06-02-Project HR.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Project HR\n",
    "\n",
    "Predict attrition of your valuable employees\n",
    "\n",
    "[IBM HR Analytics Employee Attrition & Performance](https://www.kaggle.com/pavansubhasht/ibm-hr-analytics-attrition-dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.16.5\n",
      "0.25.1\n",
      "3.7.4 (default, Aug 13 2019, 15:17:50) \n",
      "[Clang 4.0.1 (tags/RELEASE_401/final)]\n",
      "0.9.0\n"
     ]
    }
   ],
   "source": [
    "print(np.__version__)\n",
    "print(pd.__version__)\n",
    "import sys\n",
    "print(sys.version)\n",
    "print(sns.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Attrition</th>\n",
       "      <th>BusinessTravel</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>Department</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EducationField</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <th>...</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StandardHours</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1102</td>\n",
       "      <td>Sales</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>49</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>279</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>37</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>1373</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Other</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>33</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Frequently</td>\n",
       "      <td>1392</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>Life Sciences</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>80</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>27</td>\n",
       "      <td>No</td>\n",
       "      <td>Travel_Rarely</td>\n",
       "      <td>591</td>\n",
       "      <td>Research &amp; Development</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>Medical</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Age Attrition     BusinessTravel  DailyRate              Department  \\\n",
       "0   41       Yes      Travel_Rarely       1102                   Sales   \n",
       "1   49        No  Travel_Frequently        279  Research & Development   \n",
       "2   37       Yes      Travel_Rarely       1373  Research & Development   \n",
       "3   33        No  Travel_Frequently       1392  Research & Development   \n",
       "4   27        No      Travel_Rarely        591  Research & Development   \n",
       "\n",
       "   DistanceFromHome  Education EducationField  EmployeeCount  EmployeeNumber  \\\n",
       "0                 1          2  Life Sciences              1               1   \n",
       "1                 8          1  Life Sciences              1               2   \n",
       "2                 2          2          Other              1               4   \n",
       "3                 3          4  Life Sciences              1               5   \n",
       "4                 2          1        Medical              1               7   \n",
       "\n",
       "   ...  RelationshipSatisfaction StandardHours  StockOptionLevel  \\\n",
       "0  ...                         1            80                 0   \n",
       "1  ...                         4            80                 1   \n",
       "2  ...                         2            80                 0   \n",
       "3  ...                         3            80                 0   \n",
       "4  ...                         4            80                 1   \n",
       "\n",
       "   TotalWorkingYears  TrainingTimesLastYear WorkLifeBalance  YearsAtCompany  \\\n",
       "0                  8                      0               1               6   \n",
       "1                 10                      3               3              10   \n",
       "2                  7                      3               3               0   \n",
       "3                  8                      3               3               8   \n",
       "4                  6                      3               3               2   \n",
       "\n",
       "  YearsInCurrentRole  YearsSinceLastPromotion  YearsWithCurrManager  \n",
       "0                  4                        0                     5  \n",
       "1                  7                        1                     7  \n",
       "2                  0                        0                     0  \n",
       "3                  7                        3                     0  \n",
       "4                  2                        2                     2  \n",
       "\n",
       "[5 rows x 35 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"data//WA_Fn-UseC_-HR-Employee-Attrition.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A quick glance of the data shows the dependent or target variable **Attrition**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1470, 35)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1470 entries, 0 to 1469\n",
      "Data columns (total 35 columns):\n",
      "Age                         1470 non-null int64\n",
      "Attrition                   1470 non-null object\n",
      "BusinessTravel              1470 non-null object\n",
      "DailyRate                   1470 non-null int64\n",
      "Department                  1470 non-null object\n",
      "DistanceFromHome            1470 non-null int64\n",
      "Education                   1470 non-null int64\n",
      "EducationField              1470 non-null object\n",
      "EmployeeCount               1470 non-null int64\n",
      "EmployeeNumber              1470 non-null int64\n",
      "EnvironmentSatisfaction     1470 non-null int64\n",
      "Gender                      1470 non-null object\n",
      "HourlyRate                  1470 non-null int64\n",
      "JobInvolvement              1470 non-null int64\n",
      "JobLevel                    1470 non-null int64\n",
      "JobRole                     1470 non-null object\n",
      "JobSatisfaction             1470 non-null int64\n",
      "MaritalStatus               1470 non-null object\n",
      "MonthlyIncome               1470 non-null int64\n",
      "MonthlyRate                 1470 non-null int64\n",
      "NumCompaniesWorked          1470 non-null int64\n",
      "Over18                      1470 non-null object\n",
      "OverTime                    1470 non-null object\n",
      "PercentSalaryHike           1470 non-null int64\n",
      "PerformanceRating           1470 non-null int64\n",
      "RelationshipSatisfaction    1470 non-null int64\n",
      "StandardHours               1470 non-null int64\n",
      "StockOptionLevel            1470 non-null int64\n",
      "TotalWorkingYears           1470 non-null int64\n",
      "TrainingTimesLastYear       1470 non-null int64\n",
      "WorkLifeBalance             1470 non-null int64\n",
      "YearsAtCompany              1470 non-null int64\n",
      "YearsInCurrentRole          1470 non-null int64\n",
      "YearsSinceLastPromotion     1470 non-null int64\n",
      "YearsWithCurrManager        1470 non-null int64\n",
      "dtypes: int64(26), object(9)\n",
      "memory usage: 402.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Age                                      41\n",
       "Attrition                               Yes\n",
       "BusinessTravel                Travel_Rarely\n",
       "DailyRate                              1102\n",
       "Department                            Sales\n",
       "DistanceFromHome                          1\n",
       "Education                                 2\n",
       "EducationField                Life Sciences\n",
       "EmployeeCount                             1\n",
       "EmployeeNumber                            1\n",
       "EnvironmentSatisfaction                   2\n",
       "Gender                               Female\n",
       "HourlyRate                               94\n",
       "JobInvolvement                            3\n",
       "JobLevel                                  2\n",
       "JobRole                     Sales Executive\n",
       "JobSatisfaction                           4\n",
       "MaritalStatus                        Single\n",
       "MonthlyIncome                          5993\n",
       "MonthlyRate                           19479\n",
       "NumCompaniesWorked                        8\n",
       "Over18                                    Y\n",
       "OverTime                                Yes\n",
       "PercentSalaryHike                        11\n",
       "PerformanceRating                         3\n",
       "RelationshipSatisfaction                  1\n",
       "StandardHours                            80\n",
       "StockOptionLevel                          0\n",
       "TotalWorkingYears                         8\n",
       "TrainingTimesLastYear                     0\n",
       "WorkLifeBalance                           1\n",
       "YearsAtCompany                            6\n",
       "YearsInCurrentRole                        4\n",
       "YearsSinceLastPromotion                   0\n",
       "YearsWithCurrManager                      5\n",
       "Name: 0, dtype: object"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(df.iloc[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Age                         False\n",
       "Attrition                   False\n",
       "BusinessTravel              False\n",
       "DailyRate                   False\n",
       "Department                  False\n",
       "DistanceFromHome            False\n",
       "Education                   False\n",
       "EducationField              False\n",
       "EmployeeCount               False\n",
       "EmployeeNumber              False\n",
       "EnvironmentSatisfaction     False\n",
       "Gender                      False\n",
       "HourlyRate                  False\n",
       "JobInvolvement              False\n",
       "JobLevel                    False\n",
       "JobRole                     False\n",
       "JobSatisfaction             False\n",
       "MaritalStatus               False\n",
       "MonthlyIncome               False\n",
       "MonthlyRate                 False\n",
       "NumCompaniesWorked          False\n",
       "Over18                      False\n",
       "OverTime                    False\n",
       "PercentSalaryHike           False\n",
       "PerformanceRating           False\n",
       "RelationshipSatisfaction    False\n",
       "StandardHours               False\n",
       "StockOptionLevel            False\n",
       "TotalWorkingYears           False\n",
       "TrainingTimesLastYear       False\n",
       "WorkLifeBalance             False\n",
       "YearsAtCompany              False\n",
       "YearsInCurrentRole          False\n",
       "YearsSinceLastPromotion     False\n",
       "YearsWithCurrManager        False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EmployeeCount</th>\n",
       "      <th>EmployeeNumber</th>\n",
       "      <th>EnvironmentSatisfaction</th>\n",
       "      <th>HourlyRate</th>\n",
       "      <th>JobInvolvement</th>\n",
       "      <th>JobLevel</th>\n",
       "      <th>JobSatisfaction</th>\n",
       "      <th>MonthlyIncome</th>\n",
       "      <th>MonthlyRate</th>\n",
       "      <th>NumCompaniesWorked</th>\n",
       "      <th>PercentSalaryHike</th>\n",
       "      <th>PerformanceRating</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StandardHours</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "      <td>1,470.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>36.92</td>\n",
       "      <td>802.49</td>\n",
       "      <td>9.19</td>\n",
       "      <td>2.91</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1,024.87</td>\n",
       "      <td>2.72</td>\n",
       "      <td>65.89</td>\n",
       "      <td>2.73</td>\n",
       "      <td>2.06</td>\n",
       "      <td>2.73</td>\n",
       "      <td>6,502.93</td>\n",
       "      <td>14,313.10</td>\n",
       "      <td>2.69</td>\n",
       "      <td>15.21</td>\n",
       "      <td>3.15</td>\n",
       "      <td>2.71</td>\n",
       "      <td>80.00</td>\n",
       "      <td>0.79</td>\n",
       "      <td>11.28</td>\n",
       "      <td>2.80</td>\n",
       "      <td>2.76</td>\n",
       "      <td>7.01</td>\n",
       "      <td>4.23</td>\n",
       "      <td>2.19</td>\n",
       "      <td>4.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>9.14</td>\n",
       "      <td>403.51</td>\n",
       "      <td>8.11</td>\n",
       "      <td>1.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>602.02</td>\n",
       "      <td>1.09</td>\n",
       "      <td>20.33</td>\n",
       "      <td>0.71</td>\n",
       "      <td>1.11</td>\n",
       "      <td>1.10</td>\n",
       "      <td>4,707.96</td>\n",
       "      <td>7,117.79</td>\n",
       "      <td>2.50</td>\n",
       "      <td>3.66</td>\n",
       "      <td>0.36</td>\n",
       "      <td>1.08</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.85</td>\n",
       "      <td>7.78</td>\n",
       "      <td>1.29</td>\n",
       "      <td>0.71</td>\n",
       "      <td>6.13</td>\n",
       "      <td>3.62</td>\n",
       "      <td>3.22</td>\n",
       "      <td>3.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>18.00</td>\n",
       "      <td>102.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>30.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1,009.00</td>\n",
       "      <td>2,094.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>11.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>30.00</td>\n",
       "      <td>465.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>491.25</td>\n",
       "      <td>2.00</td>\n",
       "      <td>48.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2,911.00</td>\n",
       "      <td>8,047.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>12.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>36.00</td>\n",
       "      <td>802.00</td>\n",
       "      <td>7.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1,020.50</td>\n",
       "      <td>3.00</td>\n",
       "      <td>66.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>2.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>4,919.00</td>\n",
       "      <td>14,235.50</td>\n",
       "      <td>2.00</td>\n",
       "      <td>14.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>43.00</td>\n",
       "      <td>1,157.00</td>\n",
       "      <td>14.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1,555.75</td>\n",
       "      <td>4.00</td>\n",
       "      <td>83.75</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>8,379.00</td>\n",
       "      <td>20,461.50</td>\n",
       "      <td>4.00</td>\n",
       "      <td>18.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>15.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>9.00</td>\n",
       "      <td>7.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>7.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>60.00</td>\n",
       "      <td>1,499.00</td>\n",
       "      <td>29.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>2,068.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>5.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>19,999.00</td>\n",
       "      <td>26,999.00</td>\n",
       "      <td>9.00</td>\n",
       "      <td>25.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>6.00</td>\n",
       "      <td>4.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>18.00</td>\n",
       "      <td>15.00</td>\n",
       "      <td>17.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Age  DailyRate  DistanceFromHome  Education  EmployeeCount  EmployeeNumber  EnvironmentSatisfaction  HourlyRate  JobInvolvement  JobLevel  JobSatisfaction  MonthlyIncome  MonthlyRate  NumCompaniesWorked  PercentSalaryHike  PerformanceRating  RelationshipSatisfaction  StandardHours  StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  WorkLifeBalance  YearsAtCompany  YearsInCurrentRole  YearsSinceLastPromotion  YearsWithCurrManager\n",
       "count 1,470.00   1,470.00          1,470.00   1,470.00       1,470.00        1,470.00                 1,470.00    1,470.00        1,470.00  1,470.00         1,470.00       1,470.00     1,470.00            1,470.00           1,470.00           1,470.00                  1,470.00       1,470.00          1,470.00           1,470.00               1,470.00         1,470.00        1,470.00            1,470.00                 1,470.00              1,470.00\n",
       "mean     36.92     802.49              9.19       2.91           1.00        1,024.87                     2.72       65.89            2.73      2.06             2.73       6,502.93    14,313.10                2.69              15.21               3.15                      2.71          80.00              0.79              11.28                   2.80             2.76            7.01                4.23                     2.19                  4.12\n",
       "std       9.14     403.51              8.11       1.02           0.00          602.02                     1.09       20.33            0.71      1.11             1.10       4,707.96     7,117.79                2.50               3.66               0.36                      1.08           0.00              0.85               7.78                   1.29             0.71            6.13                3.62                     3.22                  3.57\n",
       "min      18.00     102.00              1.00       1.00           1.00            1.00                     1.00       30.00            1.00      1.00             1.00       1,009.00     2,094.00                0.00              11.00               3.00                      1.00          80.00              0.00               0.00                   0.00             1.00            0.00                0.00                     0.00                  0.00\n",
       "25%      30.00     465.00              2.00       2.00           1.00          491.25                     2.00       48.00            2.00      1.00             2.00       2,911.00     8,047.00                1.00              12.00               3.00                      2.00          80.00              0.00               6.00                   2.00             2.00            3.00                2.00                     0.00                  2.00\n",
       "50%      36.00     802.00              7.00       3.00           1.00        1,020.50                     3.00       66.00            3.00      2.00             3.00       4,919.00    14,235.50                2.00              14.00               3.00                      3.00          80.00              1.00              10.00                   3.00             3.00            5.00                3.00                     1.00                  3.00\n",
       "75%      43.00   1,157.00             14.00       4.00           1.00        1,555.75                     4.00       83.75            3.00      3.00             4.00       8,379.00    20,461.50                4.00              18.00               3.00                      4.00          80.00              1.00              15.00                   3.00             3.00            9.00                7.00                     3.00                  7.00\n",
       "max      60.00   1,499.00             29.00       5.00           1.00        2,068.00                     4.00      100.00            4.00      5.00             4.00      19,999.00    26,999.00                9.00              25.00               4.00                      4.00          80.00              3.00              40.00                   6.00             4.00           40.00               18.00                    15.00                 17.00"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.options.display.float_format = '{:,.2f}'.format\n",
    "pd.set_option('display.max_columns', 500)\n",
    "pd.set_option('display.width', 1000)\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A couple of observations that stood out from reviewing the basic statistical information as printed by describe:\n",
    "* **EmployeeCount**: All the values are 1. Little information here. Can drop this column.\n",
    "* **EmployeeNumber**: Sequential count. Little information here. Can drop this column,\n",
    "* **StandardHours**: All the values are 80. Little information here. Can drop this column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_col = list(df.describe().columns)\n",
    "col_categorical = list(set(df.columns).difference(num_col))\n",
    "remove_list = ['EmployeeCount', 'EmployeeNumber', 'StandardHours']\n",
    "col_numerical = [e for e in num_col if e not in remove_list]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternative method to identify categorical columns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Attrition', 'BusinessTravel', 'Department', 'EducationField', 'Gender', 'JobRole', 'MaritalStatus', 'Over18', 'OverTime']\n"
     ]
    }
   ],
   "source": [
    "categorical_col = []\n",
    "for k, v in df.iteritems():\n",
    "    if v.dtype == 'object':\n",
    "        categorical_col.append(k)\n",
    "print(categorical_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "26\n",
      "23\n",
      "9\n"
     ]
    }
   ],
   "source": [
    "print(len(num_col))\n",
    "print(len(col_numerical))\n",
    "print(len(col_categorical))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>DailyRate</th>\n",
       "      <th>DistanceFromHome</th>\n",
       "      <th>Education</th>\n",
       "      <th>EnvironmentSatisfaction</th>\n",
       "      <th>HourlyRate</th>\n",
       "      <th>JobInvolvement</th>\n",
       "      <th>JobLevel</th>\n",
       "      <th>JobSatisfaction</th>\n",
       "      <th>MonthlyIncome</th>\n",
       "      <th>MonthlyRate</th>\n",
       "      <th>NumCompaniesWorked</th>\n",
       "      <th>PercentSalaryHike</th>\n",
       "      <th>PerformanceRating</th>\n",
       "      <th>RelationshipSatisfaction</th>\n",
       "      <th>StockOptionLevel</th>\n",
       "      <th>TotalWorkingYears</th>\n",
       "      <th>TrainingTimesLastYear</th>\n",
       "      <th>WorkLifeBalance</th>\n",
       "      <th>YearsAtCompany</th>\n",
       "      <th>YearsInCurrentRole</th>\n",
       "      <th>YearsSinceLastPromotion</th>\n",
       "      <th>YearsWithCurrManager</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Age</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.51</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.68</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.31</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>DailyRate</td>\n",
       "      <td>0.01</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>DistanceFromHome</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Education</td>\n",
       "      <td>0.21</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.09</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.13</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.15</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>EnvironmentSatisfaction</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.05</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>HourlyRate</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.05</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.07</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.05</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>JobInvolvement</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.04</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>JobLevel</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.78</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>JobSatisfaction</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.07</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>MonthlyIncome</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.09</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.95</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.15</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.77</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>MonthlyRate</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>NumCompaniesWorked</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.02</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.24</td>\n",
       "      <td>-0.07</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>-0.09</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>PercentSalaryHike</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.77</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>PerformanceRating</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.77</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>RelationshipSatisfaction</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.05</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.05</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>StockOptionLevel</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.05</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>TotalWorkingYears</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.15</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.78</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.24</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.01</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>TrainingTimesLastYear</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.07</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>WorkLifeBalance</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.04</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>YearsAtCompany</td>\n",
       "      <td>0.31</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.53</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.51</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>-0.12</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>YearsInCurrentRole</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.39</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.36</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.09</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.46</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.76</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.55</td>\n",
       "      <td>0.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>YearsSinceLastPromotion</td>\n",
       "      <td>0.22</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.35</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.40</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.55</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>YearsWithCurrManager</td>\n",
       "      <td>0.20</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.02</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.38</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.34</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>-0.11</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0.02</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.46</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.51</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Age  DailyRate  DistanceFromHome  Education  EnvironmentSatisfaction  HourlyRate  JobInvolvement  JobLevel  JobSatisfaction  MonthlyIncome  MonthlyRate  NumCompaniesWorked  PercentSalaryHike  PerformanceRating  RelationshipSatisfaction  StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  WorkLifeBalance  YearsAtCompany  YearsInCurrentRole  YearsSinceLastPromotion  YearsWithCurrManager\n",
       "Age                       1.00       0.01             -0.00       0.21                     0.01        0.02            0.03      0.51            -0.00           0.50         0.03                0.30               0.00               0.00                      0.05              0.04               0.68                  -0.02            -0.02            0.31                0.21                     0.22                  0.20\n",
       "DailyRate                 0.01       1.00             -0.00      -0.02                     0.02        0.02            0.05      0.00             0.03           0.01        -0.03                0.04               0.02               0.00                      0.01              0.04               0.01                   0.00            -0.04           -0.03                0.01                    -0.03                 -0.03\n",
       "DistanceFromHome         -0.00      -0.00              1.00       0.02                    -0.02        0.03            0.01      0.01            -0.00          -0.02         0.03               -0.03               0.04               0.03                      0.01              0.04               0.00                  -0.04            -0.03            0.01                0.02                     0.01                  0.01\n",
       "Education                 0.21      -0.02              0.02       1.00                    -0.03        0.02            0.04      0.10            -0.01           0.09        -0.03                0.13              -0.01              -0.02                     -0.01              0.02               0.15                  -0.03             0.01            0.07                0.06                     0.05                  0.07\n",
       "EnvironmentSatisfaction   0.01       0.02             -0.02      -0.03                     1.00       -0.05           -0.01      0.00            -0.01          -0.01         0.04                0.01              -0.03              -0.03                      0.01              0.00              -0.00                  -0.02             0.03            0.00                0.02                     0.02                 -0.00\n",
       "HourlyRate                0.02       0.02              0.03       0.02                    -0.05        1.00            0.04     -0.03            -0.07          -0.02        -0.02                0.02              -0.01              -0.00                      0.00              0.05              -0.00                  -0.01            -0.00           -0.02               -0.02                    -0.03                 -0.02\n",
       "JobInvolvement            0.03       0.05              0.01       0.04                    -0.01        0.04            1.00     -0.01            -0.02          -0.02        -0.02                0.02              -0.02              -0.03                      0.03              0.02              -0.01                  -0.02            -0.01           -0.02                0.01                    -0.02                  0.03\n",
       "JobLevel                  0.51       0.00              0.01       0.10                     0.00       -0.03           -0.01      1.00            -0.00           0.95         0.04                0.14              -0.03              -0.02                      0.02              0.01               0.78                  -0.02             0.04            0.53                0.39                     0.35                  0.38\n",
       "JobSatisfaction          -0.00       0.03             -0.00      -0.01                    -0.01       -0.07           -0.02     -0.00             1.00          -0.01         0.00               -0.06               0.02               0.00                     -0.01              0.01              -0.02                  -0.01            -0.02           -0.00               -0.00                    -0.02                 -0.03\n",
       "MonthlyIncome             0.50       0.01             -0.02       0.09                    -0.01       -0.02           -0.02      0.95            -0.01           1.00         0.03                0.15              -0.03              -0.02                      0.03              0.01               0.77                  -0.02             0.03            0.51                0.36                     0.34                  0.34\n",
       "MonthlyRate               0.03      -0.03              0.03      -0.03                     0.04       -0.02           -0.02      0.04             0.00           0.03         1.00                0.02              -0.01              -0.01                     -0.00             -0.03               0.03                   0.00             0.01           -0.02               -0.01                     0.00                 -0.04\n",
       "NumCompaniesWorked        0.30       0.04             -0.03       0.13                     0.01        0.02            0.02      0.14            -0.06           0.15         0.02                1.00              -0.01              -0.01                      0.05              0.03               0.24                  -0.07            -0.01           -0.12               -0.09                    -0.04                 -0.11\n",
       "PercentSalaryHike         0.00       0.02              0.04      -0.01                    -0.03       -0.01           -0.02     -0.03             0.02          -0.03        -0.01               -0.01               1.00               0.77                     -0.04              0.01              -0.02                  -0.01            -0.00           -0.04               -0.00                    -0.02                 -0.01\n",
       "PerformanceRating         0.00       0.00              0.03      -0.02                    -0.03       -0.00           -0.03     -0.02             0.00          -0.02        -0.01               -0.01               0.77               1.00                     -0.03              0.00               0.01                  -0.02             0.00            0.00                0.03                     0.02                  0.02\n",
       "RelationshipSatisfaction  0.05       0.01              0.01      -0.01                     0.01        0.00            0.03      0.02            -0.01           0.03        -0.00                0.05              -0.04              -0.03                      1.00             -0.05               0.02                   0.00             0.02            0.02               -0.02                     0.03                 -0.00\n",
       "StockOptionLevel          0.04       0.04              0.04       0.02                     0.00        0.05            0.02      0.01             0.01           0.01        -0.03                0.03               0.01               0.00                     -0.05              1.00               0.01                   0.01             0.00            0.02                0.05                     0.01                  0.02\n",
       "TotalWorkingYears         0.68       0.01              0.00       0.15                    -0.00       -0.00           -0.01      0.78            -0.02           0.77         0.03                0.24              -0.02               0.01                      0.02              0.01               1.00                  -0.04             0.00            0.63                0.46                     0.40                  0.46\n",
       "TrainingTimesLastYear    -0.02       0.00             -0.04      -0.03                    -0.02       -0.01           -0.02     -0.02            -0.01          -0.02         0.00               -0.07              -0.01              -0.02                      0.00              0.01              -0.04                   1.00             0.03            0.00               -0.01                    -0.00                 -0.00\n",
       "WorkLifeBalance          -0.02      -0.04             -0.03       0.01                     0.03       -0.00           -0.01      0.04            -0.02           0.03         0.01               -0.01              -0.00               0.00                      0.02              0.00               0.00                   0.03             1.00            0.01                0.05                     0.01                  0.00\n",
       "YearsAtCompany            0.31      -0.03              0.01       0.07                     0.00       -0.02           -0.02      0.53            -0.00           0.51        -0.02               -0.12              -0.04               0.00                      0.02              0.02               0.63                   0.00             0.01            1.00                0.76                     0.62                  0.77\n",
       "YearsInCurrentRole        0.21       0.01              0.02       0.06                     0.02       -0.02            0.01      0.39            -0.00           0.36        -0.01               -0.09              -0.00               0.03                     -0.02              0.05               0.46                  -0.01             0.05            0.76                1.00                     0.55                  0.71\n",
       "YearsSinceLastPromotion   0.22      -0.03              0.01       0.05                     0.02       -0.03           -0.02      0.35            -0.02           0.34         0.00               -0.04              -0.02               0.02                      0.03              0.01               0.40                  -0.00             0.01            0.62                0.55                     1.00                  0.51\n",
