{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "500a99ff-4d32-45b6-b5f4-4a9b7ae022dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>number</th>\n",
       "      <th>incident_state</th>\n",
       "      <th>active</th>\n",
       "      <th>reassignment_count</th>\n",
       "      <th>reopen_count</th>\n",
       "      <th>sys_mod_count</th>\n",
       "      <th>made_sla</th>\n",
       "      <th>caller_id</th>\n",
       "      <th>opened_by</th>\n",
       "      <th>opened_at</th>\n",
       "      <th>...</th>\n",
       "      <th>u_priority_confirmation</th>\n",
       "      <th>notify</th>\n",
       "      <th>problem_id</th>\n",
       "      <th>rfc</th>\n",
       "      <th>vendor</th>\n",
       "      <th>caused_by</th>\n",
       "      <th>closed_code</th>\n",
       "      <th>resolved_by</th>\n",
       "      <th>resolved_at</th>\n",
       "      <th>closed_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>INC0000045</td>\n",
       "      <td>New</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>Caller 2403</td>\n",
       "      <td>Opened by  8</td>\n",
       "      <td>29/2/2016 01:16</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>Do Not Notify</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>code 5</td>\n",
       "      <td>Resolved by 149</td>\n",
       "      <td>29/2/2016 11:29</td>\n",
       "      <td>5/3/2016 12:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>INC0000045</td>\n",
       "      <td>Resolved</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>Caller 2403</td>\n",
       "      <td>Opened by  8</td>\n",
       "      <td>29/2/2016 01:16</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>Do Not Notify</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>code 5</td>\n",
       "      <td>Resolved by 149</td>\n",
       "      <td>29/2/2016 11:29</td>\n",
       "      <td>5/3/2016 12:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>INC0000045</td>\n",
       "      <td>Resolved</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "      <td>Caller 2403</td>\n",
       "      <td>Opened by  8</td>\n",
       "      <td>29/2/2016 01:16</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>Do Not Notify</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>code 5</td>\n",
       "      <td>Resolved by 149</td>\n",
       "      <td>29/2/2016 11:29</td>\n",
       "      <td>5/3/2016 12:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>INC0000045</td>\n",
       "      <td>Closed</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>Caller 2403</td>\n",
       "      <td>Opened by  8</td>\n",
       "      <td>29/2/2016 01:16</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>Do Not Notify</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>code 5</td>\n",
       "      <td>Resolved by 149</td>\n",
       "      <td>29/2/2016 11:29</td>\n",
       "      <td>5/3/2016 12:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>INC0000047</td>\n",
       "      <td>New</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>Caller 2403</td>\n",
       "      <td>Opened by  397</td>\n",
       "      <td>29/2/2016 04:40</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>Do Not Notify</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>code 5</td>\n",
       "      <td>Resolved by 81</td>\n",
       "      <td>1/3/2016 09:52</td>\n",
       "      <td>6/3/2016 10:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       number incident_state  active  reassignment_count  reopen_count  \\\n",
       "0  INC0000045            New    True                   0             0   \n",
       "1  INC0000045       Resolved    True                   0             0   \n",
       "2  INC0000045       Resolved    True                   0             0   \n",
       "3  INC0000045         Closed   False                   0             0   \n",
       "4  INC0000047            New    True                   0             0   \n",
       "\n",
       "   sys_mod_count  made_sla    caller_id       opened_by        opened_at  ...  \\\n",
       "0              0      True  Caller 2403    Opened by  8  29/2/2016 01:16  ...   \n",
       "1              2      True  Caller 2403    Opened by  8  29/2/2016 01:16  ...   \n",
       "2              3      True  Caller 2403    Opened by  8  29/2/2016 01:16  ...   \n",
       "3              4      True  Caller 2403    Opened by  8  29/2/2016 01:16  ...   \n",
       "4              0      True  Caller 2403  Opened by  397  29/2/2016 04:40  ...   \n",
       "\n",
       "  u_priority_confirmation         notify problem_id rfc vendor caused_by  \\\n",
       "0                   False  Do Not Notify          ?   ?      ?         ?   \n",
       "1                   False  Do Not Notify          ?   ?      ?         ?   \n",
       "2                   False  Do Not Notify          ?   ?      ?         ?   \n",
       "3                   False  Do Not Notify          ?   ?      ?         ?   \n",
       "4                   False  Do Not Notify          ?   ?      ?         ?   \n",
       "\n",
       "  closed_code      resolved_by      resolved_at       closed_at  \n",
       "0      code 5  Resolved by 149  29/2/2016 11:29  5/3/2016 12:00  \n",
       "1      code 5  Resolved by 149  29/2/2016 11:29  5/3/2016 12:00  \n",
       "2      code 5  Resolved by 149  29/2/2016 11:29  5/3/2016 12:00  \n",
       "3      code 5  Resolved by 149  29/2/2016 11:29  5/3/2016 12:00  \n",
       "4      code 5   Resolved by 81   1/3/2016 09:52  6/3/2016 10:00  \n",
       "\n",
       "[5 rows x 36 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd \n",
    "df = pd.read_csv(\"incident_event_log.csv\")\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27ce3164-8c1a-4cac-9abe-67626ef2ce46",
   "metadata": {},
   "source": [
    "#### Create target variable"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46eec613-3afe-4d93-a013-f3a337249997",
   "metadata": {},
   "source": [
    "1. First we saw is there any missing values in resolved_at and opened_at or not. \n",
    "2. Then to enable regression modeling for predicting how long it takes to resolve an IT service desk incident, we created the target variable time_to_resolution. This was computed by taking the difference between the resolved_at and opened_at timestamps, and converting the result into hours."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ac90c493-0e02-4af8-93ea-255a5a7fae32",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Missing values in resolved_at (as '?'): 3141\n",
      "Missing values in opened_at (as '?'): 0\n"
     ]
    }
   ],
   "source": [
    "# Count how many \"?\" values are in each column\n",
    "resolved_missing = (df[\"resolved_at\"] == \"?\").sum()\n",
    "opened_missing = (df[\"opened_at\"] == \"?\").sum()\n",
    "\n",
    "print(f\"Missing values in resolved_at (as '?'): {resolved_missing}\")\n",
    "print(f\"Missing values in opened_at (as '?'): {opened_missing}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19148c44-7523-4c62-aebc-004eef0d3e63",
   "metadata": {},
   "source": [
    "Time_to_resolution depends directly on resolved_at, missing values indicate that incident was never happened. \n",
    "\n",
    "Date and time can be imputed but in this case imputing (with mean) would mean artifically creating target values which is data leakeage and leads to garbage prediction. Therefore, dropping missing values would be better choice in this case."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5295dd7a-bb01-407b-ae01-9d4b0ed9e7d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert opened_at and resolved_at to datetime\n",
    "df[\"opened_at\"] = pd.to_datetime(df[\"opened_at\"], format=\"%d/%m/%Y %H:%M\", errors=\"coerce\")\n",
    "df[\"resolved_at\"] = pd.to_datetime(df[\"resolved_at\"], format=\"%d/%m/%Y %H:%M\", errors=\"coerce\")\n",
    "\n",
    "# Now calculate time_to_resolution (in hours)\n",
    "df[\"time_to_resolution\"] = (df[\"resolved_at\"] - df[\"opened_at\"]).dt.total_seconds() / 3600"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e107c827-f7c5-4dde-b841-adebb8cea3bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.dropna(subset=[\"time_to_resolution\"]) #dropping those rows which are having missing values. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c48b172c-39a9-4ad2-bd7e-76a058584f81",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Missing values in resolved_at (as '?'): 0\n",
      "Missing values in opened_at (as '?'): 0\n",
      "Missing values in opened_at (as '?'): 0\n"
     ]
    }
   ],
   "source": [
    "# Count how many \"?\" values are in each column after removing missing rows. \n",
    "resolved_missing = (df[\"resolved_at\"] == \"?\").sum()\n",
    "opened_missing = (df[\"opened_at\"] == \"?\").sum()\n",
    "time_to_resolution_missing = (df[\"time_to_resolution\"] == \"?\").sum()\n",
    "\n",
    "\n",
    "print(f\"Missing values in resolved_at (as '?'): {resolved_missing}\")\n",
    "print(f\"Missing values in opened_at (as '?'): {opened_missing}\")\n",
    "print(f\"Missing values in opened_at (as '?'): {time_to_resolution_missing}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbf2e385-5b4b-4731-84f1-569e7c75b342",
   "metadata": {},
   "source": [
    "We can observe that there are no missing values in all three columns. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80f07798-ecd5-4daf-8465-6d1199b08e23",
   "metadata": {},
   "source": [
    "#### Detecting Outliers. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "58af5192-6333-415c-97dc-c8c81379a9f0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Outliers BEFORE Capping:\n",
      "\n",
      "reassignment_count: 4152 outliers (Lower: -3.00, Upper: 5.00)\n",
      "reopen_count: 2310 outliers (Lower: 0.00, Upper: 0.00)\n",
      "sys_mod_count: 10900 outliers (Lower: -6.50, Upper: 13.50)\n",
      "time_to_resolution: 12089 outliers (Lower: -383.11, Upper: 649.36)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df['reopen_count'] = df['reopen_count']\n",
    "df_original = df.copy()\n",
    "# Define IQR-based outlier detection\n",
    "def detect_outliers_iqr(series):\n",
    "    Q1 = series.quantile(0.25)\n",
    "    Q3 = series.quantile(0.75)\n",
    "    IQR = Q3 - Q1\n",
    "    lower = Q1 - 1.5 * IQR\n",
    "    upper = Q3 + 1.5 * IQR\n",
    "    outliers = ((series < lower) | (series > upper)).sum()\n",
    "    return outliers, lower, upper\n",
    "\n",
    "# Columns to check\n",
    "columns_to_check = ['reassignment_count', 'reopen_count', 'sys_mod_count', 'time_to_resolution']\n",
    "\n",
    "# Print outlier count before capping\n",
    "print(\" Outliers BEFORE Capping:\\n\")\n",
    "for col in columns_to_check:\n",
    "    count, lower, upper = detect_outliers_iqr(df[col])\n",
    "    print(f\"{col}: {count} outliers (Lower: {lower:.2f}, Upper: {upper:.2f})\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e829a190-d158-433c-b520-9a0e27381b55",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define IQR-based capping\n",
    "def cap_outliers(series):\n",
    "    Q1 = series.quantile(0.25)\n",
    "    Q3 = series.quantile(0.75)\n",
    "    IQR = Q3 - Q1\n",
    "    lower = Q1 - 1.5 * IQR\n",
    "    upper = Q3 + 1.5 * IQR\n",
    "    return series.clip(lower, upper)\n",
    "\n",
    "# Apply capping to each column\n",
    "for col in columns_to_check:\n",
    "    df[col] = cap_outliers(df[col])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f89d5ce3-ee9f-49b6-b74c-fbd58ea7b8a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Outliers AFTER Capping:\n",
      "\n",
      "reassignment_count: 0 outliers (Lower: -3.00, Upper: 5.00)\n",
      "reopen_count: 0 outliers (Lower: 0.00, Upper: 0.00)\n",
      "sys_mod_count: 0 outliers (Lower: -6.50, Upper: 13.50)\n",
      "time_to_resolution: 0 outliers (Lower: -383.11, Upper: 649.36)\n"
     ]
    }
   ],
   "source": [
    "# Print outlier count after capping\n",
    "print(\"\\n Outliers AFTER Capping:\\n\")\n",
    "for col in columns_to_check:\n",
    "    count, lower, upper = detect_outliers_iqr(df[col])\n",
    "    print(f\"{col}: {count} outliers (Lower: {lower:.2f}, Upper: {upper:.2f})\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "476f353e-ddba-416f-8f74-049d4f8e1610",
   "metadata": {},
   "source": [
    "When we applied the **Interquartile Range (IQR) method** to detect outliers in the `reopen_count` column, the calculated lower and upper bounds were both `0.00`. This happened because the majority of values in the column are zeros — meaning most tickets were never reopened. As a result, the 25th percentile (Q1) and the 75th percentile (Q3) are both `0`, which makes the IQR equal to `0`. \n",
    "\n",
    "Using the standard formula for outlier detection:\n",
    "\n",
    "    {Lower bound} = Q1 - 1.5 \\times IQR = 0 - 0 = 0 \n",
    "    {Upper bound} = Q3 + 1.5 \\times IQR = 0 + 0 = 0\n",
    "\n",
    "\n",
    "Any value greater than 0 was flagged as an outlier. However, these higher values (like 1, 2, 3, etc.) are **valid** and **informative** because they indicate tickets that were reopened — which can reflect important patterns in resolution delays. So even though IQR marked them as outliers, we chose to **keep them unchanged** to retain that meaningful signal for modeling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2d6e25f8-d2d3-4fe8-a8e7-2f93633bee0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['reopen_count'] = df_original['reopen_count']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ba251e9d-d904-4e9e-bc0f-db9ec9f372b3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unique values in reopen_count: [0 1 2 3 4 5 6 7 8]\n"
     ]
    }
   ],
   "source": [
    "print(\"Unique values in reopen_count:\", df['reopen_count'].unique()) # checking if it reverted back to original reopen_count. results suggests that it has reverted back. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b659e92d-03cc-422d-b275-dca132980020",
   "metadata": {},
   "source": [
    "##### Log-transformation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "960603b6-6a8a-40d8-92fb-94ecd3c7580e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Log transform selected capped columns\n",
    "log_columns = ['reassignment_count', 'sys_mod_count', 'time_to_resolution']\n",
    "\n",
    "for col in log_columns:\n",
    "    df[col + '_log'] = np.log1p(df[col])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d6c84352-11e9-49f8-9cb4-e1642abbb6aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Compare original vs. log-transformed side by side\n",
    "for col in log_columns:\n",
    "    log_col = col + '_log'\n",
    "    plt.figure(figsize=(14, 5))\n",
    "\n",
    "    plt.subplot(1, 2, 1)\n",
    "    sns.histplot(df[col], kde=True, bins=50)\n",
    "    plt.title(f\"Original Distribution: {col}\")\n",
    "\n",
    "    plt.subplot(1, 2, 2)\n",
    "    sns.histplot(df[log_col], kde=True, bins=50, color='orange')\n",
    "    plt.title(f\"Log-Transformed Distribution: {log_col}\")\n",
    "\n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d39064b-1843-4db6-a9ed-ddfe2e34e040",
   "metadata": {},
   "source": [
    "As we can see that `time_to_resolution` are rightly skewed therefore we applied log transformation `time_to_resolution` to reduce skewness and compress extreme values. This made the distributions more balanced and suitable for modeling, improving learning stability and performance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7f6be098-e6f3-4231-aa45-03706c951338",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "df['time_to_resolution_log'] = np.log1p(df['time_to_resolution'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a6cadd4d-4829-48e1-8bee-3eb8dce27348",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Plot the log-transformed columns\n",
    "plt.figure(figsize=(12, 5))\n",
    "\n",
    "# time_to_resolution_log\n",
    "sns.histplot(df['time_to_resolution_log'], kde=True, bins=50, color='green')\n",
    "plt.title(\"Log-Transformed Distribution: time_to_resolution_log\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "78f02cfa-3eb2-4787-9d0f-e15248ccffef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>number</th>\n",
       "      <th>incident_state</th>\n",
       "      <th>active</th>\n",
       "      <th>reassignment_count</th>\n",
       "      <th>reopen_count</th>\n",
       "      <th>sys_mod_count</th>\n",
       "      <th>made_sla</th>\n",
       "      <th>caller_id</th>\n",
       "      <th>opened_by</th>\n",
       "      <th>opened_at</th>\n",
       "      <th>...</th>\n",
       "      <th>vendor</th>\n",
       "      <th>caused_by</th>\n",
       "      <th>closed_code</th>\n",
       "      <th>resolved_by</th>\n",
       "      <th>resolved_at</th>\n",
       "      <th>closed_at</th>\n",
       "      <th>time_to_resolution</th>\n",
       "      <th>reassignment_count_log</th>\n",
       "      <th>sys_mod_count_log</th>\n",
       "      <th>time_to_resolution_log</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>INC0000045</td>\n",
       "      <td>New</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>Caller 2403</td>\n",
       "      <td>Opened by  8</td>\n",
       "      <td>2016-02-29 01:16:00</td>\n",
       "      <td>...</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>code 5</td>\n",
       "      <td>Resolved by 149</td>\n",
       "      <td>2016-02-29 11:29:00</td>\n",
       "      <td>5/3/2016 12:00</td>\n",
       "      <td>10.216667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.417401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>INC0000045</td>\n",
       "      <td>Resolved</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>True</td>\n",
       "      <td>Caller 2403</td>\n",
       "      <td>Opened by  8</td>\n",
       "      <td>2016-02-29 01:16:00</td>\n",
       "      <td>...</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>code 5</td>\n",
       "      <td>Resolved by 149</td>\n",
       "      <td>2016-02-29 11:29:00</td>\n",
       "      <td>5/3/2016 12:00</td>\n",
       "      <td>10.216667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.098612</td>\n",
       "      <td>2.417401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>INC0000045</td>\n",
       "      <td>Resolved</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>True</td>\n",
       "      <td>Caller 2403</td>\n",
       "      <td>Opened by  8</td>\n",
       "      <td>2016-02-29 01:16:00</td>\n",
       "      <td>...</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>code 5</td>\n",
       "      <td>Resolved by 149</td>\n",
       "      <td>2016-02-29 11:29:00</td>\n",
       "      <td>5/3/2016 12:00</td>\n",
       "      <td>10.216667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.386294</td>\n",
       "      <td>2.417401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>INC0000045</td>\n",
       "      <td>Closed</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>True</td>\n",
       "      <td>Caller 2403</td>\n",
       "      <td>Opened by  8</td>\n",
       "      <td>2016-02-29 01:16:00</td>\n",
       "      <td>...</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>code 5</td>\n",
       "      <td>Resolved by 149</td>\n",
       "      <td>2016-02-29 11:29:00</td>\n",
       "      <td>5/3/2016 12:00</td>\n",
       "      <td>10.216667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.609438</td>\n",
       "      <td>2.417401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>INC0000047</td>\n",
       "      <td>New</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>Caller 2403</td>\n",
       "      <td>Opened by  397</td>\n",
       "      <td>2016-02-29 04:40:00</td>\n",
       "      <td>...</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>code 5</td>\n",
       "      <td>Resolved by 81</td>\n",
       "      <td>2016-03-01 09:52:00</td>\n",
       "      <td>6/3/2016 10:00</td>\n",
       "      <td>29.200000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.407842</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       number incident_state  active  reassignment_count  reopen_count  \\\n",
       "0  INC0000045            New    True                   0             0   \n",
       "1  INC0000045       Resolved    True                   0             0   \n",
       "2  INC0000045       Resolved    True                   0             0   \n",
       "3  INC0000045         Closed   False                   0             0   \n",
       "4  INC0000047            New    True                   0             0   \n",
       "\n",
       "   sys_mod_count  made_sla    caller_id       opened_by           opened_at  \\\n",
       "0            0.0      True  Caller 2403    Opened by  8 2016-02-29 01:16:00   \n",
       "1            2.0      True  Caller 2403    Opened by  8 2016-02-29 01:16:00   \n",
       "2            3.0      True  Caller 2403    Opened by  8 2016-02-29 01:16:00   \n",
       "3            4.0      True  Caller 2403    Opened by  8 2016-02-29 01:16:00   \n",
       "4            0.0      True  Caller 2403  Opened by  397 2016-02-29 04:40:00   \n",
       "\n",
       "   ... vendor caused_by closed_code      resolved_by         resolved_at  \\\n",
       "0  ...      ?         ?      code 5  Resolved by 149 2016-02-29 11:29:00   \n",
       "1  ...      ?         ?      code 5  Resolved by 149 2016-02-29 11:29:00   \n",
       "2  ...      ?         ?      code 5  Resolved by 149 2016-02-29 11:29:00   \n",
       "3  ...      ?         ?      code 5  Resolved by 149 2016-02-29 11:29:00   \n",
       "4  ...      ?         ?      code 5   Resolved by 81 2016-03-01 09:52:00   \n",
       "\n",
       "        closed_at time_to_resolution reassignment_count_log sys_mod_count_log  \\\n",
       "0  5/3/2016 12:00          10.216667                    0.0          0.000000   \n",
       "1  5/3/2016 12:00          10.216667                    0.0          1.098612   \n",
       "2  5/3/2016 12:00          10.216667                    0.0          1.386294   \n",
       "3  5/3/2016 12:00          10.216667                    0.0          1.609438   \n",
       "4  6/3/2016 10:00          29.200000                    0.0          0.000000   \n",
       "\n",
       "  time_to_resolution_log  \n",
       "0               2.417401  \n",
       "1               2.417401  \n",
       "2               2.417401  \n",
       "3               2.417401  \n",
       "4               3.407842  \n",
       "\n",
       "[5 rows x 40 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a976503-caca-4e4a-a142-35d81d24f4b6",
   "metadata": {},
   "source": [
    "#### Detecting data anomaly or placeholder in categorical data. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf3d1eee-f11e-423c-9038-a429e2e3f94f",
   "metadata": {},
   "source": [
    "##### Calculating value counts to see unique values in categorical data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8026624f-eb88-412e-8ba2-01d53396d549",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Value counts for 'incident_state':\n",
      "incident_state\n",
      "Active                38710\n",
      "New                   36392\n",
      "Resolved              24190\n",
      "Closed                23427\n",
      "Awaiting User Info    14641\n",
      "Awaiting Vendor         707\n",
      "Awaiting Problem        461\n",
      "Awaiting Evidence        38\n",
      "-100                      5\n",
      "Name: count, dtype: int64\n",
      "\n",
      "Value counts for 'contact_type':\n",
      "contact_type\n",
      "Phone             137339\n",
      "Self service         995\n",
      "Email                220\n",
      "Direct opening        17\n",
      "Name: count, dtype: int64\n",
      "\n",
      "Value counts for 'notify':\n",
      "notify\n",
      "Do Not Notify    138452\n",
      "Send Email          119\n",
      "Name: count, dtype: int64\n",
      "\n",
      "Value counts for 'impact':\n",
      "impact\n",
      "2 - Medium    131394\n",
      "3 - Low         3686\n",
      "1 - High        3491\n",
      "Name: count, dtype: int64\n",
      "\n",
      "Value counts for 'urgency':\n",
      "urgency\n",
      "2 - Medium    131135\n",
      "1 - High        4020\n",
      "3 - Low         3416\n",
      "Name: count, dtype: int64\n",
      "\n",
      "Value counts for 'priority':\n",
      "priority\n",
      "3 - Moderate    129511\n",
      "4 - Low           3830\n",
      "2 - High          2972\n",
      "1 - Critical      2258\n",
      "Name: count, dtype: int64\n",
      "\n",
      "Value counts for 'knowledge':\n",
      "knowledge\n",
      "False    113474\n",
      "True      25097\n",
      "Name: count, dtype: int64\n",
      "\n",
      "Value counts for 'u_priority_confirmation':\n",
      "u_priority_confirmation\n",
      "False    97601\n",
      "True     40970\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "cat_cols = ['incident_state', 'contact_type', 'notify','impact', 'urgency', 'priority', 'knowledge', 'u_priority_confirmation']\n",
    "\n",
    "for col in cat_cols:\n",
    "    print(f\"\\nValue counts for '{col}':\")\n",
    "    print(df[col].value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16909997-4034-49b2-8a4e-93289a47fb43",
   "metadata": {},
   "source": [
    "as in incident_state \"-100\" represents is definitely a data anomaly or placeholder. \n",
    "    -100 → 5 rows\n",
    "    Total rows → 141,712 \n",
    "That’s only 0.0035% of your data.\n",
    "Droping the rows. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "997ce9d9-20f5-456a-a275-846cb4fd51e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df[\"incident_state\"] != \"-100\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "bb1dbbe4-c85e-421a-b8d7-2b788ccaddff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "incident_state\n",
       "Active                38710\n",
       "New                   36392\n",
       "Resolved              24190\n",
       "Closed                23427\n",
       "Awaiting User Info    14641\n",
       "Awaiting Vendor         707\n",
       "Awaiting Problem        461\n",
       "Awaiting Evidence        38\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"incident_state\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2dd1e4e0-5e7e-4839-84d8-28219d6f118c",
   "metadata": {},
   "source": [
    "#### Extract datetime features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "38acf0f8-1d5e-4a07-90b2-20623a94aba6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[:, \"opened_hour\"] = df[\"opened_at\"].dt.hour\n",
    "df.loc[:, \"opened_dayofweek\"] = df[\"opened_at\"].dt.dayofweek\n",
    "df.loc[:, \"opened_month\"] = df[\"opened_at\"].dt.month\n",
    "df.loc[:, \"opened_weekend\"] = df[\"opened_dayofweek\"].isin([5, 6]).astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a6a38a0-9bd7-464f-a402-6b083d678246",
   "metadata": {},
   "source": [
    " #### Target Variable Exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc903aab-ae9a-4a25-b7b8-6b394c6ac9ce",
   "metadata": {},
   "source": [
    "#### Log-transformed time_to_resolution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b6275cf5-4f4b-45bb-9138-d09f29da96bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "sns.histplot(df['time_to_resolution_log'], kde=True, bins=50)\n",
    "plt.title(\"Log-Transformed Distribution: time_to_resolution_log\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb99ac70-1caf-43b7-9995-ae5a5e3e0a8e",
   "metadata": {},
   "source": [
    "The distribution of the log-transformed time_to_resolution is significantly more symmetric and bell-shaped compared to the original, which was highly right-skewed. This transformation reduces the influence of extreme outliers and helps stabilize variance across the dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8003a517-f17b-4ae2-a0c9-cb03e95f43b2",
   "metadata": {},
   "source": [
    "#### Avg Time by Incident State"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "347d4e36-abdc-458a-8dfa-9a5fc2cb7b5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if \"incident_state\" in df.columns:\n",
    "    avg_state = df.groupby(\"incident_state\")[\"time_to_resolution\"].mean().reset_index()\n",
    "    plt.figure(figsize=(8, 5))\n",
    "    sns.barplot(x=\"incident_state\", y=\"time_to_resolution\", data=avg_state)\n",
    "    plt.title(\"Avg Time to Resolution by Incident State\")\n",
    "    plt.xticks(rotation=45)\n",
    "    plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40a56281-553f-4642-85bc-06db28e1017b",
   "metadata": {},
   "source": [
    "🔍 Key Insights:\n",
    "\n",
    "🚨 Awaiting Vendor (2800+ hrs) and Awaiting Evidence (3200+ hrs) have the longest average resolution times by far.\n",
    "This suggests delays when incidents rely on third parties or additional proof.\n",
    "\n",
    "🧍 Awaiting User Info and Awaiting Problem also show high resolution times (400–800 hrs), indicating bottlenecks when additional information or problem identification is pending.\n",
    "\n",
    "✅ States like Closed, New, Resolved, and Active have much lower average resolution times (mostly below 300 hrs), reflecting standard workflow steps that are resolved quicker."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c9257d8-62b0-4148-9a5d-8034f8a6ce8c",
   "metadata": {},
   "source": [
    "#### Avg Time by Hour of Day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "663f301b-bf8f-4601-ad0f-d2f124142384",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 5))\n",
    "sns.barplot(x=\"opened_hour\", y=\"time_to_resolution\", data=df)\n",
    "plt.title(\"Avg Time to Resolution by Hour of Day\")\n",
    "plt.xlabel(\"Hour\")\n",
    "plt.ylabel(\"Avg Resolution Time\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1c912de-c2a9-49a2-ad51-656c743ef6eb",
   "metadata": {},
   "source": [
    "🔍 Key Insights:\n",
    "📈 Peak resolution times are between 11 AM and 4 PM, where average resolution durations are the highest (300+ hours).\n",
    "\n",
    "🕔 Early hours (5–6 AM) and late hours (9 PM–3 AM) show lower average resolution times, likely due to fewer complex tickets or auto-closures.\n",
    "\n",
    "🕘 Office hours trend: Resolution time tends to increase during active business hours when more complex tickets are likely submitted.\n",
    "\n",
    "📉 Shorter resolution times at night may suggest simpler issues or more efficient auto-resolution mechanisms."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92a2909e-30c5-480a-8b29-54271b59d590",
   "metadata": {},
   "source": [
    "#### Avg Time by Day of Week"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "974cf41b-607f-41d0-af0b-75f9cbaf2857",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 5))\n",
    "sns.barplot(x=\"opened_dayofweek\", y=\"time_to_resolution\", data=df)\n",
    "plt.title(\"Avg Time to Resolution by Day of Week\")\n",
    "plt.xlabel(\"Day (0 = Monday)\")\n",
    "plt.ylabel(\"Avg Resolution Time\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57133d6b-adb1-4a71-8e88-6687e4e043ca",
   "metadata": {},
   "source": [
    "🔍 Key Insights:\n",
    "🏢 Weekdays (Monday to Friday / Day 0–4) show significantly higher average resolution times, peaking around Tuesday and Friday (~300+ hours).\n",
    "\n",
    "📉 Weekends (Saturday = 5, Sunday = 6) show the lowest resolution times, often around or below 110 hours.\n",
    "\n",
    "This could reflect:\n",
    "\n",
    "Fewer tickets opened on weekends (faster to resolve or auto-closed).\n",
    "\n",
    "Less complex issues logged outside business days.\n",
    "\n",
    "Lower system or team load."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "932faf98-7163-496f-b55e-4ababed3781f",
   "metadata": {},
   "source": [
    "#### Treating missing values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "480a9211-91b1-41e8-8414-cbcd60d2b66f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "number                          0\n",
       "incident_state                  0\n",
       "active                          0\n",
       "reassignment_count              0\n",
       "reopen_count                    0\n",
       "sys_mod_count                   0\n",
       "made_sla                        0\n",
       "caller_id                      29\n",
       "opened_by                    4714\n",
       "opened_at                       0\n",
       "sys_created_by              49943\n",
       "sys_created_at              49943\n",
       "sys_updated_by                  0\n",
       "sys_updated_at                  0\n",
       "contact_type                    0\n",
       "location                       73\n",
       "category                       78\n",
       "subcategory                   108\n",
       "u_symptom                   32150\n",
       "cmdb_ci                    138123\n",
       "impact                          0\n",
       "urgency                         0\n",
       "priority                        0\n",
       "assignment_group            14204\n",
       "assigned_to                 27346\n",
       "knowledge                       0\n",
       "u_priority_confirmation         0\n",
       "notify                          0\n",
       "problem_id                 136271\n",
       "rfc                        137575\n",
       "vendor                     138322\n",
       "caused_by                  138543\n",
       "closed_code                   703\n",
       "resolved_by                    71\n",
       "resolved_at                     0\n",
       "closed_at                       0\n",
       "time_to_resolution              0\n",
       "reassignment_count_log          0\n",
       "sys_mod_count_log               0\n",
       "time_to_resolution_log          0\n",
       "opened_hour                     0\n",
       "opened_dayofweek                0\n",
       "opened_month                    0\n",
       "opened_weekend                  0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "df = df.copy()\n",
    "df.replace(\"?\", \"Unknown\", inplace=True)\n",
    "df.isnull().sum()\n",
    "(df == \"Unknown\").sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d7984d8-7856-4afa-a4ea-d877e59b274c",
   "metadata": {},
   "source": [
    "#### Dropping the following columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5916c91-40c1-44b5-ad16-670bd6394525",
   "metadata": {},
   "source": [
    "1. System metadata: sys_created_by, sys_created_at, sys_updated_by, sys_updated_at – not useful for prediction.\n",
    "\n",
    "2. High missing values: cmdb_ci, problem_id, rfc, vendor, caused_by – over 95% missing or \"Unknown\".\n",
    "\n",
    "3. Outcome-related: active, made_sla – could leak target info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "cb9a621a-8cd4-4f8d-98a9-c054c25b08b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "cols_to_drop = [\n",
    "    \"sys_created_by\", \"sys_created_at\", \"cmdb_ci\", \"problem_id\", \"sys_updated_by\", \"sys_updated_at\" , \"active\" , \"made_sla\",\n",
    "    \"rfc\", \"vendor\", \"caused_by\"\n",
    "]\n",
    "df.drop(columns=cols_to_drop, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6286745e-0976-43b5-a848-3ffb0e8321aa",
   "metadata": {},
   "source": [
    "##### Target-Encoding"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbad0fef-fe33-463b-97a9-855cdaba37ad",
   "metadata": {},
   "source": [
    "Target encoding is a technique where we replace categorical values with the average time_to_resolution for each category. For example, instead of using the raw caller_id, we create a new column caller_avg_resolution that stores the average time it took to resolve incidents reported by each caller. This helps the model understand patterns in resolution time without dealing with complex text labels. We applied this to several useful columns: caller_id, assigned_to, opened_by, resolved_by, u_symptom, closed_code, location, category, subcategory, and assignment_group. Each of these plays an important role in incident handling—like who reported or resolved it, what symptom or category it falls under, or where it occurred—and converting them to numeric averages makes them more suitable for regression models while preserving their predictive power."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "dea59cf2-1238-469a-9da5-738f502b33f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fallback: global average (log-transformed)\n",
    "global_avg = df[\"time_to_resolution_log\"].mean()\n",
    "\n",
    "# 1. caller_id → caller_avg_resolution\n",
    "caller_avg = df.groupby(\"caller_id\")[\"time_to_resolution_log\"].mean()\n",
    "df[\"caller_avg_resolution\"] = df[\"caller_id\"].map(caller_avg).fillna(global_avg)\n",
    "\n",
    "# 2. assigned_to → assigned_avg_resolution\n",
    "assigned_avg = df.groupby(\"assigned_to\")[\"time_to_resolution_log\"].mean()\n",
    "df[\"assigned_avg_resolution\"] = df[\"assigned_to\"].map(assigned_avg).fillna(global_avg)\n",
    "\n",
    "# 3. opened_by → opened_by_avg_resolution\n",
    "opened_by_avg = df.groupby(\"opened_by\")[\"time_to_resolution_log\"].mean()\n",
    "df[\"opened_by_avg_resolution\"] = df[\"opened_by\"].map(opened_by_avg).fillna(global_avg)\n",
    "\n",
    "# 4. resolved_by → resolved_by_avg_resolution\n",
    "resolved_avg = df.groupby(\"resolved_by\")[\"time_to_resolution_log\"].mean()\n",
    "df[\"resolved_by_avg_resolution\"] = df[\"resolved_by\"].map(resolved_avg).fillna(global_avg)\n",
    "\n",
    "# 5. u_symptom → symptom_avg_resolution\n",
    "symptom_avg = df.groupby(\"u_symptom\")[\"time_to_resolution_log\"].mean()\n",
    "df[\"symptom_avg_resolution\"] = df[\"u_symptom\"].map(symptom_avg).fillna(global_avg)\n",
    "\n",
    "# 6. closed_code → closed_code_avg_resolution\n",
    "closed_code_avg = df.groupby(\"closed_code\")[\"time_to_resolution_log\"].mean()\n",
    "df[\"closed_code_avg_resolution\"] = df[\"closed_code\"].map(closed_code_avg).fillna(global_avg)\n",
    "\n",
    "# 7. location → location_avg_resolution\n",
    "loc_avg = df.groupby(\"location\")[\"time_to_resolution_log\"].mean()\n",
    "df[\"location_avg_resolution\"] = df[\"location\"].map(loc_avg).fillna(global_avg)\n",
    "\n",
    "# 8. category → category_avg_resolution\n",
    "cat_avg = df.groupby(\"category\")[\"time_to_resolution_log\"].mean()\n",
    "df[\"category_avg_resolution\"] = df[\"category\"].map(cat_avg).fillna(global_avg)\n",
    "\n",
    "# 9. subcategory → subcategory_avg_resolution\n",
    "subcat_avg = df.groupby(\"subcategory\")[\"time_to_resolution_log\"].mean()\n",
    "df[\"subcategory_avg_resolution\"] = df[\"subcategory\"].map(subcat_avg).fillna(global_avg)\n",
    "\n",
    "# 10. assignment_group → assignment_group_avg_resolution\n",
    "assignment_avg = df.groupby(\"assignment_group\")[\"time_to_resolution_log\"].mean()\n",
    "df[\"assignment_group_avg_resolution\"] = df[\"assignment_group\"].map(assignment_avg).fillna(global_avg)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef3c6fdd-2a49-4696-835d-7290996412b0",
   "metadata": {},
   "source": [
    "##### Dropping the original columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "490f7ed3-1fd2-43f4-96a6-269d721fc5e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns=[\n",
    "    \"caller_id\", \"assigned_to\", \"opened_by\", \"resolved_by\", \"closed_at\", \"number\", \"resolved_at\", \"opened_at\",\n",
    "    \"u_symptom\", \"closed_code\", \"location\", \"category\", \"subcategory\", \"assignment_group\"], inplace=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47cc713c-b4aa-4df1-8d9b-5eccea6c7fe3",
   "metadata": {},
   "source": [
    "##### Checking if there is any missing values still left and how many columns left after dropping. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "89d3fef0-f7c3-45ea-b05e-ea56ba3fcdca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "incident_state                     0\n",
       "reassignment_count                 0\n",
       "reopen_count                       0\n",
       "sys_mod_count                      0\n",
       "contact_type                       0\n",
       "impact                             0\n",
       "urgency                            0\n",
       "priority                           0\n",
       "knowledge                          0\n",
       "u_priority_confirmation            0\n",
       "notify                             0\n",
       "time_to_resolution                 0\n",
       "reassignment_count_log             0\n",
       "sys_mod_count_log                  0\n",
       "time_to_resolution_log             0\n",
       "opened_hour                        0\n",
       "opened_dayofweek                   0\n",
       "opened_month                       0\n",
       "opened_weekend                     0\n",
       "caller_avg_resolution              0\n",
       "assigned_avg_resolution            0\n",
       "opened_by_avg_resolution           0\n",
       "resolved_by_avg_resolution         0\n",
       "symptom_avg_resolution             0\n",
       "closed_code_avg_resolution         0\n",
       "location_avg_resolution            0\n",
       "category_avg_resolution            0\n",
       "subcategory_avg_resolution         0\n",
       "assignment_group_avg_resolution    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "df.replace(\"?\", \"Unknown\", inplace=True)\n",
    "df.isnull().sum()\n",
    "(df == \"Unknown\").sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "93488637-b399-4eaa-ad34-a4791b4519c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>incident_state</th>\n",
       "      <th>reassignment_count</th>\n",
       "      <th>reopen_count</th>\n",
       "      <th>sys_mod_count</th>\n",
       "      <th>contact_type</th>\n",
       "      <th>impact</th>\n",
       "      <th>urgency</th>\n",
       "      <th>priority</th>\n",
       "      <th>knowledge</th>\n",
       "      <th>u_priority_confirmation</th>\n",
       "      <th>...</th>\n",
       "      <th>caller_avg_resolution</th>\n",
       "      <th>assigned_avg_resolution</th>\n",
       "      <th>opened_by_avg_resolution</th>\n",
       "      <th>resolved_by_avg_resolution</th>\n",
       "      <th>symptom_avg_resolution</th>\n",
       "      <th>closed_code_avg_resolution</th>\n",
       "      <th>location_avg_resolution</th>\n",
       "      <th>category_avg_resolution</th>\n",
       "      <th>subcategory_avg_resolution</th>\n",
       "      <th>assignment_group_avg_resolution</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>New</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Phone</td>\n",
       "      <td>2 - Medium</td>\n",
       "      <td>2 - Medium</td>\n",
       "      <td>3 - Moderate</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>2.616784</td>\n",
       "      <td>4.046472</td>\n",
       "      <td>3.635469</td>\n",
       "      <td>2.165793</td>\n",
       "      <td>4.321872</td>\n",
       "      <td>4.242421</td>\n",
       "      <td>3.863401</td>\n",
       "      <td>4.837026</td>\n",
       "      <td>3.804956</td>\n",
       "      <td>3.887123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Resolved</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Phone</td>\n",
       "      <td>2 - Medium</td>\n",
       "      <td>2 - Medium</td>\n",
       "      <td>3 - Moderate</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>2.616784</td>\n",
       "      <td>4.046472</td>\n",
       "      <td>3.635469</td>\n",
       "      <td>2.165793</td>\n",
       "      <td>4.321872</td>\n",
       "      <td>4.242421</td>\n",
       "      <td>3.863401</td>\n",
       "      <td>4.837026</td>\n",
       "      <td>3.804956</td>\n",
       "      <td>3.887123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Resolved</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Phone</td>\n",
       "      <td>2 - Medium</td>\n",
       "      <td>2 - Medium</td>\n",
       "      <td>3 - Moderate</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>2.616784</td>\n",
       "      <td>4.046472</td>\n",
       "      <td>3.635469</td>\n",
       "      <td>2.165793</td>\n",
       "      <td>4.321872</td>\n",
       "      <td>4.242421</td>\n",
       "      <td>3.863401</td>\n",
       "      <td>4.837026</td>\n",
       "      <td>3.804956</td>\n",
       "      <td>3.887123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Closed</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Phone</td>\n",
       "      <td>2 - Medium</td>\n",
       "      <td>2 - Medium</td>\n",
       "      <td>3 - Moderate</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>2.616784</td>\n",
       "      <td>4.046472</td>\n",
       "      <td>3.635469</td>\n",
       "      <td>2.165793</td>\n",
       "      <td>4.321872</td>\n",
       "      <td>4.242421</td>\n",
       "      <td>3.863401</td>\n",
       "      <td>4.837026</td>\n",
       "      <td>3.804956</td>\n",
       "      <td>3.887123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>New</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Phone</td>\n",
       "      <td>2 - Medium</td>\n",
       "      <td>2 - Medium</td>\n",
       "      <td>3 - Moderate</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>2.616784</td>\n",
       "      <td>4.289880</td>\n",
       "      <td>4.281948</td>\n",
       "      <td>4.247796</td>\n",
       "      <td>4.018764</td>\n",
       "      <td>4.242421</td>\n",
       "      <td>3.510381</td>\n",
       "      <td>4.467554</td>\n",
       "      <td>4.503122</td>\n",
       "      <td>2.502225</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  incident_state  reassignment_count  reopen_count  sys_mod_count  \\\n",
       "0            New                   0             0            0.0   \n",
       "1       Resolved                   0             0            2.0   \n",
       "2       Resolved                   0             0            3.0   \n",
       "3         Closed                   0             0            4.0   \n",
       "4            New                   0             0            0.0   \n",
       "\n",
       "  contact_type      impact     urgency      priority  knowledge  \\\n",
       "0        Phone  2 - Medium  2 - Medium  3 - Moderate       True   \n",
       "1        Phone  2 - Medium  2 - Medium  3 - Moderate       True   \n",
       "2        Phone  2 - Medium  2 - Medium  3 - Moderate       True   \n",
       "3        Phone  2 - Medium  2 - Medium  3 - Moderate       True   \n",
       "4        Phone  2 - Medium  2 - Medium  3 - Moderate       True   \n",
       "\n",
       "   u_priority_confirmation  ... caller_avg_resolution  \\\n",
       "0                    False  ...              2.616784   \n",
       "1                    False  ...              2.616784   \n",
       "2                    False  ...              2.616784   \n",
       "3                    False  ...              2.616784   \n",
       "4                    False  ...              2.616784   \n",
       "\n",
       "   assigned_avg_resolution  opened_by_avg_resolution  \\\n",
       "0                 4.046472                  3.635469   \n",
       "1                 4.046472                  3.635469   \n",
       "2                 4.046472                  3.635469   \n",
       "3                 4.046472                  3.635469   \n",
       "4                 4.289880                  4.281948   \n",
       "\n",
       "   resolved_by_avg_resolution  symptom_avg_resolution  \\\n",
       "0                    2.165793                4.321872   \n",
       "1                    2.165793                4.321872   \n",
       "2                    2.165793                4.321872   \n",
       "3                    2.165793                4.321872   \n",
       "4                    4.247796                4.018764   \n",
       "\n",
       "   closed_code_avg_resolution  location_avg_resolution  \\\n",
       "0                    4.242421                 3.863401   \n",
       "1                    4.242421                 3.863401   \n",
       "2                    4.242421                 3.863401   \n",
       "3                    4.242421                 3.863401   \n",
       "4                    4.242421                 3.510381   \n",
       "\n",
       "   category_avg_resolution  subcategory_avg_resolution  \\\n",
       "0                 4.837026                    3.804956   \n",
       "1                 4.837026                    3.804956   \n",
       "2                 4.837026                    3.804956   \n",
       "3                 4.837026                    3.804956   \n",
       "4                 4.467554                    4.503122   \n",
       "\n",
       "   assignment_group_avg_resolution  \n",
       "0                         3.887123  \n",
       "1                         3.887123  \n",
       "2                         3.887123  \n",
       "3                         3.887123  \n",
       "4                         2.502225  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c1d9b39-9ac1-4f85-87e6-347ed46c44d1",
   "metadata": {},
   "source": [
    "#### cor-relation between variables"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84b7284f-2e3e-45d8-ab8e-260005d1227e",
   "metadata": {},
   "source": [
    "##### correlation between numeric variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "0f180f9d-fb47-4338-b28b-eee7660f1f88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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56mXBoVUMwzAMwzAMwzAMwzwXBkb/jdCqVq1aQSqVav1+6dKlGpe5ePEiXhXskcMwDMMwDMMwDMMwDFNJYCGHYRiGYRiGYRiGYRimksChVQzDMAzDMAzDMAzDPBcSY/YTeVXwSDMMwzAMwzAMwzAMw1QSWMhhGIZhGIZhGIZhGIapJLCQwzwzfn5++PXXX/9tMxiGYRiGYRiGYRg9qFqlj9N/Ec6RwzwzZ8+ehaWlJf4rDBkyBOnp6di0aRMqE1999ZWw+dKlS8/dl0Oz+giYMBy2dcNg5uGCc33HIGHLft3LtGiIkJmfwiqkKvKj4nD3+98RvXyjWhvf0YMQ8NFwmLo5I/PKTUSM/x8yzl6tkE1Xjq3EhQOLkJuVDCePYLToMwVuvjU1tk2Ju4PTu2YjMSoCWWmxaN5rMmq3fFutzbl9f+Lelb1IS7wPI2MzuPnVQdPuE2DvElAhe1afu4VlJyOQkp2Haq72mNSxIWp4Omltn5lfiN8OXsSBW1HIyCuAu60lPunQAM0DPcX3nedsQFxGzhPL9a9XDZ91bqTTlj3b12PrhpXISEuFj38ghoz8CIHVQjS2PXPiEDatXY6EuGiUFBfDzcMbXXsNQPM2nRVt1q1aiJNH9iElORFGRsbwDwzC64NHIjAotNxx8XzjdXiPeBsmzk7IuXkbt7+ejqwr1zS2lRgZwXfUcLj17g4TVxfk3Y/EvR9/RerRE2rt6Lsqn4yHY4umMDA3Q97DKNz89EtkXbterj2rT17DsqOXkEzbyc0Rn3ZvihrerlrbZ+YV4Lc9Z7D/+gNk5ObD3c4aE7s1QfMg3yfaLjp8EbN3n8YbTWpgYrem5dqyZes2rFu/HmlpaQjw98eY0aMQFBRU7nKHDh/G9Bk/ILxxY0z98gvF/GPHj2PHjp24c/cusrKyMHfObFSpUgUVJTzEEC1qGcHaXIK4VCk2Hy9EdJL2Eps1/A3QoYEx7K0kSM6UYufpItyKKhXfGUiAjg2MEORjCEdrCfILgTsxJdh5pghZuRWzp2tTMzStYQJzUwnuxxZj9d48JKXL+tdGi9omaNfADDaWEsQkleCf/Xl4GF8ivrMwk6BrEzNU9zOCvbUBsvOkuHK3CFuP5Qn7yuP1TnZoG24NSzMD3IwswIK1yYhPLtbavnqAGXq0sUWAlwkcbI3ww6IEnL2W+9z9Ej1amKN5bTNYmEpwN7oIK3flIDFN99i0qmeKjo3MYWtlgKiEYvy9JxeRcZp/Z9zr1qhRxQRz12Xi0u0irX0e3LkaezcvQ0Z6Crz8qmHA8Enwr1pDY9uje9fj1OFtiH10V3z2CQhBrzfeU2ufn5eLjX/NwqUzB5GTnQEnF0+07jIQLTv2Q0U4d3AlTu1ZhOyMJLh6BaPDwC/g6a/5upAUeweHN89G/KMIZKTEoH3/yWjYboham98mtxHflaVeq0HoNGiqTlsiTq7ElSOLkZedDAe3YDTp8TlcvDXbQty/ugvn9s5GdloMbBx90bDTBPgEt1R8T9e6M7t+Qsyd4yjIz4K7X33Rp62TXwVGBji9byWO7VyM7IxkuPkEo+ubn8MrQLM9CTF3cGDDHMRGRiA9JRadB36KJh3Vr5kFeTnYv2EWrl/Yh5zMVLj7VkeXQZ/BK0Dz9lfl4uGVOLtvEXIyk+DsGYy2/b+Au59mW5Jj7+D49tlIeBSBzNQYtO47GfXaDNG+nnvm4+jmn1C39Vto89rnqAh1AyVoFCSBlRmQmA7suViKuFTt7YO9gBZhBrC1BFKzgENXSnEvXvm9sRHQuoYEVT0lMDcB6FJ+7q4UF+9pP5/KuXp8JS4dkt3bOLoHo3nvKXD10Tw2qfF3cGb3bCRFy+5tmvaYjFot1LdT7L2zuHhoEZJiIpCbmYROQ35DQFi7Co1LvUAJGleXjUsCjcv5UsTqGhdvoGUNA9g9HpcDl0txL075/ecDDDUut/9SKU7dlFaq+z4615zc/fhc4x2MjrrONTF3cHjLbMQ9fHyueX0yGpU518z5VPu5pvMbus81DFMW9sipxBQWVuCO9CXi7OwMCwuLf9UG5sViaGmBzCu3cG3ctAq1N/fzQoMtfyLl0Gkcq98TD+YsQ40/v4FT+2aKNu79OqP6j5Nx55u5ONawN7Ku3ESj7Ytg4uxQbv+3L+7A0U3T0bDjWAyYsAFOHkHY8ucI5GalaGxfXJQPG0dvNOk2ARbWzhrbxNw7i5rNBqHfB2vQc9RilJYUY/MfI1BUUP5T5+6ISPy09xxGNq+Jv0d0FULOmL/3IzUnT2P7opISjFq5D7EZOfixbwtsGt0TX3YNh4u1uaLNymFdsG/8a4rpj0GyG6/21Z8UEFQ5eXQfViycjb4Dh+G7X5fA1z8Q07/8EBnpmu++rKxt0Lv/2/j6x/mYMWc5Wrbrgj9mfYfLF04p2rh7+GDIqAmY8dsKTJ3xO5xd3PHdl+ORmZGm0xaXLh0R+NnHiPztT5zrNQDZN26h1uLfYeygeRv7f/gePF5/TYg9Zzr3RszqtQib9wusQoIVbYxsrFF39VJIi4txecRYnOncB3en/4SizEyUx64rdzFzxwmMbFsfq8f2RZC7I0Yv2S7EN00UFZdg1OJtiE3PwsxB7bH5owGY2rslXGyeFKqvRSdi3ZnrQhyqCIcPH8GCBQvw5qBB+G3ObAQE+OPzL74QorEu4hMSsHDhIoSFPimi5ecXIDQ0BMOGDsXTUjPAEN3CjbH/fDFmbyhAXEophncxhaWZ5va+rgYY2NYEZ2+WiPbXI0vwVgcTuNrL3m6ZGAGeTgY4cKEYszYUYMXeAjjbGWBIR9MK2dO+oSla1THF6r25+HFlFgqLgPdes4SR5ucAQd0gY/RpZY4dJ/MxfUUWohNLxDJWFjKbbK0kYtpwKA/fLs3Cip25QtR5s1P516uebWzRuYUN5q9NweRfY1FQUIopo9xgrONtnqmJBA9jCrFofcoL7bdTYzO0rW+Gv3Zm47ulGWJsxg+w0Tk29auboH9bSyFa/W9xhhib8QOsYf14bFQhIQzlP1Ph7PHdWLf0J3TtPxKf//g3vHyrYfb/xiAzQ/O55nbEOTRo1gkfTVuASd8th72TK2Z9PRppKQmKNmuXzkTEpRMY9sG3+GrWBrTpOgirF07H5bOHyrXn+tkd2Lf2ezTvNhbDp2yEi3cwVs8ajpxMzeNfVJgHe2cvtO49AZY2mq8LQz9bhw9+PKaYBo1fIuZXr9dJpy33ruzAqe0zULftWPR+bz0c3YOwc/E7yMvWbEvCw4s4sPpjBNXvi97vb4BfSFvs/et9pMbfFt9LpVLsXfEeslKj0GHwXPR5fwOs7D2wY9EwFBWWf426enoHdq6egda9xmL0tPVw8w7CspnvIFvb2BTkw97ZG+37fQQrW80vJDYtmYK7ESfw2rsz8N43mxEY2hRLfxyGzDTl9tTEzfM7cGjD9wjvMhaDP90IF69grPttOHK0XL+LivJg6+iFFj21byc5cQ+v4PKx1XD2LF8Ql1PdW4K2tSQ4FiHF4r2lSEiX4vUWBrDQcqrydAR6NjbA5QdSLN5TijuxUvRtagAnG2Ub6i/ATYKtp0uxYFcpzt6RokMdCQI9dNty59IOHN8yHfXbj0W/8bJ7m20LtN/bFBXmw8bBG427aL+3of1ciB69v8TTQOPSro4ER69JsWh3KRLTpRjQSve49A43wOX7UizcXYrbMVL0a2YAZ1tlm183lahNND60b9+Mklaq+76Iszuw95/v0bz7WIz4YqMQjf/+Vfe5xs7JC236TICVrWZbhn2+DuNnHlNMgz58fK6pr/tcwzCaYCGnEtGqVSu89957GD9+PJycnNCxY0dcu3YNnTt3hpWVFVxdXTF48GAkJycrltm1axeaNWsGOzs7ODo6olu3brh3756aGER9uru7w8zMDL6+vvj+++/Fd3TSJW8PHx8fmJqawsPDA+PGjdMaWnXz5k3xW9RPSEgI9u3bB4lEovBwiYyMFJ83bNiA1q1bCxGoVq1aOHnypKKPpUuXClu3bdsm3lhTm9deew25ublYtmyZ+E17e3thR0mJ7O0rUVBQgI8//hienp7CS6hRo0Y4dOjQE/3u3r0b1atXF+PVqVMnxMXJXiHQelL/mzdvFjbSpLq8NqKjozFw4EA4ODiI361fvz5Onz6t+P73338Xb8pNTEzE+qxYsULxnXw8VD1p6OFO9bfpL33ev3+/6JvGo0mTJrh165ZivaZNm4bLly8r7KZ5z0rS7iO4PfVXJGzeV6H2vu8OQN6DaNyYOAPZN+/j4byViF+/G/4fKN9A+I8fiqhF/yB62QZk37iHq2OmoiQ3H95D+pbb/6VDSxEa3g8hjfrCwS0QrftNg5GJGa6fXq+xvatPDTTrMRHV6naFoZGxxjY9Ry5E9YZ94OheVbwhbD/oe/EWJzE6olx7Vpy+jj51qqJX7UBUcbbDlC6NYWZsiE2XlMeUKjSfPD1+6dcKdbxd4Glnhfq+rghyVQocDpZmcLIyV0xH7kbD295atNPF9k2r0aZjD7Rq1w1ePv4YPmYiTExNcWjvNo3tQ2rURYPwlvD09oOruxc693gdPn5VcOv6FUWbpq06oEbtBnB184S3bwDeHDEOebk5eBSpef3keA8bjNg1GxC/fjNy797HrS+/QWlePtxf66WxvVvPrnj4x0KkHj6G/KgYxK5ai5TDx+A97C1FG593h6EgLkHmgXPlGvKjY5B27CTyH0WjPFYcu4I+DaqjV71gVHF1wJSeLWBmYoRN529qbL/x/E3hLfXLmx1Rx9cdnvY2qB/ggSB39Qeb3IIiTF6zX4g8NvT6tQJs2LhRnGs6dGgPXx8fvP/eezA1NcPuPXu0LkPnth9++BFvvvkG3Nzdnvi+Xds2eGPQINSpUxtPS/OaRjhzswTnbpeIG/aNR4tQVAw0CNLsoNs0zBC3o0px5EqxaL/nXDFik6VoEiprn18ELNxRiCv3S5CcIcWjRJmHj5czva0t35W5dV1T7DqVjyv3qN9SLNuRIzxJagVqPn6JtvVNceJqIU5dK0R8Sqnw4CGRIzxMtk3ikkuxcEsurt0vRnJGKW5HFWPrsXyEBRgLDyJddG1pg/V70nHuWi4exRXht1VJsLcxRIMa2kWgSzfzsHpnGs5czX2h/bZtaI7tx/Nw+U6R8DpavDUbdtYGqBOkfd9r39AMRy8V4MSVAsQll+CvnTkoLAaa1lJ/KvN2MUSHRmZYuj1b94AA2Ld1BZq164OmbXrBw7sK3hg5BSamZjixX7P36vDx36NVp9fh7R8MNy9/vDV6quwh7uoZRZv7ty4jvFV3BIU1EN44LTq8Jjx9HtzR7MWnyum9S1C7WX/UatoXzh6B6PKG7Lpw+bjm64KHX020fW0SQht2hZGx5rGztHYQD17y6c7Vg7B39oFPtYY6bbl6dBmCG/RDUP0+sHcNRLNeXwlbbp3boLH9tePL4VW1GWq1GA57lyqo3+EDOHlUR8TJVeL7jORIJEZdRtNeU+HsXQN2zv5o1nMqiosKcO/y9nLH5sTuZajfsh/qNu8DF89AdH/7KxibmOHCEc32kFdNpwGfoGbjrjAyMtEoIFw/txcd+38Mv6AGcHT1RZve78HRxQdnDvyt05Zz+5egRpP+qBHeF07ugWg/YJqw5dpJzdvJ3bcmWvWZhOD6dP3Wvo8X5udgx9JP0HHQNzC1UFEPyqFhNYkQH65GSpGSCew6L0VxMVDTX/NJoX5VCe7HA6dvSZGSBRy5JkV8OlCvqrK9l5MEVx9K8SgJyMgFLt2XCo8WDwfdJ5rLh5cipFE/VG8ou7dp2Xea8BS5eVb7vU2T7hNRtY72exvf6i3QqPN4BNRoj6ehUbAEl+5JceWBFMmZwI6zsnGpFaB5HRoGSYT3DXnW0DgevipFfJpsvOTk5KtP1TwliEwE0p90Ptbr+z4619Rp3h+15eeaN2X78CVt5xr/mmjXT3au0bYPlz3X3L0iO9f4lnOuqUxIjCV6Of0XYSGnkkFiA4kCx48fx/Tp09GmTRvUqVMH586dE6JNQkIC+vfvr2ifk5ODjz76SHxPYoCBgQF69+6N0lKZa/bs2bOxZcsW/PPPP0IcWLlypRBLiPXr1+OXX37Bn3/+iTt37ghBpkaNGlofPHr16iWEBhIy5s+fj88/1+zqSvNJdCEBo1q1akIIKaarxmNItCG7Vq9eLdaJxAyyeceOHWIiMYRsWrdunWIZEqNIEKJlrly5gn79+omHJ7Jbtd+ZM2eK5Y8cOYJHjx4JOwj6S+MmF3doIsFEF9nZ2WjZsiViYmLEGJKYMnHiRMXYbty4ER988AEmTJggBLeRI0di6NChOHjwYIW2ddkx++mnn8R2NDIywrBhw8T8119/XfQfGhqqsJvmvSrsGtdG8gGlEEck7T0G+8ayB0yJsTFs64Yieb9KyIxUiuQDJ2DXuI7OvkuKC8VF1ruacjtIDAzgXTUc8Q+fP4xMTkFelvhrVs4NIXnX3IhLRSN/5YO1gUSCRn7uuBKTpHGZQ7ejUNPLGd/vOo02v6xF3z+3YOGxqyh5vI9o+o0dVx+gZ60qQpTTRnFRER7cvYWwWvWVthgYIKx2A9y5Vf6DED1UXbt8DnExjxAcWlvrbxzYtRkWllbw8QvU2pfE2AhWodWRduKU2jZOPXEKNnU0ux8bmJigtEDdo7A0vwC29ZS2OLVtiaxrEQid/SOanjqI+pvXwL1/n3LXjbxrbsQmoXGgl/L3DCRoXMULVx5pfoN8+EYkavq44vstx9D622Xo8+saLDx04Ynt9N2Wo2gR7KPWt05biopE+FOd2rXVthN9vnFTs6hErPr7byE8d+rYES8SQwPynpHgTrRSBKf3o3djSuDjaqDVI4e+V+V2tPb2hJmJBKVSKfIKdb99dbQ1EKLNrYfK8z+FPkXGlcDfw0jrOni7GuKmyjL0KzcfFSNAyzIEhW3lF0pRqsMkF0cj2NsY4ertfMW83Hwp7j4sQJBfxTyMXlS/TnYGsLMywI0HynCnvAKpCD0L8NQ+Nr7uRrgRqTy2aHVvPChEFU/lAw55UY3oZYWVu3OQmaN7G9F54NG9G6hes5HaPhxcsxHu31aKwLooLMxHSUkxLK2U59iAoFrC+4a8dOh8dOvqWSTEPkRIrfByrwtxjyLgX139ukCfo+9fxIuAfuPaqS1CKNJ1HqZ2ybER8AwMV7PFs0o4Eh9pvkYlPLqs1p4gYUfevrREtr2NjEzV+qSHwvjICzrtLi4uFCFSASHhatuqSmg4ou492zWztKQEpaUlMDJR30/pwfrh7Qs6xyYhKgK+werbySe4CWKfczvt++drBIS2VOu7PAwMADd74EGC+v4emSiFp6PmbUzzI8u0fxCv3j46WYqqHhJYPXay9XEGHKxl7XSNDYU/eZW5t/F6wfc2FR0Xdw3jQp+9dIxL2fb3y4yLKpamEB5KJKKVhz7d94lzzcMnzzV+1Zsg5t6LO9dcPV3+uYZhtME5cioZVatWxQ8//CD+/+abb4SI89133ym+X7x4Mby9vXH79m0hkvTtq+71QN9TSNT169cRFhYmxAzqkzxp6CRCHjly6Ds3Nze0a9cOxsbGwjOnYUPNivHevXuFpw+JLrQM8e2336J9+yffDJBo0rVrV/E/eZOQCHH37l0EBwcrHn7kniwEeeSQ+EIiFXnSkLcPefSQIEKiBdm5ZMkS8Ze8huS/QSIQzZePD/X7xx9/KPol8efrr78W/1O/5ubmwrNHbn95rFq1CklJSSJXEHnkEIGBygdeEo0o786YMWPEZxLUTp06JeaT/U8DjSWJRsSnn34qxi8/P1/YTLaTuFOe3bRuNKlSJC2FseTZ9VxTVycUJCSr/05CMoxtrWFgZgpje1sYGBmhIFHdDbUgIQWWQbpjk/Ny0iAtLYGFtXoIi4W1E9ISH+BFIC0txdFN38Hdvy4c3avpbJuWW4ASqRSOlsqwKMLRygyRKRkal4lJz8bZyHh0CfPHbwPaICo1C9/tOo3i0lKMalHrifaURycrvxA9aunOd5KZmS5urm3t1UOXbO0cEBv9UOtyuTnZGDOkJ4qLCmFgYIihoz9GzTrqx/SFM8cx+8cvUViQDzt7R3z29a+wsbXT2qexvb3YxoXJ6tu4KCUFllX8NS6TeuyE8OJJP3seeY+iYN+kEZw7tIHEUBkzYubtBY9B/RG9eAUe/rEI1jVCUfWLSZAWFSF+41at9qTl5qOkVApH+Z31Y+jzgyTN4UzRqVmIvR+LLrWqYu6QLniUkoHvNh9FcUkpRrWViWU7L9/FjdhkrBpTvpgkJzMzUwi7dvbq40ciTVRUlMZlrkVEYPfuPZj72xy8aCzM6GFfgrIRZll5UhEOpQkrcwmyNLSn/DqaoLCfzg2NcfluCQq0p1wRUH4bIjNXXTDLyi1VfKfJHlqHrJwyy+SUws1B8y2NpbkEncPNcPyK7nBkO2vZ/peerS5c0Wf5d8/Cs/RraynbHpka1lP+XVkotIzGpqw4Q5/dVB6y+re3xL3oYuHpUx7ZWWniXGNtp34etrF1RHxMJCrChhW/wtbeWU0MGjDiU/z1x9f49N2OMDA0EqL4m6O/RLXQejr7ys2WXRcsbdTtsbR2RErcfbwIbl3ah/y8LNRs0ltnu/zcdGGLuZW6LebWjkhP0nyNojw65lbqnn60PM0nyAPHys4dZ3b/gua9v4KRsTmuHl+GnIx45GZpfmEgJzdLdl2wslW3x8rGEclxz3bNNDW3hHdgbRza/Duc3auIvq+c2o6ou5fg4Oqjdbk8+XYqc/2mz6nxz76dbp7bjsSo63hzovJFXkWwMJEJ+rnqt0DCW8TRWvMylC+Gvi/bnubL2XtRis71gfe7G4rrjlQK7DwnRZT6bZEa+fJ7myf2mxd3b/O046JpPR1VQsgqMi5lbo0U1PCXCI/JioRV6dN9n7ZzDR1PKc+xD6ty6+I+5OdmoVZT3ecahtEGCzmVjHr1lDc55AFCYgY9yJeFRBUScsgj5csvvxReMhRyJfcWIdGDhBwSGkhsobAf8kah0KsOHTqINuTVQqFTAQEB4rsuXbqge/fuQjQoC3nzkICkKiZoE31q1lS+paeQLiIxMVEh5JBXj2riTgoZIy8h1fWkebQMcfXqVeERROurCokWFE4mp2y/9NvyPp4F8igiIU0u4pTlxo0bePfdd9XmNW3aFLNmzXrq39I2ZiSuVRQKmSPhTJWBEge8Yag9Ue9/nUPrvxaJ8l4bJ3Nrf9GQVwKFTn3RtTEMDQwQ4u6IxKxcLDt1XaOQs+nSXTQN9ICL9cvJPWVmboHps5YhPz9XeOT8tWg2XN08RNiVnJCadUWbrMx0HNizBbNmfIH//bRAiEQvijvf/ICgb75Eo92bxNt4CpeKW79ZLRRLIjEQHjn3f5YJGtnXb8KqWiA8BvbTKeQ8+3Yyx5e9W8i2k6czEjNzsOzoZSHkxKdn44dtx/HnsG4wpeyWLwnyGvxx5k/4YNw42NpWPGRAX6CwpTfamYBeLG489qRI0KC6MQa2V+7b8zaUH9bzvJiZAGP6WCIupQTbT6g/fTSra4mR/ZXnv+8X6M758TJpFGqCNzsrr3Fz/ik/F9SzUKuqMYJ9jfG/RbpzNL0odm1YLHLsTJi2EMYqXh0Hd/yNB7evYsyns+Do7I471y/g7wXfw44En1qN8W9y+dh6VAlrAWs73eGtLwMDQ2O0e3MOjqyfguVfN4bEwFB4+HhXa16RdEYvBcqNs3HR5/jxw5biBYC7bwhqNO4qvH9eJZlpcTiw7lv0e38xjIyf3UPuRUJhVhRGtfZoiQit8nGWoENdEsulIpSIkYVoXXsoRYnuHO3/mfu+p+HSsfUI/JfONS+T/2qFKH2EhZxKhmqVKArtIWFlxowZT7STP+zT9+RlQ8k2yVuFhBwScOSJkuvWrYsHDx5g586dIqcNhReRBw6FLZEwQwINzSePG/Is+fHHH3H48GHhofOsqC4rdyWUC0xlv5e30TRPvgyNg6GhIc6fPy/+qqIq/mjqgx4inxXyhnkeyOWZULWBvIaeZcwqwuTJk4VXkCoHHHS//SwP8r4hrxxV6HNRRpYIlSlMTkNpcTFMXdTfaJi6OqIgPln3+Frai5vYsgnuqIqBhY3TC7mYR14/hD7v/QUru/K9sOwtTGEokSClTGLjlOx8kdtGE85W5jAit/jH25rwd7IVlZQojMpYZX+NTc/G6Qfx+Ok1ZfUSbdjY2IkbaqpWpQolOrYr46VTdp9z85CFBfkFVENs1ENsXrtcTcgxMzMXbWiqGhyGD9/tj4N7t6FXP2X+GlWK0mTb2MRJfRsbOzqiIEnzNi5KTcO1MR+KECsjezsUJiQi4JPxIl+OnMKkJOTcVX/rlXPvPpw76K7CYW9hJrwSyiY2ps9OWgQyZ2sLGBmqb6cAZ3skZ+WKUK3rsUkiofWAucq3wPT29XxkHFafuoazX7+jtqwcGxsbMebpaeoPzZQLy97B/on2FBpJnodTVQRX+fmhS7fuWLhgPjwen9ufhdx8md1ld1fyrsnK1XwupAcSa03t86QaRRw7KwkWbCvQ6I1DlaMi42Qu7YQ8aa+NhQEyc5TeKtYWBiJJrzZ7aB2shVeKyjKW1Ie6TabGwNi+ViKkav6mHJQ9ZZ6LyMXdmcp9zujxzaedlSHSM5V90+fI2GcvLpCeVVJuv5fuFOJ+rHI/MTaU2WJjaYAM1bGxlFWi0kR2rmxsynoz0Wf52JCI42xvgFkT1M8To/tY405UMWauVBeQrKztxbkmK139PJyZkQJbO93n4T2bl2HXxsUYP/VPkf9GDnn7bVo1B6Mn/owa9VqIefR9VOQt7NmyXKeQY2Eluy6UTTZKCXQttSTrfRqomsyDGyfQd3T5HnFmFnbClrKJjfOyUoQHgSbIG0fufaNon52i5qXj7BmKvuM2ojA/CyXFRTC3csCmua/D2Ut39UALa9l1ITtD3R5KdKwtkXFFcHDxwfDJK1BYkIuCvGxY27lgzbwP4eCsPcTUXL6dsjRsp2e8flM1K7ofWD5d6RVJHhPRd8+K6lgfzroq1l8TuYV0zyR9IoEvJXnPLuNdIofml00Cr9qezl+twiRYf0JZsSkpQwoXO6BRkAEiEzXfo5nJ722e2G9ezL3N0yAfF03rqaWGg9Zx0dTe2xlwspFg44mK3a/q032ftnONOJ5egC3pj881r4158d63zP8fOEdOJYZEmIiICOGtQiE9qhMJPikpKUKImTJlCtq2bSuS/FL5W00PGxSiRGLPmjVrRG6c1NRUhVhBYhDlrKGwKcpDQx4wZSGPHgoVoIcQORRy9CogrxjyyCEPlbLjUNEwKYJyD6kmUK6Ilwx55cjHqiw03pTLSBX6TKFhBIW4EfKEy8SzlBCvqN2UsJq2ter0PGFVRPqpS3Bso37T7dS2CdJOydaDwmAyLkTAqY1KTgCJBI6tw5F+SneMMeUEcPEKRfTtk2ousVF3TsHN9+mTvCr6kErFxfz+1X3oPWapqJJREUh0qe7ugDMP4tU8Oc5ExqOmp+bqBLW8XPAoLUu0k/MwNVMIPKoiDrH58j3hvdO8qqwsuS6MjGWlwa9dOa+0pbQUEZfPoWpQWIXWR2Z/qVbxULUNhWJpQ1pUjOyIG7APVymVLpGIcKnMi7pzaJQWFgoRh8qRO3dsi+R9yvxRGRcuwcJfvdyuhZ8v8mNjdfZpbGSI6h7OOH1X+YBON6qn78WIPDiaqO3rhqiUDNFOzsPkdCHwUH+Nqnhi3bj+WPNeP8UU6uksQrHof00ijrDF2BhVAwNx6fIlte1Ex3n1xx6IqpB4/se8uZj32xzF1LhRI9SqWVP87+z0fDeP9EY0JlmKQE/lvkeP/IEehniUoPlG+2FCKaqotCeqehqotZeLOE62EizcXvBE+IIcEneorLh8oopZGdmlCPI1UvOg8XM3xIPYYq3rEJVQgiAfI7V1oM+UP0a1n/f6WaG4FPhjYw6KNZwi8wukovy3fIqOL0JaZjHCqpmp5dYJ9DXFrUgtK1UBElOKy+2XUkYlpZUqptjkEqRnlyLYz1gt9xDlAbofo31sHsYVo7rKMjQ29PlejOw433kyD9MWZuDrRcqJWLMvF0u3ZWs81/hUqY4bKomKaR++eeUMAqppL7G9e9MSbF+3AOO+mAe/QHUBgvLllBQXC687VUj0lEpLy70uuPuEIvKm+nUh8sZJeAXozrtWES4f3yDCOqrWaFVuW7LFySMUMfdOqdkSe+8UXHw0X6NcfWqJ71WJvntCY3sTM2sh4lAC5OSYa/Ct3lanPZSs2MMvFPevn1LbVvTZu8qzXzMV9phaCBEnLycDd68eR3DdtjrHxtU7FI9uqW8n+uzxjNvJN6gx3v58K96avEkxufqEIaR+d/G/NhGHIBGXEvL6uaqLnL4uEsSkaBaxab5vmfa0vLw9nfcMDemFoPpy9FlXuhMaGxLrYu6oj0303ee7t3kWaFziNIwLfY7WMS7+Zdr7u2keR/LGiUuVilLvFUGf7vvEucY3FA9uPHmu8azyYs41FLZVkXMNw2iDPXIqMWPHjhXiCyULpiS7FOJDuWYo4e/ChQtFdScKLaLEw+ShQ+FUlF9FlZ9//ll8R2II3UStXbtWiB+Uw4GqH5FAQBWgKCzpr7/+EsKOah4dORSeRWFLb7/9tsjhk5WVJQQk4mUn8KKQqjfeeANvvfWWSAhM60K5ayi5M4kt8nw85UGCGFW1IvGLxo1CG3R5HtG4U/4dSvJMYUs0jhcvXhSeT+Hh4fjkk0+EhxPZQ15OW7duFRW7yMOJoLFs3LixSFrt7+8vhCj5mD0NZDd5VdHDoZeXF6ytrYVo86zlxy0DleFaFv5esKkVjMLUDORHxSHom49g5umKy0Mnie8fzl8N3zFvIPj7TxC1dD2cWjcW5cbP9hip6OPBr0tQa/EMpJ+/hoyzV+A37m0YWZojapnmKhqq1G41BPtWfQoX7zC4+tbEpcPLUFyYh5BGsjdye1ZOgpWtiyg7KU8cl5pwT5E0MjsjAUkxN2BsYgE7Z9l+e3j917h1fhu6DZ8LY1NL5GTK8g6YmlmLBI66GNwoBF9sOS5CpMI8nbDy9A3kFRWL5MTElM3HRWnxcW1kHi7961XDmnO38MPusxjYIFiIOIuOXxP/q0JCz5bL99C9ZoDw4KkIXXsNwO+/fIOAwGAEVgvBzs1rUJCfj5btuonv5/38NewdnTHw7dHi86a1y0VbV3dPkcD04rkTOHZwF4aN/kR8n5+fh03/LEO9hs1g5+CIrMwM7Nm+HmkpyWjUtI1OW6IWr0DwD/8ToVCZV67Ba8ibMDQ3R9x6WVWb6j98g4KERNz/abb4bFOrBkxcXZB94yZMXV3g//5okUTw0QJlxbWoJX+h7ppl8B01HIk79sC6VpgoWX7rC1leK53bqVlNfLHuIEK9nBHm5YK/jl9BXmERetWVlar9fO0BUVr8g44y8al/o1DhWTNj23EMbBKGR8kZWHjoIgY1kYlilqYmqOqm7sFgbmIEOwuzJ+aXpU/v3pj5888iF1lQtWrYuHkz8gvy0eFx/jAKpaLzzbChQ4QoK082L8fSSuaFqTqfzq90vkh5LCJHR8tEKzrnawv1lHP0SjH6tzJGdFKpmJrVMAKd5s7dlokD9B15b+w6K/t8/FoJRnY3QfMaRrj5qAS1Ag3h6WyA9UcLFA8zb7Y3EUmUl+4qFA8wco+fvAKZuKCLgxcK0KmxKRLTSpCSUYpuTc2FuHP5rlJgHNfPUnw+fFEmKO4/V4C3OlvgUUKxSIzcpp6p8L6hKlYKEec1K5gYS7Bsew7MTSSQFxkjTyJdjpjbD2eib3s7xCcVIzG1CK93tkdaZgnOqlSk+nK0G85czcGuY48TZppI4OZkrJbc2M/DBNm5JUhOL6lwv2XZfyYPXZuai7FJTi9FzxYWSM8qxcVbSmH1o0E24vPB8zI3gb1n8jGsu5UYFxLD2jU0E+Nw/Ipse9G2VfV+kpOaSVXHNG+sdt0HY+mcL+BXJQR+VcOwf9tKFBbkoUmbnuL7JbOnwM7BBb3flFW13LVxCbaunieqVzk6eyAjTeaBYmpmIcI7zS2sRC6c9ct/EeFW1IZKlp86vA393pady3XRqP1QbFkyCe6+YaJKzJl9y0TZ35pNZdeFLYsnilCF1n2U14WkuHuK/7PSExAfdUMIEw4uvmoPaZdPbEDNJr1E3p6KUKP52zi8djKcPcNElSmqSkW2VKsny3lx8J9JsLRxRcNOMm/YsKZvYev8t3Dl6BL4BLUU5cuTYyLQvLfSC+/+1V0ws3QQuXKoLPnJrd/BN6QtvKo1LdeeJh3fxoYFk+HpHwbPgBo4uWe52FZ1m8vsWTd/EmzsXdGh30eKBMlJMY/HpqQImWmJiHt4AyZmFqJCFXHn6jGhTji5+yMl4SF2r5kp/q/bTHdej/pth2Ln8klCbHH3q4nzB5ahqCAPYY1l22nHsomwsnMV5cbl2yZFvp1KZNspMeoGjE0tYO/iCxMzKzh7qIfQ03dmVnZPzNfEmdtSdGsoQXwqEJsqRYNqElCkLFVrIug7ygdGVZiIc3ekeKO1RFS7uhsnRYiPRCQGphw4BFWDe5goRZtaBiKfmjy0KsxXgv2XdXt712o5BAdWfwpnrzC4+NTElaOye5vgBrKx2ff3JFjauiC8i3Js0hKU2yknIwHJdG9jagFbJ9l2KirIQUbyI8VvZKVGizZU2cvaXns99NM3pejRmAQX2bg0lI/L4+TE3RvJxuXQFdnnM7ekGNxWgkZBEtyNlSLEVzYuVO1KFUqqTqXN9198Os93fbrvE+eaxZPg7hcGT/+aOP34XFPr8blm86KJsLZ3FeXG5bYkxaqca9ISEP9Idjw9ca45vgE1wyt+rqlM/FcrROkj/7295/8RJBiQh8ekSZNEXhvKCUMiC+WzIVGGBBQSdahUN4VTkdcMedZQGXM59NBPwgvl0qGwpAYNGojKULQ8iTkkMlA4Dgk6VLGKxAjVvDNyaFmqajVixAjRB+XVoTAs8uahcuQvG0pqTMmfqYITVZGi8uwkklDOn4ryzjvvCK8jKvNN4VqUf0h1rMpCD1179uwRv0n5g6jyFnnbzJ07V3xPAg/lw6HkxlS9isQaslO1T0o+PXz4cJH7iLYPbQt5jqKKQgmt5SXdKWSDfoNyHz0LtvXCEL5fWSI9ZOZn4m/U8g24MnwyTN2dYe6tDO3Ii4wWok3IT5Ph9/5byI+Ox9WRU5C895iiTdzanTBxdkC1qeNg6uaMzMs3cKbbCBSWSYCsiWp1uiAvOxWnd80RF15nz+roMXKBwm09Oy1WTSjMyUzE6pnKm8uLBxeLybNKA/R5T7ZeV4/LSqZumKseKtRu4HeiPKUuOob6iWS6vx++jOScPAS52mPewDaKxLpxGTlqb+LcbC0xb1BbzNx7Dv3mbxW5bwY1CMbQJupvqE/dj0NcZg561dJeHaos4c3bITMjHetWLkB6Wip8A6ri02k/K0KrkpMS1N54F+TnYcnvM5GSkggTE1N4ePli7ISpoh+CjnlKlHxk/w4h4ljZ2KJK1WBMnT5PlCLXReKO3TB2sIf/B2Ng4uyE7Bu3cGX4GBSlyIQGUw83tTftBqYmCPhwrEhoXJKTK8qQX//kcxRnKcNusq5G4NrYjxAwYRx83xspyo/f+fYHJGzZUe7YdKoZiLScfMzbd1aER1EZ8XlDu8LxcWhVfHqWWhlqNzsr/D60K37cfgL9Zq8VIs8bTWtgaIvnfzvasmULZGRmYMWKv4RHJJ0bv/n6ayG6iLFLSoKkvJrYZTh56hR+/uVXxefvH4fXUknywW++oXNZKhNOSSk71DeCtYUEsSlSLN5RoEiATKFRqkIHeeT8vb8QHRsYo1NDI1FifPmeQiSkyRrZWkoQ6id7Ez7+NfVz/Z9bC3A/TreSs/dMgRAaBnWwEF4q92KKMXe9ugeNk50hLM2VMy7cKoK1RZ4QfWgdqDT33HU5ivAwb1cjRdWrae+oZ+z8Yn4mUjO127T5QIYQZkb2d4SFuQFuPijAt3/Go6hYOSiuTkawtlS+/Q/wNsW095TnxSG9ZNfIQ2eyMPfv5Ar3WxYqy25iIsHgzlawMJPgTlQRZq3JVBsbSlJNSY7lnLtRCGuLXPRsYS7CsigMa9aaLGSVU51KFw2adkR2Rhq2rP4dmenJ8PIPwrgp82DzOAFyanKc2nn4yO5/UFxchD9nyqpCyunWfyS6vy4Tlkd8OAMbV87G4lmfISc7Ew5O7ug58D206NivXHtCGnRBTlYqDm+ZLa4Lrl7VMWDcQkW4Q0ZqnNq5Lys9EYv+p8y/dWrPYjFRafHBHyuvdxTmkJkaKyrIVJQqNbsgPzsN5/fNFuEfju7V0XnofMU1Kidd3RZX3zpoM+BHnNszC2d3/yIewtu/OQcObkohIjczCae2zxAhV9RP1To9UaeNbNzKo0YjGps07N84G9kZyXD3qY63JsxXhFZlpMTBQHVs0pIwb6ryund812IxUanx4ZOXi3mU+Hnv2l+QmRYPc0tbhNbvgHZ9x2st9SwnuF4X5Gal4vg2GhvZ9fu1sQsVoVWU80Z1bLIzErF8unI7ndu/WExeVRtiwHjldnpWbkTJQquah0lgaSYRXiL/HClVeBDaWKiH28ekAFtOlaJFmAFa1pAgLRtYf7xUlOiWs/lUKVrVkKBHIwMhIGfmAoevSXHxnu7jrWpt2m9ScWb3HDE2VIK+2wjd9zb//KK8t7l0eLGYPAIaoNcY2dgkRl3D5j/eVrQ5vmW6+BtUvxfaDpiuc1woNIrWkcaFyqevPlSKnMfjQud4KdTHZdNJWm8DtKopQWoWsPZYKZLK1HwI9ZUIj8CIR0937tGn+77QBrJ9+PDmx+ca7+oY+IHuc81CLeeatz5R7sP3n+FcwzCakEifJ0kIw+iARCaqhkVeQqpJhhn9YbuxzENBX3iwWXtJ5lfN8JRvoU/caFSxG/lXQUZX3R46r5rw6c8mXL4M4mp3h77wx/7yw/ReJdmZzx6e9KJJjHkyzPjfxM5ZS4mYf4E3erycZOvPyqOU58tH9yJJTNGTjK1U6vrZ02W9FDJy9CdbQ3JqxcPkXwUk3uoL2WUq4f3b2Nroz9jYWumPJ8lgWfqwSsnBqk8W89AHWt+5jP8a7JHDvDA2btwokgtTCAGJN+SFQlWaWMRhGIZhGIZhGIb5b8NVq14d+iODMpUeyttAeXuojDiF9lCI1ebNm1FZofw3JExpmjp37vxvm8cwDMMwDMMwDMP8P4Q9cpgXBiUbpum/wqhRo0Sy4pdRepxhGIZhGIZhGIZhngUWchhGC1T9pbwKMAzDMAzDMAzDMAwgMeTQqlcFh1YxDMMwDMMwDMMwDMNUEljIYRiGYRiGYRiGYRiGqSRwaBXDMAzDMAzDMAzDMM+FAYdWvTLYI4dhGIZhGIZhGIZhGKaSwEIOwzAMwzAMwzAMwzBMJYFDqxiGYRiGYRiGYRiGeS4kBhxa9apgjxyGYRiGYRiGYRiGYZhKAgs5DMMwDMMwDMMwDMMwlQQOrWKY/8c82HwT+oR/z2DoC5sO6dfYpNyF3lD80yXoE3ct9MeNN/OqFPpDPvQJAyP9eXfkVcUZ+kRxcSn0hUv3zaBPxMbmQV8olerP8Z2Wbgh9Qo+GRu9IT9ef41si0Z/rJZGToz/23Msrgr4wuIUVKisSQ/251v/X4ZFmGIZhGIZhGIZhGIapJLCQwzAMwzAMwzAMwzAMU0ng0CqGYRiGYRiGYRiGYZ4LA0P9CZf7r8MeOQzDMAzDMAzDMAzDMJUEFnIYhmEYhmEYhmEYhmEqCRxaxTAMwzAMwzAMwzDMcyEx4NCqVwV75DAMwzAMwzAMwzAMw1QSWMhhGIZhGIZhGIZhGIapJHBoFcMwDMMwDMMwDMMwzwVXrXp1sEcOwzAMwzAMwzAMwzBMJYGFHIZhGIZhGIZhGIZhmEoCh1YxDMMwDMMwDMMwDPNcSDi06pXBQg7DVHK++uorbNq0CZcuXXphfV45thIXDixCblYynDyC0aLPFLj51tTYNiXuDk7vmo3EqAhkpcWiea/JqN3ybbU25/b9iXtX9iIt8T6MjM3g5lcHTbtPgL1LgE47HJrVR8CE4bCtGwYzDxec6zsGCVv2616mRUOEzPwUViFVkR8Vh7vf/47o5RvV2viOHoSAj4bD1M0ZmVduImL8/5Bx9mq543Jm/0oc37UI2RnJcPMORuc3psArQPO4JMbcwcFNsxEbGYGMlFh0HDAZ4R3Ux6UgLxsHNs7GzYv7kJOZAjef6ug86HN4+tdAZdpOxLXjK3HpsMwWR/dgNOs1Ba4+mm1Jjb+DM7tnIzlGZkuTHpNRq7m6LbH3z+LSoUVIiolAbmYSOr39G/zD2qGiXDy8Emf3LUJOZhKcPYPRtv8XcPfTbE9y7B0c3z4bCY8ikJkag9Z9J6NemyFqbY5vn4OTO35Tm+fg6o9hX+4q15aIEytx+cgi5GUlw8E9GE17ToGLt2ZbiPtXduHsnlnITouBjZMvGnX+GD7BLRXf0xif2TkT0bePoyA/C+7+9UWftk5+FRgZIDzEEC1qGcHaXIK4VCk2Hy9EdJJUa/sa/gbo0MAY9lYSJGdKsfN0EW5FlYrvqMpoxwZGCPIxhKO1BPmFwJ2YEuw8U4Ss3AqZgy6NTdGkhjHMTSV4EFuCNQfykZQu618bzWsao219U9hYSBCTXIp1B/PwMEG5TJMwY9QPNoaXs6Hod+LvmcgrKN+WpjWM0aaOMawtJIhNLsWGIwV4lKjdllpVDNG5sSkcrCVIyijFthOFuPGwRK1Np4YmCA81gpmpBJFxJVh7qADJGdrHWx/H5kUf30/bZ1nCQw3RsvbjfThFtg9HJerYhwMM0JH2YWuJGHvah28+erwPG8j24WDah20e78PRJaJNZgX24SahRmhFtliQLaXYeKwIUTr2mZoBhujUUGnL9lOFCluIMH9Dsb94ORvA0kyCn//JQ2xKxfYXolF1AzQPM4KVORCfJsW2k8WITta+fJifAdrVNYSdlQQpmVLsPleC29FKe9rUMURNfwPYWkpQUgrEpEix93yxznOGnMZkS43HtqRKsbUCtrSvp7Rl11l1W9qSLQEqtiRLsaeCtuibPfp0Hm4cYoiWNWXjQrZsOVFUri3t6xsJW2hcdp4pVrOlAx1P3gbivEi23I0tfaprgj5tJ327JjCMKhxaxbxyCgsL/20TGB3cvrgDRzdNR8OOYzFgwgY4eQRhy58jkJuVorF9cVE+bBy90aTbBFhYO2tsE3PvLGo2G4R+H6xBz1GLUVpSjM1/jEBRge6ruqGlBTKv3MK1cdMqZLu5nxcabPkTKYdO41j9nngwZxlq/PkNnNo3U7Rx79cZ1X+cjDvfzMWxhr2RdeUmGm1fBBNnB519XzuzA7vXTEerHmMxcuoGuHoH4a+fRyA7U/O4FBXmw97ZG+1emwArW83jsmXpF7h//QR6j5iB0V9vQZXQplg+cygy0xIq1Xa6e2kHjm+djvrtx+K18Rvg6BGEbQtHIDdbty2Numi3pagwD44ewWje60s8LTfP78ChDd8jvMtYDP50I1y8grHut+HI0TI2RUV5sHX0QoueE2Bpo9kewtG9KkZ/d0wxDfhoVbm23Lu8Aye3TUe9tmPRZ9wGOLoHYceiEcjTMjbxkRew/+8JCG7wGvqM2wi/kHbYs/w9pMbfFt9LpVLsWT4WmanR6PD2PPT9YAOs7DywfcEwFBWWf5dMD5Hdwo2x/3wxZm8oEA+ew7uYwtJMc3tfVwMMbGuCszdLRPvrkSV4q4MJXO1lb9xMjABPJwMcuFCMWRsKsGJvAZztDDCkoykqQrv6JmhZxwRr9ufjp9U5KCiSYkxvCxgZal+mbjUj9G5hhp2nCvDDqhzEJJVgTG9LWJkr3wKaGEtwI7IYe89WQL15TO1AI/RqZoLdZwvx05pcxKaUYmQPc7V+VfFzM8DgjmY4fb0IM9fk4tr9EgzrYgY3B+WtVZu6xmhRy1jcqP+6Ng8FRcCoHuY610/fxuZlHN9P22fZB6XuTYyx71wxZq1/vA931b0PD2on24dnrStABO3DHcvsw84G2E/78LoCLN/9eB/uZFohW3o0Ncbec0X4dV2+EFze6WYqHkC12fJGexOcuVmMX9bm49qDEvE7bg6q2wfi4Y4EnqeFHrC7NDTCgUvFmLulSDwED+lorHVsfFwk6N/KCOdul2Lu5iLceFSKN9oawcVOaQ89YG49VYzZmwoxf3sR0rOkGNrRGBZmFbClkRH2XywWfZNAMLSTblteby2z5bdNRbj+sBRvtjNSbCe5LVtOFmPWxkL8ua0IadlSDNPRp77ao0/nYRI4ujU2wr4LxZizsVBmS2cTneMyoI0xzt0qweyNhYiILMXg9sYKW4zJFkeJGGf6fsW+QjjZSvB2BxNUBH3aTvp2TWCYsrCQw7x0WrVqhffeew/jx4+Hk5MTOnbsiGvXrqFz586wsrKCq6srBg8ejOTkZMUyBQUFGDduHFxcXGBmZoZmzZrh7Nmziu8PHToEiUSC7du3o2bNmqJN48aNRb+qHDt2DM2bN4e5uTm8vb1Fnzk5OYrv/fz88N1332HYsGGwtraGj48P5s+fX+F1i46OxsCBA+Hg4ABLS0vUr18fp0+fVnz/+++/o0qVKjAxMUFQUBBWrFih+C4yMlKsg6onTXp6uphH66e6nvv37xd9W1hYoEmTJrh165b4funSpZg2bRouX74s2tFE856HS4eWIjS8H0Ia9YWDWyBa95sGIxMzXD+9XmN7V58aaNZjIqrV7QpDI2ONbXqOXIjqDfuIB2Hyjmg/6HvxpjYxOkKnLUm7j+D21F+RsHlfhWz3fXcA8h5E48bEGci+eR8P561E/Prd8P9A6V3hP34oohb9g+hlG5B94x6ujpmKktx8eA/pq7Pvk7uXom6LfqjTvC9cPAPR7a1pMDYxw8WjmseFvGo69J+IGo00jwsJPdfP70H7fh/DL6gBHF190brX+3Bw8cHZg39Xqu10+chShDTqh+AGfeHgGoiWfabB2NgMN89otsXFuwaadJuIqrW12+Ib3AKNOo1HQI32eFrO7V+CGk36o0Z4Xzi5B6L9ANm2unZSsz3uvjXRqs8kBNcne7TfbBoYGMLS1lkxWVjpFv+IK0eXIrhhPwQ16At710A07z1NeDvdOqvZlmvHV8C7WjPUajkc9q5V0KDjB3DyCBFePURGciQSH11Gs15TxTjaOQegee+vxMPzvUvby7WneU0jnLlZgnO3S5CYLsXGo0UoKgYaBGl20G0aZojbUaU4cqVYtN9zrhixyVLhhUDkFwELdxTiyv0ScbP8KFH2Zpm8Cewsy3evblXHBLtPF+Dqfeq3FCt254m3pjWraHcYbl3XFCevFYmb5fjUUiF0FBZLER6q3JcOXSzE3nOFeBCv/iZUpy21jXEyoghnbhQjIU2KtQcLRL+Nqmu2hW7Gbz4qwcGLRUhMozfk9Ea9VHjEyGlZyxh7zhWKB3Z6QFq1Lx82lhLUCDCqNGPzMo7vp+2z7D58+kaJeJCkcd9w5PE+HKx5XJrVkO3Dhy8/3ofPFos38k3DHu/DhcDCbYW4cq8ESY/34U3HCuHlYiDe8OuiZS0jnL5ejLO3SsQ+s/5wIYqKpFptIdtvPSrFoUsyW3afLRJeU3JbiAu3S4THyx0Vj4KKQsfruVuluHCnFEnpdCwWi7GpV81Qq1cI/c6xa7J133ehRIhRNF/OlfuluBcrRVoWhM07zhTDzEQCN5UHZU00CzPE2ce2JD62pVCHLU1CZbYcvapuS+PqyvaXy9pyumK26Js9+nQeblZDZsv5x7ZsOiYbl/pBmseF9lXydjlypUTsY7Svki3kJUeQMLFoZxGu3i8VtpCn3JbjRcIWW0udpujddtK3a0JlQWJgoJfTf5H/5loxeseyZcuEmHH8+HFMnz4dbdq0QZ06dXDu3Dns2rULCQkJ6N+/v6L9xIkTsX79erHchQsXEBgYKASg1NRUtX4/+eQT/PTTT0LkcXZ2Rvfu3VFUVCS+u3fvHjp16oS+ffviypUrWLNmjRB2SFRShZYnkeTixYsYM2YMRo8erRBKdJGdnY2WLVsiJiYGW7ZsEWIK2V1aKrv52rhxIz744ANMmDBBCEwjR47E0KFDcfDgwacev88//1zYSeNlZGQkhCfi9ddfF/2HhoYiLi5OTDTvWSkpLhQP7d7Vmijm0cnPu2o44h++uNCtgrws8dfMwhYvErvGtZF84KTavKS9x2DfuLb4X2JsDNu6oUjef0LZQCpF8oETsGtcR2u/xcWFiH0YgYAQ5bgYGBggICQc0feebVzI20VaWgIjY/U3ZvSQ/+jO+UqzncgWCn/yqqpui2fVcCS8QFsqCtmTEBUB32B1e3yCmyD2/sXn6jst6SF+/6wZFnzZFtuXTEBmamy5tiRrGpvAcCQ80jw2NGaegcr2hFe1por2pcWyt/Sq+w31SQJUfKTu/cbQgN7aSkTYiBxy5r4bUwIfVwOtb4Lpe1VuR2tvT9ANcqlUirxC3a7iFMZia2mAW1HFinn0UB0ZXwJ/d0Ot6+Dtor4M/cqtR8Xw07JMRaB+6cH9dpT62NBY+bpp7tfPjR6u1Mfm1iNqb6BYPxtL9T5p/SjMid7cVoaxeRnH9/P0KfZhZwnuRmvYTlr2SdpXVfd5grZJhfbhAmk5thiohXAIW2JKtdpC8ynkRRUKSfF1ff7X8WSPh6NEhLGo2kOffZw1P7D6uBiIB1xV7saUwttFovU3GgQZinEhbx+dtjg9acs9ssVFuy13y9hCD+g+FbCFvDZ0oU/26NN5WG4LbXN1W0rh66LLFnWRkY4Bbe1VbaFzWGXaTvp0TWAYTfx35D9Gr6latSp++OEH8f8333wjRBzyhJGzePFi4TFz+/ZteHp6Ck8W8iwhrx1iwYIF2Lt3LxYtWiTEGzlTp05F+/ayN/Yk+nh5eQkBhUSh77//Hm+88YbwBJLbMHv2bCG+UP/kxUN06dJFCDjEpEmT8MsvvwixhTxodLFq1SokJSUJEYk8cggSnOTMnDkTQ4YMUfT90Ucf4dSpU2J+69atn2r8vv32W2E38emnn6Jr167Iz88Xnkbk1UTijpubG56XvJw0IS5YWDuqzbewdkJa4gO8CKSlpTi66Tu4+9eFo3s1vEhMXZ1QkKD07CLos7GtNQzMTGFsbwsDIyMUJKq77xckpMAySHsemNws2bhY2aiPi6WNE5Ljnm1cTM2t4FWlNg5vnQcn9wBY2Trh6untQhgir5zKsp3yH9tiblXGFisnpL8gW56GvGyZPZZlxoY+p8bff+Z+Kb9O58Hfi7w42RlJOLljLv7++Q0MnbIVJmZWGpfJz9U8NubWTkhP0jw2ednJMLd+sj3l1yHsXAJEKNWZnT+jeR/ywjLH1WPLkJMRL3IJ6YJCIQwNJMjOU5+flScVbviaIBfyLA3tKa+DJsg9vHNDY1y+WyLezOqCbmhFfznqN9NZuVLFd2WxNJeIdcjMfXIZV4dnfxiW90vrVrZfFy1jQzkT6Hv19qWwsTBSfE9kl2mTnVuq+E7fx+ZlHN/P0yeFQsi2k/r87Dzd2ylbQ3tt24D24S6Ny9+HKX+N7Hh6vn2G9o/y9oeKYGEqP77L9K/z+Aay859sX/b4DvI2wOutjETYTHYusGR3EXILKnKu0WCLrQ5byrbPf3JsyJYBrWW2UM6Vxbt026Jv9ujTeVjnuOjaZzS0t9JhS6eGRrh8r7Tca4I+bSd9uyYwjCZYyGFeCfXq1VP8T54rJJSQAFEW8qIhgYK8apo2baqYb2xsjIYNG+LGjRtq7cPDwxX/k5hC4ou8Df0OeeKsXCkLSZDnlyCPmQcPHqB69epiHoVmyaHQJBJEEhMTy10nCokiQUou4pSF7Hj33XfV5tE6zZo1C0+Lqo3u7u7iL9lIoWAVhcLVaFKlqMgExmU8Ql42h9Z/LRLvvjau/Pwi/3X6vPMDNi/+DD9PaAmJgSHcfUMQ1qgr4h7qDmV6FfB2UicgVJlsmMLO3P1qYf4XrXHrwk7UaNLvldlhYGiM9oNn48i6KVg2rZHYb8jDxzuohfAu+zehJJdvtDOBRAKR8LUs9YOMMKCtMnnIH5srmPny/wE8NvoBed+/2d4E9EhFIVuMjPtxlH+kUIhXFHIzoLUx/thaiJz8f8cWyuVCtpBnxcA2xvh9y79jiz7aU955+FXbMqitsbBl079si75tp/8yEtrwzCuBhRzmlUD5Y1RDkigEasaMGU+0I5GCxJwXAf0OhTNRXpyyqAogJBKpQmKOPDxKF+QN8zxQaI5cXJIjDwsri6qNZB9RERtVIQ8lyqejSudBX6LLG18pPptb2osHw7IJc6mqiIWNE16EOBB5/RD6vPcXrOye34OoLOR9Q145qtDnoowslOYXoDA5DaXFxTB1UX8TbOrqiIJ4dU8eVSysZeNSNrFxTmay8KR5VsjzZuinf6GwIFdUsLK2c8Ha3z8USZJ1oU/byeyxLWWT9+ZmJwsPoVeNuZXMnrKJjekzeVC9KMwsbGDv4oe0pEc62mgeG/Ku0TY25lbkffNke/LKkePsFYa+4zehMC8LJSVFMLdywMbf+ov5usjNB0pK6c2p+nx6q1v2LaL623kN7cu8pZQ/PFBOkQXbCjS+eaVcL5Hx2YrPRo9LlFpbqnuR0JtJStKriZw8qVgHqsikZpOFBJk5T59TpGy/Zd9wi361jA2NWdm3qNYWBor28jG1KtOHlYUBYpNLKsXYvIzj+3n6pIcu2XbS4LGgYztZVaC9XMShfXj+Vs37sLotsvG2es59hvYPbbY/DeRdoLRHZX8zlzzhASCHvEKszMrYo+H4pvwtqVk0SRGVVIwP+xqLnCWUJ0X3ueZJW8r2rWZLmbEk28qOTVlbPnrNGPWrGeKwFlv0zZ5/+zys2Zan3GfKjgu112iLrMrWgu2F5dqib9vp374mMExF4IA85pVTt25dREREiETDFIqkOpHgI08OTPl0VAUOCmEKCQlR64tCleSkpaWJ0Cy5pw39zvXr15/4DZqo/+eFvGTIK6ds3h45ZIfqOhD0Wb4OlNOHoLw2cp6lhDitS0lJ+ReAyZMnIyMjQ21q33+yWhvKs+HiFYro2yfVQmyi7pyCm68sz8yzQGIViQP3r+5D7zFLRYWgl0H6qUtwbNNYbZ5T2yZIOyUbV2lRETIuRMCpjdKTi14VObYOR/op7flTjIxM4OEbigc3lONCQtr9G6dEeNTzYmJqIUScvJwM3L12DEG12+hsr0/biWxx9gxF9F11W2LunoLrc9jyrJA9rt6heHRL3R767BGgPQ/S01KYn4OM5ChY6ahyRbY4eYYipszYxNLY+GgeGxqzmHvqeZ5i7pzQ2N7E3FqIOJQAOTn6GvxCdO838rKrgZ7KMBu65Qz0MMQjlfLUqlDsfhWV9kRVTwO19vKHB6pMsnB7gVZ3dbqRp+SX8omS8WbklCLIW/lOycxElmfgQVyJ1nWg0s7VVJahdaDPVOnnWaF+o0W/6mNT1csQD7UkBaZ8NdW81MeGln8YLxsbKoNLAopqG1NjWY6JyMdt9H1sXsbx/Tx9in04ScM+7GmoVmJdFdpXVdsTVb3K7MOPRRzah+kBuLxQHaUtpaIvdVsMtNpC86uWsaWaF7V//oc4soeSvFbxULeHPj/SUmaZyihX8VB/8KT2ukq5i34lEp1VdoQtdK5x12BLYsVtobF89Jy26Js9//Z5WLMtZfZhDwM8TNRuC32vZouXenu5iEM5YSgJc0Vs0cft9G9eEximIrCQw7xyxo4dK8QPqvZE4gx54OzevVskAiZBgsQcSjhMuXAoETKJMe+88w5yc3MxfPhwtb6+/vprUdGJkglTPhqqitWrVy9FvpsTJ06I5MYkkNy5cwebN29+Itnxs0L2UxgW/R4JNPfv3xcJmk+elN2ckv2U54fy8dBv//zzz9iwYQM+/vhjhUcPVdqi5M8UhnX48GFMmTLlqe0gQYxCxWgdqfJX2fApOaamprCxsVGbNIVV1W41BBGn1uLGmY1ITbiHg+u+QnFhHkIa9RHf71k5CSe2/VQmceUNMZWWFCE7I0H8n570UNHm8PqvcevcVnR8cyaMTS2Rk5kkpuLC/HLLj9vUChYTYeHvJf4385aFlwV98xFqLVF6dj2cvxoW/t4I/v4TkfPGd9QgUW78wSxlJa8Hvy6B9/D+8BzcC1bBAQib+xWMLM0RtWyDTlvCOw7B+cNrcen4RiTF3sP2FV+hqCAPdZrJxmXDgknYt+4ntQTJcY9uiKmkuAhZ6Qni/5QE5bjcvXYUd64eRVpSNO5FHMfSH94W+XLkfepCn7ZTrRZDcOP0Wtw8txFpCfdwZMNXonx4cAOZLfv/noRTO9RtSY65ISbyKMnJSBD/ZyQrbSkqyFG0IajcNv1PVbTKo37bobhy/B9cO7URKfH3sHe1bFuFNZbZs2PZRBzZrG5PYtQNMZWUFIptRf+nJSrtObRhBqLunEFGSjRi7l/A5gXviQStwfW76bSlZvMhuHlmLW6fl43N0Y1fiXLn1erLbDm4ZhLO7FTaEtZ0MKJuHcOVI4uRnngf5/bOEYlhQ5u8oWhz/8ouxN47jcyUKERG7Mf2hcPgG9oWXtWalTs2R68Uo2GwIepWNRQlhns3NwY5/J27LUuQ27+VMTo1UAoBx6+ViNwCzWsYwdlWgnb1jESC1xMRxYobdnoA9nKWYPWBQuFCT2+aaaJkkeVBFZQ6NjRFWIAR3B2pdKs5MnKkuHJPmbD3vT4WohqInIMXCtAkzBgNq1PJWwP0b2sGU2MJTl1XvvKlt6JkpzyvgoejofhMeUS02nKpCI1DjEXFIRd7CV5rZQoTIwlO35DZMqidKbqGK18CHLlchGAfQ1HZhMayY0MTkWz46BWlHYcvF6F9fROE+hmK9XujvRkyc6TCA6eyjM3LOL7L67Pcfbi6ofAIEftwC2NRsvvcLdm4vN7aWOTkkHPsqmwfblHTCM52ErSvbyQq6By/9ngfNgAGP96H/97/dPswVcKiCjYUbkS29BG2SHD2pqzvAW1M0LmRsZrtZAtVuyJbOtQ3VrOFMDeVJS2Wl0+mXCX0uaxHhiboeK1fzQB1Amn7StCjiZEoTU0ViYjXWhihQz3lQ+TJ6yXiIZyqIpEA0KaOoUh+S/MJyifSvp4hvJ0lsLOU2dWnmRFsLIBrD3Q/eFIlrPpBSlt6NpXZckHVlvpKW05E0EOwgahaRO3bPrbl1A2lLR3ktlg9tqW5zJar5diib/bo03n42NViEWpUt6qB2Cd7NTMSx5N8nyFbOqrZUoxqwhbZuLSrayTbZyJKlLa0Mxbl0NccLHrqa4I+bSd9uyZUFgwMJXo5/Rfh0CrmlePh4SGEDxJaOnToIIQHX19fUWFKHm5E4gZ5PFBZ8qysLFFVisQee3t7tb6oHVWGIqGkdu3a2Lp1q8LbhjxmSByhik9Ugpy8Dcjb53mqOqlCv7Nnzx5RNYoSJhcXFwtvm7lz54rvSeChfDiU3Jhs9Pf3x5IlS0Q5dtUkzyROUQ4hyu9DCaFpTJ4GqspFAhElUKby5fQbJGo9K9XqdEFedipO75ojHuKdPaujx8gFCpf37LRYRXgXkZOZiNUzeys+Xzy4WEyeVRqgz3uycutXj8vKaW+Y+5bab7Ub+J0od60N23phCN+vLNkeMvMz8Tdq+QZcGT4Zpu7OMH8s6hB5kdE422MkQn6aDL/330J+dDyujpyC5L3HFG3i1u6EibMDqk0dB1M3Z2RevoEz3UagsEwC5LKENeyCnKxUHNw0RyS7dfOujjc/XKAIrcpIjVWLC85KT8SfXynH5cSuxWLyDWqAoZNk65Sfm439639GZlo8zC3tUL1ee7Tt86HWkr36up0Ca3dBXk4qzu6eg9ysJDh5VEe3ESq2pD9py9pflbZcPrxYTB4BDdBztMyWxOhr2PLH28rx2zpd/A2q1wttBsj+10ZwvS7IzUrF8W2zhT00Nq+NXagIrcpMi4NEoryjzM5IxPLpMgGYOLd/sZi8qjbEgPEye7LS47FtyUfIz0kXXjCeVerhjY//gYW17hLkVWrJxubcHtnYOHpUR5dh2sfGza8u2g6cibO7f8WZXb/A1skPHd76DQ5uyoTTuVmJOLltughNsbB2RtW6PVG37WhUBCpPa2kOdKhvJB7o6Q3+4h0FisSb5JKvmmqH3r7Sw23HBrKHY/IWWb6nUJRiJagcNt2QEuNfkyWQl/Pn1gKRl0AX+84VihvjgW3NYG4qwf3YEszbmItilReeTnYGsDRXbq8Lt4thZZ6PruGmslCj5FLM25Sr5krfrKYJujRWKhPj+8vCe//akydKc2vi0l3qV4JODU1EOVjytvhza54iZMDe2gBSqXJ96A3qij354nfoZj4pvRSLd+QLbxo5By4UifXr39pUrB9501Cfquun72PzMo7v8vrUxeV7JSLpcYcGj/fhZCkWbVfZh60lKkEZsn141f5CdGpojE6NHu/Du8vsw/6yffjDfur78B9bCnBfpYKOJluszIvE8SGzpRQLtyltsddwPK3cV4hOjYyFwEO2LN1VoFYBio6nAW2U22dwB9n/e84WYc853fEp9GBqaVaMtnWNhPBDVXmW7ilS5AGhdVW1h7wW/jlUjHb1DMXDLnkMrNwvK3FNUFt6OK7bxlgkoiXPCjouFuwoUrQpzxYSHYQtKVKRJDk7X/O5hmxZc7BYCEf0oE62/LVPVvZZYYudBHWqGovtT2E40cmlmL+9fFv0zR59Og9TeXkal/b1aB+WeXUt3lmotEXDPrP6QJGwnQQesmXF3iI1W0Ie2/JBX3V1eP62wnKvCfq0nfTtmsAwZZFIVRN0MEwl4dChQ0K4oHAqOzu7f9ucSstvO/Tr8PfvKfO80QcyD92EPpGSAb2hWM9eHFnqUbWHzGz9OaYSE/Uri2Nurv4kjzUy0i+H5OJi/XGrrxJgDX0iNlZ/9mMqoawvmJo+f8nyF4keDY3eUUJxOnqCquiqDxjoUWLcvDz9uUb98p7mapiVgUsdmkMfqb3nKP5rsEcOwzAMwzAMwzAMwzDPBVetenXo1ysphtEjvvvuO1EiXdPUuXPnf9s8hmEYhmEYhmEY5v8h7JHDVEooz8zLjgocNWoU+vfv/1JKjzMMwzAMwzAMwzDMs8BCDsNowcHBQUwMwzAMwzAMwzCMbqiiJ/Nq4JFmGIZhGIZhGIZhGIapJLCQwzAMwzAMwzAMwzAMU0ng0CqGYRiGYRiGYRiGYZ4Lrlr16mCPHIZhGIZhGIZhGIZhmEoCCzkMwzAMwzAMwzAMwzCVBA6tYhiGYRiGYRiGYRjmuTAw5NCqVwV75DAMwzAMwzAMwzAMw1QSWMhhGIZhGIZhGIZhGIapJHBoFcMwDMMwDMMwDMMwzwVXrXp1sJDDMP+PGZ7yLfSJTYduQl+waRUMfaLbiV+gLxjfvQp94uoPG6EvBM2aBn3hm/gW0CcMDfXHCTj6XhL0CQdXW+gLLYJToU9Ee9hBX4hLNYS+UMWtAPpEep4x9IW4ZP16kCwthd7gbA+9wtxEfwbHyvTftoBhng79uatiGIZhGIZhGIZhGIZhdMIeOQzDMAzDMAzDMAzDPBcSA/YTeVXwSDMMwzAMwzAMwzAMw1QSWMhhGIZhGIZhGIZhGIapJHBoFcMwDMMwDMMwDMMwzwVXrXp1sEcOwzAMwzAMwzAMwzBMJYGFHIZhGIZhGIZhGIZhmEoCh1YxDMMwDMMwDMMwDPNccGjVq4M9chiGYRiGYRiGYRiGYSoJLOQwDMMwDMMwDMMwDMNUEji0imEYhmEYhmEYhmGY54JDq14d7JHDMGU4dOgQJBIJ0tPT/21TGIZhGIZhGIZhGEYN9shhmP8ArVq1Qu3atfHrr7++kP5Wn7uFZScjkJKdh2qu9pjUsSFqeDppbZ+ZX4jfDl7EgVtRyMgrgLutJT7p0ADNAz3F953nbEBcRs4Ty/WvVw2fdW6k05Yz+1fi+K5FyM5Ihpt3MDq/MQVeATU1tk2MuYODm2YjNjICGSmx6DhgMsI7vK3WpiAvGwc2zsbNi/uQk5kCN5/q6Dzoc3j619Bph0Oz+giYMBy2dcNg5uGCc33HIGHLft3LtGiIkJmfwiqkKvKj4nD3+98RvXyjWhvf0YMQ8NFwmLo5I/PKTUSM/x8yzl5FRfhn7zGs2H4AKRlZqOrjgU/e6oOwKr4a2249cgbT5v+tNs/E2Agnlvwo/i8uLsG8dTtw/NINxCSlwMrcDA3DquH917vB2d62XFtWn7mOZcevIZn2GTd7fNo5HDW8nLW2z8wrwG8HzmP/jYeP9xkrTOzUCM2reSvaJGTm4Ne953D8bjTyi4rh7WCDr3s2R6iOfVGOS5++cBv4JowdHJB77y4e/fITcm5c19hWYmgI98Fvw7FzF5g4OSM/6hGifp+LzNOnFG2ce/WBS68+MHV3F5/zHtxH7NLFyDh1slxb/tlzBH9to+2Uiao+nvjk7dcQGqhlOx0+ja//XPnEdjq+7GfF5wNnLmPD/mO4+SAKGdm5+Ou7iQjy80JFCQ81RMvaRrA2lyAuRYrNxwsRlSjV2r5GgAE6NjCGvbUEyRlS7DxdhJuPSsV3BgZAxwZGCPYxhKONBPmFwJ3oEtEmM7di9nRuZILGoUYwN5XgQVwJ1h4sEL+ji2Y1jNGmrjGsLSSITS7F+iMFeJQgs4kwMgR6NjNB3arG4v+bj0qw9lABsvN090u83skObcOtYWlmgJuRBViwNhnxycVa21cPMEOPNrYI8DKBg60RfliUgLPXcp+7X6J7c3M0r2UqxuZeTDFW7c5BYppyPTXRqq4p2jcyg62lAaITS7B6bw4i40o0tn2/nxXCqphg3vosXL5TpLXPPdvXY+uGlchIS4WPfyCGjPwIgdVCNLY9c+IQNq1djoS4aJQUF8PNwxtdew1A8zadFW3WrVqIk0f2ISU5EUZGxvAPDMLrg0ciMCgUFeH4nlU4vH0xsjKS4e4ThF5vfw6fKpqvC6cPrMX5Y5sRH3VXfPb0D0Hn18cr2pcUF2HX2tm4eekIUpKiYW5uhcCwcHQZ8BFs7V3KteXSkZU4t38RcjKT4OwZjNavfQF3P822JMfdwYnts5EYFYHM1Bi06jMZdVsP0dr3mT3zcWzrT6jT6i207vt5hcbm8K7V2LdlKTLTk+HpWw39h02GX1XN17fj+9bh9OGtiH08Nj4BIegxcNwT7eOj72PTX7/gzvXzKC0thptXFbwz4Wc4OMvOh9o4tW8lju5YrLh+dxv8Oby1bKezB//BxeNbkBB9R3z29AtB+34fqrWPOLsHZw6uQcyDCOTlZGDs/zbAw7c6KsqVYytx8eAi5GYlw8kjGC16T4Grr2Z7UuLv4PTO2UiKjkBWWiya9ZyM2i3V7yfO7fsT96/uRVrifRgZm8HNrw6adJsAe5eAcm25enwlLh2S2eLoHozmZIuPZltS4+/gzG6lLU17TEatFuq2xN47i4uHFiEpJgK5mUnoNOQ3BIS1q9C4nDmwEidU77MGTYGnjvusQ3Sf9VB5n9W4vbotpaUlOLT5N1w9tUX0aW3nglpNe6NFt9HiRWl5nNy7Cocf7zfu3kHo8Zb2/ebMwbW4QMd3tGwf9vIPQcd+49XaXzu7F6cPrEFMZARyszMw7pv1Fd5v6Hjav1V5PPWj4ylQ+/F05oj68dSdjieV9ivmTsHpw1vUlqteqwnGfv5HhexhGFXYI4dhGDV2R0Tip73nMLJ5Tfw9oqsQcsb8vR+pOXka2xeVlGDUyn2IzcjBj31bYNPonviyazhcrM0VbVYO64J9419TTH8Mkt1ctK+u+WFWzrUzO7B7zXS06jEWI6dugKt3EP76eQSyM1M021KYD3tnb7R7bQKsbDWLCFuWfoH710+g94gZGP31FlQJbYrlM4ciMy1Bpy2GlhbIvHIL18ZNQ0Uw9/NCgy1/IuXQaRyr3xMP5ixDjT+/gVP7Zoo27v06o/qPk3Hnm7k41rA3sq7cRKPti2Di7FBu/3tOXcQvKzfhnd4d8dc3E1DNxwPvz/gTqRlZWpexNDfDrt+mKaatv36p+C6/sBA3I6Mxold7/PW/Cfhx/FA8jEvERz8vLNeWXdfuY+buMxjZqjZWj+yBIFcHjP5rtxACNVFUXIJRK3YjNj0bM/u3web3+mJqj6ZwsbFQE3qGLNoOI0MDzH2jAzaM7YMJHRrCxtykXHsc2rSD93sfIHbJQkQMfxu5d++g2s+/wsjOXmN7z3dHwblnLyH2XBs8EImbNqLqd9NhUbWaok1hUiKi/5iLiOFDEDFiCDIvnEfg9z/AzN9fpy17Tl7Ar39txIg+nbDi20+EkPP+9Hnlbqed875RTFtmf6X2fX5BAWoFBeC9gT3wtNSqYojuTYyx71wxZq0vQFxKKYZ3NYWlmeb2vq4GGNTOBGdvlmDWugJERJbgrY4mcLWX3YybGAGezgbYf6FYfL98dwGc7QwwpJNphexpW9cYLWoZC/Hml3/yUFgEjOppLsQXbdSpaoRezU2w60whZq7ORUxyKUb1MIeVufIBoXdzU4T5G2HprnzM2ZAHW0sJhnXRspIq9Gxji84tbDB/bQom/xqLgoJSTBnlBmMj7Q8fpiYSPIwpxKL1KS+0346NzNCmnilW7s7B9OWZKCiSYtzr1jrHpn6wCV5rY4Htx/Lw7ZIMRCcWi2VI8CpL2wamKF/WAk4e3YcVC2ej78Bh+O7XJfD1D8T0Lz9ERnqqxvZW1jbo3f9tfP3jfMyYsxwt23XBH7O+w+ULSmHU3cMHQ0ZNwIzfVmDqjN/h7OKO774cj8yMtHLtuXRyJ7aunIH2fcZg/Dfr4OETjIXT30V2hubxv3fjDGqHd8XIz5fgvWmrYOfohgXT30FGquycX1iYj5jI62jXe5To763xs5EU9wBLfxpbri23zu/A4Y3fo3HnsXhz4kYh5GyYNxy5WZptKS7Mg62TF5r1mABLG+1CNxH/8AquHF8NJ48gVJTzx3dhw7If0aXfKHw6Yw28fIPw27ejkKVlbG5HnEP9Zp3xwdRF+Pjbv2Dv6IbfvhmF9BTl9TApPgo/f/E2XD39MX7aInw2cz06930Xxia6z8VXTu3AjlUz0KbXWIz9ej3cfIKw9Md3tF6/H9w8i5qNu2D45KUY9eXfsHV0x9IfRyi2E1FYmAffanXR8fUJeFruXNyBY5uno0HHsXj9ow1w9AjClvkjdGyrfNg6eiO82wRYWGveViSe1Gg6CK99sAY9Ry5GaUkxtvw5AkUFulXsO5d24PiW6ajffiz6jd8gtvG2BdptoXsbGwdvNO6i3ZaiwrzH4pTyul4R6D5rz5rpaKl6n/XLCPGiS5stdnSf1Vf7fdbxnQtw7tDf6DzoC4z9Zru4JzuxcyHO7F9Rrj2XT+3EtlUz0K73GLz/v3Vw9wnGoh+0H9/3b5xBrfCuePezJRgzdRVsHdyw6Afl8U0UFsj2m05Pud+cP7ELG5f/iM6vjcKkGWvg6RuEuTqOpzvXz6FeU9nxNOGbv8S5Zi4dTyq2ECG1m+K7+QcU09APfsB/CYmBgV5O/0X+m2vFvHTWrVuHGjVqwNzcHI6OjmjXrh0OHz4MY2NjxMfHq7UdP348mjdvLv5/+PAhunfvDnt7e1haWiI0NBQ7duyocLjT7t27UadOHfG7bdq0QWJiInbu3Inq1avDxsYGgwYNQm6u8gJaUFCAcePGwcXFBWZmZmjWrBnOnj2r1jf9frVq1USfrVu3RmRk5FONxfHjx4VHjIWFhVivjh07Ii0trUK/v3TpUtjZ2an1t2nTJrU3Fl999ZXwtlmxYgX8/Pxga2uLAQMGICtL9iA4ZMgQMfazZs0Sy9H0tOugyorT19GnTlX0qh2IKs52mNKlMcyMDbHp0j2N7Wk+PXT/0q8V6ni7wNPOCvV9XcXDvBwHSzM4WZkrpiN3o+Ftby3a6eLk7qWo26If6jTvCxfPQHR7axqMTcxw8eh6je3Jq6ZD/4mo0agrDI2MNd6AXD+/B+37fQy/oAZwdPVF617vw8HFB2cPqnurlCVp9xHcnvorEjbvQ0XwfXcA8h5E48bEGci+eR8P561E/Prd8P9A+fbVf/xQRC36B9HLNiD7xj1cHTMVJbn58B7St9z+V+48hF6tw9GjZSMEeLph8tB+MDM1wZbDp7UuQ7uVk52NYnK0tVZ8Z2Vhjnmfjkb7xnXg5+GCGoF+mPhWX9x4EI34ZN0PVytOXkOfukHoVacaqrjYY0q3pjAzNsKmi7c1tt948Y7wwvllQDvU8XGFJ+0Lfu4IcnNUtFl87ApcbS3xv17NhWePl701mgR6Cq+c8nAdMBBJWzcjecd25EdG4uGPM1Canw+nbt00tnfs2AlxK5YJ75qC2FgkbdqA9JMn4TZgkKJNxvFjsu+jo1AQFYWY+X+gNC8XViFhOm1ZteMgerVugh6tGiPAyx2Th/d/vJ2UD7VloWNYfTupr3OX5g3xTp/OaBhW8Qc8Oc1rGuH0jRKcu1WCxDQpNhwpQlEx0CBYs4NusxqGuB1VisOXi5GYLsWes8WISZaiaZisPXngLNxWiCv3SpCUIcWjRCk2HSuEl4sB7KzKf/PaorYx9pwtxLUHJUJUWrk3X4guNQK0Owy3qm2MkxFFOHOjGAlpUiECFRZL0ShEtoyZCcT/m44WCO+g6KRSrNqfjwAPQyFM6aJrSxus35OOc9dy8SiuCL+tSoK9jSEa1FCKjGW5dDMPq3em4czV3Bfab9sGZthxIl94ysQklWDJthzYWRmgdjXtD9DtGprh2OUCnLhaKBvPXblCHGtSU11Y83IxRPsG5li+40lPybJs37QabTr2QKt23eDl44/hYybCxNQUh/Zu09g+pEZdNAhvCU9vP7i6e6Fzj9fh41cFt65fUbRp2qoDatRuAFc3T3j7BuDNEeOQl5uDR5GarzOqHNm5FI1a90ODln3g6hWIPsOmwtjUDGcOb9DYftDYH9Gk/UB4+lWHi0cA+r3zP0hLS3EnQnYMmltY493Ji1CrcWe4ePjDt2ot9H57CqIfRCAtOVanLecPLkFYeH+ENe4LR/dAtHt9GoxMzHDtpOZrlJtvTbTsNQnB9egapX07FhbkYMeyT9B+4DcwsyjfI1LO/m3L0aRtX4S37gV37yoY8O4XMDExx8kDmzS2H/rBdLToOADe/sFw8/THG6O+glRailvXlNeRrX/PQUid5ug9+CN4+1eHs5s3ajZoDWtb5flaE8d3LUP9Vv1Qr0Ufcf3uOeQrsZ3Oa9lO/Uf/iMbtBglPCWePAPQeLttO968rvR7rNO0phKHA0CZ4Wi4dXorQxv0Q0rAvHNwC0fq1acKL5sYZzdvK1acGmvaYiGp1NN9PED1GLkT1hn3g6FYVTp7BaDfwe+ExkxgdodOWy4eXIqRRP1R/bEvLvjJbbp7VbkuT7hNRVYctvtVboFHn8Qio0R5Pw6k9j++zmvWFs0cgug1+fJ91TPd9VpiW+ywi6u5FBNVui2q1WsHOyQsh9TuJl2YxD8r3Nj62cykatuqH+i36wNUzEL2GToWJqRnOHdG83wwY8yPC2w0U+w0d331HyPabu9eV19i6zXoIYSgwNBxPwwHV48mrCga88/h4Oqj5eBoyTnY8efmVOZ6uqt+XGRmZwMbOSTFZWJV/X8MwmmAhh3lq4uLiMHDgQAwbNgw3btwQIkufPn1Qr149BAQECMFBTlFREVauXCnaEmPHjhXixpEjR3D16lXMmDEDVlZWFf5tEjV+++03nDhxAlFRUejfv78IJ1q1ahW2b9+OPXv2YM6cOYr2EydOxPr167Fs2TJcuHABgYGBQmhJTZW9SaQ+yHYSly5duoQRI0bg008/rbA9tEzbtm0REhKCkydP4tixY6KvkpKSCv1+Rbl3754QeLZt2yYmEm6mT58uviMBJzw8HO+8847YNjR5eyvDU54G8q65EZeKRv5uinkGEgka+bnjSkySxmUO3Y5CTS9nfL/rNNr8shZ9/9yChceuoqS0VOtv7Lj6AD1rVdHpYltcXChcdwNClDdsBgYGCAgJR/S9S8+0fvS2TFpaAiNj9YcauoF6dOc8XiR2jWsj+YB62E3S3mOwb1xb/C8xNoZt3VAk7z+hbCCVIvnACdg1rqOz76LiYtx8EI1GodXUxqZhaFVcuftQ63J5+YXo9sHX6DpuGj76eRHuRcfp/J3svDyxjUjk0W5LCW7EpqBxgIeKLRLx+Uq05n3m8K1HqOnlgu+3n0DrH1ehz9wNWHjksto+c/hWFEI9nPDxPwfQ6odV6P/HJqw/fwvlITEygmW1IGSeUxFspVLx2SpUszu0gbEJSgsK1eZJCwpgVbOW5h8xMIBD23YwMDNHdsTVcrZTlJrgIrZTWBCu3nmgdbm8/AJ0HzcVXd/7EhN+ml/udqoohgbkPSPB3WhlmA15ZJDYoU3g8HE1EN+rcjuqRMzXhpmJBKVSKfIKdPt7UCgWhf9Qf3JIGHqYUAo/NwOt60Aikeoy9Cv02c9N5qri7WIII0OJWhsSrVIzS+Hnrt2dxcXRCPY2Rrh6O18xLzdfirsPCxDkVzEPoxfVr5OtAWytDHAjUhnulF8gxYPYYgR4GmkdGx83Q7VlaGxuRhapLWNsBAzvYYW/9+YgM0f3NiouKsKDu7cQVqu+2j4cVrsB7ty6Vu66S6VSXLt8DnExjxAcWlvrbxzYtRkWllbw8QvUbU9xIWIeXEfVsMZq9lQNC8fDOxW7LhQW5KOkpBgWltoFkry8LHHuM7fQ/oBVUlyIhKgI+AYpr1H01pc+x0VexPNw4J+vERDaEr7BFRcsaByj7t9AcE31sQmu2Qj3b1+uUB/knUThcBZWsrEpLS3FtQtH4OrhKzx1Jg1viR8mD8LlMwd020LX78gItQdnsiUwJByP7lZsOxU93k7mOrZTRaFtReKKdzX1beVVLRzxkc92P6GJgjzZCzZd4hvZQuFPXmVtqRqO+IcvzpaKUCK/z6qubsvz3GcR3oF18ODGSaTEy65z8VE38ejuBQTWaFH+8R15HYGh6vsw7UcPn3K/0XV8V4TiYtnxFFRD3ZagGo3woKLHU4H68aTqufPpiJb4+oPuWL3gf8jO4pyczLPBOXKYp4aEguLiYiGA+PrKQmPIO4cYPnw4lixZgk8++UR83rp1K/Lz84XgQjx69Ah9+/ZVtCfh52n45ptv0LRpU8VvTZ48WYgc8n5ee+01HDx4EJMmTUJOTg5+//134fXSubMsNn/BggXYu3cvFi1aJGyk76tUqYKffvpJfB8UFKQQmCrCDz/8gPr162PevHmKeeRlRFTk9ysK3UxRP9bWMg+KwYMHY//+/fj222+Fh46JiYnwCHJzUwowZSEBjSa1fouKYUp39Y9Jyy1AiVQKR0v1B3dHKzNEpmRo7DcmPRtnI+PRJcwfvw1og6jULHy36zSKS0sxqsWTD8KURycrvxA9alXRuc65WWlCdLGyUX/rZ2njhOQ47Q/BujA1t4JXldo4vHUenNwDYGXrhKunt4sbFvLKeZGYujqhICFZbR59Nra1hoGZKYztbWFgZISCRHUX3YKEFFgG6T4u0rNyhOjhoOJRQ9DnyLhEjcv4urvgi3cGiFw62bl5+GvHQQybNhv/TJ8EV0d1rzBhR2ER5qzeho7hdWBloT0kRbHPWJXZZyzN8SBZ881JdFoWYh/EoUvNABE29Sg1E99tPynbZ1rVUbT55+xNDA4PxfDmtRARk4QZO0/B2NAAPWpX1WqPka2dEHOKyoilRalpMPP107hMxplTcBswEFmXL6EgJho29RrArmWrJ1xxzQOqoPofC2BgYoKSvDzc/WyS8Ph5pu0Um6B9O707CIG0nfLyRG6d4VN/wZofJsPVUXNoWEWh8ClDAwmyykS8Ud4YFzvNwgmF5GRraK8pVIegsJ8ujY1x+W4JCrSnXFH0TWTlqosJWbmlsLHU3L+luUS2Dk8sI4WrvYGi3+ISKfLUtTlk5Ulho8Vuws5aJvKkZ6sLV/RZ/t2z8Cz92ljJ1iUzR10Qp8/ksaQJK4vHY1NGnKFl3ByVb877t7XA/ZginTlxFMtmpot8F7b26uGetnYOiI3WLhrn5mRjzJCeKC4qhIGBIYaO/hg16zRUa3PhzHHM/vFL8bBjZ++Iz77+FTa2T56LVMnJktlD5261dbdxRGLsfVSEHat/go29ixB/NFFUWIAdf/+M2uFdYGah/UVTXo7sGmVR5hplYe2I1ISK2aKJm+e3IyHqOt74ZN1TLZedlSbGpqynDH2Oj6nYNZPy4Ng6OCP48cNrVkYqCvJzsWfTInQf8D56vjEeNy4dx4KZH4rwkaqhSoFPlVz5diozNla2jiJsrSLsWjNTbKcqz+B9o21bmVuX3VZOSE98tvuJspAXyNHN38Hdvy4c3ZUvWcqSL99vrNRtMbd2QtoLsqWiyO+zLF/gfRbRrPO7KMjLwW9Tuojjn/aFNr3Ho2bj7uXYo/34Tqrg8b1zjez4flrvm7JkZz4+nuzUx8bGzhEJsRUbm80r1Y8nonrtpqjVqC0cXTyRHB+NrX/Pxu/fjcGEb1eIsfovYGDIVateFSzkME9NrVq1hBcKiTHkXdKhQwchoFBYEYX5TJkyBadOnULjxo2F+EAiDoVRERRmNHr0aOE5Q+FYJOrUrKk5gZkmVNu6uroK8UJVDKJ5Z86cEf+TwEMeQXLhh6DQr4YNGwpPIoL+NmqknmyXvFuexiOnX79+Gr+ryO9XFAqpkos4hLu7uwgrexq+//57TJumnt/ls16tMaVPGzwP9OadQqe+6NoYhgYGCHF3RGJWLpaduq5RyNl06S6aBnrAxVp7SMHLpM87P2Dz4s/w84SWkBgYwt03RLgIxz3U7Qpd2alZ1U9McmpV9cdrE6djw4ETGN2vi1pbSnz86Zxl4m36p0M0798vYp/5sntT2T7j4YTEzFwsO3FVIeRQG/LIGddO9qBQ3d0RdxPTsfbcTZ1CzrPwaNYv8Js4GTVWrhbeO/mxMUjesQ3OXdVDsfIfPUTE0LdgaGUJh1Zt4P/5l7j5/midYs7TUrOav5jk1KoagH6ffIsN+09gdP+u0GdI93qzvQnoFo5CtspSr5oR+rdWeqDM36o5h9KrolldS4zsr3xg+H6B7jxZL5OGISZ4o5PsOkn8tlZ7DqXnoWagMYJ8jUX+nJeJmbkFps9ahvz8XOGR89ei2XB18xBhV3JCatYVbbIy03FgzxbMmvEF/vfTAiESvSwObFmASyd3YNSUZTA2edIbihIf/zXnI+HL1GfoVLxqstLicGj9t+g7dvETnqMvmz0bF4kcO+OnLVaMDYWFEDXrt0abboPF/xSGdf/WJRzd+49WIed5Obx1Aa6e3okRkzVvJ33k8IavkRp3B33fX4X/70Sc3Ymrp7ai7zsz4ewZiPhHN7F79Xci6XHtpr1f2u8e2roAl0/twLuf/fv7DYmfdDx98JXyeCLqN1Umfff0qSYSKH/1fhfciTir5v3DMBWBhRzmqTE0NBReJRTeJA9l+vzzz3H69Gn4+/uL0CLyyqH/KX8NhV7JodAlEn/kYVAkLpA3zPvvv1+h3yYhRA65Pat+ls8j75VXBeXVeR7ITZMellUh8acsL2I9yXvpo4/oBlVJ6TplJRzC3sIUhhIJUsokNk7Jzhe5bTThbGUOIwMD8UAux9/JVlQvojAqY0PlGwZKbnv6QTx+eq1lufZaWNsLoaVsYsSczOQn3tY8DeR5M/TTv1BYkCsqWNGNxdrfPxRJkl8k5H1DXjmq0OeijCyU5hegMDkNpcXFMHVRf9tj6uqIgnh1T56y2FlbivEumzCXPpfNp6INIyNDBPl5IqqM15BcxIlPScPvk8fo9MZR22fKuG3QPuRkpVmsc7a2gJGBRG2fCXB+vM8Ul8DYyBDO1uYIcFZ/O09t9t3QLZoUZ6RDWlwsqlWpYuxgj6IULUkt09OFd43ExARGNrYoSk6C1+ixIl+OKtQveewQubduwaJ6CFz7vS5y8Dz1drJT99LRuZ18vRCdoDlM7WnIyQdKSqVQyUMuoCTBZT1c5NB8qwq0l4s4lBdn/tYCjd441x4U42GC0iuFwp/kHjSZKv1ZWxiInDAa1yFPKluHMp41qn2QbdQ35cVW9cqhKl2qv3MuIhd3Z8Yo7XmceNjOyhDpmcrfp8+RsWXce56C9KyScvu9fLcQDxYXP2GLjaUBMnOUy9DnqETNY5Od+3hsynjs0DIZjz17gn2N4WxvgF8+VPfuGtXbCneii/HzKvV91cbGTrwlpmpVqlCiY7syXjplr21uHrJKan4B1RAb9RCb1y5XE3LMzMxFG5qqBofhw3f74+DebejV7y2t/Vpay+yhajZq656ZAutyrguHti/Gwa0LRT4cD58gjSLOijkfibw4Iz9botMbhzC3lF2jcstcoyhhLXk0PAsJjyLE8n/90Ecxjzwmou+dFdWxPvjlqta39lbW9uK7solY6TPl4dAFVbnas2kx3v9yvniwVOvT0Ahu3uoetG5eAbh3U3v4mIV8O5UZG0pYW971m6pcHdm+AEMnLhYJkl8E8m2VVyaZMFWMIq+c5+Xw+q8Ref0Q+oz9C1Z22j2jCTP5fpOtbkse2fKM+82zIr/PynnB91l71/6Ipl3eES/JCFevIFHh6tiO+TqFHAsdx7dVOfvwke2LcWjbQoyYtEhUsnterGweH0/p6mOTmV6x42nvpsV47wv140kTTq5e4jijpOIs5DBPC+fIYZ4JEhLI04Q8PC5evChCezZu3KgQa9asWYP58+eLsCVVjxSC8reMGjUKGzZswIQJE0S40cuAfpvsomTEqiIJJRumnDYEJUmWe/DIIW+ip/EQohCnZ/19Z2dnkbSYwrBUvXyeFvodeV4ebZiamoqE0KqTalgVQaJLdXcHnHmgTFhNnhFnIuNR01NzdYJaXi54lJYl2sl5mJopBB5VEYfYfPme8MRoXlVWllwXlAzOwzdUxFkrbKHEhzdOifCo58XE1EKIOFTC9O61Ywiq/XyeSWVJP3UJjm3UL8pObZsg7ZRs+0qLipBxIQJObVQ8wCQSOLYOR/op3fkVjI2MEOzvhTMRt9XG5mzEHdTUUta6LBTyczcqTiTTLSviPEpIEomPSYgoDxJdqns44vQDpehRWirF6fuxIneSJmp7u4gQPGon52HK433mcUme2t6uT4TzURsPW90PVyS25Ny+JcKjFEgk4rOufDZi2cJCIeJQOXL7lq2QdvRIuedByq+jezt54+wT2+kWalTVXe1KfTvFqm2nZ6WkFIhJkiLQU3lc0iM/faa8NJqgkt6q7YmqXgZqpb7lIo6TrQQLthUgVz2CUwGJO1RWXD7Fp5YKgaGqt7J/U2NZpazI+FKt6xCdWIqqXurrUM3bEJHxsnMgCR0UWqXar4udBA42BmpluCnnDJX/lk/R8UVIyyxGWDWleEllvwN9TXErUstKVYDElOJy+6UUTUnppYopLrkEGdmlCPZTiviUxNnfwwj3Y4q1js2j+BJUV1lG8li8kS+z61Qe/rcoE98sVk7EP/tzsWz7k4mPjYxlpcGvXTmvtg9HXD6HqkG6E32rUiot1fiSomwbCsUq77pA5cPvPk5ULLfn7rVT8K2q/bpwcOsi7N/4B0ZMnA/vgDCtIk5y/EMh9JBgVB6UrNjVOxSPbp9UC6+hz+5+uvOcacMnqDHemrwVgydtUkyuPmGoXr+7+F9X6AVtK++A6mqJVWls6HNAtVraH7o3L8bOdfMx9vN58K0S+kSfNC8hRl1AT4x9CAcnd93Xb79Q3Cuzne5dPwWfQO3b6cj2hTi4+Xe8/fF8eGnYTs8KbSsXr1BE3VHfVtF3TsHN79nvJ+hFHIk496/uQ6/RS2Hj6FUhW5w9QxFT1pa7p+Dm+/z3Nk+D4eP7rPsq91nSF3CfRRW0JBL1R0wKVZZ7eOk8vv1C1BIVi+M74hR8dew3h7ctwv7Nf2DYJy9uvzEyenw8qST+JltuXzsN/3KOp13r52PMZ08eT5pIS4lHTnY6bOxfrYj3MpEYSPRy+i/CHjnMU0OeNyReUEgVVWOiz0lJSUIUIcjjhkQCymfz9ddfP1HBivLFUJUoquxE+Wzky71oKJyLwrgoF42DgwN8fHxEThuqakX5dQgSlMgjiNqQAHX+/HkRDvY0Xi4UYjZmzBjRFwkqtE4UbuXk5FTu71NYF4WHffbZZyLsjMbyaX5fNfSKlqVqVZQ8mn6P3og+C4MbheCLLcdFiFSYpxNWnr6BvKJikZyYmLL5uCgtPq6N7M1q/3rVsObcLfyw+ywGNggWIs6i49fE/6qQ0LPl8j10rxkgPHgqQnjHIdi48FN4+IXB078mTu1dhqKCPNRpJntbuWHBJBELTaUt5YnykmLvKW7Ms9ITEPfohhBtqEIVcffaUYqegZObP1ITH2LPPz+KfDnyPnWVH7cMVObRsfD3gk2tYBSmZiA/Kg5B33wEM09XXB46SXz/cP5q+I55A8Hff4Kopevh1LqxKDd+tsdIRR8Pfl2CWotnIP38NWScvQK/cW/DyNIcUcs0V2dQ5Y3OrfDVn6sQ4u+N0Cq+WLXrMPIKCtG9pSxU8Ms/VsLF3hbvvS4LD1qwcTdqBPrCy9UJ2Tl5WL79oKhG1at1Y4WIM3H2UtyKjMYvE0YIASE5XfaQZ2tlIUQJbQwOD8MXG4+KUKgwT2f8dSpC7DNUxYr4fMNhuNhY4oPHYVL9GwRj9ZkbmLHrFAY2DBE5chYevYxBjWQCJ/FmeCjeXrRNJEHuEOqPazFJWHf+lgjHKo+E1X/D//MvkHPzBnJuXIdr/9dhYG6G5O3bxff+U75EUVISov/8XXy2DAmFiZMzcu/ehrGTMzyHjRDqRPyqvxR9eo0cjfRTJ1GYkABDCws4tu8A6zp1cfuj8TptGdSlNab98ReqB8i20987D4mk0/LtNHXeCjg72OK9AbJS4gs27BQVw7xcnUUuoxXb9ovt1LO1UvDLyM4R85LTZEIXlYknHB9XudLF0SvF6N/aWFRyikosRbOaRjAxBs7dkj3ov97aGBk5Uuw6I/t87GoJRvUwQYuaRrjxqAS1Aw3h5WyA9YdlAgQdyoPbm4gkykt2ForKaHIPnrwCmbigiyOXitChvokQL1IzpejS2ET8/tX7SrFiTC8zXLlfgmNXZELAoUtFGNTOVNj/KKEELWubwMRIgtPXixUJk+n/Xs1MkZtfgPxCKfq2NMWDuBKtgpWc7Ycz0be9HeKTipGYWoTXO9sjLbMEZ1UqUn052g1nruZg17HHiU1NJHBzMlZLbuznYYLs3BIkp5dUuN+y7D+bjy5NzJCYWoLkjFL0bG6O9OxSXLqtFDs+HGCNi7cLceiCbHvsO5OPId0sERlXLKa29c1AVaJPXJF9T8mNVT185FAi6JQMzWPTtdcA/P7LNwgIDEZgtRDs3LwGBfn5aNlOdm6Z9/PXsHd0xsC3R4vPm9YuF21d3T1FAt6L507g2MFdGDZalhcuPz8Pm/5ZhnoNm8HOwRFZmRnYs3090lKS0ahp+YJ6i85DsObPyfDyD4N3lRo4umu5KC/coKXsTf/fv38KW3sXdBkg80AlL5zd6+aI6lX2zh7ITJd5t5maWcDUzFJcK5bPGo+YyBsY9vE8kRdD3oaSlNLDpTbqtR6KXX9NEmILVaS6cEh2jQptLLue7Fw+EVZ2rmjeY4IiuWxKvPwaVYisjAQkRt+AsakF7J19YWJmBScP9Tf4xiYWMLO0e2K+Jtp2ewvL506BT5UQ+AXWwIHtf6GgIA+NW/cS3y+b8xnsHFzR840PxGfywtm+Zi6GfDAdDs6eyEhLVowNhccR7XoMweJfPkHVkLqoGtoQ1y8dx9Xzh/HBV4t02tK009tYv2AyPP3D4BVQAyf2yLZTvRay7bT2T7p+u6Jjf9l2OrJtAfZtmIP+o2fC3skTWY+3gcnj7UTkZqcjPSUOWemyc548jwt5Y1nb6S7nXrvlEOz7+1O4eIfB1acmLh9eJsrBU9UpYu+qSbC0cUGTbsptlZrweFuVFCEnIwFJMTfE9rBzlt1PkIhz+8I2dB02F8amlsjJlO9b1qJ6mTZqtRyCA6s/hbNXGFx8auLKUZktwQ1ktuz7exIsbV0Q3kVpS1oZW5LJFlML2DrJbCkqyEFG8iPFb2SlRos2pha2sLZXFiMoS+MOQ7Bpkcp91j7ZPly7qcyWjQsnwZrus/oqbVG9z8pMS0D84/ssh8f3WdVqtcbR7X/A1sFdVCyj+zCqjlW7WfkVOZt1HoK18x8f3wE1cGy3+n6z5g/Z8d3pddl+Q144e9fPEdWr7J08dO43mWmy/SYpLrJC+02bbm9hBR1PAbLj6eCOx8dTK9nxtPy3z2BLx9Mg2fFEXjjb/5mLt8dNFzlwMtOVxxNNlG9qx9rfUbtRO+HVk5wQJfJSObn5oHqt8u9tGKYsLOQwTw2JNFR1iqpFZWZmioTHJIbIE/qSgEC5cr777ju89Za6izR5jVDlqujoaNFPp06d8Msvv7w0W6myEynolByYPF8oMTGVMKd8PgSJK1RV6sMPPxQhYpS/huyWV9kqDxKkKESMhBhalkKtSJyhql4V+X0SXP766y8h9pBnEuUeospc77777lOt58cff4y3335bePrk5eXhwYMHQtx5FjqG+iEtNx+/H76M5Jw8BLnaY97ANopktnEZOeJhTY6brSXmDWqLmXvPod/8rSL3zaAGwRjaRP1NxKn7cYjLzEGvWrqrkqgS1rALcrJScXDTHGRnJMHNuzre/HCBwuU3IzVWTWWnm7s/v1K67Z7YtVhMvkENMHSSrJpafm429q//GZlp8TC3tEP1eu3Rts+HWstoyrGtF4bw/cqKbCEzPxN/o5ZvwJXhk2Hq7gxzb+UbyrzIaCHahPw0GX7vv4X86HhcHTkFyXuPKdrErd0JE2cHVJs6DqZuzsi8fANnuo1AYZkEyJro0LgO0jKz8cf6XUjJyEQ1X0/MmThSUVKcHvSp4piczJxcfLPwH9HWxtICwX5eWDR1nChdTiSmZeDIBVkVmkGfz1T7rT8+G4v6Idq3W6ewAKTl5GPewQsiPCrIzQHz3uyg2GfiM3LUbHGztcLvgzvix12n0e/3TXCxscAbjUIxtJmyqhQJQj+/3haz95/Hn4cvwdPeChM7NULXmrqTZBOpB/bByM4OniPegbGDI3Lv3sHtCR+i+HF4iImrGymLivaUvNjznZEw9fAQSYwzTp3A/f9NQ0l2tqKNkb09AqZMhbGjI0pyspF7754QcTLPndG9ncLrIj0zG3+u24GUdNpOXpj96WhFCByFsKntwzl5+HbhatHW2tIC1f29sWjaeFG6XM6R89fw9Z8rFZ8/nyMTf9/p0wnvvqae76gsl++ViKTHHRoYiXCk2GQpFm0vUCQ0trOWiEpHckj4WLW/EJ0aGqNTIyPhSbN8d6Eo+01Q4t1Qf5mXwIf91B9c/thSgPuxuoWT/ReKYGIsweutTYWXyv24Evy5JQ/FJeoVnKzMlP1cvFMskh53bmQikiLHJJWKZSgJs5yNRwtQKjXB0C5mIgHzzUclWHeofK+azQcyhDAzsr8jLMwNcPNBAb79Mx5Fxcq+XZ2MYG2p9IwI8DbFtPeU22dIL1m45KEzWZj7d3KF+y3L7tP5MDGR4M1OlrAwo2pjxZi9Jkt9bOwNYGWhFMbP3SwUSY97NDcXIVXRiSViGW2hcxUhvHk7ZGakY93KBUhPS4VvQFV8Ou1nRWhVclKC2tv3gvw8LPl9JlJSEmFiYgoPL1+MnTBV9CO/R6BEyUf27xAijpWNLapUDcbU6fNEKfLyqB3eWVwXSJzJykiGh28wRkz6UxFaRQ9sqvac3Lda5nEzS110bd9nDDr0fQ8ZaYm4fuGgmPfLZ+qC/qjPl6JKiHqSZlWC6nVBbnYqTmyfjdysJDh7VkefMQsVoVWU80bVluyMRPw1Q/YQSJzfv1hMXoEN0f8D5fXlWanXtBOyMtOwbc08ZKUnw9MvCGM//10kaCXSkuPV7Dm65x9RnWfhT7KHdDld+o1C1/5jxP+1G7UVZcwph87axTPg4uGHER//jMDqyjA5TdRsTNfvNOzfMFtsJ3ef6hjyyXzl9bvMdjp9QLad/p4jeyiWQ+XG2/Z5T/x/8+JBrF8gu/YSa+ZNeKKNNqrW6YK87FSc2TVHCC60rbq/u0ARWkVlw1UraeZkJmLNT8r7iYuHFovJo0oD9Bkr21bXTvwt/m6cp36v23bAdwqBSKMttbsgn2zZPUfsN04e1dFthNKWbA22/POL0pZLhxeLySOgAXqNkdmSGHUNm/94W9Hm+BZZZdOg+r3QdoDsf233WblZqThE91mZsvusN8reZ0nK3GdNU9pycvdiMdF91pCJMls6D5qCg5tmY8dfXyMnK0V4P9dr+Tpa9pDtU7qo1Vh2fJM4I45vn2AM+0T78X1qv2y/WTlb/fhu23sM2j/eJ+j4Xrfgc8V3f8+d8EQbTdRr0kkkPd7+j8rx9JnyeEotezztlR1Pi35WP546vyY7nsgrKebRHZw+vAV5OVmwdXBBcM1wdHv9PRjr8O5lGG1IpGUTdDDMC4A8TshLZ8uWLf+2KYwO8lZ8A31iU4DyQvtvY9NK3aPo36bFiZcneD4txnd1hyi9aq7OlYV16gNBs9QTiv+bfHNWd6nXV01hke7wz1dJzP3nzzn0InFwff4Syy+KkX3067YwOrP8MKdXRVyq/lSVqeL27OF+L4P0PN0vQ14lccn6FUbxClM3lovz8xU/fOGYm+jP4FiZag5b/TdoX6tyJPnWxINhMg9jfcN/8X/vmZQ9cpgXSkZGhijfvWrVKhZxGIZhGIZhGIZhGOYFw8mOmRdKz549Re4cyhfTvn37Ci9H7Sm3i6aJvvu3oHAxbXZRCBbDMAzDMAzDMAzDvErYI4d5oaiWGn8aKCky5XnRBOXS+bdYuHChyDmjCcpvwzAMwzAMwzAMw8iqVjGvBhZyGL2Aql/RpG94epZfJpthGIZhGIZhGIZhXhUcWsUwDMMwDMMwDMMwDFNJYI8chmEYhmEYhmEYhmGeCw6tenWwRw7DMAzDMAzDMAzDMEwlgYUchmEYhmEYhmEYhmGYSgKHVjEMwzAMwzAMwzAM81xIDNhP5FXBI80wDMMwDMMwDMMwDFNJYCGHYRiGYRiGYRiGYRimksChVQzDMAzDMAzDMAzDPBdcterVwR45DMMwDMMwDMMwDMMwlQT2yGGY/8fcaDQa+kTKXegN3U78An3iSJMPoS+4XDsNfcJlaS/oC/mLvoW+YF69DfSJkuxS6AtFBUXQJ3Ky8qEv+BZGQp+wtveEvmBgoD+2BFo8hD4Ra+wOfaGwyAr6RGGx/ngo+DjkQJ+wMNKfc5+5of7YAujPuYbRX1jIYRiGYRiGYRiGYRjmueCqVa8OHmmGYRiGYRiGYRiGYZhKAgs5DMMwDMMwDMMwDMMwlQQOrWIYhmEYhmEYhmEY5vmQ6E9OqP867JHDMAzDMAzDMAzDMAxTSWAhh2EYhmEYhmEYhmEYppLAoVUMwzAMwzAMwzAMwzwXEgMOrXpVsEcOwzAMwzAMwzAMwzBMJYGFHIZhGIZhGIZhGIZhmEoCh1YxDMMwDMMwDMMwDPNcSAzYT+RVwSPNMAzDMAzDMAzDMAxTSWAh5/8Zhw4dgkQiQXp6+r9tyn+CVq1aYfz48c/dz5AhQ9CrV68XYhPDMAzDMAzDMAzz34VDq/4fCA21a9fGr7/+Kj43adIEcXFxsLW1/ddsWrp0qRA//j+KSZGRkfD398fFixfFdpEza9YsSKVS6At7tq/H1g0rkZGWCh//QAwZ+RECq4VobHvmxCFsWrscCXHRKCkuhpuHN7r2GoDmbTor2qxbtRAnj+xDSnIijIyM4R8YhNcHj0RgUGi5tlw5thIXDixCblYynDyC0aLPFLj51tTYNiXuDk7vmo3EqAhkpcWiea/JqN3ybbU25/b9iXtX9iIt8T6MjM3g5lcHTbtPgL1LQIXG5p+9x7Bi+wGkZGShqo8HPnmrD8Kq+Gpsu/XIGUyb/7faPBNjI5xY8qP4v7i4BPPW7cDxSzcQk5QCK3MzNAyrhvdf7wZne93HqEOz+giYMBy2dcNg5uGCc33HIGHLft3LtGiIkJmfwiqkKvKj4nD3+98RvXyjWhvf0YMQ8NFwmLo5I/PKTUSM/x8yzl4td1z2bl+L7Rtpn0n5P/bOAjqKpGvDb9zd3YUoDsHd3WWxBRZnWdjF3WVxFnd3d3cLGghBEizu7vafW8NkZsLMJMjuF/jrOadP0tPV1dVV3V3Vb997C7YOLuj92xg4uUpvX//bV3D84Naia8bM0gYt2vVArfotPtVLHg7uXIsnD28jNiocGlra8PKtgq69h8HAyASl4fjJUzhw6AgSEhPh6OCAYYN/g7uba4n7Xbl2HfMW/g2/6tUwY8qkovJs3b4T9x88RGRUFLS0tFCxvC/69+0NIyOjEvPUqN4QmnVaQFFbD3lRoUg9vgN5YW+lptUfOAGqjuU++z375RMkb1vC/lfQ1oV2s65QdfGCoromct6/QtrxHciPjy5FzQBV3RRRw1MR2hpAdEIhTt8vQHi87OePh50CGpRXgr42kJACXHiUjzfhovTtaiihgrPkd6E34QXYeSm/xLLU9FJGvfIq0NFUQER8AY7cyEFoTIHM9D5OSmheVRUGOgqISy7EyTs5ePlRdBxvRyX4earA2kQRWuoKWLwvk+X7JXRvZYTGNfWgpaGIl28zsXZPDCJjc2Wm93DWQPvGBnCyUYehvjLmrQvHvafpRduVFIGebYxRyVMLZsYqyMgswNNXGdh+NBaJyfLrqGNDHdSvoglNdUW8/pCDLceTEB0vf59G1TTRsrY29LSV8DEqF9tPJuNtmKD8xvpKWPaXmdT9VuxJwP3nWVK3HTpzCbuOnUFCUjKc7W0xun9PeLiU/My8cPMepi1di9pVKmDB+JFFv9fo2E9q+mG9uqBnO1HfIYuTJ47j8KEDSExMgIODIwYNGQY3N3epaW/fuon9+/YgMjKC3cuWVlZo374TGjRsVJQmMTERW7dsxONHD5Geng5PL28MGjwMVlZWJZbl5vnduHpiC1KT42Bp64b2fSfC1ll6H3X30gE8uHEcUWHBbN3awQMtuv4ukf7cwX/w+M4ZJMdHQUlZhaVp3vV32MnIU9qz7+Chw0XPvqGDB5Xq2XeVPfsWsWff9CmTRed36zZOnTmDN8EhSE1NxeoVy+HkVLr+8tLp/ThzZAeSk+Jha++CngP/gqOrl9S0D+5cxqmDWxAdGYr8/DyYWdiiWdueqFG/ZVEaGicd3bMO1y4cQUZ6GlzcfdFr8HiYW9qWWJb7l3fh9tlNSEuOg7mNO5r3mAwrR+l1GhP+BlePrkDEh0Akx0egabcJqN5YcixRUJCPq8dW4dnd4yxPHX1T+NZsjzqthrAPpiXx8Mou3LtA5YmFqbU7mnSbAksH6eWJjXiDG8dXIOojlSccDTtPQNVGfT9Ll5oYjSuHFyEk8AbycjJhYGKHln3mwsLeW25ZLp/eh7NHt7N2srF3RY8BY2W207Xzh3Hn6kmEfwxh63ZO5dCh53CJ9JTPwe0rEPjkDjLT0+DqWQE9BoyDWSnaqayNQU+fOIojh/YhKTEB9g5OGDhkBFzdPu+jiTu3ruPgvt2IjAxHfl4+LKys0LZ9Z9Rv2KQoTbsWDaTu2+fX39C+Uzf8DPBZq/47uEXO/zNUVVVhbm5eqk7mRyY/Px8FBV82eP9fQsKavr4+ygJ3blzEjo0r0LH7r5i7bAvsHJwxf+ofSE5KkJpeW0cX7bv0wcxF67Fg5XbUbdQCa5fPxdNHd4vSWFjaou/gMViwagemLVgDE1MLzJ06CinJiXLL8vrxadw4Oh9Vmw5DtzGHYWzphuPrBiAjNV5q+rzcLOga2aBGqzHQ1JH+wh8e4g+fWj3Q+fd9aDt4Mwry83Bs7QDkZmeUWDfn7z7G0l1HMbB9U+ycPQautpYYsWAdEpJTZe6jpaGOs6tmFC0nlk0t2paVk4OX78MwoF1j7Jw1BotG9cOHyBiMXrKxxLIoaWkiJeAVno+cgdKgYW+NKsfXIf7qPdys3BbvVm6D97rZMG5cqyiNRefmKLdoAt7M/gc3q7ZHasBLVDu1CaomhnLzvnvjAnZtWo723fpj9tJtsLV3xoJpv8u8ZrR0dNGmcz9MW7gRc1fsQp2GrbB++WwEfLpmcrKz8D7kFdp1/RWzlm7HqPHzERn+EUvm/Fmqc716/QbWbdiEX3p0w+oVS+HoYI+JU6YhsQTxOCo6Ghs2bYGXp+SAMTs7G29CQtCze1eW37RJ4xEaFo6pM+eUWBY172rQbtkD6ZeOImHVVORFfoT+r39BQUtHavrknSsQN2dE0RK/dAIK8/OR/ex+URr9XqOgZGiC5B3LkLByCgoS46DffxygolpieTztFdC0siKuPs3HupN5iEoEejVSgpa69PQ2JgroVFsJj4MLsPZkHl6GFqBbPSWYFntckXCzaH9u0XLwRskiTnlnJbSpqYrzD3Kx9EAmIuIK8FsrdSYwScPeXBG/NFbDvaA8LDmQiefv8tCvuRrMDUX9maqyAt5F5uPUnRx8DSTItKqnj7V7ojF20UdkZRdi2ggrqCjL7jPVVRXwLiwb6/bFSN2upqoIRxs17D8Tj9HzPmD++ghYmapg0mD5IkGr2tpo4qeFzceSMW1NLLJzCzCurxFU5HyCq+atjp4t9HDkciom/xPLhBzaR1dLMNyLT87HsHlREsvBiynIzC7A09fZUvO8eOseVmzdi1+7tMWWRdPhbGeDP2YtRkJyitzyR8bEYdW2ffAt97mIcGLjMoll4rBf2bikXvVKKInr165i44Z16N7jFyxfuRoOjo6YOmUikpKk9yfaOjro0q07/l68HKtWr0OjRk2xbOnfePjwQZE4MHvWdERFRmLy1BksT1NTU0yeOA5ZWZlyy0KCy/EdC9Gk41D8MfcALO3csH7+IKQmS++jgoP8UaFGCwyZvBkjZuyCvpE51s37DckJIhHWxMIOHfpOwp8LjmD4tB0wMLHC+rkDkZYi/Xla/Nm3fsNG9OzRHf+sWMaEnElTppb44Uzw7NsML8/PX2yzsrPg6eGB/v0khYySuHfzPPZuXoq23QZi+pKdTCBYPGMEUmSNJbR10arzr5i8YAtmLduLWg1bY9PKmXj2+E5RmtNHtuHCyb3oPXgCpizcClV1dSyZMQK5OdKvXSHP75/G+X3zUbfNMAyadhhmNm7YuXQA0lOkt1NuThb0TWzQqOMYaOtJH0vcOrMBD67uQfMeUzBs9ik06jQGt89sxP1LO0qsmxf+p3Hp4DzUajkMv046AjNrd+xb0V9OeTKhb2yNeu3HQEtXenky05OxY1F3KCqpoOuIDRg4/RQadB4HdS35H4Xu3zyHfVuWoE3X3zBt8W7Y2Ltg6cxhMtvpVeBDVK3dDH/NWo+J87fC0NgMS2YMRWJ8TNH9tGreaMRGh2HEhKWYtmQ3jEws8Pf0wcgu4X4qa2PQm9euYPOGNejWozeWrFwHe0cnzJgyTs6zRhedu/XEgsWrsGz1BjRs1Awrly7E44f+RWm27DwosYwY9Rd79vnVrFNi3XD+e/755x/Y29tDXV0d1apVw/37orGYNMhwws3NDRoaGrCxscEff/yBrCzpH0i+B1zI+Ykhd51r164xaw96SNBC1jDirlW0TgLCyZMn2YWnqamJTp06ISMjA9u2bWMXr4GBAUaOHMnEEfEXmz///JN9raKv03Rxk9tWSVCafv36ITk5uahM06dPL/oi1rt3b3Y8Kkfz5s3x5s2bUp2r8DyOHz8ODw8PqKmp4ePHjyWW88OHD2jdujU7Jm339PTE6dOni7ZT/VWtWpXlZ2FhgfHjx7MverKg8zl69KjEb1QuKh9B1jhEhQoVBIPWevWkulZRuanOaTBJD49atWrB39//Mxe5S5cuoXLlyqy+yNrq1atX+FZOHd2LBk3boF6jVrC2dUD/oWOhqqaGqxdOSk3v4V0RVfzqwsrGHmYW1mjepits7Z3w6kVAUZqa9ZrAu3wVmJlbwcbOEb8MGInMjHR8fC/4oiOLJ1e3wtOvMzyqdYShuTPqd54BZVV1vLh3SGp6M1tv1GozFq4VW7IvmdJoO2gjylXtACMLF5hYuaNxj3nMeicmLLDEutl15ira1fdDm7rV4Ghljgn9OkNdTRXHr92TuQ9ppsb6ukWLkZ7oBV5bUwOrxw9B4+oVYG9pCm9ne4zt3RFB78IQFSd/gBF77jpeT1uG6GMXURrsfuuGzHdhCBq7AGkv3+LD6l2IOnQODr+Lvuo5jOqH0E37EbbtMNKCQvBs6DTkZ2TBpm9HuXmfObYH9Zu0Rd1GrWFl64h+Q8dDTU0d1y6ekJrew7sSqvjVg5WNA7tmmrXpBht7Z7x68YRt19TSxvhZK1G9ViNYWtvB2d0bvQf9iXfBLxEXG1XiuR46cgzNmzVB08aNYGdri9+HD4WauhrOnZddV/R8m79oMXr17A4Lc3OJbfRsWDBnFurWrgUba2uUc3fH8CGD8CY4GDExsXLLolm7GTL9ryLr4Q3kx0Qg9ehWFOZkQ6NyXanpCzPTUZCWXLSQ1U1hbg6yPgk5SsbmULF1RurRbcgLe4f8uCikHtsGBRVVqPv6lVg3Ncop4uGbAjwJKURsMnDybj5y8/GZRY2Q6uUUERxRiFuBBYhLBi4/KUBkQiGz6hEnLx9IyxItWaXQUer4quDuizz4v8xDdGIhDl3LQW5eIaq6S793a/uo4NXHfFx9kouYxEKcvZ+L8NgC1PQWpX/4Og8XHuTidVjJQpI0WjcwwP6zCbgfkI4P4TlYvi0KhnrKqOarLXOfRy8ysPtEPO49TZO6PSOrANNXhuPWozRExOTi9fssrN8fA2c7dRgbyFZlmtXUwrGrqXgUlIXQ6DysPZAEfR0lVConQ3UD0LymNq48yMD1R5mIiM3DlmPJyM4tRN1Kmmw7GX4mpxVILJU9NHDvWSayc6RbZe09cR5tGtVBqwa14WBjhbGDekNNTRUnL92QWY78/AJMX7YOA7q2g5XZ5y+eRgZ6EsuN+49R0csdVuamKImjRw6habPmaNykKWxt7TBs+O+sj75w/pzU9D4+vqhRoxZsbG1hYWGJtu3aMyueF4HP2faI8HC8ehmEocNHwtXVDdbWNhg6bCRycrJxrYRxzfVT21C9QSdUrdce5tbO6Nh/GlRU1XH/6mGp6X8ZvhA1m3SHlX05mFk5ostvM1FYWIA3z0UvnRVrtoKrtx+MzGxgbuOMtr+MRVZmGiI+vi6xbg4fOYpmzZoWPftGFj37Lsh99i1gz74esDD/3FqrUYMG+KVHd1QQsyIuDeeP7UKdJu1Qu2EbWNk4oveQCVBVU8eNS8elpnf3roxK1evD0sYBphbWaNK6O6ztnfHmU79AAsGFE3vQukt/VKxWjwkOA3+ficSEWDy6J7+d7p7fiop1OqNCrY4wsXRGq14zWDs9vil9LGHl4I0mXcbCq5rssURo8GO4lW8IV996TGTxqNwMTp41Ef6uZAvW+xe3wLdWF/jU7AhjS2c06ykY2wTcll4eS3sfNOg0Dh5VWkJZhmB/99wG6BiYo1XfecyyR9/YBo4etWBgIt8K5vzxXajTuD1qNWwLSxtH9Bo8ibXTzUvHpKb/7Y85aNC8C2wd3GBh7YC+Q6eytgkKEPRR0REf8fb1M/QaNBEOLp4wt7LHL4MmIjc7G/dunP2hxqDHjhxAk2Yt0LBJc9jY2mPI8D/Ys+bS+TNS03v7lEf1GrVhY2sHCwsrtG7XEfbsWSO6JgwMDSWWe3dvw8unPMwtLEusG85/y759+zB69GhMmzYNjx49gq+vL5o2bYqYGOkfbXbv3s3eEyl9UFAQNm3axPKYOHHiv1ZGLuT8xJCA4+fnh4EDBzJ3KlpIHSwOiTYrVqzA3r17cfbsWSYStG/fngkatOzYsQPr1q3DwYMHi/YZPnw47ty5w/YJCAhA586d0axZsxKFFxIbSK3U1dUtKhMJLUIx48GDB0yMobypY2jRogVyc2WbtBc/jwULFmDjxo0IDAxkIkhJ5Rw2bBgTTa5fv45nz56x/bW1BQP28PBwdvwqVarg6dOnWLNmDbspZ8+eja9FqORevHiRnfvhw9IHe2PHjsWhQ4eYmEYPD2dnZ/bwSEiQ/CIxadIkLF68mNWbsrIyfv31V3wLebm5eBf8Cl6+lYt+U1RUhFf5KnjzSjDolQe12fOnD5j1hLtneZnHuHz2GHtZJ8sNWeTn5TBxxca1hkQkfBsXP0R9EAzsvgfZmQJrGnVN+V+tcvPy8PJdGKp5ukrUTVVPFwQEf5C5X2ZWDlr9PhMtR87A6CWbEBIWKfc4aZmZTKQjked7ol+9POIui75sErEXbsKguqCdFFRUoFfRE3GXbosSFBYi7vJt6FevUMI18xKe5atK1IunbxUEv3xWymvGH1HhH+DuKfs4ZJ5N9ULXjTzoeUECi/hLB5WnQnlfBL18KXO/XXv2MdG1eVORCbQ8yP2CyqOlrSU7kZISlC3tkRMsJhIWFiIn5AUTY0qDRuU6yA64S59kP+X56cU/T+y5WFiIwrxcqNjLd58gFx8LIwW8jRS9sNN/tE6WN9KwNpFMT4REUHrJ4YO9uQL+6qyMEW2V0aqaIjTUUGJZyP3pjZjgQkchAcbOXPrQxM5M8TOB5lVoPuzNvs9QxsxIhYk2AS8zJEQYEl7cHGWLJ1+DproSCgoKkZ4p3XLUxECJiTbPQ0SWBpnZhQgJy4GLrfQXOSUlwMFSBYHBon1IuKF1Z1vpL6P2lipsufZQukVibm4eXoW8R2UfT4n7qYqPB56/FrgHSWPLgWMw0NNF60Ylf2Umd63bjwLQumHtEtPS/R0c/Ably1eQKA+tv3wZVKrnzZMnjxEWFgovL4G7iXCMQRbL4nmqqKjgxQvZ/V5eXg7C3r2Ai5efxH6uXtXx4c1TlAayPiR3EE1tPZnHuHP5ANQ1dZjbVmmefeT2KV4eeha+eCn7I8+uPXuhr6+HZqV89pUG6hfeh7yEp081ibJ4+FZF8CvRC7a8dnrx9D7rF9w+9Qux0eHMddfTR9TXUH/g5OqF4FfP5I4lyEXKsZzkWMLRww9hIV8/lrBxroB3QXcQH/WOrUeFvsTH4Edw9pZ/zVN5yEXKoVh57N1rIPzt468uz5uAy7Cw88KRdSOx/E8/bJ7dDk9u7C+xnT6EBKGcb7F28qmGkFK0E5Gdk8Vc4bS0dQV55gn6KhUxwYnyJAHqTdCTH2YMSvdTSPBr+JSvJFEW3/KV8Orli1KV5emTRwgPC4Onl3SXOXLXeuh/F42aCNzKfxboei6Ly5eyZMkS9g5NBghkJLB27Vr24Xzz5s1S09++fRs1a9ZEjx49mCFEkyZN0L179xKteL4FHiPnJ4bcdWhgQhcduVMRL6W8yNDDikQKJycntk4WOSTeREdHM1GDLt769evjypUr6Nq1K7N02bJlC/traSlQkEmMIRGIfp87d67MMlF5qFz0AiQsE0HCCgk4t27dYmIPsWvXLiY8kYULCTAlQeexevVqppgSpSknbevYsSO8vQUDOkdHkd835UXHX7VqFSuvu7s7IiIiMG7cOEydOpU90L8UExPBl0mKqyF+/sVfEKk9yIqHrJKIDRs24MKFC0xI+uuvv4rSzpkzB3XrCr7skwrcsmVLZsJHVjzFIcGKFnHoi6OqquiNKyUlifl96xlIutLo6RsiIky2WEG+6kP7tkVebg4UFZXQb8if8KkgGmwRj+7fwopFU9nAVd/ACBNnLoOunmx3ssz0RBQW5ENTRzIGiaaOMRJjBAOnb6WwoAA3js6FhUNFGFnIfwlOSk1HfkEBDMUsaghafx8pXZ23szDFlIHdWCydtIxM7Dx9Bb/OWIH988fBzOjzc8/OycXKvSfR1K8CtDW/74ujmpkxsqPjJI8XHQcVPR0oqqtBxUAPisrKyI6RNO3Ojo6HlpvseAipwmtG//NrJjJc/jUzol+romum7+C/4F1BNJgsfp3u3bYKfnWaQFNTvpCTkpLC3CoNirkq0npoaLjUfZ4HvsDZ8xewZuVyuXmLypODjVu2oV7dOtDSFFg6SENRUwcKSkooSJN0QSlITYayiUWJx1G2doSyuQ1SDm0q+i0/NhL5iXHQatoZqUe2oDA3G5o1m0FJ3wiKOvLdMzXVSEBRQFox6/a0zEIY60oXcrTVBdsl0mdBwv0pOKIAQR+BxLRCGOoooGEFJfzSUAEbz+QzIUEaFL+GypKaUSzvzEKYGkh/tlIcnbRi6Wl/Hc3vI+To6ymxv0kpklaXySn5MND9fsMlctPq094YNx6kIjNLupCjryM4p5Q0ye20TrFvpEH1oKSkgOQ0SbGLrG4sTKSLP/UqayI8JhdvPkr/YJKUmip47ukLXtKEGOrp4UO4dOu4p0GvceLSDWxbXDq3z9NXb0FTQx11q4le3kq6v/UNDCR+19c3QFhoqMz9qF/t06s7GydQ3z1k2AhUqCh4QbO2sYGJiSm2bdmM4SN+h5q6Oo4dPYy4uLjPPp5I5Pnp2aejJ9lHaesZISaidH3Uqd2LoWdgKiEGES8eXcWOFX8yFx8dfRMMmrgB2rqS5yyzbvQNpDz7wqTu8zwwkFnrrC7ls6+0pKYK6ka3eL+gZ4iosPdy+4XR/ZuzfkFBUQm9Bo2DZ/nqRXFXCF19yfrW1TNkAo/MPFMFYwktXcn9tHSNERf59WOJWs1/Q3ZmOlZNbsH6MDrfBu1Hwad6a7n7ZaRJH9tQ+eKjpMdOKw1JsaF4dG0PqjbqB7/mgxH5/hku7JsNRWUV+Pi1l99OepLtRO0WGS67ncShWDj6Bibw+CQGkQWOoYk5Du1chd5DJkFNTQPnT+xCYnw0khPlW7CWpTFoakqy1GeNHnvWfJS5X3p6Gvr36lL0rBk0bBTKV5T+bLt88Tw0NDThV7NkEZvz7WRLeQ8iCytapI3zHj58iAkTJhT9Ru3ZqFEjZiAgDXp/3blzJxNuyJvj7du3zCCiV69e+LfgQg6HCT