drewfustin/exp__autograde_vs_price.ipynb

## exp__autograde_vs_price.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "module_path = os.path.abspath(os.path.join('..'))\n",
    "if module_path not in sys.path:\n",
    "    sys.path.append(module_path)\n",
    "\n",
    "import drivin_ds\n",
    "from drivin_ds.sql import postgres_describe\n",
    "from smart_recon.core.helpers import preview_table\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.max_rows', 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "autograde_query = \"\"\"\n",
    "SELECT\n",
    "    target.serial_number AS vin\n",
    "    , CAST(assign_target.inventory_number AS bigint) AS inventory_number\n",
    "    , CAST(department.site_number AS int) AS site_number\n",
    "    , target.model_year AS year\n",
    "    , target.make\n",
    "    , target.model\n",
    "    , target.series\n",
    "    , assigntarget_autograde.autograde_value AS autograde\n",
    "    , assigntarget_mileage.mileage * (CASE WHEN measurement_unit_lk.name = 'K' THEN 0.62 ELSE 1 END) AS odometer\n",
    "    , assignment.create_date\n",
    "FROM assign.assignment\n",
    "    JOIN user_management.department \n",
    "        ON department.department_guid = assignment.department_guid\n",
    "    JOIN assign.assign_target \n",
    "        ON assign_target.assignment_id = assignment.assignment_id\n",
    "    JOIN assign.assigntarget_autograde\n",
    "        ON assigntarget_autograde.assign_target_id = assign_target.assign_target_id\n",
    "    JOIN utility.lookup\n",
    "        ON lookup.lookup_guid = assigntarget_autograde.request_type\n",
    "    JOIN assign.assigntarget_mileage \n",
    "        ON assigntarget_mileage.assign_target_id = assign_target.assign_target_id\n",
    "    JOIN assign.mileage_type_lk \n",
    "        ON mileage_type_lk.mileage_type_guid = assigntarget_mileage.mileage_type_guid\n",
    "    JOIN assign.measurement_unit_lk \n",
    "        ON measurement_unit_lk.measurement_unit_guid = assigntarget_mileage.measurement_unit_guid\n",
    "    JOIN assign.target \n",
    "        ON target.target_id = assign_target.target_id\n",
    "WHERE\n",
    "    1 = 1\n",
    "    AND lookup.name = 'Current'\n",
    "    AND assignment.create_date BETWEEN '{start_date}' AND '{end_date}'\n",
    "    AND ({vehicle_specs})\n",
    "\"\"\"\n",
    "\n",
    "price_query = \"\"\"\n",
    "SELECT\n",
    "    src_a_vehicle.vin\n",
    "    , CAST(src_a_vehicle_inventory.inventory_id AS int) AS inventory_number\n",
    "    , CAST(src_a_vehicle_inventory.co_id AS int) AS site_number\n",
    "    , src_a_sale.sale_dt AS sale_date\n",
    "    , MAX(src_a_block_activity.last_bid_amt) AS wholesale_price\n",
    "FROM bi_src.src_a_vehicle_inventory \n",
    "    JOIN bi_src.src_a_vehicle \n",
    "        ON src_a_vehicle.veh_id = src_a_vehicle_inventory.veh_id \n",
    "            AND src_a_vehicle.co_id = src_a_vehicle_inventory.co_id\n",
    "    JOIN bi_src.src_a_sale_lineup_order \n",
    "        ON src_a_sale_lineup_order.inventory_id = src_a_vehicle_inventory.inventory_id \n",
    "            AND src_a_sale_lineup_order.co_id = src_a_vehicle_inventory.co_id\n",
    "    JOIN bi_src.src_a_sale\n",
    "        ON src_a_sale.sale_id = src_a_sale_lineup_order.sale_id\n",
    "            AND src_a_sale.co_id = src_a_sale_lineup_order.co_id\n",
    "    JOIN bi_src.src_a_block_activity\n",
    "        ON src_a_block_activity.sale_line_id = src_a_sale_lineup_order.sale_line_id\n",
    "            AND src_a_block_activity.co_id = src_a_sale_lineup_order.co_id\n",
    "WHERE\n",
    "    1 = 1\n",
    "    AND src_a_block_activity.event = 3\n",
    "    AND ({keys})\n",
    "GROUP BY\n",
    "    src_a_vehicle.vin\n",
    "    , src_a_vehicle_inventory.inventory_id\n",
    "    , src_a_vehicle_inventory.co_id\n",
    "    , src_a_sale.sale_dt\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def run_experiment(start_date, end_date, year, make, model, series, style=None):\n",
    "    # Get inspection data\n",
    "    db_creds = drivin_ds.get_credentials_from_file('/Users/drewfustin/.dbconfig')['adesa-inspections']\n",
    "    dbc = drivin_ds.Database(db_creds)\n",
    "\n",
    "    vehicle_specs = f\"target.model_year = '{year}' AND target.make = '{make}' AND target.model = '{model}' AND target.series = '{series}'\"\n",
    "    if style:\n",
    "        vehicle_specs += f\" AND target.style = '{style}'\"\n",
    "\n",
    "    autogrades = dbc.query(\n",
    "        autograde_query.format(\n",
    "            start_date=start_date,\n",
    "            end_date=end_date,\n",
    "            vehicle_specs=vehicle_specs\n",
    "        )\n",
    "    )\n",
    "\n",
    "    # Get sales data\n",
    "    db_creds = drivin_ds.get_credentials_from_file('/Users/drewfustin/.dbconfig')['adesa-bi']\n",
    "    dbc = drivin_ds.Database(db_creds)\n",
    "\n",
    "    prices = dbc.query(\n",
    "        price_query.format(\n",
    "            keys=\" OR \".join(\n",
    "                [f\"(src_a_vehicle_inventory.inventory_id = {inv} AND src_a_vehicle_inventory.co_id = {site})\" \n",
    "                 for inv, site in autogrades[['inventory_number', 'site_number']].values])\n",
    "        )\n",
    "    ).rename(columns=lambda x: x.lower())\n",
    "\n",
    "    # Join data together and return\n",
    "    df = pd.merge(autogrades, prices, on=['vin', 'inventory_number', 'site_number'])\n",
    "    \n",
    "    # Build a linear model\n",
    "    ag_coef, r2 = run_model(df)\n",
    "    print(\"Simple linear pricing model on only Autograde and Odometer:\")\n",
    "    print(f\"    R^2: {r2}\")\n",
    "    print(f\"    Added value per point of Autograde: ${ag_coef}\")\n",
    "    print()\n",
    "    \n",
    "    # Show Autograde and Odometer scatter plots\n",
    "    plot_scatter(df)\n",
    "    \n",
    "    return df\n",
    "    \n",
    "    \n",
    "def plot_scatter(data):\n",
    "    sns.set_style(\"whitegrid\", {\"xtick.major.size\": 8, \"ytick.major.size\": 8})\n",
    "    fig, (ax_odo, ax_ag) = plt.subplots(1, 2, figsize=(8, 4), dpi=100)\n",
    "    \n",
    "    im_odo = ax_odo.scatter(data['odometer'], data['wholesale_price'], c=data['autograde'], cmap='copper', s=4)\n",
    "    cbar_odo = plt.colorbar(im_odo, ax=ax_odo)\n",
    "    cbar_odo.ax.tick_params(labelsize=8)\n",
    "    cbar_odo.set_label('Autograde', fontsize=8, rotation=270)\n",
    "    ax_odo.set_xlabel('Odometer', fontsize=8)\n",
    "    ax_odo.set_ylabel('Wholesale Price', fontsize=8)\n",
    "    \n",
    "    im_ag = ax_ag.scatter(data['autograde'], data['wholesale_price'], c=data['odometer'], cmap='copper', s=4)\n",
    "    cbar_ag = plt.colorbar(im_ag, ax=ax_ag)\n",
    "    cbar_ag.ax.tick_params(labelsize=8)\n",
    "    cbar_ag.set_label('Odometer', fontsize=8, rotation=270)\n",
    "    ax_ag.set_xlabel('Autograde', fontsize=8)\n",
    "    ax_ag.set_ylabel('Wholesale Price', fontsize=8)\n",
    "    \n",
    "    plt.xticks(fontsize=8)\n",
    "    plt.yticks(fontsize=8)\n",
    "    plt.suptitle((data[['year', 'make', 'model', 'series']] + \" \").sum(axis=1).str.strip().values[0])\n",
    "    plt.show()\n",
    "    \n",
    "\n",
    "def run_model(data):\n",
    "    X = data.dropna()[['autograde', 'odometer']]\n",
    "    y = data.dropna()['wholesale_price']\n",
    "\n",
    "    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)\n",
    "\n",
    "    lr = LinearRegression()\n",
    "    lr.fit(X_train, y_train)\n",
    "    \n",
    "    return int(lr.coef_[0]), np.round(lr.score(X_test, y_test), 2)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Simple linear pricing model on only Autograde and Odometer:\n",
      "    R^2: 0.62\n",
      "    Added value per point of Autograde: $1469\n",
      "\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 800x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>vin</th>\n",
       "      <th>inventory_number</th>\n",
       "      <th>site_number</th>\n",
       "      <th>year</th>\n",
       "      <th>make</th>\n",
       "      <th>model</th>\n",
       "      <th>series</th>\n",
       "      <th>autograde</th>\n",
       "      <th>odometer</th>\n",
       "      <th>create_date</th>\n",
       "      <th>sale_date</th>\n",
       "      <th>wholesale_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1G1BD5SM8H7205748</td>\n",
       "      <td>339259477962658</td>\n",
       "      <td>142</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>4.2</td>\n",
       "      <td>30031.00</td>\n",
       "      <td>2019-08-21 14:38:57</td>\n",
       "      <td>2019-09-17</td>\n",
       "      <td>11500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1G1BE5SM0H7100960</td>\n",
       "      <td>419459401866093</td>\n",
       "      <td>127</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>3.2</td>\n",
       "      <td>117422.00</td>\n",
       "      <td>2019-08-27 21:18:13</td>\n",
       "      <td>2019-09-20</td>\n",
       "      <td>5400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1G1BE5SM0H7136132</td>\n",
       "      <td>188626384940784</td>\n",
       "      <td>142</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>3.0</td>\n",
       "      <td>62263.00</td>\n",
       "      <td>2019-08-15 16:21:35</td>\n",
       "      <td>2019-09-24</td>\n",
       "      <td>8700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1G1BE5SM0H7152332</td>\n",
       "      <td>247295660390511</td>\n",
       "      <td>234</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>4.1</td>\n",
       "      <td>31513.00</td>\n",
       "      <td>2019-08-29 16:23:16</td>\n",
       "      <td>2019-09-13</td>\n",
       "      <td>12300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1G1BE5SM0H7155053</td>\n",
       "      <td>291194502621794</td>\n",
       "      <td>215</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>3.7</td>\n",
       "      <td>16887.00</td>\n",
       "      <td>2019-08-12 15:38:41</td>\n",
       "      <td>2019-08-20</td>\n",
       "      <td>13300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1G1BE5SM0H7155067</td>\n",
       "      <td>339517191997719</td>\n",
       "      <td>202</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>2.0</td>\n",
       "      <td>21071.00</td>\n",
       "      <td>2019-08-08 20:55:46</td>\n",
       "      <td>2019-09-17</td>\n",
       "      <td>11800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1G1BE5SM0H7163346</td>\n",
       "      <td>239925475309717</td>\n",
       "      <td>54</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>3.4</td>\n",
       "      <td>56475.80</td>\n",
       "      <td>2019-08-30 20:18:51</td>\n",
       "      <td>2019-10-31</td>\n",
       "      <td>9700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1G1BE5SM0H7199098</td>\n",
       "      <td>240247598311533</td>\n",
       "      <td>129</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>4.4</td>\n",
       "      <td>8740.00</td>\n",
       "      <td>2019-08-07 12:08:57</td>\n",
       "      <td>2019-08-21</td>\n",
       "      <td>13600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1G1BE5SM0H7199893</td>\n",
       "      <td>533327584907407</td>\n",
       "      <td>15</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>4.4</td>\n",
       "      <td>37470.32</td>\n",
       "      <td>2019-08-26 18:40:27</td>\n",
       "      <td>2019-08-30</td>\n",
       "      <td>13200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1G1BE5SM0H7200816</td>\n",
       "      <td>594376240175561</td>\n",
       "      <td>149</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>3.7</td>\n",
       "      <td>46237.00</td>\n",
       "      <td>2019-08-05 14:36:30</td>\n",
       "      <td>2019-08-06</td>\n",
       "      <td>11250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1G1BE5SM0H7217468</td>\n",
       "      <td>95099177937450</td>\n",
       "      <td>126</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>4.7</td>\n",
       "      <td>4577.00</td>\n",
       "      <td>2019-08-14 12:57:25</td>\n",
       "      <td>2019-08-27</td>\n",
       "      <td>13600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1G1BE5SM0H7231533</td>\n",
       "      <td>409941758448196</td>\n",
       "      <td>215</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>3.7</td>\n",
       "      <td>19969.00</td>\n",
       "      <td>2019-08-30 13:49:38</td>\n",
       "      <td>2019-09-17</td>\n",
       "      <td>12000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1G1BE5SM0H7239812</td>\n",
       "      <td>587779170463707</td>\n",
       "      <td>149</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>2.9</td>\n",
       "      <td>71907.00</td>\n",
       "      <td>2019-08-26 15:05:49</td>\n",
       "      <td>2019-09-17</td>\n",
       "      <td>8300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1G1BE5SM0H7242984</td>\n",
       "      <td>590991807635012</td>\n",
       "      <td>129</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>4.4</td>\n",
       "      <td>33822.00</td>\n",
       "      <td>2019-08-20 16:22:46</td>\n",
       "      <td>2019-09-11</td>\n",
       "      <td>12100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1G1BE5SM0H7243276</td>\n",
       "      <td>550662066662257</td>\n",
       "      <td>211</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>3.4</td>\n",
       "      <td>15716.00</td>\n",
       "      <td>2019-08-27 15:55:57</td>\n",
       "      <td>2019-09-26</td>\n",
       "      <td>12000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1G1BE5SM0H7243925</td>\n",
       "      <td>478059941246975</td>\n",
       "      <td>203</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>4.4</td>\n",
       "      <td>79479.00</td>\n",
       "      <td>2019-08-26 21:35:46</td>\n",
       "      <td>2019-08-28</td>\n",
       "      <td>9600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1G1BE5SM0H7244170</td>\n",
       "      <td>625076668062895</td>\n",
       "      <td>129</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>4.4</td>\n",
       "      <td>23323.00</td>\n",
       "      <td>2019-08-13 18:29:57</td>\n",
       "      <td>2019-08-21</td>\n",
       "      <td>13800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1G1BE5SM0H7244539</td>\n",
       "      <td>247295660390518</td>\n",
       "      <td>234</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>4.1</td>\n",
       "      <td>20288.00</td>\n",
       "      <td>2019-08-29 16:25:04</td>\n",
       "      <td>2019-09-13</td>\n",
       "      <td>13700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1G1BE5SM0H7252480</td>\n",
       "      <td>803687191476964</td>\n",
       "      <td>243</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>3.3</td>\n",
       "      <td>16865.00</td>\n",
       "      <td>2019-08-15 18:02:30</td>\n",
       "      <td>2019-08-28</td>\n",
       "      <td>10600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1G1BE5SM0H7254214</td>\n",
       "      <td>297422203035541</td>\n",
       "      <td>129</td>\n",
       "      <td>2017</td>\n",
       "      <td>CHEVROLET</td>\n",
       "      <td>CRUZE</td>\n",
       "      <td>LT</td>\n",
       "      <td>3.0</td>\n",
       "      <td>13772.00</td>\n",
       "      <td>2019-08-22 20:12:13</td>\n",
       "      <td>2019-09-04</td>\n",
       "      <td>13000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  vin  inventory_number  site_number  year       make  model  \\\n",
       "0   1G1BD5SM8H7205748   339259477962658          142  2017  CHEVROLET  CRUZE   \n",
       "1   1G1BE5SM0H7100960   419459401866093          127  2017  CHEVROLET  CRUZE   \n",
       "2   1G1BE5SM0H7136132   188626384940784          142  2017  CHEVROLET  CRUZE   \n",
       "3   1G1BE5SM0H7152332   247295660390511          234  2017  CHEVROLET  CRUZE   \n",
       "4   1G1BE5SM0H7155053   291194502621794          215  2017  CHEVROLET  CRUZE   \n",
       "5   1G1BE5SM0H7155067   339517191997719          202  2017  CHEVROLET  CRUZE   \n",
       "6   1G1BE5SM0H7163346   239925475309717           54  2017  CHEVROLET  CRUZE   \n",
       "7   1G1BE5SM0H7199098   240247598311533          129  2017  CHEVROLET  CRUZE   \n",
       "8   1G1BE5SM0H7199893   533327584907407           15  2017  CHEVROLET  CRUZE   \n",
       "9   1G1BE5SM0H7200816   594376240175561          149  2017  CHEVROLET  CRUZE   \n",
       "10  1G1BE5SM0H7217468    95099177937450          126  2017  CHEVROLET  CRUZE   \n",
       "11  1G1BE5SM0H7231533   409941758448196          215  2017  CHEVROLET  CRUZE   \n",
       "12  1G1BE5SM0H7239812   587779170463707          149  2017  CHEVROLET  CRUZE   \n",
       "13  1G1BE5SM0H7242984   590991807635012          129  2017  CHEVROLET  CRUZE   \n",
       "14  1G1BE5SM0H7243276   550662066662257          211  2017  CHEVROLET  CRUZE   \n",
       "15  1G1BE5SM0H7243925   478059941246975          203  2017  CHEVROLET  CRUZE   \n",
       "16  1G1BE5SM0H7244170   625076668062895          129  2017  CHEVROLET  CRUZE   \n",
       "17  1G1BE5SM0H7244539   247295660390518          234  2017  CHEVROLET  CRUZE   \n",
       "18  1G1BE5SM0H7252480   803687191476964          243  2017  CHEVROLET  CRUZE   \n",
       "19  1G1BE5SM0H7254214   297422203035541          129  2017  CHEVROLET  CRUZE   \n",
       "\n",
       "   series  autograde   odometer         create_date  sale_date  \\\n",
       "0      LT        4.2   30031.00 2019-08-21 14:38:57 2019-09-17   \n",
       "1      LT        3.2  117422.00 2019-08-27 21:18:13 2019-09-20   \n",
       "2      LT        3.0   62263.00 2019-08-15 16:21:35 2019-09-24   \n",
       "3      LT        4.1   31513.00 2019-08-29 16:23:16 2019-09-13   \n",
       "4      LT        3.7   16887.00 2019-08-12 15:38:41 2019-08-20   \n",
       "5      LT        2.0   21071.00 2019-08-08 20:55:46 2019-09-17   \n",
       "6      LT        3.4   56475.80 2019-08-30 20:18:51 2019-10-31   \n",
       "7      LT        4.4    8740.00 2019-08-07 12:08:57 2019-08-21   \n",
       "8      LT        4.4   37470.32 2019-08-26 18:40:27 2019-08-30   \n",
       "9      LT        3.7   46237.00 2019-08-05 14:36:30 2019-08-06   \n",
       "10     LT        4.7    4577.00 2019-08-14 12:57:25 2019-08-27   \n",
       "11     LT        3.7   19969.00 2019-08-30 13:49:38 2019-09-17   \n",
       "12     LT        2.9   71907.00 2019-08-26 15:05:49 2019-09-17   \n",
       "13     LT        4.4   33822.00 2019-08-20 16:22:46 2019-09-11   \n",
       "14     LT        3.4   15716.00 2019-08-27 15:55:57 2019-09-26   \n",
       "15     LT        4.4   79479.00 2019-08-26 21:35:46 2019-08-28   \n",
       "16     LT        4.4   23323.00 2019-08-13 18:29:57 2019-08-21   \n",
       "17     LT        4.1   20288.00 2019-08-29 16:25:04 2019-09-13   \n",
       "18     LT        3.3   16865.00 2019-08-15 18:02:30 2019-08-28   \n",
       "19     LT        3.0   13772.00 2019-08-22 20:12:13 2019-09-04   \n",
       "\n",
       "    wholesale_price  \n",
       "0             11500  \n",
       "1              5400  \n",
       "2              8700  \n",
       "3             12300  \n",
       "4             13300  \n",
       "5             11800  \n",
       "6              9700  \n",
       "7             13600  \n",
       "8             13200  \n",
       "9             11250  \n",
       "10            13600  \n",
       "11            12000  \n",
       "12             8300  \n",
       "13            12100  \n",
       "14            12000  \n",
       "15             9600  \n",
       "16            13800  \n",
       "17            13700  \n",
       "18            10600  \n",
       "19            13000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cruze = run_experiment('2019-08-01', '2019-09-01', 2017, 'CHEVROLET', 'CRUZE', 'LT')\n",
    "df_cruze.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Simple linear pricing model on only Autograde and Odometer:\n",
      "    R^2: 0.74\n",
      "    Added value per point of Autograde: $804\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>vin</th>\n",
       "      <th>inventory_number</th>\n",
       "      <th>site_number</th>\n",
       "      <th>year</th>\n",
       "      <th>make</th>\n",
       "      <th>model</th>\n",
       "      <th>series</th>\n",
       "      <th>autograde</th>\n",
       "      <th>odometer</th>\n",
       "      <th>create_date</th>\n",
       "      <th>sale_date</th>\n",
       "      <th>wholesale_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2T1BURHE0HC845711</td>\n",
       "      <td>213142088787268</td>\n",
       "      <td>218</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>2.3</td>\n",
       "      <td>25537.00</td>\n",
       "      <td>2019-08-14 16:26:03</td>\n",
       "      <td>2019-09-13</td>\n",
       "      <td>12800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2T1BURHE1HC756066</td>\n",
       "      <td>106437900037525</td>\n",
       "      <td>206</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>2.5</td>\n",
       "      <td>88745.00</td>\n",
       "      <td>2019-08-14 01:39:50</td>\n",
       "      <td>2019-09-05</td>\n",
       "      <td>8600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2T1BURHE1HC797863</td>\n",
       "      <td>592443508497879</td>\n",
       "      <td>211</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>4.0</td>\n",
       "      <td>35483.00</td>\n",
       "      <td>2019-08-15 16:17:45</td>\n",
       "      <td>2019-08-22</td>\n",
       "      <td>14500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2T1BURHE2HC753418</td>\n",
       "      <td>455034646951298</td>\n",
       "      <td>218</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>2.6</td>\n",
       "      <td>28634.00</td>\n",
       "      <td>2019-08-22 13:43:57</td>\n",
       "      <td>2019-09-13</td>\n",
       "      <td>13300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2T1BURHE2HC792879</td>\n",
       "      <td>131846939354296</td>\n",
       "      <td>234</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>2.6</td>\n",
       "      <td>30791.00</td>\n",
       "      <td>2019-08-06 16:35:59</td>\n",
       "      <td>2019-10-11</td>\n",
       "      <td>11200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2T1BURHE2HC874711</td>\n",
       "      <td>349472934334128</td>\n",
       "      <td>216</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>2.8</td>\n",
       "      <td>42435.00</td>\n",
       "      <td>2019-08-02 15:34:06</td>\n",
       "      <td>2019-08-19</td>\n",
       "      <td>12100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2T1BURHE3HC754285</td>\n",
       "      <td>488019995816929</td>\n",
       "      <td>218</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>1.7</td>\n",
       "      <td>25509.00</td>\n",
       "      <td>2019-08-28 13:09:37</td>\n",
       "      <td>2019-09-27</td>\n",
       "      <td>11600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2T1BURHE3HC780496</td>\n",
       "      <td>174607620946238</td>\n",
       "      <td>206</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>4.6</td>\n",
       "      <td>32978.00</td>\n",
       "      <td>2019-08-07 21:06:23</td>\n",
       "      <td>2019-08-15</td>\n",
       "      <td>13200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2T1BURHE4HC785707</td>\n",
       "      <td>74603623740124</td>\n",
       "      <td>218</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>4.2</td>\n",
       "      <td>41965.00</td>\n",
       "      <td>2019-08-22 11:21:48</td>\n",
       "      <td>2019-10-04</td>\n",
       "      <td>12700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2T1BURHE5HC876467</td>\n",
       "      <td>107696331105642</td>\n",
       "      <td>243</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>4.0</td>\n",
       "      <td>34473.00</td>\n",
       "      <td>2019-08-20 00:45:41</td>\n",
       "      <td>2019-08-28</td>\n",
       "      <td>14300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2T1BURHE6HC867003</td>\n",
       "      <td>300432973429015</td>\n",
       "      <td>62</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>4.7</td>\n",
       "      <td>13169.42</td>\n",
       "      <td>2019-08-06 22:42:12</td>\n",
       "      <td>2019-08-08</td>\n",
       "      <td>16100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2T1BURHE6HC897313</td>\n",
       "      <td>136111824987296</td>\n",
       "      <td>203</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>3.3</td>\n",
       "      <td>57200.00</td>\n",
       "      <td>2019-08-09 21:24:41</td>\n",
       "      <td>2019-08-21</td>\n",
       "      <td>11900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2T1BURHE7HC806629</td>\n",
       "      <td>160434241670972</td>\n",
       "      <td>234</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>3.5</td>\n",
       "      <td>38471.00</td>\n",
       "      <td>2019-08-05 18:39:59</td>\n",
       "      <td>2019-08-30</td>\n",
       "      <td>13300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2T1BURHE8HC800306</td>\n",
       "      <td>65807530716117</td>\n",