       "YearsWithCurrManager      0.20      -0.03              0.01       0.07                    -0.00       -0.02            0.03      0.38            -0.03           0.34        -0.04               -0.11              -0.01               0.02                     -0.00              0.02               0.46                  -0.00             0.00            0.77                0.71                     0.51                  1.00"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[col_numerical].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BWk16crxi2Vu3t2fXNs2x5NxvFzTnuZZldcqYW5bFtHgxzp75A4Bd2/xpoz3mhIecyOgfz565gJWNpcj+Eub1qpF4M4YkbX/+j98JKr2kPzcqaqJpI0Dqk2fEnL5G6rOUfM+pT8V6H3A/y/ji3N7j1Mo2vvhHZ3zxN2ZZxhd/H7vEs0dPKAgVso2Nzr8i+60s2e/diObeTc2V34mxD0m+n4hp6RKK5H4xprufhzFddfu6XA2/wOOERzxJfMTV8At87FBXkdzvM1lOz5evgiAmMt8jkiSZArbAELQTmZIkqSRJ+l6SpEuSJPlLkhQgSVJ37bYGkiSFSpL0myRJByRJsi6o7DFx97GyyDx4W1qUJSbuHjFx97CyMM983VzzulIsrMyJjozNzBkZi4WVuW4Za3Oi78YAkJaWRnJSMiVLmymW8WUsrcyJiozJ+D46MhZLawvdMtYWREfF6pbR/o5lzEsTp729Mi72PqXLlsr3zGaWpYmPvJ/xfXzUA8wsS+davklPR/4MOZfvuV6HobYXC2tzYrLmjorF3FpPbm0ZTe5HOXK37ujA1YvXSHmu3EmquZU50Xczs8dGxeWoc3OrbNkTM7PXrl8T35Bf2Bb8M17TlmcMCvKb2qIsadFxGd+nxd6jULYBDEDRVnaU812DxfLZqC3Nc2wvKJbW5kRHZt4SGRMZg6VVtr7FyoLoLP1PTFQMltp2Vda8NHEx2r4l5j5lFOhbAApZlCE1S72nxtyjkEXOei/WxpbyO3/AcoUHam17UluW1XlvWsw91Hr+z/KDobZzgGJWpUiOfJDxfXLUA4pZ5fz/rj2wNX3Dv6L5zF6Ez9mk972PcnlvfrCwyuyrQdMvWmbrFy2tzInK0p8naftzzf6R5b16jgX5yZCzm1uVJTYya1u/h3mOtp5ZJi0tnUeJjzArpRmYW1e0YuOBNaza/jV1G3+iaG7d42hczuNoljIv9lGz0mYULlKYAaP6sO6rnxTLm5VkVgY5PvO8S064j2Sme96lMrdBVdaaIiO9KPLFEtQf1Qcg/dY10q5fpJjHeop5rCft2jnk2LuKZbeytiDqbuaxKDoyBqts57lW1hY652b6ygD06OtKyOGI/AubjSFmL2ZdiuSoLH1y9AOKWefsk2sObI17+Fc0ntWLY3OUv4VcHzPLUtnGF/cxs8z9eNKkpwNXQs4rEe2VzCxLkZAle0LUfUq8JHujXLJXqFsNtVEh7v8bo+ddb1/JbGO6hDcY073peFD43yMmMt8vXYD9sixfAx5IkvQp0BWoDHwCDAWaAUiSZASsBLrLstwA2AAsyu0HS5I0XJKkM5Iknflxk3duxfJM3xUikiSh78IRSVLmtrLcPit7JAk9ZRS+4iVX+vJnz6a3TH4FejV9/7251WeDLnZUqFOV4LV79W5XmsG2F/2Vnq3Iy3NXrV6FsR6jWDhF2ecGvSrXq8pcPHuZHg796d9+GJ+N6YexiXH+BM3uNXI/Dj3O7fb9udtjBE9OnsV84RRlsr2G/1rvBeY12vqjkBP823Ygd7qO5MmJs1gumpzrW5XqLA22neeaK2e5iz8fYrPdJI4v3kqDsV1evDlnQYWa0Ovk1ns+Iud2LFCu7b9/2V+jrQP3Yx/QtXFvPnMewcp53zP3u1kUNVXoFso85kaWGTFlMN7rfHnyuGCu9tIr+3+5So2qrA1P1szm6ZYVmHQfBYWLIpWxQmVenkdew3i0aBjqap+gqlJTsZivV+8535e9zKgJQ0hNTcPPN+Ct5nsZw8z+en3y5Z8P4WM3iVNeW6n/oj8vaG8w3vm0ix3l61Ql5B0ZX7zJsbC+NntotuzFzUvSa8UofKesVu5c7A3Om16M6Y5ocxfkOdd7LT09f74KgJjIfL/0Bl48HXyr9ns7wFeW5XRZlqOBYO326kBt4KAkSecAD6A8uZBlea0syw1lWW44dMBLF53KEyuLskTHZl5pGRN7D4uyZbSvZ14BExOneV0pMVGxWNlk/uXT0saCuCxX5GSUKae5nUOtVmNa3JSEh4mKZcyuz+Ae7DqymV1HNhMbfQ/rLLeaWNlYEJs9f7a/7lrZWBAboylzP+5Bxq3o5hZleHDvYb7nj49+QEmbzP/jktalSYzN+bkf2tam9Wg31g9dRtrz1HzP9ToMsb0AxEbGYpk1t7UFcdG6Vz7HRGb+bprcxTJyW1ibs2KDF7PHLODOv8pdiQEQGxWLVbnM7BbW5hm3uuuUyZq9RLEcdX7jr3958vgp1T7WfY5cfkmLicu40g+0V2jG3tcpk56QBCmaq1uTdgRgUuMjRbLlpu/gHvgFb8YveDOx0XFY2VhlbLO0sczoN16IjorRudXN0tqSWG27uhf3IONWdHPLMtxXoG8B7RWYWeq9kGVZUuNyr/fE7YEY1/xQ895o3feqLXP+n+UXQ23noLkC09Qm8yoKU+vSPI7J/f/7L78TVHHW3Kr4KNt7i1mX5tFL3vs2Ze2rQdMvZj9+RkfFYp2lPy9e3JT4hwlER8bqtn2bnH1qfjLk7LFRcVjYZG3rZbmXo61nllGrVRQrUYzEh4mkPE8hUdvmr174i7s3I6lYNddT27eeW/c4as697MfRLGWy7qO16tdgjMfn+J30offQ7gwa048en3VVJDdor8AsmXneJZmVQU58kKNM6uVTkJ6G/DCW9Li7qMraUKhWE9JuX4PnT+H5U1Kv/o66Yv4eq/oP7ol/8Fb8g7cSEx2HdbnMY5GVjSUx2dp6VKTuuVn2Ml3dO+HUtiUTPp+Vr7kNPTto+2TrLH2yVWkeRefeJ//jd4LKzg1y3a6khBzjizK5ji9aje7CxqHL35nxRUL0A8yyZDfLJfsHtrVxGt2Fn7JlNzEtwuCNU9n/1TZunf1bkcyQc0xnZl2aBD25P7KtTZtsYzp940F97xXekJyeP18FQExkvickSSoDOAE/SpJ0E5gCuKP/byFoX78ky3I97dcnsiy3VSZtTg52Tdmz/zCyLHP+4p+YmhbDvGxpbJs04Nip30lITCIhMYljp37HtolyB8SLZ/+kYtUKlKtoTSGjQrTv0obgA2E6ZYIPhOHa0wWAtp0cORl+RrF8+mzZ4IubU1/cnPpyODAE154dAKjboDZJickZt4q/EBd7n0fJj6nboDYArj07cDgwFIAjB47Sxb0jAF3cO3J4f2i+5799/h/MK1tRurw5aiM19Ts15+JB3eeilqtVmR5ew1g/dBnJ9wt2EjArQ2wvAJfOXaFi1fLYaHM7d2lFSFC4TpnQoHA6aXO37ujA6QjN/4lpCVNW/rqMlV5rOH9audWEs2avUKUCNhW02V1bE3pA9/aq0AMRdOzZHoBWHR04Ha5ZVd2mgnXGoifW5S2pXK0iUbejUcKzS1cxqliOQuWsoFAhirVz4HHocZ0y6rKZg4WiDs14fuOWItlys3mDL66OfXF17MuhwBDc3DXtoW6D2iQnJmfcKv5CXMx9HiU/yuhb3NxdMvqQI/tDcdP2LW7uHTP6nPz27OKLereEQoUwbe/Ao2wrMmet92KOTUm5rqn3xxG/UbR5A1QlTFGVMKVo8wY8jlDmmc2G2s4BYs9fx6yyFcUrmKMyUvNB56bcOPi7ThmzypkTZ5Va1SNB+zyvGwd/54POTVEZF6J4BXPMKlsRe+4fRXJfOHuZSlUrUK6iDUZGhXBxa6unPz+Kq7vmGOvcyYkT2v48+EAYLm5tMTI2olxFGypVrcAfv19SJLehZ79y7grlq5TDuoIVhYwK0crVifAg3b4xPOgYLj00p6wOHez5LeIsACVLm2UsTGRT0ZoKVcpz91aUIrkvn7tCxSrlM/bRNq6tOBqku4+GBUXQoUc7AJw62mfso8PdxuDaxB3XJu54/7idn1b+iu/GnYrkBki/8zeqMtZIpSxAXYhCde1I+/O0TpnUS6dQV9P05RQtjqqsDekPopHj76GuUhNUKlCpUVetRXrsnXzN+8uGbXR07EVHx14cDAjGrafmWFKvwSea89xsE99xMfd4lPyYeg00jxpw69mRQ9pjTkun5owYO4jh/cbz9En+P1/dkLMDxJ2/Tokqmf15Ndem3MrWn5eoktmfV2xVj4Qbyh1vXub2+X8om2V8Ua9TMy5lG1/Y1KpMN6+hbBy6/J0aX9zRZi+lzV63UzMu55L956HLeZQlu9pIzYA1E/ltZxgXApRdTEzfmC57nb8Y0/2YbUx3NfQ81VvUoUiJYhQpUYzqLepwNfTduNVfeDdIBX6bl/BWSJI0AvhUluURWV4LBQ4BTYDOgDnwJzAc2ANcBvrLsnxce6v5R7Isv/JsNeXe9TduNFPmLuH02T+Ij0+kTOmSjBrSn9RUzV9c3N06IMsyi1Z8T/iJMxQpXJgFMydQW3v10U7/A6zb5APA8IG9cOuQt/nW+rX6vLqQHi1aNWPaggmo1Sp2efuz9puf+GLqMC6dv0LIgTCMTYxZvGouNT75iIT4RKaMmM2dfyMBOHB6F6bFi2JkbERiQjLD3ce+8YPcU+X/9iyz2Uum0sKpGU8fP2XmuPlcPP8nALuObMbNSbMyXO26NfD6di6Fi5gQdvgYC2Zobg8uWcqMr9ctxrq8JVF3Yhg/dDoJ8a9/YHcpmrdFGWo41MN1zkBUahWntgVz6LvdtJvQg9sXrnPp0G98/ussrKtXIDFO80D5h3fvsWHYcgBGb/PEopoNJsUK8+hhEj7T1nD16B9v9PlBT27mKTcUfHsxkvK2GrFdq2ZMnj8WlVqNn7c/6/9vEyOnDuXyuSuEBoVjbGLMwlWzqV77IxLjE5k+Yi53b0UydPxABo/tz63rmQOXkb3G8/Demz/sP6+PjbB1asrk+eNQqVXs2bqP9f+3ic+nDOHy+SscDYrA2MSYBStn83HtD0mIT2TG557cvRVJh+7ODBrdj9SUVNLldNat+ImQ/WGv/sBsdlgUyVPuInaNKTN1JKhUJO0+QMKPWyg5aiDPL13jcehxSo0dTFGHZsipaaQnJnF/4bek3LwNgPXGFRhVroBUtAjpCYnc81zBk2NvPinuHJn3v27P/XIqLRyb8+TJU2aMnZfRt/gFb8bVMbNvWbLSk8KFTTh65Bjzpy8FNH3L//24GOvyVkTdiWbskDfrWwIt835lftEWjSgz7XMktYrEXUHEr/Wm1BcDeHbpGo9DTlB6/GcUc2iGnJZGekIScQtWknJDU+/F3dpSapjmroSHa71J2h30xp/f4/6jPOUu6HY+tFDlPOUGqOhYFzvPfkhqFVd8Qvlt5R4aTepG3B83uHnwd+w8+1PerhbpqWk8S3jE0dk/8/Ca5uruBmM687G7Pemp6UR4/sKtkDfrzwFWPruWp9wtWzVnxsKJqNQqdm7Zy5pvNjJm2nAunvuTYG1//uV38zT9+cNEJo2YldGfjxj/GV37dCItNY3FHisIO3L8FZ/2dhV09tJGpnnO3sypCWPnjUKtUuPvE8imbzczdPIgrpy/RvjBYxibGDH725l8VOsDEuOTmDtqAZG3onBwacHQyZ+RmpZGelo667/6iYiDb579uZy3q7CaOzVl4rwxqNUq9mwNYOO3vzBiymD+PH81Yx+d9+0sqtf+kMT4JGaN9Mwx0Tps0mc8efSEX1dvzeVTchfcP+/P7FVX/xSTToNBpSLl9GFSgndg3KYXaXf+yZjUNO44iEIf1UdOTycleDup5yM0K567DddMZsoyqdfO8tz/pzf+/Drrb+Q5+7wvp9PSqTlPnzxl6lhPLpy7DIB/8FY6OmrWPv2kXk2WrpxH4cImhB6OwHP6lwAcOeWHsYkx8Q80ixed++0CHpNzfdLWW1eQ2WcUztsiXhWc6tLMsx+SSsVVn1DOrdxDg8ndiDt/g1sHf6fZvP6Uy9KfH/PI7M97Hf8ao+JFUBsV4lniYwL7LCH+r8g3znC1UN7GRh871MN1zgAktYrT20I4/N1unCd05/aFG1w+9BvDf52JdfWKJMZpzo3i795no3Z8MWrbXJ3xxbZpa7n2huOL/3IF2ccO9eg0ZwAqbfYj3+2m7YTu3NFmH/brTKyqVyQpS/afhi2nfhc7ei4bQcxfmefpPpNXE3X53zf6/JQ8PmKkhkM9umjHdCf1jOlG6hnTrdfWeeMeDrT+QvOsWPLPAAAgAElEQVRogkPf7eKUb97+6P31za3KPZfuHff839/zZfLPuNKnitexmMh8T0iSFAIskWV5f5bXxgI10Fx92RK4BpgAK2RZPihJUj3gW8AMKAR8I8vyuld9Vl4mMt8FeZ3ILGj/dSKzIOV1IrOg/ZeJzIKW14nMd4GSz799m/I6kfku+C8TmQXpv0xkFrS8TmQWtP8ykVnQ8jqRKeTdf5nILGh5ncgsaP9lIrOg/ZeJTCFv8jqR+S7I60RmQTPkW2HzOpH5LhATmZnep4nMQkp/oJA/ZFl20PPat6BZzVyW5WTt7eengAva7efQTHAKgiAIgiAIgiAIgiAI76MCep5lfhATmf8b/CVJKgkYAwu0i/4IgiAIgiAIgiAIgiAI77sCWmE8P4iJzP8B+q7WFARBEARBEARBEARBEARDIiYyBUEQBEEQBEEQBEEQBOE9Jb9Ht5aLxX6EN1bbsqlBNpqzl7YUdIQ8qVWjZ0FHyLM0A+0sTQsVLugIeabCcJ9nbaIyKugIeZKQ+rigI+RZMbVJQUfIkyfpzws6Qp4lpRhme7EsXKqgI+RZarphLgwB8DQ9paAj5InKQBdvAyimNsxzgKcG3C+mGPA+mmSg5wCGfL5YwqhYQUfIk8QUw1zsD0AtGe5SRTfunzfcxv6WPfvnRL7M45hUayoW+xEEQRAEQRAEQRAEQRAE4S0Rz8gUBEEQBEEQBEEQBEEQBOGdZ6B3S+pjuNcIC4IgCIIgCIIgCIIgCILwP0NckSkIgiAIgiAIgiAIgiAI7ysDfh5xduKKTEEQBEEQBEEQBEEQBEEQ3nliIlNQhK1jU/ZG+BBwwpchY/rn2G5kbMTytQsJOOHLlsD12FSwBsCsVAk27PyOU9ePMNNrktKx8fBaQcsOvejS73O922VZxuvrH2jfczBuA0Zy+erfGdv8Ag7i4j4EF/ch+AUcVCpyDh5ekzl4ahd7QrypWae63jK16nzM3tCtHDy1Cw+vyRmvm5UswUbf7wg6uZONvt9Rwqy4UrGZ4zWFI6f82BfqQ606H+stU7tuDQKO+nDklB9zvKZkvD7dczxBx3ewL9SHH35eTvESpkrFprljE/zCvdl7fBuDR+tv60vXzGfv8W38GrAOmwpWADRt2QjvAxvYHvwL3gc20Ni2gWKZX+TeFe6N33EfPhvdT2/uJWvm43fch00Ba7HW5m7SshGbD6xnW/AmNh9YTyPbTxXNDdDUoTE+YZvwjdhM/9F9cmw3MjZi4eo5+EZsZr3/91iX12S3Lm9FyD8H2HTwRzYd/JGpSyYqHR07x6YEHPNl/8kdDB0zIMd2I2MjVqxdxP6TO9gauCGjbwQYNnYg+0/uIOCYL7aOTZWMTTPHxuwI28yuY94MHN03x3YjYyO8Vnuy65g3P+1bk1HnterVYPPBDWw+uIEthzbi0L6ForlBU+f+EdsIPLE91zpfvnYhgSe2453teLRx5/ecvh7MrCz9pJLmLZ7O0TP7OBC2g9p1augt80ndmgSF7+TomX3MWzw94/VJM0dzIGwHgaG+/LpjDZZW5krFpplDY7aH/crOiC0vbS87I7aw0X91Rnt5wbKcBaF/7aff572UigwYdr9oqH0LGO4+2tShMb5hv7AjYjMDcjkWLVo9lx0Rm9ng/4Pedh7yVyB9P3dXKnIGW8em7Anfiv9x35ecuyzA/7gvmwN+zDh3MStVgh93rOLEP4eZUQDn6YbczgHmL55B+JkADobtfGmffih8J+FnApi/eEaO7SNGD+LOg4uUKl0yv+PqMMTjkaGOR18wxDoHmLt4GsGn9xJ41PelY7rAsO0En97L3MXTMl6fOOMLAo/6si/Eh03bV2OhYO73kpyeP18FQExk5hNJktIkSTonSdIlSZLOS5I0UZKkl9a3JEk2kiRt1/7bQZIk/1eU95Qk6a72cy5LktT7NXJ1kSSp5pv9Nv+NSqXCY8lkRvaZQOcWvXFxa0vVjyrrlOnapzOJ8Ym4NO3BL2u8mTj7CwCeP3vOyiVrWe65UsnIGbq4tGH1ioW5bg87fppbdyIJ8FmP59SxLFi+CoCExCR+2LgF73Xf4L3uG37YuIWExCSlYmewb21L5aoVaNPYjdmTFjFvac4TIIB5y2Ywe9Ii2jR2o3LVCrRs1RyA4WMHcTzsFG2bdOV42CmGjx2kSG6H1rZUrloRp8auzJq4kPnL9Oeev2wGsyYuwqmxK5WrVsRemzs85ATt7XrSwd6dG//cYuT4wYrkVqlUzFw8mVF9JuHWsg/t3FrnaOtufTqRGJ9Ep2Y9+XWND+M9RgEQ/yCBsQOm0t2xP7PHLWTRqjmKZH6Re/riSYzuM4luLfvqzd2lT0eS4pNwbebO5jU+jMvIHc/4AdPo6TiAOeMWslDB3C+yT/Yax4S+0+jtMJC2rk5U/rCSTpnOvV1IjE+mh21fvNdt5wuP4Rnb7v4byYA2QxnQZihLp69QPPvsL6cyvPc4Otm506GrM9U+qqJTpnvfziQkJNGuSTc2rfFm8uzRAFT7qAoubm3p1KIXw3qNY86XU1GplDmkq1QqpnlNZGzfyfSw749zl9ZUydZeXHt3ICkhCbfmvdmydhtjPDR/DPr76nUGtBtG3zaDGdNnMjOXTkGtViuS+0X2WUum8Hmf8XRu0QsXt7Y56rxbn84kxifRvml3Nq3Zmu14tIZlnt8qljcrx9YtqFytEi0bdmD6hHks+spDb7lFyz2YPmEeLRt2oHK1Sji0tgNgzcqNOLfoRnv7Hhw+EMq4Kfr/QPe2qVQqpnpNYFzfKfR0GEBb11ZUybaPuvbuQGJ8El1t+7BlXWZ7eWGi5xiOHTmpSN4XDL1fNMS+5UV2Q9xHNe18POP6TsXdYSDOetp5594dSIpPopttX7zX+TLaY4TO9gmeozl+5JSSsYEX5y6TGNlnIl1a9qa9Wxs95+mac5eOzXrwy5qtjPfIrPPvvlzLV/NWFUhuQ23nAE6tW1ClWkXsGrowbYIni7+arbfc4uWzmTphHnYNXahSrSKO2j4dwLqcFS0cmnHndqRSsQHDPB4Z8ngUDLPOARxa21G5akUcG3VixsT5LFyuP/fC5R7MnDAfx0adtGM6WwDWrvqJ9i170MHBnSNBRxk7eYTe9wv/e8REZv55IstyPVmWawFtABdg7sveIMtypCzL3d/wc76WZbke4AqskSTJ6BXluwCKTmR+8mlNbt24w51/I0lNSSVw90Gc2rXUKePUrgV+2wIACNobTBO7hgA8efyUs6fO8+zZcyUjZ2hY7xPMSuR+FWJw+Ak6t2uFJEnUrV2DpKRk4u49IOLkbzRrVB+zEsUxK1GcZo3qE3HyNwWTa7RqZ88uH029nv/tIsXNimNuWUanjLllGUyLF+PcmQsA7PIJoHV7B83729uzy8df+7o/rV0cFMndur0Du7ZpPvfcbxcoYVYcc8uy2XKXxbR4Mc6e+UOTb5s/bVwcAc1EZlqa5hkg585cwMrGQpHctevX5PaNO9y9pWnr+3cfwsFZ94ozR+cW7NkWCMBB/2Aaa9v6lYvXiIu5B8DfV65jbGKMkfGrdue3lbuGTu4Duw/nyO3g3IK92n30kH8Ije00V4xevfhXRu5/rtxQNDdAzfofc+fmXSJvRZGakspBvyO0dLbVKdPC2ZYA3/0ABPuH0tBO2atdc1Pn01oZfWNKSioBu4L09I32+PnsA+DA3iM0bdFI+3pLAnYFkfI8hbu3Irl14w51Pq2lSO5a9Wtw++Zd7mrrPMjvMPbOdjpl7Nu1wH+bps4P+4fQuIWmzp89eZaxb5qYGCPLsiKZX/jkU80+mlHnuw/imKPOW+K3TVPnQXuP0NROU+dPHj/l91PneV5Ax6O2Lo7s2LoHgLNn/qBEieJYZOsXLSzLYlrclN9Pnwdgx9Y9OLs4AZCc9CijXNGiRRSr++zt5aCe9tLS2Y592n30iH8ojewyr2C0b2fH3VuRXL92U5G8Lxhyv2iofQsY7j5aq34NnWNRkN8RWmbvF51t2ed7AHhZO7+haG7QnLvcynbu4uisW+cOzi3Yo23rB/2zn6f/wbNnzxTPbcjtHDR9+nZtn/77S/v0Yhl9+vYsfTqA56KpLJq7QvFjqSEejwx5PAqGWecAbdo7stNnL6AZk73OmG6nz17a6sldpGhhZJRt6++d9PT8+SoAYiJTAbIsxwLDgdGSRmVJksIkSfpd+9UcQPv6xazvlSRJJUnSX5IkmWf5/m9Jkspm+4y/gMdAKW25YZIkndZeDbpDkqSi2s/pDCzTXsVZTfu1X5Kk37SZ9F/v/R9YWJkTHRmb8X1MZGyOy8ItrM2JvhsDQFpaGslJyZQsbfa2o7x1MXH3sbLI/K+wtChLTNw9YuLuYWWR+TtammteV5qltTnRkdEZ38dExmBppTupZ2llQXRkTGaZqBgsrTXZy5qXJi7mPgBxMfcpU7aUAqnB0tqCyLuZmaIjY7Gy1m0zVta67SoqMhZL65wTlt37uhJ6+Fj+hc3Cwtpcpy5jo+Iy6lJfGU1bf5Sjrbfu6MiVi9dIeZ6S/6G1mWKy7qNRsZjrza0pk3tuB64qmBvA3Mqc2Mi4jO9jo+JyZDe3MidGWyYtLY3kxGTMtNltKlrxc9A6vt/xDXUbf6JYbtD2jXez7nuxOdqLpZU5UVn6xiRt32iZra3p61fzM3fM3cz2EhsVh4VVtpNpq7IZbUpT548y6rxW/Zr4hGxia/BPLJ62PGNiUwmWVhZEZau37LdXaY5HmdmT3pHjkZW1BVF3M/vz6MgYrLL1eVbWuv159jJTZo3hxIWDdOnRga8Wf5f/oQHzLG0BIEbPPppbeylcpDADRvVh3Vc/KZJVJ5MB94uG2rdochnmPpq9nWuORWVzLaOvnf/41c+KZn7BUk9bt8jeXqzNiYl8t87TDbmdA1hZWxKZpU+PiozBytoyR5ms+0PWMm3aORAdFcufl64qE1gnl+Edjwx9PGqIdQ6aMV3U3extOGfuqGy5s47pJs8aTcQfB3Dt3oGvF3+f/6HfZ+LWcuFNybJ8HU19WwCxQBtZlj8F3IFc74GRZTkd+BV48VCp1sB5WZZ1ZsUkSfoU+Es7aQqwU5blRrIs1wX+BIbIsnwM2ANM0V4t+g+wFhgjy3IDYDKgt3eQJGm4JElnJEk68+BJrL4iuZIkKefvlb0Mesoo/NfFvNCXUZIk9EXXVw/5TW/dZwv3OmWUpq+qckR6jdyjJgwhLTUVP9+At5gud/pzZ6/vl5epVr0K4z1GsWDK0rcdL3evUeGvaidVq1dhrMcoFk5Z9tbjvYze3eo16/xe7H1cG7kzsO0w/s/ze+Z/P5uipkXzJ6ge+uv01WWQc+tXFdpv87h/vih06exl3B0GMKD9cD4b0w9jE+O3nzE3eqszW3t5V49Hr9FeXtUvLlu0kqaftGG37z4GDXvl02jeirweh5BlRkwZjPc6X548fpJf8XJn0P2igfYtYLD7aG71+eoyMsOnfFZw7Rxe63zqtcoozKDbOf/tHL1wkcKMnTSc5V7K39IPGOTxyODHowZY57lEeu1zgBeWL1qFbR1n/LbvY8BQZZ+VLby7xESmsl7spUbAOkmSLgC+vPpW7w3AiydYDwY2Ztk2QZKkq8BJwDPL67W1V1heQDMJmuN+CUmSTIHmgK8kSeeANYB19nIAsiyvlWW5oSzLDUsXebPbdGOiYnVu7bW0sSAuOi5nmXKavzCq1WpMi5uS8DDxjT6nIFhZlCU6NnNOOSb2HhZly2hfz/wdY+I0ryuh7+Ae+AVvxi94M7HRcVjZZD5M3tLGktgY3bqPjorByibzL8CW1pbERmt+p3txDzJuRTe3LMP9ew/zLXe/wT3ZG+zN3mBvYqPjsCmXmcnKxoKYbG0mOlK3XVnbWBCbpUxX9444tm3BhM/1P4slP8RExunUpYW1eUZd6iujaevFMtq6hbU5X29YjMeY+dz5965iuWMjY7HMuo9aWxCXI3dmfevLvWKDF7PHLFA0N2ivBrTJ/Iu6hbV5juyxUXFYasuo1WpMS5iS+DCRlOcpJGp/h6sXrnH3ZiQVq1ZQLHvWfg809R6bvZ1HxWKdpW8sXtyU+IcJ2vaf5b02Of/P8ktsVByW5TLbi4W1ecZttDplsraXEsVy9Ok3//qXJ4+fUu1j3Wea5aeYqFiss9Vbjn00KharcpnZixfg8WjAkF4EhvoSGOpLbHQs1uUy+3MrG0tionX/sBgdqdufa8rotimA3dsDaN+pdf4FzyJrWwDNlV33ctS5/vZSq34Nxnh8jt9JH3oP7c6gMf3o8VlXZXIbcL9oqH0LGN4++kL2dp77sShnO69dvyajPUaw++RWemW0czfFsse8Zlu3tHm3ztMNsZ0PHNKLA6HbORC6nZjoWGyy9OnWevr0qMhonf3hRZnKlStQoWI5gsJ2cPzcAaxtLNkf4ou5Rf6NNQz9eGSI41FDrfP+Q9zZF+LDvhAfYqPjMvZBeNGGdTNFRcbotPPccu/ZHkg7hc5d3lvi1nLhTUmSVBVIQ3M15gQgBqgLNAReejmKLMu3gRhJkpyAJkBgls1fy7JcHc2VnZskSSqsff0nYLQsy58A84DC5KQC4rVXZ7740r8E2n9w8eyfVKxagXIVrSlkVIj2XdoQfCBMp0zwgTBce7oA0LaTIyfDz7ztGPnCwa4pe/YfRpZlzl/8E1PTYpiXLY1tkwYcO/U7CYlJJCQmcezU79g2Uea5fJs3+OLq2BdXx74cCgzBzV1Tr3Ub1CY5MTnjVvEX4mLu8yj5EXUb1AbAzd2Fw/tDATiyPxQ3947a1ztyODA033L/umEbnRx708mxN0EBIbj11HxuvQafkJSYnGOiJC7mHo+SH1OvgeZ2YLeeHTkUGAJAS6fmDB87iBH9xvP0ydN8y5zdpXN/UrFq+Yy23q5La0KDwnXKhASF0blnewDadHTkVITm2anFS5iy6tfl/J/Xas6dvqBYZk3uK1SsWh4bbW7nLq0IyZY7NCicTtp9tHVHB05rc5uWMGXlr8tY6bWG8wrnBvjz3FUqVCmPdQUrChkVoo2rE2FBuo8SCAs6hkuPdgA4drTnTPjvAJQsbZbxcH+bitaUr1KOyFvKPTD/wtnLVKpagXIVbTAyKoSLW1s9feNRXN07AODcyYkT2r4x+EAYLm5tMTI2olxFGypVrcAfv19SJPflc1eoUKU8NhU07aWtayuOHtBtL0cPhNOxp6bOW3V04LS2zm0qWGcs7mNV3pJK1SoSeTsapWQ9HhkZFcKlSxuCDxzVKaM5HmnqvG0npwI9Hm1av5X29j1ob9+DA/uO0K1XZwDqN6xDUmIysdknkGPu8Sj5EfUb1gGgW6/OBAUEA1C5asWMcm3aO/LPX8o8i+/yuStUzNJe2ri24mhQhE6ZsKAIOmj3UaeO9hntZbjbGFybuOPaxB3vH7fz08pf8d24U5HchtwvGmrfAoa3j76Q2S9aaftFJ8KytfOjQRF06OEMaNr5mfCzgKadd2nSiy5NerE1o53vUiz7pXN/attL5rlLSJBuewkJCqeztq1nPXcpSIbYzn9evxVn++4423dn/74jdNf26Z++pE9PTn7Mp9o+vbu2T7/y51/Uq25Ps3rONKvnTFRkDO0cehAXez/HZ74thn48MsTxqKHW+S/rfejg4E4HB3eCAoLp6t4JgHoNcx/TJSc/ol5DzZiuq3snDgbmzN26vQPXFTp3Ed59hQo6wP8C7fMtVwOrZFmWJUkyA+7IspwuSdJA4HWWbP0RzS3mv8iynOOBYrIs79T+rIForqwsDkRpF//pC7y4HCBJuw1ZlhMlSbohSVIPWZZ9Jc113XVkWT7/335jXWlpaXjNWM6arf+HWq1il7c//1y9wRdTh3Hp/BVCDoSxc8teFq+aS8AJXxLiE5kyInPlvgOnd2FavChGxkY4tbdnuPtYxR76P2XuEk6f/YP4+ERadenHqCH9SU1NBcDdrQMtmzUi7Php2vccTJHChVkwcwIAZiWKM2JQb3oNHQfA55/1eemiQfkl5GAE9q1tOXRqN0+ePGXG2HkZ2/yCN+PqqHliwdwpS1iy0pPChU04euQYoYc0J99rv/2Z//txMd37uhJ1J5qxQ6YrlDsch9Z2HDntx9MnT5k21jNj295gbzo5am6HmDPFi6Ur52FS2ITQw8cI0eb2XDINYxMjft7+A6BZMGj2ZK98z52WlsbimSv4wftrVGo1u7VtfdTUoVw6d4XQoHB2bfFn0ao57D2+jcT4RKaO0Kxm22twdypWKc/wCYMYPmEQACN7TeBBPl4FmzX3lzO/5nvvFajUavy8/bl+9QYjpw7lsjb37i3+LFw1G7/jPiTGJzJ9xFxt7m5UqFKeYRMGMSwj93ge3ovP99wvsi+f9X/835ZlqNQq/LcGcuPaTYZN+Ywr568SFnSMvd4BzP12Jr4Rm0mMT2T2yPkA1G9al2FTPiMtNY309HSWTl9BYnySIrlfZF84fRk/+nyLSq1i55a9/H31OmOmDefiuT8JPhDG9s17+PK7eew/uYOEh4lMGjEL0Kz+vd/vEP7hPqSlprFg2lLSFfqLaFpaGstmfs1K769Qq1Xs2bqP69duMmLKEP48f4WjQRH4ee9j/koPdh3zJjE+kZmfewJQr0kdBo7uS2pKKrIss2TGChIeJCiS+0X2RTOWs3arps53ee/ln6s3GD11OJfOa+p8x5Y9LFnlSeCJ7STEJzJ5ROZV3UGnd2FavJjO8egfhRbnOHIwDMc2LQn7LYAnT54yeXRmrsBQX9rb9wBg1uQFfPXdQgoXLkzwoXCCD2kGatPnjqfaB5VJT5e5ezuSGZMWKJI7LS2NpbO+4dsty7XtJUDbXgbz5/mrGe1l3rez2BmxhcT4JGaN9FQk26tyG3K/aIh9y4vshriPpqWlsUzbzlVqFXu17Xz4lMH8ef4KYUHH2OMdwLxvZ7EjYrO2nc979Q9WQFpaGl4zv+IH729Qq1VZzl2Gcfncn4QEhbNry168Vs3F/7jmPH1qlvP0wNM7MTUthpFxIZzatWREr3GKnKcbcjsHOHLwKE5tWhD+WyBPnzxh4ugsY5/Q7Tjba9Z/nTl5ASu0fXrIoTCOHArL7UcqxhCPR4Y8HgXDrHOA4INhOLaxI+SMP0+ePGXqmDkZ2/aFaCY8AWZPXsSyVQsoXNiE0MMRhBzS/OFw6pxxVP2gMnJ6OndvRzFr8kJFcr+v9EwjGSzpnXnuw3tGkqQ04AKa28hTgV+AFdrJyw+BHWgW5wlG84xKU0mSKgP+sizXliTJAZgsy3JH7c8zAu4DjWVZvqJ9zRNIlmV5ufb7BsAWoAYwApgK/KvNUVyW5UGSJNkC64BnQHcgHfgBzS3lRsBWWZbnv+x3q23Z1CAbzdlLWwo6Qp7UqtGzoCPkWVoBPfz3vzItpO8CZsOg0veAMQNholJuVd+3KSH1cUFHyLNiapOCjpAnT9ILbuXQ/yopxTDbi2VhZRZ7yw+p6YZ74v40XblFgt4mVQE8F/xtKaY2zHOApwbcL6YY8D6aZKDnAIZ8vljCqFhBR8iTxJRHry70jlJLhnsj74375w23sb9lT8/558s8TuF6HRWvY3FFZj6RZTnXqyy1K4zXyfLSDO3rN4Ha2n+HACFZytRFs8jPlSw/xzPbz/0NqK799gftV/bPjiDnMznbveRXEQRBEARBEARBEARBEIQCJyYyDYAkSdOBkWSuXC4IgiAIgiAIgiAIgiAIr1ZAC/PkB8O9Rvh/iCzLS2RZriTLcvirSwuCIAiCIAiCIAiCIAjC+0dckSkIgiAIgiAIgiAIgiAI7ysDXb9CHzGRKbyxVANd7cpQF8259Oe2go6QZw1r9yvoCHmSnPq0oCPkWSkDfQA6QHKaYda7IS9qYah1bsgLQ5Q1MSvoCHkS+0yZFbfzg6WJ4S5UJBlo//LMQBcpAsNdBMVQF1gEw10wB8BIynVZhHdasUJFCjpCnhnqwjOGukgRGPa5rpCFAZ8/Z2eYvYAgCIIgCIIgCIIgCIIgCP9TxBWZgiAIgiAIgiAIgiAIgvC+MuAr97MTV2QKgiAIgiAIgiAIgiAIgvDOE1dkCoIgCIIgCIIgCIIgCML7Kl1ckSkIeTJr0SQOnNyJX8gWan5SXW+ZWnU+Zk+INwdO7mTWokkZr5uVLMF631XsP7GD9b6rKGFWXKnYeHhN5uCpXewJ8aZmndxz7w3dysFTu/DwmpzxulnJEmz0/Y6gkzvZ6PudYrk9vFbQskMvuvT7XO92WZbx+voH2vccjNuAkVy++nfGNr+Ag7i4D8HFfQh+AQcVyZtVc8cm+IV7s/f4NgaP7p9ju5GxEUvXzGfv8W38GrAOmwpWADRt2QjvAxvYHvwL3gc20Ni2gdLRAZjjNYUjp/zYF+pDrTof6y1Tu24NAo76cOSUH3O8pmS8Pt1zPEHHd7Av1Icffl5O8RKmimRu5tiYHWGb2XXMm4Gj++bYbmRshNdqT3Yd8+anfWuwLq+p81r1arD54AY2H9zAlkMbcWjfQpG8Wdk6NmVvhA8BJ3wZMkZ/e1m+diEBJ3zZErgemwrWAJiVKsGGnd9x6voRZnpNyvG+/Gbn2BT/iG0EntjO0DEDcmx/kTvwxHa8s+XeuPN7Tl8PZlaWvkZphtqfg2Huo80dm7AzbAt+x7YyaHTOhdSMjI1Ysnoefse28vO+tTr7qPfBjXgf3MjWQz/h2L6lInmz81w8jdDT/uw/up3adWroLVO7bg0OhO0g9LQ/nounZbw+acYX7D+6nYCQbfyyfTUWVuaKZG7q0BjfsF/YEbGZAaP75NhuZGzEotVz2RGxmQ3+P2TU+QuW5SwI+SuQvp+7K5I3K0NuL4baNzZ1aIxP2CZ8IzbTP5f2snD1HHwjNrPe/3u97eXIX4H0KYD2ktc6Bxg6diCBJ7bjH7ENW4cmSsYGYP7iGdXYh+EAACAASURBVISfCeBg2M5c+5ZP6tbkUPhOws8EMH/xjBzbR4wexJ0HFylVumR+x9Uxd/E0gk/vJfCo70uPRYFh2wk+vZe5WfrFiTO+IPCoL/tCfNikYL9oqOdcYNjjC0Otd1vHpuwJ34r/cd+X1PkC/I/7sjngx4w6NytVgh93rOLEP4eZUUDtRXi3vXMTmZIkpUmSdE6SpEuSJJ2XJGmiJGmWJpMkqaEkSd++5L2VJUnKeeaQf1krS5L0RJv3xZdxPnzOT5Ikdc/2WvLb/pz81rJVcypVrYhzk67MmeTF3KXT9Zabu3Q6cyZ74dykK5WqVqSFU3MAho0dyImjp2nXtBsnjp5m2NiBiuS2b21L5aoVaNPYjdmTFjFvac4TIIB5y2Ywe9Ii2jR2o3LVCrRspck9fOwgjoedom2TrhwPO8XwsYMUyd3FpQ2rVyzMdXvY8dPcuhNJgM96PKeOZcHyVQAkJCbxw8YteK/7Bu913/DDxi0kJCYpkhlApVIxc/FkRvWZhFvLPrRza03VjyrrlHHr04nE+CQ6NevJr2t8GO8xCoD4BwmMHTCV7o79mT1uIYtWzVEs9wsOrW2pXLUiTo1dmTVxIfOX6W8v85fNYNbERTg1dqVy1YrYa9tLeMgJ2tv1pIO9Ozf+ucXI8YPzPbNKpWKa10TG9p1MD/v+OHdpTZVsde7auwNJCUm4Ne/NlrXbGOOhmSD/++p1BrQbRt82gxnTZzIzl05BrVZuBU+VSoXHksmM7DOBzi164+LWNkd76dqnM4nxibg07cEva7yZOPsLAJ4/e87KJWtZ7rlSsbxZc89aMoXP+4ync4teuLi1pdpHVXTKdOvTmcT4JNo37c6mNVuz5V7DMs9cD4f5zlD7czDsfXRM38l0s+9HOz37aJfeHUlMSMK1eS82r/VhnMdIAP65ep1+7YbSu81njO4ziVkK76MAjq3tqFK1EvaNOjJj4nwWLvfQW27Rcg9mTJiHfaOOVKlaCYdWdgCsWfUT7Vp2x8WhJ4eDjjJu8oh8z6xSqZjqNZ5xfafi7jAQZ9dWVPmwkk6Zzr07kBSfRDfbvniv82W0h26uCZ6jOX7kVL5nzc6Q24uh9o0qlYrJXuOY0HcavR0G0tbVico52osLifHJ9LDti/e67XzhMVxn+3jPLzh+5KSSsYH/VufVPqqCS5c2dG7ZmxG9x+Hx5f+zd+ZxUVXvH38fEMQEKQUGNM2l+qa55p7sogLupuKWmZpb7lvu+1ZaVtqmWVkZgiuCKKAs4q65l2a55AIMoClgbuD5/THjMDOAC8rF6Xffr9e8YO595s7nPvPc55x77lnGY2Wl3O2lr58HVapVwr1BIB+MmsH8j6fmazd/0VTGj5qJe4NAqlSrhI+fu2GfWwVXPLybculiklKyAfD2c6dy1Ur4NGz7wLw4Z9EUJo2ahU/DtvqyqBkAy5b+QIBnF1p7BxEbvYPhCuVFS6xzgWXfX1iq33U+H8PgHqPp4NmdgI4t8tGt83mbpl346ZvVjJySq/uLD5fx8cyliuv+TyPvFc2rGHjmGjKBm1LKulLK14EWQCAwHUBKeVBKOfwBn60MKNaQqeeMXu/91x3jnUIIdfi+nuYBXoSFbgbg6K8nKOPogLNLORMbZ5dy2DuU5sjB4wCEhW7GL9BL93l/LzaGRACwMSQCvwBvZXT7e7EhJNKg28HRAWeNmW6Nqe4NIZEGfc0DvNig170hJAK/QGV0N6hbC8cyBfdyitu5l3b+zRFCUKdmdTIzs0hLv8qufb/StGE9HMs44FjGgaYN67Fr36+KaAaoWa8GF89d4vKFJLLvZrN14za8W5n28vNp5cGm0C0AxETE0ci9AQCnTpwmTZsOwF+nzmJb0hYbWxvFtAP4BXizIVT3ex/59bguzjVOJjbOGifsHUpz+OAxADaERtAi0AfQNZLk5OToPn/wOK7lXYpc8+v1qnPx/GUuX0gm+2420WHb8WrlbmLj5e9BROhWALZHxNPIQ/c0+vbN2wa9JUvaIqUscr3G1HqjBhfOXeLS37p42bIxBl9/0x5Evv4ehIXqruHo8Dga6+Pl5r+3OLz/KLdv38lzXCV0X9Trvns3m8iNMfjk0e1pyJnR4bE0cW9o0H1o/1HuFIPu+1hqPgfLvEZr1qvOpfO5eTEqbBveZteot787Efq8uD0inob6a/SW0TVqWwzXKECLAB/WhYQDcPjgMco4OuBi5nMXjRP2DvYc0vt8XUg4LfU+z8q8YbB77rlSKHEGr9erzqXzl0ky5MVYPM3zYqtmbF4TBUBsRAIN3d/I3efvzuULSZw9fU4BtaZYcrxYam6sUe81k3iJCYvFs1UzExuPVs2IXKMrR+MiEmjgntury9PfncsXkjl3+rySsoEn87mPvyeRG2O4e+culy8kc/HcJWq9UUMx7S0DfVi7ehMAhw4eo0yZgnJLaQ4dOArA2tWbaBXoa9g/Y+545k7/RPFYbxHgw3p9Xjxy8NHKovUh4bTUazfOi6Wes0MqkBkttc4Fln1/Yal+r1lPp9vY5z6tTHV7t/Jgk153TIS57mPcvn1bcd3/ae7dK5pXMfAsNmQakFKmAgOAoUKHtxAiAkAI4WXUC/KwEMIBWAB46LeN0veYTBRCHNK/3tR/1lsIES+EWCuEOCWEWCWEEPp9DYUQu/W9QfcLIRyEENZCiIVCiANCiGNCiAc+8hJCzBBCLBNCRAM/CiHshBDfCyGO67X66O36CCE2CiHChRDnhBBD9T1QDwsh9gohyj7MR3q/LBRCnNAfP8joHBOEEKFCiNNCiAVCiJ76czouhKimt3MWQqzTn9sBIUSzB39j4dG4OpOcpDW8T0lKReNmegOocXMhJTnV1EY/VKKcc1nSUq8AkJZ6hbJOLxSVVDNNzqQkpRjea5O0aFzNdLu6kGJ0btpkLRo3nW4n57KkafW6tVcop5Duh6FNu4KrS26FSePihDYtHW1aOq4uucNTNM667Urh4uZs4svU5DSDL/OzycnJISvzBs+XdTSx8Wvjw6kTp7l7527RizZC4+ZC0mXTOHc10+/q5kxKUm6cJ+dzLQB07tmehO27i06sHhdXZ7SXc/WkJqfh4mp2I+DqhFavOScnh6yMGzjqff56vRqExP/I6rgfmP/BIsNNsBK4uJr6UpuUmmd4lYubMymXjeMlK0+8KI3G1cUkH2qNct19dLpzfZ75DOi+j6Xm8/u6LO0adXbNjQW4f40657Uxu0bvx0vNejVYE/8ToXErmafwNQrg6uZC0uXccjQlSZt/vBjFVHKSFlcjm3GTh7HnWDQdOrfmk/lfFLlmZ6OcBzqfO7s5FWhjnBftStnRe0gPvv14ZZHrzA9LjhdLzY3Ors6kJqUZ3uviJa/PtXobnc+zDPHy9pDurCimeHkSn2tcc8tXgJTk1Dx15KLE1U1jklt0eUOTxyY5T27R2bTw9yYlOZWTv/2hjGAjNG4uJF8uOOeBLnealrWmuXPs5KHsOhZF+86tWTz/yyLXbKl1LrDs+wtL9bvGzdmkHNUmp+Ji5nOdzbOlW8UyeKYbMgGklGfR6TQvFccC70sp6wIewE1gApCo7xm5GEgFWkgp3wCCAOOxJvWAkUANoCrQTD8sPAQYIaWsA/jpj9sPuC6lbAg0BN4TQtwfc1HNqEHVuGZdH2gvpewBvK8/l1pAd2ClEMJOb1cTXS/SRsBc4F8pZT1gD2A8Sc1C4yHsRts7AXWB+3oXCiHuT1xTBxgB1ALeBl6VUjYCvgWG6W0+Axbrz+0t/b6iQddWbEKep5/52hSVoEdDPILuR7F51shPnxAiX3/nd35FRX5fldffD7ap9r8qjJwyhNnjPnra8h5K/toebmR+jkNG9SMnO5uwNZFPUV0BFFLzfaPfDv9OkHdvegcM4N1hvbAt+dRn2CiQfK89c5t8TrDYr8/83Gmm/JnUfR8Lzedgmdfok5ZDJw7/Thfvt3k74D3Fr9GHaXuwTe7/C+cuoWntlmxcu5l3+nd/6hrNybfcyxPi+QfTgHHvErx8DTf/vVk04h6CRceLhebGfKtJj1h3eW/cu6wuxnh5Ep8Xd/33SWLdrpQdw8cMYNG84hm6+mj13QcXWIvmLqVZ7VaErd1M7/7dnrbEPFhsnQvLvr+wWL8Xuq5Y/PHyn0Xtkak4+VUPdgGfCCGGA89LKbPzsbEBlgshjgNr0DVa3me/lPKSlPIecATdsPT/AclSygMAUsoM/XFbAr31DYj7gHLAK/rjGA8tf9/o+JuklPdrJO7AT/pjngL+Bl7V74uTUmZKKdOA60C4fvtxvab7jDMewm603R0IllLmSCm1QAK6xlaAA1LKZCnlbeAMEJ3Psf2Apfpz2wSU0fduNUEIMUAIcVAIcfDazTTz3QXSo28XNsSuYkPsKlJT0nErn/uU1LW8C6kppsfSmj2NdC3vQqpWZ3Ml7aph6KKzSzmupv/zyDoel559uxAWt4qwuFWkpqThWj53QnZNeY1B031SkrW4Gp2bxk1DaoquF2N62lXDUHRnTTmuFKHux8HVxYmU1NyeltrUdFycyum3556fNk23XSm0SWkmvnRxczb4Mj8ba2tr7B1Kc/2fDIP94u/mM2XYLC79fVkRzb36diU8LpjwuGBSU9IoX8E0zrVmcZ6SlGoyHNXN7FroFNQGn5YejBqU/3xJT5vU5DQ0FXL1uLg5G4bQmNjoNVtbW2NfJtfn9zn/59/c/PcW1V4znVurKNEmm/pSU96FNPO8kpyKawXjeLHPo11ptMmpJvlQU94lb5wnp+JaIdfnDsWs21LzOfwXrtHcWICCrtFczQVdo+cUvEZ79wsiMj6UyPhQtClplK+QW466ltfkiZeUJNNy1K28Bm1KKuaErY0koK1f0QnXY5zzQO/zlEfLizXr1WDolIFs3Leabv0702dYL7q827HINefqsrx4uY8l5kbQ93otn9vTqOB40dnofG5Pxj8ZvF6vOkOnDGLDvtUE9e/MO8N60lnBeHkSn6cYla+g60FoXkd+2rzTrxtRCWuJSliLNiXVJLfklzeSk1JMzu++TeXKFalYqQLRievYcyQKt/IatsavyTNNytPk7X5BbI4PYXN8CKkpabhVMNdl6rvkJK1ZWZvXBmDT2i34K5AXLbXOBZZ5f2HQZaF+1yalmpSjGjeXPHlRZ/Ns6VaxDJ75hkwhRFUgB13vSgNSygVAf6AUsFcIkd9Sb6MALbqeiQ0A40fKxhMu5AAl0DWY5vcIQADDjBoSq0gpo/OxM+aG0f8P6s5mrOOe0ft7ek0P40mPbQU0NTq3ClLKPCu7SCmXSSkbSCkbPF/q0VfF++W7NXT07UlH355s3xJP+66tAahTvyaZGVmGoYX3SUu9wo2sf6lTvyYA7bu2ZvuWBABio3bQIagNAB2C2rB9a8Ij63hcVn23hvY+PWnv05NtW+LpGBRo0J2VkWUYKm7Qrb3CjawbBt0dgwIN+mK3JtBRr7tjUBvD+RQ33u5N2LR1O1JKjp44ib19aZydytKscX127z/E9YxMrmdksnv/IZo1Vm51vt+OnKRS1RepUMmNEjYl8O/gR0L0ThOb+OhE2nUNAKBFGx/279LN4elQxp6lPy/is3lfc+TAccU0//xdKG19utPWpzvRkfF07Kr7vevWr6WLc7MbyDRtOjey/qVu/VoAdOzahm1b4gHw9H2TAcP7MLDXSG7dvKWI/t+PnKJilRcpX1Hn85btm7MjytTnO6J20qarPwDN23hzYOchAMpXdDMsBOH6ooaXqlUi6WIKSnHi8EkqVa1oiJeADi2Ii0o0sYmLSqR9V9013LKtD/t2HlRMX0EY67axKUFghxbERe0wsdHp1uXMlm19i123peZzsPxr9Lcjp6hYpaLhGm3V3o+EqF0mNglRu2ijz4sFXaNuL2qoXK0SyQpcoz+uCCHQuyuB3l2JjozlraC2ANRrUJvMjExSzRvWtOncyLpBvQa1AXgrqC0xW+IAqFy1ksGuRYA3Z/4s+nknc/Oiqz4v+pIYberzHdG7aN2lFQC+bbw4uPMwAAM6DqND4250aNyN1d+u5YclP7Pm+w1Frvk+lhgv97HE3Ahw8sgfVKzyIm76eGnR3pfEaNNpJxKjdxPYRVeO+rTx4qDe54M6Dqdj4250bNyNkG/XsnLJKtYqGC9P4vO4qB0EdmiBja0NFSq5UalqRY4f+r1I9a5csZpWXp1p5dWZrZtj6dytHQBvNKhNZkZWvrklK+tf3tDnls7d2hEdGcepk39S939eNK3biqZ1W5GcpMXfu0uesuxp8tOKEFp7B9HaO4joyDg66fNi3QYFl0VZWTeo20BXFnUqIC/6BXhzVoG8aKl1LrDM+4v7WKrffztykpeMdPt38CM+2lR3fPRO2ul1G/tcpWiQMqdIXsXBM70QjRDCGfgaWCqllMbdqoUQ1aSUx4HjQoimwGvARcC4N6EjcElKeU8I8Q7wsGUXTwHlhRANpZQH9D0TbwJRwGAhRKyU8q4Q4lXgcR7F7AB6ArH6z1YC/gDeeOCnHv3YA4UQK4GygCcwDp0/HoVoYCiwEEAIUVdKeeTBHykcCdt24enXjOj9G7j17y0mjZhl2LchdhUdfXsCMHP8AuZ9Ph27UiVJ3L6bHfr5x5Z/vpLFy+fzVs92JF/SMrJ//qvkPm3iY3bh5deMbfs3cvPmLSYOn2nYFxa3ivY+Ot3Txy1gwZIZ2NmVZEfsbhK26W4aln2+ks++nU/nnu1JvpTC8H7K6B43fQEHDh/j2rUMmnfoxZB+b5Odreu4HNSxNZ5NG5K45wABXftSys6O2ZNGAeBYxoGBfbrTrf8IAAa92+OBiwY9bXJycpg/6RO+Cl6MlbU1G4MjOPPHOYaM789vR06REL2TDb9EMHfpNML3hJJxLYPxA3WrB3br25lKVV5kwKg+DBjVB4DB3UYVeW8vY+JjduLt507sgTBu3bzFB8NnGPaFxwXT1kc3JHLauHl8tGQmJe1KkrB9N/H6eJmx4ANsS9qwcu1XgG4xkqlj5xWp5pycHBZOWsyS4I+xtrZi0+rNnD19noHj+nHy6Cl2RO8iLHgzs5ZMYcPuYDKuZTBpkO686jauzTtDe5J9NxspJQsmfsL1q9eLVK+59nkTF/HN6s+wtrZigz5e3h//Hr8dPUV8VCLrfwln/tLpRO5dw/VrGYwbmLuqadSBDdg7PIeNrQ2+AV4MCBrOWQUWW8jJyWHuxEUsW/05VtZWbAgO58wf5xg6fgC/HT1JXFQi637ZxIKlM9iydy3Xr2UwdmBu77/oAxuwdyhtovuMgouKWGo+B8u9Rj+c9AlfBH+CleEaPcegcf34XX+NbgyOYPaSqYTtXs31axlM1F+j9RrXps/QXmTfzeaevMf8iR9zTcFrFCA2JhGfFh7sOLiZmzdvMXZY7jUYGR9KoHdXACaPncPHS+dgZ1eS+O07idumu8mcMG0kVV+uzL1797h8MZlJY2cXueacnBwWTv6Uz39ZhJW1FeGrIzl7+jwDxvXl5NFTJEbvZlNwJDM/n8y6XavIuJbJ5MEzH35gBbDkeLHU3JiTk8OiyZ/x2S8LsbK2ImL1Fs6dPs97497l1NE/SIzeTXhwJNM/n8SaXavIuJbB1MGzHn5gBXgSn5/54xxbN21jU+JqcrJzmDNhIfcUHGYYG7MD3xYe7Px1C7du3mT0UKPyPWEtrbw6AzBp7Gw++WIOdnZ2xG9LJHZbYkGHVIy4mER8WrgTfzCCmzdvMX5Y7krYm+N1DZ4AU8fOZeHS2djZlSRh+y7i9Xlx/LQRVH25MlKfFyePnVPkmi21znVfu6XeX1iq33Nycpg36WO+Cv4Ua2srI5+/x+9HThIfvZMNv4Qzb+l0IvbodI830r3lwHrs7UtjY1sCX39PBnYboVi8/GcppmHgRYF41uYgEELkoBv6bANkoxuS/Ym+MdIbGCulbCOEWAL4oOtN+TvQB11Pw62AE/ADEAGsA/4F4tD1qrQ3Po7+O5cCB6WUPwghGgJL0PX0vIlu6PW/wBygLboekGlAB+AFIEJKWdPsHGYAWVLKRfr3dugaZOvrz2m0lDJOCNEHaCClHKq3O69/n268Twjxg/571hp9R5b+XATwERCArjfpHCllSD7nGK9/f9DMj07AF0B1dA3bO6SUgx70G73m0vDZCppH5N4zFuuPym8nQ4tbQqFpULNXcUsoFFnZyvSyKgpesCld3BIKza17yi7M9LRQYqXQoiJHWmaF5u694nn6+zRwtHmuuCUUiit3LHeol6bks7HIXmHILqaeDk/KbQvN5wAO1qWKW0KhyMwppjk2nwLX7954uNEzio14WD+ZZ5PSJSwzzgGsxTM/qDRfLLXOBWCl4HoJT5tjKXssV/xT5mb8d0Vy01LKu6/iPn7mGjJVnn3UhkxlURsylUdtyCwe1IZM5bHUSrXakKk8akNm8aA2ZCqP2pCpPGpDpvKoDZnKY6l1LlAbMv8r3Iz7tmgaMn36K+5jy8wCKioqKioqKioqKioqKioqKioqKv+veKbnyFRRUVFRUVFRUVFRUVFRUVFRUVF5Av5Dc2SqDZkqKioqKioqKioqKioqKioqKir/VSx4egNz1KHlKioqKioqKioqKioqKioqKioqKs88ao9Mlccm8LlqxS2hUIRlnS5uCYXCUhfMATh44ufillAoXv5fh+KWUGjuyOzillBonrMuWdwSCoVLCfvillBo/riZUtwSCsWrpTTFLaHQnPo3qbglFIpG9lWKW0KhOfLvpeKWUGiy71lmTrexsiluCYXmprhT3BIKxRt2FYpbQqHZmX2muCUUGktdNMfJxnLrLjkWuoDrPQteHNLGQhdYUjHjPzS0XI1IFRUVFRUVFRUVFRUVFRUVFRUVlWcetUemioqKioqKioqKioqKioqKiorKfxV1jkwVFRUVFRUVFRUVFRUVFRUVFRUVFeVQe2SqqKioqKioqKioqKioqKioqKj8V1HnyFRReTxe86rDhO2fMCn+U3wHt8uz36tfIONjFjF2y4cMWjWFFyo4GfYNWDmBucdW0G/FeCUlmzBt3jhi94exOSGE12u/lq9NzTrVidwRQuz+MKbNG2fYPmHGSKL3rGNzQghfrVyEQxnlJtd+06cxYTuDCd8TSt+hb+fZb2Nrw0ffzCJ8Tyg/Ry6nfEVXAJp4NiQ46jvWxv1EcNR3NGpWXzHNAFPmfYJn62506DUo3/1SSuYt/oqArn3p2Hswv//xl2FfWGQMgUH9CAzqR1hkjFKSTZgx/wMSDkSwdcdaataunq9NzTrViUpcR8KBCGbM/8CwfczE99m6Yy2R8aH8tPZrXFydFdHczKcJm3auJmLPmgfEymwi9qxhVeS3JrGyOup71sX9zOqo7xWPFYAm3o1Yk/gT63atovfQHnn229jaMPfr6azbtYrvIr7C7UVXk/2aCi7E/7mFnoOClJIMwBte9fk67huW7VhO5yFd8ux/vdHrfLr5M8LObqJZYDOTfb6dm7MsYRnLEpbh27m5UpJNmDpvHNv2byQ8fjU1CsiLr9d+jYiEELbt38hUo7zo386PyMRQ/tAeoGad/K+RoqK+d32Wxy9nReIKuuTjdxtbGyZ8OYEViStYvGkxLi+6AFDCpgSjPh7FlzFf8kXUF9RqUktR3QDT539A3IFwtuxY88CyaEviWuIOhDPdKLeMnvg+W3asYXN8CD8qmFsA6nrV47PYL1mS8DUdBr+VZ3/1RjX4cPMnrD6zniaBbxq2O1Vw5sOIj1kYuZhPYpbQoqe/YprvY6lxDk8WLxNnjGLb3o1s2bGGr39cjEMZB6VkAzBl3lhi9m9gU3wwNWr/L1+b12u/RnjCamL2b2DKvLGG7f7tmrM5MYRT2v2K+t1S61wAtbzq8VHsEhYlfEGbwR3z7P9foxrM3ryIH86soWFgU5N9K8+uYU7kx8yJ/JhR305USrIBS82LzXyaEL4rhMi9a+g3LP94WbRsDpF71/DLlhWUr+gGgOMLZfhu/RfsPxvLpHljFNN7n0beDfkx4XtW7VxJj/e75dlvY2vDtC+nsGrnSr4MX4Lri7rF+fw6+vJt1NeGV+yFaF6uoewCso28G7Jqxw8E7/yRngVon/HVFIJ3/sg34UsN2gGqVa/KV5uW8GPsCn7YthzbksouaNbYuyHBO1YSsvMner3fPc9+G1sbZn01lZCdP7Es/AuDdtcXNcT+tYUfopfxQ/Qyxi0YqahuS46X/yT37hXNqxhQGzKLACFEjhDiiNFrQj423kKIiKf8vd5CiDeN3g8SQvR+mt9RGISVoNOsvizrs4APW4zhjXbN0LxsurLi5d/Ps7jtJBYFfMCxLftoM7GnYV/cNxGsGvWF0rINePs1o3LVSvg2as/k0XOYtTD/StqshROZPHouvo3aU7lqJbya636KnfF7CXDvSmuvIM6ducDgkX0V0W1lZcWk+WMZ0mMMHT174N/Rj6qvVjax6dijLRnXMmnbtCs/fxPCyClDALh29TrDe4+ns8/bTB0xh7lLpymi+T4dAlvw9SdzCtyfuOcAFy4lERmyghnjhzN70VIArmdk8tX3vxC8/FOCl3/KV9//wvWMTKVkA+Dj506Vqi/h1bANE0fPYs6iKfnazV00hYmjZuLVsA1Vqr6Ed3N3AL5Z+gP+np0J9O7K9ugdjBg7sMg162JlDIN7jKaDZ3cCOrbIEyud9LHSpmkXfvpmNSOnvA/oYmVY73G85dOLKSNmM3fp9CLXa659/LyRjOg5niDvd2jVvjlVXnnJxKZd99ZkXsvkrWY9CV6+hqFTTH06asZQ9sTuV1I2VlZWDJ4zmOnvTGdI88F4tfOk4isVTWzSktL4dMxiEsLiTbbbO9rTY2QPRrcbzah2o+kxsgelHZVdfdTLrxkvVa2IX6MOTB0zh1kf5Z8XZy6cyJQxc/Br1IGXqlbEJby6uAAAIABJREFUU58X/zz5F+/3GceBPYeUlI2VlRXvz3mfqb2nMtB3IN7tvan0SiUTm5bdWpJ1LYt+Hv3Y+O1G+k7S5Wz/HrpGtCEthjCpxyTem/oeQgjFtHv7uVO5aiV8GrZ9YG6Zs2gKk0bNwqdhW31ZpGsEX7b0BwI8u9DaO4jY6B0MVyC3gM7n/WYPZO47MxnlN5Rm7Tx40SzW05PS+WLMZ+wM22Gy/VrqP0zu9AHjAkcxqf04OgzuxAsuZRXRDZYb5/Dk8bIzfi+tmr1FgGcXzp35myGj+imm3cuvGZWrVqRFo45MHTOXmQ/w+9Qxc2nRqCOVTfx+hqF9xnNgz2HFNFtynUtYWfHO7PdY+M4cPvAbQdN2HpR/5UUTmytJaSwbs4Q9YYl5Pn/n1h2mBI5hSuAYFvefr5RswLLz4pQFYxncYxTtPLoT2LFlPvWudmRcyyCwSRd++iaY0VN19a47t++wZMEyFs1YoohWc90j5gzjg7cn8Y5PP3zb+/CSWRka2C2ArOuZ9HR/h7XL1zFg0nsAbNsQS/9Wg+jfahBzR3xIykUtf/2u3Gr1VlZWjJ47nLG9JvK2T1/8OvhS2ay+2Lp7AJnXs+ju3pvQ5esYNFmn3draiqmfT2TRhMX09u3H8C5jyL6bo6j2MXNHMKbXBHr6vJuv9jbdA8i8nkmQ+9uELF/LkMkDDPsu/51En5YD6NNyAAsnfKqobkuNF5VnH7Uhs2i4KaWsa/RaoND3egOGhkwp5ddSyh8V+u4CqVT3ZdL/TuHqxVRy7uZwOHw3NVs2MLH5a8/v3L11B4C/D//J8665Nyp/7j7B7Ru3FNVsjF+ANxtCdW3OR349ThlHB5w1TiY2zhon7B1Kc/jgMQA2hEbQItAH0N0M5OToCrsjB4/jWt5FEd0169Xg4rlLXL6QRPbdbLZu3IZ3Kw8TG59WHmwK3QJATEQcjdx1v8upE6dJ06YD8Neps9iWtMXGVrknjw3q1sLxAb0/4nbupZ1/c4QQ1KlZnczMLNLSr7Jr3680bVgPxzIOOJZxoGnDeuza96tiugFaBPiwLiQcgMMHj1HG0QEXs3hx0Thh72DPIX28rAsJp6U+XrIybxjsnnuuFFIBzTXr1eCCWaz4tPI0sfFu5cGm0EhAFyuNC4iVkgrHyuv1qnPp/GWSLiSTfTeb6LBYPFu5m9h4tWrG5jVRAMRGJNDQ/Y3cff7uXL6QxNnT5xTTDPBq3VdJPp+E9kIK2Xez2RG+gyYtm5jYpF5K5fyp89y7ZxoFb3jV53DiYbKuZ3HjehaHEw9T30vZHjx+/l5sDNkMwJFfT+DgaF9AXrTnyMHjAGwM2UyLAG8Azvx5nnNn/lZUM+j8nnQ+iRS93xM2JeTxe9OWTdm2dhsAiZsTqdusLgCVXqnEkZ1HALh+5To3Mm7wSp1XFNPeIsCH9frccuTgo5VF60PCaRnoC5jmllLP2SEVyS7wct1XSDmfQupFLdl3s9kVnkiDFo1MbNIupXLh1N9Is6f62Xezyb6TDUAJWxusrJSttlpqnMOTx0ti/B5D3eXwwWO4uilTdwFo7u/FhhBdeXP01xM4ODrgrClnpr0c9g6lDX7fEBKJXzH63ZLrXNXqvoz2fDJpF7Xk3M1mb/hO6ptdo+mX0riYzzVa3FhqXqz1hq7edelvXbxs2RiDr79pvcvX34Mwfb0rOjy33nXz31sc3n+U27fvKKLVmNfq/o/L55NI1te5YsPiadbSdMRIs5ZvsnVNNAAJm3dQ371enuM0b+/D9rBYRTTfp3q917h8/rJB+/awONxbvWli42GkPX5zAvX19cWGXg04c/IsZ34/C0DGPxncU/BaqF7vNZO67vawWDzyaG9GZD7aixNLjpf/LPJe0byKAbUhU0GEEP5CiFNCiJ1AJ6PtM4QQY43enxBCVNb/31sIcUwIcVQI8ZN+W1shxD4hxGEhxDYhhEZvPwgYpe8F6mF8XCFEXSHEXv2xNgghXtBvjxdCfCiE2C+EOC2EMK11PQUcNWW5lnTF8P5a8lUcNQX3qGjc1YeT8UeetoxCo3FzIemy1vA+JSkVVzfToSeubs6kJKUa3icnpaLJp9LfuWd7ErbvLjqxRri4OZOSlKs7NTkNjZluY5ucnByyMm/wfFlHExu/Nj6cOnGau3fuFr3oR0SbdgVXl9yKqsbFCW1aOtq0dFxdcs9R46zbriSubi4kXU4xvE9J0uaJBY2bi8lvk5ykNblJHDd5GHuORdOhc2s+mV/0vZE1bs5ojeJXm5yKi1ms6GyMYyUrT6y0KIZYcXZ1MtGempyGs5tTgTY5OTlkZdzAsawjdqXs6D2kB99+vFIxvfcp51qOtKTc2ExPTqec2Y36gz6bnpRmeH8lOZ1yro/22aeFxs2F5CTTvKgxG5KncTXNQSnJea8FpXFydSLNyHfp+fhO51/db3Mv5x7/Zv5LmRfKcO73czRt2RQrays0FTW8XOtlnN2UG4aocXMh+XLBeQN0+cf0dzH1+djJQ9l1LIr2nVuzeP6XRS8aKOtajivJubF+NfnKY8VrOTcnFm39jK/3rmDj1+v5J/VqUcjMF0uNc3g68XKfrj06kLB9V9GJNUPj5kxKUm45qk3SonE1K0ddTctRbbI2Tx1HSSy5zvWCazmuJufW068mX+EF10fv+WxT0paZ4R8xfcMC6rds9PAPPEUsNS+6uJreN2iTUvMMa3dxcybl8oPrXUrj7OZEWnKu7rSUNJzdzB4yuJYjLVlXzubk3NPVuV4oY2Lj09ab2LC4ohdsosuJVKPyPy05DSdX0/qik6sTqYb64j1u6LVXrPoiEsnHqxawYuvX9Bis7FREzka6AFKT03E2ixfnArQDuFVy5fuob1i6djF1Gik3LY4lx4vKs4/akFk0lDIbWh4khLADlgNtAQ/A9cGHACHE68BkwFdKWQcYod+1E2gipawHrAbGSynPA18Di/W9QM3HfvwIfCClrA0cB4zHf5aQUjYCRpptfyrkN/JOyvyfeNbv4E7F2lWJWxb+tGUUmvz1P9zI/ByHjOpHTnY2YWsin6K6gnkUvz/Mptr/qjByyhBmj/voact7IvKLHyFE3t9Fv11J8vu+vH7Pzyb3/4Vzl9C0dks2rt3MO/3zzoPz1HkEzQ+zuR8rs8Z9+NTlPYh8f9880vO/iAeMe5fg5Wu4+e/NohH3IB4SA4/50Uf/8FOi8HGurM485Os7c5P8dUeFRJGeks7nmz9n4IyBnPz1pKHHmhI8Wk5/cIG1aO5SmtVuRdjazfTun3euKqV4nDi4kpzOWP8RDPMchPdbPjg6KXcjb7FxztOJF4D3R/cnOyeHjWs2P015D8QS/W7Jda4nLVJGNh3A9Lbj+XL4YnpO64tLJc3DP/SUsNS8mG/8mtsUUBYVL49Qd3lI/aZ6vde4fes25/44/3SlPYxHCPSCfhdra2tqNazJrKHzGNJhBB4B7vn2HCwqCp0TgSupV+nUqDvvthrIkplfMv2LyTxn/1xRSTXDguPlv4o6R6bKQzAfWh4CvAack1L+KXWZ5+dHOI4vsFZKmQ4gpbzfDeFFIEoIcRwYB7z+oIMIIRyB56WUCfpNKwHj8Qvr9X9/BSoXcIwBQoiDQoiDxzIfb36KaylXeb587tOX593KkpH6Tx67V5rVxG9oR1b0X0iOfihZcdGrb1fC44IJjwsmNSWN8hVyK2Wu5V3QpqSZ2KckpZoMGXcr70KqkU2noDb4tPRg1KD85+4pCrRJabiWz9Xt4uZMakp6gTbW1tbYO5Tm+j8ZBvvF381nyrBZXPr7smK6HwVXFydSUnPPRZuajotTOf32XL9r03Tbi5re/YKIjA8lMj4UbUoa5SvkPqdwLa8xiQXQ9QYw/m3cymvQpqRiTtjaSALa+hWdcD3apFQ0RvGrcXMhLU+spKIxiRV7Q6xo3JxZ/N0CJg+brXispCanmWh3cXPOo93YxtraGvsyujivWa8GQ6cMZOO+1XTr35k+w3rR5d28ixwUBVeS03Eun9sTwMnNiaupVx7wiVzSk6/gVD73SXw5NyeuaIu+l1rPvl3YFPcLm+J+QZuShlt507yYqjX1e0pyqkmcu7rlvRaUJj05HWcj3zm5OXFFa+r39JR0nPS/jZW1Fc85PEfmtUzu5dxj2cxlDPUfyqx+syhdpjRJ55KKVO/b/YLYHB/C5vgQUlPScKtgnjdM/ZmcpDX7XfLaAGxauwV/BXILwNWUK5Qz6iVd1q0cVwsRr/+kXuXi6YtUb/TAKs8TY8lx/rTjpVO3tvi29GTkwKJfwKVn3y6Exa0iLG4VqSlpuJbPLUc15TWkas3K0WTTclTjpslTx1ESS65zXU25QlmjXlJl3cpx7TGu0Wv6On3aRS2n9p7gpZpVn7pGY/4LeVGbbHrfoCnvQpqZJm1yKq4V8q93FRdpyWk4G/VmdXZ1Jj3liplNumG0grW1FfZlSpNxLVe3bzsftm9UfphwWnI6Lkblv7ObM+lac+1puBjqi1aULlOajH8ySEtO5+jeY1z/J4Pbt26zN3Yfr9ZUbmqZVCNdAC5uTqRr89Z189N+985dMvRx88fxP7l8PolKVU3nwC0qLDle/rOoQ8tVCklBj9GyMf0t7PR/RQGfWQIslVLWAgYa2ReW2/q/OUCJ/AyklMuklA2klA1qOzzeimEXj57BubIrZV90xtrGmnpt3+REjOm8hRVer0yXee+xov9Csq4UbyEN8PN3obT16U5bn+5ER8bTsWsbAOrWr0VmRpZhLqP7pGnTuZH1L3Xr67rrd+zahm1b4gHw9H2TAcP7MLDXSG7dVG6uz9+OnKRS1RepUMmNEjYl8O/gR0L0ThOb+OhE2nUNAHTDgvfv0v0uDmXsWfrzIj6b9zVHDhxXTPOj4u3ehE1btyOl5OiJk9jbl8bZqSzNGtdn9/5DXM/I5HpGJrv3H6JZ46KfO/DHFSEEencl0Lsr0ZGxvBXUFoB6DWqTmZGZ58Y3VZvOjawb1GtQG4C3gtoSs0U3ZKJy1dxJsFsEeHPmz6Kfu/G3Iyd5qWpFk1iJjzbt1B0fvZN2XQN1uvLEysd8Pu8rjhw4VuRazfn9yCkqVnmR8hVdKWFTgpbtfUmMNh0CuSN6F627tALAt40XB3fqFoAY0HEYHRp3o0Pjbqz+di0/LPmZNd9vUET36aOnKV+lApqKGkrYlMCzrSf7YvY90mcPJfxKPY96lHa0p7SjPfU86nEooejngl313Rra+fSgnU8Ptm2Jp0NQawDq1q/5gLx4g7r1awLQIag127Ym5Dmukpw+eprylcsb/O7Vzou9MXtNbPbG7MWvs+5m1qO1B0d3HQWgpF1JSpYqCUA9j3rk5ORw4c8LRar3pxUhtPYOorV3ENGRcXTS55a6DQoui7KyblC3ga4s6lRAbvEL8OasArkF4K+jf+JWxQ2Xii6UsClBs7YeHIx5tMW1yrqWw7akLQCly5Tmfw1eI+lM0TbyWHKcP8148fR9k0HD3+W9niMUqbus+m4N7X160t6nJ9u2xNMxSFfe1Klfk6yMLNLMGxy0V7iRdYM6er93DApkezHmF0uuc509+heuVdxwruiCtU0JmrR151DMgUf67HNlSlPCVnfrYP+CA680eI3Lf14sSrn/ibx44vBJKhnVuwI6tCAuyrTeFReVSHt9vatlWx/27TyoiLYH8cfRP3ixSgVc9XUu3/be7I4xnTJrd8xu/Lu0BMCrtSeHduVOFyaEwLuNJ7Gb4pWUDcCpI6d4sUoF3PTam7f3YWe0qfad0XsM2r1be3Fol66+uC/hANWqV6WkXUmsra2o26Q25/9Ubh7evNp92Rm9x0z7bgKNtP+q1/58WUfD/NLlK7lRscqLXL6QrIhuS44XlWcfUfxd1P97CCGypJT2ZtvsgNOAj5TyjBAiGHCQUrYRQvQC2kgpuwkh3gAOANWA0sAGoKmU8ooQoqyU8qoQ4jDQX0r5qxDie6CKlNJbCDEGKCOlnK7/zhlAlpRykRDiKDBUSpmo3+4opRwlhIgHxkopDwohnICDUsrKDzq/0ZW7PXbQVPeuS/tp72BlbcX+0Di2fbER/1FduHj8LL9t+5VBP0/G7X8VyUi7BsA/l9P57r1FAAwNnYFLtfKULG3HjX8yCfngG/7Y8fgNJmFZpx/7M/eZ8eEEPH2bcuvmLT4YPoPjR04CEB4XTFsf3dDfWnWr89GSmZS0K0nC9t3MnKAbYhu7Pwzbkjb8c/U6oFswaOrYeY/83fYlCt9O7d68KeNnjcDK2pqNwRF8+9lKhozvz29HTpEQvRPbkrbMXTqN12q+Ssa1DMYPnMblC0m8N7IP/Ya/zd9ncyujg7uN4mp63p60D+LgiUfpeJyXcdMXcODwMa5dy6Bc2ecZ0u9tsrN1vXSDOrZGSsncT75k596DlLKzY/akUdSs/ioA6yOiWP5jCAAD3ulGx9YtH/v7X/5fh0Lpvs/sjybh5duMmzdvMXbYVI4f+R2AyPhQAr27AlCrbg0+XjoHO7uSxG/fybQPdCt9fv3DJ1R9uTL37t3j8sVkJo2djTY5b2/NgnC0KV0ozbpYGYm1tRUbgyNY/tlKhox/j9+PnCReHyvzlk7ntZqvcv1aBuMHTjXESv/hvU1iZVC3kY8dKwB2VraF0v6mb2NGzxyGlbUV4asj+f7znxkwri8nj54iMXo3tiVtmfn5ZF6t+TIZ1zKZPHgmSWaVuPfG9OHfGzdZ9XXIY3+/S4nCrRjewKcB700fgJW1FTEhMYQuDaHn6F78efxP9sfs45XarzB5+RTsHe25c/sO/6T9w/t+ulVuW3RtQZehulgKXRLCtjXbCqXhj5spDzcqgOkffoCnz5vcvHmLCcNncOKoLi9uivuFdj49AKhZpzofLpmBnZ0dCbG7mDVBN2SyRaAP0+aPo2y5F8i4nsnJ307Tt+vQR/7ul+0KPwdhQ5+GDJgxAGtra6JDolm9ZDVvj3mb08dOsy9mHzYlbRj36Tiq1axG5rVMFry/gJQLKbi86MLcn+dy7949rqRc4dNxn5J6+dGvzfuc+rfwvThnfTQRT31uGT9smiG3bI7X3diDLrcsXDobO7uSJGzfxXR9bvnyh4+p+nJlpD63TB4757FySwP7yoXWXc+nPn2m9cPK2oq40O2sX7qGoNE9OHPsLw5u20+12i8zbtlESjvac/f2Ha6lXWN0i2HUdq9D7yl9kVIihGDrys1sC45+7O8/8u+lQmsvzjgHyL5X+BEqTxIvcQfCsS1py7WrunrZ4YPHmTJ2ziN/t43Vky1WM/3D8Xjo/T5x+EyD38PiVtHepyeg8/uCJTOwsyvJjtjdRn73ZqqZ3/t1HfbI313KunBlUXHXuWqXfOisVQVSx+cNek7ri5W1FTtCt7Np6To6je7GuWNnOLztAFVqv8zIZR9Q2rE0d27f5XraP0xsMZJX6v+Pd+cNQt6TCCtB1HcRJIRsf+zv35lV+NWIizMvApQuUapQuj2aN+WD2aOwtrZiQ3AEyz79gffHv8dvR08RH5WIbUlb5i+dTvVaunrXuIFTufS3rvyIOrABe4fnsLG1IeN6FgOChnP29PnH+n4nm8LVXRr7NmLojCFYWVmxJWQrPy/5hXfHvsMfR0+zO2YPtiVtmPTZBF7R17lmDZlLsr7OVbdpHQZM7M+Qdo9+PeZHTiHbL5r4NmL4zPexsrJic8gWfvr8F/qN7cOpo3+wS699yucTeeV1nfYZQ+YYtLfs5Eevod2RUrI3dj9fzV322N9/7wkWk2rq25jhM4dgbWVNRMgWfvx8Ff3H9uHU0dPsjNmNbUkbpn4+iVf12qcPmU3ShWS8Az3oP/ZdsnNyuJdzjxUf/8CumD0P/0IzbETh+r89C/ESf2mbsvOMPcPc3LCgSBr/SnWcoLiP1YbMIkAIkYNuHsr7bJVSThBC+AOfAuno5rmsqW/ILAWEAS7oGjHdgQAp5XkhxDvoho/nAIellH2EEO2BxcBlYC/QUN+Q+SqwFrgHDAOak9uQWRfdHJrPAWeBd6WU/yjVkPks8CQNmcXJkzRkFjeFbcgsbp60IbM4KWxD5rNAYRsyi5vCNmQ+CzxJQ2Zx8iQNmcXNkzRkFidP0pBZ3DxJQ2Zx8yQNmcXJkzZkFieFbcgsbp6kIbO4eZKGzOKmsA2ZxU1hGzKfBQrbkFncPElDZnFT2IbMZwG1ITOX/1JDZr7DiFWeDCmldQHbt6KbK9N8+00g325jUsqV6Oa0NN4Whq7h09z2NFDbaFOi0b4jQJN8PuNt9H86BcyRqaKioqKioqKioqKioqKioqJigRTTfJZFgdqQqaKioqKioqKioqKioqKioqKi8l+lmFYYLwost4+wioqKioqKioqKioqKioqKioqKyv8b1B6ZKioqKioqKioqKioqKioqKioq/1XUHpkqKioqKioqKioqKioqKioqKioqKvkjhPAXQvwhhPhLCDEhn/2VhBBxQojDQohjQojAhx1T7ZGp8thE3zxf3BIKhaWu/p2Vfau4JRQaS139+68/Nha3hEJT8eXWxS2h0JSx0BXXM7NvFreEQiOwzIUcz9xKK24JhcappGNxSygUJ29pi1tCobmdc6e4JRQaISzzGrWxynfdS4vgjoWuFH/g5sXillBohAWviGxrZZm309o7GcUtodBYqs+lBa9afivnbnFLUHkaSOVjUAhhDXwBtAAuAQeEEJuklL8bmU0BQqWUXwkhagCRPGQRasstNVRUVFRUVFRUVFRUVFRUVFRUVFSeRRoBf0kpz0op7wCrgfZmNhIoo//fEUh62EEt83GGioqKioqKioqKioqKioqKioqKysMpojkyhRADgAFGm5ZJKZfp/68AGA8ZuAQ0NjvEDCBaCDEMKA34Pew71YZMFRUVFRUVFRUVFRUVFRUVFRWV/ypF1JCpb7RcVsDu/ObIMR/j3h34QUr5sRCiKfCTEKKmlLJAwerQchUVFRUVFRUVFRUVFRUVFRUVFZWnySWgotH7F8k7dLwfEAogpdwD2AFODzqo2pCpogjNfJoQviuEyL1r6Dfs7Tz7bWxtWLRsDpF71/DLlhWUr+gGgOMLZfhu/RfsPxvLpHljlJYNwJs+jQnbGUz4nlD6Ds1f+0ffzCJ8Tyg/Ry6nfEVXAJp4NiQ46jvWxv1EcNR3NGpWX2npAEybN47Y/WFsTgjh9dqv5WtTs051IneEELs/jGnzxhm2T5gxkug969icEMJXKxfhUMZeKdnMmP8BCQci2LpjLTVrV8/Xpmad6kQlriPhQAQz5n9g2D5m4vts3bGWyPhQflr7NS6uzoponjLvEzxbd6NDr0H57pdSMm/xVwR07UvH3oP5/Y+/DPvCImMIDOpHYFA/wiJjFNFrzpwPJ7Hn0FZid22kVp0a+drUrlODuF1h7Dm0lTkfTjJsHzvhfQ7/Hs+2xPVsS1xP8xaeSskGYMq8scTs38Cm+GBq1P5fvjav136N8ITVxOzfwJR5Yw3b/ds1Z3NiCKe0+6lZJ/9YKyrcfZoQuXsNW/eto/+w3nn229ja8MmyuWzdt47VW74z5EaA94a/w9Z964jcvYZmPk2UlA1Yrs/BMrU39W7E2sSfWb/rF94Z2jPPfhtbG+Z9PYP1u37h+4ivcXvR1WS/poILCX9updegbkpJNmDJdYCZ8yew4+BmohLXFVgW1apTg+id69lxcDMz5+cuxjlm0lCiEtexJWENP6/7Bo1CZdF9LLEcBV1ejNgVypa9awvMi4uWzWHL3rUEm8XL9+u/5MDZOCYbXbNKYcn5HGDy3DFE7VtPWPwv1KhVcF7cFB9M1L71TJ6be006Pl+GFWuWsnXvOlasWUoZRwelZDNt3nhi94cR+ZB67pYdofp67njD9gkzRhKzZz2RCSF8tfJjReu5b/o0Zn3iL4TtXk2fob3y7LextWHB1zMJ272alZuXGXL663WrExzzPcEx37N62w/4BChb3wLLjXVLvqdr5tOETTtXE7FnzQO0zyZizxpWRX5ron111Pesi/uZ1VHfF4v2J6lzOT5fhu/XfEH0vvV8v+YLRXPLfxJ5r2heD+YA8IoQoooQwhboBmwys7kANAcQQlRH15D5wJU9H7shUwiRI4Q4YvTKs3z6Ix5nkBAib+Z7hhBCPC+EGGL03koI8bkQ4oQQ4rgQ4oAQospDjjFSCPGc0ftIIcTzD7D3EEL8pvdtqcfU20G/ytP997OEEA+dX6CosbKyYsqCsQzuMYp2Ht0J7NiSqq9WNrHp1KMdGdcyCGzShZ++CWb01PcBuHP7DksWLGPRjCXFoFynfdL8sQzpMYaOnj3w7+iXR3vHHm3JuJZJ26Zd+fmbEEZO0YXMtavXGd57PJ193mbqiDnMXTpNcf3efs2oXLUSvo3aM3n0HGYtnJiv3ayFE5k8ei6+jdpTuWolvJq/CcDO+L0EuHeltVcQ585cYPDIvoro9vFzp0rVl/Bq2IaJo2cxZ9GUfO3mLprCxFEz8WrYhipVX8K7uTsA3yz9AX/PzgR6d2V79A5GjB2oiO4OgS34+pM5Be5P3HOAC5eSiAxZwYzxw5m9aCkA1zMy+er7Xwhe/inByz/lq+9/4XpGpiKa79O8hSdVq75E0zf8GTtiOh9+nH+8fvjJdMaOnE7TN/ypWvUlfP08DPuWfbkSP49O+Hl0YnvMDqWk4+XXjMpVK9KiUUemjpnLzI/yj/OZCycydcxcWjTqSOWqFfHUx/mfJ88wtM94Duw5rJhm0OWXqR+OZ0D3EbR1D6J1p1ZUe9W0SOncsx3Xr2fi3/gtfvwmmLFThwJQ7dUqBHZsSVuPbrzXbQTTPhyPlZVyzyYt1edgmdqtrKwYP28UI3qOo6t3b1q2b06VV14ysWnfvTUZ1zLp1KwHvywPZdgU0wcqo2cMY3fsPsU038eS6wA+fh5UrvYSng1aM2HUTOZ+XHBZNGFHw7wJAAAgAElEQVTUTDwbtKZytZfw9tOXRUu+p5XHWwR4dWF7VAIjxuX/kKtotFtmOWplZcXkBeMY1GMk7Ty6EdixZZ68+FaPdmRcyySgSWd+/Ga1Wbx8w8IZnyui1Vy3peZzAM/mb/JS1Uq0atyJaWPmMf2j/G/vpn80gWlj59GqcSdeqloJD19dXnxv+Dvs3XEA/yZvsXfHAd4b/o4iur393A313Emj5zB74aR87WYvnMSk0XOM6rnNAF0919+9C4FeQZw/8zdDFKrnWllZ8cG80QzrOZa3vHrh38GPKmZ5sUP3NmRcz6T9m91YtSyEEVMGA3Dmj7P08u9P9xbvMrTHGCZ/NA5ra2tFdN/Xbomxbsn3dDrtYxjcYzQdPLsT0LFFPuWoTnubpl346ZvVjJzyvkH7sN7jeMunF1NGzGbu0umKan/SOteA4X3Yk7iflo07sSdxPwOG91FQvcrTQEqZDQwFooCT6FYn/03fVtVObzYGeE8IcRQIBvpI+eAl1guTOW5KKesavRYU4hhIKb+WUv5ovl0I8SzN2/k8MMTofRBQHqgtpawFdASuPeQYIwFDQ6aUMlBK+aDP9AQW6X178zH1dgAMDZlSymlSym2PeYynTq03anDh3CUu/Z1E9t1stmyMwdff9Omhr78HYaGRAESHx9HYvQEAN/+9xeH9R7l9+47iugFq1qvBxXOXuHxBp33rxm14t/IwsfFp5cGm0C0AxETE0Uiv/dSJ06Rp0wH469RZbEvaYmNro6h+vwBvNoRGAHDk1+OUcXTAWWPaS9tZ44S9Q2kOHzwGwIbQCFoE+gC6Cl5OTo7u8weP41reRRHdLQJ8WBcSDsDhg8co4+iAi5luF40T9g72HNLrXhcSTku97qzMGwa7554rlWcSjqKiQd1aOJYp+Elh3M69tPNvjhCCOjWrk5mZRVr6VXbt+5WmDevhWMYBxzIONG1Yj137flVItY5Wgb6Erg4D4NDBo5RxLIOLxrQHjovGGXsHe349cASA0NVh+LdurqjO/Gju78WGEF3+OPrrCRwcHXDWlDOxcdaUw96hNEcOHgdgQ0gkfgHeAJz58zznzvytqGaA2m+8bsiNd+9mE7khOp/c6EVYyGYAosJjaeLRUL/dk8gN0dy9c5fLF5K4cO4Std94XTHtlupzsEztr9erzsXzl7l8IZnsu9nEhG3Hq5W7iY1nK3c2r9kKQGxEAg3d3zDs8/J35/KFJM6ePq+kbMCy6wAtA31Yt1rXaeDwwWOUKfOAsujAUQDWrd5Eq0BfIJ+y6MF18qeKpZajtd7Q1bsMeXFjDD554sWTsFBdXowOj6WJuy4v3vz3Fof2H+VOMcSLJedzgOYBXgafHv31hK6+6GKWF11M82JY6Gb8Ar10n/f3YmOIrr65MSTCkC+LGr8Ar0LWc3X6jOu5hw8ex7W8RhHdNetV59L53PuLqLBteJvldG9/dyL09xfbI+Jp6KHrSXfr5m2DZtuStormFbDcWLfke7qa9XTlqLF2n1amPvdu5cEmfTkaE5FbjpprL6mw9ietczUP8GKDPrdsCInAT3/tqhSSe/eK5vUQpJSRUspXpZTVpJRz9dumSSk36f//XUrZTEpZR98OFv2wYz61RyBCiPNCiJlCiEP63oqv6XswnjfugSiE+EsIoRFCzBBCjNVvixdCzBNCJAAjhBAvCSG2CyGO6f9W0tv9oO8RuVsIcVYI0Vm/3VsIkSCECBVCnBZCLBBC9BRC7Ndrqaa3cxZCrNP3pDwghGim3z5DCPGdXsdZIcRwvdwFQDV978iFgBuQfH/SUSnlJSnlP/pjfCWEOKjvTTlTv204uobPOCFEnJGfnIQQpYUQm4UQR/U9PIOEEP2BrsA0IcQqIYS9/vzv+9SwTL0QorfeP0eFED8JId4E2gEL9Xqr6f1130fNhRCH9cf5TghRsqDf7WnFxH1cXJ1JSUo1vNcmpeYZouTi5kzKZS0AOTk5ZGVm8XxZx6ct5bFxcXMmJUlreJ+anIbGLR/tScbab+TR7tfGh1MnTnP3zt2iF22Exs2FpMu5+lOSUnE10+/qZvr7JCelonHL22DZuWd7ErbvLjqxJppcSLqcYnifkqTNo0nj5mLy2yQnaXE1shk3eRh7jkXToXNrPpn/RdGLfgS0aVdwdcmtYGtcnNCmpaNNS8fVJfd30TjrtiuJm5vGxOfJSSm4mfnczc2FZDOfu7nlVvr7DuhJ7K6NLF46B0fHMkUvWo/GzZmUpFzt2iQtGlezeHE1jRdtsjbPtaw0Lq65eQ9Am5yaR5PG1Zlko9yYqc+NGrPclF9eLUos1edgmdqdXZ3QGpejyWk4m5dFRjY5OTlkZdzAsawjdqXs6D3k/9g787ioqvePvw8EUqGWyTKYpvb9VZa5lEtuCIgboogmqLibWua+r7njVrZoq+VWLoimKKLgAohLiSXutphlymqlgGkFnN8fdxhmhnFDZ2jsvF8vXzL3PnfuZ5557jnPPPfcc7qz9K0VtpRspMt+cwBPnTtpZn2Rp1m76GnWF5nbjJ08lK+O76Rjl3a8ZcO+yF77UQ9P034mIzWz2CP5WrwUxXrOvyBe7Lk9N2hLNc0XLcZLWqapjV7nY24VyMr8DYCszN+oUPFRG6i+k2s086Y2AF3CgkjYvd96Yo1w8yyKYdB+X5h/525GbWdhm14Y5zXrPktkwuesj19J+Pg3DYVNW2CvsW7Pv+k8dG5mOUAm7uY+17mRkXrzfrRlKWm/m5yrolsFsjL0bUvGbzxmo7blvkVK6/wrBUpSyHzQ7NHyUKN9l6SULwAfAmP0Bb8otJGLCCEaAj9LKTOKvy2PSCmbSynfApYAq6SUtYDVgPEzIjqgKRCIVmgspDYwHHge6Ak8JaVsAHwKDNXbvAu8LaWsD3TW7yvkGaA10ACYJoRwAiYAZ/VV4bFoE5C213/ut4QQdY2OnyylrAfUApoLIWpJKd9Dm8jUV0rpa/Z52wCp+qpzTWCHlPJTtPkCxkopw4DrQLDep77AW0LjOWAy4CelrA0Ml1IeMDq2jpTybOGJhBAuwAogVD+S9AHgNSMtJt8b9xghii9UZR7uwsJiVra+w2gJC9KL6bqVzZNPV2PElMHMGrvgXsu7JZa13drI/DMOHtmf/Lw8oiJj7qG6G2MxZor53ZJN0d8L5yymUa1WbN6wjd6vdLvnGkuCpZgWQlhs/y19PmtSYp/rr+YVn62jYZ1WtGgaTEZ6FtPnjCtmay1KHi+l28bcKoZvZIO8+XdhC+zV52Cf2kuqGSkZNLYfa5dGcu3PO33I495gzzmA5f7xdmyKjBbOWcxLz7dkc+Q2+gywXV9kt/2oxSbPTPe/MF7suT0HbisXvK3rwcbcXpwXP85SnpuXl28Hea5mc+LIKbr49KRn2wH0HdoD5zLO1hFqAXuNdbv+TVfi67O49plj599zeTfDHnMuhX1wLx4tjzDa96X+/2+Aqvq/I9AeyQZtYk9je2OMtzcC1uj//hytcFnIZillgZTyFGA8/j9ZSpkmpfwLOAsUDkc9bqTFH1gihEhBK/qVE0IUPge6TUr5l5TyEpBp9t6ANgITeBqYCBQAu4UQhc9VhgghvgWOAM9h9Ij3DTgO+Ash5gshmkkpr1iwEUC4EOIYsAuopNflB2zQa0VK+fstzvU0cE5K+b3+9UrAeDy6pe/NVIgQA/UjTg//fi3TkskNyUjLNHkk2cPLnaz0rOI2lTSXOzo64lrWlSt/ZN/ReaxBRmqWyWMm7jo3MtMv3dBG0/6wQbu7zo23l81lytCZXPjlok009+gXwtb4tWyNX0tmehZelYr0e3q5k2Hm+/RU0+9H5+VOppFNp9BAfFs1Y+SrlufXulf06h9KTMJ6YhLWk5GehVelooUqPL08TDRpujNMvhudlwcZ6cVjM2pDDG3bl/pUsQB4ulckPbMofjIyL+Fe8TH99qLPl5Glbbc2fV/pblicJz0908TnOi9P0s18npqagc7M54WjMy5l/UZBQQFSSlaviqTuC7Wsqj2sXxei4lcTFb+azPQsPL2KtHt4eZCZYRYvaabx4qHzKHYt2xrjdg+00S7F4jwtE51R21i2rCuX/7iiv26NjvVyJ8vKn8eefW7P2kE/csS4H9W5ccm8LzKycXR0xLWc1hc9V7cGQ6e8StTXEXR75WX6DO1Bl76dbKbd3nKAXv27sj0xku2JkWSmZ6Iz64vM+xnzvkizKT4//WYb9EX3Qz+akZZp0s94eLkXz7vSMvGsVBTrZf8FOaO9tecA3ft1YdOe1Wzas5rM9Esmfvf0Kq4/w2wko6eXu6Ht/C3rd8Oj6G7uj/H7pT+sprtnvxCi49cRHb+OjPQsC9eoqe40szzX3KZTaHv8Wnkz8tXJVtNsTqZRDIP2e6Hw8V8TGwttujHnfviFa39e58lnbrpkwz3FHmMd7PM3XZGuTLMcoLjfNBvL/aiHzo23l81j8tBZNtF+L3OuS1m/Gx5Fd/N4jN+s2Lb8JyilR8utwb2eXfcv/f/5aKP+AA4C/xNCuKHN4filpQOBqzfYDqY37/8y+lvcYHuB0esCIy0OQCOjImwlKWWOheON9ZsK0Yqd2/UjNMOBjkJb8GcM0EI/inQb2kpLN/5AWlHxRbSC5lwhhKVZg8MAN+BFKWUdIEP/voLiAxpuxq2Gdln63sz1fiKlrCelrFfhwTubJ/HEkdNUqV6ZSlV0POD0AG07tiQ+NsnEJj42iaCQAABatffl632H7+gc1uJkymmqVH/coL1NR38S4/aZ2CTEJdEhpC2gDdk/tF+b27BsOVeWfPEm74Z/RErycZtp/mLZetr7dqO9bzfiYhIIDgkEoM6Lz5OTnVssUcrKuMTV3D+p8+LzAASHBLJrewIA3n6NGTisD4N6jOD6tetW1b3qswgCfEII8AkhLmYPnUPbA1C3Xi1ysnPINE/wMi5xNfcqdetpBbPOoe3ZuT0egKrVqxjsWrb14ewP56yq/XbxafoSW3bsRkrJ0ROncXV9GLeKFWjS8EUOHPqWK9k5XMnO4cChb2nS0PqrCi7/dI1hcZ4d23YT0lWbveKFerX1PjdNNDIzsriae5UX6tUGIKRrELExewBM5tNsG9iSM6d/sKr21csiCfINI8g3jF3bEwgO1dqP2i/WJDc71/AYSiFZGb9xNfcqtV+sCUBwaAC7dyRaVeOtOH7kFE9Ur0ylKl44OT1AQHArC23jXoJC2wHQur0fX+nbxvjYJAKCW+Hk7ESlKl48Ub0yx749aVW99uxze9YOcCrlDFWqPY5XZa0vahnUgr1xpo9AJsXtp12XNgD4BTYned+3AAwMHkpQw1CCGoay9tMNrFj8BZHLb5SK3XvsLQdY9dk62jbvQtvmXYjdtofOXbV56LW+KPfWfVHXDsTFWOqLfK3eF90P/ahxvDg5PUBAx5bEx5ouHqfFi9Yutmrv96/IGe2tPQdYsyySYL8wgv3C2L09weDT2i/W1PLFTLN2MfM3rub+aWgXg0LasXu71i7uid1Lx1At3+wYGmjV9vLzZesJ9O1KoG9XdsbElzDP1fR5+zVm0LA+DLRBnmvMyZQzVK5W2dCmtw7yJzHWtE1PjN1PoP73RYtAH0Ob7lVZZ1jcR/e4B1WfrELar+nYCnuMdbDP33TG2p8w6kfbdPQnIc7U5wlx++ig70eLa3+L98I/JCX5mE303suca8+ORIL1bUtwaKChzVEorL6wjpRSCiE2AYuA01LK3251DHAAbfTm52jFvH03N79t4tBWTFoIIISoI6VMuYl9DmBYuUMI8QKQLqVMFUI4oD1Gfgwoh1aIvSKE8ADaAglm72HSqwohvIDfpZRfCCFygT4Wzl8eyJRS/iOE8AUKlyjdDWwSQrwtpfxNCFFBPyrTRK8RZ4CqQoj/SSl/RHv03matQH5+PuET3+Tjde/i6OjAprXRnP3uHK+PG8DJo2dIiE3iyzVbmbtkGjFfRXLlcjZjB001HB+bvAnXsg/h5OyEX9vmDAwdZrMFC/Lz85k7aREfrn0bB0dHNuu1Dx73CidTzpAYt49Na6KZs+QNth5cT/blbMYN0mrSXfu9TJVqjzNwZB8GjuwDwGtdR1r1LrU5CTv34ePflD3JUVy/dp3xw6Yb9m2NX0t7X+1RsTfGhrNg8QzKuJQhcfcBEnZpydT0eeNxLuPEyg0fAtpE6lPHhFtd956dSfi2bMbew9u4du06Y4YWxUNMwnoCfEIAmDxmNm8tmY2LSxkSdu8jfpfWVEx4YwTV/1eVgoICLv6axqQxs6yuGWDstHkkHznG5cvZtOjYg8H9e5KXlwdAaHA7vBvVJ+lgMm1D+vGgiwuzJo0EoHy5sgzq042urwwH4NW+3W+6aJA12BWXSIuW3nx1JJZrf15nxOtFK3/uSvoS/2baCK7xo2bw7gdzcXmwDHt2JhlWJ586cww1az6DRPLr+YuMHTHdZtoTdu6nuX8Tdh3azLVr15k4bIZhX1T8aoJ8wwCYNnYe8xZPx8WlDHv3HCBRH+ctA3yYOncsFR57lE/WvMPpk9/TP2SoxXPdS/Lz85k9YSGfRryHg6MDX67Zyo/f/cTQ8QM5kXKa+NgkNqzewvz3Z7Dj641c+SOb0YO0ESM/fvcTO6J2Eb0vgvy8fGaNX0CBDe+I2qvP7VV7fn4+Cya/w3tr3sTR0YEt62L46fufGTS2H6ePfsfeuP1Erd3GjPcm8+X+NWRfzmHya9Otqul2seccQOuLvEn6Jkbri4YUPZmwPTGSts27ADB5zCzeen82Li4uxO/aR/wu7QfmhGkjePJ/VSkokFz8NZWJo23TFxVpt79+ND8/nzkT3+STdVq7uGntVs5+d44h4wZy8qjWLm5cs4V5S6az/asNXLmczZhBRd9LXPImXMs+bBIvZ7+3fhHWnttzgMRd+/H2b0LcoU1c//M6k4bPNOzbtGc1wX5auzhj3DzC35uGy4NlSNp9gL36udOXvreSt5fOpXNYB9IuZDDiFcurnt9r4vV5bnzyFq5fu844ozw3On4dgb5dAZiqz3NdXMqQuHs/Cfo41/JcZ1YZ5blTxsyxuu78/HzmT1rE+2sX4eDowJZ12/jp+3O8OrY/p46eYW/cfjavjWbW4qlEHVjHlcvZTHxV+2x1G9aiz5Ae5P2TR4EsYO7Et7j8u6UH+6yn3R5j3Z5/0+Xn5xM+6S0+XPsOjo4ORtoHcCrlNAlx+9i0ZivhS6YRfVDrR8fp+9Ei7X0ZOLIvAK92HWEz7Xebc33y3kre/XQuL4cFkXYhnWH9bdO23LeU0uhJayDudP4BIUQ+2ijCQnZIKScIIX4G6kkpLwkh6qGtvO2jP6YekIy2jPpK/bbpQK6U8k0hRALanJqH9fuqAsuAikAW0FdKeV4IsQKIllJu0NvlSildhRA++uMD9dsN72e8TwhREXgfqIFWxN0rpXzVWIv++BNAoJTyZyHEGrSC5Xa0AuIcoIz+sx8CBkspr+u1NQR+QhvhuEVKuUIIMRR4HW2RIN9CP6GNxlyINmL0H+A1vV7DZ9Tr3Qo4ASlAE6CtXldvYCzaKMojUso+Qlu8aKn+/C8DU43eqwXwpv5zJ+vP99fNvrcbUdPjJbuctMJR3OsByLYhN892d4jvNXkyr7QllIgfv9tc2hJKTOX/tSttCSWmnNPDpS2hRNhr2wKQL++fhMZeKO/0UGlLKBHX8ktn5fB7QfY/N3vo59+NredLvle4PvBgaUsoMQV2OjebzefVvIf8XWCf+SLAI3aau9hzm+7sYPWxWFbBnq/R6/m2XbD2XvJ91mH77EitwLVPR1klCB98ZZHNfXzHhUyFQhUybYsqZNoeVcgsHVQh0/aoQqbtUYVM26MKmbZHFTJtjz0XSVQh0/bYc5uuCpm2RxUy7w/up0KmfbYCCoVCoVAoFAqFQqFQKBQKheKWyAL7LaabY7/DSBQKhUKhUCgUCoVCoVAoFArFfwY1IlOhUCgUCoVCoVAoFAqFQqG4X7mPFvtRhUyFQqFQKBQKhUKhUCgUCoXifuU+mhtfFTIVd4yTcCxtCf8pHrXTScQB/rbTxX7secGcX3/cVtoSSkyTWn1LW0KJyPjrj9KWUGKy//qztCWUiAou5UpbQon5/e/c0pZQIsrZ8eItLo5lSltCiXGw08V+7HXBHLDfxVv++Mc+2xaAB+z4t8Wf+X+VtoQSYc8LLF23U58X2PFiP452fI0q7k9UIVOhUCgUCoVCoVAoFAqFQqG4X1GL/SgUCoVCoVAoFAqFQqFQKBQKhe1QIzIVCoVCoVAoFAqFQqFQKBSK+5X7aLEfNSJToVAoFAqFQqFQKBQKhUKhUPzrUYVMhU1o7NuQTfvWEnUwgr5DehTb7+TsxLyPZxJ1MIJVMZ+gq+wJQEPv+qyO/Yz18atYHfsZ9Zu8YGvpdq29kW8DNiatZtOBtfQeElZsv5OzE+EfTWfTgbWs2PYxusc17c/VqcHqnctYvXMZa3Ytx6dtM5vqbuL7Elv2rSP6YCT9hvS0qHvBx7OIPhjJ6phP8dL7/CXv+qyLXc7G+C9YF7ucBk1etKnuQmbPn8TBb3ewZ/9mnq/9rEWbWrWfJX5/FAe/3cHs+ZMM28dMeJ0jpxLYlfQlu5K+pEVLb5tonhK+CO92XenY41WL+6WUhL/9IW1D+hHc6zVOffejYV9UzE4CQvsTENqfqJidNtFrzEs+DYhM+pyN+1fTa0j3YvudnJ2Y89E0Nu5fzbLoDw1xXohHJXcSfthO2KuhtpJswvS540lMjmbH3g3UrFXDok3N2jWITdpIYnI00+eON2wfPfF1duzdQEzCej7f8BHunm62ks28hVP55uhu9n0VTa3az1m0qV3nOfZ/vY1vju5m3sKphu2frXyXvQe2sPfAFo6eTGDvgS22kg3AG+Fj2XMoim2JETxX6xmLNjVr1yBmbwR7DkXxRvhYw/YJ00cQd3Aj2xIj+HDlm5Qt52or2Xar25770SnhY9h5aBNbEtbybK2nLdo8V+sZtiauY+ehTUwJH2PY3qZDC7YlRXAm4xA1a1u+tq3J5Dmjif36S6IS1vDs8zfWviVhLbFff8nkOaMN28s/Uo7PIpew46uNfBa5hHLly9pKNk19XyLmQCQ7vt7IK0N7Fdvv5OzEok/msOPrjazbvgyvyjrDvgHDerPj643EHIikie9LNtMM8JJPfdbtXUnkvi/o+Xq3YvudnJ2Y9eEbRO77gk+3foDn4x4AeD7uQcKPO1gZt5SVcUsZN2+kTXUXYq/xoq5R2/v8jfBx7DkURcwt+qLte9fr+6Jxhu0Tpo9g58EviUmM4MOVb9m0LwKYNnc88clb2b438ubakzYQn7yVaUY518TpI9n11Wa2743ko1VvU7ac7XwO9psv2nO83HcUFFjnXymgCpl3gRAi1+x1HyHEEmu9v4X9PkKIK0KII0KIM0KIN2/jPesIIQLulcbbwcHBgQlzRzOk+2g6e4fRJtif6k9VNbHp2D2QnMs5BDUKZfXHEQyfMhiAy79fZkSv8YT49uKN4bOZveQNW0q3e+3jw0cxLGwMXZr3pHVHf6qZaQ/q1o6cKzkEN+7Gmk/WM3SKVsT68buf6NVmAGEt+zG0+xgmLRiLo6NtVqtzcHBg0tzRvNZ9FB29u9E2uGUxn3fq3p7syzkENurC5x+vY8SU1wG4/PsVhvYaS2ffHkwZPos5S6bZRLMxLVp6U736EzR6oQ1jhk9j/luWv/f5i6YxZsQ0Gr3QhurVn8DPv6hY/MkHK/Fv1gn/Zp3YvXOvTXR3DGjJR4tm33B/0sFkzl9IJSbiM6aPG8asN7Wm7kp2Dh8uX8Pape+wduk7fLh8DVeyc2yiGbR4GRc+guFh4wj16U3roBZU+78nTGw6dGtHzuUcOjcJY+3SSIZMGWSyf+T0IRzcc8hmmo3x9W9KtepP0Lx+IBNHzWT2m1Ms2s15cwoTR86gef1AqlV/Ap8WTQH4eMkK2ni/TIBPCLvj9jJ8zCCLx99rWrZqzpNPVuXF2i0YMXQKb70zw6LdW+/MZMTQKbxYuwVPPlkVf31hvn/v4Xg37oB34w5siYpl65Y4m+gG8PFvQtXqVfBrEMTkUbOZuXCiRbuZCycyedQc/BoEUbV6FZq3aAzAvoSvaNs0hHbNQzl39jyvjeindN8Ee+5Hm/s3oWr1yrRsEMzU0XOYscCyz2csnMjU0XNo2SCYqtUr4633+Q+nzzKkzziSDx6xpWwAvFs05onqVWjdsBNvjA5n2oIJFu2mLZjAG2PCad2wE09Ur0IzP037gGG9+WpvMm1e6sxXe5MZMKy3TXQ7ODgwdf44BnYbTvumobTr1Jonn6pmYvNyWAeuXMmhTcPOrPp4LWOmDgHgyaeqERDcivbNujKg63DemD8OBwfb/NRxcHBg9JzhjOoxgW6+fWjZsQVVzfqi9t0CyLmSQ5emPVi3NJLXJxe11xd+SaV3qwH0bjWABRPetolmY+w1XtQ1anuf+/g3NfRFk0bNZtbCSRbtZi2cxKRRs436oiaA1he1adqFgOah/Hz2FwbbqC8y1u5bv/1Nc67Zb05h0siZ+NZvX0x76yadaevdhXNnf2HwyP42026v+aI9x8t9iZTW+VcKqELmvxAhxJ1UjJKklHWBukCgEKLJLezrADYtZNasW4Nfz13g4vlU8v7JI3bzbnxam47w82ndjK3rYwDYFZ1Ag6baSLrvTvxAVsYlAM6eOYdzGWecnJ2U9tvgubo1+PXni1w8n0beP3nERe2meeumJjbN2zQjev0OAHZHJ9Cgmab9r2t/kZ+fD0CZMs5IGzZQNes+y3kjn+/YvAvf1qajEn1aN2OL3uc7o+Np2LQeAGdOfG/w+Y9nfqKMjX0O0DrAj/XrogD49vBRypUvh7uH6V1Pdw83XMu68k1yCgDr10XRpl0Lm+o0p16d5yl/kzvL8fu+ono2ngUAACAASURBVEObFgghqF2zBjk5uWRd+p39X39Do/p1KV+uLOXLlaVR/brs//obm+l+rm4NLvx8kVRDnO/B2zzOWzdhW2QsAHuiE6nftGhUV/M2Tbl4PpWfvj9nM83GtGzry8aIrQAcOXyMcuXL4u5R0cTG3aMirmVd+fbwMQA2RmylVYAvALk5Vw12Dz30ILa6UgMC/Vm3dhMAh5NTKF++HB5mce7h4UbZcq4kH9J+IK5bu4l27VsWe6/gTgFsjNxqfdF6/Nv6sGl9NAAp3xynXPmyuJn53M2jIq5lH+aI3ueb1kfTUu/zfQlfGdrHlMPH8fRyV7pvgj33oy3aNGdThKbr6DcnKFu+LG4ej5nYuHk8hmvZh0k5fByATREx+Lf10TT/8DPnzv5iM73GtGjbnKj12wBNe7nyZXFzN9Pubqo9av02/AOaa8e3ac7mCC3eNkdEGz6Ttan1wnOcP3eBC7+k8s8/ecRsisOvjWkO4NemOVER2meL3bqHl5rV12/3JmZTHP/8/Q8Xz6dy/twFar1gebT4vebZus9w4edUQ1+0K2oP3q1NU/JmrZoQo++L4rclUq+p7UcY3wh7jRd1jdre5/5tm5ewL9L0GfdFRw4fx9PLwya6Qcu5vtTnXCmHb0/7lxFbaRXgB0BSwkEj7cfw1NmmHy3Ubo/5oj3Hi+LfjSpkWgkhxBNCiN1CiGP6/6vot68QQrxsZJer/99HCBEvhFgDHDd7r8+FEEFGr1cLIToY20gprwEpQCW9TQMhxAH9aM0DQoinhRDOwEwgVAiRIoQIFUI8LIRYJoRI1tsGcY9x17mRkZppeJ2Rlombzq2YTbreJj8/n9ycqzxSobyJjX+gD9+d+J5//v7nXku8IXat3dONjItF2jPTsnD3NOvwPCsaPl9+fj652Vcpr9f+XN1niUhYxbr4Fcwd/6ahE7E2HhZ87m7mc80mo0h3Tm4xn7cM9OWMjX0OoNN5kHox3fA6LTUdnVmio9O5k6bXr9lkoNMVdcz9BoaxZ/9m3l4ym/Lly1lf9G2QkfUbnu5F8ePhXpGMrEtkZF3C073o+/Fw07bbCjejGAYtzt10FW9oYxznLg+60Gtwdz59a6XN9JrjqXM3iZf01Aw8zOLFQ+dOulm8GCfPYycP5eCxODq+3I5Fc9+3vmi0OL94Ic3wOjU1HZ1ZcqnzMr0WUi+mm8Q5QOMm9cnMvMRPNvwh6aFzJ/VikT/TUzPxNGtjPI3adYC01Mxi3wvAy2FBJO4+YD2xRtirbnvuRz10bqSnFsVwRmoGHp5m16en6fWZkZaBh852j+zdCA9PN5N+Jt1CLHjo3ElPyzS10T9u+JhbBbIyfwMgK/M3KlR81Aaqtdwl/aKxPzOL+dPD0420i0U5QI4+B9C+L6NjUzNt9vikm2dFMs37Is+b9UUF5GbnUv5RrY/3quLJythP+GDDO9Ru8LxNNBtjr/GirlHb+9xT506aWd5iXtDz1Lmb9EWWbAC6hAWRsHu/9cSa4aFzN7QdUDyfAv3nM/leiudlACHdO5JoQ+32mi/ac7zcl6hHyxV6HtQXBFOEECloRcJClgCrpJS1gNXAe7fxfg2AyVJK80n1PgX6AgghygONgRhjAyHEo8D/AYXPoZ4BvPWjNd8AwqWUf+v/jpBS1pFSRgCTgT1SyvqAL7BQCPHwbX7+20OI4tvMRvgJCzbGowCrP12NYVMGM3vswnsq7ZbYtfbim4oNrLzJ5zt55BShPr3o1XYgfYf2wLmM873XaIlb+PN2bJ58uhojpgxm5tj591zerbhVPNzQRn9vdMVn62hYpxUtmgaTkZ7F9DnjitmWBpZG5QohLD5NYOnzWQuL5yoWLpbjfODYvqxdGsm1P69ZR9xtUOJ4MTJZOGcxjWq1YvOGbfR+pfi8bNbgXugG6NwlkI2R0fdU2624jWb9ttqhwSP7k5+XR1RkTDFba2Cvuu25Hy15nJfOY1YmlLgvtZag2+N22o0btfs361utTcn7fvgt83c6NuhK79YDeXfGB8x4fwoPuT5kLamWua/iRV2j1uT2fF78OEt9UV5evu36Im5P141yRmNeH/UKefn5bI7cdi/l3ZT7O18sfty/IV4U/24eKG0Bds41KWWdwhdCiD5APf3LRkAn/d+fAwtu4/0OSSmLPd8opUwUQrwvhHDXv+dGKWWevmFoJoQ4BjwNzJNSFt7yKA+sFEL8H1qedKNnsVoBHYQQhTNfuwBVgNPGRkKIgcBAgMfLVqfiQ6aLZdyMzNRMPIweYfPQuZOVbjpiKyM1E08vdzLTsnB0dMS17MNc+SMb0EZqLFoWztShs7jwy8XbPu+9wK61p2XhUalIu7vOzfCInomNsfZyRdoL+fmHX7j253WefKYap49+Z3XdGbfpcw8vDzIMPnc16PbQufH2snlMtqHP+77SnbDe2kDrlG9P4FWp6PrQeXmSnp5lYp+ammEyek3n5WG4434p6zfD9tWrIvl83UfWlH7beLpXJD2z6HvIyLyEe8XH8HSvSPKRY0Xbsy5Rv24tm+kqjOFC3HVuxeLlRnFes+6z+LVrzpApgyhbzpWCAsnff/1N5PJNVtXcq38oXXt2BuDYkZMm8eLp5UGmWbykp2aYPEqj8/IgIz0Tc6I2xLB83fu8Pf8Dq+h+ZWAPevUJAeDbb45T6fGiBTa8vDxNRo2ANgLT+LN5VfIkPb1opICjoyOBHVrj27SjVfQa06NfCKE9gwE4nnISr0oeFE6A4OnlTkYxn2eaPHqt83I3+V46hQbi26oZPTtZXhzrv67bGHvrR8P6dSGkpxaTx4+cwtPLEziqaffyIDPDzOdpptenh86DzHTbjUo3pnu/LnTpUaTduJ/xNIsF0EavGY968fRyN3y+37J+x839MbIyf8PN/TF+v/SHDT6BNgLTs5KxP4vrTk/LRFfJg4y0TBwdHSlb1pXLf1zRx7/RsV7FY81aZKZl4W7WF13K+K2YjYeXO1lpl3B0dMC1nCvZ+jgvHGn83fHvufhzKlWqP86ZY99bVbO9xou6Rm3v8579Qgjtqf2sPZZyEp1Z3mLeF6WZ9UXmNp1C2+PXypsenaw/T2PP/qF0LdR+5CS6Sub5lLn2DLPvxUx7V017WPBAKyu333zRnuPlvqfgX3AT5x6hRmTajsKoyUPvd6FVIo2HuV01P8iIz4EwtJGZy422J+lHfT4PvCaEKCyszgLipZQ1gfZoBUpLCKCzfoRmHSllFSnlaXMjKeUnUsp6Usp6d1LEBDiZcoYq1R/Hq4qOB5weoHXHFiTE7TOxSYzbR/sQbepO/0AfkvdrP9Vcy7my+IuFLA7/mKPJx4u9t7WxZ+2nUs5QudrjeFXWtLcKasHeWFPte2P3ERjSBoAWgT4k7/sWAK/KOsPiPp6Pe/DEk1VI/TUdW3Ay5TRPVK9MJb3P23T0JyEuycQmIW4fHfQ+bxnoyyG9z8uWc2XJF2/xXviHpCQfK/be1mL5p2sMi/Ps2LabkK7aDA0v1KtNTnZOsaQ6MyOLq7lXeaFebQBCugYRG7MHwGQ+zbaBLTlz+gcbfYqb49P0Jbbs2I2UkqMnTuPq+jBuFSvQpOGLHDj0LVeyc7iSncOBQ9/SpKHtVosvinNPfZz7kRRn+tjJ3rj9tOvSGgC/wOYc3qfN2TgweCgdG3alY8OurPt0AysWf2H1IibAqs8iCPAJIcAnhLiYPXQObQ9A3Xq19PFiVojNuMTV3KvUracViDuHtmfn9ngAqlavYrBr2daHsz9Yb67PTz/5wrBAT0z0Trp20wps9erXITs7hwyzOM/IyCI35yr16mvdUtduwcRE7zLs9/Ftwg/f/0RqqvXbli+Wrae9bzfa+3YjLiaB4JBAAOq8+Dw52bnFbvJkZVziau6f1HlRe8QzOCSQXdsTAPD2a8zAYX0Y1GME169dV7pvgb31o6uXRRLkG0aQbxi7ticQHKrpqv1iTXKzc8kyK05lZfzG1dyr1H6xJgDBoQHs3pFoE63mrFkWSbBfGMF+YezenkBQSDtA056TnWt4DLWQrMzfuJr7p0F7UEg7dm/XtO+J3UvHUC3eOoYG2uwzHT9ySp8DeOHk9AABwa2IjzXNAeJj9xIUqn221u39+GrfYf32JAKCW+Hk7ESlKl48Ub0yx749aRPdp1POULlaJXT6vsg/yI+kONPpG/bFHSBA3xf5tmvON/u1vuiRCuUNixJ5VdFRuVolUs+nYW3sNV7UNWp7n3++bD2Bvl0J9O3Kzpj4EvZFmj5vv8YMGtaHgTbqiz7/LIJ2PqG08wklLiaeTvqcq069G2vPzb1KnXqa9k5GOZe3X2NeHdaXAWHDbaLdXvNFe46X+x5ZYJ1/pYD4Vwytt1OEELlSSlej132AelLKIUKILUCklPJz/fYgKWWwEGIKUFZKOV4I0RHYJKUUQggfYIyUMtDS+wshPIBDQLqUsqF+m8kxQoiRQAMpZTchxCbgCynlRiHEdKCPlLKqEKIz0EFK2Vt/TDhQDhgqNSF1pZQ3XbqvrmeTOw6api0aMWbmMBwcHYlaG81n767itXGvcCrlDIlx+3Au48zsJVN5uuZTZF/OZsKgaVw8n8orI3rTb1hPzv90wfBer3UdwR+XLt+phBJT2todRcnvNzTxe4lRM4fh6OjAlnXbWPbu5wwa25/TR8+wN24/zmWcmbl4Ck/X/D+yL2cz6dXpXDyfRsDLrek9JIy8f/KQUrJ00QoSdyTd+oRm/C3zSqS7aYtGjJs5AkdHBzavjWbpuysZPG4Ap1JOk6D3efiSaTxT8ymuXM5m3KCpXDyfyoARfXhlWC9++elXw3u92nXEHd+lzrx+d/E1d+FUfP2bcu3P64x4fRJHU7QfUruSvsS/mXaHsnad53j3g7m4PFiGPTuTmDROWzF88cfzqVnzGSSSX89fZOyI6cUKoTfj1x9L9pjL2GnzSD5yjMuXs3mswiMM7t+TvDzt+wsNboeUkjmLPmDfV4d50MWFWZNGUrPGUwB8GR3L0lURAAzs3ZXgdq1KpKFJrb4lOq6xX0NGzRiKg6MDW9fFsPy9Lxg4th+nj54hKe4AzmWcmfHeZJ6q+T+yL+cw+bUZxX4kDhjdhz+vXmP1RxF3fP6Mv+5uFMSsBZNo7teEa9euM2boVI6nnAIgJmE9AT7aCMjn6zzLW0tm4+JShoTd+3hj/FwAPlqxiOr/q0pBQQEXf01j0phZZKQVv/t+I7L/+rPEuhcumk4Lf2+uXbvG66+OJ+XICQD2HtiCd2NtGuc6dWvywccLcHFxYdfORMaNLlrd/P2P5nM4OYXln62943NXcLm7uWOnz5+At18jrl+7zvhh0zmeot2/2xq/lva+2uNWz9epwYLFMyjjUobE3QeYMUGbqmLPoSicyzjxx+9XAG3y+qljwu9Kjz3oLvfAgyXWXdr96NX8v0qsfdr8cTTzbcy1a9eZOGwGJ45qPo+KX02QbxgANWvXYN7i6bi4lGHvngPMnKA9hNMywIepc8dS4bFHyb6Sw+mT39M/ZOgdnd/hLqbqmDpvHM38GnH9z+tMGj7ToH3TntUE+xVpD39vGi4PliFp9wFmTdQe33/k0fK8vXQuusc9SLuQwYhXJnDlcvYNz2WOsDS/zW3i3aIxE2ePwsHRgS/XbOXjd5YzdPxATqScJj42Cecyzsx/fwY1nn+KK39kM3rQZC78kgrAoBF96dS9Pfl5+cydsoikPQfv+PyPOJVshqVGfg0ZMeN1HBwciI7Yzsr3VjNgTF9OH/2OfTsP4FzGiWnvTeKp57Sca+rgWaSeT8MnwJsBY/qSn59PQX4+n761gn0771z3H//klkh3IaUZLwV38XtUXaMl8/nfBSXL0QFmzJ+At19jrl+7zrhh0w15S3T8OgJ9uwJa3rJg8QxcXMqQuHs/0036ImcuG/VFU8bMuaPzy7sonMxcMBFvfc41bugbBu3bErSCZ6H2hUtmGbRP0+dc8clb9dq1PujI4eNMGTP7ts9dcJdTXZRmvuh4R2sRm1La8fLTpSO2m/PqX86fC/tZpfj30NhlNvexKmTeBbcoZFYFlgEVgSygr5TyvL4gGYU2KnM3WgHR9VaFTP3rHcBmKeVH+tcmxwghHgR+BJoCnsBK/bn3AD31hcwKQCzao+ZzgS3AO2jzbgrgZ2MNlihJIVNRcu6mkFnalLSQWdrcbSGzNClpIfPfQEkLmaXN3RYyS5O7KWSWJndbyFTcOXdTyCxt7qaQWdrcTZGkNLmbQmZpU9JCZmlzt4XM0uRuCpmljb1eo3dTyCxt7qaQWZrcbSGzNLmbQmZpowqZRfw5v691Cpnjl9vcx2qOzLvAuMiof70CWKH/+2fAz8IxGcBLRpsm6rcnAAk3en8hxENoi/msNdpvcox+5fJK+pfngKeM3m6q3uZ3oL6ZLDXhhEKhUCgUCoVCoVAoFAqF4l+NKmTaAUIIf7TRnYuklFdKW49CoVAoFAqFQqFQKBQKhcI+kAX2OZrZEqqQaQdIKXehrSSuUCgUCoVCoVAoFAqFQqFQ3D5q1XKFQqFQKBQKhUKhUCgUCoVCobAdakSmQqFQKBQKhUKhUCgUCoVCcb9ipwtlWUIVMhV3jLDT1fmchX2Ge27+9dKWUGIecixT2hJKRDk7XbEU7Hflb4D9x5aXtoQS8WyNLqUtocQ86lK2tCUo7IR87Df5zbfjxP0vO11Z2M25fGlLKDHX8/8ubQklwp5X/rbnazTfft1utzz8wIOlLaFEXM27VtoSSswjdvzbSHF/Yp+VHYVCoVAoFAqFQqFQKBQKhUJxa9QcmQqFQqFQKBQKhUKhUCgUCoVCYTvUiEyFQqFQKBQKhUKhUCgUCoXifqXAfqfxMEcVMhUKhUKhUCgUCoVCoVAoFIr7FfVouUJxZzT2bciXSWuIOrCOPkN6FNvv5OzEvI9mEHVgHSu3fYLucU8AnqtTg7U7l7N253LW7VqBb1tvW0vnJZ8GRCStInL/anoO6V5sv5OzE7M/eoPI/av5LPoDg3bd454knI1l1c5PWbXzU8bNG2Vr6TTxfYmt+yOI+SqS/kN7Ftvv5OzEm5/MJuarSNZs/wyvyjoAyj9ajmVfvs+hn/YwKXy0rWXzkk8DIpM+Z+P+1fS6gc/nfDSNjftXsyz6Q4PPC/Go5E7CD9sJezXUVpJNmBI+hp2HNrElYS3P1nraos1ztZ5ha+I6dh7axJTwMYbtbTq0YFtSBGcyDlGzdg1bSbZbn08JX4R3u6507PGqxf1SSsLf/pC2If0I7vUap7770bAvKmYnAaH9CQjtT1TMTltJLsbU8LHsOrSZrQnreLbWMxZtnqv1DNGJEew6tJmp4WMN29t08CcmaT3fZSTbNF4A3ggfx55DUcQkRvDcDXTXrF2D7XvXs+dQFG+EjzNsnzB9BDsPfklMYgQfrnyLsuVcbSUbgDfCx7LnUBTbbqE9Zm+EXnuRzydMH0HcwY1sS4zgw5Vv2lS7vepu4vsSW/atI/pgJP2GWO6LFnw8i+iDkayO+RSvylr78pJ3fdbFLmdj/Besi11OgyYv2kxzIfbqc4Dpc8eTmBzNjr0bqFnLcvtQs3YNYpM2kpgczfS54w3bR098nR17NxCTsJ7PN3yEu6ebrWTTyLcBG5NWs+nAWnoPCSu238nZifCPprPpwFpWbPvYJGdcvXMZq3cuY82u5fi0bWYzzaDlupv2rSXqYAR9b5TrfjyTqIMRrIr5BJ0+zht612d17Gesj1/F6tjPqN/kBZvqLsQecxew72v0brS37eDP9n2R/JB5mOfrqP7/drDX30WFTJs7nvjkrWzfG3lzvydtID55K9OM2vSJ00ey66vNbN8byUer3qZsOdss9mjPNQDFv5v/TCFTCJF7k30+QojoG+z7WQhR8R5rSRBC1LuX73m3CCFGCCEessZ7Ozg4MD58FEPDxtC5eQ/adPSn2lNVTWw6dgsk+0oOQY27svqTCIZPeQ2As9/9RI82r9CtZV+GdB/N5AVjcXR0tIbMG2ofEz6ckWHj6ebTm1ZBflT9vydMbDp0CyD7ci5dmoSxdukGXp8y0LDv4i+p9Gr5Cr1avsKCCYtsprtQ+5R5Y3it+0g6NOtGQHArqpv5vVP3DmRfzibgpS58/vFaRk19HYC///qbxfM+4c3pi22quVD3uPARDA8bR6hPb1oHtaBaMZ+3I+dyDp2bhLF2aSRDpgwy2T9y+hAO7jlkS9kGmvs3oWr1yrRsEMzU0XOYsWCiRbsZCycydfQcWjYIpmr1yni3aAzAD6fPMqTPOJIPHrGZZnv2eceAlny0aPYN9ycdTOb8hVRiIj5j+rhhzHpzCQBXsnP4cPka1i59h7VL3+HD5Wu4kp1jK9kGmvs34YnqlfFv0JGpo2cz8ybxMmX0bPwbdOQJk3j5kdf7jCX54Le2lI2Pf1OqVq+CX4MgJo2azayFkyzazVo4iUmjZuPXIIiq1avQvEUTAPYlfEWbpl0IaB7Kz2d/YfCIfjbU3sSgffKo2cxcaNnnMxdOZPKoOUbaGxu0t20aQrvmoZw7e57XbKTdXnU7ODgwae5oXus+io7e3Wgb3NJCX9Se7Ms5BDbqwucfr2PEFK0vuvz7FYb2Gktn3x5MGT6LOUum2URzIfbqcwBf/6ZUq/4EzesHMnHUTGa/OcWi3Zw3pzBx5Aya1w+kWvUn8GnRFICPl6ygjffLBPiEsDtuL8PHDLJ4/L2mMGccFjaGLs170tpCzhjUrR05V3IIbtyNNZ+sZ+gU7UbWj9/9RK82Awhr2Y+h3ccwyYY5o4ODAxPmjmZI99F09g6jTbB/sTjv2D2QnMs5BDUKZfXHEQyfMhiAy79fZkSv8YT49uKN4bOZveQNm2g2xh5zF7Dva/RutX9/+iyD+4zhkOr/bwt7/V1USKHffeu3v2mbPvvNKUwaORPf+u2L+b11k8609e7CubO/MHhkf6trtucawH2LLLDOv1LgP1PIVNySEYBVCpk169bgws8XuHg+lbx/8oiN2oVP66YmNj5tmhK9fjsAu6MTqN9MG3Vx/dpf5OfnA+BcxhkpbTsc+tm6z3Dh54uknk8j7588dkbtwbt1ExObZq2bEBO5A4D46ETqNbX9iBFLPP/Cs5w/d4ELv2h+3755J35tTO9m+bVpRtT6GADitsbTsKlWX7/253WOHDrKX3/9bXPdz9WtYeLzuKg9eJvFS/PWTdgWGQvAnuhE6jctGr3QvE1TLp5P5afvz9lUdyEt2jRnU4Tm06PfnKBs+bK4eTxmYuPm8RiuZR8m5fBxADZFxODf1geAsz/8zLmzv9hUsz37vF6d5yl/k7vK8fu+okObFgghqF2zBjk5uWRd+p39X39Do/p1KV+uLOXLlaVR/brs//obGyrX8G/TnM0R2wBI+eYEZcu74uZheu/MzaMirmVdDfGyOWIbLUsxXgD82zZn03rt/l/KN8cpV77sDXQ/zJHDxwDYtD6algE+gJZQF7btRw4fx9PLw4bafUqo3beY9pTDx/H0cle6b0LNulpfVJgD7Ni8C9/Wpn2RT+tmbNH3RTuji/qiMye+JyvjEgA/nvmJMmWccXJ2solusF+fA7Rs68vGiK0AHDl8jHLly+Jupt1d37Z8q9e+MWIrrfTac3OuGuweeuhBbJV9PVe3Br/+fJGLhv5oN83N+6M2zYher+Vdu6MTaKDPGf8yyhnL2DhnrFm3Br8axXns5t34tDYdEerTuhlb9XG+KzqBBvp88bsTPxji/OyZczjbOM7BPnMXsO9r9G61n/3hHOd+VP3/7WKvv4sKadnWly/1bXrK4dvz+5cRW2kV4AdAUsJBI78fw1Nn/Vi35xqA4t/Pf6qQKTQWCiFOCCGOCyGMn4EsJ4TYJIQ4JYT4SAjhYHZsVSHEaSHEUiHESSFEnBDiQSFEDSHEITO7Y/q/WwghjujPtUwIUcbsPV8TQiwwet1HCLFY/3cPIcQhIUSKEOJjIYSjfnuuEGK+EOIbIcQuIUQD/QjPn4QQHfQ2jvrPmSyEOCaEGKTf7qO33SCEOCOEWK33yTDAC4gXQsTfU6cDbp5upF/MNLzOTMsq9oiSm6cb6amaTX5+PrnZV3mkQnlA+xEUmfA56+NXEj7+TUOjZgvcPN3ITM0y0e6mK649Q2+jac+lvF67VxVPVsYt5YON71C7wfM20w3gbuRTgIzUzGJ+d9e5kX4xA9Brz8k1+L20cPOsSEaqaby46Sre0KYwXspXKI/Lgy70GtydT99aaVPNxnjo3EhPTTe8zkjNwMPTNFnw8HQnPTWjyCYtAw+d7R7bM8fefX4zMrJ+w9O96LN4uFckI+sSGVmX8HQv8rmHm7bd1njo3EkzioX01Ew8zK5TD083k3hJT8vAwwYJ6M3w1LmTdrEoztNTM4olxZ46d5M2yJINQJewIBJ277eeWDM8dO6kXjT1uafZ9eepM20/01IzLfr85bAgEncfsJ5YI+xXt5tJ+5KRlom7mW7N5uZ9UctAX86c+J5//v7H+qINuuzT55oud1LNrlFzXR46074ozewaHTt5KAePxdHx5XYsmvu+9UWj5S4ZxXJGswLsDfojgOfqPktEwirWxa9grg1zRncLcW6eL7rrzHLdnKvF4tw/0IfvbBznYJ+5C9j3NXovtdsSe+3/7fV3USEeOnfSLt64vQb9d2OSU1rOF0O6dyTRBn635xrAfUuBtM6/UuA/VcgEOgF1gNqAP7BQCKHT72sAjAaeB57U25rzf8D7UsrngMtAZynlacBZCFFdbxMKrBdCuAArgFAp5fNoCyu9ZvZ+G8zOEwpECCFq6P9uIqWsA+QDhZMEPQwkSClfBHKA2UBLIBiYqbfpD1yRUtYH6gMDhBDV9Pvqoo2+fBaorj/He0Aq4Cul9LXkOCHEQCHEYSHE4Ut/plsyuSFCiGLbzO+q3MzmxJFTdPHpSc+2A+g71gZMYAAAIABJREFUtAfOZZzv6Px3gwVZUEy7JRPJpczfCKofSu9WA3h3+gfM/GAqD7laZdCrRSz61NyGW383tsaSbnPhlm0kA8f2Ze3SSK79ec064m6Du4330sDefX4zLPlVCGF+GRu22xp7jBe4Xd3FjzO3GTyyP3l5+URFxtxTfTfjBqF8SyNL2vPz8mym3V51346mW9k8+XQ1RkwZzMyx8++5vJthtz7nbtqWor8XzllMo1qt2LxhG71f6XbPNVqkhD4vNDp55BShPr3o1XagbXPG2wiWW30n1Z+uxrApg5k9duE9l3cr7LcvKr7Nfq7R4ttKot3W2Gv/b6+/iwq5HZ/eKFc35vVRr5CXn8/myG33Up5F7LkGcL8iCwqs8q80+K+tWt4UWCulzAcyhBCJaIW+bOCQlPInACHEWr3tBrPjz0kpU/R/fwNU1f+9HggB5qEVIEOBp/X23+ttVgKvA+8UvpmUMks/kvIl4Af9Mfv1di8CyfqL+0Gg8HbG38AO/d/Hgb+klP8IIY4b6WkF1BJCvKx/XR6tCPu3/nNe0H/OFP0x+27lOCnlJ8AnAC/omt5Ri56ZlolnpaK7Qe46N8MjNCY2Xu5kpmXh6OiIa7mHufJHtonNuR9+4dqf13nymWqcPvrdnUgoMZlpWbh7Fd05cte5kZVurj0LDy83sgzaXcnWay+8o/7d8e+5+HMqVapX5swx22jP0Pu0EA8vd7LSs4rbVPIgo1B7Wddifrc1mj/N4sWiz4vHS826z+LXrjlDpgyibDlXCgokf//1N5HLN1lVc1i/LoT07AjA8SOn8PTyBI4C4OHlQWaGqd/T0zJMHqXx0HmQmW770YCF2KPPbxdP94qkZxZ9lozMS7hXfAxP94okHzlWtD3rEvXr1rKJprB+XQjtGQzAsSOn0BnFgqeXO5lm7WN6WqZJvHjqPMg0u5ZtQc9+IYT21O69HUs5ia5S0YJPnl4eZJhpSks1bYPMbTqFtsevlTc9Oll/7r0e/UIMPj+echKvSh4UTiTg6eVeTHu6mXadl7uJzzuFBuLbqhk9O1leZOq/rtuYjNRMk/bFQ+derH3RbCz3RR46N95eNo/JQ2dx4ZeLVtdrzz7v1T+Urj07A3DsyEm8zK5R83YjPdW0L9J5eZCRnok5URtiWL7ufd6e/4GVlBeRmZaFxy1zRsv9kTE/2zhnzLzNODfJdcsW6XbXubFoWThTbRTnYL+5iz1fo/dau62w5/6/EHv8XdSzfyhdC/1+5CS6SubttbnfM8xySjO/d9X8HhY8EFtgzzUAxb+f/9qIzJsNtzEvzlkq1v1l9Hc+RYXgCCBECPEUIKWUP9ziXMZEoBVBOwObpHYLQgArpZR19P+ellJO19v/I4tuZRQUapJSFhjpEcBQo+OrSSnjbvEZrMbJlDNUrlYZr8o6HnB6gNZB/iTGmg5nT4zdT2BIWwBaBPqQvE+buNqrss4wsa/ucQ+qPlmFtF/vbETo3XA65TsqV3scXWVPHnB6gJZBfiTFmT52khR3gIAubQDwDWzOYb32RyqUx8FBu8S8quh4vFolUs+n2kz7iSOnqVK9MpWqaH5v27El8bFJJjbxsUkEhQQA0Kq9L1/vO2wzfTfiVMoZKld7HC+9z1sF+ZEUZxove+P2065LawD8AptzeJ82ufzA4KF0bNiVjg27su7TDaxY/IVNCmqrl0US5BtGkG8Yu7YnEByq+bT2izXJzc4lK+M3E/usjN+4mnuV2i/WBCA4NIDdOxKtrvNG2KPPbxefpi+xZcdupJQcPXEaV9eHcatYgSYNX+TAoW+5kp3DlewcDhz6liYNbTO/7eplkXTw7U4H3+7s2p5Ax9B2ANR5sSY52bnFkrysjEtczb1KHX28dAxtx65SiJfPl60n0Lcrgb5d2RkTT3BIoF738zfR/Sd1XtSm1QgOCWTXdk23t19jBg3rw8AeI7h+7brVtX+xbD3tfbvR3rcbcTEJJdSeYNA+cFgfBtlAu73qNuZkymmeMOqL2nT0JyHOtC9KiNtHB31f1DLQl0P7tZ/2Zcu5suSLt3gv/ENSko8Ve29rYM8+X/VZBAE+IQT4hBAXs4fOoe0BqFuvFjnZOcVukmTq25a69bSbOJ1D27NzuzbDUNXqVQx2Ldv6cPYH28yBXNQf6fT9UQv2xpreb98bu4/AEC3vulHO6Pm4B088WYVUG+WMJ1POUKX643jp47x1xxYkxJnqTozbR3t9nPsH+pCsj3PXcq4s/mIhi8M/5mjycZvoBfvNXez5Gr2X2m2JPff/hdjj76LPP4ugnU8o7XxCiYuJp5O+Ta9T78Z+z829Sp16mt87GbXp3n6NeXVYXwaEDbeZ3+25BnDfch89Wi7+LcOlrY1+1fJewCAgAKgAHAYaAs8A29Eet/5F//cnUsqNQoifgXqAKxAtpaypf78xgGthgVEIkQycAY5LKRfoHy3/HvCTUv4ohFgBHJFSviuESADGSCkPCyEeRRvd+QswXkp5SAjxLBCF9th3phCiAlBWSvmLECJXSumqP+d0IFdK+WbhZ5RSugohBuo/Yxf9aM2ngItoo0/HSCkD9fZLgMNSyhX6EZ0dpJS3zFTvdEQmQBO/lxgzczgOjg5sWbeNz95dxatj+3Pq6Bn2xu3HuYwzsxZP5Zma/8eVy9lMfHU6F8+n0u7l1vQZ0oO8f/IokAUsXbSChB1Jtz6hBZxFyWq2jfwaMnLGEBwcHYhet50V733BgLF9OXP0O5LiDuBcxplp703iqZr/R/blbKa+NpPU82n4BngzYGxf8vPyKSgoYOmby9m38+Adnz83v+SdTbMWjRg/aySOjg5sWhvNJ++s4PVxAzh59AwJsUk4l3Fm7pJp1Hj+Ka5czmbsoKlc+EUrtsYmb8K17EM4OTuRfSWXgaHD+On7n+/o/A85lrm1kQUa+zVk1IyhODg6sHVdDMvf+4KBY/tx+ugZg89nvDeZp2r+j+zLOUx+bQap59NM3mPA6D78efUaqz+KuOPzX/7n6q2NbsK0+eNo5tuYa9euM3HYDE4cPQ1AVPxqgny1WSJq1q7BvMXTcXEpw949B5g5QZsut2WAD1PnjqXCY4+SfSWH0ye/p3/I0Ns+9yNOD5dIc2n7HGD/seV3fMzYafNIPnKMy5ezeazCIwzu35O8vDwAQoPbIaVkzqIP2PfVYR50cWHWpJHUrPEUAF9Gx7J0laZ1YO+uBLdrVSLdz9boUqLjCpk2fzze+niZMGy6IV62xK+hg293QIuX+Yun4+LiQuKe/Ubx4ssbZvHSL2TIbZ87/y5WGpwxfwLefo25fu0644ZN53jKKQCi49cR6NsVgOfrPMuCxTNwcSlD4u79TJ+gPRq851AUzmWcufz7FUBbMGDKmDm3fW5Lj3/dCdPnT8DbrxHXr11n/LDpHE/RfL41fi3tfbvptddgweIZlHEpQ+LuA8ww0e7EH0bap44Jvys99qD74QdK1p4DNG3RiHEzR+Do6MDmtdEsfXclg8cN4FTKaRLi9uFcxpnwJdN4pqbWF40bNJWL51MZMKIPrwzrxS8//Wp4r1e7juD3S3/c0fmv5v11a6MbUNqxkifzSqx91oJJNPdrwrVr1xkzdKrhGo1JWE+AT4he+7O8tWQ2Li5lSNi9jzfGzwXgoxWLqP6/qhQUFHDx1zQmjZlFRlrx0Zo3ws255PPKNfF7iVEzh+GozxmXvfs5g8b257RRzjhz8RSe1uddk16dzsXzaQS83JreQ8LI+ycPKSVLF60gsQQ5Y0nbxaYtGjFm5jAcHB2JWhvNZ++u4rVxr3Aq5QyJ+jifvWQqT9d8iuzL2UwYNI2L51N5ZURv+g3ryfmfLhje67WuI/jj0uU7Ov/V/JLHOZRu7nI3fVFpX6N3w91obxXgyxvzxlHhsUfJuZLDqRPf0zfk9ds+9/+zd95hUVxdHH4vCKKixEK16xcTu8beKIKKWNEIlkSNRk2MNfbesZuiJkZjSVFEbCiigCLFjjX2JBo1SrcBdmC+P3ZZWIoFZdc1930enoede2bmt3fPnLlz5hblNZbw0uf9H/L+fKHv56IHKa83DdPMBROwV8f0sUOnaup9V6gq4Qmqel+4bJam3qepY/r+yJ3qelfFlVPHzzJ59OyXPndx09wX1nweb0MO4GT0Ad3PHfWWkjyuS74k/8znb9V5Hf8nEplCiAJALFAKWAC0RdXjcraiKD5CCEdgKhCPao7McGCwoihpr5DIHA0sBCoqinJNvc0ZWISq12Mk8KWiKE8yJzLVdv5ANUVR0ufZRL0Q0QRUvWafAV8pinLkJROZRqjmzuyAqndmPNAZ1fyYuSUyh6Ia0h6d2zyZ6eQlkfk2kNdEpr55nUSmvslrQ0PfvG4iU5/kNZH5NpCXRObbwOsmMvXJ6zw86pPXTWRKXp3XSWTqm9dJZOqb10lk6pPXSWTqG0ONi6+byNQnhlrnhszrJDL1jaE+X7xuIlOf5DWR+TYgE5kZJI9xz59E5sJtMpGZHwghagOrFEVpqG8t7wIykalbZCJT98hEpn6QiUzdY6gPjzKRqXtkIlM/yESm7jHUuCgTmZJXQSYydY9MZOoHmcjMIHl0p/xJZC7y03kdv/NzZAohvgC8gcn61iKRSCQSiUQikUgkEolEIpFI8oZhdlF7BRRFWQGs0LcOiUQikUgkEolEIpFIJBKJROfoaWGe/OCd75EpkUgkEolEIpFIJBKJRCKRSAyfd75HpuTNs8WqkL4l5Am36Pv6lpAnjIThTuthVcBc3xLyRJIBz2ET++TVVvN9mzDUuSYvXPTVt4Q8U7Oap74l5IkzB7/Tt4Q808Jhgr4l5In/mZTQt4Q8c+Dp3/qWkGcKGBlmU92Q5zxMxTC1n1nkom8Jeab6qEB9S8gzJQ107sDt5Q0ztgCcv2qlbwl5ItHUWN8S8kyhNMOMixJtFNkjUyKRSCQSiUQikUgkEolEIpFIdIfhvoqRSCQSiUQikUgkEolEIpFIJM/nHeqRKROZEolEIpFIJBKJRCKRSCQSybvKOzRFgBxaLpFIJBKJRCKRSCQSiUQikUjeemSPTIlEIpFIJBKJRCKRSCQSieRd5R0aWi57ZEp0QqGm9Sntt4YyO9dh0S/7KrnmHVtTbr8vdj4rsPNZgbl7W02Z9Q9elIvYhvXSWbqUrKG5U2MCDvmy5+gWPh/aO1u5iakJS1bOYc/RLWzcvQa7sraasgHD+rDn6BYCDvnSzKmxLmUDKu3+Bzex+8jmXLUvWjmb3Uc24717tUa7RfFirN36A5FX9zPJa7SuZfORQz1W7P+JleGr+Hhw9pWsqzeszre7vsPv6g6auTXTKmv5sTMrw1ayMmwlLT921pVkDYbsL9PnjiMs0p894ZupUatqjjY1alclMGILYZH+TJ87TrN91ISv2BO+mYDQTfy2eQVWNpa6kg3AFK8x7D22nZ2hG6lW68McbarX+hD/MB/2HtvOFK8xmu2uHV0IiNjE5dhIatTO+XvnB5O9lmDfrjudP/kix3JFUfD65kfaevTDvfeXXLicsfKyX0Awbp79cfPsj19AsK4kazFpzigCj27FL3QD1Wp+kKNN9VofsiPUm8CjW5k0Z5Rmu8V7xVjtu4w9R7aw2ncZxSx0t+rrgRNn6TBoAu0GjGO1765s5VFxCXw+cQFdh0yh3/h5xCTc0ZTV6diPbkOn0m3oVIbO1O3K6Y0dG+Ib8RtbDq6n95Ce2cpNTE2Ys2IaWw6uZ43/j9iWsdEqty5tRehfu+n1he5Xqq/lUJdFIctYEvYDHb7skq38w4bVmLNrEb9d2UxDtybZyguZF2LZ0Z/pO3OALuRqMWPueMKP7yIwYkuucbFm7WoEHdhK+PFdzJg7XrN91MQhBEZsYXeYL79v+QlrHcfFqV5jCTnmR0CYD9VziYs1aldld/gmQo75MdVrrGb7+OkjCD68lYAwH378ZTFFi5nrSjZNnRqx7YA3fod9+GzIJ9nKTUxNmPfTTPwO+/BrwEpsy6p8vZF9A9YHrmbT/l9ZH7iaBs0+0plmgGZOjdlxYCP+h33pN+TTHHUv+GkW/od9WR/wM3Zq3RbFi/HzlmUcubKPCV6jsu2nCw5eiaXTimA6/BjEmkOXs5UvDP4Dj59D8Pg5hI4rgmi+2F9T9k3IObqs3Iv7T8HMDzqDouj2QdlQ/byJY0M2R/zO1oMb6DOkV7ZyE1MTvFZMZ+vBDaz1X5FjTA/7aw+ffNFdV5IBKNi4AVYbf8Ha9zfMP+2RrbywWxtsArZi+ctKLH9ZSeEObgAY21hjuXYFlr+sxGr9Ggq7d9CpboCSTrVpdnAJzY98S4WhHbOVl+ntQpPQBTTeN48GO6ZTpEppAISJMdW//YImoQtoEjKf4k2r6Vo61k61aBOxENdDi/lgSPa6q9TbmVYh83AJ9sLRbypF1doLlymF+9W1uAR74RLsRd35/XSq29KpNg4HF+N45Bsq51Dn5Xq70CJ0Ps33zaXJjmmYp9d5AWNqf/8lLULn4xCxiMrDOulUt+TtRyYy9YAQIvk5ZY5CCP9cyq4JIUrlk6Zcz/vaGBlRcuJQYgdP5Kb75xRxdcKkUrlsZg+Cwojy/IIozy9I3rZbs/3+Ol/iJ8/PF2kvwsjIiCnzxzKwx3A6NPekXZc2VK5SUcvm414duX8/CddGXfn1J29GTxkCQOUqFXFzb02HFt0Z0H04U+ePxchId5eckZERk+aN4YueI+jYojtu7q2zae/asyOJ95Jo2/hjfv1pI19P+QqAp0+esnTeTyyc/r3O9GbW/eXsL5nWZxqDnb/EoaM9Zd8vq2UTHxXPt6O+IcwvVGu7uYU5PUf05OuOXzOy49f0HNGTIha6a5Qasr84uTSnYqXyODRoz4SvZzJ70eQc7eYsmsyEkTNwaNCeipXK4+jcHICflq3D1f5j3Bw92BcUzvDRg3Sm3cGlGeUrlcWlYWemjJrNzAUTcrSbsXACk0fNxqVhZ8pXKou9c1MA/rr4N1/1HUPk4ZM60wzQ2a0VK5bMzrU84nAkN25GEeCzmuljhzFr0TIA7icm8ePaDXiv+hbvVd/y49oN3E9M0pVsAOydm1K+UjnaNOrC1FFeTFswPke7aQvGM3W0F20adaF8pXK0aKmq8wHD+nAkPBLXxl05Eh7JgGF9dKI7NTUNrx9/48cZI9n+wxx2hx3lyo1bWjaLV/vQwbkpW5bNYlCPjnz/y2ZNWUFTU3yXzsR36UyWTh2uE82gii1jvUYwvNdYPB370KaTMxXfL69l07FHO5LuJdG1WS+8V/kyZLL2NThy+hAOhxzTmeZ0hJERn80ayII+sxjjMoymHZtT+v0yWjYJUfGsGLWUQ37hOR6j26ieXDx6XhdytXByaUGFyuWxr9+O8SNnMGdx7nFx/MgZ2NdvR4XK5XF0UcfFpWtp06IrbR26sS8wjOFjcn5pkR84ujSnQqVytGzYiYlfz2bWwok52s1aOJGJX8+mZcNOVKhUDgdn1cvBA6FHcG3eDTcHT65duc7gEbp5+DUyMmL83FEM6TmKrva9cHV3oVKVClo2nXu2J+leEp2aeLL+Jx+GTx4MwL079xjRexweTr2ZOnw2s5dN1YnmdN0T547iy55f09m+B23dW2XT3aVnBxLvJdG+STd++2kjIyZntLmWz1/J4hnLdKY3M6lpCnMDz7DcsylbB7qw58JNrsQnatmMaVWLTZ+3ZNPnLelRrzLOH6hewp6+eZvTN2/j+7kzmwe4cD76LsdvJOhMuyH7+VivkQzvNQYPx960ziGmd+rRjsR7SXRp1pMNqzYxdLJ2/Ph6+lAOhRzViV4NRka8N2o4t78eT2yPzyjcqiUFKpTPZvZoXyjxfQYS32cgD3cGAJCacJv4gUNV2z8fTNFPe2BUqqQOtQuqzuvHyZ7zONhiFLbuzTSJynSitx7ksONYjjiP59rynXwwQ/VCoswnqo4Rhx3HcsJjDh9M/wSE0Kn2ul59OdBrAYEOYynbuYkmUZnOja2HCG45nr2tJnJ5uT+1p2ckx5Ovx7K31UT2tprIqXFrdKq7+rzPONZzPmEtRmPn3lSTqEwnautBIhzHccB5AleW+1NVXee2HRthVLAAEY7jiGg9kXKfOlOobL6kQf5bpCn586cHZCJTku8UrPEBz/6NIuVWDKSk8GBPKIUdm770/o+PnUJ58DAfFeZOrY+qc+Ofm9y8HsWzZykEbAuipau9lk1LVwf8fFS9egJ3htC4RQP1dnsCtgXx7Okzbt2I4sY/N6n1UXWdaa/5UTX+zax9ezBO2bTb47dJpT1oZwiNm6u0P3r4mJPHzvD0yVOd6U2nSp0qRF+LIvZGDCnPUgjfGU7j1tq9E+NuxnHt0jXSsgTOjxzqcSriFMn3k3lwP5lTEaeo51BPZ9oN2V9atXVii89OAE4d/4NiFkWxstZuMFhZl8K8qDknj/8BwBafnbR2cwIgOemBxq5w4ULo8pbm4urAdnWdnj5xjqIW5lhm0W6p1n76+FkAtvvsolVbRwCu/HWNf65c16FiFfXr1MSiWO49EfcfOEJHV2eEENSuUZWkpGTiE+5w8OgJmjSoi0WxolgUK0qTBnU5ePSEDpWDc1sHTew4c+IcxSyKYmml/UBiaVUS86JFNHXut2kXLm4Oqv1dHdjuo3p3tt3HHxf1b5HfnPvzKuVsrShjY4WJSQFc7Ruy/8gpLZur/0bRqLaqt0XDWlWzleuD6nWrcvPaLaJuRJPyLIUgvxDs2zTXsnFo04xdvoEAhPiH0aB5Rm80B9fm3LoRxdU//9GpboD/1Xmf2GvRxP0bS+qzFA7vPEC9Vg21bBJuxvPvpevZYjpAxRqVsChlwdnw07qSrKG1mxNbNu4A1HGx2HPiYuQZALZs3EEbt5ZADnFRhz3VXNo6sG2T6ho7feKs6hrNMS4W4ZQ6pm/b5E8rN0dAleBJTU0F4NTxs9jYWetEd426Vfn3n5vcuhFFyrMUArfvw7FNCy0bxzYt2LlJlRzZ6x9Kw+aq+/zlc38RH6tKol259A+mBU0xMTXRke5q3Mike8/2vTi10b7/O7ZpwQ617mD//TRqXh9QtblOHfuDJ0+e6ERrVs5F3aFs8SKUKV4EE2Mj2lQrQ+hf0bna775wE9fqqhfMAniaksaz1DSepqaSkqpQskhBHSk3XD+vXrcq/167xS11TA/224dDlphu36Y5u3z3AM+L6dd0ojcd02ofknLzFqlR0ZCSwsO9IZjZv+QzXUoKPHsGgDAx1W0iELD46H88/CeGR9fjUJ6lErP9EFau9bVsUpMfaf43LlyQ9MZskSqluRNxDoCnCYk8S3xIsTqVdKa9RN3KJF+L5cGNeJRnqfzrdwS7NtrPNymZtBfIpF2fvJelzqO2H8Y6S51n160Wrqh+A2FshLGZKWnPUkhJeoTk9VAUJV/+9IFMZOoJoWKhEOKcEOKsECLzWK9iQohtQogLQogVQohcfychRBEhxBohRKQQ4pQQopN6+1EhRPVMdqFCiHq52ecnxlalSI2J13xOjUuggHX2NyqFnZtT2vcnrBZNwdhat8OvcsPKxpKYW7Gaz7HRcVjbamuztrEkWm2TmppKUlIy75WwwNrWkpioTPtGxel0uK21jRXRWc6fdVibla0lMbfiAG3t+qSkTUniozLe5idEJ1DS+uXe2Ja0KUlCVIav3Y5OoKSN7t72GrK/2NhaEXUrRvM5JioWa1srLRtrWystjdFRsdhkshkzaSiH/wii88ftWDJ3ef6LzqQrs6/H5ODr1jba9RsTnf37vW3Ext/GxiojVlpblSI2PoHY+ARsrDK+n7WlarsusbaxzF7nOflLdJy2jfp3KWlZgvi42wDEx92mRKniOlANsbfvYm1ZIkNjqRLE3b6rZVOlYln2HjwOwL7DJ3jw6DH3ElUDKZ4+fUb3ETPoNWoWITrswWtpU4rYqIy6jIuOx9K2VK42qampJCc+wKKEBWaFzOg9uCc/L/5FZ3ozU9ymBLejM/zzTvRtSrxkXBZC0GvyZ6z30o92G1srorPERZssfm6TJS5mtRkzaShHzgbTuVs7FuswLr689rjn2gB069WJ0H0H809sJqxsLbV8PTY6DkvbHNoumX096UG2totLe0cun/uTZ0+f5b9owDoH3VZZ7/+2lsRGZdz/k9+CNhdAXNJjbIoV0ny2LlqIuKTHOdpG3X9I1L0HNCyv+m61y5SkQflSuHy/m1bf76ZJJSsqlSqmE91guH6eNabHRsdn9/MXxPRVi9fpRGtmjCxLkRqXoTs1LgFjy+xt1UKOLbD6bRUl5kzDOFN7xdjKEqvfVmHtt5Hk3zeSlnBbJ7oBzGxK8Dgq43yPo+5Q0KZENruyn7Wm+dHvqDKlF5cmrQMg6cINLF3rI4yNKFTOkmK1KmJmp7vni0I2JXh0K0P7o+g7FLLJ3m6q3LcVroeXUHNyD05PzrhvFilniXPQHBy2TqZUo5ynAsoPzGyK80irzm9jloPu8p+1wvHot3w4pSfnJ6l0R+88SurDJzj/8SMtTy7l6o/+PLv3INu+kv8uMpGpP7oAdYDagAuwUAiRPlleQ2AUUBOorLbNjUlAiKIoDQAn9XGKABsBDwD1ce0URTnxHPvnIoQYKIQ4LoQ47n375qt90xzeuGXN3D8MO8y/bT/lVrdBPDp6CsvZY7Ltow9EjtpfbIOSy766fD2Woywli8mLfxud8xJ1/gq7vvzObwBD9pectSsvYZPx/8I5S2lSqzXbN++iz+fZ503KL/Ku/S14Xf0cctInhMjRpXP0q/zkZerzNa5lXZK17kb18+TEuct4DJvG8bOXsSpZHGNjVXMpcO0iNn47jfljBrFg1Qb+zZSo1aVGIFtvi5xtFAaO+QzvVb48eqifngyvc59p1duV0/tPcCdadw+7WryMD7/gWlg4ZymNa7Ziu+8u+g542+Ji9v2xT1/8AAAgAElEQVSy2gwe2Z+UlFT8fAPeqL5cycWPtU2e/90qfVCRYZMHM3vMwjcuL1fyHBP1HxRzUpDbHSXwwk1cPiyNsZHK4sadZK4mJBE01JWgoW2JvB7PCR0OLTdUP89ruwVFYdCYfvqL6S9xfT4+cJiYLj2J+3QAj4+fpPiUjKlnUuPiift0ALHdPqWwWxuMiuvmJSaQi1Nn9/5/1wZxoNFw/py9gUoj3QGI2rCfJ9F3aBTkxQez+nAv8k8UdU9enfCSzzdX1gWzp8nXnJ2zkQ9HdAbgcdw9AuoPZ1/rSZyZ/jsNl39FAfNC2fbNF16ybXp9bTChjUZwafYG3lfX+Xt1K6OkprGv9mD2NxhOpS/aUaj8290BwSCQQ8slb4DmgLeiKKmKosQCYUADddkxRVGuKoqSCnirbXOjNTBeCHEaCAXMgHLAJiB9lRQPwPcF9s9FUZSViqLUVxSlfo+SZV5krkVqbDzGNpnfxpUiNU77oSTtfpJmuEHSlgAKVq3ySufIL2Kj47ApnTHMxNrWirhMvUsBYqLjsFXbGBsbU7SoOffu3icmKk5riIq1nRXxMbpr3MVGx2Gb5fxxWc6v+n6qm0K69vt3tedF0jW3oxOwtMvoaVTKthR34l7uITYh+jal7DJ8raRtKW7H3nnOHm8WQ/OX3v09CQjdREDoJmJj4rErnTGRvI2ddXbtUbFaGm3trImNyZ7I8dscQNsOLvknHOjVrxs79m9gx/4NxMbEa/m6jZ0VcbHadRcTrV2/NrbZv9/bho1VKWLiMr5HbFwCVqVKqrdnaI+NV23Pb3r268a2kPVsC1lPXExC9jrPUp+xWXq9qH4Xlc3t+DuaoeiWViW5k6DdKzK/sC5ZnNj4jJgQm3AHyxLvadlYlSzON5OGsun7GQzr3RWAokUKa8oAythYUb/mh1zU0ZQEcdHxWNtl1KWVrWW2+JDZxtjYGPNiRbh/N5EadasxZPIgth/dSPfPP6bv0E/o9pm7TnQD3Im5TclMvUdL2Jbk7kvG5fc/+oDWfdz47sBP9JrUl+ZdHOk+LvsiKm+S3v27szvMl91hvsTFxGGbJS5mjXlZ46LKJnts2a6DuPhpPw/892/Ef/9GVVzMpl1bV3RUHDZ2VrnadPHsQMvW9oz8YlK+6s5MXFSclq9b22a/F8Zm0m1sbIx50SKatouVrSVL1ngxZegsbl7Xnv82P4l9Sd3Wdhn3f/O3oM0FYF3UjJjEjKRYbNIjLIua5Wi758JNXKtnPAeE/BlFrdIlKGxagMKmBWhWyYY/buVvu+ud8PMsMd3a1pKEbG30nGN69bpVGTr5C/yO+tBDE9Of1+flzZEWF4+xVYZuY6tSpCZo605LTNQ80z3024XJh+9nP07CbZ5dvYZpnZr5KzgTj6PvaPWiNLMrwZOY3NseMdsOYdlW9WiupKZxeeqvHHEez+k+izCxKMLDqzG57vumeRR9h0KlM7QXsi3Bo9h7udr/u/0wpdVDuNOepvD0rmpUyb0/rvHgeixFK9vkuu+b5HH0HQpp1XlJHj+nzqO2Hca6rUq3XZdmxIecQUlJ5WlCIncj/+S92robzi95+5GJTP3xvFcUWdPaz0tzC6Croih11H/lFEW5qCjKLeC2EKIW4Imqh2au9nn+Fi/Bk/OXMSlXmgKlbaBAAYq4OvIw7LCWjXGpjK79hR2b8PSfG/kp6aU5e+oC5SuVpXQ5O0xMCuDm3pr9gRFaNvsDw+nk2Q6ANh1acuTAcfX2CNzcW2NiakLpcnaUr1SWP07qbrGCc6cuUq5SWUqXs1Vp79yK/YHaCynsD4ygk4dKe+sOLTmq1q5P/jzzJ3YVS2Nd1poCJgWw72DP0eCXm8z8ZNgJ6raoSxELc4pYmFO3RV1Ohulu7kBD85dfV/vg5uiBm6MHQQEhdPVUrYJYt34tkhKTsiUD42ITeJD8gLr1awHQ1bMDwbv3A1Ah0wJerdo6cuWv/J2Lb/0aXzo69aSjU0/27g6ls7pO69SrQVJismaetHTi1drr1KsBQGfPduzdE5avGl8Xx+aN2bFnH4qicObcRczNi2BZqgTNGtXj0LGT3E9M4n5iEoeOnaRZo/yfC3bDGl/cW/bCvWUv9u0O1cSO2ul1nuWFQ3zcbR4kP6S2us47ebRj325VnYcEhtPZsz0AnT3bs09Hv0X1KhW5HhXHzZh4nj1LYU/4MRwb1dWyuXs/ibS0NAB+9t2FeyvV/HyJyQ94qn44u3s/idMX/qJyOTud6L5w+hJlK5bBrqwNBUwK0LpTSyKCtIdAhgcdpF23NgC0bO/A8QOquT0Hug+lc6PudG7UnY0/b2bd0t/xXbtNJ7oBrpz5C5uKtliWtcLYpABNOjTnRHDkS+27fPi3DGs6kOHNB7F+zjoObA1l4/zf8lXvr6s30tahG20duhG4K4Su3VWrrKriYvKL42L3jgQF5BQXnfI9Lv62ZhPtnbrT3qk7wQH7cfdQXWN16tV8Tlx8SJ16qmSCu0d79qqvUfuWTRk0rC8DPxnB40c5DzPOD86fvkS5SmWwK2dLAZMCtOnsTGjQAS2bsKADdPBQrYTs0t6RyIOq+7x5MXOW/r6QpV4/cSbyrM40q3RfVN//VbpdO7sQGqR9/w8NOkBHte5W7Z04dlC3cxvnRnW74ty4m8ytew94lppG4IWbOLxvm83u2u0kEh8/o3bpjDa7bbHCnLiRQEqaap7MEzcSqFQq97mf3wTvgp9fOH2JchXLYFdW5S+tOjkTniWmRwQdpF03V0AV0yMPqKYzGeg+lE6NPOnUyBNvTUzfqhPdTy9eokDZ0hjbqp7pCru05HGE9jOdUckM/zBr0ZSUa6pnOiPLUlDQFABR1JyCtaqTcuNfnegGSDx1hcKVbChUzhJhYoxN56bEBWpfg4UrZiT4LFvV5eFV1VyxRoVMVXNmAiXsa6KkpPLgT929KLl7+irmFW0oXFalvWynxkRn0W5eMVNHA5c6JP2jSrSaliwK6h7URcpZYl7RhuTruhlNcv/UFYpkqnO7zk2IfU6dW7WqywN1gvjRrQRKNlfNkmdcuCDvffQ/kv+O0onud5p3qEdmAb2cVQIQDgwSQvwClADsgTHAh0BDIURF4DqqJOTK5xwnEBgqhBiqKIoihKirKEr6ygQbgbGAhaIoZ1/CPn9ITeP23GXY/DgXjIxI2h7IsyvXeW9wH56e/5OHYYcp1rMzhR2boKSkkpaYRMKUjOFAtmuXYFKhLKJwIcoGbSBh+hIeHdJNwi01NZXZ4xfys8/3GBkbsXXDTv6+fJWh4wZy7vRF9gdGsHn9DuYvn8Geo1u4fzeRUYNUb3T/vnyVPX578T/gQ2pKKrPGLdA8HOtK+5wJi1i5UaV9m/dOrlz+hyFjB3L+jEr7lg07mLdsOruPbOb+vURGD8pYkTUochvmRYtgYmpCy7YODPQcxhUdLBSRlprGiik/MvO3WRgZGxHsE8yNP2/Q6+tP+OvsXxwLPsr7td5n0qrJmFuY09ClIT2/7sVXLoNJvp+Mz/cb+WbnNwBs/M6b5PvJ+a45HUP2l5DgCJxatSD8+C4ePXrM6KFTNGUBoZtwc/QAYNLo2SxeNhszs4KE7jvA/r2qB8zxU0dQ6X8VSEtL49a/0UwcPUtn2kODD+Dg0ox9x/x49Ogx44dN15Tt2L+Bjk49AZg2Zi7zl07HzMyMsJCDhO1VPTS0cnNi6twxlChZnFUbvuPi+T/p5zEk33WPmTaPyFN/cO9eIs6dP2Fw/09JSUkBwNO9HfZNGhBxOJK2Hv0oZGbGrIkjAbAoVpRBfXvQ/XPVqtlffNbzuYsG5Qdhew9i79KMoGPbePzwMROHz9SUbQtZj3tL1WqZM8bOw+v7aZgVKkjEvkOE7zsEwKrvf+GbVXPp2qsj0TdjGfF5zquev2kKGBsz8YtefDl1MalpaXRu1YL/lS/N8t+3Ue39Cjg1qkvk2Ut8/8tmhBB8VKMKk75U9QC8+m8UM5f9gpEwIk1Jo1+3dlQuV/oFZ3wzpKamsnDSt3y/YRFGxkbs3BjA1T+vMXBMPy6euURE0CF2eAcw4/tJbDm4nsR7SUz6coZOtL2ItNQ01k1dxfhfp2FkbETopn3c+utfPv66B1f/+JuTeyOpVOt/jFw5jiIW5nzk0oCPR3ZnbCvdrQqfG6q4aE/EiQBVXByScY/cHeZLWwfVwJdJo2exePlszMzM2L/3APv3qhJY46eNoPL/KpCWpnDr3ygmjNJdXNwffABHl+bsj9zB40ePGZspLvrv30h7p+4ATBnjxYKlMzAzK0jYvoOEqmP69HnjMC1oyq+bfwRUC6lMHj0n33WnpqYyf+I3/OC9BCNjY/y8/bl6+R++HPs5F05fIizoANs3+DN72RT8DvuQeC+R8YOmAdC9X1fKVizDgJF9GTCyLwBfdh/B3YTcey69Sd1eExfzo/e3GBsbsd3bnyuX/2Hw2AFcOH2R0KADbNuwE69l0/A/7Mv9e4mMHZRxn90duRVz8yKYmBagpas9g7oP19lCLgWMjBjfujZfbjxIWhp0ql2e/1kW44ewC1SzLY5jFVVSc/f5m7hWK6015Nnlw9IcuxZPt1X7EAiaVrbKMQmaXxiyny9Qx3RjYyN2qGP6oDH9uHjmMuFBB/Hz3sWM7yex9eAGdUyf/sLj5jupadxbvJRS384HI2Me+O8m5Z9rFB3Ql2cX/+TxgUOYe3TBrHlTSE0lLTGRu7PnA2BSoTwWw75Qdc8RkLRhEylXdLcAnZKaxqUJa/lo40SEsRG3vPfz4PJNKo/tRuKZq8QHnqBs/zaUbFGDtJRUUu4/4NwwlV+YlrKg3sYJKGkKT2LucHaI7uY7Ttd+euI6WniPQxgbcW1jGIl/3qLamK7cPfMP0UEnqdyvNVYtaqA8S+Xp/QccH7YCAMvGH1JtzMcoKakoaWmcHLdGZ3NNKqlpnJuwjoYbJyCMjbjpHUry5ZtUGfsx9878Q1zgCSr0b02pFjVJS0kh5f4Dzqjr/PqaIGp/9wX2YQtBwM2NYSRdeDs6Ohkyip6SjvmBeBvmZvkvIYQoAMQCpYAFQFtUIX22oig+QghHYCoQj2qOzHBgsKIoaUKIa4ApkJ7d2IRqzstvgaaoelteUxSlvfpc1sAtYJaiKDPU2wrlZK8+7+j0fZ/HP7VbGaTTuEXf17eEPGGk67nv3iAVC2Zf1MkQuPL47R5y/DwepuquR8GbxtRIN6vLvmkuXPR9sdFbSs1qni82egs5c/A7fUvIMy0cJuhbQp74n0n2RREMhQNJf+tbQp4pYGSYfQ4sChTWt4Q8k4ruXiK+SY7Od9C3hDxTfVSgviXkmZKmun2R+KbYXt4wYwvA+auGOVdiopGxviXkmUI67FzxpmkX6224D9NvmPufueRLHsdi7V6d17HhRjDDpTpwRVFlkMeo/zQoihKKau7KbCiKUiGXYw7KxT6WLL+xoiiPcrJ/3nklEolEIpFIJBKJRCKRSCQGyjvUI1POkalDhBBfoFq8Z/KLbCUSiUQikUgkEolEIpFIJBJJBrJHpg5RFGUFsELfOiQSiUQikUgkEolEIpFIJP8RDHeGgGzIHpkSiUQikUgkEolEIpFIJBKJ5K1HLvYjeWWqWNY3SKcpVqCQviXkiWQDXrwlVTHM1z4Cw50TOv5R/q/Oml8UNzPMCfNNDXQxDoCzF3z0LSFPVK/qoW8JecZYGOY75DtPEvUtIc/YFDLchYqepqXoW0KeSFFS9S0hzxQ00IXnHqY+0beEPFNAGO4iKIbq64bcdjFUDDWeA6QaqJ8DXL/9h+E+2L1h7vVqmS95nPfWh8jFfiQSiUQikUgkEolEIpFIJBLJG0Iu9iORSCQSiUQikUgkEolEIpFIJDkjhHAVQlwWQvwthBifi42HEOKCEOK8EGLDi44pe2RKJBKJRCKRSCQSiUQikUgk7yp6mPVNCGEMLAdaATeBSCHEDkVRLmSyeR+YADRTFOWuEMLqRceVPTIlEolEIpFIJBKJRCKRSCQSyZukIfC3oihXFUV5CmwEOmWxGQAsVxTlLoCiKHEvOqhMZEokEolEIpFIJBKJRCKRSCTvKEqaki9/QoiBQojjmf4GZjptaeDfTJ9vqrdlpgpQRQhxUAhxRAjh+qLvIhOZEp0y2Ws0wce2sSPUm2q1PsjRpnqtD9kZtpHgY9uY7DVas93ivWKs9V1O0NGtrPVdTjEL3axw3MSpIVsi1rPtkDd9hvTKVm5iaoLXiulsO+TNul0/YVvGRvU96lRlffAa1gevYcPetTi2baETvVmZNGcUgUe34he6gWo1c6/zHaHeBB7dyqQ5ozTbLd4rxmrfZew5soXVvst0VucAU7zGsPfYdnaGbqRarQ9ztKle60P8w3zYe2w7U7zGaLa7dnQhIGITl2MjqVG7qq4ka3gdP3ft6MyuCB8uxR7TufZ5C6dw4sw+Dhzxp1bt6jna1K5TnYNHd3HizD7mLZyi2b76l+8IP7SD8EM7OHM+lPBDO3QlG4CpXmMJOeZHQJgP1XPxlxq1q7I7fBMhx/yY6jVWs3389BEEH95KQJgPP/6ymKLFzHUlGzDMa3Sy1xLs23Wn8ydf5FiuKApe3/xIW49+uPf+kguX/9aU+QUE4+bZHzfP/vgFBOtEb1YM8Rpt7tSYgEO+7Dm6hc+H9s5WbmJqwpKVc9hzdAsbd6/BrqytpmzAsD7sObqFgEO+NHNqrDPNmZkzfxJHTgWy/6AfNWtXy9GmVp3qhB7awZFTgcyZP0mrrP/ATzh4fDdhR3YyZeboHPd/0zR1aoTfAW92Ht5EvyGfZis3MTVhwU8z2Xl4E78HrMKurOr+39i+Ad6Ba9i8/ze8A9fQsFk9nejNjKH7iyG2AZo5NWbnQR8CjvjSf2jO/rJo5WwCjviyYfdqTZ1bFC/Gmq3LOXY1hIleo7LtpysM9T5qiPE8HUOtczDMtgsYrm4wXH+ZPnccYZH+7AnfTI1aOV9nNWpXJTBiC2GR/kyfO06zfdSEr9gTvpmA0E38tnkFVjaWupL9bpKWP3+KoqxUFKV+pr+Vmc6a04rmWVcdKgC8DzgCPYCfhRDvPe+r/CcTmUKI5OeUOQoh/HMp6yeEOCuE+EMIcU4IkbVLbFb7zkKIapk+zxRCuDzH3lIIcVQIcUoI8UpZLyFEHSGEW6bPHXObSFVfOLg0o0KlsrRq6M6UUXOYsWBCjnYzFk5gyqg5tGroToVKZbF3bgrAwGF9ORxxjNaNunA44hgDh/XNd81GRkaM8/qaYb1G083hU9p0dqFilQpaNp16tCPpfhLuTXuwYeUmhk5WPdj/ffkqvV0H0KtVP4b2HM3EBWMwNjbOd82ZsXduSvlK5WjTqAtTR3kxbUHOLjFtwXimjvaiTaMulK9UjhYtVXU+YFgfjoRH4tq4K0fCIxkwrI9OdDu4NKN8pbK4NOzMlFGzmfkcX5k8ajYuDTtTPpOv/HXxb77qO4bIwyd1ojczr+vnf128wpC+Y4k8fEqXsmnV2oHKlStQr7YzI4ZOZvG3M3K0W/ztTEYMnUy92s5UrlwBl1b2APTvMxz7ph2xb9qRHX6B7NwRpDPtji7NqVCpHC0bdmLi17OZtXBijnazFk5k4tezadmwExUqlcPBuRkAB0KP4Nq8G24Only7cp3BI/rpTLuhXqOd3VqxYsnsXMsjDkdy42YUAT6rmT52GLMWLQPgfmISP67dgPeqb/Fe9S0/rt3A/cQknWhOxxCvUSMjI6bMH8vAHsPp0NyTdl3aULlKRS2bj3t15P79JFwbdeXXn7wZPWUIAJWrVMTNvTUdWnRnQPfhTJ0/FiMj3Tb/nFvZU7FyeRrXbcPo4VNZsGRajnYLlkxj9PCpNK7bhoqVy9PSRdUUataiEa7tWuLUtCMOjTvw4/dr8l2zkZERE+eOZnDPUbjb98TV3YVKWe7/7j07kHgviQ5NPPj9Jx9GTB4MwL079xnWeywfO33KlOGzmbNsar7rzardkP3FENsARkZGTJ43mi97jqRjix64ubfO5i9denYk8V4ibo278dtP3nw95SsAnj55ytJ5K1k0fanO9GbFUO+jhhjP0zHUOgfDbbsYqm4wXH9xcmlOxUrlcWjQnglfz2T2osk52s1ZNJkJI2fg0KA9FSuVx9G5OQA/LVuHq/3HuDl6sC8onOGjB+lEt+SNchMom+lzGSAqBxs/RVGeKYryD3AZVWIzV/6Ticy8IIQoA0wCmiuKUgtoDPzxgt06A5pEpqIoUxVF2fsce2fgkqIodRVFiXhFiXUATSJTUZQdiqLMe8Vj5CvOrg5s8wkA4MyJcxS1KIqldUktG0vrkpgXLcLp42cB2OYTgEtbR9X+bR3Y5uOv3u6Pi5tjvmuuXrcq/167xa0b0aQ8SyHIbx8ObZpr2Ti4tsB/0x4A9vmH0rCFqufFk0dPSE1NBaBgQVMUJeuLh/zHua0Dfpt2Aao6L2ZRFEurLHVupV3nfpt24eLmoNrf1YHt6jrf7uOv+S3yGxdXB7b7qHSfPnGOohbmWFqX0tZtXQrzouYa3dt9dtFKre/KX9f458p1nWjNyuv6ub60u7V3YaP3NgCOR57GwqIY1tbabz2trS0pWsycyGOqBv9G722069Aq27Hcu7ixxXdn/otW49LWgW2bVH56+sRZlZ/n6C9FOHVcFba3bfKnlTqGHAg9orlWTx0/i42dtc60G+o1Wr9OTSyK5d4TYf+BI3R0dUYIQe0aVUlKSiY+4Q4Hj56gSYO6WBQrikWxojRpUJeDR0/oRHM6hniN1vqoOjf+ucnN61E8e5ZCwLYgWrraa9m0dHXATx03A3eG0LhFA/V2ewK2BfHs6TNu3Yjixj83qfVRzj2u8wvXds74evsBcOL4GYpZFMMqS3yxsrbEvKg5xyNPA+Dr7Ufb9qp3v336d2fpN6t4+vQZAAkJd/Jdc4261fj3n5vcuhFFyrMU9mzfi2Mb7XfMTm1asGPTbgCC/ffTsHl9AC6d+5P42AQA/r50FdOCppiYmuS75nQM3V8MsQ1Q86NqmjpPeZbC7u3BOdR5C/w2qWJP0M79NFL7y6OHjzl17AxPnjzVqebMGOp91BDjeTqGWudguG0XQ9UNhusvrdo6scVnp/q8f1DMoihWWXRbqeP5SbXuLT47ae3mBEBy0gONXeHChbJ145O8Gvk1tPwFRALvCyEqCiFMge5A1qF72wEnACFEKVRDza8+76D/2USmULFQ3bPyrBDCM1NxMSHENvXy7yuEEEaAFZAEJAMoipKszhYjhBgghIgUQpwRQmwRQhQWQjQFOgILhRCnhRCVhRDrhBAfq/eZpz7+H0KIRUKIOsACwE1tX0gI8aN6joHzQogZmbQ3EEIcUp/vmBDCApgJeKr39RRC9BVCLFPblxdC7FOfa58Qopx6+zohxPfqY11N15ZfWNtaEhMVo/kcGxWLtY32glTWNlbERMVm2ETHYm2retgpZVmC+NjbAMTH3qZkqeL5KRcAKxtLYm9lzDUbFx2PlU2W4GtTitgolU1qairJiQ+wKGEBQPW61fAJ/ZWN+9cxd9wizQ1EV1jbWBKdqT5jouKwts1S57ZWxETHaduou+2XtCxBfJy6zuNuU0IHdZ6uKZvuLEMJrG0stXwlJjo223fTB6/r5/rC1taaWzejNZ+jomKwzdLIsbWzJupWxneLuhWDra22TdNmDYiLS+CqDh8MbGytiM6kKyYqFpssvmBja0VMVNxzbQC69epE6L6D+Sc2C4Z6jb6I2Pjb2FhlxEprq1LExicQG5+AjVWGr1tbqrbrEkO8Rq1sLIm5lVlPXDY91jaWRKttUlNTSUpK5r0SFurvm2nfqDidD82ytbXm1q2M+BKdS3yJzvS7REVlxJfKlSvQqEl9du/zYduu36jzUY1812yVpd7iouOz1Xlmm9TUVJKTHvCe+v6fjkt7Jy6d+5Nn6iSsLjB0fzHENoCVjaXWPSanerOyzfhdVP6SnM1f9IWh3kcNMZ6nY6h1DobbdjFU3WC4/mJja6X17BATlT1WW9tqX6PRWXSPmTSUw38E0fnjdiyZuzz/RUveKIqipABDgEDgIrBJUZTz6tHKHdVmgcBtIcQFYD8wRlGU28877n82kQl0QdWLsTbggirhmD5BUENgFFATqKy2PQPEAv8IIdYKITpkOtZWRVEaKIpSG9WP019RlEOoMs1jFEWpoyjKlXRjIUQJwB2oru7dOVtRlNPAVMBHbf8ImKQoSn2gFuAghKilzmL7AMPV53MBHmTZ1yfLd10G/Ko+13rg+0xltkBzoD2Qaw/OzBO43n8c/4KqzfUY2bZl7aX4MjY6JYcZHbLJyUFzutH5UxfwdOxN77YD+WzoJ5gWNH3zGp/Hy9Rnjjb5JejlMEhfUWOo2vOuW/tz127t2eKb4+wc+cbLac++X1abwSP7k5KSip9vwBvV91wM9Bp9ETn5sxAiR905/X75iSFeoy9z7eVYj0ou++q6T8NLXH/Pu0YLFDDmvfeK0dbZk5lTFrBq3bf5ofKl9bysTeUPKjJi8mBmjVnwpuU9F0P3l3fmGs1qk8OFoO97fzqGeh81RF9Jx1DrHDDctouh6sZw/eVNPF8snLOUJrVas33zLvp83uONa/xPkU9zZL4IRVECFEWpoihKZUVR5qi3TVUUZYf6f0VRlK8VRammKEpNRVE2vuiYBV7ha79rNAe8FUVJBWKFEGFAAyAROKYoylUAIYQ3quHkm9WrJzVANQT8GyFEPUVRpgM1hBCzgfcAc1QZ5eeRCDxGNYnpLiC3p34PoVrxqQCqhGM1VO2iaEVRIgEURUlU63ze+ZqgSsYC/Iaq52c62xVFSQMuCCFy7WOunrB1JUAVy/ovHc579euGx6edATh76gI2djaocsJgbWdNXKx2UjQmOlarq7u1rTVxMareOgnxd7C0Lkl87G0srUtyO9o14WgAACAASURBVOHuy8rIM3HR8ViXzngjZGVrqRkupmVjZ0VcdDzGxsaYFyvC/buJWjbX/rrOo4ePqfxhRS6euZyvmnv260a3TzLqPHOvFxs7K+JitOs8NstbLxs7K83vcjv+DpZWJYmPu42lVUnu5GOd9+rXDc9P3QH4IyfdWeo9JjpOy1dsbK2zfTdd8Sb9XJd8PvATevf1AODkibOULpOx2IOdnY3WG2lQ9cC0K22TYVPahpiYjDeoxsbGtO/YBqfmnfNZOXzazwPPT1Vh7Y/T57HNpMvGzprYLL4QHRWHjZ1VrjZdPDvQsrU9n3TJ/7l3DPUafRVsrEoRE5fh07FxCViVKomNVSkiT2XMyhIbn0CDurXyXY+hXqPpxEbHYVM6s57sfhITHYdtaWtio+MwNjamaFFz7t29T0yUdqy0trMiXgff5bPPe/JJn24AnD51ltKlM+KLbY7xJRZbu0zxxc6GmBiVTVRULLt2qhaGOnXyLGlpaZQsWZzbt/PP32Oj4rXqzcrWMpsPpNto7v9FM+7/VraWfLNmLpOHzuTm9Vv5pjNH7QboL4bcBgB1nWe6x6jqLT67TWlrYjX+Yp6tvahLDPU+asjx3FDrHAy37WKousFw/aV3f0+6f9pVpfvUea1nBxu77LE6Jkr7GrW1syY2RruNAOC3OYC1G5fzzfwf8kn5u4/yEklHQ+G/3CPzeZm/rIk6BTSZ4mOKosxFNba/q7p8HTBEUZSawAzA7HknVnevbQhsQTWP5p5s4oSoCIwGnNU9KXepjyty0PeqZN7/SebTvuZxs7F+jS+dnHrRyakXe3eH4u6pmsazdr0aJCcma4aKpxMfe5sHyQ+oXU81bMzd0419e8IACNkThrtne/X29uzbHfam5WbjwulLlK1YBruythQwKUDrTs6EBx7QsgkPPEB7D1cAnNs7EnlANbm8XVlbzeI+NmWsKV+5HFH/xpDfbFjji3vLXri37MW+3aF08mgHqOo8KTFZMyQinfi42zxIfqip804e7TR1GxIYTmd1nXf2bK/5LfKD9Wt86ejUk45OPdm7O5TOnirdddJ1Z3mIiY9N4EHyA+qodXf2bMfefNT3PN6kn+uSn1f+rlmgJ8A/mO49VA+R9RvUITExidgsDwOxsfEkJz2gfoM6AHTv4U6Af8a0v45Ozfjrz6tEReW/n/+2ZhPtnbrT3qk7wQH7cfdQ+WmdejWf4y8PqVOvJgDuHu3Zq/Zz+5ZNGTSsLwM/GcHjR4/zXbuhXqOvgmPzxuzYsw9FUThz7iLm5kWwLFWCZo3qcejYSe4nJnE/MYlDx07SrFH+r+hsqNdoOmdPXaB8pbKULmeHiUkB3Nxbsz9Qeyrt/YHhdFLHzTYdWnLkwHH19gjc3FtjYmpC6XJ2lK9Ulj9Ons93zWt/3oBzC3ecW7iz238f3Xqo1kesV782SYlJ2ZINcbHxJCc/oF792gB069GJPbv2AbB7116a2zcCoFLlCpiYmORrEhPg/OmLlKtUhtLlVPd/184uhAVp3/9DgyLo6NEWgFbtnTh2UDXfa9Fi5iz7fRHfea3gdOTZfNWZE4boL4bcBgA4d+oi5SqV1fhL286tcqjzCDp5qGJP6w5OHFXXub4w1PuoIcdzQ61zMNy2i6HqBsP1l19X++Dm6IGbowdBASF09VQNZK1bv5b6/p+lU5A6ntetr3qx3dWzA8G79wNQoVI5jV2rto5c+euffNUuMRzE29C1XtcI1arlvYFBqBbIKQEcBxoBHwK7UfV+vK7+fyVwGLBRFOWk+hifA50VRWkvhEhQ298FAoBbiqL0FUIsBU4qirJWvc86VL0v9wCFFUWJUw8z/1tRlBJCiL5AfUVRhgghagO/AnUBS1QLC40DNgCXAE9FUSKFEEWBR0AnoKOiKH3U58p8rB2Ar6Iov6m3d1IUxT1dj6Iom9PrRVEU8xfV36v0yMzKtPljaeHUlEePHjNh2AzOnbkIgN/+9XRy6gVAjdpVmbd0OmZmBQkPOcTM8aoOpO8Vt+C7n+diW8aG6JsxDOs/nvv3Xv5NdrEChfKkuVnLxnw9cxjGxkbs2LiLNd/9xqAx/bl45hLhQQcxLWjKzKWT+aDG+yTeS2TiF9O5dSMat4/b0GdIL1KepaAoCquWrCNsz6uu4QTJqa93s5kybywtWjbh8cPHTBw+U1Pn20LW494yo869vp+GWaGCROw7xKwJCwFVnX+zai62ZayJvhnLiM9frc5TX+O1z7T547BX+8r4YdM1unfs30BHp54a3fOXTsfMzIywkIMaX2nl5sTUuWMoUbI4ifeTuHj+T/p5DHnpc+c0/OvVtOfdz1u5OTIli/b+HkNf+tzxj+7lWffCJdNxdrHn0aNHfPXFOE6fOgdA+KEd2DdVTWFSp24NfvhpAWZmZuwNDmPsqIzVzZevmM/xyNOsXe2dp/MXN8t98ZgXMWP+eOxbNuXxo8eMHTads6cvAOC/fyPtnboDULNONRYsnYGZWUHC9h1k+vj5AIQc88O0oCn37twHVJOoTx4956XPbWr0eoMb9HmNnr2QdSaSl2PMtHlEnvqDe/cSKVniPQb3/5SUlBQAPN3boSgKc5b8wIEjxylkZsasiSOpUbUKAFv9A1n1q+q8A/t0x71d61c+f/WqHnnSnY4+r1Fjkbd3yPbOTZkw+2uMjI3YumEnP327lqHjBnLu9EX2B0ZgWtCU+ctnULVmFe7fTWTUoEncvK5aFHLQiM/o0rMDqSmpzJ28hIiQw698/jtPXq/n2NxFU2jp0oJHDx8z/KuJnFHHl30R23BuoXqJUrtuDb7/wQuzQmbsC45g4phZAJiYmPDt8jnUqPkhT589Y8bkBRwIP/rS57YpVCJPmps7N2HszOEYGRuz3dufn7/7hcFjP+f86UuEBR3AtKApc5ZN5cMaVUi8l8jYQVO5dSOKASP60n/Yp1y/+q/mWF92H5mn3jtP01LypF3f/pKivN6c4PpsAxQ0ytvCTC2cmzBu1kiMjY3Y5u3Pym/X8dXYAZw/c4lQdZ3PXTZNVef3EhkzaIqmzgMjt2FetDAmpiYk3k9moOcwrv557ZXO/zD1yYuNnoM+76MFhHGedesznsPr+bpsu+St7WKouvMaz9PRp7+kvoafz1owEYeWzXj06DGjh07R6A4I3YSbo4dG9+JlszEzK0jovgNMHTcXgBXrllDpfxVIS0vj1r/RTBw9i9jo7L01n8f123/odg6jt5jb7RzyJflXcleYzuv4P5fIFEIUQDXXZSlUQ6zbouqhOFtRFB8hhCOq+SbjUc2RGQ4MRrVk/FrADtWw8HjgC0VRrgghvgTGokp8ngWKqhOZzYBVqHo9fgxMQZXIPAj4kdHDcpGiKL9kTj6qta5DlVy9qj7GDkVR1gkhGgBLgUKokpgugCmqIe0mwFx1WXoiswKwRv2d44HPFEW5oY9Epj7JayJT37xuIlOfvE4iU5+8biJTn7xOIlPfvE4iU5+87sOAPslrIlPfvG4iU5/kNZGpb143kalP8prIfBt43QdfffG6iUx9ktdEpr553USmPnmdRKa+MVRfN+S2i6FiqPEcXi+RqW9kIjMDmcg0YNQ9HVcpitJQ31oMFZnI1C0ykal7ZCJTP8hEpu6RiUzdIxOZukcmMnWPoSZ3QCYy9YFMZOoeQ267GCqGGs9BJjLfFRLa5k8is9Ru3ScyDbM1nUeEEF8A3sBkfWuRSCQSiUQikUgkEolEIpFIJC/Pf+pVjKIoK4AV+tYhkUgkEolEIpFIJBKJRCKR6ATDHCyZI/+pRKZEIpFIJBKJRCKRSCQSiUTyX8JAZ33LEZnIlLwyu61L6ltCnugYb5hzBz5LM9w5SaoUsta3hDxx5XG8viXkmRJmxfQt4T/HmYPf6VtCnjHUuSbPX9ykbwl5pmmtvvqWkCfqFyqjbwl5Jjz5b31LyDMFhGE21S1MCutbQp55kvZM3xLyxPn5zvqWkGeqj9unbwl5poTJC9dJfSvZbG2mbwl55nSMpb4l5IknxoY7VWOa4UqXvKMYZutIIpFIJBKJRCKRSCQSiUQikbyQd6lH5n9qsR+JRCKRSCQSiUQikUgkEolEYpjIHpkSiUQikUgkEolEIpFIJBLJO8q71CNTJjIlEolEIpFIJBKJRCKRSCSSdxXl3ZnsVA4tl0gkEolEIpFIJBKJRCKRSCRvPTKRKdEJhZrVp+zOnykXsJb3+mdfJbdop1ZUCPehzOYfKLP5B4p2dc0o6+hC2V1rKLtrDUU7uuhSNgDNnRrjf3ATu49s5vOhvbOVm5iasGjlbHYf2Yz37tXYlbUFwKJ4MdZu/YHIq/uZ5DVa17I1TPUaQ8gxP3aF+VC91oc52tSoXZWAcB9Cjvkx1WuMZvv46SMIOryFXWE+/PjLIooW083KjPUc67EqdBWrI1bTbXC3bOUmpiaM/2E8qyNW882Ob7AqYwVAAZMCjFw8kh+Cf2B54HJqNq6pE71Zmew1muBj29gR6k21Wh/kaFO91ofsDNtI8LFtTM7kH64dndkV4cOl2GPUqF1VV5IBw/SVdAxR+4ETZ+kwaALtBoxjte+ubOVRcQl8PnEBXYdMod/4ecQk3NGU1enYj25Dp9Jt6FSGztTPqumG6OeTvZZg3647nT/5IsdyRVHw+uZH2nr0w733l1y4nLHatV9AMG6e/XHz7I9fQLCuJGto4tiQzRG/s/XgBvoM6ZWt3MTUBK8V09l6cANr/VdgW8YGgGp1qrI+eLX6bw2Ori10LZ2aDnVZELKURWHLaf+le7byDxpWY9auRay74ksDtyZaZb9c9WV2wGJmByxm5M8TdCVZw/S54wiL9GdP+GZq1MrZV2vUrkpgxBbCIv2ZPnecZvuoCV+xJ3wzAaGb+G3zCqxsdLvSriHGRYCmTo3YGrEBv0Mb6Tvkk2zlJqYmzFsxA79DG/ll10qNr1evUxXv4LV4B69l4951OLW115lmMOz24sGrcXRaFUKHlftYc+SvbOUL953DY10YHuvC6LgqhObf7QYg8nqCZrvHujAaLt5FyF/ROtU+1WssIcf8CHiBn+8O36T287Ga7eOnjyD48FYCwnz48ZfFOvXzJk4N2RKxnm2HvJ8b07cd8mbdrp+0/Hx98BrWB69hw961OLbVbUwv1LQ+pbevofSOdVh85pmt3Lxja8qG+GLnswI7nxWYu7fVlFkv96JcxDasvp+lS8karJxq4XxgES6Hl/D+kA7Zyiv0dsZp/zyc/s/eecfXdP9//PlJxA41MhFitLX3DhkSkhhBEQRVWkptYoba1Oyv9KvVQQcRO0hIQobY1N5qk01lEGSc3x/3Su69uUEjOeltz/PxuI/HPefzPue87vu+z+fzOZ/zGfsX0s7/S0zfr5SVVqZ2FdrvmYNTxBIcwxZjVMxETulYOjbALXIp7keW86Ee7TUGdaBT6GI6hizEyX8WZTS0A5SsVIGef/7EB5+7yyUZACuHBnSOXEqXw8uprUd3zYEdcDuwGNeQhTjvnEWZWjl197rxEx/KrPvfipRZMJ/C4D/TkCmEkIQQv2lsFxFCxAsh9uTxfO8JIUZqbDvkdi4hRLgQotkbzpeSFx0GgZERZj5fED3Ch3vdPqO0uyMm1W1ymKXsO8iDXiN50Gskydv2qQ4tY0q5EQN42G8sD/uNodyIARjJWMkwMjJixmJvPu8/jm7t+uLeoyM13rfVsvmofzeSniTj1qoXv36/iQkzvwDg5YuXrFr8PUtnfyObXl0cnNtSrboNTi08mDFhPnOX6n8InLt0GjMmLMCphQfVqttg36ENAIfCj+Fm14fO9p7cvnmPEeOGFLhmIyMjvpj/BTMHzWS403AcPBywqaUdLx37diTlSQpD2w1l5487GTJdpcu1v6oBfKTLSKb3n85nMz9DCHm70Ns7t6Va9Sq4tOjBzIkLmLNEv8/nLJ3GzIkLcGnRg2rVq9Be7fMbV24yavBkTh49I6dsg4wVQ9aekZHJwjW/sWbOeHb+bwF7I45z895DLZvlP/nRtUMbtq2ex/B+3fjml61ZacWKFmXLqrlsWTWXVbPGFrheXQw1zru7u/Ddivm5pkcePcm9B1EE+v3E7MljmLdsNQCJScmsWbcR3x++xveHr1mzbiOJSclyycbIyIjJC8cz1subPg6D6OjRAdtaVbVsPPp1JulJMj3b9mfjD5sZ7aNqrL157RaDXIfh5TKUMV7eTFsyCWNjY9m0CyMjPp73GUs/ns8U57G07tYO61qVtWweRcWzduIqjvpH5jj+5fOX+LhPxMd9Iis/XSSXbAAcne2wrV4V++ZdmDZhLvOX+ei1W7DMh2nj52DfvAu21avi0MEOgO9Xr8e1fS/cHfpwIPggYycNl027IeaLoIr1KQsnMNprEh/ZD8C1uzO271fTsunerwtJicl4tOnLhrV+jPUZAahifYDrp/Rz+YRR/ScyY4m3bLFuyPXFjEyJRfsv8G3vlmwf6si+K1HcTNDO37w71GPzYHs2D7anXxNbOryvaoRtXrVi1v4fPFtT3MSY1tXka7B3cLbLivPpE+Yzb+l0vXbzlk5n+oT5GnHeFlDFuatdb9ztPblz8y4jZY7zMV6T6G0/kE564tyjX2eSE5Pp0aYfG9dm5+l/XrvFINfP8HIZwuj+k5guY5xjZET5aaOJ/WI6D3t+SilX/c90T4MjiPL8nCjPz0nZsTdrf+IvW4if8ZU8WnUxEjRc9AlH+y/hQHtvKvdoo9VQCfBg+xHCHKcS5jydG9/upt5s1YsUYWxE02+/4Ozknwi1n8yhnvPJTEuXTbowEjRdOJiDXkvYZz+Zqt1b52iovLv9CEFOUwl2mc7Vb/fQaLZ243ijOQOICT0nm2bI1h3utYRAh8lU9Wido6Hyzo4j7O0wlX0u07nyvz000dHdZPYAomXWrWAY/GcaMoGnQD0hRAn1tgvw8DX2b+I9YOQbrRQoVv8D0u5Fkf4gBtLTSdkbTimn1m8+ECjZtinPjp4mMymZzKQUnh09Tcm2r20TzlfqN6nD/dsPeHA3irS0dAJ3huDoqv2G38m1Pf6bVb2pgneH0squOQCpz55z+sQ5Xr54KZteXZzdHNixWdW+fvaPC5Qpa4qZRUUtGzOLipQ2LcWZU+cB2LF5Dy7ujoCqgpeRkaE6/tQFLK3NC1zz+43eJ+pOFDH3YkhPSydiVwStOrbSsmndsTX7t+4HIDIgkkZtGwFgU8uGs4fOApD4KJGnSU+p1bBWgWvWpIOrPTv8AgE498dFTMuaYmZRQcvGzKICpU1LcfbUBQB2+AXi7OYAwM0bd7h9866smsEwY8WQtV+8fgsbK3MqW5pjYlIE1/YtCDum3ah3634ULRvWAaBFg9o50gsTQ43zZo3qU7aMaa7pYYeO0c21A0IIGtarTXJyCvEJjzl8/A9aN29M2TKmlC1jSuvmjTl8/A/ZdNdtXJv7dx7y8F406WnphPgfwL6TnZZN+052BGxRvQQM3RNBc7smALxIfZEV38WKFUWSJNl0A9RoVJPYO9HE348lIy2dY7sP0dSlhZZNwoN47l+9i5T5z5qF3sXNkW1+uwE4c+o8ZcqaYq6Tt5hbVKS0aWlOq/OWbX676ajOW1KSn2bZlSxZAjk9b4j5IkC9xrV5cOcBD+9FkZ6WTpD/fhx0Yt3B1Y49m1WNIwf2hNO8XVMAnmvEelGZY92Q64sXo/+iynulqPxeKUyMjehU25rwP2Nytd975SGutSvl2B9yLZq2tuaUMJFvCQZnN/s8xrkDoB3nZ05dwNLaQhbdunl6sJ483d61HXs2q/L0A3vCaaGO88LM04vV+4D0+1GkP1Q90z0NCqekQ5u3Pv75iTNIz54VoMLcKde4Jim3Y3l2Lw4pLYMHO49i2amplk16SmrWd+OSxUCda5s7NCDp8j2SLt8DIO2vFMiUz+/lG9cg+U4sT+/Fk5mWwT3/Y1R6jfYiJYuhWeBUcm3K07txJF57IJdkQKU7RUd35TfolnR0p9yLI/G6vLr/zUiZokA+hcF/qSETYC/QWf29H+D7KkEIUV4IsVMIcV4IcUwI0UC9f7YQ4md1r8pbQogx6kMWAzWEEGeFEEvV+0oLIbYKIa4KITYIna5gQoihQoiVGtufCSFW6Ng4qK+V4zxCiOZCiCNCiHNCiBNCCFMhRHEhxDohxAUhxBkhhKPadrD69+wWQtwWQowSQkxQ2xwTQpRX29UQQuwTQvwhhIgUQugfk/EOFDGvQHpMfNZ2emwCRcwr5rAr5dKWytvXYLHCB2P18Ctji4pax2bEJmBskfPYgsLC0pzoqNis7dioOCx0hoaZW5kR8zBOpS8jg+TkFN4rX1Y2ja/DwsqcqIfZ+mOi4rC00tZvaWVGTFRc1nZ0VBwWVjkfWHp5eRBx4EjBiVVT0bIi8VHZ/3lCdAIVLLUbSCpYViAhKgGAzIxMniU/o0y5Mty+fJvWHVtjZGyERRULataviZmVvEP5LKzMiInKfgCIjYrFwlLbnxaW5sRoxlV0LBYy69TFEGPlFYaoPfbRX1iYlc/atqhYnrhHf2nZvG9bhf2HTwFw4OgfPE19zpMkVef9ly/T6DtuDl4T5xF69HSB69XFUOP8TcTGP8JSo3yyMK9IbHwCsfEJWJpna7cwU+2XCzPLisRqxG9sdHyOvM1cwyYjI4OUpKeUVZdFdRvXxi/sF3xD17F4yvKsh2A5KGdZgcfRj7K2H0c/opxl+dccoY1JsaLM2b2EL3cspmnHFm8+IB+xtDIn6mF2nMdExebINyystOM8OioWSw0b7xmjOXo+mO69OrNi0bcFL1pDl6HliwBmltl1KoC46PgcQ/LNLLN1v4r1V/Wueo3rsCX8NzaH/cLCKctki3VDri/GpTzH0rRE1raFaXHikp/rtY1KfEZU4jNa2OSsiwddfYibngbOgsTSypxonXvUUieGLa3MteJcnw1Aby8Pwg8cLjixGphbmhGbI851XpK8Nk+vg1/4r2wKW88iGePc2Lxijmc6Yz3PdCU72GG9+XvMls7E2OKfUe6XsCpHalR2WfQ8+jElrHKWRbafuOBybCV1Z/bn/IxfAShd3RIkida+U3EIXkDNL7rIphughGV5Uh9ma38W/ZgSluVy2NUc7ELnoyto6NOP0z6/AGBcohgfftGVS8u3y6b3FSUty/MsSke3VU7dtQa70OWISvcfM7N11xnZlYuFoPvfjDK03HDZBPQVQhQHGgDHNdLmAGckSWoATAd+1Uj7EOgEtAC+FEKYAFOBm5IkNZIk6dWkQo2BcUAdoDrQVs/1u6mPB/gEWKdHZ47zCCGKAn7AWEmSGgLOQCrwBYAkSfVRNc7+ov59APWA/mrdC4BnkiQ1Bo4CrybvWQuMliSpKTAJ+J8+xwkhhgkhTgkhTm16/Dffiugb2qvz9vBp+DHudvyYBz1HkHrsDBYLJuV6qO6xBYo+6Tp9KoQeI7l7vOTGW7her5Gu/pHjh5KRno7/lsB8VJcLev9zXRP9moP8gkiISeCbgG8YPns4V/64IusDO6B3KLuuP9/GRm4MMlbUGLJ2TXTjYuIQT/64eI0+Y77k1IVrmFcoh7GxqtgOWreMTV9/yVfew1nyw0buR8fpO6VsWsEw4vxN6NMnhNBb7Mg5bUVe/f1K+KUzV/B0/JiP3YYzePQAihYrWiA69fGuxfi41sP4sutk/jdmJV6zhmBuI0+PKXiXOM/+vnTBKlo36MjOrQF8/Gm/fNeYG4aaL75r3nLxzGV6OwxkoNtnfCJnrBtwfVF//qbfNuhqFM4fWGFspG0Qn/KcP+OTaW0rb6PV28VLzuP0xXl6eoZ85X8e78/sPP0yng6DGOQ2TOY4f7PwZxFHeeA+kKg+w3l+/AwV53nnPKYweKtMEW6vCyGk1Xguz/flg/HdVYcWMaZ8yw/444tvifSYg7Vbcyra1S1oxdm8ZUH65/oQAlpP4NyCTdQZp9Jez/sjrq/dS/qzFwUsUg9vqfvG+hD2tFHprjdWpbu+90dc/aGQdCsYBPL1/f8HIEnSeSFENVQNfrollR3wkdouVAhRQQjx6jVpgCRJL4AXQog4ILda9AlJkh4ACCHOAtWAQxrXfyqECAW6CCGuACaSJF14y/MkAtGSJJ1UnytJnW4HrFLvuyqEuAu8rz5PmCRJyUCyECIR2K3efwFoIIQoDbQBtmhUBIrp+2GSJK1F1ejJzXqd/latKz02gSIab6WLWFQkPf6Rlk1mYvZcPElb91J+/FDVsTEJFG/eICvN2KIiaSfP/53LvxOx0XFYaQwzsbA2Jy4mIYeNZSVzYqPjMDY2xtS0NIl/JcmmUZcBQ/rgOVC1mMKFs5ewrmTBqwGQltbmxGq8SQV1Lw2NIWNW1ubEadj09OyCY8d2DOypf3GM/CYhOgEz6+x4qWhVkUex2vGSEJNAReuKJMQkYGRsREnTkiQ/UcXQ2jlrs+yW71hO1O2oAtfsNaQ3fQaqCt4LZy5jaW0JqOZzsbC2IC5Wx+fRsVrDlyysLHLElRwYcqwYsnYAiwrliI3PXrwnNuExZuXf07Ixr1COlTNGA/As9Tn7j/yBaamSWWkAlS3NaVb/Q67cvEsVPT1M8hNDjfO/g6V5RWLisjXGxiVgXrECluYVOXkmu+yJjU+geeMG+k5RIMRFx2OhEb8WVmYk5CiLVDZx0fEYGxtTukypHGXRnT/vkvoslRof2HLl/DVZtD+OeUR5q+xe9eWtKvAk9vFrjtDmSZyqp3L8/ViuHrtI1XrVibsX+4aj8s6goZ70HfgRAOfPXMK6kmVWmqW1hVa+AereXRpxbmVtQWxMzhcL/lsDWbfpW1Z+pfd9cb5g6PkiQJy6TvUKcysz4mMTctq8IdZv37hL6rPn1PjQlivnCj7WDbG++AoL0+LEJGcP74xNfo5Z6eJ6bfddecg0l5wLKQZfjcKxliUmxgXf3szN9AAAIABJREFUR2bgkD54DuwJwPmzl7DSuUd14zxaJ851bXp6dsWpY3sG9JRvDtu46Hgs3hjnb5GnyxznGbHxOZ7pMl7zTJe8PZByYz8tcF1vQ2rUY0pYZ5dFxa3KkxrzV672D3YepeFXQ7KOfXT0Ci8fq35b7IGzvNfAloRDlwpWtJrU6MeUqJStvaRVeVJjn+Rqf2/nUZou/gT4ngpNalClSwsazuyHSZmSSJkSGS/S+HNdwS9a+Cz6MSWtdXTH5K777s6jNFuk1t24BlU6t6CRTz+Kaui+IYPufzOSVDjDwAuC/1qPTIBdwDI0hpWreV0/MM1XARnk3gD8NnY/AoPJvTdmbucRGno0eV00ap4nU2M7U31OI+CJulfpq0++Lx/74uI1TGwqUaSSBRQpQmk3B56GHdOyMa6Y3bW/lGMr0m6p5iB5dvgPSrZpilGZ0hiVKU3JNk15dli+eckunrmCTfUqVLKxwsSkCO7dXQgLOqhlExYUiUcf1YwFHbs6cfzQKdn06eP3nzfT1bEfXR37ERwYTo8+quEPjZrWJzkpJUdFKT42gacpz2jUVFUx7dGnC/v3hgPQ3qkNw8YMZviAcTxP1T/MKL+5fu461tWssahiQRGTIth3s+dYiHa8HAs5hnMv1Qr27Tq349xhVWNKseLFKFZC1RbfuF1jMjIyuHfjXoFr3vDzFjwcvfBw9GL/3nB6eKpW1mvYtB4pSSnE6zTExsc+4mnKUxo2rQdAD093DuyLKHCduhhyrBiydoC679tyNyqOBzHxpKWls+/gCRxaNtay+SsxmUz1nIE/bgmgh4tqZdKklKe8TEvLsjl7+QY1bKwLXLOhxvnfwcGuFbv2HUCSJM5dvELp0qUwq1ieti2bcuTEaRKTkklMSubIidO0bdn0zSfMJy6fvYqNbWWsq1hRxKQILh4dOBisPQQyMvgwnXurFjxz6mLPyUOqKQesq1hlLQRhWcmCqjVsiHqQ+/x3+c2tc39iaWuFWRVzjE2K0KqrHadDTr7VsSXLlKJIUVVVqnQ5U2o1+5CHN+4XpFx+/ckPd4c+uDv0ITgwlI88VausNm7WgOSkZOJ0GxtiE3ia8pTGzVQN2x95diVkbxgA1TQWwXBxc+DmjdsFqt3Q80WAS2evUsW2Slasd/JwJiJIO9Yjgg7TpY9qJeQOXRz0xrpVZQuq1bAh+r48sW6I9cVX1LV6j3t/PeXhk2ekZWQSdCUK+5qWOezuPEoh6XkaDa1zDg3dd0W+YeW//byZLo596eLYl5DAsDzGuaosau/UhuFjBjNM5ji/fPYqVTTy9I4eHTgYdEjL5mDQIbr0UeXpucW5ZWV1ni5TnL+4dI0iNpUoYm0JRYpQqpMDzyKOatloPtOVtG9N2u2Cr4e/DU/O3qR0dUtK2pghTIyp3L01McHaz5SlbDUaxZ0bk3Jb5de48POUqW2DcYmiCGMjKrSuTbKM8zY+PnsLU1tLSlUxw8jEGBuPVjwM0tZe2jb7RYq1c6Ms7aHd57GnxTj2tBjH9R/2ceUbf1kaMXPT/SD49bqT1boP9JjH7pbj2N1yHNd+3MflVf5KI6aCFv+pHplqfgYSJUm6IIRw0Nh/EPAC5qn3J0iSlPSaoWPJQO4rBuSCJEnHhRBVgCaohre/LVcBayFEc0mSTgohTFENLX+lO1QI8T5gA1xTn/9NWpLU82f2liRpi3ouzgaSJOXv0mAZmSQs/Bar7xcijI1I2hFM2s27lPtiEC8uXedZ+DHKDvCglENrpIwMMhOTifNZDkBmUjJ/fb+ByptWAfDXdxvIlHGl2IyMDBZMW8baTd9gZGzEDt/d3Lx2m1GTh3Hp3BXCgiLZtnEXi1fPZu+xrSQ+SWLS8OxVTYNP7qC0aSlMiprg5GbPMM8x3LxesA8ymoSHHMLB2Y7Qk/48T33OlDGzs9J2h/nS1VE1zG2W90KWrJpDseLFiDhwhPD9qoeG2YunULSYCb9sXQOoJlKfOWlhgWrOzMhkzcw1zP99PsbGxgT7BXPv+j0GThzI9fPXOR5ynKBNQXh/7c1PkT+R/CSZxV8sBqBsxbIs+H0BmZmZPIp5xLKxywpUqz7CQw5j79yW/Sd2kpr6nGlj5mSl+YdtwMNRtRrfl96LWbxqNsWLF+Ng6BEi1D53cXdg5iJvylcox9qNX3Pl0nWG9hktg27DixVD1l7E2Jjpn3sxYtZyMjIz6e7SjppVK/Ht7zuoU6saji0bc/LCVb75ZStCCJrUe58ZIwYCqkWA5q7+BSNhRKaUyZDenalhI++8ZIYa595fLubkmfM8eZJEh+4DGDl0IOnpqpVHPXt0pn3r5kQePYlbnyGUKF6cedPHA1C2jCnDB/ej76eqFeI//6T/axcNym8yMjJYMuNrvtm4DGNjI3ZtCuTW9TsM9x7ClXPXOBh8GH/fAOZ8M4PthzeS9CSZGSNmA9CwRX0Gj/IiPT2dzEyJr6avIPFxomzaMzMy+XXWj3j/OgsjYyMObj7Awxv36TmhL7fP3+TM/pPYNqjJuLVTKFW2FI2cm9NzvCfTXMZRqVZlPln4OVKmhDAS7Fmzg6gb8j08hoZE4ujSjoOnAkhNfc6k0TOz0gLDN+Pu0AeAGZPms3z1fIoXL0b4gUOE7Vc1SEydNY7qNauRmZnJw/vRTJ80TzbthpgvgirWv5q+gm99V2BkbMSuTQHcun6bz72HcvncVQ4GH2an7x7mrZqJ/5FNJD5JYtrnqt/WuGUDBo8aQHpaOplSJoumLeeJTLFuyPXFIkZGTHWux4gtx8iUJDzqV6FmRVP+F3mVOpbv4VBL1bjzapEf3Wejh4nPiEl+TlObCvpOX6CEqeM87OQunqc+Z7JGnO8J20QXx74AzFTHefHixYg4cJhw9T2qivOi/KoR5z6TFhS47oyMDJZOX8kq3+XqPD1AnacP5Yo6zv19A5i7yocdR3xJepLEdHWcN2rZgI9HeZGelo4kSSyeJmOenpHJ48WrsVizCIyMSPEPIu3mXd4b8TEvLl8nNeIopv26U9KhNaRnkJGUTMKspVmHW/68ApNqVRAlS1A5aCMJs1fw/Kg8DfpSRibnp6+nje9UhLERd33DSb72kA8n9+LJ2VvEBJ+m+pCOmLWvh5SWzsvEp5weo4qLtMSn/Pl9IPb75oMkEXvgLLH7z8qi+5X209PXY+87BWFsxK1NESRdf0g97494fO42UcGnqTWkIxbt6pGZlsHLxKccH/OdbPpep/vUjPU4bNTWXV+t+2Hwad7/pCOW7eqRmZ7ByydPOTa28HX/myms+SwLAvFPmJtFDoQQKZIkldbZ5wBMkiSpi3rxm3WALfAMGKYeij4bSJEkaZn6mItAF0mS7gghNqJqjNwLBLw6l9puNXBKkqT1QohwddopddpUoJEkSX119Wlq0nOe5qiGkZdA1YjpDKQD3wFN1d8nSJIUJoQYDDSTJGmU+jx31NsJmmlCCFtgDWAFmACbJEma+zpf/t2h5f8UusXn3pX9n8zzjLTClpBn3i8h31xm+cnN5/FvNvqHkvFvKqEMhMtHVxe2hDxTv82YNxv9A7l0ZXNhS8gzbRoMLmwJeeJDE/kW2stvDqb8WdgS8kwRYZh9DsqalCxsCXnmRaZh1rtOLWxX2BLyTN0pBwpbQp4pb1L6zUb/QLZa6J8+wBA4G/PPWEDo7/JCxrm185tCWpg6X+gXtcGA1ecvD1o6FUg7TuXjobL72DBrR3lAtxFTvS8cCFd/fwx46LGZrbNdT+N7fx3zcI20URrfHXTs7ICVmjte6dPUpOc8J4FWuhpRDVXX1b0eWK+xXU1fmiRJtwFXPedUUFBQUFBQUFBQUFBQUFBQUDBwJENukdbhvzhHZqEhhHhPCHEdSJUkyXBfPSooKCgoKCgoKCgoKCgoKCgoGASSVDCfwuA/0yPzn4AkSU/IXlFcQUFBQUFBQUFBQUFBQUFBQUFB4S1RGjIVFBQUFBQUFBQUFBQUFBQUFBT+pfybhpb/Zxb7Ucg/mljZGWTQJLyQb5XW/KRisbKFLSHP/PVSvhXm8xND9vnjlymFLeE/R4Wi8q1end8kp6cWtoQ8UbqI4S5ScOT8+sKWkCea1RtQ2BLyTGrGy8KWkGckDLLKhbEw3NmrnqU/L2wJecKQ6y6GfI8aGegCLoYa5wBFjAyzL1YRYVzYEvJMcvqzwpaQZx48vmiYN2kBcLeJc4FUKqqe3q8s9qOgoKCgoKCgoKCgoKCgoKCgoKCQP/ybemQqDZkKCgoKCgoKCgoKCgoKCgoKCgr/Uv5Ng7ENd9yHgoKCgoKCgoKCgoKCgoKCgoKCwn8GpUemgoKCgoKCgoKCgoKCgoKCgoLCv5R/09BypUemgoKCgoKCgoKCgoKCgoKCgoKCwj8epSFTQRbaOLZke+RG/I9sYvConCufmhQ1YfF3c/A/solfAtZiVdkSgLqNauMbsg7fkHVs2r8eR7f2cksHYM6iqRw8FUBQ5DbqNait16Z+wzoEH9rOwVMBzFk0NWv/xOmjCIrcxt6ILfy+7XssLM3kkm3Qfv9y0RTCTu5m78Et1G3woV6beg1rszdyK2End/PloilZ+ydM+4K9B7cQEO7Hr1u/w1xGn7d2aMHWyN/ZfngjH4/yypFuUtSEhd/NZvvhjazb812Wz19hUcmciBv7GPB5X7kkZzFroTehJ/wJiPB7rc8DD/oResKfWQu9s/ZPnT2O4KPbCIjwY80vyzAtU1ou2YDham/l0IItkb+x7fAGBo3qnyPdpKgJC777km2HN/DznjV64yX8xl68PveUSzIAdo6tCDyyhX3Ht/Hp6EE50k2KmrBi7QL2Hd/Gpr0/Y13FKivtszEfs+/4NgKPbKGtYys5ZQN5v0frNKrNhpCf1J+fcXBtJ6tun4UraN+5L90HfK43XZIkFq5cg1ufIfQYNILL1/7MSvMPDMHdcyjunkPxDwyRS3IWbRxb4n/Il91HNzNk1MAc6SZFTVjy/Vx2H93M74E/YF1F5fNW7ZvjG/QzW8N+wzfoZ1q0bSq3dHwWTiLkxA52hftSp8EHem3qNviQ3RGbCDmxA5+Fk7L2u3brQECkH1djT1Cvof66Q0Eyc6E3+0/sZHf4Jurkki/WbfAheyL82H9iJzM18kXXbs4ERm7mWuzJQtE+Y8FEgo5vxz98I3Xq5+73XeG+BB3fzowFE7P2l32vDD9tWc2+Y9v4actqypQ1lUu2Ul+Uub5oyGWRnWMr9hzezN5jW3PVvmztfPYe24rv3p+ytJctV4Z12//HyVthzNDIb+TkXero02aPZ/+xnew9uIXvfl2JaRn57k8w3HzRkGN97qJpHDoVSEjk9tfmi/sPbefQqUDmLpqWI334qME8eHyRcuXfK2i5/2okSRTIpzBQGjLfgBBCEkL8prFdRAgRL4TYk8fzvSeEGKmx7ZDbuYQQ4UKIZm84X4YQ4qwQ4qIQYrcQ4rV3t+715cDIyIgpCycw2msSH9kPwLW7M7bvV9Oy6d6vC0mJyXi06cuGtX6M9RkBwM1rtxjg+in9XD5hVP+JzFjijbGxsZzycXRuR7UaVWnfrDNTx89hwXIfvXYLlvkwdfwc2jfrTLUaVXFwtgPg+1Xr6NTuI9zse3MgKIKx3vofQvMbQ/a7g7Md1arb4Ni8K9MmzGX+Mv0+n7/Mh+nj5+LYvCvVqttg36EtAGtXr8etfW86O3gSGnyQMZOGy6LbyMiIyQvHM9bLmz4Og+jo0QHbWlW1bDz6dSbpSTI92/Zn4w+bGe2jHQ8TZo/mSOhxWfRq4uDclmrVbXBq4cGMCfOZuzRnJQJg7tJpzJiwAKcWHmqftwHgUPgx3Oz60Nnek9s37zFi3BBF+xtQxcs4xnpNxtPhYzrpiZdu/TqT/CSZj9p64fvDFkb5aMfy+NmjOBp6Qha9rzAyMmLmV5MZ1m8sXe086dyzEzXet9Wy6eXVjcTEZFxbfsSv3/syaeYoAGq8b4t7j450bdeXz/qOZdZXkzEykq8q8i736M1rtxjkOgwvl6GM8fJm2pJJsuaL3d1d+G7F/FzTI4+e5N6DKAL9fmL25DHMW7YagMSkZNas24jvD1/j+8PXrFm3kcSkZLlkY2RkxPRFkxjZfyI92vfHtYcz1XXKoh79u5L0JJmurfvw+/d+jPNRVVOePE5kzKDJ9HIcyMyx81mwepZsugHsndtSrXoVXFr0YObEBcxZoj9vmbN0GjMnLsClRQ+qVa9Ce3XecuPKTUYNnszJo2fklA2otFetXgXnFt2ZOXE+c1+j3WfifJxbdKeqlvY/+WKwNyePnpZTNgDtO7ShanUbOrXsyayJC/lyyVS9dl8umcqsSQvp1LInVavb0M5Jpf2zMR9z7OBJXFt9xLGDJ/lszMey6Fbqi/LWFw29LJqx2JvP+4+jW7u+uPfomEP7R/27kfQkGbdWvfj1+01MmPkFAC9fvGTV4u9ZOvsb2fRq8q519EPhx+jU9iPc2vfm9s27jBw/VDbthpovGnKsOzm3w7aGDXbN3JkyfjaLls/Ua7do2Uwmj5+DXTN3bGvY4KjOFwGsKlnSzqE1D+5HySX7X4uUWTCfwkBpyHwzT4F6QogS6m0X4OE7nO89ID8bElMlSWokSVI94DHwhczXfyP1GtfmwZ0HPLwXRXpaOkH++3HoZKdl4+Bqx57NewE4sCec5u1UvS6ep74gIyMDgKLFiiIVwlJbHd0d2bZpFwBnTp2nTBlTzC0qatmYW1SktGlpTp88B8C2Tbvo5O4EQEry0yy7kiVLyPYbDNnvLm6ObPfbDcDZUxcoU9YUMx2fm1lUpLRpKc6cOg/Adr/ddNTj8xIliyMhj/66jWtz/85DHt6LJj0tnRD/A9jr+Lx9JzsCtuwDIHRPBM3tmmSl2bva8fBeFLeu35FFrybObg7s2Kx6p3L2j7fz+Y7Ne3BxdwRUFdNXMXP21AUsrc0V7W+gbuPaPLjzkCh1vAT7h9JeJ17sO7UlYEsQ8Lp4uS2L3lc0aFKXe7cf8OBuFGlp6QTuCMbJVbsXjpOrPf5+AQAE7Q6lVbvm6v3tCdwRTNrLNB7ei+Le7Qc0aFJXNu3vco++0MgXixVCvtisUX3KvqbnStihY3Rz7YAQgob1apOcnEJ8wmMOH/+D1s0bU7aMKWXLmNK6eWMOH/9DNt31Gtfh/u3ssmjfzv04dNLuzerYqR271GVRyJ4wWtip3uFevXid+NgEAP68eouixYpiUtRENu0dXO3Z4RcIwLk/LmJa1hQziwpaNmYWFShtWoqzpy4AsMMvEGc3BwBu3rjD7Zt3ZdOribOrPTvV9+DZPy5iWrZ0Lvli6SztO/0CcPkHaO/gZo//ZpX2c39cVOXp5jp+N9f2u//mAJzd7VXHu9qz009VJuz025P1fxQ0Sn1R3nzRkMui+k1U+WKW9p0hOObQ3j7rPgjeHUorO5X21GfPOX3iHC9fvJRNrybvWkePDD+aFTNnTp3H0krG+qKB5ouGHOsd3R3Zqs4XT782XyyVlS9u1cgXAWYvmMyCL1cUSjuAwj8XpSHz7dgLdFZ/7wf4vkoQQpQXQuwUQpwXQhwTQjRQ758thPhZ3avylhBijPqQxUANdS/Kpep9pYUQW4UQV4UQG4QQWv1zhRBDhRArNbY/E0Ks0KPzKFBJbVNaCHFACHFaCHFBCOGR2/WFEN5CiJPq3zDnXRylDzNLM2IexmVtx0XH5xjqa2ZpRkyUyiYjI4OUpKe8V74soHoI2hL+G5vDfmHhlGVZhZ9cWFqZE/0wJms7Jio2R6FraWVOTFRsrjbeM0Zz7EII3Xt3ZvmibwteNIbtdwsrc6IfZvszOhefR+v43ELDZtKMURw+H4RHr86sXPS/ghcNmFlWJDYq2+ex0fGYWWn73FzD5pXPy5YvS/ESxRk0sj8/LF8vi1ZdLKzMiXqo6c84LHW0W1plxwtAdFScls9f0cvLg4gDRwpOrA6Gql03XuKi4zGzqpirjb54+XH5L7Jo1cTc0owYDX/HRsdhoeNvC0uzrHs4IyOD5OQU3itfFgsrM628MjYqTtapH97lHgVVQ6hf2C/4hq5j8ZTlspdHryM2/hGW5tnxY2Fekdj4BGLjE7A0z/6NFmaq/XJhrvOfx0XH54gXTZuMjAxSkrPLolc4d3Hk6sXrpL1MK3jRalTxml3+x0bFYmGpnW9YWGqX/7HRsTl+X2FgkaOMjMsxVNnCUvu/iYmO1Zsvyo2FpVlO7Tq6LKzMiYmO07ZR/74KZuWJj3sEQHzcI8pXLCeDaqW+KHd90ZDLIgtL7fszVs/9aW6V/b9oai9s8qOO/oo+/bsTceBwwYnVwVDzRUOOdUsrC6I08kVVvFjksNH8XzRtXFwdiImO48qla/II/peTKYkC+RQGSkPm27EJ6CuEKA40ADTHfc4BzkiS1ACYDvyqkfYh0AloAXwphDABpgI31b0oX0260RgYB9QBqgNt9Vy/m/p4gE+AdZoGQghjoAOwS73rOdBDkqQmgCOwXN1AqnV9IURHoJZaYyOgqRAixwQ3QohhQohTQohTCc9idJNfi067LECONyqvs7l45jK9HQYy0O0zPhk9gKLFiv6t678zerW9jU220dIFq2hV34WdWwIY/Fm//FaoF0P2ux5Zb6Vd849ZtmA1bRt0wn9rAIM+lWe+ybz6HEliuPcQfH/YQuqz1IKS91re4M5cjXR/38jxQ8lIT8d/S2A+qns9hqpdfyy8jY3EMO9PCi1e9Mf5m22QcjlWph7T8G73KMClM1fwdPyYj92GM7gwyqPXoK+nghAi571ALr+xgHi7/Pz1NjU+sGWcz0jmeS/Jb3mv5V3L0cLEkLW/TX79VnUzuVHqi7LWFw25LEKvLB2f6zH6J9yf+VFHB/hiwqekZ2Swc0tAfsp7LYaaLxpyrL+Lz4uXKM6YicNYtnB1gelTMFyUhsy3QJKk80A1VL0xdZ9w7YDf1HahQAUhxKvXZQGSJL2QJCkBiAMs0M8JSZIeSJKUCZxVX0vz+k+BUKCLEOJDwESSpAvq5BJCiLPAI6A88GoWfwEsFEKcB/aj6qmp7/od1Z8zwGlUja+19PhgrSRJzSRJalaxpKVu8muJi47DslL2myxzK7OsoWJaNurhnMbGxpQuU4rEv5K0bG7fuEvqs+fU+FB7TpCCYNDQvuyN2MLeiC3ExcRhVSn7N1taWxAbE6dlHxMVi6W1hY5NfI7z7twaiFtX54ITroGh+X3gUE8Cwv0ICPcjLiYeq0rZ/rTS48/oqFis3sLnu7buxVU2n8djoTEs2cLKjIQYbZ/Hatho+rxu49qM9vkc/+N+9Pu0F4NHD6D3Jz0LVO+AIX3YHebL7jBf4mLisa6k6U/zHP6MiYrTGnZtZW1OnIZNT88uOHZsx/jP9c+XpGjXRjdezK3MiI/RvUf1x0u9xnUY5TOcncc30TcrXnrIojs2Og5LDX9bWGn7EiAmOi7rHjY2NsbUtDRP/kpU/w8ax1qb5/jNBcm73KOa3PnzLqnPUqnxQcGXR2+LpXlFYuKyf0tsXALmFSuo92f/P7Hxqv1yERsVr/Wfm1uZEafrcw0bY2NjSptm+9zcyoyVPy/CZ/RcHtx9l5l93g6vIb3xD9uAf9gG4mLisbTOLv8trC2Ii9WNde3y38LKIsfvkwuvIb3ZFbaRXWEbiY2J1ykjzYnTqQPERGvfj5ZWFjnuZbnoP6Q3O0I3sCN0A3ExCTm16+iK1ekFpvp9KptH8Y+zhqKbmVfgccJfBaZbqS9mI2c9HQy7LIqNjtOKcQtr85z5osb/8kq7rs/lIr/r6D37dsWpY3vGDdc/R2V+Ysj54isMLdY/HtqXoIitBEVsJTYmDmuNfNFKT74YHRWj9b+8sqlWrQpVbCoRHLmNo2eDsLK2YF/4lhxTjSi8PcpiP/9NdgHL0BhWrkbfP/fqNcMLjX0ZQJFczv02dj8Cg8nZGzNVkqRGQFWgKNlzZHoBZkBTdXosUFzPeQWwSN1Ds5EkSTUlSfopF5154tLZq1SxrYJ1FSuKmBShk4czEUHawwgigg7TpY8bAB26OHDykGoSZesqVlmThltVtqBaDRui7/+9HqF54defNuFm3xs3+94EBYTyUd9uADRu1oDkpJQchV5cbAJPU57SuFkDAD7q243gwDAAqlW3ybJzcXPk5g155rMzNL//9pMfnR086ezgSXBgGD09uwLQqFl9kpNSclSq42MTSEl5SqNm9QHo6dmVkL05fe7s5sAtmXx++exVbGwrZ/ncxaMDB4O1fR4ZfJjOvV0BcOpin+XzYT1G49HSE4+Wnvj+uJX1q35ny7rtBar3958309WxH10d+xEcGE6PPl0AaNQ0d58/TXlGo6Yqn/fo04X9e8MBaO/UhmFjBjN8wDiepz4vUN2Grv0Vl89epYptZayrWFLEpAgdPZyI1ImXg8GH6dy7E6CKl1OHVIuGDOsxmu4t+9K9ZV82ZcXLDll0XzhzmarVq1DJxhoTkyK49+hIWFCklk1Y0EE8PFUzsnTq6sSxQ6fU+yNx79ERk6ImVLKxpmr1Kpw/fUkW3fBu96hmvmhZyYKqNWyIelDw5dHb4mDXil37DiBJEucuXqF06VKYVSxP25ZNOXLiNIlJySQmJXPkxGnatpRv9e9LZ69gU70ylWxUPnft7kxE8CEtm/DgSLqpyyKXLo6cOKyaw9O0TGlW/76M/1v4HWdPXshx7oJgw89b8HD0wsPRi/17w+nh6Q5Aw6b1SElKIT72kZZ9fOwjnqY8pWHTegD08HTnwL4IWbTqsuHnLXRz7E83x/7s3xtOd/U92Khpvdfki09ppNbe3bMz+wtJ+8aft9DDyYseTl4c2BuORx+V9oavtMfp+D3uEU9TnmX53aNPZw7sVWkPDTpId09VmdDds0uB/h9KfbFw6ulg2GXRxTNXsKlehUo2Virt3V0ICzqooz3ls1+0AAAgAElEQVQy6z7o2NWJ42rthUF+1tHbO7Xh8zGf8JnXWFnqXIacL77C0GL9l5820cm+F53se7EvIJRe6nyxyWvyxZSUZzRR54u91Pni1Ss3aPSBPa0bdaJ1o05ER8Xi6tA7R3mg8N8kt4Y1hZz8DCRKknRBCOGgsf8gqkbDeer9CZIkJb1m2FYykPts/bkgSdJxIUQVoAmq4e266YnqeTj9hRBrgLJAnCRJaUIIR1QNnfquH6TWvkGSpBQhRCUgTZIk7Vcl70BGRgZfTV/Bt74rMDI2YtemAG5dv83n3kO5fO4qB4MPs9N3D/NWzcT/yCYSnyQx7fPZADRu2YDBowaQnpZOppTJomnLefI4Mb+kvRWhIZE4urQn8o9AUlOfM2lUdo+tvRFbcLPvDcCMSfNY/u18ihcvTtj+Q4TtVxUwU78cR42a1cjMlHh4P4ppE+fJotuQ/R4WEomjix3hp/aQmvqcyaOzV6oNCFdVpgBmTlrA0tXzKF68GBEHDhO+X/VwPHnWWKrXrIaUmcnD+9HMmJT7Sr/5SUZGBktmfM03G5dhbGzErk2B3Lp+h+HeQ7hy7hoHgw/j7xvAnG9msP3wRpKeJDNjxGxZtL2J8JBDODjbEXrSn+epz5kyZnZW2u4wX7o6qoa4zfJeyJJVcyhWvBgRB44Qvl/1sDN78RSKFjPhl61rANWiOzMnLVS0v4aMjAyWquPFyNiI3ep4GeY9hCvnrhIZfIRdvoHM+WYG2w5vUMdLvk9jnCfd86cu5Ue/bzAyNmL7xt38ee0Wo6cM4+LZK4QFRbJ1wy6++nYO+45vI/GvJCYOnwHAn9dusc9/P3sO+ZGRnsG8KUvIzJRvucN3uUcbtqjP4FFepKenk5kp8dX0FSTKmC96f7mYk2fO8+RJEh26D2Dk0IGkp6cD4NmjM+1bNyfy6Enc+gyhRPHizJs+HoCyZUwZPrgffT8dC8Dnn/R/7aJB+U1GRgaLpq9gje9KjIyN2em7h5vXbjNy8qdcOnuViOBD7Ni4hwWrZ7H76GaSniQxebgqz+87pBc2tpUZNn4ww8YPBmBE3/EF2sNOk/CQw9g7t2X/iZ2kpj5n2pjs+88/bAMejl4AfOm9mMWrZlO8eDEOhh4hQp23uLg7MHORN+UrlGPtxq+5cuk6Q/uMlkn7Ieyd23LghD+pqc+ZqpEv7grbSDfH/mrti/hq1WyKFy9OROhhDe2OzFJr/2Hj/3Hl0nWG9Bkli/aI/Ydp79yW4BM7eP7sOdPHzs1K2xG6gR5OKr/PmbyYhd98SfESxYg8cISD6vmNf/jmF1b+sIiPvLoR/SCWcZ/qX/U8v1Hqi/LWFw29LFowbRlrN6m07/Ddzc1rtxk1eRiXzqm0b9u4i8WrZ7P32FYSnyQxaXh2PAWf3EFp01KYFDXByc2eYZ5juCnTwn/vWkef89U0ihYrym/bvgPgzKkL+MhUTzfUfNGQYz005CBOLu049MdenqemMmFU9qrlQRFb6WTfC4Dpk+axQp0vhu+PJHR/ZG6nVHgHpMzC6T1ZEIjCnvPhn44QIkWSpNI6+xyASZIkdRFClEfVQ9IWeAYMkyTpvBBiNpAiSdIy9TEXgS6SJN0RQmxE1Ri5Fwh4dS613WrglCRJ64UQ4eq0U+q0qUAjSZL6amjR0ieE2A1sVp97N2CCarh6W8BN9/rqeTLHAp+qT5ECDJAk6WZuPmliZWeQQZPwQt4G0PyiYrHCn9g7r/z1MrmwJeQJQ/b545cphS3hP0eFovI1CuU3yemFMyfru1K6iL4BBobBkfPrC1tCnmhWb0BhS8gzqRmFs7pvfiDrvH35iLEw3EFfz9Ll65mfnxhy3cWQ71EjGecczk8MNc4BihgZZl+sIsK4sCXkmeT0Z4UtIc88eHzRMG/SAuBKLfcCqVTUvhEou48NMxeQEd1GTPW+cCBc/f0x4KHHZrbOdj2N7/11zMM10kZpfHfQsbMDVmru0NUnSVJXjc3Wurr0XV+SpP8D/k+frYKCgoKCgoKCgoKCgoKCgoKCwj8BpSHTABBCvAecAM5JknSgsPUoKCgoKCgoKCgoKCgoKCgoKBgG/6ah5UpDpgEgSdIT4P3C1qGgoKCgoKCgoKCgoKCgoKCgoFBYKA2ZCgoKCgoKCgoKCgoKCgoKCgoK/1IyJaVHpsJ/mE+LVCtsCXlinbhX2BLyRNyLJ4UtIc+0KG1b2BLyxJXnsYUtIc+UKVKisCXkmQzkW0UxP6lpUr6wJeSZA0+vFLaEPNGsROXClpBnDHXRnFMXfy9sCXmmTu3ehS0hz2Qa6KKc5ga8CFpJ42KFLSFPdClWtbAl5JnVj04UtoQ8U7G4YS6ydD85obAl5JliRUwKW0KeKFc8x9IbBkNsyl+FLUEhH5D+RQ2ZhrukoIKCgoKCgoKCgoKCgoKCgoKCgsJ/BqVHpoKCgoKCgoKCgoKCgoKCgoKCwr8UAx3koRelR6aCgoKCgoKCgoKCgoKCgoKCgoLCPx6lR6aCgoKCgoKCgoKCgoKCgoKCgsK/FGWxHwUFBQUFBQUFBQUFBQUFBQUFBYV/PMpiPwoKf5MqDg3oF74Ur8jlNB7ZNUd63QFOeIYsos++BfTYNpNytayz0pp80RWvyOX0C19KFfv6csoGoLVDC7ZG/s72wxv5eJRXjnSToiYs/G422w9vZN2e77CqbKmVblHJnIgb+xjweV+5JGsxe9EUIk7uYd/BrdRrUFuvTb2GtQmK3EbEyT3MXjQla//EaV+w7+BWAsM389vW7zC3NJNFcyP7xvxf6P9YFfEd3Ud8lCO9dos6fBWwgk03t9PKvU3W/oqVzPhqz3KWBq5kRcgqXLxcZdGrSVvHVuw+7EfgsS0MHT0wR7pJUROWrZ1P4LEtbNz7E9ZVrAAoW64MP2//lhO3Qpm+cKLcsmnj2JIdh3zxP+rHJ6NyrqpsUtSExd/Pxf+oH78GrsWqiirOW7Zvzoagn9gc9isbgn6iedsmckunrWMrdh3axJ6jWxgySr/Pl3w/jz1Ht7Ah8Ees1dpbtW/OpqB1bAv7nU1B62jRtqmsuhvYN2ZZ6GpWRPyPriN65kj/sEUdFgQs47ebW2nh3jpHeonSJVh9/EcGz/1MDrk5WPDVDI6dCSLssD/1G9bRa9OgUV3Cj+zi2JkgFnw1Qytt6LABHD61l4hju5k5d5IckgGob9+YJaGrWBbxLV1G9MiR/kGLOswLWMb6m1toruP3X25tYX7gcuYHLmf8j9Pkkgyo7lH/Q77sPrr5NXE+l91HN/N74A9ace4b9DNbw37DN+hn2ePcZ+EK2nfuS/cBn+tNlySJhSvX4NZnCD0GjeDytT+z0vwDQ3D3HIq751D8A0PkkqzFzIXe7D+xk93hm6jT4EO9NnUbfMieCD/2n9jJzIXeWftduzkTGLmZa7EnqddQf/lbkMxa6E3oCX8CIvyom4v2eg1rE3jQj9AT/szS0O7WzZm9h7ZwI+4U9RvJq72lQ3N8D/6C36HfGPBFvxzpJkVNmLtmJn6HfmPt7m+xrGwBgGVlC0L/3Mv64LWsD16L9+Jxsupu49iS7ZEb8T+yicG5laPfzcH/yCZ+CVibVV+s26g2viHr8A1Zx6b963F0ay+rboCa9g0Yc2ApY8OX025Eznp6m6FujApZwsi9ixi8YRplK1XUSi9WugSTjq2i85yP5ZKcxaIlMzl1dj+RR3fTIJeyqGGjuhw6todTZ/ezaMnMrP0/rf+aiMO7iDi8i7MXw4g4vEsu2QD4LJxEyIkd7Ar3pU6DD/Ta1G3wIbsjNhFyYgc+C7PLStduHQiI9ONq7AnZ85eVK+Zy9fIhTv8RQuNG9fTazJs7hds3T/Lk8XWt/ePGDuP8uTBO/xFC8D4/bGwqySE5i6XLvuT8hXCOH99Lo0Z19do0alyPEyf2cf5COEuXfZm1v3792oSGbefEiX1s2fojpqbyrkI+d9E0Dp0KJCRye67PdPUb1mH/oe0cOhXI3EU56ynDRw3mweOLlCv/XkHLzWLlirlceUO8zJ07hVs3T/KXTrzY2bXkxPF9pD67S8+eneWQq2Ag5EtDphBCEkIs19ieJISYnR/nVp9vkBDiohDikhDishBCvieet0AI0UwI8U0ejlsphBinsR0khPhRY3u5EGLC3zhfNSHExb+rQ+P49UKIXnk9PtfzGgnaz/+YgEFL8HWaTC2PVloNlQDXdx7Fz2Uam11ncOa7ANrOUlUAy9Wypma3Vvh2mMKegUtov2Awwki+NwlGRkZMXjiesV7e9HEYREePDtjWqqpl49GvM0lPkunZtj8bf9jMaB/th7UJs0dzJPS4bJo1cXS2w7Z6Veybd2HahLnMX+aj127BMh+mjZ+DffMu2FavikMHOwC+X70e1/a9cHfow4Hgg4ydNLzANRsZGTF03nAWfDyH8c6jaNutHZVrVdGySYhK4NuJ/8ch/4Na+5/E/cWMnlPwdh/PdA9vuo/oSTnz8gWuWVO7z+JJjOg/nm7t+uHeoyPV36+mZdOzfzeSniTh3qo3v33vy4SZXwDw8sVLVi1ey7LZq2TTq6l76qKJjOo/kY/ae+HawzmH7u79u5D8JBmP1p5s+N6PsT4jAXjy+AnjBk2hj+MgZo2dz/zVs2TXPn3RREb0n0D39v1w6+Gix+ddSXqSTJfWvfnt+02M8/lCrT2R0YO8+chxAD5j57Fg9Zd6rlAwCCMjPpk3jCUfz8PbeQxtutlRqVZlLZuEqHi+m7iKIzpx/oreE/tz5fglOeTmoINLe2xrVKVV405MGjuLJSv0+27Jii+ZNHYWrRp3wrZGVZyc2wHQtl1LXDs74dimG/aturLmm59l0S2MjPh43mcs/Xg+U5zH0rpbO6x1/P4oKp61E1dx1D8yx/Evn7/Ex30iPu4TWfnpIlk0w6s4n8TI/hPp0b6/3nu0hzrOu7buw+/f+zEu6x5NZMygyfRyHMjMsfNZIPM92t3dhe9WzM81PfLoSe49iCLQ7ydmTx7DvGWrAUhMSmbNuo34/vA1vj98zZp1G0lMSpZLNgD2zm2pWr0Kzi26M3PifOYu0d94PWfpNHwmzse5RXeqVq9C+w6qF2w3rvzJF4O9OXn0tJyyAXBwbku16jY4tfBgxoT5zF2qX/vcpdOYMWEBTi08qFbdBnu19utXbjJy8CROyKzdyMiIiQvGMnHAVLwcP8G5uxPVdOpdXfq5kZyYjKfdQPx+2MrIGcOy0h7ejWJwx2EM7jiMpVO/llX3lIUTGO01iY/sB+Da3Rlb3XK0XxeSEpPxaNOXDWv9GOszAoCb124xwPVT+rl8wqj+E5mxxBtjY2PZtAsjQZe5g/lt8BJWu0ymfrfWmNXUblyKvnyX77v68D+3aVzae4KO07QbmJ0m9uLO8auyaX6Fc0d7atSoSrNGzowfM5PlK+fqtVu2cg7jx/jQrJEzNWpUxdlF1Vg8dPA47Nt2w75tN3bvCmLPrmDZtNs7t6Va9Sq4tOjBzIkLmPOa/GXmxAW4tOhBNa385SajBk/m5NEzsmkGcHN1olZNWz6sY8eIEVP4drX+snDPnhBat83Z8HT27EVatnKjSVMXtm0PYPEi/c8mBUGnTg7UrGlLg/oOjBo1na//b4Feu//7v/mMGjWdBvVV9h07OgDw7f8WM2vmV7Ro4cruXUGMGz9M7/EFgZNzO2xr2GDXzJ0p42ezaPlMvXaLls1k8vg52DVzx7aGDY7OdllpVpUsaefQmgf3o+SSjaurEzVr2lJbHS+rc4mXgD0htNETL/fvP2Top+PZtGlnQUv9TyBJBfMpDPKrR+YLoKcQouIbLf8mQgg3YBzQUZKkukATIDG/r/MuSJJ0SpKkMXk49AjQBkAIYQRUBDRfDbUBDr/NiYQQ8tV4/ibmjWqQeCeWpHvxZKZl8OeuY9h21O4RkpaSmvW9SMliSOo7wrZjU/7cdYzMl+kk348n8U4s5o1qyKa9buPa3L/zkIf3oklPSyfE/wD2ney0bNp3siNgyz4AQvdE0Nwuu0eavasdD+9Fcev6Hdk0a+Li5sg2v90AnDl1njJlTTG30L5NzS0qUtq0NKdPnQdgm99uOro7ApCS/DTLrmTJEsiRT9VsVIuYOzHE3Y8lPS2dw7sjaebSQssm/kEc967eRcrM1NqfnpZO+st0AIoUNcHISN5O5/Wb1OHe7Qc8uBtFelo6e3eG4OSq3bPCybUd/psDAQjeHUZLu2YApD57zpn/Z++8w6K42j58HxDFCGJUYMGuKa+JsUSxRKUoCmKvWKIxmmiKNfZeYks0mi+aor6axEQRO4ooCAiCFXuJLZZE6cYoYDAqnO+PWZZdWNQYGLJ5574uLmXmmZnfHp7znDPPnnLkFH/++UBVzQB1GtTmxrWbxP+q6A7dFoGnT0sTG0+fluzQ6w4PjqJxC6UOXzx7mdTkWwBcuXCNkqVKYlPSRkXtSpnnaN+9LRwvH9My9/RpyXa99j3BuWV+4ewlg/afL1yllIraX6j/IsnXE0m5kUzWw0cc3BFLwzx+futmKjcu/EJ2dv6aV6NOTRwqOnBm30lV9ObFt31rNgYEAXDs6CnKOpTFydl0xLaTsyN29nYcjVM0bgwIol0HbwDeGtybpUtW8uDBQwBu3bqtiu5a9V8g+XoiqfpyP/SYcs8bX4qTOg1eMamju7eF56ujXj4t2b5hF6D4eeMC/FztOtqo/ms4lLUv8Pze2EN08m2NEIJ6dWqTnp5B6q3b7D98jGZuDXAoa49DWXuauTVg/+FjqukG8Pb1YFvgTgBOHjuLvYMdjnnaUEd9G3ry6BkAtgXupE07TwCuXL7OtSu/qKo5B+92nmzdEAzAyWNnKOtgX4D2MpzQt/9bNwTTRt/+X7l8jWs/q6+9doP/cPN6PAn6fldEUCQtfd4wsWnZtjkhG5WEU9TOaBq2UH8mQF7qNKjNzetG7WhQOJ55+ouevi0I1tfRiOAo3Foq7ej9zD/JysoCoGSpkoY+sFpUrl+L278k8/uNVLIeZnFmxyH+k6effu3gTzy8r/RPbpz4GQdd7pfELnWqY1fRgZ9jzqiqG8CvvTfrA5QEx9G4k5QtZ49znrbI2dkR+7J2xB1R2qL1Advw69Am3726dPVj86YdRS9aT2tfD7YGKn2TU8fOYu9gj6NzBRMbR+cK2NmXMcSXrYEheBdzfOnY0Ycf1m4C4PCR4ziUc0Cnc8pnd/jIcZKSUvIdj4o+QGbmfb3NMSpXcilawUa079CWdWu3ABAXdwIHB3t0eWab6XSO2Nvbc+SI8iXOurVb6NCxLQAvvliT2FhlcEpERCydO7dTTXtbPy82rVdGDB8/epqyZQt6pyvD8bhTAGxavx0fv1aG8zPnjmfujMWqxphOHX348W/4yy+/3OTMmfNk/4P6ZBr/DArrLf8RsAIYnfdE3lF+QogM/b+eQohoIcQGIcQlIcQCIUQ/IcQRIcQZIUROtmoSMFZKmQAgpbwvpVypv0d9IcQhIcRpIcRWIcTz+uNR+tGO+4QQ54UQbkKILUKIy0KIOXqb6kKIC0KI7/XXbxJCPKc/N10IEacfBbpCCCGM7vuJXuMlIURLo88SrP9/GSHEav31J4QQnfXHX9Vfd1L/vBdRkpQ5vbNXgbNAuhDieSFEKaA2cEIoLNTrOSOE8Dd67l4hxDrApPcghKipf76bEMJaf32c/tlD9TZCCLFMP8p1J5A/qhQCZXTPk5GQ+5KakXibMrrn89nVecubfrGf8cbk3sROX2P22nsFXFtUOOoqkpyQG1STE1NxdMnzsm5kk5WVRUbaPRzKO2Bb2pYBH/Rl5WffqaY3LzoXJxLikwy/JyUk4+xi+md2dnEiKSHZ8HtiQjI6I5txU4Zz8HQYXXq0Z/H8L4tcc3ldBX5LvGX4/Xbib1TQVXjMFaZUcKnIot3/xzeHVrHtmy38nqJOggTASedIkrG/JKTkm47v5OJIUrxS3llZWWSkZ1CuvINqGs3h5OKYx89T8vu5S+5nU3Tfy6fbu4MnF89e4qE+OaUGzma0O+XRrtg8vszbdPDigoran9eVz+fn5Z/Sz4UQ9Jv6NmvnfV9U8p6Ii4sz8fGJht8TE5JwcXU2tXF1JjEhN/4kJCTh4qLY1KpVnSbNGrErIpCtO3+g/uvmpxoVNs/rKnA78TfD77cTf+N53dOP2rYpVZJZOz5lxtYFNGzb+MkXFBJK/cuN0ymJqTibraPGfm6ujqrr509Dcupv6JxyX8acnSqSnHqL5NRb6JxyP6Ozo3JcTZxdnEg0KvekhBSc88R0Z53p3yYpMX87Wxw4uziREG+qXZfHZ3Qupm1WYkJKsWt31FUkxUhTSuItHPOUubFNVlY299Lu4fB8WQBcqur4NnQ5yzYtoV5j9ZYjctQ5khRvrDs1X/vvqMvTjqbl1tE6DV5hY9QPbNj7PfMmLDIkNtXA3rk8dxNy42Ja4m3KOhfc127Yy5PLUUqiRAiB79R+hM5bV+Q6zeHiatoWJcSbb4uM+8IJZtqrZs3dSEm5xVUVE4POLo4kGbWRyQnJOOdJ8DjrTPvoyYnJ+WK/2lRy1ZmM6Iu/mUglV91jriiYtwf2YXfo3sKS9kRcXZ25eTNXu+IvptpdXHUkGPlUfHwirnp/+emnS7TXJ8G7dfOjcmX1krA6F1M/Vt7XnPPZJOZ7p1Ns2vh6kpSYwvlzF9URrMe1EP1F4++TLUWR/BQHhTlc6UugnxDir7yR1wNGAq8B/YGXpJSNgf8Cw/U2dYCCvoJfA0yQUtZFSeQZz217IKV0B74BgoAP9fcaKITIeVt8GVihvz4N+EB/fJmU0k1KWQcoDXQwum8JvcZReZ6XwxQgUkrpBngBC4UQZYD3gP+TUtYHGgE39cnZR0KIqigJzYPAYaCZ3ua0lPIB0A2ory8vb/09cyJnY2CKlNKwKIwQ4mVgM/C2lDIOGAzc1WtyA94VQtQAuurL4DXgXXKTqvkQQgwRQhwVQhyNzbhckFlB1+Y7Zu6LoLPfh7O2xRgOzl9PwxFdci7Ob6jiF9Xmtcsn2iAlQ8cNImDlRjL/yMx/XiWeVb+xycK5S2lWty3bNu3krXfyr1WlBn/lm8PfEm8x1nckw93fw7O7Fw4V1UsSmi3LvDY8+W+iOgX4sKnJ43XXfLkGI6Z+wJxxCwtd3mN5Ch9/kk2tl2swauoHzB73SaHLK4i/4wdtBvhycu8xk4Sc6ph1mbw+U7BNiRLWlCtXlnat/Zk97VNWfqfOFFBzXa2/Uv1GNRvCjI7j+WrEEvpNH4RTVecnX1QIPK4sn9Ymx88/HvdpYcv7W5jzeyGE2b+L2fa2CHn2NrSYYzpPFdafLn6qzDOXOfBbym26Ne7D2z5DWTrrK2Z8OYXn7J4rKqlP1vQXfOXsiZ/o6dmf/u3e5e3hb1KyVMmiEWqGp4kvOdTt0hzXujWJXaGM9nXr783lvadIS1TvS2NjCquOdu/RgS2bggtX3BOw1PhSWJr69u1Go4b1WPTZ14Uh66n4u2X+/nvjGTqkP7H7d2Bnb2eYVaIGf0e7bWlbRowZwqJ5y4pMX0H8E334fxkpRZH8FAeFtmu5lDJNCLEGGAE8beYmTkqZCCCEuALkLExyBiUJWCD6hGk5KWW0/tD3wEYjk5zVms8A54yecxWoAtwBbkgpc6Zu/6jXvgjwEkKMB54DygPngJy5Blv0/x4DqpuR1hboJHLX8bQFqqIkKacIISoDW6SUOdnAnFGZbwCLgUr6/99FmXoO0AIIkFJmAclCiGiUhGQacERKec3o+Y4oidvuUsqcxdPaAnVF7shYB+BFwN3ovglCiEgznwcAKeUKlFG3fFXlzb8UfTISb2Pnmjvixc6lPH8k/16g/eWgQ7jPfRtQRmAaX1vGpTz3HnNtYZOSmIqza+63o84ujtxKMh0Rkqy3SUlMxdraGruyZbj7exqvNqhNq/YeDJ/6HvZl7cjOlvz55wM2frsl72MKlQGD/endX9kg5/SJc7hWyv3WS+fqTEpSqol9UkIyOqNvpl1cnUk2M7Q/aFMI367/kiWffFVEyhVuJ/1GBZfc0TnlXSpwO/mvd5B/T7nNjUs3qN34VQ6FHHjyBYVAcmIKOmN/cXUiNU95JyemoKvkTHKOv9jbcff3NFX0FURKQkoeP3ciNa+fJyifzeDn9mUMup1cHFm8eh7Thn/MzV/iVdWe/JTanV3Nl7mziyNLVi9gisrazfn570/p5y++/jIvu71Cm/7tsC1ji7VNCe7fu8/6T34oKrkAvP1OX958qycAJ0+coZLRdDAXVx1JiaZxIyE+2WSkg6urzjBtKCEhmZ07lM1bThw/Q3Z2NhUqPM9vvxVtfL+d9BvlXXJHvpZ3qcCdvxBf7qQo+lJvJHPh0Fmq1alJyq/JT7jq75OckGoSp51cHEnJ5+eKTUF1dMnq+UwdPlv1OvokdE4VSUrJ/SzJKbdwqlgBnVNF4k6czj2eegu3BnWLXE+/QT3x769sAnX6xE8mI7d0rk6kJJuWe1JiisnfRueSv51VizcH9TJoP3PyHK6VnA0jAXSuTiTna/9N2ywXV6di055DSmIqTkaanFwqcitPmefYpCbewtraijJly5Cm9/Wc0cYXz1wm/noCVWtW5sJp080jikZ3CrpKxrodDUs6mNiY6S8ac+3yL2T+cZ9a/6nB+VPqjJxKS7qNg2tuXCzrUp70lDv57Go2fxWPYZ1Z7T+HLP0yPlVef5Fqbi/j1t+bks8p7dGDP+6z55PAItM7+N1+DBjoD8CJ46dN2iLXSubaoiSTvrBrnvbK2tqaDp3a0qpl/s3fCpt+g3rSq78yWOPMiZ/QueoAZXSrs6szKcl56miiaR/d2cU5X+xXg/ffe4vBg5UNT48ePUnlKrl7HVSq7EJC4l9rB1u3asmkiSNo1bo7Dx4U7ZJKQ4b25+23lYEYx46donLlXO2Kv5hqT5vbfWUAACAASURBVIhPxNXIpypVciFR7y+XLl2hU6cBALzwQg18fR+brvjbvDW4N30HKK/vp06cNfFjc+9reWfH5NhUr16FKlUrERaz2XB8d9RGOnj3JjWl8L8UL2x/0dAwR2EvIPc5yui/MkbHHuU8Rz9F2/grxj+N/p9t9Hs2uUnWc8CzbLFpfK+8z8m5d96EnBRC2AJfAT2klK8BK1GSkXnvm4X5RLBASSLW1/9UlVKel1KuAzqhJHlDhRA5C1bkrJP5GsrU8kMoIzKN18d8XJr7Xp7f7wI3gOZ5NA030lRDSpmTNC7yr0RSTl3FoboO+yqOWNlY80KnplzbY7p4vEP13KBbrXV97l5Xhs5f23OcFzo1xapkCeyrOOJQXUfKyStFLdnATycvULVGZVyruFDCpgRtOrdmX5jpsqUxYftp31PZHbtVBw/iYpXPNqTrcDo38adzE38C/ruJ75b+WORJTIA1qwLx8+yFn2cvwkIi6e6v7D7ZoFFd0tPS872EpSTf4l7GPRo0Ul4Qu/t3ZM8uZZpH9ZpVDXZt2nly5fI1ipqfT13GpYYLTlWcKGFTguYdW3J0z5Gnura8roJhFEOZsmV4udF/SLii3kv72RPnqVqzCpWqKv7Srksb9oaabhiyNzSGzr38AGjb0YvDsUdV01cQ505eoGrNyrjqdft0aU1UWKyJTXRYLB31ur07eBK3X3k9titrx9IfF7J03nJOxam/Pta5k+epZlTmvl28iQozLfOosFg66bW36eDFEb12+7J2LPvxM76Y9zUn407nu3dRcuXUZXQ1XHCs4oS1TQmadWzBsT1xT3XtlyM/Z8QbQxjZYihr535H7JaoIk9iAnz733W0btmV1i27sis4gp59OgPQsFE9fWwxfQFLSU4lI+MeDRvVA6Bnn87s3hkBwK6d4bRwbwJAzVrVsbGxKfIkJsDVUz+blHvTji04/pTl/lzZMpQoqTT7ds/b82Kj/xB/+UZRyjVw7uR5qtasbOLn0XnqaFRYDJ16Ket15ffzRfzfvG84WQx19El4tmjK9t0RSCk5dfY8dnZlcKxYnuZNGnLgyHHupqVzNy2dA0eO07xJ0e+4vnb1Rjp59aWTV1/Cd0XRxV/ZfKB+wzqkp2XkS06l6tvQ+g2V5RG6+LcnfHd0vvuqwY+rN9DRqw8dvfoQFhJF117KhKL6DV97jPY/qN9QmYLdtVcHwndFqS3bhAsnL1C5RiVcqugoYVOC1p1bERt20MQmNuwAfj2VNes823twbL+y2Um58g6GtbFdq7pQpUZl4n9NRA3OnbxAlRpVDP1Fn87eRIea9hejQ/fTQV9HW3fwNPQXXau4GDb3cansTPVaVUm8kYRaxJ+6SvnqOspVdsTaxprXOjblwh7TyXC6V6vRad5g1r7zGfd+y02+bh71FYubj2RJi1GEzlvHqS0xRZrEBFi1cq1hg56dweH07qMkBhu51SftbjrJedqi5ORUMtLv0citPgC9+3QhZGe44byn1xtcvnSVhISiL/O1qzfS2asfnb36Eb4riq7+St+kXsM6ZKRlkJpsmlRKTf6Nexn3qKePL139/Ygohvjy9Tff08itLY3c2rJ9eyj9+ynJtSaNXyftbprZtQ0Lon79V/nqywV07fY2qalFP7NkxfIfaNbUj2ZN/dixI4y+/boB4ObWgLS0dJLyfsGTlEpGRgZubg0A6NuvGzuDlddmR0cl4S+EYMKEYaz679oi1f79qvX4ePTAx6MHu3dG0qN3JwBeb1SX9LQMs+90GRl/8Lr+na5H706EhezlwvnL1H/Zg2b1fWhW34fEhGR8PXsWSRITTP0laHsob/4Nf9EoXP5NU8sLbUQmgJTythBiA0oyM2cL0usoicgNQGfgr64wPx/4VAjRQUqZpF87cqiU8gshxO9CiJZSyhiUqel/NbJXFUI0k1IeBPoAseQmLW8JIeyAHsCmv3DPUGC4EGK4lFIKIRpIKU8IIWoCV/W6awJ1gUiUZOUY/bks4LYQohzKmpnv6u+5DxgqhPgeZYSoOzAO+I+Z5z8AuqAkSzP0CdRQ4H0hRKSU8qEQ4iUg3ui+a1DWx/QCCn2RG5mVTcy07+n443iEtRUXAqP5/VI8bmO6k3r6Gtf3HOe1gW2p3OJVsh9l8efde0SMXg7A75fiuRJ8mD6Rn5D9KJuYqd8hzWx8UVRkZWXx6ZTP+WLdIqytrdi+PoSrl64zdNwgzp+6yL6w/QQF7GTWF1PYsn8daXfSmfL+TNX0PYnIPTF4tWnJvqM7ycy8z9jhuTvchURtwM+zFwBTxs7hs2VzsLUtRVRELHvDlRfkidNHUfOF6mRnZxN/I5HJYz8ucs3ZWdmsmr6CKWtmYmVtxd4NEdy8fAP/j/py5fTPHA0/Qq26LzBuxSTKONjR0NuNXqP78FGb4VR+oTIDpg5CSokQgh0rtvHrRfXWO8rKymLepEUsX/9/WFtbsTUgmCsXr/Hh+Hc5d+oCUaExbFm3g/nLZhByaCN376Qxbmju3yQ0bit29s9hU9KGVu08GOI/QpWNorKysvhk8hK+CliMlbU1QQHBXL14jffHv8NPJy8QHRbLtnXBzFk2jaCDgaTdSWPiUGVljd6DulOlRmXeHT2Qd0cPBOD93qP4/Vb+0RxFpX3e5M/4OuBzrK2t2KYv8w/Gv8tPJ88TFRbL1nU7mLdsBsEHlTIfry/z3oN6ULVGZYaMfpsho5VR4O/1HsXtW0WfUMvOyua76SuZuGYGVtZWRG2IIP7yDXp81Ierp3/meHgcNeu+wOgVEyjjYMfr3m70GN2b8W1GFrm2pyE8LJrWbd05fDKMzD/uM/LDyYZzETFbaa0f2TLho1l88dU8bEvbErEnhog9yg7sAT9s4fMv5xJ9cDsPHj5kxPsTVdGdnZXNmun/Zdya6VhZW7FPX+7dPurNtdNXOBEeR426LzBqxQTKOJShvrcb3Ub7M6nNKCq9WJm3572HzJYIK0Hw11tJuHxTFd1ZWVnMn7yYrwOWYGVtbeTn73BOX0e3rgtm7rLp7Di4gbQ7aYwfquxOnuvnAxliqKOjVfFzgHEzFhB34jR37qTRusubfDC4P48eKaO5/Lu2x72ZGzEH42jXaxClbW35eLKy3LpDWXuGDuxD73cUn3/v7b6P3TSoKIjaE4uHd3MijgSRmXmfiSNmGs5t37uOTl59AZgxbj6fLJ2Jra0t0ZH7iQ5XElht/LyYPn8c5Ss8z8p1/8f5c5cY1GuYato9vVsQGRfE/cz7TDDSvmNvAB29lBFK08fN49OlsyhlW4roiANE6bW39fNi+oLxlK/wPP9d9wU/nb3E270+LHLdWVnZLJm6lMXrPsHayprgwF1cu3Sdd8YO5MKpS8TuOUDw+hCmfTGZwNgfSLuTzowPlL5J/aZ1eWfs2zzKyiI7K5uFk5aQfkedne6VdnQxXwYsxsraiu3rd3L10jXeGzeYn05dYF/YfrYFBPPx0mkEHVjP3TtpTHpvJgANmtRl4LA3efTwEdkym/mTPuPObfX2Nc3Oymbn9O8YsGYCVtZWHN8QTerleFqN7k78mWtcDD+Oz6S+lHzOFv+vlPp4N/4W695drJrGgtgTGkWbth4cOxVBZmYmw4zakuj92/ForiR+xo6ewZfffIKtrS3he6IJD8t9ZezaowObN6o7rRwgas9+PLybE35kG5mZ95k0YpbhXNDetXT2Uka0zRi3gAVLZ2JrW4p9kQeM4osn0/TxZcW6zzl/7hKDew03+6zCJGRXBL6+rbh4fj9/ZGbyzjsfGc4djQujkZvyJcOC+VPo7d+V554rzfWrR1n97Tpmf7yYT+ZPw86uDOsDlHe9Gzfi6drt7SLXDRC6ey8+Pl6cORtN5h+ZDH1vnOHcwUMhNGuqJJZHjpzKiuWLsC1tS1hYFKGhUQD07NmJIUP7A7A9KJQ1azbme0ZREblnH63atCT22C7uZ2by0TCj94foTfh4KMnCyWM/ZvGXc7C1tSUqPIbI8JiCbqkKu3ZF0M63FRfO7yfzMf4y38hfrun95eOPF9OoYT02blzF88870L59G6ZPH0P9+q0KepzG/xCiMNYo0CfM7PT/dwauAZ9KKWfqfw9CGZUZgTIy0E4I4YmyiU8H/XVR+t+Pmjn3NkqyT6CMIFwtpVwshKiPsgbmc8BVlDUhf3/CvaKAscAtIAQlmfcGcBnoL6X8QygbAvVGScLeAH7Rfxbj+1YEjkopqxs/QwhRGmVk6ht6vdf1xycBbwIPgSSgrz7xaw38DnwhpZyq1/gd0ExK+bL+dwF8CrTTf/45UspAM5+tOhAspayjT4buAeagTIufA3TUa0pFSXamAUuBVkDOvJsfpZSPTdz+1anl/xS+zfq1uCU8Eyl/qpMQKgoa29UobgnPxPn7ljvlwUZYF7eEZyYLy9yRsE4py120POLO+eKW8Ey0LffKk43+oZz+U72RVoXJ0bM/FreEZ+aV2j2LW8Izk22ha4npSpUrbgnPTGZ20U51LSo6lKpW3BKemWW/Pd3Mm38iFW2Ld8PGZ+XqXXVGKxcFpUr81XFR/wyet7UrbgnPTHKGeku7FTYPH8QXz5DBfyCHXLsVSaeiacIW1cu4UBKZlohx0q+YpVgcWiJTXbREpvpoicziQUtkqo+WyFQfLZGpPloiU320RKb6aInM4kFLZKqPlshUHy2R+e/g35TILNSp5RoaGhoaGhoaGhoaGhoaGhoaGhr/HIprPcui4H82kSmlvA5oozE1NDQ0NDQ0NDQ0NDQ0NDQ0NP61yH9RIrOwdy3X0NDQ0NDQ0NDQ0NDQ0NDQ0NDQ0Ch0/mfXyNR4dmo7NbZIp7G1ssz1VGysLHfg9O8PM4pbwjPxZ5Zlro8FYGtdqrglPDNZ0jLXyHyY/bC4JTwzz5dUdxfowuKOhcYWgFJWJYtbwjMhscimH4Cfzqu3s2xh8yjoq+KW8Ey8MHZXcUt4ZsqVtMx17DItuO9SwoLX97YSljnCKeNRZnFLeGbsSpQubgnPxIPsR8Ut4ZmxFpY7/u1y6jHLrKRFQIyuR5F05lombVK9jC3XIzU0NDQ0NDQ0NDQ0NDQ0NDQ0NDT+Z7DcoV4aGhoaGhoaGhoaGhoaGhoaGhoaj0Xy7xmcqiUyNTQ0NDQ0NDQ0NDQ0NDQ0NDQ0/qVkW+4qQfnQppZraGhoaGhoaGhoaGhoaGhoaGhoFCpCCF8hxEUhxM9CiImPseshhJBCiEZPuqc2IlNDQ0NDQ0NDQ0NDQ0NDQ0NDQ+NfSnYxTC0XQlgDXwJtgJtAnBBiu5Typzx29sAI4PDT3FcbkamhCi28mhJyYCO7D2/mneED8p23KWnD4hVz2X14M+t3rca1iovh3Lsj3mL34c2EHNhIc6+masoG4A2vJmyNDSDoYCBvD3sz33mbkjYsWD6boIOBrAlZgUsVHQBN3N1YG7qKDXvXsDZ0FW7NX1dbOk09G7Mx5gc271/LgGF98523KWnD3G9msHn/WlYHf41LZZ3JeedKTkRd3kW/9/zVkmxg2rxxhB/Zxo6o9bxS9z9mbV6t+x+CowMJP7KNafPGGY77dvImJGYDF5PjqFOvtlqSDcyaP5F9R3cSGrOZOnXNP/+1eq8QFruFfUd3Mmt+7hdTYyYPIzRmM7uiN/Lj5uU46xzVks3UeWPZc2Qr26MCeKXuy2ZtXq37H3ZEr2fPka1MnTfWcNy3U2t2xgRyIflIsZT59HnjiDwSxM7oQF4twF/q1KtNyL5AIo8EMd3IXybOHEXYwc3sjA7k6+8XYV9W3R1rLdFf3vBqQlBsADsObmDQsP75ztuUtOHT5bPZcXADP4asxFUfF5u6uxEQuppNe38gIHQ1jZs3VEVvXmbOn0B0XDC7920qsMzr1KtNaMxmouOCmTl/guH4mEkfsnvfJkKiNvDDpm9w0uroU2GJMX3qvMW4t+9NlzffM3teSsm8JV/Trtcgug54n58u/mw4FxSyBz//wfj5DyYoZI9akg3sv5pC55WRdFwRwepDl/OdXxhxll7fRdPru2g6rYykxf8pu4zH/XLLcLzXd9E0/mwnkZcT1ZbP7AWTiD22iz2xWx4bF8P3byX22C5mL5iU7/zQYQOJ//0cz5cvV9RyAaWvG7x/A7sObSqwr7toxRx2HdpEwK5Vhr6uw/Nl+XbLV8Rd3csUozqrNtPnjSfySBAhT2hHd+3boG9HxxuOT5w5ij0HtxASHcjX33+majtqyXFxytwxhB7eQlDUOl55rWDt26MCCD28hSlzxxiOO5Qry6qNy9h9aDOrNi6jrIO9WrIBmD1/ErFHQ9gT84Q6GruF2KMhzJ5vvo7evH1WtToKll3mllpHLbH91yhUGgM/SymvSikfAOuBzmbsPgY+Be4/zU0tKpEphMgSQpwUQpwVQmwUQjxXTDpGGT9bCDFICHFGCHFar83cH8b4+plCiELpqZi7lxDiuhCiov7/B/T/egohggvjmX8VKysrpn0yniF9RtKxhT/tu/lQ66UaJjY9+nXi7t10fJt0Z83yAMZOGwZArZdq4Ne1LR1b9ubd3iOZ/sl4rKzUc1srKysmzh/DsL5j6O7eD9+u3tR8qbqJTZe+HUi/k07nZv6sXR7IyKkfAHDn9h1GDZhAL68BTB85hznLpqumO0f7+HmjGNlvPP6eb+HTuTU1XqxmYtOpT3vS76TTvXk/AlZuZNjUoSbnR88cxsHII2rKBsDDuznValbBu3EXpo2Zw+xP83d+AGYtnMTUMXPwbtyFajWr4N76DQAun/+ZDweOI+7gcTVlA+Dl3ZLqtarh3qg9E0fPYu5nU83azV00lYmjZ+HeqD3Va1XD07sFAMuXfotPy+608+hJRGg0I8eZf4EubDy8m1O9ZhXaNO7KtDFzmfWYMp82Zi5tGnelukmZX2HYwPHEHTyhil5jPL2bU71mVVo17syUj+Ywe6F57bMXTmLKR3Np1bgz1WtWxUOvPTbqEO1a9KK9hz/XrvzK+6MGqabdEv3FysqKyfPH8kHfMXR172s2Lnbt25G0O+l0bNaLH5cHMsoQF+8yYsB4enj1Z9rIOcxVOS4CeHm3oEbNani4dWDSR7OZs6jgMp80ehYebh2oUbManq31Zb7sO3zde+Dn2YuIsH2MHDvU7PWFjSXXUUuN6V382vDN4jkFno85GMevNxMICVzFzPEj+HjRMgDupqXz9bfrCFj5OQErP+frb9dxNy1dLdlkZUvmh5/hy55N2DLYi93nE7hyy/T541rXYcNADzYM9KDP6zVo/ZKSVHOrVtFwfKV/M2xtrGlWXb1kPUCrNi2pUasaLRq2Y8Komcz/zHycmP/ZdCaMmkmLhu2oUasaXvq4COBaSYe75xvcvJGgimYrKyumLBjHe31H0allb/y6ts3X1+3etxNpd9Jp17QHa5av56NpHwLw4M8HLF2wnIUzv1BFqzk8vVsY2tHJH83h44WTzdp9vHAykz+aY9SONgeUdtS3RU/8PPy5fuUXPlCpHbXkuOje+g2q1ayKT5NuTB8zjxmfmp9tOePTiUwfOw+fJt2oVrMqLVsp2t8d8RaH9sXh27Q7h/bF8e6It1TT3sq7JTVqVaVFIz8mjJ7J/M+mmbWbv2ga40fPokUjP2rUqmpSR10q6Wjp2Uy1OgqWXeaWXEctsf3/tyIRRfIjhBgihDhq9DPE6LGVgBtGv9/UHzMghGgAVJFSPnW+yqISmUCmlLK+lLIO8AB46jc2/ZDWwmIU8Jz+vpWBKUALKWVdoClwuhCfhRDimZcAkFK+UZhanoW6r7/Kr9ducvOXBB4+fETI1jBa+bqb2LTy9SAocCcAoTsiadrSTX/cnZCtYTx88JD4XxP49dpN6r7+qmra6zSozY1rN4n/NYFHDx8Rui0CT5+WJjaePi3ZsSEEgPDgKBq3UEYYXTx7mdTkWwBcuXCNkqVKYlPSRjXtrzaozc3r8ST8msijh48IC4rE3aeFiY2HT3N2bgwFIDI4GrcWuaNGPXxbEP9rAlcvXVNNcw7evh5s0/vDyWNnsXeww9G5oomNo3NF7OztOHn0DADbAnfSpp0nAFcuX+falV9U1ZxDWz8vNq/fDsCJo6cpW9YepzzanfTaj8edAmDz+u34+LUCICP9nsHuuedKI6U6qzK39vVga6Dix6eOncXewR5H5womNo7OFbCzL2Mo862BIXj/A8rcu50nWzco7d7JY2co62BfgL+U4cRRJTxv3RBMGz8vQOncZWVlKdcfPYPO1Uk17ZboL3UavGISF3dvC88XF718WrJ9gzLCa0/wXhq3UJa6uXD2kiEu/nzhqupxEaBNOy82B+4A9GXu8Jgy1/vL5sAdtNX7S74yV0m3RddRC43pjeq/hkPZgkfc7I09RCff1gghqFenNunpGaTeus3+w8do5tYAh7L2OJS1p5lbA/YfPqaa7rOJv1OlXBkqlyuDjbUVPrVdifo5qUD7Xefj8a1dKd/xPRcTaV7DidI26q5E5ePXik36uHj86GkcCqij9vZlOKaPi5vWb8e3fWvD+ZlzJzB35meqtaGvva7ERUNfd9sevPL1dd0J2qDUg7AdkTRtofR1M/+4z/Ejp3jw5wNVtJrDu53HM7ajnoBpO3ri6Bl0rs6q6LbkuNi6nYfBH04dO6uUuVMe7U6m2oM27MTbz0O53teDbYHK32xbYLDhM6lBWz8vkzpacN+ljKHvssmo7wIwc+545s5YrFodBcsuc0uto5ba/v9byS6iHynlCillI6OfFUaPNTef3VDxhRBWwBJgjBm7ArG0RKYxMcALAEKIN4UQR/SjNZfnJC2FEBlCiNlCiMNAMyGEmxDigBDilN7eXghhLYRYKISI04+oHKq/1lMIESWE2CSEuCCEWCsURgCuwF4hxF7ACUgHMgCklBlSymv6e7yrv+8pIcRmcyNIC7IRQnwnhFisf8ZCIcRlIYSj/pyVfqHUinnvZ+b+GWaOuQkhTgghagohygghVus1nHjSaNJnwUnnSFJ8suH35MQUnF1Mv9131jmSqLfJysoiPT2DcuUdcHZxJCnB6NqEFFWn8Tm5OJKckJL7/MQUHPNod3JxJElvk5WVRUb6PcqVdzCx8e7gycWzl3j44GHRi9bjqKtooj0lMRVHl4oF2mRlZZGRdg+H8g7YlrZlwAd9+e9n36um1xhnFycSjf7uSQkp+abMOutMfSMpMRlnF/USUAWhc3EiMT73hTEpIRldHl06FydT7Xlsxk0ZzqEze+jSsz2fzf+y6EWDvq7l6k5OSMZZZ6rbWWeqOzkxOV9dLg6cXZxIiDf1F10eXTqjegqQmJBi1l969OtMdMSBohObB0v0F6c8cTklMTWfHxjbFBwXvbigclwEpTwT8pR5Xl9wzlPmiWbK/ODpMLr0aM9irY4+EUuO6Y8jOfU3dE657aqzU0WSU2+RnHoLnVPu53N2VI6rRUrGfXT2pXOfb29LSrr5mVoJd/8g4e4fNK6av0sZeiGedmYSnEVN3jqq1D/nPDbOJj6VmJBkqKNt2nmRmJjMT2cvqiMYpe4l5umv5vVxJxdHkuJz+1w5fd1/Ak/fFqU81gagZ7/OREXsLzqxRlh0XNQ55o+L5tqixBRTG71fVXAsT2rKbwCkpvxG+YrPq6BaQefi/Ax1NNemja8nSYkpnD+nXh0FSy9zS62j/872X+MvcROoYvR7ZcB4KLY9UAeIEkJcRxkYuP1JG/5YZCJTP0KxHXBGCFEb8AeaSynrA1lAP71pGeCslLIJcAQIBEZKKesB3kAmMBi4K6V0A9yAd4UQOXNBGqCMvnwFqKl/xhcoBe8lpfQCTgHJwDUhxLdCiI5GUrdIKd30zzuvf1ZeHmfzEuAtpRwN/Gj0ubyBU1LKnF7xaH0S96QQ4iRKorWgsnsD+AboLKW8ijKaNFL/+b1QkqZlzFxnGC58JzMl7+nHIkT+JHzeL9/M2SALuFa18S+AWV0yj4m5z5drU/PlGoyY+gFzxi0sdHmPo6AyfbKNZMi4twlYuZHMPzKLRtwTeFKZPq1NsfAU/m7eJtdo4dylNH2tDds27mTgu30KW6FZLLnMn6KaPrHMAT4YPZisR48I2hhSiOqegAX6i/nyzusrj7ep9XINRk39gI/HfVrY8p7Is/t67v8Xzl1Ks7pt2bZpJ2+9o9XRJ2HJ2h+HOX1CiPx1mALa2yLC/PPN24ZeSMD7ZResrUwNUjPu83NqOs1qqJ/w+Tt11La0LSM+GsKi+cuKTJ9ZzHa58mg2Y/RP8fGnK/P815lrRx89ylKtHbXo2PI0up6mj1AM/J1yty1ty4gxQ1g0T+U6qogyq+nJNkUl6OnR6qhGYVBUU8ufQBzwohCihhCiJNAb2G7QJOVdKWVFKWV1KWV14BDQSUp59HE3tbRdy0vrE3WgjMhcBQwBGqLsfgRQGsjJtGUBm/X/fxlIlFLGAUgp0wCEEG2BukKIHno7B+BFlKnrR6SUN/V2J4HqQKyxIClllhDCFyUJ2hpYIoRoKKWcCdQRQswBygF2QKiZz/Q4m41Syiz9/1cDQcDnwCDgWyO7JVLKRTm/6DPZ5qgNrADaSilzsuBtgU4id51NW6AqSlLV+HOu0F9LbafGfymyJCemoKuU+y2ds4sTKUmpJjZJiSm4VHImOTEFa2tr7O3tuPP7XWVkldHQd2dXJ1KTVBzVkJCCs9E0U2eX/M9PTkhB5+pESmIq1tbW2NmX4e7vaYDy7fvi1fOYNvxjbv4Sr5pu0I+SMtLu5OKYT3uOjUF7WUV7nQav0Kq9B8OmDsW+rB3Z2ZIHfz5g47dbi0xvv0E98e/fFYDTJ37CxejvrnN1IiXZVHtSoqlv6Fyc8/mVWgwY3Js+A7oDcPrEWVwq5W6apHN1JjnJNPmflJBsqt3VmWQz2rdtCuG7wC9ZvOCrItHdb1BPevXvAsCZEz+hc9WhfDcDzq7OpCTnraemup1dxKT/XwAAIABJREFUnElRsT4a8+agXgZ/OXPyHK6VnMmZuKlzdcpXnkn6epqDi6tpHOrm3wGvti3p363o15i0VH/JITkh1USPk4tjPj/IsSkoLi5ZPZ+pw2erFhcHDPand/+cMj+Ha54yz9cm5SlzFzN/F4CgTSF8u/5Llnyi1dG8WHJMf1p0ThVJSsn9HMkpt3CqWAGdU0XiTuSuMpScegu3BnVV0+Vsb0tSeu4Xkcnp93G0szVru/t8PJPavJbveNiFBLxe1GFjrc6Yh7fe6UO/AUpX/OTxsyZ11Fz9S0xIMvEpF1cdyUkpVK9RharVKrEnZovh2tDoTbRv3ZvUlKKrC8mJKSZ6nF2d8sfFxBR0lZxM+ro5cbE46D+oF/79uwFw+uQ5M22Raf1LzNOO5rXp5t+RVm3debNb0a4bbMlxse+gnvR8M1d7vriYp8yT84yoU2KnYvNb6m0cnSqQmvIbjk4VuH3r9yLV/tbg3vTV19FTJ56ljio21atXoUrVSoTFbDYc3x21kQ7evQ2jHQsTSy5zS66j//b2X+PpkVI+EkIMQ8lzWQOrpZTnhBCzgaNSyu2Pv4N5LG1EZs4amfWllMP1ux4J4Huj4y/rk4gA940SgYJ849EMx4cbXV9DShmmP/enkV0WBSR+pcIRKeV8lAxzd/2p74BhUsrXgFkoScK8PM7GsBCXlPIGkCyEaAU0AXaZ0/IEElF2gWpgdEwA3Y0+f1Up5Xnzlz8bZ078RLWaVahU1RUbmxL4dW3L3tAYE5u9ofvo7N8eAJ+OrTgUe1R/PAa/rm2xKWlDpaquVKtZhdPHzxWmvMdy7uQFqtasjGtVF0rYlMCnS2uiwkxy2USHxdKxlx+gTCGP26+kU+zK2rH0x4UsnbecU3FnVNOcw08nL1ClRmVcq+goYVOCtp1bERNmOo1gX9h+2vf0AaBVBw+OxiqLnQ/pOpwuTXrTpUlv1v93E98t/bFIk5gAa1dvpJNXXzp59SV8VxRd9P5Qv2Ed0tMyDOvq5ZCafIt7Gfeo37AOAF382xO+O7pINRbEmlXraefRk3YePQndGUn33p0AaNCoLulpGfka7BS99gaNlBfb7r07ERayF4DqNasa7Nq08+LK5aJbo3Tt6o109upHZ69+hO+Koqu/4sf1GtYhIy2D1GTTDmVq8m/cy7hHPX2Zd/X3I6KYyvzH1Rvo6NWHjl59CAuJomuvDgDUb/jaY/zlD+o3VF7Yu/bqQPiuKADcW73BkBEDGfrmKO5nPtVGeX8LS/WXHM6dPE/VmpWppI+Lvl28ic4TF6PCYujUq52iq4MXR/Rx0b6sHct+XMT/zfuGkyrGxTWrAvHz7IWfZy/CQiLp7q9MnlDKPP3JZe7fkT27zJW5p1ZHC8CSY/rT4tmiKdt3RyCl5NTZ89jZlcGxYnmaN2nIgSPHuZuWzt20dA4cOU7zJg1V0/WqSzl+/f0e8Xf+4GFWNqHnE/B4QZfP7vpvGaTdf0g91/zTI3efV3da+ff/DaCte3fauncnNCSCHvq4+HqjuqQVEBczMv7gdX0d7dG7E6EhkVz46TL1XnKnab22NK3XlsSEZHw8ehRpEhPg7InzVK1ZhUpVXZS+bpc27A3dZ2KzNzSGzr2UetC2YysOxz52sEmR88PqDXTw6k0Hr97sCdn7jO2oUkfdW73B0BEDGaJCO2rJcXHd6o10bdWPrq36EbEryuAP9XLiYp5EXmrKb9zL+MOgvXOv9kToyzwydB9d/JW/WRf/DkX+mb5ftR4fjx74ePRg985IkzpaUN8lbx0NC9nLhfOXqf+yB83q+9Csvg+JCcn4evYskiQmWHaZW3Id/be3/5ZKUa2R+SSklCFSypeklLWklHP1x6abS2JKKT2fNBoTLG9EpjkigCAhxBIpZYoQojxgL6XMuyrsBcBVCOEmpYwTQtijTC0PBd4XQkRKKR8KIV4CnjREJB1lLv8tIYQroJNS5mylVR/IebY9kCiEsEGZFm7uvk9jk8N/UaaY/2CUoP0r3EGZuh4mhLgnpYxC+fzDhRDDpZRSCNFASlmoW/dlZWUxZ+JC/hv4BVbWVmxZt4OfL15l+IQhnD15nr2hMWxau51PvpzF7sObuft7GmOGTgHg54tX2R0UTnBsIFmPsvh4wqdkZz9NdSk87Z9MXsJXAYuxsrYmKCCYqxev8f74d/jp5AWiw2LZti6YOcumEXQwkLQ7aUwcOgOA3oO6U6VGZd4dPZB3Rw8E4P3eo/j91h3VtC+c8jlfrFuElbUVO9aHcPXSdYaMG8T5UxeICTvA9oAQZn0xhc3715J2J50p789SRduTiNoTi4d3cyKOBJGZeZ+JI2Yazm3fu45OXn0BmDFuPp8snYmtrS3RkfuJDlcStW38vJg+fxzlKzzPynX/x/lzlxjUa5gq2iP3xODVxp2YYyFkZt5n7LDcHZF3RW+knUdPAKaM/ZjPvpyDra0te8Nj2RuuJPcnzhhFrReqk50tib+RwKQxH6uiO2rPfjy8mxN+ZBuZmfeZNCLXF4L2rqWzl7KyxYxxC1iwdCa2tqXYF3nAqMw9maYv8xXrPuf8uUsM7jVcJe2xeHq3IDIuiPuZ95lg5C879gbQ0UuZ+jt93Dw+XTqLUraliI44QJRe+8wFEyhZyobvN30NKIuoTxs7TxXtlugvWVlZzJ+8mK8DlmBlbc22gGCuXLzGB+Pf4Zw+Lm5dF8zcZdPZcXADaXfSGD9U2XW496AeVK1RmSGjBzLEEBdHF/moBmOUMm/JvqM7lTIfnrvbakjUBvw8ewEwZewcPls2B1vbUkRFxLI3XEnWTpw+ipovVCc7O5v4G4lMHqvV0Sdrt8yYPm7GAuJOnObOnTRad3mTDwb359GjRwD4d22PezM3Yg7G0a7XIErb2vLx5NEAOJS1Z+jAPvR+ZyQA773d97GbBhU2JaysmOhdh/c3HiJbSjq/VoUXKtrzVcwFXtGVw/NFJamZs8lP3ml98Xf/ICn9Pg2rVjB3+yInImwfrdq4s//4LjIz7/PRh7lxMWzfZtq6K+MFJo2ZzZKv5mJrW4q94bFE7okp6JZFTlZWFnMnLWLFeqWvuzVgB1cuXmPY+CGcO6X0dTev286CZTPZdWgTd++kMXao0eeK24qdfRlsStrQqp0HQ/xHcEXFzRb36tvRvXHbuZ95n/FGdTR473o6ePUGYJq+HbW1LUV0xH6i9HFRaUdLssaoHZ06dm6R67bkuBgdvh937+aEHdnK/T/uM3nkbMO5rZFr6dpK0T5r/ALmfTED29KliIk4wD79Ot4rv/ieJSvn071fJxJvJjPqHfM7cBcFkXv20apNS2KP7eJ+ZiYfDcttR0OjN+HjoYzcnDz2Yxbr+y5R4TFEhhdfHQXLLnPLraOW2f5r/PMRlrT+gBAiQ0ppZ+a4PzAJZYTpQ+BDKeWhvPZCCDdgKcr080yUtSb/AOYAHVFGJ6YCXVBGLY6VUnbQX7sMZejrd0KI4cCHKCMcB6JM83ZFGe2YCrwnpbwihHgfGI+S2DyDkmAdKISYCWRIKRc9xuY7IFhKuclIvw3wG9BYSnlBf8xwLyO760AjKeWtnDIQQnjmfB4hRFWUEZ2DUHZY/xx4Q//5r+d85oL4q1PL/ynYWqm7M25hYWNlud83/P4w315TFsGfWcW3c+jfxda6VHFLeGaypHpfUhQmD7PV3aymMHm+pHrJlcLkjoXGFoBSViWLW8Izoer61IXMT+c3FreEZ+ZRUNEuFVFUvDD2WSYO/TMoVzLfq4ZFkGnBfZcSyj6tFomViuvfFiYZj4pnHfzCwK5E6Scb/QN5kP2ouCU8M9bC0iby5nI59ZhlVtIiIMS5d5F05vyS16texhaVyPxfR79z0xIpZcvi1KElMtVFS2Sqj5bILB60RKb6aIlM9dESmeqjJTLVR0tkqo+WyCwetESm+miJTPXREpn/DnY69ymSzlz75ADVy9hyMyT/YwghJgLvk7tzuYaGhoaGhoaGhoaGhoaGhoaGxv8MWiLTQpBSLgAWFLcODQ0NDQ0NDQ0NDQ0NDQ0NDQ3LIftfNDbVcscIa2hoaGhoaGhoaGhoaGhoaGhoaPzPoI3I1Pif4b6FrmOXdzdRS+KRha4FY8llbqlrNQH8aaH+UsKC17G11PWaSgjLLXNLXWsy24LXVLfUdSYBSnT+oLglPBPW40KLW8IzY6m+XtraMtffBbifZZl9dABrC22P7Es8V9wSnhm7ErbFLeGZsNQ+F4AVlvt+oZFL9r/o72iZkVdDQ0NDQ0NDQ0NDQ0NDQ0NDQ0PjiVjm13Tm0aaWa2hoaGhoaGhoaGhoaGhoaGhoaPzj0UZkamhoaGhoaGhoaGhoaGhoaGho/EvJLm4BhYg2IlNDQ0NDQ0NDQ0NDQ0NDQ0NDQ0PjH4+WyNRQhRZeTQk5sJHdhzfzzvAB+c7blLRh8Yq57D68mfW7VuNaxcVw7t0Rb7H78GZCDmykuVdTNWUDlq39Da8mbIlZR9CB9Qwc9ma+8zYlbVjwzSyCDqzn+50rcKmsA+DV+rUJ2PMtAXu+ZX34d3i1c1dbOjPmT2Bv3A527dvIq3X/Y9amTr3a7IrZxN64HcyYP8FwfNLM0YQf2saufRv5Zs0S7MvaqyUbgJnzJxAdF8zufZuoU7e2WZs69WoTGrOZ6LhgZhppHzPpQ3bv20RI1AZ+2PQNTjpHtWQzZe4YQg9vIShqHa+89rJZm1fr/oftUQGEHt7ClLljDMcdypVl1cZl7D60mVUbl1HWQSvzp2X6vPFEHgkiJDrw8b6+bwORR4KYPm+84fjEmaPYc3ALIdGBfP39Z9iXtVNFsyXHRYDp88YReSSInU8o85B9gfoyH2c4PnHmKMIObmZndCBff79ItTIHmDZvHOFHtrEjaj2vFKD71br/ITg6kPAj25hmpNu3kzchMRu4mBxHnXrm60hR8nfKvF0nb3bFbuRyylFeq6+e9v1XU+i8MpKOKyJYfehyvvMLI87S67toen0XTaeVkbT4v10AxP1yy3C813fRNP5sJ5GXE1XTPXXeYtzb96bLm++ZPS+lZN6Sr2nXaxBdB7zPTxd/NpwLCtmDn/9g/PwHExSyRy3J+Zg1fyL7ju4kNGZzgTH9tXqvEBa7hX1HdzJr/kTD8TGThxEas5ld0Rv5cfNynFWK6ZYcF1t4NSV4/wZ2HdpUoPZFK+aw69AmAnatMmh3eL4s3275irire5kyb6zasgHLjeeW7i+WqL2ZZ2M2xfzIlv3reGtYv3znbUraMO+bmWzZv45vg78xvBe9Ur82a/es0v+sxtO3paq6QXmnC4oNYMfBDQwa1j/feZuSNny6fDY7Dm7gx5CVuFZRtDd1dyMgdDWb9v5AQOhqGjdvqLrurbEBBB0M5O2C3kWXzyboYCBrQlbgotfdxN2NtaGr2LB3DWtDV+HW/HVVdf9byRaiSH6Kg39sIlMIkSWEOCmEOCuE2CiE+EtbqwkhWgohzunvUbqodBYFQghPIcRdIcQJIcQFIcSip7imvhDCz+j3TkKIiY+7Ri2srKyY9sl4hvQZSccW/rTv5kOtl2qY2PTo14m7d9PxbdKdNcsDGDttGAC1XqqBX9e2dGzZm3d7j2T6J+OxslLPbS1d+4R5HzG831i6e7yJbxdvarxU3cSmS58OpN1Np/MbvVm7IpCRU98H4MrFq7zp+w592rzNsL5jmPLpOKytrVXT7undguo1q+Ll1pFJH81mzqKpZu3mLJrK5NGz8XLrSPWaVfFo3RyA2KhD+DTvTjv3nly78gsfjB6smnYv7xbUqFkND7cOj9U+d9FUJo2ehYdbB2rUrIZn6xYALF/2Hb7uPfDz7EVE2D5Gjh2qim731m9QrWZVfJp0Y/qYecz41Hz4mPHpRKaPnYdPk25Uq1mVlq3eAJSO6aF9cfg27c6hfXG8O+ItVXSD5ZY55Pp6q8admfzRHD5eONms3ccLJzP5ozm0atw5n6/7tuiJn4c/16/8wgejBhW5ZkuOiwCe3s0NZT7loznMXjjJrN3shZOY8tFcozJXfD026hDtWvSivYc/1678yvsqlDmAh3dzqtWsgnfjLkwbM4fZn5rXPWvhJKaOmYN34y5Uq1kFd73uy+d/5sOB44g7eFwVvcb83TK/dP4KHwwcyxEVtWdlS+aHn+HLnk3YMtiL3ecTuHIr3cRmXOs6bBjowYaBHvR5vQatX1Je1t2qVTQcX+nfDFsba5pVV+8Lki5+bfhm8ZwCz8ccjOPXmwmEBK5i5vgRfLxoGQB309L5+tt1BKz8nICVn/P1t+u4m5Ze4H2KCi/vllSvVQ33Ru2ZOHoWcz8rOKZPHD0L90btqV6rGp7e+pi+9Ft8WnannUdPIkKjGTnOfEK3MLHkuGhlZcWUBeN4r+8oOrXsjV/Xtvm0d+/bibQ76bRr2oM1y9fz0bQPAXjw5wOWLljOwplfqKbXGEuN55buL5ao3crKivHzRjOy3zh6eQ6gbefW1HixmolN5z7tSbuTTrfmfVm3cgPDpyqx48rFqwzwHUK/NoMZ0W8ckz4dq+p7kZWVFZPnj+WDvmPo6t4X367e1MzzTte1b0fS7qTTsVkvflweyKipHwBw5/ZdRgwYTw+v/kwbOYe5y6arqnvi/DEM6zuG7u79zOru0rcD6XfS6dzMn7XLAxlp0H2HUQMm0MtrANNHzmGOirr/zcgi+ikO/rGJTCBTSllfSlkHeAA8dS9ECGEN9AMW6e+R+ZTX/JOIkVI2ABoAHYQQzZ9gXx8wJDKllNullAuKUuDTUvf1V/n12k1u/pLAw4ePCNkaRitf0xF+rXw9CArcCUDojkiatnTTH3cnZGsYDx88JP7XBH69dpO6r7+qaX8K6jSozc3rN4n/NYFHDx8RGhSOp08LExtP3xYEb1BGkEQER+HWUvmW7n7mn2RlZQFQslRJpFQ3RLVp58WWwB0AnDx6hrIO9jg6VzSxcXSuiJ19GU4cPQ3AlsAdtPVrBUBM1EGD/hNHT6NzcVJV+2a99hNHT1PWwR6nPNqdnCtiZ2/Hcb32zYE7aOvnBUBG+j2D3XPPlVatcWjdzoOgDYofnzp2VilzpwomNo5OFbCzL8PJo2cACNqwE28/D+V6Xw+2BQYDsC0wGO92niopt9wyB/Bu58HWDUq5nTz2dL6+dUMwbfw8AeUlLNfXz6BzdS5yzZYcFwG823k+Y5kr/mJc5iePnkHnqk588fb1YJu+TE8eO4u9g10Buu0MdXRb4E7a6OvilcvXuXblF1W05uXvlvmVy9e49rO62s8m/k6VcmWoXK4MNtZW+NR2JernpALtd52Px7d2pXzH91xMpHkNJ0rbqLcsfaP6r+HwmJkIe2MP0cm3NUII6tWpTXp6Bqm3brP/8DGauTXAoaw9DmXtaebWgP2Hj6mmO4e2fl5sXr8d0Mf0so+J6XGnANi8fjs++j5AvpiuQh/GkuPia6+/wg1j7dv24JVPu7uhjxC2I5KmLRTtmX/c5/iRUzz484Fqeo2x1Hhuyf5iqdpfbVCbG9fjif/1/9k787gqyvb/v28QtNzKZDmouPWtpzK33EpFQFBxxUxxq8xcWlxTzNzNPdOeJ21Ry7JURNxQREHZBNTUXMq9zBYFzsFKAZdUuH9/nOFwzuGgpjA4/ub9evHSM3PNmc9c57rvueeae0nn5o2b7IiMo43dc5FP+1ZsjdgOQHxUEk1bmXsB/mP1XFS2FJ6L6jUyl9H8Z7rtm3bi2962V6hf+9ZsVp7pdkQl0KxVEwBOHj1NpvECAD+f/AXXsq64uLqopPspG90xm+IK6fZt35ota6MB2BmVSLNW5mfRU0d/sug+c/Ksqrp1tMH9nMi0Jhl4HEAI0V8IsU/pabkkPwEphMgRQrwvhPgOeA/oBUwRQqwSZuYrvTt/FEKEKMf4CiEShBCrgR+FELWUHpBfKLarhBABQohUIcRPQohmynHNhBC7lR6Tu4UQTyrbBwghNgghtiv2H+RfgBCigxDioBDiiBAiTtlWXgixXAixX/mubvYXriRhDwPVijq3EMIVeB8IUfwSomhZrBzztRDiY8X+FyHES8p2JyHEp0rP1SghRHT+vuLE3dONjPNGy2djugkPg23PBA9PN9IVm9zcXLKzc3ikSmU8DG5kpFkdm2ZSddinlrW7ebqRcd5k+WxKzyx0fjdPNzLSzDa5ubnkZF3mkSqVAfNNMyLxW9YmrGD2ux9abuBq4GFwt/gUID3NWCgZ6WlwJ93KvxlpRjwcJCx79Q0mKS615MTa4WlwJ+18wcOuI10eBneb2LC/vtCJw9nzQyzBL3Vi4ZxPSl40Shzb+NPkWHe6ydZGianH3KqQafoTgEzTn1Sp+qgKqs1o1eegxLGddkexnl9Oi7IB6NmvG4kqxLqW60Uwx0LaedtY97TT72lws/F5uoPyAPBSv24kxe0uObFWeBSq80yFhsx6eNr6NyPdcb2oNsXpc7Uw5VzDs2LBgB6PiuUwZV9zaJt26Qppl67QzLtqoX0xJ88T5CDBWZoYM//E071Aq4d7VYyZFzBmXsDTveB38XAzb1ebO68XjUXahE4czt4fdxDcsxMLVKjTtVwvenja1i1GB3WLu6GgTWmtvbTRan2u5XjRqnY3z6oYreLAmJ6Jm51udyub/OeiykqcP9PoKcITVhAW/xVz312g6nORu53fTOmZhXxubZObm0tO9uVCZTSgsx8nj57mxvUbJS9a0WTrc1NhnxvsnkUd6vbllIq6H2TySuivNLjvE5lCiDJAEOZE41NACNBSStkQyMXc8xKgPHBUStlcSjkT2AyESin7AS9i7rHYAAgA5gsh8ifraAZMlFI+rXx+HPgfUB/4D9AXaAWMBfLH/J0EfJQek1OA2VaSGyoan8WcWKwhhHADlgE9pJQNgJ6K7UQgXkrZFPBTdJW3u/5Hgf8DdhV1binldeX/4UoP1HAHrjQo19EZyO+p+SJQS9E6CHjewXH3jHAwb4L9iyxHNsgijlWxv9SDp13esc3RQ8fp6fsyLwcN5rXh/XEt61oyQh3g0KV3oN3+x3n7nUHczM1lU8TW4pR3S+7e7wX/nz9rEc/Xb8emdVt5dVCfYtfokDvQ7dimpATdOZr1eZG67LUXPs7e5q3Rr3PzZi6REdHFqs8RWq4XoSh/3t7Ikc9zb95UxedmSfdWp5cmxeVzNXF06qKmgYo5mUbAkwacnWwNMnOu8XNmNs/XVjdZfzsc+VUIUcQ1l8LcV3dyr7lNvMyftYgWzwayKWIrAwaXfJ2u6XrRoSy7usWB0YNUt9wf9fntbe6HeNGq9ru9h+Zf3LFDJwjxe5VXg4Yy4L58Lrq1Td0nazNq0lvMCP2gsGFJcQcF9Ha/S50nazNi0lvMDJ1f7PJ0tM39nMh8SAhxGDgA/A58CbQFngP2K/vaAnUU+1xgfRHf1QoIk1LmSimNQBLQVNm3T0p51sr2rJTyRyllHnAMiJPm0vQj5qQfQGUgQghxFPgIsO4THyelvCSlvAYcB2oCLYBd+eeRUv6l2LYDxivXkgiUA7yVfa2FED8AGUCUlDL/1fStzn0rNkkp86SUx4H8sYetgAhlewaQUNTBQoghQogDQogDF6+aijJziDHdhGe1guGOHgZ3TBmZNjYZ6SYMio2zszMVK1bg4t+XzG9WrYZKeni5k5mhXu8ALWs3pZvwrFbwxtnd4Gbpom9jowyjcXZ2pkKl8lz6O8vG5uxPv3H1yjXq/sd2/pvi5uXXQ9iaGM7WxHBMGZkWnwIYvDww2vk9Pc2Iwcq/nnY2L/bugn87H0YNdTxfUnHyyushRCeuJTpxLcaMTLyqedroKhQzaUab2DBfX+FyFbkumqAuASWmu+/AnmyMX8XG+FWYMi7Y+bNwrBvterx4erljMppt/sz8yzIU3c39Mf668HeJ6Qbt+hzg5YG9iEpYQ1TCGowZmRjstBeOdZPNcLdCsR5ijvXRb0wsUd35aLFe7D+wF1sSwtiSEIYpIxOvaraxbu/zDDufG+zKw4shnfFr15rRbzieu6+46DewJ5sTVrM5YbU5VuzLqF2dnpFu619PQ+GyoBbF7XO18ahYjozsgpmJjNnXcKtQzqHt9iKGlceeTMPv/zxxcb6/mtue7lXJMBXEjtF0AfeqjynbC3xuzDRvV4NXXu/NtqQItiVFYMowOagXbetr+zrdUd0JsEmFOh20WS/mY0w32dQtHl7umOzOb7RqU+Zrt28vqoVW63NrtB4vWtRuSs/EwyoOPAxuXCgU5wU2RT0X/frzb1y9cpW6T5bsc5GNrrRMG7+5G9wKl1ErG2dnZypULNDubnDjo+VzmDT8fc79dl413aY0k53PC//exjS7Z1E73QuXz2by8Bmq6n6QyRMl81ca3F8tK1vy58hsKKUcrvQ6FMAKq+1PSimnKfbXpJRF9fG+lXsv233+x+r/eVaf84D8CY5mAAnK/J1dMCcgHR2fqxwjcDwPqsDcSzP/eryllCeUfclSyvqYe0u+KYRoeAfnvhXWuoTdv7dFSrlUStlEStnkkYf+3VCvHw8dp2adGlTz9sLFpQwdu7cjISbZxiYhZhfdQjoB0L6LP3tTDijbk+nYvR0uri5U8/aiZp0a/HDw2L86/72gZe3HDp+kRu0aeNUwUMalDO27BZAUYzvsNCkmlc69ggBo29mX/SnmhRS8ahgsk1gbqntQq6436X8UPTdYcfDtl+F08g2hk28IsdEJvBjSBYCGTZ4lOyunUBI203iBnJzLNGzyLGBO5uzYZs7F+/i/wBsjXmNwv5Fcu+p4KGBx8s2X4XT07UVH317ERsfTQ9HeqEl9srOyCyUbTMYLXM65TKMm9QHoYaW9Vh1vi11gkC9nfjpLSbF6eQTd/fvR3b8fcdsS6dbLHMcNnqtn9rkyVDyfTNOfXM65QoPn6gHQrVcn4rYlARAfs4vgkM4ABId0Jm6LVrq3AAAgAElEQVR7UonpBu36HODb5Wvp7Nebzn692RGdQPdeZr81fK7oWL+cc4WGz5ljvXuvzuxU/O7j/wJDRwxgSP9RqsQ6aLNeXLl8LV38+tDFrw+x0Yl36fNEwOzzISMGMFQFn69aHkFXv7509evLzm2JBCs+bZhfRh3qvkxDpYwGh3RiZwmXxaIoTp+XBs8YHuH3vy9z/uIVbuTmEXMijTaPexay+/XPHLKu3aCBV+HpNLafuP+GlQP4tmrB5u1xSCk5cvQEFSqUx61qFVo2f47d+w5yKSubS1nZ7N53kJbN1Vnh9psv1xDUpidBbXoSszWeHr27Avl1es7t6/TeXYmNdlSn+5V4nQ7arBfzOXroBN51alDN22DWHhxIQswuG5uEmGRLG6FdF3++U7SXBlqtz63RcrxoVfvxwyfxrl3d8lwU2K0tu2Jtn4uSY1Pp1LMDAP6d2zh8LvKs5kHNut6knSvZ5yJrjh0+gXed6lTzNmvvEBxAUmyKjU1ibDJdlWe6wM5+7Es1z29csVIFFq/8kP/N/pzD+39UTbNZ90m861THS9HdPrgtiXa6k2JT6NLLvMxHQGdf9iu6K1SqwKKV81k0ewlHVNatow3Um3m8eIgDIoUQH0kpTUKIKkBFKeXtZoDfBQwVQqwAqgA+QCjmoeN3Q2Ug/7XAgDuw3wN8IoSoLaU8K4SoovTKjAGGCyGGSymlEKKRlPKQ9YFSytNCiDnAu0CfW5w7Gyh6ZnfHpACvKn5xA3yB1f/yO25Lbm4uM8fP54vwj3FydmLD6i38fOoXhr87hKOHT5AQk8y6VZuZ98l0tn+3nkt/ZzFmqLln0c+nfmF75E6iUsLJvZnLjHc/IC9PvZkYtK593oSFfBK2ECdnJzav2covp8/yRujrHD9ykl2xqWwKi2LGoslE7l7DpYtZvPfGNAAaNa/PgGH9uXnjJnkyjznvLeDiX5dU056wIxm/wFYkHoji6tVrjBtesFLd1kRzwhNg8thZzF88g3LlypIUl0riTvPNcfq893At68q36z8HzIugTBpb9AquxUn8jmT8Aluz68BWrl69xtjhky37ohPX0tG3FwATx85kweKZlCtXlsS4FBIU7eOnjKLO47XIy8vj/B/pTBg7QxXdSTtT8QloSey+jVy7co0JI9+37NsYv4ru/uZZPKaPm8vsj6dS7qGyJMftZpcyn9Syj1fw0bI59OjXlfRzRkYNcrzqeUmgVZ8DJOxIwTegFQn7N3Pt6jXGjZhm2ReVsIbOfr0BmBw6mw8WTS8U69PmvotrWVe+WfcZYF7sYNLYWSWqWcv1IkCi4vP4/ZFcu3qNd618viUhjC5+5mGoUxSfly1XlqS43STuND/wmH3uwgorn08eO7vQeUpCd5uAlsTti+Tq1WuMt9K9OWE1Xf36AjA1dA7zFk2jXLlyJMWnkqToDuzox5Q5oVR57FGWrf4fJ46dZmCvYSWuO1/7vfi8XUc/pswdR5XHHuWL1R9z/OhpXuv1dolqLuPkxPiAerwZsZc8Ken2bA0er1qRT5NP8rTnI/j+nzmpmb/Ij/3wuPOXrpCRfY3nvNXp0WhN6NS57D/0AxcvZtE2uD9vvf4yN2/eBCCkeyd8nm9K8p79BPUayEPlyjFjwmgAKleqyNABfeg9aCQAb7zW95aLBpUU5jrdh+Tvo811+rCCnnLbkiIIamOeoWni2Bks+GQm5cqVI2FnCgk7zcmU8VNHUffxWuTlSc7/kcZ7Y0q+TtdyvZibm8us9z5k6Rqz9o1hWzhz6izDxg3h2BGz9vWrNzN38TS27V3HpYtZjB1a8JvE7t9IhYrlcXF1wT+oDUNCRnDmdMknj0G79bnW40WL2nNzc/lg4n/5ePWHODs7sXlNNL+c/pWhoQM5ceQUu2JTiQzbyvSPJ7IhdTVZF7OZ+OY0ABo0e5YBw/px8+ZN8vIk8yYs5JKKz0W5ubnMmbCQz8I+wsnZmU1hUZw5dZa3xg3i2OGTJMWmsHF1FLMWT2HLnrVkXcxi3FDzs1PvgS/hXbs6Q0YPYMjoAQC82Xt0iY+cytc9b8JHfBq2ECdnZyLDovjl1FneHDeI44ruTaujmLl4MpF7wsm6mMX4oVMV3T2oUbs6g0cPYLBF9yj+vnCxxHU/yOTdeT+2+x5xP8xv4gghRI6UsoKD7SGYF/NxAm4Ab0sp99rbCyG+xjwke50wty4/wDzXpgRmSinDhRC+wFgpZWflmFrKMfUcfIdlnxDieWAFkAnEAy9LKWsJIQYATaSUw5TjozCvnJ4ohAjCPJemE2CSUgYKIR4C/gu8gLl35K9Sys4OdD0E/Ix5KLhnEeeugjkx6gLMAR7K12J9Hda+FUI4AZ9iTuyeBsoCC6WUO2712zzl3uz+DJoHlIec1ZuDpbj5+3p2aUu4K/JUnrOvOHnIuWxpS7hrrub+c3uj+xBn85pzmqSskzZXgLyed7O0Jdw1TqUx52AxkHefthfvhKPz/Etbwl1TpttbpS3hrqj7RKH1KzVD+TIP3d7oPkSrdQvAtVztLuLh6qS1fkHap0KZOx2QeH+h6baLhhNghzJStSu+mFnp1b9EGnP901aq7uP7NpGpow5CiApSyhwhxGPAPswLKd2yr7yeyFQXPZGpPnois3TQE5nqoycy1UeryQY9kVk66IlM9dETmeqjJzJ1/g16IlN99ETmg8GDlMjUa16dKCHEI4ArMON2SUwdHR0dHR0dHR0dHR0dHR0dHe1QWgvzlAR6IvP/c6SUvqWtQUdHR0dHR0dHR0dHR0dHR0dH53boiUwdHR0dHR0dHR0dHR0dHR0dHZ0HFHWX1yxZ9ESmjo6Ojo6Ojo6Ojo6Ojo6Ojo7OA4p2ZzsvjJ7I1PnXVHEptJi8Jrh483JpS7gr/snT7gToLhpdSMTFSbuLt2h5QQ4318qlLeGuyJXafb+Zk3uttCXcFZVdHi5tCXfNFY0uauXuWrG0Jdw1j4/dVtoS7hrn0JjSlnBXnDkdWdoS7hrvxzuXtoS7wrPco6Ut4a7Jc9Ju20Vf7Ed9/rqeU9oS7opHXcqXtoS7RqvtRZ0HF73m1dHR0dHR0dHR0dHR0dHR0dHReUB5kBb7cSptATo6Ojo6Ojo6Ojo6Ojo6Ojo6Ojo6t0Pvkamjo6Ojo6Ojo6Ojo6Ojo6Ojo/OAot3JsAqjJzJ1dHR0dHR0dHR0dHR0dHR0dHQeUB6kRKY+tFxHFZr7NiVs1wrCU76l/9t9Cu13cXXh/c8mE57yLUu3fIJndQ8APKt7EP/zNr6OXcrXsUsJnTtKbem08mtBVOpatu1dx6DhrxTa7+LqwodLZ7Jt7zrCtn2JVw0DAJUfrcRXGz5l/y8JTJw9Vm3ZgLa1T5o9lh37NrI5MYyn6z/p0OaZ+v9hS9IaduzbyCQrnR26tmVrcjgnjfuo1+AptSQD2vV5K78WRO+OYPt364vUvXDpLLZ/t54125ZbdAMMHvEq279bT/TuCFr6tVBTNgDP+zVjffIqNu4O49Vh/Qrtd3F1Yfbn09i4O4yvty7BUN0TgGcaPsWqHctZtWM5q3d+hW9Qa1V1v+DXnI0pYUTuCee1Yf0d6p675H0i94TzTfRSDDXMupv7NGVVzJesTfiGVTFf0rRlY1V15zN5dig7921iS+Ianq7/H4c2z9T/D1FJ4ezct4nJs0Mt2zt0DSA6eS2njPtVL6Mv+DVnQ/JqInevYUBRfv98OpG717Bi61KbeAnb8RVhO75izc6v8QvyUVU3wMRZY4j5bgORiat5+tmi68XNiWHEfLeBibPGWLZXfqQSX0YsZvve9XwZsZhKldVbvEfLbYD3575Hyvfb2JGygXr1Hcfqsw2eZmfqRlK+38b7c98rtH/osAGc//sYj1Z5pKTl2jB9znh2HdhKTPL6W2qPTdnArgNbmT5nvGX7mAnDiElez7akCFauX4KHp5sqmifNXohPp94E93/D4X4pJbM/+oygXgPp/sqbHD/1s2VfZPQOOoa8TseQ14mM3qGKXntmzJvA7oPbiUvdyLNF1G31GzxNfOomdh/czox5Eyzbx4x/m4PHE9iRvIEdyRvwD1SvjtHq/UjLbZcX/JoTmRLGlj1rGTjs5UL7XVxd+GDJ+2zZs5aV0cvwUnzewqcpYTHLWZfwLWExy2nW8jld979gyuxQ4vdFsjUpnGeKaLvUa/AU0bvCid8XyRSrtsv4aaOI3bOerUnhfLbiQypWUm8BXK22dUG7bRed+5u7TmQKIXKFEIeFEEeFEFuEELdtnQkhbrnEmBDiESHEW1afvYQQ6+5WYxHnSBRCNHGwvYkQ4uPbHOskhPhYueYfhRD7hRC1b3PMKCHEw1afo2/lKyFEayHEMcW3D93JNVkdGyyEeNrq8/tCiIB/8x0lgZOTE2NmjWRM//H083uNgGB/av1fTRubzn2CyL6UTUirlwlfto63Jg6x7Dv/WxoD2g1hQLshzB//X9W1T5wbyht9R9G1dW86dm9H3Sdsf/IefbuSdTGboBYv8c2SNbwz+W0Arv9znUVzlzB/2i3DqsTQsvY2AS2pVacGgc26M3nMLKZ/UPjBEGD6/PeYPGYWgc26U6tODXzavgDATyfOMGzAOPbvOaSmbM363MnJicnzxjGkz0i6tAqh04vtC+l+qV9XLl3KpkPzHnyzJIyxk4cBUPeJ2nTs3o4urXszuPdIpswbh5OTeu/InJyceHf2O4zoN5aebV6mfXAAtZ+oZWPTrU8nsi9l0/2FPqxeupbhk8wPyD+f+oVXOgymX+BAhvcdy4QPQnF2VmfFeicnJ8bPGcOwvmPo4dOPDt0DqGOnO7hvZ7IvZtPt+RBWLQln5CTz7fHiXxcZ9cq79PJ7hSkjZzJz8RRVNFvTJqAlNevUIKBZMJPHzOT9W5TRSWNmEtAsmJo2ZfRn3h4Qyv49B9WUbYmX4f3G0qNNfzo4iJfgPp3JupRNtxd6s2ppOCMnvQnAmVO/0L/DIPoEvsawvmOYqGK8APi0fYGadbxp3/xFpoyZzdQPxju0m/rBeKaMnU375i9Ss443rf3NPh884lX27tpPhxY92LtrP4NHvKqKbi23AfwDW1O7bk1aPRfEu6OmMWeB47I2Z8EU3h01jVbPBVG7bk38AlpZ9nlV88TH9wXO/ZGmlmwA/AJaU6tuTXyadGL86OnMWjDJod2sDycxfvR0fJp0olbdmvgq2pcs+or2rXsQ1KYncTFJjAx1nFgsboI7BvL5wplF7k/es5/fz6URHf4l08aNYMaHiwG4lJXNZ1+tJmzZfwlb9l8++2o1l7KyVdGcj3+gD3Xq1OSFxh0IHTmVuQumOrSbu3AKoaOm8kLjDtSpUxP/gILEwtJPvyGw9YsEtn6R+B27VNGt1fuR1tsuE+aM5a2+Y+ju09ehz7v37ULWxWy6PN+LlUvCGWXx+SVGvDKOl/xeZvLImcxS2eda1J2Pb0BLatXxxr9ZNya+M5P35ztuu7w//z0mvjML/2bdqFXHmzZK2yUlcS9BrXrRqU0IZ8/8zpujBqqiW6ttXdBu2+VBRYqS+SsN7qXGviqlbCilrAf8BbxdDHoeASyJTCllmpTypWL43tsipTwgpRxxG7MQwAuoL6V8FugOXLzNMaMASyJTStlRSnmrY/oBHyq+vXoH0q0JBiyJTCnlFCnlzn/5HcXOU43+w7lfz5P2ezo3b9wkLjKe1u1fsLFp3a4l0RGxACRuTeK5VqXTw8ieZxs/zR9nz3HutzRu3LhJ9KYd+HWwfUPu38GHyLVbAYjdEk+LVk0BuHrlGgf3HeH6P9dV1w3a1t62Qxs2hkcDcOT7o1SsXBE3j8dsbNw8HqNCxfIcPvAjABvDowkI8gXgzE+/cvbMb6pqBu36vH7jZ/jdWvfGWPwL6W5DZLhZd8yWeFq0bqps9yF6Yyw3rt/g/O9p/H72HPUbP6Oa9mcaPcUfv57nvFK/xEbG0aZ9KxubNh1aE7V2OwBxUYk0a23uBfDP1X/Izc0FoGxZV6SUqumu1+gp/jh7jvO/p3Hzxk1iNsXh2972Lblv+9ZsWWsuBzujEmnWyqz71NGfyDReAODMybO4lnXFxdVFNe0AAR3asEmJh8PfH6Vi5Qq4eVS1sXHzqEqFihUsZXRT+FYCS7mM1mv0FOd+tfJ75E587eLFt0MrotZuA8zx0lSJl2tW8eKqcrwAtA1qY6k7jnx/lEqVK+LmblcvutvWi5FrtxLQsY35+A5t2BQeBcCm8ChLfVnSaLkN0L6jP+vWbAbg4IEfqFy5Iu52ce7uUZWKFcvz/f4jAKxbs5kOndpa9k+b9S6zpi1QPV7adfRjvaL90IEfqFTJsfYKFStwUNG+fs1m2nf0ByAn+7LF7uGHH1JNf5OGz1K5UtE9bhJS9tK1Q1uEEDSo9xTZ2TlkXviL1O++5/mmjahcqSKVK1Xk+aaNSP3ue1U059Ohoz8RayIBc7xUKjJeKljiJWJNpE28lAZavR9pue1Sr9HTNj7fvmlnIZ/7tW/NZuVetCMqgWatzP1wTh49bfH5zyd/UdXnWtWdT0CQLxvXmu+Dh7//0Xwfddh2Kc+hAz8AsHFtFIEd/QBzIjO/HXD4wI94ermrolurbV3QbttF5/6nuF497QGq5X8QQoQqvRV/EEJMtzcWQlQQQsQJIQ4qPRu7KbvmAnWV3ojzhRC1hBBHlWPKCSG+UuwPCSH8lO0DhBAbhBDbhRA/CSE+ULY7CyG+tuo9OdpKQk8hxD4hxGkhRGvF3lcIEaX8f5oQ4lshRLzynYOV4wxAupQyD0BKeU5K+bdyzGdCiANKb8rpyrYRmBOfCUKIBGXbr0KIqkKI8kKIrUKII4rGECHEIKAXMEUIseoWfkII8Yri3yOK1heArsB8xX91let/SbFvq/jtRyHEciFEWSs9063O4biP/T3g5lkVU5rJ8tmUfgE3uyFK1ja5uXlczrpM5UcrmZ3u7clXMUtYvO4jGjR7trjl3RIPT3fS04yWz8Y0U6HhVe4GNzLO52vPJTs7h0eqVFZVpyM0rd3gRkZahuWzMc2Ih6dtY8HD050M6+tLN+JhUGfoW1Fo1efunm5knLf2pamQLz083UhXbKx1m38r22t2V2kIIpi1G89b1y+ZuHvaPTh6VsWYVuDznKzLVFZ8/kyjpwlP/IY1CV8z590PLY29EtdtcLNoArPP3QwOYsVad/blQrES0NmXU0dPc+P6jZIXbYWHwTbWMxzEuoenbWxkpBvxMKjT6C8KN8+C8gf58WJ/P7Lze1aB3+s1epqIxG9Zm7CC2SrGCyhl0N7ndv70MLiTkW6ytVGu7zG3KmSa/gQg0/QnVao+qoJqbbcBPA3upJ0vuBelpxnxNHjY2XjY/C7paRl4Kr9LYJAf6elGjh89pY5gG13upFtpz0gzWnRZ29iUUTub0InD2fvjDoJ7dmLBnE9KXvQdYMz8E0/3gjrew70qxswLGDMv4OleEFcebubtauIoXgx28WIweJBmEy+2Ph84pC9xqRtZuHgmlStXKnnRaPd+pOm2i935TemZhbRb2xTtcz9OqulzjerOx8PgTtp52/uop51+T6tYB0h3cK8FeKlfN5LidpecWCu02tYF7bZdHlTySuivNLjnRKYQwhloC2xWPrcD/g9oBjQEnhNC2E/ycg3oLqVsDPgBC4QQAhgPnFF6I4baHfM2gNITsg+wQghRTtnXEHNvyWeBECFEDWVbNSllPeWYr6y+q4yUshnm3pKOx31AfaAT8DzmxKIXsBbooiQKFwghGlnZT5RSNlGOayOEqC+l/BhIA/yklH52398BSJNSNlB6tW6XUn6h+DFUStmvKD8JIZ4BJgL+UsoGwEgp5W6rYxtKKc/kn0jx09dAiOKLMsCbVlouKOf4DCj2yfnMP60t9m+DHNoAf5r+4sVmfXit/VAWTf+UqZ9M5OEKDxeyLTEcdJWW2Gl3YKT22y6HaFj7XcdMaWvXqM8d+/L2Nsiiyq6K1+NIlv3pHWo3Gx07dJwQ31d4JWgIrw3vj2tZ1+LX6IhbaCowuXWs1HmyNiMmvcXM0PnFLu92aLWM3qvuo4eO09P3ZV4OGqxuvJiFFanr1jYlJejO0HIb4O7jBco9VI4R7wzhwzmLS0zfLbmTWLjN9c2ftYgWzwayKWIrAwYXntu0NHBUhwghHMa5w/tWCXJHdd4t7pkrvlxDi4btCWj1IqaMTKbOGlciOguh0fuRltsujl1u7/Nb29R9sjajJr3FjNAPiltekWhVdz53EOp3dK99a/Tr5N68SWREdDGquwVabesWoUsLbRed+597SWQ+JIQ4DPwJVAHyZ9Vup/wdAg4C/8Gc2LRGALOFED8AOzH35vTg1rQCvgWQUp4EfgOeUPbFSSkvSSmvAceBmsAvQB0hxCIhRAcgy+q7Nij/fg/UKuJ8kVLKq1LKC0AC0ExKeQ54EngPc/I5TgiRPx6klxDioHLdz2A1xLsIfgQChBDzhBCtpZSXHNgU5Sd/YJ2iDSnlX7c515PAWSnlaeXzCsA6uXxbfwghhig9Tg9kXP538zyZ0jNxt+p6726oygXjhSJtnJ2dKF+pPFl/Z3Hj+g2y/jb/dKd+/Inzv6bhXaf6vzr/vWBMN2HwKghNDy93TBkXCtl4VsvX7kzFihW49HcWpY3WtPcb2JPIhFVEJqzClJGJp5enZZ+HlwcmY6aNfUa6EU/r6zN4FLo+tdGaz201WfvSHVOGvb9NGBSbfN0X/75kfpttd82ZKv4OpvRMPKpZ1y9ulqFLNjZeBT6vUKl8IZ//+tNvXL1yjbr/ueW0x8WGKc1k0QRmn9v7zZhmsgxbcnZ2pkLFAt3uBjcWLp/N5OEzOPfbeVU09xvYk80Jq9mcsBpjRqZNrHt6uWOy83tGum1seBo8CsWV2pisyh8UFS92fncQL2dVipe+A3uyMX4VG+NXYcq4UNjndv402vXuMv8uZps/M/+yDOdyc3+Mvy78XaLa89FaG+DVQX2I3bWe2F3ryUjPxKtawb3I4OWBMcNkY5+elmHzuxi8PDFmmKhVuwbeNauxI3kDe4/EYvDyICZpHW7utr1oipNXXu/NtqQItiVFYMowYbDS7ulAe0aa7X3UbFO4jG5aF01Ql1Kfch0AT/eqZJgK4sdouoB71ceU7QXajZnm7SXNgEF9LIvzGDNMheIlw0G8eNnEiwfGdLPuC5l/kpeXh5SSld9E0KixOj2QtXg/Am23XYxpmTbndze4FW4vWtk48vlHy+cwafj76vpcg7r7D+zFloQwtiSEYcrIxKua7X3Uvs7LsIp1AIPdvfbFkM74tWvN6DcczztcEmitrfsgtF0eVPQemWauSikbYk4aulIwR6YA5ii9AhtKKR+XUn5pd2w/wA14TvkOI1COW3Or16r/WP0/F3OPy7+BBkCiou0LB/a5mHsnOsL+PYAEkFL+I6XcpvQYnQ0EC/OCP2OBtlLK+sDW212PklR8DnNCc44QwtGMx0X5STjQdytu90r6tv6QUi6VUjaRUjbxLO/1L04NJw+fpHrtahhqeFLGpQxtu/mTErvHxiYldjcde7YDwLdTG75PNS/S8kiVypbJt728DdSoXZ3zv6f/q/PfC0cPncC7Tg2qeRtwcSlDx+BAEmJsJ19PiEmmW69OALTr4s93KQdU03crtKZ91fIIuvn1o5tfP3ZuS6R7SEcAGjxXj5ysHDKNf9rYZxr/5HLOZRo8Vw+A7iEdiduepLpua7Tm83x+PHScmnVqUM3by6y7ezsSYpJtbBJidtEtxKy7fRd/9iq6E2KS6di9HS6uLlTz9qJmnRr8cPCYatqPHz5JjdrV8aphoIxLGdp1a8uumBQbm10xKXTu1QGAtp192Z9iXmDGq4bBMuG5Z3UPatb1Ju2PDNTg2OGTeNepjpe3WXf74LYkxtrqTopNoUsvczkI6OzL/lTzfG8VKlVg0cr5LJq9hCP7f1RFL5jLaFe/vnT168vObYkEK/HQ8Ll6ZGflFGpUZxovcDnnMg2VMhoc0omdpVxGjx0+SY3aNSzx0r5bAEkxqTY2STGpdO4VBBQdL4bqHtSq6016CcfL6uURdPfvR3f/fsRtS7TUHQ3yfW6yqxdNf3I554qlXuzWqxNx28w+j4/ZRXBIZwCCQzqrVl9qrQ2w4osw2vn0oJ1PD2Ki43ipd1cAGjepT1ZWTqGEvcl4gZycKzRuUh+Al3p3JSY6npPHf6LBEz60aNCOFg3akZ5mpH2bl8g0lVyy5Jsv1xDUpidBbXoSszWeHor2Rk3qk12E9ss5l2mkaO/Ruyux0QkA1KrjbbELDPLjzE9nS0z3v8G3VQs2b49DSsmRoyeoUKE8blWr0LL5c+zed5BLWdlcyspm976DtGxe8qsif/1FmGVxnm1b4+jZ2zwLVOMm9cnOyi4iXi5b4qVn725sj44HsJlPs2PnAE6e+KnE9YM270eg7bbLscMn8K5TnWqKzzsEB5Bk5/PE2GS6KveiwM5+7FN8XrFSBRav/JD/zf6cwyr7XIu6Vy5fSxe/PnTx60NsdCLde5nvgw2fe/YWbZcrNHzO/CKhe6/O7NyWCICP/wsMGTGAof1Hce3qNdWuQWtt3Qeh7fKgIkvorzQoKol3x0gpLylzQUYKIT4DYoAZQohVUsocIUQ14IaU0vqVZGXAJKW8ocx1mb98ZTZQ1AzfuzAn9uKFEE8A3sApwOGM8EKIqsB1KeV6IcQZzEOr/w3dhBBzgPKALzBeCNEYyJBSpgkhnDAPI/8BqARcBi4JITyAIMwJVOtrsqkllaHqf0kpVwrzau4DHGgoyk9xwEYhxEdSyj+FEFWUXplF+e8kUEsI8biU8mfgZUC1WiA3N4+PJi1i4ep5ODs5ExW+jbOnf2XQ2AGcPHKalB27iVoTzeSPJxCe8i1ZF7OZ+tYMABq2qM+gsa9xMzeXvNw85r/3EdkX1VuFMjc3l4u3Wp8AACAASURBVFnvfcjSNR/j5OzExrAtnDl1lmHjhnDsyAkSYpJZv3ozcxdPY9vedVy6mMXYoQVv6GL3b6RCxfK4uLrgH9SGISEjOHNanYcBLWtP3JFKm4CW7Ny3iatXr/HeiIKpdiMTVtHNrx8AU0PnMnfRNMqVK8uu+N0k7TQnJAI7+jJ5TihVHnuUpav/y4ljp3m91/AS161Vn+fm5jJz/Hy+CDfr3rB6Cz+f+oXh7w7h6GGz7nWrNjPvk+ls/249l/7OYszQiYB5NcTtkTuJSgkn92YuM979gLw89d7N5ebmMn/CRywKW4CzsxOb12zll9O/MjT0dU4cOcmu2FQiw7by/qJJbNwdRtbFLCa8MQ2Ahs3r8+qwfty8cRMpJXPfW8ilvxx1ji8Z3fMmfMSnYQtxcnYmMiyKX06d5c1xgzh++CRJsSlsWh3FzMWTidwTTtbFLMYPNc+E0ntgD2rUrs7g0QMYPHoAAG/2HsXfF2639lzxkbgjhTYBLYnbF8nVq9cYP2KaZd/mhNV09esLwNTQOcxbNI1y5cqRFJ9qVUb9mKKU0WWr/8eJY6cZ2GtYies2+30hn4QtxMkSL2d5I/R1jivxsiksihmLJhO5ew2XLmbxnhIvjZrXZ8Cw/ty8cZM8mcec9xZwUaV4AUjamYpPQEti923k2pVrTBj5vmXfxvhVdPc314vTx81l9sdTKfdQWZLjdrNLmcNr2ccr+GjZHHr060r6OSOjBjleObS40XIbIC52F/6BPqQe3MbVq9d4522r+nrXetr59ADgvTHv89GnsyhXriwJO1OI35Fc1FeqRvyOZPwCfUj+PpqrV68xdliB9m1JEQS16QnAxLEzWPDJTMqVK0fCzhQSdpq1j586irqP1yIvT3L+jzTeGzNDFd2hU+ey/9APXLyYRdvg/rz1+svcvHkTgJDunfB5vinJe/YT1GsgD5Urx4wJ5inwK1eqyNABfeg9aCQAb7zW95aLBpUEcbG7aBvow55D27l65Rqj355o2bcjeQOBrV8EYPw77/PfT2dT7qGyxO9ItqxOPvn9sTxT7z9IJH/8fp5xo6apolur9yOtt13mTFjIZ2Ef4eTszKawKM6cOstb4wZxTPH5xtVRzFo8hS171pJ1MYtxQ819XnoPfAnv2tUZMnoAQyw+H61KTzWt6s4ncUcKvgGtiN8fybWr13jXqu2yJSGMLn7mKTSmhM7mg0XTKVuuLElxu0lU2i7T5r6La1kXVqz7DDAvGDR57OwS163Vti5ot+2ic/8j7na+KiFEjpSygtXnLcBaKeW3QoiRwCBlVw7QX0p5Jv8YJcm4BXABDgMtgSAp5a9CiNWYE4TbgE+AKCllPWWex88x92K8CbwjpUwQQgwAmkgphyk6ooAPgb8xz4uZ3+v0PSnlNiFEIjBWSnlA0XFASllLCOGrbO8shJiGeZGeupgTph9IKZcpQ9RnAWWV79wHvCWlvCaE+BpojnlI+z/AZinl10KI4Zh7hKZLKf2EEL8CTZTrmI+5N+4N4E1F09fKNa+7jZ9eBUIx96I8JKUcIIRoCSxTzv8SMNnqu9oqfikD7FfO90++HinlBSFEE8wrpvve6rdvWc1fk7NWXLx5+fZGOsXKjTz1JpMuTlycnEtbwl2Tp+FJZco7l7290X1IriytQRX3Tk6uej0KipOKZR4qbQl3zZXcf25vdB/ymIu6SaHi5Ncrxtsb3ac4i+Jal1NdzpyOLG0Jd433451LW8Jd4VlOu4tgXMtTd9GX4sTV6Z77Ben8S3JuarPt8qhL+dKWcNdotb0IcNK0X90Jk+9j/ufdv0QeFEf+vlJ1H991IvNBRklk5kgpPyxtLfcjeiJT507RE5nqoycy1UdPZKqPnshUHz2RWTroiUz10ROZ6qMnMnX+DXoiU3202l4EPZFpzYOUyNRrXh0dHR0dHR0dHR0dHR0dHR0dnQcU7Xa9KIyeyHSAlHJaaWvQ0dHR0dHR0dHR0dHR0dHR0dG5Vx6kRKY2x6vo6Ojo6Ojo6Ojo6Ojo6Ojo6Ojo/H+F3iNTR0dHR0dHR0dHR0dHR0dHR0fnAUW7KykURk9k6vxrrsubpS3hrijvXK60JdwVTmh3fuKr4nppS7grrudpM8YBHtHwROLXcrUZL7kaHqhR1smltCXcFf9oeGGIKxpdpOBhjS7GBfCIa4XSlnDXaHUBN60umAPw+89RpS3hrmj0TN/SlnDXaHVRK4CbUpsLW2rZ5+5lK5e2hLvisoYXzHnIybW0Jejo2KAnMnV0dHR0dHR0dHR0dHR0dHR0dB5Q8rTbP6oQeiJTR0dHR0dHR0dHR0dHR0dHR0fnAUW7Y8gKo90+5To6Ojo6Ojo6Ojo6Ojo6Ojo6Ojr/36D3yNTR0dHR0dHR0dHR0dHR0dHR0XlA0eas247Re2TqqMLzvs1Yl7ySDamreXVYv0L7XVxdmP35NDakruarqM8xVPe02e9RzZ2kn7bT/43eakm20MK3GRHJ37I+dRWvDCs8kbqLqwuzPp/K+tRVLI/6zKH2xJ+20e+NELUkW2jh24zw5G+ISF3Fy0Von/n5FCJSV/Fl1KcOtcf/tI2+Kmt/wa85kSlhbNmzloHDXi6038XVhQ+WvM+WPWtZGb0Mrxpm3S18mhIWs5x1Cd8SFrOcZi2fU1U3QCu/FkTvjmD7d+sZNPyVQvtdXF1YuHQW279bz5pty/GqYbDsGzziVbZ/t57o3RG09Guhpmxa+DZlza4VRKSs5OW3+xTa7+LqwozPphCRspIvtnyKZ3UPADyre5D483ZWxC5jRewyxs0drapuMMfLxpQwIveE89qw/oX2u7i6MHfJ+0TuCeeb6KUYlHhp7tOUVTFfsjbhG1bFfEnTlo1V1d3SrwWbU9YQtSfiFnE+g6g9EayK/sIS55UfrcQX6xez90wc780eo6rmfFr6tWBLajjReyN4fbhj7R8unUn03ghWb/vSEueVH63E8g2fsO+XeCaUkvZWfi2ISl3Ltr3riiyjHy6dyba96wiz0/7Vhk/Z/0sCE2ePVVs2ANPnjGfXga3EJK+nXv2nHNo82+BpYlM2sOvAVqbPGW/ZPmbCMGKS17MtKYKV65fg4emmlmxe8GvOhuTVRO5ew4Ciyujn04ncvYYVW5da7kXPNHyKsB1fEbbjK9bs/Bq/IB/VNIO2Y0Wr96J8ZsybwO6D24lL3cizDRzHev0GTxOfuondB7czY94Ey/Yx49/m4PEEdiRvYEfyBvwD1YmbSbMX4tOpN8H933C4X0rJ7I8+I6jXQLq/8ibHT/1s2RcZvYOOIa/TMeR1IqN3qKLXGq3W6VrVDXdfvwAMGvEq2/auIyp1LS19m6sp+67bLi18mrIm5ivWJ6xkTcxXpdJG13JbV6ttRq220XXufzSfyBRCTBRCHBNC/CCEOCyEaC6EGCWEePguv2+aEKJQq1OYmSSE+EkIcVoIkSCEeOYOvm+AEMLL6vMXQoini1NbcSGE+FUIUbW4v9fJyYlxs0czsl8ovXxfoV23ttT+v5o2Nt36dCLrYjYvtuzL6mVrGT7JthH4zrTh7I7/rril3Raz9lGM7DeOEN9Xae9Ae9c+nci+mE2Plv0IWxbBsElDbfaPnjaMPfH71JQNmLWPnT2S0f3epY/vq7Tr5k+tQto7knUxh54t+xG2bB1vTxpis3/UtLfZo7LfnZycmDBnLG/1HUN3n7506B5AnSdq2dh079uFrIvZdHm+FyuXhDNq0lsAXPzrEiNeGcdLfi8zeeRMZi2eorr2yfPGMaTPSLq0CqHTi+2p+0RtG5uX+nXl0qVsOjTvwTdLwhg7eRgAdZ+oTcfu7ejSujeDe49kyrxxODmpU0U7OTkxZtZI3uk/nj5+AwgMblsoVrr06Uj2pWx6turPmmURvD2xIM7P/ZbGq+0G82q7wXww/iNVNFtrHz9nDMP6jqGHTz+H8RLctzPZF7Pp9nwIq5aEM9ISLxcZ9cq79PJ7hSkjZzJTxXgxx/kY3uz7DsE+fQjqHlhI94tKnHd+viffLlnDqElvA3D9n+t8Mm8pC6YvVk2vNU5OTkyaO5Y3+46ma+s+dOzezoH2rmRdzKJji558uySMdyYXaF80dykfTltUCsrN2ifODeWNvqPo2ro3Hbu3K1RGe/TtStbFbIJavMQ3S9bYaV/C/Gkfl4Z0/AJaU6tuTXyadGL86OnMWjDJod2sDycxfvR0fJp0olbdmvgGtAJgyaKvaN+6B0FtehIXk8TIUMfJluLGycmJd2e/w/B+Y+nRpj8dggOobV9G+3Qm61I23V7ozaql4Yyc9CYAZ079Qv8Og+gT+BrD+o5h4gehODs7q6Zbq7Gi1XtRPv6BPtSpU5MXGncgdORU5i6Y6tBu7sIphI6ayguNO1CnTk38A1pb9i399BsCW79IYOsXid+xSxXdwR0D+XzhzCL3J+/Zz+/n0ogO/5Jp40Yw40NzHX4pK5vPvlpN2LL/Erbsv3z21WouZWWrohm0W6drVTfcW/1S94nadAwOpKtPH4b2GckklduLd9t2ufjXJYa/EkoPv/5MGjmDWYsdl+uS1K7ltq4W24xabaM/yOQhS+SvNNB0IlMI8TzQGWgspawPBAB/AKOAu0pk3oK3gReABlLKJ4A5wGYhRLnbHDcAsCQypZSDpJTHi1nbfc0zjZ7ij1/Pc/73dG7euMmOyDjatG9lY+PTvhVbI7YDEB+VRNNWBW9d2nRoxfnf0/jl9K9qygbM2s/9ep40RXtsZDw+dtrbtG/J1ogY4Fbaz6qqG+DpRv+x0b4jMh6f9i1tbFq3b0m04veEqCSatCp4O+rToRXnf0/nrMp+r9foaf44e47zv6dx88ZNtm/aiW/71jY2fu1bs3ntNgB2RCXQrFUTAE4ePU2m8QIAP5/8Bdeyrri4uqimvX7jZ/j97DnO/ZbGjRs3id4Yi38H254g/h3aEBm+FYCYLfG0aN1U2e5D9MZYbly/wfnf0/j97DnqN77tu5JiwRwraZZY2ekoVtq1JFqJ84StSTRpdX+8Ga3X6CmbeInZFFcoXnzbt2bL2mgAdkYl0kyJ81NHf7LEy5mTZ1WNl3qNnuZ3uzj3a28bK77tW7NZ0b0jKoHmSpxfvXKNQ/t+4J9//lFFqz3PNn7aEuc3b9xk26YdDuK8NZGK9tgt9tqP8M8/11XXDWbtf1iX0U078Cuk3YfIteYyGrslnhatzGX06pVrHNx3hOulpL1dRz/Wr9kMwKEDP1CpUkXcPWzfPbp7VKVCxQoc3H8EgPVrNtO+oz8AOdmXLXYPP/wQUqrT8KzX6CnO/WpVRiN34mt3H/Xt0IoopU6Pi0qkaWtzGb129R9yc3MBcC3rqppm0HasaPVelE+Hjv5ErIkE4OCBH6hU2XGsV6xYge+VWI9YE0mHTm1V1WlPk4bPUrlSxSL3J6TspWuHtgghaFDvKbKzc8i88Bep333P800bUblSRSpXqsjzTRuR+t33qunWap2uVd1wb/WLXwcfojftUMpoOn+cPcezje+qj8y/5l7aLvZt9LIqt9G13dbVZptRq210HW2g6UQmYAAuSCn/AZBSXgBewpw4TBBCJAAIIfoIIX4UQhwVQszLP1gI0UEIcVAIcUQIEWf/5UKIwUKIbUKIh4B3geFSyivKuWKB3UA/xTZHCLFA+b44IYSbEOIloAmwSukt+pAQIlEI0eQ2unKEELMUXXuFEB63coIQor8QYp9yjiVCCGchxJtCiA+sbAYIIRYVZf/vXX/nuHlWxZhmsnw2pmfiZrAd0uZuZZObm0tO1mUqV6lMuYfK8cpbfVm24OuSlFgk9tpN6Zm4GaoWaeNI+xcLVqiquUCXG6a0TMtnkwO/u3m6YVRszNpzLNpffqsPX5aCdneDGxlpRstnU3omHvbxYmWTm5tLTvZlHqlS2cYmoLMfJ4+e5sb1GyUvOl+XpxsZ5wu0G9NNhbR7eLqRfr5Ae3Z2Do9UqYyH3XUb00y4qzT0082zKib7OPe8VZznmWPl0UoAeHl7siJmKZ+u+y8Nmj2riuZ83A1udvWLqXD9YnAjw7qMOowXX06pGC8eDnS728eKwQ2jTZznFNJdGrh7FvgTHMequ6GgLNxP2j083Um3K2f2Q6zN2gviJfs+0e5pcCf9fIblc0aaEU+DeyEb63rE3iZ04nD2/riD4J6dWDDnk5IXjfk+k+9PMNcv9vHi5mlXRrMKymi9Rk8TkfgtaxNWMPvdDy2JzZJGy7Gi1XtRPp4Gd9KsYj09zYjBYNsUNhg8SLPSmW4X6wOH9CUudSMLF8+kcuVKJS/6DjBm/omne8G91cO9KsbMCxgzL+DpXuBjDzfzdrXQap2uVd1wb/WLh135zkg34eFpey8oMd3F1HYJLIU2upbbulptM2q1jf4gk1dCf6WB1hOZsUANZaj3p0KINlLKj4E0wE9K6acM654H+AMNgaZCiGAhhBuwDOghpWwA9LT+YiHEMKALEAy4AOWllGfszn8AyH9NXR44KKVsDCQBU6WU6xSbflLKhlLKq1bf71CX1XftVXTtAgYX5QAhxFNACNBSStkQyMWcXF0HvGhlGgKE38K+xBBCFNpm36vCkQ1SMjR0IGHLIrh65Wrh/SrgWNed2EiGhL5WytodbCzkd0cmksGhr7GmlLQXpenf2NR9sjajJr3FjNAPChuWII5j/fY2yCKOVamr/t2WUQn8afqL4Ga9ebX9EP43/VOmfzKJhysUd4f4W1BE+bM1ufX11XmyNiMmvcXM0PnFLq9I7sDnd2RTChQVCzY23J/aHcgqVM7uX+23r19uFzPzZy2ixbOBbIrYyoDBhecHKwnuun5RbI4eOk5P35d5OWgwrw3vj2tZ15IRao+GY0Wr96J87iRmHMa6onPFl2to0bA9Aa1exJSRydRZ40pE57/FUWwIIQqXY4r4fUoIrdbpWtUN3FP9ckflo6QohrZLfhv9/dB5hexKkgetrauJNqNW2+gPMLKE/koDTScypZQ5wHPAECATc6JugJ1ZUyBRSpkppbwJrAJ8gBbALinlWeW7/rI65mUgCHOS81b9sAUFv10eEK78fyXQyuERt9cFcB2IUv7/PVDrFt/TFrMP9gshDiuf60gpM4FfhBAthBCPAU8CqUXZ30YrQoghQogDQogDmVfSb2dugyk9Ew+vgjeFHgY3LmTYvmk2Wtk4OztToVJ5Lv2dxTONnmL4pDeI/C6cPoNeYsDw/vR87UXUwl67u8GNTDvtpiK012v0NMMmDWXTd2vobdHeXVXt7l4Fb72K1u5mpb0CWYrfh016g43frSFk0Eu8OrwfL6mk3ZiWiadXQc8Ld4MbJvt4sbJxdnamQkWzz/PtP1o+h0nD3+fcb+dV0WzRlW7Cs1qBdg+DO6aMTBubjHQThmoF2itWrMDFvy+RkWayuW4PL/dCv1dJYY4V2zi/YPyzkE1BnDtZYuXG9RtkKb4/9eNpzv+ahned6qroBjClmezql8J+M6aZ8LQuo3bxsnD5bCYPn6FqvBjvULeHTZxXsOguTYzpBf6E/FjNLGxT7f7UbrArZ4Xql3QTntUK4qViKWp/5fXebEuKYFtSBKYME4ZqBQuyeXp5YMww2dhnpBlt6hGzje1vA7BpXTRBXQJKTrgVJit/gnIvMtrfi+zKaKXyhXx+9qffuHrlGnX/YzuPXEmhtVixRov3ogGD+lgW5zFmmPCyinWDlwcZdrGenpaBl5VOg5cHxnTzNV7I/JO8vDyklKz8JoJGjdXtPVUUnu5VyTAV+NJouoB71ceU7QW/jzHTvF0ttFqna1U33Fv9kmFXvj0N7piMhev5EtF9j20XD4MbHy2fy0SV21yg7bauVtuMWm2j62gDTScyAaSUuVLKRCnlVGAY0MPOpKhXmtZJSHuOYk4eVlfOkQVcFkLYJ/waA0XNd3m75PStXrXekAWvInKBMrf5nhVKj8+GUsonpZTTlH3hQC/MPtmofOet7ItESrlUStlEStnE7WHD7cxtOH74JN61q+NVw0AZlzIEdmvLrthUG5vk2FQ69ewAgH/nNuxPOQjAkO7D6dY8hG7NQwj7Yh1fL1pJxFcb/tX574Xjh09So3Z1vGp4UsalDO26+ZNsp31XbCqdera3aD+QcsiiPbh5b4Kb92aNRftG1bSfOHyKGrWrY1C0B3bzJzl2t41NcuxuOip+9+vchgOK39/oPoLuzXvTvXlvwr9Yx4pFq1inkvZjh0/gXac61bzN8dIhOICk2BQbm8TYZLr2CgLMw1P2pZrnkqpYqQKLV37I/2Z/zuH9P6qi15ofDx2nZp0aVPP2wsWlDB27tyMhJtnGJiFmF91COgHQvos/e1MOKNuT6di9HS6uLlTz9qJmnRr8cPCYKrpPHD5JjdrVLLES4CBWUmJ301GJc79Obfg+1Rznj1SpbJlk3svbQI3a1Uj7/d+97LgXjh0+iXed6ngp8dI+uC2JdvGSFJtCl14dAfPwlP1KvFSoVIFFK+ezaPYSjqgcL8cOn1BipSDOE2NtYyUxNoWuim7rOC9tjh46gbeV9qDgQAdxnkw3RXu7Ln58p8R5aWOt3cWlDB2DA0mIsV0IxKzdXEbbdfEvVe3ffLmGoDY9CWrTk5it8fTo3RWARk3qk52Vg8k+IWi8wOWcyzRqUh+AHr27EhudAECtOt4Wu8AgP878pM7czccOn6RG7RqWNkD7bgEkxdjeR5NiUums1OltO/ta2gBeNQyWxX0M1T2oVdeb9D8yUAOtxYo1WrwXff1FmGVxnm1b4+jZuxsAjZvUJzsr22Gs5+RcprES6z17d2N7dDyAzXyaHTsHcPLETyWu/07wbdWCzdvjkFJy5OgJKlQoj1vVKrRs/hy79x3kUlY2l7Ky2b3vIC2bq7eis1brdK3qhnurXxJidtExOFApowa869Tgx4PqLL9wL20Xcxt9AR/P/ozD+39QRa812m7rarPNqNU2+oPMgzS0XJR6l+N7QAjxJJAnpfxJ+TwTeAT4f+ydd1wUx/vH33MniAp2qh2NSew1diliw26ioMbExBYTYy+xdzRqjImaRBPTvoliiV0UUcFeMCr2ErtSLQgoqBzz+2OP44DDgnJ4/vadF6+4u8/efm7u2ZnZZ5+ZcQPaSymvCCGcgYMoWYj3gEBgAcr8lkeBpnq7olLKu0KIyUCC/pwfgZZSynAhxCCgBdBFSpkohPAClgCV9dsS6Cal9BdCjAccpZRfCiE2AvOklKnzdYYAI4BbpnRJKdcLIRKklLZ6+w+AtlLKXqnapJRzjcqgErAeZah4tBCiKGAnpbwmhCiCktF5DRgtpTz8DPurQB39XKNZUtel6Qs7TUPP+gyb8iVarYYN/gH89v3/6D/yU86GnWf3tn1Y57VmyvfjeLvKW8TFxjNuwGRuZWgg+g7/hMQHifz1k/+LXh4wPUTj+bTXY9iUL9FoNWz0D+C37/+i38hPORt2jj3b9hu0V6xSQa99SqbGre/wXjx8kMjfP63I4ipZo8mmboAGnvUYOmUgGq2GTf5b+P37v+g78hPOhZ03aJ/0/VgqVnmLuNg4JgyYmkl7H732ZdnQnpiSvUnUGzdrwKipg9FotaxbvolfvvuDz0f14fTxc+zathfrvNbMWDiRd6pUJC42jlH9J3Lrejh9h/Si96CeXLt8w/BZA3yHcvf2vRe6/uOU5GzpBmjarCFjpg9Do9WwZtlGFs//jS9H9+PU8bMEB+7BOq81Xy+awrtVK3L/XhzD+4/j5rVwAPoP+YTO3duhS9Yxc/w89uw88MLXL2xVIFu6G3jWY8iUL9BoNGxasYU/vv+bviM+4WzYefYG7cc6r5XiK5X1vvL5NMKvR+Du3ZS+Iz5Bp9ORotPxyze/szfoxXUDJOmy7y8jpg5Co9Wyfvkmln73JwNG9eGMkb9MXziBt/X+8lX/Sdy6Hk6fIR/z6aCeXL980/BZA3yHcO927AtdX5fNJlzx8yFotRrWLd/Ez9/9weej+nLm+FlC9Lr9Fk7inSoVuR8bx6j+E7h1XfGVLaFrsLUtgJV1HuLvJ9Dfd3C2FkRLyWYfoEmzBoyeNhStVsPa5ZtYMv93vhjVl9Nh5wjR+/nMhZMUP4+NY2T/CQY/Dwxdi61dfqysrYi7n0A/n0EvrP1lhro2adaQr6YNRaPVsHb5RpbM/52Bo/pxOiztHp21cLJB+4j+4w3at4WuxdauQDrtl15wMbf4Jw+zrX3a7HG4N2tEYmISIwaO58Rx5eF1y65VtHZTZsipVqMS3yyajo2NDcHb9zJxtB8AP/0xj/IVypKSIrl1I5wxw6cRFRGd5bUyUjxv9ufaauRZnxFTB6PRatjgv5ml3/3JZyN7cybsnKEPMG3BBN6p8hb3Y+MY89lkbl0Pp80HLek18EOSnySTIlP4ed7vhGzd8+wLZuBRSvbm1cptX4Hs36O53RbFPk7Ilu5U/OaMx8OrMYkPkxj6xTjCjivB1KA9a2jeRBmZU71GZeb/4IdNvrzsDNrDuFEzAFiweBaVq7yDRHLj+i1GDZmcKRD6NK7/t+nZRiYYOWkWocdOEBsbR7Gihfm8d0+Sk5X+hE+nNkgpmTHvB/YePEI+GxumjR1KlXcrArBmUyA//6n0s/p97EunNi1e+Po1K3fPlm7I/TrdknVntz16mfql35BedOqm3KOzJnzL3mzco1qRvXym7PZd+g7pRZ9BH6Xro3/mO+SF++gABbTPWmvXNLnd132gS8qWbsj9PqM2m/lvud1HBzgWuc98c3W85kwu0yNHgn+Tr/1t9jK29EBmbZSgZGEgGfgPZZh5N5RVxiP082R2B8agZCMGSClH6c9vDfihZKZGSymbGwcLhRAtgVlAc+AOMBFl2LkOiAQGSilP6j8rAfgW8AbuAz5SyhghxPv6ayQCDYAtwAgp5ZGn6HpaIHMISqAVACllSSGEj/5zNMAT4AspUvPJJAAAIABJREFU5UH9+ZuASlJKQzZpVvY5Gch8HchuIDO3eZlAZm6T3UBmbvMygczcJruBzNeB7AYyc5vsBjJfB7IbJMltzD1n36vkZQKZucnLBDJzm+wGMl8HLPUefdlAZm6S3UBmbvMygUyV7GOp7VF2A5mvA9kNZOY2LxPIzG2yG8h8HVADmWlMLJszgcypV9VApsViHHx801EDmeZFDWSaHzWQmTuogUzzY6lBEkt9cAQ1kJkbqIFM86MGMs2PGsjMHSy1PVIDmeZHDWTmDmogM43xZbvnSIU1/eoys5ex5XqkioqKioqKioqKioqKioqKioqKyv8bnraIjMoL8P8lG1NFRUVFRUVFRUVFRUVFRUVFxXKwzPxx06gZmSoqKioqKioqKioqKioqKioqKiqvPWpGpoqKioqKioqKioqKioqKioqKyhuK5c7qnxk1kKnywgT3LJ7bErJFwz8icltCttBJy61yatmUyG0J2SI08UZuS8g2955Y7gILlrqoRdhcr9yWkG0qDw/MbQnZ4vTXzXJbQrZpNP5gbkvIFm3zlsltCdnmr4QzuS0h2+TTWue2hGzhZFMktyVkG0tdNOfY6WW5LSHblKvYPrclZBu7PPlzW0K22O9tuYtDXgvOl9sSssXtZPvclpBtiudLzG0JKq+AlDdocLk6tFxFRUVFRUVFRUVFRUVFRUVFRUXltUfNyFRRUVFRUVFRUVFRUVFRUVFRUXlDeXPyMdWMTBUVFRUVFRUVFRUVFRUVFRUVFRULQM3IVFFRUVFRUVFRUVFRUVFRUVFReUOx3JU3MqNmZKqYBW3FmuQfsYD8Ixdh5d7JpE2eag3JP+w78g2bT17fIYb91q17km/YfPIP/x7r9r3NJdlAI4/6bNjrz6YDq/h0YM9Mx62srZi9eBqbDqzi74BfcCnlBEChIgX55Z+FHLy0gzF+w80tG4DGHvXZtG8lWw6ups+XH2U6bmVtxdwl09lycDXLtyzFpZSz4VifQR+z5eBqNu1bSSP3euaUTVW3mszeuYC5uxbRdkBmf3n7vUpM2zyX3y+toq53g3TH/ri8iukB3zA94BuG/jLGXJLTMW7GcAIPrWF9yDIqVX3bpE3lau+wIWQ5gYfWMG5Gmn8UKlyQpasWsvXgPyxdtZCChezMJdtidQOM9xtB0OG1bAhZTqVqWWvfuMufoMNrGe83wrC/VftmbN6zgnNRh6lS/V1zSWbfpSg6/BREux+38ev+85mOzwk6QddfdtL1l520/2kbjb/ZZDj27c5TdF6ynU6Lg/h6WxgyFxZKmug3ip2H1xOwawWVq71j0qZK9XfZsnslOw+vZ6LfKMP+ryYPIejAGgJ2reDHP77BrqCtuWSz73I0HX7eSbslO/j14MVMx+fsOEXX33fR9fddtP95J42/2wJA6LXbhv1df9/Fe99sZudF8y0i19CjHmv2LGP9fn96Dfww03Eraytm/TSF9fv9+WPzEpxLKm1R5RrvsjzoN5YH/Yb/9t/xaN3UbJpTqeBWjUE75jA45BuaDGiX6XjD3q0ZGDSbz7fMpNffYyhUIv2ignlt8zHi4ALaTPnYXJINWKqfZ7f9L1SkIL+t+YHQy8GMM6onzUlDj3qs3buc9QdW8ElWvr54KusPrODPgCU46/td9ZrW5e/ApawM/pO/A5dSt1Ets+pu5FGfjftWEHBwFb2/NN1fnLtkOgEHV7EsQ5n/umYRhy/vZGwu9BfH+82jaRtfOn74mcnjUkr8vv2R1l0/pdNHAzhz/j/DsfUBQXj79MbbpzfrA4LMJTkdU2eOYe+RAIL2rKFKNdNteNXqldi+dw17jwQwdWbmvmH/gb24efcURYoWzmm5Bhp71Cdg/yq2Hvony3t03pIZbD30D/5bfk3XR+876GO2HvqHgP2raORR32yaAfJUqYut32/YzvqDvN6+Jm2s6rphO30pttN/IV//sQCIYg7YTvoB2yk/YTv9F6zd25pTNgC2brV4e8ePvB2yGPsBH2RpV6h1Q6pd3Ui+qhUM+2zeKUv5NXOouG0Rb21dgMhrZQ7JBop6VKfevvnUP/g9Zb7skKWdfdt6eEatxK66q2FfmUEdqX/we+rtm09R9+rmkGvAkstc5dUhhGglhDgvhPhPCPGViePDhBBnhBAnhBA7hBDPXGHytQ9kCiGKCSGO6/8ihRC3jLYzLeUohCgqhDDdEqe3yyOEiNX/e6MQoq3RsUvGBSyEWC+EeO7l9IQQXkKIdSb2dxJCjHzez8lw7mwhxAyj7XJ6nQWz83lmRWjI27Evib9O5+G8weSp3gThUDK9STFnrNw78/DHsSTOG8Ljjb8BoCnzNtqy75L47TAezhuCtmQFtK6VzSZdo9EwduZwBnQfRsem3WjdqTmuFcums+ncvR1xsfG0bdCF/y32Z8j4LwB4/Ogxi75ewjdTFppNrzEajYZxs0byWfchtG/ii3enFpSvWC6dzfvd2xMXG0/r+h/w52J/hk1QtJevWA7vjs1p37Qb/bsNZvzXo9BozFNdCI2Gj6f1Zc7H0xntNZgG7Zvg8lZ6f7kTHsOS4Qs4sH5PpvMfJz1mvPdwxnsP59s+M82i2ZimzRpSxrU0Let1ZuJwPybNzlRXAzBp9ldMHOFHy3qdKeNamiaeDQGlc3pwdyit6r/Pwd2h9B1kngd3S9UN4ObViLKupWj+XicmDJ/BlNmmA9hT5oxhwvAZNH+vE2VdS9G0maL94tlLDOw1itADx8ymWZcimRkYxiKfhqzp58XWMze5FBOXzmZk82qs7OPJyj6edKtdnmZvKw8xx2/e4fjNO6zq04zVfb04HXGPI9dvm007gLtXY8q6lsbzvQ6MHTadaXPGmrSbNmcsY4dNx/O9DpR1LY1bs0YA7A05SKvGXfB28+HqpWt8PuRTs+jWpUhmbj/Joi71WNPbg61nw7l0Oz6dzchmVVjZy42VvdzoVqsczSoq5V63THHD/p99GmBjpaVBWfOsQKrRaBjtN4wve4zgfbcPadXRi3IZ2qKO3doSdz+eDg19+XvJCgaPHwDApfOX+bBVH7o1/4SB3YczbvZItFqtWXQDCI2g7dRe/K/XbBY2H0XV9g2wr1AinU3EmWssbjeeH1qP4fSWw7QY0y3dcc/hH3D10DmzaU7FUv38Zdr/x48es2DWYuZM/t4sWjOi0Wj4auZwBnYfzvtNe9Cqk1emflfH7m2Jj42nQwMf/l68gsHjPwcg9m4sQz4aTVePj5g4eDrTF040q+7xs0YwoPtQ2jfphnenFib6i+2Ji43Du34X/rd4eYYyX8LcyQvMpteYjt7N+Wne9CyP7zkQyvWb4QSsWMrkUYOYNlfp196Pi+fH35ax/Of5LP95Pj/+toz7cfFZfk5O4OnVhHLlS9O4jjejh05m5jcTTNrNnDuBUUOn0LiON+XKl8bDq7HhmHMJJ5q4N+DmjXBzyUaj0TDh61H06zaYdo19aNO5ZaZ79IMe7bl/P55W9d7nz8XLGTFhIKDvo3dqQbsmvvT1HcxEM/bRERpsen7Jg2/HkjCuN1b1PNC4lE7/3RxLkLdNNxL8BpMwvg9Jy34AQMbeJWHGYBImfUbCtIHkbeOLKFzMPLoBNBpKTP2MK70mc6H5FxRu35S8FUplNiuQj2K92vHgmFGbo9VQ6tth3Bq3iAstvuCy71jkE50ZtQventWbsO5+HGoyFIdOjchfsUQmM20BG0r1ac39fy8Y9uWvWAKHjg051HQYYd1m8PbXvUEjzKTbgsv8DSUFmSN/T0MIoQUWAa2BSkA3IUSlDGbHgDpSymrAamD2s77Lax/IlFLekVLWkFLWAH4Cvk3dllI+NnFKUeCZgcwM7AcaAgghHIFYwDjNq77e5pkIIbIcri+lXCulnPOC2lKZDHQRQqSmGn0PjJVSxmV9yrN5mt5XhaZUBVLuRCDvRoEumeSwveSp9F46G6v3vHhyYCskPgBAPrivHJAS8liBNg/kyQNaLSkJsTkt2UCVmpW4fuUmt66Hk/wkma3rtuPRMn02i3vLJmxYGQBA0KZg6jWuA0DiwySOHT7Bo0ePzKbXmKq1KnHjyk1uXgvnyZNkAtYF4dEqvXbPVk1Zv3IzANs27qR+47oAeLRqSsC6IJ48fsKt6xHcuHKTqrUy1jc5Q/kaFYi6GkHMjSh0T5I5uHEvtZun95fbN2O4ce4aMuX1S5Bv1trNUKZh/56iYCE77B3Sd9TsHYpha1eA40dOArB+5Wa8vN2U81u5sW6Fknm3bsUmvFq7q7qfpb2VG2tXBBi02xWyw94xg3bH9NrXrggwaLx08SpXLl0zm16AU+F3KVWkACWLFMBKq6FlpZKEPCW7b8uZm7SqrHT+BPA4OYUnuhQe63Qk6yTFCuQ1k3IFr9ZurF2p/N7H/z2p+Itj+iw6e8fi2NoV4NiREwCsXbmJ5t7ugBLg0emUDumxIydxcnE0i+5TEfcoVbgAJQvry/1dF0L+i8zSfsvZW7R6N/PDQtD5CBqVcyCflXlm6KlS811uXk1riwLXb8e9ZeN0Nu6tGrNppZI9umNTCHWb1AYgKfGRoayt81qbPXu3ZI3y3L0Wxb0bMeie6Di58SDvtKidzubKgTM8SVK6dDeO/Uchp6KGY85VymJbvBD/7TlpVt1guX7+Mu1/4sMkjh4O4/EjU13snKdKzXe5YdTvCly3A/eWTdLZuLdswkZ9v2v7phDea6z40/lTF4mJUl7qXDp3Beu81lhZmyeDp2otpb9485qie8u6IDwzlXkT1ut1b9uYsb8YxqNcKvM6NapSqGDWoyiC9x6kfatmCCGoXuVd4uMTiLl9l32H/qVB3ZoUKmhHoYJ2NKhbk32H/jWjcmjh7cFq/w0AHD1ygoIF7XDIcI866O/Ro6FhAKz230BLb0/D8ckzRjFj0jyz1o3ValU2+MuTJ8kErN1mwl/cWL9CuUcDN+6kfpO6+v1NCVi7Td9HD+f6lZtUq2WeJA+t69ukRIcjYyJAl8yTwyFY1WyUzsa6qTePdq6HhwkAyHj9c5suGZKfACDyWIMwbxgif423eHwtgsc3opBPkonduJuCLTKPOHMc3oOYxWuQj54Y9tk1qUnSuasknb0KgC42Hsz4DFKwVgUeXokk6Vo08omO6HX7sW9VN5Od61c+XFu0gZSkNO32reoSvW4/8nEySddjeHglkoK1KmQ6Nyew5DJ/U5E59PcM3gP+k1Je1sfv/IF0acVSymAp5UP95kGgJM/gtQ9kPg0hxCghxCn935f63bOAt/UZm7OEEAWFEDuFEEf1qaqm8tj3oQ9k6v+/DnDRX+MtIFZKeVsIkU8I8YcQ4qT+85rqbfoIIfyFEJuALRk01tPbltXbzdfv/0sI8Z0QYr8Q4rIQopN+v1YI8ZMQ4rQ+U3SrEKKj/ocdASzUZ4daSylX6M+pL4TYLYT4VwgRIIRw0O//QggRqv/eK4QQNvr9/kKIuUKIEGCaEKK5ECJM/3c01e5VIQoVQ8beMWzL+3cQhYqms9HYu6Ap7ky+AX7k+2IW2oo1AUi5fgHd5VMUGL+UAuOXortwHBl961XKeyqOzvZEhUcbtqMionFwtjdhEwWATqcjIT6BwkULmU1jVjg6ORCh1wUQFR6No1N67Q7O9kTeUr6fTqcjXq/d0cmeyFtp50ZGROPo5GAW3UWcinE3Is1f7kbcoYhT0aeckR6rvNZM2TibSWtnUbvFe88+4RXj6GSfrtwjw6NxdE5fdo7ODkRGRKe30f82xeyLEhOtfP+Y6DsULV7EDKotV7eiy57I8LRgVFR4VCZ/dXRyINL4foiIwtHZPNl0poiOT8KpYD7DtqNdPqLjk0zaht9/SHjsA94ro+itXrIYdcsUx+v7LTT/fgsNXB1wLW7e5HwnZwcibqWVeWR4FE4Z/MXJ2YHI8Oin2gB06dGBkB37ck6sEdEJSTjZGZe7zdPL/f5D3itdPNOxwHO3aG0iwJlT2Dul1dUA0RExOGSoz+2d7A3lrdPpSIh7YGiLqtSsxKqQ/7Ey+A/8Rs81BNfMgZ1jUe6Hp9XpcRF3KeiYdf1Qu6s7F0OUgIMQglbjexDotyzHdZrCUv38Zdr/3MbBRL/L3tmEdmNfj3+QSbtXW3fOn7rAk8dPMAcORvcfKGWe8R5Vyvz16y8+i6iYOzg5pNWDjg7FiYq5TVTMbZwc0r6jo72y35w4OTsSbnSPRoRH4eTsmMnG+H4wtmneyp3IiGjOns48vUtO4pChnx0VEZ2pT+LoZE+Ekb8Y+ujO9un7MyZ8LacQRYoj76b5ecrdGESR9C+ONU4l0TqWpMDY+RQYv4A8VdICbqKoPbZTl2D3zTIeBfinez7Maawci/EkPM0/n0TcwSrDS2+byq5YO9sTvzM03f68riVAQrk/p/DWpvnY9+9sFs2G6zsV5ZFRO/oo/A55Mzwb2VYpS16X4twJOprp3KRbRudG3M10bk5hyWWu8kopAdww2r6p35cVvckQUzOFxS72I4R4D+iBEuHVAoeFELuAr4AK+gxOhBBWQAcpZbw+wLcP2JTh40KBGvrsxIZAIFBJCFERJTMztec5CHgspawqhKgMBOgDnejtakgp7wkhvPTXbgJ8C7SXUt4UIlMatwPQCKgKrATWAl1QftiqgBNwFiUTFSnlBiFEb+AX0jJIbYB5QFsp5V0hxMco2ZufA/5SykV6u7lAT+Bn/bXLAZ5SyhQhRBDwqZTyXyGEHZDzr4Qzhu41WjTFXUhcPAFRqBj5Bszg4bzBiAIF0diX5IFfXwDy9ZmEplwlUq6cyXGJAGT+zTK/sX0em9zAxKgBmaHghQkjKSUmfNVs38nUYIcXufSQBv2Ijb6HfSlHxiyfwo1z14i+HvXsE18V2faZnBL0nFiqbnguf81NnzaFqStnNdAn8MxNvN4pgVY/FOj63QQu345n25etAPhs+V7+vX6b2iYCbjnF85V55vMy2nw+tDfJyTrWrwp4pfqywtRPbkonQOC5cLzedjaUeyoxCUn8FxNPg3LmC4S/rI+fOnaGLu49KfdWGaZ8N459Ow+aLePuefwglWodG+FSzZVffaYBULenFxeDw4iLuJuTErPEUv38Zdr/XMd0gWYwebp217fLMWj853zuM/SVy8sKk5oy2ryuZf4MTGkUQmRRn5ppyOpTrve8daNNPhsGDe9H9879ckxfVpjW9GwbZFa+Zi4/Mq0pHRotGscSPPh6OKKIPbZjviV+fB9IfIC8G0PCxH6IwsXI/+UUnhzZjYwz00i7Z9UtQuAyoQ83RszPbKfVUqBuJS62H0ZK4iNcl00n8eR/JOw/kXN6jXnWby4Eb039mLODf3iuc83nLhZc5m8oOZXTKoToBxhXpkuklEtSD5s4xaQXCiE+BOoAbs+6psUGMoEmwD+pKaj6OSkbA9sy2AngayFEY5TfrpQQojjK8HEApJSJQojzQA2gHjANZfx+Q5QAZeqw8sbAHP05p4UQ4UBqbvY2KeU9o+tWAX4Amkspsxq3tk4qre0JIURqVLoxsFJKmQKE64OzxiwChJQydabtKnqtO/UNmxa4qj9WQwgxBSgEFEQJlKaSeg1QArULhBDLUMo00wQ3xs75XYsafFqjXEaTLJH376SbA0UUKoaMu5vJRnf9AqTokPeiSYm5haa4C1rXyuhuXIDHSsZM8vmjaEtXNFsgMyo8GkeXtMwKR2cHYiJvm7BxJCoiBq1Wi62dLffvvdSI/1dCVEQ0zkbD2BxdHIjOqD0iGqcSDkRFRKPVarHTa4+MiMapRNq5Ts4OREfFmEX33cg7FHVO85eizsWIjXr+h9jYaOU2jLkRxbmDpyhTxTXHA5ndP+1Clw87AnDy2Jl05e7k4kB0ZPqyi8qQsePkkla+d2LuYu9QjJjoO9g7FOPu7XvkFJaqG6DHp13o2jNNu5OLE6BkcTm6OGby18iIqHTDOh2dHTPdD+bE0c6GyLhEw3ZUfCL2dqaT4beeucmYlmmTs++8EE61EkXJb6004Y1cnThx626OBzJ7ftoVn57KG/ETx0/jXMLJcMzJxZGoDP4SER6Nk4tDljadfdrh2aIpH3bun6O6jXG0syEy3rjck7C3zaLcz95iTPOqmfZvOxeOx1tOWGnNN6glWl9Xp+LgbG8YQpvOxsWB6NS2qGCBTG3RlYvXSHyYRPl3ynE2zDwZSHGRdynkklanF3QuSnx05gdX10aVcRvYgV99pqN7nAxAqVpvUabu29Tt6YV1fhu0Vnl4/DCJoK9X5JjeN8HPX6b9z22in7Pflc7X7dJ83cHZnnm/+jHhy2ncvGa+ETxREen9wNHFgZiMbai+b/W69RefhZNDcSKj036DqOjbOBQvhpNDcUKPpQUVomJuU7dmtRzX83FvX7p/pCwaEnbsFC5G96iziyNRkdHp7CPCI9PdD6k2ZcuWolTpEmzb849h/9aQVbT18jWMMMkpojL0sx2dM/e5IiOicS7hmO4ejb13n8jw6PT9GZfM90hOIe/FIIqm+bmmqH2mrMqUezHoLp0FnQ55O5KUyBtonUqiu5LW5sjYO6Tcuoq2YlWSj2Se7z4neBJ5GyuXtH6SlXMxnkSnPV9obPNhU7EM5f39AMhjX4Syv4znap/pPIm8TcKhU+j092t88BHyVSlvtqDao4g75DVqR/O6FONxZFo/W2trQ4F3SlFzzSQArB0KU+3PUZz4aDaPIu5gU8LoXOeiPHqB56qXwZLLXOXF0Actl2Rx+CZgPDlqSSDTpMT6ZMBxgJuU8plz81ny0PLnfeX3EUogr5Y+S/M2YOqpZT/gDtjo5508iBLIbEhaRubTrvkgw3Y4SmZjjaecY/wDiQz/z4oU0gfTBXDMaN7QqlLK1CVB/wT6SimrAjNJ/70NeqWUk4EBKMHOI0IIVzIgpVwipawjpazzIkFMgJSb/6Ep5owo4gDaPOSp3hjd2fTp48mnD6MtX0XZyG+HprgLKXcjkbG30ZarBBoNaLRoXSuTEn3zha7/Mpw+fpYyrqUoUdqZPFZ5aNXRi5Bt6RvckG17ad/VG4DmbT04vM+88wNlxaljZymt125llQfvjs0JDtydziY4cA8durYBoEU7Tw7tPaLfvxvvjs2xsraiRGlnSruW4uRR8wSPL4f9h1M5Z+xLOaC1ykP9do05GhT67BOB/AULkEcf3LEtYsdbdd7h1sUbzzjr5Vn26yo6efagk2cPdmwJMZRp9dpViI9LyNQhjom+w4OEh1Svrfh8h65t2LFFeWexM3A3HX2UGTA6+rRlx9aM7zJU3QB//7qKDh496ODRg+1bQujk423QnhCXQExUBu1Rd3iQ8MCgvZOPd45rfBqVXYpw/V4Ct2If8ESXQuCZm7i95ZzJ7uqdeOKSnlC9hNGcgQXz8+/12ySnKPNk/nv9Nq7Fc36V+P/9upK2Hr609fAlKCCYTl2V37tG7aqKv2QIrMVE3eZBwkNq1FaCgZ26tmW73l+aejak/6Be9PtwCEmJpod25wSVnQtz/d4DbsU+VMr9bDhuFZwy2V29k6CUu0vmIdBbz5p3WDnA6ePnKFWuFC6llLaoZQcvdgWmH6a8K3Afbbu2BqBZW3dC9yrDy1xKORsW93Eu6UjZ8qWJuJH1vKCvmlthlyla1onCJe3RWmmp2q4+54LSt5NOlcvQ3q83f/f5hgd30gI7/wz5gXmNBvNt4yEE+i0jbM2eHA1iwpvh5y/T/uc2p4+fo7RrSVz0/a6WHZsRsm1vOptd2/bSTt/v8mrrTqi+32Vb0JYFf81hgd9iwkLNO6eqcZnnscpD647NCQ5M319UylzR3aKdx2tT5s/CvXF9NmzdgZSSsFNnsbUtgH3xojSqV5v9h49yPy6e+3Hx7D98lEb1aj/7A1+SP5b609LtA1q6fcDWzTv5wFdZj7VWnWrExyUQnfElT9RtEhIeUquOEmT9wLc92wKCOXf2IjXedqNBjZY0qNGSiPAoWrl3yfEgJigvYJXnCxflHu3UwoS/7KaDj3KPtmznyUFDH30P3p1a6PvoLpRxLcWJo6dzXDOA7sp5tA4lEMWdQJsHq/fceXIs/TISyUf3k+dd5fFX2BZE41SSlOgIRJHiYKVfpze/Ldq3qpASab5nuodhF7Eu64JVSUeEVR4Kt2tKXNBhw/GU+IecqdWDc437cK5xHx4eO8/VPvoswF1HyfdOWYRNXtBqKFCvCklmeL5IJf7YJfK7OmNT2h5hpcWhY0NuB6bVH7r4RPZW6sOBugM5UHcgcf9e5MRHs4kPu8ztwCM4dGyIsM6DTWl78rs6E3f0v6dc7dVhyWX+piJz6L9nEAq8pV+s2hrwBTYYGwghagKLUUYyR5v4jExYckbmbmCxEGIOShZiB8AHiAeMn+gKAdFSymQhRHOyHo+/D/ga2K7fPoaS9VkcSF1CazfKcPbdQoh3AWfgP9Lm1zTmrl5PoBDigZTyeV837QV8hRB/oQwtbwr8+hT7U0BZIURt/dBwa5Qs0bNAfiBKv687YDISJYQoL6UMA8L0835WBC4/p95nk5LCo/W/kK/3RNBoeBK6g5SoG1g390V38xK6s6HoLhxDW7E6+Yd9h0xJ4XHAH/AwgeSTB9BWqEr+ofNBSpIvHEN31nwdP51Oh9/Yb/hx+Xy0Wg3rlm/i0vkrfD6qL2eOnyVk217WLtuI38JJbDqwivuxcYzqn7Zi4pbQNdjaFsDKOg+erZrS33cwly9cNZv2GWPmssT/ezRaDWuXb+TS+SsMHNWP02FnCQ7cwz/LNjBr4WS2HFzN/dg4RvQfD8Cl81fYumE7G/b4o0vWMf2rOaSYaYLlFF0Kf078hZF/TkSj1bB75Q5uXbxB52G+XDlxiWPbQylXrQJDloymQKEC1PCqS+ehPoxpPoQSb5XkE7/PkCkSoRFs+nEt4RfN10kC2LV9H029GrHt8FqSHiYxdvBUw7G1O/+mk2ckQrBXAAAgAElEQVQPAKaMmoXf95OwyZeXPTv2s3uH0hH8+fs/+Pbnmbzfoz0RN6MY0sf06uGq7jRCgvbh5tWI7YfXkZiYxJhBUwzH1gf/TQcPRfukkbOYtWAyNjZ52b1zP7u2K4Gg5t7uTJg5kqLFirBk2XzOnr5A765fmrzWqyKPRsNXLaozwH8fKSnQoXoZKtgX5IddZ6jkXAR3/UrZW07fpFWlEumGknm9U4LDV2Po8vMOBIKG5R1MBkFzkuCgvbh7NSY4dANJiUmMGjTZcGxTsD9tPXwBmDDSj9kLpmBjk5ddO/YRsl0JSEyeNRrrvNb8ufpHQFlIZfyIGTmuO49Gw1deVRiw6iApUtKhaikqFLfjhz3nqORUGPe3lKBm6iI/GYfw3br/kMj4JGqXNuNKqyj1+ddj57Fo+Tw0Wg0b/Ddz+cIVPhvZmzNh59i9bR/rlm9i2oIJrN/vz/3YOMZ8NhmAmvWq0WvghyQ/SSZFpjBzzDfE3r1vNu0puhQ2T/ydj/4cjUar4ejKXcRcvIXn0Pe5dfIK57cfpeWY7ljnt8Hnh8EA3L91m2V955lNY1ZYqp+/TPsPsC10LbZ2BbCytsKztRv9fAZx6cKVHNedqv3rsd/yw/J5aLRa1i/fxOXzVxgwqg9njp9j17a9rFu2iekLJ7D+wAriYuP4qr+SheT76fuUKleSvkN70XdoLwAG+A7h3u2cH7qq0+nwGzOXxf7fodVqWKvvL34xqi+nw84REriHNcs2MnPhJAIOKv3FkUb9xcDQtdja5U9X5ubqL46cNIvQYyeIjY2jWccP+bx3T5KTlaxon05taNqgLnsOhNK666fks7Fh2lhlyH6hgnb079UN3z7KffvZJ92fumhQTrAzaDeezZuw998tJCUmMmygUZnuWk1LNyVzc+yIacxbNB0bGxtCtu9h53bzZAFmhU6n9K1/WaHco2uWbeS/85f5cnQ/Th1X7tHVf2/g60VT2HroH+7fi2N4/3EA/Hf+MlvXb2fT3hXoknVMGz3bbH10UlJI/HsBBYbPUp7p9mwlJfwaeTt+jO7qBZKPHyD5VCh5qtTGdvpSkCkkrViCfBBHnjK1sPH9TBlaLASPtq4i5aZ56hUAdCmET/wJ1z+ngFbDvZXbeXTxOo5De5B48iJx2w9nfWrcA2J+WcdbG+aBlMQFHyE+2HzPo1KXwoUxv1LDfxxCqyF8eTAPzt+k3KiuxIdd4nZg1kk0D87fJHrDAervmUdKcgrnv1oKKWYaW27BZf6mkhvLJenjcANRpm/UAr/qRzdPBY5IKTegjHq2BVbp+97XpZTtn/a5whLmZklFCDEZSJBSztVvj0LJuARYLKVcoN+/AmW49WaU+SM3ohTaUZSsS08gErgtpSysP8cZJYvyEynl7/p9e4H7Uso2+u18KJHimsATYIiUcrcQog9QRUo5RG/nBQyUUnYUQpQFAvQ6a6Ta6QOVq6WU6/TnJEgpbYWyPP1PKMHR80ABYJaUMjjjZxuVSx3gO5QfXwvMkVL+IYQYDAwGrqEENjVSys+EEP7AX1LKTfrzl+ivlwIcB3pLKbOcHT1hdGfLcRojGv6R9YrArzM6abkrtNWyMW/W0qsiNFF945cbpFhQe2RM2Fyv3JaQbSoPD8xtCdni9NfNcltCtmk0/mBuS8gWbfOWyW0J2eavBDPNq50D5NNa57aEbGEtLDdX4ok032JYr5Jjp3NnUaxXQbmKT31efa2xy5M/tyVki4NtzLtI4KvkWnC+Zxu9htxOtEzdAMXzJT7b6DWl2tWN5p289zVmYFmfHHnYWnh1hdnL2KJ6Gfoh0Mbbs4HZJux8Muyql8VHFjY6J4IMw7qllI0zbCeSFjg13v9Lhu3t6DM7pZRXUYKqAEeMbD7McI6t/v86IcRQKWWCEMIeOISSdZnps432HUFZNCijru9QApwZ9/tm2Db/LNcqKioqKioqKioqKioqKioqKjlOitlWesp5LCqQ+f+ILUKIgoAVMElKaZ5VVlRUVFRUVFRUVFRUVFRUVFRUVF5T1EDma4iUsklua1BRUVFRUVFRUVFRUVFRUVFRsXzenHxMNZCpoqKioqKioqKioqKioqKioqLyxvImDS23qMV+VF4PXIvXtEinyauxym0J2SY++WFuS8gWVkKb2xKyjRCa3JaQLfJYcJlb8sJW0kI7BpbsL8kWuiCHJbdFUYn3cltCtiluUyi3JWQLS64XrTWWmS+htdD2HyD2SUJuS8gWVy5syG0J2aZe1UzLJ1gMibrHuS0hW1hyvagR6roz5uZcdKha6Hr6l+2SIw8si6+uUhf7UVFRSY+lBjEtGUsNYqrkDpYaxLRkLDWIacmoQUyVF8FSg5iWjKUGMVVyB0sNYloyahBTJbex3FcAmVGf1lVUVFRUVFRUVFRUVFRUVFRUVFRee9TXpSoqKioqKioqKioqKioqKioqKm8ob9IoMjUjU0VFRUVFRUVFRUVFRUVFRUVFReW1R83IVFFRUVFRUVFRUVFRUVFRUVFReUNR58hUUckGE/1GsfPwegJ2raBytXdM2lSp/i5bdq9k5+H1TPQbZdj/1eQhBB1YQ8CuFfz4xzfYFbQ1l2wae9QnYP8qth76hz5fZl6Z0MrainlLZrD10D/4b/kVl1LOhmN9B33M1kP/ELB/FY086ptNszFTZ45h75EAgvasoUq1d03aVK1eie1717D3SABTZ47JdLz/wF7cvHuKIkUL57RcA5NmjiY4dCNbdq96ur/sWU1w6EYmzRxt2D9szBds2b2KzSEr+HP1Tzg42ZtLNmC5vj7ebwRBh9eyIWQ5laq9bdKmcrV32LjLn6DDaxnvN8Kwv1X7Zmzes4JzUYepUt20n+UkE/1GsvPwejY/o8wDdq/Ql/lIw/6vJg9h24F/2LxrBT/+MdesZQ6qv+SOv1hemVt6WzRz9gSOHN/OngMbqVa9kkmb6jUqs/fgJo4c387M2RMM+5f+Pp9d+zawa98Gjp8KZtc+861wbNl+bpn1oqX6eiOP+mzct4KAg6vo/WXPTMetrK2Yu2Q6AQdXsWzLUoPuQkUK8uuaRRy+vJOxfsPNqtkYS+wvjvebR9M2vnT88DOTx6WU+H37I627fkqnjwZw5vx/hmPrA4Lw9umNt09v1gcEmUWvMQ096rFmzzLW7/en18APMx23srZi1k9TWL/fnz82L8G5pBMAlWu8y/Kg31ge9Bv+23/Ho3VTc0u32HsULLtOHzdjOIGH1rA+ZBmVqmatfUPIcgIPrWHcjLT6pFDhgixdtZCtB/9h6aqFFCxkZy7ZFqv7TUTm0H+5wSsNZAohigkhjuv/IoUQt4y2rZ/zM34TQpj28DSbL4QQPbKp8Yhez3UhRIyRvlJCiEAhRI7cHUKIPEKI2Jf8DFchhK/+305CiCtCCAej40uEECOy/oTcw92rMWVdS+P5XgfGDpvOtDljTdpNmzOWscOm4/leB8q6lsatWSMA9oYcpFXjLni7+XD10jU+H/KpWXRrNBomfD2Kft0G066xD206t6R8xXLpbD7o0Z779+NpVe99/ly8nBETBgJQvmI5vDu1oF0TX/r6Dmbi16PQaMz77sDTqwnlypemcR1vRg+dzMxvJpi0mzl3AqOGTqFxHW/KlS+Nh1djwzHnEk40cW/AzRvh5pJt8BePuu0YM2wq0+eON2k3fe54xg6dikfddun8ZcnC32ndtAtt3H3YuW03g0b0N7t2S/N1N69GlHUtRfP3OjFh+AymzM78gAIwZc4YJgyfQfP3OlHWtRRNmzUE4OLZSwzsNYrQA8fMotcYd69GhjIfN2w6U+eY1j51zhjGDZthVOaK9r0hB2nduCtt3Hy4cuk6A8xU5op21V/MjSWWuaW3RV4t3Chfvgx1angxdNAEvvl2qkm7ud9OYeig8dSp4UX58mXwaq48oPfuNQS3Ru1xa9SejRsC2bRhm1l0W7afW2a9aKm+rtFoGD9rBAO6D6V9k254d2qBa8Wy6Ww6d29PXGwc3vW78L/Fyxk24QsAHj96zIJZS5g7eYFZtJrCUvuLHb2b89O86Vke33MglOs3wwlYsZTJowYxbe5CAO7HxfPjb8tY/vN8lv88nx9/W8b9uHhzyUaj0TDabxhf9hjB+24f0qqjF+Uy+EvHbm2Jux9Ph4a+/L1kBYPHDwDg0vnLfNiqD92af8LA7sMZN3skWq3WrNot8R4Fy67TmzZrSBnX0rSs15mJw/2YNPsrk3aTZn/FxBF+tKzXmTKupWniqWjvO+hjDu4OpVX99zm4O5S+gz5WdatYNK+05pBS3pFS1pBS1gB+Ar5N3ZZSPgYQClleV0r5iZTy/DOus0hK+Xc2NdbR65sK/G2k74aUsqWU0nyt2IvjCvgCSCkjgW+A2QBCiLrAe8D8l7mAEEIjhBAvqTMTXq3dWLtyEwDH/z1JwUJ22DsWT2dj71gcW7sCHDtyAoC1KzfR3NsdUDrUOp0OgGNHTuLk4viqJZqkWq3KXL9yk5vXwnnyJJmAtdvwbJX+zadnKzfWr9gMQODGndRvUle/vykBa7fx5PETbl0P5/qVm1SrVdksulNp4e3Ban8lc+XokRMULGiHQ4Zyd9CX+9HQMABW+2+gpben4fjkGaOYMWkeUprvbUvz1h6sWbERgONHns9f1qzYSAu97oT4Bwa7fPltzPqmyFJ9vVkrN9auCAAg7N9T2BWyw96xWAbdxbC1K8DxIycV3SsC8Gqt6L508SpXLl0zi9aMeLV2z2aZewDpy/z4kZM4uThgLlR/MT+WWOaW3hZ5t/HCf/k6AI6EHqdgYTscHdNnyjs62mNX0JbQw8cB8F++Du+2zTN9VsdO3vyzemPOi8bS/dwy60VL9fWqtSoZdCc/SWbLuiATupuwfqXiT9s2BlOvcR0AEh8mcexwGI8ePTaLVlNYan+xTo2qFCqYdQ5K8N6DtG/VDCEE1au8S3x8AjG377Lv0L80qFuTQgXtKFTQjgZ1a7Lv0L