9EEKbNEjCVCouph4GCw1K2Dn0/GmHaxiPOplEogLU0IiViIJVQaXE0Cm08d/VriNLjtmqpW+BmhmPS7DGVHlEMB6mMJDtk1aG3F8dB6WoIfWqNdH9uEEhQ1lSSCZpLSqGLPNBiOyhamTeiUmyG2Fk8pQiwORjisp8APQgUT2qLzknSoCl3py15lhcXG1ksQNlAz5kMUUIpqBCZE5WQ/UQP8nJzRdVDZLCqbRScTI4CGUjhWcg8sFjyPAIPydcruY5TCGovu7Jdk3npF4C7N69Qr4GdRXgaCGmNBiSCOyDoeulfYq0zigNlGBZVg5Zv9xHPkPkeAymWJkgRbaxSONinVnsoUsK4vmHs3I457koPgNztCZNPIqWrrQjUdT2vSyahu75NJp1wEi8LxptQnkzgrjov1V0Fbl0wMXIe2meL4TWx0aSfEWoWeMV/yDRwX26imTr0zf2fiZ+/HBSYcRbYYyr1rOrtZwckrLwf5AJVrTyaEGRhLnGDPw3o+Kp9H5TuxflaSWts6JWG0aY4neG4bp86r8pv9TeFahYPBJyaui2pqQ0GQtFVFOzSUkv7eN08c5q5+mZwlDqYqdECmgHJ9VKZNYBnZXJpQq/KdCfzFlWiw0ijPb40dkP/LYzJBcTyU58sEZyocy5PJYvOzj8azNp20x9j0mQGgeudKG3p+mm+gMtk0sV+194qzX69Arthy3jMFdLFX8Ph+suqpNaqjL73/Kt+BrZWwjiu5EDZGz+4RrD/gE5PrisiuEc0PYxVjjlBh5hMdj7Q/5jsksu7noFFLJ5sq34mNQ1mJdMGECQqnvQ87dRIb1LCTI6jeuSlMsqYsujt5HlTq6K7ZmKCGyraLk9/ZLwEawJuVJ0zK4szeXlYtkjGQTqyqEwRGU5gZEdch3ijRe9+NCZKE2pgEWulq6kq3ID1b7R/atsJyXoQtXLiQe++9l+eff57h4eH0xT0yMsLAwABr167ll7/8JRdddBEHHHBAyjH+yU9+knPOOYfrrruOp59+mk9/+tM88sgjaYLkUUcdhdaa4447jieeeIKbb76Z8847b7PrO47Dsccey+mnn86SJUumwTTa2tr4wQ9+wC9+8QuOOOIIbrnlFp577jkeffRRzj333PT3L+ZcL2Sf/OQnueKKK7jkkktYvnw5F1xwAT/96U+nJeZOtQMPPJC9996bt771rdxyyy08//zz3H333Xz2s5/lgQceeFFtvt122/G73/0uhei8kN12221s2LDhBak+lyxZwtVXX82TTz7Jvffey9FHH506zQAHHXQQixcv5phjjuHRRx/lD3/4Q5qk+1JrA3R1ddHT08P3vvc9nn32WW677bbNougvpk9orTnwwAO3mGl/5513biaFvdW22lbbalttq/1vMmNfuu2f0bZG7l+EfeITn+CYY45h6dKl1Gq1lArzwAMPBMRhnjVrFocffjhf/vKX09+ddNJJTE5O8vGPf5zBwUGWLl3KTTfdlEJp2tra+NnPfsaJJ57I7rvvztKlSznnnHM2S7oESdY8++yztwg/edvb3sbdd9/NOeecw/ve9z5GR0fp6Ohgzz33TJNpX+y5tmRvfetbueiii/ja177GSSedxKJFi7j88st53etelx5jjMFNoAhKKW6++WY+85nP8IEPfIChoSH6+/vZf//9/yrRhu23357bbrstjeCff/75mx3zQtCepl122WWccMIJ7L777syfP5+zzz572qTEcRxuuOEGjj/+eF71qlexzTbb8LWvfY03velNW8S0/y2mtebaa6/lpJNOYuedd2b77bfnG9/4xrR2fLF94oQTTuC4447j3HPPRSdL4vV6neuvv55bbrnlrypXumydLaCskchMoaOVJNuEFTQ0xhqUUmQcX6Ji1TJ09afRZbwcqmeuLLGXR1lZH0bNfRUjejleUSbFj4bDeEqzwO0nXwhgUri5g4RNp5DxGLcBXcpH5X0mbYSrPFTGZdRKVLBTeSg0KucLvATQPXnaDSzISCR45HGfHaI6z2/oZJt5ozz9QC+vLo7y8HqJ1L1m2w3EoTCJ1ENXInyOiykNS1QyqbsZEQpP3Ax2YhCtNFop8q70D1sewwyskIiim8EMrMBZ0MrFsHHEqsYw6/IdPB2MsFHPYVk4wHb+rFYeZzNH2dWyglIZk8i10hKxR1ZWyIZyrc4+HCXJrGmyo58TyIOfQy+cD21FaO/m/vhxnF12A2DsujU4FkYcuK++Dr3T29holoMBk4QcLeDMKGBKw9iVj6B6Zgs8IYlQq65+wQxvXIWauYCil6e30E4pqhGvS+TZtcasf0bK2WwLY3jQTrB3IGP2T2YFqnspG9U4Xa5HviegMdCRKiKTKaCaUVfHFfhHWxfONttzj7oOgA/vtSPP3zlM9hWdEq2dim1OIve2PIaeuZBn4gn0dkuJ2IDjTUmEDSstWE6hHTu0GtW3CPfww7j/R78HYLeeYZ4d6WJ2rkK85nGBrDleC+8OxM/ej7PkVdydvYmdA0sUTElABqiV5B4WOmR1RWm5Z7US5GX8qExB4F8bE2hJZRKbL0K5xeKjHA87PoCevzM6SR4OjSYcT8rRUDxLjbZMnqpy2H2+h5MN6dxgmUwEt7b1S8KbH0fYZx+FYgd2xaNQaEe1i/COXbcCNXdb7IaVMGcxFIoS9a3J+CKoJTCYdWkU3zSpcZNnhhlZI6s/cYgdG0DPWDBtrADYsfXouUulPeKQVbbKLL/IRLKStLIyxLhXI689VO9O2Gf/hG3rgEYVMgmcKQqwkyPo/sWYgWelPNmCjOlkZUY5HmZsPSrfISw+JMw6Tbap6gRm40pUsRtn9vbSJ+KIxoqBNIn1Cb+f9qc6+WPW4V2ZBmHo0FO3aKBLy7Mpsho8YWBS2XaBLBU6sIPJc6TYhe5bBEHE/XEv25sGE7gC22lGxXVCdVotY1Y8jJq3A7p7Dk/YEnqBUKLayUnM+EBr9cLPYScGcWaJfzF0Z0xHLOM5fvYBOZ/jCowwWblwt30ND/lZdunz0JMRvhML33+scRNYTqgsqlNWZLPWoGYt4u9hZiss528yZV8s8Hur/Y/aH/7wB173utexdu3av1nV7KU8F0Acx7S3t3PllVf+XbPBXy5rSkc/++yz0yhC/5HMWstee+3FKaeckkpaf/vb3+bGG2/k17/+9V91rmtmvweAspbZftbIZw3kDFSmrO+9eeE6tGupT7rcOthPfxhT1ppxp/UgLmuoKEu3Ubz3wAGuvrWfN8/cwLI1kgew//sa2DBi9I4aj6zvY5tciXrgEicMDc+oPEfstobKRpffb5jF4busobLR486Bfg5/lbwgqwMO9ZLHXRMzOHjBOuJQ8+jqPublyjwSCp708J3X8KMn5vHefdbxnT/O4cP7rOOSu+fw4f1F3fTiO2axSz1mplcjMpq1NkcMdJmYcrJs3dCKnjimqjQNpegyMUsXDmKNolYWp23ZWDdt1lBTAgPqiWMez7jpkni7gaMO3kg4EJBZ2k3w7CjerDzRUI3aOjlofGMe149ZP1pkmZ+hzchLuablHoAkx9U19ETCUX7wjmuwBm5YPi9t++b9G54Stvng6V187ByBfZw5f4g1K7rY9nUTeEvncub3Qz6xeD33L5vN7IxgeT03Zm2ljTHHYa5pMKAyGGC2Faz0gMoQKMVCU2e9yrD3/A2MbizQ0V1j2Tq5x1WtmWkDNiqfJ33wk/TOk0/vYe1FMgGY854+bvi24YjXrmPwkQwDY6KSW0kw+Y/rfMogpIA2YylpxSrX8sn3CbTqi1c7nLbTer6/bB7bNQxGKbS1GKXwklebBVb6muPfOMLXf9HNIWENCzzitHKNDJCxMsnKGcuIq1juRHz5FOlL/37hMOfvPsyP75/HvDDCm6Kc25jCeHR31uEzD36JX+z8WeY4NZ61+ZSvPW8soVIkqSUUY6gm97c5eiYcgUEsDiJGHZeuWMaXl9QJZH+HiXnWd6lqyBv4Fz2ZTs7yuZCZu1bx5rWDVtxxdY5MQotZSNSol5kieWPJWMMM3WDIZJihG4zEGUaS/IyuOGZSOyw0ddaqDDWtEvXVVt8KFfQkx8VAt4mY0C5NEGu3iSgph1gpekzIuHJps4ay0immvsvErPJkvOQNvHGXNfizfeJJKavTncGZ04ut1Lj1yiyzdJ1K7JJRhlGkr3QTUrIu6zyXnsgw6WgmtIhNNR9fDQVdsaWqFdWkwYsGEgZePGuZYUKGtMczPuSsUOm+0R1jpCIO9O5HBWli+m3/3UnexoQoMlhyWr7PuhH32yJtpvVMNcCMSAZyTSvWuYpD3XEWvjPDrZdnKNqYCeWk97hpOWMoEDGqPEZczbvfXeGS62Sy0malDw26UodIwYwIViY36GP/VuLea3LkdETNuKlyuIdN++zTGZcPX3MI//3OW+iKY3odGeNNFWGABUtGuWHlXHojS68J2OD4vHv9Nbzc9tuZ73zJzvWGjde9ZOf632Jbnft/cGs0GqxZs4YTTjiBWbNmcc01//8H1Ut5rqatXbuWq666ii9+8Ys8//zz01hn/rfY9ddfT1tbG9tuuy3PPvssJ598Ml1dXS+rwMRLYX/605949NFHUzGx733ve7z2ta+dRov6Yuxn/e9OP8eInL22ECr53IygeNawdJbwcTue4aE1M/GsIZ7iSNWVTn9jgV1nDvHwxhlsmyulCVp+JkJpmJzMks2ENAJRPpyoZtMydOXquG7MUKmw2WcQVVFrFIPlPL2FGtYqqg0P343T62ys5ZnbXmLjZIHuXJ21tQJLusd5frQTgHntk9TqHpXQo+CFPBdJImFDiRMDoK2lpjW+FU76UCle3TeI6xuJ/gJ/WDk7dc4y1jCpHQrGpJhhoxS79wyzcaSNno4qG8bamDdjkuHRQppD0J5r0LuwzCPLZmGAknbIGyNqo8lEI2sNHpaNjkfeGHbtHcFxDY8N9Cb3R8rnWYkkhknS8o6dYzw6IYl1+yzcwKrnu5g7Z5yg6rJstIddZw6xaqCTXIKF992YKNasiXMMepqeSOo+lOD2u2OLZy0DnqYrsuwzd4Bcd0R93OG2tULP2h4bRlxNR2zTOjrWslPnWKot4Hkxy0Z7WJgpk88HxJFmtJSnp10mGU9Pyn3SWMlRSO5JqBQL/AQL3/CZ1VVmcLyQTkLkN6JsCjLRUMAOuQk2VgrMaiszVskxjJ+eTydtVzQxFkWU0IU2rzk7U6VvTokHVvYz5mgaqnWdroQffMJRdMQW11qOWHYW79zjFI5ptKVjK1SKnDEYNT0qGSf3tmlNZ7SqNNkkR8AoaEzBqYdKJiEm6V8LdDVVEA6tpjdXoxHKhFkh7CdZf8qqRnJTBmoFBlyXvihixHHpilsTl2ZC46Dj0h1HZDEEtJzyMNnf0Cp1+OtKkZ3iUjSUomAMkVKUtaJg5Kx6yjHhlOdHrBRLvDLlwKPNF+e+vb1OGDgobVk11sGI4+BZKGtFX8IEN+q4ZK1Nx1+bMeSSScTUtp1wZF/WSt6LBiZ1U4FaztkRyyQxRphiJhzFnESgKktMFYc+r56qRbd31jGxYnKytdJbD10GTDaZlJHqWQAESpJo+1UDrSx+Mu5WRG3T+q9MOGUi3wTW7lwcY8WETDgdLCOOS1tCeamAstYp01DGWHYoTBDFmnujDkJFmm/TXClsMzDPNCjbRKAvU8NaUYNuRu7zmZDhSp7Qahb1jfHsYDcHb7yWl9u2Ovd/m2117v/B7YorruC4445jt91246abbvqbkjtfynM1rbe3l56eHs4666w/S8/5j2xXXXUVX/rSl1izZg29vb0ceOCBnH/++fT09PxPF+3vYqteKfCyetXD0QYvG1Mr+7hujJeNadSSJfZYs3yyA8daKtphj94hHM9gjaJaEkfJ8QyONhgrTDhPDPTyinmD/GltH306YfVA+MxrxiWrYpSyBEbT7suy9kiQZX7XJEHDZaCa3+wzSCLuYCWPxtKTF4d/spYh54XUIynvwkWj3P78bPabt4E/rp7Fftuv4zfPzOWABQJ5uPv5WcxXNTwnZjLwWTx/lDjUZNvDFCIUh5pMQV7sYd0h2x7xh6fEgS0nfOMHzN5AHGqUtjRqLtlCmIoGNdvkyXW99LgNYqvobKszNJmnM9egEcpxk6HPWtdn364h4rjJppVwTsdJ8lvzhdzZIA41jw304ljLNh3SJkpbwoTxxnEM+WJAHGomJ7O0FaTt75yYwV75Ue6tdrOdqdHXVeaRsV52Lo4xURbnRCuL6xi6eytkO0KCsjBpZNqa7SDlyfdENCYd7lg1i0mtaDPwuqRt6yWPzJR2cDMxQdVlYiLHcEOuk1cxi7YZYfXzXUzGPlkVM79/nBUbZCKyqG8M7VihC3QsJlbC6OFYJiYkkhobRS1yafNDevrKuH4zoVZRGZc+WegMCGsOT23ooc+vMR5k2GnHQcYH5Byua7AGXN9M68fZfEj7Iqnzf987l739cSZrGRYsHCPTHmMiYemZXC/wkmwxJAo0Gze08xU35roHL2TDoR8krEt/9LIRJtLUqx5KW7L5kEbNxfPjVFitWvIxVpHLh7h+nH6nHUu+GLT6ZFtEo+xiYkkOXrehg85kHLh+zNBYGzO7S7i+oZFcf/VYO07i+EVoFJZtZ42m58q0RQRVh7ERWdHIZiKiSNPdX2FiKEel5pPxYjxPylXoaKRliRo6HTthzUkncM1zxqEmW4xSGJzjmfQYPx/TKLtYK/dgaKCNzs5aymq1bqJIh5c4wl5Mz+wKJlZoxzI5LH2p2F0nqEp7uJmYqOEQhk46LgEc1+C6hijSmFhTrkp9ih3Sbto1+PmYoOpgjcLNGMKaQ6YtojLqJ/cwpjgvZHR5lsGxNnwnZkVcIGMt3SQrDclkdMHs1kTWGilvc5yaWFGezMqzL3kGzJxbSgMGJlI4vqyQZtsjwpoI7j20diavnLsx7QfasdTKPkpbrJFnrp+TPpvrjXji4T5cZViydBgnK4xKyoeolKwCBYpbV83hkG3X0ig7rF3XiaMshWzAWBJs6SnUWFduw8MQ4LB4xhiLl/110M//P/abl9C5P2irc7/V/q+btZYPfehD/Pd//zdjY2M8/PDD7Lbbbi/LtY499ljGx8e54YYbXpbz/280pRTXX389b33rW9PvLr30Uq677roUTvOJT3yCIAhSVd2X28LB5QCJquMIun8bwZGXhnH6F2MmhmR/bZKO13yIvJuh6Od4dtm1wkiRLaQUiLY0LFSCfhZbK3Hwu6/mltO25bwLSpy0jzh+H727i4JyeGWU4ZDejXxjvIe31SMWzhNGk869c5x0U4ZOPL741gofu0E+f/7wcU66WRyPdjz2azgc8o4JvnVjJwbLSW+b5Hs/7WDvhM1m8Q7D3PPkHBbnSihlKXbWeXpdL33ZlgZAZ1cNpS1jI3l2uv98YcpIlFmlziVsrYRq65b2qU3Su/e/4zsumQRLvfrJn2CGVqNnzJfjG5VEeKhl+732dPb1Z7HKVnl/o8B1mQYHRy3YyVpP4Dvv3mst+S+fJWqZXi6hrksw925Gzh02UMVeFu93MrExrHroilZZE1y2+e0N0NGB6ujkk596gnPeJy/zm37gpDCRm90SV529Cx/8z8f59usmWHW7tO3TjXYOOXyQzKc+jy0No7tmC0d5ogCqO/tFlXd0PWrmIha++gSKXp7JsMKqBy+XCsURtjYp7CS1kmC1/RyfOfjbvD2QicaZTo2f/OcSzj5nhFc0FPsvXs/yZ3vJOeKc7PbA2Sl7SCpMFTWwlQk+fsT3ADjnfYrzr3Q4+fUbyZ/9zbS9bRxhBiU3SvctgqjBO/b/Aj86ZRb3nDPJ9guH6PvRV+XYJq5facGDt/eiMgWiG65k47UCZ1ox2EWX16ARuex556nYyqiwqUSNlKazmXfy04MuI28su8/dyKxffb+lgForoTtmYMpj2NF1OIt2x1bGseWxlNLRjA9gh1ZDvYr76jdhy2PYoIZZ+SecXd8g5Uy451WhM6WVvH+fc9nxNck4NXDGYzN5fcNDW8vr3zBAMBBz49PzUgrR+aGhrhRv/d0J2LH1qN4F2PEN6J55mOFVclCjjuqejRlZI1j5P/4SOjpbeO1Xvynpc1V0x4xEqXkiHQfNOqtir6jCVsZwZm/fGitNXvnkGBImrqP3P5O3hMUUvvS96HkW+z10KI9vfKwXvfcbUD3zMM8/iupMmG6qJWjvSfubyhWFZ7803MKkF3uFSSZbwJaGsYOrwc/iLNlz2vjRxd4WF7zjEnztC5CsWv3mvzvZY/Yg922YyY45iYo/GrXjWUtHwqhnURzw2S68I08WjYCmUnOyQtBk0QmvvoB7vxkwqj2qWvHuBz4z7bq2VsKsXoaetS2qXVbnPr3Pl/jSe5MJbKWOd+Jp6bPCTg6i2vtSVqrSf3yGa58QyN4Hf/Fe0QBIWJaatKqqrZs/7HMB284fIaw7bBhqRylLzouoJmw5P8/6fPYDCjsuMJ99b/xXsnu9dI73C9mvZ77rJTvX32Ol4R/NtrLl/JPZr371K6644gp+/vOfs2HDBs477zyUUunW09PDoYceyqOPPvo/VsZarUZXVxfd3d0pv/z/VWs0Gnzuc5/jjDPOSL877bTTuPzyy9PE7S3Zn/70JzKZDDfddNO073/yk5+QzWZZtmzZiy6DrcpLWeU7JJmvOoEqdIgzWZlA5YqyuRlc7VBtcokjCXNN51e1daMybZKYm2tHeRkaNoKMwCVM3WDqhioRFRtjlQhKZdBokqi/Z1Cupm5jocJ0NXVrEk52h6qNqdqYAEPGyrFRU73SCBzFWpVKlyskuus4hihw8IkJI4cwcvDdOI3qWauwjarIz4MIEk39vzyKyuQhjtBK0Yin8MuDJMwFNUniUxrlZ1ub5xPZGAdF3UYYFHUiDNDQsjVhDcrXqaIn2QJ4GZSXE0c/U0gd/qbDEppIXubJptxMkpTpCXWh51ElRhXzqGIeg6KhhRKxYkPIF1LtgKZFClQhg/KzKT99+rm5TdE2iGzi1FhRqFWOK/VWTqusfg7lZ6kSExtNbDQ1G4Ij+OyaVjgZQ2g1nhvjubE49k3xoSgQ5yuOwM8liqW2Vd7E+UqFtpr88k2VWzcj0mdGoqpK02o3x5PJWFPtU0v9VC5DvepRr3oUnZBa5OJqI/WbqrLavE5S1+bkKay7qaOpckXhWa9MoNu6wM9JUm6hM3XkbK2ELsrEgtKEaAuMrBHHznHTtmjqDqB02kcMLZE4Gwl9ZKgSSJJWaFf6mIdseRuTtRY7slZEoEbWQL0q1yv2iiOcL8pEp5DQcGZzQmmZ0FnaRlXqZWJsUG/VMfncpBq1jUprn5VkfduopP2iqXSs/Bw4Hi6KmhaMfENJv6rZiKqN5d406tjSsDyjskWZVGWFOjS9D8376ufSY1SiuKsyealHNi90n01l5ykqvMrPCgWo62Njk/aLWCnCukNZt0TNPCs89xksGSweFpXLijBWFKTiXLY0nAQ/aolGQoRFIGHaSt/FxIlAWqIAHUfphB5Eq4F8DvI5VCHbelZ4GamTn0vLbSJx8FxoqQxrLW2gHNn8HAEavy0S6takTrGRVUOlZJypXAY8lzp6uubEVvuHta1sOf9ktmLFCmbNmsU+++wDgOu6HHrooVx+uUTcBgYG+OxnP8sb3/jGVDX1720/+clP2HnnnbHW8tOf/pSjjz76f6Qcfw/7yU9+QltbW8p7D9DX18fBBx/MJZdcwjnnnLPF3+26666cccYZnHDCCey777709PSkarxnnnkmO++884suQxplC+rozn7M6HqJDHb1YycGJdKDcNjnPXGSBqsTwphSmRAe7uYxbV3YdYOiDOq45LUH1Sp5FCYhQcnjJtz14OcjvJJiFI+FiUNu6yEFVaBKjA1icsqXz42QgpKoYdlGFK3FVBq4tONbcUhzFkpWHmtR3cFrClrFmjg2eMoSJNjkrkyEiRVeNiY2Shysyjiqo8WLbivjwps9vBbTqKA6+si5Pq52mGgkYjJBDTu0Cjr7oTwmxycMHCAMKDnt46EoqIQ72lrqGjJT3pMTGjBWHJeE09xODLb4zbWWiHHPPIgaFN08YVNZFLATG1Ft3eL0RTG2Vkc1GrThYCcThhN8OmKbOqBNtVeATFYi5pm6BWMwo+tlxaIyIQ5as0zVCZnsdPRhy6O0ewUqUY28m0m5tO34AKq9TxhAEt5za2LyOPiOlFehoFZLBYrCqsPMQoVaklArCq5BwnNvUrEm4givWeo4xrUOppo4QVN47ptiPjaogTFklZOoJVviUKXtluoTNIXLvJywu0yWySQQh3o5j5c4PtKMWdAOSuvWvc4WoVZKE2e9bCR9KuFw1139mIEVomLbPUei9kEd3T1bRIYQLQPV1Y9d+QQ2DKTth9eiF+2WjjEqE9L2yYpI04mOkwUptw0y6FT12QaGOJCkyybWWlR0rfRzx8VWJsTxq4QtJdPBNRjHxY6sx7g+auEO0geSiZ2tV5LViD5MaUR41hOO+WabqGIvdnwAEzWETz5stMZK85mR1MUaqUtWOeRMMh6AjPYoKo8YCw1RuVVBFju2UcotnUtWDIu9qI4Zcp3SsAQskoi5mRhEd/SJ4zw50ppAN+s7vgHVOSttE/wcBDVUIUO8sTl+OnB9Q0ULvEYZySswQIcn/TM2GnKFVOnYNjUaTDIJjqRPm8kKhrwENrAtBV2QexE1pD9bIxOmOMJFiTgdgJHJdAq90I4cm0T/tS9J4tKIBekNjtvSIQEIG3hYorpD1BARK5M8h5t9PWc1tlJDFXIUVYBt/H0CblunEH+bbY3c/xPZsccey3/8x3+wevVqlFKpwFQmk6G/v5/+/n522203PvWpT7FmzRqGhobS3z722GO8/vWvJ5fL0dPTwwknnEC5XE73x3HMqaeeSmdnJz09PZx22mnT1Favuuoqenp6aDRaUV+Af/u3f5smjgUCU3nPe97De97zHi699NLN6vH4449zxBFH0N7eTrFYZL/99mPFihXp/ssuu4yddtqJTCbDrFmz+OhHP/qCbfL888+jlOK//uu/2G+//cjlcrzqVa/imWee4f7772fPPfekra2NQw89dFp73H///Rx00EH09vbS0dHBa1/7Wh566KFp516+fDn7778/2WyWpUuX8pvf/Gaz61977bW8+c1v3uz7N7/5zfzoRz96wXKDqM3Onz+ff//3fwfgQx/6ENtuu+0L6g+8kOkZC9AzFkgUdcNy9MxF4HiYgRUiZJRErcz4AKVGjdgaZrf1oPwczuI90DMXphGzdElfS5SykUTbqli8fg+vXxy3vHKERSJWlIjpJiRqaKJG65HUjTflsztNd2CG8hlVHsqRZMlAAWFECHQ5AV1OkEqpG6NwXYPjWEKr8J0Y34kJGi5KQdRIovhtXVLvoVUiiNTWJVHR5v9uBju6jtDExNYwI9fOjJxoWuBlxLH2MkL/NyXKbYMaDRMyQURkJd6cVQ4ZIwl7TlL+vhhsYIUCc2iVONC5InZsnWzlUXB9zLqnIAyoxnUyjidOYCiiSHZiUCKEYQiJWFmEFcXaRO+iqiXJsqA8CENctKia1jxqNQ+jFKYSoPycKHZ6shpgB1diB1dKlNsTyk+VKRCakL5Mp6gR1ytQr8jxI2tSeJK1sTg0WGKriK0iq1xwXbJoslaihKPVXBoxVJmCRGeTSLfq6BNnDSgRUSKCtrwIAGWdJPoq/VBNST5VjgtaM2EDVHsRD8kTababrY6LIFR5TCKlTWhZxicMHMLAQStSmkBbncCOrceObxD10DiS31VkQpgmzkYa3TEjXc0wAyvQ/Yulj214Bt09O/n+OZy5O+LM3RGlZdyRFQfaWbyHjKsn75b2yBTSPqYSMajm5MHJy2YNTBDhYGWbWSAz20kSeWULUZI8v8M+EEc4270GjJHrNa3QLisUTRGxJx7EPHEP5vG7MI/fJZMKx8UMrZ4+VvIdct/dpJzds+X3CUwKLyMrYlOPcX1xVBsVNpoaDS2OacZCw4SEGPLKQc2QCaZq7xOqyYLQWtJ0WHNFzPBqbBRIHxxem0bMVa4dM7hSJoHZvEwOhpOVi3pFxs/wqlSAj6gB2sFM1HA6Mjgd0pdNrOiJBeNurSS9ZqxlNMwyGmYZiX3shg2yglnslTJ29KE6ZsqWyaOURs/sThPFtUX67ZQtFfpKxMHSlaIolsl7FGMnRwR+VJuEakn6ctiAsEFUUYRKxOLs2DrM8Brs6HrZxpItqKWT3TjUKUNO08k3VhE1n6PDE0RWoYrdW3iLvPRmXsLtn9G2Ovf/RHbRRRfxxS9+kblz57Jhw4bNlFgByuUy11xzDUuWLEkTSqvVKoceeihdXV3cf//9/PjHP+bWW2+d5jSff/75XHbZZVx66aXcddddjI6OTlPMfcc73kEcx9NgJMPDw/z85z/n/e9/f/rdihUruOeeezjyyCM58sgjufvuu3nuuefS/evWrUsd5ttuu40HH3yQD3zgA0QJa8J3vvMd/v3f/50TTjiBxx57jJtuuoklS5b8xbb5/Oc/z2c/+1keeughXNfl3e9+N6eddhoXXXQRd955JytWrOBzn/tcenypVOKYY47hzjvv5I9//CPbbrsthx9+OKWSRKOMMfzrv/4rjuPwxz/+kUsuuYRPfepTm133zjvvZM8999zs+1e/+tWsWbOGVatWvWCZHcfhyiuv5MYbb+Soo47illtu4YorrpgmWvZizEwMplEtle/AjA2gu/rlc2lkCuSmgO+41KJAFECtwaxeJsd39qM7+yWyV+xCFbpR2YLARvKC5Y6GQ6LhkBFTY9QG8tIximwSZWzCcvBdSjYSOInvULERNQy4mkkbMGkDKsQUbQyuIxE9aRAcJGHXIkmdHSpiMvDJtzcolTJ0ZAImI5/JyCdfDAQGpC2NMIFQ+FmJfjWx9kmU0pSGkxd+gFaKYAqfepKNKcdn8vIybkKZckWUnyO2hgyaSdOgoRQlG9LQMJlsDlBToPMOuDJR0MVeUfUsdMvW1i1ObqEDfFGerUYNVLaQOEs+Kt8p9yqfwGYyGcZtiGpvQ7U32YCEgnE0rkGxQwBCkU1hBg2lcLoEuqCa6sNeJoVjQKKNoHXLYUf+plAXP9dSLs4VBaaVKzJJRDV2qcYuk6YBjkOI0BN6BYHlZLw4YSJpTRaIGtjJYYlK5oqpaqlyHWrKoHKi4GmDumxxlMBsHJn4+DkcRF0zSLhHmu2mcu2i2ZAtyP3OFqTM+RwT5SwT5Szd+RrjkU/GjRO1VTeB87QgOU0O+7IjKqX1qocpj7UcUNdvja1CdzK2usDPYkbXY0bXo2fMl8hzPVFBXr1MdAUK7bJCFNRkhcEKT7/KFVGeL9zkZWQrCQvMoKsYdBW2EWKqMT1RTLuxtBtLlxPQbiPi5x6CMCBe+TBEAeb5R9F9i9B9i1B+TtRRXV/K0NsHHd1Q7ISi6Aoo18faWFbwkmiwbVRSSBrWyOpfUwU4jmSs1CstJ7Z5r/wcynHJKzcZF5ZJLX1r3DQYNQ1suSwQl7H10vbZgmzNSLvWySQogd6097RgRo4r4yhXlAlG10xUV3+rrErLbyCdSCk/i63HmEaEaURUtKJSzjDsKFxfkovbjCFnDG06pE2HFFWE6p8pys7Jc4RaCTu6TrZaKcHhl1N2MQeJ6KdbGMgEMwygPIYN6qAdAixkfMj4KF/qr/IdAkkqdgn8KHnuhDUJIPiWRB04kygi++mmsgVqOGTaYrLFEEcbnGR101EWR8mqmmpvQxUyVJSTrkBstX9s2wrL+Seyjo4OisUijuNMo6z8+c9/TlubvPgrlQqzZs3i5z//eSqOdM0111Cr1bjqqqtS0ahvfetbvOlNb+Kcc85h5syZXHjhhZx++ump2NIll1wyTUwpl8tx1FFHcfnll6esOtdccw1z586dJuJ02WWXcdhhh9HVJQk/hx56KJdddhlnnXUWIFzuHR0dXHvttXieRHa322679PdnnXUWH//4x1MVYIBXvepVf7FtPvGJT3DIIYcAcPLJJ/Pud7+b3/72t+y7776ACH9dccUV6fGvf/3rp/3+u9/9Ll1dXdx+++288Y1v5NZbb+XJJ5/k+eefZ+5cSc48++yzOeyww9LfjI+PMz4+zuzZszcrT5PJ6Pnnn2fBggUvWO4dd9yRU045ha9+9aucc84509rixZodXQeAqVfQMxcRP/cgplFB9y8mXvlwK5GyvY+ubBsaxXijIpCBjTL5iJPkOKdvEfFzD2GRZX5Pu9BokEelsIGC9iiZkIaCbEdIbkQxgTCyAFAPKagMNeLpEJ1GREGJ01qxMe1OjK0FeAgVn2pvI28MQSID36i7+E5MI/KwRjFUz7HtrFEeHxQYw25zAiobXZSWaLIdXScOZaaQtom1IkRjRtfJS87L0O4XyGiPaiw4IzM+gF31BMxcgNVafl8ea2FTXZ+M9siiadcZdAwVEzDmMI0zvKHARgY7vArVt0he8kPyWRo5EhGt7jnY6gQzMp2ENk7xuGZwpSSPxhGEEcRlKLaTURpba62YNfm3gySarlBYY/ETdha/YUErzLqnUfmirCLUK+KgAnZkDXZiCDJ5zMAK+jNdBDaiL9OJnRAmDzsxhGrvwY6ta+Hzw1wLTgMyGajXaWCI0JgIujP1Vr+cTCLokEBHRhNMcQazCQ+EDWMR9JkqYpUkeWNiaOsmo8S5NwjTSCpAZWJImNltmDCABzVsuUqURDJd11BXmoyXROjDQK4VRdhqApfJBynBpUEJg8noOuIEoqK752A2PIMJajLOVj6MqUgCavycrPqZMMCZu5Twgd9LxHnDSozj4izZE7NhedonyRVlJceYJAdBEZTlda5di5OUZEAbiAw2EuhHs7/19lQoVD1Yv0r6abUMYYjNjGMyiZP+zJ8wjgvrVmIKHeil/5KuFgCYjSuwSgssb2ydTKhyRRlHzfuQK0qkOA5RuSJmcnD6WAERh2veKy9DFpeMhdU66Y/Kpah8mQzW6jCyUZzd0WHsRAKJChrYiWGYtQjV2S+JyOMDMnZSmNFKVM88idSPDaB7JNnUVgXaY9Y9jeqcgR1ajW3vkQlsHIGBxmqBcMUKqg2PEc/iunLeoo1wlKW7KP0pijT0zZGAAKCUg22UsZMjaR0B4oEJKrqf9jgiYxV2fGC64xwFUCvL/fazCYRGtSRXjU3HPnGYrOK0hNzCukOxeWxQk75tEvhSJoFWJdCoRlmYhRwlz0JjFV5ChZm1Cluuogo5OmhIuf4OZtPRtNX+/9hW536rccABB/Cd73wHgNHRUS6++GIOO+ww7rvvPhYsWMCTTz7JrrvuOk0Ndt9998UYw9NPP002m2XDhg3svffe6X7Xddlzzz2nQXM++MEP8qpXvYp169YxZ84cLr/8co499tgUbhHHMVdeeSUXXXRR+pv3vOc9fOxjH+PMM8/EcRweeeQR9ttvv9Sxn2qDg4OsX7+eN7zhDVus54knnsgPf/jD9P+psKJddtkl/dwU9nrFK14x7bvBwcFp1/rc5z7HbbfdxsaNG4njmGq1muYpPPnkk8yfPz917IFp7QOkycJbUsLN5eThW62KR7zTTjulUfz99tuPX/7yl2kdrrvuOvL5PHfeeSennXbaFuvetEajsRk0SvfvQCYjibTxuqdwFu6GLY/J5/k7Y8aEMcSUhhmojFHwsrRn8ui2LtQrD5bkwOTlHK99Qk6asOU0rY7F75OXuf+swzzHpxBDbcxnXMV0EqXJrfjyWOrCAzfAYunEQ3lO6hp2Kp811mFpLiBGVBTN0BgjTgc7JAme3XOqPPNUJ4tyJSoTGbadNcryDd3slJFyrX+inWJHHaUteT/Emb9zgrufEPgEpP87i/cQjHS9xHBtgozrpWw5um+RQEP6Fkmd65VpCacAgY2oJA6kby39ToFZUUtAZ60H7RZsZMUBmRiUyGnPXHFqAaU9VKEzxeSvr49grU0ZZXTPvBQaQhyjOrtAa3I4LZwuwt+dMzDTLUC1goNC+ZogodFUgBmr4s3ZXq7VPQcVNtJz667Z2LZuzOg69Nwd2VAX3P1QMIHqnCXnKPYKc0pnf4stx8uQQ1NwxDlo11nI+OTRdMYWE2pKgZ+y5eiOvrRuINhs4hBbHiOvEm7yWoOc1RAZmdgkyZnEUYszfOZiiBrUk37hYfGycQrdkSj/lEXsOJKsU62Y2S19ZfVIB/1unfFqVuqmdJrkqrKyMqVy7aA0xaSps/kwZcQByd9wFu6GKY0Qr3w43WdG16Pn7gjIRDF6/HbUjJkC29nzUGytRLzsjulsOY2K5EMENZTSZJShMDvJdzAQb7D0h5Z+FDYwmDqs8dyULScz3E1dabZ91SGYgWfRc3bADqxAz9o2ZRli8VK5xrzFqI4+zN03QbG9xZbzqiPSyLQzY2dMdQIqE+i5i1tMOJUJ1IJdZKJSHm2Nld4FrZyIWim9t1hJuG8zsG3invzWRjhKMdctQiGHWrQU1bcIs/IRVJc8q215DNXRJ/2tOiErL539MrlMoGGqd4Ewy+TaUe29mHVPC1vO4ldKP5m3o5SlZ544zclqgu70yfVI/+h4wtLXV2LHwRzVik8Ua9Y6GTxrKU1IeWOl2ObpZbivOEDgQa4vqzQdUtYmW467uJ8ZccSo9qgrhZ61bWtymuRB2GoJ3S/tDwnEpF5P+36TTUuRg+rENHXgYn+DgXFZxSHfIf3dy4CNWyspfo5sMlJMrCVirw05L6IWynmqSlj07egkoc214EEvs5mtvv3fZFud+61GoVCYBl3ZY4896Ojo4Pvf/z5nnXWWsGCoLY+0F/p+S7b77ruz6667ctVVV3HIIYfw2GOP8bOf/Szdf8stt7Bu3Tre+c7pNFtxHPPrX/+aww47LHV6t2R/bh/AF7/4xRfEo0+dLDTrtOl3xrQcjWOPPZahoSEuvPBCFixYQCaTYe+99yYIkuTBLTDMbtpWPT09KKUYGxvb7NjRUXHoZswQxc+bb76ZMAw3q+cnP/lJfN/n7rvvZu+99+aqq67aLIdhqn3lK1/hzDPPnPbdZ0/+IGeccoLAORLssWrrQiXReVXolAPjCE+7VMMGbV5WYDmDK1FdcwQyAiID73gCb4gCYVJpsuVUpf1KNkyhNNPZchIeaFdTs5FgbD2Xqo3FmfNdyjYRk1EOOaNStpymSU5qi8PZs4YgcsjmQoKGQ1bFNCJxDHPZEO0K/jqKBbusMgV5qSY4ZpUppAmCsm8MR2kaUYivk8enMcLYEdTkmLrAEpqJfMQh1lpcFBUbEgNVGxEriQRCojDJFLacTAI3AFTzhe/nUEhiavPl3IjDFDpkjZFjHVeW7pUGz6NkI1Q+yQ2gTk1LO5VMCIUi0Sao1IZSCVtODqsdgU44bhrhnMrWAxAZSYm1SIJf8xjbqKTMM1iD8rNUiAmSaHhVBVtky2l3m+w7raRYHE8mCY5AEdISa0WoBLIl7CKhBOGbbDlJ++NmJJptbZpomsKGpkT7leO1WEdyWapVgWm0ewHl0KPNE4YftJaIrHams+b4OapaVkcaNbfFiIMkrNvyGLrYg6lMpPtso5q2re7oE6rMjetklWFwJXruUshkU4dZZQqSjJrAvwgbwpaTVEOi9IpxRyVMKdIVcgaSXHIKNhaGlo0rBeYyuFIoN4dXoTqTVd3KGKqzH1UaFucylxfHvgm/mTpeEkYcW5mQCUfSP21lokVNWZ2YNlbSPlSVVT7l5LBRgIemqgWm1rRJEwj7k7Gy4jI5KPCTvLQtQV2c5iZEys/JpC2TwK4QBhyiHCqTx9Z8yLWh8sUWba0bgE7aOFuQ/uS4EBlINC0aShE0XCYdlUbuM4HEmJtOcmwVKp8XGFUUSP8LaoKLT/qJyhSgEWDQIuillEwomn3RxPK7KBDnvdABfk6emwnkTiV9WCUMUvhNRi3ps3FDpQ6eUg42wfGn8BwkibyBItMW43gWNZKIiRmVJtQarNSnVhe2nK32v8K2OvdbbTNTSqG1TiPLS5cu5corr6RSqaTR+z/84Q9ordluu+3o6Ohg1qxZ/PGPf2T//fcHIIoiHnzwQV75yldOO/fxxx/P17/+ddatW8eBBx7IvHnz0n2XXnop73rXu/jMZz4z7Tdf/epXufTSSznssMPYZZdduPLKKwnDcLPofbFYZOHChfz2t7/lgAMO2KxefX199PX1/e0NhGDlL774Yg4//HAA1qxZw/DwcLp/6dKlrF69mvXr16ewm3vuuWfaOXzfZ+nSpTzxxBMcfPDB0/YtW7YMz/PYaaedALYIzfnNb37DD37wA+6880523XVXzj77bE455RQOOuggZs2atcVyn3766Zx66qnTv3z2zoRPu47umYsZeC5h9JiNGVrdYhMpdNDmZ1EohmqT8sIaH5KXY9Px6OjDrl4mL2DHJas8qNWms+Uol7qV5NdsMSQzKWw5CxKPzdZDcqpAiQjbCMmrLGViqIfklfS/ko3oVGYaW45uL5A3UDbSL8K6QwaLtUqiUoFDMRMwUJdI65yOiVQEKDZa2sAKDjply0n+NyNrhSI0K4xBrnaYbLLl1EqSLNk7T5yXtq5WtBpxxjLaw0PRpn00ULMRZT2FzQKBymCsRO07+lBKY8bWp86WUhpTGkb1zIWgRqfXxlA83mLhGFsniYbaAWOw1SqqrUheOdhqk+FC0R5DTUOszDTHNmXLacJyhleh8p2YiUFoVFAFmcDZiaGEirATOz5AV6ZIIw4oevkU6mLHBxJ+87EWg42JyeLg6SnL+rUaIVYmOg1NX75KGDXhWRVxjkwsjng9mSwoLawhSHspwNaFmYapFKX1Fo86joevnLQscainH4sk3hobo91MypbjOnJ8LfAwKBwtUAilE1pB1xfnFGQc1EriRAOeH0ufSlawdPfs1tiaMV9YqRpVYctZ+bCUNaihZizAPvWwOIfjQxh/Jc6SPVNYh61MTOtjKpMXVd2KtImTsXjJhHlSy2qQNaK2m0nCoRlliKzGjm2U5PcwkD4TBul4t2uexiiNHVqHyRVR271ScjoSXLotj2GRnAJbmRDIWHLPbSzkA6q9R2BrcYQqdGEbFRkr3XNAJ+3WnBQkzD8+moyBwWRZK6M92rUv1K2NBlQmxVEdGUjHKXEkk42e2ej2Pmm7iY0SLU8cWTO2XggCmmw5+SIq256yMNlkYmNLw+AlOSNBDeU5hBuSsY7koU0kbDlaCQ2vZy29uQSWE2vo6hboUNTAOp6MiyacJaiJkN9YmVB1yEqStdhGdRqDk21UIIqSiUEpYYnaBJbTtOZkNg6xU/p1tjkLbuaINB38ZNXRRgEuENa0iIslsJzY6BQUk7MaW22y5TRS9quX28xWWM7fZFunYVuNRqPBwMAAAwMDPPnkk/zHf/wH5XKZN73pTQAcffTRZLNZjjnmGJYtW8bvfvc7/uM//oP3vve9KYTl5JNP5qtf/SrXX389Tz31FB/5yEcYHx/f7FpHH30069at4/vf/z4f+MAH0u+Hhob42c9+xjHHHMPOO+88bTvmmGO46aabGBoa4qMf/SiTk5O8613v4oEHHmD58uVcffXVPP300wB84Qtf4Pzzz+cb3/gGy5cv56GHHuKb3/zmZuX4W23JkiVcffXVPPnkk9x7770cffTR0yLqBx54INtvvz3ve9/7+NOf/sSdd9652aQF4JBDDuGuu+7a7Ps777wzZe/Zkk1OTnLcccfxiU98gr322guAk046iZ122okTTjjhBcudyWRob2+ftuVmbSOiTXFI/Pwjwn5jDfHKR5LlcmEDMRuWU00wnguKfaA0zvZ7ofsXY5OXimk69nGEHR9K8MuBsOXM9vBme/ho+nQO30IUaCaUsOWEdYew7mBjg4diNhmIYjw0s/CxYYyPxkczW2UYxgcjOOJYyTJ1rKDLbdDlNkTVNKm3dgyZbESl4dOuQ9p1SGUiI1H7hoPnxikXtxlc2UqCbP6fRAXt6PoU7z0z38XMfJc4WF4mZXIxgytbyXBhkDogFUwqK9+rc7THkDeyhQr6I9ECwHGTROX1koS55gnZRtYIa9GKh7H1EoGJaPPy2NIItjQizCMDKwQTX62B60CjLjj3MIQwRGNTJpIZOgelCbLKgSlsOSCwHBxPcMhKknzNuqcFypBwZdvVT0k00RpmZ3sw1mIrYwLfSdh0AGxYE8xxo0IGlbJwdDo5sJZ2q8kK4x/jtUy6H0+49lW2IMmXHTMknyGsUSemTgyei283cQISSsBmvwVasBxHtA6sTZzT8pjgxcc3SPvWq5ihVeLgTUlMD4ym6IY0IgdbGsYMrZLjNj6PDRuyjQ1IBBvIWoNSpOJUAPGax1tj67mHZF8cphAdZ9HukqC88hHIZLBRgLO9jO34gV+1ONxBWKmaEeGSOP1OzuLkLGioE5M30BeBt7iP7I5FNBLtVUDdOoQonF1fD0EdZ8d9wBq5XhTIlmub1qzmvt9i7r+F+IFfSXmSlSUztErGi3IwG1e0ElwdV1YeuiS4YTYshziSyLHfgiLakTXJ/Qqxk8MMmhqRgg6r6LAKheL/Y+/Pw+2oqvx//LV3VZ064z13HjKQhEBCQiAMAiJTAjSDoF8ERBpQI4rip3HEoXlahabpRm0HbBG1lVFpsbXRDyIiyiDIPIUQCBAy5w6583Cmmvb+/bHr1LmXBKE/7YC/znqeeu65Vbuq9l61d9Xaa7/Xe1lIumUW0dUNQiKbe8w5uSazKWVgbE7G9NF4Qqc2r0lYnoTtEm1ekwTH683rUL0vJv2AVAbVtz5JTqYr4xD6RBMedmsKuzWFqzWWVMwONVEgCSMZ04rCUDXLUDXLiJ9GrXsB4aSSoFyRLSKaOs3k23Yh8JCzO7Biph1nVyu9lmEqSpi3otAQZ9YTGsg4Tmh8wDA3jcQMOLUpdG3KsN/Eq4NqcJPpqzs2o4d7UTs2oXZsQpdGzXiIJ32+MnSYllQJMYEECAJU34iZT8QrA39q0X/E7X+j7Dbudwt33nknPT099PT0cNhhhyWMOPVA12w2y69//WtGR0c55JBDOPPMMznuuOO4+uqrk2tcfPHFvOc972HVqlUcfvjhFAoF3vGOd+x0r6amJs444wzy+fyMLK31YN1d4eVXrlxJoVDgBz/4AW1tbdxzzz2USiWOOeYYDj74YL73ve8lXvz3vve9XHXVVVxzzTXsu+++nHrqqaxfv/6PqzBM4O/Y2BgHHngg7373u/noRz86Y1VASsnPfvYzPM/j0EMP5QMf+AD//M//vNN1LrjgAu644w4mJiZm7P/Rj37EBRdc8Kr3//jHP06xWJwBsZFScv3113PPPfdw0003ve62qKGths6u2IlINxENbDC/863G4KkzUmSLZGyTkEkgIAqJXnzEeOLa5iLb5hpminwL5IrgpEzQZjaLBQQDAcFAwLCqMqxq+AKkpUkj8bTESUcxFlowqQMqmA/YVJ0tRwrGtMeY9igR0Y5vPMwCpAaRcclMQ5iMDWXpzlboizIUu6sMjudoby4zqF0GtUuxs5qke/cC23z0tQKvljAIAcZAH+0zhlRlAktKA7MRFrawYn7qwJxfZ/+owxdSJtGMQpNFMqUCqtKw/pQlDFlmExjPvZU3SZdEU7uBL9R/N7U3kvTkmsyqiOXgKd9AdGIYhCi0Jkwv+AG4acOWU2xCFJtQGHq8SQkjqgb5AqHWZlIRiycEVlsjvkYH1diYMJSodd54tILqFClp2pfAlCBJfqVDzyThcvMIN8cEIZPKYVI5lJQHQuALTUWSsOWkUyHpVJjkUahDO9RYX4xxLxBoTaANW05ZKGTBrB7pmqED1F45mXDqykSSHAkgqH/26sm10k0GupHKxEmOMgaXncswUMoxUMrR0zrFUOiSTcVe0XosgFZGF/VETG6OiXhOUJlKocYHjNGZMlhltWNzwiqlxgfMhDKVIdr+PNH257HmLEW09qArFQg8ohceQjZ1Gnaa2GjTKgDPsKfgGkM61ILKkE1lyKY2aiEQ9Nuw1cHwqU9UWWCVmR96zA89evIlupwq0dr7wfOI1j0EtYq536zFyFmLTQ6E1lkmcVtTJ6J7NrR2GMacYmuD39+vJWNFe1WzPzZAda2MGtlu+kPgm9WY+jOJ9VaHwNWTSBWkw4gFY0IzJgzca1J5jKgaenQEqiUzUQjDxgQuCo3HOgrBTTdgJy1dDbacOnVmzKpD9x6Itp6G8Rzn5tBeySSDixPGheOKcNQnHPUpScHIeI4+W+BmQtx0SJsKaNYBrW6NVrdGs+0j5801k4bKhPlbM6t7amADenLQTDx2jDIlDVQwq5Xpt3FCwXouCSolQ9lZmQAVmXfi9GRyjgu5ounDhZgyNk56V51wyEearNKNPvqKBFTCdqlgkcpFuPkQRxp/eTW0E7YciNlysikmhJOsfv2p5dVoLf9ftv+NshuW879MPv7xj/Pxj388+f+GG26YwQLzarLffvtxzz33vOpx27a56qqruOqqq17zWv39/Zx77rm4MQ83mMnBxRdf/KrXHhkZSf7ff//9ZzDxvFI+9KEP8aEPfeg16wEwf/78nfDxK1as2GnfqlWrWLVqVfL/gQceuBOV6Jlnnjnj/0WLFvHAAw/M2PfK6+6zzz6ceuqpXHPNNVxyySUA/PKXv8SyrJ2uN12uu+66Xe7fa6+9KJfLr3rerqQeQCdqk8ieRah1Dxq2nFn7oF58GKaM51m0zqIr04JAMB6UUJODsPVldOCjYliOnLvMnAOgFY6wIAjIaEEwZYyqvEwxoTx8AU42oqglZWHhV8zrSAcRTcJkVjW/bWootB/RLIzXqEqEa0foWmgyb2rATZHWUbKcG0YSx1bY2iRpGRAui3qG2F42S+sr5gkmXzS4/0gL49WKaS3ZsdnUBYynamwwMRg6UkVc6eApY+ipoS2w+SX0rJKBC1g21CcKAJaDK2yyWlKQDjLS1HTIhGysLGS0MF4mX6F3bEb27G0M1KGtyNmLTV1qU+iRfsPoMT5It1OkFgVJMiDdvxExZ5Excj3fQFYqxpOsvTixDQaaEUioqQCUQgqBDsFNGS93ytdopdGb1ho+8P6NMcOGgTPpHZthcgwcB927gZ5UM6GO6E4V0SN9pkGTo4a+ccfmJNV93dNbx7yHWqErBpajTHehYAdYMRRGjfUl0BqkRE+NGcrKbKHReetc4KEyz6Ge2VNKKBuMs66WQJskVmiNj0RFsgHbCaax5vg1w97ilQ1VYTwRcNIRFWnhpkMDZalVkj5OxQTm65gqNKIR+6GHtqJiOI2oJ7HySlhzlhI+9ztDldkxz3jrgSjwsBYciLrndsOesm0jkZDIefuhNj0T11OZPhkzE2E5RIiEbcqvyIQtp1cE6KqPqkRUQ5taTAPatU+JYEqgN79sjOSJcbO6MzpCVH/OL79IlM6it2wiyj2B3PfIGQai2rTaBBY7KdgxYTDuTqoxjsAYy/0b4yDllHEWbH4J3T2nwZYjJHq8P26XS044ZBRslWZ82cIiJx3Gohq6VIbe7Yj8OHpsHMZjWE61ihgZRM0uIVq6jDd7cgQ5e3EDKja0FdGxhzGcR/oRc/cxFJUxq43e+qKZtEyOQluPmZhHITqESp/Rmy+gFDqMphR2KkIITWu6hiU1mYwZY0FgQfdc1GivWaVQykw8RgwxQV03Ye8UJatISkUEkWzkTKj368CHqUkox++VpqqB5UR1Zqd47NfjCzBB23VoT63mUFSRecdUS6bPOimolBvQq8o4kRDUJg1bmS1VwhBVzxOSQqAnS4iMS0GHjcnYbnlDy27jfrf82WR0dJS77rqLe+65Z4bX/3+7/Ou//usM/v9yucz111+Pbf+Zhuek8cDpgW1Eax6G1nb0YC/h6ocQxWZ0zLmtX3yaZitL3nLZ221Hv/SUycRYLaFfMh+ucPVDJsmKNFCQ/Zw2wmc30qK6kLGXfD/ypGWBBZ5iYiCDo6GZBk7U7/NZoF1yCoK+GvN1B1kFfl/IQm2W89MahoOQ+YNjtEXGOxOs2YarerDiQLfm5iqbB5vpcqpMDGbYNzvOhhfaOUQYw2z7w1ksSyEtTcYJYXwYfM/gegtxAKrvGaMnm4OJcbTn0eEUsIXEjQ0lBntN5tOJUahWDD3iK57dUqeVghLsI/P0RD5HO+3s6zXI3sYsQU5pvB0at28r0cYXEY7ByEYbDeRMOI5JXPPS84h8nrxMsW+mB7XmfnORWhW1+WWzmrFlh2Ed8nwO0FmCtdsAyKge8ihaI8HR6S6ix59ioc4QVmKjBCiqCG/dJPaBJfTQDkQuD1qjB40xKfJ58Dz01BSipYWMcMjLDBUdwoC5D1GEHh5C5PPobRvNPstmWeTSIk1/OszpRG0bZM+wja5QMbUjTaQFpUqc+GrT2oYC67j9sSGolFmGMUCDZzaxZ9iDt6mKPdg7o7yeGDf1LTajh/rZQ2QIn9tEiywQhrKht6DR9/TkJNp1EY5DtGWQBU3Gm7ylr4X5dpmxyQx7DGwz8Qy2yXhLaIwtkc2id/Sx0DeGViYbQK2CHuqP2/M8pDPovi0ET9yH6OhC7+hFv/B0knBMbdmAuud2nPd/nvCB/zTjq3cz4ZOPIuOkg4bqNDDXjQ3FrIhIZWOjT0WsGHdpi0KWA97GGt6kxRApAml63FNPdOMjOTabRXseIps1enBd9HNPxTrUsPVlo/ttGwl+8xtELm3gXoBcuhSqVQgDk3TLq6FrNUSxuYHL9jxzrGomnKKj04yV8ZGGIRsE6JEdycRhFi7zfUV3nM255rYxB5es1US0eQB7/73BiSErdeavKDLXHdmB7ttq9Ol5RC+shZS5jsjlUVs2mHFUqaBWP4VwU4hZhnaYMECPj5nnOBbHTwlhgpHbjW4XbA5Z0DnGUYOtTIxmiJRkk5/DAgqVRvzKnJ/+HPuEo03/EMK8R+oe76F+9FA/MmuxJKoypRx8JIwONvqibUNpCjU4hOzsgLEh9NgQXcrCf2a7aXJFk9vnGfP8LAtdKpnxFr97im1VnqsaqCAD280EXwrw4kkDwNgQRUIDiQws/Mgi0oKMHTYyeQPBy0NEJYUtOtHPPAYrGpDaP5Wo/wZZx27ZWXYb97vlzyYHHXQQY2NjfOlLX2Lx4sV/6eq8YWTevHl85CMfSf4/66yz/qz3tw838CkdJ28SmYIxjqoxS0Pd8+XXeHTkJ9jSImOnsFd81cB5mtoTb1GSej6VAa/MU1/+Fvab9qP3t6Ok2s3L+rmNZVJI8k6WgzMhO6qRSV6UjwM6Fzfx3PMV8paNu7iZ556tUrBs0ksKPPeSMcxz0mIvYeMubmLL8xoJ2HOb2JKStPvmYz633WNqyKbdNvXP5H0GSjkKtqmrFJpswUdITaWSwj7mXcYD5leNDiD5HzA68co8+Mn3YQmJHbPh2Cu/hhrZ3ohPCLyZ1IqWw+N//3dk3Tm8rEocIppYwxSz7Sbq7J9DNrha4PYI5NGnm6DNukeuHiDnuAkUQmSbeXTyAqqhj7XiX0xdS6NxQiAJ3i2IQgFaWnlJPo2zrzFgyr+DmjSTodVqDOuwI3julsdIz3eQW0xlxqSFuzCLPPI0qE4hCm3Gg1kPms63GlrQqWFEcw+PTfyctJ2iFvpYK/857itV04ZccxJQKlJpXra+wiGRuc+T4TDWAcvYeMcAGW2Ra/XYMZInZRlDyj7qnYlHUli2CVBUEdqvsVVcZcos7KT3AU1qTgp75TmN1RKlTDA4IDv2QEchL6hLsJfMo3zbJHsUPawVZ5u6euWEFlP1r4+ZYQrYwyM4D5uVCKVJPJrWMe9MoD51SFb9mQCMWteQVcazax/6tqROelogop4aNpAXpRqsKmCgSOMDhA/8J/ZRZ6F2bDKsMP3rkfP2b/Sp0DNjrM6OxKWk2xsc6b/f4XN0PA5S3TYQMmFJynG3LPjCsCItPxJRnTLBz7VJRK4VHQeYUpkw9JHDWwydaOs90NSasDNZiw5N6i9ShulG+1Vkttjguferpt/6VaiVTSBxfazUjd14vGmtEEKy8R8uYbGVT+BNT9f6GUu1khE29rKFyIOPMoGvQ1uhEK8K1coNSGDMHqNLoyZ2oJ6YKh5PIpVGjfWhxwcR2QLW3GXmGU+NgIoaTDlx8Lb72DNJ8OrEUxbS0gzYNnvEK0wlS+JonVCgRgjsQ5ZhH3GG6bOWbaiC6wH2hXaQEvvFl6gqxYS0qUjReP9ggud1dQq2rjVUmE3tCMtmq7yU1EF7mD5UKmOtOMv0xVSmEYgfrzBmbnmYkQHzzpVHn46uTppMwbWpJD5I5Fvx9L+QbfYJfclYKYMjVcKUA7DZVjj774FTquA9JpGH75pq+o8t/1ux8n8s2W3c75Y/m2zevPkvXYXdsgupGxaq9wX0SD/W/itNYOxIP3LJW9D1wMjJEZrdHMVUniY7gxraiuwy3O7R5jXmYsN9JrtmrgCVMvOcZtSGrWR1AZk3r5u5IkOLljRFoJVAAWkZEVTN11yNVegSnRS1RI2N0UV7/LtKtzBGd5OWTEqBGqvQpIsm223JI6MLCU+6CiSyTrmpBalsRFlY9GQNjGKinCblhliOIu0GqMkRAw+oVRB1nvv6/10LTPCaX6Ur20LGShm8PaAGN5ssnJaTlKFWaRj4QjLbaTZBwjKDRLOnyFGMNJnYwBmyLVoiCEeVCQAc6oV0FlFoMb/BYImFhPFhdMcsmlN5Ol0btSXWvVLo0f44ILcf0VFDjI0zW6eIthn2koxqI6UFltYsTTeh1r3AXJEhGh9DKWO0pbXG21DBGdiAnhxBdM038IU4MFh07GEMp+E+0Ir2dJFWO88OfwLV+4KpS2TYa0T7HAPLUArcND3aJu2YCdo+ogXdN0CnsugMQypjKUItKQdxUO9oX4LD1lEQs+8Mo7avIx+vmqjxEh1RkXDYT4x506c9Y/yB0cfINnLCQVeq5GSIV3ZQ28zKgK5MJYYcg9sT2EH4ci9OTDcyJWza01VGKxlU34sGIhTz6ScQh1QaypO0RBEi7ne6NGagKJDkS1Bb16L7NyHedJIJdBwfagTOvvwEbNsImRxqxyaT7Orlxw17TqHdXMczWVqREu1VjaEoVYJQQkIBi2IUkRfG4pRpE9dRT2I1JS0CIbDmLCF8/JdYiw8nfOa3WHseTPjobY3+pjaZAEwhUc8+i2gpouNVBtG1wCQt82sm6drINqO7WYuSZGbUKsjZi02/KE+SZKxVKkmOh18zcJF48mMhcLWmM54f9KSKzJZZ2rVtzovzUKgdW5KVLz3ab2JjalPosQFj5Ac+un8T1PMQdM8zY6nQbFZU1j8P2SxRXXF+zTARtc9Bjw1QzzytpjxE2o7HhsLJROwR+niBTaRMDIvUghHZYG+L1q1HHj1iJubSQntlZMxVr6eGDeTKtnBESEYppBao4e3JxEpYjplMjw1C+1z02ACqMk6ntlDbTHyD8kLU1ufiYOA0TAyji+3JJCKqGXiY0KC2PW9WWC3b/M03m4qm0uRkyNRomsC38JUkbUXYlkIHRrt5LVD9I6iJKg6tRqe75Q0vuwNq34CiteaDH/wgra2tCCFYvXr1n+xeq1atmhHYulv+/PL5z39+BsPNmWeeyde+9rW/YI12y27ZLbtlt+yWv5zsDqj9n8luz/0bUO68805uuOEG7rvvPvbcc08+9alPcfPNNyfHW1tbOeSQQ/jyl788I7Pqn1Oq1SqzZs1CCEFvb+9rJpB6I8j8+fN3Cij+S8uOHTv4xje+wZo1a5J9X/jCF1i5ciUf+MAHaGpq2uV5d9xxB6eddhqPPPLIjFwCX/nKV/jiF7/I2rVr6e7ufl11qEM95B7LUDH0Qy44AJVKG37zWXubgtkCkVb0loch147IFIhefhyRb8Wab/qhSpukNiKdQ48PMaZqyK5ZBMInGjXwhSF8asKmO/Z0OQhCLbHdGLucshnBRwmTlXaUwPxOSYaIg9aEw5GRQqQs47UHSDt4AqbC2NurwNKaMJLk0j5+xSKrFTXPHM+mApy0uWe5mgKtkB3zjMe4nvW1c4FZwq+MG775sT6qocekX6aYMlSBIls0gZ5RaDyKE4NQnK5gRUl5OLKJUe0T4DCMjyfS1KbRLVYk2K3S0OW5uTiTZdhgwqknAiq0IJo6qUUBI+EkonOBuYBXhmzB0AE2P4mwLURLMyOihNXe6EfjlsDWgj5dQXbPZoItCLuBby1JSWp+GtE6yyTcybdCtpjQF4pCOyKVQfk1RLqJUljFEpJyWEW0xvhlFRlYR64V2mJYUyrDmIioxPofcKqIfBcVUWVKWuTafLxBSVuqlpQnpl5NklhJiWht5HAQUlCWINMmoVN9FUpYNjS1xefayNbZJshUaarKxrIVot3kjhBeHGCoFSr0kR3zTLszKSpTph+0CZ+JSpqUjBAtRi9Jfoc67MPNo7MFSlKSV4rKVMrAVGbvY7rB8Hb05LAZW5aNrk4h5yxFpTaZ4GHA2vtQ40nu3ZyML2uvQwgnRxoMMK2zGxmMm8zqQagkahr9eIhmzLIpa8sER/uQVxoZY+5bVERVSMIXHjRBwC8+DFKa++17pKlvaQzZvZCIh7H2OsTEDOQKM6gQ6+ODKDB9f2Q7qMjoELP6oisTyJ5F6MFNhsnJzUHoJX1FTwwmNLREIa6QlKTxiANUlM+Q8IiEhpqBvKmR7dA+K1lhQ0ozDrQybDH1XBVuupHoyk7F46rZZK7dax9EtohsM7lWdGUC0vG4i1fdDC2mRsb4b09IyuMpdlgO3U6ZMJI0eRpLawpxBmSNwFoSvzNDP8lkrEYMVr5Oi6nLVQQGHuVJYZhupq32EcbsPX7VnFNopyo0Iu/GTRaI9jmGLSeVQadzBq5UDxDXAqFj731zZ8IGpdPZhKJVuHkiLcgWfKJAMlFJG7Yc38GSceA0IDubEbZkVDhQ9/r/iWV3htr/mew27t+AsmHDBnp6enjLW94CGLaYk046ieuvvx6AgYEBPve5z3HqqaeydevWP3SpP5n813/9F8uWLUNrza233sq55577F6nHH1uiKEqSeP055Nprr+Xwww9nfj1YDsMGNH/+fG6++WY+/OEP7/K8t771rbznPe/hPe95D08++SSu67Ju3To+//nPc8MNN7xuwx5AbTAJdMjksfZ6E9Ez90A2/v3c701wFyB79mZBvhutNRtLA6j+9QYu0NJq6BkBuce+6A1rjbGdydAm06jBMdqjHLUho9M2HKaICIFMi0/LmKRfpJgTs+VE4z4dpJggJBrzaKPFlB/1acMYhpOEdOZqhIMeGW0ygspChmJkIBQAU6NpCsIEhmUiweBQgZ58iQ1lU9eD9xzAK9tYjsKPLNSGpwwP96y9zG9I/tdbnjeY4I65zM124AqbPs/AVKKta2H7BmjpMMZFz57owa0NTHE2T7uVpaglPSKNBHytGLahGON0pYaSAFVRqJceRy46xHDGb3keuegQII5n2LQWuegQ1NAWFme72VQbNtR6gN6wBrHXAYZXvlxFjU5iKU0Ri2gwpi2knc5QMSUlCo0ulchioSqaXN5Yh03DESiNeuoexJ5LUeufgPERxMIYm7zxKRjqhzkLUS88ytLsbPqCCfbMdqP6XjK36d1kzh3ebuAYUkI6S17LBM9rC4kaGiXCOAb8ssUeLZOUy3GSpL71Bs+eJOiJaQ9rFVIxIEP7hi0pnFREW9bMSMqVsOVMjoBStAjH6AUH37MSvaGiGILhmgRJOoLJUYJtU4Sh6SspK2IicGlzfMMupRQQJyqbjGE3+WYojeNobehZLW0YbmKjXC44ALXuIcg1mbG19n5w0+b3E3eavlRoRs7bj/DJRxHx+AonR7APOqkBl4lCRM8CVJ9hVxH5FhRQGTL3cfMRWQzH+Q5LEI1HBGUZQ8DMGOxMV6gFNvqZx0wAaaxjrRRRPYHbujWoxcvQ659Hl8awjjwd4WaTzMvh47cbesmePU07axXEnL3N7xhiI2bvZd4vgW+ObXt+xlgBEF3zUNvWmbGTb6EFh6yCDTGGqJUs3SLNqPZRQ6NYG19A5wvo/j7UhufjfuAhss9CUzNy4YGoHRvQ/ZuQex2cxIro9U+acTXej96wFrFgqXn8w1vM8ZdWI/baH/XS48m4rcdJTK0xk8wIqFUdBmzBQTFBQFFF2Ch6mgzcL4okzNvLQJHqMRFxXwTQ6Sxohf/CMGXdYzLbKonaurbRf6U0dKcjg4ZFK5sHIclriS6ZuigvTOIKdOiZsTI5aCBj8Xhqi+NbqEyZyXGYgqnxJCuvip91adwlDC1sqYjivBFObNy3KYEaHEcWMnTgw0QjWeNueePKbuP+DSarVq3ixhtvBEym2Hnz5rFixQpc100Mtu7ubj772c9y9NFHMzQ0REdHBwDPPvssH/vYx3j44YfJZrOcccYZfO1rXyOfNx7GKIr49Kc/zXXXXYdlWbz//e+fQc1400038YlPfIK+vr4ZNJVnnHEGuVxuBnf6tddey3nnnYfWmmuvvXYn4/65557jM5/5DA888ABaaw444ABuuOEGFi40npbrrruOr371q7z88su0trZyxhln/EEGnd7eXj75yU9y1113IaXkyCOP5Bvf+EZiFK9atYrx8XGOPPJIvvrVr+L7PmeffTZXXXUVjuOwYsUKtmzZwic+8Qk+8YlPAAb+dMMNN/Dxj3+cH/7wh3zmM5/hpZdeYv369TQ3N/Oxj32MX/ziF3iexzHHHMO//du/sffexiNTP++GG27gM5/5DFu3buWoo47iuuuuY+7cuWzevJk999yTxx57jDe96U1JO775zW/yla98hc2bNyOE4JZbbtklbefb3/52fvSjH72qcQ/w9a9/nf32249LL72UK664gve85z287W1v413veternrMrsfZbYfTh11Aj27H2X9H4vezoRrbW2hQvTmwnZdkUUhlD11hoNxSHsYdVTwzC7AXGc1+eoDecQu65lG32KOkO87EY6wvIxJjp0lCaERHxZh0mAbV2V5ZhApqxsXryjBDQjIPTk2X8aVOmiM26apF5cxUTq2FMaqLBCYatDuaHZoWgbUGF1atbWZ4fo1pzmDNvnKc2dbEwZz60vVuaaW8voUJJNhVgLT/O8HB7ZeTyOGis/v9BJxjj2ivz/PhW0raDG+PBrb0OQbfORrR0J4GDYv5+M3S8PZxkkZNjh/ZI6TSOEHQGekYWRguQWYnc+2DjfbNTxhipBzhKiZizN9orIVtns67cS6AjE6AHsPhNxlMYBYimPLK1iCg0UWIDVqdZSgiEYMwSWBokAtHSwjhD2O02leeNUV0TEh0q5MHHm7Z3LjDP1zceddExD2YbCkGx/zGsKf0Y10oxWBvH2sNMAHT3wgYWO+Y9F06GingoabGvI+Qec4ExFGC7ih3b8rgyxonPXWIw1loh7JTJ4KkidG2KAGOAibRDRWjsVgtr78Nm6FztMLEisnMBulZmSN+FaGoiwiff4jX0Vg+Ytmx0Jm8CPAvtuMtnUYzxzc9v66DdqVH2UsYTX50yFI6hl1B9ikK7ycAqnsHDeEOt5cc1AtKrU2Y8+VVU/3qs5cfFlJsjyCWHJ2NMbXoGOX8+ct7+ZnxZNuGjt2Ef9nZTZnLYPJe2uclKhSU0uZ7YMFQmYVoxgpbIuG61gu2OhR8r3/byeEJwwGErjUdXKRNsqSOIqTtZfqgJ0MwVEcVOort+AMXmZAXHPuQUU/9aGbnfSmNEV6ewDliaBFFrr4xYdnQjR8Qey9Cts02Q87QysnNB0pZxQmxtMTsylf2VniJr2xSEjci7yEP+BjIFVP9LJvgVEFEI2aLJVxAFZlUmW0TXJpOYCLnPYfFkqBUWLEWP9IOTMoHBYHQdhYi2ueaZxXEYVvFXFA4ydcluVLR0VJi3rYAnbSIl6bVtHA3VyTiJnYA9163BPu1D6PK4WeWaHGzUo9iJjkLc/e6j6ZGALSJNTQisJUfstFKl0muRsxcjcs2gIkbFvci2mAq2XEMUu8w4dAxbUZIoC8jNCekfECZxWesss8pk2XEejGajt0yBQN9FU3uNoGoxOeBiSUXaMQn/AHodhWwtoCfLlHUWWl+/4+h/Irsz1P7PZDfm/g0m3/jGN7j88suZM2cO/f39O3GpA5RKJW6++Wb22msv2trM0nOlUuGkk06ipaUlSUL129/+losuuig576tf/SrXXXcd1157Lb///e8ZHR3lZz/7WXL8ne98J1EUzaBlHB4e5vbbb+d973tfsm/Dhg08/PDDnHXWWZx11lk89NBDbNy4MTne29vL0UcfTTqd5p577uHJJ5/k/PPPJwzNx+fb3/42f/d3f8cHP/hBnn32WW677Tb22muvV9VJpVJh5cqV5PN57r//fn7/+9+Tz+c56aST8P3GWvS9997Lhg0buPfee7nxxhtncPjfeuutzJkzh8svv5z+/n76+/tnXP/KK6/k+9//Ps899xydnZ2sWrWKJ554gttuu42HH34YrTVvfetbCabR5lUqFf75n/+ZG2+8kQcffDDJnAsGAnT88ccnqy11uf7661m1ahVCCMbGxli7du0M478uhx56KI899hheneptF1IoFJJJ0rnnnsu2bdu45pprXrX8q4kOfXToI1JpE/AWxL8xBj+OazbMhLMWBlhxMKn2SsbzOS17pnBc87u++qE09jTqA08rIgzDTRQJbAS2MJSU0tJgW0RoNAZ2EaFRaIh/1zdL64SWTwHab7CFgAki9KTAtiOTEv5VRMbUmQRewpJD4JktNh4SFqEoJGXZ1MJg5kVyxYThBohTvU/bMFCJAIUNhFonTDkADpDRcUNiL7Wop4uPPdZCxv/HS/2RVjMm58J2TQCf5SBsK0k1H6LBTYGbQgkIMVkrPSIDydBGt9NF2NK0JQoRwvzWKkCrwEBeYoMQIFQRtrDiJ1ZvkDEURZzqXkgHpCSYVsbXUZKELBQCaWsCLXGsCMeKjGEf+tMSFQUzAljNgzf9qM5mkmTvDKeNGxU1+uIrkviY4/G+ute0XsZxTJbPQOKg0dMz4dbP0cp4smNvtrAc6r0wCqQxEuNkWfX2iFTGnOdXDUSlfu+6l1eppC7aK5k+GIXGqJ8cNuxU0yY9CLMaImwQNslX3XQngUzFuhWGp71u4CuBoa+cHDbGd3nUGIAxX7/INZv65VsgUzC0jlHUSBpVr3+s74RhKma/qbNuoZQpJ6T5P1c0hn09OV5MgSnslGGJeQVPitYaj4gQjcjnTEBqZRyRb0Vkm42hmi0aoz0ZO7YZP1HYeH/ZrvFuTx9X1jT/pu2ayZqUydgxz1YgUjYiZaMQaA3RNJpGJXYBIQmCpL/q0DfvEq9sclBMY02aIVHY6L/1FasoTCbswIyxLFzH9G0Vw4F01Ki7ZYMy9dLT+3ScjE7rKCmvEdjpiFQ2JiLQYkZfV2Des1KYHBXTV8f+hLI7Q+3/THZ77t9gUiwWKRQKWJY1A1px++23Jx74crlMT08Pt99+ewIfufnmm6lWq0mmV4Crr76at73tbXzpS1+iq6uLq666iksuuYQzzjgDgO985zszkkFlMhnOOeccrr/+et75zncm150zZ06SrRaM1/3kk0+mpcV4rE466SSuu+46rrjiCgC+9a1vUSwWueWWW5LMsYsWLUrOv+KKK7j44ov52Mc+luw75JBDXlUnt9xyC1JKvv/97yPil+r1119Pc3Mz9913HyeccAIALS0tXH311ViWxT777MMpp5zC3XffzQUXXEBrayuWZVEoFHaCrARBwDXXXMPy5csBWL9+PbfddhsPPvhgAo26+eabmTt3Lj//+c8T3QRBwNVXX81hhxmP4Y033siSJUt47LHHkqy0F154IV/72tdwXZdnnnmG1atXc+uttwKwZcsWtNbMmjVrpzbPnj0bz/MYGBhg3rx5r6qbY489ljPPPJNbbrmFH//4x7S3t79qWQDP83aeMEyM4KZSaKUM3rQ6hapE5oPslZMkMNgpMnYKS0hGapNmv19D16ameZxs9MSQ8e4JSd5y0ZNT5LRAxVDqonAQGANTCo2rBeOqwTShqz45MngodMX89tFoLyQXe/wDtMnqWPawgJQWiJSFqzFZFAHtgxW/2SMtcLIRNSGxU+ZjGFQkWgmkZQw37VUMPri529DigcGNFzvRYwPoiSFk2xxcyyHruIzVzDI8oaEvJNeSlFdDW5L2CDdHTqbIaElBNNopATs2zi0tGJOgQ92gElUKXR1NJlZaRwYH3TYXHXpk7TTVyGusmkwNJ0as9nxEpQKWRRMWatSsVkjdRGukCQW4lgWVMo4wWHTHMXpxqhpdi1CTg4k3WnvlxNOtq1Poul5qU2Rtl8mgnKxkQIyjrp9bZ0UJXZq0JBNneU0pC8rV5JzquENXrsxYJZ5YeuXE8NMQG0oe1MrkdD0Jj4+rBVEpNuhjCkNdpySNz6M6RUbYUPWwkKhINPSmI4giMzkKfOM19avo8SmyLaauY4M2rVaNWmQZAzQ2ZIVlN+A9loMeH6CoIsYsCzcfJ/ypU4EWO1Ej2wwEJlNIPN0i35JAQ/DqzDGBaY9fM7rsWdCAl+yYQnYtMBlPoyDxwurYZrSaJGkkFpq0VqiaJgosHN0wdKrSYL21V0a4OWOQO64x9uvjPZ5Q6coUhD6itQ3aug09LpjxUp1qjJfyhMF8xxlWAWTrLNTIdlToxVSxQWOs1KlVW7oTdhqRLZLBwtWaILaYczJFUZgMw/VkbGhlxuQ0/H99IiXyreb51TNG13MkTA2bCUfgGahWnTa2fnxy0MTVVKeMPuKVDFnMEQ2a9jg6i1sICacZ85PSsBDNoW5kx5CxwEcHVeN/9mvJigdRAJ6PrlQTJ4kAU6/pk89pkDQdGAM/g0zyKqC0mXyEPtrykgRuOqzG/cDG0rGRlymYSbmQaCHNCkess5SIUIEk9BuT5jreHuIEe+UqODYZohkQo93yxpXdnvu/Elm5ciWrV69m9erVPProo5xwwgmcfPLJbNliPgrr1q1j+fLliWEPcMQRR6CU4sUXX2RiYoL+/n4OP/zw5Lht2zt5jS+44ALuuusuensN/d50TzMYaM+NN97Ieeedl5xz3nnnceONNxLFmfNWr17NUUcdlRj202VwcJC+vj6OO27XXLkXXngh+Xw+2QCefPJJXn75ZQqFQrK/tbWVWq3Ghg0bknP33XdfrGkBij09PQwODr6mblOp1IzA5HXr1mHbdmK0A7S1tbF48WLWrVuX7Hul/vbZZx+am5uTMqeddhq2bSerI9dddx0rV65MoETVqnkJp9PpnepUD1CuVAxt4HSdXHjhhUm5vr4+7rzzTrLZ7E7ZcHclV155JcViccb2rzfdhii0xQGUDqKpDdk623woC21mab7YiUhlmPKrlIIahVTGeBClRORakW1zkW1zEflW5Lz9kD17I5ra2VQbRs6dw6hUyCzILGyMptiqygSAnVJ4QpNG4Vcs/IqFsCRTOsRBQsqmTEgKgbAkkzpkUodYGApN4VgmgZUA2ZzDAeY6ZeY6ZSqDNp1RwPB4jo7WMjs2NrHQLrFttMi20SKzuiax3YigZuGHFsLNIjIFw8PtZpP/9WifMQKcFGpwE+WgRiXwaHZzNNc9klFgAhyzRfTEINbsxVg9e2P17I1sncV2b5RhEbI1nKQkJDtUhSFbMBJvnjCJuURaIopdxuuYKZjgVds1m5szhlBtEuHm8CKfWugj8i1mK3aaNPROBtHZjujohDnz2aArWAvnYi2cS1Wa+w3agk3hOMzbi/E4ErPm2dQ8m1AIrI4cIl1Aj2wzfSLbbKgO6/+7OdTwNoTt4quQNtcYC8kqULZoaEQtB9mzyGzdC9kkaoxW04xW0/QGE4iOdkpETFkm/mKikqY549Gc8RqQkHxL4hUWuVbknKW8RJWXqGItmkufDEktbIo9rXEgpGXPWHGSnfPpjcqIOd1EmAldordMkzF2HBfR3GFWYPKtWAftT++GIr0biuyVmmLUS5NPBcZwnBxEl0cbhj1AdQq5xzJeTtlklMYr2cb7XWg3E53qFLLYacaJmzOe5xiiUYdTiK4FiJYuSLlmgifjVZOxHeYc13i71cAGZPdCrO6FyHwL5chB+aB88AcVG3WFPtviedchNS9LdpYiryClzTZP15gdBmCn0KUxhLDQ5Qlzv6Y2RJPJbSDSTcawr68wVEvoiSH0xFBjvIz2IVLpZKzU99fHEm7cl0ZjStf6WInbo4e3Izv2QHbsgcgU6FUVBhzJFkezxdFs9UbYFE6yRZUQbS2mnlUz4UjErzUgN7WyuX5zt7l3XBdRh91kCoiW7sZEJfZ0J3W0U8juhciOPbA6FxD2jSW3GbVsRrbmGbQFbjrEdULmBpo5gSItI9IywhEK0VQwOim0mz7c3G3q6NfMmOicD47NNp2hJYrIK23qIGS82hWvHAiJHh9AWDaydRZ9eIiudkRXO7K92fT1pk4TcBtTbcqOeciOeZQ3KHLKTDz0xKDZpoahNGZWP6aGkc3dDAiXVFHhFkLsmOPeC2xsqUzGWgEin4MgJEIg9tjnNb8zfwypr4j8Mbb/jbLbc/9XIrlcbgZ05eCDD6ZYLPK9732PK664Aq11YoC/Ul5t/67kwAMPZPny5dx0002ceOKJPPvss/ziF79Ijv/617+mt7d3J1x3FEXcddddnHzyyX+QOee1WHUuv/xyPvWpT83Yp5Ti4IMPnsEYVJd6vAGw02RCCIFS6pWn7LJO03U0HeowXXal413ptr4vlUrx7ne/m+uvv57TTz+d//iP/+Cqq65KytW97GNjYzPaASabLzTaN50OdTqDzgc+8AGWL1/OP/7jP3Lcccdx5plncswxx7xqWy+55BI++clPzty5fbUxyBzXYJoD33gx44RB9aQoWqkkcZNEGC+RV0WE3gwGDbRKDBMrXoq3EIln0dMBOn71aG28VrbQCXONKBapElDDQhazVLRPRliIQoayNp7UtJD4IoUoZikJZeoThAZLHrvrg5pFVkTUIotUJmR0LEvGDajFHionExEFxtBzrMjowE414CCQ/I/yk3T0dR0kz16rGH9tztdRkHiQAWO8IXAQ+DoiEIJAR0TTuo4NBBgYkllqV42l9Ol9OIY5JMGIQswop1WAkDEsJ8YMV3SIyJgJZCQmERoQ4GsDS4j94lgxTigC9HSYi4qMh7BeD1XP1hMm+wQi7hNR47z6ubH3VAhJRUfUfUq+NudHxIwctkkAlAy/KGwk9QHDdR8ZWFBQJ7izLAPfsmNged0LW793/FuAgXvUOen1dL3V2xfrndD8dl2qMed+a6FCUBPY1rR2CTnj2WgdIYWkEicJS1YHYmhXAnmzXZLkT5lCDGuJB4fbKGsSh1UTRpzpfVJFQQLBgsB4X+uookiQFhYVaSa9qhqgahpba/OMMAHCvpKJUWySjvlo20sgedPzNBg2Id3of9AYL/FzEsLAPQj9xjsjCsz7ob6q84qxYnYFCURG6xBHSKpxP6z3rZoOseLVGgIfHXgz4VnTYYBRGD//BrwpkRjOVP89Y5xN03s9qRlSxmPSdMqqhEhJqnVokzYZDQIhkkBxoTU6nAZfqtcpXikS9aR0XoAnMhTRSK1n9He0nAbLifUbhXhamey8AI7dCAav1x2Sugc1CwvDc//KMsk4xaziyLTAUrv+7k0RIfIFqNXQiGQl6k8tr/3l3i1/SHYb93+lUmd0qXt/ly5dyo033ki5XE689w8++CBSShYtWkSxWKSnp4dHHnmEo48+GoAwDHnyySdnUCmCMRi//vWv09vby/HHH8/cuXOTY9deey1nn302//AP/zDjnC9+8Ytce+21nHzyyey///7ceOONBEGwk8FdKBSYP38+d999NytXrtypXZ2dnXR2ds7Yd9BBB/HjH/+Yzs7OV6WGfD2SSqWS1YU/JEuXLiUMQx599NEEljMyMsJLL73EkiVLknJhGPLEE09w6KEmIOvFF19kfHycffZpeDY+8IEPsGzZMq655hqCIOD0009Pji1cuJCmpiaef/75GbAlgLVr1zJnzpxkArCrmITvf//7PPDAA6xZs4YFCxZw0UUXcf7557NmzZoZKzjTxXXdGcHSAJ4bG+aBZwJh4yVgkcqYrLUJBtmcZwlJNYqNkboBW8eRxlk7CTyE7RrjPopm4MtTwkZgsNZ1+9jTsvGtDhUOBp+tp/1GK1KiAcux0BAqbC2MuWhZSCAI4wmIpQm0wBGa0JfYlkIpYc6jbn+KZDIgYio+6rh7aPzvlc1HP4ZASCGo1Q2y+nnCwEFEpsnoLIo/tpZt9ACkhEVjbYkZIWN16r+EHUZI0EEDFyytxsQp9vBp3TBY0SrB5WulzbW1Ii1sdLXW0L8GX4PFNONUimQpPsGwa9UwNqOgYaTGhr7INvTkqcBMEupGnF8150qrgR/XirSwsOpGUDxBrIsKBBkrnBEfkRhZQiKEwbbryKzcmHpFxnAPVey5j4urBgRFxDSXFsagl7GKE73Fk7Wk7vWJqueRcYwh5vk2FtpMPCzHrGpZjrlHPfGQ7aKjkKwCJQSWMxPLLzIFA9OJs8sKIc04cbMNKMx0Q7husMaMOHXR9X6oFGAMfI2goSoTh+BMG3NazfRghkoSIBsY7el/6+M9DI3hXTcy0xnI5hvwkvqF6zAdrRpwj/qkL9scY88Dc6w+VuLySZlYT8JOIRC4MXsUmPdNOn5nGFYjg6dPDPj6/epxC6l0PDamjaN6XZ0Y1z8t6/OM424uxqSruFxoVgc9U2dHg+NEyGnIRk+YoNV6v1ZCGz3Gk2shJFpK4zyBxjgGTIRB3FApEdNMMl1fiXJSyXvWmj5mVDzepr+H4roDOOmoMUFyMo3rgXmHxPd0tDZwwGnzICEaMSYWAnwfHAdDPPznkf+tWPk/lgj9am7K3fIXk6uuuoqrrroqyei6atUqduzYkQRnjo2NcfXVV/Ptb3+be+65hxUrVlCpVNhrr714y1vewmWXXcbQ0BAf+MAHOOqoo5Kg0i996Ut86Utf4tprr2XJkiV87Wtf45ZbbuHYY4/l5z//eXL/yclJenp6CMOQm266KfHSDw0NMXv2bG677TZOOumkGXX+zW9+wymnnEJvby9SShYvXswxxxzDJZdcQrFY5JFHHuHQQw9l8eLF3HjjjVx44YV86Utf4uSTT2ZqaooHH3yQj3zkI7vUR6VS4YADDmD27NlJsPHWrVu59dZb+fSnP82cOXMStpzp7fj4xz/O6tWrue+++wA44YQTyGQyXHPNNbiuS3t7e8J6Mz4+PuOep512GuvXr+e73/0uhUKBv//7v+fll1/m+eefx3EcbrjhBj74wQ9y4IEH8m//9m84jsNFF12E1pqHH354xrWOOOIInnjiCc4//3y+/e1vzzh2xhlnsGDBAr7yla/M2L9q1Sosy+Laa6/dpU62bt3Kfvvtx5e//OWEbadSqbB8+XJOOukkvvnNb+7yvF3JA91nAqARKA2O0EQIQi1whTJBVLE0p2sobbxUo9U0GSsyhkL8IYiQTAiLdgKUhn33H2T92naaszW69jEY9b7nm7DtiHI1hSU1Y57LrGIJ2zafouLsGg88O5tICI5Zup37nzdo1uP2387vnzHc2KEQDNuCM5dt477Vcxi2DadzXkEu/vgdNGcHj/V2c0jPDp7u6+SA7iGeGehg/y6TrXXtjnZaCWhvLmPbiqHRXU+IIPYcx39Tdt0jbI75kTFYo2lBaJGSiPhjr7WgtVAhiiQ130ZrgeuEKC1Iu+ZjOVV2qUY2zekaEzU3eR5i2idO05iYKKDg+kihGa6aD7UjZvq6gtjT2eJ6SV0jJUmnQoTQKCWo+g6pOOC4rdVgoLcPFXFl9Jof17pOXDuaoYtXHlfa5DFIxSw4XR3G8zc2mkUICCNJa0uFSjnFZLUx8Yzi/ggm3tcWCl9JKlgcvGQAgN++NIcjuwd4sq+TWbIxgXmlKC3IpgKmvFSSgXMiZgOpO2alMJPMrIgItGBcOCyP+8qaHabfrN3RTof0XvU+gZIUXJ8gtAiURGuxkwcy0gKFGVsKGsYdEGoTtJiNM8vaUhkOexrGY91DXI4cUiJCIzh87ZfYttLA9YLAYtZJNjvu8rEcxVUTbaQR7BMkU6IkwH1vKlhSESmZ/PWUeYYZy9DIpqwIP7IMJGNar3Cm4bLrz3pX8spjrxwrMHO8ZJyQSAncOAbETQeUSi4pJ8KylMlJQQPbPl38yEoM01fqdvrYYdqx+v6E110LonizhKazuZxcI/AtcgWP8pTL6lozghgSCGSneb57tGfgglpiC42nJTnZMIxrymJWsUT7wjL/9excbGBfVdml7mSsL6UFqfh9W6+n1oJAC6QgeV/X38Xzusd5cKgLASxk52vX9Z5NBXixQ6Tex4DkeTwm8pzSMYDlKHq3NdOv0pw28B+7vN4fU66ffd5rF3qd8r7eH/7RrvXXIrs9938lcuedd9LTY5K3FAoF9tlnH37yk58kga7ZbJZf//rXfOxjH+OQQw6ZQYVZl4svvpj+/n5WrVqFlJLzzz+fd7zjHUxMTMy4V1NTE2eccQa//OUvZ2SvrQfr7govv3LlSgqFAj/4wQ/45Cc/yT333MOnP/1pjjnmGCzL4oADDuCII44A4L3vfS+1Wo2vf/3rfOpTn6K9vZ0zzzzzVduezWa5//77+exnP8vpp5/O1NQUs2fP5rjjjvtvefIvv/xyPvShD7Fw4UI8z3tV+A2YWIOPfexjnHrqqfi+z9FHH80dd9wxYyUim83y2c9+lnPOOYft27dz5JFHct111+10rfe///089NBDnH/++Tsd++AHP8j73/9+vvzlLyfB0bVajZ/97Gczgp2ni9aa888/nze/+c0zaDSz2SzXX389K1aseE14znRZeogxYFQNgrIk3aEIJiHyJG6LSpLjhFXJ/90yGwU0RXDSAduQsRPPG4k/OJFATYs2e+jZ2Rw4ZwfPb+sgv6MW1x/GShm0FhSzNSZ9mzmWYnzSGKnD4zmWFMbZMZlj47o2lmbHGSjl2PBsG/s0jQMwOJmjxZe8/Ewbh84e4KntXbTh85KdpiP2mLedMYf7vlvjxCPTvPR/JccsDNg2InlLp2nQ2LBFaxQQ+BbjkxkWHTaCTEtURSUe4Pr/WoGVlYSTip+unYsnoN4T/vaI7ci0RVQKEbZA+5qoEjOXxPLrZ+bSEoUEQrJHqkxfNUdnqkoQmI9qpAUpaYzOJcuHiLzY8HA1YbWhT+lodCSwXM1/PWeMglOXbE+ORZ5AK8HEYAY3Y9o2NJanPTZQpkou49XG5GHerDHW9HVwwNxBSuNmf6gFs1vLtC7xUBWNzJr7q0psXGaF8fT5INOC6x6fQ14bFpbzDt+e1FXVzLnBqDYkHTY8u6YLHbuQtwU5Dtmzn+c2dJKpBMkEoe4t32PpeOJErjPBRBWoTdiUR4yB1xP5jAzlaNUBi48YjfE9oP2GJ1JmBVFJ8+DTs9m3dYQdowXyWY9Ze8587yE0tQmHdJM5sXdDkcKsel8xHSJCsPjw0QZsSZHcR6QgGIfel5upRRZtuSrdy0pJG6IKWFkIS+CXbHKzQnQIYVlgZcz1KkM2USBJZSPS7ZFB/vhmf53qUtgmeFb5oGLyoG0rL2Tuvd8BYPK97+OFn7Sy94oy5Y3w9gFNAPw0UyMVd+wlkdHfXgeMoEOQKXM9mYKJzeZY25vA2+pjNxv9DW/IkXLDZEWiMDdApASqZph6ZNZCVWIa01T8PqgphC2QTTbReICQApm1CMfDZHxoP0br2EafjzwxiwwRLfEkau1EGy1RRNqP2Gv+CB2tZWQac91szJZVipBNNuFwgKqZaynfvMPqkioqwkoM//IEfsWcm+sKk+cXlcwzCqbFjNpZcLqNToYfiyjM8rGGFKq/GUsb497RMGKZfi2BfTMVOheVCStgpcx71SnEKxUSwgo4zaYNlTggd/HhozO6ow41YQmcZmESkYXw6GM97NNpygWBRdu8Cv6UxEppgqok3RoRxe+LVAeUR8xK3aI3jTRYlKYRTikftq5tpinjEUaSkpdCCk3aCan45g33ZnuKF3vbmds0STmyOXxJH38O+d+Klf9jyW7j/g0or8yiOp3S8Q/Jfvvtxz333POqx23bTlYFXkv6+/s599xzZ0A4Lr74Yi6++OJXvfbIyEjy//777/+qxinAhz70oV3yu7+adHd3J/z/u5Jd6eeV7Xzzm9/MM888M2PfqlWrWLVq1U7ntrS0zOD1fzU5/fTTZ0BtdiX9/f0sW7Zsl4xAJ5xwArNnz+bHP/4xf/u3fwsY6NNhhx3Gm9/85l1eTwjBb3/7210eO/LIIxPK0f+uaAVWSjcMqvoHoG4k2RqhDR/7eN1BKwFloAAAOsaWaG0gN45W1MoOaaLEqKv6Dk0Zj8mqS8e8KV5e10S57Bo8MwYyMDqVJTJkmYyVM8nqweiUmQAEWtKWruIFNjv6m5hjV7Ckphi4TMQwi+r9mzk4mEvpqTJ7eU3YPVnGpMZuMtfyhMEep9ww8RhHJYXdahNNhjP/Hw+JKgq71Vw7rWB0Gr4mKsU0chWN1WwRTEbo2EC3cxpXayIhyMZZLBXGy1gsmglPfyVHOvbW1uHqwtIJdAjAcs0kQzpmv03MBjTN2xZ6klQ+MpOsGN5SSHtUKqlEt3WP/1TNJQpkg94vLp+1QsJQon2NlZeomnkuVr5hsGlljGZV07gaajKuS92AmHZuWK3HHmiaHD/JRJzRChUZSFUYSWqBTXtzmd4xA/fZI+6D0w18rUCFcobXVgh25sSW04xuaSYjjjaeadcOTZbiut7iaxlouUZYGhUIgshqTF7rEBE0SJB23KbQQBpM/QSRJ8hmAsZ9FzsVmecX18POx23RhpqyfsxyG89PWhq/ItF1THSsTzcfJS5nHRpGnGhQoSOBkJogsJh87/sAaLrxeqL9P8XYWouWpSH5LQGhkhwQpRMGjRetEHe6zmJYPRLSBVNhf3vsya7pZIw76QjbVck5qqaxm21UJSKajLDbHaLxgKhiytit5lg4GODMconG/WSs1PViNVsEg5FpV9YYdU22z5Rv+qyLJk2EJQxVrpBm8hCVFKoSJnXRo4GpZ33SoCAKBE5GJfer9yetBEHNJtPkzzB6rXw82ZgWEGN32gSD9eBdF7tJovol+chAvIZtiauhM4jHCZj+JZkBlUom+8pcX4calCavmEEVXBdhm2crUgJdM8Z9GpXACFMyNO3WsfGvBCgS54qwGwHUMi2TCen0UAVd0WTSAVEkkfE7vL4iIKe9VzrTFYSAnqbGZPVPLbsx9/8z2W3c75YZMjo6yl133cU999zzB5NK7ZbXllKpxLp16/jmN7/JP/3TP+2yjBCCf//3f2fNmjXJPsdx/luwmv+pfPrZRjCvheGSh/ibtz3GRgM2gq98UBsaN8/nwz9po0u4TBAm3NQKGFAVumUWF8nXbngLn/7wg1xx/BAP/rYLgGPO9xEyw+hdozzzfA/7FMcptNXwSuZ1lI/MEvToRJaWpqr5aE1maW8tJ0vFI6M5XvQLHNwyzPhkhvUqx322z7tUwJA0HqepvhR5pRFSM2JLxh/12DMQ+PEcVAKbVZZ9aiFz54xzxdNmZSyLpDzt05Il5ooHclryiTNij2/NeJgvvbObDm0zKMKk/Ha8BBcugW9+ZU/UCy+iqx6j95XY+ziLyhMjqHgytCQzRLXk8PJoM99cnyOFxI9NVju+TojGQZJHMkXEv5w1Ca7DR35k4jJy8etc7oAubTNcMgbi5aeV+frPDPPUe7t3YDmKTHtE+uAePntTC1ccN8A9d3fzpjk7TLMGbJ6YbGPNM800a4uxeNJRjGE+Y0LhIGjRkhER8bn/b5RopIrVkuZf7jC0rhGagpZMCMUoATUdkRYWX/+bccovGt0e8SH49g2zWHXANiJP8Ny6TpjM4Mbwok+80IYtGrjfLBYlIkZUjVsuNXEtn738JW54p+ALP5X84vHuBhYfSMe/a2hG8PnmKp+//3ETF6bKlGsp/n5Te1zOQsW6VWgKwxbjhNRSiq/FtmNNQr7TpzIo+crjs0jHgZQWUK1n3NWCl6nyzUNH8R83KyZXPduUjCcXyQQhsj7O+jUWAgdJLUZHCwQWghXjLr/f4VPAIkTv1CfTSDbqCmlh4kz+7TSfF37SanS//6c4eM1XqP7DhxHC5VNigkLK5fzAxY0ts2Jk42rNPz/bw/6BzVonYllgsdaJ8OP7zNIO/SJkr8hmoxWSRUKtESdS227yTWSRVOK+Wq9nvUz9fwdBfq1kXER0aJsRESWB3FkkA/jJc/76xRnKd/XhtJr+5p59Iuqpp0BYXHlTDwu3SPpsTVEJxmKDtEUJJqSmX4RJfSI0DiLJrSBivVUx8RcWAkqg+3Si07w2dRwjINAaRwjOf0lQ1mZsHXJoP6oGTQt8ekckFnF27NjpAQZH/2tRYMuzLiUdIuM+3IGZrFSIGNcBf+ulOfZjKbynIlwN//xkT/J8VVz3Zm3hvAh9MmSKiK+cNML37zXlUho2ToRU4r4jEWSGJIMxc8GX1RizwxALzb89MgsL8352EdRinWwVHlfsMcxTL3bjoslbgYEBTXOb9/tZLDSzRJmq73DxZriD3fJGl93G/W6ZIQcddBBjY2N86UtfYvHixX/p6vxVy0UXXcSPfvQjTjvttF1CcuqyfPnyhGMfDFTnzyknesZrPWYbnGpHqBmKf7dFmklZN+5h/FdmSVZamqOj2cwOQmrCodeJvboClpKmojU5LfD/8zYODLsZecahWRhj2NprAdHLm2I2B81U2SWT9+kfMhCr5+007zpliPyzY/xi62z+9sQd5NeO8uveWZx1mlmSzq0dw9kU8bvJDs48rp/U7yKGoyJlESUf2e5PHsx3P/c0p/7dSm65+EH+9tgij/444LQjzGTmmc0BR0U2Zc8hGMizMhA4WgOKoG5Uxv9rBKnYYBi5r4ZXs5Ng4OOqgnarwqCKaRe1ZluqwQrlaPBu/z21Xk3hxD1oWjyFLtewmyAYj+EYUynyLR6MwkFhCldDVUzzzmO8xxJoijSBcJh4eAg7HXFIZALeM4oEA1wT0IZNVYDsaKHBPQKDfQU6mSKNmQRUNmnaCRgdMjEHuYxP92RAS1XgEFATEqmhnp7JEwJLK1wiakj671aoKIOTijiqagzDSAicmBlonZs2wZ0a7DmthM+a2ZWuVFnqZRA2BOMSRyhSVkQ6Y+AYR3st2Nr0KUdDRmkmLYeNdoOZKYWFGiuRJcfhVZ1gwvU0pLeFZouTIdzaSzM9lGspOtpKHDIeUwfG17KMg5qcgpJl8ZIVkn7zPABefLaG02mxzREcUY1MUqsYg+5TD3ZU5N0sztwQ7yGLrtYpjh1rTwKlIwQWNoO22dEdaMYtEeO1TZn++IvcFoUc7TsUo4gxyyYSUKwTEcVtmm/nE0jHjrtK7L3CQK/G1lpU/+HDZP752wQ3XckqUcWJ4B7Xpxh/8l2tySKSvttZTdEW/13nmsnxwZ7HBsflLZlRHq+0MinB1Q0vc3sU4WhQqPh5ayQq7h91B4EZS67WCEJ8ZDJW6v0aFIO2WVWQGqr3byBzQCvRsInNCG6/G/uwZehtvRzgWcyTZRbUbNpzVfrLps/OzpcYr6TZKDK4WuMJi7KMWahi/bvKGMQ12dinaOi1SRnepgjJhlQmqU9XyzBOnBsjc+SeRNt2IGd3ED4ZkVZQjDSuVvTFCfUyGrpDmKcdJmUqqUN37Nn3hEOfk2LfjkHknkcwJl8iEoKV1Qb+P0LgoLEIyFkBQ8plQrpEkyExighHa1oim5E4Q24goDPUbHOyABSPTzG42SavFG+uRVhoY9wLRUmbunY5aTILLOwXiae48ViQGj9evThkWR//tmE2y70murTP2VErfw75a/Dcj42N8dGPfjRJ/Pn2t7+db37zmzQ3N++yfBAEfO5zn+OOO+5g48aNFItFjj/+eL74xS/OyHezYsUKfve73804913vehe33HLL666bfO0iu+V/k2zevJmJiYmd6Ch3y0ypB/D+IbnhhhvwPI8f//jHM/j336iiIPGEKWC0DrURZitJE2QlhPGGBwLq4Jk6n/CgVFSFMa0qQiMzDlVhznPtENcOUdt6sfZfRrbFp4akkPOoVRyCODgsEhANe7gtikBAOOzjNkUoIBqqEg1VcVp0wopTXq/omFNiUhr4S0UKKlIQrX2RpVYzas1altgtWIe9iaeDYeTBByIPPpDVwTA5FaG0wI8spDaUdjkRIrX5sEdCkBdRbNgLmi3fwBOcCK/m4NUcBBpLKlMeQYaIsjDJbSalMcpF2jIQmB2jeH0R1l5zceY1kV2SJbskS8oN8Uo2gZDYGirS6Fxqo/eSTNAjCRY1CsyDCYT5sFvAlDTJwQSGWrNuxPhC4wtNFEiam6uk8hG4KTyhsVIaV0Z4gY0X2DhOxISwsIG0iHC1xkGTFhFpEeFonRxLo9BaUPNsfM/CReOicbQmKyIsrQnQ1OIJhw4j3EKIWwjBsqgJifLBdhUjpMjnDVxrsuoSiUZbFcaYUUAVBa4LrkuNCJFzMSR9hiXGBgQ66ZMWmpoEkZL4aLJugO/Zid7CWFeKRvbWALNSImwLYVsEaIQUOMQwkVgXrlA4xPohoiJMZG6kBXZKIbUJTp8elA4wEAdv2phnW5dAwGYZJEZeXkSktGZSGo+wjKctaa0SIzUQYDmK8kYob4SWpSFCCIKbrsR5zyWGlhNYrFIsCiSLAsljeownKZEhwnVCskRkUgFZogTKkbND0spgu12l2WZFDFqaccvA8iytCYSgEI+XCEEm/m2ehhlLltaEYPpDPFasGKYWxed7wvR5JWK8/GgJe14H9rwOhGujt/Uil+1LICCdCsk7AVoLcjIkJ0MiJXGkSvQmMMbNpDTPN6Qx8W08Ax0Hwxq9Wtok/UppRRTrNQDyLR5OOsJJR6ihUWRLHpQmo83Eaosj2OI03u9Sw6Bdf3+YfWH8zNIxW5Mn4oBgpXBjdiAr7r9mZcdoUAHZVBDr2kB16s88iFl6qsJcrxLD0yLiqXzUgABO768pacZtGvN+1WFjUqy0QAiNY0cG7hO/dLoiyYgtyDs+I3+mT1n9u/PH2P5Ucs4557B69WruvPNO7rzzTlavXs273/3uVy1fqVR46qmn+PznP89TTz3FrbfeyksvvcTb3/72ncpecMEF9Pf3J9t3v/vd/1bddrPlvMFEa82HPvQhfvrTnzI2NsbTTz/NAQcc8Ce5164YZt5osnnzZhYsWPAn1cMfU1asWMEBBxzwuuIawFBs1rPazp8/n2effZaTTz6ZF1988VXpLP/YMvV/TgZABxE6VMiMk/yeLtpX/Nvve0jFH6MPvH0UNeEhiy7aa+D8rfndhC/3gdJc/LsWrtx7iNvWzWU5hi3nCZEnAPb0IxbkJxkrZ9gq3YRtoteRHO2M09xR4Ze9szg6M0qxo8qt22ZztGUgMc3tFfKzQ255ai4nFodoWx7gLO6hdE8vftl8fZ7a1sUBswZ5rL+LIxb08djGHg6eu4OHtpsMxUct6KM6mWLjUDOj0ubEo/vQSqNqOsGX69D8X8cjqwrcvG5u7Mk2cvZbegnHFXa7hfYVqqJxulOoWgy1sAVf/V03HZGgoGBuGLA+5TA7iCjFQdSOhjmiSktTla4Dawbr32woLVUMr7GabbSv8AcVqU7Jf/x+NlUBF5xoEimpSoiqRFh5G68vJNUpQcHtD8xm5Tyz4vLCxg6GpY2FCQA8Y79t3L5mLm/OjfL8ZDMAe7olis1VivN9/DFBqs24tIMJ85VMtRm91IYkbpviR6vn0hZpJizBO/ffZtocB5em2gUiJZF5BzXp88C93YzFE91AwFvn9/LM+i6GLZsD0uNmfzxp2+vtATqIEEKgIwVKIxyT7+Dvf2K89188vcr3ftrEqsO2J9h6wOCLE6y+QOYtbrm7hzP228aLT3eQc332PN7QT6pSjF0ONVaTQzDoYzVZWEWXX//MeCkPn9/PQ5t7OKhtmOLcmglaFCa42SnE3tYauHs4PHhHO22WT3NTla6DPcOTHo8fqyuH9gIIFdpXyX2dhWYVQU2W0VUfb2ONVLedtCUajxpB3nEQa2peFlU1q2FfuLedt1fjCYEV8CkxwSrRgwJWrb4cVETl4guTMR2VFDqE1ByX8acjivvC1AuawiLzvACqGwLc2ZLaNkV6rkSVTAxBXa9JoHU8XnSoZwRgmz6psTsNDl/VwMoLokmNzJrnkpRpbbT1Hx/sZEVNMmGZerzsaBYEAl/A354yxNSaALcpMkGquThOp2qCzJ12STiqsGNIT30cmbGszDhttSDUJoam2U7GqQ41wbgJdLWabETKQvsRa37dQj7Oqrzdz1KSkrxSHHlEf9K/kBCONmIRvHGL/CKBzKVMH865RP2l5LhVdNlxv+amSjuffvsEuuoTjfozArVlWhKMKlQIqVaBSEse/G0Xhx3UF983Zr/MmnGOLYgmI5xOMzYeuL2dgxf3G7pfRyVxBMLSicXr9gievbeNWe1TaAVjE9mELSjjmHf6vAPHWftoJ9uky1J7ikUfbiZ3yY38qeU7c/+IbDkvX7tTZvZd0UL/d2TdunUsXbqURx55JEl4+cgjj3D44YfzwgsvvG7kw+OPP86hhx7Kli1b2GOPPYD/vh2xK9kNy3mDyZ133skNN9zAfffdx5577smnPvWpGcmbWltbOeSQQ/jyl788I6vqn1Oq1SqzZs1CCEFvb+9rJqZ6o8r8+fN3Cl7+n8qtt966y8y8ryZXXnklb3vb25Kstfvttx+HHnooX//61/nc5z73qudddtll/OM//uMfPH7ppZe+rjqEQ8bIqTOMWPkoCZqcvjaqfINtTcceq2ioSlRRWKEyDDOxyOIE4aD5GLbiEJQlriJGG0OBmGECnQQ4KpVOsMmBACcV4WSMZ8lxIuxpvwGctKlfIEBaCpGS6GrNfLhiqf8SQBTExvo0bKyKhAmuw0AjvEEFWhB6Fk6lEdwaeTIJtgyqFi2R8co5sV/EG1QEFYs0EZEPYc0C6aNiZkYhoU0Zw74pUlgoCpE5v85F7miNJTUqEgTDCr9k4fqhaWPZ1D3lG3aV6piDkAHFCLICggHz0VI1wwJi10KCioU1GRHVIK9UEs/gCIUV3685io0QpRPWHoiX5D0bbySkNmWj44jq2lTdAAvQSlKdTAE+LREUowiwqA7HlHqOydCKDhBWhN0UEYxDTkeMxU+gJTT1ShPhagulBFLqBm3nUBXlqxlGu0gJpBdSIDaGp2pkdBNRSRPV9LRAyIaBKSRYpZAmpfEn6v1AJEGSYakRaOn4Pt6IxKlFgGeSC2GCFC2tiSJBbdQi9KykP6k4gD2oWVjpABedBCP6AxEy/spGPrh2BVUxwaOq1riv1WYMPzVRRVUivEkLCJFpE+AZlGUSyChtTRRYyHQVVTOBuWkEMXO7CZpOuTj1GNw4SZdIW4g6jWLFBxuicZ9qKUNutEJtKk1mvJYEflbHU1gZn9pkCnvYj5mYGgHesmzaWB8vOjJjxy433gWhZ5GWAcGEIPQkTlURVC2sskbGrDthzSLlh4kuClg4OiIT36cjEhQjhScFqhRQm3LMuKhZREGU3MdyFFqFeJM2bmiuF5QlOn4+ygdv0iYdhsm41mGYsMtoJahNOugowK6EyHSI8qGmLZx4UlSHG6W1agSo2jKeqDTaXZtycAdr2E0KVVNYTRHBaOO4qlXxvTyOBpGyILTwhhr9ViuB5Zr3QBQYvn3pRGRosOFIRxNWJXbFTACsFPhTEuL4hVAIRByAXB1LJeNKWjp5hsLyDTXp9Ix6rxCREnhaUqsHHo+Mv2rZP6b8MWE5V1555U7fy0svvZTLLrvs//maDz/8MMVicUYm+ze/+c0Ui0Ueeuih123cT0xMIITYCcpz880388Mf/pCuri5OPvlkLr30UgqFwq4vsgvZbdy/wWTDhg309PQkyZNs2+akk05KOO4HBgb43Oc+x6mnnsrWrVv/InX8r//6L5YtW4bWmltvvZVzzz33L1KP/1fxfZ9UKvXaBf8fpLX19eMRq9Uq1157LXfcMTM86X3vex8XXnghl1xyyavCeT71qU9x4YUX7rT/kksu4ec//znnnHPO667H/31oDlA3PGHMkrRECltrBm2LQvwRc7TmnYsM1aEKBb+5fxZlaQzjzmkMPdlHIwQdlLXNOekyqzd0cXDTKE+VjW46o4C0iMi7AUOVDPssHKJ3Y5aumKe84DkM+jncdMgSP2BwLE8qG7KvF9LvmcBQNx1SGRcs8UJeHGjjkOF+pp4fo+mANP5qY+bc7JY54T0LueOqEU4+oZXVPxSs3E+wcch8yI6dFTG22qyOdGuP29bPNRAH3cArRsZBmyyluxrevmgbVprk6/PT5+caLGtv44OU3TITAvC21sHEgO4fy7O/O8FULYUXB6nOdcoIAeVqisefbyUT69wTgvS0xdUIA12IBgR/s3gbkSe59wnz/GpCkI05/rvwqW009+uUHtuHikZvMmIuVRDgOiFPbOrmwPZh1g63kY2tx0gJto41sbHUZiBXcQBy/WMRNlj1UONwxvJtKN8YqreuM/j/OrxADZsYARm3ZVl6kv7AjL39W0d4cLCL/bMTUIGSlyKbCghirvzf3G8wqCI+V6LJKk0LAbPjGI/Kiz6zgwhv3OIX2015hXmGMbskJWkw7W8pDvPyxnbyjs+Ql2HDE6Yv6fgeEdCiIiakhaU1SwrjvOia+xy7p2KsX1LsrvLz9Y2kfgDuMPGzguZ+zSzhkU6FbB1r4v5SWzKBszWol6AtNPCUbY5NRplxJdeaMgssm2poM0SKCcvkk80rTUYptjuNFQ9HQ34L2NrAj/YRgp9mzPg5IEpzfuByj+uzWKWoXHwhIm2RufI71DOT+v9uDJ2fXRPDep5qi//CnpGZLK6zXboGFH2OpHOHpkd7VLRFEBug2xwbPW181PnexTQ4iqXB3maOidhhXH8+dbiEiGFAdQjWO+QU/WQoxnU9uHmUSjlFzbdZc3cbGyyXcLyhh7pOADJ98eS9z9wjp1QyJictiaNB9xqdt6qQAMEO2/TsUJhn5A9Dc9xnFTCUEgTCOGw6MXERUtvYrSl0qBBpG5TGXdj4pvQ9nePBsQ6aIkVVCtqiiKE4GV1NGpz+ZkfQJ33k3B4IQn7+i0aehrqOTPwHiEEz/lZ2DvL0OrPy6KDptR2KkcIXgpyKGLRt8puMUtak4djFGXQQ8fNfdyX6nub/wB6CpaLCjrE8ltCk7RAL8IJUQl4wtDbN7HyJiUozldDh7h+m+P9mpmX5k8gf07jfVWb2/4nXHowt9sqEm2AScQ4MDLyua9RqNf7+7/+ec845Zwat97nnnsuCBQvo7u5m7dq1XHLJJTzzzDP85je/ed312425fwPJqlWr+MhHPsLWrVsRQiTeXNd16e7upru7mwMOOIDPfvazbNu2jaGhoeTcZ599lmOPPZZMJkNbWxsf/OAHKZVKyfEoivjkJz9Jc3MzbW1tfOYzn5nB837TTTfR1ta209LVGWecwXve854Z+6699lrOO+88zjvvvF0mWXruuec45ZRTaGpqolAocNRRR7Fhw4bk+HXXXce+++6L67r09PRw0UUXvW4dKaW44IILWLRoEVu2bOGyyy7bCa5z1VVXJbqr6/W0007jyiuvZNasWSxatIgVK1awZcsWPvGJTyCEQIiGJfZf//VfSf3mz5/PV7/61RnXv+aaa9h7771Jp9N0dXXN4OhfsWLFjJWAP1T2V7/6FbZtc/jhh8+4/oknnsjIyMhOATXTJZ/PJ32ivt1999384Ac/4JZbbmHvvfd+PeoEzMemJqFkSSpSmN9SUpKSsoSSFJRiHLud0dg5jZNTlKXBf1YFlKTV2LTFlLapCEnaDU1ApmX4dDTQZAXkUwG2ZXDsVspgXiMliZSkLCzyqQA3H1ISFnnXJ5WNKAlJk+PT5Pi4eZOIqSRM0iGZNl5DYTVeaQXhoEcnaMYmGp4ki0BNhuSVYbgIJ40hW/+I1OK21CQJRrwqDA67FuNaPWEoDa2sQKZBpk2Zuh7q5aasBla+JCGVDbFtRbbgk7EisjmftB3iaoWrFVJqbMskLKpIKMc6L0uSGIL6M6gJs9/OgpNTyfOpxs+wZEkq2qKGTPRX0RYVbSWJehwrolDwKEmJkw7NpCHepNAEiATTXe8f9fbX9VM/JtOGH93KNsrW9VATMGkJJi1ByYJ8zsPWGltrMsWAQJgkRc4uEhuVpaAct7cizeSlJgRT2qY5guYIapMOrtb4FYuqaOCPa5IZ/5ckpHNBEkgo0IneytN0WxGSqhRUpKRacygoKCgIJxXp2Ntbk6ZP1Le6Xvy4rbmYp9+qxxrEOqnGdZq0JCVpURPGcKvEdShLQSlwKGubIH7GBosuqEo5435+3KZJy9RdACkkKSQScLWiiE1TZOAoKJ148JEW+CGEEZ5sXDPEPNOSNmPYF1CWJoFWRQrTh4SJk6gJmei4Pj6q0+pW132931Sn7Q9eUabelpI0uHHXCSmKkEy8ufmQfJNHPutT0xZhfA1FQ/cqrns5rlMlGXuSSctsFUk8tmKdC4uyNIG35XqfjfVRivvspDWzT+aVwtVQUDFscZoFqoPIbJGipk1/LEuZ9Ks6Vt68L811M4bLEqRI9DFdj14cM1CL2+Oko4b+kfG1ZNx/LGoSpqRgSgoyWiTfeF/EMTjTdObF+krZEYGWhLrx7hToBHPvZkLKtRSVuM41MVMnfw3iui5NTU0ztlcz7i+77LLEJni17YknngCYYTfURWu9y/2vlCAIOPvss1FKcc0118w4dsEFF3D88cezbNkyzj77bH7605/y29/+lqeeeup1t3m35/4NJN/4xjdYuHAh//7v/87jjz+OZVl8+tOfnlGmVCpx8803s9dee9HW1gaYII2TTjqJN7/5zTz++OMMDg7ygQ98gIsuuijhf//qV7/Kddddx7XXXsvSpUv56le/ys9+9jOOPfZYAN75zncmUd/vfOc7ARgeHub222/nzjvvTO6/YcMGHn74YW699Va01nz84x9n48aN7LnnngD09vZy9NFHs2LFCu655x6ampp48MEHE+71b3/723zyk5/ki1/8IieffDITExM8+OCDr0s/vu9zzjnnsGHDBn7/+9/vctb8anL33XfT1NTEb37zG7TWzJo1i+XLl/PBD36QCy64ICn35JNPctZZZ3HZZZfxrne9i4ceeoj/83/+D21tbaxatYonnniCj370o/zgBz/gLW95C6OjozzwwAO7vOdrlb3//vt505vetNN5qVSK5cuX88ADDyTP57XkySef5IILLuCLX/wiJ5544uvWC8Aevnk2RRFSzNbYUi7QZnm0FKtsGCtSjCkeM07A6FYDwYpCyd5Rje3CJa8UXY6B9rS3l/FqNioSOE7EiyOt7J2dolxOJTCW9SLLEHBgxSNAMNqbxdKaYs54rrrSU7w80kLpZYdl7SNsHmqmtD7FspZR1o+2ADC5MUXBDti3eYwtY0WefaCDxfsM4W3wyc83H6n2HQ5qfIoMTRAqHmeKi45azKNPGlfre4+Zg3rJTIALrs9sL4WF+fC79dUKNBVhDCZHa0pSMr4pjbQUqazxLM7zDWQgozQprahIi7mimujXUxZbtrTSlPHYONSMRjA47KIQbIw9w81BTAOa9tm77FB0PKqhja8tWlJGL+XAiZn/BYGWjG9JU6047IthSZkMUnRkKozX0nQWy0mugQcqrfxNj6G57NvRREk5BJFg3WiBg/Oj9PcVKego4dmfqLm0Wj5zfYkSIoGm1CXx2gNKCKa2OIaPW8DswJS14+BXC9gjZeoXKcGTY+2MxwbTU5u6mK89+kYLTAiHxU3j9E3kaU2b9u7t1QjiLKF+ZCYrLdJnVs8k3x43NJZvW67oHbI5aJbPvB0KFX9UbW2eBUBZWszSHpu3t7K4Y4y+4QIOKtFbpI1x7Mc5AMZrLnknYI+l4/zwRdPf3b0LDD8Hbpti9iY9A/KVjT3MZWmxd2qKNWETB2hDerlHoJLcBhIIELRYPu1tZdzhVnLaBDnW4klHZ75C1z4lnnqim4IvmJIWLSqiM13BjletAKpSME/XkoylL5NNElO9aIUJ1eVPrFHeXlKoim+89fFYT330X0BFFL97WcKjpISBm7VZBtZRDi1aVQg4dEQh++wxTHnCbUC4qoVkvGRUHEQ/7TfT/rficWRhDFxX6QQeV5GCrihAovGxGAkyDAiX0bphvamVEVKUpGRpaoqhqEAkjAfarUPj4pWdYtRgMkoR0ZatMVVLxe2xSYsoyTw7t3uCoaE8Rd8YeRUh6znQmGNXYkpIye9lLlkh6HUkW6wI37U5vBKhQ427sBOCEP+lejJAzd49o0T9bTTJgFpg0ZzyIDCrhG2RZrZT4SFdYEB76FIZPJ+5wUw4p61NYPqgbVGMFAUdsWlbKwszhkVICE2qnKPdreGHFrmMT185T4dr3j0/Elm0H6ErEd11WFt87fqY7sBnKzlmO5X4mmacTp9ov9jbzvzWcQ6ohoxHaeZPe7f9KeUvFQx60UUXcfbZZ//BMvPnz2fNmjXs2LFjp2NDQ0N0dXX9wfODIOCss85i06ZNiZ30h+Sggw7CcRzWr1/PQQcd9NqNYLdx/4aSYrFIoVDAsiy6u7uT/bfffjv5vHmxl8tlenp6uP3225OMpjfffDPVajXJIAtw9dVX87a3vY0vfelLdHV1cdVVV3HJJZdwxhlnAPCd73xnRpKpTCbDOeecw/XXX58Y9zfffDNz5sxJsuCC8bqffPLJtLQYI+ukk07iuuuu44orrgDgW9/6FsVikVtuuSXBni9atCg5/4orruDiiy/mYx/7WLJvV8mdXimlUolTTjmFarXKfffdR7FYfJ1aNZLL5fj+978/A45jWRaFQmGGrr/2ta9x3HHH8fnPfz6p+/PPP8+//uu/smrVKrZu3Uoul+PUU0+lUCgwb948DjzwwF3e87XKbt68eQb91XSZPXs2mzdvfl1tGxwc5B3veAenn376a7IceZ630+pMoCMc8cZn89ktu2W37Jbd8r9D/lIZatvb22lvb3/NcocffjgTExM89thjHHrooQA8+uijTExMJLDqXUndsF+/fj333ntv4qT9Q/Lcc88RBAE9PT2vWbYuu2E5fwWycuVKVq9ezerVq3n00Uc54YQTOPnkk9myZQtgoraXL18+g13liCOOQCnFiy++yMTEBP39/TPgH7Zt7+Q1vuCCC7jrrrvo7e0F4Prrr2fVqlXJElMURdx4442cd14jiv28887jxhtvJIppt1avXs1RRx21y6DSwcFB+vr6OO6443bZzgsvvJB8Pp9s0+Vv//ZvKZVK3HXXXf9twx5MoOrrwdmvW7eOI444Ysa+I444gvXr1xNFEX/zN3/DvHnz2HPPPXn3u9/NzTffTKVS2eW1XqtstVolnU7v8txMJpOU/Zd/+ZcZepkeaxEEAWeeeSZdXV18//vff832XXnllRSLxRnbf1ReoCYMlKPqOVSlpBw5VCopakJS1jZlbVMNHNxMaLZ0aPC3wkAGKqFDJXSoVRyqVYdqzaFaTZEhwgssAzkRglAICkrRHGGgGEIgrRjfqgRKCWo1h5wIydghvmeRkSHZVIBXc8gRms0KDYWlZ7xxKRkRVGUD7C3BQYAfktYCVYsMTGeyRBGbIjZ6fMpAgWJ/lhdDQDwh8KSI/zcwDU8IqjEMyUmHpLImU6ftKqpSJsfNkrmgHNmUIsds2iLjBDhORE6G2CgKOiSjFZkYG24JjSW0aT+SamgzpW3zO3CoBo6BOmmLmraoCAOnyWQDyqFNOTQwqKpvytU8G883f5sijVez8Wo2ljC0dw6aJhVRqTpkUgFBTF2oMV7NWmRRlQZKUJUy0YcnTTur9f+FMFlLU0YXnmjoqq7Pku+YLXDIK5U8oiIhPhYZK8LVijBsBLtqbRIH1bCoxnrwhKCmLKplhyYtadKSaDIkpQ1TTVXKBLrTeBbmvLK2yVghXrXhz0r0FtlUo/g+QXzP0MabtMggySDRXmBw4iFJG+vbjPt4qYT1SaANpEhY8WbKlSObasUxfQsrbqeBWVQ8h2BK4GPKBkJQFSZ77wzdCkFZ2ZQCh6lo5rvWUCsaHvuCSKHDRpZfpDBbDNGpUyqGwtB1BkIYXUQWvjB90UBJJF7Z9Keab7a6vht9f+bvVz4Lb0aZxrPyRAyRwaYkJCmpSGlNThnMecYOKeiIooqohYbzP6JBAzqdGrL+LCpCUsGi5tuUlENJOVSEecZlbGrawqvZTIWOKVsf57FuS4FDKUhRDmf6PzPK6LdJEWeYjQ9YliEkiEkJfC9+3sqsONVCO3n/1YSkFKTQQLbuVBENXXrT9GKejenbFWGRkuZ96gUWfmAgUtXAphzFz0TIZLylEAaOhemz/vR+G7e1rG0z9pQkVA1z0JqWnTYtImpVh6rvoDRUoz+PI0j9Ebc/hSxZsoSTTjqJCy64gEceeYRHHnmECy64gFNPPXVGMO0+++zDz372MwDCMOTMM8/kiSee4OabbyaKIgYGBhgYGMD3zYrZhg0buPzyy3niiSfYvHkzd9xxB+985zs58MADd7JN/pDs9tz/FUgul2OvvfZK/j/44IMpFot873vf44orrviDGK/Xg/2qy4EHHsjy5cu56aabOPHEE3n22Wf5xS9+kRz/9a9/TW9vL+9617tmnBdFEXfddRcnn3zyH2TOeS1Wncsvv/xVPc9vfetb+eEPf8gjjzwyA6oipeSVbK5BELzy9NdNK7krXU6/fqFQ4KmnnuK+++7jrrvu4gtf+AKXXXYZjz/++E7R7q9Vtr29nbGxsV3WY3R0lIULFwJm0nPWWWclx6Z7+z/60Y/y0ksv8cQTT7zqRGG67CqwSPSvxXVTRFvXwnAfyw86gWjzGhjuY+m+R6D61puCk6Psdf4PaEkVaLFz/Oau92L17I2uTBC99JgpM7IDalUoNEG5xJVfeJHvviPiu7cW+eDbzLL1Fb9upUVDSqc5onMHV4+38y67Ri5vXm7tB4b84IECLTrNh9/Sz02/a6ZFZ/jgW/r4wYNm0teiXfYI4NQj+7nvviKhgPcfUObHv5zFm6RZtv5wzwAP/qyTU1Il+h9Lc2nrOA98q50LsmbStO7HNi3FCm1WmVrF4fRfrkKPDaArE8jZ5uWc/N+zN2q8H8qTvGnVzaSEjRtnwr3vF2eixwaQ3QtRw9ugWgKlQDY+lud86Dcs8JuouYoTazaPpOFgTySQqN+5OeYGmmP33s7enz8DejdBoQj5Zthh6CXJ5MCyYbAPuufwlvf9GEfa/O4Ws9KGUjDcD45DeN9DyK5WhG1x2zU+Jx9lJt/P/SJNJE3CoYfTmi+cn+fy6xSffXMfW1ebSfMWL89b9u/lsL8/F0YGELMXomtlGDOUm2L2QvTkCAxsR+y5L28567t02QX6ggkeufnoRseaHEX0LEDvME4IUmm+ceFjnKjN8/le2uVfz434/g+yLI5CsjkfWc5QjSFKx/zmfaa9gA49ZHM3anwAve0Fhi8y/S21sJnRJ8BpgjN+0YhnIfDQw8ZJIXr2RI8P8v7zf8X33tfC5DUVuooV5l4Tl6+UGs9qdAiKLWDZBLfezvlTJpr4oZ+3sCI3zrqnOzj9h0fC5KipW+BDKh53UkIU8tsPPc1ANceinhF6bvkcesQEoevSGNY+byHa+BT0bWHvQ05E79iEHtuBtdy806K196M3v8yx2Sxi+ZFYc5YQvvAg+pnHOOCwleY+Xg3tlcFOgV8DKVnznrvY64CRpPn//GwPx1UFbyJFao5LNO7zs2vAk8YwK373MgIBZ675J8Lf3Ij9N+8lfOA/sY84g/CR/9toT64JBrZBzzzUb36FaC5A7CTZf+U70FPD6OpUo++XJxFzFsFkPVHZBHLefqitz0FpHDF3MXpiCNE6C8oTpoxXRrg5dGhWFN+z6hecFsgEQvKPMmRBxqVVSz7zqS4O3GM+cq+DUU/+FmbNM4WG+qGjB5Eroge3QbHdzGi2vgw5884QXfPQ/ZuguR0CH/3ic8zN5xH7LDfXiEIYH0Z0zjX9Wylw0xzwvR8j86Yf3vvLDj7Us4P129rZ8mQzkRI8/4QVM1/NSfR/4hljzLvwfeYfIdFemYPzhlBAVyfRE4McfN9vePRbkge/GVIVkjPvOAtiHWA5UCujt76EWLAUUhmoTvH1c37F351gxqGuRSw572+gVjF9YXKMfQtFE9kO7HnFbfzn3eZbcd6394dKGSwLqhXzfgbINfH0qnsp5mqEocVYNU1KRhTTHlM1A1d60HW56K0lorESz93bxkHf3hlK+r9Vbr75Zj760Y9ywgknACaJ1dVXXz2jTN3BCrB9+/Yk4dUrYwXvvfdeVqxYQSqV4u677+Yb3/gGpVKJuXPncsopp3DppZf+t/Ll7Dbu/wpFCIGUkmrVYN+WLl3KjTfeSLlcTozYBx98ECklixYtolgs0tPTwyOPPMLRR5uPbxiGPPnkkzvhtz7wgQ/w9a9/nd7eXo4//njmzm0wQ1x77bWcffbZ/MM//MOMc774xS9y7bXXcvLJJ7P//vtz4403EgTBTt77QqHA/Pnzufvuu1m5cuVO7ers7HxVHP2HP/xhli1bxtvf/nZ++ctfcswxxwDQ0dHBwMDADKN89erVr0uPqVQqWXGoy9KlS/n9738/Y99DDz3EokWLkoFl2zbHH388xx9/PJdeeinNzc3cc889nH766Tvd4w+VPfDAA/nhD3+4y7qtXbs2Cb5tbW3dJQvPv//7v3Pddddx7733MmfOnJ2O70p2xe1bfXytwd2GPihF9PITxmhRyhj21TgwOwppTuVJSZsQhd6xmXD7S2Db4NWSMkSh+ZAEPllhIQsOWQ3DD5lJUkFL0hpSWjM+lqFbW0yFDnOajXGvQ7DjtCo61DHOHAhNSnYwOWNdbYIFLQAN4UCNQEC/ZyaR8/eYoLfXZmlXiZe3tXHA0h30Dtrs122w1qs3dtGkaoAiUtIYF1Ii8i2JoYGUiKY2dFA1H/tMnmrkIyxBMK3viFwRXZ1slB/c1lCwZdMiXQ72bdakIlrxadJpunSNUWEMpbyGLSmB3SSM4djcBuVJc89cTH9WKZnENLP2AK9G2krhIM3HHYyh5zhQrUIYoccmoLlAqzIUgmAwypV4nDRpQx+qSSHTEtsyPi6N4dDGSSHmLzGGvZNC7BF7o7yaMWjnLUKHHpFWvFwbpGBnEM1m/OrJYWPY+1VTXmsIfJoVCZ63IC208pMESNLSOEJTU2acqYENxsBUCpwU0fB209apCQ714wRmT46TVwX8MUE21jVKGWNITFuYrpZYQpbg2V5Goy72aBkz+oqfMZj26nIJUWwx42Dcp3me6bPDozbdkUkhJVq6oanNXD8K0SMx33nnXPTLa+iQHi+JLPvlQ/RYn9FBXLfohYfM2NIKNfByYpxHT8ZxTZ4HYYj2PER1ivDxXxrdZ7OmTYCuxcZwacyMNcvGkoa3vi77BzbtVgXXCRl/OqJayiQJu4jHU4TY2bB//JcwFtP/NLfC1Dj0zAOvglYKIaRJIIahRAUQmQI69BCWA80dM3Qq8i3osT5wUtDaDZaDyBVnTHyFmzOTlbgtR6sC3VGQeFxnpTK0apsWLYie24h7xt+hxwZg9oLGM+yZh7AcdHkC0T4bXZ0ydS80mfGAmVzR1m3eZ+MjyVgRlvlO6cBHdM9De1VzXWHGlj27gJoy9+kQHtm2kHxfgBdaKC2o2OAqkcQUGZ246IlB0zfcNIyPoJsMlJVMHsqTRL3DzOuAx0bbzeqhlMaoh5i/1QbLQhTa0ZVxtF+loEhIA7SMENkiemrclFcK0lnzngAKy2zUNsNEJGYtNO/3uM8mk+bJEdJ2SLGjShRIxre5KC1QcUJBiBmJlAn67Rcueutm/hzyp/K4/zGltbX1Vb/hdZnuHJw/f/5OzshXyty5c/8gmcbrld3G/V+BeJ6XUCuNjY1x9dVXUyqVeNvb3gYY2qRLL72U9773vVx22WUMDQ3xkY98hHe/+91JYMfHPvYxvvjFL7L33nuzZMkSvva1r+0yw+q5557Lpz71Kb73ve9x0003JfuHhob4xS9+wW233cayZctmnPPe976XU045haGhIS666CK++c1vcvbZZ3PJJZdQLBZ55JFHOPTQQ1m8eDGXXXYZF154IZ2dnZx88slMTU3x4IMP8pGPfOQ19fCRj3yEKIo49dRT+dWvfsWRRx7JihUrGBoa4stf/jJnnnkmd955J7/61a9eM0AFzEC7//77Ofvss3Fdl/b2di6++GIOOeQQ/umf/ol3vetdPPzww1x99dVJNPvtt9/Oxo0bOfroo2lpaeGOO+5AKbVLTtvXKnviiSdyySWXMDY2lsQwgMHi1ydXryZ1nX3hC19gzz333Il6K5PJvG74krWX8cSo7evQXg1r8eGozWvQfg05dymq76Wk7Ig3SUuqgC0s5Ky9kd0L0eVxMyEAY3xFEeQLUJGUdYguK6oiRfuh5qU2dbdCIvGFoKWtwsBojqwVJjzqWVsRoFFoREoS1kOrbIEX/05jlpeFLRPmDKcng6Wh0zEf4sp2SU8QMjqUoztfptxn0x1ETAwaI6nd8ky2TEdhBxEiXUBXp9BeFZk2BnXyf3O38aT5VdN2IbDrS+p2Cl0eN2X8mjHmsvkZxuWIqvF0yqFMxDgO4yJiQLjk4mDMkpDMCiCc1IiWLuPtzjUZ4yj2QJNrMgbA6BB09DAVVklLx+wHYzSMDhiPf8pGtDUjbItR6SHzxmjw4qyWCpgUCpHLACavgapzX0NiKOqBLcZIr04lExbRNQ8mqzDci5i3DwBz3FYG/AmoTMWdykaP7UB07oHOjiaGx7gEO/5sTxIhHIdQmMBlFRloiCPMcTl7cWKEEPqI5m70+ABqy3M8njJ6e9uBRUovQ6pFG+8lIGzHTM5iikPsFOSbWUcFZ7/ZtD5QoTKeojVbTJ4xUoKQiGJz4om3mhzG467fEkXY6XjyUx43hqN8haE0MQSFIkPKpVObjMOifR6MbIvPm8BaehTRpqehUkLO3gc9uAkd+FgHGc9ftO4hmBhHZLOIQjvW4sOJXnwYrZXRISBSGbRfNX3Dr5rJgZLIOupQwlonorOaIhtZLNi3TG60gvVU2wwcroCGYX/UWYSP3oZ92NsJH/m5KeCkjPG4w/QB4ThgNzyHws2h4zEh0wV0ecJ48Zu70bHxrr2qaef256E0Di3d6MBD5lrRjqmw9qtmchyYCfVDskS7lUPVKTfVKI6UgI21755Ez9yNXHQoDPaaiQfAcB+6fZaZWI/0m7+ptFkBy5uxnIyrplYz2RgbQ+SyMyd3ozvMJK0+aXBSRENlRNq0e0SnqI1blCObFtcjUgJXGQN6usmmgxDRNsesUAiJ7i4jC+1Jf9POANbsdrYN+RQxDDhCOuj4GWPZpl5SooMqws1DFDIh9QzjUIeeMehTafPujVcbwNDEgmHK0aP9xui3bChPQX2ikc5SC20mhzMEgUWkBY5USGEm2gCe0GBLhBR0ah8xf0/+HPKXCqj9/xfZjbn/K5A777yTnp4eenp6OOyww3j88cf5yU9+kgS6ZrNZfv3rXzM6OsohhxzCmWeeyXHHHTdjeejiiy/mPe95D6tWreLwww+nUCjwjne8Y6d7NTU1ccYZZ5DP5znttNOS/fVg3V3h5VeuXEmhUOAHP/gBbW1t3HPPPZRKJY455hgOPvhgvve97yVe/Pe+971cddVVXHPNNey7776ceuqprF+//nXr4uMf/zj/+I//yFvf+lYeeughlixZwjXXXMO3vvUtli9fzmOPPfaaQaV1ufzyy9m8eTMLFy6ko8N4nA466CD+8z//k1tuuYVly5bxhS98gcsvv5xVq1YB0NzczK233sqxxx7LkiVL+M53vsOPfvQj9t13352u/1pl99tvP970pjfxn//5nzPO+9GPfsQJJ5zAvHnzXrXu3//+9/F9n8997nNJ35i+TQ9Yfi2Jtqwh2rLGeGijkGjT04knTQ28bDxd1RIEPk1OjlSclUcNbSF85rcGZlCrNAx7pYy3zPPICRuRz5pU8GsjJtdG5LUkrw27xdR4mnZtUYls0oWQdCGMvfHmw659hUSg0KCM577uvXe1RiuTCEoC4ZDx3A8GaQaDNNk5in7HpqWtwmApS25WyKBt0dRepam9ynDkEimJiiRhaBnPlmUj0jnzO/Z0iWzBGFFKIWyXWuQRqIhq5FONzAdUZApGZ/FvvFpDJ4FPq3RZFlg0YVHQIc3aokv7+ELiC0lew4ANdpMwHsZck5koVCbMxzudNd7E8iS0dYFXI2OlcKRt9tePWba5Zxihx6fQfph47lUpMDqLn3uTluhy1TCE5C2k1CaJFIbaUjguonueMawdF9E1zxj2UWiMo665aL9KpBXbvVEcaUGhBQotCGEh2meDX51Rv2YFYSQJI0kBy/QXDIuMtAyrShRnyFSDm1ADG1D969FjA6hNq81KUnmSg32bg32b8tMTZHUje27dCyvsV9DceRUWkSV4rpfRKEW+3UN75eSZJTCq0hRxpiaiyYCmOT5Nc3xGbAutBUqDaGpHdM5FdO6B6Jwbe1ht49GvlOiQHiOWjZsP0eP9xlMf+MYIf+nReCwF6IENZsz9/9h783hPqvLO/31OLd99uWvf3uhulkYWAVHcF1CjIGLMuIzKqiOQTGQ0YpJxS0hiouanIxrjGvZhNIlbFBFJRDOIG6IIyN40vdzu23f/3vvdq+qc3x/PqfreSzcGxjVJP/2qV39vradOnVP1LJ/n8xhDctf/Jbnr/8ozjCLZ3l0i/sm/yNjzfJSfk/uyBhXkpO39LkR9PG0wfSnUZPtwbOQx4vUZLnRZvteysC2fGcHCciTKU+axTxX722+ExoIsUR/bXBA4S7c1mNtO6Ux/q7AwmDsl51BQzljKl6QPPB+qwzIuCpXVnvsgN/CWJzFPsWXGk5jxJGI8iVivS4xanxEjnnv/yafJGFy7KZunau0WuVa3haqPiaGwNA/5gsAEux2ZV9VhmR+Lc05xjrLnB6DG1g/Ga9SHbhs9UsxyFUZUn3w9oeTF9GOPfuLRcVSnigEbjcoF2KVpzMN3Yibvw267neShH5E89CPs4hS21cBML7BxbImG59FO+zQdS8pz5Wc1qliXwnH9DrVHZJmqfGkwvpJE5mUcQxxTPELmgg+o0Q3SR+MbUYdsRY2tl3u1hkIQUx3tUB9tSzqG89hHznsfrMDuzxNgd+/koPzmy0HP/W+YPLJi6pVXXpnRWf4seeITn8hNN930qNt93+fSSy99TOWM9+7dy5lnnrkKvnHxxRdz8cUXP+q55+YGeM/jjjtuFRPPI+XCCy/kwgsv/DfbAQcOY731rW9dhRv/3d/93f0KOr3jHe/Ifj9a/z396U/nJz/5yX7rX/GKV2SsQo+UZz/72XzrW9961Pau3PZv7Qvw7ne/m7e97W2cf/75aK3p9Xp8/OMf5zOf+czPPO6KK67ICpv9vOJtEQYfs/tubKeJt+VJmJ13YdtN9NqtmL3OfWkMjX4TwjKB8tDjW9Brtojn/iHHv9tpyoe3KPCwZRtj2xEJFSpHywd9aZ/BQzOColztMbuYkNfJwHMfpp57hQq1q1zrvPRONbWZ515lcAN/LI8PjPniAezuVeKpny8wWurQnvIYTRKW58WzNeI899oz+H4CuRK0F+VDmXM5Gu1F6HVR9bXicet3CHSwynOvvADbX0DV1mSeTPLFVQrMrOlxdxDSIGZZ+SyohGkVUnCeuiUNEzEkTTuA9RTKqMrQAOJTdEnmi7MwMkE76ZHTgShLIJ7KhWkollGhj6pXUEHAvO6gq+Il7a3IJ2kogyqX0ESYdrK/5z6OxZM5sVmiFvMOfjJ2CHRbMD+F2iD1FCbCOjPRkqwHUZwW9qFGN0CuKOty+VWe+2USCHxHmTnw3KfJfHrisAFMIYkEntCYxiQxP3ae+99+Uo32gxDUbKbY4/ni0XSRE+UF2EKZ+2kTHLOe+rc6tOZz1NN+S9sMAuNwEQCvHrK0Tdo6lCQoZdEK6CwLJjvF3GcQh1koVZlLcgwR02976JGNGOe5pxXhbT1JomK5RcnjmN0hnvsjny63ee93YH4OcjlUaRjv0CeTPHgr1hiso9TEExicKlSwfu9ne+47Hpu2tiksdvF+NGAg0a7QVArFSRV7/4QXEX//y9nzUoUKdnqXGHmBL1CWVIKcg3m4+dKcx/Y6qNTrDNLOsU3YyXvFcBl2ynOxPtgnilHFivQlcJtqsc4rZpeZNAvktMZ4Pt5Rm4nv+IZEG6d3o9Zukb6f3oUaXS/tbcygykPgBYKxL8hczuZVuS59ODuDCgffOOUF2MUZ1Mg6mb8AfohZaEuhKsRz31t6hOfeQs48wtMcxaih9ajqOGgPO7o08Nz3WqA1enyIydk+NSue+1UwMq2lHoHS0G2hggIUKjT0AH5qtRIjJl8UpT4IVnnuOw/1sQpiC3ZxWvo/COX/qoN5hnk6kc/yfJ6o7wn6RjsaYDcPI6xEbDQME6E2HMKvQn5dbDn/UeSgcn9QMpmfn+fGG2/kpptu2i8p5KD8cuQlL3kJDzzwAJOTk2zcuJEdO3bwzne+83Flxf+8kirvanyLfMwm7xXFI8xjZ3eg60K/ZfMl8n5IK+6Qd4pUfOt1qOoI+hCBaln3cU0VniXTQw2NEStDPCsY3UnbYV75jHh5cuWYYFGYPwYNgnkiEiXrFogxyscayz4rintfBbzU62Jji2eFT12P1wEyhou9O6psKi2zrV3laVv3sOPBYQ4rLbF9SWAsTzxkBqUtSaRZaBawKXyi38mgFGjB4ttdd8sHt7WEpzTGWvFUg+BhmwsDD6AxqOrIQHlJYjo2wkMxZ3s0dI7dtsVmv4R2bN8Rlo5SeGUlnrvxjRnWVq2RCI4qDwuO13lIi16O6d4iqu6oXJemYXwjFGuo6q0QxTBUZ1oto4fFMIgcA0ekFdvtMnriCJbZie0PPHZtrcgdVRUFOYmhvYxNogwWQmdZPKadDnZxhrKXx1eagg4zBS1TRHutDE6kwgLzKmG+I8rHVK4Dfo2uskz5Pk8a7cEM1Au9rN9su5EpPbYjXnVVHaHt2NlVuciCtnhVH5saZu65pf1vF6ZQ+RIaBZ5H13hYA6rm8nvyLbmGNdh+N8sbUIWQnXukrYdXGuxZqjAUdkWh6nXlWfe7A6MriVHVEeZ8j7VxxMJckTWzO1BOqcMazN770RuPwuTymOnt8uyUxuy5D0ASbnNF7E9/hI17xN//Mt4xzyZpLmRJqgShQFmqI6gwD9bQMx6Nh0W7z1di+hjuyQWE1ufEUKN8qTybFvEa8fp0Ek+SZxdmBYrTWMg8+ADxN65BP/MZJNvuQp94JPakp4lymPbr/KQYUv0OzO6Q8dFrYxcHEEHba8GeB2Qc9buDuZJ6qd1zVXnB45NEaBTTvqLtlLu+SdhnuyziYZcVat8kSa8Ly0vYmiQq0lrG5hdQziChUAGWUesPy/rf9pqokbWoyihmdhfqyGNlnqa5DMuuXd1WZjDj+XR3JOhAcGpznseenTXuzIWcXm4Qxx6bG8I1VQ9l3CZG4530JOzS9KBwWLdFMrPTjdkhec/ONmhQIUDyiuzy7MDQDHLYVgOWG5iH7xQvux8SgUQRnKh8Se41yImBFYTS18Di3iLlxCnJWWQ1lrwON09UZYi+0VLcLoR8V7jDFrt5ir68r/M2jx6toXxN13qo4cdOx/jzyL8HzP1vshxU7g9KJieeeCILCwu8//3vPyCG/KD8cmQlhGbr1q2r6gL8KsSmOGmzA7v9bmHG2PsA9uF7YWJjhoVl7w4qfpFW3GHMr2BmdoiiEfWw22+XffbsEFhBuYJtLDLhFbGLy1RNicTlfR6migwZzURk2LerwqjVDAVtvMBhmo1ljIAh62H7hlECalaDsaxT4mmrW4+HYp9DWc4Sbjvf34thY/btO/TZS/zjzet50bopHrh/lKOeNMP1d2zklEPEA33HznGOGF7A8yzlXF+Us8qoeGUdd6DK1+VvpVFDE9hum4IX0oy71Hzn3VMafeiJ2OntkC+JUjq9a6DcG8OYLjBiNMu6wHgSc1RQ5Mj+IGkw5wd4QNK28jyW5rHz+0QxXpqXfpneJe2K+ljPp2cixnN1zN4HsnawNC9wqulF9FAZOz3LGutj5hcBGDU+DwUB1cRylCpjduxmjAC0VKYFKBhL584lqueMY6O+wGyMwcZOcS7VUEGIbS2hhtYwHzUZCSssxR0oOnyz0nJsrgRTO6RPwjzD1mMoJwNhvS5Cp0fV5Dgi6dJZCFm2Pr4rOmRmdw04HJUW+Ea3BXNTHO0KNvXu3MXGeCPd3TE5NVAYSeJBonF5CDu3lwmVw+zYh6WGFxhJ2IUMMoMxMPmw4J49n3hvk00bJBnzrl1jTIQdmlEo3uEUa9/vDrDwpRp2chtDSYJFkc/FwmzjNQbPr1QVmMb9P4HDjobWAnbXfZIvASQzk9gH7xMYRLsBuTy2uYC95w44Xri0VZCT/pydlHbHMQUvZsSRmPR3G9bZgCf3epT8mM62iM5iyD1+jr6bG63Yo++5JM66w6DXhiCXJ/7GNQD4LzibZPJeWLMeuzxH8q1/RQ1XUQUxeNRJz83GO8agauNZkm+mUC/NYW2CHtuEWZYxqA89EbP3fvHwu/lh51zSbdRnk8ozHlnKrl/vyBUYUTk2mwC73IbakHjhAf+E3wIg/tHX8Y56JmZqmxgLOGNwfhrrC1uTWrNJ2tNtwfIidtfDWK3QT3q2bC9WRMEPwkG0zPPJb/HxN4in+5A7+qzd3OBpuxSLSwUSo5n0AzwLe92YtMBRP7oD/5CtoqAHoczLcl229zsZScHGXIsH+hX6zhuvglx2XVxOghpbL33UXKBsFbYnyrvtJvKumJ+S6NjinCQZt5YAGDuqTevWEVHySlU5n+cPYH6IQRMoS1iMiXsefeOR0wlDhS6LHWlLkgMzNU+y0GWPX8Xc/l14ztkclN9sOajcH5RMHmvRpIPyH0v0qDAiqfoExvNRhar8DvMQFlDFOiBe+ZnuZ+gmEXkvh954NHZqG5SH0M4Lako1+aCFeVShxGRyD3p0LUs6wncOzodtl3ntU/dDnjTSZna+TLMXkPIk6bzHNH0iFaDLATPut8p7TCEKZlcFPMMkqFBn5efzT6yT3J3BQ1m8x+eIqMfk3hrrx5aYf7jAlqTLnknBBW8pL5EvRVij6EW+eFHDAqo+hiqlYesCqib5GEoH2FKVuf4SiTEsOs+9qoxCr5UdTxLD0MQqz/1U8nXm/CJTtsOCrvCQ6rLRL2RJT/t8qBvwqxo9uhFbGUYVa6LEVaQtKl8R73S3jaqN000iZrqNQdSksyQsLmEBffc9qFyIGhliRk3ijUq0oqE8NOKdf9C20JsOY4adqBVfgo5W5A/Po/wcNl9E5ZwC57yZKlcSBTjMgxeQWEPPREQmQrlEZKwRo6BQgbVb5O9ciXl1G82eRH0mwzaqPsai7rFX5Ti8HhHuFQwwgF7/BMHsp/2oNCqJsZUhHvLulsdz+DBTP4LchJbnkBogsIKxZRgKFabst9Abx4Ee1qis3+i2MuXeeL7AgbTGX1Nk8VZXOTbo0ooCcjqR5MZuW5RAVihkuRJqwxEs6XsZS2LiWKOG16Gqougaz0fpADW6QX6Xh2WerYBj6OF1JPki7HxQknHNdqGZPPLYLNIgzyNC5auuqyP6ybfp7Rzc+14Vsy3IkTc5jljfwCv0WTNlaLk+GTYxXRzV5fKiJM42F1CFCvqZUg8lmbwXb/0TiKceQk8chnfSkyRKkeLT0/Ee9VCFqsyV6ohAUVyfqPqYGHhKQ6Uu23otiQamFKIg7xglUbLdfIO1XoFZx062N2kSe5aeNujhmoOgiIfaNGayc9hWQ/ooX5L5216E8lD2/iIIoVCRCNj8JOSLqEIFNbLRHT+P8nzZf+0A4pUsRigtlMUzepy183nuV0VOKswTxx7VjsHDUnSGqAG8Y4+UhNrKqEQ3ygPCBFWoijGU+wZz3ZBQSTVnVRnNWLqUF0jUME0Gro2jgCVtURXpN+335V1RHZUk6/q0nMO9LzpTXvZ+UfmSGKRBKDkKeQc7HJogQWFijbUKz4GLWr2AUMv9JICeGIZwiWpiUMeuZtj7ZcnBhNqfTw4q978CsdZy4YUX8rnPfY6FhQV+/OMf78dx+ouS8847j8XFRb70pS/9Us7/65STTz6ZE0444THlDfx7krPPPpujjjoqyxM46aSTePvb335Aas1fhmQezPlJmNqJHZmAmR3CRjE0ljFfsDjLWL5OJ+kzGlQwD98hDBjdFsmeB9053Mc2l4NWkw1eGbO4RNkU6M7IeQ6nQMUoaollbqbEuNIUvIR8zXmk+j5jhFSsxnZjhgnkd9+whpQ6UjOvtNBjWili0/nJIlCh66AuIyfnufaLIb977G5u+tEGXvjMSf71+6Ocfoiwz9z20ASHAYVyn3wYy8ddOw7slnjLla0LnCDqZUpd2S+w0FtGpUm/3WV0dRwzvV2UnfbyAHoA4Pls8CpsTDTGK7E1aHK/LXNY0mXZyis4wRdvo7GYXffINVOYj/NA2/R3Lo/tLDMclKkFRUwaNTFGWFx8HzO/hK6XYW6BrUlAvFuiFR5ryBnIW8vhqojZNUmIxqv6pHD8wEIy2xP6T8A25wU3nLj6EU2JDghMqYFWCmstRT8/SFDtdzIKyCzi4IccmnhUcrLPIaqEXWpSNyHaGpK+KBe92FFh7rwro2clXxQPu0t2PCmlwrx1gYm4RGcX5LvLg0Ed9bCLbiwWKtjZ3WxWefq37yRhgtJIf9BvKZTH87E7tmGaixDmsVHCuqOkrf/8kw0ck19itlOQfvEHuHK7LIqf8kPs3u1sNl22e3mOnWhh5nahXLvs3B5hvZnZAZPbsRsPQy3PYmcms2YnO+7G7tguntrZHdjZSRK+i33g7ixZ1SLRtjSihDWEXoJfdzSxXcvhic8zC/NEkUd3l6G7FLIn0CugDgGRIuOwt/t2iGd7ehfJtrtklzXriacewn/yS0juuYXkez8UBqay8/qOrEUxLGM1iUWxNkbmUQpFivqS5Dq8Xvp3xVxR1N38aYli7uewScRWm+cpSTsrzrWlUGOLzVMzCrNvDt+xBPlP/23iu28GwH/yaZjGjEAMo77kPyzOQqeFTfMEqsOybXY3LMxg9+6BcmkwT7UWT3jPJbK7CE64dSTzGBzmtRjd3GLrT/MstfJYYE+g8SxMxCp7PvH3f4K/5QmSAxPm5b3o6rzY2qgY7VHMlvEW350bJ1EDLD44777SEgXNlcSo73WpGck9kkfoSXRr3y5svgCL89j1m7PxXD0+JNmdDhgjeQ3GQHVkEI1tL1P0I6qb+tgYpmbFmCiGEYtdF6EBzPQCZrlHQBl7xw/hlDfyyxZzUL3/ueSgcv8rkBtuuIErr7ySb33rWxx66KG87W1v49prr822Dw8Pc9JJJ/HXf/3XHHfccb+WNnY6HdatW4dSisnJyX+z4NTjkc2bN++XKHxQRO644w6++tWvZlSbMEiyffnLX45ekZS5Uj72sY/xjne8gzvvvHNVLYI3velN3Hjjjdx+++0Ui8UDHvtISQs2qdo4plRH5SuooQlM+V5RaFOlYn6Sfd1r6ER9PKXxtpwgH+nysOBIEUPBthriSVqaY3dyO3p4Hcu6T35MVIttkx0q2qfuhQwNt5lulOgZj96SvI7yh3rM0CdWAboQME+EUQE677HPee57KqBuTea5t0D+mCrmPghTqsXvt3hyt8T2nwxxXG2ehftDDov6TO0Sj+emfJPyUNd57j1UdVw8XM67B6DCvHB4O0+1qgzR6LcwWGKHK1eVUVFu6hOosIDRGlUZGiTIWcPuZJlJP88222J7v8z2fI8teuC5nPGhakD5Cn3IMVLYJ/Xcr2Dhse2GYILrE8z0l2jFHfShzpPm2F9UUEDf9VNUIYcaqvOAtyeDFSRARwsTxkO2jd54KF12YNoJad56Tym80Zxcv99B1dYIdtgp96q+VpJKmwuo2jh9E5F4IctRW44BKNagtSCe2lTCAtu97/NEB7vZGbZQtTUs6g4TSuGFlgRF6Em/6s3HiedeueRCgCTCLs/y4/BOAM54So2p7VDY6CIoqdKSK62AVlVQE4exw95I+MT1eP83prMYUF/Rb6mSbIIQPb5F8h5yNzF9v4zJLXRY7uYoerF4uZNIONuDnEBTQObK+sPYre5kOIlpzBQYGduUKbrGD4XxZmgCU6qJN7Y2jknx3YCujpOUfgi7HkKvOQyjNN7hJ2V9DUgEJe6LB9/xlvcTj6TpHqCBh7yYW9vD5IzlkI0t/Nk+4/ssbYdZG0ukcFLKYa/WbhElfGIT+kRXwG15Dj1xGMk9t+Ad9Szs7gel5kIKF0nnixurKixgwzyqIp5kkDwdnSuJV195qNKwzJXK6KDfoo5EfDwfFfd5UHUZ1UXSQqjb4znaXkJdB+g1I9LO6gjxT/8VveFoAOJ7b0Gv3YqeOBzbWZL5W29gu0sDz70furbWsfVJqI9IuyekWCCthotU1qAjXPxKB/R2/iNeTSIRDycjVHd32U6B4wuLxIlmvGfxraXo3gcWhf/kY9ATh0sCsedjR+ezZ6yKdVG2c//C7pk8BQw9raTN6fj1fMeUVZB9K6NQgQW9AolurBAapJ77xrTQxTqjvH1vl6zQrHM64PvSf+59repl2nFAc9LHxINvTacfEGq5nwSLHh9ChctEKNRxB4tY/XuQg8r9r0C2bdvG2rVreeYznwkIu8ypp56asZ1MTU3xrne9i5e+9KXs3PnroZn6/Oc/z7HHHou1li984QuceeaZv5Z2HEgOVBDrP4p89KMf5VWvehWVyuADf/rpp3P++efz9a9/ndNOO+2Ax/3e7/0eX/rSl/hv/+2/ceONNwJw00038clPfpJ//dd/fcyKPYD53tfkR62OPuoZmFu+AsOj8vsHX4eCnEttPIITq4disezszZHc8x3MbbeixoZRY1JPQR1xIvaO70nBmyBgjS6STM4wmtToTMvXekyFzNg+PRVS3dBnYkEzrUJGHYtNcU+TCUZZJiHa22GCYZYx9Pf0mXCe+0ViNo0t0dsphZGqiUXXy0xEltgFo3ftqLOh1GR3q8xYscn39q7h5KN38/kHxRh63dMmWbzPx1poRgHmlq9gkwRVH8IuC24Va6A+LF4+QBWLPKm6maLyWUiEC9t89yuYh3egJ8ZF2RoaFjq6VFsOc6z3KtSsZqMqEilF1ybsCqCc0lq7XeNFg/nuV1HHnIRZmoUH70Id+zS5TnMeHrgLDn0C9v5beW55C3f1ZzCT90pT7/kx+rinY1qL2MVl4u378Dd1KKJJZsW77DHCSGxY8DURBttoUMenu1dlFYKrswlKKZIvX41avw7701uxcwsoVyjN9m/F7JlCrxklueM2XlQ5klnT5ajcGsz3ZSzZqX2oQw7B9nugHLa7WKJgNW2X1Bkqj+ThPcBQ1tUTxbYwFwHmp99eXWiq15MKm9auSrYLLJi2wXz3K+LpTPdPk3uVhkqVYRU66s+ATivA7BZoT4oZR2uY2YvxQ+i16W9fZmdTkgePnJjjrn2jHFZYwtx6I/R72fWt8+oqraBUoaMVY8bQ6oQyt/Ki6KrNT8DcfRuMjqOPfjbmO1+GQhG19UTMD74h55pYjz7m2UT//M8wfBPmzjux2+/Ge/Z/IblRsPA2ilDDgjnHWsgXSFDMbnPKsrYU0Sxp2BUYfquZkPQUa22PtouKPOGQWXotH/PPX8vmqlAp+pI4CyTf+le8k55E8r0fYnc/iP9b54px5fo1+fpV0gG1OraxiO33UPVhbLslFJOAGhrGzM9CP0INDWF33Lt6roDk5yiV3csQAT5wnyeRvDW2zITKs8d2SLbvRS1+HVUuYfbOokddvzXbmHIRNTGOOvRI7O77Ye9O1HHPkIJXgL3vx7D1OOzsbuwDP0Wf+GyJGtzzHRlvd/4EfdhhmMUFVD4PxRI2img+pGg5qtVlrXhovs59eXhaMSKONVtZwvcMBTd/kkijjvkdzI+/IeM1HbstF8EplCCXo/WDOSb1BtYmfdqJh/nudaujSN0OdnEJde89qIk1UChSN5p4rztP3+Bv+zEUyjIW0jwMV1Bwz0M1tkQxBrB3fAfbbqNyIXZhEVz9G1ssEVvF7L4yidEUgoh+4tFNPKqhtGVdrDB7ZlG1ImP0YW51TZVflhxMqP355CDP/S9ZzjvvPC666CJ27tyJUorNmzcDUil0YmKCiYkJTjjhBP74j/+YXbt2MTMzwBDeeeedPP/5z6dQKDAyMsIFF1xAs9nMtidJwlvf+lbq9TojIyP80R/90SrayKuvvpqRkRF6vcGHCITq8Zxzzlm17rLLLuOss87irLPO4rLLLtvvPn76059y+umnU61WqVQqPOc5z2Hbtm3Z9ssvv5xjjjmGXC7H2rVredOb3vSofdJoNLjgggsYHx+nWq3y/Oc/fxUl5SWXXMIJJ5zA5ZdfzqGHHkoulztgVbcbbriBWq22qtjWI+Xkk0/moosu4i1veQtDQ0OsWbOGT33qU7RaLV7/+tdTqVQ47LDD+NrXvrbquLvvvpuXvOQllMtl1qxZw9lnn83s7Oyqaz/72c/O+v6lL33pqv54+OGHUUrxhS98gVNOOYViscjxxx/Pd7/73WwfYwz/+I//yMte9rJV1/Y8j5e85CU/kw5TKcVll13GD37wAz7xiU+wtLTE61//ev7gD/4gMyIfs1SqshTK4g2s1iXBLyzI+mJZllyJtunTMn0a/ZZQLg7VUNV6lqSl/Bwql0MVClAskWCzMLL2LNppsb5SwhARQ4R4lP0wwQ8TVCgh2QiDCpWrpmlRflpZU/6OY6H/i0ES0owlUkKR2VOKYhjR7fvkSYi6HsMmprMQUkuglogibS14gRHat6FhKWI0vkEU9KFh6YvRdajhEdTQEExsoG36LJk+83GL+bgFQ2OokSFJTKxUpRJnvihKXb4AxTIRJuMY9wCLxQPyVhYL9BSCfS8J24cqVuR3WBCPYr4E+YJ43UpVlm1Ez0SofEmWUlkKD+VL4HnoQgBBwMqC5dZdP60NgOcRYfELBqWs0D1agRIyVIextXJfQ3UYXSNLrY4arsH4OtTQEAu2x2zSZtH0YGjULXXh46/WB/2Qk3oHRZVQVIkUKcsHpHV+TawIgoQo8ogiT/Dglbos5boU3ilVIczhuftI4RLWIFV9h0dlqQ9L35Uq8nexLJSqWsadUhIJWbWUh4SCsliBXBGloe71qXt9Wss5AmtJjIbhMRibyBZVqaIqVRgZh1yOnLX00eSCBGr1rB3ifa3KPAnCbG6pYh1VKmfPD2NQpbzwwg/V5NhcUc5Vq6OGhqXSarEsNI+lKgpLmIsJczHFiihlOetqGQhtP23r0VaytBo5mq0cql5BjwyhhmsCuRkZyjDtati1b8TdQxqtcOONoWFp0+g6aVe1DuPrs3kkc2k9qj6Mqtdhzfr950qlCqNrB/dSrmPd+MyhyaFJnJrnoyAfSHvHRoTBZcgtru2qUhWcf6k6mDu5vCwlicipYkUq/uLyJcoyvtRQHUYmpN3FkrwDiyUKown5YkS+GBFYGRM5FCZRmETT6OZY6uSI+h5R3yOOPUnarY8Mxm6xJPdcH5b1hTJ+UZLXIzSJUjJvVoxfNTKGqlZQayfceK5iFOiiL0vekzGSvhuCUKBH7n1dKXfpKC00m2MTqLFx+X/NGpmbI2ugVMVXlsA3+J5U6jZWESibVartK6SIle8w/I8STf5Fi/0FLv8Z5aBy/0uWD3/4w/z5n/85GzZsYO/evdx666377dNsNrn22ms5/PDDGRkZAaDdbnPqqacyNDSUFa36l3/5l1VK8wc/+EEuv/xyLrvsMr797W8zPz/PF7/4xWz7q171KpIk4ctf/nK2bnZ2luuuu47Xv/712bpt27bx3e9+l1e/+tW8+tWv5jvf+Q4PPfRQtn1ycpLnPve55PN5brrpJm677Tbe8IY3EMfiWfn4xz/O7//+73PBBRdw55138uUvf5nDDz/8gP1hreX0009namqK66+/nttuu40TTzyRF7zgBczPD0KXDz74IP/wD//A5z//eW6//fb9zvPZz36WV7/61Vx99dX7GSqPlKuuuorR0VF+8IMfcNFFF/F7v/d7vOpVr+KZz3wmP/rRj3jxi1/M2WefTbst2Oa9e/fyvOc9jxNOOIEf/vCH3HDDDezbt49Xv/rV2TlbrRZvfetbufXWW/nGN76B1prf+Z3fwZjV/oZ3vvOdvO1tb+P2229n69atvPa1r8367Y477mBxcZGnPGX/MOdTn/pUbr755p95Xxs3buRDH/oQf/iHf8hZZ51FuVzmL/7iL37mMQeUNEEtZVNw/yvPd0mTfrb0bEzfxkQmloI6uZzwK6f7aC3eKs+DIMBiB1SGZgX5CQplhSI7Fc+zeJ5FaZW9kJWWAlbGKfcrJYk0aOHrtu4CRoFBYVCEYUIv9gm1IY49Sjqm1/UpGUPJGOLOCko5ZYVxLZx6tQABAABJREFUIl/IlDtZ8oJ1zuUgzEGxTM8m9G1MK+nRSoRnWhVL0le5vBy/os/wQ0xKd4eE8BWKwILvFhAjR2kgCKRvlc5+Kz8nVIFBIApLENKzhsQaSV4McqLAeIGDsSjwPZTvreqzdHTqtIO1lqRQH6xVUqhJAcai8nmBKIT57Lcq1kTxLYpSSb5A1ya0TI+ejZxSVZX9C5UVHNwh+JJX4Gkj1Hsw8N4CJlFCTWqEt12OcYvr23Rs+ih8FDZ2dUwNcq1CecAGknPjsyhKs17RB0rbwfPJxr/rcz8nSp+GfBCTD2Ki2MPDSjDG3WO2pMZLqQqe73JAxFDJ2p3LZ88Nz5frhHnpW99xlAeSRCn5CZ5AW3I5Rz/pZfsT5mRMpu1OK+oGrtpyTvrEt1C0km1ujSJCZcZxFHlEsQdhKLjzfB7KZbmeoxFVBZn7qlx0rFgrJisM2l+qub4vuLkyMGxlW2FglK6cK6lDoFiRv4NQFFU3PnNWkbMqG7PK1bqgXJIKvuWS4NgLBVS5JO3N5cQQDnLgeSgdyJzwAjHcwsKqolVpoS2VL6EKAwN6MGZDvLLGz0m/eljyQSzRIquwFvpWWGZMot2iJFckfXemzzx9fqnx5CMGI1LfIRu/BedMyRdRuVAq7Lp5ZADlaZSnwVfSXn/FOzsctD3IJyTpnE8N5VJVKlinYzfMo7DZnEzpcJWy2fsgWcE3/6v0pptf4PKfUQ7Ccn7JUqvVqFQqeJ7HxMREtv66666jXBb6kFarxdq1a7nuuusyjPW1115Lp9PJKsOCQDjOOOMM3v/+97NmzRouvfRS3v72t2cFlz7xiU+sKh5VKBR43etexxVXXMGrXvWq7LwbNmzIqtuCeN1PO+00hoYkPH7qqady+eWX8573vAeAv/3bv6VWq/HZz342g8espGt8z3vew8UXX7yK0vGkk046YH9885vf5M4772R6ejorkvWBD3yAL33pS3zuc5/jggsuAKDf73PNNddklWNXSoo3/6d/+idOOeWUn/0AgOOPP553vetdALz97W/nfe97H6Ojo5x//vkA/Mmf/Akf//jHueOOO3j605/Oxz/+cU488UT+6q/+alUfbdy4kfvvv5+tW7fuV+TqsssuY3x8nLvvvptjjz02W/+2t72N008/HYA/+7M/45hjjuHBBx/kCU94Ag8//DCe5zE+Ps4jZf369ezcuRNjzKPi7gFe//rX86lPfYqvfOUrfP/7319VeOxA0uv19ovk6ONfTC4XYjvLmMUpvKedMfh94oslOQ1JHL1jfjsFP6QU5tFbTkCt2YLKFYV2DrBL06hNT5Ckz/Yy00kbvXYTU16bwnrRKBf2RJTcq6c9HzKlE55mI/IVCeX7GyvM3NanSoC/vsIMETV8gvUlZn4sCkYNn5+262zcomjcAXPaYmaWmPJH2eCMp7EjWvz4x0OcWJ2n1QrZvGWeWx9ay9aSUBPu2jbE6GgTa8TL7z/tZVKoqtvCO/TJcj/ub73+CXKP3RY/nttGwQ8JnYLgH/s8zLoj0PUJbL+D7bUFl56K0kzFf89cUGSv7RLYIjmlmYikUFcqOQu6qNHHPifDBiv3GxxLypZjoN9Bj2/hx82HSYzJeO7Vsa5KrqeFVaQmHuU2D2RsOZFSNBzu2kOjajVm7BThupD2vQJ56jqFWz/rtyVhduNRwrThnrE+5Bjpl8Up1FOO5dbG31P0c0zGs1JcCLCHHCvtPOQY7PKcwF7CPG31neyOuzZBH3oIsZoDFF5gmV4skXeYe+/QJ4uia5KMA93GfWg1MPzIDV7xLHpVjX+cq55tjVR9nd4u5xnfgu0ss8/+i3jHiagMdyXJEwTX756TdcV9VH2C3PHrGNk9DQht6rpcm0Y3h7flBGGEctAfO+ogKMW6O9dPiFCUaj38p56B7bmE6G4L76TTZW7t24Z/0ukCC2kuoJ/8ItmnOY/Zfjv66KPxtj4VtUaKNMW3Xod/krxH0jGm1x6R0ZMG+stUNqaQJOjutowmCWtiiy4qdMuyK/Dppq+SToWO1hx3yu9gTSRjy4ihaOclwVed9FzBcI+sRVXHBYYzNJwZE/7TXy7t77XwNh0nY6KzLDkC6fug20JvOBrbamDbi/hHPFXmysiGVf2iNx6b5XTM2C8SWI9NLkH1G7Qo+j51FaAnqnjPeRmqPITZfU/G4EQSyXwpSDVpVZ/A1ickEdUx9+gnnuxYrdbCVi2J3vki3laBIdnh9RD1pF/7nayIlDd2I9W1YiSXtxtGJ5ocuqNMVwfEiebhICCwsNxwlbsVbL7nDoJXXoRpNyTRenluwDLksPW5k77D6K1tHrYFOloJrafjqEdrbGeZZOddeBuOzuhXF9TN6AmHl291UUPrscuz8vyivrAzjQh8rrrlc0w6EgM9cZi8U3SArTWFsQck2Zx/pr6mTdzXLO8eQilLIYhp9+Vbvysw6Ilh7OIyHVtAjQ1yvA7Kb64c9Nz/muSUU07h9ttv5/bbb+f73/8+L3rRizjttNPYsUM4ee+55x6OP/74TLEHeNaznoUxhvvuu49Go8HevXt5xjOekW33fX8/L/D555/PjTfeyOSkvLCvuOIKzjvvvKzKXZIkXHXVVZx11lnZMWeddRZXXXUViSsNf/vtt/Oc5zzngLj36elp9uzZwwte8ILHdN+33XYbzWaTkZERyuVytmzfvn0VrGXTpk0HVOw///nP85a3vIUbb7xxlWJ/8803rzrfyoTllUnKnucxMjLCE5/4xGzdGoc/nJ6eztr4zW9+c9X5nvCEJwBkbdy2bRuve93rOPTQQ6lWq2zZIh/hR+ZMrLz22rVrV12n0+mQy+WyZ7FSCoUCxhh6vR47d+5c1ZaVRsdPfvITbrvtNorF4r/p6Qd473vfS61WW7W8/0MflY+xS4Kj2xokxHWWB55hpfG1RyeWhFqSCNvYh+13B94xlXpcxQMY2QRyOQmPxhYbi9c6wqCBqO+RQxFok3kelVbE1orXXysSHMZaaxJrSRzmOrCy3ciemF68ykvjlTVdpQhzknCYOomVtigtYWe7ogyiTYvXWCNKy4piNilNoI17hJ5PO15tIKnyMDbuZ/2m/HCweD6RTaSIEhBgia2DvyBL4BYpc++87Z4/+P3Iv52iYKx5xHbtPJPOa+/7xFjIhbIAfQWxgh4J5PICe1hRGMcAKhDPsbWJeDfDgih/xkgbgoERGZkErTxht9AeaC8rroT2VkQxgqzCMEDfndsisCovZ4isxvcEIkASuYq/XYh7MhYdNWYGy4mTgXlkHRe/MWKMpKutsJ54KIiFg35lMdCsOFcaWrIOf58LSSJNEmlCDEk6VgYDafB/uni+sNAgkSXbWUbligKrsUYUrDAv991ZzsYL3ZbMuzRi0+nIfTT2ybFGjpXjC2LwpOMsVRpDhQoVNhbYWmCtwD3SflADT6YH+NZil2eh1ZDiaK15bGPf4HmVauIFLw0PqBPTMWBkjqi8GAW23x3MFTdv0rmUFoVSypPk0PKwu/e89EUSyX5BDrSHdm02SpbIDhI7CXzXzhlJ3HXRpCypXz/i2Wjx3ivtoiJpLQTtDTzeK+dPOm7cuyyttqsCHxX4aCsRprRflZJ8GW2lyrKHzaJitt+Rys79rjy75VlZUnrXOEErS6ycdzyJsSsWjMkS6lMjzkI2l1X+AHlo3opIBY+o8pr2iTc4Tnk+sVWEFUOunFZhtqxEwRqsRGKVpqdURtf5y5b0+f8ilv+MctBz/2uSUqm0Crry5Cc/mVqtxqc//Wne8573YK09oNIHPOr6A8mTnvQkjj/+eK6++mpe/OIXc+edd/KVr3wl2/71r3+dyclJ/ut//a+rjkuShBtvvJHTTjvtZzLnPF5WHWMMa9eu5Vvf+tZ+2+r1evZ7pVGzUk444QR+9KMfccUVV3DSSSdlffGUpzxlFXwnVdiB/YwSpdSqdek5UkiNMSaLkDxSUgX9jDPOYOPGjXz6059m3bp1GGM49thj6fdXh65/1nVGR0dpt9v0+33CMFx13Pz8PMVikUKhwLp161bd2/CweBf7/T7nnHMOr33ta/mt3/otzj//fM4444yfWQTr7W9/O29961tXr9x2iyhO7QaqUM1o4FSuJB8nx76g/BzlMI9CMddZFs+bqzqZ8Yt7AXZhn3j3tKbq5bGLS5SswrjcyCIeeTQa8H1DYBXzScgm9xY2rR5llSfCYtt9SuQk+bPTp6IEKxthyFuFbfXwUOQtqNCjYGHJ4XdM12R488RogoqhrRVhTpSFeFlC6GHRSAi618K2G+jhdZiGGGDZ3zM7sPN70CMbJXIR5JlPKQ6jvlAeFuvYJELXJ0j2DQxVla9Q9fLkrKKiAhSWvOObTwv1LFjNopYkOdvYJ17gJBavXOplS2Ls8jx6zRaI+5T9Ak06GcOGXZp2RhXYXh+aLZTnM2x9zGzDtabGSGKJFOQ8D5rL+M7HEwTSL7mOxXQibGMaXRuX59xtZXz/trMslXPrE9BZphzkafSb5P3BGDaLU3JsZ1kUSKUh6lCzmmLOVb5MPHBQOI2lsxCwttpkfrmYXSf1wmcJg5EoTCXroF6diIJ1+RP9LpgEqz1RGFOPfNTDNhcoKg/b6eERkERqwExiDSRG4D9RP6u6aucWKY7IuF7c5zPmdSTBQ3sDWsogB26sKM/HLEwykiTMeR65cozttTMvtq6NY2Z2Yqxw5dvOsjBLlWpSEA4kgTgIIY5ECex3MQt7UGsPzaqX2s4yuj6Bmd8jyqhri+m6fJa6TxGNwVAnwnQtcc9D2cEHv60lL8V2lgfe7rAAST+jMCWJpY+ccpri67N777WkLUMTmIUp7PIsemQDZnlO6FORGhpmZgc0F1DD61bPlbRfhtfJvViDKtYo4ZG3lsi9D8pejpLyKOFh253MGDPzk8IHD8IC026gAuHat/2ujLvUQAVoTGeMSnZxWjzdRS8zlGxjWqJvnWVs1BFqTmPQ9TJmehEAjxz5WoyZHMByGp7kCGwyYhgkDtpi476cB2QspvMj6rmITRtPg04s2irp9xXGuk1ieQZ+To6J+4QoqTwN2DhBeb5U0PZ8bBKhkihLytVVH889c1WsZQ4X1e8MqvJ2W+R1QtxRxD2ZU8YqVqoYJauh2UaFPjViodv9FchBKsyfTw4q978hopRCa02nIy/Wo48+mquuuopWq5Upurfccgtaa7Zu3UqtVmPt2rV873vf47nPfS4AcRxnGPaV8sY3vpEPfehDTE5O8sIXvnAVdeJll13Ga17zGt75zneuOuZ973sfl112GaeddhrHHXccV1111QFZayqVCps3b+Yb3/jGY4LInHjiiUxNTeH7fpZc/HjksMMO44Mf/CAnn3wynufx0Y9+FBAj49Fw/o9XTjzxRD7/+c+zefNmfH//KTI3N8c999zDJz/5SZ7znOcA8O1vf/txXyetdXD33XfvV/fgrrvuyp6j7/sHvLc///M/Z25ujg9/+MPU63U+97nP8frXv56bb775UaE8uVxuP+hONLEZEKXBLM/ijW/BtBvysR7fAiksp91gsdui4IcM58vywRjfInR4rUXZZ2k6w1rbVoOlpIuqV2mpBVLmx2ViEjwiJap3UxkqKh7g8QshXRKqBKh8QBdDDR9VCGm79MsaPk3toUo5EkRZVUrRUVBJKemMePf7PZ9CEBEta4rG0u85thYvkUqlicLTJlNGzcIUemhi0CcLU0J32WthF6dY6nfIewH1nGMnCUJUroSujWG7Lczy3IB+D0BplpIuHc+wZPv0KdG1kXjPnTetp6DkqDBVZRTbXRasfXl4AMvRgVRBXZ5FlYZpx11JfHUKjioNY7vLkBjx2ucFn91QCbo2YE9qeEo8kNgsqoKxksSKQHeUr6FQwaQKvucLtABQlRFRohenUMPr6SUR1bBEO+4OPMrlYVFcy0NQrGewnKYytF0Rq8TvQbEItPAthMWE3XuKGRWmKg9nUA28QAzGuAQ6YFE5usyhIm0Ffl1n3nEATJgpMCosQCFm0fZR9SEMXbzADqIPqbfWmqw4kspXUNUyvSUhMCgag0ldgEm0CpaTcZPHfVSxzpL2CCzEPS1jwjH+mOU51OgG8ZQvTOKNHStjqtVAj22SfRrTsE8oEFVYQI1vgSTCbP8J+onu/Rr35FylWhahUJDlpJh2QhtDohRLNsAra4J2sipMXzCSUa0nDsPGPXRe6DXJlWDWGRrGiLGfOPrPxqLcZ1P+9zYdh+13s/liW4uYxX3o4XWZ4m4WpkR5X5oT43jNZpkrlZHMiDCL+1Y962Ub09YBTtdkKemyrIugQI0MC/xmaAK1PJsZNvSFTlMVKi5aUoLysDgenKTF5ggLqMoQttse1GVIx2xzQcZsisn3AsxSC1UUxTxBEbU9citc22Ujyv2SlXEdKwVJkkUylB/K2HJzXRUqMsaGakRJE21dgreLgsjA1qBaYhBoLYW5TEEiX2lxNq1dpeRAjBwvyOYZgGnGwrmPvLszWE7UQaVjvlDJjBEQw8RTq5XqjrJQyGEbLdo2B/VRDspvvhyE5fyapNfrMTU1xdTUFPfccw8XXXQRzWaTM844A4AzzzyTfD7Pueeey1133cU3v/lNLrroIs4+++zMK/3mN7+Z973vfXzxi1/k3nvv5b//9//O4uLiftc688wzmZyc5NOf/jRveMMbsvUzMzN85Stf4dxzz+XYY49dtZx77rl8+ctfZmZmhje96U0sLS3xmte8hh/+8Ic88MADXHPNNdx3332AsNt88IMf5CMf+QgPPPAAP/rRj/ibv/mbA973C1/4Qp7xjGfw8pe/nK9//es8/PDDfOc73+Fd73oXP/zhDx9T323dupVvfvObGUTnFy2///u/z/z8PK997Wv5wQ9+wEMPPcSNN97IG97wBpIkYWhoiJGRET71qU/x4IMPctNNN+3vDX8MMjY2xoknnnhAw+Dmm2/mRS960aMe+8Mf/pD3v//9/N3f/V0W8fjEJz7Bvffey4c+9KHH3ZaDclAOykE5KAflN0UOsuX8fHJQuf81yQ033MDatWtZu3YtT3va0zJGnDTRtVgs8vWvf535+XlOOukkXvnKV/KCF7wg81QDXHzxxZxzzjmcd955POMZz6BSqfA7v/M7+12rWq3yile8gnK5zMtf/vJsfZqseyC8/CmnnEKlUuGaa65hZGSEm266iWazyfOe9zye/OQn8+lPfzrz4p977rlceumlfOxjH+OYY47hpS99KQ888EB2LmNM5gFXSnH99dfz3Oc+lze84Q1s3bqV17zmNTz88MOroDT/lhx55JHcdNNNfOYzn+Hiiy9+zMc9Flm3bh233HILSZLw4he/mGOPPZY3v/nN1Go1tNZorfnsZz/LbbfdxrHHHssf/MEf8P/9f//f/9O1LrjgglX5ASDsRN/5zndWMRqtlF6vx7nnnsvrX/96Tj311Gz9xMQEf/M3f8O73vWuzPB6LGKaC5jmgngy4z6muSDeJgdnyDCc1pDzA/omJtCBVCGd2yVeOoe1xhjBsq7AdaKllqvty2KssN/kDHTbAUU0oTZo36IddcxK7Hyy4vVsrMU4tpns9Ai7TrK8GhLlD/s0PEWh3KcVBWhfqDI93+D5hn7iYY3g7o1V2Nai86pFWXJg9ndjGpUrYfsdQs+nE/fRSqOVFg9nZXSAoU6i1Ww5ztPmI8wfaZGtnLEZTjdvIbTSVykUJcPIpjjnrBNMdk5j7WoaIuc5F+y+sJ4kKzD3Gug4zH2CzTyUKVc7yDa0kntxHkcVFrBJJMWbtLdqWz+J8ZQW5p4Uc++HA4+40q4tXkZ7Ccj+gOf6xcsZ2tYbYO77HQcBEq+jbS5kSb0pTaLtRjK2YutgO31ZUoiDdfh7rQnxoNcnQ+mnsIckdtCcWDzxUc958X1Hd6gIcDSYK0XpAeQjvU+ls3tMIu0qr4ar5pNy0QHTbghsJO5hl+awS3OCS09iqZIa97Fzu8Sj67zM1nmeiXoy7lImKkAXPXTRw/QtCpeT4vrGJopISb5FX5Ex0pjZXbC8gJ3bjW3OY+d2ZeNN1cbFy10bl+ff7wlfu6sSnOLmiXsyd0p1F9VYHGDu4x6muYCujmBtkhWwSueKSu/F0WxiDYHSgmF3i0YN3gG9HrY1L5Cc+oTkA5SGBX+fFvl6BGNZOg8OuG1l8oXnY00kORrp+wxh7FKFnCxYTKxW5/YcSHs0kmtAqyHjtzmPXZqWpdeWa0QRnjYZ5t5GfXnmcV+iPUks0ZQ018QKUEUFgdQl8Lws4XwwN/VgDq7Io8EYyTtw95k9Y6WJrCaoWHLVBM9h7lfdSsp4Zg1tpQe1J37JcpAt5+eTg7CcX4E8sjrrlVdeyZVXXvlvHvfEJz6Rm2666VG3+77PpZdeyqWXXvpvnmvv3r2ceeaZqyAZF1988aMqxr7vMzc3l/193HHHrWLieaRceOGFXHjhhfutT5KEubm5VUxBlUqFj3zkI3zkIx854LkuueQSLrnkkv3WPxKnf9RRR7Fv375HbdOBjgHhoH+kPJJH/4gjjuALX/jCo573hS98IXffffejnmPz5s37nbNer++37txzz+Wv/uqv+O53v5slR1966aWcd955bHBFgx4puVyOn/70pwfc9rrXvY7Xve51j9ruA0kaurbtRVRpCNtexC7HDhe7NMAuhwXKQR6lFLNdp3B1W9CcH+zj+dj5veAvg+dnmPuqVcQCr2ZIBSiEctELDEEMc0nIprQ9nT4lCoKzb/epUKD3CMx9H0PVgG31UEDFKlSoKVhoOLiPaScEVmgAE6sIhixNrcgVROnszWviWBMWY4e5F3y0Ht0oGGCEvUSPbcLseUBgBWObKPo5ykGe2c6S7NPvCC46VxLmk5ENJHsfyBRuVaxR8woUrWJYhQQYfAdqLTqluuEp5r0Ucz+9AnO/mFXytDbBLknVUNvvUAmKNONO1vd2edYp6x6210c1m+B5grl3mGGoMRFbEiD0NLRbAukIvQxzX+hYbD/BLkwJBrndgKiPdqw8trUo+OaRjdjWPNVckYXeMqUgnxkXZmFPdqxddvUhghw1qynlxQjLxz6021LtV2lasyEba8vMLQ0w9zYWRVsU+J7ca79L2ab5GX2HuberMMs2iQdj0inPFeVjW108QsEXp/1mE4FR+DlR7oNchrkvjQlUZGGvx5hn0IknMIhSzSWP57CLUtRHBSFmdgfDJmafF5CvRnL/ziBR1VHJ3QBheWk1BJJTGcW4HA3b6wjtZLcrbei2MHO7URuOyAwb21kWNpj5PVibZDkZpi1974+KwawxlFSEaQvmXrM/5p7WEtTH5Jylmlw/ZbFpLqCqI5LzEOZR9WHhrU8x984A1iMbMIv7JD9lbBNmfo+MGZC/923HtBp4E4fJ/SzsQQWFA2Puy0NU8ClaQ+yKnVW9vJs3CnrOgLcGM7eLVFSQk2t6vhgP/Y4Ur8oXM4XeLu5dgbmfEcXZq2ZGqF2ckjySVkOgK0FBmIRG6phJqT8TUKUwHJPsdrSxVmWY+y1KxkpiBZYjrEZNsAXJaUgdHn2XLN1s43sWbQRzn41XXBJ4hrkPXT5Jizw6KxBGIgnpxH1R6N3+KdRI10OhRIUMwqXS/VOjvtei6MUkXUh6Wu6J1VKyGttsQeAzbCNYmueg/ObLQeX+P7jMz89z4403ctNNN63y+v8qZPfu3Vx99dUkScKzn/3sX+m1/71IPp/n6quvXlUga3x8nLe97W2/sjakeF/6HcFYj22CbguzNI0e37KKCnO+2yTvBVTCAqoyilY6w7mCw9wXa/th7hfUPOGwKGSN7TElPCIlSZzLXUNZJRhHfacKIZ0Uc18MaRFTJ0AVQlorMPeNFZj7pgKd8+koqDlvqulaisbSbQdUwz69Gc1QYmgvC3624kcEYTLA3DuscIoTlntuCeZ+eJ0YM41pFrpNCn44wNznS6h8RbDp/Y7gocvDgw5WmkbSYckzLNo+LUoY+vS0yrzITQVF6zD39QnxjmktSlyKuVceVEcEj5+vsBy1iUyS0QEqpQf7BoHg2fOFVZh7AzQd5j5ZibmPDVEk/ZJh7ks18SZXRyBnVmPuccrS0Hq6cZ9KUFjFIKQqowPMfcr8EeZpK0ur667jMPeWFqG15Csxu/fVMipMVRuXBEEQhTruCdd6Z5k5h7n3HOY+GNUZxhlAJTGJS+oU/LVh3vZR9RqWPn7ODPqt2xowqRTLEqkoVFDlIp15wdynic8GBph7z1+tKEV9VGWUhvYlIbTjoccOyTD3trMs86nXws5PojeIkWabC4KtB2jOY/c9jKrV0cUarNsKJsFs/wneCUfLefodMa5qY4NE9hWSLEa0MPSUIrIBuqjwWwZlB6H6FHOvNkjyfWq4Kc/PjBWSGFUdx7bm5Xm2W9CYxXZF+fcOPynLMdHD6wRzP79nP8y9GprAthqYfQ8L5j5fkX2cEWGaC+J1d896kYi2yme0nUtJl4YuUFOB8P9Xx4UKs7MsOQLumWSY+zQ5eGhCnBPpmKivFQU6yKGG1gwSVl3uhaqMSuJ4eQj6efF+K42ZWYBQnnFXabqLHp4VbnhrdYa5XyRlqFGQz6Oqo3ItP8Qqb0CFWRUDQ9Ur9KL2oH3pXMHh6bstqSkRFjIqzC4GTFo3xKnhuZLcb9gS48Yl7ibzvQHm3lGW4gWCvc+7sV+o0DceSU9LkvkBpKMsqlTANlp0CaRo2a9ADibU/nxyULn/Dy4nnngiCwsLvP/97+fII4/8lV77hBNOYGRkhGuuuWaV5/6grJbnPe95q/7+wz/8w19tAxwLB2FBPD+d5QxWIUqM8zgZQ6A9uknEkK44j+i0bF9J2RiEq2E54KrROsiNtSTK4lno93xCFDmdZJCclAoTBw9Z6UkyaeRDged+p2F703J84+6j4FU98dTnY+YaRSmQBFmV3MRRYWawnJQ5pLWYMZOofCkLq6vyMGZ5NqPCzPmDflHl4UypSOlDM8iE8yZrBz8JEGiRbwc0bTm7ggoTxGPoOSaqFHKT9nPUg9KQbMKuTsJLE/e0kqRarSUJL5cy2UjysYcwDuH5+31EDUihnLCAWZ51yXpI2B9QDpaTwl36SUw1LGHoDqAMfohNGgMqTCVQh5VUmCksRyFQIC9n6FuPsucU+riXKcbKD0U5cZCkwBlFth8PilglcdbXGdQm7X+tpcJpFA2KWK2kwDTuJEkMcQ+MFEVKInmGIYY4eQTNIoM+ycTzSZD+NclgTIFEgVIoi3UeVpUrYZOZbA4qL3CQjb7s09gnxnbUH0QAChXxUlsjVI3uPnQo7UraEunwrMWugK8lDpKT9rm2wNKccKqnxs2KRHxVccppZVSedxSher3s/rP5kt5XqZ5FKrJ7bi2KwlyqYdqLg7nSbqzqF2xJlOyolxkgesWwTFwhO5SSSJCD92T0vSbJYEG4cZk92zQ5VmvZlh3j4G0raEVNZwlFJYMIZcmrBZk/nrUZfW5a8CltZ9ZeZcWr3u9AZxkbFrDdpcF4Cwvy3BwVpnGF41IaV3fDA098ZzmjkjUgha0A4mQAyUuhe0qvehcb5dpljTgHjOuPFaw8sVWENUPSJaPCXCkrYTldpTM2nl+2HFTtfz45qNz/OxVrLRdeeCGf+9znWFhY4Mc//vF+jCtwYAjK45XzzjuPxcVFvvSlLz2u41Z6o39T5eSTT+aEE054TNCmn+eYnyXvfve72bdvH5/61KcAeOUrX8kzn/nM/6ck3f8Xsc0F92tBvO6thtD15SuQ4nwBFRQoBXm0Usx2GqIA97rY1kpYToBd3CMKvhpQYVasInFOqpoKMpx1ECaEPbUKlmNaPSoqL7CcZo8K+f1gORGWojUZLKe0ApaTUmHarsmqv8ZWEw5Zmp4mlxfvWHfBW02F2W1hW4sCy1mYcn0zL39PbcMuTqFHN1EMclTCwgCWEzt6v3xFYDnD60j2PjCoslsQKsyiVdRViIfNYDkl9zFveJoFLW2W6EfdGVfzA++kMdglx2DU71LyC3AgWI6nhQpzaRmlNKOPgOWMxqLg5z0P2i3hf9cK33dUmNZievGAGrC1CP3uAJaTUmEOrcM256mEBRZ6yxT9AeQvo8JsLQ5gOf6BYTlpP7XnQtY/ApaTev1tmEh/9DvQa1F2VJgDWI4ZUDiCHPcIKsyyCjIqzJWwHIzB2sjhv/vg57BRBzMzT2lM2jq/z2fU60LiraLC3A+WM7eLYRMz7QVChemgKyDKspnbhW1J1MA6WI6qjmBcwS3bFe+rYNs70G1j5veg1h+ezUPbWRYoy9xuoT90zEymK2PJH/YPCMvxLPhOuW9rRVcpUbLLQ9heR7D9ve7gOktzqPqYGBb5EmroEbCcbmsAY1uYGkDYFqYy9iw9uhGzbzs0F9Bjm1bPFWfQ6JENmLndTvEfooREPmI7oMKsq4AcGrqO9tUm2Pm9orCCUGG2FsAP0ZXRARXmitwP25iWiFrcwzYcLMcprdmYTaFkfUeFaRP0cBUzJVEgnxr5+mpYzpKD5WxWcp3YKlLuf9t3VJi9rlQpBrl+r+VgOaDj/WE5Wa0GF1mwcR96bfKo1bAcz5fxrbSjwhzAcrx6uIoK06bRwKiXRStsvyNUmO3VsBy1QsFfCcup2wgcW9JB+c2Wgwm1/07lhhtu4Morr+S6665j7969fOADH0AplS0jIyOceuqp3HHHHb+2NnY6HYaGhhgeHs4oPn9Rsnnz5l+Ycv145Qtf+AJ/8Rd/8Qs51759+/jwhz/MO97xjmzdn/zJn/CXf/mXLC0tPepx119/PWEY8qMf/WjV+g984AOMjo4yNTX1mNugRjcIRV++JDSLoxvEo9iaF2hEriR/txdZ6reJTcJooSbQhXVHoEc3CT1dsS4eyDAvikIS0zERKgjoKvDrCr+uaJOQYNHIR6SpDDUVS6JarFCBRx8jH/N8QJeEPBoVeHQxdDGEaNpKo3I+Fugqiwo8IqBqY6o2JmkPYDmVsE93RjOUJLSXQ9rLIeUgQnviifM9gy4Pibd6Zge6OoKujmR/p/R4Zno7nbjv+qDKaKEqMA4doF0Copnfk/WZcop5y/RZVoaWjemis0Svlta0tKatYCilwizWxRtqIlS+Klhrhz9XhYooiCaiZyIpJpYmDBYqAueJnXe1kIcgYEklqFIOVcqhgWWtiFIia5fobmNDkmiSRAuVH4AfCke5o6E0szsxszsl9K8DzPR2lJ/DYBnL1+U8afEv1w8EOeHX9nOosEBXWTq9gE4vEI9gIIaebyFXjplfLhB6CaGXSGGiYg1VHhLoU2VEvLW5EvMqYV4leCMlegq8qsqKIEkCuL+6oE9YcFSYlcFHz/WbNVJEyfY7TrF2xmy5SHfRp7voZ7AcEOXazO/BNKalmqtJJKmxuQD5EsvKo2QM/bY38C6HBTEOxzbJmEihKGFBlMo1h6HXHCbKZ68L+QIEOfT6I8Vrvvv+7DyEBVGGUzhGEjkqTIXyFaad0MIQKcWy9fHHA/KjCT6ihAZWYDl5a9Gbnghao9c/QZ7ruiMG4zZfhFxJlMZcCTs/C1O7sJPbsJPbUKWaeLvdfCEsYPZtl/UuWdbs2y51GYIwM2CUDsRr74rjmemH5XphAdvvsmgjmlrT1dDV0DERbZsQY1GHHQaeL3MtiaWN+SLEgk1XhSpmaVqeSQoXjHvg5o5t7BOvv6OjpNfOkrBVWMAs7JHzhAVRhMOC1IgIfQh9IhT9pjdIVraKaiJ0mE3r0bQeLeVyXgqVwRiujQ/eke4Z6rFh+rGXPRPSAmYulyOb10kkSdmO4hJjwViB5TjDMUsejzoo5aGURzwrhpBBDBe7MImdn8Qu7JGiZa4+A4hiH/d1BhO0VqGURSlLT1mJFvQi+nhQXQE5/CXKwYTan08OKvf/TmXbtm2sXbuWZz7zmUxMTOD7Pqeeeip79+5l7969fOMb38D3fV760pf+2tr4+c9/nmOPPZajjz76Zyan/jokiqJ/e6dHkeHhYSqVyr+942O4/mWXXcYznvGMVZz/xx13HJs3b96PRWelvOQlL+Gcc87hnHPOodeTl/g999zDu9/9bv72b//2ccGg7MIUdmFqAMVZmJKPSyLe24z1xRqKQY5uEpHTgSg5k/eK5zL9KBkjMA7nETOuqiRAsmRJlhwkBkvOQquZo2I1/kq2HK0P/EJeyf6Ae3lpnQEPkoWeO7dg2YOJgBlfUR7q0uiFeDkJK4e5mDAX04l98VQlijjRgv11H/2UQSj7e3FKFBDHltOKenhKZ5V6VW1ssH8azk/7TWk0iqLzNhcQzvGctfhuqRjHuqEZhM6zipL+AFqQxPLx1pKUnKwMyaf7pr9N2tcSyle5kNBaljyIMrYcVxHUWIleWGFVUb6rSqsF2qPypewZK+V4t5Vs6yURFktkpKiO8nzpK72i/e53vBKW4zi7M1hDYGgZn8BPCPxEMNzLs5jlWcFsL+yRSIY1VKymYjVmuSuVfmMrcKVIPN5pQStMknlEi8qHdocorVBrHtF3KVtO7Fh+fA9rwVpXVThZ/TyUn1sNR/MlWpUoJQwokRY4l2PLsXEPO79HIgNJJIZ0ypyTGk5pOzotbL9DsvtuidxEfZdM3MkKF61kmLFI0SJd9TFtS4DKuNiTxYioIc+15xYPBwvb+VPBze++ezCf455w3w+vR/k59PB6UUj7EfR72WJbDcfc08cszaEdZty2GpIE7gx8M7NDoEXGZHPFdpazsWLjniR7ujFeUh6htZnSqzOgHdjJ3dLOmR3okY2o2hq3jEs7TTKApqx8F62szureU6vmWDZ3klWQFXBzoRCiChJ1y+pxOOXXYzWESI7xxEB349cs7sXM7BBjudWQvI1mi8BL6CklnP79zgq2HBeRc3As22tjk1gyjrRa/S5c0d6sEq/W6LzcmzhRPDEegpw8s9Rw0B59owlrhnwtxlcrjFj3PpCTyLmWtCdJ2L8CMQ6K9YtY/jPKQeX+36Gcd955XHTRRezcuROlVKYY5nI5JiYmmJiY4IQTTuCP//iP2bVrFzMzM9mxd955J89//vMpFAqMjIxwwQUX0Gw2s+1JkvDWt76Ver3OyMgIf/RHf7SK4eXqq69mZGQkUyhTecUrXsE555yzat1ll13GWWedxVlnncVll12233389Kc/5fTTT6darVKpVHjOc57Dtm2Dyp6XX345xxxzDLlcjrVr1/KmN73pUfuk0WhwwQUXMD4+TrVa5fnPfz4/+clPsu2XXHIJJ5xwApdffjmHHnoouVxuP+YakIhIrVbj6quvftRrnXzyyavYj6anpznjjDMoFAps2bKFa6+9dr/IglKKT3ziE/z2b/82pVKJ97znPQB89rOf5WUve9l+13jZy17GZz7zmUdtA8CHPvQhms0mf/qnf0ocx5xzzjmcccYZ+1Ub/rckLYtuZneI13h5FjuzQzxf7UXs7G7s7G7wQypBkZF8ldleQwomtZawzfnBhysIsY0ZCXsDdZ3HNpYZMtBb8ugtedTwyaPxrHwgAxQLSZh9g22rRwVfKtS2epTwibGYVp8yHmU8IkwGy/EtlB0sJ2ehoX0a2se2E3JWsM8GRTisaGpFkE8I8gl96xHHGi8wEobuLGNmdqJHpNAQrQbJ9Hb5O2XEGdlI2c8zVqgy320y321KIZ9927DtRfFm18bFM7Y4JYZPv0vNy1N2bDk5ZfAcmWfZmMwrPOuJkmrmJ0UJ6Xcwi3sHDyqJsEtzklTba1ILiuS8MKNItAtTogRaI6wi7Ta23WbUepjZBma2QV8p1keWWmLJKY1tt+XjH3r4foLvJxSMxXYTYbxx0BsztxtdnxDYQnMBOz+JGjsE25imGpRY6C1TDgpYa7DWyFiqjIqC05jGLskYq1uPUr5PKd8nrzxoipe8rxTNmTyHDC2x3AtZ7oWCK++1JGrhKtOyvIBdmqVsFWWrsO2YvIVowbEd9TsDxajbFgrJfge7PEsFYcsJsMQ9PaCWTCIxCrSj+fN9ueb8EsWRmOJIzIL2RJFTFqW0eGQLFfHMx32XWBtgF6YYMRFNrchXYmxrATO3WxhvKqMyt2Z3ZFh1M7dbGKqWZmWZ3S1zqNd3VIpL2OntqA1HCFyk3RBDMz2X80SDKPHJYkSwLkfZikpcUzGmKwW1lAXfLW2l6WglEAulBwpba0nYUJbmMQ/9BDO9HTM/id23HTU0BBMbUBsOR204XN4N83tQw+ugs0wytQ29ZrObR/I+UKMbsL0Wyc678A45dsVckfvIoDDLs5jFKUgiYcsxhsBaAmuprITlRAP6UjM/idl5lyyLe8VAWXKUtZ0lmQ8pzj6Jpa1hwSXGzwyw+c6zbxenXCErUcptryWF/NaMYBda2IUWAZb8cEKsFMaI8rukoelBTcXUVEydCNtzCnp72Y3hZmZI2qgjz77Rloghkn9ke63MgKPfGbDleL5UCm/OU7Qq89xjBAtve65KddQXKs/OErazhK6G+DinQakmuROlYVRpKIsi2M4SeS/B9AewnEdK0SrschsCn1HTh+XG4/q+/L+K/QUu/xnlIOb+36F8+MMf5rDDDuNTn/oUt956K57n7ZeE2Ww2ufbaazn88MMZGRF2i3a7zamnnsrTn/50br31Vqanp3njG9/Im970poya84Mf/CCXX345l112GUcffTQf/OAH+eIXv8jzn/98AF71qlfxP/7H/+DLX/4yr3rVqwDB1l933XXccMMN2fW3bdvGd7/7Xb7whS9greUtb3kLDz30EIceeiggXO7Pfe5zOfnkk7npppuoVqvccsstxM5r9vGPf5y3vvWtvO997+O0006j0Whwyy23HLA/rLWcfvrpDA8Pc/3111Or1fjkJz/JC17wAu6//36GhyWM+OCDD/IP//APfP7zn8fzvP3O89nPfpYLLriAa665ht/+7d9+zM/jvPPOY9euXdx0002EYcj/+B//g+np6f32+9M//VPe+9738qEPfQjP81hYWOCuu+7iKU95yn77PvWpT+W9730vvV5vv4qyqVQqFS6//HJe/OIXs337dnbt2sXXvva1x9zuVPQGYeEgEeo+vf4JGSOIGtmYYWPpd9jbmsdTmkIQokc3Yf2cYHZTRpD2ImpkrXiHui0WTRdVW8+cXqYwIZjuxt6YPJqmhmKpz8JyQp4VbDmVPItElPDQlTxLRJTw0ZU8DWR8FPEEllPK0VOWDqBLAR0NNVcG3vQNOQtR16fkxfTnoJYYOk1JSCt7EUEgbDkAeuJQUQKSWH7D4O81h8n99btMtRfxlBaPN6CHJjBao4uuYmgSoVIGIoSBZCHpMBNUmbd9lm2eiIi2VpCy5WjIO7YcvW5r5pVVldEBX7znDxJWa2uY7i3SS6IBs0+hkiW7qUoRajVUpcqC2oceKgO4qrjiCW3bBFUq07UJaEXiPNORUqiijx7ZgO13xSOaRMJUA6LMFSoC2xrbRKPfJOcFLPQGiZRqdJP02/B6bIrFD3IsrahQ21I9qJbpqTk0UKz32fHQUMaWo111VqwRr6Njy1G9FnPaJZEOFWhqyK1R0g8pz781GNdvengdtlBhzgpDSUJCWEwG/ZbydiuNHRHudMI8ql6hu+gq1FqDpy1JrMQj3WqAp10ip7xfVBCixzaxqHxKxpJECm/dkYMk36iHWnekKKaOiQpjsL2WzDkQlqq5XaixcfTYIXLvhQpm1914hxwr+6Qe8PEtgwRqyHjNk8U+iyqhj5aKo2VF0DFY5WoYQOZtVhuPFENyaEK8u8PrV1d1rY4LO1NpGLvjXojj7H3gH/FUBwXpo9dslgTgbksU/JR+Mu6jRzZCEmVMOsbzZa6sSH7WKVuQ1szQp63zdN38Wkg6LKo8FeWD78n5SjWYn0TlZFynlKAqzIvHvlTHutwJlY4/F4XTxRomibAL+6RarsslMW4/PbZJxrqWKFU8M59VqO2i6Tc0FqQWAxJdCC20rKhTMaBGhqTSd7EuuRi5UkaFmTID6eEKvaiLcZEJPbYpYwwSpb0N1WG0g0Zaa1hWZlCR2pfcDxVPSJQNsrEIYJb69FTqudfYuOOcBt2MKUrXJ+gbD+vqORxImsqiaiVsqyOwnLWbDrjfQfnNkoPK/b9DqdVqVCoVPM9bBb+47rrrKJflZddqtVi7di3XXXcd2oXUrr32WjqdTla8CuCjH/0oZ5xxBu9///tZs2YNl156KW9/+9t5xSteAUjV05X89oVCgde97nVcccUVmXJ/7bXXsmHDhqwAF4jX/bTTTmNoSFg9Tj31VC6//PLMY/23f/u31Go1PvvZz2bFsLZu3Zod/573vIeLL76YN7/5zdm6k0466YD98c1vfpM777yT6enpTBH+wAc+wJe+9CU+97nPccEFFwDQ7/e55pprGBsb2+8cH/vYx3jHO97BP/3TP3HKKaf87AewQu6//36+9rWv8b3vfY+nPe1pgEQsjjrqqP32fd3rXreqQvDtt9+OtZZ16/anFlu/fn1WxXjTpkd/mT7/+c/nla98JZ/97Gf5+7//e0ZHH39p8AwLmythJu8TzL2fw+x9ADW8NvuY2Pk9jBWqNKMuGwqjmFkJMdt+R7xfgJ3aIQpHvgiNeca9EnahQd56GJdQu4aQslVUjaXVzFG1moI3YMuxy11qFKniYZa7VCis+C3jtoaHQbz8RatIgGhfRzxgTmH2x/PMeVAa7rFtZoigZml4mvKQKHMPNarUIw/tWTxtBStfHhavc0oVV6qLJz2JRdmd28VIocJSr81owSUWLs2ia+PiqcyVBPPbGni3rNaMeyVGrEdL5SiqhA3kGE1iYZ8ASlawtza22MY+MaxyBeG4dudSXjBIGq2PU/TyFL28RExAFK1lSY42s4uoOIFOhxHrYebkHGVTp+175A1sVAXsnklGVA7bXcbaMGtzMi+KtG3sG7CjLK0wWOMedmkWFRTwtSfee7uctTU1FLFGxpcxEIQMWZ0pRetVCTvfYMhqqkmCNbCUhFS9vruHHeKRhCwBkG4LuzTHhtQQ2bHMUFKnP2soLs1mDD5EvSyR15Rq2LldTKg8yeQsiroQjKT95hINAZjahfF8VJAj2TVDUJC2Rghdat96ErloL4IOJKKQtTHETG2jbA1LyiPueZiZnaKIgkTDgpw80x13S+JivoKZ2oZKExyTCB6+HxtFkjDriqexext2eL1cp1STiFASybNJYik+VBTDL2nGjFmfUa+Npw3JktByGgah+sgp+rYxIxzoUS/L2UgT7PWhJ0Kvha6OY5MY8/AO1PISqihz0Kw7QubL3C7B6VdGJbqVr2RUsGZul0DIamPYxb2i2NfGM2w+kHHcp8mvY4SUTELeeZHX5iqMq5Ax62MXl7C9puQY1NdmOHRlDapYw0w/jO0soQpV8b4vzWHTfYYmBuw1jRnYuxNbKGJGXT2RJBbqzGI9S5K2ng/GokpyjoqK8ULLhO3Rjz0pbKaFlWbJGd4WsHtnsudnwzx2Yd9gHMQ9Gce9PpVSD9t0/bkwNYDYKJfwvTQvibmdZWy/w5D1sItpvYOeYOmnd4qxvbBPxlfG9OWhrbBwmeXZQQJxEg3e10lETicoz+IFRkgOlNB8pgCdolXYRguz1GZJj8LOQYHKX6b8Z8XK/6LkoHL/H0hOOeUUPv7xjwPCb/+xj32M0047jR/84Ads2rSJe+65h+OPPz5T7AGe9axnYYzhvvvuI5/Ps3fv3qyYEkgxq6c85SmrICznn38+J510EpOTk6xfv54rrriC8847D+U8LUmScNVVV/HhD384O+ass87iD/7gD/izP/szPM/j9ttv5znPeU6m2K+U6elp9uzZc8DKuQeS2267jWazmUUoUul0OqtgPps2bTqgYv/5z3+effv28e1vf5unPvWp2fqbb76Z0047Lfv7k5/8JGeeeeaqY++5556sj1J5whOeQL1e3+86j/TQp0nG+Xx+v30LBfHEtNuiEadGG0hffuITnwBgz5493HDDDRSLRW6++WZe/epX73euldLr9faDVKnqWnK5UBIhRzdkHls1umEVzz3D65jvNgk9n/loWcLpQUE8mal3fywW5o1cAeuHzJkOamiCBb2EPyyqxT76tJTHqA4oV7s0GmV6xhMGE0CVcjRJBLpSytEmwUehS8J5D1LVNFHCc99VguX2x/MkCnz3WYh2d1kXWRrTBUbDDt0ZzXBiWJ6X/h7x+oS5WCgyjUIPTQgWOF9BDw2YYVSuJJ7AzjKqWGeus0zBD+mkvO75kigrtXHBROdKA4YbAKWZTdrMBmXmbI9lW2AvfWa9HGYFz32gxPuqinWhINQuMTRVbJVGdZbFoxgU6CY9DBZVc5Wdu8JjjUlQ1TKqWkHVaiyoBsrx3LeVwKH6CvbZHmp8Ew17v/DarxCv6qgAU3xuEqMC5x30fGEBCXKCPUfRMxEKleGmbeLYZzxfPP3WoIICS8rQ7cs+c34PVZ9gSc3T1lpygJUoqjDgXk/x0TbuQ7EO+RK7vG8DEGyqMH87hOOSB6BX0I+mhZRUrgRD69lne3jrR7GIIanqa92kaGU0kHZkAVWqo3IlvLXD9G8XeFnOSoXaQJksoVjyUAYGEUqjRjfQVBptRVnSY4dk7CXUJ4RatduCNZvQo5ug33GYdvcOaDewExtQi3MynowRRWxoTDz5bkxSkuRv63juE6uIF+OsKXMqYdrk8BLLoUXwWgL9SKvn5ozFaCXPRmt0aViec7GeGTpm7/3o+lqBmlVG0RPjUB/O2qpHNmRzQldG5HdQkEhJ2vcp93xnGfyceM1dkq1N6xAUa4MEV2COPi2dp+kiEbNxi5Lv01cWtC+QkkIFM3kfNi/jGmsk+bxQkTEYFlAprj71dOcroCU5nKiHHWlDvjig5OwsS0GwsCC1Jhw9qO1G2L60rUGNqKOZIeRwv0diLL5Jk5Qd644CNTYs5wgLknQc5LIIgqqMYOM+KhfSaEqF6giFLg+JcQqDnJ1SVcZbsYZKIhZVgsoHg3su1mFkxdzMV8A5JpJFiQLEIMw/KcQn7g2iGZVRefd2JKEWhOLTWJUZgm1lUZUiOkmomgQOOYJfhdj/tICaX4wcVO7/A0mpVOLwww/P/n7yk59MrVbj05/+NO95z3uw1mYK+CPl0dYfSJ70pCdx/PHHc/XVV/PiF7+YO++8k6985SvZ9q9//etMTk7uh/1OkoQbb7yR0047LVNeDyQ/a9uBxBjD2rVrD1iNdqWSvdKoWSknnHACP/rRj7jiiis46aSTsr54ylOewu23357tt2bNmv2OTY2ex9J/j7x+6mVfWFjYz+iYn5cPX7p+ZTuq1Wr2+41vfCPHH388f/Znf8YLXvACXvnKV+7Hm79S3vve9/Jnf/Znq9a986L/xrvf/Ebh39ZaPjxBKPRq3dZAuYw6eC6BsoajK2wvZkoeIB8i53FGa0n41JrQKmzfeeaxGd95Eglnua9Mxj+Pdrz1iLKbpK95rYX/HrDKZowVqdi+g3O4c+uioqMVQZAQJR7WKjQDnmqt3G93XdvviiLSbQ341XOljCJTleqY9iKh59OJ+4Te4PWpSjVRwoKcKIv+aiiVcfGEGItxyazaCvc4CEwilybUHiARFZzn3vMzHK5SijiJVyfeRgicJ/QhkOTBCJtxY6el7kGq/OIHLrFVsbI7VeA5rnpX1dIPMWZRtmnH5uGUmdgm+Mpb/TEOcgI3UdoZHKJo9Vcwr/cQOJBFMPc6MERWD3ju3TPBJGIouMqekkycdqwZ8NzDQDlamRSZ8sEDxIkbV6wWayBxnOEpNCIXZgpPiCExakVq54rjVpxM+TkipQisFZ77XmvAq95ZzlhZrHae2bAAupEVo1J+TralFKDtRdTweonKpMwo+dKA0ccPM3iLY4DFxjLePAuJEgYdHewPy/GtzSJMNnBGSqpUglOS8yjqcs00ETW99V5bjBXnVU6VeNtrDxTmbkveJ/mSiw4ZiRS4uhHA4L7CQuZRXinp/E+wqHJRPPJxDypDYmSBtDk/oIxVynH3g7yLYJD87JLEceM6Ez+X1R6Q8Z242hJK5hMCZUoiLYWqnHhW1nvp2Ehx666isgWX5O2ibmmyubEZzz24sZtBlSR3BWPEaPdD0O4KzhmkjB3A0FJJ7+uRkp7XjVfrCv0prTEWgpLBC22m0BvziO+Z54FWRKgBTPCg/EbLQeX+P7AopdBaZx7io48+mquuuopWq5Upmrfccgtaa7Zu3UqtVmPt2rV873vf47nPfS4AcRxz2223ceKJJ6469xvf+EY+9KEPMTk5yQtf+EI2btyYbbvssst4zWtewzvf+c5Vx7zvfe/jsssu47TTTuO4447jqquuIoqi/bz3lUqFzZs3841vfOMxQWROPPFEpqam8H1/FevMY5XDDjuMD37wg5x88sl4npdV8i0UCquMpQPJUUcdRRzH/PCHP8y8/vfddx+Li4uP6brVapW77757FSQJ4K677mLDhg2ZAXCgdvzd3/0dN998M3fccQdbtmzhTW96E294wxu44447HtWQefvb374/f/6DN4viYYx82FoNjHGe1xU89/ghRT+HVor5XlM+yv2uQBRWlk5fnBHvmNZUdQ7bWKJkFUlbPn4VfEI0ViHJrS3FohmMAdvpU6IgH/X2it8reO5jLHkr3PcekLdSVTVnoaFcpciuHfDcG02unrCkPfJFUd7mWgVR+D074Llvzgsu2CUEW4dpN7O7sQtT6JGNFH3huZ9LlZKoJ5Ae531U9QnMvkHESOUrlHWOgtXUVEDOWkI0RkHFKUsLVrOkhavcLs+KFzKJsa2lLApgk0h49Mc2YeMeRS8vxuUjee61hOyV1wTPE1jOrEAtfDvEUGzpaUXe96DTIueUgSCQD37QtZhOJAWsauOSWNjvoKvjcp1uS/jRXdXesp/PcPepMWIXpyXp0yUlojREwnNfzEn/540PLWl7aC2dhZC11Sbzyyt47o3J2GAynvvO8iqe+5IRnvtVY/AAPPcl5WM7PQJCoo4e9FtanMvPOUrFnFQanlmgNCpK9+K0z5jXwcYSnbClmhg9YQGbJj0HOezCHoZMwoL2CIuJ3EMKq6qNC41p4q7RWYZ2QyAVc7uyvpW+ilxiZVegOWs2DeZhZ1mqvs7uFrpUx3NvXW0hr+5RFNol6jie+64nCbWuf9paSe5FWkgrjcRE8UDZTnHz3RYq6kC5AiMTqOIKxb21KPNjcV9W48E0FzKvvB7ZgJl+GBP3JBKTxDJXirXsOnpsk3DhO2hNAWHLybu5W/ZyVJRPAY1tdzJF1S5MibGLY4PJF4VisjKaJVGv4rlfnkWVhmQ8LM2JQZUq0AjsTNUddKfnFGpr0LUSyawkHAcUydci7F7xcFsLDU8M8w2Jq4yNgiQRWFvKcx/1B9GZ2CW/tjt4GnRiJb0+7q0ynrKE2iAnRm4SkceNDcDGSZZ4b5UWqlxjsFHKcy9GcMpzj++KC/Zag8hit0WojXjuewOjQK+g/ylYJTz3nkdV/ep47g/Ccn4+Oajc/weSFKMN4g3+6Ec/SrPZ5IwzzgDgzDPP5E//9E8599xzueSSS5iZmeGiiy7i7LPPzrzSb37zm3nf+97HEUccwVFHHcX/+l//64CK6plnnsnb3vY2Pv3pT69ilpmZmeErX/kKX/7ylzn22GNXHXPuuedy+umnMzMzw5ve9Cb+5m/+hte85jW8/e1vp1ar8b3vfY+nPvWpHHnkkVxyySX87u/+LuPj45x22mksLy9zyy23cNFFF+3Xlhe+8IU84xnP4OUvf3lWiXfPnj1cf/31vPzlLz9gwuojZevWrXzzm9/k5JNPxvf9x8yhf+SRR3Lqqady/vnn86lPfQrf93nLW97ymKIPWmte+MIX8u1vf5uXv/zlq7bdfPPNvOhFL3rUY3fu3MnFF1/MBz7wAbZskWS0v/qrv+KrX/0q//N//k/+5m/+5oDH5XK5/RJ0+2MOc6q0KG3FmniJ0yqSqZLU77DYaxFoj0pYEMVveVZYGFI4RK8limkQYpvz7OwvoDcey4LeiVcUb9B208JHsYkaJlF0lKGi4uzjoqtFFmyfugpRtSLztk9dBehagTmnwdRVQFdpdL1EF0tbgcr5RMAosk+8rKgYQ3M5x1Cpw/zDBTabLlOzopyM11sE+RiTKPHKFipgS6J8VFzugjUDvvYgh5nezlK/Tah96ukH0tERqqLD1C7P4m04atWHend/noVCjZ1Jk44aZnfSYEmPsOSgB30lCoIueqih9ZlXV+VLq3HnQ5KAqUpDtJMunaQvHPzgQu7OAzwyhKrVoD7CAzyEd7gY3z3dYs5V/d0ZL8HGQ1k0D2BjQxSJZ7OnFN5YWdg05icF2+znhAMcUPUJgUU4isNO0mcoV6EZdzLPuSoNi1JaG0evOzJr/07VZ7Ej42+PnkWNHU2PHSx5muJIn11TNeoFud8U5iR4/Zxg/MvDqOF1bFdfAsA/bII93zSEm/Pi+XXGgPICbOox93z0xKFMmhb6kM1EzOMFdtBvvXZG3aqqIwJbqK/Ff+KRzH7lHgA2qg6tXkhOO6WtNT/A3Kce4W4LveFodgRfZSQ29Jq+jKPU4OkIlA3tyb3UxgUK1GpkECEF2MW92Ll9jgs+lL7edc8g6dQaMTRdAjhAYnTmnI2mE6boM+3n2aV8jhv2CfsxoR1UqF2TRLSUJ4p9TyrI2l4HVayg8g6SNrdHxkCrIUWnlIJOM3vGeuOx2fxQ5eEsaVbVxsE6HPncbpkXTqnXLgk49ewDAy58R0M5bbvM+lUWnK65szuHzkGoPNToYWJsOKU9TSS1kRSz086gVIUK1CdWK9VBTmBzpZqw+ISzMr9cZFKVhrJCVxkkTGv6s0tZZHZBezSmCsz5imP8hMRoJrqODtP1bWIVqlKRc2udVRG2LQdDypVQw+tQ5SKzfUughZ4UPzeIGmkvY/OxjX3o8S2o0gT76KPqLmnWd9Gb6rjcg6vGq2uSo9XbGTkTz2Hu+52Bcu8iJN6aw1gwIUe43BJPG4wVamDPJa0vKYMeGcIuNOhYD7XxCfwq5D8rheUvSg5SYf4HkhtuuIG1a9eydu1anva0p3Hrrbfyj//4j1mia7FY5Otf/zrz8/OcdNJJvPKVr+QFL3hB5qkGuPjiiznnnHM477zzeMYznkGlUuF3fud39rtWtVrlFa94BeVyeZVimibrHggvf8opp1CpVLjmmmsYGRnhpptuotls8rznPY8nP/nJfPrTn868+Oeeey6XXnopH/vYxzjmmGN46UtfygMPDBJ5jDH4fuq1UVx//fU897nP5Q1veANbt27lNa95DQ8//PABoTSPJkceeSQ33XQTn/nMZ7j44osf83FXXHEFGzdu5HnPex7/5b/8l4yS87HIBRdcwGc/+1nMCkWw2+3yxS9+kfPPP/+Ax1hrecMb3sDTn/50Lrzwwmx9sVjkiiuu4OMf/zj/+q//+pjbLyXbI7JS7GlSokmElSPlNjcGT2mMtcLvDvLxTMu4az347bimV76grbGyrOAetkYJnh5Q2qKcxyjrjUdw26/kLV65xSgk8Y0B/7TyJJwvNO4DzuaUv1mpAUQn64eUJz7tkxTOEfUyHmxPObjRSkk9hI5fW9quV8Fq0vavur/0NsnQQWlnyf9pBc2Vf6cKwIEku7bK+L0TVyyKIMiuKxRx9sAh/KxR7tqpgrJSVkA0rHWex0cem/0eMFNFK8ZDgpGHg/SH9p1i5J5fWqVT4AnJqj4wHMCzZ1b00yPhCiv32W+dO7dJBK6Q7uP7xIkWRUdZEhR6ReVO2fcR11GaSKXb2W/+sBJG5bZlUKD0uaaUidbI/HL7pBzoq8ZE5rm2KH8AzQEZUylCRLmkz3TRDhYmfPmxJNTG/YxtCciqTCvfwe6sHdyDY4VK61+s5NzP1qdK7QoOe+lXN1fSAmPp80256V316rStQAbTk2RpRz3qh4OaA874XvWMV8BPpI/06roGZsVYSa+fjp9HzFt8Db5E29Iqrtkzhv3UUJsk7pnGbgwnEhWK5W/pxyQ7j3bjIXuuK8dV2t/G7e954HmoIDjw/mkbzAH+SGFkK/ohVgodgpeTv7WyB6TEBDfnftb756D8xshBz/2/U3nLW96yimv9yiuvzOgsf5Y88YlP5KabbnrU7anX+rF4rvfu3cuZZ565yhN88cUXP6pi7Ps+c3Nz2d/HHXfcKiaeR8qFF164SnlNJUkS5ubmVjEFVSoVPvKRj/CRj3zkgOe65JJLuOSSS/Zb/0ic/lFHHcW+ffsetU0HOmZiYoLrrrtu1bp3v/vdq/4+EKc+wIte9CLWr1/P3//93/Pa174WEFjT0572NJ7+9Kcf8BilFP/yL/9ywG3PfvazMzrRxyzpRy7qibfJGPntPKEZjjkQSI5SimbUHRzn6PAASXzstUTVU5pAeRDH+FZl2liAxlMK0S1FIe9ZPdAzk4QAnwgDsXDCJ1hsbAjcKytCij/hQuE54abDB7pmoEwaRPExRpHLx3StRy0Qr1Xc9whzCV5gBh+zqDfw6KZ/F2uSIJjE4jlWCo2ineKDU4w0iMJWqAw+4AhFoq88tLt37arzashgQ12gnd5/3JMqma4vV+YzEPcdZteT4j4rx1VqlDmGj1QpyCsPOt1st4KBjkYUcldoTPk6C8V7gI1FicsgH3E/YxBKr5WynSil6CbO254m1HZbWXXelUprDk2onXcfBXZgrMUdRTmIiOLB81NKDygT1cD4zKV+qX5MgCf5Flqv0PiTgYLmlDYPnY2XVYqP9uTcnts/Za7p9SgWHSxnPo+vxKupPB+CgiuC5ImCnB6XRBSNYN390Bk/aTSjUJG5keZmOIVdFSqDpHUz2KYyIyBePSaTWLzhxmBtLF5syO7dK0rCubZQNKlR7W7VDZc+Hr0UN75yfK18XlHfFZiKUHFfquaWqpm3fFVbQCIeaTtdtCmlybXpfivnius3VazJA4kEgqJRg6qtgKc0ofLwUVnuBmnuiXvvWJugop6MlbAgzzPuu0JrjsUm7g8qv6bRMD+XJdySRIMxniafGoMqhNCVPvEt5PIxtAaJp22t8AAvcQ1WRmhJU4pS5bKAnDMK7ca0sQQrzQLtDcZvmhcAgzZbs583VvmhQNVW5hM48csr9suVJJlYa6zSg7kJBNaIjeCScYxV+NpklqEHMm8CnwDzK8PcH/Tb/3yi7KNpHQfloDyKzM/Pc+ONN3LmmWdy9913c+SRR/7Krr17926uvvpq/vzP/5yHH374cVVi/VXK5s2b9zPAHk1+8pOfcMcdd3D22WcD8KlPfYrnPe95v7J+PeMQqWKcVx45PBpWCgwFaLokmSLlo/nk/1wPrQ623eE1f9egogJaNiLvXIYBmghDgCavNB+5eJy//kCD39+6m0/cL/CfP3iVcIcvfWeJm7ev40XPnGTv7SWWHVxjpy3wwmdO0p+Db923nt96+m76c4pvP7CeFzx7EoBo3rLj3mF2mCJPXT9Fv+3zf1qjnDM0zeSUKBvFMGK+l2fL+AK3zo5xQm2eBxfqPHGjUDresmeCsjFUbEw93+OD+PhKUcJn0crH3FOKCj5dEhSKMh7veaMoz9YpzL//GRgjZMr2sv2n7AD/rVBc/e7DMLv3Ynt9Gt9aoP78Ebq3T9OZlY9xWE5Y3FPgjsURvhC2qamAhmtDyfVty8bklGaEkBn6fOwNeVQu5NyPSbg/h0deaXrWcAxF5lVChOXPX9Lg0q9KKP91lVnCQoz2LfUXjvKH18B7nzPH9d+Y4FCkzUO1Njc1R/mx12OMgCn6eChGESVoL31yaNbagF2qz6VnK+Ld8/gbhvnDa+SeIyzD+EzTp2vF45hguOz5bbb9iygWR55f5iOXKS44bhetvT4/3L2Gw/PLNHuirL436BE4BUkDHpoEQ2It//sCecZ/+Hd9/upZs3zi2+u4R3XwXAQhNaQAehgWbZ9rzsrxtmsV5yc9lIK/crptUfkYa/GVQqHIoWnamHUqx++Pylj54e41HF1dZHqpxD/kNRUkKuWjWHYcNCGaHbbNx49eZNdP61gL79WIUurm1z7Toah88vi0iQnQhGimjfR9RQeUVMA6cjxk23gockozRMCiY4qyWAp4TJo2gdIoFO+wsKcnuQpGwQsuLtD5v9tQPvzFj9dSweN3TJNc4BhpWgVCbfhAkPBcU+E7uslTbJnbVIu05vMmlWc3PbbaPA+qLkNOFU19ujO2j1aKEh7LNiZQmgo+i0SZEprOpZLyqOAzQ58xQuYYRAgKeEzbLgoxmv/3bf+Lxtmvx6/LWXKnPg3z4ENgLH98rWaLCditY9ZYn2kl9zNkPZaVYY/tUVcBizbCYKkon5ZNsfA225a2tUWc6dMhmiF8Zolo2Tg75vXdAg1XF+X5Wydpzuaobexyy4/X41vLqOcqY9tBov4/BwXuokXfXdtTiorLBerahK5NeBY1zj1yFw/fPUw+jPlfNsR3PZcgxf3q+GgUU/Ro2phPPaXBZbfKe9QD7tY9OjYRbL1ShGiW3Hvj3X6E9izaM1zWGSKHRPHyVtF0lWh32S5/UWmzY6aGryxFf+CVT4y0Ze26Bv+0by1DCRxierw3aPK1XY+/nsrjlQs3v+oXdq5PPvyPv7Bz/XuRg577g/K45cQTT2RhYSHDt/8q5YQTTmBkZIRrrrnmN1axf7xy/PHHc/zxx2d/p7z8vyr5L0kdkEJKoYWcLWZJYnkj60H+Xv6HOyTfr+1xml3HUGyJlGLBOYxSaElTQzWB7k0/5YhoI/O7ijytOwgdJzNNOkshgbXM3ZMjMZqe87jHGpKmpbsUECtFvATdpYAEMC4pt7fkkw9jkq4gO7zAsDlWTE1XmEWUw+c+bZbrf1Dmqc/S3HaD4beOanP9bSM86zD3YZtRnNC15L2Edj/gJSqPtpC3lrYevBoLxhIpUdFy1rD41T0kkSLuSXtf0hujYhIWvKLb3zAdVEk/k3kLna/eRnefpvq8YcpbFfHOeewKhMbS3jxhLqFgDM81JfIGEhUSKchlXuYcPQ21xBKpAsv/shul4RQjH/vAimdRISw8G41HU4PKB1LZEoj6HvMLRUaGW5iZJQ4zoyzdCyNJQpIWQYo1T+j3qHkhZWNoqxxGkVXSbSsxwsrGcJQOmb9hin7HJ7hzjlN6Mif7SsmxOs+kr4RrG/BGFOWyKENmT4+je8PYPjQX8owSYayiXhSj6fT+EFg5LvXkdjXMaSsVM4Eh8sSzCSUDL4nzqzybabd5wLSfp3//btbZ9XTjhPGhJqcsCxNViktOPcWBhbYOaSuoPVH65P4ZzTMn2tzWHObkniVnDQZhX+qmhq21rA0rhOvaNH8csH5sid+eG6ej03EEPV1gSctcKhuJ1uQMxC5RfM7tt7lvONIrk7OWplYUDfh24JXNWctUUKeDnCuxTQrOyKj6fVo37qFwwjBmvsnJXU1gE/ZSoOYoHadUjtBYXh5pJpKIUa/EeBKxzisy7cs9j0eWtV6BpyRtRnUR3/WNzvrJc+Pb0taBRAqsoa0G1L55a2nqgNBaim48lExCSw/2Ca1l1q9mz6Bx9uupXXMFzd97AwC9679PeOJmku17eVZ/hPEk4nDlMaHbPOhYuw6nzbTJMe0XKRpLTwXStytclzFQMtDTMq+UhZwdJPIXjCVnLR2dY8rP41sxlCbCZWqR7Jff6AE9/LqmbBMKOiY2Gl8Pon+eNmyKFRso09KiZEUWhtzrzyiY8+Cp/S7hOp/pO/IU4oSXrGCBsoBnrWPRMjR0nrZW2HiR0WQwBoZUjmUtYzwBagbmPJmfE8fu4qffHyPUhmcahW8NsVIENsnqa2wJSgwfucADMxprBY5jrCIXxJlyrz1Jbi4bQ8GL+a9mNeX0QfnNlIPK/UF53PLwww//2q49Ozv7a7v245FfZx89XkmV95aGPcqwPtG0FUzqhI14mXLSwBJU5Xc4amnskQ9WR0HbfZXmdMKQ1STArJZCUgueC2U7sd0I/5AR+t9p0vA0QT4hMTFex1FYOkrI8voIPWXRPpTX9PH2kWUJlTbEPLCzQKCsUNMlml2+5cgIis5bFs1bRhNFtLfDejOKV/VpKIs3IorFnJL9+saj6Ee0HZQhtoruCi0xQQn+F8BoctWEpDeAXbTnFUWr6DuqwUhpZlawTfgo/PE8/lIXM9+keb+l/uI1qPwczVtlv9Jwn04joKM1HSXl7I1Lsl1yb+lU+TGeFO3SgcWvirILUDeKjtP/hhJY9uTZ2NhkOHDfT6hWumjPompFGtqSq8b4GPpmcNP7dIhB0VaayME32k4h6GmFZ6GtNbEzrAIb44dmAPVAGFkipWgqgSHFCmyzh3EFqMh7LGuNiaFU63F/q0aVXlbBdtEbJIWJ4ijjbEmZjNqzjcErK2KFq/g7MG4yZlWkj3Teo6cseT8mjj0WMhjSwNsPA9hSApglGbcFd67QWrpKkWR7q6x/DNDQlmQpohxG9Hs+Tc8lSwINp2y2lWWnTjgCn46Cad9Sc4phF8tOHTGhAhoejMdScGpbYFm/ooJoZBRz2pIgNRJyOmFIi9G03A8JhjXJ7DL+pjEanqZgFDUzwHjPe4qSkUwJyV8Y4MjTuVw2hlnPYzkJSDy4zxM4VM61dVMs8yIyip6W/o6tR1cPDIB0LiVWEStNVynxHK/IpclbWHA5AYEFv65p/t4bKH/8cumTS95EsncW7wmbaHy1xbhTbpeSgILzQC/ZAKMUPQWRp4jceGusmMdFZxxGiDLc0JYcikoKWUIRWbmnprJZiCKKPQqBmOrJUgwoVN6jiyYxgdCjJh59NyaC2GcmJ46SJS0e+B42M7B7ChrKEmWwF4uvxIhbqdwrFDlr8RNF01MsuntJ302RlftdcNeIsHgoll1eSLQEFkXioEOBK/Zn0bQd5GdRQ3/ekieRvBKrpCDaitySJJJ9pwLNegMP+ysspl+iHCA75qA8Dvm5EmqttVxwwQUMDwsOdSUX9y9azjvvvP0YRf6jyMknn/yY4Bs/7zG/KLnkkks44YQTfi3X/nXJfffdx8TEBMvLQt923XXX8aQnPWlVIuxBOSgH5aAclINyUH5+sb/Af78sWVhY4Oyzz6ZWq1Gr1Tj77LP/TRrstODnyuWR+XW9Xo+LLrqI0dFRSqUSL3vZy9i9e/fjatvP5bm/4YYbuPLKK/nWt77FoYceytve9jauvfbabPvw8DAnnXQSf/3Xf81xxx3381zq/1k6nQ7r1q1DKcXk5OTjLpD0s+Tx4Kr/s8qVV17J61//+v3W53I5ut3uAY74zZR3vvOd/P7v/z6ViiRcvfSlL+VP/uRP+D//5/9w1lln/cxj//Iv/5KvfvWr3H777YRh+G9O/iiKeNe73sX111/PQw89RK1W44UvfCHve9/7WLdu3X77W2t5yUtewg033MAXv/jFx20EXx5tBwQTHSofgyW2CaHySazJmHEC7fPW//4qSWJrLfO/v3U9m3IjzMYt4mQAuembGE9pil6OP37bX/Lpf3ob5522luv+t7xunvP0JwEwdui3Gf1JjcqmiO49AYnzWy16ityWIslclwVPkdtSIHa/wy2u+uJcm9FChwfiGsWRPnFH02gaNmxaZNt2CRvf99Mxnqg6zD+QZzy27Lq5wFO7CQs/ELzvE/vivR02luEw5u96k1hrKXs5Wiat/GmoOj75BEMlyHP6hS+WG20LFd0n/+gW1uWq7I2XsUaO39GezRhkPKW5+I8/iv/VK1GjY6g7/y/6yK30f/qvlNc49pwYqut6LM8r/k+8k7wK6NkYiyV0sI/EGgLlUdQhS6bLG994Mv8/e+8dL0tVpf1/967UufvEe25OZEmSFBFGEARGRX1RVNDxjqIy8wMDOirojDg6ppEgYH5B4ug44xgGFQOIGUGCgOTLhZvOuSef07mrau/fH6u6+hzuRTG+zsi6n/7cPt1V1bt27V211trPeh6CgP/8mRRzZ7WPZyQPvZvXx7ztUDchb9x3L37xNeHd/9slMuf8QYXzrGfynau/yTuPXcODD8Y8Q0ng6gcxmzqKb0aj9LlZpmPBg1dcuXfOxk1crRlwskzFTV785udgx3eg+vr4v+/6uZyPtZScDHNxi4nmfPrZu/Y6GG4UTnf3uOfy7a/8kBftmUM91CAaTWhBY1l+uCZ8GD+BR1lrKToZmjZkulPjvD1EOfre+Hb8/Zay+baIf4/GhM0Ji2s1OS3Z/ZppM96Y4+0vOImbb/opr85rNs+U+JKScR9oD4vFQVNwAnzlMBHWGHTyvHqrjP2+GEykyBnDJ7wJctrHWourHKJkpSjGsqk+wdv7BymVWjw6UeGz+tG06DnQHm0TpvPshgTXHWgvHSsWOWYrGOCO1ihL/TIN06GfHN+y1bQv8tpnc2MKhcJRmpcP9HPPnIz7AEvwiuMJr7sBMz7Lw14/Q7Hi4Mo0QSFZQdvUT9aNeJ+OWOZn2WKmWe7n2WZm6CTMK3cFWUbjGmuzZTZFUyyxBWJMmlG9gTqhiSk4AfNxC42i5GSYj3v39YIT0DQhGkXRDZiJmywNikxGdWFxSrbZ3JpK58oZJzyH9jd/Tuu8MwHInHcp0Q+/CMbwA/0L7skGbLc1Kspnxgg8q6J9Zk2DrdEcBd2bv4FyU1R9aCJy2qdhOmS1T5CMrblkfGeVR8ENqMZtJptVYmvQSjEU7El33XENs9QmA7LrBeKirGVlroG10EkKwV3H8KAKuL2zgyiMMViy2mfQlVqT8ajGTKtGLrc3TzewJGiSy3U4p9ojmzBYAuWwwi0Re4bN0Tyz7Tp/91f784tfimZFEZdbwnHi2CTby/lMtGW+/fVDy1k1MovSlvdPNHCVQ4who1xaydjb1Jzk9bksm92ArLGsUQ2UsrRDN83e5wZCtkxb+owiG4R8pbGJ8/jj2/+EtNmpp57K1q1buf766wGB1L761a9eJOq5KzvhhBP4/Oc/n/7t+/6i79/ylrfw3//933zxi19kYGCAt73tbbzgBS/gtttuw3Gcxx9ul/Z7OfcbN25k6dKlPOtZz5KDue6iRo+NjfGe97yHF7zgBWzevPn3+anf2b785S+z7777Yq3lv/7rvzjttNP+n7RjV7YrAaf/jVYqlXjggQcWffbbKOL+LvaH7NutW7fy9a9/fScGob/927/lkksu+Y3OfafT4WUvexmHH344l1122W/8vUajwe23384//uM/csABBzAzM8Nb3vIWTjrpJH7xi1/stP1FF130e/Xn+kCcgnnToaB9HBRzpk1eebhKU0selCUdYB+R62hn51kdDLBOF6l4AVMmcRoTZ2fetCk7Gcwt32K/YITO/ZMMRYIN14c8D3Pb94g7snwfzihMrKglGN4trkEPVzDNCbY4Bj1QRNdDtrgWPVyR32+HlCottswWCVZ5ePMR/dsc6rM+c8lt7ZDdxvjyY8t59aGz3PEDw7Hrq9x0f4XD14rzsmUC1nVk6bre8lnriZNXUh5V3SteLCkvpXAs4GAf3SRiP4kA0zqvjxEVkHNdYgwF5REHhiihKMlqj/jn3yC6ZyPB206leNjtEHZQvkb5CTRo1iG/SrYfcUsUlUeHmLY1aSFeiCHG0q98qjrA7hgDpVjpC0OJhyafbOuhKCkfpRVqcIi2TWhkraI56+GVhFIxqz3s1CzFuEjTSr9VHMNQDMvdIkMqIK+kXwYSrH1ReWgUw8on47jYzY9hdkyh5musdAS3FWEYUAHTyie0cRogqmXLcd1Hk7YYhpQPNDGhqLr6bi9IXGX706JYgIoOmE/GIhkJNGIMtt0BPNZ5fWkxqAJySsZTQ2elMLc6R0a5xCHkdcRKT/qtC8vxlCaLK8XkrqZpI4p7yXdbxix+2TDjOKx2y+SSgtouk5O0xTLrNXGWDxJ2Zih7bdY7AzQTR6qoPEIMs6ZNUfk4SjFvOpS0L0w+wLxpk9ceKwiY8ftZrnNMqDYjKkMuYVtpE1NOizMjMsqlVgvoSwLsDDHm9ttxn7Evdss21oaKcmxo1P1UBXoKn2LosDYb0G9dPK0ZtC6B1uywMpcHVEDkWNbaDA0nZmQBlh5I25NXDlWdS8fmnM6mfVJRHg0tf1WUx6zKMKx88q6b5lOLykUH0n++cjAPPyIY+1GBYEY//CLuUa8guunfWK6ylKzGVzn6rIOTwHvW2YBt2sW4looOqNswnTth4iY2bURFyXdqQYFrSQdJvzmUlces8jHYdCwNRJZm8jv+7hWyE/M4I4NkrSGrIjwvRjuGTlXGm6MtQ9ZjtVehndwDPKVZkvRf3vMIlMvyEJxlZaod2W+d20s8WsBTiiHkfuy4mikdQBAsop1d4ZZoJOPLU5oAnQYzy1bNMTeRxfNi1jjFdKz6aFoJJLHphwR7Zpm7C4GXdQl/lE0x98G6DNMPRWSVh1aW/YP/HbVuv6/dd999XH/99dx888084xnPAOBzn/schx9+OA888MCvrUcMguAJawbn5ua47LLLuPrqqzn22GMBuOaaa1i5ciXf+973OP74459U+35nWM6GDRs466yz2Lx5M0qpVBm02+iRkREOPPBA3vnOd7JlyxYmJibSfe+++26OOeYYstksAwMDvOENb6BWq6Xfx3HM2WefTaVSYWBggHe84x2LKN+uuuoqBgYGaLcXS1WffPLJ/M3f/M2izy677DJe9apX8apXvWqXjtWvfvUrnv/851MqlSgWixx55JFs3NhTl7z88st52tOeRhAELF26lDPPPPMJ+2Rubi7lOC+VShxzzDH88pe/TL/vwlkuv/xy1q1bRxAEu6RIvP766ymXy4vEoXZlURRx5plnpv30nve8Z9HxrrnmGg455BCKxSIjIyOceuqpjI+Pp9/fdNNNKKW44YYbOOSQQ8jlcjzrWc/ayRH/8Ic/zJIlSygWi7zuda/bKeN+0003cdhhh5HP56lUKhxxxBE89thj6fdKqXRMdF8L+eef85zn8KY3vYl3vOMd9Pf3MzIyshNt5e/at/fffz/PfvazyWQy7LPPPnzve99DKcVXv/pVAI455pidrunU1BRBEKSUoV/60pc44IADWLFixaLtTjrpJG655RYeeeSRX3ud3ve+9/HWt76V/fbb79du17Vyucx3v/tdTjnlFPbcc0+e+cxncskll3DbbbftFCT/8pe/5IILLuDyyy9/UsfelRWVR1F5FLRP3YQUlTB21G1ITrnktUdee0JZOF+D+RoqmyGjXAatS3HBNk0b4ihRptUJ1aKjFKYlGN6CMZg7bkQfejzZ3QKmXAeUFVYH5IaUtQo7X8fpy5G1ClNtovuy8vlcHTtXR5dyTE/lKFhNPB1iOpaqkqK2fkL6CYlDRd5APBsxaB38ZS5jjsFbWcJbWWJUhQTWimiTNpSVR0l56UO+rDwK3b9xKeBQxMHO17C1OrbdwbY7FJXLUNIPBeWRRShAA+0SaFecxzjCdmLMzd+g9at59GEn4O2zAnfQwx30cDybFgt3nWeFSt93HY08cjwfjZ2agVYbD42HpqCkIC/GkMPBQ5HBgVqVjHKEEhNwg7hHjYhQ9mWNIbKayGoczzCrYUgFZNEMKp8hFZBDk0PTr3yGlE8WzbDyMeMzgqWfmKFPefQpL92+X/nktU9We/jKgfnZLv0+dOQ+YsMYJ2vpKEVsNGHkEEaOjL1kLOaUSxH5O6M8oeZLnFmVBPFFJdegpFwKyiWDQwaHonLxlYtttsRR8gxa2bTffOXgJ+xQrlLSb8olq1xsZLGROHpKS9BQxqWIsL8Uk7FRxqWES0572HoTpQW3LGPKp6R8THJt88oTJ155lHVAw0bklUteufjKYSZukbOKbDK/+pXPtO2k51dRPh6aQLvktdCs+l5MhjjFTqM0dss29L5Po6OkTqLVcWk1PFoNj5rWNJSm37r0WcWgdRkwin5cAoQ1a43xqCifslVUlMd222TctpiwbSZsm5JyySuHfNLHFeXhoSgrj0ryCtDpNfFQ6VwpKy89n2xyDQLlSjBnLPGmUZw1y3DWLANjiG76N9znnEqMZdgohqxLySpWWZ9V1idnYal16dcBPhKkdZ33LjSjogIcpfCVQw6X0Bo6NiaPSx7p5yyaARWkYzanfXLGsDQKWRqF2FobN2vAc6kpTdW6NJoe9XrAZJhhMsww08zQwVJMxm13LJaSV165Mh8SKl+F6Dp0+6P7yuNSsJoBI32YUS52ZpYsWu4xKHIJRWigNBphZMprmXMAYegQhnKN8gjLUwGd/O1I4mGqTsFAzlhMWhRsEy0MMPMd8mhmVYyxiia9+qk/pv0hYTntdpv5+flFr8f7j7+t/exnP6NcLqeOPcAzn/lMyuUyP/3pT3/tvjfddBPDw8PssccevP71r1/kl912222EYbhIxHLZsmXsu+++v/G4C+13ztx//OMfZ/369Xz2s5/l1ltvxXEc/uEf/mHRNrVajWuvvZbddtuNgQHJDjYaDU444QSe+cxncuuttzI+Ps7pp5/OmWeemfK0n3/++Vx++eVcdtll7LPPPpx//vl85Stf4ZhjjgHgZS97GW9605v4+te/zsteJnRJk5OTXHfddenyCMjKws9+9jP+67/+C2stb3nLW3jkkUdYt24dANu2beOoo47iOc95DjfeeCOlUomf/OQnKU/4pz71Kc4++2w+/OEPc+KJJzI3N8dPfvKTXfaHtZbnP//59Pf3881vfpNyucxnPvMZnvvc5/Lggw/S3y9UdA8//DBf+tKX+PKXv7zL5ZUvfvGLvOENb+Dqq6/mRS960a+9BldeeSWve93r+PnPf84vfvEL3vCGN7B69epU/KjT6fD+97+fPffck/Hxcd761reyYcMGvvnNby46zrvf/W7OP/98hoaGOOOMM3jta1+bnueXvvQl3vve9/KJT3yCI488kquvvpqLL7447cMoinjxi1/M61//er7whS/Q6XS45ZZbfutM8pVXXsnZZ5/Nz3/+c372s5+xYcMGjjjiCI477rjfuW+NMbz4xS9m1apV/PznP6dare7Ewd8de+eff37K13/ttdeybNkyjj76aAB++MMf7lLldvXq1QwPD/OjH/0o7Y8/ls3NzaGUolKppJ81Gg1e+cpXcumll/5ezEGf/Me1ANhWC9ptVF8fttGAdhuCoCd3Xm9y2icmySsPX2mu/ac9sLWabD83JwcLQxFMimMIQ1737nv57Mkx3/jCCg4dlgD/vec8SMQDHN4e4pDcDF9+eCUHxw12H5Ll5kNWtrjwyyvoM4r/b/8tXPy1FZSN4vX7bOHCL0mAVTGKA8MWpx+wha/ctpKcsbzt0K1895YVrEBu2q2qx/q4zcZf9POCzAyP/SDHi6MGt/+bXOcz++aIPY0fxNRrPue/bVB4tDsdKCQ80FEMrRY2ilFaY2t1/v6KOKVOBPjEPyzBTkyhli2HZhM6HVT/ShGyAZRWbHj3r3i2GWHT9zfx/OYIXzvhkxzVdrFIkNvUir445oTdtvHyF63FVhuokhBV21qiRFnIS0AxX0MPVnjrJ6qEVLn27GVpW+18DVXMEd67GV3MoAKPf/3HzVx2gjjSP/rqUqZch77HYr579618/Q1DfORy+LvdtrNji0Ce7t8yxGsO2kLuubtjZ+ZQlaI4i3Oy3K/6ytKO6XlUpciZnwsZoI86Mef/f0m/KS1t6a9AkAi6OS6XvH+cZ3fkvD529p189KQG135lmMHIcviqUca3F/GS7P3V/7SHjMOuOBokPP4r+ed3SgLiKy9yuPLzLufssYXCS/cXPn/HgU4HG8Vpv6nsCt79ge1c+1LNLdfmGM43uPZNy9NxjVYyZjsRNgzRlT7MxDQPfUn65DhT497bhtjDqfOSv6v09gkjyPZ0PtTg0/jOeRPkrM+yfI2L37y0x1fe7qCGBrG1mrQznxU9gnYbtSRRhZ2ewtbqxI+O4e67Xs671cZMTKMKwaJxoAZE1RZreOyCjey2RmAd2rF86KqlHNh2CNWDvPKFk5hayF03DDA9J9njffwqLevyjrcvIf7VIzhPWyf/770GW00gQtUGur+M2TGFXjJAvGkUMh7KTVhURkrgudhGEzXQL/eLdgdcJxUno9VGrV+P3bZV+sp1sLPzoF1UQZhubKOJGlyfXud3fHiMIzoDzH1Dxv0P9C9YrrLEnMtHf/FBmuecgbNmBDs12ztGrYEq5VGlfuxsFVWpyOparY4qJdz7jpN814+tNWSOFfOoXJIxj2PMtIx3VRpKxpui8fW70uv7k68sZXVJ8/3PaPbJzhMbxVQri8KyJJCVvNgo3rnfONlj9+5d+1jmJoDKlqC4nOi2+/jp1f2UnA6zrYCPvbPc2z4RAzRbx8Bx0EP9kF/Ctf8yw7+cNJ9sY9Erh8Em7e9I/6o+uaeMX/YQj7UK0IL3vcE+TtwhGa8j67jrX7bz3GWjmEizfUcJazSxAd+R+fMfP1rOuc8dJZqM+OUvlnDVOX07HeePYX9IWM6HPvQh3ve+9y367L3vfe8utW+erI2Nje1SrHJ4eJixsbEn3O/EE0/kZS97GatXr2bTpk384z/+I8cccwy33XYbQRAwNjaG7/v09S3u5yVLlvza4z7efmfnvlwuUywWcRxnkWNx3XXXUSjIzbter7N06VKuu+46dDJor732WprNZqpkCnDppZfywhe+kI985CMsWbKEiy66iHPOOYeTTz4ZgE9/+tOLxI6y2Synnnoqn//851Pn/tprr2XFihWpGitI1v3EE09MO+mEE07g8ssv5wMf+AAAn/jEJyiXy3zxi19MIRx77LFHuv8HPvAB3va2t/HmN785/ezQQw/dZX98//vf5+6772Z8fDx1Ej/2sY/x1a9+lf/8z/9M6Q07nQ5XX301Q0NDOx3jk5/8JOeeey5f+9rXUsfy19nKlSu58MILUUqx5557cvfdd3PhhRemzv1rX/vadNt169Zx8cUXc9hhh1Gr1dJrBIIJ/6u/+isA3vWud/H85z+fVqtFJpPhoosu4rWvfS2nn3562iff+9730uz9/Pw8c3NzvOAFL2D9+vWACEEttLm5uUW/B/CsZz2L73znO+nf+++/P+9973sB2H333bn00ku54YYbOO64437nvr3++uvZuHEjN910UzpG/+Vf/oXjjjsu/d2TTz6Zs846i6997WuccsopgCjOdoteQJhvDj744F1eg+XLl//RmXFarRbvete7OPXUUymVSunnb33rW3nWs571G4PAhdZut3fKWJjVexL4HqrTgvlp6B/pvR9eAfXEqWs1uK/1ZQLtkdU+rDsBlTyE1ECy8jY7Ba2mBAWtJnlVReU9HvMVR5UlSCjOa/qMsMuAMFrUOy6rKgK5cCuahrLix1UcYVvRKv0c5Bm4QwXs169pK6i5CuUqJlxFsSO3tX2e1uYHPws4dniGTdv62P+Z43ztFys5bvV2AH756BLWl+fSfnCOfgm2JpzxqiABY/dvskWYF+fphk98hKKbQyfjQz/7dSLt7gVQnxOhmPEtvcVzx6WoNlMw4Dmiv7nC+gzbNtMJd/yUVow7Ds9eYlH7HyT92mmBn5H3AJ0WKo6gWIEo4o7OV3CURu0jSQ/CjogNtVvoTaOowENVigwag5ldwCtuLG2lWWYdbL1Bg4DcWo27vUt1qVEu6COe21NDTc4D6CmaJkI/t178aTomIuv46Oe+S7apz0GQkW23JJAgz6cvnsBLZO0rBKh8QFNBzsREbYdW5BLZxMFZt5f0oTGpcJJtVmFmggPbAtlo3NMga/oxoUI/60QRLeqO61H5XbVkDXb0ESp2B+Fj87TIMbS6itpXaj/S/nVc2HQ/rJRAvfPp/2BVwlD737ev5LD8DGO1PPq4l4gAk9JyfnMStKrBFdiHf8lSvYVHyLLfsjr68OdCO1mh6IjzpzotmNqBWruPfFaf7wkeBQFs24q7/+7og4/EJuPJeeR+9KFy37JVOXdbn5P6F9el3tzCUH8SBGpY/5hmta6T8SOqd4W0qh4bnYAoGZQTcZFYw9NXrSE4+f8j/uUNZF7+VqK7bkDtEC0Jyn3g+biFPhElm/02eqAvDXydI0/C1qfl+uQq8h5QpeG0jWm/Dq+AOEIPrMS2a7J9dxtrsK26nIvjstZMMRyHKSvOPdmAktUMG0XznDPIfujTmOntmO0PiqgbiKCa0thWHe0Fab+qTitNTjCwRITBOi3U/Ax2fAe4Dvrpz06vj+tnRbxrZkeqtB2s34htS8KvdGfI0Lo6a+7OUG97xEbzgO8RWJgOezDQvfbR6MOfi53YJvNgfhpVknuKyhaxtRnUPQ+x2/A0P58aInYUhz/vFOxC9ddOE7X1IfS+R2Hr09j5SUL1PWyciKO1IrznHI/d8Rj4GZibgZGV0JR7cf/BD7H92yLs57zwJXI/0VqUcj3J7Nv5KTLeZlzfECuIrMbFUAg6zLYkEJwJQGc93H6oKleSN//D7JxzzuHss89e9NlC8c2Fdt555+0UCDzebr31VmDX8GJr7a9Nbr785S9P3++7774ccsghrF69mm984xv8n//zf55wv9903MfbH5wK8+ijj+ZTn/oUIGJHn/zkJznxxBO55ZZbWL16Nffddx8HHHBA6tgDHHHEERhjeOCBB8hkMoyOjnL44Yf3Gum6HHLIIYsgJ69//es59NBD2bZtG8uXL9/JIYvjmCuvvJKPf/zj6T6vetWreOtb38r73vc+HMfhzjvv5Mgjj9wlNnt8fJzt27fz3Oc+90md92233UatVktXKLrWbDYXwXxWr169S8f+y1/+Mjt27ODHP/4xhx12WPr5j370I0488cT078985jNp3cAzn/nMRRf78MMP5/zzzyeOYxzH4Y477uC8887jzjvvZHp6OmV22bx5M/vss0+638Ji56VLl6bnv2rVKu677z7OOOOMRW09/PDD+f73vw9I0fSGDRs4/vjjOe644zj22GM55ZRT0uOAqMfefvvti47x+MLmxxdcL126NF2q+l379oEHHmDlypWLgs+FfQsywV/1qldx+eWXc8opp3DnnXfyy1/+MoXtdH8nk1mMN114Ho2GFHWdccYZXHPNNel3C6Fmv6uFYcgrXvEKjDF88pOfTD//+te/zo033sgdd9zxWx1vVxmMd5/5Wv7xTa/DzmzDGoNevhd2ags2jtDDa7FTUqVvHZeZdpWClyNyYvTASlRpANuqY8alOLELtaBQBM+nbjeBcQkseMWu82jxtKISgx9E1GKDxmISqj+V0bSR4lGdcQixtLHp5yCFd6ESSrpQCYe1UxGRnSABjpqWJWMgbDlknRgbCdVel9rNx6AdebmOQZWHE9XPGFVMxlryty4PYxIF2MjEtE2YYl9VoR/qc6hCn7ROacjP9UjstWbadtjhZqhjiNDMKUPNOqlCZTuhvTQdiyoPiRPrZ1D5sjhxIE5CotCpcmXmo4YUY5aStsaRbOtnUBkPVc6jAp+abqFyiYbAgvtFVRlUMUdMhDW9e6sCbIQENHGEyhSxYbOnuJvvh8YstBpQ7KMZd3CUZj6so7KS6e4eTeX7scUJ2TfIUNPgJXjfKjEqmyFU4CXXXytLZJKgaWh1qhIqxypj5saxYYctnmwTLNd0HgYnsIl6sPS5jSPISkJBFQehOsM21cFbWyb345h21e3120J15WJZPo8idM4hHJe2elaUOzVWnLOmXFe0kyq0Ki+LLZSpxy6eBhMr1MDK1IlVnYw4vjPbsZ0WangtzI9jHRddkfulGX0IVZgFz0NVRtAj6zFTW7GFolwPOTlRsNUaG7ZRicJqlzpe+5rtrmVty0UpS1ASGFY0S0qJGiuh+tS7HYydGUPvcRhmdgfObocQJ8GIKg2AJwqoqjSAKuShVETlcsm470vVSlXfCLbbrgWfp3Nn4jH5LF9GkTi4US/JoFxfHHXHZauO2G1BkLbd1vBVDk+7OGtGMNPb0f3LMFvuRZWT+30yFlUmn4zZPLgBdn4KEh9OlYfk/pTJY7VGVefA89NAnnYSHOUq0jal5Rq7DsqV9jSNizVC7dnNbJvkFS7wu5TroPqWQ5BHuQG2MInql5UijKgn674CtWoz5dNXuXJP/VVr6DSxmZzMqWRVo6ZBBQv8lWwRChVx7uMIlStikyDctGLCLozez/ZUd6MoVWFWxT6BwbUcogT7r5VFKYTiExGkI+OhYoNnDar/T8Nzb/6A+qpBEDyhM/94O/PMM3nFK17xa7dZs2YNd9111y7V7CcmJhbBjn+TLV26lNWrV/PQQ5KMGBkZodPpMDMzsyh7Pz4+nta3Phn7gzv3+Xye3XbbLf374IMPplwu87nPfY4PfOADvzb6+G2ikqc//ekccMABXHXVVRx//PHcfffdiyqUv/3tb7Nt27ZFURKI0/+d73yHE0888dcy5/y2rDrGGJYuXcpNN92003cLoRQLg5qFduCBB3L77bfz+c9/nkMPPTTti0MOOWQRxeiTHTT1ep3nPe95PO95z+Oaa65haGiIzZs3c/zxx9PpdBZtuzC46f7ub0Px+PnPf543velNXH/99fz7v/8773nPe/jud7+b0jtprReNiV3Z4wMspVTaht+1b59spHv66adz4IEHsnXrVi6//HKe+9znsnr16vT7wcFBZmZmdrnv9PR0GlD88z//M29/+9t/4+89WQvDkFNOOYVNmzalsLGu3XjjjWzcuHHR+YOsRBx55JG77CvYdQbD/OAyzCO3ywNiagfG3i4PgekJjLmjt1Q8P8Oy7AD1uM2QV5TM6P0/h3J/z0GqSqaRVhMadXLKwUaxCBBNy8Mja0VevmAMU7N5hl1N3o3wC/KwtB0pCA0s2I7BATzARsLnDBBYRWAsRFbEhxQ0H5E2hN1tdi/zyF2WE9a3uO0Xg+yRU9QcUsaQupIHmufHxEZjNt+DKg9jp0cxteR6F/pgfop4YrNkZkcfYTAoM9WeZyCQ62Fnx1ClYcy2ByDIYBvVNFsLgCv4374I5lyHpbkqGVOirCKqSRFrOclS6ozCjm9JHR3brInjAtKvzSbk8thMjgGviMFiJ7f1fivpfxsZVCfCOiE5g8A/EmsrRcZaPKsEdvQ4C5VC+4hzUZ+TVQnHlfMCyDQl29qYg1hqLApuhrZxeisdnZZkTzN5ab8V2fqcAZ3wZHsoaHcomIA57ZIphjTGXXJOog66/SFxxoyBTE7GWKcFYYfVoRyjtcUQWAjrGjs71iO9C9uy8gTY/Bi2MccSfMJNE3QYwc/F0s/Qc6gcFzuZ1Ib5AbrgoWd7/WOMwqDEWU+yzLZVTzOleD60GwTKUNMK7VjMo3dJVhmwMzskk+u6MD2J2XSnOG5TY5hJWU0iirAzs9K/E5sxOx6DwWXY0e2Y0QcBCSbtzJiMEaWxVmpNVCI+FdcMZaMYzDexVhHWNWFLguBU2CtxKM1t34Pla2F8GyxdDeNboSordTbpG/eZLyL61Q8wo5PoMEwz92brfajiIGZ6G6o6iaqMYKa2YJpVCagAOz1KPL0dPbASM70NprehKktlrhT7kn4Zk2vg+hCL8uyIbjAfyzOhonz6rEPOgp2axWx/ELPlXtwDjiW6U1Z/3f2OxsxNYLbc23Ni5yZlviTPFju5rffd1A6BBxXy0i5AKQfbrGL9DDRqMmYdF5X1IZKeK3ttlEY44bsiT0i/5pI5ZoF4ch69+R6YGZfjzU5hg/ul8ysDYAxmpkahGNHpKGIFZmoL6CSoMbG0dXoCs/1+WU0I2zgWlN/dxmCnt8PEqKyUzs1is4U0weIUfcnaW6B7Pws7cn+o9uapUpbi6hAbhYxNFtPxbrtsX8h9wrZiQqWxo9v5U9ifhk1/ZxscHGRwcPA3bnf44YczNzfHLbfckiYNf/7znzM3N/dbOeFTU1Ns2bIlTYgefPDBeJ6X1t0BjI6Ocs899/DRj370SR/3jy5ipZRCa02zKUuS++yzD1deeSX1ej11xn7yk5+gtWaPPfagXC6zdOlSbr75Zo466ihAcN233XYbBx100KJjn3766Vx44YVs27aNY489lpUrV6bfXXbZZbziFa/g3e9+96J9PvzhD3PZZZdx4oknsv/++3PllVfuklmlWCyyZs0abrjhhicFkTnooIMYGxvDdd20uPi3sfXr13P++efznOc8B8dxuPTSSwEJMp7IMb755pt3+nv33XfHcRzuv/9+Jicn+fCHP5z2y66YVn6T7b333tx8882LCpUf/7sgwdbTn/50zjnnHA4//HD+7d/+bSfu1t/Vfte+3Wuvvdi8eTM7duxIg6LuctpC22+//TjkkEP43Oc+x7/9279xySWXLPr+6U9/Ovfee+9O+7VaLTZu3MjTny7L+8PDw7vE4P0u1nXsH3roIb7//e/vtGrxrne9K4VKLTyPCy+8kBe+8IVPeNxdZTBaSwTHrjIlTHVWMJt+FlufR/UvkYcuYMMO81GTRtSi7RdR/UshV07hFwC2I7h9snlot6jaCOWLImSmIo7S/A6Dg2Tec0FIw0hWtDUrtyN/GXQQgR5cEWeJEex6J2UmSawrNgR4FfnIT1yYaFuVZXGJ+c0+K2kRz1sKMbRr8jsZawiyEdYorAXyZfCzAu1IHDKVLckSer4smdlMTqg+te4xwAR5lJ/B5suSfQs72CDTy9xbw7zpMONkmSRkWyNPK2upWzd1ttpKRG9My6JGVkvG0fUlE5fAgVAaSgbaLVTfEqbCqsByBnqrZNbzBSbh9jKO406ELso1z1rDmNY4BmrKoLIZfFqYWowxvUDYmiTr3qiiKiPiYHczuuVhcdxnJ1B9I7RNhxJZ5sK64IkBchVIgh47PyXZwiDDuGOJEhGrmhND4NNU0G9C4lDTxCGTUEuqviWLM5luAO06dmqUzUnmPrNc0X4EvLxBBfkerEHpNHOP60O2wCwR7soiDqJ+XEn6zbabKMeTFZvKDCxZiXI8TC2kvkPGykAcEcUaV1lUpoQNJ5PMvZZMNUh2NMgxjcdwFDE/maGvMozKJKsZ9Tlx9DN57Nw0qm+JZIlrM5BP+i2OYHZG5lCxT7LcI+sxG++VbDSg/Kxc5wRa0V3Z0MnqjGlEzGjLaD1PXkcszRviUALsrqBWYKWAnWWrxRlcuhqiDmrpWmwCVXMPPA4zN0F074/QK/ZBD96A6itDN/GVLcoqkeOlc0cOnk/fK+XIKl4mL8cPCjJXMjmUTpxuxxXYleNC2GFcRTxMLhWomjENHK1YhS8Y+6iDKg8R3fkd3AOl6DC6+0ac3Z+BGlwhjmxWftPO7Ej7SQ2tws5PojJ5+c0wBMeRFbtk0CuA0oCs/AA4LmZ8HmekIm0JNSOzDm3jUPA6xEaTM11V4yQxhsJZ2o/qG5F+8HxskFkwTjLYZhWV8Zib83CtJVaql10H8Fx573ngeOAGKMeVTHyjk4zbSFZO4wiCnAQipQFZ9QPCHU1RhU7Ow7bqMs5b9XQs4Xh0Yof6VlfEAJPtre1l7i2gfBfcDlWtUQN/msz9n7vtvffenHDCCbz+9a/nM5/5DCBUmC94wQsWMeXstddefOhDH+IlL3kJtVqN8847j5NPPpmlS5fy6KOPcu655zI4OMhLXvISQCDvr3vd63jb297GwMAA/f39vP3tb2e//fZL2XOejP3Bnft2u52C/mdmZrj00kup1Wqpw3Haaafx3ve+l9e85jWcd955TExMcNZZZ/HqV786dcDe/OY38+EPf5jdd9+dvffemwsuuGCX3OCnnXYab3/72/nc5z63iFlmYmKC//7v/+brX/86++6776J9XvOa1/D85z+fiYkJzjzzTC655BJe8YpXcM4551Aul7n55ps57LDD2HPPPTnvvPM444wzGB4e5sQTT6RarfKTn/yEs846a6e2HHvssRx++OG8+MUv5iMf+Qh77rkn27dv55vf/CYvfvGLd1mQ+XjbY489+P73v89znvMcXNfdiXrx8bZlyxbOPvts3vjGN3L77bdzySWXcP755wOwatUqfN/nkksu4YwzzuCee+7h/e9//29sw+PtzW9+M695zWs45JBDePazn821117Lr371q7SAdNOmTXz2s5/lpJNOYtmyZTzwwAM8+OCDi4IBa+0uC0GGh4fTWoxfZ79r3x533HGsX7+e17zmNXz0ox+lWq2mwd7jM/rdwtpcLpdOsq4df/zxnH766SncqWs333wzQRAsgpDtyjZv3sz09DSbN28mjuN0JWa33XbbqRYBJJh96Utfyu233851111HHMdp//X39+P7fso69HhbtWoVa9eu/bXtebzZqmR1bKsuGdfqDOg5aHffd4vCBFdtE5o4W5uR7Gih0oPjNJvJknILrCWvXGwUi/JrU/q8bDUZqwBLbBR+kqIJSsmDzbgpPSHG4iYAGGt6mfsusw4mFZIkrkk2sqsU6SwtMOZYSis6/GI8w94FRVODGyS810rRbrpkCx2p/wvbEIeSWQ0TyEDYlkxX2EYl2WeAdhzSNkmhcRzKd52mPA5Nst0CWE5BeRQMDDoeg16DjM2TUXFK2+lbeajqjMJOjUr/uf7izL3nS0YxyGDnp6i4eaGC7Dr/xgh+W2ussYIlN5aRWGHm5HwaSlMyFtdCDo1ttmhicAd9Fk4JnVHYVsKrXp1MMsRJSFWblvPTGuan8LVHbA1FN4dNoA2EbcHl16clKEhw+8OxSukYczgQhmh8prWH4xmKKhK2F5Dx1R1XCeyAdgs6LVYkmfv2qCWwEDX1YryyNSkeG4BOixIO0ZYqMXlyA51ev4VJyOi42Oo8anoM62fQBY/ckPz+1HaXFV5M2NECUVpQ5Nt1plSQgahDPyGbnAwH9regUcUmvPHY5FrV56DT7p1fHMFsgj+PI5lDcQytOnZ6VK5npy31Fsl4657TQtiSqXWXf6DPKJYXasRGEzUVUdtZBBtpKyV/T4yKYz+5XRz78S1Ql/OJbpc6N/fgE4nu/wm21oDAR6X3g1D62XVldSdoo7xAPu+es+vK+A3q4tTaWOZKkhWHJGMetmWO25g+67AbDeZtkrnXPutsIJn7WkMCpFYDd7+jie4WRjN3v2Mw09uxc+OSnY5D6dNmHXwJbO30drnWnRbMTGDn5lDFYi+rrbVAkOanZOwkEDg9WEzoVqHiikK1r2PC2MECDUey4yvC5DooMJNz6No0zIzL2J2dwia1S/QNSzsiQ7ncJpoqSpC/oE+wJoXOSNDThrCDZ0HlkqBOK1lZm52CTAPmZ7HFmXQV1VuyAH1gjVwbYyS46Y6hsEPGjcgviwSKt+Ax3c3cC0xP7iX9cYT9DTotfygz/89y90/err32Wt70pjelzDYnnXRSmpjt2gMPPMBcQjjhOA533303V111FbOzsyxdupSjjz6af//3f081dAAuvPBCXNfllFNOodls8tznPpcrrrjiSXPcwx/Bub/++uvT5YVischee+3Ff/zHf6SFrrlcjm9/+9u8+c1v5tBDDyWXy3HyySdzwQUXpMd429vexujoKBs2bEBrzWtf+1pe8pKXpB3UtVKpxMknn8w3vvGNRcI93WLdXeHljz76aIrFIldffTVnn302N954I//wD//AX/3VX+E4DgceeCBHHHEEIIFAq9Xiwgsv5O1vfzuDg4O89KUvTY9ljMF1uzcoxTe/+U3e/e5389rXvpaJiQlGRkY46qijfiv81Z577smNN96YZvC7zvqu7G/+5m9oNpscdthhOI7DWWedlRaXDg0NccUVV3Duuedy8cUXc9BBB/Gxj32Mk0466Um3BaT4Y+PGjbzzne+k1Wpx8skn83d/93dpgXMul+P+++/nyiuvZGpqKqULfeMb35geY35+fhEGv2ujo6NPiuXld+1bx3H46le/yumnn86hhx7KunXr+Nd//Vde+MIX7oShf+UrX8lb3vIWTj311J2+++u//ms8z9uJY/YLX/gCp512GrkEg/pE9k//9E9ceeWV6d/dTH83kAPB8G3YsIHzzjsv5dUHdlICXrjPH8pURTJXKlPE1OdRlWGUl8U0aqjKkGSOEBxzNWpQD1v0ewXJeLkB5IryMCXJ3HfxznFM1YaobIFIgfbkZj2nDF0WXmt7hbUm8T6Ur+lg6CiF8h1aGDJKo3xNK8l1+0qJiIyvCRP8sJOTDH43XLTNDjmr6MxpyibGGrsT96/rx6lTq3IVgTw05tJsqyoNYtt1lJ9F5cqobJG26RDFMXHisKpcRb4r9EO2SIIS6gVFwLzt0FI5pglpRi4N1xJanbano3rtVoPLZbXADSCTEycQ5CGfLciDujzEdFhDK5WyYwAp3lZ5LgQ+BD6TuoMui6PgWcuE1hSMpYERJhlqmEaP3s4iEChVGoY4FOwwpJABVRqGqC2OUP8yqqEI5Mx0qvIdiHNSnUQVByVAtAb8DNOOXHOAuoogl8cQk0ucwZp1cLv9Wh5e4EAmjk67jp2fYiKBoPgD0H4Y3KwUdabFv3EIucTpzpag0EcVg7tEmE3CRo9VhHard63KUzC4LHGELFFdfidrDGHk4GDknBqzknl23F6WujiInZ+ial0y1tJpuFAakHZBWiCNn8XOTaLKw6hcWTKp3YLhOERNjWPDUKAtYQc1vBaVu1tWyUhqPDpN+V2t04BTlxLBr+mQOW2ZbWTwtMEJLI4n/ZKUtaC7PO5DSyWbO7hMMr+Dy7EZGW/O3s/C1ucwcxPopXtgCrmEeSizaNx354v0S/I+L+ds6zOQ81F9I6j6NCpbkrmSKUk2HyCTk/niBaiwTVUZxk2ASSbmrGmwTbssxUWV8hI0F/swcxM4uwsNYReHT6cp1yZTwnoBdnail7kfXCGBlZ8RzH2jDpmsrEx1zXGlpqRrrgthlLLyNOMYEwplq+8INaRjxZGqJWPIKNB9yf1RORKMa53WZpAvQ7uOCjxajSRAhPSek1qnJRl/LwteFut46b2ya6o8jA07AltDah9oSYBtmqHUVShk7HSDXROjnOS3ojad2CGq9e6/j7cQK8X5foc5xxEmoj+B/TGVZf9Q1t/fv6jOble2sFY0m80uIod5IstkMlxyySU7oQh+G/u9nPvHq7NeccUVKZ3lr7P99tsv5RDfZaOSrPVvylyDOIinnXbaIqjB2972tp0oDxcee2qqpwS3//77/9rOfuMb37jIUe1aHMdMTU0tck6LxSIXX3wxF1988S6Pdd555+2Seunx+Oi99957l4UaT7RPt4D58fbKV76SV77ylYs+WzjQnvOc5+zEs3/ggQfu9Nm5557Lueeeu+izj3zkI4DUAHzlK195wnZu2LCBDRs2POH3sPP5A4sKWuF379u99tqLH//4x+nfXYrPx0OdZmZmaLVavO51r9vpGI7jcO6553LBBRekzv3ExAT/+Z//+aSgTr9pXjSbTXbs2JEyFq1Zs2aX+ge/yX6XfYD04aYcFzW8ClUaTt6vRFWWLqJQm23XcZRmLmqgKyMYa1D5vgVY0SRr7WewfoaxqIbqW05NzeEmixRbbJNp5TLsZCiXmzSr8kVrXoKIfD5gjggfjcoHVInIoNF5nxkrQYSjFDEOKh/QUhBhcUcyxEDJkYdY4742u3VidmwpsrI0z9wjPmvCkPFt8mBbnamRyYeYSBNGWvDPcYjysmlhKHEoTnZSWIjnU+008R2XTpK5V56PGX8UskUp6HQDGFq1CD+7I6ox4RfZbppMUeJR22Cb21u16SjIWTANi7NqX+JtD6DcAD20ijhhfZFC2gp28jFUUGCiOUvez6AHk/oQL8Ak7DZ6sALlEqqvn03qLpzVco2n3A6uhTlHsdHUUCv3Ysr+ErSi2hInyCBZP5UtYqcSRztbxM70sP0qW0wzxs2ow0CgcLWTOsnKz2PndoDS6JH16ZjYrDo02nKdN3s1VGUpM3qKaUdgAQUVk3ETZ7Uygo06kgX2giQ7nEcVB3nQ+REA/l5D7PiFxR9xUd3sPkmQkzg8OC5qaDXbbCPphwbWgB6WFS4bRyilsXGEbVbR/VII6aweZuJ7klBarlvUOh4lv9NbkelaN9tqDHpkPdu8HzMcxVIgXBzsfV8cFLiI1rB0LboyIm0bWCYOHKDiCLO8hpragSr0yeqJNVCq9CBPIPCxbiFoHImDNplkYw2MqohHVBbHWnYfnMWaiOx2MN0YJo5pKZ0WbHcL41W2KCsQgBnbiCoPY0YfRI/shhoZRhVLgu/ujgFrevMlqc3oziNAoGXZErY+K9/5mXSuLDwX3cXoW8N222bczaUQoq3RHMa11HUgVJcJrMRsuVccdpCMfacpBcjbH4JsET24AuPcmyYnnGV7Em9/QIKPylJMuyUFtQtgObZVlSBjZL0wIjkeZq6Jasn5bNP9jOzI8KjOcEhxijjUlJpZtIViEqDGSqGGB+X6uIGMXdULwlShH8rDKNdhW61AVhlx/v1sDw7UDdr8jCQXioPobJFxFQk0ClCNpsyRXBkcD1salAAh6cv6Q0buKd1+NrHck6JO2ieqbznTsc9aIwrM3VWz2Ghc1SNAUJUiKowYjiNY3WMUfMr+fO2Pjrn/Y9n09DTf+c53uPHGG3daBvlj29atW7nqqquI45hnP/vZf9Lffsp+O/vKV75CoVBg99135+GHH+bNb34zRxxxRErbGYYho6OjvOtd7+KZz3zmTnUdXXvDG97AzMwM1WqVYrHIpk2b+OQnP/lbQ2B2ZT/4wQ845phjnlRtxx/DUkq6II+qjMiDMsijykuwjdnUuVe5MlnXR6GYaVexnWZSDBf2speFfszYxjTjmtM+tDtkrSJMVqWLiVhN10XSFsZNwFJXHCnbDvHJ0kB4x30yNDDYdkSQOFYNYvqMZOcdwLcK5Tk4wIQR52OdZwlR+G5Mq+2RL7cJEcEqkAeYiTRKS3Gc7UihaNfRkcZIltzMjiXfDeM7Lq52aHTZPozBNufFQURYOcxMr+hMuSKKU7CasvLxrRFBJ5CiYKDtKGa0xak4xFvvw1m2J2Z2jHjrvejle0lTZsawYxvRaw/Ezo4xkutnplNNHWqz7X5xbmbHhJd/bh6yWYYQoSmArMnRUYqOBV870GriKYXSikpOICjbGhlsLMV6etW+2Llx7HQVvUIYtuz8JKY6iV65D7Y6SX9QYEttgr5MARUkxZaTjwnr0vykjCEAG9OPi6N7asbUBcrkWYvSlqwjjqqMg7o4OF34S3J9CNv0J4XIZmaaDAPEtSgJBBYQAaRZ/Ag6TSrKx9abWASmkl6fBNqS4pATx9Nsn6I8IIHi2JZBMkqgGCpf7uHfTZxea1UaxIw9zEBkmNeOiIU1qz34SXkIM7lZajQqI1KQ7LjobjE2QJBB9S3Bbt8s7EczYygvi17/9J7D3GmKg9iqpw6gUpZEJBrlCuQqSIL9aNrQnnelMD2J/z0sMVYoWweXY6dGUZUh7NxEj/GoWZXsetiR8b1uT1nJ664ydKk9uzhvk6xqdJq91YTiIGZ+HJSWVZ3uXFkAJ9JFWR3DGPCzVJRHzlhCR7z7gg6o6AAXjZ2tor1Ajh9HiwpFbWMWs/0h9LLdMTNjmM33oJfujq1KMi/e/kAyr3Zgtt2PWrpOGHK682dsk2w/vR0btWUst+qoYgYzI9C4Uix1OvE8dNoucVJk7WIpJCxQkVWodXvI9WvXE8jegtWhsA1hm3hynowqMqtcjJLAJr3G1ulB3xwX4hAbhwKlS3QvbL0tQfeCc+jSbAJkl1uizeLkCQVpHeX6srrSpfpt1ckR06m5hC0HR0m+PF5Qf5O1Uviusr6QFbQb/CnsyVN6PGW7sv+xzv1BBx3EzMxMisH+U9qBBx7IwMAAV1999e8lHvSU/fGtWq3yjne8gy1btjA4OMixxx67COr0k5/8hKOPPpo99tiD//zP/3zC47iuu6g4+7DDDtuJVvN3tRNOOIETTjjhD3Ks38W6zBbKz0qhV3FQit6aVYEUdB9KrTrNqIO1lpwXSJav0Cf7d2ETzapgYl0flEPDdJKiyWZa8Fq3Eb5yiJUI7rSVJW/jFIutPIeWjdHKAd+lgxGFUM9J5dy7Tr7yHCmoVUnRF1IoCxC3xcHpRA6BFxG2XDLEtEPZLp/piJKoIwqRXYfNdlo9R09p+TvJwNnmPJ04IjKxZKpBMn3ZUkpZZzutxUv7WlM3HeZcQ92EhCpDw0aEipQrXyE4aYxF5YTyUVdGMCRZSRK6wVYVM7UF3b+cVtxmrt1I+14V+rG1Gdkv8CGbgWxO4DeJ0FKkoKUFAlS3IeQLtGwMrkLpBXSYgQt+BjPxmDgGtWnBLAOqfxlEHez4JtTwWkIbsyTXx2RzTrKdSJGxnRmTrGgXDhDkaWPT7GDddCCfJaROqDRe1iyiGFS5cuqwK8/vrYSEbaZV4jz2FWhj0TlHoC1JjQTGYLv94vrg+lRtBNk8ihbaNT242cJALshLBtoN0INlGvMSkeZUjEraTasujrnSi+gcu/Nl3tGUY0PUdmRMdLHTYVvmVpBArbJFmXOdpsApQHD/s2OSHfezMr8KfZgdG1HJCo0K8rJPtoi1RoJKq1ALnuYNDG0llStuvyaIItgOCSIKiyJGQXlQ2l0akMLiQl8a3CiSour5SRlbWx+UAusE060qI735EXTnTlOuQ3LPkLlUBO2IU59PViD8bI+2NDmX7nybtSFt5dGtoKibDnUbYnBRlYpsn8knMLUFK2yZEmSLmJkxdN8Ipl2XYKXbt82qQIwqS7BzO7Dzk+jBlWk7Fo3ZZlUCkiCPrbbQWRkrDa2JOnLPcd0YIrmPdVCoJJjSADMTspKUK8v1j9q9YtlMHqU0ur9Axzo4WLRVKMfFdmlfHRfr9LQU8AKU6wslcJf8IzBpUNVdMbWdVhp8RbPSnu49xLbrsqLVDZqTORai0zqkhWu/OhnvHWWl1iL5PC0M/iPb/wTM/Z+z/Y917v/YwkG/ziYnJ3/zRk/Zn4X9zd/8zaLi3sfbrqBJf3GWODc2jrDT2+RBHodC8Vgc7EEd6tNp5r7iF+TBEnbkYbtgG1k2RzJEsDibSgKhsZaur5S1ipwT0arKQ6sMeEpTxgVjcVCUhPMhVYUt4TKvHdBJsS1gqi2gRMUV56PTcMgS0wpdCvm2FM86Ma0kM1z2JaDoNF3J3Cd88nZ+PF3aRmlZ2fACCGWlIucFeMoh4ySFevOTsk1SgGfnx8W5X6A22S3gjrB0FlSudmGuWQs5A51xQ35oNfHDtxI35gSi87AwPNnGHCrfh9n2AKZdZ67TYCRXSYtY9cAK4sfukgd5GAo2utNmwraF9QgIVX3R72JkFcHUIkbnJSAxGqH+iyPsjkcxcYQK8rIiA6jEobUT2wR2g2LAK+IoLSscIDUbYxtRYVMclKiDMoYpOtQjeew4voZOiI+SQui6Qz32yAdJ/UazKrhjGwtnedhMqQy7egd4rjAp+Ro7P9nL1huT0nJaNwDHJcYkjlFLGJKSzLN0XsIr3phDhcOp4z81L9Cecq7FeD3HUK4pKyPzk4JVT6AogMyjTJ45DSORIQwduTZJcGOrk+IsmljmVmVE5tzcjvT3ZDxNQbst7Q872NoMdnRTirnH8WS8JSxG1hrhWk9iKGsgxlLXC+o4tBR9duecT0xkk42rs0LXWJtN2lHt9X9jVgpTK3MwuhnyRWxS1GcTOJ+tTkI3EzwzBn29hJetTooDboysPLmB9IMRKEq6TRIoEHUwWBqaVHALoG0NvrKiclufl4B2brKH25+dxHqBQHE234Np19Ej64nv+wm2JQGas3p/4k13YppVnFX7Et36DUy7Iew+AHGEmdqCCpvCTR+H4HhE052UiWiTr9htPkNbw+CaOnFbUXqwiAJaVrYJUdjqPLY+hw2bIizXrGLbzXRuWE/oNRtK4wAOVq5zyvbkyHivzQqzkBtgPZ8YKwrAAK5O9DCSVdMgj61PpyxEk4/mGYitMOxMb5ex6EiBczeg1UBDOem06Xa5o22X/TPpmxgzWyOnsovnzR/R/idg7v+c7TdTlTxl/6PMWssb3vAG+vv7UUot4sj/Q9uGDRsWFTI/Zb+b3Xjjjey1114pr/+ll176Wxc+/z5mZ8ckW9iqo4ZWy0O4XU8FeGxrHtuaRw2sJOdmyDgejVhYS+zoJuzkVskKtespbaJt1aHdwlMOxLEUtk7JK6dctFJYBdoVHvtq7BFFDlHkYMMYDbSx0IlQCAWmDWNU8q+DpWwibDvCtZCxSbYZaMYuzTgpLkSlnNRRrPGcmNgqYqtwHIu1CbGK0djGrEBI/Cy2OS+vljw8bVUUInFcPOXgJQwxsTXYsImdn5L9W1XIlbEmFNhSp4k1IYFyKFlNUXk4VhiA2gucl4aCGQfcEsQP/Rxnt0NRbkD8wM9wdjsUZ7dDwfUxYxtx1h8ESrO+uJQ4ydwqpYke+jnO2gOlaNNY7MQUhCEDysdOz2Gn5ygk6pZNlfBXd9opA1HFb1Px2xgFZDxxQJeskeLZ+XH08FrBqYdt7Ow4angltlWnzy8y0ZnH1y7KDcQRmR1DL1mbMNzUBVZgQvrwqONSx5WCzk6HGFHNdTyDpwyuG+O6sYyp1rwU0bbrUJ2RrHqnSRGXIi621hANhFYs16Fdl+vWDQTiSMZv1