       "      <td>218</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>3.7</td>\n",
       "      <td>29280.00</td>\n",
       "      <td>2019-08-21 17:51:14</td>\n",
       "      <td>2019-09-09</td>\n",
       "      <td>14200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2T1BURHE8HC957334</td>\n",
       "      <td>168053515824975</td>\n",
       "      <td>216</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>2.7</td>\n",
       "      <td>24420.00</td>\n",
       "      <td>2019-08-22 19:27:51</td>\n",
       "      <td>2019-10-10</td>\n",
       "      <td>12100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2T1BURHE9HC759992</td>\n",
       "      <td>187853321328688</td>\n",
       "      <td>218</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>1.9</td>\n",
       "      <td>41797.00</td>\n",
       "      <td>2019-08-09 20:41:59</td>\n",
       "      <td>2019-09-13</td>\n",
       "      <td>11900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2T1BURHE9HC773150</td>\n",
       "      <td>64699422792878</td>\n",
       "      <td>216</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>2.1</td>\n",
       "      <td>47608.00</td>\n",
       "      <td>2019-08-17 12:25:08</td>\n",
       "      <td>2019-09-05</td>\n",
       "      <td>10700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2T1BURHE9HC798601</td>\n",
       "      <td>666209590568506</td>\n",
       "      <td>234</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>4.0</td>\n",
       "      <td>30228.00</td>\n",
       "      <td>2019-08-28 17:11:04</td>\n",
       "      <td>2019-10-09</td>\n",
       "      <td>11900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2T1BURHE9HC861759</td>\n",
       "      <td>499015112114022</td>\n",
       "      <td>218</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>3.6</td>\n",
       "      <td>13101.00</td>\n",
       "      <td>2019-08-30 17:01:16</td>\n",
       "      <td>2019-11-01</td>\n",
       "      <td>13000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2T1BURHEXHC815356</td>\n",
       "      <td>723306887830412</td>\n",
       "      <td>216</td>\n",
       "      <td>2017</td>\n",
       "      <td>TOYOTA</td>\n",
       "      <td>COROLLA</td>\n",
       "      <td>SE</td>\n",
       "      <td>3.7</td>\n",
       "      <td>32233.00</td>\n",
       "      <td>2019-08-16 17:30:22</td>\n",
       "      <td>2019-09-12</td>\n",
       "      <td>12800</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  vin  inventory_number  site_number  year    make    model  \\\n",
       "0   2T1BURHE0HC845711   213142088787268          218  2017  TOYOTA  COROLLA   \n",
       "1   2T1BURHE1HC756066   106437900037525          206  2017  TOYOTA  COROLLA   \n",
       "2   2T1BURHE1HC797863   592443508497879          211  2017  TOYOTA  COROLLA   \n",
       "3   2T1BURHE2HC753418   455034646951298          218  2017  TOYOTA  COROLLA   \n",
       "4   2T1BURHE2HC792879   131846939354296          234  2017  TOYOTA  COROLLA   \n",
       "5   2T1BURHE2HC874711   349472934334128          216  2017  TOYOTA  COROLLA   \n",
       "6   2T1BURHE3HC754285   488019995816929          218  2017  TOYOTA  COROLLA   \n",
       "7   2T1BURHE3HC780496   174607620946238          206  2017  TOYOTA  COROLLA   \n",
       "8   2T1BURHE4HC785707    74603623740124          218  2017  TOYOTA  COROLLA   \n",
       "9   2T1BURHE5HC876467   107696331105642          243  2017  TOYOTA  COROLLA   \n",
       "10  2T1BURHE6HC867003   300432973429015           62  2017  TOYOTA  COROLLA   \n",
       "11  2T1BURHE6HC897313   136111824987296          203  2017  TOYOTA  COROLLA   \n",
       "12  2T1BURHE7HC806629   160434241670972          234  2017  TOYOTA  COROLLA   \n",
       "13  2T1BURHE8HC800306    65807530716117          218  2017  TOYOTA  COROLLA   \n",
       "14  2T1BURHE8HC957334   168053515824975          216  2017  TOYOTA  COROLLA   \n",
       "15  2T1BURHE9HC759992   187853321328688          218  2017  TOYOTA  COROLLA   \n",
       "16  2T1BURHE9HC773150    64699422792878          216  2017  TOYOTA  COROLLA   \n",
       "17  2T1BURHE9HC798601   666209590568506          234  2017  TOYOTA  COROLLA   \n",
       "18  2T1BURHE9HC861759   499015112114022          218  2017  TOYOTA  COROLLA   \n",
       "19  2T1BURHEXHC815356   723306887830412          216  2017  TOYOTA  COROLLA   \n",
       "\n",
       "   series  autograde  odometer         create_date  sale_date  wholesale_price  \n",
       "0      SE        2.3  25537.00 2019-08-14 16:26:03 2019-09-13            12800  \n",
       "1     SE         2.5  88745.00 2019-08-14 01:39:50 2019-09-05             8600  \n",
       "2      SE        4.0  35483.00 2019-08-15 16:17:45 2019-08-22            14500  \n",
       "3      SE        2.6  28634.00 2019-08-22 13:43:57 2019-09-13            13300  \n",
       "4      SE        2.6  30791.00 2019-08-06 16:35:59 2019-10-11            11200  \n",
       "5      SE        2.8  42435.00 2019-08-02 15:34:06 2019-08-19            12100  \n",
       "6      SE        1.7  25509.00 2019-08-28 13:09:37 2019-09-27            11600  \n",
       "7      SE        4.6  32978.00 2019-08-07 21:06:23 2019-08-15            13200  \n",
       "8      SE        4.2  41965.00 2019-08-22 11:21:48 2019-10-04            12700  \n",
       "9      SE        4.0  34473.00 2019-08-20 00:45:41 2019-08-28            14300  \n",
       "10     SE        4.7  13169.42 2019-08-06 22:42:12 2019-08-08            16100  \n",
       "11     SE        3.3  57200.00 2019-08-09 21:24:41 2019-08-21            11900  \n",
       "12     SE        3.5  38471.00 2019-08-05 18:39:59 2019-08-30            13300  \n",
       "13     SE        3.7  29280.00 2019-08-21 17:51:14 2019-09-09            14200  \n",
       "14     SE        2.7  24420.00 2019-08-22 19:27:51 2019-10-10            12100  \n",
       "15     SE        1.9  41797.00 2019-08-09 20:41:59 2019-09-13            11900  \n",
       "16     SE        2.1  47608.00 2019-08-17 12:25:08 2019-09-05            10700  \n",
       "17     SE        4.0  30228.00 2019-08-28 17:11:04 2019-10-09            11900  \n",
       "18    SE         3.6  13101.00 2019-08-30 17:01:16 2019-11-01            13000  \n",
       "19     SE        3.7  32233.00 2019-08-16 17:30:22 2019-09-12            12800  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_corolla = run_experiment('2019-08-01', '2019-09-01', 2017, 'TOYOTA', 'COROLLA', 'SE')\n",
    "df_corolla.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Simple linear pricing model on only Autograde and Odometer:\n",
      "    R^2: 0.53\n",
      "    Added value per point of Autograde: $831\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>vin</th>\n",
       "      <th>inventory_number</th>\n",
       "      <th>site_number</th>\n",
       "      <th>year</th>\n",
       "      <th>make</th>\n",
       "      <th>model</th>\n",
       "      <th>series</th>\n",
       "      <th>autograde</th>\n",
       "      <th>odometer</th>\n",
       "      <th>create_date</th>\n",
       "      <th>sale_date</th>\n",
       "      <th>wholesale_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19XFB2E53DE056273</td>\n",
       "      <td>523273078895034</td>\n",
       "      <td>234</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>4.0</td>\n",
       "      <td>80476.0</td>\n",
       "      <td>2019-08-16 16:44:46</td>\n",
       "      <td>2019-09-18</td>\n",
       "      <td>7600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19XFB2E53DE056273</td>\n",
       "      <td>523273078895034</td>\n",
       "      <td>234</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>4.0</td>\n",
       "      <td>80476.0</td>\n",
       "      <td>2019-08-16 16:44:46</td>\n",
       "      <td>2019-10-18</td>\n",
       "      <td>5400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19XFB2F50DE011273</td>\n",
       "      <td>279825720384398</td>\n",
       "      <td>128</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>1.3</td>\n",
       "      <td>114955.0</td>\n",
       "      <td>2019-08-15 18:52:48</td>\n",
       "      <td>2019-09-10</td>\n",
       "      <td>3600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19XFB2F50DE023827</td>\n",
       "      <td>142386766912607</td>\n",
       "      <td>128</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>1.6</td>\n",
       "      <td>107693.0</td>\n",
       "      <td>2019-08-15 20:00:24</td>\n",
       "      <td>2019-09-16</td>\n",
       "      <td>4800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19XFB2F50DE031166</td>\n",
       "      <td>370483891178535</td>\n",
       "      <td>244</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>1.8</td>\n",
       "      <td>102933.0</td>\n",
       "      <td>2019-08-28 14:55:04</td>\n",
       "      <td>2019-09-23</td>\n",
       "      <td>5100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>19XFB2F50DE032463</td>\n",
       "      <td>251749526125301</td>\n",
       "      <td>247</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>1.9</td>\n",
       "      <td>121897.0</td>\n",
       "      <td>2019-08-23 11:56:19</td>\n",
       "      <td>2019-09-20</td>\n",
       "      <td>4800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>19XFB2F50DE043950</td>\n",
       "      <td>300716441297962</td>\n",
       "      <td>128</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2019-08-07 13:40:10</td>\n",
       "      <td>2019-08-27</td>\n",
       "      <td>4300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>19XFB2F50DE268031</td>\n",
       "      <td>308906958980157</td>\n",
       "      <td>243</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>3.2</td>\n",
       "      <td>192077.0</td>\n",
       "      <td>2019-08-16 14:43:54</td>\n",
       "      <td>2019-10-09</td>\n",
       "      <td>2600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>19XFB2F52DE020296</td>\n",
       "      <td>523157103010509</td>\n",
       "      <td>207</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>1.9</td>\n",
       "      <td>92265.0</td>\n",
       "      <td>2019-08-21 14:17:48</td>\n",
       "      <td>2019-10-29</td>\n",
       "      <td>5800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>19XFB2F52DE024428</td>\n",
       "      <td>377093851701688</td>\n",
       "      <td>247</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>3.6</td>\n",
       "      <td>70429.0</td>\n",
       "      <td>2019-08-28 12:36:27</td>\n",
       "      <td>2019-09-20</td>\n",
       "      <td>7700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>19XFB2F52DE090543</td>\n",
       "      <td>175745781728010</td>\n",
       "      <td>215</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>2.8</td>\n",
       "      <td>65039.0</td>\n",
       "      <td>2019-08-27 21:19:02</td>\n",
       "      <td>2019-09-17</td>\n",
       "      <td>7200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>19XFB2F52DE202872</td>\n",
       "      <td>315388073910809</td>\n",
       "      <td>216</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>1.8</td>\n",
       "      <td>69407.0</td>\n",
       "      <td>2019-08-14 12:17:41</td>\n",
       "      <td>2019-08-22</td>\n",
       "      <td>5700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>19XFB2F52DE293173</td>\n",
       "      <td>126349381329108</td>\n",
       "      <td>234</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>2.8</td>\n",
       "      <td>123466.0</td>\n",
       "      <td>2019-08-28 14:10:42</td>\n",
       "      <td>2019-09-27</td>\n",
       "      <td>4700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>19XFB2F53DE232043</td>\n",
       "      <td>128428132579944</td>\n",
       "      <td>206</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>2.9</td>\n",
       "      <td>133914.0</td>\n",
       "      <td>2019-08-07 23:53:11</td>\n",
       "      <td>2019-08-15</td>\n",
       "      <td>4500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>19XFB2F53DE253054</td>\n",
       "      <td>219833638045975</td>\n",
       "      <td>240</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>2.8</td>\n",
       "      <td>98384.0</td>\n",
       "      <td>2019-08-20 19:06:26</td>\n",
       "      <td>2019-08-27</td>\n",
       "      <td>7400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>19XFB2F53DE259338</td>\n",
       "      <td>357135130747518</td>\n",
       "      <td>208</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>2.0</td>\n",
       "      <td>132471.0</td>\n",
       "      <td>2019-08-02 14:09:00</td>\n",
       "      <td>2019-08-08</td>\n",
       "      <td>4500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>19XFB2F53DE269433</td>\n",
       "      <td>347424218786380</td>\n",
       "      <td>251</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>2.3</td>\n",
       "      <td>93517.0</td>\n",
       "      <td>2019-08-27 12:44:56</td>\n",
       "      <td>2019-09-11</td>\n",
       "      <td>6700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>19XFB2F54DE013673</td>\n",
       "      <td>388088967955656</td>\n",
       "      <td>247</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>2.7</td>\n",
       "      <td>60626.0</td>\n",
       "      <td>2019-08-14 13:16:48</td>\n",
       "      <td>2019-09-06</td>\n",
       "      <td>7000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19XFB2F54DE096019</td>\n",
       "      <td>603142268625043</td>\n",
       "      <td>142</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>2.9</td>\n",
       "      <td>87003.0</td>\n",
       "      <td>2019-08-20 15:38:32</td>\n",
       "      <td>2019-11-12</td>\n",
       "      <td>5200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19XFB2F54DE242581</td>\n",
       "      <td>552564733766688</td>\n",
       "      <td>142</td>\n",
       "      <td>2013</td>\n",
       "      <td>HONDA</td>\n",
       "      <td>CIVIC SDN</td>\n",
       "      <td>LX</td>\n",
       "      <td>4.2</td>\n",
       "      <td>48523.0</td>\n",
       "      <td>2019-08-27 14:41:18</td>\n",
       "      <td>2019-09-24</td>\n",
       "      <td>10100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  vin  inventory_number  site_number  year   make      model  \\\n",
       "0   19XFB2E53DE056273   523273078895034          234  2013  HONDA  CIVIC SDN   \n",
       "1   19XFB2E53DE056273   523273078895034          234  2013  HONDA  CIVIC SDN   \n",
       "2   19XFB2F50DE011273   279825720384398          128  2013  HONDA  CIVIC SDN   \n",
       "3   19XFB2F50DE023827   142386766912607          128  2013  HONDA  CIVIC SDN   \n",
       "4   19XFB2F50DE031166   370483891178535          244  2013  HONDA  CIVIC SDN   \n",
       "5   19XFB2F50DE032463   251749526125301          247  2013  HONDA  CIVIC SDN   \n",
       "6   19XFB2F50DE043950   300716441297962          128  2013  HONDA  CIVIC SDN   \n",
       "7   19XFB2F50DE268031   308906958980157          243  2013  HONDA  CIVIC SDN   \n",
       "8   19XFB2F52DE020296   523157103010509          207  2013  HONDA  CIVIC SDN   \n",
       "9   19XFB2F52DE024428   377093851701688          247  2013  HONDA  CIVIC SDN   \n",
       "10  19XFB2F52DE090543   175745781728010          215  2013  HONDA  CIVIC SDN   \n",
       "11  19XFB2F52DE202872   315388073910809          216  2013  HONDA  CIVIC SDN   \n",
       "12  19XFB2F52DE293173   126349381329108          234  2013  HONDA  CIVIC SDN   \n",
       "13  19XFB2F53DE232043   128428132579944          206  2013  HONDA  CIVIC SDN   \n",
       "14  19XFB2F53DE253054   219833638045975          240  2013  HONDA  CIVIC SDN   \n",
       "15  19XFB2F53DE259338   357135130747518          208  2013  HONDA  CIVIC SDN   \n",
       "16  19XFB2F53DE269433   347424218786380          251  2013  HONDA  CIVIC SDN   \n",
       "17  19XFB2F54DE013673   388088967955656          247  2013  HONDA  CIVIC SDN   \n",
       "18  19XFB2F54DE096019   603142268625043          142  2013  HONDA  CIVIC SDN   \n",
       "19  19XFB2F54DE242581   552564733766688          142  2013  HONDA  CIVIC SDN   \n",
       "\n",
       "   series  autograde  odometer         create_date  sale_date  wholesale_price  \n",
       "0      LX        4.0   80476.0 2019-08-16 16:44:46 2019-09-18             7600  \n",
       "1      LX        4.0   80476.0 2019-08-16 16:44:46 2019-10-18             5400  \n",
       "2      LX        1.3  114955.0 2019-08-15 18:52:48 2019-09-10             3600  \n",
       "3      LX        1.6  107693.0 2019-08-15 20:00:24 2019-09-16             4800  \n",
       "4      LX        1.8  102933.0 2019-08-28 14:55:04 2019-09-23             5100  \n",
       "5      LX        1.9  121897.0 2019-08-23 11:56:19 2019-09-20             4800  \n",
       "6      LX        2.1       1.0 2019-08-07 13:40:10 2019-08-27             4300  \n",
       "7      LX        3.2  192077.0 2019-08-16 14:43:54 2019-10-09             2600  \n",
       "8      LX        1.9   92265.0 2019-08-21 14:17:48 2019-10-29             5800  \n",
       "9      LX        3.6   70429.0 2019-08-28 12:36:27 2019-09-20             7700  \n",
       "10     LX        2.8   65039.0 2019-08-27 21:19:02 2019-09-17             7200  \n",
       "11     LX        1.8   69407.0 2019-08-14 12:17:41 2019-08-22             5700  \n",
       "12     LX        2.8  123466.0 2019-08-28 14:10:42 2019-09-27             4700  \n",
       "13     LX        2.9  133914.0 2019-08-07 23:53:11 2019-08-15             4500  \n",
       "14     LX        2.8   98384.0 2019-08-20 19:06:26 2019-08-27             7400  \n",
       "15     LX        2.0  132471.0 2019-08-02 14:09:00 2019-08-08             4500  \n",
       "16     LX        2.3   93517.0 2019-08-27 12:44:56 2019-09-11             6700  \n",
       "17     LX        2.7   60626.0 2019-08-14 13:16:48 2019-09-06             7000  \n",
       "18     LX        2.9   87003.0 2019-08-20 15:38:32 2019-11-12             5200  \n",
       "19     LX        4.2   48523.0 2019-08-27 14:41:18 2019-09-24            10100  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_civic = run_experiment('2019-08-01', '2019-09-01', 2013, 'HONDA', 'CIVIC SDN', 'LX')\n",
    "df_civic.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Simple linear pricing model on only Autograde and Odometer:\n",
      "    R^2: 0.79\n",
      "    Added value per point of Autograde: $1688\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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++IOEhIQsH9yRnXv37jF16tRMD53Zt28ftra22f4h3L17t94gvidPnhATE/NK3J0aPnw4t27dYu7cuVl2H3n48CGRkZE52tfIkSMpVqwYCxYs4MGDB0D6Q1IePHjA+++/T5MmTfReXbt2pXLlymzduvW5fYL79+9Pw4YNdQ/2yakVK1aQkpJC7969sy1TpUoV3N3dWblypW62mmetXr2a6OhounbtatCxjc3b25uqVauydu1a3YBWtVrNsGHDCAkJ0ftgkyEpKYmJEydSpEgR+vbtm+2+VSoV/v7+2NraMnbsWGJjY/PtPPKbp6cncXFxLF++nIcPH2Y7oPVlEBYWxs8//0z37t0L7AO5EK8S6S4iRD6KiorSDd774IMPuHDhgt76cuXK4ejoSN++fdm0aRMffvghw4YNIzY2lq+++gp3d3fq1auX4+M1btxY95TGxMREKlasyG+//UZAQAC+vr7Z3h1u27Yts2fPZuXKlbi5ubF161a0Wm2meZXj4+M5c+ZMtsevVauWrn9tcnLyc8tWrVo104NAcqNZs2ZMnjyZ2bNnc+bMGbp3746LiwuJiYkcPXqUHTt28OTJE91T9Z7Hzs6OUaNG8cUXX7Bw4UKmT5/Ojh07cHR0pFmzZllu07VrV+bPn09ISAhvv/12lmWe7TaSlZiYGF1dpaWlcf/+fYKDg9mzZw9Dhgx54df606ZNY8CAAfTs2ZP+/ftTt25dEhISdPvo2bMnXl5eLzz/53k2xn9Tq9XUrl37udtrNBomTpzIwIEDmTlzJmvWrAGgd+/eXLlyhS+//JKjR4/i6enJG2+8wdWrV9mwYQNRUVEsWrTohf2hnZ2dmTJlCmPGjMHPz0+v+1FBXrdnzpxh/fr1mZa3aNEiR99KlS1bFjc3N1avXs27776br1MvPu88K1SooNelLaOsoigkJCQQGhrK+vXrqVChAiNGjMi3GIV4lUmSLUQ+OnToEElJSdy+fTvTg00A3SORHR0d2bhxI7Nnz2bs2LHY2tri4eGhe2BHTpmZmbF8+XKWLFnCunXriIqKoly5ckyfPv25D0Xp168fsbGxbN68maVLl1KpUiXd/5914cKF595VPXLkiK5vclRU1HPLbt++3Wh9X/v27UujRo34/vvvWbduHXfv3sXMzAwXFxc++OADevfuneNBa927d2fLli1s27aNrl27cvjwYfr06ZPt4LzOnTuzYMECNm/enG2SDekzZIwaNYo5c+ZkWnfo0CFddw+NRkOxYsWoWrUqK1as4J133nlhzKVKlWLLli1s2LCBvXv3smrVKszNzalYsSJfffWVUbocPBvjv9nY2HD69OkX7qNZs2a0b9+e4OBgfv75Z9q2bQvAxIkTefvttwkMDGTq1KnExcXpHqs+YMCALB9Pn5VOnTpx8OBB9uzZw8aNG3UfrAryug0JCSEkJCTT8jlz5uS461eHDh0IDQ3N964izzvPb775Bg8PjyzLOjg4UKpUKQYNGkTfvn0zDRQWQqRTKfk58acQQgghhBAmSPpkCyGEEEIIYWSSZAshhBBCCGFkkmQLIYQQQghhZJJkCyGEEEIIYWSSZAshhBBCCGFkkmQLIYQQQghhZJJkCyGEEEIIYWSSZAshhBBCCGFkkmQLIYQQQghhZJJkCyGEEEIIYWSSZAshhBBCCGFkkmQLIYQQQghhZJJkCyGEEEIIYWSSZAshhBBCCGFkkmQLIYQQQghhZJJkCyGEEEIIYWSSZAshhBBCCGFkkmQLIYQQQghhZJJkCyGEEEIIYWSSZAshhBBCCGFkkmQLIYQQQghhZJJkCyGEEEIIYWSSZAshhBBCCGFkkmQLIYQQQghhZJJkCyGEEEIIYWSSZAshhBBCCGFkmsIO4FWg1WpJTU1FrVajUqkKOxwhTI6iKGi1WjQaDWq14fcGtFotiqLk6tgqlSpXxxT6pB0VovDlpS2VdtRwkmTnQGpqKqGhoYUdhhAmz83NDQsLC4O20Wq1hJ46QqrKKlfH1Gg0uLm5meQfCGOSdlSIl4ehbam0o7kjSXYOZFwUbm5umJmZFXI0r6a0tDRCQ0OlDvPAlOsw49xz00ArikKqygq35J8wI9Ww46IhlHa5vnsjnjKkHTXlaz2/Sd3mn1ehbnPblko7mjuSZOdAxlebZmZmL+0/nFeF1GHemXId5qWbgRmpBv9xEMaTm3bUlK/1/CZ1m39ehbrNbVsq7ahhTOu+vRBCCCGEEAVA7mQLIUyDogCGfl1pel9vCiFEtqQdNYgk2UII02C67bwQQhiHtKMGkSRbCGEa5A6MEELkjbSjBpE+2UIIIYQQQhiZ3MkWQpgGuQMjhBB5I+2oQQo0yb548SL+/v6cP38ec3NzmjdvzoQJE1i0aBG7d+/WK5uUlMRbb73FmjVr0Gq1NGjQAEVR9KadOXz4MDY2Nty/f5/Jkydz7NgxzMzM6Ny5M+PHj0ejST+9v/76i5kzZ3L58mWKFi3Kp59+Ss+ePQvy1IUQQgghhAkpsCQ7KSkJHx8fevXqxX/+8x8SEhIYP348EydOZMWKFUyfPl1XNiQkhDFjxjBhwgQALl++TEpKCqdOncryCUUjR46kRIkS/PHHH0RHR/Ppp5+yfv16fHx8ePjwIYMHD2b48OH07t2b48ePM3ToUKpVq0bt2rUL6vSFEIXNRG6mrFu3ju3bt6NWq6lVqxbvv/8+kydP1q2PjY0F4NChQ1y9epUePXpQtmxZAIoVK8aaNWtQFIV58+Zx8OBB1Go106dPp2HDhgCsXbuWrVu3oigKo0ePpn379gV/kkKIwmEi7aixFFiSHRERgaurK0OHDsXMzAwLCwt69+6Nr6+vXrmYmBjGjh3LF198QZUqVQAIDQ2lWrVqWSbY169f59ixY/z+++9YW1tTtmxZPvvsM7766it8fHz46aefcHBwoF+/fgA0a9YMLy8vAgMDJclOTYJbf0BaEpRsAjZOhR2REPnHBL7mPHv2LEFBQWzbtg1ra2t8fX05deoUP/zwAwBPnjyhZ8+ejBs3Tle+W7duTJo0SW8/wcHB/PPPP+zbt4/r16/j4+PDgQMHCAsLY9euXezatYuEhAR69uxJo0aNcHR0LPBzFcIU3b5xjV2b1mJlbUPPj4Zg/0bRgg3ABNpRYyqwJLtixYqsXr1ab1lwcDA1a9bUWzZ//nxq1apF586ddctCQ0N58uQJ3bt35/bt21SqVIkxY8ZQv359Ll26hIODAyVKlNCVr1SpEhEREcTFxXHp0iWqVq2qd4zKlSuzfft2g88hLS3N4G1eZuqLWyD2SvqbqFC09UeCmWW+HCuj7l63OixIplyHRjlnE2jn7e3tmTx5MjY2NgC4uroSERGhW79mzRpq1qzJ22+/DcC5c+e4cOECXbp0wcHBgUmTJlGlShUOHTqEl5cXarUaFxcXypQpw8mTJzlx4gTt2rXDysoKKysrmjZtysGDB+nevXuOY8zJ79KUr/X8JnWbf/K7bp8kJTG6fzcexj4AReHCXyeZt2aLQfvIc2wm0I4aU6EMfFQUhUWLFnHw4EE2bdqkW37z5k1+/PFHtm3bplfeysqK2rVrM2LECN544w0CAwMZNGgQP/74IwkJCVhbW+uVz3j/+PHjLNdbWVnx+PFjg+MODQ01eJuXWd3EcMwy/sWkJvL3X0dIVDvk6zFftzosDFKHufX634GpUKECFSpUAOD+/fsEBgYye/ZsAOLj49m0aRM7d+7UlbeysqJr16706NGDkJAQhg4dyt69e4mMjMTJ6ek3W8WLFycqKorIyEjc3NwyLTeEIdevXOv5R+o2/+RX3Ubdvc2D+9G69xf+OsmZM2fy5VjZe/3bUWMq8CQ7Pj4ePz8/zp8/z6ZNm6hWrZpu3Y4dO6hXrx7Vq1fX2yajb3aGQYMGERQUxKFDhyhRogSJiYl66zPe29raYm1tzaNHj/TWJyUlYWtra3Dsbm5umJmZGbzdy0r1zxWU+6GACiyKUK1OczAzz5djpaWlERoa+trVYUEy5TrMOPc8MaF2/tatW3zyySf07NmTpk2bArB7927c3d31vvUbO3as7md3d3esra25cuUKWq1Wb5C5oiio1Wq0Wm2mY6nVhs0Em5Pr15Sv9fwmdZt/8rtuU1Jq8H2Z8tyNuImiKDR+uzV169bNVYy5ZkLtqDEUaJJ948YNPv74Y0qVKsX27dsz9eP76aef+OijjzJtt3DhQtq3b0+NGjV0y5KTk7G0tKRKlSrExsYSHR1NsWLFALhy5QrOzs4UKVKEqlWrcvjwYb39Xb58Wdff2xBmZmavV6NUrRvcKw+pieBUHzMLq3w/5GtXh4VA6lA8T1hYGIMHD2bw4MF4e3vrlv/88898+OGHemVXr15Nnz59sLOzA0Cr1aLRaHB2diYyMlJXLjo6GicnJ5ydnfXuXEdFReHi4mJQfIZcv3Kt5x+p2/yTX3VrZmbNok27OLBzM1bWNnTo/r78Dl9yBfYwmocPHzJgwADq16/PmjVrMiXYDx484MqVKzRq1CjTtv/88w+zZs0iKiqK5ORkli5dSnx8PO+++y4VKlSgQYMGzJ49m/j4eG7evMny5cvp0aMHAO+++y7R0dGsX7+elJQU/vvf/7J7926D+hC+ttSa9AGPZVuBpX1hRyNE/lKU3L1eITExMfj4+DB58mS9BFtRFEJDQ2nQoIFe+aNHj+rGpxw5coS0tDQqVqyIu7s7P/74I2lpaVy7do3w8HDc3Nxwd3fnwIEDPH78mPv373PkyBGaNWtWoOcohCkr+mYx3vcZxnv9PsLSyvrFGxibCbSjxlRgd7KDgoKIiIhg//79HDhwQG/d6dOnuXXrFoDeV5kZ5syZg7+/P126dCExMRE3NzfWrVuHg0N6/+HFixczffp02rRpg1qtpmvXrnz22WcAFC1alLVr1zJr1iwWL16Mo6MjkyZN0n2FKoQwESbQzm/YsIH4+HiWLVvGsmXLAGjVqhX9+/fH3Nw80/iUqVOnMnHiRLZv346lpSULFixArVbj4eHB2bNn8fLyQqVSMWvWLN3YmIw+3GlpaYwYMSLLNlsI8ZoygXbUmFSKYsIfMXIoLS2NM2fOULduXflqJpekDvPOlOswL+eu2/bBTsxINWxbNJwp+p5J1rmxGfI7NOVrPb9J3eafV6FucxujtKO5U2DdRYQQQgghhDAVhTKFnxBCFDh5iIIQQuSNtKMGkSRbCGE6DG3rVS8uIoQQJkXa0RyTJFvkiPb2BVLP7AELG8yb9EZlX7ywQxJCCCGM7tC+IP5vx3c4l6vAwFGTsbN/o7BDEq8oSbLFCylJ8aT83xLQpoFKRUpCDBZdvyzssIQwTK6mkjLdrzmFMEVXL55j2bRxAFy+8BcoCsOmfl3IUb1EpB01iCTZ4oWUxIeg/d9oYkVBeWTYY5SFEEKIV8G92zd0P2u1WiJuXCvEaMSrTmYXES+keqMkquJPn+pm5tqq8IIRIrfkIQpCiBdwa9ScN52cde/ffa9vIUbzEpJ21CByJ1u8kEqtxtxzHNpboagsrFGVdC3skIQwXG4GxQshTIqd/Rt8tWkvZ48fpkTpslSqXruwQ3q5SDtqELmTLXJEpTHHrEJ91KWqo1KZ8FBh8eqSOzBCiBywe8OBt9p2lAQ7KwXUjsbHx+Pl5aV7Gvju3bvx8vLCy8uLoUOH8vDhQwAiIiLo168fHh4eDBkyhPj4eADi4uIYPHgwnp6e9OvXj8jISACSk5MZN24cnp6evPfee1y5cuV/p6Xg7++Ph4cHHTp04MSJE8aoLUmyhRBCCCHEy+Gvv/6iX79+XLuW3h/+3r17fPXVV2zYsIHdu3dTuXJllixZAsC0adPo3bs3Bw4cwM3NjaVLlwKwaNEi6tWrx/79++nZsyczZswAICAgAEtLS/bv38/EiRMZNy59kGtwcDD//PMP+/btY9myZYwfP56UlJQ8n4sk2UII06Dk8iWEECJdAbSjmzdvZvLkyTg5OQGgUqmYPn06jo6OAFSvXp07d+6QkpLC8ePH8fT0BKBbt24EBwcD8Ntvv9GlSxcAOnXqREhICMnJyXrLGzVqRFxcHDdv3uTQoUN4eXmhVqtxcXGhTJkynDx5MpeV9JT0yRZCmAh5UowpfQ0AACAASURBVJkQQuRN7tvR+Ph4zMzMdEstLCywsLDIVHrOnDl6752cnHQJd2JiIitXrqRfv348ePAAOzs7zM3NAShevDhRUemzn0VGRuq20Wg0FClShAcPHugtf3ab7JbnlSTZQgjTIHemhRAib/LQjrZs2ZLExETd+2HDhvH555/nePsHDx4wdOhQatSoQffu3bl3716mMWLZjRlTFAW1Wo2iKHplMpZrtdosl+eVJNlCCNMgD1EQQoi8yUM7eujQoUx3snPq9u3bDBo0iDZt2jB27FgAHB0defToEampqWg0GqKionR3o52cnIiOjsbZ2ZnU1FQSEhJwcHCgRIkSREZGUq5cOQCio6NxcnLC2dlZNzjy2eV5JX2yhRCmQfpkCyFE3uShHbWzs9N75TTJTk5OZtCgQfTp04dx48bp7jibm5vTsGFD9u7dC0BQUBDu7u5A+l3zoKAgAPbs2UPDhg0xNzenZcuW7Ny5E4ATJ05gaWlJqVKlcHd358cffyQtLY1r164RHh6Om5tbHitL7mQLIUyKZM1CCJE3BduO7tq1ixs3brBz505dglyjRg3mzJnDlClTmDBhAv/5z38oWbIkCxYsAGDEiBFMmDCBjh07UqRIEebPnw+At7c3X375JR07dsTc3Jx58+YB4OHhwdmzZ/Hy