9m012l5rvcvHqTW9cVfwlcvx33lo3T2bi3asymlVsA2LEphLpNagOQlPjIcG9a57U2a3mD5d6jYNl1erPWbqxfqZRp2L+nlDrdIYN2h/Ta16/cjJe3m3J+KzfWrVDahHUrNhm+k6r7/xcpOfSXG5jlFYgQooIQ4pQQ4ifgKOCszx48IoQ4LYSYaGS7VwhRIzWDUQgxSwgRJoQ4kJp9KISYLoQYYmQ/SwhxWAhxXgjRUL+/gBDiH/25y/XXqvEMnTeFEIWN9P6q1/enEKKlEGK/EOKCEKKO3t5WCPG7/trHhBDt9PurCiFC9ZmeJ4QQrk+5ZgchxCH9+duMvqOnXvtxIcRRIUQBYBbgod83CPgBqCSEcAMWAl9IKZOFEFZCiPl6XWFCiE/0n1lECBGs/7wTQojW+v3v6O2W6H+fV95bdXJ2IOJWpGE7MjwKJ2eHTDaR4dFPtQHo0qMDITv2vWqJJnFwsifyVpRhOyoiGkfnDA9fTvZE6G10Oh3x8QkULloIR2d7IsONzg2PNvsQZydnR8KNyj0iPAonZ8dMNhFGOo1tmrdyJzIimrOnn/pu4ZXj6OxgKNM0TZn9xVh3ZHgUjkY2I8YNZN+JQDp80IZvZ/6Q86KNdVmgryv+mqY7KjwKR6f0mhydHNL7dERUpvshN3B0diD8lrEvROOUQZeTs326Mo8Ij07nL6l80KMDu3bszzmxGVD9xfxYYplbelvk7OLIrVsRhu3wW5E4ZwgAO7ukb6/CwzPbNGhUl+jo21w204OkJfu5pdaLlurrDk7py9LUtR2c076bTqcjQa/7dcBS+4vPIirmDk4OaQFZR4fiRMXcJirmNk4Oab+Po72y31zYO9kTeSvNX6IjYjL5i72RT+l0OhLiHhj8pUrNSqwK+R8rg//Ab/RcQ2DTHFjqPQoWXqc72Wd47slcXzs6OxAZEZ3eRl++xeyLEhN9B4CY6DsULV7EDKotV7fK6485xxZVApZKKWtKKW8BX0kp6wDVgeZCCFMTJhUCdkkpqwMHgKzGtQgp5XvASCA1KPolEKk/dxZQ8wX1vg3MBaoC1YAPpJQNgTFAak70RGCr/tqewDdCCBvgc2CuPvOzLvC0MRa7gfpSyprAGiB1UoiRQD/9ZzQFkvTXDdZnkH4vpUwBBgDrgJNSytSnqQHATb2uesAQIUQJ4AHQTkpZC2gOfGekowrwo/6zo8iAEKKfPhh8JC7pxRt6U0meGd8gmsoDzWjz+dDeJCfrWL8q4IU1ZAfTup9tg8ziXDPPIfF85W7axiafDYOG92Ou38Ic05cVz+MLpss9zWbujIU0qtaS9as381Ef31ctMUveLF9/Pl/JbZ7hClkamSpzXXKy2cocVH/JDSyxzP8/t0XGvP9BW9as3vRqxT0Fy/bzzPssoV60VF83fe0MNryevgKW2198FqbKVwiR+V4gC7/KIV62bjl17Axd3HvSs3VfPvnyQ6zzPtcMbq8ES71HwbLr9Oepr03b5JSg58RSdb+hpEiZI3+5gTlXLb8kpQw12u4mhOit1+CCEug8k+GcRCnlFv2//wWaZPHZa4xsyur/3Rj4GkBKGSaEOP2Cev+TUp4BEEKcAbbr959ECWYCtABaCyFSA5s2QGlgPzBeCFEGWCOl/E8IkVVZlwZWCiGcgLzABf3+fcB8IcQy4B8pZUIWFeu/QoizKNmZqbQAKgghUmeOLghUAG4Dc4UQjQAdUEYIkTob9wUpZZYTfkgplwBLAFyL13wub+35aVd8enYG4MTx0ziXcDIcc3JxJCoyJp19RHh0uqFLGW06+7TDs0VTPuxsvvkOoyKicSqR9kba0dmB6Ay6IyOicS7hSFRENFqtFjs7W2Lv3VeyH4yySRxdHIiJzPm3vR/39qX7Rx8AEHbsFC5G5e7s4khUZHQ6+4gMWS+pNmXLlqJU6RJs2/OPYf/WkFW09fI1vBl7lfTs7YNvqr8cO41ziYyaMvpLVDrdpnwKYMPqLSz1X8j8r3985ZpTsVRf7/FpF7r27AjAyWNncHJxApQhY44ujkRHZfT1qPQ+7exItBl82hQfftoVn56dADh5/DQuJRxJHRTm5OKQqcwjM5S5s0v6e7mzT1s8WjShZ2fTCwa8SlR/MT+WWuapWGJb1LtvDz7q5QPAsaMnKFEibbEHlxJO6bIvQMnSNG6vXFzS22i1Wtq2b4Fnk045qtuS/dyS68VULNHXDbqNylK5dkxmmxKOREXEoNVqsbWz5f69OLPoM4Wl9hdfBCeH4kRGp/lAVPRtHIoXw8mhOKHHTqTtj7lN3ZrVzKYrOiIapxJp/uLgbE9M1O3MNi4ORKf6S8ECmfzlysVrJD5Movw75TgbZp5sWEu7Ry25Tu/+aRe6fJimPf1zT+Zyj8owesTJxcHw/e7E3MXeoRgx0XewdyjG3dv3VN3/D3mT4sPmzMg0TFonhHgLGAx4SimrAVtRgoAZMZ4sRkfWgddHJmxe9rXaI6N/pxhtp2S4RkejeTZLSykvSCn/B3TSnxMkhHjacnKLUOYSrYqSyWkDIKWcDvQHbIFQfZllRcbpCQTQ30hXOSnlLuATID9QU5/peY+0cn/AK+Z/v66krYcvbT18CQoIplPXtgDUqF2V+LiETA12TNRtHiQ8pEbtqgB06tqW7Vt2AdDUsyH9B/Wi34dDSEpMetVSs+TksTOUcS1FidIuWFnlwbtTC4ID96SzCQ7cTQefNgC0bOfJwb1H9Pv34N2pBVbWVpQo7UIZ11KcOPqi8fQX54+l/rR0+4CWbh+wdfNOPvBtD0CtOtWIj0sgOmNHKeo2CQkPqVVH6cB94NuebQHBnDt7kRpvu9GgRksa1GhJRHgUrdy75Fin9H9LV9DG3Yc27j5sCwims087AGrUydpfEhIeUKOO4i+dfdoRtCUYgLKupQ12Xq3duXzxSo5oNmi3UF//+9dVdPDoQQePHmzfEkInH28AqteuQkJcAjFR6X/rmKg7PEh4QPXaVRTdPt7s2LorRzVmxV+/rqSdRzfaeXRjW0BINss8BFDKvN+gXvQ3U/2i+ov5sdQyT8US26KlP/9tWKBn86bt+HZTHmrq1K1B3P14ojI8PEZFxZAQ/4A6dZVZgHy7dSRg83bDcXePhly8cJlwo2GBOYEl+7kl14upWKKvA5w6dpbSrqUoUdqZPFZ5aN2xuQnde+jQVfGnFu08OKTXnVtYan/xRXBvXJ8NW3cgpSTs1FlsbQtgX7wojerVZv/ho9yPi+d+XDz7Dx+lUb3aZtN1+vg5SpUrhUspxV9advBiV2D6aUp2Be6jbdfWADRr607o3qMAuJRyNizu41zSkbLlSxNxI2frRWMs7R615Dp92a+r6OTZg06ePdixJYQOXZUyrV67ilKnZ7jHYqLv8CDhoUF7h65t2KHvu+wM3E1HH6VN6OjTNke/k6XqVrEszJmRaUxBIB6IE0I4Ay1Rgpmvkr1AV2CPEKIqSsbnqyYQGIQSlEUIUVNKeUwI4Sql/A/4Th+ArIaSpWmKQsAtoaRbGpbhEkKUl1KeAE7oMyjfBmKA51lVPRD4XAixTz9n5rvAFf21ovT7WgHmWRUCCA7ai7tXY4JDN5CUmMSoQZMNxzYF+9PWQxn6O2GkH7MXTMHGJi+7duwjZPteACbPGo11Xmv+XK1k1R3/9yTjR8zIcd06nY7pX83hlxXfo9FqWLNsI/+dv8yXo/tx6vhZggP3sPrvDXy9aApbD/3D/XtxDO8/DoD/zl9m6/rtbNq7Al2yjmmjZ5OSYt7pcHcG7cazeRP2/ruFpMREhg1MW4UycNdqWropb+LHjpjGvEXTsbGxIWT7HnZu35PVR5qF4KA9eDRvTMiRTSQmJjHqS8M0umwOUQKeABNGzGDOwmmZ/GXUxMG4ViiLTEnh1o0Ixo3IekXLV6/dMn09JGgfbl6N2H54HYmJSYwZNMVwbH3w33Tw6AHApJGzmLVgMjY2edm9cz+7tisd7+be7kyYOZKixYqwZNl8zp6+QO+uX+a4bkW7UuY7Q9eTlJjEaKMy3xi8nHYe3QCYqC/zvDZ52bVjPyF67UqZW/GHUZlPGOFnFu2qv5jfXyyxzC29LQoKDKF5Czf+DdtBYmIiAwekrVq6a98G3BopAZQRQyex6KevsbGxYXvQLrZvS3tg6fRBW/5ZZb5h5WDZfm6p9aKl+rpOp8NvzFwW+3+HVqth7fJNXDp/hS9G9eV02DlCAvewZtlGZi6cRMDBVdyPjWNkf6M+WehabO3yY2VthWdrN/r5DOLyhatm0Q6W218cOWkWocdOEBsbR7OOH/J5754kJycD4NOpDU0b1GXPgVBad/2UfDY2TBs7FIBCBe3o36sbvn0GA/DZJ92fumjQq0an0/H12HksWj4PjVbDBv/NXL5whc9G9uZM2Dl2b9vHuuWbmLZgAuv3+3M/No4xn00GoGa9avQa+CHJT5JJkSnMHPMNsXfvm1W7Jd6jYNl1+q7t+2jq1Yhth9eS9DCJsYOnGo6t3fk3nTwV7VNGzcLv+0nY5MvLnh372a2f3/jn7//g259n8n6P9kTcjGJIH9Orh6u632xS3qCcTJFTcz4IISYDCVLKuUKICsBqfRYg+qDdn0Bt4DKQrD/+lxBiLzAQOAXcllIW1p/jC3hJKfsIIabrj81PtZdSHtcPz94rpawghLDVX6MCygI2NYBOUsor+s/rA1SRUg4x0nwTZa7I4hn0/qXfXmf8XfQL8MwH6qNkt/4npewghBgPdAOeoMyP2R1IQMkwNZ4vczZwC5gD3AQOAzWklF5CiB9RhtKnACdImx90G1AEZb7R7/X6DGWg384DzARaoWRnRgHtUYKgG/T7jqAEkBsChYG/9HOWPpPnHVr+upFXY/V/7J13fM3X/8ef52YIkmhVJmL9OmxqzwwhxNYSsxRV1dqj9l5F6bd0UVqKJGLFSCQhQ2IlapTWaI0qmaokIUZuPr8/7s2812gqn/TqeXrch9zPed/7eX3O533e59zzOaO4JRSKtMx7xS2h0FgIs+KWUCiEUHOw+vPF3ETzHECrFNe+d/8MtdcbfJ6Yqr9kKuptbPC8MdW6KCnDdKdzlbP6d2yoUhhMNS5aaoprrMQ/x8xE2wC3H6UXt4RCc+XiruKWUGia1H6nuCUUigztw6cb/Usx1bioUXEdVkku55PjZMbr6Vupe5H8aNn8+w7V87jIOjKLG31nnrmiKPf1oyJDgVcVRcksZmkmj+zIVBfZkak+siOzeDDVhqnsyFQf2ZGpPrIjs3gw1bgoOzLVR3ZkFg+yI1N9TDUuyo7M4kF2ZObSp1K3IvnR4vv7TtXz2HRbGU/HGjig79DMXjNSdmJKJBKJRCKRSCQSiUQikUj+M5jmIwDjvLAdmYqi3EY3dV0ikUgkEolEIpFIJBKJRCKRmDgvbEemRCKRSCQSiUQikUgkEolE8l/nRdrsR3ZkSv4zmOpak6a6ziRAafOSxS2hUJjy2l73tA+KW0Kh0Zpo3fqKpXo7nT5v/nyYVtwSCkVZC+villBoMrJMc10yU15n0pTXJTMTplkfmXI9aqpr8NqYlypuCYXGVNeZBDh2ZkNxSygU9Wv2LW4JheYli9LFLaFQpGVmFLeEQmOq65JKXlxMt5UhkUgkEolEIpFIJBKJRCKRSJ6IKW9QWhDT3JZPIpFIJBKJRCKRSCQSiUQikfynkCMyJRKJRCKRSCQSiUQikUgkkheUF2mBANmRKZFIJBKJRCKRSCQSiUQikbygKIqcWi6RSCQSiUQikUgkEolEIpFIJKohOzIlqjFz4STCYwMJivKnZp03jNrUqlud4INbCI8NZObCSTnHJ88eQ9iR7QRF+fPV+k+xsVV3x9q5i6YQczyIsOjt1KpT3ahN7bo12B+znZjjQcxdNMUg/f2PBnH91lleLvtSUcvNx6xFHxMRt5vggwFPzvforUTE7cuYL24AACAASURBVGbWoo9zjo+b8iHBBwPYG+nPhq1fY+9op4rmFu5N2X3In6CjAQwZOcAg3cLSgmWr5xN0NIDNwWtxrugEQJmXbVm3/QtiL4czdeF4VbQWpLl7E7ZHbybwsB+DPupvkG5hacHir+cQeNiP9XtX41TBEYCa9arjG/YdvmHf4bf/e9w7tFZbOtMWjCfk2HYCIzdTo/brRm1q1nmDXZG+hBzbzrQFuXlc5iVb1gasYt/RbawNWIVtGXV38p65cCLhsYHsfUp8CTror48vE3OOd+jiSXBMAL8mH6d2PePlu6ho5taYrdEb2X5oMwM/6meQbmFpwcKvZ7P90Ga+2/N1jr9k41Denqhf99F/eG+1JOdgqjG9mXtjtkVvYsdh3yfm+Y7Dvny/95t8ZXRT2Do2ha1j8/7vcOvQSjXNAC3dm7Ln0BaCj25l6EjDHX6z42Lw0a34FoiL323/krjLEUxbOEFVzXmZvnACYbE72BXpS406j48vu6P8CIvdwfQ8Wtt3acPeaH/OJ8VSq666ZdRU42JL96YEHQ5g37Ftj/WX5asXsO/YNvyC1+X4C8B7oway79g2gg4H0MK9qWqas2nu3oTAGF92H9nC4I+MtwGWfDOX3Ue2sDFoDc4VdWW0aetG+IasY2vED/iGrKNxiwaq6i5sGQUYOmogwUe3sufQFlq4NVFTNmC6/mKqba7pC5fTumNvuvUfbjRdURQWrviKDr0G0/2dD/jlwm85aYFBYXj7DMHbZwiBQWFqSc7BlNvoTd0a4XdwPQExGxnwYR+DdAtLC+Z9NZOAmI18u/tLHCs4AOBYwYHI3/axPnQN60PXMGnxWLWlm2y+m2pseVHJQimSV3HwwnRkCiFWCCHG5HkfIoT4Ns/7T4UQ457xuyoLIc4aOe4mhNhj5Pi3Qoga+r97CiHOCSEinvL9GUKIU0KI00KIw0II463jp2gyFdw8W1K5qgsejbsyddx85i2datRu3tKpTB03H4/GXalc1QXXNi0AiIk8SvuWPfF29eHqpd8ZMWawato9PFtRpZoLLRt68/HY2Sz6dIZRu0XLZjBp7BxaNvSmSjUX3D1b5qQ5lXeklVszrv8Rr5ZsIDff3Rt1Zsq4ucxfNt2o3fxl05k6di7ujTrny/fVq76nQ+uedHTzITz0IKMmvF/kmjUaDdMXT+CDvmPp0qoP3t3bUfW1yvlsevTtQurtVLyb9uSHb3wZN+NDAB4+eMjKxatZNntlkes0hkaj4eOF4xjZbwJvufanfTdPqhTQ3q1PJ1LvpNG1eW82rfZn9PQPALh04TL92w+lT9t3+ajveKYtmYiZmZlq2lu3aU6lqi54NenBzPELmbVkslG7WUsmM3PCQrya9KBSVRdaeTQHdI2NowfjaN/0LY4ejOO9UQNV0+7m2SInvkwbN5+5Sw0fJADMXTqFaeMW5IkvOu0Xz11ixKAJxB45oZpm0PnLpIVjGd1vIr3c3qFd1zZUebVSPpuufTqSejuNHi36snnNFkZOz/+jZ9zskRwOP6ambMB0Y3p2GR3VbwI9XQfgZaSMdu3TkbQ7aXRv3ofNq3Pz/LcLl3mn/Xv0azuYkX0nMFXFMqrRaJi2eCLD+46hS6veeHdvR7XXquSzeatvF1Jvp9Gh6dts+MavQFz8hqWzP1dFqzFcPVtQuWpF2jbuzozxC5izxHgZnbN0CjPGL6Bt4+5UrlqR1voy+uu5S3w0aBJxR06qKdtk46JGo2HGJ5MY1mc0nVv60LGHl4G/vN2vC3fupNG+yVts+MaXCTM+AqDaa1Xw7t6Ozq16817v0cz8ZBIajXo/FzQaDVMXTWBE3/F0b92X9t09DdoA3ft2JvV2Gp2b9WLjN/6MmT4CgNu37jDqnUm87T6AGaPns2DVTFV1F7aMVnutCt7d2tKldR/e7zOa6cWQ56boL6bc5urm3Zavl89/bHr0kTiuXY8nyH8tsyeNYt6yVQDcSU3jq+8247vmM3zXfMZX323mTmqaWrJNvo0+fsFoxvWfTB/3QbTt1obKBdpcnft4k3YnjZ4t++O3JoAPp+X+7rn+ezwD273HwHbvsWTyCtW1m2K+m2pskZgGL5I3HAaaAwghNEA5oGae9ObAoad9iRDib9diiqIMVRTlF/3bIcAIRVHcn/KxS4qi1FMUpS6wHjD+K/AFwbODKzu26PqAT/14BtsyNtg5lMtnY+dQDmub0pw8/hMAO7bsoa23G6D70avVagE4efwMjs4Oqmlv5+3OVr9dAJw4/hO2tjbYF9Bur9d+Iu40AFv9duHl7ZGTPnvBJBbMWq76uhRtO7iz3X83AKeOP1u+b/ffTTu99vS0uzl2JUtZoajwxKX2mzW4duU613+PJ/NRJsE7w/Bon/9JuUf7VgRuCQIgdHcETVo2BCDj3n1Oxp7mwYOHRa7TGLXqV+f61evcuKbTHhK4Hzevlvls3Nq3ZM+WYAAO7ImkUSvdiJH7GQ9yfNyyhKXqvtKmgyuBW/YCcPrHszpfsX8ln42d/StY25Tm1PEzAARu2Yunt6vu8+1d2emvK+M7/ffg2cFNNe2eHdwKGV90YfrSr1e48tvvqunNpmb96vxx9QY3riWQ+SiTsMADuBbwl9ZeLdkbsA+A8D1RNGr5Zk6aa/uW3LgWz+WLV9WUDZhuTC+Y56FG8ty1fSv2bNHl+YE9kTTWl9EHecpoCZXLaO03a/CHPi4+epRJ0M4w3A3iYuucMhy6O5ymLRsBurh4IvY0D4spLoIuPuzw18Xs0z+exaaMDXYOBeKLQ/74ssM/KCeOXPr1KlcuqV9GTTUu1nmzZk49+uhRJkE7Qo3Uo64E+uuuLWR3OE1bNdIfb03QjlAePXzEjWvxXLtynTpv1jQ4R1FRq77O17Pr0X079+PmlX/0s7tXK3bp69GwPRE01rcBzp+9SErSTQB+O38ZyxKWWFhaqKL7n5RR9/atCdoZps/zBP64cp3ab9ZQRTeYrr+YcpurYb3alLF9/AjtiJijdGnfBiEEdWtVJy0tnZSbtzh07EeaNapPGVsbytja0KxRfQ4d+1E13abcRq9R/w2uX40nXl//7w8Mp7VXi3w2rdq1ICggBICIvVE0zNPmKk5MNd9NNba8yGQV0as4eJE6Mg+h78hE14F5FkgTQrwshCgBVAdOCSGWCiHOCiHOCCF8IGekZYQQYjNwJu+XCiGqCiFOCiEaPe7EQohIIURDIcRMoCXwtf48Zvr/44QQPwkhHjeczRb4S/9dlYUQ0UKIE/pX84LGj7PRX0ekEGKrEOK8EGKTEELo0xrpR36eFkLECiFs/oa+f4yjkz0JNxJz3ifGJ+HoZG9gkxif/EQbgJ79uhJ54Kl90s8NRycH4vNoT4hPwtHJwcAmIT7JqE3b9m4kJiRz7ucL6gjOg4OTPQk3CuoyzPe82hPjk3DIYzNh2kcc+imErm93ZMWiL4tcs72jXT4/SIpPNpjSbu9kR6L+urRaLelp6bxUtkyRa3sado52JN7I1Z6ckGKg3S7P9Wm1WtJT7+Zor1W/BgGRP7AlYj0LP16W08hWAwdHuwJ+kJzPD0DnT4kJyflt9Nf3il1ZUpL/BCAl+U/KlntZBdW5uuJv5Nfu6JQ/3x2d8vtVgpHrUxs7x3Ik5fX1hBTsCui2z2OT7S9lypbBqqQV74zoy5pPv1dTcg6mGtPtHe1IMiijBR5MPSbPAWrWr4F/5Ab8Ir5nkYpl1MExf5xOylP2cnQ75cYfrVZL2r8kLgI4ONmRGJ/rL0nxSTg4FogvjvYk5r3GhCQcnNRZzuRxmGpctHfMrSMBkhKSDfLSwdEup32Q11909yq/r6m1rAzo/TjP+ZMTUgy057XRtQHuGvi6Zyd3zp+9yKOHj4peNP+sjDoUuF+JCckG5aMoMVV/MeU219NISvkTR/vcusnBvhxJKTdJSrmJo33uNTrY6Y6rhWm30cuRHJ/fX+wK1P92+er/LNJT0ynzsi0Azi6OrA9ZzZdbP6Nu49rqCcd0891UY8uLjFJE/4qDF2bXckVR4oUQmUIIF3QdmkeA8kAz4A7wE9AJqAfURTdiM04IcVD/FY2BWoqiXBFCVAbQT/f2A95VFOWUEMLtKRrmCiE8gAmKohwXQgwD7iiK0kjfmXpICBEKKEA1IcQpwAYoBWQviJMMtFUU5b4Q4lXAF2hY4FRPsqmPriM3Hl3nbgshRCzgD/goihInhLAFMtCNHjXQpyjKlYLXpr+WYQCvlK6ArVW5giZPRN+fWjC/CtgYfq6gzYixQ8jM1BIYEPS3zv9PeDbtxm2sSloxavww+vYYVmT6nsSz5Kkx7eSxWbZgFcsWrOKDMYN5Z2hvPvvkq+ct86l6CoZHwdPvSXHwT3wF4OzJX+jpNoAqr1Zizv+mcSj8qHqjqJ5Bu3GbohL07DzFhR9rVNw+U1h/QVF4f+JgfNcEkHEvo6jkPRGTjemF9JVso59P/oKP2ztUfrUSc/43lcPhx9Qpo8YkFYiM/9a4CP88NhYbJhoXjefl021QHlcHq3dBz9ZuebJNtderMGb6CIb7jDE0LCr+QRktbt83VX8x6TbXUzB2/4UQRmOL0XtTRPwn2+jAn8m36Na4N6l/pfJ67df4ZN08+rq/y730e0Ul95l05bP5F+a7qcYWiWnwIo3IhNxRmdkdmUfyvD+MbrSkr6IoWkVRkoAoIHukZWyBDjw7IBDoryjKqULqaQe8o++wPAa8AryqT8ueWl4NGAOs1h+3ANYIIc4AAYCxuSVPsolVFOW6oihZwCmgMvA6kKAoShyAoiipiqJkPkVfPhRFWa0oSkNFURo+ayfmgMG92BPhx54IP5ISU3Aqn7tJhaOzA0mJKfnsE+KTcXS2f6xND5/OeLRrzdjh057p/P+EgUN6ExK1lZCorSQlJuOcR7uTswNJicn57BPiE3HKMzUy26Zy5YpUdClPaPQ2jpwKwcnZgX2RAQZT054nA4b4sDfSn72R/iQnpuBUvqCugvmelE+7sXsDsGtrMO07exaZ7mySEvL7gYOzPSkF9CQlJOOovy4zMzOsbay581dqkWt7GskJyTiWz9Vu72SXM80tn43++szMzLC2LW2g/cqvv5Nx7z7V3si/jszzpu/gnuwI38SO8E0kJ94s4Af2JBfM9wIj6hyd7UlO0tn8mXIrx6/t7F/h1s2/ilR7/8G92B3hy+4IX5ITU3Aun197QR9OLBBfnIxcn9okJ6TgkNfXney4mZjfX5Ly2OT1l5r1qzNy+nACj/nTZ+jbDBrZn57v9ihSvaYc07NJTkjB4all1Hie5+WqSmU0m6SE5Hzl08HZnmQDX8mNP2ZmZtgUc1zsN7gngRGbCIzYRHJiCo7Ouf7i4OyQEzuySUxIyrfEgIOTg8E1qoEpx8UcTXnqSNCNGi2oOzEhOad9kO0vt/+6o4+V+X0tRcX7kBSfku/89k52hr6ex0bXBsgto/ZOdqxYt4jpI+dy/fcb6un+B2U0scD9cnSyNygfRYmp+ouptbn+Do725UhMzr2WpOSb2Jd7RX88994kpeiOq4Vpt9FTsHfO7y83k/40sMmt/zVY21qT+lcqjx4+IlV/DRfOXOTG1XhcqlZQTbup5rupxpYXGbnZz7+X7HUya6ObWn4U3YjM7PUxn/TI6m6B93eAP4AWRmyfFQGM1HdY1lMUpYqiKKFG7HYB2QtGjAWS0I0abQhYGrF/ks2DPH9r0Y26FRg+uPk7+grFD+u20Mm9N53cexMWFEH3Xp0AqNegNmmp6QaNjZSkm9xNv0e9Brrh+t17dWJ/cBQArT2a8/6oQQzrP4b7Gfefl8THsn6tH16ub+Pl+jb79obzdu8uALzZsA5pqekkF2woJd0kPf0ebzasA8DbvbsQGhTB+XO/Uu91V5rV86JZPS8S4pNo79YzZ6pZUfDDWn86uvnQ0c2H0KAIevh0BqBew8fne3r6Xeo11OV7D5/OhAXr9qqqXNUlx86zgxuXfzUYrPvcOXvyHC5VK1LexQlzC3M6dGtLREh0PpuIkGi69vIGoF1nd47FHC9yXc/Cz6fOU7FKRZwr6rR7dfUkKiT/lNmokEN06tUBgDad3IiL0W0w41zRKWeheacKDlSu5kLCH4kUJZvXBdDdox/dPfpxIDiSrr06AlC3QS2drxTw05TkP7mbfo+6DWoB0LVXRw7oy2h4yEG6+ejKeDefThzYF1Wk2jeu20Jn9z50du9DaFBkIeNLZJFqfBq/nDqPS5UKOf7StmsbDobm95fo0EN07NkeAI9Orjn+Mqz7SLo28aFrEx98v93K9ys3EvDd9iLVa8oxPZtfTp2nYp48b9e1DQdDYvLZHAyJoVMvXZ4/row6VnCgUjUX4ou4jGaTNy5aWJjj3a0tESEH89no4qKuDLfr7FHscXHTugC6uvejq3s/9gdH0t1HF7PrNqhFemo6KQV+QKYk/cnd9Ls58aW7j3eRxxFjmHJczObMyV+oVLUi5V2cdf7SvZ2RevQgXX101+bV2YOjen+JCInGu3s7LCwtKO/iTKWqFfnpxM+q6Ab4+dQ5XKpWyGkDtO/mSVRo/jIaGRpNF3092raTO7GHdGsE2thas2rjMv638GtOxZ0x+O6i5J+U0YiQg3h3a6vPcydcqlbkzIlfDM5RVJiqv5ham+vv4NayKbv2HUBRFE6fPYe1dWnsypWlRZMGHI49wZ3UNO6kpnE49gQtmjRQTZcpt9HPnTpPxSrlcaroiLmFOZ5dPYgOPZzPJib0MN49vQBw7+jKj4d0G8y9VLZMzkYzzi5OVKxSnvhrCappN9V8N9XYIjENXpip5XoOAeOBy4qiaIFbQoiX0E21fg/dSMb3hRDrgbLoOg8nAm8Y+a6HQDcgRAiRrijK5kLoCQE+EEKEK4rySAjxGmDs8XBL4JL+7zLAdUVRsoQQAwFjmw89i01ezgPOQohG+qnlNuimlhvVpyhKwU7df0xEWAxuni2JiNvF/Yz7TBo1OydtT4Qfndx7AzBj4kKWrJyDlVUJog4cInK/rvE6e/HHWJawZMNW3bTmUz+eYfqEBc9bplHCww7i0bYVMT8Gcz8jg3Ef5e5aHhK1FS/XtwGYOmEey7+Yj5WVFZH7ownfH/24r1SNiLBo3Nu2JPL4HjIy7jNpZO4OnnsjdR2eADMmLGDpqnkG+T5p5miq/l9llKwsbvyRwLQJj99h8Xmh1WpZOGUZ3/j9DzMzDTt893DpwhU+nPQeP58+T2RINNs372bRqlkEHQ3gzu1UJr6f557E7cDaphQWlhZ4dHBlmM8o1TZD0Wq1fDJ1OV/4LkdjpmGX314uX7zC8IlD+OX0eQ6GHmKn7x7mrZxB4GE/7txOZcrw2QDUb1KHQR/1J/NRJllKFoumfMrtW3dU0Q0Qtf8QrT1bEBq7g/v37jN19NyctB3hm+ju0Q+AOZMWs/DzWViVLEH0gcMcPKBrBK75fD0r1izirX5dSLiexJihxnf3LQoi9fElPC6Q+xn3+ThPfNkd4Utn9z4AzNTHlxJWJYg6cJjI/bofPO283Zm5eBJlX3mZbzd/zi9nL/Jurw+LXLdWq2XJtM/4fPMyzMw07PIL4vLFq7w/cTDnTl/gYOghAn33MufzaWw/tJnU22lM+2D2U79XDUw1pmu1WpZOXcFK30/1eb5Xn+dDOKcvo4G+e5m7cjo7DvuSejuVqfoyWq9JHQZ+1I/MR5koisLiKcu5o1IZ1Wq1LJiyjNV+n6Mx07DDdzeXLlzho0nD+Pn0OSJCotm2eReLV80m+OhW7txOZcL703M+Hxq3A2ub0vni4qWLRf9gKpvIsEO4erZgf+xOMjLuM2XUnJy0wIhNdHXXxZdZExezeOVsrKxKcDD8MFH6MtrW240ZiyZS9pWXWb35M879fJEhvUYWuW5TjYtarZb5k5fyrb/OX7Zv3s1vFy4z8uNhnD2l85etm3bxyRdz2HdsG3f+SmX8+7qR0b9duMy+wP3sifFHm6ll3sdLyMpSbyl/rVbLoqnL+cp3BRozM3bq2wAjJg3l51PniQqNYcfmPSxYNZPdR7aQejuVSe/r2ja9B7+NS5UKDBs7iGFjBwHwQe+xqoyE/Sdl9NKFK+zbtZ9d0X5oM3X3Tu08N0V/MeU218RZi4k7+RO3b6fSplt/RgwZQGZmJgA+3TvSulkjoo/E0aHXYEpaWTFv6lgAytja8P6gPvQeOhqA4e/2feKmQc8b026jZ/Hp9M/5bPMSNBoNe/yDuXLxKu9NeJdzpy8QE3aY3X57mfX5VAJiNpJ6O5UZI+YBUK9pXd6b8C5arZYsrZYlU1aQelu93eJNNd9NNba8yBT3cgPPE/FCXYxux/G/gM8VRZmuP/Y90ExRlNf1G98sATqgG6E4X1EUf/3alxMURemk/0xlYI+iKLX0HaFhwHx0ozSDgbyP43sCi8hdFzMyz98a/ec6oxv9mIKuc/Rl4BxwQX/8IfCRoijH9GtebgPuARHoRkxaF9D0OJuC17EKOK4oyvf6zYpWAiXRdWJ66j9voE9RlCfW5FXL1TdJp3mYpc6C788bC/G0fup/L6XNSxa3hEJhqTHdZzz3tA+ebvQv5VHWv2eh/b9DWUvr4pZQaP58qF5D/HlS1sJ08zwj69+xBtvfxVTLJ4BGxTXknjfG1j0zBUy5Hs1UTNPXs0z4N11JM2MT0EyDY2c2FLeEQlG/Zt/illBobEz090VaZvGsa/480Cqm24l4LjnWNCvSIsCrYociqShC/ghWPY9fqI5MiTrIjkx1kR2Z6mPKP8BkR6b6yI5M9ZEdmepjquUTZEdmcWDK9ajsyFQf2ZGpPrIjU31kR2bxIDsyc3mROjJNt5UhkUgkEolEIpFIJBKJRCKRSJ7Ii7Tz+4u22Y9EIpFIJBKJRCKRSCQSiUQieQGRIzIlEolEIpFIJBKJRCKRSCSSF5SsF2hEpuzIlPxtpljVLG4JhWLevdPFLaFQmOo6kwDlTHQdu6SHqcUtodA8zMosbgn/OXZWMt2qtM0l09S+1cGquCUUGvc/TDO+/JF2s7glFBpH65eLW0KhsTEvVdwS/nOYCdOcsHbYu3RxSyg0TfeaZlwE011r8uTPm4tbQqF5FLCiuCUUikeHfyluCYXG0rVucUuQPAdepP1xTLOmlkgkEolEIpFIJBKJRCKRSCT/KUxzKIZEIpFIJBKJRCKRSCQSiUQieSov0tRyOSJTIpFIJBKJRCKRSCQSiUQikfzrkSMyJRKJRCKRSCQSiUQikUgkkhcURY7IlEgkEolEIpFIJBKJRCKRSCQS9ZAdmRJVqOBWh55RS+kV8yl1P+xskF69vwdv7V9Ej5AFdN4+g5dedQagxEvWdNwylUEXvqX5/HfUlp3DnEWTOXh8LyHR26hVp7pRm9p1axAas52Dx/cyZ9HknOPjp35ESPQ2gqMC2LjtGxwc7dSSTQv3puw+5E/Q0QCGjBxgkG5hacGy1fMJOhrA5uC1OFd0AqDMy7as2/4FsZfDmbpwvGp6s2ns1ogNUd+xKWY9fT/sbZBuYWnBzC+nsylmPV/uXoljBQcAPLt78G3I1zmv8Guh/F+Naqpqb+nelKDDAew7to2hIw191sLSguWrF7Dv2Db8gtfl5DnAe6MGsu/YNoIOB9DCvamasgGYuXAS4bGBBEX5U7POG0ZtatWtTvDBLYTHBjJz4aSc45NnjyHsyHaCovz5av2n2Niqu2O9KWov0bQR9n7rcQj4AesBfQzSS3l74Ri0Hbv1q7Fbv5pSnb0BMHN0wO67r7Fbvxr7Teso1d0wpqrBtAXjCTm2ncDIzdSo/bpRm5p13mBXpC8hx7YzbUFuLCnzki1rA1ax7+g21gaswraMjVqyKdm8IeV3rqP8ru8p866PQbp1l3ZUDA/A2f9rnP2/xrp7h5w0hy8W4hK9A/vP56mmNy+zFn1MRNxugg8GPNnPo7cSEbebWYs+zjk+ZfZY9h/dSfDBAL7esAIbW/XyHGDF8rmc/yWGEz+GUb9eLaM28+Z+zJVLcdy+dTHf8TGjh/HT6QhO/BhG6D5/XFzKqyEZgLmLphBzPIiw6O1PrP/3x2wn5ngQcxdNMUh//6NBXL91lpfLvlTUcnMw5bqouXsTAmN82X1kC4M/Mt52WfLNXHYf2cLGoDU4V3QEoGnrRviGrGNrxA/4hqyjcYsGqupu4d6UXTF+7DkS8ATd89hzJIBNQd/m0+0X8h3bIjbiF/Kd6roBzGs1wnrhd1gvXk8Jb8N2F4BFI1es56/Fev63lHx/KgDiFXusZ32J9ZyvsZ7/LZZundSUbdJ+bqpt9OkLl9O6Y2+69R9uNF1RFBau+IoOvQbT/Z0P+OXCbzlpgUFhePsMwdtnCIFBYWpJzuHQ1Zt0Wx9Dl++iWRd3xSB9WdR5fDYewWfjEbp+H0OrL8Nz0hJSM/hg+4/0WH+IHhsOEX8nQ03pmNduhPWS77FetoESnR5TRhu7Yr14HdaL1lLyA10Z1bhUo/TMlVgvWov1gjVYNHFTUTUcupJM128j6bwmgnXHfjNIXxr+C72+j6bX99F0+TaSlp+HABB37WbO8V7fR9N4eTDhvyaqqv1FJEtRiuRVHJh8R6bQESOE6JDnWC8hxL4iPu9eIUR0gWM9hBBv5HkvhBCThBAXhBBnhRCnhBD9ilLXvxGhEbSYP5B9A5aw1X0S1bo2zemozOa3nUfY5jmF7V7TOP3VXprO6g+A9sEjji/dyrF5m4tDOgDunq2oXK0SrRt2ZPLYOSz4dLpRuwXLpjN57BxaN+xI5WqVcPNsCcA3K7/Dq9VbdHDtyYGQKEZPNF7xP280Gg3TF0/gg75j6dKqD97d21H1tcr5bHr07ULq7VS8m/bkh298GTfjQwAePnjIysWrWTZ7pSpaC+oePX8kHw+YykD3IXh0dafSqy75bLx7dyD9Thr9Wg5k65ptDJv6HgD7d4Qz1Gs4wRlH+gAAIABJREFUQ72Gs2D0JyT+kcRvv1xSVfuMTyYxrM9oOrf0oWMPL6q9ViWfzdv9unDnThrtm7zFhm98mTDjIwCqvVYF7+7t6NyqN+/1Hs3MTyah0agXot08W1K5qgsejbsyddx85i2datRu3tKpTB03H4/GXalc1QXXNi0AiIk8SvuWPfF29eHqpd8ZMWaw1P4kNBpeGj+aP8dNJqnPu5Rq64F55UoGZhkHIkkZOIyUgcO4tzsIAO3NP0kZNlJ3fOgIbAb0QVPulaLXnIfWbZpTqaoLXk16MHP8QmYtmWzUbtaSycycsBCvJj2oVNWFVh7NAd0PyKMH42jf9C2OHozjvVED1RGu0VB2ykiSPpzKjR5DKd3eHYuqLgZmd0OjiPcZTrzPcNJ3BOccv7M+gJRpn6ijtQDZfu7eqDNTxs1l/jLjddH8ZdOZOnYu7o06G/i5V4u36NC6J1cu/c6IsUNU096hvQev/l8V3qjRkg8++JgvVi0yardnTxjNWnQ0OH7q1FmaNO3Amw3asm37XhYvMn7tzxsPz1ZUqeZCy4befDx2Nos+nWHUbtGyGUwaO4eWDb2pUs0Fd339D+BU3pFWbs24/ke8KprBtOsijUbD1EUTGNF3PN1b96V9d0+Dtkv3vp1JvZ1G52a92PiNP2OmjwDg9q07jHpnEm+7D2DG6PksWDVTZd3j+aDvOLq17kOH7m2NtLl0ujs168kP3/gxZvqHObpHvjORt9z7M330PBasmqWabgCEBqsBI7m7Yirp04Zg0cQdjXP+uKhxKE+Jjn1IXzia9OlDub/5SwCU27dIXzCa9FnDSZ/3ESU69ka8pE59ZOp+boptdIBu3m35evn8x6ZHH4nj2vV4gvzXMnvSKOYtWwXAndQ0vvpuM75rPsN3zWd89d1m7qSmqSUbbZbC4ohzrOr2JtveacG+Cwlc+jM9n80E1zfw798M//7N6F3PhTb/Z5+TNiPkLAMbVGb7wBZs7N2El0tZqqYdocFq4CjuLp1C+seDsWjmgcY5f5tR41CeEp37kD53FOlThnB/k66M8vABGd8sJn3KEO4unYxV/xFQqrQqsrVZCovCfuaLtxuzfbAr+87Fc+lm/ns+0aMGWwa1YsugVvR5sxJtXtU94GnkUi7n+BqfJlhZmNGssnqDgV5UlCJ6FQcm35GpKIoCDAeWCyGshBClgQXAh//ke4UQj10/VAjxClAbcBBC5K3pewB5h0h8CLgDDRVFqQW4AWb/RJcpYlevGqlXk0i7lkLWIy2XAo9SqV3+p82P0nOfalmUKgH6nv3MjAckxV0k88EjVTXnpZ23O9v8dgFw8vhP2NraYO9QLp+NvUM5rG2sORF3GoBtfrvw8vYAID3tbo5dqVIlUVR6alH7zRpcu3Kd67/Hk/kok+CdYXi0b53PxqN9KwK36DpHQndH0KRlQwAy7t3nZOxpHjx4qIrWvLxR73VuXI0n4VoCmY8yCQ+MpEW7FvlsWrRrzr6AUACi9h6kQcv6Bt/Tpqs7BwLDDY4XJXXerJmT548eZRK0I9RInrsS6L8XgJDd4TRt1Uh/vDVBO0J59PARN67Fc+3Kdeq8WVM17Z4dXNmxZQ8Ap348g20ZG+wK+LmdQzmsbUpz8vhPAOzYsoe23m6ArpNEq9UCcPL4GRydHaT2J2BZ4w0yr99AG58AmZnc2x+OVevmz/bhzEx4pIuJwsIShChCpcZp08GVwC06Pz7941ldntvn//FqZ/8K1jalOXX8DACBW/bi6e2q+3x7V3b66+7ZTv89eHZwU0V3iVqvk/lHPJk3EiEzk7shkZRye8Z8B+7HnkS5d68IFT6eth3c2e6/G4BTx5/Nz7f776advi6KjjySx89/wtHJHrXo3NmLHzZtBeBY7AnKvFQGR0fD8x+LPUFiYrLB8ciow2Rk3Nfb/EiF8k4GNkVBO293turr/xNPrP9L59T/W/PU/wCzF0xiwazlqtX9YNp1Ua36NfjjynVuXNO1Xfbt3I+bV6t8Nu5erdi1RfeAIWxPBI31bZfzZy+SknQTgN/OX8ayhCUWlhaq6b5WQLe7V/48d/NqxS59mytsT26bq6DuEirqBjCr+jpZyfEoKQmgzeRRbCQW9fO3uyxbe/MgPBDu6Tp+lLTbugRtJmTq6yNzSxDq/bQ0ZT831TY6QMN6tSnzhBH9ETFH6dK+DUII6taqTlpaOik3b3Ho2I80a1SfMrY2lLG1oVmj+hw69qNqus8m3qFimVJUKFMKCzMNXq85EnnJsL7JZt+FBNq/rqtrLv2ZjlZRaFpJ184pZWlOSQv1ftKbVXuDrKQbuWX0aAQWDfK3XSzdO/Jg/67cMpqqK6NZidfJSrqhO3b7T5TU22hs1JkdcDbhNhVfLkWFl/R5/oYzkb8lPdY++Fw87as7GxwPu5hIiyp2qua55N+PyXdkAiiKchbYDXwMzAI2KIpySQgxUAgRqx8J+aUQutpVCLFaCHFcCPGzECLnca0Q4roQYoYQ4hDQXQgxVgjxixDitBBiY55Tvg3sBPwBH/1nWwHewAr9+SoDU4HhiqKk6XXeVhRlg96+rd7ujBBijRDCMo+GBUKIo0KIOCHEm0KIUCHEJSHEe3obTyFEhBBip17fF0Lofsk+5dpmCyFOCiF+EkK8JoQwE0L8JoQoq7cxE0Jczn7/vCjt9DLpCbdy3t9NvEVpp5cN7GoM9MQn5lMaT+vN4ZkbnqeEf4Sjkz0JN3KHsifGJxn8AHR0sicxPumxNhOnjeTomTC69ezIp4u+KHrRgL2jHYnxuRV0Unwy9gWmtds72ZF4Q6dbq9WSnpbOS2XLqKLvcdg5lSMlIVd3SmIKdk4FOkgcXyElIQUArTaL9NS7lHnZNp+Ne2c3wgMjil5wHuwdc/MTICkhGQen/Hnu4GhHQp48T9PnuYOTXT4fMna/ipJn9/PkJ9oA9OzXlcgDh4pObAFMUbvGrhza5Fw92uSbmNkZ3u+Sbq2w/2ENZRfMwsw+N93M3g77H9bgEOhH+kY/sm7+WeSa8+LgaEdCvpiXjEOB/HRwsicxITm/jd6nX7ErS0qyTnNK8p+ULWdYJxQFZvblyExMyXmfmXQTM/tyBnal2rTEecs32C2dgZnDv2MEgIOTfU7sAEh4jJ8nFKiLCt4XgF59uxGlYhkt7+yYb0TijesJlHd2LNR3vTuoD/tC1Intjk4OxOeJLbo8dzCwyZvneW3atncjMSGZcz9fUEVvNqZcF9kXOH9yQoqB9rw2urbLXYO2i2cnd86fvcijh+o8CHdwsiMpb5srIRn7gnnuZEdS/JPbXG1V1g0gXi6HcitXe9atFMTL+dtdGscKmDlUoPTUzyg9fSXmtRrlfr6sHdZzV2Pz6WYeBPmh3FanPjJpPzfRNvqzkJTyJ4556lUH+3IkpdwkKeUmjnnaMQ52uuNqkXz3Pg42Vrnnt7Ei5e4Do7bxqRnE38mgUUXdT+Jrf93DpoQ543efovemI6yIvoA2S72HU7oymtt20ZXR/G0XjWMFzJwqUHrG/yg9ayXmtRsV/BrMqr4OZuZkJaszQyA5/T6ONiVz3jvYWJGcft+obfyde8TfyaCxi2GbLOR8PB2MdHBK/j5ZKEXyKg5eiI5MPXOAvkAHYIkQohbQHWiuKEo9dDu0Zy8oMVlRlIZAXaCtEKJGnu+5qyhKC0VRAoBJQD1FUeoCH+Wx6QP46l99ABRFiQaCgLH6890BLBRF+b2gUCFEKWAd8JaiKLWBUsCwPCZXFUVpChwF1mZfB5B3Ua4mwBh0I0OrA12f4dqSFEWpD3wLjFMURau/hr76dC8gTlGUWxRACDFM30F6/ODdXwsmPwUjo4WM+Psv6/fj33I8sQv9qD+q2988RxFiZLSTwcAKoza5RksXrKRp7bbsDNjLoPcM18IrCoQxTQVtjNwbNUeNGKew+Z37d/X6b/Dg/gOuXLj6fKU9BaN5rjzdBuVx90vFRtJTfFhnY/i5gjYjxg4hM1NLYEDQc9X3JExSu3FB+d7ejzlCYo++JA94j/vHT/DyjNzp29rkFJIHvEdSzwGU8vZC87I6HYE5PEOeP1PsVJtnyPd7UUe47j2A+F7vc//YScrNm6iSuCfzLD5sPL7kt/lw3FAytVp2Bux9nvKeyLOU0Wehb98eNGxQl2WffvU8ZD2VZ4stxm2sSloxavwwli1cVWT6Hodp10WGx/5uPK/2ehXGTB/BvIlLnre8x1PomGioe+5EtZeveIZ2usYMjUN57n4ynntfL6Dku+OgpG56qnIrhfSZw0ibPBCLFu0QtuqM9jJtPzfVNvrTMaZRCGG0/jd6f4qKv5F1IRcSafOqA2Yanb5MJYuTN24ztvVrbOzThOt3Mtj1y40iEmoEY9lUMEOzy+jCcdz7cgElh47PN4VclClLyeFTyFizVLXGmLGzPO6Oh5xPwPM1x5w8zyYl/T6/paTJaeUSA16YjkxFUe6iGyH5g6IoDwBPoBFwXAhxCnAFsnf96COEOAGcQNcJmLezzz/P3z8DG/XrWj4CEEKUB1yAo4qi/AKY5V0XMw9PiszVgV8VRclevG8DkHc+wS79/2f057mrKEoSkCWEyN6F4qiiKFf1nZF+QPaCTE+6tu36/38EKuv/XgtkL042GPjOmGBFUVYritJQUZSGrUu/+oRLM+Ruwi2snXIHeZZ2LMvdxL8ea38p8CiVvdRf6Dwv7wzpTXBUAMFRASQnJuNUPnfkiKOzA0kFpr4lxiflm46qs0mhIDu3BtGhs2fRCc9DUkIyjs65I3EcnO1JKaApKSEZx/I63WZmZljbWHPnr1RV9D2OlIQU7PKMILJztONm4p8FbG5ip3/qbmamwdq2NKm3c3V7dHHnwE51p5VD/vwE3Qiq5AJ5npiQjFOePLexseb2X3dIjE/O50O6+1W0T6oHDO7Fngg/9kT4kZSYYsTP82tPiM/vUwVtevh0xqNda8YOn1akuk1dO0BWcgpm9rl6zOzLob2Z/35npabmTCG/F7gXizcMY2/WzT95dPkqlvVqF61goO/gnuwI38SO8E0kJ97EKV/MM/T1pAIjBh2d7UlO0tn8mXIrZyq6nf0r3Lr5+DrheaJNSsE8z6gXc4dyaFPyx5esO2k5+Z62PYgS1V9TRZsxBgzxYW+kP3sj/UlOTMmJHQBORv08qcB9KeDnvXV+PuZ9ww1pnjcfDB/I8bhQjseFEp+QSIWKuaMpyldwIj7h8dPLjNHGoxVTJo+iW49BPHxYdFMqBw7pTUjUVkKitpKUmIxzntjiZKT+T4hPzJfn2TaVK1ekokt5QqO3ceRUCE7ODuyLDDBYgqEoMLW6KC9J8Sn5zm/vZEdygfPntdG1XUrntF3snexYsW4R00fO5frv6nU0JMUn45C3zeVkmG86G+NtLgcnO1asW8y0kfNU1Q2g/JWCKJurXVPWzmBUZdZfKTw6eRi0WpSbiWQl/oGZY4X833P7T7JuXMXstaKvj8DE/dxE2+jPgqN9ORKTc/MyKfkm9uVe0R/PvcakFN1xtbC3tiIpLXc0YFLafexKlzBqG3IxMWdaOYCDtRWv29lQoUwpzDUa3KvZcz5ZvfU9lVs3EWVz2y5Gy+itFB6d0JfRlESyEv7AzEFfRq1KUXrCQu5vXYf20jnVdDtYW5GYlrt8XFLafeysrYza7jtvfFp56IUE3F91wMLshem2KlbkiMx/L1n6F+g6EtcpilJP/3pdUZR5QohXgdGAh6IodYB9QN4SdTfP317A10BjdB2iZuimkr8CXBFCXEXXqWmwdZh+VOOjAmtoZvO0x0/Z49yz8vyd/T577c6CHqM8w7Vlf5c2+3sURbkK/CWEcAfqA6FP0fa3STl9GdsqjthUtENjYUa1rk25FnYin41tldzGhEubety5Ury7km1Y60cH1550cO1JyN5w3urdBYD6DeuQlppOclL+xk5y0k3upt+lfsM6ALzVuwuhQbqpb5XzbCTRtoM7l3413CWvKDh78hwuVStS3sUJcwtzOnRrS0RIvv2piAiJpmsv3U7I7Tq7cyzmuCransSF0xeoUKU8jhUdMbcwx6OrG4fDDuezORx2mPY92wHg2rE1Jw6dykkTQuDWqTXhuyLVlA3AmZO/UKlqRcq7OGNhYY5393ZG8vwgXX10m1l4dfbgqD7PI0Ki8e7eDgtLC8q7OFOpakV+OvFzker9Yd0WOrn3ppN7b8KCIujeS7fbaL0GtUlLTc9ZsyublKSb3E2/R70Guh8p3Xt1Yn9wFACtPZrz/qhBDOs/hvsZxqeNSO25PDx3HvOK5TFzcgRzc0p5enA/+kg+G80ruQ+ArFo1J/PqNd1xu3JQQrfIvLCxpkSdmmRe+6PINW9eF0B3j3509+jHgeBIuvbS+XHdBrV0eZ5c4IFD8p/cTb9H3Qa6Haq79urIAX2eh4ccpJuP7p518+nEgX1RRa4f4MHPFzB3KY+5sy7fS3u5cS8qf76blcvN91KuzXh05Zoq2ozxw1p/Orr50NHNh9CgCHr46Haor9fw8X6enn6Xeg11ft7DpzNhwbq6qLVHc4aPepf3+o1Wxc+/+no9DRu1o2GjduzaFcKAfm8D0KTxm6TeSTW6FubjqFevJl9+sZjuPd4lJaVop62uX+uHl+vbeLm+zb694bytr//ffEL9n55+jzf19f/b+vr//Llfqfe6K83qedGsnhcJ8Um0d+tpUE6KAlOri/Ly86lzuFStkNN2ad/Nk6jQmHw2kaHRdOml2+OzbSd3Yg/p1tmzsbVm1cZl/G/h15yKO6Oa5mzdlfK0udp38yQyNH+eR4bG0EXf5jLU/SmfL/yKU3E/qaobQHvlAmb25RHlHMHMHIvGbrpOyzxknjiMefV6AAhrWzSOFchKTtBNb7XQb3pSyhqzV2uRlXhdFd2m7Oem2kZ/FtxaNmXXvgMoisLps+ewti6NXbmytGjSgMOxJ7iTmsad1DQOx56gRRP1Bq7UdLTl2u173Lhzj0faLEIuJuJWzXDplau37pJ6/xF1nXKn8dd0KEPqg0fcuqd7iBb3xy2qvqLOhjkA2svnMXMsj7DTl9Gm7rpOyzxk/njIsIymJICZOaXHzOFhTCiZsQdV0wxQ06kM1/66y43b+jw/H4/r/xmuQ3/1Vrouz50NZxftOyenlT9PFEUpkldx8NgNbV4A9gNbhRD/UxTlpn6DntKALZAGpAohnNB1VhrscK7vtKygKEq4ECIG6IduCngfwFNRlDi93avAHmC2/nvzrn68GPhSCNFHUZQ0IcRLQE9gE/CqEKKqoiiXgf7A3/0V11TfSXoD6AWsfNZrM8JavabvFEXJeprx30XRZnF4xno6bJqE0Gi44B/FXxdv0GDCW6ScvsK1sBPUHNSO8i1rkpWp5cGdu0SN/Sbn872PrMDCpiRmFuZU8mpIcN/F3P5Vvd0/w8OicW/bmugfg8jIuM+Ej3J3Sw2OCqCDa08Apk2Yx6dfzMfKyoqI/TFE7Nc1SCbPGkO1/6tMVpbCjT/imTJ+ntHzPG+0Wi0LpyzjG7//YWamYYfvHi5duMKHk97j59PniQyJZvvm3SxaNYugowHcuZ3KxPdzd2QNiduBtU0pLCwt8OjgyjCfUVy+eFUF3Vn8b8ZKlm5ajEajIdh/H1cv/s67EwZy4fRFDocdIcgvmKn/m8ymmPWk3k5j7ogFOZ+v27QOKQk3SbiWUORaDbVrmT95Kd/6f47GTMP2zbv57cJlRn48jLOnzhEREs3WTbv45Is57Du2jTt/pTL+fd0IwN8uXGZf4H72xPijzdQy7+MlZGU99+L4WCLCYnDzbElE3C7uZ9xn0qjZOWl7Ivzo5K57XjNj4kKWrJyDlVUJog4cInK/7gfm7MUfY1nCkg1bdVM+T/14hukTFhicR2rXo83i9qcrKffZJ6Ax4+6eYDKvXMXmvUE8OneR+zGHse7VA6uWzUGrJSs1lb/m66YbWlSuRJlRw3WPswSkbd5C5iV1HpBkE7X/EK09WxAau4P79+4zdfTcnLQd4Zvo7tEPgDmTFrPw81lYlSxB9IHDHDyga3iv+Xw9K9Ys4q1+XUi4nsSYocZ3PX/uaLO4tXgVDl8tAo2G9MAQHl36nZc+GMiDXy6SEXUEmz7dKOXWDDK1aFPTuDlzac7HHdctx6JyRUSpklQI2czN2cu5f0SdH5cRYdG4t21J5PE9ZGTcZ9LI3B2Z90bqOjwBZkxYwNJV8wz8fM4nU7AsYckP274GdBtbTZ/w+J1nnydBwQdo396DC+cOcS8jg6FDx+WkHY8LpWEj3YOpxYum0dunO6VKleTq5eOs+24zc+ct55NFM7C2Lo2fr65t8McfN+je490i1x0edhCPtq2I+TGY+xkZjPsoTx0ZtRUvV13n7NQJ81iur/8j90cTvj/6cV+pCqZcF2m1WhZNXc5XvivQmJmxU992GTFpKD+fOk9UaAw7Nu9hwaqZ7D6yhdTbqUx6X1cWeg9+G5cqFRg2dhDDxg4C4IPeY1UZ8a3Valk49VO+8v0MMzNNHt3v8cupc0SGxrBj824WrprFniO6NtckfZsrV/e7DBur8+vhvceoNlKdrCwyNq2k9PjFoNHwKHofWfG/U6LbQLRXL5J56giZZ+Mwr9UA6/lrQcnivv9qlLupmFd6E6vew3VTVYXgwb4Asq6rUx+Zup+bYhsdYOKsxcSd/Inbt1Np060/I4YMIDMzEwCf7h1p3awR0Ufi6NBrMCWtrJg3dSwAZWxteH9QH3oPHQ3A8Hf7PnHToOeNuUbDx+5vMGLHCbIUha41y1PtFWu+PPIbNextczo1911IwOt1x3zT3s00gnGtXmf49uMoClS3t6VHrQqPO9XzJyuLjA0rKT3xE10ZPRhM1o3fKdFjENorF8g8eYTMM3GY126I9eJ1kKXlvt9qlPRULJp7YvZ6HYS1LZatvAC4t3oJWdcuPeWk/xxzjYbJnrX4YGssWVkKXWtX4P/K2fBlzAVqOL6Em75TM/hcPO3fcDZYauDGnXskpmXQoKJ6I3clpoMwhbU2nhUhxGwgXVGUZfr3fdGtc6lBNzV8OHAc3VTuBsBlIBPYqijKRiHEdaCWoii3hRAlgHB0HZMaYD26qdmRgIuSJ+OEED8B76LrKP0G3cjHbsDvwGR92kO9hiWKovgKIdoBS9DtYn4MGKEoysMCGobq/x6jP891oBbQEN3GRreBmnpN2bu0P8u1NQXmK4riqf9eS+AvdOuBPnUBzDUV+puk08y7d7q4JRQKWwv1nvg9b8pZWD/d6F9I0sN//9Sdx/EgS70NAiQ6ol9VeX3K50ibS+pNjXqe7HNWZw22osD9j2cfifhv4o809aZdPm8crU23jNqYlypuCYXCUmO6YyXUXCvxeRLdwXTbi033mm67y0zFndqfJyd/3lzcEgrNo4AVxS2hUDw6/EtxSyg0lq51i1tCoSk5dLmKi7H+u2ns7FokFVxsfJTqeWy6rQwjKIoyu8D7zYCxKD3gMZ+vkOfvB0ALI2YVjXyuTp631QskL9K/Cn4mFCPTuAto+NZYmv5pxV1FUXoa0fcs13YU3Rqi2bwJxD5LJ6ZEIpFIJBKJRCKRSCQSiURSHLxQHZmSv48QYhq6HdMN1vmUSCQSiUQikUgkEolEIpGYNqY648AYsiPTBFEUZT+6NUCfx3ctANRZyE4ikUgkEolEIpFIJBKJRKIqL9Kykqa5qIdEIpFIJBKJRCKRSCQSiUQi+U8hR2RK/jYXzLXFLaFQmOqmOaa6iDiA1kSf+pjyJgX3tQ+KW0KhKW1esrglFIqfL9sXt4R/gGlu9nMq0a64JRQac82t4pZQKEqYWxS3hEJjbaKxBcDa3Kq4JRSKWw/Ti1tCobEvUaa4JRSK3yNM18+1yu3illBoXjLR3xemumEOgEXPscUtoVCk+g4ubgmFxjzJdDf8k+SS9QJNLTfdHhKJRCKRSCQSiUQikUgkEolE8p/BdIcdSSQSiUQikUgkEolEIpFIJJInItfIlEgkEolEIpFIJBKJRCKRSCQSFZEjMiUSiUQikUgkEolEIpFIJJIXlBdpjUzZkSmRSCQSiUQikUgkEolEIpG8oCgvUEemnFouUYXXXesy6cCnTI5cgfsHXQzSWw/xZmLYUsYFf8L7m6bxcvlyOWlD109m3k/fMnjtRDUl59DCvSm7D/kTdDSAISMHGKRbWFqwbPV8go4GsDl4Lc4VnQAo87It67Z/QezlcKYuHK+2bACauzchMMaX3Ue2MPgj49qXfDOX3Ue2sDFoDc4VHQFo2roRviHr2BrxA74h62jcooGquhu7NWLTwe/xjdlAvw97G9U9+6vp+MZs4Jvdq3Cs4JCTVq16Vb7atZIN4Wv5fv8aLEuou9OuqeY5wKxFHxMRt5vggwHUrPOGUZtadasTHL2ViLjdzFr0cc7xKbPHsv/oToIPBvD1hhXY2NqoJdtky+gr7nVpcWg5LY9+RuWRhnGxwjueNItcQtMDi2m0azalXysPgLAwo+Znw2kWuYRm4Z/wcvMaaksHYNqC8YQc205g5GZq1H7dqE3NOm+wK9KXkGPbmbYgN4/LvGTL2oBV7Du6jbUBq7Ato56/2LvXoU3MMjyPLOfVjzobpFd+pw3uEYtx37+QVoGzsNHnO4Bt9Yq03jMHj6gluEcsRqNyfJmxcCL7Y3eyO9KPGo8pozXrvMGeKH/2x+5kxsLcerN9F0+CordwISmOWnWrqyU5h6XLZvHTmUiOHQumXr2aRm3q1a9FbOw+fjoTydJls3KO165dnfCI7cTG7iNg67fY2FirJdtk/byZW2O2Rm9k+6HNDPyon0G6haUFC7+ezfZDm/luz9c4VdDVRTXqVWdT2Fr9ax1u7VuppjkvMxdOJDw2kL1R/k+sj4IO+hMeG8jMPL4+efYYQo9sY2+UP1+tX4aNrTr+0tStEX4H1xMQs5EBH/bLbf7sAAAgAElEQVQxSLewtGDeVzMJiNnIt7u/zGm7OFZwIPK3fawPXcP60DVMWqz+jszWrm/y+oGveD3yG+w+ePuxdmU6NKfO1d2UrP1/Oces3qhMte1LeS30C17dtxKhclycvnACYbE72BXpS406jy+ju6P8CIvdwfSFE3KOt+/Shr3R/pxPilU9Lpqqvxy6epNu62Po8l006+KuGKQvizqPz8Yj+Gw8QtfvY2j1ZXhOWkJqBh9s/5Ee6w/RY8Oh/2fvvMOiuNo+fJ9dKUqLBVhQUTGJMbEm9gYoCnYxsRtj1BhjjLH33qMmppiiiZrXxIK9omABFXvD2I1d6dgoAsJyvj9mgV1Y1PjCEt5vby6ua2fm2ZnfPHvanHnOOUQ8STaldCbN+YZmbbvTqfcgo8ellMxZ9DOtu/bDr89nXLp6PevY1oA9tOnWnzbd+rM1YI+pJGdhWa8eZf5cSZnVq7Dp1TPX8eK+vjht20LpZb9RetlvFG/bNuuYc/C+rP2vzZ1tStmo3atTfNBXFP9sARYN2+U6bundE+sBM7EeMJPig+ZTYuTPWcesuo+ixMifseo6wpSSzRQR/pUdmUIhVAjRWm9fVyHE7gK63gAhxLcvYfeWEGKXEOJvIcRlIcRaIYRTQWh6jgZ3IUR3vW1vIcQTIUSYEOKKEGLeS5zjpe43vxAqgd+Mj/mt71csaDmK2h0a4fx6WQOb8Eu3+bb9RL5pPZa/dh2n7fjsAjpkyXbWDP/JVHINUKlUTJo3is96DqdD0x608WuF+5sVDWw69+xA/ON42jTowh9L1jBi8ucAPEt9xg/zlrJw2g+FoFzRPmHuKAb3HIlfs574+nnn0u7Xsz3xjxNo37Arfy7xZ9ikwQA8fviEoX3G8IHXh0z+chazF08xqe4Rs4cyqvd4PvTqh3en5lR8o4KBTdserUl4kkiPJn1Y9+tGBk38BAC1WsXk78ezcNwi+jTvz9AuI0lP05pUe1H0OYCndxMqurvhVbc940fMYNbCSUbtZi2cxIThM/Cq256K7m54tGgMQGjIMXwav0/rZl24deMOg4f3N4nuIptHVYKq8/pxpuc8DjcdiYtf46yOykwiNx3mqOcYjrUYx+0ft1NlutJJW653CwCOeo7hdNfZVJnWG4QwqfxmLRpRwd0Nn/qdmTJyDlPnjzNqN3X+OKaMmoNP/c5UcHejafNGAHwy9COOHTyJb4P3OXbwJJ8M/cg0wlWCmnM/5mjP+exrNppyfo0MOioB7m86QrDXOIK9J/D3j9upNq03AEKt4r0fPydszDL2e4whtPMsMtLSTaMb8PBuTAX38njX68TkkbOYMX+8UbvpC8YzaeQsvOt1ooJ7eZq1UHz+9+XrfN53NCePnjGZ5kx8fDx5/fVK1KjuyZAhE/j2O+MPUt99N4shQyZQo7pi36qVJwA//jSPKZO/ol49X7ZvC2TY8IEm0V1U07lKpWLMnOF82Ws0XT370KpjCyrlqEc79mhL/OMEOjfuyepf1/HFJOXB/sbVm/TxHUivlv0Z2ms04+ePQq1Wm0R3Jp7ejano7kbzeh2ZOGIWMxYYT+szFoxn4ojZNK/XUVcfKX4PDTlG6yZdaevRjVs37vLZsH4FrlmlUjFy9peM6D2OHl59admpRa62S/sebUh4kkCXJr1Z++t6Pp/4adax+3ci+KjVJ3zU6hPmj1tU4HpziKfsjEHc6juNay0/57UOzbB6vXxuM5vilO7bnqSzV7J3qlWUXzSC8Ik/cq3V59zsPgFpwnaXh3djKrqXp2U9PyaPnM3055SLk0fOpmU9PyoalIs3GNJ3DCePnjWZZii66UWbIZkXfJnFnd5lY5/G7L4ayY0HiQY2ozzewr93Q/x7N6R7LTdavJ79qDw58AIfvVeRTR815s/u9SlZwtJk2gE6tWnJL9/MyvP4oaMnuXs/ggD/ZUwbM5SZCxcD8CQ+gZ9XrGbNr9+y5tdv+XnFap7EJ5hKNqhU2A//kkejxxLX5yOsWzRHXaFCLrPk/cE86D+AB/0HkLxzZ9Z+mfosa//j8RNNp1sILH37kLJ2IclLxqF+pwGijKuBybO9q0n5bTIpv00m7dQe0q+ezjqWdiyA1G1LTKf3/wEZUhbIf2Hwr+zIlMpySoOAb4QQ1kIIG2A28Pl/c14hxCsPpRdCFAd2AD9IKd+QUlYFfgVK/4NzqHNsv4oedyBniFqwlLIW8C7wvhCi/iuct8Bwq/U6D+5E8fBeDNo0LWHbj/JOqzoGNjeOXiIt5RkAd85ex0FTKuvY9SMXSU0y7Ru7TKq/+zZ3b93n/p0I0tPS2bVlD819mxnYNPdtytZ1AQAEbQ+mfhPl3pKfpnD2xDlSU5+ZXDdAtdpvc+/WfcLvKtp3b9mLp49hZIWXT1O2rdsFwJ4dwdTTab9y4Rqx0XEAXL9yE0srSywsTfOGvWrttwi/HU7k3UjS09LZtzWYJj6NDGyatmrE7vVBAITsPMB7Td4FoK5HHW5cvsmNSzcBiH8UT0ZGhkl0Q9H1OUDL1l5s8t8OQNip89g72OHoXMbAxtG5DLZ2Npw99RcAm/y306pNcwAOhRxFq1UeXs6e+guNi2ne8RTVPOrw7us8vRVF8p0YZJqWqC1HcPI1LBe1idnlnrqEFZmjQWzeLMvDQxcAeBYXT1r8U+xruZtMO0CL1h5sXac0ks+dvqCkFyfD6tDRqTS2djaEnToPwNZ1O/Fu46F839eDLf47ANjivwPv1p4m0V2y9usk3orm6V3F7/e3HEXjYxj9nJ7T7zrHO3nWIP7SXeIv3QUg7VEiZJiu8ebt68EWf8XnYacvYOdgm0cetc3y+Rb/nbTU+fbG37e5deOOyfTq07ZdK1av2gTAyZNncXCwQ6NxNLDRaByxs7PjxAmlo3X1qk20a98KgDfecCc09DgA+/aF0rFja0xBUU3n79Suyr3b4YTr6tE9W/fh4dPEwKaZTxN2rlfiA/bvOEBdXT2ampyaVZZbWVkWygqn3q092bxO8VvY6Zerjzav20HLNl6A0pGZeQ9hp86jcS34+ujt2m9x/3YEETqf7926n2Y+jQ1smrZqTMD6QACCdx6gjs7nhU2JWm/w7E4kz+5FI9PSebz9IPatcj9KOI/sReySTcjUtKx9dk1rk3LlNimXbwOgfZwAJmx3tfD1YLO/Ur+fO30BOwc7HJ1z5FFnwzy62T8gKy8WVrlYVNPLhagnlHcoQTmHElioVfi8qSHkRkye9ruvRuJbRRkFc+NBIlopaVBB+X1KWBajuIVpX5LUqVUdh+eMGAoOPUYH3xYIIahZrSoJCYnExj3k8PHTNKxbGwd7Oxzs7WhYtzaHj5/O8zz5jUXVt9CGh6ONjIT0dFL27ce6SeMXf7GQUblWJuNhDPJxLGRo0V46RrE3807Hxd5pQPrFo1nbGbcvIVNTTCHVTAEjhPAVQlwVQlwXQuR6KyyEsBJC+OuOHxdCVHzROf+VHZkAUsoLwHZgLDAVWCmlvCGE+EgIcUIXgfiTEEIFIIRYKoQ4JYS4KITICmUSQtwXQkwWQhwG/IQQw4UQl4QQ54QQf+a8rhDiTyHEd0KII0KIm0IIP92hD4GDUsoAPY37pJSXc0Y4CiF2CyGaCCGKCSEeCyFmCSFOAPWM6HlDCBEohDgthDgohHjzBTrmAV66+x+aw2dPgXNAWd05ygghtgkh/tKdp5qR+3UWQmzS+e6EEKLBP/ypXoiDc0keRzzI2n4c+QAH55J52tfv6smVkHP5LeOVcNI4EhWRXUFHR8TglOPhy8nFkajwaAC0Wi2JCYm8VsrBpDqN4eTiSFREdNZ2TGQszi5GtEfoa0/Kpd27nRdXLlwj7VkapsBRU4aYiNis7djIWMpoDB9gymjKEKP7XbTaDJLik3AoaU9593JIJF+vmsey3b/Q87NuJtGcSVH1OYCzixOR4dnaIyOic3VGalyciNS7v6iIaJyNdFh27dmJA/sOF5xYPYpqHrXWlCJFr1xMiXiIld4LnEzKf9yKJse/483Jvbgy8XcAEi7dxdG3DkKtoribI/Y1KmHt+tLv1PIFZ41jjrQQkystOLs4ERUZY2ij+21KO5YiNka5/9iYB5Qqk3edkJ8UdylJsr7fIx9S3CW33yt93JKWxxbxzuSe/DVxJQC27hqQkoZrxuEZNJvXP889RKogcc6V/7L9mWWjMSyDoiKN51FT4+rqzP37EVnbEeFRuLhqDGxcXDVEhEdmbYeHR+LqqgylvHTpGm3btQSgc+c2lCvnYgLVRTedO2rKEK1fLkbG4pizLtKz0Wq1JMYn4aArF9+pXRX/4P+wZv8K5o39OqtT0FQ4uzgREW7od00O/RoXw7I/0shvA/BBr44c2Hek4MTqcNRrl4BS/zvmaLs4Gvg8g8T4RBxK2gPg6qbhP4FL+WnDt9SsV73A9epj4VyatIi4rO20yAdY5OgMtH7HHUsXRxL2nzTYb+VeFiRUWjmdN3Z8i+OnnU2iORNnF0eiIqKytqMjonHW5MijGieDcjE6MjpX28zUFNX0EpOUgrOddda2s501sUmpRm0j4pOJeJJM3fJKHXv30VPsrIoxcnsY3VcdZdGhq2hN+DLwZYiOfYDGKft3cHYqQ3RsHNGxcWicstOMs6Oy31Soyjiijcl+NtLGxqJyzJ2GrT2aUXrFMl6bMR2Vnl5haUnppUso9fNPWDVpkut7BYWwK4lMyG5zyfiHCDvj9aCwL414zZGM25dMJe//JbKA/p6HLpjvR6A18DbQQwiRc16s/sAjKeXrwCLgqxfdy799sZ/pwBngGVBH1xHnBzSSUqYLIZaiRCeuBsZJKR/qohyDhRAbpJSZOSFJStkYQAgRCVSQUj4TQryWx3WdgMZAdWAdsBmoBrzKqxcH4IyUcpLu+jn1BAMDdJ20jYHFQKvn6BgHDJFSdtJ93zvzQkKIUigRm6G6XTOB41LKDkKIVsDvgGHID3wPzJdSHtP1fO/Q3asBQoiBwECAlqXqUMPu9ZwmeWNkyGNeL/jf7dSEcjXc+anbjJc/fwEijGnPaYOx+yv8itnYSNOcul5kU7lKJYZNGsygbsPyW17eGBshm0u38d9FrVZTvW41BrYZTEpyKt+uW8jV89c4HWqaIUNF1ue8rHajRgabn48YQLpWy5b1O3PbFgBFNo8aHQmeW9O9FUHcWxGEpnNj3If7cWHoz0SsDsb2jbLUD5pDyv04Hp+8hjRxR4Pxcl2+hE1BCXpJXiINA9xasYdbK/ZQzq8RVYZ34szQXxDF1JSqX4UDvpPRJqfSeP1EHp+7RVzoRRMIzyOtv0zZWOhO/++1fzZoDAsXTmX8+KHs3LmXZ6Z6yVNE0/mr+jtT+MWzl+nm9REVX6/AtO8mcCT4OM9MGLn+Utn0Je5x8PD+aNPT2bo+IJdtfvPKaRx4EPOQTvW6E/8onirV3+Sr5TPp6fUxTxOfFpRcQ17kcCFwnTyAe6OMzEqlVmNT923+7jCCjORU3FfPIvn8dRKP/FVwevUoquVikU0v/8BtgVejaPGGM2qVch/pMoOz4Y9Z06sBGjtrxgb8xbZL4fhVK1dAYv85xtKFEMJomW60DC0oXuLZKOXIEZL37YO0NIp36IDDhPE8GqbMLRnbpSsZDx6gdnGh1LeLeHjzJtqICCMnNQF5pKFi7zRAe/lk4Veg/+MU0jDwesB1KeVNACHEWqAjoN9r3RGYpvu8AVgshBDyOYX1vzYiE0BKmQT4A39IKVMBb6AucEoIEQZ4AJV15j2EEGdQOj6rovT2ZuKv9/ki8KcQoheQV0t4i1T4C11043/BM5QOSH38AXQdqQ2Ajbr7+RHQnzjiZXV4CSH+AqKAzVLKzFd8TYA/AKSUQYCrbpi+Pt7AL7rrbwFK6obRGyClXCqlrCOlrPOPOjGBJ1EPeU0vWug1l9LExzzKZfdG42q0GNKJFQMWon1munnHnkd0ZIzBkCRnVydio2Jz25RVokbUajW2drY8eRRvUp3GiI6IReOavQiOk4sjMVFxedoo2m2ytDu5OLJo+VwmfTGD+3fCTaY7NjIOJ9fst4iOLo7ERT/IYROLk+53UatV2NjbEP8ontjIOM4d+4snj+JJTUnl2P7jvFntDZNpL2o+/7B/N3aG+LMzxJ+YqFhcymZrd3F1JjpHWo+MiMZF7/40OWw6d29P81bNGPap8TmqCoKimkdTIh8aRFFau5YiNSp3uZhJ1OYjOLauC4DUZnB1ykqOtRhH2EcLsXCw4enNqDy/m1/07NeFzftXsXn/KmKi4nKkBSdicvo9R1SvxtWJmGjF5kHsw6whuo5OpXkYl/e95yfJEQ8pru93l1IkP8fv97ccxUU35D854iEPjl7m2cMEtMnPiN4Xxms1KhWo3l79urAteDXbglcTHRWb2+fRhuVLVGSMQRmkcXHO9buYioGffsjRYwEcPRZAZGQ05cplN29cy2qIiow2sI8Ij8S1bHakZdmyLkTqIh2vXbtBhw59aNK4PevXbePWrYIbCvq/kM5jImNx1i8XXRyJy1kX6dmo1Wps7W1ylYu3r98h+WkylasUbDoH6N2vK9uD17A9eA0xUbG4ljX0e876KCrCsOx3yfHbdO7WDq9WTRk+yPh8z/lNjF67BJT6PGfbJcbA5yps7W2JfxRP2rM04nW+v3r+GuG3I3BzN13nTlpUHBau2VFoFi6lSYt5mLWtsi2O9ZsVqLx2Dm+F/kaJ2lWo+Nskild/nbSoOBKPX0D7KB6ZkkpC8CmKV6ts7DL5Rq9+XdgavIqtwauIiYpFoxfd7ezqnJX/MomKjDYoF51dnHO1zUxNUU0vTrbWRCdkD/WNTkjB0cbKqG3gtaisYeUAzrbWVHG0o5xDCYqpVHhVduJKjAnnmXwJNE5liIrJThvRMXE4lSmt25+drqJjlf2mIiM2FrVehKXa0ZGMOMM0LOPjIU3p2kjesQOLN9/M/v4DJW1pIyN5FhZGsTdM82wkEx4h7LL9JOxLIRON14Pqtw2HlZspWgghBupG+Gb+609mXha4p7d9n9x9W1k2Usp04AkvmMLxX92RqSND9w/K+4jlUspauv8qUsqZQog3gC+B5lLKGsBuwFrvHEl6n32AX1B6hk/lnLdSh36MfOY7kItAXssIp2PoS/1rJxvpSc7UI4A4vfupJaXUj4Y0psMYwbr7rgEMFUJUz+M7xs4hgHp61y8rpczXCSnvnbtBmYoaSpVzRG2hplb7hlzcYxjc6vpORd6fM4AVAxaS+KDwOwEzuXD2Mm7u5Snr5kIxi2K07tSS4MBDBjbBgYfo2LUNAK3ae3E89FRhSM3FxbDLuLmXy9Lu28mbA0GhBjYhQYfo0FWZa6xlOy9OHFZ+Fzt7Wxb/uZDv5vxC2MnzJtV9JewK5SqVxaW8hmIWxWjR0YvQIMNhYaFBR/HtogQue7b14MxhJeLy+IGTVK7qjpW1FWq1iloNanD7b9PNfVTUfP7HMn/aenajrWc3ggKC6dxNWcG5Vp3qJMQnZs3ZmUlsdByJiUnUqqMUMZ27tWfPrmAAmjVvxKChH/NJry9JSTbdfDZFNY/Gn71BCXcNxd0cERZqNJ0aERNoWC6WqJT9cObYsjZPbyrDblXFLXVzN0KpZtWR6VqSrhV8x/fq5evxa94Lv+a92LcrhI5dlRUxa75XTUkvMTleOMQ8ICnxKTXfU6q1jl3bsm/XAQD2Bx6kUzdlaHanbu3Yt/tAgesHeBx2A1t3DSV0fi/XqSFRQYZ+t9Hzu8a7Nom3lE7imJC/sK/qhrq4JUKtonTDqiRcu1+gelctX08Hr5508OrJ3l0hdOqm+LxWps+N5NGkxCRq6XzeqVtb9prItzlZuuQPGjZoQ8MGbdi+PYievZQhp3Xr1iY+PoGonB1TUbEkJiZSt25tAHr26szOHcpcyI6OSltWCMHYsUNY9tuqAtP9v5DOL4Vdwa1SOVzLK+Viy44tOBhkON3HoaDDtO3iC0Dzdh6cDFXmJnUt75K1uI+mrDMVKrsRcb/gX5T8uXwd7b160N6rB0EBIfh1VfxW672866OkxKfUek+pj/y6tmPvrhBAqY8GDu3Lp72Hmaw+uhx2hfJ6bRfvjs05lKvtcoQ2XXwA8GrrwWld2+W1Ug6oVMpjhKubC+UrlSXibiSm4um5v7Gs6IpFOWeERTFea9+M+D0nso5nJDzl0ru9uNJkAFeaDODp2avcHqCLvDxwhuJvVURYW4FahU39aqT8fe85V/vvWbV8PR29etHRqxd7d4Xg102p32u+V43E+ERic778jn5AUmJSVh7169bGZHkxL4pqenlHY8/dx08Jf/KUNG0Ggdei8Kyce0qH2w+TiE9Jo6ZL9jQ+7zg7EJ+axsOnSnT3yXsPcS+dM76mcPFs0oBtu/chpeTchcvY2trgWKYUjeu/x5ETZ3gSn8CT+ASOnDhD4/p5dQvkP2lXrqIuVw61iwaKFcO6RXNSDxumF1Xp7GlyrBo3Iv2OMp+3sLUFC2XOfeHggEX1aqTfvm0S3RkRN1GVckY4lAGVWumsvJZ7lJwopUFYlyAj/LqRs5jJTwpqaLl+0Jvuf6neZY3GFOfYfhkbA/7tQ8tzshfYIIT4TkoZJ4QoDdgA9kACEC+EcEHprMy1wrmu07KclHK/ECIU6AWUeMlr/wGMEUL4Sil3687XBrit++8vlBjzCuTd4WmAlPKRECJSCOEnpdysm++zupTyeRNEJgBGZymWUl4RQswHxqCb0xPlHufqhqDfl1Im5QiF34uyiNIi3T3VklKGvYz+lyVDm8HmKb/zycrxCLWKk+tCiP77Pj7DP+De+Vtc2nuaduN7YlXCmg9/+hKAx+EPWPHJQgAGr5uKU2VXrGysmXR0MevGLuXaQdMMWdFqtcwZv5Ala79DrVaxec0Obly9xedjPuHiuSuEBB5i0+rtzF08lYBj63nyOJ7Rn07O+n7gyc3Y2pXAwtKC5q09GNhtKDev3TaZ9rkTvuHnNYtQqdVs0WkfPGYAF8OucCAolM2rdzB78RS2H11H/ON4xnyqTC/bvd8HuFUqx8DhfRk4vC8An3UfbpJoEq02g0WTfuDr1V+hUqnY6b+L29fu0H9UX66cu8rhPUfZuTaASd+PZ03oSuIfJzBtsLICYeKTRPyXbuDXgJ+QUnJs/wmO7jte4JqztRdNnwME7zmEV8smhJzaQXJyCmO+yF41fWeI0uEJMHnUbBYsnom1tRUH9h0mZK/SUTv9q/FYWlnyx8ZfADh76jyTRuW9MmR+UVTzqNRmcGX8Ct5dOwGhVhG+Jpikq/epPKYL8eduEht4mvL9fSjdtBoZ6VrSnyRxYejPAFiWceC9teORGZLUqIecH/JjgevNyYG9h2nm3ZigE5tJeZrChC+zpwPZvH8Vfs17ATB9zDzmfD8V6+JWHNp3hIO6uep+/f4/LPp1Lu/36kDk/WiGDTC+GnR+I7UZ/DXhdxqtGYdQq7izJoSEq+G8NeYDHofdJCroDO79WuHYrBoyLZ1nT5I4o/N72pMkri8JwGP3LJCS6H1hRO/N1+ryuYTsCcXDuzH7TmwlOTmFcUOnZR3bFryaDl49AZg6ei5f/TANa2trDuw/zIG9SgdWyzZeTJk7mlKlS/Lr6u+4fPEa/boOMYn2wN3B+Ph4cf7CAZKfJvPpoNFZx44eC6BhA6Uj4ssvJ7F0yUKsi1sTFBRCYGAIAF26dGDgpx8q97o1kJUr15tEd1FN51qtlvkTv+X71QtRq1VsWxvAzWu3+XR0Py6fu8rBoMNsXbOT6d9PZNPh1cQ/TmDiZ9MAqFmvOn2H9CI9PZ2MDMlXE77hycMnJtGdScieUDy9m7D/5FZSklMYq5fWtwevob1XDwCmjJ7D/B+mY2VtxYF9RwjRpfVp88ZiaWXBfzYoeTfs9Hkmj5pToJq12gy+nvQ9366ej0qlYof/Lm5du80noz7m8rmrhO45wva1O5n6/QTWh/5J/ON4Jg+eCUCtBjX5ZNTHaLVaMrRa5o9fRPxjE0aqaTOImPIL7iung1rFo3V7Sf37Ls7De5F8/m/i957I+6vxScT+toU3tn0DUhIffIqEYNO9LAzZcxgP78bsPbGF5OQUxg+dnnVsa/AqOnopeXTq6HnM+2Ea1tZWHNx/RK9c9GSyrlxcuvpbLl+8Rv+uXxS47qKaXoqpVIz1eovBm8+QISUd3ylL5dK2/HT0Om872Wd1au6+GolPFY3B8Gu1SjCiaRUGbTqFlFDVyZ7OJh5WPnrqPE6e/YvHj+Np0ak3g/t/SHq6Mgqwm19bmjWsy6GjJ2ndtR/Fra2ZOWE4AA72dnzatwfdByjPqYM+7vncRYPyHa2W+G+/o+TCBaBSkRywi/Tbt7Ht9zFpV6+SevgIJd5/H6vGjUCrJSM+gSdz5wFQrGIF7EeNVBbhUqlIWrUa7R0TBXnIDJ4FrsS6xxhQCdLPHUTGhWPRrDMZkbfQ/q10ahZ7pyHpl3I/r1l/OBFVaRewtKb4F9/ybOcytDdNG2BjJl+4D5TX2y4H5JzbINPmvm6qSAfgIc9BFPYcIS9CCDENSJRSLtRt90TpqFOhDA0fBJwCVqJ0IN5EiZDcIKX8UwhxH6gmpXwshLAC9qN0BKqA/0gpFwghBuhshukWANogpdyiu16ilNJW9/ltlA4/d921w1AiQeOANShzS15ACY0dDxxDibjMmotTX49u2x34GdAAlsCfUsrZeekQQlgCQUBJYBnK3AL6c2baAH+jDFl/CqxA6VxNBAZKKS/kuF9H3fXfROnYDpZSPnd1+FEVe/y7E00e7E6+VdgSXgm1KAqB08axV+eapaBIEK/N16BkkxKflvRio38pNsWKZnr5hoqFLeGVGSpvFLaEV2KeynRTRuQ3o7VXC1vCKxGR9ODFRv9SytsW7sIe/w12RbRcfPgssbAlvDJOVoW/YOOrsMTCtrAlvNnYIIwAACAASURBVDIfJJkuAjW/KW1pwg6tfGTfpFxLIhQZLLoML2wJr8SDzv0KW8IrY+fjVtgSXhmbiStNOKHpv5s3HesUSD/OtdhTefpY1zF5DWgBhAMngZ5Syot6Np+jBPQNEkJ0BzpLKbs+75r/+ohMKeW0HNurURb3ycmHeXy/nN7nVJTFc3La/Kb3uXeOY7Z6ny+hRHsao3se+w0WFNLXo9u+aeyceemQUj4DPHOY79WzS8Jwns32Rs6tf7+xwAd5aDdjxowZM2bMmDFjxowZM2bMmDFThHnRCuMFck1lke4hQCCgRpkq8qIQYgZwSkq5DSVA7w8hxHWUSMy8+tay+Nd3ZJoxY8aMGTNmzJgxY8aMGTNmzJgxY6ZoIaUMAAJy7Jui9zkF6PJPzmnuyDRjxowZM2bMmDFjxowZM2bMmDFj5n+UjH/5tJL/hKI7+Z4ZM2bMmDFjxowZM2bMmDFjxowZM2b+32COyDTzjymqvd9FdREUewubwpbwymQUwjwc+UFhzB+SXxRVnwMkpRfNRZbiLdWFLeGVeZaWXtgSXolUddGdt72YKJrppaR10V1I5FlG0UznUHS1lyzCbZckbUphS3gl4tKL7qJWKlF0y/SEItp2STtyqbAlvDLxa4rmojmlNy0vbAmvzP0Wnxa2hFem0sTCVvDvoSg/4+akqPZJmTFjxowZM2bMmDFjxowZM2bMmDFj5v8R5ohMM2bMmDFjxowZM2bMmDFjxowZM2b+R5Eyo7Al5BvmjkwzZsyYMWPGjBkzZsyYMWPGjBkzZv5HKcpTkOXEPLTcjBkzZsyYMWPGjBkzZsyYMWPGjBkz/3rMEZlmzJgxY8aMGTNmzJgxY8aMGTNmzPyPIqU5ItOMmX/Emx41Gb3va8aELMLzsw65jjft34aRexYwfNdXfLJqIq+VLQOAy9sV+HzTdEYEKcdqtmtgaukATJ87joOndhJ4aCPValQ1alO95tsEhW7i4KmdTJ87Lmv/yAlDCDy0kV0H1vPnxiU4a0y3qmRjrwZsP+xPwLH19P/iw1zHLSwtWLh0FgHH1rN61zJcy7sA4FDSnuWbfuTEzf1MmDPSZHozqe9ZlzUH/4N/6B/0/rxHruMWlhbM+Hky/qF/sHT7j2jKOQOgKefM/uu7+D1oKb8HLWX0vGGmlk5jrwZsC13LjqPr6TfEuM/nL5nJjqPrWRXwG67lNQA0aFaXtYEr2Bj8J2sDV1Cv8Xumls60uWM5cHIHuw9uyDOdV6tZlcBDGzlwcgfT5o7N2j9y/OfsPriBgJB1/LHhF5xMmM4Bps4dS/DJ7ew6uJ53arxl1KZazarsOrSB4JPbmaqnffy04ew9toVdB9fzy8pF2NnbmUSzs1cNfA4twPfI11QZ0j7Xcfc+LWi5fx7ee+bguXUKdm+WBaBEuTL43VyB9545eO+ZQ+2vCmf1zilzxrD/xFYCDvg/3+cH17H/xFamzBmTtX/ctGHsObqJgAP+/Pyfr7GzN92K2BqvGrQ+tIA2R77mLSN+r9ynBT7759Fqzxyab52Cvc7vmZQoW5rO15dRZVAbU0kGoIlXAwKOrGf38Y0M+KJPruMWlhZ8s3Q2u49vZO2u5VnlOcAnQz9i9/GNBBxZT2OvwqlHZ8wdT+ipAPYc2vTcenRv6CZCTwUwY+74XMc/HdKX+w8vULLUawUtN4uims4bedVna+gath9d95y6aAbbj67jz4BfDeqiNYHL2RD8B2sClxdKXdTQqx4bD61i85E1fDSkV67jFpYWzPllGpuPrOH3nUtwKadof6dWVVbtWc6qPctZvXcFnq2bmlT3q9b/DiXt+W3jYo7d2Mf4QmhzAZTyqkn9w9/S4Nj3VPiiY552ju3q0zx6HXY13bP2VRjaiQbHvqf+4W8p5VnTFHINmDh7JIHHN7E1ZDVvV69i1OadGm+xLWQNgcc3MXF2to8dXrNn2frF7D62kWXrF2PvYJr6H4puG71Y9brYzv8d24UrsWrX3aiNRT0PbOctx3buMop/NgEAlVtlbKb8gO3cZdjO/hWL+p4mVK1gWa8eZf5cSZnVq7Dp1TPX8eK+vjht20LpZb9RetlvFG/bNuuYc/C+rP2vzZ1tStlMmvMNzdp2p1PvQUaPSymZs+hnWnfth1+fz7h09XrWsa0Be2jTrT9tuvVna8AeU0nOonijOpTdupxy23/HoV+3XMdtO7TCLXg9rv6/4Or/C7Z+rbOOOf80B7dDm3H+YaYpJZspIjy3I1MohAohWuvt6yqE2F0QYoQQLkKIACHEOSHEJSHENt3+8kII/3y+lrcQYst/eY7mQogGetuzhBDhQogwIcR5IUTb530/vxFCjBBCWOttBwohTFcj54FQCfxmfMyyvl/xdctR1OrQCKfXDR8MIy7d5vv2E1nUeizndx2n7XilcklLTsV/xM9802o0yz6aR/spfbC2L2FS/V7eTalYuQLN6rRl3PDpzP56klG72QsnMW74dJrVaUvFyhXw9G4CwJIfVuDT9H1ae3RhX+ABvhxtvBLKb1QqFZPmjeKznsPp0LQHbfxa4f5mRQObzj07EP84njYNuvDHkjWMmPw5AM9Sn/HDvKUsnPaDSbTm1D1y9peM7D2OXl4f492pORXfqGBg065HaxKeJNCtyYf4/7qBwRMHZh0LvxNB31YD6dtqIAvGfWty7RPmjuSzniPo1KwHrf1aGvF5e+IfJ9CuYRf+WLKWYZMUnz9++IQv+ozmfa/eTPpyJrMXTzWpdi/vJlRyr4BH3XaMHzGDWQvzTufjh0/Ho247KrlXwLOFLp0v/h3fZh/QxrMr+4IO8uWoT02m3dO7CRXd3fCq2/652mctnMSE4TPwqtueiu5ueLRoDEBoyDF8Gr9P62ZduHXjDoOH9y940SpB7Tl9Ce01n0CPMZTv1DCrozKTu5uOsKf5OPa2nMDVH3dQc1r2A33inWj2tpzA3pYTODt2ecHrzUGmz5vX68iEEbOYuWCCUbuZCyYwYcQsmtfrmMvnvk260MajG7dv3GHwMNN0xgqV4L05fTnYaz67PcZQoVPDXB2VdzYdIbD5OIJaTuDKjzuoNc2wI6XW9N5E7T9nEr2ZqFQqJn81hoE9vqR9k2607exD5TcrGdh80KsDT54k4Fv/fVYuWcOoyUMAqPxmJdr4taJ90+580v1Lpnw1BpXKtO+xm3s3pVJlN5rUacPY4dOY+/Vko3ZzF05mzPDpNKnThkqV3fDS1aMALmU1NPVsyP17EaaSXWTTuVIXjWJwz5H4NeuJr593rrrIT1cXtW/YlT+X+DNs0mBAqYuG9hnDB14fMvnLWcxePMUkmvW1j50zgqG9RtHF40N8OnlTKYf2jj3akvAkAb9GPVi9dB1fTFLaVdev3qSP7yf0atmPL3qOYsL80ajVapPpftX6/1nqM378ailfT19sEq25UAmqzOvPuZ5zON50OE5+jSmRo1wEUNtYU35Aa56cvpa1r8SbZXHq1IjjzUZwrsdsqnzVH1TCZNKbtWhEBXc3fOp3ZsrIOUydP86o3dT545gyag4+9TtTwd2Nps0bAcpLnmMHT+Lb4H2OHTzJJ0M/MonuotpGR6iw/mgoSQvGkzi2HxYNm6NyNWyjq5zLYtW+B4kzhpI4vj8pq35CJ5zkJfNIHN+fpAXjsO49GErYmE67SoX98C95NHoscX0+wrpFc9QVKuQyS94fzIP+A3jQfwDJO3dm7Zepz7L2Px4/0XS6gU5tWvLLN7PyPH7o6Enu3o8gwH8Z08YMZeZCpSx5Ep/AzytWs+bXb1nz67f8vGI1T+ITTCUbVCpKT/iC6METuO83ABtfLyzc3XKZJQUdIKLbICK6DSJx866s/U9+X0/spK9Mp/f