ab_testing.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# A/B Testing Online Advertising"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A major company with a large user base is exploring the potential of increasing sales by displaying ads on its website. However, they are uncertain whether these ads truly drive sales growth. To investigate this, they conducted A/B testing over a 30-day period with 20,000 customers. In this experiment, the group exposed to the ads is the treatment group (labeled \"ad\"), while the control group, which did not see the ads, is labeled \"psa\".\n",
    "\n",
    "\n",
    "**Variables**:\n",
    "\n",
    "* **customerID**: Unique identifier for the customer.\n",
    "* **test group**: A categorical variable in an A/B testing setup. 'ad' indicates customers exposed to ads (treatment group), and 'psa' represents those not exposed (control group).\n",
    "* **made_purchase**: A Boolean value representing whether or not the user made a purchase after seeing an advertisement.\n",
    "* **days_with_most_add**: A day of the month when the user saw the most ads.\n",
    "* **peak ad hours**: An hour of the day when the user saw the most ads.\n",
    "* **ad_count**: Total number of ads seen by each user.\n",
    "\n",
    "You can access the dataset here: [Online Advertising Effectiveness](https://www.kaggle.com/datasets/farhadzeynalli/online-advertising-effectiveness-study-ab-testing/data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from statsmodels.stats.proportion import proportions_ztest\n",
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('/Users/gulsumasenacakir/Downloads/online_ad_AB.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "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>customerID</th>\n",
       "      <th>test group</th>\n",
       "      <th>made_purchase</th>\n",
       "      <th>days_with_most_add</th>\n",
       "      <th>peak ad hours</th>\n",
       "      <th>ad_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>ad</td>\n",
       "      <td>False</td>\n",
       "      <td>24</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>psa</td>\n",
       "      <td>False</td>\n",
       "      <td>21</td>\n",
       "      <td>16</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>psa</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>ad</td>\n",
       "      <td>False</td>\n",
       "      <td>20</td>\n",
       "      <td>23</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>ad</td>\n",
       "      <td>False</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>ad</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>22</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>ad</td>\n",
       "      <td>False</td>\n",
       "      <td>7</td>\n",
       "      <td>19</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>psa</td>\n",
       "      <td>False</td>\n",
       "      <td>6</td>\n",
       "      <td>22</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>psa</td>\n",
       "      <td>False</td>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>psa</td>\n",
       "      <td>False</td>\n",
       "      <td>2</td>\n",
       "      <td>19</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   customerID test group  made_purchase  days_with_most_add  peak ad hours  \\\n",
       "0           1         ad          False                  24             20   \n",
       "1           2        psa          False                  21             16   \n",
       "2           3        psa          False                   1             18   \n",
       "3           4         ad          False                  20             23   \n",
       "4           5         ad          False                   3             13   \n",
       "5           6         ad          False                  13             22   \n",
       "6           7         ad          False                   7             19   \n",
       "7           8        psa          False                   6             22   \n",
       "8           9        psa          False                   6             15   \n",
       "9          10        psa          False                   2             19   \n",
       "\n",
       "   ad_count  \n",
       "0         5  \n",
       "1         9  \n",
       "2         8  \n",
       "3         7  \n",
       "4         5  \n",
       "5         7  \n",
       "6         6  \n",
       "7        10  \n",
       "8         7  \n",
       "9         5  "
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1) Null Values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "customerID            0\n",
       "test group            0\n",
       "made_purchase         0\n",
       "days_with_most_add    0\n",
       "peak ad hours         0\n",
       "ad_count              0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2) Duplicate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of duplicate is 0\n"
     ]
    }
   ],
   "source": [
    "number_duplicate = df.duplicated().sum()\n",
    "print('The number of duplicate is', number_duplicate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3) Whitespace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "customerID            0\n",
      "test group            0\n",
      "made_purchase         0\n",
      "days_with_most_add    0\n",
      "peak ad hours         0\n",
      "ad_count              0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "whitespace_check = df.map(lambda x: isinstance(x, str) and x.isspace())\n",
    "whitespace_counts = whitespace_check.sum()\n",
    "print(whitespace_counts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4) Change inappropriate column names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.rename(columns={'test group': 'group', 'peak ad hours': 'peak_ad_hours'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['customerID', 'group', 'made_purchase', 'days_with_most_add',\n",
       "       'peak_ad_hours', 'ad_count'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1) Number of observations and number of purchases based on control and experimental groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "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>number_of_observations</th>\n",
       "      <th>number_of_purchases</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ad</th>\n",
       "      <td>12053</td>\n",
       "      <td>803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>psa</th>\n",
       "      <td>7947</td>\n",
       "      <td>257</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       number_of_observations  number_of_purchases\n",
       "group                                             \n",
       "ad                      12053                  803\n",
       "psa                      7947                  257"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('group').agg({'customerID': 'count', 'made_purchase': 'sum'}).rename(columns={'customerID': 'number_of_observations', 'made_purchase': 'number_of_purchases'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2) 30-Day Customer Count or User Activity Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30])"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "days = np.sort(pd.unique(df['days_with_most_add']))\n",
    "days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_days = df.groupby('days_with_most_add')['customerID'].count()\n",
    "con_days = df[df['group'] == 'psa'].groupby('days_with_most_add')['customerID'].count()\n",
    "exp_days = df[df['group'] == 'ad'].groupby('days_with_most_add')['customerID'].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a function to generate a two-row bar chart: the first row displays the overall data distribution, while the second row compares the control and experiment groups using side-by-side bars."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "def bar_fig(period, data1, data2, data3, subtit1, subtit2, x_label, y_label, figtitle):\n",
    "    fig, axs = plt.subplots(nrows=2, ncols=1, figsize=(15, 10))\n",
    "\n",
    "    axs[0].bar(period, data1.values, color='blue')\n",
    "    axs[0].set_title(subtit1)\n",
    "    axs[0].set_xlabel(x_label)\n",
    "    axs[0].set_ylabel(y_label)\n",
    "\n",
    "    bar_width = 0.35 \n",
    "    axs[1].bar(period - bar_width/2, data2.values, width=bar_width, color='green', label='Control Group')\n",
    "    axs[1].bar(period + bar_width/2, data3.values, width=bar_width, color='red', label='Experiment Group')\n",
    "    axs[1].set_title(subtit2)\n",
    "    axs[1].set_xlabel(x_label)\n",
    "    axs[1].set_ylabel(y_label)\n",
    "    axs[1].legend()\n",
    "\n",
    "    axs[0].set_xticks(period)\n",
    "    axs[1].set_xticks(period)\n",
    "\n",
    "    fig.suptitle(figtitle, fontsize=16)\n",
    "    plt.tight_layout(rect=[0, 0.03, 1, 0.95])\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bar_fig(period=days, \n",
    "        data1=data_days, \n",
    "        data2=con_days, \n",
    "        data3=exp_days, \n",
    "        subtit1='Overall Customer Count by Days', \n",
    "        subtit2='Comparison of Control and Experiment Groups by Days', \n",
    "        x_label='Days', \n",
    "        y_label='Customer Count', \n",
    "        figtitle='Customer Activity Analysis')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the comparative analysis, it is evident that the experiment/treatment group has a higher customer count than the control group, suggesting that the ads may be effectively enhancing customer engagement. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3) Ad View Trends: Daily Totals and Group Comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "days_ad_count = df.groupby('days_with_most_add')['ad_count'].sum()\n",
    "exp_days_ad_count = df[df['group'] == 'ad'].groupby('days_with_most_add')['ad_count'].sum()\n",
    "con_days_ad_count = df[df['group'] == 'psa'].groupby('days_with_most_add')['ad_count'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bar_fig(period=days, \n",
    "        data1=days_ad_count, \n",
    "        data2=con_days_ad_count, \n",
    "        data3=exp_days_ad_count, \n",
    "        subtit1='Total Ads Seen by All Users Per Day', \n",
    "        subtit2='Total Ads Seen Comparison: Control vs Experiment/Treatment Groups', \n",
    "        x_label='Days', \n",
    "        y_label='Total Ads Seen', \n",
    "        figtitle='Ad View Trends: Daily Totals and Group Comparison')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similar to previous analysis, the treatment group sees more ads than the control group every day."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4) User Activity by Hours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23])"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time = np.sort(pd.unique(df['peak_ad_hours']))\n",
    "time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_time = df.groupby('peak_ad_hours')['customerID'].count()\n",
    "time_exp = df[df['group'] == 'ad'].groupby('peak_ad_hours')['customerID'].count() # for the treatment/experimental group\n",
    "time_con = df[df['group'] == 'psa'].groupby('peak_ad_hours')['customerID'].count() # for the control group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bar_fig(period=time, \n",
    "        data1=data_time, \n",
    "        data2=time_con, \n",
    "        data3=time_exp, \n",
    "        subtit1='Total Customer Activity by Hour', \n",
    "        subtit2='Hourly Customer Activity: Control vs. Experiment', \n",
    "        x_label='Hours', \n",
    "        y_label='Customer Count', \n",
    "        figtitle='Hourly Analysis of Customer Activity')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data clearly shows that user activity intensifies from 15:00 to 23:00."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5) Analysis of Ads Seen by Users Throughout the Day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_time_ad = df.groupby('peak_ad_hours')['ad_count'].sum()\n",
    "time_exp_ad = df[df['group'] == 'ad'].groupby('peak_ad_hours')['ad_count'].sum() \n",
    "time_con_ad = df[df['group'] == 'psa'].groupby('peak_ad_hours')['ad_count'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABdIAAAO7CAYAAABQ3XYPAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8fJSN1AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdeZyN9f//8ecxuzFzrDNjMnZhjCX7liFCtqSS1ESylCRFIhVaCJFKpBQSaaVSRMKH7MtUZElZY6xjxjLNjJn37w+/c30dZ+Y4w2iWHvfb7dxuzXW9r+t6v65znUvzPO95XzZjjBEAAAAAAAAAAMhQgZzuAAAAAAAAAAAAuRlBOgAAAAAAAAAAbhCkAwAAAAAAAADgBkE6AAAAAAAAAABuEKQDAAAAAAAAAOAGQToAAAAAAAAAAG4QpAMAAAAAAAAA4AZBOgAAAAAAAAAAbhCkAwAAAAAAAADgBkE6AAD/ATabTTab7T937KtJS0vTmDFjVLlyZfn6+spms6l58+Y52qdRo0bJZrNp1KhROdqP/GjlypW54j1G9mrevLlsNptWrlyZ013JEVzX/yc3/3sDAADyPoJ0AACySfXq1WWz2RQQEKDExMSc7g488OKLL2rEiBHav3+/oqKi1KRJE1WvXj3L+/nyyy+tAGfEiBE3oKfZ78KFC5owYYIaNWqkwoULy9fXVyVLltQtt9yiPn36aO7cuUpKSsrpbuZbjuvlauFv2bJlZbPZNGvWrH+lXznB8eVRVl//1eA8r1q5cqVGjRp1ze/bwoULNWrUKMXGxmZrv26E/fv3u1yv3t7eKlq0qCpWrKguXbpo0qRJOnHiRE53FQAAZIF3TncAAID8IDY2Vtu3b5ck/fPPP/riiy/Uq1evHO5V7lC5cuWc7kKGjDF69913ZbPZ9PPPP6tu3brXvK85c+ZY//3xxx/rlVdeydWjIv/++2/ddttt2rNnjyQpLCxMFStWVHJysnbu3KnY2FjNmDFDv/32m6KionK4t8jvSpcurSZNmrgs/+2335SYmKiIiAiVLl3aZb3dbv83uodssnLlSo0ePVqSrmn0/MKFCzV79myVLVtWtWrVyt7O3UB169aVn5+fJOncuXM6evSoFixYoAULFmj48OEaNmyYXnzxRXl5eeVwTwEAwNUQpAMAkA0cQWrhwoV15swZzZkzhyD9/9u1a1dOdyFDJ06c0OnTpxUSEnJdIfqpU6f0/fffy2azKSgoSAcPHtT//vc/RUdHZ2Nvs1evXr20Z88eVapUSbNnz1ajRo2sdSkpKVq+fLlmzJghb2/+VxE3Xq9evTK8XzZv3lyrVq1Sr169mOoIedbnn3+usmXLOi3bu3evpk2bpjfffFMvvfSS/vjjD82bNy9nOggAADzG1C4AAFyntLQ0ffLJJ5KkKVOmyMvLS6tWrdLBgwdzuGdwxzFtSUBAwHXt59NPP1VqaqoaN26sBx98UJLzCPXc5ujRo1q6dKkkaebMmU4huiT5+vrqjjvu0JdffqkqVarkRBcBIF+rWLGiJk6cqEWLFsnLy0uffPKJZs+endPdAgAAV0GQDgDAdfrxxx919OhRhYWFqVu3brrttttkjNHcuXMz3ebyh+Pt2rVL9957r4oXL66AgADVqVNHn332WYbbxcXF6e2331abNm1UtmxZ+fv7q0iRIoqOjs5SeHvmzBkFBATIx8dHx44dy7Rdhw4dZLPZ9M4771jLzp8/r5deekk1atRQYGCg/P39FRERoebNm+u1115Tamqq0z4ye/jbqVOnNGTIEFWpUkX+/v4KDAxU2bJl1bZtW02dOtXjWhwOHjyoxx57TOXKlZOfn5+KFy+uO+64Q4sXL3Zpa7PZrBGCBw4cuK55lx3nvXv37nrggQckXRqB+M8//2S6zcWLFzV+/Hir9ptuukl9+vRx+14YY/TRRx+pWbNm1pzmYWFhqlOnjoYOHarDhw971N99+/ZZ/32t0yNs3LhR3bp100033SRfX1+Fhobq3nvv1bZt2zLd5uLFi3r33XfVtGlTFS5cWP7+/qpSpYqef/75DJ8pMGvWLNlsNvXs2VPJyckaNWqUKlasaF1vTz/9tM6fP39N/Zek1NRUjR49WjfffLP1Hjz++OM6ffq0U7slS5bIZrOpRo0ame4rJSVFxYoVk81m044dO665T1mR1c+hdGle/HHjxqlu3boKDg5WwYIFVatWLU2YMEHJycku7S9/8O2JEyc0YMAAlS1bVj4+PurZs6fVbs2aNbrrrrsUFhYmHx8fFS1aVFWrVlXv3r21fv36G3kaXGTlfnr5fTg2Nlb33HOPQkNDVaBAAac56U+dOqWhQ4eqcuXKCggIUJEiRdS8eXPNnTtXxhiX/V7tgcGXX9sZ+eyzz9SwYUMFBgaqePHi6tSpk7Zt2+bRQ0XT09P15ptvKioqSv7+/goNDdUjjzzidi7uHTt2KCYmRqVKlbI+z3fffXem793VHu7as2dPl3n9bTabNa3L6NGjne65mZ0HB8d8446g+eGHH3baPrPzvHjxYjVr1kxBQUGy2+264447svUelR3atm2rAQMGSJLGjh3rsn79+vUaOnSo6tatq5CQEPn5+SkiIkIxMTEZ3mu6desmm82miRMnZnrML774QjabTfXq1cu+QgAA+K8wAADgunTv3t1IMk8++aQxxphZs2YZSaZq1aqZbhMdHW0kmddff90UKlTIBAUFmTp16pgSJUoYSUaSmTNnjst2L7/8spFkAgICTIUKFUzdunVN6dKlrW0effTRDI/nWH+5+++/30gyEydOzHCbuLg44+3tbXx9fc2pU6eMMcakpqaahg0bGkmmQIECpnLlyqZu3bomPDzcFChQwEgy8fHxVz32mTNnTIUKFYwk4+vrayIjI03t2rVNSEiIsdlsxm63Z3ruMrJ+/XpTuHBhI8kEBgaaOnXqmFKlSlnHfuGFF5zaN2nSxNStW9dIMn5+fqZJkybWa+vWrR4fd8+ePUaS8fb2NidOnDDGGFOuXDkjyXz66acZbnPx4kXTsWNHq28333yzqVmzpvHy8jKlS5c2AwYMMJLMyJEjnbYbPHiwtU3p0qVNvXr1TLly5Yyvr6+RZBYsWOBRn3/77TdrPz/99JPHtTpMmjTJ2Gw2I8kULVrU3HLLLaZYsWJGkvHx8TFffvmlyzYJCQmmWbNm1nVTpkwZExUVZfW9atWq5tixY07bzJw500gy3bt3N82aNTM2m81Uq1bNVK5c2brWbr/99iz1fcWKFUaSadasmWnfvr2RZCpVqmRq1aplvL29jSRTsWJFp76kpaWZiIgII8ls2bIlw/1+8cUXRpKpW7eux31xvAcrVqxw265MmTJGkpk5c6a17Fo+h4cPHzaRkZHW9VqxYkVTtWpVq+6mTZuaCxcuOG0zcuRII8n079/flC5d2nh5eZkaNWqYGjVqmF69ehljjFm4cKF1zGLFipnatWubKlWqmMDAQKf74rVw3Cev/Cxk1i6r91PHdqNHjzZ+fn6mUKFCpk6dOqZ8+fLW+f7jjz+s99/X19fUrl3blC9f3trvQw89ZNLT0zM8b5n123Ft9+jRw2XdSy+9ZO07PDzc1K1b1wQFBRl/f3/z6quvGkkmOjraaRvHdR0dHW39e1SpUiVTrVo16/2tVq2a+eeff1yO9/XXXxs/Pz8jyRQuXNjUrVvXOm8FChQw7733XqbnLbNrt0ePHi7XbJMmTazzGBER4XTPffXVVzPcj8PRo0dNkyZNTEhIiFXb5dt/8MEHVlvHuZs2bZqx2WymZMmSpnbt2tb1WKhQIbNz506XY1zLPcqdffv2WX3Zt2+f27Y7d+602u7du9dpnePfyWLFipmoqChTs2ZNY7fbrf8PuPI9+OGHH4wkU7169UyP16FDByPJTJkyxeN6AADAJQTpAABch7Nnz5qCBQsaSWbjxo3GGGMSExNNQECAkWQ2b96c4XaOIMLHx8cMGDDAJCUlGWOMSU9PN88++6wVoly8eNFpu9WrV5uffvrJZfkvv/xiqlataiSZlStXuhwvozB72bJlRpKpUaNGhn2cOHGikWTuuecea5kjMKxZs6Y5dOiQU/vjx4+byZMnm/Pnz1/12K+//rqRZFq3bm2F9A4HDhwwb7zxRoZ9ysj58+etLxO6du1qEhMTrXWzZs0yXl5eRpL5/vvvnbZzBB1lypTx+FhXeuGFF4wk065dO2vZiBEjjCTToUOHDLd58803jSRTpEgRs3r1aqf+REVFGR8fH5cQ7vjx46ZAgQLGbrebNWvWOO0vKSnJfPLJJ+aXX37xqM9paWnW+QoLCzNTpkxxeS8zs3jxYmOz2Uzx4sVdAvMZM2YYb29vExQUZI4cOeK0rlu3bkaSadmypfnzzz+t5adPnzZdunRxuc6M+b+w0cfHx0RGRprdu3db69atW2eCg4ONJLN48WKP+m7M/wWO3t7eJjg42OmLhAMHDpiaNWtm2BfHezpw4MAM9+v4YiQrwdT1BOlZ/RympaWZxo0bG0mmW7duJi4uzlp36NAhc+uttxpJZsiQIU77cgTCXl5eplGjRk7HctyzoqKijCQzdepUp/tSenq6WbFihfnmm288PidXymqQntX7qWM7Ly8v07dvX6dzduHCBZOenm594RYdHe103hYvXmyFs1OnTnXa77UG6Rs2bDAFChQwNpvNTJs2zQroz58/b2JiYqx7Q2ZBuo+PjwkPDzcbNmyw1u3evdv6UnHatGlO2/3999/W5+jJJ580ycnJxphL14sjtPfx8XG5t1xLkO7JebmazPZ7OcfnqmDBgk7tEhMTTcuWLY0kc99997lsdy33KHeyEqQbY6wvIz/55BOn5bNnz3bqjzGXvkhz3G/Lly9v0tLSrHWX398z+lL42LFjLl+QAwAAzxGkAwBwHRyjzytWrOi0/N5773U7GtMRRNSsWdPpl2BjjElJSTFhYWGZ/iKcmR9//NFIMn369HFZl1GYnZ6ebsqWLWskmW3btrlsU6NGDSPJLFq0yFo2duxYI8m8+eabHvcro2P369fPSDJff/21x/vJzPvvv28kmdDQUCtAu1z//v2NJHPrrbc6Lc+OIN0x+vzjjz+2lv3+++9WWHv8+HGn9unp6VbI8c4777jsb8uWLdb5ujxsWrdunZFk7rrrrmvu6+WWLVtmfQF0+ejXzp07m7ffftsaXX+l2rVru33fHKPmX3rpJWvZL7/8Yp3ny7/kcDh//ryJiIgwNpvN7N+/31ruCBttNpvZtGmTy3ZPP/2023A7I47AUZKZNGmSy3pHX202m1N49eeff1pfIKSkpDhtc/z48WsKpq4nSM/q5/Cbb74xkky9evVMamqqy/ojR46YQoUKmUKFCjmNSncEn35+fubvv//OcN9+fn6mSJEiHvUjq7IapGf1fupuO2P+78tGPz8/c/ToUZf148ePt67ty0elX2uQ7ghze/fu7bJNSkqKqVixotsgXVKGfxHy1ltvGUmmU6dOTssdXxDVqlUrw362a9fOSDIxMTFOy/NCkP7EE0+4rPv111+NJJe/eLrWe5Q7WQ3Sa9WqleV/Wx988EEjyfz8889Oyx1f8Gb0/x+TJk3K8pcCAADg/zBHOgAA1+Hy+bEv55gr+5NPPtHFixcz3b5Xr14qUMD5n2MfHx/VrFlTkvTXX3+5bHP27Fm9//776tGjh1q3bq1bb71VTZs21bBhwyRJv/zyi0d9t9ls6tGjhyS5POQsNjZWv/76q8LCwtS2bVtreUREhCTpu+++04ULFzw6TkYc+1mwYIHb8+MJx4Mz+/TpI39/f5f1Tz75pCRp7dq11zWn9pXWrFmjffv2qWDBgurcubO1vGrVqqpVq5YuXryo+fPnO22zc+dOHTx4UP7+/hnOC1y7dm01bNjQZbnjfG3YsCFbHmLbqlUr/fLLL+rdu7cKFy4sSTpy5IgWLlyoJ554QmXLltXbb7/ttM2BAwe0detWhYSEqFOnThnu17F81apV1rIFCxZIkrp27aqgoCCXbQoWLKhWrVrJGKPVq1e7rK9Vq5bq1q3rstwxv29Gn5Gr8fX1Ve/evV2W16hRQ02bNpUxxrquJKl8+fJq1qyZTp48qe+//95pm7lz5+rixYvq1KmTihYtmuW+XIusfg6/+uorSZfmrvb29nZZX7JkSdWrV0/nzp3Tli1bXNa3atVK4eHhmfblzJkzWrZsWVZKuCGu5X4qSQ8++KDLdtL/3VvuvfdehYWFuax/9NFH5efnpwMHDmj37t3X2339+OOPki7NAX4lHx8f62HGmSlSpIi6dOnisjyzz4qjPscc3Vdy3Dsv/yzkFRl9vqtXry5/f38lJCTo1KlT1vLrvUdlh8DAQEmX/n2/0q5duzRy5Eh16dJFzZs3V9OmTdW0aVPrPnvlv/mOOeTnzZvn8qwEx7/1V5uXHgAAZMz1/6QBAIBH/v77b61YsUKSa5B+xx13qEiRIjp+/LiWLl2qdu3aZbiPChUqZLg8JCREknTu3Dmn5du2bVOHDh105MiRTPt15cMS3Xn44Yf10ksvad68eZowYYIVsjl+2X7wwQfl5eVlte/cubPKli2rpUuXKjw8XG3bttWtt96q5s2bq1q1alk67oQJEzRr1iwtXrzY2k+LFi1Uvnx5j/cjSXv27JEkRUZGZri+UqVK8vX1VUpKiv7880+3D43MCseXKJ06dbJCEIcHHnhAsbGxmjNnjp544gmXvpYpU0YFCxbMcL9Vq1Z1ecjfTTfdpHvvvVeff/65KlasqBYtWqh58+a69dZb1bBhwwzD0aupWLGi3n//fU2fPl2//vqrNm3apKVLl+r777/X+fPnNXDgQNntdj300EOSpN9++02S9M8//6hp06YZ7tPxgNW///7bWubYbsGCBVq7dm2G2x04cMBlO4esfkY8UapUqQwDM+nS+V+zZo31Xjn06tVLq1at0uzZs3XnnXday3MimMrq59DxHkybNk3z5s3LcJ+OejN6D6pWrZppX5566ik9/vjjat26terUqaNWrVqpadOmio6OzvQc3yjXeq1kVt/V7i1BQUGKiIjQ3r17tWfPHlWpUiWrXbbEx8fr5MmTkpTpPepq966s1n+1+hzX0rFjx5SYmKjg4GC3x89NMjsXJUqU0KFDh3Tu3DkVK1ZM0vXfo7KD47258hyPHTtWzz//vNLT0zPd9sp/88uVK6fmzZtrxYoVWrx4sfUF5y+//KJffvnF5QtyAADgOUakAwBwjebOnav09HTVrl1blStXdlrn6+ure++9V9L/Ba4ZuTKAdXCMjjTGWMvS0tLUtWtXHTlyRO3atdOqVat08uRJXbx4UcYY/fHHH5LkMgLNnTJlyui2227T8ePHtXjxYknSxYsXrbDtynAwMDBQq1ev1sMPP6z09HR9+umnGjBggKKiolStWjUtWrTIo+OGh4dr3bp1uvvuu5WQkKDZs2erd+/eqlChgho1aqR169Z5XIMjgHCERVey2WwqUaKEpIxH+12L5ORkffbZZ5Jcv0SRpPvvv18FChTQpk2bnEaqOvrq6E9GQkNDM1z+0UcfaeTIkQoJCdHSpUv13HPP6dZbb1V4eLhef/11t0GLOwUKFFCtWrXUp08fff7559q5c6eqV68uSXr55ZetdgkJCZKkxMRE/fzzzxm+HKOZk5KSXLbbu3dvptsdPnzYZTuHrHxGPJXZtSL93/m/8lq55557FBwcrEWLFlmjWX/99VfFxsZeUzDl6H9aWprbdo6/2Lj8C62sfg4d78H27dszfQ9OnDghKWvvgST1799fH330kWrWrKktW7Zo3Lhx6tixo0JCQtS3b1/r2P+Ga71WMtvuavcWKfPrJascfy1js9lUqFChDNtc7YuJrNZ/tfouvxdl173z35KVc3G996jscOjQIUnO78X//vc/Pffcc7LZbBo7dqx27Nihc+fOKT09XcYYjRgxQlLG/+b36tVLkvNfm2X2BTkAAPAcQToAANfIEZBv3bpVNpvN5fXee+9Jkr7++mslJiZe9/E2btyovXv3qkyZMvrqq6/UrFkzFStWzPqF2PGLeFZd+Qv34sWLdfz4cdWtWzfD0a2lSpXShx9+qNOnT2v9+vV67bXXVLduXf3+++/q3LmzNmzY4NFxq1atqi+++EJnzpzRihUrNGrUKFWpUkXr169X69attX//fo/24widjh8/nuF6Y4wVEmbXCNlvv/1WZ86ckXRpRPqV732pUqWsYPvyL1IcfXX0JyOZ1eHv769Ro0bp8OHD2rlzp6ZPn66OHTvq1KlTeuaZZzRp0qRsqa106dJ67bXXJF0KluLj45363qRJE5lLz9nJ9HX5e+fY7v3337/qdqNGjcqWGq7Gk/N/5bVSsGBB3XfffUpNTdUnn3wi6fqCKbvdLknWdZQZx3pHe4esfA4d78GyZcuu+h5cy8j6mJgYxcbG6ujRo5o/f74eeeQReXt76/3337/qdCS52dXuLdKl0dqS8/Vis9kkZR7cZzTFlCP4NcZkOgVVdofZV6vPUZt0/fXlZjl9j/r999+tUeX169e3ls+dO1eS9Mwzz2jYsGGKjIxUYGCgdf7d/Zt/9913y263W1/8ufuCHAAAeI4gHQCAa7Bt2zZt375dNptNoaGhmb58fX2VlJSkL7/88rqP6Qgn69SpIz8/P5f1ns6NfqUuXbqocOHC+vbbb3X69GnNmjVL0tV/2fb29laDBg307LPPatOmTerWrZvS0tL04YcfZun4fn5+at68uUaOHKnt27erSZMmOnfunBVWXs3NN98s6VIYkZE//vhDKSkp8vLyyvTP/bPKEY4HBQVl+t475sv++OOPrcDJ0deDBw9mOrf1zp07r3r8KlWqqG/fvvrmm280depUSZdCoOxy+fQ6KSkpkv5v+oedO3dmafS7Y7vt27dnW/+ul2Nqh4w4zr/jvbqc40unWbNm6eLFi1bQdS3BlGP/7s7Lvn37rFDyyr96cfDkc/hvvQdhYWG67777NGPGDG3YsEEFChTQokWLdPTo0Rt63BvlaveWs2fPWmHm5deLIxTP7AubvXv3uiwrUqSIihcvLunSXzpkxDEFSXa5Wn07duyQdGlk+uVTjlxLfdL/BfDX6nq3z0xO36PeffddSZe+XC5Xrpy13PFvfuPGjTPczt2/+QEBAerWrZtSUlL0ySefaPHixTp27FimX5ADAADPEKQDAHANHEFqs2bNFBcXl+lr8ODBTu2vR0BAgCTnUYIOqampmjx58jXt19/fX/fff79SUlI0ZcoULVq0SL6+vrr//vuztB/HQzLdzd9+NV5eXtaD8TzdT5s2bSRdCpIdc3Rf7q233pJ0aSS1uykqPHXq1ClrGpxvvvkm0/d+37598vf314EDB6wH1FWpUkURERFKSkrSRx995LLv2NjYLE1rI2X9vJ8/f/6qD6h0zBNcuHBhaxqaSpUqKSoqSqdPn86w75m56667JF36QuHyB/zlpJSUFH3wwQcuy7dv367Vq1fLZrPp9ttvd1nfsGFDRUZGasuWLXr99devK5hyXLfz58/PdHoXx3kuU6ZMhsF+RjK6HhwPoJw+fXqGn5EbITIy0hpFfz33hJzkeI8+//xzxcXFuayfPn26kpOTVaZMGacvOhxfRG3atMllm/Pnz7s8hNjBcc05vsy83OVf3GQXR31TpkzJcL3j3ulo5+Cuvs2bN2ca8Dr+DbvW6VGud/vM5OQ9asmSJdaXoc8995zTOnf/5i9duvSqX55f/tdmPGQUAIDsQZAOAEAWpaWlWaOlY2Ji3LZ1TGuwcuXKa556xcHxUMmff/7ZKchMSEjQAw88kOEv255y/ML98ssvKyUlRZ06dbJGVF/ujTfe0OTJk12OdfDgQc2YMUOSVLt27aseb8SIEfrggw9cprXYvn27Nfe4J/uRLs1HXrp0aR07dkw9e/Z0Gmn88ccfa/r06ZKkYcOGebS/q5k/f75SU1NVunRpRUdHZ9ouODhYHTt2lPR/X6QUKFBATz/9tKRL5+DyB9sdOHBAPXr0kI+Pj8u+li9frmeeecZl5Oi5c+c0YcIESZ6frz/++EPly5fXyy+/rD///NNp3cWLFzVnzhyrjw899JA1p7AkjRs3TjabTY8//rhmzJhhzd/t8Ndff+nVV1/VV199ZS2rW7euunbtqlOnTun222/Xtm3bnLZJS0vTypUr9cADDyg5OdmjGq6Xt7e3Ro4cqVWrVlnLDh8+bD1YtUuXLpn+9cLDDz8sSXrhhRckXXsw9dhjj6lw4cLatWuXHn74YWsKHUlKT0/XnDlzNHbsWEnS8OHDnUbjZvVzeNddd6lhw4batWuXOnbs6DJiODk5Wd999511H/BUYmKiunXrppUrVzr9lUJaWpreeustxcfHKzAwMNPR9Lndbbfdpnr16ik5OVn333+/0xQoS5cu1ejRoyVdurdc/v60aNFC/v7+2rx5szXFl3Rpmp6ePXtmGtYOGjRINptNM2bMcPoLk6SkJPXp00f79u3L1voee+wxBQcHKzY2Vk899ZT11yfp6ekaP368vvvuO/n4+FhfCDvccccdki59eblx40Zr+R9//KEePXpk+vBjRwC/du1al3uHJxzb/+9//7umZyNkJifuUXv37tXgwYPVoUMHpaWl6cEHH3SZBsnxUOfXXnvN6b3ftGmTevXqJX9/f7fHqF+/vqKiorR582Z9/fXX1/QFOQAAuIIBAABZsnjxYiPJ+Pv7mzNnzly1/S233GIkmbFjx1rLoqOjjSSzYsWKDLfp0aOHkWRmzpzptHzIkCFGkpFkSpcuberUqWMCAgKMj4+PmTZtmpFkypQp47I/xzbu1KhRw2q3aNGiDNs8+eSTVpuyZcua+vXrmypVqhgvLy8jyURFRbmck4yOfeeddxpJpkCBAqZixYqmfv36pmLFilbbFi1amNTUVLf9vdz69euN3W43kkxgYKCpW7euiYiIsPb3/PPPu2yzb9++TM+XOw0aNDCSzPDhw6/a9uuvvzaSjN1uN0lJScYYYy5evGjatWtn9a1KlSqmVq1axtvb25QuXdoMGDDASDIjR4609rNgwQKrfYkSJUzdunVNzZo1TcGCBa39b9myxaP+x8bGWvuSZEJCQkydOnVMVFSUCQoKspY3b97cnD171mX7KVOmWO93UFCQqVOnjqlbt64JDQ21tp02bZrTNmfPnjW3336707XboEEDU716dRMQEGAtd5wjY4yZOXOmkWR69OiRYR0rVqwwkkx0dLRHdV++TbNmzUz79u2NJHPzzTebW265xXh7extJpnz58ubo0aOZ7uPYsWPGx8fHSDK+vr7m1KlTHh//Sj/88IN1zn18fEyNGjVMvXr1TLFixaxz8uijj7psdy2fwyNHjlj3IkmmYsWKpkGDBiYyMtL4+voaSSY0NNRpm5EjR7pci5eLj4+39hcYGGhq1qxp6tata4oXL24kGZvNZt5///1rPj+O+2Rmx7+yXVbvp1fbzhhj/vjjD1OqVCkjyfj5+ZnatWs73atiYmJMenq6y3Yvv/yy1eamm26y7tWhoaFm1KhRmV7bo0ePdtquXr16Jjg42Pj5+ZlXX33VSDK33Xab0zZX+yy4u9d9/fXX1vtfpEgRU69ePRMSEmLdn6dPn+6yTXp6umnVqpXVpnLlyiYqKsoUKFDANGvWzHTv3j3D852QkGCKFCliJJmSJUuaJk2amOjoaKd/G93Zu3ev1dcyZcqYW2+91URHRzsd52r/1pUpU8ZIMvv27XNafi33KHcc51ySqVu3rmnSpIlp0qSJqVWrlnV+HfeQUaNGmYsXL7rsIyEhwZQvX95qV716dVO5cmUjyURGRpqnn376qp+PiRMnWse65557POo7AADIHCPSAQDIIsfo4o4dO7o8ADAjjlFm2TG9y/jx4zV58mRVqVJFcXFxOnDggFq1aqXVq1erbdu217Vvx8jasLCwTPf16KOPatSoUWrWrJlSU1MVGxur+Ph41atXT2+//bY2btzo0Tl5/vnnNWzYMNWrV0/nzp1TbGyskpKSFB0drY8++khLly7NdFRjRho0aKBffvlF/fr1U/HixfXrr7/q3Llzat26tb777ju9/PLLHu/LnT/++MN6iKMnD1G84447VKxYMSUkJOjbb7+VdGn6moULF2rs2LG6+eab9ddff+nYsWPq0aOHNm7cqGLFirns59Zbb9Vbb72ljh07qlChQvr999+1f/9+VaxYUUOHDtWuXbs8HpFes2ZNxcbGauzYsWrVqpWCg4O1a9cu7dmzxxpFP3fuXC1fvtx6CN/lHn/8ccXGxqp3794qUaKEduzYoT/++EPFixfX/fffr88//9wa2e1QqFAhLVmyRHPnzlWbNm104cIFbd26VSdPnlSNGjX07LPPauPGjVcdYZldbDabFixYoFGjRik9PV2///67SpQooccee0wbNmxQWFhYptuGhIRYI3Iz+8sNT7Vu3Vrbt2/XU089pUqVKunPP/9UbGys/Pz8dNddd2nx4sWaNm2ay3bX8jksWbKk1q1bp6lTp6pZs2Y6deqUtm3bprNnz6p+/foaPXq0VqxYkaX+BwUFac6cOYqJiVFERIT279+vHTt2qGjRonrwwQe1bds29e7d+5rPT25QsWJFbdu2TUOGDFHp0qW1Y8cOHT9+XM2aNdOcOXM0e/bsDOfufv755/XOO+8oMjJSJ06c0KFDh3TPPfdo8+bNKlOmTKbHe/HFF/Xpp5+qfv36On36tPbu3aumTZtqzZo1qlmzpqTse2iydOka3rJlix544AH5+/srNjZWxhjdddddWrNmjfr27euyjePz8/TTTys8PNyay3/48OFaunRphn9VI136K52lS5fqjjvuUHJystatW6dVq1Zp165dHvW1QoUK+vbbbxUdHa34+HitWbNGq1at8vjB1O7cyHvU5s2b9fPPP2vdunXav3+/goKCdNddd2nSpEk6fPiwRo4cmeHDioODg7VmzRo99NBDCg4O1u7du5WSkqKnn35a69at8+g6iImJsfbNtC4AAFw/mzHZ+HdxAAAgzxo2bJjGjRunIUOGWNOFAHDVsGFDbdiwQYsWLVL79u1zujv4j5g4caKGDBmiJ5988pqfiYH/ll27dqlq1aoKCwvT4cOHMwzsAQCA5xiRDgAAlJqaas277pgDGoCrHTt2aMOGDSpZsuR1/xUI4Km0tDTrHt2kSZMc7g3yCsdDlS8fmQ4AAK4dQToAANBbb72lo0ePKjo6WpGRkTndHSBXSktL04gRIyRJffv2JZhCtvvggw+0evVqp2WnT59Wz5499euvvyo8PNx6iDHgzr59+zR9+nR5eXmpX79+Od0dAADyBc8nHwUAAPlKXFycunXrplOnTmn79u0qUKCAXn311ZzuFpDrLFmyRK+99pr++usvHTp0SKGhoXryySdzulvIh1avXq3evXurUKFCqlChgowx2rlzp1JTU1WwYEHNmTPnX3uWAPKmQYMGaePGjfrll1904cIF9e3bVxUqVMjpbgEAkC8QpAMA8B/1zz//aNWqVfLx8VG1atU0evRopgwAMhAXF6dVq1YpMDBQLVq00OTJk1WkSJGc7hbyoR49eig1NVXr16/Xn3/+qZSUFIWHh6tly5YaOnSoKleunNNdRC4XGxurdevWKTQ0VL1799Zrr72W010CACDf4GGjAAAAAAAAAAC4wRzpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAkEU2m82j18qVK6+6rzFjxmjhwoXX3Z9Ro0Z53P7kyZPy8/OTzWbT5s2bb+ix3NmwYYPuuusulS5dWn5+fgoNDVWjRo00ePDgbNn/jdKzZ08VKlToXz1m7dq1ZbPZ9Prrr2e4ftasWbLZbNq/f7+1rGfPnipbtuxV9928eXNFRUVluO7kyZPZ+p7nJr///rtGjRrldM7ccZxjx8vf319hYWFq0aKFxo4dq+PHj7tsM2rUKNlsNqdlKSkpevTRR1WyZEl5eXmpVq1akqTTp0+rW7duCgkJkc1mU+fOna+zwhvn+++/z9I1cbXPTKFChdSzZ8/r7xgAAMANRJAOAACQRevWrXN6tWvXTgEBAS7La9eufdV9ZUeQnlVz5sxRSkqKJOmDDz74V4/t8N1336lx48ZKTEzU+PHjtXTpUr355ptq0qSJPv300xzpU24VGxurbdu2Scq59ys/+v333zV69GiPg3SHmTNnat26dVq2bJneeecd1apVS+PGjVPVqlX1448/OrXt3bu31q1b57Rs2rRpmj59ukaMGKE1a9Zozpw5kqSXX35ZCxYs0BtvvKF169Zp/Pjx11XfjfT9999r9OjROd0NAACAf5V3TncAAAAgr2nYsKHTzyVKlFCBAgVcludWH374oUJCQlSmTBl98sknmjRpkgICAv7VPowfP17lypXTDz/8IG/v//tf0m7duuXqADEnzJgxQ5LUvn17fffdd1q7dq0aN26cw726cS5cuKCCBQvmdDcyFRUVpbp161o/33333XrqqafUtGlTdenSRX/88YdCQ0MlSaVKlVKpUqWctt++fbsCAgI0YMAAl+UVKlTQAw88kG19TUpK+tc/23lJbr/WAABA7sKIdAAAgBvg9OnT6t+/v2666Sb5+vqqfPnyGjFihJKTk602NptN58+f1+zZs63pIpo3by5JOnHihPr376/IyEgVKlRIISEhuu2227R69err6teGDRu0fft2xcTEqE+fPkpISNCXX37p0i4xMVF9+vRRsWLFVKhQIbVt21Z79uxxaXfixAn17dtXERER8vPzU4kSJdSkSROXkblXOnXqlIoXL+4UojsUKOD6v6iffvqpGjVqpMDAQBUqVEht2rSxRmlfbvPmzerUqZOKFi0qf39/3XLLLfrss8+c2jim6FixYoUee+wxFS9eXMWKFVOXLl105MgRt/2+3I4dO9SyZUsFBgaqRIkSGjBggC5cuGCtb9mypapUqSJjjNN2xhhVrFhR7du3v+ox/vnnH82bN0916tTRG2+8IenSFyE5ydP3/Mcff1TLli0VHBysggULqkmTJlq+fLlTG8fUJ1u3btU999yjIkWKqEKFCpKkv/76S926dVN4eLg19U/Lli0VGxvrtn+bN29Wt27dVLZsWQUEBKhs2bK6//77deDAAavNrFmzdO+990qSWrRoYX3+Zs2adU3npHTp0po4caLOnj2r6dOnu9TnYLPZNGPGDCUlJTkd02az6ccff9TOnTtdpoZKSUnRK6+8oipVqljn++GHH9aJEyec+lC2bFl16NBBX331lW655Rb5+/tbo8bj4uLUr18/lSpVSr6+vipXrpxGjx6tixcvWtvv37/fmj5o0qRJKleunAoVKqRGjRpp/fr1VruePXvqnXfesepxvLI6sv9qDh48qAcffFAhISHy8/NT1apVNXHiRKWnp1ttVq5cmeE0Wo5aLn8/HdPL/Pbbb2rdurWCgoLUsmVLSdK2bdvUoUMH61jh4eFq3769Dh8+nK01AQCAvI0R6QAAANnsn3/+UYsWLfTnn39q9OjRqlGjhlavXq2xY8cqNjZW3333naRLU8TcdtttatGihV544QVJUnBwsKRLQbwkjRw5UmFhYTp37pwWLFig5s2ba/ny5VbgnlWOqUF69eqliIgIDRo0SB988IEefPBBq40xRp07d9batWv14osvql69evr55591xx13uOwvJiZGW7du1auvvqqbb75ZZ86c0datW3Xq1Cm3/WjUqJFmzJihgQMH6oEHHlDt2rXl4+OTYdsxY8bo+eef18MPP6znn39eKSkpmjBhgm699VZt3LhRkZGRkqQVK1aobdu2atCggd59913Z7XbNnz9f9913ny5cuOAyB3Pv3r3Vvn17zZs3T4cOHdIzzzyjBx98UD/99NNVz2NqaqratWunfv36adiwYVq7dq1eeeUVHThwQN9++60k6cknn9Sdd96p5cuXq1WrVta2ixcv1p9//qm33nrrqsf56quvFB8fr169eqlSpUpq2rSpPv30U02ePPlfn6fdwZP3/OOPP9ZDDz2kO++8U7Nnz5aPj4+mT5+uNm3a6IcffrACTIcuXbqoW7duevTRR3X+/HlJUrt27ZSWlqbx48erdOnSOnnypNauXaszZ8647d/+/ftVuXJldevWTUWLFtXRo0c1bdo01atXT7///ruKFy+u9u3ba8yYMXruuef0zjvvWNMwOUL8a9GuXTt5eXnpf//7X6Zt1q1bp5dfflkrVqywrrNy5cpp3bp16t+/vxISEjR37lxJUmRkpNLT03XnnXdq9erVGjp0qBo3bqwDBw5o5MiRat68uTZv3uw04nzr1q3auXOnnn/+eZUrV06BgYGKi4tT/fr1VaBAAb344ouqUKGC1q1bp1deeUX79+/XzJkznfr4zjvvqEqVKpo8ebIk6YUXXlC7du20b98+2e12vfDCCzp//ry++OILp2lrSpYsedVzdHlw786JEyfUuHFjpaSk6OWXX1bZsmW1aNEiDRkyRH/++aemTp3q0X6ulJKSok6dOlmf24sXL+r8+fO6/fbbVa5cOb3zzjsKDQ1VXFycVqxYobNnz17TcQAAQD5lAAAAcF169OhhAgMDrZ/fffddI8l89tlnTu3GjRtnJJmlS5daywIDA02PHj2ueoyLFy+a1NRU07JlS3PXXXc5rZNkRo4cedV9nD9/3gQHB5uGDRs69d1ms5m9e/dayxYvXmwkmTfffNNp+1dffdXlWIUKFTKDBg266rGvdPLkSdO0aVMjyUgyPj4+pnHjxmbs2LHm7NmzVruDBw8ab29v88QTTzhtf/bsWRMWFma6du1qLatSpYq55ZZbTGpqqlPbDh06mJIlS5q0tDRjjDEzZ840kkz//v2d2o0fP95IMkePHnXb9x49erg9P2vWrDHGGJOWlmbKly9v7rzzTqd2d9xxh6lQoYJJT093exxjjLntttuMv7+/iY+Pd+r7Bx984NTOsXzfvn1O/SxTpsxVjxEdHW2qVauW4boTJ05k+T0/f/68KVq0qOnYsaPT8rS0NFOzZk1Tv359a9nIkSONJPPiiy86tT158qSRZCZPnnzV/l/NxYsXzblz50xgYKDTe/b5558bSWbFihUe7cdxjjdt2pRpm9DQUFO1alXrZ0d9l7vyfuGQ0fvwySefGEnmyy+/dFq+adMmI8lMnTrVWlamTBnj5eVldu/e7dS2X79+plChQubAgQNOy19//XUjyezYscMYY8y+ffuMJFO9enVz8eJFq93GjRuNJPPJJ59Yyx5//HGXutxxfGbcvS6/Dw4bNsxIMhs2bHDaz2OPPWZsNptV44oVKzJ8Dx21zJw506UPH374oVPbzZs3G0lm4cKFHtcDAAD+m5jaBQAAIJv99NNPCgwM1D333OO03DEi+srpLTLz7rvvqnbt2vL395e3t7d8fHy0fPly7dy585r69dlnnykxMVG9evWylvXq1UvGGKdRqStWrJAkl7mau3fv7rLP+vXra9asWXrllVe0fv16paametSXYsWKafXq1dq0aZNee+013XnnndqzZ4+GDx+u6tWr6+TJk5KkH374QRcvXtRDDz2kixcvWi9/f39FR0dbUzrs3btXu3btsvp8edt27drp6NGj2r17t1MfOnXq5PRzjRo1JMlpChB3Mjs/jvNXoEABDRgwQIsWLdLBgwclSX/++aeWLFmi/v37O035kZF9+/ZpxYoV6tKliwoXLixJuvfeexUUFJSj07tc7T1fu3atTp8+rR49eji9D+np6Wrbtq02bdpkjTp3uPvuu51+Llq0qCpUqKAJEyZo0qRJ2rZtm9OUHu6cO3dOzz77rCpWrChvb295e3urUKFCOn/+/DV/djxlrpjG53otWrRIhQsXVseOHZ3OZa1atRQWFuYypUmNGjV08803u+yjRYsWCg8Pd9qH4y9MVq1a5dS+ffv28vLyctqn5PnnIjMBAQHatGlThq8r53H/6aefFBkZqfr16zst79mzp4wxHv3VSGauvNYqVqyoIkWK6Nlnn9W7776r33///Zr3DQAA8jeCdAAAgGx26tQphYWFuQSlISEh8vb2vuq0J5I0adIkPfbYY2rQoIG+/PJLrV+/Xps2bVLbtm2VlJR0Tf364IMP5O/vr7Zt2+rMmTM6c+aMatSoobJly2rWrFlKS0uz+u/t7a1ixYo5bR8WFuayz08//VQ9evTQjBkz1KhRIxUtWlQPPfSQ4uLiPOpT3bp19eyzz+rzzz/XkSNH9NRTT2n//v3WA0ePHTsmSapXr558fHycXp9++qkVuDvaDRkyxKVd//79Jclq63BlfX5+fpLk0fl1d34uf3979eqlgIAAvfvuu5IuTZsREBDg9GVGZj788EMZY3TPPfdY71dqaqo6deqkn3/+Wbt27brqPjzh7e1tvfdXckzFcfm0O1d7zx3vxT333OPyXowbN07GGGvqIocrpwWx2Wxavny52rRpo/Hjx6t27doqUaKEBg4ceNXpNrp3764pU6aod+/e+uGHH7Rx40Zt2rRJJUqUuObPjifOnz+vU6dOKTw8PNv2eezYMZ05c0a+vr4u5zIuLs7lms5oepVjx47p22+/ddm+WrVqkrL3c+FOgQIFVLdu3QxfVz4X4dSpUxnW4ji3ntxDM1KwYEFr+iwHu92uVatWqVatWnruuedUrVo1hYeHa+TIkR5/MQgAAP4bmCMdAAAgmxUrVkwbNmyQMcYpTD9+/LguXryo4sWLX3UfH3/8sZo3b65p06Y5Lb/WOXv37NmjNWvWSLr0YMSM/PDDD2rXrp2KFSumixcv6tSpU06hWkbhePHixTV58mRNnjxZBw8e1DfffKNhw4bp+PHjWrJkSZb66OPjo5EjR+qNN97Q9u3brf1L0hdffKEyZcpkuq2j3fDhw9WlS5cM21SuXDlL/XHH3fm5fJndbrdC5yFDhmjmzJnq3r27NcI8M+np6daDEjOr58MPP7S+cLgeoaGh2rRpk8v1Kkl///231cbhau+54714++231bBhw0yPebmMRueXKVPGmtN/z549+uyzzzRq1CilpKRYX0xcKSEhQYsWLdLIkSM1bNgwa3lycrJLeJ/dvvvuO6WlpV3z8wsy4ngQbmafpaCgIKefMzqPxYsXV40aNfTqq69muI/sDP6zS7FixXT06FGX5Y6HATuuMX9/f0lyeoiz5PrlgENmfwVSvXp1zZ8/X8YY/frrr5o1a5ZeeuklBQQEOF1HAADgv40gHQAAIJu1bNlSn332mRYuXKi77rrLWv7RRx9Z6x38/PwyHOlps9mskaAOv/76q9atW6eIiIgs98kRSL7//vuqWLGi07qkpCTdeeed+vDDD9WuXTu1aNFC48eP19y5czVw4ECr3bx589weo3Tp0howYICWL1+un3/+2W3bo0ePZjji1DH1hiPca9Omjby9vfXnn3+6TMlwucqVK6tSpUr65ZdfNGbMGLfHzi6ZnZ8rg9SBAwdq6tSp1sjyAQMGXHXfP/zwgw4fPqzHH3/cZYogSRowYIA++ugjjRkzRt7e1/e/9K1atdK8efO0ZMkSlwfKfvbZZypQoIBuu+22DLfN6D1v0qSJChcurN9//92jWj1x88036/nnn9eXX36prVu3ZtrOZrPJGOPy2ZkxY4bLqPvsGmktSQcPHtSQIUNkt9vVr1+/696fQ4cOHTR//nylpaWpQYMG17yP77//XhUqVFCRIkWypV+Xn7srp2XJDi1bttTYsWO1detW60Gw0qV7qM1mU4sWLSRJZcuWlXTp3timTRur3TfffHNNx7XZbKpZs6beeOMNzZo1y+21BgAA/nsI0gEAALLZQw89pHfeeUc9evTQ/v37Vb16da1Zs0ZjxoxRu3bt1KpVK6tt9erVtXLlSn377bcqWbKkgoKCVLlyZXXo0EEvv/yyRo4cqejoaO3evVsvvfSSypUrZ0234amLFy/qo48+UtWqVdW7d+8M23Ts2FHffPONTpw4odatW6tZs2YaOnSozp8/r7p16+rnn3/WnDlznLZJSEhQixYt1L17d1WpUkVBQUHatGmTlixZkukoaoc2bdqoVKlS6tixo6pUqaL09HTFxsZq4sSJKlSokJ588klJl4Kyl156SSNGjNBff/2ltm3bqkiRIjp27Jg2btyowMBAjR49WpI0ffp03XHHHWrTpo169uypm266SadPn9bOnTu1detWff7551k6b+74+vpq4sSJOnfunOrVq6e1a9fqlVde0R133KGmTZs6tb355pvVtm1bLV68WE2bNlXNmjWvuv8PPvhA3t7eeu655zIcMdyvXz8NHDhQ3333ne68887rquWBBx7Q1KlT1bVrVw0bNkz16tVTUlKSvv/+e73//vt64oknVL58eUmeveeFChXS22+/rR49euj06dO65557FBISohMnTuiXX37RiRMnXP7S4kq//vqrBgwYoHvvvVeVKlWSr6+vfvrpJ/36669uRwgHBwerWbNmmjBhgooXL66yZctq1apV+uCDD1z+CiAqKkqS9N577ykoKEj+/v4qV66cy9QmV9q+fbs1z/jx48e1evVqzZw5U15eXlqwYIFKlChxtVPusW7dumnu3Llq166dnnzySdWvX18+Pj46fPiwVqxYoTvvvNPpy7qMvPTSS1q2bJkaN26sgQMHqnLlyvrnn3+0f/9+ff/993r33XdVqlSpLPWrevXqkqRx48bpjjvukJeXl2rUqCFfX99rrvVyTz31lD766CO1b99eL730ksqUKaPvvvtOU6dO1WOPPWbNAx8WFqZWrVpp7NixKlKkiMqUKaPly5frq6++8vhYixYt0tSpU9W5c2eVL19exhh99dVXOnPmjG6//fZsqQcAAOQTOfWUUwAAgPyiR48eJjAw0GnZqVOnzKOPPmpKlixpvL29TZkyZczw4cPNP//849QuNjbWNGnSxBQsWNBIMtHR0cYYY5KTk82QIUPMTTfdZPz9/U3t2rXNwoULTY8ePUyZMmWc9iHJjBw5MtP+LVy40EgykydPzrTNkiVLjCQzceJEY4wxZ86cMb169TKFCxc2BQsWNLfffrvZtWuX07H++ecf8+ijj5oaNWqY4OBgExAQYCpXrmxGjhxpzp8/7/acffrpp6Z79+6mUqVKplChQsbHx8eULl3axMTEmN9//z3DGlq0aGGCg4ONn5+fKVOmjLnnnnvMjz/+6NTul19+MV27djUhISHGx8fHhIWFmdtuu828++67VpuZM2caSWbTpk1O265YscJIMitWrHDbd8f7/euvv5rmzZubgIAAU7RoUfPYY4+Zc+fOZbjNrFmzjCQzf/58t/s2xpgTJ04YX19f07lz50zbxMfHm4CAANOxY0enmvbt2+fUzyuvlcwkJiaaoUOHmkqVKhlfX19TsGBBU7duXfPuu++a9PR0q11W3vNVq1aZ9u3bm6JFixofHx9z0003mfbt25vPP//cajNy5EgjyZw4ccJp22PHjpmePXuaKlWqmMDAQFOoUCFTo0YN88Ybb5iLFy+6reXw4cPm7rvvNkWKFDFBQUGmbdu2Zvv27aZMmTKmR48eTm0nT55sypUrZ7y8vIwkM3PmzEz36zjHjpevr68JCQkx0dHRZsyYMeb48eMu2zjqu1xG9wtjjImOjjbVqlVzWZ6ammpef/11U7NmTePv728KFSpkqlSpYvr162f++OMPq12ZMmVM+/btM+z7iRMnzMCBA025cuWMj4+PKVq0qKlTp44ZMWKEdc3u27fPSDITJkxw2f7Ke0xycrLp3bu3KVGihLHZbC7X3pUyq9khMDDQ5b05cOCA6d69uylWrJjx8fExlStXNhMmTDBpaWlO7Y4ePWruueceU7RoUWO3282DDz5oNm/e7PJ+ZtaHXbt2mfvvv99UqFDBBAQEGLvdburXr29mzZqVaX8BAMB/k82YbH60PAAAAAAnd999t9avX6/9+/c7PbgTAAAAQN7A1C4AAADADZCcnKytW7dq48aNWrBggSZNmkSIDgAAAORRjEgHAAAAboD9+/erXLlyCg4OVvfu3TVlyhR5eXnldLcAAAAAXAOCdAAAAAAAAAAA3CiQ0x0AAAAAAAAAACA3I0gHAAAAAAAAAMANgnQAAAAAAAAAANzwzukO5Cfp6ek6cuSIgoKCZLPZcro7AAAAAAAAAIBMGGN09uxZhYeHq0AB92POCdKz0ZEjRxQREZHT3QAAAAAAAAAAeOjQoUMqVaqU2zYE6dkoKChI0qUTHxwcnMO9AQAAAAAAAABkJjExUREREVau6w5BejZyTOcSHBxMkA4AAAAAAAAAeYAn03TzsFEAAAAAAAAAANwgSAcAAAAAAAAAwA2CdAAAAAAAAAAA3CBIBwAAAAAAAADADYJ0AAAAAAAAAADcIEgHAAAAAAAAAMANgnQAAAAAAAAAANwgSAcAAAAAAAAAwA2CdAAAAAAAAAAA3CBIBwAAAAAAAADADYJ0AAAAAAAAAADcIEgHAAAAAAAAAMANgnQAAAAAAAAAANwgSAcAAAAAAAAAwA3vnO4AAAAAAABAXmKz5XQPPGdMTvcAAPIHRqQDAAAAAAAAAOAGQToAAAAAAAAAAG4QpAMAAAAAAAAA4AZBOgAAAAAAAAAAbhCkAwAAAAAAAADgBkE6AAAAAAAAAABuEKQDAAAAAAAAAOAGQToAAAAAAAAAAG4QpAMAAAAAAAAA4AZBOgAAAAAAAAAAbnjndAcAAAAAAAAAIL+x2XK6B54zJqd7kPsxIh0AAAAAAAAAADcI0gEAAAAAAAAAcIMgHQAAAAAAAAAANwjSAQAAAAAAAABwg4eNAgAAAACQS+SVB9PxUDoAwH8NI9IBAAAAAAAAAHCDIB0AAAAAAAAAADcI0gEAAAAAAAAAcIMgHQAAAAAAAAAAN3jYKAAAAAAAAPKlvPIAX4mH+AK5HUE6AAAAAAAA8kzoTOCcP3H9IbdjahcAAAAAAAAAANxgRDoAAAAAIM/JKyMXJUYvAshe3P+AnMGIdAAAAAAAAAAA3CBIBwAAAAAAAADADYJ0AAAAAAAAAADcyNEg/X//+586duyo8PBw2Ww2LVy40FqXmpqqZ599VtWrV1dgYKDCw8P10EMP6ciRI077SE5O1hNPPKHixYsrMDBQnTp10uHDh53axMfHKyYmRna7XXa7XTExMTpz5oxTm4MHD6pjx44KDAxU8eLFNXDgQKWkpNyo0gEAAAAAAAAAeUSOBunnz59XzZo1NWXKFJd1Fy5c0NatW/XCCy9o69at+uqrr7Rnzx516tTJqd2gQYO0YMECzZ8/X2vWrNG5c+fUoUMHpaWlWW26d++u2NhYLVmyREuWLFFsbKxiYmKs9WlpaWrfvr3Onz+vNWvWaP78+fryyy81ePDgG1c8AAAAAAAAACBPsBmTO56fa7PZtGDBAnXu3DnTNps2bVL9+vV14MABlS5dWgkJCSpRooTmzJmj++67T5J05MgRRURE6Pvvv1ebNm20c+dORUZGav369WrQoIEkaf369WrUqJF27dqlypUra/HixerQoYMOHTqk8PBwSdL8+fPVs2dPHT9+XMHBwR7VkJiYKLvdroSEBI+3AQAAAABknc2W0z3wXFZ+684rdeWOJCHn5JX3SeL6yys1SZ7XlR9rkvJOXfmxJum/e1/PSp6bp+ZIT0hIkM1mU+HChSVJW7ZsUWpqqlq3bm21CQ8PV1RUlNauXStJWrdunex2uxWiS1LDhg1lt9ud2kRFRVkhuiS1adNGycnJ2rJly79QGQAAAAAAAAAgt/LO6Q546p9//tGwYcPUvXt369uBuLg4+fr6qkiRIk5tQ0NDFRcXZ7UJCQlx2V9ISIhTm9DQUKf1RYoUka+vr9UmI8nJyUpOTrZ+TkxMvLbiAAAAAADIpxiRCQDID/LEiPTU1FR169ZN6enpmjp16lXbG2Nku+xfalsG/2pfS5srjR071nqAqd1uV0RExFX7BgAAAAAAAADIW3J9kJ6amqquXbtq3759WrZsmdNcNWFhYUpJSVF8fLzTNsePH7dGmIeFhenYsWMu+z1x4oRTmytHnsfHxys1NdVlpPrlhg8froSEBOt16NCha64TAAAAAAAAAJA75eog3RGi//HHH/rxxx9VrFgxp/V16tSRj4+Pli1bZi07evSotm/frsaNG0uSGjVqpISEBG3cuNFqs2HDBiUkJDi12b59u44ePWq1Wbp0qfz8/FSnTp1M++fn56fg4GCnFwAAAAAAAAAgf8nROdLPnTunvXv3Wj/v27dPsbGxKlq0qMLDw3XPPfdo69atWrRokdLS0qxR40WLFpWvr6/sdrseeeQRDR48WMWKFVPRokU1ZMgQVa9eXa1atZIkVa1aVW3btlWfPn00ffp0SVLfvn3VoUMHVa5cWZLUunVrRUZGKiYmRhMmTNDp06c1ZMgQ9enTh3AcAAAAAAAAAP7jbMbk3KM0Vq5cqRYtWrgs79Gjh0aNGqVy5cpluN2KFSvUvHlzSZceQvrMM89o3rx5SkpKUsuWLTV16lSn+cpPnz6tgQMH6ptvvpEkderUSVOmTFHhwoWtNgcPHlT//v31008/KSAgQN27d9frr78uPz8/j+tJTEyU3W5XQkICATwAAAAA3ED59QGWeaWu/FiT5Hld+bEmKe/UlR9rkrj+8kpd+bEm6b/7sOWs5Lk5GqTnNwTpAAAAAPDvyK/hRF6pKz/WJBFk5pW68mNNEtdfXqkrP9YkEaR7kufm6jnSAQAAAAAAAADIaQTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuEGQDgAAAAAAAACAGwTpAAAAAAAAAAC4QZAOAAAAAAAAAIAbBOkAAAAAAAAAALiRo0H6//73P3Xs2FHh4eGy2WxauHCh03pjjEaNGqXw8HAFBASoefPm2rFjh1Ob5ORkPfHEEypevLgCAwPVqVMnHT582KlNfHy8YmJiZLfbZbfbFRMTozNnzji1OXjwoDp27KjAwEAVL15cAwcOVEpKyo0oGwAAAAAAAACQh+RokH7+/HnVrFlTU6ZMyXD9+PHjNWnSJE2ZMkWbNm1SWFiYbr/9dp09e9ZqM2jQIC1YsEDz58/XmjVrdO7cOXXo0EFpaWlWm+7duys2NlZLlizRkiVLFBsbq5iYGGt9Wlqa2rdvr/Pnz2vNmjWaP3++vvzySw0ePPjGFQ8AAAAAAAAAyBNsxhiT052QJJvNpgULFqhz586SLo1GDw8P16BBg/Tss89KujT6PDQ0VOPGjVO/fv2UkJCgEiVKaM6cObrvvvskSUeOHFFERIS+//57tWnTRjt37lRkZKTWr1+vBg0aSJLWr1+vRo0aadeuXapcubIWL16sDh066NChQwoPD5ckzZ8/Xz179tTx48cVHBzsUQ2JiYmy2+1KSEjweBsAAAAAQNbZbDndA89l5bfuvFJXfqxJ8ryu/FiTlHfqyo81SVx/eaWu/FiTlLW68pOs5Lm5do70ffv2KS4uTq1bt7aW+fn5KTo6WmvXrpUkbdmyRampqU5twsPDFRUVZbVZt26d7Ha7FaJLUsOGDWW3253aREVFWSG6JLVp00bJycnasmXLDa0TAAAAAAAAAJC7eed0BzITFxcnSQoNDXVaHhoaqgMHDlhtfH19VaRIEZc2ju3j4uIUEhLisv+QkBCnNlcep0iRIvL19bXaZCQ5OVnJycnWz4mJiZ6WBwAAAAAAAADII3LtiHQH2xV/A2GMcVl2pSvbZNT+WtpcaezYsdYDTO12uyIiItz2CwAAAAAAAACQ9+TaID0sLEySXEaEHz9+3Bo9HhYWppSUFMXHx7ttc+zYMZf9nzhxwqnNlceJj49Xamqqy0j1yw0fPlwJCQnW69ChQ1msEgAAAAAAAACQ2+XaIL1cuXIKCwvTsmXLrGUpKSlatWqVGjduLEmqU6eOfHx8nNocPXpU27dvt9o0atRICQkJ2rhxo9Vmw4YNSkhIcGqzfft2HT161GqzdOlS+fn5qU6dOpn20c/PT8HBwU4vAAAAAAAAAED+kqNzpJ87d0579+61ft63b59iY2NVtGhRlS5dWoMGDdKYMWNUqVIlVapUSWPGjFHBggXVvXt3SZLdbtcjjzyiwYMHq1ixYipatKiGDBmi6tWrq1WrVpKkqlWrqm3bturTp4+mT58uSerbt686dOigypUrS5Jat26tyMhIxcTEaMKECTp9+rSGDBmiPn36EI4DAAAAAAAAwH9cjgbpmzdvVosWLayfn376aUlSjx49NGvWLA0dOlRJSUnq37+/4uPj1aBBAy1dulRBQUHWNm+88Ya8vb3VtWtXJSUlqWXLlpo1a5a8vLysNnPnztXAgQPVunVrSVKnTp00ZcoUa72Xl5e+++479e/fX02aNFFAQIC6d++u119//UafAgAAAAAAAABALmczxpic7kR+kZiYKLvdroSEBEayAwAAAMANZLPldA88l5XfuvNKXfmxJsnzuvJjTVLeqSs/1iRx/eWVuvJjTVLW6spPspLn5to50gEAAAAAAAAAyA0I0gEAAAAAAAAAcIMgHQAAAAAAAAAANwjSAQAAAAAAAABwgyAdAAAAAAAAAAA3CNIBAAAAAAAAAHCDIB0AAAAAAAAAADcI0gEAAAAAAAAAcIMgHQAAAAAAAAAANwjSAQAAAAAAAABwgyAdAAAAAAAAAAA3CNIBAAAAAAAAAHCDIB0AAAAAAAAAADcI0gEAAAAAAAAAcIMgHQAAAAAAAAAANwjSAQAAAAAAAABwgyAdAAAAAAAAAAA3CNIBAAAAAAAAAHCDIB0AAAAAAAAAADcI0gEAAAAAAAAAcIMgHQAAAAAAAAAAN7yvdcOUlBQdP35c6enpTstLly593Z0CAAAAAAAAACC3yHKQ/scff6hXr15au3at03JjjGw2m9LS0rKtcwAAAAAAAAAA5LQsB+k9e/aUt7e3Fi1apJIlS8pms92IfgEAAAAAAAAAkCtkOUiPjY3Vli1bVKVKlRvRHwAAAAAAAAAAcpUsP2w0MjJSJ0+evBF9AQAAAAAAAAAg18lykD5u3DgNHTpUK1eu1KlTp5SYmOj0AgAAAAAAAAAgP7EZY0xWNihQ4FL2fuXc6DxsVEpMTJTdbldCQoKCg4NzujsAAAAAkG/lpcd1ZeW37rxSV36sSfK8rvxYk5R36sqPNUlcf3mlrvxYk5S1uvKTrOS5WZ4jfcWKFdfcMQAAAAAAAAAA8posB+nR0dE3oh8AAAAAAAAAAORKWZ4jXZJWr16tBx98UI0bN9bff/8tSZozZ47WrFmTrZ0DAAAAAAAAACCnZTlI//LLL9WmTRsFBARo69atSk5OliSdPXtWY8aMyfYOAgAAAAAAAACQk7IcpL/yyit699139f7778vHx8da3rhxY23dujVbOwcAAAAAAAAAQE7LcpC+e/duNWvWzGV5cHCwzpw5kx19AgAAAAAAAAAg18hykF6yZEnt3bvXZfmaNWtUvnz5bOkUAAAAAAAAAAC5RZaD9H79+unJJ5/Uhg0bZLPZdOTIEc2dO1dDhgxR//79b0QfAQAAAAAAAADIMd5Z3WDo0KFKSEhQixYt9M8//6hZs2by8/PTkCFDNGDAgBvRRwAAAAAAAAAAcozNGGOuZcMLFy7o999/V3p6uiIjI1WoUKHs7luek5iYKLvdroSEBAUHB+d0dwAAAAAg37LZcroHnsvKb915pa78WJPkeV35sSYp79SVH2uSuP7ySl35sSYpa3XlJ1nJc7M8tYvDkSNHdOrUKVWvXl2FChXSNebxAAAAAAAAAADkalkO0k+dOqWWLVvq5ptvVrt27XT06FFJUu/evTV48OBs7yAAAAAAAAAAADkpy0H6U089JR8fHx08eFAFCxa0lt93331asmRJtnbu4sWLev7551WuXDkFBASofPnyeumll5Senm61McZo1KhRCg8PV0BAgJo3b64dO3Y47Sc5OVlPPPGEihcvrsDAQHXq1EmHDx92ahMfH6+YmBjZ7XbZ7XbFxMTozJkz2VoPAAAAAAAAACDvyXKQvnTpUo0bN06lSpVyWl6pUiUdOHAg2zomSePGjdO7776rKVOmaOfOnRo/frwmTJigt99+22ozfvx4TZo0SVOmTNGmTZsUFham22+/XWfPnrXaDBo0SAsWLND8+fO1Zs0anTt3Th06dFBaWprVpnv37oqNjdWSJUu0ZMkSxcbGKiYmJlvrAQAAAAAAAADkPd5Z3eD8+fNOI9EdTp48KT8/v2zplMO6det05513qn379pKksmXL6pNPPtHmzZslXRqNPnnyZI0YMUJdunSRJM2ePVuhoaGaN2+e+vXrp4SEBH3wwQeaM2eOWrVqJUn6+OOPFRERoR9//FFt2rTRzp07tWTJEq1fv14NGjSQJL3//vtq1KiRdu/ercqVK2drXQAAAAAAAACAvCPLI9KbNWumjz76yPrZZrMpPT1dEyZMUIsWLbK1c02bNtXy5cu1Z88eSdIvv/yiNWvWqF27dpKkffv2KS4uTq1bt7a28fPzU3R0tNauXStJ2rJli1JTU53ahIeHKyoqymqzbt062e12K0SXpIYNG8put1ttAAAAAAAAAAD/TVkekT5hwgQ1b95cmzdvVkpKioYOHaodO3bo9OnT+vnnn7O1c88++6wSEhJUpUoVeXl5KS0tTa+++qruv/9+SVJcXJwkKTQ01Gm70NBQa5qZuLg4+fr6qkiRIi5tHNvHxcUpJCTE5fghISFWm4wkJycrOTnZ+jkxMfEaqgQAAAAAAAAA5GZZHpEeGRmpX3/9VfXr19ftt9+u8+fPq0uXLtq2bZsqVKiQrZ379NNP9fHHH2vevHnaunWrZs+erddff12zZ892amez2Zx+Nsa4LLvSlW0yan+1/YwdO9Z6OKndbldERIQnZQEAAAAAAAAA8pAsj0iXpLCwMI0ePTq7++LimWee0bBhw9StWzdJUvXq1XXgwAGNHTtWPXr0UFhYmKRLI8pLlixpbXf8+HFrlHpYWJhSUlIUHx/vNCr9+PHjaty4sdXm2LFjLsc/ceKEy2j3yw0fPlxPP/209XNiYiJhOgAAAAAAAADkMx6PSD99+rQOHz7stGzHjh16+OGH1bVrV82bNy/bO3fhwgUVKODcRS8vL6Wnp0uSypUrp7CwMC1btsxan5KSolWrVlkheZ06deTj4+PU5ujRo9q+fbvVplGjRkpISNDGjRutNhs2bFBCQoLVJiN+fn4KDg52egEAAAAAAAAA8hePR6Q//vjjKlmypCZNmiTp0ojuW2+9VeHh4apQoYJ69uyptLQ0xcTEZFvnOnbsqFdffVWlS5dWtWrVtG3bNk2aNEm9evWSdGk6lkGDBmnMmDGqVKmSKlWqpDFjxqhgwYLq3r27JMlut+uRRx7R4MGDVaxYMRUtWlRDhgxR9erV1apVK0lS1apV1bZtW/Xp00fTp0+XJPXt21cdOnRQ5cqVs60eAAAAAAAAAEDe43GQvn79es2cOdP6+aOPPlLRokUVGxsrb29vvf7663rnnXeyNUh/++239cILL6h///46fvy4wsPD1a9fP7344otWm6FDhyopKUn9+/dXfHy8GjRooKVLlyooKMhq88Ybb8jb21tdu3ZVUlKSWrZsqVmzZsnLy8tqM3fuXA0cOFCtW7eWJHXq1ElTpkzJtloAAAAAAAAAAHmTzRhjPGkYEBCgXbt2qUyZMpKkdu3aqVq1apowYYIkac+ePWrUqJFOnTp143qbyyUmJsputyshIYFpXgAAAADgBrLZcroHnvPst+5L8kpd+bEmyfO68mNNUt6pKz/WJHH95ZW68mNNUtbqyk+ykud6PEd6cHCwzpw5Y/28ceNGNWzY0PrZZrMpOTk5670FAAAAAAAAACAX8zhIr1+/vt566y2lp6friy++0NmzZ3XbbbdZ6/fs2aOIiIgb0kkAAAAAAAAAAHKKx3Okv/zyy2rVqpU+/vhjXbx4Uc8995yKFClirZ8/f76io6NvSCcBAAAAAAAAAMgpHgfptWrV0s6dO7V27VqFhYWpQYMGTuu7deumyMjIbO8gAAAAAAAAAAA5yeOHjeLqeNgoAAAAAPw78usD3PJKXfmxJomHPeaVuvJjTRLXX16pKz/WJPGw0Wx92CgAAAAAAAAAAP9FBOkAAAAAAAAAALhBkA4AAAAAAAAAgBsE6QAAAAAAAAAAuJHlIH3r1q367bffrJ+//vprde7cWc8995xSUlKytXMAAAAAAAAAAOS0LAfp/fr10549eyRJf/31l7p166aCBQvq888/19ChQ7O9gwAAAAAAAAAA5KQsB+l79uxRrVq1JEmff/65mjVrpnnz5mnWrFn68ssvs7t/AAAAAAAAAADkqCwH6cYYpaenS5J+/PFHtWvXTpIUERGhkydPZm/vAAAAAAAAAADIYVkO0uvWratXXnlFc+bM0apVq9S+fXtJ0r59+xQaGprtHQQAAAAAAAAAICdlOUifPHmytm7dqgEDBmjEiBGqWLGiJOmLL75Q48aNs72DAAAAAAAAAADkJJsxxmTHjv755x95eXnJx8cnO3aXJyUmJsputyshIUHBwcE53R0AAAAAyLdstpzugeey8lt3XqkrP9YkeV5XfqxJyjt15ceaJK6/vFJXfqxJylpd+UlW8lzv7Dqov79/du0KAAAAAAAAAIBcw6MgvUiRIrJ5+BXK6dOnr6tDAAAAAAAAAADkJh4F6ZMnT7b++9SpU3rllVfUpk0bNWrUSJK0bt06/fDDD3rhhRduSCcBAAAAAAAAAMgpWZ4j/e6771aLFi00YMAAp+VTpkzRjz/+qIULF2Zn//IU5kgHAAAAgH9Hfp13Nq/UlR9rkpijOq/UlR9rkrj+8kpd+bEmiTnSPclzC2R15z/88IPatm3rsrxNmzb68ccfs7o7AAAAAAAAAABytSwH6cWKFdOCBQtcli9cuFDFihXLlk4BAAAAAAAAAJBbeDRH+uVGjx6tRx55RCtXrrTmSF+/fr2WLFmiGTNmZHsHAQAAAAAAAADISVkO0nv27KmqVavqrbfe0ldffSVjjCIjI/Xzzz+rQYMGN6KPAAAAAAAAAADkmCw/bDQzaWlp+vbbb9W5c+fs2F2exMNGAQAAAODfkV8f4JZX6sqPNUk87DGv1JUfa5K4/vJKXfmxJomHjXqS52Z5RPqVdu3apQ8//FCzZ89WfHy8UlJSrneXAAAAAAAAAADkGll+2KgknT9/Xh9++KGaNGmiatWqaevWrXr11Vd15MiR7O4fAAAAAAAAAAA5Kksj0tetW6cZM2bos88+U6VKlfTAAw9ow4YNeuuttxQZGXmj+ggAAAAAAAAAQI7xOEiPjIzUhQsX1L17d23YsMEKzocNG3bDOgcAAAAAAAAAQE7zeGqXvXv3qlmzZmrRooWqVq16I/sEAAAAAAAAAECu4XGQvm/fPlWuXFmPPfaYSpUqpSFDhmjbtm2y5aXHzwIAAAAAAAAAkEUeB+k33XSTRowYob1792rOnDmKi4tTkyZNdPHiRc2aNUt79uy5kf0EAAAAAAAAACBHeBykX+62227Txx9/rKNHj2rKlCn66aefVKVKFdWoUSO7+wcAAAAAAAAAQI66piDdwW63q3///tq8ebO2bt2q5s2bZ1O3AAAAAAAAAADIHWzGGJPTncgvEhMTZbfblZCQoODg4JzuDgAAAADkW3npcV1Z+a07r9SVH2uSPK8rP9Yk5Z268mNNEtdfXqkrP9YkZa2u/CQree51jUgHAAAAAAAAACC/I0gHAAAAAAAAAMANgnQAAAAAAAAAANwgSAcAAAAAAAAAwA1vTxq99dZbHu9w4MCB19wZAAAAAAAAAAByG5sxV38ma7ly5Tzbmc2mv/7667o7dbm///5bzz77rBYvXqykpCTdfPPN+uCDD1SnTh1JkjFGo0eP1nvvvaf4+Hg1aNBA77zzjqpVq2btIzk5WUOGDNEnn3yipKQktWzZUlOnTlWpUqWsNvHx8Ro4cKC++eYbSVKnTp309ttvq3Dhwh73NStPeQUAAAAAXDubLad74Lmr/9b9f/JKXfmxJsnzuvJjTVLeqSs/1iRx/eWVuvJjTVLW6spPspLnejQifd++fdnSsayKj49XkyZN1KJFCy1evFghISH6888/ncLt8ePHa9KkSZo1a5ZuvvlmvfLKK7r99tu1e/duBQUFSZIGDRqkb7/9VvPnz1exYsU0ePBgdejQQVu2bJGXl5ckqXv37jp8+LCWLFkiSerbt69iYmL07bff/ut1AwAAAAAAAAByD49GpOeUYcOG6eeff9bq1aszXG+MUXh4uAYNGqRnn31W0qXR56GhoRo3bpz69eunhIQElShRQnPmzNF9990nSTpy5IgiIiL0/fffq02bNtq5c6ciIyO1fv16NWjQQJK0fv16NWrUSLt27VLlypU96i8j0gEAAADg35FfR/nllbryY00SI4LzSl35sSaJ6y+v1JUfa5IYkZ5tI9KvdPjwYX3zzTc6ePCgUlJSnNZNmjTpWnaZoW+++UZt2rTRvffeq1WrVummm25S//791adPH0mXRsrHxcWpdevW1jZ+fn6Kjo7W2rVr1a9fP23ZskWpqalObcLDwxUVFaW1a9eqTZs2Wrdunex2uxWiS1LDhg1lt9u1du3aTIP05ORkJScnWz8nJiZmW+0AAAAAAAAAgNwhy0H68uXL1alTJ5UrV067d+9WVFSU9u/fL2OMateuna2d++uvvzRt2jQ9/fTTeu6557Rx40YNHDhQfn5+euihhxQXFydJCg0NddouNDRUBw4ckCTFxcXJ19dXRYoUcWnj2D4uLk4hISEuxw8JCbHaZGTs2LEaPXr0ddUIAAAAAAAAAMjdCmR1g+HDh2vw4MHavn27/P399eWXX+rQoUOKjo7Wvffem62dS09PV+3atTVmzBjdcsst6tevn/r06aNp06Y5tbNd8XcSxhiXZVe6sk1G7a+2n+HDhyshIcF6HTp0yJOyAAAAAAAAAAB5SJaD9J07d6pHjx6SJG9vbyUlJalQoUJ66aWXNG7cuGztXMmSJRUZGem0rGrVqjp48KAkKSwsTJJcRo0fP37cGqUeFhamlJQUxcfHu21