KaoPGyrRYwiDnXab8px5RX0ssHK9TGTc7jayMs1VJWIQqkgjyoNClVlaQDlBVKAm+DOMxZqShOHEhh2x5XKlXtza3itBMLNeYG/TW7FTm6FOEQv3xNbq8nqyOgmbGsevdvB0o/tujjDjitjq12XQBxF3NbEbU3YcPBQSZGn8N6HdU3eGPIG8gYGci2G3DZsflgmwLZNEkiMbupBXqbHJYPdlOug9j8ctfeh6L2egd7rGb3x7md7cyeTk/7v/u36Mm+aVaF17c6V1uJtCDspNKeoRPSupeQVKNGJAASS0mlJANRsinbAzA5p4+wEZuu96KW7gzHE9/0EZ+8jxHkP8sSb7sRZvb8I0d3zA5yDju8JmQFmeht6YCXU57DNhOu/00S5CtOIMY2Y1R3LXNsnBKa35JgZzbHar7M6qFFyQkpOSFlFOEe8QPqmWU36oypBST0573adeGx+8X240+xd47ApdQpRBM0atl3Ddppk0NhqQ14zPdE45bi9mhwbY20sMMTuPaYoK0CqNAj5khRzJ7UGWWtoVT0aVR9HS768HQlEx1GWwKpEJdohSt4/ZX/+9pRz/7/Mrr/+eq644gquu+46RkdH+djHPoZSKn0NDAxwwgkncNddd/0/aV+n0+Ff//VfOeigg8jn85TLZQ444ADe8573sH37n0Yc48/N3vGOd/Dud787pQV9/etfz6233rqoEPjxtn37dvr7+3cqMP75z3+eCmA8acsWU15ojIFcUZbOrWBgVb5fMtGdJh0T0ow7dOJIts/kUMU+KVLLdBVN87I0X+onxoDWtJTFK8urY2M6NiZCYDnd5fdMLiSTC1FKuO3nCUErIgxzyMpAaA2hNczZUDL0xgo7BaDyGVwLVetStVKg6SBQD5U4+K5j6ODQwcHLCMd9thwK5MILUEFBHDxPYDjKS/i3tU6hOgZLZGNCExIaKcDtsqAoT3jylZcVJzDIozJFQmuYV4ZOwtDfsFEKJzJKRLqyVtRFu068Xra7QGPGNopTv3wv4V+feAxVXkJkYiaa8z2+dT9LPLYRZ9W+qMBHlQqQS7KSCf1gnKwaFAzMmRYUy8zZEF1wyec75PNCt6fzCWPU/JTAHUhWZRLGE0AgD7kiFkvZy9GMO9ioLVAVLcGSCkQpFD+bQjf6dIc+3RFYjufRwDDlKvyioeD16CtVly89CRgIMqmj1sLQwqByWUJAuVq2UTotYFR+VsahG6D8LG0rmXsNiyBItlmVLGuiCkyzim3MoQfLaGXRytLpOBRtRCeUjKqtTYsTWJvpwSLadQjyaAQaprSV8+7ODcdbPLdcgXPhuDKHin1SfNppgu+J05vJicPWXQFRWuZqck5SALtYvM/LGkIkY+tZcCsuflmy+5GSV7XlMxMFkC+kwmh02sl8HkygduIs4nnyf7slqxuhvBbNj+Qa4yS87Ml1wvFk3vii+6DcQN4/bhv8jJxHJk+9S7maWIQhROaOKhUgTO4YnidMOJ4vdJeen6xqTAkUJ8gQb7sfZ/leOMv3koLz6e3ooVXg+ZiNt+OsObA33hxPgslsUa6bGyRKuhYbgY2grRX92RYTjsV1DdqxbOrkebRdYMlwlSXDVUYGq5iHb5Pr5/rST12oktbpXNADOZwulMci36neSzmesPVEkfRjV0fA1fLKeAIPa1ZlDNeSYNHxUtVig9QEUJ+TMV6dliCjNiMvx0Vh8TIxQSYSeBeiO7LIXAdVKRIog8o9jtXnj2TmD/j6S7SnnPv/ZbZx40aWLl3Ks571LEZGRnBdlxNOOIHR0VFGR0e54YYbcF2XF7zgBX/ytrXbbY477jg++MEPsmHDBn74wx9y22238dGPfpSpqanfi/Yp7N7w/4fZT3/6Ux566CFe9rKXpZ8FQcCpp576a/tj2bJlXHzxxZxzzjmpbHWz2eQ1r3kNp59+Oscdd9yTbkP3Ya5cXyAl3fdzO6TwKskK2eY8jbBNZGKKXg7l+qiR1eIIJM6wbcwmhXHC+R1bC56HQQr9lAshAgUJLHQaUkxWckJMrDCxggQ7P4CPyshDahAvzcwDDCqfR00OlQ+IgXllMbN12goGnTaDTpugENHCwdWi4FkstJhtZSg7HcpOh9pMRmA5DQffiSWAyZclS5UENKrQJ+wz/culX7yARtSmGbXRypG6gExeqP4Ksr+N2mmf4bhgDaHtOfVGKTLKpWgEKtF9BQaiWYOzen/J7G27P31v23XirfcKi0ergW3O82htB0MLGFT0qn2h0yR+7C7hSc/lwBhmbAc10Ica6KOpFQahRCzqDLRbZHCwrZjJ2TyTs3kJOqaq6OVJLZPnp9lQjAHXlyJfpSHIs70xhbWWyESpI6uXrE9VR1WQT6ECM4REVhNZTUa54HkU0RRiaE67zHYC2h2XdkeEjVSmKNnJbFGuhxuglIPBLsbkukq2KQ4m1603brusJS1iES3C4vqm52xl8j1sfLfwMVtMxyGIs6OxaJ1k7jPiiKpMvudgBnmU46UrMo4rBaYq2c4252WuOC52aksPf59QhqrioKx6TWxG5Qty/iOrJfu9+X5UQc4rredwA3lpwW37ZYNfFupLhYynghGOctOBeUfT0NDQUDcuTaVRS1ZD/5D8P7BEBNTakilWS1bLeZX6pQ0P3IHdeA/2sXuxj93bmy9xlPY7sVB4dtua3l8K/QlFblHmSr4vqVNJAp2uA0wSPCPsUTkLoYlo2ogMLjiOtHN4JRQrqKFVqKFV8n5wBc7Kp0mA2axKlr5ZJX7sLuLH7krnkpneLu9rM0R3fx/lZ1B+Rsa7MRIwZUtJMauHzjl4IwHeSEBNg+sY1oYK7RhJGiiZU/eODshrsh+7Y1SoQrMlCewyOVRlSF7d4CzroxEa31ApGbfde3FB3uNnUEPLhUbTz/boawt5CcCTgIhMXgTC3CANKkykpR5AIcfpjtdsoTdmHY+W0vj5GC8rq5oAGTdKVzgbyoLSmMk52lan8KI/tllr/2Cvv0R7yrn/X2QbNmzgrLPOYvPmzSilUjXXIAhS0aMDDzyQd77znWzZsoWJiYl037vvvptjjjmGbDbLwMAAb3jDG6jVaun3cRxz9tlnU6lUGBgY4B3veMeiSXPVVVcxMDBAu90rMAM4+eSTU8z7hRdeyI9//GNuvPFG3vSmN3HwwQez2267cfzxx/OpT32KD37wg0/6WOeddx4HHnggl19+OevWrSMIAqy1bN68mRe96EUUCgVKpRKnnHLKb6QVveKKK6hUKlx33XXsueee5HI5XvrSl1Kv17nyyitZs2YNfX19nHXWWcRxL6t0zTXXcMghh1AsFhkZGeHUU09lfHw8/f6f//mfWbZs2SLq1ZNOOomjjjoqheB88Ytf5HnPe95O3PonnXQSX/3qV1Nl513Zq171Ko4//ng2bNiAMYZzzjknXRn5bczOj8urXUf3LZNis8Ycqn95uvRuW1Jom3V9AsdjplMVp3Nim+A5u9CDhC3D1ufAGALtQrtNzirCGXmVlJ9CQZQWQaWp2EdpYUyhE+GhaBBjWyEuOmXL8ZTGU8J3XzFRypaTW8CWMxP7zMS+rAooReDFtFsu2rFEVthyHG0wNgkmEFgO7brAB4qDveXxxpycU3M+wbz34yoH33FpRC0aUcLr36wK5rpZFe7pxCHvMr7ktU/JaioqILAGD3nwBtYSWEtLwXbX4la0OCIrn4YK8vJ+xd44K/YWTO3YRvT6g1DKYXl+kI6J0kyfeewu9NI9IMhjjcFOzUCnzYjKYHZMYnZMkjUi+gRS10CnLXUMWlHKtille3POTG9Hr9xbsMizY+gVe6NXyN92dlS+6zTpC4psbU4KxCVxIMzsGHrZnrJtY1ayvZ0mw/jp8X3lQLtNjLDlaNeScyKMURijJBvZrksmu9OUcRi1se0afbj04WJma2RQmFoCJYnaSfFimK5WELahXRe2nFpd2HI6CzKkrt+jcFTCR66UxmyfolRsUSq2aIUuIUnhaq6MGliJ7lsmRa5JYNtlfemLLXOOg+uaBOIhmVVdHsbOjgr8bWBlMmfmpAB6cgtmcos41UOrsK2W4PEntsm83OPQHsyoMSttTcZrl2ElasjLRJBBp+Jw0ayw5XiW9JVRMVlrBIbjZ7A7HpOgY3yL1AhEIvKV1tW067DH/qg9D0bvcai0p11P2GQGF8+dTlP45OtzSZH3tBTtlod7c6XTkvnSqguVbqeZioFVlEd+Qbo1p30qKsBRCjsrha5d8S87Pymwn7AD9bmUEQelUxhON+CMN9+Ds2pfcAPiTXei1+wnsJxktcFMPiZsOe16L0nRquMUfUwjwjQiloVy34gUNGs+7ZaHn8zhsoooq4iijVB7P13OqXsPaDWw7aY4xmEH2nXM+DweNuXzJw7TvicOFxVrdxmfumw5tlbHVJtCXkACy+mqJSfjpLC0k8Jy9MBK1MAK1MBKVN8IenB1SqGbs4Z2zaFdc1EgTr3puYZZqyAMUVmfCN0TlnvK/qztKef+f5F9/OMf55//+Z9ZsWIFo6Oj3HrrrTttU6vVuPbaa9ltt90YSGSkG40GJ5xwAn19fdx66638x3/8B9/73vc488wz0/3OP/98Lr/8ci677DJ+/OMfMz09vYjf/mUvexlxHKfiSyCFx9dddx1/+7d/C4jo03HHHZeKOD3eukWHT+ZYAA8//DBf+tKX+PKXv5zWFrz4xS9menqaH/zgB3z3u99l48aNvPzlL/+NfddoNLj44ov54he/yPXXX89NN93E//k//4dvfvObfPOb3+Tqq6/ms5/97CJGnU6nw/vf/35++ctf8tWvfpVNmzYt4vR/97vfzZo1azj99NMB+PSnP80Pf/hDrr766hSC88Mf/nCXCruHHHIIYRhyyy23/Np2f/rTn+ahhx7itNNO49JLL+WKK67YpertrzOV75NXrizsG4UkY21MIkiTZAutoR2HNMK2sNdki5IxKw4mgjYV2SdXFLrAbJGmCcHzBJbTJ6+6jWjYWNhiEracDLLErR0LrqZtDR1MypbTxqA8h441dKyhRYyXfBYjmehull8nrzhUeNYSRhrfj+m0XTI6ph25tCMXPxCoj5eJhcHFz0rGNmr3IAPZojiHXoDKCGbYJP2glRIRqQSSQybZPo56WbusMHjUTYdZFVO3ISFK/leiFNpWCgcoJ/RzKldJRXlUtiS0fjNjItKTyWHGN6HKQ7RNyGyrnjonKt+PnRuXB3kXlpPN0SBGZTOobAYDtJWsFMybNhTLtGyM0irFumtA5XyUG2CmtgpWV3uYme2Yme0yNrrwoEI/sTUMBmXqYRMbdrBhR/adHUvGQUmy3bkKLSyBjgl0LL8fBLQxtLXCy0ng7DoG1zGL9pUsuWTxVa7CDBEzROhKgRYWnXESJ93rvfysvLwAlSuLoFpeRKy0Y4V9RzvYTkteiZiU4Ngj9HCFdsul3XJxlCWjYqJYY9sN7Nw4pjopznpitjGHypVpaEXBGKIoWRXIlSXzmlBFqnxZhIQSQSeMkWx2d/UngQ8pPyPzK1cRZ7O7EpEtJfOsDPmyFDsD2pUXQBNDS8u8cPsdMpVIis6TV2yV0BpWBqFZk+x8qwGFSm8VIZNLV0BUrpI6pQtrU8jke1S4mXzK7JJC/eIwvYaCX/eT65JJM87EUZItL6L8jLDlaAiRVyNhy2nZGFUp9pxLx+1lox03yU4XMbM70OUhmUdTW9GDK9CDK1ALmHRUroid3IoaWNm7EfpZgZoVE754Pwv5MnG1g3IVylXUtcZxDPMaHE+SBA2tqGkRtfKdGF8bGN/ag2RlSwLHCrKoIDn3bBHdXyBEobtJMsdbsOKXvFda+j2pCQkTthzleajAkyRKHMq86zSx7UYabIbVhOJTkYzVMezsqIzdeXlJobnC8XpCZ102K5W8IoWw5QQ+Cosq/unYcv5Qr79E+x/LlvOU7WzlcplisYjjOIsoOq+77rrU4avX6yxdupTrrrsudTCvvfZams1mquwLUtT5whe+kI985CMsWbKEiy66iHPOOYeTTz4ZEKdyofhXNpvl1FNP5fOf/3wKMbn22mtZsWJFqqj64IMP7qSu+pKXvCTFh++///789Kc/fVLHAnGur776aoaGhgD47ne/y1133cWmTZtYuVJu2ldffTVPe9rTuPXWWzn00EOfsO/CMORTn/pUyn//0pe+lKuvvpodO3ZQKBTYZ599OProo/n+97+fBguvfe1r0/3XrVvHxRdfzGGHHUatVqNQKOA4Dtdccw0HHngg73rXu7jkkkv47Gc/y+rVq9P9Hn30UZYtW7ZTe/L5PJVKhUcffTQVt9qVDQ8P8/73v58zzjiDv/u7v+Ooo456wm1BoFGPXxGh0yHw/V3v8JQ9ZU/ZU/aUPWV/YvtLxcr/oewp5/4vwI4++uhUxXZ6eppPfvKTnHjiidxyyy2sXr2a++67jwMOOCB17AGOOOIIjDE88MADZDIZRkdHOfzww9PvXdflkEMOWQTNef3rX8+hhx7Ktm3bWL58OZ///OfZsGFDmpEHFr0H+OQnP0m9Xufiiy/mhz/84W91rNWrV6eOPcB9993HypUrU8ceYJ999qFSqXDfffdx6KGH8rSnPY3HHnsMgCOPPJJvfetbAORyudSxB1HeXbNmzaIs+JIlSxbBbu644w7OO+887rzzTqanp1OozebNm9lnHxH8WbduHR/72Md44xvfyMtf/nJOO+20ReffbDZ3guR0LZvN0miIYMiJJ57Ij370o/S8f/WrXwECl7ryyivJ5XLcfPPNRFGE6z7xtP7Qhz7E+973vkWfvfv1L+c9b3yFZCznxlNhFDs/KTLyybK/rc9R8vNYa6h4BaE9bDWw9Wlo19JtaNZEHXR+mqz2oN2VPZf/NAIJ8SyYWJFLqDDbzYThJozJKYd+POjUyZGlHxcbxmQT8ad+XKaVwsaGrhxRPFVHU6TPleCl03DJqZhW5FJyWzQaPr4TUwuTDL+SDG6r6hFbJZSECBVhmp1SWv72s1i3ip2doOwXcJQmn1BhmonHsHMTkuF3XNl+AQuHiHl5eCgcpYmVIqMcHNNbOs1aKMTQ3mHJ9y8jeuBn2JntOGsOJHro53KYqa1Q6MNufZB4dpxq2GBNaUmPB79/mdBmjm3EztdQlRLUa8zbMGXViFQHjVBh5pUH1TnyyiWej9g6L/SfRgutqG3NY0c3YVp1Uegdk3ljEsgVo49h4ohAe4z4ZbKOjx3fJCfk+djxLZiED14yuj51IpoJFWnBD6DZomIdtIXmjEc19ihoGS9mdkwgHsb0FGqjSIoMF/Stk4wAM7VlMRXmTALHC9tYP4uL6AjIbkrgHMkxUFqgQzM7kixrHtvuMNuSuTlUrDM/X6QvaGF3bBK2FtdNs6oA1s+g8mUaSgpqTZyw5TSTwHl+Sthk2nXhUy8NynfzUz1eeD2HnRrFNhoijtVqYGe2YTfeA2vlnpKOsYRyskufGCdgf2sUDqrHlBJZgbVbi59gqh1l8a2R9s9OCf56XgoszeQW2a86i53eBjMT2Mo27EO/kjqOLvXnHlpWPmbH0/liZydQfUt6l6crimUMdm4CE4e9udI95/mpVGmWsI2nNKEinddZ7aOUwkNjaw3U/IzQaE7tEN52kDZqLcqz2+7Hzu0Qust7foCZFmXlLhWmndmGs+5goh99CTuzA71mPzlGs4qZ3pEIdWVS2tVoMsYpSL896ln2aARkNYw8o4PtGDbdWEJhqRq5r0Ro7A7JkhN1EsagqUUrDrgBth3SVlk8LJ61ogDdZaLRWhjHZqfkXB0X2y2oXTD27fy4rDIkNJd24jG5lsDE1gLDUSzUnGOPSEG0FliNrc+n/d1coLjc5bb33JhGJ7lPWqDRxExVyai8nMtT9mdvTzn3fwGWz+fZbbfd0r8PPvhgyuUyn/vc5/jABz6AtXYnp7trT/T5ruzpT386BxxwAFdddRXHH388d999N//93/+dfr/77rtz//33L9pn6dKlAPT39/9Wx+qe10J7ovNY+Pk3v/nNtPg2m+3dLL2uMEhiSqldftZ14Ov1Os973vN43vOexzXXXMPQ0BCbN2/m+OOPp9PpLNrvhz/8IY7j8Oijj+7kfA8ODjIzM7NTm0ECsW7w8n//7/9N8fcL2/Wxj32Mhx56iFtvvZVjjjmGD37wg/zTP/3TLo8HcM4553D22Wcv+szc8Gns6COo8pA4HJvvR/UtEez49od7CpvDq6h4+V5/VmewD90LS0ZgUFYfVGkQOy/83MzN4CsHG4aUjKI1IQ+RgvKIEk/fy8QEVtExDo2GPJRsqy40iYBphin3sm3F4qAhvPb9NsTUQoKkIFUHLs6CFdhO28XXMR3joB3LbCvDkkqNbbPCXb5bUYp4w9ChFTuCN9ayDG5biQpjwlZhJ0eFnaPdpuBmCLSHl7jmdmYHjG7GDjTEKbAmxQ/LSRgC5VGymnJC6eeiaaledqqtwNPgBJbo9m/jPO3ZmC33yfv9j5bDPHoXdsv9qJV7YXc8ygHFNWzrzKQ6BPFt38I58Fjih38hvNRbx9Cex4AKMNPC4V8wAQ2tqWmk/a0mORxMS4qaASZxUfmgh8ee2SFOR0b6zc5PQXVW+mNiO8uDPjomos/J9QShpkYhV5Btuw5YnKGCx0Ti1PnKwdbqREqTMwY/geXkiwmP/vykBIrGiMNSn09YiTJkun3fbOLhY6PEmU8EltBaYCYg17UySEl52KZQYXbaTk+/wcYo5cjvJI4+xmDG56laCXjWVtpM1/pY7ppFCqwLFXS74xIgRlFr+NjxzWm/KVf6VPUtQQ+sFFXabEEgIo/eJzuOrEKt3Atz5+3Y2XGZX7vthVq7D3ZqtPebcSRc6V31XhSdRsKz3nKF5hQY05a4YYjbmn4TESRc7CtH5mi3XOwDv5LrODMjfTY5gdpzXznmlkclGBndDpUB9EGL1djt+JY0wEnnS9TBLuyTqCP3A8dNFHcXzJWuUxl1sP5kuk8RF2VhLmE0CrRQYYbWCAXk+A5UdQ47O49K7uV2bg7VqGPaLdTSddj5SaJbv4Fz0PGYjbdLt937Y/Sa/bCTW4l+9CXcI08huvM7qYKy3bYRihU5r2JFClPjiLCuidvSljWh4jGbo+3AxK2ij/H09WNo1zL2mBS3R7HGOeFVmEdul3PSGho1mE10F+IIChXCLVU6qkzRGDysXN/u+HVcoc2szqNaTRG3ypcoWE28Q4JSUwtxTbx4LHp+j8M+6T8HJChOAg2aTSmqRZiistYwP5khDB1hE4scqm2frCvHzS0IiuM/IRXmUzz3v5895dz/BZpSCq116izus88+XHnlldTr9dRh/slPfoLWmj322INyuczSpUu5+eabU9hHFEXcdtttHHTQQYuOffrpp3PhhReybds2jj322EVZ9Fe+8pW85z3v4Y477nhC3P2TPdaubJ999mHz5s1s2bIl3fbee+9lbm6OvffeG2ARJOb3sfvvv5/JyUk+/OEPp7/1i1/8Yqft/v3f/53/+q//4qabbuLlL38573//+xdlzp/+9Kdz77337rTfxo0babVaaT8tX758p21+9atf8d73vpdrrrmGffbZh09/+tOccsopvPjFL2b//fffZbuDICAIgkWfNUsVeZMrorSHzRVShwTP7ykShm3aJiS2htDECU1fTnDBXTGZOIRcQR5SA0vSlZ2mBr8sD4VouyGyNlWojRS0raZY7MGFIiw7SMR/IH0fJTf8CToM5tvpQ8ezoIpZPAvbYgna9qKNsQqFxcQKV5n0eACOZwlbDqXBFhNVofXEcSGvew9Mx03EilryvesT2RgMVE2i8pgvY7M5yCe0hp6IJqUPQT9LjKGmLJG1ONbSIsYocLvFrV3YbUEJTd/YRvTaA4nv/RFmmwTEev1BxL+8ATu9HTWwjBjDjtZMTyzLz2C23oez5+GYn/1QMLK5HD4K2kl2l4DAwkAMs6oN+SITto23zGNwmzgFY5MZdCmfOrnkS+JYd7Pi2YI43VEE+RKRjdFKUTW9bGz6f7Yg+HDHgyBDBsVyJINZM21wK9SI2Oa5eHnDSK5B2BEHVGXy2LCTsJaIc4ifkVWU7kBxHEIsGGTFyXmcMBUIY09G8MpojSZGKyviWCBUgt19MrmUV18Pl+hLVhHmprIMmJBmy+sdFxJmKD/9PZXJU0xWZAIvlvZ2VVQzecmwdqkE/YzUp2RK2GIlPWea1eTaFSGXE2w9pBlZMrkeNWt3VWOBZUsdqEng2GcVbsXFRhEhijBJckxMFKhGHisLQoWp8jkRPvODdNXJ6qSupiB1A7ZVl7HddcozObk/5BKxLqXBKcl16vaR0tBOHHmdKL5mc+lckh8yvfuHG1AnIrAeAYsTNRaLKuZFxMnzoZAX9hxAFYuQycrn7Tp6cCWm3cA8dhfOblLTFN39fVmZHFmPndlBdOd3cA98HvGmO3r967iQK0idR9LfblZ0AqQNsM6tcavOSTcYuHPjEjRw2DMl+LIRmDu+B0PLpC+UTthpvLTfVCaPOxiQM6YHP0muKyDtiDqoIEgYnWQfjahyA+iMkSx8JKtHtlGVPk7GQzYX0m4+bqxakyo4g6iSuxgyuRA/jpmZzcrcQKVZfMcCWqFH+il49d6z4Y9sf6lY+T+UPeXc/wVYu91mbEyUI2dmZrj00kup1Wq88IUvBOC0007jve99L695zWs477zzmJiY4KyzzuLVr341S5bIEuub3/xmPvzhD7P77ruz9957c8EFFzA7O7vTb5122mm8/e1v53Of+xxXXXXVou/e+ta38o1vfINjjjmG8847jyOPPJK+vj4efPBBvvWtb+E4zpM+1q7s2GOPZf/99+e0007joosuIooi/v7v/56/+qu/2mXR6u9jq1atwvd9LrnkEs444wzuuece3v/+9y/aZuvWrfzd3/0dH/nIR3j2s5/NFVdcwfOf/3xOPPFEnvnMZwJw/PHHc+WVV+50/B/96EesW7duEVRooUVRxGte8xpe8pKX8NKXvhSQYuKXvexlbNiwgVtuueXXwnMWmrP2QHnjBdhOE732QKHC7LTQ6waxXacubLOlJgxLgeuhl+6BsQZV6il60s1qegE0qtRMB1UqEjKD6gp52phMAq9p112qyqABPyvOsi5nadmYgnJx+qQgNI+DLgc0E4csrxw2NYqsHhCnueEobDukqmFdsk3f8jr331dhfbZKs+mzfOkcD24bYHUgTuzE1gLl/iZxqMi5Ic4ez5AGJsqUqZkYO7Q6UdBs82j1k7jaQSeOkrPuIEz/spRtBZBgIHlQK6WZj1vgQM2GOGTQKEpxz6mfcUXISrlKnBHHhajdew/QqgtDTZAHrflVdQtRHKMHEkiDL5zjtjaNymQgm4F8gSYG1S9ZxabuUu9BVnnCYZ44UfWaODMtpTCTc3j7PwcbR0JRGIe9YMULsMvrKa/7PfPSH5GJcfc6Qs6/u3LhBalSLH6W6gIkrUahBvrwmKQvhk5VU235tDpyvnrpHjDYliLvZDx22W92Wp9L+s12gzJrUjiG7l8OcUjdRqigCDQJ8hHO8FrZtLuP1piNtwuNpxegXIfhPlnxGJ0u4ilDFGvcvY6Q83NcaVOiEKzKw9jaNK6Fee2wR7mVXD8vbZPN96P8DLYxJ2JkbgBRG60l+dBVRFbLluOs3JdYacnyTz6Gs8dhC8akSWlWURoHS35J9zzAbreUY9BYTCsmbip2uC6Jj0q5E9BQGrXXARJ4aRHzSscRoJ/+bCk41Voc4vt+ii30Avl0vpgFvPTdud/9zBoJ0EDOszKCSYpbF51Ldx/HS0dIMXkzFzcp6YA8LiqXlXYV+jHT21IhJmozqMqI/K1FnKyrPGtqsjLq7PnM9FroNfthG7PEm+7AWSsJFNO/PO0DG0dyDCCzZ55MItea2WSpVJrsPV2k0xbRvWnHxcFyx80Ck4pRHPkacHY7VFiCXF+KV5fJMXRlRILMSp4sMVPao6kVzu7PSCGQaAfbrGK23IseWS8JFu0wq76CHk4gUPUmzm6HYGozEvDOT4pIVShJkvLKFlOzyT1q36Ok2NZxE0GxbsAYEKPIFCOitiaaTlZXvQ6tREl6OjCQy0KtwWSYEbrNp+zP3p5y7v8C7Prrr0/hL8Vikb322ov/+I//SItTc7kc3/72t3nzm9/MoYceSi6X4+STT+aCCy5Ij/G2t72N0dFRNmzYgNaa1772tbzkJS9hbm5u0W+VSiVOPvlkvvGNb+ykXpvJZLjhhhu46KKL+PznP88555yDMYa1a9dy4okn8ta3vvVJH2tXppTiq1/9KmeddRZHHXUUWmtOOOGE34s//4lsaGiIK664gnPPPZeLL76Ygw46iI997GOpsqy1lg0bNnDYYYelrEPHHXccZ555Jq961au48847KRQKvOpVr+Kd73wnDzzwAHvuuWd6/C984Qu8/vWvf8Lf/+AHP8i2bdsWFTUDXHLJJTztaU/7jfCchZY6Yp0mZnwTemAlVjcxOzahB1f2lv7nxsm6gn8dzlREKTPsJFhSycaaCcFly8NmSqgwwxCNwibP+KxyKeCQMdBqeARW0ecvoFeLYgKlqeBiOxE+AX24EBn85IFbwaWRvPcQ0at4qgFUyKmEdaUAda0JMiHz1QxBIaKqHFbn5eE3MVOgGLdQRuG7ce9BPDvW4+juPpgTUSQ7O0bgeoK5dxNe7sZcooQqzDULJeBBsn1dzL2vHHI2pqhcyvECUSmrhOd+XmAfdmZ7Im40KOrBXcsWsdPbUIV+PO2Qy5QwU1vTr830tkQhuIUKfGg28NFp0BEmqxeBgX4vgOo8OSU891Gc9Ke1mHpH2EM23wP9y1GFPsxWWWFSfctRvggE6cGVtKKQlYUK82Fd+iK5/mbsYVFfTehA6TTxFmQEy04GopiS1QTWEnU0sVXoBBdua9M9qXs3kONYAyYm14Xl1FsE5LAtk14H6YhYKBe74ztsk0lgQKDRrk37rYtZB7DToxhXVGpxBM4FEFpNzhHub1ObETpKx0vOLdnfcbGNOcFPI+rLEgQk6qqzo6lIldn2gARqbgc7+VjqUBO2sZsfgCjEVAWnbRtz2AfvxBYHe33RxVqD1B1og+omwhMqzJKJcawVESYj9I3dXGhDaZpaybgNO5JZDttyTlVxhlWuKPU0WkN9DnP3L1F9FUjgjLZ/uZzz3HjKqmNnx1KdDJC6CdUNOmfHMG4gv9msSmCDUPGqvDivxCE+mqyxKTQvqzwyOAJpi+NUyVUpp7ea1M14W4MZ2ySZ9ziSACDpf7V8T8yOjdLXzarAcDwf0y+roro8TLzpDmEKsgbTacq+xqIK0taSiXGDmKEoZq6eEVpMDVhFNUlYGMA89DD6aZNC3+r6AmHs1i65ycqeq8noGJGwE7alNCjSTkKtWxOl20TgymMxLMZMb8fOjWMzeezMmMyKZA5oXzjuFVL7kFJrLqDZ7AqgeXmDdkXoz9GLYTcKoN3BzNSIqYhw25/A/lL56f9Q9pRz/7/M3vKWt/CWt7wl/fuKK67giiuu+I377bffftx4441P+L3rulx00UVcdNFFv/FYo6OjnHbaaTvBP0BgIe985zt55zvf+RuP8+uOdd5553HeeefttP2qVav42te+9qSO3bUNGzYsorB8ouM/vh9f+cpX8spXvnLRZwtvSN/73vd2+q0LLrhgUdDU19fHmWeeyQUXXMBnPvMZAO655x7uvPNOvvSlLz1hm//pn/5pl857f38/o6Oju9jjic3Wk8yqG0j2sTopmcvKsMiwdx+gQYbA8VBKMd6a7fHZQy9LnStix7dgE2e9qHxsvUnOQtRMHFkcfLRQVjoiuLMlzDPiSZGXaYbkcKgTY5P3NUz6OUAdQ5+xmGobzwoXsy54BBa2Kxkre0aSuQSIjUY5Czilu+duFG4mphM5Etw059GVEXnQQvq3mR0TqsO+ZWQdH1e71MIEZxxHIlAUFLCmii4NY0Yf6v1IJk9BB5SMoqQFqe+hMUrhd2FLSrHVM7j9jogYjayXYszJrSLSA9j6DHZ8M3r9Qdi5cSp+gVrUC4rM5BYpsmxWod3Bzs2D5zFoHcw2WXEpmH4s0NQKD4VtNFJ8dj4v0ZeezWM7RqBBq/bFTm/HjE2jV0hBp53ejpkdxVm1L2ZmO0tyfWyujTOcLfecurGH0Uv3EPq9pHBVeQEDVgTDAIKEs7vrSlijKPgh020pYrXtegolsLKBOCb1OSoJD7eptgksxDWb4N97GeMUvxy2sY1ZirjYZgtFhrDZWyVUbkBXjdkqLQFVHBJvmaQ4IseYnvTIExGZHpc/iONjxh5Oxn4Zs2MTQybkMdfHz8VyDt3fqSwVR971UZUhcXB1HVUZwWxPxovjQrkfOzsjK0b1OaHT3G3/Xo1AW/ax09uk3YmDFieyJE4BClYwIx6WcBZa8x6uBS8Z/qn7NjspwlXTO1BDy7GzE71C1+oMqgv38LPo9ethYKQHoQnbsppUGcHWZrAmRFVGoFXHNGUu68qIFAabWL4DmSvZUto3qjIiReFWqHf7cAmsJUyCvIIbUFYePgozPYebBEK2We3V43SaEkC0qsJVPzOGmdoiiYpWcl8Z3yTfzU1gpncIrt5x02x9N4sfb7sfGnOiF9Guo4pZzKQEig4ZgmJEWyl8J8ZYxZyGjIGliQaKAfSyFT2NBaWFBjTpN2tjaDUx0zU8nev56gvx89aIA660qAAbg42a5K3GJvozttYWKFp1MoFEuTKGqzLf3EEfRQJZHFyBaiVFt82qECUgCZucimlOu4QtR5S6AaXAJv2ftxpbr6PyGSKlBKL3J7Cn2HJ+P3vKuX/K/mA2PT3Nd77zHW688UYuvfTSP5tj/bnbu9/9bj7xiU8QxzGO47B9+3auuuoqyuXyn+T3VV+C57dGsov9y8WxmB2TZfkke2qrkzSSjE/JF95yBlekWTKQhwX5kjx06nNUbQeVDWiqJl5RHhxVIoq4xDhYIwqIffSypzrr0cRQxEHlAxrElHHRWU9URpGiuzntoPM+oYKWAiJDpGDA9I7lWogjTeBFmFDjWps+tFTClmNiydyrXFmyXAlfOSRZr/qcnKPS2FaVZtyBuEPWEUdW+RnIVcQJM5KtVd0sa2LzcYtZzzBvQ0IyhMRYoAto0MCQ0diOkQCrm5l1g/RhrYKCKOBOPIYaWMlcWKcdhyl2OXXsHVd4qfsqqGyWOWXQfVJA1+XW10DbGlSxSMwYNrIp1j1KAiBV6BcHf2Q91GYwCROOHl4Lcy5m9CH0ir1pRC2W5QcYrU+n40AVB8W56l+O6jTFcQvy1FTvkS285SU00zhWeLarHR8/WXnpait04RpEbXH2lWZCyzbOQJ6mAqeU6A10V5msgSBhocrkUVoza0NUqYAmwg3itN9sNwvcaUpBYrsOro8zUqFxh2QpSybG8QwdI44aTRFTslFbsqwkzmaxnwntUY4NnYaDXjAObG0G1SeF53Zic8qxbquT6KHVSVtq2PlpVE4w1mpwhQQND96abq+yxZ5gVIJvN1bhJFBo24FZFROjCVF4FVmd6EySzjKNsKCo4ZXYdlMUXzst1MAyyRhDgqevQLslbZidQVmLzSSwnaW79847UXIW4ao+FLKqIMJv8p2tTct55irCAZ8EJTSr6UoZwCQhTR2QyD5QjdvMKh9HBcJzH3aE+9/PQFIfoOanZLx4gdSklIdRYVPmTgIBEp777bKyUBmSwtlcjw1NFQdFFXr5Xr1gK1fGVpvoftmuhSZsOARW1IoxkDPiQE/rnjtlp6blHqK0QI7iMK2NULmKQO6Gy7Rig07OU/nZFCKmkpod6/agUsrPUlMGlU0SXcb2CtghFXHrKv1G0x0SjT7szBg2bCYCYM0ec4+foW5dvGwsAoKIGvPC7H09+U1ba0iQXVpMfvHHsqcKan8/e8q5f8r+YHbQQQcxMzPDRz7ykUUQk//Xx/pzt3K5zLnnnpv+/bznPe9P24BkuVhl8vLgjUN58Bb6E/x5cpvIFjHW4nSz9I6LmRlDDa2WYkEAO4B2l8mDLDPJeDiPGhykoTZjk6TUxnCWrPbZXQ/gBxG5thS9xmE3++8zazto5aMCj3kb4ikFGY/pLrZHATionE8LiwFUPiBnYDArwcjsYxlWqibb54vstW6CzY/0sWdxlgdnKwAcvG4MaxVxqGiHbpL98+T/brGf48lD0RjJ8CYrFTqhtQREQGZ2DNW/TLZv1wUn2/0+jpiKajS8IbZG88zpPJuiacbc4RTv7lhoaMHc4/niyELyfgH+P1+WNjSrOMrB1b2CShV1hBpQO+hVK6XAsDLIr+Jfovc4AIAZZysFAxMO3NeZgJV/zYS5G11wU1iOthZnKC9OdX0OO71d+iM5dzsjMCHbrEpWFsg5AcO5Sg/ipTU05rCOh7N0d3FatOYeM89zO+KFPsRmlL8nO1REn+fhBgZXmTSzr5zkmiQrR7Y2jcqW0Mv34lEr11ivXsa4msVbWRJ4SUqFuSALGgrWe8KIExuyQ1BK3X5bQJ9JJoetz6IHVqKfdQQb/+9PAVjTP8tD032sL0vfi6iU16PqBKzj4izbkwd92LujhG4z6kjQASlGXgV5bGlAYDCZPHjZHkwiV4GBpdiZyYTOc6wHOelClJJ+0f3LUEpjrRFRqiShamPFDCEb/Syx0hxRcnEbEZXYUnNkvK1wG9RCL6VotJ2WOHyZXIqHt+NbYKknq1jNstRxLKiLSudLKFlztCPvO5keFKnT7NVHRJ3eXKmMpP1v2/UUh04cUbcRY26GWpJFnmxWMVimtI8qDWFndkh/NWq9eolI7gtqZL1816wKO5Gf6d2/urUPYVtYl4oVuRYLsuU05jDbH0Iv2z3Frtt2hE2ofh/z86waz3N3xmG3bEjYcSi0LNrCSiXXp2McCMpS6AppDY+dFBiYcgP0wArMVJWHnQHWRm2q1pXtk5UnG4cyfsOOBMkj61HFQR6zTfTqdbLNfDVZ7ZBCfgp9EHbQS9YAMPtwwEAkIla2MSt9lIhideuonKFVPOy7HLZSY2oxzhZxqduhK/cWoIOVoMoaMtb8yQpqn7Lfz55y7p+yP5g9+uijf5bHesqepBmBJqQYYj+7qFhOLSgy7ZjwcawhiUPmJuwORjKjccLOsJD5wFF6UVbGAlXrppkj24kJ8AUuEsf4uEKB2YkIEIfAQZEzBtuJUUAGhcr6+BaB2AAFJ8GQYohDwXrHsSb5mdSxt0ZhrEozsMrPpu+752QXOttIfUfYZVt5XD90C87SQmStMV0cNpI1fzwTRKhgXhlURigauzhlok6aicNxoVaTQMpxhTPfmDSIMF2lUIAwhJwU3ma1h02EyxzbK6iVE9Hp8rfTzdwpBVHiHOeSIuGo0wvgABs2UyfQ046sZnTbCOIodlc74kgcdWvIKRe7sBxW61Q1VWnhX++urMj3ToJzEE71bu3Agh7v9aTWvbV8TY/V5XFmkFWbNPjqbucIrrlbYErUIe+I4xd1HBRWVGcT+EN6/MTpVlr2y1pFjMUNFgQNIPt0nXg3SM4tCc7CBSw/3WBA616wkissGmfKDdL2KyW1CgsttFZUmgHlO+hMtKjPtLKSMU5WQpIT2GV/pXSOubywH3VZe7rzZUGBpfKSuZO0e1HxpZ9dzKbUvbd0A+lukTAJi1RySrE1Kf4+3Vct6JvuviCZ63TcyXxI2xCH0j7Hk7Ht+rI60Z0/nWYKceqqUqcOfsLKFViwll3mlNMphYUgSBmC0n7tzo3u38kxtUq45FX3iiV9291X6V1fG2N759KdH11VW4RmOLUuo1L32nT7RGthw4lsmnx5vHkoCCNsFAN60XPgj2lPseX8fvYEs/kpeyKz1vKGN7yB/v5+lFLceeedf7Tf2rBhw5MqJH3K/ufaZZddtihT//a3v503velNf9pGOF5P7rzLFKN17333ZQzWWmJjJGvdxXmmculegouOkuK4SDLTRh7OygXlynKrWvCwbipLjjiRQLeofECMIcai8hliLFHyPkrex1iaWgsfOzCnDISR0Es6BtcxmFiWl2M0jmdludkxREoRKYVSvdUC343Th7GNw/SB2l0eV9pL6S2ttanDoVHiHCzogy7FolIJa8fCArjkgdV1VjS9m3DB6uSB7UobEmfWxmGvTdpJxbJiazBdajudPHTjBU/oMEy365qLyMkHdueHp6OlMFN360Z0soTfpfYM26nTo7SscCgvS2wNvnaJzILfTth+0uxs1EmdKE8ZPGUkwDMGsyDUi5KCPkebnqPieL0+TpzDbkAAC5yqrjMFi52hrqPU/ZMET6z1os/Tc16wf9s4tI2D4xksCtdNfjXhmmfBWLE2xsYyBh0QXH86Px4/t6Le/EkCwjQwjiMBPSst+HztSf1Ad85pp0fjqSVz76jF19JLoFfaSrBsOr0+M0gNirEIdElrcdi1/N6iNicvaUMoQV7YSdvTnR84nvSBCRfdF6yNF51/eh2T65reM7rXIhkPZqEv34WJocQT7l7nx7fTTeZg2EElFLY9x1cvdoS71KoLTHWhX93gKuyN38VDpCeEtuhzZeUFvYAoPU93wfVLxljGwwEiK/ej1EHvBrHdMZx+LnVK1tg02FjEVNQ1K3UqcSgsSo5N2tMdr0ZqV7rvF2Z4u6NILRhPDQw4Dsrz/qQ4eGvtH+z1l2jK/qWe+e9o3/rWt3jRi17ETTfdxLp163j729/Otddem37f39/PoYceykc/+tEn5Bp/srZhwwZmZ2f56le/+qT36XQ6fPzjH+cLX/gCDzzwAK7rsmbNGl74whfy93//9yxbtuz3atP/RluzZk2qWtu15cuXs3Xr1ifY4w9j7XabdevW8cUvfpEjjzwSgPHxcdavX89dd93F2rVrf6s2L7RHH330SXP6z7/uOABsx4CrUK7G1EKUq1EZB1PrYdgv+ekyLILDfPdzJ7GRQfkO0WQ3I6kwLYuT06iM5ivfW8oJ67fy4INDVDKC83ykVSRjDSUdknEjNod5+glZNTILCMvIL7Yuoak1Ry4b5Rdbl9DQmqOS9wBNranEMfuvGufOLcPEKNYENR7uFMklD7xnHTvOlT9axql7buF7v1rBXx83xuXfX8qr9xYFzm/fvZJ93CqlUotG3WfNCy1ohe4vYSZ7LFC6v5j+rct5PnStRwfLHOIcnP+yKGHxiLBhjDNYIto+g0rAtCpw+bevD7BbGDLuuByYn+GuWh/rdINiwtzz0HyZ7a7DC1ZuJ7fCoHMOptFdDUnYYzrCfOKtLWHrbT79nWEcC687XCgfrZHvAZpjDl4iCvXLe0bYc6Xg9u/dMsSSoIlSlkfaBY46YBv/fc9K/nr3rcztEKdm63SJ5X1Vlp3g4iwdJB6dBGPRSwRrayZmIIpxVo8QbxnnfV8vMkdEHy7v/Zsk+z85hx7px4zPCPOOsShX84NvDPLM/QTK8417V/KC/bfwszuWUSHEUZaBciOFTR114gRKK6yx6EAUik0rFlXQm6UmQmvLdCtDyeuw1yuswEa0ZBrjCYFSOMsqmOka3/r6IM9YMs7ERIFsELLiGUlBp6vlN3IuzYfb+P0KNNQedSjtK31/9fdGeI43y3Qjy8FnuKhsRoSFAPOYKOHqZQNEG8fY9uMMP2v38ddrtlHYN8DGSRY7H2DmmtiW6CToig+RQXkO8ZyMg2jWYBO/P9g9j6m202vqlLvZVoUu59MxpjyH7TcpBtdLgbc77HHXtyos6atR6Guz8ZEBWtbhAb+Xce2u3Pzt4dtwlxeJJ+rogRxmpkHrMRk3mbUu8WyIv8cA0eYZao8osoMxTkGcTmdIMvG6UsDM16UtAxUZH+nckbmkXI1eMoCZmE6w4iFdsLku54knBVOksj4/+kKeEb9JmCgZ3+HkGIgsOWN4xkHbCdYL173K+phx2U8PFiW4n2uiihlstUU03UG5Ku0/nXNwij5xtUM0GRPWNW7WkNkzydYbiypmsdUmtt1z/LMf+QzNc84AYPRHDstflGXb15r8alYoKX+QMWRQ7N/prfbt58+x9q8jTLWD8jWmFqFLXnr9bCemtSki7ih+tEmeyc9/VQPlJ1ScUQxaEW+f5f9n78zj7CrKvP+tOstd+t6+vaXTnZ2EBBKWsIqArLILjoqAyqoC6gwoCi4MIgiooIKIjDIiBFAGURTUiCCCKLITQLYQtiydpDu9d9/9LFXvH3XOud0kCIzgjPPm6U99+tyz1nrOU0/9nt9jz2hDV+toL+D2X7Ry4DvMd0l5kJqfx19dRKYlYUnhzs4meZeFDNf9vJmMhg99Shr2rDAEy0JXqsk4fe4Wl9lbDqMCwcpX2hFCk3V9ynWzotIrUuwytR83G/DCyx1sNX+Q7r/8kbdb3j3jrYOn3r3292/Zvf5ZZLPl/k3Kyy+/THd3N3vssQddXV3Yts0hhxxCb28vvb293H333di2zeGHH/4Pz1u9XufAAw/k61//OieddBJ//vOfWbZsGd/85jcZGhr6uygh46iu/1flggsuSNqwt7eXJ554YpPnvZX18Itf/IJcLpco9gCdnZ0cdNBBXHXVVX/z2kcffXRSfnt7e1m+fDnTpk3jiCOOYNasWW84H8KxTMraBP0+wrGQWZtgODCKRM5B5hxUReEL8IRmRhgHGrIRKRuZtZBZi7Ckka5RjsLxgDAytI1h0zqlQuuUimFwQCdQAkdrmlN16jWbes2mVjaMMu1hQK1sPogd0baFsYpOCQNKUuJVbdIRFnS8nmLMEqRRpFFYhRRVATJa9Re2pC7AygmsnKBoGSt/ueRS941SKDIuav2QmdjY0vzuM4GiRNoh7DdKvo9mKi5TcQ3utSkNtoVsShEOjhvF3pZgS7Qf4gkYkTYVKShXXVJam2iQnoXnWTTpkC38wMCHcjaqEiKk2dZBTGeoEa4g3FBCZIyvgTfBeGhFyoOKfOWkC37FmgSDaRIBJc9hoJahA5/Qg6zSuO1QKqUolVLYQhsLflOacGUvsqOAzGdQ6wZQ6waQbc2ITIrgpXXIqW34aKZrlxECtO+bYEj5jGHYaWtOJjmxDLySY+CVHBKwsoIQwaxpo6TtgGIpRRs+bfiJ0g0YBVmKZKKjtIFSKSVwhFmpAYzyEih0oCK8g4CIozx2FFZa4KaCxIwdTxjiSawOtJlUaAj6fYJ+n2YFjhtS0ha6WkdtGEIPj6N6h5Jy6XIVpGConGG6H1AediHqQyLjEm4oIVM2Im3hDSqEJREpG39DFZm1TUpDfdwyMSGURqRtrLxLZaVOyiNcm7DfKMwAKlLmnC4Xp8slGPSNk6QbokLDQJS3fHxBkhxtkszZqGINkbbQVQ+RtpGORjoae0YbdpsLSmMVUpTHUpR6HcprBOU1wijYKQfVP2oU+0wqYWWKy6z6hk2+Uw7hyl5TpqZ0Ug7h2ma8CDNJoeYzZllUfQfHCnGskADD7uRGduNE8Q4UVlcLVlcLhCEil0WkbNRIJXqHWdHYMfSgMmsTFo3Cb+UE0tYmOFWgzCQr66IGiyZ/NCzk1bM/SeYbV5H5xlVoJSg/MkTnNlUcNCmtWRjabBlYLHMDlrkBz7mKbNZLYDfxfXTcLyNxWqOJuBQRLWmIrnvoumf6cd0HhVHsAwVK42iNP45JRYku16PyaZQH2g+T56mxKjVh4meogRFU3wBqw5BJ/SOofjNJD7Ug9CWhLxFCYwmNJXWyypNRCq2hNJLCR2Kl/jH2e4V+y9L/j7LZcv8m5KSTTpoUcGj27Nnsu+++G1nX77vvPvbee2/6+/uZMmUKAE8//TSf+cxnePDBByfxyOdyxgs/DEM+//nPc+2112JZFh//+MfZsGEDY2Nj3Hbbbdxwww189rOfZf369ZNoIY888kiampq44YYbuPjiiznnnHN47LHHNhkBVmuNEOIN3ev888/ntttu49Of/jQXXXQRq1atIgxDenp6OP3007n77rsn8cjHwa42Jddddx1nnHEGP/nJTzjzzDPp6enhsMMO4/rrr+eWW27hvPPOY2xsjOOOO47LL788CWbleR5f/vKXufHGGxkdHWXbbbflkksuSfj5h4aGOO2007jvvvsYHh5m3rx5/Pu///skesp9992X7bffnnQ6zY9+9CNc1+WTn/zkJJrLOXPmbEQhGosQgh/84Af87ne/4w9/+ANnnXUWX/3qV/nNb37D+eefz7PPPsu0adM48cQTOeecc5LAUS+++CIf//jHeeSRR5g7dy7f/e53Oeigg7j11lsTqNV73/tettpqK771rW9Neub111/Pueeey5o1a16zTl8tSikOO+ww1qxZw0MPPURzc/Mbvvbn3ccChkUlEJBTmpoQ+NF2PQ7WhGaPrg1ISyNtzR9XT6OgQkIE45ZRNHxhcN1FCVkN/7JdD398cgaLW4ZYPWysre88qoiu+vQ9YNEzXMBC0ZmrJA6dK+rN7L/LWoIS3Pv8DA7YaS1+UfCXF6ezf2S1CkowuCrHc5UW3jmrl/JYisfG21lkF9lQN7jzPY8a58KlBb7ygTLn/7KJc/cb4Lv3TOWMg4wCctnvp7ClL9hC1cin66yu5bC0xo7qAgyswcHUQbw9b8oIYSgSbPhLIy3kRUBR2yhhJiuDlp1YR9Nac+B2a/GKktxCG2+9h90i8foVfsX09f51eQqFKv1DOR62s0z3TRsM2TDN10n7VCVM80N8Idh96/WEnuB3awzbUVXAlEDjR9c1Ryv2H7qgi0suMPSoJ7b007OhhdnTRmh7V5rrbm3hvVP6THCvtoj+M5T0jOVNYDERUtU2Ak0qYrqpaAsXRUooKtpieq5EEEocJ2T9uMHhhwhcQipYvOLaZAyxCMd+sZn1P3gZgKl7C5bdmmfbnfoZXZ1mdDxD2g2SfvCs3+jDEo2jTf/qswWnHGssj9+4KcUZ89fx0+dnMteLVjoi4JcVfdQVMGjbvGenHq7760z2DCq0Nlf5S6k9OQ6QURE7EibY16AFnz7V5OXcqz3O2aaXJU/PZMe6nzD6AFS1GfMuIc+5KU44apzHbkyxxfQRlq3vTGIZxFKWglBAITT9SgOp6DNckgJPwBZ+wJi0SGtFXUhCIBvBqxQCRyuGLZuqNEr6LqlRshGVKUBhTp3Mu+aiBob540+yWFozYtnkotWGdY4ko6AtVEwRdYa0S7vwGNIuQ9H7d1bgMSAd5lllVoVNFKXA0ST1mlMKGf0OMU7xDpqakFhReWzAj9rCQVNDkhcBY9iJ74uDZkRaScTmvbdaR3qmRTjesJ6781vQpTr339pCs/SpKpuCU2fEN9+vFtujGtqsky7NoaIiJStdwWxPU48mlyUJ03xFWUpWOZo5vqn7dJTXZhViRXlc7Vqkovy9KzeUQHDmPXAl1bM/idXVwlk/hjZs9qoqXBS1yFaaJaTXcrG1UdzjcsZ17wvBqCXYKzvMzGNy3HaNS04pbK0NXh8i4KJ5F6VFyBg2NSHZd9u1/OFZE7QuDoDXawtcDTUJczxFr2PyccI57fzswiFaQkUbPrYwjteOVNQi48w6K8V79lnHsns6sTDwLktoXCtM3m9Tu8e5fUM3WQUzAo+ysDii7ybebtl3xgFv2b3uXbsxLfX/ddnsUPsm5Lvf/S7z5s3jhz/8IY8++iiWZfH5z39+0jmlUokbb7yRLbfckvZ28/GoVCoccsghvPOd7+TRRx+lv7+fk08+mdNOOy3hTr/00ku59tprueaaa1i0aBGXXnopt956K/vvvz8ARx11FJ/+9Kf59a9/zVFHHQXA4OAgS5cu5Y477gBM4KMDDzxwk4o9GEX1jd4L4KWXXuJnP/sZv/jFLxKF+33vex9NTU386U9/SiLAHnPMMdx7771/s+4qlQpXXHEFP/3pTykWi3zgAx/gAx/4AC0tLdx+++288sorHHnkkbzrXe/imGOOAeCjH/0oq1at4qc//SnTpk3j1ltv5ZBDDuHpp59m/vz51Go1dt55Z774xS/S3NzMb3/7W44//njmzp3Lbrvtljz7+uuv53Of+xwPP/wwDz74ICeddBJ77rknBx544N9u8EjOO+88vvGNb/Cd73wHy7K48847Oe6447jiiivYa6+9ePnllzn11FOTc5VSfOADH6Cjo4OHHnqI8fHxTU4c7rvvPo499tiN9r/jHe+gp6eH1atXv2FozZe+9CUefvhhHnnkkTel2APs0tkPQLXkEoSS5pYapfEUfmBRaKtSqxiLcLnm8tT6KVjafMB3aR4m314jqEtGhgyDgh9YeKGFS0gm5TO+NsV0alQqLq2OgR4UH68ibY1XT2GhqGGhtDDWLqCrVmfk5TRrh5qZJuoMvZJh7XAz3aLO8IvGqrZ+uBkLzVTq1IoO/aNNdGuPsdBlMHZcU5o0EjVWpV03Y7VmqQqdwAFSCKaGPt2d44yPp9lpiw2oQJBuCfBKpr+HviBdCAiqEhUKUs0h9z09HSUEYxHzyKHz1mG5Gr8q8WsW2Vaf/tWNCJyptM/gyiYcN6T+mCLbKhhf65Ap+KjA3CMIJc8OtLNlfoz9fB/PssimfEIlqURsOflMHS+wyOY9bFvx1+VduITslDIMNbalGPVTtGerDJUzSeCl8i2PsmPdTABGhrO0pGvkun1Kj4cs8pro35BnSrpKU4up/7WrW5iSrtLeWSbbFVAfMla9TIdRtuqjFioQNM0IqPZZ/Hl1N4OWoNWDAxcZyFNtzCHb7lMbtenekANhcLzFX/bQuadRyEYeC5jaXGasJ0216hIqiW0rNpQNTGKX1iFsWxlItmWoMmsVh8HRJsL1o6avhN3Uxy2yGnac1xdBlTUqEHgV0w/SzT4jvVn6n29iS08ZKLut2EkWkzbSGtKZgJpnY1uKum+zrp5BzjHQuJfVEzhdLjwN2y7qw84ROfpCudc8J9Ma0Px8C9oLqJAlP9NnZ/rxa6Yv2a7xAymXUlTqDp2dRby6uTamHhwabaIUOGzROYK0NE4mpDzqUqs6tE6pJHlN5QOG1uQIlZlUpTI++Wmm/exmiapB2LMB2ZqjFGG8e21IabO92gpJWYJPdG8g2x5QG7VIt4TUxy3WrzGT8O45Y3QPp+mYU6Z5bY1XhltosTzSjukHHV0lVGjGh18xfSLTZu4VK8PxWNIK0m0h3phMxkrs75Iu+Iz1ZdBakEoHlAZTQJ3Ym6I0mCIzMI6dUcxulkyZW44D89I1auo21RyifEHXhjSpTEDgWWw5nmZMubSlasn4UI7xu1lQSbFaZ5lrl2hpMRNFOxWSypuyzOpvQmsD+5r+LxnKj5gVmtiKX/vyv7I47MDR8MN0iYJwOMCLIjwrSU0I9u/qo1pyse0Q37fItZj3nwoF4yMZ2maWwWll2IKalBw2Z12DjjIwKwtexaJpakBt2KJesul7qZlt3PGk3+byddYNNONKRdW3mNZWZFY5YoHq2JoxawiNZK8d+o2/UwDCbcREmNmbprZOM7XJQNTGKmmk0Lh2SCmC5YwOZpnphcxuKvK8KjDHmkC/uVn+18pm5f5NSKFQIJ/PY1kWXV1dyf6lS5cmFvhyuUx3dzdLly5FRi/VG2+8kWq1yg033EBTk/lwXXnllRxxxBFccsklTJ06lcsvv5yzzz6bI488EoCrrrpqUvTRTCbDRz7yEZYsWZIo5DfeeCMzZsxILNkvvPBCsh3L+9//fu666y4Att9+ex544IE3dC8wlvMf//jHyerDXXfdxVNPPcXKlSuZOdNwLv/4xz9mm2224dFHH2XXXXd9zbrzfZ8f/OAHzJs3D4APfvCD/PjHP2bDhg3kcjkWLVrEfvvtxx//+EeOOeYYXn75ZW666SbWrl2b+AmcddZZ3HHHHSxZsoSvf/3rTJ8+nbPOOit5xumnn84dd9zBz3/+80nK/fbbb895550HwPz587nyyiu5++67Jyn3X/ziF/nyl7+c/P7617+eOLZ+5CMf4WMf+1hy7Pjjj+dLX/oSJ554IgBz587lwgsv5Atf+ALnnXcef/jDH1i+fDmrVq1ixowZyf0OPfTQ5B6jo6OMjo5u0gdi+nSjiL1R3PxNN93EZZddxm9/+1vmz5//N8+t1+vUI+aUWO7f0I4jLIZswYjUbLmhmYF4eyiXKLFVCz60xTqkrXEKmp89PpMFr3iMCpt1kbVo1NZkLEFdaGQo+Ncdevn9vRkObhlndV8LAIX9OkAK/DuGWFPOsWXbKLWqwwtDBsP6YsrmxMVDTEmPcO3dXXx0+yGmukPccG83J+xs8Lyd7ihP/7bAk06arboHaO6u8asVM9kmrDJLReVTxvFWZBzDry4FNVTCWd0rDAxjeX87rdLj0ZVdBEKg15JYHkMhUOuM1c0Xxg34HbP7CH2ZsKHcv3IaXbrOAC6+EKgBWGeLxCnQKsPJ+/RS6wnJbpultsKj88A0fo+XWCebhj0Wt47zfM8UVjs2oYCRADpC8CMo70iQoSMUNI0Zp9gD5qynaYbi2kdNH2vxoe7ASJAi5QryCnpsm7N3m8ZTz5nMbNdcpVRMUR+RtP7bu/jVOS9wwe6j/OHeaQy/YiZOXbkyK0vNrF+TRa8xVlcF6DWxY2PkNLjGWF13bhtCa4HvWTz2XKM/B+sFEs2TKZngPz/zToe+XxnNYtrpi3jm/AH2OqZE0Fvkz/dNw6mGZKSpk3tL7YadBKPmNYeKMUvyUlqxw2zzTlpthWSnhYz0wgMrp2HrhrU+tpg7fZqXXcnHd1/HLx9qZTYB5ZLLvREXuxM9w/EgAJp8Y+Vd6QQc+PwKAObLPH5/kbSGR5ZPSyztQBIpOd2jeChtcSYjdDo1hl9M88RIB6VoMlmW0B5qBi3BkKNZ2J9h3DJBkKZHuPD1tmDYVezV30afbTMr8NhgOfTZgtk9+aRPBgL6bWFgZ3U4LBjFGogs+72S5i085PQpoDQ55ZPWCqlt8pE/ipeyaVbwYk8HufU+5dCmyQoohzZPp4xSt1uP4AWRZcGzaVaSYUUaUmQTi/Hc1blkfKS06SPhWpGMHaLfTvQ7WGPs0vFYiQPK6V4YsoVZQSnD0dv2YLcYfx+AzDyF1dUBjs0f/1My5+k0oRZYQlNX5hxXhoRKskqmCccN50xdgu/CAKY8W9RMvY1LyEioW/CozLJw2NTrlCCkLgQprXk6Ha1PhPCBXw3RuU20etnVQu3L/0r6ou+T/c1XyIWKT/pZMiLglrTpt+3aolXBX/q6qEmz+qcETI/G+ohl0eMIjlgTkq3W6ArSNKmQB1/qnoSTFoCtNa3rPPp0igFbcvTua7n5ITPeUwqsYeh3TYzbugPTx1KsihpowV+foiMwqwKPPtZtoJDRilo5Uv1eSlmcsHAta1fksNCkRYiFmdTElvtpC8e569kCT4Ut7KJ8npE5duHtF7UZVPJ3yWbl/i2Q/fbbjx/84AeACb70/e9/n0MPPZRHHnmE2bNns3z5chYvXpwo9gB77rknSilWrFhBOp2mt7eX3XffPTlu2za77LLLJE/vU045hV133ZV169Yxffp0lixZwkknnZRY5IFJ2wDf//73KZfLXHHFFfz5z39+U/eaPXt2otgDLF++nJkzZyaKPcCiRYtoaWlh+fLl7LrrrmyzzTaJo+dee+3F7373OwCy2Wyi2ANMnTqVOXPmJJOieF9/v7EiP/7442itWbBgwaTy1Ov1ZEUkDEMuvvhibr75ZtatW5corhPrGdjIsbm7uzt5Tiyf//znJ0Wp7ehoBJ/ZZZfJr7Jly5bx6KOP8rWvfS3ZF4YhtVqNSqXC8uXLmTVrVqLYA5PaFqBaNdaidDrNqyUThXevVIyl7rXqFOCJJ57g4x//OBdffDEHH3zwRvd6tXzjG9/gq1/96qR9n2qZz7+2LsBxQ2xbUa04ybZXn0AJKeDFlzrwtSREsF/rEBXhMsWqsm3aKMq2rZLAUFoL7vhDF/vmh3mlr40my5xz5zVp6lIwXbXRIn0sS7O22pQoY9vVPZ79Yzv5dJ0d63We/VM7zZk623geT91lJgD5lEdzps6iisVLz3UwY/ooB3ZswKtbqAjWcf1vO/jcDj3c+KuZfGZBDz+/aSZfWtDDLTeY/vvv89ZSHXNYu6HAgE4xJxVFftQiYYuQwtBpiogJQ2nB6tXGsTS2ts53iwShZK7lJefvmPaJh65Wgj/f1YmlNenlCls0Mfa0TUpnE0hIp1ul3NtMm1Nj+7mjjPZlse2QfGed0b5M8jwhoVJ2EULz2OousqsUR3Ybh85su8d4r+lPlqMMxWco+NnVUzgybSZF/UM5hsIUG17OUjzzZf6tZZzH75nCXLfEE9ooOW1BjXmFMcZKaYO9n1AHJh+aemA49qXQlEqpiH1FMNWZQOkYnTs/ZdpdhYI/XduML8z4XXH+IJ12nUdubsInxzS7StV3aM6Yydm+qQoqisIjBASBRArNu1trLFnSDcAXFvRw74PT+fAW6xlYn5v07InByhbYIcvu7eSY9kGGRpsIlOT9XRsafVtq/JqV1JudCrFdxY+uNxPtL23Tw28fn8nRW/ewZkXrJLrOKRHePwglH0rVueeWFuZmivSP5FiYGUPGUT+lNveOxlal7GLbCiEbrE3vyATYbsjYcIZZ0QpCl1NmJ0dRl5M/1zulG7CVR8fbUb0tAORCxbohSbAsJKPhmD170Upjt7kJ5nv3SogONKuXtVAPLFpTZlWoNVXnPTkDzxodz7BrZpjxcprFmVF2y/qoMKKNBWoy8vGYUBc6CoAU75vYBkoJ42cSWGxpNwwMSgu2scNk+/4nppPTYQJzCYQgoxUlIViUGadcd3Ato8znHLNa4Ycm8vEu+SG8uo1th3TMKTPck00YjqSlqJZcLEfRtZvHwKO2iekUvePGymlcK0RKzZaZyP9CCZ4dbeWF+03d3r4sZHHYQfY3X+HDf70AQp/SaZ9AB5qFUcBqFcB4b5pazbxH41UML3K4nSE1O6cCVg23cNt/2XziHT2oGqx9vpD0FaVFMu5CJZhrlVhgKV64v409XNM+wsa8I9pq+DWLTMGnf02eXaO8X3pDO5/94Ci66rHi9sY3UWlBTppzZlkhz93XQXP0OxOtyiglEp77gZeaOFCOMVxN056tsWVzIyr22ymbVfu/TzYr92+BNDU1seWWWya/d955ZwqFAldffTUXXXRRgnXflLzW/k3JjjvuyOLFi7nhhhs4+OCDefrpp/nNb36THJ8/fz7PP//8pGu6u81HsK2t7U3dKy7XRHmtckzcf/vttydOp7GSCuA4k7lxhRCb3KdiBgqlsCyLZcuWJZCgWOIJwaWXXsp3vvMdLr/8crbbbjuampo444wz8Dxv0vl/6zmxdHR0TGrDifLqelBK8dWvfpUPfOADG52bTqc3Sb316nprb29HCMHIyMhG5w4PDwMkE6vXqtOBgQHe97738YEPfGDSCsbfkrPPPpvPfe5zk/a9sN2HUMo4VWklCEKJjHDeQTBRudfYQqG0oaULffPhAYk1gSlChjq5zsLACAQ6+eBntQIlTeCqWAnAOFYCeEiabQ/XDfGqFs1OFTcV4FUk+WiCkE4FqFDgI8gJje0qqjXbfBATjCv4Y8Jgm8dtskrjVyxykaObV7EIfYmvJVqYDxrEH1ZzD4VIfuvY9yD66MX0g0oJQmUUkXgCEAQyuR8YHL4EshFveiq0sFGTnF0tqfBDi6BuIEC+bmwD6MhKaercWEQtNGEQOVb6Jh8TFbAwkCZaatwewuC809q0g+9ZOMI8V8XMe0KjNYRaILWxqIZaELdwqAyVoiWMtdaS2kx+aChzDeUEfL+R72bhMxxZUjOECGGshWgryXM8iTD9Syb7gtAo937NpimmNa9KQydYn1zfcR5MeYzi7QiF7xuLrCVVUm8xxCPus4liqkTitxCUTX0HVYnWYpJCG07oN75vkdUhWoNrhUmeAYSKxkJkpU+ChkVlA7ACM4mKyx1G49FsT+a/CH3ZqDOMrwsYlgwLSKsGLhuInDLjbeMEEUYxHkIljGOlEkk9hEoSBKa+glCaPh3KZNIahBIhYOLrTmmB1vJVv81kOe4bRmFtXKS12ae1Od/WmowMCJV5bwutyYiAQNsmnxPqId7W0bOSd1JgEdbN5DZm+BdhdK1vmMFCJUFNbnelBSiSaM2xxLj5NmwcbSZQMbWpcZ4HFehJ+QpCCV7DWBDnVWmNjOImZLWBymhl3iNqwvtAC5GUVwpNgDQOxmE8JqJ2qFtmHNfNhCeI8p7XArwAlJ48AaMxToNQ4lohXoTB17px31gsW1GqpKhhsdmY/s8jm5X7t0GEEEgpE+vsokWLuP766ymXy4mieP/99yOlZMGCBRQKBbq7u3nooYfYe++9AQiCgGXLlrHTTjtNuvfJJ5/Md77zHdatW8cBBxwwyYr+4Q9/mC9/+cs88cQTr4m7f6P32pQsWrSINWvW0NPTk5z73HPPMTY2xsKFCwHeMEb89WTHHXckDEP6+/snsclMlPvuu49/+Zd/4bjjjgOM0v3iiy8meXm7ZKeddmLFihWvORmI62n9+vUJ7ObBBx+cdI7ruixatIjnnntuo4i0zzzzDI7jsM022wCbrlPf9/ngBz9IZ2cnP/rRj95w3lOp1CQnaoAVvpn4NSmFq5VxvKsrMloxYNkJBKFVBWw91zij2umQ+56fwZglSAXQFjFYZAlxpWJIu1SEZLao0jueozVVZ33d4PJnZUuU6w62VNQDG8tWtEqP9Rircw1JPlenbWaF559uIZer0zaryvLRVprzxmrUNrPCcE+WupA0pb0Iy+zSlPMoTDHjrtYDVso4mAL0OYbKr7jW/LZdxVB/mgHp0KECntB5LA1jlpkYgFGOxqRZ9nYUjEr4yNwImhSxXfzi0ZkoCa4GV0HRgs6KSmAHdSFY3DSK51s052v0DueZ2TzOWDnNemXKXNCCmfNHeOy5aaxb3UUHPhuEi1XUdAlj5VxPmowyPP1FKTlgq7UEdckzqzoBqAxK5jhlXglyFFSAE/kzzHHLDNfMc7qbS6TG09SQbJEb5+VyM4s6hnlusA1nwkd9pJThBZmhKCGtIRXBGQAyEePkmGX48o/cqgcrZ1h6bnnGvBfyoXGqTivI1HQUuAsWN49wb930v4/kx3h6sJ2tm0cZK6UjnK/D9GZT3sc2dBpH5ghOoARklKZQDclH2lZl1KUVn3rVZpnOE8ZQKA3N0SxvxBYUPM0O+RGGi1ksqfCUxYsDrUl5JQZek9fGQdxG0WQFvOSajpDdyqX0irn5MtlEXTTgFp2RUjdiCdprmjwhzS01Ht7QSV03YCkx5CNXU+R1wForRcrTMXQfgPaqT1u6xkqviZIl8QU01zUFFbIuctZXUVvMrETRRCOYTuzAPWhLcso47K52DMOQobVtfO5T80yfee4xi4ptIB5V27TnnDEzgV5nOzRXFesdSWdds4BxxmopPG0UwVWOg6Ua42Xi2ImV4XHLOHZb2uTZ0aawtmpMRsYs6KpF7SkFi6wKQTT5B5iZreA4IU1Vh6FahhWuk9RZNhqnFStq82oGhXFYbn4hz2y3zErPfHNDIXC1piIFK+9pZsd5fTz58lSGIx+dQJqxnlWQqzW02IfSIQtDc85e1YAfpkt80s9SOu0TCClo+o9rEgt+LM31Gg+sbCfnaRNXQmlGInYjqSHvaeqWIABk2nSmR3WeWAcX2kCLmhUM2KZOMz7s1dXHX/oMJNjWGnzorqapa0nTaMA60hARuvWmQsPYFSoesrPJs+M4FwCZEN6ZHebxchuu1mxl1QmVZKyWIueaG7mpkPHApcexmWUpRoazbMHbL/+/sty8VbKZCvMtkHq9Tl9fH319fSxfvpzTTz+dUqnEEUccAcCxxx5LOp3mxBNP5JlnnuGPf/wjp59+Oscff3zCMvOZz3yGiy++mFtvvZXnn3+ef/3Xf2V0dHSjZx177LGsW7eOq6++ehIOHOCzn/0su+++O/vvvz/f/e53efzxx1m5ciV33nknv/vd7zaygP+te21KDjjgALbffnuOPfZYHn/8cR555BFOOOEE9tlnn42gK3+vLFiwgGOPPZYTTjiBX/7yl6xcuZJHH32USy65hNtvvx2ALbfckrvuuosHHniA5cuX84lPfIK+vr63NB+bkq985SsJo9Czzz7L8uXLufnmmxPM/gEHHMBWW23FCSecwF//+lfuu+8+zjnnnI3uc/DBB/OXv/xlo/333Xcfe+211yQr/avljDPO4K9//Ss/+MEPGB0dTfpfnF69evG3xNUaVxsbsh39lhirsKs1MkoWChUIk3yJozUpZazSdnTtq1gPAcN0ElvvBYZmMbZ6iwlWYo2xKvlCRHAFs21ZGmRjf3zMkgYH77ihYfCR2sRviayFaWUsuxmlCTxpflcMO0Za68TRMVY8HW3YOpwJydKRYq/NhzGljZOtCgTaA+1F1yXXm6AxFiT1FuPAhTCOoY5UJkYRJNSegZKoKOiMBGxhbHgSEgYLMHXoaGVw8IGJritpvMilNM/UNFYfbEtFNR9ZmIVhOLEchSKyKjL5PpbQ2NpMWOyoHlJRsqJ9qaiOVGAUe+U16s2O+oZtmi4pi22HpBCkEFi2KYe0VGM1BEO7p6N7uFpH99SklMaKGEUcbVIYKYEqlJPazdGNuo3bLhaljR/BppKI/stoVSmvJXktUeM+jobAm/AcTB3YE/qNBFIYWFoqyuPE43FeLGGOCUjK4sTjTuoo36YODYOT2qh8Sb+K6jben0r6qjJKnIxiJSjdSH6QUCumlGnnlDZKfjJONUkQJDuibnWkSoKQvXq8TMzDxLo3YyF+t0wcK41+ZMV9PWqjGBICpi9IKx4zelI/nDhO7eg5bjQGRfR+ifu1FY1FGb2LpK2jZ5o2t3VjtUNOSGmEqQsNLoqCcMiIIKGnjS34qqZRNR1RqTb6ra2Nb0pKEb0vzbvB1aYsMd2rO6E8jW2djLOYpSh+T5K8P6Iyinh8mLLntaHh1YFK7hG/y5I6xLyTDMXxplEEdirEx6zgBeXUyeUAAQAASURBVKFs0M6+zbKZCvPvk83K/Vsgd9xxB93d3XR3d7Pbbrvx6KOP8vOf/zxxTs1ms9x5550MDw+z66678sEPfpB3v/vdXHnllck9zjzzTE444QROOukkdt99d/L5PO9///s3elZzczNHHnkkuVxuo+i16XSau+++my996UssWbKEd73rXSxcuJAzzjiDPffcc6NgWH/rXpsSIQS33XYbra2t7L333hxwwAHMnTuXm2+++c1W2RuSJUuWcMIJJ3DmmWey1VZb8d73vpeHH344WTU499xz2WmnnTj44IPZd9996erq+odE9D344INZunQpd911F7vuuivvfOc7ueyyyxILu5SSW2+9lXq9zjve8Q5OPvnkSfj8WE455RRuv/12xsbGJu2/6aabOOWUU/5mHr7//e8zNjbGrrvumvS9iemBBx546wq8WTbLZtksm2Wz/ANlc4Tav08289z/E8qBBx7IwoULueKKK/5X3Wuz/G0RQkziuQc4+uij2XHHHTn77LMB+O1vf8vnP/95nnrqqYQz/+2WO6Z+CDABjtqbqqwp5cmLgNamKqtKeQoiYnRJeaRcsz1WThMqyXqRoqBCmi2zUpBLe1iWolpzcJ2QwXKGjBViScWgb6AhMd91q/TIOAFCaEZrKdoyBnJT9UwAm3HPJWOFBq7hOThSJRa9cd9l63kDrFrZhiMVaTeg0F4h2x6wfoWhAv2tLvCpPdbx479M50Nb9/DDF2Zw2r59XHmvWdY+bd8+lt3RTlu6RsVzGFEuAk1eBIxrg/e10DSJgAFcnMhiPKcwjrQU5YhybqCeYVxaZFWIDWREgCtV4k8wkTPathQVz6GuJQGSasS0skXa0DJ6gcWwnyYnfdoLFVaPFJK6ndJWpmegGUcYjHt35zgbBvK4lgGGD3oZmi2Prs4ioyMZ/MCic2qRdb2F5PkpO8ALLRypeEE3sZ07xvpqE51uFdcx93HckNCXvFAu0KRDisLCAnLaHC8JY0Ns0iFj0maXqf3UazbZvMdTawzcIxAicYpsEb7BuCtJ1vUZiOIQiIgTXWp4xbXYS46Ta6onGOiB8Sw1bSUWqDqCnAhpy1Z5ulYA4F3T+3hqTSdbTxnm5YFWfBqMPrmIi76obVqET8oOcO2QiufgKYusbWAHDbyxoLWpykg5gyUVs+aMcFuPcag9ausefv/sTPafu44nXpwc0yMdAdmrWLRK01ZZ12e8nqKkLVKR5bDg1JO2bctXeWWsmTSKjkyVgaqBTbSlauRzNdYMmfINSYcWFTCjucgr44XkmRlC0jI01lqhWa2yDEWsVlMChQX0RTCQI7cx9KSpeVm0b+okHPXQnuaeR4zTv6bB8T/PNo7ly8M8XaFPSRg/gi27hvG9hsP6y2OFZHzE46VZ+IziJCsleRFQimA8BRFQ1jbj0iKjVGKJThMmq0wWOsHnj0b3jJ20B/00U1NVXvZz+MIEX6tEFzaHipKU5FVIToSmb2mLZstnaqcZW8/1tlMQAa4VUgwc2tI1Zu0wxhMPmfdBUVjkdciwtJkpqmZFRGhe0E0si957B1RhxLJ5xA04d6teVABOm4nK3bxkiSlE6LN8t7NYX23CRREgyYiADcK8L7IqpN3y6FVpNtiSo3buQQfw0GPTEoatGPKV1ophaViO4r5SrDVglXUtyds+XmiRcXyGvDTNkV/SI1aWk/5lGO2H/OW2BgQNGlbdNCEt6Trj9ZR596VM/x2tpWjPmvex1uadnE35ZJs8isUUO6z+NW+3vHPavm/ZvR5af+9bdq9/FtmMuf8nkuHhYX7/+99zzz33TLL6/0/fa7P89+Vb3/oWv/5140VZLpdZsmTJP0yxh0YQn1ALvMAyDpSY7VA0HF2DUJKxDOOHJTReDPOg4djmBxZaC7zQQkqNIzSBMo5gsRgHSgNNiB24QhrOk3VlON7dQOEpSZPt4QYW1dCiLcKBpsPQMF0oScYJcJwQFTuWRopsWoOqKNLawHOyWqBKIdnYsW+8wQyhdUxdaRwLE99MHf2WgjBaGpeWwrJ0AiUJiJfKBUEE5/CUTGAwUmnSTmCiqdohdmAhtKY2weExdkDV2jgJx1EjA8CP6iUIJD4SicLSZjndjpxw43z4kUOtHxgHVb9mkXV9hmpGoc5E9J+WVDT7IXXfNgF4AjtR7i2pCJGG/jIqQzihn+hoOz4mIodaIKm3+BwljALiKPC1pD3tY9XNJK/J8vHCFE0EZHUDMhibmwxUSyTL6hpBoE3ZMhGUIfAMlCkITF3FUWhtDUHs3CvA14Imq+FYLDD9EiCY4AAaKsMEpZSJWRD7XvhlSUpr/FqjXZP8ToA7BbrB4GKhI0fxxr2DqFxBIM3Y0sZhNq7bIJQNB2QmOJuHkon+wloLAi0RWqNiZqfomIG4aDIxHGni+nykDBv4yKRiJOCFSU6qNPp26BuH2tjBWwmS8RHXuxk7woDGMW0Qs2ApGmMlvtbsF8lEGKFwhYFpOYF5B9qWwpKabBAmzsuN/DXyokREE6oNxMxHECiZOE6HQuBrgVBmYh2EEh006jmOyArgKatB+SohkwSo8qkpSbu2UBPqT9gYeA6A5RjH9qgNY4d0OaEfe8r024ye4FArGuUhgsrpiX0AwzZUj/pr7IviR33WDy3CqMwAWWki1qL0Rn02HlMhEtcO8WsNHwcw3SQeh44TMlZL4QQS/Y9B5EzK42b578lm5f6fSHbaaSdGRka45JJL2Gqrrf7X3Guz/Pdl9uzZnH766cnvo48++h+eh32/aCgQRXs7dHSxYPkziM4p0D6VBa+8AJEDrpg9j+NP/T0AdcvnZ1/fivDp5YjWAnJm5GLV0o5+4XnQCjU8xpdusvj6waP8YukUDpyzHoAf9XXjC81WvsO7Z6xnac80FokaJc9Y6hbt2M/ly6fT5EpO3baH7z47g6wjOHm7Hi5fYSypGVfgrGxhm+37+d1zM7FK8J6d1/Hz+2aynTKcdPvaRVY93sI836My6rJt3WdoeYq5nvlClXpstugaoTiWpuzZvPvfI8voRMqIKFaFHi8litHxV7k0YSOjc37wlQ70hkFEWwEialNhWwmWFuCsr69jES69SrEtgmdSmpmhTBwC+4NmmpTmnTP62OZjM5C77ItevZw5G/qQuxuHa/3KU8zc0IeYvwi96kU+83XBS4xy+zXGt0eveBa57xHoFcvo+MP9eGvqpLdv47KfZfn0ASZC7ZN/aGetlWJIwItpn0uOtbniJy4nTFtPb49Z8Xi50sz+7xtmzhYpyGYgDMH3IR8F5vJ9Ux8AUvD5/2yjqANSVckV5xvLPaUyorUF7fvmWttCuCm+e0EfsyNPyj+7mkvePchVf5jKLjWPrrnjPLtiKovmG5raOf++LbpSaThyBCHYRvG9+xsjAOyzwGfdkM0usyvMPH2eeRYYj98wbFzXnOfbX+vnjIP7eXhpGzMLRWZ/95DGIJAS6jXoXw/zFoHv0f+lX5Kd0IaO1owPZ9jvq51QLJpn+IGpo+Qkhx9fNMRiv2LoYr/cishEdLeZJnRvL6JrKnROZ+6KZxDZLLS2oZYbljM5e0vomsmMW27D3nVbwuUvYi2cD7O3ZO7yp5L6BxDNeXQQgpTor/SwTcb0+1rd4U6RpyuAPscEHasVHdY/0UQtmkTN7x7Gq1scfOQIIpNC+wEi5YAfYO1qyBgWPv4U1rZbETz8V+ydt0Fs8350rQyBmbzMifMDpq6VMv/T6UbdK4Wue2Y81C1Eeyu6dwAxpW3StSKfR4chQgq+feEGZgeCgchA/YJIMUU7eGnNF7frZ+tFEmFbhIPjWN3mPmpwDNmaQ3R2IOYugJEBdHEca8/DUS8tA6B7Qy9i4Y7Qvxa9oQ/rkONQT/yBvU6MsvriS8hpM9BDw5AqmPeeUuQvfoXdogB7j3od1ISgVRm6y1BJmus1hITluxnGslBJtn38O2x182XJGKFaQ5dM+4hCM2QyjCz5K4+t7GLZY91UheTAc1qgHvlK2Ra6VEaX6wgZIjrbIZPhugsHOGp7sxITVCUtnzsQci3mGq2gOAqjhm3N+soqHr2tBQXsd3YzeryESLmo0XHkNLP6JDJpHvvyGposf5KBxgwb8/vRoMBRR/SjKgHP3dPKDuc1KJ7fTtGblfu/SzYr92+DaK35xCc+wS233MLIyAhPPPEEO+yww99931WrVm2076STTmJ0dHQjPP1/516b5e2VtxIBNzQ0xMKFC3nkkUeYM2cOTz/9NIceeigrVqzYiLrz9cT5sKHG1F4VXRlD7HggeFV02WzrcuQTUC+zdMM3cS2brJPCPuhbyD1GEG4aXTVL37pWRLROhaYCslrkqRuuxV64JevvKNE0y2iyL/RVyGIxS6QJ6pLn7YC5vsWiiIknNa+J9cs98sLGnd9M77MeeWGR2iLDuhWGSaVJ2KwLM2w9P8u6F0z27FmtKEhsVFNnjPPky1PpcqsEgWTulFF6Bprpssxyc3ksRTrrU2irwjA4R5+HrpfRvofMmWXs+LdIN6G9KnhV7v7ayTjSwoogNfb7L0APr0cUOo3yoxWoEGTDGv34+V8m7XaxUpXZVeV5RVfYUuUS+MIqR5PVggO3VFj7fRC8GmKbPWEbwDcffLFwd/TsUbAc5MyF/G78dEKlsBbuYfI6cyE6qCO22hl7zWrsXQuIQgt9P38WZ775mK/7o0UgoBBCn6giFy3mefEcTXM02X6jNIYBqKqP+94T0F4Vme9A18uNfDS3o0sj6MoooqWbX33zE6Qsl7Jf5fsHfcHkpVoErRDZAroS9R/bpV/8gP0w97khrGLvMJ/xu0fZYDksVIK0CFn5slHYdj3ko2A1PlHai2ACxUFWXPJ9ANwdZrHy0QB3hov9/k8hojbRYYDa8DIAcuo88Kosu+gC7O3mIpeO0lSoN+qtVjZtJSS69WVobke4GTqOnMYONxou/Bde7qDLqlGquVgHfhiqRcOfGQZo38BGRLYASpFTS+hTaXac1o9z9EVJvvHrkG6CWhlVHMTebj8z5rwa1k7RBK40ghpeh33Q3th7Honc20RGVeuex35fxMYS+qZPumnTWFKivnIxnQuiyKESVj+dYrZ2mO1BboEg1V/j/pEpVKPBEfa2GzarT34UPdaPaJ+BHu9HtE5Hj/dH42kBon0G9hZbI7u2RD1xN7S0gxvB6z54usl/4CEyeaiV0V4V0dwBXjVpM5HJo0vDaK+K1bkFamgtoqULAjOW4/FF6IOQPHPhBcwghxuNjce9Dcx2WsgLh8wBC5G7vxvROh255hlEq4HUyNIwotCJyLVBGJh3UnnMvI/m7WDO2W5fk6/pW6NHe1GvPA5TpmFtaYIvym0GG3028Ez7SskWT301WZKyfwX7R4w1tZpDEEoeWNmOo6EjjFYCga1uvgznmM+ZNrdsdGkk6cvCzaADj5aer5H6oaIqTERb54Ono6N7ICXUyoSrn0LOWIRoMn3rua9fRHYf43Omy1Xk4v2hPAZu2rTf7O2S9868bc7hF8/PRGjY++APoetlhHSQtXFEkxljIpOnrC9ju9n9+FWLnr4CjlTkXY9KZGxZmVZY09uRpQol5SC3eweb5X+/bHaofRvkjjvu4LrrrmPp0qX09vby7W9/GyFEktrb2znkkEN46qmnXv9mb5NUq1VaW1tpa2tLKDvfKpkzZw5CCH76059udGybbbZBCMF11133lj7z7ZLrrruOlpaW/+lsbCTf+MY3OOKII5gzZw4A2223He94xzv4zne+86bvpcPApMCLrG8B2veMkhoG5iMc1EEpXMsmZTu40jYfotA314WBSYAOfeL1Wx8FSiERybq3R0hNK7QwwZYgXvY3SfshDgIHw9PsIEghUfUAEf1ZmGix2g8TVg6RSdESavKZOvlMneJwmnbLY8RLk817jI2lacvUGAtdxkKXpkLdQIKiAEKqMmYUguIgqjJmfpdG0MVBdLVoFJTSMFk7RdZO0eRkaHIy5pyxfnNOZRRdHDTWTb9uklclRBGgCTDUnHUUZWlo6YIEbxzxj3s1dL0UKX5Vs10vGSUy8KBaRHtVXOngWjbaq5lULxvlJVKsiGI5eChj8bYNyjnBsGsFUuIgUBUTTElETC060EYpHx9CV8ZMKg6aVB4z5RwfQlfHSVsp8naGtO2iioOo4mBSD7oyhg590yfCAC+CwwRKEqIhDE3fiERhcM5SaNO/pGVS1NeQEoRkUNUYVDVEW4EaGlnIoMtjjXarjKHLoyZVxtCBR00bq7KFMjEdfM/088BL6k3rEKKJjEi5jBfTjBfTNLse1dAiZYeNeigOosvDjecUByEMKElj5VehQEcKr2nHsrFkx+Mk8MzYicZW3F7CSZnVEa9mylwvmzEZP6c8Zp4bXa99D19LgophgworUNIB41IwZAtkk4vdLGkOFTllaBWbpU9LhMvRQ72glfkf+mZiqkIzqfdqMNJv6idmW4vG+sbj41XbpREzZqrFpC+peKzE18bXRJMcXa/g6ZCyhHGpGZeaQIXUtaKio1WKgXXoyqjJV3nMpJF+GB8yE4zSsKl3v9oYD14V6mV0rWi2J77rqkWTasUkv/jRO8+vo4oequyjyj5VKaiWXGrS+KbYliKnNDmlcDHJiS3Ofh2caNWzqZD0ZV0vm/dmzafXtpkqa0xRvqnPOC9RolJqjLl6mToK4ThJolpEKz8pT3xvQp/KkENWGepaXRxEj0d9dnyo0X+9KhUhI5Yxk+14NIrIt8fVAsIQ7RmgULya+XbLZofav082K/dvg7z88st0d3ezxx570NXVhW3bHHLIIfT29tLb28vdd9+Nbdscfvjh/2N5/MUvfsG2227LokWL+OUvf/mW33/mzJksiR2MInnooYfo6+t705blfwZ5M9STf69Uq1WuueYaTj755En7P/rRj/KDH/yAMF4Sf6MijYVKRJYqLDtRorBssByTpCTUiiAMCSPFEGk1rnutl76UBOiIbztWz41oJRKcayzCMopfiAbbIkTjoxGuQTHr+Fh0riJSkMOQihTUfZu6b5NKB9SVRVqEBJ7EdWKMeYhLiF+zE4VWaYFwM+CkEG4GYbsI2wU30/gdHQ90iK9CAhUQKGMlxE1H16QQTiaqtyjZ7sZVQkTdR4OKMxHLNvmwHISdMgqCk0JIJzrmIiyHUIcEKmzk1XZNO9mpjZ43UWIctYzaJozaRqsoQRSYx4VUGtyM2Y7KiZMyz3DTCDuF0iFBnJeovsw5Jk9CWAhhgWUb6kHZoL7EsjbC1ibBhOL+pMKoXzqJAuwKC1dY4PlmMlLxEI6b1IVw0wgnZZLtJs+OJ51CaoRlIya2k5My+bRT5ncY4tgKxzZ+DZbQhEqY9nUzSb3Ez8HNgJTYNHwPTDtGz7FTE8aaZfIZj6+J40cpAwuzbKMQRvmbWLfCySR5F5aNLTSWC5YL0gYpBDaG7lD7IaqmqEpBTWKSskwEWCFNGwtp2jaeTEkLHFNvuOlNvBPsxvhwzPjAiX5H+yeOnbgvCcdNxsqkcybeMxob8QQ/7h/J2yVl+p3pi/Fz06Yc0fjFSZlzbDcZP3F/TLaj8kwaP3HfTcrqIFwJtgBbGEpPO0Rq8+7SOo4xYIJlBRj8OzJqv2gFT9fKjQ7uZsxzXZu01oyGLqPClF04btKPTb7jd4rZJwHt+0nCdhvvBSlNmYXJu51S+HH8AzcT9dF0o5xuBiwHJ6JujR2lXy2BMONURA7aiH+M2vjPQIU5MjLC8ccfT6FQoFAocPzxx2+SwnyiTDT0Tkzf+ta3knP23XffjY5/6EMfelN526zcv8Vy0kkncfrpp7NmzRqEEIllNZVK0dXVRVdXFzvssANf/OIX6enpYWBgILn26aefZv/99yeTydDe3s6pp55KqVRKjodhyOc+9zlaWlpob2/nC1/4wqRZ6Q033EB7ezv1eiO0N8CRRx7JCSecMGnfNddcw3HHHcdxxx3HNddcs1E5nn32Wd7znvfQ3NxMPp9nr7324uWXX06OX3vttWyzzTakUim6u7s57bTTJl1/7LHH8qc//Ymenp5J1xx77LEbOYtedtllSYTZmTNn8q//+q+Tyg1w9dVXM3PmTLLZLO9///u57LLL3pBFfcmSJSxcuJB0Os3WW2/N97///eTYqlWrEELwy1/+kv32249sNsvixYuTgFP33nsvH/3oRxkbG0sG2Pnnnw+Y1YmLLrqIk046iUKhkFBX/uIXv0jqZc6cOVx66aWT8jNnzhwuvPBCPvKRj5DL5Zg2bRrf+973kuMf+9jHNpr0BUFAV1cX1157LQC/+93vsG2b3XfffdJ5Bx98MENDQ/zpT3963XqZKMYSOMFqVB4zFqF62Vh7quNJyjopmlNZmuyMsSzVyuaaenmC5bhmrKBelZSw0NUaKQSqplA1hY1ACoHQIG1tjkGiXKqyRxaLLBJd9WjCIqclatwjjRUlia01quyT0sY6hePQGYTkc4ZxpDiWJu96jGmbdD6gVHPJZesUhU1R2KTzPio0joJSaGNRHNtg/heHTBrtRY/0GWv0aB96fJC8kyXvZGl2mmh2mlBj/eiRDeac8X7UaG9kOR4xqThIWjhYCBwhI357iU/DiW8ix3xiZSsNo8f7zfZ4bCUeM5a30jA5O0PeyTas5WP9jeu8wGCzfQ8rWgHBi6LjRtzxlpBQq5LGQtW0iRVgGc5vVQuN1X5kQ6NORjY0fo8Pwqix/jXZGfKWyYse7YtSP3pswJSlNm5SZcxENlbGedoVFlSqxjKI0btjvm4ptOlXEewjsWRqBV4NT4d4OgTbNhO/fMa0w9gAemzAbI8PoceHUOP96NKwKa/SyGi1ZpJ1OU5xny8Pg2VRqTtU6g4Z18fXxvlQj/dH5YueFz1Hj/ajq+Mmaq82juem7YYa1tJqMRpbJVRxqPH8WtmkoG5WObx6Y+yVhqE8jhrvN2UZ22DqOLJa68oYdS3xyyYFEfbGF1AVIJpSWM027WFIe6BoDxQtbp0W6ZsxOzpk/o+Z51ErmzQ+bCzkwwMmD/U6VEtQHofyuBkf4/0mFYei+ojqZLQ3GTvJytbIhsZYGe9vnBO3VWkYVRzEEgIfqKOpo8lINxo3xoLM+LBZJRkdStqb0Vf11WLDSk1xBIpmHBK3w/gQVEpQLSX1avp7n7lHtNqgK6OoUpAkMBGX48mbECb+QlorMiIgIwLShBHGfsSsiJRHEU0tjRWckT50tYgqVilJwdy2UeZnikm/TfpxaRhKo+h4X3EIiZhkudfxKllpGF0pmraIVq5qRYfmUJMLtemb46a+GB82eRjpQ5eHqQuJ5Whs1xiF4ojK8TjMaoEu11DluplcRBDMzQIf+chHePLJJ7njjju44447ePLJJzn++OP/5jWxkTdO1157LUIIjjzyyEnnnXLKKZPO+8///M83lbfNyv1bLN/97ne54IILmDFjBr29vTz66KMbnVMqlbjxxhvZcsstaW9vB6BSqXDIIYfQ2tqa8OT/4Q9/mKQ0X3rppVx77bVcc801/OUvf2F4eJhbb701OX7UUUcRhuEk9pXBwUGWLl3KRz/60WTfyy+/zIMPPsjRRx/N0UcfzQMPPMArr7ySHF+3bh1777036XSae+65h2XLlvGxj32MIDAvtx/84Af827/9G6eeeipPP/00v/71rzeK1jp16lQOPvhgrr/++qR8N9988yaDZUkpueKKK3jmmWe4/vrrueeee/jCF76QHL///vv55Cc/yWc+8xmefPJJDjzwwE3yxr9arr76as455xy+9rWvsXz5cr7+9a9z7rnnJnmK5ZxzzuGss87iySefZMGCBXz4wx8mCAL22GMPLr/8cpqbm5MBdtZZZyXXfetb32Lbbbdl2bJlnHvuuSxbtoyjjz6aD33oQzz99NOcf/75nHvuuRtBkL71rW+x/fbb8/jjj3P22Wfz2c9+lrvuugswUYPvuOMOent7k/Nvv/12SqVS4mz75z//eZNBw1zXZfHixdx3332vWzebEl02Cg5amY/FmMHeUhqB0gi6PIYtLCwRLc9Xi4jmdnP+aKTwDPVC7xr0wDoY6WeqlUMPjJBRIFyBcAXdIs0WOk2TAhUYhpmJlmvtKTJIHC3QtZAMMoGKNGHRhEUagS8E2lNJEBtdrDBqWQmUotBeYbCeptOpMdafoauzyNrxPDNTZWamyvSvyxP6EiENI4ex1gbGEhhZv1DKWM8yzcZKlsljCYklzCpGqJWxwjYVjNU3CBBOCj24Fj203qSxATqsLFkkU0QKR2umiTStIXQFAV1BkJRfVbTBtvuRQuvXo8lSDV0xy/QoleDfXWkb2EaMifdqUC2hR8bQY+Po/n6ma5ewd5iwd5isUmQiGMFskUWt76UFexILhqU13qBGB3VIZY1lOQwgnTXJcoySnc6CZWMJSV35+CpsWMHDILEE64F1Jg2vp0vbNKU8mlIe3TKLLpXJakFHGOBVzKS/GDoUQ8comBEERIeB8XuolVF9LzNTZpkps6i1vUxTNsGa0WR1AMtO2oIgQEgHPdZPi0ihh0YawYCiSQdeDWoVA8Moj5v2q5Xxn15J55QinVOKrK820ZqqGxrC2IpupxCpxiqksBx0fw9TAlOZ0lAaof2qgYhE0CRdGkaPGCy/ro4nsBvCAD20HvrWmDbWClnobPhuxH1SK4OxHu1DDa9Dj/XTJAOcvDKpoJmCS5ev2NILCHtLeH0BA5bNqCUZtSRr/CbWkzYY9eZWZL4DmtuMf0U8kYodNeNgeuWi6WMxhMiyTZlsN8mXsCIrcnxOKm2s4GFgxo/lmLEycXXJTZvJ1PgQVMbIC4fWEKaFgmmhoMNuYqpIM1OkjSN3cxuibbqx4OdaEblWSKWMz0Pkg0AYoOtVqFWSSRyBF02cIgPE6DCMDiV51aFvsP9OCj28PpqQ9CGbHWTORuZsckqRa6kz3Q/wPAs/sBixJWPSYoNIsUGkGBaOcZ6NIHNICzXWjyx0mvZ0MwYfb0um+wE9wwXWVHLJilxSh9EqqpgyC2Gn0NVx2rBRG4ZM6h+N3ttjpv+WRk05oklWrqPOqCUoWQKRmrD6ZtmIdJMpa3GEVhVQHnUpjqbxtURpw8rjK4mvJLYGXa6hvdC8p0YH3/S35b8j/9thOcuXL+eOO+7gRz/6Ebvvvju77747V199NUuXLmXFihWveV1s5I3Tr371K/bbbz/mzp076bxsNjvpvEKh8Bp33LRsdqh9i6VQKJDP57Esi66urmT/0qVLyeVygKE77O7uZunSpchoKfbGG2+kWq1yww03JLCVK6+8kiOOOIJLLrmEqVOncvnll3P22WcnM7yrrrqKO++8M3lGJpPhIx/5CEuWLOGoo45K7jtjxowkoBYYC/qhhx5Ka6txGjzkkEO49tprueiiiwD4j//4DwqFAj/96U9xHONUs2DBguT6iy66iDPPPJPPfOYzyb5dd911o7r42Mc+xplnnsk555zDLbfcwrx58zbpWHzGGWck21tssQUXXnghn/rUpxIr+/e+9z0OPfTQRLFesGABDzzwAEuXLn3NdgC48MILufTSS/nABz6Q3Pu5557jP//zPznxxBOT88466yze8573APDVr36VbbbZhpdeeomtt96aQqGAEGJSW8ay//77T1L2jz32WN797ndz7rnnJvl87rnn+Na3vsVJJ52UnLfnnnvypS99KTnn/vvv5zvf+Q4HHngge+yxB1tttRU//vGPkwlO3J5x/1m1ahXTpk3bZJmnT5/+pp2lRTpSUFqnI6pFRCoLbdOhOo5oakmw9NTLlP0a9dAnY7uIfLvB0qaakG2GxUbXxtFuGpHNo+tVNoQl5Kx5jMiSgXoAA9qjKCy6ZcpYUDFRPWXEomK1phnCp0nYyNYM/fjkhYXdnmY4iq2ei2IzWu1pSrGJIgwZtqDsmz47LRtSEyaiogoFOqKyjFkg0m6A7RqsebnkGkXHTkFQN9tglq6Dulkmz3eAV2OkXsQSEjtSukRhClr5ZqITOTmKfMeECpb0hSXmyRxDuo7GYUB7BMJmxGpEyQ0AKycRbdPAr5rldimNIy+YD361aJbfsy2UgqqZXLSauifVZBQXaSHaWxDNeUQ+z6B4BavTfBh8IahKQxW4XleQ07egjxewmxsUhzUhSU2zkO0zjYNuvsMoFypiaWlqM3mpjCGyLYz6JVzpUAlqiJbuRl60apyrFMLNMCL+lFA99loVRMdMSqLIsLRxs6afZSN+epFrbSiNmXxUNononEU1mg6J5hyj0gdbIApTGopw6CPau6Nz2pHpJioEiFyWmg6wU2Gj3ibUry6OQCaPdDPYs9pRy4wzsDOh34iWbnR1HCEs0+6piCEp2wL5VqryUVDSQH+yhQRqogPPjK2WLgMbyRZM3XjVBEolWjrRWsFALyLfgS4OGgfPdNYohhgH1Dgqqgj9pMwJWkJBhZC6cPCFlZjwapLEobY91PgIM7nI5NDVonF8rZdNvWMc7EWmGV3oQGRb0JkmyBgl1LRPmxkfft20j5OC2KHWjSYEQR3cjOlLftU4nQd1RL7d9JHoHJFqinwsJDUdGgrVKK/9QYkmx6EubESm2TxLhZOce2nthKaCyVPkuCycDDrdlORFZPII30sUXB1NWGWLebdrO4XWISLb0oC3SAlSIFwrGT8qFIxYFjOkRkURb8Hw14PxHxKFZuM4Wy+b59fKKGWip8vWLrRlI3JZbKDfsqkLETkDN+g0KY+im5pN/8+1IpoKVFCIjOkrWmlEYWoEHTKQMNHSlUAepWMiz0ow76MY6mM5ELWxyDSjgFQmwLI0TsWAWIJQJpbfUamQnS2IUsWUrSMaN2+zvJVwmnq9vhGiIZVKkUr9bQjj35IHH3yQQqHAbrvtlux75zvfSaFQ4IEHHnhDLIQbNmzgt7/97UYGRzC6209+8hOmTp3KoYceynnnnUc+Zix7A7LZcv8Pkv32248nn3ySJ598kocffpiDDjqIQw89lNWrVwNmFrh48eJJePQ999wTpRQrVqxgbGyM3t7eSVAM27Y3suCecsop/P73v2fdunWAUQxPOukkRMxDHIZcf/31HHfccck1xx13HNdff32C1X7yySfZa6+9EsV+ovT397N+/Xre/e53v26Z3/Oe91Aqlfjzn//Mtddeu0mrPcAf//hHDjzwQKZPn04+n+eEE05gaGiIctngFFesWME73jHZQ3/i7zVr1pDL5ZL09a9/nYGBAXp6evj4xz8+6dhFF100CV4EsP322yfb3d3dSTlfT15d98uXL2fPPfectG/PPffkxRdfnISDfzWcZvfdd2f58uXJ75NPPjnxV+jv7+e3v/3tpLqrVqukI8rFV0smk6FSqbxmnuv1OuPj45NSvWKcsEQmD5m8UU4zeaOsRPvjpLQ2eHswFq7RvsbHJ9eKaO5Eds1DdMxGtHYx4BcRbW14QhNWFGFFsTYssiYsUYvePunoNSRtExJeZF3KOsBHITIuVR0SoCHtUNQ+Re1TjRihRdrBizH5mRR5BYV0nUK6TmkwxRRZZ6iWodBZpX8gT3dziXVBlnVBlvZpZaQdcdWH0pQ1tjpHzrDxb103LDi6XiJUscXeQLXQysCTwsB8PMMA0TYN2T4D2T4D0drFqF/GQ7EhKFOVgnVhkTELBi3BoCXIaoEvMPheyzbKRbrJWDtjXHKqyeyLcc+AHzGDCDfGIUcY6PY2RFs7dM2kR1UQM6chZk6jZJnnjFiw0h+B6VswqjyEKxOseygEVmuEZ/Yii7PjNhyEo9UKXa+CVgQqxJU2bowxVqHJi1+H0Ed2zEZOmY1om8ZaXaMYOBQDhx5vBJHLMSZChmyBlTJtkXV9sq5v6jJmHlIqYW2yuufTr6r0qyqivY1RQuwZLZEDuB85harEiq/DANkylXFVRzTn8RFISyf1RoKXt8xE16sahXTx9vQN5ukbzDOtuchQkKKQjZxcA89Mdvz6JMuv7NyCdbaBmalQmHMTfLPpS6KpBdHUavpbKlI+o3yL5s6EAQYpzfiKrPix4ztSQuAhC1OQbdOQhSnUlJU41PpFwaj2We8IXnYFViGFlYNCqBOH2ulOhanaM6tz5fEE5qNH+xqrL9VS4nSKVgklbiITxgdh0LDYR/snHXNc046hb8ZK4DX8DHwP0VRA5loRmTw1HTJkQb/U9EvNiF9ifVBkbViCfN5Y4kfWmzqPVxl8z6yAxIw0QppnppuSd1fi8xD7jORazEQmzodlG8fUoG7Gbts0ZEsX2guTNGoJxkcy9DgCN2WCouWVJqsU7ZZHu+XRLHzIGEacuJ6wbPTIOpPGBxHNHehShXW2zdTQpzU0fTdp42icEQambSJGog26jpjRhZjRhdVtDAhJH2oqgJQm323TKA+4NIeQVZhVOG3axrzwjCO5zLfTazvkpvvkptRwIl+YUInEN8ZDI5oyiFTkO5TOvub35X+rfOMb30hw8XH6xje+8Xfds6+vj87Ozo32d3Z20tfX94bucf3115PP5xMDZCzHHnssN910E/feey/nnnsuv/jFLzY65/Vks+X+HyRNTU2ToCs777wzhUKBq6++mosuugitdaKAv1pea/+mZMcdd2Tx4sXccMMNHHzwwTz99NP85je/SY7feeedrFu3jmOOOWbSdWEY8vvf/55DDz2UTLwMuwn5W8deLbZtc/zxx3Peeefx8MMPT4IQxbJ69WoOO+wwPvnJT3LhhRfS1tbGX/7yFz7+8Y/jR3zOm6qbiUtt06ZN48knn0x+t7W1JddeffXVk2bWAFbM+hDJxElM/BylXj9ax6sdg18vn39LJl53wgkn8KUvfYkHH3yQBx98kDlz5rDXXnslxzs6OhgZGdnkfYaHh5k3b95rPucb3/gGX/3qVyftO3v/7TnngB2gVDHc0XO6Gtszp6BHDcZSjVT4cOcuZJA0Y+FfdaHhL0+5qGGjeKnhkgmaojQEmk+68ynf9AALvZnJ8z4TTEEAjg4IPMn0UDK9MMrIBvPREA+Mc3AwHVvD+H0DvDuYjgUUHynxnsBYjWwNrdQZf6jILrUsg7ZN36/GGbOm8ELd8LUfsPt67vjLFI7aqoc/Pz+D/Xday6+fnMnBc83E98GXupmfKdKUM6w5/o1XGJaSUgXR3mIy6wfoYgWRdtBBiC5W+XDHTtiIZFLi/+RyQ0vX0oyuewY68Ko+dkJmAR0B7Eg382WJE/VUFvhVvIhbekw4TLcrDCyz6VryXcL+caz2JrAswv5xAKzWLFppwoEydneeD+W3QQPe96L2dGzCvjFkIcPo/RXSLcYS/ql6NwM/fBaAhWGBfp2iHY/pYgaVy2/kEDWT8ecrCda2RQVUni0jf/J9wv4xwyWuFWF/pFxPbUXXPcK+MewZbRxT2I5ObbNBBPhLvmva0LVRA+PIzhbU4BgoM2n7aC3DtILpT2eW51K74zEOrXZh41EeNMqjbUVMSz+8CB3xfgs7oqqMnnta3Sg26y9/jmNqeZb/RLMof3niV4BWhgMeECkXXfc4Sk9h/CeP02K1URxO0xLVmy41LHqq6iNcC+FYbLhXsdViQ2P5q2dncuDMXh5Z18Wca69AF6sgDbOTzJuJtg4UeAGH2DbjforSeBr/x5cleVLjZeTUNvR4ydTdvC6oe6iREnL6FHPOhmGCdUVk1sJe8YJhOCpX8Z4fJLXdvUk+daUKjg11856bVghwoi6rA82H62m2mdKP1oINfwavnmOV03jHPKDzaAd2vvcuwnWDWNM7UP0jyM5W016RiNTdEQf+Hyg/MoSdjQI2AaldH4AgNOOltdAYOy15E1sA0KUKckobulRGjVWQbXnDe59yIYohoCtVRC4bceVr9qTAO7wafuSLkc0uZLoPbqAJli1HPPMisjWHGikh0k5S9yLlJPz3si0HgSLsG0e2R++VjIvqN8d03cfvKWJ3pJAt0XvclqjhElZnATVUNPlLO9RWBjitJq97ZYdpm1nmiDUhq4ZbEGjqlsAFepXpBxaakSV/paXna+iab8ZCsZo4pIpcFl2qkPr3y/nAwClcfN9UUlpwwHWXmrgJAJaFrtbRxSoi65r6AT5Vt1h7xYtJ+3T3fB1d9RGOhSr7yEIKXTf3aNkmZMMwuBr8H/6HCWglBdoLkanIOJB2ePesMk8/0oklNG6k3MfvAoAdPcn4bwxsNyM6CG65EXadjA9/O+St5Lk/++yz+dznPjdp32tZ7c8///yNvpGvlhhuvSnd7G/pcq+W2A/x1ca62IcPYNttt2X+/PnssssuPP744+y0005v6N6blfv/IRFCIKVMaCgXLVrE9ddfT7lcTpTG+++/HyklCxYsoFAo0N3dzUMPPcTee+8NGEfLZcuWbdTYJ598Mt/5zndYt24dBxxwADNnNhSra665hg996EOcc845k665+OKLueaaazj00EPZfvvtuf766/F9fyPrfT6fZ86cOdx9993st99+r1vOj33sY3z729/mmGOOSWBAE+Wxxx4jCAIuvfTSBKL0s5/9bNI5W2+9NY888shG18Vi2/ZGmH8wEJVXXnmFY4899nXz+Vriuu4bZp9ZtGgRf/nLXybte+CBB1iwYMGkCcVDDz006ZyHHnqIrbfeOvnd3t7O+973PpYsWcKDDz44yV8CzATuJz/5ySbz8Mwzz/DBD37wNfO4qZfcn7f8OPc/U6cubGqigxZVoyZsKqKDVhVQFaY/apo4s3kUHUVHveuHrbThobTHmDAvp5LMUpLGmS+l4cRD+/nNb2eyS/MQAyvMfQ48VaF9n3W3VhgabWLbsE5uWo2+dUYpf+mVDvaf0ctQf47nX57Cvl0b6B/Is/KVdg7cwgTCGu5rwg8kL73SwTbTB1m5rpVfFKcggeciA9Nh+2zPXfe/zMeP3Zn/uuBF3vMvO/Hrp1/imOO3BeDmi3s4sdLEHKnQGp75jxJSaGwLvMAooOa3ouqHWEJjSZeP4ZlIspFivvyqkFzWo1g2H0ZLwho/nUTtzKqQT+zRQ22DJLfQxlvvMb+zSDgeEEZ+430vNZMv1OjpK7DiOgcLo7yaO5ptiYl4mSFDgORjraMA/OEnZlxltSKgAxtY6RQI+8z1Hz25zg9+bKzBR0/vxe3LM33OGDvskuPHv5jJQc0DDPU3JUp13vJZ/3ILwQsBjp2m7ntYUmFb5mNYj/D+KaeJmh9ynOVR9R0yjs8L/2XKEyqNY7vUfY/nhPErSmvN4R8ep/asWZH7lxkey+9sY7v5G1ChYNXKNjKOn/TLP1wlqIk0SkBWaXI6pN/K8KKT4fM/Ne+ew46/md8c5/PpWxw+9YNyEulXadFg5KHK2iDLMfus43sPTefduoabCvn9T1qi46ZfWkBNCKYon1Fhc2fa5/KjtjF5ef4Vjt7F4alBmPtThRARNEI3Iro6NjwadvDh46s8c72hEXz4e14jgi1ZQurURIqy7GJKGKCQ+KKApc0EoyibKVkFFoZVqkrhCEP/WtbdND/UqBtLWPToNHWRQaI5cPFahB0pFEqz/2dc5Nw9QSm+cfZLOBrWSy+JtNqn62SFxcP/IZk9BXoGPGZOCVk36DGGWfqfmSozVHPZorPM2oE06+QMMkrjRAaLjkfNhNCS4IelqI9o6n5jomjG0hiOFWJbgrpfI99UZ6ykk3MsCYOeRiFx0Jy4fQ/utIZqsqMCa1oBwpAHftzGlp3DlIpVcvmAsTHzfSoU6tQqinWlHGmRx9MWFSGBNJZusO04tOEjqIsMnigYH5QohnBahjgySy1UvGS1J33igNklwg2mbmcekwOnlWy1xm3/ZZPVBk6X0gInmoxkNDy2sovUDxW9dhNprSnJFNMjxd0G1tnNfGDgFLLfuZond/w3WmWaZ37YUAhN7FmBJdNkUz7jVY/x0OWdh4/x69+ZmBUprVn984B+yyGlNTUhmBZ6vBjBpo4/p5XyX4YBwUtLXYTQUZRsRT2Cxq0Jshx0osPoSoesVrh4JvKvbuRl29Q4f3lxOrNlBUto7r4+zb9cwtsu6i3Eyr8ZCM5pp532usw0c+bM4amnnmLDhg0bHRsYGGDq1Kmv+5z77ruPFStWcPPNN7/uuTvttBOO4/Diiy9uVu7/t0m9Xk+WakZGRrjyyisplUoccYSJLnnsscdy3nnnceKJJ3L++eczMDDA6aefzvHHH590lM985jNcfPHFzJ8/n4ULF3LZZZdtknbp2GOP5ayzzuLqq6/mhhtuSPYPDAzwm9/8hl//+tdsu+22k6458cQTec973sPAwACnnXYa3/ve9/jQhz7E2WefTaFQ4KGHHuId73gHW221Feeffz6f/OQn6ezs5NBDD6VYLHL//fdPirQay8KFCxkcHCSb3fRS3rx58wiCgO9973scccQR3H///Vx11VWTzjn99NPZe++9ueyyyzjiiCO45557+N3vfve6s+Pzzz+fT3/60zQ3N3PooYdSr9d57LHHGBkZ2UjBfS2ZM2cOpVKJu+++m8WLF5PNZl+zLGeeeSa77rorF154IccccwwPPvggV1555SSGHjCTtm9+85u8733v46677uLnP/85v/3tbyedc/LJJ3P44YcThuEk/wAwrDhnn302IyMjkyZMq1atSiZ0ryWbesmF0qEK2FpT0AanbmlNmw4oCovsBG/LdNZH2oYnPK0VJSxCIchE5+TDgDanluCTH/51K3NEjUrF5dnAKA0v/jDE0Q4dTopyaLNgziCPre5iShTcqEemmFax6Zo1zgsvT2MLYM6CYe56YQbtQ2YS0dpZpjyW4sWxHG2jabbdoZ+tq4LcLs0EG4zG/OWLQ278oOSii/q4/uA6X/v6Bm44zOfbF5sIjj/ct8jqP4WsLeVpEgFrRYoAgQwaONoAAQG4aALADmH3Wb2T2ODuXT0NXTLc5oEQEEKLDhPHTU9IVi9rMWVbZVFXFikZUgod/Ejx63BqjPYVSFshQ6GLH/P4T2gngQk5P46NANxUgLQ0zog5qyQMTtYHdrfHkNLgxO/7UZZ3p8xkZdXaNvKux4svdRC8KNhBVqnVHAZqmSS/3c0lXhkvUJIS5YPUEQPlhMUsW0PUXOw2tQ8hjKJ733oDa5NoIvcIZgcettCUtMWym9IMSDOJm/VslaEwhXillfHQoUkGSKkZr5r+mdKKgjaTqqK2qSOYrWvsmKry3ZPuBeCWxR633DSVS9+5ltsfnGEYlDB5lnGAWgE5FC/+pYXDrRKhJVg/mCcVKQ8idrBF0I3PoHBIa8XXFvZz2YVGUfrBHmP8dOl0Pr1ND3c+PRN7gsKYOEP7sJWq84clKWY5ZTzfYlg6yInKpTbMKs1hkBxz0MmHuFt7uCqkqBzGpE1GKepCkEaxWky27rWqkAIajeAXT8+kEvXJnIL64yEj8gVSCD7/L2MI10LO7E7IzHXJTLDu/17AI8MdFAjNfx0mPO0venlcoXlwqJMMiu7Qw4+pHoFVOmPGS2jGS6AEMrLGx8qhDAwzUz005ykEutRkGJnic0KNM2E8rXqujf6n0kl/nJqqUvQsBJJmy+PhoSnYGjxPJO0QDJl3S0YoRoWNhYnXAKBiSGq0Hdd5XikUMCRjA5aDUobFcougjhQQaMF9K6dRjfyFnGtg2IKuIM0n3tGDDkCmhVmpjDqCDkiizi7UFUZDl50Lo/QMG7+XfstmduBx8X1TeXLHf+PXT/wHhD637HiBGVdRn01F9/RDgRLgSHhoaTu7TzEMe1rBM8PtdIY+PoIOQgaly7aBWW362iVDnH1UGV3zuf0XrUlftQKIzVV5HXLzjVkOmtmLCgUD/TksaShfXcuc1dZVpvmVJpbLJhbKMpng9Ve13wr5n4pQ29HRQUdHx+uet/vuuzM2NsYjjzySwIQffvhhxsbG2GOPPV73+muuuYadd96ZxYsXv+65zz77LL7vJ7DhNyKbMff/ILnjjjvo7u6mu7ub3XbbLWHEiR1ds9ksd955J8PDw+y666588IMf5N3vfjdXXnllco8zzzyTE044gZNOOondd9+dfD7P+9///o2e1dzczJFHHkkul+N973tfsj921t0UXn6//fYjn8/z4x//mPb2du655x5KpRL77LMPO++8M1dffXVixT/xxBO5/PLL+f73v88222zD4YcfzosvvrjRPWNpb29/TTjPDjvswGWXXcYll1zCtttuy4033rgRFm7PPffkqquu4rLLLmPx4sXccccdfPazn31N3HksJ598Mj/60Y+47rrr2G677dhnn3247rrr2GKLLf7mdRNljz324JOf/CTHHHMMU6ZM4Zvf/OZrnrvTTjvxs5/9jJ/+9Kdsu+22fOUrX+GCCy6Y5EwLph2XLVvGjjvumDj9HnzwwZPOOeCAA+ju7ubggw/eyHl2u+22Y5dddtloheOmm27ioIMOYvbs2W+4fAAVKaIkqYgoSYuKsCbvExI3G+BmQ5x0SEVIalGKj1exKNddSr5DJXBotnxq2jJOrcLwfxcIyIsA21LGQUuSWAMBPAFuNkA6iroUOOkQ6WjqElIZn1TGx3KMZbQuBY4bImzwq+Zzrj2F9hRZJKpYI6cl4ahHVgvCokeTFjRpYSznkdVVCN3gAY+cTuPfnoC6ENSEoC4ETkZhp0PslMJOKWrRSsVEHvGSlJNSNuuRcgKa0h6uDM1/ESaBbyxplsRDLShLSVlKKrKxHf+uCGmeI0SjHaRMUlmaaJdVz6Hm2ZTrLs3Sp+I5VDwHW5gPc0qGNDseJeXgpgKDQ0cbpRwIojqIHXDjssepKhvbTlphOQonrfCEqa/4/JoQjAuborYpS4tm18PRxvqbz9SpC0HKCXAwZZ/UL4WkgkVV21SkZfqasqhUDZtKawjemCSjNP6oNg6jUV4n5q8mBCUpaUqbqJs6ek6j3qwoSWraoi6Fed6wRbMSNCtBMKrIKAiqwvQHKUwSYtL2GDZ53VjpS8aVNO1m+oNFWVjURGPMlaJU0Rbl0MHDtHd8/1oUxbQ2oR+WpEVRWJSE4dZ3tEm2hmYFzVrQrEBXPXTFM5CPmMWm7oEXUBVGWa9N+B8nL3pWGJW3gjXp+KvHS7xdExP49Cf8rgtTd37UP+K+YsoikvdQ2g3IEJIVUcp65F2PfMqjFlqECLwJ+apL40fiCZJ6rsTjRTbqrBKNjYnvtLgccapH/4tRny2KyfbPnFJkNTSpEFUD5YHyNDqgkRRJ1NlKaFMRknrNoYakhqQuzP1TWtAq04lzdE0IytKkOJ++MGPQ/BY0iYBK2aVSdqlWXVNWEfVfTJ8qapP3nJYGKqZ00j/N/Rr1VpYWzaEm8CSB11hd1hPGop1SVITEF2bSVvkH8dz/b5eFCxdyyCGHcMopp/DQQw/x0EMPccopp3D44YdPcqbdeuutN4Ikj4+P8/Of/3yjWDVg2AwvuOACHnvsMVatWsXtt9/OUUcdxY477riRT9/fEqH/fw3f9X9cDjzwQBYuXMgVV1zxP52Vt0VOOeUUnn/++f827eP/lMyZM4czzjhjEkPQpqRSqTBt2jSuvfbaTTrS3H777Zx11lk888wzSCmp1+vMnz+fm2666U29AAC8tU+bjaCOLo0gCp3gR9tt0ww9JoBXo2W3U3GkRdZJsebpnxrnsIhlAzDsOZWicbqqVXjPh3/Mbz4/l0svK/JvO60F4KwnppDFYnHgsH/LAP9ZauOwasBW8w3FWm6XHJ++zSWPzdc/UOXTvzTbFx0+zqeXmkliEzb71m0OPmqMK35VQAGfOWSQq+6Yws41YzLecY8+bn94Ju9sGWBkLMus+SPc//w0FjWPAjBaStPZXsJOhYwOZln4yGXGCc6vJwxCE5lJCOpor0bL4mOxhMSJWEr6X/kdamzARKH068YJLg5fDyAl++/97+ztdPGKrnBiLc3NGZ/D6o3J6UpXYGs4ZZ9e0ud8xTi8xWwdMVsREXVi5GA7b8/TCVTI6mVRsLhq0TjOKYW661ZobUHkmznn7BVceKxROH+9xKUeWTJ/b5e55muLOOWc5Xz/oBJr7jZW6uXVAgcf1k/6nK9FjCn5RpkwrCNxNF6R72DGTifiShtPBax79pYon4aTXqSy6OKQyZ/tcv4h/8mRgXH4Pl/6/OzsuXztkiF2qAveNW89r7zUjh3BaXZ8+DxznQoTJhbtmwi9F7zXsEt86b3jXPmrFj61xzqavvvDBluOCgnXGzo6q3s+ulrkxH0u4ken5Hjgez7bzu+n7frIiBA7GVoOavVTiI4ZiFQTwc9/xOjvDCXt4yunMsOtUPIcdnv0XBOUSEozTmoRhKu5E10Z47cHLCEUgj3m9NL5y/9IItKaKK+24e0f7UN2zzfX1xsO8Loyih5cC8P92PscgxpcC24GteYZrIXRuI4dLmOHVSl5fI+vs9Xuw8l9vrasm/2qBv+927v6qA/AbStnJGw5M30D4/jg0qMNy0rEzISQhg8+EpHviBh02lAPLoXWjsSh0t7hQNMvvKqhKfVNpF+Ra204k8ZMQFGEXjllNmqkD5lrbdRLUDfnRMw/n9jrAg6rpylF1vIfsZ65dgt5YfPtTxewDjoakS2ghnoarDxaIdJ5w1CjFcKyjeNtxLAEEctTNJb1yDpD25vOYs3fLar7MeMM7mYa41dK/KsuMf4AwJ9ubGKn+X08+FI3c1MllBI8qvO4GjojPwMl4N3ntOJ88HRUZQxhu4ZffiLLUOjjX3cpz/ywzitkqAnBcX+9oMGWIyS6XkGtego5Z3uEm0aHAf++x0V89WOmPLpcxf3Uv6NG+wwz0Hg/or0Bwa2eey7XPzgdS8Mp954W9b+IYjZ6vwk3zQO7XcLChQP4Vcnq1W0Iocm6PsW6ye/taZcvnyzRY2X+fEOK/W4+iMy+mybHeCtlYec7Xv+kNyjL+x95/ZP+GzI8PMynP/3phH78ve99L1deeeWkGDxCiITYJJYf/vCHnHHGGfT29m5EcdnT08Nxxx3HM888Q6lUYubMmbznPe/hvPPOo62t7Q3nbTMs5/+YDA8P8/vf/5577rlnktX/n12+/e1vc+CBB9LU1MTvfvc7rr/++o3gLv8XRClFX18fl156KYVCgfe+972bPO+www7jxRdfZN26dcycOZPVq1dzzjnnvGnFHjAfV4iYGnxE6BsFRJntWLnUyjeMKBAFlPGNMhlmEt51fBOERwBah4bOTBq4iJ4QxFdF3PZaYYIsYaKGmoMaC5Hsl5AsscexbS0Er/aE0J6JHGnFNIm2sVJZjrEKC0sTCoFtmytDJdHaBM4yO4JJzCRRoScp12Cif06SmE3Eq5rrwsAopEkOnaQcE/9vap9WOlKk61H0zJTZjiXwkkitEmHoOGPlNGIqmZTf6DxkjPs2k4jgbyDaRJQPHZd9IoMHGCrBiMEmfpYQwjwnVk7ifmO7SVTZSWT6r3pefFiICYvx8b2UMgqZb5hMtA7ZKPuKSNG1GjeLKS6je/hRv9AI7MyrmENi/vgwiCg3HROVM8KFKyIqVaEb+UryGY0PbaziShi2HMtRRkmMKRLDwOQ77h9xX5l4v3ifHzGnBHVEPMGL86uVUWBj/v/X+IxbaDPulJ5Qy6+q96Bu6jZmF4Ikmqpwor4XTWLwDcMKoZvkVcd9Pxo3SRkmEhKEvqmbaDsZX/E+pZL9KLBNT9pEjjEMQnHfklajr8d5j+pTR+xFROMoeXbgNfLrR4w9ST8LG2WKx6+2EK6NrkfvFExEa4nxx1EItIiC0cUuDwioe9F9oveJDhFxXiNWnNh51tYmIHFiRIjyItx0QoMb36uGQkSxcUQmFRkfApAmpgOh3yhvFFFXxnUspClXHJ8AQLmESOy8Rjph0t+l0JNhHUFo4i6AiRHwD5D/KVjOm5G2trbX9H+LZVP281NPPZVTTz11k+fPnDnzTQei3JRsVu7/j8lOO+3EyMgIl1xyyRviWf1nkUceeYRvfvObFItF5s6dyxVXXLHJJa1/dlmzZg1bbLEFM2bM4Lrrrtsomu9EmRhnYMGCBZNiEbwpiT4oQikQVoNqUcgoFH30mheSUKmGciukCbgS08hBI/jKqyQERKQTTHxpC7kJPmMpksitsejkv570P1Zazb1exVQUGNytCo2yoEMzNZgIxRETWCHMhz66V/SB1In13YLQ5EhpjTVRwZ8Yql4pc82rqkCho2BdjYBdSpBg+xURH7UUky2p8b3B0E/G9SsliihAS6wQyEjxl9ZGz570e1Nak5p8TlKXcR60nNQPJgVWmviceL+0jBIVXx8rF5uQiU/WWjTaJKl7kw9h2UapFV7jGimi57Jxv7MmkwGEWiMcBwhQwYTjsZIZBw+K/2uVcP/HcCWtRWMiEDfkxHJFeZCYAG3JuJhYl/H5MXXoxOvjQFW2jYjHV7yCE+c3VszidtmEqMglEwxuWysxaTxBVO/x/ePAXzFVZJQ/YTlGwYzpMcWEfjDx+dE+rVU0GYkzomAiKUNcPimT8WSut6JBYBFGoztuYzXxdzxpkJGi6kT1qyfs15ah4RQWOi5f/Iy4feN3lmVv1GeFZZuJgYwYmoKGGUEjTLvS8CsQOvLxiDMstPEkntDeIn6vRnUulDKMOIQEIipbrHxHedG1WlJOkcomqyF6ZNT8L1awLdu8b+L3wsSxGWiUMNlJ6khEE0VrMqQ1KEFQsyaNv0n9JWpfBZP79Gb5XyubW+n/mLzZAEb/LPJqfPk/q7xe+8yZM+dti6j3WpKEEw99E0mzXomiOEbh0uPjQZ0mJ4VC40gLXa+YJXshTZh6MJESa5WE790SEsIQF4GK0Ac2EomIrIpE7qETJAhxEDgIdKBwkDgIUBo70prt6HqCsHEvTzFRrRW2se5LSxEoiXQ0ISQsKqEWieVeaWEslrHlLq6b2JIaW/tCn7TlYEmZOHTrWtnUVcyzPtGKCSAkKWGRQuJg8NESowzEJXeiJteeMhAnr2o+xE7KLKNjFADtVc0EAkjJaLYUtY8O6lAeQ+sQHYQI31g47ajuwCipRkGNVkx8f/JEBZBaoz2VQClMhFo/gV5hOSZ/QR3qZWxh4QgLrIbVl1rZ8MCLKAiXVqDDxOIJ0fODECtZjzFtk+giMVxFhabMMezIqybMJHgBKS3QnjbPdlKmPwaegYdhoFXaq5IWFrpURkR+HpPqDaLAXCW0O9qoiyiwWrxWIIQ2+fLrDchUXC/ReIHIcdHVZuzECmlQN4qYVzM8+eWxpF5FrLh7VWNRLhn+dl0vR/Vca4zDqJ/paJIRT0B1EDkI2yIaPxqBRqYlVkph6cYH39barCfVyoliqCPFMI4ngOM2oDqVMXStaoJA1Y3lNi6bDgMQE6LsxpGFoWGh96pRvIhKA5400dIfjzlpxrqlddIrUsLCEdFKnpTJu2nSdU7K1GucB6tuIgOXRxt1G6+CWbbJY3nctENcr7VyAmtLIt0KaQwIfsP5WtqG/0gKjRbmHRPQmDSHCOOwXDNJO9FKXBQEjvKoabdqHYEgpTShFOh6xcRdAHStZqCBkWVel0bQWuEgkLHPWOCbvFeL6NA3fa9WNIYBAFuQ0pFyH4/BqJ8nYzkqU6pL4gYKsSoqp3jVqqLvowNl+k+1xD9C3kq2nP8f5U0p91prPvGJT3DLLbcwMjLCE088scmIo2+FnHTSSYyOjnLbbbe9Lfd/M3LddddxxhlnbJKZ5p9dzj//fG677bZJPPH/jPJGsez/V2TFihXss88+vPjii+TzeZYuXcq5557LsmXLEkrRNypqzTNmw/fAq6Ez6xvbYwNGWY+OT8u0YwlJSjrmuuIoOp1tLNX6HlTK6KEN4NWZZeVRa3ppDZsJo5CTU3FwtSAbfWtyWprvZ+QQG47UaKFARkvUSJVm8jRpSThSo5UWALJaklWKcKhKPl7dr4VkJnwP/GFNTmm8uo0tFbVRm7wKqdXMxy9thQSBREYUkOHqp0z+tTJwEpis2Eflm5XrxJWNV2e4+ikYH4am5gY8yatNwtzPsJopKEGXTCHQdOKS0jpRapu0wNIQVhR6zfMNK9uroSyVMjqVAttlZrqNug5R66JQ5/FHVyn00CjUalCp0Kotwn6De8+oDhP5U8MU4aLW99GGQzjuAzFLjSYcD1CrnjaKRTpryhXVgU6loVIyilEmx5ymqUgEoVaNvhT1Ge24RokCcFxalUwsnl1WBt0/SE67pHSIX7MmMQSpNc80Jkq2a+pUKahXKET3CIdq5BUE49q0w0QZNLSpYehDvcJckSVY209atFDqT5HvfTFpU8DUd/96U66RftTaQQLPtKGjDSVq4EtUz3MmL1IaKERU73p8CColMkoZJ8hx25QhVkAn9CGqJXSlGAUTChqKbqUExXFU/wCseQZG+o3yPdSPSj8zuU/GVlhpVqaCUlwMTYu2sCIgkj+s8EoWTQoiqvXEgV2vecHEZJi4qlAcS6pQ5/Lg+5DOoEfHTbyCKJhRGJcthl8FEUQklW2UOVaSY/hIc1tjrCg1+ZxIWrCxon4IMMNuZgouOS1Ra/sQa180fXJ4YNKqgE6lDWQsLkdp1NRttPqpRzY02nl0CF0cR6RSpj3BtKOQ5ny/4TMTrh9NzNg2WbyKha01oZKEyjgtxyxIYKz7ulw3/bFSMpOk0mgDOtTUbMZVsYol0xBdr1Y91YhGHdWZvdMhBMtuN/UbBswLbYKHnzD3qXo4XTOgOBo9o4gujyfjJxgOSatoFWntcjMps2zTd+NJhOPiCMX4i5Kg3jCNBKFMLPitSqJGSqiyhyALA28sQNPfK/8MsJz/zfKmtIA77riD6667jqVLl9Lb28u3v/3tJEqjEIL29nYOOeQQnnrqqde/2Vss11133aS85HI5dt55Z375y1/+w/MyUQ466CAsy9qI2/zvlZNOOmkSE87bJffeey9CCFpbW6nVJmPtHnnkkUaUzs3yD5VzzjmHf/u3f0vCUR9++OEIIfiv//qv/+GcbZbNslk2y2bZLJvlf1LelOX+5Zdfpru7O+HwtG2bQw45hCVLDFtDX18fX/7ylzn88MNZs2bNW5/b15Hm5mZWrDBWrGKxyJIlSzj66KN59tln/0fw52vWrOHBBx/ktNNO45prruGd73znPzwPryVa6zccnAlM8Kpbb72VD3/4w8m+a6+9llmzZv2PtPX/z7J27Vp+/etfc/nll0/a/9GPfpTvfe97HHfccW/qfrLLRLTVlVF0eQzZPhNdHjbbXfPQI8ZSo4M6A94YEoEjHcMq0rkFWvnoIWMlpTwOtSpkm8BxCNGQcqhJsFIxNMRQUYLBrZaFoq4lTiaKKGpbESc1YBsW8kCAsGWCAw2EpiQlwjUUbYDZBvzIZuF2SEYtQSbn0TuSIzcnZF2vzeKpxqq8+pWpNGMmrLalsGYsMsvcTqqBK60WwXYNg0Z0bEPtP7GETJaN5fStoSuImE/KCDeD6nt5ErbaRxFG2FoJpJCkJ3Dhj8dY7bRAtHcb63vCQjLB8dN2EW0m7kWfN4YtLESr+a2bmo1VLrZEp1wQkqwGXYuYPDAWUQXksBIWEJm1ErhMIATKA9E9F2GnjDXTryKcBp1tA6Jj01cbxo/oH+XMReb42AZEKmd8A3qWGyttKk1KQ9o1Vl1HpUwEoyhPoW+2y2HkA9IxwzxfKWOZjJhc9IbVpGJfBU8l8C45fWtEzJ4S+oSR9diasz2qZzljhMiMg68lmYKPKEyJChObZV30+AiiewsIAkOb2m3KNdBrsYWlCLQwZYyx0VoZdpsov+rlJ2giYINwSTcHyO75jbqKre0RxEJ2zTNMOzEEi8i6XC4hO6eYcdkx00DjADl9q0Y/sGz0aJ9ZOXBcpNA4LRF0yBU4K6DJ8sm6PiqA0JeULAMfAei3LTOmtlhkGHH8KiLbArWyWbEBxJTpUT9qMlj055cj8nnIGYOCNWORKZudMpbmV48ViOB5EXzEspGFTrQXWZBjCJeTQo9tMBZ8J4VEkNIKO/J3CB2FhSCrBVgWctu9EZk8av3zDT8EyzaMMfVywiKk01ljjQ+CyeXxPbSUiJph0knef7Vi0sfVUE/iG2DPaENXzRhMi5CmqQGt6zxCJQiVZMA2QawIGuqUkCFyxiJ0cdA4xY/1I6bMavSZ0T5E1iWb8vFDQ1Ep52yfXB879wbLbsfe+TD0+CBqvJ8xeT8i4yanye75KPGyYTASEjF1dgKrcqe5lJ4xSp6cvV3iOK6DuhlXgC4O4khDYyuEgSpaQpNyAsYitpy6MKQIwpYmLsebXBn+78pmWM7fJ2+4lU466SROP/101qxZgxCCOXPmACYoTldXF11dXeywww588YtfpKenh4GBgeTap59+mv33359MJkN7ezunnnoqpVIDtxWGIZ/73OdoaWmhvb2dL3zhC5NwxzfccAPt7e3U6xNYI4AjjzySE044IfkthEjyMn/+fC666CKklJNWEkZGRjjhhBNobW0lm81y6KGHbsTRft111zFr1iyy2Szvf//7GRoaSo6tWrUKKeWkCKkA3/ve95g9e/akfC9ZsoTDDz+cT33qU9x8882Uy+VJ14yOjnLqqacydepU0uk02267LUuXLk2O33///eyzzz5ks1laW1s5+OCDGRkZ2WT7aK355je/ydy5c8lkMixevJhbbrklOR5b4O+880522WUXUqnUJmkkV65cyZZbbsmnPvUp1ATGgxNPPJFrr702+V2tVvnpT3+6UYCloaEhPvzhDzNjxgyy2SzbbbcdN91006RzisUixx57LE1NTXR3d/Od73yHfffd93UhNeeffz6zZs0ilUoxbdo0Pv3pT7/muUuWLKFQKHDXXXcB8Nxzz3HYYYeRy+WYOnUqxx9/PIODhvLtN7/5DS0tLUl5n3zySYQQfP7zn0/u94lPfCKZ2Fx33XW0tLRw5513snDhQnK5HIcccgi9vb0b5WHhwoWk02m23nrrSew+nudx2mmn0d3dTTqdZs6cOZP4/f9WWX/2s5+xePFiZsyYMel5733ve3nkkUd45ZVX/mY9vlpEodOk9pnI9pmIwhREx2yjXOXbEW3TTGrtYrRWpuhVqYV1ZOs088Fu7kR2zUN2zUN0zYYZ8xBTZ0PHNNYGRWTXFMaExmoWWM2CtdRZKX1KEmxb4aFxUKjAOKvJQoZhfKOMRdtFQmQhxRAeQ3iME2IBspChJqAiNDLnUI+wohIDcckpTbXk0ux61HoFnYFifDDN+GCaTruG44RIy0RuFJk8ItdqFIVM3qR8e0PZTzdB6FPyalT8Or4K8FUQUUX6iOYOZEsXuBnk9K0aadoC1gbjDImQ9bpGDclqaoxYFsPSZljaBqOtQaYtREsXNLcjp26BaOlCtJokO7cwCoqbQeQ7qAQ1Rrwion2mabuWbnNu5yzElFZERzuiayqrZYA9qw17Vht1KRi3JCVL8oquIufMYlB7ZuKkje+BJwTuNNcoexjqy3g7+R2XOdNMNfSwhCSIGD6Em0bkO0w9ZguIaVsiZixAds9nvaWoeTY1z2a1KiOmtDMuFGPSIp33CZQkZ/nkLB/ZOg2Ra0U0tyNybQg3gyhMRcxYQI+l6LEU7hYF+i2N2ymR2YJ5tu0iUk2I5g5EcwfYKcS0+azXVawtuqlFn7243kRzp0n5DmifCqkmRGsXzrxOKn02lT6bKUFIzbNxhDK46Il48aaCSZaDmLk1w8LBAvyqTPqEbOlCNLX9P/bOO96Oovz/75ktp9+ee9MLNfRAAClCQIEAEjoWEEU6SK8i0jtCKPKliCQBKRZUvghSpQihCEioMbSQ3m5uO/3s7szvj9ndc24SBL+iP/1+efI6r5x7dnZ35pmZ3WeeeZ7PB9nciRgyBtE1BtHciWwfafo4+nSNhRFjIZszdRcSkW6GdBaRaTGfbCvYCWTX2oihayOGjDH5I0qjlUZVFIulzwqVYGE5g9smSGR9hIZAmE9zoExYnJsykKbSMXkzlo0YMsKMM6WMTvyq6cehXdDcakJqMk3hfGlDRPMl2wrSir/HcyndbMoJC5Ewc0gkMvUyQiI7x5lP+0iWUqVfWix1zGe+P8ACXeFDWUMOaTOOh2qxHjojZIwkJHId5trNnWY+tA0zi9Rha5k+zrQh2keaBfHQkTByrbgeIt1s5nkqFz/P5NB10OUq2ldoX9GPTaXHYqlOYFsKxwrIKkgryKmAnArIKoXobEdkmk19mtqhqT0OYRLpZkTnOEQ2zUA5gQqx/4WbjJN8RcosoMyCs9uMo44xdIvA5ABECe+pHKJjJLJtBKJ9GCLbhuwah+waR9DnGcdINHHj3I86bJkYMoZKYJnIw0DEBmHNt3CExhHaPFs7mpEtBj6T0auzwf8zRH+O//4vymc27m+44QYuvvhiRo4cyZIlS3jllVdWK1MoFLjnnntYZ511aA/hmkqlErvvvjutra0xcdOTTz7JCSecEJ937bXXMm3aNO644w6ef/55enp6BoH+H3TQQQRBEGOJAnR3d/PQQw/xve99b431DYKAO+80WMiNdL2HHXYYr776Kg8++CAvvvgiWmv23HNPPM8ku7z88sscfvjhHH/88cyaNYudd96ZSy+9ND5/7Nix7LLLLvFuRSQRjmmcZKc106dP59vf/jbjx49nvfXWG5QUqpRijz324IUXXuDuu+/m3Xff5corr8SyTNzbrFmz+OpXv8pGG23Eiy++yPPPP8+UKVM+0dv+ox/9iOnTp3PLLbfwzjvvcOqpp/Ltb397NUils846iyuuuILZs2ez6aabDjr29ttvs/3223PQQQdxyy23DIrdPvTQQ3nuuediL/1vfvMbxo4duxoVcqVSYeLEiTz00EO8/fbbHH300Rx66KG8/PLLcZnTTjuNmTNn8uCDD/LEE0/w3HPP8Ze//GWN7Yrk/vvv57rrruO2227j/fff54EHHmCTTTZZY9lrrrmGM844g8cee4xdd92VJUuWMGnSJCZMmMCrr77Ko48+yrJly/j6178OwI477kg+n+f1100s47PPPktHR8cg3T3zzDNMmjQp/rtUKnHNNdfw85//nD/96U/Mnz+fM844Iz5+++23c+6553LZZZcxe/ZsLr/8cs4777x4TN544408+OCD/OpXv2LOnDncfffd8YL509r6pz/9iS233HK1do8ZM4bOzs7/Mfa/SGTq+MeRQRe9rFM5RCJDoBWeCoxXxUkYb79W9TKZNmNgNncicm30BiVEUxM1ETI4KlipKizVZfNCk1FymkEi0VogEg4VHVBDhd8VVRTCtanogIoOKKOQWiNcCw+NBwjHxGwnRUBSBAQlSIUx964TUOpzacVjoJhkoJgkl6liOeaF5wfSxD1bTh3KT9X/1mFOgfGiagKtBoWk6Vq5DjOnAmPQNXeaT66dfr9EBU2vquALwQpVpiAFBct84pkmMUmhdsJ4TMPvwk6YvnFTxpgJPdQ15ccGNY6LcFKhYZtDZLPQ0s5KPMSQNsSQNkNAJaAgYUlQgCHDKGgvhL40+leAyCVDTPZqqJfwe5R8KqQxElSA1hpXOiZ5ukFvUdlIF6K5k248aoFFLbBY4RcQ2SwVNAUpsBKmLxKOT8IxXtx49yNKzBUS2TKUPnz68BFtTRSERja56BBiMfo/Nvy0QubaKSsP0ukQlUg36C1h9Gk5xgMaeGaBNno4hb4Ehb4ErbJG2XNIWkEIY1irQ5ZGEnjIthGsDAPbI6QdnITpxxBtZtBiyU2Zj7TMXEs3G2MQDGpLlKgeIalE6DqBh8i2IrOtyHSzSQgPSZRUBfIE9EuLZbaNSJpk8sZt+pw2RijlvEnWLPWhB7rN/WzXGJVR/HeYQEsqbY6Feo10bOA+w7miQv1YTn0uReNHB6ZvamUiTHuDQuXFixaRylHQPiUp6JOYj19kpSqzVJUhkzL17F9udrSi5NpKmNwfQfXartntcVP1xahjdhhEpPNMk+GmiOoRerUhXCRk2wxmf803UJC+Ye+uFmxW2BLbUkipSSmz85REkQxJ6UiljE4itBzLLJ50qc+Mx2wrAAOBi6MN1K9ueO5ovxZD0aqB5ehKEZHM0IeHHNJmPh3Npj2J8LmQzJgFZq4DkevAHzBoYQZ4wEAbm8TeOgyrTDfTLxzcnCKR9WOwAT+QWFJhSUUVjUglEK6BMxBh3b+Qf2/5u0isrr/+eq6//voY8eOwww7j7rvvjplCi8Uiw4YN46GHHoqNvttvvz325mcyxnD4wx/+wJQpU1i8eDFdXV0MHz6ck08+mbPPPhsA3/cZN24cEydOjBNqjz/++JitC8xi48Ybb+SDDz5ACMGMGTP43ve+F9+jXC7jOA633nprTB7w/vvvs9566zFz5sw4tGjlypWMGjWKO++8k4MOOoiDDz6Y3t5eHnnkkbjd3/zmN3n00UfjhNpf/epXHHvssSxZsoREIsEbb7zB5ptvzkcffRQbaE888QSHHHIIixcvxrZtrr/+eu6//36ef/55AB5//HH22GMPZs+evUYIw4MPPpj58+fH5VeVxoTjYrFIR0cHTz31FNtuu21c5sgjj6RUKnHvvffyzDPPsPPOO/PAAw+wzz77xGWihNpbbrmFvfbai3POOWeQkRqd19vby/e+9z0233xzzj//fL7yla+w7777Mnr0aPbbb7+/ifDyta99jQ022IBrrrmGfD5Pe3s79957LwceeCAA/f39DB8+nKOOOmq1UJNIpk6dym233cbbb78dM+U2SpRQu2zZMu68804ee+yx2CA+//zzefnll3nsscfi8gsXLmTUqFHMmTOH9dZbj4kTJ3LwwQdz+umns99++7HVVltx0UUX0d3dHY/r2bNnM378+HisffDBB6y9ttnSvfnmm7n44otZutSEsIwePZqrrrpqUBjTpZdeyh/+8AdeeOEFTjrpJN555x2efPLJ1XIWPq2tEyZM4IADDuC8885b7dgWW2zBPvvswwUXXLBGPVar1dV2wH60yRHYwgo96AaVoobZCldgQmsw6CaXHVQFKdDFCuc+lKNL25SEphxjiEMFRV77JIXkxuNynHFLkUs2Wcbzr5ht8V1/kEMXipSfW8DMN0aw9TpLyK9MMC+kZ19kO+y18QKCquChD0ay9wYL8MuSJ+aO4GtbLACMAVNc4fL0ii52HbkYO6H4749GsrFf4cMQ5m2rdA8fDTSz2dhlPLZoOLt0LuWlJV1MWncRAI98OJK1gyoWmoTt82s7RQCkkXGbfTQpLSkLg+KSRHLmvgMIx0YXjdFz+R9aadKSKhpfaBJa8JGo4IdzIiEkN36/ieqfPyLx5fHkH5hN9qujqL2xkPxcs5hXvqRlA59Hnh3On92AJAbq0kOTog5DF6BxEZRQXLRvEZTmRw9mzX0QJMOyAZoqmn58rj/M5uwZpn8uXH8pC//azPB1+slOGc9x13dz4w59PPNEFx0Yj15brsTsfAsvJzVNWjIgDFZ+Uwh7OCAUAZpmLekXivP2LaB6S8hcgqseaonHVVZLCkLxoS6F40dy2/cSfDjD7Nquc8pwrr2uwAlbL6LwscX789vJ2R5OyEMwTaSoEuL0A+3YDBCwWJe58wjj2TxjmseVO/dw81NDGRAhDng4DodpY+h1i4DFusrP7j2Ab3zrPs5TNs/KLPNliOjS4NlLIWnSkm4RsFCXuWmtPgAeen8Uu49azCtzh/LqKsTYmVAvZaF5V+eZ8XWLhf9d5a8DLfwpqfDD60eoUNE8i/rTQZAO+62EQUTpUhbzpU+ntigLTVZLekRQH5NIFlOlqs08PTlQLPdMxZIoJu6+kmDAR9iCF/40jBQBYzv7cJLmGnMXtOHKgKedNDkF/VLTrAT90iyUTf8JBsLfe6WiRUnDMh0e7xVmlrgIvFCLSSQVVFwmGbY5ANJakBeKVm3RJ4JY60kky6jFcLBXTlwRI/8AJCetB4kEurePe281Xu6CNDtdUUieow1D7XLhk8bMxQAdz4dIt2kkXnjnrDb8G32hXh0EmXDMztNmYSOBfWuZOAF5h00WsfSDJkZumee9mW04VkD7ELMj399jFty2pXim1sq7lheOXxOK2BYur0oolukqx1UtNvtaPy891E5G+Pwu6VBpAKB0EKwd2PRLTbcI6MPjp6/+mO9OPB2AkSKJH0LsAgZ5B8HccL5dkamQLyRx7IBfqeYYEjeaTwDv6yJ3nNjB5TeVaFeS7fwSjhVQC6y41Nj1V/LQ+6NwNGyR6OP+oJkL593DP1vGtW/2uV1r7so3Prdr/afIPwyFufPOO3PLLbcAhkDp5ptvZo899uDPf/4zY8aMYfbs2Wy22Wax0Q2w/fbbo5Rizpw5JJNJlixZMsgotW2bLbfccpDBeNRRR7HVVluxaNEiRowYsZqnHExceOQBLpVKPPnkkxxzzDG0t7czZcoUZs+ejW3bfOlLX4rPaW9vZ/3112f27NkAzJ49m/32229QG7fddlseffTR+O99992XE044gd/97nd885vfZNq0aey8886xYQ9wxx138I1vfCPGKf/Wt77FmWeeyZw5c1h//fWZNWsWI0eO/ERs8lmzZnHQQQd9pj549913qVQq7LrrroN+r9VqbL755oN+W5PHd/78+eyyyy5ceumlnHrqqZ94n8MPP5yTTz6Zb3/727z44ov8+te/Xs1LHAQBV155Jb/85S9ZtGhRbExG/f/RRx/heR5bb11nn2tubh6UE3H55Zdz+eWXD2rfQQcdxPXXX89aa63F7rvvzp577smUKVMG4cBfe+21FItFXn31VdZaa63499dee42nn36abDa7Wps+/PBD1ltvPXbaaSeeeeYZTjvtNJ577jkuvfRSfvOb3/D888/T19dHV1cX48ePj89Lp9OxYQ8wbNgwli9fDsCKFStYsGABRxxxBEcddVRcxvf9mI3usMMOY9ddd2X99ddn9913Z6+99mK33XYD+NS2lsvleEG9qqRSKUql0hqPAVxxxRVcdNFFg347Z9JGnLvTJpBIGMjEas18BxOTHW0BK83Z01wqBFhkmHpUArVgObI9V8ebti2DppHNQLXGSdev5PoDPR64dxRbZExI2enXGzKfSdWRbJLp45mPhjNC1VhrSB8AE4ZVuGf2KJIKDthkAb94exQJDfuMX8BdbxgGxoSGtWo+UyYs4NG3RqEE7L/hAt5/u4Mvt5l+qFZs2q0q8+a1sUNrN0uXNrFhcoA35wwFYKehyygXXAIlKVYdzj9cmnYEAfjhS9ZxDFqI0pBKQLXGKTOSaDQWZjxNDdkbsaXBUQ8CxKiGkKkg4KQfL2VbfyR/fmUl+5SH8fu5Nbb1RpINsb4TWrNgpcXXRixh732GofMlhG1BKmGuDeb6UqJrPiKX5sxpKRwklx8e4XQLdM+AIS3yA4RrI9pbOOf2Kld+yxiyv79zJE2BYtZfm/jjByu47cQ2Lr8pwfFrLWH5ImMwLxnIsv0Gi5m862h0Xx6RSYIt0X0mjlpk02Bb5lg6xcl3JciRQQGXH6bjNutiBZFJIsesZeqkFOdcuYxv1cyC9YjrlvHTKTV++uBIRnqaLYd0MzCQxA+MQXbFcQkz9pRG2BZqRQ8inUKOXocrLjXIJ1d9tZe7Hx/KMVssILHVKEQiRAGp+ahFJjTUGjcM0TqM8w95iDu3L/Lm0x18c9xiWvYYFo5rFWPx64EiKl/BGtGOGDKKly4282CHtm5mfdTFBq297Pr15ljfBAGq38w32ZZDjhnPf12wmA2qSbYYtYxd92iHdJQHYLy/8TyrVMwxpethPsKMv9obC3G3GI1asByRTaALVTPPwORS+AGia5gZn0rx5sULGN/ZY+phaX729DC6fGP8TtliAUFZ8PrsoVTCnZC1U3mqnsX3d1uOsGT8rhWiHvKhqz4il0SEOxH+kjwybSPCPAk5tNXUxQsRexwH7XmgZIyoo6O5E/YjlmPGTdKB6BnmeYiWNoPaA9z84wQdAVRCu/zVN3oRCFJILtt7AB2YHT3hWuhSyJqcDtlfW5sN3KnjmDGaL8UQQSKbqR8DgmXdCMdCdrbG40AXCohUAjnGvD+00lQe/gteCPj05Dsj2cgd4JcvjWQ7tx8/kDy/dCgaGKfMYr+qJQdtuoD0pFGxToTjoJaZ8F6RSiBGjmThje/z4CNdbDtkBaWiy0XfS8QEVbq3DzluHP7Lr5sYeymQQ9r47sTTufO1a0O9VanddnF9tSUFeD5ynHkvzb1iDlXfouzZnH14LX5+idbmuC5y7XFce9lyzj1/ODoI+OslHxEoSdr1qHrmmf7Q+6PYd/MFqAq8/3YHp+/Xw79CVuM/+UL+LvmHjftMJsM669RjsCZOnEhzczO33347l156KVrrT0RT+XtQVjbffHM222wz7rrrLiZPnsxbb73F73//+0FlpJSD6rLpppvy+OOPc9VVVzFlypRP9C431vGzbGS4rsuhhx7K9OnT2X///bn33nsHeZx7enp44IEH8DwvXviAMXynTZvGVVddRSqVWsOV6/JpxxslihV/+OGHGTFixKBjichIC6VxkRXJkCFDGD58OL/4xS844ogjaGpqWuN99txzT4455hiOOOIIpkyZEodeNcq1117Lddddx/XXX88mm2xCJpPhlFNOoVYLCTgaXyIN0qj3Y489Ng6ZARg+fDi2bTNnzhyeeOIJnnzySY4//nh+/OMf8+yzz8be7R122IGHH36YX/3qV/zgBz8YpJ8pU6Zw1VVXrVbfYcPMC36nnXbijjvu4I033kBKyYYbbsikSZN49tln6e3tHRSSA6zmURdCxG2I+uP2228ftJAE4rCrLbbYgrlz5/LII4/w5JNP8vWvf51ddtmF+++/P95R+KS2dnR0fGLuRU9PD0OGDFnjMYBzzjmH0047bdBv3gXfNoZYGPKlK179eyPTpNKkSZitWQRUKqiqjyhXoRZGdtoSaj5CabTnkcZCFwo4OhtDIGawDFZ+qC9bGzbNIAxjUJ7A0eBqUDXzkHJ0/Xcwxr2DJqiZc63wuNYC3w9f5sIQVllSEfjS4FKH9wJDbqW0YR5VWqCLZUTCNQZJaNwL1zckNkGA0Apd80njhsZ9OIbLVZNwZ1vmvCBAFIp1g01pMtgklGm7g8ZFYuk6866FJq3Ar0l0sWx2BVzj6412CLAttBRG11KQxDVcAEXjZRS2hSpWzVj0ArQXIBNFMiTQeWOYOzoZ/g9ZYaMLRVJaEniGrRcMFr7yBZTKDfeWsSFlSJbqfydJxh7SqC5ohSpWkVKgB/KxAZtt8BtmhYMuF0lp4qRYqOPgUyrHRqG2QkNOafRA3iRXAqrkk9AQlMJ+8ANjqFdrqLLxQctyFay8gQQtmJvUSla9rhGBV1hnVfKRhRIkDEwgQOBLLDQqEOhSPQGWIECXw2dbsYIeGCAbjWdPmnnVMH+0H5i5pXSIc07d+A11qz2PoKTRhSKq6iOlQFV9CPtC+OZ8USiaxajSKC3wPDOaXOnj6gjuUiBskI428yV+/mozHyoBWjaQNDUQwelKgLRr4FimvjWFlgHaDudG+MzQfhAvOgkC88yIiJ+iv8N2Ctsyc0UrRKh37Qdg143uCAbTC/s4F5opEdeFrtShRXU1wscPk4lLZXSxCgmD+6nzZUiGCdpS1o9phSp4yKSqjwNAF6rxGIvGhaqB8iJIVFMuocw6TAjDGdAoEo1fNvMYxzfPE8eP54tWGmvA7F4ltI7HvS6WEako0bUU4tjX4+N1qsRIkawzFTsJdCHigjBjSNcCxICZ69IyIY+W0KhixRBnVT1IJuvzur+fViXQQYCQgui1HD2rozZr3zxfLaHrOv8ny7+a7+V/m3zuJFZCCKSUlMtmwmy44YbceeedFIvF2LCcOXMmUkrWW289mpubGTZsGC+99BI77rgjYDycr7322mrx3EceeSTXXXcdixYtYpdddmHUqFGfWh/LsgbVxfd9Xn755UFhOe+99x4bbLBBXGZV2Mo1wVgeeeSRbLzxxtx88814nsf+++8fH7vnnnsYOXLkahj9f/zjH7niiiu47LLL2HTTTVm4cCHvvffeGr33m266KX/84x9X87KuSTbccEMSiQTz589fzQj9LJJKpXjooYfYc889mTx5Mo8//ngMsdgolmVx6KGHcvXVVw8KW2qU5557jn322SdGbFFK8f7778f6XXvttXEchz//+c9x/w0MDPD+++/HdW9ra6OtrW2N9dx7773Ze++9+f73v8/48eN566234nGy9dZbc+KJJzJ58mQsy4oTYrfYYos4R+CTGF+juPvrr7+eSZMmIYRg0qRJXHHFFfT29g5ig/006erqYsSIEXz00Ucccsghn1iuqamJb3zjG3zjG9/gwAMPZPfdd6enp4e2tra/2dbNN9+cd999d7XrVSoVPvzww9V2axolkUistuCrHhm2zU3VCWfclInNbMR4l5JptxwDgCUkVx82A2vx+5BrjdEXUArVtyRGzHjr1l9ijV+LeY8U2Xmceeks+8AlISS9dpJk2uOtAJrLNqMyxhhLj0/y6scVspbFgRtkePXDChnLZv8NErw238zlFBadvkV6/RQLPjIvovSEHK9+lGTjHmPkbLjucj7sb2aEU0QrQUdHgblLW2l1zYutVHRpai2jlaDWbeEceVbcThoWNSb2uT826O699XgsUfd2XnXU3ai+pSaOWgWm7Q3lsWxev/FiWp2hLNBlKiLNCl3BEzal0CiZ49h4aFo39HG+exIi04IOyW5E2niKdaEXXS0i24ajy3l+dfuJeIHPJSf80hzvXYqdyqGLPQSP/BqRSiKGdNLPnNg7WRGCqmWRt2CZriDX3YwPxLvk1tOsXG7as0K6bLGRi/3dkxFu0lDca4VIpM19/Fqd/Mivcf/PTsJXAY60uejksC75bkQqZwikwjhj4aQo/dft+CFD8MKggL3JWiz+Y57mQOKmfap9daxt+7BTw/EX1Mm8tEIHHt03/tyUGdnCYkvjdEico86uY/FrhdVjwq9EyzDQindumEpymzFU/lxDWhr3RPNsFY4be+/9t57GWmdLsBxqN11EZ4sZbyv707goKlUH97TLQxIrEy+u+kwonmwdjupbSu6qe1lp2UhL4xx7Voy8JCzbYOEnM+Z8y47ZYHVYV5wElPNkxr+BtdPXUfPfQXSMRBd6EM1d4RwL6iykKjDe8Gum0j4mNPQkfNTv0xqYxaGQ4Jcli2yHcmizucUMFSHZ4Nu7ItLNBkElRGYSYd6NLuWRHaNQ3QuQXeOwP3wdmtri46J1RL1djdj7MIgwKSILQ0hEpnnQXDFl6kzBwnZ595Yf0yoShLQY/Nlbzki7ibSwkKM6cXaaDKkcumdxnJ+gi/1hEu1QM+7KhgRMpHJmLoJJlM40o4v96IHl2CqAWsX0N6B6Fpvy4TiLcggS83+MWwwN6g8hm6ti9YAdho/hmQVJVUchcYKW03ZFbvaVGEFI57vjhXzUj8MWXM68X/u83dNOWQrWP+5UM9fAMM+W8zhDRyKHrQupnBmf06433npAF0okfnCdeU44CXSh1+QIhGg57Y+cw4vvmvfo5qefadC3wutGzxS0Yq1rrqFvxiy8ikXVN449SwmC0MD/yNGkth2JLpbpnp3AOXh3vpB/f/mHjftqtRrHGff29nLTTTdRKBSYMmUKAIcccggXXHAB3/3ud7nwwgtZsWIFJ554IoceeihdXWaQn3zyyVx55ZWsu+66bLDBBkydOnWNhFGHHHIIZ5xxBrfffjt33XXXase11nFdyuUyTzzxBI899hjnn38+AOuuuy777LMPRx11FLfddhu5XI4f/OAHjBgxIo5DP+mkk9huu+24+uqr2XfffXn88ccHheREssEGG7DNNttw9tlnc/jhhw/ytN9xxx0ceOCBbLzxxoPOGTNmDGeffTYPP/ww++yzDzvuuCMHHHAAU6dOZZ111uGvf/0rQgh23313zjnnHDbZZBOOP/54jj32WFzX5emnn+aggw6io6Nj0HVzuRxnnHEGp556KkopvvzlLzMwMMALL7xANptdDdFmTZLJZHj44YfZY4892GOPPXj00UfXGMZyySWXcOaZZ67Raw+wzjrr8Jvf/IYXXniB1tZWpk6dytKlS2PjPpfL8d3vfpczzzyTtrY2Ojs7ueCCC5ANjJ9rkhkzZhAEAV/60pdIp9P8/Oc/J5VKMWbMmEHltt12Wx555BF23313bNvm1FNP5fvf/z633357HBrV0dHBBx98wC9+8Qtuv/12LMuiubmZCRMmcPfdd3PDDTcAxuA/6KCD8DyPnXba6VN12CgXXnghJ510Ek1NTeyxxx5Uq1VeffVVent7Oe2007juuusYNmwYEyZMQErJr3/9a4YOHUpLS8untnXy5MkceeSRBEEQ7wSAWYQmEolBIW6fRSKoPhFRyIess0g5mMnQTpAMyZ0cYRlGzkIvwrYhE76gI8M48KFWIQhf8gEQ8T6V8alpA2HpJAPkANgoygVz7ZbwHKuBWdVp+A4mftnRGh2omPZdODaOhibbvCD7lqXotCusrKRYb3Q3Cxa2MKypwAd582LbYuQytIJq0aEWWOh8t3mpe9U4YRVCBlOvZvRRKZK2E/UEUkD1L0cvnw/tYQx3vtsk8omwbwLfxMALTU0FFKSkQkC/BemQ1lJqaNICVQmTUStFk7DqpuJkXkMbb8dGviMstNR1IwkMm2lEIBR6T/u0h0ibl7YSYeiAgIKqxSRAuqLibXgFiJSL7l9m7h3BUEYoGyFhkS7lEW6KJidD0nJQWqO655kytbKBanRTMTQh0qcfn2IYC1/WHviBSYgWxtNYCSw6s6W4LVFSp/Br6PKAMWptl54wMly0NVERHjLroPqXD1qM6kJ9d0ukmqgSIDIpoGZgN+NQGAlWQ2KoUmbXxLb4sNeMlQ2HreQvS4cwOtuPWj7XLDRCoqEIqlSFi+LlNqxVM+NZl/rqsIMQQoqGISuVPCLqq6iPw+ReXa0aVthCr0Hi8WtmXIHpb7+GaOo0bfBreFpQy4fzVwtKBKy0bcoCZFpilxTNgcIK53hHokLZs00iar4Pkml0X7dJKI6QWnqWops6YNkC838qa8Z00DDOo/kRGsL4tRg6E6h7mbVCV8sIf+iguRKNlagtulamrAPyEnrDiR0EipL2qekAdAq9bB5kW2DFkjqbdN9Ks5BMN5tnllJGj1GSalSHQq9J4E3mwoToGiocJ7p/edwmkWyK2+nNy6PD2yyxBYtWNLHchVxbBb9qMaycxELjhsa+p6SpX7EfrTzjMQ/8OvOv5SASGXTZY7nl0Bl4CGWZRWKkWxFCi+b7UOJDg1yWyJj4+obNVF3sQ2RajFOheQiqt36NebNbGe17eAjUkvdMUq6TMAuhKGk700ZRWvg1s3tnCU2gDcRn9DaOsxY8nxS2eR78C+SLsJx/TP5hwNJHH32UYcOGMWzYML70pS/FiDiRMZROp3nsscfo6elhq6224sADD+SrX/0qN910U3yN008/ne985zscdthhbLvttuRyudXi3sF4Og844ACy2ewaCZwGBgbiumywwQZce+21XHzxxZx77rlxmenTpzNx4kT22msvtt12W7TW/OEPf4jDLLbZZht+9rOf8ZOf/IQJEybw+OOP86Mf/WiNbT/iiCOo1Wocfvjh8W+vvfYab7zxBgcccMBq5XO5HLvttht33HEHYBBnttpqK771rW+x4YYbctZZZ8VoOOuttx6PP/44b7zxBltvvTXbbrst//3f/x17npVSg7zQl1xyCeeffz5XXHEFG2ywAZMnT+b3v/894yKq6s8g2WyWRx55JEYQWhW6E0xIUkdHxyca4ueddx5bbLEFkydPZqeddmLo0KGr9dXUqVPZdttt2Wuvvdhll13YfvvtY8jIT5KWlhZuv/12tt9++3hX4/e///0aFxnbb789Dz/8MOeddx433ngjw4cPZ+bMmQRBwOTJk9l44405+eSTaW5uHoQItPPOOxMEQTx2W1tb2XDDDRkyZEi8OPmscuSRR/Kzn/2MGTNmsMkmmzBp0iRmzJgR90c2m+Wqq65iyy23ZKuttoqTxaWUn9rWPffcE8dxePLJJwfd87777uOQQw4hnU7/XXWN0VjshHlJ224I/+jEx8xxFy/wzUcHprybrBtwERqI5cR/ayDe6w0xKgUGHUZoTEhMeDhCZxBCEIQJcciGpF4p8LU2HwxWO1KYJD8BaEWAwWoOtMBNmMQwVwQEniTl+FRrNkmtSGoVM+JGIQrCTcWIQcJNxR8SmbidIpnBVwE15VFTfohWEyJyREg1iazRV6QTy0ah45eVHb6zLG22vJ1QByp+m0pjAIbIJMJxzd+Oa4wr26DiBFrhh55bLMcYm2E/CSlNmJCUgxLooG4bWKv8HunfFNKmX1O5sP2hHsL2RbogkcRTHpXAoxzUwvabcoQIS0JGY8pFEoZRoU1olxRIRKwTGYZSBcq0Rbgpo8sQ4UQ4ZtFkhYnfBEEc2iKi42E/xn2YyBrvaYOxIKSu90/oBRcN/RVJhIDi1yQOBnkpRpWKxkoiZT7JJoR0sLUx5IXUBjfdbfjYbjjP7PoxJ2EMJsc1ugKEZYXnJM0YDMubMZY197bsGNlGCrBcbT4hApSjTfgaCpQPNSHwQtjFmm9RUWYsmbEdfhw3RvchkTb3Tqbq/AFS1uEaG/o6RmyJdB7WNW5fOF4GzZWoTIgKZeqSMqEkmAW9STwOE/qj50hU14SpI4k0JFNmYWI5dV2v2qeWbdCR7MSgnYV4nkd9Guk2/MikRCYFMilwNbhS4QBexaJWtahqSUVbMQqUH3rwcZNm7DruoPuIUCfCsUz4EQbnvlEnInrmOC4k0/E5gyeyNr+FOzm6VqmjAjkJ0gmPbmnTa1mmj5INfRV93BRWxFYcQuGuKtFzFssiQNSdFv9k0Vp/bp//i/J3ee5POeWUQVjkM2bMYMaMGZ963iabbMJTTz31yZUI0WQ+CSmlUZYsWcIhhxyyWmjBYYcdFqPi/C1pbW1do9e/UQ4//PBBBjuYBcia6rLxxhuz1VZbxb9NnDjxbw6mRjjPtra2Qdjxq8qkSZOYOXPmGo8tX758UH6BEIKTTjrpE7Hfd9pppzXW68ILL+TCCy+M/85ms4Pu+UnnRbLvvvsOOt7W1rZaONKqksvluOeeerZ9sVjkoosu4uijj/6b9/lbjLwRglMkO+644yAuhXXXXfdT2YqvueYarrnmmkG/zZo1a7Vyaxprq+oBDOLRwQcfvMZ7HXXUUYOSbVe91t9qq2VZ/PCHP2Tq1KlMnjwZMEm8999//2r8C59FYo9gRG4ysBId+IZ8pdiQPOWmaHLDLXmEOdbfbV69OS8uo8t58F0oFbCFhMBg0gehc3JVY9PRoBH4vnlpaM8jicRFoqs+CSQuAl3xSYYvlgQSG9C1II6DRWmSGuzQQC2XHFKOx8paEstRFGoOXa0FitUQXSbr41clvm+MSd2/PLx/ddCLVAee8axaxtOZc9K40jbGKaHHL6K2jyQ5eIGVEJYxVoTEF2GMOcShB5Y2HxQGnjDaPrcT6FpIW1/JG0+on4JynqSVMOFBYdiDrhYNxGChF12uGJzyiNAqIqsyYdh18TwsDEZ6FC4TLXd1/3LjBQx3cWKvomWbnYxaBaQ0+hB2/RyohzZExk0EgQiGCCccB7pq6ueLekRHFO6g891mJ0IpE3ZQ7ANhGS/zGrx6utFzL6UJgQHzdzqHixXvZqigrrdYKkUoF4zeMbHgZcw4cJIGBjGZ9kx/R577cIcKzLgRbsq0BdBKoAeWG6MVzCKilDcQh0JCqT9eGOv84BwaXSiY9vR3o5MZMwZDSEqtg/ruTHgtXwu8cui5V2bB5AmoCMAWWC5kVECU5ZFJ1bBqCgZ6jX4qJTNGHMcYfWC84S3Loa8nHgsxjCXEZGk68MxuU+CZernF+u5J4DV48cPyq8wV7VfrZQBbCAKIUW0SwsaJBkfNh/5ec5/+vvpCbKDPXKsp3NUOfOMdb4ATFYGPliGkakR0VcqjB8IdiN6l9V2mELMfICgoVDiNKhLKnkXVgVSzh1MNyPT5SKFxrdBzH1hmvA8sr4/FUh4KfeE4kJBpRhU9KkLQQQAKU9734zK6VoZC3uyaWY5ZSFJPeEYKs3PaPARdLiFSOYKF9XDNfDnBBokBA/Pbv9zo37KhXIgfAVorAiGQlsayzeI+UBIhNISGfgIB1Rq66pmMoVXnzRfybymfe8z9P0t6enp4/PHHeeqppwZ5/f9/SKFQYPbs2fzkJz/hkksu+Zfeu7e3lxdeeIFnnnmGY4899l96789LXn/9df7617+y9dZb09/fz8UXmxjCRojOL+Rvy9FHH01vby/5fJ5cLsfcuXO5+eab/66dmlhC3GKRajLGY641JJvxEZnBuQ8DtSIKTcJyEMkcujkkaYmZQQ1jprAT6GQ6xD7XSF033pLCwkWS0FApOgSAQJNMh6EWjkUQwkAKx8JHU8Ng2kcAegbbXhqce2GMVl3xGJDQXzUG2ah1+njpr8NZK52nrzvNqKH9vL+kjbFJs+hbtiBHa3sJNxHgWgGibbjxlDcYGgizFNGlftMmv0p/rYhswLgX7aOMJy6Zi3Gt4zALiBkdbS2wkDQHAUnHpllBOgw1yktBSYKwhTHK05kQ77qKSJrQEKEVWgWGWMg1nvtK4MXY3loYDG+d8iHhGsQSrWkRTmxEixCCMaEhK13TxwiEFGQSof4rKXSxihwyZnAMdRQbDSbsJjTyVlYNlIgQos72WeyPvYq6kjdtshM0YZMTxoBJSQeRcElpn5QySbwCzUDR7OCJdHMdJ912450h/BrthOFEfXlSOosq+KYfohj9sO8ARHMnKIUjJLpi+sWylQk9C9sC1D3o0jIhOkHAmIwxZFauyNCsAlb2ZBg5bF0TriSlYSUuGsNctAxF9y9niA8FKXHcwISbRHNDK7Rlm3lTyZt+DEmdSIehMJZjQi2yWURzp5lfLUNhYLm5FmH4XGOiu5QkhCLZFrZbQWqFpNPXKATBQEAtL1lu2zECzeJilrKQbJRrNgvRiAU4+h9gxDjDXjtirGlb9yJw2szOHJj5YjmIwDP9Gy12on4iNKi9siHJUp55njTOFTBhK5GRLs2zoVkN3llKIM3C3rZg6ChEOodOZesx97lew6+RNJj2ulZBF3vqmPam0w1Ge7WEXjEv7GtDNAbhotZNmQVlZAgD7pg02jO6HfuWYnhbnhH9CZbPzxEoySKSWEqTCxfQAQLyfYgxm5gQRzsRs+9G4wQpkc0Jhgc1uqVLRQgzfqOFk5BQyaOLA4bwLNsGlmMMbS9cZNcCRLYV1bs0NuytkRuiug1c8LgNVnLf+6NwgI1GjDfjPMTbb3yu51QQT/NogQ/Ey+cqGiwLkXAoCusLhtr/EPmPMe632GILent7ueqqqwbBJv7/kBNOOIH77ruPfffddzUP/z9bDj/8cF555RVOP/30/2hj+JprrmHOnDm4rsvEiRN57rnnVssl+EI+WWzbHhRutvXWWw+CF/17JNpyF27SGI+YbWFdKw9OkvNreCpACuMZFGECrgnTCEOqAh/ROc68yEp9LK31I4ZuyYD8OL7MXK+PpHTYVCawLI0EfCR2IjROkkmK2scVEpF2KeuAlJCIhE0xDH51hMATFiLlUkVjC4HIJGkLoD1pjLW+pSmGW2WWlDJsvPYy5n/cyqjmPH8daAHgS+sswa9KgigeRkhjwJbz9fZEf8u6IejrAAsZe6sB4/VNNxsvW7WIbB9VP0cpltUG6E93sNAboN/KsCjI02ulKYReOAfoRyOzlvHklvqNMWInBiUkIi30wHJjIK7ivTZe/rIxHIYPM6RD7UP5SL2JHLEhAHlrKUllyIE+rK2E0euyXL2FbLKJ3qVSm0UVhImx6RbjSYzikdPNxggcWAlN7QghyNopqkHNeLTBGLL5bkQyh+ysLzg/1iVK2oy3udVuRPMGLBX9tNoudkLhSBWj5Qg3FcbBBzEhkkjmEEPG8FGI5S3HjGC56MEe1YDwFSWbNsTUy7ahLA1KiI6RKJbhpBoQYqLdDa8GbhK9cgGifRTWTpNY9nNDvjeus5ePV2QY21Q2sfDVYrzQiBcHxX6sYesy19Gs44Gb8uvkVZhE5ChsKDKCheOaRVIY5y6cFAQe2rbNeVqhvTI63xsb9yb/oYwcMgYhDPmapwVBmC2rfMFyXWOBkyYAnE4XqJGdq9GhwTwkUaZQc8IdhAIkkvX/o12B4gA61xbmFZTNzkFxIM4BEe0jzfmh3pBWaMy6cR/oatGEGkkJEb9GpQjJXPxc0V4R2VzPnRrQHiutBPlwHKyoDuCjyEjXMMuWC2b3qFape5G9MMk712Hi6t2UWVCUB+LFSJSvEi3iohj0OC8g8M2YdVPIrrFEBGi66hsoV2CJIxldTPCxo9kq5eHXLPBACUGTNIa5ryT09RhSsoh0LpGJd7UEhthNV33ed1w29ivklR33bTSGhXRMnkax3xBqpZuZq0sx1KUYyJtFdOCjq2Y+qO4FyA4DVJFflowXeLrQExv31MoxgpE1Yn0+cG22GasJBmosW1436qOlVVVoRCaFrtawtDaOn3+B/F9llv285O8isfpCvpAv5H+fLNvZoBQFVZNU5WZ9vJJF4EmSzR5eKdye9iRPLh+K1IYwZsroRVgJhbShtNKJy/i+JPBNCENvT5qk69NXSpJNGCNqyMgCgSdYvjhHwXPJa5vR6QKplDne258m4fj0lJOkrADXDuipJml2qiScMEm0nMAKt8JtS5GvuhS1zVLbJswr5Ihz2/nOFXO569RhnHD9Sm46tYOjpy7ntqNNWM7Zt1fZrwyj2vopFBKM28YkvFktLkFfHYLOanEJemoGwq7J5q6nhuELKITGx4lfXoJwJWrAR/saq82hOMfE+QO4WZ8PZg+hOV0hlfbIdVXoWZChubNMLdTtwsUtFLXN2LY+pNBkO6oEnqSSd0g1mbqoQFDsT9CxdomgAs+/M4KylGzfacIctAbbNS/tRYuaSTo+nm+x3m55nnnEGIbjknn6KwmGteXJtNVYOLeFPt9lXHsf0jLtWbSiiY5ciaETStjDsgQrimhfY3eZUKNgZRld09gjsgTLikx/cQTLpaJdSY6ebAwYv7uKMyxNsLLCyndcbNf0W9PaPn6fuc/AkiSZtioDK5JoLQg8iZCa7ry5z9prrQzbJbAcZWzpqmTlkgzj9jLX++mDbXy9awmPLhnGQTuEiDNSgK9j2Eu7zaY0V9G3LMV7+RbaqDFmZC8qhEytVU0fJDMelaJjcjWqFq/3tbPPf+8LwM773czjB2Q498EMl07uQySc2HvuLTILGmdYmhXPBXTumuTxe7PsuPmiON4dQLrgFwVe2cKrWOSGVgnCuKxorJT7HSoVh+b2MqkO34SyaUGtaJEZGUFAgtVkU/xQ4VUsnGRAtWjTsl6482ILSvOgeZcuCAKe+ZmNLwSvJQWpMNSiVwS4CI4btpTcxjalOTXS6zqUP6rRt8Tof8gGJcpLLZo2cyn9tcLij5rJZSsxEVbTOFMf2WSbnRMpkC0uQU+dJM9qcfG7qyZuvclFDdQQSYugz2so41Cd75kNmiwsezfL0I0LMbb8gvdbGT7azM1ayaZtIqhKgJVz8ZaZhZXTlUKVPYrvK1IjNH6fpvvjDJnmel2UL8kOq+HlJSsWZg27bNqjeVQl7h+7w8XvqdH3QQInaeZwx1dSqH5zH3urDREdQ1BvvMm1dznktGCJDMhpSUvoJEhr2EiVWHujlZRWOtgJRSXvkO0IGZsdTXGFS8tGAe6XN+Kyq1aS1ZLjtlkEdmhS+xpsgd8T4A53Cfo8/AFN/6IktapZCEhL0z6myLzZraQTHvlygnEbrCS/zDgmRj9zC8dteRZDcPnhXn1mgeUHiKSDyps2Vz6qkhhpM+/ZNFJqektJLKFJux7FqtnBca2ASmDRmq4wr5hjg86VrPXW4/yzZWjL35fn9rdkad/sz+1a/ynyb23ca6055phjuP/+++nt7eX1119nwoQJ/5R7NTK+/v+WGTNmcMopp6wRMej/gggh+N3vfvc3486/EIPK9Mtf/pLHHzcP2jPOOINarcaNN974d13n1lEGttTRJkyk3zJ48tlA02sLQpuPlII9Ji5A+xCUDXtsxBCZDJ2kWWXw670wZGV8qp/5xSyjMwXeKZvwkrWtIloLHDsgX3UZMWSAD5a3xfjzvdLmSyOXYicUL34wjK3HmO/PvT+CL40waFiWoyn0Jnirv40Jrd0kMj6FvgTDt6tSmWeMj+s/Hs4Pd+/hxkfaOX7rRdzw5xGc+pVl3PKUIbE6ZuuFvPtcB3ltkyTgLTeBEib2PQ7jb/g7SiP7xoQFxqkX2lp3vzUqRuwB4/FKDQa1YNeOZVRKDkJqlvRmGdpcpK+QZCAwL9CRWeOBXF5Is8RyCTCJwglV12UkKkyK3H2UYeZ9Zs6I+HeFQANdgUcNSausGfQUbWrfkajgByamVmvB0iDJ+q29fNzTEtd3rbY+FvQ0867rIDD3shva54t6InBJwnc2WwAKhAt3vma8hhITKqUENAXE19lS5plfM56/9Zv6eKnYxsaiQI+XJCV8UrZPOgwPerHaGutVCfAxW81DvYByuCsyobWbhSubGN6W55FiR3xPqQ1PApg46aSCnXPdLOhpptWt0FdLsCJMXk1qjURTkJKsUlSEJKMC1mvv5f6i4Yw4eosF/OrVUXxzu0VMf3FEmCcSemFDvXgCmgMY5XsMyxboLqZ500nExxPalEkoyCnNUltgY+oWUjyQDTTNKqBfWqy064nn7YFmSWj4RWMyo8yYDDB9UYzyODWM8H2WhzsGu6yzEGFp0uun4rwgXTNY+b/647BB41QLyIabGkVp2hYIU4dxnk9ZSKI9j0WOXG2+CMz3OEm+YdzYmByTxrkSndMY6PGVVA8rBtLxLsPooX2Uiw6eZzGvkmWxbULxbAbPMcOCa8YJGJ154ZwgbEf0vOoMcy+qQrLSMj/WwlyJQNTBfCw0Ky1hcheAjgD6LejwYe8D+0wOgC3RXlDf7fICXnmghfddh7Qy92wKNH3hfbxwTiyzoSg0px1UQPuKab9tHjTeE9qMjYKsP3+2FXmqYW6SAN4VaUb7JnF2g8QAT6tmOkN23z+6VW559WoIPG7d8hKsUF+OHszsO8bzGZ3NI6TG8yyTzA7xjmbn0DyvLuyiLCWbuP3MrjbxjSX/fIbarubxn17oM8qy/r9+btf6T5F/TfDU/1AeffRRZsyYwUMPPcSSJUu45pprEGGsqxCC9vZ2dt99d958881/ed1mzJgxqC7ZbJaJEyd+atLmP1N+85vf8JWvfIXW1lbS6TTrr78+hx9+OK+//vo//d4ff/wxQog1JqB+3rLTTjshhODKK69c7diee+6JEGJQkvD/RqlWq5x//vmcd9558W9nnXUW06dPZ+7cuf+ja6pPOy7CQqoh4mGVF7UOP0H4v2UpNAIpdIwI49oBjh0gQ9g1FZhY6/DS5sWdUEjbGLZ2QiEsjS+MZ9p2VexljiAUpa0JQmZT5QuUL0hrgSp6pLUgKGiyWqAKPhllDKOgoAlC5B4wL0tLG6NBhB8Z/m1hHpZR0qtu+EhtwmqicyKjo/EjpEZaCscJcKXCtgNsqbAxn3ofCIKGWGO/wbBXwhjWMfRnqPxIr6rhvACBLwxqUMoxcHgeAksqlBZYUpNwfNN+YXTvYIiOor8F5uVva/PdDQ1mWxtd2Jjv2jdEP9qvG/1WqBMrNLajXOFkwiOhFQltdCAx40FQDxlRn4DaES0YfCFIq4C0CvA8y8D3+dLkdYT3bDw7MjBtW+FhiHok9fEYhPqK9KeAQBhSqBYFLQqCgmlXUFBxGx3qbY2QjzSQkj5+ILFDAqwQJMr0WcN8WdPL1/RjXYRm0PhsHJONZRv7x9XGKM0qRVoptBKgDbEZvgJfoUsBumLOjhZBdni/SC829TEvQ72s6gmM6tI49qM6RseisWLp1edKdM6ga1rKzBFhPkJqHCfACXft7IbrOY2fsI7RPb1VhlBAfe54Df0d65p6fzbOqZQ2hnZCQ0ugaAogqxS6XDNkcVUfXQti4jhUOH8alKWojwMZ9p2rIaMFuuJBzY9J7aywbVHfRzoFcOxgtfnhhY4AP5AGeSts2xBcE8NvOfFYjcgBo+8AScw1tapfUzRU3nI0VSkIBLHh/6+QCGHs8/j8X5R/65j7Dz/8kGHDhsWEU7Zts/vuuzN9+nQAli5dyo9+9CP22msv5s+f/y+vX1NTE3PmzAEgn88zffp0vv71r/POO+/8y/MCzj77bK699lpOOukkLrroIkaOHMn8+fN5/vnn+eEPf/iJpFOfJlprgiD4RPKnz1NqtRqu+9kwdEeNGsX06dMHMdEuXryYp556Kmad/d8sv/nNb8hms+ywww7xb52dney2227ceuuta2Tj/SQ57IEDzZcoqS0i6IEwrjjc2laKdfY0CeSBUsx99ix090JEprkep0uIhpFMQ+DzzaMe5d5TXKbd3MoBY03YxJWLO0kKyWY1i82zvdxX7GAiARM3MF751LouP3yiEwfBRXt386PHurARXDB5Gec+bcJLLARfqUi+9rXl/PSJLkQ/HLnzEmY8PYyxNWO0nLD9In771Ej2G7KMOa8P4bDNF/DwzFHsNcSEsbz5ly7GDOnHSfr0rMhw1GMnEJFGxcQ3ShlimP4V5u9khrFbH40UgmqY/LZ41o9R+e44cU40taOWfliPubcT7L/vrXyVNmbLCt9WgqmlZib7NiFYKI94rfRLzem7L2W74442CYz57jqeOaCLPeh8L3LspuhCDxN2vYCa8pn9zLmh3peaxMxSnuCJhxGZBLR2ce1lyznlG6Y9f/h1syHc8QV/cqtcd14bJ//Y45rdV7D4BZPw93ZPO5N2XMyOF1+AbB+J6lsGXhXZMdKopH+FwSZvG47uXsiYHU+hr1KkNZll/uxbTZkV883xQg965UITwpJIcu1BDzAlZeItzi+m+dkpLtfd1MT6ErboWMHAQJL5RRM2dcjjIdKUVvV8gsBDl/Pc/G0DA7v9dlUef7qNg8eu4Ohbz68PaqXQy80iV3SOQ+e7OWP/e7jykBIv3pNi/VHdbDvjB/VxH+Kiq7f/hFhrUzMNbvsJX19kkhMfeWUUm4oic/7SwTGzzqsnF6uAYME75jLD1yf44FVmHvgQ7/gp9tlwAROv+2F9HCQy6N5Fcdwz6WYDK2jZBjs/rDflAixdiNxxf9SCdxEtnVDKmwTWUB+kcjE6kHBSvL77bay3pQljkknJjS8NZ5tKQFIESEdR7nV54LEuaqH9NtTXVIXg27dsihi+NrpniSHL6ltukHMAMk0GPlGHmPFvvgBDhkLG5DdEydPxfFHKkERFSEnhMdW31LQz04wQsj5XGsuEHBMikeH8PX7KdkrEBG+XrCgx1sqRweKiozXWlP1M4muht/7M0srkvACyfZRBNOpZDLlWiPDl3SSyfRQq341e+lGMTGNtvKO5RP8Ko4PepQZhx0mAUgSP3I9a0QvA679IssOE5bzy6jDm/CGD0oKX7DQJDaNDlm6NYOdzmthx8jdjzgvdtxyRCHObch1ov4r30//ig4dc/vCbVqpScNSfThicKF0roxbORo7ZxPzt17hsrxmcfXgYplessPnpZ6KWvBfH9G80YryJrwf2vv0mbt3yEhzgiNcvNoa+kOhqyUCCAqp3KS/vdBNDRheoFS0WLGwBIO16VH2j22mLh3HqoWXwfJ68N8veN/7/zXn8Qj6b/Nt67g877DBOPPFE5s+fjxCCsWPHAoZhc+jQoQwdOpQJEyZw9tlns2DBAlasWBGf+9Zbb/GVr3yFVCpFe3s7Rx999CBYxCAIOO2002hpaaG9vZ2zzjprEIzhXXfdRXt7O9VqPV4P4IADDuA73/lO/LcQIq7Luuuuy6WXXoqUctBOQm9vL9/5zndib/oee+zB+++/P+i6M2bMYPTo0aTTafbbbz9WrlwZH/v444+RUq4GcfiTn/yEMWPGoLXmpZde4uqrr2bq1KlMnTqVHXbYgXHjxjFp0iTOPfdc/vCHP3zmaz3zzDMIIXjsscfYcsstSSQSPPfcc1SrVU466SQ6OztJJpN8+ctf5pVXXvmbffjuu++y5557ks1m6erq4tBDD6W7uzs+vtNOO3HCCSdw2mmn0dHRwa677rrG61x88cV0dXUN2hXYa6+9WLly5SDYzhkzZrDbbrvR2dk56Py7776bLbfcklwux9ChQzn44INZvnz5oDIPPvgg6667LqlUip133pk777wTIcTfDI268MILmTBhAtOmTWP06NFks1mOO+44giDg6quvZujQoXR2dnLZZZcNOm/q1KlssskmZDIZRo0axfHHHz9ofB5++OFsuumm8fjzPI+JEycOYrv9xS9+wd57771anfbee2/uu+++T6zzGqWUN59KMfyU6t+rRXQl/NTKJKSLIyxcy4ZqCB1YKcaMkLpSNMltgQ9eLUbLsTC40F7FYJQLDG27H0icyHsujLtK+yrGuEZpQ1gVfo9+d0JsaKhv66tCEHoZTZiFcAU1AZZjEg6lazzflqOwHEWACL3vxnutq6bu2q+hq0Xz8avh3wUD2Vcrk7QMgVX00VVDOKUreVOuVjE6qFbMJ/BwQnQgB4kjdIjtrmPM9/hBLIXRZ9X0g66WzXUreQOnVymF8ItlXGmTslx0ecB8amUDtVjqj6EvCfxBD3lfmPtKNA4GdWXVl4AAtK/NfQLfLPYC35AEebU6Uo5SBgEFs3tpSUMEpf0wAbNWNjr0qkZ31YpJxBYgRJ2kLEJF0eGOQizlfPzRtbIhBSrnoVaJPdS6ZkjMtMIYzF7VfGrleNxSK4NfNZCffriTZOm63sK+plaGStlAVJbzYFsIWyBsE+qkdDhOogTciME5nCs6hIoMQhhKK0k4Hsqm/tVi2IdFdLVs2lUtxH3d+NHVkLSrXDB9Ws7Xx2TN6DZqr44W36FbWIfzLRpbOhBoHSMbDupnSiFZWqlg9FYcqH9qlTrxUimPLpVMubiOxbBtlRCG1Tc6COcRXs3MhXAeoVR9rsTnluvt8QxKTQKJrXXsXbZjXgOMvmuVOMk87mOl4uTmWE/VsF/icVAx9yrnw7lZMs+vasl8/Kop75XNtcJxJBIuwpYI2+zGCNvscjXKqrueesD0q64Uw/uVDOxmKW/6tVY2oTxCxztSRDCjgWccKlqZevoGdlb7VeOFTiUglTBEc+E4J9J