/ARnIAvkvDJ7bkpVK7Okg4BshhLUQwgaYDXz+31xUCJHXkPZZwE4pZU0p5dvAJJ2Oe1LK3F34hU9zIGdowwIpZS2gB/C7EMKgNn/OvecHI4CsjkwppY+U0oSllXHK13qduDtRPLwXgzZNy7ntR3mnVR0DmxtHL5GW8gyAu2ev46ApBUDcrSjibkcBEB/ziMQH8diWsjep/lZtvNi4dhsAZ0/9hb29HU7OZQxsnJzLYGtny5mTysPtxrXb8GnTHIDEhKQsuxIlipsspLv6u29z99Z97t+JID0tnV1b9tDct5mBTXPfpmxdFwBA0PZg6jdRfpfkpymcPXGO1NRnJtGqT9Xab3H/djgRdyNJT0tn39b9NPVpZGDTtFVjAtYHARCy8wDvNXnX5DqNUa224vPwu4rPd2/Zi5ePoc89fZqyTefzPTuyfX7lwjVio+MAuH7lJlZWllhYWphMe8vWXmz03w7o0rnDc9L5qb8A2Oi/nVZtvAAj6dxEukHRvkmnPezUeewd7HDMod3RuQy2djac1Wnf5L+dVro8eijkKFqtFlDuXePiVOCaS9WuTOLtaJLuxiLTtNzbegxXH8PIp/TE5KzPxUpY8W+an9u7tQeb1+0AIOz0y/l887odtGzjCSgdPNk+P4/G1dkkukvVrkyCzu8ZaVrubj1G2X/g97K+75F0J4YnV++bRG8mNd59J6s8T0tLJ2BzkJHy3IOt/spDV+D2/TRoWle3vxkBm4NIe5ZG+N0I7t66T4133zGp/lZtvNigq0fPPLcetcmqRzfo1aMA02aPYfbUb0w6LKqopvNqtd/mXo66yNPHMDrRy6cp29YpD4x7dgRTL4+6yNLEddE7taty73Y44bo2QNDWfXj4NDGw8fBtyo51SkzFvh0h1Guq5OHU5NQsf1tZWZo0rfw39b/S5vqL1NRUk+nVx/7d13l6K4qUOzHINC0xW47g6Fs3l537uG7c+XEbGSlpWfscfesSs+UI8lk6KXdjeXorCvt3XzeZ9hatPdi6Tin3zp2+oORRp9IGNo5OpbG1syHs1HkAtq7biXcbD+X7vh5s8Vfy+Bb/HXi39jSJ7qLaRldXfouM6HBkbCRo00k7FozFe4ZtdEuvtqTu3QZPEwGQ8Y8ByIi6T0Z0uLLv8QNk/GNUdqaLrreo+hba8HC0kZGQnk7Kvv1YN2lssuv/N9SpVR2H54wWCg49RgffFgghqFmtKgkJicTGPeTw8dM0rFsbB3s7HOztaFi3NoePnzaZbqtqVUi7F0F6eBSkp5O0O4QSno1e/EUdKSfOIpOeFqDC/39IKQvkvzB44St5KeUFYDswFpgKrJRS3hBCfCSEOKGLPvxJCKECEEIsFUKcEkJcFEJkvcYVQtwXQkwWQhwG/IQQw3VRl+eEEH/qzFyA+3rX/kv33deFEGG6zwOEEBt00YZ/CyHm6l2jrRDijO6cQbp9tkKI33Vazwohco8j00MIMV0IcVIIcUEI8UtmR2ROvUKIysAAYLTOBwa5Uuc3AZTU2X8thAgG5gghygghtgkh/hJCHBFCVNNdY5ZOa5AQ4rYQopPuexeEEDszO0GFEC31oj5/FUJYCiGGA07AISHEXj2fv6b7PEZ3ngtCiC/0/HpBCLFM93vt0o/ozC8cnEvyJOJB1vaTyAfYO5fM075uV0+uhOSOdilfszJqi2I8uBOd3xKfi8bFicjwqKztqIjoXB0dGhcnoiKi87QZPfELjp3fQ6cubfl67o8FLxpw0jgSFRGTtR0dEZNruK+TiyNR4YpurVZLYkIir5VyMIm+vHDUlCFGT3dMZByOOXTr22i1GSTFJ+FQUungdnHTsCJwCYs3LKJmveqmEw44uzgSre/zyBicXByN2Dzf5y3beXHlwjXSnqVhKjQuTkTkSOfOOdK5c450HmkknR/9K4hOH7TlGxOl80xdkeF56wJdPs6RR3PeH0DXnp04sO9wwYnVUVxTiuTw7HIxOfIhxTW5y8XKfVvie/Qbqk/qQdik/2Ttt3FzpEXQbDw2TaJMfeND6QqSly8XY55rA9ClV0dCTOBzyO33p3n4/fW+LWl79BtqTurBGZ3f1cWteOvz9lz8epNJtOrjpMkuq0EpW5xzli0ax6x8oNVqSdCVLc4ujgb51lhdUNBoXJwNyhcljzrnsonMVb4oNi19PYmKjOHyxaumEZylqWimc6ccv3lMZGyu9KJvo9RFSbnqIu9CqIucNI5Eh+u3AWJx0uTo9NaUyaprtVotifFJOOi0v1P7bfxDVrI2+Hfmjl2Y1bFZ0ORX/V8YWGlKkarXTk+NeICVLqAgE9tqFbFyLcODPWdyfTdFr0xNjXyY67sFibPGMUfdHmO87RIZY2ijKwNLO5YiNkbRHxvzgFJl8n4+yU+KahtdlCyDfBibtZ3xMBZR0jB/qjTlULuUw2byd9hM/YFi1XN3iqvdq4C6GBkxpouwV5VxRBuTrV0bG4vKMXddaO3RjNIrlvHajOmonLKPC0tLSi9dQqmff8KqSZNc3ytMomMfoHHK/h2cncoQHRtHdGwcGr17cHZU9psKtVMZtFF6Po+Jo1iOl4EAJVo0oez6JTgtnIza2bTtEzNFl5cdWzQd6Am0BubrOt78gEa66MNiQOYkGeOklHWAmkBLIcTbeudJklI2llKuB8YAtaSUNYEhuuOLgf8IIfYLISYIIVwwTk3gA6AG0FsI4SqE0AA/A366c2bqmQLsllLWQ4mg/PoFnXXfSSnrAtUBB8BXt99Ar5TyBvAbughMKeUR/ZPoOjZTpJQPdbsqAy2klGOAmcBxKWUNYBrwu95XKwFtgPeB1Trt1YAMwFcIUQJYDrwvpawOlAAGSikXATFAUymldw4t9YBeQD2gITBYCFFDd7gK8K2U8h0gGehkzClCiIG6DupT5xKuGzPJG2FkiEkeHfe1OzWhXA13DizdbrDfzvE1un8zmPWjfzF9r78R/bkkGLXJNlow+wcaVG/JlvU76ftJ7jkfCwJhTFNOG56vuzAwqjuHprzu7UHMQzrX68HHPp/yw/SfmPrjRErYmnAqgpfQ/iKbylUqMWzSYGaMNu1Qilf2u57Jgtk/0LBGK7Zs2MlHA0yTzhVdufe9jPacGfnzEQNI12rZsn5nbtv8xtjIOyN578bve9jdcATnZ6/lrWFK8ZwS85iAOl+yr9VEzk37k3o/fk4x2+IFLNiQl0svub+X02bw8P6kp2vZuj4gX/XlyUv6/frve9jZcATnZq/lbZ3fq41+n2tLd5H+1PRRUy/Ke3nZIPMqL01bzr96+SKxLm7N0JEDWTjH9MNui2o6f7ky8fk2mXXRzNHz81ve83lxUZ2XeAAunr1EN88+9Gk9kI+/6I2llWX+azRGPtT/hcaLyggheGPGR1yftvKlvmvS4uWV/V5Qgl6OotpGf6k6VKVG5VyWpDkjePrTbIoPGGkwhFw4lKL4oPEk/7rAtD/ES2hPOXKE2K7defBxf1JPncZhQvZczbFduvJg4Kc8mTET+y+GoHZ1LWDBL4+xdCGEMOpeo22FguIl8ufTA0e51/pDwrt8SvLxszjOGm0qdf8vyZCyQP4Lg5fqyJRSJgH+wB9SylTAG6gLnNJFSnqgdNQB9BBCnAHOAFUB/Y5M/XkuLwJ/CiF6AWm66wTozrNM972zQgjD8QEKe6WUCVLKZOAK4IbSQRcspbyjO1dmB2IrYKJOZzDK0OvckzNk00IIcQI4p7uvzPFXufTmwWjdtb4C9IfDr5dSZug+NwH+0OkMAlx1w/YBAqSU6cB53fHMWXnPAxVRfPq3riMVYCVgOBYhN02BjVLKp7qh5lt0GgCuSynP6z6f1l0jF1LKpVLKOlLKOjXt/tmQkSdRD3Fwzf4ZHVxKEx/zKJfd642r0XxIJ34fsBDts/Ss/Va2xem3Ygy7v17H3bP/sBP1FenTvzu7Dqxn14H1xETF4FJWk3VM4+pMdFSMgX1URLTBkDHFJpacbNkQQOv23rn2FwTRkTFoXLPfSju7OhGbQ1N0ZAyasoputVqNrZ0tTx7Fm0RfXsRExuKkp9vJpQxx0XF52qjVKmzsbYh/FE/aszTidfqvnv+b8NsRuLmXM5n26IgYnPV97uJEbFScERvjPnd2cWTR8nlM/GIm9++EF7jePv27ERCyjoCQdURHxeKaI53H5EgvOdO5i5G8ALDVBOn8w/7d2Bniz84Qf2KiYnEpm1OXofbIiGhcnpNHO3dvT/NWzRj2ae4FRgqC5MiHFC+bXS4WdylFcvTjPO3vbTlKWV9lWFnGs3SePVKGbD3+6zZJd6Kxq6zJ87v5xYf9urIjeC07gtcSHRVrpFzM6XPDMiiXz7spPh8+yHRzTeX0e4kX+P2unt9Lv1uZmpN70O7Et7z5iS9Vh3bk9Y9bFrhmMCyrQSlbcuXPyJisfKBWq7Gzs+XxoydERcQY5FulLij4iIyP+ncn8MAGAg9sIDoqxqB8MVZ2REZEGeTRTJuKFctT3q0sQYc2cjQsEBdXZ3aHrM81fDS/+F9I59ERsQa/uZOLIzG56qJsG6Uussmqi5xcHFm0fC6TvphhkrpIn5jIWJzL6rcBHLOGuhvYZLUB1Nja2+Rqu9z++w7JT1Oo/JbhXLIFxX9b/xcmqZEPsNJrp1u5luZZVHY7XW1rjc1b5am9aSoNTy7G/r03qLFyDHY13UmNfIC1Xplq5VKK1OiHFCQ9+3Vh8/5VbN6/ipiouBx1e+6yMTpHlLTG1YmYaMXmQezDrLLE0ak0D+NyP58UBEW1jS4fxiFKZUfMqUo5Ih8/MLDJeBhL2pkjoNUiY6PIiLyH2lnXFrcugc2oOaRsWI72xmVTSicjNha1XnSi2tGRjDjDPCrj4yFNecxP3rEDizffzP7+A+U+tZGRPAsLo9gbb5hA9cuhcSpDVEz2vUTHxOFUprRuf3a6io5V9psKbXQsar1IY7VTGbQxOdLLk4QsnydsDMCq6puYMfMy/JPZ3jN0/6C801iui0SsJaWsIqWcKYR4A/gSaK6LNtyN3pyNQJLeZx/gF5QowVNCCDWAlPKBlHKVlLI3EEZ2h5s++uEQWpSIUIHxd4AC6KSn1U1Kec2IHbpox8UoUZ01UCIfM/Ub1WuEzAjNplJK/TFE+vee8/WE/nbmvWUA+pOfZOjd5z/led8x5st85f65G5SpqKFkOUfUFmpqtm/IpT2G83O4vlOR9+cM4D8DFpL0ILuSVluo6bNkBKc3HeJ8wPH8lpYnK5etpbVHF1p7dCFw537e766stF67Tg0S4hOJydmojo4jKTGJ2nWUQNf3u3cgKCAYgIp6kxq3bO3Fjb9vmeQeLpy9jJt7ecq6uVDMohitO7UkOPCQgU1w4CE6dlVW3m3V3ovjoadMou15XAm7QrlKZXEpr6GYRTFadGxOaNBRA5vQoCO06dIKAM+2Hpw+fBaA10o5ZC1i4ermQvlK5Qi/G2ky7RfDLlNBz+e+nbwJCTL0eUhQKB10Pm/ZzosTh5W8YGdvy+I/v+b7OT8TdvIvk+hducyfNp5daePZlaCA/bzfTZl5Q0nnCS9O593as2eXsXTuWeDp/I9l/rT17EZbz24EBQTTWae9Vp3qJMQn5nrwjY2OIzExiVp1lOkGOutpb9a8EYOGfswnvb4kJTmlQHVn8ijsJraVNJQo74iwUFO+YwMiAw3LRdtKep063rVIuKUMcbUsbZe1mIKNmyO2lTQk3sndoZzf/LF8He28utPOqzt7AoLx69oOgFrv5e3zpMSn1HpP8blf13bs3XUAUHz+6dC+DOw9zGQ+B3gYdhO7ShpsyjuislDj1rEB4c/xu6t3LRJ1ft/faSY76g1jR71hXPt1N5e/38r1FaZZAfT82Uu6ssUVC4titPFrZaQ8P0jHbsoagz7tm3NMV54HBx6ijV8rLCwtKOvmSgX38vx15mKBa/7PsrX4eHyAj8cH7N65nw909ei7z6lHExOf8q6ufPlAV49eufw3tap40LCWDw1r+RAZEY2vZ5es4aD5zf9COr8Ydhk393IGddGBoFADm5CgQ3ToqqzlmbsuWsh3c34h7OT5XOcuaC6FXaF8pXK4lle0t+rYgoOBhtoPBobSrqsyYKpFO09OhirDnV3Lu2Qt7qMp50yFym5E3IvCFPw39X9hk3D2BiXcXbB2U+ojp06NiAvMbg9qE5IJfXsAR+sO4WjdIcSf/pu/+swn4dxN4gJP4dSpEcKyGNZujpRwdyH+TMEGHaxevh6/5r3wa96LfbtC6NhVKfdqvldNyaM5yobYmAckJT6l5nvVAOjYtS37dHl0f+BBOnVT8ninbu3Yt/tAgWrPpKi20bU3r6DWlEU4akBdDIsGXkqnpR7ppw9TrGotAIStPSpNOTJiI0FdDJth03kWGkT6iYMm15525SrqcuVQu2igWDGsWzQn9bChdlXp7GkRrBo3Iv3OXQCErS1YKHMFCwcHLKpXI/32bZNpfxGeTRqwbfc+pJScu3AZW1sbHMuUonH99zhy4gxP4hN4Ep/AkRNnaFz/vRefMJ9IvXgVC7eyFCur+NzG15OnBwyf6dRlsn1ewrMhz27dNZm+/4/IAvorDF6102ovsEEI8Z2UMk4XNWkD2AMJQLxuWLgPSmemAbpOwHJSyv1CiFCUYc8ldEOgj0gpk4UQ9ijDrF82NR8GvhVCVJBS3hFClNJFZQYCQ1E6WBFC1JZSns3jHMVROgzjhLLa9/vAqrz06u71VVYFP6g7x1whhDdwX0qZ9JKh3peAN4QQ7lLKm0BvILPWzdSTM7zkILBECLEAUAMdMYwWLVAytBlsnfI7A1aOR6VWcXJdCNF/36fV8A+4f/4Wl/aepu34nliWsKb3T18C8Dj8Ab9/spAabRviXu8tbEraUucDJfDUf9QvRF66Yyr57N9zCK+WzTh0OoDk5BRGDcleEXnXgfW09ugCwMRRM/n6x1lYW1sTvDeU4L1Kg2Tc1GFUfr0iGRmS8HsRjB850yS6tVotc8YvZMna71CrVWxes4MbV2/x+ZhPuHjuCiGBh9i0ejtzF08l4Nh6njyOZ/Sn2SvJBp7cjK1dCSwsALVqOAAAIABJREFULWje2oOB3YZy89ptE+jOYNGkH/hm9VeoVWp2+O/i1rXbDBjVlyvnrhG65wg71gYw+fsJ+If+QfzjBKYOVnxaq0ENBoz6mHStlgxtBgvGLyLhsenWu9JqtcyZ8DU/r/kWtVrFFp3PB4/5hEthlwkJCmXz6u3MWTyVHUcVn4/R+bx7vw9wq1SOgcM/ZuDwjwEY1H2YyaIDlHTelIOndirp/IvstBAQso42nl0BmDhqFl8vnoW1tRUh+0IJ3qs8YI6bMgz31yuSkZFB+L1IJowyTToHCN5zCK+WTQg5tYPk5BTGfJG9yu7OEKXDE2DyqNksWDwTa2srDuw7TIhO+/SvxmNpZckfG38BlEU5Jo3Ke3XI/EBqMwib8DtN14xFqFXcXnuA+GvhvD36fR6du0Vk0Bkq92uFU9NqyDQtz54kcWqoos+xwVu8PfoDZLoWmZHBmbHLSXuc9IIr5i/Be0Lx9G5C8MltpCSnMGbotKxjO4LX0s5Lmd1l8ug5zP9hei6fT5s3FksrS1Zu+BlQFlKZNGp2geuW2gzOTPgdD53fb+r8Xm30+zw8d4uIoDO80a8Vzk2rkaHz+3Gd3wsTrVbLrHEL+M3/e1RqFZtWb+f61Zt8MXYgF8IuExx4iA2rtvHVj9PZfXwjTx7FM/JTJQLw+tWb7N66lx2h/mjTtcwcO5+MjIwXXDF/2b/nIM1bNiX09C5SkpMZMUSvrjmwAR+PDwCYMGom3+jq0ZC9h9i/91BepzQJRTWda7Va5k74hp/XLEKlVuvVRQO4GHaFA0GhbF69g9mLp7D96DriH8cz5lOl3Myui/oycHhfAD7rPtxkdZFWq2XBhEX8sOZr1GoV29bu5Oa123w6uj+Xz13hYND/sXfe4VUUbR++n4TQm0hIAEHAjkhREOkB6VJFAcEuKqKCioCgKAqCimLBhr18IE0BQXoJvTdBioqAQkICIhA6SZ7vj9kkJ42ESM6e9Z37vbxednf25JfJnJndZ56ynGnf/cQro19gyorvOHbkGIN6DgGgeu2q3PdEd+LPxaOqvDZwFEcPH/Wb7pyu/wCz1v5A4cKFCMmbhyYtG/Jo1z5+eeYCMy/+OvALqo9/HgkOIuq7RZzYuY+K/TsTt3kXh+ZkbnA9sXMfsT+u5Jalo0iMT2Tnc59Dov9eahfPX07DpvWYu2YKp0+eZlCfV5KvTVk4lo5NugPwcv/XGP7eS+QvkI+lC1awZIExYH363te8/ekIOnVvR/S+GJ7qkXHV84uNV5/RSUzk1DejKdTvdQgK4tySWSTu30u+2+8nYfdO4jeuJH7LWvLcUJPCr30BiQmcHv8JevwYIXWbEnxNVaRwUfI2aAHAyU/eIPHPXVn80ItEQgLH3nmXS94cCUFBnJo5i/g9eyj84AOc27mTM8tXULBTJ/LVqwsJCSQei+PoiNcAyFPhcoo+2xcSEyEoiBNjx5Gw13/vov1eeo21G3/myJFj3Nrhbno9dA/x8SZ6sUvH22hYpxZLV66lVecHKZA/P0MHPQ1AsaJFePT+u+jaw7xf93yg23mLBl10EhL5e8T7hH80AoKCiJs6h3O79lK8132c/eVXTi5eSdFuHSgYUQeNN31+aPDI5NtLfzmKkArlkIIFKDd3HIeGjOLUCvcN+l7G9fQUFxHJ7i8jIkOA46r6pnPcDZM3MggTat0TWIcJdb4J+AOIByar6v+JyD6giqoeEZF8wEKM0S0I+FpVR4rIc8B9zucFAZ+p6jsicqXzOdVFpIfzOU85OmYDw1R1mYjchqmqLkCUqrZyQrbfwVQXD8KEUrd3DIjTAd9tu44Y42UnYC+m8NDvwMhM9F4LTHJ+z8cxuS0Pqeo7afru/xz9U53jksCXwOXAcUyOy60iMizpfqewzyFVTSrW43utOfAGxii5Guilqmedgj89gb9UtWmaPu8P3OtIGqOqo3371fkZzwF5VPW8b/D9K9zlyW/A+GNb3ZaQI4qGFMq6UYBSLI8f81NeROISTmXdKEA5es6/Bq2LSVCOHM7dZ2TeKm5LyDH9z21zW0KOGBFSOetGAcqQhN/clpAj4uK9Wzk0b5D/qm5fbIrk8W/+24tFSKaBS4HPWY3PulEA8o6Wc1tCjuml/olWyg3yeHSsL2/u3feLU3v9U8TrYnPpD1+4LSHH7Lv1Ubcl5JiKm+d58wUjFwgrdm2u2HFiju7wex9n25BpsSRhDZn+xRoy/Y81ZLqDNWT6H2vI9D/WkOl/rCHT/1hDpv+xhkx3sIZM/2MNmf7HGjL/G4QWuyZX7DgHj+70ex9fSI5Mi8VisVgsFovFYrFYLBaLxWJxhYte2MVisVgsFovFYrFYLBaLxWKxBAb/pWhs65FpsVgsFovFYrFYLBaLxWKxWAIe65FpuWDO4U1LfrB4024flL1q9gFJiEf7/HTCObcl5Jhgj+ZqAiju0XywBfxcAfpikqDezDOV6N1p0bO5JmOO+6dqdW5QoVi42xJyjFdzBx9POO22hBxTICiv2xJyRMkC3s3vjTenRQAS1JvPAHkbVXNbQo7JE3PIbQk5wst5Ji9bMMZtCZaLQOJ/yCPTGjItFovFYrFYLBaLxWKxWCyW/yg2tNxisVgsFovFYrFYLBaLxWKxWPyI9ci0WCwWi8VisVgsFovFYrFY/qMkejRFYEZYj0yLxWKxWCwWi8VisVgsFovFEvBYj0yLxWKxWCwWi8VisVgsFovlP4rNkWmxXCDXNqrGwAWjGBT5Drc+1i7d9UYPtWbAvDfpN+t1Hhv7ApeULZl8rVanhgxa9DaDFr1NrU4N/Sk7mZdGDGDR2unMWjKJ66tem2GbKtWuY9bSySxaO52XRgxIPv/MwMeZtWQSP0VO4JvJH1MqPNRfsqnX+BZ+XDaeGSsn8eAT96S7HpI3hDfGDGXGykmMnfkZZcqZyq7FLinKZ9+/z6pdCxg4vK/f9CZxc0Qtvln8JWOXfU23x7umux6SN4QXP3yBscu+5sPpowm/LAyAph2b8Nmcj5P/W/jnXK6sfIW/5fPC8GeZt2YKP0Z+R+Wq12TY5vqq1zJ98XjmrZnCC8OfTT5frHhRvpz0AXNX/8CXkz6gaLEi/pLNi8P7s3DNNGYunnD+cb5kIgvXTOPF4f2Tzz835CnmrfyBmYsn8NHXb1GkaGF/yaZu49r8sHQc01aM5/4n7k53PSRvCK99/DLTVozn658+ofRlZpxfX/06vpv3Jd/N+5Lx87+icSv/zy+hjavRaPlbRKx6myueTD83lr+3KQ0iX6f+ghHU+fElCl9dFgDJE0y19x6jQeTrNFr6Jlf0bu9v6QwZMYDFa2cwe8lkqlS9LsM2Vapdx5yl37N47QyG+MyLfQc+zuwlk5kZOZFv/Twvlo6oym1LR9Jm+Vtc90TbdNevvOdWWi14jZbzhtN06osUvapsqusFy17KHb99zrU9W/tLcjKvjBjIsnUzmbf0h0z7/IZqlZm/7AeWrZvJKyMGprv+6BP3s+/wVi4pUTy35abi7VGvsH3bMjasn0eN6lUybPPKKwP4Y9da/jn8a6rz9evXZs3q2Zw6uZfbb7/NH3KTGTy8H/PXTGV65HgqZzIvXl/1WmYsnsD8NVMZPLxf8vmW7Zoyc+lEdsaspUq1jP9euUXdxrWZsuw7pq2cwAOZzYtjXmHaygl8M/MTSjvrf+2GtRg753MmLvqGsXM+p1a9G/2qO4nnX+3LnNU/MC1yHJVvyHwd/THyO+as/oHnX015VilWvCifT3qf2au+5/NJ7/ttHfVynxdudCPXLPiIayLHEPrYHZm2K9aqLlX3TKfADVcmn8t/bQWu+GEkV8/9gKtmj0byhfhDcjJeHCsA9RvfwswVk5i9+nt6PHlvuusheUMY9cmrzF79PeNnfUGZcqWTrz3c+z5mr/6emSsmUa/xLX7TDLB8dyztP4uk7aeL+GL17+muj1y4jc5fLaXzV0tp91kk9d+bA8DaPw8ln+/81VJuHjWLhb8d8Kv24Eo3UKDn6xR4bCQhddqku563aTfy9xhK/h5DKdDzDQr2/Sj5Wr6uz1Kw70fk6/yMPyUnU6BuTcpO+4LLpn9FsQe7pLteuF1zyi+aRJkJH1NmwscU7tgq+VrYh8Mpv3QKYaOH+lMyAC8MH0XD27rS4e6eGV5XVYa//RGtOj9Ix3sfY9vOlDE1beY8Wnd5iNZdHmLazHn+kvyfJlE1V/5zg4tiyBTDMhFp5XOus4jMvhifn+ZnBYnIYREp6hxfJiIqIrf4aPlbRIqLyOMi0t05/6CIhPt8zj4RyfApXkRuE5H1IrJNRHaIyOsXQfc+EVmU5txWEdn0bz870JEgodMrD/LJ/a/xerO+1GhXj7ArU78Y7t+2h1FtBzGy1QA2z1pN24HdAShYrBAt+nTinQ4v8Hb7F2jRpxMFihbyq/6IpvWpUKk8jWu1ZeAzrzDszRcybDfszRcY9PQrNK7VlgqVytPo1noAfPL+V7RqeCe3RXRh4dwl9H72Ub/oDgoKYtCIvjzW7Rk6NLyLVh2bUenqCqna3N6tLceOxNGmzp18O2Y8T73wOABnz5zlg9c/4a2X3/eL1rS6+wx7kgH3DOK+xg/RpH1jLr+qfKo2rbu24vjROLrXv4/Jn37PI4MeBmD+lIX0aNGTHi168mqf1znwVwy/b9vlV/2NmtajQqVyNLu5I4P7vsrLb6Q3JAC8PHIgg/u+SrObO1KhUjka3loXgEd638/KpWtoXvt2Vi5dwyO97/eL7qRx3uTm9gx6ZhhDRw7KsN3QkYMY9MwwmtzcPtU4Xxa5ipb176R1oy7s2bWXXk896BfdQUFBDBj+DE92f5ZOje6mZYemVEwzzjvc1YZjR+NoX7crYz+ZQJ8XHgNg184/uLtlD+5q9gBPdOvL82/0Izg42C+6jXjh+tceYE2311nc4FnKdKybbKhMIuqH5SyNGMCyWwey64MZXPey2ZAo3a42QfnysDRiAEubD6L8PbdSoFzJjH5KrtC4aX0qVrqcRrXanHdefPXNFxj49Ms0qtWGipUuJ+LW+gCMef8rWja8g9YRnVkwdwl9/DQvSpBw0/D7iez+BjMj+nN5+zrpDJV7pqxg1q3PMbvZILZ/OIMbh3RPdf3GIXcTvXCzX/T60qRpAypeUZ76NVsz4OkhjHhrcIbtRrw5mP5Pv0z9mq2peEV5Gjetn3ytdNlwGkTUYd9fUf6SDUDLlk248sqKXFe5Po89NoD33x+RYbufZsyjbr30hsq//trPQz2eZvz4qbktNRWNmtbj8krlaHpzBwb3HcYr55nPX+g7jKY3d+Byn/n8t+2/8/j9/Vi7coM/ZRMUFMRzI/ryRLe+dGrYnZYdm6Zb/zt0a0PckTja1+nC2DET6PNCLwCOHD7CU/cOoHPje3mxzzCGvf+iX7UDNLy1LpdXKk+L2rfzYt/hvPTGcxm2e+mN53jx2eG0qH07l1cqT4Mmpt8f7n0fq5aspeUtnVi1ZC0P974v1zV7us+Dgij7Sk923z+EX5s9TvF2Dcl3Zbn0zQoV4NL723Ji446Uk8FBlHv7GfY//wG/Nn+cP7oOQs8l+E26F8cKmPEy+PX+PHJXH9rW78Jtt7fgiqsrpmpzR/d2HD0aR8vanfhmzHc8O/gJAK64uiKtOzanbYOuPNy1Dy++3p+gIP/4JiUkKiPm/cIHd9zMDw82Yvb2KHYdikvVpl+Tyky8vwET72/AXTdezq1XmdfvWuVLJp//tEtt8ocEU6eC/zYxESFvy3s5Pf5NTo15juDrb0FKlknV5Oz8cZz+bDCnPxvMuXXziN+5PvnauVUzOfPjGP/p9SUoiEsHPUlMr0Hs69iDQi0bE1KpfLpmJ+YuJqpLT6K69OT4lFnJ549+NYmDL/xrc0aO6NC6GR+PGpbp9aUr1/LnvihmTvicIf17M/RN8+559FgcH305ju8+fYfvPn2Hj74cx9FjcZl+juV/j4sy66nxUe0JjBKR/CJSCHgVePzffK6IpAt9V9VEYC2QtP1UD9gI1HWOKwNRqnpEVT9Q1bHO+QeBcLJARKoB7wB3qWploAqwJ6eaHcNqUj8XF5EyzvkbgPjsfq6/yKjP/y3lq1/Job0H+PuvWBLOJbBx+gqqNK+Zqs3vK7dx7vRZAPZu/I3i4SUAuKZRNXYu28LJoyc4dewEO5dt4dqIahdb4nlp1qoxP0yYDsCmdVsoWqwIoWGpDQahYSUpXKQQG9f9DMAPE6bTvHUTAI7HnUhuV6BgftRPSXar1KjMn7v3sf/PKOLPxTN76nwat0jtcRbRogE/TpwJwLwZi6hd3/xdTp08zcY1P3PmzBm/aPXl2urXsH9PFNF/RhN/Lp6F0yKp17xeqjb1mtdl9qS5ACz+aQk31a+R7nNubd+YBdMW+kVzqp/bshFTJpg+3bx+K0WKFSE07NJUbULDLqVwkUJsWrcFgCkTZtK0VYS5v1UjpkyY4ZyfQdPWEX7R3bRVI6ZMND930/rsjfMpE2fQzNG3LHIVCQnm5WXjui2Elwnzi+4qNa5j356UcT5n2nwiWtRP1SaiZX1mTDQPdAtmRFKrwU0AnD51Jllz3nx5/R5uUfzGKzm5+wCn9sai5xKImrqSsJap58b446eS/52nYD5I0qgQXDAfEhxEcP68JJ6LJz7uFP6iWavGfO/MixvX/UzRYkUolWa8lAorSeEihdngjJfvJ0yneevGQOp5sWDBAn5LPV6ixhUc3xPDiT8PkngugT+nreKyFjelapO2z32HRdmWN3H8z1iO/rrPT4pTaN66MZPH/wjAhnU/U7RoZn1eiA1rjaF18vgfaeGsRQBDXu3Pqy+N8vtYb9e2Bf83djIAq9dsoFjxYoSHl0rXbvWaDRw4EJvu/N69+9iyZTuJiYm5rtWXpi0bMXXCTwBsWr+VIsUKZzIvFk6ez6dO+Ilmzny+67c97N6116+awcyLf/ms/3OmLiCiRYNUbSJaNGC6s/7PnxHJzfXN92Dn1t84GHMIgF07dpM3X15C8vrXw+7WVo2YNtH0++b1W816VCrNOloq9To6beJPNG3dyNzfshFTnXV06oQZyetrbuLlPi9Y/SrO7o3m7F8x6Ll4jkxfQtHmtdO1C+vbnYNjfkDPnEs+V6RBDU7v2MPp7XsASDgSB378nnpxrABUvfF6/ty9j317ozh3Lp6ZU+bSpGXqZ/QmLRsxzZl/5kxfyC0NajnnGzJzylzOnT3H/j+j+HP3PqreeL1fdG+NPkK5SwpyWfGChAQH0eLaMkT+HpNp+1nbo2h5XZl05+f9eoB6FUMpEOK/zeOgMleQeDgWPXIQEhNI2LaKPFdn7v2c5/pbiP9lZfJx4p5t6JnT/pCajnxVruHcX1HE7z8A8fGcmB1JwYi6Wd/ocHrNRvTEyVxUmDk1q99AsaKZezovWraKdi1vRUSoVuU64uKOc/DQYZavXk+dWjUoVrQIxYoWoU6tGixfvT7Tz7FkD82l/7nBRdu+UdWtwHRgAPAS8I2q7hKR+0RkjYhsEpEPk4x6IvKJiKwTkV9EJHnr0fFcHCwiy4GOIvK04xm5WUT+z2m2nBTDZV3g7TTHK5zPGiYiT4lIF6A6MMHRkddp+5SIbBSRn0XkaufcAGCoqv7q/F7xqvqR83n/JyIdfLQed/6/qYjMF5HxwEYRudLxtvwY2AAkxQJMAjo7/74L+M7ns64QkaWOnvUiUtvnsxeIyA8islNEvvG552URWZv0s0REnPO3OL/TChEZmeT1KSJ5RGSU8/f4WUR6ZKQ/G3/uC6J4WAmORP2dfHw0+jDFwkpk2r5258ZsjzSOqsXS3Hski3tzg7DSpYjen7JIR0fFEF469QtYeOlSREeltDkQFUOYT5tnn3+C5T/Pof0dt/H2iA9zXzQQVjqUmKiUF8KY6FhKlQ7NoI3RnZCQwPG44xQvUcwv+jIjtHRJDkan6D544CChpdM8lIZfysHogwAkJCRy/NgJil1SNFWbxm0jWDgtlRO0XwgrHcqBqJRQmZioGMLSvLCHhZfigM94iYmOIcz525QMLcHBGDPmD8b8zaUlL/GDamcM70/RfSCTcX7AZ0xl1Abgzu7tiVywPPfE+hAaHsqB/SmaYqMPpgtTDg0PTdadkJDA8WMnksd5lRqVmRT5LRMXfc3wAW8mGzb9Qf7wSzjlM7+djvqb/OHp/96XP9CMiNXvcO3gbvzy/NcARE9fTcLJM9z680c02TCaPz6awbkjJ9Ldm1uEly5FVJrxEpZmLISVTj3O086d/Z5/kpU/z6XDHbcxasQHuS8aKBhegpM+fX4y+jAFSqfv86vub0abFaOo9sJdrB9s+jy4QD4q92rL1rd+8IvWtISXDkvV56Y/w9K1iU7X56ZNs5YRHIiOZfsvO/0j2IcyZcJTeYHu3xdN2TJZ7i27Tli6tT2WsDTzS1h4aKpxfiA6/XfB35TKYP0PTbP+lyqdZl6MO5Fu/W/aJoKdW3/l3Nlz+JOw8ND0/Z7R/BIdm7qN87e5NLQEB2OddTT2b0r4YR31cp+HhF3KuahDycfnov8mJM0GbP7rK5G3dChxC9emOp+vUllQqPjNy1w14x1CH73dL5qT8OJYASgVHsqB/b7PgbHJz4FJhIWHJr9/JCQkEOc8o5vnTJ97o2L9lp4l9vhpwosUSNFYJD+xxzM27kUdPUnU0VPcXD59tMicHVG0ysDAmZtIkUvQuJT1X48dRopk/PeWopcixUNJ3LPNX/LOS3CpkiQcOJh8nBB7iDxh6fu14K31KTtpDKXeHExwmB+9Xf8FMQf/JrxUyu8SVqokMQcPEXPwEOGlUn6HsFBz3mJJ4mL7ob8MdANaAW+ISBWgI1BXVatjigslJbx7TlVrAtWAZiJS2edzTqhqPVWdBPQHqqtqNeAJ5/oKUgyXtYDJQAXnuC7G0JmMqk4ANgFdVLW6qp51LsWoag3gMyAp4UUVICfm/luA/qp6g3NcGfhcVWuo6n7n3CQgKfFMa+Ann/ujgWaOnu7Aez7XbsR4t1YGrksKowfeVdVawA1AMaClc/5LoIeq1gXE53MeAWJV9WZMvz0uIkl+6Wn1p0JEHnEMz+u2xF1gqK5kcC4Tb5CbOtSnXNVKLPxkuvNzs39vbpGRhrTeLJJxo+R/vvnq+9Sr2oJpk3/i3h7pcz7mChloSueFk502ficjTWmbnL/NdTWu5czpM+zeuefiSssGGY2F7IwXt/s9e7rT35e2Ta+nHyI+PoFpk2ZeVH2Z8W/7e+vGbdwZcQ/3tHqYB568m7z58qZrm2tkOMGlZ++X84is/RQ7ho3jqqc7AlC8xhVoQiILqvViUa0+VOp5GwUu95/xJOf9nvLvka+Opk7V5kyd/BP39bjromvMkGyuKb99NY8ZdZ9h86vjqdLH7F/e0K8TOz6dRfxJ/3uqw78b6/kL5Kd330d4c7j/04VAYM552cGr83kmk3WaJufXXemaivR+oRfD+o286PKyJMfPL7klKBt4uc+z0i5CmcE9iHr18/TtgoMpVKsyf/Z5i9/vGEDRFnUoXLdq7mlNixfHClmvj5m1QTO5108eURn9lMyeZObsiKbp1eEEB6VucfD4aX4/GOffsPLMyKTb8lx/Cwnb17o/UJLIxjg/uXglf7W6h/13Psqp1RsJHdYv3T2BSEbrpYhk2PUZficsF4TNkZkJqnoCmAB8q6pngKYYg9k6xyuwEZBUeeMuEdmA8Vi8DmOkS2KCz79/Af7PyXWZtD25CqgpIoWdn3sK+FNEKuDjkZkNktwq1pNiCM0pK1X1T5/jXaq6Nk2bg8AJEekK/Az4bmHlAz4Xka3AeFL3xypVjVbVBIxBNknrrSKyBtiM6dvrRaQkkFdV1zhtxvl8TnPgAedvsRooDlyVif5UqOonqlpTVWveUOTCiqccOXCY4mVSdnaLlS7B0dh/0rW7ul4Vmj3Rkc97jCThbHyG9xbP5N6LzT0PdeGnyAn8FDmB2AMHKV02xeuldJkwYnx2xcB4vZT2CaUNz6ANwI+TZ9GybdPcE+5DTFQsYWVSDBthpUtx8MChDNoY3cHBwRQuUpij/xzzi77MOBh9kFCf3fTQ8FAOHfg7TZtDyZ4OwcFBFC5aiGNHUnQ3adeYBVP9F1be/cE7mbZoLNMWjSX2wEHCfTyNwsqEERuTeiwciI5JFXodVjqMWOdvc+jg4eRQ9NCwS/n7UO6N93se7MyMReOZsWg8MQcOUrpsiu6MxnB0VCzhPmMqbZvbu7SlSfOGPN3z+VzTnJbY6FjCy6ZoKlU6NDlEL1UbR3dwcDCFixZKN853/7aXUydPc8W1qXNU5Sanow9TwGd+y1/mUk4fyPzvHTVlJWGtTOh5mdvrcXDhZjQ+gbOHjvHP2l8pXq1Sruq996EuzIycyMzIicQcOEiZNOMlNs14ORCVepybuTN92PC0yTNp5ad58WT0YQr69HnB0iU4deBIpu33Tl1JWSfc/9IaV1D9hbtou/odrunRkspPtueqB5rlqt77HurKnMWTmbN4MjEHYlP1eUb9GR11INValNSmQoVylCtflrlLv2flpjmULhPG7MhJ6UIwLyaP9byPdWvnsm7tXKKjD3BZuRTvm7KXlSYqOvNwRDfp/uCd/LhoHD8uGmfmxVRreyli08wvB6JjU43z8NLpvwv+Jjab63+qebFIyrxYqnQoo74YzuAnh7Jv7378QbcH72TKwrFMWTiW2AOH0vd7mj6NSePhbf42ps3fBw8nj+3QUpdyOBfX0SS82OdJnDtwiJAyKR5RIaUv5Vzs4eTjoMIFyH/15VwxfjjXLvuMgjWuocJnL1Dghis5d+AQx1dvJeGfY+jpM8QtWkeBKrlbZNHrYwWMB2Z4Wd/nwPS6D0THJr9/BAcHU6RIYY78c5QDUannnLAy6cdabhFWOD8HfNLYxMSdJrRw/gzbzt6RcVj53J3w6HWOAAAgAElEQVTRNL4qjJBg/9Yc1rh/kCIpa54ULYEez/jvHVw5dVi52yTEHCTYx+s2uFRJEmJTvxslHo2Dc8ZUEvf9TPJddzVeILxUSQ7EpozfmNhDlCp5qXM+5TsRc9Cct/w7VDVX/nOD3JhBEp3/wGzSfOF4QVZX1WtUdaiIXAX0AZqoalVgNuA7C/rGx7UAPgZuxhhEg1X1OLAXeABY57RbBbQFiqlq+hJqGZPkVpGA8RYFYzi9KePmxOP0mYgE+9yTVnNGx0lMAD7AJ6zcoS/wF8a78maMYTOtzmStIlIQeB/o6PThF5g+PN9WhQC9fP4eFVV1QRZ6/zV/bd5FaIVwSlwWSnBIMDXa1uWXeamdXsteX4E7hz/MZz1GcvzvFAPDzsWbuaZBVQoULUSBooW4pkFVdi7O/SIL334+gdsiunBbRBfmzlzE7V1MZdvqNW8g7tjxdIaSgzGHOH78BNVrGofW27u0Zd4sE9ZcwScZc9NWEfzx2+5c1w/wy6btXF6pHGXLlyZPSB5admhK5NylqdpEzl1Gu86m8m6zNo1Zs9z93CM7N+/ksoplCS8XTp6QPDRpH8GKean3JlbMW0HLO5sD0Oi2hmxYnlIzS0SIaNOQhT9G+k3z2C8m0b5xd9o37s78WZF07GL6tNpNVTh+7HhyqHgSB2P+5sTxE1S7yVTu7dilNQtmLwZg4ezFdOzSxjnfhgWzFuea7m+/mEibxl1p07gr82YuomNn83Or35T5OD9x/CTVbzLjvGPnNsx39DVsUpdHe9/PI3c/xelT/ssh9MumHZSrWI4y5cw4b9G+KYvnpA5rXzxnOW06m1p0t7aJYO0yU3ijTLnSycV9Sl8WRoUryhP9l/8qaB7duItClcIpUD4UCQmmTIc6xMxJ/R0sWDHFcFWqWQ1O/GH0ndp/iEvrm5xYwQXzUfzGKzn+e+4WcPnm8wm0juhM64jOzJ25kE7OvFijZlXijsWlM/DExhzixPET1KhpvHM6ZTIvNmsVwS4/zYuHN/1BkYrhFCoXSlBIMOXb38K+uan7vHDFlBfEMk2rE7fb9PmCjkOZXvspptd+ip2fzWbb6Gn89mXuVtH8+vPxtGh0By0a3cHsnxZyR1dT2f7GmlWJO3Y8wz4/fvwkNzp9fkfXdsyduYgd23+j+jWNqFO9BXWqtyA6KoaWEXcmh1TmBh99/DU1azWnZq3mTPtxDnd3NwEptW++kWNHj2WYCzMQGPvFJNo17ka7xt2YPyuSDl1M8aHqN1U5z7x4gurOfN6hy23Mn51783Z2+GXTDspXuowyzvrfosOtRM5dlqrN4rnLaOus/03bRLDWWf8LFy3M6P8byejhY9i8dovfNI/7YhIdm3SnY5PuLJgVSfvOpt+rJfV7mrF6MPZvThw/mbyOtu98W/J6uXDOEjo462iHLm2S19fcxIt9nsTJzb+Rt0IZQi4LQ0LyULxtQ47NW5N8PTHuJNtu7M6O+j3YUb8HJzfuZE+PYZza8jvHF2+gwLUVkPz5IDiIQrWrcPq3v3JVr9fHCsCWjducZ/QyhITkoXXH5iyak/oZfdGcJbR35p8WbZuwatk65/xSWndsTkjeEMqWL8Pllcrx84Zf/KL7+tLF+POfE+w/cpJzCYnM2RFFoyvT50Tfc/g4x06fo1qZ9KHbs7f7P6wcIDHqD4JKhCHFSkJQsDFW/po+o5qUCEfyFyRxf3bNCbnPmV92ElK+LHnKhkOePBRqGcHJxakNrcElU1KvFYyow9ndmfonBRQR9W/hx9kLUFU2b91O4cKFCC1Zgnq1b2LFmg0cPRbH0WNxrFizgXq1MzPRWP4XueiFXdIwH5gsIu+q6iERuRQoBBQF4oBjIlIaY6xMV+HcMRZepqoLRWQZJuS6oHPvcuApIKlU6krgK+f/MyIOyDzTbApvYHJprlDV3x0NfVR1FKboz00YT86OQE4yFH8PhALzSO0FWgz4XVVVRO7j/AZJgAIYg/EhESkCdALGqupBETknIjVVdR0pofwAc4BeIrJYVeNF5Bog12e5xIREvn/xSx79ZhBBwUGsnriIA7/to+XTd/LXlj/4Zf562g3sTr6C+bj/w6cA+Gf/IT5/+E1OHj3B3Pd+4OkfXwVg7nvfc/Ko//LAASyat5TGzeoTuW4Gp06dpv+TKdUkf4o0Bk+Awc++ysj3h5I/fz4WL1hO5HzzANv/xT5UurICmpjI/r+ief7ZzCu3XUwSEhIYPugtPvruHYKDg5j63Qx27dxNr/4Ps23TdiLnLmPKuOkMf/8lZqycxNEjx+j/aEoV3Flrf6Bw4UKE5M1Dk5YNebRrH/74dY8fdCfy7uDRjBz7GkFBQcyaMJs9v+7lgWfvY+fmX1kxbyUzx89i0LvPMXbZ1xw7EscrvV5Nvr/aLVU5GH2I6D+jc11rRkTOW06jpvWYv2Yqp06dZmDvl5OvTVs0lvaNTQXkl/q9xmujh5A/fz6WLFzB4vnG+PbJe1/z7mcjuKN7e6L3HaD3QxlX4LzYLJq3jIim9Vm09kdOnzpN/95Dkq/NWDSeNo3NVDK433DeGP1yunE+5LUB5M2Xl28mfwSYgkEvPPtqup9zsUlISOD1QaP44LtRBAUH8eP4n/jj19307PcQ2zbvYMnc5Uz9bgZDRw9m2orxHD1yjIE9ze9Wo3ZV7n/ibuLPxZOoiYwY+BZHDh/Ndc1JaEIiWwd+xc3jByLBQez7LpLjO/dxdf87OLJ5N7Fz1lPhoeaUbHADifHxxB89webepn/3fjGXau/2pOHikSCwb/xi4rb576F14bylNG7WgCXrfuLUqdM8+2TK3DEzciKtI0w66OefHcZb7w8jf/58RC5YxiJnvDz34lNUurICic68OOjZoX7RrQmJrHv+KyLGDUCCg/hj/GKO/bqfG/p14vDm3eyfu4GrH2hOeIMqJMYncPbICVb1+dgv2rJi4bwlNGnWgGXrZ3H61CmeeSKlz+csnkyLRsZQOOjZoYz6YBj58+cncv5SFs5fmtlH+o1ZsxbQqmUTdmxfzqlTp+jR45nka+vWzqVmLbMxNWLE83Tt0pGCBQuw+491fPHlOIYOHUXNm6oxadLnXHJJMW67rRkvvtiX6tWbZPbjLhqR85bRqGk9FqyZxqlTp3nOZ178cdE42jXuBsBL/Ubw+ugh5M+fn8ULlyfP581aN+bFEf0oceklfDruXbb/8isPdn4iox91UTHz4tt8+N0ogoKDmfbdDP7YuZvH+vdg26YdLJ67jKnjZjDs/cFMWzmBY0eO8dyjLwHQ9cFOlKt4GQ8/fT8PP30/AI91fYp/DmXuuXyxWTx/OQ2b1mPumimcPnmaQX1eSb42ZeFYOjYx6+jL/V9j+Hsvkb9APpYuWMGSBWbT89P3vubtT0fQqXs7ovfF8FSP3F9HPd3nCYlEvfgxlb55GYKD+GfifM789idhT3fn1JbfODZ/Tea3HjvBwc+mctWPo0CVY4vWEbdoXabtLzZeHCtgxsuw50by2YT3CAoO4odx0/l95x88OeARtm7azqI5S5k89kde/+BlZq/+nqP/HKPvoyba5fedfzB72nxmLJtAQnwCQwe84bdCaHmCgniuaRUem7yGxESl/Q2XcWXJIny4bCeVw4sT4Rg1Z22PouW1ZdKFAu8/epIDcae4qZwLnnWayNk535D/rv4QJMRvXoIe2k9Iw9tJjN5Nwm/GqJnn+jrEb1ud7vb89zxP0KWlIW9+Cjz5Dmd/+pyEP/y08ZCQyN8j3if8oxEQFETc1Dmc27WX4r3u4+wvv3Jy8UqKdutAwYg6aHwCicfiODQ4JUVF6S9HEVKhHFKwAOXmjuPQkFGcWuGf72m/l15j7cafOXLkGLd2uJteD91DfLyJvOzS8TYa1qnF0pVradX5QQrkz8/QQU8DUKxoER69/y669ugDQM8Hup23aJAle7hVmCc3kIvtCioiQ4Djqvqmc9wNk+cyCBMa3hPjRfkNxij4B8bTcbKq/p+I7AOqqOoREckHLMQYIIOAr1V1pPO5d2HCpiuq6h4RKQAcBZ73aTMMOKSq74hIZ2AocArj8fiHz8+5BRimqk2d+9oBQzDGQgWmqepAx+g6zflV5wJPqWphEWkKPKGqHZz7r3R+n+o+/ZL8e/mcS27nGBUnYzwj55/nsz8Gljl99RrGgLkX2IcxhA4TkbrAGIzxdglQR1UbOUbZV4E2joRYoD1Q2/dnZMXTFbp68hswNW672xJyRJGQgm5LyDEl8hRyW0KOiDrjvxe2i028+q9YzcWmeIg3x8vQxHJuS8gxveL948VxsXktX4bpnD1Bv9O5H1WQG8RkEoLnBSoUC/zCQplRODjjsM1A51Ti2awbBSgFgvyYK/ki8nV+/xbDvJh0Pum/aIiLjWTpexKYbBhe320JOSYxxj+h9Beb2InuOFlcDC5bMMZtCTkmpGQlb35Jc4F8+cvlih3nzOm//N7HF92QaXEfESnshN8jIs8DJVS178X6fGvI9C/WkOl/rCHTHawh0/9YQ6b/sYZM/2MNmf7HGjL9jzVkuoM1ZPofa8j0P9aQ+d8gb77LcsWOc/bMPr/3cW6HllvcoZ2I9Mf8ffcA97uqxmKxWCwWi8VisVgsFovFYvmXWEPmfxBVHUfqauUWi8VisVgsFovFYrFYLJb/Qf5L0djWkGmxWCwWi8VisVgsFovFYrH8R/nvmDFtjkxLgCEij6jqJ27ruFC8qhusdjfwqm7wrnav6gbvaveqbrDa3cCrusG72r2qG6x2N/CqbvCudq/qBu9q96pusNot/1sEuS3AYknDI24LyCFe1Q1Wuxt4VTd4V7tXdYN3tXtVN1jtbuBV3eBd7V7VDVa7G3hVN3hXu1d1g3e1e1U3WO2W/yGsIdNisVgsFovFYrFYLBaLxWKxBDzWkGmxWCwWi8VisVgsFovFYrFYAh5ryLQEGl7NjeFV3WC1u4FXdYN3tXtVN3hXu1d1g9XuBl7VDd7V7lXdYLW7gVd1g3e1e1U3eFe7V3WD1W75H8IW+7FYLBaLxWKxWCwWi8VisVgsAY/1yLRYLBaLxWKxWCwWi8VisVgsAY81ZFosFovFYrFYLBaLxWKxWCyWgMcaMi0Wi8VisVgsFovF8p9ARELd1mCxWCyW3MPmyLRYLBbLfw4RWaCqt2Z1zmKxWCwWS3pEJK+qnnX+XQG4Gligqglu6soKERFgvare6LaW/yVEpLiqHnFbR04RkXyqesZtHReCiOQFOgAVgDxJ51V1uFuasoOIBAMbVLWa21os3iVP1k0sltxDRMKA4UAZVW0lIpWBOqr6ucvS/icQkUKqesJtHZbAR0QKAOVVdafbWs6HiOQHCgIlReQSQJxLRYEyrgnLAhGZDmS6s6iq7fwoJ0eIyO3A60ApTL8LoKpa1FVh/yOISH3gKlX90vFGKqyqu93WlRHOWMkUVf3BX1r+DV6ZF33JpO+PAltUNdbfev7LiEiJ811X1cP+0pJDVohII6AIsAzYAnQD7ndTVFaoqorIWhGpqqo/u60nJ4jI5Zj5fL4zz+RR1Ti3dWXBehFZA3ypqnPdFpNdRORm4HOgGFBeRKoBPVT1SXeVZYspwGlgPRDQGwy+qGqCiGwTkbKqut9tPRZvYj0yLa4iIrOAL4HnVbWaiOQBNqrqDS5LyxIRuRr4CAhT1SoiUhVop6rDXJaWJSJSF/gM86KbtGg/qqq9XJaWJSJSDxgCXI7ZjEkyllRyU1dWOOOlHym6AVDVJq6JyiYi0hZ4E8irqhVFpDrwSiAa10SkD/AUxmi5nxRD5jHgU1V93y1t58N5WcwUVV3sLy05RUR+B9qq6na3teQEj8/pLwE1gWtU9WoRKQNMUtV6LkvLEBH50vlnKaAusNA5bgxEqup5DZ2BgJfmRV9E5CegDrDIORUBrMJ4272iqt+6JC1LvLaOishuzAaVZHDZC88tG1W1hog8DhRV1REisklVq7utLStEZBNwPfArcIKUZ8WbXRWWDUTkYeARoISqXiEiVwEfB3pEiYgEAS2AB4HqwHfA16q6y1VhWSAiq4AuwFRVreGc26qqVdxVljVe0ZkRIjIPqA2sxHxHAfDC+m8JDKxHpsVtSqrqRBEZCKCq8SLilR2lTzEP1GMAVPVnERkHBPxLL/A25mHjRwBV3SwiDd2VlG0+B57GY7uPwCTgY8y48ZJuMIbjm4FIAFXd5ISZBRyq+i7wrog8qaqj3daTXXwNlV708nKI8aoR08HLc3pHoAawAUBVo0SkiLuSMkdVHwAQkRlAZVWNdo5LAx+4qe0CGIJH5sU0JALXqWoMJEfGfIR5oVwCBKwhE4+to6pa0W0N/xIRkRoYL8yezrlgF/VcCF3cFvAveBwzt6wGUNXfRKSUu5KyRlUTgVnALBGJAMYCTztemgNVdY2b+s5DkKruNRkJkgn4+cVhlYhUVtVtbgvJAa+5LcDibawh0+I2J0TkUpyQShG5BRPi5AUKquqaNAtfvFtiLhRV/cuji/ZRVZ3ltogcEK+qH7ktIofEq+rRNOMloFHV0Y7ncQVSe+5845qobODr5QV4xsvLYZ2ITACmAsl5prwSJoy35/SzTjhl0lpayG1B2aRCkhHTIQbjGegFPDcvOlRIMmI6xAJXq+phETnnlqhs4sl11MnZ2B2oqKpDRaQ8EB7Ahp0knsWkC5mrqltEpBKwwmVN2SJpI1BEigL5XZZzoZxR1bNJc4sTrRbwIZQiUhwzzu8F/sE4HUwBbgImAIFq2P/LCS9XJ3fjkxhPXi9QG9joRMScIcXzOODzw6rqAhG5DJNCYZGTGsorGyWWAMAaMi1u8wzGK/AKEVkOhAJ3uCsp2xwSkStIMcLeAUSf/5aA4S/HyKNOoujegFc8qRaJyEjgB1IbSza4JylbTBeRXpiHOl/dgZ4jC2CriHQDgp0Qp94E+MuMiHwLXAFsIsVIr0BAGzLxrpcXmDykJ4HmPucU8131Al6e0yeKyBiguBOW+CAmfUigEykiczAhiAp0JSXkOdDx3LzosNTxhJ3kHHcCljjG70Av1OHVdfRDjCdsE2AoEAd8D9RyU9T5cAw6jVU1eT5X1T+AR91TlX1EpAXwHlAeM65LAbuBK93UlU0Wi8ggoICINAN6AdNd1pQd1gLjgM6qutfn/CoR+dQlTdnhMVLGSgww3znnBTq4LSCniMiDwBOY3KRXYPr/Q6Cpm7os3sHmyLS4jrPTeA1mF2mnqga6RwAAzs70J5j8Xv9gHpC6p1m8AxIRKQm8i1ksBJgL9FHVv10Vlg1EJKOXXA3UHFlJOLmy0hLwObIARKQg8DwpBqo5wNBAru4oItsxIaueWuREZLWq1k7KTeac+1lVq7qt7b9OJnP63aq6x01d2cV54W2OmdPnqOo8lyVlCxHpCCSlNlmiqlPc1JNdMpgX52LmxdPuqcoaxzuwE1APM1aWAd97Ya706joqIhtU9cY08/pmDfCKvSKySFUbu60jJzg5Mptj5sIaItISk8P5cZelZYmTa/IhfOZz4LNA/46KSJATXm7xIyJSBajvHC5V1V/c1JNdnO/ozcBqn3lxixfqZFgCA2vItLiKeLh6pohUVNXdjhdDkKrGJZ1zW5vFcjERkTtVdVJW5wIJEZkE9E4TthrwiMjnwALgOYyxoTcQoqo9z3tjAOCECI3GGEgUYyDpo6r7XBV2gfjO6W5ryS4i8rqqDsjqXCAiqavzFgSCvdD3IlIhrZFbRGqp6lqXJFkCFBFZjdkgWesYNEMx4do1XJZ2XpzolwrARFIX45jplqbsIiLrVLWmiPwMVHNSb6xW1dpua8sKZw06raoJznEwkE9VT7qr7PyIyJWYSLsKpE7p0zyze9xERN7mPCH7qvqMH+XkCBF5AuOxO9U51R74QFU/dE9V9hCRVap6i6QUFQsGNllDpiW7WEOmxVXE29UzN6TNQSIi61X1Jrc0ZRcRqYjJAVOB1A8bAZ+HT0SKAS+R4sGzGDNWAjq3qoiEYEJVknRHAmO84IGcyVhPdy6QcDx3qwNrSB2CGNBjPBPv12GB7uUFyRUox5FSLORujJd6M/dUZR8nv9e9pJ8Xe7ulKbtk8h0NeE9e8Wh1XjB9jvHw2u8cN8S8QAb0S5izgfw6JtRWSMmpVtRVYdnAq+uoiHTHFJ+5Efgak0LphUDeDAQQke8yOK2q2s3vYi4QEVkItAHeAgpgQoYjPGLIXAU0VdXjznFhjOG7rrvKzo/jYfc5aYpxqupq10SdBxF56HzXVfVzf2nJKY6hvm6asbIi0Nd+ABF5C/O9fABjjH0c+E1VB7oqzOIZrCHT4ioiMh3ooemrZ/bAhJhVcVNfRojItcD1wBuYCrdJFAX6qer1rgi7AERkM+ZhYwsmbxOQunJyoCIi3wNbMS8DAPdgdtsz8u4NGETkMyCE1LoTVLWHe6rOj4i0AloDnTGJ2pMoignbvtkVYdlARBpldD7Qx7iI1FDVjW7ryAkisklVq2d1LlARkRWYjbS08+LXmd7kMiLyGOYFoBKwy+dSEWC5qt7tirBs4uXQMhGphcnn1RZjoBqOMWz+5aqwLBBTFKKtqnolL3YyXlxHk3CeHW/FGI4XeLH/vYSzMXUcCMIYSooBX2vqQlcBiVfX0kDf4M4KESkAoKqn3NaSXURkC1AzKdWTiOQD1nlkDQ3GbGT6plAYY9MTWLKLLfZjcRsvVs+8BrPLWxzzApNEHPCwK4ounNOq+p7bInLIFarayef4ZedlONCplSYf1kLHoBzIRAHrgHaYHfYk4jDVKAMWVV2cUciq27qywSgRKY0pxDHeK7mOHA6JyN2Ywi0AdwEBn3fXh/xeCCVLwzhgFjACk44giTgN/AIo4NHqvACqulZEemNyY54GmqnqQZdlZYcYDxvRvLiOIiLvAhNU9QO3tVwIYopB3oPZvE+u/K2qvVwTlU1U9Yizll6pqmMcA0+Q27qyyQkRuVGdIpYichPgBePaNBF5hPTFuI65JylrRKQyZnOktDmUfcD9Hpknv8UUU/reOe5IykZPQOOkTvjI+c9iuWCsR6bFVUTkQ0yVMt/qmfswno4zAjnJuIjUUdWVbuvICWIqrV6FeQHzUuVvRGQlxvN1mXNcD3hTVeu4q+z8OGGId6rqLue4EjDZC7vXIhIS6KF7afF4yGo4xgu2C8b7dYKqDnNXVdaISHngfUy6EMVUcO6jHiiABiAiT2M8eGbgrYrIyYhIKVIbHP50UU6WiMgbmIrC92LSnfQCtqnq864KOw9OJInvw3NlTHX7f8AT6SveBcIxOdV8x/kPronKJl5dR0XkPsx8fjXGyDNBVde5qyprnNDyfZhQ+NeAbpgc9k+4KiwbOH3+NFDEeQa4FhjthVQnjrf3eMxmMhgDWxdVXZ/5Xe4jIhl5o6uqlve7mAtARJYBL6tTIE9EmgJDVLX++e8MDJzx0gDj1bhEPZKnWUQ2kn7j8ijGgWKEl569LO5gDZkWVxHjhnE7KdXW/gZKqzeqCubHVBVMu1P9oGuisomIjMDssu8iJYRSNcArfwOISHXMbmMxzKJ9GLNzGtBeGSJyK/Al8AdG9+XAA6qaURX2gMIxAo7AvLD7jvWArRTr5ZDVJETkBqA/5gUmr9t6/uuIyOPAqxjDWtLDkQbyOE9CRNoCo4AymMiGy4HtgZ7qRDKozquqn7qr6vxklrYiCQ+kr/gyg9PqkWcXz66jACJSArNh3xUor6pXuSzpvCSFMyfl23U8NGd5ZENwI3ALsMqLzwBOPthrMON8h9c2k72EiGxO4+md4blAQkQKqeoJEckwt3Gge8FC8kamYCJLwMyLCZgN5VsCfVPQ4j42tNziKqqqIrILqI3xQNoNfH/+uwKGb4EdQAvgFaA74IUwBDChB5VU9azbQi4UVd0EVEtavL2wWAOo6gLHIOj7YHomi9sChS8xBZbeBhpj8k2Jq4qyxpMhqyJyHcZz507gEMYro6+rorJARPqr6hsiMpoM+lg9UCzH4RlMGOIht4XkgGGYl/b5aqp/NsaE9gc6NRzDZbLxUkTaqup0FzWdl0A3VGaFqj7gtoac4vF1FOBK4FpMQbFt7krJFknPiEdF5GrMJkkF9+RcEGdU9YzPM0AwHngG8KEWKYXnaogIqvqNu5KyxvF8TbvpPS7zOwKCPSIykNSFCgM9kmQy0Ar4hdTjWpzjgPaCdaibxut1o4gsU9X6Tu5Pi+W8WEOmxRWcB6KupORQm4DxEA7YUPIMuFJV7xSR9qr6tYiMwyQq9gKbMTk+Y90Wkl1E5G5V/T8ReSbNeQBUdZQrwrJARJqo6kIxlWJ9ucJ5MA34cD6ggPMCKU6Y8BARWYoxbgYqi0VkEFBARJphQlYD1jjiw5eYHJPNVDUqq8YBQtIGTsCHSmbBL8BJt0XkkHOq+reIBIlIkKouEpHX3RaVDT4VkftUdQuAiNwFPEUAf1d9XrTiyOAFUgO0+reXNxy8vo4638XbMVEwE4ChqnrEXVXZ4isRuQQYAizEVP9+2VVF2Wel87yYT0QaYCoiz3ZZU7YQkW+BK4BNpFT/ViCgDZki8gLGu/5azPtQC2AZKR53gcqDwFBgpnO8BLNhH7Coaivn/8u5reVfUEREbkpKmSAiN2LSKQHEuyfL4hWsIdPiFjuApZjKmb9Dcn4yL5EU5nFERKoAB/DOTnUYsENE1pI6R1Ygu/EXcv6/SAbXAnmXvRHmBaBtBtcUCOgXMIfTTgjobyLyBLAfKOWypqx4DhOyugV4FPOA+pmrirKBqt4ipnKmF3bTAfDxnjupqpN8r4nInS5IyikJwCYRWUTqeTFgDTw+HBGRwpgXsLEiEos3XgTuACaLSHdMipl7MS/CAUuSB4mqZrQWBTJe3nDw+jq6G6jjNW9vVf3Q+ecC4DI3teSAfsBjGOPxAIxh7cPz3hE41AQqq/fyv3UBqgMbVPUeMcWWxiIP1QMAACAASURBVLisKUtU9W/MZncyIuKJ8S4ic1W1eVbnApRHgW+dNAqC8QB/SEQKAW+4qsziCWyOTIsriEhHjEdmXcwO6XjgM1Wt6KqwC0BEemDC4G8AvgIKAy+q6sdu6soOmeX48kLInIjUU9XlWZ0LNESkoqruzupcIOIkEt+O8eIdislP+oaqrnJV2H8QJ9fhm0BeVa3o5IR9JcA3GQBTiCNt0Y2MzgUqTnGIdKhqwFcAdR78T2Gq8nbHfEfHOi9oAY0ToTEV+AvooKoBXZ3XyXOYKYFeoEBE7sxowyHtuUDEq+uosxHYDZPS5xUxhdHCVXWNy9LOi4iUxHhgllXVDk7qk5qq+m0Wt7qG44X5jqomZtk4QBGRSUBvVY12W8uFICJrVPVmEVkPRGByHW5R1SruKssc5/m2LLBMVQ+JyPUYw3cTVQ1YY6aTrzY/ximoPinpnopiUsxc65a2C0VELsXYpDy10WNxH2vItLiK8/LVARNi3gRTxGWKqs51Vdj/ACIShsnBA7BGVT0RZu5VY0kmuter6k1uafo3iMjlGsDVqEWkDcboejkm+iCgwz6TcF4AmgCRPgUKflbVqu4qyxwRaQW0xuQ5nuBzqSjGq+RmV4TlAOfl4GrncKdXCyw4+eC6qupYt7VkhJP/yvcBtBSmWukZgAAf77sx2gVTTTiKlJdI1QAvDuXVNRS8u46KyEeYwopNVPU6J1x7rqrWyuJWVxGRGcBEoK+qVnM8p9YH+PdzDObZtpdXN1udqIDqwBq8EzWV1PcDMJtpvYFjmKJz97oqLBPEFD7thEm3VRGYAvQBXgc+UtWATTXjRDE+g1k7fd/fjgGfquo7rgi7QESkBemL5g53T5HFS9jQcourqOoJYCwmFK4EpsDFc0BAGzKdl8RLknaPnJff+4BnVPU6V8VlAxHpDIwEIjEvYKNFpJ+qTnZV2HkQkToYD97QNHkyiwLB7qjKGifx+fVAsTT5vYris3AHKk6/lwWWqGqsiFTFfEcbAIGcm+cdTE6yLR4Lz4pX1aNJuV89QhQmXLUdsN7nfBzgmZQhIhKB2Uzbg5kXyzn5G5e4qet8iCl69jjmO/ojMM857ofJrxaQhkygjdsCcopv5IiIbEzacAh0fDYcyorIez6XihLgaQi8vo4CtVX1RjGVtFHVf5znxkAnTFW/SUr9pKrnRCSgPR1V9VHHy260iGwGkozISdd/dk1c9hnitoCcoKqPOv/8QETmAEVVdYObmrKgPVBNVU8576BRzvFOl3Vliaq+DbwtIk95xWiZFhH5EBPp1RCTH74T4MnNB4s7WEOmJWBwwrHGEOD5VESkK0bjCRH5DfPA8S2wFrML6QWeB2oleWGKSCgwH1MFL1DJiwnfz0PqPJnHMHnWApVrMC/txUmd3ysOeNgVRdlEREZitG8CBjjeGb2A4Zjk6IHMX8BWjxkxAbaKSDcgWEx13t7ACpc1nRdV3QxsFpEpwAlVTYDkDZ98roq7MN4Cmie9xDghz98Bgezt9S3wD7AS6IExYOYF2qvqJjeFnQ9V3euE2/4cyGGH2cBL84uXNxw8u446nBOfqtnOM1dAGwQdTopIcVJ034gJFw5oVHWtiPTHpKy4npTvqWKMJgGNF9I8ZYaItMOEOium0E8gGzJPJ6UyUdXDIrLDC0bMNHwgIr1IGdeRmFRtAb055VBfVauKyGZVHSwib2BStlks2cKGllssF4iIbMXk8frdeahbiQnhm+KytGwjIltU9Qaf4yBgs++5QCXQQ5ozQ0TqqOpKt3VcCCKyDbhRVU87oXBRQFVV/c1laVnieGQMBRaTOjQrIKvbJyEiBTEbDUmJ2udgKtyeyfyuwEBEVgFNVfW4c1wYEz5Z111l2SOjEH4PhPUnz+WOoeQQUF5V49xVlj1EZCwwUFX/dFtLTvBKSLYvIhLi4ZQJnltHAcQUs+oC3Ijx+r4DGKyqE10VlgUiUhsYBVTGGKQqAHcGspedk9dzJHAdJrw8YLVmhojcAozG/A55MVFHJzyQGmc0ZqyMd051Bnao6pPuqcocETmCKSIGJgqjsc8xqnp7RvcFEk44fyFSKtrfjTHQPuKequwhIqtVtbaIrMZ4x/4N/KKqV2dxq8UCWI9MiyUnnFWn0rqqbhCR3V4yYjrMdsI+vnOOu2CqOnuBk46nYNqcKk3ck5QteorIdlU9AuAYBt9S1f9n79zDLp3q//96zzDOQ0gp51NCxvlMkkOFKCHHiqKc6ZeUJHzlUFQOJcIXOSeiiMghBmMwwzj1zSGUVM5nhvfvj7X2PPvZs5/97GdOa63nWa/r2tez73XPvq737Ove97rXZ30+70/OmY1v2H4TJpXCPVJCEDNyNCFzZFbCQqAIoifTofEFgKQfA/8vmajumbURxASw/WoMzJbCWElnErIcIWTY393h3+fApICU7XfjfFREEDOyIPCApDHAa43BnL3gWqxNFmg5zn6zBFgsesMtR+85NGtvz0iJ8yi2z4/+x58kBEy2tv1QPx9LhqQ5bb9q+05JGwErEHRPaDwTZMwYQsO83QqsyGhwCqEh6qWEDua7AksnVdQdGwErNL53SWcBOZfyb9NyfEoSFVPHWrZHNR1fFy0VSuCamPH9Y0Ll17v0BGQrlX6pgcxKZeC0LlzmbD4uYBGD7W9J2gZYl/BwenpBwdjzCQ1FtgC+TvAm/U9SRd2xYmPxBZMCg7l7qy0p6cr4XoQFcOM462ADMK/tTfv/Z0WwHWUEMl+TtEojA0bSqoRO2qXwDYK/5H6E6/0W4OdJFfXPKEkv09NsZramY+eewUPoiFwazdYmZ7Qcl8DZwOHATwgZSF+h5/rJnRLnUQBsPww83DiW9KTtRRJK6sQ4SYfY/k2sBsh9Q6eZtW0/K2kfWgJTkvaxXUSwKlZ9DY9WLWdLytpiJvJXYCGCtQ+EjaoJ6eR0xvYN0P66iNfPDUmEDYz3JC1m+wkASYtRhm0Ftn8Q314aratmizZzlUpX1NLySmWASDq803nbJS7MikGxQ2lzyaekm21/PLW2TsQd0g1tvxCP5wVuzrmcX1LH7zRnHydJxwJ/tp1147BukPSU7ZwbKwGTyvkvIlgQQFjEbG+7iEWwpDkIJVm9PD6dcefSwYCkDxC6DAOMaXg3546keUtcdDXNoc22BH+xvX5qbf1R4jzaFznf1yUtDvwMmJlQnv14YkkDpp3tgwppziXpFmBj4FfAv4BngC+3ZN5lh6Q/A2vQ07BlTYLH92uQb6l24dfKJsCZhCCygKWA3W1fn1RYl0hag2BZMSm5zvYFyQRViqJmZFYqA6QRqCxxESPpFdo3Jyglewd6SimfkbQ5IWiyUEI93XICMFpSo6HStoTy52xpBColbQFcbbuIXd7I3sDBkt4G3ibzazwuyNueopBsKYcGC8sSGnOI4I1VkhffDYTFY6M8fjbgOiB7j89oP3CW7QdTaxkIkrYj+NndRLhmTpb0Lds5N55rcKekcYQMx2sKKmN9M/pi/1/MOvoHsEBiTd1S3DzagWyvlxi4/KykLYHbo/9xc+fvLANSAJK2J5RlLy7pt02nRgIvtv9UduxC8MXch9CIa2EmL4POkaJ+ix2ulbko5Fqx/SdJHyH4qQp40LGBUe5I+l+CxUmjrBzCfbEGMitdUTMyK5UpRKFjeYmLGKCc3cZWYlDtL4QHu5MJD6dH2L6y4wczQNLyhFI+ATeUEnSQ9GtgbUI3wbNz9vYqFUmPEx7g2gUtXYh/HZJWYHLvvSI8jySNs71Sf2M5IumrhBLhmQhz0oW2X0qrqn9iht0mjSxMhW7O1+eeeQQgSYTA926ELKSLgf+1/dekwvohZk4/ROgAfhQwN3C87Ts6fjATSppHW/1Tm08Bh9ruawMrOZKWBk4FXo9/mwOZ2ZbcxmzSJYFjgEOaTr0C3FvY5lqRRG/s5gy7lxPK6ZPBcK3ETalPMXlW40mpNHWLpIeB5QpLkqhkRA1kVipTSKmLmAbtSikq0x9JC9A7yFNEt15JI4EdCMES0xMsybKxSPx97gQsbvsoSQsDC9oek1jaoCXabmxICGReDXwauNX2F1Lq6hZJtwH7tnh8nmJ77bTKuidmZnyF8Fu9DTjD9o1pVfVNc3lzPB4GjC+tVFjSJ4BfE7rHjgcOcUHdtSUtavvvqXV0SynzaKlWRJL+h9BZ/Vu2r0qtZ0qIwbQ3bFvSkoRKgetsT0wsrU8k3U+HTN2GnVKuSNod+B9Cdt179FTC5OoFWzySriJcM/fTe7PhsGSiukTSZcA3SrGTqeRHDWRWKtOAEhcxpQYyJZ0D7O/CupZK+iyhLO5DwL+BRYGHbC+fVNgAkDQ/sDNwACGjZyngJNsnJxXWBkm/IDzUbWT7o/E6uc726v18NDmSPg+sR3g4/YvtKxJL6oq4CBtFyGQYFb0Pf2V7y8TSumIQeHwOJzRB+wohY/0SwnX0mu0vptTWF5J+BKwIXBiHtgfus/3tdKq6Q9J8hPvhLsCzBJ+yK4GVgEttL55QXlskrQ18GLjF9r8lrUjIRFo/V7/GZgbDPFoCko4DflBKiWo7JI0FNiBkHN8F3Au8YHvXpMI6IGnRTudz32yIlWrrlhaYkrQVcCzhvtKw88nWiqiZ1s3AkpB0PbAywVP1rcZ4ztYVlbyoHpmVyhTSZhGzL02LGCDHRUzz5DBPyzG2f0v+lNq19ChgLULZ5Mox+L1DYk1dEX2ydiOU4JwHrBEXwbMTAprZBTKBNW2vIulemHSdjEgtqj8k/ZwQIG4Edr4uaRPbeyeU1S1v2H5P0sSYwftvoIiSeCjb41PSicBnCT6fP2zKPD5O0iPplHXG9rckbQOsS/jOT7d9eWJZ3XI74X64te2nm8bHSjotkaY+iUHjLQiWON9W6BK7F/BDwv29BIqcR6NlwteYvPwzy++9sZEQA8etvARMsP3cjFU1YIbZfl3SboTM+mOjp2225B6o7ILHgCzLyPvhBOBztu9PLWQKuFbSRrb/nFrIFHBMagGVsqmBzEplyilqERNpzoy6ueXYQAmBzGGS3ufeXUtLuJe9Y/s5ScMkDbN9Y8x6KIFtgZ/YvqV5sGmRkCPvxAw1w6SFZAk+PB8HVmh47sYM5FIersdKmgc4A7ib0DSntFL+1ekJNqwsqRSPzwnA99y+w/oaM1pMf0g6gFD6fq/tywj+u8UQ7y2/t31Uu/O2c7y3bw6sbPvNmKH+T8LG4P8l1jUQSp1Hf0fw9r6enqYWJfANgj/2zfF4A0L21NKSvu+8uwsPi1n2OwJ7xLHhCfV0jaS1CBvEHwVGEHS/VkCG4CHAbQrNoZoz7Pryis2FZwsNYkK4r1wlyfRubJmt/26DnL12K2VQwuK/UsmVj/TV4CfTRQy2v5JawzSg1K6lL0qaE7gFOF/Sv4FsvZqa6VSKlfGDyEnA5cACko4m+H19L62krngEWARoZGYsDNyXTk7/SFrX9m3AgbbfAk6T9EdgpO2stTcj6TxC1nFrB81sA5mSGvYg44BlgzVsD7bvybTpz0LAzwia7wNGEwKbt9t+PqmyLrD9rqTsGxK18IbtN2FShvojhQUxodx5dPYS7BLa8A7wUdvPAEhakBBgWwu4iby7Cx8EHAH8wfYESUsQgj4lcAqhm/alwGrAroRKjdw5jXAf7+XXWAB3STofuILeAdjsm4gCPwHWp7zvvGHn0wjYz0IIwr5VQMC+kgnVI7NSGSBNxsptsd2uFCcrYtbUrkxe5rRfKk0DQdJywEaU0bV0FttvSZoDeJOgeSeCb9P5OZdnSXqF9td6Ef5BsUz4k/RcJ9l2W2+6r8xNyApsZDKuAYy2vXEqbf0h6W7bq5bqu9tA0kOEDprFPBhJ6tTIx7Y3mmFipoBo97AasA4h82tt4EXbyyUV1gWSTgCWJgQbXmuM52rRIulFQgAQwj1x/abjrJ9dSp5HYVLznNG2r06tZSC0899rjEkaZ3ulVNoGM5LG2l5N0n2NBj+SRtteJ7W2Tki63QU1x2sQNzFbcc5+qg0kXQt8qqTnlgaS7iJYtF1EeNb9MrCw7e+n1FUph5qRWakMnB+nFjANuJpQHlTiDt4ihJLVK5vHnGnXUoIFwSrAabZ3iWPnJNTTNbbnSq1hSpH0M+Bi26em1tIlJd9X3pF0NvBhSSe1nixlg4RQnv1B4JnUQrrF9idSa5hKZgNGEgJScxPKnUsp8ZsXeI6wqdYgZ4uWrVqOS7rnFDuPRvYHvivpbUKWIxSwGUgoE/4doXEYhMqG0TGgnLUXYmxO+E1geXp3uN80majueT1u8oyTdDxhTpojsaZuuCHaDV1F78zGrK+VpntKifwT+LOkq+n9nU/2LJYhw2w/Immm6Ed+hqTRQA1kVrqiBjIrlQFi++b+/1X2zFqAZ01f/IGeLMHZCE2VHiE8rObICElfAtZpba4E+WbvNJA0jNBFeIXUWgbIPcD3JC1DKDG/2PbYxJr6pPm+otDtu9FdfYzz7wC6BbAxIaBTRIfvPpgfeFDSGHovCLLNVGtG0jpMnmWfZVm8pNMJ9+xXgDsJpeUnNryPS6A0q5aWe8xswCK2s20E1ULR82jBm4J7AdvR04zrYuAS2+8R/DJz5teEuf9zwN7Al4B/JVXUPbsAw4B9gAMJFjPbJFXUHV+Kf49oGjPBLidbJC0FnAp80PYoSSsCm9suoRnN0/GV+6ZIO16LAfvxkn5ICNjPmVhTpSBqaXmlMkAkXWJ7O0n306bstlEGkjOSDiRkNf6e3gv27L3JWokecXva3jO1lnZIWo9QArcdTVmkEefatbSZ6B30nYyzXvskNoPahuA3tYjtpRNL6oik7YAfEfzHGuWf37L9m06fywFJo2yPT61jSpH08XbjJWxe9eXvmWs2bPRQnZ+QBTuakHE3oaTyOEmzArszecZX1vd0SVsSsjFH2F5c0krAkTkH7AfJPPpZeoJ/N9n+fUo9g50my5P7bK+oYCB8o+0NU2ur5IWkm4DvAqfaXjleKxNs55ogMRlxcwrbb6TW0i3Rt/afhPnzm4SqjFNs/zWpsEox1IzMSmXg7B//bpFUxdTxNiFYcig9wVgDSyRTNIXYvicaRmeJ7VuBW6Pn0Zmp9UwhCwIPxEy1Zi+4bBe+TSwFLEvIVMvWS7WJQ4HVG1mYsdv69UD2gUxgJ0mPA28AfwRGAQfY/nVaWd1RQsCyA6tRkL+n7U/FxeLyBH/MbwIrSHqe0PDn8KQCu+M84GFgM+BIQqAtWx/eJn5A8CO7CcD2OEmLpZPTP6XPo5KOJWTZnx+H9pe0nu1DEsrqF0lbAccCHyJsrBXhjx1plPD/S9JmhIDJwgn19IukpQnPAM8DJwJnEDYzHwW+avuuhPL6RdJMhA7xkwL2wK9s596Qaw7boxvN8mxb0jv9fCYLYs+AcwjP6ZL0NPDlnD3hG9h+LL59EzgspZZKmdRAZqUyQBrdG23/vb9/mzEHAUvZ/m9qIQNFUnNJ/DCCb9Z/EskZCC9Lmsv2K5K+R9B9lO17UwvrgiP6/yd5Iek44POEBcAlhO/6xbSqumJYSyn5c4TrvAQ2tX2wpM8RSp22BW4klPhlS1NTK9E7y76kRXuJ/p4GJsQmNC/F1xaEIFsJgcylbG8raSvb50i6ALg2tagumGj7pdYO94VQ6jz6GWClWJKNpHOAe4GsA5nACcDnbJfiW9vMDyXNDfw/QtnwyPg+Z84GziVovRM4gFAavz6hk/ma6aR1xakEL8+z4vHOhN/oHskUdcdzkhYnzv+StqYcG4LTge/a/hOApI0JAfD1kqrqgKR7Op13wU0jKzOWGsisVKYQSWsBJwMfBUYAw4HXCln0PgC8nlrEFNLsNTWR4Jl5WSItA+Ew25fGErnNCKV9p5H/g2mpmWqPA2sXGKz/Y+xCeWE8/iJwTUI9A2Hm+PczwIW2ny8hWFKwf11zt/u5KMjfU9J+hEzMdQmZU7cRysvPopxmP42MnRclrUBY+C6WTk7XTJC0IzA8ZoDtRyjvL4Fi51FgHkKmHYQSyhJ4ttAgJrYbFgT3EQKBSNonnaKumNP26QCSvm770jj+J0k/SqirW9ayParp+DpJJdjN7AOcCSwr6e+EDcEvppXUNXM1gpgAtq+XdEJKQV0wgjB/XkBYw73V+Z9XKu2pgcxKZco5hTDRXUoo69uVUMZaAu8SuiHeSO9Fb5Z+as3YLi47MNLwrdsc+IXt30n6QUI9XdOUsQbhAWRmMg3aR89UgDHAIrHL/SRsd9wJTo3tb8VmFo3mCqfZviKxrG65StLDhNLyvWJZ/JuJNXWNpB8DZ9kuwYKgQUmdp5tZjGCXcGCjyqFATpf0PkJJ3JWEJgUldFvdl1C++hZhIXkt8D9JFXVPqfPoMcC98ZlLhNLb76SV1BV3RY/sK+j9rNjqU1oKBxOe3XPlvab3rZ2+3yN/3pO0mO0nAKJlRda6JQ0HRtneKGbwqpDqnQZPSPoOweoEQhZs1hWDtleIm387EOw2xhPmousbWeuVSjfUZj+VyhQSvZpWaxiJx7HRttdJra0/YvfPybB9zozW0i1NmUdtyTXzqIGk3wP/IHR3XpUQ7BnTsntdBLHsZg3b302tpZW4UOwL295ohokZAC3B4tY0xjcJJfKH2r5hhgobIDGw87LtdyXNDoy0XUSJlqSvAl8hbPKeTcgqfSmtqu6QdJztb/c3lhuSlgSetv2WpA2BFYFzC1tIVmYQJc+jkhYk+GQKuLOE+2JsItaKbe86w8VMAyQ9ZTtbn0xJrwN/I1wjS8b3xOMlbM+RSls3SNqEkNn4V4LmpYDdbV+fVFg/SPqL7fVT65gSJM0HHEVPKfktwOG2n0unamBI2p5gS3Cc7RIyjyuZUAOZlcoUIukWwsP0rwglZc8QDJazf6AGkDQCWCYePmI7a2Prpo7Cnyd4wTV893YAnsgxqNZMDOp8Crjf9v/FRc3HbF+XWNoUIekO22ul1jEUiBkDKwDn214htZ5WJG1k+88xk3QybP92RmuaGiR9hBDQ3IFQ8nyG7U4B8uRIuqfVV6p5ky1XJI0jVDQsRsgMvBL4iO3PpNTViRaf5smwfeKM0jIlSPoTsG0jWBw3Hy6yvVlaZf1T2jwqaVnbDzdVCvQi9wqBwYakJ20v0v+/TIOkRTudL8GbP3bP/ighkPmgC+iiHf12XwUupndDy9as2KyIz4ZH5940rB2SPghsD3yB8N1fAlyW+3deyYtaWl6pTDm7EJpw7AMcSOiGuE1SRV0SM1/OAZ4gPGwsLOlLtm9JqasTDZ9GSUfZ3qDp1FUxqJwlkkbGiXlWYpdYSfMSyrTGJpTWNS0BqmGEwEPWu2CSZga+Qe/umb/MPWDfDtvvAuMlnZxaSx98HPgzsGWbcwaKCWTGhcGy8fVfQsnTQZL2tJ2dZ5akbwB7AUtIuq/p1FyU4Xv4nu2JsUHUT22fLCn3xi3FeqpG5m/OeLX9gqQFUgrqj4Ln0YMIjU7aedYZyLVC4Ju2T5DUNihvu2MwPyWSXqD984nI/LfbHKiMQc2lo+fhbGS8Zpe0AzDc9q9j4PKeOP5VSa/Yvjitwn7ZM/79Jr0b/2Ub9IbwbChpjdQ6BoqkGwiewZcCX6apYWvTvb5S6ZeakVmpTAXRAw7bJXTNnoSku4EdbT8Sj5chlFGumlZZ/0h6CNjc9mPxeHHgatsfTausPZJ+b3sLSY/T84DUwLaXSCStaySd3XQ4kRAAP8O9u2tnhaRfEbw8G3YJuwDv2v5qOlWDG0mL2368v7FciYv2zwI3AGfaHtN07hHbH0kmrg+ip9f7CB58zVkZr9h+vv2n8kHSncBPCZ6NW9p+XNKEHDOPBwtx/v+c7Sfj8aLA5a0ZvTlR+jwqaVbbb/Y3lguStrZ9haTd2523feaM1tQtcTOqT+LGYNZI+hohAD6v7SUVmnKdZvuTiaW1RaEL9YatAag4P/0557WFpGEEq6Q7UmuZEqK39xKEoGBzNmm2PraSnqZns6E5ECXC/TzrAHIlH2ogs1IZIJIEHE7IxBQhQ20icLLtI1Nq65Z2JYcllCECSPoUcDrwWBxaDNjT9rXJRFWyQ9L4VpuHdmOVaUcf5c1357yIaUbSboQS29fbnJs7d7/MuID/AE2ZO41gVa5IWg74OnC77QvjxtT2to9NLK1fJM0K7A4sT8gUBMD2bslEdUHTHHpzHNoA2KPOodOPPu6Nk43lhqRFWu8hklYpoSReodHMP22/rdDlfkXg1yVke0XLjTUIXqorx7H7bX8srbL2dFo/lLC2KNkqqVQf27iWXtD2P1NrqZRLtmnqlUrGHEDoKLx6I9NI0hLALyQdaPsnSdV1x1hJZ9LT5W4n4O6EerrG9h/j7vSycehh2291+kwOSLqhdTe93ViOSFoIOJlw3Ru4Fdjf9tNJhXXmXUlL2n4UJv1Gs8/EKBFJyxKCOXO32BCMpCnAkytN/nXjgGXD83UPtu8pIIi5D/AD4Fl6usSasHjPFtsPSvo2sYQvzqnZBzEj5wEPA5sBRxLm0YeSKuqCOIeuAqxF2Iw90PZ/E8vqitLm0egD92FgNkkr05NJOhKYPZmw7vmtpC1tPwMQA4KnETybc+cKYHWFhmLnAn8gdEbeIqmq7ngrBmABkDQTedv5jJA0e+smoKQ5gVkSaRoIf5K0le3fpRYyBezrApvj2bZCE9ciNroreVIDmZXKwNkV2KT5wd/2Y5J2Bq4DSghkfgPYG9iP8GB9C/DzpIr6QdLBto+Ph5+1fWnTuR8602Y/MWtndmB+haYKzQuZDyUTNjDOJiwAto3HO8exTZIp6p9vATdKeozwnS9KaOBSmfZ8hLA4nIfePpmvAF9LomhgtPOva5Ctj10LBxCa5BTTqRRA0pbAj4ERwOKSVgKOtP3ZtMq6Yinb28YF8DmSLiA0LCqBWYDnCeuA5SSRs0d2wfPoZgQPuIWAZr/Jfg+hkgAAIABJREFUV4Asn1la2Bv4naQtgJWB44HN00rqmvdsvxM3135q+6QC/Hcb3Czpu4QA+CYEH+SrEmvqxFnApQpe0k/DpA3wnxOeFXNnH8JG7FvAG/SUOM+bVlbfSPoM8L/x/ZvAdgWWx48pJcO7kie1tLxSGSCd/LtK8PaK5Yfn2N45tZaB0FyG1VqSlXOJlqT9CUGGDwH/oGcB9jLBZ/KUVNq6RdI42yv1N5YbkmYhBNlEIZm7JSNpbdu3p9YxFJF0I2GDbWJqLQMh+jVuBNxUQgllM5LG2F5DodncXsC/gDEF+DUeR+gW+wBN2bs5B49Ln0clbWP7stQ6poSYhXkq8Dawhe1nE0vqCkljgB8BhwFbx4SD7J/RYZJv4+7ApoRr/VrgV8540R6rAr5DT5LUO8Cxuf82oW9f1Zz9VCWNJ/Q6eEDSOsAxtj+eWtdAkHQ/ocP9owR/z0YAOcv1XCU/akZmpTJw3p7Cc1ng0OXu/ZJG2M5ebxPq432742yw/TPgZ5L2tZ1r1+n++G/MOL4wHu8AZJ35FR/yLgIuaZSXV6Y790ram8I8A5uJC4LF6O0zeW4yQd3zGHCTpD8QOjkDYLtt1+GMmGj7pZZy/mwX6y2cHrMDDwOuBOaM73Nna0L2bjEbO4NgHr1J0knAevTYsxyZawa1pMvp/TucHXiRYKGE7c+3/2RW7EbYYDg+BjEXp+cZJkuabBKOsf1t4IzUmrrF9imxVPglQqLUC9DeZzVD1uxjfPQMVTEw3rX9AIDt0ZLmSi1oCtg6tYBK2dRAZqUycEZJamcWLgrwg4s8Adwm6Up6d7nLedHrPt63O84O2ydLWgFYjt5BnhKCJLsBpxBsE0x4uMs9OPVZQtbRJZLeAy4mBDVzf6AumSI9AxtE0/wlCV6ZjUwME/zVcufJ+BoRX6UwQdKOwPDofbwfeS8eJ2H7V/HtzYSusaXwGDAzTQHvUih4Hr2IYOGzTTzeiTAnbZxMUWeyz6LrD9sTJB1Ab//do9Oq6pcFJX0c+Kyki2jZpC+gBPfyNtl0VwC5Z9g1b0DNSvBtvBfIOcNxAUn79XVs+6QEmromZsH+1rUBZ2UqqKXllcoQRNLh7cZtHzGjtXSLpHfpKT2YDWiYiguY1fbMqbR1Q/zONyQswK4GPg3cavsLKXUNBWKA5DBgJ9ttS4gqU4+ke22v3OhSKmlm4FrbJXhMIukhYLmcy/f6I2Zl2ParqbV0g6TZgUPpXUJ5lO03kwrrQPT1vM/23+Px9wkBqr8TmqA9nlJff0i6DBgF3EDv7N39+vxQJpQ6j0q62/aqLWNjba+WSlN/xEDD1bY3S61lSpC0OcGXdITthv/u4bY/l1han0j6AqGkfD1gbMtp5zqXSlqGUCJ8InBg06mRwHdtL5dE2BSi0PH+h7Z3TCylTyQd1eG0bX9/homZQiRdCPw/2/9IraVSJjUjs1IZQkiayfbEnAOWfTEIAlBfICwe77X9FUkfAH7Vz2eSIulkOmS75r7wjQ+j2xEyM98FDk6pZwjwTvz7Ysya+hehTLsUJgAfBJ5JLWSgxO/7PGDeePxfYNdG6VmuxC63h8ZXKRxN6PhNbIKyM8FuY2VCR+fcAz9XxleJFDePRm6U9EXgknj8BUIX7WyJNkRvSxppu10VUu4cSSgZvhHA9jhJS6WV1BnbvwF+I+kw250CVbmxPPB5QsO/bZvGXwH2TKJoKrD9RJxTs8X2YQCS1mpt8iNprTSqBsz8wEOSbqd3dWAJ1hWVDKiBzEplaDGGWOIh6WTb+ybWM5R4w/Z7kiZKGgn8m/zLEZszAo4A2mby5oikOwnlk5cC29p+LLGkoUCRnoHR18vAXMCDsUlEc6Zatk1QmjgdOMj2jQCSNiT4q62TUlRfSPqp7QOavvteZP6dOwZgISzez7R9N3C3pL0S6uoK2+ek1jAVlDiPQgjmHAT8Oh4PA16TdBDhehqZTFlnXgXGS7qO3oGGg9JJ6pp3bL9Ykv+upGVtPwz8QdJk5di5lpbbvhy4XNJ6tm9tPidp5USyukZSwzYJwm9zZUIztBL4OZOX7p9KKI/PnWNTC6iUTQ1kVipDi+YnunWTqRiajJU0DyG4cDdhgTAmraTONC94JR1Q2AL4S3FBUJlBFOwZ+OPUAqYBczSCmAC2b5I0R0pB/XBe/Fvidy9JcxLsTT5JWEg2yN4nO1ptHMPkPpMl/GaLm0cBbJfYiAPg+vgqkYckbQcMi41+9gfu6OczqTkI2AM4oc05A1mWljdoBDFjqfkXgR2BN4GVUurqgglN7ycSvD5vTiWmGyStSagMeH+LV+ZIwiZ+9ti+IbWGStnUQGalMrTIejd6MGO7kalzmqQ/AiNt35dS0wAp7dp5PDYRWYzeHaiPTKZokFK6Z2BjwSLpuNgpdhKSjiMEZnPnMUmH0RMg3BnI9nuPGYzkvljsg58SGkK9DDxkeyxMyjwqwZbgbEJ2/U+ATwBfoaWpSK6UOI9KGkFo7rM8YR59EDjf9ttJhXWB7TMlzQQ0SrL/ZntiSk0DYB/g+8B7wOUE/93vJlXUD7b3iH8/0Xou93JhSQsRgpc7AMOBhYE1bf8tqbAOSJofmM/2mS3jy0qaz/ZziaR1w+yE0uyZgPc3jb9C7/L+bJH0Cj1ri5kI181bGWeoVzKjNvupVIYQkl4H/kZYtCwZ3xOPbXvFVNoGK5IWBV60/VI8/gSwNSHIc0oJixkASfe06UaZLXGR+xIha6fRgRrb7TIdKlOBpPuAtWy/Hj0DT6THM3DbUppFtLvGG42LUmnqlljSfwShSYQIHZJ/YPuFpML6QdK6wA+ARQkLmcZclHV2oKQPAwsA422/F8cWBGay/VRScf3QaDwj6X7bH4tjf7G9fmptfVHqPCppOYLNxm2EuUiEMtB1ga1y97CVtD5hc+QfBO0fBHaxfVtSYUMQSU/aXiS1jnZIuoVwP7wYuMj2Q5Iet714YmkdkXQBcEZzNUMc/zShOeTOaZR1j6QlGtZJCj4Ks9t+rZ+PZYekYQSrllEN/89KpT9qILNSGULExUCfNDKqKtOO6NX4Odv/jF0zryeU9a1I8HD6alKBHWjZLZ2d3p3ic/b1QtIE21mbtQ8WJI23PSq+Pwt4xPZx8Tj7ALikbwB7EcrhH206NRcw2vZOSYQNASQ9TOhy27rhkHMmDACSbrD9yf7GckPSbcD6wG+APxOCVMfa/khSYR0odR6VdAPhu/1Ty/jGwKHtMu9yQtJYQtOwB+PxR4HznHG39QbRY/IQJq/KyHo+6gtJT9leOLWOdkj6A7ACIfP1AttjJD1WwIbUA7aX7+NcEc+Qks4lZB9PJPjaz0+455yYVNgUIukO21lnH1fyoZaWVypDiOZAZQxqLm37ekmzUe8H04vZbP8zvt8ZOMv2CXH3cVxCXf1SsK8XwGhJH7N9f2ohQ4CiPQOBC4BrCIGRQ5rGX7H9fBpJ3SGpY/fpzJvmALxk+5rUIgaCpFmJZX0xE7ZRlj0S+FAyYd1zAEH/fsBRBN+9LyVV1D+lzqMfbg1iAsTnrpNTCBogIxpBTICYaTcipaABcAGhlPx+Qnl56WSbeWR7c0nzAl8AjpO0CPA+Savk2qAo0mndU4TPJPAx2y9HK6XrgIMJAc3sA5mSmp9PhgGrUYjNSSUPauCiUhmCSPoawVB8XkKJ+ULAaYQgRGXa0jwpbwR8ByB2Xk2jaGiwHvBlSY8TOlBX+4TpR9GegbFc9SVgB0nDgQ8Qno/mlDSn7SeTCuzM2sBTwIXAnZS3CLhR0o+A39K7U3zOi989CcHAD9FTLgzh+j81lahusX1XfPsqwR+zBEqdR4dJmsX2W82DMRhewhrsHkm/pMd7dyfg3oR6BsJztn+bWsRAkHQV7QOWAuabwXIGRNz0Ox04XdKHCH6Zp0n6gO2O1WAJeVTSZravbR6UtCkZe0y3MCL62G4F/ML225JKCdw3e3lOBJ4g/D8qla6opeWVyhBE0jhgDeBO2yvHsUl+WZVph6SfAQsSAjqfBZax/U70U7uqhBKtEunLRqHaJ0wfOngGzpx5IHASkvYh+DU+S08GT9bB7xh43YTgSboi8Afgwty99xpIurHNsG1n3Z0XQNK+tkvIquuFpNWAQ+nxJQUg8+u8yHlU0vcInYX3sf1EHFsMOAkY68ybz8WA63709t492fabSYV1QQxGbUOwIWjeJOmYxZ4SSR/vdL6k5mjRr3EOYIGGh2NuSFoWuIrQ0O/uOLwasAGwpe2HU2nrFkkHAt8idF7fjNBk6QLb6yUVVqnMAGogs1IZgki60/aaku61vXLczbsn54VMqcSHue0JJvmX2v5HHF+Z8IB3bafPVwZGLG/qk9xLhUtH0ucJi14Dt9q+PLGkrpH0N0KX1ez9GdshaRZCQPNHwJElBtlKQ9I6TO7Bd24yQV0g6RHCwrdXyW3OmzxN8+iCwCUlzaNxg+RgQjk/wGvAj3P+fcambaNLni8lnUPY3HmQ3htTu6ZT1R2SVrV9d8vYlravSqWpG0r0a4zB+l0IHp8ADxB8YN9Ip2rKiffKmXNtgAYg6RjgCdu/bBk/EJjf9qFplFVKowYyK5UhiKTjgReBXYF9CY0uHqyTx/RD0nG2v93fWGXqiKXkpn2JrXM3ny8ZST8HliKUOUMIPDxqe+90qronZgduYntiai0DIQYwNycEMRcjdEk+qxHsyR1JmwPL0+SnmnumGoCk8wjWLOPoaVRk2/ulU9U/km4tOVtH0gcJFSUG7rL9r8SS+iUGS2YGsP1KHJs310ChpCsImaQvEDqujwZus/1IUmEDoJRmLe2QdA/wpYbHt6QdgANsr5lWWWeakiN2JPxGDyZkHtckiemIpM2YfA79YTpFnZH0ILBCo3qnaXw4oaqnyN9tZcZTA5mVyhAkGuTvDmxKCPhcC/zK9YYw3WjXvVnSffUBrzJYkPQA4eHU8XgYcH9fXUFzQ9KZwEcI5dnNpYg5Z5OcQ8gkuQa4yPaExJIGhKTTCJlqnwB+RWgWMcb27kmFdYGkh4DlSps3JX2SEPS+gd7XefZ+gpJ2Bw4ndFsX8HFC9vFZSYX1Q+zqvFVjkySWxP/e9qpplXVG0lLAOvG1NqGy5M4Cmog17ufHlxR8bSBpCeA3BE/S9QhJB1tEP+dsic8Ao4DzCX6NN0kab3tUYmkdkbQVcCzB91j0eKqPTCqsC+IG8jyEcvizCXYKd9jeLamwDnTaZFCHTvKVSislGE1XKpVpz2yEjJ0zYNIu2GyErsOVaYikbxAyXpeQdF/TqbkIWQ6V6URLmfNfbF+RWNJg5xFgEaBRorowcF/f/zw7noyvEfFVArsQSlWXAfZranxSykJsHdsrxk2dIySdQGj8UwITCIGd7BtatfAVYFlChuCkklvK+N4PBlZu2D9Imo8wj2YdyASuAH4jaRvCffFK4P+lldQ/tv8W7ymN4M76hKBJCawB3BctQ5ob/q3S+WPpsf2YpC8SrpungE0LKXU+gzCHTgBuVuhe/kpaSV1xAvC5RgZsYawX59Dxtg+LFXeXpRbVD29KWtL2o82DkpYEsvffreRDDWRWKkOTG4CNCV1LIQQxryPsulemLRcQsqWOAQ5pGn8l17KywUCbMuevS9qklDLnkmjqtDo38JCkMfHUGhQUrLd9BICkucKhX+3nI8mxPSy1hqmksTh/PXa6fQ5YPKGegTA/8GC83pszG3PPVhtVcGO/p+kdGHmFEOjJGttnSBpBCEwtBuxpO9t7o6SDCRmYHwL+BtxByJjeuyDrja1TCxgoku6nd9fyeYHhwJ2Scm/INRx4yvaHmsaeBrJv3AY8W2gQE3rm0Dej7cZzhHtMzhwOXC3pKHo3WTqUAjZ4KvlQA5mVytBk1uZFuu1XJc3e6QOVKSOWAr0E7BAf9D5AuPfOKWlOF9LRuUA+Tu8y53MIzS0q054fpxYwLZC0AnAeYfGIpP8Cu7qQDuCF8ntJ8xAaFN1DWMSfkVZS1/wgtYAp5A5Jy9l+MLWQKeAfhKDO7wjXylbAGEkHQX42EA1djUNCNuY4YC1Ja+Wmt4k9CD7qVxA2o8aUsLEDIGkO268B/0mtZQrYIrWAKcX2u5IOoCkbMHogZtt0pom7JJ1PuN6L6HDfxDVxDv0xPX7N56SV1Bnbf4hB7oMJjecgNFn6ou1x6ZRVSqN6ZFYqQxBJtwH72r4nHq8KnGJ77bTKBi+xc+kPgGfp3UEz2x32kpH0W+DARideSYsSumfukFbZ4EbSB4DV4+EY2/9OqWcgSBoNHGr7xni8IfBD2zVTfQYQmxbNmrsPXDPxvrK07evjZuDwRjOXXInenksCj9O75Db7uUjS4Z3ON7Kqc6E0vc1IWoAef8w1gVmAewndzM9Lqa0Tkq6x/WlJT9HT+G/SX9uLJBXYD9Fb+r4SG55I+h6h0utiguUJALZfTiaqC2LjtlbsAjrcNyNpNkKF3eJu6XpfqQxGaiCzUhmCSFoduAj4ZxxaENi+TnzTj+jTtGbD26syfWgpc14d6FXmbHvjVNoGO5K2I2TW3USPn9q3bP8mpa5uadeUoIRGBSUTuznvRY+X7a2EJhHZ+2RJ+hohc21e20tKWho4zfYnE0vrSAy+TkZj06dSaSYG1lYGNgS+QQiSDE8qqgOSFrL9dGodU0PMDvxOaRU7MXjcSvbB48GGpCdL+M5jM7GDCKXwk6qEbW+aSlOlLGogs1IZokiamdChV8DDtt9JLGlQI+lGYJOC/KWKRNLHO523ffOM0jLUkDSecI3/Ox6/H7i+lECgpMsJ5c2N7IydgdVsF+e1VgqSLiH4HP46Du0AvM/2tulUdYekcYQNkjttrxzH7s/Zf7LUbC9JP7V9QNNGVS9y9yWV9CdgW9svxuP3ARfZ3iytsvZI+gw92ZgrERq5jY6v22z/K6G8jki6p4SGPp2Q9Gd6NmKbMxuzvs5LQ9JPaHM/aWD7oL7O5Yykp2wvnFpHf8Q59EyCT+a7jXHbdyYTVSmK6pFZqQxdVqdnF2zlaCR+blpJg5rHgJsk/YHeHjy5emQVSXOgsuQy50IZ1vIdPweU1IxmN+AIQvdmAbcQOjxXph8faQl03xgD4iXwlu23G53iJc1Eh0VxDth+T9J4SYsUlu3V2Fwo1Y/3/Y0gJoDtF2Lpdq58nRC0PBy4q4QM6SaUWsA0IFvLgf6QtCywHDBrY8z2BekUdWRCagHTiaznoSbes31yahGVcqmBzEplCBL9YJakxxgawsRXA5nTjyfja0R8VaYjbcqcT5ZUTJlzofxR0rX0dIr/InBNQj0DwvYLwH6pdQwx7o1NT+4AkLQmcFtiTd1ys6TvArNJ2oRQIn9VYk3dsCDwQOy2XkS2V8P2puCM+nebg8exvD/bYEPO10IXfFhSnxvEJWTZ2b65xI3Y6JG5KbAscC2wGcEuJMtApu0zW8cUdqZmjw2jsiVWkLS7hwiYbwbLGRCSRsa3v5O0B3A5vRM8svZUreRDLS2vVIYg0ex/OdcbwAynqaNmZTpSeplzqUj6PLAuMaPR9hWJJfWLpI6dSQtf1GdNnIs+QtjkAVgEeIjQEC3rBjSxTHt3wsJdhIX7r3KfV/uy3yghSChpXULTvEUJyRiNBi5LpNTVH5I+BZwONL7jDYA9bF+bTlXfSHqBvoMktj3vDJbUNZL+DhzZ1/l2wavcKNVvWtL9BCuCe2yPkrQg8Mvc51BJ5wL7ABOBscD8hOaQ2VZMSeroxWz7hhmlZaC0NOJqpXqqVrqmBjIrlSGIpEuB/Ww/k1rLUEHS2gQvmDltLyJpFLCn7b0SSxuUtHrVxaDD+Jz960pF0iv0LHpbH0zfBB4ldAPP8sFa0n+ApwiZpHfS8n8oIcBTKn01nmmQcwMaSXMAb9p+Nx4PB2ax/XpaZf1TYrYXgKSHgQOZ3FMt+yZ6kuYH1oqHd9j+b0o9nYjXcp80rvkcGSQemUVuxEoaY3sNSXcTmkO9CtyfuyevpHttryxpR4Lv8cHA2Jw30pqRNAJYxPbfUmsZCJJmbu3P0G6sUumLWlpeqQxN5gcejKVlzen8We+aFs5PCWU2VwLYHi9pg7SSBjVFlzmXhO25+joXF8QrAOfHvznyQWATQqOZHYE/ABfafiCpqiGA7b/HxicL07tr6T3pVHXNDcDGhMU6wGzAdYQGKdlSuO3GS7ZLvY+vQ8jEbPD7VEL6ozVQKWlemjwPgX/OWEUDItsg6wAo1W/6XknzAGcRMhtfJjTQy50R0eN4K+AX0fv4vdSiukHS5sCJBMuqxSWtBBxu+3NplXXFnUDrpkO7sUqlLTWQWakMTX6QWsBQxPZTjcYQkcHwwJ0ltr/VUuZ8WgllzoONuCAeLylbQ/eo8Y+E4PcshIDmTZKOrEb00xdJRwFfJmTtNrJ6DWyUStMAmNV2I4iJ7VclzZ5SUJccCqzemu0FZBvIlNRY2N4o6UeEhlzNm7BZB0skHUvIgD0/Du0vaV3b30koq19ikOQnwEKEYNqHgb8SPBCzxPbqAJLaZdO9BDxlO/cgVetG7PbA1Qn1dIXtPePbU6P+kbn/NiNnEOxNJhC8jxehZ4Mqd44E1gRuBLA9TtJSaSV1JjY6W5DgL/0xeqpgRgIlzKGVTKiBzEplCFJLJZPwlKR1AMcykP0IXnCVaUiHMuevScq+zHmwYvuXqTV0IgYwNycEMRcDTiIESyrTl+2AJW2/nVrIFPCapFUaC3VJqwJvJNbUDSVme53Qcrxa0/sSAt+fAVZqBNAknQPcC2QdyASOJmwGXhdLbzcBtkmsqVvOJPg1PkB4FvgoIVA1t6Q9cnwGkHQAodnZd4EtgfUI2k+3fXlKbd0i6YuEe/rRkhaWtGqjWVeOxKqRp2x/qGnsafK/pzR4x/aLLUkSufsGbg7sRtgg+XnT+CvAYUkUVYqkBjIrlSGIpLWAkwkPdiOA4cBrtkd2/GBlavg68DNCRsPThBLEvZMqGoQMgjLnygwmBhVWIFgPHGF7QmJJQ4kJwDxAER6NLewPXCqpUWa7ICFzKneKy/ay/YnUGqYB8wDPx/dzpxQyACba/o+kYZJk+0+Sjk4tqkv+D9jd9n0AMfPrQOCHhOzjlRJq64uFCM+JywL3AaMJgc3bU4rqFkmnADMTLBSOBl4DTqPHjzc7bL8bA8iXNY29B5SyufZQtAsZJmlxwrx0R2JNHbF9NnC2pO1sX5JaT6VcarOfSmUIImkswTPwUkJmw67A0ra/m1RYpTIDkLRn7hmClRlH9MJ6LR42PxQ1OvTWDZ7phKTVgN8RAprF+DXH5mFrAXcRuq4LeDjnJgWSZrH9Vnz/eXqyvW4pKNtrf+BsQubOGQQvtUNsX5dUWD9I2gE4llD+KUKg57u2L+z4wcRIugH4LHA8oezz38C6ttfq+MEMaDRwaRkbZ3ulxt9U2vojVu2sRvBVXTu+XrS9XFJh/dBotNT83UsaX0CTou8RSskvpudZANsvJxPVJbHp3PeBTePQtcCROTedk7SD7Qvj/XyyQJTtkxLIqhRIzcisVIYotv8maXj0hztb0ujUmgYzcad0X0LZanNTi6wX7IORGsSsNGM797Lawcw5wHHA/UDuvnWTsP2epBNsr00IwpbA7cAqks6zvQtlWifsZvtnkjYDFgC+QghsZh3IjIv2mwiZaQK+bftfaVV1xdbAm8ABhA3vuYEtkirqnkejN/NF8Xh74G/RRmRiOlldMRshcDx3fP2TcI/MnXfiJo8BJM1HGff1hrfnN5vGDCySQMuAsP0a8O34KoX3xb/zJ1VRKZ4ayKxUhiavxx3fcZKOB54B5kisabBzBcGz6SrKeLCrVCqV6c1/C86+uE7SNsBvXUZ50whJXwLWiRmZvbBdQmCzYQT3GeBs2+PVYg6XI5JusP1J4Mo2YznznVip8y7h+QVJPyR4OObOroTN40MI182tBE/SiUCW37uk04HlCRnHdxJKy0+0/UJSYd1zKqFE+/2SjiB4IB+RVlL/2F44tYYpRdIfgS/afjEevw/4te3N0yrryK8BbFc/zMpUUUvLK5UhiKRFgWcJ/pgHEnZ8T7X9aFJhgxhJd9peM7WOSqVSyQVJJxJKyq+koC7UMKmx2ByEIM8bZG5FIGk9YCdCcOHKltO2vduMVzUwJJ1N8JleHBhF8Pe+yfaqSYX1gaRZCV14bwQ2pHd33mtsfzSRtK5olAq3jGVfKlwqMSg1PyHLezQhi3pC7hslkq4G9rL9hKTlgY0J1/r1pXhOS1oWWA6YtTFm+4J0irqjDwuFycZyQtJ/gX/Q4wE72vZjaVVVSqQGMiuVIYik/W3/rL+xyrRD0o7A0oQSuKIW7JVKpTI9kHRjm2HbLqVjbFHEss/v2C6lYUsvov6VgMdip975gA83GrrkRvSAOwD4EGHh3uAV4AzbpyQR1g+S9iQ0KFwGeKTp1FzAWNs7JBE2AGJTy8OBRelt57NMMlFdEDOMlyf4Y65DaET3PHC77cNTauuL2GzmfwhWIcfn7BXcjuiRuSmhydK1wGbArbYny1zPDUl3A1vZfjoeLwL8LudAJoCk5ei5xtchbO7cDtxm+8SU2irlUAOZlcoQpI9d9qx38EpH0jHALsCj9JSW1wV7pVKpFEgMOOwELG77KEkLAwvaHpNYWkck3R69PYtE0oeZPDh1SzpFfSNpdeBp4Au2T46l/dsATwA/sP18p8+nIpanzgccQyjNbvCK7X+nUTUwJD0EHAzcTciaBsD2s8lEDQBJCwHrEoI8WwDz2Z4nraq+aWo68yngPJoslHIPTEm6n7BBco/tUZIWBH5Zgoe9pM2BnwN/jkOfAL5h+5p0qgZGrBLckrDps5DtWfv5SKUCVI/MSmVIETtn7ggsLqm5tGwk8FwaVUOGzwFL2H47tZBKpVLJAUlzE7KmNohDNxM6rr6UTlXX/JywWN8IOIrQ9fZUQkOXnCnN23NDV6DRAAARmklEQVQSko4jNG15kJ7glIEsA5nAL4GNYxBzA0JgcF9C0OR04AspxfVF9GR8AdhW0gqEDvcAfyF0Li+Bl21flVrEQJC0HyFwuS7wDqHs9nbgLPJv9vMOoeP3LITM3ZK84N+w/a6kiZLmAv4FLJFaVDfY/oOkNQid7RuNxLL+jUa9jUzMxYAngTuALwNjkwmrFEcNZFYqQ4vRhMY+8wMnNI2/AmRZmjWIGA/MQzmLgEqlUpnenEXwg9suHu9C6EKdfUkfsKbtVSTdCyH4E5vo5c5BRG9PSdl7e7awNfAR22/1+y/zYHhT1uX2wOm2LwMukzQuoa6ukLQ3sDehWSHAJZJOtf3zhLK65c+xEua39LbzyflZdzHgN8CBtp9JrKVrJH0KOJHgvbuK7dcTSxoo90qahzAfjQVeBkqyfRKhs/1MwFKSlrI9OrGmTtxB+H5/AvymoPt5JTNqaXmlMgSJJSBv2H5P0jIEX5hrSvO1KQlJNwErAnfR+6E6+9KVSqVSmR5IGmd7pf7GckTSnYSMkrtiQPP9wHXVomX6IekaYFvbr6bW0g2SJgAr2Z4o6WFgj0YZvKQJtldIq7Azku4D1ml835LmJDTmWDGtsv6R9Jc2w7a9QZvxylQQv+uv234gtZapRdJSwMhS/Osl/RDYGXiI3rZVn0mnqjPRHqRhm7A6Iat+LCH7+HbbTyaUVymImpFZqQxNbgHWjz5INxAmkO0Jfl+V6UOWJu2VSqWSkDckrWf7VgBJ6xI6gJfAScDlwAKSjiaUCX8vraT+KdXbM/I6ME7SDfTeENwvnaSOXAjcHLv0vkEozW4ES0qwTxChZLjBO/R0Xs8a2+un1jBUGAzftaQvAkvaPlrSwpJWtX13al1dsA2wjO03UwvpFtv/AC6Jr0ZyzVeAo4HFgeHp1FVKomZkVipDkEazH0n7ArPZPr42+6lUKpXKjETSKOBcYO449ALwZdvj06nqHknLAp8kBHdusP1QYkn9IukXRG9P2x+NG5rX2c7d25PYLGcybJ8zo7V0S+yevSDhO34tji0DzJlr1pekmWIW6cHADsBl8dTngAtt/zidus5I2sH2hdFvcjJsnzSjNVXyRtIpwMzABvGeOC9wbSH3xD8Cny+pnD9mdq9Fj0/masDfCfZnt9m+KKG8SkHUjMxKZWgiSWsTsjJ2j2P1fjAdkfR54DhgAcKityRfskqlUpnmxIDlKEkj4/HLiSX1i6RZga8DSxEacPzS9sS0qgZEqd6e2D4nal0mDj2SuyWO7TvajP01hZYBMIbgdXi8pBuB9QnPLF+3fVdaaf3yvvj3/UlVVEpinZZ74vOl3BMJPQ7ulXQ9vbPUD0onqV/+TrjHjAZ+BNzR2OSpVAZCDVxUKkOTA4DvAJfbfkDSEsCNiTUNdo4HtiwhY6dSqVSmJ5IOAl6yfSb0BDBjlcBw2z9Nqa8fziGU2P4F+DTwUcKcWgrvSBpO8CUjensW0WFY0oaE7/8JQmBtYUlfavhOVqYZk8rHY+Ay9+DlJBqNiGwfllpLpRjekTSMnnvifBRyTwT+GF8lMb9bSoKj5cnsNaBZGQi1tLxSqVRmAJJus71uah2VSqWSmtgEZRXbb7eMz0JonpNtMxFJ99v+WHw/EzDG9iqJZXWNpJ0IntirEIKCXwC+Z/vSpMK6QNLdwI62H4nHyxBKnVdNq2xwIelpQhfqttju81wuSJof2I3QCXxS4o7tPVJpquSJpF0JtgmrETqXbwccUUucpy+SzgX2ASYSejXMDxxbwv2lkgc1I7NSGUJI+qntAyRdRdx5bKZ20J6ujJV0MXAFvcs/fptOUqVSqSTBrUHMOPhWzMzImUmlzNFHMKWWAWP7/BgQbHh7bl1QpcDMjSAmhBJtSTOnFDRIGQ7MSSGNffrgd8AdwK3Au4m1VDJE0tXAXrbPjffEjQnX/La2J6RV1xlJF9reIZbDt1vPlbC59jHbL0vaEbgOOJgQ0KyBzEpX1EBmpTK0OC/+zdaofRAzktBxddOmMQM1kFmpVIYckj5g+9nWsVR6BsAoSQ0vTwGzxeOsfY8HgbcnhA3BM+l5ltkJKKGzcGk8Y/vI1CKmkjlsfzO1iErW/C9wnaRzgONtP5BYz0D4Vvz7haQqpo4RsaphK+AXtt+WVEpJfyUDaml5pTJEib5Y2P5Pai2VSqVSGTrEUr79gG8Cjc7NqxK8hE/NuQt1qcSKgGZvzydsl+Tt2bAe2BtYjxA4vgX4ue23On6wMiAk3Wt75dQ6pgZJxwA32r4utZZKvkiaA/g+8CnCBsmkQFpJJc6S3ke4Lz4Zm+hlj6QDCFmYE4DNgIWBC2yvl1RYpRhqILNSGULEkr3DCZ4kAoYRvElOHgS771kjaSHgZGBdQibmrcD+tp9OKqxSqVQSIOnTwCHACnFoAsEf65p0qgYvpXt7VmYckua1/XxqHVODpBeAuQmVMG/TkzE9b1JhlayI3ckPAXYELqZ3IPOIVLr6Q9IVBG/jCZI+SNgQHA8sTtgMPDmpwH6IDee2tn1Z09gwYKZ2tjOVSjtqILNSGUJIOhD4DLCH7cfj2BLAL4A/2v5JSn2DGUl/Ai6gpyRuZ2An25ukU1WpVCqVoYCke5oDl63HOSPpEtvbSbqf9n5w2TaHqqQhBkomw3b1y6wAIOlTBD/GK4Ejbb+eWFLXSHrA9vLx/XeA5WzvImkkcGsJ90RJf7G9fmodlXKpgcxKZQgRTaE3sf3flvH3A9eVXkqUM5LG2V6pv7FKpVIZKkhaHNiXyTsL18Zz0xhJ7wKvNQ6B2QjZall7ewJIWtD2M5IWbXfe9t9ntKZKnkha2vb/SWobyLF934zWVMkTSX8Bvl6YNybQe/0g6XrgTNsXtp7LGUnfA14lZMI25iZsv9znhyqVJmqzn0plaDFzaxATgk9m7fw53fmvpJ2BC+PxDsBzCfVUKpVKaq4AzgSuoqmkrzLtsd02Q60EbD8T3+5l+9vN5yQdB3x78k9VhiiHALsDp7Y5Z2CDGSunkiuFZwP+Q9I3gKcJ/tLbwqSmbiNSChsAe8a/zU25DCySQEulQGpGZqUyhOhUSlZSmVmJSFoEOAVYmzBRjyZ4ZNZMkkqlMiSRdKftNVPrqJRBu+cUSfeVUEZZqVQq04roi/k/wILAKQ1vaUkbAavbPi6lvkplRlADmZXKEKKltKzXKWBW2zUrczoQvZr2qx6klUql0oOkHYGlgeuASZ2nbd/T54cqQ46YebQXsATwaNOpuYDbbO+cRFglayQtCywHzNoYs31BOkWVyvQjNnSd3Xa7dV6W1N9oZWqogcxKpVKZAUi6yfaGqXVUKpVKLkg6BtiFEJxqlJbb9kbpVFVyQ9LcwPuAYwilww1eKb27dmX6EP33NgWWBa4FNiM0Qfl8UmGVyjRE0rnAPsBEYCwwP3Cs7ROTCuuC+hutTC01kFmpVCozAElHA3Mzual1zTyqVCpDEkkPAyvafju1lko5SFqA3hk8TyaUU8mQ2OF+JeAe26MkLQj/v717C7m0LMM4/r/GXaIziGZbbOOGMg/McUM7kkKrg8INWCNWtDuIOiikIgosbUdFA0VRFlSmlghWRApuTkxBqBl1wDZQYRRUGGWYWuno1cFak5/2adb4redd8/1/J9/7PuvkOvjWhvu9n+fmQgeJaU+S5Ja2x813N5wEfADYtgzHbfge1e5y2I8kLcZL5n8vWLFWwM4jSevVDuAg4I7RQTR9SV4HbAWewex/5tnAz4FjRubSJP297QNJdibZCPyR2dEE0p5k3yR7A6cBX257X5JlGZzne1S7xUKmJC1A21eMziBJE/NU4BdJfsLDz8i0I0Or+TjwIuC6eRfSK4CzB2fSNN2S5CDg68y23N4FuANGe5qvAb8FbgOunw8WvXtspMfN96h2i1vLJWkNJXlj20uSnLva68twjo0krYUkJ6+23vb6RWfR9CXZ1vaEJDuA49o+mOTHbU8anU3TMR968rS2f5jfHwls8igf7Unmg0RPb3vFirUNwN7LdlyL71H9P+zIlKS1dcD878ahKSRpYixY6n/01yQHAj8CLk1yB7MhF9K/tW2SHwLHz+9/NTiS9ISbb8t+L3DFirUHgaUpYibZAhzR9hNJDktyfNvto3NpOdiRKUkLkOTQtn8anUOSpiLJ35idFQywL7APcE/bTeNSaaqSHAD8AwhwDrMBepe2/fPQYJqcJF8GvmaHl/Zk88nfd/Ofg0TvGhbqcUryRWbf+S9ve3SSg4Gr2544OJqWhIVMSVqAJL8Ebmf2Y+O7be8cHEmSJiXJ6cBJbT80Oouk5ZNk77Y75xORjwZ+zazAE2bNmpuHBpSeQEl+t8py2z5r4WH+R0lubrt51+T1+dqOtseOzqbl4NZySVqAtkclOQnYAnw4yc+Ay9peMjiaJE1C2+8n+eDoHJqWR3TuwrwoxUPFKTt4tcuPgc3A6aODSGut7WGjM+yG++dnehYgySHAskxc1wTYkSlJC5bkycBW4Jy2e43OI0kjJDlzxe0G4ATg5LYvHhRJ0hJb2d0lrQdJng+8AHjSrrW23x6X6PFJ8mbgDGbf+18HXg+c3/ayocG0NOzIlKQFSLKJ2Rf2FuAI4HuAk1YlrWevW3G9E/gNcNqYKFoGSV4GHNX2G/OHghvb3j46lybj0CTnPtqLbbcuMoy0luZnZL4KeD5wNfBq4EZgsoXMJFcB72r7rSTbgVOYddef1fa2sem0TCxkStJi7AC+D1zQ9qbRYSRptLZvHZ1ByyPJR5h17zwP+AazAVGXAC8dmUuTshdwILPCiLSnewPwQuDmtm9K8nTgwsGZ/ptvAtckuQj4TNufDs6jJWUhU5IW4/B6lockkeS8x3i5bT+2sDBaJmcAxwE3A7T9fZKNYyNpYv7Q9oLRIaQF+XvbB5LsnH8W/hE4fHSox9L28iRXAucB25JczIqzMe2a1uNlIVOSFuOoJO8DnsOKz962rxyWSJLGuGeVtQOAtwOHABYytZr72jbJruEQB4wOpMmxE1PryS1JDmJ2xuQ24C7mD3om7n5mvwP2AzbikB/9Hxz2I0kLkGQH8BVgO/DArvW224eFkqTB5l0k72FWxLwc+FzbO8am0hTNHwYeBZwKfAp4G/Cdtl8YGkyTkeTgtn8ZnUNatCRHApvaTrqQmeQ1zAae/oDZcVv3Do6kJWUhU5IWIMn2tsePziFJU5DkYOBc4BzgIuDzbe8cm0pTl+RUZsMtAlzd9trBkSRpmCRbgCPafiLJYcBTptwkkeQG4J2ejandZSFTkhYgyUeBO5hNK//nrnU7ByStN0k+C5wJfBX4Utu7B0fSEkqyF7Cl7aWjs0jSoiX5IrAP8PK2R88fEF7d9sTB0aQ1ZyFTkhYgye2rLLftpA/llqQnWpIHmT3Q2Qms/CEaZp+Lm4YE0yQl2QS8G3gms+2I187v3w/c2va0gfEkaYgkN7fdnOSWtsfN13a0PXZ0NmmtOexHkhag7XNHZ5CkKWi7YXQGLZWLgTuBm4B3MCtg7guc1vbWkcEkaaD7k2xg/kAwySE4OEfrhD8kJWkNJfnAiuuzHvHaJxefSJKkpXJ427e0vRA4GzgBeK1FTEnr3JeAK4BDk5wP3Ah8emwkaTHcWi5Ja2jXto9HXq92L0mSHs7vTkl6SJKrgHe1/U2SY4BTmB3Ncl3b28amkxbDreWStLbyKNer3UuSpIc7Nsld8+sA+8/vPVNV0nr0TeCaJBcBn3ECuNYjC5mStLb6KNer3UuSpBXa7jU6gyRNRdvLk1wJnAdsS3IxK87GbLt1WDhpQSxkStLaOnZF58j+j+gqedK4WJIkSZKW0P3APcB+wEYc8qN1xkKmJK0hO0kkSZIkPRGSvAbYCvwA2Nz23sGRpIVz2I8kSZIkSdLEJbkBeKdnY2o9s5ApSZIkSZIkafI2jA4gSZIkSZIkSf+NhUxJkiRJkiRJk2chU5IkSZIkSdLkWciUJEmSJEmSNHkWMiVJkiRJkiRNnoVMSZIkSZIkSZP3L1zJuCN6mh7cAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1728x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(24,8))\n",
    "sns.heatmap(df[col_numerical].corr(), annot=True, fmt=\".2f\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1728x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(24,8))\n",
    "# Mask for the upper triangle\n",
    "mask = np.zeros_like(df[col_numerical].corr(), dtype=np.bool)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "\n",
    "# Generate a custom diverging colormap\n",
    "cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "\n",
    "# Heatmap with mask and correct aspect ratio\n",
    "sns.heatmap(df[col_numerical].corr(), mask=mask, cmap=cmap, vmax=.3, center=0,\n",
    "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5});"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1728x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(24,8))\n",
    "\n",
    "# Mask for the upper triangle\n",
    "mask = np.zeros_like(df[col_numerical].corr(), dtype=np.bool)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "\n",
    "# Generate a custom diverging colormap\n",
    "#cmap = sns.diverging_palette(10, 220, as_cmap=True)\n",
    "cmap = sns.light_palette((210, 90, 60), input=\"husl\")\n",
    "\n",
    "# Heatmap with mask\n",
    "sns.heatmap(df[col_numerical].corr(), mask=mask, cmap=cmap, annot=True, fmt=\".2f\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are some points to note from the correlation matrix. The correlation coefficient is on the higher side. I used 0.7 as my land in the sand. i.e., Higher than 0.7 is closely correlated. This part is subjective. I am using 0.7 as a guide to inform me to investigate further.\n",
    "\n",
    "E.g., \n",
    "* Monthly Income and Job Level, \n",
    "* Total Working Years and Job Level, \n",
    "* Total Working Years and Monthly Income, \n",
    "* Performance Rating and Percent Salary Hike, \n",
    "* Years in Current Role and Years at Company, \n",
    "* Years with Current Manager and Years at Company, \n",
    "* Years with Current Manager and Years in Current Role"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Department',\n",
       " 'JobRole',\n",
       " 'Attrition',\n",
       " 'BusinessTravel',\n",
       " 'OverTime',\n",
       " 'EducationField',\n",
       " 'MaritalStatus',\n",
       " 'Gender',\n",
       " 'Over18']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col_categorical # Note this is same as the search method we performed earlier. We can bring up categorical_col to compare."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Attrition',\n",
       " 'BusinessTravel',\n",
       " 'Department',\n",
       " 'EducationField',\n",
       " 'Gender',\n",
       " 'JobRole',\n",
       " 'MaritalStatus',\n",
       " 'Over18',\n",
       " 'OverTime']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorical_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Yes', 'No'], dtype=object)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Attrition'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "attrition_to_num = {'Yes': 0,\n",
    "                    'No': 1}\n",
    "df['Attrition_num'] = df['Attrition'].map(attrition_to_num)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some useful references\n",
    "\n",
    "1. [get_dummies or labelEncoder](https://stackoverflow.com/questions/38413579/what-is-the-difference-between-sklearn-labelencoder-and-pd-get-dummies)\n",
    "2. [Encoding Categorical Features](https://towardsdatascience.com/encoding-categorical-features-21a2651a065c)\n",
    "\n",
    "Point to note:\n",
    "* Perform one hot encoding before train-test split. This is fine as you are just transforming the data. There is no leakage here.\n",
    "* Perform data processing after train-test split because standardisation etc learn from the data by calculating mean, standard deviation etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Department',\n",
       " 'JobRole',\n",
       " 'Attrition',\n",
       " 'BusinessTravel',\n",
       " 'OverTime',\n",
       " 'EducationField',\n",
       " 'MaritalStatus',\n",
       " 'Gender',\n",
       " 'Over18']"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col_categorical"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Department',\n",
       " 'JobRole',\n",
       " 'BusinessTravel',\n",
       " 'OverTime',\n",
       " 'EducationField',\n",
       " 'MaritalStatus',\n",
       " 'Gender',\n",
       " 'Over18']"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col_categorical.remove('Attrition')\n",
    "col_categorical"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Department_Human Resources</th>\n",
       "      <th>Department_Research &amp; Development</th>\n",
       "      <th>Department_Sales</th>\n",
       "      <th>JobRole_Healthcare Representative</th>\n",
       "      <th>JobRole_Human Resources</th>\n",
       "      <th>JobRole_Laboratory Technician</th>\n",
       "      <th>JobRole_Manager</th>\n",
       "      <th>JobRole_Manufacturing Director</th>\n",
       "      <th>JobRole_Research Director</th>\n",
       "      <th>JobRole_Research Scientist</th>\n",
       "      <th>JobRole_Sales Executive</th>\n",
       "      <th>JobRole_Sales Representative</th>\n",
       "      <th>BusinessTravel_Non-Travel</th>\n",
       "      <th>BusinessTravel_Travel_Frequently</th>\n",
       "      <th>BusinessTravel_Travel_Rarely</th>\n",
       "      <th>OverTime_No</th>\n",
       "      <th>OverTime_Yes</th>\n",
       "      <th>EducationField_Human Resources</th>\n",
       "      <th>EducationField_Life Sciences</th>\n",
       "      <th>EducationField_Marketing</th>\n",
       "      <th>EducationField_Medical</th>\n",
       "      <th>EducationField_Other</th>\n",
       "      <th>EducationField_Technical Degree</th>\n",
       "      <th>MaritalStatus_Divorced</th>\n",
       "      <th>MaritalStatus_Married</th>\n",
       "      <th>MaritalStatus_Single</th>\n",
       "      <th>Gender_Female</th>\n",
       "      <th>Gender_Male</th>\n",
       "      <th>Over18_Y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Department_Human Resources  Department_Research & Development  Department_Sales  JobRole_Healthcare Representative  JobRole_Human Resources  JobRole_Laboratory Technician  JobRole_Manager  JobRole_Manufacturing Director  JobRole_Research Director  JobRole_Research Scientist  JobRole_Sales Executive  JobRole_Sales Representative  BusinessTravel_Non-Travel  BusinessTravel_Travel_Frequently  BusinessTravel_Travel_Rarely  OverTime_No  OverTime_Yes  EducationField_Human Resources  EducationField_Life Sciences  EducationField_Marketing  EducationField_Medical  EducationField_Other  EducationField_Technical Degree  MaritalStatus_Divorced  MaritalStatus_Married  MaritalStatus_Single  Gender_Female  Gender_Male  Over18_Y\n",
       "0                           0                                  0                 1                                  0                        0                              0                0                               0                          0                           0                        1                             0                          0                                 0                             1            0             1                               0                             1                         0                       0                     0                                0                       0                      0                     1              1            0         1\n",
       "1                           0                                  1                 0                                  0                        0                              0                0                               0                          0                           1                        0                             0                          0                                 1                             0            1             0                               0                             1                         0                       0                     0                                0                       0                      1                     0              0            1         1\n",
       "2                           0                                  1                 0                                  0                        0                              1                0                               0                          0                           0                        0                             0                          0                                 0                             1            0             1                               0                             0                         0                       0                     1                                0                       0                      0                     1              0            1         1\n",
       "3                           0                                  1                 0                                  0                        0                              0                0                               0                          0                           1                        0                             0                          0                                 1                             0            0             1                               0                             1                         0                       0                     0                                0                       0                      1                     0              1            0         1\n",
       "4                           0                                  1                 0                                  0                        0                              1                0                               0                          0                           0                        0                             0                          0                                 0                             1            1             0                               0                             0                         0                       1                     0                                0                       0                      1                     0              0            1         1"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cat = pd.get_dummies(df[col_categorical])\n",
    "df_cat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</div>"
      ],
      "text/plain": [
       "   Age  DailyRate  DistanceFromHome  Education  EnvironmentSatisfaction  HourlyRate  JobInvolvement  JobLevel  JobSatisfaction  MonthlyIncome  MonthlyRate  NumCompaniesWorked  PercentSalaryHike  PerformanceRating  RelationshipSatisfaction  StockOptionLevel  TotalWorkingYears  TrainingTimesLastYear  WorkLifeBalance  YearsAtCompany  YearsInCurrentRole  YearsSinceLastPromotion  YearsWithCurrManager  Department_Human Resources  Department_Research & Development  Department_Sales  JobRole_Healthcare Representative  JobRole_Human Resources  JobRole_Laboratory Technician  JobRole_Manager  JobRole_Manufacturing Director  JobRole_Research Director  JobRole_Research Scientist  JobRole_Sales Executive  JobRole_Sales Representative  BusinessTravel_Non-Travel  BusinessTravel_Travel_Frequently  BusinessTravel_Travel_Rarely  OverTime_No  OverTime_Yes  EducationField_Human Resources  EducationField_Life Sciences  EducationField_Marketing  EducationField_Medical  EducationField_Other  \\\n",
       "0   41       1102                 1          2                        2          94               3         2                4           5993        19479                   8                 11                  3                         1                 0                  8                      0                1               6                   4                        0                     5                           0                                  0                 1                                  0                        0                              0                0                               0                          0                           0                        1                             0                          0                                 0                             1            0             1                               0                             1                         0                       0                     0   \n",
       "1   49        279                 8          1                        3          61               2         2                2           5130        24907                   1                 23                  4                         4                 1                 10                      3                3              10                   7                        1                     7                           0                                  1                 0                                  0                        0                              0                0                               0                          0                           1                        0                             0                          0                                 1                             0            1             0                               0                             1                         0                       0                     0   \n",
       "2   37       1373                 2          2                        4          92               2         1                3           2090         2396                   6                 15                  3                         2                 0                  7                      3                3               0                   0                        0                     0                           0                                  1                 0                                  0                        0                              1                0                               0                          0                           0                        0                             0                          0                                 0                             1            0             1                               0                             0                         0                       0                     1   \n",
       "3   33       1392                 3          4                        4          56               3         1                3           2909        23159                   1                 11                  3                         3                 0                  8                      3                3               8                   7                        3                     0                           0                                  1                 0                                  0                        0                              0                0                               0                          0                           1                        0                             0                          0                                 1                             0            0             1                               0                             1                         0                       0                     0   \n",
       "4   27        591                 2          1                        1          40               3         1                2           3468        16632                   9                 12                  3                         4                 1                  6                      3                3               2                   2                        2                     2                           0                                  1                 0                                  0                        0                              1                0                               0                          0                           0                        0                             0                          0                                 0                             1            1             0                               0                             0                         0                       1                     0   \n",
       "\n",
       "   EducationField_Technical Degree  MaritalStatus_Divorced  MaritalStatus_Married  MaritalStatus_Single  Gender_Female  Gender_Male  Over18_Y  \n",
       "0                                0                       0                      0                     1              1            0         1  \n",
       "1                                0                       0                      1                     0              0            1         1  \n",
       "2                                0                       0                      0                     1              0            1         1  \n",
       "3                                0                       0                      1                     0              1            0         1  \n",
       "4                                0                       0                      1                     0              0            1         1  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = pd.concat([df[col_numerical], df_cat], axis=1)\n",
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0\n",
       "1    1\n",
       "2    0\n",
       "3    1\n",
       "4    1\n",
       "Name: Attrition_num, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = df['Attrition_num']\n",
    "y.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    1233\n",
       "0     237\n",
       "Name: Attrition_num, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1470 entries, 0 to 1469\n",
      "Data columns (total 52 columns):\n",
      "Age                                  1470 non-null int64\n",
      "DailyRate                            1470 non-null int64\n",
      "DistanceFromHome                     1470 non-null int64\n",
      "Education                            1470 non-null int64\n",
      "EnvironmentSatisfaction              1470 non-null int64\n",
      "HourlyRate                           1470 non-null int64\n",
      "JobInvolvement                       1470 non-null int64\n",
      "JobLevel                             1470 non-null int64\n",
      "JobSatisfaction                      1470 non-null int64\n",
      "MonthlyIncome                        1470 non-null int64\n",
      "MonthlyRate                          1470 non-null int64\n",
      "NumCompaniesWorked                   1470 non-null int64\n",
      "PercentSalaryHike                    1470 non-null int64\n",
      "PerformanceRating                    1470 non-null int64\n",
      "RelationshipSatisfaction             1470 non-null int64\n",
      "StockOptionLevel                     1470 non-null int64\n",
      "TotalWorkingYears                    1470 non-null int64\n",
      "TrainingTimesLastYear                1470 non-null int64\n",
      "WorkLifeBalance                      1470 non-null int64\n",
      "YearsAtCompany                       1470 non-null int64\n",
      "YearsInCurrentRole                   1470 non-null int64\n",
      "YearsSinceLastPromotion              1470 non-null int64\n",
      "YearsWithCurrManager                 1470 non-null int64\n",
      "Department_Human Resources           1470 non-null uint8\n",
      "Department_Research & Development    1470 non-null uint8\n",
      "Department_Sales                     1470 non-null uint8\n",
      "JobRole_Healthcare Representative    1470 non-null uint8\n",
      "JobRole_Human Resources              1470 non-null uint8\n",
      "JobRole_Laboratory Technician        1470 non-null uint8\n",
      "JobRole_Manager                      1470 non-null uint8\n",
      "JobRole_Manufacturing Director       1470 non-null uint8\n",
      "JobRole_Research Director            1470 non-null uint8\n",
      "JobRole_Research Scientist           1470 non-null uint8\n",
      "JobRole_Sales Executive              1470 non-null uint8\n",
      "JobRole_Sales Representative         1470 non-null uint8\n",
      "BusinessTravel_Non-Travel            1470 non-null uint8\n",
      "BusinessTravel_Travel_Frequently     1470 non-null uint8\n",
      "BusinessTravel_Travel_Rarely         1470 non-null uint8\n",
      "OverTime_No                          1470 non-null uint8\n",
      "OverTime_Yes                         1470 non-null uint8\n",
      "EducationField_Human Resources       1470 non-null uint8\n",
      "EducationField_Life Sciences         1470 non-null uint8\n",
      "EducationField_Marketing             1470 non-null uint8\n",
      "EducationField_Medical               1470 non-null uint8\n",
      "EducationField_Other                 1470 non-null uint8\n",
      "EducationField_Technical Degree      1470 non-null uint8\n",
      "MaritalStatus_Divorced               1470 non-null uint8\n",
      "MaritalStatus_Married                1470 non-null uint8\n",
      "MaritalStatus_Single                 1470 non-null uint8\n",
      "Gender_Female                        1470 non-null uint8\n",
      "Gender_Male                          1470 non-null uint8\n",
      "Over18_Y                             1470 non-null uint8\n",
      "dtypes: int64(23), uint8(29)\n",
      "memory usage: 305.9 KB\n"
     ]
    }
   ],
   "source": [
    "X.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Decision Tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = DecisionTreeClassifier(random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=None,\n",
       "                       max_features=None, max_leaf_nodes=None,\n",
       "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                       min_samples_leaf=1, min_samples_split=2,\n",
       "                       min_weight_fraction_leaf=0.0, presort=False,\n",
       "                       random_state=42, splitter='best')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_train, clf.predict(X_train))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00       178\n",
      "           1       1.00      1.00      1.00       998\n",
      "\n",
      "    accuracy                           1.00      1176\n",
      "   macro avg       1.00      1.00      1.00      1176\n",
      "weighted avg       1.00      1.00      1.00      1176\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_train, clf.predict(X_train)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[178,   0],\n",
       "       [  0, 998]])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "confusion_matrix(y_train, clf.predict(X_train))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7721088435374149"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_test, clf.predict(X_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.41      0.32      0.36        59\n",
      "           1       0.84      0.89      0.86       235\n",
      "\n",
      "    accuracy                           0.77       294\n",
      "   macro avg       0.63      0.60      0.61       294\n",
      "weighted avg       0.75      0.77      0.76       294\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, clf.predict(X_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 19,  40],\n",
       "       [ 27, 208]])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "confusion_matrix(y_test, clf.predict(X_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import preprocessing\n",
    "from sklearn.model_selection import cross_val_score, cross_val_predict\n",
    "from sklearn.metrics import accuracy_score, classification_report\n",
    "from sklearn.metrics import confusion_matrix, roc_auc_score\n",
    "def print_score(clf, X_train, X_test, y_train, y_test, train=True):\n",
    "    '''\n",
    "    v0.1 Follow the scikit learn library format in terms of input\n",
    "    print the accuracy score, classification report and confusion matrix of classifier\n",
    "    '''\n",
    "    lb = preprocessing.LabelBinarizer()\n",
    "    lb.fit(y_train)\n",
    "    if train:\n",
    "        '''\n",
    "        training performance\n",
    "        '''\n",
    "        res = clf.predict(X_train)\n",
    "        print(\"Train Result:\\n\")\n",
    "        print(\"accuracy score: {0:.4f}\\n\".format(accuracy_score(y_train, \n",
    "                                                                res)))\n",
    "        print(\"Classification Report: \\n {}\\n\".format(classification_report(y_train, \n",
    "                                                                            res)))\n",
    "        print(\"Confusion Matrix: \\n {}\\n\".format(confusion_matrix(y_train, \n",
    "                                                                  res)))\n",
    "        print(\"ROC AUC: {0:.4f}\\n\".format(roc_auc_score(lb.transform(y_train), \n",
    "                                                      lb.transform(res))))\n",
    "\n",
    "        #res = cross_val_score(clf, X_train, y_train, cv=10, scoring='accuracy')\n",
    "        #print(\"Average Accuracy: \\t {0:.4f}\".format(np.mean(res)))\n",
    "        #print(\"Accuracy SD: \\t\\t {0:.4f}\".format(np.std(res)))\n",
    "        \n",
    "    elif train==False:\n",
    "        '''\n",
    "        test performance\n",
    "        '''\n",
    "        res_test = clf.predict(X_test)\n",
    "        print(\"Test Result:\\n\")        \n",
    "        print(\"accuracy score: {0:.4f}\\n\".format(accuracy_score(y_test, \n",
    "                                                                res_test)))\n",
    "        print(\"Classification Report: \\n {}\\n\".format(classification_report(y_test, \n",
    "                                                                            res_test)))\n",
    "        print(\"Confusion Matrix: \\n {}\\n\".format(confusion_matrix(y_test, \n",
    "                                                                  res_test)))   \n",
    "        print(\"ROC AUC: {0:.4f}\\n\".format(roc_auc_score(lb.transform(y_test), \n",
    "                                                      lb.transform(res_test))))\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Result:\n",
      "\n",
      "accuracy score: 1.0000\n",
      "\n",
      "Classification Report: \n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00       178\n",
      "           1       1.00      1.00      1.00       998\n",
      "\n",
      "    accuracy                           1.00      1176\n",
      "   macro avg       1.00      1.00      1.00      1176\n",
      "weighted avg       1.00      1.00      1.00      1176\n",
      "\n",
      "\n",
      "Confusion Matrix: \n",
      " [[178   0]\n",
      " [  0 998]]\n",
      "\n",
      "ROC AUC: 1.0000\n",
      "\n",
      "Test Result:\n",
      "\n",
      "accuracy score: 0.7721\n",
      "\n",
      "Classification Report: \n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.41      0.32      0.36        59\n",
      "           1       0.84      0.89      0.86       235\n",
      "\n",
      "    accuracy                           0.77       294\n",
      "   macro avg       0.63      0.60      0.61       294\n",
      "weighted avg       0.75      0.77      0.76       294\n",
      "\n",
      "\n",
      "Confusion Matrix: \n",
      " [[ 19  40]\n",
      " [ 27 208]]\n",
      "\n",
      "ROC AUC: 0.6036\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print_score(clf, X_train, X_test, y_train, y_test, train=True)\n",
    "print_score(clf, X_train, X_test, y_train, y_test, train=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "****"
   ]
  }
 ],
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    "name": "ipython",
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