z7Ngxl+OfOHHCZbT75fz8/BQcHOz0AgAAAAAAAADkL1kO0gMDA615wcPDw/Xnn39a606ePJl9PZPUpEkT7d6922nZnj17VKZMGUlSuXLlFBYWpmXLllnrU1JStGrVKjVu3FiSVKdOHfn4+Di1OXr0qLZv3261adSokRISErRx40arzYYNG5SQkGC1AQAAAAAAAAD8N2V5jvSGDRvq559/VmRkpNq3b6/Bgwfrt99+01dffaWGDRtma+eeeuopNW7cWGPGjFHXrl21ceNGvffee3rvvfckXZqOZdCgQRozZowqVaqkSpUqacyYMSpYsKC6d+8uSbLb7XrkkUc0ePBgFStWTEWLFtWQIUNUvXp1tWrVStKlUe5t27ZVnz59NH36dElS37591aFDh0wfNAoAAAAAAAAA+G/IcpA+adIknTt3TpI0atQonTt3Tp9++qkqVqyoN954I1s7V69ePS1YsEDDhw/XSy+9pHLlymny5Ml64IEHrDZDhw5VUlKS+vfvr/j4eDVo0EBLly5VUFCQ1eaNN96Qt7e3unbtqqSkJLVs2VKzZs2Sl5eX1Wbu3LkaOHCgWrduLUnq1KmTpkyZkq31AAAAAAAAAADyHpsxxuR0J/KLxMRE2e12JSQkMF86AAAAANxANltO98BzWfmtO6/UlR9rkjyvKz/WJOWduvJjTRLXX16pKz/WJGWtrvwkK3luludIL1++vE6dOuWy/MyZMypfvnxWdwcAAAAAAAAAQK6W5SB9//79SktLc1menJysv//+O1s6BQAAAAAAAABAbuHxHOnffPON9d8//PCD7Ha79XNaWpqWL1+usmXLZmvnAAAAAAAAAADIaR4H6Z07d5Yk2Ww29ejRw2mdj4+PypYtq4kTJ2Zr5wAAAAAAAAAAyGkeB+np6emSpHLlymnTpk0qXrz4DesUAAAAAAAAAAC5hcdBusO+fftuRD8AAAAAAAAAAMiVsvywUUlatWqVOnbsqIoVK6pSpUrq1KmTVq9end19AwAAAAAAAAAgx2U5SP/444/VqlUrFSxYUAMHDtSAAQMUEBCgli1bat68eTeijwAAAAAAAAAA5BibMcZkZYOqVauqb9++euqpp5yWT5o0Se+//7527tyZrR3MSxITE2W325WQkKDg4OCc7g4AAAAA5Fs2W073wHNZ+a07r9SVH2uSPK8rP9Yk5Z268mNNEtdfXqkrP9YkZa2u/CQreW6WR6T/9ddf6tixo8vyTp06MX86AAAAAAAAACDfyXKQHhERoeXLl7ssX758uSIiIrKlUwAAAAAAAAAA5Bbenjbs1auX3nzzTQ0ePFgDBw5UbGysGjduLJvNpjVr1mjWrFl68803b2RfAQAAAAAAAAD413k8R7qXl5eOHj2qkJAQLViwQBMnTrTmQ69ataqeeeYZ3XnnnTe0s7kdc6QDAAAAwL8jv847m1fqyo81ScxRnVfqyo81SVx/eaWu/FiTxBzpnuS5Ho9Ivzxvv+uuu3TXXXddew8BAAAAAAAAAMgjsjRHui0vfY0CAAAAAAAAAEA28HhEuiTdfPPNVw3TT58+fV0dAgAAAAAAAAAgN8lSkD569GjZ7fYb1RcAAAAAAAAAAHKdLAXp3bp1U0hIyI3qCwAAAAAAAAAAuY7Hc6QzPzoAAAAAAAAA4L/I4yDdGHMj+wEAAAAAAAAAQK7k8dQu6enpN7IfAAAAAAAAAADkSh6PSAcAAAAAAAAA4L+IIB0AAAAAAAAAADcI0gEAAAAAAAAAcIMgHQAAAAAAAAAANwjSAQAAAAAAAABwgyAdAAAAAAAAAAA3CNIBAAAAAAAAAHCDIB0AAAAAAAAAADcI0gEAAAAAAAAAcIMgHQAAAAAAAAAANwjSAQAAAAAAAABwgyAdAAAAAAAAAAA3CNIBAAAAAAAAAHCDIB0AAAAAAAAAADcI0gEAAAAAAAAAcIMgHQAAAAAAAAAANwjSAQAAAAAAAABwgyAdAAAAAAAAAAA3CNIBAAAAAAAAAHAjTwXpY8eOlc1m06BBg6xlxhiNGjVK4eHhCggIUPPmzbVjxw6n7ZKTk/XEE0+oePHiCgwMVKdOnXT48GGnNvHx8YqJiZHdbpfdbldMTIzOnDnzL1QFAAAAAAAAAMjN8kyQvmnTJr333nuqUaOG0/Lx48dr0qRJmjJlijZt2qSwsDDdfvvtOnv2rNVm0KBBWrBggebPn681a9bo3Llz6tChg9LS0qw23bt3V2xsrJYsWaIlS5YoNjZWMTEx/1p9AAAAAAAAAIDcKU8E6efOndMDDzyg999/X0WKFLGWG2M0efJkjRgxQl26dFFUVJRmz56tCxcuaN68eZKkhIQEffDBB5o4caJatWqlW265RR9//LF+++03/fjjj5KknTt3asmSJZoxY4YaNWqkRo0a6f3339eiRYu0e/fuHKkZAAAAAAAAAJA75Ikg/fHHH1f79u3VqlUrp+X79u1TXFycWrdubS3z8/NTdHS01q5dK0nasmWLUlNTndqEh4crKirKarNu3TrZ7XY1aNDAatOwYUPZ7XarTUaSk5OVmJjo9AIAAAAAAAAA5C/eOd2Bq5k/f762bt2qTZs2uayLi4uTJIWGhjotDw0N1YEDB6w2vr6+TiPZHW0c28fFxSkkJMRl/yEhIVabjIwdO1ajR4/OWkEAAAAAAAAAgDwlV49IP3TokJ588kl9/PHH8vf3z7SdzWZz+tkY47LsSle2yaj91fYzfPhwJSQkWK9Dhw65PSYAAAAAAAAAIO/J1UH6li1bdPz4cdWpU0fe3t7y9vbWqlWr9NZbb8nb29saiX7lqPHjx49b68LCwpSSkqL4+Hi3bY4dO+Zy/BMnTriMdr+cn5+fgoODnV4AAAAAAAAAgPwlVwfpLVu21G+//abY2FjrVbduXT3wwAOKjY1V+fLlFRYWpmXLllnbpKSkaNWqVWrcuLEkqU6dOvLx8XFqc/ToUW3fvt1q06hRIyUkJGjjxo1Wmw0bNighIcFqAwAAAAAAAAD4b8rVc6QHBQUpKirKaVlgYKCKFStmLR80aJDGjBmjSpUqqVKlShozZowKFiyo7t27S5LsdrseeeQRDR48WMWKFVPRokU1ZMgQVa9e3Xp4adWqVdW2bVv16dNH06dPlyT17dtXHTp0UOXKlf/FigEAAAAAAAAAuU2uDtI9MXToUCUlJal///6Kj49XgwYNtHTpUgUFBVlt3njjDXl7e6tr165KSkpSy5YtNWvWLHl5eVlt5s6dq4EDB6p169aSpE6dOmnKlCn/ej0AAAAAAAAAgNzFZowxOd2J/CIxMVF2u10JCQnMlw4AAAAAN5DNltM98FxWfuvOK3Xlx5okz+vKjzVJeaeu/FiTxPWXV+rKjzVJWasrP8lKnpur50gHAAAAAAAAACCnEaQDAAAAAAAAAOAGQToAAAAAAAAAAG4QpAMAAAAAAAAA4AZBOgAAAAAAAAAAbhCkAwAAAAAAAADgBkE6AAAAAAAAAABuEKQDAAAAAAAAAOAGQToAAAAAAAAAAG4QpAMAAAAAAAAA4AZBOgAAAAAAAAAAbhCkAwAAAAAAAADgBkE6AAAAAAAAAABuEKQDAAAAAAAAAOAGQToAAAAAAAAAAG4QpAMAAAAAAAAA4AZBOgAAAAAAAAAAbhCkAwAAAAAAAADgBkE6AAAAAAAAAABuEKQDAAAAAAAAAOAGQToAAAAAAAAAAG4QpAMAAAAAAAAA4AZBOgAAAAAAAAAAbhCkAwAAAAAAAADgBkE6AAAAAAAAAABuEKQDAAAAAAAAAOAGQToAAAAAAAAAAG4QpAMAAAAAAAAA4AZBOgAAAAAAAAAAbhCkAwAAAAAAAADgBkE6AAAAAAAAAABuEKQDAAAAAAAAAOAGQToAAAAAAAAAAG4QpAMAAAAAAAAA4AZBOgAAAAAAAAAAbhCkAwAAAAAAAADgBkE6AAAAAAAAAABuEKQDAAAAAAAAAOAGQToAAAAAAAAAAG4QpAMAAAAAAAAA4EauDtLHjh2revXqKSgoSCEhIercubN2797t1MYYo1GjRik8PFwBAQFq3ry5duzY4dQmOTlZTzzxhIoXL67AwEB16tRJhw8fdmoTHx+vmJgY2e122e12xcTE6MyZMze6RAAAAAAAAABALperg/RVq1bp8ccf1/r167Vs2TJdvHhRrVu31vnz560248eP16RJkzRlyhRt2rRJYWFhuv3223X27FmrzaBBg7RgwQLNnz9fa9as0blz59ShQwelpaVZbbp3767Y2FgtWbJES5YsUWxsrGJiYv7VegEAAAAAAAAAuY/NGGNyuhOeOnHihEJCQrRq1So1a9ZMxhiFh4dr0KBBevbZZyVdGn0eGhqqcePGqV+/fkpISFCJEiU0Z84c3XfffZKkI0eOKCIiQt9//73atGmjnTt3KjIyUuvXr1eDBg0kSevXr1ejRo20a9cuVa5c2aP+JSYmym63KyEhQcHBwTfmJAAAAAAAZLPldA88l5XfuvNKXfmxJsnzuvJjTVLeqSs/1iRx/eWVuvJjTVLW6spPspLn5uoR6VdKSEiQJBUtWlSStG/fPsXFxal169ZWGz8/P0VHR2vt2rWSpC1btig1NdWpTXh4uKKioqw269atk91ut0J0SWrYsKHsdrvVJiPJyclKTEx0egEAAAAAAAAA8pc8E6QbY/T000+radOmioqKkiTFxcVJkkJDQ53ahoaGWuvi4uLk6+urIkWKuG0TEhLicsyQkBCrTUbGjh1rzalut9sVERFx7QUCAAAAAAAAAHKlPBOkDxgwQL/++qs++eQTl3W2K/5OwhjjsuxKV7bJqP3V9jN8+HAlJCRYr0OHDl2tDAAAAAAAAABAHpMngvQnnnhC33zzjVasWKFSpUpZy8PCwiTJZdT48ePHrVHqYWFhSklJUXx8vNs2x44dcznuiRMnXEa7X87Pz0/BwcFOLwAAAAAAAABA/pKrg3RjjAYMGKCvvvpKP/30k8qVK+e0vly5cgoLC9OyZcusZSkpKVq1apUaN24sSapTp458fHyc2hw9elTbt2+32jRq1EgJCQnauHGj1WbDhg1KSEiw2gAAAAAAAAAA/pu8c7oD7jz++OOaN2+evv76awUFBVkjz+12uwICAmSz2TRo0CCNGTNGlSpVUqVKlTRmzBgVLFhQ3bt3t9o+8sgjGjx4sIoVK6aiRYtqyJAhql69ulq1aiVJqlq1qtq2bas+ffpo+vTpkqS+ffuqQ4cOqly5cs4UDwAAAAAAAADIFXJ1kD5t2jRJUvPmzZ2Wz5w5Uz179pQkDR06VElJSerfv7/i4+PVoEEDLV26VEFBQVb7N954Q97e3uratauSkpLUsmVLzZo1S15eXlabuXPnauDAgWrdurUkqVOnTpoyZcqNLRAAAAAAAAAAkOvZjDEmpzuRXyQmJsputyshIYH50gEAAADgBrLZcroHnsvKb915pa78WJPkeV35sSYp79SVH2uSuP7ySl35sSYpa3XlJ1nJc3P1HOkAAAAAAAAAAOQ0gnQAAAAAAAAAANwgSAcAAAAAAAAAwA2CdAAAAAAAAAAA3CBIBwAAAAAAAADADYJ0AAAAAAAAAADcIEgHAAAAAAAAAMANgnQAAAAAAAAAANwgSAcAAAAAAAAAwA2CdAAAAAAAAAAA3CBIBwAAAAAAAADADYJ0AAAAAAAAAADcIEgHAAAAAAAAAMANgnQAAAAAAAAAANzwzukOAAAA4NrZbDndA88Zk9M9AAAAAIBrQ5AOALkU4RgA5C955b7OPR0AAABwRZAO/AfxizwAAAAAAADgOYJ0ZJu8Es5KBLQAcDX59Z6eV+r6r/87lVfeJ4n3CgAAAPivIEgH3OAX+byD9wo5iesPAPIP7ukAAADICEE6AOBflVcCCsIJALi6vHJPl7ivAwAA4PoUyOkOAAAAAAAAAACQmxGkAwAAAAAAAP+PvTsPi7L6/z/+GtlBHQVlS8QNcV/ST4qWS+7llpWmRZpmi1uYZpmVS6mpuWSmpplrpfUxzaxwSy0/7hppZmqlaSm5IbiCwvn90Y/5NoIDKOMAPR/XNdfFnPvMOe/33PcM97y5OQMADlBIBwAAAAAAAADAAQrpAAAAAAAAAAA4QCEdAAAAAAAAAAAHKKQDAAAAAAAAAOAAhXQAAAAAAAAAABygkA4AAAAAAAAAgAMU0gEAAAAAAAAAcIBCOgAAAAAAAAAADlBIBwAAAAAAAADAAQrpAAAAAAAAAAA4QCEdAAAAAAAAAAAHKKQDAAAAAAAAAOAAhXQAAAAAAAAAABygkA4AAAAAAAAAgAMU0gEAAAAAAAAAcIBCOgAAAAAAAAAADlBIBwAAAAAAAADAAQrpAAAAAAAAAAA4QCH9OtOnT1fZsmXl7e2tOnXq6LvvvnN1SAAAAAAAAAAAF6KQ/g9LlixRTEyMhg0bpu+//1733HOP2rRpo6NHj7o6NAAAAAAAAACAi1BI/4dJkyapV69eevLJJ1W5cmVNmTJFYWFhmjFjhqtDAwAAAAAAAAC4iLurA8grUlJStGvXLr300kt27S1bttTmzZszfUxycrKSk5Nt9xMTEyVJSUlJzgsUuaIg7iJyyj8KYl7klH8UxLzIKf8oiHmRU/5REPMqiDkVVAVxXxXEnKSCmRc55R8FMS9yyj8Kal5ZSa/jGmOy7Esh/f87ffq0UlNTFRQUZNceFBSk+Pj4TB8zduxYjRw5MkN7WFiYU2JE7rFaXR1B7iOn/KMg5kVO+UdBzIuc8o+CmBc55R8FMa+CmFNBVRD3VUHMSSqYeZFT/lEQ8yKn/KOg5pVd58+flzWLJ4FC+nUsFovdfWNMhrZ0Q4cO1fPPP2+7n5aWprNnzyogIOCGj0H2JSUlKSwsTMeOHVPRokVdHU6uKYh5kVP+URDzIqf8oyDmRU75R0HMi5zyj4KaV0FUEPcVOeUfBTEvcso/CmJe5ITsMMbo/PnzCg0NzbIvhfT/r0SJEnJzc8tw9fnJkyczXKWezsvLS15eXnZtxYoVc1aI/1pFixYtkG8OBTEvcso/CmJe5JR/FMS8yCn/KIh5kVP+UVDzKogK4r4ip/yjIOZFTvlHQcyLnJCVrK5ET8eXjf5/np6eqlOnjtasWWPXvmbNGjVo0MBFUQEAAAAAAAAAXI0r0v/h+eefV3R0tOrWrauoqCjNmjVLR48e1TPPPOPq0AAAAAAAAAAALkIh/R+6dOmiM2fOaNSoUTpx4oSqVaumr776SuHh4a4O7V/Jy8tLw4cPz7B8Tn5XEPMip/yjIOZFTvlHQcyLnPKPgpgXOeUfBTWvgqgg7ityyj8KYl7klH8UxLzICbnNYowxrg4CAAAAAAAAAIC8ijXSAQAAAAAAAABwgEI6AAAAAAAAAAAOUEgHAAAAAAAAAMABCukAAAAAAAAAADhAIR151vTp01W2bFl5e3urTp06+u6771wd0i359ttv1a5dO4WGhspisWj58uWuDumWjR07Vv/5z39UpEgRBQYGqmPHjjpw4ICrw7olM2bMUI0aNVS0aFEVLVpUUVFR+vrrr10dVq4aO3asLBaLYmJiXB3KLRkxYoQsFovdLTg42NVh3bI///xTjz32mAICAuTr66tatWpp165drg7rlpQpUybDvrJYLOrbt6+rQ7tp165d0yuvvKKyZcvKx8dH5cqV06hRo5SWlubq0G7J+fPnFRMTo/DwcPn4+KhBgwbasWOHq8PKkax+3xpjNGLECIWGhsrHx0dNmjTRvn37XBNsNmWV02effaZWrVqpRIkSslgsiouLc0mcOeEop6tXr+rFF19U9erV5efnp9DQUD3++OM6fvy46wLOpqz21YgRI1SpUiX5+fmpePHiat68ubZt2+aaYP/FstpPPXr0yPA7q379+q4JNgey83lj//79at++vaxWq4oUKaL69evr6NGjtz/YbMoqp8zOLywWiyZMmOCagLMhq5wuXLigfv36qVSpUvLx8VHlypU1Y8YM1wSbA1nl9ddff6lHjx4KDQ2Vr6+vWrdurUOHDrkm2GzIzmfd/HhOkZ288tt5RVY55cfziuzsJ84pXINCOvKkJUuWKCYmRsOGDdP333+ve+65R23atMnTJ3lZuXjxomrWrKlp06a5OpRcs3HjRvXt21dbt27VmjVrdO3aNbVs2VIXL150dWg3rVSpUnrzzTe1c+dO7dy5U/fee686dOiQ50+IsmvHjh2aNWuWatSo4epQckXVqlV14sQJ223v3r2uDumWJCQkqGHDhvLw8NDXX3+tn376SRMnTlSxYsVcHdot2bFjh91+WrNmjSTp4YcfdnFkN2/cuHGaOXOmpk2bpv3792v8+PGaMGGC3nnnHVeHdkuefPJJrVmzRgsXLtTevXvVsmVLNW/eXH/++aerQ8u2rH7fjh8/XpMmTdK0adO0Y8cOBQcHq0WLFjp//vxtjjT7ssrp4sWLatiwod58883bHNnNc5TTpUuXtHv3br366qvavXu3PvvsMx08eFDt27d3QaQ5k9W+qlixoqZNm6a9e/dq06ZNKlOmjFq2bKlTp07d5kj/3bJzXt66dWu7311fffXVbYzw5mSV16+//qq7775blSpV0oYNG/TDDz/o1Vdflbe3922ONPuyyumf++jEiRP64IMPZLFY9OCDD97mSLMvq5wGDhyo2NhYLVq0SPv379fAgQPVv39/ff7557c50pxxlJcxRh07dtRvv/2mzz//XN9//73Cw8PVvHnzPPvZMTufdfPjOUV28spv5xVZ5ZQfzyuys584p3ARA+RBd911l3nmmWfs2ipVqmReeuklF0WUuySZZcuWuTqMXHfy5EkjyWzcuNHVoeSq4sWLm/fff9/VYdyy8+fPm4iICLNmzRrTuHFj89xzz7k6pFsyfPhwU7NmTVeHkatefPFFc/fdd7s6DKd77rnnTPny5U1aWpqrQ7lp999/v+nZs6ddW6dOncxjjz3moohu3aVLl4ybm5tZuXKlXXvNmjXNsGHDXBTVrbn+921aWpoJDg42b775pq3typUrxmq1mpkzZ7ogwpxzdA5x+PBhI8l8//33tzWmW5Wd86Lt27cbSeb333+/PUHlguzklZiYaCSZtWvX3p6gkEFm+6l79+6mQ4cOLoknt2SWV5cuXfL176nsvKY6dOhg7r333tsTUC7ILKeqVauaUaNG2bXdeeed5pVXXrmNkd2a6/M6cOCAkWR+/PFHW9u1a9eMv7+/mT17tgsizLnrP+sWhHMKYxx/hs+v5xXZqUvkt/OK7OTEOcXtwRXpyHNSUlK0a9cutWzZ0q69ZcuW2rx5s4uiQnYkJiZKkvz9/V0cSe5ITU3V4sWLdfHiRUVFRbk6nFvWt29f3X///WrevLmrQ8k1hw4dUmhoqMqWLatHHnlEv/32m6tDuiUrVqxQ3bp19fDDDyswMFC1a9fW7NmzXR1WrkpJSdGiRYvUs2dPWSwWV4dz0+6++26tW7dOBw8elCT98MMP2rRpk+677z4XR3bzrl27ptTU1AxXJvr4+GjTpk0uiip3HT58WPHx8XbnGF5eXmrcuDHnGHlcYmKiLBZLvv8PnX9KSUnRrFmzZLVaVbNmTVeHg+ts2LBBgYGBqlixonr37q2TJ0+6OqRbkpaWpi+//FIVK1ZUq1atFBgYqHr16hWI5SbT/fXXX/ryyy/Vq1cvV4dyS+6++26tWLFCf/75p4wxWr9+vQ4ePKhWrVq5OrSblpycLEl25xhubm7y9PTMN+cY13/WLSjnFAXtM7yUvZzy23lFVjlxTnH7UEhHnnP69GmlpqYqKCjIrj0oKEjx8fEuigpZMcbo+eef1913361q1aq5OpxbsnfvXhUuXFheXl565plntGzZMlWpUsXVYd2SxYsXa/fu3Ro7dqyrQ8k19erV04IFC7Rq1SrNnj1b8fHxatCggc6cOePq0G7ab7/9phkzZigiIkKrVq3SM888owEDBmjBggWuDi3XLF++XOfOnVOPHj1cHcotefHFF9W1a1dVqlRJHh4eql27tmJiYtS1a1dXh3bTihQpoqioKL3++us6fvy4UlNTtWjRIm3btk0nTpxwdXi5Iv08gnOM/OXKlSt66aWX1K1bNxUtWtTV4dyylStXqnDhwvL29tbkyZO1Zs0alShRwtVh4R/atGmjDz/8UN98840mTpyoHTt26N5777UVA/OjkydP6sKFC3rzzTfVunVrrV69Wg888IA6deqkjRs3ujq8XDF//nwVKVJEnTp1cnUot2Tq1KmqUqWKSpUqJU9PT7Vu3VrTp0/X3Xff7erQblqlSpUUHh6uoUOHKiEhQSkpKXrzzTcVHx+fL84xMvusWxDOKQrSZ/h02ckpv51XOMqJc4rbz93VAQA3cv2VisaYfH31YkHXr18/7dmzJ99cUeBIZGSk4uLidO7cOS1dulTdu3fXxo0b820x/dixY3ruuee0evXqPL0GZk61adPG9nP16tUVFRWl8uXLa/78+Xr++eddGNnNS0tLU926dTVmzBhJUu3atbVv3z7NmDFDjz/+uIujyx1z5sxRmzZtFBoa6upQbsmSJUu0aNEiffTRR6patari4uIUExOj0NBQde/e3dXh3bSFCxeqZ8+euuOOO+Tm5qY777xT3bp10+7du10dWq7iHCP/uHr1qh555BGlpaVp+vTprg4nVzRt2lRxcXE6ffq0Zs+erc6dO2vbtm0KDAx0dWj4/7p06WL7uVq1aqpbt67Cw8P15Zdf5tsibfqXYXfo0EEDBw6UJNWqVUubN2/WzJkz1bhxY1eGlys++OADPfroo/n+fHfq1KnaunWrVqxYofDwcH377bfq06ePQkJC8u1/lnp4eGjp0qXq1auX/P395ebmpubNm9udz+dljj7r5udzioL0GT5dVjnlx/MKRzlxTnH7cUU68pwSJUrIzc0tw19xT548meGvvcgb+vfvrxUrVmj9+vUqVaqUq8O5ZZ6enqpQoYLq1q2rsWPHqmbNmnr77bddHdZN27Vrl06ePKk6derI3d1d7u7u2rhxo6ZOnSp3d3elpqa6OsRc4efnp+rVq+vQoUOuDuWmhYSEZPiDTeXKlfP1Fy3/0++//661a9fqySefdHUot+yFF17QSy+9pEceeUTVq1dXdHS0Bg4cmO//66N8+fLauHGjLly4oGPHjmn79u26evWqypYt6+rQckVwcLAkcY6RT1y9elWdO3fW4cOHtWbNmnxx1Vh2+Pn5qUKFCqpfv77mzJkjd3d3zZkzx9VhwYGQkBCFh4fn63OMEiVKyN3dvcCeZ3z33Xc6cOBAvj/HuHz5sl5++WVNmjRJ7dq1U40aNdSvXz916dJFb731lqvDuyV16tSxXax04sQJxcbG6syZM3n+HONGn3Xz+zlFQfsML2WdU348r8gqJ84pbj8K6chzPD09VadOHa1Zs8aufc2aNWrQoIGLokJmjDHq16+fPvvsM33zzTd5/iToZhlj8vW/8jZr1kx79+5VXFyc7Va3bl09+uijiouLk5ubm6tDzBXJycnav3+/QkJCXB3KTWvYsKEOHDhg13bw4EGFh4e7KKLcNXfuXAUGBur+++93dSi37NKlSypUyP40ys3NzXbFX37n5+enkJAQJSQkaNWqVerQoYOrQ8oVZcuWVXBwsN05RkpKijZu3Mg5Rh6T/mH30KFDWrt2rQICAlwdktPk9/OMf4MzZ87o2LFj+focw9PTU//5z38K7HnGnDlzVKdOnXy/NvDVq1d19erVAn2OYbVaVbJkSR06dEg7d+7Ms+cYWX3Wza/nFAXxM3x2cspv5xU3u584p3A+lnZBnvT8888rOjpadevWVVRUlGbNmqWjR4/qmWeecXVoN+3ChQv65ZdfbPcPHz6suLg4+fv7q3Tp0i6M7Ob17dtXH330kT7//HMVKVLE9td4q9UqHx8fF0d3c15++WW1adNGYWFhOn/+vBYvXqwNGzYoNjbW1aHdtCJFimRYS83Pz08BAQH5ei28wYMHq127dipdurROnjypN954Q0lJSfl6WY2BAweqQYMGGjNmjDp37qzt27dr1qxZmjVrlqtDu2VpaWmaO3euunfvLnf3/H/60a5dO40ePVqlS5dW1apV9f3332vSpEnq2bOnq0O7JatWrZIxRpGRkfrll1/0wgsvKDIyUk888YSrQ8u2rH7fxsTEaMyYMYqIiFBERITGjBkjX19fdevWzYVRO5ZVTmfPntXRo0d1/PhxSbIVyoKDg21XzOU1jnIKDQ3VQw89pN27d2vlypVKTU21nWP4+/vL09PTVWFnyVFeAQEBGj16tNq3b6+QkBCdOXNG06dP1x9//KGHH37YhVH/+zjaT/7+/hoxYoQefPBBhYSE6MiRI3r55ZdVokQJPfDAAy6MOmtZvVe88MIL6tKlixo1aqSmTZsqNjZWX3zxhTZs2OC6oLOQnc9QSUlJ+vTTTzVx4kRXhZkjWeXUuHFjvfDCC/Lx8VF4eLg2btyoBQsWaNKkSS6MOmtZ5fXpp5+qZMmSKl26tPbu3avnnntOHTt2tPuyzrwkq8+6FoslX55TZOczfH47r8gqp2vXruW784qscrp48SLnFK5igDzq3XffNeHh4cbT09PceeedZuPGja4O6ZasX7/eSMpw6969u6tDu2mZ5SPJzJ0719Wh3bSePXvajruSJUuaZs2amdWrV7s6rFzXuHFj89xzz7k6jFvSpUsXExISYjw8PExoaKjp1KmT2bdvn6vDumVffPGFqVatmvHy8jKVKlUys2bNcnVIuWLVqlVGkjlw4ICrQ8kVSUlJ5rnnnjOlS5c23t7eply5cmbYsGEmOTnZ1aHdkiVLlphy5coZT09PExwcbPr27WvOnTvn6rByJKvft2lpaWb48OEmODjYeHl5mUaNGpm9e/e6NugsZJXT3LlzM90+fPhwl8btiKOcDh8+fMNzjPXr17s6dIcc5XX58mXzwAMPmNDQUOPp6WlCQkJM+/btzfbt210d9r+Oo/106dIl07JlS1OyZEnj4eFhSpcubbp3726OHj3q6rCzlJ3PG3PmzDEVKlQw3t7epmbNmmb58uWuCzgbspPTe++9Z3x8fPLN76uscjpx4oTp0aOHCQ0NNd7e3iYyMtJMnDjRpKWluTbwLGSV19tvv21KlSple1298sorefq8KTufdfPjOUV28spv5xVZ5ZQfzyuyyolzCtexGGOMgzo7AAAAAAAAAAD/aqyRDgAAAAAAAACAAxTSAQAAAAAAAABwgEI6AAAAAAAAAAAOUEgHAAAAAAAAAMABCukAAAAAAAAAADhAIR0AAAAAAAAAAAcopAMAAAAAAAAA4ACFdAAAAAAAAAAAHKCQDgAAAAAAAACAAxTSAQAAgAKqR48e6tixY4b2DRs2yGKx6Ny5c7c9JgAAACA/opAOAAAAINddvXrV1SEAAAAAuYZCOgAAAPAvt3TpUlWtWlVeXl4qU6aMJk6caLfdYrFo+fLldm3FihXTvHnzJElHjhyRxWLRJ598oiZNmsjb21uLFi3S77//rnbt2ql48eLy8/NT1apV9dVXX92mrAAAAIDc4+7qAAAAAAC4zq5du9S5c2eNGDFCXbp00ebNm9WnTx8FBASoR48eORrrxRdf1MSJEzV37lx5eXnpqaeeUkpKir799lv5+fnpp59+UuHChZ2TCAAAAOBEFNIBAACAAmzlypUZitepqam2nydNmqRmzZrp1VdflSRVrFhRP/30kyZMmJDjQnpMTIw6depku3/06FE9+OCDql69uiSpXLlyN5kFAAAA4Fos7QIAAAAUYE2bNlVcXJzd7f3337dt379/vxo2bGj3mIYNG+rQoUN2BffsqFu3rt39AQMG6I033lDDhg01fPhw7dmz5+YTAQAAAFyIQjoAAABQgPn5+alChQp2tzvuuMO23Rgji8Vi9xhjjN19i8WSoS2zLxP18/Ozu//kk0/qt99+U3R0tPbu3au6devqnXfeudWUAAAAgNuOQjoAAADwL1alShVt2rTJrm3z5s2qWLGi3NzcJEklS5bUiRMnbNsPHTqkS5cuZWv8sLAwPfPMM/rss880aNAgzZ49O/eCBwAAAG4T1kgHAAAA/sUGDRqk//znP3r99dfVpUsXbdmyRdOmTdP06dNtfe69915NmzZN9evXV1paml588UV5eHhkOXZMTIzatGmjihUrKiEhQd98840qV67szHQAAAAAp+CKdAAAAOBf7M4779Qnn3yixYsXq1q1anrttdc0atQouy8anThxosLCwtSoUSN169ZNgwcPlq+vb5Zjp6amqm/fvqpcubJat26tyMhIuwI9AAAAkF9YzPWLHQIAAAAAAAAAABuuSAcAAAAAAAAAwAEK6QAAAAAAAAAAOEAhHQAAAAAAAAAAByikAwAAAAAAAADgAIV0AAAAAAAAAAAcoJAOAAAAAAAAAIADFNIBAAAAAAAAAHCAQjoAAAAAAAAAAA5QSAcAAAAAAAAAwAEK6QAAAAAAAAAAOEAhHQAAAAAAAAAAByikAwAAAAAAAADgAIV0AAAAAAAAAAAcoJAOAAAAAAAAAIADFNIBAAAAAAAAAHCAQjoAAAAAAAAAAA5QSAcAAAAAAAAAwAEK6QAA5GMWiyVbtw0bNmQ51pgxY7R8+fJbjmfEiBHZ7n/69Gl5eXnJYrFo586dTp3LkW3btumBBx5Q6dKl5eXlpaCgIEVFRWnQoEG5Mr6zfffdd+rcubPuuOMOeXp6ymq1qkGDBpoxY4YuXrzo6vCcrkmTJmrSpImrw7gpX3zxhdq1a6egoCB5enrK399fzZo104cffqirV686bd7NmzdrxIgROnfuXK6PfeTIEVksFs2bNy/Xx86JDRs2OHxfdHV8Wckrz2NWbvZY2rRpk7p27Wp73/Xz81PVqlU1aNAg/fzzz84JNo+wWCzq16+fU+dIP37eeuutTLe/9dZbslgsOnLkiFPjAACgIHF3dQAAAODmbdmyxe7+66+/rvXr1+ubb76xa69SpUqWY40ZM0YPPfSQOnbsmJshOrRw4UKlpKRIkubMmaO6devetrnTffnll2rfvr2aNGmi8ePHKyQkRCdOnNDOnTu1ePFiTZw48bbHlBPDhw/XqFGj1KBBA73++usqX768Ll26ZCtuHTx4UJMnT3Z1mE41ffp0V4eQY8YY9ezZU/PmzdN9992nSZMmKSwsTImJiVq/fr369Omj06dP67nnnnPK/Js3b9bIkSPVo0cPFStWzClz5BVjxoxR06ZNM7SXL1/eBdFkX0hIiLZs2ZLn47yZY+mVV17R6NGjFRUVpVdeeUURERG6du2a9uzZo/nz52vSpEm6du2a3NzcnBs8AABADlBIBwAgH6tfv77d/ZIlS6pQoUIZ2vOqDz74QIGBgQoPD9fHH3+sSZMmycfH57bGMH78eJUtW1arVq2Su/v/nRo98sgjGj9+/G2NJac+/fRTjRo1Sr169dLs2bNlsVhs29q0aaMhQ4Zk+GNLQXLp0iX5+vpm6w9Fec2ECRM0b948jRw5Uq+99prdtnbt2mnIkCH65ZdfXBRdRpcvX77tr83cEhERkW/eEyUpNTVV165dk5eXV76KO7s+/vhjjR49Ws8884ymT59u977VokULPf/889n641j66x/5yz+PbwAA8huWdgEAoIA7e/as+vTpY1v2o1y5cho2bJiSk5NtfSwWiy5evKj58+fblj1IXyrj1KlT6tOnj6pUqaLChQsrMDBQ9957r7777rtbimvbtm368ccfFR0drd69eysxMVFLly7N0C8pKUm9e/dWQECAChcurNatW+vgwYMZ+p06dUpPPfWUwsLC5OXlpZIlS6phw4Zau3atwzjOnDmjEiVK2BXR0xUqlPFUacmSJYqKipKfn58KFy6sVq1a6fvvv8/Qb+fOnWrfvr38/f3l7e2t2rVr65NPPrHrM2/ePFksFq1fv17PPvusSpQooYCAAHXq1EnHjx93GLckjRo1SsWLF9fUqVPtilHpihQpopYtW9ruX7lyRUOHDlXZsmXl6empO+64Q3379s2wJEOZMmXUtm1brVy5UrVr15aPj48qV66slStX2uKuXLmy/Pz8dNddd2VYlqdHjx4qXLiw9u3bp2bNmsnPz08lS5ZUv379dOnSJbu+7777rho1aqTAwED5+fmpevXqGj9+fIZlTZo0aaJq1arp22+/VYMGDeTr66uePXvatl2/tMuMGTNUs2ZNFS5cWEWKFFGlSpX08ssv2/X58ccf1aFDBxUvXlze3t6qVauW5s+fb9cnfXmQjz/+WMOGDVNoaKiKFi2q5s2b68CBAzfYM45dvXpV48aNU6VKlfTqq69m2ic4OFh333237X52XsfS/y0ZsXDhQlWuXFm+vr6qWbOmbd9J0ogRI/TCCy9IksqWLZthCaj0/f/ZZ5+pdu3a8vb21siRI7P9nGXHqVOn5OnpmWn+P//8sywWi6ZOnSrp74Lp4MGDVbZsWXl7e8vf319169bVxx9/nON5M7Np0yZ5eHho8ODBdu3pr885c+bY2tKf3/fee08VK1aUl5eXqlSposWLF2cYNz4+Xk8//bRKlSolT09PlS1bViNHjtS1a9dsfdKX3xg/frzeeOMNlS1bVl5eXlq/fn2mS7uMGDFCFotFe/bs0cMPPyyr1Sp/f389//zzunbtmg4cOKDWrVurSJEiKlOmTKZ/DExKSrI9n+nvAzExMRmWgcqNYykzb7zxhkqUKKHJkydn+r5lsVjUt29fu6vRHb3+jx49qscee0yBgYHy8vJS5cqVNXHiRKWlpdken/46vj6uzJ7jnLx/ffrpp6pXr56sVqt8fX1Vrlw5W1zZ4eg4OnLkiNzd3TV27NgMj/v2229lsVj06aefZnuu7Prggw9Us2ZN22vtgQce0P79++363Gg5rR49eqhMmTK2+46O77S0NL3xxhuKjIyUj4+PihUrpho1aujtt9/O9ZwAAMg1BgAAFBjdu3c3fn5+tvuXL182NWrUMH5+fuatt94yq1evNq+++qpxd3c39913n63fli1bjI+Pj7nvvvvMli1bzJYtW8y+ffuMMcb8/PPP5tlnnzWLFy82GzZsMCtXrjS9evUyhQoVMuvXr7ebX5IZPnx4tmLt3bu3kWT27dtnkpKSjK+vr2nSpIldn7S0NNO0aVPj5eVlRo8ebVavXm2GDx9uypUrl2GuVq1amZIlS5pZs2aZDRs2mOXLl5vXXnvNLF682GEcTz75pJFk+vfvb7Zu3WpSUlJu2Hf06NHGYrGYnj17mpUrV5rPPvvMREVFGT8/P9vzZYwx33zzjfH09DT33HOPWbJkiYmNjTU9evQwkszcuXNt/ebOnWskmXLlypn+/fubVatWmffff98UL17cNG3a1GHcx48fN5JMly5dHPZLl5aWZlq1amXc3d3Nq6++alavXm3eeust4+fnZ2rXrm2uXLli6xseHm5KlSplqlWrZj7++GPz1VdfmXr16hkPDw/z2muvmYYNG5rPPvvMLFu2zFSsWNEEBQWZS5cu2R7fvXt34+npaUqXLm3bbyNGjDDu7u6mbdu2dnENHDjQzJgxw8TGxppvvvnGTJ482ZQoUcI88cQTdv0aN25s/P39TVhYmHnnnXfM+vXrzcaNG23bGjdubOv78ccf2/bp6tWrzdq1a83MmTPNgAEDbH1+/vlnU6RIEVO+fHmzYMEC8+WXX5quXbsaSWbcuHG2fuvXrzeSTJkyZcyjjz5qvvzyS/Pxxx+b0qVLm4iICHPt2rUMfbN6DWzevNlIMi+++GLWO85k/3VsjLHFetddd5lPPvnEfPXVV6ZJkybG3d3d/Prrr8YYY44dO2b69+9vJJnPPvvM9ppPTEw0xvy9/0NCQky5cuXMBx98YNavX2+2b9+e7efs8OHDGY71zDzwwAMmLCzMpKam2rUPGTLEeHp6mtOnTxtjjHn66aeNr6+vmTRpklm/fr1ZuXKlefPNN80777zjcPz0/bFkyRJz9erVDLd/evPNN40k8/nnnxtjjPnxxx+Nr6+veeyxxzI8v2FhYaZKlSrm448/NitWrDCtW7c2ksynn35q63fixAkTFhZmwsPDzXvvvWfWrl1rXn/9dePl5WV69OiR4bm64447TNOmTc1///tfs3r1anP48OFMn8fhw4cbSSYyMtK8/vrrZs2aNWbIkCFGkunXr5+pVKmSmTp1qlmzZo154oknjCSzdOlS2+MvXrxoatWqZUqUKGEmTZpk1q5da95++21jtVrNvffea9LS0uxyvdVj6Xp//vmnkWS6du3qcN9d70av/5MnT5o77rjDlCxZ0sycOdPExsaafv36GUnm2WeftT0+/Vi4/ndWZs9xdt+/Nm/ebCwWi3nkkUfMV199Zb755hszd+5cEx0dnWU+2T2OHnjgAVO6dGm79xljjHn44YdNaGhohuM4s9zGjRuX6fE/btw4I8kcPnzY9pgxY8bY9s+XX35pFixYYMqVK2esVqs5ePCg3f7453vuP5+78PDwDDFkdnyPHTvWuLm5meHDh5t169aZ2NhYM2XKFDNixIgsnz8AAFyFQjoAAAXI9YX0mTNnGknmk08+seuX/gF69erVtjY/Pz/TvXv3LOe4du2auXr1qmnWrJl54IEH7LZlt5B+8eJFU7RoUVO/fn272C0Wi/nll19sbV9//bWRZN5++227x48ePTrDXIULFzYxMTFZzn2906dPm7vvvttIMpKMh4eHadCggRk7dqw5f/68rd/Ro0eNu7u76d+/v93jz58/b4KDg03nzp1tbZUqVTK1a9fOUORo27atCQkJsRUO0wvpffr0ses3fvx4I8mcOHHihnFv3brVSDIvvfRStvKMjY01ksz48ePt2pcsWWIkmVmzZtnawsPDjY+Pj/njjz9sbXFxcUaSCQkJMRcvXrS1L1++3EgyK1assLV1797d4X7btGlTpjGmpqaaq1evmgULFhg3Nzdz9uxZ27bGjRsbSWbdunUZHnd9Uadfv36mWLFiDp+PRx55xHh5eZmjR4/atbdp08b4+vqac+fOGWP+rwB3fcH6k08+MZLMli1bbG0bNmwwbm5uZuTIkQ7nXrx4sZFkZs6c6bBfupy8jiWZoKAgk5SUZGuLj483hQoVMmPHjrW1TZgwIUMRLV14eLhxc3MzBw4csGvP7nOW3UL6ihUrMsR/7do1Exoaah588EFbW7Vq1UzHjh0djpWZ9H13o9uxY8dsfdPS0sx9991nihUrZn788UdTpUoVU6lSJXPhwgW7MSUZHx8fEx8fbxdzpUqVTIUKFWxtTz/9tClcuLD5/fff7R7/1ltv2f6AaMz/PVfly5fP8Ec8R4X0iRMn2vWtVauWrZid7urVq6ZkyZKmU6dOtraxY8eaQoUKmR07dtg9/r///a+RZL766iu7XG/1WLqeo/et9N8t6bd/FvVv9Pp/6aWXjCSzbds2u/Znn33WWCwW2zGc00J6dt6/0vdl+nGfE9k9jtLjXrZsma3tzz//NO7u7lm+z6TnltUtfb8lJCTY/qD+T0ePHjVeXl6mW7dutracFtIzO77btm1ratWq5TAHAADyGpZ2AQCgAPvmm2/k5+enhx56yK69R48ekqR169Zla5yZM2fqzjvvlLe3t9zd3eXh4aF169Zl+Hfv7Prkk0+UlJRk9y/wPXv2lDFGc+fOtbWtX79ekvToo4/aPb5bt24Zxrzrrrs0b948vfHGG9q6dWuGpUFuJCAgQN9995127NihN998Ux06dNDBgwc1dOhQVa9eXadPn5YkrVq1SteuXdPjjz+ua9eu2W7e3t5q3LixbcmAX375RT///LMt5n/2ve+++3TixIkMS4K0b9/e7n6NGjUkSb///nu2csiO9C+gTd/36R5++GH5+fllOBZq1aqlO+64w3a/cuXKkv7+l/5/rkuc3p5ZrDfab+n7VZK+//57tW/fXgEBAXJzc5OHh4cef/xxpaamZljCp3jx4rr33nuzzPWuu+7SuXPn1LVrV33++ee2ffhP33zzjZo1a6awsDC79h49eujSpUsZ1pbPzj5q3Lixrl27lmHN81uV09dx06ZNVaRIEdv9oKAgBQYG5uh4qlGjhipWrJghjpw8Z1lp06aNgoOD7V7zq1at0vHjx+3eG+666y59/fXXeumll7RhwwZdvnw5R/OMGzdOO3bsyHALCgqy9bFYLFqwYIGKFCmiunXr6vDhw/rkk0/k5+eXYbxmzZrZPdbNzU1dunTRL7/8oj/++EOStHLlSjVt2lShoaF27wFt2rSRJG3cuNFuzPbt28vDwyPbObVt29bufuXKlWWxWGzjS5K7u7sqVKhgt99XrlypatWqqVatWnZxtWrVKtOlT3LjWMqugIAAeXh42G7XL/WV2ev/m2++UZUqVXTXXXfZtffo0UPGmAxfvJ0TWb1//ec//5Ekde7cWZ988on+/PPPHI2fneOoSZMmqlmzpt59911bv5kzZ8piseipp57K1jzPPfdcpsf/9V9kvGXLFl2+fDnD74iwsDDde++92T5fyExmx/ddd92lH374QX369NGqVauUlJR00+MDAHC7UEgHAKAAO3PmjIKDgzOsQxsYGCh3d3edOXMmyzEmTZqkZ599VvXq1dPSpUu1detW7dixQ61bt85xQSvdnDlz5O3trdatW+vcuXM6d+6catSooTJlymjevHlKTU21xe/u7q6AgAC7xwcHB2cYc8mSJerevbvef/99RUVFyd/fX48//rji4+OzFVPdunX14osv6tNPP9Xx48c1cOBAHTlyxLbG8F9//SXp7+LJP4s9Hh4eWrJkia1Ym95v8ODBGfr16dNHkjIUdq/PL/1L2Bw9v6VLl5YkHT58OFv5pT+XJUuWtGu3WCwKDg7OcCz4+/vb3ff09HTYfuXKFbt2R/stfa6jR4/qnnvu0Z9//qm3337b9geN9KLR9fmHhIRkK9fo6Gh98MEH+v333/Xggw8qMDBQ9erV05o1a2x9zpw5k+l4oaGhdjGmu5l9dCM3s+9y8jq+Ptb0eHMSa2bPTU6fs6y4u7srOjpay5Yts63TP2/ePIWEhKhVq1a2flOnTtWLL76o5cuXq2nTpvL391fHjh116NChbM1Trlw51a1bN8Pt+sJeQECA2rdvrytXrqh169aqXr16puNl9v5z/bH9119/6YsvvsjwHlC1alVJGd8Dsntsp8vsdejr6ytvb+8M7f98bf7111/as2dPhriKFCkiY0yW701Szo+lf0r/I0xmhfgNGzZox44dmjlzZqaPvR3HZLrsvH81atRIy5cvt/2BtVSpUqpWrVq21+7PznEkSQMGDNC6det04MABXb16VbNnz9ZDDz2U6eMzU6pUqUyP/1KlStn1S5/zRs/nzT6XNxpz6NCheuutt7R161a1adNGAQEBatasWYbv3AAAIC/J+K1aAACgwAgICNC2bdtkjLErwp08eVLXrl1TiRIlshxj0aJFatKkiWbMmGHXfv78+ZuK6eDBg9q0aZOk/ysoXm/VqlW67777FBAQoGvXrunMmTN2RY3MiuMlSpTQlClTNGXKFB09elQrVqzQSy+9pJMnTyo2NjZHMXp4eGj48OGaPHmyfvzxR9v4kvTf//5X4eHhN3xser+hQ4eqU6dOmfaJjIzMUTyZCQkJUfXq1bV69WpdunTJ7irxzKQ/l6dOnbIrphtjFB8fb7u6Mrc42m/pbcuXL9fFixf12Wef2T2ncXFxmY6Z2RcT3sgTTzyhJ554QhcvXtS3336r4cOHq23btjp48KDCw8MVEBCgEydOZHhc+pe8Zue1cbPq1q0rf39/ff755xo7dmyWeeXG6zinMovJGc/ZE088oQkTJmjx4sXq0qWLVqxYoZiYGLsvmvTz89PIkSM1cuRI/fXXX7ar09u1a6eff/45x3PeyJo1azRjxgzdddddWrZsmZYuXaoHH3wwQ7/M3n+uP7ZLlCihGjVqaPTo0ZnOlV7oTZeTY/tWlChRQj4+Pvrggw9uuN2ZQkNDVbVqVa1Zs0ZXrlyxK/zXqlVLknThwoVMH3srx2T6PNd/OW9m/60iZe/9S5I6dOigDh06KDk5WVu3btXYsWPVrVs3lSlTRlFRUZmOff14mbX9c45u3brpxRdf1Lvvvqv69esrPj5effv2dTj2zUif80bP5z+PDW9vbyUmJmbod6PnM7N95+7urueff17PP/+8zp07p7Vr1+rll19Wq1atdOzYsSx/pwEA4ApckQ4AQAHWrFkzXbhwQcuXL7drX7BggW17uhtdZWixWGxX36bbs2dPjpdxSDdnzhxJ0uzZs7V+/Xq721dffSUPDw9bkadp06aSpA8//NBujI8++sjhHKVLl1a/fv3UokUL7d6922HfzIoGkmzL1qQXvFq1aiV3d3f9+uuvmV7dV7duXUl/F8kjIiL0ww8/3LDfP5dKuBWvvvqqEhISNGDAABljMmy/cOGCVq9eLen/9vWiRYvs+ixdulQXL160OxZyy432W5MmTST9X3Hln8eXMUazZ8/OtRj8/PzUpk0bDRs2TCkpKdq3b5+kv5+Pb775xlZwS7dgwQL5+vqqfv36uRbD9Tw8PPTiiy/q559/1uuvv55pn5MnT+p///ufLdbsvo6z62auqHfGc1a5cmXVq1dPc+fO1UcffaTk5GQ98cQTN+wfFBSkHj16qGvXrjpw4IAuXbqU4zkzc+LECT322GNq3LixNm/erPbt26tXr16Z/tfAunXrbP95IkmpqalasmSJypcvb7vKt23btvrxxx9Vvnz5TN8Dri+k3y5t27bVr7/+qoCAgEzjKlOmTI7HzOmxNGzYMJ0+fVrPP/98pu9bOdGsWTP99NNPGd7nFyxYIIvFYvsdkp7Xnj177PqtWLHihmNn9f71T15eXmrcuLHGjRsn6e8lq7KSneNI+rto/dRTT2n+/PmaNGmSatWqpYYNG2Y5fk5FRUXJx8cnw++IP/74w7asU7oyZcro4MGDdn+YOHPmjDZv3nxTcxcrVkwPPfSQ+vbtq7Nnz+rIkSM3NQ4AAM7GFekAABRgjz/+uN599111795dR44cUfXq1bVp0yaNGTNG9913n5o3b27rW716dW3YsEFffPGFQkJCVKRIEUVGRqpt27Z6/fXXNXz4cDVu3FgHDhzQqFGjVLZsWV27di1H8Vy7dk0LFixQ5cqV9eSTT2bap127dlqxYoVOnTqlli1bqlGjRhoyZIguXryounXr6n//+58WLlxo95jExEQ1bdpU3bp1U6VKlVSkSBHt2LFDsbGxN7wqPF2rVq1UqlQptWvXTpUqVVJaWpri4uI0ceJEFS5c2LaObJkyZTRq1CgNGzZMv/32m1q3bq3ixYvrr7/+0vbt221XzUrSe++9pzZt2qhVq1bq0aOH7rjjDp09e1b79+/X7t279emnn+boebuRhx9+WK+++qpef/11/fzzz+rVq5fKly+vS5cuadu2bXrvvffUpUsXtWzZUi1atFCrVq304osvKikpSQ0bNtSePXs0fPhw1a5dW9HR0bkSUzpPT09NnDhRFy5c0H/+8x9t3rxZb7zxhtq0aaO7775bktSiRQt5enqqa9euGjJkiK5cuaIZM2YoISHhlubu3bu3fHx81LBhQ4WEhCg+Pl5jx46V1Wq1XXk/fPhw2zrWr732mvz9/fXhhx/qyy+/1Pjx42W1WnM878aNG9WsWTO99tprWa6T/sILL2j//v0aPny4tm/frm7duiksLEyJiYn69ttvNWvWLI0cOVINGzbM0es4u9KXLXn77bfVvXt3eXh4KDIy0uEfeZzxnEl/fz/C008/rePHj6tBgwYZ/mOjXr16atu2rWrUqKHixYtr//79WrhwoaKiorJ11eqhQ4e0devWDO2lSpVSqVKllJqaqq5du8piseijjz6Sm5ub5s2bp1q1aqlLly7atGmTbQkj6e+rnO+99169+uqr8vPz0/Tp0/Xzzz9r8eLFtj6jRo3SmjVr1KBBAw0YMECRkZG6cuWKjhw5oq+++kozZ87MsLTG7RATE6OlS5eqUaNGGjhwoGrUqKG0tDQdPXpUq1ev1qBBg1SvXr0cjZnTY6lr167at2+fRo8erR9++EE9evRQRESE0tLSdOzYMdv7e3b+4Dhw4EAtWLBA999/v0aNGqXw8HB9+eWXmj59up599lnbOv/BwcFq3ry5xo4dq+LFiys8PFzr1q3TZ599lum42Xn/eu211/THH3+oWbNmKlWqlM6dO6e3335bHh4eaty4cZaxZ+c4StenTx+NHz9eu3bt0vvvv5/l2DejWLFievXVV/Xyyy/r8ccfV9euXXXmzBmNHDlS3t7eGj58uK1vdHS03nvvPT322GPq3bu3zpw5o/Hjx6to0aLZnq9du3aqVq2a6tatq5IlS+r333/XlClTFB4eroiICGekCADArXPZ15wCAIBc1717d+Pn52fXdubMGfPMM8+YkJAQ4+7ubsLDw83QoUPNlStX7PrFxcWZhg0bGl9fXyPJNG7c2BhjTHJyshk8eLC54447jLe3t7nzzjvN8uXLTffu3U14eLjdGJLM8OHDbxjf8uXLjSQzZcqUG/aJjY01kszEiRONMcacO3fO9OzZ0xQrVsz4+vqaFi1amJ9//tluritXrphnnnnG1KhRwxQtWtT4+PiYyMhIM3z4cHPx4kWHz9mSJUtMt27dTEREhClcuLDx8PAwpUuXNtHR0eann37KNIemTZuaokWLGi8vLxMeHm4eeughs3btWrt+P/zwg+ncubMJDAw0Hh4eJjg42Nx7771m5syZtj5z5841ksyOHTvsHrt+/Xojyaxfv95h7Ok2btxoHnroIRMSEmI8PDxM0aJFTVRUlJkwYYJJSkqy9bt8+bJ58cUXTXh4uPHw8DAhISHm2WefNQkJCXbjhYeHm/vvvz/DPJJM37597doOHz5sJJkJEybY2tKPwz179pgmTZoYHx8f4+/vb5599llz4cIFu8d/8cUXpmbNmsbb29vccccd5oUXXjBff/11hvwbN25sqlatmmn+jRs3th2vxhgzf/5807RpUxMUFGQ8PT1NaGio6dy5s9mzZ4/d4/bu3WvatWtnrFar8fT0NDVr1jRz586165O+Lz799NNM8/5n//S+jl4D1/v888/N/fffb0qWLGnc3d1N8eLFTdOmTc3MmTNNcnKyrV92X8eZ7SNj/t6n3bt3t2sbOnSoCQ0NNYUKFbJ7vm+0/43J3nOW2XPjSGJiovHx8TGSzOzZszNsf+mll0zdunVN8eLFjZeXlylXrpwZOHCgOX36tMNx0/fHjW7Dhg0zxhgzbNgwU6hQIbNu3Tq7x2/evNm4u7ub5557ztaW/vxOnz7dlC9f3nh4eJhKlSqZDz/8MMP8p06dMgMGDDBly5Y1Hh4ext/f39SpU8cMGzbM9jrI7PWTLrPncfjw4UaSOXXqlF3fzN77jcn8dXPhwgXzyiuvmMjISOPp6WmsVqupXr26GThwoImPj8+Q6/Vyciw58u2335ouXbqYUqVKGQ8PD+Pr62uqVKlinn32WbNz584s80j3+++/m27dupmAgADj4eFhIiMjzYQJE0xqaqpdvxMnTpiHHnrI+Pv7G6vVah577DGzc+fODM9xdt+/Vq5cadq0aWPuuOMO4+npaQIDA819991nvvvuuyxzz8lxlK5JkybG39/fXLp0KcvxjXF8bBljzIQJE4wkc/jwYbv2999/39SoUcN2bHTo0MHs27cvw+Pnz59vKleubLy9vU2VKlXMkiVLMpwXOIph4sSJpkGDBqZEiRLG09PTlC5d2vTq1cscOXIkW/kBAOAKFmNu8f/pAAAAgH/o0aOH/vvf/95wrWMgv7JYLOrbt6+mTZvm6lDgJHnx/evkyZMKDw9X//79bV+ADQAAbj+WdgEAAAAAII/5448/9Ntvv2nChAkqVKiQbakxAADgGnzZKAAAAAAAecz777+vJk2aaN++ffrwww91xx13uDokAAD+1VjaBQAAAAAAAAAAB7giHQAAAAAAAAAAByikAwAAAAAAAADgAIV0AAAAAAAAAAAccHd1AAVJWlqajh8/riJFishisbg6HAAAAAAAAADADRhjdP78eYWGhqpQIcfXnFNIz0XHjx9XWFiYq8MAAAAAAAAAAGTTsWPHVKpUKYd9KKTnoiJFikj6+4kvWrSoi6MBAAAAAAAAANxIUlKSwsLCbHVdRyik56L05VyKFi1KIR0AAAAAAAAA8oHsLNPNl40CAAAAAAAAAOAAhXQAAAAAAAAAABygkA4AAAAAAAAAgAOskX6bpaWlKSUlxdVhADni4eEhNzc3V4cBAAAAAAAAuASF9NsoJSVFhw8fVlpamqtDAXKsWLFiCg4OztaXLwAAAAAAAAAFCYX028QYoxMnTsjNzU1hYWEqVIhVdZA/GGN06dIlnTx5UpIUEhLi4ogAAAAAAACA24tC+m1y7do1Xbp0SaGhofL19XV1OECO+Pj4SJJOnjypwMBAlnkBAAAAAADAvwqXRd8mqampkiRPT08XRwLcnPQ/AF29etXFkQAAAAAAAAC3F4X024z1pZFfcewCAAAAAADg34pCOgqkDRs2yGKx6Ny5c64OBQAAAAAAAEA+RyEdWYqPj1f//v1Vrlw5eXl5KSwsTO3atdO6detydZ4mTZooJiYmV8fMyvfff68uXbooJCREXl5eCg8PV9u2bfXFF1/IGHNbYwEAAAAAAACQN/Floy5mGXl7l8sww3NWHD5y5IgaNmyoYsWKafz48apRo4auXr2qVatWqW/fvvr555+dFGnmjDFKTU2Vu/utH7qff/65OnfurObNm2v+/PkqX768zpw5oz179uiVV17RPffco2LFijk1BgAAAAAAAAB5H1ekw6E+ffrIYrFo+/bteuihh1SxYkVVrVpVzz//vLZu3Wrrd/ToUXXo0EGFCxdW0aJF1blzZ/3111+27SNGjFCtWrW0cOFClSlTRlarVY888ojOnz8vSerRo4c2btyot99+WxaLRRaLRUeOHLEt0bJq1SrVrVtXXl5e+u6775ScnKwBAwYoMDBQ3t7euvvuu7Vjx45s53Xx4kX16tVL999/v7788ku1bNlS5cuX11133aUnn3xSP/zwg6xWqyTddAzz5s3LUIhfvny53Vrj6c/Le++9p7CwMPn6+urhhx9mSRoAAAAAAAAgD6GQjhs6e/asYmNj1bdvX/n5+WXYnl4kNsaoY8eOOnv2rDZu3Kg1a9bo119/VZcuXez6//rrr1q+fLlWrlyplStXauPGjXrzzTclSW+//baioqLUu3dvnThxQidOnFBYWJjtsUOGDNHYsWO1f/9+1ahRQ0OGDNHSpUs1f/587d69WxUqVFCrVq109uzZbOW2evVqnTlzRkOGDLlhn+u/XDO3Y0j3yy+/6JNPPtEXX3yh2NhYxcXFqW/fvjkaAwAAAAAAAIDzUEjHDf3yyy8yxqhSpUoO+61du1Z79uzRRx99pDp16qhevXpauHChNm7caHeFdlpamubNm6dq1arpnnvuUXR0tG2ddavVKk9PT/n6+io4OFjBwcFyc3OzPXbUqFFq0aKFypcvL29vb82YMUMTJkxQmzZtVKVKFc2ePVs+Pj6aM2dOtnI7ePCgJCkyMtLWtmPHDhUuXNh2W7lypd1jcjuGdFeuXNH8+fNVq1YtNWrUSO+8844WL16s+Pj4HI0DAAAAACgALJbcuwEAcg2FdNxQ+pdtXn9l9vX279+vsLAwuyvIq1SpomLFimn//v22tjJlyqhIkSK2+yEhITp58mS2Yqlbt67t519//VVXr15Vw4YNbW0eHh6666677ObLqRo1aiguLk5xcXG6ePGirl27dltiKF26tEqVKmW7HxUVpbS0NB04cOAmMwEAAAAAAACQmyik44YiIiJksViyLAwbYzIttl/f7uHhYbfdYrEoLS0tW7H8c2mZGxX4bxRHZiIiIiTJrljt5eWlChUqqEKFCrkSQ6FChWz90l29ejXL2NIfn91cAAAAAAAAADhXni6kX7t2Ta+88orKli0rHx8flStXTqNGjbIrvhpjNGLECIWGhsrHx0dNmjTRvn377MZJTk5W//79VaJECfn5+al9+/b6448/7PokJCQoOjpaVqtVVqtV0dHR//ovfPT391erVq307rvv6uLFixm2pz8/VapU0dGjR3Xs2DHbtp9++kmJiYmqXLlytufz9PRUampqlv0qVKggT09Pbdq0ydZ29epV7dy5M9vztWzZUv7+/ho3bly248tpDCVLltT58+ftnru4uLgMYx09elTHjx+33d+yZYsKFSqkihUr3lRsAAAAAAAAAHJXni6kjxs3TjNnztS0adO0f/9+jR8/XhMmTNA777xj6zN+/HhNmjRJ06ZN044dOxQcHKwWLVro/Pnztj4xMTFatmyZFi9erE2bNunChQtq27atXdG2W7duiouLU2xsrO0LH6Ojo29rvnnR9OnTlZqaqrvuuktLly7VoUOHtH//fk2dOlVRUVGSpObNm6tGjRp69NFHtXv3bm3fvl2PP/64GjdubLccSlbKlCmjbdu26ciRIzp9+vQNr1b38/PTs88+qxdeeEGxsbH66aef1Lt3b126dEm9evXK1lyFCxfW+++/ry+//FL333+/Vq1apd9++0179uzR+PHjJclujfabiaFevXry9fXVyy+/rF9++UUfffSR5s2bl2Esb29vde/eXT/88IO+++47DRgwQJ07d1ZwcHC2cgEAAAAAAADgXHm6kL5lyxZ16NBB999/v8qUKaOHHnpILVu21M6dOyX9fTX6lClTNGzYMHXq1EnVqlXT/PnzdenSJX300UeSpMTERM2ZM0cTJ05U8+bNVbt2bS1atEh79+7V2rVrJf29xndsbKzef/99RUVFKSoqSrNnz9bKlSv/9etUly1bVrt371bTpk01aNAgVatWTS1atNC6des0Y8YMSX8vQbJ8+XIVL15cjRo1UvPmzVWuXDktWbIkR3MNHjxYbm5uqlKlikqWLKmjR4/esO+bb76pBx98UNHR0brzzjv1yy+/aNWqVSpevHi253vggQe0efNm+fr66vHHH1dkZKTuvfdeffPNN1q8eLHatm3r8PFZxeDv769Fixbpq6++UvXq1fXxxx9rxIgRGcapUKGCOnXqpPvuu08tW7ZUtWrVNH369GznAQAAAAAAAMC5LOb6RZzzkDfffFMzZ87U6tWrVbFiRf3www9q2bKlpkyZoq5du+q3335T+fLltXv3btWuXdv2uA4dOqhYsWKaP3++vvnmGzVr1kxnz561K7LWrFlTHTt21MiRI/XBBx/o+eefz7CUS7FixTR58mQ98cQTmcaXnJys5ORk2/2kpCSFhYUpMTFRRYsWtet75coVHT58WGXLlpW3t3cuPDsoCEaMGKHly5dnuuRLXsMxDAAAAAC3QW5+X1beLfkAQJ6QlJQkq9WaaT33eu63Kaab8uKLLyoxMVGVKlWSm5ubUlNTNXr0aHXt2lWSFB8fL0kKCgqye1xQUJB+//13Wx9PT88MVyoHBQXZHh8fH6/AwMAM8wcGBtr6ZGbs2LEaOXLkzScIAAAAAAAAAMjz8vTSLkuWLNGiRYv00Ucfaffu3Zo/f77eeustzZ8/366f5bq/1hpjMrRd7/o+mfXPapyhQ4cqMTHRdvvnl20CAAAAAAAAAAqGPF1If+GFF/TSSy/pkUceUfXq1RUdHa2BAwdq7NixkmT7Msbrrxo/efKk7Sr14OBgpaSkKCEhwWGfv/76K8P8p06dynC1+z95eXmpaNGidjcgJ0aMGJEvlnUBAAAAAAAA/s3ydCH90qVLKlTIPkQ3NzelpaVJ+vuLMIODg7VmzRrb9pSUFG3cuFENGjSQJNWpU0ceHh52fU6cOKEff/zR1icqKkqJiYnavn27rc+2bduUmJho6wMAAAAAAAAA+HfK02ukt2vXTqNHj1bp0qVVtWpVff/995o0aZJ69uwp6e/lWGJiYjRmzBhFREQoIiJCY8aMka+vr7p16yZJslqt6tWrlwYNGqSAgAD5+/tr8ODBql69upo3by5Jqly5slq3bq3evXvrvffekyQ99dRTatu2rSIjI12TPAAAAAAAAAAgT8jThfR33nlHr776qvr06aOTJ08qNDRUTz/9tF577TVbnyFDhujy5cvq06ePEhISVK9ePa1evVpFihSx9Zk8ebLc3d3VuXNnXb58Wc2aNdO8efPk5uZm6/Phhx9qwIABatmypSSpffv2mjZt2u1LFgAAAAAAAACQJ1mMMcbVQRQUSUlJslqtSkxMzLBe+pUrV3T48GGVLVtW3t7eLooQuHkcwwAAAABwG1gsuTcWJR8AcMhRPfd6efqKdAAAAAAAkAsozgIAcEvy9JeNAgAAAAAAAADgahTSka/16NFDHTt2dHUYAAAAAAAAAAowCulwqEePHrJYLBlurVu3dnVokqS3335b8+bNc3UYkiSLxaLly5dnq+/69evVtm1blSxZUt7e3ipfvry6dOmib7/91rlBAgAAAAAAAMgx1kh3tdxcpy47bmItu9atW2vu3Ll2bV5eXrkV0U1JTU2VxWKR1Wp1aRw3Y/r06erXr5+io6O1ZMkSlS1bVidOnNCOHTs0cOBA7dq1K9PHpedcqBB//wIAAAAAAABuJypyyJKXl5eCg4PtbsWLF5ckbdiwQZ6envruu+9s/SdOnKgSJUroxIkTkqQmTZqoX79+6tevn4oVK6aAgAC98sorMv8o6qekpGjIkCG644475Ofnp3r16mnDhg227fPmzVOxYsW0cuVKValSRV5eXvr9998zLO3SpEkT9e/fXzExMSpevLiCgoI0a9YsXbx4UU888YSKFCmi8uXL6+uvv7bL8aefftJ9992nwoULKygoSNHR0Tp9+rTduAMGDNCQIUPk7++v4OBgjRgxwra9TJkykqQHHnhAFovFdv96R48eVUxMjGJiYjR//nzde++9Klu2rBo0aKDnnntOO3fuzDLnhIQEPf744ypevLh8fX3Vpk0bHTp0yPa4ESNGqFatWnbzTpkyxS6m9Odt5MiRCgwMVNGiRfX0008rJSUl07gBAAAAAACAfzMK6bglTZo0UUxMjKKjo5WYmKgffvhBw4YN0+zZsxUSEmLrN3/+fLm7u2vbtm2aOnWqJk+erPfff9+2/YknntD//vc/LV68WHv27NHDDz+s1q1b2xWIL126pLFjx+r999/Xvn37FBgYmGlM8+fPV4kSJbR9+3b1799fzz77rB5++GE1aNBAu3fvVqtWrRQdHa1Lly5Jkk6cOKHGjRurVq1a2rlzp2JjY/XXX3+pc+fOGcb18/PTtm3bNH78eI0aNUpr1qyRJO3YsUOSNHfuXNvV5ZlZunSprl69qiFDhmS63XLdfyhklnOPHj20c+dOrVixQlu2bJExRvfdd5+uXr2a6Zg3sm7dOu3fv1/r16/Xxx9/rGXLlmnkyJE5GgMAAAAAgH8tiyX3bgDyPArpyNLKlStVuHBhu9vrr79u2/7GG2/I399fTz31lB599FFFR0frgQcesBsjLCxMkydPVmRkpB599FH1799fkydPliT9+uuv+vjjj/Xpp5/qnnvuUfny5TV48GDdfffddkvKXL16VdOnT1eDBg0UGRkpPz+/TOOtWbOmXnnlFUVERGjo0KHy8fFRiRIl1Lt3b0VEROi1117TmTNntGfPHknSjBkzdOedd2rMmDGqVKmSateurQ8++EDr16/XwYMHbePWqFFDw4cPV0REhB5//HHVrVtX69atkySVLFlSklSsWDEFBwfb7l/v4MGDKlq0qIKDg21tS5cutXtu9+7de8Ocjx8/rhUrVuj999/XPffco5o1a+rDDz/Un3/+me312dN5enrqgw8+UNWqVXX//fdr1KhRmjp1qtLS0nI0DgAAAAAAAFDQsUY6stS0aVPNmDHDrs3f39/2s6enpxYtWqQaNWooPDxcU6ZMyTBG/fr17a62joqK0sSJE5Wamqrdu3fLGKOKFSvaPSY5OVkBAQF289SoUSPLeP/Zx83NTQEBAapevbqtLSgoSJJ08uRJSdKuXbu0fv16FS5cOMNYv/76qy2u6+cOCQmxjZET11913qpVK8XFxenPP/9UkyZNlJqaatt2fc779++Xu7u76tWrZ2sLCAhQZGSk9u/fn6M4atasKV9fX9v9qKgoXbhwQceOHVN4eHhO0wIAAAAAAAAKLArpyJKfn58qVKjgsM/mzZslSWfPntXZs2dveLV4ZtLS0uTm5qZdu3bJzc3Nbts/i9s+Pj4ZitCZ8fDwsLtvsVjs2tLHSL/yOi0tTe3atdO4ceMyjPXP5WkyGzenV29HREQoMTFR8fHxtqvSCxcurAoVKsjdPePL8fqczQ2+LNYYY+tXqFChDP1ysuxLdp5jAAAAAAAA4N+EpV1wy3799VcNHDhQs2fPVv369fX4449nKDBv3bo1w/2IiAi5ubmpdu3aSk1N1cmTJ1WhQgW72z+XQHGWO++8U/v27VOZMmUyzJ+TPwh4eHjYXU2emYceekgeHh6ZFu2zo0qVKrp27Zq2bdtmaztz5owOHjyoypUrS/p7mZn4+Hi7YnpcXFyGsX744QddvnzZdn/r1q0qXLiwSpUqdVOxAQAAAAAAAAUVhXRkKTk5WfHx8Xa306dPS5JSU1MVHR2tli1b6oknntDcuXP1448/auLEiXZjHDt2TM8//7wOHDigjz/+WO+8846ee+45SVLFihX16KOP6vHHH9dnn32mw4cPa8eOHRo3bpy++uorp+fXt29fnT17Vl27dtX27dv122+/afXq1erZs2eWhfF/KlOmjNatW6f4+HglJCRk2qd06dKaOHGi3n77bXXv3l3r16/XkSNHtHv3bk2dOlWSMlyV/08RERHq0KGDevfurU2bNumHH37QY489pjvuuEMdOnSQ9PcXwJ46dUrjx4/Xr7/+qnfffVdff/11hrFSUlLUq1cv/fTTT/r66681fPhw9evXT4UK8bYAAAAAAAAA/BMVM2QpNjZWISEhdre7775bkjR69GgdOXJEs2bNkiQFBwfr/fff1yuvvGJ3FfTjjz+uy5cv66677lLfvn3Vv39/PfXUU7btc+fO1eOPP65BgwYpMjJS7du317Zt2xQWFub0/EJDQ/W///1PqampatWqlapVq6bnnntOVqs1R0XliRMnas2aNQoLC1Pt2rVv2K9///5avXq1Tp06pYceekgRERG67777dPjwYcXGxtqt556ZuXPnqk6dOmrbtq2ioqJkjNFXX31lW3qmcuXKmj59ut59913VrFlT27dv1+DBgzOM06xZM0VERKhRo0bq3Lmz2rVrpxEjRmQ7XwAAAAAAALiQxZJ7N2TJYm606DJyLCkpSVarVYmJiSpatKjdtitXrujw4cMqW7asvL29XRShazRp0kS1atXK9EtI4Ro9evTQuXPntHz58mw/5t98DAMAAAD5Xm4WSSgjOBf7Kv9gX8HVOAZvmaN67vX4slEAAAAAAAAABRcFZ+QClnYBAAAAAAAAAMABrkiH023YsMHVIeA68+bNc3UIAAAAAAAAQL7BFekAAAAAAAAAADhAIR0AAAAAAAAAAAcopN9mhi8kQD7FsQsAAAAAAIB/K9ZIv03c3NwkSSkpKfLx8XFxNEDOXbp0SZLk4eHh4kgAAAAAJ7JYcm8sLkYBAKDAoJB+m7i7u8vX11enTp2Sh4eHChXinwGQPxhjdOnSJZ08eVLFihWz/VEIAAAAAAAUQLn1B0X+mIgChkL6bWKxWBQSEqLDhw/r999/d3U4QI4VK1ZMwcHBrg4DAAAAAAAAuO0opN9Gnp6eioiIUEpKiqtDAXLEw8ODK9EBAAAAAADwr0Uh/TYrVKiQvL29XR0GAAAAAAAAACCbKKQDAAAAAID8hy+GBQDcRnzjJQAAAAAAAAAADlBIBwAAAAAAAADAAQrpAAAAAAAAAAA4QCEdAAAAAAAAAAAH8nwhvUyZMrJYLBluffv2lSQZYzRixAiFhobKx8dHTZo00b59++zGSE5OVv/+/VWiRAn5+fmpffv2+uOPP+z6JCQkKDo6WlarVVarVdHR0Tp37tztShMAAAAAAAAAkEfl+UL6jh07dOLECdttzZo1kqSHH35YkjR+/HhNmjRJ06ZN044dOxQcHKwWLVro/PnztjFiYmK0bNkyLV68WJs2bdKFCxfUtm1bpaam2vp069ZNcXFxio2NVWxsrOLi4hQdHX17kwUAAAAAACiILJbcuQGAi1iMMcbVQeRETEyMVq5cqUOHDkmSQkNDFRMToxdffFHS31efBwUFady4cXr66aeVmJiokiVLauHCherSpYsk6fjx4woLC9NXX32lVq1aaf/+/apSpYq2bt2qevXqSZK2bt2qqKgo/fzzz4qMjMxWbElJSbJarUpMTFTRokWdkD0AAAAAwKlys1CXlz5uF8S8CmJOEnllpSDmJBXMvApiThJ5FTA5qefm+SvS/yklJUWLFi1Sz549ZbFYdPjwYcXHx6tly5a2Pl5eXmrcuLE2b94sSdq1a5euXr1q1yc0NFTVqlWz9dmyZYusVqutiC5J9evXl9VqtfUBAAAAAAAAAPw7ubs6gJxYvny5zp07px49ekiS4uPjJUlBQUF2/YKCgvT777/b+nh6eqp48eIZ+qQ/Pj4+XoGBgRnmCwwMtPXJTHJyspKTk233k5KScp4UAAAAAAAAACBPy1dXpM+ZM0dt2rRRaGioXbvlun9jMMZkaLve9X0y65/VOGPHjrV9OanValVYWFh20gAAAAAAAAAA5CP5ppD++++/a+3atXryySdtbcHBwZKU4arxkydP2q5SDw4OVkpKihISEhz2+euvvzLMeerUqQxXu//T0KFDlZiYaLsdO3bs5pIDAAAAAAAAAORZ+aaQPnfuXAUGBur++++3tZUtW1bBwcFas2aNrS0lJUUbN25UgwYNJEl16tSRh4eHXZ8TJ07oxx9/tPWJiopSYmKitm/fbuuzbds2JSYm2vpkxsvLS0WLFrW7AQAAAAAAAAAKlnyxRnpaWprmzp2r7t27y939/0K2WCyKiYnRmDFjFBERoYiICI0ZM0a+vr7q1q2bJMlqtapXr14aNGiQAgIC5O/vr8GDB6t69epq3ry5JKly5cpq3bq1evfurffee0+S9NRTT6lt27aKjIy8/QkDAAAAAAAAAPKMfFFIX7t2rY4ePaqePXtm2DZkyBBdvnxZffr0UUJCgurVq6fVq1erSJEitj6TJ0+Wu7u7OnfurMuXL6tZs2aaN2+e3NzcbH0+/PBDDRgwQC1btpQktW/fXtOmTXN+cgAAAAAAAACAPM1ijDGuDqKgSEpKktVqVWJiIsu8AAAAAEB+ZLHk3lh56eN2QcyrIOYkkVdWCmJOUsHMqyDmJJFXAZOTem6+WSMdAAAAAAAAAABXoJAOAAAAAAAAAIADFNIBAAAAAAAAAHCAQjoAAAAAAAAAAA5QSAcAAAAAAAAAwAEK6QAAAAAAAAAAOEAhHQAAAAAAAAAAByikAwAAAAAAAADgAIV0AAAAAAAAAAAcoJAOAAAAAAAAAIADFNIBAAAAAAAAAHCAQjoAAAAAAAAAAA5QSAcAAAAAAAAAwAEK6QAAAAAAAAAAOEAhHQAAAAAAAAAAByikAwAAAAAAAADgAIV0AAAAAAAAAAAcoJAOAAAAAAAAAIADFNIBAAAAAAAAAHCAQjoAAAAAAAAAAA5QSAcAAAAAAAAAwAEK6QAAAAAAAAAAOEAhHQAAAAAAAAAAByikAwAAAAAAAADgAIV0AAAAAAAAAAAcoJAOAAAAAAAAAIADFNIBAAAAAAAAAHCAQjoAAAAAAAAAAA5QSAcAAAAAAAAAwAEK6QAAAAAAAAAAOEAhHQAAAAAAAAAAB/J8If3PP//UY489poCAAPn6+qpWrVratWuXbbsxRiNGjFBoaKh8fHzUpEkT7du3z26M5ORk9e/fXyVKlJCfn5/at2+vP/74w65PQkKCoqOjZbVaZbVaFR0drXPnzt2OFAEAAAAAAAAAeVieLqQnJCSoYcOG8vDw0Ndff62ffvpJEydOVLFixWx9xo8fr0mTJmnatGnasWOHgoOD1aJFC50/f97WJyYmRsuWLdPixYu1adMmXbhwQW3btlVqaqqtT7du3RQXF6fY2FjFxsYqLi5O0dHRtzNdAAAAAAAAAEAeZDHGGFcHcSMvvfSS/ve//+m7777LdLsxRqGhoYqJidGLL74o6e+rz4OCgjRu3Dg9/fTTSkxMVMmSJbVw4UJ16dJFknT8+HGFhYXpq6++UqtWrbR//35VqVJFW7duVb169SRJW7duVVRUlH7++WdFRkZmK96kpCRZrVYlJiaqaNGiufAMAAAAAABuK4sl98bKSx+3C2JeBTEnibyyUhBzkgpmXgUxJ4m8Cpic1HPz9BXpK1asUN26dfXwww8rMDBQtWvX1uzZs23bDx8+rPj4eLVs2dLW5uXlpcaNG2vz5s2SpF27dunq1at2fUJDQ1WtWjVbny1btshqtdqK6JJUv359Wa1WW5/MJCcnKykpye4GAAAAAAAAAChY8nQh/bffftOMGTMUERGhVatW6ZlnntGAAQO0YMECSVJ8fLwkKSgoyO5xQUFBtm3x8fHy9PRU8eLFHfYJDAzMMH9gYKCtT2bGjh1rW1PdarUqLCzs5pMFAAAAAAAAAORJebqQnpaWpjvvvFNjxoxR7dq19fTTT6t3796aMWOGXT/Ldf/GYIzJ0Ha96/tk1j+rcYYOHarExETb7dixY9lJCwAAAAAAAACQj+TpQnpISIiqVKli11a5cmUdPXpUkhQcHCxJGa4aP3nypO0q9eDgYKWkpCghIcFhn7/++ivD/KdOncpwtfs/eXl5qWjRonY3AAAAAAAAAEDBkqcL6Q0bNtSBAwfs2g4ePKjw8HBJUtmyZRUcHKw1a9bYtqekpGjjxo1q0KCBJKlOnTry8PCw63PixAn9+OOPtj5RUVFKTEzU9u3bbX22bdumxMREWx8AAAAAAAAAwL+Tu6sDcGTgwIFq0KCBxowZo86dO2v79u2aNWuWZs2aJenv5VhiYmI0ZswYRUREKCIiQmPGjJGvr6+6desmSbJarerVq5cGDRqkgIAA+fv7a/DgwapevbqaN28u6e+r3Fu3bq3evXvrvffekyQ99dRTatu2rSIjI12TPAAAAAAAAAAgT8jThfT//Oc/WrZsmYYOHapRo0apbNmymjJlih599FFbnyFDhujy5cvq06ePEhISVK9ePa1evVpFihSx9Zk8ebLc3d3VuXNnXb58Wc2aNdO8efPk5uZm6/Phhx9qwIABatmypSSpffv2mjZt2u1LFgAAAAAAAACQJ1mMMcbVQRQUSUlJslqtSkxMZL10AAAAAMiPLJbcGysvfdwuiHkVxJwk8spKQcxJKph5FcScJPIqYHJSz83Ta6QDAAAAAAAAAOBqFNIBAAAAAAAAAHCAQjoAAAAAAAAAAA5QSAcAAAAAAAAAwAEK6QAAAAAAAAAAOEAhHQAAAAAAAAAAByikAwAAAAAAAADgAIV0AAAAAAAAAAAcoJAOAAAAAAAAAIADFNIBAAAAAAAAAHCAQjoAAAAAAAAAAA5QSAcAAAAAAAAAwAEK6QAAAAAAAAAAOEAhHQAAAAAAAAAAB9ydOXhKSopOnjyptLQ0u/bSpUs7c1oAAAAAAAAAAHKNUwrphw4dUs+ePbV582a7dmOMLBaLUlNTnTEtAAAAAAAAAAC5zimF9B49esjd3V0rV65USEiILBaLM6YBAAAAAAAAAMDpnFJIj4uL065du1SpUiVnDA8AAAAAAAAAwG3jlC8brVKlik6fPu2MoQEAAAAAAAAAuK2cUkgfN26chgwZog0bNujMmTNKSkqyuwEAAAAAAAAAkF9YjDEmtwctVOjv+vz1a6MX9C8bTUpKktVqVWJioooWLerqcAAAAAAAOZWb3/GV+x+3b15BzKsg5iSRV1YKYk5SwcyrIOYkkVcBk5N6rlPWSF+/fr0zhgUAAAAAAMBtYhmZe0W6f2eJDkBB4pRCeuPGjZ0xLAAAAAAAAADkW/yBKv9yyhrpkvTdd9/pscceU4MGDfTnn39KkhYuXKhNmzY5a0oAAAAAAAAAAHKdUwrpS5cuVatWreTj46Pdu3crOTlZknT+/HmNGTPGGVMCAAAAAAAAAOAUTimkv/HGG5o5c6Zmz54tDw8PW3uDBg20e/duZ0wJAAAAAAAAAIBTOKWQfuDAATVq1ChDe9GiRXXu3DlnTAkAAAAAAAAAgFM4pZAeEhKiX375JUP7pk2bVK5cOWdMCQAAAAAAAACAUzilkP7000/rueee07Zt22SxWHT8+HF9+OGHGjx4sPr06eOMKQEAAAAAAAAAcAp3Zww6ZMgQJSYmqmnTprpy5YoaNWokLy8vDR48WP369XPGlAAAAAAAAAAAOIVTrkiXpNGjR+v06dPavn27tm7dqlOnTun111/P0RgjRoyQxWKxuwUHB9u2G2M0YsQIhYaGysfHR02aNNG+ffvsxkhOTlb//v1VokQJ+fn5qX379vrjjz/s+iQkJCg6OlpWq1VWq1XR0dGs5Q4AAAAAAAAAkOSkK9LTHT9+XGfOnFGjRo3k4+MjY4wsFkuOxqhatarWrl1ru+/m5mb7efz48Zo0aZLmzZunihUr6o033lCLFi104MABFSlSRJIUExOjL774QosXL1ZAQIAGDRqktm3bateuXbaxunXrpj/++EOxsbGSpKeeekrR0dH64osvbvUpAAAAAAAABZxlZM5qHY6YXBsJAJCbnFJIP3PmjDp37qz169fLYrHo0KFDKleunJ588kkVK1ZMEydOzH6A7u52V6GnM8ZoypQpGjZsmDp16iRJmj9/voKCgvTRRx/p6aefVmJioubMmaOFCxeqefPmkqRFixYpLCxMa9euVatWrbR//37FxsZq69atqlevniRp9uzZioqK0oEDBxQZGZkLzwgAAAAAAAAAIL9ySiF94MCB8vDw0NGjR1W5cmVbe5cuXTRw4MAcFdIPHTqk0NBQeXl5qV69ehozZozKlSunw4cPKz4+Xi1btrT19fLyUuPGjbV582Y9/fTT2rVrl65evWrXJzQ0VNWqVdPmzZvVqlUrbdmyRVar1VZEl6T69evLarVq8+bNDgvpycnJSk5Ott1PSkrKdl4AAAAAAABAbuC/IgDnc8oa6atXr9a4ceNUqlQpu/aIiAj9/vvv2R6nXr16WrBggVatWqXZs2crPj5eDRo00JkzZxQfHy9JCgoKsntMUFCQbVt8fLw8PT1VvHhxh30CAwMzzB0YGGjrcyNjx461ratutVoVFhaW7dwAAAAAAAAAAPmDUwrpFy9elK+vb4b206dPy8vLK9vjtGnTRg8++KCqV6+u5s2b68svv5T09xIu6a5fcz0767Bf3yez/tkZZ+jQoUpMTLTdjh07lmVOAAAAAAAAAID8xSlLuzRq1EgLFizQ66+/LunvQnVaWpomTJigpk2b3vS4fn5+ql69ug4dOqSOHTtK+vuK8pCQEFufkydP2q5SDw4OVkpKihISEuyuSj958qQaNGhg6/PXX39lmOvUqVMZrna/npeXV47+MAAAAAAAcI7cWtaAJQ0AAEBmnFJInzBhgpo0aaKdO3cqJSVFQ4YM0b59+3T27Fn973//u+lxk5OTtX//ft1zzz0qW7asgoODtWbNGtWuXVuSlJKSoo0bN2rcuHGSpDp16sjDw0Nr1qxR586dJUknTpzQjz/+qPHjx0uSoqKilJiYqO3bt+uuu+6SJG3btk2JiYm2YjsAAAAAAACA24d135HXOKWQXqVKFe3Zs0czZsyQm5ubLl68qE6dOqlv3752V49nZfDgwWrXrp1Kly6tkydP6o033lBSUpK6d+8ui8WimJgYjRkzRhEREYqIiNCYMWPk6+urbt26SZKsVqt69eqlQYMGKSAgQP7+/ho8eLBtqRhJqly5slq3bq3evXvrvffekyQ99dRTatu2rcMvGgUAAAAAAAAA/Ds4pZAu/b1kysiRI29pjD/++ENdu3bV6dOnVbJkSdWvX19bt25VeHi4JGnIkCG6fPmy+vTpo4SEBNWrV0+rV69WkSJFbGNMnjxZ7u7u6ty5sy5fvqxmzZpp3rx5cnNzs/X58MMPNWDAALVs2VKS1L59e02bNu2WYgcAAAAAAAAAFAwWY0yu/XfD2bNndenSJZUqVcrWtm/fPr311lu6ePGiOnbsaLtavCBKSkqS1WpVYmKiihYt6upwAAAAAOBfI9fWSB+RK8P8/8Hy0GICltxbIiHP5JWHcsrVJShG5NpQBTOvvHL8SRyDWQ5UAHOSyKuAyUk9N1evSE9fumXSpEmS/v5Sz3vuuUehoaEqX768evToodTUVEVHR+fmtAAAAAAAFDisDwwAQN5RKDcH27p1q9q3b2+7v2DBAvn7+ysuLk6ff/65xowZo3fffTc3pwQAAAAAAAAAwKly9Yr0+Ph4lS1b1nb/m2++0QMPPCB397+nad++vcaOHZubUwIAAAAAgHwk15bhyZVRAADInlwtpBctWlTnzp2zfRno9u3b1atXL9t2i8Wi5OTk3JwSAAAAAAAAyBaWTAJws3J1aZe77rpLU6dOVVpamv773//q/Pnzuvfee23bDx48qLCwsNycEgAAAAAAAAAAp8rVK9Jff/11NW/eXIsWLdK1a9f08ssvq3jx4rbtixcvVuPGjXNzSgAAAAAAAAAAnCpXC+m1atXS/v37tXnzZgUHB6tevXp22x955BFVqVIlN6cEAAAAAAAAAMCpcrWQLkklS5ZUhw4dMt12//335/Z0AAAAAAAAAAA4Va6ukQ4AAAAAAAAAQEFDIR0AAAAAAAAAAAcopAMAAAAAAAAA4ACFdAAAAAAAAAAAHHBKIX337t3au3ev7f7nn3+ujh076uWXX1ZKSoozpgQAAAAAAAAAwCmcUkh/+umndfDgQUnSb7/9pkceeUS+vr769NNPNWTIEGdMCQAAAAAAAACAUzilkH7w4EHVqlVLkvTpp5+qUaNG+uijjzRv3jwtXbrUGVMCAAAAAAAAAOAUTimkG2OUlpYmSVq7dq3uu+8+SVJYWJhOnz7tjCkBAAAAAAAAAHAKpxTS69atqzfeeEMLFy7Uxo0bdf/990uSDh8+rKCgIGdMCQAAAAAAAACAUzilkD5lyhTt3r1b/fr107Bhw1ShQgVJ0n//+181aNDAGVMCAAAAAAAAAOAU7s4YtEaNGtq7d2+G9gkTJsjNzc0ZUwIAAAAAAAAA4BROKaTfiLe39+2cDgAAAAAAAACAW5ZrhfTixYvLYrFkq+/Zs2dza1oAAAAAAAAAAJwq1wrpU6ZMsf185swZvfHGG2rVqpWioqIkSVu2bNGqVav06quv5taUAAAAAAAAAAA4Xa4V0rt37277+cEHH9SoUaPUr18/W9uAAQM0bdo0rV27VgMHDsytaQEAAAAAAAAAcKpCzhh01apVat26dYb2Vq1aae3atc6YEgAAAAAAAAAAp3BKIT0gIEDLli3L0L58+XIFBAQ4Y0oAAAAAAAAAAJwi15Z2+aeRI0eqV69e2rBhg22N9K1btyo2Nlbvv/++M6YEAAAAAAAAAMApnFJI79GjhypXrqypU6fqs88+kzFGVapU0f/+9z/Vq1fPGVMCAAAAAAAAAOAUTimkS1K9evX04Ycf2rWlpqZq+fLl6tixo7OmBQAAAAAAAAAgVzmtkP5PP//8sz744APNnz9fCQkJSklJuR3TAgAAAAAAAABwy5zyZaOSdPHiRX3wwQdq2LChqlatqt27d2v06NE6fvy4s6YEAAAAAAAAACDX5XohfcuWLerVq5eCg4M1bdo0derUSRaLRVOnTtWTTz6pEiVK3PTYY8eOlcViUUxMjK3NGKMRI0YoNDRUPj4+atKkifbt22f3uOTkZPXv318lSpSQn5+f2rdvrz/++MOuT0JCgqKjo2W1WmW1WhUdHa1z587ddKwAAAAAAAAAgIIhVwvpVapUUdeuXRUUFKRt27Zp9+7dGjRokCwWyy2PvWPHDs2aNUs1atSwax8/frwmTZqkadOmaceOHQoODlaLFi10/vx5W5+YmBgtW7ZMixcv1qZNm3ThwgW1bdtWqamptj7dunVTXFycYmNjFRsbq7i4OEVHR99y3AAAAAAAAACA/C1XC+m//PKLGjVqpKZNm6py5cq5Nu6FCxf06KOPavbs2SpevLit3RijKVOmaNiwYerUqZOqVaum+fPn69KlS/roo48kSYmJiZozZ44mTpyo5s2bq3bt2lq0aJH27t2rtWvXSpL279+v2NhYvf/++4qKilJUVJRmz56tlStX6sCBA7mWBwAAAAAAAAAg/8nVQvrhw4cVGRmpZ599VqVKldLgwYP1/fff3/IV6X379tX999+v5s2bZ5gvPj5eLVu2tLV5eXmpcePG2rx5syRp165dunr1ql2f0NBQVatWzdZny5Ytslqtqlevnq1P/fr1ZbVabX0AAAAAAAAAAP9OuVpIv+OOOzRs2DD98ssvWrhwoeLj49WwYUNdu3ZN8+bN08GDB3M85uLFi7V7926NHTs2w7b4+HhJUlBQkF17UFCQbVt8fLw8PT3trmTPrE9gYGCG8QMDA219MpOcnKykpCS7GwAAAAAAAACgYMn1LxtNd++992rRokU6ceKEpk2bpm+++UaVKlXKsMa5I8eOHdNzzz2nRYsWydvb+4b9rr/i3RiT5VXw1/fJrH9W44wdO9b25aRWq1VhYWEO5wQAAAAAAAAA5D9OK6Sns1qt6tOnj3bu3Kndu3erSZMm2X7srl27dPLkSdWpU0fu7u5yd3fXxo0bNXXqVLm7u9uuRL/+qvGTJ0/atgUHByslJUUJCQkO+/z1118Z5j916lSGq93/aejQoUpMTLTdjh07lu3cAAAAAAAAAAD5g9ML6f9Uq1YtTZ06Ndv9mzVrpr179youLs52q1u3rh599FHFxcWpXLlyCg4O1po1a2yPSUlJ0caNG9WgQQNJUp06deTh4WHX58SJE/rxxx9tfaKiopSYmKjt27fb+mzbtk2JiYm2Ppnx8vJS0aJF7W4AAAAAAAAAgILF3dUBOFKkSBFVq1bNrs3Pz08BAQG29piYGI0ZM0YRERGKiIjQmDFj5Ovrq27dukn6+4r4Xr16adCgQQoICJC/v78GDx6s6tWr2768tHLlymrdurV69+6t9957T5L01FNPqW3btoqMjLyNGQMAAAAAAAAA8po8XUjPjiFDhujy5cvq06ePEhISVK9ePa1evVpFihSx9Zk8ebLc3d3VuXNnXb58Wc2aNdO8efPk5uZm6/Phhx9qwIABatmypSSpffv2mjZt2m3PBwAAAAAAAACQt+S7QvqGDRvs7lssFo0YMUIjRoy44WO8vb31zjvv6J133rlhH39/fy1atCiXogQAAAAAAAAAFBS3dY10AAAAAAAAAADym1y7Ij0nXyI6YMCA3JoWAAAAAAAAAACnyrVC+uTJk7PVz2KxUEgHAAAAAAAAAOQbuVZIP3z4cG4NBQAAAAAAAABAnsEa6QAAAAAAAAAAOJBrV6Rf748//tCKFSt09OhRpaSk2G2bNGmSs6YFAAAAAAAAACBXOaWQvm7dOrVv315ly5bVgQMHVK1aNR05ckTGGN15553OmBIAAAAAAAAAAKdwytIuQ4cO1aBBg/Tjjz/K29tbS5cu1bFjx9S4cWM9/PDDzpgSAAAAAAAAAACncEohff/+/erevbskyd3dXZcvX1bhwoU1atQojRs3zhlTAgAAAAAAAADgFE4ppPv5+Sk5OVmSFBoaql9//dW27fTp086YEgAAAAAAAAAAp3DKGun169fX//73P1WpUkX333+/Bg0apL179+qzzz5T/fr1nTElAAAAAAAAAABO4ZRC+qRJk3ThwgVJ0ogRI3ThwgUtWbJEFSpU0OTJk50xJQAAAAAAAAAATuGUQnq5cuVsP/v6+mr69OnOmAYAAAAAAAAAAKdzyhrp5cqV05kzZzK0nzt3zq7IDgAAAAAAAABAXueUQvqRI0eUmpqaoT05OVl//vmnM6YEAAAAAAAAAMApcnVplxUrVth+XrVqlaxWq+1+amqq1q1bpzJlyuTmlAAAAAAAAAAAOFWuFtI7duwoSbJYLOrevbvdNg8PD5UpU0YTJ07MzSkBAAAAAAAAAHCqXC2kp6WlSZLKli2rHTt2qESJErk5PAAAAAAAAAAAt12uFtLTHT582BnDAgAAAAAAAABw2znly0YlaePGjWrXrp0qVKigiIgItW/fXt99952zpgMAAAAAAAAAwCmcUkhftGiRmjdvLl9fXw0YMED9+vWTj4+PmjVrpo8++sgZUwIAAAAAAAAA4BROWdpl9OjRGj9+vAYOHGhre+655zRp0iS9/vrr6tatmzOmBQAAAAAAAAAg1znlivTffvtN7dq1y9Devn171k8HAAAAAAAAAOQrTimkh4WFad26dRna161bp7CwMGdMCQAAAAAAAACAU+Tq0i49e/bU22+/rUGDBmnAgAGKi4tTgwYNZLFYtGnTJs2bN09vv/12bk4JAAAAAAAAAIBT5Wohff78+XrzzTf17LPPKjg4WBMnTtQnn3wiSapcubKWLFmiDh065OaUAAAAAAAAAAA4Va4W0o0xtp8feOABPfDAA7k5PAAAAAAAAAAAt12ur5FusVhye0gAAAAAAAAAAFwmV69Il6SKFStmWUw/e/Zsbk8LAAAAAAAAAIBT5HohfeTIkbJarbk9LAAAAAAAAAAALpHrhfRHHnlEgYGBuTLWjBkzNGPGDB05ckSSVLVqVb322mtq06aNpL/XZB85cqRmzZqlhIQE1atXT++++66qVq1qGyM5OVmDBw/Wxx9/rMuXL6tZs2aaPn26SpUqZeuTkJCgAQMGaMWKFZKk9u3b65133lGxYsVyJQ8AAAAAAAAAQP6Vq2uk5/b66KVKldKbb76pnTt3aufOnbr33nvVoUMH7du3T5I0fvx4TZo0SdOmTdOOHTsUHBysFi1a6Pz587YxYmJitGzZMi1evFibNm3ShQsX1LZtW6Wmptr6dOvWTXFxcYqNjVVsbKzi4uIUHR2dq7kAAAAAAAAAAPKnXL0i3RiTm8OpXbt2dvdHjx6tGTNmaOvWrapSpYqmTJmiYcOGqVOnTpKk+fPnKygoSB999JGefvppJSYmas6cOVq4cKGaN28uSVq0aJHCwsK0du1atWrVSvv371dsbKy2bt2qevXqSZJmz56tqKgoHThwQJGRkbmaEwAAAAAAAAAgf8nVK9LT0tJybVmX66Wmpmrx4sW6ePGioqKidPjwYcXHx6tly5a2Pl5eXmrcuLE2b94sSdq1a5euXr1q1yc0NFTVqlWz9dmyZYusVqutiC5J9evXl9VqtfUBAAAAAAAAAPx75foa6blt7969