8kKlUjFr1iysrKzyHLsk2UIIIYQQ4qXy66+/AtCrVy969eqVZZnSpUsTEBCQabmDgwMrVqzItNzS0hJ/f/9My1UqFePHj2f8+PF5jFqfJNlCCNMg3T+EECJvpB01iCTZQgjTIAMfhRAib6QdNYgk2UII0yB3YIQQIm+kHTWIJNlCCNMgd2CEECJvpB01iCTZIn8k3ofrv6T/YyzXCqyKFXZEQgghxCvt+t/nOPDdKiytbej80XAcnUoWdkjiOSTJFsanKHBuPTx5mP4+LhwajCrMiIQoUP7+/jx48IC5c+cWdihCiNdEUmICi8YO4knSY1RARPglJq7YXthhieeQh9EI41NS4Uksus5bKfGQmlTYUQlTl/E1p6EvAx05ckQ3l6sQQhhL3P1okh7Ho2i1aLVa7oRfKfggCqgdfV1Iki2MT20Ojq5P379RETQ2T98rCiTHgza14GMTpqsAnvgYGxvLwoULGTJkiNHCFkIIgGIly1C2Sg3d+8ZtOhZ8EPLkXINIdxGRP1z7wP3zoGihWE1Q0h+DijYNLn4HD/4BMyuo1R+KlC3cWIVpyMOAnfj4eMzMzHRLLSwssnwk8JdffsmoUaO4c+dOXiIVQohM1GZm1GrQjHtXL6I2M8O1XuOCD0IGPhqkQO9kX7x4kQ8//JDGjRvTvHlzfH19iYmJAWDKlCnUqlWLevXq6V5btmzRbbtq1Src3d2pW7cu3t7eXL16Vbfu8ePH+Pn50aRJExo0aICvry8JCQm69deuXWPAgAHUq1ePFi1aZPkUIGFkajMoXhuc6qbf2c4Qeyk9wQZIewLhPxdOfEIYoGXLljRo0ED3+s9//pOpzLZt2yhZsiTNmjUrhAiFEK+72Kh7HAragMZMjRqFXSvmFXZI4gUKLMlOSkrCx8eHevXqERISwp49e4iNjWXixIkAhIaGMmPGDE6fPq179e7dG4CdO3cSEBDAmjVrOHr0KDVr1mT48OEo//s0NWPGDO7cuUNwcDA//fQTd+7c0T2nPiUlhSFDhuDm5sbRo0dZuXIlgYGB7N+/v6BOXTxLZfb890Lklzz0JTx06BAnT57UvT755JNMu9+3bx+HDx+mS5cuLF68mF9//ZWZM2cW9Fmybt06OnbsiJeXF35+fiQnJ7N582ZatGhBly5d6NKlCwsXLgQgLi6OwYMH4+npSb9+/YiMjAQgOTmZcePG4enpyXvvvceVK+l9PxVFwd/fHw8PDzp06MCJEycK/PyEMFVqs2f/XqowMyuEzgjSJ9sgBZZkR0RE4OrqytChQ7GwsKBo0aL07t2b48ePk5yczD///EOtWrWy3Hbr1q307duXKlWqYGlpyZgxY4iIiODo0aMkJiaye/duhg8fjoODA2+++SZjx44lKCiIxMREjh8/TmRkJMOHD8fCwoIaNWrg7e1NYGBgQZ26eJZDJXCql/6zhT24tC/ceITpyENfQjs7O71XVl1F1q1bx549e/jhhx8YPnw4rVu3ZtKkSfl/Xs84e/YsQUFBbNu2jR9//JHU1FS+++47zp49y5QpU/jhhx/44YcfGDUqfbafRYsWUa9ePfbv30/Pnj2ZMWMGAAEBAVhaWrJ//34mTpzIuHHjAAgODuaff/5h3759LFu2jPHjx5OSklKg5yiEqbJ3LIaXz2jUZhosrW3oPWpqwQchfbINUmBJdsWKFVm9erVev8bg4GBq1qzJxYsXSU1NZfHixbz11lu0b9+elStXotVqAbh8+TJVq1bVbWdubk6FChW4ePEi169fJyUlRW99pUqVSEpKIjw8nEuXLuHi4qL3R7Fy5cpcvHixAM5aZKJSQ9Vu8NZUaDQGbEsUdkRCvDbs7e2ZPHkyNjY2qFQqXF1diYiIIDQ0lC1btuDl5YWvry9xcXEA/Pbbb3Tp0gWATp06ERISQnJyst7yRo0aERcXx82bNzl06BBeXl6o1WpcXFwoU6YMJ0+eLLTzFcLUtOo+gLk/HGXm9hBqNm1V2OGIFyiUgY+KorBo0SIOHjzIpk2biI6OpnHjxnh7e7NgwQLCwsIYOnQoarUaHx8fEhISsLa21tuHlZUVjx8/Jj4+HgAbm6ezV2SUTUhIyHJba2trHj9+bHDcaWlpBm8j0mXUnV4dKtpCiubVlGUdmgjjnHMuvrZU5e4WTLdu3ejWrVuuts2LChUqUKFCBQDu379PYGAgs2bNIjw8nM8++4w6deqwcOFCZs6cybx584iMjMTJyQkAjUZDkSJFePDggd5ygOLFixMVFZXtckPk5Hdpytd6fpO6zT8FV7cqFEXJ1XHyHlvBtaOvgwJPsuPj4/Hz8+P8+fNs2rSJatWqUa1aNZo3b64rU7t2bQYMGMC+ffvw8fHB2tqapCT9eZaTkpKwtbXVJdeJiYnY2trqfob0r3htbGx07zM8W9YQoaGhBm8j9Ekd5p3UYS7l5mvLV/Rvw61bt/jkk0/o2bMnzZo10xuM6ePjQ9u2bbPcTlEU1Go1iqKgUqkyLddqtVkuN4Qh169c6/lH6jb/vNZ1a0LtqDEUaJJ948YNPv74Y0qVKsX27dtxdHQE4OeffyY6Opo+ffroyiYnJ2NlZQVAlSpVuHTpEu+88w6QPpgxPDycqlWr4uLigrm5OZcvX6ZOnToAXLlyRdel5P79+4SHh5OamopGk366ly9fpkqVKgbH7+bmptfdReRcWloaoaGhUod5YMp1mHHueWMafx3CwsIYPHgwgwcPxtvbm5iYGPbu3Yu3tzeQXpcZ14+TkxPR0dE4OzuTmppKQkICDg4OlChRgsjISMqVKwdAdHQ0Tk5OODs76wZHPrvcEDm5fk35Ws9vUrf551Wo27y3pabRjhpLgSXZDx8+ZMCAATRt2pRZs2bp3f1QFIU5c+ZQvnx5mjZtypkzZ9i4cSN+fn4AdO/enSVLluDu7o6LiwsLFy6kWLFiNGzYEHNzczw9PZk/fz7ffPMNAPPnz6dTp05YWVnRpEkTihYtytdff83IkSO5du0aAQEBuoE/hjAzM3tp/+G8KqQO807qMJdM4G9DTEwMPj4+TJkyhXbt2gFga2vLsmXLqFevHrVq1SIgIIB3330XSJ+aMCgoiM8++4w9e/bo2tSWLVuyc+dOGjZsyIkTJ7C0tKRUqVK4u7uzfft2OnXqxI0bNwgPD8fNzc2gGA25fuVazz9St/nnta5bE2hHjanAkuygoCAiIiLYv38/Bw4c0Ft3+vRp/Pz8mDp1Kvfu3aNYsWJ8/vnnuoE3PXr04NGjRwwdOpSYmBjc3Nz4z3/+g7l5+vzLU6ZMwd/fHy8vL1JSUmjTpg2TJ09OP0GNhrVr1zJ9+nSaN2+OjY0N3t7ehdJfUghRiHIzldQrNvXUhg0biI+PZ9myZSxbtgyAVq1asXDhQiZNmkRSUhIVK1bE398fgBEjRjBhwgQ6duxIkSJFdFOfent78+WXX9KxY0fMzc2ZNy99Pl4PDw/Onj2Ll5cXKpWKWbNm6b5xFEKYABNoR41JpSgmfPY5lJaWxpkzZ6hbt+7zP50+vg9JsfBGOTAzz76cCcpxHYpsmXId5uXcddv+vQEzrWHTzaWpzTlTbYBJ1rmxGfI7NOVrPb9J3eYfY9Tt33//zb1792jatGmWU4XmVW5jlHY0dwr0iY+vtXuh8Od8OLUKji2F1CeFHZEQQgghXhGrV6/G1dWVli1b0qpVK5KTkws7JJFHkmQby/Xf0XU8SrgHMZcKNRwhxL/Ik8qEEC+xOXPm6H4+cuQI//3vfwsxmmxIO2oQSbKNxfINQPXMe/vc7ScpBqLOQKJhc88KIYQQ4tVVunRpXXcKlUpFiRI5e1jbsSN/smPL98TE3M/P8EQuFMrDaF5Lrp0hLSm9X3bZt9L7ZRsq4Q6cWwNKavqTEWsMhCK52I8QIhNFUTB0CIoMWRFCFJR169bx4YcfEhERgZ+fH9WqVXvhNutXr+SLcemzpZUsVZqfDx/FwaFovsUo7ahhJMk2Fkt7qO+Tt33cvwDK/57GpCgQHSpJthBGIoPihRAvs0qVKvH7778btM13G9fpfr4TcZv/Hg7Bo6OXsUPTkXbUMNJd5GVi/SZPJ5RUwOrNwoxGiNdKxh0YQ19CCPGyqupaXa+LSQWXivl6PGlHDSN3sl8mxepA8iOIvQz25cG5cWFHJIQQQoiX1Mx5X2NlZc31a1fpP+hjXGvULOyQxDMkyX6ZqFRQ+u30lxDCqORBZUKI142DQ1HmL15WYMeTdtQwkmQLIUyCDNgRQoi8kXbUMJJkCyFMglYBlYFtvdZ0/zYIIUQm0o4aRpJsIYRJkFHxQgiRN9KOGkaSbCGESZCvOYUQIm+kHTWMJNlCCJMgA3aEECJvpB01jMyTLYQQQgghhJHJnWwhhEnQKgoqA7+21Jrw15xCCPFv0o4aRpJsIYRJkAE7QgiRN9KOGkaSbCGESZABO0IIkTfSjhpGkmwhhMkw3aZeCCGMQ9rRnJMk+yWhJD2Cq/8Fc2uo1AyV2qywQxLitaLNxfecptyXUAiRLikpia3fbyIpMYleffvh4FC0sEMqNNKOGkaS7JeAkpYC+/3hUTSgwN2/4e1BhR2WEEIIYfKGDBrAgb27UalUBAas59eQo5iZyY0w8WIyhd/LIC4SHkWh+xLm5l+FGo4Qr6OMGzCGvoQQpktRFP7vwD7dz3+HXeDWzZuFHFXhKah2ND4+Hi8vL27dugXAn3/+iZeXF+3atWPhwoW6ft5hYWF069aN9u3bM3HiRFJSUgCIiIigX79+eHh4MGTIEOLj4wGIi4tj8ODBeHp60q9fPyIjIwFITk5m3LhxeHp68t5773HlyhUj1JYk2S8HuzfBwgZU6vTXm+Xz5zgpCRD+f3DtADyJy59jCPGSUlB0g3Zy/JLeh0KYNJVKhVudupiZmWFmZkax4sUp4excaPHcuXWDZXOnsWbxPOIfFfzf8YJoR//66y/69evHtWvXgPTuOn5+fixbtox9+/Zx7tw5Dh48CMC4ceP44osvCA4OBmDz5s0ATJs2jd69e3PgwAHc3NxYunQpAIsWLaJevXrs37+fnj17MmPGDAACAgKwtLRk//79TJw4kXHjxhmlviTJfgmozK2g/Vio1Axc34GWn+TPgc4HwK0/4PafELoGFG3+HEeIl5DcyRZC5EbA5u0MHDSY9z/oz659/4eVlVWhxPHkSRLD+nZhe8BqNq1YzOTPfQo8hoJoRzdv3szkyZNxcnIC4OzZs5QvX55y5cqh0Wjw8vIiODiY27dvk5iYSIMGDQDo1q0bwcHBpKSkcPz4cTw9PfWWA/z222906dIFgE6dOhESEkJycrLe8kaNGhEXF8dNI3xjIX2yXxKqoqXhrf75dwBtGsTffvo+KSb9zrZFkfw7phAvkfSPlAYO2MmPQIQQr5TiTiWYNe/rwg6DyIjbREfe070PPXWswGPISzsaHx+v15fdwsICCwuLTOXnzJmj9z4yMlKXcAM4OTkRFRWVaXnx4sWJioriwYMH2NnZYW5urrf83/vSaDQUKVKEBw8eZLuvsmXLGnSu/yZJtqlQm4F9eYi7kf7euhiY2xZuTEIUIHmIghDiVeZcuizOpcsSeec2iqLQ8C33Ao8hL+1oy5YtSUxM1C0fNmwYn3/++Qu312q1qFSqZ/anoFKpsl2e8f9n/fv9s9uo1epM22QszytJsl93ihYe3QKNFdT4AO4cAyUNSjZO7//9Okt6CH9tgPh7UKI21OiR/mFDmCR5iIIQ4mUWHf43vyz/ksS4B9Tp0I96nQforTe3sGBp4C7WLZ2PrZ09Hw03Tr9hQ+SlHT106FCmO9k54ezsrLsTDRAVFYWTk1Om5dHR0Tg5OeHo6MijR49ITU1Fo9HoykP6XfDo6GicnZ1JTU0lISEBBwcHSpQoQWRkJOXKldPbV14VaJZ18eJFPvzwQxo3bkzz5s3x9fUlJiYGgODgYLp06UL9+vVp3bo1S5cuRat9+mWtp6cnderUoV69erpXxujPx48f4+fnR5MmTWjQoAG+vr4kJCTotr127RoDBgygXr16tGjRghUrVhTkaRceRQsXNsHZVXBqCdw7CWXdodw7pnEX+8pP8OhO+oeKu6ch8lxhRySEEEJkKWTj1yTERJKWksypH9YRc1N/hgtFUVg4cxK7tgQSuOZbtqxfWUiR5o6dnZ3eK6dJdp06dbh69SrXrl0jLS2N3bt34+7uTunSpbG0tOTEiRMABAUF4e7ujrm5OQ0bNmTv3r16yyH9bnpQUBAAe/bsoWHDhpibm9OyZUt27twJwIkTJ7C0tKRUqVJ5PucCS7KTkpLw8fGhXr16hISEsGfPHmJjY5k4cSLnzp3D19eXkSNHcuLECVatWkVQUBDr168H0vvxXLt2jX379nH69Gndq1KlSgDMmDGDO3fuEBwczE8//cSdO3eYP38+ACkpKQwZMgQ3NzeOHj3KypUrCQwMZP/+/QV16oXncRQ8uPT0/c1DhRdLYUhLfv57YVJMZeDjunXr6NixI15eXvj5+ZGcnMzhw4fp1q0bXbp0YcCAAdy+nT4+4+rVq9SvX58uXbrQpUsXBg1Kn59fURT8/f3x8PCgQ4cOuj9iAGvXrsXDw4P27dvrBhMJIfIu9Umi3l3ilCdJeusjbt7gt+C9uvcbV3xTYLFlKIx21NLSEn9/f0aMGEGHDh2oVKkSHh4eAMyfP585c+bg4eHBkydP6N8/fWzblClT2L59Ox06dODUqVOMHDkSgBEjRnD27Fk6duzI5s2b+fLLLwHw9vYmNTWVjh07MnPmTObNm5e3oP+nwLqLRERE4OrqytChQzEzM8PCwoLevXvj6+vL7du36dOnD++88w4AlSpV4t133+X48eN89NFHnDt3DgcHB0qXLp1pv4mJiezevZuNGzfi4OAAwNixY+nfvz++vr6cPn2ayMhIhg8fjoWFBTVq1MDb25vAwEDdyNPXlrkNoCJ9kIIKzO0KOaACVqEVxFyC1CQoUiq9y4gwWQqGTyX1qk3hd/bsWYKCgti2bRvW1tb4+vqyfv16NmzYwKZNm3BxcWHr1q3MnDmTb7/9lrNnz9KtWzcmTZqkt5/g4GD++ecf9u3bx/Xr1/Hx8eHAgQOEhYWxa9cudu3aRUJCAj179qRRo0Y4OjoW0hkL8fpo1OMTfv12Ktq0VCo0cMepYnW99UXs7THTaEhLTUWtVlP0zeIFHmNBtqO//vqr7udmzZrx448/Zirj6urKjh07Mi0vXbo0AQEBmZY7ODhk2ZshI5E3tgK7k12xYkVWr16t1x8nODiYmjVr0r59e/z8/HTLk5KS+O2336hZsyYAoaGhWFtb88EHH9CkSRO6deummyPx+vXrpKSkULVqVd32lSpVIikpifDwcC5duoSLi4ve1xKVK1fm4sWL+X3Khc+iCFTrAVaOYFcSXHsVdkQFy740vD0R3hoLjYeBxrKwIxKFSKvk7vUqsbe3Z/LkydjY2KBSqXB1dSU6OpovvvgCFxcXAKpXr86dO3cAOHfuHBcuXNDd4b50Kf2br0OHDuHl5YVarcbFxYUyZcpw8uRJfv/9d9q1a4eVlRVvvvkmTZs21bXFQoi8KV+vBX0X7aTX3O9p/ek0VP8aeGfvUJSZ36ykbIWKVHatwawlqwo8RlNoR42pUAY+KorCokWLOHjwIJs2bdJbFx8fz4gRI7CysmLgwIHA/yaDd3Nj9OjRlCpVigMHDvD555+zadMmUlNTAbCxsdHtw9raGoCEhAQSEhJ0759d//jxY4PjTktLM3ibwqK6/V9U134Fc1u0NXulJ9kAhXQOGXVX8HVoBpZF//ev/NX5/WWl8Oqw8BnjnE1h4GOFChWoUKECAPfv3ycwMJDZs2fTtGlTIL0ely5dSuvWrQGwsrKia9eu9OjRg5CQEIYOHcrevXuznc4qMjISNze3TMsNkZPfpSlf6/lN6jb/5LVur176mymjP+N+VCQDhgyn98CPM5Vp0aY9Ldq0z3RMQ2PMLVNoR42pwJPs+Ph4/Pz8OH/+PJs2baJatWq6dVevXmX48OG8+eabbNy4ETu79O4NPj76E6537tyZPXv2EBwcjJeXF5DebcTW1lb3M6R3srexsdGbMubfZQ0RGhpq8DaFwSItHre49D7nSkoCT04FEGbfrpCjSveq1OHLTOowd0xpCr9bt27xySef0LNnT12CnZSUxLhx49BqtXz66adAete6DO7u7lhbW3PlypUsp8ZSq9V6g9EzGDrNlSHXr1zr+UfqNv/ktm7nTRzF9auXULRavpk9BftiJShZppyRo8sbU2pHjaFAk+wbN27w8ccfU6pUKbZv367Xj+/QoUOMHj2aXr16MWbMGDSap6GtWbOGGjVq0KxZM92y5ORkLC0tcXFxwdzcnMuXL1OnTh0Arly5grm5ORUqVOD+/fuEh4frpnIBuHz5MlWqVDE4fjc3N73uLi+tR7fh6TglrDUKdevWzd2+tGmgUuV5ur+0tDRCQ0NfnTp8CZlyHWacu3ixsLAwBg8ezODBg/H29gbg4cOHfPLJJ5QpU4YFCxboHtKwevVq+vTpo7uhodVq0Wg0ODs7ExkZqdtnxnRWWU2lldENJadycv2a8rWe36Ru809u6jY1NQW12gy1Wk1qSjLKMx9kS5d0pnZu/3a/IEZRMAosyX748CEDBgygadOmzJo1S+/ux5kzZxg6dChTp06lR48emba9c+cO27ZtY9WqVZQsWZJdu3Zx+vRppk2bhrW1NZ6ensyfP59vvkkfaTt//nw6deqElZUVTZo0oWjRonz99deMHDmSa9euERAQwKhRoww+BzMzs1ejUXqjDBRzheiLqFBBpXa5i/vab/DPflBroE4/cKqR59BemTp8iUkd5o4pfM0ZExODj48PU6ZMoV27p99eDRs2jNq1a+Pn56d3h/ro0aNoNBoGDhzIkSNHSEtLo2LFiri7u7N9+3Y6derEjRs3CA8Px83NDUtLSyZNmsTAgQNJTEzkyJEjjBgxwqAYDbl+5VrPP1K3+SendfvdigVsX7sMG1s7fOd9y+CRvkwdMxStVkvjFi1xq9/opfsdmUI7akwFlmQHBQURERHB/v37OXDggN66Jk2akJqayqxZs5g1a5ZueYMGDVi9ejW+vr6o1Wr69u3Lo0ePqFy5MitXrqR8+fJA+lQt/v7+eHl5kZKSQps2bZg8eXL6CWo0rF27lunTp9O8eXNsbGzw9vamW7duBXXqBU+lhjr90x/CYm4NVg6G7yMpDv7+31RBacnwVyCUbgSlG/Lk3i1S7l7CvGwtLF3qGTd2IfKJguGPSX/V/jRs2LCB+Ph4li1bxrJly4D0MSinT58mNjaWrl27AlCsWDHWrFnD1KlTmThxItu3b8fS0pIFCxagVqvx8PDg7NmzeHl5oVKpmDVrFlZWVtSuXVvXhzstLY0RI0ZQokSJwjxlIQzyMOY++7esR1G0ePYeiEMhzNABcDv8CttWLwEg4VEcy2f6seKHQ9Rr3IzYBzFUrlbdKE8cNDZTaEeNSaWY8keMHEpLS+PMmTPUrVv3pftUmW+SYuG3WfrLVGqSHj0h/l5seiKvaLHvNBqL8i+eGs8k69DITLkO83LuGds6/LEElYFzpStmFsS+/blJ1rmxGfI7NOVrPb+Zct0qisIEby9uX0ufRadkORf8A/cZLZk1pG7/Dj3NhA+f3uyztLJmc8gFo8TxPLn9/Us7mjsv38ck8XKwcoCKrfWXKVpSE5PS+2grWlCpSbnzT+HEJ4SBTOVhNEKIrD1JfMzNK3+j1WrRarXcDr/C4/hHhRKL6n+vDBqzQpnszWDSjhpGkmyRvaqe0GYalGuR/l6lxtzWJv1fzP8SbXMlKT3hFuIll9GX0NCXEOL1YGltQ8XqbqjUalRqNeWquGJbxD5fjvXwwX3WzJvM4skjuHz+r0zry1asguObxTE302CmVtO4Zdt8icPYpB01zKvx0UkUHnMbqO4Fdk6QFItlqfrw95+knjuAuaUGi7sn4EpZqNyysCMV4rm0Cqhk6ikhTJZKpWLConX8HBSIoii07dZXbyCwMS2ZPIJ//jqJgsJfR35jcdDv2Nq/oVtvbWvH7HVB/PrjVoq8UZR23fvmSxzGJu2oYSTJFi+mUkO5p9MnWtpaY2lvg+5x7Q9vF1poQgghRE7Z2b9B14Gf5ftxblwKQ6tNf/DLk8REou7e1kuyAZxKlaHPkNH5HosoPNJdROTM/Qtw5ls4vxEcyz8zb7YCpY07j6cQ+UHJ5X9CCGGoZu966X4uWc6F0hUqcFyQHAAAIABJREFUG2W/Z4+G8MVH3ZkxzJtb1y4bZZ+GkHbUMHInW7zYk4cQtoX0iXtUkJoErcdB1CUoWhYcK6SXi7oMj2OhZE2wsH7ODoUoeIqCwXNJmfLXnEKI7EWEX+bGpTCq1G7AmyVKZVo/YPSX1KjfhIRHD2nSugPmFhZ5Pubj+Ef4jx1MakoyKpWK+eM/ZdHW/8vzfg0h7ahhJMkWL5b8iKczYyqQ9ADsndNfGS7+Aqd3pP9sVxw8J4LGsqAjFSJbSi6GuZvygB0hRNbCTv2XBWM+QqvVYmllzZerduBcrqJeGbVaTZPWnkY9btyD+6QkPwHS26bouwXfVVPaUcNId5FXwfUTsMsPdk9Jv1tc0GxLgl3pp+9LN8tc5vIfT3+Oj4KoKznbd8wN2Dsddk6AK4fzFqcQz6FVcvcSQohn/RwUyPlb9/nz0j3Cbtzj6M97C+S4JcqUx61xc917j14DCuS4z5J21DByJ/tll/wYjqz/3zR5KghZDe/NLdgY1GZQexDEXk2fbaRI2cxl7EtAfPTTOO2K5WzfR9ZD3D1AgWOB4FwdbB2NGLwQ6dL7BRp4B8aE+xIKIbIW8ucRouKSUICbMQmE/PE7XT76PN+Pq1Kp8Fu4hnPH/8TSygbXug3z/Zj/Ju2oYSTJftmlPDsPtZKedOeRok0FlZlhUxepzcGx2tP32rT0wY8Z+2j4PpzZCY9joFprKOKUs/0mJ6D3DzYlMecxCWEA6UsohMiKoiikpaaiMTfPUXm1uX5XSDOLrLtGarVaFK0WM83TVCs1NQWNJmfHyYpGY07dZoU3Za60o4aR7iIvO1tHcHmme0Ztr+zLvoCi1ZL46yriV39CwvfjSXsQkbsdhe2HH8fB3olw9zz8uRx+mQ4p9+HtwVC2Xs735dbp6c9l6sAbmQeQCCGEEPnhzq0beHu2oG3t8kwa9hEpyS9+ZPhnYyaiMUtPn2ytLPhkzBeZyoQeC+ETj0YMbFWLneuWER8Xy/TBPfF5pxYzP+1DwqM4o5+LePnInexXQZMPwLXN/7N3nuFRlF0Dvreld0ghQAgBUoCEkkBoUqSLFCmi8oENURABlUikGukShZeqKIJSBIGIIAjSBVEJID2UUEIgQHqvuzPfjyULIYHsZlPJ3F6rOzNPOTNOzpx95hRQqMDascTDaKLPoo78BwAxI5GsvzYgc3ADhRLzZj2Rm1kWP0haLFzao/2elwUnN4CQ/eDYPYg8AE366y9Uw+egVmPIzQI714cr4xISpYwUsCMhIZGcmEDY2u8QRZGB//c2q5eEEhN9C4Cj+3dzcPcOevQb9NQxnuvRh4PhZzh/6jitOnTB1r5GoTbfzZtCZkYaiCJbvl1EenIiNy6fB+DaxTPs27qW/m+8X/onWMZIetQwJCO7KiCTaQ1QIxEfJMYH7U2fe+cy4q2LgEje7YvYDZqqzyDFbGswGMsa8Ih9r8lMAWQoLMqm3K1E9UTU/cvAPhISElWG3OwsMlOTsXV0KeQSKYoik0a+ws3IKwAcO7CHeo28efQvXaPO02sel9puuNR2e+JxtVpdwBhV5+Uhe2QmQVOCZ2UlQNKjhiG5i1QjlG7NUNRpqt1QmSOq87RGsiiivheJ+LjBXBTWzlC/g/a7XAl+g8CmlnbbzBY8OhslY9LfYUStGE3UivdIPrnLqLEkJB5FEMUSfSQkJKoG0ZfOsuCtnix8ty9rpr2HOq+g60d2VibXr2grMQqChlvXrzJo+Ehs7bXB9r4tW9Old79SkeWNj6brfLx7vfwGA958H0dXbdIAlzrudB04rFTmKW8kPWoY0kp2NUKmUGLeewJidhooTUneNB0hNRZEULl6IZPp8ZtLJoPmg8Gnt9Z9RWkCdVtCTjqYWGozkTyN3Ay4uR/UWVC3PdjV0x0ScjJJOrZFt514eAO2zXsgU0i3qYTxlETNG9rnyy+/ZN++fchkMoYMGcKbb75ZglklJCRKwoGN35CXrXVfvHnhJFdOHKVx2+d1x83MLWjU2I/IS+eRAe4NvWjcrCWbD54kNSUZ+xo1DUsI8BRade7JN7tPkJebg7WtPQBz1/1OanIiNnYOyBWFn5VZ6ansXruc1MR4OvR9hQZ+5Z89pDjKQ48+S0jWSzVDJpMhM9e6YdgNnEzW+QPIFCrMfLsaNpDpI/4dMjmY6efaIb+4CZKuazfiIqBDsNY4B5DLtUb6A7cWmUL5SPl2CQkjEUXDfQMNaH/48GFOnTrFjh07yMvLo0+fPnTq1AkPD4/iO0tISBiNysSMR30ylI9VWZTJZMz/dgPbN/6AIAj0f/UNZDIZSpUKh5olj3d6EmbmFpiZW+i25QoFdjWePM/Gr2Zw4d9DIIpc+OcQk7/fiZ2jc6nLZRRlrEefNSQjuxojt7DFsvVL5Ttp+l10GlDIg6xEnZEtV5nh2OMd4vevAZkcx56jkMklI1uiatCpUyfatWuHUqnk/v37CIKAhYVF8R0lJCRKhZ5vjCf+zg2S7t2hRbd+NGzRrlAba1s7hr07vgKkK5471yIQBa3bpkadR3xMVOUzsiUMQjKyJUqfzES4+AvkpAIK0KiRuXcAFIhOzZDd+VvbzrwGWLkU6GrdpCNWjZ8DKLXXdhISULL8rojahbH09HQUj7zeNTExweSxVTIAlUrFwoULWbNmDb1798bZWXpASkiUFzVc3Ri3LAxRFCvd80OjUbPt24Vc/u8ffPzb0f/tCZz75zC71n2NtZ0Dr4ybSssufdi/6TsAbGs6U6dRkwqWujDG6NHqiGRkS+iHOhuSroKpDdjUe3rbM+sg5TbwINWPWkB2ZiNmjn0QG70ADvUhLxOc/bR+3Y9R2ZSjxLOBUILUU4giCrSr1FlZDwsljR07lg8+KLrC24cffsh7773H6NGj+fnnnxk6dKgRUktISBhKZXyG/Ll9Iwe2/ADAnWuXMbeyYfvqxQgaDXK5nFWzg/hkyQbqNmpMalI8fh26YWZROK1ubk4Op/8+hKmZBX6BHcr9XI3Ro9URyciWKB5NLpz5GrIStNv1e0Ht9k9un5WI7qfuAwUgA0w0GVofa2e/MhVXQqIojPEKPHz4cKGV7Me5evUqgiDg5eWFubk53bt35/Lly0bMKiEh8ayQeC8GuVyBIGiQyxXcu3VNl8ZPEATiY24jk8nwbf/k+ChBEJg1bgSXTp8AoPfLr/Pmx9PLRf58qq93dcmQHF6rI5lJsPdLCPsEzvxa/K/StOiHBjbA3eNPb1/vuYffBe3YomVN0k30LLUuIVEGiA8Cdgz9AFhZWRX4FGVkX7t2jRkzZpCbm0tubi5//PEHAQGVLzuAhISEcaSnpTJ59AgGtG3Kgmkfo1Gri+3TultfXXl1hUrF8wOH4+7tqzveRY+UfrF3bukMbIB92zaWQHrjMEaPVkcMWsnOzMxk6dKlREVFMXfuXJYvX8748eMxNzcvK/kkyoL/wiDhhjZH9sU94OQJtXye3N7Ujoch2zIwr/n08Rt0BYcGWpcQlQXkpCPYeyCcjyjFk5CQMIyS+hLqS69evbh48SIDBgxAoVDQq1cvXnjhBQMnlPSshERlZ8PKJRw/chBBEPh960YaN/Onz+DXntqnbiMfpq/+jVtXzlPPqyn2TrX4eNGPRJz8GysbOzyaNC92Xhv7GpiamZObk41MJsO5zpOL4ZQVZa1HnzUMMrJnzJhBgwYNuHXrFiYmJmRkZBAcHMz//ve/spJPoizISS+4ep2b8fB7fkGaR1PnmdcA76Fw5xiY2oKHHoaDvXvB7Spa3aoAoqi9PsXlApeolJTUl9AQPvroIz766CPD5ngMSc9KSFRuUlOSH7pCyuSkpSQX2U4URQSNRreC7eBcCwfnWrrjKhNT/Np2LnY+QaNBrlBgYWXNp4u+Z/O3/8PMwpLXx082/mQMpDz06LOEQe4ikZGRvPfeeygUCszMzJg5cybXr18vK9kkygqfHtqc1AB2tcH1QRXIW8dh+yTt59ZjLiE1m0Czd8D7ZTCxKl95KwOZcfDvl/DndLj4c+Fy8hISpYSkZyUkKjcvvfYGZg/eLNV0dqZ7v0GF2vz3z1GGdvTjpUBPNn67pETzqHOyCP/6U/YG9+PYwnHkpCfTuEVrZixfz6TQlbjUdTfmNCTKAYNWsuVyObm5ubpo1vj4+DIRSqKMqeUD/WZrfbPtaoNCCRo1nNoE4oMV51OboHZL7TEJuP4HZD9YrYg9A45NtB+JKkNVec0p6VkJicpNA+8m/LT3X+7cukm9Bp6YF5EPf3HIJ2Skp4EosnZZKJ1696eWge4dt//dTeL1cwCk3b3BzYNb8Oo7slTOoaRUFT1aWTDIgnrrrbd48803iYuLY9asWezdu5dx48aVlWwSZYm5jfajQ6DgX4L4YJ8EoKtCqUNaya5yiFSNp4OkZyUkKj/WtnZ4+z7Zj1qtVhdwk9Co8wyeQ3zEzVImA+Hx51AFUFX0aGXBICO7T58++Pj48Pfff6PRaFi5ciVeXl5lJZtEeaIwgab94Nyv2u2m/bT7JLTU7wqpt0CdBXYNoOZTAkUlKiVVZQVG0rMSElWf9yZ9xhefjkOdl0ffV9+gdj0Pg8eoHdiTmFMHSb93E1Pbmrh3LOcKzUVQVfRoZcEgI/vChQssWbKEr7/+mitXrhAcHMwXX3xBw4YN9ep/6dIl5s+fz4ULF1CpVLRv357g4GAcHBw4c+YMs2bNIjIyEnt7e0aPHs2QIUN0fX/55ReWL19OXFwcHh4eTJs2jRYtWgCg0WgIDQ3l119/JSsrizZt2hASEoKTkzZlXEJCAtOmTeP48eMoFAr69evHpEmTUColV4gCNOwMbq21302kctAFsK4N7YK1GVNMrHVBLxJVh6oSsGOsnl29ejVbtmxBLpfTtGlTQkJCuHbtGlOmTCEjIwN/f39CQkJQqVTExMQQFBREQkIC7u7uhIaGYmVlRWpqKhMnTiQ6OhoHBwcWLlyIk5MTubm5TJkyhfPnz2NmZkZoaCgNGjQo4ysiIVH1aN/tBTa170xOdja29g4lGsPEwpp2Hy4hNz0ZlaUtckXFB91XFT1aWTAo8PGzzz7j7bffBsDT05PJkyczdepUvfpmZ2czcuRIWrRowdGjR/ntt99ITk5m8uTJpKSkMGrUKAYMGEB4eDizZ89m7ty5nD17FoB///2XmTNnMm/ePMLDw+nXrx+jR4/WVWBbsWIFf/31F1u3buXIkSOYmZkVkGvChAlYWFhw5MgRtmzZwt9//82aNWsMOfXqg4nFEw3s7PQU7keeIzcrvZyFqiTIldqKl5KBXSXJfzYY+ilvjNGzZ8+eJSwsjM2bN7N9+3bUajUbNmwgKCiIKVOmsGfPHgA2btTm1w0JCWHo0KHs3r0bX19fli5dCsCiRYto0aIFv//+O0OGDGHmzJkArF27FlNTU37//XcmT55MUFBQaZ++RBUgJuo61yLOIQiS29zTMDO3KLGBnY9MLsfUxqFSGNhQdfRoZcEgIzs7O5tWrVrptgMCAsjOztarb0xMDN7e3rz//vuYmJhgb2/P0KFDCQ8P548//sDOzo5hw4ahVCpp27Ytffv2Zf369QBs3ryZPn364O/vj0ql4o033sDe3p5du3bpjr/zzjvUqlULKysrpkyZwp9//kl0dDRRUVEcP36coKAgzM3NqVu3LmPGjNGNLaEfSXdu8MuUYexZMJ5fpo0gPf5eRYskIfFMYoyetbGxYdq0aVhYWCCTyfD29uby5ctkZWXh7+8PwMCBA9mzZw95eXmEh4fTu3fvAvsBDh06RP/+/QF48cUXOXr0KLm5uQX2t2rVitTUVKKjo0vt3CUqPzvWf8eHQ3sw+c2X+OrT96t1oREJieIwyF/CycmJDRs26JTsrl27cHR01Kuvh4cH3333XYF9e/bsoUmTJly9ehVPT88Cxxo2bMiWLVsAbUqrQYMGFTp+6dIl0tLSuHfvXoH+NWvWxNbWVlfS2M7ODmdnZ93xBg0aEBMTQ2pqKjY2NuiL5lnI9VxCLh/+FXWu9kGfm57K1b9+x+/FEXr3z792ha6hoEF2dTeypGuINb0QG3QvmKO7rEiPQX57n1aEut3A0rXs5zSSJ17DakBpnLP4yL8rM8boWXd3d9zd3QGtm9z69esZOnQoN2/e1LVxdHQkLi6OpKQkrKysUKlUBfYDxMbG6tztlEol1tbWJCUlFdj/aJ+6devqfX76/L+szvd6WWPstd36/VLd9/DDe7l9IxLXEvgbP4sYem0vHf+TQ1u+x9LGjhff+QR7Z8OfQ9lpyfy3eRnpCXdp1LE/7oHd9ZKxpFQVPVpZMMjInjNnDp9//jmhoaEolUoCAwOZNWuWwZOKosiiRYs4ePAg69at48cffyxUzczMzIzMzEwAMjIynng8I0NbSMXisRQ6ZmZmumOP983fzszMNMjIPnfunN5tnzWS0rMR80ukiwLxKemcPn3a4HEev4ZOmZepk/EfMkCWFkNUXDrx5mXs4ykKNFP/AWijvYWLazmr7FFl3ECq831oDFUlYKc09Ozt27d59913GTJkCAEBARw+fFh3TBRFZDKZ7r+P8vj2o33kcnmhPvn7DcGQ+1e618uOkl5bUwtLsjMztPeCXM6NW9HEJqWWsnRVG32ubVZqMrsWTUIUNMhkclbfm8DzIw0vLhNzYB3pN8+DKHJ8XSj30/MwrVF2i0ZVRY9WFgwysp2dnVm2bJlRE6anp/Ppp59y4cIF1q1bh5eXF+bm5qSlpRVol52djaWlJaA1ih9/XZqdnY29vb3OYM73z368vyiKhY7lb+ePry++vr4oKolfVHmj9vHib3KIu3oO16aBtH5lFHIDcmhrNBrOnTtX6BrKLkVBhhwQEJFRt6YldRoVX14WgPgbyG78DRb2iN7dQKHSU5gcFKd26jZV5NLcr0mlz6bypGtYHcg/d2MQq0jAjrF6NiIiglGjRjFq1CiGDx/OnTt3dCvUoM277eTkhIODA2lpaajVapRKJXFxcbpVaicnJ+Lj43FxcUGtVpORkaF7IxgbG4ubm1uBsQxBn/u3Ot/rZY2x1zZo/gq+mTOZrIw0hr73Me2e61QGUlZuRFHk/MFfuXftIvWbt6Nhq86AYdf29tULiA9S8omiQE5aMs2b6/nse4TYPSsL6Kk6jnbU9nvyOMbq0vLQo7/99hsrVqwAoGPHjkyaNImIiIgqGbytl5X07rvv8s033/D8888XudKxf/9+vSa7desW77zzDq6urmzZsgUHB21AgKenJ3/99VeBtpGRkTRq1AiARo0acfXq1ULHO3bsiK2tLc7OzkRGRupcRuLi4khOTsbT0xNBEEhOTiY+Pp6aNWsCcO3aNVxcXLC2ttZL7nwUCkW1VfgKCys6j5qhf4f46/DfT6DJA98B4OKrHefxa1inFdwJB0FAplAiq+0P+lzjjAQ4tFibr1oUITsFWg/T92SgRlNIOK/druGLwsT86X0qEdX5PjSGkjwbZOVoY5eGnk1MTGTkyJHMmDGDHj16AFC7dm1MTU05ceIEAQEBhIWF0bFjR1QqFQEBAezcuZP+/fvr9gN06tSJsLAwxowZw2+//UZAQAAqlYpOnTrxyy+/EBAQwIkTJzA1NcXV1bBVM0PuX+leLztKem0bNvZjwbrfykCiqsOZfWEcXPMlMrmciCO/MzB4EfV8W+uOKxQK7ly7zA/zPyUjLZV+b42jXa+C6ffqNPShdqMm3Ll6AYD2fV8t0f8Pz84DOL7uSwAsa9ailnfLMv2bKWs9mp2dzcyZM9m1axe2tra8+uqrHDt2jDlz5hASEoK/vz+TJ09m48aNDB8+XBe83a9fP5YtW8bSpUsJDg7WBW+vXLmSbdu2MXPmTJYsWVIgeDs8PJygoCDCwsIMOyED0MvIzo8sX7BgAS4uLiWaKCUlhddff502bdowe/bsAq8Yu3fvzoIFC1izZg3Dhg3j5MmT7Nixg+XLlwMwePBg3n//fXr37o2/vz/r168nISGB7t21vkcDBw5kxYoV+Pr6Ym9vz5w5c2jdurVutcXf31/3CjYpKYnly5czePDgEp3HM4sowv1z2qqGLn5gZmfceMdXQ046IEL4j9Dr86Lb2daFDkGQehts3cBcz3mT74CgfrgdZ2DZ6YYDwfHBr31byZ+wOiCKouFBWuW4kl0aevaHH34gPT2dZcuW6VbDO3fuTGhoqG4VqEmTJowYoY2nmDFjBsHBwXzzzTfUqlWLr776CoDx48cTHBxMnz59sLa2JjQ0FIDhw4czffp0+vTpg0ql4osvvjD2tCUkqhx3Iy8gk8sRBQGZTMa9yAsFjGyA7+d8QuztKERRYF3oNHz822Lv+PDvWqFU8conX7Djx+XYOjjScfCbJZKlQbve2NdtSEbCfVy8WqAyN+wNvaEYo0fT09ML/AAwMTHBxKTgG2S1Wo1arSY7OxsrKys0Gg1KpbJQ8PaiRYt45ZVXCA8P12VFGjhwIK+99hrBwcEcOnSIdevWAdrg7ZCQEF3wdn5xr0eDtw2JKzEEvYzs/NeBU6ZMYffu3SWaKCwsjJiYGH7//fdCY/z33398//33zJ49m8WLF+Pg4MDUqVNp06YNAG3btmXGjBl89tln3L9/n4YNG/Ltt99iZ6c1yN5//33UajXDhg0jIyODwMBAFi1apBt/8eLFfP7553Tt2hW5XM6AAQMYM2ZMic7jmSVyL1zbq/1+7QA8FwQmJfxjFUVtPul8RyxRAHXuk9tbOGg/hlCjPqjMIS9bO08dP8P6y+Rgp1/eYYlng5K4EpYnpaFnP/zwQz788MMij23durXQvtq1a7N27dpC++3s7Pj6668L7Tc1NWX+/Pklkk1C4lmhfvN2RBz5XfvGSSajnl9goTYZqcmIDyoDi6JIZnpaASM7OyuLoDcHE3v3DqIocvd+LO9PmV0ieRzqNsKhbqOSnYyBGKNHO3XqVMB9d+zYsXzwwQcF2lhZWTFhwgR69+6Nubk5rVq1QqVSFRlwXVHB24ZgkE+2t7c3W7dupXnz5gWCCfV5Xfjmm2/y5ptP/qXm6+ury91aFP3799dF2z+OSqVi4sSJTJw4scjjNWvWZPHixcXKWK25d+bh97wMSL4FTiWsaiiTgXcvuPjA77leIJjbGi/jo5hZQ89guHVCa6C7tyq+j4REOdKvXz9eeukl+vfvr3ON0wdj9KyEhETZ49WmK6bmlty7HkE939a4NGhcqM2Lr7/PxsXagOVm7Z/H1b3gos7Nq5e4H3Nbt31k784SG9lVhcOHDxdayX6cy5cvExYWxsGDB7G2tubjjz/mr7/+KhRwXd7B2ydOnODs2bPIZDJ8fX0JCAgotg8YaGSfPXtWVyAmH5lMprdPtkQlxrYuZDwIjpLJwcr5qc0TLh0n+doZbN2bUrNJ28INvLpD7eZan2ybWlAWRQusHaFJ79IfV+KZpLzdRcaPH8+GDRv46quv6Ny5MwMHDqRTp07FKnRJz0pUR+Lu3mZf2AbMLa3o9fLrmFmUrduDsbg3a4N7szZPPN6p/6s0af0cWRlp1PbwKmT8ubq5Y2ZuQW6ONqlDo8YGvo2tIIzRo1ZWVsX6ix85coTAwEBq1KgBaF1Avv/++woL3s7NzWXcuHFcuXKFpk2bolAoWLduHW5ubixfvrxQ9rrHMcjIPnDggCHNJaoSjQdqqxlmJ0HdNk9130i8fIKL62aDTE7M37/h/conODZtX7ihlX65fSUkygOhnAMfu3btSteuXencuTO+vr4sWrSIGTNm0L9/fwYNGqTLZ/04kp6VqG7kZGcxY9TLpCUlIooCV8//R1DotxUtltHUrFXnicds7OyZt2oTv67/Hhs7e157d0I5SlZyylqPent7M2/ePNLT07G0tOTgwYMEBASwd+/eCgneXrx4MS4uLixduhSl8qHJPGvWLBYuXMjkyU9Pu6iXkR0XF8e8efO4evUqLVu25KOPPjIov7REFUBpAl4v6NU05cZ57Wq3KIBMTsqN80Ub2RISlYiKCnxUKBS6lHrXrl1j6dKl9O7dm4iIiALtJD0rUV2JvRNNSsLDlcqIU/9WoDTlh2eTZgTN+V9Fi2EQZa1HO3ToQL9+/Rg0aBAmJiY0bdqUUaNG0bNnzwoJ3t63bx87duwoYGADTJo0iT59+pSOkf3pp5/i4+ND//79+e2335g7dy5z587Vp6vEM4ithx+3j/6iM7TtGpThay5NHkT8Aan3oF4A1G5WdnNJPNOIVEjaa0RR5NSpU+zcuZM9e/ZQp06dIvWnpGclqivOddywr+lESmICoijQJKAIF8RKTtSFk5zYvYUsDfh4NsLC+tn8gVweejR/UeJR8mNVHqesg7dVKpUusPLx/Y8XQSwKvYzs+/fv60qit2nThoEDB+otoMSzh4NnS5oMn0by9bPYujehhk/hyOpS48IuuLwfEOHOaeg6ERzqld18Es8s4oN/DO1VUjIyMti8eTOxsbGMGjWKvn37smrVKry8vIpsL+lZieqKiakZn63czIFtGzG3tKT74OEVLZJBpMTdY8PMDxAFDSKw+zsZAz+cU9FilQnlrUcrGjMzM65fv46HR8FUv7du3cLMzKzY/noZ2Y8uk5uYmBRaNpeofjh4BeDgpV90rVEkRVPgDzQlRjKyJaoEXbp0oXbt2kybNo2+ffsWu+oh6VmJ6kxNF1defu+jihajRCTE3ETQPKzbcO/apQqURqI0GTVqFKNHj2bSpEn4+/ujUqkIDw9n7ty5T8xo9ygl0uJPSpEiUYW4FwEXf9fmmm4xuPIGKdZtAbGXtd+VpuBU9CrgU0m+iebiVjRpiWRpHLDq9DYKSyOL7UhUOco78PH111/n4MGDfPvtt3zzzTe6/foGNkp6VkLCeCIOhBF5bA/2dRsQOHQsKrPiX/EbimvDJqSolVy9dRczlYLXegwplXFFQeD0b2uJPvMXzo38CBj8LgplYdcIArCSAAAgAElEQVSF8qS89WhF0717d/Ly8pg/fz5RUVEA1KtXjwkTJtCtW7di++tlZN+8eVPnZF7U9o8//mio3BIVSU4G/PUNCBptTuu/V0H34IqWqmg82msznaTeA9emYGlg0RpNLuLZNcg1uchNQJ4XS/K+b6nRP6hs5JWotJR34OO2bdsIDg7G29tbL4NZ0rMSEqVLTMRJ/t24BIDE6EhUpmYEvjKu1OeJj4vjv6vRiKJIeo6aYyfP0vcd48e99u8+Tu9YA0BCdCTmtg749X7N+IGNoLJXzi1t7t+/z++//058fDzm5ua0bt2a6dOnU7t2bb3662VkP7oKI/EMkJ2iNbBBe/OnJ1SsPMXh4qP9lIS8LGRCnvbHBKBQKVDfvVeKwklUFcQSrMAY40poa2tL165d9W4v6VkJidIlPf6u7rsoCqTG3imTee7H3NYZnqIoEhN1s1TGTYu7i0wmRxS15dvT4mJKZVxjKG89WtF88skndO3alblz5yKTydi5cydBQUFs2LBBr/56GdmtW7c2SkiJSoaNC9TwgITr2u2GHStWnrLE1AbRriGy5EgAMhPSsWzWp4KFkqgIyjtgp2PHjoSEhNC9e/cC/tVP0qeSnpWQKF3q+LXDzPp7stOSQCbD87m+ZTJPkxatqFu/IdE3tM+Z/q+9XirjerTuwvk/NqHOyUImk9OwXc9SGdcYqlvgY3JycoE3ii+//DI//fST3v2lyJrqiEwOncbC/UugMoOaDYvvU1WRyZD5jUCIvUheQjQqL09Maj3D5yvxRMrbl/DEiRMAXLt2TbdPFMUi001JSEiUPha2Dgz4bDX3rpzG1sUN+9r1y2QeM3Nzlm/aSfhfh0hMTqXvoJdLZVxbFzcGfv4DcTcu4lC3ITZO+rkolCXVzSfb19eXPXv20LNnT0RR5LfffsPPT/+0xZKRXQ0RBQ0yhQpcfStalPJBrkDu4oupSzU5X4kiKW9fwqJ8qI8ePVri8SQkqjKiKCIIQrFltUsbM2tb3P07lfk85paWtO/ai9OnT5fquJYOjlg6lL38+lLdfLL37NnD1q1bMTExQRAE1GptFpmff/4ZURS5dOnpmWQMNrITExO5fv06LVu2JDk5GQcHAwPRJCqM7JQETnw3nbS7N3D0aUWLEVNQqEwqWiwJiWeS3bt3c/ToUTQajW7fgQMHeP7552nZsiVDhjw5A4GkZyWeJc6dOs60D94mLSWZYaM+4K1xn1S0SBISehEeHm5Uf7khjQ8ePMgrr7zCpEmTSEhIoHfv3uzfv98oASTKj2v7N5J+X5uCJi4inDsn9lWwRBIS5Ud+wI6hn5ISGhpK8+bNCQwM1H0sLS11/30Skp6VeNYInR5ESlIiGo2GH1cs4sbVyxUtkkQJKW89WtGkp6czf/58Bg4cyODBg1mwYAHZ2dl69zdoJXvp0qVs2rSJN998E0dHRzZt2sQHH3xgUAS9RMUhqPMeCT+QFUieX24yaDRkJcdjYVcDuULyVpIoR0rwmlNmxNPh448/pnfv3gX2OTg40LHj0wONJT0rUZkQRZGUhFjMrawxLWGO6bzc3AKhb+q83NIRTqL8KWc9WtGEhIRga2vL3LlzEUWRLVu2MH36dL744gu9+htk5chkMuzt7XXb7u7uBgkrUbF4dBlC3KUT5KQmYu1an9r+5fvQzs1IYeu0EaTF38XG0ZW+wUuxsKtRrjJIVF9EDI9xN+bREBAQwPjx4/nnn3+Qy+W0adOGadOmFdtP0rMSlQVBo2HN7I85d+wAJqZmjAxZQqPmgQaPM/bTEGZMGEVebi69XhpKQ5+mZSCtRHlQ3nq0orl06RI7duzQbU+dOpW+ffXPUmOQke3q6qp7bZmSksLatWv1TsgtUfFYOtam85Q15KYnY2rtgExukLeQUeSkxHNv72rS4rU5qtMS7nHx4DYCXnq73GSQqN4IoohQjgE706ZNo1WrVsyePRvQBspMmTKFFStWPLWfpGclKgvXzp3g3DFthdK83Bx2rFrER0v0T1+WT7suPfj12AWyszJxqFl0deHbkREc2PoDZhZW9B4+GmtpAaZSUt56tKIRBIHExERdXExSUhJyA2wng4zskJAQ5syZw7179+jevTtt2rTh888/N0xiiQpFrlBiZluz3OeNWDcL0mLJ/00riiLyCi4PK1G9KIlvoDHPhjt37vD111/rtt966y22bdtWbD9Jz0pUFgoExstkKE1KHihvYWmJxRNiEbIz0lnyyVvkZGUCcPfmVcZ/+UOJ55IoO8pbj1Y0I0aMYPDgwXTr1g25XM6+ffsYO3as3v0NMrLt7e1ZsGCBwUJKVG9EQSAz9hb2FiZkZOeRlafBqb4PTbsOrGjRJCTKDJlMRnR0NHXr1gUgOjq6QFGaJyHpWYnKQv3Gzek44P84un0DNjWcGDTm0zKZJynuHtkZ6brt25FPT4smIVFeDB06lCZNmnDixAmUSiXLly/H09NT7/56GdnPP/88sgdlqYtCinyXeBoyuRwH70ASL/1LvZrWWNbyoMXoL8vVXUVCoiT5XQ3OB/sI48aNY8iQIfj7+yOXyzl9+jRz5sx5YntJz0pUNmQyGS+99wn9R0006BW5oTjWrodT3frERt8ERJo/173M5pIwjvLWoxXNL7/8AoCtrS0AFy5c4MKFC7z00kt69dfLyJYqlEkApMXdISHqKo4ejbF0cDKor+eQjzi1cz11XGvh3KKzzsAWRZHLZ06QkZqCb2AHTEzNih1LUOeREvkfClNzrN2bPtUwKVMEDSRHglwJth5QUXJI6EV5B+x069aNZs2acfr0aRQKBSEhIU/Ndy3p2epLSkIsURdPU8vDC8fa9SpanEI8amCLosjFU/+SlZFOszbPoTIxNXp8pUrFhwvXcvLQ75hZWNKyszYrz71rF0mNv08939aYWjw57WV1QlDnkXj1PxQmpth5+JX786+6BT4eP35c9z0vL4+TJ0/i6+tbukZ2ftBNTk4Of/75JxkZGQBoNBqio6OZMGGCoXJLVDHirl9kT+gEBI0ahYkZfT5djp2ru9795UoVynrNcWnevEDFr23fL2Xb6qUA1PfxZdqKjSie8kpdFAQurw0hLeoiAC5t++HW840SnZNRiCJcXKc1sgFcWkND/SOOJcqf8grYOX/+PDdu3KBLly6sWbOGv//+G7VaTfv27Xn//fexsrIqsp+kZ6sn8TFRLJ3wGjlZmcgVSt6euQIP34CKFuuJ/LR8Ab+uXQmAVzN/PlvxU6mscltY2/Jc31d026f3hrH/e63blJ1zHYbP+wGTEqYQfFYQBYEzq2eQcuM8AHXa96dhn/JNHlDdAh/nzp1bYDszM5MxY8bo3d+gv4yPP/6Y9evXs3DhQo4cOcLChQu5ceOGIUNIVFGu/b0HURQAEPJyuRF+oFTG3bd1ne77jYhzRF97epGC7MS7OgMbIDZ8d6nIYTA5KQ8NbIB74VVakVQHyquIwowZM6hTpw6TJ09GoVAwb948QkNDAfjkk+Ir3Ul6tnpx7ug+ch8UtxBFgVP7dxTTo2LZs+Whzr585iQxUdfKZJ7Tf2zRfU++f5vbEaVbrrwqkpV0T2dgA8T8u6vcZahuxWgeJykpiVu3bund3iAj+8qVK6xZs4Zu3boxcuRIfvrpJ27fvm2wkBJVD2tHV0QhPzOIgI1T6aQUc6rthlyuAJkMhVKJvaPzU9urLO2QKU0AGcjkmDq4lIocBqOyAHl+pL0MzOwld5FKTr4voaEfQxEEgRYtWhAVFcVHH32Ep6cnnp6eTJo0iejo6GL7S3q2elGjVh3dAgaiSI1adStWoGJwql0XuVyOTCZDZWKKnUPRKfmMxb6W2yNxOzJsnVzLZJ6qhImlLXKVifZZI5NjVgHPv/LSo5UFHx8fvL298fHxwcfHh65duzJixAi9+xuUXSTfn9DDw4PLly8zYMAAsrKyDJNYotIiigIyWdG/u3y6DiIrJZF7V85Qx68NHoGlE5gy5vOFrFs0i4zUFPqOeA9bh6enF1SaW+L52mTuHNqEwtScer3eKhU5DEZhAk2GQ9Q+kKvAo3fxfSQqlPJKPSWTybhz5w5ubm5cvnwZLy8vAM6ePatXvmtJz1YvfDv0ICEmmgv/HMTNpxnPDdT/AV4RfDx3GWsWziIzI43Bb4/DytauTObp/vYnKJQqUmJjaNl7KDVqu5fJPPkIglCmwZ2lgdLMEt8R07m5fwMKE3Mavjiy3GWobin8IiIidN8FQeCff/7h0KFDevc3yMhu1KgRISEhvPLKKwQFBXH//v1Kf1NKFI8m/hZZe5YgZiajatwF03avFgqmkCuUBAwZXepzO9aqw4fzvy6+4SPYevhh6+FX6rIYjK07+JW/kpOo3Hz00UcMHz4cURQZNGgQjRo1ArQr1PqkfpL0bPVCJpPRZehIugytGrrEpa47wV99V+bzWNg68OK4mWU+z/2Y20wf8zrRNyLp0P0FPpm7GKWq8tZwsG/gh32DSvD8q4bI5XLatWtXyE/7aRhkZH/22Wf8999/eHl5MW7cOP7991+++uorgwVNTExk6NChzJo1i8DAQKZPn16gbCVAdnY27dq1Y9WqVQiCgL+/P6IoFjD+/vrrLywsLEhISGDatGkcP34chUJBv379mDRpki4n7ZkzZ5g1axaRkZHY29szevRohgwZYrDczyo5x35CzEwCUSTvwn6UHgEoa2mNAU1eHif/2EJ6Yjy+nfvgWNejXGTSpCeRcW4fMoUKy2Y9kJtW74AXCeMREBHKIS6+Q4cOHDhwgMTERHJycgx+VVoaejY9PZ1XX32VFStWcPnyZRYvXqw7FhcXh7u7Oxs2bODIkSNMnDgRFxfta+fGjRszd+5ccnNzmTJlCufPn8fMzIzQ0FAaNGiAKIp88cUXHDx4ELlczueff05AQOUN0pMoSOTFsxzdswO1TIGfn1+BIPRnlejLZ7l4bD9Obg1o/nzfQgtI65Z/xe2b1xFFkSN/7KRNlx4830e/zBHVkfLSo5WFTz8tmBv+9u3b2Nnp//bGICNbo9HoIuOzsrJQKpUGTQZw8uRJgoODCziOf/755wUqmh09epSPP/6Y4OBgACIjI8nLy+PUqVOYFFFxasKECTg7O3PkyBHi4+MZPXo0a9asYeTIkaSkpDBq1CjGjRvH0KFDCQ8P5/3338fLyws/P+nXIICoySv4N6BR677+sfpL/tu7DZlczqm9vzB6yRYsbZ+chqx05FETv2UmmrQEQCQn+gI1B00p0zklnn3K+zXn4cOHi9xfXOonY/XsmTNnmD59ui5YsmvXrnTt2hXQLnC8/PLLTJ8+HdC6sIwePZo33nijwBhr167F1NSU33//nfDwcIKCgggLC2PPnj1cuXKFXbt2ERUVxciRI9m9ezeqSrzyJ6Hl7q0bTB05BEEjIAgarMxMeeW9DytarDIlNiqSNVNGadPOCRoy01JoP2B4gTZ5ubk8+gDUbks8iermLhIYGFhgu3v37nTo0EHv/ga9gwwKCmL79u2cOXOGJUuWYGVlVcjKfxq//PILEydO5MMPn/yHnZiYyMSJE5kyZYruNeu5c+fw8vIq0sCOiori+PHjBAUFYW5uTt26dRkzZgzr168H4I8//sDOzo5hw4ahVCpp27Ytffv21R2XANPAwfCgxLmiXnMUrl66YzfO/AuIiIKG3KwMYm9eLXN5NBlJaFLjQBRAFMm9c7lKB05IVA7KO2Dn+PHjus+ff/7J8uXLCQsLK7afsXp248aNTJs2DSenwrnsv/zySwYMGIC3tzeg1a0HDx6kb9++jB49mnv37gFw6NAh+vfvD0CrVq1ITU0lOjqaw4cP07dvX+RyOfXr16dOnTqcPHlSb9kkKo6r58+gzstDEDQAnDtxrIIlKntuXTqLIGgQH5zzzXPhhdoMHTkWKxttoRFvvxZ06imlYn0a1S3wMV9fpqamkpGRgbu7e5G26JMwaCX7+vXr/O9//2PBggUMHjyYUaNGMXCg/qWxO3ToQN++fVEqlU80tENDQ2natCn9+vXT7Tt37hw5OTkMGjSIO3fu0KBBAz7++GNatmzJ1atXsbOzw9n5YVaKBg0aEBMTQ2pqKlevXi3kB9mwYUO2bNmCoWg0GoP7VAVkzo0wH/YlYk4WMgtbBBF4cK7uvq05vf9XZHIZKlNzatT1KNF1yO+jV18zG+TWNRHSEwERVS1PBEEweM5nDYOu4TNGaZxzea/APO63JwiCXgUMjNWzT/IXzDeS9+7dq9tna2vLkCFD6Nq1K5s2bdKlD4yNjS1gpDs6OhIXF/fE/Yagz//L6nyvlxUePr4oVSoEQUDQaGji3+aZv761PZsilyt0K9luTVoWOme3Bo34Yc/fpCQl4uDojFwuL/F1qQr3rbGyVbeV7K1bt7JkyRK6devG7t272bVrF6+99hp9+vTRq79BRrZcLic9PZ0DBw6wcOFCkpKSyMnJ0bu/o+PTU/1ER0ezfft2Nm/eXGC/mZkZfn5+jB8/HltbW9avX8/bb7/N9u3bycjIwNzcvED7/O3MzMwij5uZmZGZmam33PmcO3fO4D5VHceWz+MlKshJT6G2X1uu3rgF6J8j8nH0vYZyrwFY3juDKFOQ4dqCW6elHKn5VMf7sDQQS+BLKCtFX0K5XE779u31ameMnn0SmzZtYujQoQX04fz583Xfhw4dSmhoKGlpaYXiX0RRRC6XIwhCkfsNwZD7V7rXS5dhH3/OxfCjODi70ijgOU5XA73aZvhH3I04hbWjK+ZuTZ56zrfv3i+VOZ/l+7ai9Wh5s2bNGrZs2ULNmjU5efIkq1ev5tVXXy0bI3vYsGF069aNbt264e3tTffu3Rk9uvQyTmzdupUWLVrg4+NTYH++b3Y+b7/9NmFhYRw+fBhnZ+dC6a3yty0tLTE3NyctLa3A8ezsbCwtDS/R6uvrWy0CRR6npb/xgU0ajYZz584ZeA3193uqDpTsGj4b5J+7MYiUYAXGiPnWrFnD0qVLCQwMZPHixXzxxRcMHjy42H5lpWf37t3L118/zOSTm5vLqlWrdGOLooggCCgUCpydnYmNjcXNzQ2A+Ph4nJyccHFxITY2VjdG/n5D0Of+rc73elnSvHlzevZ9qXpd2+bN4cVB5TJVVbhvjdWl5a1HKwM1a2pTC4uiiImJiUFv1g0ysl9++WVefvll1GptYNyOHTswMzMzZIin8scff/DWW4XzHi9cuJCePXvSuHFj3b7c3FxMTU1p1KgRycnJxMfH6y7EtWvXcHFxwdraGk9PT/76668C40VGRur8vQ1BoVBU2j8cY8lKvM+VHSvJy0qn/vNDqeHZskzmeZavYXkhXcOqwapVq9i1axdLlizh8OHDdO7cmZkzZ/Ljjz8+tV9Z6NnExEQyMjKoX7++bp+JiQk7duygUaNGdOvWjbCwMJo3b46FhQWdOnXil19+ISAggBMnTmBqaoqrqysdO3Zky5YtvPjii9y6dYubN2/i6+trkCyG3L/SvV52VOS1FQSBDd8sIvzIAfxateX1sZ9U6rR5hiLdt88OHh4eTJs2jSlTpqDRaPj6669p2LCh3v0Nes9348YNBg8eTLdu3bh//z6vvfYa169fN1jookhKSuLatWu0atWq0LErV64we/Zs4uLiyM3NZenSpaSnp9O9e3fc3d3x9/dnzpw5pKenEx0dzfLly3UrRt27dyc+Pp41a9aQl5fHP//8w44dOxg0qHx+2VYVzm+YT/ylE6TcjODMDzPJTU+uaJEkJEqV8g7YsbGxwcnJiS5duhAZGUnbtm3JflA++2mUhZ69ffs2rq6FK+Z9+eWXrFy5khdeeIFt27Yxa9YsAIYPH45araZPnz7MmjWLL774AoBevXrh6elJ3759GTt2LLNnzy7VhRaJ6sG+7VvY8PUirl44y9Y1K9mx8YeKFklCT6pb4OO8efOwtLQkNzcXNzc30tLS+Oyzz/Tub5CRHRISwuTJk3WBhm+88QaTJ082VOYiyS8b/GgAYz5z587Fzc2N/v37ExgYyPHjx1m9erUurdXixYtRq9V07dqVl19+meeee44xY8YAYG9vz/fff8/u3bsJDAxk6tSpTJ06lTZt2pSK3M8KmQl3tdk8EBE1anJSEytaJAmJUiU/YMfQT0nx9vbmp59+wtPTk0uXLhETE0NiYvF/V6WlZw8cOECdOnUA8PPz4+effy7UxsfHh59//pldu3axdu1aatWqBYCpqSnz589n586dbNu2jSZNmgDawimTJk1i165d7Ny506BUVhIS+dyNvolcrl3plSvkxETfrFiBJPSmvPVoRWNubk5wcDA2NjYsW7aMoKAg1q5dq3d/g9xFUlNTadnyoRtBv379WLVqlSFD6Lh8+XKBbV9f30L78rGzs3tqhZ2aNWsWKLbwOL6+vmzcuLFEclYX6rTtw80DmwCwqdMIS+d6FSyRhETpolX2hml7Yx4OZ8+eZdeuXbrtQ4cOERQUVGy/0tSzEhKVkU69+rNt3XfkZGuQy+V0fVH/7DkSFUt569GKZv78+ezfv1/nvgcQGxvLzz//TGBgYLHVHw0ysi0tLbl7964uuvz48eOYmpqWQGyJyoZH92E4NGyGOisdB8+WyCV/sqIRNHD3NGhyoFYLUJkX30eiUiA8+BiCrPgmT2TVqlXUrVu3UIW54pD0rMSzjnsjL77ZdpBLZ0/RqLEvteq6V7RIFUJuRgr3zx5FZWGNs28HZAZm6qkIyluPVjQHDx5k1apVOh97mUzGO++8w8qVK/XS7QYZ2Z9++iljxozh5s2b9OvXj9TUVBYtWlQyySUqFTKZDHsPwwKYKhv5v64NNWp0P7P16XfuZ7h7Svv91t/QbgLIpR8kVYGS+AYa40vo4ODAvHnzOHZMW/SjdevWjBs3Dltb26f2k/SsRHXAqVZtnGrVrpC5S/yseHwcQSixYazJyyF82USyE7UFoFJuRuDV/12j5CkPyluPVjTffvstzs7OXL9+HYVCQf369fnxxx9xcNCv8rVBRnbjxo3ZvHkzN27cQKPR4OHhYVDlGwmJsiLrzF4y/t6ETGmKdfd3Mannp1/Hq3/CqS2gUEHbN6B2MT807p99+D39HmQmgJVhKcwkqgeffvopderUITQ0FJlMxs6dOwkKCmLlypVP7SfpWQmJsuPKP/s4+P18RBG6vDERr/Y9DR4jOzWJP1dMIelWJLWatKLdyOkoTQx725R+L0pnYAPcP/tnlTCyqxuJiYkMHz4cGxsboqOjcXd3Z86cOaVrZBdX0rc4nxQJidJCyM0m5b89iHk52DTritK6BkJGMhlH1wMgatSk7f+OGm892UdfR046nNgEiCCo4Z8fYOCCp69oW7tCSrT2u9IMzOyMPymJcqG8K5XdvHmTJUuW6LY9PT0LVLJ9HEnPSkgYhygInD24g6S7t/Bu1x0XD+8CxzVqNftXzkajzgNg/3dzadCqs8EG8sU/fiL59jVA5O6F49z4ezeNOvU3aAxzB2fkKlOEB7JYuzYwqH9FUd0qPs6ePZsvvviC1q1b89JLL7F8+XI++eQTvYMf9TKyW7dubZSQEhKlxf0di8iKOgfISLt4BLe3vkIUHisTq1EX2bcQgoYCafIFPfq1fB0i94I6B+p3BqW0wlhVKO/XnPXr1+fs2bP4+Wnfqpw8eZIGDZ78IJX0rISEcRwLW82xLd8hk8s5tXszb4aux96l7sMGooDwyPNCEDSIoqEexiDk5T3ckMl0hrIhmFja0vKd2UT/tR2VhTUe3V4zeIyKoLq5i+Tk5Oh0syiK1KpVi4yMDL3762Vkv/TSS7rvV65c4fjx46jVagICAmjatKmBIktIlJysWxcf/CwW0aQlkJcah4mDK2bNepJ9Zg/I5Fg+p6eyMrcFnx4Q8Qcgg5ZDivfLNrWBJlKO9aqIIGo/hiAzsP3q1avZsmULcrmcmJgY9u3bh5ubG4IgEB0dTY0aNejatSuiKHLgwIECfSU9KyFhHFHnjgPaFW2NIBBz9UIBI1uhMqHd0DH89dMyANoOeReVqeHB615dB3Pn7DGyUxOxdalH/baGu5wA2Lp5YetWfMahykR56NHKhLm5Odu3b9e9hTx16hQ2NjZ69zfIJ3vbtm0sXbqUbt26IQgC48aN491332Xo0KGGSS0hUULM6/qQdes8IENhaYfKxhEAqw6vYtHyBVAokZta6j9g8wHg3VUbvGhiUTZCS1QKxAf/GNpHX86ePUtYWBibN2/G3NycsWPH4unpyZAhQwyaU9KzEhIlw61pAHcun0UmVyCXy3Ft2KRQmxa9X8G7Q29AxNy6ZO5+1k61eXHmOrJTkzC3q6HL+V0dKGs9Ctoc/0uXLiUrK4v27dszdepUjh07xty5c8nJyaF3795MmDABmUxGREQEU6ZMISMjA39/f0JCQlCpVMTExBAUFERCQgLu7u6EhoZiZWVFamoqEydOJDo6GgcHBxYuXIiT05PjqubMmcPEiRMJDAwkOTmZOXPmsGDBAr3PxSAje/Xq1WzevBl7e3sA3nvvPYYPHy4pf4lyw7nfBFJO/o6Ql4Nt8+7IlA9L8cotnp614YmYWT/1sDrpLghqFA51jI5GJysZslLAro6UlaScKWtfQhsbG6ZNm4aFhfbHWvPmzfnzzz+5evUqcrmc5557jsGDBxd7D0l6VkKiZLQb9BaWtjVIunsLn/bdsa9Vt8h2mswUrduDlW2JdbpCqcLS4aFxJgoasu5eg+zUEo1XVShrPRodHc2MGTPYvHkzNWvW5PXXX+fQoUPMmDGDtWvX4urqyrvvvsvBgwd5/vnnCQoKIiQkBH9/fyZPnszGjRsZPnw4ISEhDB06lH79+rFs2TKWLl1KcHAwixYtokWLFqxcuZJt27Yxc+bMArEzj+Ph4UFYWBgA+/btQ6k0yGw2zMgWBEGn+EGbokpeBfI6Sjw7yE3MsW9bfjzrAyoAACAASURBVIULMsN/JfP4LwCY+nTE+vm3Sj7YnTPw9/faypoO9aDzeG1WE4lywRhfwvT0dF2eVAATE5NCGT/c3d1xd3cHICEhgRUrVuDh4cGIESNYsGABrq6ufPnll0ycOPGpc0p6VkKiZMjlClr0ePrz4dJvq7hxaCsA9Z4bQOP+o4yeV9SoufHTTDKjIzBBRoqtEoemzxk9bmWkrH2y9+7dywsvvICLiwsAX331FVFRUdSrVw83NzcA+vbty549e/Dy8iIrKwt/f38ABg4cyKJFi3jllVcIDw9n6dKluv2vvfYawcHBHDp0iHXr1gHw4osvEhISQm5u7hMzOI0YMaJI+Us18DEfHx8fZs2apVuN2bx5M97e3sV3lJCogoiiQOaJ7brtnIg/sWwzqOQr5hF7HpSuBxKjIPYK1Cr8OlOi8tGpUyeysrJ022PHjuWDDz4osu3t27d59913MTMzY+PGjSiVSpYtW0ZwcDADBxb/A1HSsxISZYMmL0dnYANEHdmGZ8//Q2lmnKtgxu1LZEZHPNgSiT8W9swa2cagz2JFVFQUJiYmjBkzhtu3b9OlSxcaNWpUwKXDycmJuLg4YmNjC+x3dHQkLi6OpKQkrKysUKlUBfYDBfoolUqsra1JSkrC2dm5SJkf1fNZWVn8999/XL16Ve9zNsjI/vzzz1myZAlTp05FEAQCAwOZMWOGIUNISFQhZMhMLBCz0wER5MqnZhMRstPJu3MJhZ0Lyhp1CjcwsQKZ/KGhbYjvuITRGBOwc/jw4UIPh6KIiIhg1KhRjBo1ig0bNpCXl6d7vahWq9FoNEX2exRJz0pIlA0yuRKFqTmaHO0PZoXKFLnS+LeJSvNHXQ5lKMz1D4yrahijR/VZrNBoNBw5coT169djaWnJ6NGjMTMzK+DWI4oiMpkMQRCK3J//3wIyPMEtSBTFp74pbNWqVYHtjh078sILLzz9hB/BICPbzMyMoKCqFQkrIVFSZDIZNr3Hknbge9CosezwKnKToiPRhcxUkjZNQ8xMAWRY93of0wYBBRv5v6zNxZ2RAJ6dwcG9rE9B4hGMCdixsrIqYGQXRWJiIiNHjmTGjBn06NGDlJQUXn31VdasWUNWVhZjxoyhV69exc4p6VkJibJBrlDg7OHDvUvaqr2O9b1Lxcg2c6qHS9cRxP3zK3kKc2r1esfoMSsrxuhRfRYratasSdu2balRowYA3bp1Y/fu3QX6xcXF4eTkhIuLi26FGiA+Ph4nJyccHBxIS0tDrVajVCp17UG7Ch4fH4+LiwtqtZqMjAzs7AwLgJ03b57ebQ0ysrds2cKXX35JcnIy8PBXQ0RERDE9JSSqJipXLxz+b36x7XJvnn5gYAOIZF84VNjItqwJXT8ufSEl9KMEATuGPEt++OEH0tPTWbZsGcuWaVOEubu7Y25uzuDBg/H09KRTp07FjiPpWQmJskGTm0Nm1AVszLXFZ7JvX0KdnYHSzPi3ijVbv4i9f29Onz6NqUMto8ertBihR/VZrOjSpQtBQUGkpKRgZWXF0aNH6dmzJytXruTGjRu4ubmxY8cOBg8eTO3atTE1NeXEiRMEBAQQFhZGx44dUalUBAQEsHPnTvr376/bD9rV9LCwMMaMGcNvv/1GQECAzq1EX/JrH+iDQUb2ihUrWLNmDV5eXgYJJCHxrCO3dXy4IZOhsJVKrVc2yjpg58MPP+TDDz8s8tg77+i/siXpWQmJskGuVKG0tEGdmQaA0swShcqsgqWqWpS1Hm3WrBmjRo1i2LBh5OXl0bZtW1599VUaNGjA+PHjycnJoVOnTrq3gqGhoboUfk2aNGHEiBEAzJgxg+DgYL755htq1arFV199BcD48eMJDg6mT58+WFtbExoaatC5GIpBRradnZ2k+CWeGYry2yopJrV9sHzu/8iOOIKyZl0s2hqWG1mi7CmJL6Gh7UsDSc9KlJR8Y6a09Nqzhkwux2f4dKJ2rwFE3HqMQFbMyqpEQcpDjw4ePJjBgwcX2Ne2bVu2b99eqK23tzdbt24ttL927dpFZgCxs7Pj66+/NkwgI9DLyA4PDwegUaNGhISE0KNHjwK5Ah93DJeQqMxo1Hn8vHAa54/uxamuB6/PWIKdo4vR45r7dcPcr1spSChRHZH0rIQx3Ph3Hyc2LgKZjNavfUS9gC4VLVKlxMq1AU3emlnRYkhUE/QyshcvXlxgOzIyUvddJpPx448/lq5UEpUWQRD4b/92EmKiaNqhJ64Nql5qsXNH93LuyB8AxN6+wb4NKxg8PqSCpZIoa8r6NaexSHpWoqSoc3M4vi4UQaMG4J+1C6jTvANH92zn9vWrBD7fi4ZNmlewlBLPApVdj1Y29DKyg4KC8PX1lV5BSfDn5lUc2vgNMrmcf3du5P3/bcahVhHp6iox6tzcp25LPJuIGBTHqOtTXkh6VqKkiIKAIDxMDylq1Ozc8D0bV4QilyvYvekH5v64nToejSpQSolngcquRysbepURmz59Om3btmXcuHFs2rSJ27dvl7VcEpWUa6f/AbRKXZOXR/TlsxUs0f+3d+dxUVf748dfMzDsKKKC+xJCZqKSKJqm5pILEOZeSstNzTQ1C1xzxbUwuy5ZWlqhXUuFDEWt7880y9zL5SYqJkqisonsMMN8fn9wmUQsGbYB5v3sMY+YzzLz/hzHN2/PnHM+xvN86hmauBfcBMbG3pGew14xcUSiMhT2wBj7qCySZ0VpaWxsaf/sX3ejbT94HL+fPgaAXp9Pfr6Oi2dPmSo8UYNU9Txa1ZSoJ/ubb74hIyODkydPcuLECcLDw0lPT8fHx4du3brRt6+MQzUXLT07ERd9BpXaArVaTROPtqYOyWjWtnZMeO9z7ibdwsGpLhora1OHJCqBUoqlpyrzd4PkWVEWbfo/zyNPDkSlUmHtUJvLN1M4e+wwarUFqMC9rZepQxQ1QFXPo1VNiVcXcXBwoFevXvTq1Ytr165x7NgxwsLCiIyM5OTJkxUZo6hCeo0ch0OduiTHX8fzqf7UbdTM1CGVilqtpo5LI1OHYfZy05LJS7+DQ4OWFT7LX68o6I3M9sYeX1aSZ0VZ2Dj+dVMNv9HjcKjlRNwfl+jSexDNWlXxFWsUBbJug4UV2DibOhrxN6pDHq1KSlRkZ2RkcOTIEX788Ud+/vln6tatS/fu3Zk/fz4dOshkCnOitrCg80BZnk6UXeL5n4n+KhQUPbWaP4bnKyHlcve1v1PVxxJKnhXlSa1W0ztgpKnDKBlFgcvbIeX3gufNB0DDLqaNSTxQVc+jVU2JiuwuXbrQuXNnhg4dyltvvYWzs/wrU4gHSr4CV74HS2to7Q929UwdUZV1/YevQNEDkHbtAndj/0udVuZbTEqeFWYrJ/mvAhvgz4NmUWSnXj7NjcM7sbSrRYuBr2JdW35f1DQlmvj42muvkZWVxfr161m/fj2HDh0iJyenomMTonrRZsOpTyDlD0i4AKdlybV/orGvBaq/UpDGzrFC30+hFBN2KrEPRvKsMFsWNkDhqjoqsLQ1ZTSVIi89hYtfLiP92gXuRB/n8o6Vpg6pRKp6Hq1qSlRkT548mW3btrF161a8vLzYt28ffn5+vPLKK3z66acVHaMQ1UNuOuh1GL5Qy0oydURVmnvAJBwaPYLGvjYt+7+EQyO3Cn2/wgk7xj4qi+RZYbasHMAtADSOYFMX3Ic9/JxqLi8tGaXw94WiJyc53tQhlUhVz6NVjVG3Va9duzZ9+vShbt26NG/enD179rB161ZeffXViopPiOrDvh44tYDU2ILnTWv+151lYVu3IV6vV17vTXWZsCN5Vpil+h0KHmbCzrUFdg1aknXrKgCunQaaOKKSqS55tKooUZG9f/9+Tp8+zalTp7h16xZPPPEETz75JGvWrKFFixZGv2lKSgojR45k8eLF+Pj4ADB//nx27tyJRvPXxKeZM2cycmTBxI2NGzcSFhZGWloanp6eLFy4kEceeQSArKwsQkJCOHDgADqdjj59+jB//nzs7e0BuHr1KgsWLODs2bPY29szZswYJkyYYHTcQvwjlRo6jYekaLCwhrpy44eqpKovPVWeeTYjI4Pnn3+e9evX06RJE1auXMmePXtwdCwYkjNixAhGjx5NfHw8wcHBJCcn06JFC0JDQ3FwcCAtLY2goCDi4uJwdnZm1apVuLi4kJeXx5w5czh//jw2NjaEhobi5lax30AIUROpLTU8/upSUmN+xdLWkVotHjd1SCVS1fNoVVOiIvurr76ia9euLFiwgMcff7xMdyQ7deoUM2fO5Pr160W2nzt3jpCQEJ577rli50RERBAWFsann35Ks2bNWLVqFVOmTCEyMhKVSkVISAg3b95k//795Ofn8+abbxIaGsr8+fPRarVMmDCBfv36sXHjRmJiYnjttddo3rw5AwdWj385imrEQgOunqaOQjyAgvFjAytzLGF55dkzZ84wb948rl69ath29uxZ1q5dS5s2bYocu3DhQkaOHMmzzz7LunXrWLt2LTNnzuSDDz7Ay8uLDRs28M033xASEsKaNWsICwvD2tqavXv3cuLECYKDgwkPDy/TdQthriysbKjbpqupwzBKVc+jVU2JxmRv2rSJcePG0bZt2zIV2BEREQQFBTFt2rQi2/Py8rh06RJt2z74xiZff/01L7zwAu7u7lhbW/P2228THx/PsWPHyM7OJjIykilTpuDk5ETdunUJCgoiPDyc7OxsTpw4QUJCAlOmTMHKyoo2bdoQGBjI1q1bS30dQghR3sorz27bto25c+fi4uICFNyh7cKFC6xevRp/f38WL15MXl4eWq2WEydOGDobhgwZwv79+wE4ePAgAQEBAPj5+fHTTz+Rl5dXZHunTp1IS0sjLi6uLJcthBA1llFjssuqe/fu+Pv7Y2lpWaTQjo6ORqfTsXr1ak6dOoWjoyNDhw5l7NixqNVqYmJiGDdunOF4jUZDixYtiI6OxsnJCa1Wi4eHh2G/m5sbOTk5xMbGcvnyZVq2bImVlZVhf6tWrdiwYYPR8efn55fyykVh20kblp45t2F5XLO5fM25bNmyIs/v3LlDhw4dmDFjBk2bNmX27NmsX7+e559/HgcHB8MQvfr165OYmAhAQkKCoUi3tLTE0dGRO3fuFNl+7zlNmzYtcXwl+bM05896RZO2rTjVoW3LGpu55NHyUqlFdv369R+4PT09nc6dOxMYGMj777/PhQsXmDRpEmq1mrFjx5KZmYmtbdElfWxsbMjKyiIjIwMAOzs7w77CYzMzMx94rq2tLVlZWUbHf+7cOaPPEUXV6DZUFNTaLPSWNqCuuLsX1ug2rEBKKSbsKDXgt4Ozs3ORToVXXnmF2bNnM2rUqGI95n/Xg64oCmq1GkVRihxTuN0Yxnx+5bNeccy5bRVtwdKYKo1Nhbx+TW5bc82jpVWpRfbf6datG926dTM8b9euHS+99BJRUVGMHTsWW1vbYuvF5uTkYG9vbyius7OzDRMds7OzgYJbFNvZ2RmeF7r3WGN4enpiUcG3fq6p8vPzOXfuXI1tQyVfS8aeD9DFR6OyccDBLwjLeiXv3SuJmt6G/6Tw2svCXHtgrl27xq+//srgwYOBgra0sLDA2dmZ9PR0dDodlpaWJCYmGnqpXVxcSEpKokGDBuh0OjIzM3FycsLV1ZWEhASaNWsGQFJSUpGe7ZIoyefXnD/rFc3c2/bWsSiu798MQNN+L9Kwq3+5vXZ1aNuy5lJzzaOlVSWK7P/7v/8jKSmJUaNGGbbl5eVhY1Pwr0x3d3cuX77M008/DYBWqyU2NhYPDw9atmyJRqMhJiaG9u3bA3DlyhXDkJLk5GRiY2MNv0gAYmJicHc3fuUHCwuLKvsXp7qoqW2Ye+UEuvhoAJTcTHJO7aL2oKkV8l41tQ0rmrlO2LGysmL58uV07tyZhg0bsmXLFvr164dGo8Hb25s9e/YQEBBAeHg4PXr0AKBnz56Eh4czceJEdu/ejbe3NxqNhp49exIREYG3tzcnT57E2tqaRo0aGRWPMZ9f+axXHHNsW71Oy/XvPjdUfXHff0HDzgOwsCrfHu2a3LbmmkdLy7jv+SqIoigsW7aMX375BUVR+PXXX/niiy8My/cNHTqULVu2EB0dTW5uLitXrqRevXp4e3tja2vLwIEDCQ0NJSUlhZSUFEJDQ/Hz88PGxgYfHx/q1KnDypUryc3NJTo6mrCwMIYNq/mL3YtKdN/wEFUFDhcRpWOuN1Fo2LAhc+fOZfz48QwYMACVSsUrr7wCFCydumPHDgYNGsTp06d58803AZg6dSpnz57F19eXbdu2MW/ePAACAwPR6XT4+vqyePFi3n33XZNdlxClce9wJ5VKDWWYZGyOzDWPllaV6Mnu168fs2bNYsGCBdy+fZt69eoxefJkwyz2YcOGkZ6ezqRJk0hJScHT05OPP/7YMGFn/vz5rFixAn9/f7RaLX369GHu3LlAwaSdTZs2sWjRIrp164adnR2BgYEMGTLEZNcrah6rR57AqlVn8mKOo3ash30X+UdcVWNuN1E4cOCA4WdfX198fX2LHdO4cWPCwsKKbXdycuKjjz4qtt3a2poVK1aUb6BCVBK1pQa3gEn88e16FEXhEf/XsNBYmzqsasXc8mhZmazIvnjxYpHno0aNKjJc5F4qlYp//etf/Otf/3rgfgcHB0JCQggJCXng/ubNm8ttiUWFUqktqNV/Ikrf8aC2KNMSbEkXjnPtx3CsHJ3x8BuLdS3ncoxUCCFMS1H0pB3/lpyrv2Hd9DFqdx1Wad/+1e/Qi3rtngLkG0dR8apET7YQNYXKomx/pXJSEzgbtgRFrweVGm1WGk+MXVxO0Zk3mbAjRNWQ9ftPpP2yA4C8WzFY2NXG0WtApb2/FNelJ3nUOFJkC1GF5KQmFhTYAIqerMQbpg2oBlEUxeilpMx56SkhKoo29Rao1KAUdCbo7twydUiihCSPGqdKTHwUQhRwbOyOvctfS/816TLQhNHULEopH0KI8mXn0QVV4eobKhV2rbv98wmiypA8ahzpyRaiCrHQWOE9KZTki6ewcnCiziOepg6pxpAeGCGqBqv6zWgQuILcmzFYubZEU6ehqUMSJSR51DhSZAtRxVha2+H6v4k5ovzolYKHsecIIcqfZW0XLGsbdyMjYXqSR40jRbYQwiwUTNgxtgemgoIRQohqSPKocWRMthBCCCGEEOVMerKFEGZBlp4SQoiykTxqHCmyhRBmQfnff8aeI4QQooDkUeNIkS2EMAsyYUcIIcpG8qhxpMgWQpgFWXpKCCHKRvKocaTIFkKYh1KMJTTjbzmFEKI4yaNGkdVFhBBCCCGEKGdSZAtRStqcLK799jPJ1y+bOhRRAkop/xPCnOlys0m6cJz0+D9MHYqoAiSPGkeGiwhRCtrcbCJCxnP3VhwAT70UTOsefiaOSvwTPaWYsFMhkQhRPeTn5XD6w7fJSvwTAI/n3qBRp2dMHJUwJcmjxpGebCFK4ebFM4YCG+D8/+0wTSAZSXDo37B/EVw9YpoYqonCCTvGPoQwV6lXzxsKbIA/f/7WhNFUL/kpf5IVEULmVzPRxhwzdTjlRvKocaTIFqIUHJxdDD+r1Gpq1W9kmkBOfwl3YiErBX77GtJumSaOaqDwJgrGPoQwV9a16//1RKXGtm4D0wVTzeQc2IA++RpKWiK5Bzeiz7xj6pDKheRR40iRLUQpODd5hJ7/moVz01Y079CN7i++bZpActKLZrC8DNPEUQ1ID4wQxnFo0JzWw6Zi37Al9R7rjMfgSaYOqdpQsu7+lZsVBSU307QBlRPJo8aRMdlClJJHtwF4dBtg2iAe7Qun/1Pws3OLgod4ID3Gjw0057GEQgA0eKIPDZ7oY+owqh0rLz/yjm4DwKJJW9R1TPRtZzmrzDy6YsUK7ty5w/Lly7lw4QJz5swhMzOTjh07snDhQjQaDfHx8QQHB5OcnEyLFi0IDQ3FwcGBtLQ0goKCiIuLw9nZmVWrVuHi4kJeXh5z5szh/Pnz2NjYEBoaipubWykjfDjpyRaiEtz8I5r/C1vLbz/sLt9/1Tf3gX5z4Kkp8NRkUMu/m4UQBT2Od879yM0ftpIVf8XU4ZgdK89+2A0LwfbZWdj0n4pKJeWWMX755RciIiIMz4ODg5kzZw779+8HYNu2gn/ALFy4kJEjR7Jv3z48PT1Zu3YtAB988AFeXl7s3buX4cOHExISAkBYWBjW1tbs3buX2bNnExwcXKHXIX/qQlSwpBvX+GTGK/z8zRd8s3oBP4V/Xr5v4FAf6j0Caovyfd0aRr7mFOYk6fhu4r5dQ+Iv33Ll8znkJMY9/CRRrtR1GmHh2gqVuuaUWpWRR1NTU1m1ahUTJkwA4MaNG2RnZ9OxY0cAhgwZwv79+9FqtZw4cYKBAwcW2Q5w8OBBAgICAPDz8+Onn34iLy+vyPZOnTqRlpZGXFzF/d2oOX/yQlRRcdFnyNdpUfQFX5pd+e2oiSMyTzJhR5iT9D/OFPyg6FH0+WTGRZs2IFEjlCWPZmRkFHnk5eU98D3mzZvHtGnTqFWrFgAJCQm4uPy12ED9+vVJTEzkzp07ODg4oNFoimy//xxLS0scHR25c+fO375WRZEiW4gK1tijLWq1Bar/9TS3aPuEiSMyT9KTLcyJQ7PHC35QqUGlxq6xh2kDEjVCWfJoz5496dixo+Hx8ccfF3v97du307BhQ7p27WrYptfrUalURWJQqVSG/9/r/uf3nqNWq4udU7i9osgATiEqmEvTR3h58cecO7yfek1a0Kn/MFOHZJaU/z2MPUeI6qj+kwFY2NiRkxhH7TZPYuva3NQhiRqgLHn00KFDWFj8NazRysqq2LFRUVEkJiYSEBDA3bt3ycrKQqVSFeltTkpKwsXFBWdnZ9LT09HpdFhaWpKYmGjopXZxcSEpKYkGDRqg0+nIzMzEyckJV1dXEhISaNasWZHXqihSZAtRCZo91oFmj3UwdRhmTa8o6I3smTb2eCGqCpVKTd2O/U0dhqhhypJHHRwcihTZD7J582bDz+Hh4Rw/fpxly5bh5+fHyZMn8fb2Jjw8nB49eqDRaPD29mbPnj0EBAQYtkNBr3l4eDgTJ05k9+7deHt7o9Fo6NmzJxEREXh7e3Py5Emsra1p1KjiVn6RIluICpZ0I5bvP1+DTpfH06Neo4lHW5PEoc/N5u5PX5J/5yZ2bZ/GrnU3k8QhhKh4+Xk53Px/W8hJuE6ddj2p62Wmy/DF/ARXj4NTI/B6DiytTR2RKIXQ0FDDEn6PP/44L774IgDz589n5syZfPzxxzRs2JD3338fgKlTpzJz5kx8fX1xdHQkNDQUgMDAQObNm4evry8ajYZ33323QuM2SZGdkpLCyJEjWbx4MT4+PgDs37+fDz/8kLi4OJycnBgyZAgTJ040jJUZOHAg8fHxRcbO7NixAzc3N7KysggJCeHAgQPodDr69OnD/Pnzsbe3B+Dq1assWLCAs2fPYm9vz5gxYwyzVoWoaFsXv0lqQjwoCn9ePEfQpn1orG0qPY67h7eSfeEwKHry4i9iWachVq6PVHocplKaiYzVtSM7IyOD559/nvXr19OkSRMiIyPZsGEDAM2aNWPp0qXUrl2bw4cPExQURIMGBXfya9OmDcuWLfvbtWQVReHdd9/lhx9+QK1Ws2jRIry9vU15qeJv3Dq4jeTT34GikBl3AWvnBjg0f9zUYVWu25fg+JcFPydeKVjitKMM1yuLysyjQ4YMYciQIQC0bt2anTt3FjumcePGhIWFFdvu5OTERx99VGy7tbU1K1asKF1ApVDpEx9PnTrFyJEjuX79umHb+fPnmT59Om+++SYnT55k48aNhIeH89lnnwEFvzCuXr1KVFQUv/76q+FRuIB4SEgIN2/eZP/+/Xz33XfcvHnT8K8WrVbLhAkT8PT05NixY2zYsIGtW7eyd+/eyr50YYb0ej2pt2+g6PUoikJuVgZZ6XdNEovuTjwof90WQJd62yRxmIq5THw8c+YMo0eP5urVqwDcvn2b9957j88//5zIyEhatWrFmjVrADh79iyvv/46u3btYteuXSxbtgz4+7Vk9+/fz6VLl4iKimLdunXMmDEDrVZrmgsV/yg3Ob5IdZObcsuE0ZhIesI9TxRIM8M2KGfmkkfLS6UW2REREQQFBTFt2rQi22/cuMGoUaN4+umnUavVuLm50a9fP06cOAEUFOFOTk40bty42GtmZ2cTGRnJlClTcHJyom7dugQFBREeHk52djYnTpwgISGBKVOmYGVlRZs2bQgMDGTr1q2Vcs3CvKnVajr09jc8b+nZiVp1K26SxT+xf7yX4We1XW2sm5lm2IqpmMsSftu2bWPu3LmGyTwqlYpFixbh7OwMwGOPPcbNmzcBOHfuHD/88AP+/v68/vrr3LpVUIT83Vqyhw4dwt/fH7VaTcuWLWnSpAmnTp0ywVWKh3Fu38vws4WtA7VaeZkuGFNp1Bas7P967vak6WKpIcwlj5aXSh0u0r17d/z9/bG0tCxSaPfv35/+/f+aoJGTk8PBgwfx9y8oTs6dO4etrS1jxozh8uXLNG7cmMmTJ/P0009z7do1tFotHh5/LU/k5uZGTk4OsbGxXL58mZYtWxaZxdqqVSvDV6fGyM/PL81lC/5qO3NsQ9/XZvFo557otHm4d+yOXl+6m8yWtQ2tH+2Gc+0G6O7exrqZJ1jZVZs/j/KIU0FBb+S8eKUari9S2BtdyMXFxVBwZ2dns2HDBkaPHg1A7dq1GT58OH369OGrr77i7bffZuvWrX+7lmx5rDFbkj9Lc84X5cXxUR/cXl5KbvIN7Ft4orarTX5+vnm1rbUjDJiN6vZFlFoNwLkpVOB1V4e2LWts5pJHy0ulFtn169d/6DEZGRlMnToVGxsbXn75ZaCgJ8bT05O33nqLRo0asW/f/37XPgAAIABJREFUPiZPnsyWLVvQ6XQA2NnZGV7D1tYWgMzMTDIzMw3P792flZVldPznzp0z+hxRlNm2oYUDWMD5//5e5pcqexvawUXzu82yOY3JfpA7d+4wadIk2rRpw9ChQwGKjE0cOXIkoaGhpKen/+1asg9ar9bYNWaN+fyabb4oV44QE1tsq3m1rQZSk+F6cqW8W01uW3PPo8aqUquL/PHHH0yZMoW6devyxRdf4ODgAMDYsWOLHPfss8+ye/du9u/fb+jtzs7ONkx0zM7OBgqWi7GzszM8L3Tvscbw9PR86PIz4sHy8/M5d+6ctGEZmHMbFl57WZRmbGBNGUt448YNXn31Vfr06UNQUBAAeXl5fPrpp7z++utAwbXq9XosLCz+di3ZBg0akJDw1zjX0qwxW5LPrzl/1iuatG3FqQ5tW9Zcas55tDSqTJF96NAh3nrrLUaMGMHbb7+NpeVfoX366ae0adOmyB2A8vLysLa2pmXLlmg0GmJiYmjfvj0AV65cQaPR0KJFC5KTk4mNjTUsVg4QExODu7u70TFaWFhU2b841YW0YdlJGwpj5OXl8eqrrzJq1CjDt4NQcCOIyMhI3N3d6du3L+Hh4XTo0AE7O7u/XUu2R48e7NixAz8/P65fv05sbCyenp5GxWPM51c+6xVH2rbiSNuKQlXituq//fYbkyZNYtasWcyYMaNIgQ1w8+ZNFi5cSFxcHDqdjh07dvDrr7/y3HPPYWtry8CBAwkNDSUlJYWUlBRCQ0Px8/PDxsYGHx8f6tSpw8qVK8nNzSU6OpqwsDCGDZNlfIQwJ+Y6Yeebb77h+vXrREREEBAQQEBAALNmzQJg5cqVbNiwgUGDBvHNN9+wePFioGAtWZ1Oh6+vL4sXLzasJTtgwAA8PDzw9/fnjTfeYMmSJdjYVP5ylEII0zDXPFpaVaIn+6OPPkKn07FkyRKWLFli2N6xY0c++eQTpk+fjlqt5oUXXiA9Pd0wcbF584LbxM6fP58VK1bg7++PVqulT58+zJ07FwBLS0s2bdrEokWL6NatG3Z2dgQGBhrWXhRCmAd9KSbsGHs8FF+j2lQOHDgAwIgRIxgxYsQDj3nsscf4+uuvi23/u7VkVSoVM2bMYMaMGeUbrBCiWqisPFpTmKzIvnjxouHnBy0Yfi8rKytmz57N7NmzH7jfwcGBkJAQQkJCHri/efPmfPrpp6UPVghR7VXGhJ0zZ84wb948wxrVQghRk8jER+NUieEiQghR0cpyE4WMjIwij7y8vAe+x/1rVAshRE0iN6MxTpUYLiKEEBWtLD0wPXv2LLJK0RtvvMHkyZOLHX//GtVCCFGTSE+2caTIFkKIhzh06FCR1QLuvbmVEEII8SBSZAshzIJeUdAb2aVSeLyDg4MsySWEMHtlyaPmSIpsIYRZUP73MPYcIYQQBSSPGkeKbCGEWVAoxZ3KzPrXgxBCFCV51DhSZAshzEJlTtgpXKNaCCFqEpn4aBwpsoUQZqE0S0mZ89JTQghxP8mjxpEiWwhhFvRKwcPYc4QQQhSQPGocKbKFMAP6fB1xR/eRl5FKY+8+2NVtaOqQhBDmIl8HMT9BTjq4dQWHeqaOSIhKIUW2EGbg94j1xB3dCyo1137eTc+ZG9HYORr267Radn/6PjFnTtDGpwcDAiehrnFL1imlmIBjxl0woupSFLh0AOJOgFMT6DAcLK1NHdXfO/4fuHIEVCq49CMELAIrW1NHJUpF8qgxpMgWwgwkXDhR8IOiR5uVRtrNWOq6eRr2H971JYe//Q8oCjdjL+PcoAldBgwxTbAVRCbsiBrj1u9wflfBz3dvgsYO2lfhv683zhf8X1EgNwNSb4BLK9PGJEpF8qhx1KYOQAhR8eq6eYJKhUqtxsLaFgfXZkX230m4gVpVkA5UajV3bsebIswKVThhx9iHEFVOVso9T5T7nldBrh6AClRq0NhC7QamjkiUkuRR40hPthBmoO3wKdi7NCUv/Q5NuwzA2qF2kf2d+gZwbF8Een0+Gisbnnh6kIkirTgyYUfUGI3awYW9Bb3CKhW0fNLUEf2zroFQuyHkpoN7d7B2MHVEopQkjxpHimwhzICFxppWfUf97f6mHo8zY+MublyJppnH49Su51qJ0VWOgjuVGXsTBSGqINva0G82JP0BtVzBsYr/fbW0gnY17x/u5kjyqHGkyBZCAODs2ghn10amDqPCyFhCUaNYO0DjdqaOQpgZyaPGkTHZQgghhBBClDPpyRZCmAW5U5kQQpSN5FHjSJEthDALMmFHCCHKRvKocaTIFkKYBemBEUKIspE8ahwpsoUQZkHB+Fnu5vurQQghipM8ahwpsoUQZkF6YIQQomwkjxpHVhcRQgghhBCinElPthDCLMiEHSGEKBvJo8aRIlsIYRbka04hhCgbyaPGkSJbCGEWZMKOEEKUjeRR45hkTHZKSgr9+vXj2LFjhm1nzpxh+PDheHl50bt3b7Zv317knIiICPr160eHDh0YMmQIv/76q2Fffn4+K1as4Mknn8TLy4vXX3+dhIQEw/7k5GQmTpyIt7c3Pj4+LFmyBJ1OV/EXKsR98vN13Lx6iaz0u6YOxewU9sAY+xCiusi7c5u81ISHHyhEKUkeNU6lF9mnTp1i5MiRXL9+3bDt7t27jB8/nsGDB3PixAmWLFnCsmXLOHv2LADHjh0jJCSE5cuXc+LECZ599llef/11srOzAVi/fj0///wzO3fu5PDhw9jY2PDOO+8YXv/NN9/Ezs6Ow4cPs2PHDn755Rc+++yzSr1uIfJysln/9ousmTqK5a8M4Or5U6YOybwooBj5qK5dMBkZGfj7+/Pnn38CcOTIEfz9/XnmmWdYtWqV4ZfehQsXGDJkCP3792f27NlotVoA4uPjGT16NAMGDGDChAlkZGQAkJaWxvjx4xk4cCCjR48u0pkhTOvWwS+59NFkLq1/g9uHvzZ1OKKmMqM8Wh4qtciOiIggKCiIadOmFdn+3Xff4eTkxOjRo7G0tKRr1674+/uzdetWALZv346vry8dO3ZEo9Hw8ssvU6dOHaKiogz7x40bR8OGDXFwcGDOnDn8+OOPxMXFce3aNY4fP05wcDC2trY0bdqUiRMnGl5biMry+7GDxP8RDUC+No+D2zeZOCLzoleUUj2qmzNnzjB69GiuXr0KQE5ODrNmzWLdunVERUVx/vx5fvjhBwCCg4OZM2cO+/fvB2Dbtm0ALFy4kJEjR7Jv3z48PT1Zu3YtAB988AFeXl7s3buX4cOHExISYoIrFPfLz80m6ZdvDM8Tf9qJXpdnwohETWUuebS8VOqY7O7du+Pv74+lpWWRQvvy5ct4eHgUObZVq1bs2LEDgJiYGIYOHVpsf3R0NOnp6dy6davI+fXq1aN27dpcvHgRACcnJ1xdXQ373dzciI+PJy0tjVq1apU4/vz8/JJfrCiisO3MuQ2tbe3/eqJSYWPvaFR7mHMbmuM1l9a2bduYO3cu06dPB+Ds2bM0b96cZs2aAeDv78/+/ft59NFHyc7OpmPHjgAMGTKEDz74gFGjRnHixAlDYT1kyBBeeOEFZs6cycGDB9myZQsAfn5+LFy4kLy8PKysrEocX0n+LM35s14aelSoLDQo+QXfRKg0VugVUB7QftK2Fac6tG1Vjq0mqtQiu379+g/cnpmZia2tbZFtNjY2ZGVlPXR/ZmYmAHZ2dsX2F+67/9zC51lZWUYV2efOnSvxseLBzLkNFbUdrXz6EvvrTzjWb0gT7z789ttvRr+OObdhWRi+ujTynOpm2bJlRZ4nJCTg4uJieO7i4kJiYmKx7fXr1ycxMZE7d+7g4OCARqMpsv3+17K0tMTR0ZE7d+4U6cR4GGM+v/JZLzm1px+Wv38HKhXaNgM4c/af207atuLU5LatjDy6efNmduzYgVqtpm3btixcuJArV64wZ84cMjMz6dixIwsXLkSj0RAfH09wcDDJycm0aNGC0NBQHBwcSEtLIygoiLi4OJydnVm1ahUuLi7k5eUxZ84czp8/j42NDaGhobi5uRkXoBGqxOoitra2pKenF9mWk5ODvb29YX9OTk6x/XXq1DEUzIXjs+8/X1GUYvsKnxe+fkl5enpiYWFh1DmiQH5+PufOnTP7NvTy8ir1uebchoXXXhbK//4z9pzqTq/Xo1KpDM8VRUGlUv3t9sL/3+v+5/eeo1YbN+qwJJ9fc/6sl14HeGbEQ4+Stq041aFty5pLKzqPnj17lvDwcLZv346trS3Tp0/nyy+/ZMeOHSxcuJCOHTsye/Zstm3bRmBgoGFo27PPPsu6detYu3YtM2fONAxt27BhA9988w0hISGsWbOGsLAwrK2t2bt3LydOnCA4OJjw8HBjm6HEqkSR7eHhwc8//1xkW0xMDO7u7gC4u7tz+fLlYvt79OhB7dq1cXV1JSYmxjBkJDExkdTUVDw8PNDr9aSmppKUlES9evUAuHLlCg0aNMDR0dGoOC0sLKrsX5zqQtqw7KQNS8dcerLv16BBA0NPNBTkRxcXl2Lbk5KScHFxwdnZmfT0dHQ6HZaWlobjoaAXPCkpiQYNGqDT6cjMzMTJycmoeIz5/MpnveJI21acmty2ZcmjGRkZRdrFysqq2FCzWrVqMXfuXMPohNatW3Px4sVyG9p28OBBpkyZAkCnTp1IS0sjLi6Opk2bGt0WJVElbqver18/kpKS+Oyzz9BqtRw9epTIyEjDOOxhw4YRGRnJ0aNH0Wq1fPbZZyQnJ9OvXz+goGHXr19PXFwcGRkZLF26lM6dO9OsWTNatGhBx44dWbp0KRkZGcTFxfHhhx8ybNgwU16yEKKS6SnFhJ0a0JPdvn17/vjjD65evUp+fj6RkZH06NGDxo0bY21tzcmTJwEIDw+nR48eaDQavL292bNnT5HtAD179jT0+uzevRtvb2/DsBIhRM1Xljzas2dPOnbsaHh8/PHHxV6/RYsWdO7cGShYfnnr1q20aNGi3Ia2/d0wuYpSJXqy69Spw6ZNm1iyZAmrV6/G2dmZd955hy5dugDQtWtX5s+fz4IFC7h9+zatWrVi48aNhh6USZMmodPpGD16NJmZmfj4+PDBBx8YXn/16tUsWrSIPn36oFarGTx4MBMnTjTJtQohTMNce7Ktra1ZsWIFU6dOJTc3l549ezJgwAAAQkNDDeMcH3/8cV588UUA5s+fz8yZM/n4449p2LAh77//PgBTp05l5syZ+Pr64ujoSGhoqMmuSwhR+cqSRw8dOlSsJ/vv/Pnnn7z22msMHz4cb29vDh06dM/rlX5o2/3nlGbImzFMVmQXrvxRyNPT07B81IMEBAQQEBDwwH0ajYagoCCCgoIeuL9evXqsXr269MEKIUQ1c+DAAcPPXbt25dtvvy12TOvWrdm5c2ex7Y0bNyYsLKzYdicnJz766KPyDVQIYRYcHBxKNIzmwoULjB8/nvHjxxMYGMiNGzfKbWibq6srCQkJhtWWCl+rolSJ4SJCCFHRlFL+J4QQokBF59GUlBTGjh3L3LlzCQwMBCjXoW09e/YkIiICgJMnT2JtbU2jRo3KrX3uVyWGiwghREUz1+EiQghRXio6j37++edkZGSwbt061q1bB0CvXr3KbWhbYGAg8+bNw9fXF41Gw7vvvmvcxRhJimwhhFkozZ3HzPlOZUIIcb+KzqPTpk0rdlfwQuUxtK1wjkplkSJbCGEWpCdbCCHKRvKocaTIFkKYBUVRUIzM9sYeL4QQNZnkUeNIkS2EMAvK/x7GniOEEKKA5FHjyOoiQgghhBBClDPpyRZCmAWZ+CiEEGUjedQ4UmQLIcyCTNgRQoiykTxqHCmyhRDmoRQTdsz6t4MQQtxP8qhRpMgWQpgF6YERQoiykTxqHCmyhRBmoTS3SZfbqgshxF8kjxpHVhcRQgghhBCinElPtqgStFotOTk5ODo6mjoUUUPplYKHseeIyqUoCjmZGSiK3tShCCHuI3nUONKTLUzuwIED1K1bl1q1ajFp0iSzvjuUqDiFdyoz9iEqT15uNp/MGc+SMU+z79+zSbn5p6lDEkLcQ/KocaTIFiY3ZcoUMjIyAPjwww85ffq0iSMSNVHhhB1jH6LynDm4l6vnTwGQnXaHQzs2mTgiIcS9JI8aR4aLCJNTqVSmDkGYAZmwUw1ILhCiSpM8ahzpyRYmt2bNGsNY7DfeeIMnnnjCxBGJmqhwLKGxD1F5OvQcyCPtOgFgW9uZXiNeNXFEQoh7SR41jvRkC5Pr1asXycnJ5OXlYWdnZ+pwRA1VmrGB5jyW0BQ01jaMXfwxWRnp/B59kTqujU0dkhDiHpJHjSNFtqgSLC0tsbSUj6MQAqxt7WQYmRCi2pOqRghhFuROZUIIUTaSR40jRbYQwiwU/HIw9mvOCgpGCCGqIcmjxpEiWwhhFvT/exh7jhBCiAKSR40jRbYQwizIhB0hhCgbyaPGkSJbCGEWFEoxlrBCIhFCiOpJ8qhxZJ1sIYQQQgghypkU2UIIs1D4NaexD2NERkYyaNAgnnnmGbZs2VJBVyKEEKZRGXm0JpHhIkIIs6Bg/AQcY3413L59m/fff5/w8HCsra0ZNWoUnTp14tFHHzXyXYUQomqq6Dxa00hPthDCLFR0D8yRI0fo0qULderUwc7Ojv79+7N///4KvCIhhKhc0pNtHOnJLoHCD0h+fr6JI6m+CttO2rD0zLkNC6+5LMnazs7e6Ak7dnb2AGRkZGBhYWHYbmVlhZWVVZFjExIScHFxMTx3cXHh7NmzpY63pjEmj5rzZ72iSdtWnOrQtmXNpWXJo+ZIiuwS0OsLvhw5d+6ciSOp/qQNy86c27Dw76IxVCoVlpaWREVFleo98/Ly6NatG1qt1rDtjTfeYPLkycViu/dW4IqiyK3B71GaPGrOn/WKJm1bcapD2xqbS8uaRy0tLc0yH0qRXQKWlpZ4enqiVqvN8kMihKkpioJer8fS0viUpVar8fT0LHXPjVar5ejRo0W23d+LDdCgQQNOnjxpeJ6YmFikZ9vcSR4VwvRKm0vLmkdVKhVqtfmNUJYiuwTUavUDf6kKIaqHsiT3e4eJ/JMnn3ySNWvWkJycjK2tLfv27WPJkiWlft+aRvKoENWbORbJZSVFthBClANXV1emTZvGiy++iE6nY9iwYbRr187UYQkhhDARlWLO0z6FEEIIIYSoANL3L4QQQgghRDmTIlsIIYQQQohyJkW2EEIIIYQQ5UyKbCGEEEIIIcqZFNlCCCGEEEKUMymyxUNFRUXRpk0bvLy8DI/g4GAADh06hL+/Px06dGDgwIH88MMPRc7duHEjPXr0oEOHDgQGBvLHH38Y9mVlZTFr1ix8fHzo2LEj06dPJzMz07D/6tWrvPTSS3h5edG9e3c++uijyrngcpSSkkK/fv04duyYYduZM2cYPnw4Xl5e9O7dm+3btxc5JyIign79+tGhQweGDBnCr7/+atiXn5/PihUrePLJJ/Hy8uL1118nISHBsD85OZmJEyfi7e2Nj48PS5YsQafTlfi9hTC1yMhIBg0axDPPPMOWLVtMHU6NsnnzZnx9ffH392fWrFnk5eWZOqQaZ8WKFcycOdPUYYiqQhHiIZYvX67MnDmz2ParV68qnp6eyvfff69otVplz549Srt27ZRbt24piqIo4eHhylNPPaVcunRJycnJUZYtW6b4+voqer1eURRFmTlzpvLSSy8pd+7cUZKSkpQxY8YoCxYsUBRFUfLy8pRnnnlGee+995Tc3Fzlv//9r9K9e3clKiqq8i68jE6ePKn07dtX8fDwUI4ePaooiqKkpqYqnTt3VrZs2aJotVrlyJEjipeXl3LmzBlFURTl6NGjipeXl3Ly5EklLy9P2bx5s+Lj46NkZWUpiqIoa9asUfz9/ZX4+HglPT1defPNN5Vx48YZ3nPMmDHK22+/rWRlZSnXr19XfH19lY0bN