1CEYcwMzNjSqLQMkX4m9CUjCxXyBTX1VXyxZdujtIE/pQGmaCRRQm5PgmhvMjdi7aVBhKJfHxEqndpyknuS0OGDMH58+fZzUmijjAPOi5ZNInHEyKlNS0tDWFhYbC1LV3Qti8lJCSEdQB0LCH0ZZAeCsXrQvx8yfWLoHaSVrZ58+ZhxgzJgfVvw//CoBHjvrnM6hqamL98G7KyMtjXkJ2bVsDM3JKZvArx8KnI0tCL/+Xzx7F8wRTMWrzhMwHgv+TqoZksQHKnkbv/lfx9XOzZIsTXxQGdxs7H4cu3MaSz5BcYCnw8fuU29hVnfN+ShcsfHbpm5izbwXzmA5/6Y9fm5TAxt2JuV+KQK+PKhZOYINB3yNjvXg5mybd4CUaNHA49PcmXVWlQeWbPW8jsR0YOG4J/E7LGoZg6EoGRC/JZHB2djv1hMm0ti5+TExKI7FelswD4N3j+XiSuxCQVIjoxD6M6qMDerADvospOEPfi1KmigyHdRa4ks9dIF/q+J2SJ9NcAwbN67V6RAFzDVwO/thVZZfy9veR4KN8Kxdrx89HA0SuyY3x9KemZmZi5YgPGD+kLfV3pcaCKQy5aTWtXh5qqdKuh7wHFK1ixag2yMrPw5OljbNqwDubmFsztisYekyZPxfLlS9Cta0eBhU+FiqhUuYrApOlf4tKxDSzGztApW6Ei9kGFcPKoijHzDyE9NQl3Lx/EjuVjMHLWns9Eo2999i0sevb97ybAKN4vzFi6G9mZGXgR4M9i7JiaWTG3q7JGoP8ZPLt7Ah0H/g0TK2dEfXyJc3vnsqDH5WtKF07+TWjsQBY59dqPZuvmth4sSPLja3tlCjnfyulDW1iMnbGz1hddwxRMeNi4v7F11UyM7FWPCStkieVdsea/NqlHWRqDkjCzdNUGZGZmIuDpI2zesBpm5hbM7ao4ly6cQZ36DSWsATn/HvOkvAeRG5QwxIc4JOTTOyS9/4pD69KMIgiyxKH9KBwGXes0Xhw8ePC/6lrFhRwOEwnEIeFC2m/C4MEkZCgpKTGlkv6KIy7+/NfQQE1cdClNOQcMGMBclk6dOsXEHLrJyVVpxIgRX1UGOn7xjqq0rmFfg3g7Cc9dVpBnUpXJ11OcFx8lYzro6uqzTpdmChCHgszpF/tCIg4NfM0trdn/9o6uiAj9gGMHtkt0ourqGiwNLS7uXvjjty64cuEk2nXuLTVPDS0D9kWueGBjmr1KU9cY30PEef/iKjoM3wltfenWUeLo62hBSVHxs8DGtG5UCgGAUFZWgpu9FUKLWcYIRZyo+ESsmTD0u1vjCK1vyCpHHFrPTU5FQVY2cuISUZCXBzVTyRcFNTMjZEdJllccHeE1UywQIa3LGyAJrhmBq6edoyvCw97jxMFtEkKOQMSZiPiYSEyYvbpEaxyC3DYp7+KBjWnd0ODzr2+RkVGIjo7B1Bmzin4T3sPNWrfD5vVrYPlJJGUizvyFiImNwcK5s+Va4xAFGalMaFH8ZHJedO46eswqRy4qqlDzrY70C5+7X+ZFvEfiyilQUNOgiwqF6akwGDoNuWHyvy5nZAP5BYWfBRPW1lBgVjbSEFjf0LOlsJiVjuzjJKYB6VmFMNJRkCnk0HYqC1nZFC9LcSsdIfS7drH0tH9qxtcFtr8fkMbcpoQIAxrr6yojMUVk1aKnq8SCGX8fEccSJoYqmLo8VMIah+LghISKAgspfyqLrrYiklJF6Wj9Y6T0PoXqIT+/8JPFjiiNnrbiZ1Y6RFUvDaipKODmY9mNqa+jI3juJUlalSUkJ39mpUOER8WyIMdj54ksPAo+3U+1O/fHnpXzYC0WB+fJi9f4GBGFWWNKJ4oK7++kRMkYYhR8lOJNyIL2sbQUBJd2dHJC2MePOLB/LxNyCGcXV6xctZZZ7uTl5UJPTx+jR42Ai4tsS02tT8++4oGN05LjoaMvv4+6cnILLh/fhMETN7IAycVRU9eEmrkdjM3tYOfii3l/NMf9K4fRsN3AkuumWCBWevZRHMAvefY1b90Wm9avLXr2fSk6OoK6KR4wNzk5AboGssUoKr+ZhaBfsHV0Q0TYO5w8tJUJOXqfLHFSkuKhbyiq35TkBNg4yG4nTR3BWKJ4IOH0lDho6339WOLCgUWo2WIgi6NDmFm7sRmubp5eL1fI0dSWPrah8n1LeSgos7GF6KMsYWzhiFePpceOkminZMl2onYT1rcsaJar04e34M8Za1kga3HsnTwwfeleZKSnMtdBHT0DzB7bG/ZO0md7KotjUB1dPanPmuRSPGssip41zuxZc2j/7s+EnMDnAQgPC8Wf40UTYPwslNVZqyZIeQ+SZo3ztVBoEvL2II8OMkwIDg7G77//jlmzZmHKlCn4N+Axcn5ySOUVD1L8PaBAvZQnWX5Q7BbxRZa7UEllKleuHHtJundPFDQ2Pj6eBe8l165/s5zkPkWKKcWrGTNmDHNjEpZJGKtHCLl+6ejowNpa0GFIc52i2DfiLmP01Uv83Al5bULWUZSOjiUuBlGw46+tC+HDigZ64ou4WxWhrCKYlvF5wMOi30gYCnz6AC5u0qeilEZBYUGJAhalITNYWSgpq8LU2hNhr+9IuEKFvrkLc7svC7ooDrUniThvn11E+6FboWckvS2Lo6KsDHcHa9wPfC1RN/6Bb+DjLH368eKQi0JwaCQLelxcxPkYHcsCH5Ng9G+QdPcJjBoITNSFGDesgcS7nwJJ5uYi+VEgjBuImfgrKMCovh+S7sr22xdcM+7MqkbimgnwZ0GKSwu1rfg1IxRxoiNCMX7WKjaoKq246eLsjCdPnkqU58mTABakuDg2NtZY989K5lYlXKpXqwpfH2/2v4mxsYSIEx4RgflzZrH7p0Ty85noouokNhOMggJUnTyQ+1F2fBFC3bsqFJSUkfVELGZRMQqzM5mIo2RkBmUrB+QEPZJfnAIgMr4QjhaiQRb952CugNBY6eJJWGwhHM0lB2W0f2isbPFEVxMsRk5qMZes4mUJiy2Ai5VIZKejuFgr4UOU9Lw/RBew7eK42ijhffTXCTk0I1VUbG7REhqZg4TkPPi4iQQ6DXVFuNqr49XbrO8i4liYqmDaijCkpkuWOSunENEJ+UVLeEweklLz4ekoekZrqCnAyVoVbz5Kf25St/IuIheeTqKvu6TvezqpIViK61S9Spp49DJLrhCmoqIMNyd7PHz2QuJ+ehAQBC/Xz+NL2FlZYMfSWdi6eEbRUqtyeRbImP43M5J8ATp56TrcnezhYm9b6vvb2dkFT58+kSjP0ydP4O4u/yVRHBKXpPVRFNicRByKkUexeKr5yQ4grqysyqYGFw9UTGV5E3iPiS+yIAHn4uG1+G38Otg4la5fLSygr7s5pXr2PX4SUOzZ9xQe7m4ynn2rsGbliqJF9OxbUfTs+xqoX7B3cseLTwFwhWUJon7BrXTTqBOFYuMEEzMr6BkYMUsdIZkZaQh5/RzObt5yxxKWdp54GyQ5lngbdBfWTl8/lqCZpBQUJF+jKA4HlVkeVB5zW0+8L1aeDy/vwMpRdpy4krB2qoj4aEkxPyH6PfQMreS2E00fLgxUXNROz+7DSU47nTmyFScPbMQfU1fB3ln2uFRTS4eJOBQA+X3IC5SvJpjgQ155ysoYlO4nJ2dXZlUjXpaAJ4/g5l76sXihjLJcPH+G5e/gKCm+cf491KS8B8kScoyNjZkRAIUZEYfWZb3rklhDblRkJEAhOyjeLAk7ZCTwb82kzC1yfnLIRYrEkffv3zMrlO9xIZGrUs+ePdkMU2S9QoJJbGwsm0GJXH0oTktJZSJrGUpP8WzItcvFxQVt27ZlQaUosDKJJRTzhWabot//rXKOGjWKxaGhtDRrFsUBIgGHGDp0KAvMTNY5FDSZRCUywSM1V1Z8nAYNGrCYOuSSRWINxdMRt5qhAMxkOURxekgMolg2xU2aaSBJ7l4UC8fQ0JC5SS1cuJAJQv3798e/Tct23bBm6Ww4OrvD2dUDZ47tQ3ZWFuo2asW2r14yEwZGJujeR/AF9eiB7SytmYUVCyL3+MFt3LxyFr8OEcTyoelbj+7fhkpVa0Hf0Ij5HZ8/dQiJ8XGoVrOB3LKUr9cXF3ePh6mNF8zsfPDk2jbk5WTCo1oHtv38rnHQ1jNl040LgwgmRAtmISjIz0VacjRiw4OgoqoJfROB2HLt0Ey8engSrfr/AxU1LaSnCHy21dR12KwR8ujZvB6mr9sNDwcbeDrZYffZa8jMzkHrugKXwKlrd8HUQA/DuwrqasORc/B2toO1mTHS0jOx/dQVNhtVu/rVi0ScsSu24tX7MCwdM4AJPXGfvnzraWsy8Uje9ONazqKXH00Ha+j6uiMnIRlZoZFwmz0a6lZmeNpP4Dr3Yf1e2A3tCfd5fyF06yEY16/Ophv3bzOoKI93y7bAd/MCJD18jmT/ANiP7ANlLQ2EbpMelFtI87bdsW7ZTDg4l4OTqwfOHt8ruGYaCuph7dLpMDA0Qdc+w9j68QNbWVqaYSI3NwdPH9zGratn0HfIuCLRZMX88Xj/9hXGTFnMnltJn2Ig0BS1NNiTR8f2bbFoyTK4uDjD3dUVh48dZ7GjmjZuyLYvXLwURkaG6N+3DxNNHewlhThtLYGYJvydyjNr7ny8CXmLWdOmoCC/AAkJgq90Ojran1kwipNx4yx0Ow9EXvg75Ia+hWbNJlBQVUPmw+uC/Tv/hoKURKSfOyCxn3rlush+8QiFGZ/PhKTmVQUF9KUzKZ7F0NFp3RPZLx4i503JwSBvBxWgfU0lhMcVIjy+EH7lFKGqDDa9OEHbyPLl4mPB+t2gAvRrqoQaHhRouABeDoqwNFLAibsCMZr2reeriBcfCll8GwMdBTSppISEVIqdI9+M/vrTXHRroMZEoY8x+ajjo8KmD7//UjDo7d5QFcnphTh9V7B+IyAXQ9uqo66vMoI+5KO8izILmHzgqshahgQkA21F6GoJxCdTA/qryM5JnrAk5MTlRHRuboiImBzExOeiR2tjJu6Iz0g1c6Q17j5Nw+lrAqsvdTUFiRg0pkYqcLBWQ2p6PuIS85iIM3agJZxs1TB7dTio+9DXFQhSaen5bMYvaZy9lY529XUQHZ+HmMR8dGqkw8Sdh0EiUWnCr0Z48CITF+4KPhicuZWGQR0N8C48FyFhuWhWQwtqqgqfBTM2MyTrQNVSuXB1a90Es1duZIKLh4sj9p08j6zsbLRqUEtQHys2wMRQH0N+6czco5xsJcVxHS2BMFb89/SMTFy+448RfbrhS2jXviOWLlnExg2uru44duwwmyK7UeOmbPvivxcy9+m+/QT95f59e5hlDc1YxT6KPLiPK5cvspmphNy8cR26enowNTHF+/fvsH7dGlSvXgMVZcS2EFKnZR/sXTMRNo6esHX2xvUzO5CTnYmqdQUWGbtXT2AxcFp2/4OtXz6+EWcPrGKzVxmYWCIlSdj/aEJNXQvZWRm4dHQ9PCvVZ7Fx0lMTcev8HiQnRsO3muD85NGhfTv8vWQpXF2c4ebqiiPHjrFnX5PGjdh2cqUyNjLCr5+effYynn3iv6ekpiI2Jhbxn+IFhYYLXBDJysfQUHbcniZte2Lj8unsRd/RxRPnT+xmrrQ0rTixYdlU6BuZonOv4Wz95MEtrF8wMbdmY4mAh7dw5+pp9Bo8ocjquHHr7jhxYBPMLG1gbGqFI7vXsL6FZrGSR/UmfXF003hY2nvBysEHdy9uQ252JsrXFIwljmwcBx0DUzbduHAsERshGEvk5+UiJTEaUR+DoKqmCUMzQd24+tbHjVNroWdoAVMrZ0R+DGKzY5WvJX+WR4Li2JzcOg7m9l5sRir/S9uYMORTQ1CeE1vGQkffjE03LixPXKSwPDlIS4pGdGgQVKg8poLyVGnUBzsWdMft02vhXrk5It8HsGDHzX6ZKbcsTdr0xKYV05gVDc0ydfGkoJ1qNmzDtm9cPgUGhqbo2EtgqX768FYc27MGA0fPhbGpJZIT44quYXJxIvxvXWACjpGxOcI+BGPPpkWoULUevMr7/VBj0LbtO2P5kvlwdnGDi6s7Thw7xJ41DRs3Y9uX/T0PRkbG6NVPYCl3cN9uZt1n/ulZ8/DBPVy9fAGDh42SyDcjIx23b1xDvwGDS6wPzv8GVVVVVKpUib0zCmcVprEordM7oTToPa34+6HQI+TfcivkQs5PDgX37dOnD7PkIH9NCvL7PaB8aPYmsmChL1ekXFavXh2tWgketPKgYFBkAUOBk8nqRuifSHmSCRrlQUGm6tSpw4JEyXtJ+tZykthCM1dRzBtSZmlGq6VLl7JtJCLR8UlQIcGJRBUSUiZPnizzeCQYUXTz2rVrswDLNHMYuXYJIV98miFs5syZLGAypZM2bfv8+fPZA4OU3dTUVDbF+Llz56SaR39v/Go3QkpyEg7u2sAi6ts5umD8jCVFZq1xsdESX6Gow9+y5m/Ex8cwCx+aLnrYmGksH4IeahSk7vql06wD1dbVg5OLO6bNX82mgZSHa4UWyExLwL2zK5ngYmJVDm0GbWABj4m0xAgJd7r0lBjs/Vtk0vz4yma2WDlVQYfhO9hvz27tYX8P/yNpTtuo+1w2Lbk8mlSvgMSUNKw9dBbxySlwtbPCyrGDiqYUJ5FGUaw8KekZmL1xP0urq6UJd3trbJo2kk1dTsQkJuP6I8HLd49Jf0sca+3EYajsIXtGBb1KXvC7JDgnwuNvgQ9u6PbDCOg/AWoWJtCwEZnFZ74PY6KNx+IJsB/RG1lhUXg2aDLiLtwsShN54AxUTQzhOm0k1MxNkPI0CPdbDUBOsQDIxaleuzG7Zg7tXs+CTpKr1Njpy9jXU6nXTHYWtq5diIT42KJrZsjoGSwfIjE+Bo/uC6Y2nvS7ZJC4iXNWfxZHpzj16tRGcnIytu/czQRaCmI+Z+b0ovsnJjZW4ropibj4eNy5J/hiOWTE7xLbFs2bw75gyyL72T2kaetAq1EH5lJFMW+StixC4acAyBSkuHgcDppiXNXBDYmbFkjNU1FXH9ote0BRm1y0kpD1+BbSLx8t1bkEvi+ElloBGpRXYi5WUQmF2HEpH+mftAE9LSqOqG7IUufgjXw0LK+EhhUUEZ8C7L2aj5hPnmsFhYCZgQJ8HRWhrkpWOIJZrS4/yWdWN/J4EpwPLfUcNK2qAl1NVYTHFWDDyawity19bcmv2++jCrDzYjaaV1VFi+qqiE0qxJYz2ewchHjZK6NbQ9EXtl5NBOLsOf8cnPcv2c31yIVEqKspYmgPM2hpKiIoJBMzV4WzadGFmJuoQFcs4LCzrTpm/yGaEbJ/J4Hr0OU7yVixIxpG+qLpy5dNEsXMIiYvDcXzN9Jdm07eSGMizK/t9KGprojXH3KwcGs8csViMZsaKkFHU1SWe8+yoKuVjI4NdaCno4QPkblsn5RiFkA0HXlCSj6eic1wJYtGNashKTkVG/YeZTNMuTjYYsnk0TDUF3yEiI6Ll3julZYLN++xS79xLelBzmVRp249JKckY+eO7UX398yZc4ru79jYGCiKmfbTS+Dq1SsRHxfHnjcU3HjMn+NYPkISEuKxccNaJDE3JEM0aNgI3br3LLEsFfyaIz0lAecOrkJKUhys7NwxcPy6IteqpLhIiWfN7Qv7mDCwbZlA2BHSpONQNO00jLmVUKBk/+vHmIijpa3PrHaGTdvOpiIvCdGzb5fYs2+GWN3EfnFb3b17D4uXiVzl5i2gGGFgU5LTlOWyqFarCVKTE3F0z1rWL9g6uGL0tJVFLjvxsVHF+oVMbF+3gD3/qZ0oaO7AP2axfIS0aN8HOVlZ2Lp6LnPbcS1XHqOnrvgsxlBxvKq2QEZqAq4eXYm0lFiY25RDzz82FLkyJSdIjiVSk2KwboZoLHHn3Ga22LlVQd+xgn63eY/JuHJ0BU7vnIn0VHKnM0Wlul1Rt83QEuvUo0oLZKQl4MbxFWxsY2pdDl1GbmQBmImUhEiJuqHy0CxUQu5d2MwWW9eq6DlGUB4ShDoMWYVrR5bg5ql/2JTojbpMhFc1gSAji6q1miI1JRFH965BSmI8bBzcmKWNsJ0SirXT1bMHmPvhmoWiiTeINl1/Q9tuAmGCxJ19W5YgJTkeegbGqFGvFVp3lu0WWFbHoLXq1kdyShL27NjC7ieynpk2c0FRWehZIz4bEpVl3erliI8TjG2sbGzwx58TWT7i3Lh2BYUoRO168oWkH5Wy6lr1pdCHe3qHpncwilNKH/fJ/Zbe8wgyFKB3RbK4IVq3bs1muiLDAaFrFVnp0O/FQ3x8LxQK/y2JiMPhlHkevZb/gv5fczv4fxf4uDh9TM6gLHG9huTA/3+J6XORC2RZwFRJ0vT1f4nGpjkoK/xTTjTbVVkgLU2+a8h/Scjzfz+w8ZegbfC/iy9XnOXdSzdbzX9FgoZs15D/mlfJZacsXrpfP8PRv0FE7tfF0/k3eB9fdu4nIiev7LzYOpumoyyhqfxtbqvfEw2lslOWck5l51nzpcRMkB536H+N6bztX7wPeVksWrQIUVFRKF++PPsYL5yYp169eszLhGYZFlpv02zCNPMzGQ9QuA0Sceg3/WIzqX4vuEUOh8PhcDgcDofD4XA4HM4nyI1KlitVcY8K8rogLxNa/it4sGPOd4dizlA8HmkLBX0qK3lyOBwOh8PhcDgcDuc7Qe5mZXH5CeEWOZzvzsaNG1k8HmlQnJmykieHw+FwOBwOh8PhcDg/GlzI4Xx3KPDTj5Anh8PhcDgcDofD4XA4PxpcyOFwOBwOh8PhcDgcDofzTXzJrKCcb+PndBjjcDgcDofD4XA4HA6Hw/kJ4UIOh8PhcDgcDofD4XA4HM4PAnet4nA4HA6Hw+FwOBwOh/NNKPykM0SVRXhNczgcDofD4XA4HA6Hw+H8IHAhh8PhcDgcDofD4XA4HA7nB4G7VnE4HA6Hw+FwOBwOh8P5JhQU+axV/xXcIofD4XA4HA6Hw+FwOBwO5weBW+RwOP+PSW7ZAGWJvMVPUFZQCX6GsoTp83soK8R4VUNZwmtLH5QV4vuNRVkh+1o+yhJZGbkoKygql63vWBpaaigrBCr4oiwRHqWJskJkHMoMeZZOKEskpimhrBCbUICyhKYGygzXn6mjLKGrU3bub0vjQpQVypWt25tTRuFCDofD4XA4HA6Hw+FwOJxvg89a9Z/Ba5rD4XA4HA6Hw+FwOBwO5weBCzkcDofD4XA4HA6Hw+FwOD8I3LWKw+FwOBwOh8PhcDgczjfBZ6367+AWORwOh8PhcDgcDofD4XA4PwhcyOFwOBwOh8PhcDgcDofD+UHgrlUcDofD4XA4HA6Hw+FwvgkFBW4n8l/Ba5rD4XA4HA6Hw+FwOBwO5weBCzkcDofD4XA4HA6Hw+FwOD8I3LWKw+FwOBwOh8PhcDgczrfBZ636z+AWORwOh8PhcDgcDofD4XA4PwhcyPmJsLe3x7Jly/7XxeB8BQoKCjh69Oj/uhgcDofD4XA4HA6HwynjcNeqnwh/f39oaWnhZ6Fv375ISkr64QSO6dOnszI/efIEPypWPbvCZkAfqJoYI/3la7yeOR+pAc+lplVQVobd4P4wb98aqmamyHz7HiGLliHhxm2JdLTN6a9RMKpTE4oa6sj8EIqX46ci9fkLuWV5fmsXnlzbhIzUOBhZuKNWu8kws/WRmjYh6g3un1uBuPBApCZGoEabCfCt3UciTcRbfzy5ugmx4YHISIlFsz6r4ODVqFT1svf+C2y79RxxaZlwNTfA+OZ+8LY2kZk+JTMbqy4/xKWgD0jOzIaFnjbGNquG2q42RWmiU9Kx7MID3AoOQ1ZuHmwMdTGzbW14WhmXWJ4Lpw7g1JFdSE6Mh62DC3r/NgZOrp5S0/rfvoLjB7ciOjIM+Xl5MLO0QYt2PVCrfgu2PS8vDwd3rsWTh7cRGxUODS1tePlWQdfew2BgJPscCcNaleE4pj/0KnpB3dIUDzoORfTxS/L3qVMVHn+Ph7aHC7JCIxE8bw3Cth+RSGM3pAccR/eHmrkJUgJeInDULCT7P0Np2Ov/EtvuPEc8tZWZIcY1qwpvKzltlZWDVVce4fLLj0Vt9VeTKqjtYs22N19xEJHJ6Z/t16WyGyY2ry63LEdPncH+w8eQkJgEJwd7jBjUH+6uLiWew+XrNzFn0VLUqFYFsyaPL/p92+59uHL9JmLj4qGsrAxXZ0f82qsHyrm5ojRU91BCXR9laGsAkQmFOH47F2GxhTLTezsoonFlZRhoKyA+pRBn7ufhVWhB0fZGFZXh46QIfS0F5BcAYXEFOO+fh1A5eYrTsqY6anqrQkNNAW8j8rD3QiZik0T5S6NOeVU0qqIOXS0FhMfmY/+lTHyIymfbNNUV0LKGOsrZK8NARxFpmYUICM7FiZuZyMopuTzdWhiisZ8uNDUU8fJdFtbvj0VkbK7M9B5O6mjb0ABONmow1FPG/A2RuP9M8lqp5qOFprX0WBodLSWMXvAR78NLLkybOhqoXV4dmmoKCA7Lxa6z6YhJlF839SqpoWk1DehpKyI0Og97zmfgfWSe1LQju+rA20kV/xxMwZPXss/xypl9OHd0O5KT4mFj74ruA8bCwcVLatrrFw7jztWTiPgYwtbtnMqhfc/hEumzMjNweOcKPL53FelpyTA2tUSDlt1Rr2knlIb7l3bh1tlNSEuOg7mNO5r3nAxrR+n9Qkz4G1w5ugIR7wORHB+Bpt0mwK+JZL+QnZmGy0dW4OXji0hPiYe5bTk07zEJVg7eJZbl+e1deHptEzI/9VE1206GqZw+6sH5Faz/SUuMgF/rCfAp1kd9aZ7FuX1hN66f2ozU5DhY2Lqhbe9JsHGSvu+9Kwfw6MYxRIcFs3UrBw806zKqKH1+Xi7OHVyBV0+uIz42DOoa2nDx8kPzrqOha2BaYlkeXt2Fe+c3IT0lFqbW7mjcdQosHaSXJTbiDW6cWIGoD4FISQhHw84TUKVh38/SpSZG4+qRRQgJvIG8nEwYmNihRZ+5sLArua1e3NmFZzc2IzMtDobm7vBrPQkmNrLr9d2zs3h4YQXSksKha2SHKs3GwMatbtF2ah//c4sR/uYWsrNSYW5fmeWpZ2xfYlkCbu7Co8uCsY2xpTvqdJgMczvpZYmPfIN7Z1cgJlQwtqndbgLK15W8bh5cXIeQgAtIjHkLZRV1mNtXQM3WY2Bg6lhiWSo5K6CauwK01YHoJOD8owJEJshO724N1PVWhJ4WkJAKXAkoQEikaPvErkpS97v0pAD3XhX+UHVz58IuXD+9uehZ00bO/XT/yn48vnkcUWFviu6npp3/kEj/3P887l3eh/D3gchMS8aI2YdhaVcOPxMKitxO5L+C1/R3JCenFCPEfxETExNoamr+T8vA+fExbdEUzhP/xPtV6/CgXTekBb2C7+Y1UDE0lJre4Y/hsOzaiYk995u3R/jeA/BavRTaHu5FaZR1dVBx71YU5uXh6YBhuN+8A4LnL0ZuSorcsgQ/OY1bJ+ajcuNh6DTqMIws3XBy4wBkpMVLTZ+XmwVdIxtUazEGmjrSX9pzczJhZOmO2u2mflG9nH3+Fn+fu49B9cpj76A2cDMzxJCd55hQIPU4efkYvOMcIpLS8HeXBjg2vCOmtakJU11NCaGn76ZTUFZSxD89m+DwsA4Y06QqdDVUSyzP3RsXsGvTcrTv1h+zl26Drb0zFkz7HclJ0kdfWjq6aNO5H6Yt3Ii5K3ahTsNWWL98NgIe3WXbc7Kz8D7kFdp1/RWzlm7HqPHzERn+EUvm/FliWZS0NJES8ArPR85AadCwt0aV4+sQf/UeblZui3crt8F73WwYN65VlMaic3OUWzQBb2b/g5tV2yM14CWqndoEVRPp16E45wLfYfEFfwyq44s9A1vD1cwAQ3dfREK6jLbKz8fgnedZWy3qVA9Hh7bH1FZ+MNURtdWu/q1w8Y8uRcvano3Z743LyR+wX7lxC2s3bkXv7l2wdtkiODnYYdzUWUhMSpa7X1R0DNZt3gZvz88HeNaWlhgxeAA2rFqC5Qtmw8zUlOWZlCw/T8LHURGtqivj4qM8rDySg8j4AvRvrgotdenpbU0V0K2BCh68yseKIzkIfF+AXo1VYGYg8oGPTS7A8Vt5WHYoB2tO5CAptRD9W8jOU5zGVdVQr4Ia9l7IwKJdqcjJBYZ30oKy9PcARkU3FXSop4HTd7Iwf0cqwmLy2T7amoIy6WkrsOXw1UzM2ZqKHWcymKjzS7OS+8f2jfTRso4e1u6PxfglYcjOKcCUIZZQUZbt86+mqoj34dnYcCBWZhp1NUUEvc3EjuPSn13SaFZdHQ0rq2PnmTTM3ZrM6mZUN125dVO5nCq6NNRiotWszcmsbkZ104HOp7oRh4QwlEJr8795Dvu3LEHrLr9hyt+7YW3vgmUzhyFFxrPm1fOHqFqrGcbMXI/x87bCwMgMS2cMRWJ8TFGa/VsX4/nj2xgwajZmrjiERq16YM+GBXhy/1qJ5Xl+/zTO7ZuPem2GYdC0wzCzccPOJQOQliK9bnNzsmBgYoNGncZAW096v3B86xS8fXEb7QcswJCZx+HkWRPb/+6HlMToEvuoOyfmo1KjYej4+2EYWrjh1KYByJTTR+kY2qBac9l91JfmKc7Tu2dwctcCNGw/FCNnH4SFrTs2LfgNacnS930bdB/l/Vrit0lbMHT6bugZmmPjgoFIThCcd05OFsLfv0CDdoPx+6yD6DVqBWIj32HrkmElliXowWlcPjgPtVoNQ7+JR5iQs29lfyaUSa2bnEzoG1ujXvsx0NKVXjdZ6cnYsag7FJVU0GX4BgyYdgoNOo2DuqZeieV5G3Aa904vQIWGw9B22CFWr2e3DJRZr9EfHuPKvj/hWrkj2g0/DDuPhri4cwQSol6z7YWFhbiwczhSEkLRqNc/LI22viXObP4VuTkZcsvy+vFp3Dg6H1WbDkO3MYdhbOmG4+sGICNV/timRivZ1014iD98avVA59/3oe3gzSjIz8OxtQOQmy2/LOVsFNCwvAJuBhZi8/kCxCQVoltdRWiqSU9vZQS081PEk7eF2HSuAK/DC9GppiJMxJpg+bF8ieXk/QJWX6/CSn7glKW6Cbh7Gqd20/00DMNnHWLC6OaFA+XcT/7w8WuBgRO3Ysi0PdA3tMDmhQOK7iciJzsT9q4V0bzrmBLrgsMpCS7kfAP16tXD8OHDMWrUKBgbG6Np06Z4/vw5mjdvDm1tbZiZmaFXr16Ii4sr2ufs2bOoVasW9PX1YWRkhFatWiEkRPDVSigGUZ4WFhZQV1eHnZ0d5s2bx7bRQ5CsPWxtbaGmpgZLS0uMHDlSpmvVy5cv2bEoHw8PD1y8eFHChef9+/ds/fDhw6hfvz4TgXx9fXHnzp2iPLZu3crKevLkSbi5ubE0nTp1QkZGBrZt28aOaWBgwMqRny/4GkpkZ2fjzz//hJWVFbMSqlatGq5evfpZvufOnUO5cuVYfTVr1gyRkQJJn86T8j927BgrIy3i+8siLCwM3bt3h6GhITtu5cqVce/evaLta9asgZOTE1RVVdn57Nixo2ibsD7ELWnIIkj82PSX1i9dusTypvqoUaMGXr16VXReM2bMwNOnT4vKTb99Kc+ePUODBg2goaHBrpPffvsNaWlpRdvJeoLqXHgdjRs3Dn369EG7du3wrdj82gsR+w4j6tAxZAS/xaups1GQmQWLTtLzNm/bEh/WbkTCtZvICg1HxO4DiL92Eza/9i5KY/vbr8iOjBZY4AQ8R1ZYOBJv3kHWxzC5ZXl6fSs8qnWGe5WOMDRzRt0OM6Cioo6X9w9JTW9q440arcbCpXxLKCmrSE1j514H1ZqNgqO34EW8tOy48xwdKrqhXQVXOJkaYHKrmlBXUcbRx4JBXXGOPH7DLDuWdmuECrZmsDLQQWV7C7iZGxWl2XwzAGZ6WpjVrjaz7LE20EENZytmlVMSZ47tQf0mbVG3UWtY2Tqi39DxUFNTx7WLJ6Sm9/CuhCp+9WBl4wAzC2s0a9MNNvbOePVCcL1ramlj/KyVqF6rESyt7eDs7o3eg/7Eu+CXiIuNkluW2HPX8XraMkQfu4jSYPdbN2S+C0PQ2AVIe/kWH1bvQtShc3D4XfT11WFUP4Ru2o+wbYeRFhSCZ0OnIT8jCzZ9O5aY/467L9ChggvalXeBk4k+Jrf0g7qKEo4+EXx1Lg79npKVjaVdGqCCjSms9LVR2c4cbuYi0chQSx3G2hpFy/U3YbChNrUzk1uWg0dPoEXTRmjWqAHsbW0waugg9vw+e0G2xRI9S+cuXoY+PbrCwuzz/BvWq41K5X1haW4OeztbDBnQF+kZGXj7/kOJdVPLWxn3X+bj4et8NmA/ejMPOXlAZTfp6kBNL2W8DivA9YB8xCYV4sLDPETEFcLPU5T+aUgBgiMKkJBaiJjEQpy8mwd1VQWYG5Y8xKhfUQ1n72YhIITyLcC20+nMksTXWfr9y86/shpuP8vB3ec5iIovYBY8JHL4eQkE0Mi4Amw8noHnb/MQl1yA16F5OHEzC16OKiXGYGxVVx8HzyfC/1k6PkTkYMWOGBjqKaGqj2xr18dBGdhzKgH3Aj632BJyzT8VB84m4ukr+S8OEudZVQOnbmXi6ZtcZnW0+UQa9HUUUcFNttDbuKo6bjzJxu2AbETG5WPnmXTWvjV9Jd/KbEyV0KSaOraeEvUrsrhwYhdqN26Pmg3bwtLGEb8MmgRVNXXcunxMavqBf8xB/eZdYOvgBgtrB/QZOpWNX4IC7helCXkZgBr1WsPNqzKzxqnTpCMTiN4FS7f8FOfOua2oWKczKtTuCFMrZ7TqPQMqqup4fEN6v0BWNU26jIV3Nen9Agk9Lx6eR+POf8LerQqMzOxQv90IGJrawv/KHrlleXZjK8p96qMMzJxRp8MM9sX/pb/sPsqv1Vg4l28JRRl91JfmKc6NM1tRtX5nVKnbAWZWzmjfbxpU1NThf+2w1PTdhy6CX+PuzCLA1NIRnQbOQmFBAYIDBQK/hqYOBo7fBN/qzWFi6QA7Z1+07T0Z4e8CkRgXIbcs9y9ugW/NLvCp0RHGls5o1kPQfwfcln4eFvY+aNBxHDyqUDtJv8bvnt8AXUNztOwzj1n26BvbwMGjFgxMbEusm+c3t8GtSme4VurA6rVm2+lQVlXH64fS6ybw9nZYu9SCT53+0Dd1QqXGv8PIshyC7u5m21Pi3yM29Clqtp0GE2tv6Js4sP/zc7Px9ukpuWV5cnUrPP06w6NaRxiaO6N+5xmsLC/uSa8bM1tv1GozFq4VZY9t2g7aiHJVO8DIwgUmVu5o3GMes1CJCQuUW5aqbgpMlAl4V4i4FODMg0Lk5QG+DtIfllVcFRASBWZZE58KXH9eiKgkgVWPkPQsycXFUgEfYoAk2Y/IMlk3N85sQ5V6nVG5juB+atdvOnv2Pbgu/ZrpRvdTox5F91OHAYL7KeSF6L2qYq22TBhy9qxRcmVwOCXAhZxvhMQGEgVu3bqF+fPns5fvChUq4MGDB0y0iY6ORpcuXYrSp6enY/To0Ww7iQGKiopo3749CgoEptIrVqzA8ePHsX//fiYO7Nq1i4klxKFDh7B06VKsW7cOb968YYKMt7e3zBcBeqknoYGEjPXr12PSpElS09LvJLqQgOHq6sqEEBIKhJBoQ+Xau3cvOycSM6jMp0+fZguJIVSmgwcPFu1DYhQJQrRPQEAAOnfuzIQaKrd4vn///Tfb//r16/j48SMrB0F/qd6E4g4tJJjIg4SOunXrIjw8nNUhiSljx44tqtsjR47g999/x5gxY5jgNmjQIPTr1w9XrlwpVVsXr7PFixezdiTXhl9//ZX93rVrV5a/p6dnUbnpty+BrhESBUkgI3e5AwcOMBGO6lTIggUL2LWxZcsWdu2lpKR8Fxc0BRVlaHuWQ+JtwSCOUViIhNt3oVtBuimpoqoqCrIlrdEKsrKhV6l80bpxw7pIfR4IzxWLUPPuFVQ+tg8WXTrILUt+Xg4zP7d2EbU7mWtaufgh+sN/67ZG1jVBEfGo7mhZ9JuiogJbDwiT/hX+2quP8LE2xbxTt1F/0W50+OcwNl5/ivxP16MgTSg8LY3x5/7LqLdwN7qsPYpDDwWioDzycnOZwOJZvqpYeRTh6VsFwS9Ldj2il6rnT/0RFf4B7p4VZKbLTE9jYiSJPN8T/erlEXdZNLAhYi/chEF1wTWjoKICvYqeiLsk5p5XWIi4y7ehX112eYXWNUGR8ajmINZWCgpsXVZbXX0dCh8rU8w7cxcNluxDx7XHsPFmgERbFT/G6Wdv0ba8M6sfmWXJzcXr4BBU9PWRaKeK5X3w4pV0AZDYsfcA9PX00KJJyS5/dIxTZy9AS0sTTp/6ClkoKQJWxgoIDhedF30fpXU7U+nDATszRYn0BAk7stLTMaq6KyEzu5BZ+8jDSE+RiTavPoj6G3J9eh+ZDwdLZZn525gp4aXYPnQOLz/mwVHGPgS5bWXlFKJAzgdhMyNlGOgpS4gtGVkFePMhG272pTAv+o4Y6ytCX1sRQe9E7k5Up+R65mglu27sLJQR9F70PKbTDXqXAycr0QuOqjIwoJ02dp1LR0p6YYnPmg8hQSjnU03iGqb1kFcBpToXsurIz89jVoFCnNx98MT/GrPSoefRy2f+iI74CE9f+W6KeXk5iPgQCEePGhLlcfTwQ1jI1/UL9HW+sCAfyiqSYheJJx/fPCyxj7JyluyjrL+hj/qWPKluwt+9gItndYm6cfb0w8fg0pUnN1vQVprasi1csjJT2XNPQ1NX7nlEfQyEfTnJ86D18LeP8bW8eXoZ5rZeOLJ+JFb85YfNc9rhyY39Je5H5YmLCISls59EeSyd/BDzUXrdxHx8KpGeIGFHmJ7czgglZTWJPEmEiv7wSG5ZSECwcZWsGxsXP0R9x7FNdmYq+yvPWok8YCwMgPfRks+Bd9GFrK+QhpWRwmfp30bKTq+lBjhbgolFJVGW6oY9a94HsvtH/H5y+or7SUOrZIuxnwkFRYUyufyM8Bg534iLiwsWLlzI/p89ezYTcebOnVu0ffPmzbCxscHr16+ZSNKxo+TXZNpOLlEvXryAl5cXEzMoT7KkoY6SLHKE0DZzc3M0atQIKioqzDKnalXRi5w4Fy5cYJY+JLrQPsScOXPQuPHnVggkmrRs2ZL9T9YkJEIEBwfD3d296EVBaMlCkEUOiS8kUpElDVn7kEUPCSIkWlA5SWCgv2Q1JDwGiUD0u7B+KN+1a9cW5UtCxcyZM9n/lC9Zo5Blj7D8JbF7927ExsYy8YMscghnZ+ei7SQaUdydoUOHsnUS1O7evct+p/J/CVSXJBoR48ePZ/WXlZXFykxlJ3GntOWWdh6U1/bt24tiHq1atQqtW7dmAg5Zeq1cuRITJkxggppwO4lq34qKgQEUlZWREydpNpobHw8tJwep+yTcvM2seJL8HyLzYygMalSDSZMGUFASfbFXt7GGZY8uCNu8Ax/WboKOtydcpoxDYW4uoo5ItyDJSk9kg2sNbZEFC6GpbYykmHf4L0nMyEZ+YSGMKKiIGEZaGngXlyR1n7DEVES8i0QLH0fmNvUxIQVzT91BXkEBBterUJRmv/9L9PLzRP/avggMj8WCM3ehoqSINuVlx1BJTUlCQUE+9PQl3YxoPTJctlVGRnoaRvRrhbzcHCgqKqHv4L/gXUH0giZOTk429m5bBb86TaCp+X2FHDUzY2RHiywVCVpX0dOBoroaVAz02HWYHSN5HWZHx0PLzbGUbSX54m2kpY73cdJdj8ITU+GfFIkW3o5Y1b0RQqmtztxDXn4BBtcVCZJCLr8MRWpWDtr4ip4v0khOSWVCsoGBvsTvBvp6CA0Ll7rPs8AgnLlwCeuXL5ab9537DzB70VL2jDQ0MMDCmdOgpyffkktTnV72FVjMGHFo3URfujBDl7y09NoakoMid1tFdG+gAhVlIDUD2HQ6BxnZcovD4tsQKRmSgk9qRkHRts/Lo8DOITW92D7pBTA3lD6k0dJQQHM/ddwKkO/+rK8r2D85VWRdSiSl5sFAV44/07+AnpagPVKknKdwW3HItYzqprg4Q+vmRqL67NJYCyFheczSpyTSUgXPGt1izxpajwp/X6pzObR9BfQNTOAhJgZ1HzAOO9bMxtiBzaCkpMzGO72GTIGrZyW5eWWkCvoFbV3JfkFL1xhxkV/XL6hpaMPaqTyunVgNYwtHaOsZ49m9U0wYIqscWRT1UTqSZdH4hj7qW/LM+NRWVH5xdPSMEBv5tlTHP713MYt9I/7yKk5uTjbO7F0CX78WUJfTL2SkCc5Dq3g76RghPqp0ZZFGUlwoHl/fg6qN+sGv2WBEfXiGi/tnM0sMbz/BeEgaWRlJUscTtJ4cK71eKY4O1bs46tpGLG4LQRY4WvoWeHBuKWq2nw5lFQ08v7UN6clRyEiV7WaZ+amNNYu1saaOMRK/09iGrEBuHJ0LC4eKMLKQHTtNU1XwUYqsZsShdSMZ3Ql1rZ+lzxb8Lg1vBwVmMVkat6qyVDei+0myLDq6RoiNKF1Zzuz7+9P9xK1vOP8OXMj5RipVEg06yAKExAx6kS8OiSok5JBFytSpU5mVDLlcCa1FSPQgIYeEBhJbyO2HrFHI9apJkyYsDVm1kOuUo6Mj29aiRQv2ck+iQXHImocEJHExQZbo4+Mj+lpMLl1ETExMkZBDVj1CsYUgIYGshMTPk36jfYRuQWQRROcrDr1wkBuQkOL50rGFeXwNZFFEQppQxClOUFAQc1ESp2bNmli+fPkXH0tWnZG49q1QOcnFTTxwNZWTrhVqV3KVIxFNvD2VlJTYtSi8nqRB9U+LODmFBVBV+DbDvDezF8Jt9lRUO3eUfVkld6nIQ8ckXLEUFBSZRc7bJSvZetqLl9B2dYZl984yhZwfnYLCQuaOM7V1TSgpKsLD0hgxKRnYdvtZkZBDacgiZ2Sjymy9nIURgmOScODBS7lCzteirqGJOct2IDsrE4FP/bFr83KYmFsxtytxyCJv5cJJZASDvkPG4meHrDQMtTQwpaWfoK0sjBCTmoFtdwKlCjlHn7xBTWcriRg634OMjEzMX7ICo4cPKVGUKe/jhfXL/2Zi0anzFzBrwWKsWjyfiUT/C0IiCrDicA4Ti8gip0cjFfxzNEdiwF+lnAq6NxbV2erDJbv1fCvqqsDQDlqIjM/HqduSbx91KmtjUFdRwNY56+S7ivybVPNUxS/NRX3qyv3y44d9Lb4uKnC3U8GsTdIF6O/NmcNbcP/WOfw1cz1UVEWWC5dP7cXb188wfMJSGJlY4PWLR9i9YT70DU3g4StdXP436TBwIY5tnoglY+pCQVEJFnYe8KrWEpEf5Lte/ExcOb4BT++exqBJ2yTaSghZoOxaOZr18+37TvuflJGObWHnhbrtRrN1c1sPFiT58fW9coWcfwOK09Oo50rcODwZO2dVZ9cNWfhYu9bG/5qrh2ayIMCdRgrcwP6XkItW4MdCFgi/LPBf1c3VExsQcPcMBk6Ufj9xON8DLuR8I+Iv2+TaI7SaKI7wZZ+2k5XNhg0bmLUKvXiTgCMMlFyxYkW8e/cOZ86cYe405F5EFjjktkTCDL3I0+9kcUOWJYsWLcK1a9eYhc7XIr6v0E1AXBAonjelkfabcB+qBxIWHj58yP6KIy7+SMuDOumvhaxhvgUymSTEy0BWQ19TZ2URirVEFlfi9DYwRV8jkdiXm5iIgrw8qBpLfoFQMTJCdqykBUXRPgmJeD70D+ZipWygj5zoGDj+NYrFyxGSExuL9GDJr3DpIW9hIsd1RF3LgA2MigcizEiLY19n/ksMNNWgpKDwWWDj+PRMGGtLf5k30dGEsiJ9IRcJZY4memzGK3LVUlFWgomOBhxNJK01KM3FIPlfunV09ZlFTfHAxrRe3Eqn+DVubimYMcvO0RXhYe9x4uA2CSFHIOJMRHxMJCbMXv3drXGE1jdklSMOrecmpzK3vJw4wXWoZip5HaqZGSE7Svp1+HlbSb60x6dnsdg20jDR1mABp8XbysH4U1vl50NF7DlGAZHvvYvE4s71SjxPPV0dVueJiZIvzRTo2LCYlQ7LOyoKUTExmDxLEBdN/HnUuG1nbFu7EpYWgvtVQ10dVpYWbPFwd0Xv34YxS54enWW7LGZkAfkFQmsa0XOO1tMypD976ZIvbn3D0hez0snNA5vRKj4FCI3Jw59dVFHFTQlXn4qsW2jmqPeRApN2Qhi0V1dTESnponQ6moosSK/08tALQSF0mFWK2D5alIdkmdRUgGEdtZlL1fqj6Sj+iKaZpV6/Dy1aFwY01tNRQmKKKG99HWW8CyvBvOgbefImB28jRNeJipKgLLpaikgWrxstwUxU0qA2pLopbs1E68K6IRHHxEARy8dIPieGdNDBm9A8/L1LUkDS1hE8a4oHNqZ1XX3J+7M4NMsVCTmjp6+Ftb3oww4FVj+yexWGjl0Mn8qCl17aHvruNc4f2y5XyNHUEfQLxQMbp6fEfWaJ8iWQ5U2/8TuRk53BZrDS0TfFgTV/sCDJJfZRxYKwMkuOr+yjviVPzU9tRbPriJOaHA+dEurm2qnNuHpyI4uHQwFdZYk4SfERGDhhi1xrHFYWbcF5FA9snJ4az6ynvhYKVm1kIfoASBiZO+LVo3Ny91PX1Jc6nqB1WfVK1jhU7+JkpcVLjD+MrTzRfsQR5GSlsjrS0DbE8dVd2e+y0PjUxsWD95Klj+Y31I24UPH+xVV0GL4T2vryLcMzcmjsWvhZYHotKVY3Qqhr/Sy9muD34tgYk2WPAo7cKd34uCzVjeh+kixLako8dPTll4Vmjbt2cgP6j9ss9X766fnGD8Sc0sNr+jtCIkxgYCCzViGXHvGFBJ/4+HgmxEyePBkNGzZkQX4TExM/y0dXV5e5KJHYs2/fPhYbJyEhoUisIDGIYtaQ2xTFoSELmOKQRU9oaCiz3BBCLkf/BWQVQxY5ZKFSvB6+xN2IYg+JB1AujZUMWeUI66o4VN8UT0YcWifXMIJc3AhhwGXia6YQ/9JySysnWXdRrBzxctILIbWrnp4es4ASb0863qNHsn2yCXLFSk5Ollh6GEpOH1qYm4e0wCAY+IkNpBUUmLtUymP58RAKcnKYiEPTkZs0bYi4i6LYQ8mPnkDTQTJ+h6a9HbIiZH8BJz9zEytPhAXfkTCJDQ++CzO7z60k/k1IdClnaYR770TlpcHPvbcR8JEx/Xh5G1OEJpBrjejl8kN8ChMNKD9BGjO8j5d096E0lnryB8nKKipwcHZnVjWi8hQgMMCfBSkuLVSf4mKlUMSJjgjF+FmroKP771h3JN19AqMGkrEwjBvWQOJdwf1GLnfJjwJh3EDMvF9BAUb1/ZB0V358BRJdyLLp/nvRfUyWT/ffRcpsK18bU+b6Ruk+a6tiYvSxp8HM0ko4LbncsqiowNXZCY8Dnkm00+OnAfCQMlW4rbUVNq5aivUrFhctflUro7y3F/vfpJjAKg6VXZbwLIS+iIbHFcLZStT10yu/s6UiPsRIH2h/iC5g28VxsZadvihfBRJqJAWF7FywacWFC8XQSU4rgJudsoQFjb2FEt5F5Mk8h9DofLjZivaho9A6xY8Rz2d4Z23kFQBrj6QjT8ojOSu7EFFxuUVLaFQOEpPz4OMqEmc11BXgYqeGV+9lvNV8JyjMWGxiQdESEZePpLQCuNuLPhpQAGmKA/Q2XHbdfIjMQzmxfahuaD0kXHBtnLmTiRkbkzFzk2gh9l3MwNaTaVKfNTR9uHigYrqGad3JTfa0zWePbMWpgxvx+5RVsHf2kCxnfh7y8/I+m6KW+riSPuYoK6vC0s4T74LuSJTnbdBd5h71raiqaTIRJzM9GcHPb8KtfIMS+6jw79hHfUueVDc03bEwULGwbmjd1ln2vldPbsKlo2vx69j1sHb0kinixEV/wIDxm6Clo1+q8zC39cT7l5Ln8eHlHVg5yo9zJg9rp4pIiJZ0a0mIfg89I6sSy2Ns6YnI4LsS5YkIuQtTW+l1Y2rry7aLEx58W2p6VXUdJuIkx71HXPhz2Ho0lFsWU2tPhL2WrJvQN3dh/g1jG7p3SKh4++wi2g/dCj2jkvsoErcjEwF7M8lnNa1TXyGN8PhC2JtKpncwl57e11EBkQmFiCmlAWBZqhv2rLH3RMgLyfsppIT76drJjbh8bA36/SX9fuJwvidcyPmODBs2jIkIFCyYXrLJnYpmZaKAuvSiTcFrybWIAg9TDJrLly+zOC3iLFmyBHv27GEzTlFcHQp0S+IHzU5Esx9t2rSJBep9+/Ytdu7cyYQd8Tg6Qsg9i9yWaCYjCjZMQgAJSIS84JzfA3Kp6tmzJ3r37s1mxCILo/v37zOLkFOn5EfyF4cEMSo7iV/khlbSSwrVO9UVBXmm86U6IhFMOAvXX3/9xeqQ4v2QixvVNZVPGGCZ6rJ69eosaDW5N5Glk7DOvgQqN50ziUBU7uLuTCVBdUfuU9R21NbkrjdixAg2AxoJOAStU33SrF5UPxTEmURBeW1LM+WQSCi+SHOrCt28AxZdO8C8fWtoOjnAdeZkKGloIPKQIJhyuYWz4ThGNFuarq83jJs0hLqNFfQqV4DvptVsgP5xg2i2rtAtO6Fb3ht2g/tDw9YGpq2bsynLw3ftk1sXvnX6IujeAbx8cASJ0SG4fng6mz7cvYrA6uDSnnG4e3qxZEDD8CC25OfnIj05mv2fHCeKG5ObnV6UhkhJCGP/0wwG8ujl54XDD1/j+JM3eBubhNmnbiMzN4/NYkVMOnwNyy8+KErfpYo7m7Vqwdm7LDbL9deh2HjjKbpWFU0n/YufJ56FxbAgyB/jU3A6IAQHH76SSCOL5m274+r5Y7h+6RTCQ99hy5oFyM7KQt2Grdj2tUunY9+2f4rSHz+wFc8e30NMVDhLf/rILty6egY16zUrEnFWzB+Pd8FBGDJmBhuwJCXGs4UCnpY0/biurztbCE0Ha/a/uo3AEtFt9mj4bhFZKn5YvxeaDjZwn/cXi3ljN7gHm2783XLRNfNu2RbY9O8Cq17toO3uCK9/pkNZSwOh26TPFiHRVtU9cPjRaxx/Gszaas7pu6yt2n6KaTP56A2suCQKYtqlkhtSMnOw8Nx9fIhPZjNSbbr1DF0qC85HXCyhPFv7OEG52EuoLDq1a41T5y7i3KUr+BAahmWr1yMrKxtNGwleEMmVauO2nUUisIOdrcSiraUFDQ119j8JQ5lZWdi4fRdevHyN6JgYFkx50fJ/EBefgLo1pce1EOfmszxmKVPRRREm+gpoV0sZqipgs1ixuqingqZVRCLJred5cLVRRG1vJZjoKaBRRWUW1PJOoCA9xcRpWlkZNqYK0NcWBFPuVEcZupoKCHhXsqB95VE2mlVXg7eTMiyNFdG7uRYTd54Gi665kZ21ULeCaBabSw+yUdNHFdU8VWBmqIhujTWY9Q3NYlUk4nTShpqKAnadzYCGqgIrDy0ldX8nryWhU1MDVPHShK2FKkb+YoaE5HzcF5uRavowSzSvrSchsNhbqbKFMDVSZv8bG4jqUVtTkf1mYy5IY2UqSK+vIzv2zqX7mWhZU4O5Q1mZKOHX1tpISi3A41eiWD+je+iifiXR5/EL97NQu7w6/LzVYG6khJ7NtaCqooBbAYJ+iCxzImLzJRYiISWfzfAljcate+LGxSO4feUEIsPeYte6uWwK3ZoN2rDtm5ZPweGdArdZ4szhrTi2Zw36DJvGZqRKToxjS1amIIi0hqY2i4VzcNsyvHr+ALHR4bh1+TjuXDuFCtVKjlfn17QvHl47gCe3jiA2IgSndkxHbnYmKtQS9AuHN4zDxYOLJYKWRn4MYguJEqlJ0ez/+GhRvxD8/AbePLuBxNgwhATewtaFfVi8HGGesvCu3Rcv7x/Aq0991I0jgj7KrbJgv8t7x+HemWJ9VEQQWwryPvVREZJ9VEl5yqN28764f/UgHl4/iujwEBzZMoPVTeW6ArejfWvH48y+JUXpr57YiPMHV6DzwNkwNLZEalIsW7KzBNc71dfOFaMQ9i4Q3YYsZPFLhGmoXuVBcWye3tyPZ3eOIC4yBOf2TEdOTiZ8agjO48SWsbh6RLJuokOD2FKQn8Paif5PjBHVTZWGfRDx9ilun1nLfg+8f4Ido2LdHiXWjVetPnj14ADePDqKpJgQ3Do2g0157lpRUDfXDoyD/zlR3XjW6I2w1zfx7MYWJMW8xaOLqxAXHohy1UXHevfsLCLf3mdTkH94cQlnN/dn05Rbu9SUW5by9foi8O4BBN0/goToEFw5OJ2VxaOaoG7O7xqH2ycl6yY2PIgtBfm5SEuOZv8nxYrq5tqhmXj14ASa/vI3VNS0kJ4Sy5a8HPki9P1XhSjvqABvewUY6QDNKyuw5zrNYkW0rqaAet6iB6f/60I4Wghmu6L0tT0VWMDkh8GSQg4FVXe3EcyI9SWUpbqp3bwP/K8ewMMbRxETHoJjW2ewZ1+lOoJrZv/acTgrdj+RFc6FQyvQaeAcGBhbfXY/ERlpSYj4EITocMEsmhTbi9YpHYfzpXDXqu8IuUqRgEBTQVNcG3qBJ5GF4tnQlyZ6yaZZnGjaaHKnIusKsqyhacyF6OjosODJJDSQW1KVKlVYEFvan8QcEhlI/CFhiGasOnHihETcGSG0L81iNGDAAJYHxdUhNyyy5iGR4N+GghpT8GeawYlmkaLp2UkkoZg/pWXgwIHM6oim+SZ3LRI0xOuqOPQSdP78eXZMih9EL6ZkbfPPP4KXWRJ4KB4OBTcm4cPBwYGVUzxPCj7dv39/Fm+G2ofaQhijqLRQQGvhlO40fTkdg2IflRaKHUQCIJWR2o7WKU8SnoTQNRYVFcXEMmpriv1DM10Vd2X7GmJOn4OKoQEcfh8KVRNjpAW9QkD/ociNF1g6qVmao7BQNOBXVFOF4x/DWEDj/PQMNg35i78mIS9V5EKR+iwQz4eNZgKQ3fBBbPrxN3MWIvq4/ADNzuVbIDM9Af7nVrLggcaW5dBqwIYi0+a0pAgJ8So9JQYHlon85J9e28wWS8cqaDtEMNV8TNhzHF/bpyjN7RPz2V+3Su3QoJvgf2k083JEYnoWVl95xFxuaGrq1b80KQqAHJWczmZHEmKup401vZpi0dl76LzmKEx1NdGzmif61RJZzHhZmWBJ14ZMVFh37QmsDLQxtlk1tPSRNB2XRvXajZGSnIRDu9cjOTGeuUqNnb4MegaC50FcbDSLTSQkOzsLW9cuREJ8LFRV1dgU40NGz2D5EDR7zKP7N9j/k37vJXGsiXNWfxZHRxy9Sl7wuySoX8Lj74nsb+j2wwjoPwFqFibQ+CTqEJnvw+DfZhA8Fk+A/YjeyAqLwrNBkxF34WZRmsgDZ6BqYgjXaSOhZm6ClKdBuN9qAHKKBYD5FcUAAQAASURBVECWRlNPByRmZGHNtSeCtjIzxOoejYraKjIlXeK6MdfTwuqejfD3eX90XnectVWPquXQr4bk17S7byMQmZyOduXlBzkWp37tmsz6beuuvczFysnRAfNnTC5yrYqJjfsicZ3cvyhQ8vRLV9lsdbq6OnBzccay+bPZVOQlEfC2AFrqeWhcSQUU4icivhCbz+QwFypCX4tcXEXpP8YUYu/lXDSprMwEnrjkQuy4kIvoREEiSkuC0C+uqszcnty3wmILsO5EDpuKvCQu3M9mQkOPJppsZqmQ8Dz8c0jSgsZYXwlaGqIfHr3KhY5mJlrV1ICOpgKbmvufg+lI/eQeZmOmXDTr1YyBkrGGpqxPQUKKbGuiIxeToKaqiMHdTKGloYigt1mYtSYCuXmiczE3VoGutuhZ62SrjlkjRRYBv3YQWH5dvpeCVbsEcd+qeGlhxC+iqeTH9BNYp+47k8AWadC07KqqCujVXBua6gp4E5qL5ftSJOqGglRTkGMhD4JyoKOZgbZ1NJhbFrlhLd+XitQSZqeSR5VaTZGaksjEmZSkeNg4uDFLG6FrVUJclIR1zbVzB5CXl4u1i/6SyKd1l9/Qpttg9v9vo+cx8WfjsklIT0thcXLa9RiGuk07lVger6otkJ6agCtHVyItORbmNuXwyx8bilyrkhMiJGYoSU2Kwbrpon7h9tnNbLFzq4J+4wTPrayMNFw6tAQpiVHQ0NJHuUqN0bDDHzKnMxbvo7LSE/DgvKiPatFfdh+VkRKDQ2J9VMD1zWyxcKyCNoN3lCpPedA04ekpCTh/aCVSk+NgaeeOX8euK3KtSoqLlOgX7l7aWyTWiNOo/VA07jgcyYkxePFIYF27fJKkkPTbxK1w8pAee5EoV7kFMlITcOPECvbSbGpdDl1HbCxyrUpJkCwLtdOWOaLYevcvbGaLjUtV9Byzo2iK8g6DV+Ha0SW4deof6Btbo2HnifCsJhAV5eHoQ/WaiIcXVyAzNQ5GFuXQtN/6IteqtCTJ8pjZVUD9rovw8MJyPDi/FLpGdmj0y0oYmousKal97p1eUOSi5VKhLcrXH1JiWVwrtEBmWgLunV3J6sbEqhzaDBK7bhI/H9vs/Vt03Ty+spktVk5V0GG4oG6e3drD/h7+p7fEsRp1n8um3pZFUGghNNWAOl4K0FJXQHQSsO9aAQtgTJAALm4pFx4PHLtTgLreikzgSUwDDt4qQGyxuQQ8bBWYReCLj1/27ClLdeNTvQXSUhNx8dAKdj9Z2JZjljZF91O89Ptp14rfJfKh6cYbdRDMPBv06AoObhCMkYg9/4z5LM2Pzs86Q1RZRKHwW4KScH4oSGSi2bDIGkg8yDDnx4esJ8gli2IqzZo1q9T7XXHxRVni6eL/dlpxeQxOF8xGV1Z4VnEQygoxXv99MFJ5NNgiEub+18RXLfmF4r9i1bXSC07/BanJ/6570pcQ+VF+rKX/GiNzA5QVerX9b6daL4nwpO8bVPxbiCxDl42jZdmKy5eY9t/O7CaP2ISyVTeaxeKM/S9JSS1bdaOrU3acQyyNy84rcYeqZadevpSUJZLCcFlBd/Qy/Gxwi5yfmCNHjrDgwjSdOYk3ZOFBsx9xEefH58OHD8z6iKZAJ8svmn6c3Ll69CjZvJjD4XA4HA6Hw+FwOD8uP67cxymR1NRUFreHphEn1x5y06GYKj8qc+fOZcKUtKV58+Yoq+zatUtmuT09Zc9sIA9ytaN4P9SmJM5RwGuazYyscjgcDofD4XA4HA7nP4dcbcvi8hPCLXJ+Yih+Ci0/C4MHD2auQ//G1OP/Jm3atEG1atJdUb522niair74DFwcDofD4XA4HA6Hw/n54UIO54fB0NCQLT8aFMCaFg6Hw+FwOBwOh8PhcL4VLuRwOBwOh8PhcDgcDofD+Sa+ZCZOzrfxczqMcTgcDofD4XA4HA6Hw+H8hHAhh8PhcDgcDofD4XA4HA7nB4G7VnE4HA6Hw+FwOBwOh8P5Nn7SGaLKIrymORwOh8PhcDgcDofD4XB+ELiQw+FwOBwOh8PhcDgcDofzg8BdqzgcDofD4XA4HA6Hw+F8EwqKfNaq/wpukcPhcDgcDofD4XA4HA6H84PAhRwOh8PhcDgcDofD4XA4nB8E7lrF4fw/xm9+X5QlgjXLjjnms4VHUJYw3doOZQWvLX1QlrjcbxvKClWfNERZIS+vAGUJFbWyM+RQUlJCWUJJqex8V1NSKERZQkmx7JRHTbXstJO6Sj7KEhpqZadu1FTLzliCyMlFmcHSrGw9+9RVy879ratehhoKavhhUSg7z4KfHV7THA6Hw+FwOBwOh8PhcDg/CFzI4XA4HA6Hw+FwOBwOh8P5QSg7ds4cDofD4XA4HA6Hw+Fwfkz4rFX/Gdwih8PhcDgcDofD4XA4HA7nB4ELORwOh8PhcDgcDofD4XA4PwjctYrD4XA4HA6Hw+FwOBzON6HAZ636z+A1zeFwOBwOh8PhcDgcDofzg8CFHA6Hw+FwOBwOh8PhcDicHwTuWsXhcDgcDofD4XA4HA7n2+CzVv1ncIscDofD4XA4HA6Hw+FwOJwfBC7kcDgcDofD4XA4HA6Hw+H8IHAhh1PmuXr1KhQUFJCUlISflf8P58jhcDgcDofD4XB+XhQUFcvk8jPCY+RwOP8C9erVQ/ny5bFs2TL8iOy98xzbbjxBXFomXM2NML51TXjbmMlMn5KZjVXn7+PSi3dIzsiChb4Oxraqgdpudp+l3XTtMVacu4eeNbwxtlXNEsvy+Nou+F/chPSUWJhYuaNhlymwsPeRmjYu4g1unVqB6I+BSEkIR/2OE1CpQV+JNLdOrcSd06skfjM0c8CvU8+iNJh26Ajz7r9AxdAQGSHB+Lh0MdKDXkhNq6CkBItefWDUvAVUjU2QFfoRoWv+Qcq9u0VpTNp1gGm7DlCzsGDrme/eImLrZiTfvVNiWY6fPIUDh44gITERjg4OGDb4N7i7uZa435Vr1zFv4d/wq14NM6ZMYr/l5eVh6/aduP/gISKjoqClpYWK5X3Rv29vGBkZlZjnXv+X2HbnOeLpmjEzxLhmVeFtZSIzfUpWDlZdeYTLLz8iOTMbFnra+KtJFdR2sWbbm684iMjk9M/261LZDRObV5dbFsNaleE4pj/0KnpB3dIUDzoORfTxS/L3qVMVHn+Ph7aHC7JCIxE8bw3Cth+RSGM3pAccR/eHmrkJUgJeInDULCT7PyuhZoBDZy5iz9HTSEhKhpO9Df4Y0AseLk4l7nfx5l1MX7IatatWxLzxo4p+r9Wht9T0Q3t3RY92LUvMt4anMuqVV4aOpgIi4wtw5GYuQmMKZKb3cVRCs6oqMNBRQFxyIU7dzcHLj6L0Xg5K8PNUhrWJIrTUFbBkfyYi4gtRWppXU0V1T2VoqCngXWQ+DlzJZseRRy1vFTSoqMLOISKuAIeuZ+NjtKhMykpA21qqqOiiwv5/+TEfB65mIy2z5HJ1baaPhn460FJXxMv32dhwIA5RcXky05dzVEebBnpwtFaFoZ4yFm6Khv/zjG/Ol2hdSx21fNVY3YSE52HP+QzEJMpuK6JuBTU0qaYGXS1FhMXkY9/FDLyPzC/a3qOpJsrZKUNPWxHZuYV4G56Hw1czEZ0gO99Lp/fj7NHtSE6Kh429C3oOGAtHVy+paR/euYyThzYjJjIU+fl5MLOwRdO2v6BGPdG1WVhYiKN71uL6xSPISE+Ds7sveg+aADNLW5SGexd34eaZzUhLjoO5rTta/jIJ1o7S+4Xo8De4fHglIt4HIik+As27j0eNpn0k0mRnpuPS4eV48egi0lMSYGFXDi16TIS1o3eJZXl6YxceXd6EjNRYGFu6o27HKTC3k16W+Mg3uHtmBWJCA5GaGI7a7SagQj3JPirg5m48u7WH9WGEkbkLqjYdCnuPuqWqmxvn9uDyia1ISYqDlZ0bOvabADtn6edx+9JB+F8/gcjQN2zdxsEDrbr/LpF+1+pJuH/tuMR+7r41MWTi2hLLcu/SLtw+s4m1k5mtO1r0nCyznWKonY6sQOSndmrWfQL8mhRvpzSWJoi1UzwsbMuheY9JsCpFOz27tQtPrlI7xcHIwh2120+Gma30siREvcH9cysQG0btFIGabSbAt45kWSJC/PH46ibEhgciIyUWzfqugqNXI5SW57d34em1Tcj8VJ6abSfDVE55HpxfwY6VlhgBv9YT4FO7zzflKc7DK7tw7wK1UyxMrd3RpNsUWDpI3y824g1uHF+BqI+BSI4PR8POE1C1keQ1TKQmRuPK4UUICbyBvJxMGJjYoWWfubCw9/6hrptrZ/fi4nHh/eSKLr9OgL2L9P1uXTyIe9dOICI0mK3bOnqgTfeRn6WPCnuLozuX4s2LhygoyIO5tRMGjlkCQxPBOJDDKS0/pzzF4XC+mrMBwfj79G0MalgZe4d1hJuFEYZsOcVe0KWRm5ePwZtPIiIpFX/3aIxjo7thWvu6MNXV+izt87AYHLz/golDpeHlw9O4enge/FoMQ6/xR9gA4+Cq/khPjZdeltxM6BlZo07bMdDSlS0iGFm4YMjcm0VLt9G7S1UewwaNYDP8d0Rs2YjA/n2QEfwGrkuWQVnfQGp6q98Gw6RtOyb2PO/VHTFHj8Bl7nxouojElpzYGISt/QeB/fsicEBfpDx6COd5C6Hu4CC3LFev38C6DZvwS49uWL1iKRwd7DFxyjQklmDVFRUdjQ2btsDL00Pi9+zsbLwJCUHP7l1ZftMmjUdoWDimzpxTYr2cC3yHxRf8MaiOL/YMbA1XMwMM3X0RCekyrpn8fAzeeR4RSWlY1Kkejg5tj6mt/GCqo1mUZlf/Vrj4R5eiZW3Pxuz3xuXsSyyPkpYmUgJe4fnIGSgNGvbWqHJ8HeKv3sPNym3xbuU2eK+bDePGtYrSWHRujnKLJuDN7H9ws2p7pAa8RLVTm6BqYig370s372LVlt3o16UdNv09E872thg9cxESk1Lk7hcZE4t/tu6Br4fbZ9uObVohsUwYNoBZ9NWtXqXEc/V1UkKbmiq48CAXyw5mMcFlYCs1aGtIT29npoiejVVx/2Uelh7IwvN3+ejbTA3mhqJghqoqYEIBCTxfSsOKKqjjq8LEm6X7M5GTCwxuq8HEF1lUcFFGu9qqOHs/B3/vzUB4XAEGt9GAtoaoTO1rq8HLQRlbz2Zh5eFM6Gkp4NcW6iWWp20DPTSvo4v1B+IxYVkEsrMLMHmwOVSUZQdvVFNVwIfwHGw6FP9d8yUxpn4lNew+l4EFO1KRk1uIEV205dZNJXcVdGqggZO3sjB3awoTcmgfEryEfIzKw7bTGZixMQUr9qex337vqgMFGUW5f/M89m1ZgjZdf8O0xbtgY++KJTOHIyUpQWp6LR1dtOr0KybN34qZS/eiVoPW2LxyBp4/vl2U5syRbbh4ai96D5qIyQu2QU1NA4tnDkduTjZK4tm90zizdwHqtxuGITMOwdzGDdv+Hoi0FBn9QnYWDExs0LjzaGjrGUtNc3TLZAQH3kan3xZg+OxjcPasia2LfkVKYrTcsrx+dBo3js5DtWbD0O3PIzC2csextf2RIaOPyvvUR9VsPQaaMvoobX1z1Gz9J7r/eRjdxhyCtWt1nNw0jIlAJfHo9lkc2b4ITTsOxl/z98PSzhVr5g5CarL08gQH+qNijeYYPnUz/pi1E/pG5lgzZxCSEiTPu1z5mpi17krR0mfkghLL8vzeaZzbOx/12g7DoOmHWTvtWDygxHZq1HkMtPWk182xLVMQEngbHQYuwNBZx+HkVRPb/u5XYju9eXIat47PR+XGw9B51GEYW7rh5IYBMtspNycLuoY2qN5iDDR1pJclNyeTCXd12k/FlxL85DTunJiPSo2GoePvh2Fo4YZTmwYgM03WdZMFHUMbVGsuuzxfmqeQF/6ncengPNRqOQy/TjoCM2t37FvRnwkess5b39ga9drLHmdlpidjx6LuUFRSQdcRGzBw+ik06DwO6lp6P9R18/DWWRzetggtOg/G+AX7YG3nhlVzBsu8n14HPkDlWs3x+7RN+HPOThgYmWPV7MFIihcdJzYqFEum9IGZlQNGzdiEiX8fQvOOv0FFVbXEuuFwisOFnJ+EgwcPwtvbGxoaGuzreaNGjXDt2jWoqKggKipKIu2oUaNQu3Zt9v+HDx/QunVrGBgYsC/wnp6eOH36dKldgc6dO4cKFSqw4zZo0AAxMTE4c+YMypUrB11dXfTo0QMZGRkSL4sjR46Eqakp1NXVUatWLfj7+0vkTcd3dXVledavXx/v37//orq4desWs4jR1NRk59W0aVMkJiaW6vhbt26Fvr6+RH5Hjx5l5ypk+vTpzNpmx44dsLe3h56eHrp164bU1FS2vW/fvqzuly9fzvaj5UvPgTh06BBrDzU1NXacxYsXS2yPjIxEy5YtWT05ODhg9+7dLN23WgHtuBmADlXKoV0ldziZGWJy2zpQV1XG0YcvpaY/8vAls6hY+ktTVLCzgJWBLio7WsLNQnLAnJGdiwn7LjGRR1ejdB3Wg0tb4F2jC7z9OsLYwhmNu82Aiqo6nt85JDW9hZ0P6nUYB/fKLaGkLPsYiopK0NIzKVo0teW/jAsx69YdsSeOIe70KWS9f48PixagICsLxq1aSU1v1LQZIndsY9Y12RERiD16GEl37sC8W4+iNMm3bgq2h4UiOzQU4evXoiAzA9oe0r92Czl05BiaN2uCpo0bwc7WFr8PHwo1dTWcO39R5j75+fmYv2gxevXsDgtzc4ltdP8vmDMLdWvXgo21Ncq5u2P4kEF4ExyMmJhYuWXZcfcFOlRwQbvyLnAy0cfkln5QV1HC0SeCr1LFod9TsrKxtEsDVLAxhZW+NirbmcPNXNQOhlrqMNbWKFquvwmDjYEOKtvJtgwTEnvuOl5PW4boY7LrQhy737oh810YgsYuQNrLt/iweheiDp2Dw++ir4wOo/ohdNN+hG07jLSgEDwbOg35GVmw6dtRbt57T5xF68b10LJhHTjYWOGvQX2hrqaGk5evydwnP78AM5euRf9uHWBp9vnA1MhAX2K56f8IFb3KwcrctMRzreurjHsv8uD/Kh/RiYU4dC0HubmFqOIu3UC3to8yXn0swNUneYhJKsQ5/1wmnNT0EqV/9DofFx7m4U2YfEsRadQpr4Lz/jlMICLroF0Xspjo4u0o22C4XnkV3AnMxf2gPHYOJALl5BWimodgH3VVsP+P3sjGm7B8hMUWYPelLDhaKjFhSh4t6+ri0PkkPHiegY+RuVi1OxYGukqo4i0SGYvz5GUm9p5JxP1nGd8134aV1XHmThaeBuciPDYfW06mQ19bEeVdVWTu06iKOm49zcadZzmsPkkEys0FaniLnoc3n+YgOCwP8SkFCI3Ox/EbWTDUVYSRnvS6OXd8J+o0bo/aDdvAysYRvQdPhKqaOm5cOiY1vbtXZVSq3gCWNg4wtbBB49Y9YG3vjNdBT4qscS6c3I3WnfujQrV6zMJnwO8zkJQQi0f3rqIkbp/bhsp1O6Ni7Q4wtXJG6z7TWb/w6PphqenJqqZZt7/gU70llKX0C/TS/uLBBTTt8ifs3arAyMwODdoPh5GpLe5f3iO3LI+vboGXXxd4VOsII3NnNOg8A8qq6nhxT3ofRRYgtdqOg2vFllBSkt5HOXo1YNY3+ib2MDB1QI2Wf0BFTRNRHwT1J4+rp7ajRsOOqF6/PfvK32XAVKiqauDuFUnrQiG9Ry5A7abdYG3vDjMrR3QfPAMFhQV4/eyeRDqqN11946JFU7vkF/Lb57eiUp3OqFC7I2unVr0F/ffjG9LrhqwjmnYdC+9q1E4qUtsp6OF5NBFrp/rtRsDQ1Bb+JbTT02tb4VGtM8pV7QhDc2fU7TgDyirqeOkvq528UaP1WLhUoLGE9PvNrlwdVGs+Co7ego8MX8KzG1tRrlpnuFfpCAMzZ9TpIL88pjbe8Gs1Fs7lW0JRRnm+NE8h9y9ugW+tLvCp2RHGls5o1lNwDQfclr6fpb0PGnQaB48qLaGsIv0avntuA3QMzNGq7zxm2aNvbANHj1owMLH9oa6bSycF95Nf/XawsHFCt9+msPvpzuWjUtP3+30+6jTtBhsHd5hbOaDn4OkoLCzAq+ei++nEnpXwqFAb7XuNho1DOZiY28CnSn3o6JXuA+cPAb0zlcXlJ4QLOT8B9ELfvXt3/PrrrwgKCmIiS4cOHVCpUiU4OjoywUFIbm4udu3axdISw4YNY+LG9evX8ezZMyxYsADa2tqlPjaJGqtWrcLt27cRGhqKLl26MCGBRIVTp07h/PnzWLlyZVH6sWPHMoFi27ZtePToEZydnZnQkpAg+LJHeVDZSVx68uQJBgwYgPHjx5e6PLRPw4YN4eHhgTt37uDmzZssL3qBLc3xS0tISAgTeE6ePMkWEm7mz5/PtpGA4+fnh4EDB7K2ocXGxuaL8n/48CGrSxKIqF2onqdMmcKEJiG9e/dGREQEa286p/Xr1zMh7Vsg65qgiFhUdxa4txCKigqo7mSNgI/Sv1xcC3oPH1szzDt+E/XnbEOHZfuw8eoj5BdIvtTNPX4DddxtJfKWR35eDqJDA2HnXqPoN/JxtXWvgYi3j/EtJMZ+wJqJtbBhakOc2jIGKQkRJe6joKwMLVc3pDwQEx4LC9m6tqd0M1tFFVUUZEtaKRRmZ0Pbx1f6QRQVYdiwERTVNZAWKNtlh+5jElgqlC8vtqsiKpT3RdBL6YIbsWvPPiZUNm/aBKUhPT2dCZFa2lqyy5Kfj6DIeFRzsBSVRUGBrQeESReArr4OhY+VKeaduYsGS/ah49pj2Hgz4LNrRvwYp5+9RdvyzhKi6vdCv3p5xF2WdGWLvXATBtUF9augogK9ip6Iu3Rbou3jLt+GfvUKMvPNzc3D65D3qOzjKdFOlX08EPhKushFbD1wFPp6umjVqGRXCnLXuv3wKROKSkJJEbAyUcRrMcGFHI3ehBfIFDjo9zfhIrcc4lUopZdjFlJKjHQVoKeliNehovyzcoAP0QWwN1eUeQ7WppL70DnQur25oEw2pkpQVlKQSBOTWIiElALYW8gut6mRMgx0lfHsdVbRbxlZhQj+kA03e7WvPs+vyddYT5G5PgW9z5Oom3cReXC0VJZZN7bmSgj6kCdRN0Hvc+FoJX0fsqYikSc2KR+JKZ/ff3m5ufgQ8hIevlUlrmEPn6oIeVWyWyGJNi8C7iMq/APcPCqy32Kjw5GcGA8P32pF6TS1dODo4oWQVwFy88vLy2EuUo4efhLlcfL0Q2hIyUKHNAry81FQkA9lVcm2oJfZD68fye2jYsICYeMq2UfReuT7b+ujispWkI/Xj04hNzsD5vaynzVEXl4uQt++gKt3dYm6ofX3b56W6ng52VkoyMv7TKgJfvEAkwbWxZxRrbF/4yykpyaV2E7k6uLoWUOiLNRuocFf2055gnZSkWwnesn/+Oah3HYilyTrYu1k7eJXKnHseyMsj5Xz5+WJ/sryfG2etB+5SDmUk9zP3r0Gwr9hnPUm4DIs7LxwZN1ILP/TD5tnt8OTG/tL3K8sXTf07At9GwR3H8n7yd2nGt6+LuX9lJOFfLH7qaCgAM8fXYeZpR2z1BnXvy4WTuiBp/cvf9W5cTg8Rs5PAAkFFN+CBBA7O0FMErLOIfr3748tW7bgr7/+YusnTpxAVlYWEwmIjx8/omPHjkXpSfj5EmbPno2aNWsWHWvChAlM5BDm06lTJ1y5cgXjxo1jL4Vr1qxhYkTz5s3Z9g0bNuDChQvYtGkTKyNtd3JyKrI+cXNzKxKYSsPChQtRuXJlrF69uug3smohSnP80kIPY8pHR0eHrffq1QuXLl3CnDlzmIWOqqoqswgyL2b1UFqWLFnCBCkSbwiyUHrx4gUWLVrELH5evnyJixcvMmsiOl9i48aNcHFxkZknCXa0iFOYmwc1FdFjIDEjC/kFhTAq5mdB6+9ipQ/cwhJSEfE2Ai18XfBP3xb4GJ+MucduIC+/AIMbCsp25mkwgiLisHtoh1LXQWZaIgoL8qGlI/mVgtYTot7ia6H4Os17zWNxccgf/M7pf7BnSU/0m3wCquqyRUxlPX0m5uQWE/1yExKhbifd3Sf5/l2Yd+uO1KdPkB0eBt1KVaBft95nQdc0HJ1Qbu0GKKqqIj8zE8ETxzGLH1mkpKSwa9CgmPUYrYeGCuIqFOd54AucPX8Ba1YuR2nIycnBxi3bUK9uHWhpyrYaSMzIRn4hXTOSbitGWup4H5csdZ/wxFT4J0WihbcjVnVvhNCEFMw9c09wzdQViVNCLr8MRWpWDtr4OuPfQM3MGNnRcRK/0bqKng4U1dWgYqAHRWVlZMdImlNnR8dDy032MzM5NZWJU4b6uhK/G+rr4UN4pNR9nga9wsmL17BlyexSlf3MlZvQ1FBH3eqCe00eFL9GSVHhszgxqRmFMNWXLpyQSw5tFycto1DCVedrEeZRPP/UjALoaknPX0tDcA6f71MIMwPFonzz8guRWczTKzWzELpyyq2vIxB5ktIkhStaF277Gr4mX11tQTlT0gs+O0+KfSMNbU1B3Ujbx9xI6bM4Ou3raUBdVQFR8flYvi8N+VJ01NTUJPYSpFvsa7GuvhEiw2U/ozLSUzFmQHPk5eZAQVEJvX4bD8/ygheilCTBfaSrJ2kJqatvyGLwyCPjU3m0i5VHW9cIcZHv8DWoaWjBxrk8rh5bAxMLJ5Z3wN1T7MXR0Ey2BUFmuqCP0izWR9F6YvTX91FEXMQrHFjWDXl52VBR1USr/v8wix95pKcksrop/mWf1mMiSlc3x3ctha6hCdzExKByvrXgU7URjEytEBcdipN7VmDtvCH4Y/ZOZt0qjYxUQVmoXcQh17a4qK9tJ23YOJXHteOrYWzhyPJ6Vop2yhK2k7ZkWTR0jJEY83Vl+RaE5dEodt1oaBsj6SvL87V5ZqRJv4a1dI0Q/w3jrKTYUDy6tgdVG/WDX/PBiHz/DBf2zWbWRD5+7WWXpwxdN2mpsu+nqPDSlYXi4OgZmsD90/2UmpyA7KwMnD+6Ca27jUDbnqMQ9OQWNvz9B3PHcvEsuR/ncMThQs5PgK+vL3vpJzGGrEuaNGnCBBRyK6KX/smTJ+Pu3buoXr06Ex9IxCE3CoLcjIYMGcIsZ8gdi0QdH5+SA6MJEU9rZmbGxAtxMYh+u3//PvufBB6yJBAKPwS5flWtWpVZEhH0t1o10Vc6gqxbvsQip3PnzlK3leb4pYVcmIQiDmFhYfHN1jDiUHnatm0r8RuVm6ydyLro1atXUFZWRsWKgi+cBFkXUZvLYt68eZgxQzJmyKTOTTC5a7NvKmtBYSEMtTQwtX0dKNGXWisTxKSkY9uNp0zIiUpKw8KTt7Du11YSotH/CkdPkZUDBU+2sPfF+in18erRGXjXkH7tfC0fly+F/dgJ8N61l1lwZEWEI+70SZi0lHTFyvr4AYH9ekNJWwuG9RrAYdJUvBwxRK6Y8yWQe+OCxUswauRw6OlJigrSIGF49ryF7Hv+yGFD8L0pKCTXKQ1MaeknuGYsjBCTmoFtdwKlCjlHn7xBTWcriRg6PyMZmZmYvXwdxg79Ffq6oueLPE5dvo4mtf2g9gP411dyVUaX+qKvoutPSI+h9F9Rq6IWBnURuYDO2yA/XsK/SVUPVRaEWMg/BwWxa/4t7gVmM0sdEoUaV1XDwLZaWLQzFXmSWtNXo66hhelL9rCXFrLI2btlCUzMrZjbVVmEYuMc2TQJi/6oy8QJCzsPeFdvyax//heQS1X3v44iJysVb56cw/ld49BxxM4SxZxv4cLRjXh8+wyGT9sMFTHrpIo1BR++CEtbV7bMGtkCbwL9JQSf/4IOvy3E0c0TsXi0WDtVa4mID/+bduLItsQji5x67UezdXNbDxYk+fG1vXKFnJ/pujl/ZBOLsTNqhuh+IjcrwqdyfTRo1Yv9T25Yb189wY0L+38eIecnnSGqLPK/f6vifDNKSkrMqoTcm4SuTJMmTcK9e/dY7BRyLSKrHPqf4teQK44Qcl0i8UfoBkUv+2QNM2LEiFIdm4QQIeTyIL4u/I0sB/4rKF7Mt0Bmk9QBiUPiT3H+1+f5NZC11OjRgk5VSOHpdRLrBprq7Itu8cDGtG4s4yXaREcTykqK7IVciKOJAeJSM5ir1ouIWBb0tts/B4u2k9XPw/eR2Hv3OfxnDpTYV4iGtgH7kls8sDGta+lKD1j5Nahr6sLA1B6JsR/lpstLTkJhXh6brUocFUMD5MbLCFCYlMSsaxRUVaGsq4fcuFhYDxnG4uWIQ/mSxQ6R8eoVNMt5wKxzVxaDRxoUf4qu1eKBjWnd0EDSSoeIjIxCdHQMps6YJTrmp+u8Wet22Lx+DSw/zZrFRJz5CxETG4OFc2fLtcYhDDTVoKRA14zIbYSIT89isW2kYaKt8dk142Csx2ZJIzcqFSXRV14KiHzvXSQWd66HfwuyviGrHHFoPTc5FQVZ2ciJS2TuBmqmkl/m1MyMkB0lackjjp6ODjvHhGKBjckdykj/8xgT4VExiIyJw/i5SyWEUqJup77YvWoBrMxFMYKevniFj+GRmDF6WKnOMz2rkN174kGBhRYsKcUsXMStOYpb35DlR3GLmNLw/F0ePkSLlAJyf5J2fB1NRRYTRuo5ZArOoXiZxPOgslHeFIpL3CpHR0PyOA8CMxD8t8iCTflT4GF9bSUkpYiOT+vvI748kLOQpNT8EvN9GpzD3KZEZRH8JaElJT1f4jwpgLE0yFKK6kZgsSO5T3ErHXLTysopYDNg0XGX/K7PYu88CJLs73R09NmLT0qx4J5kVaOnL/s5TM8nMwuBS7Gtgxsiw97h1KEtTMghax6WR3IC9A1FMaAoeLKtg/xZ9zQ/lSetWHkoEKqsQMalgeJl9J+wAznZGWyGGx19U+xb/QcMTWS7AmtoCfqo4gFzaV3zG/soivGmbyKwsDa18UJM6DM8vbYdDbrOlLmPlq4Bq5vigVhpXedTncuCZrm6dGwzhk7ewGa6koexmQ20dAwQF/VRppCjqSMoS/EAtTQLkbbut7XTr+N3SrTT/tV/sGC3slAXtlOxoL80s9O3ttPXICxPZrHrJjMtjlkJ/Zd5ampLv4bTv/F+oqDDxhaSMzOSNcyrx+fk7leWrhttHdn3E8WJkgfNcnX+6GaMmLqezXQlkaeSMsxtJOvG3NoRIS+/jzsm5/8XXDL7SSAhgSw2yOLi8ePHzLXnyJEjRWLNvn37WAwVclsSt0ghKH7L4MGDcfjwYYwZM4a5G/0b0LGpXBSMWFwkIfcgimlDUJBkoQWPELIm+hILIXJx+trjm5iYsKDF5IYlbuXzpdBxhHF5vgaqB/FyErROLlYk3JHLGb1wU1sLCQ4OLgrqLA0KmkwCgPhS3EJGRVkJ5SxNcC9Y9HJTUFCIeyHhLA6ONMrbmSM0PpmlE/IhLokJPJRfNScrHBzZBfuGdy5aPK1MmCsW/S9NxBEOZM1sPPHxlSh2SWFBAVu3dJQfK+BLyMlKR3JcKLTlzHLFjp2Xh/TXr5h7VBEKCmxdXjwbtm9ODhNxaDpyg7r1kHjjeon3M8XXkQUJiS7OznjyROSnTULikycBLEhxcWxsrLHun5XMrUq4VK9WFb4+3ux/E2NjCREnPCIC8+fMYtdISZDoUs7CCPffR0qID/ffRcLHWnqd+tqY4mNCSpFIQXyIT2ECj7iIQxx7GswCHwunJf83SLr7BEYNJF9IjBvWQOLdT8FZc3OR/CgQxg3ErAMVFGBU3w9Jd2UPvlRUlOHqZI+HAYES7fQw4AU83T7/sm5rZYHtS+diy+LZRUutKhVYIGP637TYNPAnL12Dm5M9XBxKN2Uzuc6ExxbAxVp0z5F04WylyOLSSIN+d7GSbBNXa0r/5c+37FywacWFS1RCAZLTC+BiI8pfTUUQl+d9VIHMcwiLoXNQkjgHVxslvI8SlCk0Jp+5Vonna6qvwAL6ik/DnZVdyKb/Fi5hUblITMmDl6vITZCm/Xa2U8Or9yXPpiSLmPi8EvOlUFqxSQVFS2RcAZLTCuBuJ3pGUxBnB0tlvBUTfIrXzceofIl9qG7c7VXYFOOyEMaBVPkkrImjrKICOyd3BAX4S1zDQc/84eRW8tS9QgoLClnMCcLEzAp6BkbMUkdIZkYa3r55Dic3+RbBFHTX0t4Tb1/clSgPrZP7xLeiqqbJXvJo1p3gZ7fgXrGhzLTUR5laeyL0jWQfFfr6DixKiGfzpdCXfIpnIg8K9Grj6CERqJjq5vXzu7B38ZUd0PXYZpw7tA6DJ6yBrZMonpcskuKjkJGWBF0DE7ntZMHa6Y5EWd4F3WVubN+znUKe34R7hQZy28nEyhPhxdopLPguzO2+vSxfSlF5giXLEx58F2ZfWZ6vzZP2M7f1xPsgyf0+vLwDq28YZ1k7VUR8tKT7UUL0e+gZWsndryxdN/Tss3Esh1fF7idad3SVfT9dOLYZZw6ux7BJq2FX7H4SPE89EV3MLTUm4gMMjfnU45wvh1vk/ASQ5Q2JF+RSRbMx0XpsbCwTAwiyuKEXMopnM3PmzM9msKJ4MSQQkAhA8WyE+31vyJ2L3LgoFo2hoSFsbW1ZTBty+6D4OgQJSmQRRGlIgKKgv+IBfktjdUIuZkOHDmV5kaBC50TuVsbGxiUen9y6yD1s4sSJzO2M6vJLji/uekX70mxVFDyajkdfKEsLCWpVqlTBrFmz0LVrVxa4mYJKC2P/uLu7M1e43377jcX9oRd72ocskr41GGyvWj6YcvAKPK1N4GVtip23ApCZk4t2FQVf6SYduMymFv+9qcAFrks1T2ZZs+DkLXSv4YWPccnYePUxetQQzLqkpaYKF7HZiAgNVWXoa6p/9ntxKjfshzPbx8HM1ovFtnl4eRtyszPhVV0Qa+f0trHQ1jdj040TNNCNjwwR/J+fg9SkaMSEBrEZPwxMBV83rx5eACfv+tA1tERacgxun1rJYta4V5Y+85Q40Xv3wGHSFKS/DEJ60AuYdekKRQ11xJ06xbY7TJ6K3NhYhK1bIzh3D0+oGpsgI/g1VIxNYPXrAGZyGrV7Z1Ge1oOGIOnuHeRER0NJUxNGjZtAp0JFvB49Sm5ZOrZvi0VLlsHFxRnurq44fOw4i3/VtLHgxWPh4qUwMjJE/7592H3gYC84fyHan9wrhb+TiDNr7ny8CXmLWdOmoCC/AAkJAmFQR0f7Mys0cXpV98CUYzeZi5SXpTF23Q9CZm4e2n6KaTP56A3mFjWyYSW23qWSG/b5v8TCc/fRvYo7PiSkYtOtZ+heRfLZQ0LP8afBaO3jBOUvuH9o+nEtZ5G4oelgDV1fd+QkJCMrNBJus0dD3coMT/uNY9s/rN8Lu6E94T7vL4RuPQTj+tXZdOP+bQYV5fFu2Rb4bl6ApIfPkewfAPuRfaCspYHQbdJnyhHSrXUzzFm5Ae7ODijn4oj9J84jMzsbLRsIghPPWr4OJkYGGPxLF+Ye5WgnKVhpawksoor/np6RiSu372N4X9EMaKXh2tM8dGugymZy+hhdwGalUlVRgP9LwYs+bUtOL8SZe4KX7hsBeRjaVo3NdvXiQz4qOCvD2kQRB6+JXio11AADbYWiuDYmLN5OAbOMSS3Be+r6k1w0qUzBdguQkFKIFtUFx3/2ViQ8DG2njoC3+bgZICjT1Se56NFIDaExdA75qFteFarKCmw2LqG1Cf3frpYaMrKykZVTiI511fAuMl+mYCXk1LUUdGysj6jYPMQk5KJrcwMkpuTDX2xGqqlDzHH/WTrO3hTMVEhxZsyNVSSCG9tbqiItIx9xSfmlzrc4lx5koXkNdWY1Q/m0qa2BpLQCPHktspoZ1VUbT97k4uojgSB00T8LfVtq4UNUPt5H5qFBZXUW0Pj2s5yiIMqVyqki6F0ui0VkoKuIptXU2axfz99+bn1KNG3zCzaumAZ7p3JwcPFiM05lZ2WiVsM2bPuG5VNhYGiCTr0ElrynDm2GvZMHTMytmXgT8Ogm7lw7hV6DJrDt1Ec1btUDJw9sgpmFLUzMLHFk9xpmnVOxWsmWdzWa9sHhDRNg5eDFZqy5c347crIzUbG2wGXj4Ppx0DUwQ5POo4sCqMaGC/uFXKQkxiDyQxBU1TXZDDbEm2c3mfursYUD4qM/4Ny+v9n/FWvJdwOpUK8fLuweBzMbLzYj1ZNr25CXkwmPaoI+6vzOsdDSM2PTjbPj5+UgIUpQloL8HKQnRyM2TNBHCS1wbp1YDHuPOtDRt0BOdjpePTyJsOD7aDd4U4l1U69lb+xaPYkJMrZO3rh2mqyMMlGtXju2feeqidAzNEXrHoL+5eKxTTi9/x82e5WhqRVSkgQWhmrqmmwh17izB9fAt2oj6Ogbsxg5x3ctgbG5Lcr51pTfTk364sjG8bCyp3bywZ3z21hZKtQS1M3hDePYS3XjzmNE7RQh3k7RiPwYxF6+he0U/OwGC+BtbO6AhJgPOL9vEbP0EOYpC9+6fXF573iYWHvB1NYHATcE7eReRbDfxT3joKVnCr8WonZKjBaVhdopLlzQTnrGgrLkZtNHIJElb2pCGEujpqkHHQNR8H9peNfui6v7P5XHxgfPbm5j03q7VRaU5/JeQXlouvGi8sR8um7yPpUnIojFTxKWp6Q8ZUFxbE5uHQdzey82I5X/JcF+PjUE+53YMhY6+mZsunFhWeKE46y8HKQlRSP60zjL8NM4q0qjPtixoDtun14L98rNEfk+gAU7bvaLbIuysnjdNGzVG9v/mQxbJw/YO3vj8qmdyM7ORPX6gvtp28qJ0Dc0Q9uev7N1ssI5te8f9P19PgxNrJCcKLqf1DUEfXmjNn2xeelfcPGoCBfPqnjx5BaePbyG36eXfH//MPykM0SVRbiQ8xNAIg3NOkXxUygIKgU8JjFEGNCXBASKlTN37lw205E4ZDVCM1eFhYWxfJo1a4alS0Vm/d8bmtmJFG0KDkyWLxSol6YwF8Z2IXGFZmD6448/mIsYxa+hcgtn2SoJEqTIRYyEGNqXhA0SZ2hWr9IcnwSXnTt3MrGHLJMo9hDNGEWCyZfw559/ok+fPszSJzMzE+/evWPiTmmh2Df79+/H1KlTmZhDMXhIhKN2FLJ9+3YmQNWpU4cFVSa3uMDAQDat+rfQzMcZielZWH3Rn7lH0TTiq/u1hNEn16qopFQoij2jzfW1saZfSyw6dRudVxxgIk/Pmt7oV+fbv564V2qBjNQE3Dq5AhmpsTCxKodOwzYWuValJEZCQUH0gk/CzPb5gg6WeHBpM1usXaqi2yjB7G2pSVE4uWU0stKToKFtCCunSuj5535o6pQ8BXnC5YtQ1teH1YCBUDE0QkbwG7we8wfyEgUBkFXNzAUBYD5BwYutBg6CmqUlC2KcfPc23s6agfw0UfwLZQMDOE6eBhUjI+SnpyEjJISJOCkPJC3TilOvTm0kJydj+87dTISl2FRzZk4vupZjYmO/SNSLi4/HnXuCYw4ZIRiUCFk0bw6z3pFFU08HFih7zbUnzD3KzcwQq3s0KgqaHZkimP1KiLmeFlb3bIS/z/uj87rjMNXVRI+q5dDvk/gn5O7bCEQmp6Nd+S+LC6FXyQt+l0Sz9Xn8PZH9Dd1+GAH9J0DNwgQaNqKvX5nvw5ho47F4AuxH9EZWWBSeDZqMuAs3i9JEHjgDVRNDuE4bCTVzE6Q8DcL9VgOQUywAcnEa1qqOpJRUbNxzmLlUOTvYYvGUv1jAYyI6Lp7NDPelXLx5l9470ajWl8WoeBqSD22NXDStosJcbiLiCrDxZDaE3pQkyIh7l5LwsetiDppVU0HzairMkmbr2WxEJYgSedoroVsDUUyNXk0E/5/3z8X5B9LFASGXHuUyIalrfTVmpfI2Mh/rjmdKxGoh8UFbXSTAPH6Tx4IeN6+mysQjsjKifcSDOB+5kY2CQlX0a6H+f+ydB3RURRfH/9vSe0IIJIEkdAi9S+9FUBCxICCKDURFVBT1E8FeKIKFXgWVXqX33nvvKaT3nm3fubPZmt1N6Bu8v3PeSd7uvNn7Zua1/7v3DuQy4GKUGst2luxVs3p7hhBm3nzOH26uUly8UYBvpsdDqTLWXT5ADk93o7dPRKgzxo0wjqchfXSeUzsPZ+G3v5JLXa8lmw8VwFkhwUvd3ODmIhFThk9dkm3WNuV8pWahcscuKuHploferV1EiBWFYdE2+lA4JXkqhcjRqYmzqDMzR4ur0UqRH8dWuFyz1l2RlZmGVX9PE7NNhYZXx/tfTIV3UbhOalK8mKlOT0F+PhbO+B5pKYlwcnJGUHAYXh/5tahHT4++LwsxaP4f34jEyNVqNcCo/001y81ii7rNeyInKw3bVk4RIRcVKtXC4A9mGEJBMlLiIDW5LmSlJeH3scYHtn0b54iFpiIeOmaB+Cw/Lwtblk5CZlo8XN29UadJV3TuN9Lm1NN6qjfqibycVBzcMAU5mbpr1NNvzoJbUThLlsU1KicjEX/9bLxGHd8xRyzBVZqh3zu6c1Zedgo2//kxcjIT4ezqiYCKNYSIU6mGfeGEaPREd2RnpgpxhkQZmlb8rTHTDKEgaSlxkJicb/ZtWQK1Som5E83Drrs/Oww9+g8XLzlu37qMw7vWIC8nU4hANeq1RM/nRticelpPpOinVGxfNVVMLBBUqRYGjZpp0k+3za4LWemJmDbWKJzt3zhHLNRPr3yia5v8vGxsXTaxqJ98ULtxF3Tq936J/VStQU/kZ6fi8Kap4l4ioGIt9HptpqGfstPMbaG2XzLJaMvJXXPEUjGiKfoM19mSGH0Wq6e9bGzLNbqZS2s06YNOL+j+t0VVsicnFUc3G+3pOdTEnnRze3IzE7F8stGe07vniKVCRFM89dbCUtVpi9pNeyI3OxV71ujGcGBILTz3rsl9Vqr5GKZ+olmo9BzaMkcslao3w0sf6GwhQeiZYb9i18qJ2Lv+N/gEhKDzc58isrlO/C0r46Zxq+7i3Lfun9+RlZ6M4LAaePuzPwzhoWnJ8WZts2fzEjF73KwJOpFJT8/+b+HJ54aL/xs07ySmMaccOkvn/IDAimF47cOJqFrLmPOSYUqLRGuZEIR5LKEHfvLSWbNmzaM2hXlAkBhHYXI0mxUJUKUhf/mDE+3uhoXe78NRaPDlw03iWBKB8+bDUQg8uByOxPZXHKdtmp3UPRg6Aj/sLn3oy8NApXKcPGKx15PgSPgHFc9t9agY1Nv+w83DJjbDcZKcJ6U7TkaCKhXuPm/TgyA913HGTYJ9ff2hY21GuEeFn7djeUu4ODnOY2iAh+McU53rlSxqOyq580v2vHoUuL38BR432CPnMYfe2NP03YsXL2YR5zFj+/btyM7OFqFkNAX96NGjhdcPeegwDMMwDMMwDMM8TMiTj3k4cEs/5tAU1pQ7h/LFdOnSpdTbUXnK7WJtoe8eFRQuZssuCsFyVB5Ee1KiZgohq1OnDvr27SsSNdOMZPZymTAMwzAMwzAMwzBlG/bIecwxnWr8TqB8LJTnxRqlmcnmQTFr1iyRc8YalN/GUXkQ7UlJrGlhGIZhGIZhGIZh/juwkMNYhWa/osXRCA62P3Who+Ko7ckwDMMwDMMwDHNfMEkAzTxYuKUZhmEYhmEYhmEYhmHKCCzkMAzDMAzDMAzDMAzDlBE4tIphGIZhGIZhGIZhmHtD6lhT3D/OsEcOwzAMwzAMwzAMwzBMGYGFHIZhGIZhGIZhGIZhmDICh1YxDMMwDMMwDMMwDHNPSHjWqocGtzTDMAzDMAzDMAzDMEwZgYUchmEYhmEYhmEYhmGYMgKHVjEMwzAMwzAMwzAMc2/wrFUPDRZyGOY/TFyD3nAkMs9o4SjU+GUcHIn82d/AUUh5ZTQciWYnO8FRONxgMBwFvz/Pw5FISsqDoxB3NQqOhKePOxyFxnFr4UjU8wqAo3C6cls4Cg1TNsCRiK7YAo7CNZcgOBIqjeMEQAR7ZcCRcJYWwlEoX3ALjkPzR20AUwZwnDMLwzAMwzAMwzAMwzAMYxf2yGEYhmEYhmEYhmEY5t7gWaseGtzSDMMwDMMwDMMwDMMwZQQWchiGYRiGYRiGYRiGYcoIHFrFMAzDMAzDMAzDMMy9IeFZqx4W7JHDMAzDMAzDMAzDMAxTRmAhh2EYhmEYhmEYhmEYpozAoVUMwzAMwzAMwzAMw9wbUvYTeVhwSzMMwzAMwzAMwzAMw5QRWMhhGIZhGIZhGIZhGIYpI3BoFcMwDMMwDMMwDMMw94aE/UQeFtzSj5idO3dCIpEgPT39UZvyWNC+fXuMHDnynusZMmQI+vTpg4fFl19+iQYNGjy032MYhmEYhmEYhmHKJuyR8wiEBnpgnzx5slh/4oknEBcXB29v70dm07x584T48V8Uk27evInw8HCcOHHCTEj55ZdfoNVq8V9lzdp1WLZ8OdLS0hARHo7hw95CjRo1Stxu565d+P6HH9GyRQuM/eJ/hs/37tuHf//dgCtXryIrKwu/TZ2CKlWqlMqWc/sX4dTu2cjLSoZfhZpo9fTnCAytZ7P89dMbcWTzL8hOi4VXQGU07/EhKtVsZ/g+NysZhzf8jJjL+1CQn4UK4U1End4BYaWyZ8nm3fhz3XakZGSiWqVgfPTys6hTtbLVsmt3HcL46YvMPnNSyLFv/kTD+vbDp7Bi215cvBGNjOxc/PntaNQICymVLa4tOsGtbU9IPbyhio9G1pqFUMVct1rW5/UxcIqoVezzgosnkVFkj8TDCx7dn4dTtUhIXdxQePMSstcshDoloURbVq3fgCUrViM1LR1VwsPwzptDUbN6tRK32757L775aRKeaN4UX33+ieHz+Yv/wY7de5GUnAK5XI7qVSPw6qABqFWjOkrD8g1b8deqf5GanoEqYaF4/7VBqF2t5DG3de9BfDnxd7Rp1gjffWIUhVs/M9hq+eGDn8eAPk/arM+vdRNEfDAU3o0i4VIxEEf7DUfCmm12bfBr2wy1f/4EHrWrIT86Dle/+wMxC1aalak8bAAiRg2Fc1A5ZJ6+iHMjv0LGkTMoDY2rStC8pgQeLkBCOrD5uAZxqbbL1wwB2tWVwtsdSM0CdpzW4Fqc8ftPn5dZ3W7bSQ0OXbJ/Hm1VV4GODRXwdJPgdrIGK3YXICpRY7N8/Soy9GjhDD9PCZIyNFi3vxAXbqnNynRv5oSWdeRwcZbgZpwaS3cWIDmj9OfzoS+FoXfXIHi6y3HmQiZ+/v0KYuLybJYf+Gwo2j0RgMrBbigo1ODMxUz8Me86omON2zgpJBgxtAo6tQmEQiHF4ROpmPDHFaSlK+3a0qe9O9o2coGbixRXo5VYsD4Lianm+2tJx6au6P6EG7w9pIiOV2HRhizcuK0yfD/6ZR/UDHMy22bH0TwsXJ9ls86/dx3F/C0HkZyZjeoh5fHJc11RNyzYatnVB07hi4XrzD5zkstwZIrx+E7JzMbkVTtw4MJ1ZOXmo1G1SvjkuW6oHOiH0rBky14sXE/n4SxUq1QRHw1+BpFVbJyHdx/GuBl/mdujkGP/3J/E/yqVGr8v+xf7Tl5AbFIKPFxd0CyyOt55vhfK+ZZ8b7bt3yXYuGoBMtJTEBpWDS+9NhoR1SOtlt21eQX271yP2KhrYr1ylVro99LbZuWpnmULpuDsyYPIy8lC9TqNRJ3lK1YqVdv8s/0g5m/ai5SMbFQPDcLHL/ZCZIT1a8qafccxdu4K87aRy3Fo2pdmn12/nYhflm/G8cs3oFJrEFExED8PexEV/H3s2rJ+7WqsXL4EaWmpCA+vgjeGjUD1GjWtlt2/bw+W/fMX4uJiRZ9UDA5Gn77PokOnLoYyeXl5mD93Fg4d2IesrEyULx+EXk/1RY8ne5eqbfZu/gvb185FVkYyKlaqgWeGfIrKVetaLXtg2zIc2bMG8TFXxXpIeG08+fx7NssvmTUOB7YtRZ9BH6Ndz0El2rJv82LsWj9H2FKhUg30efkzVKpi/d7m0PalOLZ3NeKjdbYEh9dGj+dHGsqrVUpsXDoFF0/uRkpSDFxdPVA1siV6vjAK3r6BJdqyef0yrFuxCBlpqagUXhUvvzkKVavXsVr28P6dWL10PhLiYqBWqRBUMRQ9+7yINh17iO9VKhWW/jkdJ4/uR2L8bbi6eyCyfhO8+PJw+PqXQ2nYsG4lVi//G+lpqQgLr4Khb72HajWK378QB/ftxoolf4pxQ/ZUqBiC3s88h/Ydu5mVi4m6iYVzp+P82VNQq9UIqVQZH336FcoFli8T9xIMYw0Wch4xTk5OCAoKwuMOnTTJ80haRjKZP0ph7VGza9duzJw5E++MGIEaNWtg1apV+Ox//8OsGTPg42P7pi0+IQGzZs1GZJ3iF//8/ALUqVMbbdq0wS9TppTalmun/sWBdd+jTd8vEVipPs7snY9/Z7+G5z/cAFcP/+I23DyObX99gGbdR6FSzfa4enIdNi8YgWfeXQ6/oOpCnNu84G1IZQp0ffl3OLm44/TueVg/81X0/2AdFE5udu3ZfOA4Jv+5Ep+8+jwiq1bGXxt24Z3vf8eyCZ/Dz9vT6jburi7iez0SiUXbFBSgfo0IdG7REN/M/LvUbeNctzk8nhyArFXzoIy+BrdW3eDz6kdImTAa2pziD2QZf06BRGY85UvcPOD37tcoOHPY8JnPoJHQqlXIWDgZ2vw8uLXuDp+hHyNl0ieAstCmLTv27MO0WfMw8u03hXizYs06fPzFV5g3bSp8fWwfS/EJiZg+Zz7q1il+gxZSsSLeees1VAgqj8KCQixbratzwYxf4VPC8blt70H8OncxPnxzCGpXr4Il6zZh1Pif8NfUH+Hr42Vzu7jEJPw27y/Ur11ctFw923zcHjx+Gt//PhvtWjS1a4vM3Q2Zpy8het5yNFn2G0rCNSwETddMR9SMv3Fy8Ifw79gSdad/jfy4JCRv2SvKVOjfA7V+GoOzb49F+uFTCH/3ZTRfPxs763RHYZIdRQZArVAJOjWQYOMxLW6naNG0ugQvtJNi+r8a5BYULx/sD/RpKcWO01pcva1FncoSPNtKijlbNEjK0JX5ZbW5sFClggRPNpXgUox98aRBVTn6tHYSQsuteDXaNXDCm0+54rtFucjOK75tWJAUg7q5YP2BQpy7qULj6gq82tMFE/7JQ3yqTvzp2EiBtvUVWLw1HymZWvRo7oS3nnLF94tzobKvfwhe6heKZ3sF45vJFxGXkI/XXgrDxPF1MXD4ERQqre9Pw0gfrFh/GxevZEEmleCNweGYNL6e2Ca/QGfXO69VxRNN/fC/H84jJ0eF99+qhm/G1MHwj0/atKVHKzd0bu6KWasykZymRt8OHvhgoA8++y3F5r40reOM57t6CFHmeowSXVq4YdRAH3z6awqyco327zqWh5U7cgzrtvaN2Hj0PH5evhWfv9gDdcMqYtH2wxg29W+s/vIt+Hu6W93Gw8UZq8e+ZfW8R+fhkdOXQS6TYvKb/eHh6owF2w7hzSmLsOJ/b8LN2VxksmTzwROYtGgVxrzSX3ce3rgL7/wwHct/GmP3PEzfG+0xGpRfWIiLN2PwWp8uQpzPys3FzwtXYtTEWVj41Qd2bTm8dzP+mTsRg976VIgxW9YuxsTxI/Dtryvg5VNclLp07hiat+mGqjXrQ6Fwwr8r52PCuLfx9ZSl8PUPFG3z63cfQCaX490xE+Hi5o7Naxbh5y+H4espy+Ds4mrXnk2Hz2DCkg34bOBTiIwIxeKt+zF88jys+nok/Lw8rG5D7b/ya+ODpgTmF6noxBS8+sNM9GndGMOe7gh3F2dcu50IZ4X9R4g9u3Zg9sxpGD7iPVSvWQtrVi3H2P99gj9mzIWPj2+x8p6enuj/wgCEhIRCrlDgyKGD+GXST/D28UGjxrrz7OyZf+D0qZMY9dEnCCwfhBPHj2Lab1Pg5++P5i2esGvPiQMbsGrhj+g/9AtUrloPuzYsxPTv38SYCWvh6V38fuLqhSNo9ERPhFdvALnCCdvXzsG0797Axz+tgo+f+cP/6SNbcevq6VKJJsTJAxuwdtEP6PfqWCHG7Nm4ELO+fwOjf14PDyu2XLtwGA1aPonKgxtA4eSMHWtnYeb3r+PDH9bA2688CgvzEXvzPDr3fQsVKtVEXk4mVi/8FvMmvI33vl5q15YDe7biz1lT8Orbo4V4s2HNP/j+i/cxYdrf8LYyhj08vdDnuZdRMSRMvGQ5fmQfpv/yDbx8fFG/UQsUFuTjxrVL6Pv8K6gUXg052VlYMHMSfv56NL6ZNLfEttm3ezvmzfwNb44YhWo1amPdqqX46n8fYuqMP+FtZdx4eHqi3/MDERxSSYybo4cP4LdJP8Db2xcNGzcTZeLjYvHZ6HfQqWtPPD/wFbi5uSP61k3xDFZW7iXKFFKLG13mgVE2nqofEyhcZ9euXcLbg24iaCFvGNPQKlqnh+V169YJDwg3Nzc8++yzyM3Nxfz58xEWFgZfX1+8++67QhzRU1BQgA8//BDBwcFwd3dH8+bNRdhWSVCZV155BRkZGQabKMyHIG+MwYMHi98jO3r06IErV66Ual/1+7FmzRrUrl0bzs7OiIqKKtHOW7duoXfv3uI36fs6derg33//NXxP7desWTNRX4UKFfDJJ58I9d8WtD8kRJhCdpF9BHnjEA0bNhRlyWPKWmgV2U1tHhgYCBcXF7Ru3RpHjhwxa0faftu2bWjSpIloL/K2unTpEu4GjUaD8ePHIyQkROwreQtt3LjRrMz+/fvF52QP/SbtJ9lw8qTtB4PSsGLlSnTv3h1du3ZB5UqVhKDj7OyCTZs329yGxuKPP/6EgQNfQlCF4sJk504d8dKAAWjY8M7Cx07vmYeazfqjRtN+8C1fFW36joNc4YJLR5ZbLX9230KEVm+N+u2Gwrd8FTTt9h4CKtYWXj1ERvJNJEadQus+YxEYWhc+5SKESKRS5uPayfUl2rP43x3o0+EJPNW+BSJCKmDM0Ofg4uyENbsO2tyG+iTAx8uw+HubX/x7tmmG15/pgWaRJXs8meLWpjvyjuxE/rE9UCfeFoKOtrAArk2M3kemaPNyoMnOMCzkdaNVFiK/SMiRBQRBUakqslbNhyrmBtTJ8chaPR8ShRNc6re0a8uyVWvRs1tndO/cEWGVQjFy+Jti3G7css3umPl2wmS8POB5VChf/I1Yp/Zt0LhBfVQMCkJY5UoY9toQ5OTm4vrNWyW2zd9rN6J3l/Z4slNbhIcG46M3h8DF2Rnrtu+yY48G4ydNw9AXnkHF8sXfGvr7+pgte48cR6PIWggOsn/jnrRpNy6PnYyE1VtRGiq/8QLybsTgwugfkH3xOm79vgjxyzch/L0hhjLhI19B9OwliJm/AtkXruHM8LFQ5+YjdEi/EutvVkOCk9e1OH1Di+RMYMNRLegUWj/c+o0XCT3X4iE8a1KygN1ntYhP13n16MnJN1+qVZTgViKQbtQJrNK+gQIHzilx+IIKCWlaLN1RgEKVFs1rWX9AJIHmYpQaO04okZimxYZDhYhJ0qBNPYWhTLv6Cmw+WoizN9SIS9EIQcfLXYK6EaV7b9X/qWAsWHILew+l4NrNHHw96SL8/ZzRpkWAzW0++PIMNmxLwI2oXFy9mYNvJ19CUKALalTViQrubjL06hKEqbOu4fjpdFy6lo1vf7mIerW9UaeGdeGB6NLcFWt35+DkpULEJKqFoOPjKUWjms42t+nWwg27j+dh78l83E5WY8G6LCHStGloLgDQZ5k5GsOSX2hbyFm4/RCeadUAfVrWR5UK5fD5iz3h4iTHqv2nbG5DOkmAt4dh8TcREW4lpuL0jVh89kIPRIZVRFh5f3z+Qg/kF6qw8eg5lMSiDTvRp0NLPNWuOSKCg4SgozsPH7Jvj9l52NjuHm6u+P2TYejSoiHCKgaibtUwjB7cDxduxCA+Oc2uLZvW/Im2XfqiTaenEBwagcFvfQonZxfs2bbaavk33v8GHXs8h0rhNVAhJByvDP+fEG/On9adhxNuR+Ha5TMY9OYYhFergwrBYeL/woICHNpjfg9gjT+37MMzbZrg6daNUaVioBB0XJwUWLX3mJ2tJAjw9jQs/t7mgs+vK7eidd3qGNm/O2pWqojQQH+0b1DLpjCkZ/XK5ejavSc6d+2OSpUqY/iIkeK6sHWz9f2oW68BWj7RGqGVKqNChYp4qs8zCAuPwPlzZw1lLl44j46duoqy5I3TvUcvhEdUwZVLF0tsm53rF6Blx2fRvH1fBIVUEYKOk5MLDu0093bUM2jED2jd9QUEh9VE+eAIPP/GOGi1Glw5a369T09NwIp532Hg2z9AavKyxB67N8xD8w790bTdMygfUhXPvDoWCmcXHN5l7h2lZ8DbP+GJLi8iOKwWAitGoP/rX0Gr0eDKOZ0trm6eeGPMbNRv0QOBFcNRuVp99H35c8TcOIe05Nt2bfl31V/o0O0ptO/cCyGVwjF0+GjRT7u2mHvV6aldtxGatmyP4NAwlK8Qgh5PPY9KYVVw6bzufODm7oFPv5qCFm06o2JIZVSrGYkhb36AG1cvIjkxvsS2WbtyCTp374WOXXoitFIY3hzxAZxdXLBts/FZwJTIeg3R/Im2CKkUhqAKwej19LOoHB6Bi+eNHqqLF8xCoybNMfjVYYioUl2Ua9qilVVhyFHvJRjGGizkPERIwGnZsiVef/11EU5FS2hoaLFyJNpMmTIFf//9t3h4J5Ggb9++QtCgZeHChZg+fTqWLVtm2GbEiBE4cOCA2Ob06dPo37+/eBgvSXghsYHCvLy8vAw2kdCiFzOOHj0qxBiqm242evbsCaXSviu46X788MMPmDVrFs6dOydEkJLsfPvtt4Vosnv3bpw5c0Zs7+Ghu1mIjY0Vv9+0aVOcOnUKf/zxB2bPno2vv/4ad8vhw7qbp61bt4p9X7HC+kV09OjRWL58uRDTjh8/jqpVq6Jbt25ITTV/+/3ZZ59hwoQJot3oTcWrr75612OF6vn5559FO9FvPfXUU4Z2yszMFIJX3bp1hT1fffUVPv74Y9wr1LcU/tTQJMyMvKho/cJF2zdKi//6Swhk3buZu7LeC2pVIZJjzyGkmvEtm0QqRXDVlkiIsi5WJdw6ieCq5m/lQqq3MpTXqHReJXKFs1mdMrkT4m/au9EFlCqVCH8yFVyobWj9zJUbNrfLyy9A73fH4skRX+CDCTNwLcYkJuVukckgrxiGwqsmDz1aLQqvnRdiTGlwbdIWBacPGj1t9DegKpPjW6uFVqWEIqy63TFz+eo1NKpfz6xdGjWoh/OXLtvcbuHfS4VnTc+unUu0lX5j/cYtcHd3Q5Uw+yFwSqUKl6/dRJN6dczsaVKvNs5d0rmlW2Pe0lXw8fZCr87WhTBTyMV6/7FT4ubufuPTogGStx8w+yxpy174ttAdkxKFAt6N6iB5235jAa0Wydv3w6dFQ7t1k0NkBV/gZoL5Q/uNBC2CA6wLOcH+kmLlr8fZLu/uDFStCCEW2UMmBUICpbgcbXwhQVtciVGjcpD1UK2wIJlZeeJSFJXX3cr4e0ng5W5eZ34hcCtBI7x5SqJieRcE+DnjyEnjw3tOrhrnL2cisqbtt6+WuLvr7M/M0h1LJOhQONXRU8Z6o2LyEJ+Yjzo26i3nI4WPpwznrxuPx7wCrfCyqRJqFK4s27RyRTnOXy80a1NarxJivk2Lui745aMAjB/mh36d3OFk4/lTqVLjQlQcWtTQvfQgpFIJWtQMx+kbMTbbILegEN0/n4qun07Be9OW4OrtJLM6CVOPDqqTwq9OXLNdp/E8HIPmdaqbn4frVMPpq7ZF3rz8QvR6bzyefHccRk2cXeJ5ODsvT4jwJPLYQqVU4ta1i6hdv5mZLbXrNcO1S6ULcywozIdarYK7h24cqIquUeStY1oneYRcuXCyxLa5cOs2mteuYrZt81pVcPp6tM3t8goK0WP0T+j+0Y8Y+eufuBabYPZSae/pS6hUPgDDJ81Dx/e/w6BvpmHHifP2bVEqcfXqZTRo0MjMlvoNGuHiRfvbEnS/eerkccTGxKBOpPHaUrNWbRw+tB8pycmiDHnn3I6NQYNGTezWp1IpEXPjPKpHtjCzp1pkC9y6YluQNIU8TTQqFdw8vM3aZ9FvY9Ch1xBUCC3dtZf6OPbGefHb5ra0xK0rJ0ttC40bN3fb3ql5eVliDLu6edkdwzeuXkJk/aZmtkQ2aIorl4wCmi2oD86eOoK42CjUqmP7+pObmy1scfOwLVzrx821q5dRr0FjM3to/fLFkkVeMSZOHsPtmGjULho31EfHjhxAxeBQjP/fh3hlwNP45P23cOjAnsf6XoL5b8ChVQ85XIfc+MhbQx9OddHKwzGdyEik0OcQIY8cEm8SEhKEqEEeLh06dMCOHTvw/PPPC0+XuXPnir8VK1YU25AYQyIQff7tt9/atInsIbvoBGsa4kWCAQk4+/btE2IPsWjRIiE8kecHCTAlQfvx+++/o379+mK9NHbSd/369RMCBREREWGoj+qi3//111+FvTVr1sTt27eFgPHFF1/cVdhWuXI6tdzf399miFtOTo7oD/LiIa8kgkKPtmzZIoSkjz76yFD2m2++Qbt2upM3eQs9+eSTyM/PF14zdwIJOLRfL7zwglgnQYv6m0S33377DYsXLxZtQHZQ3TQmSOgikdAWJJDRYvkZvXnRQwIRXfR8fM1DqEikiY62fiN49tw5bNq0Gb/9OhX3k/zcNGg16mIhVK6eAUhPsi6c5GUnw9WzeHnKr0P4BEbAw6ciDm+YiDbPjIPcyVWEa+VkxCM30/igYY30rByoNZpirvu0fvO29RwylSsE4n9vDEDVShXFgwHl1hk6dhL++XEMyvvbfxNkD6mbJyQyGTTZmWafa7IyIC9XocTt5SERkAeFInP5bMNn6qQ4qNOS4d6tP7JWzoVWWQC3Vt0h8/GH1NN2SF1GZpYYM74WY4ZCqqJjYq1uc+bcBWzYsg0zfplg184Dh4/i658miXHq5+uLH8ePhbeFR1Mxe7KydP1k4fbs5+ONW7HWH95OXbiEdVt3Ye7E0onCG3bshZurC9q1sP/wcDc4lw9AQYJuvOqhdYW3J6QuzlD4ekMql6MgMcWiTArcaxjPl9Zwc9I9MJPXjCm07m+jWSmPTrHyBbrPrVE3XIJCJUoMq3J3lYgwpCyLECoK/wn0sX4upzw6puFBuvIaeLnJDd8T2RZlsnM1hu/s4eere3i2zFuTll5o+K4kyPPj3der4vT5DOGhQ/j7OqFQqUF2jrkIlZpeCH8f6/V6eejagLxlTKF1b3db7SMVbWptmwoBxtu9Q2fykZyhQXqWGqHl5Xi2sweC/GX4bYn5+UTse3Yu1Bot/L3MQ6gopOpGgvkY1EMeNuMG9kK14EBk5xVg/taDePnn+VjxvzdQ3tcLYUH+qODnhSmrd+B/A3rA1clJeP0kpGchKSMbd30ejku0fR5+/QWRSyc7Nw9//rsDr46bgiXff4zyVnK8FBQqMfXvdejWsiE83Gxfu7Oy0qHRqOFlEQrj5eOPuNibKA2UC8fHNwB16jcX60HBYfAvF4Rlf/6Kl4d9BmdnV2xeuwhpKQlITzM/L1jvK00xTxnyhroZb33bykEBGDukL6qHBCErLx8LN+3FkO9nYNm4d1HezxupWTlClJu7YTfe7tMZ7/Xrhn1nL+OD3//CjA9fRRMTgc+UzMyMonsJ8+schVTF2riXIHJysvHKoBfE/SPd07319rto2Mj4UP/msBH4dcokvDL4BchkMkgkUox4731E1rWdN0/Um5km+soyhIrWE2/bfhFjyrrFE+HlWw7VI40eqtvXzIZUJkPb7gNLVYewpWjceHibe/l5eJEt1nPcWfLv3xPg5RsoxB9rKAsL8O9fE9GgZU+4uNn2nMrK1Nni7WseQkUhVbdjbAujuTnZeHvIU1ApCyGVyvDKsA9Rt6FR0DSlsLAAf837HS3bdhEhTfbIEuNGXSz0jjxnYqOj7I6bNwY/C2WRPa8PH4n6DXXiVEZ6GvLz8rBy6WK8OGgoBg15EyeOHcZP3/wP476bjDp1GzyW9xKPFJ616qHBQo4DQkKPaSLY8uXLi5AqvWeK/rPERN1NC3muUJhC9ermb83p4YcEirvhwoULwqOEQp/0UF0U7kXflQYSierVM15cS2MnhS8NGzYMmzdvRufOnYWoo6+Dfpc8mkxj21u1aoXs7GzExMSgUqXSJQK8U65duyZuKui39CgUChHiZdkWpvtLoV8E9dOd2EZiCglUpr9H0Dp5IhEUskW/ZSoQkT32+O677zBu3Dizz9595x2MfO9d3C3kdfXTzxPw3rvvlom8QpQbp8ugKdi97HPMH9ccEqlMePiE1mgrvBruN/Wqh4tFT/1qEej/0TdYsW0/hj336JLakTeOKi7KPDGyRi3y6Hj2G4pyY6dBq1aj8No5FFwq3dvK0pKbm4fvJ07BqBHDShRlGtSLxIxffhZi0frNW/DVDxPw64Tv7ebduWN78vLw9S/TMXr4q/Dxsv+2UM/67bvRtU1LOJcQX/9fhEK0zkVpobadr9hh6NIuEB+9bbwejR5fOi8Ke4x6qxoiKrlj+Mcn7mi7FnWdMbiXcfxNXlyUgOgBsOu4UZmLTVQjPUuD0S/7opxvDpLSSpFIqATqR4SIxbBeJQR9x0/H0r3HMaJ3eyhkMkx841l8+ec6tPlwohCfmtcMR+s6VR7IJAP1qoWJxWBPtXA8O/p7rNi+H8P69zQrS0l2P5k6X9jxyZCSX1jdC+uXzxU5dkZ/NUPkPSHkcgXe/vhnzP11PN4Z1EE8lJLHT91GrR5I29SvUkkspuv9/vcLlu0+IoQbTdFvUijVwK66e5IalSrg1LVoLNt12KaQc7e4urph8q/TxYP3qVMnMGfmNAQFVRChVMS6Natw+eIFfD5Wl6T23NnTmP77VPj5+aNBQ6Pgc7/ZunqWyLHz9v/mGvoq+vo57N74Jz74dqnZfemDZvuamTh54F+89fl8gy2mUOLjP6eOEv54z7wy9oHY4OLqhu9+mY/8/DycO3UUf86egsCgYBF2ZQqlPpjyw+fi/urV4aPxoKBx8/PUWWLcnDl1HPNm/Y7yQRVF2JX+uKFQqt59nxP/h1ephksXzmLTv6ttCjl3Ct9LMI8CFnIcEBIJTKELhLXP6G0HQUIGvZk4duyY+GuKqfjzsHF1dTW7uJXGztdee02EEa1fv16IOSQ+UIjRO++8c1c20O9b3vyUNjTsbjDtJ/2+6/vpUTNmzBiMGkUXdyPkfmoKhdjRW7D0NPMZzCiHk69fcQ8SCkcjT7GxJgKRvr179uqNWTNnoGKRoHWnuLj5CqElL9v8rS9517h5Ws9X4epB3jfFy5NXjp5yIZHoN3IVCvOyoFYr4erhh5W/Pic+t4ePpztkUilSM8wTCdO6v0/pLtpyuQw1KocgJsG+909JaHKzhNAiLXLH1yP19BZeOXZROMG5fgvkbCkeRqi6fRNpU/8HibMrGSuSJvsOHwtljO03lt5enmLMpFmMmbT0DPhZeOkQt+PjEZ+YiM+/+q7YmOnydH/MnzYVFYvyLLm6uCC4YgWx1K5ZHYPfeFt48gzo/4xtezw9df2UnlnMhdnfigAUG5+IuMRkfPLtJMNn+oeXds8OweJff0BwkDGHz6nzlxAVG4dxo97Gg4C8b8grxxRaV2ZkQZNfgMLkNOHe7xxoLtI7l/dHgY237npyC+l8pIW7hZOBuxWvGz3Z+She3ln3uSWhAbrwppUHSj7n5eSR2KOFp6v5AxB5zmRaeNToIW8cS88a8kLRl9d763hY1OHhJhX5YizZezgF5y8fNaw7KXRvEX19FEhJM4Yn+fo44ep1+54ixPtv6hIajxhzCkkpxu2pLqrbw11m5pXj5+OElHRdOcqDcz3GGHolL7o7o1CxjGxje9J6VIL1vHDknURtSmVMsazDkuuxumtioJ+smJDj6+EmhJaUTPOERylZOQiw8NKxBQk3NUPKIzrJuH+1K1XAkk9fF14gFGrl5+mOl36cizqVKtz9ebgEYdjsPBwWjGgLzze9iBOfkoY/xgy3641DeHr6CKElM8P8mpOZngJvH9s5lQia5erfFfPw4bg/xExXpoRVqYVxk/5Cbk6WeBD28vbFV6MHI6xKbbt16vpKitRM87FKM4RZ5r2xhYLaplIFkeBYXyclpY6oaJ7rI6JCOZy4Yttjw8vLu+hewjzHUHp6Gnys3EvooW0qVtTNhhZRpSpioqKwbMlfQsihl34L58/BmM+/RNNmurCk8PAI3Lh2DStXLLUr5Lh7+Yq+yrLoK1r3KqGvdqybi21rZmPYpzNRsbIxtPr6xePIzkzF+HeMs2qRN8nqP38SiZS/mGo9r6B70bjJzjAff9mZKfC08NKxZOf6OSLRMeXDoVm3rIk4C6eOEnlx3vx0rl1vHMLTS2cLzVZlSkZ6Knx8/e32E81WRYRFVEds9E2sXrrATMjRiTifibw4n33za4neODp7aNzIxDgxtycNPhZeQ5b20GxVepEmJvoWVixdJIQcqpOeOSjfjikhoZVxwSSPzuN2L8H8N2Dfp4cMeamYJim+H1CiXqqTPD8od4vpUpoZsazZVKtWLXESPnTImDwwJSVFeIJQGM+DtJPCp9566y2Rr+aDDz4Q4UN6m/S5evRQ6BfNdEBJgW2FTpHYYBoyRl4kpvtO2OsT8o6icvRbpmIQJTu+27awB4kpFHpm+nsEret/jzyjyMPJNFTKNPmyNSiEiuo2XUzDqvRCVLWqVXHylDFOm4QoSqBcq2bxKUOpr6b9/ht+/3WqYWnRvDnq16sn/i8XYP+mxB6UtyYguA5irxrzhVByv9tXD6J8JetvUMpXboDYa+b5RWKv7Lda3snVU4g4lAA5OeYswmp3tGuPQi5HzfBQHDl32axtjpy7hLrVSvdWktx0r0bfFsk27wm1WoguTlVMZgiTSOBUpTaUUbZjtwmXus3E7FX5J01yrFigLcgTIo7MvzzkweEovHDcZlkaM9WrVsGJ02fM2uXEqdOobWWq8EohwZj16yTMmDLBsLRs1gQN6kaK/8sF2L55pJuikoRYhUKO6lXCcOy0MZ5exMifPo86NYrnMKgUXAELJn2LuRO+NiytmzYUyQfp/0ALr8Z123ahRpUwVAt/MB6A6QdPwr+jMXcCEdDpCaQd1B2TWqUSGcfPIaCjiUu9RAL/Di2RftC+FwhpynFpFPpiLobQemyydfEkNkWLsEDz8uFB1svXj5AgLlWLRHNNzyrksROTqEH1UKOoT79SLUQmZrCyxs14NaqHmL8EoO1vxetECpqlisKITMs4K4DK5aW4WVTGlLw8NWLj8g0LhUIlpxagSX3jg6abqwy1q3vh7MXiYUeWIk7blgF477PTYrYrUy5dzYJSqUFjk3pDg11FQuRzRfVSsuHENLVhuZ1EnjJq1I4wvhxwcZIgIkSBa9FKm21667YKtSKczNqU1q/F2D5uKgXpfiMjS231wb5WpQo4dMkYKkRiIK3XC7d+3S1ulwZXbichwEpyXE9XFyHiUALk87fi0L6e7XxcxvNwCA4XOw9fQb2qlUttz9XoOLPzsF7EiUpIEomPSTAqCZohp3KVmrhw+oiZLRfOHEGVGtanqCY2rJyPtUtnYdQXvyK8qu17CDd3TyHiUALkm9cuoGHzdiW2Ta3KFXHownUzew5fvI56EcXzMdpsm9gEkfRYX2ftsGDcshCJbyUk2516nK4LVatWx6lTx81sOX3yBGrWLP19k0arMZzzKScM3ZdKLcI2pDIptBr73krk6UTTh18+e8jMnivnDonEwLbYtmYONq+Yjjc/mYZKVcxf9jRp0xsf/bACH36/zLDQrFUder+Ct8ZMt2OLk5g+/GpRomK9LVfPHkTlara9Q3asnY1tK6fhtdEzEBoRaVPESY6/JYQeEoxKM4bDq9bAudNHzWwhL5tqNey/3DKFkkBTmJWliBN/Owaffj1FiCmlgcZNlarVcebkMYtxcxzVa9a5Q3uUxrFYrSZiY8xDs27fjrY79XhZv5d4pNCLbEdcHkPYI+chQyFSJI7cvHlTeKHcD28NClV66aWXxAxT5L1CgklSUpKYQYnCbyhPS0k2kbcMlad8NhTaVa1aNTz99NMi5wolViaxhHK+0GxT9PmDsnPkyJEiDw2VpVmzKC8MCTjE8OHDRY4Y8s6hpMkkKo0dO1Z4mdjKj9OxY0eRU4dCskisobwzpl4zlICZPIcoTw+JQRSqZBkiRLNnUbgX5cLx8/MTYVI//vijEISGDh2KBwH9Fu0biUg0MxXlECIxhfIUEQMGDBCJld944w3RL5RbiPLqEPfq4vtM3774eeJEMQZqVK+OlatXI78gH1276N46USgVhcK9+soQIXDR+DHF3UN3A2z6eVZWlhDwUoqSQ8cU5U6h2cmoTW1Rr80Q7FzyifCWKRdST+SzUSrzUL2JziNjxz8fw90rEM166KaIjWw1CGunD8bp3XN004+fWo+k2HNo02+8oc7rpzfCxd1X5MpJjb+M/Wu/QeU6nRBSvXWJbTOgZweMm/YnakWEok4Vmn58p0ii2budLgRx7O8LUc7PGyNeeEqsz1yxQcyAElK+nMjNsHDdNjELytMdjA/hGdk54rPkNJ0nza2iPA/+RbOr2CJ3z0Z49X8dqtgbUEZfh1urrpA4OSPv2G7xvWf/N6DJTEPOJvOpR12atEPB+ePQ5hb3MHCObApNThbU6Skih45n75dQcP4YCq/YT3r4bJ/e+GHSVCHo0PTjy1evE1POd+usE8colCrA3w+vvTxQjJnwyuY3Lh7uujGj/zwvPx+LlizHE82awt/PR4RWrV6/EckpqWjXyv4MWsQLvbvjm6kzUbNqOGpVi8CStZuRV1CAJzvqEgp+9ct0lPP3xVsDnxMuzRGVzR9IPdx109Bbfp6Tm4cd+w9jxJABKC00/bh7VeP+uoWHwKt+TRSmZiA/Og41vh4Fl+DyOPWKLln5rRl/o/Lwl1Dzu4/ElOUBHVqI6caPPPWmoY4bk+ei/pwfkH7sLDKOnEbYuy9D7u6K6PnWk7WbcviSFr2bk+ACMf04zWJFOWdpFiuCvsvKBXae0a0fuazFwI4SUe7abS1qV5KIhMk025UplCy3ZqgE206WPvxj50klBnR2RnSiBrcS1GhX3wlOcgkOXdB5nNB3GTlaMd04sfuUEiP6uorZrs7fVKFhdQVCA6VYssMoaO86pUSXJk5IStcgNUs3/XhmjhZnrtue3dCUpWti8fLzlRB9O083/fjAMKSkFmDPQeOD7OSv62H3gWQx5TjxwbCq6Ny2PMZ8cxa5eSr4+eiuMdm5ahQWakTC5HVb4vHO0CrIzFIhN1eFkW9WxZkLGTh3ydyzxJQth/LQq407ElLUSErXTT9OYVDHLxr398NBPmJ9+5E8sb7pYC5e6+OFm7dVuBGrm37cWSHB3pO678v5ykQY1+krhSJ3EOXIeaGbJy7d1M2MZY1BHZvjfwvWoE7lCoisXBF/7jiMvAIl+rTUhRJ/Nm8NAn088V6fDmJ92r97UC8sGJUCfZGVm495Ww8iLjVDzHylZ/PxC8Lbg3LlXIlNxI9Lt6BD/ep4orb9PE/ESz3a48vpi1E7XHceXrxxl0jYqz8PfzFtEQJ9vTHi+V5ifebKTahbtTJCygcgOycPC9bvEOfcPh1aGESc0VPm4dLNGEz64DUhZiQXvYX39nATYoYtuj01ELOmjBVeNOHVIrFl3WIU5Oehdaeia8AvX8DXrxyeHaTzKiYvnFV/TcMbo75BQGAFZBTlvXF2cRPhKsSRfVvg6e0Lv4AgxN66isWzf0ajZu0R2aDkc9/ALq3wxZzlqF25IiLDQ8T049Q2T7fSeat8PnsZAn288G6/rmJ9+trtQuShmaior+Zv2oO4lHT0bWPM2fFytzb4ePo/aFQ9DE1qRGD/uSvYfeoSZn5kfzKHp/v2w+SJP6JqtRqoXr0G1qxeIe4lOnXpLr6f9PP38PMPwMuvvCbWl/6zWJSlsHQSb44ePYyd27di2Nvvie/Jo4Ny4cydMwNOzk660Kozp7Fj2xa8+rpxqntbtH9yMBb/8RlCI+qgctVI7NrwJwoL8tC8nW6G0kW/jxFCTK8X3xfr5IWzYemvGDTiR/iVC0ZmurGvaCGhxFIsoVmrvLwDxMxR9mjbYwj+mT4GIeGRCK1SF3s2LhC2NG3XV3z/1x+fCFt6vqDzoiYvnE3LporZq3zLVURmepKJLe5CxFnwy0jE3ryAVz/8XXgG6ctQcmYSj2zRs8+LmDbpK0RUrYkqNP346r9Fbsd2nXXHz+8Tx8HPvxxeeHm4WF+9dD4iqtZCYIVgIZacPLofe3dsxKvDRhtEnF++/1RMQf7RFz+L55z0NJ0nlIeHlxCP7EHhT1Mnfocq1WqiWvWaWLd6mTimOnbR5aicMuEbYc/AIW+I9RVL/kSVajVQPojsKcTxo4ewa/tmvPG20QP96X4vYOIP41A7sr7w0qEcOUcPHcD47yeXmXsJhrEGCzkPGUru+/LLLwvPiry8PPGAfj+gemj2JvJgoaS3AQEBaNGiBXr10p2I7UHJjMkDhhInk9cNCQg0BTnV+d5774k6CgsL0bZtWzFrlmWY1/20k8QWmrmKct6QxwjNaDVpks5NkUQk+n0SOUhwIgGAhJTPP//c5u+RYETTq7dp00Z4udBsUBTapYfyANEMYTTVNyVMpnLWpm3//vvvxcVo0KBBQpSg6b43bdokhIgHAeUKoinhqZ1IAKHxQsmnSVwhqG3Wrl0rBCYSeig5NNlPAs+dJla2pF27tsjIzMDChX8KMY0STn89frxhXxOTkiCR3plYdODgQUycZLxgfvfDD+IvTUk+aOBLNrerUr8n8nJScXTzVORmJcG/Yi30fHWmIbQqO/22mXAVFNYInV78GUc2TcbhjZPgHRCGroN/hV+Q8S1vblYiDqz7XoRsuXmWQ7VGT6NRp2Gl2o+uLRshPTMb05f9i5T0TFSvHIIpnwwzuPSTS75p22Tl5OGbWX+Lsp7ubqgVHorZ40aKqcv17D52FuOn6wQ64rOp88Tf15/pjjeeNc/fYErBmUPI9vCEe+dnREgV5bxJn/sTtEUJkClJsWXeH5pi3Cm8BtJm69rfEqmXDzyeHACpB4VopSP/xD7kbF9VYrt0aNNKjNd5i/4WIVZVIsLx/bjPDaFViUnJdyQwkjszJUr+cttOkTPKy8sTNapVxeTvvxZTkZdEp9YtkJ6ZhVl/rRBu0FXDK2HC/z4SSQqJhOQUkfT3Ttm696Bo0s6tzT1m7OHdOBItty00rNf++VPxN3rBCpweOgbOFcrBNdQ4HvJuxgjRpvaEMQh7ZzDyY+Jx5s3Pkbxlr6FM3NINcCrnh+pj34VzUDlknrqAw71eQ6FFAmRrXIjWws0ZaBspgbuLBAnpwD+7NCKBMeHlZh6OGpsCrD6gQbu6UrSvK0FaNrBsnwZJFhF8JPBQi56PKr2Qc/KqCh6uEnRv5iSmCI9N0mD62jxkFyVA9vWUijeresirZuHmfPRs4YwnW+rEmjn/5iM+1Vhm+3GlEIOe6+AMV2cJbsSpRZ1FEyWVyKLl0XBxkWH0iOrwcJfjzPkMfDD2jJiuW09wkCt8vIzXwb49daEgv35n/jb9m8kXxbTkxNRZV6HVVsE3Y2qLGawOH0/FhD/szyq5YV+uEGFe7u0JNxcprkQpMfHPdLN9oXAoCi/Tc+RcATzdstGnvTu8PaSIjldh0qJ0IWYRKrUWtcOd0KW5G5ydJEjNUOPYhXys3W30VLWke5PaSMvOwe/rdiE5Mwc1Qsrj9xEvGKYUj0/LMDueSBAYv3i9KOvl5oLaoUGY/+HLYupyPZTU+OdlW0SIVjlvD/RqXhdv9miD0tC1RUOkZWZj2vKNSMmg83Awpo5+0zClOIk0UpPzTWZOLr6etUSU9XJ3Q82wEMwe+66YupxITMvA7uM6sXrAZ7oXInqmffo2mtS2PRtRs9ZdkZWZhlV/T0NGWgpCw6vj/S+mwpvOvxSGkRRvZsuOjcvEDEq//2ieL+Sp599Anxd0Yi0lNf577iQRskWJkFu2fxJP9bc9kYEp3ZrVFX31x+ptIqSqRmgF/DbyZUNoVXxKupk9WTn5GD9/lSjr5eYqPHrmjXlDTF2up2Oj2vhs0FOY8+9u/PjXepEg+adhL6KhSd4ha7Rp10HcSyxeOK/oXqIKvhz/neFeIikpUcwaqacgPx/Tfp+ClOQkODk5IyQ0FKM+/ETUo+ejjz/HgnmzMeGn75CdlSXEnIGDX0WPnr1LbJuGLXsgOzMNG5f9KkSZ4Mo1haeNZ1FoVVpynEierGffln+EQDJv8vvmbdxvGLo/e2/hMA1a9kBOVqoQZ7IyklGxck289vF0Q2hVeoq5LQe2/q3zuPllpFk9XZ4Zjq79RiAjLRHnj+8Qn0361Dz0+K3P5qFKbds5FFu26YzMjDQsWzRLCC6VI6rhk3GTDAmQU5ISzLygqJ/m/PETUlMSRT/RFOPDP/hS1EOkpSTh2CHdjFBj3h1s9luff/tbsTw6lrRq2xEZGen4+885SE9LRXhEVXw+/idDaFUyjRsTe0h0mvH7JKQWjZvgkEp478PPRT16aHpyEnYo3GrO9CmoGFwJH306HrXq1Csz9xIMYw2J9kFkT2MY5qFD3jokWtEDNXkZlYYb1+yH4TxsVpwxJvl+1Lweaj2+/VGRv8wo9jxqCl95cEkL7wZnpXn+jkfJ4QbmN66PklN/ljzN78MkKUnnFeIIHNlkFPQdgepNdJ6njsDvrTfCkVB63X2I7v3mtLvjTBPcMGUDHInoio7zUHoto+S0Ag8TlcZxMlkEez24ROp3g7PUGJL1qClfYDvv08OmXB3jZDNljfx1f8ARcelVupe2ZQn2yGGYMsqCBQuEtwx5KtFsVhQ29txzz5VaxGEYhmEYhmEYhmHKHo4jETMPDMo5Q/l4rC3ffvutw9T5OFOnTh2b7aXPe3OnxMfHY+DAgSKH0Pvvv4/+/ftjxowZ9912hmEYhmEYhmEYxnFgj5z/ALNmzRL5eKxhL9Hsw67zcYZy+9iabad8edtZ8+0xevRosTAMwzAMwzAMwzxyHtMZohwRFnL+A1DoTVmo83GmcuXSTYvKMAzDMAzDMAzDMPbg0CqGYRiGYRiGYRiGYZgyAnvkMAzDMAzDMAzDMAxzb5hMD888WLilGYZhGIZhGIZhGIZhyggs5DAMwzAMwzAMwzAMw5QRWMhhGIZhGIZhGIZhGObekEodc7kLfvvtN4SFhcHFxQXNmzfH4cOH7ZZPT0/H22+/jQoVKsDZ2RnVq1cXMxc/KDhHDsMwDMMwDMMwDMMwDIB//vkHo0aNwrRp04SIM3nyZHTr1g2XLl1CYGBgsfKFhYXo0qWL+G7ZsmVihudbt27Bx8fngdnIQg7DMAzDMAzDMAzDMAyAiRMn4vXXX8crr7wi1knQWb9+PebMmYNPPvmkWHn6PDU1Ffv374dCoRCfkTfPg4RDqxiGYRiGYRiGYRiGuTckEodcCgoKkJmZabbQZ9Yg75pjx46hc+fOhs+kUqlYP3DggNVt1qxZg5YtW4rQqvLlyyMyMhLffvst1Gr1A2tq9shhmP8w07YFw7HIh6PwdXxbOBKutTrCUSjY9eAuSneDSqWBo+D353k4CvUH1oYjsWXiMTgKTbo2hiORlZ4HR+G72BfhSBRcd5zzjUathaOwRtoLjoT8iuO8G5bJHKefCJVKBUdBpXSFIyGROo49Ekl9OArf13nUFjx+fPfddxg3bpzZZ2PHjsWXX35ZrGxycrIQYEiQMYXWL168aLX+69evY/v27XjppZdEXpyrV69i+PDhUCqV4nceBCzkMAzDMAzDMAzDMAzzWDJmzBiR88YUSkh8v9BoNCI/zowZMyCTydC4cWPExsbip59+YiGHYRiGYRiGYRiGYRgHReI43nmWok1phZuAgAAhxiQkJJh9TutBQUFWt6GZqig3Dm2np1atWoiPjxehWk5OTrjfOGZLMwzDMAzDMAzDMAzDPEScnJyER822bdvMPG5onfLgWKNVq1YinIrK6bl8+bIQeB6EiEOwkMMwDMMwDMMwDMMwDAOIMKyZM2di/vz5uHDhAoYNG4acnBzDLFaDBw8W4Vp66Huateq9994TAg7NcEXJjin58YOCQ6sYhmEYhmEYhmEYhrk3aJaox4Dnn38eSUlJ+OKLL0R4VIMGDbBx40ZDAuSoqCgxk5We0NBQbNq0Ce+//z7q1auH4OBgIep8/PHHD8xGFnIYhmEYhmEYhmEYhmGKGDFihFissXPnzmKfUdjVwYMH8bDg0CqGYRiGYRiGYRiGYZgyAnvkMAzDMAzDMAzDMAxzb5iEGzEPFm5phmEYhmEYhmEYhmGYMgILOQzDMAzDMAzDMAzDMGUEDq1iGIZhGIZhGIZhGOae0D4ms1aVBdgjh2HukCFDhqBPnz6lKtu+fXuMHDnygdvEMAzDMAzDMAzD/DdgjxyGYYrRsrYMbevL4ekqQVyqFqv3FSImSWuzfN1wKbo2VcDXQ4LkTC02HFLiUrRGfCeVAN2aylGjkgz+nhLkFwJXYtXYcFiJrNyyZYuwp44M7RoU2ZOisyc60Y49EVJ0I3s8JUjO0NlzMarIHqnOnppkj1eRPTFqUSazFPY0qyHFE3Wk8HAFElK1+PewBrEptm2pXVmCjg1k8PEAUjOBLcfVuBJrLN/nCRkaVjXX96/EavDnNnWJtrSoLUO7enJhC/XTmv3KEvupSxO56KcU6qfDKkM/EZ0byVGvihQ+7hKoNUBMsgabj6gQbadOU56oI0d76ic36icNVu5VIjrRWL8l9SJk6N7M2E/rDxYa+omIDJehZR05QspJ4e4iwcQlebhtp61NaVxVguY1JfBwARLSgc3HNYhLtV2+ZgjQrq4U3u5Aahaw47QG1+KM33/6vMzqdttOanDokm2b/Fo3QcQHQ+HdKBIuFQNxtN9wJKzZZtd2v7bNUPvnT+BRuxryo+Nw9bs/ELNgpVmZysMGIGLUUDgHlUPm6Ys4N/IrZBw5g9LSo7kTWtSRw9VZghtxaizdUSD6wB6t6yrQsZFC9O/tZA2W7y5AVIKxv+Qy4OnWTmhUTSH+vxilxtKdBcjO05Ype55u54a2DV3g5iLF1WglFm7IRmKq/eOxQxMXdG/pBm8PKaITVFi8MRs3bqsM3380yBs1w5zMttl5LA8L/80uE+caRzvfONI1wdGumc1rSdEmUtdP8WlarDugQkyybVsiw6To3IjGja6fNh1V43KMsZ86NpShXjidG3X9RGNwyzGV3f2zHMetImWGcbz+sBqxduypQ+O4obxoHGux+Zj5OO7bisaxrNg4XrjVeLzZogW1Td2itknVYm0p2qZLY2PbbDxi3jadqG0iTNommewtXdvczzEsbA2XokVtOYKLrpeTluaLekuLI43h+3muIVu60vEdKoVfkS1Xb2vu6B6UYUxhjxyGeQwpLCy8623pgbZXSwW2HVNhyooC8RA8tKcz3F2sl69cXooXOznhyEW1KH/+phqDuzqhvK/OtdJJDgQHSLH9uAq/rCjAwi0FKOcjxZBuzmXKFqJ+FRl6P6HA1qMq/LK8yJ4n7dszoLPOnl+WFeAc2dPNwp5yUmwje5YVYMGmInu6l2xPnTAJujWRYucpNaavUyE+DRjUWWbTltByEjzbRoYTVzWYtk6Fi9EavNBehkAfFLsJ/WmJ0rAs21PygxXdPPZqIcfW4ypMXVmoa5ceTjZtqRQowQsdFTh6SY0pKwtx7qYGg7ooDO1CJGVosGafCpOXF+KPtYVIz9JiaE/bdVr201OtFNhyVInJy/KF4PJ6L2dxI2arn17q4oTDF1XihvPsDbXogyA/oz1OCuBmnFoIPHdCrVAJOjWQYO85LeZs1iAxXYsX2knhZqOLg/2BPi2lOHldi9mbNLgcq8WzraQo520s88tqtdmy7rAGWq0Wl2Ls3yjL3N2QefoSzr47rlS2u4aFoOma6UjZeQh7mzyNG1Pno+70rxHQpbWhTIX+PVDrpzG48vVv2NusL7JOX0Tz9bPhVM6vVL/RqZECbesrhFgyaUkeCpXAW0+7CrHDFg2rydGnjRM2Hi7Ez3/nIjZZg7eecoWHq7G/+rZxRmS4HPM25mPqijzxcPNqT5cyZU+PJ1zRuZmrEFi+mZOGAqUWowZ427WlaW1nPN/FA2t252DczDQh5Lw/wFsITKbsOp6H9ycmG5alW3PKxLnG0c43jnRNcLRrJj3Q9mwmx/aTKvy2RinEiiHdFHb76bn2chy9rMFvq5W4EKXBS53kCPQx9hOJBmsPqjBlVSFmrFeKfnqlmwJupbgukBDSvalMjONpa5VCWBrcWW5/HLeV4/gVNf5YS/Zo8WIHc3uIKzEa/PhPoWFZultVurZpLse2EyqxryQQvNLdfts830HXNr+uUuL8LQ0GdpabjWFqmzUHVPhlZSGmr1MiLVuLV+3U+aDGMOEkl+BmvAYbDipxpzjSGL7f5xoF2eIvEf1O3y/cWogAbwle7mourJd5JFLHXB5DHs+9YhyegoICvPvuuwgMDISLiwtat26NI0eOiO927twJiUSC9evXo169euL7Fi1a4OzZs2Z17N27F23atIGrqytCQ0NFfTk5xpvRsLAwfPvtt3j11Vfh6emJSpUqYcaMGWZ1REdH47nnnoOPjw/8/Pzw9NNP4+bNm4bv1Wo1Ro0aJb739/fH6NGjxQPTnaDRaMR2VH9QUBC+/PJLs++joqLE73p4eMDLy0vYk5CQYDeUi8K1KGxLD/0/YsQI8XlAQAC6deuGu6VNPTkOX1Tj6GW1eOhcuUcJpQpoWsO6Ax+93bocrcHu0ypRfvNRFW4na4VHBJGvBGb9W4jT19XiRiMqUfd2hTwb6O1nWbFFb8+hC2pxkU5M02LF7iJ7alq3p3VdnT27ThXZc0Ql3pK1iiyypxCYta4Qp6+pkVRkz6q9hQgJlIq3bvZ4opYUx65ocPKaFkkZwLqDaijVKPaW2/Tt39XbWuw7p0FyBrD9JHmFaMUbSlNUaiA737iQjSXRuq6un44V9dOqvSoUqoAmNaw/cdL+05vE3afVSErXvVGlfqK3gnpOXdOIN1WpWVrR1usOquDiJEGQX8mXrXb15Th0XoUjl9RISNNi+a5CKJVam/1E/XopSoOdJ3X9tOmIUjyM6/uJOH5ZLeykm/Y7oVkNiRBlTt/QIjkT2HBUC5UKqB9uvX+bVpfgWjyEZ01KFrD7rBbx6TqvHj05+eZLtYoS3EoE0m0/iwuSNu3G5bGTkbB6a6lsr/zGC8i7EYMLo39A9sXruPX7IsQv34Tw94YYyoSPfAXRs5cgZv4KZF+4hjPDx0Kdm4/QIf1K9RttGyiw+UihEM/oJnnRlnwhctSNsO0w3L6BAgfOKXH4gkr0L4kuhSotmtfWbePiBPH/qj0FwpshJkmDxdvyEVFRJm76y4o9JOKs25OLk5cLEZOoxuzVWfDxlKJRTdsPIF1buGL3iXzsO1WAuGQ1Fq7PRqFSi9YNzJ886LPMHOOSX6gtE+caRzvfONI1wdGumVT30UsaHL+iEe2+ep9K2NK4usymFwadX/ee1e371uNqIcLT53pOX9fg2m0t0rIg7P33cFE/mYgItniitm4ck8BI43jtAd04bmRvHMeajmO1GMfNa1qMY81dXDMjZThS1DaJRW1TaKdtnqija5s9Z8zbpkUtkzFs2TaHStc293sMEyR+baXrZeydXS8dbQzf73NNgRKYvUGJM9dpTGmF19OafUphC3ngMsydwkIO80ggYWP58uWYP38+jh8/jqpVqwrxITXVGG/w0UcfYcKECULgKVeuHHr37g2lUqfuX7t2Dd27d0e/fv1w+vRp/PPPP0LYITHDFNq+SZMmOHHiBIYPH45hw4bh0qVL4juqi36TRJ49e/Zg3759QkyhevUeLbT9vHnzMGfOHFE/2bdypXlYQUnQPrq7u+PQoUP48ccfMX78eGzZssUg8pCIQ/Xu2rVLfH79+nU8//zzd9ym9DtOTk5iP6ZNm4a7QSalNxcS8bChh27vr8aqUcnGAwc9iND3plyOsV2eoJsLjVaLPDsPD45ki8GechJctbCH7LP1MEa/a2q/sCe6lPYU2G+bCv4SXI8zlqH/aJ3eIlojpJx5eYJu+kLLmdsSFiTBR/3leOdpOXo1l8K1hJdW+n66anLDpusnDSoH2usn8xs8uvmxVZ5+o1lNmWgTergu0Z5yUjOXc9FPZI+dcUOu1qaQK3Tl8nZcH0oBhUlU8AVuJpi3+40ErWgza9DbOsvy1G+2yrs7A1UrQohF9xufFg2QvP2A2WdJW/bCt0UD8b9EoYB3ozpI3rbfWECrRfL2/fBp0bDE+il0xNtdKo4JPfQQdCtBg7Ag22OBHmpNt6E9p/WwIF1/hQbKIJdJzMrQA0pqpgZhFWRlwp4AHyl8PGU4f8P4VEjj/3qsElWC5TZtqVxBjgsm25At528oUSVEYVa2RaQLJn/gj/Fv+uKZju7irbWjn2sc7XzjSNcER7tmki0V/SVCHDOz5bYGlWyMm0qBUjFOTKF+Cw2U2PyNpjV0/UTePvbQj+NrFvbQOj1EW4PG6/U48/4nYcdy3NM4Hv2cAu/2UaBXC1mprpkVaQxbsYU8Omy1DYmjppCwU6kUbUPi06Mew6XF0cbwgz7XmNpSWiGbYUzhHDnMQ4e8Zv744w8hkPTo0UN8NnPmTCFizJ49G02bNhWfjR07Fl26dDGIFCEhIUJEIY+V7777Di+99JIhkXC1atUwZcoUtGvXTtRNXjxEz549hYBDfPzxx5g0aRJ27NiBGjVqCPGHhJRZs2YJDyBi7ty5wvuGvIK6du2KyZMnY8yYMXjmmWfE9ySQbNq06Y72l7yKaF/0dv7666/Ytm2b2Df6e+bMGdy4cUN4FRELFixAnTp1hIClb4vSQHWTUHQvkHuyTCpBdp7551l5WuGKag0KH8iyUp5im61BYQE9milw6qpavJ0oC7YQ7kX2WNZPOS4CbdhD4QzZVspbhjmY2tOzRSnaxtl621DdAV7W66b8LJb5OOjtoWm4Ed1YXoiCcMmm+G2KuR/YSYJZG9T0fF5CP1nUbbefrNiSpzULRSFqVpLixY4K4Y5M8eOz/y1EbgHsQvH41uzJyrXfT/S9mT25tvuptLg5kZgjEV4zptC6vxds9lOx8gW6z61RN1wiwn9KCqu6G5zLB6AgIdnsM1pXeHtC6uIMha83pHI5ChJTLMqkwL1GRIn169vXsu2zcjXwsvGm1N1V17/Ft9GivK/UUK9KTTfpxc8FXnb61JHsofw2BHnLmJKZo4FX0XfF7ZcKWzKzNcW2qRBgFHIOnS1ASkYu0rM1CAmU49lO7gjyl+H3pZkOfa5xtPONI10THO2aaRw3d9hP+cXLW9pSI1SK59vLRT9l5wJzNylLvC7o7bF2LjYNWy1uj/lnZJ+Hq9F+ypdzPkolvGD8PHW5lgZ1lmDmv6q7u2Z638EYzi8+bqhtXuggN4zhORuVj3wM3wkONYYf4LnG1JbuzeTCI7Ck47tM8ZiGMTkiLOQwDx3ypiFvmFatWhk+UygUaNasGS5cuGAQL1q2bGn4nsKSSHyh74lTp04JT5xFixYZylDIEwkzJIrUqlXLIKLoIbGGQpsSExMNdVy9elV45JiSn58vbMzIyEBcXByaN29u+E4ulwsPnzsJrzK1gahQoYLBBtofEnD0Ig5Ru3ZtISaZtkVpaNy4cYnhbLSYolJqIFeULvb+fkCJ3l7q7ATSzSj57KPEkWwR9kiBgV2cQJd7cm1+FJy9aRzX5EackKbCyGcUCCuvwY34+y8UlAS9oZyyolDcUNEb8gGdFfhtVWGxm/H/MhSidS5KK5JbOjqNq8vxXAfj+WbGWou77/+wPc0jnTH4SeO16Je/Mh7Yb1HolZ7YRDUysjX4aJAPyvlKkZSm+U+eaxzxfOMI1wRHvGaSl8yvqwqFaE8hLi90UGDa2kfTT2dvGo+XxHQgIU2J9/s5Iby8BNcfwTimtqFcLtQ25JFDwuQfa/ia6WhjWG/LgE4KYcsqB7gHZcomLOQwZZLs7Gy8+eabIi+OJZQLx1QgMoXEHBJ79HWQ+GEqBumhUK77hT0bSoNUKi0mHOlDzEyh8C17kBfTuHHmSU6f6PUpWvf+3LCemw+oNfT2wHxberNh+cbZ/I2ZlfIWbyX0F1CK85+5rqDEtw+OZAuRU2SPZf0eduyhzz1KUV5/w072zFhbirYpsN42VLflG0TzN+L0SKC1eHNu+3fSsmm/tWKmB1sPV8Z+sqibbLHZT3pbLGy36CeKi6dZH1IygehEFT58zkncnFKySluQvUZ7jNDbwkw7/WT5NtHDipfOnZJbSOGT2mKJEWk9x04/FSvvXPzNMBEaoAsHWnngwTx8k/cNeeWYQuvKjCxo8gtQmJwGjUoF50B/izL+KIg39+Qhzt5Q4VaCse8o3Mha35BnSWyS9T7OydP1r2V/mdZB/UZ1uzrBzAuGzgWmv+NI9py6XIhxscbQYrlcVx95AmWYTCbl5S5FdLz1ZKrkOUS2WHrs0DYk1tiCwrWIQF9ZMSHHkc41jna+caRrgqNdM43j5g77yaV4P2VZ6SeazY/yGUUnqfB+P4XILUN5SUqyx9q52NKbw9we88/IPnszzenHsZ+XbSHH3hi23Fe7Y9ileL9ats2oZxVoUl2GXacf/hi+GxxqDD/Ac43OFt0sWzPXFz5e3jjMQ4V9n5iHTpUqVQy5XEyFCQolIm8UPQcPHjT8n5aWhsuXLxs8bRo1aoTz58+L3DqWC9VdGqiOK1euiITLlnV4e3uLhbxnKLeNHpVKhWPHjt2nloDYH0q4TIse2q/09HRDW5CoRJ5Bppw8efKOf4tCxMjLyHRp0f0jszL6KSurBhvzNtAlqWpFmdlUuqZQ/ogqJuWJasFSs/L6Cyhl55+1vqBEN2hHs8VgT5IVe4Jl4netQb9b1dKeEAt7im7YyR66uSht29BUnhEVjDcM9F94kMTmdLk0XWZEkPkNBm0fnWT7Ac/LDSLe39bNpXk/SS36SYpbNqb7pvai7y3bxVZ5Q70S48O2XXuSNKI+M3uCpTb7iT6vZtFP1ckek4f8u4H02rg0IKy8RU6F8hKbU97SdLphFnkPqF+tla8foZuald4EPwjSD56Ef8cWZp8FdHoCaQd15x+tUomM4+cQ0LGlWSf5d2iJ9IMnitVHN6uU4FG/xKdqkJGjQbVQY9s7K3R5BmjGE2uIqaETqX/Nj8PqoTLcjNf1V3SiWoQymdZLM834eUnFzGOOaA8lG05M0xiW20lqpGepUSvcySyXQkSwAtdiVTZtuRWnQi2TqcXJllrhClyLsf2kUKm87p2eNbHHkc41jna+caRrgqNdM8kWSsZbxaTdyRZaj7IxbqISNahS0by9qby9abBFvRKJ3ZnczMexuT20TsnHrUHj1bS8zh7b4/5OrpmUALdqBSttk1j6tqFjwFb50rbNgxrDd4ujjeEHca7Rizj0EoaSMJf2+C5LaCUSh1weR1jIYR465DlCSYcpmfHGjRuFcPH6668jNzcXQ4cONZSjpMCUQ4Zmq6KZm2g2Jv3sTZTvZv/+/SK5MYkaJMisXr26WLJje1COHaqTkg1TsmMKyaLcOOTlExMTI8q89957+P7777Fq1SpcvHhR5NshkeV+0blzZ9StW1fYQkmfDx8+jMGDB4tcPxTCRXTs2BFHjx4VuXNoPynfjuUMXqXB2dlZzIplulgLq9pzWiXcyhtVo+liJejbRgFyKjp6Wffw8Fx7Bbo3NTrz7TurFnHZberKUc5bgs6N5SLZ7P5zKsNFi25KKQHm39sLxc0xvW2hhZLJ2cORbDHYU0sm3v4Je9oqxLTURy/p6n++g0LEO+vZe0ZnT9t6cpTzkaBLE7lIrLjvbJE9UmBQkT1/bbsze/Zf0KBRNal4mA/wBnq1kIqEpTQjB9G3lQydGxorOXiBbr4kYuaOAC+gfX2pSEZ5+JKuPG3btbEUIQES+LjrHtRoqlV6u2eZZNGSvWdU4s012UP72ae1XLQLzfSg76duZv2kQnXRTzJdPzWSi6SCB87pylN8f7cmcpHk0sdDl3CQpoGlfCKnb5QsrtBsGs1ryYXbPfXTM6KfJDhyUdfuL3R0Qo/mCrN+pX6i2a7I/q5NFGb9RNDNObWXfhpRipGndcs3gZYcvqRFgwgJ6oZJ4O8J9GgiEftHs1gRvZtL0L6u8QbjyGV62NDNdkXl29SRiITJx66a9wH1V81Q3YxYpYWmH/eqX1MshFt4iPjfJbSCWK/x9SjUn/uDofytGX/DLTwUNb/7SOS8qfzWADHd+I1f5hnK3Jg8F6FDn0PwoD7wqBmByN++hNzdFdHzV5TKpt0nlejaxAl1wmWo4C/FwK4uyMjR4sx1Y9sP7+OC1vWM/bXzpBIt6yjErCrUH/07OIvpbmmmMoKSRtL/fVo7iwcC6ssXO7vgRpza5sOJI9qz9XAeerV2Q/3qTggOlOG1Pp5Iz9Lg+EXjnf+HA73RsYnRbWDzwTy0beSCJ+o5o0KADAN7esBZIcG+Uzr3GQqf6tXGDZWD5PD3loq6hz7thUu3dDNjOfq5xtHON450TXC0aybV3aS6VMxuRnU/9YRc9L2+n6iNuzY2PoAfOK8WD700CxE9cHdsKNP103ljP3VpLBPJhmnc0Jh6pjX1E3nXlSwi7D+vQePqUjSoIi0axzJhz/GicfxMaxk6N5LZHMcd6svEbx66aDqOZYZxTOLlgI5ypGbqkiLbg2bmalLD2DZPt9K1zXHTtmlitGX/ObV4uUCzXVH5TkVtc/CCsW266tvGo6ht2uja5kwJbXO/x7D+elnB5HpJ+XZo3dLTxtHH8P0+1whbOivEdOj/7FDe8fHNMJZwaBXzSCBxhMKLBg0ahKysLCFaUBJhX19fszIkpJB40aBBA6xdu9bgbUN5Z2iWp88++0xMQU6hR+TpcyezPbm5uWH37t1CFKJkxmRHcHAwOnXqJEQO4oMPPhDeMC+//LIIcaKpzPv27Su8We4H9LaEBKh33nkHbdu2Fb9Bs2ZNnTrVUIZm1vrf//4nZvqi/D1kA4k9lCT5QUBTNLq7Al2byEV4AL1Vm/NvgcEtntxSTSO96EGEbji7NdVd7OnN9oLNhWIaXoKm7q0TprshGfmsuZ/y9LUFxWaFcFRbiFPX1MIVu2vTInuStZi93sQeT4mJA67OnsXbCtG9mQLdmxfZs8nCnnCdPe/3N7dn2poCXDeZ1cKScze1cHfWoGMDmbgJoFk7Fm5TG0J2aCpLrdYoENBbxGV71OjUQIZODaUifODvnTSlpu57jRbipqt+hFRMl0zu5jSDCE25WlL+FZoS1t1FhS6NFfB0072JnbOh0Ngu7ub9RG8R/95OD8xycRNE7bJwi9LQLlSWbpoGVncS7U0uzvTWdPraQjHbT0lQP3m4KsU40PWTBrPWGfvJ18q4WbS1EN2bK4TAQ/bM21hgNhMKjZsXOhqFz0Fddf9vPqLE5qO2vR0uRGtFos22kRKRtyAhHfhnl0YkMCboYdE0dDI2BVh9QIN2daVC4CFX/WX7dNPlmlK7kkS8HTwfVXohx7txJFpuW2is4+dPxd/oBStweugYOFcoB9ciUYfIuxmDI0+9idoTxiDsncHIj4nHmTc/R/KWvYYycUs3wKmcH6qPfRfOQeWQeeoCDvd6DYUWCZBtse24Uohsz3dwhqszzXakxvQ1eWJqaj0B3lJ4uBgH4YkrKpFkuEdzJxF6RB5YtI2p+/rKPQXQaJ3wSk8X8Ub6YpQay3YWlCl7NuzPE7a8/KQn3FwkuBKlxKTFGWa2lPOVwcPN+ARw5HyBGPN92rmLEKvoBJXYRp80mbatHa5Al2aucHaSIDVDjWMXC8Q052XhXONo5xtHuiY42jWTBATqp06N5ELwJu/BeZuVJuOmeD8t2alC58YyIUpQmNuibboppQ395C1Bo44KkceIPBnoWJv5r9JQpqR8NrSdbhzLdON4q8rCHq35ON6tQqeGciHwkD1/7TDaQ+OYpvZuUEVuMo412HZCVeI41rcNiQ6ibVK0ImmzPlzRsp+obf7ZQWNeJgQesuXPrapiY7hhNYVxDCdrMGN9yW1zv8cwUTtMhuc7GD0DX+qi+3/LUSW2HLXuUeiIY/h+n2vIFmob4r1+5i9SZ6wrLPEelGEskWjvJGsrwzwEyCumQ4cOIpyKkv4yD46PZzzaZKOOjNbBrqeubo6juxcU3FvI0f1GpXKczvLze3jJw0ui/kBjqKojsGXi/QtLfdzISnecc3FIZce67jrS+UajdpxbZkebGEYudxyDZCWE4D5sVCrHGTc0yYUj4UjjWD+DrSPw/es2pqosA+TuXgJHxK3tc3jccKDDh2EYhmEYhmEYhmEYhrEHCzkMc5dERUXBw8PD5kLfMwzDMAzDMAzDMMz9xHF89RmmiPbt2xebbtsRqVixot3Zo+h7hmEYhmEYhmGY/wQOFKL2uMNCDsPcJXK5XExVzjAMwzAMwzAMwzAPCw6tYhiGYRiGYRiGYRiGKSOwRw7DMAzDMAzDMAzDMPeGlP1EHhbc0gzDMAzDMAzDMAzDMGUEFnIYhmEYhmEYhmEYhmHKCBxaxTAMwzAMwzAMwzDMPaHlWaseGuyRwzAMwzAMwzAMwzAMU0ZgIYdhGIZhGIZhGIZhGKaMwKFVDMMwDMMwDMMwDMPcGxL2E3lYcEszDMMwDMMwDMMwDMOUEdgjh2H+w2RnFsCRkModR1uWyRzHFkKdrYGjkJ+rhCOhcHacS1lSUh4chS0Tj8GR6DKqMRyFHVNOwJH4se8VOAqfra8FR0Ktdpxzn1whg6OgUqrhSDjSNdPZxXGuCUR6Sg4cBTdPl0dtgsOi1WjhOHA/MSXjWGc6hmEYhmEYhmEYhmHKHFoOrXpocEszDMMwDMMwDMMwDMOUEVjIYRiGYRiGYRiGYRiGKSNwaBXDMAzDMAzDMAzDMPeGRPKoLfjPwB45DMMwDMMwDMMwDMMwZQQWchiGYRiGYRiGYRiGYcoIHFrFMAzDMAzDMAzDMMw9wbNWPTy4pRmGYRiGYRiGYRiGYcoILOQwDMMwDMMwDMMwDMOUETi0imEYhmEYhmEYhmGYe4NnrXposEcOwzAMwzAMwzAMwzBMGYGFHOaRM2TIEPTp0+eut2/fvj1GjhyJh82MGTMQGhoKqVSKyZMnP/TfnzdvHnx8fB767zIMwzAMwzAMwzCPDg6tYpi7IDMzEyNGjMDEiRPRr18/eHt7P2qT7jtPtnJBq7pOcHWW4PptFf7ekoekdI3dbdo2cELnpi7wcpcgNkmNJdvycCteLb5zc5HgySdcUCtMDl9PKbLztDh9VYm1e/OQX2jflp4tnPFEXYWw5cZtNf7Znl+iLW3qKdCpiTO83CSITdZg2Y483EowbvNEpAJNaioQUk4m6h39RybyCkrXNj2aO6FFHbnOnjg1lu4oQHKG1u42resq0LGRAp5uEtxO1mD57gJEmdgjlwFPt3ZCo2oK8f/FKDWW7iwQ7WSLVpFytG9QVGeKBiv3FCI60Xa71KsiQ49mTvD1lAh71x0oFL+jp26EDC3rUJtI4e4iwYR/8kS9ZXXcOEw/UZ0NjXWuoDrt9FN96qcWzvDzlCApQ4N1+wtx4Zaxn4juzZzQso4cLs4S3KR921nyvjla2/i1boKID4bCu1EkXCoG4mi/4UhYs82uDX5tm6H2z5/Ao3Y15EfH4ep3fyBmwUqzMpWHDUDEqKFwDiqHzNMXcW7kV8g4cqZU7fJEHTqm5GIf4+iY2qu0f0xFyNC9mcJwTK0/SMeUsXxkOB1TcsMxNXEJHVOl66flG7Zh0eoNSE3PQNWwShg19CXUrhZR4nZb9h7C2EnT0KZpQ/zwybvGfev3itXybw96Di/16VEqm3q3dkHr+s5i3FyLVeGvzblITLN/fLdr6IyuzZ3h5S5FTKIa/2zNFWNWz4BubqhVWQ5vDykKlFpcj1Vhxc48JKTar/eptq5o08AFbs4SXI1RYtHGnBJtad/YGd2au4rfik7Q2X8zTmW17LvPe6JuFSf8tiwTJy8rURK9WrmgdT3juW/x5pLPfe0aOqFL0blPtI3JuY8Y0NUVNalt3PVto8bK3WWrbRxpzBA9WjihZaTxfmLpDrqfKOHcV0+Bjo2dDPcTy3fmm537qL7GNeQILScT5+RP/shCXgnXJ6JvRw+0b+wKNxcprkQVYv7aTCSkmp/rLenUzA09WrkX9ZMSf67PwvVY8z6oEqrAs508UCVEAY0GiIpX4acFqVBa706HHMOOZIsjjmOHhmetemhwSzPMXRAVFQWlUoknn3wSFSpUgJubGx4nujRzRvuGzvh7Sy5+WpSFQiUw4ll38XBmi0Y1FHimvSv+PZCP7xdmiYsWbePhpouV9faQiIUuUt/My8LCDbni4Xxgd/tt17mJk7g4/7MtHxP+zhEXu+F93ezbUl2Ovm1dsOFgAX5cnCPEgeF93eHhaozbdVJIcOGmCluOlFK9KaJTIwXa1leIB99JS/JE27z1tKtdexpWk6NPGydsPFyIn//OFTeCbz3lamZP3zbOiAyXY97GfExdkQdvdwle7elis84GVWV4qpUTNh9VYtLSPPFg/UYvF3i4Wi8fFiTFwC7OOHRBhYlL83D2hgqv9HBGkJ9Jm8h1D/XrD5TiDtTBx43j9JMcfVo7YdORQkz4J1cIY29a1GnZT4O6ueDQeSV+/icXZ6+rRf1BfsbLdUf9vu0swOSleSigfXvK/r45YtvI3N2QefoSzr47rlR2u4aFoOma6UjZeQh7mzyNG1Pno+70rxHQpbWhTIX+PVDrpzG48vVv2NusL7JOX0Tz9bPhVM6vxPpJQHuqlQJbjioxeVm+EFxe7+Vs85iqXF6Kl7o44fBFFSYtzcfZG2oM6W5xTCkgbtxJ4LkTtu47hCnz/sarzz2NuT99iaqVQ/H+VxOQmpFpd7u4xGT8Ov8f1K9Vvdh3a2dNNls+fftVSCQStG/RuFQ20QNJh8bOWLwpFz8spONbi3ee87A7bhrXVODZjq5Yty8f387LFMc3bUNCmR56yJz/by7GzcrElCXZ4rP3nve0m2ahewsXdGrigj83ZOPbeRliDI98wcuuLU1qOeG5Tu5CBP5qToawZeQLnma26CFhGaXXRdG1mTM6NHLG4i25+HFRFgoKgXf72z/3Na6hQL/2rli/Px/fLshCTJJabGPeNmos2JCLcXOyMHVpjmiTd/t7lJm2caQxQ3Rq7CReHCzZXoBJ/+QKe97q41biuY/ObZsOFeCnv3JxO0mNYX3czO8n5MDFW2psOVr647xna3d0ae6GeWszMX5GCgoKtfhwsC8Udl6xN4t0wYvdPbF6ZzbGTktGdLxKbOPpLjUTcT4c5Iuz1woxbnoqvpyegq2HcqHVlp0x7Ei2OOI4Zhg9LOQ8JhQUFODdd99FYGAgXFxc0Lp1axw5ckR8t3PnTnGztn79etSrV09836JFC5w9e9asjr1796JNmzZwdXUVIUNUX05OjuH7sLAwfPvtt3j11Vfh6emJSpUqifAiU6Kjo/Hcc8+JkB8/Pz88/fTTuHnzpuF7tVqNUaNGie/9/f0xevRoaEu6uphA9gwePBgeHh5CQJkwYUKxMgsXLkSTJk2EjUFBQRgwYAASExPFd/RbVatWxc8//2y2zcmTJ0UbXb161SDUkO30O15eXmKfEhISDCFNdevWFf9HRESI7X799VexT7R/pvV98sknht947bXXMHDgwFK3N/Xphx9+iODgYLi7u6N58+aiL22RlJQk9rtv375i23uBLqAbD+bj9DWVEAjm/5sj3hjUr6qwuQ15v+w/U4iDZwsRn6IRnhh0A9ky0kl8H5eswaw19GCqQnKGBpejVVi7Nx+REQpI7Vy02jd0EjdQZ67rbFm4SfeAWK+K3K79B84qxcNwfKpGiECFKq3wNtGz80ShuOm6YfK2pjS0baDA5iOF4qGN3tgv2pIv7KkbYdse8po5cE6JwxdUSEjTigdosqd5bd02Lk4Q/6/aU4ArMWrEJGmweFs+IirKxMOiVTvqK3DwvApHLurqXL6rEEqVFs1qKmx6KF2KUmPnSSUS07TYeFiJ2CSN8BbRc+yySjzEXo65szZxxHHjKP1ks85acpv9Sp4sO07o+mnDoULxO9R/etrVV2DzUeO+Ld6aL95A2ts3R2ybpE27cXnsZCSs3loquyu/8QLybsTgwugfkH3xOm79vgjxyzch/L0hhjLhI19B9OwliJm/AtkXruHM8LFQ5+YjdEi/EutvV1+OQ3RMXVIbjymlFk1rWm+XNvXkuBSlwc6TKiSma7HpiFIIXOQpp+f4ZTW2HFPhSsydvWH9e+1mPNW5LXp1bIPw0GCMfnMwnJ2dsG7bHpvbqNUafDl5Ol57vg+Cy5cr9r2/r7fZsufwCTSKrIngoMBS2UTiwIYD+Th1lc4dasxdlwMfDykaVLd9fNND/75TBThwplA3VjflQqkEnqirO76JvacKcTVGhZRMDaIT1FizJx9+XlL4e9u+Re3UzBXr9+Xh1BWdLXPWZsPHU4qGNYz1WtKlmQv2nCzA/tMFiEtW488NOShUAa3qO5uVCw2UoWtzF8xbr3uwKg0dGztjA537rqrEeXVe0bmvQTX75759pwtxoOjc99dm83OfaJvT1DZqpFLbJKqxZm9emWobRxozRLuGCmw+XCCuJ3SN+nNz0bnPzv1E+0ZO2H+O7idUwlOCRCA697UwuZ/YdVKJrUcLzbwtSqJbSzes3Z2NExcLhAfUjBUZ8PGUoVFN2+J39yfcsOtYLvacyBOCEolAJCq0bWRUmwd098SWg7lYv4deYqkQn6LG4XP5UKnLzhh2JFsccRwzjB4eKY8JJIgsX74c8+fPx/Hjx4VY0a1bN6SmphrKfPTRR0L4IIGnXLly6N27t/AqIa5du4bu3buLMKHTp0/jn3/+EUIDhQ+ZQtuTWHDixAkMHz4cw4YNw6VLl8R3VBf9Jgkoe/bswb59+4QQQvUWFhYatichZM6cOaJ+sm/lSnO3eHvQPuzatQurV6/G5s2bhbBB+2sK2fHVV1/h1KlTWLVqlRCSKA8PQeIKCVFz584124bW27ZtK9pNo9EIEYdso9/asmULrl+/jueff16Upb9bt+oePA4fPoy4uDgMGjQIWVlZol0I2i4gIMBMeKHPKJ9Padub/j9w4AD+/vtvUaZ///5imytXrhRrFxLQSBSKjIzEsmXL4OxsfvN1J9AFhC6Yl24ZfXAphIVuUMIrWr/ZkUmB0PIyXDTZhuS5i1EqRNjYhiAX1fxCLTQ2tDx/L4lwgb0UbWFLvBrhFWS2bQk034aqvxSlQpiNbUqL3p7L0WozeyhkizwpbNkTEmi+DdlD62FBMsPNsVwmMStDD/F0s2HNZlFnOal4YDarM0aNyjbsoIdpS4HmEtlg4yH7cRg3DtFPVuqkfqtcVKcl9Fum5QkS4PT9SvvmdYf75ohtczf4tGiA5O0HzD5L2rIXvi0aiP8lCgW8G9VB8rb9xgJaLZK374dPi4Z266Z9DC5Hx4jGvK9iNTaFKPr8SqzlMUXl721/lUoVLl27iSb16hg+o1xsTevVxtnLupcN1pi7dDV8vb3Qu3PbEn+DwrX2Hz+N3p3alMqmgKLjm7wYTcfNjdu2j1Vq00pBMlywOL4v3FQiItj6NuTBRA86SelqpGVaF78CfKTiIerCDWM4SV6BVoRf2KqXbKlcQY4LNwvNbblRiCrBCjPPitf6eGDRphxk5mjvqG1Mz2OibUo491HbFDv33bLdntQ29FCaXEbaxpHGjNm5L8ri3Ef3E0H27ydMtxHnvig69939tbOcr0yINueuFZr3U6wSVUOtiwMyGRBWQWG2Db0HpfWqIbptyDOnaqgTMnM0+Pw1P0wZXQ5jXvVDtUq2BQeHG8MOZIsjjuOygFYiccjlcYRz5DwGkBfHH3/8IQSSHj10ce4zZ84UAsTs2bPRtGlT8dnYsWPRpUsX8T8JPiEhIUJEIW+T7777Di+99JIhaXC1atUwZcoUtGvXTtRNXjxEz549hYBDfPzxx5g0aRJ27NiBGjVqCDGCRJBZs2YJwUQvkJCnCgkaXbt2FUmBx4wZg2eeeUZ8P23aNGzatKlU+5mdnS32588//0SnTp3M9sMUEmr0kMcM7Qe1AW1PwhKJOl988YUQYZo1ayaEn8WLFxu8dLZt24YzZ87gxo0bwlOGWLBgAerUqSNEMKqLvIkIEsTI64do0KCB2E8Suujv+++/j3HjxonfzcjIEN4+1J5ESe1NHkTUduQZVLFiRVGGvHM2btwoPifPKD0kpFG/kicOta++7S0hLx1LTx21qgAyubnoQ2/2icxc8wtJVq7G8J0l5GIsk0qQlWOxTY4GQX7WTzPurhL0aOki3qDYgh5YdfWY3zRm5WoN31mrl2zJzC2+TXm/e3vA0rvEZhWr23bb6O0pvo0W5X2lhnpVam2xmPqsPK2IyS9Wp4v1OikXSWBRndZsz7Zig6fb/RFyHGncOEw/6evMK15noI/tfrJqt5vcbN8s+zI7V2M1DMJa/XobHmXb3A3O5QNQkJBs9hmtK7w9IXVxhsLXG1K5HAWJKRZlUuBew35uGf0xlX2PfUX9Upp+sEd6VhbUGg38fLzMPvfz9sat2Hir25y6cBlrt+3B/AmlC1P7d+c+uLm6oF3zJqUq7+VRdHxbHqt2zsUUHinOxVa2CfKXFcsl0be9K1ycJMKD4Jd/sqG28SxDD+NWbcnRGL6zbYt5f9F6kL+xv57r4o5rMSrhzXLH5z4r9pR07rM8X9J6eYtzH4UC9W1n0jZLc8pE2zjSmCE8i/rC2nlM/53tc19xewLv4X6ChAEiI9ui/7PVhu+K2e8mhUwmQYZF22TkqFGhnM7LI9BXZ1PfDh74e1MWbsUp0bqBKz4e4ofPfk22mX/HkcawI9niiOOYYUxhIecxgLw7SIxo1aqV4TOFQiFEigsXLhiEnJYtWxq+p7AnEl/oe4K8V8jrY9GiRYYyFIZEwgwJGrVq1RKfUWiWHhIMSMTQhy1RHSRWkEeOKfn5+cJGEjPIe4VChPTI5XIhfJQmvIrqIM8e0+31+2HKsWPH8OWXXwp70tLSxD4QJIrUrl1bCCOU24a8gqiN1q5dKwQO8nghqE1IwNGLOARtR4KUaXtaQiIMCTgffPCB8EgisWbJkiUGzyP6XRJsStPe5AFEYVrVq5vnOSA79SISkZeXJzxxKHyspJmzyB4Slkxp0uVjvP3e//BiF2O+kd9XlN6d/G6hMIzhz7gjLkUt4pkN9tSQ44VORhfhaatz8ShpXF2O5zoYha4Za/MeqT2ORNNaCocZN9xPtuG2efzJycvD+Ckz8cmwIfDxMr/+2oJCtLq1aQFneg1shWa1nUQiTj2/LXuwx/ehcwXibTU9GFGurdefdsdPf2aJcJDmdZwwsIeHoezUJfbzBN0t9aspULOyAl/NTi/x3Degq8m5b/mDbZvD5wuFNwDlCqNErq/3dsNPi7OhUjpW2zjSmCEo+fDzHY1hStPXPLpzX8t6LhjS2yjMTlyU9kB+R/8eb8dRXfgVsXhjFmpHOInwq6Vbsx1rDKsdyxZHGscMUxpYyGEE5DXy5ptvijwtllAuHFOByBQSc/RCCdXRuHFjM3FCD3muPCzvJArvooXsoN8lAYfW9eFd+nw1FA5FHkXk4ULhUveasJjCpkgcIpGG2qlmzZriMxJ3SFDSe+OUpr1J5JHJZEKUor+mkFeRHgqh6ty5M9atWyfCziifji3IE4ryE5ky+vc8MQPQzTjjRUOfvM3LTYrMHLXZ2yBK1mYNeout1tBbLXo7YbKNO9VhLtI5K4C3+3mI0JgZq3LEjAp6KA/OzXjjRZNCNXT1mHvY0BtvilO2Rk6RLZZeALSN5duRkqCEwLcS1MXtcbO0R1qiPZZv6U3roLc0VLerE8w8Gjxdi3sWiTrzrddJb6Us3zbqoc89rNhg+aaxtDjSuHHYftLXaZHY2NKu4l5SluWlZjYQHhZ1eLhJcTu5+L45atvcDeR9Q145ptC6MiMLmvwCFCanQaNSwTnQ36KMPwrizT15bB1THvfYV9Qvto7B0uLj6QmZVIrUdPOH8tSMjGJeOkRsfJJIcjz6u18Mn2mKXo606T8Uf039DiEmeXBOnr+MqNvx+OqDYTZtOHW1UIQO6JEX3S3Sw4b58a2bHcYa5J0kzsWWx7eVczGFKuQXasQsMPS7E9/zEfknjl5Q4uSVQly/bRQQFEVjmOolbwRDve662Zbs22LeX7SuP9eQUFHOV4pfPjBPjD3sGU9ciVbh50WZ9s99lm1TNFONVXsM1ynzttGdP7VW2yYpncI5cjDhHW+RK+TgGbVDtY0jjRmC8uDcis8pxbmP7ic0JZz7yB6N+bXzDu4nKA/OtZiUYv1E3jemXjleHjJExVn3eKJrtVqtLeZZ5e0uQ0aWro70or+3E837+naSCn7exntJRxnDRy8qHcoWwlHGcZmGZ616aHBLPwZUqVIFTk5OIieNHvLQoTAg8iTRc/DgQcP/JCxcvnzZ4GnTqFEjnD9/XuSIsVyo7tJAdVD+Fkq4bFkHTc9NCyUoPnTokGEblUolxIrS7icJJKbb6/dDz8WLF5GSkoLvv/9eeKqQmKL3GDKFQsQogTCFMVG4kmk4FrUJ5ZyhRQ+1TXp6ull7WkK/R3lySBzSizZ6IYcWfX6c0rR3w4YNhUcO2W75vT6US583gZI7k4DWoUMH3L5926Z9JPpQ4mbThcKqaMYbmtJRv1BSNrqxqFFZbuYJQXkuTC9uppAbKCVqq1HJuA3dptA6xeab1jOivwdUGmDaypxiyffIFprCV79QomJyI64RamFLkEzES9u0JVGD6qHmttD6nSQitGdPtVCZmcBAuTJuxmts2hOTqEG1EJmFPTKR64egpHsUlmJab6CPRCS9s2azqDNJg2rB5nXSb9yyYQflQDG1AXobTKZQvRPKwrhxiH4SY9FaP1kfi/Rb1a30k75fUzK14kbQtIy9fXPUtrkb0g+ehH/HFmafBXR6AmkHT4r/tUolMo6fQ0DHlmavqP07tET6QV3+MlvQPtLDXLUQqdk+Vg2WimPH5jFlcgwS1UOo/L3tr0IhR40qYTh25rzhM3phcvT0BURWr1qsfOXgClg46SvMmzDOsLRu0kAkMqb/y/ubP3yv27YbNauEoVqY8SWNJTRLjNnxnaw7vmnqXtPjknJWmB6rlm1Ks8SYbkNtWjNMIabZtedVQIv+YVfYkqYxLCRYppMtYcaHHQpLoHwVtuolW27FqVDLZBuqndavFU3dvOFAHsbNysD42caFoCmD563LLvncV8mibUo491HbmJ4vxbmvsu32NG0buQO2jSONGXvnPtPzsbMTRL4yW5MeGO8nrJ37Sn/tpBcQialqw0JJiNOz1MJTxtA2zhJEBCtwNdq6kENzadyMU5ptQ/tM6zTFPKHL96JGUID5e3paT8lQO+YYdiBbHHEcM4w9WMh5DCBBgpIOk0cGiRIkELz++uvIzc3F0KFDDeXGjx8v8r/QbFWUJ4aS8fbp08eQ72b//v0iwS7NuESCDCUUtkx2bA/K+UJ1UqJgCi2iECESMMjrJCYmRpR57733hMhCSYhJdKF8OySQlAbyRKH9of3cvn27YT9IzDD1ZiEhZOrUqSI8ac2aNSLxsSXk5ULbkpcKhTuZhp2RhwvNSkX7Q4mUKZcOzZRF4gyFgdnC19dXhJ6RJ5BetKEEylQHiU2mHjkltTeFVNHv0++uWLFCtCXZQeFRNPuY5b7Qb9avXx8dO3ZEfLz1HAp3wo7jBejewlnM5FAxQIrBPdzFhYwy9uuhaR1pWnA9244WoFU9JzSvo0B5Pyle6OIqHhBpNiLDw/izHnBWSLBoYy5cnSTCa4YWeznIaHapbs2cERkhRwV/mprZFRk5WjEzkp4Rz7iJ2X5M7X8iUoFmtRQih8dznVzE7x48rzR7M0LJTcsVzQ5Q0V8m1t1KyBO9+6QSXZs4oU64TNgzsKuLsIe8ifQM7+OC1iazDNFMUTRjFs1+U95Xgv4dnMVU3zQLhv6NDP3fp7UzqgbLRCLjFzu7CLHK1kPk7lNKMUsQhaMF+krQr52TqPNw0VulFzs5oWcLow17TitRM1QmZuahB+yuTRXid/adMbaJqzO1g9SQ94TqpXVLj5KyMG4cpZ+ozha1dXVSez7bvqjOC7o6B3R2xpMtncz6tWYlmZglivqpWzMnkWyT+k/PrlNKdKF9C9Pt20tdXMRbR9N9s4ejtA1NP+5Vv6ZYCLfwEPG/S2gFsV7j61GoP/cHQ/lbM/6GW3goan73kch5U/mtAWK68Ru/zDOUuTF5LkKHPofgQX3gUTMCkb99Cbm7K6LnryixXXadUonZxJrUkIm2f6atAk4KiZgZjnihoxN6NDc9plSoESoVx1Q5OqaaFB1TZ1UWx5REtBlRzkcq1j1tTGmu54XeXbFm6y78u2Mvbsbcxk8zFiC/oAC9OuqmWqdQqj/+XCr+p/CoKpVCzBZPdze4ubiI/0kY0pOTm4ftB46gd6eSEyJbsu1oPno84YJ6VRXi+B7ypLsQDU5eNo7Nkc97oH0j40l065F8tK7vjBaRTgjyl+LFbm4iqSfNVKdPJNqthQsqlZfB15MeZGUitIBmBTp73XYulm2H8/BkK1cR8hNcToZXe3sIb4QTl4zuYKMGeKFDY2NozZbD+WjTwAUt6zqLPBUv9XAX/bvvtC53HB1DNBOQ6UKkZqrFjHn22H6sAD1bOovZFKltXu6pO/edNMkn895zxc99res5idmPgvykeLGr7txHs+4Y2qa5s7FtKsrw+lO6tjl3o2y0jSONGWLXCaWY2jrS8txncj/x9jOuZrME7jxeiJaRCjStRec+Kfp3dBZtQ7Nimt1PBEhFsmmiQoBMrNu7n9h0IBdPtfNAwxrOCAmU441nvIW4c/yiMWx49BBfdG5m9BbfuD8X7Rq7oVUDF/EbL/fygrOTBHuOG8PG/t2Xgy4t3NCktrPI4/NMRw9UCJBj97G8MjOGHckWRxzHDKOHQ6seE0gcoTd2+tmTSHCgJMIkLpiWISGFRANKzEu5YfTeNiRA0KxKn332mfAsoXwt5AGjn6mpNFBo0u7du4VIQcmMyQ4K9aHExOT9QVD+GMqT8/LLLwsBhjxhKEkv5c8pDT/99JMIS6IZtygXD9Vnui2FUlHS508//VQkDybPF0pi/NRTTxWri0QhShr8yiuvFAsXI1HlnXfeEUIM2UmzRZE4VBIk1pAwoxdyKIcPefHQ1OWmuXxK094U8vX111+LfYyNjRUiGU0b36tXr2K/S7mG/vrrL7E9iTkkoJFn1N2y5XCBuFGhuGWaIeharAq/LTf3hAjwkcHd1fjB8UtKeLrloVcrV0Po02/LcgxhBqHl5YYZB8a9bh4e8L8ZmWJ2G2vQlJ70wPhiJxdhy/Xbavy+MtfCFincXY2C3vHLKni45uPJls46W5I1+H1VrlnIA13we7YwXnRHPucu/v65Oc/sBs2SbceVom2e7+CssydOLWLvzezxlsLDxbg/J66odEl6mzsJd3V680/bmCZWXbmnABqtE17p6SJci2kK6mU7bU8jf/KqGu4uJHIp4OXmJPZx5rp8ZBfdq9HMJVqt0QZ6e/jn1gL0aEb7TTMjaDF3QwHiU402RIZRjiJjmwzqqrvR33SkEJuPKMvUuHGcfqKxKEH3ZiZ1rjXW6etZvJ8Wbs4XY5MEHnojOOfffPE2Wc922je5ROS+oX0jsYTqLGl6WUdrG+/GkWi5baFhvfbPn4q/0QtW4PTQMXCuUA6uRaIOkXczBkeeehO1J4xB2DuDkR8TjzNvfo7kLXsNZeKWboBTOT9UH/sunIPKIfPUBRzu9RoKLRIgW+PUNTU8XJXo1lQhxiJNTzxrXYHhmPL1kIhZYvSQQLVoayG6N1cIgYfe+s/baH5Mkdj2QkfTY0r3Px1Pm4/aPqY6t2qO9IwszPx7lZhhqlp4JUz8fBT8fLzF9wnJKZDexSwcW/YeEvvQpbUx11xp2XyoQAiqL3UjkUgips2dusSYW4Kg8BvT8LRjF3XHd+/WLiLMgEIRaBv98a0kL64QuZg6mOokwYA8EihHhL0QtY0H8+HkJMGgHh5iuyvRSvzyT6a5LT5Ss3DSoxcK4emWi6fbugpbKNTol3+yiiXTvxs268991DZF576py8zPfeV8ZPAwOfcdu6SER9G5j44p0TYm5z6lSouqIXIxFbOhbWIojCm7zLSNI40ZYtuxQvEw/bzJ/cS0Veb3EzQDI53rTM99Hq4F4pxMLxBikjViG9PfalVXgR4m9xPv9deJL4s25+FwkWhvyb97c4QIM+QpL7i5SHElqhA/L0yD0qR4oK8cHu7G88Ths/kiXOiZjp4iLCsqXim2MQ3X2XwgFwq5BAN6eIl2jYpX4cf5qUhMU5eZMexItjjiOHZ0tML/iHkYSLSlyTLLlGnooZ7CbigMiRL2MjrIa4hEJgqhKl++PP6LvP1z6byhHhZSueM4Ccpo/kgHgmarcBTycx3rbZHC2XHeSTjSDJeOdnXvMqoxHIUdU+yHWj1sxrTRhYc5Ap+t14VcOwpqB5rCRa64t5kP7ycq5f0JWXwcr5nOLo5zTSDSU4y5eh41bp5GTyzGHK3GcS6a0z42vogva2Qc3wpHxLtRZzxuONaZjmEeAjTzU1JSkpjZimaq+q+KOAzDMAzDMAzDMEzZw3Hkc+Y/D80uRXlwbC30/f2AQpAqV64scvP8+OOP96VOhmEYhmEYhmGY/zJaidQhl8cR9sj5D0D5WspCBF3FihVFfhl7398PKMkxLQzDMAzDMAzDMAxT1mAhh3EYKGEvTa/NMAzDMAzDMAzDMIx1WMhhGIZhGIZhGIZhGObeeEzDmBwRbmmGYRiGYRiGYRiGYZgyAgs5DMMwDMMwDMMwDMMwZQQOrWIYhmEYhmEYhmEY5p7QSiSP2oT/DOyRwzAMwzAMwzAMwzAMU0ZgIYdhGIZhGIZhGIZhGKaMwKFVDMMwDMMwDMMwDMPcE1qeteqhwS3NMAzDMAzDMAzDMAxTRmAhh2EYhmEYhmEYhmEYpozAoVUM8x8mMTYNjkRIlXJwFGKuJcGRUBYo4ShI5Y71DkAmk8FRiLsaBUehSdfGcCR2TDkBR6HDuw3hSEycfhqOQuz163Ak/Mr7wlG4dOQCHIWqDarDkbh9PQ6OQqUaIXAk5ArHuUbl5RTAkVAp1XAUHOk+C3Cc894dw7NWPTQc626cYRiGYRiGYRiGYRiGsQkLOQzDMAzDMAzDMAzDMGUEDq1iGIZhGIZhGIZhGOae4FmrHh7c0gzDMAzDMAzDMAzDMGUEFnIYhmEYhmEYhmEYhmHKCBxaxTAMwzAMwzAMwzDMPaEFz1r1sGCPHIZhGIZhGIZhGIZhmDICCzkMwzAMwzAMwzAMwzBlBA6tYhiGYRiGYRiGYRjmnuBZqx4e3NIMwzAMwzAMwzAMwzBlBBZyGIZhGIZhGIZhGIZhyggs5DD/aYYMGYI+ffo8ajPuii+//BINGjR41GYwDMMwDMMwDMMAEoljLo8hnCOHYcoAEokEK1eufKii0/PdfdCppSfcXaS4eLMAM5cmIz5ZZbN8rQgXPNXRGxEhTvDzluPH2Qk4cjb3nuttVVeBjg0V8HST4HayBit2FyAqUWOzfP0qMvRo4Qw/TwmSMjRYt78QF26pzcp0b+aElnXkcHGW4GacGkt3FiA5Q1vm2oZ4sZc/urTyhrurFBev52HaX4mIS1LaLF+7qiv6dvFFlVAX+PnI8d30WBw6lWP4XiYFXnoqAI3ruKN8gAK5eRqcupSLBauSkJZh3o7WeKGnH7q09IIb2XMjHzOWJNm3p4oLnu5E9jiLtvl+ZhwOnzHaQzSv545urb1FGU93GUb9EIWbsYVlqp+IoS+FoXfXIHi6y3HmQiZ+/v0KYuLybJYf+Gwo2j0RgMrBbigo1ODMxUz8Me86omON2zgpJBgxtAo6tQmEQiHF4ROpmPDHFaSl225zokdzJ7SoI4erswQ36BjYUfIx0JqOxUbGY3E5HYsJxmNRLgOebu2ERtUU4v+LUbpjKzvPdr1P1JGjfQO5qDMuRYOVe5WItnN814uQoXszBXw9JcLe9QcLcTHKWD4yXCaO7ZByUri7SDBxSR5up5R8bPu1boKID4bCu1EkXCoG4mi/4UhYs83+Nm2bofbPn8CjdjXkR8fh6nd/IGbBSrMylYcNQMSooXAOKofM0xdxbuRXyDhyBqWheS0p2kTK4eEKxKdpse6ACjHJtvclMkyKzo1k8PGQICVTi01H1bgcY2ybjg1lqBcuhbe7BGoNEJuixZZjKsQklf7c91LvAHRt4yvONxeu5eH3xXGIS7Q91upUc8UzXf1RpZIL/H0U+Ob3aBw8lW1W5sVeAWjb1AsBvgqoVFpcjcrHwlWJuHwz364tfTt6oH1jV7i5SHElqhDz12YiIdX+OapTMzf0aOUObw8pohOU+HN9Fq7HmttfJVSBZzt5oEqIAhoNEBWvwk8LUqEs4RB/9cVK6N05CB7uMpy5mIWJ068iJs72PtSv7YUX+oSgRhV3BPg549PvzmPv4VSzMr7eCrw1OAxNG/jAw12OU+cy8cusa3brJfq0d0fbRi6iba5GK7FgfRYSS2ibjk1d0f0JN13bxKuwaEMWbtw27vTol31QM8zJbJsdR/OwcH2W3XoHPh2IbjRm3GS4cDUXv/15G7cTbZ+/61RzQ7/uAaha2VWMma9+vYWDJ23/xtsDK6Jnez/M+DsOq7emoCR6tXJB63pO4tx3/bYKizfnISnd9jmHaNfQCV2ausDLXYKYRDX+2ZaHW/HG9hzQ1RU1K8vh7S5FgVKL67FqrNydh4RU+/U+3c4NbRsa+2nhhuwS+6lDExd0b1nUTwkqLN6YbdZPHw3yLtZPO4/lYeG/5sedNfp2cEe7RkXHVHQhFqzLKvmYaupqOKboWPlzQyZuxJofLHQs9aNjKlgBjVYryv28MM3uMdWvkyc6NHUTtly+VYi5a9KRkGLfls7N3fBkGw94e8gQFa/EgnUZuB6jO74DfGSY/FF5q9tN+SsVh8/aP6b6d/NGp+Ye4tx36UYBZq1ILfG63/UJD/Ru7w0fTxluxRVi7spUXIs2jv3y/nIM7OWLmuHOkMslOHUpT5TJyLY/bhhGD3vkMAxTjKc7eqNHWy/MWJqCMZNvo6BAg8/fCoJCblvRdnaS4FZsIWYvT7lv9TaoKkef1k7YdKQQE/7Jxe0UDd58yhUertbLhwVJMaibCw6dV+Lnf3Jx9roar/Z0QZCf8VRHD6Jt6yvEA+bkpXkoUAJvPeUqHjzLUtsQJMj0au+DaX8lYPRPUcgv0GLsO8F2t3FxkuBGTAGm/5Now1YpIkKdsWRDCkZ9dwvfz7iN4EAFPnsr2GadBns6++DJtt6YtiQJn0yMEeLD/4ZVLKFtpLgZS2JIkm2bnaW4cD0PC9eUfJPuiP1EvNQvFM/2ChbizRsfnkBevhoTx9cVQowtGkb6YMX623jzoxN4/3+nIZdJMGl8PdEeet55rSpaNfPH/344j3fGnBQPhN+MqWPXlk76Y2BHASYtyUMhHQNP2z8GGlaTo08bJ2w8XIif/85FbLJGHDemx2LfNs6IDJdj3sZ8TF2RJwQDOv7sia5PtVJgy1ElJi/LF4LL672chXBhjcrlpXipixMOX1Rh0tJ8nL2hxpDuzgjyM9rgpIAQZ0nguRNk7m7IPH0JZ98dV6ryrmEhaLpmOlJ2HsLeJk/jxtT5qDv9awR0aW0oU6F/D9T6aQyufP0b9jbri6zTF9F8/Ww4lfMrsf664VL0bCbH9pMq/LZGifhULYZ0U8DdRnNWCpTgufZyHL2swW+rlbgQpcFLneQI9DG2DQlfaw+qMGVVIWasVyI9S4tXuingZruLzOjXzR+9Ovrh90Vx+PD7m8gv0GD8u5VKON9IxfmGzlG2uJ1QiGl/xWPE+Ov4+KebSExRYvzISvDysD0ge7Z2R5fmbpi3NhPjZ6SgoFCLDwf7QmHn9WSzSBe82N0Tq3dmY+y0ZCFW0Dae7lIzEefDQb44e60Q46an4svpKdh6KBfaErSuAX2D0e/Jipgw/Sre/PgU8gvU+PmLSLvHt4uLDNduZmPSjOs2y3wzphYqlnfBp99dwNBRJ5GQlI+JX0aanQMs6dHKDZ2buwrx5utZqaJtPhjoY/f4blrHGc939cCaXTliv0kgGDXQRwispuw6loeRPycblqVb7IsDz3YPQO9O/kK8GfXtNTFmvno/zP6YcZbiRnQ+/lh0GyXRsqEnaka4IjnNvnCtp2szZ3Ro5IzFW3Lx46IsFBQC7/Z3t9s2jWso0K+9K9bvz8e3C7IQk6QW25i2TVS8Ggs25GLcnCxMXZojXv6/29/DrhNAjydc0bmZqxBYvpmTJgSgUQO87fdTbWc838UDa3bnYNzMNNFP7w/wLt5Px/Pw/sRkw7J0q/nLEWv0bOUmjqn567IwXj9uBvnYP6bqOOOFbp5YRcfU9BQhjn44kI4piZmIQ+Pv3LUCjJuZgnEzUrH1sP1jqlcbD3Rt6Y45qzMw9o8kFCg1+HiIv11bmtd1wUs9vbFyexY+/y1JCDm0jVfR8Z2Socbb38WbLcu2ZiKvQINTlwvsts1THbzQo7UXZi1PxWdT4pFfqMWnrwfatadlfTcMfsoPy7ek45PJcbh1u1Bs4+UhNdxv0DoxfloCvvg1XlzjR78a+Lg6jzAPABZymHumoKAA7777LgIDA+Hi4oLWrVvjyJEj4rudO3cKb5L169ejXr164vsWLVrg7NmzZnXs3bsXbdq0gaurK0JDQ0V9OTnGC09YWBi+/fZbvPrqq/D09ESlSpUwY8YMszqio6Px3HPPwcfHB35+fnj66adx8+ZNw/dqtRqjRo0S3/v7+2P06NHQlnR3ZkL79u3xzjvvYOTIkfD19UX58uUxc+ZMYecrr7wi7KpatSo2bNhgtt2uXbvQrFkzODs7o0KFCvjkk0+gUqnM6qX9JXvI7qCgIBE2ZbrvRN++fUVb6tf1LFy4UHzm7e2NF154AVlZ9t+OlYYn23lh+eZ0HD2bi6g4JX5dnARfLxma1nWzuc3Ji3n4e0MaDp/JvW/1tm+gwIFzShy+oEJCmlY8eBaqtGhey/rVkx5OyQtgxwklEtO02HCoEDFJGrSppzCUaVdfgc1HC8VDIHkALN6aL96y1Y2Ql6m2IXp39MWSjak4fDpHCBC/zI8XniTN63vY3Ob4+VwsXpuCQxZvxfXk5mvw5dRY7DuejduJSvFWfMaSRFSt7IIAX/tt1KudD5ZtTsORMznipmXKwkT4ecvQrJ67zW1OXMjFX+tTcei07RvNXUeysHRjmvAMKi2O1E9E/6eCsWDJLew9lIJrN3Pw9aSL8PdzRpsWATa3+eDLM9iwLQE3onJx9WYOvp18CUGBLqhR1VN8T2+4e3UJwtRZ13D8dDouXcvGt79cRL3a3qhTQ1fGGm0bKLD5iPEYWLQlX4gu9o4Bm8dibd02Lk4Q/6/aU4ArMWpx3C3elo+IijIhwFijXX05Dp1X4cgltahz+a5CKJVaNK1p3Y429eS4FKXBzpMqJKZrsemIUghKrSKN5Y9fVgsvkysmniilIWnTblweOxkJq7eWqnzlN15A3o0YXBj9A7IvXset3xchfvkmhL83xFAmfOQriJ69BDHzVyD7wjWcGT4W6tx8hA7pV2L9rSJlOHpJg+NXNEhK12L1PpV4e924uvWnvJa1ZWKf955VIylDi63H1UIYo8/1nL6uwbXbWqRlQbTfv4dVQtgN8i3dU8NTnfyw5N9kce4g8XXS3NvCq69FA9tj7di5HPy5OsmuR8WuI5k4dTEXCclKRMUVYtbSBLi7yhAW4mxzm24t3bB2dzZOXCwQD7MzVmSIt96NatpWpcjbZNexXOw5kYfbSWohAhUqtWjbyKgcDujuiS0Hc7F+Tw5ik1SIT1Hj8Ll8qEpwRuzfKxgLl0YLj5rrt3LxzS+X4e/nhNbN/W1uc+h4GmYtjsKeQ9aF45CKLois4YUJ06/h4tVsRN/OE/87O0vRqU05m/V2ae6KtbtzcPJSofAembUqEz6eUjSqaac9W7hh9/E87D2Zj9vJauGJQW3TpqG5qkqfZeZoDAs90Nrj6c7++Gddouj/mzEFmDAnRoyZlg29bG5z7Gy28Mg6cML+vYy/jxxvvVgRP82KgVpdunu5jo2dseFgPk5fVSE2SYN5/+YIT5IG1Yz3CJZ0auKMfacLceBsIeJTNPhrs078bhlp9HrZe7oQV2PUSM3UIDpRjTV78+DnJYW/t+3HLBJx1u3JxcnLun6avTqrxH7q2sIVu0/kY9+pAsQlq7Fwfbbok9YNXKz0k3EpqZ90dbsJgejEpQLEJKgwc2UmfMUxZe84dBeikRg3SWohAoljymTcDOjuIcTQ9XtzRRk6po6cK7B7THVv5Y7VO7Nw/EK+OL6nLU0Xx3fjWraP7x6tPLDjaK4Yx7eTVJi7OkOIY+0a667NdLtPni6mS5Parjh0Jk+IVvbo2cYTK7Zm4Oi5PHHd/+3vZPh6ydE00s3uvcK2Q1nYeSQHsQlKIQJR23Roqrs/qxHmjEA/OX7/m0RlpVioXvIIjqxaSnXdQdFC6pDL48jjuVfMQ4UEiOXLl2P+/Pk4fvy4EDO6deuG1FSji/BHH32ECRMmCIGnXLly6N27N5RK3RuUa9euoXv37ujXrx9Onz6Nf/75Rwg7I0aMMPsd2r5JkyY4ceIEhg8fjmHDhuHSpUviO6qLfpPElD179mDfvn3w8PAQ9RYWFhq2nzdvHubMmSPqJ/soXOlOoH0MCAjA4cOHhahDNvTv3x9PPPGE2PeuXbti0KBByM3VPQjGxsaiZ8+eaNq0KU6dOoU//vgDs2fPxtdff12sXnd3dxw6dAg//vgjxo8fjy1btojv9KLY3LlzERcXZ1jXt92qVauwbt06sZBo9P333+NeCPSXiwvUmctGN9PcfC2u3ioQF56HVS+F+IQESnE52ni1p0stPSRWDrL+MBMWJDMrT1yKovK6U52/l0S8nTEtk18I3ErQCG+e+70PpeVu6i3vrxCizemLuWYiDAkvNSLu702Am4sMGo0WOXm2H47JRdjXW24mtpA9V8Q+PNybEkfqJ4LeqJOnzJGTaYbPcnLVOH85E5E1bT/QWOLurhv3mVm6cycJOhROdfSUsd6omDzEJ+ajjo166RjwvsNjwNaxSOt0zBGhgTLxNtG0DImp9GATVkFmtc7gclKz0B9xfMdqbAo/9PmVWIvjO5rKl9Kd7j7i06IBkrcfMPssacte+LbQ5S2TKBTwblQHydv2GwtotUjevh8+LRrarZvapqK/BFdvm7cNrVcqZ110qRQoFSKNKVdjNQgNlNj8jaY1ZMgr0Apvn5KgMEs635y8kGN+vrmRJzwi7hfkjdC9jQ+yc9W4GW39LXk5X5l4qDt3zeh1RftBIVJVQ60/kMtkQFgFhdk29GBH61VDdNuQZ07VUCchUHz+mh+mjC6HMa/6oVol2w/5RIXyzkK0OXoq3ez4vnAlSwgxd4uTXHccFCpNxoGW7ne0qFfLer3lfKSibc5fV5q3TYxSeBvZGguVK8px/rpJ2wBinbwpTGlR1wW/fBSA8cP80K+TO5zsaPtBNGZ8FOZjJk+DS9fzULPKvY0Z8lj4YGgIlm9KRtRt+94UegK8pUK0uXhLZXbuo9DS8Ipym21TKUhmtg21Da1H2NiGvAJJ5ElOVyMt0/o1M0DfTzeKj+EqwbZtqVxBjgs3LPrphrJ4P0W6YPIH/hj/pi+e6Wi/n0yPKdMxQPZco3ET4mT7mLIcN3RMmYwb8syh7emY+myoL375MACfDPG1e0zpbTl7rcDClkJUq2TblvCKCpy7WmBuy9UCVLXxW2EVFWIhcdceJLaI6/4VY0hzHl33owpQrbKzTXsigp3M7hXInjNX8g3bUCiVOJ5VxvMvHdv0WY3wu79PYf5bsJDD3BPkjULixE8//YQePXqgdu3awkuFPGtIsNAzduxYdOnSBXXr1hWiRUJCgkFE+e677/DSSy8JT5dq1aoJUWTKlClYsGAB8vONJ0ESREjAIaHo448/FoLKjh07xHck/mg0GsyaNUv8Rq1atYTwERUVJbyCiMmTJ2PMmDF45plnxPfTpk0TXix3Qv369fH5558LO6ku8jAiO15//XXx2RdffIGUlBQhSBG///678DD69ddfUbNmTZHjZty4cUJUInv1kLcStRHVMXjwYCFYbdumy89AwhdBnkTkraNfJ6gOEqciIyOFRxOJSPrtrHlOZWZmmi1qVfEbILqAEunZ5g9MtK7/7m6403rdXSWQSSXIssivkZWrhZeFG7Eeci+m783Lawzl9e7H2RZlsnM1xVyT78c+lJa7qdfHu2ibTPMY7YxMtbjpuF+QC/zLfQOw52gW8vJtCzk+Rb+ZkWWxD1kq4bHyMHGkfiL8fHU3n5Z5a9LSCw3flYRw1X+9Kk6fzxAeOoS/r5N4yMvOMbcnNb0Q/j7W69WPc6vHiYk7vNVjMdf2sUj1qtRa5FlENNHxa+14pfw1VGf2PR7fdCyX5ti93ziXD0BBQrLZZ7Su8PaE1MUZTgG+kMrlKEg097YoSEiBc5BtLyzCzRlW24bWPWzsK4WjZecXL+9pEYZaI1SKLwY54cuXndCqjgxzNymRW4rnYP05JT3TYuzT+cb73s83Tet6YMkvNbD815p4upMfvpgchUyLca2HHsYJyzwSmdlqw3eWeLpJIZNJkJFjvk1GjhrenrptAn11x3DfDh4ihOjnBWm4dZvCM/xQ3s/28a0/1tIyCosdhyRk3C23YnWi7BsDK4u8O/TgRyFcgQHO4ti3hj5sgx6cTaF1EnBtto1UYn0bk/Y8dCYfM1Zm4sf5afh3bw5a1nPB68/YFqr04yLN4hpF1yzK/XMvUMgW5Xlas6304bb685vlfmbl2D73UeioaJtci7axcr5s28AJk97zxi8jfVAnXIFfluYIG62hb1fyljGrl2yxN4bJluwS+ulsAWauysRPC9Oxfl8uWtZ1xmt97QuKNo8pi7qt2WN9G93xEljkxdunve6YmvBnOm7FKTF6sK/NY4q8kkQ9xY5vY702j2+La3OGnW3aN3FDbKISV6Lsh+Xpr+0ZWRbnDjvXfS93mXV7stTwKbofopdc5An00pO+IgSTQq0G9fYV25EnFMOUBk52zNwT5BFC3jCtWrUyfKZQKEQo0YULF4QnCtGyZUvD9xQ+VKNGDfE9QZ4qJHwsWrTIUIZCnkikuHHjhhBd9GKHHgoxIlEjMTHRUMfVq1eFR44pJASRjRkZGcKbpXnz5obv5HK5EEzuJLzK1AaZTCZCtEg40kPhVoTeLtpH2neyVw+1VXZ2NmJiYkSImGW9BIVg6euwB4VUme6zve1IMCMRyZRazd/Fm29/hjefMz5YfDfTdi6D/xqtG7k7TNu0beqJYS8aE/V9/UfsA/9NegP40WsVxP/T/jYfV22beODN53Xx3cQ300vOZ/Bf6CeiS7tAfPR2dcP66PGlS25rj1FvVUNEJXcM//jEHW3XuLocz3Uwvt2bsdZ2cmXm8ed6nAa/rioUQlqTGjK80EGBaWsLkWOR57NdMy+8/ZLu2CfG/xr9QO06fSkH7319XeTF6draFx+/EYwPvr8pHnxIMBjS2/ggOnGR0QPtfqK/TFN4BoVfEYs3ZqF2hJMIv1q6VReO2qVtOXzwVlXDdh9/c+6B2EPhQp//cAEfj6iGf/9sKYTSY6fScfBYKlBka4u6zhjcy3gPMHlxBh4Uu44bB0lsohrpWRqMftkX5XxzkJSmRvvm3hgxqKKhzJdTbj0QOyjMl0K23h1/zW65prUUGNDVGPry+/KSk/3eC4fPF+LCTRW8PSQiMfLrvd3w0+JsEULUPNIZg5809tMvfz24fqLQK9N+IjHjo0E+KOcrRVKaToxoWdcFL/c22jNpkdGb7IEcU8d04VdEVHy2OKYobG/Ztmw8Ud8Vrz5tfKn68wLzhN8PAspt07KeK1btKB6+17qhO15/1pjH7PvZJd+L3w0kIE5amIShz/ihe2tP4Ymz72QOrscUQFP6xxKHRMtJfh4a/2fvLKCjOr4//k027h7iTgIEgru7uxdrgVKkSGkptFAKFSqUYsXd3d3dJQkSJIEQd/dsNv9zZ1nN7iZI6fL7z+ecd5K3O2/2vpn35s27c4Urcjj/OaTUGDNmDIsTo4xE0SFREMlDyhGJVQvVUadOHQVlkAR5C5Z3RZUM8p9JFDby1jZvW29F6niT48iCiGIEyTPi+zjceZSH8PkypQCt+hFWZgKF1Vfaj4x7swCi8mS8ttSoaL25+aUoEZVdUabV9yylVXkJ2SpW52mlRlJesppvplSHmYkuiwugjDa1za3QHIUsLpJgkWQJky53jKWFgAUXfT9KHGfY2+jjh0XRZaxxKLPUs8joMvJYmgsU5LEy13sv8mhCm/qJuHIrFY+f3ZHuG+iLVxitrfSRmi4rZ21lgPAX5b9cTBnji8b1bDBhRgiSU2XHU11UN63Wy1vl2FgZIDVDXO7hSyFeJcq+I/cnVfcR3SexyaotIKT3Ypl7S0fh3qK6jQ2gYJVD96+q+zW3QFyn2Tve32YqrHQ+BGR9Q1Y58tB+cWY2RAWFKEpJh0gohKGDYowUQ0dbFCYoWvIoQxYysraRG6eMdcpYE0rIyQfMjJTaxrisRSPF2UnLpq0U0clCTOmjz+LuXApV7PtbITl49vKFivFGoGBhQfsv1LhAvQm0Mk3Z7Wh7+jIeK+f6oF0TK+w5kcri4ETEyCwv9F9fw2QpIG8NQEogil+hCrI4I8WIslWKpalAutJOigkiLknRgoTibVCsLwkUB+fxM5lCldwbCWtLA6TKBd2l+zD8ZflBZjXx7EUuC3JM8bBoXMvMEmLF70F4GkEvoHosDs6LGJliS+/1rJ5ciBXaxlQXUYlC9W0jKpUGhZU/RlP2HEm2LwcbAVPk3AzOxtOXEWWuGbLmSs+Uv2b08CL67RXK1fxMYWmuhw1/+Es/IyuGkf0rMQXPZ9Ofsc9Cw4sRGS97UZcEEabzkrf2Ipc6ilGjCrJqY21jQm0jK0P7ytY05KZVUEQxrYCXcbn460tLFnvnzpNihDwrwpzYtDLPKLLqyZR7BJBsFIRbYz+ZvWU/WVM/ictRHJwIuWxtkrYpc0/RdVOOPJYq5SlReGbSPSQPxcqRxA+iODjymZykbWOmK70nJfvl3t/M+kZWRnw+Zfu2fqAxDPV1cOW1wlaeO4/z8HxBoYq5DckjN9fSMJ+g60smjwyaH8nPHUKfFWDSb3Hs+UttSa7aK39wRVJaxeMBcv5/w12rOO+Ej48PDAwMWEwaCWShQ3FcyM1Kwo0bN6T/p6en49mzZ1JLm9q1a+Px48fMZUp5o7orAtXx/PlzFnBZuQ5yn6KNrFUoBo0ECjh89+5d/JvQOV6/fl3B6ofaiqxoXF1dK1wPKWwoWPO7QMGWLSwsFDaBniHLdEQpFCVbTEIxm6gHVpbFNaE0nb4ehnga+fYT9qRU4RvVSybJMUkiVHaTPQjpcernKlBI+ylPZEIJKrsqPjjp+FcJ4skApeQls1/5Mob64tgbka/LyKNNbcNkSS6WbtHxRUjLFKKGv2zF0dhIF5U9jfD0heY0mhVV4jg56GP24hi2cqS6bYqlW3RCEZus16gsL48O8wd/Wk4a4XdFm/qJyM8vQWx8gXQjV6iUtELUDbKWljExFqBqZQs8fJJVrhKneSM7TPo+FPGJiu34NDwbxcUi1JGr183FmAVEfvS6XsrKRtmKJFtCmoi5l/i5VewekL8X6d6Tvxfp3qJ7jqAAn2QxIF8vZUyigJ+URUpVnRRs1M9VV6FOXxddFq9HFfS5n4vS/e1K5d9tbHwbMm4Ew7Z1Q4XP7No0RvqNYPZ/aXExMu89gl3rRgrL07atGiHjhmarKmobClTs46zYNrQfpSZVeFSSCD7OioocKh+dpFnJRcp/VVlyKJOLRLFCW9Tr8SYowFRxvPEyxpMX79/KS0dX9gJFgVopJbNkoyDE9EJFq/oSjAx14O2iz1I4q4Ien5HxxQrH0LoL7Ye/Tk8sjmlSgkp2imuctE8ZbyRQxrnYhALpFhmdh9S0ItSpYaVwf1fxM8fDp5rv74pCMXdIiePqZAR/HzNcuZkma5v0EulGL8jitpEt8lBAa29XfUSoaxsR8CpOiCrybUPzF28DFiNFHe6V9BXcadk1k1Qk3Sh2TVpGMYKqKF4z/t7GeBLx9tfMuesZmPBjOL6cI9soa9W+kymY9bcswQWNfZRWXLJRYHdSUvi7y/qXgrR7OQkU0ncrtw1lpPL30FNoG9qn1OXqoGuLNoniXNxPIukm6acqXgaK/eSij4hY9bK8iheiiqdSP3npa+4nx9duz3IKGuV7SnrdyMtjSPFtqO4i9fdUnFDhGMk9JZEnJUPE7iknW8VBppKtACmZIqkslOJcssUmie/vat6GCs9ZirXzPEq9LC/jilHNR1GWaj6GCFfhOtWyjgnuPSlgCiBV84nEVKF0i0kUzyeq+yk9990NmXuUOnlexBYpHEPyUBBjVceQHKTEqeZrxBRWtDjF4VQEbpHDeScoQC8F/KVgxuQyRRY0FKyXgv2OHDmSuTwRFLyX3JDI9ej7779ncWUoXgxB8W4okxUFNx41ahSrkxQ7FOyXYstUBIqxQ3F6KFMV/RYpSV69eoV9+/axYMy0P2nSJBYImOLQULyaBQsWICPj3zEnlUAxfSg2DwVGpvOj4MwUC4csY3R1K65HJRcqin1DblmkkKGsWf8mRy9moU87KyQkC5GUVowBnazZw/i2XDafH8ZWYlYZJ66IV7xY9hM7fYXAsJ7OBixoJU2QK1qvPBeCizG4rSGik0TsZa1FkAEM9HRwM0w80aHvMnNLcfS6+OF+KaQYE3oZsww7jyOFqFVZH24Outh1XvbgvBhSjHZ1DdjEjlalOzWgQHylePBC+FG1DXH4XDr6dbJBXFIRS9k7uJsde9mSz0g1d6IrboTk4NjFDOnkzMleNtlxsNWHl6shsnNLkJIuZEqcaaOd4eNuiJ+XxYIuU4lPN1l9aMo0ceRiBvp2sEZ8chGbAA3qYoO0zBKWVUvCj+OdWYaq45czZW1jr9Q2LtQ2IiaPxGKKMmZRsFXCxUEsP61sya+QaWs/EbsPxWL4AHeWeYYUMqOGeCI1rRCXb8isMxb+XAOXrqewlOPE1LG+aNvcETN+eYi8fKE03gbJU1QkYi93R04n4MuRPsjKFiIvT4jJY3zxICwTj55mo66HalkuBRejveQeyCpF54YG7D6SvwfG9TRC6IsSXAktLnMvRtG9WPP1vfhYKF2Npv97NjVEXkEhm5z3aWHIAomqU8xcDBFiYGsDluEqKpGyy+mxWAG3n4jrpO9IruM3xTJcDhViXA9Dlu3q8asS1PLVg6u9LvZclE3ujQ0BazMKaq4jDf4KiJjVTna+5vTjpr4yC1ATL1dYBAWgKC0TBdHx8P/5Kxi5OCLk02/Z969W7YDHuE8QMO8bRG/YC7tWDVm68dvdx0jreLlwPYLW/Y6Muw+ReTsUnhOHQ8/UGNEb96E8rj4sQZ9meohN0UVMcikaVxOwgKV3n4mvw77N9di4dequeP/64xKM6qzPsl1RAOga3rpwsdPBgatCqStByyABnkSJ28LESAcNqwhgYUJWWxWzID10Ng0DOtux8YYyTA3pYY+0DKFCRqqfp7izbENHL6SrHG8c7QzYeENjSXK6kMWF6N/ZDrdCstnYZWGmhy4trVlGoqt31StBTl7PQ/cWZkhMpXpK0LuNGRsL6OVMwrQR1rj3uJClOiZOXMvD6F6W7IWPgv9Sxh36/cv3ZBfGsau5LEYOpS4mS4SmNY3hZKeHpTs0zxV2H4nFsH5uiIkX398jB3sw5Q5lqZPw95xAXL6Rin3H46VKDZdKsqC/To5G8PU0RVaOEEkp4mdWy8a2yMgUIjGlAD4epvhypDez+LsdkgHfmjLXVnlO38xH12am4rbJKGHnQ5YN957InoNfD7Vi++dui8/95I08jOppwV7MX8YWo11DE7HFQnC+NAAtuXGFPi9iY7Obox5LO/00UpxxSR0Hz6RiYBcHlmI+IaUIQ3s6smvm+n1Z3/4y1RPX72XhyPk0afpx59djPFHJ3gDebkbsGZWcVsz+0iYPWT/QQkJsomaLy3N3C9G5kSG7ZkiR0K2pMVNwBD+XvexP6m/K9i/eF9d19k4hhnc2YdcDKaVb1zVkym/KYiUJolwnQJ+5VdELubW5Ljo0MGJZ/R69VK9gOXMrH12bmjDlBT1ferU0LdtPQyzF/XRHfF2fupGPkT3MmVKSlE+U+Yr66WqI+Htyn2oQaIQH1E/5IrhSP7Uzw9NXmvtJXHceujU3RQLJQ/dUa1Oks3tKJs+0YVa4+6QQZ2+9vm6u58ruqdhilvmK5Lks5951/FoeerY0ZRZh7J4KMhLfU7vUu5eduJqLnq3M2TyCFJR925qz+/tumKzeGZ/Z4s7jfJZljv3O1RyM6WPNrl9SJHVsLL6/lYMZU2wef0+DN3LhOnY5G73aWCKePfeFGNDRiil3bj+U1T1zjANuP8zHyavZ0rnCuIF2TBEWEVWIzs0smDwXbsvmZy3rmbKMVrTASIteI3pYs9+i3/mYKSVNPOeDwBU5nHeGlCPkzkOBdin1NcWdOXnypIKygcqQIoWsZmrWrInDhw9LrW0oPgxlWyIFDwXsJesVsvQZMGBAhWUwMTHBpUuXmFKIghmTHC4uLmjTpg2zPCGmTp3K4uQMHz6cKVEolTml9Kb4Of8WJMOxY8eYoosCJZOyixRcFDD5TaDgyKT8oUDSVKd8WvV/g4PnMtlL7Zj+tjAx1sWTl4X4ZWWCQnR9Rzs9mL/OokN4uxlizgRZTIURPcUuBRduZeOf7SkVrlee4HAhcw/oWN+AvZjRCv7Kw/nSIKA0YSotlb2EkEXB5lMF6NzQEF0aiV9U1x0rYFYIEs7dK2YvoBQ3hFZV6EWT6iwvvay2tQ2x/3Q6m/SOG+wIUxNdhEXkY+7SWIVjSElCLgcSfN2N8PMUN+n+yL7il4Fz1zOxeHMie4GSpC9f+L1iqvuZf0fjoVzmhjLynMmAoYEuvhjoAFNjXYS9KMBPy+MU5bFTlMfH3Qg/TXSR7n/WW+wKee5mFpZuFfum1ws0xZdDZPGBpn5aif3deTyNbdreT8TWvdEwMhJg2oTKMDPVw4PHmZg6+wFLRyqBXuqsLGSKpF6dxe2ydJ44E5KEXxY+YWnJiSVrwlFa6oNfZlRlLh637qXhr+XPNcpylu4BfR0MeH0PvKB74JDiPUAvJ2ZGsvvm/nMhC3pMik/pvXhIdi8S+y+Tb78BPu1sxKw8nkSVYM8F9RZQIRElMDMuRod6+sxlKi5FhDVHCpmbEEEKGfkQZqQQ2nqmCB0b6KNTA31mYbThRKFC1qVqngIMbC1byR3aXvz/qdvFOHVH/UuVZZ1ANDq7Wbpfdf537G/0pn0IHTkDhk72MHaTXRv5kTFMaVP1rxnw/HIYCmIS8GDMTKScviItE7/7OAzsbVB59kQYVrJHVkgYbnUdhSKlAMiqePBSBFMjIdrU1oO5MRCfVooNp4qlsWwoXbx820QllWLXBSHa1hGgfR0Bsz7celacpp2gsvaWOqjdWh8mRmL3LerD1ceKpWXKY+/JVHbtTxjixMabx+H5mL04WuP97ethjHlTZRrFUf3F9/HZaxlYuDEe5AnsWskAbRq6suPIJeF5ZAGm//mKWQGpg4Lt0kvRiO4WMDHSZSv18zenM9cxCRRo1cxU1ue3HhYwl5jerc2ZywUpa+gY+eC3p67nMUugwZ0s2LOHXjz/2JjGXiY1sW1/LLu/vx7rK76/w7Lw9U8PFe5v50pGsJS7v/19zLH4Z1mMvS8/82Z/j59LxLwl4nuYghpP+NSbBQcmV8qTF5KwcbfmeEXHr+axl2mKgSJum2Is2JKhcH+TOxS5c0igdNDmJjnshZvahtx7KG6KxH2IrO3I8qJdAxPW7qSgp5fqw5c0K7D3nEhhz6gvhzkz97DHz/Mwa2GkwjVDij4Lc9nriJ+nMX77xku6P3qA+L47czUdf69/t9hwp24VsrFvcAcTmBjqMOuXJXtyFdrG3koAM2PZB3efFsPMJB9dmxizsY8UInSMxKWTzsXXVY+lNicFKbVZeIwQ87fmaHT7PH4tn8kyvAv1kw7rp7+3ZSrKYi1gCxkSbj+mftJBzxamzHKDUnPTMbJ+Aqp66aMdKXgk/fSkkKU5L49jdN0Y6ODT19fNs6giFpxY4Z6y0YO5idw9RdeNaTZTForvKSH+2qJ0T92gewoY1MEcZsbk4leMPzenM2WaOo5czmGyfNbTSizLqyL8sSFVSRa6hgUKwbgtTDPRp405c2GioMp0jHJwa0pHnpZVggdyGa7K49D5LCbP533Fz/2nLwswb3WSgjyUSdTcVFbn9ZA8WJilo38HKxYUmdyw5q1JUrCMcrLXx6BO1qyPk9KF2H82E0cvlY3bw+GoQ6f0TSK9cjhvCGWMatWqFXOnoqxLHO2i35SX0CZcfd5fPKN3JSYiGdpEMdmJawm6r9PiagsUeFxbiA+PgrZQt30daBN6WnTdtJqoOQX4h+baSnGmQ20g9KYsNo42YOP471qgvgkvH4RDW/CtKQuorg0kRv87QWHfBnf/iruufwiKCrTn+V2iLpXWf4Sw+MO7xn4M86yd89WY1H4EJDx5s6QMH4pKAdr13H8fcIscDofD4XA4HA6Hw+FwOO9EqSStHudfR3uWxzic/5CoqCiYmZmp3eh7DofD4XA4HA6Hw+Fw/mu4RQ7nX6Vly5YKGZu0FWdnZwQHB2v8nsPhcDgcDofD4XA4nP8arsjhcFjsBj2WqpzD4XA4HA6Hw+FwOG8Oz1r14eAtzeFwOBwOh8PhcDgcDofzkcAVORwOh8PhcDgcDofD4XA4HwnctYrD4XA4HA6Hw+FwOBzOO1Gqw7NWfSi4RQ6Hw+FwOBwOh8PhcDgczkcCV+RwOBwOh8PhcDgcDofD4XwkcNcqDofD4XA4HA6Hw+FwOO9EKbhr1YeCW+RwOBwOh8PhcDgcDofD4XwkcEUOh8PhcDgcDofD4XA4HM5HAnet4nD+H2NlbwFtQigUQVuwcbSENpGbXQBtwdjUENqEQKA9axLmVqbQFrIz8qFN/NHrObSFBStDoU00HlMD2sKLKaehTZSUaM9zwbdmZWgL+bna80wg3P1doS0IBNrl2pGVlgNtwc7ZGtqESIvu73xd7bpuPlZKdbRnTva/Dm9pDofD4XA4HA6Hw+FwOJyPBK7I4XA4HA6Hw+FwOBwOh8P5SOCuVRwOh8PhcDgcDofD4XDeCZ616sPBLXI4HA6Hw+FwOBwOh8PhcD4SuCKHw+FwOBwOh8PhcDgcDucjgbtWcTgcDofD4XA4HA6Hw3kneNaqDwdvaQ6Hw+FwOBwOh8PhcDicjwSuyOFwOBwOh8PhcDgcDofD+UjgihwOh8PhcDgcDofD4XA4nI8EHiOHw+FwOBwOh8PhcDgczjvB049/OLhFDofD4XA4HA6Hw+FwOBzORwJX5HA+SkaMGIGePXv+12KoZMOGDbCysvrgv/vjjz+iZs2aH/x3ORwOh8PhcDgcDofz4eCuVRwORyXdmxujWU0jmBjqIDymGFtP5CIpXaTxmJZ1DNGhgTEszXQRnSjE9lN5iIwXqiw7cYA5qvsY4J89WQh+Vqyx3s4NDdG4uj6MDXXwMq4EO88VIDlDsyzNauijTV1DWJjoIDZFhD3n8/EqUXZM40B91A3Qh6u9gNU7bXkW8gtRIbo1M0azIEN2XESsENtOVqBtahuiXQMjWJrqIiapBDtO5yIyvkRl2S/7mSHQxwDL9mYj5LnmtunTxhyt6pnAxEgXz14VYf2hDCSmqq5XQtsGJujSzAyWZgJEJRRj05FMvIgR/46dlQALv3FUedzi7Wm49bDgo7luujU1QlO5fqJ6y5OlRS1DtG9gCIvX/bTzDMkia8/BHUxQxUOPyVpYXIoXsULsu5CPxDTN9RI9W5qieW0j1lfh0cXYdDQbSWma+6p1PWN0bGwibpsEIbYez8bLOFnbTBtuhQBPA4Vjzt/Jx+aj2Rrr7dHCBM1ryWTZfDynXFla1TVCx0avZUkUYtuJHAVZvhlqWUaWC3fzsflYjto69x4/i60HjyMtIxO+nu74auQnqOrnjfI4feUmZv+9As3q1cLv0ydKP2/c51OV5ccP7Y9PenYqt94GVXTRLFAPZsZAQnopjlwXIialVG35QE9dtK0tgJWZDlKzSnHyTgmexciuhda1BKjhpQtLUx2UiIDY1FKcvitETLL6OgmbpnXhPXUkLGsHwsjZAXf6jEPiobOaj2leH1XnT4dZVT8URMcjfN5yxGzar1DGY+xgeH81EoaV7JEV+gSPJv+EzNsPUFH6trdE6/pmMDXWwdPIIqzbn4aEFNX3qoR2jczQrYUFLM0FiIovwoaD6YiILpJ+72CjhyFdreDvaQg9PR2EPs1nZTJzRB/V2KdN97c29VPXJkZoWsOAjcMv4oTYdiq/3Od3i1oGaFfPCBamOuJx+Gw+XiXIjcPtjRFA47CpZBwuwf5LFRuHuzQ2RONAAxgb6bDjqO7y5GkeZCCeT5jqIDa5BLvPFyjI06Q6zScM4Oognk98809mheYTAzpaoU0jc5ga6eJJZCFW707R2E9VvI3QvbUlvF0NYGOphz/WJuL2w7x3rvff6isTIx1WZ1VPPVib6yInv5TNaQ5dyUeB7NLS+nkW0bu1GVrWFY83z6OKsOFQJhLLub/b1DdB56ambLyJTijG5qNZeBErG28WTHVQedySHen4mOHpxz8cvKU5HE4ZOjY0Qpu6RthyPAe/bshEUTEweaAF9ATqj6lbxQD925ji8JV8/LQukz1EJw80h7lJWV/ZtvWMyIm2QrSta8AmCjvPFuCvHbls0jaul4lGWWpX1kOv5kY4fqMQf2zLZROvcb1MYWYsk8VAXwdhkUKcvl1B7c1rOjQwQus6hth6Mhe/bcpi8pByQWPbBBigb2sTHL2Sj1/WU9sI2TGq2qZNPcOKNg26NjND+0amWHcwE7OXJ6OwWIRvR9hCX4OKvkF1I3zS2RL7z2Vj5j/J7GWGjiHFBZGaWYLx8xIUtj1nSMklQsizwo/muiFlTKs6hth2Mg+/b85GUXEpvuxvplGWOgH66NvaGEeuFuDXDVlMFjpGXpaoBCE2HsvDnDVZWLxLrKCYNMAcOuW4hHdqYoK2DYzZy93Pa9JQWFSKqUOsNMpTr5ohBrQ3w6GLuZizMo0pT74aYlWmbS7ezcfk+SnSbffpHM2yNDZG2/rGTMHyy7p0dg1/NdhSsyxVDTGgnRkOXcrFnNXpTJYpgy3LynIvH1MWpEi33Wdy1dZ55upNLN6wA5/174H1f/4IXw83TPnpL6RlZmmUPz4pBUs37kRQlcplvju8ZqHC9t34z6Cjo4OWDeugPKp76aJzfT2cCxbin0PFSEgrxYgO+jA1Ul3e3UEH/Vvq4c4zEf45WIywKBE+aaMHBytZm6RkluLwDSEWHyjCqqPFyMguxacd9GGipk