ioqK0pUrV1S4cGEtW7ZMVapUsRW5g4KC7PoHBQXp999/lyTFx8fL09NTxYsXz9AnPj7e1iez4n9gYKCtz40kJycrOTnZdj8pKSnnCQIAAAAAAAAA8rRcvSLdGSIjIxUXF6etW7fq2WefVffu3fXTTz/Ztl+/LrsxJsu12q/vk1n/7IwzduxYWa1W2y0sLCw7KQEAAAAAAAAA8pE8X0j39PRUhQoVVLduXY0dO1Y1a9bU22+/reDgYEnKcNX4yZMnbVepBwcHKyUlRQkJCQ77/PXXXxnmPXXqVIar3a83dOhQJSYm2m7Hjh276TwBAAAAAAAAAHlTni+kX88Yo+TkZJUtW1bBwcFas2aNbVtKSoo2btyoBg0aSJLq1KkjDw8Puz4nTpzQjz/+aOsTFRWlxMREbd++3dZn27ZtSkxMtPW5ES8vLxUtWtTuBgAAAAAAAAAoWPL0Gukvv/yy2rRpo7CwMJ0/f16LFy/Whg0bFBsbK4vFopiYGI0ZM0YRERGKiIjQmDFj5Ovrq27dukmSrFarevXqpUGDBikgIED+/v4aPHiwqlevrubNm0uSKleurNatW6t379567733JElPPfWU2rZtq8jISJflDgAAAAAAAADIG/J0If2vv/5SdHS0Tpw4IavVqho1aig2NlYtWrSQJA0ZMkSXL19Wnz59lJCQoHr16mn16tUqUqSIbYzJkyfL3d1dnTt31uXLl9WsWTPNmzdPbm5utj4ffvihBgwYoJYtW0qS2rdvr2nTpt3eZAEAAAAAAAAAeVKeLqTPmTPH4XaLxaIRI0ZoxIgRN+zj7e2td955R++8884N+/j7+2vRokU3GyYAAAAAAAAAoADLd2ukAwAAAAAAAABwO1FIBwAAAAAAAADAAQrpAAAAAAAAAAA4QCEdAAAAAAAAAAAHKKQDAAAAAAAAAOAAhXQAAAAAAAAAABygkA4AAAAAAAAAgAMU0gEAAAAAAAAAcIBCOgAAAAAAAAAADlBIBwAAAAAAAADAAQrpAAAAAAAAAAA4QCEdAAAAAAAAAAAHKKQDAAAAAAAAAOAAhXQAAAAAAAAAABygkA4AAAAAAAAAgAMU0gEAAAAAAAAAcIBCOgAAAAAAAAAADlBIBwAAAAAAAADAAQrpAAAAAAAAAAA4QCEdAAAAAAAAAAAHKKQDAAAAAAAAAOAAhXQAAAAAAAAAABygkA4AAAAAAAAAgAMU0gEAAAAAAAAAcIBCOgAAAAAAAAAADlBIBwAAAAAAAADAAQrpAAAAAAAAAAA4QCEdAAAAAAAAAAAHKKQDAAAAAAAAAOAAhXQAAAAAAAAAABygkA4AAAAAAAAAgAN5upA+duxY/ec//1GRIkUUGBiojh076sCBA3Z9jDEaMWKEQkND5ePjoyZNmmjfvn12fZKTk9W/f3+VKFFCfn5+at++vf744w+7PgkJCYqOjpbVapXValV0dLTOnTvn7BQBAAAAAAAAAHlcni6kb9y4UX379tXWrVu1Zs0aXbt2TS1bttTFixdtfcaPH69JkyZp2rRp2rFjh4KDg9WiRQudP3/e1icmJkbLli3T4sWLtWnTJl24cEFt27ZVamqqrU+3bt0UFxen2NhYxcbGKi4uTtHR0bc1XwAAAAAAAABA3uPu6gAciY2Ntbs/d+5cBQYGateuXWrUqJGMMZoyZYqGDRumTp06SZLmz5+voKAgffTRR3r66aeVmJioOXPmaOHChWrevLkkadGiRQoLC9PatWvVqlUr7d+/X7Gxsdq6davq1asnSZo9e7aioqJ04MABRUZG3t7EAQAAAAAAAAB5Rp6+Iv16iYmJkiR/f39J0uHDhxUfH6+WLVva+nh5ealx48bavHmzJGnXrl26evWqXZ/Q0FBVq1bN1mfLli2yWq22Irok1a9fX1ar1dYnM8nJyUpKSrK7AQAAAAAAAAAKlnxTSDfG6Pnnn9fdd9+tatWqSZLi4+MlSUFBQXZ9g4KCbNvi4+Pl6emp4sWLO+wTGBiYYc7AwEBbn8yM/X/t3X9UVHX+x/HXLL8lJEERSCRMRFOzhFZRN38RypY/26Qs01VrPf7EX5lZK2uFbq32Q1ZLM63I1TqZmpWKq2Iey98UmUdttbQCKUP8mSDc7z9f54TYDMLInbk+H+fMOc6d6/R6eZP53DfXy8yZ9nuqBwcHKyoqqvoFAQAAAAAAAABuyWMG6aNHj9aXX36p//znP5Ves9lsFZ4bhlFp2+Uu3+dK+zt7n6lTp6q4uNj+OHbsmLMaAAAAAAAAAAAP4xGD9DFjxmj16tXatGmTGjVqZN8eHh4uSZWuGi8sLLRfpR4eHq6SkhIVFRU53Of48eOV/rs//fRTpavdf8vPz09169at8AAAAAAAAAAAWItbD9INw9Do0aO1YsUKbdy4UTExMRVej4mJUXh4uLKzs+3bSkpKlJOTow4dOkiS4uPj5ePjU2Gf/Px8ffXVV/Z9EhMTVVxcrB07dtj32b59u4qLi+37AAAAAAAAAACuT95mB3Bk1KhRWrp0qVatWqWgoCD7lefBwcEKCAiQzWZTWlqaMjIyFBsbq9jYWGVkZKhOnToaOHCgfd9hw4Zp4sSJCg0NVUhIiCZNmqTWrVsrKSlJktSiRQv17NlTjz76qF577TVJ0mOPPaZ7771XcXFx5pQHAAAAAAAAALgFtx6kz58/X5LUpUuXCtsXL16sIUOGSJIef/xxnT9/XiNHjlRRUZHatWun9evXKygoyL7/iy++KG9vbw0YMEDnz59X9+7dtWTJEnl5edn3eeeddzR27FglJydLknr37q3MzMxrWxAAAAAAAAAA4PbcepBuGIbTfWw2m9LT05Wenv67+/j7+2vu3LmaO3fu7+4TEhKirKys6sQEAAAAAAAAAFiYW98jHQAAAAAAAAAAszFIBwAAAAAAAADAAQbpAAAAAAAAAAA4wCAdAAAAAAAAAAAHGKQDAAAAAAAAAOAAg3QAAAAAAAAAABxgkA4AAAAAAAAAgAMM0gEAAAAAAAAAcIBBOgAAAAAAAAAADjBIBwAAAAAAAADAAQbpAAAAAAAAAAA4wCAdAAAAAAAAAAAHGKQDAAAAAAAAAOAAg3QAAAAAAAAAABxgkA4AAAAAAAAAgAMM0gEAAAAAAAAAcIBBOgAAAAAAAAAADjBIBwAAAAAAAADAAQbpAAAAAAAAAAA4wCAdAAAAAAAAAAAHGKQDAAAAAAAAAOAAg3QAAAAAAAAAABxgkA4AAAAAAAAAgAMM0gEAAAAAAAAAcIBBOgAAAAAAAAAADjBIBwAAAAAAAADAAQbpAAAAAAAAAAA4wCAdAAAAAAAAAAAHGKQDAAAAAAAAAOAAg3QAAAAAAAAAABxw+0H6li1b1KtXL0VGRspms2nlypUVXjcMQ+np6YqMjFRAQIC6dOmiffv2VdjnwoULGjNmjOrXr6/AwED17t1b33//fYV9ioqKNGjQIAUHBys4OFiDBg3SyZMnr3E7AAAAAAAAAIC7c/tB+tmzZ9WmTRtlZmZe8fXnn39ec+bMUWZmpnbu3Knw8HDdfffdOn36tH2ftLQ0ffDBB1q2bJm2bt2qM2fO6N5771VZWZl9n4EDByo3N1dr167V2rVrlZubq0GDBl3zfgAAAAAAAAAA9+ZtdgBnUlJSlJKScsXXDMPQSy+9pGnTpql///6SpDfffFMNGzbU0qVL9be//U3FxcVatGiR3n77bSUlJUmSsrKyFBUVpQ0bNqhHjx7av3+/1q5dq88//1zt2rWTJC1cuFCJiYk6cOCA4uLiaqcsAAAAAAAAAMDtuP0V6Y4cOXJEBQUFSk5Otm/z8/NT586dtW3bNknS7t27VVpaWmGfyMhItWrVyr7PZ599puDgYPsQXZLat2+v4OBg+z5XcuHCBZ06darCAwAAAAAAAABgLR49SC8oKJAkNWzYsML2hg0b2l8rKCiQr6+v6tWr53CfsLCwSu8fFhZm3+dKZs6cab+nenBwsKKiomrUBwAAAAAAAADgfjx6kH6JzWar8NwwjErbLnf5Plfa39n7TJ06VcXFxfbHsWPHrjI5AAAAAAAAAMDdefQgPTw8XJIqXTVeWFhov0o9PDxcJSUlKioqcrjP8ePHK73/Tz/9VOlq99/y8/NT3bp1KzwAAAAAAAAAANbi0YP0mJgYhYeHKzs7276tpKREOTk56tChgyQpPj5ePj4+FfbJz8/XV199Zd8nMTFRxcXF2rFjh32f7du3q7i42L4PAAAAAAAAAOD65G12AGfOnDmjb775xv78yJEjys3NVUhIiBo3bqy0tDRlZGQoNjZWsbGxysjIUJ06dTRw4EBJUnBwsIYNG6aJEycqNDRUISEhmjRpklq3bq2kpCRJUosWLdSzZ089+uijeu211yRJjz32mO69917FxcXVfmkAAAAAAAAAgNtw+0H6rl271LVrV/vzCRMmSJIGDx6sJUuW6PHHH9f58+c1cuRIFRUVqV27dlq/fr2CgoLsv+fFF1+Ut7e3BgwYoPPnz6t79+5asmSJvLy87Pu88847Gjt2rJKTkyVJvXv3VmZmZi21BAAAAAAAAAC4K7cfpHfp0kWGYfzu6zabTenp6UpPT//dffz9/TV37lzNnTv3d/cJCQlRVlZWTaICAAAAAAAAACzIo++RDgAAAAAAAADAtcYgHQAAAAAAAAAABxikAwAAAAAAAADgAIN0AAAAAAAAAAAcYJAOAAAAAAAAAIAD3mYHAODhbDbXvZdhuO69AADVx9d2z8GxAgAAAGoFg3QAuF4wbAEAAAAAAKgWbu0CAAAAAAAAAIADXJEO92TFK2et2AlwB676u8XfK1QHX9sBAAAA4LrAIB0AroThLOB6DJ1hJv7/8yx8DgMAAMDNMEgHAAAAgGuNb+YAAAB4NAbpAAC4G4YtAAAAAAC4FX7YKAAAAAAAAAAADjBIBwAAAAAAAADAAQbpAAAAAAAAAAA4wD3SAcCN2f7huntlc6dswNr4egEAAAAA1w6DdAAAXIAhJoCq4uuF5+BYAQAA4BIG6XAZTjQAwHqs+rXdVb3cqZNVcawAAAAAuAMG6cB1iMGYc+7UCwAAAAAAAOZikA44wZVwgOvxTQ8AAAAAAOBJGKQDAAAAqDG+SQoAAAAr+4PZAQAAAAAAAAAAcGcM0gEAAAAAAAAAcIBBOgAAAAAAAAAADjBIBwAAAAAAAADAAQbpAAAAAAAAAAA4wCAdAAAAAAAAAAAHGKQDAAAAAAAAAOAAg3QAAAAAAAAAABxgkA4AAAAAAAAAgAMM0i8zb948xcTEyN/fX/Hx8fr000/NjgQAAAAAAAAAMBGD9N9Yvny50tLSNG3aNO3du1d/+tOflJKSoqNHj5odDQAAAAAAAABgEgbpvzFnzhwNGzZMw4cPV4sWLfTSSy8pKipK8+fPNzsaAAAAAAAAAMAkDNL/X0lJiXbv3q3k5OQK25OTk7Vt2zaTUgEAAAAAAAAAzOZtdgB38fPPP6usrEwNGzassL1hw4YqKCi44u+5cOGCLly4YH9eXFwsSTp16tS1C+rOfnXdW7n0T7Cmx8NFvazYSaKX8zeyYCfJmr2s2Emi1+/ha7tDVuxlxU4SvZy/kQU7STXvZVV8vXDIir2s2Emil/M3smAnyZq9rNhJopfFXJrjGobhdF8G6Zex2WwVnhuGUWnbJTNnztQ//vGPStujoqKuSbbrSbBL38yl71ZtVuwk0cv5G1mwk2TNXlbsJNHrGrNiJ8mavazYSaKX8zeyYCfJrXpZkVWPlRV7WbGTRC/nb2TBTpI1e1mxk0Qvizp9+rSCnfwZMEj/f/Xr15eXl1elq88LCwsrXaV+ydSpUzVhwgT78/Lycv3yyy8KDQ393eE7nDt16pSioqJ07Ngx1a1b1+w4LmHFThK9PIkVO0nW7GXFTpI1e1mxk2TNXlbsJNHLk1ixk1VZ9VhZsZcVO0n08iRW7CRZs5cVO0nW7VXbDMPQ6dOnFRkZ6XRfBun/z9fXV/Hx8crOzla/fv3s27Ozs9WnT58r/h4/Pz/5+flV2HbjjTdey5jXlbp161ruC4EVO0n08iRW7CRZs5cVO0nW7GXFTpI1e1mxk0QvT2LFTlZl1WNlxV5W7CTRy5NYsZNkzV5W7CRZt1dtcnYl+iUM0n9jwoQJGjRokBISEpSYmKgFCxbo6NGjGjFihNnRAAAAAAAAAAAmYZD+G6mpqTpx4oRmzJih/Px8tWrVSh9//LGio6PNjgYAAAAAAAAAMAmD9MuMHDlSI0eONDvGdc3Pz0/Tp0+vdNscT2bFThK9PIkVO0nW7GXFTpI1e1mxk2TNXlbsJNHLk1ixk1VZ9VhZsZcVO0n08iRW7CRZs5cVO0nW7eXObIZhGGaHAAAAAAAAAADAXf3B7AAAAAAAAAAAALgzBukAAAAAAAAAADjAIB0AAAAAAAAAAAcYpMOtzJs3TzExMfL391d8fLw+/fRTsyPV2JYtW9SrVy9FRkbKZrNp5cqVZkeqsZkzZ+rOO+9UUFCQwsLC1LdvXx04cMDsWDUyf/583Xbbbapbt67q1q2rxMREffLJJ2bHcqmZM2fKZrMpLS3N7Cg1kp6eLpvNVuERHh5udiyX+OGHH/Twww8rNDRUderU0e23367du3ebHavabr755krHymazadSoUWZHq5GLFy/qqaeeUkxMjAICAtSkSRPNmDFD5eXlZkerkdOnTystLU3R0dEKCAhQhw4dtHPnTrNjXRVnn7mGYSg9PV2RkZEKCAhQly5dtG/fPnPCXgVnvVasWKEePXqofv36stlsys3NNSXn1XDUqbS0VFOmTFHr1q0VGBioyMhIPfLII/rxxx/NC1xFzo5Venq6mjdvrsDAQNWrV09JSUnavn27OWGvc86O1ZAhQyp9frVv396csFehKuce+/fvV+/evRUcHKygoCC1b99eR48erf2wVeSs05XWGjabTS+88II5gavIWa8zZ85o9OjRatSokQICAtSiRQvNnz/fnLBV5KzT8ePHNWTIEEVGRqpOnTrq2bOnDh06ZE7YKqrKua8nri+q0svT1hfOOnnq+qIqx4r1Re1hkA63sXz5cqWlpWnatGnau3ev/vSnPyklJcWtF3VVcfbsWbVp00aZmZlmR3GZnJwcjRo1Sp9//rmys7N18eJFJScn6+zZs2ZHq7ZGjRpp1qxZ2rVrl3bt2qVu3bqpT58+br8AqqqdO3dqwYIFuu2228yO4hItW7ZUfn6+/ZGXl2d2pBorKipSx44d5ePjo08++URff/21Zs+erRtvvNHsaNW2c+fOCscpOztbknT//febnKxm/vnPf+rVV19VZmam9u/fr+eff14vvPCC5s6da3a0Ghk+fLiys7P19ttvKy8vT8nJyUpKStIPP/xgdrQqc/aZ+/zzz2vOnDnKzMzUzp07FR4errvvvlunT5+u5aRXx1mvs2fPqmPHjpo1a1YtJ6s+R53OnTunPXv26Omnn9aePXu0YsUKHTx4UL179zYh6dVxdqyaNWumzMxM5eXlaevWrbr55puVnJysn376qZaToipr9J49e1b4HPv4449rMWH1OOv1v//9T506dVLz5s21efNmffHFF3r66afl7+9frVBBBAAAERZJREFUy0mrzlmn3x6j/Px8vfHGG7LZbLrvvvtqOenVcdZr/PjxWrt2rbKysrR//36NHz9eY8aM0apVq2o5adU56mQYhvr27avDhw9r1apV2rt3r6Kjo5WUlOTW55FVOff1xPVFVXp52vrCWSdPXV9U5VixvqhFBuAm/vjHPxojRoyosK158+bGE088YVIi15NkfPDBB2bHcLnCwkJDkpGTk2N2FJeqV6+e8frrr5sdo8ZOnz5txMbGGtnZ2Ubnzp2NcePGmR2pRqZPn260adPG7BguN2XKFKNTp05mx7imxo0bZ9xyyy1GeXm52VFq5J577jGGDh1aYVv//v2Nhx9+2KRENXfu3DnDy8vLWLNmTYXtbdq0MaZNm2ZSqpq5/DO3vLzcCA8PN2bNmmXf9uuvvxrBwcHGq6++akLC6nG0ljhy5Ighydi7d2+tZqqpqqyPduzYYUgyvvvuu9oJ5QJV6VVcXGxIMjZs2FA7oXBFVzpWgwcPNvr06WNKHle5Uq/U1FSP/ryqyt+rPn36GN26daudQC5ypV4tW7Y0ZsyYUWFb27ZtjaeeeqoWk1Xf5Z0OHDhgSDK++uor+7aLFy8aISEhxsKFC01IWD2Xn/taZX3h6JzeU9cXVZlTeOL6oiq9WF9cO1yRDrdQUlKi3bt3Kzk5ucL25ORkbdu2zaRUqKri4mJJUkhIiMlJXKOsrEzLli3T2bNnlZiYaHacGhs1apTuueceJSUlmR3FZQ4dOqTIyEjFxMTogQce0OHDh82OVGOrV69WQkKC7r//foWFhemOO+7QwoULzY7lMiUlJcrKytLQoUNls9nMjlMjnTp10n//+18dPHhQkvTFF19o69at+vOf/2xysuq7ePGiysrKKl2RGBAQoK1bt5qUyrWOHDmigoKCCmsNPz8/de7cmbWGByguLpbNZvPof6VzuZKSEi1YsEDBwcFq06aN2XFwBZs3b1ZYWJiaNWumRx99VIWFhWZHqpHy8nJ99NFHatasmXr06KGwsDC1a9fOEreevOT48eP66KOPNGzYMLOj1FinTp20evVq/fDDDzIMQ5s2bdLBgwfVo0cPs6NVy4ULFySpwlrDy8tLvr6+HrXWuPzc1yrrC6ud00tV6+SJ6wtnvVhfXFsM0uEWfv75Z5WVlalhw4YVtjds2FAFBQUmpUJVGIahCRMmqFOnTmrVqpXZcWokLy9PN9xwg/z8/DRixAh98MEHuvXWW82OVSPLli3Tnj17NHPmTLOjuEy7du301ltvad26dVq4cKEKCgrUoUMHnThxwuxoNXL48GHNnz9fsbGxWrdunUaMGKGxY8fqrbfeMjuaS6xcuVInT57UkCFDzI5SY1OmTNGDDz6o5s2by8fHR3fccYfS0tL04IMPmh2t2oKCgpSYmKhnnnlGP/74o8rKypSVlaXt27crPz/f7HgucWk9wVrD8/z666964oknNHDgQNWtW9fsODW2Zs0a3XDDDfL399eLL76o7Oxs1a9f3+xYuExKSoreeecdbdy4UbNnz9bOnTvVrVs3+zDQExUWFurMmTOaNWuWevbsqfXr16tfv37q37+/cnJyzI7nEm+++aaCgoLUv39/s6PU2CuvvKJbb71VjRo1kq+vr3r27Kl58+apU6dOZkerlubNmys6OlpTp05VUVGRSkpKNGvWLBUUFHjMWuNK575WWF9Y6Zz+kqp08sT1haNerC9qh7fZAYDfuvwqRcMwPP7KRasbPXq0vvzyS4+6iuD3xMXFKTc3VydPntT777+vwYMHKycnx2OH6ceOHdO4ceO0fv16t77v5dVKSUmx/7p169ZKTEzULbfcojfffFMTJkwwMVnNlJeXKyEhQRkZGZKkO+64Q/v27dP8+fP1yCOPmJyu5hYtWqSUlBRFRkaaHaXGli9frqysLC1dulQtW7ZUbm6u0tLSFBkZqcGDB5sdr9refvttDR06VDfddJO8vLzUtm1bDRw4UHv27DE7mkux1vAspaWleuCBB1ReXq558+aZHcclunbtqtzcXP38889auHChBgwYoO3btyssLMzsaPiN1NRU+69btWqlhIQERUdH66OPPvLYIe2lH4rdp08fjR8/XpJ0++23a9u2bXr11VfVuXNnM+O5xBtvvKGHHnrIEmvfV155RZ9//rlWr16t6OhobdmyRSNHjlRERIRH/ktTHx8fvf/++xo2bJhCQkLk5eWlpKSkCmt7d+fo3NeT1xdWOqe/xFknT11fOOrF+qJ2cEU63EL9+vXl5eVV6Tu2hYWFlb6zC/cxZswYrV69Wps2bVKjRo3MjlNjvr6+atq0qRISEjRz5ky1adNGL7/8stmxqm337t0qLCxUfHy8vL295e3trZycHL3yyivy9vZWWVmZ2RFdIjAwUK1bt9ahQ4fMjlIjERERlb5p06JFC4//gcuS9N1332nDhg0aPny42VFcYvLkyXriiSf0wAMPqHXr1ho0aJDGjx/v8f/y45ZbblFOTo7OnDmjY8eOaceOHSotLVVMTIzZ0VwiPDxcklhreJDS0lINGDBAR44cUXZ2tsdcLeZMYGCgmjZtqvbt22vRokXy9vbWokWLzI4FJyIiIhQdHe3R64369evL29vbsuuNTz/9VAcOHLDEeuP8+fN68sknNWfOHPXq1Uu33XabRo8erdTUVP3rX/8yO161xcfH2y9cys/P19q1a3XixAmPWGv83rmvp68vrHZOLznv5KnrC2e9WF/UDgbpcAu+vr6Kj49XdnZ2he3Z2dnq0KGDSanwewzD0OjRo7VixQpt3LjRIxY+1WEYhkf/893u3bsrLy9Pubm59kdCQoIeeugh5ebmysvLy+yILnHhwgXt379fERERZkepkY4dO+rAgQMVth08eFDR0dEmJXKdxYsXKywsTPfcc4/ZUVzi3Llz+sMfKi6hvLy87Ff6ebrAwEBFRESoqKhI69atU58+fcyO5BIxMTEKDw+vsNYoKSlRTk4Oaw03dOkk99ChQ9qwYYNCQ0PNjnTNePp643px4sQJHTt2zKPXG76+vrrzzjstu95YtGiR4uPjLXFP4NLSUpWWllp2vREcHKwGDRro0KFD2rVrl1uvNZyd+3rq+sKK5/RV6eSJ64vqHivWF9cGt3aB25gwYYIGDRqkhIQEJSYmasGCBTp69KhGjBhhdrQaOXPmjL755hv78yNHjig3N1chISFq3Lixicmqb9SoUVq6dKlWrVqloKAg+3ffg4ODFRAQYHK66nnyySeVkpKiqKgonT59WsuWLdPmzZu1du1as6NVW1BQUKX7pgUGBio0NNSj7303adIk9erVS40bN1ZhYaGeffZZnTp1yqNvqSFJ48ePV4cOHZSRkaEBAwZox44dWrBggRYsWGB2tBopLy/X4sWLNXjwYHl7W2PZ0atXLz333HNq3LixWrZsqb1792rOnDkaOnSo2dFqZN26dTIMQ3Fxcfrmm280efJkxcXF6a9//avZ0arM2WduWlqaMjIyFBsbq9jYWGVkZKhOnToaOHCgiamdc9brl19+0dGjR/Xjjz9Kkn1IFh4ebr9Szt046hQZGam//OUv2rNnj9asWaOysjL7WiMkJES+vr5mxXbKUa/Q0FA999xz6t27tyIiInTixAnNmzdP33//ve6//34TU1+fHB2rkJAQpaen67777lNERIS+/fZbPfnkk6pfv7769etnYmrnnH29mDx5slJTU3XXXXepa9euWrt2rT788ENt3rzZvNBOVOV86tSpU3rvvfc0e/Zss2JeNWe9OnfurMmTJysgIEDR0dHKycnRW2+9pTlz5piY2jFnnd577z01aNBAjRs3Vl5ensaNG6e+fftW+EGd7sbZua/NZvPI9UVVzuk9bX3hrNPFixc9cn3hrNfZs2dZX9QmA3Aj//73v43o6GjD19fXaNu2rZGTk2N2pBrbtGmTIanSY/DgwWZHq7Yr9ZFkLF682Oxo1TZ06FD7/3sNGjQwunfvbqxfv97sWC7XuXNnY9y4cWbHqJHU1FQjIiLC8PHxMSIjI43+/fsb+/btMzuWS3z44YdGq1atDD8/P6N58+bGggULzI5UY+vWrTMkGQcOHDA7isucOnXKGDdunNG4cWPD39/faNKkiTFt2jTjwoULZkerkeXLlxtNmjQxfH19jfDwcGPUqFHGyZMnzY51VZx95paXlxvTp083wsPDDT8/P+Ouu+4y8vLyzA1dBc56LV68+IqvT58+3dTcjjjqdOTIkd9da2zatMns6A456nX+/HmjX79+RmRkpOHr62tEREQYvXv3Nnbs2GF27OuSo2N17tw5Izk52WjQoIHh4+NjNG7c2Bg8eLBx9OhRs2M7VZVzj0WLFhlNmzY1/P39jTZt2hgrV640L3AVVKXTa6+9ZgQEBHjU55azXvn5+caQIUOMyMhIw9/f34iLizNmz55tlJeXmxvcAWedXn75ZaNRo0b2v1dPPfWU26+fqnLu64nri6r08rT1hbNOnrq+cNaL9UXtshmGYTiYswMAAAAAAAAAcF3jHukAAAAAAAAAADjAIB0AAAAAAAAAAAcYpAMAAAAAAAAA4ACDdAAAAAAAAAAAHGCQDgAAAAAAAACAAwzSAQAAAAAAAABwgEE6AAAAAAAAAAAOMEgHAAAAAAAAAMABBukAAAAAAAAAADjAIB0AAACwqCFDhqhv376Vtm/evFk2m00nT56s9UwAAACAJ2KQDgAAAMDlSktLzY4AAAAAuAyDdAAAAOA69/7776tly5by8/PTzTffrNmzZ1d43WazaeXKlRW23XjjjVqyZIkk6dtvv5XNZtO7776rLl26yN/fX1lZWfruu+/Uq1cv1atXT4GBgWrZsqU+/vjjWmoFAAAAuI632QEAAAAAmGf37t0aMGCA0tPTlZqaqm3btmnkyJEKDQ3VkCFDruq9pkyZotmzZ2vx4sXy8/PTY489ppKSEm3ZskWBgYH6+uuvdcMNN1ybIgAAAMA1xCAdAAAAsLA1a9ZUGl6XlZXZfz1nzhx1795dTz/9tCSpWbNm+vrrr/XCCy9c9SA9LS1N/fv3tz8/evSo7rvvPrVu3VqS1KRJk2q2AAAAAMzFrV0AAAAAC+vatatyc3MrPF5//XX76/v371fHjh0r/J6OHTvq0KFDFQbuVZGQkFDh+dixY/Xss8+qY8eOmj59ur788svqFwEAAABMxCAdAAAAsLDAwEA1bdq0wuOmm26yv24Yhmw2W4XfYxhGhec2m63Stiv9MNHAwMAKz4cPH67Dhw9r0KBBysvLU0JCgubOnVvTSgAAAECtY5AOAAAAXMduvfVWbd26tcK2bdu2qVmzZvLy8pIkNWjQQPn5+fbXDx06pHPnzlXp/aOiojRixAitWLFCEydO1MKFC10XHgAAAKgl3CMdAAAAuI5NnDhRd955p5555hmlpqbqs88+U2ZmpubNm2ffp1u3bsrMzFT79u1VXl6uKVOmyMfHx+l7p6WlKSUlRc2aNVNRUZE2btyoFi1aXMs6AAAAwDXBFekAAADAdaxt27Z69913tWzZMrVq1Up///vfNWPGjAo/aHT27NmKiorSXXfdpYEDB2rSpEmqU6eO0/cuKyvTqFGj1KJFC/Xs2VNxcXEVBvQAAACAp7AZl9/sEAAAAAAAAAAA2HFFOgAAAAAAAAAADjBIBwAAAAAAAADAAQbpAAAAAAAAAAA4wCAdAAAAAAAAAAAHGKQDAAAAAAAAAOAAg3QAAAAAAAAAABxgkA4AAAAAAAAAgAMM0gEAAAAAAAAAcIBBOgAAAAAAAAAADjBIBwAAAAAAAADAAQbpAAAAAAAAAAA4wCAdAAAAAAAAAAAH/g8lXxxESJYpqgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bar_fig(period=time, \n",
    "        data1=data_time_ad, \n",
    "        data2=time_con_ad, \n",
    "        data3=time_exp_ad, \n",
    "        subtit1='Total Ads Seen by All Users at Different Hours', \n",
    "        subtit2='Total Ads Seen Comparison: Control vs Experiment Groups by Hours', \n",
    "        x_label='Hours', \n",
    "        y_label='Total Ads Seen', \n",
    "        figtitle='Analysis of Ads Seen by Users Throughout the Day')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similar to previous analyse, the total number of ads viewed generally increases for both groups between 15:00 and 23:00 compared to other hours. Additionally, the treatment group consistently sees more ads than the control group during these peak hours."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6) Conversion Rate by Groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th colspan=\"4\" halign=\"left\">made_purchase</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>sum</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>&lt;lambda_0&gt;</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ad</th>\n",
       "      <td>12053</td>\n",
       "      <td>803</td>\n",
       "      <td>0.066622</td>\n",
       "      <td>0.249377</td>\n",
       "      <td>0.002271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>psa</th>\n",
       "      <td>7947</td>\n",
       "      <td>257</td>\n",
       "      <td>0.032339</td>\n",
       "      <td>0.176911</td>\n",
       "      <td>0.001985</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      customerID made_purchase                               \n",