5bovYUwtVu3bim9evVSUlJSlMzMTMXf31+Jjo42dVg1wpkzZxQ/Pz8lMzNT0ev1SlBQkLJ582ZTh1WjHDlyRPHx8VFmzJhh6lBEFSE92eKhzp07R9u2bYttj4iIwNvbm759+2JpacmgQYPo1KkTX331FQBff/01L7zwAu7u7lhbW/P2228THx/PsWPHyM7OJjIykilTpuDk5ETdunUJCgoiPDyc7OxsTpw4QUJCAlOmTMHKyoo2bdoQGBjI1q1bK/vySyUiIoKgoCCmTZtWZPt3332Hk5MTo0ePxtLSkq5du+Lv72+4ru3bt+Pr60vHjh3RaDS8/PLL1KlTh6ioKMP+cePG0bBhQxwcHJgzZw4//vgjcXFxXLt2jePHjxMcHIytrS1NmzZl4sSJhtd+2HsLYWpHjhyhS5cu1KlTBzs7O/r378/+/ftNHVaNUKtWLebOnYudnR0qlYrWrVsTHx9v6rBqjNTUVFatWsWECRNMHYqoQqTIFv9Ir9fz3//+l4MHD/L000/To0cP5s6dy927d4mJicHDw6PI8a1atSI6Ohqg2H6NRkOLFi2Ijo7m2rVraLXaIvvd3NzIyckhNjaWy5cv07JlyyK3Yb73tau67t278/333zNo0KAi2y9fvmxUm927Pz09nVu3bhXZX69ePWrXrs3Fixe5fPkyTk5OuLq6Gva7ubkRHx9PWlraQ99bCFNLSEjAxcXF8NzFxYXExEQTRlRztGjRgs6dOwMFw8q2bt1K7969TRxVzTFv3jymTZtGrVq1TB2KqEKkyBb/KCUlhTZt2tC/f3+ioqLYtm0bsbGxBAcHk5mZia2tbZHjbWxsyMrKAvjH/RkZGQDY2dkZ9hUem5mZ+cBzbW1tDa9d1dWvXx9LS8ti28vSZoXj1e9ts8L9/9RmgOH8f3pvIUxNr9ejUqkMzxVFKfJclN2ff/7Jiy++yPDhw+nSpYupw6kRtm/fTsOGDenataupQxFVTPEqQIh71KtXr8hwAltbW4KDgxkxYgQ+Pj7k5OQUOT4nJwd7e3vDsX+3v7BQzM7ONhyfnZ0NgIODA3Z2dobnhe49trqytbUlPT29yLaStFmdOnUMBfL97VJ4vqIoD2wzAHt7+4e+txCm1qBBA06ePGl4npiYWKRnW5TNhQsXGD9+POPHjycwMNDU4dQYUVFRJCYmEhAQwN27d8nKymLx4sW88847pg5NmJj0ZIt/FB0dTWhoKIqiGLbl5eWhVqtp164dly9fLnJ8TEwM7u7uALi7uxfZr9VqiY2NxcPDg5YtW6LRaIiJiTHsv3LlimFIibu7O7GxsUVWxrj3tasrDw8Po9rs3v21a9fG1dW1SJslJiaSmpqKh4cH7u7upKamkpSUZNh/5coVGjRogKOj40PfWwhTe/LJJ/nll19ITk4mKyuLffv20aNHD1OHVSOkpKQwduxY5s6dKwV2Odu8eTO7d+9m165dTJkyhd69e0uBLQApssVDODk5sXXrVj755BN0Oh3x8fG89957PPfccwwePJjjx48TFRWFTqcjKiqK48ePExAQAMDQoUPZsmUL0dHR5ObmsnLlSurVq4e3tze2trYMHDiQ0NBQUlJSSElJITQ0FD8/P2xsbPDx8aFOnTqsXLmS3NxcoqOjCQsLY9iwYSZukbLp168fSUlJfPbZZ2i1Wo4ePUpkZCRDhw4FYNiwYURGRnL06FG0Wi2fffYZycnJ9OvXD4AhQ4awfv164uLiyMjIYOnSpXTu3JlmzZrRokULOnbsyNKlS8nIyCAuLo4PP/zQ0GYPe28hTM3V1ZVp06bx4osv8txzz/Hss8/Srl07U4dVI3z++edkZGSwbt06AgICCAgIYNWqVaYOS4gaTaXc20UpxAMcP36c999/n0uXLmFtbY2vry/BwcFYW1tz+PBhQkNDuX79Oo0bNyY4OJiePXsCBeMpN2/ezNatW0lJScHT05OFCxfSsmVLADIyMlixYgUHDhxAq9XSp08fw+x3gGvXrrFo0SLOnDmDnZ0dY8aMYfz48SZrh9J69NFH+eKLL/Dx8QEKVmtZsmQJly5dwtnZmYkTJzJkyBDD8bt27WL9+vXcvn2bVq1a8c4779C+fXug4NuAf//733z77bdkZmbi4+NDSEgIdevWBSApKYlFixZx7Ngx1Go1gwcPJigoCAsLixK9txBCCCHKhxTZQgghhBBClDMZLiKEEEIIIUQ5kyJbCCGEEEKIciZFthBCCCGEEOVMimwhhBBCCCHKmRTZQgghhBBClDMpsoUQQoga5OrVq7Ru3ZqIiIiHHvv111+ze/fuSojqL7179+bPP/+s1PcUwhSkyBZCCCFqkJ07d9K/f3+2bdv20GNPnz5NXl5eJUQlhPmxNHUAQtwrKyuLVatWcfDgQWxtbbGxsWHcuHGGOx7e69FHH+XixYsVFsusWbN44403aNy4cYW9hxBClKf8/Hx27drFpk2bePnll4mOjqZ169b07t2bL774giZNmnDs2DHWrl3L+PHjOXDgAEePHqVu3bq0bduWOXPmcOPGDSwtLZk2bRo9evQgPT2d6dOnc/36dZo2bcqtW7dYu3Ytx48fJyIigtTUVLp3785zzz1HSEgI2dnZhtu4v/DCC6SmphIcHMytW7dwc3MjNzcXAL1ez8qVKzly5Ag6nY4BAwYwadIkE7egEOVHimxRpUycOBE3Nzf27NmDlZUV165dY/z48Wi1WgYNGlSpsRw7dkwSvhCiWvnxxx9xcnLC3d2d/v3785///IeFCxc+8NinnnqK3r1707lzZ3r27Mmbb76Jt7c3H330EXFxcTz//PN88803fPLJJzRv3pz169dz9uxZRo4caXiN+Ph49u3bh0ajYcmSJUyYMIFu3bpx48YN/Pz8eOGFF1i9ejWtW7dm48aNnDx5kr179wIFPe5arZaIiAi0Wi0TJ07k4MGD9OrVqzKaSogKJ0W2qDJOnDjB9evX2bRpE2p1wUim5s16SnieAAAF9ElEQVSbM3v2bJYuXUq7du0IDg4mKyvLcJtxgOzsbObNm8eFCxdQqVS8+uqrDB48mPDwcH744QfS0tK4fv06L774IvHx8Rw9epTatWvzySefYGNjw+7du9m0aRP5+fm0atWKhQsXEhYWRkJCAuPHjycsLIzbt2+zdOlSMjMzcXR0ZP78+bi5uREYGEitWrW4cuUKy5cvp0OHDqZqPiGEYOfOnfj5+QHg5+fH2LFjmT59eonOPXr0KIsWLQKgadOmtG/fnjNnzvDzzz/z3nvvAdCuXTs8PDwM57Rt2xaNRgPAjBkzOHToEB9//DHR0dFkZWUBcPz4cUJDQwHw9vamadOmABw+fJjff/+dY8eOAQW5/NKlS1JkixpDimxRZZw7dw5PT09DgV3I29ub2NhYFi1aREBAAKNGjeLbb7/lq6++AmDt2rU4Ojqye/duUlJSGD58OK1btwbg7Nmz7Nmzh9TUVPr06cMnn3zCnDlzCAwM5KeffqJly5Z8+eWX/Oc//8Ha2pr169ezbt06ZsyYwfbt29mwYQO1atXi1VdfZd26dTRu3JhTp04xffp0du7cCUCrVq1Yt25d5TaWEELcJyUlhYMHD3L27FlDfszNzSUyMhIARVEA0Ol0Dzxfr9cXea4oCjqdDgsLiyLbVSqV4WdbW1vDz1OnTsXJyYmnn36aQYMGERUVVex4wPB6+fn5BAcH079/fwDu3LmDjY2NcRctRBUmEx9FlaEoCvn5+cW2a7VaoKA35N4emsLek6NHjzJ8+HAAnJ2d6dOnD8ePHwcKCnQHBweaNGkCQNeuXQFo3LgxaWlp/PLLL8TGxjJixAgCAgLYvXs3V69eLfL+V69eJTY2lokTJxIQEMCiRYtISEgwTBZ64oknyrsphBDCaLt27aJTp078+OOPHDhwgAMHDvD222+zbds2nJycDHNYvv/+e8M5FhYWhrzbpUsXvv76awDi4uI4deoUHTp0oGvXroYVSC5evMjly5eLFc4Av/zyC1OmTKFv37789NNPQEEh3bVrV8NKJ2fPnuX69etF3k+r1ZKdnc3LL7/Mzz//XEGtI0Tlk55sUWW0b9+esLAw8vLysLKyMmw/ffo0zZs3JzEx0dATo1KpDEler9cXSfiFvS+AoRAvZGlZ9COfn5/PwIEDmTt3LlAw8fL+mfZ6vZ6mTZuya9cuw+vfvn3bEKP0vAghqoLw8HCmTJlSZNuIESP48MMPefnll1m+fDkffvghPXr0MOzv3r077733Hvb29syZM4d58+YZcl1ISAiurq5MmjSJWbNm4e/vT7NmzahXr94D897kyZMZOnQojo6OtG7dmiZNmhAXF8eUKVOYOXMmvr6+PPLII4bhIqNGjeLatWsMHjwYnU6Hr68vffv2rcAWEqKSKUJUIePGjVPmzp2r5ObmKoqiKFeuXFH69eunREZGKhMnTlQ+++wzRVEUZd++fYqHh4eiKIqyfPlyZeHChYqiKEpycrLSq1cv5cyZM8rOnTuVGTNmGF678HhFUZQZM2YoO3fuVC5cuKA89dRTSkJCgqIoivLOO+8oS5YsURRFUfr27avExsYqubm5ylNPPaUcPXpUURRF2bVrlxIQEKAoiqKMGTPGsF0IIWqiXbt2KSdPnlQURVHi4uKUXr16Kfn5+SaOSoiqT3qyRZWyZs0aVq9ejb+/P5aWltjY2PDWW28xYMAAOnXqRHBwMDt27MDT0xN7e3sAJk2axIIFC/Dz8yM/P59x48bRrl07YmJiHvp+rVu3ZvLkybzyyisoioKbmxszZ84EoE+fPowfP54NGzbw73//m6VLl5KTk4OdnZ1hEo8QQtR0LVu2ZP78+YYx2wsWLCg2d0YIUZxKUf73/bsQQgghhBCiXMg/RYUQQgghhChnUmQLIYQQQghRzqTIFkIIIYQQopxJkS2EEEIIIUQ5kyJbCCGEEEKIciZFthBCCCGEEOVMimwhhBBCCCHKmRTZQgghhBBClDMpsoUQQgghhChnUmQLIYQQQghRzqTIFkIIIYQQopz9f+1B3Eo0R5fPAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 800x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>vin</th>\n",
       "      <th>inventory_number</th>\n",
       "      <th>site_number</th>\n",
       "      <th>year</th>\n",
       "      <th>make</th>\n",
       "      <th>model</th>\n",
       "      <th>series</th>\n",
       "      <th>autograde</th>\n",
       "      <th>odometer</th>\n",
       "      <th>create_date</th>\n",
       "      <th>sale_date</th>\n",
       "      <th>wholesale_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1C4RJEBG0FC220905</td>\n",
       "      <td>187922032481751</td>\n",
       "      <td>234</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>2.8</td>\n",
       "      <td>97003.00</td>\n",
       "      <td>2019-08-27 20:40:25</td>\n",
       "      <td>2019-08-30</td>\n",
       "      <td>14500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1C4RJEBG1FC868088</td>\n",
       "      <td>184610587796718</td>\n",
       "      <td>231</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>4.0</td>\n",
       "      <td>91091.00</td>\n",
       "      <td>2019-08-06 19:48:28</td>\n",
       "      <td>2019-08-07</td>\n",
       "      <td>16400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1C4RJEBG3FC765397</td>\n",
       "      <td>518930851685277</td>\n",
       "      <td>247</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>2.8</td>\n",
       "      <td>35995.00</td>\n",
       "      <td>2019-08-28 14:14:45</td>\n",
       "      <td>2019-09-13</td>\n",
       "      <td>17200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1C4RJEBG4FC682920</td>\n",
       "      <td>60318562421769</td>\n",
       "      <td>220</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>3.4</td>\n",
       "      <td>110902.00</td>\n",
       "      <td>2019-08-31 02:34:33</td>\n",
       "      <td>2019-09-19</td>\n",
       "      <td>12700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1C4RJEBG5FC187464</td>\n",
       "      <td>436351539013421</td>\n",
       "      <td>220</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>3.9</td>\n",
       "      <td>33009.00</td>\n",
       "      <td>2019-08-12 16:50:49</td>\n",
       "      <td>2019-08-22</td>\n",
       "      <td>20600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1C4RJEBG5FC686572</td>\n",
       "      <td>703631633365727</td>\n",
       "      <td>243</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>2.3</td>\n",
       "      <td>83366.00</td>\n",
       "      <td>2019-08-21 17:24:37</td>\n",
       "      <td>2019-09-18</td>\n",
       "      <td>13500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1C4RJEBG5FC856400</td>\n",
       "      <td>726631171874123</td>\n",
       "      <td>222</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>2.7</td>\n",
       "      <td>110218.00</td>\n",
       "      <td>2019-08-09 16:40:14</td>\n",
       "      <td>2019-09-12</td>\n",
       "      <td>11300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1C4RJEBG6FC713990</td>\n",
       "      <td>458457712123572</td>\n",
       "      <td>247</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>3.4</td>\n",
       "      <td>58126.00</td>\n",
       "      <td>2019-08-09 13:53:12</td>\n",
       "      <td>2019-08-23</td>\n",
       "      <td>17600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1C4RJEBG8FC104755</td>\n",
       "      <td>249030805851057</td>\n",
       "      <td>126</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>3.6</td>\n",
       "      <td>35446.00</td>\n",
       "      <td>2019-08-28 15:51:37</td>\n",
       "      <td>2019-09-24</td>\n",
       "      <td>17700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1C4RJFBG0FC130806</td>\n",
       "      <td>487637714557502</td>\n",
       "      <td>129</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>4.6</td>\n",
       "      <td>31607.00</td>\n",
       "      <td>2019-08-06 16:44:42</td>\n",
       "      <td>2019-08-21</td>\n",
       "      <td>23000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1C4RJFBG0FC233059</td>\n",
       "      <td>457645952085895</td>\n",
       "      <td>58</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>3.7</td>\n",
       "      <td>40781.74</td>\n",
       "      <td>2019-08-01 19:33:50</td>\n",
       "      <td>2019-08-02</td>\n",
       "      <td>26750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1C4RJFBG0FC612031</td>\n",
       "      <td>270303781716878</td>\n",
       "      <td>215</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>0.0</td>\n",
       "      <td>55196.00</td>\n",
       "      <td>2019-08-27 21:33:50</td>\n",
       "      <td>2019-10-29</td>\n",
       "      <td>8500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1C4RJFBG0FC644722</td>\n",
       "      <td>155958887908525</td>\n",
       "      <td>216</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>1.8</td>\n",
       "      <td>72779.00</td>\n",
       "      <td>2019-08-20 19:10:58</td>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>15900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1C4RJFBG0FC646048</td>\n",
       "      <td>98891643726518</td>\n",
       "      <td>241</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>3.0</td>\n",
       "      <td>62432.00</td>\n",
       "      <td>2019-08-27 08:32:00</td>\n",
       "      <td>2019-10-08</td>\n",
       "      <td>18000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1C4RJFBG0FC876155</td>\n",
       "      <td>129549113212805</td>\n",
       "      <td>211</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>3.9</td>\n",
       "      <td>45940.00</td>\n",
       "      <td>2019-08-21 01:41:16</td>\n",
       "      <td>2019-08-22</td>\n",
       "      <td>21600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1C4RJFBG0FC956295</td>\n",
       "      <td>325283678575626</td>\n",
       "      <td>216</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>4.3</td>\n",
       "      <td>40393.00</td>\n",
       "      <td>2019-08-16 19:50:57</td>\n",
       "      <td>2019-08-27</td>\n",
       "      <td>22100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1C4RJFBG1FC103517</td>\n",
       "      <td>96525122261203</td>\n",
       "      <td>202</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>4.1</td>\n",
       "      <td>43059.00</td>\n",
       "      <td>2019-08-10 18:44:59</td>\n",
       "      <td>2019-08-20</td>\n",
       "      <td>21900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1C4RJFBG1FC158114</td>\n",
       "      <td>140565725165328</td>\n",
       "      <td>216</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>4.3</td>\n",
       "      <td>36058.00</td>\n",
       "      <td>2019-08-30 19:20:00</td>\n",
       "      <td>2019-09-19</td>\n",
       "      <td>19600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1C4RJFBG1FC757126</td>\n",
       "      <td>371076596488808</td>\n",
       "      <td>126</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>4.3</td>\n",
       "      <td>38943.00</td>\n",
       "      <td>2019-08-02 12:26:26</td>\n",
       "      <td>2019-08-27</td>\n",
       "      <td>22200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1C4RJFBG1FC926108</td>\n",
       "      <td>616280575104726</td>\n",
       "      <td>129</td>\n",
       "      <td>2015</td>\n",
       "      <td>JEEP</td>\n",
       "      <td>GRAND CHEROKEE</td>\n",
       "      <td>LIMITED</td>\n",
       "      <td>4.6</td>\n",
       "      <td>29648.00</td>\n",
       "      <td>2019-08-26 20:08:24</td>\n",
       "      <td>2019-09-11</td>\n",
       "      <td>22700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  vin  inventory_number  site_number  year  make  \\\n",
       "0   1C4RJEBG0FC220905   187922032481751          234  2015  JEEP   \n",
       "1   1C4RJEBG1FC868088   184610587796718          231  2015  JEEP   \n",
       "2   1C4RJEBG3FC765397   518930851685277          247  2015  JEEP   \n",
       "3   1C4RJEBG4FC682920    60318562421769          220  2015  JEEP   \n",
       "4   1C4RJEBG5FC187464   436351539013421          220  2015  JEEP   \n",
       "5   1C4RJEBG5FC686572   703631633365727          243  2015  JEEP   \n",
       "6   1C4RJEBG5FC856400   726631171874123          222  2015  JEEP   \n",
       "7   1C4RJEBG6FC713990   458457712123572          247  2015  JEEP   \n",
       "8   1C4RJEBG8FC104755   249030805851057          126  2015  JEEP   \n",
       "9   1C4RJFBG0FC130806   487637714557502          129  2015  JEEP   \n",
       "10  1C4RJFBG0FC233059   457645952085895           58  2015  JEEP   \n",
       "11  1C4RJFBG0FC612031   270303781716878          215  2015  JEEP   \n",
       "12  1C4RJFBG0FC644722   155958887908525          216  2015  JEEP   \n",
       "13  1C4RJFBG0FC646048    98891643726518          241  2015  JEEP   \n",
       "14  1C4RJFBG0FC876155   129549113212805          211  2015  JEEP   \n",
       "15  1C4RJFBG0FC956295   325283678575626          216  2015  JEEP   \n",
       "16  1C4RJFBG1FC103517    96525122261203          202  2015  JEEP   \n",
       "17  1C4RJFBG1FC158114   140565725165328          216  2015  JEEP   \n",
       "18  1C4RJFBG1FC757126   371076596488808          126  2015  JEEP   \n",
       "19  1C4RJFBG1FC926108   616280575104726          129  2015  JEEP   \n",
       "\n",
       "             model   series  autograde   odometer         create_date  \\\n",
       "0   GRAND CHEROKEE  LIMITED        2.8   97003.00 2019-08-27 20:40:25   \n",
       "1   GRAND CHEROKEE  LIMITED        4.0   91091.00 2019-08-06 19:48:28   \n",
       "2   GRAND CHEROKEE  LIMITED        2.8   35995.00 2019-08-28 14:14:45   \n",
       "3   GRAND CHEROKEE  LIMITED        3.4  110902.00 2019-08-31 02:34:33   \n",
       "4   GRAND CHEROKEE  LIMITED        3.9   33009.00 2019-08-12 16:50:49   \n",
       "5   GRAND CHEROKEE  LIMITED        2.3   83366.00 2019-08-21 17:24:37   \n",
       "6   GRAND CHEROKEE  LIMITED        2.7  110218.00 2019-08-09 16:40:14   \n",
       "7   GRAND CHEROKEE  LIMITED        3.4   58126.00 2019-08-09 13:53:12   \n",
       "8   GRAND CHEROKEE  LIMITED        3.6   35446.00 2019-08-28 15:51:37   \n",
       "9   GRAND CHEROKEE  LIMITED        4.6   31607.00 2019-08-06 16:44:42   \n",
       "10  GRAND CHEROKEE  LIMITED        3.7   40781.74 2019-08-01 19:33:50   \n",
       "11  GRAND CHEROKEE  LIMITED        0.0   55196.00 2019-08-27 21:33:50   \n",
       "12  GRAND CHEROKEE  LIMITED        1.8   72779.00 2019-08-20 19:10:58   \n",
       "13  GRAND CHEROKEE  LIMITED        3.0   62432.00 2019-08-27 08:32:00   \n",
       "14  GRAND CHEROKEE  LIMITED        3.9   45940.00 2019-08-21 01:41:16   \n",
       "15  GRAND CHEROKEE  LIMITED        4.3   40393.00 2019-08-16 19:50:57   \n",
       "16  GRAND CHEROKEE  LIMITED        4.1   43059.00 2019-08-10 18:44:59   \n",
       "17  GRAND CHEROKEE  LIMITED        4.3   36058.00 2019-08-30 19:20:00   \n",
       "18  GRAND CHEROKEE  LIMITED        4.3   38943.00 2019-08-02 12:26:26   \n",
       "19  GRAND CHEROKEE  LIMITED        4.6   29648.00 2019-08-26 20:08:24   \n",
       "\n",
       "    sale_date  wholesale_price  \n",
       "0  2019-08-30            14500  \n",
       "1  2019-08-07            16400  \n",
       "2  2019-09-13            17200  \n",
       "3  2019-09-19            12700  \n",
       "4  2019-08-22            20600  \n",
       "5  2019-09-18            13500  \n",
       "6  2019-09-12            11300  \n",
       "7  2019-08-23            17600  \n",
       "8  2019-09-24            17700  \n",
       "9  2019-08-21            23000  \n",
       "10 2019-08-02            26750  \n",
       "11 2019-10-29             8500  \n",
       "12 2019-10-03            15900  \n",
       "13 2019-10-08            18000  \n",
       "14 2019-08-22            21600  \n",
       "15 2019-08-27            22100  \n",
       "16 2019-08-20            21900  \n",
       "17 2019-09-19            19600  \n",
       "18 2019-08-27            22200  \n",
       "19 2019-09-11            22700  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cherokee = run_experiment('2019-08-01', '2019-09-01', 2015, 'JEEP', 'GRAND CHEROKEE', 'LIMITED')\n",
    "df_cherokee.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Simple linear pricing model on only Autograde and Odometer:\n",
      "    R^2: 0.59\n",
      "    Added value per point of Autograde: $1609\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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bRmJiIp999hl+fn54eXkV+Ho+Pj74+PgwY8YM0tPTeeKJJ9i3bx8rV67kvffey3N947xUrVqVCRMmMGbMmHzzTpw4kX79+hEaGsqrr75KkyZN0Ol0HD16lPDwcPr27avvlR85ciSHDx+mZ8+evPrqq3h5eaFWq4mMjGTZsmX4+fnh5+dHbGwsBw4coF+/fqjVOfs4mjVrRv369VmzZs0jH6DTsGFDhg4dypw5cx55D//73/9ITEzMtWcVspeU++KLL3Ks0Z3bChq2trYG6z4Xh4CAAD788ENWrlyZ5/KEu3btIikpKc9VR0JCQpgzZw6rV6/OseoNZPdIL1++nObNm9OxY8ccK6o0aNAAW1tb7t69y9WrV/XbXbt2ZdmyZYwePZoRI0bg7OzMxo0b2b9/P/PmzctzbkHPnj3ZsmULo0aN4tChQ/j5+WFnZ8elS5dYsWIFNjY2BivTCCEeXxJkCyEKbP/+/WRkZHD9+nXCwsJy7J8+fTqhoaE4OTmxYsUKPvnkE0aPHo2NjQ2BgYG89957Rl3PxMSEr776innz5rF8+XLi4uKoXbs2H330kcE61cbo1q0bO3bsYM+ePY/M17RpUzZs2MDXX3/Nd999R1xcHCYmJjRo0IDx48cbBJw1a9Zk/fr1fP3112zevJklS5agKAp16tRhwIABvPrqq6hUKjZs2IBWq80zYATo3r07n3/++SMf0AMwcOBAdu/ezZ9//plnnoiICKpUqcJzzz2X634XFxfatGnDrl27DIaeTJ8+PUded3f3Yg+yHR0d8fX15dChQ/oH+/xbREQEjo6OeX4C4ubmxjPPPMOOHTsYP358jmEcu3fvRlEUTp48SZ8+fXIcv2rVKry9vdmzZw8TJ07Ub9vY2LBixQpmz57NF198QWJiIo0aNWLBggW88MILed6Tubk5y5cv59tvv2Xnzp1s3ryZjIwMXF1dad++PYMHDzZYP14I8fhSKXmtFyWEEEIIIYQoFBmTLYQQQgghRDGTIFsIIYQQQohiJkG2EEIIIYQQxUyCbCGEEEIIIYqZBNlCCCGEEEIUMwmyhRBCCCGEKGYSZAshhBBCCFHMJMgWQgghhBCimEmQLYQQQgghRDGTIFsIIYQQQohiJkG2EEIIIYQQxUyCbCGEEEIIIYqZBNlCCCGEEEIUMwmyhRBCCCGEKGYSZAshhBBCCFHMJMgWQgghhBCimEmQLYQQQgghRDGTIFsIIYQQQohiJkG2EEIIIYQQxUyCbCGEEEIIIYqZBNlCCCGEEEIUMwmyhRBCCCGEKGYSZAshhBBCCFHMJMgWQgghhBCimEmQLYQQQgghyoXPP/+coKAgOnfuzPLlywH49ddfCQ4OpmPHjsyePRtFUQA4e/YsoaGhdOrUifHjx5OVlQXAjRs3CAsLIzAwkLfeeouUlBQAkpKSGDRoEEFBQYSFhREbGwtAZmYmY8aMISgoiB49ehAdHV0s9yJBthBCCCGEKHP79+/n999/Z/Pmzaxbt46VK1dy7tw5xo0bx4IFC9i2bRunT59m7969AIwZM4YJEyawc+dOAFavXg3Ahx9+SJ8+fdixYweenp7Mnz8fgDlz5uDl5cX27dvp1asXU6dOBWDlypVYWFiwfft2xo8fz5gxY4rlfkyL5SyPOZ1Oh0ajQa1Wo1Kpyro4QlQ6iqKg0+kwNTVFrTa+b0Cn0+l7PoylUqkKdU1hSNpRIcpeUdrS0mhH/f39adOmDaampty+fRudTkdSUhJ16tShdu3aAAQHB7Nz5048PDxIT0+nZcuWAISGhjJnzhz69u3L0aNH9YF1aGgoL7/8MmPHjmXfvn189913AHTt2pUPP/yQzMxM9u3bxzvvvANAq1atSEpKIiYmhlq1ahXqfh+QILsANBoNkZGRZV0MISo9T09PzM3NjTpGp9MR+ftvaFSWhbqmqakpnp6eEmgXkbSjQpQfxralxdGO1qtXz6AdNTc3z7UMZmZmzJ49m/DwcIKCgoiNjcXFxUW/38XFhbi4uBzp1apVIy4ujoSEBGxtbTEzMzNIBwyOMTU1xc7OjoSEhDzPJUF2KXjwQ+Hp6YmJiUme+bRaLZGRkfnmqyykPgxJfRgypj4e5C1MoKsoChqVJZ6ZuzBBY1wZMSWSjoXuvRH/KGg7CvJeKQ1SxyWvPNZxYdvS4mhH/fz8SE9P16cPGzaMt99+O9djRo4cyVtvvcXgwYO5fPmywadfiqKgUqnQ6XS5pj/4/2F5fXqmKApqtTrHMQ/Si0qC7AJ4UPEmJiYFeqMUNF9lIfVhSOrDkDH1UZRhBiZojP7lIIqPse2osXlF4Ugdl7zyWMeFbUuL0o7u37/foB5y68W+cOECOp0ODw8PrKysCAgIYMeOHQbHxcXF4eLigpubm76HGiA+Ph4XFxecnJxITk5Go9Fgamqqzw/ZveDx8fG4ubmh0WhITU3FwcEBV1dXYmNj9UNSHpyrqOTzTyGEEEIIUaJsbW0NXrkF2dHR0UyePJnMzEwyMzPZtWsXL774IhcvXuTSpUtotVo2b96Mn58f7u7uWFhYcOzYMQAiIiLw8/PDzMwMb29vtm7dapAO2WO+IyIiANiyZQve3t6YmZnh7+/P+vXrATh27BgWFhbUqFGjyPcsPdlCiMpBUQBjh33IMBEhhNAr4XY0MDCQM2fO0L17d0xMTAgMDKR79+64uroyfPhw7t+/j7+/P4GBgQDMmjWLCRMmkJqaylNPPcWrr74KwOTJkxk7dixff/011atX54svvgBg+PDhjB07li5dumBnZ8esWbMA6NevH5MmTaJLly6YmZnx6aefGnmPuZMgWwhROUi8LIQQRVMK7ei7777Lu+++a5Dm6+vLpk2bcuRt3Lgx69aty5Hu7u7OypUrc6Q7ODiwaNGiHOkWFhbMnDmzCKXOnQTZQojKQXqyhRCiaKQdNYqMyRZCCCGEEKKYSU+2EKJykB4YIYQoGmlHjSI92UIIIYQQQhQz6ckWQlQOlbczRQghioe0o0aRIFvk79YJuBsFjvWhuldZl0aIwpGPOYUQ5djNmMtsWx2OhaUVIa++iV0Vh7IuUk7SjhpFgmzxaLGn4fRqQAU3joFKDW7Ny7pUQhiv8rbzQohyLvP+fT54ozdJ9xJAUfgr8nemLv6hrIuVk7SjRpEx2eLREq8AKkDJDrDvXSnrEglRSEohX0IIUbLu3L5B4t14dFotOp2O85EnyrpIeZB21BgSZItHc25E9htEBYru720hKiD53SCEKKeq1aiJW606qNRqUKnw8vUr6yLlTtpRo8hwEfFozg3h6YGQEA2OT4BTg7IukRBCCPFYMTU1Y9rSNezZ+CMWVtZ06N63rIskioEE2SJ/TvWzX0JUZDJhRwhRjlVxqkrof4aUdTEeTdpRo0iQLYSoHCpvOy+EEMVD2lGjSJAthKgcpAdGCCGKRtpRo8jERyGEEEIIIYqZ9GQLISoH6YERQoiikXbUKBJkCyEqD2PbelWJlEIIISouaUcLrEyGi9y9e5eAgAAOHz6sT9u5cychISE8/fTTtG/fnvnz56PT6fT7169fT0BAAC1atCA0NJQ//vhDv0+r1TJz5kzatGmDl5cXgwcPJjY2Vr//zp07DBkyBG9vb1q3bs20adPQaDSlc7NCCFHKUlJSCA4O5tq1awBs3ryZ4OBggoODGTp0KPfu3QPgxo0bhIWFERgYyFtvvUVKSgoASUlJDBo0iKCgIMLCwvTtaWZmJmPGjCEoKIgePXoQHR1dNjcohBAVQKkH2cePH6dPnz5cvXpVn3b69Gnee+89RowYwbFjx1iyZAkRERGEh4cDcPjwYaZOncqMGTM4evQo3bp1Y/DgwaSnpwOwcOFCfvnlF9atW8eBAwewtLRk4sSJ+vOPGDECa2trDhw4wNq1a/ntt9/05xZCVBKKUrhXBXPy5EnCwsK4dOkSALdv3+azzz7j22+/ZfPmzTRo0IB58+YB8OGHH9KnTx927NiBp6cn8+fPB2DOnDl4eXmxfft2evXqxdSpUwFYuXIlFhYWbN++nfHjxzNmzJiyuUkhRNmoJO1ocSnVIHv9+vWMHj2akSNHGqRfv36dvn370q5dO9RqNfXr1ycgIICjR48CsGbNGrp06ULLli0xMzOjf//+ODo6sm3bNv3+gQMHUr16dWxtbZkwYQI///wzMTExXLlyhSNHjjBmzBisrKyoVasWQ4YMYdWqVaV560IIUSpWr17NBx98gIuLCwAqlYqPPvoIJycnAJo0acLNmzfJysri6NGjBAUFARAaGsrOnTsB2LdvHyEhIQB07dqVgwcPkpmZaZDeqlUrkpKSiImJKe1bFEKICqFUx2Q/++yzBAcHY2pqahBod+rUiU6dOum3MzIy2LdvH8HBwQBERUXx4osvGpyrQYMGnDt3juTkZG7dukWjRv887rtq1apUqVKFv/76CwAHBwdcXV31++vXr8+NGzdISkrC3t6+wOXXarUF2p9fvspC6sOQ1IchY+qjWOqsUD0qFa8HZvr06QbbLi4u+oA7PT2dxYsXExYWRkJCAra2tpiZmQFQrVo14uLiAIiNjdUfY2pqip2dHQkJCQbpDx9Tq1atApfPmO+3vFdKjtRxySuPdVzkslSSdrS4lGqQXa1atXzzpKSkMHz4cCwtLenfvz8AqampWFlZGeSztLQkLS2N1NRUAKytrXPsf7Dv38c+2E5LSzMqyI6MjCzWfJWF1IchqQ9DpVYfhZkU/xhJSEhg6NChPPnkk7z44ovcvn0blcpwRtK/tx9QFAW1Wo2iKAZ5HqQbw5jvt7xXSp7Uccl7rOq4krejxipXq4tcvHiRd955B2dnZ1asWIGtrS2QHRRnZGQY5M3IyMDR0VEfMD8Yn/3wfhsbGxRFybHvwbaNjY1R5fP09MTExCTP/VqtlsjIyHzzVRZSH4akPgwZUx8P8hZJJe6BuX79OgMGDOCFF15g9OjRADg5OZGcnIxGo8HU1JS4uDh9L7WLiwvx8fG4ubmh0WhITU3VfyIYGxtL7dq1AYiPjzfo2S4IY77f8l4pOVLHJa881nGR29JK3I4WRrkJsvfv38+7775L7969GTVqFKam/xStYcOGXLhwwSB/VFQUfn5+VKlSBVdXV6KiovRDRuLi4khMTKRRo0bodDoSExOJj4+natWqAERHR+Pm5oadnZ1RZTQxMSnQG6Wg+SoLqQ9DUh+GpD5KVmZmJgMGDKBv3776TwcBzMzM8Pb2ZuvWrYSEhBAREYGfnx8A/v7+REREMGTIELZs2YK3tzdmZmb4+/uzfv16vL29OXbsGBYWFtSoUcOo8hjz/ZafjZIndVzypI4rr3LxxMcTJ04wdOhQxo0bx/vvv28QYAP07NmTzZs3c+jQIbKysggPD+fOnTsEBAQA2RN2Fi5cSExMDCkpKXzyySf4+PhQu3Zt6tatS8uWLfnkk09ISUkhJiaGr776ip49e5bFrQohyopSyFcFt2HDBq5evcr69esJCQkhJCSEcePGATB58mTWrl1L586d+f333xkxYgQAw4cP59SpU3Tp0oXVq1czadIkAPr164dGo6FLly58/PHHfPrpp2V2X0KIMlBJ29HCKhc92YsWLUKj0TBt2jSmTZumT2/ZsiVLly7F19eXyZMnM2XKFG7fvk2DBg1YsmQJDg4OAAwdOhSNRkNYWBipqam0bt2aOXPm6M8zd+5cPvroI1544QXUajXdu3dnyJAhpX6fQoiyVLmeVPbTTz8B0Lt3b3r37p1rHnd3d1auXJkj3cHBgUWLFuVIt7CwYObMmcVbUCFEBVK52tGiKrMg+8HKH0Cujfm/PeiByY2ZmRmjR4/WjzX8t6pVqzJ37tzCFVQI8Xio5D0qQghRZNKOGqVc9GQLIUSJkwk7QghRNNKOGkWCbCFE5SA9MEIIUTTSjhpFgmwhRCUivx2EEKJopB0tqHKxuogQQjxOZs6cydixY8u6GEIIIcqQBNlCiMqhlJae+u2331i/fn2xFFkIIcoVWcLPKBJkCyEqhwcTdox9GSExMZHZs2fz1ltvldBNCCFEGSqFdvRxImOyyzNFBxl3wcwWTC3LujRCVGxF6FFJSUkxeGKbubk55ubmOfJNmjSJkSNHcvPmze0+5TcAACAASURBVEIWUggh8qYoClcvX8K+ShUcnZzLoABU6p5pY0lPdnmly4JT38DxL+HIp3DvUlmXSIiKrQg9MP7+/rRs2VL/+vrrr3Ocfs2aNVSvXh1fX9/SvjMhRCWg0+kY/J9X8PdpTqunGrBjy8bSL4T0ZBtFerLLq7vnIflq9te6LLi6FzzrlW2ZhKik9u/fn6Mn+9+2bdtGXFwcISEh3Lt3j7S0ND7++GMmTpxYmkUVQjymTv5xnB1bNwGg0WiYMXUygV1zf0ifKB8kyC6vTCwe2lD9a1sIUZpsbW0NguzcLF++XP91REQER44ckQBbCFFsrK1t9F+r1WpsbW3LsDSiIGS4SHnlUB+qPwNqU7CuBvUCy7pEQlRs8jGnEKIC82jyJGPGT8La2hr3mrWY8cX80i+EtKNGkZ7s8kqlgvpdsl//lpEMmgywqZqdTwiRv1KcsBMaGkpoaGjpXEwIUebi42JJT0ujZu06qErw9/LQkWMYOnJMiZ0/XzLx0SjSk13RXDkKmyfA9o/g8LeV+i9EIYwiPTBCiBKw9r8r8WvRmI6+Xkwc9TbK49xuSDtqFAmyK5rITej/jIw5DvdulGlxhBBCiMps1seT9YF1xOpVXLl0sYxLJMoLCbIrGlMLQPWvbSFEvqQHRghRAmxsbfVDRFQqFdbW1mVcohIk7ahRJMiuaFq9AtaO2Q+naR4KtlXLukRCVAxKIV9CCPEIM+ctwrV6Dezs7fngk89wcate1kUqOaXQji5fvpwuXboQHBzMuHHjyMzMZPXq1Tz77LOEhIQQEhLC7NmzAUhKSmLQoEEEBQURFhZGbGwsAJmZmYwZM4agoCB69OhBdHR0dvEVhZkzZxIYGEjnzp05duyY/rrLli0jMDCQTp06sXPnzkJX0cNk4mNF41wXunyYMz0rDe4ng001lPupcD8V7F1LdAKGEEII8bhLvHuHxIS71K5XH7U6Z9+kd+s27D12usjXURSFa1cvY25hievjHKg/wqlTp4iIiGDNmjVYWVnx3nvv8d///pfz588zefJkAgICDPLPmTMHLy8vFi9ezIYNG5g6dSrz5s1j5cqVWFhYsH37do4ePcqYMWOIiIhg586dnD9/nm3btnHlyhXeeOMNduzYwdmzZ9mwYQMbNmwgNTWVXr160apVK5ycnIp0P9KT/Ti4Gw0HPoFDs1H2zED58T2UDZNRflqAotOVdemEKCcK8xGndGULUZnt27WNoGc86RXQluGvv4RGoymxa308fjTBfq0IfKYZq8OXlth1iqZk21F7e3s++OADrK2tUalUNG7cmBs3bhAZGckPP/xAcHAw7733HklJSQDs27ePkJDsB/J07dqVgwcPkpmZaZDeqlUrkpKSiImJYf/+/QQHB6NWq6lXrx41a9bk+PHj/Pzzz3Ts2BFLS0ucnZ155pln2Lt3b5FrS4Lsx8GlPaDTAqDcjgHl78D6WiTEywQMIQAZLiKEMNrCL2ag0Wb/fj30815OHj9SIte5ef0a6/77LZDdo/3lzI9K5DpFVoR2NCUlxeCVmZmZ4/R169bFx8cHgDt37rBq1SratWtH9erVGTZsGJs2bcLNzY2PP/4YgNjYWFxcXAAwNTXFzs6OhIQEg3SAatWqERcX98h0V1fXHOlFJcNFHgemlv98