4JAlMTZIU+xcOJc1ARjD1dUe/QSqReuIkrdXvg5ZKNqL7yZ9i1ayot49SvE6r8OQPPf/4HV+r3QnboEzQ4uhYG9jYV+o1uLc3RsYk51u5Lw6wliSgsEmH6SAeN403DIBMM7WaNvWcy8d2ieLyKL2bHSMYbQ30dfDfaHqWlwM+rkvDjskQIBDr4eoS9xntK28Y+bbq/tamf2tc3RKvahth2Og9/bM1GYREwsZ+p5nHYXx99Whrj6LUC/LopGzHJJewYxXG4BJuO52HOumws2Z3LZJjYz6zccbhtPQO0qGmIHWfzMX9bDnsujO+tWZ7alfXRqwXNJwrw+5YcxCaL2DHy8wl9PR08jhTi1K2Kzyd6tLZEp+YWWLU7FTMWxqGwUISZX1RidanD0EAHr2KLsHZv6nut99/qK1Jw07b3Qj5+2pDN+qyqlx6GdjT5aOZZRJdmpmjX0JQpb+asTGH39zfDbTSPN4FGGNzJAgfO5+CH5Sls7kDHmMuNN1/+nqiw7T2bzcab0OdvNi/l/Hv8888/8PT0hJGRERo0aIBbt25V6LgdO3awuce/7T3CFTn/jyksLMTEiRPh4ODALtCmTZvi9u3b7LsLFy6wC/Do0aOoUaMG+75hw4Z4+PChQh1XrlxBs2bNYGxsDDc3N1Zfbq5s4k4X/6+//orPPvsM5ubmcHd3x6pVqxTqiI6ORv/+/Zk7ko2NDXr06IHIyEjp9yUlJfjqq6/Y97a2tpg2bRpKaTZRAY4cOcKOozqI4OBgdl7Tp0+Xlhk1ahSGDBlS4XOidvv666/h4uICU1NTdmNTe6kjOTkZdevWRa9evdixIpEI8+bNg5eXF/uNoKAg7NmzR1pe0vZnz55lx5mYmKBx48Z4+vSpQr2//fYbHB0dWbuOHDkSBQWaVwvfhDb1jXH0aj5bpSAlyLrDObAy10Utf8WVQXna1TfC5eBCXAstRHxKCbYcz0WREGgSZKhQzs1BgPYNjLDhqObJqISWtQxw8mYhHrwQIi5FhM0n89nqdg0f9U9Qmoxcf1iMm4/pZUzElEBFwlI0qqYvLXPhfhFO3ynCS7lVtYrQpp4Rjl0rkLbN+iO5sDLTRc3K6tumbX0jXAkpxLUHRYhPFWHriTym5GhcQ7FtaDWvXT1jbDqm/uVXno5NTHHwQjbuhRWwl4AVuzNgZS5AnSrq3xI7NTHD+Tt5uHQvH3HJQqw/mMkmSS3qiCdWdGvRCqv8VreqMW4+yGeTl4/luiGF0vHrBQgJV+4n2TWgSlF0NaQQ11/3EymBiqmfqsvkvxJShPAYIVKzRIhOLMGhywWwsdCFraXmx2m7BsY4fCkXwU+LmIJozYEs1ja1AxTPU54ODU1YP10JLkBcSgk2HRErpJrVMlYoR59l5YqkW0E5/URKnCOX8xD8TCzL2oPZ5crSvqExLt0vYO1D/bT5qPglqGlNIxWyyDZNsuw4fArd2zZH19bN4OXmgmljhsHQ0ABHzl5We0xJiQg/LlyJUQN6wsXRvsz3ttaWCtvlW/dROzAALpVUr3zK0yRQgDtPRbj3XITkjFIcvCpEsRCoU1n120OjqgI8jxHhysMSJGeW4sy9EsSllrLPJYS+ECEirhTp2UBSRimO3RLCyEAHlaw1v1Qln7yEZ7MXIvHgGVQEj88HIv9lDMKm/Y6cJy/watlWJOw9Ca9JI6RlvCZ/iui1uxCzcR9ywiLwYNxslOQVwG1Enwr9RqemFth/NhN3H+czJciynamwthCgbjX1L2Vdmpnj3M0cXLyTi9gkIVMuFBWL0LKeGfu+sqch7K31sGJXKluxpm35rlRmcVDNx/CjGfu06f7Wpn6il3FSgISGC5kCZMOxXGZ9VNNP/ThMli9XQ4tw/WERElJF2H4qnz0vGwXKjcOhNA6XII3G4aQSZuFRkXG4VS1DnLxZgAcR4vnEphN5sDTTQZCvenla1zHAtYdFuPFIPJ/YcSZfPJ+Qk4fNJ24XqrUkVUWXFhbYeyoDdx7mISq+GEu3JbN+qlddfT8FP8nHjuPpuPUg773W+2/1FbXxqoN5rL1TMkR4GiVkz8zqPvrQ1fk45llEh0amOHQxB/eeFLLxZuVe8XhTW8N407GxKS7cycPl++LxZsPh1+NNbWMN440Rs/wrb7zhfBh27tzJ3j9nz56Ne/fusfe1Dh06ICkpSeNx9A5L74n0LvlvwxU5/48hhcjevXuxceNGdoH6+vqyCzQtLU1a5ptvvsFff/3FFDz29vbo1q0biunNBkBERAQ6duyIPn36IDQ0lF3wpASZMGGCwu/Q8aSQuH//PsaNG4exY8dKlRJUF/0mKSMuX76Mq1evwszMjNVbVFQkPZ7izqxbt47VT/Lt369oLq4Ouomys7PZbxMXL16EnZ2dguKFPmvZsmWFz4n+v379OtO2Upl+/fqxY54/f17m90lJRTIEBgYyZY2hoSFT4mzatAkrVqzAo0ePMGXKFKZIIjnk+f7779m537lzB3p6ekwZJmHXrl0sJg4pyeh7JycnLFu2DO8DOytd9sAMeykzNc0vLGVmtt4uqpUnAl3Aw0kPYZEyW1l6DIW9LIKPi2wSYKAHjOppxlZZ6CWvPGwtdJiJ7NNo2eSIzHEjE0rg5SRQK4ubg+Ix9Es0gfBUc0xFsbPUZRObsEhZ2xQUljJTeE1t415JoHAMyfMksljhGFrZGdndDNtPV6xt7K0FbCLxMKJQoZ8iYorg5656siMQAF7O+ngULjuGJhO07+uuerLm6azPtot31U8cte26kfWT4nXD+sm5nH56pXjdUL+pk99AX6zkSc4oQXqWepNve2obcwEev1Bqm5hi+Ljpq28bZz08fqHYNrTv46p4TMPqRlj0jR3mjrVBnzamrL009hPJ8rJIUZbYYviU108vlWR5WVxWlkAjLJxqi7ljrNG7tXpZiouFeBoRibo1qkk/09XVRb0aVfHwWbha+dfvPghrSwt0a9sc5UHuWtfuhaJbm/InU3SOzrY6CI8TKZwj7bvbq37jcHfQZUoaecJjRXBz0FH7G/X8Bay9ydrnfWLVsCZSzl1X+Cz59BVYNxTHTdPR14dl7WpIOXtNVqC0FCnnrsGqYa1y63ewEbCXwYfPZQsG+QWliIguhJ+HofrxxsUAD8MLFMYbqsPPQzxGkZUAfVYslLVHcXEp+8zfy+ijGPu06f7Wpn6SjMNPXimNw/El8CpnHJY/hj0vX6kfu2kcJsVBSjnjsK2ljlieqLLzCU9N8wlHAZ4qyUP76uYgFcHBVg/WFnp48EzW5nkFpQh/Vchc1z50vR+qrwhylSJlpKhU++dZ8uPNI6Xx5kVMEXzd1I83NHY8eqE43jyOKFR7jKezHjycyh9vPpasVdq4vSkLFizA6NGj8emnn6Jq1arsvY0W1+l9VB1kOPDJJ59gzpw58PYu3038XeExcv6fQhYmy5cvZwqSTp3EcQNWr16N06dPY+3atahXrx77jLSQ7dq1Y/+TwsfV1ZUpUciChhQSdLFOnjyZfe/n54fFixejRYsWrG6y4iE6d+7MFDjEt99+i7///hvnz5+Hv78/U5SQhcqaNWuYFQqxfv16ZkVDypb27dtj4cKFmDFjBnr37s2+pxvp5MmTFTpPS0tLFgCY6iJlEv0lxQndYDk5OcjMzER4eDiTmSjvnEgLS/JFRUXB2dmZlSGt64kTJ9jnpFiRQMoqajuyxKFzoPMjixwqc+bMGTRq1IiVoxudlEUrV66UykH88ssv0n2yIOrSpQuzuqF2pfrICoc24ueff2Z1vg+rHFKcELTyJ092rkj6nTJmJjoQ6OqUeTDSfiVb2eDZv50pImKEFfJHJiRm3dlK9WbnlUq/U4ZiAjBZ8soe42jzboocCzPVbUP7ZCWkqW2Uz4GOqWQrm7D3b2PCXqYr2ja02svqUYpPQPvkj60KcxNdZg6fmaNohUQrQU72qicX5BMem1SM51HFH891Y6ajWhYN141MlrLHVLIVlImj06ulMbOsSEgtwaKdOSz+ydtdN7rq+0qFPLTvZCd7dN98UICUTBEyskvg5qiHvm3NmLz/7FLtnkQTZHE9Za9HiZxqZclRJYvsGr75sBCpmXnIyBHB1UEPfduYMlmW7S4rS0Z2NkpEIthYWSh8bmNpiVexCSrlCAl7hsNnL2PjXxVzNzp24SpMjI3QokHdcsuaGNLLgA6L4SAP7dOLuioojk5OQdny5nIuF4S/my4GtNRjLxE5ecD6k8XIe8+W84aOdihMTFH4jPb1Lc2ha2QIfWtL6OrpoTBJ0SWjMDEVpv7lTzYpbgpRZuzILpGORcpYmArE40122fHG2UF83TyPKmSrz4M7W2HHiUw21R7U2Yodp65ebRv7tOr+1qJ+opgp6p4Jku+UMZM+v5XaJU8ERxvFV5bmNQ3Qq4XcOLw7V/M4bPJ6PqE8N6iAPMrH0PzC0ebt18JJMUBkKPUT7Uu++5D1/tt9JT8/69SILGeKPop5lvwzUzkWVGauiC1eaRpvlMcoNt7I3d/ytKgtHm8ovhbn36GwsJBt8tACO23KkDHB3bt32fun/GJT27Zt2WK+OubOncs8Xej9jAwU/m24Iuf/KWR5QtYwTZo0kX6mr6+P+vXrIywsTKrIkSgbCHJ7IuULfU+EhIQwi5StW7dKy5DLEylmXr58iSpVqrDPyDVLAikzKlWqJDVLozpIkUIWOfKQQoJkJEVLfHw8c1+SQNYppJSpqHsVKUNIgTN16lR2U5GyhixaJNY9pJAhhU1FzunFixdM21q5smJsBhoYyO1LQn5+PrPEGTx4MFO6SKBzzcvLkyrH5AeMWrUUV0Xl240sbghqN3JPoz744osvFMpTX5GC7E0GsBJhIRoHmWNIJ7H5NLFEzQTxXQny00eAhz5+Wpuhtkxdfz0MbCMzK19x8L9dmahf1QCfdDSV7i/drTnA5NtSw1cf/h76zK9bHY2DjPFZD0vp/vxNMsu5fwt68WxUwxgHzpc97wbVDLTmuqF+oiDEEv7ZUzH3q7fl5qNCtvJHSqF29Q0xuocp/tySDeHruXPD6oYY1lU2pi3cpr5f35WL92TK29ikEmRkizBtuDXsrXPZC2CDQEMM6yKTZdH2f08Wcr2Sl4Umrd8MtYK9tS6SywlSWR65+fmYu3g1po8dASsLxeeFOshFq0OzhjCkJfv/kBfxIiw9UARTIx3U9RdgYCt9rDhchNz35w373mlSywSjesti5/yxPvlf+R16UVy4JQUje1ujQxNztmp9LTiPrXZLHvHaNvZpy/0dlatd/VSvij4Gt5eNw8v2/rvj8K3HRczqklyjKNju6G4m+HNbjnQcpmQGg9rK5hPLD1TcleZ907S2Kcb0t5Puz1udiP+SD91XhJEBWGwhUroduVaglfMsolENI3zaXTbe/LUl/YOMNw1rGOPghX+/H/4/M2/ePLaQLw8ZLJCHgzIpKSnsfY9CWMhD+0+ePFFZP71XkjEEhfH4UHBFDuetIYuWMWPGsBgyypCyQV5BJA8pc0gxIqmjTp06CooTCeTK9T4gtykygyMlDckSEBDAPiPlTnp6uoIVTHl9a5m4AAEAAElEQVTnREoegUDAtLT0Vx5yCZNA2l3S2lKMHnJPo3g6kvoJij0k+Uz+GHnk201irSRpt/c1gNVq/Q1MTL7FizjZS7K+QPxb9JKamStb1aEAbeQbrIqcvFKUiMjaQXG1hPYlK//0Mk4vdIumKgbWHNvbHM+jhZi/NYvFwYlMkD3I9F7LYk71yK2IUfA68ptWRW7+a1mUAtzRMcorPOUREl6El+tk50yZOsTnpYssubahffLT19Q2dA7yiNtXpNA2f0+xVijzRS8zPI8RYsE2cSwI+QwiUlnMdNnkXlqvmS7zi1dFdp4IJSWlr1etixVWnJRXcIn6gcYsyOWV+/llvgt+XqQ11w3rJ7lML3qvn2zK/UTXAMWv0CwLrbCVaLxuyOS8oEjEMmjQ7y6YZMVi79wJE7cpxcl4EZOuUh75VT3aj1LTNqyvpPLIt41iHcpIMmKQiwUpckKeFWFObJqKa5isExTrpaw5GmUxe0tZrAVlFDlW5uYQ6OoiLUNRAZiWmVnGSoeITUhmQY6nzVsk/Uz0+g2yWb+R2L5kHlzl4uAEP36GqLgE/DR1LCoCWcjQOYoDmMrGGtqna0MVOfmAmZHitUvls5WseijOTlo2baWIThZiSh99FnfnUuibxefSBFnfkFWOPLRfnJkNUUEhilLSIRIKYehgq1TGFoUJipY8BMVXCY+SWUZJAqXS2CE/3pAFSGSc6vGG7j023ihZAtB4QxYmEh48L8Dk3+PZKjb1AbmCLJ/lgush4utR68Y+Lbm/o2K0q59Cw4sRGS97CZcEpi0zDr/OKKSKHOnzW3Ecpn1lK0LJOJycQW6zufjrS0sWz+XOE/F5PogoZm5TyvKIx/TSN5JHOWAuzS8q6ppD3HmUh/D5sTJZXveTFfVTluy3aT8yrpx0ThqQ9Fd59X7ovjLUByb0NWMxYlYcyIX8VFab5lnE/SeFiIhJUXFPKd6bZG33StMzs6TsM1O5Dgn1qonHm6vBZcebj5HS8qKO/0fMmDGDxbyRR5U1zttAYTyGDh3KvFsohMeHgity/p/i4+MDAwMDFpPGw8ODfUYWOhQLR+JWRNy4cUOqlCGlx7Nnz6SWNrVr18bjx49ZbJ23heog9yoyQ7OwKDt5l1ij3Lx5E82bi2MiCIVCpkihY98kTg65dEmUNqTIoWDBdE5kqSMvj6ZzIqsZ0tCSZYymIFZkfrd582ZmkdOqVSumNCLLH/KxpEGDXLPkFUhvCvUBtcmwYcMU+upNB7DJC3NYZoLkIsUHC7lGBHjqSx+aZLpMPs/yq4PykDnzq3ghqnjqS1NC0zBO++fuio85fj0fl0MULYLmjLZi6Z1Dn4snGIXFQGGm/ASglD2E/d30EJtcJF3V8awkYMEO1ckSnSRCZTc9hEYIpbLQ/mUN5ryqUNU2ma/bRjK5IXnIh/zi/UK18lCGDWoLiTmvzutJxfnX7XniRj4L0ifP7FGW2HU2j024CPIpL1BKdUmTtmrehoh6HWCRfM99XA1w9qbqlUeK+f0yrhjVfAxwN0z82/S8pWCVp2+UPaZlHRPce1LAJiUVaZv/7LpR108eemX66VKw5n6iYxT6yVMfF17LogpqP9okiixpXxWV7auq3vpSpRZrG1d9lkpYbdvECVHF2wD3nxbJ2sbbAOduqZ/suVcSK4AlbhJiWUrLyFLFywDRifkyWVzUn6esn5Rk8dLHudsaZHEUTzFUTVz19fXg7+OJuw8eo0WD2lJF9Z3QMPTp1KZMeQ8XJ2z++yeFz1Zt24e8ggJM/mwwHG0VFX1Hzl5CgI8n/DxliwqaoHOkQMU+zros+5TkHGn/Rpjql4eoJBF8nHVw7bHsMyofnaT5BY8U85qyr7wNGTeCYd9JMW6QXZvGSL8hXhksLS5G5r1HsGvdSJbGXEcHtq0a4dWyLWXqo5gUBYWKLynpWSUI9DNiGY2k442bIU5fz1E/3sQWIdDXCHce5cvGG18jnLpW9hjJOEPjEb2AkZJCG8c+rbq/taif6PmtnKqa7n1/d6Vx2EnAAtxrGof9aRx+/eyjdqH9C/cKyx2HJYs/EnkK1chTZj4RomE+kVjCjlGYT7jTs6Ti8wnqp4Qy/SREYGUjqYKF+snXwxAnr729RUpSqrBC9X7IvqJ6KNW3UAgs25crtZjSxnmWpvGmKo03rxU3RoZ0fxvg7O08tfcUKU5pjLoXJv5Nuj6pjjMqxqgWdYxx76nq8Ybz/jBU40alClLG0IJ9YqKi9Rztk2eJMuRFQkGOKZasBMniO3mSULgNevd+33BFzv9TKNsSBR0maxFymSJlzR9//MHcfsivj6xXJL5+5DJEpmQUfJcubEkqNYp3Q5msKPgvZX6iOkkJQnF2li5dWiE5KB7Nn3/+yTJV0W9RDJ5Xr15h3759LBgz7U+aNIkpXcj9iaxpKPhURoZ6NwtlrK2tmZsSWf1I5CKlEMX5IeWVvEKlvHMilyqSmRQoFIiYFDuUlYoyTNFvUBwbCTQA0G8OGjQIrVu3Zsocuvkppg7F6aEbnDKFkfsYKdRIkTV8+PAKnRO1yYgRI5iLGbnH0e9Q4GRNgbVUDWACPdUrdGdv5aNLE2MkpZewTAM9mpuw1T3JhJP4arAF2z//+uXv9K0CfNbNDJHxJcxKgTIIUIrvq6Hih5g4i03ZF6K0rBJmOaAOygbRob4hkjJESM0UoWtjQ2TmlkonVcSE3iYIjSjGpRDx+Zy/V4gh7Y0RlViCVwklaFnbgK123HgsO19aYSOrBPvXWS6cbQUoKC5lwRI1xa84e7sAnRsbISlNLHePZsZMgUEZgCRMGWiO+8+KpJOZM7cKMKKrKctoQRtlVDIwAMvUpLltxOesjhNXc9GzlTkSU4Wsr/q2NWcTDsmLCjHjM1vceZyP0zfEE47jV3Mwpo81XsYWIyKmmGVWoJSmygH2KJ6Qv6fBG7kxaNN1c/ZOATpRP6WLWBDM7tJ+kl0DkweYIfh5sayfbhdgRBdTds1QP7WmftIHy4IhCcJYp4oBC+hMEy5rC12WJpUymDyUC3SqitM389G1mSkSU0tYcORercxY21AWDAlfD7Vi+xLlyMkbeRjV0wKRcULWX+0amoitBF6v2lEQRnLzIIVWTp6IxdAY2MEcTyPFmXN01KQFOXMrH12bmiCRrmGSpaVpWVmGWIpluSPup1M38jGyhzki44tf99PrFcQQ8fe00knpVh+QLPkiuJIs7czw9JVYFlUM7NYePy9ZwxQuVf28sfPIKRQUFqJra3HKbHKlsrexwtgh/Zh7lI+7q8Lx5qZi1wDlz3Pz8nHu+m18OXwg3oSrD0vQp5keYlN0EZNcisbVBCyw7N1nYvn7Ntdj1+Opu+L9649LMKqzPst29TRahBreunCx08GBq0KpuXzLIAGeRIlYjA0TIx00rCKAhQnw8KWo3PTjpr4yJZSJlyssggJQlJaJguh4+P/8FYxcHBHy6bfs+1erdsBj3CcImPcNojfshV2rhizd+O3uY6R1vFy4HkHrfkfG3YfIvB0Kz4nDoWdqjOiN+yrUPsevZKFna0skpAiRlCZEv/aWTGlA1gYSvh/tgNuP8qQKgKOXszG2vy1zwQmPLkSnpuYwNNDFxTsyBUGLuqYsNgTFk6jsYYBh3a1x/Eo24pOFH83Y91/c3x9DP527W4jOjQyRTM+ETBG6NTVmL+k07kqY1N+U7V+8Lx5nz94pxPDOJuylmZ4LresaMosOyowkHYcD9JlbFRuHzWXj8CO5YPuqOH+/EB0bGDELQco82KWxETJzSqWKCOLLvqZsX6KoOXe3CEM7iucTZOHTSjKfeFRUZj5BweQJZzsBUwikZ4stl1Rx9GIW+rSzQkIy9VMxBnSyZv10Wy4j1Q9jK+HWg1ycuCJWwrCMd3JxySi4saezAXLyxGN5Rev9UH1FChhKC6+vr4P1R3OZUsn49TSUxkR1ERK0aZ5FnLyeix4tzZCYJmTt06eNeLwha0EJ346wYePPmZvidj5xLReje1uxe5ss6do3MmHjDWWqk4es6/w9DPDX5n/fhYtTccjYgTxG6P1O8t5L7220r5zUh6D30wcPHih8NnPmTGZIsGjRIpYF+d+AK3L+H0PKEbooyRSMLjRSClAQYVJ8yJchpQFlZKKgwYcPH2YXN0GKC8q0RAoesk6hWDKkbRwwYECFZaDo35cuXWIKFApmTHKQy1GbNm2kFjpkMUNxckjJQZYulL2JAgiTAqSikLKGfBYl2alIeUXWMaRZpbg/EipyThTUmIILk1yxsbFMuUXKn65du5b5XdLCbt++nR0vUeb89NNPzG2MXJ0o5g4FdiZLoO+++67C50P1kfaXlF0UT4iybJFirqJBoMvjxI0CGBjoYGgnM/by8Ty6GIt2ZimspFAAUAowJ+FOWBHMTfLQo7mx2AQ2UYhFO7PLBJ97U87cKYKBng4GtTFik4AXcSVYtj9PQRaaPJkay0xY7z0Twsy4AF0aGYrdsFJEWHYgTyFgYdMaBujcUKbYmtxf7KO95VQ+S1uuDkpdSm0zpKMpaxtKRb14Z7aiPNbUNjJ57jwpYm1FygRqG5qE0zHKARTflCOXc9jE4LOeVjAx0sWzV0X4Y0Mqc+WQnySYmwgUgmdamGayiQiZ0tOqLR2j7D5EKXlJWfJALsvLx3TdnLpZyCbbn3QwkfbTkl05irJQP8kFpr37pBjmJvno1tRI2k90jKSfiktK4eeqx1KuUp00MaTAhBQfp7y+PH41j8kzvJs56ysKoLpgS4aCPOK+kl03tx8VwtwkBz1bmjKTbHJ9+ntrhtRsXVhSiqpeBmjXQDxBTMsUv8gevqR5wn78Wj5Tlg3vQrLoMFn+3pap1DYChWv49mOSRQc9W5gyc3HqJzpGJgtQ1Usf7UjBI5HlSSFLc66Otk0aICMzG6t3HGAZpvy83LFg5lewsRLHJ0hMSYXuW5hon75yk70gtGsqi61WER68FMHUSIg2tfVgbgzEp5Viw6liaSwbCrQp/+IRlVSKXReEaFtHgPZ1BEjNKsXWs0KWZpygsvaWOqjdWh8mRmL3LUrru/pYsbSMOizrBKLR2c3S/arzxc+H6E37EDpyBgyd7GHsJo6dRuRHxjClTdW/ZsDzy2EoiEnAgzEzkXL6irRM/O7jMLC3QeXZE2FYyR5ZIWG41XUUipQCIKvj8IVs9nI/qo8Nu4afRhbit7VJCuONo60ezE1l482NkDx2L/Vtb8mCrb6KK2LHyFtpOdnrYWAnK5gZUywlIQ6cy8Kxy9kf1dinTfe3NvXTqVuFbKyhGGYmhjqIiBViyR5Fqwx7KwHMjGUf3H1aDDOTfHRtQs8EsTssHSMdh4Wl8HXVY+mypeNwDLnZysZqdZy5XcT6aVA7YzafiIgtKWMlQooi+efCvWckjw5T+kjcuv/ZJ5OHaBZkgM6NZNm7pgwQu9pvPpGndj5x8FwmU8yM6W8LE2NdPHlZiF9WJihkBnO0U+wnbzdDzJkgu+9H9BS7Sl64lY1/tqdUuN4P1VekfJRkvfpptKLV/fcrs5gSRdvnWcTRy7nsuqHYOeL7u4gpesuONzJ5bj4sgLlpFnq3MWOujuT2+eemtDLjTfPaJmwBUT4L38dOaal2ula9KeTFQO+e9H5MMWQp5iklC6IsVgQt6tM7K73PUSIaylAsD73fEcqfv090SisaMZbz/wpSOJBLELkeSS5Ezv8eo3+t2AT+Q2Fk8t8GJZWnqED9KuN/QW629kRGNTZ9Pz7F7wsB5R7VEooKtCfjhDqLnP+KP3o9h7aw4FYdaBONx8iC2//XbJlyGtqEgEybtAQDTbm/PzD5WhYt28petXv8fwFlDNImEqP//QDdFcXOWTFGzH+NSFOqsQ9Mfq72KFM2/SRT2H1shEe8hDbi6+P1xseQNwZ5jiQkJDCDBspkLEnAQ8YBnp6eLAO0KshzgjxIDhw4gH8L7XkicTgcDofD4XA4HA6Hw+H8x0yYMEGlK5XE6EET6hQ87xOuyOF81FDQYHKRUgfFt5HPoMXhcDgcDofD4XA4nPdPKbTHSvp/Ha7I4aiEzMU+Bq87ygRFsW80fc/hcDgcDofD4XA4HM7/ClyRw/mooWDC75L+nMPhcDgcDofD4XA4nI8JrsjhcDgcDofD4XA4HA6H806UQruCjf8vw53YOBwOh8PhcDgcDofD4XA+Ergih8PhcDgcDofD4XA4HA7nI4G7VnE4HA6Hw+FwOBwOh8N5J7hr1YeDW+RwOBwOh8PhcDgcDofD4XwkcEUOh8PhcDgcDofD4XA4HM5HAnet4nA4HA6Hw+FwOBwOh/NOcNeqDwe3yOFwOBwOh8PhcDgcDofD+UjgihwOh8PhcDgcDofD4XA4nI8EndLS0tL/WggOh/PfcOFhPrSJ4BdG0BaaB6RBm/Aoegpt4ZFOELQJgY72PMbqxO+DtjAvdhC0icT4HGgLsS8SoE2YWZpCWxjydztoE35PTkNbiMypBG3BxzwG2sTTDDdoC9Ep+tAmmnnHQVuIzLL/r0XQWlzN06Et1PBzwMdKWEQstJEqPi74X4Nb5HA4HA6Hw+FwOBwOh8PhfCRwRQ6Hw+FwOBwOh8PhcDgczkcCz1rF4XA4HA6Hw+FwOBwO550oLeVZqz4U3CKHw+FwOBwOh8PhcDgcDucjgStyOBwOh8PhcDgcDofD4XA+ErhrFYfD4XA4HA6Hw+FwOJx3ohTctepDwS1yOBwOh8PhcDgcDofD4XA+Ergih8PhcDgcDofD4XA4HA7nI4G7VnE4HA6Hw+FwOBwOh8N5J7hr1YeDW+RwOBwOh8PhcDgcDofD4XwkcEUOh8PhcDgcDofD4XA4HM5HAlfk/A/y448/ombNmtL9ESNGoGfPnv+pTP+rREZGQkdHB8HBwe9cF9Vz4MCB9yIXh8PhcDgcDofD4Xxo1ypt3P4X4TFyOJz/QNFGChtl5U98fDysra2hDZw/vgOnD25EZkYqXD0rY+DIb+HlV11l2cun9+LGxSOIiwpn++7eVdHzkwkK5Qvy87B/yyIE3zqP3JxM2Dm4oFXnQWjRoV+5sjy8uhXBF9ciLzsFtk4BaNpzJhzda6gsm5bwHLdOLkZK7CNkp8ehcfcZCGo2/J3qVObU0b04vG8rMtPT4O7lixFjvoJv5aoqy966dgEHdm9CYnwMSoRCVHJ2Q5eeA9GsdSdpmT3b1uD6pTNITUmCnp4+vHz9MWDoGPj6VytXlr3Hz2LrweNIy8iEr6c7vhr5Car6eZd73OkrNzH77xVoVq8Wfp8+Ufp54z6fqiw/fmh/fNJTJrMqzh/fiZMHNrFrxs2zMgaNmgYvv0CVZS+d3ofrF+iaiWD7Hj5V0ItdM4EK18y+LYtx/+aF19eMM1p3GYSWHfqiIpw9tgsnpPL44ZNR0+BdWbU8d6+fw5G965AUH42SEiEcndzRoccQNG7ZRVqmtLQUB7avwKUz+5GXmwPfgCAMGzMDjs7u5cqy4+IdbDx9AylZOajs6ojp/dujuqeLyrIHr4fgh81HFD4z0BPg9uLp0v3UrBwsPHAe18NeIDuvALX93DG9fwd4ONhUqG3q++uicTVdmBkDiWmlOHZLhNjUUrXlq3rooHVNAazMgLQs4PS9EjyPlZXv2ViAWr6K60LPY0XYcrakQvJ0a2qEpkGGMDbUQUSsENtP5SEpXaTxmBa1DNG+gSEsTHURk1SCnWfyEBkv+73BHUxQxUMPlma6KCwuxYtYIfZdyEdimuZ6iU+62aF9M2uYGusiLCIfy7bFIz6pWG35an7G6N3eFj7uRrC10scvy6JxIyRHocygrnZoXs8Cdtb6EApLER5VgM0HkvAsskCjLH3bW6J1fTOYGuvgaWQR1u1PQ0KKUOMx7RqZoVsLC1iaCxAVX4QNB9MREV0k/d7BRg9DulrB39MQeno6CH2az8pk5qhuG5umdeE9dSQsawfCyNkBd/qMQ+KhsxplsGleH1XnT4dZVT8URMcjfN5yxGzar1DGY+xgeH81EoaV7JEV+gSPJv+EzNsPUBGOHj6IfXt3Iz09DV5ePhgzdjwq+weoLHvt6mXs3rkd8fFxEApL4OzijJ69+qJ1m3bSMvn5+di4fg1uXL+G7OwsODpWQrfuPdGpS7dyZbl0YjvOHt6ArIwUuHj4o+9nM+Dpq/p5efXMHty6dBjx0c/Zvpt3VXQbNEmh/OZ/vseti4cUjqsS1ATjvl9RobY5fPgw9u7Zg/T0dHh5e2Ps2LHw9/cv97iLFy7g999/R8NGjfDDDz8ojH1bNm/GiRMnkJubi6pVq2L8hAlwcVE9hslz5dR2nDu8HtmZKXB290fvEd/BQ03bXD+7B7cvH0JCjHgu4epVFV0GTFJbfteaObh+djd6Dv0WLToPRUUIvrQVd86uRW5WMuxdAtCq7yw4eap+9qfEP8e1o4uRFP0IWWmxaNl7Bmq3GqG27lunVuHK4b9Qq+UwtOrzfbmyHDuyHwf27kRGeho8vXww6ouJqOxfRWXZ61cvYe+urYiPj0WJsAROzi7o0bs/WrZur1AuOuoVNq9fhUcPQ1BSUgI3dw9M+24O7B0cP6p+0iZ5ThzZh0P7trN+8vDywWdjJsPPX/Wc7+a1i9i3azMSWD/RnM8V3XoNQIvWHaVllv79Cy6ePaFwXFDt+pg5969yZeFwlOGKHE650EOcHgh6eh/X5VJUVAQDAwN8LFSqVAnawO2rJ7Fnw18YPOZ7pow5e2QrFv80DnOWHISFZdkXxWeP7qBe047w8Q+Cvr4hThxYj0Vzx2L2wr2wthVPHnZvmI+nD2/js0m/wNbBGY+Dr2P76nmwsrFHUL2WamUJDz6Gq4d/Q4s+P8LBPQihlzfiyJpRGDTtOEzMbMuUFxYXwMLWDT5BHXHt0G/vpU55rl8+g81rFmPk+G/gW7kajh/aid9+mIK/VmyHpVXZtjEzt0Cv/sPh7OrB7p97t69ixaJfYWFljaDaDVkZJ2d3jPhiKhwqOaOosBDHD+7Erz9MxsJVu2BhqV6xd+bqTSzesAPfjBmGan7e2HnkNKb89Be2L5kHG0sLtcfFJ6Vg6cadCKpSucx3h9csVDzf+6GYt2w9Wjaso7Fdbl85iV3rF2DImO/gVbk6zhzZioVzx+OnJfthoaJdnj68i/p0zQTQNWOAE/s34O854zBn0R5Y2zqwMrs2/IUnD25j1OSfpdfM1lW/wcraHjXrt9Aoz60rp7Bz/QIM/eI7prw5fXgbFsydgF+X7lMpj6m5Bbr2/QxOLl6sn0LuXMa6JXNY+wfWaszKHN+/EWeO7sCoiXNg5+iC/duW46+5E/DL4t3QNzBUK8uJO48xf+8ZzBzUCdU9nbH13C2MXbIDB3/8ArbmpiqPMTMyxMHZX0j3dXQUx+PJK/dAT6CLhWP6wczYEJvO3sSYxVuxb9YYmBhqHvOqeeqgQ11dHL5RgtiUUjSsIsDQtgIsOShErgqdgpu9Dvo2E+DsfRGexohQw0sXA1sKsPKoEEkZioqbA1dlihRh+foSBiljWtUxxMajeUjJFKF7MyN82d8Mc9ZkQahGD1QnQB99Wxtj26k8RMYJ0bqu+JgfV2chO0+sYIpKEOLWoyKkZ4lgYqyDrk2MMGmAOb5fkYlS9Tor9Olgi66tbbBwQxwSU4rxSXd7zJ3ojnE/vkCxUPWBRga6eBlTiNNXM/H9WFeVZeISi7BiewISUophqK+DHm1tMXeyOz6fGYGsHNUn2q2lOTo2McfynalIThOiXwdLTB/pgG/+ikOxGl1OwyATDO1mjbX70hAeVYhOzSzYMVP/jENWroj99nej7fEqrhg/r0pix/Rrb4mvR9jjh38SVbaNwNQEWaFPEb1hL+ru+QflYezpinqHViJq1Q4ED/satq0bofrKn1EQn4yU01dYGad+nVDlzxl4OH42Mm6FwGvicDQ4uhYXqnVEUXKaxvovX7yANatXYvyEiagcUAWHDuzDD7NmYMWqdbCyKjtmmptboP/AwXB1dYOevj5u37yBRX/Ph5WVFWrXqcfKrF29AqEhwZj6zXQ4ODri/r27WP7PYtjY2qJBQ/EYoIq7105g/6Y/MWD0LHj41cCFo5ux7JcxmLXwMMwtyz5Pwh/fRp0mneDtPwN6+gY4c3Adlv08Bt8t2A8rG9nLdpWaTTBk3M/SfVLyV4SLFy9i9apVmPDllwjw92eLRrNmzsSq1avZ+aojMTERa9asQbXAssruPbt349ChQ/hq6lQ2T9m8aROrc8XKlRrnWPevH8eBzX+g38gf4OFbAxePb8bK38Zgxl9q2ibsNmo37gyvyjVZ25w7vA4r5n2Ob/88oNA2ROjtM3gVHgpLa/HzoiI8vXsMF/fPQ5sBc+DkEYR7FzZi37KR+HTWCZiYq5hPFOXD0s4VlWt1xMV98zTWnfAqFKFXd8DOuXyFGXHl0jmsX70cX0yYwpQ3hw/swdxZ07B01Sa113DfAUPg4uoOPX093Ll1HUv+/h2WllaoVac+K0NKnu+mTUTb9p0wcMgIGJuYIPpVJPTLmQdrWz9pkzxXL53FxjVL8fn4qfD1r4qjB3fjlx+mYtHKbbBU0U9mZhbo3X8YXNzc2T1799Y1LFv4GywtrVGzTgNpOfp/3OQZ0n2aB3E4bwN3rdJSRCIR/vjjD/j6+sLQ0BDu7u745Zdf2HfffvstKleuDBMTE3h7e2PWrFkoLi5+o7rnzZsHLy8vGBsbIygoCHv27JF+f+HCBebmc/z4cdSpU4f9/pUr4smXOiIiItCjRw84OjrCzMwM9erVw5kzZ6Tff/fdd2jQQDaISaDfnjt3LvtfKBRi4sSJbLJha2vLznP48OEVdgtr2bIlJkyYgMmTJ8POzg4dOnRgnz98+BCdOnVicpF8Q4cORUpKivQ4Ovfq1auztqDfbdu2LVt1krQVyefq6sragVzWaFVKHRs2bCgzWaKJFLWn5Ps5c+YgJCSEfUYbfabKterBgwdo3bq1VK7PP/8cOTk5ZVzm5s+fDycnJ1Zm/Pjxb3QtqOLM4c1o2rY3mrTuCWc3H3wyZiYMDI1w7axqt6+Rk+ehZccBcPMKQCVXLwwbO5u9bD55cEta5sXTEDRq2Q3+gfWYNU7z9n2Zpc/L5w81yhJyaQOqNuiHgHp9YOPoixa950Bf3whPbu1VWd7BrToad50Gv5pdIFAz8X3TOuU5emAHWnfojpZtu8LV3Qsjx02DgaEhLpxWtKCQULV6bdRr1AIubp5wdHJFp+4D4O7pg6ePQ6VlmrRsj+o168GxkgvcPLwxZNRE5OflIipSbK2ijh2HT6F72+bo2roZvNxcMG3MMBgaGuDI2ctqjykpEeHHhSsxakBPuDjal/ne1tpSYbt86z5qBwbApZLmSc/pw1vRrF0vNGnTA85u3hgy5nt2zVw9d1Bl+dFTfkGrTv3h7uUPJ1cvDB/3A7tmwkJl10zEk1A0ZtdMXWaN07x9H7h6+uFluOZrhjh5aAuat+uFZm26w8XNG8O++I7Jc/msankCAuuiTsPWcHbzgoOTG9p1GwxXT188CxNbzZFsp49sQ7d+I1GrQUtm4TNq0hxkpCXj3s0LGmXZfO4mejepiZ6NguDjZI+ZgzrDyEAPB66FqD2Ghgs7SzPpZmthJv3uVVIaQl/G4vuBnRDo6QxPR1vMHNgJBUVCnLjzqNy2aVxFF3efixAcUYrkTODIjRIUl6CMRY2EhlV0ER5XiquPREjJBM4FixCfVsqseuQhpUtOgWwrkBmAaKRNXSMcv16AkPBixCaXYP2RXFiZ6aJmZfUvrm3rGeFqSCGuPyhCfKoI207mgYa9xtVlk+ErIUUIjxEiNUuE6MQSHLpcABsLXdhaap72dG9jg13HUnAzJAeRsYX4e30cbKz00LCmudpj7j7KxZaDybgRnK22zMXbWQh5kseUQ2Qls2Z3IkyNBfB0Va8E7NTUAvvPZuLu43xEJRRj2c5UWFsIULeaidpjujQzx7mbObh4JxexSUKm0CkqFqFlPfE1VNnTEPbWelixKxXRCcVsW74rFd6uBqjmo1qW5JOX8Gz2QiQelD3TNeHx+UDkv4xB2LTfkfPkBV4t24qEvSfhNUlmzeA1+VNEr92FmI37kBMWgQfjZqMkrwBuI/qUW/+B/XvRoWMntG3fEe7uHhg3YRJ7Pp8+dVJl+eo1gtCocVNmneDk5IzuPXvD08sbjx/J7pewsMfMQofKkjVOx05d4OXtg2dPn2qU5fyRTWjUpg8atuoFJ1cfDBj9AwwMjHH9vKL1kYThE39H8w4D4eoZgEou3hj8xRyUlorw9MFNhXJ6egawsLKTbiZmlqgI+/fvR8dOndC+fXu4e3gwhQ61zalTp9QeQwt1NN8cMnQonJQWlJgl4oEDGDhwIBo1asTmjVO//hqpqam4fu2aRlkuHN2ERq37okHLXqjk6sNezA0MjHDzguq2GTrhdzRtPxAungFwdPHGgM/FbfP84Q2Fchlpidi3YR6GjP8duoKKLzDePb8egY36I7BhH9g6+aLtgDnQMzDCw+uqn/2VPGqgRc9vEVCH5hPqX7SLCnNxbOM3aDfoZxiZVKyfDu3fjXYdu6BNu05wc/fEFxO+gqGREc6eOq6yfGCNmmjYuNnra9gF3Xr0ZVY8YY9lz8Ntm9aiTt0GGP7ZF/D28WPl6jdsolIxpM39pE3yHDmwE206dEOrdl3g5u6Fz8d/zeYS504fVVm+Wo1aaNC4OVzdPFHJyQVdevSDh5c3njxWtDTU19eHtbWtdDMzU/98+RgpLdXRyu1/Ea7I0VJmzJiB3377jSlpHj9+jG3btjElBGFubs5e/unzRYsWYfXq1fj7778rXDcpcTZt2oQVK1bg0aNHmDJlCoYMGcJWcuSZPn06kyEsLAw1amh2OyEFQ+fOnXH27Fncv38fHTt2RLdu3RAVFcW+/+STT3Dr1i2m8JFAvx0aGorBgwezfTLp3bp1K9avX4+rV68iKyvrjWPGbNy4ka0Q0fF0fhkZGUwZUqtWLdy5c4cpYWjlqX///lJ3pkGDBuGzzz5j50lKrN69e7PJC0Ht+9dffzFlCclKyqHu3bvj+XOxWfSbMmDAAEydOhXVqlVjv00bfaYMKZLot8jV6vbt29i9ezdTjJGiSp7z58+zNqW/dO50XUgUQ2+DsLgYURFhqFJDpnTT1dVFQI0GePFMpnzQRFFRAXNPMZWbeHr7ByHk9gWkp9KKbymePriNxLhXqBrUSG09JcIiJMc+gqufbDVUR1cXLn6NkPjq7WISvUud1DYvw58iMKiuQtsE1qyH50/LVy7QeT8MuYP42CgEVKup9jfOnTgIE1MzuHv6qq2ruFiIpxGRqFujmoIs9WpUxcNnYvNiVazffRDWlhbo1rZ5ufKSu9a1e6Ho1qaZxnIk8ysV1wztRzx9w2vGXGZJ5BNQA8G3LyI9Nem1YpCumShUC2pYAXmeoGpQfQV5qtaoj4in5btt0G89Dr2FhNhX8K9am32WnBiLzPRUVA2SnaOJqTm8/QI1nmOxsARhUfFo6O8lJ4sOGgZ4IfRljNrj8gqL0HHmErT/bjEmrdiF8LhkhToJQ309hTrJ/ep+hPo6CYEu4GSrgxfxMrML+o/2yfJGFa72iuWJiDgqrzh98Kykg2/66eHLHnro2kAXxur1E1LsLHWZ61NYpMy8hBRAL+OE8HbWU3sO7pUECHslO4akC4sshreL6mMM9MVKnuSMEmahow5HO33YWOohOEysyCfyCkR49jIfAd7GeF/oCYCOzayQk1eCyOhClWUcbARMafPwucxMKr+gFBHRhfDzUN24AgHg5WKAh+GyY+hRRnX4eYhfRPX1aEJL15GsT4uLS9ln/l5G7+X8rBrWRMq56wqfJZ++AuuG4nFPR18flrWrIeWsnCKgtBQp567BqmEtjXXTQkV4+DME1RTfm5L7u2bN2nj65HGF7u+Q4HuIjYlBtUCZ60WVKlVx8+Z1pKaksDJknRMXG4NatdVbIwqFxYh+8Rj+1RsqyEL7kc/UK2rlKSosYC4Y8s9LIvzxHcwY1QI/TeqGnat/Qm62nPmbprZ5/lwhRqK4bWriSViY2uO2b9sGK0tL6eKXPAkJCcxFq2YtWb+YmpoyV62wJ080tk3My8eoHKjYNn6BDfHqecXbRiQUKiixaHFt6z8z0KrrCDi5qX9Gqnr2J0Y/goe/4rOf9uMj7+NdOLdrLryrtYBHgHrLLeV+imDXcB2FtqnBruHylfHs+gy+i9iYaFQNrCFtlzu3b8DZxRVzZn2D4YN7YdqUsbh5XfMirLb1kzbJQ/30IvwZapTpp7p4VsF+ehB8B3Ex0agSGKTw3aMHwRj5STdMHDMYq/6Zj+yszArJxOEo83H5yvw/ITs7mykQli5dyixSCB8fHzRt2pT9P3PmTGlZT09PfP3119ixYwemTZtWbt2FhYX49ddfmVKAVlcIsuohi5uVK1eiRQuZywJZorRrJ/Mh1wRZ1tAm4aeffmIrQ2SOS8oHUlzQ96SQIuUUQUobstIhqyNiyZIlTIHVq1cvtk/nf+zYMbwJfn5+bGVJws8//8yUOHTOEtatWwc3Nzc8e/aMKaDIEoiUNx4eHux7ss6RQAocsgyi1SiJsomUJgsXLsQ//5RvYq4MWdeQZRC5b2hypaJ2KigoYAo3mjRJ2oOUYySDRKlHih76XCAQICAgAF26dGHKtNGjR6vse9rkKSoSwUDOLSQnOx0iUQnMrRTNVy0sbZEQG1mhc9y3eSEsre0VXuwHjpqOLSvmYvrnHdhKiK6ODoaM/QGVq6mfJBfkpqNUVAJjJXcnEzM7ZCS9rJAs77POrKwM1jaW1oquOeRSFRfzSu1xFE9l3IgeEBYXQVdXgE/Hfo0atWRKBuLeratY/OcPbAJiZW2L7+YuhIWlejP4jOxslIhEsLFSdKGysbTEq9gElceEhD3D4bOXsfGvOagIxy5chYmxEVo0kCmuVJGTLW4XZZcl2q/oNbN302LmMlVV7poZNOpbbF7+M6aN7giBQI9ZrA0dO0vjNUNkS+RRMsG2sLJFvAZ58nKzMXVUJ9ZPOroCDP18OqrVFE8mszJSxXVYlj1HisGjjvScPJSISmFroehCRS5VLxNVH0cWNnOGdIWfiwNy8gux8cwNDJ+/EftmfQ5Hawt4VrKFk40FFh88j1mDO8HYwIBZ/SRmZCM5UzEuizImhqQI0UFOvuLnOfmlsLNQrcgxMxJ/r1C+ACy+joTwOBHCouh8S2FjroM2tQQY0kYHa46XaHRjsjAT/ya5/MhD7lEU+0alPCY67BxUHVPJVlAmjk6vlsYwMtBBQmoJFu3MQYkGly9rC/GUKCNL0dWJ9q0t3326VK+6Gb4Z5QJDAx2kZwrxw8IoZOWqdqui+DZEppLbVWZ2CazMVbeNhakAAoEOK6NwTI4Izg5iC6fnUYUoLCrF4M5W2HEik4V/HNTZih2nrt43xdDRDoWJMqtXgvb1Lc2ha2QIfWtL6OrpoTBJ8R4oTEyFqb/mGF9ZWZnspUw5nhxZHcRER6s9jhZHRgwdyF7O6GVs7PiJCkoairGzdPFCjBg2iD1PdXR08eWkKQisrn4RKzdL/LyksUUeen4mxlXsGXVw69+wtLFXUAZVrdkUNRu0ha2DC5ITonFk+2Is+3Uspv6yhT1D1EGLXyrbxtoa0TGqlbyPHj7EyZMnsVTNfIaUOISqOiXfaWobZVcY2k+qYNsc2bYAFtb2qBwoW/A5d2gtdAUCNO84BG9C/utnv4mF0rPf3BZpiS/wtjy5exSJ0Y/xyTcyq/byoJd26idl1xy6hmOjxYufqsjNzcGoYf2k1/Dn4yajZi3x8zkzIwMF+fnYt3s7Bg/9DMNGjMG9u7fw+y8/YO68BQisXvOj6CdtkkfcTyVl3Oap32I1zPmon8YM7y2d840a+xWCaoldOIlatRugQeMWcHB0QmJ8LLZtWoVfZn+DX+YvZ2MPh/MmcEWOFkKWIfTC3aZNG5Xf79y5E4sXL2aWGBJFhIWF+pgY8oSHhyMvL6+MgobiyZDCQ566dTW/wMlDclAQ36NHjzIrE5KJggdKLHIkVjmkRCFFDmmqt2/fjq+++op9l5mZySxl6teXveDSgEauXfTAqyhUXh5yYSLFCylPlKH2I/NjamdS3tBqFO337duXTVpoUhQXF4cmTZooHEf7VO+/fQ2Q4kuixJH8LrXF06dPpYocUpDJD/zkYkUuWeosscitS57hY7/DiHEyxeC7cmLfOhZjZ+qcNQpxQ84f246Xzx5g3PRFsLV3wvPH98QxckjhU46FxceOkbEJflu0EQUFecwiZ8vaxXCs5MzcriRUrVGblcnOysC5U4ew6PdZ+Omv1Srj7rwNufn5mLt4NaaPHQEri4qZ8JKLVodmDWFI5gz/Isf3rcetqyfxzdxVCtfMuaM78OLZA0yY8Te7Zp49vodtq39jcZXkLWPeF0bGpvhxwXYUFuQxi5wd6xfAvpILc7v6kAR5u7JNuu/jil5zV2L3lXuY0K0l9AUCLPi8L37ccgTNvl7AlBoNArzQtJqP1JLwQ/MwUva7SRmlSEwXYnJvfXg6ivAyQfZd/aoGLAixhH/2aFY8vSs3HxUySx1SCrWrb4jRPUzx55ZsaeydFvUtMP4TJ2n5uUvVKwLeB6FPczHp5xewMBOgfVNrfPu5C6b+FskUL01qmWBUb9n9/sd6mRXW+yQ7V4SFW1Iwsrc1OjQxZ4q2a8F5eBFTpFHp9rFDiyiLlq5gL7shIfdZTJxKlZyYKxVx+NBBPH0Shlmz57LAsI8ehmLFsiWwsbFFzVqysfp9curAGty7ehwTf1ynMPZRDB0Jzu6V4eJRGXO+7Iznj24rKHzeFZoL0mLVxEmTYGlZMZegD8WZg2tYrJTxs9ZL2yb6xSNcOrEFU3/dLXVX/y/JTo/Hhb2/oM/4ddDTr4AJ4jtibGyCBUvWsGs4NOQe1q9ZhkqVnJnbFbkSEfUbNkb3XuIkEl4+vnga9ggnjx1Wq8j5X+snbZCH+unPxetQUJCPh8F3sXHtUjbnI7crokmLttKyHp4+8PDyxYRRA/D4wX1Ur/lh5xv/FqL/0QxR2ghX5GjphEMd169fZwoReiEnxQM9fMkah9x/KoIkxgopXJQzDpAftTzySoTyIKug06dPs0kBWdjQOZBChBREEsiFiaxb7t27x5Q80dHRKt2K3gVlmel8JVYsypDSg5QgJPe1a9eYDzlZBX3//fe4efMmiznzptAqifLL1LvGrNEE+dnKQw8pdYovsnaSKM4k3AhXLGtmbs1WELKVrAyyMlNhaWWnUZZTBzfixP51mDx7JYt/I4GsTA5sW4Kx0xageh2xSw99Hx35FKcObVKryDEytWaWEfk5irLk5aTAxFyzLOp4lzotLKxY21C2KnkyM9JgpWSlo3xNUOYCwtO7MuKiX+Hg7k0KihwjI2NWhja/gEBM+bw/zp8+gp79hqms08rcHAJdXaRlZCl8npaZWcZKh4hNSGZBjqfNWyT9TPT6Om3WbyQLkOwqFwcn+PEzRMUl4KepY1EeZubidsnKUGwX2ldeqVaGslyRIuerH1eUuWb2b1uKcdP+Qo26zWTXzMtnOHVwk0ZFjrlEnkylazhD8zVM/eTo5Mb+p9g98TEvcXTveqbIkZxHVmYaUyTJn6O7V9mg0RKszUyYoiU1S+aqQ6Rm58JOyUpHHaS4CXB1RHSybPW7qrsTdn03Gtn5BczVysbcFJ/8sR7V3GVKCVXkFYJZCMlb0xBmxjrMykYVYusbmpSVKlnpqP+d9Bwgt6AUtuY6CoqckPAi5jYlQRI/nxQt8pYp5iY6LBOVSnnyStk5iC12FI9RttIhN62CIhHLgEW/u2CSFYu9cydMPCbfCsnBs5ey1XhyOyKsLARIz5LJSfsv1LhAvQlkCROfXMy2py/jsXKuD9o1scKeE6ksDk54VEIZWSzNBMjIFilY6kTGqX6mUBuWlJRKrXmkx5jpIkPOSufB8wJM/j0e5ia6rC3zCkqxfJYLrodozoZV4fNMTGFWOfLQfnFmNkQFhShKSWeuD4YOiuODoaMtChMULXmUsbCwZPeqsjVIRkY6rG3UxwKhY5ydxXMebx9fREdFYfeu7UyRQwtnmzeuw3czf0S9+uKxxcvLGy8iIrB/3261ihxTC/HzUmKxJ4Gen+WNfWcPbcCZA+swYdZqlulKE3aObuzZnJwQpVGRQwt6KtsmPR02KjJi0qIbLaDN+fFH6WeS+UvXLl2Y277EEofqtLGxUajT28dHrSyStslWGodpn2L+aOL8kfU4e2gtxn63Gs5ybfPiyT3kZKVh7peyhUiymDi45U8WEPeHJerjABm/fvbnZSk9+7NTYWrxdvOJxKhH7Pgtf/SWfkZWPzERt1l2rEl/P1BpQWX++hrOzCh7DZc3l6BsVRIlTUz0K+zdvZUpcqhOms9SvB15XN3cEaYUn0Wb+0mb5BH3k4DN8eShfiPLac39JJ7zeXn7ISYmEvt3b5YqcpQhJQ/9FmW6+l9R5HA+HFyRo4WQexApQshFZtSoUQrfkcKBXIBI2SDh1Sv1Jn7KUNpIUtiQpYy8G9W7QjFpKPiuxC2KFCiRkYpuDBQwmH6TXKpIkUNWQQ4O4pdHUkiRlQnFg2nevLk0AB8pfeT9vd+U2rVrY+/evcwFTV3WLVJ+kLULbZRyk9qX3MJI6eHs7MzOTb6taF/eckgee3t75hpHZtwSpZJymnGK4UPnpokqVaqwWDfy9dDvMv/7CqQRVQX1u7KyzsBA8W2MMnq4+1RB2INbqNmgNfuMFENPQm+hVSexe5kqTh5Yj2N712LSrGXw9FVMm02xTygGAJmql1V6qbe2ouCC9i7VEBN+HV6B4hWMUpEIseE3ENj4kzc48/dTJ7UNpQZ/GHqXBTCWtM2jkDto36X8AJ0SRKWicpV7VIbMctWhr68Hfx9P3H3wGC0a1Jb5yIeGoU+nspZ8Hi5O2Pz3Twqfrdq2D3kFBZj82WA42ipOHo+cvYQAH0/4eZafWpvahdKHU6DiWg1aSWWh/dad1StqKVPVsb3rMGnWUnj6VlV9zeiqumZKKyBPAMJCb6O2vDwPbqN1J3FsrIpQKipl8XYIe0cXWFrbMksdUvIQ+Xk5ePH8IVp1VJ8OXV9PgCruTrj5NBKta4qPE4lK2f7AFhWbsJEL3fO4ZGZxo4y5sZE0APLjV/EY31XzmE5uRfGppfB20sGTaHE7krrAq5IObj1VfS/GJJfCu5IObsiF2KDjo5PV37sWJmAxcrKVXLIKi4DkIlEZt58ADz2p4sbIAPBy1sOl4EK15xCVUMKOCXleLD2HAE99XLirPpU3LcTSpi+QrRTmF4qQr3QeaZlCBAWYsixUhLGRLip7GePYxfJjlLwpNCRKFDYFhaUoKFRUpKRnlSDQzwiv4sXnSenZfdwMcfq6aksmeqy8jC1CoK8R7jwSj+10ztV8jXDqWtljsvPE505BjkkxRsqk90HGjWDYd1KMw2XXpjHSb7wOHl5cjMx7j2DXupEsjbmODmxbNcKrZVvKXbzw9a2M0JD7aNS4ifT+Dgm+jy7delRYRhpHJOMwjTdkRay8Wk+uGJosgikrDaUPf/bwJoLqi8ddKv/s4Q006zhI7XGUqerkvtUsnbi7j+LzUhXpqQnIzclgLsvlto2fH0KCg9G4cWOpPDQH6da9e5ny5GK+bPlyhc/InTs/Lw9jvvgCdvb2bN5Eyhyqk1z8ibzcXGYZTK7cmtqG0kBT21SvJ2ub549uoml79W1z9tA6nDmwCmNmrIS7j2IGrbrNuqGykiJr5bwxqNOsGxq06Fnus9/RrRqinl2Hb5Ds2U/7NZu9mfuPBHf/hhg247DCZye3zoCNozfqtR2t1g2O+smHruHge2jQqKm0bR4E30OnruI59JvOJcR9H8Di5sgTFxejMfW4tvWTNslDbertWxkPQu6ifqPmsn4KuYuOXWXKu4rMJTTN+VJTkpCTnQUrmzdfPOZwuCJHCzEyMmKWKxTzhl76ScGQnJzMggOTkoeUMGSFQ5mhyLKGlA4VhQIlk/UMBTimAYni7pBbEykJaDVHEpPnTSG59u3bx6xfaDJE7lOqJkBkTTR79mxmqaMcoPnLL79k7j9k0UPxXsg6hlaB3sUUkrI40aoSWQNRe9KKErmXUftRqk0KgEwKM3KpIqUSWeJQW5Mihfjmm2+YvDSBIYUSBWKmSREpo1RBMX8omxhl6aIMXFSfcvBhUiq9fPmS1UPKLeoTZQWLpJ2oP8hljWSi9qGMWxK3qn+Ltt2GYsOSWfD0qQpPv0CWfryoMB+NW4snyesXz4SVjQN6DZnI9k/sX4/DO5ax7FW29s7ITBevqBoamTC3ImMTMxbXZO+mv5mpK5WhlOU3Lh5Bv+FTNcoS1HwEzu2cDnvXQDi61WCpwouL8hFQT/wQPbv9W5haOqBh56nSgIbpieKA2iUlxcjNTERKbBj0DU1gaedRoTo10aXnQCz/+2d4+wbAt3JVliq8sKAALdp2Zd8vWzAX1rb2GDRcbMlyYPcmVtbRyYUpBe7fuYYr50/gs7HfsO/J9PbAro2oU78pe4iTT/apo3uRnpqCBk3EijR1DOzWHj8vWcMULlVZ+vFTKCgsRNfW4okhuVLZ21hh7JB+zD3Kx10xLbK5qdjFRfnz3Lx8nLt+G18OV6+4U6Zdt0+wbslsppDx8quGM4e3sWumSWvxy8PaRbNYWvHeQ75k+8f3bcChHcsxasqvLCOVumtmz8aFLIaTDblWPbqL6xePov8IRasyVXToPgRrFs+Gp08VePkFsoxThQX5aNpGLM/qRT/A2sYefYeK5Tm6dx273u0rubJ+Cr13hf3W0DHi9KA0BrXrOhhHdq+Fo5M77B2dWfpxss6p3aClRlmGtm6AWZsOoZqHEwI9nLHl/C3kFxajZyNx7I3vNxyCg5U5JvUUK51WHLuMGp4ucHewRnZeATacuYH4tEyW+UrCqXthzNqHYuU8j03CH7tPo1VQZTSuqjm+CHEtTIReTQQs9XhsaikaVdGFgR5w/7V1Hn1H8WbO3Bfv3wgT4dMOAjSuqotnMSIEeunC2VaHpS8n6NiWQbp4/KqUxdKxNtdB+zoCpGVT7JzyfXXO3ilAp8ZGzGomJaME3ZsZIyNHhOBnsonv5AFmCH5ejAv3xMqVM7cLMKKLKV4llCAyXpx+nDwArz0okgZRrlPFAGEvi5mywtpCFx0aGKFIWIqHLzQrUQ+dTcOAznaISypiGaaG9LBHWoZQISPVz1Pccf1+No5eEK+oGxnqwMleltXG0c4AXq6GyMktQXK6kMXE6d/ZDrdCspmiyMJMD11aWsPWSg9X7ypa1clz/EoWera2REKKEEmUfry9JVPu3HmUJy3z/WgH3H6UJ1XUHL2cjbH9bZmrVHh0ITo1NYehgS4u3pEpclrUNUVsUjGyckSo7GGAYd2tcfxKNuKTVVvkUPpxU1+ZUtfEyxUWQQEoSstEQXQ8/H/+CkYujgj59Fv2/atVO+Ax7hMEzPuGpSy3a9WQpRu/3X2MtI6XC9cjaN3vyLj7EJm3Q+E5cTj0TI0RvXEfyqNnrz74e8Ef8PWrjMqV/XHw4H4UFBagbTtxsN4F83+Hra0dhn86ku3v3rmdlaWMVcXFRbhz5xbOnzvD4uSw8zExZbFw1q9bzZ7F9g4OePggFOfPnsbI0V9olKVV12HY8s/3cPeuBg/f6rhwbDMKC/PRsKX4BXHT0u/Y87L74Mls//SBtTi26x+WvYpi4GRlyMY+2si18/ju5Qhq0JZZIKQkRuPglgWwq+SOgCBFN29V0GLagr/+YnOyyv7+OHjgALM4krjTk9U0WRt/+umnbH5J8xF5zF4vHMl/Ttkxac7k7OLC5h+bN29mdTR6rSxSR8suw7Bt+fdwY20TiIvHt7DnguTleeuyGSwNdNdBU9g+WVMc370UQyf8ARv7sm1jam7FNnko5p6FpR0cnGUB5dVRp9WnOLHlWzi6B7KMVJR+vLgwH9Uaip/9xzdNg5mVI5p1l80nUhNezyeERcjOTERSjHg+YW3vAQMjM9g5K1pk6huYwMjUqsznypD70+IFv8HHrzL8KlfBkYN7WFzENu06su8X/fUrbGztMXSEON7h3l1b4ePnz1ypSClw785NXDx3GmPGT5H1U58B+Ov3uSwAcvUatXD/7i3cvnkNP/228KPqJ22Sp2vPAfjn71/h40dzvios/TjNJVq17cy+X/LXz7CxtcMnI8TjxP5dm+HtF8AyVtFYc//2DVw6fxKjx4mvqfz8POzevh4NG7dk1lcUI2fz+uWsfM3aqheIP0ZKuWvVB4MrcrQUUoTQSghZiFCcFnID+uKLLzBy5EimhKEAwvRwphURKksv+xWFAhGT5QgpTV68eMHSZZPlCikf3pYFCxawzE+0CkSpv0kRRTFmlCF3K5KdTECV04rTMZQhYdiwYex7SrdN7mPvEvxLYlFDdZOyhtqMLG4oqxat7pPy6tKlSyx4MclL35GbGqUrJ0gZQ4ouyjSVlJTELJoogDNNklRBiqItW7YwBRApkCj+DvUNnYuEPn36MKVXq1atWFYtUg6RNZM8pAyiAISTJk1iCjvap+Oonf9t6jXpgJzMdPaiTQ9EVy9/TJy5TGoqnpYSr6Bcu3RyF8s0sHL+1wr1dO0/Bt0GiBUao6b8jv1bF2Pdou+Qm5MFGzsn9Bg0Ac07iH251eFbszPyc9Nw++QS5GUnw865CrqOWi11g8rJiFOQJTcrCbsXyla0Qi6uY5uzdz30GLu5QnVqolGztsjKzMCerauRkZ4GD28/TJ+zQGoOnZKcqGB5RA/89cvnIzU1iSkknF09MH7qbFYPQdcgBUq+dPYYU+KYWViyCcPs35axVOSaaNukATIys7F6xwGWYcrPyx0LZn4FGytxrIPElFQWVPpNOX3lJouV0a5pxePQ1GvaAdlZ6Ti4na6ZVLh5+TNLG9k1k6BgXXPx5G52zaz4U6zQktCt/+foPlA8Ifr8q3nYt2UJ1iz8nl0zFCen5+DxaNFBvQWMhPpN2zN5DuxYwbJNuXlVxpQflsBSIk9ygkLbkDJu86rfWIYs6qdKLp4YPflnVo+ETr2Gs/7cuPwXFhjZr0pNfDVriUJsC1V0rFsV6Tm5WHbkIlKycuHv6ohlEwZKU4onpGeyrFMSSHkzd9tRVtbCxAhV3Sph49fDWepyCRTUeP6e08xFy97SDF0bVMeYTpqzi0l4FFkKU0MRWtcUMBerhLRSbD5bgtzXxiyWpuLUoRKik0ux53IJ2tQUoE0tXaRmATsulCDptYGKqBRwtNZBkLcus6bJzhdntToXXKIxsLCEUzcLYaivg086mMDESIelDF+yK0cax4awt9Z97d4l5u6TYpib5KNbUyNmSULWPHQMKaCI4pJS+LnqoU1dQ1ZnVm4pwqOLWXwcSRl17D2ZyoIjTxjiBFMTXTwOz8fsxdEKWZ4q2emzODcSfD2MMW+qWFFMjOovVrafvZaBhRvjQWsarpUM0KahKzuOXKCeRxZg+p+vWCpydRy+kM2UMKP62MDESBdPIwvx29okFMvpWxxt9WBuKpPlRkgea5O+7S1hZS7Aq7gidgxZPklwstfDwE5WMDPWZYqmA+eycOyy+tTplnUC0eisePwkqs4XzxWiN+1D6MgZMHSyh7GbzK0vPzKGKW2q/jUDnl8OQ0FMAh6MmYmU07IMOvG7j8PA3gaVZ0+EYSV7ZIWE4VbXUShSCoCsimYtWiIzKwNbN29kiz3e3j6YM/dXqRtQcnISdOTuKXpBXr5sMctIRfe3q5sbpn49ndUjYdq332PjhrWY/+c85GRnMyuGocM+RafOYiW9Ouo07sjcNo7u+gfZGSksBfK471ZI3UDSlZ6XV06Ln5drFygqpDv1HYvO/cexcTI26hluXjyE/NwsWNo4IKBGI3QZMAH6+upTYEsg6+GszExs3rIF6WlpzP1p7k8/ydomKemNnwt9+/Vjbbhk8WJmbU2x+ahOUgRpolajTsjJSseJPUvZXMLFIwBjpq+AuULbyJ4LV0/vRImwGBsWypQTRIc+Y9Gx73i8K/51OiMvJw3Xji5mz357lyroPW6N1LWKYt7Iy5OTmYQtv8vmqXfPrmObq2999J8kux/ehqbNW7N+2rFlA9LT01iq+x/m/i6dS7BrWE4Wav9VyxYiNSWZXcMuru6Y/PV3rB4JlJ6cFDv7dm/D2pVL4OzihmnfzUHVarIEHh9DP2mTPE2at2Fzvp1b1rI5n6e3L76fO19xzic/1hQWYM2yBdI5n4urB76cOovVQ5CVVtTLCFw8e4IFRbaxsUONWvUwcMioCt3fHI4yOqX/VXREDqccyKKHLGMoVTgpnzjvnwsP348p/fsi+MX7SX/7PmgeoOgX/V/jUfQU2sIjHcVUmv81Ah3teYzViS/fouBDMS9WvSn6f0Fi/L8b3PhNiH2hOrvbf4UZadC0hCF/Vyxb5YfC78lpaAuROeqzTX5ofMxVZ6L6r3iaIY4xpg1Ep/y7QfrflGbecdAWIrM0u+j9f8bVXH0mtg9NDT9Z3MKPjfvPNcc6+6+o5fd28bC0GW6Rw9EaKNYPBRymFSWynKG02uSCNHjw4P9aNA6Hw+FwOBwOh8PhaEDeqpfz76IYSZLDUQOZ0lIKb1Wbungxbwq5mVA8GXIlorhAlEb7zJkzzCqH4gKp+33a5NOcczgcDofD4XA4HA6H878Kt8jhVIhjx46pjbr+voLvUgYFimejLtaNcvYn5e85HA6Hw+FwOBwOh8P5X4crcjgVgoIA/5dQ4GfKZsXhcDgcDofD4XA4HO2DZ636cHDXKg6Hw+FwOBwOh8PhcDicjwSuyOFwOBwOh8PhcDgcDofD+UjgrlUcDofD4XA4HA6Hw+Fw3gmeterDwS1yOBwOh8PhcDgcDofD4XA+Ergih8PhcDgcDofD4XA4HA7nI4G7VnE4HA6Hw+FwOBwOh8N5J3jWqg8Ht8jhcDgcDofD4XA4HA6Hw/lI4IocDofD4XA4HA6Hw+FwOJyPBO5axeFwOBwOh8PhcDgcDued4FmrPhxckcPh/D8mKtUY2kRcXD60hRhnK2gT5tYu0BZiE0ygTQh0S6Et1LCwg7ZQ+KIE2kRJiQjago2jNbQJbWobvyenoU08D2gHbSH/Shi0BZNNM6FN2I1eDm3B0MkQ2kRyofbMJ7wsk6BNFIv0oS1UjjoBrcFv2H8tAecjgLtWcTgcDofD4XA4HA6Hw+F8JHCLHA6Hw+FwOBwOh8PhcDjvhPbYl/7vwy1yOBwOh8PhcDgcDofD4XA+Ergih8PhcDgcDofD4XA4HA7nI4G7VnE4HA6Hw+FwOBwOh8N5J3jWqg8Ht8jhcDgcDofD4XA4HA6Hw/lI4IocDofD4XA4HA6Hw+FwOJyPBO5axeFwOBwOh8PhcDgcDuedKAV3rfpQcIscDofD4XA4HA6Hw+FwOJyPBK7I4XA4HA6Hw+FwOBwOh8P5SOCuVRwOh8PhcDgcDofD4XDeCZ616sPBLXK0DE9PTyxcuBDagDbJoq2MGDECPXv2fOd6fvzxR9SsWfO9yMThcDgcDofD4XA4nP9duEWOlnH79m2Ympr+12Jw/kV0dHSwf/9+BQXQ119/jS+//BLawp3zW3Hj1FrkZCbD0TUA7QfNgotXDZVlk+Oe4+LBxUiIeoTM1Fi06z8D9duOUCizdEZr9p0ydVoORsfBszXK0qiaAC1q6sHcWAfxqaU4eLUI0UmlastX99ZFh3r6sDbXQUpmKY7fLMaTKBH7TlcX6FBPDwHuAtha6KCgCHgeU8LKZOVVrG2untqGi0fXITszBU7u/ug5/Hu4+6hum5vnduPulYNIiA5n+y5eVdFpwGRp+RJhMU7sXownwZeQmhwDY2Mz+AY2QueBX8HS2qFcWY4cPoR9e3cjPT0NXl7eGDN2PPz9A1SWvXb1Cnbt3I74+DgIhUI4u7igV6++aN2mrbRMeno6Nqxfg/v37iI3NxfVAqtjzBfj4eLiUq4st85uxdUTdM2koJJbADp9MhOu3qrbJSn2Oc4fWIy4SLpm4tBh4Aw0aj9coUxhfg7O7V+MJ/fPIDcrFZXcq6DT4O/h4lUdFeHmma24cnydWB73AHQZ8r1aeRJjn+PcviVMnozUOHQaNB2NOyjLk4uz+xbh8T2SJw1OHlXQefB3cPUuX55dp69g89FzSM3Mhp+7M74Z1huBPh4qyx6+dAtzVm1X+MxAXw/X1v/J/hcKS7BszzFcDQ5DbHIqzIyNUD+wMr4c0BX21pYVapuGVQVoUUMPZsZAfFopDl0rRkyyhnvKSxft6urB2kwHqVmlOH5LiKfR4nuKaFtbDzV8dGFlqoMSERCTIsKp20JEa6hTnu7NjdGsphFMDHUQHlOMrSdykZQuq18VLesYokMDY1ia6SI6UYjtp/IQGS9UWXbiAHNU9zHAP3uyEPysuFx5erU2Q8s6xjAx0sXzqCJsPJyFxLQSjce0qW+CTk1MX8tTjC1Hs/EiVvG3fNz00beNGXxc9SESAVEJQvy5KQ3FqsVm9Gljjlb1TJgsz14VYf2hDCSmapalbQMTdGlmBkszAaISirHpSCZexIhlsbMSYOE3jiqPW7w9DbceFqj87ujhg3JjjQ8bayqrHWsuY7d0rCmBs4szerKxpp20TH5+PjauX4Mb168hOzsLjo6V0K17T3Tq0g3lYdO0LrynjoRl7UAYOTvgTp9xSDx0VvMxzeuj6vzpMKvqh4LoeITPW46YTfsVyniMHQzvr0bCsJI9skKf4NHkn5B5+0G58tw4sxWXj70ea9wC0HXo93BT80y4fX4X7l89hMSY52zfxbMq2vWbolC+tLQUZ/ctwe0Lu1GQlw0Pv1roPmI27Cp5oiKYNGkH05ZdITC3RHFcFLL2b0RxdIT68s06wrRxWwis7SDKzUZ+yE1kH9sJCIvfuk4Jp4/uxrEDW5CZngo3Tz8M+/xr+FSuprptrp/H4d3rkZgQw55RlZzd0KnHJ2jaqrNCmXMn9iEyIgw52Vn4+e8t8PCujIpy8fgOnD60EVkZKXD1qIz+I6fD00/1GH7l9F7cvHgYca+f3+7eVdFj8JdlysfHvMCBLQvx/PFdiEqEqOTqg8+//gs29k4aZTl/fCdOHdiIzIxUuHpWxqBR38LLL1Bl2cun9+H6hSOIi3oti08V9PrkS4XyBfl52LdlMYJvnkduTibsHJzRussgtOjQr9x2OXb4APbv3YmM9DR4evlg9NgvUdm/isqy169ewp6d2xAfH4sSYQmcXFzQo1c/tGrTXlqmZ+fWKo8d/tnn6NV3YLnynDiyD4f2bWfyeHj54LMxk+HnX1Vl2ZvXLmLfrs1IYPLQdeOKbr0GoEXrjirLr1o6H6dPHMSI0V+iS4/+5cqy4+IdbDx9AylZOajs6ojp/dujuqfqOdHB6yH4YfMRhc8M9AS4vXi6dD81KwcLD5zH9bAXyM4rQG0/d0zv3wEeDjblysLhKMMVOVqGvb39fy3C/wQ0ESopKYGe3sdxiZuZmbFNG3h8+xjO7J6HTp/MgbNXEG6d3Ygdi0bii7knYGphW6Z8cVE+rO1dUaVOR5zeNU9lnZ9+twelItnLR3Lsc2xb+Ck7RhNBPgJ0a6yPfZeKEZUkQrPqehjZxRB/bi9Aror3DQ9HXQxua4ATN4UIe1WCmn4CDOtggEV7CpGYXgoDPcDFXhdn7wkRnyKCsSHQvYkBRnQ0xOJ9heW2TfD14zi89Xf0+Ww2U8ZcPrEZa377HNPmH4WZZdm2iQi7hZqNusBjWE3oGxji/OE1WP3baHz9+yFY2jiiqKgAsZGP0bbXF3ByD0B+bhYObv4VG/4aj0k/79Yoy6WLF7Bm9UqMnzAR/gEBOHhgH36Y9R1WrloLKyvrMuXNzM3Rf+AguLm6Q09fD7du3sTCv+fD0soKderUZffMzz/9CD2BADN/mAMTExMc2L8XM7/7FstXroaRkbFaWR7eOoaTO39D16E/wsU7CDdOb8SWBaMw4dfjMFN5zRTA2t4NVet2xMkdv6ms89CGWUzh02vU7zC3ckDo9UPYNP9TjP/5KCysVb+ISnhw8xiO7/gd3Yf/yJQ3109twsb5ozHpt2Oq5SkUy1OtXgcc365angPrZ7KXr76fi+UJuXYYG/78DBN/PaJRnlM37uPvrQcw49N+CPT1wPYTF/Hl7yux988ZsLE0V3mMqbER+15e+SuhoKgITyJjMKpnO/i5uyA7Lw/zN+/HVwvWYPNPU1EeNbx10bWhHvZfESI6SYQmgQKM7GSA+bsKVd5T7g46GNhaHydvCxEWJUJNHwGGttPHkv1F7J4ikjNFOHRVhLTsUtCQ24zq7GyAP3eqrlOejg2N0KauEdYdzkFKhgg9W5hg8kAL/LAqA0I1+oq6VQzQv40ptpzIxcs4IdrWM8LkgeaYtTID2XmKyiP6DhXTJzE6NzVFuwYmWL0/EynpJejd2gxfD7PGd0tT1Cpc6gcaYVBHc6bwiYgpQodGpuyYbxenIDtXJFXifD3UGkcu5zIlT4moFO6V9FGqQbauzczQvpEpVu7NQHKaEH3bmePbEbb4dlGSWlkaVDfCJ50tsf5gBsKji9GxiSk75pu/k5CVK0JqZgnGz0tQOIYURaT4CXmmegy8LDfWVA6ogkNsrJmBFavWqRxrzM0t0H/gYLi6ukFPXx+3b97Aor/nw8rKCrXr1GNl1q5egdCQYEz9ZjocHB2Z8nj5P4thY2uLBg0bq28UAAJTE2SFPkX0hr2ou+cflIexpyvqHVqJqFU7EDzsa9i2boTqK39GQXwyUk5fYWWc+nVClT9n4OH42ci4FQKvicPR4OhaXKjWEUXJaWrrDr1xDMe2/Y4eI35kypirJzdhw5+jMeUP1WPNyye3UaNhZ7j71YK+viEuHV2DDX+OwsRfD7NnAmvvo2tw/fQW9Bk9Dzb2rji9dzGrc9K8I+w5ogmjmg1h0X0IMvesQ3FUOEybdYLN59OR/PtUiHKyypav1RgWXQYiY+cqFEc+g8DeCVYDv2DfZR/a8lZ1Srhx+TS2rVuIT8dOZ8qbE4d34I8fJ+KPZbthaVX2pdXMzALd+30KJ1dP6OnpI/jOFaxe/BMsLK1Ro3YjVqawIB+VqwShQZM2WPvPr3gT7lw9gb0b52PQ5zOZMubc0a1Y8vNY/Lj4IMxVPL+fP7qDuk07wds/iLX7qQPrsOSnsZj1915Y2Yr7KjkhGgtmjkCjNr3Qtf9YGJmYIT46AvoGBhpluX3lJHav/wufjPkeXpUDcfbINiyaOw5zlxyAhYq2efrwDuo37QifgCDo6Rvg5P4NWDhnLH5ctBfWtuJFn90b/sKTB7cxcvIvsHVwxuPg69i2ah4sre1Rs35LtbJcuXge61Yvx9gJk1/f33sxZ9a3+GfVRjVzCQv0G/gJXF7PJe7cvIElf//BytZ6fX+v37JH4Zh7d25i6aL5aNSkOcrj6qWz2LhmKT4fPxW+/lVx9OBu/PLDVCxauQ2WquQxs0Dv/sPg4ubOrpu7t65h2cLfYGlpjZp1GiiUvXntEp49fQRrGztUhBN3HmP+3jOYOagTqns6Y+u5Wxi7ZAcO/vgFbM1VL7qbGRni4GzxPUTIPb7ZPGvyyj3QE+hi4Zh+MDM2xKazNzFm8VbsmzUGJoaar5uPBZ616sPBXavekhMnTqBp06ZsYmJra4uuXbsiIkK8OlFUVIQJEybAyckJRkZG8PDwwLx586Q3MbnRuLu7w9DQEM7Ozpg4caJad6YnT56w36F6qlatijNnzrBJ/YEDB9j3kZGRbH/fvn1o1aoVe/kKCgrC9evXFeS9cuUKmjVrBmNjY7i5ubHfpBV3CUlJSejWrRv73svLC1u3bn2j9liwYAGqV6/OrImo/nHjxiEnJ4d9l5WVxeo9fvy4wjFklWJubo68PLEpxLVr15h7EZ1r3bp12TnSuQUHB5f7+xcuXGBl6Tfq1KnD2pbOWSQSsbancyIZqG327NmjYIHwySefMAUafe/n54f169dLv3/w4AFat27NvqN+/vzzz6XnVVF3NDon6nPJ90SvXr2YvJJ9Zdcqknvu3LlwdXVl50Lf0TUnoaL9/jbcPL0eNZv2R1CTPrB39kXnT+ZAz8AIIVf3qizv7FkDbfp+i2r1u7AJhipMzW1gZmkv3Z4/OA9re3e4V66vUZZmNfRwM6wEd56WICm9lCl06AWmXoBqBV3T6gI8ixbhYogQSRmlzCogNqUUTQLF5ckCZ82RIoRGlCA5sxRRSaU4cKUIrg66sDIr/8Fz6fgGNGjVD/Va9Iajqy96fzYb+oZGuHVxn8ryg8f/icbtBsHFswocnL3Rb/RPKBWJ8PzRDfa9sYk5Pp+xFkENO8HB2QsefkHoNXwmYl4+QnpKnEZZSMnSoWMntGvfAe7uHhg/YRK7Vk6fOqmyfI0aQWjcuCnc3N3h5OSMHj17MSuex48esu/jYmPx9EkYxtHLWmV/9hI2bvxEFBUV4uKFCxpluX5yA2o374dazfrAwcUXXYfNgb6BEe5fVn3NkFVN+/7TUL1BFwj09FUqeh7fPYV2/b6Gp3892Dp6oFXPL2Hj4I7b5xWtVVRx7eRG1G3RD7Wb9WbydBv+I5Pn3iXV/URWNR0HfoMaDbtAT89AtTx3TqNDf5k8rXtNgK2DO26d0yzP1uMX0LNVI3Rv0QDeLpWYQsfI0ACHLt5UewxN/OysLKSbrZzCx8zEGMumj0W7hrXg6eyA6r6emDasD8JexiAhJb3ctmlaXQ+3npTg7rMSdo8cuCJEkRCo6y9QWZ7unWcxIlwKLUFyRilO3xUiLqWUWcpJCIkQITxOrMih+/TIDSGMDHRQyab8KUab+sY4ejUfIc+LEZtcwhQ6Vua6qOWvfkLbrr4RLgcX4lpoIeJTSrDleC47hyZBii+5bg4CtG9ghA1H1Y/ZynRoZILDl3Jw/0khs/RZtS8TVuYC1A4wUntMx8YmuHg3D5fv5yMuuQQbDmehqLgUzWvLlJ+DO5rj9I08HL2ci9hkIRJSS3DrUYFaZRWrt4kpDl7Ixr2wAibLit0ZTJY6VdTL0qmJGc7fycOleySLEOsPZqKwuBQt6piw70lxlJkjUtjqVjXGzQf5KCwq1TjWtG3fkY0148oZa6rXCEIjNtZ4sLGme8/e8GRjzSNpmbCwx8xCh8qSNU7HTl3g5e2DZ0+fojyST17Cs9kLkXjwDCqCx+cDkf8yBmHTfkfOkxd4tWwrEvaehNckmeWo1+RPEb12F2I27kNOWAQejJuNkrwCuI3oo7Huqyc2om7LfqjTXDzWkEKHngl31TwT+o/9Ew3bDoazRxXYO3uj10jxM+HF4+vSOSIpg1p2/wJV67RBJXd/9BvzG7IzkhB2r/zzNW3eGXk3ziP/9kUIE2ORuXctSosLYVy/hcryBp6VURT5DAX3r6EkPQVFzx4g//41GLj7vHWdEo4f3IaW7XuiedtucHH3ZgodQ0MjXDpzWGX5KtXroG6jVnBx84Kjkys6dBsIN09fPAsLkZYh65xeA0ehWpDmuYMqzh3ejCZte6NR655wcvNhCh0DQyNcOyeeTyvz6eR5aNFxANy8AlDJxQtDvvgRpaUiPHlwS1rm0LYlqFa7KXoPnQI37yqwr+SGGvVaqlQMyXP68BY0bdcbTdr0gLObD1PokCxX1cgyasqvaNmpP9y8/OHk6oVh435g18qTUNlzJOJJCBq17Ar/wLrMGqd5+z7M0icyXHbfqeLg/t1o37Ez2rTvBDd3T4ydMIXd32dPKc7ZJVSvURMNGzd7fX+7oFvPPq/vb5n1mrWNjcJ288Y1BNaoiUpOziiPIwd2ok2HbmjVrgvc3L3w+fivWducO31UZflqNWqhQePmcHXzRCUnF3Tp0Q8eXt548ljRmi41JRnrVi7EpK9/qPAi7+ZzN9G7SU30bBQEHyd7zBzUGUYGejhwTXZNqnx+W5pJN1sL2SLtq6Q0hL6MxfcDOyHQ0xmejraYObATCoqEOHFHcz9xOKrgipy3hJQgX331Fe7cuYOzZ89CV1eXvZzTC/jixYtx6NAh7Nq1C0+fPmVKEckL+969e/H3339j5cqVeP78OVNWkAJEFWRRQu439JJ+8+ZNrFq1Ct9//73KsvQ5ueeQ0qNy5coYNGgQM00lSMHUsWNH9OnTB6Ghodi5cydTcpCyST7WS3R0NM6fP88UHcuWLWPKnYpC50/n/ejRI2zcuBHnzp3DtGnT2HcWFhZM0bVt2zaFY6hdJOdHyh5SJFFb3Lt3Dz/99BO+/fZbvCnTp0/Hb7/9hrCwMNSoUYMpcTZt2oQVK1Yw2aZMmYIhQ4bg4sWLrPysWbPw+PFjpgCiY5YvXw47OztpH3fo0AHW1tbM5W337t1MkSbfbm8K1UOQsig+Pl66r8yiRYvw119/Yf78+azPSI7u3buza6ai/f42lAiLEB/1CF5VZCuiOrq6bD/mxf23rlf5Nx7eOMQURfKWBsoIdMl6hlwtZG869JpBrlBkeaMKd0dd9r08z6JL2OfqoBdOUWkp8gs1L9sLhUWIffkYfoENFa57v8BGePW8fGUjUVRYgJISIUxM1bvA5Odns3YxNrFQW6a4uBjh4c9Rs2YtBVlo/8mTsHLloAlgcPB9xMREIzCwurROwkBuJZHq1NfXx+PHYmWPunaJe/UI3lUbKxznXbURYiIq1i7KkHk6WXDp6Su+mOvpGyHq+V2NxzJ5IkmeRgry+FRrhOi3lqcEIpJHaTWcFJyvnt1Te1yxUIgnL2PQoFplBVnqV/NDaPgrtcflFxSh66S56DJxDr5asBYRMfEa5cvJz2fXDCl5NMHuKTsdhMfK3Jboqqd9DwfV9wjda/LlCVLsqCtPv1E/QMDup/hUze5RdlakQNVF2EuZCwcd9yJOCG8XPbX1ezjpISyySOEcwl4WwcdFphQk67tRPc2w9WQusnIrZpJjby1gipJHEUWK8sQWw9dNX7U8AsDTSV/hGFKW0L6vq/gYc1Nd+LoZMIuYmaNssHiaPWZ8ZgM/d/1yZXkYUaggC1n8+LkbqJXFy1kfj8ILFWUJL4Svmt/ydNZnGymi1I81zxBUs7bSWFMbT588Viu/7PdLERJ8D7ExMcxVU0KVKlVx8+Z1pKaksDJknRMXG4NatevgfWPVsCZSzikuciSfvgLrhuLFEx19fVjWroaUs9fkBUfKuWuwaigbY9WNNb7VFMca36qNEBVesbGm+PUzwfj1MyE9OYa5aNF4JcHIxJxZFkaFq395ZAgE0Hf1QuFzufG6tBSFzx7CwMNP5SGkxKFj9N3EihuBjQOMqtREQVjwW9dJCIuLERnxBNWCxBYakrah/fCn5bur0TXxKOQW4mNfwb+a+j6oKCRP1Isw+NdQfH4HVG+Il09DK1QHWdBSX5maiZ/NNN9/eO8yHJw8sOSnLzDts5b4Y/onCL51rnxZIsJQpUYDBVlo/8WbymIum0uQtU7I7YtIT00SK3ke3EZi3CtUDZKds6r7OyL8GWrUrKMgS1DNOm9xf6t2JyT3qLu3b6Bte5mLnCZ5XqiQp0bNunj25FGF5HkQfAdxMdGoEhgk/Zz6asmCn9G99yC4eXiVWw+TRViCsKh4NPSXldfV1UHDAC+EvoxRe1xeYRE6zlyC9t8txqQVuxAel6xQJ2Gor6dQJ7lf3Y9QXyeHo46Pw+9ECyGliDzr1q1jVh2kFIiKimKWHWRJQ5NrssiRQN9VqlQJbdu2ZS9IZJlTv77qlYXTp08zJQxZm9AxxC+//IJ27WR+5hLoZb5Lly7s/zlz5qBatWoIDw9HQEAAU2aQ1cnkyZPZ9yQbKV1atGjBFBckEykybt26hXr1Xps9r12LKlVU+8eqQlI3QUqrn3/+GV988QVTCBH0+0OHDmXWNxLFzdGjR5lVDkFKHmqr1atXS62PYmNjMXr0aLwJZMUiaZ/CwkL8+uuvTPnSqJF4UuTt7c2UWKRIo/Onc69VqxazAJLILoFkKigoYIogSdyipUuXMoXT77//DkdHze4dmlznyJJL0qeqIAUOKbIGDhT7EtPvkZKNrH3++eefCvW7MtQetMlTXGSoYKqdl5POXqCVXahMzW2RGv8C74OnwWdQkJ+NGo17aSxnakQvbTrIzlf8PCe/FA5Wql8izU10kKOiPH2uCj0B0LmhPkLCS1BYTuiM3OwM9jJvZqlokkvm80lxFWubYzv+goW1A1P+qKK4qBDHti9AzUadmYm2Ouj+oYmJlbWimTGZNsdER6s/h9xcDB86iE2WaHI0dvyX0hcnVzc32Ns7YOP6dZjw5SQYGhkxd62UlBSkpal3LcjLFl8zym4EphZ2SIl/ibfB0NgMrj41cfHwMtg5ebM2f3DzKFMMkVWOJvKk/aQoD8n39vKYws23Ji4cXA57Jx9Wd+iNo4gOD4aNo3p5MrJzUSISlXGhov3IeNWKcg8nB8waPZDF0snJy8eWY+fx2ZzF2PXbt3C0tSpTvrCoGEt2HEGHRrVgZqLeUoMweX1P0T0hD+3bq7mnKI6OqvJmxor3VIC7Lga11gfNT7PzgLXHipBXjreipan4N0nBIQ+5I0m+KyOPiQ47B2XlDO1XspXJ1L+dKSJihMzSp6JQfBuCrFQU6s4pkX6njLmJLgQCHWQqnUNmbgmc7MUKFwdrsfVSr1Zm2HEyG6/ii9G0pjG+HWGD75emqIy/Q1ZJ4t9WlkXEYt9olCVHsT46H4ksyrSsa4LYpGI8j1LdTllZmWysoQWNNx1rRgwdKDfWTFRQ0lCMnaWLF2LEsEEQCATQ0dHFl5OmILC66pfBd8HQ0Q6FiSkKn9G+vqU5dI0MoW9tCV09PRQmpSqVSYWpv3f5Y43S2EfjQ3IFx5oTO+ezZ4JPNbEinGKvSepQrNMOORmyF0JV6JqaQ0cggCg7U+FzUU4m9BxUW0KQJQ4dZzthNsgbQkegh9xrZ5B79uBb18nOI0vcNsouVOQ2FBejXomdl5uDiZ91gbC4CLq6Agz/Yhqq11R0j3kbcrLTmTwWSu1qbmWLxNiK9dX+LQuZm1LAa2VQdmYaCgvymMtVt4ET0HPIZDwOvorVf36FST+uQeVqdTXLotQ2JEt8bGSFZNm7aRGTRV4ZNHDUt9iy/Cd8O7oDdAV60NXRwdCxs1C5mnrlaPbr+1t5LkEuTDHRUWqPy83Nwcih/aX395jxk1GzturzPXfmFIyNTdCoSbNyz0ssT9nrhuSJ1XDdkDxjhveWXjejxn6FoFoyJeLBPVvZONO5e19UlPScPOYCa2uh6EJFLlUvExXHCglkYTNnSFf4uTggJ78QG8/cwPD5G7Fv1udwtLaAZyVbONlYYPHB85g1uBOMDQyY1U9iRjaSMytuOartiN7AnZnzbnBFzltClhE//PADs5ShFx0aCAlSDJB1CykT/P39mSUMWaO0by8OAtavXz/2Mk4KBfquc+fOTDGgysyPrHnITUn+hV+d0oesTySQSxdBFjX0Qh8SEsKsOuTdpUhrTTK/fPkSz549Y79PLkkS6DhSNlQUUpaQwohcweglk6xCSAkiUdzQeZLiiiyVSDlBlklkqUMKLcm50jmQEqe8c9WERCFDkEKDfl9Z8UWub6S8IcaOHcuUcmQFRH1EFkKNG4snVGShQ+5K8sGnmzRpwtqN5H0bRU5FoPaLi4tjvyUP7VNfVrTflaH+IWWPPD2Hz0avT8VuXx+KkCt74RPYHOZW/077VRQKfDyknQHz5CWXrX+bc4dWI/j6MXwxc6PKOAcU+HjLkq+YfUHvTzUHgH5byEVw8dLlKMgvQHDIfaxdvRKVKjkxtysaA76f+QMWLVqAgQP6iFfda9VGnbr1xMv6H5jeo//AwXXfYcHUFtDRFcDJoyoCG3RB/Kv/xvyYYuPsX/s9/pzSgk0USZ7qDbuwFfn3SQ0/T7ZJCPLzQt9pv2HfuWsY209xRZMCyU5fspGN59NHlB/Q8t8kIk6ExfuKmLKILHIGt9XHPweKFGLkNKhmgCGdZArKJbvUx9d4F4L89BHgoY+f1mZoLNeohhFGdJNZvi3YWr5r2tsgMTwklydyvyK2nchGVW8D5n61+0wOGgcZ47MestX1+ZvUK0/fF6R0a1TDGAfOZ/8rY82ipStQkJ+PEDbWrGBjDblSEYcPHWSunLNmz4W9gyMePQzFimVLYGNjy8ad/w9cPLwaD24ex6gZqp8JHwIDnyowa9MDmfvWofhVBAR2jrDsOQyitr2Qc0YxGPSHwMjYBL8s3MKum0eht1mMHQdHF+Z29V9ycv9a3L16ApN/XCvtK3KzImrUa4U23Yay/8kN68XTEFw5tVutIuddOb5vHW5fPYmv565WuG7OH92BF88eYPyMhbC1d8Kzx/ewbfVvsLSx12iV8zaQYubvpatZ0PLQkHtYt3oZHNn9XTb76tnTx9G8VRsFa9/3Dcnz5+J1KCjIx8Pgu9i4dikcKzkzt6uI8Kc4emgP/li0VqMV+PsgyNuVbdJ9H1f0mrsSu6/cw4RuLaEvEGDB533x45YjaPb1ArYo0SDAC02r+bDnOIfzpnBFzltCyheytCELEopzQy/3gYGBTElQu3ZtpiAhKxdScPTv358pLMhliRQzpASgz8nihmLJ/Pnnn8zVhxQdb4v8sZKBSqJcopguY8aMUYjFI4EsgkiR8y5QvBZSVpFShCyGbGxsmNXLyJEjWXuQIocG8L59+zIrF1Lk0N8BAwa892DE8koXSSwbsvxRzrpD/r9Ep06d8OrVKxw7doz1R5s2bTB+/HhmEfM20Muv8mAscVn5N9DU78rMmDGDuQPKs/um4uTRxMyavTRTliB5crNTYapkifI2UOaql2HX0GfsknLL0gsgrYaYK3mLkCWAckBTCfS5WQXKS5Q4FBdn1eHCcq1xCFNzK/YCT2bv8uRkpcK8nLa5cHQdC3RM8XCc3f1VKnE2L/mKxcUZ8916jdY4BClB6VrLSFd88czISGf+6OqgY5ydxfeCt48PYqKisHvXDqbIIXz9KmPJ0hVsNV0oLIalpRW+mvwl/PzUZwUxMRdfM9QO8uRmpZSxXnoTyPLm0+lbUFSYxzJYUYDh3cunsKDEmjCR9pOiPCTfu8ozcsZmBXl2LpvCgpGqw8rcFAJdXaRlKr4o076tpXrXOXn09ATw93RBtJJFgUSJk5CajuUzxpVrjUPkvb6nxNY0snuC9nPU3FNk4aZsfcPKK1npUOwqymiVmgVEJwnxdX8D1PMX4EKIzDok+HkRXsTJlCv6AnG9Fqa6zIJFArkiUUwYlfLklbJzsDBVlIn2JVY6pMSxt9bFoqmK98LY3uZ4Hi3E/K1iBRLFwYmISS0jD1nfyFvlWFD2p3jVg0R2ngglJaVlLIgsTQXIzBbXkfH6b1yS4jlRDBsbS7F1DcXBiYiWuWfp6b1uGzNd6fGS/XJlYRY7sjLi8ylr9VM/0BiG+jq48lq5pAoLC0s2blA8ubJjTdnAo6rHGl9Es7FmO1PkkGXo5o3r8N3MH1GvvtiigOJ1vYiIwP59u9+7Ioesb8gqRx7aL87MhqigEEUp6RAJhTB0ULTWMHS0RWGC4n2ncqxRGvto7ClvrKEsV5eOrsan09axODgSJM8SqsPCSpa5kJ47lClPE5RxqrSkBLpy7jaErpklRNmqlZrmHfsh/+4V5N8Ux0ETJkQj28AQlv1GIefsgbeqk9VrIW6bzAxFhWRWRhqsrG01XjeOTuIxnrJRxUW/xOE9G95ZkWNmbs3kyVJ6LmRnUDtr7qvTBzfi1P71mPjDShZzRqFOgR6cXBWttiieTsST4PJlUWobksXSSnNsnVMHNuHEvvWY8uMKBVnIbXv/tiUYO20BatQVW77Q9zEvn+L0wc1qFTnmr+9v5blEZgXmEk5y9zfNJfbu2lZGkUMK2tiYaHw9/QeN56UoT9nrhuQp77pxchY/i728/RATE4n9uzczRc6TRyHIykzH2E9l1jhk9bNx7T8skPKydaoTS1ibmTBFS2qWLJ4okZqdCzslKx11kOImwNUR0cmy9q3q7oRd341Gdn4Bc7WyMTfFJ3+sRzV3zVnOOBxV8Bg5b0FqaipTxsycOZO9+JMLkvIkh160SFFBih6KSUMWKBL3BFqpIkUQuTeR2xQFqKWgusqQRQ/FrUlMTJR+pi6miiZIsUQuX76+vmU2UrCQ9QZZ0Ny9K4s9QeeXkaF5NVMCHUfKA4rp0rBhQxarhSxKlCH3KgrYS7FqKIYO7cufK7WBvOvP25yrPOSeRQobspJSPm9SqMm7Ow0fPhxbtmxh1lIUi4igfiULGPmg0FevXmUPDJJXFVQXxb6Rt64hpZ6y8oXiH6mDrh1SDtJvyUP7dE5vC7UF1S2/Ka8CCvQM4OReDZFPZPEEKBBjZNh1uHq/u596yNV9MDG3hV919RkUJFAa49jkUvi6yNwI6NWG9l8lqlZWRSWKFMoTfq667HNlJY6dpQ5WHyks1/1DAgXBpfTh4a8DFRN03Yc/vAEPv7KrUBLOH16Ls/tXYNS0VXDzDlSrxElJeMUUPaQwKg+6hnx9/RASEqwgS0hwMAICKu4SSbGBVCkaSSFKShxyb6RYPA1euyaqaxdnj2p4GXZdQZYXYTeYe9S7YmBowpQm+bmZCH94Bf41Vac1VZDHsxpePFbsJ9p3e9/yPLiKgNpt1JbV19NDgJcrbj16piDL7UfPUcNXdfpxZcg1Kzw6ngU9VlbiRCUms8DHpDCqWF1gwb99XXQV7ylnXbxKUn1P0b1G3yvfU+rKS+vVIddFRWVLYRGQnC6SbnEpJcjIESHAU18hZpW3sx5exArVnsOreCGqyB1Dv0L7Ea/TfR+/no85azIxd61sI3aeycOGIzLz9YKiUiSllUg3CkKckV3CLGWk8hjqwNtFn2WAUilPCRAZX6xwDJ077VMqdSIlowTpWSWoZKe4cEH7lEVKIgu5WEm22CSxLNW8ZWO0saEOfFwNWEp0dbK8jCtGNR9FWar5GCJchetUyzomuPekgCmANI81lREacl9prLkP/4CKP49K5cYaiu1Bcw7l1XFdcuFRsxDxLmTcCIZta8UXWbs2jZF+Qzx+lhYXI/PeI9i1lhvndHRg26oRMm7cL3esiVB6JkQ8vgF3X/VjDWWqOn9wOYZ/vQquSs8EygBJSiD58asgPwcxL0Lh7iuL+aGSkhIUx7yEoZ9cem8dHbZf9Eoxvp70a4pD9tqyRILE0uRt6yQoW5mnTwAeh95WaJtHoXfg6686LqTa60YuDfrbQvK4e1fB0wey4MDMuvrBTXj5q3fnO3VgPY7vXYUJM5fBw7damTo9fKohMU7RHSop/pXG1ONMFp8qCoGKSZaw0Fvw1iDLif0bcGTP/7F3FuBRHG0c/8fd3d2DS3B3dy1WXAoUKBQopUD7UYoVd3d3d3cLEiAEi7t77vI97xxn4e4SoEBo5/c8+yR7Ozs3N7M7u/vfV1Zh1JQlcC3SFjqnKPW2mrr8OUUvWYRFxrfo+e3Bzu+7cm0Jvn/3A89vocJ7idMnj7H6KZB5SaD2uHt64+GDO3LtoXVv34CSt0conW/q1G+KOYvWM4sd8UJZqyhezuTpc5W3RVMDfs52uPFMOr5CYSFbL+um/AVO0et3aFQ8LGUCHosx0tNlIg4FQH7yJhr1yip/YfYtZq0qjcu/EW6R8xGQrzhlMKIHfnJnIaGAguzKZnCiz8l9hx76KUguuUeRq9L69evZQ3xQUBCzVCHxgIQd2Tg6YsglyMPDg4kMf/31F9LT05l4RHyIeSDFWiGBhYL0DhgwgD2kkbBDFigU80XsAkZWOxQzh6xkKOYNtaskkDBCE+aiRYuYQEWCAwUXLkqdOnVYP5CAQ1mkqA/E9OjRgwXupaxQ1JfUp2KrmI81haSMWBRDhgIc04WAYhalpqay9pGIQf1K7nHkUkaxZUhEOnz4sCQ2ELVz6tSprBxllYqPj8cPP/zAYv0oc6uiDFc0xtQPNN5UP/nlykJxeChANrlKkbhSNPYA8dNPP7HvpvGnjFUUHJkCGn9oNrGPIahxPxxcNwF2LoGwdyuLm6c3sBTjZWt2YNsPrh3P3KLqdxgrCV4cHx0m+T89JRYx4SHsgdfc2kVOEHpwdS/K1mjH3mKVhEvBBehSXwsR8UKWKrlWWU1oawG3n4ke8rrW10JqZiGO3xStX34owJA22qhTVhMhbwUo76kBRyt17LmQKxFxejXWZkGU1x3LYw85Ygue7FzRQ6Iq6jTvix0rJsLRLRBOHmVw6fhG5OVmo0pdUbyfbct+homZNVp0E1k+kRXOid2LWPYqMyt7pL2LcaCjqw8dXQMm4mxcMBqRr0Pw/bil7C2RuIy+oYnCDEpi2rXviPnzZrOYV97evjhwYC9ycnPQqHFTtn3unL/YPNW3X3+2vnPHNmZZQ1lk6Hy9dfsmzp09zTJTibl86SKMTUxgbWWN169fYeWKZahWrQYqKvF9F1O9aV/sW/0z7F0D4eBWlqUfz8/NRoVaomNm76oJLA5Eo05jJUFC46PEx0w+O2ai34qOGcoIRbx4dIl5dFnauiEp7g1O7pzN4uWI61RFjaZ9sHfVRDi4BcLBvQxLP07jVLG2aJx2r6T22KBJ5zHS9kS+a48gH2nJcYh+EwJtXWl7Qh9eZi5mlnZuSIx9gxM75rD/K9ZSHeupZ/N6+G3FVvi7OSHAwwVbj19Adm4eWtcVzX+/Lt8CazMTjOjaiq2v2ncCZTxd4GhjiYzMbGw8co5lo2pXv5pExBm/cD2evY7A/LED2I1iQorIwsTEUJ+JR6q4/LAAneu+O6fiC1ErUIOdU5TFiuhST3ROUbpx4sqjAgxurY3aZTTw9K0Q5Tw0WMDkvZcEEvecBuU18eStgFm+Geiqobq/Boz11RD8SkVKpnecuZmNljX1EJcsYOnH29bRZxYo955JxYoxPYzZ+rk7Ij+tUzdz8H1rQ7yOFojSj1fVhbaWGq4Ei85zssxJk7HwEZOUJkBCquqT/MS1LLSpa4jYRAHiKf14Q0MmqJDgIWZ8XzPcfZKL0zdFAYKPX83CwPYmTER5GZHP0o/raKvh0l2ppcvRK5ksRs7bmHy8jSlgMXLsLDWxeLvyFybHr2SiXX0jxCYWsP7p1MiIteVOiLQtE7+3wO0n2SwjFnHsSgYGdzTDq8h8hEXko1kNUVuKBjO2MSdLL+0SuXCJ5pq/mMUeZbQ7cGCf3Fwzb84sWFhYos+7uWbXjm2srGiuycPtd3MNxckh9PUNWCycdWtXsWuglbU1Hj0Mxrkzp9B/oDRtr6r04wae0thU+m6OMC7ni7ykVOSER8Pn9zHQdbDBg36ihAlvVm6Hy7Ce8J35E0tZblm/Gks3fqvNYEkdr/5eh3JrZyHlziOk3gqG68g+0DTQQ/gGxdmnxNRs1gd73s01lP3u6ru5plId0bywa4VormnaRTTXXDy8Cqf3LkKXoXNgZumA9Hfzvfa7awLd79Rs2hvnDixncw8JO6f3LGTisV9FkSu6KjIvHmXpw/PDXyL/bRj06zSHmrYusm+KEjyYdB8KYWoS0o/uYOs5T+7CoG5z5Ee+YanFybWKrHToc7FLbXF1KqN52x5YuWAa3Dz94O4VgBOHtrP04XUaiea65fOnstTZXXsPZ+sHd69nZW1sHdlx8+DOVVw5fxR9h0gTX2SkpyIxPhbJSaJ+o2DI7HeZmcPUTLVlTYPWvbBx8RQmvrh4BuLckc3Izc1G9frt2Pb1CyfD1MIa7XqOYusn963F4R1L0W/0nzC3skdqcoLk+k0uYETjtn2wZv54ePpVgndgFRYj5+Htixg9bbXKtjRu/R3WLfoVLp7+cPMKxOlDW9lxU7NBW7Z97YJfWFs6fCc6Z8gK5+D2Zej/4/9YavGibdHTN2SxcPZs+Bva2roi16rHd3D9wmF07itviV2Utu07Y8G8P+Hp5QMvb18cOrCHnd8NGzdj2/+eM5Od3736iWJW7t6xlZ3ftu/uJe7cvoHzZ09hyHBprEwiKysTVy9dQL8BxZ/TsrRq1xVL5v8PHl6+8PT2Y1YzdNzUbyRyLV4093eYW1iiZ19Rvft2boK7ly/LWEXHzb1b13Hx3AkMHDZWYuVDiyz0nGNmZs5SqKuiV4MgTNl4EAEudgh0scfmczeRnZuPdtVFgtvk9QdhbWqEUe3qs/XlRy+hrKsDnK3NkJ6Vg/WnryM6KZVlvhJz8m4Is/ahWDmhkXH4a9cp1C/njRr+yuNxcTjK4ELOR0DizPbt25mrErlTkRBC1jX16tWTCAgkvFAcHXqIpwDC5LpD+9HDPWVVIhcXEnQoS9OhQ4fYA1dRaF/KakXiC9VBcXXIDYtEAtlYMsVBcVTIdYuEEkpBTm84SCAgiyExJBTQ91AAYBIpKFgxZXQqCRRHhsQrCshL7jsk2FA8lt69e8uVoxsUyqpEfUMChywkrFA/kHsWCRfUL1SGBJ4P+a1FoexXZCVD7Xn58iXrf7JQmjRpEttOFknUZnIPI+GK+ofGliCh7cSJExg1ahTrf1qneDr0W5VBdZEFDrmamZiYsO8vapFDlks0/mStRS5f9N1FoWOLRKexY8eymDdkiUPxheih/XPjX6UFMtOTcOHgQmSmxcPG0Q/dRq6GobHoJik1KZoFphRDaVHXzBDdCBHXT65lC6UW7zVuk+RzcqlKS4pi2apKyoMwAQt63KSKJgtYTGmP1xzJlQQ0NjUilV3eemDrmTw0q6qFZkGaSEgtxMYTeYhNFpUyMVBDgJtIWPuxs/xxtfxgLl5GqX7IK1+9OesbEmcoKKW9iy8GTFghMYdPSZTvm2unt4ssbhbI3+A07jAMTTqOQGpyHJ7cPcc+mz9JXqAYMnk9PPyVx4mqU7ceUtNSsXnTRmYRSPPD9Ol/SITB+Pg4lg1BTG5ODpYuXcSyxGhr67DgxmPHTWD1iElKSsTqVcuZNR7d5DRo2Ajdukst55QRWFV0zJzbvwgZqfGwdfLDdz+ukrgXpCZFyb0ppGNmxW9SAeTq8bVscfGpgn4TRMdMTlYGzuyZh7TkGOgZmMKvUmM07PCjwnTlRSkTRO1Jxpl9C0UuCc5+6D12pbQ9idFQlz2Gk+OxdKq0/68cX8sWSjXef+JGUXuy03Fq1/x37TFBQOUmaNRxdLHtaVKtApLTMrB8z3EkpqbB28UBi8YPlqQUJ5GGglKKScvMwu+rd7Kyxgb68HV1xJqpI1nqciIuORUX74oyyPSYLO8CunzScFT291TZnuCXQhjoFqBxJS0Y6QNRiYVYeyxPek4ZqMmFRHobV4jtZ/PRpLImmlYRnVObTuVLzikqa2Wqhu+8tdm5Su5bJBKtOJTHUpEXx/HrOdDWVkOv5obQ11VDaHg+FuxIk0vLTYGYKcixmNsheTDSz0LbOnrMLYvcsBbsSEd6CbNTqeLo5UwmfPRtYwx9XXVm/TJnUzJzHRNjbaYJQwPp2+ebj3JgrK+ODg2MmBsTiTW0j2wQ55PXsqClqYYezY2ZaxqJOX9tSGICjTIOX8pgbfm+nSlry/M3efhrfaJ8W8w1YKQvfVlw42EOjA1S0bGhEUyMNFhgZdqnaEBpSkdOwtZDmQxXyqjN5poUbNm04d1c44Fp0/8nN9fInt8UH2/Z0oVF5pqfWT1ixk+YjA3r12DO7JnISE9ncXJ69e6H5i1ED/mqMKkUiOpnpNcW/zmi63n4xr0I7j8ROnZW0HOSWkRkv45goo3/3Ilw/aE3ciJi8HDwL0g4dVlSJnrXMWhbmcN76kjo2Foh7UEIbrYagLwiAZCLUrbau7lm70J2TaC5pu9P8nON7DXhxlnRNWHbIpFYIKZBu+Fo2EGUEbN2ywHsoX7/uqnIyUqDi1dF9B23skRxdHLuX0eagTEMm3aChrEpE2iSVv0JYYZI7NUg1x0ZCw1RHJxCGDXvDA0Tc1aORJz0oztLXKcyqtVujPS0ZOzZuhKpyYlwdvPGT1MXSNyHEhNiWVZMMfSwvmH5X0hKjGPHjZ2DC4b8OJ3VI+buzUtYtXC6ZH3JHFEmV0pJ3qH7IJXtqVyzGTLSknF4+1KkpSTA0dUHIyYvhfG79iQnxLD7dDEXT+5iLsar5ogEATEtOg9Bq65D2f/lgxqi+8BfcGLfWuxaNws29q4YOG4uPP1UuwdWqdWU9c3BbcuQlpIIRzcfjJyyRNKWpIQYub65cELUlhWzf5Krp1WXwWjTTSRoDBzzJ/ZtXoQ1f09CZkYaswpq12M46jZVHT+tVt367PzetmkdO7/Jembq9FkwNTOXOb/lx2nF0gUsnTeNk4OTE34cN4nVI8ulC+dQiELUrqfairYoNes0RFpqCnZsXsMyXrm6e2Ly9DmS9iTEx8rPN7k5WL10HhLfHTcOji74YewUVs+n0qyyP5IzMrH08AUkpGXCx9EGS0d0k6QUj0lOlbvPIvFm+tYjrKyxvi78nWyxYVwflrpcDAU1nrP7FHPRsjIxRKugMhjcvPhA0ByOItQKeXSlbwqyJiHLEgrkS2LMvxmyPunXrx8TNEpqHcT5MDaqfqH2xXkUojxWw5emVuXPF5jvY/AzKz2pKW/HqH6L9aXRUC89l7HmmsdRWvjj/ofdQH9uEuPlYw18TfJyPn+A8w9BUJw54Bfk1+8Vu7V9LUJ938/U+bXIvhyC0kLNnd+hNBE+cBlKC+n5Xyd4tDI01UvP+W2t+3mCun8s+cKPjw/6T+P9tvRcv3Ubyr8M/5Y4/6j03MvLUi/w3/csyS1ySjmUntvQ0JBZYpB4Q9Yh5JLzbxRxKM03WRWQlQrFpiGXMAoUzUUcDofD4XA4HA6Hw+FwRPBgx6UciotDWZQoIDGlNScXnwMHDnxxyxgSkxQtFFvmnyImJgbfffcdi1FDcW0oVbs48PCQIUOUtoG2cTgcDofD4XA4HA6H81+AW+SUcijOTNFYM1+aNm3ayAUmluVTUqYXZfz48WxRxPTp01ngYkVQfB0Oh8PhcDgcDofD4Xw9eNCWLwcXcjjFQsGbafmaWFtbs4XD4XA4HA6Hw+FwOJz/Mty1isPhcDgcDofD4XA4HA7nG4Fb5HA4HA6Hw+FwOBwOh8P5JISQpmTnfF64RQ6Hw+FwOBwOh8PhcDgczjcCF3I4HA6Hw+FwOBwOh8PhcL4RuGsVh8PhcDgcDofD4XA4nE+isJC7Vn0puEUOh8PhcDgcDofD4XA4HM43AhdyOBwOh8PhcDgcDofD4XC+EbhrFYfD4XA4HA6Hw+FwOJxPorDwa7fgvwMXcjic/zBxiUKUJoSlaPaPTtJAaUJd3QGlhegElCp0tEuPcWmwSx2UFoSC0nM+EZpapeecenYrBKUJz/LeKC28zrBEaSL7cukZK71afigtXLjwFKWJxFelJy5GUkoBShPlvEpP37yKLz33EoRG6bl845nBdygtdP7aDeB8E5Si04fD4XA4HA6Hw+FwOBwOh6MKbpHD4XA4HA6Hw+FwOBwO55MoROmxQPu3wy1yOBwOh8PhcDgcDofD4XC+EbiQw+FwOBwOh8PhcDgcDofzjcBdqzgcDofD4XA4HA6Hw+F8EsLSlWfhXw23yOFwOBwOh8PhcDgcDofD+UbgQg6Hw+FwOBwOh8PhcDgczjcCd63icDgcDofD4XA4HA6H80kUFvKsVV8KbpHD4XA4HA6Hw+FwOBwOh/ONwIUcDofD4XA4HA6Hw+FwOJxvBO5axeFwOBwOh8PhcDgcDueTKORZq74Y3CLnG6Zv375o165dicrWq1cPo0eP/uxt+q9x/vx5qKmpISUl5ZPqef36Navn/v37/1jbOBwOh8PhcDgcDofz74Nb5HA4X0GAI+Fn//79ks+cnJwQHR0NS0tLlAYeX9uC4ItrkZ2RAHNbX9RoMxnWTmWVln/58Dhun1qIjORIGFu4oGqzsXD2rSvZnpWegJvH5yIy9Apyc9Jh51qZ1Wli6VpsW2oEaKJeeU0Y6ashOlGIfZfzER4nVFq+rLsGmlXVgpmRGhJSC3Hkeh6evpWWD3TTQPUATThaqcNAVw3zdmYjKrHkrw/uX9yC22fWIDMtHlYOvqjfaQrsXBX3TUJ0KK4eWYi48MdIS4pEvQ4TUbF+X6V13zy5EpcPzUWFer1Rv+PkYtty+eRWnD+0DumpCbB39kH7vpPg7Km4LdfP7MLtSwcRE/GCrTu6+aNF11Fy5U/sXoJ7144hNTEGGpparEzzrqPgoqROWR5d3YIHF9YgOz0BFna+qNn2F1g7K94vKSYUt08uRHzkY2QkR6F664koW7vPJ9VZlAeXtuDu2TXISo+Hpb0v6nacAlsXxfsmRofi+jHROKUnR6J2u4moUE9+nIIvb8XDK9vYOBIWtl6o2nQYXP2lx7kyzhzdieP7NyI1JRFOrl7oOWA83L0DFZa9cHIvrp4/gsi3YWzdxcMPHXsOlytP9ezeuBCP7l9HdmY6vAMqsjpt7J1L1DfVAzRQl84pPTqnCnHgSh7C45SfA2Xc1dG0ivScOnYjX3JOqasDTatowtdZAxbGasjJA0IjBKxMWlaJmoNWNXVRq6w29HTU8DKqAFtPZiM+Rfk5TtStoI3GVXRhbKCGiDgBdpzJxpsYgWR7jyZ68HXRhImBOnLzC/EyUoB9F7MRm6S6XuL77s5o3cgWhgYaePg0HfNWvEBEdI7S8uX8jdGtnSN8PAxgaa6DSTOf4PLNJLkyZiZaGNLbFVXKm8LQQBMPHqdhweowlfUS7eoZoE5FXejrquNFeD42HklHXJL0dyqiQRU9NKuhDxNDdYTHFGDLsXS8iiqQbB/fxxS+rtpy+5y7nY1NR9KV1nnx+DacObQeaSkJcHDxQafvJ8LVs4zCsldO78bNi4cQHR7K1p3c/dG6+yi58puWTMbNCwfl9vMrVxPDJi9HSbh+egsuHV2LjNQE2Dr5olWvyXDyUHx+3zq3E/euHERshKg9Dq7+aNz5R7nyhYWFOLN3EW6d34WcrHS4eFVAm75TYWmr+hplXqsy3Mf2h0nFQOjaW+N2x2GIPXhG9T51qsJ/zs8w9PdCTng0XsxchoiN++TKuAztAfcx/aFja4W04Kd4PHoGUm89LFHf3DizBVePrWF9Y+PsixY9f4Gju+K+iYsMxdl9CxH9+jFSEqPQrPtEVG8iPxfnZmewMiF3TyMzLRF2zn5o3mMyHNwVj//nnIdvnVqBsOCTSI57CU0tXdi5VkDN1uNgZuNeor6p7KWG6r7qMNQDYpOB43cEiJI/VeXwc1JDvbLqMDUAktKBM/eFeBEtP1daGgMNy6nD2VqNzYcJqcCuy4Ji578rJ7fiwpG17Ppt5+yDdn0mw1nJMXzj7C7cuXwAMeGi67cDuzaPlpQXFOTj+K6FeHr/IhLjI6CnZwjPwOpo0W0MTMysi+2XO+e24MYpOmbiYe3oiybdpsDeTXFb4qNCcengQsS8fYzUxEg07DwRVRu9f1+TnhyLc3tnI+zxJRTkZcPMygUt+/wPdq7FHze3z23BtROi9tg4+aJp9ylwUNaeyFBcOLgQ0W9E7WncdSKCirRn0c8N2LaiVKrXA817Ti12rrl8TGau+W4yHJXNNed34r7MXGPv6o8mnX6UK8/mmn2LcPvdXONMc02f4ucaDkcR3CKH868lLy8P3woaGhqwtbWFpubX11bDgo/i+pFZqNhwONqP2AMLOx8cWzsQ2RmJCsvHvrmHs9vHwadyR7T/YS9c/Rvi1OYfkBTzXHLROrVpBNKTwtGk1xJ0+GEvDM3scXTN98jPU32nU85DA21qauHU7Xz8vTuHCS4DW+mwmzBFuNioo2djbdx8WoD5u3Lw6JUAfZvpwNZcGkFfWwt4HS1gAs+H8uzOUVzYNxPVmg/Hd+P3MSFn79L+yEpX3Dd082Ji6YhabcbCwNhKZd0xb4IRfGU7LO19StQWElwObvoLTToOw4//2wV7Fx+s/HMw0lMVt+VFyC1UqNECQ39Zix+mbYGphS1WzByE1KRYSRkrOxd06DsZ42btw4ipm2Bm5YCV/xuIjDQVd7pU9/2juHboT1RqNBwdR+2FuZ0PjqwZoPSYKcjPgZG5E4Kaj4W+kdU