       "           count           sum      mean       std <lambda_0>\n",
       "group                                                        \n",
       "ad         12053           803  0.066622  0.249377   0.002271\n",
       "psa         7947           257  0.032339  0.176911   0.001985"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conversions = df.groupby('group').agg({'customerID':'count', 'made_purchase': ['sum', 'mean', 'std', lambda x: np.std(x, ddof=1)/np.sqrt(len(x))]})\n",
    "conversions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "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>number of observations</th>\n",
       "      <th>total_conversions</th>\n",
       "      <th>conversion_rate</th>\n",
       "      <th>std_dev</th>\n",
       "      <th>std_error</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Treatment Group</th>\n",
       "      <td>12053</td>\n",
       "      <td>803</td>\n",
       "      <td>0.066622</td>\n",
       "      <td>0.249377</td>\n",
       "      <td>0.002271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Control Group</th>\n",
       "      <td>7947</td>\n",
       "      <td>257</td>\n",
       "      <td>0.032339</td>\n",
       "      <td>0.176911</td>\n",
       "      <td>0.001985</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 number of observations  total_conversions  conversion_rate  \\\n",
       "group                                                                         \n",
       "Treatment Group                   12053                803         0.066622   \n",
       "Control Group                      7947                257         0.032339   \n",
       "\n",
       "                  std_dev  std_error  \n",
       "group                                 \n",
       "Treatment Group  0.249377   0.002271  \n",
       "Control Group    0.176911   0.001985  "
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conversions.columns = ['number of observations', 'total_conversions', 'conversion_rate', 'std_dev', 'std_error']\n",
    "conversions = conversions.rename(index={'ad': 'Treatment Group', 'psa': 'Control Group'})\n",
    "conversions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "groups = conversions.index.tolist()\n",
    "conversion_rates = conversions['conversion_rate'].values\n",
    "errors = conversions['std_error'].values \n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "bar_width = 0.45\n",
    "index = np.arange(len(groups))\n",
    "\n",
    "bars = ax.bar(index, conversion_rates, bar_width,\n",
    "              color=['red', 'green'],  \n",
    "              yerr=errors,  # Error bars\n",
    "              capsize=5) \n",
    "\n",
    "ax.set_xlabel('')\n",
    "ax.set_ylabel('Conversion Rate')\n",
    "ax.set_title('Conversion Rates by Group with Error Bars')\n",
    "\n",
    "ax.set_xticks(index)\n",
    "ax.set_xticklabels(groups)\n",
    "\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The treatment group, represented by the red bar, shows a significantly higher conversion rate compared to the control group."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7) Conversion Rates by Days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "days_with_most_add\n",
       "1    0.045597\n",
       "2    0.038405\n",
       "3    0.044510\n",
       "4    0.059701\n",
       "5    0.042836\n",
       "Name: made_purchase, dtype: float64"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "days_conversions = df.groupby('days_with_most_add')['made_purchase'].mean()\n",
    "days_conversions.columns = ['conversion_rate']\n",
    "days_conversions.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [],
   "source": [
    "days_conversions_exp = df[df['group'] == 'ad'].groupby('days_with_most_add')['made_purchase'].mean()\n",
    "days_conversions_exp.name = 'conversion_rate'\n",
    "days_conversions_con = df[df['group'] == 'psa'].groupby('days_with_most_add')['made_purchase'].mean()\n",
    "days_conversions_con.name = 'conversion_rate'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bar_fig(period=days, \n",
    "        data1=days_conversions, \n",
    "        data2=days_conversions_con, \n",
    "        data3=days_conversions_exp, \n",
    "        subtit1='Conversion Rate by All Users per Day', \n",
    "        subtit2='Conversion Rate Comparison: Control vs Experiment Groups by Days', \n",
    "        x_label='Days', \n",
    "        y_label='Conversion Rate', \n",
    "        figtitle='Analysis of Daily Conversion Rate')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The conversion rates vary significantly throughout the month, with notable peaks on the 14th, 27th, 29th, and 30th. The second chart illustrates that the experiment (or treatment) group generally achieves higher conversion rates than the control group on most days. The exception to this trend occurs on the 18th, where the control group outperforms the experiment group."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index([30, 14, 29, 27, 21], dtype='int64', name='days_with_most_add')\n"
     ]
    }
   ],
   "source": [
    "top_days = days_conversions.sort_values(ascending=False).head(5)\n",
    "print(top_days.index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 8) Conversion Rate by Hours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "peak_ad_hours\n",
       "0    0.065789\n",
       "1    0.051282\n",
       "2    0.046448\n",
       "3    0.040936\n",
       "4    0.031662\n",
       "Name: made_purchase, dtype: float64"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hour_conversions = df.groupby('peak_ad_hours')['made_purchase'].mean()\n",
    "hour_conversions.columns = ['conversion_rate']\n",
    "hour_conversions.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "hour_conversions_exp = df[df['group'] == 'ad'].groupby('peak_ad_hours')['made_purchase'].mean()\n",
    "hour_conversions_exp.name = 'conversion_rate'\n",
    "hour_conversions_con = df[df['group'] == 'psa'].groupby('peak_ad_hours')['made_purchase'].mean()\n",
    "hour_conversions_con.name = 'conversion_rate'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bar_fig(period=time, \n",
    "        data1=hour_conversions, \n",
    "        data2=hour_conversions_con, \n",
    "        data3=hour_conversions_exp, \n",
    "        subtit1='Conversion Rate by All Users per Hour', \n",
    "        subtit2='Conversion Rate Comparison: Control vs Experiment Groups by Hour', \n",
    "        x_label='Hours', \n",
    "        y_label='Conversion Rate', \n",
    "        figtitle='Analysis of Conversion Rate Throughout the Day')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index([5, 7, 0, 18, 21], dtype='int64', name='peak_ad_hours')\n"
     ]
    }
   ],
   "source": [
    "peak_hours = hour_conversions.sort_values(ascending=False).head(5)\n",
    "print(peak_hours.index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is significant variability in conversion rates throughout the day. Peaks occur at specific times, notably at 5 AM, 7 AM, midnight, and 6 PM. When comparing the two groups, the experiment group consistently demonstrates higher conversion rates across almost every hour, except at 11 AM where it underperforms relative to the control group. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A\\B Testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['number of observations', 'total_conversions', 'conversion_rate',\n",
       "       'std_dev', 'std_error'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conversions.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_con = conversions.loc['Control Group', 'number of observations']\n",
    "n_exp = conversions.loc['Treatment Group', 'number of observations']\n",
    "conv_con = conversions.loc['Control Group', 'total_conversions']\n",
    "conv_exp = conversions.loc['Treatment Group', 'total_conversions']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "n = [n_exp, n_con]\n",
    "conversion = [conv_exp, conv_con]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Notes:\n",
    "\n",
    "* $\\beta$ (Prob of Type 2 Error) = 0.20 or **Power**: 0.80\n",
    "* $\\alpha$ (Level of Significance) = 0.05"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Z-critical values for alpha, 0.05: (-1.96, 1.96).\n"
     ]
    }
   ],
   "source": [
    "alpha = 0.05\n",
    "\n",
    "# Z-score for two-tailed test\n",
    "z_critical = stats.norm.ppf(1 - alpha / 2)\n",
    "print(f\"Z-critical values for alpha, {alpha}: (-{z_critical:.2f}, {z_critical:.2f}).\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1) Two-tailed Test\n",
    "**Null Hypothesis ($H_0$)**: The ads have no effect on sales.\n",
    "\n",
    "**Alternative Hypothesis ($H_1$)**: The ads have a significant effect on sales. That is, there is a statistically significant difference in sales between the treatment group (ad) and the control group (psa).\n",
    "\n",
    "$$ H_0: \\mu_{\\text{ad}} = \\mu_{\\text{psa}} $$\n",
    "$$ H_1: \\mu_{\\text{ad}} \\neq \\mu_{\\text{psa}} $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Z-score of the two-tailed test is 10.590. Since it is significantly higher than 1.96, we can reject the null hypothesis and conclude that the ads have a significant effect on sales.\n",
      "OR The p-value of two-tailed test is 0.00000, which is lower than 0.05. That is, there is a statistically significant difference in sales between the treatment group (ad) and the control group (psa).\n",
      "In other words, both the Z-score and the p-value are consistent with each other and indicate a significant effect of the ads on sales.\n"
     ]
    }
   ],
   "source": [
    "z_test_two, pval_two = proportions_ztest(conversion, nobs=n)\n",
    "\n",
    "print(f'The Z-score of the two-tailed test is {z_test_two:.3f}. Since it is significantly higher than {z_critical:.2f}, we can reject the null hypothesis and conclude that the ads have a significant effect on sales.')\n",
    "\n",
    "print(f'OR The p-value of two-tailed test is {pval_two:.5f}, which is lower than 0.05. That is, there is a statistically significant difference in sales between the treatment group (ad) and the control group (psa).')\n",
    "\n",
    "print('In other words, both the Z-score and the p-value are consistent with each other and indicate a significant effect of the ads on sales.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Confidence interval**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Difference in conversion rates: 0.03428\n",
      "Standard error of the difference: 0.00302\n",
      "Margin of error: 0.00591\n"
     ]
    }
   ],
   "source": [
    "convrate_exp = conversions.loc['Treatment Group', 'conversion_rate']\n",
    "convrate_con = conversions.loc['Control Group', 'conversion_rate']\n",
    "convrate_diff = convrate_exp - convrate_con\n",
    "se_diff = np.sqrt((conversions.loc['Treatment Group', 'std_error'])**2 + (conversions.loc['Control Group', 'std_error'])**2)\n",
    "margin_error = z_critical * se_diff\n",
    "print(f\"Difference in conversion rates: {convrate_diff:.5f}\")\n",
    "print(f\"Standard error of the difference: {se_diff:.5f}\")\n",
    "print(f'Margin of error: {margin_error:.5f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The 95% confidence interval for the difference in conversion rates is (0.02837, 0.04019).\n"
     ]
    }
   ],
   "source": [
    "ci_lower = convrate_diff - margin_error\n",
    "ci_upper = convrate_diff + margin_error\n",
    "print(f\"The 95% confidence interval for the difference in conversion rates is ({ci_lower:.5f}, {ci_upper:.5f}).\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2) One-tailed Test\n",
    "**Null Hypothesis ($H_0$)**: The ads have no effect on sales.\n",
    "\n",
    "**Alternative Hypothesis ($H_1$)**: The treatment group has higher sales compared to the control group. In other words, ads increase sales.\n",
    "\n",
    "$$ H_0: \\mu_{\\text{ad}} = \\mu_{\\text{psa}} $$\n",
    "$$ H_1: \\mu_{\\text{ad}} > \\mu_{\\text{psa}} $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Z-Critical value for one-tailed test with alpha 0.05: 1.645\n"
     ]
    }
   ],
   "source": [
    "z_critical_onetailed = stats.norm.ppf(1 - alpha)\n",
    "\n",
    "print(f\"Z-Critical value for one-tailed test with alpha {alpha}: {z_critical_onetailed:.3f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10.590153051109288, 1.6552506718082564e-26)"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conversion_onetailed = [conv_exp, conv_con]\n",
    "n_onetailed = [n_exp, n_con]\n",
    "z_test_one, pval_one = proportions_ztest(conversion_onetailed, nobs=n_onetailed, alternative='larger')\n",
    "z_test_one, pval_one"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Z-score of the two-tailed test is 10.590. Since it is higher than 1.645, we can reject the null hypothesis and conclude that the ads increase sales.\n",
      "OR The p-value of two-tailed test is 0.00000, which is lower than 0.05.\n",
      "In other words, both Z-score and p-value show that the ads lead to an increase in sales.\n"
     ]
    }
   ],
   "source": [
    "print(f'The Z-score of the two-tailed test is {z_test_one:.3f}. Since it is higher than {z_critical_onetailed:.3f}, we can reject the null hypothesis and conclude that the ads increase sales.')\n",
    "\n",
    "print(f'OR The p-value of two-tailed test is {pval_one:.5f}, which is lower than 0.05.')\n",
    "\n",
    "print('In other words, both Z-score and p-value show that the ads lead to an increase in sales.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Confidence Interval:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Margin of error: 0.00496\n"
     ]
    }
   ],
   "source": [
    "margin_error_onetailed = z_critical_onetailed * se_diff\n",
    "print(f'Margin of error: {margin_error_onetailed:.5f}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The 95% confidence interval for the difference in conversion rates is (0.02932, 0.03924).\n"
     ]
    }
   ],
   "source": [
    "ci_lower = convrate_diff - margin_error_onetailed\n",
    "ci_upper = convrate_diff + margin_error_onetailed\n",
    "print(f\"The 95% confidence interval for the difference in conversion rates is ({ci_lower:.5f}, {ci_upper:.5f}).\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "Main result of this study is that **ads increase sales**. Additional findings include::\n",
    "\n",
    "* The treatment group exhibits higher customer activity and a greater total number of ads viewed compared to the control group.\n",
    "* Between 15:00 and 23:00, customer activity and the number of ads seen are significantly higher than during other hours.\n",
    "* Despite the increased activity during these hours, the peak times for making purchases across all users are at midnight (0:00), 5 AM, and 7 AM. This indicates that higher customer activity does not necessarily lead to higher conversions."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.0"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}