rVKRPTFSyblPiEqtMFGzRNlCVGa2tnaoVSp0f0/es7W1K5HrWFpZoVar0el02ZMnbcrr0xwL3476+/uTnp6uTx02bBhvv/12rkdcu3aNN998k169euHr64uvr69+3xtvvEGHDh1yv5KioFarURTFYLjsg/QH9Ztb+r/lNjTIWNKT/Tho1BXsqoOJOaomz4K9C5hZonq6ByqnmmVdOiHKB+nJFkIYady0WdSuVx8bW1veencsHk95lsh1HJ2cmTRzDlUcHHFxq8GMeYtL5DpFVoR2dP/+/Rw/flz/evPNN3O9xNmzZ3nppZfo27cvgwcP5u7du6xcuVK/X6vVYmJiAoCLiwvx8fEAaDQaUlNTcXBwwNXVVT8JEiA+Ph4XFxfc3NzyTH+45zouLs6gx7uwpCf7cWDlBK3fAbL7sFVeZVscIcqlwiwlVYmXnhJCQAOPJqzZ/UupXKt775fp3vvlUrlWoRWhHbW1tdUHx3m5e/cub7zxBpMnT6Zjx44A2NjYsGDBAry8vGjatCkrV67UT4D09/cnIiKCIUOGsGXLFry9vTEzM8Pf35/169fj7e3NsWPHsLCwoEaNGvj5+bF27Vq6du3K1atXuXz5Mp6enlhYWDBx4kT69+9Peno6v/32G8OHDze+fv5FgmwhROUgo0WEEKJoSrgd/fbbb0lJSWHBggUsWLAAgOeff57Zs2czceJEMjIyeOKJJ5g5cyYAw4cPZ+zYsXTp0gU7OztmzZoFQL9+/Zg0aRJdunTBzMyMTz/9FIDAwEBOnTpFcHAwKpWKadOmYWlpSbNmzejevTs9e/ZEq9UyfPhwgzHahSVBthBCCCGEKHMjR45k5MiRue7bsGFDjjQHBwcWLVqUI93CwkIfiD9MpVLx/vvv8/777+fY9/rrr/P6668XotR5kyC7vEuOhdPbsz9uado5e7y1EMJ4MlxECFEMdmzZxIa1P9DQw4Nh776PhUUlevKytKNGkSC7PFN08NNcSEsEFIi9ACFTQSXzVYUQQojSdvL3Ywwd0A+A3Tu2kpWlYeykcrrcnihzEmSXZ5pMSL37z3ZaAmTdB3OrPA9Rku+g6LJQydMehTCgKAqKkT0qxuYXQlRsOp2O6PPncHKuinO1nJ8cnzt75p92QVH4M/JkKZewbEk7ahwJssszUwtwawy3zmVvu3qAWd7rXmtO7UBzdB0A6ibPY94mrDRKKUSFIJ9yCiEeJSsri2Gv9eHorwcwMTHh06+W0a5TZ4M8z/o9j42tLakpKQB0DQkti6KWGWlHjSNBdnmmUoH/YLh8DFCgjvffD5vJSVF0aI5v1G/rzu5D8QpGZWVfSoUVonyTHhghxKP8cfQQR389AGT3aC+aPTNHkO1eqzbb9v7Knl3baejRhLZ+z5dBScuOtKPGkSC7vDMxg/q++edDBWYWcF/z96ZJ9rFCCCGEyJet3T+dUiqVCrsqDrnmq1WnLv0HDi6tYokKTGbQPSZUKhVm7d8EWyewssfM/3VUjxi7LURlIw98FEI8ypOezRk6Zjz2VRx4oqEHE6bNKusilTvSjhpHerIrKm0WJN0CG2cwtwZAZe+KWYe3UTu4oEqJg8xUMLcp44IKUT7Ix5xCiH9LuHuH2zeuU9+jCWZmZgwYOpIBQ3Nfp9kYGenpXPjrLGmpqXnmSUlO5tqVS9St3wBLK+siX7M0SDtqHAmyK6L7KbBvNqTGZ0+OfO5tMmOvkr5vGaBgamuLtaM5KhNz8BkIjvXKusRClDmdAioj23pd5f3dIMRj79hvBxn6Wh8y79+nYZOnCF+3FWsb2yKfNy72Ni8FB3Dz+jWsbWxYuX47jZ9sapDn8sUo3ujZhXuJCVRzdWN5xA5cq9co8rVLmrSjxpHhIhXRtd+zA2wAbSZE7SPj6HoefCijSUlBl6UFnQYu7i+7cgpRjjyYFW/sSwjxeFq+cC5ZmZkAXDj7J/t37yiW825cs5rbN28A2T3a34cvzZFn7XfLSUlOAuBOXCybflxVLNcuadKOGkd6sisis3+NtdZqUGkyUACVWoWljQUqnQ50OjCrGB9BCVHS5GNOIcTD7B0cUKnVKFotQJ4THf9t55YNbF2/hvoNPXhrxHtYWBourWtnb48aBTNTNToFbO3scpzDzs5e374oilLga5c1aUeNI0F2RVSrJcRHw/UTYF8Drp7E2kRLmlqFdRUr1KYm2R/nZGqhQfuyLq0Q5UJhJuBU3l8NQjz+Ro7/kJvXrnEp6i+693mFts+/kO8xkX8c5/2hbwBw4KfdaLVa3p3woUEe56pVMTc1AcAEcHJ0ynGeVwYO5dyfkZw4eog2/i8Q+tKrRb+hUiDtqHEkyK6IVGp4um/2K/EGbPsYExMVdjYWYGLyTz5FB7qyK6YQQghRXrm4VSc8YptRx0T9dVb/taLTcf7M6Rx5LkedR61Wo9PpUKvVxFy+mCOPja0ts5d+Z3yhRYUiY7IrOntXqPLQZAlr53++dqgFNjn/ghaiMtIpSqFeQgjxgK9fO2xs/xn+ERjyYo48/h0CMTHJ7sPU6XS80Dm41MpX0qQdNY70ZFd0ahPoOAqu/p49VruGJ9yMzJ4QWdMru9dbCCGPAxZCFJlbDXfW7PyZAz/t5omGjWjl+2yOPA2bPMWqrT9x5NcDmFpY0cY//2EoFYW0o8aRIPsxoJhakpSURurFg2D6E3euRWFuY0u9brUwd3KHmyfg+nGwdYWGnbKfBKm5D2e2QUos1HkG3JuX9W0IUaJkwo4Q5U/i3TssmPUJd+Jiefn1N/HOJWgtiOjz5/h6zmeYmJjw1rvvU6de/WIu6T9q1KxFn1dfz3O/oihEHjvEiV/24eBSHW33FzF5eCgn2T3c3y2ez8njh3nmuXb07DcAlUqV77WP/nqA75cvxrmaC0PHTMAhl/HeJUnaUeOUSTfn3bt3CQgI4PDhw/q0kydP0qtXL7y8vGjfvj1r1qwxOGb9+vUEBATQokULQkND+eOPP/T7tFotM2fOpE2bNnh5eTF48GBiY2P1++/cucOQIUPw9vamdevWTJs2DY1GU/I3WkpSLxwlfs9y0i+dJO38ce7Hx3HzwnnOrpwEiVfhxCqIOweXfobz27MPitwIUfvh1hk4vAwSr5ftTQhRCirLU8pSUlIIDg7m2rVrAPz6668EBwfTsWNHZs+erf+ld/bsWUJDQ+nUqRPjx48nKysLgBs3bhAWFkZgYCBvvfUWKSkpACQlJTFo0CCCgoIICwszaGeFKIxJo4ay8YdVHNizk7f79yE+9pbR59BoNLz5Ug/2bN/Mrq0bGfJKrzIN7H7Zs4O5U8dz9OBedkf8lw3/XZ4jz/r/hvP1F59waP8e5nw8kT1bN+Z73ts3b/BO/74c2LOTjT+u4sMxb5dE8fNVWdrR4lDqQfbx48fp06cPV69e1afdu3ePQYMG0b17d44ePcq0adOYPn06p06dAuDw4cNMnTqVGTNmcPToUbp168bgwYNJT08HYOHChfzyyy+sW7eOAwcOYGlpycSJE/XnHzFiBNbW1hw4cIC1a9fy22+/ER4eXqr3XZIy46/BQ38Bm5mqQYGUhERIuf1QTgWS/g6m790Asv8ivX8/i6xb50u1zEKUtsoylvDkyZOEhYVx6dIlADIyMhg3bhwLFixg27ZtnD59mr179wIwZswYJkyYwM6dOwFYvXo1AB9++CF9+vRhx44deHp6Mn/+fADmzJmDl5cX27dvp1evXkydOrUM7lA8Ti6c/ROdTouiKGRlZnLtymWjz5GcdI878XGoUFApOm5cu0rm/fvFX9gCunzhL1Tq7PBKpVZz6cJfOfJcvHBO37utVptw8cK5XM+VcDees6dOcP9+BtevXiYrKxNFUdBptblOuixplaUdLS6lGmSvX7+e0aNHM3Kk4SNLd+3ahYODA2FhYZiamuLr60twcDCrVmUvzr5mzRq6dOlCy5YtMTMzo3///jg6OrJt2zb9/oEDB1K9enVsbW2ZMGECP//8MzExMVy5coUjR44wZswYrKysqFWrFkOGDNGf+3Fg09Ablfqfj6LSM7N76d0aNwXnhmBi8U/m9Ntw/x7U9kZRFG7euse164lc3bKEpMi9pV10IUQxW716NR988AEuLi4AnDp1ijp16lC7dm1MTU0JDg5m586dXL9+nfT0dFq2bAlAaGgoO3fuJCsri6NHjxIUFGSQDrBv3z5CQkIA6Nq1KwcPHiTz74d5CFEYXV/so/+6Zu26NG7azOhzODg68UTdOjjZWuJka0mTxh451q4uTW1e6ISp6d+jcRUF/05dc+RpH9hN39uuVqvxCwjKkefU8SP09G/FwJ5BvBb8AjXr1KVGrdr6/V1f7FsyNyCKTamOyX722WcJDg7G1NTUINC+cOECjRo1MsjboEED1q5dC0BUVBQvvvhijv3nzp0jOTmZW7duGRxftWpVqlSpwl9/Zf/16ODggKurq35//fr1uXHjBklJSdjb2xe4/Nq/F6zPb39++YqbqZM71V+ZRkbMWUzsHbG6/Admto44teyOVq1GVaMpqlsnUKlAIQvlxnGUOv7cT88k/dI/T6K6+8s6bJ70K7ZylVV9lFdSH4aMqY/iqLPKMmFn+vTpBtuxsbH6gBvAxcWFuLi4HOnVqlUjLi6OhIQEbG1tMTMzM0j/97lMTU2xs7MjISHBoH3NjzHfb3mvlJzyUsdvjhzLU81bknAnHv+OQZiZWxhdppSkeyTffWiI6M0Y0tPTMDe3eMRRJadO/UYsXLODPw7/gtrciqd9n8txTy18fFm8ZjtnT/1Oc+9nqNugUY48q5ctIjMr+4/Ya5cv8uve/xG+fif7dm7DuVo12rYLMLquivr9riztaHEp1SC7WrVquaanpqZiZWX4FENLS0vS0tLy3Z+amgqAtbV1jv0P9v372AfbaWlpRgXZkZGRxZqv+DnDPcCxJbaaOMwPLUKjtkCLCS6mDz60UIi5dYf4uydQpyvY61NV3MeEEydOFHupyq4+yiepD0OlVR8KhZiw8xiMKNTpdAYTqhRFQaVS5Zn+4P+H5TUhS1EU1GrjPhA15vst75WSVx7q2M7ZBTtnFy5dvgJcMfr4rMxMTM3M0WRlAirMLa04ffpPo382i1vtxtm98o+q4zqNm5GYkpbr7977WRqDNutu4j0uXb5CHY+ngOyhYaWtsrajhVUuVhexsrIiOTnZIC0jIwMbGxv9/oyMjBz7HR0d9QHzg/HZ/z5eUZQc+x5sPzh/QXl6euaYIfwwrVZLZGRkvvlKXGYK6iMbQNGCVgVV6oBJY5SkqyjOHtRsEELNv4eXJFlruXdoPWpre6oFvoV5tdr5nLzgyk19lBNSH4aMqY8HeYuisvbAuLm56XuiAeLi4nBxccmRHh8fj4uLC05OTiQnJ6PRaDA1NdXnh+xe8Pj4eNzc3NBoNKSmpuLgYNzjoI35fst7peQ8bnU88fOFfDVjMiZqNW9P/ASvp58u6yIVuY73uddCp1NQoaBToGmz5rRo0aJYylRYlbUdLaxyEWQ3atSIX375xSAtKiqKhg0bAtCwYUMuXLiQY7+fnx9VqlTB1dWVqKgo/ZCRuLg4EhMTadSoETqdjsTEROLj46latSoA0dHRuLm5YWdnhzFMTEwK9EYpaL7ikhYbQ2bSHUwsrbGtXh9V5r3sABsABdLioO2E7M3EGLj+Byr35qjMLHF8uiOOT3cs0fKVdn2Ud1IfhkqrPrIffmpca/84PDC1efPmXLx4kUuXLlG7dm02b95Mz549cXd3x8LCgmPHjuHt7U1ERAR+fn6YmZnh7e3N1q1bCQkJ0acD+Pv7ExERwZAhQ9iyZQve3t76YSUFZcz3W94rJa881nFi4l1+2r6V5i1bUb9R4wId06ZdR9q0K/rvMo1GQ9TZ0zhVrYZLdfcinw8KX8c3r8eg1f3TCl29FI1P25xDOmNv3eBO7G0aNmmKqZHvR2NV1na0sMrFk0oCAgKIj48nPDycrKwsDh06xObNm/XjsHv27MnmzZs5dOgQWVlZhIeHc+fOHQICAoDsiTkLFy4kJiaGlJQUPvnkE3x8fKhduzZ169alZcuWfPLJJ6SkpBATE8NXX31Fz549y/KWi82VXSs4teAdzq38kD+XvM+Z8EnorKqBVdV/MrllT2zS/bWD+xFTydyzlMwfRqOk3SujUgtR+h70wBj7qugsLCyYOXMmw4cPp3PnztSvX5/AwEAAZs2axfTp0wkMDOT+/fu8+uqrAEyePJm1a9fSuXNnfv/9d0aMGAHA8OHDOXXqFF26dGH16tVMmjSpzO5LPJ6uXIqm/dNN+PD9EYR2aMua78JL7dpZmZmMePVF3urdmb4dWrN3+6ZSu3ZuOnUL1X9tbWNLm+dzPtTmwP+281KH1gzu04VhYSHcv5+RI09xqqztaGGVi55sR0dHli1bxrRp05g7dy5OTk5MnDiRZ555BgBfX18mT57MlClTuH37Ng0aNGDJkiX6jymHDh2KRqMhLCyM1NRUWrduzZw5c/Tnnzt3Lh999BEvvPACarWa7t27M2TIkDK51+Kky8rk5i/rDdKSr54h+XoUVZ4eDPFnwMwGnD0A0Py5W//Trty/j/bcHkyfDs1xXiEeR5XtIQo//fST/mtfX182bcoZMDRu3Jh169blSHd3d2flypU50h0cHFi0aFHxFlSIhyz8Ygbah55jsWTe5/R6pX+pXPvksUOc/uMokD2XYcXCObQL6lYq185NQNfuuNVwJ/r8OVo/9zzV3WvlyPPd13P1kxnPRZ7g998O4vt8hxIrU2VrR4uqzILsByt/PODp6alfozU3ISEh+qWj/s3MzIzRo0czevToXPdXrVqVuXPnFr6w5ZTKxAS1uRW6TMMx56ZWdtmPWK/e0jC/uSWQ9M+2lQNKUhzKH+tBq0HVvCsq5+Ibky2EEEIYo6qLm8G2rV3BFycoqioPPT1RrTbBwcmZpHsJfDN7OvG3bxDy8uv4PNe+1MoD4Pl0KzyfbpXnfgcnZ9RqE3S67EC7Sik/AVI8WrkYLiIKR6U2waPv+5hXqYbKxBQTS1vqBL6OjVvdXPObth2I2t4eTE0wqfsU6sbPo+yZB1d+h5hTKLtmo2hkzVvxeJKPOYUo/0aMm0zjp5qhUqmo4ujI51+Hl9q1GzZpypD3J+NU1QWPp5ox6sNPmT15DLs2/MDxX39myjuvc/Oa8auflKQRk6bTpFkLHKtWY+C743iyeclO+JR21DjlYriIKLwq9Zvz9LuL9dva9GTu3ziPmXNN1BaGyxqqHOti3utzUHSQeA0lJQ6SYtFPYshMg4wUsJW/hMXjR/n7n7HHCCFKj6mpKT9sL54HoyXevcOVS9E08HgSG1vbAh3Tu/+b9O7/pn778oW/0P09+VCr1XLj6mWq16yT73nSUlOIOvcnqclphSt8AVV3r8WC7zeX6DUeJu2ocSTIfoxkxscQ++NHKJnpqK3scX3pI0ztqxpmUnTw62K4fRYVoFR/Am5GZ+9zaQA2jqVebiFKg07B2Enx2ccIISqcc3+eYlDvbqSlpVLN1Y0VG3dTzdUt/wP/pVOPPiyfOxMAl+o1adK8ZT5HQNztmwzp3YU7cbexsLRizsoIPJ4y/kmW5ZG0o8aRIPsxknpqD0rWfQB0GcmknjlAlWd6GGa6dwNun9VvqrKS4Pk3QauB2i3yfOiEEBWdTNgRovL4ccU3ZPy90kZ8XCzb1q/htbfeNvo8fQYMpeFTzbgTe4tn/AOwtsm/R3z3xrUk3Mlegz4z8z6bVn/LmKmfG33t8kjaUeNIkF2OaNKSuPa/lahSYqnhYo+ZTRV4sjNUqYGiKFw9uIm4s0dwqNOYJzq8jFqtgrM74U40uD6J2soO/Z+YioKJdS4TRsytIbsPG1ChsrCDOmW/aL8QJU0eoiBE2du5ZSPfr1hO7br1GDNxCnb2VfI95srlS3zy4SQy0tMZMWYsXi298z3G0cn5n9W0dDocnZ0LVV6VSkVL35xrUz+KvYOTfoiJotNha2/cA5vKM2lHjSNBdjlyedMCkqL+oGlDF0zvJaAkqVHdvQydP+J25K/8tXkJAHejTmFqaUNdd2c4tyP74LgL2Hn1JatBK+5f/wurei2weco/50WsneDpvnB2O5jbgPcrpXeDQgghKq3zZ8/wzsD+KIrCoYM/k5Gezqfz8l8Ssv9LvYi+cD77uF8P8sfZaKzzeWLzf4aM5HJ0FKdPHOf5jp3p3KN3cd1GviL//JP0TA3mpiZkaXUcO/5HqV1blC8SZJcjGXExqFEwN3vwZCgF7idDVgapt2NApcr+k1ClIuX2VbDL4uFeaXXaXap2eSf/C9V9JvslRCUiH3MKUbYuXYzSv6d0Oh3nz53N54hs0VEX9GtBpyQnExcXSx2beo88xtbOjs8XryhagfOQkZ7OmdMnca9ZG9fqNXLsP3fmNMkZWahUGhRFIebq5RIpR1mQdtQ4soRfOeLc4gV0ikJi0kPrXrs9CebWuHj6ojZ58LhUhepez0NqYvZExgfcm5dmcYWoUBSyH+9rzKvy/moQovj5+D5rMPmw50sF+yS1V98w/dfePq2pVTv/1T1KStK9e7zYyY9Xe3QmsM3T/HZgX448/Qa8SXYHWLbQPmE58lRU0o4aR3qyyxG3Z0OxcW9IVlI8WntrTMwtoEb2jGQ7t7q0GbWAhIunsa/ZADtnVzi6OPt9rFZl/yTbuZZp+YUoz5RCDCaszD0wQhQ3RycnNu85yL49u6hVuw6tfNsW6LjPvpxPx6DOpKel0alLMGp12fUP7t21jSsXs1fk0miy+HbxV/g+97xBng6BXViyej0b1/5ArXr1GThseBmUtGRIO2ocCbLLEZVKhf0TeS/zY+1cHWvn6tkb2iwwMQdtJmgBM0tQm/yTOSUW/toGihYadoIqNUu28EKUc0ohlp6qxL8bhCgRTlWrEtrnZaOOUavVdOrctYRKZBwn53+WxVWp1VR1cck1n++zfvj4tuXEiRO57tdqtSydO4s/jvxGm+dfoN+gYRVidS9pR40jQXZFZWIGzw2C4z+CSg2t+mb/D9k/0ceWQnpi9nbiVWj/Aajl2y0qL+mBEUIU1bPtOvDW8NFErP6Oho2fZOS4yYU6z5oV37BswWxQFP448hvVXKsT1L1nMZe2+Ek7ahyJuiqyGk9CjSk50xUdpCf8s52VBhnJkHKH9PR0MlVm2Lk3RG1ikvNYIR5TOgVU0gMjRLlz7fJFEhPu0NjTC1PT8h2WqFQq3hg2gmefb0eNWnVwrlqtUOe5cjEKE7UarVaL8kSXqQAAIABJREFUWq3mSvSFYi5pyZB21Djl+6dZFI7aBKq3gJt/f0zlVB/2fw0JV7FUFC5du0tm1UY0/88UVGoJtIUQQpSNLT+uYtbkMQC08GnDrG9Wl+tAOznpHoN6BnH9yiVMTc2YuXglrdrmslxuPjoG92DjD98BYGpmRvvO3Yq7qKIcKL8/yaJomr8E1ZuDTguKKUQv0O+qU82eo1EnSb5xEfuaDcuwkEKUHgXjBxMqlXpevBAlb8WiOfqvTxz5lb9On+SpFvk/urysHNyzk+tXLgGg1Wr4cfniQgXZXj6+fLd1L2dO/kFz79bUqvvoJQnLC2lHjSNB9uNKpQbXpgBobpzlVlwyWVodznaWaP5ea9vMJpcnQv5N0WSScmgtmtiL2FZzxMxMlX2+us9lr9cNEHMErh4BOzd4MhhMLUrjzoQoFJmwI0T541zVhfjbN7OfkKhS4eCU/5MZdTod3309j0M/7+XpZ9rwn2GjMCnA8MfIY7+xdtkCbO2r0H/EeKq5uRtdXoOJjyo1/2fvvONrOvsA/j13ZO+9RGJEokIQoy1Sq6UR1Ki2yquKVtVqm1pFU5sYLVqUt15a1G5tLaql1CqpEStCJCKTDJn3nPePyyVNSG7GTcL59nPrnOc+z3N+5+Te3/2d5/yGvWPRgY//5mbUJdYvnYskivQaMhoPbx/++nU75079RW56Ch4DhsqBj08hspH9DBB7+GcysvJAkriXk0GukQW+PUdgavv4lH+ZJ7eRdWYvZjamqNLvaA3r1Gtgagsu/pASDafXaTunXNO+79/TMCckI1MK5IAdGZmqx7hZXzJz3ChSkhLp9/5I3D29ih2zZ+tGls2fCUDEyb+wsbWnV/93nzgm7U4qU0a8Q35eLoKgICHuJnNW/aS3vM1bt2XAhx+zY+Maavn48X7ohGLHiKLI7I8GcjclCYCoC//wyhuD2PTfrwGJyNMnsHd2JejV1/SWx9AYQo9+9913bNy4EYVCQYMGDQgLC+Pq1atMmDCBzMxMmjZtSlhYGGq1mri4OEJDQ0lOTsbLy4vw8HAsLCxIS0vjk08+ISYmBjs7O+bPn4+TkxO5ublMmDCBs2fPYmJiQnh4OLVr10aSJGbPns2BAwdQKBR88cUXBAYG6iV3UcjFaJ4BcpJiC3wp6vYchUuT9gBk300m5WoE+dn3CozRpN4CQKl+dHVAgMxE7eaDfwGQIP12RYguI1NuiFLpXjIyMuVHbk42EcePcOvmDQA8vevw9brtrPv1L4J7lSy1341rV1DcjydSKJXcuHa12DGpSbfJy81BkiREUUPc9ahSyS8IAgOHf8Kmg6eY8+0P2Ng5FDsmLzeHO0kJSKKIJIqk30nh5rXLKJRaE0yhUJZaHkNT0Xo0IiKCzZs3s2HDBn7++Wfy8/NZs2YNoaGhTJgwgT179gCwbp12kS8sLIw+ffqwe/du/P39WbRoEQALFiygcePG7Nq1i969ezNlyhQAVq9ejbGxMbt27WL8+PGEhmrjAfbs2cOlS5fYuXMnixcvZsyYMeTl5ZX5eslG9jOAXeP2um0jWxfM3LR+2KnR5zk0axAnlo7ncPhQctIfZiQx8W0FQE5GzsOJlGrtKjaAYz0wsnj4nmeLijsBGZlyQCrlfzIyMuVD1r17DH8zhE8Gvs6A4Nb8vndHqeZp17krKrX2QbwgCHQMKX4F2MOrDrV8G+j2O/Z4s1THLg3GJqY0b9tJt9/4xXa0DXmYrk+pUvF8h1cNJk9ZqGg9amVlxcSJEzEzM0MQBHx9fbl48SJZWVk0bar11e/Rowd79uwhLy+P48eP07lz5wLtAL/99hvdunUDoEuXLhw6dIjc3NwC7c2aNSMtLY2YmBgOHjxISIi20JG3tzceHh6cPHmyzNdLdhd5BnBo2Q1Tt7rkpadgWbsJCiMTAGIOb0fU5AOQk5ZC/Jk/qNlKG+Fs7BWAbZ8vyE+OQbSxR5mfCXa1tO4iACZW8FIoJF4ECyew8ayUc5ORKSmyL6GMTOXy99E/uHY5EgBJFNmwcgltXg7We5669Ruwesdv/HPqOH7+AdSsXXwAv1KlYvry9Rz/fR/mlpYEtGyj93HLwtDJ83j+5a5IokjAi21RqdTMW7uLK+cj8GsUiLNH9fgNLYsezcjIKOA7b2RkhJGRUYG+Xl5eeHl5AZCcnMwPP/xAnz59iI6O1vVxdHQkMTGR1NRULCwsUKvVBdoBEhIScLpfKEilUmFpaUlqamqB9kfHPK69rMhG9lOEJIqc2v49NyKOUsPnOfzs1UgZKRj7d8C8VmHfImMrW7R12bXfGuOUU3DLFVybAaB28ETt8IQvvrEleJTdZ0lG5mlh7ty5/PrrrwiCQO/evXnnnXcqWyQZGb3RaDR8++Ucjh3+nZZt2jJo+MflUsrc1uGhEaNQKrF3fHxcUHG4e3qVyH/7UYxNTGn18sPKkZkZGSycGcbVS5GE9H6Trr31q0SpD0qViqatOxRo8/Cug4d3Hb3m+evgr2z63zLsHJwY8ukk7BxKFnhZFQgKCiIrK0u3/+GHHzJ8+PAi+968eZP33nuP3r17ExgYyMGDB3XvSZKEIAi6fx/lccGjkiShUCgKjXnQLopike1lRTaynyIuHdnL8c3LAaijSCQv1RIBuBd/GYvXp6K0dS3Qv1aHt8hKTSAt+h9cXMxxts2Hqz+DqQPYVI90QjIyJaWiA3YOHjzIqVOn2LZtG3l5eQQHBxMUFEStWrX0FVVGplLZvOZ/LF84F4CIU8dxcnah+xv9yjyvX8PGDPlkIj+t+Q7XGjX5cPyUMs9ZFhbPmcpPP36PKIpEnDyGV626NGzarFJlehK3424yZdRgNBoRhVJB+t07TFv6vUFlKIsePXjwYKGV7KK4cOECQ4YMYciQIfTr14/Y2NgCq8pJSUk4OTlhZ2dHeno6+fn5qFQqEhMTdavRTk5OJCUl4eLiQn5+PpmZmdjY2ODs7ExCQgKenp4F5nJxcSEhIaHQMcqK7JNdjZFys8iPvYCYkQLA3fgYhPt3XlamxjxyT4aYGAXxFyHv4V2k2tScgP4TaNMzGJ/6bg/v4rKTDHcSMjIGQkL726DXS4/5g4KCWLlyJSqVipSUFERRxMzMrKJOR0amwrhx7arOGFIolVy/Vn5Beb3+M4TVe44we/k6HJxdix9QgVy/elmbOvA+MdElO8+se/c4eeQQ8bExFSVakSTExaLRaAAJUaMh5toVgx4fyqZHLSwsCryKMrJTUlIYNGgQEydOpF8/7Y2du7s7xsbGnDhxAoDNmzfTpk0b1Go1gYGB7Nixo0A7aPXx5s2bAdi+fTuBgYGo1WqCgoLYsmULACdOnMDY2Bg3NzfatGnDzz//jEaj4dq1a0RHR+Pv71/m6yWvZFdTxKw0MjZ9gZSZAgoV5q+OpnbzdpzZ/SMaMZeoxHSa1NTmG1VZ2qI6tU5bmMbUBjqNBdNHcmQ7N4bUS9ptlSnY1quEM5KRqVhESUIo5QpMSXwJAdRqNfPnz2flypV07twZZ+fSPw6XkaksXunak43fr0Sj0aBUKnklpHtli1Qh+NRvyIkjhwAQFAoaNC7e/THt7h0G9ehEXMx1lCoVs5euokXrthUtKgA+DRpRo1YdYqK0xnXw628b5LiPUhY9WhL+97//kZGRweLFi1m8WFtE76WXXiI8PFyXwu+5556jf//+AEyePJmxY8eydOlSXF1dmTdvHgAjR45k7NixBAcHY2lpSXh4OAD9+vVj0qRJBAcHo1armT17NgCdOnUiIiKCkJAQBEFg2rRpmJiY6HWeRSEb2dWUvGsntQY2gKgh59x+7F8eRp/pq4i/fBYnb1/MhRzEjGTUcWcQbkZo+2bdgRunoN5LDydzaAABdnAvEWxqgZGlwc9HRqaiKU0M44Mx+vgSjh49mvfff5+hQ4eyfv16+vTpU4ojy8hUHg0CmvDjnt85e/oUDZsE4lHz6XQfPHc2gqy8fARAI0qcOXWCmrVqP3HMoX17iIu5DoCo0bB+5bcGM7KNTUxY8MPPHP9jP7YOTjQMbGmQ4z5KWfRoSRg9ejSjR48u8r1NmzYVanN3d2f16tWF2m1sbFiyZEmhdmNjY2bNmlWoXRAExowZw5gxY/SQtnhkI7uaojCzASBfI3Ip/i734v+ktnVdvFq8jJWj2yM968LdmIfxjQBm1oUntHDTvmRknlYkSf/iMnr4El6+rH30XK9ePUxNTenYsSMXL14sk8gyMpWFp3dtPL2fbHD+mz/2/8J/v16AnYMjn06ehrOr/hUVDYmjswsIivsuGODk4lLsGAenh0+nBEGBo4FdXszMLQjq1NWgxyxAGfTos4hsZFdTVDUDMG7ShfO71xN3JxPI5OQP4Vi5eGJX07dgZ/8ucC8VUm5AzWbgEVApMsvIVFcsLCyKLdt89epVVq5cyapVqwDYu3evvIot88yQEH+LUYPeRqPRICgUpCQl8d3G7ZUt1hP5+LMw7qSmcOXiBXq+1Z8WLxaf1q/Zi0EMGvUp2zespXY9P97/ZLwBJJWprshGdjVFEARMmvUg5/AhSEzRtWckxhU2so1MofWQJ86nycvlzvULmFg7YO5YxtWH7FTITgGzyg1qkZF5lNLkd0WCohNCFaZTp06cP3+e7t27o1Qq6dSpE6++Wj0KTMjIlJX4W7Hk52vrLkgazWOrMOZkZ3PhzAkcXdxxr2Q3FDt7BxavXKvXGEEQGPDBaAZ8ULRLQ0WTn5fL1XOnsbSxw81Lv/R/5UFF69GnDdnIruZ4v/AqyVFnATCxssPZt6nec2hys/lr8Sdk3IoGQcC/z0e4Nimlj1nqFTi/GiQRhZE1SsWLpZtHRqacEUuRegpJ4snr1wX56KOP+Oijj/Q7hozMU4Dfcw3x8XuOSxfOAdC738BCfbLuZTK6b1duRF1GEAQ+nbmwcl0fqhn5+XmEj/oPUefPANB39CSCur5hUBkMoUefJmQju5pTs3kHrFw8yUiMxcm3KcbmVsUP+hcpV//RGtgAkkT075tLb2THHQVJmxJJyL2LjTqudPPIyJQzz65XoIxMxaM2MuJ/W3Zx+MA+bOzsCGxZeIHl9F+HuRF1GdBmnNiy+lvZyNaD6Av/6AxsgN1rVxjcyJb1qH7IRvZTgK2nD7aePqUeb2xt/3BHUGBs5VB6YYyteDTKMk8wLf1cMjLlSGmKKDzLATsyMvpiZmZOx+DHG82PVidUKJTYOxUfaCjzECs7ex78vioUCmzLUDGztMh6VD/0KkZz7949Zs+ezbBhw0hLS2PmzJkF0lrJVE+s3Grh230opvau2NVpSP0ew0o/Wc0OYOcLJraINdqSpqg+JV9lnm70LqBQit+S8kDWszJPK/X8A3jv089xq+FFQMtWfDCucis+Vjec3GsyYMw0nD28qOPflAFjphtchuqiR6sKeq1kT548mdq1a3Pjxg2MjIzIzMxk7NixfPnllxUln0xJ0ORBchSZGZnkSkqsa9ZHoVLrNYXnC8F4vhBcdlnUZlD/LQCke+lYXtsHmTXByrHsc8vIlIHS+hIaGlnPyjzNdOs7kG59C/prX7l4gZSkRBo3a4n6MaW2K5Nb0Ve4m5JE7QaNURsZl2jMndQU/jl9ipw8TbnK8kKn7rzQqfKKA1UXPVpV0MvIvnLlCnPmzGH37t2YmJgwZcoUQkJCKko2mZKgyYXfFsDdWMwkiZjoJK6ZuRMwZAYKZeV5A0mZqbB9GnWy05Fi9iK9PBrBuW6lySMjU12Q9azMs8S6lcuZNXksAA2bBLJ8/TbUav0WiSqSwzs38cPcSQDUqOPHJwt/KNbQjo25wVtd2nP3TipqIyOW//gTjZo0M4S4MlUMvdxFFAoFubm5CII2GUtSUlKFCCWjB0lX4W6sbtfDxZq0mIukx16pRKGA6ychO127LYpIFw9WrjwyzzzV5TGnrGdlniVWLl2o2444dYLzEacrUZrC/Lr+O912zJULXD37d7Fjdv20ifS0uwBo8vPZvLZwRcLqSnXRo1UFvZY6Bw4cyDvvvENiYiJTp07ll19+YcSIERUlm0xJMClYvTEnJx8EASMLmxIN12RlkLT/f+Sl3sIqoCNWDYJKJ0fSFbi4C5TG0KA7mNk+zIspAGa2pZtXRqackChlglcDI+tZmWcJZxc3Em/HI2o0CIKAg2Pp4ngiI/5mxYIZKJRKhnz8GbV9nysX+WwdnUmIvY4kioCAtX3xro9OLq6IojbLliRJOLu4cf3SeTYsmYMkivR67xO8/fzLRT5DU130aFVBLyM7ODgYPz8/jhw5gkajYdmyZdSrV6+iZJMpCdZu0LgPYuQvZNy9S0yGEX69R2NqV7Ko7aT9q8iIPAKSSOLupRg71MDYpZZ+MuRlw7FvQaMtRMCxFdB2LFKDTuRc+hNjt3oIjcrB31tGpgyUtoiCoZH1rMyzxNQFX/PFmNEkJyYw6MPRuHvW1HuOvLxcJnzQj8yMdARgwgf9WbvvhO5pUFl4+5MpfD93EqkJ8XTsMxDXmsWXmu/S43WuXLzA/j078KxVl36DhzKp/6uk300FCeaHDmL+1sMoVdUvwVt10aNVBb3+wufOnWPhwoUsWbKES5cuMXbsWGbPnk2dOoavOiTzCN4voPB+ASugpAXTNXl53LjwN2nXLmJxP681QN7dxIdGtiRB6g2t37d9LVA8Jp18boY2+PIB91K0yi2gKxfwJCAgAKGYktQyMhVNdQnYkfWsTHlz+fw/pKfdpWHTFqiqkL8zQI2a3ny7bmuZ5sjKzCTjvnuGBKQmJZCXm4ORsUmZ5bNzdmPE7OV6jVEoFAwaNpLWbYJIz85DpVKRlpqsez8z/S45Wfcws9S/rkVlU130aFVBL5/szz//nHfffRcAHx8fxo8fz2effVYhgslUHKJGww9ffMj3YcP4+cCfnI/VlmVXWdpjWrPBw47nd8Jv8+CPRXB0+eO/KGb2YP+IAeAlV3mUqXpUF19CWc/KlCfrli9maO/OfPruG3w66E00mvLNdlEVsLKx5cX2nXT7Hbr2KhcDu7Tcjo1hWI92TB/9Lt9MHE705Uie7/gwf3jToFeqpYEN1UePVhX0WsnOzs6mWbOHEbKBgYFkZ2eXu1AyFUvCjStcP39Kt38xJZe2Q0dh6vkcShPzhx0v73+4HX8e7iWDeRGFagQBWg6BxIugNCpocMvIyOiFrGdlypP13y3VbUecOEr05YvU9q1fiRJVDBPmfMOpI3+gUCpo3LJ1pcry++6fyMzQBv5rRA37fvqRDz6bScuXQ5BEieeayQtRzwp6GdlOTk6sWbOGbt26AbBz504cHeX8x9UNc2s7FAoloqhBUCiwdnTDwqd5oX65ghEqKQ8BARRKBLXZ4ydVqMC5fAJNZGQqAumR/1dlZD0rU544uriSkXYHURRRKpXY2NsXO0aTn8/3i+dw5tghGj8fxFtDP0ZZxV3+lCoVzVq3rWwxAHBwdr0fKAlIEnZOLigUCho0r1zjvzyoLnq0qqCXu8j06dM5fPgwrVu3pm3btvz+++9MnTq13IQ5d+4cffv2JTAwkFatWjF16lRyc3MBOHjwICEhIQQEBNC5c2cOHDhQYOy3335LmzZtCAgIoF+/fkRFReneu3fvHuPGjaNFixY0bdqUTz/9lMzMzHKTu7phaedIj4+m4+RZG0+/xrw2uvDf8G5CLD/t+5vbKZkkp2VxPE4CoycY2TIyVZzq8pizovTs9u3bCQ4OJjg4mFmzZgFw4cIFevTowSuvvML48ePJy9PGVsTFxdG3b186derE+++/T0ZGBgBpaWkMGTKEzp0707dvXxISEsosl0zF8ln41/g3bYF3XV8mhH+NfQlKce/auJqtq7/l2sXzbF75Db9sWWcASZ8egl59jdf6v4erpzcNn3+J7v3eq2yRyo3qokerCnqtZDs7O7N48eIKEUQURd577z2GDBnC6tWrSUhIYMCAAdja2hIcHMzw4cOZN28eL730Env37mXUqFHs3bsXZ2dntmzZwurVq1mxYgWenp7Mnz+fESNGsG3bNgRBYMqUKdy6dYs9e/ag0WgYNWoU4eHhTJ48uULOpSogafLJunkBhZEpJq4P3TfSb8dwL/kWdRu3xO/5do8dn5F8m+S0e/x0+DIAVo5uFF7rlpGpPkjVJGCnIvRsdnY2U6ZMYefOnVhbW/Pmm2/y559/Mn36dMLCwmjatCnjx49n3bp19OvXj7CwMPr06UPXrl1ZvHgxixYtYuzYsSxYsIDGjRuzbNkytm7dypQpU1i4cGHxAshUGjW8azN35Qa9xtyOjUGhVCBqNCgUShLiYkp9/OtXLxMfG4N/0xaYmZsXP6CUiKLI6eNHERQKAgJblEtmkdKiUCjoP2IsfYeFcvr0aYxNKs8/vLypLnq0qlCilez33tPehbVr14727dsXepUHd+/eJTExEVEUtX9EtB9UU1NTtmzZQmBgIB06dEClUvHqq6/SrFkzfvzxRwDWr1/PW2+9Rd26dTE2Nubjjz8mLi6Ov/76i6ysLLZt28aIESOwsbHB3t6eTz75hM2bN5OVlVUuslc1JEkkbuMsbm2YQewPk0j5czMAcaf/4LdZ73Hs28kcnPMBeVkZj53DufZz2Lp76/YbdOxZ4XLLyFQkkgSini9D/jZUpJ7Nz88nPz+f7OxsNBoNGo0GlUpFVlYWTZs2BaBHjx7s2bOHvLw8jh8/TufOnQu0A/z22286N5YuXbpw6NAh3dNGmaeHl4J7oLxfMVilVtOmc7dSzbNvx1b+E/ISY957m8E9Our8lCuCzz8extC3XuP9N7oxa+KnFXacZ52qrkerGiVayZ4yZQoAc+bMwcWlZPmX9cXW1pYBAwYwa9YsZs+ejUajoX379gwYMIDhw4fj4+NToH+dOnWIjIwEtGWIBw8erHtPrVbj5eVFZGQkNjY25OXlFRhfu3ZtsrOziY6Oxs/Pr8QyFheV/eD9yo7ezk2OJTvmnG7/zokdWLfoRtTvP+k+7fdSbhN/7hhujYsuPiMoVXSbsJjY8ycxs7bHqZaf3udVVa5HVUG+HgXR53qUxzWTJEl3A6/HoDIft6RUpJ61sLBg1KhRdO7cGVNTU5o1a4ZarcbJ6WHhD0dHRxITE0lNTcXCwkJX2vpBO0BCQoJujEqlwtLSktTUVJydi3dBeIA+f2/5u1JxPOkae9X148sf9xAVeZba9Rvi6OJWqr/FptUPs1LF3ojmrz8OEPRy+ddMSLuTyp6fN+v2t6xdxYjxn2NciRlGoGp+jssqS1XXo1WNEhnZD5TqhAkT2L17d4UIIooiJiYmTJw4kV69enH9+nU+/PBDvvrqKzIzMzE1NS3Q38TEhHv37gE88f0HvoRmZg/9iR/01dcv+59//inXfhWFkHsPK0EBkrZClUZtxunTp8lGpc0Ecv8D/8+eHzm9fRVWz7XColbjx0xmwZ20HOJOl77UbWVfj6qGfD0KYqjrUZoaCoakIvXsxYsX2bx5MwcOHMDS0pKPP/6Yw4cPF3ikLkkSgiDo/n2Uxz16lyQJhUKv0B69/t7yd6XiedI1NrFzITY+gdj4kvnenz1xhAPbNmJuaU33/7yHkak5gkKhCwK8k5bB6TL8ljyO/Pw8TEzNyMnWPp02t7Tk/PkLleoy8ihP0+e4quvRqoZePtm+vr5s2rSJgICAAkatm5tbmQX55Zdf2LNnj+7HpW7dugwbNoxp06bRpEmTQimssrOzMb/v32VqavrY9x8Y11lZWbr+D9xELCws9JLR39//iRHWGo2Gf/75p9h+huCevQmpRzahMDbHvt1/MLJ3J7euN/9sXERmwk00okTa7etIkkjSH+tp9GIHLJ1rlKsMVel6VAXk61EQfa7Hg77Via5du/Laa6/RrVs37OzsSjyuIvTsH3/8QYsWLbC/n1miR48e/Pe//9WtUAMkJSXh5OSEnZ0d6enp5Ofno1KpSExM1N0AODk5kZSUhIuLC/n5+WRmZmJjY6OXLPr8veXvSsVR3tc4Mf4W4xbNQRS1ftzbVi9l0vxlzP9iLDejo+j6Rn+69epTDpIXzbzlP7BwZhgKpZLRE76gfqPHLBwZkKr4Oa6OurQqcOLECSIiIhAEAX9/fwIDA0s0Ti8jOyIigoiIiAJtgiCwb98+faYpklu3bhXy7VOpVKjVanx8fDh37lyB965cuUKDBtrCKXXr1uXy5cu0batN35OXl0d0dDQ+Pj54e3ujVqu5cuUKjRo1AuDq1as6lxJ9UCqVJfqilLRfWRCzM8i7dRmlnRsq68KPai19mmHp06xAm6mVHc0HTgJg77R3kR6p9JhzNwkbN68KkdUQ16M6IV+Pghjqehj6MefIkSNZs2aNLmC7R48eBAUFFbvyWxF61tfXl5kzZ5KRkYG5uTkHDhwgMDCQX375hRMnThAYGMjmzZtp06YNarWawMBAduzYQbdu3XTtAEFBQWzevJkPPviA7du3ExgYqHMrKSn6/L3l70rFU17X+E5yIqKodUUQRQ3xN2NwcHJm2qLvyjx3SWja8gVWbt3zxD65ubkcP3IIS0srGjYpmZFUHjxNn+NnzV0kNzeXESNGcOnSJRo0aIBSqeT777/H09OTr7/+upAXxb/Ry8jev39/8Z1KSatWrZg7dy5Llixh8ODBxMXF8c033xASEkLXrl357rvv2LlzJy+//DJ79+7l2LFjTJgwAYCePXuycOFC2rRpg7e3N/Pnz8fBwUH3A9C5c2fCw8P58ssvAQgPD6dLly6YVNOIX01GCinrJyFlpYNCiU2XjzGqoV+O6tptunN6gzYrgKWzJ/a1GxQzQkamelOaAByhDL8NDwIWX3rpJfz9/VmwYAGTJ0+mW7du9OzZ87E3+RWhZ1u1akXXrl3p2bMnRkZGNGjQgCFDhvDKK68wYcIEMjMzee655+jfvz8AkydPZuzYsSxduhRXV1fmzZsHaG97nsgtAAAgAElEQVQcxo4dS3BwMJaWloSHh5e7rDLVkzp+DfB5rhGXzp0BoEe/dytZooJoNBoGv9WDE0f/BGDYx2P5YLQcIKkvhtajlc1XX32Fi4sLixYtQqV6aDJPnTqV+fPnM378+CeOL5GRnZiYyMyZM7l8+TJNmjTho48+wsqqfEuC1qlTh6VLl7JgwQKWL1+OpaUlXbt2ZdiwYRgZGbF48WLCw8OZMGEC7u7uLFy4EG9vbfaLXr16kZ6ezrBhw0hJScHf35+lS5fqVlgmT57MrFmzCAkJIS8vj/bt2zNx4sRyld+Q5Fw9oTWwAUSRrPO/6W9ktw7BzsuXrDtJOPkEoDKqnjccMjIlpbJWYJRKJUOGDGHIkCFcvXqVRYsW0blzZy5cuFCgX0Xr2QcyPMoD15R/4+7uzurVqwu129jYsGTJknKTSebpQaVWM3/VRv7+60+sbW3xa9ikskUqQNTlizoDG2DVt9/IRnYpeNZWsn/99Ve2bdtWwMAGGDNmDMHBweVjZI8bNw4/Pz+6devG9u3bmTFjBjNmzCi91I/hhRde4IUXXijyvdatW9O6ddHVkgRBYODAgQwcOLDI9y0sLJgyZYouer86I2Zncu/ysYcNAigtiyh1XgJsa9TFykRNxoaJ5GWmcdfKC6+eH6HU0+AWs9LI+mMV4t0EjP07YOTbhvhT+4g59BPZgjG5tT0xtZEr1slULhKVo+slSeLUqVPs2LGDPXv24OHhUaT+NJSelZGpKIxNTGkZ9OR0k7s2reXntd/hWsOLEZ9NR5Ofy9oFX5CWmsQrbw6madAr5SJLdlYW0yeP4/SJY3TsHMKbA95FpVKRr9GgEBS4unuQmX6XVfPCiLt2hTZdetGxV39+3baJTauW4eTqzojPpmPvVDEZ1aorlaVHKwu1Wl2kS5xarS6QUONxlMjIvn37NsuXLwegZcuW9OjRQ08xZcqLO4fWkRV7CaUgoVAIGNXwxyywdDlMJUkiZ+dcjPKyMFKCSfpVovato27nAXrNk/XH9+RHnwZJJOvgSnIFYyI3al1zEAQu//QNDf8zqVQyysiUF9L9//QdVVoyMzPZsGEDCQkJDBkyhJCQEFasWEG9evWK7C/rWZmnncvn/2FBmHb1OPrKJZRKJSb5mUSd+xtRFFkx9RO8fP2xdy57MoXli79k05rViKLI5cgL1KpTlwXfrmLx3JlY29gwcXo4678J5/iB3UiiyJqvpmNkasGcz0aDJBF9+SILvhjLlEUryyzL04Sh9WhlY2JiQlRUFLVq1SrQfuPGjRK5HJfIyH50mdzIyKjQsrmM4chPSwRJRCOBRpSwrNMcRWldPUQNQn62Ls2RSimQkxIPaCtGcisSjEzBsdYTUyGJ6Yn30wVqyU268fBNSSI79Xbp5JORqca0bdsWd3d3Jk6cSEhISLGrHrKelXnaSbh1U7ctihpuxd7AUspCvJ/iTxJF7iTdLhcjO+5mjDZlLdrCdnE3Yxg8fDRtO3bS9Um8dVOXXhAgJuqSbplWG7x5HYCrF86Skngb/2bPY2Ja/OqlzNPDkCFDGDp0KGPGjKFp06ao1WqOHz/OjBkz+OSTT4odr1+C0/tUldyTzyIWDdvrFIfSwhYT79KnKRKUKvB6mIEkMT0btxavIkki0i8LkPYtRNo1G+n0tifOY9ygg25bYeWEVUBHzBw9dG1uz3cptYwyMuWFvlXKHrxKy3/+8x+USiXffvstXbp0oV27drRr167E42U9K/O0EdCiFW6eXtodQaDbm+/Qvmd/3fs16tanpo9+8UWPo+ebb+sy+VhYWtGp62uF+rTr/qbue2br6EKn3v3xrFVX9/5rbw9i14bv+fjtEKaNHsSn/3mNnH+lC37WMLQerWw6duzIyJEjmTVrFi1atKBJkyZMnz6dkSNH0qFDh2LHl2ipJDo6Whd1XtT+qlWrSiG6TGkwq9MMdb9Z5N+Jx9itHgoT8zLNZ9JuMLnXAsmIj8bepwVmDu5Id+Lg9uWHnS7sg8ZdHzuHUb0XUTrURMxIQuXmi6A2oemweSRfOU30rWRcA18uk4wyMuWBoQN2tm7dytixY/H19S2RwSzrWZmnHXMLSxb/uIuIE0dxdnXH20dbcbluw0DS76RQr3ELVGqjcjlW0xbPs+uP41y6cI5GTZth71A4Ligw6GWm/m87CbHX8WkYiJmlFQvXbOfMiSM4OLlQ2/c5Pnjt4Y3xjauXiDxzgkYtWpWLjNWRZy3w8fbt2+zatYukpCRMTU1p3rw5kyZNwt3dvUTjS2RkL126tExCypQvajs31HZlf5wmSRJ3jm4lPfJPjF1qYWKlLVSBiRUISiRJgwAgaSAzGcztHzuX0t4Dpb129VoTd4H845uwUqgwt6n8ggAyMqDV83rr+jL8NlhbW9O+/ZODwB5F1rMyzwJm5ha0DCq4AlizXtlTyP5z8i+WzZ2KUqFk6NjPqdcgAA/Pmnh41nziODev2rh51dbtr/lqOsf3bcPYzJwRs5bi7F6D+Js3tDnABQEHZ9diZRFFkTXfzOWvA3tw8PCivt9XmJYgSK46YGg9Wtl8+umntG/fnhkzZiAIAjt27CA0NJQ1a9aUaHyJjOzmzZuXSUiZqsm9qydJObwBgLyUOJSmVji81BfBxIJ8S2eUGbdAAIxAOrICoUPx6Y6k/BzyflkE+XkggGdqPLxQ/CMVGZmKxtABO23atCEsLIyOHTsW8K9+nD6V9ayMTOnIy8tl4ocDyMrMBEHgs2EDWP/b33q7XJ06tI+/9mhTWmal5fLlp+8xaflmls6cRGJ8LN3fHoz7Iwb54/h9909s+u5rAGKvR/HT6mW88d4o/U+sCvKsBT7euXOnwBPF119/nbVr15Z4vBxZ8wwhajQkXfobhUqNfZ2G5KUlFXg/Py0JTV4uN8+dREhIwNPR+OHYeylIty4h5eegcPdDUDzmo5OTBfn3K3dKoMq7d7+y5NNR7Uqm+mLoIgonTpwAtBVmHyBJUpH5p2VkqhoJt2K5cj6Cus81wtGl9E9Or148T1zMdRq3eBELy/Ktr/GArHuZ3MvI0O5IEndTksnLzcHIuGBSgLzcHM78dRhzSyt8GzUtZITfjLpcoC3nXgb2Ti6Mn7dML3kSb8UiKBTaoEpBIDE+tnQnVgV51orR+Pv7s2fPHl555RUkSWL79u00bNiwxONlI/sZQZIkTnw3hdvn/gKg5gvB1O/0FqlHtiJmpYGgwKLBS/w8axS3r5wFoHEdJ1rU1/od5avtEXfOAUBw88Oo0+iiVwnMrFHUDEC8fhqAFIfncBFKFV8rI1OuGNqXsCgf6kOHDpV6PhkZQ3E18iyhA3qSm5ONsYkpc1dtxauur97z7P15E9PGjABJwsW9Bsu37MXSyrrc5bWytqVt524c2PUTAK/26lvIwNZoNEwa+jYXTmtvfl8fNJy3hn5UoM/zHUPY9t8vUSq0v20u3j6lkqf1K1356ftvyUxPQ6FQ0L7b66WapyryrPlk79mzh02bNmFkZIQoiuTn5wOwfv16JEkiMjLyieP1NrJTUlKIioqiSZMm3LlzBzs7u9JJLmNQctJSdQY2wPUjO/HvORTPgXPIjruMkb07d9PSdQY2wNlrSdRztkYUJcyMo3TtUtwFpPREBCunQscRBAF1u6GI8RcRURAfl46cyl/mWWT37t0cOnQIjUaja9u/fz/t2rWjSZMm9O7d+7FjZT0rU5ns376Z/Pw8APJyczmwcwvvjByn9zxbfvhOZ2DFx8Zw4s/fadsppFxlfcCYmV/RuddbKBQK/Ju2KPT+zWtXdAY2wPZ1KwsZ2bHXr3I3Kxe1UoEoSpimpZdKFhcPTxZt2sfFf/4mI0dDPf+qVf1SpuQcP368TOP1WmI8cOAAb7zxBmPGjCE5OZnOnTuzb9++MgkgYxjUpuYojU216f8EBSbWDggKJUpTS8xrN0Ft44yZtR0KpQqtIzaYG6vIycknX2GMYG53P3WgAEo1gonFY48lKBQo3fxQONfRpRuUkalsHgTs6PsqLeHh4QQEBNCiRQvdy9zcXPfv45D1rExlY+/sgnj/5lAUNTi6lCyTwr9x8/RCoXjoKujiXqNc5CsKhUJBQPMXaBjYssinrDb2DqhUahAEFAoFzm6FZXFwdgNBIE8jIgkKXDw8Sy2PjZ0Dga3aYWP/dFU7NrQerWwyMjKYNWsWPXr0oFevXsyZM4dsPdI46rWSvWjRIn788UfeeecdHB0d+fHHHxk+fLheEfQylYPSyJgWg8O4sGMlCqWaBq+9V6iPmbUdrwyfxvEtK7h78wp1XaxJysgmKj6P4N6TyDuyFvJyUAV2RzB6OiKlZZ4hSvGYUyjDr8PHH39M586dC7TZ2dnRpk2bJ46T9axMZaNAQEAbriYgFCg2pg8jxn+BmJ9PTHQU3d/6D37+AeUqpz5Y29ozdu5Sflz2JRZW1gwZE1aoj4d3HYZ/Ppcda/+Lg4sb74YW7vPMY2A9WtmEhYVhbW3NjBkzkCSJjRs3MmnSJGbPnl2i8XoZ2YIgYGtrq9v38vLSS1iZysW+tj+tRswlJ/0OyVFnEZRKLJ0L3qnXDHgeGzdP1n76JsejEgFQqo1Q2Lhi3PmjoqbVn7RYuJcC9nVAbVo+c8rIFIOE/jHuZflpCAwMZOTIkRw9ehSFQkHLli2ZOHFiseNkPStT2SQnxKNWqxE1GhRKJckJ8aWax9rWjr5DPiTu5g2atHixnKXUn8BWbQls1faJfVp36kbrTt0MIk/yrZvcvHKBmr4NsXF0Nsgxy4qh9WhlExkZybZtDwvyffbZZ4SElNzlSS8j283NTffY8u7du6xevbrECbllqgZZdxI5GP4heZlpIAg0HxyGs1+zAn2sHN2o0bAlMRFHAWj4Sp/yEyD2JESs026b2ECr0aCWV8VlKh5RkhANGLAzceJEmjVrxrRp0wBtoMyECRP45ptvnjhO1rMylU37rr3Yu3ktOZosjIxNaNelZ6nm2fvzRmaMHQmAs5sHyzfvxaICAh+rI9cjI1gcOhBNfh5GJqaMXPADLjWLTw9Y2Rhaj1Y2oiiSkpKii4tJTU3VVRItCXoZ2WFhYUyfPp34+Hg6duxIy5Yt+eKLL/STWKZSif/niNbABpAg5uieQka2IAh0HjmdWxfPoDI2xamWX/kJcP3Ph9vZdyDpMrg2Kr/5ZWQeQ2l8A8vy2xAbG8uSJUt0+wMHDmTr1q3FjpP1rExl41XXj2+2HiAq8hy1/fyxLaJaYknYuuZ/uu3bcTc58efvvFRBgY/VjRO/btOm+EObWvDvg7vo3P/DSpaqeAytRyub/v3706tXLzp06IBCoeDXX3/lww9L/nfSy8i2tbVlzpw5egspU3Uws38k14cAZvZFV69SKFW4129a/gKYO8DdGHQPkMzkrAkyTyeCIBATE0ONGtoAq5iYmAJFaR6HrGdlqgJ2js7YldGFwb2mFxfPntFWSwRcyxBI+LRh5+KBeN/XXRJF7F08KlkimaLo06cPzz33HCdOnEClUvH111/j41Py1I4lMrLbtWv3xMpJcuR79cHJrxn1uw7i5qkD2HjUweeVvoYVwK+bNogmMxE8XwDrios2l5F5lNLkd9U7H+wjjBgxgt69e9O0aVMUCgWnT59m+vTpj+0v61mZp43h475AEkVioqPo+kZ/6jWQn1o+oE33t0hLTuDqPyfwa96awA5dK1ukEmFoPVrZbNmyBQBra62b07lz5zh37hyvvfZaicaXyMiWK5Q9PQiCQO22PandtnQ+dmXGyAwCDGzYy8hg+ICdDh060KhRI06fPo1SqSQsLOyJ+a5lPSvztGFlY8tncxZXthhVEqVKTbf3QitbDL0xlB7NyMjgzTff5JtvvsHDw4O5c+eyY8cOLC0tAW158759+xIXF0doaCjJycl4eXkRHh6OhYUFaWlpfPLJJ8TExGBnZ8f8+fNxcnIiNzeXCRMmcPbsWUxMTAgPD6d27dpIksTs2bM5cOAACoWCL774gsDAQI4dO6aTKS8vj5MnT+Lv71++RvaDoJucnBx+//13MjMzAW0FpZiYGEaNGqXXxZORkZExNIYK2Dl79izXrl2jbdu2rFy5kiNHjpCfn8+LL77IsGHDsLAoOse8rGdlZGSqOobQo2fOnGHSpElcu3ZN1xYREcGiRYuoX79+gb5hYWH06dOHrl27snjxYhYtWsTYsWNZsGABjRs3ZtmyZWzdupUpU6awcOFCVq9ejbGxMbt27eL48eOEhoayefNm9uzZw6VLl9i5cyfXr19n0KBB7N69mxkzZhQ43r179/jggw9KfC56FaP5+OOP+eGHH5g/fz5//PEH8+fPL3ARZGRkZKoqhiqiMHnyZDw8PBg/fjxKpZKZM2cSHh4OwKefflrseFnPysjIVFXKokczMjIKvHJzc4s8xrp165g4cSJOTk73jylx4cIFvvrqK0JCQpg6dSq5ubnk5eVx/PhxXT2CHj16sGfPHgB+++03unXTpmLs0qULhw4dIjc3t0B7s2bNSEtLIyYmhoMHDxISEoJCocDb2xsPDw9OnjxZSLbU1FRu3LhR4uull5F96dIlVq5cSYcOHRg0aBBr167l5s2b+kwhU0lcOfkH/w19i+8nDiLh+uXKFkdGxuA88CXU96UvoijSuHFjrl+/zkcffYSPjw8+Pj6MGTOGmJiYYsfLelamIhFFkaVzp9H3lRf5fnE4WfefmMjIlISy6NGgoCCaNm2qey1durTIY8yYMYPAwEDdfmpqKgEBAYwZM4YtW7aQlpbGN998Q2pqKhYWFqjVagAcHR1JTNTW90hISNAZ6SqVCktLS1JTUwu0Pzrmce1+fn74+vri5+eHn58f7du3p3///iW+XnplF3ngT1irVi0uXrxI9+7dycrK0mcKmUogK+MuW+eNQ9TkIwgKts4bx5AvN1a2WDIyBsVQqacEQSA2NhZPT08uXrxIvXr1AO3jzpLku5b1rExFsn/nT/ywbBEAt27e4PulX/F+6GeVLJVMdaEsevTgwYMolUpdu5GRUYnG29nZsWzZMt3+O++8w/jx43njjTcKBYs/LnhckiQUCgWSJBXo86BdFMUi2y9cuKBrE0WRo0eP8ttvv5VIbtDTyK5bty5hYWG88cYbhIaGcvv2bb2ScstUDJrcHBIiT6A2s8S+tn+hD1l2RhqiJh8ASRLJuJNUpuMlxkRx+/oVatZvjKXdY/Knpt9GSIlBnX+vTMeSkalufPTRR/Tr1w9JkujZsyd169YFtCvUJUn9JOtZmfJEkiQu/H2MjLQ7BLQMIvF2PIIgaFcXBYHEUlZzLCnnIv7m5o3rtGwVhLWNbfEDnhJSE+O5dOYEGXkAlVdOviphYWFRwMguKdevX+fvv/+me/fugDZORalUYmdnR3p6Ovn5+ahUKhITE3Wr0U5OTiQlJeHi4kJ+fj6ZmZnY2Njg7OxMQkICnp7adJJJSUk4OTnh4uJCQkKC7pgP2h9FoVDwwgsvFPLTfhJ6Gdmff/45f//9N/Xq1WPEiBH89ddfzJs3T58pZMoZUaPh8KJQ7sZoXUDqdnwT31cLPsqwcfagduMXufr3YQBahLxd6uNd/fsIa6ePQhJFjM0sGBz+PbbO/1qdS7wMh75GIYk8J6ggwwesXYqeUEbGQIhIiAaIi2/VqhX79+8nJSWFnJwcvV1OZD0rU55sWLaArSu/BsDbtwHDp3zF2uWLuZOSjFKhpGuffhV27J82rGXyJ8MBcHZ1Y/3ug8+EoR1/4xozhvYmJ+segkKJu7MDvk1aVrZY5YKh9OijGBkZMXPmTJo3b46rqyvff/89HTt2RK1WExgYyI4dO+jWrRubN2+mTZs2gNY1ZfPmzXzwwQds376dwMBA1Go1QUFBbNmyhcDAQE6cOIGxsTFubm60adOGjRs30qVLF27cuEF0dDT+/v6MGzeugCw3b97ExsamxLLrZWRrNBpdZHxWVhYqlUqvg8mUP+m3rukMbIDow9sLGdmCIPBa6GxuRp7ByNQMF2/fUh/vzIHtumc/OVmZRP51gOe7/stov36MB18qhZSPFHdGNrJlKh1DVyo7ePBgke3FpX6S9axMefLr5jW67WuRZ8nOTOOH3Yc4d+YUGdm5NGgc+ITRZWPjDyt127dvxfHX4d95ObhbhR2vqnDq4B5ys7O1O5LE0V9+fmqM7Mqo+Ojq6srEiRMZMmQIeXl5NGnShHfeeQfQBpqPHTuWpUuX4urqqluQGDlyJGPHjiU4OBhLS0td8Hm/fv2YNGkSwcHBqNVqZs+eDUCnTp2IiIggJCQEQRCYNm0aJiYmtGjRooAsHTt2pFWrViWWXS8jOzQ0FHd3d3Jycli4cCHdunVj3LhxrFixQp9pZMoRE2sHBKUKSaMBQcDcwa3IfgqFEs/6Tcp8PFvXR6pSSRJ2LkUUk7Fw0N24CoBk7lDm48rIlBVDF1F4NL9qdnY2Z8+excXFpVgjW9azMuWJs4cn9yLTkSQRpUqFraMLltY2NHsxiNOnT1fosT29a3PuzGldxUcPz5oVeryqgqO7J9KDao6ShKPb01Pp0pB6dP/+/brt4OBggoODC/Vxd3cvssaAjY0NS5YsKdRubGzMrFmzCrULgsCYMWMYM2ZMgfbu3bsTGRnJsWPHUCqVNGzYsMS+5KCnkR0VFcWXX37JnDlz6NWrF0OGDKFHjx76TCFTzhhb2tB80Odc/mUdajNLGrz2XoUer3XPgeRkZhB75Rz1n2+PT7M2hTv5tIecTKTka8Rhj4ubXOVLpvIx9ArMv/32RFEsUQEDWc/KlCcjpn7FqvlTyUy7Q7cBH2BtZ2+wY4/5fDqCIHA96gq9336H+v7Phm9yYNvOJN2K4fSh/Vg6udGh94DKFqncqIyV7Mpk06ZNLFy4kA4dOrB792527tzJW2+9VaTBXxR6GdkKhYKMjAz279/P/PnzSU1NJScnp1SCy5Qf9rX9ycnOQmVkgqmtU/EDiuBuQhy3rpzFuZYftkWtTt9HZWRMp0GhJEdHkp4YR25mGqKo4daFv7F2rYm9Zx1QqKBRD0SNhvjTp3F5QqloGRlDIZXCl1Aooy/hoygUCl588cUS9ZP1rEx54ejqzsezv3liH1EUOXn4N/Lz82nWqi2q+ynRHiU/L5czR35HbWxEg2atUCgUHN63mzPHDtOx++vU9fMvNMbK2oap8569io+CINC573u8/MYgTp8+XeT1rK5Uth41NCtXrmTjxo04ODhw8uRJvvvuO958882KMbL79u1Lhw4d6NChA76+vnTs2JGhQ4eWSnCZ8kESRfZ99SmJV/4BwOel7jTrM1yvORKvX2bd5++hyctBoVTRe+JiXOs0eGz/q3/u5ujqOQCYWNmSnZNHbmYaAG3f/xyvpkGlPBsZmYpDohQrMGU43sqVK1m0aBEtWrTgq6++Yvbs2fTq1avYcbKelTE08yd9zL5tmwAIbNWWsEUrC6Uzmxc6hPMnjwAQFPI6aks7dq5ajCAI/PHzWsYvWoN/0+aVIr+M4TC0Hq0KODhoXV4lScLIyAhRFEs8Vq+8UK+//jpHjx7l888/B2Dbtm3yY8xKJiPpls7ABrhyaIfec1w8+iuiJg/QpviLPLz3if0vH9qu285OSyX/Xppu/9IfO/U+vozM08iKFSvYuXMndnZ2HDx4kJdeeokpU6YUO07WszKGJD8vT2dgA5w4dIA7KQXTvKYkxOsMbIDfd2zkwM/rdfsC8NMPyytcVhkZQ1OrVi0mTpxIdnY2Go2GJUuWUKdOnRKP18vIvnbtGr169aJDhw7cvn2bt956i6ioKL2Flik/TKxsURqZgCAgCAosHYsOfASIO7mPP2YN5q/FoWQmxurabV1qIN2/M5NEEZsnuIsAWDvXQKlQYG1qhJ25Mf4edoQE1CTI1w07J+dC/TMSY/nps7dY9+HLrBnXn4w7KaU8WxmZ0mOoio8PsLKywsnJibZt23LlyhWef/55sh9kHHgCsp6VKQu//LicsP6dWPLZUNJSi6+JoFSpcHRxQ6FQICgUWFhZY2FpVaCPhbUNJmbmCIKAQqHA0dUDO+eHvzWCIOBV149jv27jiwHBzB/Vj9sx14o83hejBtPRvyY9XvTn8vmIsp1sBbB/yxpC+3Rg5oj+JMXHFj/gGcPQerSymTlzJubm5uTm5uLp6Ul6erpuAaQk6GVkh4WFMX78eF1C7wEDBjB+/Hh9ZZYpR9QmZrT7cAbOdRvh5t+CoPeLXim7lxLP2fULyEq+xd0bF/ln3Vzde/Vbv0rLnu/iUqcBzUL60ajDk4OzmvYehqOLG0YqJXbmJtR3t8PCRI2rjRkNnEwL9f/z28/Ju5uISpAwyrjF7mUzy3bSMjKl4EHAjr6v0uLr68vatWvx8fEhMjKSuLg4UlKKv8GU9axMabl85jjb//slKbdjiTz5J1uXhRc7RhAEvlj8P5q+GERA8xeZ8vVq1EbGBfoYm5jyydwV+DVpiX+LNoyatYSJXy7XxuCoTfBr2ZbOr73OD3MmkBR3g+jICFbNGlfoWHu3/Mi+3TvIzcsjOTmZicPeKbdzLw9irkSyal4YiXExXDpzgpWzJ1a2SFUOQ+vRysbU1JSxY8diZWXF4sWLCQ0NLTKbyePQyyc7LS2NJk0epoHr2rWrnFaqCuBUtyEdRmuNZkmSiD5zlLycLLwDXkB1X1nmZtx9+EmXRHLSHv7YCwoFLV8bSMvXBhY5/7Vzf5N85Qy1a9bAul4zjMysMLe2Iy09GbXq4X2aAAjZ6Ui3IiEnA1z8dMd+1L8vIyXh34eQkalwtMpe39RTpT9eREQEO3c+dJ/67bffCA0NLXacrGdl9CHyzAmS4uMIeD6ItJREXbskitxNLpmu9fCuQ4fX+pKfn0etevWL7FOnQWM+XbCyQNvCH3frtq9fPKv7fkmiSFpyIv/m1s3oAvsZ6WmF+lQkOdlZnAl3HP4AACAASURBVDp0ADMLSxq2aFWoOvLd1GTdtihqSEm8DcDliBOkJiXQoHlrzCwsDSpzVcPQerSymTVrFvv27SM/P1/XlpCQwPr162nRokWx1R/1MrLNzc25deuW7oN57NgxjI2NixklY0gOrl7A6b0bAXCp04A+k75BUCiwcq+Djfdz3Ll2DgDvtr1LNN8fW3/g52XaIEdrUyMGvByIW/+ZeL3Uk4gfZpGakUO2BkyUgKBAaWGDtHe+drCNG4JbZ3w6vsH5n78FICM7jxZvDyjXc5aRKQni/Zc+lCUvzooVK6hRo0ahH/LikPWsTEnZ+eP/+G94GKDNIjJt+Xoc3WuSGHsdhVJJ2x79i5lBS1joCHZt3QDA80Ht+PK/a/X+3HrU8aVOw2ZciTgOQMc33i3Up1vfd1n736VkZWndprq9UXHVJv+NJj+fSUPeICryLABd3x5MvxFjC/TxaRiIV70GRF88C4JAcN/B7F3/HRu/0f4GOrrVYNLyLRibmhlM7qqGofVoZXPgwAFWrFihKwcvCAKDBw9m2bJlJfqO6GVkjxs3jg8++IDo6Gi6du1KWloaCxYsKJ3kMhXC2d+26bbjr5wlNT4GO7eaKJRKAodM4+6NSNRm1lg4P9nv+gFHd23Ubd/NyuVm3C0cbpzFpWErrNxrk30nEQs3b4Q7cQgWdrBztq6/cCcOU7tkfNr2wMmnEbGRZ3Bv0AL7pygxv0z1wdDFaOzs7Jg5cyZ//vknAM2bN2fEiBFYW1s/cZysZ2VKyq9b1uq2E2/FEnXxPJ9+vYHrkf9g5+KOvYt7sXPk5+XpDGyAIwf3k5KUiL2jfulglUoVw2YuJfpCBGZWNrjWrF2oj42dAxsPnubXnzfg7eNHo+Yv6HWMsnAz+qrOwAb4ZcvaQka2kbExE75ey9Vzp7FxcMKlhhefvd1Z935iXAxXz52mfqDh5K5qGFqPVjbffvstzs7OREVFoVQq8fb2ZtWqVdjZ2ZVovF5Gdv369dmwYQPXrl1Do9FQq1YtvSrfyFQcmpwsrv60mEYeNiSn3SM6OQOV2hhzm4eFBxRKFbbej0/NVxRONbxJvBmNJEkIgI2ZEUobbXCjmb0rZvau2o6m9QAQrZ21riKSiKRQkqvWloe29/TB3tOn7CcqI1NNGDduHB4eHoSHhyMIAjt27CA0NJRly5Y9cZysZ2VKirtXHW5eu4ooahAEARePmhiZmFI3oOSp9JQqFS5u7iTE3wLA3MISS6sn3wg+fi41tf2bPrGPhZUV3d8uvMr9AEmSWDRnGju3bMC3QUPCwhdiZW1TKnkexc7BCbWRMfl5uQiCAjdP7yL7qY2M8G388Pq51qxF0q0YRFFEUChwcC3+xkXm6SHl/+zdd3zM9x/A8dfd5bKcyB5ChEhQYjQJYlMrCJVSrZRuo63RltYoqmq1WopSXdrqoIiiRvAzalUTas/YBEnI3nff7++PyJEaySW53CX5PD3u4e77/X6+3/ddLu/75HOfcecOgwYNws7OjqtXr+Lt7c2MGTNKt5I9fvyDAxjuV1ifFMH4YvdEcOfkPtQKGfdqNlg5eeLffwRWtpoSnbffiEmoLS25HXOUwHq1qNUzHLXbgy0U+RRtX0WOXgVZKfBEV7RxOSW6viCUlrJYqWzp0qWsWrUKpVLJzZs32bt3r76C7OfnR+/evR9ZVuRZwVBDxk3D0tqa+NhrhAwYTI3aRZ9aLJ9CoWD+DytYMOsjcnNzGf7ueCxN2D1pR+RGli76AoD4W7dY/Pks3p9a8sHyVe0dGD/3WyKWLqZK1aq8OHpikcoNHjuN3xfN5k7cDTr3G4yrZ+VYGv5RKtuKj9OnT+eTTz6hefPm9O3bl0WLFvHee+8VefBjkSrZzZuLCebNXU5aEnk9n2RQKGjcoQee9Uu+hK1Op6NOowB8/erh9cST2Pg9fol0RRUHFO1fh8xkpNiT2GYmPz7uzDSuHzuATTVH3Os1K3G8gvAoxv6a8+jRo0RERLBy5UpsbGzo2LEjc+bM0c8McvDgQXx8Hv0HqsizQmHS01I4tGcH9s6u+AcGU9XegREfFj6DSGFq1/Xj829/Nrhc1I6NnPv3AC1DwqjT4PGfDUWVcHewIeStLng7vvQGyvsHtcI/yLCuHlXtHXl1wuwC25LvxHP64H7catbGu/6DK11WZJWtu0h2drY+N8uyjIeHB+np6UUuX6RKdt++96Z0O3v2LP/88w9arZbAwEAaNTKs+4FgHG5B3bl9bDdSbjYWtnY4Ny75qovJt+P5dHgYte1UWKtVnI38mSefGUaDzoUMmsxMho0fo8xOpwEgVXeAOi0eOEybk8XmWW+QGpc3F2mTPq/SqPvAEsctCA8jyXk3QyjuHp+WlqYf+AJgaWn5QBcOOzs7Jk2ahK1t3qCorKwsfvrpJ/766y8kSeLq1as4OTnx1FNPIcsy27dvL1Be5FnhcbKzMnlvcB9uXr0MQPibYwl7yXQrga5bOp+9q75HoVBw+H9reW3GN/g1CSrxebv06M0PixdwM/YaFhYWDHjxtVKItvQkJcTx8et9SU9JAuCViZ8Q1KloS2xXBCXJo+WRjY0N69at038LeejQIezs7AopdY9BfbL/+OMPFi5cSOfOnZEkiZEjRzJ06FAGDBhgWNRCqdNU96Hp6K/IjL9GFffaWNhUKfE5T0XvQZmTgbX6Xn+4mD0bCq9kx56E7Ly/9GRAcfHvh1ayEy6e0lew888tKtmCsch3/xlaBqB9+/ZkZmbqt7/11luMGDGiwLHe3t54e3sDcPv2bSwtLfnss89o1sywb2hEnhUe5uzxw/oKNsDWNctNWsk+uO3eIHsFsDNiWalUsh2cnFm5ZTenjx+hpncdXN09SnzO0nQyao++gg2wf/MflaqSXZI8Wh7NmDGDMWPG0KJFC5KSkpgxYwaffvppkcsbVMleunQpK1euxMHBAYBhw4YxaNCgUkv++U9g165dSJJEUFAQH374Ia6urhw5coSPP/6YmJgYHBwcGD58OP3736vsrVmzhkWLFhEfH69fBjP/w02n0zFnzhzWrl1LZmYmLVu2ZOrUqbi6GjZ62txZauyx1JR8gEg+1xreZOXq9F/1KBQKqnkUoT+aXd7rercUsp37Q6fw0Th7oFCqkCUJhbKI5xaEYipJX8Jdu3Y90JL9KNeuXdNXihMTE5kxYwZKpZK2bdvSr1+/Qqd9MnaeFcont+o1UapUSDoJpVJZrP7Xpcne1YObSXlzYSsUCmrUbVBq566i0RDQsnWpna80uda49zmlUCpx96pjwmjKXmXrk12nTh0iIiIA2LZtGxYWBlWbDVvxUZIkfeKHvCmqlEqDTvFYI0aMICMjg61bt7Jjxw5UKhWTJk0iOTmZIUOG8PTTTxMVFcX06dOZOXMmR4/mLcl64MABpk2bxqxZs4iKiqJ3794MHz5c3/K0ePFi9u7dy+rVq9m9ezfW1tZ88MEHpRZ3RVWnYTPCRk4h1doZZRUHagU9RfPwdwov6OIDLQaBS13i7esjNw596GEaJ3faDZuKW72m1ArsRPCgwhfqEITiKslywBqNpsDtUZXsU6dO8fzzz/Pcc8+RnJzMjh076NOnD6dPn+b8+fN89tlnDy13P2Pl2e3btxMWFkZISAgff/wxAPv27SM0NJSuXbsyd+5c/fM9deoUYWFhdOvWjQkTJpCbmwtAbGws4eHhdO/enWHDhpGWllbiuISica1eg/c//YpGgS1p2703b02eXXghIxry0UKcatVDYWmDb4tO9Bhkulb1slTXP4BBYz/Gt3Eg7UIH0OfVUaYOqUxVtmXVBw8ezKBBgxg0aBAvv/yy/n5RGVQlb9CgAR9//LG+NWblypXUr1/f4KAf5vjx4xw5coR9+/ah0eTNiDFt2jTi4+PZsmUL9vb2hIeHAxAcHExoaCi//PILjRs3ZuXKlfTs2ZOAgLypg1566SVWrFjBxo0beeaZZ1i5ciVjxozBwyPva6eJEyfSpk0brl69Ss2aRZsvurJq2a0vLbvl9RW9EXOCC4f24uUfhMbBJe+A+AuQGgceDcDmvmmffIKRvJtz9fBhnCwePVK9hn8wNfyDjfkUBKFM3Llzh9dee40pU6bQtWtXevXqxR9//IGFhQVffvkl48aNIywsrNDzGCPPXr16lSlTprBy5UqcnZ158cUX2blzJ1OmTGHZsmVUr16doUOHsmPHDjp16sTYsWOZOnUqAQEBTJgwgeXLlzNo0CCmTp3KgAED6N27N19++SULFy5k3LhxhQcglIrAtk8R2PapUj+vpNMRvft/6HRaAts+9cCy6g9Tpaod7y1aUeqxlAdPBLZGksHDq06lXpimMri/W2BmZib//vsv586dK3J5g5pHPvroI6ysrPjggw8YP348arWaKVOmGHKKRzp69Ch169bl999/p0uXLrRp04bZs2fj4uLCuXPn8PMrOMdy3bp1OX36NAAxMTGP3J+amsrNmzcL7Hd2dqZatWqcOXOmVGKvDE7v28KKD4ew5evp/Dx+MGmJ8XBhP2ydA3//BBunQ2bZLpErCIbIH7Bj6K2ofvzxR9LS0vjyyy/p06cPly9f5vPPP9fv12q16HS6Qs9jjDy7detWevTogbu7OxYWFnz++efY2tpSq1YtvLy8sLCwIDQ0lMjISK5fv05mZqa+0SIsLIzIyEhyc3OJiooiJCSkwHah/Fs4dQyfjXuDeRNHMvvdIeW65dHYEhNuMWFwKN9MH8dHQ59l/5b1hReqQIydR81NUFCQ/tauXTtGjRrFhQsXilzeoJZsa2trxo41zlf6ycnJnDlzhkaNGrFmzRqysrJ47733eP/993F2dsbGxuaBWDIyMgBIT09/5P78qVbyR/zfv9+QaViAQj8g8/cX5YO0vDnx10b9/ay0FC4e3k8jbd5fcwqA7DSk2JPI3vcGvlTk16M4xOtRkCGvR2m8ZsYesPP222/z9ttv6x8vXLiQbdu2kZSURGZmJm+88Qbdu3cv9DzGyLOXL1/G0tKSN954g2vXrtGxY0d8fX0LjEtxdXUlPj6euLi4AttdXFyIj48nMTERjUaDWq0usN1Qhvy8xe+K8eS/ttnZWey9r6J4LGoviQlxVHN0NlVoZu3wvl0FBj7u3hhB86d6PPRYc3wflzSWyjbw8WFmzSr6vO0GVbJXrVrFZ599RlJS3htMlmUUCgWnTp0yLMKHyO/jOHHiRKysrNBoNIwePZpnn32WsLAwsrKyChyflZVFlSp5M2jY2Ng8dL+Dg4O+8n3/zAD/LV9Ux44dK9XjyhOd2hYUCv0IhvjUbBJUapxRIJO3GuSxi7Hs//o1Um5epfoTQdR/KowTe7fyy8cj0dg70fH54dg5VazBpsVREd8fJVFmr0cxBuyU5LPhrbfe4oknnsDGxoZ+/frh5+dH+/aFT61pjDyr0+nYvXs3v/zyC1WqVGH48OFYW1sXGISZfx1Jkh66Pf//+xU2iPNhDPl5V+bflcy0FP5asYQ7N67hG9iGgG6FD5p9mNuxV9i+fAnZ6WkEhfSjXmDbAvtPnjyFnZMLqXduAzJWtlWIuXAJ1ZVrpfRMKpa0bK3+vkKhQF3FjsOHDz+2TIV6H5dxHjVHjRs3LvKxBlWyFy9ezA8//EC9evUMDqowdevWRZIkcnNzsbq72pQkSUBeH8Vff/21wPExMTH4+voC4Ovr+0AfmZiYGNq1a0e1atVwc3Mr0KUkPj6epKSkB7qYFMbf37/ADAP/pdPpOHbsWKHHlUcNG9Rj/0pnEq5doEHr7jRoGwK52chH16JIuYVUuyXX/7eLhAsnkSWJi/9so4aPH/vX5i1wkJmazL+bVzDq0+9M/ExMpyK/P4rDkNcj/9iSMMUiCp06dQLg9ddfL3IZY+RZZ2dngoODcXJyAqBz585s3ry5wOseHx+Pq6sr7u7uBVqoExIScHV1xdHRkdTUVLRaLRYWFvrjDWXIz7sy/678NncqsTF5+fTojj9p0aEL/i07GHyeqfOncOfGVWRJYufyr+napz8OLu7617hx48ZMXvATK776HK02l36vjaR2vYal/4QqiKZNm1LN1oq9m/+gRh0/nnl99CP7ZZvj+7ikubSyLUZTUgZVsu3t7Y1SwQZo1aoVNWvWZMKECcycOZPs7Gzmzp1L586d6dWrF/Pnz+eHH34gPDycgwcPsn79ehYtWgRAv379ePPNNwkJCSEgIIBffvmF27dv06VLFyCv7+DixYvx9/fHwcGBGTNm0Lx5c7y8vAyKUaVSFekXpajHmVpOZgaX/t2Dla0GrybBj20lUdlq6PjiO//dCM2fB/K6jGT+sbbAX6wpt+9buUuSSE28Uy5eF2MrL++PslJWr0dx+gaaoi+hMfJsx44dGTt2LMnJyWg0Gvbs2UO3bt34+uuvuXjxIl5eXqxfv55+/frh6emJlZUV0dHRBAYGEhERQbt27VCr1QQGBrJhwwb69Omj324oQ37elfl3JS3pToEmw4yUpGK9FmnJich3G6xkWSYrPQ2V+73zqFQqatbxZcwniwuUu3z+LCcPH6RhsyC86ph2ukBz067nM7Tr+UyRj69I7+PykkfNRZEq2VFRUUBei/HUqVPp2rVrgbkCg4JKPgG9Wq1m2bJlzJo1i27dupGdnU2nTp2YOHEidnZ2fP/990yfPp358+fj6OjIBx98QMuWLYG82UamTJnChx9+yK1bt6hbty7ffPMN9vZ5c0a/+eabaLVawsPDSU9Pp0WLFsybN6/EMZdnOq2WtTPe5PbV8wA07vYsrZ5/q0TnbN7zOc5G70abk001Fw/aPP0i0fv3EXclBoVSSY8XhpZG6IJQIRkzzzZp0oQhQ4YQHh5Obm4uwcHBPP/88/j4+DBq1Ciys7Np3769vs/4nDlzmDhxIunp6TRs2JDBgwcDMGXKFMaNG8eSJUvw8PAoMLBTKF2d+g3m1MF9aHNzcKnuRdM2nYt1np6Dh7N8/nQA/Fu2o3pt30LLnPg3mndf7odOq8XCQs28ZWuo59+0WNcXhMqsSJXs+fPnF3gcExOjv69QKPjpp59KJRg3Nzfmzp370H3+/v4sX778kWX79OlDnz59HrpPrVYzZswYxowZUypxVgSJ1y/qK9gAp3dvLHElu2b9JoxYvJbEm9dw8/ZDpbYk9I2JONiosXdxw9nds6RhC0KxmfvXnMbOs/369aNfv34FtgUHB7Nu3boHjq1fvz6rV69+YLunpyfLli0rURxC0fg1bc5HP0eScOMqNX2fwNLKuljneSrsBRo1b0NGWiq1fJ8o0pzrOzev07/3JVliV+R6UckWAPPPo+amSJXssWPH4u/vX6xBF0LZk2WZM5uWceXvTWjcavHkC+9hXc2xwDEaJ1dUakt02lwUCgUO1b1L5doaeyc09nn9PnU6HUqVBbWfaFJhvioTyi8Zw8fflOVHg8izwn9Vc3KhmpNLic/jVsPboONr+fgh3Z2FQtLp8PIxbPxSvlux15n8zhtcvXSBfi+8zCtvFWExM8GsmXseNTdFqmRPnjyZmzdv0rx5c1q3bk3r1q2pUaOGsWMTiin+zCHObf0NgJy0FE6u/44nXyg4JZi1pho9x8zh3w2/Yl2lKi2eHWaKUAWhzJh7C4zIs4K56NFvIMmJdzj8z14CWrWja5/+xTrP59M+4OihKCSdjiVzZ9OsRSuaBbUs5WiFsmTuedTcFKmS/ccff5CWlkZ0dDRRUVFERESQmppKixYtaN26NZ07F6+vmGAcOenJ+vsyMjlp96YCu35sPzkZadRs2obq9ZpSvV7pfgWYcPksty+fxaN+M6o4uZfquQWhJORiTD1Vlp8NIs8K5kKpVBI+dCThQ0fqt+VkZ3Hor62oLa1o1uYplCoVp48dJub0CQJatcPD88HVk+/cTtDPEgaQdOd2mcQvGI+551FzU+TZRTQaDR06dKBDhw5cvnyZAwcOsGzZMtavX090dLQxYxQM5NawBRq3mqTduopCqcKnY94o6IOrFnNme14/y5Nbfydk/GJUFupSu+614/+wdf44kGVUakt6jl9ceCFBKCOSLCMZmO0NPb6kRJ4VzJEkScwd8yoxxw4B0LJLb/yad2DSqNdAlrG2seXbNVupUat2gXIvDhvBe8NfRqfV4tugIS3bdjBB9EJpKg951JwUqZKdlpbGvn37+Ouvv9i7dy9OTk60adOGKVOm0LSpGAxhbtTWVWj37kJSrp/HxsFN3x/7wv57SyAnx14k+cYlHGsWPtK8qC788z8Udxen0WlzuXJ4D1QX860K5sHc+xKKPCuYq8T4m/oKNsCBbeu5HHcHBXm/I1mZGezfuY3+LxacD75Np678sSuaWzeuU79hY9R3F50Tyi9zz6PmpkiV7JYtW9K8eXOeeeYZ3nnnHRwdHQsvJJiUSm2Jg3eDAtvsq3uTcPEksiyjsrCkisPjF5K4+vcmLmz9Dcuq9jR67h2quns/9niH6t73+l7JMkkXj1HVvX5JnoYgVBoizwrmqqq9I7YaOzIz0lAArjVqUdu3Hru3btQf4133wQab27diWTr9PeKuX6Zjn+fp9eIbrPr+S/5cvhT3GrV4Z/oXuHqIcQdCxVWkSvbQoUPZu3cvixcv5vDhw7Rp04YWLVpgbV28KYUE02jz2iQO//EtOempPNF1AFaaao88NuP2DU5FfAlAdloSx1fMJXjUF489f8Muz3Lj+AHiYo5hqVKSeuEYKlcfeDKgVJ+HIBSHTDEG7JRhG4zIs4K5srSy5p3Pv+fPHxehtrKm72ujsXd2Izcnh7MnjtGhWy+CWnd4oNyKhTO5ePIIkqRj3Q8LsdRU45dFcwBITUrim08+ZOLcb8v42QglYe551NwUqZI9YsQIRowYQXJyMnv37mXz5s1MmzaNmjVr0qZNG1599VVjxymUAlt7Z1q9NK5Ix+ZmpN57IEvk3jeY8lGUKhXuXj7k3DiXt8KYQoGUnV7ccAWhVJn7gB2RZwVzVsuvIW9O/7LAtiHvTHhsmdSkO0jyvYGPt2/F6u9LkkRKohgIWd6Yex41N4XPSn+fatWq8dRTT/H000/Tr18/EhIS+OWXX4wVm2BCdp4+OPk9qX/s02Vgkcp5t+mFyjKv5c2qqgO2dZ4spIQglI38ATuG3sqayLNCRREycAgqZd4aCV6+DegV/ho+DfwBUKqUPPPyG6YMTyiG8pJHzUWRWrIjIyM5dOgQBw8e5ObNmzz55JO0atWKBQsW4O3tbeQQBVNQKFU8+coUUmMvoratio2jW5HK2VWvzVOTfiA9/jq2LjU4fuqMkSMVhKIx9xYYkWeFiqZxcHtmLt9GYvxNatatj4XakllLV3PxzEmcXN1xdCna54pgPsw9j5qbIlWyV6xYQXBwMB9++CENGzYUK5KZsavnTrDskwlkpqXS86URtOzWt9jnUihV2NWoW+TjJZ2Ozd99ysm92/Co24A+I6c+9vjkq+c4vuJztJnp1A0ZjGegmAdYMB757j9Dy5QVkWeFwvz6/RJ+XDwfFzd3Pv7iK7x9Cp8d6vLZE3w/YxzpKcn0eXUkbXv2K4NI77F3dsXe+d4g+12rfmDP2l9x9KhB+PuzcHTzLNN4hJIx9zxqbopUyf7++++NHYdQSn6aNY7461eQZYnlc6dQP6AV9s5l01pwYu8WDkbmzcN98eg/7F75Ha7NOj3y+GO/fkrGnRsgy5xY+QVOvs2wruZUJrEKgrkReVZ4nPNnTzP340kAJCXeZtr7o/lu1YZCy3378XvcunoJWZZYNmcyDYNa4+jqYexwH+rSyX+JXJbXrzsjLZm1X83m5SnzTRKLIJQFg/pkC+YvPSUJ+e5AE1mWyUxLLaRE6clMTQYUBR4rdTlI5/ahu3hQH1e+3MzUe98jyTLarIwyi1WofPK/5jT0JgjmICUpSX9fkiSSEu8UqVx6anKBz4SMMvxM+K+M1BT9fVmSSE9ONFksj5KaeJs9f67kxD+7K/Vy4I8i8qhhRCW7ggkZ/Kb+fuPWnXGv5VNm127Yphv2d1tI1JZWNO/xLLXP/YFu70/kbv+K3H0FB2/5dA3X33fzb00VVzFfqmA8cjEG64gPWcFc+D8ZSGBwGyBv2fMho8YWqVyfl0eQ3/jRtM1TeNYuvQXIDOXbrCU1/fIWKFOqLOj03OuFlChbGWkpzBren9/mTWXRhOFs+U1ML/hfIo8apsjLqgvlQ9vQ53giqC1Z6Wl41PYt036dVao5MGzeCuKvnsfezRPL7FS0WfdaW6SYv6H1IP1jr1a9cK4fiC4rA41HbdEHVTAqMWBHKM8sLCxY+NNKzp06gb2jE+7Vi9aXuX3vATQMakNmeiqedfxMmmfVlla88ekP3Lh4DjsnF+wcXUwWy8NcPHmUpIQ4/eO/t6yl20Dz+kPA1EQeNYyoZFdATu6mG0iitrKmet28lgqthQU6pRqVpAWFAoXDg3HZOrqXdYhCJSUG7AjlnUqlon6jxgaXc/Ywn8GFKgs1NXyfMHUYD+VawwulSoUkSSgUCmrWFSsW/5fIo4YRlWzBaBSWNlz26YVP9kWUVrZYBBR/phNBKCnRAiMIwuO4VPdi2LQv2b1+OQ4u7oS+MtLUIZkdkUcNI/pkVwBXYk6zLeIXrsScNrhszLGD7Fz7G/HXrxghMsis4kZO075cUTiREHvZKNcQhKIQiygI5iw9LZWI5T8Tuf4PdDodAEej9rNu+Y/cuGac/Fza0lOS2bNhJUf2bCu3/XAbNm/DsGkLGTDyA2w1dqYOx+yUVR5NS0sjNDSUa9euAbBv3z5CQ0Pp2rUrc+fO1b+/Tp06RVhYGN26dWPChAnk5uYCEBsbS3h4ON27d2fYsGGkpaUBkJKSwpAhQwgJCSE8PJy4uLzuQTk5OYwdO5aQkBD69u3L+fPnS+PlEi3Z5d25oweZOeIFJElCqVQybsEy/BoHFqls9I5NfDvtXQAsh01nhwAAIABJREFUrW344JsIXD1rlWp82vQktn86TT9zSMDz7+Ad3L1UryEIglCeabVaXnqmJ2dPnQDg6WfDadOuHZ9OfBsAG9sqLInYirtnTVOG+Vg52Vl8OuI5EmKvAtCp34uEDS3a4ExBuN+RI0eYPHkyFy9eBCArK4vx48ezbNkyqlevztChQ9mxYwedOnVi7NixTJ06lYCAACZMmMDy5csZNGgQU6dOZcCAAfTu3Zsvv/yShQsXMm7cOObNm0ezZs34+uuv+eOPP5g2bRoLFixg2bJlWFlZsWnTJqKiohg7diwRERElfi6iJbuci/5rK/emzVMQvXNL0cvu2AR3B8HkZGVy/MBfpR5fZmxMgan5rhzcUerXEISiEFNPCebq6qUL+go2wKa1q9m5aZ3+cWZGOtF7d5kitCK7fv6MvoINEPW/P00YjWAsJcmjaWlpBW45OTkPvcby5cuZNGkSrq55ixgdPXqUWrVq4eXlhYWFBaGhoURGRnL9+nUyMzMJCAgAICwsjMjISHJzc4mKiiIkJKTAdoCdO3fSp08fAHr16sWePXvIyckpsD0oKIiUlBSuXr3639AMJirZ5VxNn3pIUt5Xi5Kko6ZPvSKX9azjx/3jzD1r+z1wzJ1DWzn9xeucWzKazBsXDI7P0v6+hXAUCuxrlN2UgoJwP/nuVFKG3gTB2FzdPaiiqYpSqUSpUlG3fgPq1HsCheLeR3RtP/MehOfk4YmFpSUKhQKFUolnnaJ/FhkqJzubzyaMYFDHJsx6dwiZGelGu5ZQUEnyaPv27QkICNDflixZ8tBrzJw5k8DAe9/Ix8XF6SvcAK6ursTHxz+w3cXFhfj4eBITE9FoNKjV6gLb/3suCwsLqlatSmJi4iPPVVKiu0g517r706SnJnPq4N/Ub9aCNj3Cilw2JHwIsixz7fxpnmzXjXrNWhTYn5MUx43IvHlCdZmpXFu/EN8hnxsUn5VLTYJenMC1g9up6l6LJ0IGFV5IEIxAvnsztIwgGFsVTVW+Xf4H3y+ej22VKrw1ZgL2jo4oFHAp5iwde/ShYdOidQM0FTsHZ0bM/pbtq39CU82B0JeNN2gwcvXP7N+2EVmWid6znfW/fMezr4tBimWhJHl0165dqFQq/XZLS8silc+f7UV/PllGoVA8cnv+//d71NSVsiyjVCofKJO/vaREJbucUygUdHv2Jbo9+5LBZS3UlvR+ecQj90s5mfceyDJSVvFaCzybtsUroEOxygpCaSlOy7RoyRbKyhONmzJn8fcFtr0yapyJoiken0ZP4tPoSaNfJz01pUBlKj012ejXFPKUJI9qNJoCleyicnd3L9CqHB8fj6ur6wPbExIScHV1xdHRkdTUVLRaLRYWFvrjIa8VPCEhAXd3d7RaLenp6djb2+Pm5kZcXBxeXl4FzlVSoruI8EhWLjWpWi+/dVuBa/vnTBqPIJSEJBfvJgiCeencZwDVHJ0B0FStRrd+L5g4osrDFHm0SZMmXLhwgYsXL6LT6Vi/fj3t2rXD09MTKysroqOjAYiIiKBdu3ao1WoCAwPZsGFDge2Q12Ulf0Djn3/+SWBgIGq1mvbt27NmzRoAoqOjsbKyonr16iULHNGSLTyGQqGkZt+3yU64hsrKFrWdk6lDEoRiyxuAY2gLjJGCEQSh2Jzdq7MwYjuxVy7iUaMWNlU0pg6p0jBFHrWysmL27NmMGjWK7Oxs2rdvT/fuebOUzZkzh4kTJ5Kenk7Dhg0ZPHgwAFOmTGHcuHEsWbIEDw8PPv88r6vrqFGjGDduHD179qRq1arMmTMHgEGDBjF58mR69uyJWq3mk08+KVnQd4lKdiVxKHIVe1Z+g01VO3q99REePg2KVE6hUGDtUvrTRkX/tY2ln04BhYJX3/uIJ9t0KvVrCIIgmKPM9FR+mfU+l04eoUHzNgx4ZxoW6qL1Ty0pbW4un0way19bNuDp7cOn3/yMo5NzmVy7NFnb2FKnXkNThyEY0fbt2/X3g4ODWbdu3QPH1K9fn9WrVz+w3dPTk2XLlj2w3d7enq+++uqB7fkV+dImuotUAklxsWxbOoestGSSbl5n46KPTBpPbk42CyePJjEhjsT4OBZMGo1OqzVpTELFJ6bwE8zFzlU/cPbfv8nOTOfwrkgObC75fLxFtWXdajavWUFGehoxp47x81dflNm1hfJP5FHDiJbsSiAn896ARVmWyMpIfeSxsTEnuHLqCCev3eF67HUC/LwIbN8VVy/Dpt7Ljb9E9rXTqNOkB/bptNr75seUycnOQqfVorIQb0fBeOS7/wwtI5Sta5fOc3DPDrRKS5o2bWrqcIwiMy0VBQpk8rrlZaU/OieXVE5ODj/Mm0FK4m3C3xhDWmqyftAgQFpKitGubW7SU5M5uGMTNlWqEtChO8piDMKr7EQeNYyo1VQCLl518WvRibMHtoNCQbsBwx563KVj0fw89U22nbjKrtM3AKhqrWZ096a8Mfdn3L0fnEf7YXJunCVpzUyQJdxQkFvbC5VXI/1+a9sq9B40lHU/5X1l8/RLb2BpbV3CZykIj1ecAThi4GPZunYxhrcH9iInOwsAZwc72oc8beKoSl+b3s9z5K9IMlKTqebsSlBX4z3Hd8N7ce3iOWRZZv/2zSxYtZU1v/zA9SuXsLKypt+Lrxnt2uZEm5vDJ28N5NbVvFUEzxz+hxfenWriqMofkUcNIyrZlYBCoaDP6Oncib2EpY2Gqo4uDz3u9D87QaHg6NU7+m2pWblcSUjmXPSeoleyLxwq+Pjiv1jfV8kGeG74u3QM7QcKBW6eXoY9IUEoBjGFn/k7tG+XvoKNQsH+7ZEVspLtWrM245du5M7Na7h41kJtZbxGhmsXzwF5nwOSTsvZ44f54c8dXIo5R8KdJHzqPWG0a5uTm1cu6ivYkLfisahkG07kUcOIPtnlzD87IxneM5g3erXi0J7thRe4S6FQ4ORZ+5EVbAB3bz9kSUd1e1sU5C3WrlQocNJY4X53NchbF06x9N1nWTykG/9u/v2h57Fw9gI5r5uIAhmV88MHTrrVqCUq2ELZKU4/wsr72WAS3n53B2QrFCCDt695r3JYXCnJybz16iBCuz7FeyOHk5OdbbRr2WrsCvSLrdeoGVZW1tSt/wTWtrYAHNn/F2+GtmZYj5b8vW2j0WIxJUc3D6xsbFEolSiVSmrUNd6KlBWayKMGES3Z5UhOdjYLJ7+DNjcHULBg0mi+3Xqo1PoyN+kUSnZmOjUb7yfy3xhuxSXQxr82YQPC8Q1oA0DkkumkxN1AliV2/fwFtZu1wt6tRoHzWPkFo8nJIOfqCW5JGhzrtSmV+ARBqNgaB7Xi7Y/nsf9/m7C2cyDsxYd3bSvvvlv0Bft3/4Uk6Yj8cy2BLYIJf2WIUa416/vVfPL+G2Smp/HcsNF41KxVYL8kScyfNIrM9HRA5supY2jaugPWNrZGicdUbDV2vPP5D2z9/QdsNBpCX3r0QmyCUFpEJbsc0Wpz7lawAWRycrLR6XSlVslWKBS06PU8LXo9z0uPOCYnMx1Zlu57nPHQ89j6d8bqiY6cP3z4kcuZCkJZEgN2yocOPZ6mbbdQDh8+XGEHQ6empJCfFhUKBampxht8WLNOXRas3PLI/bIkkZ2VSX5zo06bS25OdoWrZAPUqteI1ybNMXUY5ZrIo4YR3UXKEdsqVek9eKj+8TOvvIWllVWZxtD62aEoFHlvm7pBHXDxqlum1xeE4pIoxkplpg5aqJAGvTqUqtWqAeBe3ZOw50y3YqHKwoJnh7ytf9zj+VeoWs3BZPEI5k3kUcNUzGaCCuy54WPo1GcACoUSFw/PMr9+gzbd8WoURHZGGg4eXqKVWig3xIAdwVzUruvLtgNHuH7lMrVq+2Bl4tmVeg8eSquuoeh0WjFORngskUcNIyrZ5ZBr9dJfgdEQVeydqGIvllgXypfiLIpQiT8bBCOrUkWDXwPzWbHQ2b26qUMQygGRRw0jKtmCIFQKogVGEAShZEQeNYyoZAulIvnWNS79uxd7Dy9qNQk2dTiC8AAJw/sGVua+hELlduHkEc4dO4hf4yBqN/A3dTiCmRB51DCiki2UWOrtW6ya/Cq52ZkAtHlhNI06h5k4KkEQBKE4Th36m8/eeRlZBoVSwXvzfsKvSaCpwxKEckfMLiKU2PWTh/QVbIAL0TtNF4wgPEL+15yG3gShsvl397a7s0jJKFBweF/RFz4TKjaRRw1jlpVsnU7HoEGDGDdunH7brl27CA0NpWnTpoSEhLBjx44CZb755hvatWtH06ZNGTRoEBcuXNDvy8jIYPz48bRo0YKAgADee+890tPTy+z5VHTOXj55K7Tdvbl4l2yVtvTkRH6Y+BoznmtNxOcT0Wm1pRSpUJkZukpZcQb4CIK5uXr6KHNf78WMge34e/1vRSpTq15DJEmXtxS7pKOWb+VYel0onMijhjHLSvbChQuJjo7WP7506RIjRoxg1KhRREdHM2LECEaPHs2tW7cAWLNmDcuWLeO7777jwIEDNGzYkJEjR+r/epo2bRo3btwgMjKSLVu2cOPGDebMERPSlxbnWn6EjJqJT1BHAnq/SPNnXivR+Xav+o5rZ4+hy83hxN4tHNtVMZf5FcqWaIHJM3v2bH0DxqlTpwgLC6Nbt25MmDCB3NxcAGJjYwkPD6d79+4MGzaMtLQ0AFJSUhgyZAghISGEh4cTFxdnsuchFM2a+VNIuX2LnMwMNn//GYlxsYWWadXtacJHTyagfTcGvzuV5k/1LINIhfJA5FHDmF0le//+/WzZsoWuXbvqt61Zs4bAwEA6d+6MhYUFPXr0ICgoiBUrVgDw+++/M3DgQHx9fbGysuLdd98lNjaWAwcOkJmZyfr16xk5ciT29vY4OTkxZswYIiIiyMzMfFQYgoFqNW1Flzc+JKjvK6jUlgX26bIzuf73Rq4f2IQuJ7vQc+Vk3v8tg4LsTBN+65BwHs7+DxKvmC4GoVTIxbxVJPv372fNmjX6x2PHjmXixIlERkYCsHz5cgCmTp3KgAED2Lx5M/7+/ixcuBCAefPm0axZMzZt2kT//v2ZNm1a2T8JwSA5WZkFKjm5WYV/7ikUCjr1HcjwqfNo33uAUddDkCSJ6O0b2LH6J1LuJBjtOmUt+dp5LuxcTc6ti6YOpVSJPGoYs6pk3759m4kTJ/LZZ59hY2Oj3x4TE4Ofn1+BY+vWrcvp06cful+tVuPt7c3p06e5fPkyubm5Bfb7+PiQlZXFpUuXjPuEBGRZ5vhP0zi37ivOrV3MsZ8K/1Bu2TscK1sNAE7VvWjcvoexw3y4myfhr/lwfB3s/BxuV6xkWdlIslysW0WRlJTE3LlzGTZsGADXr18nMzOTgIAAAMLCwoiMjCQ3N5eoqChCQkIKbAfYuXMnffr0AaBXr17s2bOHnJwcEzwboai6DB6hX6W3cfseuNSsY+KIClqz5FN+mjWONV/P4dO3BpCdmWHqkEos+eo59n4xmrMbf+TO/77n1vH9pg6p1FT2PGoos5ldRJIkxo4dy8svv0z9+gX79KanpxeodANYW1uTkZFR6P78rzltbW31+/KPNbRftk6nK9L+wo6rLHQ6HeRmkXLllH5b0oWj5GSmo7J89ApnTp61eWvRWlJu38LBrQYqCwuTvKaK2KMoFEoUspTXryz2OLJ98VdDE++Pggx5PcRrVnKTJ0/m7bff5saNGwDExcXh6uqq3+/i4kJ8fDyJiYloNBrUanWB7f8tY2FhQdWqVUlMTMTNza3IcRjy8xY/95Jr1LY7tRs3JycrE3vX6khS3oRq5vIa/7trc94dWSY5IY4rZ09Sp1Ezk8ZUUjdPHECWJUAGhYJbJ/7GrZF5TG1r6p93ZWM2lewlS5ZgaWnJoEGDHthnY2NDVlZWgW1ZWVlUqVKl0P35levMzEz98fndRDQajUExHjt2rFSPqxTUVmBdFTkzFZCRVJYcOXYCpUpVpOLX4pOKddns1EROrPuGjNs3ca0XgG+X51EoDfvixikVvGUJGVAgcyEpl6TDh4sVz/3E+6Ogsno9KvNKZStXrsTDw4Pg4GAiIiKAvIaN+7sByLKMQqHQ/3+/R3UXkGUZpYG/V4b8vMXvSum6fCP+gW3Hjh0j+dIJLm1fDpKOmu2ewdEv4IHjYg7u5p8/f0WlUtOm/2t41mtcKjFVc69JauJtAJQWam4lppBSCnnWlLJzVHeThwJkmVRsOFzOn1O+ypxHi8NsKtlr164lLi6OwMC8uTjzK83btm0jPDycEydOFDg+JiaGRo0aAeDr68u5c+fo2LEjALm5uVy6dAk/Pz9q166NWq0mJiaGJk2aAHD+/Hl9lxJD+Pv7o3pM5VCn03Hs2LFCj6ss8l8PhZsvqWcOIMsyyRnp1JJSqB3Q0ajX3vrNDDISYpEliVsnD9CsQwi+LToZdhK5CdJFD7hzEdmlHt61mpcoJvH+KMiQ1yP/2JKozCuVbdy4kfj4ePr06UNycjIZGRkoFAp9CzVAQkICrq6uODo6kpqailarxcLCgvj4eH3rtaurKwkJCbi7u6PVaklPT8fe3t6gWAz5eYvfFePJf40bNWzIb99/gC4r75vhyzuW07b3QNTW974dzkxLYdnEV5AkiVwy2bvqW6b/vqtU+mrX853Pll+/ITXpNm1Dn6NW/Qqw8E3TpsR6uHDrZBQZFhpahL2Kxd1vhkytpLm0MufR4jCbSvbmzZsLPM4f/T5r1izOnz/P0qVL2bhxI127dmXLli38888/TJw4EYBnnnmGBQsW0K5dO2rXrs3cuXNxdnYmMDAQtVpNSEgIc+bM4YsvvgBgzpw59OrVC2vrR3dZeBiVSlWkhF/U4yoLCQW303Lufn0GUm620V8fbXZWgdEWutyc4l3Ttz3QvtTiAvH++K+yej0qcwvM0qVL9fcjIiL4559/mDlzJr169SI6OprAwEAiIiJo164darWawMBANmzYQJ8+ffTbAdq3b09ERARvvPEGf/75pz7HGsKQn7f4XTE+pVKJLvfegHRZpwNZKvC6S5JO380EIDcnC5VKVSqVbI2dPWHDxpb4POamZlBnqj/ZkcOHD2OhVleY93FlzqPFYVYDHx/Fx8eHL7/8kiVLlhAUFMSiRYtYsGABtWvXBqBfv3689NJLvPnmm7Rs2ZKTJ0+yZMkSffKfMmUK3t7ehIaG0r17d2rUqMHkyZNN+ZQqlYZdB2Bxt1XEsaYPtYOM24oNENR7kL4lxsXbD98Wxr+mYN5kZCQDb3IFHxc/Z84cZs6cSffu3cnOzmbw4MFAXs5ctWoVPXr04NChQ4wePRqAUaNGcfToUXr27Mny5ctFHq0AlCoVQc8M1T9u2vMFrDV2BY6xc3CmU78X7z5S0Oe1d4w644hgvkQeNYzZtGT/16xZswo8btu2LW3btn3osQqFgldeeYVXXnnlofs1Gg3Tpk0T002ZiJOXLwM+XUlGYgJVXaoXuT92SbjVrs9rC/4gPTGBam6eKJUVoxVBKD7RApMnLCyMsLAwAOrXr8/q1asfOMbT05Nly5Y9sN3e3p6vvvrK6DEKZatxtwHUbdEZSdKhcXR96DFPDxlD+6dfQKW2wM7BuYwjFMyFyKOGMdtKtlCxqK1sqOZes0yvaWlti6VH8WcDEYwr4ep5or7/iH3pyTwZ8hytnh1q1NYx0ZdQEB7hzmlsL6wFWQJdD3Bp8tDDHFzdyzgwwdyIPGqYctFdRBCEimfXT3PJSrmNTptL1Ppl3Dx/0tQhlYq0tDRCQ0O5du2aqUMRhMLJMsREgDYTdNlwYW3e/4IglJioZAtGkRR/k12rf+TSkb8LDJgRhHy5WZkFvkfUZmc95uiSy/+a09CbIY4cOUJ4eDgXL4qFiwTjkySJqO0bifztW27fvF7Ms8gga+97KIEs5lIWHq4s8mhFIirZQqnLSE1h3sjn2fzjAv5e9Q2RPy00dUiCGQruPwSFKq/HmnfTYDzrP/wr6tJi6GCd/Jshli9fzqRJkwos8iIIxrLhxy/5fvpY1n43jxnD+pOadMfwkyiU4NXl3mPPtmBh++jjhUqtLPJoRSL6ZAul7tq5E6QnJ+ofH9v7P3q9+rYJIxLMUa3GLWg5dDq+tWvh4F7D6LMVlGTATlpaWoEpuCwtLbG0tHzg+JkzZ5YkREEwyL+7twJ5fV4zUpO5ePIIjVsVYyYlj2Bw8gcksLQr9HCh8hIDHw0jWrIrgSunjzC6ZyADg30Z3qM5N64Y96tsN686WKgt81ZYVCjwqgiLCwhGYWFlQzXX6mUyHVj+gB1Db5A3P3RAQID+tmTJEqPHK1RcyYl3eOP53nR4ogbvDx1EdlZmsc5T54mmKBQKFEolKgs11Wv7PnDMkai/6d2qCZ38vfn1u8WPPpmlRlSwhUKVJI9WRqIluxL4edZ44u4kA5CcmMh3sz/ggy9/Mdr1qjm7MWz2t+z783eytDJhb4432rUEoahK0gKza9euB1qyBaG4fv12EScPH0KSdPy963+sW/Ez/V983eDzPPvWeKo5uXD7VixtevbD2aPGA8dMHzeaxNvxyLLMotkf0aFrT6rXFLMuCcUjWrINIyrZlUDufwaU5RSz1SRfWkoyuzasxtLSivY9n8HyIStn1qrfmBq+DTl8+DCW9y3PKwjlkUajqTArtgmml52ViZVaiVqpJFsrF7sl29LahtCXRzz2mJzsrAItidnZJcv/giAUneguUgmEvfk+VazyVr9UWVgwcETxW5YlnY5pwwfy64JZLJ3zIfMmPj7BC4K5kGS5WDdBKG1PNGyIs8YKOxtLXO2seaKR8brUvTluiv4PxJ79nsfbx89o1xIqPpFHDSNasisB/zbdmP/n38RejKF6HT9sqmiKfa7bcTe5euGs/vGR/buQJAml0rC/12RZFsvyCmVKvnsztExxbN++vZglhcrg8pnjKJVKJElCoVRy4dRRnmxdtAGLhubOLr360qJtR7IyM3B1r17ckAUBKNs8WhGIluxKwkZjh4//kyWqYAM4OLtg7+SCUqlCqVThXa+hQRXsy2eOM3ngU7zb60k2/LigRLEIgiFkijFgp1J/PAjG4vNEE33jhCxJ+DRoXKRym35cyPu9A/loUFeunj1R5OvZVbMXFWyhVIg8ahjRki0YxEJtyeTFv7Hh129RW1rR58VhBpX/ff5HpNxJQJYltvz6NU3adKGGT30jRSsI94gBO4K56Nj7WSRJx7lj/9KkZTuaFaEV+1rMKbYt/waAlNvxrFrwMW8v+M3YoQpCASKPGkZUsgWDudesxavvTytW2dzsLGRZKvBYEMpCcaaSqsxTTwnGo1Ao6Nx3IJ37DixyGW1ujv6+LEvk5ojcKZQ9kUcNI7qLCGWqz+tjsFDnTX/WrF03atUv2tekglBSkly8myCYA696/jRp2xXI+0ZRLPAlmILIo4YRLdlCmWrYoh3TV+wiKyONas5uZjH4Ub77/ZfCwMGbxolFQqEwfRyCIJgXpVLJoPGf0Pv1MVhX0WBtW6VUz5/f2mgOOflhzD0+QXgYUckWypx1FQ3WJRyAWVpuxBxn/dwJZKUlEdjrBVr1H2KSOCRtDhdWfUZKzCFs3Lyp+/wE1BoHk8RScRVnAE4lboIRzI5CocDexa3Uz3vt39388/OnyJJEs2ffok5w91K/RklkXPiX+E2LkLW5OLYPx65pF1OHVImJPGoI0WQmVGr/+/5TMlLuIOl0/LP2R+KvxJgkjttHdpJy7iDIMpm3LnNzT4RJ4qjI8gfsGHoThIpMliQOLPsEbXYmutxsDv42l9ysDFOHVUD85q+QsjOQdbnc3v4juowUU4dUaYk8ahjRki1UarrcnAJ/ZOvuG1xUlmRtLqAgPxhJa5o4KjIxYEcQHkZG1mnvPZIkZElnwngeJOty739kdvFVJmWRR9955x1OnDiB9d3VpN966y1q1KjBxIkTSU9PJyAggKlTp6JWq4mNjWXs2LHcvn0bb29v5syZg0ajISUlhTFjxnD16lUcHR2ZO3curq6u5OTkMHHiRI4fP461tTVz5szBx8fHoPgMIVqyhUqt7cC3UFnk/a1Zr1VX3Oo0MEkcjk06YOPqBYBFFTvcgvuYJI6KTAzYEYQHKZQqmoQNhbt9nRv2HIylbVUTR1WQU4fB+viqBYViIbrSmUxZ5NHjx4+zYsUK1q5dy9q1a+nSpQtjx45l4sSJREZGArB8+XIApk6dyoABA9i8eTP+/v4sXLgQgHnz5tGsWTM2bdpE//79mTYtb0a0ZcuWYWVlxaZNm5gwYQJjx44tvRfnIURLtmD2JJ0O5d1lgUtbnWatGbp4AzlZGWgcXIxyjaKwsK5C/dc/ITf1DhYae5QqtcliqajyViozsAXGOKEIAmDc3GYI3/ZP4xXYCVmSsK5qb+pwHlDVvwO2vkEgaVHZVjN1OJWasfNoUlISd+7c4d133yUuLo5u3brRt29fMjMzCQgIACAsLIx58+bx3HPPERUVpa9Yh4WFMXDgQMaNG8fOnTv5+eefAejVqxdTp04lJyeHnTt3MnLkSACCgoJISUnh6tWr1KxZ06DnVFSiki2YrZysLOZOeIsj+3fh5VufcXO/x96p9CvCljZVsLQp3ZH6xaFQqrCsZrqKfkUnFlEQzEV6ciLLZ4zmxvlT1PZvTv/3P8XS2sakMVlVsTPp9QujsjZ9jhZKlkfT0tJQ3fdHpaWlJZaWlgWOTUhIIDg4mMmTJ6PRaBg+fDgqlQpXV1f9MS4uLsTHx5OYmIhGo0GtVhfYDhAXF6cvY2FhQdWqVUlMTCyw/f4yxqpki+4igtnatWE1R/bvAuDa+XOs/XGxiSMSBEEouf1rl3Hz4hkALh6P4t+ta0wckSAYX/v27QkICNDflixZ8sAxdevWZcGCBbi4uGBjY8MLL7zAvn37CkzdKMsyCoVC///9HjXFoyzLKJXKB8rkbzcW0ZJqZY12AAAgAElEQVQtmC1tbo7+FynvcW4hJQTh0cTAR8Fc5A2wzvugVwA6rchtQvlQkjy6a9euB1qy/+vYsWPExcXx1FNPAaDT5Q1yzW+hhrzWbldXVxwdHUlNTUWr1WJhYUF8fLy+ldrV1ZWEhATc3d3RarWkp6djb2+Pm5sbcXFxeHl5FTiXsYiWbMFstev5DDXr1gOgmqMTPQe+ZuKIhPJMDHwUzEWL0IFUdXAGwMnTm6adxUBnoXwoSR7VaDQFbg+rZEuSxPTp00lNTSU3N5fly5czYMAArKysiI6OBiAiIoJ27dqhVqsJDAxkw4YNBbZDXqt5RETeVLh//vkngYGBqNVq2rdvz5o1ed8cRUdHY2VlRfXq1Y32eomWbMFsValqx4wf1pKYcItqDk765dgFoThES7ZgLuxdq/Pml2tIT76Nxt7ZLAY/CkJRGDuPNmnShMGDB/Pss8+i0+no2rUrvXr1om7duvop/Bo2bMjgwYMBmDJlCuPGjWPJkiV4eHjw+eefAzBq1CjGjRtHz549qVq1KnPmzAFg0KBBTJ48mZ49e6JWq/nkk08Mei6GEpVswawplUqcXD1MHYZQAcgYPluIqGILxqKysMDOqfRXbxQEYyqLPPrSSy/x0ksvFdhWv359Vq9e/cCxnp6eLFu27IHt9vb2fPXVVw9st7KyYvbs2QZGVHyiki0IQqUgWrIFQRBKRuRRw4g+2YIgCIIgCIJQykRLtiAIlUJxBjKKgY+CIAj3iDxqGFHJrkQkSUKWJP0y4oJQmYivOQVzo83NxUItVncVyg+RRw0juotUEof37+K1Lk/yYodGrPvpwQngBaGik4t5E4TSdichnlee7kynRl6MHPQMGenppg5JEIpE5FHDiEp2JfHNjAlkZWYg6XQsXzyHhJuxpg5JEMpUfguMoTdBKG2/fbeIC2dOA3Akaj/rf39wdgRBMEcijxpG9BuooHRaLdvXrSAxPo62Pfqi1Wrhvje6JOkeWVaWZQ7/Fcm182fwD+6Ad4MmZRGyIBiXXOBXoMhlBKG0aXNzke97c+m0j87H97tx5RLb/1yNo4srXZ5+TnQ1EcqeyKMGEZXsCmrZFzPYsmoZSqWSrat/5vm33mfppx+i0+bSM/w1XKvXfGTZfRtX8vv8aSiUSravWsq7C5ZTw6d+GUYvCKVPkmUkAz8dDD1eEIqihrcPOp0OpUKBTpLw8vEttExKUiJjBvchIy0VSZK4HHOWYeOnlUG0gnCPyKOGEZXsCurwvp1A3mDH9NQUXNw9+WZLNNqcHDTV7B9b9vTB/aBQIEsSMhBzNFpUsgVBEErJ6RNH0aEgVyuhVCo5efQwbTp1fWyZi2dOkpaSrH98cO8OY4cpCEIJiT7ZFVSDJ1ugUChQqlRY2dhS08cPaxvbQivYAHUaNQNZRqlUoVAoqC26iwgVgCwX7yYIpa1pYEsknYRSpUKSJBoHNC+0TK26fljbVkGpysvLjQJalkGkglCQyKOGES3ZFdTLYz7Eo6Y3d+Jv0bF3f+ydXIpctv3TL2BlbcO182do3KoTter7GzFSQSgb8t1/hpYRhNLWI+xZFEolxw5FEdy+Ey3bdii0jL2TC7O/X8WWNctxdHGld/irxg9UEP5D5FHDiEp2BWVpZUXvwUOLVVapVNKqR/9SjkgQTKs4LSqVuQVGMB6FQkGPvv3p0dewPOvt14Ah7081UlSCUDiRRw0jKtmCIFQKEsUYsFOJW2AEQRD+S+RRw4hKtiAIlYJogREEQSgZkUcNY1YDH0+fPs3LL79M8+bNad26Ne+99x537twB4MiRI/Tv359mzZrRqVMnVq5cWaDsmjVr6NKlC02bNiUsLIx///1Xv0+n0zF79mxatWpFs2bNGD58OHFxcWX63ARBEARBEITKw2wq2VlZWbz22ms0a9aMPXv28Oeff5KUlMSECRNITk5myJAhPP3000RFRTF9+nRmzpzJ0aNHAThw4ADTpk1j1qxZREVF0bt3b4YPH05mZiYAixcvZu/evaxevZrdu3djbW3NBx98YMqnKwhCGZOL+a+iWLp0KT179iQ0NJTx48eTk5PDqVOnCAsLo1u3bkyYMIHc3FwAYmNjCQ8Pp3v37gwbNoy0tDQAUlJSGDJkCCEhIYSHh4vGCkGoZCp7HjWU2VSyY2NjqV+/Pm+++SaWlpY4ODgwYMAAoqKi2LJlC/b29oSHh2NhYUFwcDChoaH88ssvAKxcuZKePXsSEBCAWq3mpZdewsHBgY0bN+r3v/7663h4eKDRaJg4cSJ//fUXV69eNeVTFiq47NRELm77lcs7V6LNyjB1OJVeZZ566ujRo0RERLBy5UrWrVuHVqvl119/ZezYsUycOJHIyEgAli9fDsDUqVMZMGAAmzdvxt/fn4ULFwIwb948mjVrxqZNm+jfvz/TponFUISSkbS53DrwJ9f/9wtZd26YOhyhEJU5jxaH2VSy69Spw7fffotKpdJvi4yMpGHDhpw7dw4/P78Cx9etW5fTp08DEBMT88j9qamp3Lx5s8B+Z2dnqlWrxpkzZ4z4jITKTNLpOPz1eC7v+J2LW3/m2LKPTR1SpZe/Upmht4rAzs6OSZMmYWtri0KhoH79+pw5c4bMzEwCAgIACAsLIzIyktzcXKKioggJCSmwHWDnzp306dMHgF69erFnzx5ycnJM86SECuHKhiVci1zKzX1/cPq7cWiz0k0dkvAYlTmPFodZDnyUZZl58+axY8cOfv75Z3766SdsbGwKHGNtbU1GRl7rYHp6+iP3p6fn/cLa2to+sD9/X1HpdLoi7S/suMqiMr8eWUnx/2/vzqOavtL/gb8TQFlEERVscWtFYL4KbojgghRFrMLQKlRrq5WvghUrllEQx10Hjo7buOBSGZdRp60KloJW2znWalVwUAvWUYv+pKCMgCDKviT394clX1NtIRj4xOT9OidHPxv3yZPk8nBzb4LKojzV9qM7P6Lul7fiDTEfz6PJ80MbOTPkBTs9evRAjx49AABFRUU4ePAgJk6ciOzsbNU5nTp1QmFhIR4+fIg2bdrAxMREbT8AFBQUwMbGBgBgbGwMS0tLPHz4ELa2to2ORZPHm6+V5qMrOX50+5f1U0IJRWUZyv97B226/UHSmLRFV3L8tBeNxZD70abQuSK7rKwMCxcuxLVr13DgwAE4OjrCzMwMpaWlaudVVVXBwsICAGBmZoaqqqpnjrdv315VfNfPz37e9Y119epVrZ5nKAwxH0KpgMzcCqLyESAAeYcu+PHaNQCGmY/f01L5EEJAaNjba3q+rrt79y5mzpyJoKAguLq64rvvvlMdE0JAJpOp/n3ar7efvkYu1+wNUU0eb75Wmp/kOW7XBSgrAWQywKgVbt0vAYp/kDYmLZM8x1rEflQzOlVk5+TkICQkBK+++iqOHDkCa2trAICDgwPOnTundu6tW7fQq1cvAECvXr2QlZX1zHFPT0+0a9cOtra2alNKCgsLUVJS8swUk4Y4OzurTWf5NYVCgatXrzZ4nqEw9HxU91yLvNTjkBub4NUh/pC3MjPofPyaJs+P+nNfhPjlpuk1+uL69esIDQ1FaGgopkyZgnv37qlGqAHgwYMHsLGxgbW1NUpLS1FXVwdjY2MUFhaqRq9tbGzw4MEDdO7cGXV1dSgvL4eVlZVGcWjyePO10nx0JcfK3v+Dwn8fR135I3ToPxKmHbtIFou26UqOn/aifamh96Oa0pki+9GjR/jggw/g7u6OmJgYtdERHx8frF27Fnv37sV7772HS5cuITk5Gdu2bQMABAYGYvbs2XjzzTcxcOBAHDx4EEVFRfDx8QHwZE7h9u3b4ezsjPbt2yM2NhZubm7o1q2bRjEaGRk16oXS2PP0RXV1NbZt24b8/HxMnz5d9cdPPUPLRz1za1vYjw1Wbde/TWeo+fgtzEfzKy4uxowZM7Bs2TKMHj0aAGBnZ4fWrVsjPT0drq6uSExMhKenJ0xMTODq6opjx44hICBAtR8ARowYgcTERISFhSElJQWurq6qaSWN1dDj/VNGOi6d/RdEK3P07duXz41mJvXrz8jIDK8OnyBZ+y1B6hyTdHSmyE5MTEReXh6++uornDhxQu3YlStXsHv3bsTExGDz5s2wtrbG4sWL4e7uDgDw8PDAsmXLsHz5cuTn58Pe3h67du1SjbDMnj0bdXV1eO+991BeXo7Bgwfjb3/7W4vfR3314YcfYt++fZDL5di1axeysrJU70IQ6YqmLMDRlwU7+/btQ1lZGeLi4hAXFwcA8PLywrp167Bo0SKUl5ejd+/emDp1KgBg2bJliI6Oxs6dO/HKK69gw4YNAIC5c+ciOjoa48aNg6WlJdatW6fVOLNv/ojVc6dCBhmUSgVsOlhj1IT3tdoGETWdIfejTaEzRXZwcDCCg4N/87izs7Pq46WeJyAgQLXq/ddMTEwwf/58zJ8//4XjpGd9/fXXEEJAoVCguLgYP/74o2rki0hXGPKCnYiICERERDz3WEJCwjP77OzssH///mf2W1lZYceOHVqPr97NjHQI5S9fwiyT4caVNBbZRDrEkPvRptCZj/Cjl9eoUaMgk8lgZGQEKysr9OnTR+qQiJ71y4IdTW4G/dtBAr2cB0Iml0MuNwKEgGO/QVKHRERPYz+qEZ0ZyaaX186dO9GnTx/k5+djxowZnCpCOokjMLrv9T84I2rjHlw68w1EKwu88dZkqUMioqewH9UMi+yXWEVZKY5/vg/VVZUYEzQFHWw6SxKHqakpIiMjJWmbqLGa8vW+hvx1wFJx6j8YvVxc8cMPP/zmRwe+bB4WF+Hg7k8AAO/9byjaW3eQOCKipmE/qhkW2S+xNfNn4tqVi5BBhrMnv8TWxFMwNtZspT8RETUfIQSmT3wLt25eBwCcOnkcCV+f0Zs/IIjot3FOthbV1dWhrKysRdoSQuDalYsQSiWUSgUK/3sPRfn3W6RtXVf/Gb9ET1OKpt2oZSmVShT89x4UCv14DZeVluKn69egVCqhVCrx0/VrKC8rbfhCIh3EflQzLLK1JD09HXZ2dvDy8sLkyZOb/WtUZTIZeg8YDJlMDrlcDptXuqCDrTTTRXSFEAIhISFo27YtOnbsiLNnz0odEukQTRfrNOWbzejFPHpYDBf7bni1a3e8OfIN/HDxvNQhvbA2lpZw+ENvyOVP+mqHP/SGRRtLqcMiahL2o5rhdBEtiYqKwsOHDwEAhw4dQnBwMMaMGdOsbS5Yu+PJnOzqKowJfN/gp4pcuHAB8fHxAIDHjx9j7ty5uHz5ssRRka7ggh3dtyl2Ga7duQcAKCmvxJ/nz8XJcy/3a1gmk+Hvn3+hNiebU0XoZcV+VDMssrVEik7TvI0lAqd/1OLt6qqnHwOZTMZfZKSGC3Z039OvWX3KfHvrDvho/kKpwyB6YexHNcPpIlry17/+VfXRdZMmTVJ9pTu1HHd3d8ycORMA0LZtW2zatEniiEiXcC6h7vt40Uq42HcFAFi3McPqDZsljoiInsZ+VDMcydaSgQMHIi8vD2lpafDw8ICRkZHUIRkcmUyGHTt2YP369TA1NeVjQGqaMjfQkOcSSsGynRUysnLwIP+/+H8/58BloKvUIRHRU9iPaoYj2Vokl8thZmYmdRgGz8LCggU20UusfUcbGBlxDIiIXm7sxYjIIHDBDhHRi2E/qhkW2URkEJ78ctD0bc5mCoaI6CXEflQzLLKJyCAof7lpeg0RET3BflQzLLKJyCBwwQ4R0YthP6oZFtlEZBAEmjCXsFkiISJ6ObEf1Qw/XYSIiIiISMtYZBORQah/m1PTmyaSk5MxduxYjB49GgcOHGime0JEJI2W6Ef1CaeLEJFBENB8AY4mvxry8/OxYcMGJCYmonXr1pg0aRIGDRoER0dHDVslItJNzd2P6huOZBORQWjuEZjz58/D3d0d7du3h7m5OXx9fXHy5MlmvEdERC2LI9ma4Uh2I9Q/QRQKxe+eV3+8ofMMBfOhjvlQp0k+6s95kc7a3NxC4wU75uYWAICysjK1bxFt1aoVWrVqpXZuQUEBbGxsVNs2NjbIzMxscrz6prH96NPn8LXSfJjj5qeLOX7RvvRF+lFDxCK7EZTKJ2+OXL16tVHnN/Y8Q8F8qGM+1GmSj/rXoiZkMhmMjY1x/Phxja8FgJqaGgwdOhS1tbWqfR999BHmzJnzTGwymUy1LYRQ2zZ0mvajmp5LTcMcNz9dzLGmfemL9qPGxsYG2R+yyG4EY2NjODs7Qy6XG+SThEhqQggolUoYG2veZcnlcjg7Ozd55Ka2thapqalq+349ig0AnTt3Rnp6umq7sLBQbWTb0LEfJZJeU/vSF+1HZTIZ5HLDm6HMIrsR5HL5c3+pEtHL4UU696enifyeIUOGYMuWLSgqKoKZmRlOnDiBmJiYJrerb9iPEr3cDLFIflEssomItMDW1hYRERGYOnUq6urqEBgYCBcXF6nDIiIiiciEIS/7JCIiIiJqBhz7JyIiIiLSMhbZRERERERaxiKbiIiIiEjLWGQTEREREWkZi2wiIiIiIi1jka0lRUVFCAsLg6urKwYPHoyYmBjU1dVJHVaTFBcXw8fHB2lpaap9GRkZCAoKQv/+/eHt7Y3Dhw+rXXP06FH4+PigX79+GD9+PK5cuaI6plAosGbNGgwZMgT9+/fHrFmzUFBQoDreUO4aaru53LhxA8HBwXBzc8PQoUMRFRWF4uLiRsWkj/m4cOECgoKCMGDAAAwdOhSrVq1CVVVVo2LSx3xQ80hOTsbYsWMxevRoHDhwQOpw9NKePXswbtw4+Pv7Y+HChaipqZE6JL21Zs0aREdHSx0GSUWQVrz//vti3rx5oqKiQuTk5Ihx48aJXbt2SR2WxtLT08WoUaOEg4ODSE1NFUIIUVJSItzc3MSBAwdEbW2tOH/+vOjfv7/IyMgQQgiRmpoq+vfvL9LT00VNTY3Ys2ePGDx4sKioqBBCCLFlyxbh7+8v8vLyRGlpqfj4449FSEiIqs3fy11DbTeXyspKMXToULFp0yZRXV0tiouLRUhIiJg5c6ZB5qOoqEg4OzuLhIQEoVAoRH5+vvDz8xObNm0yyHxQ87h//77w8vISxcXFory8XPj7+4sbN25IHZZeycjIEH5+fqK8vFwolUoxf/58sWfPHqnD0kvnz58XgwcPFgsWLJA6FJIIi2wtyM7OFg4ODuL+/fuqfceOHRNeXl4SRqW5xMRE4eXlJY4dO6ZWZB86dEiMHj1a7dylS5eKqKgoIYQQ8+bNE4sXL1Y7PmbMGHHkyBEhhBCenp7iyy+/VB0rLCwUjo6OIicnp8HcNdR2c7l9+7aYPn26qKurU+3717/+JQYMGGCQ+RBCiNLSUiGEEEqlUty8eVP4+PiI/fv3G2w+SPsSExNFdHS0anvr1q1i06ZNEkakf+7cuSPS0tJU2/Hx8SImJkbCiPTTw4cPRVBQkNizZw+LbAPG6SJakJWVBSsrK9ja2qr29ezZE3l5eXj8+LGEkWlm2LBh+OabbzB27Fi1/VlZWXBwcFDbZ29vjxs3bgAAbt269ZvHS0tLcf/+fbXjHTt2RLt27XDz5s0Gc9dQ283l9ddfR3x8vNpXap88eRK9e/c2yHwAQJs2bQAAI0aMgL+/Pzp16oTx48cbbD5I+woKCmBjY6PatrGxQWFhoYQR6Z8ePXrAzc0NwJOpWAcPHoS3t7fEUemfpUuXIiIiAm3btpU6FJIQi2wtKC8vh5mZmdq++u2KigopQmqSTp06wdjY+Jn9z7t/pqamqvv2e8fLy8sBAObm5s8cLy8vbzB3DbXdEoQQ2LhxI7799lssWrTI4PPx9ddf48yZM5DL5QgPDzf4fJD2KJVKyGQy1bYQQm2btOfu3buYOnUqgoKC4O7uLnU4euXw4cN45ZVX4OHhIXUoJDEW2Vpgbm6OyspKtX312xYWFlKEpFVmZmaqBW71qqqqVPft947XF0C/zk/98YZy11Dbza2srAzh4eFITk7GgQMH4OjoaND5AJ4Usba2toiMjMTZs2cNPh+kPZ07d1YbuS4sLFQb2SbtuH79Ot59911MmjQJs2bNkjocvXP8+HGcO3cOAQEB2Lx5M06dOoW//OUvUodFEmCRrQW9evVCSUkJHjx4oNp3+/ZtdO7cGZaWlhJGph0ODg7IyspS23fr1i306tULwJP7/1vH27VrB1tbW9y6dUt1rLCwECUlJXBwcGgwdw213ZxycnIwYcIElJWV4ciRI3B0dARgmPm4fPkyxowZo/YpBDU1NTAxMYG9vb3B5YOax5AhQ3DhwgUUFRWhoqICJ06cgKenp9Rh6ZXi4mLMmDEDS5YswZQpU6QORy/t2bMHKSkpSEpKQnh4OLy9vbF48WKpwyIJsMjWgh49emDgwIGIjY1FWVkZcnNzsW3bNgQGBkodmlb4+PjgwYMH2Lt3L2pra5Gamork5GRMmDABABAYGIjk5GSkpqaitrYWe/fuRVFREXx8fAAA48ePx/bt25Gbm4uysjLExsbCzc0N3bp1azB3DbXdXB49eoQPPvgAAwYMwN///ndYW1sbdD4cHR1RVVWF9evXo6amBvfu3cOaNWsQGBgIX19fg8sHNQ9bW1tERERg6tSpePvtt/HHP/4RLi4uUoelV/bt24eysjLExcUhICAAAQEB2Lhxo9RhEeknqVde6ovCwkIxZ84c4ebmJtzd3cXq1avVPpniZfP0p4sIIURmZqaYOHGi6N+/vxg5cqRISEhQO/+LL74Qvr6+ol+/fiIwMFD88MMPqmM1NTVi7dq1Yvjw4WLAgAFi1qxZ4sGDB6rjDeWuobabw+7du4WDg4Po27ev6Nevn9qtMTHpWz6EECIrK0sEBwcLV1dX8cYbb4gNGzaI6urqRsWkj/kgIiL6PTIhhJC60CciIiIi0iecLkJEREREpGUssomIiIiItIxFNhERERGRlrHIJiIiIiLSMhbZRERERERaxiKbiIhIj9y5cwdOTk44evRog+ceOnQIKSkpLRDV//H29sbdu3dbtE0iKbDIJiIi0iMJCQnw9fXFZ5991uC5ly9fVvsmVyLSHmOpAyB6WkVFBTZu3IjTp0/DzMwMpqamCAkJUX074NMcHR1x8+bNZotl4cKF+Oijj2BnZ9dsbRARaZNCoUBSUhJ2796NadOm4caNG3BycoK3tzf+8Y9/oEuXLkhLS8PWrVsRGhqKU6dOITU1FR06dECfPn2waNEi3Lt3D8bGxoiIiICnpydKS0sRFRWFnJwcdO3aFffv38fWrVtx8eJFHD16FCUlJRg2bBjefvttrFq1CpWVlaqvb588eTJKSkoQGRmJ+/fvo2fPnqiurgYAKJVKrF+/HufPn0ddXR3GjBmD2bNnS5xBIu1hkU06JSwsDD179sSxY8fQqlUr/PzzzwgNDUVtbS3Gjh3borGkpaWxwyeil8qZM2dgZWWFXr16wdfXF59++ilWrFjx3HOHDx8Ob29vuLm5YcSIEfj444/h6uqKHTt2IDc3F++++y6++OILxMfHo3v37ti+fTsyMzMxceJE1c/Iy8vDiRMnYGJigpiYGHz44YcYOnQo7t27Bz8/P0yePBmbN2+Gk5MTdu3ahfT0dHz11VcAnoy419bW4ujRo6itrUVYWBhOnz4NLy+vlkgVUbNjkU0649///jdycnKwe/duyOVPZjJ1794df/7znxEbGwsXFxdERkaioqICffv2VV1XWVmJpUuX4vr165DJZJg+fTreeustJCYm4ttvv8Xjx4+Rk5ODqVOnIi8vD6mpqWjXrh3i4+NhamqKlJQU7N69GwqFAvb29lixYgX279+PgoIChIaGYv/+/cjPz0dsbCzKy8thaWmJZcuWoWfPnpgyZQratm2L27dvY/Xq1ejXr59U6SMiQkJCAvz8/AAAfn5+mDFjBqKiohp1bWpqKlauXAkA6Nq1K/r27YuMjAycO3cOa9euBQC4uLjAwcFBdU2fPn1gYmICAFiwYAG+++477Ny5Ezdu3EBFRQUA4OLFi1i3bh0AwNXVFV27dgUAnD17Fv/5z3+QlpYG4Elf/tNPP7HIJr3BIpt0xtWrV+Hs7KwqsOu5uroiOzsbK1euREBAACZNmoQvv/wSn3/+OQBg69atsLS0REpKCoqLixEUFAQnJycAQGZmJo4dO4aSkhKMHDkS8fHxWLRoEaZMmYLvv/8er732Gv75z3/i008/RevWrbF9+3bExcVhwYIFOHz4MD755BO0bdsW06dPR1xcHOzs7HDp0iVERUUhISEBAGBvb4+4uLiWTRYR0a8UFxfj9OnTyMzMVPWP1dXVSE5OBgAIIQAAdXV1z71eqVSqbQshUFdXByMjI7X9MplM9X8zMzPV/+fOnQsrKyu88cYbGDt2LI4fP/7M+QBUP0+hUCAyMhK+vr4AgIcPH8LU1FSzO02kw7jwkXSGEAIKheKZ/bW1tQCejIY8PUJTP3qSmpqKoKAgAIC1tTVGjhyJixcvAnhSoLdp0wZdunQBAHh4eAAA7Ozs8PjxY1y4cAHZ2dl45513EBAQgJSUFNy5c0et/Tt37iA7OxthYWEICAjAypUrUVBQoFosNGDAAG2ngohIY0lJSRg0aBDOnDmDU6dO4dSpU5g3bx4+++wzWFlZqdawfPPNN6prjIyMVP2uu7s7Dh06BADIzc3FpUuX0K9fP3h4eKg+geTmzZvIysp6pnAGgAsXLiA8PByjRo3C999/D+BJIe3h4aH6pJPMzEzk5OSotVdbW4vKykpMmzYN586da6bsELU8jmSTzujbty/279+PmpoatGrVSrX/8uXL6N69OwoLC1UjMTKZTNXJK5VKtQ6/fvQFgKoQr2dsrP6UVygUePPNN7FkyRIATxZe/nqlvVKpRNeuXZGUlKT6+fn5+aoYOfJCRLogMTER4eHhavveeecdbNu2DdOmTcPq1ZjWVj0AAAI6SURBVKuxbds2eHp6qo4PGzYMa9euhYWFBRYtWoSlS5eq+rpVq1bB1tYWs2fPxsKFC+Hv749u3bqhY8eOz+335syZgwkTJsDS0hJOTk7o0qULcnNzER4ejujoaIwbNw6vv/66arrIpEmT8PPPP+Ott95CXV0dxo0bh1GjRjVjhohamCDSISEhIWLJkiWiurpaCCHE7du3hY+Pj0hOThZhYWFi7969QgghTpw4IRwcHIQQQqxevVqsWLFCCCFEUVGR8PLyEhkZGSIhIUEsWLBA9bPrzxdCiAULFoiEhARx/fp1MXz4cFFQUCCEEGLx4sUiJiZGCCHEqFGjRHZ2tqiurhbDhw8XqampQgghkpKSREBAgBBCiPfff1+1n4hIHyUlJYn09HQhhBC5ubnCy8tLKBQKiaMi0n0cySadsmXLFmzevBn+/v4wNjaGqakp/vSnP2HMmDEYNGgQIiMjceTIETg7O8PCwgIAMHv2bCxfvhx+fn5QKBQICQmBi4sLbt261WB7Tk5OmDNnDoKDgyGEQM+ePREdHQ0AGDlyJEJDQ/HJJ59g06ZNiI2NRVVVFczNzVWLeIiI9N1rr72GZcuWqeZsL1++/Jm1M0T0LJkQv7z/TkREREREWsE/RYmIiIiItIxFNhERERGRlrHIJiIiIiLSMhbZRERERERaxiKbiIiIiEjLWGQTEREREWkZi2wiIiIiIi1jkU1EREREpGUssomIiIiItIxFNhERERGRlrHIJiIiIiLSsv8P4a7EGchZHzgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 800x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>vin</th>\n",
       "      <th>inventory_number</th>\n",
       "      <th>site_number</th>\n",
       "      <th>year</th>\n",
       "      <th>make</th>\n",
       "      <th>model</th>\n",
       "      <th>series</th>\n",
       "      <th>autograde</th>\n",
       "      <th>odometer</th>\n",
       "      <th>create_date</th>\n",
       "      <th>sale_date</th>\n",
       "      <th>wholesale_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1N4AL3AP0FC159090</td>\n",
       "      <td>632180549338610</td>\n",
       "      <td>247</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>2.1</td>\n",
       "      <td>69429.0</td>\n",
       "      <td>2019-08-23 18:18:18</td>\n",
       "      <td>2019-09-20</td>\n",
       "      <td>6600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1N4AL3AP0FC159123</td>\n",
       "      <td>69054504684048</td>\n",
       "      <td>206</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>0.0</td>\n",
       "      <td>143275.0</td>\n",
       "      <td>2019-08-09 03:35:15</td>\n",
       "      <td>2019-10-03</td>\n",
       "      <td>1500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1N4AL3AP0FC199623</td>\n",
       "      <td>179027136436462</td>\n",
       "      <td>211</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>1.3</td>\n",
       "      <td>52806.0</td>\n",
       "      <td>2019-08-05 15:45:12</td>\n",
       "      <td>2019-09-19</td>\n",
       "      <td>2400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1N4AL3AP0FC219501</td>\n",
       "      <td>260369527914021</td>\n",
       "      <td>206</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>4.1</td>\n",
       "      <td>93509.0</td>\n",
       "      <td>2019-08-08 14:13:00</td>\n",
       "      <td>2019-08-15</td>\n",
       "      <td>8300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1N4AL3AP0FC228571</td>\n",
       "      <td>656326856570737</td>\n",
       "      <td>237</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>3.1</td>\n",
       "      <td>78725.0</td>\n",
       "      <td>2019-08-14 18:23:49</td>\n",
       "      <td>2019-10-23</td>\n",
       "      <td>4900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1N4AL3AP0FC268813</td>\n",
       "      <td>242820306533172</td>\n",
       "      <td>216</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>2.1</td>\n",
       "      <td>147056.0</td>\n",
       "      <td>2019-08-27 22:03:37</td>\n",
       "      <td>2019-09-19</td>\n",
       "      <td>3900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1N4AL3AP0FC282758</td>\n",
       "      <td>724406399451937</td>\n",
       "      <td>216</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>1.5</td>\n",
       "      <td>66268.0</td>\n",
       "      <td>2019-08-15 18:22:31</td>\n",
       "      <td>2019-10-24</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1N4AL3AP0FC450530</td>\n",
       "      <td>356147311461448</td>\n",
       "      <td>234</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>3.2</td>\n",
       "      <td>66624.0</td>\n",
       "      <td>2019-08-14 14:28:34</td>\n",
       "      <td>2019-10-11</td>\n",
       "      <td>7500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1N4AL3AP0FC482071</td>\n",
       "      <td>458281620939175</td>\n",
       "      <td>206</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>1.3</td>\n",
       "      <td>111258.0</td>\n",
       "      <td>2019-08-19 20:33:06</td>\n",
       "      <td>2019-09-19</td>\n",
       "      <td>4700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1N4AL3AP0FC582879</td>\n",
       "      <td>564947126454205</td>\n",
       "      <td>209</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>2.4</td>\n",
       "      <td>45014.0</td>\n",
       "      <td>2019-08-05 17:35:30</td>\n",
       "      <td>2019-09-06</td>\n",
       "      <td>6600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1N4AL3AP0FC584745</td>\n",
       "      <td>430969921439924</td>\n",
       "      <td>247</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>3.7</td>\n",
       "      <td>96816.0</td>\n",
       "      <td>2019-08-14 18:14:09</td>\n",
       "      <td>2019-08-23</td>\n",
       "      <td>6400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1N4AL3AP0FN914565</td>\n",
       "      <td>676105195123955</td>\n",
       "      <td>234</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>2.6</td>\n",
       "      <td>62230.0</td>\n",
       "      <td>2019-08-09 17:21:01</td>\n",
       "      <td>2019-08-30</td>\n",
       "      <td>7200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1N4AL3AP0FN917689</td>\n",
       "      <td>72481882828332</td>\n",
       "      <td>236</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>1.6</td>\n",
       "      <td>75093.0</td>\n",
       "      <td>2019-08-05 22:06:35</td>\n",
       "      <td>2019-09-12</td>\n",
       "      <td>2400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1N4AL3AP1FC162743</td>\n",
       "      <td>238452314668854</td>\n",
       "      <td>223</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>1.9</td>\n",
       "      <td>122153.0</td>\n",
       "      <td>2019-08-29 18:26:32</td>\n",
       "      <td>2019-09-25</td>\n",
       "      <td>4100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1N4AL3AP1FC221810</td>\n",
       "      <td>170291173251607</td>\n",
       "      <td>225</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>2.8</td>\n",
       "      <td>99168.0</td>\n",
       "      <td>2019-08-02 00:47:45</td>\n",
       "      <td>2019-08-28</td>\n",
       "      <td>7700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1N4AL3AP1FC423000</td>\n",
       "      <td>254910618921046</td>\n",
       "      <td>215</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>1.6</td>\n",
       "      <td>78462.0</td>\n",
       "      <td>2019-08-27 20:36:32</td>\n",
       "      <td>2019-10-08</td>\n",
       "      <td>6200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1N4AL3AP1FC455302</td>\n",
       "      <td>107619010493224</td>\n",
       "      <td>225</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>2.8</td>\n",
       "      <td>60080.0</td>\n",
       "      <td>2019-08-14 16:47:13</td>\n",
       "      <td>2019-09-04</td>\n",
       "      <td>9200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1N4AL3AP1FC488137</td>\n",
       "      <td>556322831074557</td>\n",
       "      <td>249</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>4.6</td>\n",
       "      <td>60104.0</td>\n",
       "      <td>2019-08-05 20:43:24</td>\n",
       "      <td>2019-08-15</td>\n",
       "      <td>9800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1N4AL3AP1FC567114</td>\n",
       "      <td>273550778472357</td>\n",
       "      <td>203</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>3.7</td>\n",
       "      <td>100402.0</td>\n",
       "      <td>2019-08-19 22:48:30</td>\n",
       "      <td>2019-08-28</td>\n",
       "      <td>8400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1N4AL3AP1FC576797</td>\n",
       "      <td>58063684420033</td>\n",
       "      <td>207</td>\n",
       "      <td>2015</td>\n",
       "      <td>NISSAN</td>\n",
       "      <td>ALTIMA</td>\n",
       "      <td>2.5 S</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97857.0</td>\n",
       "      <td>2019-08-05 22:02:05</td>\n",
       "      <td>2019-08-27</td>\n",
       "      <td>2500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  vin  inventory_number  site_number  year    make   model  \\\n",
       "0   1N4AL3AP0FC159090   632180549338610          247  2015  NISSAN  ALTIMA   \n",
       "1   1N4AL3AP0FC159123    69054504684048          206  2015  NISSAN  ALTIMA   \n",
       "2   1N4AL3AP0FC199623   179027136436462          211  2015  NISSAN  ALTIMA   \n",
       "3   1N4AL3AP0FC219501   260369527914021          206  2015  NISSAN  ALTIMA   \n",
       "4   1N4AL3AP0FC228571   656326856570737          237  2015  NISSAN  ALTIMA   \n",
       "5   1N4AL3AP0FC268813   242820306533172          216  2015  NISSAN  ALTIMA   \n",
       "6   1N4AL3AP0FC282758   724406399451937          216  2015  NISSAN  ALTIMA   \n",
       "7   1N4AL3AP0FC450530   356147311461448          234  2015  NISSAN  ALTIMA   \n",
       "8   1N4AL3AP0FC482071   458281620939175          206  2015  NISSAN  ALTIMA   \n",
       "9   1N4AL3AP0FC582879   564947126454205          209  2015  NISSAN  ALTIMA   \n",
       "10  1N4AL3AP0FC584745   430969921439924          247  2015  NISSAN  ALTIMA   \n",
       "11  1N4AL3AP0FN914565   676105195123955          234  2015  NISSAN  ALTIMA   \n",
       "12  1N4AL3AP0FN917689    72481882828332          236  2015  NISSAN  ALTIMA   \n",
       "13  1N4AL3AP1FC162743   238452314668854          223  2015  NISSAN  ALTIMA   \n",
       "14  1N4AL3AP1FC221810   170291173251607          225  2015  NISSAN  ALTIMA   \n",
       "15  1N4AL3AP1FC423000   254910618921046          215  2015  NISSAN  ALTIMA   \n",
       "16  1N4AL3AP1FC455302   107619010493224          225  2015  NISSAN  ALTIMA   \n",
       "17  1N4AL3AP1FC488137   556322831074557          249  2015  NISSAN  ALTIMA   \n",
       "18  1N4AL3AP1FC567114   273550778472357          203  2015  NISSAN  ALTIMA   \n",
       "19  1N4AL3AP1FC576797    58063684420033          207  2015  NISSAN  ALTIMA   \n",
       "\n",
       "   series  autograde  odometer         create_date  sale_date  wholesale_price  \n",
       "0   2.5 S        2.1   69429.0 2019-08-23 18:18:18 2019-09-20             6600  \n",
       "1   2.5 S        0.0  143275.0 2019-08-09 03:35:15 2019-10-03             1500  \n",
       "2   2.5 S        1.3   52806.0 2019-08-05 15:45:12 2019-09-19             2400  \n",
       "3   2.5 S        4.1   93509.0 2019-08-08 14:13:00 2019-08-15             8300  \n",
       "4   2.5 S        3.1   78725.0 2019-08-14 18:23:49 2019-10-23             4900  \n",
       "5   2.5 S        2.1  147056.0 2019-08-27 22:03:37 2019-09-19             3900  \n",
       "6   2.5 S        1.5   66268.0 2019-08-15 18:22:31 2019-10-24             5000  \n",
       "7   2.5 S        3.2   66624.0 2019-08-14 14:28:34 2019-10-11             7500  \n",
       "8   2.5 S        1.3  111258.0 2019-08-19 20:33:06 2019-09-19             4700  \n",
       "9   2.5 S        2.4   45014.0 2019-08-05 17:35:30 2019-09-06             6600  \n",
       "10  2.5 S        3.7   96816.0 2019-08-14 18:14:09 2019-08-23             6400  \n",
       "11  2.5 S        2.6   62230.0 2019-08-09 17:21:01 2019-08-30             7200  \n",
       "12  2.5 S        1.6   75093.0 2019-08-05 22:06:35 2019-09-12             2400  \n",
       "13  2.5 S        1.9  122153.0 2019-08-29 18:26:32 2019-09-25             4100  \n",
       "14  2.5 S        2.8   99168.0 2019-08-02 00:47:45 2019-08-28             7700  \n",
       "15  2.5 S        1.6   78462.0 2019-08-27 20:36:32 2019-10-08             6200  \n",
       "16  2.5 S        2.8   60080.0 2019-08-14 16:47:13 2019-09-04             9200  \n",
       "17  2.5 S        4.6   60104.0 2019-08-05 20:43:24 2019-08-15             9800  \n",
       "18  2.5 S        3.7  100402.0 2019-08-19 22:48:30 2019-08-28             8400  \n",
       "19  2.5 S        NaN   97857.0 2019-08-05 22:02:05 2019-08-27             2500  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_altima = run_experiment('2019-08-01', '2019-09-01', 2015, 'NISSAN', 'ALTIMA', '2.5 S')\n",
    "df_altima.head(20)"
   ]
  }
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