549iQMt4FiDz4SAuRSJt+CmFcS9rCbYdUR91BE+3exe3yfHTNN2OmXOJfIV/g3P9j8m9r3N9www1cfPHFjBw5kiVLlqzRkCwUCtxzzz2ss846McFPqVRi9913p7W1NSbUevLJJznhhBPi86699lqmTZvGHXfcwfPPP09PTw+/+93v4uMHHXQQQRAMwqTv7u7moYce4nvf+94a6xsEAXfeeSdgkH0iOeyww3j11Vd58MEHefHFF2OCKM8zXr+XX36Zww8/nOOPP55Zs2ax8847c+mll8bnjx07ll122SXerYhk+vTpHHbYYQghuO+++8hmsxx//PFrrFsE2fdZrhXJWWedxRVXXMHs2bPZdNNNOeuss/jNb37DnXfeyV/+8hfWWWcdJk+eTE9PD2uSJUuWMGnSJCZMmMCrr77Ko48+yrJly/j6178+qNydd96JbdvMnDmT2267bdAxrTUnn3xy3E+N+Rau63LIIYcMasuMGTPWiF5Uq9W45JJLeOONN3jggQeYO3fuIJz6jz/+mAMPPJB9992XWbNmccwxxwxCovlb8uGHH/LII4/w6KOPct999zFt2jS+9rWvsXDhQp599lmuuuoqfvSjH/HSSy/F50gpufHGG3n77be58847eeqppzjrrLPi4zfeeCPFYjHelTjvvPPo7u7m5ptvjss899xzbLnllqvVZ+utt2bBggXMmzfvM9UfiAl0YuIWO/w/Il+xnPijdIBCG+bZkKyqkbQqgpcDjJcofLAq6kZ19MJQAqQ0ZFUKjPWhDSxj44slCvWh4XeFRq7y0BauGPTK1b424QuBQAoTNmJrk1infBnH+MfnhzBvQkiEdMxHWAYyMSKJsuyYdTfe8rVC1JGIECnChbdDXRKFekTnGBkUchN/0UbXdgLsULchUZH5XideUlrjqaBOOhTp33brWNjRtaVY5TcREoPJVSoQdV1YVsp6mei7aPg70nX0EhWy/onGRnSOlIO2yPUq/5vrGM+nRoTtSdRhMB03Hmt+GKIkbBP3LSQxmhDSGkRCFN0/QCPsEKFFiVhvMeGYk4CIPCr02mpfmyTpRuyORijAqN8jD7JlgqysMFwpHjfh2BFhPwnLiYniBtXVjuaQaKjXKvNTyobxJgfXp6HPFQwK8RrUv9EXy6pfC+r3cuo6RykzFhOuQdNpINyK50xEvhWR2DXqSjTUcdBcifQSkbCZawVoE1JGFDKlCFbVf7jbEj2XYo+3tAxaT/w8GkwmF+tbyphYbdX+i8dvWB8CE2qDMmGE2h+sV9kQOhXrNxHqJ5q/jf3oJMLrC5QS9anXqLdojkX1aYAXpVoLPwYGVzgRAaFd16XlgB/Un6OiXkPt18x5EUkX4PVpKj2Dyakaw8nM8yPaiXT4V4jS+nP7/F+Uf9uwnObmZnK5HJZlMXTo0Pj3hx56iGzWbNsWi0WGDRvGQw89FDON3nPPPZTLZe666y4yGZO4ddNNNzFlyhSuuuoqurq6uP766znnnHNiFtlbb72Vxx57LL5HKpXi4IMPZvr06Rx00EHxdUeOHBmzlwL09/fHdSmXyziOw09/+lPWXttsV77//vs8+OCDzJw5Mw4tuueeexg1ahQPPPAABx10EDfccAOTJ0+ODbn11luPF154gUcffTS+z5FHHsmxxx7L1KlTSSQSvPHGG8yaNSuO73/vvfdYa621BoXOTJ06lfPPr29TL1q0iObm5k+9ViQXX3xx7EkvFovccsstzJgxgz322AOA22+/nSeeeII77riDM888c7X+u+WWW9hiiy24/PLL49+mTZvGqFGjeO+991hvvfUAWGeddbj66qtXO9/3fb7zne/w6quvMnPmTEaOHLlamSOOOIIvf/nL3HDDDbz22mv09/fzta99bbV4+0aDf6211uLGG29k6623plAokM1mufXWW1l//fX58Y9/DMD666/P22+/vZrHfU2ilGLatGnkcjk23HBDdt55Z+bMmROzza6//vpcddVVPPPMM2yzzTYAg4jgxo0bxyWXXMJxxx0XG+/ZbJa7776bSZMmkcvluPbaa/njH/9Ic7PZdu7r66Ovr4/hw4evVp8RI0xy5ccff8yYMWNWO16tVlfbkVL9PSRcY1BqHRgPkOPWCYwaCHOSVgJfh17hUt5A40VlIwl8s+Xt12JWSRvjuYcoft2wknq+RRKTWCjC4OjI8+g0eHbr3404CJQw5EvRCygoKBpfTzJpEu+M596wTFYlMeRmDRnHriotjMfOskPvX7iTEoVQVIshyyk40ixy7IipsRKSR4Xb8oTe6kiEkDhCkgixux0ZYGGTaMDTT+h6PLCuFqHUZ7y8WiFKIZRiOfTcF/uhVsYRFpYl62EHfg1d9E2f+IFBxgh3OyLyJhkuLiQaFwmhk8F4fOsGi1baGLfhjg2ACP+PSYcqxlsrhSBhO7jSrsNChuEzsRdXqzApsH4PRwi0Mn0WvX6l1PVFV6VkxqNSBi+92G/uG/ikwiKqZEjMlCdiUi1zQBnPLMSEWy4CXaoBacNQG+pNhwasDnwol9ADYdhI6LkHY8yJqJ61ch3G0R8M/4lfw0GbJFQX47UNceO1UqYPbdfUVQfGMFuVF6FUNKRBlbzxLCfTkO+L4TKREr3qOdQTvIU0xEMJoXBlgLC0ISnSZkE0SMrhTlAxH/4/UIesTKaN17ip3YyD3j6Em4gNad1cAMtB1Mr1uRN65SNjWXhVcw1phXOkUvdMx8Zq6HkWpl1JLXB0EO9nJYWNi9nhA8Jni2/0EOpeJDNmJ8WvmZ2raOfL6jO7H1Hflfri3R/KxrsdQ82GY9bsItSICdEsy3wARyqEC24Up064yFzFflR9A8jKgLmeVzU7HiEJWWTE61qAYyss3yz6qdT1FvMFhB57QkhYiUC0Nof9kzRzrNiP8H0zVkp98RwUSSeOsdfVkvHY+zUDMRsRd3llBJrU+mmSVR8aopujp5MEtK/i55su1neZ/5nyf9Xj/nnJv63n/pNk5513ZtasWcyaNYuXX36Z3XbbjT322CP2VM6ePZvNNtssNuwBtt9+e5RSzJkzh/7+fpYsWcK2224bH7dtezUv6FFHHcXjjz/OokUmTnhN3u1cLhfX5fXXX+fyyy/nmGOO4fe//31cF9u2+dKXvhSf097ezvrrr8/s2bPjMo11AVb7e99998W27Xh3Ydq0aey8885xqBIwqF5gDNpZs2Zx2223USwW44nyWa4FDNLHhx9+iOd5bL/99vFvjuOw9dZbx+1YVV577TWefvppstls/Bk/fnx8vTXdp1FOPfVUXnzxRZ577rk1GvYAm266Keuuuy73338/06ZN49BDD8VxVvcqvP766+yzzz6MGTOGXC4XL9CiPI05c+YMYhkGVsOMb2xHI3nY2LFjyeVy8d9dXV1suOGG8WIz+q0xDOjpp59m1113ZcSIEeRyOb7zne+wcuVKisViXGbbbbfljDPO4JJLLuH0009nxx13jI+Vy+bhnUwmV2trKmXiOkulNW+dXnHFFTQ3Nw/6/Pje/1k+xhfyhXwhX8gX8oV8If9+8m/ruf8kyWQyrLPOOvHfEydOpLm5mdtvv51LL70UrfVqhm4kn/T7mmTzzTdns80246677mLy5Mm89dZbsdEeiZRyUF023XRTHn/8ca666iqmTJnyiSvPxjp+ltWp67oceuihTJ8+nf333597772X66+/Pj6+7rrr8vzzz+N5XmzctrS00NLSwsKFC/+ua0XSuDiK6riq/v6WrpVS8W7JqtKY8Np4n0bZddddue+++3jssccGxZqvKocffjj/9V//xbvvvsuf//zn1Y4Xi0V22203dtttN+6++26GDBnC/PnzmTx5MrVa7RPbsWq/NMb7NzXVCXNWXUwIIdb4mwq9XfPmzWPPPffk2GOP5ZJLLqGtrY3nn3+eI444Ig7VAqO/mTNnYlnWajka7e2GOKi3t3e19kZhUkOGDFntGMA555zDaaedNritbz6EcB2wE8Y3FnnVpGW8YQ1e+aJvFhaBViZZrZxHpHIN2+ISXa3E4TlBqEcfSGTMdfx+jY2mJiTJhEeppvExOPtgQkL8CF9FCmoR1oQU1EKvrgYSWsUhPBKDZ96IkBEM+KSVwcZOSR9/QJNWmmrR9E9aBFgNWH0ROYtwU5Cq97FwU+hExoQfJDJUVQ2JQEWe91QO/CoikUUrQ0gkEqm6Z9JJUNMBRQE1FJXAwkNRETZOqJ8Q7hzta0Sm2bCXAtQqg8mLQup6/Co17RuG2rCsDjxEpgXtuAjHMVvplkUFbZg9IYSKNPkKFQIIx6r2tfFmh7oVttmGF25IuuTVYqZP4aaMNz8KMRECXwXUlF9nA3USZlwEPrh5tA4QbgoPk2cBUBEBQko8TCyvtBSe37D3kmk24zFMGiUidSrlKURRQ02mz6WjIdnwLFGBIdsCQ7CUzBiW42wCgTaY+pGOw+uSyKCbWkziqlZQ8QgKRidJbZCVLKFNG0OWWGG7JqE87B/cJFUMfKyfF5BtNaErUT3CHSASKcNOG4boxLHt0XXyAyZRNdtiWFXthCETA6PLVFOd4CvqlwZXXQVNQVskgxApRw1+vkmtTZRWrsm0v6nVzNmmNtPXAMk0IplBe1VTh64uaO+KE2pFNEfcFCLwQy+3YeCN4bSchGmnDJ8n0VyJdgnBHA9j8kUiQ0EYONJS6CCpaJ+KCOq7cmFoi873GI99NPatnNlJyLaZ+P9K0bATR+EujovMdaC0QhcHIJU19wzHifariEyL8ZZrZUJdAg9dKqPLZjejEmQIClDEJis9tBYxkk6kfoVGDu8yLLBhorYO/LiuZFvBryETNlXPIgCTP5TM1BlqraTZAXGT4S5SIn4Oq2Uh/0Oxgkg3G5beRMagD2XaYoIqla/gibCv3GQcjqMHumNWXlEtYqHpf62KV7HQWiCEJlCyoT0gHNvkAwGiuYV/hfxfRbn5vOQ/zrhfVYQQSCljb+aGG27InXfeSbFYjA3HmTNnIqVkvfXWo7m5mWHDhvHSSy/F3lDf93nttdcGxcqDCYe57rrrWLRoEbvssgujRo361PpYljWoLr7v8/LLL8dhOStXruS9995jgw02iMs0xmMDq/0d1WXjjTfm5ptvxvM89t9///jYt771LX7yk59w8803c/LJJ39qHf/WtdYk66yzDq7r8vzzz3PwwQbBwvM8Xn311UEhJo2yxRZb8Jvf/IaxY8f+j5B29t57b6ZMmcLBBx+MZVl885vfXGO5gw8+mDPOOIPNNtuMDTfccLXjf/3rX+nu7ubKK6+M+2/VhOLx48fHSceRrFqmcRH3j8irr76K7/tce+21sXf/V7/61WrlfvzjHzN79myeffZZJk+ezPTp0+N8D9d12XDDDXn33XfZbbfdBp339ttv4zgOG2200Rrvn0gkSCQSg36rdo0FwhdArWKMqeh7o8VQK9NfKyERJG0X2TqcoG+5oVMPqdUJPPNCtV10qZ+PaiuRozamW87HbTYvnTkLBnCEZLTVipsI8DyToKZCsG+RS9KjPTLCQjan6NUeOWEjMy492hgeaWGhcBG5JJVwT1y2pnE0tAtTprJC0un79PSm6Wgp0v1xhrUos6jbvPBGdAzgJM0L0/Mt85KPtvojxlDLNkaCa4xLXS1SrFWwpMQOEYWEmzQJprkOhJQGWWbMpoN0PLfazXqpHB/4ffSJTt4LVrKpMySGaYy0LFxp9AmI5q76yx7M724Kiv2IdDMlv0LJryKazUIuGk/CScHo4ZDJQUs7s5mHNX4tAAasldgaeix40+tGjN+VpepBhCtjKFFPCENYlcigVsw3urAcgz4CsSGhln6ASLfgBT6dqWY8HTSEBOQMwlAygxw3IWykZA6/5Cs1Y2z9lSWIYRvQLebSadmkmj2Wr7Bot0Oyn/aRoQGrDJNrf4BIZJDD1uNdaearM34Ui5+ukFw7hUik60alUiacBbMYka1D+TAYQI5bm4BunGQQ6003hvO0dpokyuYu7B22Yt7jrwMw1ioy4Lm0JkzSpWpkqA1Fl/qx1/0ScxJP0ulDUBOGWTRa8HhVaB1uDOZy3hjFtmuMrhCJSNgJE1rRu8IYqW4SkciiCr1msQRmjNXKWMPXj/UaKImqRfXQzBdVupwknoAthgmEVcNeUV9EDqFGMbAh04QeWAnJtPnfTSJyreY6+V5oHWqQelqy6HRopEeL/VQunh+kcoYtt1qM62l0Ww7nlYUuDxhm1sa5AlApYnWtHZ+zQFcY52ToCw/PLXdTdj1S0kEMXQs9sNLUsVapG+5ezSwaWkeY+ZpuroclRChDlmN0neswicjlvOmb8NklIhZZN4k1ZHS8gPO6p5uYe2CRlWDUkiQfJCxGWwF+IEkFJtQwGTIABEhEKmn0EMXBSwl544wRqSZkrh0v6TDfT5PTARLLINiowWhx2nENa+6QMch0M+/rInLtceZgvwlTE5k2s4AIx741woyLykfVGO5S9S41ixbLNqE4VbNLLIeMYa7jsvlIRVAIsFcYkzpQAlua65WERna0oAtFHK0RIz+fd+GnyRdhOf+Y/McZ99VqlaVLDWReb28vN910E4VCgSlTpgBwyCGHcMEFF/Dd736XCy+8kBUrVnDiiSdy6KGH0tXVBcDJJ5/MlVdeybrrrssGG2zA1KlT14iKcsghh3DGGWdw++23c9ddd612XGsd16VcLvPEE0/w2GOPxbHu6667Lvvssw9HHXUUt912G7lcjh/84AeMGDGCffbZB4CTTjqJ7bbbjquvvpp9992Xxx9/fFC8fSQbbLAB22yzDWeffTaHH354HH4BJoTj9NNP5/TTT2fevHnsv//+jBo1iiVLlnDHHXfEC6DPcq01SSaT4bjjjuPMM8+kra2N0aNHc/XVV1MqlTjiiCPWeM73v/99br/9dr71rW9x5pln0tHRwQcffMAvfvELbr/9dizLWuN5jbLffvvx85//nEMPPRTbtjnwwANXK9Pa2sqSJUvWGI4DMHr0aFzX5Sc/+QnHHnssb7/9NpdccsmgMscccwxTp07l7LPP5ogjjmDWrFnMmDED+Pt2ez6LrL322vi+z09+8hOmTJnCzJkzufXWWweVmTVrFueffz73338/22+/PTfccAMnn3wykyZNYq21jJE2efJknn/++dUWV8899xw77LDDp/Zpo8z88vUAVDDemiQBpdBP5qCphAa+pTUvD18faSkCX/LM1leTlR6+ljFJUoCg17IoWJBW8NREh1+cs4BvN3cz9802AH69VwlVqLLkz5pF3U1MsUpkm6rM+9gYFcWPbC4a0ke55PDCz7Oc19ZHteLw51/nuLTTvCCrFRsrVWDmfS0c2NqDCgQz72tiLD6zHdP2tROKeY7NVpv3cvcbo/j2Zgt4clYbh2xl4A3v+csoNlpRo8WtorTg5e2uxtOSpAzQYSy+pwXJkKHRQ5IUAc91jseyFJ5n2vzKly7Hlual6CmJKxXzdYpqOHaySvHshCTFFd20TpSU31/MpHaorVxIodsYFsWCy9C1B3j5D8OoPvJTkuGLuoYk2ZDtWkHiYHY6nh7VSbVi8+TWJmdFAi4KW2g+tBLUxHLgQ6Z9z+WiK01Y2OnrL+aNt4ey94SlHLN+M9cf/if+a1iJNx5pJyGNcbKOU+Cd3yYp/voGUtKnrGwEmoxljLpiYFNDkhYBFW0xc8QYymUXN+Hz8nb1/JmU7VPyHd52Elihd/O2Y1J8OG0AgD/t3cojZ83jh5ssoXdhisVzmwm0IJM0VuozW18d61BqaBIeA9rhI9fihinGOLnu5gRnjl/MtD+MYssHLqeqZZhXIEiH9fWUZKFMcN+kCtOu7GMrq8YHH3UwK9RbTcg4nt7ROr7PkynNxSEg1Y8fzHDc2MX86cPhlLa7moq2sFAESLKWWYDVlOQvbpLj7pnMnw96kCfnjWDkdlOphWamE6YKl8O5lURRDfNN3NAwLGERCEEzPlV9ORnpE8Rj0ZDVaQSuCFgqEpSlwNGa8a7H/LdbjN6THpeO7iY1zkL7mrf+2I4lNBuKEq4w95lPhgSK1w97mqTtU/FtUo5P2bOphVjmjjC7FWnbo+Q7+FpgC42Id8+ewNeCpAwItMDTkrTlU1MWfljnZDimakqStAJqyiIhA6rKiuxlXKnoVS6+EDhaccmQEm3r91LrMQWOSqdIrJ8iWFnkzcsWk3Tmm8W40NSCUJe2Ty2w6Alc0gR4SErCIqVVXN+KkKS1QckqC0lKG46JxuTYtAgoapsPXDvmvNhYuXEffG2nRVQWab6zgSHAc62AbdI9SEtTLpt3kGsHvPqj+RT1VErCzNeqkLSGVMUKWGI7fHV0kd2+6/DLe9I0BZoXvnQVQUOktEDjCIUjzW5fv3C444wOrr3MzOVWJVjrmmsoSgtLawIhyKmAD1xj1h36FZsxb/skCXh5p5soacuQolHPa5nruHxn1sWcs+W5jAkstqaEAGqBhRMa94cle3lmajNpNF1OmT8f8AA7Lv3k3fQv5N9D/uOM+0cffTQO68jlcowfP55f//rXcRx1Op3mscce4+STT2arrbYinU5zwAEHMHXq1Pgap59+OkuWLOGwww5DSsnhhx/OfvvtR39//6B7NTU1ccABB/Dwww+vkS11YGAgrksikWDMmDFcfPHFnH322XGZ6dOnc/LJJ7PXXntRq9XYcccd+cMf/hAbo9tssw0/+9nPuOCCC7jwwgvZZZdd+NGPfrSaAQomgfSFF15YIyLMNddcw9Zbb80tt9zCtGnTKJVKdHV1seOOO/Liiy8OCiX5tGutSa688kqUUhx66KHk83m23HJLHnvsMVpbjUEWhZ1EXvrhw4czc+ZMzj77bCZPnky1WmXMmDHsvvvugxYanyYHHnhgfF8p5Rp3GVpaWj7x/CFDhjBjxgx++MMfcuONN7LFFltwzTXXDIKRHDduHPfffz+nn346N9xwA9tuuy3nnnsuxx133Gpe7n9UJkyYwNSpU7nqqqs455xz2HHHHbniiitiiNVKpcIhhxzCYYcdFi9YjzjiCB5++GEOPfRQ/vSnP2FZFkcddRRbbLEF/f39caItwH333cdFF130d9VpnVFmmzeR86kVbLSGRDagVgwN/JR5QftVycz5wyhLQUZptltrCYXeBOlcDTth+j/wBJmRCiSoiubXs0Zx4KYLePUvw2LP1vRHhpDQML5WjQFcVuQzdLWYRK02JfhwRSs2ijGt/Xzc04JLwPCmPO8tNwsEB42HiNlUFTA0WcK2FGu75j4r52fZ2K8w9/VWJlkDzH+jhW1UkfdfMchaOzgD+I5Jqq0pyTrrrMTJKYKyIAgBwZ2MIqgKAk+SaArwipLH5o6gJI2xCrDXeMMAWh2wcVKGsn7doXU4WxT87rVRrOtXeaA7wea1KnPsBOt6VbzwZd6RqPDoX0ex/ZAVpFtqVAs2diLATijK/eZZYTmGvEsrQaLJ59G/jiKlNNuOXRL2kyK/PIHlKDborJnIqjTcPX0UZ21uFjTPvTKCdlHj+ddG8PFbkmO/tJD/fmEkO3SsoLfPLIryNZcRHQOst3aF6kqJlVBYSaj2hou8hMLOgtcvsFOa+94dRavJZWTPjRbEza4O2NgJxaZjTDK0qih+fvsotg7b/LMHchw8fiHPvj2ShFaMS+dxnSAOzdloLWPEGGAmTbHHZWzGZ/u1FI/9znhjvz1sGc+/MYL9Ry3BzQQmPAdQPlRCvaXbPTbKwkPPjmKvzmXMX9rCqK4+bDfEWW+A3/SrFuWiw7i2CpO2z/LmfWb+H5Qc4KMP2lnLKjF6vR4sF4QNfgmqefPMy3T5bNrpcP83HqNNW0xedyG1ooWbDcPRKhaBJ0hkA6oF08ZENsAryzhsxs0EVAZsvIpFuqVGvidJOlej0JegqcMkZNrJAOVJNmxWyKRA+5r3XmmnKWV2PIJA8pc5Q7HnGENurSF9BIFgWW+WYtXUdYRTwleS5kyF5iFlBrpTNHWUyfcksUKjzk37KF/SNKZGYZFN97KsSQANj7d0lXBzCr8czpWcJqiY8Lpol84v1f9WNdCBMIR0ZYmTCcuUJeumFNI1ff3mX7p4f4WMnxfz7QT9b0JWNfHV4UuwXYVXsciN8SguDHU/3McvwDgFtYIZd1pBJe/gJINYt9WChRWOkYHuJMm0RzLnx3O93GPm8NajJIRMr5UlJowL4LWnOunKFFk4J0uT9KgFFn8ptuEJWCsIoYsrkozlscmY5SYnNxBm/PYZr3wi5bPFCI+3/txJ31yH3UYtwa9J0q0edi4MYyxAYqhk4H2JkzRtcXOKy28awbnnm7Gvg4C+GbPwa6Zu0tIICduMNdeY92yW0dk8SguGjC7gthtUnNT6afpfM3XdfKTinC3P5YpXL0PXyry59bkESpJN1CiFO2zzeptZu7WfwJN0F9N0NtVzw/6Z8n8V5ebzkn9r4/6UU04Z5JmcMWNG7FH9W7LJJpvw1FNPfeJx27a5/vrr1xhrvqosWbKEQw45ZDUj77DDDhsEp/hJ0traukavf6McfvjhqxnZp59++hrrsvHGG6+W/BnJ17/+9dWgJj9JPulaO+200xq3w5LJJDfeeCM33njjGq8XJYw2Ihutu+66f5Ox95lnnlnj76vef9V2fdJ5kazKkvutb32Lb33rW3/zHnvvvfcgg/+yyy5j5MiRa0xajeTCCy9cDZlnTeNz1fqeeuqpnHrqqYN+O/TQQ+Pv77zzzmrXWFWP48ePZ6+99uLmm2/mnHPOAeDhhx/Gsqw17nD8LfGrxtCwXYVfM4aG5ZgXmkE3NLryKhYJrVEaXK3xqxKvZsUvF4DAkwQl8zJVNUOfHlQG40KnVchyGhr2llRYgY4NHK2NUSIxvwl0XDa6k4VCIU2MKAY3XimBlgKvFqLyWAZ2UwqNUgLbUlR9K95uVqvEIftViXQUflUShMH7lqvDvyV2VeFVZIy/nVT18yzH6E7aprwKdQDGYEkqsIUirQz+uKNDz6iu6yDlaXzf3Nuvybrea/VdLuVD4EvshCKlNI7WMQqRtHS8mxBUTZy1gyKljbEAkNQKLQQJrUgrSVAwdWkA7jGwjwpUxRgq4Z3j+wgJqqKolSwgIKlNTLqHMdQAo4ewDaoQxCy26ShBIhwHflWSaiDuMVj3KtarVgajXQUK37ewaoqg4JNWQTwmk9rUTdoaK4o39kVskAVVgZCatFLUqlYcc98oQhDeR+L7Fn7VQvWXsYQdj8lIgqpEB8aQ8sqyfp8KyAGf1pBjoFow17GcensCT2K7isCTqEBiOTqef6be5pjnmXnl1SwCz9TJK4f6F0a30lFYSscoOVEug5SaBBor3PGJ+tYSuhFQ0pzjW/H9As/cjzAyxK+aGGztG/jYQElEUNeFX5NYVTPeAaxEQBDOnaBS15Vfk9g1RVCVoaFr5ooVUuPG5yuFDszugNba5DcAKWWYqpNam3oI8GsW2vdi3WvfICYpX8TjFMDzrJjN2q8aXUcx6Z5n4QZBfH9pm7nUOGZNn0hUCDMU6bQRRtfVGhDxDoHAxKx7ZSseU1oF1MKFlWVp/IKHJTRprVCBQAUSryyRIQuvX7FwfYVftRAihPO1Ne1KosPxJaRpq3lOCyw7dLAM1OJxIKRGKqgVLayUT61gkaz6sY6CQsCYwDLhU259t7eRiVaEz2EVPmt9/1+Dw7LqWP1C/j4R+ovApjVKT08Pjz/+OIcccgjvvvvuv5xxtlEKhQKzZ89mypQpXHLJJRx11FH/FtcCk6/w8ccfc/bZZ/Phhx+uZlj/p8jNN9/MVlttRXt7OzNnzuTEE0/khBNOGMQ58O8m8+bN48EHH+TEE08ETOz+mDFjBqEzfRaZOdQsBixpCNlrSmIJ83L1lYyNLVsqZAPmW8U3W/gqhN2LyhQCh1a3YoyBcOs8l6zRVzYL5JRt3poJJyBfcUnaPl6wCsZyeJ+IOChO8mq4v20par6FFBpLKgIlsS1FEBrttcAi5fhUfQvXCih7DpkGj1Ta9fB8K95yj+oLxL9ZQschOpEeEnYwyNgre04cOBOVd626cR+d69gKzzd19AOJlJpi1VhSKcfDC+omgyV0DNPZ2OZIH4EWJOyAQIm4fio0jCMD2QuMbhqp6hOOT77qkkvUqHp2/Fux6sZ1VlrghPoSDe2PdLPq3ymnnnBd9uy4jGjQhWrQYcR86VoBtcAik6hR8WyssF1RPSq+Pagfou9JK8C2wnjgmkMuWaVcc/DD/ovuHektCpWypMJXMl7cNeotEscKYsNGaYEffs+E+rKkikNBVr1PoGTcVtcOKHt2XCbqxyCcT1Y4L0Q4z+JQGKmwG+5RU4b0zA7r3ihRO6Jrew3HjSEf9mVYzmooH0Ub5muuMUa14YJQ2ujX3NsaZMSmHM/E9of68leZL9YnjJUAgS1UXd9RnRva0lg3OxzDjX0f9UegBb4OFwMNnBGN7Y7aLsLrRvcNtIgDcKTQ8bMi0mvj/I/uqVn9uSDDNmRdD62Jx2LjOALIVwfHz3s6CncyoTZR6ajtVd8epLdV7xk9n52wf4SAqm/Fz4pofEfXrSlJc9J46Aur1CXSib3K2Nhs1lSe2egcmiwv7nm3YU5EstWi3/HPlkx67Od2rWLp48/tWv8p8oVx/wkyduxYent7Oe+88zjjjDP+v9blsMMO47777mPffffl3nvv/Uzx6v+Ka4Hxkm+33XZMmDCBW2+9lU033fTTT/o3lFNPPZVf/vKX9PT0MHr0aA499FDOOeec/1Ey8H+avDDM8D00GgSrfgfzkkk5vvGshy8W1lBmTYZF9PKJJDI6B6EzNBhjyXABUPFtkraPEMZwjAy/qGwUKxw9xSIPLBjj3rUCvMCKX3zR31A35CK86shwbnxJN/4dfY/qE718SzVnNQPc1zKOYdcQG2fR/Z3QCIxempFuaoE1yDiJzif8u7Ge0Ys5Mk4aTYvonpExGZVxG+4btccJjWxLDH4VRMZi40JrTTpJ2PWFTGTcR2XkKtdsNEijukfGQzQOrIZ2rUkHjRIt6hwroOJ/8lyN6ln27HjBtyZpXEQI6ou8tOtR8exBhnfjOYRlpdCxAeYFVvwb1PUX9W8kjXqK+thTMp47ouHajddp1G1jvRvnXaRTqBuFjdfww/Hf2F+flGWkWd2AXdP8aKzbquVXLbem36PxEOukoZ2N9f00iXTZeKfo+dTY3mCVuqx6/VWfb9GxxnG/aj0jp0HjYiJq86rzObpONHf+liRtf5Ch3Vj36HqN9Y4W3p907VX7eyBw2OmdK3hjwmm4Yb0CJan5ZpkXLci3WfzJO/Kfl6RSYz63a5XL8z63a/2nyBfG/Rfyhfwfl9dH7wMQP8ATdkAtfDmlHJ9aaAgFodEQedAcqUg4Pn4gY4On0fCMDLfIyI5eSpGnK/KaRYZd9CLyA2PgCbHm72CM+ELNIRkaq1JoKoEVe2gBkq5PTylFa6pCXzlBe6bM0kKGoVkTM7q0kCEhVOxJjerVKNHT0XUClBIIAZWa8ShHL+uU4xsDOqh7NVf1dDV61CPPvRB1o75UMxQ9CcdHa7FaX4B5cb8j02xlm9yg54Nmvmz1xx54xw6oeDZKC25LwCUdfSxb0jTI+x55xmPDJjSWnIZFTzrhMVBOkHK8eBETtb1RL1JqLKkZCHdkIm9m1LeNBt6qHt26XnTcr1G5aCy5DR76xvtGiyOoL4YiPUqp43ZFYSqObeL4o75x7SA+1lgns0NEvBsihI4NnELVjY1C21JxfaXQsf7r/Wp2vLLJmjHyGsK/ZOixjwyvQIlBC5pyuEBJ2X58r3LNIdCCdKjbaBxF94361wnrqrUgUAJLahw7iPvH1zIOHYmM3OZkdTVjtq9iQhFbUxWKVYe061GuOZQDCyfcRQMGLfQ/SRrHXr3Pje6isDgZjoFGb7Vt1XcJq57xaFtSU/MtUq4X33NV6yVQMta3JTXVhn5vNIwdOyBfddEIsk4d8Siak426Nf0d1cXCtQOk1HH9+yuJWKemj821cm79ulGbwDzHovkRG/xh/zX2Q/TMS4TPYD+Q+ErG4yDSYdSmVeeWbanVdo4a9WT+N/Mtm6jFRrwlFZvNmsqjGxuW9k5pvP8as4j0lGS7Jb/hny3J5OjP7VqVyvxPL/S/TL4w7r+QL+RfIDNmzOCUU05ZIyrTmuSZZ55h5513pre3928mDH8eEnnuIy9O9OKHumc1EksqpDQv7KpvxYZ54zZ247Z69HujBzEqFx1z7ICqZw/yOjV6pdf0HYyRVqi6sSc98uJGhls5sGlNVegtJ2MDvzlZjV/GzckqVa9uqK9qhET1htW34yMDBaBYdVEN7WGV77FuQ0On0aPX2JboRRv1QxRqYTW8nB07oFRzsIQml6pSqdmxUR4tuITQtLaUWdydoyVVpVh14j6MdjGk0HHYDqx5Z6Xi24OM8jXpB4xXOzo3H+q20dCoKUnG9uMdksawmGiMRP87dhAbTZERHJWNQmAaaxG1JSobG1jUF05Bw7hpDNNY1ZMa9Vt0DbshhCgK50o5fhzW1ViHNd2n7NsGnaSh/yIvcNS3UXsaw7EaUWAiQ95q+C2SWI/h9+j4qouqyBhcUx+Wag6eFjhCx/8nwl2zsm/jSkVVWbgyiBeF0TVWrc8nyar3bUi7WE2HsPruTLzLh1nwFTwTSqQb4tyjUWGH4YGRDhrn4ao7Mq4VxOM8klXDVSDcLQi/J60AT5mFSFQmWgBGxrvWxiiPwtqi+sQ7Yau0N5qbRc8ZhC0fjZ0oNCsKy5GrtGnVHbvob1/JuC+rvh1fs1H/Uahl4w5A2vWYV8my+9uGof3tLU6NHQzR/PlXhOV8Ydz/Y/KFcf+FfCGfIC+88AI77LADu+666xrhST9Jxo4du1oyeLlcJp/P09nZ+ZmuUavV6OnpoaurCyHE3704+HvkR2MNd0EApLSgFoYNJLSgLHT8Ikhowal7GBQYVfb48bNdpLSIsbPBQBaOCgTv2D5ZLA5vWc6fVnSxRaKPD0oGsemr+/agyh49syR9vWnGTOzjTy+O4LEQc/72xTMp/PFK9Pz3aPreNPLh99z3ppF/0rxwWPAhesVyms56iMJMk+S96Hs/pWOiz/w/GXxzSyrmF3KMH7aSF5d3MrF5Je/3tLLRMEO9/pelQ1gnmWdOtYlZCRO/q9BktKQcGUjh37XIW6kFJ03pBUCXjdF0xR+HkNaCijDXMDrRVEPDwwJOG7eY5R83MWaXKiteFLRvVKPn3TqSR7Vo4yQDnlw+lI9sRSJ82VaFjr/HW/zh/yfu3o0Qgh8/2h7X1dUCF8FwH1ZYpuzhk5bws2cNqteeiR7cRECtajHiKwFTH+3gpAkL+eOf6yzQ241dwodz23kk6dCkJQVhEpObwpjhAaGwwr/7heLsyStRBQ+Ztrn6iY54LGW1oCQ0HpqslqwUARdtv5x3n2oFYJMDytz53218c+MF9Hyc4o2+drYZuZSVyw0/yf0ii0QgNfhCk9KGsKwiNKesa5jDH5w9iq+0L+ONZUN4eZXc93Sot6gO505cwt1/Hsn25Cl7Do8kTRyyrQVKmLHbrAWegBKaTiX4asaM90W9OTpSZVaU0zydskiExqZFPYbckBFpThy9mJ5Fpg0/D5pjMp6Ulvjh3EqGulFoUloOMnZdBK0BfGwrsmGb25VgURTbHY4xX0CeAAvBWoHFNuTjayyppdlqY8NLYGdBuIIVbydJpMwcm7Oog6QImJlI4GgzzhwEHppktMsjTJsEEKAZ7gtqwvwOsMBSg+bLqt8BMlpSDedOWgsKQpMO2x5JSgsGRJSoCt/vWI606knP6XaPxFpJ1ECNXz83gl4LPDRWbNqbOnpoSuE4ieZrosFojY75YV+nQ7Kxnobwp4yWFIWihtFHCcX2VStO+t5k1HL6utMM32CAFR9ksGyFmwiwEwE9y0yfO07AC+U25toKN7xfWgvssLJ90lx/85pk48QAbUOL2AnF9R8PHzR+JdCqjP5K4fPkzHGLeeh9w9fiaPjI1rHBnkBQRcf63t8r0zVsAMvRTFs8bNB1ozFbEprDkr3M621GoGl3KwhhdnGjRcvGf7mOTTf8JiMSrVwjEwxUE+y49Nf8syWR/HReoc8q1cqCTy/0v0y+MO6/kC/kE+TII48km83ys5/9jHfffZfRoz+bJ2FNxv0/Kv9M4754scEsFukUulQ2pEFNWXShZPaYIyIrz+O0Gb4x1rC44pgkaslKZHMa0WwMd10qo3oGsMYOR/f0c+sMm8O/tJDnnxvGZiMNotIl3W20YrN1VbKOm+dNv4mtMz2M3Nt4RO0Dvkl20hns2rUpv/vVd+rff/FtsjufBcCuXZvyNdo58rf7MWaXc9m/dVNOSea5udLMDtV6GMuO6y/idx+O5BtbL+SV54eyTmcPs1YYA3TrMUuRlsZKKJwWSEwcZVhgC0VEJkSOsCwolOLvulDipN+6WAjSIV755Ue56L48ojljypfKiGwGnNAjGARcc1OVDWvwXCJgu6rFrIRmi6qIcdwjmfLVJdjrDzOZjZZloE4iQHDLgmoN7XkI2+KHP5fk8fnJMSHzpReyhEqJ/+FSRNIGpbngiTYu3tvA5fzxV01YaKSGx1Oay75R44ZfpDhizCKKPcbr/mLPEHYYupSOfbvQAwVENg22he434UwilwY/QPUMIJsznH2PJIdFCcXlh4XtsS10voTIpBDZNLpcRWTTXHhdP/vXzDb/Xa7NFTus5GfPDmN8NeBLWyzm+ddH0BTClHzplBSEzKDYFrpcQdgWIpvh2ptNyMNJOy7lt08NY68NF5DeaQyESCJIUT834SLSKa79SZmTd1nOGw83k0vUWPfY1rrepAjblEekXEQuTTB3GU89bIiuNh3SzfzlzXRmS4w5tAldrJhzgiDuZyEloiXHXTfW2NCrUtWS7b5vI1JGr7oYEnxFc6txzoXs1KIpix4o4H2wAmfT0WZ+dbaglvch23J1XRTNGBPZNNRqrLhvPnMWmXHdmSyxtJLm+ZSkK5BsFtZlRLZAsWIWNM1NZSplh3F7+mZ82TL830J2NAOglvYgh7ahlvciO1tRi1eacqHIoW31+ZFKDJ474TNDF4qIhGGr1vkSojmD7i+aMRTme+lCEdneGs+VO27ySDZYJQtsTQ8+GSQ/nLQcmXIg6YAfIEJMd+0rRMJBtOSgWoOEa/pGqZid2cAbeeZYqWzaKwWkw7lerRnW11TCXMfzwbJYfve8OPznsZ4uRtUC/pqw2FWakLgB38VD0GqZMVlTks2mDGCNaDd1sCx0sWLGDCA7WxCZFAO//4jn3x9BkwooCcmuJ0jwo/Fr6qp6CyAlsqMZkUpw3w019g1hbbUPqW1H1sd7tQaWFT+7Xrt2gBW4VKVgyqHleJxrXxnGWUB2tPDM1DJrt/ajlSBfTKyWD3GYv5A33/0F/n/fzJvnfcTam6yk47Fn+WeLmxj56YU+o9SqCz+3a/2nyP/+bMEv5Av5H0ixWORXv/oVr7zyCkuXLmXGjBkxORnAgw8+yMUXX8zbb79NNptlxx135Le//S077bQT8+bNGwR3qbUeZJzPmTOH8ePHM3v2bMaPHx9fc+rUqdx4443MnTuXZ599Ng7LmTVrVsxOG5FqXXDBBUgp+fWvf81bb701qO4TJ07ka1/7GhdffPFnaqvqMaRColxBZFKo7jyiWkNkUuiegbqRqjQtJPHQ5AnQAwVUf7gYqITGSSaJvyiPcJaDFAwJbPw+bSAYw3CLsdqlFHow0+ka5Tw0d5ZBhS/qRR+yU9fGPLHsTfSiD5nUuZH5vmQuX+naBIAnlr3JgZ07o+fN5uDWCbzqrYCkSxLB2yEwxNf8EkvmNrFerUbPnAQeBoavGgbFOumA3kUZRuxpUXt/oG68unb8HSkQtoXqL4JtIaSgBRsbQSWCGiwUUQMl432Nyvf0x4YHjkOrEqRUQKe2aFM+YFEVhoAIDHlSwZJ4y31ke78xVHJpVLf5DtT/ziTRStNMCg8VLz5UvoxwLURTlqDPR6ZN/dq0RbDMtCeps6RFgI9AItFVD4c0yhe0jDHGh98LTjJALe9FJB10oYSueIikqYceKKALVXBtVH+RFlqMpx4ZG7C6XEWkEuh8yRgp+TJSK3Ja0tpkyjiVZoIBHxvDihuUhRkn4R6F7suD56OVRtgSXfHQtoUoVxnpG0O3utinOVAUlrukCkXwG2A1PbNIEDUfPI+UdlEFHzfMj4j0pmt+3Ne66pl79eWpLa7RKcwCoac3TXOImKOLFbTnI6RAKw21aAEi0UrR4SfxtMRBofvydaM+kzL91zC3dDTnVubDOWj0FhQUTqGE6i8jbInMpdAD9TGJY6N7+6FSAcfBchSjmsJ5LGC4KLJZtYmVNiyQCSoS+kstlMKxP6Hsm1j+3oIZsw1YsyI04IPeCrgDqHwV4eYRzWmEXQ/F0X15ELI+X7Qy9Yq+g/k7qrdjo4tlM1eCoAEL1zJtCcu0BhZZpVjqmHq0KkFKOPSJAL/bx24DESh0JQA7jGtXGuHWEJ5vFmeA6iuY+dBixopa0Vs/FupbDm2rz5/egplbhRJohfYDhOPgpn0KvWaBllYwJpPnzaCFnnKSChYLHBPyMsIx7XR8iSr5yEIJXQsQtkQVq+haiHJTKBlDGxgjS8yWGTzBYL1hFiyqWDPjMV+Cag1HJ1AhzKjyhBlb4SJEVz1EwkFXjU5a01XmV5Jmp8XzzTiXEmp+rHtdKJIOoWHXlPALMCLRiv/fN2Pvczy9P/whqg6O9U+VL/zO/5h84bn/Qr6QNci0adO45ZZbeOWVV3jooYc48cQT+eijjxBC8PDDD7PPPvtw7rnn8s1vfpNarcbDDz/MD3/4Q3p6ethss804+uijY5jRoUOHruZ533LLLdljjz0GkZVtueWW7Lbbblx++eWDYu7T6TS33HIL559/PnPmzAEgm83S19fHmDFjeOmll2K+gjfffJMJEybwwQcfxGy2nyZPdRkOgaKwaMbH14KisMiFHtRK6KFukh7tzSUcJ6CQT7CinA7x5sUgFk4LRV7Y5LRPV1ORuQNNDA8JpsDgz0tL092XYcyYHlYsyeEHkmIY+xol+mWyNRZ1N9GSrJDJ1ljcnYuh3bK5Kv39KUo1h6qWjO3sY+7yVhyh6MiYl/X8Qo4xTQN059NkHI+yZ2ATo4TBtnSZmmfRW0uSsTz6ApeqkDRrL25z9HeApCQkOe0zvC2P4wYUBsx1FpUyFKRFWgUEQpDRAT71OF0HzbBsgeWFNF1NRbrzaVpSVZaW0nQkzJu65luMXquX19/vihk2HRRS1CH0XBGgEVS0WRis19KHCgRLBrIA2MJwEDhCxwyqAKOGDPD6SuPV3TjXi5CaasUk3q6spGhLVEglPRb3m+t0Zkr0l5L0aQdfCAIw/Abh2z7ALEqUAA/BhCHdSEtjJwJem2d4LhytCIRAYVhHI3/vWm19DOSN3iypWVJNkSagJVmlVHMY1jnAshXGGCsGTsweGkEyRoyurbYZB425At1eclBcccStEGDyJTqTJaqeTcLx6askiMAIo3toBFnpUVMSD4mFjsf16GyeUtXBthTzqtlBcfoRm3BFSJJakSRgdGc/Hyxvw0JTCa+RE/W51YyPpyUVJDnhx5sz/cIhp31soamGC4Qe4TCEGkVtx/VNERAg0AgsNFnLoxiY48OaCgwUk1SVRdapxcmnjbkCASIeK0tEgk5doweHNjwqIdv0YtumKVAxYdyQUBvRuC5rm2rIplvSFiUhaQvnTsRq3aI9algMSIsOVYu/N6kAL9R7k/AoazvuM0coUlbdgkwlvDjufnkxTV7YOFrhCUk+JERsC3z6LYvOwI+vmxYBvq7D9Fa1xMckFSeFYdXNOh7dXjLWiS9EGDZVD4GK5mM0DnukQ7PyGZouxVCYfiDJZI1RrRUs781SUE4cONSot2jxmhK+yTMJ83dWBu6gmHsbgzEftUcCIzOFOEHaEpruIBGPBQtNURi22ug+o1IFAiWZV8usFpsPxqnQ5ZQp+aauSSuIc5cak5urnk1v4PLVdy7npY3PYoel9/PPFscd8bldy6st+tyu9Z8iX3juv5AvZA1yxx138O1vfxuA3XffnUKhwB//+Ed22WUXLrvsMr75zW8OYoLdbLPNAGhra8OyLHK53CBCr1XlkEMO4aabboqN+/fee4/XXnttjYRnruvS3NyMEGLQNbPZLJMnT2b69OmxcT99+nQmTZr0iYZ9tVqlWq0O+m3ib/cn4YYvfr8Glm22sP0a2C7UjAGqvSobHfgTEtIhZbm88Ngx6HnvIjpGgBO6ywMf7VUh3wfVEtt//w88/6OxXHat5IzNTQzwma91UKkptnGSrJMOuF9m2L6qSISvnKFNeZ4st+H0wU4tK3m62I7VB1/O9fBkxTDUWn2wS7abhOPTXUzz8fIWtj0tzW9v8LBL5jU6fthKPlrSSs72SKe82DMVGS/ZpirSViR7fd4ttbDX/buja2Uo9CHaTIyq9sO2JJLg1SDfzxYnP0LGSpAKjcrHf30AfDwHMW5DU744gBi+Dvh1PW+3zw1slUpTrCU5CJfrVI2dXQdXGb13O5p1Pkyx04YLabrguxD4iHQOXamzQYpkBl3sN/Vp6WC3b99Hf1Diz3842tS1dylYNsJN4T/0W2RbM6K1hfMuXcJFhxvD48Hpray0jLH7tMxz19XjOOmCD7l0eD8rB0yuwtxSjq8cFSC3+RL0roAhw8D3YcDkGtDeBeUCrFgKncPZ7bhHaLFS9AVlHr9ja1NGyrieuEmEkwApufKbD7GNZzyYP02WuPvsHLddXyYbJJiy7kI+er+d9mazOJtw72FQDdtv2abtlo2wHI4/xCT03XRcjktuqXLOV1ew0Xf3NX3UeH+AdBbRPIRDD7yLO88awjNX9LPRiG66bj/B6K3YhxAWWgfmHCkh04R65glm/9Tc3w/k/2PvrOOi2P7//96luzullBABu1ARAwOxrpiAcBVFsbu9othitygYYOsVUa4JdoIKKiqIhS0ootTr9wdf9seyMxugNz7O8/GYh3LmvOecmT2z+z7nvIO+FCuQYmkZtd/cgOhz3v+ZThQRqf6fWVRZGfFMatHB3glU9EaXbA0+ktnmwYLVWHwvJJ6GLlFZ6f9/z4jKr1Hx/pSVEb4VEFKvEr9pW8KrLCJ1baK8d0S6xoJ3jAryiWdZh6iwfAU6sftRaupY/n6hjGhcNpF/qS695ynRkGFyhPef6FSsIn37P03fmldIhaVy5LGuASEnm3jWNoTnOcQztxSM/bLbl4jn4kFIu0481wZE73PL77liPBpY/P/3Q1u//Hsi/wORvun//xy+fCLS1CUqyC9/ZiZWRDmZRJb25ffxf3V4FnWISouJSkuoe+9o6lOmR9n/Z6R+8GsWuSoZUyGV0I4pOkQKCsTT1SO8ekk8vXJ/E3z6RDxtbSIrB6LvX4mnrlP+LpeVEU9VQ/D8qegb8TR0CPnvy012lFWJJ/9/ZlNfPpb3U1O3vFyu/N38OGkzyf1fBu4r90zJWq6A7vLVyU6z/Hvx4wdVkpcro8+f/3+iS7dZ5sSv26j8efH4hMLPRJ/KfX14+mZEyqpUsm8nndquTColZfSVx6cOcd6C71qSk///7xifT2RpRzx1HYrsdYDGdf/wf/dTQgr9OhIpKJaP38LPRHw+8ZTKx+PL4TF07V25WZnvytpEhV+J5BUIBV+Ip6Vd3hdzO7ra8xAZahZQSQmfCr8rCJzTK8Kp5n9XIqd6b6ishOiyy0RqcncR/R1wq841BBwcHELcv38f8vLyyM3NFZSFhYWhb9++AAAVFRVs3bqVVd7KygrLly8XKtu2bRu0tLQEf798+RJycnK4dOkSAGDmzJlwc3MTnD9z5gyICB8/fmSUr+DAgQPQ1tZGYWEhioqKYGBggB07drD2bdasWaDy703BMW3aNMyaNQvfvn1jlWPj27dv1ZKtrtx/UZbr78+V5fr775Xl+vtzZf+p/nL8++GUew6OKkyYMAFEBDk5OcHB5/OhpKSEDx8+QFdXt8bKPQB4e3tj5MiRAAB7e3ssWbJEcE5a5b64uBhGRkbYtWsX9u/fD01NTRQUFLD27du3b8jLyxM63rx5AyJCXl6e+AfDQF5eXrVkqyv3X5Tl+vtzZbn+/ntluf7+XNl/qr8c/344sxwOjkqUlJTQjh07aOnSpdS+fXuhcz179qSdO3eSq6srnTp1SuDkWhVFRUUqrYjaIYb+/fvTpEmTqG/fvvT48WPy9/dnrct2TXl5eQoICKBt27aRkpIS+fv7k6qqKut1lJSUSElJSagsPz9fYl85ODg4ODg4/htwyj0HRyX+/PNP+vjxIwUHB5OWlpbQuV69etGWLVto+fLl1LZtW7K1tSV/f38qKSmh48eP08SJ5WEara2t6fz58+Tv709KSkqkr6/P2FaPHj1o2LBhNGzYMGrTpg2ZmbE7EFlbWwvs/uvVq0eqqqoCJT4kJIQcHR2JiOjChQs/4jFwcHBwcHBw/EepmiiOg+OXZsuWLeTt7S2i2BOVr9zfvn2bNDU1ae/evXTkyBFyc3MjLy8vunLliqDe3LlzKTs7m2xtbcnAwIC1LU1NTeratSulpqZS//79xfarWbNmFBoaSn369CEDAwNatOj/OzXZ29tTs2bNqHbt2tS4ceNq3DUHBwcHBwfH/wrcyj0HRyWOHj3Kes7Dw0MQe9fDw4N69OjBWK9JkyaUmpoqVBYYGEiBgYEidePj4xmv0bp1a5E4v+vWraN169aJ1AVAr1+/pqFDh7L2XRxKSko0a9YsEXOdnyn7T7T5T8ly/f25slx//72yXH9/ruw/1V+Ofz9cnHsOjv8wb968oZiYGJo1axY9e/aMdHR0/ukucXBwcHBwcPyDcCv3HBz/YYyMjEhfX582btzIKfYcHBwcHBwcnHLPwfFfhtt44+Dg4ODg4KgM51DLwcHBwcHBwcHB8T8Cp9xzcHBwcHBwcHBw/I/AKfccHBwcHBwcHBwc/yNwyj0HBwdHJZ4/f/5Pd0Emvnz58k93geMnIC4srzi48cDBwcEp9xwcvwjp6ekS68TGxjKWv3nzRqJscnKyzH2SxB9//EGPHz9mPZ+fn0+DBw/+oW26uLhQTEzMD71mBSUlJZSTkyNSvnXrVrFynz9/ppCQEMZzdevWpfPnz1erP8nJyVRUVMR6/tu3b7Rjx45qXZuNnj170vv373/oNYOCgujly5dS1X327BklJyfTiRMn6ObNm/T9+3ep2ykuLqZnz57RgwcP6MOHDxLrBwcHCyW4q8rHjx/Jy8uL8VyvXr0oODhYZmW9JuNBEgUFBazX/vbtm0T5zMxMkbK2bdvSgQMHWGXevXtHNjY2jOdqMn5jYmLEfoYFBQU0d+5c1vNslJWVMb7jVZF1LDEhy9jl+MUABwfHL4GysjIWL16MsrIykXO5ubno2rUr1NXVGWUNDAywd+9exnNfv37FyJEjoaCgwNr2u3fvcPr0abx//x4A8PbtW0RGRmLOnDlIT09nlePxeNDV1UVSUhLj+dzcXPD5fJHyoqIiTJgwAba2tmjYsCG2bt0qlRwArFmzBhoaGujRowfevXvH2rfqcPv2bcZ2NTU10blzZ7x69UrkXGJiIiwsLODq6sp4zQkTJkBBQQFjx47Ft2/fZOoPj8dD48aN8fLlS8bz4p7T/fv3MWvWLHh5ecHGxgbGxsaoW7cuBg0ahJ07d7L2pWnTpjAyMsKRI0dk6isApKamMh4KCgo4ePCg4O+qZGdnY/LkybCysgKfzwePxxMcSkpK8Pb2Rnx8PEpLS0VkP3/+jPXr16NVq1ZQUVEBn88XHJaWlggJCcHVq1cZ+8vj8aCsrCwy/ioQ93xv374Nd3d3WFtb4+zZs1I/o5qMB0mwjV8AqF27Ni5fvswqu3TpUqiqqoqU83g8yMnJYebMmYxy4p5RTcYvj8eDjY0N7ty5I5Msn89HeHg441iR1GZNxhJQ/l0QEBAAGxsbyMvLg8/nQ11dHZ6enpg3bx5evHjBKvvp0yds27YNgwcPhpeXF5o0aYKuXbti5syZuHDhAqscx38TTrnn4PhF2LdvHwwMDNCiRQs8evRIUB4TEwNdXV14enoKlVdm8eLFUFFRgb+/v0BBB4Dz58/D1tYWDg4OSElJYZS9cuUKtLS0wOPxoKOjg+vXr6NWrVqwt7eHnZ0dVFRUcOPGDUZZHo+HoKAgKCgoYNmyZSLn2X5IZ82aBSMjIyxevBjTpk2DlpYWhgwZIiTH4/GYHxSAJ0+eoE2bNjAyMsLhw4dZ68kKm3KUlZWF1q1bQ1dXF7t27QIA5OfnY/DgwVBUVMS0adNQVFTEet1Lly7B0dERTk5OrM+SCR6Ph7p168LExIRRMWN6vjdv3oS3tzeUlJTQpk0bTJo0CStXrsSmTZuwcOFCDBw4ENbW1tDV1UVkZKSIgllWVoZFixZBRUUFgwcPRn5+vkz9raqcVxwV5VX7Gx4eDg0NDfTs2RPbt29HRkYG8vPzUVxcjNevX+PUqVOYPXs2ateuDWdnZyHlatmyZdDT00P9+vUxZ84cHD9+HGlpacjMzMSVK1ewZcsWBAYGQktLCx06dMDDhw9F+jtz5kwoKCgwKoTiFEEAKC4uxqxZs6CkpISxY8fi/fv3yMvLEzqYqO54kIQ45T4sLAyKioqYPHmy0FjNzMxE8+bNoa+vLxjbleHxeNi4cSO0tLTg5+eHz58/C52XpKDLOn4ry7Zr1w7q6urYv3+/1LI8Hg8aGhpo27at0HdhZTmm75aajKWDBw/CwcEBRkZGCAoKwrp163DkyBEkJSUhLi4OM2bMQOvWraGkpIShQ4fizZs3AtmXL18iJCQEKioqqFWrFvr06YOxY8di2rRpGDZsGFq2bAlVVVU4Ojpiz549jM+K478Hp9xzcPxCvH79Gn5+flBTU8PixYvh6+sLVVVVrFixgnFFvzLp6elo0KABTExMsHfvXoSHh0NeXh6jR4/G169fWeW8vb0REhKC/Px8LF68GObm5ggJCRGcDw4Ohp+fH6Msn8/H69evERsbC1VVVQwaNAjfv38XnGf7Abazs8PRo0cFfz969Aj29vYIDAxEWVmZRKWqglWrVkFeXh5169aFu7u70MFE1TpVjzp16ohtd/ny5VBTU0Pnzp1haWkJFxcXXL9+XWI/AeDbt28YP348lJWV0bVrV3Tv3l3oYILP5yMnJwchISGMK8xMz8nS0hKrVq1iVGwqc/HiRfTu3RsRERGM5zMyMtCkSRNYWVlh6dKliIqKEjqYqFevHjp37oyMjAxkZ2cjOzsbWVlZkJeXR1JSkqCsMuPHjxdSdsRx7NgxoR2qXr16IS0tTaLct2/fsGbNGmzatEmonMfj4fXr1zh79iwMDQ1FFEJpx+GJEycgJycntNLLNJGp2idZx4OOjo7YQ1NTU2ybp06dgpWVFVxcXHDt2jUsW7YMKioq8PPzQ25uLqNMxTNKT0+Hg4MDXFxc8PjxY6meUXXGb2XZ169fY968eYw7B+JW7i9fvox69eqhVq1aIiv/bHI1GUsNGzbEkSNHWHcLKnj+/DkmTJiAJUuWCMoMDAwwbtw41h0KoHz3ddeuXWjUqBEWL14ssY8c/354AJcFh4PjV6N///60e/duUlNTo4sXL1LdunWlkistLaX+/fvT3r17SVVVlRISEqhly5ZiZXR1denChQvk6OhIxcXFpKysTJcuXaJGjRoREdGtW7eoa9eujI6sfD6fcnNzydDQkG7cuEE9evQgExMTOnjwIJmYmNDr16/J1NSUSktLheRUVVUpPT2drK2tBWUvX74kLy8vatCgAS1atIgsLCxE5Crz9OlTCgwMpPT0dBoyZAjJywvn/Js1a5aIjLKyMvn7+1OtWrUYr/nq1SvatGkTa7uFhYXUv39/OnToEKmpqVFKSgrVq1ePtY+Vyc/Pp5EjR9LevXupZ8+eIv3dtm2biEzl57t27VoaM2YMhYaG0vLly4nP5zM+36KiIlJUVJSqT5Lqb968mUJDQ8nExESovzwej548ecJ4rYkTJ1JSUhLFxsaSu7s7EREpKChQamoqOTk5Sd2vv4PKz/fp06fUvXt3ysvLo8OHD5OLiwvr+K3MgQMHaNiwYeTs7EzTpk0T+VxbtWrFKFed8aCmpkbDhg1j/T54+vQpzZkzR2x/P3/+TAMGDKA///yTVFVVacOGDdSvXz/W+pWfUV5eHvXt25euXLlCcXFx5O3tLfYZVWf8Msn++eefNGDAAGrTpg3FxMSQuro6q2yFnIaGBgUGBlJCQgJt376devToQUQk1Wf6d/L27VsyMDD4afU5/qX807MLDg6Ov48PHz6gb9++UFVVxZQpU2BjYwNHR0exdp4VFBUVYcqUKVBQUEDfvn2ho6MDLy8vPH36VKycmpoasrKyBH+rq6sLrcw9ffoUysrKjLIVq3oVvH79Gi1bthRsw7OtktWqVQt//fWXSPmLFy/g4OAAb29vsSuQGzduhIaGBrp37y71qi8A1K9fH2vXrmU9f+vWLdZ2U1JSYG9vDycnJ5w4cQK9e/eGiooKozlSVU6cOAFzc3M0atQIGRkZUve36vM9d+6cYIX5w4cPUq8sy0pubi66dOkCbW1tREdHyyyfkJAAc3NzzJ8/H6WlpZCXl8e9e/d+eD9rStXn+/XrV/j7+wtMQcQ9348fP6Jv375QU1PDihUrZGq3uuOhWbNmYtsSZ5ZTwYYNG6ChoYGmTZtCUVERQUFBYk2vqj6jsrIyTJo0SWCKJ8m0prrjt6psRkaGwDTr8ePHYs1yKsvNnz8f8vLygpX/n/XOcHDIAqfcc3D8Ihw9ehTGxsZCP/hfvnxBaGiowK67uLiYUfbWrVtwcXFBrVq1cPr0aQDlirKPjw80NTVFzBEqU6dOHZw6dUrw959//ilkxnP58mWYm5szylZsnVemuLgYoaGhUFZWxvz58xl/SIODgzF48GDGaz5//hx2dnasP8AdOnSAjo4Otm/fznpPbIwaNQqjRo1iPf/o0SO0bt1apHzs2LFQVFQUcYLcs2cP9PX10bJlS6EJUWWGDBkCJSUlzJkzByUlJTL1t6qiApRPtjw8PGBra4uTJ0+KPKfdu3dLff2cnBwRX4zdu3dDT08P3t7eyMnJkam/lcnNzYWPjw9atGghVrnv0KGDVA6D+fn5iIyMxOrVqwVlQ4cOlbqPe/bsQWxsrFAZ0/gFgMjISCgoKGDYsGGs49DExASNGzfG/fv3BWUpKSkSnWRrMh4iIiIwe/Zs1vM5OTkIDAxkPPf8+XO0b98eOjo62LZtG4DyyUC9evVgYWGBkydPMsqxPaM9e/ZATU0NXbp0kVpBBySPX3Ht5uXloXPnztDV1cWOHTukUu6BcnMubW1t+Pn5ITMzk1GuJmNpwYIFKCgokEr28uXL+PPPPwV/X7x4USo5oPz34O7du1LX5/j3win3HBy/CEpKSoiIiGC02zx58iQsLS1Rr149RllFRUX8/vvvIs5uALBp0yZoaWnBx8eHUXb27NliFcKpU6eiR48ejOeYfkgr2LBhA5SUlBh/SLOzs5GYmMja5suXL1lXjL29vfHs2TOhMg0NDVbl+kdga2uL8+fPM57Lzc1Ft27dWCMZOTs7izhNuri4SKVIsD3fwsJC9OvXD4qKiiLP19PTE7Vr10ZkZCRjpKNPnz7h2LFj6Nu3LwwMDESi4qiqqmLlypUS+yYtUVFR8PPzE/nMKti8eTPMzMxQp04dTJw4EfHx8UhJScH169eRlJSEqKgo9O7dG2pqaujTp4/Qc5s+fTo0NTXRsWNHrF27FlevXsXz58/x7t07ZGZm4vDhw5gwYQIsLCzQpEkTEZtqceP3+PHj0NHRYVU+//jjDxHlXJpxWJPxUBO0tbXRoUMHkc+hqKgI06ZNg4KCAkJDQ0XkxD2jW7duCSIcMVGd8StJtqysDFOmTBH4NlSFbTLy4MEDODo6sva3JmNp4MCB0NPTQ2hoKBISEoR2E4uLi5Gamoo1a9agadOmsLa2FvousbOzg7e3N+Li4hi/vwHg3r17mDJlCoyNjbFjxw7GOhz/LTjlnoPjF4EpRGBl8vLyWFe7ExISxMo+ffoU3t7e1epXQUEB62rk7Nmzxa5YpaSkICgoqFrtykJVU6IfzZcvXyTWYfvRrexgXIG0/W3dujU+fvzIen7RokWoVauWSPnRo0fRvn178Pl8aGhowM7ODi4uLjAzM4OcnByMjY0xZcoURiWoakSZv4Pv379j586d8PX1hY6OjlCEHRcXF4wbN05ohbwyr1+/xvz58+Hq6irk0Mrn86GlpYWePXvixIkTjLLR0dFiV9ofPnyIOXPmSH0f0nyuNRkPNUGcORoAXLt2Dc7OziLlZ8+eZd0xBMrD6LLtolV3/AJAYGCgWHOhuLg4tGnTRqRc3GQkPz9f7E5DTcZSamoqhgwZIpgQKigoQF1dXSBfv359bNiwQWS8FRUVYdWqVahduzbk5eXh5OQEb29vdOnSBc2bN4eenh6UlZXRr18/sU63HP8tOIdaDo5fmM6dO9PmzZvJxMREZtnhw4fT3LlzSV9f/yf0jJ3nz5+Tqakp8fk1y8F3/vx5qlevHmlpaUmsq6GhQampqazJdGQhJyeHzMzMSE5OTmw9TU1Nun37drXa/JH9Fcf79+8pJSWFsrOzqbCwkPT19cnd3Z3c3d1r9PlI+my+f/9OV69epezsbPr69SsZGBiQu7s7qyNzVfLy8qiwsJD09PRIQUFB6n59+vSJnj59KrhXW1tb4vF4UssTEV24cIEaNGhASkpKMskRVf9z/VHj4dWrV1RcXEyWlpZS1Y+MjKTQ0FDS1tYmIumdsXfv3k2+vr6kpqZWk+7+Y+Tk5Eh8RtUdSwAoLS1N6J1zc3OT6nv45s2blJycLPK+tmnThnR1daW+P47/AP/w5IKDg+MfpCYrej/SVGXOnDk4d+7c39puRYKsymHj2AgNDcXbt29r3GZFuw4ODoyxtStTk8/Gx8eHNbGPrDx9+lRm2+2awvbZXLhwAf7+/lBWVgafz4euri7MzMwECYHs7OywaNEimWLn/93UZPzu3LlTql2eqvyo8SAplGtVqnuvNXlGNTFBqm67w4YN+2HfDxwcPwJ5yeo/BwcHhyj4gZt+27Zto8jISGrbti0dPXr0b2k3KyuLsrKy6MSJExLrrlu37oe0SUR05swZysrKon379gnC5/1oEhISfti1rK2tyd7enhYsWPDT+lsVps+mW7dudO3aNerXrx+dOHGCGjRoQKqqqoLzT548oeTkZNq9ezctW7aMduzYQe3ataMjR45I3a6vr6/Q32lpaVLLurq6SlWvJuNXXEhJcfyo8bBjxw76+vWr1PWre681eUbZ2dlUXFz8t7YbGxtL48ePl3oXMzExkdTV1alFixZERLRmzRratGkTOTk50Zo1a0hHR0eofn5+vtR90dTUZD03e/ZsCgoKIisrK6mvx/HfhFPuOTh+YaysrGQyS/hZZGVl0bdv3+jcuXN/W5tWVlZkZWVFrVu3ZjyfnZ0t2MKubPrRtGlTUlZWrna7rVq1olatWlFgYKDYegMGDBD7Q12VmpqqsCFuMlJaWkrLly+n+Ph4ysnJoaKiIqHzHz58qFabTJ9N+/btae/evaxmHTY2NmRjY0MBAQF07949evnyJRER+fn5CdXj8XhCSlxlU4iqscnd3NwE9SWZTPyMuOZ5eXl08OBBxnHYoUMHatasGavszxgPDRs2rLbs/zKyTgomTJhACxcuJCKiO3fu0Lhx42js2LF0+vRpGjt2rEgOAm1tbanNv8SNw6NHj9K8efOoVatWFBwcTD169KjRdxnHv5h/bM+Ag4ODoxrMnz9frBMdAMydOxePHj1iPZ+Xl8fqiLtz5040btwYPB4PRkZG8PDwQPPmzeHo6AhFRUVoampi2LBhIplQAUgVaz0mJkZiHVmoiamKpIyXkpgxYwZMTEywePFiKCsr448//kBwcDD09PRYs8wy5R+o2qc//vijRv1iIykpCR4eHkhMTEReXh7y8/ORmJiIBg0aMIZqrMh4m52djYMHD8LW1hbr169HamoqUlNTsX79etjb2+PgwYNS90Ea05qXL18iJCQEKioqqFWrFvr06YOxY8di2rRpGDZsGFq2bAlVVVU4Ojpiz549QrI/w3Rp27Zt+PTpk9T1K8jJyamWSVdycrLEkJ9s1MQEqbrmd7Ka0FXO/TFr1iz07NkTAHDjxg0YGRmJ1D979qzgiI6OhrGxMSZPnozDhw/j8OHDmDx5MkxMTKTKGZGamorRo0fD0NAQ2traCA0NlSrPCcd/C0655+D4BcnJycH58+eRmJiIGzduyPRDWlRUhJycHNy/fx/v37+XWN/Ly0usffnbt29ZI1pUlwqb7aSkJMbzbIlm3N3dUb9+faxatYoxOde3b99w5swZDB06FPr6+oiPjxc6r6ysjMWLF6OsrIyxza5du7KGtASArKws7NixA3PnzsXkyZOxdOlSnD59GoWFhYz1fX19YWJignHjxuHcuXMikYUeP36M6OhodOjQAcbGxiIKbKNGjfDgwQPW/kjCxsZGEFNbXV1dMKGKiopC3759GWUUFBQQFhbGGAXpzp078PDwgKmpabX7VAHTZ+Ds7Izk5GSR8vPnz6NOnTpir9ewYUMcO3ZMpPzYsWPw8PCofkcZMDAwwLhx48RGL/n69St27dqFRo0aYfHixQBqPh7YUFBQYAx7KglZvle+fv0q1N/s7GwsX76cNXrMfxkdHR3BQkDz5s2xYcMGAOXvv4qKilhZLy8v7Nq1S6R8586daNWqldR9KC4uxoEDB9C1a1coKCjAxcUFK1asqNYkjuPfB6fcc3D8ImRnZ2Py5MmCOMwV4QB5PB6UlJTg7e2N+Ph4xtXcz58/Y/369WjVqpVgBbAilKClpSVCQkJYV394PB7k5OQEGRyrIimjY1lZGc6cOYO5c+di8ODB8Pf3x8iRI7F161ZWxzkej4egoCBBlktp26yc/EUSb9++Fbnnffv2wcDAAC1atBDaOYiJiYGuri48PT0ZdxSqu1uwevVqxtCHTNy9e1dEmevdu3eN4s6rqqoKJkHGxsaC+OqPHz+GpqYmo8zly5dRp04d2NraChJcVazWKyoqon///vjw4YOIXJ06dbBz506J9/vw4UOEhoZiwYIFIueUlZVFYtED5auZbFmSK8syKbjp6eliZT99+oRt27Zh8ODB8PLyQpMmTdC1a1fMnDmTNbmWLFmRK9ev6XjQ0dFhPHg8HrS0tAR/s5GYmIiAgADY2NhAXl4efD4f6urq8PT0xLx58/DixQtW2Xbt2mHdunUAyrPzGhkZwdzcHMrKyhLDbH779g3nz5/Hjh07sH79euzfvx9PnjyR6jnIOqGujKwLHRV07doVHTp0wNy5c6GgoIDnz58DKM8sbG9vL1ZWRUWFMZzsgwcPJE4MKvP9+3fs2bMH7du3h7y8vCB/hYaGhshuEMd/D0655+D4BQgPD4eGhgZ69uyJ7du3IyMjA/n5+SguLsbr169x6tQpzJ49W5B+vbLSumzZMujp6aF+/fqYM2cOjh8/jrS0NGRmZuLKlSvYsmULAgMDoaWlhQ4dOoj88PB4PGzcuBFaWlrw8/MTSaTCpmh//foVERERMDMzg7KyMho3bowePXqgf//+8PHxgYWFBeTk5ODj44NLly4JyVYkmomNjYWqqioGDRokpPT8zBTxr1+/hp+fH9TU1LB48WL4+vpCVVUVK1asYFxNruluQU3Zu3cvDA0NGZN3ScLBwQGXL18GALRo0UKgUO/ZswcGBgascoWFhRg1apRgFb9+/fowNjbGoUOHWGVOnTqFBg0aQFtbG7/99hsWLVqE2NhY7Nu3D5s2bcKYMWPQsGFDqKmpYdKkScjLyxO5RsuWLeHl5SVktvHq1St4e3vD09NT7L26u7ujX79+Qkrft2/f0K9fP7i7u4vUr4lpzT+Furo6OnfujOjoaMGxbds2yMnJISIiQlBWlYMHD8LBwQFGRkYICgrCunXrcOTIESQlJSEuLg4zZsxA69atoaSkhKFDhzJOXvT09ATZUTdt2gRXV1eUlpYiPj6edVelJiZI1Z1Q12Sho4KnT5+ic+fOcHV1xebNmwXlo0ePxsiRI8XKOjg4YOzYsSLlY8eOhYODg1hZALh+/TrCwsKgq6sLExMTTJo0CZmZmYLzS5YsgaGhocTrcPy74ZR7Do5fgPHjx0u9Gnjs2DHs3btX8HevXr0YVzur8u3bN6xZswabNm0SKq9I+pKeng4HBwe4uLgI2aeyKdrm5ubo2bMnjh49iqKiIsY2s7OzMX/+fFhaWmLjxo0ibQLlP2aWlpZo3LixQKlja1PWMIPi6vfr1w88Hg/q6upin19NdwtkgWlyAZSv/Pbu3Rva2toYOXIkxowZI3SwMWnSJERERAAonyTIy8vDzs4OioqKmDRpksS+9O3bV/CMMjIypLqHCxcuIDw8HG5ubtDW1oaSkhLMzMzQpUsXrFq1Sqw/RmZmJlxcXKCgoABbW1vY2tpCQUEBzs7OQgoOE1euXIGhoSH09fXRtm1btG3bFvr6+jAwMMCVK1dE6lfXtAYALl68KPlB/B9fvnwRKMWyUnU8ZGZmomHDhhg0aJDQJFxeXl6sP0nDhg1x5MgRiT4cz58/x4QJExjDz6qoqAgmt71798bs2bMBlJsQMq1I18QEqboT6poudPwIjh07BmVlZTg7OyM4OBjBwcFwdnaGsrIyo9lYZerWrQt5eXl06tQJBw8eZPSHePPmDXg83g/vN8ffC6fcc3Bw/FQqK9qfPn2Cj4+PkD08m6ItS7bE79+/C/2QVs0i+fr1a7Rs2RImJia4fPkya5vGxsaIiIgQaz5QVlaGkydPomPHjpg/f77I+Q8fPqBv375QVVXFlClTYGNjA0dHx5/itPYjTFUAoKSkBDNnzoS8vDxatGiB1q1bCw6mLJ1sXLp0CUuXLsXhw4fF1nv06BFatGgBIyMjbNiwAU2bNoWhoSEOHDggdVvVpaysDCdOnEBUVBRWrFiBkydPsk56qlJQUIANGzZgzJgxGD16NDZu3Mg6wauuaQ0A2NnZwdvbG3FxcSI7XRXcu3cPU6ZMgbGxsSB78Y8YD8XFxZg4caKQ2ZQk5f5HULduXURFRSEnJweampqCCc7169cZnUxrYoJU3Ql1TRY6Ku8k5eXliT0k8ezZM0ydOhXdu3eHn58fpk6dKlVs/7lz5wpMgDj+t+GUew4Ojp9KVUW7rKwMkyZNEtjD/wwTmQqznMoUFxcjNDQUysrKmD9/PmOb9+/fR69evaCoqIhGjRph+PDhmDdvHpYsWYJp06ahe/fuMDY2hoWFBdauXSuy8nX06FEYGxujUaNGgpXoL1++IDQ0FIqKipg2bRqKi4uFZGqyW/AjTFXu3r0Ld3d3WFtb4/Tp0zL1pTqsWrUKampq6NGjh0ChLS0tRWRkJJSVlVlt7nV0dASRTIKCgqqVqGr79u2MTp7fv3/H9u3bZb7ez6KoqAirVq1C7dq1IS8vDycnJ3h7e6NLly5o3rw59PT0oKysjH79+glNgn/EeKh8LUtLS0yZMgUKCgo/Xbnfu3cvFBQUwOfz0a5dO0H5/Pnz0bFjx5/a9t9B5e+kCjOeqkdFuTiePn3KOhll2oVgo6ysTOpJLcd/Dx7wAzPRcHBw/Cvp2LEjzZw5U2xcbCKiz58/09q1a0ldXZ3CwsKIiCg0NJSmTZtGFhYWEtuJi4ujkpIS6t+/v6BMTk6OXr16RYaGhiJ1g4ODqU2bNpSQkCASn1maFO6VefHiBZmZmREREZ/Pp9zcXJE2iYg2btxI4eHhVFxczBoT+vnz57R37146f/68SKr2Dh06UKdOnYjP54vIKSsr08yZM2ny5Mki55OSkigkJIR0dHTo9u3bgnITExMaOXIkBQYGkqmpKWN/ANBff/1Fy5YtI09PT5oyZYrQ+YsXL1JcXBxrfwcMGEDa2toi142MjKTZs2dTv379KCoqijQ0NBjbF8eLFy/owoUL9ObNGyorKxM6Fx4eLlJfT0+PVq5cKTRGKrh37x4FBATQq1ev6MWLF0Ln1NXVKS0tjWxsbEhOTo5yc3PJwMBApr6yjcX379+ToaGhVLHq09PTGWP6V02AdenSJWratKlU/SooKKDs7GxydnYWOXfz5k1BnPvKn2ubNm1IV1eX8XrVHQ9Vef/+Pf3+++905swZunz5MtWuXZuxXmRkJIWHhwslFWPjypVAfU2NAADjH0lEQVQr9O7dO+rcubPIudzcXHr16hXVq1dP8P5cvXqVNDU1qU6dOhKvLQ5UylVQUFBAampqUsvKWp+Jc+fOUfPmzUleXl5iPo9WrVqxnqvpGN6yZQstX76cMjMziYjI3t6eRo8eTSEhIVLeCcd/gn92bsHBwfF3sHnzZpiZmaFOnTqYOHEi4uPjkZKSguvXryMpKQlRUVHo3bs31NTU0KdPH6Et3unTp0NTUxMdO3bE2rVrcfXqVTx//hzv3r1DZmYmDh8+jAkTJsDCwgJNmjQR2bauunJfmVu3bgmi91TF0NAQISEhjPbMFXz69AkbN26Es7OzUMSX2bNnM4ZarCAlJYU1zn1NSE1NFXs+Ly8PgwcPFiqr6W5BTTA2NsaRI0eEyjp16iR1nPCtW7dCUVER6urqsLKygrW1teBgC28q6dolJSWYO3euSLm3tzfq1q2LwMBA8Hg8+Pv7IygoiPFgg8fjMZrL3L59W2wUGKDchtvV1VWwuloRaapi1bUq1TWtqUp2drbYsfxvYODAgdDT00NoaCgSEhKEnnFxcTFSU1OxZs0aNG3aFNbW1jh//nyN26yJCVJ1ze+GDh0qlfkLUO5UHhsbK1VdWWAbw9nZ2VBVVRUrO336dKipqYnEyFdXV8e0adN+eF85/jm4lXsOjl+EoqIi2rdvH8XFxVFycjJ9+vSJiMozdDo5OVGHDh3o999/Z1yde/PmDW3ZsoX27NlDd+/eFTqnoaFB3t7eNGTIEGrfvr2IbOUVKybev39Px44do0GDBgmVf/jwgebPn09bt24lBQUFatCgAZmampKysjJ9/PiR0tPT6d69e9SgQQOaPn06+fj4iL3/58+fk6mpKeOKOxOFhYWkoqLCeO7Vq1dkYmIi1XU6d+5Mmzdvlli/ursFFWRlZcmcffT9+/ekp6cnVKahoUGpqalkY2MjUd7CwoJCQ0NpypQpUj9XJurWrUsJCQlid4dev35Ny5cvp8ePH9P+/fupY8eOpKSkxFj34MGDQn+7u7sTj8ej1NRUcnZ2FhqLpaWllJWVRR07dqT4+HjW9rt27UpycnK0adMmsrGxoatXr9L79+9p3LhxtGTJEmrZsqVQ/eLiYtqwYQOtXr2aHj9+TA4ODkLj9/79+1RQUEA9evSgKVOmkIuLi0ibZWVlpKysTPfu3SN7e3vWvknLp0+fpFqxrw5paWm0Zs0a2rt3L+Xl5ZGcnBwpKSnR169fiaj8MxgyZAgFBAQIPreqGY/FceDAAaG/T58+TZMmTaJHjx5R+/btGb8fUlJSKD09nUaMGEFTp04VZHx+8OABTZ8+nY4cOUJubm6MspcuXSIFBQWaMmUKDRkyhOTk5GjGjBm0cuVKatasGfn6+rK2uWfPHjIzM6ONGzdS3bp1Re4lMTGR1NXVqUWLFkREtGbNGtq0aRM5OTnRmjVrSEdHR0Rm7NixREQUFRVFv//+u9AuSWlpKV25coXk5OTowoULrM9QX1+fVq1aRX379hUq3717N40cOZLevXsn5afB8W+HU+45OH5R8vLyqLCwkPT09EhBQUFquU+fPtHTp08Fyqetra3UqdEr2L17N/n6+kq11f3t2zdKSEhgNE3o0KEDo1LEhKamJt2+fVsqpZWIqE6dOrRr1y7y8PAQKt+3bx8NGzaM3r59K9V1ZFGWa4KcnBx5enpScHAw9erVq9pp5WXpr56eHl29epVsbW2r1VZ12iQiqlWrFl2/fl1kYsLGnDlzBP+OGzeO1NXVBecUFRXJ2tqaevbsSYqKiqzX0NfXp9OnT5OrqytpaWnR1atXqXbt2nT69GkaN24c3bp1i1W2OqY1FTg7O9OWLVuoSZMmUt1rBQsXLiRra2vq06cPERH17t2b9u/fTyYmJpSQkED16tVjlFu7di0dOHCAdHV1KTQ0lLy8vATn3r17R40aNaInT56wtguA0tLShO7Vzc2N9PX1ReoGBQUJyR08eJC0tLSoQYMGRER048YN+vTpE/Xo0YO2bdvG2F5NTJCeP39O8fHxrN8tTBPqmix0VFC3bl1auHAhderUie7cuUMNGjSgcePG0enTp8nR0ZHxXtu0aUNE5YslTZs2FRqrFWN4/PjxYieBOjo6dPXqVZE6Dx8+pEaNGgkWfDj+B/gntw04ODh+TTQ0NGRK1/4jkDVF/IgRI6CkpIQFCxagrKwMnz9/RkBAgMxJn2Rtt7rcuXMHY8aMgaGhIbS0tDBkyBCxJk1sODs7S216MGHCBNYIPLIgzTP6EQ610dHRMmVNrYy2tragjzY2NgLn40ePHsmUPEhW/vzzT7Ro0UKm6FEAUKtWLUGSrJMnT0JbWxsnTpxAcHCwkMNqZaKioqCqqoqwsDAMGDAASkpKQhGhfmZ+iIkTJyIkJETI7KykpARDhgzB+PHjf0qbNeXjx4+4ffs2Ll26hMzMTKkdVNXU1JCVlQUAmDVrFnr27AkAuHHjBmNkoMoEBgZKFVGHiREjRjCGth03bhyGDx9erWty/DvhVu45OH4Bjhw5InXdqo6BlbG2tqbBgwdTYGCgTM6uVfm7VrNr2mZiYiIFBQWRnZ0dvXz5kjQ1NWnnzp3k5OQk9TVcXFzo+PHjrCYnFdvt0rBs2TKJdUpKSujo0aMUHR1Nx48fJ3t7ewoODqaBAwfK7IAqidLSUurSpQsVFhZS3bp1RXaApOkvEVGnTp1oy5YtYk2XfoRD7bNnz4jH45G5uTkRlTtr7tq1i5ycnGjIkCFiZVu2bEnjxo0jPz8/6tevH338+JGmT59OGzdupBs3bois4v4odHR06OvXr1RSUkKKiooipmIfPnxglFNRUaGHDx+ShYUFjRo1ir59+0YbNmyghw8fUuPGjenjx48iMs7OzjRt2jTq168fEZU7Bfv5+dHQoUNp7ty59Pr1azI1NRXrtLllyxYKDg4WKS8pKaEZM2bQggULGOUMDAwoJSVFxCzwwYMH1KxZM3r//j1rm9WluLiYateuTX/++adM73RN0dXVpZSUFHJycqIWLVrQoEGDaMiQIZSdnU1OTk4CUyZpyM/Pp9OnT1OdOnUkOh2PHDmSduzYQRYWFoKdoMuXL9OzZ89o0KBBQu+vtO8ux78TZiNYDg6O/yn8/PyE/ubxeFR5Xl/ZrEbcD/e4ceMoOjqa5s6dS23atKHg4GDq3r07q+3zj6KgoIAiIyPp1KlTjFFZxJkJVDB16lSJJhBVad++PfXo0YPWrVtH8vLydPToUZmVAElKX1Vzjhs3blBpaalAyXn48CHJyclR/fr1pWpPXl6eunfvTp06daK1a9fSlClTaPz48TRlyhTq06cPLVy4kFGJfvbsGWVnZ9PXr1/JwMCAnJ2dJX6u8+fPpxMnTgj6WnkcyWKqlZCQILFO06ZNyc/Pj+rXr08AKDw8nNUnYuvWrYzl/fr1oyFDhtDAgQMpNzeXvL29ycXFhWJjYyk3N5dmzpzJ2v706dOpoKCAiIjmzZtHXbp0oZYtW5Kenh7FxcWJ1K+w85eGmzdvsp5bsWKFVNeoio6ODj179owsLCwoMTGR5s2bR0Tl5i9s73hWVpZQRK2mTZvS6dOnqW3btlRcXEyjR4+W2O64ceMoISGBNm3aJHjf7t+/T/369aO8vDxW5b6kpIQyMjJElPuMjAyR952JU6dOsX4/sI0HBQUF+v79u8xmhUTVs5uvoEWLFjR27Fhq3rw5Xb16VTB+Hj58KJh4svHbb7+Rp6cnjRgxggoLC6lBgwaUnZ1NAGjPnj3Us2dPVtm7d+8KzAwfP35MROWTKgMDA6Hvqeo8D45/Gf/ktgEHB8ffT1JSEjw8PJCYmIi8vDzk5+cjMTERDRo0EEr0Io7bt28jPDwcBgYG0NHRQVhYGG7cuCF1H5KTk1FYWCh1fX9/f5iYmGDixIlYvnw5VqxYIXT8DB49eoRGjRrB0tISJ0+exLRp06CkpIQJEyawZsytTE5ODs6fP4/ExETcuHFDKnOQpUuXomvXrkJx3j98+IBu3boxZvVk4tq1axg2bBh0dHRgbm6OadOm4cmTJ0hJSYGXlxcaNmwoqJudnY3JkycLIhZVRIDh8XhQUlKCt7c34uPjWTOPamtrY9u2bVL1qyrfvn3D+fPnsWPHDqxfvx779+/HkydPWOvn5uZi0qRJ6NWrF/h8Pnx8fODn58d4sKGtrY379+8DKDdBadasGQDgxIkTrNF9xPH+/XtWU4zZs2cLjsmTJ0NTUxNNmjQRZP1t2rQpNDU1MXnyZJnblYawsDBYWVnB29sbenp6gog9e/bsgbu7O6OMhYUFYySbe/fuwcjICAMHDpRolvPkyRM0b94cpqamOHnyJFavXg0VFRUMHDhQrCnVmDFjoKOjg8WLFyM5ORnJyclYvHgx9PT0xGZJBsqfNZ/PR6NGjdCtWzepxwMALFiwAAEBASL5JyTh4uIiyAiblpYGJSUlTJkyBY0bN0ZgYKBY2adPn6Jz585wdXXF5s2bBeWjR4/GyJEjxcoaGRnh9u3bAICdO3fCzs4OBQUFWLt2Ldzc3GS6B47/XTjlnoPjF8PZ2RnJycki5efPn0edOnVkulZRURFWrFgBJSUl8Pl8uLq6YsuWLT88OYqWlpYgW6a0lJWV4cyZM5g7dy4GDx4Mf39/jBw5Elu3bpXKplxdXR19+vTBx48fBWUXLlyAra0t649oTZVlU1NT3L17V6T8zp07MDExEdvfpUuXwsXFBQoKCujWrRuOHj0q0k5mZibk5OQAAOHh4dDQ0EDPnj2xfft2ZGRkID8/H8XFxXj9+jVOnTqF2bNno3bt2nB2dmbMsGtkZCSUGVgaLly4AH9/fygrK4PP50NXVxdmZmZQUVEBn8+HnZ0dFi1aJFYRtLa2xrt372RqFxC2de7atSsiIyMBlCtbysrKMl9PWoKDgzF9+nSR8pkzZ0oMySopmylbZtOioiIsXrwY4eHhuHnzpqB8+fLlQplTK9O3b1+MGjWK8dzdu3dhYGAglc19aWkpwsPDwefzoaCggN27d0sls3DhQpiamgreGVNTUyxcuFBi+FdxoUQl4efnBw0NDZiYmKB9+/bo3r270MFGTezma4KysrLg+2vgwIGYNGkSgPIxrKamJvV1nj17xmWr/R+GU+45OH4xlJWVGVOop6amSq3gFBUVIS4uDh07doScnByaN2+OrVu3Yt68eTA2Nkbfvn2F6t+/fx+zZs2Cl5cXbGxsYGxsjLp162LQoEHYuXOnxFVta2trpKenS9W3r1+/IiIiAmZmZlBWVkbjxo3Ro0cP9O/fHz4+PrCwsICcnBx8fHxw6dIl1uuwKQv5+fkiseqBH6Msq6ur49SpUyLlp06dgrq6utj7trOzw/z58/Hq1SvWOt+/f0d0dDQAYPz48Yzxspk4duwY9u7dK1I+f/58iSuNlfH19YWJiQnGjRuHc+fOicRvf/z4MaKjo9GhQwcYGxtLtZMkyw5Qo0aNMGnSJJw/fx7KysqCFdBLly7BzMxMYjuLFi2Cj48P6tevD3d3d6FDHJqamoyToIcPH0JTU1OsLFs2U1kzm0pDamoqtm7dynr+7t27mD17tsTrHD58GAYGBmjRogUMDAzg5eUlNqZ8VZgmK+LQ1dXFo0ePpK5fmcDAQLEHGzo6OoKsvc2bN8eGDRsAAFlZWVI5WJeUlGDfvn34448/MG/ePOzfv1+qHBb29vaIi4vDly9fYGBgIPi+uH37NvT09MTKlpaWYs6cOdDU1BSMHS0tLcydO5d1wYHjvwmn3HNw/GK0bNkSXl5eQsmEXr16BW9vb3h6eoqVvXHjBkaMGAE9PT0YGhpi3LhxyMjIEKpz9epVwSTh5s2b8Pb2hpKSEtq0aYNJkyZh5cqV2LRpExYuXIiBAwfC2toaurq6iIyMZFXyY2Ji0KtXL6mS+Zibm6Nnz544evQoq/lMdnY25s+fD0tLS2zcuFHiNaXhRyjLAwcOhKWlJfbu3Ytnz57h2bNn2Lt3L6ytrTFo0KAf0s8fiZ+fHzQ1NVGrVi106dJF4qrn6tWrJSYdquDu3busyn1paSnmzp0LU1NTyMnJCaLYTJ8+XcjMoSpnzpyBtrY2+Hy+0Ir5lClTxK7SAuWr2vr6+ggNDcWsWbOEzG4kKbxGRkaMSvPWrVthaGgoVjY6OhrGxsYiiYdMTEwQHR2Ns2fPCo6qcn/++afg7wkTJkBLSwtNmzZFdna22DZrwpAhQ6CkpITFixejrKwMr169go+PD3R1dREXF/dT2pw4cSJj4rOfSdeuXdGhQwfMnTsXCgoKglXwEydOwN7eXqxsZmYm7O3toaqqCnd3d7i5uUFVVRW1a9eWOElZs2YN5OXloa2tDVdXV4FSvnLlSrRu3Vqs7OTJk2FgYIC1a9ciNTUVt2/fxpo1a2BgYICpU6fKcPcc/3Y45Z6D4xcjMzNTYL5ha2sLW1tbKCgowNnZGZmZmWJl+Xw+OnTogPj4eFbF+cuXL4IVL0tLS6xatQrv378Xe92LFy+id+/eiIiIYDzv5uYGDQ0NqKurw8XFReyqqSwhA79//y7RrOTevXs4fvy4QLE6fPiwSFbXH0VBQQGGDRsmMHPi8/lQVFTEsGHD8OXLF4nyHz58wOLFizF48GAEBwdj8eLFEp99TajuqmdNmTNnDmxsbBAbGwsVFRWBch8XF4cmTZqIlS0pKRHyaQDKV1vZsihXoKmpKbNpWAULFiyAkpISwsLCEBMTg5iYGISFhUFFRUViKFEvLy/s2rVLpHznzp1o1aoVq5yDg4NgVffixYtQUVHBhg0b0LVrV4kTGXE8ffpU7Aqzs7OzYEekMqtXrxZrNpKbm4sBAwbAxMQEcnJyIrsT4ggPD4e2tjY8PT0F4R4rHz+DmtjN+/j4oGPHjkLv5rt379CxY0d06tRJYtvXr1/HgQMHhDIf//nnnxLHp4mJCQ4fPixSfujQIZiamkpsl+O/AxcKk4PjFwQAJSUl0f379wkAOTk5kbe3t8QoCU+fPiUrKyup2ykqKhKbGEja+hVJiNiYNWuW1G1Iy5MnT6h79+50584doehCFc9IXFShmlJQUECPHz8mAGRnZydVsq9z586Rr68vYxKgI0eOUKtWrYTqd+zYkWbOnCkUHYWJz58/09q1a0ldXZ3CwsKqf1PVAADjmLSzs6MNGzZQ27ZthUKc3r9/n5o2bcoY5rEqkZGRFBoaKnXGVicnJ9qzZw+5urrKehtERBQfH09RUVGUkZFBRESOjo40atQo+u2338TKqaqqUmpqKmPiITc3N9awiaqqqnT//n2ytLSkSZMm0atXr2jHjh107949at26tdRJ2KrC5/PJ3t6eFixYwJhh9vv376xRlh48eMCYAZuIyMfHh3JycmjEiBFkYmIi8rl369aNtU8VCZ6Y4PF4dPr0adbzPyqqkSyoqanR5cuXRbLXpqamUvPmzenLly9SXefChQvUoEEDqaOVKSsrU1paGjk4OAiVP3jwgNzc3KiwsFC6G+D49/MPTiw4ODj+AbZv385o/vL9+3ds3779H+jRj+Xp06cy1WdzKuvSpQu6deuGN2/eQF1dHenp6UhOTkajRo0YI4p06NBBkDRIHPn5+YiMjMTq1atl6qcknJ2d8fvvvzMmAXJ2dhapv3nzZpiZmaFOnTqYOHEi4uPjkZKSguvXryMpKQlRUVHo3bs31NTU0KdPH0Yn5K9fvwqZSmVnZ2P58uU4ceIEYx/r1KmDnTt3SjTNefjwIUJDQ1lXtZWVlQWmJZUTYN27d09qp0JZE6klJCSgY8eOP9WkhQkHBweMHTtWpHzs2LFwcHBglTMwMBA40rq5uQne7UePHsnkeFmVs2fPYtu2bSJ+NTVFXV0dt27d+qHXlAZxkYwmTZrEanp148YNId+lQ4cOoVu3bpgyZYrE8a2jo8P4XZGSkgIdHR2p+y7rGG7UqBHjrsKIESPQuHFjqa/D8e+HU+45OH4x+Hw+ownCu3fvJG5/a2trQ0dHR+TQ1dWFqakpPD09hWyLpYmSUUFOTk61zR4qY2hoiJCQELHZWT99+oSNGzfC2dmZNdusnp4eUlNTAZSbZFSEUDx16hRjtJwfoSwD5T4LEyZMQJ8+faSO3AGUK7wVfazM/fv3WR2lv3//jp07d8LX1xc6OjqCKCV8Ph8uLi4YN24c4zUraNeuHdatWwegPFunoaEhzM3NoaysjLVr14rUP3XqFBo0aABtbW389ttvWLRoEWJjY7Fv3z5s2rQJY8aMQcOGDaGmpoZJkyaxOlXWr18fMTExAISV+9mzZ6NFixZin1MFsmYOfvPmDVq3bg0+nw91dXWRd0ActWrVYozu8/HjR4khOI8dOwZlZWU4OzsjODgYwcHBcHZ2hrKysiAUIxP9+vWDh4cHgoODoaqqKmj/8OHDjJO9H8nevXvRu3dvNG7cWGrHY0dHR6GoPn8X1Y1k1KBBA+zbtw9AuSO4srIy+vbtCzs7O9aIQxUMHDgQzs7OuHz5MsrKylBWVoZLly7BxcUFAQEBUvdd1jF89uxZqKmpwdHRUWC65+joCHV1dcYFC47/Lpxyz8Hxi8Hj8RgdP2/fvi1RSVm2bBn09PQwYMAArFy5ElFRURgwYAD09fURERGBkJAQKCkpCZxUPT09Ubt2bURGRjJGu/n06ROOHTuGvn37wsDAQMiWXUdHB2/fvgXAPqlgUqzevXuHcePGQUdHB4aGhujUqRNCQkIwYsQI9O/fH+7u7lBUVESzZs2QkJDAeq/a2tqCH04bGxucPn0aQPnKJ1s0jJoqy7t374aCggI6d+4MRUVFdOnSBbVr14aWlpZEG/ZmzZrh4MGDIuUHDx6UaIdewadPn/Dq1Sup4vgD5ROgitCdmzZtEjj4xcfHiw2reuHCBYSHh8PNzQ3a2tpQUlKCmZkZunTpglWrVgmFH2XiyJEj0NLSQmRkJFRVVbF48WKEhIRAUVFR6lwNsipGbdu2hb29PSIjI7Ft2zZER0cLHeLg8XiME+rc3FwoKipKbDsnJ0fg9Ovn54epU6dKDOf68eNHhIWFwdfXF8ePHxeUz5w5E/PmzZPYZnWJioqCuro6wsLCoKioiKFDh8Lb2xtaWlpinTZPnDiB9u3bC8JLykp1J8XVjWSkqakpcH6NjIxE+/btAZSvvpubm4tt8+PHj/D19QWPx4OioiIUFRXB5/Ph5+cncexXRtYxDAAvXrzA1KlT0aNHD3Tv3h3Tpk2TKZIRx38DTrnn4PhFcHNzg7u7O/h8PurWrSu0mubq6goNDQ307t1b7DV69OghWKmtzPr169GjRw8A5VEbXFxcBOeOHj2K9u3bg8/nQ0NDA3Z2dnBxcYGZmRnk5ORgbGyMKVOmiCg/0dHRAvOhqoqUNIpVYWEh9u/fj9GjR8PPzw8dOnRA//79sWTJEqmcblu0aCFQlvv27YuOHTsiJSUFgwYNknrlU1ZluW7dugJznYof7rKyMvz++++YOXOmWNk9e/bA0tJSJAmQtbU19uzZg9TUVMHxo1BRURGYQfXu3VtgupCTkyNVOMCakJiYCE9PT6ipqUFFRQXNmzdnNQdiIicnR6rQgxWoqKgwOoqKo8IBm8fjYceOHUJO2QcOHEBYWJhY05p/G+np6RJ3GmrXri1wAK6sfM6YMQNhYWGsctra2gIlV9adkZpMiqsbyUhDQ0MwKfD29hYk05MlZ0JmZiaOHDmCw4cPSwxmwMTOnTulcrQHysMXt27dGg8ePJC5HY7/HpxDLQfHL0KFU+qcOXNo3LhxpK6uLjinqKhI1tbW1LNnT7EOsOrq6nT79m2ys7MTKn/06BG5ubnRly9f6PHjx+Tq6koFBQVCdd6/f08pKSmUnZ1NhYWFpK+vT+7u7uTu7k58Pv+H3WdaWhq5uLjU+JonTpyggoIC6tGjBz158oS6dOlC9+/fJz09PYqLiyMvLy+h+h4eHnTq1CnS0dGhuXPn0vjx40lVVVWmNtXU1OjevXtkbW1N+vr6dObMGapbty5lZGSQl5cXvXr1ilVW0v1WOAXzeDxGZ+CHDx/S2bNn6c2bN1RWViZ0bubMmYzXdHV1pZCQEOrevTu5uLhQYmIiNW3alG7cuEGdO3em3NxcKe76v4GHhwetXbuWmjRpIrVMxWdS2SG7AgUFBbK2tqalS5dSly5dhM5VHsNpaWli2xDn4JucnEwbNmygJ0+e0N69e8nMzIxiYmKoVq1a1KJFC6nvo4LU1FTy8PAQ60yuqqpKGRkZZGVlRYaGhpSUlET16tWjzMxMatKkCb1//55Rbvv27WLbDggIYD3n6upKQ4cOpbCwMIGDda1atWjo0KFkYmIi1iE/MjKSZs+eTSEhIYLP9vLly7R161aaOXMmTZ48mVHOy8uLLCwsyNvbm4KDgyk9PZ3s7Ozo3LlzFBAQQNnZ2axtsn0/FBYW0uLFi1nft5piYGBAFy9eFHHO5vjfg1PuOTh+MbZv307+/v5SR1iojKWlJY0ZM4bGjBkjVL58+XJavnw55eTkUFpaGrVv355yc3Np5cqVNGTIEFJWVqacnByysLCQOjIFE2/evGFUPisrOHJycvTq1SsyNDQkGxsbunbtGunp6VW7zcp8+PCBdHR0GO9BRUWFMjMzydzcXKgPsmBhYUEJCQlUt25dqlevHk2ePJn69u1Lly5doo4dO1JeXh6r7NOnT6Vup2rEo02bNtGwYcNIX1+fjI2Nhe6Px+OxRgnZt28f9evXj0pLS8nLy4uSkpKIiGjBggV0/vx5On78uNh+nDp1ik6dOsX4mW7dulXifdy4cYMyMjKIx+ORk5MTubu7i63P9tnxeDxSVlYmOzs7CgwMpKCgIJE6J0+epDlz5lBERATVrVuXFBQUhM5ramqytlurVi26du0a6evrS7wnovJJQW5uLhkaGhKfz2ecHFT0m03R3r9/Pw0cOJD69+9PMTExlJ6eTjY2NrR27Vr6888/KSEhQURm7NixYvv19u1b2rVrl1jl3sbGhvbt20ceHh7UsGFDCgkJoaFDh9LJkyfJ39+fPnz4IOHuZacmk2Ki6kUySktLo/79+1NOTg6NHTtWELFr5MiR9P79e9q1axerLNv3w/v378nQ0FDs8+3evbvEMdyvXz/GqETjxo0jBQUFioyMZL0+x/8G8v90Bzg4OP5evLy86O3bt2Rubk5ERFevXqVdu3aRk5MTDRkyRKzsjBkzaNiwYXTmzBlq1KgR8Xg8unr1KiUkJND69euJiCgpKUkQdnHs2LHk7+9PysrKVKtWrWopvETlSlxAQABlZGSIKDlVFRxtbW3KysoiQ0NDys7OFlEaa4Kuri7rOTc3NwoKCqIWLVoQAFqyZInQ7khl2FbmWrZsSUlJSVS3bl367bffaNSoUXT69GlKSkqitm3biu2bLCFKqzJv3jyKiIigSZMmySTXq1cvatGiBb169Yrq1asnKG/bti11795drOycOXNo7ty51KBBA8bQh+J48+YN+fv709mzZ0lbW5sAUF5eHrVp04b27NlDBgYGjHIzZ86kiIgI8vHxoUaNGhEAunbtGiUmJlJYWBhlZWXRsGHDqKSkhH7//Xch2Y4dOwrurTLidkMqyMrKEin79OkTaxjOrKwswT0wyUrDvHnzaP369TRo0CDas2ePoLxZs2Y0d+5cRpmoqChyc3NjnahIE6LRy8uLjh49Sh4eHhQcHExjxoyhffv20fXr1xlDZ+bn50t1P+ImT7q6uvT582ciIjIzM6O7d+9S3bp16dOnT6yhQivz22+/SQxJWhVXV1e6c+eOSPnixYtJTk5OrCxYQrympqaK/Y4hItLS0qJDhw6RtrY21a9fnwDQrVu36NOnT9S+fXuKi4ujhQsX0qlTp6h58+ZCskVFRbR582ZKSkqiBg0aiITYXbZsmdi2Of47cCv3HBy/GC1btqQhQ4bQwIEDKTc3lxwcHMjFxYUePnxI4eHhEreEL1y4QKtXr6YHDx4QAKpTpw6NHDmSMV66paUlTZkyhTp16kS1atWi69evs65eWlpasrbp6upKdnZ2NGnSJDIyMhL5Yays2A4ZMoR27NhBJiYmlJOTI1hJZ+LJkyesbX779o1WrVpFZ86cYVxZrrqa/eDBA5o1axY9fvyYbt68SU5OTiQvL7p+Im4l/MOHD/Tt2zcyNTWlsrIyWrJkCaWkpJCdnR3NmDGDdHR0WPtLRPT48WNasWKFYDW7YgXS1tZWrJympibdvn2bbGxsxNYTx+7du8nX11eqmPxERCYmJrRo0SIaOHCgzG316dOHHj9+TDExMeTo6EhEROnp6RQQEEB2dna0e/duRrmePXtSu3btKDQ0VKh8w4YNdPLkSdq/fz+tWrWKNm7cKKK4nTt3TmyfquYRqMzChQvJ2tqa+vTpQ0REvXv3pv3795OJiQklJCQITYx+FKqqqpSenk7W1tZCuQCePHlCTk5O9O3bNxGZOnXq0PTp02nAgAGM17x9+zbVr19f7ESmrKyMysrKBGM/Pj5eMIZDQ0NFzP4qdibYkGby1K9fP2rQoAGNHTuWIiIiKCoqirp160ZJSUnk4eFBBw4cYJWtCZ8+faJ9+/bR48ePacKECaSrq0s3b94kIyMjMjMzE6lfsXOUl5dHmpqaQvddWlpKX758odDQUFqzZg1rm5MnT6b8/HxavXq1wOyrrKyMRo0aRRoaGhQREUGhoaF07949SklJEZIVlw+AiOjMmTOy3D7HvxhOuefg+MXQ0dGhy5cvU+3atWnlypUUFxdHFy5coJMnT1JoaCirwltcXExDhgyhGTNmSK0Ebty4kUaOHEklJSWsdaT58dbQ0KBbt26J2PqzkZiYSI8ePaLw8HCaO3cuaWhoMNYbNWoU6zX69etHSUlJ1KtXL8YJhbjEWZXNKv4uTpw4Qb6+vuTm5kbNmzcnAHTx4kVKTU2lo0ePUrt27Vhlg4ODqWHDhiJKryzIOkHQ09Ojq1evSpx4MKGlpUV//fUXNWzYUKj86tWr1L59e/r06ROjXE18RmqCjY0NxcbGUrNmzSgpKYl+++03iouLo/j4eMrJyaGTJ09KdR1ZnrGtrS1t2LCBvL29hZT7HTt2UGRkJKWnp4vI9O/fnwwNDWn58uWM10xNTSV3d/cfuhsmadJUgbjJk6yTYl1dXXr48CHp6+uzmmpVvjYTaWlp1LZtW9LW1qbs7Gx68OAB2djY0IwZM+jp06e0Y8cOEZnt27cTABo8eDCtWLGCtLS0BOcq/J6aNm0q9jkYGBjQhQsXRBJRPXz4kJo1a0bv3r2jO3fuUMuWLVnfA47/fTizHA6OX4zi4mKBvf1ff/1Fvr6+RFS+aifONlVBQYEOHjxIM2bMkLqtIUOGUN++fenp06fk6upKf/31V7Xs39u2bUupqalSKfcVNv8dO3akGzduCFa0ZOXYsWOUkJAgsrXNRmWH2lmzZrGa5EiDNL4FVZk8eTKNGTNGxJ528uTJNGnSJLHKfYUSVJE1s6o9eXh4uMQ+y7pOFBISQrt27ZJpPFVQVlYm0kei8jEqTvHU1dWlo0ePiviMHD16VGAOUVBQIHG81K1blxISEsjCwkKq/r569UpQ988//6TffvuN2rdvT9bW1tS4cWOprkEk2zMeOnQojRo1irZu3Uo8Ho9evnxJly5dovHjx7Puzi1dupS+f//Oes169epJpdh/+/aN0tLSGMdwxfdNBeKUdmmpbMrC5/Np4sSJNHHiRNb6y5cvF3zGK1asqFabY8eOpaCgIFq0aJHQePHx8aF+/foxygQEBAgWOry9vQWmkbJQUlJC9+/fF1Hu79+/L1ggUVZWZpywDB48mKKiokTGd0FBAY0cOVIqPxeO/wh/W1weDg6OfwWNGjXCpEmTcP78eSgrKwvC+126dAlmZmZiZQMDA7F06VKp24qKikJhYSGA8nCWX79+rVaf3759i06dOmH27NnYt2+fUEjBw4cPC9WtnKSLLXmQNDg6OsoUNlJZWRnPnj0T6YMsXL9+Hc7OzuDz+YIY+ZVj5YtDSUmJMV73gwcPoKSkJFbW2tqa9ZAU+rACWWNuh4eHQ1tbG56enhgxYoQgO2jFIQ5fX194enoKxed+/vw5WrVqBT8/P1a5jRs3Qk5ODl27dsUff/yBefPmwdfXF/Ly8ti8eTMAYMmSJfjtt99+6L2amJgIMpI6ODggPj4eQHmCMQ0NDamvI2u7U6dOhYqKimAMKSsrMyZs+pEcP34cBgYGIuNX0hiueP5VKS4uxuTJkyW2++jRI0ybNg3+/v6Cd+/48eOCPAw/mspx7it/LtnZ2RLfNxUVlWpnOh45ciT09fWxbNkyJCcnIyUlBcuWLYO+vj7Cw8MBlOecaN68uYgs2/fS27dvIScnV63+cPw74ZR7Do5fjDNnzkBbWxt8Pl8oA2NFkhxxzJs3D9ra2ujZsyfmz5+PqKgooaMqcnJygh+T6iq8QHm8cE1NTakUBl1dXVy+fBkAe8IuaUhISEDHjh2l/hFu0qQJvL29MXv2bPB4PEyYMAFz5sxhPNioW7cuunfvjsuXLyMrKwvZ2dlChzjMzc0FSmNl4uLiYGFhIdU91ITk5GRBXgJpaN26NevRpk0bsbI5OTlwd3eHgoICbGxsYGtrCwUFBXh4eAgmWGykpKTA398f7u7ucHNzg7+/v0DxlhZZleywsDBYWVnB29sbenp6+Pz5M4Dy3ATisrZWJTQ0VJDYTVoKCgpw7do1XLlyRdCuLAwbNkymNm1tbTF8+HDk5ubK1I6WlhZ69OiB9+/fC8oyMjLg7u4OGxsbsbJnz56FiooKvL29oaioKPhsFi5ciJ49e0rdh06dOuHly5dS1TU0NBRk1K08Hk6cOCExiVXr1q0ZE85JQ0lJCebNmwdjY2PBd6CxsTEiIiIEeRuePn0q9B7k5eXh06dP4PF4ePToEfLy8gTHhw8fsH37dpiYmFSrPxz/Tjibew6OX5DS0lLKz88XskXNzs4mVVVVsXbitWrVYj3H4/FE7PV/lEOttbU1denShWbMmEFGRkas9Yh+nEPt27dv6bfffqPz58+TqqqqiBlIVVvcH+FQK6tvQWXmzp1Ly5cvp8mTJ1OzZs2Ix+NRSkoKLVy4kMaNG0fTp0+X6joVPwnSRK+JjY1ldb6cMGECLV68WPobqAZJSUl0//59AkBOTk7k7e39U9uroFOnTrRlyxYyMTGRqn5xcTFFRUXRs2fPKDAwUBCyc8WKFaSurk4hISE/s7s1QlZfCk1NTbp165bMvhRZWVk0cOBAysrKoujoaHr48CFNmDCBevXqRWvWrBFrKtW0aVPq3bs3jR07Vsi/4Nq1a+Tn50cvXryQqg+VZSUxZMgQevv2LcXHx5Ouri6lpaWRnJwc+fn5kaenp1hzn7179wrM6OrXry/ihC7O/K4yFZGGxEUSIpLstMzj8WjOnDk0bdo0qdrl+PfDKfccHL8wkZGRFBoayhqSr6b8SIfa27dvS60w/AiHWm9vb8rJyaHg4GBGh1pxSXWq61Dr5+dHAwcOpJ49e8okR1T+HFesWEFLly6lly9fEhGRqakpTZgwgcLDwyUq6zt27KDFixdTZmYmERE5ODjQhAkTxEaz0dbWptjYWJEkTGPGjKE9e/ZIjC9ewfPnz4nH4zFGGPlZFBYWUnFxsVCZJCXpnyA8PJzs7OxE/B5Wr15Njx49YlUiCwoKKDIykjWPgLiJbWVkUXiJyu26mzdvTsHBwVLVr0xZWRmNGTOGVq9eTXJycrRjxw7y9/eXKKeurk537tyhWrVqCfU3Ozub6tSpwxgZiAlZ7jU/P586depE9+7do8+fP5OpqSnl5uZS06ZNKSEhQWzUKKaEc5KSzNWEc+fOEQDy8vKi/fv3C/koKCoqkpWVFZmamv7QNjn+WTjlnoPjF6a6IRCLioooKyuLbG1tGVenK/P582epHGrFhQMMCAigli1byrzCGRQURCtXrqyWQ62qqipdunTpp4QpZOPdu3cUEBBAjRo1IhcXF5HdgqrOiBWUlJTQzp07qUOHDmRsbCyI+S3tfS9btoxmzJhBI0aMEETauXDhAq1Zs4bmzZsn4oBaQWJiIvn7+9ORI0fI09OTiMqT+Bw4cIBOnTpFderUYW2zrKyM5s2bR0uXLhXET9fQ0KBx48bRtGnTGBWg06dP04gRI+jy5csiinheXh41a9aM1q9fTy1btmRs8+vXrzRx4kSKj49nzJQqTqk6cuQIY3nl5EHidrYqkPWdMzMzoyNHjlD9+vWFym/evEm+vr70/PlzRrm+ffvSuXPnaODAgYx5BMRNbCsjq3L/9etX6t27NxkYGMjsnH3kyBEKCQmh2rVr04MHD6hu3boUExMjUfE0Nzen+Ph4atasmVB/Dx48SOPHj6fHjx9L1XcXFxc6fvy41I7SROVj8ubNm1RWVkYeHh5S7R5JSjgnKWfFvn37BJGWioqKhM6x7QpWtGthYfFDM4Jz/Ev5R4yBODg4/hXIajtcUFCAwYMHQ05ODnJycgLZkSNHYsGCBWJlo6OjZbLJrsy8efOgr6+PgIAALFmyRKKtf1UyMzORmJgocOgtKyuTKOPu7o5Lly5Vq78AsGPHDjRr1gwmJiYCe/lly5bh0KFDrDKy+BZUpSZOetbW1ti+fbtIeXR0NKytrcXK7t69Gzo6Orh27RqGDRsGU1NTPHjwQGKbkydPhoGBAdauXYvU1FTcvn0ba9asgYGBAaZOncoo07VrVyxbtoz1mlFRUWIdaocPHw5HR0fs3bsXKioq2Lp1K/744w+Ym5sjNjZWbH8rPgOmz6XiX09PT3z48EHsdWR955SUlJCZmSlSnpmZKdZxU0tLCykpKVK386PYtGkT5OTkoK6uDisrK6mds4cMGQIlJSUsXrwYZWVlePXqFXx8fKCrq4u4uDixbU6YMAEtWrTAq1evoKGhgczMTKSkpMDGxgazZ8/+0bf4jxIVFQV1dXWEhYVBUVERQ4cOhbe3N7S0tFjfm8p8/PgRJ06cQExMDLZv3y50cPzvwCn3HBy/MNWJcFK/fn0kJydDTU1NIHv48GG4ublJlP/48SM2bdqEyZMnCxznbty4gefPn4uVq240l/fv38PLy0ugfFX0d/DgwRg7dqzYNk+cOIFmzZrhzJkzePfunZATWl5enljZtWvXQl9fH/PmzYOKioqg3W3btqF169asclZWVggLC5PZGRGomZMemwL58OFDiZE/gPL7VVJSgrm5OeN1mDAxMRGJdAQAhw4dgqmpKaOMpaUl0tPTWa+ZkZEh1nnYwsICZ86cAQCBEgiUT8R8fHzE9vevv/5C48aN8ddffyE/Px/5+fn466+/0KRJExw7dgwpKSlwdnbG4MGDxV5H1nfO2dkZq1atEilfuXIlHB0dWeWsra3FPitJFBUVIScnB/fv3xdycpWEkZERIiIiUFpaKlN7zs7OgshdlVm9ejXU1NQk9rVfv36CiZaCggL4fD4GDBggcDKVxPXr1xETE4PY2FjcuHFDKpm//voLU6ZMQXBwMIKCgoQOcVRVqmVRsmvXro1du3YBEB5LM2bMQFhYmFjZI0eOQENDA3w+H1paWtDW1hYcOjo6Ut0zx38DTrnn4PiFycnJkfrHDyhXripWsyv/sGRmZkoM6ZeamgoDAwPY2dlBXl5eIDt9+nQMHDiwmncgnoEDB6JDhw549uyZSEQLJycnsbKVV2YrH9Ksojs6OgoU7crt3rlzB3p6eqxy6urqgvB6shIfHw8bGxusWrUKFy9eRGpqqtAhDmdnZ0RERIiU//HHH3BxcREqqxqysuKwsLCAr6+v1OEslZSUGFf479+/D2VlZVYZcZOHzMxMVlkAUFNTE+xumJmZ4cqVKwCAJ0+eSFQgnZ2dGaPqpKSkCMZSUlKSxMhEska82bJlC1RUVDBz5kycPXsWZ8+exYwZM6CqqoqNGzeyysXExKBXr14oKCiQuq3Pnz9j/fr1aNWqFVRUVITGu6WlJUJCQnD16lWx19DR0anWGBa3q3f//n2prvHo0SPs3bsXcXFxjGFhmXj9+jXatGkDHo8HHR0daGtrg8fjwcvLS2ykrdmzZ4PP56NRo0bo1q0b/Pz8hA5xVFaqtbW1oaamBh6PByUlJYlKduUdOgMDA8GE6OHDh9DV1RUra29vj1GjRsk0Jjj+m3BJrDg4fjGuXbtGZWVl1LhxYyHb0itXrpCcnBw1aNCAVfbt27eMTqIFBQUSHTbHjBlDgYGBMiV9YeLChQvUoEEDQSIucZw8eZJOnDghkizG3t5eot1rTVKxZ2VlCSKiVEZJSUls5tMePXrQmTNnqpW1tU+fPkQkbNMsrZPenDlzqE+fPnT+/Hlq3ry5INLOqVOnKD4+XqjurVu3GK9ha2tL+fn5gvOSxkO9evVo9erVtHLlSqHy1atXs/o5mJmZ0Z07d1ijCaWlpYmNYFPhZGllZUVOTk4UHx9PjRo1oqNHj0p0Kn/8+DGjw62mpqbAOdXe3p7evXsn9jrr1q0Te74qgwcPpu/fv1NERAT98ccfRFQePWrdunU0aNAgVrmlS5fS48ePycjIiKytrUVs36vaZi9fvpwiIiLI2tqafH19afLkyWRmZkYqKir04cMHunv3LiUnJ1O7du2oSZMmtGrVKrK3txdpNyAggOLi4mjq1Kky3ae497l27dpSXcPW1lbmd2fkyJGUn59P9+7dI0dHRyIiSk9Pp4CAAAoPD6fdu3czyq1fv56io6PFOpyz8fHjR5GyzMxMGjZsGE2YMEGsrLGxMb1//56srKzIysqKLl++TPXq1aOsrCyJSc5evHhB4eHhpKqqKnOfOf5bcMo9B8cvRlhYGE2cOFEkM+aLFy9o4cKFdOXKFVbZhg0b0rFjx2jkyJFE9P8VuE2bNklMm379+nXauHGjSLmZmRnl5uZK3X8fHx+pHRILCgoYf8jevXsncXJQk8yZtWrVotu3b4s4xh0/fpycnJxY5RwcHGjKlCmUkpIiszNiVlZWtfvbs2dPunLlCi1fvpwOHTokCC159epVkUlKTSY9lVm0aBF17tyZ/vrrL2ratCnxeDy6ePEiPXv2jBISEhhlOnXqRDNnziQfHx9SVlYWOldYWEizZs0SidxTmaCgIEpNTaVWrVrRlClTqHPnzrRq1SoqKSmhZcuWie1v/fr1acKECbRjxw4yMDAgovLJ7sSJE6lhw4ZEVK6gMWUdrW7EmwqGDRtGw4YNo7dv35KKiopU2Y/9/Pwk1qnMxYsX6cyZM1S3bl3G840aNaLBgwfT+vXracuWLXTu3DlG5b60tJQWLVpEJ06cIFdXV5ExLO45V9dRFADt27ePzpw5wxgZ6MCBA6yyiYmJ9NdffwkUeyIiJycnWrNmDbVv355VrqioiJo1a8Z6Xlbs7e0pMjKSBgwYQPfv32et5+XlRUePHiUPDw8KDg6mMWPG0L59++j69evUo0cPsW106NCBrl+/LnMABY7/Hly0HA6OXwx1dXVKS0sT+YLPysoiV1dXQaQVJi5evEgdO3ak/v37U3R0NA0dOpTu3btHly5donPnzolE9KiMkZERJSYmkru7u1BEi5MnT1JwcDA9e/ZMqv7LEr2jc+fO5OHhQX/88QdpaGhQWloaWVlZkb+/P5WVldG+ffukarNu3bqUkJAgdRSNbdu20YwZM2jp0qUUHBxMmzdvpsePH9OCBQto8+bNrOH9ZM0jUJnz589Ts2bNRKIXlZSU0MWLFwXRbH4UJSUlpKysTLdv3yYXF5dqXePly5e0Zs0aoVj1w4cPZ42O8vr1a/Lw8CA5OTkaMWIE1a5dm3g8HmVkZNCaNWuotLSUbt68KTEXQgU5OTl0/fp1srW1lRgV6cGDB9StWzfKysoiCwsL4vF4lJOTQzY2NnT48GFycHCgQ4cO0efPn0VWc6sb8Yao/L0sKSkRUaQzMzNJQUGBrK2tpbrXv4s2bdqwnuPxeHT69GnGcytXrqRp06ZRQEAAbdq0iYKCgujx48d07do1CgsLo4iICNbrhoeH08aNG6lNmzaMYWu3bdvGKquhoUHJycnk5uYmVH7r1i1q1aqVIJZ8VSZNmkTq6uo0Y8YM1mvLiqQ2icqjTJWVlQne8/j4eEpJSSE7OzsKDQ0lRUVFVtktW7bQ3LlzKSgoiHHxgC0aF8d/kH/QJIiDg+MfQFdXFxcvXhQpv3DhArS1tSXKp6WlYdCgQXB2doajoyP69++PtLQ0iXK///47/Pz8UFRUBHV1dTx58gRPnz6Fu7s7Ro0aJXX/ZXFIvHfvHgwMDNCxY0coKiqiV69ecHR0hJGRkUx2wbI6QQLAxo0bYWlpKbDdNzc3x+bNm2W6hiywZQB+9+4do49AZafgqs7C0joP29jYMDpB/kyys7Ph4+MjFLmGz+fDx8cHWVlZP7XtsrIyHD9+HFFRUVixYgUSExOlchytbsQbAPD09ER0dLRIeUxMDFq1asUqN3XqVJw8efI/Y19dE0dRHR0dHDt2rFrt+vr6wtPTEy9evBCUPX/+HK1atRJrOx8eHg5tbW14enpixIgRIj4o4jh8+LDQcejQIaxbtw7Ozs7o2LFjte5DGpiicEkbjYvjvwW3cs/B8Yvh7+9Pubm5dPjwYdLS0iIiok+fPpGfnx8ZGhqK2Fj/KGqS9KUyu3btom7dukldPzc3l9atW0c3btwQxKIOCwuTOrsokeyxvivz7t07KisrkzmhlSy+BUTliXFev34tMBmp4OHDh9SgQQOR1UA5OTl69eoVGRoasmawhAR7/W3bttHevXspNjZWKDEOG2lpaeTi4kJ8Pp/S0tLE1pWUpfPDhw/0+PFjAkD29vZC2ZarsmPHDol9IyKxNuw1wcXFhUJDQ2nEiBFC5atWraJ169ZReno6q6ympibdvHlTxM/g0aNH1KBBA/r06ROjXMeOHenixYv0/ft38vDwoNatW1OrVq2oRYsWjGY9oaGhNG3aNKl2p+Li4qikpIT69+8vtt7u3bvJ19dXqndVVVWVMjIyyMrKigwNDSkpKYnq1atHmZmZ1KRJE8a8BBXUqlWLjh8/LjavAhvPnj2jbt260d27d4V2ZOrWrUuHDx9mNLMiqv4OBZFoEisej0cGBgbk5eVFS5cuZfxuysnJkep+xGX65vh14GzuOTh+MZYuXUqenp5kZWUlsKe+ffs2GRkZUUxMjET5srIyevToEaNtqzjTD01NTUpJSalW0pe8vDwqLS0lXV1dIefbDx8+kLy8vNjMosbGxjRnzhyJbYijZcuWpKKiIrPc27dv6cGDB8Tj8YjP55O+vr7UstL6FlTY2fJ4PAoMDBSaDJSWllJaWhqjbfDp06cFCnl17ehXrlxJjx49IlNTU7KyshJR4qraSbu5uQky97q5uQkcfqsibkJR2RyowtZdEoGBgaSurk7y8vKsToc8Hk+icl9QUEDnzp1jtAkX5w8xduxYGjFiBL19+5a8vLyIiOjUqVO0dOlSifb2PB6P0VSu4p1gIzExkUpLS+nq1at07tw5Onv2LK1du5YKCwvJw8ODLl++LFTfwMCAXFxcqFmzZuTr60sNGjQgU1NTUlZWpo8fP1J6ejqlpKTQnj17yMzMjNF/pipDhw6lxo0bSzUpromj6OzZs2nOnDm0detWmd9TCwsLunnzJiUlJQmZh0n6XqqJ70nV783KsN1rZZO9ijqVJ+SSJuJV+fbtm4jfCsf/Dpxyz8Hxi2FmZkZpaWm0c+dOSk1NJRUVFQoKCqK+ffuK2GBW5fLly9SvXz96+vSpyI+QtD8sXl5eAgVHWvz9/alr1640fPhwofL4+Hg6cuQIqwMmUfmuxJYtWygjI4N4PB45OTnR4MGDBbsW4uQqIqhUvf6jR49YI7YQlSuBI0eOpB07dgh+yOXk5GjQoEG0atUqqaJVSLupWnEfAEhDQ0NIuVFUVKQmTZrQ77//LiJX2WG4Vq1aglXLqn0Q5wshq9NmVlaWYGehug7A8vLyZGVlJbUSQ0Tk6OhIr1+/pgEDBtDgwYMl7gowcevWLerUqRN9/fqVCgoKSFdXl969e0eqqqpkaGgoVrmvbsQbovKJ5YIFC2j37t0kJydHROWTtgULFlCLFi3EysrJyVHTpk1JV1eXdHR0SENDgw4dOsSYsfWPP/6gkSNH0pYtW2j9+vV09+5dofMaGhrk7e1NmzdvFutoWhlZDANq4ijau3dv2r17NxkaGkoVGaiCyhPFdu3aUbt27aTub1JSErVo0aJak/4FCxbQlClTRMpLS0tpwIABjBF6eDwemZubU2BgIHXt2lViZnAmSktLaf78+bR+/Xp6/fo1PXz4kGxsbGjGjBlkbW1NwcHBMl+T41/K328JxMHB8V+lXr166N27N9LT0/Hx40d8+vRJ6JDE2bNn0aVLF9ja2sLOzg5du3bF+fPnJcrp6OgwJuTJyMgQG9v52rVr0NXVhZmZGbp37w4/Pz+Ym5tDT09PYqKapk2borCwUKT8/v37MDMzEys7ZMgQ2NjYICEhQWC3fuzYMdja2iI0NFSsbAWy2vnPnj0bX758kbp+ZWS11/8RnDt3DsXFxSLlxcXFOHfunFjZrVu3wsfHR6bkSpcvX8aQIUOgpaWF+vXrY+3atRKTkVWmVatW+P3331FSUiL4bHJycuDp6Yn9+/dLfZ03b97g8+fPUte/d+8e9PT0YGtri8DAQAQGBsLW1hYGBga4c+cOq9zatWvRp08fGBsbw8DAAD169EBUVJTEnAcVfPz4Ebdv38alS5eQmZkpVVbnqsgyhktLS4XGQ1xcHEaOHImoqCh8//5drGzv3r2hr6+P0NBQzJo1C7NnzxY6xFFdvxENDQ0oKiqiadOmmDx5MhITE6X+XA0NDbFhwwahsuLiYvTq1Qt16tRhlHn16hUiIyNRp04dGBkZYdy4cTInKZszZw5sbGwQGxsrlFwvLi4OTZo0kelaHP9uOOWeg+MXY/78+diyZYtI+ZYtWxAZGSlWVlVVVeoMpFWJiYmBvLw8fvvtN4FD4m+//QYFBQXs3LlTYrtMTrtpaWlQUVFhlWvRogUCAwOFlIbi4mIEBASgZcuWYtvs1KkTOnToICSbnp4OY2NjhIeHi5XV09MTZEKtzOnTp6Gvry9WtoKdO3dWW1mXFR6Px5iwJzs7G6qqqmJlq5t1uCYTCjc3N6irq0NJSQkODg5wd3cXOsTx9etXbN++Ha1bt4aqqir69esnNoFSBVpaWoJkSlpaWgLF6vLly6hdu7ZY2SdPnjAmVXr48KFUTsAvXrzAlClT0KlTJ/Ts2RNz5syROLHh8XgwNDTEwoULZZrE/EiSk5OlerY1RVVVFcnJydWSrc5EEQBKSkpw8eJFLFiwAB06dICGhgYUFBTQuHFjTJo0Sazs9evXoa2tjbi4OADlGXa7d+8OR0dHvHr1SmLbycnJGDx4MDQ0NNC4cWNs3LhRKsduW1tb/PXXXwCEJ14ZGRlSBVPg+O/AKfccHL8YVlZWjJk2L1++DGtra7Gybdq0wfHjx6vVbp06dbBs2TKR8qVLl7KuVlXQqlUrjBgxQqR8+PDhaNGiBaucsrIyMjIyRMrv3bsndlIAAIWFhWjRogV69+6NsrIy3LlzB4aGhhIjYQDlWSSZVtXu3r0rUVmuLrm5uRgwYABMTEwgJycnklmXiYrIHnw+H0OHDhWK9hEeHo7GjRujWbNmrG3WJOsw24TiwYMHErMdV12ZlWWltoJz586hdevW4PP5+PDhg8T6+vr6goy6Dg4OSExMBFCuGEkaS9WNeCOOd+/eYfny5aznDx48iDFjxsDd3R1KSkpo1KgRJk6ciISEBIkrzFZWVpgzZw6ePn0qc79iYmJYz40fP16sbGFhIa5cuYKjR4+KRJQRR+3ataXekahKTSaKlblz5w4CAgIgLy8v1W7XmTNnoKmpiUOHDqFr165wcnJCbm6uTH3Pzc1FmzZtwOfzpZqcKCsrC7LbVlbu7927JzFDM8d/C87mnoPjFyM3N5cxGoOBgQG9evVKrOzIkSNp3LhxlJubyxgnWZwt85MnT6hr164i5b6+vhKzWUZERJC3tzelpqZS27ZtiajcIfHatWt08uRJVjlNTU3KyckRiaLx7NkzoSy5TCgrK9Off/5JrVu3pt69e1NycjINGjSIFi9eLFaOiKhp06Y0a9Ys2rFjh8BprbCwkObMmSMx2de5c+doyZIlAh8BR0dHmjBhArVs2VKsXGBgIOXk5NCMGTPIxMREYoZYov+fbRYA3blzRyhGtqKiItWrV4/Gjx/PKj927FiZsw5X1wG4MrNmzZJ4b0y8ePGCtm/fTtu2baOCggIaMGAArVu3TmyknQrc3d3p+vXr5ODgQG3atKGZM2fSu3fvKCYmhjXxUwW3bt2i5s2bi5Q3adJEJIKOOADQyZMnacuWLXT48GHS1NSk0aNHM9b18/MT+ETk5eVRcnIy7du3j7p160Y8Ho++f//O2s64ceMoOjqa5s6dS23atKHg4GDq3r27VJGbRowYQdra2iLJxMaMGUN79uxhfX8SExNp0KBBjBl+JfnzLF26lCZOnEjr16+XOe6/rH4jFWRkZAgclc+dO0elpaXUokULWrp0qVQJ8Fq3bk0xMTHUs2dPcnR0pHPnzkntcH/x4kXaunUr7d27l2rXrk1r1qyRmGGZiMjZ2ZmSk5NFkuvt3buXMaM2x3+Yf3p2wcHB8fdiZ2fHuLq2Y8cO1KpVS6wsW3xkaeIk29raYv369SLl69evh52dncR+37p1C/369YOTkxPq16+PoKAgRlOHyowcORLm5ubYs2cPcnJy8OzZM+zevRvm5uaMsfWZYrw/ePAAFhYWGDZsmFSx34HyVTwzMzPo6enBy8sLbdu2hZ6eHszMzHD37l1WuZqYLqmrq+PWrVti67ARGBhYLdMNTU1NQb6AyiuB2dnZrPHbK+zGeTwe+vTpI/g7MDAQQ4YMwfz58/H27dtq3QcbcXFx6NixI1RUVODn54fDhw+jpKREpmtcu3YNp0+fBlBuN+/j4wMNDQ24u7tLtNnW1NTEzZs3RcqvX78OdXV1iW1nZWVhxowZsLCwAJ/Px4ABA5CUlCTxHt6/f48DBw4gPDwcrq6u4PP5MDAwQK9evSS2CQC3b99GeHg4DAwMoKOjg7CwMIm+KsePH4eWlpaQ38SIESNgamrKuItWga2tLYYPHy7z6jUAaGtrQ1FREXw+H+rq6tDR0RE6fgYVZk/z588X+05X0L17d8bDxMQELVu2FCpj4uXLl4iMjETt2rUFO4jStFuZI0eOQEtLC5GRkVBVVcXixYsREhICRUVFnDx5UqZrcfy74eLcc3D8YixcuJAWL15MixcvFgrLN3HiRBo3bhxjFIcKnj59KvbaVVeEKrNu3ToaPXo0DR48mJo1a0Y8Ho9SUlIoOjqaoqKiaOjQodW7ITEUFRXRhAkTaP369VRSUkJERAoKCjRs2DCKjIwUWYkUF++diAShG6WJDFRYWEixsbFC4fX69+8vNrqGo6MjDRkyhMaMGSNUvmzZMtq0aRNlZGSwyjo5OdHOnTv/1hW4mmQdnjNnDo0fP17qfAWVKS0tpeXLl1N8fDxjWMoPHz4I/c3n88nS0pL69+8vNnutuIg3NaFLly6kqqoqEvGmT58+VFBQQMePHxeR+f79Ox04cIA2b95MFy9eFOyG9O3bl1JTU8nJyUlsm66urpSenk66urrk6elJrVu3ptatW1crm3BxcTGtXbuWJk2aRMXFxeTi4kKjRo2ioKAgxvdlz549NHz4cDp58iRt3bqVDh8+TGfOnCEHBwfWNjQ1NenWrVtka2src/+2b98u9nxAQADrucDAQBo8eLDMGZxHjx5N58+fp3v37pGbm5vg+bZs2ZIxj0BQUJDU12bKqKuoqEimpqYUEBBAvr6+rJHNJEWCOnHiBM2fP18o78fMmTOljoDE8d+AU+45OH4xANDkyZNp5cqVAqVIWVmZJk2aRDNmzJDKnKO6HDx4kJYuXSpQUitMTrp16yZWLiEhgeTk5KhDhw5C5SdOnKCysjLy8fERK//161dBwiM7OzvWUJTnzp2T+l6k2XqXFSUlJbp37x5jwiIXFxf69u0bq+zJkydp6dKltGHDBplNE4iIrl27Rnv37mVUlg8cOMAoM2TIEHr79i3Fx8eTrq4upaWlkZycHPn5+ZGnp6fEGO7VZebMmbR582YaO3YszZgxg6ZNm0bZ2dl06NAhmjlzpoiSbm1tLXFc83g8evLkyU/pb3p6Onl6epK2trbAvCo5OZny8/Pp9OnTjAq3vr4+OTk50YABA6h3794C0yEFBQWplPvVq1dXW5mvoLi4mA4ePEjbtm2jpKQkatKkCQUHB9PLly9p9erV1KZNG9q1axej7Lp162jMmDFkYGBAZ86cERs6lqg8XGjz5s3/9nCMPXv2pGPHjpGFhQUFBQVRQEAAmZmZSS3/6dMnSk5OpnPnztG5c+fozp075ObmJpJHoKZUTnxVMZarqm+yxLnn+N+GU+45OH5Rvnz5QhkZGaSiokL29vakpKREJSUlEuMnx8TE0Pr16ykrK4suXbpEVlZWtGLFCqpVq5ZEJb26uLq6UmRkJHXq1EmoPDExkSZNmkSpqalC5aWlpXTv3j2yt7cXWSkvLCykzMxMQaZUJkpKSigiIoIGDx4sVcbOCm7cuEHjx48X2ENXJi8vj/z8/GjFihVUr149Rnk7OzuaMGGCyC7Ghg0baMmSJZSZmcnato6ODn39+pVKSkpIVVVVZGWv6mp2Zfbs2UODBg2i9u3bU1JSErVv354yMzMpNzeXunfvzriSSFTzrMP79u1jXX1ni01ORGRra0srV66kzp07k4aGBt2+fVtQdvnyZVaFszpIm5NBXEZSIhIoxBW5JVxdXWnEiBGsmX11dHTI1dWVBgwYQH369BGMJ2mV+wqKioooKyuLbG1tpY6NfvPmTdq2bZtgp2HgwIEUEhIi5Lty7do18vT0pMLCQho7dizjdfbt20fu7u5Cq/HLli1jrPv161fq3bs3GRgYMPrzSLur0rlzZ9q8ebNMGajfv39PsbGxFB0dTXfv3iVvb28KDg6mbt26Scz98eHDBzp37hydOXOGzp49S/fu3SMDAwPKzc2Vqu3IyEgKDQ2VaDMvade0AnG7p5UZPnw4zZ07V6bEehz/HTjlnoODg9LT02nLli0UGxtLr1+/Zq23bt06mjlzJo0ePZoiIiLo7t27ZGNjQ9HR0bR9+3bGrI0fP36k2NhYCggIYFR4d+zYwXiuMioqKpSRkSGyIp2dnU3Ozs5UUFAgVB4dHU2rV6+mK1euCMwgKigtLaXGjRvT6NGjacCAAaxtamho0J07d2RaBe/Xrx85OjrSjBkzGM/Pnz+f0tPTKTY2lvF8TUyXamKa4OrqSkOHDqWwsDCBeU2tWrVo6NChZGJiIjHDb3WyDq9cuZKmTZtGAQEBtGnTJgoKCqLHjx/TtWvXKCwsjCIiIlhl1dTUKCMjgywtLcnExISOHTtGHh4e9OTJE3J3d6e8vDyJ7UsLn88nKysr6ty5s1hFb/ny5TJf+/379xQTE8PoFPvt2zfav38/bdmyhS5fvkw+Pj4CRf/27dsSlfvCwkIaMWKEYFxUJCwKDw8nU1NTmjx5MqusnJwctWvXjoKDg8nPz4/xvgsKCmjEiBG0bds2atOmjVT3y+PxWCdBmzdvptDQUFJRUSE9PT2hnRZZdlUqm4dVh1u3btHWrVtp8+bNpK6uTgMGDKDhw4eTvb29UL1Ro0YJlPmamD5pampKlYn6R/NPtcvxN/FPGPpzcHD883z+/BmbNm1CkyZNICcnh+bNmzOGqqyMo6MjDh48CEDYgfLOnTvQ09NjlJk7d65YB77evXtj3rx5Yts1MjLCqVOnRMqTkpJgYGAgUt6iRQvs3r2b9XpxcXES49x369YN27ZtE1unKjY2NmJD8qWlpUl0Wj5w4ACaN28OXV1d6Orqonnz5jh06JBM/ZAVVVVVQbx1PT09QU6Birj+P4PatWtj165dAITH0owZMxAWFiZW1sHBAZcvXwZQ/lkvWLAAALBnzx7G8VAZWROpLVy4EI6OjgInRnGJo6ShrKwMiYmJ6N27NxQVFaXKe/Do0SNMmzYN5ubm4PF46NevH06ePCnWoTY8PBz169dHcnIy1NTUBM/38OHDcHNzE9teRbjEvxMjIyNERERIFa9dHLImf6tMhdOqg4MD1NTUMGjQILRr1w7y8vIi3409e/bEqlWrajweqtPfjx8/YsmSJQgODkZISAiWLl0qVRLBmrbL8d+BU+45OH4xkpOTERAQAHV1ddStWxdycnJISUmRSpYtTvLDhw+hrKzMKFOvXj1B4hQm/vrrL4nKxu+//466desKIrMAQGZmJlxdXREcHCxS38DAQGxyoCdPnkhUqtavXw9jY2OMGzcOu3btkirutpKSEp48eSK2XbbnVFxcjNmzZyMnJ0dsv8RRoQT6+/sLEkQdP35cYlQNc3NzgULv6uoqULovXrwITU1NkfpRUVESjzVr1mD//v2MiaqA8lwAFWPJwMBAEHHm4cOHYrMOA8CkSZMQEREBANi7dy/k5eVhZ2cHRUVFsQmEahKN6OLFiwgJCYGmpiYaNmyIdevWyRRhqLoRbypTWlqKhIQE9OzZE4qKiqwTagCwtLTEpUuXAAi/q5mZmRLzCFSX4uJiyMnJVUvh1dHREXq/q4uzs7NM71BRURH27duHzp07Q0FBAfXr18e6deuQn58vqLN79+6fluRJViW7Jlm3a9Iux38LTrnn4PhFWLhwIWrXrg0zMzOMHz9eoEzJy8vj3r17Ul3D0dFRsIpc+cchKioKHh4ejDLq6upik+E8ffpUorLx6dMnNGnSBPLy8rC2toa1tTXk5eXRpk0bxgREqqqqYlfQU1NTJSaTYgr7WTn8JxPm5uZik3wlJCTA3Nyc9byamppUGUuZOHv2LFRUVODt7Q1FRUXBZ7Nw4UL07NlTrGzfvn2xdOlSAMC8efNgYGCAkJAQWFlZMYbmq/gMxB2WlpZQU1ODiooK9u/fL3KNWrVqCZSRBg0aCMKknjhxQubwhZcuXcLSpUslJjuqSSK1CgoKChAdHY2GDRtCTU1NrIL/7ds37Nq1C15eXlBWVkb37t0FkxFp3zk23rx5I/jMmFBRURGMgcrv6u3btxknbJXR1tYWCSepo6MDXV1dmJqawtPTE1u3bmWUtbGxkRgalInRo0cLJmx/J3p6etDR0cHw4cNZQ8l++PCBMcHfjh070KxZM5iYmAgmqsuXL5dppy0nJ0emCV5Nsm5z/Dpwyj0Hxy+CnJwcpk6dKvJDIouisXXrVpiZmWHPnj1QU1PD7t27MW/ePMH/mdDS0hKsIDJx6dIlaGlpSWy7rKwMJ06cwKJFi7Bq1SqhONpVqVevHtatW8d6fs2aNahXr57ENmUlMDCQNWNuWVmZ4IeZjeqYAlXQpEkTgbJXWZm7evUqTE1Nxcq+f/8eL168AFC+Orxw4UJ07doVY8aMkSp7KxulpaWIiIhgVJyDg4MF2WTXrVsnmJhoa2tj8ODB1W5THIqKisjMzBQpz8zMZI3LX5Xk5GQEBQVBXV0djRs3xtevX1nr6unpoWXLltiwYYPQc5TlnQsICBA71tnw9PTEypUrAZSPh4odpbCwMHTo0EGs7LJly6Cnp4cBAwZg5cqViIqKwoABA6Cvr4+IiAiEhIRASUkJGzduFJHdunUrfHx8pMqYWpmRI0dCS0sLnp6eGDFihFC2ZGmyQgPleQNiYmIQGxsr9Sr2jh07UFhYKFNfAWDt2rXQ19fHvHnzhCZS27ZtQ+vWrWW+nrTUJOs2Ux6PvLw85Ofn4/v37z+ryxz/AJxyz8HxixAREQF7e3tYWFhg4sSJgq1zWVcRN27cCEtLS8Eqtrm5OTZv3sxav3Xr1mJNJSZOnFitH8PS0lIcOXIE3bp1Ezm3cOFC6OnpMa7e3759G3p6eli4cKHUbUn74//o0SNoaWmhUaNGiIuLw+3bt5Gamoo9e/agYcOG0NLSYlQuK6iOKVAFampqAgWusnKflZUlteL6M3j+/DmjCVRpaanQ6mNcXBxGjhyJqKgomRQNDQ0Nqc0LqptI7cWLF4L3x8jICOPGjZPqndHW1oanpyc2btwotMIvyzvXo0cPKCkpwc7ODhEREXj+/LlUchcuXICGhgZCQ0OhrKyMUaNGwdvbG2pqarh+/brENpkmx+vXr0ePHj0AACtXroSLi4tIHTc3N6irq0NJSQkODg5wd3cXOtho3bo169GmTRux/X39+jXatGkDHo8HHR0daGtrg8fjwcvLC2/evBErW12q439UQU12RgwNDXHixAmR8sTERBgaGoptt2LXke2wtLTEzJkza+z3wPHPwyn3HBy/GGfPnsWgQYOgpqYGV1dXmWzuK/P27VtWe+rK7Nu3D/Ly8li1apXQrkFJSQlWrlwJBQUF7N27V+p2Hz58iMmTJ8PExATKysqMyn1RURFat24NeXl5dOzYEaNHj8aYMWPQsWNHyMvLo1WrVigqKhLbTklJCebOnQtTU1PIyckJfrynT58udjJz7do1ODs7C/2Q8ng8ODs74+rVq2LbrI4pUAVmZma4cOECAGFl48CBA7CxsRGpz7aKx3SIQ1YH1R+NLLbDa9euhaKiIkJDQ7Fjxw7ExMRg6NChUFJSYlT6AcDHxwfKysrw9fXFoUOHhCYkkigsLERsbCzatGkDFRUV9OjRAwcOHICCgoJME+p3795hxYoVcHNzE4zp+Ph4iWM4LS0NgwYNgrOzMxwdHdG/f3+Bb4U41NTUWHc41NTUAJRPZJlM22bPni32+Bn89ttvqF+/PtLT0wVl9+7dQ4MGDeDv788o8/LlS0ydOlXwd/PmzYUmIQ0aNBA7kaqO/1EFNdkZkTXrdmW2b98Oc3NzTJ8+HUeOHMHhw4cxffp0WFhYYMOGDZg3bx60tbX/EfMojh8Lp9xzcPyi5OfnY926dWjUqBHk5OTQtGlTsTa8VVmwYAE+fvwoVd2pU6eCx+NBU1MTbm5ucHd3h6amJvh8vthV/Qq+fv2K6OhotGzZEgoKCuDz+YiKisLnz59ZZYqKirBw4ULUq1cPqqqqUFFRQb169bBw4UKpVobnzJkDGxsbxMbGCm27x8XFoUmTJhLlb926hfj4eMTFxbHa8v5IJkyYgBYtWuDVq1fQ0NBAZmYmUlJSYGNjw6hUSVrFq5iUiJtUyOqgmpqaKvUhLbI6BsoajYjH48HU1FQwbtkOSVQn4g0TN2/exIgRI6CsrAx9fX2MHj0aDx8+FKkn7hlWrDizYWFhweibsGzZMlhYWAiub2RkJFPfpWXXrl348uWL1PU1NTUZJ85XrlxhNfmbPn06hg8fLvhbXV0d4eHhgklI48aNMW7cONY2q+N/VEFNdka+f/+O8PBwKCoqCt5TJSUljB49Gt++fRPbrpeXF+Li4kTK4+Li4OXlBaDcTKl27dpir8Px74dT7jk4OJCWloZRo0ZJDCNYGVnMIYBy2+9Ro0ahU6dO8PHxwahRo3DlyhWxMleuXMHvv/8OTU1NNGjQACtWrEBubq5UZg0lJSU4e/aszLa/Fdja2gqi/FT+8c7IyBAbOaOoqAi1atWqlsOkuEg7kigqKkK/fv0ESnnFJGjAgAGMCuTZs2elPtiQ1UG1YrIgbodCml2KyoSGhuLt27cS61U3GpGklWhZV6RliXhTFVlCNRobGzO+n/v27ZPoTL5x40bIycmha9eu+OOPPzBv3jz4+vpCXl5esGu1ZMkS/Pbbb4zyHz9+xKZNmzB58mTB+3fjxg2pTYpk/W5RV1dnnEDfvHmT1Vm/Xr16OHnypNA1KreZmJgIJycn1jar439UQXV3Rip/pxUUFCAtLQ2pqakoKCgQ214FKioqjBPBhw8fCuz1nzx5ItF2n+PfD6fcc3D8YohTICVt81dGlhXT6ipWcnJyGD16NO7fvy9ULq3NsqTQlOJg23a/d++e4AeYDVNTUyETAWnh8/lo3bo1YmJiquXkBwCPHz/G3r17ERcXx/hD/iOR1UE1Oztb6uNnUJNoRD8DSRFvgOqHapwzZw6sra3x8uVLQdmePXugqqqK+Ph4iX1LSUmBv78/3N3d4ebmBn9/f4HZlzhSU1NhYGAAOzs7yMvLC5mzDRw4UKI8IPtujK+vLzw9PQVO4UC5r0erVq3g5+fHKKOlpSXURvfu3ZGbmyv4OysrS6KSK6v/UQU12RmpyXeavb09407ppEmT4ODgAKDcrFCSAz7Hvx9Ouefg+MX4EQokIPsPsLq6usyKVbt27aChoYF+/frh+PHjKCsrAyC9ct+gQQOxMfbFUb9+fcTExAAQvtfZs2ezRsSpYMGCBQgICJDJPhsod8YbM2YMDA0NoaWlhSFDhkjc3WAiJSVF4hZ9Vc6fP4/+/fujadOmghXWHTt2IDk5mVWmug6qNYUttv7KlSuxceNGnD59mnG3oibRiCrGAhPjx48XK1vdiDdAzUI1hoeHw8nJCe/fv8fOnTuhoqKCffv2iW2vqKgIgYGB1Y6B3rZtW0yYMAGA8Htz4cIFWFlZSXUNWb9bcnJy4O7uDgUFBdjY2MDW1hYKCgrw8PDAs2fPGGXU1NRw8+ZN1mvevHlT7CS+skliVf8jcU7zQM12RmrynXb48GEoKioK8oOEhISgXr16UFJSwtGjRwGU+6VIG52I498Lp9xzcPxiMCmQFdk+ZUHW+MzVVaxycnIEq5BGRkYIDw+HvLy8VCvjJ06cgJubG44ePYqXL1/K5Ch65MgRaGlpITIyEqqqqli8eDFCQkKgqKgotJ3PhJ+fHzQ0NGBiYoL27duje/fuQockiouLceDAAfj6+kJBQQFOTk5YunSp1JE/ZDVr2LdvH1RUVASOfBWya9asgY+PD6tcdRxUK1PdOOHW1tZQU1MDj8eDrq4udHR0wOPxoKamBiMjI/B4PNja2orsFNUkGpGWlpZAAarM6NGjJWbxrW7EG6D6oRorGDBgAOzt7aGqqip1/PWqq9qyoKmpKUhGVVlJz87OlincqKyTUwA4efKkwEE1KSlJbF0PDw+sXr2a9XxUVJRYX4qmTZsyfi7379+HmZmZxL5Wd2ekJt9pQPnnMHnyZEECrMmTJ/+rdrM4fgyccs/B8YtSHQXy6tWrjBOBy5cv49q1a2Lbq4liVcHJkyfh7+8PZWVl2NvbY8qUKWLjWVe145bWUbSCxMREeHp6CpIxNW/enDEMXVUCAwPFHtLy7ds3LFu2DEpKSuDxeFBUVMTAgQOFTC2YkHXl083NDdu3bxeRvXXrlkSnSVkdVCuoSZzwXbt2oXXr1iIZi728vLBnzx48e/YMzZs3F0neVRM7/+PHj0NLS0toBX7EiBEwNTVljDtelepGvJGFqu/U4cOHsW/fPlhYWCA4OFjq9y0wMFAm5/rKGBoaClbEK4+lEydOiE3gVt2dkepmxV20aBF0dXVZw+Xq6upi0aJFrPKdOnVChw4dhHbn0tPTYWxsjPDwcJn6Igs1/U7j+DXgAQBxcHD8snz//p3Wrl1LU6ZMoaKiIlJQUKA+ffrQwoULycTERKhuo0aNaOLEidSrVy+h8gMHDtDChQvpypUrrO3w+XzWczwej0pLS6Xu88ePHyk2Npa2bt1KaWlprLLnzp0Te51WrVpJ3ebfyfXr12nr1q20Z88eUlNTo4CAAAoODqaXL1/SzJkz6fPnz3T16lVWeQ0NDUpNTSUbGxup2lNVVaX09HSytrYWkn3y5Ak5OTnRt2/fRGRKSkooIiKCBg8eTBYWFjLfo5OTE82fP5/8/PyE2rx79y61bt2a3r17xypra2tL+/fvJzc3N6HyW7duUc+ePenJkyd08eJF6tmzJ7169UrmvrGxZ88eGj58OJ08eZK2bt1Khw8fpjNnzpCDg4NM17l16xZt3bqVNm/eTOrq6jRgwAAaPnw42dvbExFRjx49pL7WgQMHBP8X945VRtL7FhERQUuWLKG2bdtS/fr1SU1NTeh8eHg4q+yQIUPo7du3FB8fT7q6upSWlkZycnLk5+dHnp6etGLFCkY5bW1tio2NpS5dugiVjxkzhvbs2SP2c7S1taUDBw5QvXr1WOtUpbi4mLy9venixYvUrl07ql27NvF4PLp//z4lJSVR06ZN6dSpU6SgoMAo/+3bN2rXrh2ZmJhQXFwc3bt3j9q2bUv9+/enZcuWSd2PwsJCKi4uFirT1NRkrX/27Fni8Xis56X5Tvv69Svl5ORQUVGRULmrq6tEWY7/CP/07IKDg+Of4dq1axg2bBh0dHRgbm6OadOm4cmTJ0hJSYGXlxcaNmwoIqOmpsa4IvzkyROoq6v/Hd0WQdpMlP8Fli5dChcXFygoKKBbt244evSoSEKZzMxMyMnJib3Ozp07ZQolaGNjIzBjqLzaun37djg6OrLK1cRBtSZxwlVUVBh3iq5evSpwgszKyhKxma5JNKIK1q5dCyUlJZibm0u0rWZCmog3lXd5AgICoKmpCQsLC4FZl6WlJTQ1NWXaBZIFa2tr1qNWrVpiZfPy8tC8eXNoa2tDTk4OFhYWUFBQgKenp9gxWZOdkepmxf3+/TsWLFiAevXqQUVFBSoqKnB1dcWCBQukMgv69OkT3Nzc0LNnTxgaGkr0vaigoKAAYWFhMDAwYAxB+7N48+YNOnfuzBr6luN/B0655+D4xaiJAqmrq4uLFy+KlF+4cEFseMiaYmVlhTlz5uDp06fVki8oKEBGRoZUsdTZskdWPgwMDFC3bl2MHTuWNdb/3r170bt3bzRu3FjqmOh2dnaYP38+Xr16xVrn+/fviI6Olun+JbFw4UI4OTnh8uXL0NDQQHJyMmJjY2FgYIBVq1axytXEQbUmccI7deoEDw8PIYfImzdvon79+ujcuTOAcp+JqnHCZXUmHzNmDONhYWEBX19foTJxVDfiDVCewTkkJEQkAdyQIUOkViYrkDYvxY/g1KlTWLx4MRYuXCjR/r2C3bt3Q0dHR7DwYGpqigcPHkiUq25WXFlhSvD24MEDWFhYYNiwYVLbvg8fPhyOjo7Yu3cvVFRUsHXrVvzxxx8wNzdHbGysWFlra+tqfxf269cPzZo1w9WrV6GmpoaTJ08iJiYGtWvXxp9//inz9Tj+vXBmORwcvxj29vY0ePBgCgoKImNjY8Y6RUVFtHv3bgoICBAq9/f3p9zcXDp8+DBpaWkREdGnT5/Iz8+PDA0NKT4+XmzbBQUFdO7cOcYtYXFb/atWraLo6GhKTU2lNm3aUHBwMHXv3p2UlJTEtvf27VsKCgqi48ePM55nMk3Yvn272GsSEZWVldGbN29o27Zt5O7uTrt37xY6v3LlSpo2bRoFBATQpk2bKCgoiB4/fkzXrl2jsLAwioiIkNhGdTh37hwtWbKEMjIyiMfjkaOjI02YMIFatmwpUXbatGm0fPlygQmOkpISjR8/nv744w9WmQ0bNtDs2bOpf//+jOYbvr6+rLLbtm2jGTNm0NKlSyk4OJg2b95Mjx8/pgULFtDmzZvJ39+fVTY3N5cGDhwoZDZRUlJCbdu2pZiYGDIyMqIzZ85QcXExtW/fXiB39+5d2rp1K+3cuZO+f/9Offr0oeDgYGrUqBFjO23atGHtQ2V4PB6dPn2a9by+vj6VlZVR37596ffffxcxJyIqNzXz8PCgrKwsoXIDAwNKSUmh2rVrC5U/ePCAmjVrRu/fv2dsc+HChWRtbU19+vQhIqLevXvT/v37ycTEhBISEqQyYSkqKqKsrCyytbUleXl5ifV/BOvWraMxY8aQgYEBnTlzhuzs7CTKzJkzR+z5WbNmsZ4LDAykwYMHk6enp8R2+Hw+o0lMhRrF4/EIgESzJ0tLS9qxYwe1bt2aNDU16ebNm2RnZ0cxMTG0e/duSkhIYJWt7nchEZGJiQkdPnyYGjVqRJqamnT9+nVycHCgI0eO0KJFiyglJUXiNTj+G3DKPQcHh9S8ePGCPD096f379+Tu7k5ERLdv3yYjIyNKSkoSa3t969Yt6tSpE339+pUKCgpIV1eX3r17R6qqqmRoaEhPnjyR2H5qaipt3bqVdu/eTSUlJdSvXz8aPHgweXh4MNbv378/ZWdn04oVK6hNmzZ08OBBev36Nc2bN4+WLl1KnTt3rt6D+D9u3rxJ7dq1E1Gw6tSpQ7NmzaK+ffsK2ZPPnDmTPnz4QKtXrxa5Vn5+vsDWNiEhgUpKSgTn5OTkJPY1NjaWgoKCqEePHtS8eXMCQBcvXqSDBw9SdHQ09evXj1GutLSUUlJSqG7duqSsrEzp6elUVlZGTk5OpK6uLrbNmvpRbNq0iebNm0fPnj0jIiIzMzOaPXs2BQcHi5Wr4P79+/Tw4UMCQHXq1BFRgNkoKSmho0ePUnR0NB0/fpzs7e3/X3v3HRXF9fYB/Lu7VOksEAVRQBBFRcSOkShYscbeEVAsUSyoqImJNYpGxfKzA4rYe6yY2CKJioKABQt2jSYKEkVUhH3ePzw7L8v2Ait6P+fsOdnZuTt3yYJ3Zp6CsLAwDB48GPb29iq9hzo2b96M3r17w8TERO2xNjY2iI+PR/fu3SW279+/HyEhIXj58qXMcW5ubkhMTISfnx9+++039OnTBzt27MDOnTvx8OFDHD9+XO4xCwoKMHbsWO5E99atW3Bzc0NERAQcHR0xdepUqTHLly9X+lkMDAxQuXJlfP3113BwcMDEiRNl7rd79240aNAANWrU4LapE8eujp49e+Lw4cNwdnZGSEgIgoOD4eTkJHNfZTk8JSmKfTc3N8e1a9dQvXp1VK1aFXv37kWTJk1w79491KtXD/n5+UrfX92/hcDHWP7MzEy4uLjAxcUFW7ZsQYsWLXDv3j3UqVMHBQUFKn8+5hOnv5sGDMOUl9LhKIoeyuTn59PatWtp9OjRFBkZSZs2bVKp4sc333xDw4cPp6KiIi4M4+HDh+Tv70979uxR6/MUFhZSTEwMGRsbE5/PJ29vb4qNjeXq4ItVrlyZqxNvYWHB3eI/cOAAtWjRQuExVKkMVFBQQDExMVL7mJqacvHk9vb2lJ6eTkQf48ltbW2l9j948CD5+Phwz83NzaWqYuzatUvhfNXtFluSNo1xNPHhwwfauHEjF35Uuk54eVG1GpGmFVl0YcKECWRjY0OLFi2is2fP0tmzZ2nRokUkFAoVhgOZmJhwpUAjIiIoPDyciIhu3rypNIQuIiKCGjZsSGfPnpXIszlw4IDE97QkRXH64ke1atW4ylN79uyhVq1aqfRo3bq1wvlq00eASHYlo127dum0klFJ9erV4zo/t23bliIjI4noY0iaKmU0S1L1byHRxxr5x44dI6KPIXWDBw+mx48f05QpU8jNzU3LT8V8StjinmG+AOIFoqwSauWVVGVlZcV1mrWysuLq1J8/f548PT1Veo/CwkLasWMHdejQgQQCAbVo0YLi4uJo7ty5VLlyZerfv7/E/hYWFlzCZ/Xq1Sk5OZmIVGux3rhxY5kL6j179lCTJk0UjnV1deUSfRs1asTVfE9KSiIbGxup/bt06SLR2bJ0Kcvo6GiF9eaJ1O8WW5KmjXG0OSEoeQKkiUePHtH//vc/ioqKkoqJV0aTZHI3NzfuJE0VpXsbKHooUlxcTNHR0eTo6Mj9/jo6OlJ0dLTCPhNVqlTh6qbXrFmT60p748YNsrCwUHjMatWq0blz54hI8rt4+/ZtpWOVKS4upnnz5ik94VSHNn0ESktLS6MxY8aQiYkJ2dnZ0fjx42V2ej569KhEg7eVK1dS/fr1qX///pSbm6vwGEuWLKFly5YREdHJkyfJ1NSUjIyMiM/ny7xYIIu6fwuJiBITE7kcmbS0NC6h18TEhLZv367ScZmKgS3uGeYLcP/+fe6xb98+rrOo+Gr9mjVryMPDg/bt26fwfX7++WeKjY2V2h4bG0sLFixQONbOzo67cl6zZk3uClJWVpbShXZqaiqNGTOGhEIhOTg4UGRkpFQFjZSUFKkqK9pcqdKmMlBYWBjNnDmTiIhWr15Npqam1KZNG7K2tqbQ0FCp/atXry5R/aX04j4zM5Ps7e0VHlObbrGaNsbRpttxq1atlH7f5Pn999+pUqVKVKdOHTIwMCAfHx+ytrYmKysrhVd5tUkmV7ciS1lUvFG1URER0XfffUfVq1enNm3akFAopNevXxMR0fbt25UmmZbsO1Dyu5ienk6WlpYqz1eex48fk52dHfdcF3dGdHH1XZVKRmJ169alw4cPE9HH308jIyOaNm0aNW3aVO0qRg8ePKA9e/aodPKo6d9CWd68eUOpqan0/PlztebLfPrY4p5hvjCNGzfm/lEq6fDhw0qrlFSvXl1mF8Xz58+Ti4uLwrFt27alLVu2EBHRiBEjqEmTJpSYmEjt27dXeiWcz+dT+/btFTb9yc/Pl/pHVZsrVdpUBiouLpZobrNjxw4aO3YsLVu2jN6/fy+1f+mwmIsXL0p8zrt375KRkZHCY2rTLVbTxjiyuh2Lw6CU2blzJ7m5udGKFSvor7/+Uis8rHHjxjRjxgwi+v/F5+vXr6lr1660atUqueO0qUakTUUWXVS8+ffff+ns2bOUnJys0mKssLCQFi1aRBERERJVhZYuXUrr169XONbf35+WL19ORB9/vuLv5nfffUft27dXOFb8PS9txYoVNG7cOLnj1L0zooiqV9+JNK9kVLIM7E8//cQ1TEtNTVXa+E0bmv4tZL4sLKGWYb4wpqamSEtLQ+3atSW2Z2VlwdfXF2/fvpU71sTEBFlZWXB1dZXYrqjZkdilS5fw+vVrtG7dGs+fP0dwcDCSk5Ph7u6O+Ph4hdU7Hjx4gOrVq6v4CeUrKCjAjRs3UK1aNdjZ2SncV9vKQOpwdHREQkIC2rRpI/P148ePIzg4WGlDpn379mHx4sXIysoCAK5aTrdu3RSO07bZlyYJqrKScVWtNmJhYYH09HTUqFEDNjY2SE5ORp06dZCRkYFu3brh/v37CuerCW0qsmha8Qb4WGFq7NixSEhIgEgkAvAxwXrIkCFYsWIFKlWqpManUM1ff/2FDh06YODAgdi4cSNGjBiBa9eu4dy5czhz5gwaNmwod6yTkxN+/fVXqX3S0tLQtWtXPH78WOa4+Ph47Nq1C4mJibC1tdV47k+fPkVCQgLi4uLw5MkTrpHZqVOnsHDhQkyYMEFif00rGdna2iI5ORleXl74+uuvMWTIEISHh+P+/fvw8vKSmZyakJCg0mcYMmSI3Nc0+Vs4e/Zslfb78ccf1Xpf5hOm55MLhmHKWYMGDWjAgAESYRTv3r2jAQMGKL0C6e7uLrNNfEJCgtLmNtpwdXWlFy9eSG1/+fKlysdNTk5WqTGN2OPHj8nNzY2srKy4xD5ra2vy9PTkEhVVUbduXaX79+3bl7p06SL39U6dOlGfPn3kvv7hwweaOXOmWvMSKywspFatWqlUT1wZVRNUiSRDxWQ9FPnqq6/o2rVrRETk5eVFBw4cIKKPYSOlG1eJlQxnOXz4MB04cIB7lHWNb2tra5khSPv27VN6Fyg8PJzc3NzoyJEjXFjO4cOHqUaNGjRy5EiVjm9hYSEzxEyRzMxMGjJkCNWpU4dq165NAwcOpMzMTKXjjI2NNcr90ObOiDZ9BBISEtQOKSP6mCfTvn17mj17NhkaGnJx/klJSeTh4SFzDI/HIwsLC7KxsSFra2uZD1k5ObK8evVKInROHHYl77hOTk7UoEED8vHxkfnQZT8ARv/Y4p5hvjAXLlwgBwcHsrOzo8DAQAoMDCQ7Ozuyt7dXGlKxYMECEgqFFBcXxy3CYmNjSSgU0s8//6zyHObPn69WQx0ejyezmsqzZ8+UhquIabLA0bQyUEml4+dlSUtLI2NjY+rVqxelpKRQXl4e5eXl0YULF7hkQWWdeLXpFmtnZyc3bEEV6iaoFhYWkqurK7dAV1e3bt1o3bp1REQ0efJkcnd3p7lz55Kvry8FBgZK7a+LakREH08m169fT1OnTuVi71NTU5UmcGpa8YaISCgU0qlTp6S2nzx5UiJuXRFVvoO6UqdOHZmNz5YvX66w2/HMmTMVPhQRCoVkY2NDo0ePpsuXL8vcJzc3V2nooDoePHhAnTp1Im9vb4lk+PHjx9PYsWNljvHy8iKhUEjjxo1TqTJZSZcvX6agoCDuubm5uUQInUAgoJSUFJljO3bsSCYmJtStWzc6cOCAwkRs5vPAwnIY5gtUUFCAxMRE3LhxA0QELy8vDBgwQKoJUWlEhKlTp2L58uVcEyoTExNERUVhxowZMhu8yGJpaYn09HS4ubkp3O/XX38FAHTv3h2bNm3iwmOAj/XZT5w4gd9++w03b95UesyS9ebLk6rHPXDgAIYNG4bc3FyJ7TY2NtiwYYNUnfPSunfvju7du2Po0KFqzzEyMhKGhoZYsGCBWuOWLFmC+Ph43Lx5E0FBQRg2bBiCgoIkQm6ys7NRq1Ytibr9wMfwjd9//10qPEwVd+/eRX5+Pry9vVFQUIBJkyZxIV5Lly6VClvo2rUrunXrxtXPL/3/ZOHChTh9+rTC5kGZmZlo06YNrKyscP/+fdy8eRNubm6YMWMGHjx4oDDkQiQS4ZdffsGyZcu40KoqVapg3LhxiIyMhEAgkDu2UqVKSE1Nlfo5Xbt2DU2aNMGbN28U/7BkfF5ViEQiZGdn499//+XCgcQUNXyKi4vDmDFjMHnyZAQEBAAATpw4gcWLFyMmJgbDhw9XeQ6qUrePQI8ePVR+771792o6LZkuXLiAuLg47NixA+7u7ggLC8PAgQO5HhfyhIWFwd3dHdOmTQPw8f/p2rVr4eTkBCJCXFwciAibN2+WOf7p06fYuHEjNm7ciFevXmHIkCEIDQ1VuTcEU8Ho88yCYZiK6fXr15SSkkJXrlzhQl1KJpAqo+qVxJJXVkteaRWHfNSsWZMOHjyo02OKaVMZqKSOHTvKDEuR5c2bN7R3716Kjo6m6Oho2rt3L+Xn56s0ds2aNVS5cmWKjIykrVu3SoSdiMNW5BkzZgxZWlqSr68vhYeHq1xaUpsE1fnz51NwcLBa3xtN6aIaUWBgIE2ePFlq/J9//knVq1dXeS7qVLwhIgoICKDevXtLhI4UFBRQ7969Zd6lkGXkyJFqVUQ5d+4cubq6yvy9U6Vc7qpVq8jJyYkb4+rqSps2bVI6TtM7I+rSdSWjoKAglX/HxQoKCmjTpk3UqlUrqlSpEg0YMEBh2KCnpyf98ccf3PPS3+Hz589TtWrVVDr2mTNnaOjQoWRhYUF+fn5UUFCg1tyZTx+7cs8wX6A7d+4gJiYGWVlZ4PF4qF27NsaNGyfREVJV169fR2xsLBITE/HPP/+oNEbdK4murq64ePGi0iRYRbZu3Ypu3bopvTsh5uLigq1bt8LPz09i+4ULF9CvXz+J5LrS8vLyYG1tLfO17OxsuLu7y3zt3r17UsnKqtKmW2zr1q0Vjj158qRGc1Lk22+/xYkTJ2Bubo569epJ/X/R5RXT0ongly5dQv369WFoaAjg48+9Vq1aeP/+vdz3sLKyQlpaGmrUqCHx/X3w4AE8PT0VJpOLPX/+HDdv3gSPx4Onp6dK3+erV6+iQ4cOePfuHerXrw8ej4f09HSYmJggKSkJderUUfGnoDofHx/UrFkTs2bNQpUqVaTuyJW8g6bI8+fPYWpqqrTTMaDZnZGnT59i5cqVmDdvHgDg66+/lkhkFQgE2L9/v9yOswAQFRWF3NxcrFmzhruDUlxcjNGjR8PS0hKLFi1SOndt7gr+8ccf+Omnn/DHH3/gxYsXsLGxkbmfmZkZrl+/zt2VWrp0KcLCwrgr/g8fPkTNmjVV+h6+ffsWu3btwv/+9z9cuXIFz549U3rngKlYDPQ9AYZhyldSUhK6du0KHx8ftGjRAkSEv/76C3Xq1MHBgwfRtm1bpe+Rn5+P7du3IzY2FhcvXkSzZs1ktqSX5/r163B0dFR5f0ULaUX+++8/FBcXw9bWFgMGDOC25+bmwsDAQOE/aM+ePUOVKlWkttvb2yutWhMUFISTJ09KhQncvHkTgYGBciuGuLu7w9/fH2FhYejVq5fKYQYApEIn1HHq1Cm1x7x69Yr7+R05ckQi7EYgEKBTp04Kx1tbW6Nnz55qHVPVxdPdu3clntva2uLOnTvc4r5Ro0YSr9++fVtphRYTExO8evVKavvNmzflVgQS06biTd26dXH79m2JMLp+/fph4MCBMDU1lTsuIiIC7u7uiIiIkNi+cuVKZGdnIyYmRu7Y27dvY/fu3XJPQhW5d+8eioqK4OHhIfFzuX37NgwNDeHi4iJz3MSJEzF06FAsXLgQFhYW3PaOHTtK/O6WtGrVKuTl5XHPMzIyEBoayv2/PHr0KJYuXYpffvlF7nzj4uKQnJwsERolEAgwceJE+Pn5qbS4V9eTJ0+wadMmxMfH482bNxg0aBBWr14td2EPAMbGxnj8+DG3uC9d9efRo0dKKyedO3cOcXFx2LlzJ2rWrImQkBAMGDCALew/R/q9ccAwTHnz8fGhqKgoqe1RUVFKKyacPXuWgoODydzcnOrVq0cCgYDr+qpMSkoKnT9/Xmr7+fPnJUImxJYtW8aFIixbtkzhQ54OHTrQ//73P6ntq1evVtrxVZvKQEFBQdS+fXuJkJPr169T5cqVKSIiQu44berGa9MttqRHjx4pDYPQVYKqung8Hrm4uND06dMpJiZG7qM0basRERENHz6cunfvToWFhVzt9wcPHlCDBg0U1m8n0k3FG3U5OjrSpUuXpLanpqaSk5OTwrGtW7emo0ePanRcf39/mWFYmzdvpm+++UbuOEtLS8rOziYiyZCT+/fvy62yU79+fTp+/Dj3vHSoyrFjx8jLy0vhfLWpZCRWp04dlSpViTvKmpqaUvfu3dVKbg0ICFDYE2HixIkUEBAg87Xo6GiqVasW2dvb0/jx41WqesRUbGxxzzBfGGNjY5mVUW7evCn3H9Ho6Gjy9PQkJycnmjRpEtdsxsDAQOWKJ40bN5a54NuzZ4/MJlYuLi5c+UsXFxe5D0ULbRsbG7p+/brU9qysLLK1tVU4X20qA719+5a+/vpr6t27N4lEIrpy5Qo5ODgorYwi9uHDB9q7dy917dqVDA0NycvLixYvXkz//vuv3DHadIstLi6mWbNmkaWlJVd9w8rKimbPni3VwZXoYxnAkhVCSi+qoqOjlZ48iZVszqTo8xH9/+LIxMSEvv32W5kdZmXRRTWi//77j1q0aEHW1tYkEAjI2dmZDA0Nyd/fX2lehDYVb0qWgH348CHNmDGDJk2aRGfOnFE4TtOSlEREe/fuJS8vL4qPj6dLly6p1WDMwsJC7nGtrKzkjnNwcOCabZX8PiUlJVHVqlVljrGyspL43n377bf07Nkz7vm9e/eUdr/WppKRung8HlWvXp2mT5+u9sWK3bt3k4GBAa1cuVLiO19UVETLly8nQ0NDuSfU4uN+9913Uvk0quTWMBUPW9wzzBematWqtHPnTqntO3bsIGdnZ5ljBAIBTZ8+XeoqkzqLezMzM5kJrXfv3iVzc3OV3kNdlSpVknmVKjMzU+k/+iKRiKZMmUImJibcgrdSpUo0a9YsEolESo+dl5dHPj4+1LNnT3JwcFC5E2lJ6tSN1+aq/9SpU8ne3p5WrVpFGRkZlJ6eTv/73//I3t6epk+fLrW/LhJU8/PzKSQkhAQCAXfF38DAgEJDQ+nNmzcKxz5+/Jjmzp1L7u7uVKVKFYqKilJaynP//v1kZ2cnUT6Qz+eTUCiUeeVWnhMnTtCiRYsoOjqafvvtN5XGmJqayjzJvHr1KlWqVEnmmMzMTKpevTrx+Xzy9PSky5cv01dffUXm5uZkaWlJAoFA4bw1LUlJRFJJtCWT2pUl1FpaWkp0xBW7dOmSwt9zTe6MmJmZyTyWWFpamty+B2LFxcUUHR1Njo6O3Gd1dHSk6Ohola6qX7p0iTZv3kyJiYlKTxCrV6+u8EKFsosVU6ZMIR6PR5aWllxtevEJuaK/L9988w3Xq0Peo3Xr1ko/K1NxsMU9w3xhZs2aRdbW1rRgwQL6448/6OzZszR//nyytramOXPmyBwzb9488vDwIGdnZ5oyZQpduXKFiNRb3Nva2tJff/0ltf3PP/9Uevv79OnTKh2jtG+++YbGjBkjtX306NH09ddfq/QeqlYGKtlQRvy4efMmOTs706hRoyS2K6Nu3fiSNLnqX6VKFZkVdfbv30+Ojo5S242NjSXCgC5evChR///u3btK+w/oKlTl9OnT1KpVK+Lz+ZSbm6twX22qEWlDk4o3HTp0oM6dO9PZs2dpxIgR5OTkRCEhIVRcXEzFxcU0evRoatq0qdxjxsbGkqmpKf344490+vRpOn36NM2YMYMqVarE9QiQR5sGY506daLevXtLLIyLioqoZ8+e1KFDB7njNLkz4uvrSytXrpT7nsuWLVOrOZM6lYz++ecfat26NfF4PK4pFY/Ho4CAAKV3oLRx7tw5ioiIoI4dO1LHjh0pIiKCzp07V2bHYyomtrhnmC+MSCSiJUuWSJSqc3JyopiYGKVXpE+fPk1DhgwhMzMz8vb2Vivmvm/fvvTNN99QXl4et+3ly5f0zTffUO/evRWONTQ0JGdnZ4qKilIrXjQ5OZlMTEyoZcuWXDOcli1bkomJiURZOVVdu3aNJk6cSA4ODlKvia9qln6oc+Vz8eLFVLduXTI0NKRu3brJDDu5ffs2CQQCpXNV56q/sbGxzA61N27cIBMTE6ntVapUUXjVOikpiSpXrqxwfto2Z3r79i1t3ryZWrduTaamptS3b1+lHYg1yUtQlu+xbNky+t///kd79uyR2WiN6ONdFScnJxIKhRQQEECBgYEkFArJycmJrl69KnOMUCjkQmBev35NPB5P4m5JVlaWwjAXIs1LUmrj2rVrJBQKqUaNGly5yRo1apC9vT13UUARde6MLFy4kGxtbWWGCqWnp5OtrS0tXLhQpXmXDA9TpWxonz59qGHDhhJ3ZK5du0aNGjWifv36qXTM8qYopEqdu1fMp48t7hnmC/bq1SuJFu3qjFu9ejU1adKEBAIBNW/enBYvXqxwzOPHj8nNzY2srKy4W8HW1tbk6empNBnt+fPntGLFCvLz8yMej0f16tWj6OhoevTokdK5Xr58mQYMGEBeXl7UsGFDCgkJUasb6+vXr2n9+vXUrFkzEggE1KJFC1qyZInUfuKro6o85NGmbryYJlf9mzRpIrOr5pgxY2ReHdZFgqomoSpEHxOwhw8fTpaWltSgQQNasWKF0iv2YprkJSgLo3BxcaFq1aqRmZkZmZqa0p49e2S+T0FBAa1bt44mTpxIEyZMoPXr1yusL166K3Pp0Kdnz56pVHOe6OPC9fXr10r3GzVqlMR+CQkJEs9fvnypUi7FkydPaNq0aRQUFEQ9e/akWbNmcXXrdamwsJD8/f3JwMCAOnbsSOPHj6cJEyZQx44dycDAgFq2bKm0o7Sm4WGWlpYyO8JeuHBB6UnX2LFjZcbWr1ixQmlydvXq1WnWrFkqJfCWVrlyZZmhkbt371b4O8dUPGxxzzBfuPfv36v0D788mZmZNG7cOKUx1kQf/yFdu3YtjR49miIjI2nTpk1K//Et7e7duzR37lyqU6cOCQSCMosV1bQy0IcPH2jmzJka/eOrDW2u+p8+fZrMzMyodu3aFBoaSmFhYVS7dm0yNzeXeYdDFwmqmoSqeHl5kZ2dHUVERChN7JRFm7wEZYqLi2nevHlUq1Ytnbwfj8eTCO8Qx6GLKVvc3717V+ZJ7K1bt+jevXsyx/D5fIkTCgsLC41PKEp78eIFLV26VGq7tndG3r9/T/Pnz6f69euTqakpmZqakre3N82fP1/pnRwizcPDzM3N6fLly1Lb09LSyMLCQuExtalktHz5cvL19SWBQEBt2rShbdu2qfQ5iT6GZLq4uEjcvdu+fTtVqlRJZh4WU3GxxT3DfEHi4uJozJgxlJiYSEQfEymNjIyIz+dTmzZtJCpzyKIorEHdRbo2ioqKuHKMihYbhw8fpmPHjkltP3bsGB05ckTmGF1UBjI3N5e7gCqtdCUSRQ9FtL3q//jxY5o+fTr16NGDvv32W/r+++/pyZMnct9L2wRVTUJVeDwemZubk7W1NdnY2Mh9KKNJXoIqHj9+LDOkSJOKNzwej4KCgriuqQYGBtSuXTvueVBQkMLvviYlKXV5t4DoYwjgsWPHqHfv3mRkZCTzZ6OrOyOa0jQ8rGvXruTv7y/xO/L48WP65ptvqHv37gqPqU0lI7H09HSKiIgge3t7srGxoe+++07pCTURUUREBHl5eVFOTg5t2bKFTE1Naffu3Sodk6k42OKeYb4Qc+fOJVNTUwoMDCRbW1saOXIkVa5cmRYsWEALFy6kqlWrKk1k1Kbc4s8//0yxsbFS22NjY2nBggUqvUdycjKNGjWK7O3tycLCggYOHCh3kU5EVK9ePTp8+LDU9qNHj5K3t7fMMbqoDNStWzeKj49Xad+S8fjy4vbFj0+Ntgmq6oaqbNy4UaWHqtTJSyD6eIejc+fOVKNGDXJ3d6cuXboozN3QtOJNRkYGDRo0iItZV/SQR5OSlLpa3N+7d49mzJhBzs7OxOfzadCgQfTbb7+pXNNdFkV3RoKDg5WWBpVH0/Cwhw8fUoMGDcjQ0JDc3NyoRo0aZGhoSL6+vkrDBbWpZFRaYWEhxcTEkLGxMfH5fPL29qbY2FiF+VODBg0iDw8PqlSpEu3fv1+t4zEVA1vcM8wXwt3dnbZu3UpEH+OySzcaOnLkCFWrVk3he8gKa5DVmEqW6tWr059//im1/fz58+Ti4qJw7LRp08jFxYWMjIwoKCiItmzZorRcIhGRiYmJzCvo9+7dk/sPty4qA61Zs4YqV65MkZGRtHXrVjpw4IDEo6SSVUj27dtHNWrUoDVr1nBX69esWUMeHh4Kr4aXrPBx+PBhiWMdOnRI6Xzj4uJk3pbfuXOnwsWyrhpnlTdN8hI2b95MBgYG1KdPH1q2bBnFxMRQnz59yNDQkLZs2SLzOJpWvCkZHuPq6qr0jposmpSk1GZx/+7dO9q6dSsFBARwfQh27dql1u+NMvLujIhDwdzd3WnevHlKm7CVpEl4WEnHjx+n5cuX07Jly1QujapNJSOxwsJCru+DOBcoLi6O5s6dS5UrV6b+/fsTEUn97Tlw4ADt3r2bnJ2dKSwsTO7fJaZiY4t7hvlCGBkZScSBGxkZ0Y0bN7jnjx8/JkNDQ5XeS5OwhtLlE8Xu3Lmj9FZ08+bNaeXKlSpVsSjpq6++ohMnTkht/+2335TmCGhTGUhWnfCSV+blady4scw7DYcPHyZfX1+ZY3TRLbZmzZp08uRJqe2nT5+mmjVryh2nrzs56nY7FtMmL6FWrVoyE6kXL14sN85e04o3tra23OcrHXuvKk1KUvJ4PBoxYgTX1MjIyIhCQ0O55yNGjJD7/RUKhdSyZUtau3atRIKzqot7bZJMiT6GPsXExJCPjw8ZGBhQhw4daNeuXUrDBTUJD/vw4QMJBAKVqv/Io2klo9TUVBozZgwJhUJycHCgyMhIysrKktgnJSWFq3Kl6G+Rqn+XmIqHLe4Z5guh63haIvXCGtzd3Wnz5s1S2xMSEhQ2btHG8OHDqV69elxbe6KPizdvb28KCwtT6T00qQykKRMTE5khAtevX5dZkpJIN91ijY2N5d7hkHdcIu0SVLW5k6Nut2MxbfISjIyM1I6T1vR3bvjw4WRkZEQuLi7E5/OpWrVq5OrqKvMhjyYlKVVpdtSqVSuZY62trcnf35/WrVsncSdJ1cW9NkmmpaWlpdGYMWPIxMSE7OzsaPz48QorZKkbHkZE5ObmxuXjaEPVSkZifD6f2rdvTzt37pR74pKfn68wZIv5/LHFPcN8IXg8Hp06dYoL9zAzM6PDhw9zz0+cOKHy4l6TsIYFCxaQUCikuLg4LgwlNjaWhEIh/fzzzyod99q1a3T06FGFYS4l5eXlUbNmzcjAwIBLzjMwMKDWrVurXD6xJHUqA4mpc0W7QYMGNGDAAIkx7969owEDBshtxqOLbrHOzs5ym1ipsrAq7zs5+uh2LA6XKm3NmjXk7u4uc4w2FW+OHj1KK1asIB6PR3PmzKGYmBiZD0XKqyQl0cfveWJiItd3oEePHrR3714yNDRUaXGviyRTIqK///6bFixYQDVr1iQzMzMaMmQItW3blgwMDGTeedFUXFwcdezYUaOfpyaVjMSUNRGTp7CwkFq1aiWznwXz+WGLe4b5QpRO3JTVWp7H4yl8D23CGkQiEU2ZMoVMTEy4BNFKlSrRrFmzlDbPunPnDnl7e8tNPlVEJBJRUlISLVy4kFasWKFy4p02lYGKiopo9uzZ5OjoSAKBgFuI/vDDDxJX2Uu7cOECOTg4kJ2dHQUGBlJgYCDZ2dmRvb293CviuugWO3nyZKpevTqdPHmSioqKqKioiE6cOEHVq1enyMhIhWNLKq87Oep0O9ZVNaJVq1aRkZERjRw5khISEmjz5s00YsQIMjY2lrnoJ9K+4g0R0dChQzXqRSGPvJKUihQVFdHly5dVPiHOzs6m77//nqpWrUo8Ho8GDBhAx48fV5hQq02SaWFhIe3evZs6depEhoaG1LBhQ1q9erXEz23btm0yO2FrUsmIiMjHx4fMzc3J2NiYatasSQ0aNJB4KKJJJSNdsLOzU6vHB1Nx8YiIwDDMZ+/BgwfcfxcXF0MgEEi8LhKJIBAIUK1aNbnv4eHhgdDQUISEhKBy5coy9yksLMS2bdsQHBws8/X8/HxkZWXB1NQUHh4eMDY2RlFREQwMDOQet0uXLhAIBFi/fj3c3NyQkpKCnJwcREZG4pdffkHLli0VfXSpz3n48GHExsZi//79cvcTCATw9/dHWFgYevXqBRMTE5WPMXv2bGzatAmzZ8/G8OHDcfXqVbi5uWHnzp1YunQpzp07J3dsQUEBEhMTcePGDRARvLy8MGDAAJiZmcnc39HREQkJCWjTpo3M148fP47g4GA8ffpU7jELCwsxePBg7Nq1i/v/IBKJMGTIEKxZswZGRkYKP++lS5cQFxeH7du3w8zMDMHBwQgLC8Pff/+NH3/8Ea9fv0ZKSorEmOjoaCxatAiLFi1CQEAAAODEiROYMmUKIiMjMW3aNLnH69evH549e4YDBw7AysoKAJCXl4fu3bvDwcEBO3fu5Pbl8/ng8XgQ/1PH4/Hkvm9xcbHCz7lv3z4sXrwYWVlZAIDatWtj8uTJ6Natm9S+mZmZWLRokcLvtVh8fLzSfbRBRDh+/DhiY2Nx4MABWFpa4vnz53L3Hz9+POrVq4ewsDAUFxfD398f586dQ6VKlXDo0CG0atVKpeOKRCIkJSUhNjYWBw8ehIWFBV68eCFz37i4OIwZMwaTJ0+W+D4sXrwYMTExGD58uNzj2NnZQSQSoX///hg+fDh8fHyk9nn58iV8fX1x7949AMCVK1fQpUsXPHr0CB4eHti+fTs6dOiAN2/egM/n482bN9i9eze6d+8u85izZs1S+Nl/+uknua9ZWloiLS0N7u7uEtuzs7PRqFEj5OXlSWy3sbFR+L0tKTc3V+5rkZGRMDQ0xIIFC1R6L6YC0+upBcMw5a50oxqxFy9elHtS1bVr12jixInk4OCgcL+SiYmWlpZcIvCJEyckkkkVuXXrFk2dOpWqVKlCJiYm1K1bN4X7a1MZqEaNGvT7778TkWSYTFZWlsyrh9rQRbdYsVu3btHOnTvp4MGDKt3+L6s7Ocqo0+1YF9WINGlMpouKN9rStCSlk5MTF+q1b98+cnR0pJs3b9L3339Pfn5+Gs3l33//VZqrommSaUJCgtoJ3ZpWMtIFdSsZlSzzunjxYrKxsaF+/fpxTb769etHNjY2SsOOxowZQ5aWluTr60vh4eFcorT4wXw+2OKeYb4w8qpv3L9/X2Z5SF2FNYi9fv2a1q9fT82aNeNKuCn7R8na2ppbILu5uXGVXbKzs8nU1FTuuIKCAtq4cSO1bNmSDA0Nic/n07Jly9RKYNMkntzExIRbHJdc3F+7do3MzMwUHi87O5vGjBlDgYGB1KZNGxo7dqxEQnBpuugWW1JycrLKHS+1bZxF9PH7kJKSQleuXFH5uESadTvWpBqRmJmZmcqNyYh0U/FGE7ooSWlsbMzVah8+fDhXrebu3btKu69qU3NeTN0kU01oWslITJvPqUklI7EePXrIDF9asWKF0gsWipKky6rTN6Mfyu8XMgzzWZg4cSKAj2EJM2bMQKVKlbjXiouLceHCBZm3s318fHQS1pCcnIwNGzZgz549cHV1xfXr13HmzBm0aNFC6dzr1q2LzMxMuLm5oWnTpli4cCGMjIywbt06uLm5Se2fkpKCDRs2YMeOHahZsyYGDRqEXbt2oWrVqmjTpg3Mzc2VHlPMwMAA3377LYKCgrBq1SpMmzYNkyZNwrRp09C3b19ER0ejSpUqEmPq1KmDs2fPonr16hLbd+3ahQYNGsg9VlJSErp27QofHx+0aNECRIS//voLderUwcGDB9G2bVupMQ0aNMCOHTswbNgw7N27V+I1GxsbbN++Hb6+vip/3o4dOyI9PV3mz7W027dvK93HyMhIbogWAJibmyM7Oxtdu3aFsbGxyvM0MzNDeHi4yvsDH0MxXF1dpbaLv4+KtGnTBqdPn8bQoUNVOlbPnj3h7+8PR0dH8Hg8NGrUSCoUTuzu3bsqvacqnJyc4OXlhUGDBmH37t2wsbEBAPTv31/l9/jqq69w/fp1VKlSBceOHcOqVasAfAwZk/cZxF6/fo127drB2dkZISEhCA4OhpOTk9Jj3rt3D0VFRfDw8IC9vT23/fbt2zA0NISLi4vE/j169FD585T+vQA+hq+IQwvNzc1hZmYGW1tb7nUbGxu8fv1a7ntq+jkBYOHChfD394enpycXUnj27Fm8evUKJ0+eVDg2KSkJ0dHRUtvbt2+PqVOnKhx76tQplebHVHxscc8wX4jLly8D+Bh/e+XKFYk4aiMjI9SvXx+TJk2SGieOURW/x6RJkzB58mQ0b94cAHDu3DksXrwYCxculHnchQsXIi4uDvn5+ejfvz+Sk5NRv359GBoacgsPZX744Qe8efMGADB37lx07twZLVu2hFAoxI4dO6T29/Pzw9ixY5GSkgJPT0+VjiFP6XjySZMmScSTd+vWTSqe/KeffsLgwYPx5MkTiEQi7N27Fzdv3kRCQgIOHTok91hTp07FhAkTpGJip06diqioKJmLewDo1q0b2rZti6SkJG7B7eHhgXbt2smN1ZeHlKRhZWZmqvxe3t7eKu03YsQING3aVKUTCgCYP38+vvrqK4SGhkpsj4uLw/PnzxEVFSVzXO3atTF37lzExsZyORTv37/H3LlzUbt2bYXH7NixI6ZNm4arV6+iYcOGUj/Xrl27Sjxft24devTogezsbERERGD48OGwsLBQ6fNpo7i4GDweDzweT+lCXJ6QkBD06dMHVapUAY/H4753Fy5cQK1atRSO3bNnD3JycpCYmIiNGzfip59+Qps2bRAaGoru3bvD0NBQ5rihQ4ciNDQUHh4eEtsvXLiADRs24PTp0xLbxbkWwMfv7L59+2BlZYVGjRoBAFJTU5GXl6fwJKD0hQpV49oVfc6wsDB069ZN7ucEAC8vL2RmZmLlypXIyMiAqakphgwZgjFjxkicYMgiFAqxb98+TJ48WWL7/v37IRQKVZp7dnY27ty5A39/f5iamoKI1PrsTAWgz9sGDMOUv6FDh0rUoVaHJmENAoGApk+fLhXnq23nypycHLlVdtq2bUsWFhY0YMAAOnr0KLefOsfUJp6ciOjYsWPk7+9PZmZmZGpqSi1atKCkpCSFxzQ2NpZZzeLmzZtKywHqqlts6VKapcmrWCTroatjlqZpjXxNqhGJadMASNcVbxTRtiSl2K5du2jJkiVceA7Rx9jv/fv3qzUfVWvOW1hYyC2FqSg8hohoypQpNGzYMKkwl/DwcJo0aZLMMbqoZKTJ51RElUpG8fHxxOfzKSgoiObMmUNz5syhTp06kUAgoPj4eKXvHxAQwH1nxb9zoaGhNHHiRLXmynza2OKeYRiVadJkad68eeTh4UHOzs40ZcoUroGOqgttTbtBPnz4kGbNmkUuLi701VdfUUREBBkYGMicvyy6iCdXV9WqVWnnzp1S23fs2EHOzs4Kx2rTLbakLVu2UH5+vtzXdZGgWpq6i3ttauS/efOG1q5dSxMmTKDx48fTunXrFH7eikyTkpS6pE7NeXWTTEuys7OT6LYtduPGDbK1tZXanpGRQYMGDeKaeyl66PpzliYSiejYsWPUu3dvMjIyIjs7O6XHO3/+PNf7wsfHhwYMGKBSsv/gwYOpffv29OjRI4nfuaSkJPLy8lLpszIVA1vcMwyjMk2aLImdPn2ahgwZQmZmZuTt7U0CgYCSk5NVOq623SCPHz9O/fr1IxMTE/Lw8KBp06aplWRaXmbNmkXW1ta0YMEC+uOPP+js2bM0f/58sra2pjlz5igcq023WE1pk6Ba0tmzZ9VKptVHt2Nd3RnRh+LiYjpy5Aj17NmTjIyMSCgUSu0jrryiykMRTWvOa5Nkam1tLfNkct++fTKrU+mikpE2tfWJNK9kpI2vvvqK+ztacnF/9+5dpYn+TMXCFvcMw6hMm7AGsVevXtHq1aupSZMmJBAIqHnz5kpL5GnTDbKk3NxcWr58Ofn4+Mi85a5tZSBra2uysbFR+LC3t6d69erRxIkT6eXLlxLjRSIRLVmyRKIcoJOTE8XExCht9CWmSXUfoo8nX507d6YaNWqQu7s7denShf744w+FYzS5kyMma3EuJi+UQkybbsfqViMS09WdEX2TV5JS3MFZ/DAzMyMej8d9b3k8HpmZmSk9eRIKhWRjY0OjR4+my5cvy9wnNzdXKnzq2rVrJBQKqUaNGtxV8xo1apC9vb3Su3YTJkwgGxsbWrRoEZ09e5bOnj1LixYtIqFQKLPEoy4qGWnyOXVRyYjo40nP7t27ac6cOTR37lzau3evSicF5ubmXKhQycV9SkqKzDscTMXFmlgxDKMWdZssKXLlyhXExsZi69at+Pfff+Xu16BBA2RnZ+PDhw+oXr261LHS0tLUPnZaWppUFRltGx5t2rRJ6XFFIhH+/fdfxMfHo0GDBti2bZvM/cSVOjRNwnz//j1X3aewsBCGhoZyq/skJiYiJCQEPXr0kKjSs2/fPmzcuBEDBgyQeQxfX1/Url1bKkE1NDQUWVlZCv+/WFtbIzExEZ07d5bYPmHCBGzfvl1h0y0iwtSpU7F8+XIUFhYCAExMTBAVFYUZM2bI/f8mrxpRRkaG3GpEYlevXkVcXBy2bNmC9+/fo2/fvggLC0OTJk3kjtEncYKqv7+/2mO3bt2KVatWITY2lktIv3nzJoYPH44RI0Zg4MCBcsdu3rwZvXv3Vqvpm9jff/8tkWTq7e2tUpKpSCTCL7/8gmXLlnHfmypVqmDcuHGIjIyUSiwODw/Hpk2b4OjoiIcPH6Jq1apqVzLS5HPa2dlxlYx69+7NFRQwNDRERkYGvLy8lL5HdnY2goKC8OTJE3h6eoKIcOvWLTg7O+Pw4cOoUaOG3LGdOnWCr68v5syZAwsLC2RmZqJ69ero168fRCIRdu/erfJnYT5tbHHPMEy5uHfvnswyhADw4cMHhdUlNO0G6eLigtDQUAwdOlRh512xkl18lVUGkte5UlVpaWlo27YtcnJy5O5TWFiIwsJCtUp3atIttnbt2ggPD8eECRMkti9ZsgTr16/nOrKWlpKSgi5dukAkEqF+/foAgIyMDPB4PBw6dEjhwvfYsWPo168ffv31V24BOnbsWOzduxcnTpxQWpUFUL/bcYMGDdC+fXuZ1YiOHz+u0kliUVERDh48iI0bN+Lo0aPw8PBAWFgYBg8eLFHCUd969uyJw4cPa1SqsUaNGti9e7dU2dbU1FT06tVLooJWWcvJycHmzZsxfvx4lfZ/9eoVgI9dYBU5duwYV8lo9uzZck+ix40bp9Z8FbGxsYG3tzcGDRqEvn37cnNUZ3EfFBQEIsKWLVu4k56cnBwMGjQIfD4fhw8fljv2+vXraNWqFRo2bIiTJ0+ia9euuHbtGnJzc/Hnn38qPDFgKhg93TFgGKaCqkhhDcuXLydfX18SCATUpk0b2rZtm8qx3drEk6ekpMhMcDt//jzXKKegoIBiYmK41+Li4mjMmDGUmJhIRERTp04lIyMj4vP51KZNG6VxwdpU9zEyMpJbqaQsE1S3bdtGNjY2dPHiRRo1ahTXCVUTqnQ71qYaUWnv3r2jJUuWkLGxMfF4PDIyMqLBgwfT33//rfbcy8qLFy8oJiaGfHx8yMDAgDp06EA7d+5U2uzL1NRUZpjdhQsXZDaNE1eYUeWhCk2STIk+hhydPXuWkpOT6fnz5yqNUbeS0d9//03Tp0/nnrdo0YIaNGjAPRo1akSPHz+WOVYXlYwqVapEmZmZUtvT09NVipt/+vQp/fjjj9SpUyfq2LEjff/995/Ud5bRDba4ZxhGZceOHSMjIyNq0qQJt5hr0qQJGRsb0/HjxxWOlZXwqUqFh5JevXpF//33H/dQtYtleno6RUREkL29PdnY2NB3332nNKFWm3jyxo0b065du6S279mzh5o0aSK1fe7cuWRqakqBgYFka2tLI0eOpMqVK9OCBQto4cKFVLVqVRo5cqTCY2pT3Udc8aa0NWvWkLu7u8LjamvVqlVkbGxMVatWlXmCoYi63Y61qUYkJj4RsbGxoapVq9L3339Pd+/epeTkZAoICKDGjRur9RnKizqlGjt37kze3t508eJFLtfj4sWL5OPjQ126dJHav2R1meDgYLK0tCRnZ2duQV+tWjWytLRUWn1G0yTT/Px8CgkJIYFAwOWqGBgYUGhoKL1580bFn5BqfvjhBxo9ejT33NzcnCIiImjmzJk0c+ZMatq0KUVGRip9H00rGdnY2MgsA5ucnEw2NjbqfyDms8QW9wzDqMzHx4eioqKktkdFRSmtliOmTsLn5cuXKSgoiHtubm4uUUddIBBQSkqKyvMvLCykmJgYMjY2Jj6fT97e3hQbGyszWVWbykBmZmYySzvevXtXZlk/d3d32rp1KxF9XETx+XyJk4MjR45QtWrVVP6c6lq1ahUZGRnRyJEjKSEhgTZv3kwjRowgY2NjmYv+ktS5kzNhwgSZD2dnZ+ratavENkXOnj1LwcHBZG5uTvXq1VO58pI21Yi07XugT+qWavz333+pY8eO3B0J8R2kjh07clVm5FG35rwukkzDw8PJzc2Njhw5wp34Hz58mGrUqKH0pFhd9evXl7iQUbqM67Fjx9QqK6lKJaOSBg8eTHXq1KHz58+TSCQikUhE586do7p161JwcLDMMaoUCLh27ZrWBQuYTwdb3DMMo7LyDmsIDQ2VqH5ibm5OW7ZsodOnT9OpU6do8ODBNGjQIKXHKiwspB07dlCHDh24K7xxcXE0d+5cqly5MvXv319qjDaVgWxtbemvv/6S2v7nn3/KLI1nZGREDx8+lHhesm7348ePydDQUGqcttV9Stq7dy+1aNGCbG1tydbWllq0aKG0YZG6d3JatWql0qN169YyjxcdHU2enp7k5OREkyZN4sr6qboQ1KYakT76HmhD21KNRB9/rw8cOED79+9XOVxK3ZrzQqGQWrZsSWvXrqXc3FxuuzqLe6FQSKdOnZLafvLkSZVDelRlZWUlsZj/9ttv6dmzZ9zze/fuyQxdUoW8SkYlvXz5krp27Sp14tW9e3fKy8uTOaZ04zlFzdgaNGigdk8R5tPDFvcMw6isvMMaPD09Jcoxlr5Kdv78eYVXtFNTU2nMmDEkFArJwcGBIiMjKSsrS2KflJQUuWE2msaT9+3bl7755huJf2xfvnxJ33zzDfXu3Vtqfx6PJ3FFtPTnfPbsmczSnbroFvvhwweaOXOmxMmFqnRxJ0cduux2/OrVq3LrGqsPmpak1Ja6Neetra3J39+f1q1bJ9E5W53/p6ampjJD6K5evUqVKlVSffIqMDMzk9lsSywtLU1p7HtwcDCdOXNGq3ncvn2bfv31Vzpw4IDScLaSjefkPe7evUvnzp2jHj160Ndff63V3Bj9Y4t7hmFUVt5hDZUqVaL79+9zz5csWSKxAHjw4IHCOwZ8Pp/at2+vMIkwPz9f5U6Uqnr8+DG5ubmRlZUVdzXa2tqaPD09ZS6ieTwenTp1irvKbmZmRocPH+aenzhxQuYCXVfdYs3MzOjevXtqf05N7+Ro2nVY227Hpb1//16lvI2S37nDhw/TgQMHuMehQ4fUPm55SEhI0DhxvaioiDZs2ED9+/enwMBAat26tcRDEXVrzusiyTQgIIB69+4t8XkLCgqod+/eFBgYqN6HV8LX15dWrlwp9/Vly5YpPbHt0aMHGRsbk7u7O82bN09uAq4+3L59W+cnREz5Y4t7hmFUVt5hDTY2NgpjqZUlkZU8MdCEppWBiD6eNKxdu5ZGjx5NkZGRtGnTJrknGIpum5fcrog21X26detG8fHxKn2ukrS5k6NN12FNuh1rWo3o4MGD5OPjwz03NzeX+v8jK3m6Ivvuu+/IzMyM+vTpQ+PGjaPx48dLPBQpLi6m6OhocnR05H5Gjo6OFB0drTRZVNMk0ytXrpCTkxMJhUIKCAigwMBAEgqF5OTkRFevXlX78yuycOFCsrW1lRnqlp6eTra2trRw4UKl76NJJaNbt27R7t27uW7Jhw4dopYtW1KjRo1o7ty5KjW6e/nyJf3yyy8UFhZGw4YNo8WLF0vcYSwqKtKqGzjzaWB17hmG0Yi2TZZUERgYCF9fXyxatEjm65GRkUhPT8eJEydkvu7m5oaLFy9CKBRKbM/Ly4Ovr6/cBjWAdg2P1FWyvn5xcbFUQx2RSASBQKCwVr+pqSnS0tJQu3Ztie1ZWVnw9fXF27dv5Y5du3YtZs6ciYEDB6Jhw4ZSTcK6du0qc9zs2bOxdOlSTJ06FX5+fuDxeEhOTkZ0dDQiIyPxww8/yD1mfHw8du3ahcTERKVNiuR5/fo1tmzZgvj4eKSmpqJJkybo1asXJk6cKLHfvHnzMG/ePPj5+eHy5cvo06cP9u/fj/Hjx4PP52P58uXo3LkzVq9eLXWMrl27olu3bggLCwPw8fuekZEBNzc3AMDChQtx+vRpHDlyRKPPoEs9evRQed+9e/fKfc3Ozg4JCQkICgrSaj6q1pwvTSQSISkpCbGxsTh48CAsLCzw4sULhWPevn0r1Vxv4MCBMDU11Xj+snz48AFt2rTBX3/9hbZt28LT0xM8Hg83btzAb7/9hubNm+PEiRMK+3aUdvnyZcTFxWHDhg0wNzfHoEGDMHr0aHh4eHD77Nu3D3369OEa7a1btw7h4eFo3bo1BAIBkpKSMHfuXERFRck9zqVLl9C+fXuYmpqiSZMmICJcunQJb9++xfHjx6Wa+jEVmF5PLRiGqdCUhTVom/C5e/duMjAwoJUrV0qE8BQVFdHy5cvJ0NBQ4VXT0rHsYs+ePSMjIyOFn02bePKff/6ZYmNjpbbHxsbSggUL5I7j8/ky5/vixQuFcfNE2lX3UZZkJ482d3J8fHzI3NycjI2NqWbNmhK1wjWJ18/MzKRx48aRvb291GvaVCOqXr0615uASDofIjMzU+Yx9UFXJSmrVKmicb8BMU1qzst7H2VJpuXt/fv3NH/+fKpfvz6ZmpqSqakpeXt70/z581XuoyGmaiWjhg0b0vTp00kkElFcXByZmprS0qVLudfXrl1LtWrVUnisr7/+moYOHUofPnzgtn348IGCg4OpZcuWas2b+bSxK/cMw6gkPj4eaWlpaNasGQYOHIhp06ZhyZIlKCoqQkBAALZv3y51hVx8lUn8Z4bH48l9/+LiYpnbo6KisGjRIlhYWMDNzQ08Hg937txBfn4+Jk6cKPOq/q+//goA6N69OzZt2gQrKyuJ45w4cQK//fYbbt68KXc+JiYmuHLlisTVMwC4desWvL298e7dO7ljXVxcsHXrVvj5+Ulsv3DhAvr16ye3wyefz8c///wj1en0wYMH8PLywps3b+QeU5tusbqg7p0cTbsOA+p3OzY2NkZ2djacnZ2555mZmfD09AQAPHnyBK6urigsLJR6PxMTE2RlZXHHu3TpEurXr88d4969e6hVqxbev3+v8POUt6ioKOTm5mLNmjXcnaDi4mKMHj0alpaWcu+GAcDixYtx9+5drFy5UuHvrCxv3rzB2LFjkZCQAJFIBAAQCAQYMmQIVqxYgUqVKskcN3ToUISGhnLditWRk5PD/e159OgR1q9fj7dv36JLly4avV9Z+/DhA3799VfEx8fj+PHj8Pb2xrBhwzBw4EDu92f79u0YNWoUXr58CeDj71V6ejpq1KgBkUgEIyMjpKeno27dugCA+/fvw8vLCwUFBXKPa2pqisuXL0t1f75+/ToaNWqkcCxTwej55IJhmApA0yZLukr4PH/+PI0dO5Y6duxIHTt2pIiICDp37hyJRCJ68OCB1P6y4tXFDyMjI6pZsyYdPHhQ4TG1iSc3Njbm4mJLunPnjsxEU3Ftdz6fTyNGjJCo9x4REUFNmzYlPz8/hcck0ry6j6y5akLVBFVtqdvtWNNqREQfr2L/9ttvct87KSmJKleurMbsy4e6JSlL6t69O1lZWZGrqyt17txZrS6zmtac1yTJNDMzk6pXr058Pp88PT3p8uXL9NVXX5G5uTlZWlqSQCBQ+rdFU9pUvNGkkpE232ExBwcHSkpKktp+7NgxhZ2dmYqHLe4ZhlFKF02WtEn41DRcxcXFReOQAG0qA7m7u9PmzZultickJJCrq6vUdnFFHR6PR35+fhI139u1a0fh4eFyu4nqgrqLZSLNE1RLevnyJa1fv56mTp3KNdBJTU1VurBTt9uxptWIiD6WNZXVlVWsU6dO1KdPH6WftbypW5KypJLhPbIeimhTc17dJNMOHTpQ586d6ezZszRixAhycnKikJAQKi4upuLiYho9ejQ1bdpU4TE1pU3FG00qGfH5fIlGfxYWFhIn5aos7seOHUtVq1al7du308OHD+nRo0e0bds2qlq1Ko0bN06t+TCfNra4ZxhGKU2bLJVkYmIisxb19evX5daZF+PxeDI72N6/f7/MyrZpE0++YMECEgqFFBcXx925iI2NJaFQKNGUq7ShQ4dKlF1Ul6bVfWQtlhU16tL0Tk5JGRkZZG9vT+7u7mRgYMBdhfzhhx9o8ODBKn1eVbsda1ONKC0tjYyNjalXr16UkpJCeXl5lJeXRxcuXOAWeKmpqSrNtzypW5JSV3RVcz4tLY3GjBlDJiYmZGdnR+PHj5c6wRUKhVy+zuvXr4nH40nkR2RlZZGVlZVmH0QFsk5Gdu3apbDijaZ4PB5ZW1uTjY0N2djYEI/HIysrK+65tbW10sX9+/fvKSIigjsJ5/P5ZGxsTOPHj1c7V4D5tLGYe4ZhlOLz+Xj27BkcHBwASFcM+eeff+Do6Cg3bh4AfH19Ubt2bcTGxsLExAQA8P79e4SGhiIrKwtpaWlSY8RVT5YtW4bhw4dLxOsWFxfjwoULEAgE+PPPP7nty5cvR3h4OExMTLB8+XKFnysiIkKlz69uPDkRYerUqVi+fDkXx21iYoKoqCjMmDFD7ThmVeiiuk9RUREOHjyIjRs34ujRo/Dw8EBYWBgGDx4skQfg4eGB2bNno3///rh06RKaNm2KHTt2oFevXgCAo0ePYuTIkRJVgEpr06YNfH19sXDhQonv019//YUBAwbg/v37Kn/29+/fY9WqVZg2bRoKCwthaGiIvn37Ijo6GlWqVNG6GtGBAwcwbNgw5ObmSmy3sbHBhg0b0L17d5XnWl5EIhF++eUXLFu2DE+fPgUAVKlSBePGjUNkZKTUz0BXAgMDIRQKkZCQwP2ev337FsHBwcjNzcXvv/+u9D2ePn2KhIQExMXF4cmTJ+jZsyeePn2KU6dOYeHChZgwYQIA3fxd0hVlFW+0rWS0adMmlcYGBwfL3F5cXIzk5GTUq1cPJiYmuHPnDogI7u7ucvMgmIqLLe4ZhlGKz+fj5MmTXMlCPz8/7Ny5E1WrVgUAvHjxAm3btlX4j6gmCZ+tW7cGAJw5cwbNmzeHkZER95qRkRFcXFwwadIkiaRXV1dXXLp0CUKhUG7SJfAxuVdRKczSCgsLUVhYCHNzc5XH5OfnIysrC6ampvDw8ICxsTGKiopgYGCg8nuoqkGDBmjfvj0WLFggsX3q1Kk4fvy4zJMneZQtlrVJUBWzsrJCWloaatSoIbEoe/DgATw9PRUmLItdunQJcXFx2L59O8zMzBAcHIywsDD8/fff+PHHH/H69WukpKRw+wsEAjx9+pRbDIrl5OTAwcFB4fe3oKAASUlJuH37NoCPJzjt2rWTKhv6KdKkJOXu3buxc+dOPHz4UOr/o6Lv0tWrV9GhQwe8e/cO9evXB4/HQ3p6OkxMTJCUlIQ6derIHKdJkmnpBHQLCwtkZmZyv/fltbhX5WQkJCSE25+IsG/fPlhZWaFRo0YAgNTUVOTl5aFHjx6Ij48vk3mWTg5nPmP6u2nAMExFoYsmS0SaJ3xqG66iLl3Ek5d27do1mjhxYpklrmnaLbakixcv0qhRo8jGxoaqVq1K33//Pd29e5eSk5MpICCAGjduTES6S+5LS0uTGp+UlERVq1ZVOFaTbsfieWsa3qWrpOPypklJymXLlpG5uTl99913ZGRkRCNGjKA2bdqQlZUVTZ8+Xen4goICWrduHU2cOJEmTJhA69evp4KCAoVjNE0yDQoK4hJ9DQwMqF27dtzzoKAgpd9DTRUWFtLu3bupU6dOZGhoSA0bNqTVq1fTq1evuH22bdsmM79hypQpNGzYMInmXEVFRRQeHk6TJk1SeFxtEnkbNWpEv//+u0ZjmYqFXblnGEYpXTRZ0oczZ87gm2++UWuMNg2PSsvPz8f27dsRGxuLixcvolmzZujZsycXVqBLzs7OWLJkCXr37i2xfefOnZg0aRIePnwod+ySJUsQHx+PmzdvIigoCMOGDUNQUBD4fD63T3Z2NmrVqoWioiKd3MkJDw/H8+fPsXPnTtja2iIzMxMCgQDdu3eHv78/YmJi5I718PBAaGgoQkJCULlyZZn7FBYWYtu2bQgODtYovKs0gUAAf39/hIWFoVevXlzIyadK05KUAFCrVi389NNP6N+/v8RdlR9//BG5ublYuXKlzue7efNm9O7dW+Wfa2ZmJhYtWqTSXbCyuBJuZ2cHkUiE/v37Y/jw4fDx8ZHa5+XLl/D19ZUqfWtvb4/k5GTuTpfYzZs34efnh5ycHLnH7dmzJw4fPgxnZ2eEhIQgODgYTk5OKs35+PHjiIqKwpw5c2Q2q1O32RjzCdP32QXDMBWHNk2WiDRP+NSUoaEhOTs7U1RUFGVmZqo0RheVgc6ePUvBwcFkbm5O9erVI4FAQMnJyZp/EBVoW93n559/pqdPn8rd5/3797Rx40Yi0s2dnP/++49atGhB1tbWJBAIyNnZmQwNDcnf31+luznq0EU1InWTjvVN05KURB+TYu/fv09ERPb29pSenk5ERLdu3VJaRrPkXa2HDx/SjBkzaNKkSRpfbZan5N8iV1dXje6maUOTijdi2lQyItI8kbf076n4oaxZHVPxsCv3DMOoTJsmS7pI+FTXixcvsH37dmzbtg3nzp1D3bp1MWjQIAwYMIC7ylyaNvHkCxcuRFxcHPLz89G/f38MGjSIa3iUkZEBLy8vnX9GMSJCTEwMFi9ejL///hsA4OjoiMmTJyMiIkKnSby6vJNz8uRJpKWlQSQSwdfXF23atJG5X2Zmpsrz8/b2lrk9JCQEy5Yt0+oKpapJx/pmZ2eH3bt3o1WrVhLbT506hT59+uD58+dyx7q5uWH37t3w9fVF48aNMWzYMIwYMQLHjx9Hv379pBKLAeDKlSvo0qULHj16BA8PD2zfvh0dOnTAmzdvwOfz8ebNG+zevVsi+VibJFOhUIgjR46gadOmcv8ufaomTpyIjRs3Yvr06WjWrBkA4Pz581iwYAGGDBmCJUuWqPxeyhJ5Szp9+rTCvwPq3uVkPl1scc8wjFK6CGvQZcKnJu7du4etW7di27ZtuHHjBvz9/XHy5Emp/bSpwGFgYICoqCjMnj1bYsFbHov7ktSp7vPq1StusXvkyBEUFRVxrwkEAnTq1EnuWG0SVNWli27HuqQs6VjfKlWqhNTUVNSuXVti+7Vr19CkSROFJ+LDhg2Ds7MzfvrpJ6xZswYTJ05EixYtcOnSJfTo0QOxsbFSYzp27Mh9/xMTE3Ho0CG0a9cOGzZsAACMHTsWqampOH/+PDdGmyTT8PBwbNq0CY6Ojnj48CGqVq0qtwKQOonzimhb8UZMV5WMVK0qxHx52OKeYRilNKlaU5qJiQmuXLkitc+tW7fg7e2tUnUUbRUXF+Po0aOYMWMGMjMzZS4CtYkn//nnn7Fx40a8e/cO/fv3x+DBg1G3bt1yX9wDqlX3OXToEGbMmIHLly8D+HgyUHLRx+PxJEpclqbJnRxl5UmBjydJlStXxtdff82dOJS8W3D58mVMmjQJkydPRvPmzQEA586dw+LFi7Fw4cIyLU2pboUefdGmJKVIJIJIJOLi2Xfu3Ink5GS4u7tj5MiREr//YnZ2djh58iS8vb2Rn58PS0tLpKSkcAv1GzduoFmzZsjLy5N5zKioKOTm5mLNmjXc4ra4uBijR4+GpaUlFi1aJDXm2LFjyM7ORkREBGbPni33ZHbcuHHyf1BqKIuKN+pWMtKkqpCYq6srQkJCMHTo0E8uP4rRMT2FAzEMUwFpU7WmatWqtHPnTqntO3bsIGdnZ22nplBycjKNGjWK7O3tycLCggYOHEhHjhyRua8u4slPnz5NQ4YMITMzM/L29i7zmHtNq/t06dKFNmzYwD0vXfUmOjqaOnbsKDVuwoQJNGHCBOLz+TRixAju+YQJEygiIoKaNm1Kfn5+Mo/p4uKi9FGtWjUyMzMjU1NT2rNnj9R7aNPtWFOaVujRlytXrpCTkxMJhUIKCAigwMBAEgqF5OTkRFevXtX58bStoGRnZyfRGE/sxo0bSuP8hw4dKlGlpjxoU/FGTJNKRppUFRJbvnw5+fr6kkAgoDZt2tC2bdtY86rPFFvcMwxTLrRJ+NTUtGnTyMXFhYyMjCgoKIi2bNlCb968UThG3FH2/v37dOfOHYnn9+/fp7t379KDBw9UOv6rV69o9erV1KRJExIIBNS8eXNavHixLj4aR5tusdWrV5fo6Fl6QZaZmUn29vZS43SRoKpMcXExzZs3j2rVqiX1mjbdjjWlbtLxp0CTkpRiubm5tGjRIgoNDaWwsDD65ZdfKCcnR+7+pcuMmpubS5QPVba41zbJtLxpczKSn59PISEhJBAIuIsFBgYGFBoaqvTvkzaJvGLp6ekUERFB9vb2ZGNjQ999990n2WWZ0Rxb3DMMUy5EIhEtWbKEnJycuH/QnJycKCYmhkQiUZkcs3nz5rRy5UqVr4qVpG1loNIyMzNp3LhxMhfL2tCmuo+xsbHEAuzixYsSFTfu3r1LRkZGco9d1v0HHj9+THZ2dlLbGzRoQAMGDJBY5Lx7944GDBhADRo0KLP5fClOnz5NVlZW5OzszNWMr1atGllaWtLp06dljtG25vyECRPIxsaGFi1aRGfPnqWzZ8/SokWLSCgU0oQJE8rqo2pMm5MRbSoZ6VJhYSHFxMSQsbEx8fl88vb2ptjY2DL7e8yUHxZzzzBMuVMn4VNftKkMdO/ePbldID98+ABDQ0OdzVOb6j6Ojo5ISEiQW6Hm+PHjCA4O5pL+dO3MmTP45ZdfkJWVBR6Ph9q1a2Py5Mlo2bKlwnGadDvWhC4q9OhLTk4OhEIhAODRo0dYv3493r59iy5dusDf31/h2Lp168LPzw+rV6+Win//888/cfXqVYn9dVFzXldJpuVFm4o36lYy0lUir9iHDx+wb98+xMfH47fffkOzZs24vJGVK1eidevW2Lp1q8rHZD49bHHPMIxeqJLwqSvXr1/Hw4cPpRa4Xbt2ldq3ojU80qa6T79+/VBQUIBff/1V5nt37twZZmZm2LFjh87nnZiYiJCQEPTo0UOiNOq+ffuwceNGDBgwQOH4goICJCYm4saNGyAieHl5YcCAAVKNebTxqVXoUYUmJSlLMzU1RXp6uswmSz4+Pnj79q3E9pJVk9zc3HDx4kXuxEIT6iaZ6oM2JyPqVjLSVSJvWloa4uPjsW3bNggEAgwePBjDhg1DrVq1uH0uXrwIf39/qf/HTAWjv5sGDMN8KTRN+NTWnTt3yNvbWyoZVty8RZayanh0/vz5sviIxOPx6NSpU5SRkUEZGRlkZmZGhw8f5p6fOHFC7mdNS0sjY2Nj6tWrF6WkpFBeXh7l5eXRhQsXqEePHmRsbFxmsbi1atWiJUuWSG1fvHixzDh7fSiZa7Fv3z6qUaMGrVmzhvvZrlmzhjw8PGSGZ+hLhw4dqHPnznT27FkaMWIEOTk5UUhICBUXF1NxcTGNHj2amjZtqvA9/Pz85IacNGvWTGq7ra0t9/0uHXuvLk2STPVNHFqjqoCAAOrdu7dEWFlBQQH17t2bAgMDFY7VJpGXz+dT+/btaefOnXIbXuXn59PQoUNV/izMp4kt7hmGKVPaJHxqq3PnztStWzf6999/ydzcnK5fv05nz56lJk2a0B9//KFwrC7iyT98+EB79+6lrl27kqGhIXl5edHixYu1WvyUpm11n/3795OdnZ1Ex0o+n09CobBMF61GRkZ0+/Ztqe23b98mY2NjpePLu9uxPir0aEIoFFJGRgYREb1+/Zp4PJ5E0nRWVhZZWVlJjROfsGRkZND27dupWrVqUvHvLi4utH37dqmxw4cPJyMjI3JxcSE+n0/VqlUjV1dXmQ95tEky1SdNTka0qWSkTSKvuOsw8/ljYTkMw5QpDw8PzJ49G/3798elS5fQtGlTidrpR48exciRIyXqmOtKydrbVlZWSElJgaenJ06ePInIyEiuvntZK8uGR7roFltQUICkpCTcvn0bwMf/Z+3atdNpiEtp7u7umDx5MkaMGCGxfe3atfjll1+4uciij27HpqamSEtLkwqlyMrKgq+v7ycTxqBpmFbpECR5eDyezBAkbWvOjxgxAr///jtWrlyJFi1aAACSk5MRERGBtm3bYvXq1Yo/eDl78+YNxo4di4SEBIhEIgAfw5OGDBmCFStWSITzyfL27VupsLKBAwfC1NRU4TgbGxvEx8dLhVXt378fISEhUrXtZXn9+rXE/2c+n18u4ZFMOdLnmQXDMJ8/IyMjevjwocTzkleeHj9+TIaGhmVybGtra660o5ubG508eZKIPl71NTU1LZNjlnTx4kUaNWoU2djYUNWqVen777+nu3fvUnJyMgUEBFDjxo11dixtqvuUrJhTXlatWkVGRkY0cuRISkhIoM2bN9OIESPI2NiY1qxZo3Csj48PRUVFSW2Piooqs2o5FaVCj6YlKUuXfFX0UETTmvNCoZBOnToltf3kyZMyKybpm74q3mhSVejy5csUFBTEPTc3N5e4SycQCCglJaXM5syUP7a4ZximTGnb3EYbX3/9NRda0r9/f+rQoQMlJyfTkCFDqE6dOmVyTCL9NDySF+t8//59qlSpksKxfD6fWrVqRZs3b9a6hrY69u7dSy1atCBbW1uytbWlFi1a0P79+5WOMzY2lpn3cPPmTZVCejRx4cIFcnBwIDs7OwoMDKTAwECys7Mje3t7unDhQpkcUxPalqTUF1NTU5m9C65evar0+6sP2pyMlMwxevjwIc2YMYMmTZpEZ86cUXrc4uJiio6OJkdHRy58ydHRkaKjoyXi8EsKDQ2ln3/+mXtubm5OW7ZsodOnT9OpU6do8ODBNGjQIKXHZioO5XWrGIZhtHT9+nU8e/YMwMdqDzdu3EB+fj4A4MWLF2V23B9++IGrPDF37lx07twZLVu2hFAoLJMKMGKrV69GaGgoQkJCULlyZZn7VKtWDbGxsVofS1zdh8fjYcaMGTKr+/j4+Ch8j4yMDMTFxSEyMhJjxoxB3759ERYWprOSkqUVFRVh3rx5CA0NRXJystrj7e3tkZ6eDg8PD4nt6enpXDiKrjVp0gT37t2TCKXo27evziv0aCMzMxMDBw6UKEk5aNAgqf2GDBmi8ntaWloiPT2dC+spK82bN8dPP/2EhIQErrrU27dvMWvWLDRv3rxMj62JgoICfPXVV1LbHRwcUFBQIHOMskpGS5cuVVrJiM/nY8qUKZgyZYrKVYX+/PNPDB06VGJbs2bNuP+npqam6NOnj8L3YCoWFnPPMEyZUhTLW3K7OG61rOXm5sLGxkZhWcOKpHXr1gA+1oxv3rw5jIyMuNeMjIzg4uKCSZMmSS2EZSkqKsLBgwexceNGHD16FB4eHggLC8PgwYOl6v1ry9zcHFevXoWLi4vaY2fPno2lS5di6tSp8PPzA4/HQ3JyMqKjoxEZGYkffvhBp3OtKHRdkhKQjtkvK1evXkWHDh3w7t071K9fHzweD+np6TAxMUFSUhLq1KlTpsdXV2BgIIRCodTJSHBwMHJzc/H7779LjenYsSMMDAwQFRWFxMREHDp0CO3atcOGDRsAAGPHjkVqairOnz+v9PjPnz/HzZs3wePx4OnpCTs7O7n7mpmZ4fr166hevToAYOnSpQgLC+NOCh4+fIiaNWvi3bt3av8cmE8TW9wzDFOmdJHwqYmioiKYmJggPT0ddevW1el7y6LvhkchISFYtmyZTmqDl2UCsFj37t3RvXt3qSuKqiAixMTEYPHixfj7778BfGzINXnyZERERJTZidudO3cQExMj0XRr3LhxqFGjRpkcT11CoRBHjhxB06ZN5TZhU1d5Le4BzZNM9UGTk5GSCf75+fmwtLRESkoKV6/+xo0baNasGfLy8uQeV5NEXltbWxw8eJBLVC7tzz//RJcuXZCbm6vBT4L5FLHFPcMw5aLkVcWScnJy4ODgUCZNgGrUqIG9e/dyXUzLUkVseFTapUuXEBcXh+3bt8PMzAzBwcFc58off/wRr1+/RkpKik6OtXbtWsycORMDBw5Ew4YNpUJbZDUYk6W8uh3ro0KPusLDw7Fp0yY4Ojri4cOHqFq1qtxmSnfv3lXpPUeNGoU5c+YovDL8pVL3ZESbhnNimlQVCgwMhK+vLxYtWiTzPSMjI5Geno4TJ06o9fmZTxdb3DMMUy7kXUl88OABvLy8pLoy6kJ8fDx27dqFxMRE2Nra6vz9Syp5h+Ly5cuYNGkSJk+ezMULnzt3DosXL8bChQsVxtTqw5IlSxAfH4+bN28iKCgIw4YNQ1BQEPh8PrdPdnY2atWqhaKiIp0cs+R7lyav3KI85dHtuEGDBmjfvj0WLFggsX3q1Kk4fvw40tLSyuzY6tC2JKW+5OTkcCFEjx49wvr16/H27Vt06dIF/v7+ep6dbpT+G2hhYYHMzEy4uroCUG1xb2dnh927d6NVq1YS20+dOoU+ffrg+fPnUmP27NmDfv36ISYmBqNGjeJ+94qLi7Fq1SpERkZi69atXHlipuJji3uGYcqUOOFz2bJlGD58uMyET4FAgD///FPnx27QoAGys7Px4cMHVK9eXerqcFktyJo0aYKZM2ciKChIYvuRI0cwY8YMpKamlslxNeXh4aE0AbiwsBDbtm1DcHBwOc9OUnx8PNLS0tCsWTMMHDgQ06ZNw5IlS1BUVISAgABs375d6zhzWUxMTHDlyhWp3IVbt27B29v7k4tXDgkJwfLlyzW6oxEREQF3d3dERERIbF+5ciWys7MRExOjo1kqTzJ98+aN0iRTfdDkZITP56Njx44wNjYGABw8eBABAQHc36X379/j2LFjChf3lSpVQmpqqlS/hWvXrqFJkyZyL5JERUVh0aJFsLCwgJubG3g8Hu7cuYP8/HxMnDhR7lV9pmJii3uGYcqULhM+1TVr1iyFr//00086PyZQcRoe6dO9e/e4K5aqmjdvHubNmwc/Pz9cvnwZffr0wf79+zF+/Hjw+XwsX74cnTt3LpOGR87OzliyZAl69+4tsX3nzp2YNGkSHj58qPNj6ouTkxN+/fVXNGzYUGJ7WloaunbtisePH+vsWLpMMi0Pmp6MZGZmYtGiRRKVjOSJj4+X+5omibxi58+fx7Zt2ySa1fXv3x/NmjVT4ZMzFUq5Ft5kGOaLNXToUPrvv//0PY1yUREaHmVkZKj8KAua1NZ3d3enrVu3EtHHBmF8Pp927drFvX7kyBGqVq1amcx31qxZZG1tTQsWLKA//viDzp49S/Pnzydra2uaM2dOmRxTX4yNjen27dtS22/fvq3zPgJCoZD7jr1+/Zp4PB5dvHiRez0rK4usrKx0ekxtdOjQgTp37kxnz56lESNGkJOTE4WEhFBxcTEVFxfT6NGjqWnTplLjSjaZc3V1lah1r44rV66Qk5MTCYVCCggIoMDAQBIKheTk5ERXr17V6rMxnw925Z5hmM9eebdbT0lJQZcuXSASibhk3oyMDPB4PBw6dKjM6serQ98JwFevXkVcXBy2bNmC9+/fq1Rb39jYGNnZ2XB2duaeZ2ZmwtPTEwDw5MkTuLq6orCwUOfzJT1V6NGHunXrYuTIkRgzZozE9hUrVmD16tW4fv26zo6liyTT8qRpxRtdVjLStKqQi4sLF34n/h1iPk9scc8wzGcnPT0d33//PQ4fPgzg44KhZGMZHo+Hc+fOoXHjxmU2h4KCAql/gD+lhkefSgKwOrX1P5WFYHlV6NGXuLg4jBkzBpMnT0ZAQAAA4MSJE1i8eDFiYmIwfPhwnR1LF0mm5UnT72BZVDJS14oVK7Bx40ZkZGSgdevWCAsLw7fffsvlADCfD7a4ZxjmsxMWFgZ3d3dMmzYNwMd/gNeuXQsnJycQEeLi4kBE2Lx5s55n+mn4FBKAVamtz+fzcfLkSa7ykZ+fH3bu3ImqVasC+NjtuG3btuWyECyPCj36tHr1asybN4+7S+Hi4oKZM2eq1d1WFbpIMi1P2pyM6KKSkS6qCok7Um/btg1FRUUYMGAAQkND4evrq9J45tPHFvcMw3x2atWqhfXr16Nly5YApK+uXbhwAX369JG4eq1rn3rDo5L0mQCsTm19fXU71leFnk/B8+fPYWpqWiYnMbpKMi1PujgZ0aSSUVlUFfrw4QNWrVqFqKgofPjwAXXr1sW4ceMQEhLyWYWZfYnY4p5hmM+OvtutV4SGRyX5+vqidu3aiI2N5SpwvH//HqGhocjKyiqTkqGa1NbXR7djfVbo0Zd79+6hqKhIqoLV7du3YWhoCBcXF50cp2RjOzc3N1y8ePGTPknS58mILqsKffjwAfv27UN8fDx+++03NGvWjDuhXrlyJVq3bo2tW7fqdP5MOSvf/F2GYZiyZ2NjQ8nJyXJfT05OJhsbmzI7vo+PD0VFRUltj4qK+mSq5ZR04cIFcnBwIDs7OwoMDKTAwECys7Mje3t7unDhQpkc093dnX7++Wd6+vSp3H3ev39PGzdulNpesvJISS9evCA+n6/zeeqrQo+++Pv7y/y5b968mb755hudHcfW1pbOnz9PREQ8Ho/+/fdfnb13WdBVxRtN6KKqUGpqKo0ZM4aEQiE5ODhQZGQkZWVlSeyTkpJCJiYmOp8/U77YlXuGYT47+m63XtEaHgGffgJwSeXZ7VifFXr0xdLSEmlpaXB3d5fYnp2djUaNGklVgtHUp5Bkqg5dVrxRly6SyQUCAdq2bYuwsDB0794dhoaGUvu8efMGY8aM+WTCoBjNKL+3xDAMU8GMHj0a/fr1g4uLi8x26ytWrCjT28729vZIT0+XWtynp6dz/zh/aipVqoTw8PByOdarV6+4EKkjR45wYTfAxwVIp06dZI4Tdzvm8XiYMWOGzG7HPj4+Op3rhw8fJKqJGBkZSSyKDAwMPplkT13h8XhcRaCS/vvvP51+1nXr1qFHjx5ckunw4cM/6QpEPXv2hL+/PxwdHcHj8dCoUaNyPRkpHQevblz83bt3uVBFeczMzNjC/jPAFvcMw3x2evbsiYkTJ2Ls2LGYPn26zHbrvXr1KrPjDx8+HOHh4bh79y78/PzA4/GQnJyM6OhoREZGltlxtVFeCcCHDh3CjBkzcPnyZQBA3759Ja6083g87NixQ+b/H/EYIsKVK1ekuh3Xr18fkyZN0ul8AeD69et49uwZd+wbN24gPz8fwMcKPZ+bli1bYv78+di2bRu3eC0uLsb8+fPx9ddf6/RYHTp0AACkpqZi3Lhxn/TiXt8nI0OHDuVONN+9e4eRI0dKJPIqo2xhz3w+WFgOwzCfrQsXLmDLli3Izs4G8P/t1ps2bYpHjx7pNPGyJKpgDY/KMwG4a9eu6NatG8LCwgBIhxcsXLgQp0+fxpEjR+S+R0hICJYtW8Zd/S9L+qrQo0/Xr1+Hv78/rK2tuYpTZ8+exatXr3Dy5EnUrVtXzzPUP00q3mhKm0ReGxsblf/e5ObmajQ/5tPDFvcMw3y2SlbjKCknJwcODg7lEk5RERoeNWjQAO3bt8eCBQsktk+dOhXHjx/XabUcFxcX7N69m+voWXpxf+XKFQQGBuLff//V2TG1oY8KPZ8CceWUjIwMmJqawtvbG2PGjOF6DDDlR5uqQps2beL+OycnB3PnzkX79u0lmtUlJSVhxowZmDBhQpnMnyl/bHHPMMxnqzwTLxX51BselWcCsImJCbKysrimP5cuXUL9+vW5OPZ79+6hVq1aKoUZlKdP4URR33JycrB582aMHz9e31P5ougqkbdnz55o3bo1xowZI7F95cqV+P3337F//34dzZjRNxZzzzDMZ0cfiZdiFbHhUXkmANva2uLOnTvc4l58BV/s9u3bn+TVYSKSGd6Qn5/P9Qb4HBERjh8/jtjYWBw4cACWlpZscV/OdJXIm5SUhOjoaKnt7du3x9SpU3U2X0b/2OKeYZjPjr4SL0s2PNq6dSuSk5Oxf/9+zJ49m2t49MMPP3xyDY/KMwHY398fy5cvR5s2bWS+vnz5cvj7++v0mNrQ54miPt2/fx9xcXHYuHEjnjx5ggEDBuDw4cNo3bq1vqf2xdFVIq9QKMS+ffswefJkie379+//5C44MFoq78L6DMMw5WXo0KH033//ldvxKmrDI5FIREuWLCEnJyfi8XjE4/HIycmJYmJiSCQS6fRYaWlpZGxsTL169aKUlBTKy8ujvLw8unDhAvXo0YOMjY0pNTVVp8fURqtWrahVq1bE4/HIz8+Pe96qVStq164dhYeH061bt/Q9TZ149+4dbd26lQICAsjExIS+/fZb2rVrFxkYGNC1a9f0PT2GPv5Ne/XqlUZj4+Pjic/nU1BQEM2ZM4fmzJlDnTp1IoFAQPHx8bqdKKNXLOaeYRhGRz6HhkflkQB84MABDBs2TKo6h42NDTZs2IDu3buX2bE1VZ4VevTFzs4OXl5eGDRoEHr37g0bGxsAgKGhITIyMuDl5aXnGTLaunDhApYvX46srCyuWV1ERASaNm2q76kxOsTCchiGYXTkc2h4ZGFhgcLCQuTn55dZAnC3bt3Qtm1bJCUl4fbt2wA+lilt167dJ9kRF5AuMfg5Ki4uBo/HA4/HkxvTzVRsTZs2xZYtW/Q9DaaMscU9wzCMDlW0hkf6SgD+559/8O233+r8fRnNPX36FHv27EFsbCzGjRuHjh07YtCgQZ9cXwZGc8XFxdi/fz/XrM7Lywtdu3ZlJ3OfGRaWwzAMoyMVreFRyQTgy5cvo0+fPti/fz/Gjx/PJQB37ty5TBKABQIB/P39ERYWhl69en3WFWcqojt37iA+Ph6bNm3CkydP0L9/fwwdOhQBAQFsIVhBZWdnIygoCE+ePIGnpyeICLdu3YKzszMOHz6s827UjP6wxT3DMIyOVLSGRx4eHpg9ezb69++PS5cuoWnTptixYwd69eoFADh69ChGjhwp8bl05erVq4iLi8OWLVvw/v179O3bF2FhYWjSpInOj8VoTiQSISkpCbGxsTh48CAsLCw+yTtQjHJBQUEgImzZsoUrN5uTk4NBgwaBz+fj8OHDep4hoytscc8wDKNjFaXh0aeQAFxUVISDBw9i48aNOHr0KDw8PBAWFobBgwdr1KiHKTvPnz/H5s2bufKgTMViZmaG8+fPo169ehLbMzIy0KJFCy58kKn4+PqeAMMwzOeGKkjDo08hAdjAwADffvstdu7ciejoaNy5cweTJk1C1apVMWTIEDx9+rRMj89IGzp0KP744w+p7fb29mxhX4EZGxtz1bBKys/Pl+gFwlR8LKGWYRhGRypiwyN9JwBfunQJcXFx2L59O8zMzDBp0iSEhYXh77//xo8//ohu3bohJSWlzOfB/L/Xr1+jXbt2cHZ2RkhICIKDg+Hk5KTvaTFa6ty5M8LDwxEbG8uFv124cAEjR45E165d9Tw7RpdYWA7DMIyOiLt3njlzBs2bN5fqjOvi4oJJkybBw8NDX1OUoM8E4CVLliA+Ph43b95EUFAQhg0bhqCgIPD5/39DOTs7G7Vq1UJRUZHOj88olpOTg8TERGzcuBFXr15FmzZtEBoaiu7du0vc3WEqjry8PAQHB+PgwYPc/8OioiJ07doVGzduhJWVlZ5nyOgKW9wzDMPoWEVpeKTPBGAPDw+EhoYiJCQElStXlrlPYWEhtm3bhuDgYJ0fn1Hd5cuXERcXhw0bNsDc3ByDBg3C6NGjP5mTVEY92dnZEk2s3N3d9T0lRsfY4p5hGOYLV1ESgJny9/TpUyQkJCAuLg5PnjxBz5498fTpU5w6dQoLFy7EhAkT9D1FhmFKYTH3DMMwX7jySgDOzMxUeV9vb2+dHZdRz4cPH/Drr78iPj4ex48fh7e3NyZMmICBAwfCwsICALB9+3aMGjWKLe4riNu3byMzMxO+vr5wdXXF4cOHER0djbdv36J79+6YPn06a1b2GWGLe4ZhmC9UeScA+/j4SMTyK1pMsLsF+lOlShWIRCL0798fKSkpMr8D7du3h7W1dbnPjVHfvn370KdPHy7HZt26dQgPD0fr1q1haWmJmTNnwsDAAFFRUfqeKqMjLCyHYRjmC1XeCcAlY/wvX76MSZMmYfLkyWjevDkA4Ny5c1i8eDEWLlyI7t276+SYjPo2b96M3r17f1JlWxnNNWrUCO3bt8fcuXOxceNGfPfdd/j5558xfvx4AMC6deuwdOlSZGVl6XeijM6wxT3DMMwXTh8JwE2aNMHMmTMRFBQksf3IkSOYMWMGUlNTy20uDPM5s7CwQHp6OmrUqAGRSAQjIyOkp6ejbt26AID79+/Dy8sLBQUFep4poyssLIdhGOYLFx8fX+7HvHLlClxdXaW2u7q64vr16+U+ny9djx49VN537969ZTgTRtfevHnD5Urw+XyYmppKhOCZmpri/fv3+poeUwZYh1qGYRim3NWuXRtz587Fu3fvuG3v37/H3LlzUbt2bT3O7MtkZWXFPSwtLXHixAlcunSJez01NRUnTpxgtdArIB6PJ5HfUvo58/lhYTkMwzBMuUtJSUGXLl0gEolQv359AEBGRgZ4PB4OHTrEddBkyl9UVBRyc3OxZs0arvdBcXExRo8eDUtLSyxatEjPM2TUwefzYWVlxS3o8/LyYGlpyTWMIyK8evWKJbF/RtjinmEYhtGLgoICJCYm4saNG1xDnQEDBsDMzEzfU/ui2dvbIzk5GZ6enhLbb968CT8/P+Tk5OhpZowmNm3apNJ+rFnc54PF3DMMwzB6UalSJYSHh+t7GkwpRUVFyMrKklrcZ2VlQSQS6WlWjKbYov3Lwxb3DMMwjF7cuXMHMTExyMrKAo/HQ+3atTFu3DjUqFFD31P7ooWEhCA0NBTZ2dlo1qwZAOD8+fNYsGABQkJC9Dw7RlNDhw5FaGgo/P399T0VpoyxxT3DMAxT7pKSktC1a1f4+PigRYsWICL89ddfqFOnDg4ePIi2bdvqe4pfrF9++QWVK1fG0qVL8fTpUwAfG1tNmTIFkZGRep4do6nXr1+jXbt2cHZ2RkhICIKDg+Hk5KTvaTFlgMXcMwzDMOWuQYMGaN++PRYsWCCxferUqTh+/DjS0tL0NDOmpFevXgFAufZAYMpOTk4OEhMTsXHjRly9ehVt2rRBWFgYunXrBkNDQ31Pj9ERtrhnGIZhyp2JiQmuXLki1f321q1b8Pb2liiRyejH8+fPcfPmTfB4PHh6esLOzk7fU2J06PLly4iLi8OGDRtgbm6OQYMGYfTo0TrrSM3oD6tzzzAMw5Q7e3t7pKenS21PT0+Hg4ND+U+I4bx58wahoaGoUqUK/P390bJlS1SpUgVhYWGsi+ln4unTpzh+/DiOHz8OgUCAoKAgXLt2DV5eXli6dKm+p8doicXcMwzDMOVu+PDhCA8Px927d+Hn5wcej4fk5GRER0ezuG49mzhxIs6cOYODBw+iRYsWAIDk5GREREQgMjISq1ev1vMMGU18+PABv/76K+Lj43H8+HF4e3tjwoQJGDhwINfBdvv27Rg1ahQmTJig59ky2mBhOQzDMEy5IyLExMRg8eLF+PvvvwEAjo6OmDx5MiIiIlgHTT2ys7PD7t270apVK4ntp06dQp8+ffD8+XP9TIzRip2dHUQiEfr374/hw4fDx8dHap+XL1/C19cX9+7dK/8JMjrDFvcMwzCMXr1+/RoAuKuHjH5VqlQJqampqF27tsT2a9euoUmTJnjz5o2eZsZoY/PmzejduzdMTEz0PRWmjLHFPcMwDKN3hYWFKCwshLm5ub6n8sULDAyEUChEQkICtxB8+/YtgoODkZubi99//13PM2QYRhG2uGcYhmHKVXx8PNLS0tCsWTMMHDgQ06ZNw5IlS1BUVISAgABs374dQqFQ39P8Yl29ehUdOnTAu3fvUL9+ffB4PKSnp8PExARJSUmoU6eOvqfIqKhHjx4q77t3794ynAlTntjinmEYhik38+bNw7x58+Dn54fLly+jT58+2L9/P8aPHw8+n4/ly5ejc+fOLGlTz96+fYvExETcuHEDRAQvLy8MHDgQpqam+p4ao4aSHYWJCPv27YOVlRUaNWoEAEhNTUVeXh569OiB+Ph4fU2T0TG2uGcYhmHKjYeHB2bPno3+/fvj0qVLaNq0KXbs2IFevXoBAI4ePYqRI0fiwYMHep4pw3xeoqKikJubizVr1kAgEAAAiouLMXr0aFhaWmLRokV6niGjK2xxzzAMw5QbY2NjZGdnw9nZmXuemZkJT09PAMCTJ0/g6uqKwsJCfU7zi5aTk8OFRT169Ajr16/H27dv0aVLF/j7++t5doym7O3tkZyczP2uid28eRN+fn7IycnR08wYXWNNrBiGYZhy8+HDBxgbG3PPjYyMJNreGxgYoLi4WB9T++JduXIFLi4ucHBwQK1atZCeno7GjRtj6dKlWLduHQICArB//359T5PRUFFREbKysqS2Z2VlQSQS6WFGTFlhTawYhmGYcnX9+nU8e/YMwMc44Bs3biA/Px8A8OLFC31O7Ys2ZcoU1KtXD4mJiUhMTETnzp0RFBSEDRs2AADGjh2LBQsWoHv37vqdKKORkJAQhIaGIjs7G82aNQMAnD9/HgsWLJCIzWcqPhaWwzAMw5QbPp8PHo8HWf/0lNzOriSWPzs7O5w8eRLe3t7Iz8+HpaUlUlJSuOTLGzduoFmzZsjLy9PvRBmNiEQi/PLLL1i2bBmePn0KAKhSpQrGjRuHyMhILg6fqfjY4p5hGIYpNyUTZYuLi6UWFCKRCAKBANWqVSvvqX3x+Hw+nj17BgcHBwAfm4plZGTAzc0NAPDPP//A0dGRhU19Bl69egUAsLS01PNMmLLAwnIYhmGYclO9enUAgEAgwNOnT7mFpFhOTg4cHBzYAlJPeDyewudMxff8+XPcvHkTPB4Pnp6esLOz0/eUGB1ji3uGYRim3BGRzIVjfn4+1xWVKX9Dhw7lEp7fvXuHkSNHwszMDADw/v17fU6N0dKbN28wduxYJCQkcGFvAoEAQ4YMwYoVK1CpUiU9z5DRFba4ZxiGYcrNxIkTAXy8IjxjxgyJBUVxcTEuXLgAHx8fPc3uy5WZmYmBAwfCwOD/lwWDBg2S2m/IkCHlOS1GhyZOnIgzZ87g4MGDaNGiBQAgOTkZERERiIyMZI3jPiMs5p5hGIYpN61btwYAnDlzBs2bN4eRkRH3mpGREVxcXDBp0iR4eHjoa4pfpJJhUm5ubrh48SJX6575PNjZ2WH37t1o1aqVxPZTp06hT58+eP78uX4mxugcu3LPMAzDlJtTp04B+FiWb9myZSyh7xNhbW2Ne/fuwcHBAffv32fVij5DBQUF+Oqrr6S2Ozg4oKCgQA8zYsoKu3LPMAzDMF+48PBwbNq0CY6Ojnj48CGqVq0qtzTi3bt3y3l2jC4EBgZCKBQiISGBy2t5+/YtgoODkZubi99//13PM2R0hS3uGYZhGIbBsWPHkJ2djYiICMyePRsWFhYy9xs3blw5z4zRhatXr6JDhw549+4d6tevDx6Ph/T0dJiYmCApKQl16tTR9xQZHWGLe4ZhGIZhOCEhIVi+fLncxT1Tcb19+xaJiYm4ceMGiAheXl4YOHAgTE1N9T01RofY4p5hGIZhGIZhPhMsoZZhGIZhGOYzl5OTw1VAevToEdavX4+3b9+iS5cu8Pf31/PsGF1iV+4ZhmEYhmE+U1euXEGXLl3w6NEjeHh4YPv27ejQoQPevHkDPp+PN2/eYPfu3ejevbu+p8roCF/fE2AYhmEYhmHKxpQpU1CvXj2cOXMGrVq1QufOnREUFIT//vsPL1++xIgRI7BgwQJ9T5PRIXblnmEYhmEY5jNlZ2eHkydPwtvbG/n5+bC0tERKSgoaNWoEALhx4waaNWuGvLw8/U6U0Rl25Z5hGIZhGOYzlZubi8qVKwMAzM3NYWZmBltbW+51GxsbvH79Wl/TY8oAW9wzDMMwDMN8xng8nsLnzOeFVcthGIZhGIb5jA0dOhTGxsYAgHfv3mHkyJEwMzMDALx//16fU2PKAIu5ZxiGYRiG+QxlZmZi0aJFMDBQfi03Pj6+HGbElAe2uGcYhmEYhvkMCQQCPH36FA4ODnBzc8PFixe5WvfM54vF3DMMwzAMw3yGrK2tce/ePQDA/fv3IRKJ9DwjpjywmHuGYRiGYZjPUM+ePeHv7w9HR0fweDw0atQIAoFA5r53794t59kxZYUt7hmGYRiGYT5D69atQ48ePZCdnY2IiAgMHz4cFhYW+p4WU8ZYzD3DMAzDMMxnLiQkBMuXL2eL+y8AW9wzDMMwDMMwzGeCJdQyDMMwDMMwzGeCLe4ZhmEYhmEY5jPBFvcMwzAMwzAM85lgi3uGYRiGYRiG+UywxT3DMAzDMAzDfCbY4p5hGIZhGIZhPhNscc8wDMMwDMMwn4n/AzdGI5gwB+MnAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(x_train.corr())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3fc6b1e8",
   "metadata": {},
   "source": [
    "## Find the correlation matrix which stores the corr b/w each features and o/p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "1506de95",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "197\n"
     ]
    }
   ],
   "source": [
    "corr_matrix=x_train.corr()\n",
    "#store columns in the corr_matrix\n",
    "columns=corr_matrix.columns\n",
    "#store the columns which we need to drop\n",
    "columns_to_drop=[]\n",
    "# look for multi-collinearity by Specifying the Threshold\n",
    "for i in range(len(columns)):\n",
    "    for j in range(i+1,len(columns)):\n",
    "        #access corr of each feature with every other feature\n",
    "        if corr_matrix.loc[columns[i],columns[j]]>0.95:\n",
    "            columns_to_drop.append(columns[j]) #e.g. f1-f2=0.95 droping f2 \n",
    "            #other way is to find after this corr with o/p the feature wch having max keep that one and drop other one\n",
    "#number of columns to drop\n",
    "len(columns_to_drop) #it has included repition also e.g. f1-f4=0.96 and f2-f4=0.97 f2 included twice like that\n",
    "columns_to_drop=set(columns_to_drop)\n",
    "print(len(columns_to_drop))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3dcc82a3",
   "metadata": {},
   "source": [
    "### Dropping these columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "f0d6dedf",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train.drop(columns=columns_to_drop,axis=1,inplace=True)\n",
    "x_test.drop(columns=columns_to_drop,axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6f87cb9",
   "metadata": {},
   "source": [
    "## New how many features remained"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "765a5a1c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(7352, 154)\n"
     ]
    }
   ],
   "source": [
    "print(x_train.shape) # 154 features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c9b464e",
   "metadata": {},
   "source": [
    "## Annova"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "8cb481f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_selection import f_classif\n",
    "from sklearn.feature_selection import SelectKBest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "26b48984",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\suhaib mukhtar\\AppData\\Roaming\\Python\\Python39\\site-packages\\sklearn\\feature_selection\\_univariate_selection.py:113: RuntimeWarning: divide by zero encountered in divide\n",
      "  f = msb / msw\n"
     ]
    }
   ],
   "source": [
    "sel=SelectKBest(f_classif,k=100).fit(x_train,y_train)#f_classif means perform annova on each feature then slect best 100 among them\n",
    "columns=x_train.columns[sel.get_support()] #returns best 100 columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "ee2af96c",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train=sel.transform(x_train)\n",
    "x_test=sel.transform(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "4af709bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "#new df\n",
    "x_train=pd.DataFrame(x_train,columns=columns)\n",
    "x_test=pd.DataFrame(x_test,columns=columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "efb9f3f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
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       "      <th>tBodyAcc-std()-X</th>\n",
       "      <th>tBodyAcc-std()-Y</th>\n",
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       "      <th>tBodyAcc-max()-Z</th>\n",
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       "      <th>tBodyAcc-min()-Z</th>\n",
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       "      <th>tBodyAcc-entropy()-Y</th>\n",
       "      <th>tBodyAcc-entropy()-Z</th>\n",
       "      <th>...</th>\n",
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       "      <th>fBodyAccMag-maxInds</th>\n",
       "      <th>fBodyBodyAccJerkMag-min()</th>\n",
       "      <th>fBodyBodyAccJerkMag-meanFreq()</th>\n",
       "      <th>fBodyBodyAccJerkMag-skewness()</th>\n",
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       "      <td>-0.913526</td>\n",
       "      <td>-0.744413</td>\n",
       "      <td>0.852947</td>\n",
       "      <td>0.685845</td>\n",
       "      <td>0.814263</td>\n",
       "      <td>-0.407747</td>\n",
       "      <td>-0.679338</td>\n",
       "      <td>-0.602122</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.999454</td>\n",
       "      <td>-0.793103</td>\n",
       "      <td>-0.988175</td>\n",
       "      <td>0.346989</td>\n",
       "      <td>-0.516080</td>\n",
       "      <td>-0.128989</td>\n",
       "      <td>-0.841247</td>\n",
       "      <td>0.179941</td>\n",
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       "      <td>1.0</td>\n",
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       "    <tr>\n",
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       "      <td>-0.998245</td>\n",
       "      <td>-0.975300</td>\n",
       "      <td>-0.960322</td>\n",
       "      <td>-0.818409</td>\n",
       "      <td>0.849308</td>\n",
       "      <td>0.685845</td>\n",
       "      <td>0.822637</td>\n",
       "      <td>-0.714892</td>\n",
       "      <td>-0.500930</td>\n",
       "      <td>-0.570979</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.999856</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.989549</td>\n",
       "      <td>0.532061</td>\n",
       "      <td>-0.624871</td>\n",
       "      <td>-0.271958</td>\n",
       "      <td>-0.844788</td>\n",
       "      <td>0.180289</td>\n",
       "      <td>-0.054317</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.995380</td>\n",
       "      <td>-0.967187</td>\n",
       "      <td>-0.978944</td>\n",
       "      <td>-0.818409</td>\n",
       "      <td>0.843609</td>\n",
       "      <td>0.682401</td>\n",
       "      <td>0.839344</td>\n",
       "      <td>-0.592235</td>\n",
       "      <td>-0.485821</td>\n",
       "      <td>-0.570979</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.999954</td>\n",
       "      <td>-0.862069</td>\n",
       "      <td>-0.999890</td>\n",
       "      <td>0.660795</td>\n",
       "      <td>-0.724697</td>\n",
       "      <td>-0.212728</td>\n",
       "      <td>-0.848933</td>\n",
       "      <td>0.180637</td>\n",
       "      <td>-0.049118</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.996091</td>\n",
       "      <td>-0.983403</td>\n",
       "      <td>-0.990675</td>\n",
       "      <td>-0.829711</td>\n",
       "      <td>0.843609</td>\n",
       "      <td>0.682401</td>\n",
       "      <td>0.837869</td>\n",
       "      <td>-0.627446</td>\n",
       "      <td>-0.850930</td>\n",
       "      <td>-0.911872</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.999931</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.995562</td>\n",
       "      <td>0.678921</td>\n",
       "      <td>-0.701131</td>\n",
       "      <td>-0.035684</td>\n",
       "      <td>-0.848649</td>\n",
       "      <td>0.181935</td>\n",
       "      <td>-0.047663</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.998139</td>\n",
       "      <td>-0.980817</td>\n",
       "      <td>-0.990482</td>\n",
       "      <td>-0.824705</td>\n",
       "      <td>0.849095</td>\n",
       "      <td>0.683250</td>\n",
       "      <td>0.837869</td>\n",
       "      <td>-0.786553</td>\n",
       "      <td>-0.559477</td>\n",
       "      <td>-0.761434</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.999926</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-0.982177</td>\n",
       "      <td>0.559058</td>\n",
       "      <td>-0.528901</td>\n",
       "      <td>-0.273582</td>\n",
       "      <td>-0.847865</td>\n",
       "      <td>0.185151</td>\n",
       "      <td>-0.043892</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 100 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   tBodyAcc-std()-X  tBodyAcc-std()-Y  tBodyAcc-std()-Z  tBodyAcc-max()-Z  \\\n",
       "0         -0.995279         -0.983111         -0.913526         -0.744413   \n",
       "1         -0.998245         -0.975300         -0.960322         -0.818409   \n",
       "2         -0.995380         -0.967187         -0.978944         -0.818409   \n",
       "3         -0.996091         -0.983403         -0.990675         -0.829711   \n",
       "4         -0.998139         -0.980817         -0.990482         -0.824705   \n",
       "\n",
       "   tBodyAcc-min()-X  tBodyAcc-min()-Y  tBodyAcc-min()-Z  tBodyAcc-entropy()-X  \\\n",
       "0          0.852947          0.685845          0.814263             -0.407747   \n",
       "1          0.849308          0.685845          0.822637             -0.714892   \n",
       "2          0.843609          0.682401          0.839344             -0.592235   \n",
       "3          0.843609          0.682401          0.837869             -0.627446   \n",
       "4          0.849095          0.683250          0.837869             -0.786553   \n",
       "\n",
       "   tBodyAcc-entropy()-Y  tBodyAcc-entropy()-Z  ...  \\\n",
       "0             -0.679338             -0.602122  ...   \n",
       "1             -0.500930             -0.570979  ...   \n",
       "2             -0.485821             -0.570979  ...   \n",
       "3             -0.850930             -0.911872  ...   \n",
       "4             -0.559477             -0.761434  ...   \n",
       "\n",
       "   fBodyGyro-bandsEnergy()-1,8.1  fBodyAccMag-maxInds  \\\n",
       "0                      -0.999454            -0.793103   \n",
       "1                      -0.999856            -1.000000   \n",
       "2                      -0.999954            -0.862069   \n",
       "3                      -0.999931            -1.000000   \n",
       "4                      -0.999926            -1.000000   \n",
       "\n",
       "   fBodyBodyAccJerkMag-min()  fBodyBodyAccJerkMag-meanFreq()  \\\n",
       "0                  -0.988175                        0.346989   \n",
       "1                  -0.989549                        0.532061   \n",
       "2                  -0.999890                        0.660795   \n",
       "3                  -0.995562                        0.678921   \n",
       "4                  -0.982177                        0.559058   \n",
       "\n",
       "   fBodyBodyAccJerkMag-skewness()  fBodyBodyGyroMag-meanFreq()  \\\n",
       "0                       -0.516080                    -0.128989   \n",
       "1                       -0.624871                    -0.271958   \n",
       "2                       -0.724697                    -0.212728   \n",
       "3                       -0.701131                    -0.035684   \n",
       "4                       -0.528901                    -0.273582   \n",
       "\n",
       "   angle(X,gravityMean)  angle(Y,gravityMean)  angle(Z,gravityMean)  Activity  \n",
       "0             -0.841247              0.179941             -0.058627       1.0  \n",
       "1             -0.844788              0.180289             -0.054317       1.0  \n",
       "2             -0.848933              0.180637             -0.049118       1.0  \n",
       "3             -0.848649              0.181935             -0.047663       1.0  \n",
       "4             -0.847865              0.185151             -0.043892       1.0  \n",
       "\n",
       "[5 rows x 100 columns]"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "2b5aaefd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7352, 100)"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa1ba2f9",
   "metadata": {},
   "source": [
    "## Applying the Logistic Regression On New Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "11be0409",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\suhaib mukhtar\\AppData\\Roaming\\Python\\Python39\\site-packages\\sklearn\\linear_model\\_logistic.py:469: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-7 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-7 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-7 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-7 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-7 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-7 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-7 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-7 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-7 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-7 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-7 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-7 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-7 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-7 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-7 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-7 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-7\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" checked><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LogisticRegression()"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "e425ed84",
   "metadata": {},
   "outputs": [],
   "source": [
    "ypp=lr.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "facd04ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.995928062436376"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_test,ypp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "27bb6655",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix,classification_report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "3d82ed18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cm=confusion_matrix(y_test,ypp)\n",
    "plt.figure(figsize=(5, 5))\n",
    "sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', cbar=False, vmin=0, vmax=100)\n",
    "plt.xlabel('Predicted Labels',weight='bold',fontsize=12)\n",
    "plt.ylabel('True Labels',weight='bold',fontsize=12)\n",
    "plt.title('Confusion Matrix Heatmap',weight='bold',fontsize=14)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "836c1aca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           1       1.00      1.00      1.00       532\n",
      "           2       1.00      1.00      1.00       491\n",
      "           3       1.00      1.00      1.00       537\n",
      "           4       0.98      1.00      0.99       496\n",
      "           5       1.00      0.98      0.99       420\n",
      "           6       0.99      1.00      1.00       471\n",
      "\n",
      "    accuracy                           1.00      2947\n",
      "   macro avg       1.00      1.00      1.00      2947\n",
      "weighted avg       1.00      1.00      1.00      2947\n",
      "\n"
     ]
    }
   ],
   "source": [
    "cr=classification_report(y_test,ypp)\n",
    "print(cr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "93ea07ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "\n",
    "# Sample classification report data (replace this with your actual data)\n",
    "data = {\n",
    "    'Class': [1, 2, 3, 4, 5, 6],\n",
    "    'Precision': [1.00, 1.00, 1.00, 0.98, 1.00, 0.99],\n",
    "    'Recall': [1.00, 1.00, 1.00, 1.00, 0.98, 1.00],\n",
    "    'F1-Score': [1.00, 1.00, 1.00, 0.99, 0.99, 1.00],\n",
    "    'Support': [532, 491, 537, 496, 420, 471]\n",
    "}\n",
    "\n",
    "# Create a DataFrame from the classification report data\n",
    "cr_df = pd.DataFrame(data)\n",
    "\n",
    "# Set the 'Class' column as the index\n",
    "cr_df.set_index('Class', inplace=True)\n",
    "\n",
    "# Plot the heatmap\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.heatmap(cr_df, annot=True, cmap='Blues', fmt=\".2f\", cbar=True)\n",
    "plt.title('Classification Report Heatmap')\n",
    "plt.xlabel('Metrics')\n",
    "plt.ylabel('Classes')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "5c1a79fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "\n",
    "# Sample classification report data (replace this with your actual data)\n",
    "data = {\n",
    "    'Class': [1, 2, 3, 4, 5, 6],\n",
    "    'Precision': [1.00, 1.00, 1.00, 0.98, 1.00, 0.99],\n",
    "    'Recall': [1.00, 1.00, 1.00, 1.00, 0.98, 1.00],\n",
    "    'F1-Score': [1.00, 1.00, 1.00, 0.99, 0.99, 1.00],\n",
    "    'Support': [532, 491, 537, 496, 420, 471]\n",
    "}\n",
    "\n",
    "# Create a DataFrame from the classification report data\n",
    "cr_df = pd.DataFrame(data)\n",
    "\n",
    "# Set the 'Class' column as the index\n",
    "cr_df.set_index('Class', inplace=True)\n",
    "\n",
    "# Define custom colormap with blue and pink colors\n",
    "custom_cmap = sns.diverging_palette(250, 120, s=90, l=50, as_cmap=True)\n",
    "\n",
    "# Plot the heatmap using the custom colormap\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.heatmap(cr_df, annot=True, cmap=custom_cmap, fmt=\".2f\", cbar=True)\n",
    "plt.title('Classification Report Heatmap')\n",
    "plt.xlabel('Metrics')\n",
    "plt.ylabel('Classes')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "08fa1c3e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}