Proj_4_Abalone.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Abalone Case Study\n",
    "Given is the attribute name, attribute type, the measurement unit and a brief description. \n",
    "The number of rings is the value to predict. \n",
    "\n",
    "Name / Data Type / Measurement Unit / Description\n",
    "Sex / nominal / -- / M, F, and I (infant)\n",
    "Length / continuous / mm / Longest shell measurement\n",
    "Diameter / continuous / mm / perpendicular to length\n",
    "Height / continuous / mm / with meat in shell\n",
    "Whole weight / continuous / grams / whole abalone\n",
    "Shucked weight / continuous / grams / weight of meat\n",
    "Viscera weight / continuous / grams / gut weight (after bleeding)\n",
    "Shell weight / continuous / grams / after being dried\n",
    "Rings / integer / -- / +1.5 gives the age in years. \n",
    "\n",
    "we have to predict the rings of each abalone which will lead us to the age of that abalone. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importing librarires\n",
    "import numpy as np  \n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline #To Do : Inline Priting of Visualizations \n",
    "import seaborn as sns\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sex</th>\n",
       "      <th>Length</th>\n",
       "      <th>Diameter</th>\n",
       "      <th>Height</th>\n",
       "      <th>Whole weight</th>\n",
       "      <th>Shucked weight</th>\n",
       "      <th>Viscera weight</th>\n",
       "      <th>Shell weight</th>\n",
       "      <th>Rings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M</td>\n",
       "      <td>0.455</td>\n",
       "      <td>0.365</td>\n",
       "      <td>0.095</td>\n",
       "      <td>0.5140</td>\n",
       "      <td>0.2245</td>\n",
       "      <td>0.1010</td>\n",
       "      <td>0.150</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M</td>\n",
       "      <td>0.350</td>\n",
       "      <td>0.265</td>\n",
       "      <td>0.090</td>\n",
       "      <td>0.2255</td>\n",
       "      <td>0.0995</td>\n",
       "      <td>0.0485</td>\n",
       "      <td>0.070</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>F</td>\n",
       "      <td>0.530</td>\n",
       "      <td>0.420</td>\n",
       "      <td>0.135</td>\n",
       "      <td>0.6770</td>\n",
       "      <td>0.2565</td>\n",
       "      <td>0.1415</td>\n",
       "      <td>0.210</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M</td>\n",
       "      <td>0.440</td>\n",
       "      <td>0.365</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.5160</td>\n",
       "      <td>0.2155</td>\n",
       "      <td>0.1140</td>\n",
       "      <td>0.155</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>I</td>\n",
       "      <td>0.330</td>\n",
       "      <td>0.255</td>\n",
       "      <td>0.080</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.0895</td>\n",
       "      <td>0.0395</td>\n",
       "      <td>0.055</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Sex  Length  Diameter  Height  Whole weight  Shucked weight  Viscera weight  \\\n",
       "0   M   0.455     0.365   0.095        0.5140          0.2245          0.1010   \n",
       "1   M   0.350     0.265   0.090        0.2255          0.0995          0.0485   \n",
       "2   F   0.530     0.420   0.135        0.6770          0.2565          0.1415   \n",
       "3   M   0.440     0.365   0.125        0.5160          0.2155          0.1140   \n",
       "4   I   0.330     0.255   0.080        0.2050          0.0895          0.0395   \n",
       "\n",
       "   Shell weight  Rings  \n",
       "0         0.150     15  \n",
       "1         0.070      7  \n",
       "2         0.210      9  \n",
       "3         0.155     10  \n",
       "4         0.055      7  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#importing dataset \n",
    "df = pd.read_csv('abalone.csv')\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4177, 9)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Features of the dataset \n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sex               0\n",
       "Length            0\n",
       "Diameter          0\n",
       "Height            0\n",
       "Whole weight      0\n",
       "Shucked weight    0\n",
       "Viscera weight    0\n",
       "Shell weight      0\n",
       "Rings             0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Null values\n",
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4177 entries, 0 to 4176\n",
      "Data columns (total 9 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   Sex             4177 non-null   object \n",
      " 1   Length          4177 non-null   float64\n",
      " 2   Diameter        4177 non-null   float64\n",
      " 3   Height          4177 non-null   float64\n",
      " 4   Whole weight    4177 non-null   float64\n",
      " 5   Shucked weight  4177 non-null   float64\n",
      " 6   Viscera weight  4177 non-null   float64\n",
      " 7   Shell weight    4177 non-null   float64\n",
      " 8   Rings           4177 non-null   int64  \n",
      "dtypes: float64(7), int64(1), object(1)\n",
      "memory usage: 293.8+ KB\n"
     ]
    }
   ],
   "source": [
    "# Data and datypes  \n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "M    1528\n",
       "I    1342\n",
       "F    1307\n",
       "Name: Sex, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sex colums is object type , lets check what are the distinct values  \n",
    "df['Sex'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "According to the Infomation:\n",
    "1)Dosen't contan Null data\n",
    "2) Features \n",
    "    1 Object Type \n",
    "        M    1528\n",
    "        I    1342\n",
    "        F    1307\n",
    "    7 Float Type with conitniuos data\n",
    "4)Label- Int Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Length</th>\n",
       "      <th>Diameter</th>\n",
       "      <th>Height</th>\n",
       "      <th>Whole weight</th>\n",
       "      <th>Shucked weight</th>\n",
       "      <th>Viscera weight</th>\n",
       "      <th>Shell weight</th>\n",
       "      <th>Rings</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4177.000000</td>\n",
       "      <td>4177.000000</td>\n",
       "      <td>4177.000000</td>\n",
       "      <td>4177.000000</td>\n",
       "      <td>4177.000000</td>\n",
       "      <td>4177.000000</td>\n",
       "      <td>4177.000000</td>\n",
       "      <td>4177.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.523992</td>\n",
       "      <td>0.407881</td>\n",
       "      <td>0.139516</td>\n",
       "      <td>0.828742</td>\n",
       "      <td>0.359367</td>\n",
       "      <td>0.180594</td>\n",
       "      <td>0.238831</td>\n",
       "      <td>9.933684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.120093</td>\n",
       "      <td>0.099240</td>\n",
       "      <td>0.041827</td>\n",
       "      <td>0.490389</td>\n",
       "      <td>0.221963</td>\n",
       "      <td>0.109614</td>\n",
       "      <td>0.139203</td>\n",
       "      <td>3.224169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.075000</td>\n",
       "      <td>0.055000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002000</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>0.000500</td>\n",
       "      <td>0.001500</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.450000</td>\n",
       "      <td>0.350000</td>\n",
       "      <td>0.115000</td>\n",
       "      <td>0.441500</td>\n",
       "      <td>0.186000</td>\n",
       "      <td>0.093500</td>\n",
       "      <td>0.130000</td>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.545000</td>\n",
       "      <td>0.425000</td>\n",
       "      <td>0.140000</td>\n",
       "      <td>0.799500</td>\n",
       "      <td>0.336000</td>\n",
       "      <td>0.171000</td>\n",
       "      <td>0.234000</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.615000</td>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.165000</td>\n",
       "      <td>1.153000</td>\n",
       "      <td>0.502000</td>\n",
       "      <td>0.253000</td>\n",
       "      <td>0.329000</td>\n",
       "      <td>11.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.815000</td>\n",
       "      <td>0.650000</td>\n",
       "      <td>1.130000</td>\n",
       "      <td>2.825500</td>\n",
       "      <td>1.488000</td>\n",
       "      <td>0.760000</td>\n",
       "      <td>1.005000</td>\n",
       "      <td>29.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Length     Diameter       Height  Whole weight  Shucked weight  \\\n",
       "count  4177.000000  4177.000000  4177.000000   4177.000000     4177.000000   \n",
       "mean      0.523992     0.407881     0.139516      0.828742        0.359367   \n",
       "std       0.120093     0.099240     0.041827      0.490389        0.221963   \n",
       "min       0.075000     0.055000     0.000000      0.002000        0.001000   \n",
       "25%       0.450000     0.350000     0.115000      0.441500        0.186000   \n",
       "50%       0.545000     0.425000     0.140000      0.799500        0.336000   \n",
       "75%       0.615000     0.480000     0.165000      1.153000        0.502000   \n",
       "max       0.815000     0.650000     1.130000      2.825500        1.488000   \n",
       "\n",
       "       Viscera weight  Shell weight        Rings  \n",
       "count     4177.000000   4177.000000  4177.000000  \n",
       "mean         0.180594      0.238831     9.933684  \n",
       "std          0.109614      0.139203     3.224169  \n",
       "min          0.000500      0.001500     1.000000  \n",
       "25%          0.093500      0.130000     8.000000  \n",
       "50%          0.171000      0.234000     9.000000  \n",
       "75%          0.253000      0.329000    11.000000  \n",
       "max          0.760000      1.005000    29.000000  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Data Manipulation \n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "lab_enc =LabelEncoder()\n",
    "# Categorical data will not have any outliers \n",
    "\n",
    "df['Sex']  = lab_enc.fit_transform(df['Sex'])\n",
    " # feature encoding complete completed       "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sex</th>\n",
       "      <th>Length</th>\n",
       "      <th>Diameter</th>\n",
       "      <th>Height</th>\n",
       "      <th>Whole weight</th>\n",
       "      <th>Shucked weight</th>\n",
       "      <th>Viscera weight</th>\n",
       "      <th>Shell weight</th>\n",
       "      <th>Rings</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>0.455</td>\n",
       "      <td>0.365</td>\n",
       "      <td>0.095</td>\n",
       "      <td>0.5140</td>\n",
       "      <td>0.2245</td>\n",
       "      <td>0.1010</td>\n",
       "      <td>0.150</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>0.350</td>\n",
       "      <td>0.265</td>\n",
       "      <td>0.090</td>\n",
       "      <td>0.2255</td>\n",
       "      <td>0.0995</td>\n",
       "      <td>0.0485</td>\n",
       "      <td>0.070</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0.530</td>\n",
       "      <td>0.420</td>\n",
       "      <td>0.135</td>\n",
       "      <td>0.6770</td>\n",
       "      <td>0.2565</td>\n",
       "      <td>0.1415</td>\n",
       "      <td>0.210</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>0.440</td>\n",
       "      <td>0.365</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.5160</td>\n",
       "      <td>0.2155</td>\n",
       "      <td>0.1140</td>\n",
       "      <td>0.155</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0.330</td>\n",
       "      <td>0.255</td>\n",
       "      <td>0.080</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.0895</td>\n",
       "      <td>0.0395</td>\n",
       "      <td>0.055</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Sex  Length  Diameter  Height  Whole weight  Shucked weight  \\\n",
       "0    2   0.455     0.365   0.095        0.5140          0.2245   \n",
       "1    2   0.350     0.265   0.090        0.2255          0.0995   \n",
       "2    0   0.530     0.420   0.135        0.6770          0.2565   \n",
       "3    2   0.440     0.365   0.125        0.5160          0.2155   \n",
       "4    1   0.330     0.255   0.080        0.2050          0.0895   \n",
       "\n",
       "   Viscera weight  Shell weight  Rings  \n",
       "0          0.1010         0.150     15  \n",
       "1          0.0485         0.070      7  \n",
       "2          0.1415         0.210      9  \n",
       "3          0.1140         0.155     10  \n",
       "4          0.0395         0.055      7  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "VISUAISATION\n",
    " 1. Histogram\n",
    " 2. Drisitnbution plot \n",
    "\n",
    "We will  ignore Sex and Rings for EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1800 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#HistPLot\n",
    "plt.figure(figsize=(20,25))\n",
    "plt_num=1\n",
    "for plot in df :\n",
    "    if plt_num<=8 :\n",
    "        ax= plt.subplot(2,4,plt_num)\n",
    "        plt.hist(df[plot])\n",
    "        plt.xlabel(plot,fontsize=30)\n",
    "    plt_num+=1\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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D46BeFUDe3Sfpp40xjqKw6N9Za3/VGPN9kmSt/aikvyTprxljfEktSd/eG/ANZOJWvaPrO2195QOrA73+3HJFXmC11ejq1GI53cUBmCufv7qtlWpRD5+604rrOgU9fGpBr92mUgmzodUb1F10zZs+7hQMM5WAMREqAcg1a+3nJb3vgI9/dN8//5ikH5vkuoCjPH9tV5J0frU60OvjIGmTUAlAwj73+o7ec2FFvYLevvtWK3ppfU9eEN7TUgRMm5YXqGAkx9wbKtH+BoyHdwAAAKbMc2/sSJLuWxksVDq5UJIkbTa7qa0JwPxpe4G+dHNP77mwcs/n7lupKrTS+l4ng5UBw2l1o/Dz7nDUdYz8gFAJGAehEgAAU+bFG3u6cKKqaunoId2xpYort2C02SBUApCc56/tKgit3nNh9Z7P3bcSzXy7vt2a8KqA4bW84MCKOrdQoP0NGBOhEgAAU+alm3t669mlgV9fMEYnaiVCJQCJev5aVDX5FefvrVQ6uVBSySnoOidPYga0vUAl995bX2YqAeMjVAIAYIp4QaiXN+p6/OziUL/v5EJJW4RKABL00s26lspuvyppv4IxOrdS0fVtQiVMv2bXV9Ex93w8mqnE6W/AOAiVAACYIq/dbsgLrN42RKWSJJ1YKDJTCUCiLq3X9diZxXvm0MTOLle0vkeohOnX8g4eKO8yqBsYG6ESAABT5Es36pI0VPubJJ2sldT2QrW6QRrLAjCHXlqv6/Ezh1dNnl4sqdkN2Hcw9drdg2cq0f4GjM/NegEAAOCOL9/ckzHSW84s6vNXdwb+ffEJcLcbHV0o1dJaHoA5sd3s6la9o7ccESqdWihLYt/BdHrq6Sv9f35ju6XF8r23vlQqAeMjVMLE7d/gR/WRDzyYwEoAYPpcWq/rwZM1VYqDnfwWW61FodJOy9OFE2msDMA8iK/TXrvdkBTdjB/m1GK079yqd3XhBKESplc3CFU8YFC363D6GzAu2t8AAJgiL2/U9ejphaF/31Ilek602/aTXhKAObS+15EknVm6d0h37ORCSUbS7XpnQqsCRuP5oUqHDeoOGNQNjINQCQCAKRGGVq/ebujRteFOfpOkhbKrgpH2Wl4KKwMwbzb2OnILRqu14qGvKToFrVSLus3Jk5hy3eDgQd3MVALGR6gEAMCUuLHbVtsL9cgIlUoFY7RUKVKpBCARm42uTiyUVDjk5LfYqcUSlUqYet4hoRIzlYDxESoBADAlXrkVzTAZpf1NkpYrrvbaVCoBGN9mo6tTvQMAjnJqsaxbdSqVML2stfICe2ioRKUSMB5CJQAApsTlXqj0yNpooVJUqUSoBGA81lrdbnQGCpVO1kpqeYE6XjCBlQHDiyuRSgcM6nYKBfmhlbUES8CoCJUAAJgSr2w0VC06OnvEYNyjLFdd7bZofwMwnr2OLy+wOjlAqBTPXNpmnhumVNePBnEXDxnULUkUKwGjI1QCAGBKvHKrrodPL6hQOHqGyWGWK0W1vEAeJ9kAGMNmr53t1GL52NeuVnuhUpMWOEyn+D2xdEj7myT5Ie+bwKjcrBcAAECePfX0lXs+9pEPPHjga1+51dC77l8Z+c9aqkQ3d3sM6wYwhvg0t8EqlaLXUKmEadUN4kqlA0KlXvVSEFjujIERUakEAMAU6PqhXt9q6dER5ylJ0aBuSdrl5g7AGDYbHRndaW07ymLFlWOMtpvsO5hOXhD1th0UKjn9SiX634BRESoBADAFrmw2FYRWj4x48pskLfXaUBjWDWAcm42uVmpFuYXjbxUKxmilVqT9DVPL681UOmhQd9z+xglwwOgIlQAAmAKvxCe/jREqLZajSqV6h/Y3AKPbbno6UTu+9S22Ui1SqYSpdaf97aBB3dHtMJVKwOgIlQAAmAKv3KpLGi9UqpUcGUmNDkd7AxjddsvrD+AexIlakZlKmFreUTOVGNQNjC21cWTGmJ+U9K2S1q217z7idV8j6dOS/rK19hfSWk/WDhrUOqzDBrsCAGbfK7caOrlQ6g+9HUXBGFVLjhpdKpUAjCYIrXZb3lB70Uq1pN3WtoLQ9mfUANPiqJlKtL8B40uzUumnJH3oqBcYYxxJ/6uk/5jiOgAAmHqXNxpjVSnFFsquGrS/ARjRbsuTVVR9NKjValFW0h7z3DCF/CPb3wiVgHGlFipZa39H0uYxL/ubkn5R0npa6wAAYBa8ciuhUKnk0v4GYGRbrWjg9soQodJytXfyZJtAG9Mnbn9zDzr9zeH0N2Bcmc1UMsacl/TfSvroAK99whjzjDHmmY2NjfQXBwDABNU7vtb3Onp0LYlKJdrfAIwuHrh9ojp4+9tSpXfyJHOVMIXutL/dW6kUn3DoB4RKwKiyHNT9I5L+jrX22Mep1tonrbUXrbUX19bW0l8ZAAAT9Grv5LdHaX8DkLHt5iiVStFraX/DNDpqUDftb8D4UhvUPYCLkn7eGCNJpyV9izHGt9b+coZrAgBg4l7eiE9+Wxz7ay2UXLW6AQNzAYxku+lpseweeAN+mFrJkWMM7W+YSl5g5RijgjmoUonT34BxZRYqWWsfif/ZGPNTkn6VQAkAMI9eudWQMdJDp2pjf62FsiOrqNrg1GJ5/MUBmCvbTU+rQ1QpSdHJk0sVl/Y3TCUvDOUe0PomcfobkITUQiVjzM9J+gZJp40xVyX9sKSiJFlrj52jBADAvHjlVkP3r1RVKTpjf62FcvTWvtkgVAIwvO1WV+dWqkP/vqWKqz0qlTCF/CA8tPLOKTCoGxhXaqGStfY7hnjt96S1DgAApt0rtxqJDOmWovY3Sbrd6OrxRL4igHlhrdV209M7zi0P/XuXq0Vt7HVSWBUwHi+wBw7plpipBCQhy0HdAADMPWutXtlo6JEEhnRLUfubFFUqAcAw6h1ffmiHGtIdW64Utcugbkwh74hKpf7pb4RKwMgIlQAAyNDGXkd7HT+Rk9+kO+1vtwmVAAxpuxmFQidqpaF/73LFVdsL1fUZeIzp4gf28FCpV8EUBPx/C4yKUAkAgAy9vNGQJD12ZvyT36Q77W+bdUIlAMPZ7g3aHnZQtyQtVaPfQ7USpo0XHD6om5lKwPgIlQAAyNDLG3VJ0qNryYRKTsGo5Ba0wylMAIa03YzC6NXq8JVKS5Uo0GZYN6bNUe1vBWNUMMxUAsZBqAQAQIYubzRULTq6b7mS2NesFR1CJQBD22p6KrsFVUvDn0S52Gu9rXcIlTBd/NCqWDi4UkmKHsZQqQSMjlAJAIAMvbxR16NrCyocccE7rGrJ0U6L9jcAw9lpdkeapyRJS5Wo/a1O+xumTNT+dvhtr1soECoBYyBUAgAgQ5dv1RNrfYtVqVQCMILtljfSPCVJqpUcGVGphOnjHTGoW5LcglEQMqgbGBWhEgAAGWl7ga5utfTYWjInv8WqJad/ihMADGqr2dVKdbRQqWCMFsouoRKmTjRT6ej2N2YqAaMjVAIAICOv3GrI2uSGdMeoVJp9xhjHGPNHxphfzXotmA9tL1DbC0duf5OiYd0M6sa0OWpQt8RMJWBcbtYLAABgXl3eaEhS4pVKtZLTPxocM+sHJL0gaTnrhWA+xNWNB7W/PfX0lYG+xiKVSpgy1lr5gZV7RKWS6xj5AaESMCoqlQAAyMjLG3VJ0iOnE25/Kzrq+qHaXpDo18VkGGMuSPpzkj6W9VowP7ab0XD/1TEqlQiVMG2C0MpKKh0zqJv2N2B0hEoAAGTk8kZd51erqpWSLRyu9r4ec5Vm1o9I+tuSDpwca4x5whjzjDHmmY2NjYkuDPm11Tq8UmlQixVX9bYva7lBx3TwehVIR53+xkwlYDyESgAAZOTljYYeTbj1TYoGdUtirtIMMsZ8q6R1a+1nDnuNtfZJa+1Fa+3FtbW1Ca4OebbT7MopGC2WRw+5F8uu/NCq43OSFqaD1zvV7bhB3T6nvwEjI1QCACAD1lpd3qjrsYSHdEtR+5t0p50FM+XrJH2bMeZVST8v6RuNMT+b7ZIwD7aanlaqRRXM4Tffx1mqRIFUnWHdmBLxrKRi4aj2NwZ1A+MgVAIAIAM3dztqdIPEh3RLdyqVGNY9e6y1f9dae8Fa+7Ckb5f0n62135nxsjAHtpvdsVrfJGmxHP3+PeYqYUp4QVSBdNSgbtrfgPFw+hsAAMc46OSjj3zgwbG+5pdv7kmSHjuTfKVSrUj7G4DhbLc8vfXM0lhfY6Ec7T0M68a0iEOl4pGDuqlUAsZBqAQAQAZevLErSXrHueRPjO/PVGJQ90yz1n5S0iczXgbmgB+E2mv7Y1cqLfTmMTW7hEqYDvGg7iNDJYfT34BxECoBAJCBF6/v6dxyRScWRj+++zBlt6CCkf7ry7f6N3mxcSusAOTPTv/kt/H2o1ov0G52g7HXBCTBDwYc1B0wqBsYFTOVAADIwAs39vT2+8ZrNTmMMUaVoqMWN3YABrDdD5XGq1RyCwWV3YIatL9hStyZqXT4bS8zlYDxECoBADBhXhDq0vqe3p5C61usUnTU9giVABwvPinyxJiVSlLUAkelEqZFv/2tcHilEjOVgPEQKgEAMGGXNxryAqu3n0unUkmSKsWC2h7l/ACOt9X0ZCQtV8efjFErOVQqYWoMMqjbMUahJVQCRkWoBADAhMVDutNqf5Okiuuo7VMtAOB4201PSxVXbmH8W4OFEpVKmB5erwLJPWKmUoH2N2AshEoAAEzYC9f3VHSMHj29mNqfQfsbgEFtN7tjD+mO1UqOGpz+hikRDFKpVDAKrWSpVgJGQqgEAMCEvXhjV4+tLarkpvc2TPsbgEFtt7yxh3THFsqumh0CbUyHuALJOWKmUsFEn6NYCRjN+I3TAABgKC9e39PXPnbqTR976ukrif4ZVCoBGERorXaant59/0oiX69WctQNQnlBeGR1CDAJ/gChUtwZx1wlYDTs9AAATFCz4+vGbjvVId1SFCp1/ZCLZABH2mv7CqxNrlKpFD2zZq4SpkEQWhXMnWqkgxR6gRNzlYDRECoBADBBN3bbkqS337ec6p9TcQuykro+LXAADrfZ6EqSTi0kM1NpoexIEifAYSr4oT2ySkm6U8UUEioBIyFUAgBgguJQ6R0TqFSSRAscgCPFodLJhEKlWq9SiWHdmAbBAKFSXMUUUNkLjIRQCQCACbqx09bJhZLWlsqp/jnlfqhEpRKAw202ujKSVhJqf6v1KpUY1o1p4IdWbuHoW16H9jdgLIRKAABMUDxPyRwx3yEJlWL0Fk+lEoCjbDW7Wq0Vj73xHtQClUqYIoNUKjmc/gaMhVAJAIAJCa3Vzd223n4u3XlKklRxe5VKPqESgMNtNro6kVDrmyRVS46MGNSN6eCHodzj2t+oVALGQqgEAMCEbNa78gKrt9+X7jwliZlKAAZzu9HVyVpyoVLBGFVLDoO6MRUGm6kU/Z3TUoHRECoBADAh1/tDuidQqdRvf2OmEoCDdfxAjY6f2JDuWK3kUqmEqRCE9thKJWYqAeMhVAIAYEJu7LRlJD1+djH1P4tKJQDH2Wp4kpI7+S22UHKYqYSpMNxMJUIlYBSESgAATMiN3bZOL5b7gU+aik5BTsFQqQTgUJuNrqTkQ6Va2eX0N0wFP7RyjhlCz0wlYDyESgAATMiNnZbOrVQm9udV3AKDugEcarOZTqhEpRKmxVDtb1QqASMhVAIAYALaXqCtpjfZUKno0P4G4FCbjY4qxYKqCVdPLvQqlSw36cjYYIO6e+1vFPYCI3GzXgAApMkYU5H0O5LKiva8X7DW/vBdrzGSflTSt0hqSvoea+1nJ71W5NvN3pDuc8sVPfX0lYn8mZWiow7tbwAOsdk7+c2Yo2+6h1UrOQqsVcdn/5llxpj/SdJfkWQlfUHS91pr29muajh+GB4/U4n2N2AsVCoByLuOpG+01r5X0ldK+pAx5oN3vebPSnq899cTkn58oivEXLgRh0oTrFQquQV1aH8DcIjNhqcTCbe+SdJCKXpuzQlws8sYc17S/0PSRWvtuyU5kr4921UNLwitXIdB3UCaCJUA5JqN1Hu/LPb+uvuq4cOSfqb32k9LWjXG3DfJdSL/buy0VXYLWq0WJ/Znlt0ClQIADhSGVlvNrk6lECrVylE7XaPDXKUZ50qqGmNcSTVJ1zJez9D80PZDo8PEc7ypVAJGQ6gEIPeMMY4x5llJ65J+w1r79F0vOS/p9X2/vtr7GJCYG7ttnVupJN5mchRCJQCHubnXVhDalCuVCJVmlbX2DUn/VNIVSdcl7Vhr/1O2qxreIJVKBSqVgLEQKgHIPWttYK39SkkXJL3fGPPuu15y0NXGPVcWxpgnjDHPGGOe2djYSGGlyCtrrW7stHVueXKtb5JUdh1CJQAHeu12U5J0spZCpVKpV6lE+9vMMsacUFTJ/Yik+yUtGGO+84DXTfW1kR8cP6ibmUrAeAiVAMwNa+22pE9K+tBdn7oq6YF9v76gA0q8rbVPWmsvWmsvrq2tpbVM5NB2y1PHDyc6T0mKKpW6zFQCcIDLGw1J0umlcuJfe6Hcq1Si/W2W/SlJr1hrN6y1nqRfkvTH7n7RtF8bBdbKLRx9y8tMJWA8hEoAcs0Ys2aMWe39c1XRRdKLd73s45K+20Q+qKjE+/pkV4o8u7ETDem+b8KVSiW3IC+wXCgDuMfljbqKjtFKCnPeym5BBUOl0oy7IumDxpha75Tcb5L0QsZrGlowQKVSoV+pNIkVAfnjZr0AAEjZfZJ+2hjjKArS/5219leNMd8nSdbaj0r6hKRvkXRJUlPS92a1WORTfPLb2Ym3v0XPjrp+qErRmeifDWC6vbxR1+nFcn+eTJKMMaoUHbU8QqVZZa192hjzC5I+K8mX9EeSnsx2VcOx1iqwQ7S/8QAGGAmhEoBcs9Z+XtL7Dvj4R/f9s5X0/ZNcF+bLjZ22Ti6UVJ5wsFN2oz+vQ6gE4C4vbzR0ejH51rdYreSoRaXSTLPW/rCkH856HaOKZyS5x4VKcfsbM5WAkdD+BgBAytb32jqTwtyS45SK0dt8h2oBAPu0vUCvbzW1luK+VC06arP3IENxqHRs+1vv07SKA6MhVAIAIEWhtbpd72otxYqAw8Ttb5wAB2C/V283ZK3SDZVKjppUKiFD/qChEqe/AWOh/Q0AgBRtNz35oU3lhKXj7G9/AzBbnnr6yj0f+8gHHkzka7+8Hp38lmbYXSk6ulXvpvb1geMMWqnETCVgPFQqAQCQolv1jiSlOrvkMHcGdVMtAOCOL93ckzEpVyoVmamEbPn9mUpH3/IWjJERM5WAUREqAQCQoo29KFRK8+btMLS/ATjIl27s6uFTCyo66d0KVEvRTCVu1JGVQSuVpKgFLuCtEhgJoRIAACnaqHdUKRa0UJr86WslQiUAB/jSjT297exSqn9GtejISqp3/VT/HOAwfhi99x13+psUnQDHoG5gNIRKAACk6NZeR2uLZRlz/EVt0pipBOBuza6v1zabetu59EMlSdppeqn+OcBhhqtUYlA3MCpCJQAAUnSr3smk9U2Sik40J4KZSgBiL92sy1rp7WmHSr3qzJ0WoRKyEfRnKg0QKhnDoG5gRIRKAACkpN7xtdv2MxnSLUnGGJXcApVKAPq+dGNPkiZWqbRLqISM+ENUKjkFw/wvYESESgAApOTyRl1SNie/xcqESgD2+eL1XVWLjh46tZDqnxNXKm0TKiEjw1QqMVMJGB2hEgAAKbm80ZCUzclvsbLrECoB6PvCGzt61/3LA1VvjKM/U4lQCRm5M1Pp+Fve6PQ3QiVgFIRKAACk5PJGXUbSqYVSZmsoFwvMVAIgKbrJ/uK1Xb37/ErqfxYzlZC1fvubM1ilUkCmBIyEUAkAgJS8fKuhEwsluU52b7clt6COR6USAOnljbpaXqCvmECoVHIKKhhCJWQnCKP3PneA01eZqQSMjlAJAICUXN5oaC3DeUqSVHaYqQQg8oWrO5Kkr7iQfqhkjFG16BAqITPBEJVKhYJofwNGRKgEAEAKwtDqlVt1nV7MrvVNkspFRx3a3wAomqdULTp6bG1xIn9etUSohOwMdfobg7qBkREqAQCQgms7LbW9UKczHNIt9drfqFQCIOmPrmzpPRdWUh/SHasWHe0SKiEjw5z+VjBGAaESMJLUQiVjzE8aY9aNMc8d8vn/3hjz+d5fnzLGvDettQAAMGn9k9+ybn9zC+oSKgFzr+0Fev7arr7qoRMT+zOpVEKW/GDwSqUCM5WAkaVZqfRTkj50xOdfkfQnrLXvkfSPJD2Z4loAAJioyxt1SdJaxpVKZbcgP7TMigDm3Oev7sgPrb76wcmFShVmKiFDceWRWzj+ltcpGN4ngRGlFipZa39H0uYRn/+UtXar98tPS7qQ1loAAJi0y7caWiq7Wiy7ma6j7EbHelOtBMy3z16JLrvf9+DqxP7MatHRdpNQCdmIK5UG6faMZiqlvCAgp6ZlptL/KOnXsl4EAABJubzR0KNrCzIDHGWcprIbvdUzrBuYb8+8uqWHT9V0aoItudWSo922R1sRMhGEVm7BDPQ+XKBSCRhZ5qGSMeZPKgqV/s4Rr3nCGPOMMeaZjY2NyS0OAIARXd6o69EJnbB0lFI/VKJSCZhXQWj19Cu39cFHT030z60VHVkr7XX8if65gCQFYTjwUHrHiEHdwIgyDZWMMe+R9DFJH7bW3j7sddbaJ621F621F9fW1ia3QAAARtDs+rq209ajpxeyXsq+SiVCJWBePX9tR3ttX1/72GRDpWopar/lBDhkwQ/twKESg7qB0WUWKhljHpT0S5K+y1r75azWAQBA0uKT3x47Mw2VStFNHe1vwPz61MvRs9uJh0rFaP9hWDeyELe/DSKaqUSoBIwitemhxpifk/QNkk4bY65K+mFJRUmy1n5U0t+XdErSv+z1ufrW2otprQcAgEm5fCsKlR5dW9BnX9vOdC39SiWPSiVgXn3q5dt6/MyizixVJvrnVkqESshOMGSlEjOVgNGkFipZa7/jmM//FUl/Ja0/HwCArFzeqMsY6eFT0xMqcfobMJ+6fqg/fGVTf/lrHpj4n02lErIUtb8N1pjjGKOATAkYSeaDugEAyJvLGw2dX62q0ruhylK5SPsbMM8+d3VbLS+YeOubRKiEbA3T/sZMJWB0hEoAACTs5Sk5+U2iUgmYd5+6dFvGSB98JINQifY3ZMjn9DdgIgiVAABIkLVWr9xq6LG17E9+kyS3YFQwnP4GzKtPvXxL775/RSu14sT/7JJTkFsw2m4SKmHyhpmp5FCpBIyMUAkAgATd2G2r2Q2mplLJGKOSWyBUAuZQqxvoj65s649l0PomRfvPSrVIpRIy4Q/Z/sagbmA0hEoAACTo8kZ08ttjp6ejUkmSyq5DqATMoc+8tqVuEGYyTym2Ui1ql1AJGRiqUskYWYlqJWAEhEoAACTo8kZdkqamUklSr1KJQd3AvPnUy7fkFoy+5uGTma1hmUolZGTYQd1SVN0EYDiESgAAJOjljYYWSo7OLpezXkpf2S0wqBuYI089fUVPPX1F/+Fz13R+tapfefZaZmtZrha11yZUwuT5Q1YqRb+H90pgWIRKAAAk6OWNuh5ZW5Axg13ITkKZmUrA3Gl7ga5utTKvmlyquNpr+5muAfMpCK1cZ7DbXSqVgNERKgEAkKDLGw09NkWtb1I8U4n2N2CevHKrIStlfhLlcsXVLqESMhCEtl+BdJy4oCkICJWAYREqAQCQkLYX6NpOS4+enrZQiUolYN5c3qjLLRg9cLKW6TqWKrS/IRt+aOU4g4ZKVCoBoyJUAgAgIa/casha6dGMKwPuVnIL6niESsA8eXmjoYdO1VQcsP0nLUtlVx0/ZK4bJi4Iw6FnKgWESsDQCJUAAEjI5Y2GpOkLlcpuQV7ADR0wLxodXzd221PRirtUcSWJaiVM3HCnv0V/Z1A3MDxCJQAAEvLyRl2S9Mjp6QqVim5Bfmh5AgvMiVdvRwH3NOxFS5WiJDGsGxPnB4Of/lagUgkYGaESAAAJubxR1/nVqmolN+ulvEm51/5CtRIwH1691ZBbMDp/opr1UvZVKhEqYXKC0MpKg1cqMVMJGBmhEgAACbl8qzF1rW+SVHIdSWJYNzAnXrnd0AMna3IL2V/q36lUov0NkxPP8HIG/BkoFKhUAkaV/TsNAAA5YK3V5Y2GHp2CdpO7ldzoYtkjVAJyb6/t6fp2eypa36Q7lUq7VCphgrq9ytzBK5Wiv/sBoRIwrOmqzwcAYEZt7HVU7/jabHT11NNXsl7Om5ScXqUS7W9A7n3mtS1ZSQ+fmo5QaZlKJWTgTqUSM5WAtFGpBABAAl7unfx2eqmc8UruVXKjt3uO9Aby7w9e2VTBSA+erGW9FEnScpWZSpg8b+hKpXimEu+TwLAIlQAASEB88tvaIqESgOz84aubOr9a7f/cZ22xHLe/UamEyRm6Uqn340KlEjC86Xi3AQBgxl3eaKjoGC1Xi1kv5R79UIn2NyDX2l6gz72+o4enZJ6SJLlOQbWSQ6USJiquVBq2/Y3T34DhESoBAJCAy7fqOr1Y7l+YTpOSE1cqBRmvBECann19W90g1CNTMk8ptlRxmamEiYpPOx26/Y1B3cDQCJUAAEjA5Y2GTk9h65tE+xswLz57ZUuS9OCp6ZinFFuqFKlUwkQNW6nkxKe/MVMJGBqhEgAAY+r4ga5uNbU2hUO6JalMqATMhc+9vq1HTi+oVpquA56jSiVCJUzOnZlKg93uFgqc/gaMilAJAIAxvXa7qdBqaiuV3IKRkdRhphKQa8++vq33XljJehn3iCqVaH/D5Hi9NjZmKgHpI1QCAGBML6/3Tn6b0kolY4xKbkEelUpAbt3YaevmbkfvfWA166Xcg0olTFo3iGYIDjtTiUolYHiESgAAjOnyrYYk6fRiKeOVHK7kFvqDSwHkz7OvR/OUvnIKQ6XliqtdQiVMUNcfslKpd1dMpRIwPEIlAADGdGm9rvtXKiq7TtZLOVTJKahL+xuQW3/0+raKjtE77lvOein3oP0Nkxa/3w1aqeT0K5V4nwSGRagEAMCYXlrf01vOLmW9jCOV3AKDuoEc+9zr23rnfcuqFKcv3F4qu+r4IXsQJsbzhzv9rT9TKaBSCRgWoRIAAGMIQ6uX1xt6y9pi1ks5EqESkF9BaPWFqztTOU9JimYqSaJaCRPTr1RyOP0NSBuhEgAAY3hju6WWF+jxs1MeKtH+BuTWpfW6Gt1gKucpSdJytShJDOvGxHjBsJVK0d+ZqQQMj1AJAIAxXOqd/PaWM1MeKlGpBORWPKR7eiuVCJUwWfH7Hae/AekjVAIAYAz9UGnK29/KhEpAbn3u6o6WKq4eObWQ9VIORPsbJq07dKVSb6YSoRIwNEIlAADG8NL6nk4vlnVioZT1Uo5UpP0NyK3nr+3qXfcv9+fCTJs4VNqlUgkT4vlRODRwqNS7K+b0N2B4hEoAAIzh0npdbzkzndUB+1GpBOSTH4R68fqu3nnfStZLOdRyv/2NSiVMRjcIVDB3KpCOQ6USMDpCJQAARmSt1UvrdT1+ZinrpRyr5Bbkh1Y+1UpArrxyq6GOH+pd9y9nvZRD3Wl/o1IJk+EFduAqJWnfTKWAUAkYFqESAAAj2tjraK/tT/2Qbik6/U2Sml6Q8UoAJOmL13clSe+c4lBpsUyohMnq+uGQoVL0dyqVgOERKgEAMKKXekO6H5+FUMl1JEnNDqESkCfPX9tVySlMdbjtOgXVSg7tb5iYbhDKLQx+q2uMUcFw+hswCkIlAABG9NLNPUma6pu5WMmNHsM2ulQKAHnyxWu7euu5RRWd6b6sX6q42iVUwoQMW6kkRS1wVCoBw5vudx8AAKbYpY26liuu1pbKWS/lWCUnqlRqdalUAvLCWqvnr+3oXVM8pDu2VCnS/oaJGTVU4vQ3YHiESgAAjOilm3U9fnZJZsDTZbJUcqO3/EaHmzogL27strXV9PSu89M7Tym2VHEJlTAxHT9Q0RkyVCowUwkYBaESAAAjenmjrresTX/rm3QnVGpSqQTkxvNv9IZ03zcLoVKRmUqYmLYXDt0SGlUqESoBwyJUAgBgBFuNrm7Vu3r8LKESgGx88fqujJHePgOh0jKVSpigthcMNahbYqYSMCpCJQC5Zox5wBjzX4wxLxhjnjfG/MABr/kGY8yOMebZ3l9/P4u1YrZc2ohOfntsBoZ0S1K598SWQd1Afjx/bUcPn1rQYtnNeinHWqoUtUuohAnp+OHw7W9GCgJCJWBY0/8OBADj8SX9LWvtZ40xS5I+Y4z5DWvtF+963e9aa781g/VhRr10MwqVHp+RUKkYVyoxUwnIjRdv7Old909/lZIUVyrR/obJaHuB3GHb3wpUKgGjoFIJQK5Za69baz/b++c9SS9IOp/tqpAHL63vqVp0dP9KNeulDKQch0oe7W9AHrS6ga5sNvXWs0tZL2UgC2VXHT+UH3C6FtI3WqUSp78BoyBUAjA3jDEPS3qfpKcP+PTXGmM+Z4z5NWPMuw75/U8YY54xxjyzsbGR5lIxAy6t1/WWM4sqDHlkcVbcgpGR1OwQKgF5cGm9Lmult81IqBS36DXYgzABHS9QkZlKwEQQKgGYC8aYRUm/KOkHrbW7d336s5Iesta+V9L/JumXD/oa1tonrbUXrbUX19bWUl0vpt+l9frMtL5JkjFGJbfAoG4gJ750c0+S9NZzMxIqVaJQaa9DCxzS1/ZDuaPMVCJUAoZGqAQg94wxRUWB0r+11v7S3Z+31u5aa+u9f/6EpKIx5vSEl4kZ0vYCXd9pz8yQ7lgUKjFTCciDl27uqeQU9NDJWtZLGchSr1Kpzlw3TEDbC1QccqaSw0wlYCSESgByzRhjJP2EpBestf/skNec671Oxpj3K9obb09ulZg1G3sdSbMzpDtWcgpqUKkE5MKXbu7psTOLQw8jzspCHCpxAhwmoDNSpZKhUgkYAae/Aci7r5P0XZK+YIx5tvexvyfpQUmy1n5U0l+S9NeMMb6klqRvt9ZyVYFDxaHSW2YtVHILalGpBOTCSzfruvjwiYFf/9TTV1JczfHi9jcqlZA2LwgVhFbu0DOVRKUSMAJCJQC5Zq39PUlHPqqy1v6YpB+bzIqQB+t7bZWcgh6ckbaTWMktMCQXyIG9tqc3tlv6yNkHs17KwGh/w6S0e6eccvobMBmzUS8LAMAUWd/r6JHTCzPTdhIrM1MJyIUv36xLmp2T36R9lUq0vyFlHT8KhoadqVQoGPkBlUrAsGbrahgAgCmwvtfRW87OVuubFF1gc/obMPteik9+m6FQaYFKJUxIXKnkFjj9DZgEQiUAAIbgBaG2Gl09tjZ7oVJUqUSoBMy6L93cU7Xo6MKJatZLGdhCiVAJk9H2RqxUMpz+BoyCUAkAgCHcbnRlJT22tpD1UoZWdApq0P4GzLyXbtb11rOLKgxZiZElp2C0UHJof0PqxpupRKgEDItQCQCAIdzqnfxGpRKArHzp5p4en6HWt9hixaVSCamLZyoNO/ewUKBSCRgFoRIAAEO4VY9CpUdOz16lUsktqOuH8gJOtwFm1U7T08ZeR4+fmb1ge6Hsao9QCSnrxDOVhq5UknzeH4GhESoBADCEjb2OVqrF/tDZWVLqPbWlWml6GWMqxpg/MMZ8zhjzvDHmH2a9JkyXy7eik98encFqyaWyqwahElLW9nvtb4XhZyrR/gYMb/auiAEAyNBGvaPTi6WslzGSkutIklrdQCvVYsarwSE6kr7RWls3xhQl/Z4x5testZ/OemGYDpc3GpKkR3tz3Z56+kqWyxnKYsVlphJS1xlxULdD+xswEiqVAAAYkLVWt+odnV4sZ72UkZTc6G2fYd3Ty0bqvV8We39xl4O+y7fqcgtGD56sZb2UoS2WmamE9MWVSqO0v1GpBAyPUAkAgAHVO77aXqi1pRkNleL2tw7tb9PMGOMYY56VtC7pN6y1T2e8JEyRyxsNPXiyNnQVxjRYKLvao1IJKWuPWKlUMEZ+yEwlYFiz924EAEBGNnpDutdmvFKpSaXSVLPWBtbar5R0QdL7jTHv3v95Y8wTxphnjDHPbGxsZLJGZOeVW42ZPChA6s1UYv9ByuJB3cXCkJVKBWYqAaMgVAIAYEC39rqSNLOVSmWXQd2zxFq7LemTkj5018eftNZetNZeXFtby2JpyEgYWr1yq9GfpzRr4plK1nLjjvS0/ajayB2pUon/N4FhpRYqGWN+0hizbox57pDPG2PMPzfGXDLGfN4Y81VprQUAgCRs7LVVdIyWZ3TIdZFQaeoZY9aMMau9f65K+lOSXsx0UZgab2y31PHDmTz5TYra3/zQquPTYoT0tL3RZio5RgoCQiVgWGlWKv2U7nqydpc/K+nx3l9PSPrxFNcCAMDYbtW7Or1YVsEMd6E6LcoOg7pnwH2S/osx5vOS/lDRTKVfzXhNmBKXb/VOfpvh9jdJzFVCqjp+qJJTGPq9mkolYDRuWl/YWvs7xpiHj3jJhyX9jI3qXz9tjFk1xtxnrb2e1poAABjHRr2j86vVrJcxsv5MJU5fmlrW2s9Lel/W68B0emUjOhhwViuVFivRrUej489sGzGmX9sLVC4OXzvBTCVgNFnOVDov6fV9v77a+9g9GEgJAMiaH4TaanRn+kaoHyp5tL8Bs+jyrYaWyq5OL5ayXspIFstR63CdYBspanuhyq4z9O8rGHH6GzCCLEOlg+oRD4yGGUgJAMjaZqMrK83szZwkuQWjgpGaHUIlYBZd3oiGdJsZbcFdKEc3+rS/IU0dP1BllEolYxTaaCA+gMFlGSpdlfTAvl9fkHQto7UAAHCkzWZ08tvJhdmtVDLGaKHEkd7ArLq8UZ/Z1jdJWqJSCRPQ8UJViiNUKhWisDbgdEJgKFmGSh+X9N29U+A+KGmHeUoAgGm12YhDpdmtVJKkaslRi9PfgJnT9UNd22nP7JBu6c0zlYC0tL1AZXe0SiVJzFUChpTaoG5jzM9J+gZJp40xVyX9sKSiJFlrPyrpE5K+RdIlSU1J35vWWgAAGNdWo6uiY7RQGv7p5zRZKLtqECoBM+d2oyNJemRthkOl+PQ3QiWkqOOPWKnU6yrlBDhgOGme/vYdx3zeSvr+tP58AACStNno6uRCaWZnmcSqRYfT34AZdLseVUs+fGr2Q6U6M5WQopYXqDpSqNSrVAoIlYBhZNn+BgDAzNhqejpZm+3WNykalNukUgmYOVu9uW4PnKxlvJLRVYoFOQWjesfLeinIsUbHV22EquJ4phInwAHDIVQCAOAY1tp+pdKsq5VcNRnUDcyczUZXK9WiVqrFrJcyMmOMFsuuGpxAiRQ1u8FooVKvEJmZSsBwCJUAADhGoxuoG4Q6kYtQyWGmEjCDtppdPTjDVUqxxbKrPdrfkKJmN1CtPPyUF8fElUqESsAwCJUAADhG/+S3HLS/1Uoup78BM2izkZ9QifY3pKnZ9VUbZ6YSoRIwlNQGdQMAkBdbvVApD5VKC2VHDdrfgJkSWqutpjeT85SeevrKm37d8gLVOSwAKQlDq5Y3WqVSoVduQaUSMBwqlQAAOMZmb0DuiRxUKlVLjprMMwFmym7LUxDaXFQqVYoF1dmDkJK2H8hajThTKa5UYlA3MAxCJQAAjrHZ6Gqp4qrkzv7b5kLJVTcI5QVcNAOzYrN/8ls145WMr+w6qrdpf0M64tNNF8YIlahUAoYz+1fHAACkbLPRzUWVknTn6W2TuUrAzIhbcPNQqVR2C7S/ITVxJW61NEL7WxwqBYRKwDAIlQAAOMZWo6uTOZinJEWDuqVokCmA2bDZ8GQk3b+ah0qlghq0v80EY8yqMeYXjDEvGmNeMMZ8bdZrOk7Ti97bRqpU6t0ZM6gbGA6hEgAAR+j6oXZaXm5CpYUylUrArNlqdrVaK6rozP6le7noqN7xFXLjPgt+VNKvW2vfLum9kl7IeD3HavQrlWh/AyZl9t+ZAABI0bXtlqykk7lpf+tVKlEpAMyMzUY3F6dPSlKlN5uOUyinmzFmWdLXS/oJSbLWdq2125kuagBxFe7CKKe/9Qd1EyoBwxj+pw0AgDlyZbMpSbm5obszU4kbOmBWbDa6evu5JT319JWslzK2shvtQfWOr6VKMePV4AiPStqQ9G+MMe+V9BlJP2Ctbex/kTHmCUlPSNKDDz448UXeLa7CHen0t165hc/pb8BQqFQCAOAIV7dakqQTtXzc/DCoG5gtXT9UvePnpgW3XOxVKjGse9q5kr5K0o9ba98nqSHph+5+kbX2SWvtRWvtxbW1tUmv8R7xA5PaCIO6HSqVgJEQKgEAcITrOy0ZKTdP1OOWAFpPgNmw2YxOfstLtWRcqbTXZg+aclclXbXWPt379S8oCpmmWvzAZKRB3cxUAkZCqATMKGutvIDyXCBt17bbWq4W5RRM1ktJRLVIpRIwS7YaUaiUl7lulV6lUp1Kpalmrb0h6XVjzNt6H/omSV/McEkDaSYwqDsICJWAYTBTCZhRf/Dqpj7+7DX9+nM39K+++6u1nJMqCmDaXN9pabmSn7fLuFKpyQ0dMBM2G/mqVCr1BnXXqVSaBX9T0r81xpQkXZb0vRmv51h3ZiqNMKi7P1OJUAkYBpVKwAyy1uq/XrqlxYqr3798W5/4/PWslwTk1vWdtlZyUiEg3Zmp1KBSCZgJOy1PRceM1M4zjSr7BnVjullrn+3NS3qPtfYvWGu3sl7TcZpdX2W3MFJ1Mae/AaMhVAJm0MsbDd2qd/Vn3nVOD56s6f/3BUIlIA3WWl3bbmm1mp9KwLJbUMFILUIlYCZstzytVEsyJh8tuGXa35CiRtfvV+QO685MJcZLAMMgVAJm0PPXdlR2C/qK8yv6c++5T596+XZ/5gKA5Gw1PXX8UCs5CpWMMVoouQzqBmbETrObs2C7V6lE+xtS0OwG/dmBw4qLm6hUAoZDqATMoDe2Wzq/WlXRKehPv/OsgtDq9y/fznpZQO5c225JUq5CJSkaYBoPMwUw3bZbnlZq+dmDnIJR2S1QqYRUNDuBFsojhkoFTn8DRkGoBMyYILS6sdPW/atVSdI77ltWwUgv3tjLeGVA/lzfaUvKX6i0UHbV9AiVgGnnh6HqbT93e9BSxSVUQiqaXqDqCEO6pX3tb5z+BgyFUAmYMet7bfmh7YdKlaKjh08v6MXruxmvDMif6zu9SqUcVQlI0bBuTn8Dpt9uy5eVctX+JkmLZUIlpKPZ8Ucean+n/Y2ZSsAw8nNGMjAnrm1HlRPne6GSJL3j3LKeu7aT1ZKAXHnq6Sv9f/7NL67LMUaLIw79nFa1ksNMJWAGbLeieYmrOTqBUpIWKy4zlZCKZjfQ6ogPghxD+xswCiqVgBlzbbulklvQqcU7F5hvO7ek12431eCpH5Co3ban5arbL4nPi1rJ5fQ3YAbsND1JOWzBLbna45oFKWh2/dHb33qlSgzqBoZDqATMmI16R2eWym+6yX37uSVJ0pdvMlcJSNJ208vdzZwkLZQdNQiVgKm308pnqLRUcXkQhlS0vEC1kU9/o1IJGAWhEjBjNhtdnbirDP5thEpAKnZa3dzdzElStegyUwmYAdtNT7WSo5Kbr0t2ZiohLa1uoOqoM5V6P2ZUKgHDGegdyhjzi8aYP2eMydc7GjBjQmu13ezq5MKbQ6Xzq1U5BaOrW62MVjYZ7EWYpNBa7bZ8rVTzNctEiiqVOP0tfexZGNdOy8vdkG6JmUppYc+R2l6oyriVSpz+Bgxl0A3nxyV9RNJLxph/bIx5e4prAnCInZan0OqeUMl1Cjq3XMl9qCT2IkxQo+MrsDZ3J79J0UylZodQaQLYszCW7VZXKzkb0i1JC2VmKqVkrvccPwjVDUJVxwiVjOH0N2BYA4VK1trftNb+95K+StKrkn7DGPMpY8z3GmPyd7UNTKnNRnQKzN2hkiSdP1HVGzkPldiLMEnxLJM8VgnUSo66QSgv4MI5TexZGFde57otlV11/VBdnz0oSfO+57R7/z9VS6MXarkFw0wlYEgD/8QZY05J+h5Jf0XSH0n6UUUb1m+ksjIA99jqhUp3z1SSpAurVV3dak56SRPHXoRJ2c7pqUtPPX1FL96I5q/9zKde01NPX8l4RfnGnoVRtb1AHT/MZbC9WI5O52JYd/Lmec+JTzUdtVJJkpyCYaYSMKSBzls0xvySpLdL+t8l/Xlr7fXep/4PY8wzaS0OwJttNrsqmINvci+cqOrGblteEKro5LOVnr0Ik5TXU5ckqdzbI7pBqKpGv/jG0dizMI7tuFoyhy24i5Xo36ne8XXigOprjGbe95x2b1bgqDOVJMktFKhUAoY0UKgk6WPW2k/s/4Axpmyt7VhrL6awLgAH2Gx0tVorySmYez534URNoZVu7LT1wMlaBqubCPYiTMxOy5NbMKqNeIrMNCv2TpKi9SR17FkY2U4zqk7OY7C9WI721T2GdSdtrvecVi9UGvX0N4lKJWAUg5Yz/H8O+NjvJ7kQAMfbbnqHPrE8f6IqSXkf1s1ehInZbXtarhZlzL0h7qwrEypNCnsWRnanUil/lTyL5ehaptElVErYXO85SbS/RTOVeG8EhnFkpZIx5pyk85Kqxpj3SYqvrJcl5bYUAphWu21Pj5xaOPBzF3qh0hvb+QuV2IuQhd2Wr+XKoAW9syVuke0EnACXBvYsJGGn6algpKUc7kOLvX+nvbaX8UrygT0n0q9UYqYSMFHHvUv9GUWD3i5I+mf7Pr4n6e+ltCYAB7DWaq/ta6lycKXSfStVGaO8ngDHXoSJ22t7un+1mvUyUhFXKnlUKqWFPQtj22l5Wq4UVchhtWQ8qLveIdhOCHuO7oRKlTHa39yCkR8QKgHDODJUstb+tKSfNsb8RWvtL05oTQAO0OoGCkKr5erBP7Ylt6CTtZLW99oTXln62IswadZa7bY9vaO6nPVSUlHqhUodQqVUsGchCTutqAU3j+LqqzozlRLBnhNpJ3H6m0OlEjCs49rfvtNa+7OSHjbG/D/v/ry19p8d8NsApGC3d+F1WKWSJK0tlbW+15nUkiaGvQiT1vFDeYHNZduJJJUcZiqliT0LSdht+zq3XM56GalY6Fcq0f6WBPacSBLtb5z+BgzvuKvleHjLYtoLAXC03d7cgaNmvOQ1VBJ7ESZspxX/vOWzSiCuVOoGhEopYc/C2Hbbnt56Np//C9WKjoyhUilB7Dni9DcgK8e1v/2r3t//4WSWA+Aw8TDL4yqVXl6vT2pJE8NehEmLj7leOqTddNaVOP0tVexZGNde21PXD3MbbBcKRoslV3sdQqUksOdE4tPfKpz+BkxUYZAXGWP+v8aYZWNM0RjzW8aYW8aY70x7cQDuuNP+dvhN7pmlijbqHVmbzycs7EWYlLgycCWnN3RuwciIUClt7FkY1c3dqOr4sDmKebBYcdUgVErUvO85bU5/AzIxUKgk6U9ba3clfaukq5LeKun/ldqqANxjr+2pWnT6R4Ef5MxSWV5gtd3M7YwC9iJMxF7r+MrAWWaMUckt0P6WPvYsjOTmbnToRl4rlaToBLg6oVLS5nrPaXmBnIJR0Rn9xMSoUolQCRjGoKFS/I72LZJ+zlq7mdJ6ABxit+UfOzR4bSka6JnTuUoSexEmZLftq1Is9NvE8qjsFqhUSh97FkZyY6cXKuX09DcpqlTaY6ZS0uZ6z2l1Q1WLjowZPVSiUgkY3qBXy//BGPOipIuSfssYsyYpf+eWA1Nsr3380cJn+qFSbn882YswEbttL7dVSrGiU1CHUClt7FkYyQ0qlTCaud5zWl4w1jwlqXf6W0CoBAxjoFDJWvtDkr5W0kVrrSepIenDaS4MwJvttX0tlY+uVDqzXJEkbeS0Uom9CJOy2/JyO08pVnYL8mh/SxV7Fka1vtvOfbXkUsXl9LeEzfue0/YCVUvj/cxQqQQMb5jpf++Q9LAxZv/v+ZmE1wPgANZa1Tu+Fo8Jleag/U1iL8IE7LV9nT5dznoZqSq5VCpNCHsWhnZjt53rKiVJWihRqZSSud1zWt1grCHdkuQ6Rh0/SGhFwHwYKFQyxvzvkh6T9Kyk+KfMak42KCBr3SCUH1otHBMqLZZd1UqO1nfzGSqNshcZYx7off6cpFDSk9baH73rNUbSjyqaQdCU9D3W2s8mvX7MhtBa7bX9XM8ykaJQqdnlwjlNXD9hVDd2O7nfgxapVErcvO85LW/8UIlKJWB4g1YqXZT0TpvXc8qBKdfoRNcFx4VKknR6sazbjXyGShptL/Il/S1r7WeNMUuSPmOM+Q1r7Rf3vebPSnq899cHJP147++YQ81uoMDaYwfjz7qSU9CWn9uTIqcF108YyfpuW/etVLJeRqqWyq7qXV/W2rEGK+NN5nrPSWamEqe/AcMatOn0OUVP+QFkoNErD18oH/9GeXKhpM1GN+0lZWXovchaez2uOrLW7kl6QdL5u172YUk/YyOflrRqjLkviQVj9uy2oqAl760nJdfh9Lf0cf2EoQWh1fpeJ/d70GLFlbWiYjJZc73nRDOVqFQCJm3Qx7CnJX3RGPMHkvolENbab0tlVQDeJA6VjpupJEWhUnwUcQ6NtRcZYx6W9D5JT9/1qfOSXt/366u9j10fZ7GYTXvtXqiU89aTkmsIldLH9ROGdrveURDa3O9Bi+Xo36/e8QeqxMZA5nrPaXUDVVcTOP2NUAkYyqA7+D9IcxEAjtbo9iqVSoOFSi9c3017SVn5B6P+RmPMoqRflPSD1tq7v0EH1d3fc0VhjHlC0hOS9OCDD466FEy53d6Mj+Xct7856nL6W9r+QdYLwOy52ZuLmPc9aLH377fX9nV2OePF5Mc/yHoBWWKmEpCNgd6trLW/bYx5SNLj1trfNMbUJI33EwtgYPUhZiqdWijpdqObyxkFo+5FxpiiokDp31prf+mAl1yV9MC+X1+QdO2AP/9JSU9K0sWLF7niyKndXqXSYs5v6EpudOHMxXN6uH7CKG7sRtXGea9UWupd03ACXHLmfc9pe6EqY7a/RTOVeOACDGOgmUrGmP+7pF+Q9K96Hzov6ZdTWhOAuzQ6voqOUck9/kf2xEJJXT9UI4czCkbZi3onu/2EpBestf/skJd9XNJ3m8gHJe1Ya2l9m1O7LV8LJUduYdCxg7Op5EYX3rTApYfrJ4yiHyrlfKZS/KCME+CSM+97TjupSqWAhy3AMAa9Yv5+SV8naVeSrLUvSTqT1qIAvFljiHkDJxdKkqStfA7rHmUv+jpJ3yXpG40xz/b++hZjzPcZY76v95pPSLos6ZKkfy3pr6eyesyEvbaX+woBSSo70SUALXCp4voJQ7u501bB5L9acrFfqcQplAma6z2n7QUqD/AA9iiuw+lvwLAGfbfqWGu7cSuNMcbVAfNGAKSj0fUHGtItRe1vknS70dUDJ2tpLisLQ+9F1trf08Ezk/a/xiq6EAO02/a0lPObOUkq9i68O37+qhqnCNdPGNrN3bbWlsoq5KyF/W5L+2YqITFzu+f4QSg/tKowUwmYuEGj3N82xvw9SVVjzDdL+j8l/Yf0lgVgv0YnGGhItxS1v0nSZqNzzCtnEnsRUrfX8nPfdiKp/zTX87l4ThF7FoZ2Y7etc8uVrJeRukVmKqVhbvecuOp2kFERR+H0N2B4g/7U/ZCkDUlfkPRXFbWK/M9pLQrzKwit6h2fJwR3idrfBnvycqofKuWynJy9CKnyglD1jj8X7W/xhXcnoFIpRexZGNrN3bbOzkGoxEylVMztntPxolBp3PY3p2Dk0xYODGXQ099CY8wvS/pla+1GukvCvLLW6mO/e1mvbTb14Mma/urXP5q708tGVe/4A1cqncxxpRJ7EdJ2q96Rleai/a0Uz1RiUHdq2LMwipu7HX3gkVNZLyN1JbegsltQvUuolJR53nPiSqWym8TpbzzcBoZxZJTbOwnpHxhjbkl6UdKXjDEbxpi/P5nlYZ68vtXSa5tNnV+t6spmU69vNrNe0lTwej3itQGPSF0suyo5Bd3O0aBu9iJMys3dKIxdmYP2t7hSiVApeexZGFXbC7TT8nRuJf+VSlIU4FOpND72nDuVSuO2vzFTCRjecT91P6joBIGvsdaestaelPQBSV9njPmf0l4c5sunL99W2S3ou772IZXdgj79ymbWS5oKzW7UmlIdsFLJGKMTC8W8nf72g2IvwgTc7B3lvTRH7W+ESqn4QbFnYQQ3dqI9aB7a36ToQRgzlRLxg5rzPSc+dGLs0996lUrRGS4ABnHcT913S/oOa+0r8QestZclfWfvc0AigtDqi9d29Z4LK1quFPXeB1b1/LUdnhRIanlxqDR4Oe/JhbI28xUqsRdhItZ7odLyPLW/MTsiDexZGEkcbJ9dLme8kslYKFOplJC533M6flIzlaLfzy0IMLjjrpqL1tpbd3/QWrthjMn/Y1xMzPpeW90g1COnFyRJj5xa0B+8sqmbu23dv1rNeHXZavUqlQZtf5Ok1WpR281cDepmL8JE3Nhtq2DuDJDNMyqVUsWehZHc6IVK55Yren2zlfFq0rdYdrVHpVIS5n7PiUOlT718W7fqoz9YdZ1onqsfhnIK481nAubFcVHuUT+RuSqDQLaubkUXThdO1Hp/r77p4/Os1RtgWS0OESrVitpp5SpUYi/CRNzc7WipUlRhDg4JcAtGBUOolBL2LIykX6nETCUMZ+73nLj9zS2M9/4d/366JYDBHfco9r3GmN0DPm4kHftuZ4z5kKQfleRI+pi19h/f9fkVST8r6cHeWv6ptfbfDLJw5Mvrm01Vi45O9U4uO7lQUrXo6PWtpt7/yMmMV5etUdrfVqpFbecrVBprLwIGdXO3PRcnv0nR/LWiU6D9LR3sWRjJzd2OaiVHS3NQLSkxUylBc7/nxJVKrjP+oG5JnAAHDOHIdyxr7cg1f8YYR9K/kPTNkq5K+kNjzMettV/c97Lvl/RFa+2fN8asKTqp4N9aa3OVqH/+6rZ+96UNvefCqlbmYPjrKK5utXThRFWmVx1gjNEDJ6u6usUJcPGg7toQlUor1XxVKo2zFwHDWN/taHkOTn6Lld0ClUopYM/CqG7stnV2udK/Hsq7xQqhUhLYc+5U3SZWqRQQKgGDGi/KPdr7JV2y1l7uhUQ/L+nDd73GSloy0TvnoqRNSbl6Z3n29W19+F/8V/3aczf0iS9cz3o5U8kLQt3cbfdb3mIXTtS0vtuZ+xueVjdQwQx3ROpKraiuH6rdq3ICMJgbc1SpJEX7SmfO91hgmtzcac/NkG5JWiwXaX9DIjoJhUpOr9KJSiVgcGmGSuclvb7v11d7H9vvxyS9Q9I1SV+Q9APW2lxd3f7c01dULTp6/8Mn9dwbO7q118l6SVNns9GVlbS29Obq3LXFsmzv8/Os5QWqFp2hnlrGFXE5G9YNpKrtBdppeVqeo4rSklOQR/sbMDVu7LZ1bnkuupUkRTOVukHYn4cDjKrTe5A6bvsbM5WA4aUZKh10B3z3T+efkfSspPslfaWkHzPGLN/zhYx5whjzjDHmmY2NjaTXmZp6x9d/+Pw1fet77tM3veOMnILRH7y6mfWyps7tehS0nV4svenjp3q/vlWf7yCu2Q1ULQ1XORGHSnlqgQPStr4b7TXz1P5GpRIwPay1Wt/t6OwchUqLvdlRjQ6hEsZzZ6bSmJVKhTunvwEYTJqh0lVJD+z79QVFFUn7fa+kX7KRS5JekfT2u7+QtfZJa+1Fa+3FtbW11BactN97aUPNbqC/+FUXtFQp6oGTNb1yq5H1sqZOfOznqYU3l3ufXox+fZtKJVWLw/2orlajQI5QCRjczb3o1KXlOWt/m/cWY2BabDU9dYNwrkKlhV6oRAscxhW/lxULVCoBk5ZmqPSHkh43xjxijClJ+nZJH7/rNVckfZMkGWPOSnqbpMsprmminn19R0XH6L0PrEqSHjpZ0/WdFhfwd7ndiE46uft0s0rR0ULZ7VcyzatWN1BtxEql7eZ8B3LAMOKjvJfmrP2N09+A6XBjJ9qDzq3MT6gUVyrtdXgIhvHElUrOuDOVOP0NGFpqoZK11pf0NyT9R0kvSPp31trnjTHfZ4z5vt7L/pGkP2aM+YKk35L0d6y1t9Ja06R9/uq23n5uWZXeqV0PnaoptNLrnGj2Jrfq3X5V0t1OL5T6lUzzquUF9wRux6H9DRhefEM3X5VKDg86gCkRV0vO06Du+GAEKpUwrngu17jtb26v0olKJWBwqV45W2s/IekTd33so/v++ZqkP53mGrIShlZfuLqjb/vK+/sfe/DkgiTptdtNPba2mNXSps7teufQ78epxbJeWt+b8IqmS7Prq1ocMlSqESoBw1rf66jkFob+eZtlJdcQKgFT4uZOHCrNX6VSvUOohPF0/VCOMSoMcbDNQfqVSgGhEjCoNNvf5tortxva6/h674XV/seqJUdri2W9QaVSX9cPtdv2deqwSqXFkvba/tyeChJaq7YXDl2ptFR2ZYy0S6gEDOxm79SlYU5anHUlx6H9DZgSN3otuGeW5ihUqhAqIRkdP5QzZpWSxEwlYBSESil57o0dSdJXXFh508fPLJe1MeftXPttNeMh3aUDP3+y9/GtxnyGI+3e8ai1IUOlQsFouVLUNqESMLCbu+25ajuRokHdQWipVgKmwM3djk4vllRy5+fyfCmeqUT7G8bU8YN+IDSOOJji9DdgcPPzrjVhL6/XVTC6p63r9GJZm40O6XdP3J61cshg3HmfDdTqRqHSKO04q7Xi3H7fgFGs73Z0Zo7aTiT1b17jvQZAdm7utueqSkmiUgnJ6Xihis74t7ZUKgHDI1RKySu3mzp/onrP06a1xbJCK202qFaS9oVKNUKlgzTjUGnISiUp+t7N6/cNGJa1Vjd22zo7Zzd05d4FeNPjhg7I2o2d9lyd/CZFD80KRmoQKmFM3SBMplKJ09+AoREqpeTVWw09fGrhno+vLUWtFbfqnUkvaSrttDwZScuVg0OlpUpRRtJOaz5DuFbc/jZCpdJKtajtJqESMIh6x1ezG8xl+5skNTpUKgFZi1pw5ytUMsZooezS/oaxdbywHwiNIz79jUHdwOAIlVJgrdWrtxp65PS9odLp3kDqjT1CJUnaaXpaqriHvgk4BaOliqud1nxebMQtKZURK5UY1A0M5uZutCfPW5VAHCo1u/O5xwLTouuHut3ozl2wLUVzlWh/w7g6fpBI+9udSiVmKgGDIlRKwe1GV3sd/8BKpWrJ0ULZ1QaVSpKiSqXlQ+YpxaI2rvmsVGr2B3W7Q/9e2t+Awa3P4alL0v5QiUolIEvre9EedG7OKpWkaK5SnUoljCmp9rdiPKibSiVgYMPfqeJYr95qSNKBlUqStLZYov2tZ6fl6cwxT+VWaiXd2GlNaEXTpdWrHhhlUPdKNTr9zVo7V0ekA6O42buhO7tc1iu9PXwelBwqlYBRPPX0lXs+9pEPPDjy17uxE+1B961WR/4as2qRSiUkoOOFcp0E29+oVAIGRqVSCuIbkocPCZVO1ErMulHUJrjT8rR6XKVSxdVOLxyZN61uoJJbGKlHfLVWVBBaNahAAI51YycK+uf19DcqlYBsXY9DpTlrwZWkxUpRe4RKGFPHD/uB0DhKbnTN3aVSCRgYlUopeH2zqYKRLpw4+GnTai2adROENpGBcrOq7YXqBmH/hLfDrNRK8gKrlheM1AY2y1peMNKQbunNJ+ctlufr+wYM6+ZuW4tld+5+VvqhEoO6gUzFlUrzMqh7f6XXZqOrm71/f2BUSc1UujOom0olYFBUKqXgje22zixVDt3YVqslWUl77fmuVtruzUlaqZWOfN3+cGTeNLuBqiMM6ZbufN+2m/M5jwoYxvpeey4H5JZ771MN2t+ATF3faatWcrRcma9gW5IqbkEdn2Ab4+n6ycxUcpmpBAyNUCkFN3Zbum/18CdNK7X4Zn/+QpL94uNjj7uAWul9fncOT4BrecFI85QkaaUahXXzGMYBw7q525mbCoH9irS/AVPhxm5L51YqczkDsewW1PapCsF4kmp/i4sCPGYqAQMjVErB9e227l85fNDiahwqzfnNfhwqLVWObn9b7H2+3pm/71crgUql3Tn//wwYxI2d9lyGSm7BqGAY1A1k7fpOey7nKUlSueio64cKQypDMLqOn9SgbiqVgGERKiXMWqtrO60jLwxW4wqSOW9Lik/6OG6GSfz5eTxuttUNVBs1VKIiDhiItVbre+1jT6LMI2OMSm5BDWYqAZm6sdPWueX5O/lNiiqVJNpwMZ7k2t96lUrMVAIGRqiUsO2mp7YX6twRoVLJLahWcua+Uqne9lR2C/1BsYcpuQWV3cLcnQxirR2z/W1+Z1EBw9hqevICq7NLc1ol4Doc5w1kyA9Cre915rZSqeJG1znsQxhHxw/6gdA4ivFMJSrngIERKiUsPhL2/tWjnzatVotzX0Gy1/EHPmlpsez22+XmhRdY+aFVdcQT7xZKjtyCIVQCjnFtuyVJuv+IWXh5VnYLc1kJCkyLW/WugtAe+UAyz8rF6HaEfQijCkIrL7DJVCpx+hswtPk7YiJl13eim5Pjnjat1kq6Ve9MYklTa6/ta3HAU06WKu7cPcFqeVE7Sm3ESiVjjFaqRUIloGf/Edaxj3zgwX2h0ny2nlSKVCoBWRr02jGvyr1KpXmrSEdyur1B70lWKnnMVAIGRqVSwq4NWKm0XJ2/ypu71du+lgatVKoU5+77FQ/OrYw4U0mKWuDmvc0SOM68h0rz2F4MTJMbvWvHea1UqlCphDH1Q6UEKpWMMXILhplKwBAIlRJ2fbslt2B0evHoga9LlaJaXjDXG9Zex+uf7HacpbI7d6e/tb3o/41RZypJ0bBuTn8DjvbGdktlt6BTC6Wsl5KJctFRvc0+AWQlHp1w3xEnB+dZmZlKGFPHj6r7kzj9Lf46zFQCBkeolLAbu22dWSrLOSYpX5rjE82k6ESFthdqaYj2t7YXzlUI1+61v8VP8EZB+xtwvGvbbZ1frcqYZC5GZ03FLXAzB2Toxm5bJbegE7XBHrTlTXz627xeE2N83d79gZPQ+3ixUJirew5gXIRKCdvY62ht+fjy5aVehc7enD4djm9gBm5/m8MQ7k6oNGb725wPhAeO88Z2a25b36Re+9sc7a3AtLm+09Z9K5W5DbbjQd204WJUd2YqJVipxEwlYGCESgnb2Oto7ZjWN0n9Cp3dOb2Qj8OhYQZ1S/N1wdHuvUGOEyqtUqkEHOvadmtuT36Toj2m2Q0UUOoPZOLmTlvnBnggmVdx+1tjjq7xkKx+pVIhmVtb1ynID6lUAgZFqJSwW/WO1pYGD5XmKSTZL34qvjjEoG5JczX3oxNXKrmj/5guVYqqd3xZy80icJCOH2h9rzPflUpF5pkAWbq+25rbk98kySkYFR3DHoSReX50nZvEoG5JKhYMp78BQyBUSpAfhLrd6OrMAKHSQtlVwcxv+1ujO1yotFCKn2IFqa1p2rS9QG7BjHU86lLFVRBaNbvz830DhnFzpyNpfk9+k+4E19zQAZMXhlY3dzo6N6dDumNl15nba2KMrxtE17nHzbQdlOsU5DNTCRgYoVKCNhtdWauBKpUKxmix7M7tHItm7+alVhosVIpfF4dR86Dthf0KglHdmd01P983YBhvbLckSefnOFTqVyqxTwATt9nsqhuEc12pJEWHkszrSAiMrxPPVEosVDLyaAkHBkaolKD1veiJ9yChkhTd8M/rU5lGN1DRMSoN2NpVcgsqOmauKm5aXjBW65u0r81yTv8/A45zrRcqzXOlUv/kpQ77BDBpN3bakqSzczxTSYpmu/EADKPqJhwqFQtUKgHDIFRK0MaQodJcVyp1/YGrlGILJXeuhjh2/EDV0riVSvM9EB44TlypNM9VAnF4Pa/vR0CWrrEHSYpCpV0OFsGI4vlHzhgjI/YrusxUAoZBqJSgfqg0wOlvUnTDP68X8Y1O0J+TNKha2ZmrSqW2F6riJtP+tkulEnCga9stnV4sj3XK4qyL29/m9f0IyNLVrShUunBifqslpbhSiWsVjCauVEpsplKhII9KJWBghEoJ2qgP3/7W6PgK5/BkrmbXV23AId2xhZI7ZzOVApWL4/2ILvfb3+bn+wYM443tls6vUiEgMagbyMLVrZaqRUcnF0pZLyVTFZeZShhdPKg7sfY3x8inUgkYGKFSgjb2OlquuAM/8V4sO7LSXFXfxJrdQLVhK5VK81apFIxdPXFnUDdP/4CDXNtuzfU8JWnfTCVu6ICJu7rV1AMnqzImmZvhWVWlUgljSHqmklsoyA+pVAIGRaiUoI29zsBVSpK00KvUmac5QbFG19fCkDOVauX5mqnU9sMEB3XPz/cNGJS1Vte223MfKsUHJuzN0f4KTIurWy1dOFHLehmZKxcdtb2wHw4Aw+jGM5WSPP2NSiVgYIRKCbpV7+jUgPOUpGhQtzR/LQdBaNX2QtXKw1XhLJQcdfxwLp4cBKFV1w/HrlSqlRw5BcPTP+AArW6glhfMfahUMEaLZZdKJSADr281536ekiRVi/GBAVyvYHh3KpUSGtTtUKkEDINQKUGbja5ODdETP6+VSs3eXKShK5V6r5+HFriOH/07jhsqmd7NIpVKwL22eycNzftMJSmqaqx3uJkDJmmn5Wmv7RMq6c71DnOVMIrkB3UzUwkYxnB39TjSVrOrE4RKx4pDoWFnKsXfr3kIldpe9OaYxIlUy1VCJeAg282uJI1cqfTU01eSXE6mCJ+Bybu61ZQk2t9053qHSiWMIj6pzXWSGtTN6W/AMKhUSkgYWm01PZ2sDR4q1UqOjKR6J/8hyX7xCW4LQ57+FodQzTkI4dpeXKk0/o/oUrnIRRpwgNuNKFR66ORCxivJ3mLFnbtWbCBrV7dakkSlkvZVKrXYhzC8rh/KKRgVEhp47zpGfkilEjAoQqWE7LV9BaEdqlKpYMzcDZ+WpGZnxEqlXvtbYx4qlRJqf5OithbKyYF7bTa6WqkWtVIrZr2UzFGpND2MMQ8YY/6LMeYFY8zzxpgfyHpNSEccKj1ApVL/IRoPwTCKbhCqmFCVktSrVGJoPDAwQqWE3G50JGmomUqStFh25u7pcFypVBv69LdepVI3/9+vTtz+5iYRKhW5WQQOcLvR1cOnuJmT4plK7BNTwpf0t6y175D0QUnfb4x5Z8ZrQgpe32xqoeRolWB730wlQiUMr+uHKjnJ3dYWHSOPSiVgYIRKCdnqzeYYplJJiqpvGnMQkuw36kyl+PWNOWgXbCXY/rZccXnyBxxgs9HVQ6dofZPE6W9TxFp73Vr72d4/70l6QdL5bFeFNFzdaunCiZpMQi07syx+iMZDMIyiG4QqJfAgNuYWCvKZqQQMjFApIZuN6KZ9mJlKUjRXaP7a33yV3IKKQz5RcAsFld3CXFQqxTOVygm1v3GRBrxZEFptN7t6iEolSVFFI5VK08cY87Ck90l6OuOlIAVXt5rMU+opFwsyhtPfMJquH6rsJndb6zqc/gYMg1ApIZu99rcTC8OVMC+W56/loNENtDBklVJsoezO2elvCQzq7t0sWsubIxDbbnYVWlGp1BO/F4WU+08NY8yipF+U9IPW2t27PveEMeYZY8wzGxsb2SwQY7HW6o2tFqFST8EYLZZc7baorMbwun4KM5VCKpWAQREqJSSuVDq1UB7q9y2UXbW9UP4cbVzNrj/0PKVYreTMRWVXxwtUdIzcQhKhkqsgtHMRxgGD6p/8RqWSpGifkKT6HFSCzgJjTFFRoPRvrbW/dPfnrbVPWmsvWmsvrq2tTX6BGNtuy9dex9cDJ9mDYstVZkBiNF0/VCnJSqUClUrAMAiVErLV7KpSLKg67Ilm8fDpOZgTFGt2g/6/97AWSnNSqeQHiQzplqJKJYk5BcB+t+tRdSmhUmSx3AuV2CcyZ6IBOz8h6QVr7T/Lej1Ix+tbTUmiUmmf6LRaKpUwPC9IOFRyCvJDS5U/MCBCpYRsNrpDz1OS7pyANg9BSazRGbNSaQ6epLe9MJF5StKdCgSGdQN3rO91VCkWtLY4XHVpXi3GlUpzUAk6A75O0ndJ+kZjzLO9v74l60UhWVf7oRLBdmy5UuRaBSPpBgmf/laIWul8WsKBgYx2Z497bDa6Q5/8Jt050Wwehk/HmuPOVJqDqq62FyQyT0m6Eyox/BK4Y2Ovo7XFMqcu9cSVSlQ0Zs9a+3uS+B8z565utSRRqbTfUsXV9Z121svADOr44dAHAB3F7X0tP7BK6BkvkGtUKiVks9HVybFCpfwHJZLU8QN1/FC18uiVSt0g7J+OlldRqJRs+xsl5cAdG3sdnVmqZL2MqRHvE1QqAZPx2u2mlsquVqrDHfCSZ8vVovY6XKtgeEm3v8VDv7vB/My8BcZBqJSQreaoodJ8tb9tN6OLhdqolUq979dWs5vYmqZR2wsTC5WWK1QgAPu1uoH2Or7Wlmh9i/UHdbNPABPx6u2GHllboFpyn6WKq90WexCG1/VDlRMNleJKJUIlYBCESgnZbHR1YqSZSvPV/rbZO3FpYcSZSvEg9Pjr5FU0qDup9rd4UDdP/wBJ2tiL2ivOECr13Wl/Y58AJuHyRkOPnF7IehlTJZ6pxHBkDCvx098cZioBwyBUSkDXD7XX9keqVCo6BRUdMzeVSlu9MKg26ulvvRufrUa+b3ySbX+jUgnYb30vOvmNSqU7GNQNTE7bC3Rtp0WodJeliqvQSo05uSZGcrpBsjOVioXoa3lUKgEDIVRKwHavFWuUUEmKWuDmplKp970a5/S3/V8nj4LQygtsYoO6ayVHTsFQgQD0rO915BbMSIcr5FVcPUr4DKTvymZT1opQ6S7LVSqrMRrPT/b0t36lUkClEjAIQqUEbI4dKjlzV6k0zulv+79OHnV6Q8iTqlQyxmip4nKzCPRc227p3EpFBWaZ9DkFo8WyS6USMAGXNxqSCJXuRmU1RtVNeFB3//S3kEolYBCjlYvgTTbrUcAxykwlab5Cpc1GPKh7xJlKxfzPVGrFoZKb3Bmm8xwqGWN+UtK3Slq31r77gM9/g6RfkfRK70O/ZK39Xya2QEyUtVbXdlr6ivOrWS9l6iyWXQZ1AxPw6u0oVHp4X6j01NNXslrO1FiOT6ttUak0TYwxjqRnJL1hrf3WrNdzkE7CM5WKheihk0elEjAQQqUExJVKpxZHb3+7vtNKcklTa6vZVdktyCmMViHgFIyqRSfXp7+1/eipSFKVSpK0VC7Oczn5T0n6MUk/c8RrfndaL5SQrO2mp7YX6v7VStZLmTqLFSqVgEl4ZaOh04ulfoiCCJVKU+sHJL0gaTnrhdwtDmNb3UCX1ut6/MxSIl+3X6lEqAQMhPa3BMStWFQqHW+n5fXnIo2qWnK0k+OnWO1++1tyP55LFVe7c3qRZq39HUmbWa8D0+FaL8C/f6Wa8Uqmz2LZ1R6hEpC6l9b39JYzi1kvY+rEM5V25/ch2NQxxlyQ9OckfSzrtRwlCK3cER9YHySeqdRlUDcwEEKlBMQtXau10Z441UqOWt1A4RwcobrT8votbKOqFvMdKiU9U0mSlipFnvwd7WuNMZ8zxvyaMeZdWS8G6bm23ZaRdHaZSqW7RW2y+d1bgWlgrdVLN5OrqMiTuFJpXh+CTakfkfS3JU1tuhKEVlaSU0jutrbUr1Sa2n9tYKoQKiVgs9HRcsUd+SjLWsmV1Z0KlTzbaXmqJFCptN3M741P20u+/W2Zm8WjfFbSQ9ba90r63yT98mEvNMY8YYx5xhjzzMbGxqTWhwS9sd3UmeVyorMX8mK5Usx1YA9Mgxu7be11fL31LJVKd2Om0nQxxsTzKD9zzOsyvTYKwuihfKKVSr2v5Yf5f+APJIGr6gRsNj2dWiyP/PvjdrB5aIHbaXmqJVCplOcLjrYfD+pOtv2NSqWDWWt3rbX13j9/QlLRGHP6kNc+aa29aK29uLa2NtF1Ynyhtbqy2dRDJzlx6SArtWKu91ZgGrx0sy5JevwslUp3qxQdlZwC1yvT4+skfZsx5lVJPy/pG40xP3v3i7K+NopPaBt1XutB4plKHpVKwEAIlRKw1ejqxIitb9J8hUrbTU9VZiodKT79rZxw+1u948vOQYvlsIwx54yJzpY3xrxf0b54O9tVIQ03d9tqe6EeOlXLeilTaaUaVSqxTwDp+fLNPUnS48xUOtBy1WWm0pSw1v5da+0Fa+3Dkr5d0n+21n5nxsu6R79SyUkuVCr2vhaDuoHBcPpbAjYb3bFOEqqVov8MzW6+n8xYa7Wb0Eyl7d6NTy8LyJWOF6romESfuCxVXAWhVbMbaKE8Xz/2xpifk/QNkk4bY65K+mFJRUmy1n5U0l+S9NeMMb6klqRvt9xV59Jrt5uSpIdOUal0kJVqUV5g1fKC/vsSgGS9dLOuUwulsSrc84wZkBiWn0r7W2+mUkilEjAIrhoTsNno6l33j37K5rxUKrW9UN0gHDtUqpUcBaFVoxtoMYcBSdsLxv4e3W2pN6dgr+3PXahkrf2OYz7/Y5J+bELLQYZeu93QcsUdq7I0z1Z6Jy9Fp3TO1z4BTMqLN/f0OPOUDrVccWnDnULW2k9K+mTGyzhQ0KsmSnJQd1yp5FGpBAyE9rcEbDW7OrFQGvn336lUyneoFLesjT2ouxe4bDe7Y69pGrW9INHWN+nOiSoM68a8CkOrlzcaevj0Qi4rHJMQh0p5PggByJIfhHrx+q7edf9K1kuZWlGlEnsQBufbOFRKfqYSlUrAYHgUOaa2F6jjh/2L8VGUiwUZ5b/9LQ6Vxn0CHs9k2ml5unBi7GVNnbYfJjqkW+KYXsyfp56+8qZfv7HdUr3j660Mxz3U/kolAMm7fKuhjh/q3edHr27Pu+Wqq+s7rayXgRkSVyqlcfoblUrAYKhUGlN88T1OqFQwRtWSk/tKpbiyKImZSpK0k9On6W0vUCWl9jeGX2JevcRw3GMRKgHpeu6NHUmiUukIK9WSdlo8AMPg4mqiJEOlIqe/AUNJNVQyxnzIGPMlY8wlY8wPHfKabzDGPGuMed4Y89tpricN8cX36pgzOmolN/ehUvy9GjtU2leplEdtL0w8VFrut79xoYb59KWbe7p/tdIPWHEvQiUgXc9f21XZLejR0xwWcJjVWlE7rS6nUGJg/UHdTvIzlTj9DRhMau1vxhhH0r+Q9M2Srkr6Q2PMx621X9z3mlVJ/1LSh6y1V4wxZ9JaT1ri2ROr1dFnKknR8Ol5aX+rJjRTKa83PlGlUtLtb/Gg7nx+z4Cj7LU9Xbnd1J98+8y9xUzUSu/hCENygeTsb8X9zy+u68xSWf/umasZrmi6cQolhuWn0f5GpRIwlDQrld4v6ZK19rK1tivp5yV9+K7XfETSL1lrr0iStXY9xfWkIm7pGqf9TYpCpRaVSgOJQ6ntnN74pNP+RqUS5tdz13ZlJX3FeVpOjrJYclUw+Q3sgSwFodUb2y3dv1rNeilTbZUDAzCkoNf+luSg7n6lUkilEjCINEOl85Je3/frq72P7fdWSSeMMZ80xnzGGPPdKa4nFbS/DW6n5cmYaDD5OEpOQUXH5PLGxw9D+aFNPFSqlRw5BUOlEubSF67u6MxSWWeXK1kvZaoVCkbL1SI3c0AKbu621fVDPXSK1rejxNfT7EMYVL/9LdFB3b3T36hUAgaSZl3pQT/Zd8e9rqSvlvRNkqqSft8Y82lr7Zff9IWMeULSE5L04IMPprDU0fUHdY8dKs1H+9typajCmMd5G2O0ktMbn7YXvXklffqbMUZLFZdKJcyd7WZXr91u6BvfQevbIFaqxVwG9kDWrmw2JUkPnaxlvJLpttIbJ7Hd6ma8EsyKNGcqcfobMJg0K5WuSnpg368vSLp2wGt+3VrbsNbekvQ7kt579xey1j5prb1orb24traW2oJHsdPyVDBR28A4aiVHXmBz3bu70/LGbhOMrVSLuZz70fGiarWkK5UkESphLv3R69uykt73wImslzITCJWAdFzZbGqp4o5d2Z538XViHq/xkI54plKS7W/GGDkF0z9ZDsDR0gyV/lDS48aYR4wxJUnfLunjd73mVyT9cWOMa4ypSfqApBdSXFPitptRUFIYcyOLhxHmuQUu6VApj0+x+pVKaYRK5SLtb5gr1lp99rUtPXJ6QScXxjtMYV4QKgHpeO12Qw+erMmMWa2dd7S/YVhx8JNk+1v89Tj9DRhMau1v1lrfGPM3JP1HSY6kn7TWPm+M+b7e5z9qrX3BGPPrkj4vKZT0MWvtc2mtKQ3bCQUltd7w6WbXTyx4mTZJhkqrtZLW99qJfK1p0upVKo07d+ogSxVXu1QqYY68vtXS7UZXf+Kt01XhOs1WqkW9sdXKehlArmw1utpqevpjj53OeilTrx8qEW5jQEG//S2ZUGn/iY3PvbGTyNcE8i7VszqttZ+Q9Im7PvbRu379TyT9kzTXkaadlqeV2vhPwO+ESjmuVGp6iZ16slIt6qX1vUS+1jRp90KlcU/IO8hSpag3trlZxPx49vVtuQWjd3Pq28CoVAKSd2mjLkl6y5nFjFcy/apFJ7eHsSAddwZ1J/tAtmAMp78BA0qz/W0u7DS7/eNPx0H723DyOqi74/dmKrnJh0rLFZf2N8yNILT6wtVtvf3cUirtpHkVtRZ7spYLaSApl9brWq64OrNUznopUy86jKWUy2s8pMMPrIykhLvf5BaMQt4LgYEQKo0pqaCk2qtUauU0VLLWJh4q7bX9fslrXqQ6U4lB3Zgjl9branQDfeUDq1kvZaasVIsKQqtGTt+LgEkLrdXLG3U9trbIPKUBrdaK2snh3EykIwhDOQWT+M9XoWCU4/OTgEQRKo1pu+UlcpJHrR8q5fOmv9kN5Ic20VBJyt/pIO1UZyoVVe/4VCBgLnzu6raqRUdvPbuU9VJmSry30noCJOP1zaaa3YC9aAi04WIYfmgTm6e0n0OlEjAwQqUxhGFy1TdFpyC3YNT08vl0OB64mNyg7nze+LS9QCW3oEIKTzOXKq6C0Oa6xRKQogMPvnhtV+8+vyLX4W1uGP29ldYTIBHPX9uVUzB62zlCpUGt5nTEAdLhB1ZOwvOUpGimUt46IoC0cLU9hr2OL2uTC0qqJSe37W/xDUoS86ekO9/zvJ0O0vZDVdx0fiyXKtH3jBY45N1/eXFD3SDUex9gQPewlqlUAhJjrdXz13b0lrVFZrsNYaVGqITB+aGVm/RAJUlOQYRKwIAIlcbQD0oSOP1Nik68aOW0UmmHSqWBtL0gtQvPpUo0DJ5h3ci733rxpqpFRw+fWsh6KTOH9jcgOV94Y0dbTU/vun8566XMFNrfMAw/DNMJlQztb8CgCJXGkHRQUis5uW1Nir9XywlXKuXtoqPjhamHSruESsixMLT67S9t6K1nF1NpI827O3srQ3KBcf3CZ67KLRi9+zxVk8NYrZZU7/jymJKMAQQpzVSKBnUTKgGDIFQaw3bvojuJQd1Sr1Ipp6HSbsIBXL9Fo5mvG5+2H6iSwpBu6U772y7tb8ixz13d1u1GV287R2XAKPIa2AOT1vYC/cqz1/Su+5dpfRtSfF2dt8NYkA4/sHJTmKnkGKOASiVgIIRKY4j7vZObqeTmtv0tDuBWEgrg8nrj0/YCld10Lj6X++1vhErIr9976ZaMkd56ZjHrpcykxbIrp2Byt7cCk/brz93QTsvTVz10IuulzJy8zs1EOoLQykllphKVSsCgCJXGEF90JzV8upbnQd0tT07BaKnsJvL1yq6jatHJ3SDHdqrtb/Gg7nx9z4D9Pv3Kbb393LJqCe0188YYo+WKS6gEjMFaq5/4vVf02NqCHlsj4B7WSk7nZiIdXlozlQpGIaESMBBCpTEkPSeoUnTUDUL5Yf56yHdanpYrrkyCM05Wa/kb5BgN6k6r/Y1KJeRb1w/1mde29MFHT2a9lJm2Witpp8U+AYzqD1/d0hfe2NH/7b95hNluI1jtjzjI1zUe0pHaTCXa34CBESqNYbvZVaVYSKyypFaKvk4eq5V2Wn5ibYKxvJ0O4oeh/NCmVqlUKzlyCoZKJeTW569uq+2F+sAjp7JeykxbztneCkzaT/zeZa3Wivq/vO9C1kuZSfGpytscGIAB+IGVk8ZMpYJRDp/zA6kgVBrDTsvTarWU2Ner5jpU8lIJlfLUb9/2oneuipvOj6UxRksVl0ol5NbTr2xKkj7wCJVK41ipFnN3CAIwKa/dbug/ffGmvvMDD/Wv6zCcFSqVMAQ/tKm0v3H6GzA4hk6MYbuZbFBS7VWo5HFY906zm1ibYGylWtSVzWaiXzNLnd5/9zRPiSFUQp790ZUtPba2oBMLyYX982ilWtSV242slwHMpJ/+1GtyC0bf9bUPZb2UmfPU01ckqX8j/7sv3dL3fN0jWS4JMyBIa6aSEe1vwICoVBrDTstL7DQzKe/tb16/nDkpeWt/61cqpRkqlYu0vyGXrLV69vUdvfeB1ayXMvNWqgzqBkbR7Pr6Pz/zuj707vt0drmS9XJmllMwqhQLaubwISuS56c0U4lB3cDgCJXGELW/JV+plMc30aj9LdnCuNyFSn70372c0qBuKapU2qVSCTn0xnZLt+odvY9QaWyr1ZJ2Wh4X08CQfuXZa9pr+/puqpTGVi3m90RkJCutmUoM6gYGR6g0hsTb33JaqRSGNrWZSs1uIC/IxxS9dtz+5qbZ/lak/Q259LnXdySJSqUErNaKCi0nRQLDsNbqZ37/Nb393JIuPnQi6+XMvGqJUAmD8dNqf2OmEjAwQqUxRC1dyQUllaIjo/zNVKp3fYVWyYdKve99XqqVJtH+tlxxaX9DLn3u6rZKTkFvP7ec9VJm3qnFqFX5dqOT8UqA2XFls6kXru/qu7/2YRmT/A3uvKkV3dxdDyMdQUqDugmVgMERKo2o4wdqeUGic4IKxqhSdNTM2ZOZ+PSONCqVpDyFSvGg7nTb36g+QB4998aO3n7fkkopnZ44T0703te2OAEOGNjTr2xqqeLqL7zv/qyXkguVUv6uh5G80FqFVnLSmKlkjELa34CBcPU9ojjISPpEs6jcN183/fH3aqWa7KDu5byFSvFMpZTb3+odX5Y3SeSItVZfvL6rd91PlVISTi2UJUm364RKwCC8INQXr+3qW99zv2olDlZOQq3oUKmEY/lBdD3rpjFTiUolYGCESiOKq2+SHNQt9QYT5uxNdLdFpdIgOl6oklOQk0IJb2yp4ioILU//kCvXd9rabnp6532ESkk4sRDtrVQqAYP50o09dYNQf/4992W9lNyIH7LyEAxHiUOftNrfQiv+HwQGwOOUEW2nFJTUcjiYcCflUGk3J6FS2wtSbX2TokolKRrAu1Dmxx+z56mnr9zzsTNLUWXNO6lUSkS/UqlBqAQM4gtv7Gih7Or9j5zMeim5USs50YEBHV/LlWSvH5EffhjNI3VTaH8r9Gaj+aFVMYWvD+QJlUoj6lcqJTioW1IuZyr1A7iEv1d5q1Rqe4HKKQ7plqJKJUkM60auvHB9V8ZIb2NIdyKqJUfVoqNN2t+AYwWh1Zdv7umd9y3JdbisTspCr41wu8H1Cg7np1ypJN1psQNwOEoVRhQHJasJzwmqlfLX/pZ2pVIc8M26th+qkvKQ4ThU2iVUQo588fquHjpZ0yLVdyO7uwKs7Ba0SfsbcKwrm011/FCPn1nKeim5UitHD9luNzp68FQt49VgWsWBj5PCTKW4OMkLQ1WV7kNfYNbxSGVEaQUl1V77W55OG9hpeXILRgulZDfkolNQreT0A75ZF7W/pV2p1GsZ5AQ45MhL63W97Rw3dElaKLvapP0NONZLN/dUMNJbzixmvZRciSuVmO2Go/Tb31KoVCpQqQQMjFBpRDvNroy5U/mRlFrRkZXU9cNEv26WdlqeVqpFGZP8hr9SLeao/S1MPVRa7re/ESohH4LQ6rXbDT22xg1dkhbKDqESMIAvr+/pwZO11N+/500895FTKHGUtAd1S5If5OeeDEgLodKItluelivFfoqdlGqvmidPw7p3ml7iFV2xPIVKnYkO6s7H9wzYbHTlBZZQKWG1EpVKwHFa3UDXt9t6jCqlxNV618NUKuEo/fa3FAZpO72H4V1CJeBYhEoj2ml5iQ/plqRqMXoy08zRXKWdlqfllEKl5RyFSm0/UMWd1KBuKpWQDxt7HUnipi5hCyUqlYDjXNlsyEp6+NRC1kvJnbJbkFMwnEKJI90Z1J3CTCXa34CBESqNaLvpaTWFoCSXlUopBXBSVKm0m4NQKQitvMCmfvpbreTIKRgqlZAbG/VeqLTGTV2SFsqumt1A7Rw94ACS9urtpgpGeuAEg6STZkw0i3OLUAlHCCYxUymkUgk4DqHSiNKqvolDpWY3P5Uk8UylNOSl/S2+cUu7/c0Yo6WKS6UScmNjr6Ozy+V+ayeSEQ/JpVoJONxrtxu6f7WqUsont86r6MCA2b/GQ3q8XhWRm2L7m0elEnAszl8e0U7L0wMnk38yVetVqrRy9HSYUOl4d0Kl9Ad9EiohTzb22mPNU3rq6SsJriY/FnrHeW82urp/tZrxaoDp44ehrm619MFHT2W9lNyqlRxtNjpZLwNTLB7U7aQ6qJtQCTgOj1ZGtN3saqWafCaXt/a3MLTabacbKjW7gbwZH6LX7p32l/ZMJUlaKhdpf0MuWGu1Ue8wpDsFNSqVgCPd3OnID20qDxgRqZVcbTW5XsHh0pypVIgrlWh/A45FqDSCMLTRnKBqKfGvXXQKcgsmN6HSXtuXtUo1VJI089VKk2p/k6JKpV0qlZAD9Y6vthfqLQzpTlx8nDehEnCwq9tNSdJ5KvlSs1B2dbtOpRIO56c4U4lKJWBwhEojqHd9hVapDZ+ulZzctL/FYU9ap7/lJVTq9P57pz2oW5KWKkXa35AL/ZPfqFRK3ELpTvsbgHu9sdVSreToRErXgoj2od22P/PV6EhP0K9USmNQd/R3n///gGMRKo1gp5luUFItOWrmpFIpDnuoVDpa24vb39L/kVyuuLS/IRfW41DpDCe/Ja3SOymSUAk42BvbLZ1frcqY5G9mEYkrJrea7EM4mN8f1J389XN/UHdIpRJwHEKlEcQBxmpaoVIxf5VKaYVKy3kJlXwGdQPD2qh3VHILOrdcyXopuVMwRidqRd0mVALu0fYC3dxt6/wJWt/SVOtVTG5xAhwO4U9gULfnU6kEHIdQaQTbzXSDkmrJzc1MpX4Al1J5ePzfYHfWQ6WJnv5WVL3jy1qevGC23drraG2xTKVASk7UStoiVALu8aUbewqtdP8KoVKamO2G4/hhKKOUT39jUDdwLEKlEdwJSpIf1C1JNSqVBpan9reiY1J5U7zbUsVVENrctFhifq3vdbS2VM56Gbl1cqHEzRxwgBdv7EqS7luhSjJNC5xCiWMEgZXrpHPt3D/9jUHdwLHcrBcwi7Zb0ZtbWtU30UylfLQnTSxUmvEjZ9teoIqbfpWSFFUqSdHJfPFTQGDWdPxAOy2PUClF9Y6v9d2Onnr6Sv9jH/nAgxmuCJgOL1zfU8kp6MRCOg8XEamVewcGMFMJh/BDm9oDWSqVgMFRqTSCtIOSasmRF9hcnDaw0/JUdIyqKbV1ldyCqkVn9iuV/HAiJ79JUaWSJO0yrBsz7FY9uslYWyRUSstC2VUjJw84gCS9eGNXZ5fL/UoGpKNfqVQnVMLB/NDKLaRzO+tQqQQMjFBpBDtNT2W3kNr8mziAyUML3E7L00q1mOrMk5VqceZDpY4XqFKczI9jHCpxAhxm2Ubv5DcqldKz0JvvFzJ/Deiz1urFG3s6xzyl1DkFo6WKy+lvOFQQhnJTqlQqxJVKhErAsQiVRrDd9FKrUpKiSiVJuZh5s9Pq9k9oS0seQqW2F0xkSLd0p/1tlxPgMMM29toqGOkU7SepWSg7slJuDo4AknBjt63tpsc8pQk5tVDiFEocyg/Tm6lE+xswOEKlEey0vNTmKUnRoG7pzolgsyyuVEpTPkKlUBV3Mj+Oy/1KJUIlzK6NvY5O1EpyHd7G0hK3njQ67BVA7Es39iRJZ5cJlSbhxAKnUOJwfkD7GzANuBofwXarq9Vqek/H81WplH6otJyHUMmffKUS7W+YZRt1Tn5LWzzIv85cJaDv0npdknSG/WciTtY4hRKH88MwtUHdcVaVhxm3QNoIlUaw0/JTbemq9Z4O56HlYKflaXUClUq7sx4qTbT9jUolzLbQWt2qd7mpS9liHCqxVwB9l9brOrlQ4vTUCTm5QKiEw0WDutNtf/MIlYBjESqNYKfZTbX9LVeDulOePyXNfvtbEFp5gVV5QoO6ayVHTsFQqYSZtdXoKggtlUopW+wF0HXa34C+S+t1vWVtMetlzI2TCyVtNruyHBiAAwSBlZPWTCXa34CBESqNYDvllq5ysSCj2W9/C0OrvY4/kVCp0Q1m9klCpxceVtzJVCoZE52mQqUSZlX/5LdFQqU01UqOCoZKJSBmrdWljbrecpZQaVJOLpTU9UM1ZvyaGOlIs1LJGCPHmJm9vwAmidrdIXX9UM1ukGpLV8EYVYqOWt5sX8jvtX1Zqwmc/hb9b7zb8nRqBm8y2370ZjWp9jdJhEqYaRv1Xqi0FA3KferpK1kuJ7cKxmih7FKpBPTcbnS13fSoVJqgE70TPrca3X5LLhALwvQGdUtRCxyhEnA8KpWGFLdZpdn+JkXDume9Uin+XqVeqdT7bzGrLXDxKX+VCbW/SdJSuUj7G2bWxl5Hi2W3f6gB0rNUJoAGYvGQ7recIVSalFO9UOk2c5VwgDQHdUtxqET7G3AcQqUh7bSiN7W0q29qJacfNsyqiYVK1byESpOtVNrlRhEzan2Pk98mZbFCpRIQI1SavJNxqNSrUAX28wOrYkozlaQoVOpSqQQci1BpSHcqlUqp/jnVIpVKg5r9UKnX/jahmUqStFQpUn2AmWSt1cZeh3lKE7JYLhIqAT2X1utaKDm6b6WS9VLmxuneXn+LUAkH8EMrJ+32N59QCTgOodKQtpu9UCnloKRactSa8VBpu1fVtZJyq+DMh0r+5Nvflisu7W+YSY1uoJYXUKk0IYtlV/W2z8lLgKSXN+p67MyijEmvMgJvFu/1t+q0v+FefhimNqhbYqYSMChCpSFNqvqmWnTUykn722o13aquuBVxd1ZDpd5/5zKDuoFj9U9+I1SaiKWKq8DamX8/ApJwab3OkO4JqxQdLZZdKpVwoCDF098kZioBgyJUGlK/Uinl6ptar1IpnOGnw7S/Dabf/jbJQd2VqKWF6gPMGkKlyYpPW6oTQmPO1Tu+ru+09RjzlCbu9GKJSiUcyA+snBRnKrnMVAIGQqg0pO1ecLFUSb9SyUrqeLO7ke20PJWcQuphSdl1VCkWZjZU6viB3IJJ9UjUuy1VXAWhnfm5XZg/G3ttFR2TeliNyGIlCpX2mKuEOfcyQ7ozc2qxrFt7VCrhzfwglJVofwOmAKHSkHZbnpYrbqrHV0pStRRdyM9yy8Fuy9NytTiR2QMr1eLMhkptL5zoyW/SnVB0HlrgjDE/aYxZN8Y8d8jnjTHmnxtjLhljPm+M+apJrxGD26h3dHqxrAIzTSaiX6lEqIQ5x8lv2YkqlQiV8GZxBVGaD2UdQ6gEDIJQaUjbzW7qJ79JUfubpJke1r3T8rRSdSfyZ812qBRMtPVNiiqVJGl3PoZ1/5SkDx3x+T8r6fHeX09I+vEJrAkj2tjr0Po2QfFeQfsb5t2ljbqKjtFDJ2tZL2XunF4sEyrhHnE3h5ti+1t0+hujIoDjECoNKQpK0m+7iCtXmt7sXshP6nslzXao1PGDDCqVei0tcxAqWWt/R9LmES/5sKSfsZFPS1o1xtw3mdVhGG0v0HbTI1SaoGrRkWMMlUqYe5fW63r41IJch0vnSTu9WNZW06NiBG8SVyql2T3iMFMJGAjvjEPabnmpD+mW8lSpNMlQaTZvetpeqIqbTfvbLtUHknRe0uv7fn2197F7GGOeMMY8Y4x5ZmNjYyKLwx2XNxqyktYWCZUmxRijRU6LBPTyep3Wt4yc7j1I2GwwrBt3dP0JtL8xUwkYCKHSkHaaXv8I+zRV41BphmcqTTJUWq4WtTujlUptL1B5wu1vy/1KJW4UJR30iOvAWmdr7ZPW2ovW2otra2spLwt3e3kjmmlCpdJkLZZd1Tuzub8CSej4gV693SBUysjaYjR2YoNh3din0w+VGNQNZI1QaUg7LU+rkwiVirNfqbTdpP1tEC0v6P/3npQ7g7pn83uWsKuSHtj36wuSrmW0Fhzh5Y26jKJWCEzOYtllphLm2qu3mgotQ7qzEu/5zFXCfnGlUtrtb17ATCXgOIRKQ7DWTqz9regUVHTMzIZKQWi11/a1MoGh5lIUKtU7vvwZfJrQziRUolJpn49L+u7eKXAflLRjrb2e9aJwr0vrdZ1YKKnITJOJWqy4zFTCXItPfntsjVApC3dCJdrfcEf/9LcUB3W7BdMPrwAcbjJHc+VEoxsoCO3Eqm+qRUfNGW1/iytgJlmpJEUzgk4uTCbISoIfhPIC2293nJRayZFTMHNRqWSM+TlJ3yDptDHmqqQfllSUJGvtRyV9QtK3SLokqSnpe7NZKY7z8kaDeUoZWCpHoVJoeVqL+XRpvS5jCJWyEs9UolIJ+3V690hpz1RiUDdwvFRDJWPMhyT9qCRH0sestf/4kNd9jaRPS/rL1tpfSHNN49huRk9IVquTCS2qJWdmK5XiVrRJh0o7LW+mQqV4ZtakT38zxmhpTobvWmu/45jPW0nfP6HlYERhaHV5o66vefhk1kuZO4sVV6GVmjP6fgSM69JGXRdOVCf+AAiRhZKjslvQbUIl7NOvVGKmEpC51EIlY4wj6V9I+mZFM0v+0BjzcWvtFw943f8q6T+mtZakbDejoGQSg7olqVp0Z3ZQ96RDpbglcdbmKsX/fSfd/iZJy5XZnUOF+fPGdksdP2RIdwYWy9GlAi1wmFfPvLqp5UpRTz19JeulzCVjjE4vlml/w5v0T39Lsf3NMUYe7W/AsdIcTPF+SZestZettV1JPy/pwwe87m9K+kVJ6ymuJRHx6WKTmKkkRS1KVCoNZn+l0ixpd7OpVJJme7g55s+l+OQ32t8mLh7sz7BuzKMgtNrY6xBoZ+z0Upn2N7zJZAZ1FxjUDQwgzfa385Je3/frq5I+sP8Fxpjzkv5bSd8o6WtSXEsiticcKlVLjppbs3kRT6g0mJYXvSFmUVK/Ui32g1Jg2l262QuVuLGbuDuVSuwXmD9vbLXkh1ZnBth7qGRKz9piSVe3WlkvA1PkTvtb+jOVrLUyJr3wCph1aVYqHfSTd3fU+yOS/o619shyHGPME8aYZ4wxz2xsbCS1vqFNOiipFh3a3wa0PLOhUnbtb1QqYZZ8+eaeTi+WtVDmfIlJ47RIzLNLG3uSCLSzRvsb7tbxJzNTSZL8kGol4ChpXp1flfTAvl9fkHTtrtdclPTzveT3tKRvMcb41tpf3v8ia+2Tkp6UpIsXL2b2Ux3PVJrUoO5ayZEXWHlBOHNHaGdVqTRrlTft/qDuyf/3Xa4WtdPiJhGz4cvrdb31LCcvZaHsFlR0DKES5tKl9ahK8sxSJeOVzLfTi2VtNjoKQptquxNmRxwqOSnOVIoDq1m8FwMmKc2fjj+U9Lgx5hFjTEnSt0v6+P4XWGsfsdY+bK19WNIvSPrrdwdK02S71VXJKUwsAIhbomaxWmmn5ankTu57VXYdVYqFmau8yXRQd9XVbsuT5ZhwTLkwtHrp5p7eenYp66XMpei0yKJ227O1vwJJuLRe12LZ5eS3jJ1eLCm00laTaiVEOr1r6GLK7W+S5PlcKwNHSe2n0FrrS/obik51e0HSv7PWPm+M+T5jzPel9eemabflaaVWnFhPbRw0zOKw7p2mp5Xq5L5XUq+dqzlbNz2tbqCiY+Rm8PRjpVpUNwjV9jjVAtPtje2Wmt2AUClDS2WXSiXMpS/drA80TwnpOt37b8CwbsTiSqVimqe/9UKleH4TgIOlOpzCWvsJSZ+462P/f/buPM6t+6wX/+fRvow0mn2xx/saO3YWx87apHuaLqHQQpPSUigtBQoULr2UXi7tBX4XaC+0QFtKKKEtNC2la9IkTbPvseO48b7b4/Hs+4w02qXv749zNBmPZ5FmJJ1zpM/79ZqXPdKRzqMzo++c8+j5Pt+vzrPth0oZSzGMR1MIlWk6FzCjUsmKSaVYqmxT33Ks2CMonsoYUqUEzJgyGE/xE1gytdODWk+TTS01OKU37KbyCnid6J+IGx0GUVnlqiSv6ggZHUrVa9RX/hwOJ4FWg4MhU0ikMhCUdvW3mdPfiGh+nBxagPFoeRMlPqeW87Pq9DcmlRYXS2XgMTipZLVjRtUnl0jayEolwwQ8DoQ5/Y2qzMWxKKLJDFqD7KdktMYarZ8pK5UoJ57OwmGXks6KsDOpRJQXJpUKMBFLIeQrf6VSlJVKebFqUsnoSiWrHTOqPqf6w2gJuss+ptBrgm4HEuksoklOgaPqcaJfq5JsYVLJcNOVSkwqkS6RysBRwn5KAJNKRPliUqkAE7HU9NL15TDdU4mVSnkJWjCpFE9mDJt6FvToSSWL9aGi6nNqkE26jRbQx/PBSV7QUfU42R+GCJNKZlDrdcLlsGEozDGINPFUtqT9lIAZPZXYqJtoQUwqFWAilkLI6yrb/txOGwRAzIKfDBtVqTRpsaQSp78RLSyTVTgzGGFSyWABjzYde5AXdFRFTvaHsareB5eDp8tGExE01bg5BtG0eDpT8oVuWKlElJ+SNuquJKlMFpFEuqzT32wi8Djtlpv+lskqhOPpslZ1AVqSJJxII5NVJW3aV0yc/kY0v/v2dmEkkkA8lcXYVBL37e0yOqSqFdArGwcm2aybqseJ/klsZkLbNJqDbo5BNC2Ryk430i4VJpWI8sOPXvKUu/Aud/WNz2W33PS3XDPXcq6UB8xYzcwiSZJsViGRyho3/W3G6m9EZjWgT7fi9BNjBVmpRFUmnsqgcySKLa1MKplFc4CVSvSaeDoDZ5kqlZJMKhEtiEmlPOWSSuWsVAK0Zt0xi1UqGZWAy+1v3CJJpXAiDQUYNv3NbhME3A5WKpGpDYa1T6WbA26DI6luXqcdDptM/zyIKt2ZwQgyWYXNrUGjQyFdS9CDQVYqkS6R0lZ/KyWH5CqV2FOJaCFMKuVpXG9mXO4pXV6n9SqVjE4qWSVJkquoMmr6G2DN5uZUXfom4gj5nHAb+D4hrZ9JjcfBRt1UNU7qK79tZqWSaTQH3JiMpxG32HkxlUZ5KpW050+lWalEtBAmlfKUSwCUe0qXFSuVxqLGVHXl9jceTZZ1v0s1MZ1UMu5tGLRgc3OqLn0TMbTXeo0Og6CtGMlKJaoWJwfCcDlsWNPgMzoU0jUHtGnQXAGOAH31N/ZUIjIFJpXyNB7TEhUhX/lWfwO0nkpWa9SdS+qU+1jl9perKjO7XDLHY1BPJQCo9XL6G5lXIpXBcCSJ9hD7KZlBgJVKVEWO901iY3NNyVeXovw1BbVp0ExuEwAkyrj6G3sqES2Mq7/lKZeoKPeULq/Tjngqg6yyzlzesSktqVRX5kqlOj2pNGa5SiUjk0pOdA5HDds/0UL6JrQLB1YqmUPA48Cx3kmjwyBakrlWj7x7z6p5tz/RH8YtGxtLGRIVKNdbb4DJbYLWUynkLVelknWuw4iMwI9f8pRLAORWwCkXr8sBBW3gtIoxgxJwtV4nRF7bv9nlVl0zOqnESiUyq96JGACgPcSkkhkEPU72M6GqMDAZx1A4gStX1BodCs2QWwWUzboJ0CuVbOWpVOL0N6KFMamUp/FoCgG3o+xl0D494WClZt3j0SSCnvIfK7tNEPQ4LdhTiUklorn0jsdR43YgUOZkPs0t93NgPxOqdIe6JwAAO1aGjA2ELlHvc+mrUHIMIr2nUolXf2NSiSg/TCrlaTyaRJ2/vD2CAK1RNwBEk+my73upxqIpQ44VoE25s0ql0kQsBZsALoeBjbo9TsRSGSS5qgWZUN9EDO0hD0RKe9JI+Ql4tOrTAVYJlJSI3CsigyJyxOhYqtWh7nHYbYIr2oJGh0Iz2GyCxho3k0oEoDw9lRy5nko8TyZaEJNKeRqNpsreIwh4rYrFSpVKY9Fk2Zt054R8LstUKk3G0vA47YZeMNfqv9OsViKzSaQzGJiMs5+SieQqlXhBV3JfB3C70UFUs0PdE9jYXDP9wR6ZR3OQSSUCMlmFVEbBUbZKJfZUIloIk0p5GpsytlIpZqEV4MYNSsABuUolaySVJmIpeAyc+ga81veKSSUym1P9EWQV0MZ+SqaRq1RiP5PSUko9A2DU6DiqlVIKh3smsGMl+ymZUXPAzTGIpnv7OdlTicgUmFTK01g0iXoDqm9809PfrJNUGosmp1diK7c6nwtjU9ZIkEzGU4b2UwKAoJ5UyjUNJzKLI71aT5MVTCqZhs9lh8MmGGCVAFWwCyNRjE4lcVVHndGh0ByaAh72dSMk9Olopa5UsonAJkwqES2GSaU8jU0ZM6XLitPfxqMphAyqVLLS9LeJWMrw0npWKpFZHe2dgMdpM6zqkS5nE0FTwI1BLudtOBH5qIjsF5H9Q0NDRodTUfZfGAMA7FrDpJIZtQTdGJlKssdNlZuuVCrDokBOuw1JJpWIFsSkUh4S6QymkhnU+8t/ceOw2+C0i2WmvyXTWUQSaQMrlZyYSlqj8bQZpr8F9eksk0wqkckc7plEW62XTbpNpjnowWCYU0+MppS6Rym1Sym1q6mpyehwKsorF0YR9DiwoanG6FBoDs0BDwBgOMLkdjWbrlSylf4cwWW3IZVmTyWihTCplIdxfTUxo1Y087kclkkqjce0KiGjqgtC+s/ICtVKk7G04dPfWKlEZhRPZXCsdwIddT6jQ6FZmlmpRBVuf+cYrl1dB1sZLlapcM0BNwAuGFDtylqp5LAhmbHGdRiRUZhUysPoVC5RYkxSyeu0I2qR6W+5BJxRq7/lklljUXMnSZRSmIyl4HUa+xacTiqZ/HhRdTnUPYFURmF1A5NKZjMRS+HiWBT37e2a/qLiEpFvA3gRwGYR6RaRDxsdU7UYjyZxejCCXWvqjQ6F5tEc1JNKbNZd1XJJpVL3VAK0SiUrzIAgMpLD6ACsILeamGFJJZfdMpVKYwYn4HL7NfsKcIl0FslM1vBKJZfDBq/TzkbdZCr7L2gLX62qZ1LJbIIeB6LJDNKZLBxl+IS4Giml7jI6hmr10rkRAMCetUwqmcXsxHWuspqVSqUnIh0AvgmgFUAWwD1KqX8wNipNbvpbOSqVPE7b9P6IaG5MKuUht5pYvUHT37xOO0amrPHHc2y6UsmoRt3afs0+/S2X9PK6jH8L1nqdnP5GpvJK5xjWNfnhdxv//qBLBfQ+bGEDe+cRlcpzZ4bhd9mxsyNkdCg0jxq3AwLgiRODsM3ouXf3nlXGBVW50gD+h1LqgIgEALwiIo8qpY4ZHdj09LcyTFN1O+xIpJhUIloIP2bMw2jU2D5BVqpUyiVzjOo/9VqlkrmTJLlEpc/g1d8AIOh1MKlEppHNKrzSNYZdq7nykhkFPFqiLxxPGxwJUfG9cGYEe9Y1lKX6gZbGbhP43Q4uMFIGSqk+pdQB/f9hAMcBrDA2Ks10o+4yvFfdThsSaWtchxEZhX818zCuT+kyqk+Qz2lHNJmBUuZfeSCXzDEqAWeV6W+55JsZkkqsVCIzOTccwXg0hV2rOf3EjHIrRoY5ZZYqTO94DOeGp3Dj+gajQ6FFBDwOJrbLTETWALgawN457vuoiOwXkf1DQ0NliaecPZXcDk5/I1oMk0p5GI0mEXA74HIYc7h8bgfSWYWoBaqVxqPJ6T49RvC67HA7bNMNw80ql3zzmWL6m8v0x4uqx/7OMQDAtWtYqWRGuUqlSV7QUYV56qR2MXzLxiaDI6HFBDwOhBM8bykXEakB8H0An1BKTc6+Xyl1j1Jql1JqV1NTed4/0z2VbGWoVHLYmVQiWgSTSnkYj6YQ8htTeQMAfr2aJbcKnZmNRZOo8zkhYtxSvHU+13TDcLPKVVL53MZXKtX5nEwqkWnsvzCGer8L6xr9RodCc/Dr/UxYqUSV5okTg1hZ58WmlhqjQ6FFBDxOViqViYg4oSWUvqWU+oHR8eQkyl6pZP4P9omMxKRSHkankqg3sCFprlmtNZJKKcObt4Z8Tgv0VDLP9Ld6vwtj0aQlpldS5TtwYQzXrKozNDFN87OJcOoJVZx4KoPnzwzjjVuaOfZYQMDjQCSeRpbnLSUl2pvh3wAcV0r9vdHxzBRPlW/1N7fTxkbdRItgUikPY9GkYY2nAWsllcajScNWfsup87kssPpbCn6XHY4ylO0uJuRzIZHOIpbipzBkrMHJOM4NT+E6Tn0zNa1KwNyJe6JCvHB2GLFUBq/f0mx0KJSHoMcJBWAqweR2id0E4AMA3iAir+pfdxgdFIDpyqHyVCpx+hvRYoxv6GIBY9Ek1jcZVw5trelvKWxsNrZ0vM7vxMn+sKExLEZLvpljOe56fWrnWDRlih5PVL2eOT0MALh5Y6PBkdBCAh4Hp8xSRfnJoT4EPQ7cuJ5jjxXM7O0W8Bj7QWYlU0o9B8CUpXvxVBY2AexlqCzk9DeixRlfJmEBY1PGTumyXqWS0dPfzN94Wqt+M8eJUO7nZfY+VFT5nj41hMYaN7a2Bo0OhRYQ9DoxyUolqhDxVAY/OzqAt21vM2xBFipMgKtQVr1YKgOv016W6apc/Y1ocSxLWEQynUUkkUadgVO63A4b7CIYMflFv1IK49GUoccK0BtPx1JQSpm2N4IZek/l1OtTO8dMPmWQKsd9e7suu+1XruvAc6eH8PotzbDZzPm+JU3Q40Q0mUEqky1LPwuiUnrq5CAiiTTeubPd6FAoT7lKJfZ2q17RZAbeMlXXu5129lQiWgTPBheR681jZE8lEYHfbTd9JUk4kUY6qwxPltT5XMhklamXvB6PJg0/Tjm5JKAVKuGoch3pmcBYNIVbN3E5b7Or9fKCjirHAwf70FjjwvXr6o0OhfIUcOfGIFYqVatYMl22xW5y09+4oA3R/JhUWsSonlSqNzCpBAA+l8P0lUrjU9ofd6Mbdeemc5m5WffoVNLwiq6cOk5/IxN45tQQRICbN7CnidkF9aknEzFe0JG1RRJpPH5iAHdc2QYHq+4sw2G3weu0M7FdxXLT38rB7bAhq4B0lkklovnwL+gixkySKPG77RidShgaw2Jy06eMrsDJJWvGTNpXKZ3JYjKeNrz3VE6t19zHi6rDM6eHsL29Fg01bqNDoUUE9TGDfZXI6h4/PoB4KsupbxYU9DqYVKpi2vS3ciWVtP2wrxLR/JhUWsSYSSqV/G6H6acnTSeVDG5APd142qSVSrlP981SqeSw21DrdZr2eFHli6cyONA1jtdtYpWSFeQqlSZZqUQWd/+rvWiv9eDaVXVGh0IFCni4YEA1i5ezUsmpXS4nUlwBjmg+TCotIpfIqTe4qsTvMn9SKbfimtEVOLlkjVmnv+Uqgozs0zVbnc/JSiUyzOnBCDJZhVs3NRsdCuXB47TBaRcmlcjSosk0njk9hHfsbOfiABYU9Dg5BlWxaDJT1p5KACuViBbCpNIicokJoxMlPrcdk/E0UhnzDmjmmf6m7X90ypwnG2b5nZqpzu9iTyUyzNHeCTT4Xbh2NasFrEBEtAs6Tj0hCzvWO4lURuGdOzj1zYqCXgciiTSybJ5clWKpDDxlSip5nJz+RrQYJpUWMTqVQo3bAZfD2EPl15fNNPOF/0gkCZsAIa+x07pqvU7YbWLaHlRmqX6bqd7n4vQ3MkQqk8WJ/jDesq0FdlYLWEbQyyoBsrZD3RNY0+DD9hVBo0OhJQh6nMgqIMLkdlWKJTPwlbFRNwAk0pz+RjQfh9EBmN1YNGl4jyBA66kEaKvRNQc9Bkczt5GpBOr9bsPLyG02Qb3fhZGIOZMkr00TNP73Kifkc+F436TRYVAVOjsUQTKdxVu3tRodChWg1uvEhZEpo8MgWpJwPIWzQxHctrkJ39538ZL77t6zyqCoqBC5RUYmYqnpxQOoesRS5Zz+pu0nnmKlEtF8WKm0iLFo0vDpXADg1wfOUZMmSgBgOJJEY43xxwoAGvwuDJv0WL3W0NwcxwoA6v3sqUTGONo7CbfDhhvXs0m3lQQ9DkzG01CcekIWdKRnAgrAjpUho0OhJeIqlNUtmizf9LfpSiU26iaaF5NKixibMklSSa9UGjH19LcEGkySVGqscWPEpNPfxqIpOO0ynSg0g5DPhVgqgzj/YFIZZbIKx/smsbUtaPgUYypM0OtEJqswleSYQdZzqGcCLUE3Wkxa+U2LC3q082JOw60+maxCMp2Fz1meCTfTq7+xpxLRvHgWv4jhSNIUiZLp6W9mTipNJdHgdxsdBgCgocbM09+SCPlcEDFP/5h6vWqKfZWonDpHphBNZnBFG3uaWE3Qo1cJ8IKOLCYcT6FrJIrt7bVGh0LL4Hc7YBfhggFVKKZ/AOp1lecyNjf9jUklovkxqbQApRSGIgk01RifKPE67RAxeVIpkkSjCY4VoFcqRcxZqTQ6lUSdifopAZiOx8y/X1R5jvZOwmkXbGoJGB0KFYhTT8iqjveFoQBc0c5ktpXZRBDwODDBxHbViSa1RKLXVaZKJTbqJloUk0oLCCfSSKazpkiU2G2CWq/TtBf98VQGkUTaFFVdgFapNJXMIGbCqRnj0ZQpplTOlItnbIonZ1QeWaVwrHcCG5sDnPpmQa9NPWGVAFnLsb4J1PtdaOXUN8vjKpTVKZ7UKobKt/qbXqnERt1E8+KZ/AKGw1qlS2PAHAmAer/LtEmlXK8nszTqbtSn4Zmxr5JZmr/PVMfpb1Rm3aNRTMbT2MZqAUsKeJwQsFKJrCWeyuDs4BS2tQVNNQWdlibodXIMqkLRVK5SqUxJJfZUIloUk0oLyK0eZoZKJUBb0cy0SSV9qpmZeioBMOUKcGPRFOr8Zpv+xqQSldfR3knYRbCllUklK7LbBDVuB6sEyFJO9IeRUYpT3ypErceByRhXoaw2uVkIZUsqcfob0aLKMxnVosyWKKn3u9A5HDU6jDnlmmKbZ/qbXqlksr5KSqnpRt1mEtJ7KnH6G5WDUgpHeiewvtk/fVJ4394ug6OiQrFKgKzmWO8EAm4HOup9RodCRRD0OpHMZFlBUmWmk0rlnv7G3zOiebFSaQHDEfNNfxsxaaXS9LEyUVUXANOtABdJpJHOKtM16nbabQh4HKxUorLom4hjLJrCNq6+ZGlBvUqAyArSmSxODUSwtS0IG6e+VYTcggFs1l1dcqu/+cpUqZTr+8ieSkTzY6XSAoYiSYgA9SapKqn3uzAWTSKbVbDZzHVClEt2madSSZ/+ZrKeSrlKILP1VAK0mJhUonI42jsBAbC1jVNQrCzodaJzxJzVs0SzXRiNIpnJYnPrwqtNsmrSOoIefRVKJpWqSjRZ3qSS3SZw2oXT34gWwEqlBQxHEqj3ueCwm+Mw1fvdyGQVwnHzfTI8EknA67TDV6blPRfjczngc9lNV6mUS9qYMqlk4p5dVFmO9k5iTaMfNW5zjBe0NEGvE7FUBvEUT7TJ/E4PRGATYF2j3+hQqEhq9UolTsOtLrnpb54yTX8DtClwnP5GND9zZEtMajicMM10LmDGlC6TVd8A2jQzs1Qp5TTUuEzXU2k6qWSyRt0AUOdzYjzKEzMqrTODEQyGE1z1rQLkqgQGJuMGR0K0uNODYaxu8MNdxgtRKq2AR/tgYoLTcKvKa9PfyvfBlNthY6US0QKYVFrAcCRhmn5KwGv9iobC5kqUAMBQJDHdHNssGvxu0/Wgmm5obpLm7zPV+1ipRKX3yNF+AGA/pQoQ9Gon9P0TTCqRuQ2FE+ibiGNjc43RoVAROe02+Fx2Tn+rMtEyN+oG9KQSeyoRzYtJpQUMR5KmuvhvCuhJJZNV3wBasqTRb54EHAA01rgwbLLpb7kqM7NVdQHa9Ldx9lSiEnvkaD866rzT0xbIunKVSv2sVCKTe+7MEABgY8vC/ZTIemq5CmXVyVUqeZzlu4x1Ozn9jWghTCotYDhirulvzXpSaXDShEmlqYTpEiUNfrfppr+NRJJwO2ym7CVT73dhKsn+KFQ6w5EEDnVPYHMrp75VglxikNPfyOyeOTUMv8uOtlqP0aFQkQU9TlYqVZlYMg2v0w4p4yqOnP5GtDAmleYRTaYRTWZMNf0t5HPCaRcMmmz6m1JK76lkngQcoFUDjU5pq+WZxZCeqCznH8J85Xp2DZssEUeV47nTwwCATS2cglIJ3A4bXHYb+ic4ZpB5ZbMKz54ewobmGthM+LeXlifodWDChAvYUOnEUpmyrfyW43Hap6fdEdHlmFSaR673jZkqlUQETTVu0/VUmoylkc6q6aSEWTTUuJHOKlOVRZuxoXlO7nfdbCvmUeV45tQQ6v0utIe8RodCRSAiCHodrFQiUzvRH8ZwJImNzZz6VomCXiemEmlWkVSRaCIDb5mTSn63fXrVOSK6HJNK88j1LWoyUVIJAJqCHgyGzXUCP6z3Ccr1fDKLxhrzVd6MTCVMl3zLaTDh8aLKkc0qPHN6CLdsbGS1QAUJepzsqUSm9uK5EQDAejbprkghr3buwgUDqkckkS57Gwmfy8FKJaIFMKk0j2G9GshMlUoATFmpZNYVzXI/OzM16zbjNMGc146XuX6/ikFEbheRkyJyRkQ+Ncf9t4nIhIi8qn/9uRFxVrJjfZMYjiRx66Ymo0OhIgp6nbyYI1N78ewI1jT4uDhAhQr5tJ9rz3jM4EioXCKJNAKecieV7IgmOc2SaD5MKs0jl4gw21Sl5qAZk0rmXNEsF49ZpnO91nvKXMcpx4xJuGIQETuALwN4G4ArANwlIlfMsemzSqmr9K+/KGuQVeDpU9rqS7dsZFKpktR6nRgMx03Vu44oJ5NV2Hd+BNevazA6FCqRkJ4s7B1ncrtaGFWpNMVKJaJ5Mak0j2GTJkqaA26MTCWRyphnWcvhKXMm4HKVUyNT5kjCTcbTSGaypptSmeN12eF32SuxUmk3gDNKqXNKqSSA7wC40+CYqs7Tp4awrT1oummytDxBjwOpjMLIVGUlo6kyHO+bxGQ8zaRSBQtOJ5VYqVQtIvE0/GVMKt23twsXR6OYiKVw396usu2XyEqYVJrHcCSBoMcBt6O8jeAWk7sgM0v1DfBapVK9z1xJpTqfEyLmqbwxa0XXTI0Bt2mOVxGtAHBxxvfd+m2z3SAiB0XkYRHZVp7QqsNkPIUDF8Y49a0ChfRxv2+CF3RkPi/p/ZT2rKs3OBIqFafdhhq3g0mlKmLE9DeXw4ZUOgulWJVLNJeSJpXy6GPyfhE5pH+9ICI7SxlPIYYjCTSa8BP15oAHAEzVrHskkkSdzwmH3Vw5SofdhjqfazqZY7TcJ/lm6z01U2ON2zTHq4jm6go9+6zgAIDVSqmdAP4JwI/mfCKRj4rIfhHZPzQ0VNwoK9gLZ0aQziomlSpQrk9Nzxgv6Mh8Xjqn9VNqq+WKk5Us5HOyp1IVMWL6m8tugwKQyjCpRDSXkmUB8uxjch7ArUqpHQD+EsA9pYqnUMPhpOmadAPa9DcAGJw0z4X/UDhh2ubTDX6XaXpQWaFSqcHvqsTpb90AOmZ8vxJA78wNlFKTSqmI/v+HADhFpHH2Eyml7lFK7VJK7WpqYoIkX0+fGkKN24FrVtcZHQoVGZvkklllsgp7z4/ihvWc+lbpar1OVipViUxWIZrMlHX6G6BVKgFA0kTtR4jMpJSlJYv2MVFKvaCUGtO/fQnaxZ4pDEcSpux9k5v+NmSiC//BcBwtQfMdKwBoCXowaJKk0pA+rcyMycqcCp3+9jKAjSKyVkRcAN4H4P6ZG4hIq4i2zr2I7IY2No6UPdIKpJTCM6eGcOP6BjhNVs1Iy+d1ar3Y2CSXzOZY7yTC7KdUFUJeJ3rH45yaVAUiCW0FtrJXKuWSSmkmlYjmUsoz/Hz7mOR8GMDDJYynIEORhCkrSnIJCTNVKg1MJqan5ZlNc8A8q+UNTcYholUDmVVjjRtj0STSFfRJjFIqDeDjAB4BcBzAd5VSR0XkYyLyMX2z9wA4IiIHAfwjgPcpnp0WxdmhKfSMx3DrZlZ2VSIRQXvIi57xqNGhEF1iup/SWiaVKl3I50IslcF4NGV0KFRiU3pSqew9lfQPxRJprgBHNJdSviPz6WOibSjyemhJpZvnuf+jAD4KAKtWrSpWfPOKpzIIx9OmrChxOWyo8zlN01NJKYWhcALNJq1Uag56MBjWPr3SC1EMMxhOoMHvNl3vqZkaa1xQChidSqI5aM5E4VLoU9oemnXbV2f8/0sAvlTuuKrB06e03lOv28ikUqVqD3lZqUSm89K5Eaxt9KO1tnL+ltHcpnu7jcdQZ+IP7mj5cpVK5Z7+5malEtGCSnl1u2gfEwAQkR0AvgbgTqXUnNNNyt3HJFfZ0mrSi+rmgMc01Tfj0RSSmSxaTFqp1BJ0I5VRGDPBp1dD4cR0Tyyzmu7ZZZLfL7K+p08NYX2THx31PqNDoRJZUedlTyUylUxWYd/5UU59qxK53m7sq1T5wnGDp79VUCU/UTGVMqmUTx+TVQB+AOADSqlTJYylIP2T2ieuLSb9dKs56DbNRX8uDtNWKunJroFJ4z9FHwwnpntimVWTfrzMkrQka4unMth7bgSv46pvFW1FyIvRqSRiSU4LIHM41juJcCKN69fVGx0KlUHIp1UnMalU+SJGTX9jpRLRgkqWVMqzj8mfA2gA8BUReVVE9pcqnkLkEhBmbT7dVGOePkGvHStzJuByP0MzJOEGw3ELVSoZn4Qj69t7fhSJdBa3MqlU0VaEtOXaeyd4QUfmkOunxEql6uB32eFy2NA7wXOXSheJGzP9LddTiUklormV9B2ZRx+T3wTwm6WMYSn69T9KZp3+1hTUkkpm6RMEwLTJErNUKmWyCsORpGkrunJy8Q2YqBE8WdfTJ4fgdth4YVfh2vWkUs9YDOubagyOhgh48dwI1jX6TfuBFxWXiGBFiNNwq8GUwau/JZhUIpqTeTsGG2gwnIDLYZtu/Gc2zQEPkpksJmLG9wnKJWtMu/qbniQxurJrLJpEJqtMe5xy3A47QiZqBE/W9vSpQexZ1wCP0250KFRC7SFtXOPUEzKDdCaLl8+PYg+T2VWlPeThGFQFwrnpb+7yXqNx+hvRwphUmkP/RBytQY/hVUDzaTJRM+XByTgCHge8LnNeNHqcdgQ9DsMrlQb1yh+z91QCgJaAZzpeoqXqHovi7NAUXrex0ehQqMRagx7YBKwSIFM41sd+StWovdbLpFIVeG36W3mvO5x2NuomWkh5awctYmAybtp+SsBrU82GwglsagkYGstgOGH68vKWoPFJklzlj1mnCc7UHHRjwAQJS7K2Z04NAwBu28x+SpXOYbehNehhUolMIddP6QZWKlWV9pAXg+EEkunsdFUJVZ6XO0fhtAu+u7+7rPu1icBlt7FSiWgeTCrNYTCcwLb2oNFhzMtMzZQHJs3ffLol6Jle0c8or/WeMncCDtCqqc4ORowOgyzu6VODWBHyYu+5Uew7P2Z0OFRi7SFWCZA5vHRuFOua/Gg2+QdeVFwrQl4opZ2XdtT7jA6HSiSRzsLtMGZ2hMvBpBLRfJjKn0Uphf6JuKmrb3Kx9ZlglYu+iTjaar1Gh7Gg1lrPdPN1o+R6Olli+lvQg6FIAtmsMjoUsqhUJovnz4zgdZuaTDuNmIprRR2b5JLxcv2UuDhA9VlRp52LXhyNGhwJlVIinYHboEo0l8PG6W9E82BSaZZwIo1YKmPald8AbRnNoMeBvnFjEyXpTBaD4QTaas17rACgrdaDwXAcaQP/EAxMxlHrdZq299RMzQE3UhmFsWjS6FDIog5cGEMkkcatm9hPqVq0h7zon4gjw2Q0Gei1fkpMKlWbVXp1UheTShUtkcrC7TQoqWS3cfU3onkwqTRLrqKlxeSJkvaQ1/BKpaFIApmsQlvI3MeqrdaLrDK2sblW0WXu45STq4QbYLNuWqInTw7BYRPcuIFJpWrRHvIilVGGr7RJ1S3XT+n6tWzSXW3aaj1w2AQXmFSqaLFUxrAVZV0OG1JMKhHNiT2VZsmV768wfaLEg74JY6ca5JJa7Saf/pZLevVNxNEeMibW/ok4Wi2TVNKm6A2E47gC5u0tRub1xIkB7F5bj6CnvEv+knFW6mNrz3jMMmMdVZ4Xzo5gXZMfjx0fNDoUKjOH3YaVdV50jTCpVMliyYxhiym5HTbEUxlD9k1kdqxUmiXXaNSo5EO+2kxQqZSbfmf2C4hchZCRSbi+iZhlKpVyPbKMnl5J1nRxNIpTAxG8YUuz0aFQGeX6mXSP8YKOjBFPZfDSuRHcwgrJqrWqwY8Lo1NGh0ElFE1l4HUZUxPhcnD6G9F8mFSapXc8BrtNTL9KV3utB6NTSUMz5rkkjekrlfT4jGrWnUhnMBxJojVo7uOU0xxwwybGJuHIuh4/PgAAeOPWFoMjoXLK9TO5wCoBMsi+86OIp7K4bTMT2tVqdb0PF0aiUIq93SqRUgqxZBo+g/qTep12VioRzYNJpVn6xuNoDXpgt5l7xaLpahIDq5X6JuLwOu0Ies09izLoccDnsqPXoMqbQb03kVUqlRx2G5oDHsOOF1nXfXu78J97u9BY48aLZ0dw394uo0OiMrhvbxd+cKAHtV4nnjwxyJ87GeKpk0NwOWxs0l3FVjf4EI6nMR5NGR0KlUA0mUFWackdI3icdsRTrFQimguTSrP0jMfQbvJ+SsCMPkEGLuHcPxFHW8hj+iXDRQRttR70TxpzrHKJP7NPE5ypLWR8zy6ynkQqg/NDU9jSGjA6FDJAvd+FkSmuGknGeOrUIK5f12CJVVapNKYrJtmsuyKNx7RkoVHvcY/TjmQmi5SBq0kTmRWTSrP0TsSmq4DMLDflrNfASqVei/UJMqryJpecscqxArTfL6N7dpH1nB6MIKMUtrQxqVSNGphUIoNcHI3i3NAUbtvUZHQoZKDVDX4AQBeTShVpPKr9fTGqUsnr1C6bw/G0IfsnMjMmlWbIZhX6DVwhrBC5qhcjK5V6x62RgAOA9pBnugl7ufVbsVKpVjte7EtAhTjeNwmP04bV9X6jQyEDNNS4MZVIs+cEld1Tp4YAALduZlKpmuUqlbpG2Ky7Ek3o0xqN6qnk0ZNZkzFOrySazdzNcMpsOJJAKqOwwgLT3zxOO5oCbnSPGZMoSaQzGJhMoKPOZ8j+C7WyzofBcALxVGb6j0K59E3E4XfZEbDQ8uptIS8S6SzGoynU+V1Gh0MWEE9lcKxvEtvag6bvSUel0aCPFaOsVqIyum9vF7710gXU+Zx46ewI9p4bNTokMojXZUdzwM0FAyrUhMHT33IVUpNxJpWIZmOl0gzd47lpStaovllZ58VFg5Zvzk0lW1lnnWMFwJBqpZ7x2PRy21aRm6rXy75KlKenTg4hkc5ix8qQ0aGQQRpqtKQSp8BROaUyWZwdimBTS8D0PR6p9FY3+NhTqULleir5XMbURLinK5U4/Y1oNiaVZrio/xHqqLdG9U1Hnc+wpFLuWFknqaT9TC8aUNnVPRab3r9VtE1Pr2RfJcrPAwd74XfZsb6pxuhQyCD1Pj2pFEkYHAlVk9MDYaQyCtvaa40OhUygo96HLlYqVaTcqn7G9VRipRLRfJhUmiE3layj3hqJko56L/rG40gbsArBa8fKGsmS3M+024AkXPdY1DLJt5xcZZURx4usJ5JI47HjA7hyZS2nvlUxt9OOGreDlUpUVkd6J+Fz2bG2kb3cCFhd70f/ZJy93SrQeCwJu03gtBtznuHRG3WzpxLR5ZhUmqFrJIrGGrdhZZWFWlnnQzqr0D9Z/mqSi2NROGyClqD5+08BQHPAA6ddcHG0vJVKE7EUwvG05ZJKTTVueJw2Qyq7yHoePdaPRDqLnZz6VvUa/C72VKKyiacyON43iSva2MuNNKsb9Mp0ToGrOBPRFHxOu2HTXFmpRDQ/JpVmuDgWtUyVEoDpJtnlTpQAWqVSe8hrmZM4u03QHvKWvfImtz+rTX8TEays8/GkjPJy/6u9WBHyWqZykUqnocbF6W9UNo8fH0QincWVKzn1jTSr9KQSm3VXnolYyrAm3QDgctggYE8lorkwqTRD12h0ejlSKzB6SpeVEnBArgdVeRNwuWmCVqtUAoCOOi8rlWhRfRMxPH1qCHde1Q4bm+RWvXq/G5PxNGJJTj2h0vv+gW4EPQ72cqNpaxq0aZCdI1MGR0LFNh41NqkkIvA47axUIpqDNeZ5lUEqk0XveAzvvnqF0aHkra3WC5sY03z64mgMb9zSXPb9LsfKOi8ePTZQ1n2+llSyTrIyp6Peh/2dY1BKcUWdKnff3q7Lbrt7zyoAwHf2XYQCcNfuVXj29HCZIyOzya0A1zUaxebWgMHRUCUbDMfx9Kkh3LS+kQltmlbncyLkc+LsEJNKlWY8ljKsSXeO12XHBHsqEV2GSSVd33gcWWWdxtOAVobZVust+xSlqUQaw5HEdImxVXTU+zAylUQkkUaNuzy/+t1jUfhcdtT5nGXZXzF11PkQTqQxEUshpK/qRDRTMp3Fd17uwq2bmiw1dlLpNPi1saJzZIpJJcrbQonr+Xx770Vksgq7VteVKiyyIBHBhqYanB2KGB0KFdlIJGH4jBKP08ZG3URz4PQ3XZeemOmwWEXJmkYfzg+X99OYXElxrsTYKnIrw3SW8XhdHI1hZZ3XkpU+uemNRvTsImu4/2AvBiYT+LUb1xgdCplEg98NoLzjLFWfZDqLb+29gFs3NaEx4DY6HDKZDc01ODvIpFIlyWYVRqaSZftQeD7a9Df2VCKajUklXS5Rstpi1TdrG/3lTyoNawm4NY3WOlZGzLO/MDKFVfXWSr7l5KbsXTSgZxeZXzar8C9Pn8WW1gBu29RkdDhkEl6XHX6XHec49YRK6P6DvRgMJ/AhJrRpDuubajAylcQYV6KsGGPRJDJZhRqPsUklr9POSiWiOTCppDs3NAWv047WoMfoUAqypsGPiViqrH84rVqplEuClesT9GxW4cJoFOuarHWccnLTmbq4AhzN4SeH+3B6MILfvm29JSvxqHSagx6cHgwbHQZVqHQmi3964jS2tQdx22YmtOlyG5q1xu2cAlc5hiPadY4ZKpXYU4nockwq6c4PR7C20Q+bzVoXR7kpXefKWK10fngKzQE3/AYP7IXyuRxoCbpxfrg8SZLeiRiS6azlkm85tV4nGvwuTmOhy2SyCn/3s5PY0hrAO3a0Gx0OmUxzwI3TAxEopYwOhSrQf7/SjQsjUXziTZuY0KY55ZJKZzgFrmIMhRMAgIDH2B6lPqcd47EU/74RzcKkku7c8BTWWrCixIg+QZ3DU1jTaL1jBWjHq1zT36w6TXCmtY1+TmOhyzx/ZhgXRqL4k9u3wG6xRDyVXkvQg3AijYHJhNGhUIUZjybxuZ+ewHVr6vCmrdZagZbKZ0XIC4/ThtNMKlWM4Yj298ToSiW/24FkOoupZMbQOIjMhkklAIl0BhdHo1hvwURJR70PdpuUta9S58gU1lq0+mZto79sCbjzevJqrQV/r3LWNfnLWgVH5jc6lcTjJwbw5ita8PotvKijyzXrjZNPDXAKHBXXX/zkGCbjafzFndtZpUTzstkEm1oCONnPMahSvFapZHRSyQ4A7NdFNAuTSgAujkaRVbBkpZLTbkNHnbdsSaXJeArDkaRlK5XWNPgxMpUsy3zozuEpeJw2tASs1adrprWNNRiOJDAZ5/xx0qa9fXf/RdhE8Nl3bTM6HDKpZr03IasEqJh++PNu/OBADz7++g3Y2hY0OhwyuS2tAZzonzQ6DCqS4UgCLocNboexl64+l5bUGmFSiegSTCoBOKtP71nXWGNwJEuzvqmmbPPGTw9o+8nNV7ea1+bZl/7Tq87hKaxpsF6frplyTcbZV4kA4JGj/egajeIXrl6BFSGv0eGQSdW4Haj3u3CKVQJUJK9cGMOffP8wdq+px++9YYPR4ZAFbGkNYjiSnK5wIWsbiiTQVOM2vEIx1092dIq/V0QzMamE11aHsGKlEgBsbAng3HAEqUy25Ps6rU9n2NRizaTSppYAAODUQOmTcOeGpyw99Q0A1uUawbOvUtV76dwInjszjOvXNWDnypDR4ZDJsUqAiuVA1xg+9O/70FbrwVc/cC0cdp660uK2tGnnexyHKsNQOIFGfWq1kfwubfrbSISVSkQz8S8zgFP9YbTXehA0eEWBpdrcWoNURuFCGRpQnxqIwOO0oaPOms2nV4S88DrtJe/1EU9lcGFkChv1JJZVrWrwwSbAOS7LW9X2nh/B/Qd7sbklgLdf2WZ0OGQB29qDONEfRroMH3ZQZbpvbxf+6sFjeN89L8Fpt+FXdnWg3u8yOiyyiC2t2hTJE32smKwEw5EkmmpMkFSarlRiUoloJiaVAJzoD2Nzq3Uv/jc2a7Gf7C/9hf/pwTA2NNdYdkqXzSbY0FwzPY2vVM4MRpBVwGaLJ5XcDjtWN/jZG6WK3be3Cz9+VUsovX/PKq72Rnm5oj2IRDrLRv+0ZKcGwvjGC52o9Trx0VvWIeRjQonyV+93oSXoxvE+VipVgqFwAk0B48cAt8MGl92G0SiTSkQzGdtC3wRSmSzODkVw22brrmK0obkGNtFOwN6O0lYRnBoI46b1jSXdR6ltbKnBc6eHS7qP04PWniY402auoFK1vr2vC5/+4eHphBKnnVC+rmirBQAc652cnnZMlK9TA2H8x0sX0Bxw49dvWmv4MuJkfvft7brstu3ttTjUM2FANFRMyXQWI1MJtASNX/hGRFDvd2GU09+ILlH1Vwjnh6eQyihsbrXuxb/HqVWTlHpK10QshYHJhOWndG1qCWAwnMBEtHQrmp0aiMBpF8uukjfT5tYAOkemEE9ljA6Fyug7+7rwpz84jNdvbmJCiQq2vskPl8OGY6wSoAKdGYzgP/WE0odvZkKJlm7HyhDODkUQSaSNDoWWoW8iBqVgmgVC6v0uTn8jmqXqrxJO6BUYm1usvTztppaakleT5JJWVk7AAa9NSTtewuaNp/rDWNdYA2cFXIhvbg0gq1DyKYNkDvft7cIf/der+NQPDmNTSw1u29zMhBIVzGG3YUtrAEdYJUAF6B6L4j9e6kRDjQu/cdPa6eW7iZZiR0ctlAIOd3McsrKesRgAYEWdOZJKDTUujDCpRHSJqr9SONk/CbtNsL7Z2hUl29trcX5kqqSfxuT+KG9vry3ZPsph2wotgXi0t4RJpcEwNlbA1DcA0/3GuIJKdTjRN4kf/rwHG5tr8P49qysiMUrG2LkyhEPdE8hkldGhkAVMJdK4b28X/C4HfuOmtdMNcYmWascK7Xz1cM+4sYHQsnTrSaWVIXMsElTnc2GMPZWILlH1VwuHe7R+D26H3ehQlmX7Cu3TmKMl/FT4SO8EmgJuNJtgTvNyNAc8aA64S3asJqIpXByNYWubtavfctY0+OF22NhXqQqc6J/Ed/ZfRHvIy4QSLdtVHSFEEmmc5eqRtIisUviv/RcRTqRx955VCFh0NV4yl4YaN1aEvDjISiVL6x6PQQRorTXH9Qd7KhFdrqo/BlJK4XD3ON5yRavRoSzb9ulPYyawZ11DSfZxtGcSV66wdpVSzpUranGktzQnGbnnrZRjZbcJNrcGSlrZRcaY2dg0mkjjy0+dgdthw69evxouBxNKtDxXrQoBAH7eNcZm3bSgZ08N4cxgBO++agVW1pmjGoEqw9WrQtjfOQalFES4eqkV9YzF0Br0mOa8pLHGhXAijXgqA4/T2kUJRMVijnenQbrHYhiLprCjw/oX/00BN1qDnpL1r4glMzg9GMb29sqovtm2ohZnBiOIJos/XfBwT2UllQBgx8paHOmZQJbTWCqSUgo/erUHk7E0fnXPatR6WSVAy7e2wY9arxOvXhw3OhQysc7hKTx+YhDb2oPYtabO6HCowuxeW4/+yfj0FCqynp7xqGmadAOYnrExFE4YHAmReVR1UumQXg67Y0XI2ECKZPuK2umERrEd759EVmnJmEpw5YpaZBVwvAQrEx3unsDKOi/q/K6iP7dRdqwMIZxI49zwlNGhUAkc7J7Akd5JvGlrMzrqWSVAxWGzCXZ2hHDgwrjRoZBJKaXwv398BHab4J072llJQkV33Zp6AMC+86MGR0JL1TMeM02TbgBo1ZNKfRNxgyMhMo/qTir1jMNlt003Ira6qzpqcXZoChPRVNGf+8CFMX0foaI/txF26tVpP+8aL/pzH+6ZwI6VlZF8y9m5MgQAONQ9bmgcVHwTsRTuP9iDVfU+3LKpyehwqMLsXlOHkwNhLr9Mc7r/YC+ePT2Mt25rRZAVklQCm1sCCHocTCpZ0H17u/CfL11Az1gM49HUJVP2jdSm93bqn2RSiSinqpNKP78wjivag6aZo7tcu/RPY17pKv4fzlcujKGj3osWizfpzmkOeLC6wYeXO4t7rEankugajeLKCql+y9nQXAOfyz5d3UeV48FDvchkFd5z7UrYWCVARXbDeq3H395zIwZHQmYTT2Xw1w+dwM6Vtdi9tt7ocKhC2WyC69bUY+95jkFWNB5NIau05thmkWsY3j/BKZVEOZWRTVmCeCqDVy+OY08FncjsXBmC0y54uXOsqM+rlMLLnWO4bnXlHCsAuHZ1HV65oDVvLJZckuq6CusLYbcJtq+oxc+7ivu7RcY6NxTBkd5J3LqpCY01bqPDoQq0Y2UIPpcdLzKpRLN888VO9E/G8ek7tjKhTSV188ZGdI5E0TUSNToUKtBgWKsGag6Y5xwl4HHC77Jz+hvRDFW7+turF8eRzGQr6tMxr8uO7Stq8XKRS3wvjEQxHEng2gpLlFy3ph4/ONCDzpEo1jb6i/Kc+86Pwu2w4coKm/4GALvX1OOfnz6LSCKNGnfVDh0VI5NV+MmhPoR8TtyykdPeqDScdht2ranHi2eZVKLXTMRS+PKTZ3Hb5ibsWdeAs0P59eszy/QXspZb9andT58axAduWGNsMFSQXDPsJhMllQCtWmmA09+IplVtpdK+86MQAXZVWPXNdWvqcah7AvFUpmjPuU+vvqm8Y6UlyfYVsSR63/lRXL0qBLej8pYYvX5dAzJZhf1FnjJIxvjOy13on4zjbdvb4LRX7Z8CKoObNzTg9GAEPeOcKkCae545i4lYCp9862ajQ6EqsLbRj1X1Pjx9asjoUKhAg+EEatwO+Fzm+jCztdbDSiWiGar2SuKlcyPY3BJAra+yGkPeuL4ByUwWe4tYrfTs6WE0BdzY1FJTtOc0g/VNNWgOuPHM6eGiPF84nsLR3gnsXttQlOczm2tWh+CwCV46x6SS1U1EU/h/j5zE2kY/trcHjQ6HKtwbtrQAAJ44MWhwJGQGg5Nx3PtcJ+68qh3b2iuvqpfMR0Rw2+YmPH9mBLFk8T50pdIbnIybrkoJAFqDXgwwqUQ0zVxp3zKJJNJ4uXMUv37TWqNDKbrr1zXA7bDh6ZND0+W+y5HJKjx7eghv2NJccUv9ighu3dSEnx0bQDqThWOZ1RovnB1BVgHXr6usiq4cn8uBnR0hvMTeKJb3xcdPYSKWwvv3rF7y+5rTUGghM38/lFKo97vw+PEBfOD61QZGRWbwj0+cRiqTxR+9eZPRoVAVuX1bK7754gU8eXIQd1zZZnQ4lAelFIYiiekViM2ktdaNgXACmayC3VZZ10dES1GVlUrPnxlGKqPw+s3NRodSdB6nHXvWNeDpU8X5RPhwzwTGo6miJKjM6NbNTZiIpXCwCKuaPXliEAG3A9etqcykEgDctKERh7rHuTy4hZ0eCOObL17A+3avQnvIa3Q4VAVEBFtaA3jh7AimEmmjwyEDdQ5P4b69Xbh2dR2ePzOC+/Z2MUFNZbF7bT0aa1x48FCf0aFQnsKJNOKprDkrlWq9yGQVhiMJo0MhMoWqTCrlLv53VVjj6ZxbNzXh7NAULozk1/hyIU+eGIQIKraR780bGmET7XUuh1IKT54cxC2bGiu6P82btjYjq5Z/vMgYSin8xU+Oweey43+wSoDKaFt7LZLpLH52rN/oUMhAf/foKdhtgjdsqbwP9cjcHHYb3ra9DY+fGECEyW1L6NP78LXWegyO5HKr6n0AtEQ5EVVhUimTVXj8RGVf/L/lCq1/xYOHl/dpjFIKDx7uw+419aj3u4oRmumEfC5cv64BDx7ug1Jqyc9ztHcSA5OJiqx+m2l7ey2aA248fmLA6FBoCZ44MYhnTw/jE2/ahIYa833yR5VrdYMPK0Je/PjVXqNDIYMc6ZnAAwd7cdP6RgQ8ldXPkqzh3desQDyVxY9f7TE6FMrDxbEYBMAKE1ZVr9NXjT7HpBIRgCpMKr10bgRD4QTesaPd6FBKpqPeh6tXhfDAweUllU4OhHFmMIJ37KzcYwUA79jRjvPDUzjaO7nk57j/YC8cNsGbtrYUMTLzsdkEb9zagqdPDhV1hUEqvUQ6g7/8yTGsb/Ljgzewrw2Vl00E77qqHc+eHp5eIpqqh1IK//eh46j3u/C6Cp1OT+Z3dUcIW9uC+M+Xupb1QSKVR89YDE0BtylXVF4R8sLtsOHsYMToUIhMoeqSSj9+tQc1bkfFl16/c0c7jvdN4sxgeMnPcf+rvbAJ8LbtrUWMzHxu394Ku03wwMGlfYKeySr8+NUe3La5GXUVWtE10zt3tGEqmcHPjrFayUq+8uRZdI5E8Zl3bqvYKk0yt1+6ZiUyWYXv7r9odChUZk+dHMILZ0fw+2/YAI/TfBeIVB1EBO/fswrH+yaxr4irJFPxKaVwcSyKjjqf0aHMyWYTrG30s1KJSFdVVxbRZBoPH+7HW7a1VPxJzTt3tsNpF3xriQ0wk+ksvru/G7dtbkZjhU+Tqfe78IYtzfjvV7qXVH3zwtlhDEwm8O6rV5QgOvO5fl0D2ms9+P4r3UaHQnk6MxjBPz91Fnde1c4qATLMhuYa3LyhEf/50gWkM1mjw6EyyWQV/vrh41jT4MPde1glScb6pWtWorHGhS89ecboUGgB3WMxRJMZrKgz39S3nPVNNTg7xEolIqDKkko/ONCDcCKNu3evMjqUkmsKuHHHlW343v7uJa228/CRPgxHElUzTebXbliD0akkHlpCH6p/f74TDX4X3ri1sqvfcmw2wbuvWYFnTw+hV2+iSOaVzSp8+oeH4XXZ8b/fcYXR4VCV++ANq9E3EV92zz+yjvv2deHUQASffOsWuBxVddpJJuR12fGRW9bh2dPD2N/JaiWzeln/2eQaYptJbtXKaDKNrpEovvlCp9EhERmuav66K6Xw9Rc6ceWKWly7ujJXfZvtgzesQTiRxrf3FVatpJTC1549jzUNPryuQld9m+2mDQ1Y3+THPc+cQzab/zz7M4NhPHFiEB+8YU3FV7/NdNfuVRAR3PvceaNDoUXc+/x57Ds/ik/fsaXiqw7J/N60tQVbWgP44mOnWa1UBfon4vjbh0/gpg0NuOPKyp5KT9bxgRtWozXowWcfOIpMAed8VD7PnR6Gz2U35cpvOY01bigAI1NJo0MhMlzVJJUePtKPM4MR/MbNayAiRodTFteursNNGxrwlafOFrR86k+P9ONwzwR+9/UbYLNVx7ESEfz+GzfiRH8YDxzKv7fSFx47DY/Thl+9vvKr32ZaWefD269sw7f3dWEimjI6HJrHga4x/M3DJ/CWK1rwy7s6jA6HCDab4A/fvAnnh6fwX+ytVNGUUvizHx1BOpvF/333lVVz7kXm53M58L/evhVHeibx78/zwzGzUUrh2TPD2NBcA5uJx402fVW67rGowZEQGa8qkkrpTBb/75GT2Nhcg3ftrI6+NzmffOsWjE4l8U9PnM5r+1gyg889chIbmmvwi9esLHF05vLOHe3Y2hbE5356EuH44omSvedG8OChPnzs1vVVuTz7b9+2HtFUBl9+in0JzGhsKomPf+sA2kIefP69O3lBR6bxlitasGdtPf724RNcCa6CPXi4D48dH8AfvXkTVjf4jQ6HqlBumtJcX5OxFLa2BvDXD5/A/3vkpNGh0gwnB8IYCiewoanG6FAW1Bxww+ey49wQm3UTVUVS6Z5nz+Hc8BT+5+1bYK+SypucqzpC+JVdHfjXZ87hlQtji27/uUdO4PzwFP7iXduq7ljZbIK/+oVt6JuI4S8eOLbgcrOT8RQ++b1DWBHy4rdet76MUZrH1rYg3nvtSvz78+fZqNBkYskMPvof+zEcSeIrd1+LWq9zzpNqonLK/d59e99F3Li+EVPJDD75vYMFTTkma+gcnsKffv8wVtZ54XU6OO6Q6YgIfvGalfC77PiPly6gfyJudEik++mRfgDAxpaAwZEszCaCdfoKcAtdMxBVg4pPKh3tncAXHz2NO65sxZuvaDE6HEP82Tu2oj3kxW/9xyvoGpm/RPM7+7rw78934kM3rsGNGxrLGKF5XLu6Hr9z2wb89yvd+Oenz865TTyVwcfv+zl6x2P4x7uugtdVPb2UZvvjt26Gz+XAH/7Xq0im2R/FDKYSaXzkm/ux/8IYvvArV+HKlbVGh0R0maaAG2+/sg1PnRzC3z3KKoFKMjaVxG9+cz9sNsFdu1dV3QdUZB1+twMfvGENYqkM7v7aS+ib4OIjRstkFb778kXcsrERtV6n0eEsal1TDSZiKXSNcgocVbeKTioNTsbxkW/sR73fhb+4c7vR4Rgm4HHi679+HVKZLN7z1Rew99zIJfenMln80+On8ac/PIzXbWrC/3r7VoMiNYc/evMmvGtnOz7305P40x8cwuiMBnynBsK4619fwrOnh/B/330lrl1db2CkxmsOePC3v3QlDnVP4H//6Ag/qTFY91gUv3LPi3jh7DA+/56dePuONqNDIprXnrX1uGt3B7785Fn8w2OnOX5UgNGpJH7t3/ehazSKf/nAtajzuYwOiWhB7SEvPnTDGgxOJnDnl57HC2eGjQ6pqj11chC9E3HLrNSdm6L3yNF+gyMhMpbD6ABK5eJoFL/6b3sxHkvhu791Q9WverShOYDv/tYN+Oh/7Mev3PMSbljXgGtWhzCVyODxEwO4OBrDu3a2429/aQec9orONS7KZhP8/S/vRHvIi68+fRbfP9CDLa0BxJIZnB6MoNbrxJfvvgZ3XMkLdgC4fXsbfv8NG/CPT5xBS60Hf/TmTUaHVHWS6Sy+u/8i/vanJwAF/OsHd+GNW6uzMpOsQ0TwV79wJRLpLL7w2CmcGYrgL+/chhATEZZ0pGcCH7/vAPom4vjn91+D69c1sNcIWcKaRj++99s34He/dQDv/7e9+Nit6/G7r9+AGnfFXiaZ0r3Pncc/PXEadT4nhiIJOGzmvx5pDLixpsGPb754AR++eR0rM6lqlXS0FJHbAfwDADuAryml/mbW/aLffweAKIAPKaUOFGPf//58J8amkvjP39yD7Ss4/QMANrcG8NDv34Kvv9CJH7/agy8/eRZuhw3Xrq7DZ96xDW/c2sxmvjqH3YZPvW0L3nPtCnxn30Wc6A+jOeDGe65difdcu7IqG3Mv5A/fvAmprMKbtjYbHcqcjByLSqlnPIaHD/fh3547j76JOPasrcfn3rMDz58ZYe8SsoT/evkirl1Vh0g8jQcP9eLx4wP4ndvW4wM3rLHE1IdSWWzMMpPusSi+9ux5/MdLF9BU48a3fnMPdq2p7ipesp4trUE88Hs34zM/Pop/fuosvvvyRfz2bevx3ms7UOvjWIQSj0VD4QS++eIFjEdT+Ojr1lkioZRz04YGfGtvFx483Id37Ww3OhwiQ5QsqSQidgBfBvBmAN0AXhaR+5VSx2Zs9jYAG/WvPQD+Wf932f70ji344A2rsaaRK47M5Hc78Luv34Dfff0Go0OxhA3NAfzZO64wOgzTExH8ye1bjA5jTkaPRcuVySqMTCUwOJlA91gMZ4ciODsUwZGeCZwa0Bqk715bj7/5pR143cZGiAiePzOyyLMSmYeI4LbNzdjUEsCjxwbw/352Cv/81FnctrkZb76iBdetrUd7radqPvTIc8wyRDyVmR6HjvRM4JlTQzjUMwGbCH55Vwf+51s3o87PSjOyJp/Lgc+/dyfef/1q/L9HTuKvHjyOzz1yEm/e2oI3bGnG9esbsEJfRr4alGss+tnRfnz6h4cxEUvhvbs6LLda5Na2IK5oC+Kz9x/F9Wvr0Rz0GB0SUdmVslJpN4AzSqlzACAi3wFwJ4CZA9GdAL6ptEYKL4lISETalFJ9y925025jQomIAIPHosFwHJ3DUaSzWWSyCumMQjqrkMlmkcooxFIZhONpTMZSCMfTmIilMBRJYCisfY1OJTB7caxarxPNATfetr0Vm1sCaA560DMWw7f3XVxuuESGaQ958Ws3rsHOjlr850tdeOz4AB48rL0FG/wurGvyo63Wi7aQB001bvhcDvhcdnhddniddjhsAptNYBNBQ40L602+HPUC8hmzCjYRS+HUQBjpjEJWvTYOpTMKmaxCPK2NReF4GpPx1PS4NBJJYjAcx2A4gXA8Pf18AqCj3oc3bmnGNavq8Dv8sIosbHZ17x1XtuFTb9uC773SjQcO9k6PRY362LKq3oeGGjcaa1wI+VxwO2xw6V9uu216LKpxO3BFe9CIl1QMJRmL4qkMDvdMoH8ijp8e6ceDh/uwtS2Iu/esRqsFEzI2Ebz5ihZ85akzeMsXn8Ftm5rx3l0rYROBTaD/Lry2/cz2gTNP7y65Xf9m3vsx95Pks/3M2yfjKZwaiODVi+M4OxhBa60Hu1bXYduKWoS8TjjsAofNhoU6oyzWDnGhuxd97AIbLNaFcaHnVos9esHHlm6/Cz92YfFUBmcGI9h7fhTnhrR2LTs7Qri6I4T2kBd+twNXdYQWeZalK2VSaQWAmVc43bj8k/+5tlkBYNkXckREOkPHosePD+JPf3A4r21r3A4EPQ40BdxYEfLgqo5aNNW40RT04ETfJGq9TjTVuOF2Vu+Kg1T5trXX4q9/8Ur8f9ntONI7gYMXx3GoewJdo1G8enEcDx+JIZVZ+PTq7Tva8OW7rylTxEWXz5hVsMPdE/jVf9ub17Yuuw0BjwMBjwONNW5sbg3g5g2NaA560FbrwZnBCMciqnjbV9Ri+4pa/Pk7rsDJgTBeOjeC432TODMYwTOnhzASSSI9+1OfWXasrMX9H7+5TBEXXUnGooHJON771RcBAAGPA7/3hg34vTdsxPde6V7uUxumJejBh29eh++90o0fvdqDH73aY3RIeRNo8TcH3bAJcO/z5xf9G0vm1ar/LGu9Ttz/au90wrzO58TP//wtJdtvKZNKc9Wpz/4NzWcbiMhHAXxU/zYiIoutP9wIwGzLNyw7pvcXKZBZzHisgEXiKtGxWIwpj9X7zRlXPjGtLkcgMHYsAsz581kKvg7zqZTXcsnrKMb4/hUAX8n/ico1FuVr0fFoiWNRTkl+b/I83Eb+zlbrvo3ev2X3vcyxqBHA8AUA8nt5P8ZyYxGw7PEIf6x/wfj3yXzMGFdRY+osztOY8TgB5oyrZDFdWOB2+cyiD8/FVfBYVMqkUjeAjhnfrwTQu4RtoJS6B8A9+e5YRPYrpXblH2rpmTEmgHEVwowxAeaMy2QxGTYWAaY7FkvG12E+lfJaKuV1FNGi49FSxqIcI483922Man3t1brvIirZudFczHrMzBgXY8qfGeMyY0zA8uIqZWv9lwFsFJG1IuIC8D4A98/a5n4AHxTN9QAmitHDhIhoBo5FRGQl+YxZRESlxrGIiPJSskolpVRaRD4O4BFoy1Deq5Q6KiIf0+//KoCHoC3hfQbaMt6/Xqp4iKg6cSwiIiuZb8wyOCwiqjIci4goX6Wc/gal1EPQLtZm3vbVGf9XAH63BLtedglmCZgxJoBxFcKMMQHmjMtUMRk4FgEmOxbLwNdhPpXyWirldRTNXGNWERl5vLnv6ts/921hJR6LZjPrMTNjXIwpf2aMy4wxAcuISxZaqo+IiIiIiIiIiGgupeypREREREREREREFaoikkoiUi8ij4rIaf3funm26xSRwyLyqojsL1Est4vISRE5IyKfmuN+EZF/1O8/JCLXlCKOJcR1m4hM6MfmVRH58zLEdK+IDIrIkXnuL/uxyiOmsh8nfb8dIvKkiBwXkaMi8gdzbFPW45VnTIYcr3Iz6/t+KfJ4Le/XX8MhEXlBRHYaEediFnsdM7a7TkQyIvKecsaXr3xeh/4+e1V/Hz5d7hjzlcfvVq2IPCAiB/XXwt5mS2T0mJTH/reIyIsikhCRPy7zvks2huWx7zv1/b4qIvtF5OZy7XvGdkUf8/J43SU9FzBynMzjtX9yxus+oh/7+mLt34qMHp+WGJMh5z5mPJcx63mJGc8xxJrXukv7XVdKWf4LwOcAfEr//6cA/O0823UCaCxhHHYAZwGsA+ACcBDAFbO2uQPAwwAEwPUA9pbh+OQT120AflLmn9vrAFwD4Mg89xtxrBaLqezHSd9vG4Br9P8HAJwy+ncrz5gMOV5l/tmY8n1fwtdyI4A6/f9vM+Nryed1zNjuCWj9It5jdNxL/HmEABwDsEr/vtnouJfxWj4N/e83gCYAowBcRsdutS+jx6Q8998M4DoA/x+APy7zvksyhuW57xq81npiB4AT5dr3jO2KOubl+bpvQ4nOBYwcJ/M97jO2fyeAJ0pxHKzyZfT4tIyYyn7uY+T7epnHqiTvtyLEVfZzDFjzWndJv+sVUakE4E4A39D//w0Av2BQHLsBnFFKnVNKJQF8R49tpjsBfFNpXgIQEpE2E8RVdkqpZ6C9oedT9mOVR0yGUEr1KaUO6P8PAzgOYMWszcp6vPKMqRqY9X2/FIu+FqXUC0qpMf3blwCsLHOM+ch3zPs9AN8HMFjO4AqQz+u4G8APlFJdAKCUsvJrUQACIiLQLr5HAaTLG2ZFMHpMymccGVRKvQwgVaR9FrLvUo1h+ew7ovQzdQB+aL/zZdm3rhRjntHnmEaOk4W+9rsAfLtI+7Yqo8enJcVk0LmPGc9lzHpeYspzDCte6y71d71SkkotSqk+QLvQhfYJ2FwUgJ+JyCsi8tESxLECwMUZ33fj8ovsfLYxIi4AuEEvCXxYRLaVOKZ8GHGs8mHocRKRNQCuBrB31l2GHa8FYgLM93tVbGZ93y9FoXF+GNonLGaz6OsQkRUA3g3gqzCvfH4emwDUichT+t+2D5YtusLk81q+BGArgF4AhwH8gVIqW57wKorRY5KR452RY1he+xaRd4vICQAPAviNcu27hGOe0eeYRo6Tef++iYgPwO3QLv6rmdHj01Jjmqlc5z5mPJcx63mJVc8xzH59kPfvuqPEgRSNiDwGoHWOu/5XAU9zk1KqV0SaATwqIif0bF2xyBy3zf4UKp9tii2ffR4AsFopFRGROwD8CMDGEse1GCOO1WIMPU4iUgPthOQTSqnJ2XfP8ZCSH69FYjLj71WxmfV9vxR5xykir4f2x6ZoPUGKKJ/X8UUAf6KUymgfWplSPq/DAeBaAG8E4AXwooi8pJQ6VergCpTPa3krgFcBvAHAemh/p5+dY1yhhRk9Jhk53hk5huW1b6XUDwH8UEReB+AvAbypTPv+Ikoz5hl9jmnkOFnI7/o7ATyvlDJdNXyZGT0+zcWs5z5mPJcx63mJVc8xTHt9UOjvumWSSkqpef/oisiAiLQppfr0krE5y+yUUr36v4Mi8kNopXLFTCp1A+iY8f1KaNnQQrcptkX3OfMNpZR6SES+IiKNSqnhEse2ECOO1YKMPE4i4oSWvPmWUuoHc2xS9uO1WEwm/b0qNrO+75cirzhFZAeArwF4m1JqpEyxFSKf17ELwHf0k7BGAHeISFop9aOyRJiffH+3hpVSUwCmROQZADuh9Tgzk3xey68D+Bt9etAZETkPYAuAfeUJsWIYPSYZOd4ZOYYV9LqVUs+IyPoi/U00cswz+hzTyHGykJ/5+8Cpb4Dx49NSYzLi3MeM5zJmPS+x6jmGKa8PlvS7rkrcDKocXwA+j0sbdX9ujm38AAIz/v8CgNuLHIcDwDkAa/Fak7Bts7Z5Oy5tyLWvDMcnn7ha8VrzyN0AunLflzi2NZi/UVjZj1UeMRl1nATANwF8cYFtynq88ozJkONVzi+zvu9L+FpWATgD4Eaj413O65i1/ddhzkbd+fw8tgJ4XN/WB+AIgO1Gx77E1/LPAD6r/78FQA9KuLhGpX4ZPSYV8v4D8FkUt1G3YWNYnvveMONv4jX67/iy/yYaOebl+bpLdi5g5DiZ73EHUAuth4m/mL9zVvwyenxaRkxlP/cx8n29zGNV9vOSPOMy5BwD1rvWXdLvumUqlRbxNwC+KyIfhvaH6r0AICLtAL6mlLoD2i/PD/VMrgPAfUqpnxYzCKVUWkQ+DuARaF3o71VKHRWRj+n3fxVaZ/47oP2wotCypiWVZ1zvAfDbIpIGEAPwPqX/ZpWKiHwb2oogjSLSDeAzAJwzYir7scojprIfJ91NAD4A4LCIvKrf9mlob3yjjlc+MRl1vMrGrO/7pcjztfw5gAYAX9HH07RSapdRMc8lz9dhevm8DqXUcRH5KYBDALLQ/ubNuUyskfL8mfwlgK+LyGFoJ1h/oiqrqrEsjB6T8tm/iLQC2A8gCCArIp+AtlLPsqYhGDmG5bnvXwLwQRFJQfub+CvF+Jto5Jhn9DmmkeNkAcf93QB+prTKjapm9Pi0jJjKfu5jxnMZs56XmPUcw6LXukv6XZcijelERERERERERFRFKmX1NyIiIiIiIiIiKiMmlYiIiIiIiIiIqGBMKhERERERERERUcGYVCIiIiIiIiIiooIxqURERERERERERAVjUomIiMgAIvJ1EVEissboWIgoPyLylIhw6WQiqgrFOlcRkQ/pz/Oh4kRGZsKkEpWEiNhF5CMi8rSIjIpISkQGReSQiHxNRN5ldIxEZG76yYdlL95E5LP6a7jN6FiI6DW5sWXGV0JEhkTkgH6O8jYRsRsdZymJSKeIdBodBxEVLp/zI/09bukPrvjhm3U4jA6AKo9+IvYTALcDGAfwIIBuAPUA1gO4G8AWAPcbFCIRERHR/9H/tQMIAdgG4AMAPgxgv4i8Xyl1atZjPgjAV7YIiYiM9acA/gZAj9GBkHkxqUSlcBe0hNJBALcqpSZm3ikiPgB7jAiMiIiICACUUp+dfZuItAD4JwDvBfCYiOxSSg3OeExX+SIkIjKWUqoPQJ/RcZC5cfoblcKN+r9fn51QAgClVFQp9eTs20XkLhF5UkTGRCQuIsdF5M9ExD1jmzq9nDMhItfOerwt1+tARH616K+KiEwtnzFkxrZKHy8aReQeEenTx5WjIvLr8zy/W5/Sdk7f9ryI/JV+uxKRp2Zs2wngM/q3T86cajPPc/+WiBzW4x7QY6pd/lEhokIopQYAvA/AUwA6AHx65v1z9VQSEZeIfFxEHhKRC/r4MCoij4nI2+baT276mYjUiMgXROSiiMRE5FUR+QV9G4eIfFpETutjw1kR+fh8sYvIW/UYhvUYzorI50UkNGOb2/T4VwNYPWsa4NdnPd8WffrJRf35BkTkPhHZPMe+c9NU1onI74nW7iA2c1wkInNY4nt7zazbRUT+QESO6eNTj4h8SURqZZHptSLyen0sDYvIpIg8KCJbZ22jAPya/u35GePUvM9LxmGlEpXCiP7vpnwfICL/BuA3oE2T+wG0aXPXA/hLAG8UkTcrpdJKqTEReR+AZwH8l4hco5Sa1J/mMwBuhZbM+s/ivBQisoJ8x5BZDwsBeB5AEsD3AHgAvAfAvSKSVUp9Y8bzC4DvA3g7gNMAvgTACeBD0KbMzPZFAL8AbUz6BoDOBcL/HIC3AngAwM8AvB7ARwBsAPCGxV47ERWXUiorIn8F4DYAd4nIHyqlFupfUg/gHwC8AOBRAEMA2gC8E8BDIvIRpdTX5nicU9++HsCPAbigVXt/X0TeAuB3oFV2PwwgAa166p9EZEgp9V8zn0hE/hzadL5RaC0IBgHsAPDHAO4QkRv086VOfbtP6A/94oyneXXG890ObSx1QhubzgBYCeAXAbxdRF6vlDowx2v6BwC3QGt98BCAzNyHjIiMsIz39mxfBvDbAHoB3APtXOpdAHbrz52a53HvAHAntHHtqwCuAHAHgOtE5Aql1LC+3f+Bdh61E9q4Mq7fPg4yH6UUv/hV1C8AV0MbWLIA/gPaILV6ge0/BEBBG+C8s+77rH7fH8y6/X/qt39b//710E5cjgHwG30M+MUvfi3/S3+Pqzy2W8oYovSvrwGwz7j9CgBpAMdmbf8BfftnALhm3B4CcEK/76l59n3bPHF/Xb+/C8CqGbc79P0oALuN/jnwi1+V9pXP2ALADe2iSAFYO+P2p2Y/Vt925RzPUQvgCLREz+yxqVN/7gcAuGfcfot++yiAlwGEZty3Tj+/+vms53q9/pgXZm6v35cbH78wx/4753ntdQDGAAwDuGLWfdsARAAcmHV7bjzrmXm8+MUvfhX/a8Y5zGcX+BrXt1kz43HLeW/PfJ7cOHVy1hjlmnH+0jnreXJjURrAG2fd99f6ff9zsX3zy5xfnP5GRaeU+jmAXwUwoP/7fQCdIjIiIj8UkXfOesgfQBtgfkMpFZt1319Cq3x6/6zbPw/gpwDeJyKfAvAtaCdav6KUmirqCyIis1vKGAIAUQB/pJSa/iRdKXUMWvXSVhEJzNg2V4L9Z0qp5Iztx/V9LMdfqBl9WpRWUfXv+re7l/ncRLQESqkEXqu8blpsW6VU9xy3TwC4F9qF3HXzPPwT+r5yj3kWwHn9MX+ijzG5+85BG5+ulEtXp/t9/d+PzNxef8zXoVUgzTUGzueD0BLmn9HHxJnPdxTAvwK4WkSumOOxn1NKnS9gX0S0dJ9Z4GuuKfTLeW/PlDsn+v9mjVFJaI29F/IdpdTjs267R/+X5zwWxelvVBJKqe+KyA+hfXp2M7TqpZuhlTH+goh8E1rG2gutrHEYwCe0GSaXSQC4ZJ6tUkqJyAehnSj9tX7zbymlDhf7tRCReYnW+L/gMUR3Wr02fXami/q/IQBh/f9XQ6u+fGGO7Z8rIOS57F8ghrplPjcRLV1uQFlw6W4AEJFtAD4J4HXQpr55Zm2yYo6HjSulzs5xey+AtQBemeO+Hmir1bXitdWYboBWVfVeEXnvHI9xAWgSkQal1Mgc9892g/7vThH57Bz359obbIVWIT7Tvjyen4iKQCk150kPMN3bcfWsm5fz3p7pav3fuc5/XoL2Qd98eM5TgZhUopJRSqWg9Qf5GQDon6r9ErRP7T4I4IfQSrsF2qeAn5n7meZ9/iEReQZaQ80RaFPtiKi61GGJYwjmn5efOxmaWQlQC2BUXd6XCdCqMpdjrjjmioGIykREPNB6HQFaj6SFtr0ewBPQzqsfB3A/gEloieiroPUPuWzBAACXLWaiSwPTlU5z3getZ0lOg77vxcbAGrxWfbWQBv3fj+TxfLP15/H8RGSM5by3Z8pVQV12/qOUyojIQuPM+ByPSesfCvKcx6KYVKKy0aeYfFdErgTwZ9Aa0D6m3/1zpdQ1hTyf3rD7fdAqFBoB/CMWHySJqLLkLroKHkMKNAmgXkQccySWWkq4XyIyxs3QzpMHlFKdi2z7Z9Aqr1+vlHpq5h0i8qfQkkqlNAHAppSqX3TL/J8PAHYqpQ4V+NhFq7qIyDDLeW/PlKvybgFwbuYdehFBA16rpKQqwJ5KZITcdBJRSkUAHAWwTUTyPhkSkfXQ5t8OAbgGWlO439QTTURUJZY6hizBz6H9zbxxjvtunucxuV5N/OSNyEJExAbgf+nf3pfHQzZAq2R8ao77bi1WXAt4CUCdPgUvXxnMPza9pP97y7KiIiKzKdZ7++f6v3Od/1yP4hWu8DzKIphUoqITkbtE5M36Sdns+1rxWjXRM/q/fw9tvv+9IhKa4zF1InLNjO9dAP4LWmnmrymlLgK4G1pJ9z0isqGYr4eITK+gMWSJvqn/+1f6GJR77loA/3uex+TKv1ctc99EVCYi0gzgOwBug7Yy4//N42Gd0CoZd8x6rg8DeGuRQ5zLF/R//1VE2mffKSJ+fYreTCPQ+ix553i+f4c2ReUzInJZ41wRsYnIbcuKmIiMUKz3du6c6H/p50G5x7uQ35iZL55HWQSnv1Ep7IG2GlO/iDwHbRUTQGs6+XZoJeI/BvA9AFBK3Ssi1wL4HQBnReQRaCdy9fpjXgdtEPyY/jyfA3AtgL9XSj2sP0ePiHwI2tK83xGRG2eu0ERE1iUiX1/g7t9ZwhiyFN+ENt32dgBHROR+aD1Nfgla08nN0PqnzPSkfttfi8h2aMv4Qin1V8uIg4iKZEajWhu0xvzboH3y7oLWcPr9SqnhPJ7qi9CSR8+JyHehTTHZpT/X9wC8p5hxz6aUelxfCfevAZwWkYegnXvVQGvUeyu0hrq3z3jY49BWpPup3p8yAeCgUuoBpdSIiLwHWu/Ll0TkcWgVoVloF3c3QJveMrsZORGZWLHe20qpp0XkHgAfBXBURL4PbbGAd0Ib/3px+TnRUjwObQGEfxWR7wGIQFvg4EtFeG4qIiaVqBT+DsBpAG8CsAPaiZYHWrb5KWil5Pcppabn3SulfldEHoZ20fcmaCd3o9AuDD8P4D8BQETeCS1htR/Ap2buVCn1ExH5AoA/1B/zB6V6gURUVr+2wH2fABDNdwxZKn3FyXcD+DSADwD4PQB9AL4B4CvQeqZMznrMcRH5NQB/DC3hlTtJY1KJyBxyja2T0KbmX4CWQP4+gJ8ppfK6KFJK/VQ/P/kzAL8CbcrGPmgr4K5DiZNKegx/KyLPA/h9aMmsO6Fd3PVAaxcwexrfX0EbJ98J4CZo00u+Ae3DuVyiage08eut0KbLJKFdLD4B7RgRkcUU8b392wBOAPgtaOdeI9CSVZ8G0A1grpUtC431ERH5H9BmufwhtIT/BQBMKpmMzLiuJyIiogKJyJuhrXL5N0qpPzU6HiIiIiIjiMhGAKcAfEcpdZfR8VB5sKcSERFRHubpVdIA4G/0b39Y3oiIiIiIyk9EWmf3zxURH7TpwADPiaoKp78RERHl5+9FZCeAF6CtPLkSwNug9W76F6XUPiODIyIiIiqTTwC4S0SegtYOoBXAG6GdGz0M4L8Ni4zKjkklIiKi/PwAQAu0HiQhAHFoDS7vBfA148IiIiIiKqtHAewE8BZoH66loU17+0cAX1TssVNV2FOJiIiIiIiIiIgKxp5KRERERERERERUMCaViIiIiIiIiIioYEwqERERERERERFRwZhUIiIiIiIiIiKigjGpREREREREREREBWNSiYiIiIiIiIiICsakEhERERERERERFYxJJSIiIiIiIiIiKhiTSkREREREREREVDAmlYiIiIiIiIiIqGBMKhERERERERERUcGYVCIiIiIiIiIiooIxqURERERERERERAVjUomIiIiIiIiIiArGpBIRERERERERERWMSSUiIiIiIiIiIioYk0pERERERERERFQwJpWIiIiIiIiIiKhgTCoREREREREREVHBmFQiIiIiIiIiIqKCMalEREREREREREQFY1KJiIiIiIiIiIgKxqQSEREREREREREVjEklIiIiIiIiIiIqGJNKRERERERERERUMCaViIiIiIiIiIioYEwqERERERERERFRwZhUIiIiIiIiIiKigjGpREREREREREREBWNSiYiIiIiIiIiICsakEhERERERERERFYxJJSIiIiIiIiIiKhiTSkREREREREREVDAmlYiIiIiIiIiIqGBMKhERERERERERUcGYVCIiIiIiIiIiooIxqURERERERERERAVjUomIiIiIiIiIiArGpBIRERERERERERWMSSUiIiIiIiIiIioYk0pERERERERERFQwJpWIiIiIiIiIiKhgTCoREREREREREVHBmFQiIiIiIiIiIqKCMalEREREREREREQFY1KJiIiIiIiIiIgKxqQSEREREREREREVjEklIiIiIiIiIiIqGJNKRERERERERERUMCaViIiIiIiIiIioYEwqERERERERERFRwZhUIiIiIiIiIiKigjGpREREREREREREBWNSiYiIiIiIiIiICsakEhERERERERERFYxJJSIiIiIiIiIiKhiTSkREREREREREVDAmlYiIiIiIiIiIqGBMKhERERERERERUcGYVCIiIiIiIiIiooIxqURERERERERERAVjUomIiIiIiIiIiArGpBIRERERERERERWMSSUiIiIiIiIiIioYk0pERERERERERFQwJpWIiIiIiIiIiKhgTCoREREREREREVHBmFQiIiIiIiIiIqKCMalEREREREREREQFY1KJiIiIiIiIiIgKxqQSEREREREREREVjEklIiIiIiIiIiIqGJNKRERERERERERUMCaViIiIiIiIiIioYEwqERERERERERFRwZhUIiIiIiIiIiKigjGpREREREREREREBWNSiYiIiIiIiIiICsakEhERERERERERFYxJJSIiIiIiIiIiKhiTSkREREREREREVDAmlYiIiIiIiIiIqGAOowMoVGNjo1qzZo3RYRDRMr3yyivDSqkmo+NYKo5FRJWBYxERmYHVxyKA4xFRJVjKWGS5pNKaNWuwf/9+o8MgomUSkQtGx7AcHIuIKgPHIiIyA6uPRQDHI6JKsJSxiNPfiIiIiIiIiIioYEwqERERERERERFRwZhUIiIiIiIiIiKigjGpREREREREREREBWNSiYiIiIiIiIiICsakEhERERERERERFYxJJSIiIiIiIiIiKhiTSkREREREREREVDAmlYiIiIiIiIiIqGBMKhERERERERERUcFKmlQSkdtF5KSInBGRT81xf62IPCAiB0XkqIj8einjISIiIiIiIiKi4ihZUklE7AC+DOBtAK4AcJeIXDFrs98FcEwptRPAbQD+TkRcpYqJiIiIiIiIiIiKo5SVSrsBnFFKnVNKJQF8B8Cds7ZRAAIiIgBqAIwCSJcwJiIiIiIiIiIiKoJSJpVWALg44/tu/baZvgRgK4BeAIcB/IFSKlvCmIiIiIiIiIiIqAhKmVSSOW5Ts75/K4BXAbQDuArAl0QkeNkTiXxURPaLyP6hoaFix0lERERUUiLiEZF9M/pI/p85trlNRCZE5FX968+NiJWIiIgoX6VMKnUD6Jjx/UpoFUkz/TqAHyjNGQDnAWyZ/URKqXuUUruUUruamppKFjARERFRiSQAvEHvI3kVgNtF5Po5tntWKXWV/vUXZY2QiIiIqEClTCq9DGCjiKzVm2+/D8D9s7bpAvBGABCRFgCbAZwrYUxEREREZad/gBbRv3XqX7MruImIiIgspWRJJaVUGsDHATwC4DiA7yqljorIx0TkY/pmfwngRhE5DOBxAH+ilBouVUxERERERhERu4i8CmAQwKNKqb1zbHaDPkXuYRHZVt4IiYiIiArjKOWTK6UeAvDQrNu+OuP/vQDeUsoYiKg6iMi9AN4BYFAptX2O+z8J4P36tw5oiwQ0KaVGRaQTQBhABkBaKbWrPFETUTVRSmUAXCUiIQA/FJHtSqkjMzY5AGC1UioiIncA+BGAjbOfR0Q+CuCjALBq1aqSx01EREQ0n1JOfyMiKqevA7h9vjuVUp/P9SkB8KcAnlZKjc7Y5PX6/UwoEVFJKaXGATyFWWOWUmoyN0VO/2DOKSKNczyevSaJiIjIFJhUIqKKoJR6BsDoohtq7gLw7RKGQ0R0CRFp0iuUICJeAG8CcGLWNq0iIvr/d0M7Txspc6hEREREeSvp9DciIrMRER+06oCPz7hZAfiZiCgA/6KUumeex3LKCREtVRuAb4iIHVqy6LtKqZ/k+kzq7QHeA+C3RSQNIAbgfUopNvMmIiIi02JSiYiqzTsBPD9r6ttNSqleEWkG8KiInNArny6hJ5vuAYBdu3bxQo+I8qaUOgTg6jlun9lr8ksAvlTOuIiIiIiWg9PfiKjavA+zpr7piwZAKTUI4IcAdhsQFxERERERkaUwqUREVUNEagHcCuDHM27zi0gg939oK1IemfsZiIiIiIiIKIfT34ioIojItwHcBqBRRLoBfAaAE7hkesm7AfxMKTU146Et0Jb2BrQx8T6l1E/LFTcREREREZFVMalERBVBKXVXHtt8HcDXZ912DsDO0kRFRERERERUuZhUqkL37e2a8/a793A1KyJ6zVxjBccJIjIjjldEZEWzxy6OW2RF7KlEREREREREREQFY1KJiIiIiIiIiIgKxqQSEREREREREREVjEklIiIiIiIiIiIqGJNKRERERERERERUMCaViIiIiIiIiIioYEwqERERERERERFRwZhUIiIiIiIiIiKigjGpREREREREREREBWNSiYiIiIiIiIiICsakEhERERERERERFYxJJSIiIiIiIiIiKpjD6ACIiKi87tvbddltd+9ZZUAkRERERERkZaxUIiIiIiIiIiKigrFSiYiIiIgsY65qSyIiIjIGK5WIiIiIiIiIiKhgTCoREREREREREVHBOP2NiIgu0Tk8hXg6g0xWwW4To8MhIiIiIiKTYlKJiIgAAEopfPGx0/iHx08DAFbWeXH37lUI+VzT23DlOCIiIqLCsR8cVSpOfyMiIgDAg4f78A+Pn8YvXrMCf/UL2zEUTuDe5zuRSGWMDo2IiIiIiEyISSUiIkIincHf/vQEtrQG8Pn37MSvXr8aH7h+NUYiCdx/sNfo8IiIiIiIyISYVCIiIvz0SD8ujsbwJ7dvme6jtK6pBrdtbsLPL47j/PCUwRESEREREZHZMKlERER44GAfWoMe3Lqp6ZLbb93UjJDXiQcP9UIpZVB0RETzyyqFeCrDMYqIiMgAbNRNRFTlYskMnjk1hA/csBq2Wau9uRw2vGlrC753oBunBiLY3BowKEoiqnRLWQjg4mgU39p7AZPxNFbV+/C+6zouWVyAiIiISotJJZOab3UArrJERMV2cmASyUwWb9/RNuf9OztCePT4AJ4+NcikEhGZxnA4ga89dw4BjxNv3NKMZ88M497nO/F7b9gAp53F+EREROXAv7hERFXu3NAUgh4HrloZmvN+u01wy8ZGdI5EcWGEvZWIyHhKKfzw1R7YbYKP3rIOb9zagl/dsxrDkQQeOz5gdHhERERVg0klIqIq1zkyhd1r6y+b+jbTrtX18LnseOrkUBkjIyKa24n+MM4PT+H2bW0Iep0AgA3NNbh2VR1eODuCyVjK4AiJiIiqA6e/ERFVsXA8heFIEg6bbd5pt4DWW+nG9Q147PggBifjaA56yhglEdGlnj09jJDXiWtX111y++u3NONA1xiePzuMj9223qDoiIiIqgcrlYiIqljnSBQAsLbRv+i2u9c2wC6CfZ2jpQ6LiGhePWMxdI5M4aYNjbDPqrCs97uwfUUt9p0fRTSZNihCIiKi6sGkEhFRFbs4GoXDJmgPeRfdtsbtwLYVQRzoGkMynS1DdEREl3v5wiicdrmsSinn+nUNSKSzeORof5kjIyIiqj5MKhERVbHe8Rhaaz2Xfdo/nz1rGxBPZXG4Z7y0gRERzSGeyuBQ9zi2tdfC47TPuc3qBh/q/S5875XuMkdHRERUfZhUIiKqUkop9E3E0Va7eJVSzpoGH5oDbuw9zylwRFR+jx0fQDyVxTWr5q5SAgCbCK5eFcILZ0fQPxEvY3RERETVh0klIqIqNR5LIZbKoK02/6bbIoLda+vRPRZDz3ishNEREV3ugYO9CLgdWNe0cB+4K9troRTw6DFOgSMiIiolJpWIiKpU37j2CX4+/ZRmurqjDg6b4MCFsVKERUQ0p0gijSdPDmH7ilrYZOEpu00BN9Y1+vGzYwNlio6IiKg6MalERFSl+iZiEACtwfwrlQDA67Jja1sQB7vHkc6yYTcRlcdjxwaQTGexY2XtotuKCN6yrRUvnh3BRCxVhuiIiIiqE5NKRERVaiCcQL3fBZej8D8F16wKIZrM4FR/uASRERFd7ieH+tAa9KCj3pfX9m/Z1oJ0VuGpk4MljoyIiKh6MalERFSlRiIJNNS4lvTYDc0B1LgdONA1XtygiIjmMBlP4ZlTQ3j7jrZFp77lXLUyhKaAG48cZV8lIiKiUmFSiYioCimlMBJJoqHGvaTH222CqzpCONkfxuhUssjRERFd6tGjA0hmsnj7jra8H2OzCd58RQueOjmEeCpTwuiIiIiqF5NKRERVKJxII5nJotG/tEolALh6VQgZpfDAwd4iRkZEdLkHDvViRciLqztCBT3uLVe0IJrM4MWzI6UJjIiIqMoxqUREVIVGIlp10VIrlQCgrdaLtloPvn+gu1hhERFdZiSSwLOnh/HOne2QPKe+5Vy/rgFuhw3PnB4qUXRERETVjUklIqIqNBJJAAAal5FUAoBrVtXhUPcETg+wYTcRlcZDR/qRySrceVV7wY/1OO3YvbYez54eLkFkRERExKQSEVEVGplKwiZArde5rOfZ2RGC3Sb4HquViKhE7n+1B5taarClNbCkSePtrQAA8FVJREFUx79uYxPODEbQNxErcmRERIU71D2Or79wHo8dHzA6FKKiYFKJiKgKDUcSqPe7YLcVNpVkthq3A7dsbMRPDvZBKVWk6IiIND3jMbzcOYZ3LWHqW84tmxoBgNVKRGS4sakkvrv/IrpGo3jixCDODUWMDolo2ZhUIiKqQiORJBr8y5v6lvP2K9vQMx7Doe6JojwfEVFObiGAd+1cseTn2NwSQFPAzaQSERnuqVODEBH8zm0bUO934SeH+owOiWjZmFQiIqoySimMTCXQWLP0ld9messVrXDaBQ8e5okRERWPUgo/PNCDqzpCWNXgW/LziAhu2dCI588MI5tlRSURGSORzuBA1ziuXVWHxho3blzfgP7J+HSfSyKrYlKJiKjKhONppDJqWSu/zVTrc+KWjU148BCnwBFR8VwcjeLkQBi/vKtj2c91y6ZGjE4lcaxvsgiREREV7vzQFDJZhe0ragEAW1qDAIDj/VzshKzNYXQAVJj79nbNefvde1aVORIisqrhKe0TsQZ/cSqVAOCOK9vwxIlBvHpxHFevqiva8xJR9dp7fhQ1bgfetYRV32a7aYPWV+mfHj+NWzc3T9/O8yciKpdTgxE47YLVeuVlvd+F5oAbJ/omcbM+RhFZESuVqtyx3kn8/aOncO9z53FmkFlyomowEkkCQNEqlQDgzVe0wGkXPMQpcERUBNFkGod7JvALV7ejxr38z0CbAx5sbK5B50i0CNERERXu9EAYaxv9cNpfuwTf0hpA58gUUpmsgZERLQ+TSlXs9GAY39p7ATYBeidi+Mg3X8FkPGV0WERUYiORBOw2QcjnLNpz1nq1KXAPHe7nFDgiWrYDXeNIZxXu3r26aM+5a009LoxOIcsxioiW4b69XZd9LaZ/Io6RqSQ2NAcuub2j3oes0u4nsiomlapUVin89Eg/6vwu/PZt6/H+PavRNRrFl544Y3RoRFRiI1NJ1PtcsC1xee7ZcidUtV4nesZj+MKjp4vyvERUnZRS2Hd+BKvqfbiiPVi0571uTR3iqSwGJ9kUl4jK61D3OABgVZ33kttXhLTvu8dj5Q6JqGiYVKpSx3on0TcRxxu3NMPtsGNtox93XNmGb+/tQiSRNjo8IiqhkUgSDUVa+W2mza3ap28n+tkIl4iW7tzwFIYjSexeW1/U571ujfZ8nSNTRX1eIqLFHO6ZgE2A1tpLk0q1Xif8bgd6xphUIutiUqlK7escRcjnxM6O0PRtH755LcKJNP57/0XjAiOikspmFUamEmgsYj+lnKDHiRUhL05wFRMiWoZ950fhddpxpb5CUrGsrPMi6HHgApNKRFRmh3sm0BzwwOW49PJbRLAy5EXPOPu9kXUxqVSFJmMpnB2M4OqO0CXTX67qCOHKFbX40au9BkZHRKU0EI4jlVGoL+LKbzNtaQvg4mgUwxFOLyGiwoXjKRzrncQ1q0KXNLMtBhHB6gY/LrBZNxGVkVIKh7snsGLW1LecFXVeDE4mkEyzWTdZE5NKVehg9zgUgKs7Ll/2+44r23Dw4ji6x3jCRVSJzg9rn9CXolIJALa2BqEAPHlisCTPT0SV7cCFMWSUwu61DSV5/tUNPozHUhiPJkvy/EREs/XqTbpz/ZNmaw16oAAM8QM5sigmlSwmk13+iiXHeifRXutBY+Dyi8o7rmwFADx8uH/Z+yEi88l9Ql+KnkoA0FbrQdDjwOPHmVQiosJklcK+zlGsbfSjaY5zlGJY0+AHAFYrEVHZnNR7TbbVeua8PzfeDYW5AhxZE5NKFtE3EcNXnz6LP//xEfzHi52YjKWW9DxjU0l0jUaxuXXu1VRWN/ixtS2IR48PLCdcIjKpzuEpOGyCWq+zJM8vItjSGsSzp4eQSGdKsg8iqkxnBiMYi6awp8gNumdqCXrgdtjYrJuIyuZkfwQA0ByYO6nU4HfBJsBQmJVKZE1MKllAOJ7CN17oxNhUEtetrcfZoSl848VOxFOFX7A9fWoICsAWfZWmubxuUyN+3jWGaJKrwBFVmvPDU6j3uy7pp1Zsm1sDmEpmcODCeMn2QUSVZ+/5UfhddlzRPvcHX8Vgtwk66ny4OMpKJSIqj9MDYbQGPfC67HPe77DbUOdzMalEllXSpJKI3C4iJ0XkjIh8ao77Pykir+pfR0QkIyKl+3jKoh483IdYKoNfu3ENfuGqFbh7zyr0T8Txs2OFVxM9cWIQfrdj3kZxAHDzhkakMgr7zo8uJ2wiMqHOkSk0lKhJd87aRj/sNsFzZ4ZKuh8iqhx9EzGc6JvErjX1cNhK+5nnijovBiYTSGXYFJeISu/UYBibFvhAH9CmwLGnElmVo1RPLCJ2AF8G8GYA3QBeFpH7lVLHctsopT4P4PP69u8E8IdKKWYyZhgKJ3C4ewK3bGxCu97cbVNLALvX1mPf+RHsWVuPluDcpZSzpTNZPH1qCJtbAgtWKVy3ph4uhw3PnxnGbZubi/I6iMh42azChZEorltT2ty9x2nH1R0hPHd6GJ98a0l3RUQmdN/erstuu3vPqgW3efSY1suxmOPTXHEAwIqQFxmlMDDJ/iVEVFqZrMLpgQg+cP3Ciw80B9w4PRhBOpOFo8grXxKVWsmSSgB2AzijlDoHACLyHQB3Ajg2z/Z3Afh2CeMpm/lOYmafUOXjuTNDcNgFN29svOT2N21twasXx/HEiUHctTu/5z3QNY6JWAqbF8mUe5x27Fpdh+fOjBQcLxGZV/9kHIl0tmRNume6eWMj/uHx0xibSqKuxJVRRGRt6UwW+zrHsLk1gPoyjBe5FZh6xmMl3xcRVbeLo1Ek0llsagkgvcCCS00BNzJZhe6xGNY0+ssYIdHylTINugLAxRnfd+u3XUZEfABuB/D9EsZjOalMFod7JrC9vRY17kvzf363A7vX1uNIzwRGp/JbFveJE4Nw2AQbm2sW3famDY043jfJub1EFaRzWGtM21hTmlWVZrplYyOUAl44y+Q0ES3scM8EphJp3LBu4U/yiyXkc8LnsqNnjEklIiqtUwNhAMDGloWvvxr82rnZBfZ7IwsqZVJprvlV86Vn3wng+fmmvonIR0Vkv4jsHxqqnh4dpwbCiKey2NkRmvP+G9c3wiaCF84O5/V8T54YxO619fA4524SN9PNG7TKqHyfm4jM77y+2lGpeyoBwM6VIQTcDvZVIqJFvXhuBE01bmzI40OvYhARrAh5WalERCV3elBb+W1jy8IzRXJV3V1MKpEFlTKp1A2gY8b3KwH0zrPt+7DA1Del1D1KqV1KqV1NTU1FDNHcDnVPwO+yY33T3CdZtV4ntq8I4kAeK7V1j0VxciCMN2zJr0fS9hW1CHoceP4Mk0pElaJzeApuhw1Br7Pk+3LYbbhhfQOePT0MpeYv9yai6nZxNIrusRiuX98AKeGqlLO11XoxyGbdRFRiJ/vDWBHyXjbrZLaAxwGHTbgyJVlSKZNKLwPYKCJrRcQFLXF0/+yNRKQWwK0AflzCWCwnk1U4NRDG1rYg7Lb5T7L2rG1APJXFAwfny9dpnjwxCAB5J5XsNsGN6xvx/JkRXhASVYjzw1GsbvAt2Ki/mG7Z2IjusRgujPAEiYjm9uyZYbgdNlwzT1V2qbTWupFRCuf1acFERKVwaiCMTYtMfQMAmwjqfC508ZyJLKhkSSWlVBrAxwE8AuA4gO8qpY6KyMdE5GMzNn03gJ8ppfhXfYaZTd0WsrrBh5agG//50tzNwXMePzGINQ0+rJun6mkuN25oQM94DN3sOUBUES6MTGFNQ3maP963twtj0RQA4AuPnZp3AQMiql79k3Ec7ZnADesa4M5jan4xtQa1Zt3H+ybLul8iqh7pTBbnhqYWvZ7Lqfe7OP2NLKmUq79BKfUQgIdm3fbVWd9/HcDXSxmHFZ0eDMMmmHfqW46IYM/aBtx/sBcHL47P2X9pMp7CC2dH8IHrVxcUw/V6w8wXz46go953yX3FXOGOiEovm1W4MBrNu1qxGBr8LoS8TpwZjGDP2vI04CUi63js2ACcDtt0H8dyagy4YBfBif4w7iz73omoGlwYjSKZyS7aTymnzu/E0Z5JKKXKOh2YaLlKOf2NluH0YAQddT54XYt/cndVRwg+lx3/8dKFOe9/5Eg/kuks3rGjraAYNjbXoMHvwkvnuHoTkdX1TsSQTGfLukytiGB9cw3ODU0hy2m0RDTDyf5JHOubxG2bmuBbpNdIKThsNjQF3DjZHy77vomoOpzSx5d8pr8BQL3PhXAijYlYqpRhERUdk0omFI6n0DMWw/o8V0HxOO34xWtW4P5XezEYjl92//0He7Gq3oerCuxXICK4fl0DXjzHvkpEVtc5rJVTl2v6W86GphrEUhn0cpUlItINTsbxw5/3oCngxs0by1+llNNa68ErF8Zw396uS76IiIrh1EAEIsh7Zct6rgBHFsWkkgkd6BqHQmEXf7958zqksll8/fnOS27vGoni+TPDeNfO9iWVUV6/vgF9E3E22iWyuM4RrW3dmkbfIlsW17ombRw7qy+pS0TVbTKewke+uR/xVBbvu64DDptxp6LNATcmYikkUhnDYiAic5uddC4k8XxqMIyOOh98rvyqMev0pNLFUX4QR9bCpJIJvXx+FDYBOuq9eT9mTaMfb9veim++eAGDk69VK/3LM2fhsNnwgRsK66eUc8O6egDgFDgii+scnoLHaUNLwFPW/QY8TrQGPTgzxKQSUbWbiKXwgX/bh6O9k/iV6zrQVpv/eU4pNAfcAIChSMLQOIjKSUQ6RORJETkuIkdF5A/m2OY2EZkQkVf1rz83IlarO53nym85Ia+WVOqbYFKJrIVJJRPa1zmKtlov3I7CVkL55Fu3IJnJ4rMPHIVSCif7w/jv/d14z66VaAku7UJyfVMNGmvceJFJJSJL69RXfrPZyt/4cUNzDS6MRBFnNQBR1YolM/jgv+3Fsd4JfOX912BrW9DokNCYSyqFmVSiqpIG8D+UUlsBXA/gd0Xkijm2e1YpdZX+9RflDdH6kmlt5bd8m3QDgMdpg89lRw9bBpDFMKlkMqlMFgcvjmNNQ+FTVNY2+vEHb9yIhw7344P37sOv3bsPIZ8Tv/+GjUuOR+urVI+X2FeJyNLOD0+VvZ9SzvomP9JZhf2dY4bsn8gMRMQjIvtE5KBeHfB/5thGROQfReSMiBwSkWuMiLUUvvDYKRzsnsCX7r4Gb9nWanQ4AIAGvxs2AQaZVKIqopTqU0od0P8fBnAcwApjo6o8nSNTSGcVNheQVBIRtIe86Bu/vEcukZkxqWQyJ/vDSKSzWFm/tL4nv3PbenzqbVtwpGcC9X4X7v3QdWitXd50lxvWN2BgMoHzw1PLeh4iMkYmq3BxNFbWld9mWtPoh02A584MG7J/IpNIAHiDUmongKsA3C4i18/a5m0ANupfHwXwz2WNsEQGJ+P42rPncNfuVXirSRJKAGC3CRr8blYqUdUSkTUArgawd467b9CT4A+LyLbyRmZ9pwa0ld82FjD9DQDaQ170cvobWUz513ClBR3sHgcArAwtrc+AiOBjt67Hx25dX/Bj52s8d8O6BgDAS+dGsa6psIGRiIzXOx5DMpNdUgVkMbgddqyq9+F5JpWoiimt3DfXXMypf80uAb4TwDf1bV8SkZCItCml+soYatHtvzAGu03wx2/ZVPBjS70aW1OASSWqTiJSA+D7AD6hlJqcdfcBAKuVUhERuQPAj6Alu+d6no9CS4Jj1apVpQvYYk71h2ETrZVIIdprPTjWO1GiqIhKg5VKJnPo4gRCPuf0kpJmsLbRj+YA+yoRWdU5vcrQyKTw+uYaHOmdwNhU0rAYiIwmInYReRXAIIBHlVKzqwNWALg44/tuWHxaSiarcPDiOF6/uRkNNW6jw7lMU8CNkakEMllO8afqISJOaAmlbymlfjD7fqXUpFIqov//IQBOEWmc67mUUvcopXYppXY1NTWVNG4rOdwzgQ3NNfA4C+uR2x7yYjiSZB9KshQmlUzmYPc4dqwMQaT8zXTnIyK4YX0D+yqRqYnIvSIyKCJH5rl/3pVMROR2ETmp9zH5VPmiLo/z+spraw2a/gYAG5pqoBSYnKaqppTKKKWuArASwG4R2T5rk7n++F/2h1dEPioi+0Vk/9DQUAkiLZ5zwxGEE2n84jUrjQ5lTk01bmQVMBZlwpuqg2gXGf8G4LhS6u/n2aZV3w4ishvaNSP/gOdJKYXDPZPYvqK24Me26W1L+ifYV4msg0klE4klMzg9GMHOlYUPQKV2/boGDIUTODvEvkpkWl8HcPsi21y2komI2AF8GVovkysA3DXPKiiWdW54CgGPA401xlVArqzzocbtYF8lIgBKqXEAT+HyMasbQMeM71cC6J3j8ZapDDg/PAWbALduMmecDfq4OBJhUomqxk0APgDgDTM+aLtDRD4mIh/Tt3kPgCMichDAPwJ4n6ryT5YT6QxePj+K584MI5nOLrjtwGQCw5EErlxCUmmF3gKFfZXISthTyUSO9U0gk1XYsTJkuvn9r/VVGsGGZvZVIvNRSj2jN5ws1G4AZ5RS5wBARL4Dra/JsSKGZ6hzQ1NY1+g3tALSbtNWkmRfJapWItIEIKWUGhcRL4A3AfjbWZvdD+Dj+ji0B8CE1fspXRyNorXWA6+rsCkg5ZJrNzAylQCQ/ypNRFallHoOc1dFztzmSwC+VJ6IzC+dzeLfnjuP7jEt0bP33Ah+57YN845rh3u0nkhLSSq155JKXAGOLISVSiZy8KI2AJmxUml1gw+tQQ+nrpDVzbWSSd49TKw05WSm88NTpmiyf9OGRlwYieLiaNToUIiM0AbgSRE5BOBlaD2VfjKrOuAhAOcAnAHwrwB+x5hQiyOrFLrHYuioM2aRgHzUuB1wOWysVCKieT12bBDdYzH88q4O/PpNazAWTeL+gz3zbn+4ZwI2Aa5oDxa8r9yq3QOTTCqRdbBSyUQOdY+jNehBc9BjdCiXyfVVevb0EPsqkVXNt5JJXj1MAG3KCYB7AGDXrl2WeCPEkhn0jMewzsB+Sjk3b9B6fD5/Zhjv280VYqi6KKUOQVu6e/btX53xfwXgd8sZVykNhhNIpLNYVW/epJKIoNHv0iuViIguFUmk8cLZYVzdEcJVHSEAwBu2NOOx44O4bk1kzg/tXj4/is2tQfhchV9qe5x2BD0ODDKpRBbCSiUTOdQ9gR0mrFLKuX5dPYYjSZwZjCy+MZHJLLCSSV49TKzqvL7y29om45NKG5pr0Bxw41lOgSOqCt16VaKZK5UAoL7GzUolIprTvvOjSGfVJX3hbtnYhIDHgcdPDF62fSyZwSsXxtDgd+G+vV2XfOWrJejBwCQT3WQdrFQyiYlYCueGp/BL15pzdRQAuGGdVmXwwtkROO3MR5K1iEgrgAGllJq1ksk4gI0ishZAD4D3AbjbsECLLJdUWtdo/PQ3EcGtm5rw06P9SGWycNptc55k3b2HVUxElWAwnIDDJqg3cJGAfDT4XTjWq/W1tNvMs/ouERkrm1XYd34EG5trLplJ4rTbcOumJvzkUB/ODUcuOcfa1zmKZCa7rB60zUE3BsKsVCLrYGbAJI7oDd3MXKm0qsGHlXVeNtolUxKRbwN4EcBmEekWkQ/ns5KJUioN4OMAHgFwHMB3lVJHjXgNpXBuSKssXNNojkqBN13RgnA8jZfPjxodChGV2OhUEvV+F2wGLhKQjwa/C1kFjEdZrUREr9l/YQyT8TSuWV132X3XralHwO3AE8cvrVZ6/swwXHYb1jQsvUK8JeDBICuVyEJYqWSw3Kf0T5/UBqRT/RFcHC3OEpKFlFnm66b1jXj4SB9et6nJ9CeJVF2UUnctcv+8K5no0+EeKkVc5TTXe/788BTaaz1LmtdfCrdsbITLYcOjxwdwo95jiYgq08hUAg1+c1cpAUCdHuNYNIWGGrfB0RCRWTx0uA8Om2BLy+UrQzrtNrxuUxMePNyHs/oHeKlMFg8c7MWedfVwOZZeu9Ec9GAwHIdSytCVe4nyxUolk+gej6HB7zLtkrs5N25owGQ8jd7x4iS+iKi0zg5PmaKfUo7P5cDNGxrx2PEBNv0nqmBZpTA6lbREkqbOpyWVWKlERDnZrMLDR/qwqSUAt3Pu67Pda+tR53PigYO9SKazePBQH/om4vj1m9Ysa98tQTdSGYWxaGpZz0NULkwqmUT3WAwr6rxGh7GoG9Y3AADODk0ZHAkRLUYphXNDEVP0U5rpjVubcXE0htNs+k9UscLxNFIZhXoLVCoFvQ4IgPEYL+CISHOsbxIDkwlc0Racdxun3YZ37mzHYDiBj3xzP/7m4RPY0FyD2zY1L2vfzQGtf9MAV4Aji2BSyQTC8RQmYimsNPnqKIA2yG1qqZku8yQi85pKZhCOp7G20TyVSgDwxi0tAIBHjw0YHAkRlcrolFb102DyJt0A4LDZEPQ6WalERNOePjUEANjYsvAHc1tag3j7lW148dwIvC47vvDLV8G2zIb/LUGtwnMwzL5KZA3maLJR5XrGtKlkK0PmrFSa3aelocaN/Z2jSGeycHAVOCLTGtJPRtaZaPobALTWerBjZS0eOz6A917bYXQ4RFQCIxFt/Gnwm3/6GwCEvE5ONSGiaU+fGsK29iACHuei2960oRH/585tCHgccDuW38qkJchKJbIWZgRMoGssCpsA7SZNKs22vrEGqYxC12jU6FCIaAG5izqzTX8DgDdtbcHPu8YxGedFHFElGp1KwiZArXfxCzIzCPlYqUREmnA8hQMXxnDrpqa8H9NY4y5KQgkAmgJ6pRKTSmQRTCqZQNdoFG213mWtElBO65r8ELCvEpHZjUwl4bQL2kMeo0O5zO3bWwEAx/smDY6EiEphIpZC0OOEfZnTQMol5HNhIpZClgsIEFW9/Z1jSGcVbjZolVqP045ar5PT38gyrJHFqGBZpdA9FkNHvTWqlABtoGsPedE5wqQSkZmNRBLoqPOZcprqxuYarG3042gvk0pElSiSSKPGY50uCyGfE1kFTLJZN1FVu29vF+59/jzsNsGpAeN6yLYE3Zz+RpZhnb/2FWpwMoFkOouOZTbpnt33qNTWNPiw9zz7KhGZ2chUEltaA0aHMScRwVu3teKeZ84ilszA6ypOyTgRmUM4nkadBVZ+y6nzabGyrxIRnR+ewso6Y2eRtAQ9GJhkpRJZA7MBBsv1JVpVb/6V32Za2+hHOqtVWRGR+SilMDKVxOoGczXpnun27a3IKuBEP6uViCrNZDyFgNs6n12GfFrvJ/ZVIqpuiVTm/2fvz6MsOc/zwPN5b8SNuPvNrFyqshYsBCCSoERKVAkUTdmiPJJNygvt0zrTJG3p2CMNhmpxxur29GkenxnZo54/7PYcTVsiZRhNc9iyXaLdLYpid4OiZUsyqaZYAgiRBLGJQKFQVagll8r1brF980dE3MxK5HLvzYgb2/M7p44qlyp+LDG+jHjjed8PNzd6eEvCJ+cuNM3hgStEaZedn/Y5df1uFzVDw6kMvc0DMHxQvbrWwQMpO66ciPzWE8vx8GCKr893nmujXS3j+Ztb+IH7ZoefPyh5+dH33DfNpRHRCbieQtdy0cxS+1vVvw/bYPsbUaG9frcLTwEPJnzIyelWBcvbfXieQikjs+mouLLz0z6nrq13cd+pGkSytVnUTR0LTZNzlYhSam3Hf9t+/1x6U5ClkuDtSy08c/UuLMfLzGEFRHS0nYEDAPccxT3tNv1xGXoJdUNjUomo4F5b7aAkyXeRnG6asF2F9a6FuYaZ6FqIjsM7+ARtdm2sbA9wIWOtb6H7TtVw/W4PiielEKXOWsd/MHogxe1vAPDoUguOp/DqSnLDMIkoWtt9P+2TpaQSAMzWDc5UIiq4Kys7OD9bS/xF12LLP7mXJ8BRFrColKBv3tgAgBMP6U7KfbM19Gx3+PBKROmx1hmgJMC52XSfLPnAfA2mXuJcJaIc2e6HSaVsFZVmqmUmlYgKrGs5eGOjl4rRAadbfjqJJ8BRFrColKBvvL4OAXA+5Q99hwkTVteDYeNElB5rOxZmagbKKT+dUS+V8MhiAy/f3mbqkSgndotK5WO+M11magY2ujb3IqKC+sbr68E8peSLSovNIKnEE+AoA9L9tJFzX7+yhrMzVVTK2TxKe7FlwtBLuL7OohJR2tztWJjLyAEAbzvTwlbfwa1Nvo0jyoOw/a1uZuv+ZqZWhuMprOzwIY6oiL5+ZQ0lScc8yoWmn1Ra3ua9EaUfi0oJ6Vku/vTaeuLHVZ5ESQTnZ6q4sd5LeilEtIdSCqs7g8wMdnzktH/CyivLnKtElAfbAwc1Q4NeytZt5mzNL8S/wfsaokK6fOUuzs1UYerJF8QrZQ0ztTJus/2NMiBbP+1z5Buvr8N2Fd6ykOxxlSd1dqaK25t9uB6j4kRp0bFcDBwvM0mlZqWMxabJYd1EObHTd9AwszVPCfCTSgDwxgaLSkRF07NcfOvGRipa30ILDROr25zzRunHolJCvvbqKrSS4IEUxCtP4uxMhVFxopS5G1yPc41sFJUA4C0LDVxd68DxvKSXQkQn1LNd1IwMFpWq/p55a4PJAKKiefaa/8L/wfn0vPCfb5hY5TMWZUD2fuLnxH/6sxX8wIUZmBmdpxRaavtDxm9t9HAmOPqSiJIVnsg4V89G+xsAPLxQx9evrOH63XScukJEo7l0+dqbPtezXJzKSFJyr0q5hLImbDchKoi9+9fvvXAbgnTMUwrNNQw8f5On41L6MamUgDtbfTx/cws/9rbFpJdyYgtNE2VNcJNRcaLUWOtYEACz9eycvPRAUEh6fa2T8EqI6KS6loOqkb2XZiKCVoUzTIiK6MpKB+dm03WA0nzDxOo2k0qUfiwqJeAPXloGAPzFHBSVSiI406rgJk9tIkqN9Y6FdrWcqSG5NUPHfMPEtbs8TZIo63q2i1qKHszG0aqWcZv3NESFYjkerq938VDKZt3ONwxsDxz0bTfppRAdKTtPHDny+y8tY6ldwdvONJNeSiSW2v6wbqU4rJsoDTZ6NtrV7KSUQvedquH63S73EqIMs10PtqsymVQCgDaLSkSFc3WtA08hdadyzwen+IZjDYjSikWlKetaDr7y3RX8xKOnISJJLycSiy0TPdvF9sBJeilEBGCzZ6OV0aJSx3JxlzdPRJnVtfw36lktKrUqZSxv9+HxVFuiwriy0oEmgvvnUlpU4rBuSjkWlabsD19eQd/28IHvPZP0UiKz2PQHdC9vccMjSppSCls9GzMZLCpdOOUP/mcLHFF29YKiUhZPfwOAVlWH7Src7bK4TVQUV1Z3cP5UFYaerkfj8BRfngBHaZfNn/gZ9tRzt3CqbuCxB04lvZTInG75VfTlbcbFiZLWsVw4nkK7lr2i0ulWZTj4/wfum016OUQ0ga7tp5ZrGU4qAcDtzf4wJUBE+XDQaZV928Ub6z28/63pm3Ub7kGr2yxyU7qlqxybc33bxR+8tIy/9Ohp6Fp+/ukbpo5qWcMdJpWIErfZswEgkzOVOPifKPvCpFI1o4O6w72Tc5WIiuHqagcKwEML6Wp9A/YUlTp8xqJ0Y1Jpir763VV0LBcf/L6lpJcSKRHB6ZaJZR7BS5S4ze69RaWD3solZZS1nGlX8Z03NqGUys3cOaIi2W1/y2ZRKZxHd5v3NESFcGW1A70kuHCqdqK/J477raqhoW5oTCpR6uUnLpMBX/rOLbQqOt77lrmklxK5xVYFd7Z5AhxR0jZ7/o1HFpNKALDUrqBnu8PEFRFlS9YHdTdMHSVhUomoKF5d2cF9p2oop7SLZK5hYo1JJUq5dF49OeR4Hn7vhTv4iUfPpG4IXBQWGib6tsdTm4gSttmzoYmgbmYziLrU9gf/3+IDHVEm9WwXmgiMlD6gHUcrCRaaJpNKRAXQtRzc3uzjLQuNpJdyqPmGwUHdlHrZ/ImfQVdWOtjuO/hgjk5922s+OJ3g6lon4ZUQFdtmz0arqqOU0daxM62wqNRLeCVENImu5aJqaJluXz3TquAOi0pEufdaiucpheYaJtvfKPVYVJqS77yxibqh4UcemU96KbGYCwbJXVlhUYkoSdt9Z3h6URaZZQ2n6gaWt/lWjiiLepaT2da30Jl2he1vRAXw6koHZU1wbraa9FIONc/2N8oAFpWmwFMKL9zawv/h7adRyehpKMeZrRkoCZNKREnbHjhoVLLZ+hZaaJhYYVGJKJO6totaxu91zrRYVCIqgtdWd/DAXB16Kb2PxAsNA3c7FlyPc2spvdJ7BeXIzY0eupaLH3/0dNJLiY1WEszWDLy2yqISUZJ2+g4aGZ2nFFpomljdGcDj4H+izOnbbuZfoJ1uV7A9cNAZOEkvhYhi0h04uLM1wIPz6W19A/xuEE8B6122wFF6sag0Ba8u7wBALk9922u+YbL9jShBrqfQs93MJ5XmGyZsV/EEOKIMGtgeKuVs316GBwZwWDdRfl1d6wIAHphLd1FpPhgxwmHdlGbZ/qmfEa+udnC6ZWKhaSa9lFjNNwy8vtaFx3gmUSJ2grfqeUgqAWALHFEG9R0PZtaTSsGBAWyBI8qvq2sd6CXB+RTPUwKAueAwpLUdJpUovVhUipnjenh9rZPqoyqjMtcw0bNdDtglSkhYVGqyqERECRnYLip6tm8vz7CoRJR7r612cOFUDbqW7v2KSSXKgmw/eWTAzY0ebFfhLSnv143CbM2vpF9f7+JMEB0nonhcunztTZ/b6ecjqVQ3NFTLGm+giDLG8Tw4nsp8UukM29+Icm1gu7i50cP737qY9FKONR8klfiijdIs3aXZHHhjowcAOD9bS3gl8Zut+8eYX7/bTXglRMW0M/BnEDUq5YRXcjIigvmGgRUWlYgyxbI9AICZ8aRSzdDRquhMKhHl1Ot3u1BA6od0A0C7WoZeEqx12P5G6ZXtn/oZ8MZGH3XTvznJu2FS6W4v4ZUQFVNekkoAcKpuYJ03UESZ0nf8olJFz3ZSCQAWWxUsb7OoRJRHV1c7KAlw36n0v/QXEcw1DKwyqUQpxqJSzG5u9HBupgIRSXopsStrJZxumbi+zqQSURJ2Bg4MvQQj4ykBwC8qbfZsuBz8T5QZA8cFAJgZP/0NABabJmdEEuXUa2sdnJupZuZ+ab5hMqlEqZaNKymjLMfDna0+zs2kvwoelQuzNba/ESVke+DkIqUE+MlHTwGbPTvppRDRiPrD9rccJJWaJpa3WFQiyhvH9XBjvYcH5tLf+haab5icM0mpxqJSjG5v9aEAnJtJ91GVUbpwqoYb62x/I0rCzsDJ/MlvoVN1v532Lt/MEWVGmFSq5CGp1KpgZXsApZiWJMqTO9sDuJ7C+Qy0voXm6gbWdng/ROmV/Z/6KbYcnBpyumUmvJLpuTBbxc3NHqxgrgIRTU934KLOohIRJWSQs6SS5XpMSxLlzM3g5ffZDJ1Ufapu8H6IUo1FpRit7gygiWA2eDgqgvOnalDKnyVFRNPVtRzUjOw/zAFAq1qGJsKbKKIM6edpplLLf+DkXCWifHljs4dKuTR8eZUFs3UDPdtFz3KTXgrRgbL/Uz/FVncsnGoYKBVgSHfofNDqd3OTRSWiaetaLqo5KSqVRDBTK+Nul0UloqwIk0q5OP2t6afMOVeJKF9ubvRwtl3N1CFKc2F6m/dElFIsKsVoZWeAhUZxWt8A4EwQJb21wWN4iabJcjw4nkLNyEf7G+DHvdeZVCLKjL7jQgCUtew8rB1mWFTa5v0MUV64nsLtzT7OZmzebdj1wnsiSisWlWLiKYW7OxbmG9mJVkZhqe1v0re3eBNGNE09249E18rZTwiEZmoGNjjPhCgzBrYHs1zKVALgMGx/I8qf1Z0BHE9hKUPzlADOmaT0Y1EpJusdC65SmC9YUqlqaJiplTlTiWjKupYDALlpfwOAdrWMzsCB7XLwP1EWDBw3F61vANAwddQMje1vRDmyEhSJw6JxVrCoRGkXa5+EiHwAwD8DoAH4tFLqHx/wPe8H8N8DKANYVUr9aJxrmpbVHX/TWmgWq6gE+Gml25tMKhFNUzcY3piXQd0AMFMrAwBPXyLKiH6QVMqLxabJ9jeiHAmTh2keT3Lp8rU3fe6D33sGAItKlF6xFZVERAPwKQA/AeAGgKdF5ItKqRf2fM8MgF8H8AGl1DURWYxrPdO2Flz0WTpZICpL7QpusahENFXhiSB5SirNVP2i0kaXRSWiLBg4LsycJJUAYLFZYfsbUY6sbPcxUyvD0LNV/G5XyygJi0qUXnFeUY8BeEUpdUUpZQH4HIAP7fuejwL4vFLqGgAopZZjXM9UbfZs6CVB3czP0NxR+UUltr8RTdNuUik/e067yqQSUZYMHA+VHCWVFlrmsF2GiLJveXswHMKfJaWSYLZm8PQ3Sq04f/KfA3B9z8c3gs/t9T0AZkXkD0XkGyLyMzGuZ6o2ezZa1TJKORhWOa6ldgXrXRv9YHAwEcWvF8xUylP7W1hU2ujxJoooC/q2l7Okkok7PHiEKBc8T2E1wydzz/JEXEqxOItKB1VT1L6PdQA/COCvAPjLAP6fIvI9b/qLRB4XkWdE5JmVlZXoVxqDja49bN0omvAEOLbAEU1P13KhlwRlLT8pAV0roWnq2GT7G1EmWI6bubaSoyw2K+haLnYGTtJLIaITemOjB9tVWGxma0h36FTdGI5XIUqbOH/y3wBwYc/H5wHcPOB7flcp1VFKrQL4CoB37f+LlFJPKqUuKqUuLiwsxLbgKG327OFb9qIJj+lkCxzR9HRtN1cppVC7Vmb7G1FGDBwvZ0UlP9GwzLQSUeZdXesAAOaa2Zx3e6rGpBKlV5w/+Z8G8IiIPCgiBoAPA/jivu/5HQB/XkR0EakBeA+AF2Nc01S4nsJWzx6eXFQ0Z8Ki0gZvwoimpWe5uZqnFGpXyxzUTZQBSinYrgczR2nJxVZQVOJcJaLMu37Xf9l9qpbRolLD4KBuSq3YnkCUUo6IfBzAlwFoAD6jlHpeRD4WfP0JpdSLIvK7AL4NwAPwaaXUd+Ja07Rs920oAO1qNjetkwrb327zzR7R1HQtJ1cnv4Xa1TK+e2cn6WUQ0TFcT8FTyFlSyX9JxqISUfZdX+9CE0Ero50kp2oG1rsWPE+hVCrezF5Kt1hfayulngLw1L7PPbHv438K4J/GuY5pC1s1itr+VjU0zNTKbH8jmqKu5WIhgyeaHKdVKcNyPewMHDQKeJomUVZYjgcAuZjrdunyNQBAN5il9LvfuY2//q6zSS6JiE7o+t0u2rXsHqI0WzfgKWCrb2Mmo2kryq/s/+RPoY2gqFTU9jfATyux/Y1oenq2i2o5f0mlZsUvJHGmCVG6Wa5fVDJzlFSqGhq0kmC7zxZcoqy7sd7LbOsbAMzV/bVzWDelEV/7xiA8qWh/Uil881UES+0KT38jmqK+7aKSw6JSGFO/szXAWxYaCa+GiA4zCJNKOSoqiQiaFR3bfZ7+RpR1N9a7eHC+nvQyJjYbFJXWOxaQjXOrqEDy85M/Rbb7NgytlMsHvFH5RSW2vxFNg+sp2K5CpZy/Lb0ZtLwtb7NITZRmdphUykH7215NU2dSiSjjupaD1R0Ls0wqEcUiXz/5U2Jn4KBRKXYIbKldwXrXRt92k14KUe4Ngussj4XsMKm0vMVBuURplsekEgA0K2UmlYgy7sa6/6I7y0Wle5JKRCmTr5/8KcGBsntOgGMLHFHs+sHDXEXPX1HJ1Esoa4I7nKlElGq2k7+ZSgDY/kaUAzfWuwB2CzNZFM6DuttlUYnSJ18/+VOCRSU/qQQAN9kCRxS7/jCplL8t3Z9pUsYdHulNlGrhoO48nP62V7NSRs92mbwmyrBwzmuWT+auGhqqZQ13d1hUovTJ10/+lNjus6h0Jigq8QQ4oviFDztmDtvfAKBV0ZlUIko5K0gqGTlLKrWCcQYrLGwTZdadrQFKgsw/n52qG0wqUSrl6yd/Cjiuh57lFn6m0umWX1Ra5k0YUez6dn7b3wA/KcAHOqJ0s/I6qLsSHhbAPYgoq+5s9jHfMKGVJOmlnMipuoG7nKlEKZSvn/wpcLdjQSH7lfCTqps66obGB0GiKeg7+W1/A3aTSkqppJdCRIewcjyoGwBWeAIlUWbd2e4PX3hn2Wzd4KBuSqV8/eRPgZUdv4hS9KISACy2KjwGnGgKBjlvf2tWyuhaLnYGHJZLlFaW46EkgJ7xJMB+TCoRZd/tzT5Ot8ykl3Fic2x/o5Ri5SNiq8HwtGZB298uXb42/L1SCs/f3MKly9fw0ffcl+CqiPJtePpbXpNK1d2HujA1QETpYrkeyloJIvkqKtVNHQJgeYtFJaKsWt4e4Afvn016GRMLn6+Wt/q4szXgsxWlTj6fQBK0us2kUqhRKfMYXqIp6Nsu9JJAL+VzSw8LSRzWTZReluPBzFnrGwCURNCo6ExeE2XUwHFxt2Plov2tZuqwHA92MMOOKC3y99M/YatsfxtqVnRs9+2kl0GUe33bQyWnrW/AnvYTJgWIUitMKuVRs6Kz/Y0oo8J7hzy0v9UM/16va7kJr4ToXvn86Z+g1Z0Byprk7kjdSTRNHQPHGw7vJKJ49G03t61vANBiUoko9SzHy+29T9Mss6hNlFHhvUMukkqG/5Ktx6ISpUw+f/onaK1j+f33OZspMImwZYXDdYniNXBcmHp+k0qmXkK1rDEpQJRiuS4qMalElFl3hkmlPBSVwqQSn60oXfL50z9BG117eMEXXdiywhY4onj57W/53c5FBKdbJpNKRClmuR6M3La/lbHWGcDhHBOizAnvHRabbH8jigsH/0Rso2uhVuY/K7A7V4rDuoni1bddNCvZv1k6ymKrwvYTyjQRuQDgNwCcAeABeFIp9c/2fc/7AfwOgNeCT31eKfXLU1zmxCzHQ7uaz9MZmxUdSgGf/upraO3578jTl4jSb60zgFYSzNaMpJdyYtVgfibb3yhtWP2I2EbXRp1DugHsSSqx/Y0oVgPHQyXH7W+AH1t/7sZG0ssgOgkHwN9XSj0rIk0A3xCR31NKvbDv+76qlPqrCazvRPKcVGpVdl+StXJaOCPKq7sdC7M1A6VS9keThDOV2P5GaZPPn/4JWu9abH8L1E0dAmCH7W80BSLyGRFZFpHvHPL1vyUi3w5+fU1E3rXna1dF5DkR+aaIPDO9VUcj74O6AT+2fmdrAKVU0kshmohS6pZS6tng99sAXgRwLtlVRSffM5X8QhLb+YmyZ3XHwnwj+yklADD0EvSSsP2NUiefP/0T4nkKmz3OVAqVRNCo6Gx/o2n5LIAPHPH11wD8qFLqnQD+WwBP7vv6jymlvl8pdTGm9cXCUwoDx4NZzve+c7plome7TD5SLojIAwB+AMDlA778XhH5loh8SUTeMd2VTS7fRSW28xNl1d2OhVP1fBSVAH+uUtdmUYnSJZ8//ROy3Xfgqd1oIgFNk0Ulmg6l1FcA3D3i619TSq0HH34dwPmpLCxmtuMPjjVz+jAXWmz6p7ZwrhJlnYg0APwWgF9USm3t+/KzAO5XSr0LwK8B+MIhf8fjIvKMiDyzsrIS63pH4SkFx1Mo57T9rREUlbYGTCoRZc3azgBzjfzMnawZOpNKlDr5/OmfkPWuBQCoMqk01Kjo2GGygNLnZwF8ac/HCsC/F5FviMjjCa1pIoPgNKK8JgRC376xCQD43NPXcOmy/4soa0SkDL+g9G+UUp/f/3Wl1JZSaif4/VMAyiIyf8D3PamUuqiUuriwsBD7uo/juH5bal5nKumlEmqGhu0e72eIsmZtx8JcjpJKVUPjTCVKHUZqIrTR899gsf1tV7NSxu1NHgNO6SEiPwa/qPQjez79PqXUTRFZBPB7IvJSkHza/2cfB/A4ANx3XzpO/bEKklQKT5PcYfKRMkpEBMC/BPCiUupXDvmeMwDuKKWUiDwG/+Xf2hSXORErKG6XtewPwj1Mq1LmTCWijBk4ftt8nopKNUPDyjZT25QuLCpFKEwqsf1tV9P0k0qep3Jx6gJlm4i8E8CnAXxQKTV8UFNK3Qz+77KI/DaAxwC8qaiklHoSwSymixcvpmJi9CAoKhlavovZYfsJk4+UYe8D8NMAnhORbwaf+wcA7gMApdQTAH4KwM+LiAOgB+DDKgPT6e1hUSm/xe1mRedMN6KMudvxn83y1f6msf2NUofVjwhthEWlnA/MHUezosNTfsEtTxs6ZY+I3Afg8wB+Win1Z3s+XwdQUkptB7//SwB+OaFljm2YVMr56W81Q0NJmFSi7FJK/RGAI9+uKKU+CeCT01lRdIZFpRwnJpsVHctMBxBlytqO/2yWr0HdOnqWC6UU/AAsUfJYVIrQRpftb/s1gmN4l7fzNSSP0kdEfhPA+wHMi8gNAP8QQBkYJgB+CcAcgF8Pfgg7wUlvpwH8dvA5HcAlpdTvTv2/wIQsx39blddZJqGSCOoGZ7QRpZEdzFQql/K7DzWD9jdPKZT4IEeUCWtBUmm+kZ+iUrWswVUKHcsdjgYgShr/lxih9a4NEaDCotJQM9jsVrYHePtSwouhXFNKfeSYr/8cgJ874PNXALwrrnXFbdj+luOEQKhR4WmSRGkUnkJZ1vNbbAmT110+yBFlxtqOny7M04vtMLyw3rG4F1Fq5P8pZIo2uhZalTLfYO3RrOwWlYgoekUZ1A34w7qZVCJKH9sLZ7vldx9qBclrDusmyo5wplLe2t8AYLPHvYjSI78//ROw0bUxWysnvYxUae5pfyOi6BUqqcSiElEq2Y7f/qbnuqjkP8ht9bgHEWXF6o6FsibD6zcPqmFSKZjlS5QG+f3pn4CNno12lUWlvQy9BFMvMalEFJPwKO9CFJUqflEpA4dhERXK7ulv+U1qN5lUIsqczZ6FmZqRq4HWw/a3LvciSo/8P4VM0VbPRotFpTdpmDpWdlhUIoqD5XjQSgI9xwNyQ01Th+sp9G0v6aUQ0R5hUSnP7W9hO/8W57oRZcZG18ZMzp7NwqLSJpNKlCL5/emfgO2+Pey5p10NUx8OyiOiaA0cN9cPcns1goe67QHfzhGlSVhUynP7m66VUDM0JpUo80Tkgoj8gYi8KCLPi8jfO+B7RER+VUReEZFvi8i7k1jrSW10bczkbDRJlUklSqH8/vRPwFbfQauan57dqNRNHWs7rKYTxcFyvEIM6QaAhunfGHKuElG62K7fkpr3AnerUmZSifLAAfD3lVJvB/DDAH5BRB7d9z0fBPBI8OtxAP98ukuMhj+aJD9DugFAL/mjRThTidIk3z/9p2y7bw977mlXw9Sx1mFSiSgOA8crxDwlYDeptMOHOqJU2U0q5WduyUGaFZ1JJco8pdQtpdSzwe+3AbwI4Ny+b/sQgN9Qvq8DmBGRpSkv9cQ2u1bukkqA3wK3yaQSpQhjNSdw6fK14e8dz0Pf9vDaagcPzNUTXFX61E0ddzsWXE9BK+X7hpNo2oqVVAqKSkwqEaWK7XrQS4JSjobhHqRVKePOVj/pZRBFRkQeAPADAC7v+9I5ANf3fHwj+Nyt6awsGhu9/M1UAvwWOCaVKE2K8SQyBeHg2EpBHu7G0TA1eArY4OZHFLkiJZVqhoaSMKlElDa2q1DOeesbADSr/gmUHk+gpBwQkQaA3wLwi0qprf1fPuCPHPg/fBF5XESeEZFnVlZWol7mxAaOi67l5jSppHOmEqVK/u8ApqRvuwCASllLeCXpUw/SBWsdFpWIomY5Hgy9GPtOSQR1U2dSiShlbNdDOeetb4CfVPIU0OEeRBknImX4BaV/o5T6/AHfcgPAhT0fnwdw86C/Syn1pFLqolLq4sLCQvSLndBmzy+6tGv5mqkEBO1vPRaVKD1YVIpIWFSqsqj0JmHLyipPgCOKnOUWp/0N8PeTbSaViFLFcr1CJJVawVw3DuumLBMRAfAvAbyolPqVQ77tiwB+JjgF7ocBbCqlMtX6Fs4cymX7W5ntb5QunKkUkbD9zWRR6U2GSSWeAEcUuYHj5f7Epb0aTCoRpY5TlPa34DCW7Z4NzFQTXg3RxN4H4KcBPCci3ww+9w8A3AcASqknADwF4CcBvAKgC+DvTn+ZJ7MRJHny2v622bM5r5ZSg0WliDCpdLjGsKjEpBJR1CzHLVxSaXmbewlRmhSm/S1IPDCpRFmmlPojHDwzae/3KAC/MJ0VxWNjmFTKZ/ubUv7J4zM5bO+j7CnOk0jMdmcq8Z90v2owXHeVSSWiSHlKwXZVYQZ1A/6R3jsDB4qDcolSw3I9lAuwDzVMHQJgq89ZJkRpFx4QlM+kkh9i4LBuSov83wFMSY+Dug9VEsGpuom1DtMFRFGyHL/ttkhFpYapw/XUsOWYiJLnuArlUv73Ia0kqHGuG1Em7A7qznNRiS/sKR3Y/haRvu1BUKyHu3HMNwwmlYgiVsiiUjAod3vAt3NEaVGUpBLgD+veZlKJKPU2uja0kqBp5u9xt2b4/52+8Kdv4KVb2wCAj77nviSXRAVXjDuAKejbLsxyCSXJ/0yBScw1DM5UIoqY5QZFpQIMyA01TP+NI4d1E6WH7XowCjBTCQBalTLb34gyYKNnoV0tQ3L4bFYNkko9y014JUS+/JVuE9K3Xba+HWG+YeKb1zeSXgZRrhQ5qbTD9hOi1LBdBb0gxe1mRcfNjV7SyyCiY3z7xiYEwKXL15JeSuRqwTNnOH6FKGnFuAOYgr7t8uS3I8zVTayx/Y0oUnaQVCrCUd6h8DRJJpWI0sNPKhVjH2pVy9gZOHA9HhZAlGZ92x0mevKmEvz36jKpRClRjDuAKeg7HpNKR5hrGNgZOMNT8ojo5IrY/lYLTpNkUokoHZRSsB0P5YK0vzUrOhRY2CZKu77toaLn89msJIJKucT2N0qN4jyJxKxvu6gUqAVlXPMNAwCw1mFaiSgqtuO/KS/KgFzAv5Gqmzq2+UBHlAquUlAoTmKyVfHnunFYN1G6hfNu86pm6Gx/o9TI75U2ZQPHg8mk0qHm6iYAYHWbw7qJomIN29+KkRAINUydSSWilBgWtwtWVNrqcQ8iSrO8jyapljV0Le5DlA7FuAOYgr7twixQWmBcc8OkEotKRFGxC9j+BgRFJSaViFIh3If0ghS3m1V/rhtPgCNKt76d79EkNUNj+xulRrGeRGJkOR6LSkeYbwRJJQ7rJopMUYtKzQqLSkRp4XjFSio1TB0Ctr8RpZnterBcD5Uct79VDY2Duik18nulTZHjeXA8xfa3IwyTSiwqEUXGcoL2t4IVtMOkklI8fYkoaUU7hbIkgkZFxxZbcIlSK2yRz3NSqVrWOFOJUqMYdwAxs2z/hopJpcPVDB3Vsoa1Hba/EUXFdj0IAL1UjLaTUMPU4XqKM02IUsBx/eJukfahVqXMpBJRim2HRaWcnv4G7La/eXzBRinAKkgEBg6LSqOYaxg8/Y0oQpbjoayXIFKchzkAaASDcldYpCZKXNGSSoDfgrvNpBJRaoUzz3KdVDJ0KACDINxAlKTi3AHEKCwqGTmuhkdhrmFilQ+BRJGxXVWoB7lQw/QH5a7wNEmixIUzlYqWVNrqMalElFa7RaX83iPVgoIZW+AoDfJ7pU3RwPEv5gqTSkearxsc1E0UIdv1YBTkxKW9GhW/qMQiNVHyCplUquroWO5wrh0RpUvYHp/vpFJQVOKwbkqB4twBxIjtb6M5VTewzvY3oshYrleoB7lQmFRiUYkoecOkUoEK3C224BKl2nYR2t+C/25dm624lLziPY3EoB/EDo0cb1xRONUwcLdj8cQmoojYrgejgMXsmqGhJCwqEaVBEZNKrSAteWern/BKiOgg4emM1Rw/mzGpRGlSnDuAGIXxZ7a/He1UzYDleuhw8yOKhOUUM6lUEkHd1DlTiSgFinj6WzNIKt3ZZFGJKI3CpJKZ55lKQVGpy+cqSoH8XmlTtNv+lt9qeBRO1Q0AwF3OVSKKhO0qGAUsKgF+CxxntBElr5BJpapfVLrNpBJRKm33HRh6CaUcn45b5aBuSpHi3AHEqB8M6i5iG8o4wqLSWofpAqIo+Eml/N4wHaVZ0dn+RpQCRZypVDc06CXBLSaViFJpq2fnuvUNAHStBEMrsf2NUoFVkAhYtv9gpxUo+j2JsKi03mW6gCgKRZ2pBARJJba/ESUuTCoVqf1NRNCqlnFzo5f0UojoANt9pxAHKFUNje1vlAp60gvIg4HjwWDr27Hm6iYAYI0tK0SRKOrpb8Bu+5tSCpLjeDtR2jmugl6Swl2H7WqZSSWilLh0+do9H//Z8nauT34L1QwNPYunv1HyWFSKQN9xC1ENP4lLl68NT8n7/ZeWYQeDPT/6nvuSXBZRptmuV+iZSpbrYavnoF0rJ70cosKyPa9QrW+hmWoZt1lUIkoly/GGg6zzrFrW0OVMJUqBYj6NRMxyPJ78NgJTL0ErCToDVtSJTspTCrarUC7o3tMITl9a4VwlokQ5rkK5VLx9qF0t4/ZWH24wU4qI0qNve4U4QKlqaJypRKlQvLuAGLD9bTQigrqhocPNj+jEwmO8i5xUAoAVzlUiSpTjFjOp1KqW4XqKexBRClkF6SKpsahEKZH/q20KBnYxNq4o1E2dSSWiCFjDY7yL9zAHAI2KX1TiCXBEybI9Bb2Axe2Zqp+WvLnJYd1EadN3vEI8m1XLOrq2C6WYmKRkxXq1icgHRORlEXlFRD5xwNffLyKbIvLN4NcvxbmeuAwcD2Y5/xtXFGo8pYAoEvawqFTMvadpsqhElAaO6xWyuB3Ocru1wblKRGniKQXL8WAWZFC366nhrFqipMQ2qFtENACfAvATAG4AeFpEvqiUemHft35VKfVX41rHNAwKUg2PQt3U8cY63+oRnZTl+EUlo6B7T9XQoJWERSWihNmuB72gM5UA4BaTSkSpYgf3R0V4NqsGw8i7PAGOEhbn1fYYgFeUUleUUhaAzwH4UIz/eYmxnGIMg4tCzdDR4cZHdGJFTyqVRDBXNzjPhChhjqsKmVSqljVUyxpu8QQ4olTpD4tK+X82qwZprB5PgKOExfk0cg7A9T0f3wg+t997ReRbIvIlEXnHQX+RiDwuIs+IyDMrKytxrHVinlKwXK+wD3bjqpsa+rbH01KITiiMOhd571lomljdsZJeBlGh2V4xk0oigqV2hUklopQZOH6BpQhJpdowqcSiEiUrzqvtoNdW+ysJzwK4Xyn1LgC/BuALB/1FSqknlVIXlVIXFxYWol3lCQ1PYCrAxhWFuuF3XDKmSXQydsEHdQPAfMNk+xtRwoqaVAKApZkKbnKmElGqDOwgqVSAebdh+xtPgKOkxXm13QBwYc/H5wHc3PsNSqktpdRO8PunAJRFZD7GNUUuPIHJKOgN1bjqwXDdzoCbH9FJFL39DfCLSmx/I0qW7XqFPP0NAJbaVSaViFJmUKD2t1rwsp5FJUpanHcBTwN4REQeFBEDwIcBfHHvN4jIGRGR4PePBetZi3FNkdsdlpv/jSsKYUyTc5WITiZsf9MLXNCebxpY27F4lC5RghyvuEmls+0KlrcHwyI/ESXPKlD7WzhTqcuZSpSw2E5/U0o5IvJxAF8GoAH4jFLqeRH5WPD1JwD8FICfFxEHQA/Ah1XGng6GSaUCbFxR2E0qsahEdBLOMCVZ3L1noWHCcj1s9Zzh8d5ENF1FPf0NAJZmqlAKWN4e4NxMNenlEBH2DurO/75U1gR6SdDjy3pKWGxFJWDY0vbUvs89sef3nwTwyTjXELdhUqmgb+nGVR8mlVhRJzqJ8M14UdtOAH9QNwCs7AxYVCJKSJFnKp1pVwAAtzZ6LCoRpcSw/a2c/y4SEUHV0DiomxJX3KeRiIRFpXIBquFRCHt/u0wqEZ3I7ulvxXyYA/yZSgA4V4koIUopOJ4qbHH7bNsvJN3c5LBuorQY2MVpfwP8Frge298oYcW42mJkswVlLFpJUC1rnKlEdEK2x0HdYVKJJ8ARJSNMBJRLxSxuL83sJpWIKB0GjoeSAHpB9qUak0qUAsV9GonI7qBu/lOOqmZoPP2N6IQcV0ETQUmKcdN0kDCpxKISUTLCo7uLmlRqVcpomDpuMalElBoDx4Wpa5CC3B9VDZ2nv1HiinkXECGLSaWx1U2dSSWiE7Jcr9AnvwHATLUMrSRsfyNKyCA4ZanIe9FSu4Jbm0wqEaXFwPZglovzXFZj+xulQHGuuJgwqTS+uqGhy6QS0Yk4rlf4YnapJJirG0wqESWkb4ftb8Xdi860K0wqEaXIwPEKM08JQDComy/rKVmxnv5WBEwqja9u6rjB+QNEJ2K7qtDpgNBC08TqjpX0MogKiUklf1j3i7e2hx9funztTd/z0ffcN80lERVa2P5WFDVDg+0q9G0XlQKceEfpxErICVnBMDitIMPgolAzdHQHLpRSSS+FKLNs1yv0kO7QfMNkUokoIWFSSS9wUmlppoLVncGwwEZEySpiUgkAtnp2wiuhIivOFRcTy/Vg6KXCDIOLQt3U4Co1PDWGiMbnuIpFJfhFJc5UIkpGWEgpFzypBADLW9yHiNJgYBesqBSkkzZYVKIEFeeKi4ntcK7JuOqG33XZGbD/l2hSNgd1A/Db39Z2LCYfiRIQzpXUCrwXLc1UAAA32dZPlAr+C//itIHVgueqjS6LSpQcVkNOaOCwBWVcddPf6Ds8/pJoYmx/8803DFiuh60ei9RE0zZw2f621PaLShzWTZQOluPB0ItT6A7b3za6nC9JySnuXUBE7KD9jUYXVtS7TCoRTczx2P4G+EklAFjZ4QMd0bQNhjOVivMAt99S0P52c5NJJaI0sFwPhlagpBLb3ygF+ERyQn41nP+M46ibQfsbj78kmpjleIWeYxJaaARFpW2+oSOaNstlUalu6mhVdNzaYGGbKGmup+B6qpBJpU22v1GCWA05Ib8azn/GcdSDza8zYPsb0aQcT6Fc4JaT0HyQVOIJcETTF85U0gt+H3R2popbTCoRJS7ck4r0bGbqJZQE2Ojx5RolpzhXXEyYVBqfoZegl4RJJaIT4KBu33yDRSWipISnvxU5qQQAZ9oVzlQiSoEwPVmkQd0igkpZwybb3yhBrIacEJNK4xMR1E2dSSWiE+Cgbt9MtQytJFjZZlGJaNqGSaWCF5WW2lXcZlGJKHF2mFQqUPsbANQMjae/UaL4RHJCluOhzKTS2GqGhi6TSkQTUUrBcRVnKgEolQTzDYNJJaIEDNj+BsA/AW6tY6Fv82UZUZLCEymL9sK/yqQSJaxYV1wMbNeDWbCNKwp+UolFJaJJWK4HBTCpFJhvmFjd4SwBomkLk0pa4ZNKFQDAnS2mlYiSFO5JRXvhXzN0JpUoUcW64iLmKQXbVYXbuKJQMzR0LL7RI5pEPzjGm0Ul33zDZPsbUQIsx4OARaWzM1UAwE2eAEeUKDtIKhXthX/V0DiomxJVrCsuYnYBTxiICpNKRJMbBC0WHNTtW2iabH8jSsDAcbkPwR/UDQC3t3gCHFGSippUqnKmEiWsWFdcxHZPGOA/47jqhoaB4w03fyIaXS8oKjGp5JtvmFjbsaCUSnopRIViOR70EvehsP2NSSWiZFkFfeFfK2vY7jtwXD5XUTKKdcVFrKgbVxTqpg4AWO8yqkk0Lra/3Wu+YcByPWz1mH4kmibL9Qp/8hvgzzNpV8s8AY4oYUV94V81NADAVp/3QZSMYl1xESvqxhWFmuEXldY4XJdobOEJQ2U+zAHw298AYGWHD3RE0zSwPba/BZbaFdzaZPsbUZKGL/wL9mxWC4pKG3xZTwkp1hUXMbugG1cU6iY3P6JJ9Yczlbj3AMBCIygqbXM/IZqmgetBY/sbgLCoxMI2UZLCF/5FS3JXy/7L+o0e5ypRMop1xUVsUNCNKwr1MKnU4UMg0bj6w9ZbJgQAYD5IKnFYN9F0DWwPZe5DAIClmSqLSkQJsxx/TypJsfalMKm0yWHdlBBWQ06ASaXJhZsfZyoRjY9JpXvND5NKLCoRTZPletDYhgsAWGpVcLdjDY80J6Lps1yvkC/7w5lKGz0+V1EyinfVRSiMWJoF3LxOKpypdJdJJaKxDYKCNmeZ+GaqZeglYVKJUk1ELojIH4jIiyLyvIj8vQO+R0TkV0XkFRH5toi8O4m1jspyXA7qDizNVAEAW2w/IUqM7XgwC/iyv1YOx4pw/6FkFO+qi5Dl+MdXlwu4eZ2UVhJUyxqLSkQTGISDulnQBgCUSoK5hsGiEqWdA+DvK6XeDuCHAfyCiDy673s+COCR4NfjAP75dJc4noHjMTEZWGpXAACbLCoRJWbgFDOpVDFYVKJkFe+qi9Dw9LcCbl5RqBksKlF0ROQzIrIsIt855OuHJgBE5AMi8nLwtU9Mb9WTGSaVmBAYmm+YWOVpkpRiSqlbSqlng99vA3gRwLl93/YhAL+hfF8HMCMiS1Ne6sgsx+M+FGBRiSh5tusVcixJSQStis79hxJTvKsuQpbjpwWKuHlFoW7qnKlEUfosgA8c8fUDEwAiogH4VPD1RwF85ID0QKrsFpW494QWmiZnKlFmiMgDAH4AwOV9XzoH4Pqej2/gzYWn1LAczlQKLbX99jc+1BElx3KKWVQCgJmawVO1KTHFvOoiYjkKmghvqCZUNzSsMVlAEVFKfQXA3SO+5bAEwGMAXlFKXVFKWQA+F3xvag2ccFA3956Qn1RiUYnST0QaAH4LwC8qpbb2f/mAP6IO+DseF5FnROSZlZWVOJY5kqK2mhykamiYqZVZVCJKkOV6he0gmamVscH9hxKiJ72ALLMKGrGMSs3UcWO9m/QyqDgOSwAc9Pn3THFdYxvYbH8DgEuXrw1/v7w1wPLWAEopSMGOEqbsEJEy/ILSv1FKff6Ab7kB4MKej88DuLn/m5RSTwJ4EgAuXrz4pqLTtDCpdK8zrQqLSkQJKnJSqV0tc6YSJaaYV11E7AJvXFGoGzrWOzaUSux+mIrlsATASMkAIF3pAL0kLJ7s0ajocJXiAx2llvgX7L8E8KJS6lcO+bYvAviZYAbcDwPYVErdmtoixzTg6W/3ODtT5R5ElKBiJ5UM7j+UmGJedREZuIx9n0Td1GC5HnYGTtJLoWI4LAEwUjIA8NMBSqmLSqmLCwsLsS30OJbjsfVtn6bpB2/ZAkcp9j4APw3gL4rIN4NfPykiHxORjwXf8xSAKwBeAfA/APgvElrrSDio+15n2kwqESWpyEmlmWqZM5UoMWx/OwE/qcSbqUnVDP9/fusdG81KOeHVUAF8EcDHReRz8NvbNpVSt0RkBcAjIvIggDcAfBjARxNc57H8dEAxb5oO06j4+8nKtoWHFxNeDNEBlFJ/hIOTkXu/RwH4hems6OQs14POl2tDp5sVdC0XjudxjyaaMqWUf/pbQfekcKab5ymUWOynKWNR6QSKHLGMQt3UAAB3uxbum6slvBrKOhH5TQDvBzAvIjcA/EMAZQBQSj0BPwHwk/ATAF0Afzf4miMiHwfwZQAagM8opZ6f+n+BMQyYVHqTBpNKRFPleQq2q5hU2uN0ywQA7PQdzNSMhFdDVCyOp+Cp4p7K3a6W4Slge+CgXeXLepouFpVOwHK8YWGExlcPkkp3O3wIpJNTSn3kmK8fmgBQSj0Fv+iUCQO2nLxJ2P62ss39hGgaLJcHBux3ulUBAGyxqEQ0dbbj70lFHU0S7jmbXZtFJZq6Yl51EWFS6WRqRpBU6nD+ANE4Bjbb3/arGBpKwqQS0bQMggc4jfdBQwtNP6m0xblKRFMXFrrNgiaVZoJC0kaPc5Vo+op51UWkyMPgolA3w5lK3PyIxsH2tzcriaBh6iwqEU3JwHEBMKm0V5hU2uYBJERTZ4VJpYI+m83UgqJSl0Vtmr5iXnURsRye/nYSpl5CWROssahENBb/xCXuPfs1Kjrb34imJHyAY1Fp11zdQEmAbSaViKYuTCoVtYtkWFTi/kMJKOZVFxHb9QobsYyCiGC2ZjCpRDSmgeOizKTSm/hJJe4nRNMwLCoV9AHuIKWSoFkpY6vPpBLRtIV7UlG7SNrVcKYS74No+op51UXA9RQcTxU2YhmVU3UDd7n5EY2Fg7oP1jDLbH8jmpIBk0oHalZ0bPeZFCCatqInlcLh3Gx/oyQU86qLQNfy30IVdeOKyqm6gbtMKhGNZeB4HI57gHCmkn/QHxHFie1vB2tWythmUolo6oqeVDL0EuqGxvY3SkQxr7oIdC1/QGVRN66ozNbZ/kY0roHjoswHuTdpVnTYrsImb6iIYjdg+9uBWhUdW0wqEU3dsKhU4D1ppmYwqUSJ0JNeQFb1wqJSgTeuKJyqsf2NaFwDm6e/HaQRnCi5ujPATM1IeDVE+RY+wGkFLnBfunztTZ9rVnR0LReO67HgRjRFw/a3Ar/wb1fL2OzxuYqmr7hX3Qn1bL+oxNPfTuZU3a+oO8EPAiI63oCnvx2oUfGLSivbvKEiipvl+vdBbH+7V9P055rsDNgCRzRNdsHb3wD/BDgmlSgJI111IvJbIvJXRKS4V+k+u0Ul3kydxKm6nyZg/y/txT3naJbDpNJB9iaViOLEPcpPTALgXrRPWNxmUYmmhfuRb+B6EBS70D1TK/OZihIx6ubzzwF8FMB3ReQfi8jbYlxTJvSZVIrEbFBU4lwl2od7ziGUUhg4LpNKB2iaYVKJRSWKXeH3qLDVhHvRvcLiNotKNEWF348AP6lU1ksQKW5RqV1lUomSMdKdgFLqPyil/haAdwO4CuD3RORrIvJ3RaQc5wLTKnxDx6LSycwFRSWeAEd7cc85nOMpeIopyYNUDA16SZhUothxj9o7qJt70V7DohJPgKMp4X7ks1wPZsGfy9pVA1s9m6fg0tSNfOWJyByAvwPg5wD8KYB/Bn/z+r1YVpZynKkUja9fWQMA/M43b+LS5WvDX0Tccw424HDcQ5VEMNcwWFSiqSj6HjUsKnEvugfb3ygJRd+PAH80QLnA85QAv/3Ncr3hcyrRtIx0+puIfB7A2wD8KwB/TSl1K/jSvxWRZ+JaXJr1OVMpEjXD/59gx+LNF+3innO4QbD38FShgy00Tba/Uey4R+2e/sb2t3uVtRJMvYRtFpVoSrgf+SzHK/yp3DNVP5i20bWHz1hE0zDq/9o+rZR6au8nRMRUSg2UUhdjWFfqMakUjbqhAQC6FivqdA/uOYcI0wFlpgMONN8wsbrDdlqKXeH3qIETFri5F+3XMHW2v9E0FX4/Avz2tyKf/Ab4SSXALyqdnakmvBoqklGvvP/3AZ/74ygXkjV9zlSKhB680evwjR7di3vOISzOMTmSX1RiUoliV/g9ymIr7qEaFZ3tbzRNhd+PgCCpVPCiUrsanqrNl2s0XUcmlUTkDIBzAKoi8gMAwjuHFoBazGtLNba/RadmaEwqEQDuOaMYsOXkSAtNv6iklCr0CTAUD+5RuyzHg14SlHidvUnD1LG8xeI2xYv70b1sV6FZKfa9UZhU2uQJcDRlx7W//WX4Q9/OA/iVPZ/fBvAPYlpTJvRtFwK+oYtC3dSZVKIQ95xjsOXkaPMNE7arsNmzMVMzkl4O5Q/3qMDA8WAWPBVwmGZFx5WVTtLLoPzjfrTHwHELn1Qatr/1WFSi6TqyqKSU+h8B/I8i8p8ppX5rSmvKhJ7loqyV+CY8AnVDx/aAmx9xzxkFk0pHm2/4haTVHYtFJYoc96hdbDU5XMPU0bNdOK7HQxUoNtyP7mW5ioO6w/Y3JpVoyo5rf/vbSql/DeABEfmv9n9dKfUrB/yxQug7LpMCEakZGu5s9ZNeBqUA95zjDWwe432U+YYJAFjdGeDhxUbCq6G84R61i0WlwzVMPy2wM3BY3KbYcD+6l809CZVyCYZe4kwlmrrj2t/qwf/lnfk+fdvjkO6I1E0dHYvtbwSAe86x2P52tLCotMYT4Cge3KMCA8eFqWtJLyOV6ubuybYzhZtsQ1PE/SjgKQXb5bOZiGCmWuZMJZq649rf/kXwf/9f01lOdvRst/AbV1TqhgbbVXzrSdxzRjBsf+P+c6C5oP1trcMhuRQ97lG7eHz34WqGf3vNF2YUJ+5HuxxXQQHck+DPVWL7G03bSFeeiPx3ItISkbKI/EcRWRWRvx334tJsYLs8+S0iNdO/+ery5osC3HMOFx7jXWb724FmawZKAqxus6hE8eEe5bficlD3wYZJpQFPtqX4TbIfichnRGRZRL5zyNffLyKbIvLN4NcvxbP6aFiuf29k8NkMM1WD7W80daPeDfwlpdQWgL8K4AaA7wHwX8e2qgxgUik69eEbPd580RD3nEPstr9x/znIv336OqqGjq9fuYtLl6/h0uVrSS+J8qnwexSTSoerM6lE0zXJfvRZAB845nu+qpT6/uDXL598mfGxg6ISn82ANpNKlIBRr7xy8H9/EsBvKqXuxrSezPBnKrEaHoXwjV5nwJsvGuKec4iw/U1jUulQDVPDDvcTilfh96iB4xX+pKXDVA0NAqDDpBJNx9j7kVLqKwBys2+FRSW+cIM/U6nHohJN16hX3v8iIi8BuAjgP4rIAoBCH9fVs5hUiko4e4Dtb7QH95xDhKe/sf3tcHVTZ1GJ4lb4PWrgeDDLHNR9kJIIqobG+xqalrj2o/eKyLdE5Esi8o4I/r7YOK4CwPY3gDOVKBkjVUWUUp8A8F4AF5VSNoAOgA/FubC06zssKkVlN6nEN3rk455zOLa/Ha9h6kw+Uqy4R/nz3ZhUOlzd0NnWT1MR0370LID7lVLvAvBrAL5w2DeKyOMi8oyIPLOysnLC/9jJMKm0a6ZmoGe76Nvcf2h6jjz9bZ+3A3hARPb+md+IeD2Z0bdczFSNpJeRC5VyEBPnGz26F/ecwN65QN94fR0CgEGlwzWYVKLpKPQeZTkuB3UfoWZq6HIfoumJdD8KZjSFv39KRH5dROaVUqsHfO+TAJ4EgIsXL6pJ/zNPwg6SSkV+4R/eK/7ZnW0AwGe/dhUf+9GHklwSFchIRSUR+VcAHgLwTQBh2VOhQDdP+/UdzlSKSkkENUPjKSk0xD3ncI6noGsCEe4/h2mYOgaOB9v1Cn2DSfHhHhW0v7GodKi6oWOtw1MoKX5x7EcicgbAHaWUEpHH4He3rJ1wqbFxhoO6eW9UDdqSe0xK0hSNmlS6COBRpVQi1ec06vP0t0jVTJ1JJdqLe84hHFdBL3HvOUrDDE5eGjiYqTFRSrEo/B5lOTz97Sg1Q8P1u3yoo6kYez8Skd8E8H4A8yJyA8A/RDDwWyn1BICfAvDzIuIA6AH4cJr3O4vtb0O7s2q5/9D0jFpU+g6AMwBujfOXi8gHAPwzABqATyul/vEh3/dDAL4O4D9XSv3P4/xnJEEphZ7tshoeobqhc6YS7TXRnlMEjseU5HHqQVFph0Ulik/h9ygmlY5WD16Wpfg5nPJj7P1IKfWRY77+SQCfPOG6piYc1M1DTPzTJwEmlWi6Ri0qzQN4QUT+BMAwy6uU+uuH/QER0QB8CsBPALgB4GkR+aJS6oUDvu+fAPjymGtPjOV6UKrYfbtRq5saVrYZE6ehsfeconBcBY03TUdq7CkqEcWk8HsUk0pHqxsaPOUX34hiVvj9yPbC9jfuSbWw/c3mPRBNz6hFpX80wd/9GIBXlFJXAEBEPgf/JIIX9n3f/xXAbwH4oQn+MxLRt7hxRa1m6OhY3aSXQenxj5JeQFrZnmK8+xh729+IYvKPkl5A0iyXRaWj1LgP0fT8o6QXkDQO6t4VJpXY/kbTNFJRSSn1n0TkfgCPKKX+g4jU4Le0HeUcgOt7Pr4B4D17v0FEzgH4mwD+IrJUVBoe6c20QFTqpoae5cBTCiUOIC68CfecQnBcj/HuYwzb3/p8mKN4FH2PclwPrqdg6oX5rzy2evBg1+GDHcWs6PsRwEHde5l6CSVh+xtN10jlXBH5PwP4nwH8i+BT5wB84bg/dsDn9jeW//cA/hul1JH/qxeRx0XkGRF5ZmVl5fgFxyy8SA1WwyNTN3R4yh+ATjThnlMILpNKxzL0Egy9xPY3ik3R96hwKC6TSocbDsvlPkQxK/p+BAC260EAjgcAICKoljV0+UxFUzTq3cAvAHgfgC0AUEp9F8DiMX/mBoALez4+D+Dmvu+5COBzInIV/ikDvy4if2P/X6SUelIpdVEpdXFhYWHEJcdnN6nEm6mo1MKoJod1k2+SPacQbFdB503TsRqmzoQAxanQe5QVzAniy7XDhYlJ7kM0BYXej4Dg3kgTCLsdAABVQ2dSiaZq1JlKA6WUFV6oIqLjzamj/Z4G8IiIPAjgDQAfBvDRvd+glHow/L2IfBbA/6qU+sKIa0rMblKJG1dUdm++HMzDTHg1lAKT7DmF4HjesAhLh6sbGtvfKE6F3qPC4dNmmUWlw9SHc024D1HsCr0fAX5SifOUdtUMjUUlmqpRr77/JCL/AEBVRH4CwP8E4H856g8opRwAH4d/qtuLAP6dUup5EfmYiHzsJItOWt/2b6aYVIpO3QgHWnIDJAAT7DlF4bgKeol7z3EalTLb3yhOhd6jmFQ6nqGXoJWEg7ppGgq9HwH+vRGLSrv89jfuPTQ9oyaVPgHgZwE8B+D/AuApAJ8+7g8ppZ4Kvnfv55445Hv/zohrSVzY/sbNKzo1k2/06B4T7TlF4HgeDwkYQcPUcOMu9xOKTaH3qEFwH2SWNdgur7ODiAjqhsb2N5qGQu9HgD/njaMBdtUMDcvb/aSXQQUy6ulvnoh8AcAXlFLJT8pOWN8Ki0rcvKKym1TizSlxzzkKk0qjqZs6OsGJkkRRK/oeNWBSaSQ1Q+egbopd0fcjIDgZl/vRUNXQ0GVBm6boyKtPfP9IRFYBvATgZRFZEZFfms7y0olJpegZegllTfhGr+C45xzP9hSTSiNomP6JkpwpQFHiHuUL299Mnv52pLrJpBLFh/vRLttTfNm/R9XQMHA82MFJnURxO+5u4BfhnybwQ0qpOaXUKQDvAfA+Efkv415cWvUs/wJlUSlaNUNn+xv9IrjnHMn1PJQZ8T5WIxj+z7lKFLFfBPeo3UHdLCodifc1FLNfBPcjAP6gbs663VUr+2NFtnp2wiuhojju6vsZAB9RSr0WfkIpdQXA3w6+Vkh9m+1vcaibGgd1E/ecYziu4o3TCFhUophwj8KeQd0sKh2J9zUUM+5HAcdVbMfdoxqMFdlgUYmm5Lirr6yUWt3/yaBftxzPktKvZ7P9LQ51w5+BQoXGPecISik4nuIwyhHUTc5po1hwjwKLSqOqGTp6tguHLSgUD+5HAT+pxHujUM3wk0obXRaVaDqOuxuwJvxarg1sFyLgg13EahwqR9xzjuR4/tBp7j3HY1KJYsI9Cnvb37SEV5JuYXGbaQGKCfejgM1B3feoBu1vm71C/c+AEnTc6W/vEpGtAz4vACoxrCcT+o6Hiq5BhA92UaqbOlMFxD3nCI4bFJV443SsqqGhJCwqUeS4RwGwXP8FEJNKR6sHaYH1joX5hpnwaiiHuB8FHJeDuveqMqlEU3ZkUUkpxVdQB+hZLipl3khFrWboGDgeY+IFxj3naI7nXxuMeB+vJOK31LKoRBHiHuUb2BzUPYpaMNfkbodpAYoe96NdFgd136M2TCqxqETTwatvAn3bHcYKKTp10/83ZQsc0cF229+4dY+iburY6bOoRBQ1y+VMpVGE9zUsKhHFy3EVyrw3GqowqURTxqtvAj3bRYVFpcjVgzd6HNZNdLDd9jcmlUbRqOhsfyOKAQd1jyZMKq3zwY4oNq6n4Cq2v+1VEkGlXGJSiaaGdwMT6NseTBaVIlcL3ujx+F2ig4Xtb2UO6h5Jw9TRYfKRKHK7g7p5G3mUMNW+wWG5RLHp81TuA9UMHRtd7j00Hbz6JuC3v/GfLmphUqnLpBLRgcKkksaI90jqhsb2N6IYhEUlgw9xRzL0EvSSYJNJJaLY7BaV+MJtr2pZ48mTNDW8G5hAn+1vsQiP3mWygOhgNgd1j6VRKcNyPRaqiSJmOR4MrcRTcEdQMzSsMy1AFJt+UORmUuleNUPjTCWaGl59E+hxUHcswn9TntZEdLAwqcT2t9E0gpbatR0+0BFFaeC4bH0bkd+Cwgc7oriESSWe/navqqFxphJNDa++CTCpFA+tJKiWNaYKiA6xO6ibW/coGkH6cXVnkPBKiPLFcjwO6R5RlWkBolix/e1g1bLGmUo0NbwjmEDf9lhUiknN0Diom+gQ4aBunUmlkYQttUwqEUXLcjwmlUZUMzQO6iaKUd9m+9tBakFSyfNU0kuhAuDVNwE/qcR/ujg0TJ3tb0SHcDwmlcbBpBJRPAZMKo2sWtawzqQSUWx229/4wm2vqqHDU8A2n6toCnhHMIE+ZyrFpm7q2OHmR3Sg3fY33jiNYphU6jAlQBQltr+Nrmbo2OzaUIppAaI4DNvfeDLuPWrBsypb4GgaePWNSSmFHmcqxaZRYVGJ6DBsfxtPWSvB1EtMKhFFzB/UzfugUdQMLTiFkq39RHFg+9vBasFhJXf5Yo2mgFffmGxXwVNg+1tMGqaOnuXCcb2kl0KUOsOkEt/Gjaxh6ljlTCWiSFkuk0qjqhlBWoCnMBHFgoO6D1Y3/LT2OpNKNAW8IxhTL9i4mFSKR8PUoQDc5QZI9CZ2mFTijdPIGqaONSaViCJlOR4MpgJGUg2KSutMCxDFou+ERSXuSXvxsBKaJj3pBWTNgEWlWA0H625bWGxWEl4NUbq4roImgpKwqDSquqnzhoooIpcuXwMA3Nzoo25qw4/pcLUgLbDJpBJRLNj+drAwJcmkEk0Dr74xhUklDuqOx+5gXSYLiPZzPMWU0pj89jfuJ0RRcj3FNtwRVflgRxQrnv52MFMvwdBKPKyEpoJ3BGMKq+FMKsWjySPAiQ5lux6HdI+pUdFxt2vB9XjyElFUHM/jA9yIdk9gYlKJKA4D24WAh5jsJyKYrZfZektTwaLSmMJqeNXgP10c6nva34joXn5SiXvPOOqmDqV4+glRlBxX8QFuRGFSie1vRPHo2S50TSAcDfAmp+om739oKvh0MqbhoG4epRuLSrkErSRYZfsb0Zs4TCqNrcGWWqLIOZ6Cxva3kZS1EqpljWkBopj0bY/tuIc4VS+zqERTwStwTGFSqWKwqBQHEfFnoDCpRPQmnKk0vgZPPyGKHNvfxjNbK2ODSSWiWPRtF2XuRwdiUommhUWlMfWZVIpdw9SZKiA6gN9ywm17HHXT36s5p40oOmx/G0+7ZmCDg7qJYtF3PJ78dohTNSaVaDr0pBeQNeGg7iqTSrHhaU1EB2M6YHxNswwAWGVSiSgSSqng9DfuRaOarZU5qJsoJn5SiUWlg9zY6GGr7+Bf/fHr0II9+6PvuS/hVVEe8Qoc03CmUpn/dHFh+xvRwRxXocyk0lgq5RLKmrBQTRQRVykogIcGjGGmVsY6k0pEsWD72+Hqhp8f6VpOwiuhvOMdwZjY/ha/etD+phSPACfaizOVxiciOFU3sMaiElEkXNf/2cyk0uhmagZPfyOKycD2WOQ+RHiqdmfgJrwSyjtegWMKk0psf4tPo6LDdhW2eqyqE+1lu94wvkyjm2+YbH8jiojj+UUl7kWjm6n67W98WUYUvb7DpNJhasHzaodJJYoZi0pjCmcqmTr/6eLSCAfrclg30T0cT3FuwATmGyaTSkQRCYtKbMUd3WzNgOMp7Az4YEcUNc5UOlyYVOpaTCpRvHgFjmlgu6iUSxBhRTwujXCw7jYfAon2clyPLScTmGsYTCoRRcRx/ZdrGpMBI2vX/PsaDusmil6PRaVD1cOkEgvaFDNegWPq2S4qZba+xakRVNX5EEh0L85UmsxCw8TKDue0EUUhTCqxwD262ZoBgEUlojj0bb5wO0wtGNTN9jeKG4tKY+rbLqosKsWqHrS/rbH9jegejqegs+VkbPMNE5bjsfWEKAK7RSXuRaOaCZJKPAGOKHpsfzucVhJUyiUO6qbY8QocU8/2mFSKWd3UURK2vxHt57gek0oTmGv4KQGmHylpIvIZEVkWke8c8vX3i8imiHwz+PVL017jcdyg/Y170ehmqkH7G0+AI4rcwPY4qPsIdUNHl0klihmLSmPqs/0tdqXgCPDVDh8AaTwi8gEReVlEXhGRTxzw9f96z8Pad0TEFZFTwdeuishzwdeemf7qj+Z6Cp5iy8kk5hsmAHBYN6XBZwF84Jjv+apS6vuDX788hTWNxWb729hmhu1vvK8hipLrKViux6TSEeqmzplKFDs96QVkTT8Y1E3xmqubTCrRWEREA/ApAD8B4AaAp0Xki0qpF8LvUUr9UwD/NPj+vwbgv1RK3d3z1/yYUmp1issemcuWk4ntJpW4p1CylFJfEZEHkl7HSbgsKo2tXeWgbqI4DBy/rYtFpcPVDA2bTElSzHgFjqlvu6joTCrFbb5p8AGQxvUYgFeUUleUUhaAzwH40BHf/xEAvzmVlUXAYcvJxBaCpNIK298oG94rIt8SkS+JyDsO+gYReVxEnhGRZ1ZWVqa6OMf1i0oaH+JGZuglNEydRSWiiPVt3hsdh0klmgbeEYypZ7uoGiwqxW2ubmKN7W80nnMAru/5+EbwuTcRkRr8FpTf2vNpBeDfi8g3ROTx2FY5obDlpMyk0thO1f2kEtvfKAOeBXC/UupdAH4NwBcO+ial1JNKqYtKqYsLCwvTXB8cL3iIY1JpLO1qme1vRBHr20wqHaduaOhYLk/ApVjxChxT3/bY/jYFC00TK2x/o/Ec9IRz2E/Qvwbgf9/X+vY+pdS7AXwQwC+IyF94039AgumAYcsJ38aNTddKmK2VmX6k1FNKbSmldoLfPwWgLCLzCS/rHg7b3yYyWy9zUDdRxHrDohL3o8PUTR2upzBwvKSXQjnGmUojuHT52vD3azsD3DL1ez5H0VtsmuhaLnYGDhom/2dKI7kB4MKej88DuHnI934Y+1rflFI3g/+7LCK/Db+d7iv7vudJAE8CwMWLF6f6yscetr+xqD2J+YaJNba/UcqJyBkAd5RSSkQeg//yby3hZd0jbH/jXjSemaqBdSaViCIVJpU4b/JwNcN/jupaPGyK4sMrcEyWqxixnILTrQoA4M5WP+GVUIY8DeAREXlQRAz4haMv7v8mEWkD+FEAv7Pnc3URaYa/B/CXABx45HdSmA44mbkG57RR8kTkNwH8MYC3isgNEflZEfmYiHws+JafAvAdEfkWgF8F8GGVsp4Ftr9NZqZWxiZnKhFFKpypxGezw9VNv5DEuUoUJ0ZAxuS4HiOWU7DY9AfrLm8N8NBCI+HVUBYopRwR+TiALwPQAHxGKfV8+LCmlHoi+Na/CeDfK6U6e/74aQC/LSKAvy9eUkr97vRWf7zhoG4+yE1kvmHi+ZtbSS+DCk4p9ZFjvv5JAJ+c0nImwtPfJjNTKzOpRBSxAdvfjlUPkkodi0Ulig+LSmOyXY/V8ClYDJJKy9tMKtHoghkkT+373BP7Pv4sgM/u+9wVAO+KeXknMkwqcf+ZyHzDZFKJKAI2298mMlszsNmz4XkKJRbkiCLRdzio+zj1YIwIk0oUJ16BY3A9BU8BZZ3/bHFbbO0mlYiISaWTmm8Y2O47w/kLRDQZ1/MgALgVjaddLcNTwHafD3ZEUWH72/F22994/0Px4RU4hnBQbpl3UrFrmjoq5RJnKhEFHJ7+diLzDb9QvdZh+wnRSTieglYSBO3CNKLZmgEA2OhxDyKKSp/tb8cytBLKmmCHSSWKEYtKY+DpS9MjIjjdqmB5m0klImD3xKUyTziZyLCoxBY4ohNxXMXi9gRmamUAwDqHdRNFJkwq8dnscCKChqmz/Y1ixStwDOEcAYMb11QsNk0mlYgCwxOX+DA3kbmGnxLgXCWik3E8xeO7JxAWlTY4rJsoMkwqjaZu6kwqUax4VzCG3aQSN65pWGxVsMKkEhGA3aK2xvbbiYRJpdUdPtARnYTjerwPmsBM2P7GpBJRZHo2B3WPosGiEsWMV+AYwqISk0rTwaQS0a5wphJvnCazW1RioZroJPykEotK45qpMqlEFLVBUFTinnS0OtvfKGZ8OhkDj9GdrtOtCjqWy02QCDz97aSqhoa6oWF1mw90RCfhsv1tIu2wqNRjUokoKn3Hg6mXeHDAMcKkklIq6aVQTvGuYAy7SSVuXNOw2PSTBRzWTbSbVGL72+TmmybWOtxPiE7C8dj+NgldK6FZ0dn+RhShvu2iUtaSXkbq1U0dntodbE4UNRaVxsDT36brdKsCAGyBI0Jw4hKP8T6RubrB9jeiE3JcxeL2hGZrBtvfiCLUt11UWVQ6VsPUAYBzlSg2rI6Mgae/TReTSkS7mA44ufmGiTUO6iY6Ec5UmtxMrYx1JpWIItO3PVTKfC47DotKFDdehWPg6W/Ttdj0k0rLTCoRwXEVypxjciJzDZNJJaITcjyPM5UmNFMzOFOJKEJsfxtN3fT/jTinluLCu4Ix8PS36WpVdZh6iUklIvgPchoL2hO5dPkaLl2+htubfaztWPjXX3896SURZZbjKr5cm9BMtcz2N6II9R0PJotKx2JSieLG6sgYHJ7+NlUigsWWyZlKRPDbb5kOOJlGRYcC0LXcpJdClFku29/GFha2l7cHWN4a4NLla0kviSgX+paLis57o+PUDBaVKF68Csdgsf1t6k43K1jeYlKJyPEUytx7TmT4pq7PmyqiSfkzlXj7OImaoaFvu/B4rDdRJPoO299GoZUENUNj+xvFhncFY3BcD3pJUOLpS1Oz2DJxZ5tJJSLX85gOOCHGv4lOznHZijupmqFBwU9XENHJ+TOV+Dg7irqp8/6HYsOrcAyWq1Bm69tULTYrWGFSichvf+P+cyIsKhGdnOMplFngnkh49DlbcImi4Z/+xqTSKBqmzqQSxUZPegFZ4rge20+mbLFlYnvgoGs5w35goiJyXN44nRSLSkQn53gKGtvfJlIzgqKSzaIS0UmEc8nWuxbeWO8BDya8oAxomDpubbL7g+LBu4IxWK7HpNKUnW5WAAB3mFaignM4HPfEKuUSNBG+qSOakFLKH9TNF2wTCV+OdS3uQURRsPlsNrI6k0oUI16FY3DY/jZ1S22/qHRro5fwSoiS5bD97cREBHVT46Buogk5XnAKLgvcE6kGSaUe29+IIuE/m3E/GkXD1NCzXViOl/RSKIf4hDIGm+1vU7c0UwUA3GRckwrO4aDuSDQqHFRJNCmXRaUTGba/sahEdGKeUn6Kmy/cRlIPRgDc7VgJr4TyKNarUEQ+ICIvi8grIvKJA77+IRH5toh8U0SeEZEfiXM9J8WI5fQxqUTkY1IpGg2efkI0sWFSiXvRRCplDQIWlYii4Lj+fsRns9GEcyVXdzhShKIX21UoIhqATwH4IIBHAXxERB7d923/EcC7lFLfD+D/BODTca0nCjbb36auUtYwVzeYVKLCczjHJBIsKhFNznH9tgkmlSZTEkGlrKFncw8iOik72I/YRTKasKi0xqQSxSDOCsljAF5RSl1RSlkAPgfgQ3u/QSm1o5RSwYd1AAopZrseH+oSsDRTwa1NJpWo2BzP4zHeEQiLSrs/eohoVGFSSeNeNLGaoTGpRBSBYVGJp1GOZFhUYlKJYhDnVXgOwPU9H98IPncPEfmbIvISgP8NfloptWzXg8Gk0tQttau4tcGkEhWXUortbxGpmzpcT2GbaSWisYXtJtyLJlczNA7qJorA7n7EIvco6sOiEpNKFL047woOusLf9GpYKfXbSqm3AfgbAP7bA/8ikceDmUvPrKysRLvKMdh8qEvE2XYFN5lUogJzlYICW06iMJwpsM03dUTjcjy2v51UlUklokjYXtj+xmezUZh6CXpJOFOJYhHnVXgDwIU9H58HcPOwb1ZKfQXAQyIyf8DXnlRKXVRKXVxYWIh+pSPyk0q8kZq2pZkqtvsOtvt20kshSsTwbRwf5E6sUeFMAaJJ8fS3k6sZOroWk5JEJ2VzUPdYRAQNU8cKi0oUgzivwqcBPCIiD4qIAeDDAL649xtE5GERkeD37wZgAFiLcU0n4s9U4sY1bcMT4DismwqKJy5Fh0klosnZbH87MSaViKLBQd3ja1Z0rPD+h2Kgx/UXK6UcEfk4gC8D0AB8Rin1vIh8LPj6EwD+MwA/IyI2gB6A/1yldHqq6yl4itXwJJydqQIAbm708D2nmwmvhmj6eOJSdHikLtHkXLa/nVjN0DBwPNiux3tKohNwXLa/jatZKWN5i/c/FL3YikoAoJR6CsBT+z73xJ7f/xMA/yTONUSF1fDkMKlERcekUnRqhg4BsMpBlURj292LeC80qVpZAwBs9mzMN8yEV0OUXTYHdY+tUdHxyvJO0sugHOITyohsVsMTc7pVQUmAWxsc1k3FxJlK0dFKgqqhMalENIFwL9K4F02savjvcze6nBNJdBJ8Nhtfs6LjbseC5XhJL4VyhlfhiBwOg0tMWSthsVnBTSaVqKCGJy7xbVwkGqbOI3WJJjBMKpV4LzSpmuEnlTa63IOIToKDusfXMssAOAKAosercEQW298StTRTwa1NJpWomIYRbz7IRaJh6ryhIpoAC9wnt1tUYlKJ6CSGSSUmJ0cWnoC7zGHdFDE+oYyISaVknW1XcWuDSSUqpvBBjkXtaDQqLCoRTYKtuCdXC9vfeiwqEZ3E8BATPpuNrBkUlXgCHEUt1kHdeWKxb3eqLl2+ds/Hmz0bNzd7UEpBhDezVCwOk0qRapg6rqx0kl4GUea4bH87sWqZ7W9EUbB5cMDYmhW//W15my/qKVq8KxiRw/a3RLWrZfRtj3FxKiSeuBStpqljZ+CgZ7lJL4UoU+wgNclB3ZOrlEsoCdvfiE7Kdj3oJUGJL5tH1jB1iADLW0wqUbRYVBoRTxhIVrvqV9bf4AlwVEDDiDcf5CLRCN7UMf5NNB7XVSgJi0onISKolDWsM6lEdCK2q/hcNiatJDhVMzhTiSLHK3FEPGEgWWFR6RZPgKMC2k0qcf+JwnCmwA73E6JxOJ5iQSkCNUPnTCWiE3Jcjx0kE1homnypRpHjE8qIbLa/JWqmFiSV1rsJr4Ro+phUihYHVRJNxvE8zlOKQM3QOFOJ6IRs1+PLtgkstipY4UwlihivxBGx/S1ZDVNHtazh+jrb36h4OFMpWg2TR+oSTcJxFfehCPhFJSaViE7Cb3/jfjSuhYbJ+x+KHCskI2L7W7JEBOdnq7h+l0klKh6bp79Fqm7qKAmTSkTjcjzFxGQEqmUN6x0mlYhOwnY9PpdNYLHlt795wQtLoijwShxRmFTiG7rkXDhVww0mlaiAXM/jcNwIlUQw3zB5+gnRmBxPsd0kAg1Tx1rHglJ8qKNkiMhnRGRZRL5zyNdFRH5VRF4RkW+LyLunvcbj2K7iy7YJLDZNOJ7iXDeKFK/EEfkbF4+tTNKF2Squc6YSFZDDG6fILTRNrOywqEQ0Dic4wptOplHRMXA8dCw36aVQcX0WwAeO+PoHATwS/HocwD+fwprG4ngc1D2JxWYFALDMuUoUIT6ljMgfBseNK0nnZ2vY7jvY5BwCKhjb4xyTqC3y9BOisbH9LRr1YK7bKvcgSohS6isA7h7xLR8C8BvK93UAMyKyNJ3VjYbtb5NZaJoAwLQ2RYpX4ohs14PBjStRF05VAYBpJSocpgOit9A0+ZaOaEwOT1uKRHhYwFqHD3WUWucAXN/z8Y3gc6nBQd2TWQyLSixqU4R4ZzAiHluZvPOzNQDgsG4qHM4xid5C08TqjsVBlURjcDw+xEVhmFTa4bBuSq2DLvQDf2CKyOMi8oyIPLOyshLzsnY5TCpNZLHlF5WY1qYo8Uocke0qJpUSduFUUFRiUokKhkml6C02K3A9hfUuH+qIRsX5btFoDItKfKij1LoB4MKej88DuHnQNyqlnlRKXVRKXVxYWJjK4oBg3i2fzcZWM3Q0TJ1pbYoUr8QROR5nKiWtXS2jVdF5AhwVjsOZSpFbYPybaGy8F4pG3dQAAGtMKlF6fRHAzwSnwP0wgE2l1K2kF7WXP1OJ+9Ek/BEAvP+h6OhJLyArLEcxYpkCF07V2P5GheMPx+X+E6WwqLSyPcDbUzV6lCi9mFSKhl4qoVXRscakEiVERH4TwPsBzIvIDQD/EEAZAJRSTwB4CsBPAngFQBfA301mpQfzlAracbkfTWKhaWKFg7opQiwqjcjxPNQMLellFN752SpeXekkvQyiqWL7W/Q4qJJofDyJMjrzDZMzlSgxSqmPHPN1BeAXprScsTmuP96pzHujiZxpVfDN6xtJL4NyhOXdEVkOh8GlwYXZGm6sd+H/rCMqBr6Ni97epBIRjYYF7uj4RSXuP0STcFwPADhTaUJLMxXc3uzzsBKKDK/EEfGhLh0unKqhb3tY4Y0YFYh/+iQf5KIUDqpkUYlodGzFjc5cw8Bah0kloknYQTGEhyhNZqlVgeV63IMoMrwSR2Q7HAaXBhdOVQGAw7qpUPw5Jtx/ouYPquTpJ0Sj8DwFl+1vkZlrGEwqEU3IHiaVuB9NYmnGf566vcl7IIoGi0ojsj22v6XBhdkaAHBYNxUKk5LRu3T5GpRSeP7mFi5dvoZLl68lvSSiVLOChzjOMInGfMPERteG5XhJL4Uoc8KiEu+NJnO27ReVbm7yJT1Fg1fiiGye/pYK54OiEpNKVCRsf4tHs1LGdt9OehlEmTBwOMMkSovNCgAwrUQ0geGgbt4bTWRpxt9/bm3weYqiwTuDEXhKwVWKG1cKVA0N8w0Tr6/xBDgqDh7jHY9GRcd230l6GUSZMHBcAGw3icrpln9YwJ0ttp8QjcvmoO4TmasbMLQSbrH9jSLCK3EEjFimywNzNby+xvY3Kg7HY1IpDi1Tx8Dx2H5CNIKBHTzEscAdiTCptMzDAojGxmezkxERnGlXcJNFJYoIr8QR2MOIJf+50uD+uTqLSlQYtuvBU9x/4tColAEAOwOmlYiOs9v+xgJ3FBaDpBKLSkTjs9n+dmJL7Qpuc6YSRYRPKSPYrYZz40qDB+ZquL3VR89yk14KUeyGD3Icjhu5ZkUHAM5VIhrBsP2Ne1Ek5uoGSgIss/2NaGzDZzMmJyd2dqaKmxvcfygaetILyALbYcQyTe6frwMArt3t4q1nmgmvhiheAzucY8L9J2q7RSUmlYiOYzlsf4uSrpUw1zCxvMWkEtG4wkHdTE6OLzzt9m7Hwq3NHlxPQePLAjoh3hmMwPbY/pYmD8z5J8Bd5bBuKoAwqcRjvKPXMIOiEtvfiI7F9rfoLTZNLG8zKUA0Ltvz9yODz2YTa1fL8BRPoKRo8Eocgc0bqVS5/5SfVOIJcFQEfSaVYlM3dQiAHba/ER2LBe7onW5VcIdJJaKx2cOkEu+NJtWu+nMleQIcRYFX4ghYDU+Xdq2M2VoZVzmsmwqAM5XiUxJBo6Kz/Y1oBGzFjZ6fVGJRiWhc4UwlvvCf3LCotMFh3XRynKk0AtthNTwNwh5gwG9buXxlDZcuX8NH33NfgqsiitcwHcAbp1g0TRaViEbBAnf0FlsVrHUGcFyP95hEY3BcD3pJUBLuR5OaCYpKN5lUogjwJ9gIwqQSH+rSY65hYq1jJb0Motix/S1ezUoZO5ypRHSs3ZlK3IuicrplQilghTNNiMZiuYoppROqGhrKmjCpRJHgncEIHJenv6XNXN3AZtce/v+GKK84xyRefvsbZyoRHWfgBAVu7kWRWWpXAIDHehONyXE9PpedkIigXS1zphJFglfjCCyXp7+lzVzDgAJwt8u0EuUb55jEq2nq2Bk48JRKeilEqWbx0JLInZ2pAgBubTIpQDQOm0WlSLSqZe4/FAlejSPYTSrxRiot5uomAODuDotKlG99PsjFqlnR4Smga7lJL4Uo1XZnKvHWMSpL7aCoxKQS0VhsVzE1GYEZJpUoIrwzGIHF9rfUmasbAMC5SpR7YVKpzAe5WDQq/qBKtsARHW1gs8AdtVZFR93Q8AZnmhCNxfE8GDrvi06qXS3jzlZ/eJoe0aR4NY7AcRU0njCQKlVDQ6VcwlqHwy0p3wZMKsWqafqHoPIEOKKjDRwXmvBeKEoigrMzVbafEI3JTyrxMfakZmsGPMW0JJ0cr8YRWK7H1reUERHM1U2ssf2Nci48/Y1JyXi0qmFSiUUloqMMHI/F7RgszVTZfkI0JpvPZpE4FXR+XLvbTXgllHV8ShkBTxhIp7mGgVUew0s5tzvHhDdPcWhWwqQS29+IjjJwXO5DMTg3U8FNtr8RjcVxFZ/NIsCiEkWFV+MIbG5cqTTfMLHRtYdJDqI8CotKGh/mYlHWSqiWNWyxqER0pIHt8RTKGCy1q1jdsXgvQzQG22VyMgqtahmGVmJRiU6MdwcjsF2Pb+dSaKFhQgF4fY0bIeVXmA4QzjGJTbOiY6vH9jeio1i8F4rFUrsCALjNFjiikdnsIolESQTnZ6u4zqISnRCvxhHYLk8YSKP5hgkAuLKyk/BKiOIzsHnjFLdWtcz2N6Jj+EklFpWidn62BgA8AY5oDH4XCfejKFw4VcPrdztJL4Myjk8qI7Actr+l0XzD7wO+ssqNkPJr4Lh8kItZq1LGFgd1Ex3JT03yXihq9835RSWmrolGZ7seytyPInHfqRqucf+hE+LVOALb9WCwqJQ6ZllDq6LjygqLSpRfA5stJ3FrVXRs9214nkp6KZRzIvIZEVkWke8c8nURkV8VkVdE5Nsi8u5pr/EwPP0tHmdaFZQ14UwTohEppeB4ijPeInL/XA1bfQebXSa2aXK8GkdguR7KbH9LpfmGiSurbH8jn4h8QEReDh7IPnHA198vIpsi8s3g1y+N+meT0ndcJiVj1qyW4SngbtdKeimUf58F8IEjvv5BAI8Evx4H8M+nsKaRDBwmA+KglQQXZmu4xvYTopGEB5gYLHJH4sIpPy3JwjadBO8ORuAnlbhxpdF8w8SVlQ6UYsKg6EREA/Ap+A9ljwL4iIg8esC3flUp9f3Br18e889OHeeYxK9V0QFwUC7FTyn1FQB3j/iWDwH4DeX7OoAZEVmazuqOxlbc+Fw4VeMDHdGIwpMSmVSKxn0sKlEEeDWOwHI4KDet5psmNns21hnZJOAxAK8opa4opSwAn4P/gBb3n43VwPE4xyRmrUoZALC8zaISJe4cgOt7Pr4RfC5xbMWNz/1zNby+1uULMqIR9G0/qcRns2iESSUO66aT4NU4As5USq+FcFg3T4Cj0R/G3isi3xKRL4nIO8b8s1PXt5kOiFszSCrd2RokvBIiHHSxv6nSICKPi8gzIvLMysrKFJbljwJgMiAe952qYbvvYLPHF2RExwmTSjz9LRoNU8dc3cB1JpXoBHh3cAyllH9sJWcqpdJ8wwQADusmYLSHsWcB3K+UeheAXwPwhTH+bCIPcpxjEr9mkFS6s8WkEiXuBoALez4+D+Dm/m9SSj2plLqolLq4sLAwlYUxqRQftp8Qja7H9rfI3TfHFlw6GV6NxwiHwTFimU4zNQNlTfAqh3XTCA9jSqktpdRO8PunAJRFZH6UPxv8mek/yHGOSey0kqBu6kwqURp8EcDPBKfA/TCATaXUraQXBXAvitP9c3UAwGurfEFGdBwmlaJ3H+e60QmxUnKMruVvXBzUnU5aSXD/XB2vMalEwNMAHhGRB0XEAPBh+A9oQyJyRkQk+P1j8PfAtVH+bFL6Nme6TUOromOZSSWKmYj8JoA/BvBWEbkhIj8rIh8TkY8F3/IUgCsAXgHwPwD4LxJa6ptwvlt87p+rQYSpa6JRcKZS9O47VcPNjT5s10t6KZRRetILSLvesBrOjSutHpyv4wrf7hWeUsoRkY8D+DIADcBnlFLPhw9rSqknAPwUgJ8XEQdAD8CHlT8Z9cA/m8h/kX0GjsuWkyloVcq4w0HdFDOl1EeO+boC8AtTWs5YBg5PooxLpazhwmwNr3I+JNGx+k7wbMZ7o8hcOFWD6ync3OgNk5NE42BR6Ri9IKnEmUrp9ZaFOv7w5WU4HCJaeEFL21P7PvfEnt9/EsAnR/2zaeA/yPF/13FrVnS8zug30YEc14PrKSaVYvTQQh2vMqlEdKyBzWezqN0fzHW7utZlUYkmwqvxGL1h+xv/qdLq4YUGbFexF5hyaWB7fBs3Ba1qGas7AziMfhO9ye58Se5FcXnLQgOvre7A8950RgQR7TFsf2OROzJvWWgA4GnaNDlejcdg+1v6PXK6CQD47jI3QsoXpRT6HI47Fc2KDqWA1R0r6aUQpY4VFJXYihufhxYa6Nsebm72kl4KUar1h6e/cT+KynzDQLOic64bTYyVkmOERSUO6k6vhxf96vorLCpRztiuglIsak9Dq1IGANzhsG6iNwmTSmzFjc9DC37LCVvgiI7W5wv/yIkI3rLQ4Fw3mhivxmP0LAcA+3bTrGHqWGpXWFSi3BkEwyiZDogfi0pEh+NeFL+Hghdk372znfBKiNKt7/D0tzg8NF9nUokmxqvxGLtJJf5TpdnDiw18d5k3YpQv4dwApgPi16z651bc2R4kvBKi9GFSKX7zDRPzDRMv3uK9DNFRwnm3bH+L1lsW6ri91Udn4CS9FMognv52jJ7FangWPLLYxKU/eR2ep1Dim1TKiTAdwOG48WuYOkoCLDOpRPQmA5szlaJ26fK1ez7+6Hvuw6NnW3jx1lZCKyLKhr7jQisJSsL9KEoPBcO6X1vt4HvPtRNeDWUNKyXH6IbtbywqpdrDi/6Ayzc2OOCS8mOYDuAJJ7EriWChabL9jegAw/Y3Frhj9falJl5Z3hkORieiNxvYHl+2xSA8AY5zlWgSfFI5RjgMzuBMpVR75DSHdVP+8IST6TrdquDOFtvfiPZjgTt+ly5fw3rHhuV6+LXf/+6bkkxE5OvbLsrciyJ3/1wNIuBcJZoIr8hj9GwXJQE0Rr5T7eGgus65SpQnAw6jnKrFZoVJJaIDWMO9iPdCcVpqVwAAtze5DxEdpm+7PEApBpWyhvOzVSaVaCK8Io/Rszw+0GXAbN3AfMNgUolyhXNMput0y8QyB3UTvcnu6W+8H4rTfMOEXhLcYlGJ6FA922WBOyZvmW8wqUQT4aDuY/Rshye/pVwYEW9WyvjjV9eGH3/0PfcluSyiE9udY8I9aBpOtyq427EwcFyYupb0cohSY7f9jQ9ycdJKgtOtCm5tcj4k0WF6Nl/4x+UtC3X8yWt3efARjS3WK1JEPiAiL4vIKyLyiQO+/rdE5NvBr6+JyLviXM8kehYjllmx2PRTBkqppJdCFIk+k0pTdbplAgBWmFYiuscwNcl0QOzOtCu4tdnnvQzRIfqWy6JSTN6y0EDPdnGbowBoTLEllUREA/ApAD8B4AaAp0Xki0qpF/Z822sAflQptS4iHwTwJID3xLWmSfRsl0mljFhsVTBwPGz3HbSq5aSXQ3RiYVKJN0/Tsdjy55nc2erj/Gwt4dUQpQdTk9Oz1K7gG6+vY7vvJL0UolTis1l8HlqoAwA+/dXX8PBi456vsQOEjhLnFfkYgFeUUleUUhaAzwH40N5vUEp9TSm1Hnz4dQDnY1zPRLoW+3azYrHppww4aJfyYthywj1oKk43w6ISk0pEe7H9bXqW2lUA4FwlokNwplJ8HgoOPlrZ5v5D44mzqHQOwPU9H98IPneYnwXwpYO+ICKPi8gzIvLMyspKhEs8Hk8YyI4zQcqAkU3Ki4EdDsflzdM0nGnvJpWIaBcL3NMT3stwrhLRwXpsf4vNYtNEw9SxssOXazSeOAd1H3TncWCDuIj8GPyi0o8c9HWl1JPwW+Nw8eLFqTaZM2KZHXVTR7Oi8yheyo3B8Bhv7kHT8KXnbkETwR+8tDIc1M24N5G/F4kAmrCoFLeqoWG2VsZN3ssQHYgv/OMjInhooc7ZkjS2OK/IGwAu7Pn4PICb+79JRN4J4NMAPqSUWotxPRPpshqeKWdaFSaVKDeYDpguEUGzqmOrbye9FKJU8U9ELEFYVJqKczNV3NxgUonoIHzhH6+HFhssKtHY4rwinwbwiIg8KCIGgA8D+OLebxCR+wB8HsBPK6X+LMa1TIwnDGTLmVYFy9sDuB5PTaHs69su0wFT1q6UsdVjUYlor4HtDdN7FL9zszXc7VjY6FpJL4UoVZRSnKkUs4cWGtjqO+gHIxiIRhFb+5tSyhGRjwP4MgANwGeUUs+LyMeCrz8B4JcAzAH49eDtl6OUuhjXmibRs10YOjeurDjTrsD1FFbZC0w5MHA8pgOmrFUtMyFAtM/A8WCw3WRqzs34w7qfe2MTf/6RhYRXQ5QelutBKY4FiNKly9fu+Ti8B1rdGfAkXBpZnDOVoJR6CsBT+z73xJ7f/xyAn4tzDSfF9rds4aBdypOB7aJSZjpgmtrVMl66vQWlFIt5RIGw/Y2mIywqffsGi0pEe/UtzpqM20JwmvbKNotKNDpekUfwPIWB43HjypCFhomSgMO6KRf6tscHuSlrV8uwXT9eT0S+MDVJ01E1NMzVDTx3YzPppRClSvizmTOV4jNX95+lljlXicbAK/IIfYcbV9boWgnzDZPDuikX/HQAk0rT1KqWAQCbnKtENMSZStN3braK595gUYlor7CoVOZokthoJcGpuslh3TQWVkuO0LPCjYv/TFlyps0T4CgfBo6HSpn7zzS1g6ISh3UT7bJcDyb3oqk6P1PFGxs9zogk2iN8NtNL3I/itNg0scK9h8bAK/IIXStMKrEaniVLrQo2ujaPBafM81tOmA6YpvYwqeQkvBKi9BjYnKk0beeCWSZsgSPaNWx/434Uq4WmibUdnqZNo+MVeYTwKEXOVMqW08Gw7pdvbye8EqKT6fNBbuoapg4B29+I9mKBe/rOtisQ8Yd1E5GPz2bTsdA04SngbsdKeimUEbwij8BhcNl0puUXlV5iUYkybuCw5WTatJKgWdHZ/ka0Bwd1T59Z1vDQQgPPvbGR9FKIUmM4moRdJLFaaOyeAEc0Ct4hHKHLmUqZ1K6WUSmX8NKtraSXQnQiA8dFhemAqWtXy9hk+yzR0MBx2W6SgHeeazOpRLRHj0mlqVhohkUlzqil0fCKPAI3rmwSEZxpVdj+RpnXt5lUSkKrWmb7G9EeA9tDpcwC97R93/k2lrcHuMPDR4gAsItkWiplDa2KzmHdNDJekUfoW9y4supMu4KXbm9DKQ6Yo+waOC7nmCSgXS2z/Y1oj77t8iTKBLzzfBsA5yoRhYYzlZicjN1802T7G42MV+QRuuzbzawzrSp2Bg5urPeSXgrRxPx0ALfpaWtXyxg43vDmlajo+jZbcZPw6FIbWknw3I2NpJdClAqcqTQ9Cw0Ty9sDvqCnkfBp5Qg9VsMz60zL7wVmCxxlmX/6Gx/kpq1VLQPgCXBEAKCUQs922f6WgKqh4ZHFBr7FpBIRAI4mmabFpomB42F74CS9FMoAXpFH6LNvN7NOByfAvchh3ZRhPHEpGe2KX1RiCxwRYLsKngJTkwl55/k2nntjk2kBIvizJg29hJIwqRS3hab/LMUWOBoF7xCOsNv+xn+mrDHLGu6fq+HF2ywqUTYppVhUSkibSSWiob7j3wsxqTR9ly5fQ9/2cLdj4df/8FVcunwt6SURJapvu6hyL5qK3RPgWFSi4/Fp5Qg920VZE2glVsOz6NGlFl64yaISZdPA8QAAVUNPeCXF06z6/+abfRaViMLUNotKyTg/WwUAvMEZkUToWSwqTUurosPQSywq0UhYVDpCz+IMgSx7x9kWrq51sc0HQ8qgcBglW06mTy+V0DB1tr8RwT8wAGBRKSlnWhVoInhjg0Ulop7tompwL5oGEcFCgyfA0Wj4tHKEvu2ixo0rs95x1j+K9yUO66YMCodR8o1cMtrVMtvfiLC7F7HAnQxdK+F022RSiQj+fsSxANOz0DSxssOiEh2PV+URuoxYZtqjZ1sAgOff4KkplD1hywnfyCWjxaISEYA97W88iTIx52ZquLHR5bBuKrw+k0pTtdg0sdmzMQh+DhAdhkWlI/AI3WxbbJqYbxh4gSfAUQaF6QCTD3KJmKmWsdFlUYmoz/a3xJ2frQ4HdhMVGWcqTdd8IxjWzbQSHYNFpSOwGp5tIoK3L7XwPId1UwYxqZSsmVoZA8djWokKb3cv4i1jUs7N+MO6b3CuEhVcj6e/TdUiT4CjEfEO4QhdizOVsu4dZ9v47p0dWMFJWkRZEaYDePOUjJmaAYAnLhH1mZpM3OlWBXpJuB9R4fVsFxU+m03NqYaBkjCpRMdjUekIjFhm36NnW7BcD68s7yS9FKKx8PS3ZM3WygDAE5eo8HYHdfN+KClaSbDUrnA/osLr89lsqvRSCafqBpNKdCw+rRyhz5lKmfeOYFg35ypR1vQdnv6WpHbVLyrd5EMcFdxgOFOJt4xJOjdbxRsbPXgeh3VTcbH9bfoWmhUss6hEx9CTXkCa8fS3bLt0+Ro8pVDWBJ9/9sawBe6j77kv4ZURHW83qcQ9KAkNU/fbTVhUooILC9zci5J1bqaGr1+5iyurHTy82Eh6OUSJ6HHe7dTNNwz82Z1tuJ6CVpKkl0MpxddOR+haDuom625ZVhLBUruKW5v9pJdCNJY+W04SJSKYqZU5w4QKj3tROpyb9Yd1P/fGRrILIUqI5yn0bY970ZTN1U24nsKtTd4P0eFYVDqEUoqDunNiqV3Brc0elGJknLJjOKibe1BiZmoGT1uiwgv3oorOW8YkLTZNlDXBt65vJr0UokQMHB5gkoS5hn9wyetr3YRXQmnGO4RDWK4Hx1NMKuXA2XYVfdvDepdHg1N2DIfj8kEuMTNVJpWIeraLsibQNe5FSSqJ4OxMFc+9waISFVOYmqxyvttUzdX9otLVtU7CK6E041V5iHCeCZNK2bc0UwHAgbuULXyQS95MzcDqzmB4I0tURH3bRUXnvVAanJ+p4vmbm3BcL+mlEE1d+LKNCe7palXL0EuCq6ssKtHh+LRyiA6LSrlxulVBScBeYMoUnj6ZvNkaT4Aj6tseTO5FqXBu1k9ef3d5J+mlEE1dj/PdElESwam6gatsf6MjsKh0iO7AAQDUDLa/ZV1ZK2G+YXJYN2VKn8fmJq49LCpx76DiGtguKmw3SYWzM/6w7udvbiW8EqLpC7tIeG80fXMNk0klOhLvEg4RJpXqJjeuPDg7U2XagDKlZzGplLTZqj9H4I0Nvp2j4uo73IvSYr5holIu4QUWlaiAeBJlcubrBl6/24Xn8dAjOhiLSodgUilfltoVbPUd7AT/fyVKu77t8W1cwlrVMkoCDuumQutZTE2mRUkEbzvTwgu3OKybioczlZJzqmHAcjzc3mJymw7GotIhhkklFpVyIYyMc64SZUXPdlHhjVOitJLgTKuCG0w5UoH1bY/tbyny6NkWXry1DaWYGKBiYftbcubqJgCwBY4OxbuEQ3StIKnE9rdcWGr7J8Dd4mwUyoie7aKic4tO2rnZKpNKVGhsf0uXty+1sNmzcZNzIqlgOKg7OfMNfxwAh3XTYfjEcoguk0q5UjN0zFTLuMmkEmXEwHYZ8U6BczNVvMGkEhVY3/Zg6tyL0uLRpRYAcK4SFU6f7W+JaVXLMPQSXl9jUokOxqLSITrB7B1uXPmx1K7wBDjKjB5Pf0uFc7NV3N7sw+VwSioonv6WLm8704QIi0pUPGx/S05JBPefquE1tr/RIXiXcIgwqVRjUSk3lmaqWN0eDH8oEaVZz2bLSRpcmK3B8RTnsVFhcS9Kl7qp48G5Ood1U+H0bA8Ai0pJuX+ujtfZ/kaHYFHpEB3LgaGXUNb4T5QXZ9sVKAAv3ebbPUo/fzgub5ySdv9cHQB4I0WF1WdqMlUuXb6GuqnjT167i0uXr+HS5WtJL4loKsKZSibnTSbigbkarq514DG5TQfgVXmInuWizpRSriwFJ8A9z8g4ZUCfx3inwv1zNQDAVc4RoILi6W/ps9SuYL1rM3lNhdIPWnFLJUl6KYX0wHwdA8fDnW2OEqE3413CIToDFzUO6c6VmWoZ1bKGF26xqETp55+4xC06aWdaFRh6CdeYVKICUkpxvlsKLbX9l2S3t/hwR5MRkQ+IyMsi8oqIfOKAr79fRDZF5JvBr19KYp17MTWZrAeC5PbVVd4P0ZvxieUQXctB3eTGlScigqV2hUklSj3b9WC7ijdPKVAq+cMpmVSiIuqHM0z4ki1VlmYqAMBZbzQREdEAfArABwE8CuAjIvLoAd/6VaXU9we/fnmqizxAjwnuRDG5TUdhUekQHYtJpTxaalfw0q0tOK6X9FKIDsVjc9OFwympqLpWcBIuU5Op0jR11A2NJ9rSpB4D8IpS6opSygLwOQAfSnhNx+rZLiq8L0rM2ZkqDK3EohIdiHcJh+gOmFTKo7MzVQwcj0diUqoNh1HyjVwqhMMpleJwSiqW3ZNw+ZItTUQESzNVJpVoUucAXN/z8Y3gc/u9V0S+JSJfEpF3TGdph2P7W7K0kuDCqSpeZ/sbHYBFpUN0LBfVMm+i8iacQ8C5SpRm4fDVGm+eUuH+uRr6tofl7UHSSyGaKqYm02upXcGdrQFcnsRE4zto0vX+/yE9C+B+pdS7APwagC8c+peJPC4iz4jIMysrK9Gtcp+e7fJU3IQ9OF9nUokOxKLSIXqcqZRLC00Thl7iXCVKtTAdwD0oHe4PhlOyBY6KZjepxL0obZbaVbiewgqL3TS+GwAu7Pn4PICbe79BKbWllNoJfv8UgLKIzB/0lymlnlRKXVRKXVxYWIhrzZyplAL3z9WZ3KYDsah0CM5UyietJHjr6SZeYFGJUix8kONw3HQYnnjCt3NUMMO9iA9yqbPU5rBumtjTAB4RkQdFxADwYQBf3PsNInJGRCT4/WPwnxnXpr7SPXq2x6RSwh4Iktt3tljMpnvxieUQ3YGDOt/M5dI7zrbw5edvQymF4OclUaqEw3GZDkiHszMV6CXB6ywqUcGw/S295hsm9JJwWDeNTSnliMjHAXwZgAbgM0qp50XkY8HXnwDwUwB+XkQcAD0AH1YJx1N6lsO9KGEPzPsv2V5b7eBMUNgmAlhUOpBSCl3b5QNdTj16toXPPX0dt7f6wxlLRGnCdEC66FoJF07VcJXtb1QwHNSdXlpJcKZdwU0mlWgCQUvbU/s+98Se338SwCenva6jdCwXDY4FSMyly9dwt2MBAP7dM9fx3ofmEl4RpQnb3w7QtVwoBTQqvInKo3ecbQEAnn+DLXCUTr3hTCXuQWlx36kak0pUOExNptuZVgW3Nvqcb0KF0B04LHAnbKZWhiaCtR0r6aVQyrCodICdgX8TxQe6fHrbmRZEeAIcpReH46bPA3M1vL7W5cMbFUovaH/jHJN0Wpqpome7uL3FFjjKt7CLhKNJklUSwWzdwFqHM5XoXiwqHSAsKjVYVMqluqnjwbk6nr+5mfRSiA4UpgM4OyA97p+rY7vvYL1rJ70UoqnpscCdameDmSY8fITyrm97UIoHmKTBfMNgUonehEWlA+z0WVTKu7efbTGpRKk1TCoxHZAaD8zXAPjDKYmKgvPd0u1Mi0UlKoaOFXaRcC9K2lyQVGJym/ZiUekAHSaVcu8dZ1u4freHzR5TB5Q+XcuFoZega9yik3bp8jVcunwN3wlmsF26fC3hFRFNT892YeollEo8KTWNzLKGubqB51lUopzrDnhoQFrMNUzYrsKdLbbA0S4+sRxgmzOVcu/RJX9YN9/uURr1LIftJikzWzOglwTL25xdQsXRs3gSbtqdaVfw4m3ey1C+DZNK3I8SN9cwAABXeXgJ7cGi0gHCpFKTp7/l0qXL1/Dy7W0AwL/++utMHlDqdCyXrW8po5UE8w0Ty3wzRwXStVwmA1JuqV3F62vd4TxQojwankTJF/6Jm6ubAICrHAdAe7CodACe/pZ/zUoZTVPHzY1e0kshepOe5XJIdwotNE2s7LCoRMXRsx3uRSm3FAzrfolzIinHwvluTColb6ZWhiaCq2vdpJdCKcKi0gF4+lsxLM1UcGuTrSyUPl3LYVE7hRabJtY7FvrBMetEede1XA7pTrmwqPQii0qUYx3OVEqNkghm6waTSnQPFpUOsNN3oJcEps5/njxbalexvN2H43pJL4UiIiIfEJGXReQVEfnEAV//WyLy7eDX10TkXXu+dlVEnhORb4rIM9Nd+b34IJdOi60KFIBXV3aSXgpl1Ah71PtFZDPYh74pIr+UxDpDTE2mX7taxkytzBNtKde6PP0tVeYbBmcq0T1Y7j1AZ+CgUdEhwtNO8uzsTBWeAu5ss50lD0REA/ApAD8B4AaAp0Xki0qpF/Z822sAflQptS4iHwTwJID37Pn6jymlVqe26EN0LRfzwSBESo+Fpj9H4Lt3dvCOs+2EV0NZM+IeBQBfVUr91akv8AA928WpOveiNBMRvP1MCy/c2k56KUSx6QTtbyxyp8Nc3cCz1zaglOLzMgFgUulA2wMHdcYrcy+MjN/iXKW8eAzAK0qpK0opC8DnAHxo7zcopb6mlFoPPvw6gPNTXuNIupbDiHcKzTcMaCJ46TYf3mgix+5RacPUZDY8eraFl29vwfVU0kshikU3nHfLe6NUmGuY6Nku7vDwEgqwqHSAzsDhyW8FcKpuwNBLuMm5SnlxDsD1PR/fCD53mJ8F8KU9HysA/15EviEij8ewvpHxGO900kslLDRNzi6hSY26R71XRL4lIl8SkXcc9BeJyOMi8oyIPLOyshLHWgGw/S0r3r7UQt/28BpnnFBODZNKLHKnwlyQYGULHIVYVDrAzoBDcougJIKlVoVJpfw4KH974GtbEfkx+EWl/2bPp9+nlHo3gA8C+AUR+QsH/LmpPMh1bRaV0mqpXcFLt1lUoomMskc9C+B+pdS7APwagC8c9BcppZ5USl1USl1cWFiIdpV79LgXZcKjSy0A4Fwlyq2e5aBmaCiV2GqVBnMNfxwAh3VTiEWlA+wMXJ78VhBLM1Xc2urDY2Q8D24AuLDn4/MAbu7/JhF5J4BPA/iQUmot/LxS6mbwf5cB/Db8VpV7TOtBrjtwUWXEO5XOtCu4szXA3Y6V9FIoe47do5RSW0qpneD3TwEoi8j89JZ4L7biZsPDiw2UNWGKknKrY7nci1JkplZGWRNcXesmvRRKCRaVDrDTt1lUKoiz7Qosx8Prd7kp5sDTAB4RkQdFxADwYQBf3PsNInIfgM8D+Gml1J/t+XxdRJrh7wH8JQDfmdrK93BcD5brMR2QUmda/iy2l/jwRuMbZY86I8HUUxF5DP592tqb/qYp8DyFvu2hwnaT1DP0Eh5ebOKFm9yXKJ+6A4cnv6VISQQXTtWYVKIhVk4O0GFSqTCWZqoAgBdubuHB+XrCq6GTUEo5IvJxAF8GoAH4jFLqeRH5WPD1JwD8EoA5AL8ePLc5SqmLAE4D+O3gczqAS0qp303gvwa6tj83gEWldDoTDPh/4dYW/tzDiQVIKING3KN+CsDPi4gDoAfgw0qpRKK0fYd7UZa8famJP/pu4oeXEsWCSaX0eXCuzplKNMSr8wCcqVQcp5smSgI8f3MTf+WdS0kvh04oaBd5at/nntjz+58D8HMH/LkrAN4V+wJH0LPCBznuQWnUrJRxumXiO29sJr0UyqAR9qhPAvjktNd1kM6ARaUseXSphc8/+wZWdwaYD+adEOVFN5ipROlx/1wdX3t1DUopBC9lqcDY/raP5yl0LAcNnv5WCLpWwmKzwuGWlBqd4Nhc3jyl1/edm8G3WVSinOvwCO/MuHT5Gm4FJ9l+6g9ewaXL1xJeEVG0OgMeGpA2D87X0LNd3NkaJL0USoFYi0oi8gEReVlEXhGRTxzw9beJyB+LyEBE/u9xrmVUXduFUkCDfbuFcXamguc5h4BSohsem8ubp9R61/k2rqx0sNW3k14KUWx2wqISk9uZsBTMe7u10U94JUTR61kuC9wpc/+cPzaELXAExFhUEhENwKfgH8/9KICPiMij+77tLoD/G4D/T1zrGNdOnzdRRbPUrmJle4Dlbd6IUfLCdADnuqXXOy/MAABb4CjXuBdlS83U0a6WcXuL9zKUPx3LQY0v/FMlnEXLYd0ExJtUegzAK0qpK0opC8DnAHxo7zcopZaVUk8DSM3r3u3gzXOrUk54JTQtSzPB4F2mlSgFOhYf5NLu+861AQDfvsGiEuVXuBfxxKXsWGpXcGuzl/QyiCLXZVIpdc7OVGFoJbzGohIh3qLSOQDX93x8I/hcqm0FSaVWlUWlolhqBSfAca4SpcA205Kpd6pu4L5TNfzptfWkl0IUm51gUDcL3Nlxpl3ByvYAtuslvRSiSO0MmFRKG60keGC+hldXdpJeCqVAnEWlg8bAT3Qsrog8LiLPiMgzKysrJ1zW0baGSSXeRBVF1dBw36kanmPqgFIgnGPS5B6UahcfmMU3Xl9HQqe9E8Wuw5lKmbPUrsJTwPI2B+dSfgwcF5bjsYskhR5ebOCVZRaVKN6i0g0AF/Z8fB7AzUn+IqXUk0qpi0qpiwsLC5Es7jBbPb+o1OTGVSjff2EGf3ptI+llEPFBLiN+6IFTWN2xcHWtm/RSiGLBvSh7ltrhsG62wFF+dJiaTK2HFxq4dreLvu0mvRRKWJxFpacBPCIiD4qIAeDDAL4Y439eJHbb37hxFcm775vB7a0+bvJGjBK203cgAtTKjHmn2Q89MAsAePrq3YRXQhSP8EGuzpMoM+NU3YChlXCLw7opR8JDlFhUSp+HTzfhKZ4ARzEWlZRSDoCPA/gygBcB/Dul1PMi8jER+RgAiMgZEbkB4L8C8P8QkRsi0oprTaMIk0qMWBbLu+/3HxCZVqKk7Qz8YZSl0kEdxJQWDy00MFsr4+nXWFSifOpYDirlEnQtzvePFKWSCM60K7i1waIS5Uc4mqTBsQCp8/BCAwDYAkeI9epUSj0F4Kl9n3tiz+9vw2+LS42tvg1DL6HClEChvO1MC6ZewrPX1vFX3rmU9HKowHYGNt/GZYCI4LEHT+Frr65BKQURFgEpX3YGDveiDFpqV/CtGxvclyg3hrMmuR+lzlsW6hBhUYnibX/LpK2ewyHdBWToJbzzfBvP8jQnSlhn4PJtXEb8yMPzeGOjx7lKlEudgcN5Shm01K6ib3u4sc52fsqHYfsb741Sp1L2Dzv67h0WlYqORaV9tvs2W98K6t33zeL5N7YwcDhsjpKzzQe51Lt0+RouXb6G9a4fyf///t6fJbwiouh1Bg7qBveirDk3UwUAfJsn2lJO7J6Ky+ezNHrr6SZeur2V9DIoYSwq7bPVd9CsctMqoh+4bxaW6+H5m9wYKTk7fZsR74yYqxuYqZUZ+6ZcYvtbNp1um9BKgm/f2Eh6KUSR2B5wUHeavW2phddWOzwBruBYVNpnq2ez/a2g3n3fDADg2dfZAkfJ6Qxc1E3OdMsCEcEji028urLDhCPlDveibNJLJZxtV/DN6xtJL4UoEmH7W5PPZ6n0tjP+CXB8wVZsLCrts9W30WJSqZAWWxWcm6nyBDhKlJ8O4B6UFW9famLgePj6FZ4CR/nCmUrZdW62hu+8sQnXU0kvhejEdgY29JLA1PnYmkZvO9MEALx4i50eRcarcx8O6i62H7x/Fk9fvQuleCNGyfCLSkwHZMVDCw2UNcF/eOFO0kshihTb37LrwmwVHcvFqytMDlD27fQdNCo6TzNMqfvn6qiUS3jp9nbSS6EEsai0zxYHdRfaD79lDsvbA1xZ7SS9FCogpZT/IMfCdmaUtRIeWWzi9164A4+pAMoRJpWy69ysP6z7W2yBoxzYZoE71bSS4K2nm0wqFRyLSnv0bReW47H9rcD+3ENzAIA/fnUt4ZVQEfVtD66n+CCXMd97ro3bW308fZUtcJQPnqfQsVzuRRk13zDRNHV8i8O6KQe2+ywqpVF4Eu6ly9dg6hqevbbOTo8CY1Fpj+1gEBzb34rr/rkaltoVFpUoEcNjc3nzlClvX2qiWtbwxW/dTHopRJHoBqf4sBU3m0oi+L7zbXz7xmbSSyE6sZ2+wyHdKXd+toq+7eHqWjfppVBCWFTaY6tvAwCabH8rLBHBex+awx9fWWMrC01dWFRiOiBbTF3Djz96Gv/bc7d4ChzlQod7Uea98/wMXry1xT2JMo/z3dIvbLn9NtORhcWi0h5bvbCoxI2ryP7CIwu427Hw3Bt8w0fTFT7I8eYpe37qB89jo2vjS8/dTnopRCe2w70o877/Qhu2q/DiLQ7PpWzbGTh84Z9yi80K9JIwHVlgLCrtsdH1i0ozNSPhlVCS/sL3LEAE+MOXV5JeChVM2ILLB7ns+fMPz+PB+Tp+44+vJr0UohPbCfaiusG9KKvedWEGAPDs6+vJLoTohLb7PMAk7bSS4OxMlUmlAmNRaY/1rgUAmK2xGl5kp+oGvv/CDP7g5eWkl0IFw/a37CqVBH/7h+/Hs9c28B2mHCnjwnEAbd4PZdZSu4pzM1U88zoPEKBs2xnYnDWZARdmq/j2jU223BYUi0p7rAdJpVkmlQrvx966iG/d2MDydj/ppVCBhC24bZ5AmUk/9YPnUS1rTCtR5m1yL8qFxx48hT95jScyUXbZroe+7THBnQEPztcxcDy2wBUUi0p7bHQtiAAt3kQV3l9+xxkoBXz5+TtJL4UKhA9y2daulvE3fuAcfuebN7ERJF+JsmirF56Gy70oy37ogVNY3RnwRCbKrHAsAOfdpt/9c3UAwJ+8xnRkEbGotMd610K7WoZWkqSXQlN26fK1e349c/Uu5hsmvvTcraSXRgUSFpVY2M6uv/PnHsDA8fCZ//1q0kshmtiw/Y17UaY99uAsAOBpPuRRRg1ftrEVN/Xqpo63nm7iMvebQmJRaY/1rs3WNwIAiAi+71wLX7+yhtWdQdLLoYLY7PlzA1jYzq63nmniA+84g//fH72GzaClmihrNns2ypqgUuZtYpY9tNDAfMPA115dTXopRBMJU78zVT6fZcFjD57CM1fvwnK8pJdCU8a7hT02uhaHdNPQO8/PwFPAF/70jaSXQgWx1bOZUsqBv/fjj2B74OBf/tGVpJdCNJGtno1WpQwRFrizTETwvofn8UevrHGuEmUSE9zZ8he+ZwFdy8XTV3fTSvu7QSifWFTaY73DpBLtOt2q4Afum8G/ffo6b8ZoKjZ7NttNcuDtSy188HvP4F985Qo+/dUrvJGizNnqO9yLcuJ9D89jdWeAl+9sJ70UorGFRaUZvvTPhPc9PAdDL+H3X+IJ2kXDotIeG10LMywq0R7/x4sX8N3lHTx7bSPppVABsKiUH3/vxx/BwPHwR99l2wllz2bPRpN7US78yMPzAMC9iDKJB5hkS83Q8cNvmcMfsKhUOCwq7eHPVOKmRbv++rvOolXR8Zk/ei3ppVABsKiUXfvj3c++voF3nm/ja6+uYbvP2UqULX77G09byoOzM1U8vNjAH7zMhzzKno0ui0pZ8+NvX8SV1Q5evs10ZJGwqBTo2y56tovZOpNKtKtu6vjoe+7Hl75zC9fv8kheiheLSvny428/Dcfz8IcvryS9FKKxbHEvyry9Re6z7Sr++NW1YeqDKCs2ezbqhoayxkfWrPjJ71uCVhL8NmfSFgqv0EBYCWfPLu33d9/3AHSthF/7/e8mvRTKuY2ezWNzc2S+YeIH75/Fn7x2F+sdK+nlEI1sq89DA/Lk7UtNeAr4Q6aVKGM2ujZHk2TMfMPEj37PAn7nm2/A8ziTtihYVAqsB0dWclA37Xe69f9v78zjpCquxf89Pfs+DOvAsO+LoCAKrogaxQ2NS9REQxZNTEw0z+RlT0zMS/JeXqIvi1tck5973BNUDIiIIMguIDsDDMM6MPs+U78/6jY0TfdMz3T33J7u8/187qdn6tatOnX71umqc0+dSufWaYP5x8oStmqgSyVK1De10Njcqt4BccbMMX0RgfkaX0DpJhhjqKxrJjdddVG8MLAgk6y0ZOZtPOC2KIrSISp0V9xuyWcnD2BfRT3vb1FP7URBjUoOXqOSeiopgfjGBSPISkvm529s0J3glKig2+bGJ3kZKUwb1pPVu4+qUVrpFtQ3tdLYogbueMIjwoT+ucz/9ADVDc1ui6MoIVNR10i+6qJux2fG9aNfbjqPa0zahEGNSg5Ha+yETj2VlEAUZKXyg1ljWLK9jJdWlLgtjhKHHNs2VwdPccf5o3qTmuzh9/O2uC2KorRLZb3XwK2BuuOJUwfmU9/Uyjvr97stiqKEjMaa7J6kJnu49azBLN52mNLyOrfFUboANSo5HK5uAKB3TprLkiixyk1TB3Hm0ALufXMD2w5Wuy2OEmfotrnxS1ZaMueM6MXbG/azdk+52+IoSptUer0mdflbXDGoIJOBBRm8slpfjCndh4q6Jl1F0k35/JmDyctI4Z0NashOBNSo5HC4ugGPqKeSEhyPR/i/G08jIyWJrz79MYeqGtwWSYkjKnTb3LjmnBG9KMhK5X/nbXZbFEVpEzVwxyciwvVTBvLhtjJ2HNIXY0r3oLxWPZW6K3kZKXz7wpFsPVjNFl3+H/eoUcnhUFUDPbPTSPKI26IoMUy/vHQevfV0DlQ2cOsTy3V7XiVi6EQuvklLSeLr5w/jg62HWaPeSkoMo/Hd4pcbzxhISpLwt6W73BZFUdqlvqmFhuZW3RW3G3PLtMEUZKUy95N9tOhOcHGNGpUcDlU10Dtbl74pJ/Lsst0nHZv3V/HorVPYdrCKOU+qYUmJDOVqVIp7bnZcwR9auM1tURQlKGU1duOSnlnquR1v9MlJ57JTCnlpxR7KnQ1qFCVW0Zdt3Z/UZA+Xju/HwaoGVuw64rY4ShRRo5LDoeoGemk8JSVEzh3Zmz/dNJn1eyv43CNLOVhZ77ZISjenrLqBZI/o4CmOyU5L5ovTB/POhgNsO6iu4EpsUlbtGJWy1agUj9wxYzg1jS084ezK5P/iTFFihfJa7wYmqou6M+P75zKkZxbzNhygRnefjFvUqORwWD2VlA5y6YR+PDFnKruP1HLdw0vZXVYb0LNJUUKhrLqRgqxUPLoEN66Zc/ZQMlKSeGjhDrdFUZSAHKlpID3FQ2aq7v4Wj4zpl8ul4/vx5IfFxzapUZRYxPt89lIDd7dGRJh9an8amlt4W4N2xy1qVAKMMRyqbtCd35QOc+7I3jx72zQq65u49uEl7KvQbTOVzlFWY+O6KfFNQVYqN54xkNfX7GWvbrOrxCBlNY30zFJdFM9895LR1DW18N9vbXJbFEUJiteopGOj7k/f3HTOGdGLlbuOsqJYl8HFI2pUwq7ZbWoxaglXQsbXE2ljaSVfnD6EhqYW/vrBDkqO1rotntINOVTdqDooQfjqucMA+Osi9VZSYo+y6kZd+hbnjOiTzVfOGcpLK0vYfUTHLEps4t1lWVeSxAcXjOlDXkYKP3ltPc0trW6Lo0QYNSpx3BKunkpKZ+mbm87Xzh9ORkoSTy/dxZEaDYCpdIyy6gZ66cAprvEaot/ffIiJRfk8s2wXZbr8RIkxjtTYpbhKfPOtC0fSNzeNN9bupdXorkxK7FFW00hKkpCboUtx44G05CSumFjIpv1VPLWk2G1xlAijRiXgYJUalZTw6ZGZyhenD6GltZWnlxRT26jB6JTQKatu1N2WEojzRvWiucXw5IfFbouiKCdQVt2gy98SgOy0ZH58+ThKy+tZsr3MbXEU5SQOV1ldJKKxJuOFcYW5XDC6Nw/8eysHq3STo3hCjUocd6/so0YlJUz65KZzy7QhHKlt5KUVJRh9+6eEQE1DM3VNLRo3IIHok5POuP65PL20mKr6JrfFURTAxpgsq9Hlb4nClRMLGdMvh3kb9nO4Sr0mldjicHUDvXJUF8UTIsJPrxhHQ3ML//vOZrfFUSKIGpU4blTSpSdKJBjaK4tZE/qx+UAVyzUYnRICuoV3YjJjVB+q6pv5fx/pLpFKbFDb2EJDc6t6TSYIIsLVpw4gOUn4x6oSXQanxBRlNY06N4tDhvXO5ktn25hu60rK3RZHiRBqVAJKy+vJTE0iLyPFbVGUOGHasJ6M6J3N3E/2sfNwjdviKDHO4RoNRpmIDOiRwXmjevP44h3UN7W4LY6iHDNwa0ylxCE3I4UrJ/Zn95Falmw77LY4inIM7/I3pfvgu5GR9wjEt2aOoGdWKr94c6Ou6ogT1KgElJbX0T8/Q9fsKhHDI8K1U4pI9nj43ktrVWEqbaKeSonLN2cM53B1Iy+u2OO2KIpCWY13C2/VRYnEqQPzGdsvh3kbD7D9ULXb4igKxhgOVzfq8rc4JSc9hf+8ZAwrdx3ljbWlboujRAA1KgF7y+sYkJ/hthhKnJGXkcKsCf1Ysesor63Z67Y4Sgzj3YFSYyolHmcMLWDK4B488v4OmnSLXcVljhm41TsgLgnmRSAizD5tAClJ9kVYS6u+CFPcpbK+mcaWVnqpLopbrptSxCkD8vjN3E26uVEcoEYljnsqKUqkmTy4BxOLrMKsblCFqQTGu628xjFJPESEb14wnL3ldby6Wo3PirscqdHlb4lKbnoKV07qz6rd5Ty+eIfb4igJjndcpJ5K8YvHI/z8ynHsr6zn4YXb3RZHCZNktwVwm/qmFspqGinqoUYlJfJ4RLj3qvF89sEl/OW9bXz/0jFui6TEIAcqG8hNTyY9JcltURQXuGB0H04ZkMf9727hyon9yUjV50Bxh30VdovnPrnqHZCITCrKo7y2kf+dt4WZY/owok8OQMC4KDefOairxVMSiMPqNRm3+OuTiUV5PLJoB9efPpCBBZkuSaWES8J7Ku0trwOgf366y5Io8cqmfVVMHpTPo4t28OcF29oMXKckJqXldQzooT+kiYqI8JPLx7Kvop7HPlAPAcU9Ssvr6J2TRlqyGjYTERHhV9dMIDM1ie++tE6XwSmusa/Czs8K83R+Fu/MmlCIR4TfvPWp26IoYZDwRqVSr1EpTz2VlOhx8bh+eATmbdzvtihKDGLjuunAKZE5c1hPLh3fj4fe386Bynq3xVESlNKKOvrrJC6h6ZOTzi+uGs+aPeX8VY3cikscf+mv87N4Jy8jhTtmDGfuJ/tZur3MbXGUTpLwRqW9R63SGqDL35QokpeRwjkjerOupII9R2rdFkeJMTSumwLww8vG0NTSyn+/vcltUZQEZV9Fveoihasm9efS8f34w7tb2Hqgym1xlARk79E68jNTyEpL+EgtCcHt5w1jQH4Gv3hzg3pIdlMS3qhUWl6HR6Bvrr6ZU6LLeSN7kZWWzNz1+zBGFaZiqapvorK+WSdyCoN7ZnH7ecN4ZdVe3tt00G1xlATDGENpeR2F6rmd8IgI9109gazUJL6ru8EpLlBaXqerSBKI9JQkfnTZWDbtr+LvS4vdFkfpBAlv/t1ZVktRj0xSkhLevqZEmbSUJC4a24fX15Ty6b5Kt8VRYoTScrvUaYAalRIS//hqfXPS6ZubxreeW82dF4wgNyMF0KC4SvSprGumtrFFY0wqAPTOSeOXsyfwredW0y83nfNH93FbJCWB2Ftex+CeWW6LoXQhl53Sj/NH9eY3b23inJG9jm0UoHQPEt6Ssv1gNcN7q9JSuobTBxfQOyeNt9bvp6ml1W1xlBigVOMGKD4kJ3m4ceogGptbeWbZLhqbVU8oXUNpheoi5USumFjIZaf049+bDh6LcaMo0cYYw96jdfqyLYF4dtlunlu+h+nDe5LkEe5+YY2Of7oZCW1Uam017DhczfDe2W6LoiQISR5h1vh+lNU08txy3QFOOR6MUgdPipe+uelcN6WIkqN1PLd8txqglS7Ba+DW3ZYULyLCr64+hey0ZJ5dtou6xha3RVISgMq6ZmoaW3RclIDkpqdwzWkDWL+3kt/P2+y2OEoHSGij0t7yOuqbWhneR41KStcxul8OQ3tl8cC/t1JZ3+S2OIrLlJbXkewReuekuS2KEkNMGJDH1acOYPOBKp78cCeHqhrcFkmJc0or7FJc9VRSfCnISuWmqQOpqGvi5VUlGhNSiTol5XZDG91EKTEZ3z+PL0wbxCOLdvDKqhK3xVFCJKGNStsPVQOop5LSpYgIl00o5EhNIw8v3B7ydc8u233SoXR/9hytozA/nSSPuC2KEmNMHVrAjVMHUnK0jln/9wEvryzRgLlK1Cg5Uktqkode2WrgVk5kUM8sZk0oZOO+ShZvO+y2OEqc492ZWw3cicvPrxzPtGEF/ODlT1i564jb4ighkOBGpRoAjamkdDkDemRw9an9eXzxzmNLDpTEZOuBKkaoYVsJwsSifL4xYwSFeenc89JaLv/jB7y6uoTaxma3RVPijG0HqxnWO0sN3EpAzhrek/H9c3lnw36KD9e4LY4Sx+wqs55KgwoyXZZEcYuXVpRw0di+5KQnc8vjy/nDvC1ui6S0Q0IblbYdrCY/M4WCrFS3RVESkO9eMhoD3PfPjW6LorhEc0srOw7VMKqv7nChBKdfXjqvf/Ns/nTTadQ3tfCdF9Zy+q/+zRV//IBvP7eaB97dwjMf7VLvRSUsth2q1nAASlBEhGsnF9EjM5XnP97N4WpdkqtEh80HquiVnabzswQnMzWZOWcNIdkjPL54B1sOVLktktIGCW1U2lBawZh+OYjoWzml6ynqkcldF47krfX7eXNtqdviKC6w60gtjS2tjFSjktIOHo9w5aT+LLhnBi/cPo3Zp/Znz9E63lhbygPzt/Lbtzbxwse7eXHFHt2lSekw9U0t7D5Sy0g1KiltkJ6SxE1nDKK2sYW7n1+jy3GVqLD1QBWj+qouUqBndhpfPXcYHo9w818/Yv3eCrdFUoKQ7LYAblHf1MKn+yr5yjnD3BZFSWC+dt4w5m08wI9e/YRJRfkM6qmuvonEVuetiw6elFDxeIQzh/XkzGE9mdA/jyM1jew4XMP2Q9VsO1TDf/5jHWCXDUwdUsDEojy+eNYQd4VWYp7th6oxBkb2UQN3otOex2P//AyunNSfV1fv5Y/zt/Kdi0d1kWRKItDaath6sJobTh/otihKjNArO42vnjOMF1fs4XOPLOWhL0zhvFG93RZL8SNhPZU27qukqcVw6sA8t0VREpjkJA9/vuk0PCLc9rcVVNTqbnCJxNYDulmA0nlEhJ7ZaUwdUsCNUwfxo1lj+PbMkVwyvh+1jS28vKqE38/bzEsr9qhHgdIm2w5aXTRCPZWUEDh9cA+unVzEHxdsZdGWQ26Lo8QRe8vrqG1s0bAAygn0zknjlmmDyUlPYc6Ty/n2c6t55qNdboul+JCwnkprdpcDcOrAHu4KoiQ8AwsyefDzk/nSkx8z56nlPPHFqfTQdeQJwZaD1RT1yCArLWFVsRIiocRLEhH65aXTLy+d80b2YsfhGt7ZsJ/v/WMd9/97C589rejYbjo3nzko2iIr3YitB6pJ8ghDeqm3rNI+IsKvrp7A+r0V3P3CGv717XMozNOdupTw8cbNGd1PDdzKieRmpHD7ecN44eM9vLG2lJKjtVw7pYj0lCS3RVNIYE+lNXvK6ZdrB9+K4gbPLtt97NhVVssNpxfxSUkFs//yIR8X6/aZicDaPeWMK8x1WwwlDhERhvfO5o7zh/O50wdSWdfMgwu3MW/DfppaWt0WT4kxPtlbwfDeWaQl6+BcCY2M1CQe/MJkGppa+MYzq6hvanFbJCUO2LTfGpVG6FJcJQDpKUncMn0wM8f0YdXucq7802LWlZS7LZZCghqVWlsNS3eUMWWIeikpscO4/nl85ZyhtBrD9Q8v5ZbHl/GPlSXsPFxDqy5diTv2VdSx+0gtZw7r6bYoShwjIkwamM/dF43k1IE9WLjlEH9asI0VAQzXvoZu76HEP80trazcdZQzhha4LYrSzRjeO5vf3zCJ1bvLueeltTpWUcJm2c4jjOyTTV5GituiKDGKR4SLxvblS2cNoaq+mWseXMLv522msVlfmLlJQq65+GRvBYeqGrhwTB+3RVGUExjcM4t37j6Pp5YU8/elu/juS2sByEpNoiArlX556QwqyGJMvxxdMtXNWbbDTurP1Imc0gVkpiZz3ZQiJhXl8eqavVz/yFK+OH0I37tktOqSBOfTfVVUNzRzxlA1cCsd59IJhfxw1hh+89YmBhVk8v1Lx7gtktJNaWppZUXxEa6bUuS2KEo3YGTfHO6+eBS/fHMjf1qwjXkbDnDf1RP0BYlLJORIcv6nB/AIzBitRiUl9shKS+abF4zgjvOHs3FfJRtLK9m4r5L3txxi/d5KPi4+imADqg7plcn0YT0REbfFVjrIsp1l5KQnM1aXvyldyMi+Odx14Uh2ldXy9NJi3t14gP+4eBRXTCp0WzTFJZbtLAPUwK10ntvPG8auI7U8tHA7qUke7r5opI5LlA6zrqSC2sYWpqsHtxIieRkp/P6GScya0I+fvb6eGx5ZymcnD+CHs8bSOyfNbfESioQzKhljmLfxAJMH9aBAgyErMYzHI0wYkMeEAXaHwmeX7cYYQ2l5PRv2VbBy11Fu/usypg7pwQ9mjWHKYJ0QdBeMMSzedpgzhhSQ5NGBt9K1pCUnce9V47lyUiE/fnU997y0lt++vYkJ/fOYMlh/GxONJdvLGNwzk765GmNS6Rwiwn2zJ9DY3Mr/zd9KydE6fnX1BDJSNUaXEjof7XAM3GpUUkLEd5n+7ecN573NB3l9dSlzP9nHxeP6cebQAr4wbbCLEiYOCWdUWrHrKJv2V3Hf1RPcFkVROoyIMKBHBgN6ZHDB6D6IwJ8XbOPah5ZyxcRCvn/pGAYW6O49sc7ynUfYc6SOuy8c5bYoSgIzZXABb911Lh9sPcwTH+5k4eaDvLf5IMN6ZTFlcA/G989zW0QlyhyubmDRlkN8+ZyhbouidDMCxVz7n2snMrBHJvf/ewsrdx3hR5eN5eJxfdVrSWkXYwxvrCllUlGevthQOkVqsodLxvfjtEH5vLm2lDfXlrKy+Ajj+ucyeZDGUY42CWdUevLDneRlpHDt5AFui6IoYZGS5OHmMwdx7eQiHlm0g0cXbWfexgN85ZyhfGPGcHLSNchhrPLSyhKy05KZdUo/t0VREhwR4bxRvTlvVG8efG8bq3aXs3LXEV5aWcIba0vZcrCKOWcNYVRf3YknHnl9TSnNrUZjmCgRweMR7rpoJFOH9uDHr67n9r+vZFxhLrefN4xLxvdTzyUlKGv2lLP5QBX/dY2+9FfCo09OOl8+eyif7K1g7if7+OyDS7hqUn++NXMEI7tgLBPI4H7zmYOiXq/bJJRRaeWuo7y1fj9fP384makJ1XQljslKS+Y/Lh7FTWcM5Hdvb+ahhdt58eM9fO38YVxzWpGuKY4xSsvr+Oe6UmZPGqB6SIkp8jNTmTmmDzNG96b4cA0rdx3l5ZUlPLtsN+eP6s1Xzx3KOSN6qddBnNDY3MozH+1iUlGeGg2ViHLW8F68+53zeG1NKX95bxt3v7CG7LRkLj+lkGunFDF1SA/VI8oJ/P2jXWSkJHHVpP5ui6LEASLCxKJ8RvfN4WB1A08vKebNdaVcMLoPV0ws5MKxfXWHwQgT1RmNiFwK/B+QBDxmjPmt33lxzl8G1AJzjDGroiFLZX0T3395HYW56XxjxvBoVKEorlKYl8EfPncqc84ewq/nfsqv527iv9/ezLRhBUwZXMCkojzWlVSQl5FCesqJbwvjxYIejs5p79pIYIzhvn9uxBi4c+aISBevKCET6E2aF48Iw3pnM6x3NpdO6Mezy3bx9NJd3PL4cop6ZHD5KYWcP7o34wpzyc9MDVpevOiVSBJL46LHFu9gx+EaHv/i6dEoXklAAumBr5wzlOKyGlbtKufV1Xt5YcUeBhZkcOXE/lwxsT9jC3PUwOQCsaSLlu88wiur9nLbuUPVy16JKGkpSXz/0jHcdu4wnli8k5dXlbBg00EABhZkMLJPDr2z08jPSqEgM5UeWan0yEwlPzOF/IwU8jJTyMtIIS35ZC9LYwxHa5s4UFnPwaoGDlbWU1HXxLqSClKTPfTKTqNvblrAa+ORqBmVRCQJ+AtwMVACfCwibxhjNvpkmwWMdI4zgYecz4iyt7yObzyziuLDNTz1pTNUYSlxzcSifJ6/fTrbDlbx8qq9vLfpIH9esJVWczxPWrKHvIwU8h1lebi6gaIeGQzumcXQXln0yEzpdoO8cHROiNeGRWur4ffvbuat9fv53iWjNfaV0i0oyErlzpkjue28Ycz9ZB9vrCnl8cU7eWTRDgB6ZafSJyed5tZWctJTyE1PJic9hZz0ZFbtPkqfnDT65KSTmuxxuSXuE0vjorfX7+f+d7fwmXF9uXBs30gXryjH8IgwrFc2w3plc9Wk/mworWB/ZT2PLNrBgwu3M7x3FueP6sO0YQWMH5BHYW46Ht3AIqrEki7afqiau59fzYD8DL5zscaZVKJDQVYq371kNP9x8ShW7yln6fbDbNpfxfZDNWworeBoTRONLa1Br89MTSI/I4XcjBQam1upbmjmaG0jTS0m6DVe+uamseVAFdOGFXDG0J5xGzMsmp5KZwDbjDE7AETkeWA24KuwZgN/M8YY4CMRyReRQmPMvnArP1hVz8rioyzaeojXVpdiMDz0hSmcM7JXuEUrSlRpy4Ogo2UM7JHJrdOH0NDUwv7KesrrmqiobaKi7vixt7yej4uPnnB9TnoyQ3tlMaRnFkN6ZjKkVxb9ctPJdQxROWkpJCcJyUlCiscTKwPATuscYEgI13aKsuoG/v3pAZ5dvoe1e8q56YyB3HG+eksq3Yu05CSuOa2Ia04roqK2ibUl5Xy6r5Kdh2s4WNXApv2V7Kuop7q+Ge8Q6xlHD3nEelIO7plJUY8MctJTyExNoqXV0NDcyvq9FTS3GppbWp1PQ9+8dDJTkshKSyYnPZncjBR6ZKYce4PYI9O+TczNSCYlyRNruigYro6LahubWbz1MK+vLeVf6/Zx2qB8fnf9pHCLVZSQSU32cJoTMPfckb3ZUFrBhr2V/G1pMU98uNPmSfLQKzuV1GQPdU0tJHs8eASSPEL//AxSkjxkpSWRl5FCbrqd5OVm2BdkNi35+N8ZKaQkeTDGYAy0GkOrgZZWQ1VDE5V1zVTVN1FV30x5XRNHaxp5f8shahubqW1sob6pBUEYWJBJskfITEs6Xqejl+z/yeSmpxyTKTs9OdZ3dnVVFzW1tLJmTznvbjzA//toF5mpSTz95TM0JIASFQLNqwqy0jhreBpnDbd2AWMMjc2t1DS2UNfYQm1Ts/1sbKGuyabVOX9npSVTkJXK2MJcZozuTZ+cdPrm2hdo+VkpPL98D/VNLRyqaqC0oo5dZbW88PEenlpSDMCYfjlMHVLA0F5ZDCrIJDfDjomaWlqP1VnT2ExFXROLthxy6m2lvqmFwT0zSUv2kJZsx0c9Mh0HgcxU+3eG42WVab2rUpKky5wEotl7BwB7fP4v4WQLd6A8A4CwFdZjH+zk0UU7yEhJ4rJTCrn7opHqGaAkLGkpSQzumUWwTTU/O3kAe8vrKD5cQ3FZrfNZw+o9R/nnutITvJwC4RFITvLwtfOGcc9nRkdc/hAJR+eEcm2nmPvJPn76+gYGFWTyu+smcu3kolif+CpKm+RlphwL7u3FO2hrNYaahmaq6puZMrgHB6vq2Vtez+6yGnYfqeX9LYeorm+mprGFZI+QluzBAMkeITnJQ7JHSEnykF7XxL7yOluWU14oeASSPR4un1jI/Z87NQqtDwtXx0XLdhzh9r+vJCctmTsvGMEdM4aTlaaTOMUdstOSOXNoT84c2pPmllbGFOay9WAVu8tqKatppLG5le2HqmluMbQYQ0urM+lraKbkaDOV9XbS1dgc3Lugs2SkJJGZmnQsVEBpeR3Nra3UNLRQ6Rih2sM7mZtUlMdLXz8r4jKGiau6qPhwDdc/vBSPwKxTCvmB7lysuIyIkJaSRFpKEmSFfl2gZf7ZaclkpyXTKzuNsYW5AFw3pYhP9pbz0Y4jfLSjjFdX76W6IbRxTWqyh4yUJNJTPDS3ttLQbA1MNQ0tIZXhHRf1yk5lyQ8vDL1xHSSao4lAsyb/qWkoeRCR24HbnX+rRWRzRwTZBPyhIxecTC/gcHhFhI3bMrhdv8oQoP7Px4AMvnz3v+C7oZcTzMbVWcLROVHXRbuAD0LNfDIx9dwlWP2J3HY+303v/QPAAzeGnD3SuigYMTMu+p5zdAK3+0Ok0HbEFnHbjq2A3BHy9d1OF0F4+uhB5+ggsfq8qFwdo9vLFeo8LELztbDu11ZAfhRy9g7romgalUqAgT7/FwGlnciDMeZR4NFICxgqIrLCGONqJEu3ZXC7fpUhNuqPFRmCEI7OSQ3hWtd0kdv3PJHrT+S2u12/222PAt1+XBQv34m2I7bQdnQ5EdNF0PX6KFbvs8rVMVSujhGrcnmJZuTMj4GRIjJURFKBG4E3/PK8AdwqlmlARSTW6iqKkpCEo3NCuVZRFCUcdFykKEosoLpIUZSIEjVPJWNMs4jcCbyD3a7yCWPMBhH5unP+YWAudqvKbdjtKr8ULXkURYlvwtE5wa51oRmKosQpOi5SFCUWUF2kKEqkiWqERmPMXKxS8k172OdvA3wzmjJECNeW3vngtgxu1w8qQyzUD7EhQ0DC0TmBro0h3L7niVx/Irfd7frdbnvEiYNxUbx8J9qO2ELb0cV0c10Uq/dZ5eoYKlfHiFW5ABCrMxRFURRFURRFURRFURQldKIZU0lRFEVRFEVRFEVRFEWJU9So5IOIXCoim0Vkm4j8IMB5EZE/OufXicjkLq5/hohUiMga5/hZJOt36nhCRA6KyPog56N9D9qrvyvuwUAReU9EPhWRDSJyV4A8UbsPIdYf1fsgIukislxE1joy/CJAnqg+C4lCOHqnvWsjUPfnnTrXicgSEZnkc65YRD5xnr8VHa07xPqDPufhtj3E+r/nU/d6EWkRkQLnXFjtD0fXRqjt7dUfte8+hLqj+r0rbROOToolwtFvsUSoz7yITHV01HVdKV+ohNIOp++vETvueL+rZQyFEJ6rPBF5U46PnzQWUSeJVV0Uq7olVnVFrPb9WOzLIYyPYvf31xijh10CmARsB4ZhtxdfC4zzy3MZ8BYgwDRgWRfXPwP4Z5Tvw3nAZGB9kPNRuwch1t8V96AQmOz8nQNs6eJnIZT6o3ofnHZlO3+nAMuAaV35LCTCEY7eCeXaCNR9FtDD+XuW73cMFAO9otz2gM95uG3vTBnAlcCCCLa/U7o2Em0Psf5ofved0vORarsebX43ro6FurgdQZ/xWDlCfeadfAuwMXKuc1vuTn4f+cBGYJDzfx+35e5kO34E/Lfzd2/gCJDqtuzd7YhVXRSruiVWdUWs9v1Y7cu4PA8P51BPpeOcAWwzxuwwxjQCzwOz/fLMBv5mLB8B+SJS2IX1Rx1jzCJspwlGNO9BKPVHHWPMPmPMKufvKuBTYIBftqjdhxDrjypOu6qdf1Ocwz8AW1SfhQQhHL0Trs5o93pjzBJjzFHn34+Aoo42MJz6o3RtZ8u4CXiug3UEJQxdG5Hfivbqj+Z3H4aej4nfyTjH7bFQpHBbv0WKUJ/5bwEvAwe7UrgOEEo7bgZeMcbsBjDGxGJbQmmHAXJERIBsrK5r7lox44JY1UWxqltiVVfEat+Pyb7s9jw8HNSodJwBwB6f/0s4eSIfSp5o1g8w3XHDe0tExkeo7o4QzXsQKl12D0RkCHAa1lPHly65D23UD1G+DyKSJCJrsD887xpjXLkHcU44eifc+9/R67+CfTvixQDzRGSliNzegXo7Wn+g5zwSz17IZYhIJnApdiDmJdz2d1Y+N/pdpL/7UIjW9660jdtjoUgRrn6LFdpth4gMAK4BHiZ2CeX7GAX0EJGFjm65tcukC51Q2vFnYCxQCnwC3GWMae0a8eKKWNVFsapbYlVXxGrf7659OWZ/f5PdFiCGkABp/p4ZoeSJZv2rgMHGmGoRuQx4DRgZofpDJZr3IBS67B6ISDZ2Enm3MabS/3SASyJ6H9qpP+r3wRjTApwqIvnAqyIywRjju8bX7WchHghH74R7/0O+XkQuwA6MzvFJPtsYUyoifYB3RWST84YlkvUHe84j8ex1pIwrgQ+NMb5vj8Jtf2fl69J+F6Xvvj2i+b0rbeP2WChShKvfYoVQ2vEA8H1jTIt9oR6ThNKOZGAKcCGQASwVkY+MMVuiLVwHCKUdlwBrgJnAcKyO/CDAOE5pm1jVRbGqW2JVV8Rq3++ufTlmf3/VU+k4JcBAn/+LsJbJjuaJWv3GmErvkiRjzFwgRUR6Raj+UInmPWiXrroHIpKCNeg8Y4x5JUCWqN6H9urvymfBGFMOLMR6avji6rMQJ4Sjd8K9/yFdLyITgceA2caYMm+6MabU+TwIvIp1Je4I4ei8SDx7HSnjRvyWvkWg/Z2Vr8v6XRS/+zaJ8veutI3bY6FIEZZ+iyFCacfpwPMiUgxcBzwoIld3iXShE+pz9bYxpsYYcxhYBEzqIvlCJZR2fAm7lMcYY7YBO4ExXSRfPBGruihWdUus6opY7fvdtS/H7u+viYHATrFwYK2kO4ChHA/YNd4vz+WcGBxreRfX3w8Q5+8zgN3e/yN8L4YQPEBY1O5BiPVH/R44bfsb8EAbeaL5LIRSf1TvAzYgXb7zdwbwAXBFVz8L8X6Eo3dCuTYCdQ8CtgFn+aVnATk+fy8BLo1C2wM+5+G2vSP3D8jDrm/PimT7nWvb0nVR+d47UH/UvvsQ6o7a965Hu9+Lq2OhLm5HwGc8lo6OPvPAU8RmoO5Qvo+xwHwnbyawHpjgtuydaMdDwL3O332BvYSxsUGiHrGqi2JVt8SqrojVvh/LfRmX5+GdPXT5m4MxpllE7gTewUaEf8IYs0FEvu6cfxgbKf8yrKKoxVowu7L+64A7RKQZqANuNM4TFilE5Dnszju9RKQE+Dk2SHPU70GI9Uf9HgBnA7cAnzgxhcDuADDIR45o3odQ6o/2fSgEnhaRJKxH44vGmH92VX9IFMLRO8GujXDdPwN6Yt9mATQbY07H/ri+6qQlA88aY96OQtuDPedhtb0D9YONPzDPGFPjc3nY7e+srg33e+9A/VH77sPQ8xFpuxIct8dCkSJM/RYzdEBPxTShtMMY86mIvA2sA1qBx8yJS+5dJ8Tv4z7gKRH5BDvx+76x3hdKB4hVXRSruiVWdUWs9v1Y7ctuz8PDwfsmUFEURVEURVEURVEURVFCRmMqKYqiKIqiKIqiKIqiKB1GjUqKoiiKoiiKoiiKoihKh1GjkqIoiqIoiqIoiqIoitJh1KikKIqiKIqiKIqiKIqidBg1KimKoiiKoiiKoiiKoigdRo1KcYqIzBERIyJzunMdXU2k2iQiQ5xynoqMZIrStcRi/xaRYhEpdqHemLsX/ojIQhEJeztXEbnXaeuM8KVSlOjiPKsL3ZYjEYmUPhaRp5zvcUj4UilK7NNFc7QZTh33+qVHZKwQLSI5f3JrzJioqFEpBhCRKU4H+ijI+Zud80ZEhgY4nyEi9SJSKyJp0ZdYiQbdYeKqdF9EJElEbhOR90XkiIg0ichBEVknIo+JyFVuy6h0T2J9kKrENiLyrPPbd0cIed918l7dBaIpMYpOFpVYQsdX8YE6BIRHstsCKACsBo4Cp4tIrjGm0u/8TMAA4vz9uN/5s4E04F1jTEO0hY1zXgU+Ava5LYiiRAoRSQL+CVwKlAP/AkqAAmA4cDMwBnjDJRGV8LkVyHRbCEXpBI8CNwG3AQ8Fy+R4slyI/X3+p5M8FqiNsnxKYC50WwBFcRsdX0WcvVi9XuG2IErHUKNSDGCMaXXct68Bzgfe9MsyE1gITCSwUWmm8zk/elImBsaYClSRKfHHTdgBz1rgfOc5P4aIZAJnuiGYEhmMMbvdlkFROoMxZqGIbAFOE5HJxphVQbJ+Ffty7UljTLNz7aauklM5EWPMdrdlUJQYQMdXEcQY0wSoXu+G6PK32MFrEJrpm+i8mRvqnH8fuCDAtW0alUTkAmd5QpWIVIrIv0RkbJC8hSLyF8e1uFFEDonIKyIypSONEZEiEfmziOwQkQYRKRORN0RkaojXZzv1f+iX7l3qZ0TkFr9z33DSv+yXXiAivxGRT0WkTkQqRGS+iHwmQL1Bl6CJyCUi8qGI1Djura+JyJj24gE47pTPi8hhR/YVInKFX56FwJPOv0/6LHfUOANKJDjL+XzKf8ADYIypNca8F+ziUHVIW8ug2ulbRSLyRxHZ6vSRIyKyXER+GkrjxC4RbnD6+GCfdG//3OOcP+AstRkdpJwRIvKSiBx1+vkSEbk8FBl8yvia087b/NK/7KSftEzZaWu9iGT4pZ8pIv8Qkf2OPtwjIo+ISP8A9Qa89yKSJjZOklcX7xSRXznpbcajEZHrHNlqne/keREZ4HN+iFPn+c7/vnoraLmKEoC/Op+3BTop1htgDtZr+zGf9JOeNRHJEZGfish6R19Vich2EXlBAoxlROQM59xep4/sE5F5InJDgLwd7pMikioiPxORzU75Tznn80TkeyKyQERK5PiY6w0RmRbqjRM7vjEicrFf+i+d9JOMP478JxmixY5z5oodrzQ49+13IpIfIG/AJWhOux5w2lQvIptE5D9EZJi0s7TE0Z+fONcdEJFHRSTP5/wMR+cMBgb76Zyg5SpKFOmS8ZWTN1NEfigia8SOUapFZKmI3BShtvjXt9TRA1l+6YucPve4X/o4J/1vfunJYudoHzltrBWR1SJyp4h4/PIGXYImIqNE5GXxG6NJO+FDnPv2OxHZ7bRnm4h8X0TEJ8+9wE7n3y/66ZaA5Sonop5KscMC59PfnfhCn/MVwGdFZJwxZiOAiOQCp2NdLgO93bsCmA28BTwMjAMuA6Y65Rz2ZhQbr2kx0N+p7zlgIHA9cLmIXGuM+SftICKTgXlY1893gFeAXsDVwGIRucYYM7etMowx1SKyHDhTRHKMMVXOKe9SP++9+bvPZScZ18ROMBcCQ4APgLeBLOe+vC0iXzPG/JV2EJHPAc8CDcCLWPf7s4Cl2LcTwRgMLAd2OLIWAJ8DXheRi3x+aJ7CfoezgdeBNT5llLcnn6K0Q5nzOaoT14asQzqDiJyO1RMFwCKsvsh06rkXuK+d6/8T+C2wBLjKGHPESb/UKSsF6/25DSgCPovVZxf4ekSIyEhsf+7ptHUNMAJ4zfk/VLz650KOT5ThuH7KAKZj9RLOhGky8IExps5Hni851zdg3eb3ACOx3hpXisi09ryTnAHTy8DlwFbgz9j7MQcY3047vgFc5dT9PvZN6+eASSJyqrPUuhz4hVPeYOdvL8XtlK8ovjwN/Bdws4jcY4zxX9J2GTAAu8x/50lXOzjP/Nsc/31+DGjGjmVmYMcBK33ye5fctWCf9a1AH+y46hvY33tv3s72yZeBqVg98hpw0Ekf67R5EXbJzFFgELbfzRKRK40xbwdrqw/zgR9gdc67PulenTNMRIYYY4qddkwA+mLHHccQkZ9h+/AR7HKeg1gP+e8Cl4nI9ADhGU5ARNKx48fJ2NAOzwB5wI+Bc9tpx/8Al2D19TzsS9TbsHrY25ZiR8a7nf8f8Ll+TTvlK0o06JLxlWPYXQCchp3vPYF1DrkEeFZExhtjftLZRgRhPjAN23ffduTw9bzyn7MGmod5x2CXAJuxc6l6bP/+k1PWLbSDiIwBPsSOFf8FrAOGYcOWtDWnTMHqk/7Y+9yMnY/+Fkjn+LhlIZAP3IWd173mU8aa9uRTAGOMHjFyYNeRtgK9fdKeAaqwBsDx2Ld0d/qcv9JJe8WvrDlOejNwod+53zjn/tMv/R0n/cd+6Wc55ZQB2QHqmOOTloydvNVj3UB9y+nvtHEfkBbC/filU/7lfrI3YxXrHp90D3AY2O5XxkLnnt7ol56PVRJ1QN922pSDHew1AJP8yvmtk98AQ3zSh/ik/9zvmkuc9LlBvrM5ge6HHnp09sAOQhqdvvB3rGFlcDvXdEaHLLQ/K22WN8cnLRX7ZsgANwe4ZqDf/8VAsfO3BzsgMdhJW7pPvh5Onz0MjPMrYzxQDazyS5/nlHWXX/psn748J1DbAsi9CzshE5+0UuxAqwW4L0D5P/VJG+V8X9uAAX5lz3TKeLW9e48dqBnspDXVJz0f615ugIV+19zrpFcCp/ide9Y5d0Oo37seeoR6AC8E62fYly0GuM4v/YRnGDjFSXs1QBkeoIfP/+OAJqwRZXyA/EU+f3e6T2InP70ClJ8XJL3I0RefhnjfMrBjro990rIdeb167Ss+5+5y0m7xSbvASVsC5PuVP8c5d79fejGOPvZJ+6mT9zk//TcQOOSce8rvmqec9N3AIJ/0ZEd3GeCM9urWQw83DrpufPVUkPR0rMGnFTjVJ32Gk/9ev/wLCfH3muMxfX/nk+adw3h1y3Cfc686aQN90u510v4EJPmkJ2HDuRhgtk/6kCB6Yr6Tfodf+iyCjNEcPWGwRqcMn/Q+2Jdi5UBKe3XrEdqhy99ii/ew8QJ8l7hdgH2D3WyM2YCdqPgukWsvntLzxhj/c486n2d4E0SkCPgM9kf9f3wzG2OWYAcIBVhl2RaXYwPT/ckY875fOaVO2f0ILcCj7xt/fP5eiZ1EFomI983AqVgPA1/r+CTssoyXjTHP+8lSDvwcq4yvbUeO2dhJ2DPGGH+vpF/RtifRLiePb93vYO/zGQGvUJQIY4xZDXwBOOB8vgwUi12W+qqIXNnG5SHpkE5yJfZH/A1jzLMB5N4T6CLnbfg/gDux3jfXG2PqfbLciu2zPzeOV6dPmRuw3ganicg4p7wi4GKsgevPfvlfx3rqdIQFQG/sBBennkJH5lWcrNPgRB1+B/bt2l3GmL1+8izAeklcKSI57cjxRefzJ8aYRp8yymnHAwz4ozHmE780r+eV6i4lGnj1yld9E0WkEPv2/gDWuBQKdf4JxphWY8xRn6Q7sIaL+xy94J+/xC9vZ/vkT00Aj05jTEWQ9BKsrhgjIoMCtu7E/HVYr6zJItLDST7PkfcBrDEnkM5Z4JP2befzNkc/+Jb/FPYl3OfbkwWrc1qBHxpnluaUsYcTvYoC8Uvj4+llbNysJ51/VecoMUlXjK9EpKdT9gpjjP8crR74Pnb+eHNYjTmZJViDtb/+aMbOobz/4yxjmwFs9Y7dnLQ7gf3Ad4wxLT5ytwD3YI04beoWERmIne9uAx7xPWeMeQv4dzvt+Lbx8QQ3xhzE/pbkAQHDISgdR5e/xRbzsR1rJvCiz0Tkfp88C4GLRcRjjGnluFEpWIdaESDNO1Hr4ZN2mvP5gbFB0vxZgFVopwF/C3Dey3Tnc7CzPtWfkc7nWNp2VwQ7SKrjuMLKw7pU/w8nLhfcwvH74DtI8sqSF0SW3j6ytIX33iz2P2HsMr01WEUaiDW+StSHPT7yKUrUMca8KCKvYg3V52Cf63OwbsBXO2vg5/hOBBxC1SGdwRs3pCPLyzKwunI68H3/AZaDt29NCtL3vcboscBGfPp4kP66ECduUIgswL6JvBDrpeBr/B8C/IfPst6ZWM+p5QHkP18Cx6Hrg33LNwqfpTwBOA07wVsS4NxJ+syPaH7vihKIBcB24GwRGWuM+dRJ/xJ2vPpUkPGJLxuxBpCbnOXvr2Of9RW+hlWHjuifcPrk8pOzW0TkbKzn0HSnjFS/LAOwL6HaYwF2HDID6y0wE+uFtQj7wnKmU18S1uC02c84Nt3Jf72IXB+g/FSgt4j0NMaUBTjvDccwHOtFXhwgi+ocJS7pgvHVVKx+MUHGNCnOZ3vzmQ5hjKkXkSXABT59fybWK3KpiBzAjnMexc7P8rEep15GYV/4bwV+4hPCyJe6EOQ+1flc6sx9/VkMXBTk2gpjzLYA6apbIowalWILf8+cQIaShcAN2Lfsu7BvwvcaYzYHKbPcP8EY0+x07CSf5Dznc1+Qcrzp+UHOe+npfAYalPiS3c55jDGNIrIYuEhE+mAHPUnAfGPMpyJSir1XDzmfhhPvlVeWi52js7J4782BIOeDpUNwL6ZmNFC+0sU4E7J5zuGdYFyLXZt/K3Yy8prfZeUBygmkQzpDvvO5t61MfmRjBy+V2CW7gfD2/YBBf/3Kgvb7+P6QpbP46vL7nc8SY8wWEZkP/Cd2cvoxdjneXOetvBev/N9rp55QdNcRv7K9tKW3ILDu8pYT7veuKCdhjDEi8hh2+cdXgXucGElfwS9AdxtltIjITOBnwHXAfzunqkTkaawHTbWTlu98hqJ/wumTAfWHiFyD9Uiqx8ZC2g7UYA3BM7CG7LRA1wZgPjZkwIVYPX4hsMx58TUfuMGJpZSF1QvP+F3fEzsn+Dltk83xGDL+5DqfnRkrgeocpRsT5fGVV/9MdY5gtDu36gTzsfPRCxxdchrwa+fcAqyjgxDY69or90ja1i1uzcNAdUvE0EltDOG4/W4HRvi4+pVjgx16ec/5nOkcQvClbx3Bu2NBvyDnC/3ytVfObGOMtHH8os1SjrMA28aZWIXVgA3UBvZeXCB2J6VzgQ2OS6O/LHe1I8uX2pHBG5iyb5DzwdIVJaYxxrQYY17kuDfkzLbyh0Ar2J0+ApzLD5BW7nwOCHAuGIewwS1TgPecQN/+ePv+pHb6/tN++YP15WB6MSDOUt/NWMNRGnaC6NXTi7HxFy4i8DIUX3ny2pG/vWV5lUBBkO9D9ZYSizyJ9Zi5VURSsTppGPBekLfNJ2GMOWqM+Y4xZiDHA2lvwi7DeMgna7nzGYr+6XSfDOCd4OU+rC443RhztTHmHmPMz4wx92L1R0dYjvV4vMhZKjOJ4zrHq1/a0zlH22mbGGN2tSGDjpUUxSHC4yuv/rm/nf4ZaIfwcPHVHxdgbQe+uqUXVt94X+6/53OtV+5X25F7aDsyqG7pBqhRKfbwdtSLsG+p3vd19TPGbMJ6DXmNSr7XhIPXcHVOkAmIV1EF2mHOl4+cz/Z2+QgV3zf+M4EPzfHYKfOxcZ7uwL59878PkZLl2L3xPyEi2Rx3ywwX77IbtZorXY13d8WAvskdwBuvZGCAc4GMP94+OqsjlRgbg+BS7Jv1f4uI/1LSjvZ9X/0XqP/N6Ih8DvOxb9/uwBrU5oPdXtiRz6vTvHl9iaTu8nB8y2NfTtJnYdACx97MKkqnMcYcwMYn8u4Y6/U2fDTYNe2Ut80Y8zh2PFWNjZHopSP6J9JjG7C7mm00x5f5AcfikHSofzreiIuw8UFuweeFo2OM281xndPKiRM/sO3rISLt7QrZlgyV2J1uB4jIkABZIq1zVN8o3YFIjK+WY/ttJPVPqHyMNep49Yc3hhscH7tcht2de505MU7cJqzxfpqzC1xn8Y7Rpjv60Z9I6Radh4WBGpViD69F+DtYg4n/Dz/YJXDnYgNrQwSMSsYGhnwXG+/jbt9zInImNvjbUaz7Zlu8jvW2+qaIXBYog4hMd7akDIWVWIU0G7tMxLet3r9/6Hye8ObNGLMCu33wZ0Xky0FkOcVZWtcWr2Ot7Z93gn/78hPaXxIYKl6X8nYDcypKRxCRm0Tk4kA/xiLSj+MTt0VhVuWNHXLCsjMRuRC4KUD+N7G7c1wlIiedF5GgHgTGmA+wy1oNME9EfGMePYnVGz8XkZMCvIqIR0Rm+JTl1X9Dsd4Mvnln07F4Sl68+iiQfloATMBuHV6G3b7Wlz9jvTXu99mMwFemVBEJZXDpjX/3K8frw3t9HnaXpkihukuJJN6A8PdgDUuHaX/sAYCIDA1iGOmBXUrmG8D7IewSiJ96g/b7lVXk82+k+qQvxcBIEenvU45gl4mcJE8I+OqcGmCZ37nzsRO/tcaYI37Xer0p/uorj49cWSIyzT89AH/Dzi1+Iz4BVBzv+7tDaUSIlGFjPGVEsExF6TBdMb5yVmE8A5wuIj8N9PJfRIaLSHseP52puwUr+whsaJPFxpgG59xOrB67C8jk5HlYM3bXt0Lgj4H6q4gUBtK/fuXswc59RwBf87v+UoLHU+ooR7FjSh3LdAKNqRR7LMA+0Kf4/O/Pe9gJ2lBODrYYDl/HLi37nYh8BhtAbiBWibQCXzI2sGxQjDFNIvJZbKyTfzkB3tYAtU5ZU7Gu7IVOWpsYY1pF5H2Ov12c73Nut4hsxwaGbCHwDk03Y+/h4yLybewgqxy7Ze9E7MRuOnZXvWAyVIrIN4D/BywRkRex3mJnYV0+38cO1gIFj+sIS7H35G4RKeD4GuE/GWPaW3aoKG1xJvZHf78Tp2ynkz4Uu2NjBtZ4+o8w63kSG3Pkh44BdiM2UOMs7KTwhJ0WjY2bdj02BsGzIvI17BvzdGzgxgtp43fKGLPMiZ/yLjBXRK42xrxrjCkTkeucOj9y4gBswPbRQdg+39Opx8s3sX3wAUf/rcUOYK7BGr/a2sElEO859fUBNvnp6fnYbXZ7A//wXx5jjNnkGMKfADaIyNvYDQlSHPnPxS4DHNOODH8DbsR6da0XkTecMq7F6vfRhK+3vO25HnhFROZiJ+67jDF/j0DZSuIxD6ujvAbhP5uTg2wHYxLwqoisBNYDpdh+Nhv77HtjLGGM2ej8tj8MrBaR17EBZXtiPSurcLy0I9gnfbnfp+6XsUars7EGpc7oHO/4qA/wtt89m4/dPMA33zGMMfNF5AfYeFZbnX68E+ttORg7xlmM1SVt8T9YQ+CNwGgRmYeNh3IDdmJ6NZHTOVOBt0VkETY0wlpjzJsRKFtROkJXja/uxC7n/SVwi1PXAaA/drw0FTs33Bm0hM4zHxt2oA8n64/52Lh3BDgHdpnvJOwc80oRWYCNY9cH256zgR9jx4tt8U3sHPVBx2lhHXY+eS32/s4mTN1ibAy6ZcC5IvIMVse3YHcoXhdO2QmBMUaPGDuwkxmDHaBIgPMjnPMG+EuQMuY45+cEOW+AhQHSB2Df3u3CrvU/jA0sN7UjdWCVxW+xg7parNv5VqxS/QKQ3IH78S2nngogye/cI865ZW1cnwP8COv1VI2d8OwE/gXcDmSF2KZZ2F2UarHW7NexA8h/Otfk++Qd4qQ9FUSmhTihFvzSL8VObKt9vuMhbj+TenTvA2vQ/SbWyLIZ68rciDWOznX6pMfvms7qkPFOmVXOc7wQOyFpq28NAh50+mUj9i30MuDHfvmKgeIA10/ABsOtBy73SR+C9TDY6pyrxLpj/x24OkA5IxwdVY59078UOyhs8160cd9XEkBPYyei3j5+RxvXnwI8hdXHDcARrE59BJjplzeYTknHDkJ3OmUUA/+F1fUGeM0v/71O+owAZQXUa1hX8V9jl740BXs29NAj1AM7yfD+Bo5uI98Jzxr2hdGvsZOP/c4zX4Ld4W1WkDKmY7cBP+jon1LgbeC6AHnD7pN+eeZgX7zVcNwj65S2+mEbZQl23GiA7/md6+9zPwPeByffOcCLzj1odMpbA/wBG/vJN28xgfVxPvBHp4wGrM69B2skNMADfvmfIshYB7v02AD3+qVnYceqJVhvs6DjLT30iOZB146vUrHGpSXYOVEDdmnrfKwnYE+fvMH6Trt6KUC9p/joj6l+525y0puAnCDXC3ZZ7nxHZzZiDUuLsfOzgT55hwTrz9g51yucPEb7rnPN1X75A+oo59y9BNCx2HHgm9hxaGtb35MeJx7i3EBFUTqBE0NkB5BmjOlQMF9FURS3EJGLsR4hvzXG/LC9/IqiKOEgIrdhY2N93RjziNvyKIoSHzheRTcDY0zw3dCVKKMxlRQlBEQk3z8OlBMv4CdYL4tXXBFMURSlDYLER+mJ9SSFEGPVKIqihEIQnTMQG8etGevdrSiKEjJOLMyTXt47MTs/h930QA1KLqIxlRQlNKYBLzjxAYqxcQamYXd+24N1o1QURYk1/uDEt1qCXcpShF3KWwA8YoxZ3tbFiqIoHeRlZ6cn70YrQ7DxWDKBH5rIxQFVFCVxSAX2iMh72CW1zdhwCxdjl9N900XZFNDlb4oSCs6OCr/CBpTrjTXIlmDfuP3a2G2QFUVRYgoRuQG4Azv4ysfGltqADTj8mNFBgKIoEcQJfn4LNghvHjZ+3GpswHX16lYUpcM44UYeAGZiX45lYuPQLcIu41/tnnQKqFFJURRFURRFURRFURRF6QQaU0lRFEVRFEVRFEVRFEXpMGpUUhRFURRFURRFURRFUTqMGpUURVEURVEURVEURVGUDqNGJUVRFEVRFEVRFEVRFKXDqFFJURRFURRFURRFURRF6TBqVFIURVEURVEURVEURVE6zP8HxRgAAhJmSGMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x1800 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Distplot \n",
    "plt.figure(figsize=(20,25))\n",
    "plt_num=1\n",
    "for plot in df :\n",
    "    if plt_num<=8 :\n",
    "        ax= plt.subplot(2,4,plt_num)\n",
    "        sns.distplot(df[plot])\n",
    "        plt.xlabel(plot,fontsize=20)\n",
    "    plt_num+=1\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "DATA is skewed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Features are not Normally Distributed and have different Scale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1800 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,25))\n",
    "plt_num=1\n",
    "for plot in df :\n",
    "    if plt_num<=8 :\n",
    "        ax= plt.subplot(2,4,plt_num)\n",
    "        sns.boxplot(data = df[plot],orient='v')\n",
    "        plt.xlabel(plot,fontsize=20)\n",
    "    plt_num+=1\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " and also have outliers as per Boxplots "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Data is shewed in some segments \n",
    "#Checking correlarion and heat map \n",
    "df_corr = df.corr()\n",
    "plt.figure(figsize=[18,20])\n",
    "sns.heatmap(df_corr,annot=True)\n",
    "plt.title('Corr- Matrix')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rings             1.000000\n",
       "Shell weight      0.627574\n",
       "Diameter          0.574660\n",
       "Height            0.557467\n",
       "Length            0.556720\n",
       "Whole weight      0.540390\n",
       "Viscera weight    0.503819\n",
       "Shucked weight    0.420884\n",
       "Sex              -0.034627\n",
       "Name: Rings, dtype: float64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_corr['Rings'].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sex               2.0000\n",
      "Length            0.1650\n",
      "Diameter          0.1300\n",
      "Height            0.0500\n",
      "Whole weight      0.7115\n",
      "Shucked weight    0.3160\n",
      "Viscera weight    0.1595\n",
      "Shell weight      0.1990\n",
      "Rings             3.0000\n",
      "Age               3.0000\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# finding using IQR\n",
    "\n",
    "Q1 = df.quantile(0.25)\n",
    "Q3 = df.quantile(0.75)\n",
    "IQR = Q3 - Q1\n",
    "print(IQR)\n",
    "\n",
    "df_iqr = df[~((df < (Q1 - 1.5 * IQR)) |(df > (Q3 + 1.5 * IQR))).any(axis=1)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sex               0\n",
       "Length            0\n",
       "Diameter          0\n",
       "Height            0\n",
       "Whole weight      0\n",
       "Shucked weight    0\n",
       "Viscera weight    0\n",
       "Shell weight      0\n",
       "Rings             0\n",
       "Age               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_iqr.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3781, 10)"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_iqr.reset_index()\n",
    "df_iqr.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Splitting data in X&Y also scale the data using standard scaler "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Scale the data using standard scaler \n",
    "# Setting X and y axis and splitting the data into train and test respectively.\n",
    "x = df_iqr.drop(['Rings','Age'],axis =1) \n",
    "y = df_iqr['Rings']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "scaler = StandardScaler()\n",
    "x_scaled = scaler.fit_transform(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sex              -0.097270\n",
       "Length           -0.495017\n",
       "Diameter         -0.481941\n",
       "Height           -0.152640\n",
       "Whole weight      0.345472\n",
       "Shucked weight    0.455297\n",
       "Viscera weight    0.454848\n",
       "Shell weight      0.342490\n",
       "dtype: float64"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.skew(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finding Best Random state"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "88"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import r2_score\n",
    "my_acc = 0\n",
    "rs = 0\n",
    "for i in range (1,200) :\n",
    "    x_train,x_test,y_train,y_test = train_test_split(x_scaled,y,test_size=.15,random_state=i)   \n",
    "    lr = LinearRegression()\n",
    "    lr.fit(x_train,y_train)\n",
    "    y_pred =lr.predict(x_test)\n",
    "    acc= r2_score(y_test,y_pred)\n",
    "    if acc>my_acc :\n",
    "        my_acc =acc\n",
    "        rs=i  \n",
    "rs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Thus SPlitting data \n",
    "\n",
    "x_train,x_test,y_train,y_test = train_test_split(x_scaled,y,test_size=0.3,random_state=88)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R2_SCORE: 0.5121556922015172\n",
      "Mean Absolute Error_LR: 1.2988407999632041\n",
      "Mean Squared Error_LR: 2.8212986181605957\n",
      "Root Mean Squared Error_LR: 1.679672175801158\n"
     ]
    }
   ],
   "source": [
    "#Using  Regression models \n",
    "# LinearRegression\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import mean_absolute_error,mean_squared_error\n",
    "lr = LinearRegression()\n",
    "lr.fit(x_train, y_train)\n",
    "lr_y_pred = lr.predict(x_test)\n",
    "R2_lr_score =r2_score(y_test,lr_y_pred)\n",
    "\n",
    "print('R2_SCORE:',R2_lr_score)\n",
    "print('Mean Absolute Error_LR:',mean_absolute_error(y_test,lr_y_pred))\n",
    "print('Mean Squared Error_LR:', mean_squared_error(y_test,lr_y_pred))\n",
    "print('Root Mean Squared Error_LR:', np.sqrt(mean_squared_error(y_test,lr_y_pred)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R2_SCORE: 0.5023891895993067\n",
      "Mean Absolute Error_XGB: 1.301641061337509\n",
      "Mean Squared Error_XGB: 2.877780204304798\n",
      "Root Mean Squared Error_XGB: 1.6964021351981369\n"
     ]
    }
   ],
   "source": [
    "#Using  XGB models \n",
    "import xgboost as  xgb\n",
    "xgb = xgb.XGBRegressor()\n",
    "xgb.fit(x_train,y_train)\n",
    "xgb_y_pred = xgb.predict(x_test)\n",
    "R2_xgb_score =r2_score(y_test,xgb_y_pred)\n",
    "R2_xgb_score\n",
    "print('R2_SCORE:',R2_xgb_score)\n",
    "print('Mean Absolute Error_XGB:',mean_absolute_error(y_test,xgb_y_pred))\n",
    "print('Mean Squared Error_XGB:', mean_squared_error(y_test,xgb_y_pred))\n",
    "print('Root Mean Squared Error_XGB:', np.sqrt(mean_squared_error(y_test,xgb_y_pred)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R2_SCORE_DT: 0.14898492038180655\n",
      "Mean Absolute Error_DT: 1.6334801762114537\n",
      "Mean Squared Error_DT: 4.921585903083701\n",
      "Root Mean Squared Error_DT: 2.2184647626418816\n"
     ]
    }
   ],
   "source": [
    "#DecisionTreeRegressor\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "dt = DecisionTreeRegressor()\n",
    "dt.fit(x_train,y_train)\n",
    "y_pred_dt =dt.predict(x_test)\n",
    "R2_DT_score =r2_score(y_test,y_pred_dt)\n",
    "print('R2_SCORE_DT:',R2_DT_score)\n",
    "print('Mean Absolute Error_DT:',mean_absolute_error(y_test,y_pred_dt))\n",
    "print('Mean Squared Error_DT:', mean_squared_error(y_test,y_pred_dt))\n",
    "print('Root Mean Squared Error_DT:', np.sqrt(mean_squared_error(y_test,y_pred_dt)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R2_SCORE: 0.5490273267386866\n",
      "Mean Absolute Error_LR: 1.205298543851099\n",
      "Mean Squared Error_LR: 2.6080627765075883\n",
      "Root Mean Squared Error_LR: 1.614949775227573\n"
     ]
    }
   ],
   "source": [
    "# USING SVM Regression\n",
    "from sklearn.svm import SVR\n",
    "svr = SVR()\n",
    "svr.fit(x_train, y_train)\n",
    "svr_y_pred = svr.predict(x_test)\n",
    "R2_svr_score =r2_score(y_test,svr_y_pred)\n",
    "R2_svr_score\n",
    "print('R2_SCORE:',R2_svr_score)\n",
    "print('Mean Absolute Error_LR:',mean_absolute_error(y_test,svr_y_pred))\n",
    "print('Mean Squared Error_LR:', mean_squared_error(y_test,svr_y_pred))\n",
    "print('Root Mean Squared Error_LR:', np.sqrt(mean_squared_error(y_test,svr_y_pred)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " CV score LR 0.414299992563834\n",
      "\n",
      " CV score XGB 0.4154840305527784\n",
      "\n",
      " CV score SVR 0.4527379866034903\n",
      "\n",
      " CV score DTR -0.03497507526640733\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_score \n",
    "#Cross Validation \n",
    "cvLR =cross_val_score(lr,x,y,cv=5)\n",
    "cvXGB =cross_val_score(xgb,x,y,cv=5)\n",
    "cvSVR=cross_val_score(svr,x,y,cv=5)\n",
    "cvDTR=cross_val_score(dt,x,y,cv=5)\n",
    "print ('\\n CV score LR',cvLR.mean())\n",
    "print ('\\n CV score XGB',cvXGB.mean())\n",
    "print ('\\n CV score SVR',cvSVR.mean())\n",
    "print ('\\n CV score DTR',cvDTR.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "HyperParameter tuniing usog Grid Search"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=5, estimator=SVR(),\n",
       "             param_grid={'C': [1, 1.1, 1.2, 1.21, 1.23, 1.25, 2, 27],\n",
       "                         'coef0': [0.01, 10, 0.5], 'gamma': ('auto', 'scale')})"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "param ={'C' :[1,1.1,1.2,1.21,1.23,1.25,2,27] ,'coef0' : [0.01,10,0.5],'gamma' : ('auto','scale')}\n",
    "GSV = GridSearchCV(SVR(),param,cv=5)\n",
    "GSV.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Best Parameters "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['C', 'cache_size', 'coef0', 'degree', 'epsilon', 'gamma', 'kernel', 'max_iter', 'shrinking', 'tol', 'verbose'])"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SVR().get_params().keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'C': 2, 'coef0': 0.01, 'gamma': 'auto'}"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GSV.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R2_SCORE_TUNED in precent : 54.90273267386866\n",
      "Mean Absolute Error_SVR_TUNED : 1.2016130010341444\n",
      "Mean Squared Error_SVR_TUNED : 2.5900558892783594\n",
      "Root Mean Squared Error_SVR_TUNED : 1.6093650578033436\n"
     ]
    }
   ],
   "source": [
    "#Using tuned parameters\n",
    "from sklearn.svm import SVR\n",
    "svr_t = SVR(C= 1.25,coef0= 0.01,gamma= 'auto')  #checking \n",
    "svr_t.fit(x_train, y_train)\n",
    "svr_t_y_pred = svr_t.predict(x_test)\n",
    "R2_svr_t_score =r2_score(y_test,svr_t_y_pred)\n",
    "R2_svr_t_score\n",
    "print('R2_SCORE_TUNED in precent :',R2_svr_score*100)\n",
    "print('Mean Absolute Error_SVR_TUNED :',mean_absolute_error(y_test,svr_t_y_pred))\n",
    "print('Mean Squared Error_SVR_TUNED :', mean_squared_error(y_test,svr_t_y_pred))\n",
    "print('Root Mean Squared Error_SVR_TUNED :', np.sqrt(mean_squared_error(y_test,svr_t_y_pred)))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### EFFICIANCY ACHIEVED \n",
    "\n",
    "R2_SCORE_TUNED in precent : 54.90273267386866\n",
    "\n",
    "Mean Absolute Error_SVR_TUNED : 1.2016130010341444\n",
    "\n",
    "Mean Squared Error_SVR_TUNED : 2.5900558892783594\n",
    "\n",
    "Root Mean Squared Error_SVR_TUNED : 1.6093650578033436\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10.57191706  9.36683091  9.96383837  7.50145894  9.51000519  7.76589023\n",
      " 12.15987715 11.1318293   9.93030862  6.44729254  8.24111492  6.38350934\n",
      "  6.70976514 11.06319844  8.88286385 10.38997506  8.13314598  9.25094628\n",
      " 11.20742927  5.3737943   8.56787529  8.53104302  6.93032813  9.47941805\n",
      " 11.62416889 10.68638399 10.17985229 11.0763073  10.42628983  9.51474493\n",
      " 11.10409127 10.47116222  8.83738752 10.62256618 10.43740777 10.72689863\n",
      " 10.66420758 10.3855662   7.52580363  7.32332225 10.50622644  9.78251009\n",
      "  7.95704723 11.0020763  11.1918049  10.29362984 10.69113014  9.71978668\n",
      "  9.74236307  7.04217259]\n",
      "[10.53514772  9.34328444  9.89849727  7.51278336  9.52903283  7.77526472\n",
      " 12.12755631 11.11420147  9.92850826  6.45027708  8.24597364  6.38725283\n",
      "  6.72940086 11.07891551  8.83777811 10.37652981  8.15095514  9.19405025\n",
      " 11.16138352  5.38335531  8.56465814  8.52596106  6.93947097  9.46429218\n",
      " 11.57405372 10.62383525 10.28824818 11.05558536 10.44009311  9.50455971\n",
      " 11.0433487  10.49803039  8.83835575 10.59874856 10.4388551  10.74127264\n",
      " 10.61896597 10.35404195  7.51629022  7.33608175 10.51368318  9.70445628\n",
      "  7.9479926  11.03257938 11.21423943 10.34913732 10.66354013  9.62413488\n",
      "  9.67678804  7.04745328]\n",
      "[13  8 10  7 10  8 12 15 11  6  9  6  8 12  9 11  9 15 14  6  9  9 12  7\n",
      " 14 10  9 13 11 12 13 12  8  8 14 12 12  9  8  6 13 10 10 12 15 11  9  9\n",
      " 13  7]\n"
     ]
    }
   ],
   "source": [
    "#Checking efficiancy in random \n",
    "\n",
    "print(svr_t_y_pred[:50],)\n",
    "print(svr_y_pred[:50],)\n",
    "print(y_test[:50].values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Saving the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Abalone.pk']"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Dumping the model \n",
    "import joblib as jl\n",
    "jl.dump(svr_t,'Abalone.pk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Loading the model \n",
    "abln_reg = jl.load('Abalone.pk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Yabln_reg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.571917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9.366831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9.963838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.501459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9.510005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1130</th>\n",
       "      <td>9.634082</td>\n",
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       "    <tr>\n",
       "      <th>1131</th>\n",
       "      <td>11.044759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1132</th>\n",
       "      <td>9.488142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1133</th>\n",
       "      <td>10.577593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1134</th>\n",
       "      <td>8.444334</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1135 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Yabln_reg\n",
       "0     10.571917\n",
       "1      9.366831\n",
       "2      9.963838\n",
       "3      7.501459\n",
       "4      9.510005\n",
       "...         ...\n",
       "1130   9.634082\n",
       "1131  11.044759\n",
       "1132   9.488142\n",
       "1133  10.577593\n",
       "1134   8.444334\n",
       "\n",
       "[1135 rows x 1 columns]"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y_abln_reg = abln_reg.predict(x_test)\n",
    "df_abln_reg = pd.DataFrame({})\n",
    "\n",
    "df_abln_reg['Yabln_reg'] = Y_abln_reg\n",
    "df_abln_reg"
   ]
  }
 ],
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