/Uqcsz+8exaX9MxHUbDi6jdsHSwdfHFiuYpzys2Fi4YiarcdCX8k4GZrasgeG7uP2otvYPXD0robDa4azhw9V3Lx8EjvWzUObroMwde4WOLl6Y970EUhLUdynzx7fQVDtphg/YwUm/7kO5pY2mDttOJIT4yTn0+KZYxEfG4mRE+dh6rytsLCyw5zfhiI3J7vYvqFzqnUNLZy+XYAFe3KZONq/pQ4MdJWfUz0aaePWUwEW7M7F49cC9G6qDRsz0TmlrQk4WKnjzN0Ctn3jiVxYmaqz864kNKmqg/oVdbD1VBb+2pKO3DxgZGcDaGoo36eSjxY61tPDkas5+N/GdETEC9g+JPaKeRsjwMZjWZi2Nh2LdmVCTY3qNWR/VdGjvQM6trTH3BUvMHjCA+TkCjDn10BoaynfUVdXA2GvMzB/5UulZf6Y6Ad7G11MmhmC/mPuIzY+B/N+C4SujvLbsOY19dEoSI+JN7+vTkJuXiHGfmeqsm+qBOigaxNDHLyQiWkrkhAeW4Ax35nK9Q1x4U42Rs9JkCy7TmUorfPO1ePYt3E2mncagvGzdsLBxRtL/1Ax1zy5hUo1m2Pk1LUY8/tmmFnYYunvg5EiM9cQfuVr4o+V5yRL31GzUBKCrx/F0a2z0KDdcAyfvge2zj5YP5vmKcXtefX0FspWa4H+E9djyK/bYGJhh/WzB8jNfZeOrMa1U5vRtu9vGDp1B7R09Fmd+Xm5KtuiYaCPtOBneDRyWonarufqiCoHVyDx/A1crtwWrxZtQJkVv8OycS1JGbvOzeE3eyJCf1+Cy1XbIz34KYKOrIG2lXmx9T+6cRQntv+Jem2HY/Bve2Hr5INNcwco7Zv83ByYWTmhUeexMDRRPPcdWDcFYY+vosPAWRg24yA8Amtiw5x+SEuWH88vMQ9Hht1E2Vo90WX0TrQbug5CYQH2L++P/NziVWN/ZzU0rqCOi4+EWHVcgNiUQvSorwF9JVOVoyXQoYY67oeJyj+LKESX2uqwMpGWMTME+jTSQEI6sOmsACuPCXDpsRAFqrVW3L92DIe2zELjDsMw+vfdsHf2xeo/ByFDyTkVFnIT5au3xODJ6zBi2lZ2/V7150DJMZyXl4PI10/QqP0QVl/v0QsRH/0K6+cOL7Zfntw6ijO7Z6JWy+H4fvI+2Dj6YsfC/ky0U0R+XjZMLR1Rr73y+5rszFRsmt0d6hpa6PrDKgz87QgadJ4AXQOZzlPC41tHcWrnTNRuPRwDpojas+3v4tvToIPyY/j7ybsxes5lydLjx3Xsc7/KzVS25eGNozi2bRbqtx2OYdP2sPNp/ZwSzDU/r8fgKdtgYm6H9XMGIE12rjm6GtffzTVDft0BbR19bJhT/FzzLSGEWqlc/o3854Wc3NxcjBw5EtbW1tDV1UWtWrVw69YtObeZI0eOoGzZsmx7tWrV8OjRI7k6Ll++jNq1a0NPT49ZVlB9mZmZku2urq743//+h++//x5GRkZwdnbGypUr5eoIDw9Hly5dYGpqCnNzc7Rt25a524gRCAQYM2YM225hYYHx48ezG/oPoaCgACNGjICJiQmz/JgyZYqkjunTpyMw8P03xOXLl2flioP6rHHjxqxeqr9u3bq4e/euZHuPHj3QtWtXuX3y8/NZ+Y0bN7L19PR09OzZEwYGBrCzs8P8+fM/yCWM+nnGjBno3bs3jI2NMWjQoBKNz9KlS+Hl5cXG18bGBp06dSrR8aGI3377jfWZLH///Tdrm3j7hg0bcODAAXZs0ULHmSLXqgsXLqBq1arQ0dFh/fHzzz+zMRRDfUNto2OBjhkSgqj+T+XhpQ3wrdIZPpU7wMzGE7Xa/QZNbV08u71XYflHVzbC0asWytXpDzNrD1RuMgqW9n54fG0r256a8Bpx4Q9Qs91UWDmVgamVG2q1nYqC/FyEPTiisi11y2nixpMC3HomQGxyIfZcyEN+fiGq+CoWvGqX1cSzt0Kcv1+AuJRCnLiVj8gEIWoGSsvffS7AqTsFCI0o/s18Ue6cW4fA6l0QWK0jLOw80ajrNNY3j67tUVie3jzWbTcBvpVaQkNT/g24LHm5mTi64Sc07v47dPWLv9EhLh7ZgGoNOqFqvfawdfREx/5ToaWti5vnFY/TdyP+Qs0m3eHg6gcbB3d0GTQdhYVChD66LilTsWYreJepDgsbJ9g6eaLtd+ORk52BqLciUU4ZDy+th19QZ/hW6ciOmTodprG3pU9vKe4Xa6cyqN5qPDzLt4S6ptY/Uqcs986Lxsk/qCMsbD3RoLNonJ7cULyvjXNZ1Go7Ad4VW0JDQ/E4uQc2YNY3plauMLN2Q42WP7KHvZg3qt0hTxzcjDqN26N2wzZwcHJH7yGToK2ji0tnDigsP+jHP9CgeRc4u/nAztEN/YaJ5uknwTfZ9tiotwh7/hC9Bk+Em1cA7Bxc2f95ubm4cel4sX1D58iNEAFuPxMgLrkQey/mI78ASs+pWmU08DxciAsPROfUyVsFiEwolJxTZIGz+nAegsMEiE8txNu4Quy/nAdHa3WYGhZ/49Sgkg6OXc9B8IsCRMYLsf5oJrMkKe+l+LggGlbWwZXgPFx7lIeYRCG2ncxGXj5QPVA6dpeD8/AiQoCkNCHC4wQ4eDkb5sbqsDBRfdvTuZUDNu0KZxY1L99k4Y8Fz2Fhro1aQRZK97lxNxmrt77FpRuKb+4d7XUR6GOMuSvC8PRFBsKjstn/OjrqaFhbucDbOEgPhy5m4v6zPGZ1tHp/GkyN1FHRV7lI1rSaPi7ezcbl+zmIShBg4+F05OUXonYFefWbPkvLFEqWnDzl9xPnDm9E9YYdUa1+e9g5eqDrwF+hra2Ha+fkrUjE9Bk5C3WadoOjqy9sHdzRY8g0Ntc8e3hDrpympjaMTS0li75hyea+K8c3oHK9zqhUpwOsHTzZA5GWji7uXFA893UZOhvVGvWAvYsfrOzd0b7/DBQKhXj55BrbTufXlRMbUa/NEPhXasiEoc6D/0R6ShyzQlFF/ImLeD71b8QeUF1OjMugbsh+FYGQ8bOQ8fQl3izdgpg9J+A2SmpB4Da6H8LX7ETEhr3ICAnDw2FTIcjKgVPfjsXWf/XkelSq0xkVandkfdOq9zR2Xbh3SfHcR1Y1TbuOR5mgltBUMBfn5+Ug5M5JNOkyDq4+VWBh44L67X6AubUzbp3d9sXn4XZD1sA/qAMs7LzYi5RGPf5EenIU4iIeF9s31XzUcS+sEA9eFSIhDThyS8jmvvLuiuepqt7qzPrm2lNR+fMPhYhOBqp4SeeQ+mXV8SKqkFnqxCQDyRnA88hCZBXzTH7x2HoE1e+MKnU7wMbREx2+n8qO4ZtKjuEew2ejRmPR9dva3h2dB4qO4dDHouu3nr4RBk1cg3LVmsPa3g0uXuXQvs8viHj1GMkJUSrbcvP0OpSr1QVla3aEpb0nmvUUjVPwVcXjZO9aFg06TYB/lZbQ1FI8TtdPrIKRmS1a9Z3JLHtMLZ3g7l8LZlbFW43eOLUOFWp3QfmaHWFl74kW34mO4ftXlLTHrSwadZ6AgKrK77MMjMyZyCNeXgSfY21x8a5a/FxTVzrXtKG5RlsXdy4qmWuGzEZQwx6wKzLXhMnMNVdprmk9BH4VRXNNp0Elm2s4HEX854Ucegjes2cPe7gm4cHT0xNNmzZFUpL0belPP/2EuXPnsgd4KysrtG7dmokQRFhYGJo1a4aOHTsiODgYO3bsYMIBCSay0P6VK1fGvXv3MGzYMAwdOhTPnj1j26gu+k4SeS5duoQrV67A0NCQ1Su2KqH9169fj7Vr17L6qX379im+iVIG/Uay+Lh58yYWLFiAefPmYfXq1WwbiUwhISFyIgW1lX5Tv379iq2bRJg+ffqwtl2/fp0JIy1atGCfEyTQHDp0CBkZ0rd+J06cQFZWFtq3b8/WSaii337w4EGcOnWK9YWsGFQS5syZg3LlyrG2kwBV3Pjcvn2biSEkZNF4HD9+HHXq1Pmg4+NDGDduHBPsqE3kSkVLjRo13isXGRnJ+q9KlSp48OABli1bhjVr1uD333+XK0ftIuHrxo0b+Ouvv9jvoL77WAQFeUiIegwHz+qSz9TU1eHgUR1xbxU/sMa+fSBXniBhR1xeKBCdK5qaOnJ10gU35rXy8dVQF73pfy4juNCjRmikkFkJKII+D42UfxX2LJzKq3iF/QF9Exv+GC4+NeR+B61Hv773SXWf3Tkd7gF14eL7/rGgiIKCPES8egKvQGm/q6urwzuwGt6EPihRHXm5ORAUFCh9eKLvuHZ2F3T1jZjblqp+IRcpB0/5fnH0qo7YYkSOz1En7Us39U7e8vvS+qeOkxihUIDnd4+wt8C2rhWUlivIz8ebsKfwL1dVbpz8y1ZF2LOSuUnk5uVAICiAgaGxqM4C0TVBS+YGmuqkG+rQENV9Izqn1JjAIXdORQiUnlPOdE7JlCeehwvY58rQ1VaDsLAQ2bmqXzZYmqgz0ebpG6lATcLQq2gB3Ow1lf4GZ1sNuX3oW2jdXck+ZIVHIk9CigDJacoFXDsbHSba3H4gjXmWmSVASGg6E2I+Fm1NUV/l5cvMZYV07S9EWT/F9ZJVk6mRBp68FM2fBPXny4h8eDhpKe0bF3tNPHmZJ9c3tO7hKL9PtTK6WPCTJaYPNUfHhgbMskoRBQX5CH/5BD5lqskdb7T++vmHzTUGReaaF09uY+KAupgxqjV2rJqBzPTiY83R8R/1+jE8A+TnPk//6nj7omTzDVmh0Dml9846IDk+grlNeMjUSfMeuSO9fVGy31hSTKuVR8JZ0UOdmPhTl2FWTfQCSE1LCyYVA5Bw5qq0QGEhEs5ehWk15XONuG/IRco9oIZc37j7V0d4CfumKEJBAZvvNLXkxUN6mH0beuerzsNEXrboHrO4FyDk8mRnDryKkZ+TXsUWwtFSsZBDn9N2WV5Gy5f3tFdDUnohetRTx5j2Gvi+sQZ8HNSKHadIdv2WP6foev4m9H7JzylBAfRVWLhkZ6ezF4R6+sYqx4lcpNz85MfJ1bcGIl9+/DiFBp+FnUsg9q0YiQXjqmPt7+1w/9LOYvej9pCL1Hvt8auByLB/5rih73h44yDK1ezI+qe4uUZ2XqBxovXwD51rDIufa8L/4bmG89/g6/txfEXIKoMekEkgad68Ofts1apV7EGYHprpIZqYOnUqszYRPzg7OjoyEYUeyGfOnMlECrHVCAkYCxcuZBYpVDdZcRD0UE4CDjFhwgRmbXLu3Dn4+PgwcUEoFDJRRTyprFu3jlnfkLVGkyZNmFXHxIkT0aFDB7Z9+fLlTAj5EMgahb6XvoO+9+HDh2x94MCB7DeRQEHfK/7d9D/9Dnf34n2PGzRoILdOFkfUfrIqadWqFaubBAfqt169erEyW7duRZs2bZiARYIP9S191rBhQ8n329vbf9BvpHaMHTtWsj5gwACV4/P27VvWLmojtcPFxQUVKlQo0fFBAt+HQgIdWQaRpQ9Z0CiDrIRovBYvXszGy9fXF1FRUezY+fXXX9nFhCBLMTo+xb+Nyp85c0ZyvH4oOVkpKBQKoGco//ZZz8gCKfGvFO5DcXT0DOVj+9D+9DlBFjiGpna4eWI+arf/DZpaenh4ZQMyU2OY37wyKH6NhroaMrLlb6TSswphbar4IZLcB2i7LBlZhe+5FXwM2ZnJrG/0jeX7Rt/IAkmxyl0qiuPpnSOIDX+Cnj/tLvE+mWkp7ObayES+LYYmFoiLUjxORTmydS7znZcVg4gnd89j08Jx7E2skakVBk9aBUNjM6X15LzrFzpGZKFjIiWuZG35J+uUjFORfWk9+RPGiUiIeoZdf3dDQUEutLT10ar/EvamWRnp6aJxMi4yTsamFoiOlFpcqoJi4ZiaWSKgXBBbt3VwhYWVLXZvXow+QydDR0cPJw9tQXJiLFKSReecMsh9is6p9CIeWHSOqTqnMhSUV3ZOkdtPi2paePBCgFypBqEQim9DkEWILOmZQsm2ohjqieaFtCz5fWjdxlz+lqZOeW20r6vHhKWYRAEW7MqEQIUhnoWpSBxLTpV3u0xKyYO5qXILoeJ4E5mNmLgcDPrOBXOWvUBOrhBdWtvD2lIHFmaK3yAbG6or7Btap7g/ijDSVxf1jYJ97CylfXPjYQ4SUoVISRfAyUYTnRoZwtZCA0t2pr1XZ2ZasugYNpU/ho1MLRBbwrnmwJb5MDG3khOD/MvXQvmgRrCwdkB8TDgOb1uIpf8birF/bIa6unLhPevdOWVo/P7cR64kJeH4jjkwNrOGxzvBg2KUiOuQr9MSGSnKr1Efg46NJXJj5c9TWtcyMYK6rg60zEygrqmJ3Dh5667c2EQY+Ki+F8tKT1bSN5ZIiPm4uVhHzxBOHuVx4eBSWNq5s7oeXj/CHmTNbZy/yjwshiwdLu77H+zcKsLCzltlWXKfUqf7iRz5+4PMHMDSSMlcoyvaLgvtb6CnJplPdbTUUMNfHeeDhcwqx8NODZ1rq2PjGQHeKjl0SLBk42Qif99E4xYXVbK+Obp9LjuGi16/xZCbztFt81C+egvo6hsqrScrQ/E4GRhbIDHm48cpJT4cdy9sQ9VG/VC9+RBEv36IUzt+Zxa4Zau3L7Y99P1F++ZT2iPLs3unWWyacjWVt4O1RTJO7881CSWca07snAMjU2t4+IvmGhJxxHXI1WlsifTUf3au+ZrwrFVfjv+0kEPWGmQNU7NmTclnWlpazJ2FrFPEgkb16tKJklxYSASh7QRZS5Clx5YtWyRlyHSOhJlXr17Bz89P8sAthh7M6SE+Li5OUseLFy+YkCBLTk4Oa2Nqaiqz3AgKEt3IE2RZQxY+H+JeRW5hsuoz/S6y9CG3LYrRQoIOWeaQpQ4JBSSqkNBTEmJjY/HLL78w4Yl+F9VJ1jYklIjbS8IX9RMJOSSSkHvR9u3b2faXL1+ysaC+F0MuWtTXHwL1iSzFjQ8JHiTekFhFVjK0kIWQvr5+scfH54Tqp/GRHS9qB1k0RUREMPe8oscVQS5Y4uOqKCQe0SJLQb7We2/a/mnIR7rRd4twcc8v2Di9GtTUNZiFj5N3bfa2+L9MenI0zu/5Ax2Hr/3s4yDLmQOrWIydYVPWQ0tb/ns9/Kti7J972M3m9bO7sWnBWIycse090ei/CLlUdf9pP/Jy0hF6/wRObpmAjj9sVinmfApH9qxjMXbGz1gpGSdyfxg+YQ7WLZ6OH3rVZw+9ZPFTpmLND3a3/achffm7xtrME51ctopSxU8LPZroS9aX7lEel+Wf4OaTPIS8LoCJoRoLjDywtT5mb82QxK9oXMcKY4dIx27CH8W7Z3wMAkEhfpkVggkjvHB0c3UUCApx50EKrt9Jgthtv1oZHfRuJb0H+HtrKj4XF+5Kn04j4wRISRdifB8zWJllIj65mOAeH8jJ/atx98oxjPxtrdxcQzF0xNg7e7O4O9N+aIHQx7fkBJ9/mguHVuHhjWMYMHHDe3MfRzEdBv2F/WsnYe6Yumy+sXPxZ65YUW8+z/lSUs7vnsZilHUaJXLj/tKIb8+eRxTixjPR3Etxd5wsC1HJSx1v4z/cfbsknD24CvevHcWQXxQfwxT4ePOiMcwer0M/1YF8Pxd0LSKLnHrtqR2ArbM/C5J878J2lULOl+D+5T3wDKwDI1Obz/o9Fw6L5pr+P/O5hvP5+E8LOf8E9GA9ePBg5p5TFPHDtlgAkIUe0ElMENdRqVIlObFBDLlyfSnIZYzisZDVjLa2NhMxZOPFqILcqhITE5nLFgkjVA8JEbIBh8kyhixhSGggqxayTCHh5J+ErGs+ZHzod5LLFAlQJ0+eZNYuFGdGVRwcVZAAVvRhSuyG9zlQdVwVhazHpk2TD8jYuMuvaNJVeqHX1TdlQkvRgLLZ6YnQN1KcUYusJMTWN5LyGYlyVjpWDgHoOHIfewCmmww9Q3PsX9IVVo4BSn9bZk4hBMJC9gZeFrIESCtidSOGrHGKWgoYKrDS+Rj0DMxY32QVCXJHgRsNjD8u21js28ds/81/iSztCHobFRF2i2XHGjX/ocK30wbGpuzzosFGKVCikanqtpw7vA5nD67BkEmrWYDkoujo6kPH1gWWti7Mz37mj81x89xeNGw3UGF9uu/6hY6R9yy1lBwzxfEpdUrGqci+tK7/keMkhtwBTa1c2P/WToGIC3+IBxc2okHX6QrLGxmJximtyDilpSTCpJhxoixXR/eux7hpy1imK1lcPfwwbf42ZGWms7hZxiZmmDG+N1w9/FXWSW+X6ZwyKhIsnM4xZecIfW5YgvJiEYfi4qw8lKvQGif4RT5eR0szI4mD9hobqCMtUyogGBmos5gwiiBrIPoNxvpklSItQ+tpmfJtIjetnDwh4lOAV1GZmPuDCYu9c/upqHEUB+fJc6m5vpaWyNLFzEQbicnSH2Buqo0Xr6Rx1T6G5y8zWZBjA30NaGqqITWtAMtnlcOzMFF/UByclxHJ0r7RlPZNaoZ0Tqf1t7FStzJZ0rOEor4pYrFTtI6ivIwU/VZrc433hBwDYzPRMZwifwynpyS+Z6VTlDMH1+P0/rUYMWUVy3SlCksbJxgamSE+5q1KIUf/3TlVNNgozX1FLRyKQlmuLh5ZhX7j17LYFGKM3u1HdRibSjP80NtzinXxT0LWN2SVIwut56emQ5iTi7yEZAgLCqBjLd+3OjYWyI1RbXGnb2SmpG8S2Bv/j4Xi4Xz/82bk5WaxDFZkYbBz6Y8sSPLXmIeJ87un49WT80xINzJVbt0s+d5ccokthKEu3R9I5wmyqilqpSMmI0e0XRbaPzNbWiedb/Fp8vtTPB0nK+VWwAbiY/iddYbk+9ISJceiMs4fWYtzh1azeDiKXJ7p/mrTojEsLs7gSetUWuMQ+oaKx4kCCxd3PqmC4tBY2nnIfUYWXc/unShRe4oGNqa++ZRjWExKYiRehVxFp2GLii0rmWsU3GcV1zeXj67FJQVzjXg/0b2azFyTRpnL/tm5hvPf4D8dI8fDw4M9yFNcFtmHbnqI9/eX3hBTzBcxycnJeP78ucTSpmLFinjy5AmLnVJ0obpLAtURGhrKAuoWrYOsUmghSwuKgyKGbt7v3FHun6wI2f3Fv4vcccgaR2w1Q4IMuTTR0q1bNya2lATqQxJLyIUsICCACTkJCfIXKYoFQ+5C5EpGolXnzp0lQgRZxND/sgIKWSJRX38KJRkf+t2NGjViMWbIeocCD589e7bEx0dR4S0mJkZOzJENYExQnWSxpAo6vq5duyZXD7WDrLbIDe5jINc86lPZpUGHn997ULW0D0Bk2HU58+WosOuwdpYP4izGxrkc2y5LxIurCstr6xoxEYcCICdEPoKLn8iNThHkAkHBT70cpdMU3Rp5OqjjTazihxL63MtBXvjwdqTyn/6WmfrGxikAb59fk+sbWqcUqB+Ds0819J54CL0m7JcsNs6B8Kvcmv2vzMWAgoRSanDZQMUk4IU+vsHEF2WQgHN673IM+nkFnDwUp78uSqGwUBKXRVm/kFAX+UK+XyJfXIeNi+Jjpjg+pU7a19oxAOGh8vuGf8I4KYMCuJK/vTI0tbTg4uGLkOBbcuMU8vAWPHyUp2A9tm8DDu1ajTG/Loabp3JxRt/AiIk4FAD5dVgIKgSpToUuOqcK4SlzjojOKQ2l59TbWKFceYLOSfq8qIhjaaKGVYdzlQb6JHGH0oqLF8qYRQKDj7P0nZKuNuBmpyGXLrvob6CMVD4umnK/gdYpdbmqt+e0aGpIH7CycwSIjMmRLK/Ds5CYlIdKZU0lZfT1NODnZYRHz953O/oYKOYOiTiOdrrw8TDE5RuieGsUbDguWSBZouLJUkYAf3epWE8uYu6OWggLz1faN2+iCuDnLr33oF9L62ERyl8oONuKviM1/f15kizAKH3480c35I7h54+uw9Vb+Vxz+sBaHN+zAkMnLYOzh3LBXkxyYgwyM1JgYqb65RXNffauAQh7F+RV3J6wJ9fh7Kl8brh4ZDXOHViGPuNWwtFdfu4zs3JkD1gvn0jrpCDvES+D4eyp/Dd+DCnX78OigbxQZdmwBpKvi+4TCvPzkXr3MSwbyLjMqKnBon51pFy/V2zf2LkGSII4E8z6OOQ6nFT0TUmh7Dr08EkZicIeXYZvBXmX+i8xD9M9EYk4YQ9PocPwDTCxUC4myULvt6KTAFdbeYHFzUYNEQmKhRz6nLbLlbeVlqc6oxIBiyKuWeZGQGoRUbnoOFH68BdFjuEXj67DxUv5OJ07tAZn9i3HgPEr4VTkGJYVcRJi3jChhwSj4qBxsnUOwOsQ+XF68/QaHNw/fpwcPSoiMVbe/Sgp9jVMzB2KbY+dSwBeFWkPtc/B49Ov3w+u7GVuW15l6hVbVjzXyM4LNE60rup8ogx45w4uQ5+xK+Hgpniuofmq6Fzj9A/PNV+TwkK1Urn8G/lPW+SQ9QYFHaZYJ+QyRRYa9DBPLkH9+/dnbjkEBZClTFGU0Wjy5Mks01K7du3YNopZQi5LFDyX4rFQnSQckMUJxSspCWSpMnv2bJapir6LHtTfvHmDvXv3smC7tD5q1Cj8+eefTHiheCnk/pSSUnxgQFnIzYkCCpOFClmhLFq0iLlWyUK/QSxSyQoYxUHt2rRpE3NtSktLY32qSASi7FUU34cEGooRJIYEChKRxGNBohbFfiELF1XByIqjuPE5fPgwc+uiAMdmZmY4evQom6jJpau440MRlEkqPj6elSNrJgqefOzYMZZFSwxlsKL4RhRcmY4rEuqKQvGUKC7SDz/8wNpOZak/aPzE8XE+FBLXaJFFU+v9h7cytfvgwq6JsHIIZFmmKCsVpXf0riQyhz23cwIMjG1QtZnIZDawZm8cWtkbwZfWwdmnLktfnhD5GLXbS61/Xj48Dl0DcxYrh9KSXzv0P7j4N4Sjt9RtTRGUKadbA21ExAvZgyNl3KE0wLeeih7YaBvdMB27IXpIuRRcgGFtdVi2qydvBKjgqQlHK3XsviB92NbToZShapIYHBRUlJIlkoVB0dghRalUvx+Ob57AxBbKSHX3/Abk52YjoJrIoubYxvEwNLVB7TaiOE30kJ8YEyb5Pz01FnERISzbkZmVC7R1DWFpL+/bT7FXdA1M3/u8KHVa9sH2ZZPg5B4AZ88yuHhsE/Jys1G1rmicti6dyGLgtOz+I1s/e3A1ju9azLJXmVnZI+1d7AdmgaNrgNycLJzZvxIBleqz2DiZ6cm4cnIbUpNjUS6oqcq2lKndF+d3/gwrx0BYO5XFw8sb2DFDmc/Yd2+fAAMTa5ZuXNwXyXGifhEW5CMzNRYJUSHst5tYupSoTlVUqNcPp7ZOgI1TIMuEcv/CBpYKnrKdECc3j4eBiQ1LcytuT9K7cRIK8lh74t+Nk9gC58qhuXD1J3NsO5Zl7Nmdw4h4cZNlUVFF0zbfYfXCqcyKxs0rEKcOb2Vpwms1bMO2r1rwK8zMrdCp1w9snaxw9m9bjkFj/oCltR1S38W9oXHS1RO5Jd26cgpGJmYwt7RF5JsX2LpmDipWrYfA8orjJchC50iX+lrsnAqPE6IWO6eA289E51TX+lrsnDp+U7R++aEAQ9poo05ZTYS8FaC8pwY7p/ZcEKk1NB31aqzNgiivO5bHxBKxBU82e2Otuj1n7+SiRXUdZglCcVta19Jj4s79UKnwMKqLAVu/cE90Hp+5nYs+LfTxNqYAr6MFaFBZBzpaYFmsxEGUK/lqMbcqslIxM1JH0yBd5BUU4vEr1RaSuw5HondnJ0REZyM6Ngf9e7gwceeyTEaq+dMCcel6IvYei2brerrqcLCVXu/sbHTh6WqAtIwCxCWI+qleDQukpBYgNiEHHi4G+KG/Oy7fTMQtmcDKRTl1IxutahsgNlGA+BQB2tc3ZG5Qd59KlbJxvUzZ+tlbosnrxPUsDGhnjNdRBXgVmY/G1fRZHI/L90Xbrcw0mBtXcGgeMrKELEZOt6ZGePZalBlLEfVb9cbmJZPh7B4AF88yOH90E3Jzs1Gtnug+aOPiSTA1t0abHqJYdKf2r8HRnUtY9iqKgZOWIj2GaaG55tiuZSgX1Ihlq0qIDceBzfNgaesM33KqrwlEzWZ9sGfVRPaQ5OheBldPbmRzX6U6orlv14oJMDazQdMuomvUxcOrcHrvInQZOgdmlg5Ifzf3ab+b++geo2bT3jh3YDnLykQPW6f3LGSihV/FRsWmHzfwlFpf67s5wricL/KSUpETHg2f38dA18EGD/pNYNvfrNwOl2E94TvzJ4Sv3wPL+tVYuvFbbQZL6nj19zqUWzsLKXceIfVWMFxH9oGmgR7CNyjOlCNLjSZ9sW/1z3BwDYSDe1lcO7mB9U2FWqK5b++qCex3Ne4smvtIpI+PeneNEuSzlOLRb0OYaEN9Qbx4eInZsFjauiEp7g1O7pjNrCvEdX7JeZjcqWjubTVgKbR0DJCZJr6OGbFMS6q4/kyIttXUEZ2khqjEQlT1UYeWJlgWK4K20T3A2QeiSevmcyF6N9RANV81hEYWIsBFHfbmomxXYq49FaJjDXKjUsPr2EIWI8fbQY3FyFFFneZ9sWPFRDi6BcLJowwuHRcdw1XeXb+3LfuZXb9bdBMdw2SFc2L3Ipa9StH1m0ScjQtGI/J1CL4ft5TFdhGXoYQGJEoog+LYHF4/AbaugSwj1a0zomtt2RqicTq0bjxzQ6J04+JxSoiW3tdkpMQiNlw0TubWonGq0qgPNs3qjqtHl8O3cnNEvw5mwY6bfafYelWWoMb9cHDtBNjRMexWFjdOi9pTrqaoPQfWjIeRmQ1LNy5ug+QYpvus5FjE0DGsK22PWBAiIads9XZQ1yjZ4694rrEXzzUn3s01tUXjtPvdXNNEPNccWYUzNNcMmQNTJXNNjaa9cf6gdK45s7dkcw2Ho4j/tJBDkDhCD+4Ut4UC7pIQQQ/Z9FAvW4aEFLKaodTSlH1JbM1BMUoooC8JPJTimt4WkCVH0VTbqqB4LBcvXmSiAwUzpnY4ODiwoL9iAYAC+FKcHBI76EGeYtlQLBeyqigplJY7OzubxXghKxz6TeIU3bKCDFnOUFYm2Zg8xUHBf6kusoAhqxtKt04ZmhSJVn/88Qdzv5KNPUOQODVkyBAWeJh+N4lYlJZdHDD6YyhufCggMwlm5E5FMYno92/bto1ZFZX0+JCFRDAKVEy/n1KhU7Ys6gfZdPMUi4hcuagucv0iQUucnlwMjT+JSiQiURYuEpJIPKI4RJ8bj7ItkJORjDunFyIrPQEWdn5o3m+lxLUqMyUaampSMcnGpQIadJuN2ycX4NaJ+exBvPF3i2BuKxUistLicf3ILOZyRfV4VWiLCg2GFtuWB2ECGOrlo2kVLeYyFZUgxOrDuZLgqyTIyHqykVXBltN5aBakheZBWkhILcT647mISZIWCnDVQLcGUkGrVxPR/ydv5ePkbdUPeT6VWiArIwlXj1DfxMPKwQ8dhq2WuFZRzBvZvslIjcPmWaKHHeLOmbVscfSsii6jNuFTqFC9OTLTknBi92L2oOTg4ouBP6+QuFalJETLiaBXT+1gN3sb/hYJO2KadByGpp2GM+sfCpR86+IBJuIYGJoyq53hUzeyVOSq8CzfAjmZSbh9chHrF0o/36L/Kskxk5ESJdeWrLQ47Plb6icffHEtW+zcq6DNkE0lqlMV3hVbIDszCdePLWQ3+jRObQevluxbdJwyU+OwbY50nO6eW8sWB4+q6PiDqD107J7cPAGZaXHQ0TOCpb0PE3GcfVQ/eFat1QTpacnYv305UpMT4eTmjR9/XQSTd24pSfExUJfpm3PHd7NMQUv/Gi9XT5uug9Cum+hhj4Iab183n7lsUSDk6vVaok1nxa5vis4pchdoUkXz3TlViDVHpOeUqZGaXOwqOqe2nslDs6paaBakyc6pjSfyEJssKmVioIYAN5HFzo+d5efq5Qdz8TJKtZJz8mYuE2d7NNWHvo4awiILsGh3piSODWFlqgFDPekHd57lw1A/G61q6jFBlgQI2kfs7pVfUAhPR02W2lxfl4L/FuJFRAHmbMko1s1y675I6OpqYNxQTxgaaOJhSBrGzXjE0nWLsbfVhYmx1FLGx8MIC3+XWlj98L0oKO2xs7GYuSiU/U9BjUf0c4eZiRYSk/Nw4nwcNuwKV9mWY1eymAjTp7UR9HXVEfo2H/M2p8j1DblDUZBjMbce58JIPwPt6hmwjGDhMQWYvyVF4nZG8Xn83bTROEgfOtpqSEoV4E5IDg5dzFLajko1miEjLQlHdi5BOs01rr4YNmk5E2GI5CJzzeVTO9kxvGae6OFGTPNOQ9GiyzCWhSby7XPcuHAQ2ZlpMDG3hm/Z6mjZdYRcNjZllK3Wgs1R9ABEgYrJJaHvTyslbgupifLn942z29nct23RKLl6GrQbjoYdRBksa7ccwB7Q9q+bipysNLh4VUTfcdLYVMowqRSI6mekc7n/nEnsb/jGvQjuPxE6dlbQc7KTbM9+HcFEG/+5E+H6Q2/kRMTg4eBfkHDqsqRM9K5j0LYyh/fUkdCxtULagxDcbDUAeUUCICsiMIj6Jgln9y9CRmo8bJ390GvMKpm+kZ+LKe3x8qnSufjq8bVsoVTj/X7eJLEYOL17HtKSY6BnYAr/So3RsOOP0FCQrvxzz8MPr4hSnu9dLEqaIaZR95kSgUgZT94WQl9HiLpl1Fkg49hkYOt5gSSgsbE+3U9Iz/OIBGDfVSFLMV6/LJCUDuy8JES8zG33s4hCHLktRE1/dTStCCSmA7suCxGu2gsO5en6nU7X70XsGLZ38cWACSskrlUpRY7ha6dFx/CmBSKxVEzjDsPQpOMIpCbH4cld0cvR+ZPk+2HI5PUs9p0y/KuI7msuHRSNk7WjH7qMlN7XpCXJt4WOGcpCJebGqbVscfauip5jReNEglCHoYtxYd88XD6yBKaWjmjUZRICg0QvMFQRQO1JT8KFA6L22Dj5ofuo1RLXqlQF7Vk9Q9qe6yfXsoXa0/sn6bn5MuQq0pKiWLaqklKGzqc00VzDXC2d/ZhVn/h8SqG2yLxcvSmeaxbLzzX1aa5p/26uaSGaaw6sF801zl4VWZ08jg7nY1Ar/NrREUsx9LBdv3595k5FD/z/BehwIDGDLELI+uNrQgGRSdAgqyFlFjCcT2PO3s8TjO9jiYktkiLiK+LlIQ3KWhpwsFTuNvKleR7+6enc/0nogbS0UN7l8wbw/RAOXCxd45SersTn6ivw+OojlCY8y6u2wPuSdGtXuu530nJKzztHvVqlJ45F+oWnKE0kppaeeTgppfRcL4lyXqWobzJK13VBoxQF+dDVLj33xJ2rlaKO+UD23/png+b/U7SrUrqO/X+C0nN15Hx1yCWIskhRjJd+/fp98e+/d+8enj59yiyGyNKI3MwIcjnjcDgcDofD4XA4HA6Hw4WcfwUU+0ZZ8F2CYsLIZtBSBsWlofg/5AZU1HXI0FB55HuKAUNuS/8Ec+bMYfFgyHWNMnldunSJtYn+Nm8uTVdaFHJR4nA4HA6Hw+FwOBwO598OF3JUQIFrvwXPM3t7+/cyIxXdXhJU/VZV9ZP70z9BhQoVlGbiongyqtrA4XA4HA6Hw+FwOJyvxzfw6PyvgQs5/wIofTal0/6cfO76i4MyYH3tNnA4HA6Hw+FwOBwOh/O1+XYjKXE4HA6Hw+FwOBwOh8Ph/MfgFjkcDofD4XA4HA6Hw+FwPolClJ4sbf92uEUOh8PhcDgcDofD4XA4HM43AhdyOBwOh8PhcDgcDofD4XC+EbiQw+FwOBwOh8PhcDgcDueTEBaWzuVjWLJkCVxdXaGrq4ugoCDcvHlTadlVq1ahdu3aMDMzY0ujRo1Ulv8n4EIOh8PhcDgcDofD4XA4HA6AHTt2YMyYMZg6dSru3r2LcuXKoWnTpoiLi1NY/vz58+jevTvOnTuHa9euwcnJCU2aNEFkZORnayMXcjgcDofD4XA4HA6Hw+FwAMybNw8DBw5Ev3794O/vj+XLl0NfXx9r165VWH7Lli0YNmwYypcvD19fX6xevRpCoRBnzpz5bG3kWas4HA6Hw+FwOBwOh8PhfBKFH+nG9LnJzc1liyw6OjpsKUpeXh7u3LmDiRMnSj5TV1dn7lJkbVMSsrKykJ+fD3Nzc3wuuEUOh8PhcDgcDofD4XA4nH8lM2fOhImJidxCnykiISEBAoEANjY2cp/TekxMTIm+b8KECbC3t2fiz+eCW+RwOP9hnO1QqkhO0UBpwcNWXrX/2njqv0FpocDeA6UJXS0BSgsVEo+htHBQvRVKEwX5pWecPMt7ozSRnZmD0oKHUQRKE/obf0Fp4cKFpygtGNX1RWnC6cEdlBYKXdRQmsgpKD2PW64OiShNFBSWnvs+v4ijKD30+toN+NcxceJEFvNGFkXWOP8Ef/75J7Zv387i5lCg5M9F6ZlZOBwOh8PhcDgcDofD4XyTlFbXKh0lblSKsLS0hIaGBmJjY+U+p3VbW1uV+86ZM4cJOadPn0bZsmXxOeGuVRwOh8PhcDgcDofD4XD+82hra6NSpUpygYrFgYurV6+udL+//voLM2bMwPHjx1G5cuXP3k5ukcPhcDgcDofD4XA4HA6HAzA3rD59+jBBpmrVqvj777+RmZnJslgRvXv3hoODgyTOzqxZs/Drr79i69atcHV1lcTSMTQ0ZMvngAs5HA6Hw+FwOBwOh8PhcD4JYWHpilH1sXTt2hXx8fFMnCFRhtKKk6WNOADy27dvWSYrMcuWLWPZrjp16iRXz9SpU/Hbb7/hc8CFHA6Hw+FwOBwOh8PhcDicd4wYMYItiqBAxrK8fv0aXxoeI4fD4XA4HA6Hw+FwOBwO5xuBW+RwOBwOh8PhcDgcDofD+Vdmrfo3wi1yOBwOh8PhcDgcDofD4XC+EbiQw+FwOBwOh8PhcDgcDofzjcBdqzgcDofD4XA4HA6Hw+F8Ety16svBLXI4HA6Hw+FwOBwOh8PhcL4RuJDzD0Opx9TU1HD//v3P+j2Uj57y2ZeEvn37ol27dp+1Pf9F/smxpnr279//j7SLw+FwOBwOh8PhcDj/XrhrFYfzBSEBjgSbouJPdHQ0zMzMUFq4cXoLLh9bi4zUBNg6+6Lld5Ph6F5WYdnYyFCc3bsIUa8fIyUxCs27/4waTfvIlcnNzsSZvQvw5O5pZKYlwc7FDy16TIKje5li2xLkp47agZow1ANikgtx+FoBIhKU220GuqqjUUUNmBqqITGtECduC/A8QijZ3qCCBsq6qcPEQA0CIRCZWIhTdwoQEV8yW9ALx7fj9MH1SEtJgIOLN7p8PxGuXop/x5XTu3HjwiFEhb9g687u/mjTfeR75WMiXmL/5vkIfXIHQmEBbB09MHDsPJhb2alsy8HDR7B7z14kJSfD3c0Nw4YMhq+Pd7G/4fyFi5j512xUrxaE36b8Ivn88pWrOHLsGEJfhCE9PR1LFy6Ah4d7ifrl6qmtuHhkLdJTE2Dn7IO2vSfDyUPxMXPj3C7cvXQAsRGifnFw80ezLqMl5QUF+TixeyGe3b+IxPgI6OoZwiuwOpp3HQNjM+sStefSiW04e0g8Tj7o2G8iXDwVj9PVM7tx6+IhRIeHsnUnN3+06j5KrvyWpZNx88JBuf18y9XE0EnLi23LjrPXseHEZSSmZsDbyRYTurdCoLujwrIHr9zF1HV75T7T1tTEjeW/yX32MioOC/acxN3nr1AgEMLd3hpzhnaHnYVpse2p7q+BOuU0YaSnhuikQhy4kqfy+C/jpo4mVbRgZqiGhLRCHLuRj2fhonNKXQ1oWkUTPs4asDBSQ04eEBopwLGb+UjPQoloU0cPtcvrQl9HDS8i8rHleCbikqXnrCLqVdJB0yA9mBiqIzy2ANtOZuF1dIHCsiO7GqGMhzaW7E7D/ef5xbanXT0D1KmoC31ddbwIz8fGI+mISxKo3KdBFT00q6Evak9MAbYcS8erKGl7xvcxha+rttw+525nY9ORdJX1dmpiggZVDWGgp4Znr/Owdl8SYhIU/04xjasbonVdY5gYaeBtdB7WH0hGWHieZLu1uSa+a2UKH1cdaGqqIfhZNiuTmqG8zw8dOoQ9u3cjOTkZbu7uGDp0KHx8fFAcF86fx6xZs1CtenX8+uuvks8LCwuxedMmHD9+HJmZmfD398fwESPg4OCAkqBfszEM6rWChpEJ8qPeIm3fBuSHhykvX7sZDGo0goaZJYSZ6ch+cAPpR3cABfkfXaeYG2e24OqxNex6aePsixY9f1F6vYyj6+W+hYh+d71s1n0iqjcper3MYGVC2PUyEXbOfmjeYzIcirlemteqDPex/WFSMRC69ta43XEYYg+eUb1Pnarwn/MzDP29kBMejRczlyFi4z65Mi5De8B9TH/o2FohLfgpHo+egdRbD1ESzhzdieP7NyI1JRFOrl7oOWA83L0DFZa9cHIvrp4/gsi3oj538fBDx57D5cpTPbs3LsSj+9eRnZkO74CKrE4be+cStefs0R0y7fFGj2Lac+38Ybn2dOg5QmF7Ht+/huzMDHgHVECPARNK1J7SdC9x/PBeHNy7DSnJSXBx88D3g0fDy8dfYdkbVy9g785NiImOhKCgALb2jmjdvivqNmgmKbN4/h+4cOa43H7lKlbFL9PnoiScPLIHh/ZuQWpyEpzdPNF38Bh4eituz82r57F/10bERke8a48TWrbrhtoNmkvK7N66GtcunkZiQhw0NbXg5umDrr0Gw9MnoNi2bD9/GxtOXUNiWga8HW0woWtTlHFVPE8duPYAUzcekvtMW1MDNxdNlKxn5eRhwf6zOPfgGVIzs+FgYYru9augc51K+Lcg5K5VX4z/nEVOXp70Zobz7+VbG2dbW1vo6OigNPDwxlEc2z4L9dsNx9Bpe2Dr5IMNcwYiIy1RYfn83ByYWTmhcecxMDSxVFhm/7pf8OLxVXQaNAsjfj8Az4CaWD/7e6Qlx6psCz1AtqiqibP3C7DkYD5ikgrRt6kWDHQVl3e2VkOXepq4/VyIJQfyEfJWiJ4NNWFtqiYpk5BaiEPXC7Bwfx5WHslHSnoh+jXVgr6SOmW5c+U49m6YjRadh+DnWTvg6OKDxX8MQXqq4r55/vg2KtdqjlFT12DcH5thZmGLxb8PQUqi9HfHx4Rj3pQ+sHFww+hpazBpzh407zgIWtryD31FOX/xElauWo2ePbpjycK/mZAzecqvSElJUblfTGwsVq1Zi8CA929gcnJzEODvj/795B8siuPB9WM4vGUWGrYfhpG/74adsy/WzBqEDCX98jLkJspXb4lBk9dh2G9bYWJui9WzBiI1SdQveXk5iHz9BA3aDcGoGbvRa/RCxEe/wvp5w0vUnrtXj2Pfxtlo2nEIfvpzJ+xdvLHsf4OVjtOLx7dQsUZzjPh1LX6csRmmFrZY9sdgpLxrjxi/8jUxY8U5ydJn5Kxi23Li5kPM3XkMg1vXx9ZfhzEhZ9jf65GUlqF0H0M9HZyaO0GyHJ01Tm57eFwivp+1Cm62llj1U3/s/G0EBraqBx2t4t/NlHXXQKvqWjhzpwAL9+YiOlGI/i10lJ5TLjbq6N5QG7eeClj5J68F6N1EGzZmonNKWxNwsFTH2bsFWLA3F5tO5cLKVB19m5ZsPmtWTRcNK+ti87EM/G99KvLygdHdjKGpoXyfyn7a6NLQAIcuZ2PG2lRExAkwupsRjPSl57mYRlV0gQ+4qWxeUx+NgvSYePP76iTk5hVi7HemKttTJUAHXZsY4uCFTExbkcSEpTHfmb7Xngt3sjF6ToJk2XVK+TFAtK5nhGY1jbBmbxKmLIpFbp4QP/e3hqphrlZOH71am2HP6VRMWhCNN9H5bB9jA9Htno6WGiYNtGIxDH5fGYfflsZCQ0MN4/paQe397hO1+8IFrFq5Ej169sSiRYvYXDPll1+KnWtiY2OxevVqBAS+/6C8e9cuHDx4ECN++AHz//4burq6rM6SXLt1y1eDcZvvkHFyLxLmT0ZB1FuYD/oZ6obGistXqAHjlt2QfnIv4meNQ8qOldArXx1GLbp+dJ1iHt04ihPb/0S9tsMx+Le97Hq5ae6AYq+XjTqPhaGJlcIyB9ZNQdjjq+gwcBaGzTgIj8Ca2DCnX7HXSw0DfaQFP8OjkdNQEvRcHVHl4Aoknr+By5Xb4tWiDSiz4ndYNq4lKWPXuTn8Zk9E6O9LcLlqe6QHP0XQkTXQtjIvtv6bl09ix7p5aNN1EKbO3cKEk3nTRyAtJUlh+WeP7yCodlOMn7ECk/9cB3NLG8ydNhzJiXES8W/xzLGIj43EyInzMHXeVlhY2WHOb0ORm5NdgvackGnPViYszZ8+XGV7qtZuhp9mrMSkP9ez9sybNqxIe8YgPjYCP0ycL9OeIcW2pzTdS1y5eAYbVi9G5+59MWvBari4eeKPX8ciNSVZYXlDQ2N06NIbf8xZhjmL16N+oxZY+vefuH/nhly58pWCsHLTfskyerz8ywhlXLt0GptWL0TH7t/jf3+vY+3589cfkapknAyNjNG+Sx9Mn70SsxZtRN1GLbB8wf/w4O51SRk7e2f0HTIWsxZvwtRZy2BlbYf//ToaaamKf6OYE7cfY+6eUxjcsja2TRrAhJxhC7chKS1T6T6Gujo4/edoyXLsjx/kts/ZcwpXn4Thj35tsXfqEPRoUBV/7jiO8w+el6h/OJz/lJBTr149jBgxAqNHj4alpSWaNm2KR48eoXnz5jA0NISNjQ169eqFhIQEyT67d+9GmTJloKenBwsLCzRq1Ii9MSKEQiGmT58OR0dH9uBN7k30RkkRVJbKLVu2TO7ze/fuQV1dHW/evGHrdDM0YMAAWFlZwdjYGA0aNMCDBw/k9vnzzz9ZW42MjNC/f3/k5OR8cF9MmzZN8h1DhgyR3DBt3LiR/c7c3Fy58uSORX1THGFhYWjbti1rH/VplSpVcPr0acn2SZMmISgo6L39ypUrx/qSKCgowMiRI2FqasraMmHCBPTp06fELmGKxpn4UmNNrF+/nrVfFrK+Ibcp8XYaAxpb+owW+kyRa9XDhw/ZcSBu16BBg5CRkfGeu9ycOXNgZ2fHygwfPhz5+cW/bS6Oqyc2oHLdzqhYuwOsHTzRus9v0NLWxd2L8lYCYsiqplm3n1C2Wktoar5/w5Cfl4Mnt0+haZdxcPWpAgsbFzRoPwIW1s64eXabyrbUDNTA7WdC3A0VIj6FLAcKkF8AVPLWUGppEBohxOVHAsSnFuL0XQGiEgvZ52KCXwoRFlWI5HQgLqUQR28WQFdbDbbvHkxVcebwRtRo2BHV67eDnZMHug2aAm1tPVw7q9gtrt+oP1GnaTc4ufnC1sENPYf8hsJCIZ49kt7wHNq2CP4VaqN9rzFwcvODla0TylapDyMTC5Vt2btvP5o1a4qmjRvBxdkZI0cMg46uDk6cPKV0H4FAgFmz56JXzx6ws7V5b3ujBg3wXY/uqFBCt00xl46tR9X6nVGlbgfYOHiifb+p0NLRxa0Lio+Z7sNmo3rj7rB38YO1vTs6DZyBQqEQLx6Lbrz09I0w8Oc1KFetOazs3eDiWQ5te/+CyFePkZwQVWx7zh8RjVO1+u3ZG8kuA35l43T9nPybZjG9R85C7abd4OjqCxsHd3QfMg3CQiGeP5S/MaXj29jUUrLoG5oU25bNp66gQ+3KaFurEjzsrTH5uzbQ1dbC/st3VOylBksTI8liYWIot3XxvtOoVcYbozs3g6+zPZysLVCvvB/MjeXLKaJ2WU3cfCrA7ecCdvzvu5TPzqkqPppKz8Hn4UJcDC5g5U/eLkBUQiFqBIjK5+QDq4/mIfilgImkb+NEFj6OVuowNSj+nGpYVQ9HrmTjQWg+IuMFWHsoA6ZG6qjgo/zho3FVXVy6n4urwbmIThBg87FM5BUANcvJi0dO1hpoEqSL9UdUCyZydQfp4dDFTNx/lscEotX701h7KvoqF6aaVtPHxbvZuHw/B1EJAmw8nI68/ELUrqAnV44+S8sUSpacPNUKU/Naxth3JhV3nmTjbUw+lu5IhJmxBioH6Cvdp2VtI5y9kYELtzMRGVfARKC8fCHqVREdG96uOrAy08TynYkIj8lny7KdiXB31EaAh+LfuG/fPjRr3hxNmjSBs4sLE1/omnjy5EmVc81ff/2F73r1gp2trdw2egCm6123bt1QvXp1uLm5Yey4cUhMTMS1q1dRHAZ1WiDr+jlk37qAgthIpO5Zg8L8XOhVrauwvLarN/JeP0fOvasQJCcg7/lDZN+7Cm1nj4+uU8zVk+tRqU5nVKjdkV0vW/Wexq6X9y7tUVierGqadh2PMkF0vdRSeL0MuXMSTWSul/Xb/QBza2fcKuZ6GX/iIp5P/RuxB6T3X6pwGdQN2a8iEDJ+FjKevsSbpVsQs+cE3Eb1lZRxG90P4Wt2ImLDXmSEhOHhsKkQZOXAqW/HYus/cXAz6jRuj9oN28DByR29h0yCto4uLp05oLD8oB//QIPmXeDs5gM7Rzf0GzaFHStPgm+y7bFRbxH2/CF6DZ4IN68A2Dm4sv/zcnNx45LyezMxJw9uYe2p1bAt7J3c0WvIZNaeyyVsT99hv7L2hMi05yVrzyTWHlsHV3w3eBLyS9Ce0nQvcXj/DjRs2hr1G7eEk7MbBg0fx/rl7KkjCssHlK2AoBp14OjkCls7B7Rs2xkubu54+kTeSktLSwtmZhaSxdDQCCXhyP7taNC0Deo1agVHZzf0HzYe2jo6OH/qsMLy/mUqokr1unBwcoWNnSOat+kKZ1cPPHsSLClTs14TlClfBTa2DnByccd3A0YiOysTb1+rtrjbdOYGOtSsgHY1ysPDzgq/dG8hun5fUxFSQQ2wNDGULBZFrssPwiLQulpZVPF2ZdY4nWpXhLeDDR69jixR/3A4/ykhh9iwYQO0tbVx5coVJojQA3KFChVw+/Zt9mBOb426dOkicXHp3r07vv/+e4SEhOD8+fPo0KEDm7yJBQsWYO7cuewBOjg4mAkGbdq0QWioyCRfFhJrqK6tW7fKfb5lyxbUrFkTLi4ubL1z586Ii4vDsWPHcOfOHVSsWBENGzZEUpJIfd65cydzyfnf//7H2kwP7kuXLv2gPjhz5ozk92zbtg179+5looL4++mmi96OiaH2HDlyhPVDcZDA0KJFC/YdJFI1a9YMrVu3xtu3b9n2nj174ubNm0zwEfP48WPWfz169GDrZHpN/bJu3To2TmlpaR8cM0Z2nJcvX84Esi811iWha9euGDt2LAICAth300KfFYWEJPoucrW6desWdu3axYQxEqpkOXfuHOtT+ku/nUQhsTD0sRQU5DEXKXf/6nLHsUdAdYSHfVwsIKFAAKFQAE1t+YcETW1dvHl+V+l+GuqAvYUaXkRJzf1pZGjd2UrxA6KztToTaWR5ESmEk7Wa0u+o4qOB7NxCZu2jioL8fIS/DIFv2WpyfeNbNggvn8sLr8ogSxMy/RULACQWPrp7ETb2Luzt2oT+dfHXxB54cPOsynpIsAt98QIVy5eTawsJME+ePlO635Zt22FqaoJmTZvgn4KOmchXT+AVIN8vngHV8fZFyY4ZekstEEj7RRE52elM8NTTV/2GvKCAxukJvMvIt4fWX4eWcJxycyCUGScxL57cxuSBdfHH6NbYuXoGMtNVWyTkFxQg5E0Ugvw95NoS5OeB4JfhSvfLzs1D8/Gz0eynvzB68WaERUrfutIxczn4GZxtLDFs/no0+HEmev2xHOfuPSn2d9Hx7mCphtAIgfw5FSmAs426Uosc2i7L8wjl5QkSRoWFhcguRqiwNFWHqaE6Ql5JBWg6F19GFcDdQVPpb3Cx00TIa6nlBn1LyKs8eDhIH4zJUmhAO0NsOZGJtMySmeSQJZGpkQaevCzSnoh8eDhpKW+PvSaevJRvD617OMrvU62MLhb8ZInpQ83RsaEBa6MyrM01mGjzKFT60iY7pxBh4bnwclEsuGhoAG4O2nj0QroPXc6oDi8XkTCmpanGPssvkPZJfn4h+8zHTVfhXPMiNFQuJh8dw7T+NCREafu3bd0KUxMTyUsVWWJiYpiLVvkKFSSfGRgYMFetkKdPlXfKux+p5eiG3NBH0s8KC5H7/BG0XbwU7kIiDu2j5SQ6DzXMraHrVx45Ifc/uk7x3EcuUu4BNeT6hq6f4SWc+4oiFBSIrpda8mNM4tDbUFXi74djWq08Es5ek/ss/tRlmFUTjbWalhZMKgYg4YyMuFZYiISzV2FaTTp2yq6Xb8Kewr9cVbm+8S9bFWHPSuaWlUvXS0EBDN5ZRVF/E1pa2nJ1amppI1Q8lirbEwK/ckFF2hOEsGfBX7Q9pe1e4uWL5yhbvpJcW8qWr4znTx8X2w66X354/zaiIsLhFyi9HyEeP7yP/j1bY+TgHli5ZA7S01KLrY/65tWLZwgsV1muPYHlqyD02aMStefRg9uIjnwL34DySr/j7PED0DcwhLOrp9K68gsECHkbjSBfN5m2qCHI1xXBLyNVX78nL0TTSQswetlOvIiKl9tezsMR54OfIzYljbX31rPXeBOXhOr+JXNj/xYoLFQrlcu/kf9EjBwvLy/2Zoj4/fff2YM9iSJi1q5dCycnJzx//pyJEmQdQg/0YqGFLDbE0EM9WYvQmySxAEEP0n///TeWLFny3neTiEFiAIkazs7ObLLdvn07fvlFFJfi8uXLTOQg4UTsWkPfQSIGWYuQJQbVTVY4tIh/Az3Yf4hVDgkc9Dv19fWZkECWJj/99BNmzJjBrD5IUCERhUQdYvPmzay9ZOlSHGRZQ4sYqpPe4DGz6REj2PfRdhK0pkyZwsqQaENWOp6eokmUzLUnTpyI9u3bs/XFixfj6NGj+Nhx/hpjXRzUz2QZpKmpyVyplEH9RGNLllJ0cyvuDxLHqA1kWUSQ0EOfa2howNfXFy1btmRi2sCBAxXWSxZXRa2u8vO0oCUjsGSlp7CbSMMib3AMjS2QEP0KH4OOngGcPMvj/IFlsLLzYHUHXz/CbnTNbZT7kevr0EOSGjKy5R/CaJ0euBRBcXQyct4vT7FAZPFxUkfXeprMRSEjC1h3Ih9Z8l3zHhnpyaxvir7dovWYyJL1Dfmum5hbwfedyJCemoTcnCyc3L8Grbv9gLY9RyPk/hWsmvMjM6H2CpDezMhCQifNJaam8nGVzExNER4eoXCfR48fM2udpYsW4J9EesxYvtcv8dEvS1TH0e1zWewbEn8UkZ+Xi2Pb56Fc9RbQ1VdtdZKZpnyc4qJKNk4Ht8yHsbkVfGTEIL9ytVC2aiNYWDsgITYch7ctxPKZQ/Hj75uhrq7YQiw5IwsCofA9Sxl6Q/c6RmoZKIuLrSWm9m0Pb0dbpGfnYNOJy+j750rsnjYSNuYmSErPRFZuHtYdu4jh7RphVMemuPLoOcYu3YaV475HZR/pTWdRyH1QdE7Jf56u8pxSQ7qC8kXPKTHkgtS8qhYevBAgtxgDQZN37j5knSJXf6ZQsu299uirsd9QVJyhdVsLaZu6NDZAWEQBs/QpKcaGituTpqI9Rvrq79rz/j52ltJbrBsPc5CQKkRKugBONpro1MgQthYaWLIzTWG9FN+GSM2QF9FS0wXMQkhh+w00mJsUlZHbJ0MIe2uRqBT6Npe5i/VoYYrtx1Pp5TG6tzBl+ymqVzzXFI3hZmpmhvAIxXPN40ePcOLECSxWcp0kEYdQVKd4mzLUDYygpqEBYbr8Q6EwIxWa1vYK9yFLHNrPYsRU9rZcTUMTmVdPI/OdJcbH1Elkvbsm0PVRFpoLE2I+9nppCCeP8rhwcCks7dxZXQ9LcL38qO+ysURurPw8ROtaJkZQ19WBlpkJ1DU1kRsn7+6TG5sIAx/VD53p764LxkXmYWNTC0RHvi5R+yj2jKmZJQLeiS9k8WJhZYvdmxejz9DJ0NHRw8lDW5CcGIuU5IQStkfeJczY1PwD22MFf5n2mFvZYs/mxehdpD2pyfIP76X1XoLEFWqLial8v5iYmiEyQuQ1oIjMzAwM7tMBBfl57Po3YOgYlKtQRbK9QsUgBNWoC2sbO8RGR2LrxpX4Y+pPzB2L7lmVkZYmGicTs6LtMUeUivZkZWZgWN+2kvb0GzoOZStIRUTi7s0rWDj7V/aixtTMApOm/w1jE+Ux5UTX70JYGIvuw+Wu37GKXeBcbSzwW6/W8HKwRkZ2Ljaevo6+s9djz6+DYWMmEgB/7tIU07ccQdOJC6Gprg41dTX82rMlKnmJnkM4nA/hPyHkVKokVZrJrYUexumBuihk3UCmw2QNQw/09CaJ1jt16sRuOOiGJioqilnTyELrRV2hxNBbKz8/P/Zw/vPPPzNfcxJtxIIJ7UeCArnGyJKdnS2xYCFrEXKFkoXMkel3lBQSUkjEkd2fvjc8PJyJGPTwTy5RkZGRLNggWXaQ+47YLUgVVA9ZDJEFD1mZkDhC7Rdb5IgFLRJRSMghBZqsgsaMGcO2paamMkuZqlWlky5N9DRudAP5MeP8Ncb6n4LGm8ZLLOKIv5f64tmzZxIhhwQy2QsiWWqRS5YyZs6cKbHCEtPp+1/RecDUz/I75L5n0CzsWzMZs3+syy6ydi7+KFOtJbP++Rq8jBZi8f48GOiqobKPBrrV18LyQ3nI/HCPxRJzct8a5hc/etpaiXhGptFE2cr10aCVyI2RTKdfPruPS6d2Kr35+lCysrLw19x5GD1yBExMincH+pKcO7gKD64fxeDJG+RERTEU+HjLojFs3mjf9/Mfq6f2r8a9q8cwYqp0nIiKNaWBE+2dvdkyY2QLhD6+JSf4fCrlPJzZIrveccoC7L54iwk3ZOlCkCvVd01E85OPsx0ehIVj94WbKoWczw0FPu7ZSJvFWtl3+X0BJShAG981l87Hi5SIGJ9KOS8t+LpoYcYa1RZT1crooHcrqbn/31uLf2P8sVy4K51cIuMESEkXYnwfM1iZZSI+WYCaFfQxoIP04eWvdcofBD8FEsn+3pyA/h3M0LSmEbPEuXo/Cy8j8tj//8RcQy9BRo4aVWrmGm0PPxg2bIvUvWuR/yYMGpY2MGnXG8JG7ZFxWrG75dekw6C/sH/tJMwdI3O9DGqJqDdf53r5NTiyZx2LsTN+xkrJPEyuaMMnzMG6xdPxQ6/6rG/I4qdMxZoSS+rPxVHWnhMK27N+8XSM7FXvi7Xna95LiNHT08fshWuRk5ONR/fvYMOaxbCxtWduV0TNuo0kZV1cPVicmxEDuuLJw3soU/6fbQuhq6ePPxdsQE5OFrPI2bxmIWsPuV2J8S9bkZVJT0vB2ZMHsWDWFMyYu+o9EetTKOfuyBbJuocjOkxbjt2X7mJ4G9GL8W3nb+Hhq0gsGNoFduYmuPviLWZuPw4rE0NU8/v3WOVwvgz/CSFH9oGYRAexZUNR6EGYHoxPnTqFq1evMv9vshSZPHkybty48Z7YUlJIxBALOfSXXI/EdVF76HvJracoReOtfE7IcoXEA7ICIUGDXJ9ImCkJ48aNY31GN29kYUOWJySIyAYtJBcmsm65e/cuE3lIQFLkVvRPjfPXGGsy/yx68f4nYtYog/yPZSHRTZXwRRZPYvFMzKF78nXoG5mym5GiQWopcKOyQMYlgfz7+0/chLzcLJaRw8jUGjuW/ghzK8WZewiykKG3IWQRIButlNYzshTfJJGlgaGumgKLgiLjUgAkpdNSiPD4AvzYUYvF3bkYrDwzjaGRGeubosEIaZ3ipaiCMlOc3L8WP/y6kmWnkKtTQxO270z+xdg6uiPs6T2l9VGcKzreUooEI0xOSVGY/Sw6OgaxsXH4ddoMyWfiY7V567ZYs3I57O1UZ7VQhvSYSXivX4yKOWYuHFmL84dXs3g4lOlKmYhD2V0GTlxXrDUOYWCsfJyMTFWf15Tl6syBtRj2yyqW6UoVljZOMDAyQ0LMW6VCjpmhPjTU1d8LbEzZL4rGvVGGlqYGE2oowLG4Tk0NdbjbywdKdbezwr1Q5W8siawc8Tkl/zlZ16QrPafI+kZB+SLnlFjEoWxxqw7nKrTGuR+ah5dRUnFFS0N0rlIg3tRM6blnZCDKRKWwPVmF7DcYF4m/Q+tiKx0ScazM1LFgrPwN+tAORggNL8CcLSIBieLgvIyQnkOa7+6IWHtkMjjR+lsl7UnPEr5rj7w1S9E6ivIyMl/iQkVCDsXBefE2Rto3mqLfZ2KowUQfWUud11GKrytpmQIIBIUSax7JPobqzBJIzMPQHIyeFc2siajtWTmFWDbFAdceFCida4payqQkJ8Nc4VwTzV7MTPvtt/fmmlYtW2LVqlWSOYrqNDc3l6vT3UN+LiwKZZwqFAigbiQvEqkbmkCoxNXRqFlnZN+5jOwbovusgphwpGvrwKTzAGSc2f9RdRL6764JRQMb01xoaPxp18vvf94sd73cufRHFiT5n4Ssb8gqRxZaz09NhzAnF3kJyczFVMdaft7UsbFArhKLQjFG764LaUXm4bSURJgUc72krFJH967HuGnLWEBiWVw9/DBt/jZkZaazl4bGJmaYMb43XD38S9ge+YC5FOjYpJjrgqg96zBu2nIWsFm+Pf74bf521h5ydTIyMcPvrD1+38S9hJGxCWtL0UDCFOiYrFaUQXOCnb3o/s3N3QsREa+xb9cmiZBTFBJV6Lso05UqIcfYWDROlK1Kvj1JMC1ipVO0PZQ9i3B190ZU+Bsc2LVRTsjR1dVjZWjx8g3Ej4O64Nypw2jXubeK6zdlP8187/ptWYJ4dISWhgZ8nGwRHi/6PTl5+Vh04BzmDe6MOmVExzYFUH4WHsusd/4tQs5n1lU5/7UYObJQ/BkSKVxdXZnoILuIhQB6ICYLCLJeoJgv5JZErkJ0Q2Nvb89isMhC65Q6UxnktkRBdyn+DblLkbAj2x7yFyd3m6LtoaC9BFn0kLggy/Xr0mjsJYGsSEhAkd2fLFXIzUgMBVwmSxxysaKgv7LbVEG/n6x3yC2KrFvIbej1a3lTVQoYXLduXeZSRUvjxo1hbS1KI0xv7cjKhOLBiKGYPST6fEtjTYGkKWWzOFgyUTTNONVPv00VNN40XrL10PfShaok6V6VQa579Ltkl6IWEBTM1d41AC+fSI8vEodoncy9PxVtHX12U5qdmYoXD6/At2JDpWUpNTgFKvawl05T9GhD62+VpEp+GyeEh738Ax6VD49TfVWh40BVVhpCU0sLTu5+eCYTAJdZST28AXdved9wWU4dWItju1di+OSlcPEIeK9O+iy2iGl3XNQbmFvaqRTxvDw9ce9+sFxb7t9/AH/f948RJydHrFiyGMsWLZQs1YKqolzZMux/q3dzzcdAxwylDxcHKha3hdadPZUfM+cPr8GZ/cvx/fiVcHQPVCriJMS+wYCf18DAqGTCNr0ldXL3lwtUTO15/ug6XL2UjxMJOCf2rMCQicvgXGScFJGSGIOsjBQYmynOPENoaWrCz8UeN0JeyrXl5tOXKOtesvmVXLNeRMayoMfiOv1dHfCmyIPUm9iEYlOP0zkVmVAITwfpwU5ni6e9Bt7GKhYd3sQK4SFTnvByUJcrLxZxLE3UsPpIrlI3xdw8ID5ZKFkoMHBKhhC+rlpy8XXc7TXxMrJA6W94E10AP5l96DfQetg7ceTYtWxMW52K6WukC7HjdBbWH5aKahRsOC5ZIFmi4slSRgB/9yLtcdRCWHi+8vZEFcDPXVu+Pe7aCItQLuQ724q+Q+wGlZNbiNjEAskSEZuP5DQBAr2kcWv0dNTg4aSD0DeKO5guLa8i8xDoKd2HrKMCPHUR+iZPoQhFIg4FOSbhicQkRXONp5cXHshcy0RzzX34+r3/sEr3DUuXLWNuVeIlqFo1lC1blv1vaWXF7hFIzJGtMyszk1mc+vn6Ku0z8Y/Mj3gFHS+Zc1RNja3nvVEcv06N4s28s1gQI7Zg+Ng6xXOfHbteXpPrm1ch15k78T95vQx7dBm+FRrgnyTl+n1YNJAXoS0b1kDyddG4FObnI/XuY1g2kHF5VVODRf3qSLmuXByQXtt8ERJ8S65vQh7egoeP8jTqx/ZtwKFdqzHm18Vw81R+X61vYMREHAo4/DosBBWC6pagPX6SQMXS9tyEh09ZFe1Zj8O7VuPHXxfDtZj2GEna8wTlg+p9M/cS7p7eePjgjlxbaN3bt/jroJhCYaHKF5eU9jsjPQ2m5qpFM/odlBr8UbB8ex4/uA0vH8Vp4hVByQqKe5FKZcgVS9VLFD9nO9x8JnV3EwoLcfPZa5R1V5x+XPH1O05y/S4QCNmiXsTbgWLviK1tOZwP4T9hkSMLZfahN0JkITJ+/Hj2NujFixcsbg2lyaSguBRnhKxSSGggASU+Pp49XBMUV2bq1Knw8PBgblMketANDYkTyiAhoUaNGizGDT3EU8BcMSSYkJsTZSCi+C7e3t7MpYesYUgYqVy5MkaNGsWEEvqfRAf6LhIo3N1LrtySdQx9P8XmIZGFfgPFryFxQFZwIusa6h+yzPmQ2DQUPJmsX+iBmNynFFmGkIBF30ttmT9/vty2H374gbn+kMhC8V7IOobe1pXEtau0jDXF/CH3NcrSRRm4qL6iwYfpWHj16hWrh8QtykJWNO24uJ8oaxe5rFGbqH8o45bYrepzUqNpH+xdNREOboEsw8a1kxuRl5uNirVF8Yt2r5wAYzMbNOk8RhLwLz5S5AYoEOQjLTkO0W9CoK2rzzJuEKEPLzOJ3tLODYmxb3Bixxz2f8VaojqVceWRAB1rayIyQR0R8ZQpR4MFCL3zXPTw06mOJnsLf/KOaP3aEwEGtNBimXaehQtR1l2dBXfdf0X0UEgxceqV08DTt0JmgaCvq4Zqfhow1gcevSreja9hq97YuOQXOHv4w9WzDM4e2Yzc3GxUqy/KrrZh0SSYmtugbc9RbJ3enB3ZsQR9R/0JcysHpL7z49fR1WemwESjNn2xdv5P8PKvCK+Aqnhy/woe3rmAUb+tUdmWDu3bYc68+fD28oSPtzf2HTjAYis1aSwyaSZXKksLC3zftw8TEF1d5f2vDd+JmbKfp6WnIz4uHonvAq2HR4oC+tFDl7n5+2/fxdRu3hc7V0yEo1sgHD3K4PLxjcjPzUbluqLx3bH8ZxYDp3lX0TFz/tBqnNyziGWvMre0R3qKyI2EjhkdXQMm4mxeOBqRr0PQd+xSFAoFkjJ6hiYKs6PJUq9lb2xZOpkJMs4eZXDhKFmDZSOonmicNi+eBBNza7TuMZqtnz6wBkd3LmHZq8ytHZCWIh0nWij2wPHdy1CuaiMYmVqyGDkHt8yDpa0z/MrJu18W5bvGNfHr2j3wd7FHoJsjtp6+yoIhtq0pcgX9Zc1uWJsaY2RHUQDqFYfOMpGHMlGlZ+Vgw4lLiE5MQfva0reYfZrWxoQVO1DR2xWVfdxx9XEoLj54hlU/FR+c/lJwAbrU00JEvJAttcpogoz7bj8XnSO0jc6p47cKJOfg4NbaqF1GE0/fClDOUwMOVurYcylXIuJ811ibnWfrj+cx4UBs8ZPNrOpUt+fMzWy0rKnHhJSEFCHa1tFnFij3nklvsMf0MGbr5+6I3JNO3czB960N8TpagFdRBWhUVRfaWmq4EixqE7WfrFOKkpRGmbVUN+jUjWy0qm2A2EQB4lMEaF/fkLXn7lOpeDKulylbP3tLJHycuJ6FAe2M8TqqAK8i89G4mj5L8335vmi7lZkGc+MKDs1DRpaQxcjp1tQIz16LMmMp49jlNLRrYIKYhALEJRWgcxMTJu7cfpwlKTN5oDVuPc7CyasigerIpXQM7WLBXKVehOeieS0j6Gir48JtqYBVt7IBIuPykZYhhLeLNnq3McOxy+mIjlcsntG9yLy5c9m13tvHBwf272fx1uiFDEHWuGTF2q9fv3dzjauSuUb6Od3z0LXY3sGBXdc2bdrE6qheQxo4WBmZF4/CtNsQ5Ie/RP7bMOjXaQ41bV1k37zAtpt0HwphahLSj+5g6zlP7sKgbnPkR75B/tsXzLWKrHToc/Gr4+LqVEaNJn2xb/XPcHCl62VZXDu5gc01FWp1YNv3rprAxJjGncdKr5dRstfLWES/DWGijfh6+eLhJWaDamnrhqS4Nzi5YzaLlyOuU1X6cQNPqVumvpsjjMv5Ii8pFTnh0fD5fQx0HWzwoN8Etv3Nyu1wGdYTvjN/Qvj6PbCsX42lG7/VZrCkjld/r0O5tbOQcucRUm8Fw3VkH2ga6CF8g+KMhLI0bfMdVi+cyqxT3LwCcerwVpaWu1ZD0T3wqgW/wszcCp16idIzkxXO/m3LMWjMH7C0tlN4vbx15RQTTMwtbRH55gW2rpmDilXrIbC84vhqsjRp0xNrWHv8WZap0+/aU/Nde1YvmAIzc2t0lGnPgW3LMHDM/2Bpba+yPRaWtoh48wLb1sxGhRK0pzTdS7Rq1xVL5v8PHl6+8PT2w5EDu1i/UFpxYtHc32FuYYmefUUhHvbt3AR3L1+WsSo/Pw/3bl3HxXMnMHCY6BjPzs7Crm3rUK1GPWZFQzFyNq1bxsqXrygft0YRLdt1w7L5v8Pdk9rjj2MHdiA3Jwd1G7Vi25fOmw4zCyt07zOUre/ftZGVtbFzYIGM792+isvnjuP7oT+x7eT+tX/nBlSqWosJSRQX6OSRPUhOTEBQTdXiaK+GQZiy4SD8ne0Q6OqALWdvIDs3H22riwS3X9YfgLWpEUa2E9Wz4shFlHFzgLOVOYtxt+HUNUQnpaJ9TZGwa6ing0pezpi/9wx0tDVhb26C26FvcfjGQ4ztKJpPOZwP4T8n5IitLMjNhx7g6WaEYsSQuxOJGmSlcPHiRRbQluKk0DYKVkwprAl6QKeYLpR9iGLdkHUGBfWlGxxV0MP5sGHD0Lt3b+Z6JIaECgrqSy49dBNED+30tqpOnTqSh3ZyQaKYLiRG0INax44dMXToUBZMsKRQLBhqI9VLv5nEDRIJZCHLGKqbRKSSpv0m5s2bxzI/kVhFVkTUt9R3RSF3KxKPyKWpaP20D1kmUf/QdgryTHFrVAVFK21jTUIRBYkmAYgEJOpz6mP6LWKof0n0ql+/PsuqReIQiXSykBhEY0sCHsUtonXaj/r5S1AmqAUy05NxZt9CZiJu5+yH3mNXSlyrUhOjoa4mFQDTk+OxdKr0BvPK8bVsodSp/SdulGQcOrVrPtKSY6BnYIKAyk3QqONoaChIvyrLw1dCGOgWoGFFTebeEZ1UiPUn8yWxbEwMRBlYxFDq453nC9CokgaaVNJAYlohtpwRpU0mqKyViRoqNtBigV/JciAyXohVR/MlZVRRqWYzpKcl4/COpUhPSYCDqw+GT17GAjgSyQkxUJPpm0snd7IsSqvnim5wxLToPAQtuwxj/5cPashSj5Lf+661s2Bt74oB4+bB009qEqyIenVqs+Nz4+YtTPQkYfeP6dMkbgs0lxR961Mc16/fwNy/pcGQZ84SBQ+nlOSUslwZlCY8My2JiTPpqQmwd/HF9+NXSFyrUhKi5frl+pntErFGlkbth6FxxxFITY7Dk7uiGGALJss/vAyatB4e/qpvBivWaIaMtCQmzpAoQ2nFh0xcLjFbT06MZgEGxVw5tZO1Z908edfDZp2GonnnYVBTV0fUm+e4eeEgsjPTmAjkU7Y6WnQZwTKUqKJp1TJIzsjEsgNnmEm2j5MdlozuI3GtiklMkRun9MwcTN+wn5U11tdjFj3rJw5iqcvFNKjoj8m92mDt0Yv4a9sRFiB59tDuqOAl/wCtCEoTbqAHNKmsCSN9NWb1tvZoriQAMrlGyZ5TZJGz7UwemlbRQrOqmizF+MaTeYhNLpScgwGuonl6dCf5rEcrDuWyeFSqOH49B9raaujV3JAJq6Hh+ViwIw0FMvoGBWKmIMdibofkwUg/C23r6DFLEnLDWrAjHeklzE6limNXspgI06e1EfR11RH6Nh/zNqfItYfcocgtScytx7kw0s9Au3oGzI0pPKYA87ekSFy9CgSF8HfTRuMgfehoqyEpVYA7ITk4dFEqyCji0Pl0JsIM6GjO2vLsdS7+XBPHXEPF2FhowshAep28/iCL9UmnJiYsA9ebqDy2j6ybl52VJro1N4Whnjrikwuw/2wajl5KV9oOsqZNS03Fps2bkZyUxNyfps+YIZ1r4uI+eK7p1Lkzu59ZtHAhc4NmSRhmzGBCUHHk3L+ONANjGDbtBA1jUybQJK36E8IM0X2HBs3HMhY3ojg4hTBq3hkaJuasHIk46Ud3lrhOZQSy62USzu5fhIzUeNg6+6HXmFUy18souRdS6SlxWD5V+gLj6vG1bKHrZb+fN4nakp2B07vnvbtemsK/UmM07PhjsddLk0qBqH5GVAfhP2cS+xu+cS+C+0+Ejp0V9Jyk1hnZryOYaOM/dyJcf+iNnIgYPBz8CxJOXZaUid51DNpW5vCeOhI6tlZIexCCm60GIK9IAGRFVK3VhF0v929fjtTkRDi5eePHXxdJXJmS4mPkjptzx3ez6+XSv8bL1dOm6yC06yYSlyio8fZ185nLFgVCrl6vJdp0Vpzg4f32NH3XnmVIY+3xYZY2su2RvU6dP76LtWfZXz+915623USiBgkqO9bNY+0xMbNEjXqt0LoE7SlN9xI16zREWmoKdmxeg5TkJLi6e2Ly9DkSV6aE+Fi562VObg5WL52HxMQ4aGvrwMHRBT+MncLqIcg16u2rMFw4c5wFRTY3t0TZClXQ7bsBchm+lFG9diPWnt1bVrH2uLh74edp8+TbI9M3JDqtWzZH0h57RxcMHzuV1SNqjzoLlHzxzFEm4hgamzDRauqfS1kqclU0rRzAgh4vO3wBCWmZ8HG0wdIfuktSipNII3t+p2XlYMaWI6yssb4us+jZ8FNflrpczKz+HbDwwFlMWnsAaVnZLE7OiDb10LmO6nH6lhBy46Ivhlrh544QxvmmIPGBbqgWLlz4VdtBFj1kGUOpwikLFufzsPNayYNJfwkehHy+mEIfSv1/Ph7fJ+Gprzr+yZfkfrLqOBZfGl0t1e6KX5I66aJMOKWBaSGiN5ilhaQE1cLFl0SQX3qOGSL7c0Za/0B+H6LYMudrob9ElOWzNHCho3Lr6y+NUd1i3NC+MKYy7jlfm0Lm4Fh6yCkoPe/NrfU+X1D3j6Gg8ONf2P7T+EV8WLbcz4leA1HQ6m+R9e+HfS0V9C0+EfM3R+mZWThfFXqjTwGXaVm6dOkX//43b96wgMP05o8sZyitNrkgkbsXh8PhcDgcDofD4XA4HBFcyPkXoCi9tphjx46hdu3aJcpaRWIOZXgqGlCXLHRIaFHEihUr5II3fyxk+kjxZChGDxmJBQYG4vTp08wqh9KYqwom/eTJEzg7S/3CORwOh8PhcDgcDofzZeG+Pl8OLuT8CyiaGUkWB4eSRVYvmmVKForhoyz6+z8VfJcyXRTNECUb60bVb6TtHA6Hw+FwOBwOh8Ph/BfgQs6/AMr09DmhIMBfE3Fqdg6Hw+FwOBwOh8PhcP7rcCGHw+FwOBwOh8PhcDgczifBXau+HNL8bRwOh8PhcDgcDofD4XA4nFINF3I4HA6Hw+FwOBwOh8PhcL4RuGsVh8PhcDgcDofD4XA4nE9CyF2rvhjcIofD4XA4HA6Hw+FwOBwO5xuBCzkcDofD4XA4HA6Hw+FwON8I3LWKw+FwOBwOh8PhcDgczifBs1Z9ObhFDofD4XA4HA6Hw+FwOBzONwIXcjgcDofD4XA4HA6Hw+FwvhG4axWH8x8mNbN0abmlyRwzJVsLpYkoLTuUFpIzNFCa0NMpPcdxuH01lBY0Q0tPvxAaGqWnPVEvo1GacPZxRGnhWYoBShOWA5ehtJD4Sg2lBacHd1CaSClXCaWFtPNPUZoIeZGP0sKwoEiUJgzSS89c/NC+DUoLVb92Az4BofBrt+C/Q+m5q+JwOBwOh8PhcDgcDofD4aiECzkcDofD4XA4HA6Hw+FwON8I3LWKw+FwOBwOh8PhcDgczr8mTMK/HW6Rw+FwOBwOh8PhcDgcDofzjcCFHA6Hw+FwOBwOh8PhcDicbwTuWsXhcDgcDofD4XA4HA7nk+CuVV8ObpHD4XA4HA6Hw+FwOBwOh/ONwIUcDofD4XA4HA6Hw+FwOJxvBO5axeFwOBwOh8PhcDgcDueTEHLXqi8Gt8jhcDgcDofD4XA4HA6Hw/lG4EIOh8PhcDgcDofD4XA4HM43AhdyOJxP4PXr11BTU8P9+/c/uS6qZ//+/f9IuzgcDofD4XA4HA7nS1JYWFgql38jPEbONw49/O/btw/t2rX72k3hlJDffvuNCTZFxZ/o6GiYmZmhNHDvwhbcOr0GmWnxsHLwRcMuU2DnWlZh2YSoUFw5shCxbx8jLSkS9TtORKUGfZXWfePkSlw6MBcV6/dGg06Ti21LNT911C6jCUM9ICapEIeuFSAiQfmEHOiqjsaVNGBqqIbEtEIcvyXA8wihZHvDChoo664OEwM1CIRAZEIhTt4pQER8ySb566e34NLRtchITYCtky9a9ZoMJw/FfXPr3E7cu3IQsRGhbN3B1R+NO/8oV/7xrZO4eW4HIl89RnZmKobP2At7F78SteXM0Z04tm8TUlMS4ezqhZ4Df4K7d6DCsrevncWR3esQGx0OgaAANnbOaNa2J2rUbykpQxe6/dtW4MKpfcjKzICXbzn0GvIzbO2di23LnfNbcOOk6JixdvRF465TYO+muF/io0Jx6dBCxLwRHTMNO09ElYbvHzPpybE4v282wh5fQkFeNsysXNCiz/9g51Km2PbcOLMFV4+tYeNk4+yLFj1/gaO74vbERYbi7L6FiH79GCmJUWjWfSKqN+kjVyY3O4OVCbl7GplpibBz9kPzHpPh4F58W44cOoB9e3YiOTkJbm4eGDR0BLx9fBWWvXrlEnbv2Ibo6EgUFAhg7+CAdu07oX7DxpIy2dnZ2LBuNW5cu4L09DTY2NiiVZv2aN6yNUpCEJ1Tge/OqeRCHC7BOdWoovScOnFb/pxqQOeUm8w5lViIUx9wTrWupYta5XSgp6OGsMgCbDuZhbhkaf2KqFtBB02CdGBsoI6IOAF2nM7C62iBZHuPpvrwc9GEiaE6cvML8TKyAHvPZyM2SXW9xHdtrdG0thkM9DUQ8iILSzZHISouT2n5AC99dGxmCU8XPViYamHG4je4fj9dafnh39mjRT1zrNwejQOnE1W2pVVNXdQqq8365mVUAbaezEZ8SnF9o43GVXRhbKAm6psz2XgTI9M3TfTgS31jIO4bAfZdVN03l09uw9lD65CemgB7Zx906DsJLp6Kj/1rZ3bj1qWDiIl4wdYd3fzRsusopeV3rp6Ga2d2oV2vCajbohdKwqkju3B0/2akJifCydULvQeNg4d3gMKyt66dw6Fd6xAbE4GCggLY2juhedueqFW/hVyZs8f34nVYCDLS0/D7/M1wcfcuUVseXNqCu2fXICs9Hpb2vqjbcQpsXRTPNYnRobh+bCHiwh8jPTkStdtNRIV68nPfrVMrEBZ8EslxL6GppQs71wqo2XoczGzcS3xdOL5/I7suUN/0HDBe6XXhwsm9uHr+CCLfhrF1Fw8/dOw5XK481bN740I8un8d2Znp8A6oyOq0Kea6YF6rMtzH9odJxUDo2lvjdsdhiD14RvU+darCf87PMPT3Qk54NF7MXIaIjfvkyrgM7QH3Mf2hY2uFtOCneDx6BlJvPSy2X26e2YIrx9dIrt3Ni7kmnNu/EFGvHyM1MQpNu71/TRAKBTi/fzGCrx9kdRqZWqN8zfao03oouzcvjqo+6qgZqMHm4dikQhy5KWD3I8oIcFFDgwqaMDUEktLovkWA0Ehp+fY1NVDBU0Nun9BIITadLii2LfuOnMD2/YeQlJwKD1dnjBrUD37ensXud+biVUyfuxC1girjj0njJJ/PXLAUx89elP+9Fcph9m8TURJ2nrqMTUfOIjE1HV7O9vipdwcEergoLHvo4k1MW7lN7jNtLU1cXTeb/U/X0aW7j+LK/RBExifCUE8XVQO98UPXVrAyM/mm5hoOpyjcIofzryUvT/mNd2nE1tYWOjo6X7sZeHrnKM7vnYnqLYaj18/72EP57sX9kZmu+IEjPz8bJhaOqNN2LAyMrVTWHf0mGA8ub4eVg0+J2lLGTR0tgjRx5l4BlhzIR3RSIfo104KBruLyztZq6FpfE7efC7F4fz6evBHiu0aasDGT3lQlpBbi4LUCLNiXhxWH85GcUYjvVdQpS/D1ozi6dRYatBuO4dP3wNbZB+tnD0RGmuK+efX0FspWa4H+E9djyK/bYGJhh/WzByA1KVZSJi8vGy7eFdG061h8CDcun8T2tfPRtttA/DZvM5xcvTF32g9IS0lSWN7Q0BitOn+PX2atw4y/t6NWw9ZYs2g6Ht67JilzdN8GnDq8Hb2HTMSUv9ZDW1cX86b9gPy8XJVtCbl9FGd3z0StVsPRb5LomNmxqD8TPBRBooyppSPqtVd+zORkpmLT7O5Q19BClxGrMGDqETToNAG6+sXfeD26cRQntv+Jem2HY/Bve2Hr5INNcwcoHaf83ByYWTmhUeexMDRR3J4D66Yg7PFVdBg4C8NmHIRHYE1smNMPacnSsVTEpQvnsGbVcnTr0QvzFy2Hq7s7pk75GSkpyQrLGxkZoXO3Hvhr7kIsXLoSDRs1xYL5s3H3zi1JmTWrlrH1MT/9jCUr1qJ1uw5YsWwRbly/WrJzqqomzt4vwJKD+Uwc7dtU9TnVpZ7onKJzMOStED0basLaVP6cOnS9AAv352HlkXykpBeiX1Mt6JfgnCIxpn4lHWw9kYVZm9KRl1+IH7oYQlP+eUSOSr5a6NRAD4ev5OB/69OYWEH7GOlL2/Q2pgAbjmZh2uo0LNyZwT4b1dUIxT1fdWpmidYNLZh4M+Z/YcjJFWLGj67Q0lS+o66OOl6F52DZlqhif2/1CkbwdddDQnJ+sWWbVNVB/Yo62HoqC39tSUduHjCys4HqvvHRQsd6ejhyNQf/25iOiHgB20e+bwTYeCwL09amY9GuTNYnIzsbKu2be9eOYf+mv9C041CM/d8u2Lv4YMWfg5Geqvh8ehFyCxVrtMDwX9Zi1LTNMLOwxfKZg5AiM++JCb51Gm9eBMPEzBol5fqlU9i69m+07zoAM+ZthLObF/76bSRSVcx9bTr3w6+z1uB/C7aiTsPWWLVwBoLvSue+3JxsePuVQ9feI/AhPL97FJf2z0RQs+HoNm4fLB18cWB5f2QpuV4WvLte1mw9FvpK5r7IsJsoW6snuozeiXZD10EoLMD+5f2Rn5tVbHtuXj6JHevmoU3XQZg6dwu7LsybPkLpdeHZ4zsIqt0U42eswOQ/18Hc0gZzpw1HcmKcRNxfPHMs4mMjMXLiPEydhV3LLwABAABJREFUtxUWVnaY89tQ1meq0DDQR1rwMzwaOQ0lQc/VEVUOrkDi+Ru4XLktXi3agDIrfodl41qSMnadm8Nv9kSE/r4El6u2R3rwUwQdWQNtK3OVdT+6eRQndvyJem2GY/DUvbBx8sHmeSquCXnvrgmdlF8TLh9dhVvnt6FFzykY/scRdv24cmw1bpzeVOxvJXG8WRUNnH8gwPJD+UxQ791IU+k87GSlhk51NHE3VIBlh2geLkT3+vLzMBEaIcRfO/Iky66LxYs4Zy9dxZK1m9CnayesmjcTHm4uGPfbTCSnpKrcLzo2DsvWb0ZZf8UvJapWLIe965dLll/H/YCScPL6Pczfsh8D2zfF5t/HwtvZHj/MWoGkVOXiuIGeLo4vniZZDv39q2RbTl4enr6OwIB2jbF5xljMHt0Pb6LjMGbe6m9qruFwFMGFnA9g9+7dKFOmDPT09GBhYYFGjRrhwoUL0NLSQkxMjFzZ0aNHo3bt2uz/9evXw9TUFIcPH4aPjw/09fXRqVMnZGVlYcOGDXB1dWWWGCNHjoRAIH1rRp/PmDED3bt3h4GBARwcHLBkyRK57UT79u2Z+i9eJ5YtWwYPDw9oa2uz79y0Sf7CQuVXrFiBVq1asfb4+fnh2rVrePHiBerVq8e+r0aNGggLE72lKQ4q17ZtW9jY2MDQ0BBVqlTB6dOnJdsnTZqEoKCg9/YrV64cpk+fzv4n9Zr6gPqK+nfChAno06dPia2NqN0jRoxgfW9paYmmTZuyzx89eoTmzZuzdlH7evXqhYSEBJXjmpmZybYJhULWPkdHRyaylC9fHsePH1faBvFYy0LWN+K3M7R92rRpePDgAfuMFvpMkWvVw4cP0aBBA0m7Bg0ahIwM0QMJ0bdvX9Y3c+bMgZ2dHSszfPhw5OcX/4Cgittn1qFMjS4oU70jLO080bjbNGhp6+LRtT0Ky9u5lEW9DhPgW7klNDS1ldabl5OJo+t/QtMev0OnBA/jRK1ADdx6JsTdUCHiUgpx4EoB8gqASt6Kn2RqBGiwG5lLDwWITy3E6bsCRCUWopqftPyDl0KERRUiOR2szqM3CqCrrQZbGbFHGVeOb0Dlep1RqU4HWDt4om3f36Clo4s7F/YqLN9l6GxUa9SDWdhY2bujff8ZKBQK8fKJ9KJeoWZbJgx5BtTAh3DywBbUadIOtRu2gYOTO3oPnQhtHV1cOnNQYXnfMpVRqVp92Du5wdrOEU1ad4ejqydCn9yX3LCfOrQNrbv0R8WgeuzN08BR05GcFI+7N86rbMvN0+tQrmYXlK3REZb2nmjWYxq0tHQRfFXJMeNaFg06ToB/FeXHzPWTq2BsbouWfWYyyx5TSye4+deCmVXx1kFXT65HpTqdUaF2RzZOrXqLjuF7lxS3h6xqmnYdjzJBLaGpqaXwpj7kzkk06TIOrj5VYGHjgvrtfoC5tTNunZV/E1iUA/v2oEmzFmjUpBmcnV0wbMRoNpecPql4HilTtjyq16gFJ2cX2NnZo027DnB1c8eTx48kZZ6GPEGDhk1YWbLGada8FdzcPRD67GmxfUNvgG+/O6fi351T+SrOqer+onPq8iP5c4o+FxNc9Jy6WfJzqmFlXRy7loMHL/IRGS/AusOZMDVUR3nv98dBTKMqurjyIBfXHuYhOlHIRCCa9mqUkR5Llx/k4UVEARLThAiPFeDgpRyYG6vDwkT1bU/bRhbYcTiOWdS8jsjF3LURMDfVRPUKxkr3ufMoA5v2x+HaPeUPGoSFqSaGdLfH7NUREAiKt1ZqUEkHx67nIPhFASLjhVh/NJNZGJX3Ut43DSvr4EpwHq49ykNMohDbTmYjLx+oHijTN8HUNwIkUd/ECXDwcrbKvjl/ZCOqN+iEoHrtYevogc79f4W2ti5unJe3lBDTa8Qs1GrSDQ6uvrBxcEfXQdNQWChE6KPrcuVI2Nm7fia+Gz4L6holNxA/dmAr6jVphzqNWsPB2R39hv4MHR1dXDx9SGF5vzKVULl6fTg4ucHGzhFNW3eDk6snnoc8kJShN+btuw1AQLmq+BDunV+HwOpd4B/UERa2nmjQeRo0tXXx5IbiucbGuSxqtZ0A74otoaGheO5rN2QN/IM6wMLOi1nENurxJ9KToxAX8bjY9pw4uBl1GreXXheGTHp3XTigsPygH/9Ag+Zd4OzmAztHN/QbNoVdC54E32TbY6PeIuz5Q/QaPBFuXgGwc3Bl/+fl5uLGJeX3QkT8iYt4PvVvxB6Q3guqwmVQN2S/ikDI+FnIePoSb5ZuQcyeE3AbJbVYchvdD+FrdiJiw15khITh4bCpEGTlwKlvR5V1XzuxHhU/5JrgVgZNuoiuCRoKrglE+It78C3fEN7l6sHM0hEBlZsxgT/yVfHWQTX81XEnVIh7L4SITwUOXRMgXwBU9FRXapn8IrIQVx4LkZAKnL0vYC+2gnzlyxcIgYwc6ZJTgveZOw8cQasmDdCiUT24Ojti7NAB0NXRxtHTyq/7AoEQv89bjH7dO8HeVrEIq62lBQszU8liZGhYfGMAbDl2Hu3qV0ebukFwd7DFxH6dWXsOXrihdB+6xbY0NZYsFiZGkm2G+npY+vNQNK5WAa721ijj6YrxvTsi5FUEYhIUv1ApjXPNtwR5MZXG5d8IF3JKCLm9kKDy/fffIyQkBOfPn0eHDh1QqVIluLu7ywkl9CC9ZcsWVlYMiTYLFy7E9u3bmRBA+5MAc/ToUbbQ/iSskKggy+zZs5nYce/ePfz8888YNWoUTp06xbbduiV6Q7tu3TrWPvE6uVpRubFjxzIRY/DgwejXrx/OnTsnVzeJRL1792YuPr6+vujRowcrO3HiRNy+fZtdzEkYKQkkMLRo0QJnzpxhbW3WrBlat26Nt2/fsu09e/bEzZs35YShx48fIzg4mH0vMWvWLNZv9HuuXLmCtLS0D44ZQ8IYiVe0//Lly5GSksLEkAoVKrDfRH0fGxuLLl26qBxXsS/lggULMHfuXCaWUFtJHGrTpg1CQ0WuMh9K165d2bgEBASw76aFPisKCUn0XSTw0bju2rWLCWNFx4PGlPqU/tJvJ1FILAx9DIKCPMSGP4aLr1RUUFNXh7NvDUS9vIdP4fTO6XAPqCtXtyo01AF7SzW8iJKa+9OohEUJmZWAIpyt1fEiSn62podQZeXpO6r4aCA7t5DdFKmioCCPmVl7BlSXfKaurg5P/+p4+6JkMZLI8oPcmvQMSiZkKW1Lfj5ehz1FQNkgubb4l6uKF8+Ci92f3ag/uImYyDfwCajAPqM3rmQ6HFBWenOhb2AID+9AvHj2UOUxE/P2MVz95I8ZWo/8hGMm9MFZ2DoHYt/KkVj4U3Ws/aMd7l/aWex+NE7kIuUuI4xR37j7V0d4CcepKEJBATOj19SSt5ijB4G3oXeU7kfXghcvnqN8+YpybSlXviKePn1SonF6cP8uIiMiEBAodQHw9fPHzRtXkZiQwMoEP7iPqMgIlK9YufhzyuL9c4rWna2Un1Mk0sjyIlIIpxKcU2TtowpLE3UmTIS8lr41pgePV1EFcLfXVFq/s60GQt5I96FvCXmdD3cHxftoa4lEnvgUAZLTlLsP2VpqwdxUC/dDREI+kZUtxLOX2fD10MOnQA8aY/s7Ys+JBLyNUm3hJts3T98U6ZtoAdyK6ZunRfqG1pX1J/UNiTwJSvqmoCAfEa+ewDuwmtwx7BVYDW9CpQ8nqsjLzYGwoAD6htJ5j16SbFkyEfVb9YWdU/EuHO/NfeWqyLWH1lXNU2LofHn84CaiZea+j4XmPhJXnLzl5z5aj379addLWfKyRQJhcdaI1Ddvwp6y64DcdaFsVYSVoG+I3DzRNcrA0FgynxJaWtpydWpqaSM05NNjA8piWq08Es5KX3IQ8acuw6xaefa/mpYWTCoGIOGMjOVhYSESzl6FabUKqq/dbx7D3f/9a0JE2Mf/BifPCngZcg0JMa/Yeszbp3gbehdeZeqo3I/OUzsLNXYvU/TextFK8WOZk5U6XkbLn58k7JCljiyutmoY30ULI9tpoVU1DegVY+Sdn1+A52GvUKlcGbm+ofXHz54r3W/Djj0wNTFBy8YNlJa5/+gJ2vYehO+G/oi5y1YjNU210M3aU1CAp68iEBTgLdeeqgFeCH7xRul+2Tl5aDVqOlqOnIYx89YgLCJa5fdkZGezl6ck8nwLcw2HowweI6eE0AM3WYzQQ76Li8hPk6w4iP79+zPx4aeffmLrhw4dQk5OjkQsEN/Qi61kCLLIIfGGRAWyFPH390f9+vXZA7nsg33NmjWZgEN4e3szgWL+/Plo3LgxrKxE5p5kAUJuOWJIdCBrjWHDhrH1MWPG4Pr16+xz+g4xJO6I20jWL9WrV8eUKVMkliwkBlGZkkBiEy2yIhEJSgcPHmTiAwkXtH3r1q3sOwgSbchKx9NTdBO3aNEiJiKRwEUsXryYiVwfgpeXF/766y/J+u+//85EnP/973+Sz9auXQsnJyc8f/6cCVDKxlXcl9Q33bp1k4hNNEZ///23nHVUSSHrGhpvTU1NuTErCvUTHUMbN25k1lHi/iBxjNpAlkUECT30uYaGBhPjWrZsycS0gQMHvldnbm4uW2TJz9OBlrb0Sp+dkYxCoQAGRhZy5Wg9KeYlPpant48gLvwJvhsvL1SqgtwyNNTVkJEt/zBI61ZK3hyTr/l75XMK5dwKCB8ndXSrrwktTSA9C1h7PB9ZxTxbZaWnsId5Q2P5vjE0sUB8tOhGrjiO75gDYzNreHyg9U1R0t+1xdhU3pzcxMQcMRGvle5HcW/G9G+Ogvw8qKlroNfgCQgoX00SB4EwNpX/fcYm5kzgUVqn+Jgxfv+YSfyEYyYlIRz3Lm5D1Ub9UL3ZEMS8eYjTO39nb0fLVG+vvD3pyUrGyVJyw/2h6OgZwsmjPC4cXApLO3dW18PrR5gwZG6j3EIoLS2VPbCaFol9ZWpqhsjwcKX7ZWZmoF+vbuy6QTeOQ4aPRIWKlSTbBw8dgcUL56Nf727s3FdTU8eIUT8isIzieA9i9HVUnFOmKs6pnPfLG+m9f051rSc6pzKygHX/Z+8soKO4ujj+3427uwtxJLi7u1uLtFC0Qg2KtEAN2tJSpIK7FQkuwYK7EwIEj7v7Zvc79y2r7G6CNvR7v3PmJLP7ZvbOe/Nk7lw5UHGfsjSXniO3QPUBJa9QwmLfaJTHVMCuQdMxznZ6z8TR6dXShFkHJWeUY96mfBbDRxs2VtIlUVauqjtCdq4INlbarWAqA7ls0W/vPKw7Jo4Mim9DPHOdBWL5d+qYmzytm0LVY2jfyVZ1ude8liF6tVCqm80FGuumIFfanyysVPsT7acmVq4/7V7/GyxtHBAQplCCH9m5DEI9PTTv+C6eh7xc6dhnpTb20ViYGP9Y59j38ftd2NgnFOph2JiJqF7rWSvh56GoQDr2marNl7SflfLiY58yZMF5POJHuPjUhp1LQOXmBbW2ojE9KUH7vKAMxcKxtrFHaE1p3Ti7ecPOwRlb1i7EsLFTYWRkgshd65CVkYLsLIVl86vAyMkeJSmq56R9AysLCI2NYGBjBaG+PkpSVftQSUoGzAJ9dc4JEg1zgpmlPdIrOXdromnnUSgpKsDCqZ3ZPUV136b3BNRo1K1S43BBserntO+gRVcnHYdVP6Nx2dxEMU5SvJxbT0TMMtLWAmhbWx9D2gqwZK9IqzVCTm4uysVi2Fir/jDtP4lP0HjM9Vu3sffQUSz9fbbWa6wfXgvNG9aHs5MjEpNTsGTNRkz8djb+/Ok76JEmSwvZeTQOiWGrZFFD0P6jJKm7nzpeLo74+oOBLJZOfmER1u49ivdnzsc/syfByU7VQp4oKS3Dgo270aFROMx1+P9WpbGGw9EGV+RUElJCtGnThj3kk6Kjffv2TBlDD9KkNJk2bRpTljRs2JBZRJCCRPYATpD7kkyJQ9CDOLlC0UO98mepqaoDFSlX1PdJiaALsiwhNxxlSCFE1iXK1KihWPTLFAPKSgz6jJQJZBljaandrJwghQgF8d2zZ49c6UUBOWUWOTKrHFKikCKHNNUbNmxgSiYiJyeHKbXq11e8SaIHFLJ4ogehykLllSEXJlK8KNezDLJkoXbU1q503YmJiazulKF9Ou/rhNqQ7jnle4h+l+rizp078vYiBRnVkwxysSKXLE3MmjWLuXUp03XIdHQfOgOvk9ysJBzZ8gP6fbT8GYuGfwt6s7UgohRmxgJmPTCotQH+2ln6zMLqVXJs1xLcOLcPIyevUlGevUmMTUwxc+56lBQV4tb1CyzGjqOTG3O7qmrQGOHiFYYWPaVjhLNnCAuSfOX4Rp2KnNdF71E/Y/vyKfj1sxZscebiFcLM7ulN76vGxMQUvy9chOKiIly7dgXLl/wNZ2cX5kpF7N65HXdvx2Da9O/g4OiE6JvXsejPBbC1tUOtcNUx8E32qYXbpX2qbqAeBrYywN+7VPtU/RBDFoRYxh9bFK6ir4Nz0SXMUoeUQu3qG+GDHmb4ZW0eRE89mFs2sMKHQ1zl5WfM1744fxn8vYyZy9bH32p3Va4XbIDB7RV18+fW11s352+VMksoK3MBC4z8QTdT/LI+X143r4pDO5ayGDvjv14hH/fiHkTj+P61LN5OZYLCvqqx74ff17I+FX39Aot7QWMfuUJUZaK2zGQBkvt+sv61/9aerStYjJ2J3y2WtxW5mo6fNAcrFn6Lj4a0YmMfWfxUr93kP5sFprJEX9iHG2d3oc+oOcxdiyxy9m/4UR70+E1z85FirZyaDaRkleHTPobwcRLgQfKraavCwiL8MPcPfDH+A1jreC5o01zxsoqCJ9M2aPQnuHozWsX651VQo5o322TUrOaDvhNnY9uR0xjbTxFkWBb4+KsFq9i9+9XwfngdvK1jzavkOR7bOC8JV+RUEnpYJpem06dPIzIyklmPTJ06FefOnYOPjw+zlCCrHPp/3759zEVHGYqjowwtXjR99jxKi5dF+fdliylNn1VGpi+++ILVD1mwkIUNWZ6QQkQ54DC5MJF1y+XLl5mSJy4uTqNb0cugrPiQKZhkVizqkNJDV7tSzJnnhd6eqy9uXjZmjS6e5x4iayeZ4kzG2pOqCgUTcxtmqaEe2Jj26e3Vi0DZrCjw4+rZveWf0dux+HsXWHasT+fdYItDdQqLgXIxvXGi+1BRp7Sfp2ZRICO/SPq9MubGAva2XhmKCZKZR5sEcWkifNbXAHUD9HDsuvanGFMLayanenDE/JwMZqGhC8pydXzPErw3cTkLkPyyWDyVRT2AZU5OJixt7HTen04uHux/T99AJMY/xO6tK5kix+qpJU5udgasbRXXk5uTCQ8f7W+CTWX3TO6ru2cICjBp56JQfhN2zr64c/mAzuNMLWy0tFM6zF9CHoqH8/5Xa1FaUsgyWNFi/Z8/P2UBMbVhaWnF6jw7S9UPnwIdW9tqz1BHx7i6urH/ff38Ef/kCbb8s4Epcsiqbs2q5Zg8bQbq1ZdaU/n4+OLh/fuI2LZZpyKHLGS09al8tT6i0qeM1fqUhj6o3qc+7WPA4u4cV+pT1+6VMrcpGfpPVyCkaMktUJQjCzoKYKxRnkIJuwapxY7qMerWK+SKVFwqZhmw6Hd/+8Saxd65GCMdk89dzcOdhwrliiygsY2lPrJyFHJaW+rjQZzuwK66CK1mBisLfaz8WdH39fQEGNHfmSl43v/qLq7fK8OjJIXrgSyg8TN18zRLl8a6KXpaN6aqdUP7uQUSjXWTlk2ubAX49SMrFnvn4m3V+crMUtqf1AMb076lte7+dHT3ChzeuQxjpyxhAZJlPLh9Gfm5mfj2I0UmNnrzvWPtLzi2bw2+WRCp9ZwWltKxTz3YKI2F1pUc+yhDTGLcQ+zasvKlHq5MzKRjn3pgY9o3fYmxRkbUlm/x8FYU+ny0FhbW2i14n5kX1NqKxnSrCtqKslzt3bYSX8z8i8VHU8bbLxgz525AYUEee0lnaWWD7yYOhbdfCF4lZH1DVjnK0H5ZTh7ExSUoTc9iLnpGjqrtbORkh5LkdJ1zgkDDnFCQm17h3K2Lg//8gqadP2AKfcLJPZBlPTyxZ7FORY5sHFYPbEz7eVqGGek4rPoZjcvq1pXKZOWTlY8EtpbaFTlWlpbQEwqfCWxM+7Y2z1qzJCSnIDk1DVO+l2aEIsRP17ytew3Gmj9/g5vLs/eqq7MTrCwtkJCUolORY21hxuRRD2xM+3ZWul8oy9DX10Ogtxvi1Ky7ZEqc5Iws/DV5nE5rnKo21nA42uAxcp4DekgmqwiyaqA4MBSLhdyHiJEjR2LTpk1YvHgxs7xRt+J4UcjKR32fAhMrP8grB0gm6HtywVKG9sl963VB5yfLJHKLIusWcht69EjVlJcCBrdo0YK5VNFG7mGOjtIgaVZWVszKRBbnh6DrIqXPy1C7dm0Wi4esn0jBpLzJlD7a2pWskFxdXZ+rLsndLS8vTx4smVBPM07nV28zdagNyepH+Tz0uzRBUPDqF4ECrNI1KW/qliEUeNbJIxRP7pxRMe2mfVffF/Px9QpsiGFTd2Ho5O3yzckzDCF1u7H/NSlxCDLzT0yXwN9FMUzRY5afqxBPUjUvSp6kiuHnqvrQ6e+mvbz8vAKBzkwwhL6+IVy9Q3E/WtEnSWl2/9ZZePpLLSU0cXzPUhzd8ReGfbEY7r6aU8A+L/oGBvD2C5IHpJTJEnP9AvwDdbvXKEMBSMn8l3BwcoOVjR2z1JFRVJiP+3dvwj9Q+8KL7hlnz1A8uq16zzy+fQZuL3jPEO5+tZGZomr2npnyCFZ2UgWHrnZy8Q5VCShNdfMw5iw8dLRTZTE0MmVKHEoVf//mSQSFa48RQOOzv38Arl27rCLL9atXEBRU+fFYLBHLFcIUv4IepoQC1elbqCeERKz7Pmd9KkPC+tAzfSqt8n2Kyse9QJ+irEuUOlu2JaWLkZMvZqmwZRgbgsWAoVTb2q6Bsi4pH0PSBXkbsBTj2uWRbgZ6imspKhEjKbVUvlHsmszsMtQMVrwQMDEWItDXBLfvv7gi58iZbHw44x4+mqnYKGvVtgPp+HqudJ4sKVOrmwxp3QR6qtWNi56KMkxT3QSq1Q3ta6tP5brRV6obGWSRQenD7948p3IPx0afg1c1hTu1Ood3LkfktkUY/dXf8PRTHffqNuuGL3/ahi9mb5FvlLWqVbf3MGbyIq3nVB37LqjIE339os5xSh164VImermXLDT2ObqHIi5WdeyLu3uGpQx/UUg2UuLcv3EQvcevgpWddmWxet14+QWxeUBlXrhxAX466mZfxCrs2rwUn32zED7+2sclUzMLpsShAMiUOjm8QQu8SrLPXoVda0UsJsK+TWNknX0akL+sDDmXo2HfWslSXSCAXatGyD57Rffc7RWKhzGqc8KDmLNw93vxOaGstIjFRHr2ZZ7ul5/UT5MyJPBVW9vQfnya5mPj0sQq5Qkal+O0jNuEpSlYjBxtL74IAwN9BPj54NL1myp1c/n6TYQGPvsCx9PdFSvm/4Klv/8k35rUr4Pw6iHsf0d7zYqx1PQM5Obls6DHujDQ10eQjzvOR99VkedCdCxq+GtOP64OuWbdi0tiQY/VlThPUtJY4GNSGFVEVRprOBxtcIucSkIWGhR7hFxvSPlA+2lpaXKlCrnl0IMxxWSRZWF6FdDDO8V8oexEZDlCQW/JfUkGKShILlJE0IM6uQRRrB5y7aLYMJSBiWL2bNu2TSWL1KuGYtPQb5D1Cy3gyX1Kk2UIuVdNnz6dWepQrB9lPvroI+b+Q0oWivdC1jFZWVkvZXpNWZyWLFnCrIEmTpwIW1tblpmLgk4vXbqUBUDW1a5UlyQvKecoYxVZXZFihhRRmqCYP+RGR1m6KAMXnU89+DC12cOHD9l5SLlF6YbV047L6omydpHLGslE9UMZt2RuVa+Lum3ew77Vk5iyhbILXTqyCmUlRQhrKLWo2btqIsytnVi6cVnAx4wk6Vvt8vJS5GWnIDUuBgZGprBx9IKhsTkcXFUXBPSdsbn1M5+rQ5lyKOVmfDotcCQs446hPnD5rlQRRt/lFkoQeVG6fzq6HB90MWDZru7EiVHDVwg3ewG2n5I+xFD8jlY19VgKZVrcmBoJ0DBEjy14bjys2PKsScdh2LpkMtx8wuDuWx2nI1ejtKQIdZpL375tXjQJljZO6NBfavl0fPcSHNq2AP3HzoGNvRvystPY54bGpjAyli4kCvOzkZ2RhLxsqVulzGffwsoeFtba07m37/EOls6bAW//EPhWC0XkrvUsrSWlFSeW/P4NrO0c0W+INED27i0r4OMfDAdndxbE7/qlUzgTtRdDxkxm31M/a9dtEHZtXgYnVw/YO7ohYv1fsLF1YFmsdEFxbHavnMRcoeieuXhkFUurXqOx9J7ZtWIiLKydWLpx2T2T/vSeET+9Z1LiYpiShO4Zol6bYVjz8yCc3vc3gut0QuIjSl3/Dzq+U/H42rj9cEQs/Qpu3mFw862BM5GrWDuFN5XKs23JJKaMadfvc3kwzLRE2T1cxlKKJz2RykMZqoh7N04wGxZ7Zx9kpj5G5KZfWLwc2Tm10aNXH/z+28/wrxaIgIBA7NyxDcUlxWjTriP7fu6c2bC1s8ew90ay/c2b1rOyZDFIypuLF88j6sghjB3/Cfve1NSMxcJZsXwxDI0Mpa5VN67j6OGDeP+DMRXWzamb5ejTTB8JT/sUZXqjPnVJuU8VSBB5Sbp/5lY5RnY2YH1PW59qWVMPt6lPFUpgaixgWeKoT92sRJ86fLEYnRobM6sZCrjbvZkJsvPFuHpXsfCdMMAcV2PLEHVZGnTn0IViDO9ihsfJ5XiUJELrusYsaO/pG6XyQMF1gg0R87AMeYVi2FgK0aGBMUpFEtx8oHtBveNQBgZ2cURiSimS00sxpKcTMrNFOHMlV17mh8+9ceZyLnYfzZSnH3d1VASDdXYwhK+HMfIKypGWWcb+0qYMZa0iq5+EFO1pZY5cKkHnRkZIyypHeo4Y3ZqaMOUO1YWMT/qbsf1jV6TnOXyxBMM6m7L064+SytG6rhGMDMCyWMnrJsiAuVWxurFQ1E30Q81107LLUKz/ayo8fEPh5R+GY/vIMq0IDVpIM0qu+3MyU8R0HfSpVIady7Bv80IM+fBn2Dq4ITdb+mbciI17pjCzsGabMpS1ytLKHo6uPqiITj0GY/G8mWw8o7HvwK6NbOxr3rYr+/7vudNhY+eIAUPHs/2dW1aysk7O7igrK8W1S6dxKmovho+ZJD9nfl4OMtJSWJY+ggKUElY2tixmjDbCW76Hg+snwckjjGWkunpsFUSlRSzrFBG5diLMrJxYunHZ2JeZrBj7CnJSkBYvnS+tHbzk7lR3Lu1G15F/wsDIDAW5UpmMjC1YRixddOj+LpbOn86saHyqheHgbtm80J19v2TeN2xM7ztEmgqarHC2b/gboz77AfaOLsh5GveG2olcRIgLpw7CwsoGtvbOSHh8D+uXzUHt+i0RVkvV9V9T+nEzf0UMMVMfd1jWDEJpZg6K45IQ+P1nMHZzwrX3pO3wePFGeI17B0GzvkTcyq2wb9WQpRu/0H20/BwPf1+Bmst/Qvalm8i5cB3eHw+DvpkJ4lZpzhwpo1EH6ZzgSnOCTw2cPShd1yjPCRS/jtKNPzMniMrYHKU+JwTUaoXju/+Gla0LHMi16nEMy45FmbEq4vQtMXo11WOK9fh0MRoFP13b3JOOmb2b6iG3ECxLIHE2Roz3O+qzbFd348Wo7qPHAtfvPCP93vDpOHzrsZhZ6dhaCNC+rh4yc6VBkXXRv0cXzJr3F4L8fRFUzR9bdu1FUXEJOrWVKurIlcrBzhajhg6CkaEhfL1UFYvmZtL7RPZ5YVExVm3cguaNG8DW2orFyPl71Xq4uTihXm3tyl8Z73RqiRmL1iPExwOhfl5Yv/8YikpK0a2FNM7MN3+vg6ONFT4cIO3vSyIOoLq/F9yd7JFfUITVe46ybFQ9WzWUK3Emzl+JO4/iMffzkUzRk54tHc+tzE2Z8uhtGGveJv7PvS7fKFyRU0lISXP8+HEWn4Zip1BgXMpmRGmtZVp4skihoLqUCepVQRmOSNlA1iIkw2+//SYPRkyQDOQuQ8oKSk9OVjCk9KF4OOTmRAGLyd2LFBCUnvt1QXJR5idKWU6pv8mFiupJHXK3ouDH5NKknlacjqE07lR/9D3F+aFrVY4B87zILGro3KSsIbcEajvKqkVtVlG7kjKG4vdQO1D8IrLEoQDOpLjSBCmK1q5dyxRA1CYUf4cUMcoxi/r06cOUXhR4mrJqUdvQvaMMKYMOHDjA2o9SudM+HUf1/LoJqtMZhXmZOLV7Pgrz0uDgFoy+45fK3WQo5g0FV5WRn5OK1bMVbXnx8HK2uVerj4ETVNPePy+kXDEzFqFtHX1YmEjfYlEQVVnQP2tzgcqEQZY3m46K0K6OHlvEZORKsPaQCClZ0kJU1sFagPBqBsyMmdy3aBG1eE8ZS5tcETUadkZBXhYOb5uPvJx0uHgGY/iXi+Xm2TkZqnVz7shGtgjcsED6EC6D0o236S1VsNy+chRbl0yRf7fpz8+fKaOJBk3bIy8niy3CKRixp08APpu+QO4ilZGWrCJLSUkRVi/6CVkZqTA0NGJBLD/49Dt2Hhmdew1DaXExVv75IzOjDwiuhc++mV9hTJ/gutJ75sSu+eyhw9E9GAM+UrpnMlXrhZRWK35Q3DPnDy5nm0e1+njnc+k9Qwqh3mMW4tj233Bqzx+wtndHm35TENpA+kCii7AG1E6ZOLJ9AfJz0uDsGYwhny1RaqdEFQUxyfP3dIUp/On9y9lGqcbf+0oqT3FRPg5t+Q25WckwMbNGSJ12aNPnU62paWU0a9EKObk5WL9mJVNM+/r6Yca3s5jSnUhLS1V5q1tSXIy//5yPjPQ01k7uHh747Iuv2HlkfDlpGlavXIZff5mF/Lw8psx5d+j76NRZd5BN5T7VpvbTPpUpwcrIMnksGyuzZ/vUP1HUB/XQvo60T607LJL3F9anrASo3dqABSgntwFKlb1kb+X6VOS5EhgZCPBOB1OmBKKU4Qv+UY3V4mAjVHGZvHS7DBamRejW1Ji5HpGrER0jc6EsK5egmrs+S8VN5yTF1L24MhYfR93NUp0t+9OZYuajoa4wM9XDrdhCfP37I5SJFMe5OBjC0kKxfKrmbYLZXyoUEB8McGF/D53KwtwVmgOGVobI8yUwNBCwuEKkdL6fIMKCLQWqdWOtB3MTxQeX7pTB3LQIXZuYsKDIrG62FCjqRiSBv7s+S20ur5t4EeasU9SfOuGNOiE/Nwv7tyxkShk3ryBmaWPx1F0nK121f586uImNeyt/lyp2ZHToMxYd+0ofeF6Ghs3aIS83C1vXL5aPfV9On6cY+9JT1PpUEVb9/TMyn459Lm5eGPPpt+w8Mi6fP4El8xVK4j/mTGV/KU1w70GqMQeVCajdGUUFmTi7Tzr20XzZY/RSmFpI6yZPbb4syEnFhjmKse/y0eVsc/Orjz4fSceaG6c2sL/bFg5R+a22g2bJFUTaqE/zQm4Wtm+UzgvkFvvpN4p5ITMtGUKlse/o/i0sM9mfP09UOU/3AaPQc6BUgUJBjTeumMtctuhBs1HLLuje79mECupY1QlDo8OKNUDIHOk8F7d6G66PmAwjFweYeEj7ClH0KJ4pbUJ+nQzvj4aiOD4ZN0ZPQ/rBk/IySZv3wdDBFgHTP4aRswNyr8XgfNeRKFULgKxOWH3pnHBUNid4BOPdT5XmhMxECISqc8KiGc/OCV40J0ySXlPnwdNwJGI+9qz9lrkW08uBOi0HoEV3aaKRiuLZ0HjZuhb1Xz2W4W/NIZHaOKzoj2R5s+W4CG3C9dG2tnQc3nBUMQ6TMaazjQC1/PSZ5R65aFEWrMNXRDoDvBOtmzVGdm4ulq/fjMysbPj7eOGX6V/B1lqqbE1NT4dQqW4qglyj7j96gv1HjyO/oAD2tjaoW6sGRrzTn6Ukr4j2DcORlZuPv7fuR0ZOLgK83LBg4mh5SnFS0ijfw7kFhfh+6T+srKWZKYK83bFs+scsdTmTPysHxy9LLY4GT52j8lt/TxmPuiH+b8VYw+FoQiD5f49W9gqh7FVkOUEP+q8CstyYMGEC2/4fIYsesowh6yLKgsV59Sx5fUZaL8TDxxWn5X1T1A57uSw1rxpXS4Wb3b/NnWTVjBL/NiZGVWcaC3eKR1Vh9TGp62pVISOtEFWFuNgXV7C8DjwD3VFV6NamYreDN4m9adW5by481J0C/E1Sy+v1BsR+XrJrVp0YILlRt1GViLlXdVxrxjV49QH6XwazPN2pwt8kMRavJizGq6B+UNUZa56X33dWnTWZMhO6v5ng+m8SbpHzCiCLDcoURCmjX5US5/+Rx48fs4DDFEeHLGcorTa5IA0ePPjfFo3D4XA4HA6Hw+FwODqoIFwf5xXCgx2/Anr06MHcdsaMGcMC+P4XoTTXlMJb06YtXszzQq5OFE+GXIko5g8pxyiuD1nlUBpzbb9Pm3Kacw6Hw+FwOBwOh8PhcP6rcIucV4B6qvFXhXrWp3+TvXv3ak2j/aqC73p4eDyTIUo51o169if17zkcDofD4XA4HA6Hw/mvwxU5nEpBQYD/TfT19Vk2Kw6Hw+FwOBwOh8PhVD149N03B3et4nA4HA6Hw+FwOBwOh8N5S+CKHA6Hw+FwOBwOh8PhcDictwTuWsXhcDgcDofD4XA4HA7npZBU2bRVAvzX4BY5HA6Hw+FwOBwOh8PhcDhvCVyRw+FwOBwOh8PhcDgcDofzlsBdqzgcDofD4XA4HA6Hw+G8FFXWs+o/CLfI4XA4HA6Hw+FwOBwOh8N5S+CKHA6Hw+FwOBwOh8PhcDictwTuWsXh/B+Tnln+b4tQZUlKr1rR7UvLzFFVSMsUoyphZFh12uq+sTOqCnp6Vcu+2ci46iw5PAPdUZXQ06s693BcugGqEkYuRqgqZGaLUFWQeFWde4bIjbqNqoJlyyBUJfLmXkJVYV9SOKoSAkHVkccafE38KpBUraXHfxpukcPhcDgcDofD4XA4HA6H85bAFTkcDofD4XA4HA6Hw+FwOG8JVcfOmcPhcDgcDofD4XA4HM5biZinrXpjcIscDofD4XA4HA6Hw+FwOJy3BK7I4XA4HA6Hw+FwOBwOh8N5S+CuVRwOh8PhcDgcDofD4XBeCp616s3BLXI4HA6Hw+FwOBwOh8PhcN4SuCKHw+FwOBwOh8PhcDgcDuctgbtWcTgcDofD4XA4HA6Hw3kpuGvVm4Nb5HA4HA6Hw+FwOBwOh8PhvCVwRQ6Hw+FwOBwOh8PhcDgczlvC/6Ui59GjRxAIBLh69er/rQz/9u//V1i5ciWsra1f+jxRUVGsPbKzs1+JXBwOh8PhcDgcDofzJhFLJFVy+y/CY+RwOG+Yli1bolatWvj999/lnzVu3BhJSUmwsrJCVaC2vwANAgUwNwZSs4HIK2IkZWovH+QONA8TwsoMyMwDoq6LcT9Z8b2BPtCqugDV3AQwMQRyCoCL9yS4cr/igbVhsBDNquvD3ARIzpRg1xkR4tO1HxfmLUS7OnqwNhcgI1eC/RfKcTdeLP++TbgeaviSrAKUi4GEdAkiL4kQn1a5Qf76yXW4cnQZCvPSYe8ahOa9psHJq4bGshnJsTi3bz7S4qORl5WIpj0mo1aLYSplLh5ahAc3DiIr9QH0DYzh7B2Oxl0/h42jb4WynD+yDqf3L0N+TjqcPYLQafA0uPlqliU1IRZR2+cj8XE0cjIS0WHgZDRspyqLWFyOqB0LcePsTnZOC2tH1GzSC827jmWKRl3cOrMON04sR1F+Omydg9Co21Q4eGiWhXh4Yz8uHZyP/OwEWNp5oV7Hz+ER2EL+fVFeOi4c+BUJsadQUpwHZ++67JxW9t6oDDdOrcPVKGk72bkEoRm1k6dmeTKTY3H+gKKdmnSfjJrNVesm8f4FXIlahrSEaBTmpqHj8IXwDWtbKVlORm7AkV0rkJeTDlfPQPQePgVe/tU1lj1zeAsunNiJ5Ph7bN/dJwRdBnyitfw/S2fizOHN6DlkElp0HlIpeeoHCtEkTI/1qZRMCfacL2f9QBuhXgK0DteHtTmQmUv9pRyxCYryvZroIdxfT+WY2AQx1hwSVUqeTg0N0SjMACZGAjxMLMfmo8VIy9bdH5vWMEDrOoawNBUgIV2MrVHFeJKi6Od0vjqB+vBw0IOxkQBf/ZWHotJKiYOuTYzRtIYhk+dBogjrI4uQlq04tyZahBuiXT1jWJoJEJ9ajk2Hi/A4uVz+/eD2Jgjy0oeVmRAlZRI8SChHxPEipGTqPm+XxkZoHGYIE2MBO4bOW5EszWsaok1dIyZLQpq0PpVlaVLdAHWDDOHuqMeu8cs/clBUortOrh5fh4uHl6EgNw0ObkFo1fdruHhr7k/pSbE4vWc+UuOikZuZgJa9J6N2q+Faz30+cjFO7voV4S2HolWfqagMx/ZtxMGdq5CbnQ53rwD0H/EVvKtp7iMnD27FuWO7kBgn7VOeviHoMfijZ8onxT/A9rW/I/bWJYjLRXB298OoL36FrYOLTlnqVhOgUZBQ2p+ygP2XypGoY74M9hCgZQ0hrJ/Ol4evinEvSfV+t7cE2tQUwtNRAKEQSM8BNp8sR25hxXVzZO8m7N++GjnZGfDwDsDgkRPhGxCmseyxyG04E7UbCU/us30vv2D0fudDlfJ0ni2r5yP66hkUFeQjIDQcg0dOgpOrZ4WynD+8DqeU56h3psFdxxx1lOaoR4o5qlF7DXPU9oW4rjRH1aI5qpvuOcq2aV34fj4CVrXDYOzqiIt9xiFl52Gdsts2r4+QOV/BPKQaiuOScG/WX4hfHaFSxmvsYPh+NgJGzg7IvX4b0RO+Q86FG6gM1A9bhxvAwlSAxHQxth0vwZNU7X27pp8eOjU0gq2FAGk5Yuw+XYqYx4p+TXSsb4hGofpszHuUVI7NUSVIz6l4bXMpah3ORUr7t6N7ENoN+BquPprbKS0xFid2zUfyY2n/btNvMuq1ebZ/52WlICriF9yPPgFRaRFsHLzQediPcPGqXrE8R9fh3EG6b6TytB9YgTw75yP5Cd03Unnqt9Usz9FtqvJ0IXm8dctz+uB6HN+znM3fLp6B6DF0Kjz8NMty7uhmXD6xAylP5283nxB07D9BXr5cVIYDW+bjztXjyEiLh7GJOaqFNUKnAZ/B0saxwnrhcNT5v7TI4fx/UFZWhrcFQ0NDODs7V/iw/CagRWabmgKcjJZg+UExUrIlGNBcCFMjzeXd7IAeDYW49lCC5ZFixCZK0KeJkC1EZdD5fJ0F2HVOjCX7xbgQK0H7cAH8XXXLUt1HiM4N9HH4igh/7ChDUqYE73U0gJmx5vK06B3QSh8X74qxcHsZbj0W4922+nCyUdQrLWp2nhFhXkQpFu0uQ1a+BO/rOKcysVf24uSO2ajXYTwGfLYNdq6B2Ll4JArzMjSWF5UWw8rOA426fg5TCweNZUhBUL3JYPT9ZBN6jF7OHiB2LhqJshLdK/ab5/cictNstOg+HqOnb4OTRyDWzh2JglzNspSVFsPawQNt+3wOcyvNspzatwQXozag0+CvMf77PWjb93Oc3rcU5w+v0SnLg+t7cW7vTwhvMx49xm+FrUsg9q/4AEX5mmVJeXwFRzd9gYC6fdDzw23wCmmDQ2s/QmbyXfa9RCLBwbUfIjczDm2H/MHKmFu7Yt/y91FWWvGTTOzVvTi1czbqthuPfhO2wd41ELuXaG8nqhtLWw807Ky9ncpKi54q7r7B83DlzD5sX/MzOvQZi89/3AxXr0Asmj0aeTmaZbkXcwG1G3fG+GnL8cnMtbCxc8bfs0YhOzPlmbLXLxzC43vXYfUcC0BSdHasp4eoa+X4e1cZkrMkGNpWX+v97+EgQN/m+rgcW46/dpUh5okEg1rpw9FadayKjRfj502l8m3z8copcdrUMUTzWob450gJ5m4qRGmZBGN6mkJfVS+kQng1ffRqZoQD50rwy4ZCJKaVY2xPU5ibKGQy1AduPy7HwYuV1N48pX19I7SqbYT1Bwvx87o8lJQCH/cz0ylPnUAD9Glpgj2ni/Hj6jzEp5WzY+gBTcaT5HKs3leImcvzsGBzAWio/7ifOfurjbb1DNGilhE2Hi7CnPX5rG7G99YtS+0AA/RqYYx9Z4vx09p8JKSJ2THKdWOgL8CtRyJEnq9Ae/OUO5f24ljELDTsNB7vToxgipxtf47QMe4VwcreHU27fw4zS839SUby4+u4fmoj66OV5eKp/di6ag669BuNyT9vhJt3IBZ8P1Zrn4qNvoi6TTthwoyl+PLHNbCxd8KC78YiO0PRp9KS4/DbtOFwcvPBpzOWYuqvW9C57ygYGBrqlCXEU4B24UIcv0lzWzmbLwe30tM6X7rbA70bC3H1vrT8nXgJ+jcTwkHpHY6NOTCsrR7S84A1R8qxeF85TkSLIVJ9ZtfI+ZMHsGnFb+g+YBSm/7oeHt7VMPfb8cjN1qxZuhN9CfWbdcSX3y3GlNkrYWvvhN9mjkNWRqp8LF446zOkpcTjo8lzMf239bBzcMGcGWNQUlxU4Rx1YNNstFSeo34biXwdc5QNzVF9tc9RJ/cuwYWoDej8ztcY/8MetO33OU7tW4pzh3TPUXpmpsi9fgc3P56JymDi7Y56OxchI+ocTtbtgYcLVqH6ou9h366pvIxLv04I/mUyYr//Ayfr90Le9dtosGcZDB1sKzx/LX999GxqiAMXSvHrpkIkZogxuruJSj9VxttZiCEdjHHuVhnmbCrEzQfleL+zMZxtFY9xrWsboHlNA6a8+X1zEUrKgDHdTXSOF0TMxb04smUWmnYdj/emRDDFyaYFI7SuJah/W9u7o2Uv7f27uCAHa34ZBKGeAfp/uAQjp+9B676TYGxa8cvKWxf24jDJ02U83p8aASeSZ752ecoqIU+RkjwDPlqCD2bsQet+k2Bspluea2f3Yfe6n9Cm1zh8/P0WuHgGYdlPo5CvZax5EHMetRp1waipKzBuxnpY2Tpj6U8fIOfp/F1aWoyER7fQuucYfPLdFgyZMB9pSQ+x8rfxFdYLh/N/p8gRi8X4+eef4e/vDyMjI3h6euKHH37QWPbYsWOoX78+K+fi4oKvvvoKIpFiIbplyxZUr14dJiYmsLOzQ9u2bVFQUCD/funSpQgODoaxsTGCgoLw559/qpz//PnzCA8PZ9/XrVsXV65cea5riY6ORteuXWFpaQkLCws0a9YM9+/fl1/nt99+C3d3dyY/WXvs37//uX//5s2b6NSpE8zNzeHk5IQhQ4YgPT29UvLR7zVt2pS5GVH9kKwy+WQWJ5MmTVI5Ji0tDQYGBjh+/DjbJ4uULl26sDr28fHB+vXr4e3trWK5ogtSgvz111/o3r07zMzM5G29Y8cO1K5dm127r68vZs6cKW9bWqTMmDGD3RtUd66urvj444/l58zKysLQoUNhY2MDU1NTVj+xsbFaZRg+fDh69uyp8tmECROYFY7se7rX5s2bx+SljdzcNLlWbd26FaGhoUwuqodff/1V5bz02Y8//oj333+f3RN0DYsXL8bLUj9AgGsPJLjxSIKMXHq7KAFVVw0fgda3kQ+SgXN3JMjIA47flCA5G6hTTVHe3V6AG48leJIG5BQCVx9IkJINuNrqVlw1DdPDhTtiXI4VIzVbgh2nRCgVAXUCNK9MGofqsQfKEzfKkZYjwaHL5UjMkKBhsKL8tQdi3E+UICuPrI0k2HtOBGNDAZyVlD3auHpsJUIb9kNI/T6wdfZHq74zmRVNzPmtGss7eVZHk+4TERDeBXr6BhrLdB+9FMH1e8POuRrs3YLQdtAsZhWSGh+tU5azkStRu3k/hDftAwdXf3QdMhMGhsa4clKzLG4+1dG+/0SENdAuS9y9Kwis1QYBNVuyhVFI3Y7wC22ChIe63zDePLkKgfX6IaBOb9g4+aNJjxnQNzTG3UvbNJaPPr0a7tWaokbzEbB29EOddp/AzjUYMWfXs+9zMx4hLe4amvSYDgf36rB28GH/l5eV4MG1PaiIa8dWIqRBPwQ/bacWfaTtdPuC9nZq3G0iquloJ6/g5mjQaQJ8q7fD8xC1ZzUate6LBi17sTf8/UZ8A0NDY5yLUn2zK2PIhz+hafuBcPMOgpObLwaMmgmJRIzYm2dVypFiZ9vKWXh3/E8Q6lXeuLZxiBCXYsW4ck+MtBxg15lylJWTFZ5Qq0XcvQQJTkWLmVXAkavlTKHaIEi1vEgM5BcrtuJK6k9ahBswhcLNByL2VnptZDGzlqvup/2aWtY2xOnoMpy7JWIWLaQEKhVJ0DBU0XbHrpbh0MVS9lb6eWhdx4gpQa7fEzElyMq9BbAyF6JWNc33BUHWL6eul+LMzVIkZ4ixIbIIpWVkFaRQApy8Xop78eXIzBUjLrUcO08WwdZSCDsr7cuwVuGkrCrGjfvSulm9vxBW5gLU9NcuC1kpnb5ZirPRZUjOFGPjoSJWN8qyRF0pxcELJXiUVDll26WjKxDWqD/CGvaBnYs/2g6Yyfr3zTOa+5OzVw206DkJQXWoP2lXhJSWFGDvqi/RbtD3lXrAk3Fk1xo0adsbjVr3hIuHHwaNmgZDI2OcPrJdY/n3JsxCi44D4OETBGc3H7w7ZgbrU7dvnJeX2bl+AUJrN0XvIZ/CwzcYDs4eqFGvJSys7HTK0jBQyCxL6UVGei6w54IYZSKglq/m+aR+gJBZ35y5LS0fdUOMpCygXjXFfdCqhhD3EiXMUic5C8jKB+4mSFBYCb1b5M51aN6uF5q26QFXD18MGTOV1c3Jwzs0lh/16Q9o3ak/PH0C4eLug+HjvmHropjr0rpJSXyCB3dvYMjoKfCpFgpnN2+8O3oKykpKcO6E6jpTnTMHns5RzfrA0c0fXYc+naNO6J6jqlcwRwU9naNs7N0RSnNUWMVzVNqB47g7/Xek7DiEyuA1aiCKHsYjZuJPyL/9AI//XIfkrQfg84nC0sNnwnuIW/YP4ldtQ37MfdwYNx3lhcXwGN6nwvO3rGWAM9FlOB8jQkqWBJuPSsewBsGaxz1S0Nx+Uo6jV8qQmiXBvnOliE8To1kNRT21qGmAyIuluPmwHEkZYqw/VMys8qr76p4fzh9agZpN+qNG4z6wd/VHx8EzYWBgjOunNbcTWeK17jMJIfW09++zkUtgaeuMLsNmMUsaa3sP+IQ0hY1DJay4SJ6m/VGjyVN53pGON9rkcSV5+krl0TfQIs+BJbCwcUbX4Qp5fCshz4l9K1G/VT/Ua9EbTm7+6PXedBgYGePCMc1rm0HjfkGjdoPg6hUMR1df9P3gO0jEYtyLls7fJqYW+OCrZajZsBMcXH3g5V8TPYZOQ8LDaGSlJ+K/gkRcNbf/Iv9pRc7kyZMxe/ZsfP3117h16xZTDJCCQp2EhAR07twZ9erVw7Vr15gyYNmyZfj+++/lCoZBgwaxB+aYmBj20N27d2822RHr1q3DN998wxQH9D09XNNvrlq1in2fn5/PFBshISG4dOkSUxx88cUXlb4Okq958+bsgf7IkSPsHCSLTBlBSgF6yJ8zZw6uX7+ODh06MGWGTOFQmd8nBULr1q2ZsufixYtMMZOSkoL+/ftXSkZSan322Wfs2MOHD0MoFKJXr15MyUS888472Lhxo7zOiE2bNjHFCSmlCFKYJCYmsvolJQYpJVJTpW+FKgtdG/3ujRs3WB2dOHGCnfeTTz5h98CiRYtYXBuZkod+Z+7cuexzqq/t27czhZ0MUrzQNe3cuRNnzpxh8tO98qLWPtRWjRo1wgcffMDuK9o8PDyeKUftRHU/cOBAdi10XXRPkezKULvLFHPjxo3D2LFjcefOHbwoZMLtbAM8TFE1xX2UKoGbneaFKX3+SK38w2TV8uQKVc1VwEzPCU8HwNZCWk4bekLA1V6Ae4mK0ZdK308UM8sbTXg6ShfAypBiR1t5+o16gXooKpGwh1NdlItKmXLFI6Cx/DOBUAj3gEZIfvTqYk2VFOWxv7oebEgWcpHyDVaVxTekEeLvv7gsHv7heBhzBhnJD9l+ctxtPLl3Gf7Vm+uUJT0xGq7+jVRkcfVrhNQnmmVJfXJNpTxBih1ZeTI/JvT0jVTOSYvGlMeXdV4DyUPuT+7q7VStEZIfv9mYYCJRGeIf3kJAWEP5ZzQ2VgtriMex1yp1jtKSYohFIpiaK+4HGlfX/TEZrboOh4uHf6XlofvdxU7A+pB6n3J30Lwc8HAQ4kGS6gqIFDtkqaOMt7MAE/sb4OOeBujakFx2KpbHzlLAXI3uPlEoW0gBRG5APs56Wq/Bw1H1GLoG2qe31i+DvZWQKW1uPxapyPMwqRw+rvpa5fF01lM5huShfV8txxgaSJU86dnlyMrVvLq0sxJIZXmiKsuj5HJ4u+ioGyc93FGThfZ9tBxTEdSfUuKi4RWo2p9oP+nR872QUufIP9/CN7QFvIIU564IUVkZnjyIQWAN1T4VVL0hHt65Xqlz0Fvx8nIRzMwt5f3p5uUTcHTxwoLvxmDi+y3x81fv4Or5IxXOly62z85jNH/SywtN0Ofq8+uDJNXy/q4CZOZJMLilEJ/10sP77fQQ6CaoVN08vh+D4JoNlGQUIqRGA9yvZN2UqNWNSCTVyBooPSDTOemBOTZG+3gqks1RIY1VjnsVc9SDmDNIl81RT27jSexlVNMxR70I1g1rIf3IGZXP0g6ehE3DWux/gYEBrGqHIv3waUUBiQTpR07DumG4znNTP3WnMSxOdQyLjS+Hl5Zxz9tZT6U8cecJlRfKx1JLGkvj1MbSFLHOcZH6N7kkeautJWg/4cGL9+/Ya0fg7BmGiMUfY/6XjbD8h564euKfCo+TyeOjLk/QS8pz/QhcvMIQsehjzPuiEZZ/X7E8dA8nPLyFaqGqY41/aCM8uVe5e7isRNqflOdvdYqL8tiLXBNTJTN2Duf/PUZOXl4ee2heuHAhhg2T+tj6+fkxqxGygFCGrGfoYZrKUmciixpSKJAFCSlo6GGblCakvPHy8mLHKD/sT58+nT1Q0/cEWZPIlAb026RAooUCKYfIKoSsLOLj49lDd2X4448/WOwUUoSQBQsREBAg/54UOCQrPfQTP/30E44ePcosWejYyvw+XTspcUgJJWP58uWsXu7evavye5ro00f1DQQd6+DgwOohLCyMKSXIMuXkyZNyxQ3JRQoyqvPbt2/j0KFDuHDhAlNMyKycqlWrhudh8ODBeO+99+T7pMwh6yrZPUAWOd999x0mTpzI2u3JkyfMpYksrKhuyaqFLLMIUuyQAufUqVPMokimtKM6IYVPv3798LxQO5IbFVn30O9q47fffkObNm2Y8oag+qe6/OWXX5hySQYplUiBQ9A9QEopavvAwMqbqStjakgTleCZN38FxYCdheZjKI4Ofa9enj6XcfCKBJ3qAh9100O5WELrHey7KEGcDoMvU2Na8AiQX6S66KV9By1vsUlR9Ez5YomKiwMR6CHEwFb6LHZPXiGwfH9ZhW87iwqyIBGXw8RC9Q2tqYU9slOli8qXhd7cnNjxI1x8asPORXufK8yTymJmqSqLmaU90pNeXJamnUahpKgAC6d1hlCox+IRtO41ATUadtN6THFhtrRezFVlof2cNM2yUBwdE3N7lc+Mze1YPBuCLHDMrF1w8cBcNOk1A/oGJrh5ahUKcpJRmJem8xqKn7aTqbo8FvbIekXtVFkKcrNYHaq/1af91MTKybJ7/W+wtHFAQJhC8XVk5zII9fTQvOO7zyUPuXtQn9LUX5VdO57pU2rlqU+Zmyj6IMXLufVExKzcSEHbtrY+hrQVYMleEevr2rAwk/bLvELVQrQv+04dMxMBu4a8QvEzxzjavpiyQga9vSZyC9TOXSCWf6eO+VN5ctXkoX0nW9UlFrmQ9WphwiwAkzPKMW9zAYvTpVEWU6HmuqmELOrH5BZK4KTkgvE8yMY9U7WxxtTCDpkpD/Ci3L60Bylxt/DOl1ue67j8PGmfslTvU9Z2SEmoXJ+KWPs7rGwcEPRUGZSXk4mS4kJEbl+ObgM/RM93J+DW1VNY8stn+GTGUgSEStckmvoTzZfUH9T7k72FoNLzJR1P9zVBLo5GBgJmOUex5sgqx89FgH7NhFh9uJxZtWojLy/7ad2ouvZYWtsiKUF13asNioVjbeOAkKfKILLAsXVwxta1CzF07FQYGZkgctc6ZGWkICcrrcI5yvxVz1Gdn85RUxVzVJveE1CjkfY56kUwcrJHSYrqAoX2DawsIDQ2goGNFYT6+ihJVXWxKUnJgFmg7vh28jFMba3CxjBrzf2U1jDPjpNiWJpKxxjZGidfrUx+ofiZ9Y8yhfla1hIWdshIfvH+nZ0ehyvHN6B+2/fQqOMYJD++gUP/fM8srao36lWhPDS+qMhj+ZLypMXh8rGn8nQag6RHN3Bw0/cQ6hughhZ5Cp/2J3Mr+2fm77Skysmyd+OvLPYNKX80UVZagn0bf0PNRp1hbGr+AlfG+X/nP6vIIcuYkpIS9jBcmbJkJaEcn6RJkybMkoUUHjVr1mTnIeUNWbu0b98effv2Ze42ZIlCLkQjRoxgVhYySPEjC1xL569RowZTosig36sslFmKlB8yJY4yubm5TOlE8ipD+2RdVNnfp7KkACC3KnXo+ipS5JDSg5Re586dY+5YMkscUpSQIoeUOlRvpAiha3n48CGzcCFlF0FWJPr6+swFSga5xFEdPw8yJZDydZEiRtmlrry8HMXFxSgsLGTKGFJ4kYKnY8eOTDHSrVs3JgvVG/1t0EDxdovcxkhJQt+9Tuj8PXr0eKZNSVaSX09P+sBC7SqD7l9SDmmzYqL+QJsyojJ96BtU4tX5S0JuVuRGtflEOXOt8nQQoH1tqZLm0fMZXb0SyMJgQUQpzIwFzCJnUGsD/LWz9JkF9pvm2LZvkZkUiz4fSV2M3jTRF/bhxtld6PPBHDi4+bO3nQc2/igPKPmmID/2tu8swIlt07D2u4YQCPWYhY97gFQJ/P/CoR1LWYyd8V+vgIGhtJ/GPYjG8f1rWbydqhBTi7j5SKGNoODoKVll+LSPIXycyO1S8WBBwYcHtFbMQ4t26o6x8bqpF2yAwe1N5ft/bs1/rb93/lYpYh6JmHsUBUb+oJspflmfz2Kf1A0ywKC2T00WAfy1XeG6/V8jLysJUVt/QJ/xy9/I/KPMgYhluHRqPybMWCbvU+RmRdSo1wptukkDhpMb1oM713AycrNWRc7rQNal78ZLmLsyQXF3POwlqFNNiCdpr88/YO/WFSzGzsTvFsvrRl/fAOMnzcHKhd/i4yEtmfIkpGZ9VK/dRMXC+o3PUaPmMHctmqP2b3jzcxRHN3RvkAVMi56fsX1nzxAWlPjK8Y06FTmvW56WvdTkObZRqyLnZTm6cwmund2L0VNXyfuTMmR5vG7BZ0y2XsOn47/EvzE2/L/yn1XkUJyVVwU9NB88eBCnT59GZGQkFixYgKlTpzKlBVlWEEuWLFF54JcdV9WuRRuktCIFBlnzqEMxgyqCjiVrJaoHcpciRQ4pcEpLFYESyL2K4s9Q/ZE1DinGlC2bXgUUG0f9uigmjsxaShlSbJF1DSmRyBqI2pisW8jqheLYvAhkdqk+gL3OoMvqyj16sJMp0dSZNWsWqwtlWvf9Gm37KSaQwlIyM5c8E6iR3hKqv5WXQZ+rB0pVLk+B9lqGCbD1tBj3k6SfUfwaR2ugQaAQj7RkaSgsBrPekQb/U9Qp7au/yZLLUiT9Xhlz42ffZFEMA8oWQubrcWkifNbXAHUD9HDsuvZ4GiZmNkyhUKQW4JOsSMgq52U5tvVbPLoVhd7j18LcWru1FmFqIZVFPfhfQW76M2+PnoeDm39Bk84fsDg6hJN7IMsecnLvYq2LZGNTa2m9qAU2pn2ygtEEWeOQVY4yxfkZKvVo7xaKXh9FoLQ4jy14TMxtsfPPAexzXRg/badCdXmonSxfvp2eBzNLG/bgox6ElfYtrXXLcnT3ChzeuQxjpyxhAZJlPLh9Gfm5mfj2I0WsHnpruGPtLzi2bw2+WRCp9ZxkdUZ9SlN/zdOiU2F9Sq089Sl1yzdlKKZHQbEEtpaqihyKg/M4WaGg0NeT9lV6Y0xWIzJon+LTaKKgSMKuwYJZrIhV31irWdJUxPV7ZXiUlKckj/QvuSjkFijGAgszIctEpYn8p/JILWgUZWg/t0C1jsjVobhUjLRs4GFiAX79yIrF3rl4uww37pcxtyl1WVjdKJ2nMrKov4GnzF7qslQW2bhXqDbWUKBjsq54EVKeRLPj1/6smJfpLXz8/QssO9Ync2+wfqMJcwtpn8pV71PZFfepgztWITJiBT7+ZhHcvQNUz6mnDxd3VUsKiqdz//ZVnf2J5kvqD8pzlHT+k1R6vqTjC4pU+2harurxFE9H3Z1RHQsL66d1oxrYmAIdW1nrjvVDWa72bluBL2b+zTJdKePtF4IZczeisIDGYhEsrGzw/cSh8PYLrnCOyn/Vc9Q/v6Bp5w9YHB3ZHJWdkYgTe7TPUS8CWd+QVY4ytF+WkwdxcQlK07OYy6uRo2q9GjnZoSRZd2xJ+RimtlZRHwefsVJU69c0BsrKy9Y45mrnMDcVIjFd+7rG1FzLWuIl+jf7XSsH2Ln4qXxm5+yLO5cP6DxOJo96IHWS72XuG5LHXk0eexdf3LmiXR7Tp/2JsqOpz98WFchybM9yRO1eyuLhUKYrbUocunc/mLyCW+NwXpj/bIwccskhBQjFa6kIClIsi38ig6w4KIAsBRCWPSCTRQQ9CFM8EnKPiYiIYDF3SHHx4MEDZkGivJGLlez8FLuGrEBknD2rGrhSF2R1QbFeNCkEKPgx/T7JqwztU0ycyv4+WcJQQGUKoKt+HerKEXUyMjKYMmTatGnMcol+j4IEq0MWJiQDxd8hRQ4pdmSQlQtZMSkHYb53757G8zwPdF0km/o10UZKF4LuE1JEzZ8/n8XnoXuB4tLQdZBMpLBTv1ZZ3apDlkfkiqduUaUM3TtkVaML+m1NbUqWUS+qIKSYUTk5OSpby55fqZQhHRAFV/R2Ul0weDkKkJCheYFBn3uplafjZeWFAlJqCp5xsaB9XQYF5HKQmC6Bv4timKLifq5CPEnVLAul7vRzVT2pv5v28vLzCgQVZnag+CyO7qGIiz2j4goVH3sWzt5Sv/kXgcYdUuI8uHEIPceuhKWddMypSBZXr1AWK0BZlgcxZ+Hu9+KyUPYHgUB1WiD/dNkba22y2LuGIuneWRVZEu+fhaOnZlkcPWuy75VJuHdaY3lDYwumxMlJf4T0hJvwDNFtZUnyOLiFIkG9ne6dhbPXi9fNi0Bvsyl9+N2bijGEFK2x0efgVa2m1uMO71yOyG2LMPqrv+Hpp5o2uG6zbvjyp234YvYW+UZZq1p1ew9jJkstHHX1qaQMCXzV+hTtU+BMTcSliVXKE9TH4tK09ylLU7AYOeoKV8qiQlnjZBsF480pECPAQ9H5jAzB4kQ8VFJqqF9DXKrqMXQNtP8o+fkUOSQPpfKWbRQgNCdfjEBPxTsuY0Ow+DIPE0Va5aGMVIFe+iry0D6lLtcGjX20yZRZrG6yxfItWYssFCtDWwBnVjcp5SrHsLrx1Gdxfl4E6k9OHqF4cle1P9G+i7fuWCDa8AxsiKGTd2HIpO3yzckzDMF1u7H/tSlxCH1ygfYNxp0bqn2K9n0CNacEJiK3r8C+rYvx4bQ/4eUf+sw5vfxCkZKo6n6UmvRYZ+pxmi+TMqXxoZQhSzSKC6cJ+py+VynvrChP50zMIFdm1TLksphTgTJOeh3B8kDF0vOJEXPjPPx01M2+iJXYvXkpPv1mIbz9Na9tCFMzC6bEoQDIj+7fQq0GLbXL8nSOophryrK8kjnq6dpN9QXaq7VUyj57FXatFbFRCPs2jZF1Vrqek5SVIedyNOxbK1m3CwSwa9UI2Wd1x3KhfhqvYQyr5q7H4oNpgpS8Ae6q/YKOf/x0zMvIlTCXUOUyRgaAl5NQ57hI/dvZMxSPbqv278e3z8DN98X6N+HuVxuZKaoudJkpj2Bl56bzOLk8Ma9engxN8ti66byHKX24LFCx7B6mfU9/7fdw1O5lOLz9b7w/cTHcfVXnb2UlTnrKY4z8ahnMLKxf+Lo4nP+sIoesLShmCMVCWb16NXMPIuUFxYlRh6ww4uLi8NFHH7FYLZTliOKnUPBemiDoQZ5ix1DQW3IV2rZtG8u4RA/bBCl3yNqBFAEUT4aUACtWrGBxTmRxW+hBkVyvKM7J3r17WVybyvLhhx8yFyqKgUMykBvTmjVr5EFtv/zyS2ZJQ8GD6TOKCUPKAwrwW9nfHz9+PDIzM1nMGopTQ/V14MABFm+mIqUDuT+RyxEFJyblCwVkprpThxRClNGJ4r6Q6xD9lgyKS0RxakaNGsUybJFCh/4nJcvLuA+Quxe1P7URKarodynWECmdCAoeTPcEZewiZdzatWvZb5J1ESkDSflE9UaxfchN691334Wbm9szbk8yKGA0tRH9JrUT3Ud0bmVIWUb3FMVqUnZDU+bzzz9nSkiK50P3FAXOpjhGzxMkWx0Klk2KP+VNk1n7+bsSlnGjupeAxcXpWEfAYslcfyhdRHatL0CL6oo2uRgrga+zNNsVLTabhgrgYgNcipWWpyxTj1MlaF1TyIIcW5kB1b0FCPMS4E6C7oXpyZvlqBsoRLg/pWcVoEcTfZZW+PJd6T1JaZHb11UsXE5H02JHyLJdUfk24XpwsxfgbIy0PF1H+zp67M2mtTngaidA72b67MHzxsOKF4K1WgzHrbObEXMhApkp9xG1ZQZLxUlZp4iD6yfh9O5f1QLvxrCtvLwMBTkp7P/stMfyMqTEuXNpF9q/OwcGRmYoyE1jG6Uu10XD9sNx+fhmXD0VgbTE+9i9dgbKSopQq4lUloilk3Boq6osyU9i2EYLidysFPZ/ZopCloCarXBiz9+4ey0K2enxiLl8kGXHCgrXnakprOkw3Lm4GbGXtyM79T5O7ZjJ6iWgtvQN6bHNk3DhgHQ8JEIbD0X83ZO4cWIFslMf4PKhhUhPiEZww8HyMg9v7EfSg/MsBfnjW4exf/kIlqbcvZqqG6kmalI7nduM20/b6dg2aTsF1ZPWzaENk3Bmr2rdpCfEsE3WTvR/TrqibspKCuRliLzMePY/ZRjTRcsuQ3H26BacP7YDKQn3sWX5dygtKUKDFtLsduv+nIzdG+bKy5MVzr7NCzBw9HewdXBDbnY62yiGB0GLPhePaiobWRNYWtnD0VX68kAXp2+JUSdAiFp+QthbgQUmZn3qnvT+791UD21rK/rU2Rgx/N2kMTvsLYFWNfVYvzl3W1re8GmfomCt1maAr7MAg1vrIzNXGhS5Io5dKWMpv8N89OBiJ8S77Y3ZAytlapIxvreJSnaWqMulaBRmgHrB+nCyEaJfayMYGghYal4Z9PbazV4I+6cxJ1zsaSwQak0LLePIpRJ0bmSEGn76cLUXYlhnM6ZQuRqrOPcn/c3QIlwR/PXwxRI0rWHIsmZROuBB7U3YQxRlsZIFUe7QwAieTnqwsRDA11UPH3Q3Y1lqoh9qt9g8eqUEHRsYs6wzJMuQjqbIyZfg2j3FMR/1NWOxdxTyl6JxdUM0CDFgcXEGtDVmMVfORpeq1o2Dom5cqW4chDBlliXPUqfVe7hx+h9En4tARvJ9HPpHOtaENpT2p32rJ+LETtX+lBofwzb6Py8nhf2f9XTcMzQ2h71rgMpmYGgKYzNr9n9FtO42BKcObcPZqJ1Iin+AjUu+R0lJERq1kvaplfOnYvu6efLykRHLsXvjHxgybiZsHVyRk5XOtuIiaZ8i2vUYhkunD+Dkwa1ITXqCqH0bcOPicTTvoDvhw9k7YtT2E7CsjtQ/OtcTsnmGslgRPRoK2dwn4/xdacybhkHS+bV5mBCutsCFWMX8c+a2GKGeAoT7CVgqcsoMGeAmwEWlMtpo3/0dHD8YgVNHdiEx7gHWLvqRpQlv0qY7+37pvK+xdc0Cefm921Zi+/q/MPzD6bB31Fw3F04dxO2bF5GWHI8r56Lw64yxCK/fEmG1dIcIaNRhOC4dU8xRe9ZI75vwptL7ZtuSSTi05VeV4LJJT2LYRnNUXnYK+z9DeY6q1QrHd0vnqCyaoy4dZNmxgmu3qzD9uGXNILYRpj7u7H9jD6miLvD7z1BzhcIi/fHijTD18UDQrC9ZzBuvMYNZuvGH8xQJJx7+vgIeI/rDbUhPmAf5IuyPGdA3M0HcKs0ZjZSJulqGhiEGqBekD0cbAfq2NIKhvgDnYqTj3uC2RujSSNGvj18rQ5CnHst25WgtQIf6hizo+4nrirHg2LUytKtriFBv6Vj6TjtjZol344Hu7HQUN+bayX9w40wE0pPu48CGGSgtLUKNxtJ22rViIqIiVPt3SlwM28Tlpayd6P+sVEU71WszDIkPruH0vr/Z59Hnd7HfqN1CMcfrkufqyX9w/ak8+9fPYAq8yshD/+c/lSdTWZ62T+XZ+zf7nOShYMe1W+qWp1mn4TgftQWXjm9n83fEipnsHq7bQrq22fT3V9i3SbG2idq1FJFb5qPfB9/D1t4VedlpbCspllqi0n29dv4ExD+MxsCxPzNLRFkZWWDx/wL0WFMVt/8i/1nXKoIUBhTjhB7mKY4MuQiNGTPmmXL0YE7KDVKIUDwcW1tbFvNG9rBPD7yUIpvik5BChR7yKbgxpaImRo4cyVysyCWHzkEKC3IZouC+BMWd2bVrF/ttCihM1hykeFEPEKwNUpKQcoTO3aJFC2aRQSnGZXFxyF2JrCvo4Z/io9D5KUivLFBwZX5fZtVDyi+KZUOxVOg6KW6MzHJFG/Q9KUdIDnKnIusaUmrJUm4rQ1Y4FIeGsnBRYGFlSPlB9U7fUawXUo6R8kU5ts/zQjGNdu/ezdKz0zWTKxIpjajNCEqXTpnNSPFECitqN6orqnOCFHKkEKOsX+QmRrLRvaIpXpHs9+i+IwUiWR9RsGXKmkXKPRmkjKHgy9QORUVFLF6QJkuif/75h927pMyhe5euQTnQ8esiJk7qWtUsTMBiyFDMi3+Oi+XBgMlMX9l6LSED2HlWzBakpOAht4qtp8TMFFzGjrNitKwuQPcGQvZWObcQOHZTwtK26oKUK2bGIrStow8LE6k1wYoDZXK3LWtzVUsfsrzZdFSEdnX0mIKH3lKtPSRN70lQWQdrAcKrGTDzdnLfik8XY/GeMpaKvCKqhXdGUX4mzu9fwJQtDm7B6DZqidwliB7qlRWPBbmp2PSrwtz7StRytrn61UPv8WvYZzdPb2B/I/4cqvJbbQb+KFcQaSKsfmcU5mUiavsC5OemwdkjGO98ukRufpyTqSpLXnYqFs1UyHLmwHK2eQXWw/CJUlk6DZ6Go9vnY+/ab5lpNcUdqNNiAFp0lwbU1oZvjc4syPClQ/OZC5OdSzA6vLdY7lqVn52kYunj5BWOVgN+waWD83Axci4s7bzQ9t0FsHVWPMRRUONze3+Su2hVC++BWq0qFyC+Wq3OKKZ2OrCAncfeNRhdRyraKV9DO/0zV1E3V48tZ5urbz30HCetm9S4m9jxtzRoOnFq52z2N7BuT7QZKP1fE+GNOiE/Nwv7tyxkChk3ryBmaWPx1A0kK121bk4d3MQWeyt//1TlPB36jEXHvuPxKuLZUCDx1rX0YG6ih+RMCdYcEsnjQ1Hqb+X+TZY3W46L0CZcnyl4qE9tOCqS9xexhDLdCVDLT5/1bXLRoixYh6+ItAbyVebwpVKWxWlAG2OYGAnwILEcf28vZHFjZFCKblkwWOJKrAjmJiXo3NCIjUfUh+kYZRfKJtUN0KmhQmvzST+pG/S6yCKW8lcblAqdlEKDO5jC1EiA+wkiLNhSoCKPgzXVneKDS3fKYG5ahK5NTFggYnJ9omNk8pSJJPB312epzUlZQg9X9+JFmLMu/xm3T2UOXShlSphB7UxY3dxPKMef21RlISWRsjvp5bskiwBdGhs/dVErxx/bFLIQzWoaonMjxbz66QCpWf+a/YUqyjAZgXU6ozA/E6f3zGf9ica93uOWyl0vKOaN8j2cn5OKtT/1VNTP4eVsc/evj/6fSPvTy1C3SUfWp3Zv/JP1KXfvQHw49U9YPnUfykpPVlm3HI/czDLILZnzucp5Ovcbg64DpGNKrQZtMOiDaTgQsRybV/wEJ1dvfPDFr/APVsTt08StJzRfitGiupC5IKZkAeujyuX9SX2+jE8HIk6LWYrxVjWkLr7/nBAjLUdxzjvxEuy5KEaTECE61AYy8oDNJ8U6kwPIqN+0A/Jys7B941/IzcqAh08gs7SRuVZlpiWrtFXUfmnd/PXzlyrn6T5gFHoMlK6XSbGzacVvzJ3NysYejVt2Rbd+ipiQuuaogrxMHKU5Kkc6R72rPkeRya7yHDVDMQ6f3r+cbTRHvTdJet90HjwNRyLmYw/NUblP56iWFc9RVnXC0Oiw4t4LmTOF/Y1bvQ3XR0yGkYsDTJ4qdYiiR/G40H00Qn6dDO+PhqI4Phk3Rk9D+sGT8jJJm/fB0MEWAdM/hpGzA3KvxeB815EoVQuArImr92gME6BjfUM2ZpAr6aJdRXKXVRsLVSsjsqpZE1nMxjxS8JAF4fK9xcyqUcaRy2VMGdS/lREbL8gKj86pPF5oIriudC1xYtd8tq5xdA/GgI8U/Ts3U7V/Uzut+EHRv88fXM42j2r18c7na+QpynuPWYhj23/DqT1/wNreHW36TUFoA6lCURch9aTjzYmdCnn6f6xbHspCJePcweVs8wxQyEMpynuPXYhjEb/h5FN52vafgrAK5KE04QW5mYjcugB5Oelw9QrC+xMXyV2rstXm77OHN8qVNcq07TUO7fp8iJysVNy6fJR9Nm+q6vpu1JSV8AuRJlvhcCqLQMIjEnGqKBRommLYUPyaygSt5jw/s/55MXP710Venu43R28SF2fF27CqgJ327JVvnHi19Ln/NkaGVSPoL1HNrercw2dvVK12ysmuIDXcG6S0tGqNfeR+WlWoHlaFBhtyj3X5l6PQK3H6ZtV5/9mqZtXpT0RcliJw+L+NZUup5U1V4dDcS6gq1AitWvFYqkjMfoa1WdWZF3rWezVxVv8Npq9+fbFBX4aZQzW/hH+bqTozEuf/HrI6ouDEZBVDcWbIqoXckMgKhsPhcDgcDofD4XA4VRduI/Lm+M/GyHmbIJcncn/StGlyBXvTUFwgbfLRRt+/CiiY85QpUxAaGopevXqxwMEUfJjcmChtubbfp/IcDofD4XA4HA6Hw+H8P8AtcqoAFPtEWxBbis/zb0Pxc9QzL6l//yqg+DK0aaJ79+7PpHeXoS1eDYfD4XA4HA6Hw+FwOP81uCKnCuDo6Mi2qgoFjKZ03f8mlAqeNg6Hw+FwOBwOh8PhVD0oCQLnzcBdqzgcDofD4XA4HA6Hw+Fw3hK4IofD4XA4HA6Hw+FwOBwO5y2Bu1ZxOBwOh8PhcDgcDofDeSkk3LfqjcEtcjgcDofD4XA4HA6Hw+Fw3hK4IofD4XA4HA6Hw+FwOBwO5y2Bu1ZxOBwOh8PhcDgcDofDeSkk3LPqjcEtcjgcDofD4XA4HA6Hw+Fw3hK4IofD4XA4HA6Hw+FwOBwO5y2Bu1ZxOBwOh8PhcDgcDofDeSnEPGvVG4Mrcjic/2NMTaqWUV52thhVBXHVEYVRKhKgqmBqgipFaRmqDCJx1elTIpEIVYnsjAJUFfQN9FCVyM3MR1VhXPeq005EWok1qgo1q1WdcbhYVLWW8DH3qs5AnDf3EqoSbT+tg6pCxqE7qEo8Tqw685RXWNW5h4EqttDiVEmqzoqTw+FwOBwOh8PhcDgcDoejk6qlzudwOBwOh8PhcDgcDofz1iHhaaveGNwih8PhcDgcDofD4XA4HA7nLYErcjgcDofD4XA4HA6Hw+Fw3hK4axWHw+FwOBwOh8PhcDicl0JSxZKF/JfhFjkcDofD4XA4HA6Hw+FwOG8JXJHD4XA4HA6Hw+FwOBwOh/OWwF2rOBwOh8PhcDgcDofD4bwUYp616o3BLXI4HA6Hw+FwOBwOh8PhcN4SuCKHw+FwOBwOh8PhcDgcDuctgbtWcTgcDofD4XA4HA6Hw3kpJNy16o3BLXJeMS1btsSECRP+VRmGDx+Onj17/qsy/D/w6NEjCAQCXL169aXPRefZvn37K5GLw+FwOBwOh8PhcDj/XbhFzluuSPDx8cGVK1dQq1Yt+efz5s3j2tAqyowZM5jCRl35k5SUBBsbG1QVbpxah6tRy1CYlw47lyA06zUNTp41NJbNTI7F+QPzkRYfjbysRDTpPhk1mw9TKZN4/wKuRC1DWkI0CnPT0HH4QviGta2ULI1C9NC8pj4sTARIypRgx6lSxKdpv7+r+wjRvp4BbMwFSM+VYN+5MtyJE7PvhAKgQz19BHrqwc5CgOJSIDahHPvOlyGv8O2qF+LS0XU4d3AZ8nPS4OgehPYDv4arj2Z50hJjcWLnfCQ/iUZORgLa9JuM+m2HP1MuLysFR7f9gvvRJyAqLYKNgxe6DPsRLt7Vdcpy/eQ6XD4irRt71yA07z0Nzl6aZclIisW5/fORGietm2Y9J6NWC9W6uXhoEe5fP4is1AfQNzCGs3c4mnT7HDaOvpWqm5un1+HasWUoetpWTXpMg6OOtroYOZ+1Q35WIhp1m4wazYa91DmVORW5Hsf2LEdeTjpcPAPRc9hUePppPu7ckc24dHIHkuPusX03nxB0GjBBXr5cVIb9m+fj9tXjyEiLh4mJOfzDGqHzwM9gZeNYqbppGCxEs+r6MDcBkjMl2HVGhPh07X0qzFuIdnX0YG0uQEauBPsvlONuvLRPEW3C9VDDVwgrMwHKxUBCugSRl0Q6+6kyvVqbo2UdE5gaCxH7pBSrduUiJbNc5zFt6puiUxMzWJkLEZdShrV78vAgoUyljJ+HAfq2MYefuwHEYuBJsgi/rM5EmUi3PD1amKJ5uDGT515cGdbsy0dqBfK0qmuMjo1Mn8ojwvr9+XiYqPihL4dYIcjbUOWYqEtFWLM3X+d5B3S0RptGFjAzFuL2oxIs2ZyO5HTtFxDsa4zura3g624IWyt9/LwsBRduFr70effujsD2rZuQnZUJbx8/jBzzMQICgzWWPXPqOLb+sw5JSQkoF5XDxdUNPXr3R8vW7VXKxT15jDUrFiP65jWUl5fDw9MLE6fMhIOjEyri6L5NiNy+CjnZGXD3DsCgkZPgUy1MY9kTB7fhTNRuJD6R9ilPv2D0eucjlfLFRYXYtnY+rp47ioL8HNg7uqJ1l0Fo0aHfW9e/j+3fiEM7VyI3Ox1uXgHo//5keFfTPH6fOrQF547tQuJTeTx9Q9B90MfPlE+Of4Dta+ci9tYliMUiOLv74YPPf4Otg4tOWeoHCtEkTI+NNSmZEuw5X87GB22EegnQOlwf1uZAZi6NI+WITVCU79VED+H+eirHxCaIseZQBZ36KU2qG6B1uAEsTAVITBdj2/ESPElVjGXq1PTTQ6eGRrC1ECAtR4zdp0sR81h1LOhY3xCNQvVhbCTAo6RybI4qQXqO7rHPtmld+H4+Ala1w2Ds6oiLfcYhZedh3cc0r4+QOV/BPKQaiuOScG/WX4hfHaFSxmvsYPh+NgJGzg7IvX4b0RO+Q86FGxXWy8Wj63A2UrqWcKK1xKCv4aZjLXFsh2It0a7/s2uJhZNbs+/UqdNyMDoOnl6hPHWrCdAoSCi9b7KA/ZfKkZipvXywhwAtawhhbQZk5gGHr4pxL0m1DewtgTY1hfB0FEAoBNJzgM0ny5Fbwdovat9GRO5chVwaa7wCMGAEjTWa+9OJg1tx7thulf7UY/CHKuXH9FU8rynTe8gEtO/x7JqMw9EFt8j5D2JlZQVra2v8P1NaWoq3CWdnZxgZGaEqEHt1L07tnI267caj34RtsHcNxO4lI1GYl6GxfFlpMSxtPdCw8+cwtXDQUqZI+nDf65vnkqWGrx66NjLA4UsizN9WgqQMMUZ0NoKZsebyXk5CDGpjiAu3y1n5W4/KMbS9IZxsBOx7Q33AzV6II5dFmLetBGsOlsDBWojhHYzeqnohbl3Yi8NbZqFpl/F4f2oEW3xtmj8CBbna5CmCtb07Wvb6HGaWmuUpKsjBml8GQahngAEfLcEHM/agdb9JMDaz0inL3St7cWL7bNTvMB4DP5fWzc5F2utGVFYMSzsPNO6qvW4S7l9AjaaD0e+TTegxZjnE5SLs+Hskykoq1rjdu7oXZ3bNRp2249Hnk22wdQnEnmUjUZSvXR4LWw806KRdnuc9p4yrZ/Zh17qf0K73OEz4fgtcPYOwdPYo5OdoPu5+zHnUatQFo6euwIcz18PazhlLZn+AnMwU9n1paTESHt1C215j2PmGTpiPtKSHWPnreFQGUnR2bqCPw1dE+GNHGVOOvtfRQGufokXvgFb6uHhXjIXby3DrsRjvttWX9ymCHlp2nhFhXkQpFu0uQ1a+BO/rOKcynZuaoV0DU6zclYtvF2egpFSCL4bawEDHa6b6YcYY1NECO6LyMf3vdMQli9gxFmZCFSXOF0NscPN+KWYuysSMRRk4dK4QFb3j6NTYBG3rmzAFyw/Ls1BSJsFng62gr/rsqEK9ECMMaGeOnccLMHNJFlPkfDrYij0sKnPschE+/S1dvm0+VKBTlh6trdCpuSUWb87A5N8TUVIixrQxzjDQVz2vMkaGAjxOKMWyrRmv7Lwnjx/BiiV/YcDgYfh1/mKmyPn264nIzs7SWN7CwhJ9B7yL2XP+wNw/lqJ1u45YMPcnXLl0Xl6GlDxTJn4MNw8PfDd7LivXb+AQGBiqKrs0ceHkAWxe8Su69h+NaXPWw8M7APO+HYfcbM1PenduXkT9ph3x+bdLMGnWKtjaOeP3mWORlZEqL7N55a+IvnIaIyb8gJnzt6FN13ewYclPuHo+6q3q35dO7ce2Vb+gc78x+OqnTXD3CsTCH8YgT4s8d6Mvom7TTvhk+jJ88cNa2Ng5Y+H3Y5CdIZWHSEuOw29fD4OTmw8mzFyGKXO2olOfURW2FSmAO9bTQ9S1cvy9qwzJWRIMbauvdVzwcBCgb3N9XI4tx1+7yhDzRIJBrfThaK16X8bGi/HzplL5tvl45ZQ4tfz10bOpIQ5cKMWvmwqRmCHG6O4mMDfRfN97OwsxpIMxzt0qw5xNhbj5oBzvdzaGs61inGld2wDNaxow5c3vm4tQUgaM6W6ic7wg9MxMkXv9Dm5+PLNSspt4u6PezkXIiDqHk3V74OGCVai+6HvYt2sqL+PSrxOCf5mM2O//wMn6vZB3/TYa7FkGQwfbCtcShzbPQrOu4zFiWgQcPYKwcZ7utYSNgzta6VhLvDdlCz755aR8GzxhBfs8uE7HCq81xFOAduFCHL8pxpL95UjJlmBwKz2YalmmudsDvRsLcfW+tPydeAn6NxPCQWnZYmMODGurh/Q8YM2RcizeV44T0WKIdOvncfHUAWxZ9Su69huNKT9vYErjBd+PQ25Opo7+1BGfzliCiT+uho29E+Z/R2ONoj/9tOSQyjZ03AxmlR/esPIv8ao6YrGkSm4vwh9//AFvb28YGxujQYMGOH9eMY9pYvPmzQgKCmLlq1evjr179+J1whU5r5GsrCwMHTqUWVqYmpqiU6dOiI2NVSlz6tQp5o5F31O5Dh06sOOI/fv3o2nTpkwpY2dnh65du+L+/fvyY8kahwgPD2eDAJ1Hk2tVSUkJPv74Yzg6OrIbi8554cIF+fdRUVHs+MOHD6Nu3bpMlsaNG+POnTuVuk6SqUePHnBycoK5uTnq1auHQ4cOyb+fMmUKu/nVqVmzJr799lv2v0gkYjLKrnXSpEkYNmxYpV3E6No//PBD5tZmb2/P6pG4efMmq3eSi+QbMmQI0tPT5cdt2bKFdTQTExP2u23btkVBgXRxLRaLmXzu7u5MyUJWT9Qm2li5cuUzCjSyvqG6lX0/c+ZMXLt2jX1GG32mybXqxo0baN26tVyuUaNGIT9f8eZW1sZz5syBi4sLKzN+/HiUlam+kX4Rrh1biZAG/RBcvw9snf3Ros9MZhFx+8JWjeWdPKujcbeJqBbeBXr6BhrLeAU3R4NOE+Bbvd1zydKshj7O3y7HxbvlSM2WIOJEGXubXi9Q81Mevfm7GyfG8esiVj7yogiJ6RI0DpWWLy4Dlu4txfUH5ezh80mq1MLH3YHe5Ajemnohzh9agZpN+6NGkz6wd/VHx3dmQt/QGNdPa5bH1bsGWvedhJB6XaBvoHkBfvbAEljYOKPr8FnMssfa3gO+IU1h4+CpU5arUSsR2qgfQhpI66ZVP6kst85pr5um3ScioLb2uukxeimC6/eGnUs1OLgFod3gWcx6JzU+usK6uXFiJYIb9ENQvT6wcfJH896628rRozoadZ0I/1pdINQiz/OeU8bxfSvRoFU/1GvRG07u/uj9/nQYGBnj/LFtGssPHv8LGrcbBDfvYDi6+qLfB99BIhYjNvos+97E1AKjJi9DzYad4OjqA69qNdFr2DTEP4xGVnpihXXTNEwPF+6IcTlWzPrIjlMilIqAOgGanzwah+qxB6cTN8qRliPBocvlSMyQoGGwovy1B2LcT5QgKw/snHvPiWBsKICzkrJHGx0amWLX8XxcuV3CFCCLt+XA2kIPtYO0a4E6NjbFsUuFOHGlCIlp5UwJVFomQfPaJop67GiBg2cLsedEARLSREjOKMf56OIKF+6kxNl9ohBX75YiPrUcy3bkwdpCiNpB2pW97Rua4PiVYpy6VoKk9HKs2ZPP5GlaS/Ua6LPcAsVWXKp7YdmlhSW2Rmbj4s1CPEkqw8L1abCx1EO96qZaj7l6uwgb92Xh/I3CV3benRGb0a5jF7Rp1wkent4Y8+FnMDI2xuHIfRrLh9WohYaNmzELGxcXN3Tr0Zcpf2Ju3ZSXWb96GerUbYBh74+Br181Vq5+wyawtq7YMvXgrrVo2q43mrTpAVcPP7wzeioMjYxx6ohm9+SRn/6Ilp36w8MnEC7uPhg67htmtXz7+jl5mfu3r6FRy64IDKvLrHGat+/DHtoe3Yt+q/r34d2r0bhNHzRq1RMuHn4YOOprGBqa4IyWunnvk9lo3mEgPHyC4Ozmg3fGzIBEIsadm4q62bVhAULCm6HXkM/g4RMMB2cP1KjXChZWdjplaRwixKVYMa7cEyMtB9h1phxl5UBtf6FWS8F7CRKcihYza4kjV8uZorlBkGp5kRjIL1ZsZFlbGVrWMsCZ6DKcjxEhJUuCzUdLUCqSoEGw5vUEKWhuPynH0StlSM0i616yBhajWQ3FHNGipgEiL5bi5sNy9qJp/aFiWJoJUN1Xt8ND2oHjuDv9d6TsUKyVdeE1aiCKHsYjZuJPyL/9AI//XIfkrQfg84nCgsNnwnuIW/YP4ldtQ37MfdwYNx3lhcXwGN5H57nPHVyBWk37o2aTPnBw9Ufnp2uJa6e0ryXa9J2E0Pra1xJmFrYwt3KQb7E3jrJ1hGdA/QqvtWGgEFfuS3DtoQTpucCeC2K27qvlq3k+qR8gZNY3Z25Ly0fdECMpC6hXTXHftKohxL1ECbPUSc4CsvKBuwkSFJboluXQrjVo0rY3GrfuycaawaOmsf59Wkt/GjFhFlp2HCDvT0PGTGdjzZ0biod/Kxt7le3ahSgEhNaDg5N7hXXDebNs2rQJn332GaZPn47Lly+z51Z6vkxNVbwEUOb06dMYNGgQRowYwbxl6DmNNnoWfV1wRc5rhB62L168iJ07d+LMmTOsM3fu3Fn+sE3uNW3atEFISAj7/uTJk+jWrRszMSZIoUA3EJ2DlCxCoRC9evViCgZCphUkpQm55mzbpnnhMHHiRGzduhWrVq1iN6K/vz+7ETMzVTXKU6dOxa+//sp+T19fH++//36lrpMUDHRdJCPduB07dmTX8eTJE/b9O++8w2RVVkJFR0fj+vXrGDx4MNv/6aefsG7dOqxYsYIpt3Jzc587Zgxdn6GhITv+77//RnZ2NlOGkKKLromUMCkpKejfvz8rT3VGHY6uMyYmhim0evfuLXdLIxc1qg9SlpCsVGfdu3d/RhlXWQYMGIDPP/8coaGh7Ldpo8/UoXan3yLFHincSLtLbUyKKmWOHj3K6pT+0rWTUkimGHpRykWlzL3EPaCx/DOBUAj3ao2Q/PjlYwE9D3pCsp4RIDZe8eRFLXMvoRyeTkKtFjn0vTJ347WXJ+iBUyyRoEjHQ1VVqheZPGTW7BOsKo93UGMkPLjywueNvX4ELl5hiFj0MeZ90QjLv++Jqyf+qVAWUq54qNWNxyuum5KiPPbX2FS3dZCsrdz8n22rlBeU50XPKRKVIuHhLVQLayj/jMbxamGN8Di2crKUlhSjvFwEUx1WUUVFeUwZbGJqWWGfcrUX4F6iwpWA7vr7iWJmeaMJT0fpAlgZUuxoK0+/US9QD0UlEvYQpgsHGz2mtIm+r3gSo+PIRcrfQ7NCTU8P8HYxUDmGhmza93eXHkOWOf4ehsgtEGPaSFvMn+iAye/bopqn5nPKsLcWMnluPXxWHj83fa3X6+WijxilY+iqbz0sYy5dyjQMM8bvn9vh29E26N3ajFkIasPRTh82lvq4cbdY/llhsQT3Hpcg0PvFrTef97y0Xrl/7y5q1qqjcg/XqFUbd25XrFSl+fT61UtIiI9DSJjUVYPWMBcvnIWrmztmfv0lhg3uhYmfjsW5MycrPJ+orAxP7scguEYDFXlo/8Gd65WqA7J6oT5lZqHoU35BNXHtwjFmpcOUPDcuICXxMUJqNnxr+jfVTdyDGATVUJUniOrm7rXK141IBFNzK3lb3bx8HE6uXsxSZ9KIFvh58mBcO39E53moX7jYCdjYoj7W0IsTTXg4CPEgSdXNiRQ7ZKmjjLezABP7G+Djngbo2lAPJpXoDiSPu6MQd+NU1xO0vvBy1qzE9namF0Oq64k7T6i8VH47SwEszVTPSUqlxyliZs3zKrFuWAvpR86ofJZ28CRsGkrddAQGBrCqHYr0w6cVBSQSpB85DeuG4TrntiQNawnaj3+JtYT6b9w8u5MpimQvNrVBLk8utsDDZNW542GKBO72mo+lz+l7ZR4kqZb3dxUgM0+CwS2F+KyXHt5vp4dAN0HFY80DDWNN9ecfa2T9SR1y17px+SSatOFxTd8EJSUl7PlSeaPPtPHbb7/hgw8+wHvvvcee1enZkowdli9frrE8PTfSM/CXX36J4OBgfPfdd6hduzYWLlz42q6Jx8h5TdDDPilwSKlA1i0EKSo8PDyYgqJfv374+eefmQXMn3/+KT+OHvJl9OmjqkWnG8fBwQG3bt1CWFgY+58gawxyzdEEKQX++usv9oBPlinEkiVLcPDgQSxbtozdbDJ++OEHtGjRgv3/1VdfoUuXLiguLmZWPLogDSVtMujGjYiIYNdPyge6Jvp+/fr1+Prrr+V1QVY6pFQiFixYgMmTJzNFFUE3/fOao1WrVo3VqYzvv/+eKXF+/PFHlTqkNrh79y5TQJElEClvvLy82PdknSODFDhkGTRw4EC5somUJr///jsztXteyLqGLINISaatvQiqJ6r31atXw8zMTF4fpBwjGciyiCBFD32up6fHzPiovUiZRoOOJmiwUh+wRGWG0DdQrIKKC7IgEZfD1Fz1TZuJhT2yUh/iTWJqTIsvAfKLVD/PK5IwdyhNkIl0nobyFF9HE2T+3Km+Aa7dK2cm0dqoSvVCFOY/lcdCVR4zSztkJD944fNmp8Xh8rENqN/2PTTqNAZJj27g4KbvmZVKjUbSvqlOUYFmWUxfYd3QG+sT23+Ei09t2LkE6CwraysTNXlMzO2R/YLyvOg5C/KyIRaXw9zKXuVzc0s7pCZWrp32bvwVljaO7OFQE2WlJdi74TfUatQZxqbmlexTqote2new0tan8Gz5YskzbkOBHkIMbKXPXKIo3tTy/WUVvu2keDJETr7qw1tufrn8O3UsTIXQ0xMgp0D1mJyCcrg4SN8OO9pIH8x6tTLHxgN5eJxUhqa1TDBpuC2mLkzXGn9H9ptkLaMiT4EYlrrkEQqQq34NBWK42CsUOeduliAjpxDZ+WK4O+qjbxszONvp4c/NuRrPSwolIjtfVVbal333IjzvefNyc9jDvJWapQxZziTESV/WaKKgIB8jh/ZjiiB6+Bk1bgJqhddl3+VkZ6O4qAjbNm/A4CHvY+jw0bh86Tx++uEbfDvrN4RV1xxDgsjPy2J9ytJa1V3EwtoOSQmPKlUHW1fPg5WNg8oD2sCRk7D2r+8w6YMOEOrpQygQYMjYrxEQWuet6d+yulG3lKH95ITKjX0UB8fK1gFB1aXKoLycTJQUFyJy+zJ0G/gRerwzATFXT2HJnE+ZO1a1UGmbqkNuMNQvChT6QgbtK7u8PDPWqJWnscbcRNH3KF7OrSciZv1nawG0ra2PIW0FWLJXpNNt0sxEwOSh9YAyeYUSOGpZT9AYR9+rlhfD0lT66CQbA/PVyuQXip8ZH18WIyd7lKQorMkJ2jewsoDQ2AgGNlYQ6uujJFXVHaokJQNmgb4VriVo7aCMmYUdMpJefC2hzJ2rh1BclIcajTWvIdTvGyHNUcWSZ+4bewvNdWpuLP1eGTqe2pwgVz4jAwGzEIu6LmZWOX4uAvRrJsTqw+V4klbBWKPen6ypP1VurNm29vdnxhplzkTthLGJKcIbtMF/iaoapnXWrFnMM0IZsrah+KWaQnRcunSJPZvKoLmMPDfI+EIT9DkZYChDL+ZfZzIbrsh5TZCFBz2wK7sUkcIlMDCQfSezyCGFji5l0DfffINz584xdyCZJQ5ZupAipzKQxQYtpJo0aSL/zMDAAPXr15fLIaNGDUVgM3LXIch8zNNTt1sFKUSoE+zZs4dZmZBypKioSG6RI7PKISUKKXLobdeGDRvkN3tOTg6zlCGZZJByok6dOvJrrgxUXhlyYSLFCylPNNVL+/btmUUUKW+oo9F+3759mYKEtLSJiYkq9UbQPp33dULtQoovmRJH9rtUF+TuJlPkkIKM6km5zcgl63kGsA4Dv0Gnwc8OYP8PUODjd9oagl4QRZx8eZe0/wLUN8kip2Uvad909gxhgQ2vHNuoVZHzJoja+i0LkNz34/X4f+LIziW4emYvxkxbBQPDZ187U2DUtQuorSTo/V7FASRfJ/QmfUFEKcyMBcwiZ1BrA/y1s1Rlgd2ohjGGd1NYFfy2TnOMlZdF9tL36EWp+xWxfn8eQnwNmfvV5kNSN9UGYUYY2sVCfty8DTl4XZDrlYyE1HKmvPpyiDUcbIRIyxKjaW0zjO6vUAjMWqKIqfA2YmJiit8WLGUKm+vXLmPF0j/h7OzK3K7IdYeo37AxuveSroF8/PxxJyYaB/bu0qnIeVn2bVuOC6cO4Itvl6j0qaN7NuLB3RsYP/l32Dm44O6ty1i/ZDZTauiyyvkv9e/IiGUsxs6Emcvl8sjaqkbdVmjddQj7n9xGHty5ihMH/9GqyHld3HykWBOmZlMg3DJ82scQPk4CPFCz4uBUDa6d3Aq/sOawsK44iPnrnA/uxktw7o70HqG4Ox72EtSpJsSTtMo/ZzwP+yOWsxg7n81YqrF/E6eP7ED9Zp21fs95tUyePPkZRYu2+KT03E0eMrJnLhm0f/v2bY3HJCcnayxPn78uuCLnX4QsNHRBFhhkKUIWNK6uruxBnhQ4ryuQLyl4ZMjMHyujSPniiy+YhQ9ZsJCFDV0XKUSU5SQXJrJuIdcuUvLExcVpdCt6GZQVHzIFk8yKRR1SepAShOQmn8bIyEhmFUTuZaQ4I6Xb80KaWvVsYa8iZk1l2kvWZrraS9MAtuSQqn+zsZkNBEI9FKoFcKUsPaaWqm8dXzeFxUC5mN7GqX5O1jXqb8lkkOWAhabyam/hZEocysKzZHeJTmucqlYvhKn5U3nUgglTcEL1t8PPA/my27v4qXxm7+KLO1cOaD3GxEyzLIWvqG5IifPoVhR6f7gW5tbaLdnU26pITZ6i/HRmQfUivOg5zSysIRTqIT9H9U1qfm4GLCpop6g9y3F011IWL8PVM1DjQ96aBZ+xuBmjp6yo8G29ap+i8V2iZsmmrU9Jv1fG3PjZPkgxDChbCJmvx6WJ8FlfA9QN0MOx6wrLD4qDcz9eUYcGegK5JYyyVY6luR6L3aIJeiNeXi6BlVJgY3YOMz3k5EnPkf30b2KqahDUxDQRbK2UYvvcLcXMBIWLsf7TYL8U4yJHKZkUuU9QQGWt8oglz1js0DHqlkbKyDJskfUQKXIuRhfi3pyEZ2SxNtdDdq6iDmn/UeKLrwGy88qf67wWllZsbstRC2xMgY6tbbQHUaVjKFuVTEkTH/cYWzevY4ocOifNvxRvRxl3D0/E3NKdYcfcwob1KfXAxnnZGbCy1j1vR25fjf3bVuDTGX+z+DfK7k0R6xdg7MTfUKNuM6ks3gGIf3gHB3es0arIqWr9W1Y36oGNad/SWrc8lOUqcvtyfPTNYpbpSuWcevpw9lCdF5zdfXH/tnbXG7LGo36hHtiY9tWtZlXGGrXyNNaoWwQqQ7FOCoolsLXUrcgpKJIwedStc8lyJlfLeoLGOHXLGrLAk5WXjYHmaucwNxUiMb2CYFzPCVnfkFWOMrRflpMHcXEJStOzIBaJYOSo2geMnOxQkqx6f2paS6gHNi7Iy4DZS6wlZFDmqocxp9Fn7IJKlaf7hoLSUrsrz1F036hb6cggKy71+4yOLyhSvRfTclWPp3g66m57Gsca9f6UXXF/ityxCgcilmPCN4tUxhplYm9dRkriI3zw2bPPKJzXg5GRUZVJLPOq4DFyXhPkG0eWKaQUkJGRkcEsKsjPTmYBQ64wmpCVnTZtGrMaofPJgiDLoHgwhCymjib8/PzkcWOUlQsUe0Umx8tC56Z4QOQWRdYt5DZEqdGVoYDB5LZFLlW0tWvXjgVflmXZIo2lcgBmuiZS+rwM5JdIsXgo2jgpmJQ3mdKHlB9k7UKWKhTfh+qK3MIsLS2Z8ky53mTXqq3eyNUtLy9PHiyZUE8zTufX1V4EtTVZ/Sifh36XFsZk0fWi0OBF16W8KbtVEXr6hnBwC0VC7BkVt5b4e2fh7PX63pJqQpbG2N9N8eBFU66/qx6epGh+QCLfdD+l8kQ1N6FKeZkSx95KgKV7Sip0/6hq9SKTx9kzFI9iVOV5fPsM3Hy1+8NXhLtfbWSkqJrgZ6Y8gpWtm05ZHN1DEX9XVZa42JerG1KKkhLnwY1D6DVuJazsKhcIUN5W91TlSbh3Fk4vKM+LnlNf35ClF773NJApQcrWezfPwqua9uOO7lqGwxF/Y+TExfDwDdP6kJee/Jg9CNIDZWX7FAX/9ncRqvQpP1chC/ytCUrN6+equtj1d9NeXn5egeCZzC0U3JfSeMs2CkJMigWylJFBKXx93QxY2m+N11AOPEoqUzmG3jvQ/r146THp2eXIyi2Hs73quyraz8hRjmchQWqWWL5R4GSSJ9hHSR5DqTz3E0Ra6/RxkgjBSqnFqbaCfQxw/6k8mvB0ksomU/YUl0hY+m/ZFp9chqxcEcICFE8oJkYC+HsZ4c6jSgxaWkjNED3XeemFgZ9/AK5fvaxyD9+4ehmBQQpX8IoQS8TyFxt0Tv9qQSxujjKJifEVph7XNzBg6cOVAxWTPDHXz8M3UHO6ZGJ/xErs3rIEn3z9B7z9VeWmGBYUF0ZAk4MS9IBLcr8t/ZvqxsM3GHduqNYN7fsGKNzf1Tm4Yzn2bVmM8VP/hJdf6DPnpM9S1FxJUhMfw9Zee+px6hdJGRL4qo01tE8BgzURlyZWKU/Q2BOXpn2ssTSl+1fqQq0Lkic+VYwAD9X1RDV3PTxO1rwme5RcjgB31UGMjn+cLJU/I5eClotVyhgZSGP1PXpa5lWRffYq7FqrKhTt2zRG1lnpGlNSVoacy9Gwb63koicQwK5VI2SfvaJzbnOhtcRt1bmN1hbuL7GWkHHt1Dbmdl2tujQZS0XQu8ikTGkcJGXI4ipeS9p6+py+VynvrChP50zMAOzUXLPINS9HzY32mbHGNxi3lQIVU3+ifV1jzYHtK7B36xJ8NO1PeKmNNcqcOhLB0pO7e7/4ur6qIhFLquT2PFDiHHrhQB4jytC+tvAY9PnzlH8VcEXOa4LitVAmJ4pXQkGM6cH83XffhZubG/tcZiFByotx48axYLpkqkXxbMici9x7yCpk8eLFuHfvHo4cOfKMNQUpQsj6RRbEl1yU1CGFxdixY1ksHCpH8XVIpsLCQhZV+1VdKwVaJqUFXScFMNZkGULuVRs3bmTBe+l/ZT766CPm+rNjxw6mwPrkk0+Y4qqiwGi6oCxOFNCZrIGonsmd6sCBAyxoFSlTSMlG8XMoEDK5gdE1pKWlMUUKQXVG1jwUtZxkorhBdI0kmybIjY6CYFGWLvotinWjHnyYlEoPHz5k56F21hRki+qG4hJR1i6KdE7uYVQ/lHFL3WTvdVCzxXDcOrcZty9EIDPlPo5tmwFRaRGC6vVm3x/aMAln9v6qEsguPSGGbeXlZSjISWH/56Q/lpcpKymQlyHyMuPZ/5SFSBcnrotQP0gPtavpsRSkvZoZgAyRLt6VPlT1b2mAjvUUD2unbpazWB3NquvDwUqAtnX04eYgxOloaXlap7/bzhDuDgJsPFLKHgDJ4oc2Cob4ttQLQXFsrp78B9fPRCA96T72r5/B0oLWaCyVZ9eKiYiKUJUnJS6GbfR/fnYK+z8zVSFPvbbDkPjgGk7v/Zt9Hn1+Fwt2XLulNCi5Nmq1HI7os5sRc15aN0e3SOsmpIFUlsh1k3B6t6osaQkxbBOXlyE/J4X9n52mkOXY1m9x5+IudHh3DgyMzFCQm8Y2UamaM7wGqjcbjtvnN+POxQhkpdzHiQhp3QTWlcpzZOMknNun1laJMWwTi562VaJqW1V0Tm007zQc545uwcXj25GScB/bVsxEaUkR6rWQuqpt+Osr7N34m7w8vaU/sGU++o36HjYOrsjNTmNbSXGB/CFv9bwJiH8QjcHjfmY+/LIyFHy1Ik7eLEfdQCHC/Sk9qwA9muizoLuX70ofZij9b/u6igeT09H0MCNk2a6ofJtwPRaE/GyMtDzFxGlfR4+92bQ2B1ztBOjdTJ89YN14WPHDzIEzhejewhzhgUYsdsyo3lZMmXL5tqKdJw63Qdv6ioxK+08XokUdUzSpZQwXez0M62rJ0m6fuKx41b/3VAHaNTRF3RAjONrqoXdrc7jY6+P4JS3mAE85dL4IXZuaomaAIdwc9TCypwWz8Ll8WzFWf/GuFVrXVShCIs8WoXltYzSuYcTkebezOYvJcOqa9BrIfaprM1N4OevDzkrIzj2ihyXuPJZmxtLGnmO56NPOGnVDTeHpYoAP33FgCqoLShmpvhnrjI5NLVQUT96uhmyTBTem/+2t9Z7rvMqQ+9PBA7tx5NB+xD15jEV/zGVx3Nq0k6YSnvfrj1izcom8/NZ/1uHqlYtITkpk5Xds+wfHjhxEi1aK7Hw9+wzAqRNHEbl/N5ISE7B3VwQunDuNjl0qDvrZrtu7OHEoAqeP7kRS/AOsW/Qj61NNWkvXVsvnTcO2tfPl5ckKZ+eGPzFs/HTYOboiJyudbcVF0us1MTVnsXC2rvqdpSpPT0nA6SM7cfbYboQ3aPVW9e82XYfi1OGtOBu1A8nxD7BxyfcoKSlCw1bSel21YAp2rJsnL09WOLs3/oF3x82ErYPbM3VDtO0+HJdP78epQ1uQmvQEUfs24MalY2jWQbdV9elbYtQJEKKWnxD2VmCBidlYc086LvRuqoe2tRX35dkYMfzdpLFM7C2BVjX12Hhy7ra0vOHTsYaC2FqbAb7OAgxurY/MXGlQ5IqIulqGhiEGqBekD0cbAfq2NIKhvgDnYqTrg8FtjdClkUIhe/xaGYI89Vi2K1p/dKhvCA9HIU5cVyhoj10rQ7u6hgj11oOLnRDvtDNmMbZuPBBVmH7csmYQ2whTH3f2v7GHVDkW+P1nqLlCYanxePFGmPp4IGjWlyzmjdeYwSzd+MN5ijXmw99XwGNEf7gN6QnzIF+E/TED+mYmiFulORGKjAbt3sOVE//g+mnpWmLfuqdriSbSuW3n8ok4uk11vkyOi2Eb/Z+XncL+V15LyBRC105vQ43GPZlVV2U5e0eM2n4C1PARsPugcz0hm2coixXRo6EQrWsqFmzn70pj3jQMEsDOAmgeJoSrLXAhVjH/nLktRqinAOF+ApaKvG41AQLcBLioVEYTbbsNwclD21gsGxprNiz5gfXvxq2kY82K+dMQsU4x1hyIWIFdG/9kKcXtHJ4da2QUFebj8pmDaNrm33NZ5+iGXrxTyA5lgwt6tqX9Ro00xzSjz9UNNMjzQ1v5VwF3rXqNUAYmeuintOHkZtS8eXMWwFfmEhMQEMBceujBn+LDkFKGlAGkeCDrC1J6UEpucqciS4z58+fLU4wTFIOHPqMU2RRLp1mzZizzkjqzZ89mNx8pAshihAIsk0KDlEWvAorqTZmfKKgzaTDJhYpizKhD7lYU/Jg0nOppxekY8iGkdO30PaXbprg1yjFgnheZRQ2dm+LfkNKEXNUoojjVL1mkHD9+nAUvJnnpO8pSJQsKTXVPyjHKNEWxgsgShwI4k+JKE7a2tli7di1TAJE7HFlSUewguhblANakMGrVqhXLqkX3CFkzKUPKIGofuncolTvt03FUz2+CarU6ozg/E+cPLEBhXhrsXYPRdeQSFryWyM9KVFGwFeSm4p+5isno6rHlbHP1rYee49awz1LjbmLH38PkZU7tnM3+BtbtiTYDpf9rgtKEm5kA7evqMxNnSnu8fG+JPAAyuUYpe7ORRc6Gw6XoUM8AHevrsxTjqyNLWapRwspMwBZcxIS+qra4i3aVPJMxo6rWCxFSrzMK8zNxYud8puBwdA9G/4+XwuypO1NuZhIEAsViJy87lWWhknHu4HK2UTrQdz5fI08r2nvsQhyL+A0n9/wBa3t3tO0/BWENuuuUJSC8M4ryM3Fu/wImi4NbMLqP1l03G+co6ubK0eVsc/Orh94fSmW5cWoD+7vtj6Eqv9V20I8sLbku/KmtCjJxMVLRVp1HKMmTrSpPYW4qtv6ukOf68eVsc/Gth+5j1lTqnNqo1agTCvIycWDLAuTlpMPVKwgjJy2Su15kZ6i205lDG6Vv5OdNUDlPu97j0L7Ph8jJSsWty0fZZ3OnqNbDmKkr4ReiO70rKVfMjEVMyUluiPTWfMWBMnmQUfU+RZY3m46K0K6OHlPw0FvotYek6XsJKutgLUB4NQNm3k7uW/HpYizeU8ZSkVfE3pMFTAkzvLslTI2FiH1SijlrspirlgxHG32Ymykens7fLIalqRC9W1swt6wnyWXsGHo7LiPyTCEM9AUY3MmSuYY9SRbh51WZSM3SbRG573QRDA0EGNbFAqbGAsQ+KcPc9Tkqacsp2xa5T8i4cKuEjU89W5gxFytKo07HyIIm07EhPgZoV9+EXWtmTjku3S5hac51seNIDlPMjO5vB1MTIW4/LMEPi5JRJlLUq5O9PizMFPOkr4cRZn6osJQY3lPqahF1Pg9/bEiv9HmVadq8NXJzcrBx7UpkZWXCx9cP33z7k9y1Ki0tVeUeJiXP4j9/R0Z6GgwNjeDm7okJX0xh55FB6clHj/8U2zavx7JFC+Dq5oGJU2YiJFSRcEAb9Zp2QF5uFnZu+ItlfXH3CcTHX/8By6euVZnpySzzjoxjBzZDJCrDol8UyR2Irv1Ho/vAMez/Dz6bjYi1C7Ds9ykoyM+FrYMLeg4ejxYdtMcxrIr9u06Tjqxudm/6E3nZ6XDzDsT4qX/J6yaL6kZJnhOR/7C6Wfrr5yrn6dxvDLr0Hye9xgZtWBpziqGzeflPcHT1xsgvfoN/cO0K49lQgPXWtfRgbqKH5EwJ1hwSyeNm0Xys7I5OljdbjovQJlyfKXhorNlwVCQfR+iFurONALX89GFsKHXRoixYh6+ImMVNRVy9J2JjQcf6hsx9MiFNjEW7iuSuWzYW5B6vOBFZ1ayJLEbnhlIFT1q2GMv3FiM5U1HmyOUypgzq38qIWbY9TCpn51QeLzRhVScMjQ5L5xYiZM4UaR2s3obrIybDyMUBJk+VOkTRo3hc6D4aIb9OhvdHQ1Ecn4wbo6ch/aAi01vS5n0wdLBFwPSPYeTsgNxrMTjfdSRK1QIga1pL0D187Olawsk9GAM/Xgrzp2uJHA1riWXfKdYSZyOXs43WEkO+UFwTuVTlZiaybFXPw60nEpgaidGiupC52qVkAeujyuX3jaWp6n0Tnw5EnBazFOOtakhdfP85IU15L+NOvAR7LorRJESIDrWBjDxg80kx4rR7nTHqNpGONbs20liTzqxnPpr6p9JYk6RiyXfsaX9aPOcLlfN06Tca3QaMle9fPLWfzZ31mkqV4ZyqyWeffcZeqtNzMz2n0/MieUuQQQBBz6xkoEGGCAQ9t5H3CT1LUgIaeo4nYwEyynhdCCTqQT04nCoAKZ7IMoZShVMWLM7rYd6uqtX9E5MqtrZ4U7i66M7W9qax0pKx4d9APUvHv01pFYpV7e/2egInvghnr+l+K/ymSXj8eoIbvwj6Bi/+kuB1kJupFJTnX2bm+KoVQyCtpHKuRW+CnKKqUzemhlWrfx+/UnXmqLy81xNL8kVp+6n27GdvmoxDd1CVeJxYde7jpmFVZzHRqrruOKpVmY9+15yN8d9mwQRFsoXKQtmBf/nlF2ZsUKtWLWZAIUtkRMYV5Gmh7H1BXicUFoVCjMiyKXfu3BmvC26Rw6kSPH78mFknkSaTLGeo45ALErlpcTgcDofD4XA4HA6H86b48MMP2aYJTV4wlI1aV0bqVw2PkcOpEEpzTSm8NW0UuPhVQK5OpNEkVyIKPkxptA8dOsSscih+jbbfp005zTmHw+FwOBwOh8PhcDj/ZbhFDqdCKK6PtjTaryr4roeHxzMZopRj3ahnf1L/nsPhcDgcDofD4XA4/x7PmyGK8+JwRQ6nQigI8L8JBXWmlOEcDofD4XA4HA6Hw+H8v8NdqzgcDofD4XA4HA6Hw+Fw3hK4RQ6Hw+FwOBwOh8PhcDicl4K7Vr05uEUOh8PhcDgcDofD4XA4HM5bAlfkcDgcDofD4XA4HA6Hw+G8JXDXKg6Hw+FwOBwOh8PhcDgvBfesenNwixwOh8PhcDgcDofD4XA4nLcErsjhcDgcDofD4XA4HA6Hw3lL4K5VHA6Hw+FwOBwOh8PhcF4KnrXqzcEtcjgcDofD4XA4HA6Hw+Fw3hK4RQ6H839MfoEYVQmBQICqgoMNqhSetgWoKhy/YYyqhKuTHqoKbpY5qCqIykxQlTC1qDr3TVFBCaoS9q5VZ8B5lGuGqoSPVSqqCg/T3FBV8HbLQFViXIMEVBX2JYWjKpFx6A6qCnZtA1GV6L/rS1QVUkyaoepQtdqJUzXhihwOh8PhcDgcDofD4XA4L4VEwl2r3hTctYrD4XA4HA6Hw+FwOBwO5y2BK3I4HA6Hw+FwOBwOh8PhcN4SuGsVh8PhcDgcDofD4XA4nJdCzLNWvTG4RQ6Hw+FwOBwOh8PhcDgczlsCV+RwOBwOh8PhcDgcDofD4bwlcNcqDofD4XA4HA6Hw+FwOC8Fz1r15uAWORwOh8PhcDgcDofD4XA4bwlckcPhcDgcDofD4XA4HA6H85bAXas4HA6Hw+FwOBwOh8PhvBQSnrXqjcEtcjgcDofD4XA4HA6Hw+Fw3hK4IofDeQlatmyJCRMmvPR5hg8fjp49e74SmTgcDofD4XA4HA6H89+Fu1b9C8yYMQPbt2/H1atX/21ROG+YR48ewcfHB1euXEGtWrXkn8+bN69KRXmv4y9Aw2ABzI2BlGwg8pIYiZnaywd5AC2qC2FtBmTmAUeuiXE/SfH91IF6Go87fFWMs7d1X3fDED20qKEPcxMgKVOCnafLEJ+m/ZjqPkK0q6sPG3MBMnIl2HdehDtxYvadUAC0r6ePIA8hbC0EKC4F7iWKse98GfIKK6wWnD+yDqf3L0N+TjqcPYLQafA0uPnW0Fg2NSEWUdvnI/FxNHIyEtFh4GQ0bDdMpYxYXI6oHQtx4+xOdk4La0fUbNILzbuOhUAgqFCeI3s3Yf/21cjJzoCHdwAGj5wI34AwjWWPRW7DmajdSHhyn+17+QWj9zsfqpSn82xZPR/RV8+gqCAfAaHhGDxyEpxcPSt1zzQIUrpnLouRpOuecZfeM1ZP75mj11XvmSkDtN8z5+5U3FcuHV2HcweprdLg6B6E9gO/hquP5rZKS4zFiZ3zkfyE2ioBbfpNRv22w58pl5eVgqPbfsH96BMQlRbBxsELXYb9CBfv6jplidyzBbu3rUNOViY8ffwxbPRn8A8I1Vj2/Oko7Ni8CilJ8SgXieDs6oHOPQehWetO7HuRSITNaxfh6sXTSE1OhImZOcJq1sWgYeNgY+eAytAoVA8taunDwkSApAwJdpwqRVyqjj7lK0SHegawsRAgPUeCfefKcPuJtE8RYT5CNAzRh5uDEGbGAszdXMzOW1m6NjFG0xqGMDES4EGiCOsji5CWrTi/JlqEG6JdPWNYmgkQn1qOTYeL8Di5XP794PYmCPLSh5WZECVlEjxIKEfE8SKkZOo+L9GrlRla1DaBqbEQsXGlWL07DymZinNrok09E3RqYgYrcyGeJIuwdl8uHiaIVMr4uRugTxtz+LkZQCyRsHJz1mShTPTm6sbUWMDOGeKtDxsLIfKLJLgWW4adJ4vYeKiNk5EbcGTXCuTlpMPVMxC9h0+Bl7/m+/7M4S24cGInkuPvsX13nxB0GfCJ1vL/LJ2JM4c3o+eQSWjReQgqw95d2xGxdROyszLh7eOHD8Z+hIDAYM3ynDqOLZvWIykpAeWicri4uaFHr35o1aa9vEzPzq01Hjvs/VHo1XfgWzPWEPt3b8PObRtY3Xj5+OH90RNQLTBEY9lzp49h2z9rkMzqhsYbd3TrNQAtWneUl1k49wccO7xf5biatetj2re/VihLxJ4D2Lh9FzKzcuDn7YlPRr2H4AD/Co87fPw0vv11Ppo2qIsfpnwh/3zWvD+x/8hxlbL1w2vilxmTKzznpah1OBe5DAW50nZqN6CCdto1H8mPo5GbKW2nem00t1NUhGo7daZ28qq4nS4eXYezkdL7xonum0Ffw02HPMd2KO6bdv2fvW8WTm7NvlOnTsvB6Dh4ulY5bJvWhe/nI2BVOwzGro642GccUnYe1im7bfP6CJnzFcxDqqE4Lgn3Zv2F+NURKmW8xg6G72cjYOTsgNzrtxE94TvkXLiByrDxxGWsOnIB6bkFCHBzxFd92qC6l4vW8rmFxVi45wQOX49FTkExXGwtMbFXazQL9X3hc8rYuXsPNm+NQGZWFnx9fDB+zCgEBQZUeNzRY8cx6+c5aNSwAWZ+PVU+f69cvRbnL15CUnIyzMzMULtWTYwYPhR2dnb4r8Bdq94cXJHDQVlZGQwMDPBfory8nD0IC4Vvh9GZlZUVqgrBHgK0DRdg30UJEjMkqB8owMCWQvy9R4zCkmfLu9kBvRoJcfS6BLGJEoR5CdCvqRDLIsVIy5GW+X276kOQn4sAXesLcDtO92Bfw1eIrg31EXFShLhUMZqE6WFEJ0PM+acEBcXPlvd0FGBgawMcuCBCzBMxavnpYUg7AyyIKEVKlgQG+iSvAIeviNiDpokR0K2RAYa1N8TC7TqeYgDcPL8XkZtmo8uQGXD3rYmzB1dh7dyR+PCHfTCzfHYCListhrWDB0LqdsSBTbM1nvPUviW4GLUBPd+fDUc3fyQ+uokdy6fA2MQcDdoO1SnP+ZMHsGnFbxgyZgp8A6rj4K51mPvtePywMAKW1rbPlL8TfQn1m3WEf1BNGBgYYl/ESvw2cxy+m78FNnaOTJG4cNZn0NPXx0eT58LE1AyRO9dizowx+H7+VhgZm+i8Z9rUEmD/Jek9Uy9AgIEthFi0V/s90/PpPXMvUYJQLwH6NhFi+UHFPTNvx7P3TJd6AtyJr3iBcOvCXhzeMgsdB8+Eq09NXDi8Cpvmj8Comfu1tFURrO3dEVSnIw79M0vjOYsKcrDml0HwDGiAAR8tgamFDTJTH8PYTHffPXPiENYunY/3x09kypt9Ozdh9jef4te/N8JKQzuZW1iiZ/9hcHX3hr6+Pi5fOIVF836ApbUNatZuiNKSYjy8fwe9BrwHT59qKMjPw+olczHn+4n4Ye6KCuumpp8eujU2wLbjZXiSKkaz6voY0cUIv2wo1tinvJyEGNzWEPvPiRDzuBy1qulhaAdDzNtSwvoUYagvwKNkMa7fL0ffloZ4HtrXN0Kr2kZYta8AGTlidGtigo/7mWHm8jyItOhO6gQaoE9LE2w4WISHSSK0rmPEjpmxLA95hVKZniSX4/ytUmTmSphyiZQXH/czx7TFudClM+/cxBTtGphiSUQu0rLL0buVGT4fYo2pf2RoVbjUDzXCwA4WWLU7Fw8SytC+oSm+eNcGXy1MR16BRK7E+fxda+w5WYC1e3MhFgMezvo6ZXkddWNtLmDb1qgiJGWIYWcpxKB2JrAyN8WSnZq12VfO7MP2NT+j34hv4OVfA8f2rcGi2aMx+dddsLB6tj/di7mA2o07wyegFvQNDHFk13L8PWsUJv2yHda2Tiplr184hMf3rsPKxhGV5eSxo1i+5C+M/XACAoKCsXP7Vsz8ehL+WLwK1tY2GvtUv4HvwM3dE/oG+rh47iwWzP2ZlQ2vU4+VWbF2i8oxly+ew8J5c9CoSfO3ZqwhTh0/jFVLF2LU+M/hHxiCPTs244dvPse8RethpaluzC3Ru/9QuHl4Ql/fAJfOn8afv8+GlZUNatVpIC9H/4+boFCW0BxSEUdOnMYfy9fgs7EjERLgj8279uKLGbOw9s/fYGOt/VqSUlLx18q1qBESpPH7+rVr4quPx8r3DWlir4CYi3txZMssdKB28q6JC0dWYdOCERg1Q3M7iWTtVLsjDm/W3E7FT9vJK7AB+n8obacsaifTituJ7ptDm2eh0zvS++b84VXYOG8Exnyr/b6xcXBHcJ2OOKjlvnlvyhZIxIqBIS0hFut/f48dows9M1PkXr+DuJVbUXfLHxXKbuLtjno7F+HJ4o24OvQL2LVuhOqLvkdxUhrSD55kZVz6dULwL5Nxc/x0ZJ+/Bp+Ph6HBnmWICu2I0rRM3YrIy7cxJyIK0/q3Q3VvF6yLuoSxf23GjqkjYGdh9mzdiMox5s/NsLUwxZz3usPRygJJWbmwoAXeC55TRtTxE1i0ZBk+/nAcU95s274TU76ejmWL/4KNtbXW45JTUrBk2QqEhaoqUEtKShB7/z7eGTQAvj7eyM/Px5+LluKbb3/AH/N+01kvHI4m3o6n3CqIWCzGzz//DH9/fxgZGcHT0xM//PAD+27SpEkICAiAqakpfH198fXXXzNlCbFy5UrMnDkT165dY4oG2ugzIjs7GyNHjoSDgwMsLS3RunVrVk6Z77//Ho6OjrCwsGBlv/rqKxXLDpLr22+/hbu7O5OLvtu/f7+KRQj95qZNm9CiRQsYGxtj8eLF7Pe2bFFdyJDVEGmL8/LyKqwPXdd89+5d9pu3b99WOWbu3Lnw8/OT7+/cuRPVqlVjMrVq1QqrVq1ix1G9VATVobW1NTtHSEgIu/YnT56wQfOLL76Am5sbu5YGDRogKipKftzjx4/RrVs32NjYsO9DQ0Oxd+9e+ffHjh1D/fr12flcXFxYfZNGXRskL9WbMiSXrI3JGocIDw9nZck1S5NrFcn98ccfs7am+mjatCkuXLgg/56ugY4/fPgw6taty+q9cePGuHPnDl4Wsqq4el+C6w8lSM8F9l6QgC65pq9mCxFS9JAlBVnWZOQCx25IkJwF1K2mKE8PiMpbgJsAj1KB7ALdsjStro/zt8tx6W45UrMl2H5ShFIRUDdQs7VGkzB93I0X4/j1cqRlS3DwkgiJ6RJmgUCUlAHL9pXhxgMxsywgK4Sdp8rg7iC1DNHF2ciVqN28H8Kb9oGDqz+6DpkJA0NjXDm5VWN5N5/qaN9/IsIadIGevmZFady9Kwis1QYBNVuyRSMpffxCmyDhYcVvrSJ3rkPzdr3QtE0PuHr4YsiYqTA0MsbJwzs0lh/16Q9o3ak/PH0C4eLug+HjvmHKm5jr59n3KYlP8ODuDQwZPQU+1ULh7OaNd0dPQVlJCc6dUH0bq+keuPpAcc+QEpDdMz6a7xlS9NxPBrOsycgDjt+UIDlbatWj7Z6p5irA40rcM8T5QytQs2l/1GjSB/au/uj4zkzoGxrj+mnNbeXqXQOt+05CSL0u7MFTE2cPLIGFjTO6Dp/F3uJa23vAN6QpbBx0Wyvt3b4BrTp0R8u2XeHu6YMR4yay8eTYwd0ay4dUr416jVrCzcMbTi7u6NR9ADy9/XDnlnQuMDUzx5Tv5qNhs7ZwdfdCtaAwDB/9OR7eu4301OQK66ZZDX2ciynHxTvlSM2SMIUOKSjqBWl+GGpaXQ9348Q4dk3E+mDkBRES0iWsr8m4HFuOQ5dEiE2o2NpFHVI07DtbjOv3REhIE2Pl3gJm1VKrmvaXC23qGuHU9VKcuVmK5AwxNkQWobQMaBSmaLuT10txL74cmblixKWWM4sTW0sh7Kx0L3tICbPzeAGu3ClBfIqIKXRsLPRQO0jxUKBOh0ZmOHa5CCevFiMxrRyrduehtEyC5uEK5efgjuY4dK4Qe04WsjLJGeW4EF2iVSHzuuomMV2MxTsKceO+COnZYtx5IsLOE8Wo7mfALBY1EbVnNRq17osGLXvB2d2PKXQMDY1xLkr1DbyMIR/+hKbtB8LNOwhObr4YMGomJBIxYm+eVSmXnZmCbStn4d3xP0GoV/n3ijsiNqN9x85o074TPDy9MfbDT1mfOhy5T2P56jVqoWHjZvDw9IKLixu69ewDbx9f3IpWjLM2trYq27mzpxFWoxacXVzfmrGG2L19E9p06IZW7brAw9MHo8Z/weaFIwf3aCwfWiMcDRo3h7uHN5xd3NClRz94+fji9i3VOYhe9tnY2Mk3c3OLCmX5Z8cedG3fGp3btoS3pzs+HzsSxkaG2HtIsQZTp7xcjO9/W4j3BvWFq7Nm5Z6hgQHsbKzlm4W5eYWysHZq0h81Gj9tp8EzYWCgvZ1cqJ36SNtJT19LO0UugaWtM7oMU7STTyXb6dzBFajVtD9qNpGuJzo/vW+undJ+37TpOwmh9bXfN2YWtjC3cpBvsTeOMlk8A+rrlCXtwHHcnf47UnYcQmXwGjUQRQ/jETPxJ+TffoDHf65D8tYD8PlEYSHkM+E9xC37B/GrtiE/5j5ujJuO8sJieAzvU+H510RdRO/GNdCzYXX4OdtjWv/2MDY0wPazNzWWjzh7AzmFRZg7sifCfd3hZmeFuv4eCHRzfOFzytgasQOdOrZHh3Zt4eXpiU8+HAcjYyMciDyk80Xy7F9+xZB3BsHF2VnlO3rO+OmH79CiWVN4uLsjOCgIH44djdh795CamlZh3XA46nBFzgsyefJkzJ49myksbt26hfXr18PJSfqmiZQs9OBOn5PLzJIlS5jSghgwYAA+//xzpjBISkpiG31G9OvXD6mpqdi3bx8uXbqE2rVro02bNsjMlGqv161bx5RFP/30E/uelEd//fWXilz0e7/++ivmzJmD69evo0OHDujevTtiY2NVypFC4pNPPkFMTAx69+6NgQMHYsUK1be5tN+3b192PRWh65pJwUPKBpJfGdofPHgw+//hw4fst0iZQcqr0aNHY+pUqSliZSksLGR1s3TpUkRHRzMlyIcffogzZ85g48aNrD6ojjt27Civj/HjxzOlyfHjx3Hjxg12vPnTRUFCQgI6d+6MevXqMZmorpctW8aUaS/K+fPSh+ZDhw6xtt+2bZvGchMnTsTWrVuZMuvy5ctMYUhtKbsXZFAdUXtfvHiRvb1///338TKQAZOLDfAwRfU1Me2722le5ZOFi3r5B8kS9rkmzIwAf1fg2gPdlhV6QsDNXoB7Sg+HdATtezlqHrrIekC5PEGKHW3lCWNDAXNz0OVWUC4qZS5SvsGN5Z8JhEL4hjRC/P0Xd5H08A/Hw5gzyEh+yPaT427jyb3L8K+u+y2wqKwMj+/HILim4o0pWZ+F1GiA+3euV+q3S0qLUV4ugpm5pfScotJn3rTSOWnRGBtztcJ75pGGe4baTxN0b6iXf5CkvbzsniFlUUVQW5H5uY9aW3kHNUbCgyt4UWKvH4GLVxgiFn2MeV80wvLve+LqiX8qbKeH9+4grKb0rb+sTsNq1UPsHd0LSIIUbTevXUBSwhMEh4ZrLVdYmM8Uu6YVPFyxPuUgYAoO+W/QtcWXs76jCU8nIftembtx5ezzl8XeSsgUE7cfK5Tj1A8fJpXDx1Vf6zV4OuupHEPXQPu+Wo4xNJAqMtKzy5GVq13Z5GCjB2sLPdx6oBgMikokuB9fBj93zQ9PenqAt6u+yjFkZRP9oJRZ4RAWZgJ2fG6BGFNH2GDeF/b4argNqnka/Ot1Q5DbVnGpBJqs4UWiMsQ/vIWAsIYq93C1sIZ4HKv6okkbZEUmFolgam6l8tJp3R+T0arrcLh4VOxqI4NeEN2/dxc1atVRkadmrTq4c/tWpfrUtauXkRAfj9AwzW4s5JJ06cJZtG3f+a0Za2R180BD3dSoVRd3b0dXqm5uXL2IxPg4BIfVVPku+sZVjHinGz4ePRiL/5iDvNycCmQR4e79h6hTs7qKLLQffeeu1uNWbdoKaysrdGmn2dWNuHrzFnoMHYV3x36KX/9aipzcvEq1k7d6OwW/ZDtdOwJnzzBELP4Y879shOU/VK6dSJ4kDfcN7ce/hDzqv3Hz7E6mKKqMm/bzYN2wFtKPnFH5LO3gSdg0lL5UFhgYwKp2KNIPn1YUkEiQfuQ0rBtqn8dk1jUxccloGOAl/0woFLD9648SNR5z7OY91PB2xazNh9Bq6h/oPWsFlkaeRTmZPb7gOdlxZWVMwRKu9LKc7uHwWjURo/ZiWpl1GzaxF7idOihcN3VRUFDA2sjMvIK3iW8RtKauitt/Ee5a9QKQhQopKxYu/B97ZwEexdHG8X/c3d0FCMEluLu7FPsoXqAthVIopUCBUtyhuLu7u2uw4BYj7i73Pe8cp7m7BEuOMr/nWcjt7e7NzszO7vz3lUXo00cY84IsS8hqgvj999/F27q7uzOLEBISaHJuYGDAhAKadNtLKbUXL15kk3wScujNEkFiDFl3kKXMwIEDsXDhQvTv3x/9+vVj3//xxx84fvw4M80TQfuQdQwJMwQJE2fOnMG8efOweLHEZJIC9JKAI4Kse8iig8QFsjyhcpBlCgkORUHVORM9e/Zk9TVlyhSxlQ6JURs3bmSfly9fDj8/P8ycOZN9pr8fPHggtnIqCjToLlmyBOXKCR9AyCKHxCj639FR+FaNykUWSrR+2rRp7LuOHTuibFnhwwZZE4mgY7m4uLBy0yDr7++PiIgIVr9U9x/jtkXWVgT5wkq3v/ygTqIRCWPNmwvjYpAwduLECSYkjR49Wrwt1Q9ZVonEuZYtWyIzM5NZ8chDghUt0uTmaENbR/Km2VBXeIOTd7Ggz1bC+X4BKCaKou2NlHjilPXQYG+IC3OrMtSniYkGi+EgDX22MVdc9xRHR9H2xgaKH2S0tYBmVbUR/CKfWesoIz0lgZksy5s8G5laIzZSKMJ8DLWaD0RWRhoW/d4CmppaLGZOg/Y/IrB6a5X7paQksm1NzWRdc8ilKjL8dZF+m2LhmFvYoPR7MYgscCxt7LFr4yL0HjIeenoGOH5gExLiopCUoPxN0WfrM1nC9ar6TFHcqtJThW1laCLfVlaIe/cSH0tiTChun9uCqo36Iaj5YES+vo8T2/6CprYOAoPaK9wnJVnYTmYWsu1ELlURYW+Un0NaKob1bYPcnGzWL/oN+QVlKyh+q5qdnYUta5cgqE5jGBqqfhA0en9NpWSgwDViq+SaMjGka7Dg9rT+U6EYLgQJHNKkpOWLv5OHrmU6h+R02X3os52l7CNNnfK6aF/XgIm1ZAEzf0ca8lQYDZFwQiSlyh07LV/8nTwmhpqsPIr2cbAWij+2FsJytatnjK3HU1hsnJrl9DGmtwV+XxKnMP7Ol64bEUYGGmgepI+LwYqV7LTkBNaH5V2o6HN0RNHGvoOb58DUwga+AUHidaf3r4KmlhbqNPsOHwIJCCQCmVvIugmR21BY6Ful+6WlpaJ/ry7sOYHu3YOG/YjyFSsr3Pb0yeMwMDBEUM3aX81YI6mbvAIum1Q34SrGG6qbQX06iMeb74f8jHIVJOJzhYrVUK1GXdjaOSAqMhyb1/+LqRNHY+qspdAiJVMBScnJbCIt70JFn9+GFYzjQtx79BiHT57BynmKXZGJqhXKo071qrC3s0XEuyis2LAVYyb/jSUzpkCLlEwV7VTg/m3yie0UG4o759+3U7PBePfmPk5u/4tZ4JZV0U4qyxP58eWR5sndk8jMSEFgDeXl+Fj07KyRFRUrs44+65iZQFNfDzoWZtDU1kZWdJzcNnEw8pM8YysiIS0DefkCWJkYyqynz6+iFbtkhcUlIeLZW7SoVBqLB3fE25hETNtxArl5eRjcvOZHHZNITiYX2PwCLlT0OTRUcR9+8PARjh4/gaUL56MoZGdnY+WadahXtw6MDGXLx+EUBS7kfARkxUITYrKWUQS5LS1YsAAvXrxgIgu54pDrkirI4oO2lQ92lZGRwY5DkNvM0KFDZb4nt5/Tp0+LBx0SGmrWrCmzDX2Wd9EiCxn545CVEFmAkCBAAoubmxvq1FFtGVDUcyZhiUSUq1evonr16swahyyOSBwRnRtZvsiX6UPQ1dVFYKDkDRtZ2JCJI1kESUNtJ6pncl8aMmQIE8QaNWrERB3RMaidg4KCZN5mUF3S+YWFhTGLqC8B1SE9bEq3I5k1U31QmaSRPl8S4AgS4RSVbfr06cytT5r6HSegYSflQfC+BOSi9eCNQOWEqjggN4IeDXVAzbv3ogoV5wvy8MYR3L96AB0HzIKNkzfevX2MY1unsaDH5Wt+/gcwEYd3rWExdsZM+Rc6ukIhj+IjDPt1FtYumowRveqxB/rS5aqibMWaJR6Im1y0Hr4t2T5DdUBvyeu1/5l9tnctzQJQ3jm3VeXk6mPQNzDE9PnrkJmZgYfBN7Fx1QLY2jsxtytpaJxdMON39rbzf0OFork6U6WUDno0kTysLtkleQnxJaAYOSGvc2FmrMGC/w5obYiZm1PF7kxBZfXRp7XEimnupsLdeD8G0S3kzC2h+xXx9l0qSnvqonYFA+w8lVrsdUPo6wLDOhgxkevgZQUBkj4DJ/etZDF2hk1YIx5rQl8+xPmjGzFq2o7Pbi2gDBJm5i5awZ6p7gXfxuoVS2Bn78DcruQ5deII6tRvyJ4p/utjjahuZi5YzcabB3dvYd2qRbCzd2RuV0TNuo3E27q5e8HNwxs/fN8Vj+7fQdnyisWwDyU9PQNT5y7GL8MGwFzF83LDOhIrFgqeTEv3QSNx98FDGeuf4mynuu3k2un8VpVCTnEQfHEXvALqwMRcNibVfxGytLA0NsQf3ZpAiyyTXewRnZTCAhuTkFNcMK+A2XPw44gfYGames4nun//Nf0fZjc5Ypgk5hOH8yFwIecjIKsaZZAbD1mf0ISZXGEoiC1ZppD7iypIHKCJuHT8FhFkove5IT9Necgqh6x2SMghixWy/CnKQ1ZRzpmsTyjmD7mgkZBD/5OA8rnbRbq8VKf0togsf+TfGoncp+icqcyHDh1iYg6JHVTu4cOHf1QZ6PflJ72iWEFfAukg1aJzpzcIytwBf/5Z+MAhYu4+2SEgPZv2p+CgsvvS5zS5t/IiUsn6pojbu9gA1qYa2HO58Bl5eibYWxShNY2kTulz6vuApgXKkiH8Xhq2vZyVDok4PRvpsMxWKw5lq7TGISiIoYamFtKSZd8wpSXHwtjMGh/LiR0zUbPFABZHh7Bz9mMZri4e/lelkGNiYs6EluQk2bdJyYnxMDNXnfmAslwd3r0Gv0xaxjJdSePuVRp/zt2K9LQUlsHExMwCf43pDXcvxdlgCu0zmR/QZ/SE6+VxsSbLHg3suVI0FcfQWNhW6SnybRX3SW1FMQesHSQxvQhrB088uXNM6T4mpsJ2omxV0iQlxsPcQnk7kcUAZasi3D19ER76Gvt2rJcRcoQizngWF2f81EWFWuMQae+vKRO5WxhdI6IgwfLQeuMP2F4V957n4HVkioxFHGFqpInkNIlViomRJsu2pAi6lukcTA3p7btkG/qc/D6wsLQrUmZ2PmISgVcRaZg93IzFl7n5WHjBUxycF+E5BcpD1jfSFjZUPrKiUURKej4rj7zFDu2TlCosX2KK8P+IGNljUKwcUcye4q4bPR3gh07GLKPXsr1pLPiyIoxMLVgfTkmSvZ7os6m56uvpzME1OLV/FYaMWwFHNz/x+pePbyM1OR6ThzcWryNLkn0bZ7JAyn8sPK70mCamZuz6SExIkFmflJjAYtsog/ZxcHRif3t6eSPs7Vvs2r65gJDz8ME9hIeF4pexf+BrGmskdaPFxhf5uilsvHFwdGZ/e3j6ICzsNfbs2CAWcuQhkYd+izJdKRNyzExN2aQ6IVHWBYs+W1oUfKYNfxeFd9ExGPeX0CqbELlCNGjfAxuWzIGTQ0ErZkd7O5iZmiA8MkqpkCNqpwL375Q4ZlX7Ke1kJddOVvaeeHJbdTupLM8n9BsRlLnqVchldByyEF8Csr4hqxxp6HNOUgryM7OQHZvAXCn1bGX7nJ6dFbLeyVryyGNhZMCsCuPk0ojSZ2slQYltTI2grUWWkZIx2NPOimWnIreqjzkmQS+j6dpIkIvTSZ8V9eHIyHeIiorGH5OEngeEaD7QrHU7rP53KRzfv3BlIs7f/yA6Jhr/TPvrP2eNw7NWFR88Rs5HQAF5STSgQLPyXL58mVmyUOwSsnqhbSmgrjT0locsRaQh65R3794xlyuKhyK9WFtbi92NpAPeEtKfadAhF6JLly7JbEOfKQBwYXz33XesrGRZQ7FuRG5jhVGUcyZI7CHLHRJ+Xr58KXb/Ep0bxXlRdm4fAwUUpnomCxX5OpV2ayL3qcGDB7N4NRS/iNyYiFKlSrGySgszVJcUD4iCSStznSL3NBEUi4dUehGiN3zy7S8NuenRdtLtSGIQ1UdR2lEZ5LJHfUR6kXarIuhhPjIBcLeTFUPoc5iSdMLhcQJ4yG3vYa/B1iuyxqEU4tFFePFN1hcUVNXbSTJM0a94O2riTbTiWcebqHz2vTQ+zrLbi0QcEgdWHs5WmFVJHgp26OhWBi9DJH7hgvx8vAy5Cmevgm90iwplotDQkC0v+cpTYFBVaOvosPThokDFIgEv5P51ePkpjvtAUKaqgztW4qc/FsHdW3lfMjQyYSIOBUB+/eIRylcTBuVWhKo+Q+2nCOob7rYK+kzsp/UZUVvZu5bBa7m2evP4Cpw8Vfvnq8LZqyLiomRdSeKjXsPMUjg5VNZOHt5+eHjvpkw7kZWNj5/iNPGKoP5Abg/yIs67iDCM+2sBm1QVBXZNxdA1pSV7TTlpsWtHEW/pmpLaXnRN0foPhQRTSp0tWihrEgkmfq7aMlYiHg5aeBWRq/QcKCOVn5u2zDnQZ0rPrQzSuWnR1pL0O4oLEx2fJ15IWCHRpbSHxBJDX4/i2+jgRZhi1yMayl9H5MrsQ79D1jYUW4egoMIJyXlwsJKtR3srLcQm5Rd73dBxRnQxZmVfsjtNZcBlstSj9OFPH1yT6cPPHl6Dm49sHBVpTu1fjeO7l2PQ2GVw9ZLt65Vrt8boGbvxy987xQtlrarfuh8G/7a80JcXXt6+zKpGujz37t6Gn3/pD7qmFL1kOXn8CDu+h6fsBF3dxxpR3Xh6++J+8C2ZuqHPvv5lPmgSpuoFVFxsNFJTkmFuqVwc0tHRhq+XB27deyBTltv3HqCMgtTNrs6OWLNgJlbOmyFealathAplS7O/bd8/B8sTHRuH5JRUFvS40HZ6/PnbKV5RO1mpbicqj4OC8lA/cv6E8ogIvrSbufv5lFV+3/4UEq/ehVUDScwswrphDSRcFcbSE+TkIOn2Q1g3kLhS0qBoVT8IiVdVxwDS0dZCKRd7XHsqmUPQiyL6THFwFFHewwmhseTGLHl+eBOdwAQeOt7HHJOVRUcHPt7euHs3WKYP3717jwUplsfFxRnLFy9kblWipXq1qigXWJb9bfO+D4tEnPCICPw9dUqhHhscjiq4Rc5HQPFHKE4KxX+hCTe5wMTExLAAuyRiUNwVskghVyGy9NizRzazA8WQoeC+d+/eZYIACQPk1kNuPBTsl7JhkTsQuUnR/u3bt2cCCVmJDBgwgP1N8WxIFKEAvtJxXSh+ysSJE5kYQBmryLKGfkc+0LAiKHMTxc2hYzRp0kSpWCFPUc6ZoGOTFQ4tlJVKFLeGoODGc+bMYfVKcYCozKJMTx9rek11SOJR7969mZUNCTvUTiTAkUsSxZOhWEEUh4a2TUhIYPGESMAhyI2NYgtRvVPQZHL/orolqxZl8XHI6ohi6lBbklhD5yNtNUMBmEkEpDg9VL/Ul+RTj5O1FNURtYOlpSVzk6I+QYIQ1c2X5tpjAdpUp8kzEBEvQFVfDZa2+977QLOtqwljbJy9J/x8/YkAvRpqoJqfBkslXdpNgwW/pWxX0uhqC9NUn7pTdKX+4v1cdK6rg7CYfITGCFArQIsFLqUsVkSXejpIShOwdOPEpQe5GNRaF7XLauHx23yWapkC6O6+kCcWcb5rpANHa02sO5bNJlwia4OMLOFESBnVm/TF3lVj4egeACePQFw9uQ45WRkoX1MYa2rPyl9hYmGLRh1HiYMNxkQI3SLzcnOQnBCFd29DoKtnCEs7YdA933L1ceHQMphZOrD045FvQ1h2rPK1Cs/s0KRNT6xaMJFZ0VCWqZMHNyMrMwM1G7Zh36+cPwEWlrbo2EtoXXZ491rs27IUA36eBmtbRyQlCN+M6ekbMlce4salE0zAsbK2R9ib59iyaiYqVK2HgPJSD2QKoD5A/YL1mfcp61mfeSXVZ9KBs/eFn288FeC7BhrCjGfUZ1yFfYayXcn3GX/qM3c/7O0OxSw4uPZX2LsHsGwflBKYRLPAGsK2OrBmDDM5r9de0laxkaK2ykZqYhSiQkOgQ21lK2yrKo36YMOM7rh8eBn8KzdH5Ot7LLBls+8mqyxLi3bdsWzuFHh6+8OL0o/v28riWNVt1Ip9v2TOJFha2aBbH6Hb7L4d6+DpXQq2Dk4sWPLdm5dx8cxR/G/IGPFD4Py/x7EU5KP/mMUeLBMT4sSphEk8UsWFe7noUv/9NRWdj1qB2uyauvlEeA11rS+8po5eF36+eD8Pg9vook6gNkLe5qG8txbL8rbrnEQBpSyvlNLa7H3sFmG8nXxmtSMfX0ee07ey0CJIDzEJeUzUaF3LgAkYd59JJpIjuxixz+fuCMWUUzez0KeFIbOSeR2ZhwaV9ZiFCWVqEgUKruSvw9yqyGLGwkQTTavpIztXgIevVJvfHb+ajtZ1jPAuPg+xCXno0MAICSl5uP1Ycr5jepvj1uMsnLouPLljV9IwoL0ZXkXkiNOP6+lo4MIdiYnZkcvpaFfPCG+jclm5a5XTh4O1NhZtTyrWumEiTmdj6OhoYM2hNBboWJSll9pLkRdlvZa9sXnpeLh4loGbdwDOHdmI7KwMVKsrzLS4aclvTIhp1f0nYRn2r8KRHYvQ64d/YGnjhOREyVhDi5GJOVukoaxVpmbWsHUUZnZURdv2nTF/zt/w9vGDj68/DuzbhcysTDRsLEyzPG/WdFhZWaNXvwHs885tm+Ht48syUJFAcevmNZw9fQKDh/0oc9z09DRcvnAO/b4fjK9xrCFateuKxXOnwcvHH96+pVj6cbov1G8kDNy8cPZfsLSyRs++wnPcs30DPH38WcaqnJxs3LlxFefPHMOAocLyZmSkY8eWNaheox7MLSxZjJwNa5ay7ctXVO3+3qVtS0yfvxT+3p7w9/HGzgOHkZGZheaNhHH9yJXKxsoSA3t3h56uLjzdhFaIIoyNhPcl0fr0jEys27oTdWpUg6W5GYuRs2zdZjg52KFKxXJFaidyhaKMVDdPr0N2EdspPy8bKe/bie7fFqJ2atgHG/7pjstHlqFUpeaIeH0PwRe3o1nPwtupWuN+2L9GWB7KeHWdnieoPO+fJ/avFpanfgep5wmpfkPlefe+PKJ+IxKEgi/vRmCNdkXOBEfpx428Je74hh7OMC3nj+z4JGSGRsLvr5+h72SH4H6/su/f/LsVbkN7wn/6aJay3Lp+dZZu/EabQeJjvJq3BuVWz0DirQdIunEP7iP6QNvIAKHrFCf4kKZXvcqYsOkwyrjaI8DVARvP3URGdg7aVRMKwuM3HmIpxke2FoZ+6FKrPLZeuIMZu0+he52KeBuTgJUnrqJH3YpFPqYyOrZvi5lz5sHHxxv+vr7YvW8/u383bSwMrfHP7LmwsrJE/7592HzQw13SFoTxe+8H0Xq6f0+Z9jeevXiJKRMnID8vH/HxQutCExMal1XfvzkcebiQ85FQtiqynqGgtyS4kFsUWXXQRPunn35iE3+KxUJiAW37559/ivelOCxk/UFiBqXWJrGF0k9TcGGyaiGXJhIcyGqEYtSIsmGRKEGWLBRrhgaSLl26sP1EmZBEMV+SkpKYZQlZopAFhyitd1Gg8pPb04dkP6KsWIWdM0GCFaX63r59O1avXi3zHaXlpqDOVG4KJE1CCNUFCRqi4M8fA9UtZZmi41IWKrJuIteuVq2EkygSWyhzFcW8IVWcMlqJsm1RynJqExJUKIAyiSpUP9KBneUhwYjar3bt2kyoonMh1y4R1GfI4olSxFPfoe0UudNRRjSaoPXq1YsF1ybx7tixY0xs+9KEhArdZOqW1YCRvgaiEoGtZ/NZMFqCJmsCKVen8Dhg75V81CuriXqBGohPAXZczEeM3PykjJsGeztMsU6Kyr2X+TDSz0XjSjqgOHUkEqw+ki2eHJpTWaQO9zZagK2nc9CksjaaVtFmKcY3nMhBVIJAXPbS7sK34iM7yvarfw9m42WkciUnoGoLpKfE4+zehUhNjoG9Syn0/GmF2IQ+KT5CRnRMSYzG8kkS96grx1azxc2vCvqO2cDWNe/xO87sXYDDGyczs2qKjVOpblfUbSMbC0sRVWs1RUpyAvZuXYrkhDi4ePgxSxuRa1V8zDsZa5+zR3ewDDRL/5EEyybadB2Itt2ED/Uk7mxbMwfJSXEws7BGjXqt0LqzcDJUWJ8x1APqBEj6zLZzkj5jaijrckh9Zt+VfNSlPlNWAwmpwM5LBfsMCTxUo48+oM+w/aq0QHpqPC7sX4C05BjYOpdClxErxWb0yfGRMnVDbUWZYURcO7GaLZS2tecoYVvRJK3DkEU4t2cOLh5azNLFN+oyDgHVhMKZMoJqN0JyUgJ2blrJBBc3Tx+MnTRXHAA5LiYKmlJlycrMxOqlMxEfFw1dXT2WYnzoqD/ZcYiEuBjcunaB/f3biN4yv/X7tMUF4ujIE/wij13fTapos4DFEbECrDqUJbmmTOj6lkCWOptPZaNZVR00qya8ptYfyxZfU6y+3bXQtb7EIqVnY+HfJ27m4MRN5VYyxPHrWdDV0UCPpoYw1NPAi/BcLNwpayViY64FYwPJiltPcmBsmIFWNQ1Y4F9yNaJ9RO5eObkCeDtrs/TdhvoazK3oeVguZm1KLdQl7PCldOjpaqBfaxMY6mvi6dtszN6YyFK0i7C1pLqTiCnXH2bBxCgF7esbMxcrElFmb0yQCVRMAhGJm92bmsDYgCyacjBzQwITaYqzblzstMVZr6YMkH0TPH55MkvXLk+FoOZITU7A0Z2LmCjj5ObPLG1M3rtWJcTKXk+XTmxj4vXaeUJhR0TTjkPQrNMwfCq16tZHUnIitmxYw17AkPXMxMkzmNBAxMREM8tGESRkLF8yH3GxMeyacnJxwU+/jGPHkebCuTPs3la7nvKMSeo81hA16zREclIitm1cxbJvuXt6Y/zkWeK6iY2JgoZUnnkSwFYumYO49+ONk7Mbho+awI5DkKvW21cvcO7UURYU2dLSGoEVqqDbd9/LZDhURIPaNZCYnIzVm3cgPiER3h5umDlxLCzfhwuIjo1lgfKLCrnOvHj9FkfPnEdqWhqsLS1QuXwg+vfswlKSq6JUZeH9+8IBSTt1Ha66ndZMlbTT9ROr2eLiI2knEoQ6DF6Ec3vn4NL7dmrYeRzKFKGdqN+kpcTj3Pt+Y+dcCt1GrITx+/IkKSjPqimS8lw9vpot1G96/SIsD0EuVcnxESxbVVExqxSAoFOSY5SeNY79H7p+N+71/w16DjYwcBG6BBEZr8OYaFN69m9wH94bmWHvcH/Q74g9cVG8TeSOI9C1sYTvxBHQs7dBcnAIrrf6HtlyAZAV0ayiPxJS07Hk8CXmHuXnbIslgzvBylQoirxLSIGm1LOWvYUplg7phJl7zqDzjLWwNTNGz7qV0K9R1SIfUxn16tRmc6r1GzezsYZenE+d/Kf4WTw6JuaDXjbHxsXhyjXhnG3I8JEy382cPpVZ7/wXKOm4it8SGgJe2181jRs3ZoLPhg2SQfhToOOQKEPiVEkF+pPOyLRs2TKEhoaWaDn+y0zdqsKmvgRISSmZoMOKCCz18QLil8DVUta/uyQ5f19JeqkSwtFOceaUkqCso/IsGMXNttPK47mVBCkpRfBjLCYyRCqjmmBAQaLUhNYN1SsNrodZNNSFa6Gq3WaKk4pO6lMvhG2e4kw+JcGRyE93UfqcKEmoVSJYNZLEq1IHGh6QfblUkkR5q85UV5y4eatXO30IvSdIQkyoE+unSATJ/wrcIucrglxrSNig4LwUvHfLli0sPTilpf4cx6bYLmQJQm5OJSHiULpvcs2ijFIUH4ZSkZOVD4fD4XA4HA6Hw+FwOBwhaqQRcwqDzPfI1YfcrSpVqoQDBw5g165dLL7Op0IxWCgVOFn3UHYjaaZNm8ayPClaKL7M54ICA7dt25a5g02ZMoW5Q4ncs+h3lJWBysfhcDgcDofD4XA4nJKDgkmr4/JfhFvkfEVQkFyywPkSkGAiH9NGBMX+oXg8ysr0uaDYNKL4NPKsXLkSGRmKo2ZS7BoOh8PhcDgcDofD4XC+BbiQwykUEkpKWiyhwMMcDofD4XA4HA6Hw+F863Ahh8PhcDgcDofD4XA4HM4nIfiPujGpIzxGDofD4XA4HA6Hw+FwOBzOVwIXcjgcDofD4XA4HA6Hw+FwvhK4axWHw+FwOBwOh8PhcDicT0Ig4K5VxQW3yOFwOBwOh8PhcDgcDofD+UrgQg6Hw+FwOBwOh8PhcDgczlcCd63icDgcDofD4XA4HA6H80kI8vNLugjfDNwih8PhcDgcDofD4XA4HA7nK4Fb5HA43zBmpuql5aalaUBdMNBVrzcKhtqZUBdMTQyhTujrqk9gPT3NbKgLGpoGJV0EtSU3Jw/qRH6eeo036kROvg7UBS01umXmCrSgThilREJd0NCoAHXiTUQu1IUuB0ZDnTjVeibUBZ/HTUq6CBzOB8GFHA6Hw+FwOBwOh8PhcDifRH6++rxc+6+jRu8WOBwOh8PhcDgcDofD4XA4quBCDofD4XA4HA6Hw+FwOBzOVwJ3reJwOBwOh8PhcDgcDofzSQgE3LWquOAWORwOh8PhcDgcDofD4XA4XwlcyOFwOBwOh8PhcDgcDofD+UrgrlUcDofD4XA4HA6Hw+FwPgkBz1pVbHCLHA6Hw+FwOBwOh8PhcDicrwQu5HA4HA6Hw+FwOBwOh8PhfCVw1yoOh8PhcDgcDofD4XA4nwR3rSo+uEUOh8PhcDgcDofD4XA4HM5XAhdy5HB3d8e8efNKuhicrwQNDQ3s3bv3k4/D+x2Hw+FwOBwOh8PhcIoCd60qAerVq4fy5cvzifs3yNq1a/Hjjz8iMTFRZv2NGzdgZGQEdeHexU24fXoV0lNiYe3ojzodfoe9W6DCbeMin+Ha0QWIDn2IlIQI1G73G8rX7SOzzc2Ty/Hi3gkkRL+Eto4+7N0roGbrUbCw9Sy0LNVLaaJ2WW0YGwDv4gU4cCUXYbHKzTYD3DXRuJIWzI01EJcswNEbeXgali/+vmEFLQR6asLMSAN5+UB4rADHb+UiLKZopqBXTmzGucOrkZoUCwcXP7TpPR4uXorr5vqZHbh9cR/ehT1nn509SqNp5x9ltn9w4wSund6G8NcPkZ6ahBF/7YKjW6kileX4oV04sHsTkhLi4erhjb6Dfoa3b2nFZbl8Fnt3rEdUZBjycnNh7+iClu26oXaD5uJtdm5eiSvnTyIuNhra2jrw8PZD116D4O1X5qvqM8S1U5tw+cgq1k52rv5o0fN3OHsqLk90+DOc3rMAka8fIjEuAs26/4agJrLlycpIZduE3D6JtOQ4OLiWQvMe4+HkWbbQshw5uAf7dm1FYkI83D280H/wSPj4KW7jq5fOY/f2jYiMDGft5ODojNYduqBeg6Yy24W9fY0Na5bj0YNg5OXlwdnVDaPHTYGNrV2h5QkqrYU65bRhYqCByHgB9l3KVtn/y3pookkVHVgYayA2WYAj13LwJFR4TWlqAE2raMPPVQtWJhrIzAaehefhyPUcpKSjSLSqqY9agbow0NPAy4hcbD6egZhEyTWriLoVdNG4ij5MjTQQFp2Hbacy8OZdnvj7Hk0M4O+mDTMjTWTlCPAyPA97zmcgKl71cYmODU1Qv4ohDPU18fRNNtbsT0RUnOTYimhUzRAtaxvDzFgLb9/lYP3BJLwMy2HfWZtrYd5oxe2yYEs8rj/IVHrc1rUNULucHqubF+G52HwsDdEJqs+hXkU9NK6mz86d6mbriTS8jlRc/uGdjRHgpYslu1IQ/ExYXkVcPL4Fpw+sQUpSLBxd/dCh7zi4eSvu+1dO7cSNC/tlxr2WXUcq3X77ykm4cmoH2vX6FXVb9EJROHpwN/bv3sKuKTcPL/xv0I/w8VM89l27fA67t2/Au/fXlD1dU+27om6DZgq3/3fRLJw4ug99BwxHy7ZdCi3LzTObcOUYjTUxsHPxR9PuE+DkoXisiQl/hnP7FyDyzUMkxYWjcdffUK1RX5ltFo5twL6Tp1K9Hmjec+JXdV/YfuIiNhw6jbikFPi4OmJ07w4I8HJTuO2B89cx6d8tMut0dbRxec1M9ndubh6W7DyMS3dDEB4TB2MDfVQN8MXwrq1gY2FWaFlundmEayeE7WTr7I8m3SbAUVk7RTzDhf0L8O6tsJ0adv4NVeXaiUhJiMKZ3TPx4uEF5GZnwMLGDS37TIODe+H3hco+Ggjy12TPNlEJwNFbeYiIV759KRcN1AvUhLkREJ8CnLqbj+eRsuO2tSnQsJwmXG01oKkJxCYBOy7mIbmQsXjrhdtYd/oGYpPT4Otki7EdG6Ksm4PS7ZPTM7Ho0AWcuvcMSWmZcLA0xZj2DVC7jOdHH1OEZa3K8BzVH2YVA6DvaIubHYciav8p1fvUqYrSs8bCuLQPMkMj8Xz6UoSt3yOzjduQHvD8uT/07G2QfO8xHv44BUk37hdankMH9mH3rh1ISIiHh4cXBg0ZBl8/f4XbXr50ATu2bUFkZATrr45OjmjXvhMaNGws3iYjIwPr1qzE1SuXkZKSDDs7e7Ru0w7NW7bGf4V8QeH3Wc7ngVvkfOPQBCA//793wWVnZ+NrwsbGBoaGhlAHnt45jAt7/0bVpsPQbdRuWDv6Yf/y75GeEqdw+9ycTJhauaBGq1EwNLFRuE34ixsIrNUDnUduQ9vBq5Gfl4t9y75HTpbqpwuaQLaopo1Td3KxeF8Om3T2a6YDI33F29PDS9f62rj5NB+L9ubg0Zt8fNdIG3YWGuJtYpME2H8lF/P3ZGP5wRwkpArwPxXHlCb46hEc3DwDjdoPxfApO+Hg6o9V/wxEapLiunkZch3lglpi4Lg1GDpxM8ws7bHqnwFIio8Sb5OdlQE334po1nUUPoQrF05iw8oF6Nj9f5g2bw3cPLzx9x8/ISlR8ZOgsYkp2nfpg8kz/8WMhetRt1ELLJs/DcG3r4q3cXB0Rd/BozBj0QZMnLEUNrYOmPbHj0hOSvhq+gzx4NphHNv6N+q1HYZBf+6GvYsfNsz+HqnJisuTk5UJCxsXNOo8CsZmisuzb80EvHh4GR0GzMDQKfvhFVAT62b1Q3KCpC0Vcen8aaxdsRhdevTBzAUr2KRzyoRfkJSouE6NTUzQset3mD5rMeYsXo36jZtj8dwZuHPrungbmpCOHzMcTi6umPT3PLZd5259oKurW2jdBHpqoVWQDk7dysWC3VmIjMtH/xZ6Svu/m50mujfUxY3HeWz7R6/z0LuJrvia0tUGnKw1cfp2LubvzsKGE1mwMddE36Z6KApNquqhfkU9bD6Rjn82pSArGxjR2QjaWsr3qeSng471DHDociamrU9BWEwe28fEUHKdv32Xh/VH0jFpdQoW7kiDhgYd15j9r4pWtY3RJMgIq/clYeLSGGTl5OPXvlbQUfHaq1pZffRsYYY9p1Pw++IYJuTQPqZGwkesuKQ8DJv+TmbZeTIZGVn5CH6apfS4Tavpo0ElPWw6loa/1yczQWpEVxOVdVPZXxedGhji0MUMTF2ThLDoXLaPdN2IaFhFD0WRr+9cOYK9G/5B045DMGraDji6+WH534OQomTcex5yAxVrtMCw31dj5KSNsLCyx7LpA5EoNe6JuHfjJN48vwczC1sUlUvnT2HdykXo3L0vZsxfyca+qX+MUn5NGZuiQ5femDprKWYtWov6jVpgyby/cffWtQLbXrt8Hk+fPISFpXWRyvLwxmGc2D4dtVsPw/cT9sDO2R9b5vVnYq8icrIzYG7tjAYdlI81/xu/Ez/Ouiheevy0hq0vVVmx8KSu94XjV+9g7qa9GNC+KTb+NQq+ro4YPmM54pNSlO5jZKCPo4smiZcD8/4Qf5eZnY3Hr8PwfbvG2DhlFGb+2A9vIqPx85yVhdbLoxuHcWrndNRqOQz/Gy9sp20LCm+neu1HwchUcTtlpCVhw8zu0NTSQdfhKzDgz0No0PlX6BsVLiqVdtVA4wqaOP8gHyuO5iEqUYAe9bVgqGTYdLYGOtTQxN0Xwu2fhAnQpbYmbKR+ysIY6NNIC7EpwIbTefj3SB4uPMxHrmoNGkdvP8asPWcxqGkNbB3dG36ONhiydAfiUtIU101uHgYv2YGI+GTM6tcG+8b3x8RuTWFrbvzRx5RGy8gQyfee4MGISSgKBu7OqLJ/OeLOXsPFym3xauE6lF3+F6wb1xJv49C5OUrN/A3P/lqMi1XbI+XeY1Q7tAq6NpYqj33h3FmsXLEc3Xt8h3kLl8LD0xN/TPgNiUrGGhMTU3Tp1gMzZ8/HwiXL0ahRU8yfOwu3b90Qb7NqxTLcvnUTo0aPxZLlq9CmXQcsW7oI165eLtL5cjj/eSFn586dKFu2LAwMDGBlZYVGjRohLS2NWcKQNYQ07dq1Q9++sip7SkoKunfvziwknJycsHjxYpnvyZpi0KBBsLOzg76+PgICAnDw4EH2XVxcHNuX9qOJOZVjyxbJGwb6rXPnzmH+/PnMLYeW169fs+8ePHiA5s2bw9jYmB27V69eiI2NlSlXz549WbkcHBwwd+7cAueUkJCA3r17w8LCgv0+He/Zs2cyFiHm5ubYv38/SpcuDT09PVy8eBE6Ojp49+6dzHnScWvXrl1ofRd2zv/++y8cHR0LCEZt27bF//73P/Hnv/76C7a2tjAxMcH333+PsWPHMsulokD1Sm05depU9lt+fn5sfWhoKLp06cLO2dLSkv2mqL6Js2fPomrVqqxOaZuaNWvizZs34u+XLl0KLy8vNkGiY27YsEFpGehY1J7S1jZ3794VtzF9369fPyQlJYnb/s8//1ToWvX27VtWVuoLpqam7ByioiQPwbQf1Q2Vh/Y1MzNDt27dWB/5VO6eXYsyQZ1RulpHWNp7o37nSdDW1ceja7sUbm/nWha12oyBb8WW0NLWUbhN20ErUapqB1g5+MDGyR+Ne0xnlhjRYQ9VlqVWgBZuPMnH7Wf5iE4ky4FcZOcClXwVz2RqlNHCs7B8XLifh5gkAU7ezkNEnADVS0m2D36ZjxcRAiSkgB3z8LVc6OtqwF5K7FHGxSNrUbVeZ1Su0wF2Tt5o128idPX0cfP8boXbdxs6E0GNujMLG1tHT3T8fgoE+fl4/kjykFyxVhsmDHmXCcKHcGjvVjRo2gb1GrWCs6sH+g8dA109PZw9IRyL5CldtiKqBNWFk4s77Byc0bxNV7i6e+HJo3vibWrWa4Ky5avAzt4JLm6e+O77EchIT8Pb1y++mj5DXD6+FpXqdEaF2h1h6+SNVr0nQUdXH3cuKC4PWdU07ToGZau1ZG+c5cnJzkTIreNo0uUXuPtVgZWdG+q3Gw5LW1fcOC37BlmeA3u2o1GzVmjQuAVcXN0x6IdR0NPXx6njhxVuHxBYAdVq1IGzqzvsHZzQqm0nuHl44vEjyZvDzetXomLlauj9vyHw9PJl21WpXhNm5haF1k3tQG1cf5yHm0/zWP/fcyEHOblAFT/FSkXNAC08Dc3H+Xu5bPvjN3MREStAjTLC7TNzgJWHs3HvZR4TSd9GCy18nG3ozXHh1xQJFUeuZuLe81yEx+Rj7eE0mBlroryP4n5BNKysh0v3snHlQTbexeVjy/EMZOcAQQESIevivWw8D8tDfHI+QqPzsP9iBixNNWFlpvqxp1lNI+w7m4LbIZkIjcrFsh2JMDfRQqVSypXe5jWNceZmOs7fzkBETC7W7EtiokvdSkJxXiAAklLzZZbKpQ1w7X4GsrKVSykNq+jj8OVMZikTHpOHNQfTYE5146tcsGtUVR8Xg7Nw+X42E+k2HU1ndVMjUHaG6GyrhcZVDLD+cOETq7OH1iOoQSdUq9ce9s5e6Nz/D+jq6uPaWdk33iJ6/TADtZp0g5O7P+ycPNF14CQIBPl49kAy7hEk7OxeOx3fDZsBTa2iG4gf3LsNDZu2Rv3GLeHi6oGBw35h4/DpE4cUbl9GdE25CK+plm07F7imiLjYGKxePg8jf/kD2tpFK8+1E2tQoXYXlK/ZETaO3mjxnXCsuXtJ8VhDFiCNOv+KMlVp7FPcjkYmlkzkES3P752BhY0r3HyrflX3hU1HzqJd/SC0qVsNnk72+K1fZ+jr6WL/uYICmggSWq3NTcWLlZmJ+DtjQwMsGTsEjatXgLujLcp6u2NM744IeRWGd7GqRaXrJ9egXK0uCKzZEdaO3mjWU3iPundZSTu5B6JBp19RukpLaOsobqerx1bAxMIerfpOZ+1qbu0Cz9K1WFsVRnU/Tdx5IUDwKwFik4FDN/LZOFzeU/GYWdVXk1nfXHks3P7s/XxEJgBVfCTjWf1ATTyPEDBLnXcJQEIq8DRcgHTlWjFjw9mb6FAjEO2ql4WXvTV+79IE+ro62Hv1gcLt91y9j6T0DMz9vh0qeDrDycoMlb1d4Odk+9HHlCbm2Hk8nTgPUftOoii4DeyGjFdhCBkzA6mPX+LNkk14t+sYPEZK5nYeP/ZD6KrtCFu3G6khL3B/6ETkpWfCpW9Hlcfeu2cXmjZrjkZNmsHV1Q1DfxjJ5k0njh9TuH3ZwHIIqlELLq5ucHBwZCKNu4cnHj2UPLeEhDxiFjq0LVnjNGveEh6eXnj65EmRzpfD+U8LOZGRkUxUIIEgJCSETZ47dOgAAT1JFZGZM2eiXLlyuHPnDhMTRo4ciRMnTrDvSIwgceTSpUvYuHEjHj16hL///htaWsKJYmZmJipVqoRDhw4xYWbgwIFMkLl+Xfg2lQScoKAgDBgwgJWVFhcXFzb5b9CgASpUqICbN2/i6NGjbOJOE3gRP//8M/tdEmGoPBcuXMDt27cLCBq0P21z5coVdt4tWrRATo7EZDo9PR0zZszAypUr8fDhQ1SuXBmenp4yIgVtv2nTJhmhRRmFnXPnzp2Z2HPmzBnxPvHx8ewcSZgi6LdIhKFy3bp1C66urkxE+RBOnTqFJ0+esLohYY3OoWnTpkwYorqiuiNhpFmzZsxiJzc3l4k/devWxb1791h9UdlJYCH27NnD2n7UqFHsvEi8IyFG+jw+hBo1ajCxhoQZUdv/8ssvBbajPkYiDtURiX50Pi9fvkTXrl1ltnvx4gWLz0PnSgttS33xU8jLzWYTZRffGuJ1GpqacPEJwrs3d/G5yMoQCk76hsrfXGlpAo7WGngeIREA6Sp+EZHPLG8U4WorfJCRhoQdZdvTb1Tx00JGloBZ+6giNzcb4a8fwbtMdfE6TU1NJsC8eV60uiHLj7y8XBgW4Y2dyrLk5ODV8ycIKFdZpiwB5avg2ZPCH5RoXHgQfBOR4W/hX6a80t84fXQfDI2M4eru/VX0GVbu3GzmIuVZpoZM3XiWDkJoEdtJHrIGys/Pg7aO7GSYJmxvn91Suh+NQS+eP0Vg+UoyZaHPTx8/LFI73bt7CxFhoSgdECgeH27duAJHJxdMnvAL+vVoi7E/Dca1KxcKPR71dydrDTwLk7yipV7/PDwPrnaaSi1y6HtpnoYp354gYTRfIECGCpGCsDbTZKLN4ze54nXkmvUqMg8ejtpKz8HVXktmH/oV+uypZB9dHaHIE5uYh4Rk5RaoNhZaTLR58EIy86Gx4UVYNnxcFU/m6Nbv4aiDh88l+9DjBn32dlUsRrk76rDl3K30Qusm5LXk3p2ZJcCriFx4OqmuG+l9WN28zpHZh6yL+rcxxpYTaUhOK2zcy0HYq0fwDZAd93wCquPNs2AUheysTOTn5sLQWHLtUj/etPg31G/VFw4uyscXRdfUS4XXVOUiX1P3795k11SpgHIy5Vk45y+06dAdLm4eRSoLjX3kIuVRSnbscy9VA+Ev7hT5nAr7jfvX9qNczY7iZ5Ov4b6Qk5uLx6/CUK2Mr0xZqpbxwb3nkpdl8mRkZqPVyMloOWISfp6zCi/CIlWWOTUjg9ULiTyq6pBcpAq0k38NhL/8+HZ6du80HNwCsGf5CMz/JQir/2qHuxe2F7ofuTw5WAKv3slee6+iBHC2VtzGtJ6+l+ZlpOz23o4aiE8RoEc9TfzcXgv/a6wFPyfVfYasa0JC36G6r8TdTVNTg32+9zpC4T7nHjxHoLsjpu84ifrjF6PD9DVYefwq8t6/rP2YY34K5tXLI/b0FZl1MScuwqK6sA9r6OjArGIZxJ6SsngRCBB7+jLMq1dQOdY8f/4U5cpXlDoPTZQvXxFPHj8q0vUUfPc2wsPCUCZA4mpXqlRpXLt2BXGxscJ7fPBdRISHoUJFyZj2X8hapY7Lf5H/XIwcmhzTBJ3EGzc34SBCFiIfAlllkIBD+Pr6MgGArF8aN26MkydPMoGCRCL6jiARRARZpUhPzocPH45jx45h+/btzPKDLCfIuoMsV+zt7cXbLVq0iIk406ZNE69bvXo1E3mePn3KLHDWrVuHzZs3o2HDhuz7NWvWMOsTEWR5QwIOlZdEA5FAQsegCT8JKqLBacmSJUysEtG/f392vNGjR7PPBw4cYAKNtJCkjMLOmayDSPySLjtZTVlbW6N+/frs88KFC1kZSCgh/vjjDxw/fhypqalFbjeyqiFxSuReQEIbPZzROtEDEJ0jWd6QwEcCFlnHtGrVilndEKVKSeJWzJo1iwljQ4cOFQtpV69eZetF5f4QqFzU/lQW6bZXJEjdv38fr169Ym1HrF+/HmXKlGGxdKpUqcLW0bmRhRUJVQSJZ7QvCWIfS0ZaAgT5eTA0sZJZb2hijYToV/gckEXKhb3T4OBREVYOkoc8eQz1aWKigdQM2cGXPtsoeatOvuYFts8UFHAr8HPRRLf62mxCQ3E8Vh/NKfStVXpKIpvMG5vJmtwbm1ohJuIlisKRbbNhamH7wdY38iQnC8tiZiFrFmxmbomIMOUPyelpqRjaty1yc7KhqamFfkN+QWAF2be8t69fwoKZf7DJl7mFFcZNngdTM/Ovos8Q6SkJwnYylS0PtVvsu48rj56BMVy8yuPc/iWwdvBkx7p/9RAThiztlL99TUlOYmUxl7OUIcuZ8NC3SvdLS0vFwN6dkPO+nQYM/RHlKgive3IfyczIwJ4dm9G9V3/06juIuV3NnDoBk6bPQ5my5YtwTcmVk64pc2XXlAZSFGxP8XUUQW4/zavqIPh5HrKUh1xhUHwbIjlNVlxJScsXf6eoPHQOyemy+9BnO0vZR5o65XXRvq4BE5bexeVh/o40FhdLGeYmwjpITpU7dmo+i32jCBNDTWhpaSApVVbsIqsbBxvF4k+9yoYIj87Bs7fKK8jUWFNh3dBniu+lCGNDYd2kyIkztI+9lURU6tLQEC/Dc1TGxBGRliy8nkzMZK8n+hwdUbTr6eDmOTC1sIFvgGTcO71/FTS1tFCn2Xf4EETXFI11Ba4pFWMfXVOD+nQQj33fD/lZfE0R+3ZuYi/kWrTpVOSypKcKxz4j+bHG1Apx74p2TyiMJ3dOIjM9BeVqtv+q7guJKXSt5cNSyqKGoM+vI6MV7uPmYIsJA7qxWDqp6RnYePgM/jdpAbb//SvsrAr+VlZ2DhZuPYimQRVgTINbIe0kf48y+sR2SowJxe1zW1C1UT8ENR+MyNf3cWLbX9DU1kFgkPL2IvcpEjbo2USatEzA2kTJta0v/F4a2t/o/ThMrrF6OhqoUVoTZ+/lM6scLwcNdK6tifWn8vA2RnFZEtIykJcvgJWJrGs/fX4VrdgdLywuCRHP3qJFpdJYPLgj3sYkYtqOE8jNy8Pg5jU/6pifgp6dNbKiJN4LBH3WMTOBpr4edCzMoKmtjaxoWTe6rKg4GPkpj7mXzMaafDaHkYbu52GhoUr3Iw+Qvr26sbkWCT9Dho2QEWkoxs6iBfPQt3d3NuZoaGhi+MifEFBWcbwmDuebEnJInCCxgMQbssZo0qQJOnXqVOBCVAVZzMh/Frm9kKuMs7OzWMRRFHOGxBgSMcLDw5nlR1ZWVqHxT4KDg5mlB1mMyEOWFxQciwYFEkZEkCggciEiSFwic+Bq1aqJ15FrGW1D30kLCoGBsgMGCRa///47EyqqV6/OBAIScYoSgLco50yWN2SFRAISmSWSwESuQDTIEWRJIxJMRNC5nj59GkWF2lw6RgTV6fPnz8VChwgSqKhOqW/QeVM/IZGOXPDonEk0E9UnWejIi3xkVfUlod8lAUck4hDkBkcCFH0nEnLIpUr63Kjc0dGKH5AIahNapMnJ0YWOnJXBl+bsrsks2G2nEZtRUryMzMfCPdkw0tdgFjndG+hg6f7sAg9Kn5OzB1Yg+OphDBy3Djq6xVvnIvQNDPH3/HXIzExnb143rloAO3tHZl4vonRgRbZNSnIiTh/fj/kzJmDK7BUFJk7fWp/pMPAf7F09DrN/rssmOw5upZkrVsSbwq0APhQDA0PMWriSCTb3g29j7colrJ3I7UpkXUquVK3bC4V2Dy8fPAl5gGOH96kUcr40FPi4ZyNd5h6x52JBkaBKKR30aCK5LyzZVXSh/mO4/igbIa9zYWaswQIjD2htiJmbU8UxI2qUM8D/2kqsRGat//yTDHlIPA4KNMDeM7JusFVL66JnM8n9dtGOT3eTVUSgtw783HRY/Jzi4OS+lSzGzrAJa8TjXujLhzh/dCOLt1OYlcnnvKZmLliNzMwMPLh7C+tWLWLXFLldvXj+BIf278Q/81cVW3mKyt2Lu+AdUAcm5oUHMf/a7wuBPu5sEVHOxwOdxvyN3acvY0jnFjLbUiDZsQvXsfFwbF/hS8rihn6bLHLqtf+ZfbZ3Lc2CJN85t1WlkPMlEHXbp2ECXHsivEdQ3B0XawEq+Wjibczni4VJ1paWxob4o1sTaGlqorSLPaKTUlhgYxJyvnUorMf8RcvY/Ts4+A6LiWNv78BcqYgD+/fhyeMQTJg4mSUnePjgHpYtWQhLSyuUryC55jicb1LIIXWTXFEuX77MLDrI0mP8+PG4du0aEw3kXaykXY6KeoEW5pZFE30SfkhYICGEYs0UFnyXLE9at27NXIvkoQk6CRKfCzoH+YcVik1Dv08WKx4eHjhy5AizWikKRTlnOjbVPblfkRBBrk5k5fQ5kRedqE7J5YtEI0XBhQk63xEjRjA3r23btjExi/oPiVkfikiUku5jH9q/PgSKayQNtamqwNXTp0/HpEmyweOa9/gDLXoK4/QQBkYW0NDUKhCkljIRGZoWLfhjYRPy14/OosMPG2Fsrtwqif1mJthbHXoDL3QQkLYQUGwiSZYGwu0lGOtrICVd7rrPFWZ9IDPk0Jhc/NxJB5V9tXDunvKogIYm5mwCT1mQZH4zOQ7G5qrr5vyh1Th7cCW+/3UVHFwl4uvHYmoqLAtlJZGGAlqay72Nle+jlLGFcPf0RUToG+zbsV7mgV1f34BtQ4uPfwB+GtgFZ04cRLvOvRUeU536DGFoYiFsJ7kgltRuxp9QHoqH87+xG5Gdlc4yWJmY22L7kp9YkGRlmJiasbLIB0Ykq5rC2omyVYlEmrDQN9i9YxMTcuiYdJ+jeDvSOLu4IUQu5ofya0qunAYFrxERZOFmomh7uWtQJOJQtrgVB7MUWuPce56D15ESgUIUtJeCAienSa49k/fZlpSVh87B1JDGW8k29FneTYjctDKz8xGTCLyKSMPs4WYs9s7Nx8LCURycF6GS+5S2tobYGiYxRTKW0ue3kYrH8pT0fOTlCd5b7Ei2IbcoeSsdomqAAXtzfvGOrJlT8PNsvFqdW7AscnVDn0OV1U26sG5M5Cx2aJ+k95Y9/m46sLHQxNyfZF9uDW5vjGdhuZizWVZAMjIVXk/ygY3ps2kh496Zg2twav8qDBm3ggVIFvHy8W2kJsdj8nBJJheyJNm3cSbOHdmAPxYeL/Sakg/eK7ymZC0ulF5Tnj4IC3uNPTs2MCHn8cNgFrh3SL9OMuVZt2oxDu3bgSWrdyg8pqGxcOyTD5jL7gmfYexLjAvHq5DL6DR04Vd3XzA3MWKTfPnAxvTZysy0SOejra0FP3cnhMpZW4hEnHdxCVj621CV1jjS7SR/j6J2k7ew/RAofpG1g9CaWwRZbD65ozh+igiy/s2ncVhf9tmGrGrkrXREpGYKv5f5fX0NpGVIjknXfkyy7P4UT8fFRrk4aWFkwKz44uRSDNJnaxPFL3JtTCkYvSZrXxGedlYsOxW5VX3MMT8Fsr4hqxxp6HNOUgryM7OQHZvAXDv1bGXHBz07K2S9k+1b0piysUaTxR6Vhu7nFpbKjQNoH0dHJ/a3p5c3Qt++xY7tW5iQQy9TN6xbjXG//4kqVYUv3T08PPHyxQvs2b3jPyPk/FfdmNSR/1yMHNGEliwnaNJKcW7ISoPindDknVyvpC1JKPaJPGSVIv9Z5HJDlixhYWHM3UkR5NZE8U2+++47Zh1Eblfy21J56LelqVixIotXQ1YW3t7eMgsJFHQcmriTa40IcguSPjaVkdzKSLQSQbFpyNqFLDoKgwIMk5hBwYnJ1YjqsCgU5ZwpKDS5u5GoQoGQyUqIzlkEfZY+N0L+84dCxyd3MxKp5OuUrJlEkEvbb7/9xsQ/ClxNLmCi+qRzkz9XZXUpEoek+xhZcBXW9vLQ71KQZlpEUCwmiqNUlHZUBp0j9RnppXGX32S2oeCLts5lEPb0ioxbS+izq7B3+/g3/SRu0YT85f2TaD90LcyshA+NqiAXCAqq6u0gGaboccTLUZMFVFXE2+h8eDnKPrR4OynfXnxcDQ2VmWAIbW1dOLmXlglUTMLZ84dX4eatvG7OHVyFU/uW4X+j/4WzZwA+B9o6whSwD+7dkinLw+Cb8PEL+KAUkYWJjbQNmdwrQ536jKidHNzL4OWjKzJ18yrkKlxUtFNR0dUzZCIOZSx58eAi/Cs0ULotjdle3r64f1e2ne7dvQ1f/8JT94qgQLEUm0J0TG8ff4SHybpmRUSEFpp6nK6pcLqmnCSdna4Wb0ctvI1SLAK/icqHl9T2hA9dU1Lbi0QcazMNrDyUpdRNkcQdSisuWigYL7kg+blK3inp6wIeDlosFoyyc6CMVH5u2jLnQJ8pdbky6N0FLdpakvEhM1uAqPg88RIenYvElDyU8ZRYzFHaby9nXTx7q/gaoOH8VUQOynhJrEHpd8p46eG5AtepepUMcftxJhOAZOomW65uYvNY3fi768jWjaM2XoarrptSUvtovBdvRPscvZqBKauS8ddqyUJsP5WOdYcKBj6m4N+UPvzpg2syffjZw2tw85G4Z8tzav9qHN+9HIPGLoOrl+yYVLl2a4yesRu//L1TvFDWqvqt+2Hwb8uhCur/nnRNBcteU/T5g66pfIF47KtTvylmLVzLLHZEC2Wtong54yfPVjn2ObiVwasQ2bHvdcgVOHkpj71RVIIv7WbuPz5l63119wUdbW34ezjj+sOnMmW58fAZAr0Vpx+Xh1yznodGsqDH8iLO26gYFviYBKPCoHaydy3D2kW6nd48vgInz49vJ2evioiLknUvjI96DTNL4SReGfS+LTIecLeXfVbxsNNAWKziZxVaT9/LbG8v2Z6OGRFH7kuy21iaAEkq4mDpaGuhlIs9rj2VuN6RyESfKQ6OIsp7OCE0ltz4JMd9E53ABB463scc81NIvHoXVg1kX75aN6yBhKvC529BTg6Sbj+EdQMpbwsNDVjVD0LiVeUxkti91tsX94LvyPTh4Lt34Odf+oOeZUTXE8VIpHma/Mt0cjP9L2YQ5nx5/nMWOSRiUJwQcpuhCTx9jomJYZNjEkQozglZhZBQMWfOHJkMQ9KT9X/++YcFwiXrjB07drB9CAqMW6dOHXTs2JHtT6LA48eP2UVJQXR9fHxY/BcSBcidi7ahoMXSE3ASa6hclMmIXKkom9KwYcOwYsUKFqh5zJgxbB1Z4WzdupXFeCEXmj59+rAYNvQdndvEiROZ8isaEOi3SVAhF6bly5ezfSjWD8WwofWFQS5GFIiXskdNnjy5yHVelHMWuVdRPBoSrEj0kYbi6lC5KW4NxfchQYkCEEvHH/pQ6PfIWojOnc6HXOIoI9Xu3btZHdPASqJVmzZtWKwhErxI+KGsXwTVNblakdBDblcUN4j2pThJiqC+QO5QlFGK4tSQmDV7tuxDILU9WQpRHyXRi9zP5N3u6LfIsonKT1ZONOiT2xn1Paqfj4Vc2miRRken4A2+fL2+OLl5LGxdAmDnFoi759YhNzsDpat1YN8f3/QrjM1sWepoUSDB+Chh9or8vBykJkUhJjwEOrqGMLcRPrCd2zUZT24dRKv+i6GjZ4S0ZKHDtp6+CcscoYyLD/LQqY42wmI1ERYjYBl0KN3x7adCMYy+S06nTDrCz5cf5mFASx2W7epJaD4CPTVZcNe9l3LFbg31y2kh5G0+sygw1NNA9dJaMDUE7r8q/CZaq3lf7Pj3Nzh7BMDFsywuHlvP0odXqiM0o962bCybkDTrKjS1JiucE7sWsuxVFtaOSEkUnreuviH09IUPoOmpiUiMi0RygtAtLiZSmFXNxMwaJuaK054SLdt1w9K5f8HT2x/evqVxZN82ZGVmom6jVuz7JXMmw8LKBt37DGGf9+5Yz7a1c3BiosCdm5dx8cxR/G+IMC4WuRzs3b4OlarWgrmlFYtFcfzQLiTExaJaTeVihbr1GaJGk77Ys3IsnNwD4OQZiCvH17F2qlBLWJ7dK35lYkzjzqPEAZJjIoTlycvLYSnFI9+GMNGGMlQRz+9fYO9Ore09EB/9Bse3zWRvX0XHVAa5Py2cMx1ePv7w8fXHwX07kZWZgQaNm7PvF8yeCksrG3zXV+jGuXv7Rnj5+LEMMTRRun3zGs6dPo6Bw4R9imjbsRvmzJiE0gHlmJUOxci5ee0KJv8tyXynjAv3ctGlng7CYvLZUqusNsi47+ZT4TVC35Fly9Ebws+XHuRhUGtd1C6rjcdv81DOWwtONprYdSFLLOJ811iXXWdrj2YzEUNk8ZPB3hKrLs/pW1loEaSHmATKepWP1rUMmIBxVyp+y8guRuzzuTvCieOpm1no08IQb9/l4nVkHhpU1oOeDlgWK1Gg4Er+OsytigQTCxNNlso7O1eAh69UT1CPXkpDu/omiIrLRXRCHjo1MmHizq0Qid/lb/+zws1HGThxVfjG+cilVAzqaIFX4Tl4EZaDZjWMoKerUSCYsZ0lWRjoFtmF69SNTLSooY/oeGHdtK1tgESqm6eSCfRP3Uxw52k2zt4WtsfJ65no28oIryOpbnLRsLI+yOP48j3h99S20hY+Iii7V1yS4saq17I3Ni8dDxfPMnDzDsC5I2SZloFqddux7zct+Y2Ne626/yQs9/5VOLJjEXr98A8sbZyQnCh8663Hxj1DGJmYs0UaylplamYNW8fCAw23atcVi+dOY9eUt28pZjVD1xSlFScWzv4LllbW6Nl3MPu8Z/sGePr4s4xVFHfqzo2rOH/mGAYMHSW28qFFGnJTt7CwhJOz6gxE1Rr3w/7Vv8KBxhqPQFw7uY6lri5XUzgu7Fs1BiYWdizduGjsE481udlISYjCOxpr9A1haesmIzSQkBMY1O6DMnqp032hZ/N6+HP5ZpT2cEEZLzdsPnoOGVnZaF1XaInwx7JNsLUwww9dhWVbsecYynq7wdnOGqlpGVh/6AzLRtWufnWxiDNmwVo8eR2GuaO+Z0JPbKJQiDQzNmTikTIojs3Btb/C3j2AZaS6cUrYToE1hO10YM0Y5r5G6cZFbRMbKWmn1MQoRIWGQEdP0k5VGvXBhhndcfnwMvhXbo7I1/dYsONm3xX+/Hz1ST7aVtdEZLwGy6xZ1U+TPZ9QFiuCvqPYZKeDhdfk9af56N1QC9X9NfAsXIAybppwtBRmuxJx5XE+OtYgNyoNvI4SsBg5vk4aLEaOKnrVq4wJmw6jjKs9AlwdsPHcTWRk56BdNaH4N37jIdiamWBk6zrsc5da5bH1wh3M2H0K3etUxNuYBKw8cRU96lYs8jELSz9u5C257gw9nGFazh/Z8UnIDI2E318/Q9/JDsH9fmXfv/l3K9yG9oT/9NEIXbsL1vWrs3TjN9oMEh/j1bw1KLd6BhJvPUDSjXtwH9EH2kYGCF2nOOOoiHbtO2LunH/g7eMLX18/7Nu3B5lZmWjUuCn7fs6sGbCyskaffv3Z5x3btrBtKWMVjTU3b17HmdMnWZwcdi6GRiwWzprVK9jzuI2tLR7cv4czp06g/wDheMXhfNNCDgkR58+fZxPg5ORkFvCYJtMUbJcm7hQ3hSbqdJP+6aefFAatpSxFlPmJLHroeCRMkMghYteuXSy4L4kuFNSKJvCibEHkmkMZhmh7mqBTjBUShMj6QQTtS6IMCR0U+4aC2tIEnwSkX3/9lYlQZH5HZSdxSOSyQ+UYPHgwE0OoXCRGkNUGWbuIIFchyrRE25BrE4lOhw8fLuCGowj6HYoZQ/FuRGJGUSjKOROUlYtEKBJMevToIfMdiRZ0DKobUZBlKoso89XHQGWhvkB1StZAlJqbRC2KoUT1R3VPIhwFkSbLJXJhI0GNslMRdA7kMkbBjalOyeWM6pdSviuC6pisjYYMGcIst8iFjEQxUZBpgkQqakPKQEW/SWKcKAW5CBLm9u3bx8Qtaj9qF+oH5CZYHPhWaIGM1HhcO7qQTZ5tnEqhzaAVLHgtkZoQIfM2IS05GltnSfzB75xZzRYnryro8IMwE9r9S8IUzbsXy/arRt2nsRTTyiBxxUg/F40qaTP3jsg4AdYcy2FmxgS5cUh7S5LlzbYzuWhcSQtNKmshLlmAjSdzEZUg3Ii2tTHXQAUfHWamTK4mYbH5+PdQDkutXBjlqjdHWko8E2dSkmLh6OqP/41ezkQXggQZClwn4uqprcjLzcGmBT/KHKdh+6Fo3OEH9vej22ewc8V48XdbFo8qsI0igmo3QnJSInZuWoHEhHi4efpg7KQ5YhP62JgombLQRGfN0lmIi4uGrq4eHJ3dMGzURHYcgvoZBcQ8f+owe1g3NjVjE6WJfy9hKWe/lj5DBFRrwdrp9N6FSE2Kgb1rKfT6eYXYjD4pTrY8KYnRWDZRUp7LR1ezhVKN9xsrLE9mRipO7pyD5IR3MDAyR+lKjdGw409K06eLqFmnAZKSErF142rWTh6e3vh98kypdoqWaSca//5dMhfxsTGsnWgiOfKX39lxRFAqZRJ2yN1q9fIFcHRyxehxk1GqTOHBEilNuJEB0KSyNgsCTpOI1YezxAGQ5a8pssjZciobTavooFlVbZZifP3xbPE1RYF3y7gLLXZ+7CQrsC0/kMXiUani+PUs6OpooEdTQyasvgjPxcKdaeI4NoSNuRaMDSQrbj3JgbFhBlrVNGBBkckNi/YRuYfl5Arg7azNUpsb6msw8eJ5WC5mbUpV6kIm4uCFVCbC/K+dOQz1NfH0TTb+WRvH3DFF2FpqwcRQYqV07X4mTI2S0LGhCcxMtPAmMoftIx+omNKRxyfn4b5UhitVHLuWCV1dDXzXzIidB53Dgm0pMnVjbaEJY+ZmJuTm42wW9LhNbaoboYsa7VPYeauiQlBzpCYn4OjORUyUcXLzZ5Y2Ju9dqxJiZce9Sye2sXFv7TyhsCOiacchaNZpGD6VmnUasrFv28ZV7Jpy9/TG+MmzZMc+UhjfQxOvlUvmiMc+J2c3DB81gR3nUylTpQXSU+Jxbt8CNvbZuZRC95Erxa5VSfGydUNjzcopQgGMuHp8NVtcfaui92hJ5tCXIZeRHB/BslV9COp0X2hSvQISklOxbNdRxCUlw9fNCQvHDBKnFCeRRlNqHE5OS8dfK7ezbU2NDOHv7oxVE0ew1OVEdEISzt8WWtH3GD9L5reWjRuGyqWVZ9EqTe2UGo8L+4XtZOtcCl1GrITR+3ZKVtBOlIVKxLUTq9lC7dRzlLCdSBDqMGQRzu2Zg4uHFsPc2hmNuoxDQLU2hbbTo7f0IikfdctqskDGUQnA5rN54jh9poY0Dkuu2bBYYM/lfJZivH6g0DV8+4V8xEg9Zj8JE+DQzXzULK2JphXJlQnYcTEfocq9hxjNKvojITUdSw5fYu5Rfs62WDK4E6xMhS+b3iWkyLSTvYUplg7phJl7zqDzjLWwNTNGz7qV0K9R1SIfUxVmlQIQdEpyLZSeNY79H7p+N+71/w16DjYwcBHGsiQyXocx0ab07N/gPrw3MsPe4f6g3xF74qJ4m8gdR6BrYwnfiSOgZ2+D5OAQXG/1PbLlAiDLU1ybPsgAAObDSURBVLtuPSQlJ2LThnXMxcrT0wuTJk8Tx12Nofu39FiTmYmlSxawjFR0PTm7uGDUL2PZcUSM+XU81q1dhVkzpyM1JYVZ0vbq3Q/NWwgFzf8CH5IpmvNpaAh4bX+1kIhEwgQJVZTx6XNAxyELJsp+VdJQAGLK7iSdFp3zeVl0WL0u/4hI1bGkipMqZdVL53YzL2g9WFJcfl5ygY8VYa08eUqxE2AbBXVhw+lPS3P/uUlOKpqAURykJCpP/V0SGJmotjIrTto2kU0QUNI4m8jGqChJgiNtoS6UsVc9CS1ufJIk7nclza402eDIJU1opHK3z+JmtMVaqBOnWs+EuuDz+ATUBV8v1daA6kzbIU+gjuxb+ukxKtUN9ZqpcFRC8X7IgoSyOZG1i8j9qShuU4VBx6OU1xQfpiREnPT0dCxbtoxZ9VAgT7JsIRcmcm3jcDgcDofD4XA4HA6HI4QLOV8Z5OZDrkkUNJcyMlH2J2vrT8+OQGIQuTGR2w9ZwkhDbmn0O4oYN24cWz4VcnMgFzCKLUOmiRT8mFzYKF4MoSgtuwjKsFW7du1PLgOHw+FwOBwOh8PhcD4OHri5+OBCzlcEBd29dUuSjeBzoirVOAVbpngyiqCYN58rJbqyIMKKsj9JQ+5lHA6Hw+FwOBwOh8PhfAtwIYdTKOoglFBAaQ6Hw+FwOBwOh8PhcL51uJDD4XA4HA6Hw+FwOBwO55MQ5KtXIpX/MpJcexwOh8PhcDgcDofD4XA4HLWGCzkcDofD4XA4HA6Hw+FwOF8J3LWKw+FwOBwOh8PhcDgczichEPCsVcUFt8jhcDgcDofD4XA4HA6Hw/lK4EIOh8PhcDgcDofD4XA4HM5XAnet4nA4HA6Hw+FwOBwOh/NJ8KxVxQe3yOFwOBwOh8PhcDgcDofD+UrgQg6Hw+FwOBwOh8PhcDgczlcCd63icL5hzIw1oE68yMiBumCsB7XCQCsT6oKjtXqZzZrqq0+/sct6A3VBQ6Mc1Al1MrfOyVKfPkNkaKrPWOxskgt1wvftUagLT4y+g7pQKuww1In7jm2gLpgjD+qEW4D6jDdRBrWhTvg8bgJ14Zl/Y6gLvjlP8LWiTvf6/zrcIofD4XA4HA6Hw+FwOBwO5yuBCzkcDofD4XA4HA6Hw+FwOF8J3LWKw+FwOBwOh8PhcDgczieRL8gv6SJ8M3CLHA6Hw+FwOBwOh8PhcDicrwQu5HA4HA6Hw+FwOBwOh8PhfCVw1yoOh8PhcDgcDofD4XA4nwTPWlV8cIscDofD4XA4HA6Hw+FwOJyvBC7kcDgcDofD4XA4HA6Hw+F8JXDXKg6Hw+FwOBwOh8PhcDifhCCfZ60qLrhFDofD4XA4HA6Hw+FwOBzOVwIXcjgcDofD4XA4HA6Hw+FwvhLURshxd3fHvHnzSroYHM4HcfbsWWhoaCAxMfGTjvP69Wt2nLt37362snE4HA6Hw+FwOBxOcWatUsflv4jaxMi5ceMGjIyM8F+hb9++bHK/d+/eki4K5yvoGy4uLoiMjIS1tTXUgZtnNuHKsVVITYqBnYs/mnafACePQIXbxoQ/w7n9CxD55iGS4sLRuOtvqNaor8w2C8c2YN/JU6leDzTvOVFlWWqW1UGDCjowMdRARGw+dp/Pwtto5f635by00Ly6HixNNBCTlI+Dl7MR8iZPZptmVXURVEYb+noaeB2Zhx1nsxCbVLRB/tzRrTh1YC2SE2Ph5OaLzv/7De7eZRVue+nkTlw/fwARoc/ZZ1fP0mjdfYTM9hsW/45r5/bL7FeqXA0MG7+s0LIcPrAXe3ZtQ2JCPNw9vDBgyHD4+pVSuO2VS+exc9tmREaGIy83Dw5OTmjbvjPqN2wi3qZdiwYK9+3zv4Fo36mbyrJcObEJ5w+vRmpSLOxd/NGm93i4eCnuM9fPbMedi/vxLuwZ++zkURpNO/8ks/2DG8dx7fQ2hL9+iIzUJAz/azcc3RSfm7J2Orlf0k5dqJ18lLfTtXOy7dSG2klu+3dhL7F341w8e3QL+fm5sHf2woBRc2Bp46CyLLuOnMSWvYcRn5gEL3cX/PR9L5T28Sr0HE5evIo/5yxB7aoVMX3sj+L1tTr0Vrj90N5d0aNdy0KPW720FuoGasPYAIiMF2D/5RyExSjv/2U9NNG4sjYsjDUQlyzAkeu5eBIqvAY1NYAmVbTh76LJrrnMbOB5RD6OXM9BSjqKROta+qhVTg8Gehp4EZ6LLcfTEZ2g2se+bgU9NKmmB1MjTYRF52HbyXR2LYvo0dQQpdy0YWasiawcAV6G52L32QxExRfuu9+5qRkaVjOGkYEmnrzKwsrd8XgXm6tynyY1jNG6nhnMTbTwJjIba/bE40Votvh7OyttfNfKAv4eetDW1kDwkwy2TVKq6vJ0aGCMepUNYaiviWdvs7F2fxKi4mXHM3kaVjVEi1pGMDPWQui7HGw4lIyX4TnsO2tzLcwZZatwv4VbE3DjYabC744e3I39u7ewscbNwwv/G/QjfPxKK9z22uVz2L19A96xsSYX9o7OaN2+K+o2aCbeZtHcqTh36qjMfuUqVsXvk2ejKGw9dxPrTlxFbHIqfJ3tMLZLE5R1d1K47b4rwfhjw0GZdbraWrixYKz4c1xyKubtPYMrIS+Rkp6Jij6uGNulKdxsLQsty9WTm3DxiGTsa/XdeDgrGftunN2Ou5f2I+r92OfoXhpNOv0ks71AIMCpPQtx8+wOZKanwNWnAtr0mQhre/ei1c1Zqpsr7Jyobn7t2lRl3Uxcf6BA3Vxf+Jv4c3pmNubvPY0zwU+QlJYBJytzdK9fBZ3rVCq0LCcO7cDhvRuRlBAHF3cf9B74C7x8yyiumytncGDHGkS9C0Mu6zcuaN62J2rVbyGzzemju/H6RQhSU5Lx19yNcPP0RVG5fGIzzh9ajZSkWDi4+qGtivvUtTM7cPvCPkSFPRffp5p1+VG8fV5uDo7tXIAnd88jLiYM+gbG8AkIQvOuP8PUQvE1Js3ZI1txfP86JCfGwdnNF137/woPJfeoCyd24dq5gzL3qLY9fpDZfnCn8gr37dDrRzRpK/tMJs/+g4ewY9cexCckwNPDA8MGD4S/X+H1eubceUz/ZxaCqlfDpAnj2Tpqu7XrN+L6zVuIfPeOze0qli+H/n17w8rKCkXh0IF92L1rBxIS4uHh4YVBQ4bB189f4baXL13Ajm1bEBkZgdzcPDg6OaJd+05o0LCxeJuMjAysW7MSV69cRkpKMuzs7NG6TTs0b9laZTksa1WG56j+MKsYAH1HW9zsOBRR+0+p3qdOVZSeNRbGpX2QGRqJ59OXImz9Hplt3Ib0gOfP/aFnb4Pke4/x8McpSLpxv0h1w+GopZBjY2NT0kX46qCbfV5eHrS11aYZ1Yrs7Gzo6uria0BLSwv29vZQBx7eOIwT26ej+XeT4ORRDtdPrsOWef0xZMpRGJkWvAnnZGfA3NoZpSo1Y/sp4n/jd0KQL5l8RIc/w+a5/VCqsuTBXhHlvbXRrpYuE1revMtD3fK6GNTGANM3pSM1o+DE091eE72a6uPQlWw8fJ2LSr46+F8LfczeloF37ydwDSrqoE45HWw+mckmpc2r6WJwGwP8vTkduarnR7h1+Sj2rJ+JrgMmsEn+mUMbsXjqYPwxbz9MzArWzbNHN1GpZnN09isPbR09nNi3Gov/Gozxc3bD3NJOvF3p8jXx3dAp4s/a2oX324vnzmD1iqUY8sOP8PUvhf17d2HShF+x+N91MDe3KLC9sYkpOnfrCSdnV2jraOPmtatYOPcftm2FSlXYNms27pTZ5/bNa1g0fxaCatZRWZZ7Vw/j0OYZaNfvT/aQe+noeqz+ZwBG/XMYxgrq5WXIDQQGtUBrnwqsXs4fXInV/3yPH6cfgNn7esnOyoC7b0UEVmuG3av+wIdw69JR7F43E90GTmCiGbXToqmDMXG+4nZ6+vAmKtdqDg/f8tDR1cOJvaux6K/B+J3ayUpYnph3oZgzoQ+CGrRHy65D2UN7ZOhz6BQyxpy6eBWL1mzGL4P6orSvF7YfPIafJ8/EloX/wMLcVOl+kdExWLx2C8qV9ivw3b5VC2Q+X719D38vWYW61YXtqIpAT020qq6NPRdzERqdj5oBWujfXBeztmchTcEc3tVWA90a6ODYjVyEvM1HeS8t9Gqsg4V7shGVIICONuBkpYFTd3IRGSeAgR7QOkgHfZroYtFeiZChDBJj6lfSw7pD6YhNykeb2voY3sUYk1YmK70eK/nroFMDA2w+no7XEbloUFm4z58rkpGSLhwX3r7LxfWH2UhIzoehgQZa1dTHyK4mGL8sCQIVmm2b+qZoXssUS7bGIjo+F12ammPcAFuMmhmBHCVaTlA5Q/RuY4mVu+KY2NKitgnb56d/IpCcmg89XQ32+W1kDiYvi2L7dG1mjjH/s8XvC98pLU/L2kZoXN0IK3YnIiYhDx0bmmB0H0v8tjBGaVmqBeijR3NTJvi8CMtB0yAjts+Y+TFISctHXFIehs8QlkEECUUk/Nx7lqXwmJfOn8K6lYswcNgoePuVxqF9OzD1j1GYv3wzzBSNNcam6NClN5xcXKGtrYNb1y9jyby/YWZmgfKVqom3o7+H/igRDHR0ina/PnrzEWbtOonfuzdHWXdHbDp9HUMWbsW+PwfDykTxC0FjfT3smzhY/FlDQ/ZZ6sflO6GtpYl5gzrD2EAP609dw6AFm7B7wiAY6ikv1/1rh3Fkywy06SMc+y4fW4+1swbgxxmHYazgfvnq8Q0EVm8BV+/3Y9+hlVg763uMmHoApu/HvguHV+LqiY3oOGA6LKydcXL3AqybNQAjph1k45Mqjt18iNm7TmA81Y2HE6uboQu2YN+fQ2Bpqrxu9v45RGHdELN2ncCNJ68xtV9bOFqZ48qjl5i+9QhszExQr5zyyf7VCyewefU89Bsylok3Rw9sxT9/jsA/S3bAzNxSYb9p07kfHJzdWb+5e/MiViyYAlMzCwRWDGLbZGVmwLdUOVSr2RCrFk/DhxB89QgObpqB9v0mwtU7EBePbsCqGQPxy8xDSu5T11E+qCXcfIX377MHVmLljAH4+e/97D6VnZ2J8NeP0KDdYDi6+iM9PRkHNkzD2jnDMGLKDpVluXnpGHaum40eA8ezZ4nThzZh4V9D8eeCfTA1s1Ryj2oGL79yrA8c27sGC6YMwR9zd8Hi/T1qxoqTMvs8vHMRG5ZOQoXqjVSW5ez5C1i+YhVG/DCUiTe79+7HuAkTserfpbAwN1e637uoKKxYtQYBZWQF3aysLDx78QI9u3eFp4c7UlNTsWT5SvwxeSoWz5+Dwrhw7ixWrliOYT+MeP9ssxt/TPgNy/5drfDZxsTEFF269YCzswu0dXRw49pVzJ87C+bm5qj4/tlm1YpluBd8F6NGj4WtnR3u3L6FpYsXwNLKCtWq11BaFi0jQyTfe4LQtbtQeefiQstu4O6MKvuX4+2/W3G39y+wahCEssv/QmZkDGJPXGTbOHRujlIzf8ODYROReD0YHiP6oNqhVThbphmyY+IL/Q0O55Ncq44ePYpatWqxC4SU1VatWuHFixfiifMPP/wABwcH6Ovrw83NDdOnTxffKP/880+4urpCT08Pjo6OGDFihFLXqsePH7PfoeOULl0aJ0+eZK4nIisGkSvK7t27Ub9+fRgaGqJcuXK4cuWK+Bhr165l5Tx48CD8/PzYNp06dUJ6ejrWrVvHftPCwoKVgwQR6UHol19+gZOTE1OSq1Wrxlxo5I977NgxlCpVCsbGxmjWrBmzqCDoPOn4+/btY2WkRXp/ZVy+fBnly5dn51y5cmV2rtLuNiI3niNHjqBSpUqsHi9evMjKS+dga2vL9qV6Iwsn+fJKIzq2CCoz/fby5cuZdQjVVZcuXZCUlFSkfkG/17hxY2ZRYmZmhrp16+L27dvi73v06IGuXbvK7JOTk8O2X79+PfuckpKCnj17sjqnPjR37lzUq1cPP/4oeROtCmrPKVOmoHfv3jA1NcXAgQPZeqqj2rVrw8DAgJ0b1VVaWpp4vyVLlsDHx4fVnZ2dHesjIgqrW3lE9SgN9Wsqm6q+oci16ty5c6hatSprZ6qPsWPHsjcdIqhuqGxjxoyBpaUlE4Lo+J/KtRNrUKF2F5Sv2RE2jt5o8d0k6Ojq4+6lXQq3d/QIRKPOv6JM1ZbQUiJAGJlYwtjMRrw8v3cGFjaucPOtqrIs9crr4MrDHFwPyWWTxh1nspCdK0C1UorFSxJoHr/Nw5k7OYhOEODItWyExeSjdqCOeJu65XRw/GY2HrzKQ2RcPhN0TI00UNazcEH09MH1qNGwI4Lqt4ODsxe6DZgAXV0DXDmj2PKu74i/UadpNzi7+8PeyQM9B/8JgSAfT+5fk9mOhBtTc2vxYmisfIIvYt+eHWjSrAUaNmkOF1d3DPnhJ9ZXTh0/onD7soHlUb1Gbbi4usHBwQmt23WEu4cnHj2UvAWysLSUWa5dvYyAwPKwd3BUWZYLR9ahSr3OqFynA+ycvJmgo6unj5vndyvcvtvQmQhq1INZ2Ng6eqLD91NYloMXjyTjd8VabdGw/TB4l1H+kKWMU9Lt5OLFBB3WTqcVt1O/kcJ2cvGQa6cHknY6sGUhSleojfa9foaLRynY2LsgsEp9hcKQNFsPHEXrxvXQsmEdeLg4YfSgvtDX08PB0+eU7pOXl4/Jc5ehf7cOcLQr+JLDysJcZrl44zYqBpSCk33hb4FrldXG9cd5uPU0D9GJAuy9mIvsXKCyn5bC7WsGaONpWD7O38tDTKIAJ27lIiJWgKAywu2zcoBVR3Jw/2U+s2oLjRZg/6UcONtowqwIRrYNK+vjyJVMBD/PQXhMHtYcTIO5sSbK+0quWXkaVdHHpeAsXLmfLbyGj6UjJweoUVYy/lwMzsbzsFzEJecjNCoP+y9kwtJUE1Zmqh97SITZfTIJNx9mMOFl8dZYWJhqo0qAodJ9WtY1xalrKTh7Iw3hUTlYuSse2TkC1K9izL73c9eDraU2E4fIQoYWOq6nsy4CvPWVHpdEmP3nUnH7cRZCo3KxfFcis/ipWEr5Ps1qGOHszXRcuJOBiJhcrD2QxCyS6lY0YN+TaERWQNJL5dL6uP4gE1nZihWlg3u3oWHT1qjfuCVcXD0wcNgv7Po+feKQwu3LBFZAtRp14OziDnsHJ7Rs2xluHp54/Ej2jbOOjg4sLKzEi7GxCYrChtPX0KFmebQLKgcvBxv83r0F9HW1sfdysNJ96HHH2sxYvFiZCtuGeBMdj3uvwjG+W3MEuDvC3c4Kv3drjszsXBy9+VBlWS4dXYfKdTujUp0OsHXyRpu+f7L75S0lY1+XwTNRrWEPOLiVgo2jJ9r3lx376FmZxKB6rQejVMWGsHf1Q6eBfyMlMRoht08WXjenqG4qoF2N8lJ1o4O9V1S4bauoGyL4RRhaVw9EFV93Zo3TqXZF+DrZ4cHrgla20hzZtxn1mrRDnUat4eTqyQQdPT19nD8pawEkolTZSqgcVB9OLh6wc3BG09bd4OLujachknYl65z23b5HmXKqnx0UceHIWlSt3xlV6grvUyTo6Ojp48Y5xW3Vne5TjbuL71OdBgjb6vnDq+x7A0MTDBi7CuWqN4eNowfcvMuhbe/fEf7qIRJiI1SW5eSBDajZqANqNGgHRxcv9Bj4OyvLZSX3qP4/Tke9Zl3F96hegyeyvvLk/nXxNmYW1jJL8I2z8C1TBTZ2zirLsmvPPjRv1gRNGzeCm6srRv4wFHr6ejh2XHl/oznT3zNno1fP7nCQewlJz/Azpk5B3dq14OLsjFL+/vhhyCA8e/4c0dExKIy9e3ahabPmaNSkGVxd3TD0h5Hs2ebE8WMKty8bWA5BNWq9f7ZxRJt2Hd4/20iu3ZCQR8xCh7Yla5xmzVvCw9MLT588UVmWmGPn8XTiPETtK/zaI9wGdkPGqzCEjJmB1Mcv8WbJJrzbdQweIyUWUR4/9kPoqu0IW7cbqSEvcH/oROSlZ8Klb0f8V6DnJ3Vc/ot8sJBDE+Cff/4ZN2/exKlTp6CpqYn27dsjPz8fCxYswP79+7F9+3Y8efIEmzZtEk9gd+3axSbmJBQ8e/aMCQlly5ZVOkC0a9eOiQnXrl3Dv//+i/HjhSZ78tB6El1oAuzr64vu3bvLTHZJtKFybd26lYlQNGmm8h4+fJgtGzZsYGXauVPyJprEKBKEaJ979+6hc+fOTKihcksfd9asWWz/8+fP4+3bt6wcBP1PIohI3KGlRg3Vk5Hk5GS0bt2a1QkJICRI/Prrrwq3pQn933//jZCQEAQGBrKJPNUvCQS0r7e3N5o2bYr4+A9Tdp8/f87a7sCBA6yu7ty5g6FDhxZpXxJh+vTpw0STq1evMmGkRYsWbD1BAg0dl5R5ESSEUT1SexDUry5dusT60IkTJ3DhwgUZMagoUJuQoEdlnzBhAhMZqR06duzI2nLbtm2sjNTGBPVjEkMmT57M+iydd506EuuDz1W3IoraN8LDw1n9ValSBcHBwVi6dClWrVqFv/76S2Y7KhfdNOk6+eeff9h5UN19LHm52cxFyqOUpEwamppwL1UD4S/ufPRx5X/j/rX9KFezo4yYKI+WJuBsq4mnoRKRlaYZz8Ly4GaveNLpbq8lsz3x5C1tLxzqrEw1mCuG9DbkCvImKp9Z86giNzcHoS9D4Fe2ungdjX9+Zavh1VPlEwhpsrMymauBobFZAcudsd/XxeSRrbF1xRSkpqiOuUQi6IvnTxFYvpJMWcqVr4Qnjx8VWg56AAy+exvhYWEoE6DYrJxcKG7duIpGTSRm7YrIzc1GxOuH8C4TJFMWrzJBePu8aDGfcqhe8nJhYCRbLx9Dbo6wnfwDZdvJP7AaXha1nbJl24nubw9un4edoxuz1Pm1f13881sPBF8/rfI4OTm5ePriNSoHlpEpS+XA0nj4RGgir4i1O/bC3MwUrRrVLbSs5K51+VYwE4oKg64pJ2sNPA/Pl7mm6LObreL+72anKbM9QcKOsu0JfV0N5AsE7NpShbWZJnN9CnktuWfTPq8icuHpqK30HFzttRDyJlfmHEJe58DTSfE+ujpCkScmMY9Z6CiDxBYSbe4/yxCvy8gU4PnbLPi4KbaE0NICPJ10cf+pxJyJxJL7zzLF+5ArFa3LyZUIJTk5ArbOz0PxcW0stJho8/CFxEomI0uAl2HZ8HbRVVoWd0cdPHwp2Yd+49GLLKX7uDtqw81BB+dupSsda14qGGsCy1fG08eqRQ7h7wtw/+5NRISFolRAOZnvHt6/i/49W2PEoB74d/EspCQX/uIoJzcPIW8jUd3PQ6o8Gqju74F7r8KU7peelY1mvy9Ek3ELMHLZdjyPiJE5JqFH5mVSxyQXozsvwgod+2iskx/7Qj907Hs/1iTEhDEXLelj6huawNkzEKHPg4tUN9X8Zeummr877r1ULrpkZGWj+fgFaDpuPn5cKls3RDkvZ5y99xRRicmsPck6h8SvoNKeKsfh1y8eo0y5KjJ1Q5+fPynchYR+52HwdUSGv4FfmQr4VKitwl89gk8Z2fuC90fcp+Tv39JkZqSw5xoDQ1OVdfP2ZQhKBVaTKUupstXw8sm9ot+jVJSF3LXu376Img3bqT6nnBwmsFSQegFJZalQvhxCHj9Wut+mLdvYC+LmTSWu2YXNHalejIyNCi3P8+dPUa58RZnylC9f8SOebSRzzFKlSuPatSuIi41l25B1TkR4GCpULNw98EMwr14esaclL6SImBMXYVFdWL8aOjowq1gGsacuSxcasacvw7z6p/dzzrfHB/vk0IRYmtWrVzO3qEePHjExgybwZLVAFyxZ5Iig78hioFGjRuwtDFnmkLWBImgiShNwEl1E7iZTp05lFh+KJsYtWwpjAkyaNAllypRhgoS/v794UKBJsJeXMB4BWVuQ+BIVFcUsacjahyx6zpw5wyxGqJxr1qxh/5PVkOg3aIJP66dNmyY+7rJly8THJWGAJtEEHZesP8iao6juMps3b2Z1tmLFCrEVEk3mBwwYUGBb+h1RXdDgSOdHVjfNmzdn6+gYVIc08R89ejSKSmZmJrOOIUskYuHChaxuZ8+eXeh5NGggG1uDxDca5MmqhKy2SPwgwWHPnj3o1auX+JzbtGkDExMTJviQKEHrGjZsyL6n+ha1QVGhcowaNUr8+fvvv2ciksiqh/onCXtkMUT1Ru1M5aIyUjmoz1aoUOGz162IovYNshIi66FFixaxfkH9OSIigol7f/zxB7uxESTkTZw4UXxutD0JrIquFfpNWqTJydaTMdVOT01gLlDyLlRkIh737iU+B0/unGR+/+VqCgU8ZRgZaEBLUwMpci5U5Dpha654EklxdESuFZLt82FqqC3+nkiV2yY1PV/8nTJSkxOQn58HE3PZujE1t0JUxCsUhX2b5sLM0gb+UmJQqfI1Ua5aQ1jZOiH2XRgObFmApdOGYtTUDdDUVCxY0YSHxAVzC1kzY3JzCAt9q/T309JS0b9XFzZ+UR8aNOxHlK9YWeG2p08eh4GBIYJq1lZ5Tukpiaxe5E3TTUytEFPEejmybRaLKfAx1jfypKa8byf58phZ4V140cpDcXCk2yklKR5Zmek4vncVWncbjrY9f0TI3UtYMesnjJy4Cj5lFNdhUkoK8vLzYSnnQmVpboY34UILTnmCQ57g4MlzWDNHVrRVxpEzF2FooI+61RWXQRpDfRJCNAq4JdJnGyXXFMXRUbS9sYHi60Vbi2JQaSP4RT6z1lGFqbHwGMlpsuIKXcMkuCosj6FwXFC0j72VVoE4Ou3rGTBh6V1cHuZvS0WeipdyJJwQSSmyGyWl5om/K3AORlrQ0tJg28jsk5IHR1uhVdGzN1nM2qVnSwtsOZLIrEN6tDBn+1koOS4JXMLflitLWj6zWFKEiaEmOya5c8mWPx8O1oof9+pWNER4dA6eh+aoGGvyCrjC0FgTHvYGqsaaQX06IDcnm41j3w/5GeUqSCb1FSpWQ7UadWFr54CoyHBsXv8vpk4cjamzljJXY2UkpKYjL18AKzk3IXKpehUVp3AfsrCZ9F0r+DjZIjUjC+tOXkWfWeuwe8JA2FmYwt3eCg6Wpliw7wwm9GgOA11dZvUTlZiCmCTJy6eijn30OTayaGPNse2zYGJuC6/SwrGPRBzRMWSOaWqNlCTV1gxK68bUGK9V1M2fvVqL62b9yavoO3Mtdv0xiNUNQbGCJm86hKa/LYC2piY0NDXwR8+WqOQjecaXJyU5UWG/MTW3RISKfpOelooR/2sp7jd9Bo9B2fISweNjkbSVdYH7Qkxk0Z5tDm+d/f4+JRHZpMnJzsKRrXNQLqgF9A1lrZoU3aNM5e9R5nSPel2ksuzeOA9mFjYyYpA0V87uh76BISpUEz5Pq3qJTM8S8i5U9Dk0VLH49+DhIxw9fgJLF84vUlnJW2PlmnWoV7cOjAwNCymP8NmGvCWkIZeqsNBQpfvR83rfXt3EzzZDho2QEWkoxs6iBfPQt3d3Nr5oaGhi+MifEFBW8Yusj0XPzhpZUcJrWAR91jEzgaa+HnQszKCprY2saNnrMSsqDkZ+yoVRDuezCTlklUITSbIAiI2NZRccQRNiCuJKE0hyYyKLA5ocN2kiVGvJqoVcTDw9Pdl3ZG1AFiiK4ruQZQRNYqUnuspEH5rIiiD3EyI6Olos5JBVj0hsIch1hqyEaEItvY72Ie7fv88sgsi6RxqaAEsH6ZI/Lv226BgfA50znQuJOIWdM7ldiSDBiwaumjVriteRUEb7ksXOh0DimkjEIYKCglj7UtkKE3JIGPv999+Z+Eb1QHVI1jbULwhqZ7JEISstEnJo0CX3IrJ6Il6+fMnOQ/qcyUWL+tKHIF03BFmzkCUO/a4IUuPpvF69esX6K4k3on5JC1kIUft+zrr9UOj4VP/SFitUDrJoCgsLY20l3/8L64fk5khipzTt+k5Eh36f7o71Idy9uAveAXVgYi6JEfMtQCIAxW4Z+edqGfGsck2hSEg4ufqywLx/Dm+BZw9vyFj/fA5ImJm7aAUL/Hcv+DZWr1gCO3sH5nYlz6kTR1CnfsMvHmfq7IEVuHf1CAaMW1do/Ifi4PgeYTv9OEnSTiKT3MDK9dGglVCIJhP3l0/u4sKJ7UqFnA8lPSMDf81fjjFD/wdz06K5mRw6fR5NagdBTw3igVHg4x4NdZhQsfdiQWGgamldFoRYxOKdyifJn4NrD7OYpQ6JQo2r6mFAWyPM3Jgijr1Tq4IRBnSSTDT/XvXx93BVUGyauRti0L+DJZrVMmFWMpfupuFlWBZEiTSCAvXRr43k7frsjQn40pABSvVAA+w7+/nbgcaamQtWIzMzAw/u3sK6VYtgZ+/I3K6ImnUlcTvc3L3g5uGNH77vikf376Bs+c9zPYko5+nMFvFnL2e0n7wcOy7exg+t60FHSwtzBnbCnxsPovYvc5hQSFYttcp4seeFL8W5gytw/9oR9B9bcmOforrpMGkZdl64jWFt6rF1W87ewP1X4Zg/pAscLM1w+/lbTN96FDZmxqhe6vNOPkl8mDpvIzIzMvDw3g0WY8fWzom5XZUkZ/avQPDVwxg0XnFbUeDjTQt/Zv2lfV/VCRw+laN7VrMYOz//uVJpv7l8eh+q1m7x2fsVPdfPmD0HP474AWZmhbuAk4fEX9P/YXaTI4ZJ4jB9bugF6fxFy1i/CQ6+w2Li2LNnG6EV4IH9+/DkcQgmTJwMG1s7PHxwD8uWLISlpRXKV5BY/3A+D/n/0QxR/wkhh8QXmviSZQJZS9CEOCAggCmuFStWZJNjiuFCMW1o4k4WOOS2RMIMCQK0niwayGVn5syZzGKDJscfi/S+okmvSFyS/160jaJ1on1ookxq7a1btwq8FZIWfxQd40ve8KX50OxepE7Ll40Eis8JuVXFxcVh/vz5rH+QPysJEdQvRJBlDFnCkNBAfYAGXhJOvmTdUHsOGjRIJh6TCBJDaJJKLlMkQB0/fpyJlBRnRlUcnJKua2lU9WV5fvvtN+a+Js3O67I3eUNjC2hoaiEtWfZtQWpyHHsj+KkkxoXjVchldBq6sNBt0zIE7O2iidybf7KcSZazqJF+Ky9vWUNvqUXbi6x1jOWOYWyoiYhY1ZGOjU0t2BvClMS4AibMFNdGFZQ9iQLo/jDhXybUqMLazhnGJhYsuK4yIcfE1Iz1tcQE2cleUmICi22jDNrHwVEo1np6eSPs7Vvs2r65gJBDDznhYaH4ZWzhQYYNTcxZvaQmydZLSnIcTAqpF8oeQpOZ/r+uZhlEPgdUd6yd5MuTVLR2Or53NYb/IdtO7Jha2rB3kc00Ze/siRePlbscmpmYQEtTE/GJyQXcoazMC5rEh7+LRmR0LMZOmyteRy5KRN1OfbF50Qw42UsE0OBHT/A2PBKTfh6GopCeCXZNCa1ppPq/gUYBKzURqRnC76Vh28tZ6ZCI07ORDststeJQtkJrnODn2cxtSoToPQ4JLclpkuuPrmHKRKWwPOnCcUFosSO7j7yVDrlpZWbnswxY9LtzRpqz2Ds3Q4SFu/koHc/mSKwUdbSF52lmoonEFMmxKfvT6wjFfmJU7rw8AdtGGjMTLSQmS45x72kmRv4dwcYjKn96pgDL/3BGdLzQpenO4yy8CIstWBZjTRmrHDMjTbx5pzjSMVkfUllM5Sx25I8hokoZA+jpaODSXYkrmeKxRgtJifEFxhpzC6tCxhqhQODh6YOwsNfYs2ODWMiRh0Qe+i3KdKVKyLEwNmRCS1yyJM4dEZeSBmslwXzlIeHG39kOoTGS8bO0qwO2jxuAlIxM5qJkaWKEnv+sQRlXhw8e++izvOWHPBcPr8aFQyvQb8xqFgdHhGg/OgZZ6oiPmUxZllRn7VNaN8mpsJaLe6Oqbvxc7BH6PuhqZnYOFu47gzmDOqNOWR+2jjJhPQmNYtY7yoQcE1Nzhf0mOTG+0H5j5+DC/qZsVBGhr3Bg59pPFnIkbRVb4L5gUkhbnTu0GmcPrmTxcBTdp0QiTmJcBAb8tkalNY70PSpZ/h5VhGeJ4/vW4die1fjxj+Vwdlf8LPHs0W1ERbzGgJ9noDAoniTVeUKirDs3fba0KBjoODLyHaKiovHHJElyBtEzb7PW7bD636VwfP9SnYk4f/+D6Jho/DPtr0KtcYTlET7bJMg92ySyZ5uCgY5F0D6OUs82oW/fYsf2LUzIoRfxG9atxrjf/0SVqkILJg8PT7x88QJ7du/4rEIOWd+QVY409DknKQX5mVnIjk1Afm4u9GxlrwE9OytkvZPtmxzOZ4+RQxN1EmPI8oLcXyjQr/zFRoMCuSiR0EPxSCi+iCieCE3cSQgi1xaaOFMcGrKAkYesMEJDQ5mVh4iPnVh/KORWQ9YkJDZQPBTp5UOyCpFAIB1AuTDonKkupF1finLOZBVEv0WxZaSFA9qX3LMIcn0j1yXpAL/SQXVFkPUMue+IoFg3LAZIEaxi6PdJLCFLK3JvIyGHLLakoVgwJOhRvyALGbLSEgkRZBFDf0ufMwVafvr0KT4FEhfJ7U++LWkRWRqQtRAJjhRjhqx3KPDw6dOni1S38lBdv3tHWUgESuu6KH2Dri26PqSPQ+Ug9y9nZ9WB65RBbULXp/Qi/7aGghU7uJXBqxCJjy8F93sdcgVOXp/uvxt8aTdz2/IpK3zTpwpygQiLzoevi2SCRFMbH2ctlsFKEa/f5cHXWXZCRfu/eSecxFCWKprsSW+jpyOMA/L6/TbKoCwaLp6lZALgkmj29ME1ePjKxn6QhjJVHd31L4aOWwI3L8VpV6VJiHuHtNREmFoof6Cja8XL25dZ1UiX5d7d2/DzV9w3FUGWJoqExpPHj7DjUzDAwqBAzY7uZfDi0VWZsrx4eBWu3orToRLnDq7E6X1L0W/0v3D2DChymQstj877dpIKKM0sC+9fg2ch7XRk578YNr5gO9ExaV2UnNl7dMQbWForn+jp6GjD18sdt+49lCnLrXuPUMbPu8D2rk4OWD93GtbM/ku81KpSgQUypr9t5VK3Hjx1Dn5e7vDxEFroFeWaCo8VwNtJU+aa8nbUxJtoxf2f4kfR99L4OMtuLxJxKAbVysPZSFec/AhZ2UBMYr54iYwVBtv1d5O8U9LXBTwctfFSSvCRP4e37/Jk9qFz8HfXYSnGlUHveWjR0ZKIUplZAkTF5YqXsKgcJCTnoqyPxDKWUqJ7u+ox9yiF5ckDXoZny+xDv0NBjBXtQ2ILiThlvPWZ4HLzoVDIycwWIDo+T7yER+cyMam0p2SM1tfTYAGSn0ulNZcvy+uIHJSR2ofKQsdQtE/dSga4/SSTlUnVWOPp7Yv7wbdk+jB99vUvfDwTIcgXqHypERcbzdJJm1uqDh6uo62FUq4OuPbktczbX/oc6FG0eyO5Oz6LiFEobpgY6DMRh2LAPHoTiXqBvoWOfS/lxj767KJi7LtwaCXO7F+KPqP+hZOH7NhnYePMxBzp8TQzIxVhL+/BxVv5+CVdN9efvJKpm+tUN56K048rqpvn4dGwNhNaBObm5bNFUy6eHcXeEYnMiqAx093LH4/u3ZCpm4f3bsLbT3F8TEXQM1BO7qe/DKO2ovThokDFovI8L+Q+dfbgKpzauwz/G6P4PiUScWKj3uD7satgZGJeeFkovIRnKTyWClRMZaHPnn7KXX0oU9XhXSsw/PclcPNWfu1dOr2HpSd3di/82Z2ubx9vb9y9GyxTlrt377EgxfK4uDhj+eKFzK1KtFSvVhXlAsuyv22srWVEnPCICPw9dQp73iwKVB5v9mxzR6Y8wXfvfOCzjWS8oVhCVB75mIyaWlpKX3x+LIlX78KqgewLOOuGNZBwVTgPEOTkIOn2Q1g3kHLP09CAVf0gJF79PHEoOd8WH2SRQz6L5F5E8U/IhYMm/hR4V8ScOXPYehJDSADYsWMHEz8oVgrFGaHJK2WAIreVjRs3MmFHOo6OCHJ3oUk0WXnQ5JpECBKPCFXBUT8H5FJFliOU+Yhiw9C5xMTEsLgj5MYiisdTGOS+RcF8SfiiOiM3IVWWR5TViQI3U6YlqlOqWwrcW9g5kwXKkCFDWLwWylxEViZUZ2T+2L9/f7aNqM7HjRvHxBZyi6P2kIfcuqjO6XfJb5a2JauqoghYFJ+FYg+RaxPtS+Wh9lV0nhRbiAQaikskggQK+m3ReVCWKIr9Qv3oU9qcYspUr16dxTCieDlUXyTskEUQxZOhjGbk1kUBjql/UwBsGthJvCpK3cpDmaSov9B2FI+JYiuRhZr0TUxR35CHLNbIFXH48OGs7LQt1QdZ1Iji43wpqjXuh/2rf4WDewCcPAJx7eQ6lmK8XM0O7Pt9q8bAxMIODTqMEgcvjol4If47JSEK796GQFffEJa2bjKCEAk5gUHtmHVDUTh7Nwc9GumxNMlvovJQt5wudLU1cC1EOGGj75LSBCzdOHE+OAc/tDdg2a4evc5FBV8duNhqYvsZyYTqXHAOGlemwKf5iE8Rph9PThPg/kvlk0ARDVr1xobFv7OHJJbW+vBGZGVloHo9YUDB9YvGsbSkbXuMZJ/JCufQ9sXoM+JvFgMnOVEoburpG7KF4q4c3rEU5as1Ym/iYqNCWXwWa3tXlConcelTRNv2nTF/zt/w9vGDj68/DuzbhcysTDRsLLRymzdrOqysrNGrnzDO1s5tm+Ht48syUNEDzq2b13D29AkMHiabFS49PQ2XL5xDv+8lqXoLo3bzPtjx729sUuLiWRaXjq1n6cMr1RHGQdq+7FeYWtihWVehRRhZ4ZzYtRDdhs6ChbUTUhKFsR+oz+jpC9+qp6cmIjEuEskJQncXUcwJentqYl4wk5M0DVv1xnpqJy9hO50+9L6d6gvbad3CcSz9e9uewnYiK5xD2xaj78i/YWnjhKQESTuRqT/RqE1frJ47Gj6lK8KnTFU8unsJ92+dw8g/V6ksS7fWzTB14Qr4e3uglI8nth84joysLLRsIAxOPGX+cthYWWDwd12Ye5Snm+xk1NhI+Pvy69PSM3Dm8nX80LcHPoSL93PRua4Oy+YWGiNArQAtFgyYslgRXerpsGuK0o0Tlx7kYlBrXdQuq4XHb/NRzkuLBUzefSFPLOJ810gHjtaaWHcsmwkHFFeHyMgSCi+qOHUzE81r6DOrmdjEPLSpbYDE1HzcfSqZvP3Y1Rh3n+Xg7G3hdXzyRib6tjRigu7rSGH6cTqHy/ezxUGUK5XSRcirHCZSWJhqomk1fZbx7sFL1ZPCwxdS0L6hGSJjcln6cUoTTuLOjQeSYMC/D7LFjQcZOHZJGMz/0LlkDO1mjRdh2XjxNgstapuylONnb0hclupVMWIZrUhIpiDIfdtasN+i31HGsStpaFvPGFHxueL04yTu3A6RBFb+ta8lboVk4uQ1YfmOXk7DgA7meBWeg5fhOWgSZMjKcv62rNWNraUW/Nx0MXtD4S5crdp1xeK50+Dl4w9v31Is/Tilga7fSBgIfeHsv2BpZY2efYVjxp7tG+Dp488yVuXkZOPOjas4f+YYBgwV3jMyMtKxY8saVK9RD+YWlixGzoY1S9n25SsWno2oV4NqmLB+P8q4OSDAzREbz1xHRlYO2gUJJ8Hj1+6HrbkJRrarzz4vO3wBge5OcLW1QEp6JtaevIrI+CSW+UrE8dshzKKFYuU8C4/GPztOoH45X9RQEdCXqNmsD3at+A2OHgFw9izLMk6xsa+2cOzbuVw49jXpIhz7zh9agVO7F6LL4FkwVzD20fNOjaa9cXb/MljZuTFh59TuBcw6p1TFRoXXTcNqmLBuP7MwCnCn9OPXWN20DRKKQL+v3cfqZkQ7YVzD5YfOszTlrjaWzBpp3YkrrG7av68bSsVeyccVc3efgp6uNhwtzXDz2VscvHYfozoWjMUnTfO2PfDv/Enw8C4FT58yOHZgK+s3dRq1ErbL3ImwsLJF195Ci8L9O9eybe3snVm/Cb51GZfOHkbfwZLEH6kpSYiLiUJCvLDeKBgyYWZhCXMVLz+I2s37Yvvy3+BMbeVVFhePrkdOVgYq1xW21bZlY1kMnObv71OUbvz4roUse5WltWOBtiIRZ+OCHxH+OgR9Ry1h8QVF21DwahKPlNGodS+sXTQBbuweFcDSj1O/qVG/Lft+zYLfYW5li/Y9hdbkx/aswYFtS/C/H6fDysZR4T2KyEhPxe0rJ9CptyRWZGF0bN8WM+fMg4+PN/x9fbF7334WM7NpY2F8nX9mz4WVlSX69+3DXkR6uMvO24zfW8KL1pNoMmXa33j24iWmTJyA/Lx8xMcLxxkTE+NCvTDate+IuXP+Yc8rvr5+2LdvD3u2adS4Kft+zqwZ7NmmTz/hc/iObVvYtpSxivrNzZvXceb0SRYnhzA0NGKxcNasXsFeaNrY2uLB/Xs4c+oE+g9Q/ZxD6ceNvCUvSgw9nGFazh/Z8UnIDI2E318/Q9/JDsH9hH30zb9b4Ta0J/ynj2Ypy63rV2fpxm+0GSQ+xqt5a1Bu9Qwk3nqApBv34D6iD7SNDBC6TnH2tK8Ret7nqKGQQxNIimlCE3xyp6LJLlnX0ORVNBmnCSzF0SG3JMq4QxNj2o/EHMq0RBNREnQoOxNlMZKOOyOC9qWsVjTxpmOQtQa5YZE1j3QMmS8FBdml7EAUNJcCDlOKbBIDKOZPUaEgxWR1RMIGufeQaCGqJ0XQRJ/qg4QDSl9N9UNuPiR8FHbOVK8kPlDsGRK96DdJKBAFCyMRgoQzEiTIUoqsqch9SJSeWwRZqXTo0IFZ1ZAVFZ0vBd0tChT8l45HFjBkdUNBoUVZvKQhkYwCV5OAJx17RiQEDh48mP0u1QdljCLLrE9pcxLfyH2PRDJKQU4qPYmEolTo1C8phT3VB924SJDasmULsyoqSt0qsqShOqPzp8xjFByc6oHET1V9Q5TdTQTFKqJrh9qMsnBRG5J4JBI0vyRlqrRAeko8zu1bgLTkGNi5lEL3kSvFrlVJ8ZEsUJwISou6cookM8LV46vZ4upbFb1HbxCvfxlyGcnxESxbVVG5+zyXuXE0q6rLUoSHx+Rj+YEMsVuHhQm5skluGGRVs+F4JlpU10PLIKFYs/pwJt7FS7Y5fTuHiUFd6uuxt+2vIvPYMUVxM1RRqUYzFvT40PYlSEmMhZO7H4aNW8oCHhPxse9k6obip1C2q1VzZB+qmncajJZdhrKMYOFvn+Hauf3ISEuBmaUt/AOD0KrrD9DRUR3zpFbd+khKTsSWDWuYZSRZz0ycPINNjIiYmGh2fBH0AL18yXzExcZAV1cPTi4u+OmXcew40lw4dwYCCFC7nmwAc1UEVm/BAjie3LUAKUlCFwCytBGZrJMgI10vV09tFb7JXCAUUkRQuvFGHYQZ5UJun8HOFePE321ZPKrANsqoVLMZUpITcHCbVDuNl7RTgnw7HRe208rZsu3UorOwnYjy1RqyNOYUQ2fH6hmwdXTH97/MgXcp1WbZDWtVR2JyClZu2c1cqrw9XDF7wmgW8JiIio1jb7c/lJMXr7JYK41qfVgcpXsv82Gkn4vGlXRgYghExAmw+kg2c6EizI2EGZZEvI0WYOvpHDSprI2mVbRZivENJ3IQlSDcyMxIA6XdhRZuIzvKWvj9ezAbLyNVP9Adv5bF3Ht6NjWEob4GSxm+cHuqzPVoY6Ep495163EOTAwz0LqWPnOxIjcs2kfkOpmTJ4CPszYaVtZjxyShloL5Unwc+WDo8uw/k8yEj4GdrGBooIknrzIxfUU0cqT0FjsrHZgYScThK8HpMDVOQJem5iwoMrlhTV8ZLePO5GCjg+7NLZgbZ3RCLvacSsKh80IhSBmHLqSxuqHYOYb6mnj2Nhuz1sfLlIUEGXLXEnHtQSZMjJLRoaExc/eiFOoz18cXcDurU9GQZfB6IJUVSxk16zREclIitm1cxbLZuXt6Y/zkWeKxJjYmigXAFUGTrpVL5iAuLlo41ji7YfioCew4BLmVvH31AudOHWVBkS0trRFYoQq6ffd9oeMe0axyaSSkpmHJwXOITU6Dn7MdlvzQTZw2+11Cksw1ReLN5M2H2Lamhvoo7WKPdb/0Yem5RVBQ41k7TzAXLYr90qpaWQxqrjrQO1G2WgukJScwsSX1/djX55d/xS5SiXS/lBqHr58Wjn1bFsmOffXbDUPD9sJxrXaL79mkft/aichMT4arT0V2zKLEO2lauQwLerxUum6GdxfXDYk00i/HktMzMWWTpG7Iomfd6L4ydTOjfwcs2Hca41bvQ3J6BouT80ObeuhcR/XYV712YzYO79r8L5IS4uDq4YvRE+fD7P04HBcbVeAetW7ZP4h/328cnNww+KfJ7Dgibl+/gBULhIlFiMWzhBltKSV5h+6yz7TyUJrwtOR4Js7QfcrRzR//G7Nccp+KVXyfIrFGmkbth6Jxxx+QlBCNR7eFLyTnjxe+6BIxcNxaeJVWLkpWrtmU1c2BrUvZCx6ynhk+fonUswT1G0k7nXt/j/p3luxzdcvOg9C6qyT2zM1LR9n4XaVW0cMW1KtTm1nAr9+4mT1L0Jxr6uQ/xc+50TExH/RCNTYuDleuCa2NhgyX7eczp09l1juqqF23Hnu22bRh3fvyeGHS5Gni8gifbaTGm8xMLF2ygGWkon7j7OKCUb+MZccRMebX8Vi3dhVmzZyO1JQUFienV+9+aN5C9bzOrFIAgk5JnmNLzxI+k4Su3417/X+DnoMNDFwkVrkZr8OYaFN69m9wH94bmWHvcH/Q74g9cVG8TeSOI9C1sYTvxBHQs7dBcnAIrrf6HtlyAZA5nKKgISiuwC6fCLmVUDYsykglHWT4vwy5H/Xr148NsIqsWz4nJGSQeKbI5aqkIFcwEjTIMkqZBQzn09hwHmrF7XtfNvjph9Ci9sfH7voSOBurj/90SJxyd6KSwFT/y8Wh+lDKaanPGDr7smpXjOImMV55LJbiJiFGNm5RSaNnUPLBqkX80lt51qiSwPftUagLB4y+g7rQKl2SxEEduO/YBupCRErRYgIVF2b6it0hSwJPA+WZLUuCLI0vO7/5EJ75q7YyK05a5jzB10q9TrIp2NWFszsVZ5z7poIdFxeUppqCC5OFBIk3I0eOZBYc/2URh1J/kxJO4gVlWyK3IHJt+tIijrpw584dPH78mGWFIvFKlM69bVuhqSmHw+FwOBwOh8PhcNQTionGKR6+bLCNT4DcWIYNG8bSiFNac3KxonTVXyvkakPClKKleXNh+mEKkvvdd98x95yffvqJBQOWdskpSZSVnZYLFy58tt+h+DzkSkTBh8kih45Nrm30v6oycDgcDofD4XA4HA6H8y3w1bhWfe1QzBlR9i55yOKGrHDUGbKKUgaV/UtbDWVkZLB4Rcqg+D6cD4e7VimHu1Yph7tWKYe7VimHu1Yph7tWKYe7VimGu1Yph7tWKYe7VimHu1Z9Hup2uAx15NzuGvivobauVf81KFgtLV8rJS2UkFBU0mXgcDgcDofD4XA4HA6npOFCDofD4XA4HA6Hw+FwOJxPQjqbLOcbjZHD4XA4HA6Hw+FwOBwOh8ORhQs5HA6Hw+FwOBwOh8PhcDhfCdy1isPhcDgcDofD4XA4HM4nwdOPFx/cIofD4XA4HA6Hw+FwOBwO5wOhzNQ9e/aEqakpzM3N0b9/f6Smpqrcfvjw4fDz82MJfVxdXTFixAgkJSV90O9yIYfD4XA4HA6Hw+FwOBwO5wMhEefhw4c4ceIEDh48iPPnz2PgwIFKt4+IiGDLrFmz8ODBA6xduxZHjx5lAtCHwF2rOBwOh8PhcDgcDofD4XwSgnz1zFqVlZXFFmn09PTY8imEhIQwEebGjRuoXLkyW7dw4UK0aNGCCTWOjo4F9gkICMCuXbvEn728vDB16lR89913yM3NhbZ20SQabpHD4XA4HA6Hw+FwOBwO5z/J9OnTYWZmJrPQuk/lypUrzJ1KJOIQjRo1gqamJq5du1bk45BbFblmFVXEIbhFDofD4XA4HA6Hw+FwOJz/JL/99ht+/vlnmXWfao1DvHv3Dra2tjLrSIyxtLRk3xWF2NhYTJkyRaU7lkIEHA6H8wlkZmYKJk6cyP5XB9SpPLwsX0d51Kks6lYedSqLupWHl+XrKI86lUXdyqNOZVG38vCyfB3lUaeyqGN5OB/Pr7/+Sum3VC4hISGCqVOnCnx9fQvsb2NjI1iyZEmhv5OUlCSoWrWqoFmzZoLs7OwPKqMG/fNh0g+Hw+FISE5OZuaJIpPAkkadysPL8nWUR53Kom7lUaeyqFt5eFm+jvKoU1nUrTzqVBZ1Kw8vy9dRHnUqizqWh/PxxMTEIC4uTuU2np6e2LhxI0aNGoWEhATxeopzo6+vjx07dqB9+/ZK909JSUHTpk1haGjIgiTTPh8Cd63icDgcDofD4XA4HA6HwwFgY2PDlsIICgpCYmIibt26hUqVKrF1p0+fRn5+PqpVq6ZS9CMRh9y79u/f/8EiDsGDHXM4HA6Hw+FwOBwOh8PhfAClSpVCs2bNMGDAAFy/fh2XLl3CDz/8gG7duokzVoWHh8Pf3599LxJxmjRpgrS0NKxatYp9png6tOTl5RX5t7lFDofD4XA4HA6Hw+FwOBzOB7Jp0yYm3jRs2JBlq+rYsSMWLFgg/j4nJwdPnjxBeno6+3z79m1xRitvb2+ZY7169Qru7u5F+l0u5HA4nE+CTAInTpz4WSK//9fKw8vydZRHncqibuVRp7KoW3l4Wb6O8qhTWdStPOpUFnUrDy/L11EedSqLOpaHUzxQhqrNmzcr/Z6EGemwxPXq1ZP5/LHwYMccDofD4XA4HA6Hw+FwOF8JPEYOh8PhcDgcDofD4XA4HM5XAhdyOBwOh8PhcDgcDofD4XC+EriQw+FwOBwOh8PhcDgcDofzlcCFHA6Hw+FwOBwOh8PhcDicrwQu5HA4HA6Hw+FwOBwOh8PhfCXw9OMcDofzGXn79i1cXFygoaEhs54SBIaGhsLV1bXYy5SdnY3o6Gjk5+fLrC+JsnDUm5ycHDRr1gzLli2Dj4+PWpRHR0dH4XexsbGwtrYu9jJxvg5ovHv+/LnCsa9OnTolVi4O52uGP09wOOoDF3I4HM5HsX79enTt2hV6enoFbvJbt25F7969v8myeHh4IDIyEra2tjLr4+Pj2Xd5eXnFVpZnz57hf//7Hy5fvlxAVCKhqTjLom4sWLBA4XqqF319fXh7e7PJnpaW1hcvy71791SWhR6Q5fv2l4JEE2XlKQm6deuGnTt3FhBGo6Ki0LBhQzx48KBYy5OWloa///4bp06dUjiZefny5Rf9/QoVKhSoC2Xcvn0bxQmNJ2vXrlVaN6dPny62sly9ehU9evTAmzdv2HgnTUmNfVQvyupm9erV+BZRpz4jfd88c+aMwvL88ccf+FZRp+eJkh6HFcGvb05JwIUcDofzUfTr14+9uZcXLFJSUth3xSmeqFNZRA818qSmprJJeXHSt29faGtr4+DBg3BwcCjyBPBL0b59e4VlkBZPaPLl5+f3xcsyd+5cxMTEID09HRYWFmxdQkICDA0NYWxszB7GPD092QM9WVh9ScqXL6+ybUhcIaFy+fLlxdKHvvvuO6xatYo9KKuDhdv333/PyiPi3bt3qF+/PsqUKVPs5aGynDt3Dr169SqRa6pdu3bivzMzM7FkyRKULl0aQUFBYgHj4cOHGDp0KIqbkSNHskl5y5YtERAQUKLjzeDBg1G5cmUcOnRILca+SZMmYfLkyaxM6lAedRFQ1KnPECtWrMCQIUOYpZ+9vb1Meejv4hZy1KWd1O15oqTHYXW/vjnfDhoC+VcVHA6HUwQ0NTXZW3EbGxuZ9cHBwWySRRYo31JZfv75Z/b//PnzMWDAACYISD+MXbt2jVl3XLp0CcWFkZERbt26BX9/f6gD9CC4d+9emJubo1KlSmKrgcTERDRp0oS11+vXr9lDa82aNb9oWbZs2YJ///0XK1euhJeXF1tHbhiDBg3CwIED2e+TNQg9zJNFyJdk3759+PXXXzF69GhUrVqVrbt+/Tpmz56NiRMnIjc3F2PHjmVizqxZs/ClGT58OLNyI9cqaifqR9LMmTMHxQWJbWQZ1bx5c/a7ERER7JouV64cs7aja784ob5L4sCX7p9FnczQpGHKlCky66nPkBtncb8Fpskv9ZsWLVqgpKE+S+MJicPqALXTP//8wyae6sAPP/wgFlAUTTxJ6P7W+gzh5ubGRFAaj9UBdWkndXueUKdxWB2vb863A7fI4XA4H2XaTwu5NtAbGmnB4tWrV8w65lsry507d9j/pI3fv38furq64u/ob5p4/vLLLyhO6E09xRFRF0gUIYubRYsWiSfg9IaR3sqamJiwiTm9SaeH6IsXL37Rsvz+++/YtWuXWMQhaNJHQknHjh2ZaTY9mNHfX5qpU6cyAbBp06bidWXLloWzszMmTJjARB16iB41alSxCDnkrlSxYkX299OnT2W+K+43jSTOHj9+HLVq1WKf6W0wlW3Tpk3FLuIQZL1laWkJdWDHjh24efOmQosqejNc3EIOjXPqIpxUq1aNCbPqUh5y861RowbUBRprt2/fXuICijr1GZFVZufOnaEuqEs7qdvzhDqNw+p4fXO+HbiQw+FwPsq0/+7du2ziSW4o0g9l7u7uxTL5VbeykAsOQa5cNCk3NTVFSTNjxgyMGTMG06ZNY8KAfNDY4i4juceQRZL0BJz+JgsQegiictIbyNq1a3/xslAcI7J0kYfWkesO4ejoyNzzvjQk/NGbYHloHX0ncr+iMhdnX1YXyLXtxIkTrF80btwYGzZsKDHTdbJ+IfeKdevWyVjdlQQGBgbsepIPSk3rituNkyChkcY+EmpL2rWAxhQqD13Lisa+wMDAYree2rx5MxNm1QF1EVDUqc8QJOKQcEwvFNQBdWkndXueUKdxWB2vb863A3et4nA4HwXdQMnVoyQmDOpcFnVCJJgoyqBVEgE/6S0atVWbNm1k1u/fvx99+vRhb0MpoCK5F9HfXxIyVadJHrlWkWWXyKqK3OLIcogsPw4cOIBx48aJxZQvBf0+WWyRq5fIkouyNVFZyD2EykWTc7K0ICuz/zrUTxRN6iieEQV9lg5AXRxuk/IBhsnSg64hEorlJzPFGWCYYhhRbAbqJyKXPHLhJEscmlCQO15xx8AiEZDelFP8Ivm62b17d7GVRZG1FrVhSY19ZHVILkQkINEiXzfF6a5IkNsmWR2WtICiTn2GmD59OmsLuj8oEitGjBjxTbaTuj1P0Jj84sULtRiH1fH65nw7cIscDofzUdDEW11SUapTWdQpm4K6WVaQ/3j//v2ZOFKlShW27saNG+wNnyggNQUwLI4gtmQdROWhGDCihy6yxiEXPVFgXbLwogfpL83ixYuZuEWuVCJLARKP6MGYBCVRvymuALYUg0bVpOFLB9icN28e1AnpAMPqBAk1FJCbLBo2btzI1pUqVQpr1qxBly5dSiRuBU3M1QF1EzwpExxZ1RHymdZKYoJOrqt0fzhy5EiJCijq1GcIEtNp3Kf7EC3y7VTcQo66tJO6PU+o25isbtc359uBW+RwOJyvPhWlOpWle/fuKrMp0JubbxVqBxK56O0iBacm7OzsmBsExcUhSwvKUkRv/kjUKA4eP34sjgND2bKKI2OWIsiFi+K+SJeF4glR7KDi5qeffpL5TNZB5L5ID6gkmpJwwOFwvl7IBVgVJAZySh7eThwORxVcyOFwOB8FZQug4ML0VliRYEGuIt9iWdQtmwJlhCILk5CQEPaZ3uqR6GVmZlai5UpOTmb/q0MsIdFtkL85U82ff/6J1NTUYgm4LA2Z0NOEhf4nEcnW1pa9oSZLu+JOQU4WMGRFZmVlVeA6oyDMxWlxJ0IdLBHlM409efJELEjKZxMsLqi/kHWXaOyjYK0kpEsHOC8JwsLC2P/FJVZ/DahLn5GG3xfU/3mCsmhJl0XkJl2S8OubU6yQkMPhcDgfiqGhoSAkJESgDqhTWdzd3QWPHj0SqAM3btwQWFpaCpycnATt27dni7Ozs8DKykpw69atEitXdHS04MKFC2yJiYkpsXKsW7dOEBAQINDT02NL2bJlBevXry+Rsjx//lzwww8/CBo2bMiWESNGsHXqxLNnzwQWFhbF+ptnz54VGBgYCBo1aiTQ1dUVvHjxgq2fPn26oGPHjoLiRkNDQxAVFVVg/bt37wQ6OjrFWpanT58KatWqJdDU1JRZqIz0f3GTmpoq6Nevn0BLS4uVgRZtbW3B//73P0FaWlqxluXo0aOsv1StWlXw008/sYX+puv8+PHjguImLy9PMGnSJIGpqam4nczMzASTJ09m36nDWEx/f8t9Rh3vC+rSTur2PEFjcP369Vl/oXsSLfR3gwYNSqR+1PX65vz34UIOh8P5KCpXrsweKtQBdSrLhg0bBJ06dSqxh1BpaJLXt29fQU5Ojngd/d2nTx9B7dq1v+mH9tmzZzMBcMyYMYJ9+/axZfTo0WzdnDlzvulJpzJoMuPg4FCsv1m9enXWVoSxsbFYyLl27RqbUBQXoj5CfZbqQfSZlt27dwuGDRsm8PX1FRQnNWrUENSpU0dw+PBhwZ07dwR3796VWYqbgQMHCjw9PVl5kpKS2HLo0CGBl5eXYPDgwcValvLlywt+/fXXAutpXYUKFQTFzdixYwU2NjaCJUuWCIKDg9myePFitm7cuHHf7FisTn1G3e4L6tRO6vY80aVLF/bcJ/3S7OHDh2xdt27dBN/69c35duBCDofD+ShOnTolCAoKEpw5c0YQGxsrfggTLd9qWWgCYWJiwiad9FaPJg3SS3Gir6+v0FKJHnjIyqG4UaeHdrKcojev8qxdu5Z99y1POkVvW0VLu3btBNWqVWOTiT///LNYy2JkZCR4+fJlASHn1atXTOgqLkSTKJHFi/RCIhyJOAcOHBB8q5aIBL2ZpzFYntOnTwusra2LtSzUN8hiSZ4nT54Ua78RQQIoiQLy7N27V+Do6PjNjsXq1GfU7b6gTu2kbs8TZPly/fr1AutJ4CdLmG/9+uZ8O/CsVRwO56No1KgR+5+y/JR0gGF1Kos6ZVOg+DMUPNjf319mfWhoaIkE0d21axd27tyJevXqide1aNECBgYGLMvO0qVLi60skZGRqFGjRoH1tI6+K07Ix3/79u0F1lPsgZLI4CQf74CCT1PcismTJ6NJkybFWhaKOUXt4eHhIbOeUrI7OTkVWzlE8WeoHBQjx9raGiUNxXyJjY2FukDp4Sl4uTwU04i+K04oxgoF6Pbx8ZFZT+uoPMVNfHx8gXGYoHX03bc6FqtTn1G3+4I6tZO6PU/QeCyfwYugdfKxwr7F65vz7cCFHA6H89WnolSnskycOBHqQteuXVm6bwpOK3o4vXTpEkaPHs2yaxU36vTQ7u3tzcQTSoUuzbZt2wpM/r61Sac6ZULp1q0by2i2Y8cOJsrSQzr14V9++UWcsv5bTWs9Y8YMjBkzBtOmTUPZsmULTGyKO5B4UFAQG//Wr18PfX19ti4jIwOTJk1i3xUnAwYMwMCBA1nwaemxj+rs559/RnFDAfcpW9+CBQtk1tO64gzGr25jsTr1GXW7L6hTO6nb80SDBg1Y4PItW7bA0dGRrQsPD2cZF+Vf6H2L1zfn24FnreJwOJz/KJTNhh6yli1bhtzcXLaOJntDhgxhacD19PSKtTz0gEXZfuQf2imlNb21OnnyZLG+6aQHU7LmEmUYo4fSU6dOsQf59u3bF1tZyNJl7ty5LOuaoknnhAkT8K1mBKE+PGzYMKxdu5ZZ1lF2OvqfUrPTOkpZX9xQH6FFUaao1atXF1s5yFJKUVadkrBEJCg9fdOmTZGVlSWevAQHB7Nr/dixY8WaYYzqgKzZZs+ejYiICLaOJnw0Ho4YMaLYMxGdO3cOLVu2ZJnERALFlStXmDXD4cOHUbt27W9yLFanPqNu9wV1aid1e56g66ZNmzZ4+PAhXFxcxOsCAgKwf//+Ys8YpW7XN+fbgQs5HA7nozh//rzK7+vUqfNNloUmV6omCcU9uSLozR2l4iUo9a6hoSFKAnV7aCehggQUkVhRqlQpjBo1qtgFC3WbdJJAQZYwZ8+eZa5NorSz9evXx9atW0skNTCZ9FP/ofTn1D4l8XacIEsBEt4qV64MBweHAm2zZ8+eYp08qKJu3booibFm06ZNePz4sfia6tmzJ3MFKSlSUlLY/yXhTioNXduLFy+WqZuhQ4f+v703Afdq3N//n3MMRc6RMmSWISGKpFAIDZITKmNIhgqpDCXRIEmhKGkwFyWUokQTyhQKTTRQQkol6UTkWP/r9f7+1/6t/dm7XW19nrV2635d1+fqs9d2nf2cNT/3837ftwsrCtJ6L07aOZOU50LSjlPS3id4biJkRc+bsM0+7de3SA8ScoQQf2s1OEp0UuNTsEjSWMaMGZPr540bN5qfx7PPPmuTQEqT00zSXtqTRhImnaxI05LCKjDHB+bNm2erwLQeUM7uG1aDaWti4kBVTlwg3vTq1ctdccUVsY1BiG2B7sVFAx0nIcSmkJAjhCgUa9euzVewoA2ke/fuXvuUkzSWTTFs2DDrs88UerY1F154obWc4I/B94IYNWqUSxO//PLLFv+3vv1FkgRmx6x0VqlSJdf2jz76yMyOqc7xOYlp1aqVCaGwYMECd+ihh9o2zI5pR/MJbQ7sBwSlJDBt2jQ3aNAgE97wEWKfDB061EyZq1evnvW/TxvDOeecYy0WfC8IWiGyyQknnGAtMHvssYdVTxRUyTZz5kyXbWbNmmWtHiw08L0gjjvuOJcWknTOhM+F8H6/uWdE2p4LSXqfwH8G3yuqkTK9aDKhkjXb6PoWSUBmx0KIbZJsA7Vq1XI777yz+XpQnpzGsWyKatWq2UuIj30RTmB4+fLdlpPJ5l7Ufb600ya0uf3hy19kcxNN35POpCaCdOjQwVoJaPOqW7duznZK6Lt06eJdyLn22mtNlI3LtyjTz4PKIFbnOUdovwiFbQyQ8WbwkdK3fPlyM18tKLHPxzXVoEGDHJ8Ovsd976tUqVLOvuE748lv7dSXn1FSBJQknTOA8EciFePZ1DPCp+9UUo5T0t4naHfjXoeQw/dNwRh9CDlJu75FOlFFjhBim0L5L/4ReFnETVLGgjkhE9Lx48e7+fPnuzSRX9tbfvh42dmcp4hPfxHa7JKahMYkmKqbzEQQXqKZ9Pj0gTn44IOtkg0hlHYzRB0qchYtWmQVGFtTZbUtICmFljNWWPlkCl69e/f2NhbEQFJaSO+K7huqEZkIMskQ8fHNN9+Y+Sn3Nr5v7jz3cS8OJ54F3ZfTNvHkuYCxMS2bSfCd0nEqGiTt+hbpRBU5QohCkVlKiibMqhbpBaxOpHUsTHSjq1aMBd8TDAGfe+457xGdlDuHhrUhTH5ZCZ0yZUrWx+C7gmNbv4RjVoi57Z577rlNx1IYcQZhhRXYEiVKuGxCZCp/55BDDsmTCOL7HF65cmW+Eezr16+PZXWYe014T8GINIrv8SAK52fkziq6z/a3EAQu/JUy02vwN8Ik22dcPILWxx9/bK1wUdgvCIC0omWb6OSNiR6JdJn+TqT/vP/++14metF7cVLuy0k4Z6LPBVoSuefllwTHPdAHSTxOSXmfCOGZfNttt+UxWmbR7IEHHnCdOnVK3fUt0okqcoQQfyudKfMWwso5Ebzly5dP5VhCL4/o2Ej5qVq1qok8Pomu7GWmEuGlgZdQEjn22GOtLSQUEeKEcvLPPvvMJoZpGktSEkEQKho3bmyeOFSdIKQw2eLnhQsXujfeeMOlFc6DwYMH23GJVuQwOUbExqDaJ0TBhy0qUVavXm3bfBvg53fvW7Fihd1XEArSum+SIqAkcb8kbTxJOU5Je59I2nFK2nhEelBFjhCiUJAgk59gQf9ymsdCsk/cRCuUmMxFWyx4oWDyy4tXUlmyZEliRKYkrXX4HAvCKD5TfOIErxfahDiPWd185JFH7DurnFvTKpcNvvvuO/v3gAMOiOXvX3fdddbqhVjN8SL+9oMPPrCV6jg8fEIfkfz2U34+Ztkg6ilCPHP073LvwwwZITAp+4aJXrYr7PLj6quvNs+pzIkn1aP8zpdAkIRzZkvGQ3t2HO8TSThOSXyf2NRxQswuVaqU17Ek8foW6UFCjhCiUCSpVDRJYwnL95988kn3xRdf2M/HHHOMa9asmbcX09B4jw/l0JkQW9qvXz8vYxFFEya8fFhtzSzvRzjwBclLVCFRYUKl1oQJE6w1BsGCn33Dvrj33nvdQw89lOO9RTXMrbfe6jp27LjFnlDbAoyeGQ+pfKR7Ub3Eyj1CDhVLvgiNu/kwlmh7ARM9hPaoUXU2Cc1zGUumqI6fEe2CHDtfhEk/jKdp06a5KivYN0ySacnwTdwCSpLOGSAUARgPImi0ZYfxTJ8+3XubdhKOU9LeJ8LWdT7lypXLtW84TtyTW7Ro4dJ+fYv0ICFHCFFoWBF/8MEHcwSLo48+2t1+++2uRo0aqR3LJ5984urUqWMvNyeddFKOASox6OEkNNvwEswLIG0WRCVTnRRCkhere5QCC7EpI2Y8CDAK33fffWNP/yHq+/HHH3dJALEGkRZhCYNUePfddy1Ba8OGDXad+4IKJcbDfQ7zZyYx3Pd22203t2rVqm3u67Q58QTBjXsffz96v0E8adiwoZexhKIjVTd45PjaB5sinGxzP0bw47kQ3Te0/1JZ5YukCChJOmcAg/DwOM2ePdvGEB1PxYoVTSBN23FK2vvEww8/bGNhYYznVFTMCs+bk08+2aX1+hbpQx45QohCgekppb2sSIQTmvfee88SbZ555hl32WWXpXIsCEeHH364TTzDly8mXMQWY7A5depUb2MpqkT9PuImjWNBvOnVq5dFW8cNrQM1a9Y0Q9IkHANSvAYOHJgn9nfMmDFmjE26ly+Y6L788st5hDZ8YJj8ZZox+/AHw88jjhaUpMOkEyEg7jaLMC2Pf6ki25SAEhUy0nTO8B5B+yZ+ZHGStOOUNFi4o9IlMzUw7de3SB8ScoQQhQLz0+uvv97ib6NQfYKIEVbGpG0srMiwupdpsExvORUOtED4NEosCJ9GiVtDGsWTJI2FpB9WXqmEiRsEUMRPKk7wYUDQOeOMM+zfI444wvt4mHBSLk9Zf2aCFC0IpKb4okqVKhaBToVQCIabtD/QzonIk1aoKCsIH6k2SSZpAopI/nFK0vvE0qVLC/w9seBCpAEJOUKIQkEv8Ny5c636JAoTLmKKaTNI41j22WcfN3ToUFe7du1c2zHe5EWH1XJfZKZkYSCMkMQqHh4AP/30k0siPgQLXgQLipkNXwRbtmzpunXrFnuLBnAujx8/PutpXu3bt7cV4DgMczcFlS4IOqzE8lmwYIFVDoWGw74gfY5P3759c23Hk4ZWng8//NBrNDu+OJhBI1pjdkz1Em0gJNr49OuJpgduCp/JLbSmZN77aBGhShKBcubMmc4ntHoVtG98xKEnkSSdM5CfB0wUnxHbSSNJ7xNJO290fYu4kEeOEKJQMJnEDDVTPCGy2HdsdJLGwurZNddcY349ockdbV74WFx66aVex7JmzZo824hsRpxgPL7Z0ijVQYMGmSCW7Rev/OJCeRnld+GL4IABA5wv2A/5mQuHolI2W2VCs0/g7xNrzfVDxUdm+TqiQRyTCCqF+LdkyZI2IY96NfiClrNzzz3X9k3oxYDxMuLf66+/7nUs/P/HdwtDaBg7dqx5cD3//PPeRRwYNWpUrskMEz2qE6kqCFtFfHueRPnll1/MkPSCCy5wvmnTpk2un8N9Q+JPHPfipEyEk3TOACJoFMaDjw/33jgSKZNynJL2PpF5fYfnTehHmPbrW6QHVeQIIQoFE1weXpjORQULPGnoMW/evHkqx8JknAc3Php44wATYV52MEjNFDHiAEPmJk2auC+//NLr38UQMT/xhIhOtvl8KeUFmeqoTDHgm2++McPY9evXexsLL8Ocu0Rq55dY4mO/UMmxJTAen6vSd955p3v77bftpZgWyrC1ikqUzBViX1D50r9//5zrh3Hhj4N/ThxQnYQ3F1HxVAPGbU6dybBhw9yIESPMRyhuMLI977zz3JIlS1wS4Dzifvz00097/bujR48uUEBhMSJOknTOAGbmmImzQOOTpB+nON8n8mPcuHHugQcesGdGmq9vkR4k5AghCg1mwkS5hh40TGgQMRo0aJDqsQAlx1999ZV9p5Q/GmcaN6wwMhFmhdonmxJPaKNCSPBRmh1WniDwkSaRX8wsghNCoC8w6KbChDjp/FKiMleJkwJtTYgX2az+4H+b8wX/K8zMM71p0kYYv5vf/QaROJoek5TWSdoKqOwK49rjhIQxhJz8qgvi2jd4K/m+FyddQEnSORO2aZNCmZRrKinHKc73iU0dJ56XPhdiitL1LbY/1FolhCg0lKjHUaae5LGsXbvWBIFSpUq5Y489Nmc7L4BM1n2mYbz66qu5fka3pyLm0UcfzUn3SluUatJiZsMX4RkzZuQxyE46VC4x9mx6GXG88MRhhRWhlmMUVuXwiUPYwXMLw+P82uAy06yyEb9blMD8GT8hjKp9kulhFN77qFjCUygpYEjNsyIpEJdMcEAaz5mCoH0yCYbDcR6npLxPQKYwEo6Fyqk4TPCLyvUttj8k5AghCgXGnkxiMP6MElY0kNCUxrFccskltuJLq0WUF1980V6EfPponH/++bl+RkihugFDRybFvsfBpL9OnTqbjFL1wVtvvZWomNlQEFm1apUravgo6EVY43PzzTfnVG/16dPH3XjjjXbN+za1xPMAL6f8jpePNrg4fDoKWy3E+bFu3Tqrenvuuee8joVzJL/KLvZfhw4dnG9CMTu6b5YvX26G1Y899phLAnEIKEk6Z4Cqv/wEAtpjkmL+HpfQlZT3CcAnLb+gAjwR8dvzTVG4vsX2iYQcIUShYCLVrl27POIJ6TI9e/Y0ESWNY+Fv5WcGS/VAx44dnU8yqwXionPnzvYvgk1SolST1LPOOcr5e99991kVV6a5cBLEprjghZiqHCpy+NAaw2osbRdU5viGdKrGjRtbfHW2Dbm3BNo3OZf5F2ESrymSzTDIJoLct3gSncyE4gn3Zd9+RlT5JYnMSXC4b3guxFGJlxQBJUnnDOy+++65fmY8Rx55pMXZZyZRpuk4Jel9Irogk3neEHgRrfhN6/Ut0oM8coQQhYKqCtoLMtsqeIFmksXLRhrHUqJECYsgjrZVAW08vJziZZF2NpfO5AN66DGfJu0sv7H4jAsNPWbyW2H0ZXac1Jh4JjL4ZFCVE7ZUYezLimwcIKohLOF7FTe0nNEmRFsD0ez4g3EsOK+pIKCsX4j8IAggSQKKyB8dJyFEQagiRwhRKDDWxLg2cxJHGbLvFZEkjQVDRKKb+/Xrl2s7KVaVK1fO+t+PxkhvDt8x0klIZwq59tprbSJ8xRVX5GswHOfqYtqhbQD/Byq37r33XjtGSalKatSokVUGJUHIwRyb/cM1j6gWQqsDvhU+QEDfUhDVfbbFbC72OttsjcGp7/ObGPa4SNI5k3TiPE5Je5/I9OgpiGx7lSX9+hbpQRU5QohCcemll5pQQmpCWI78888/W4kp5f14wqRxLKQdnX322a5KlSpm7AtUfeDjM2HCBKsmSGOMdNLSmajoIKrUt0nj9gQvp9kwO+YcIeKba3dTkfVxQUUdrVWsiufXBhd6+fiqRKTSr2zZsrmqo4jWppwfU+ZsQ4UA1/HmXiV9CLX4XiWptTLcNwXhU8ROioCSpHOmoCS4/PCRWpWU45S094ktTUf0dd4k7foW6UQVOUKIQvHggw9a5OTBBx9sRm/ApA7fCJJB0joWhAESLh544AETkHbZZRd72XryySe9pCkkubojSelMvLwnKU0C4ZFzhPYYwN+E6qVMz4Ykka11ICLNR44c6erVq2d/g5jzTYkSPtvxYPjw4SbIUi1EZU70RZ7vPoUcxEhELoScKLR++TJCTZIXTZJ8r5J4LyYGOQkCSpLOmSQmwSXlOCXtHE6SR0/S9o1IL6rIEUL8LZ+R559/3laCQ8GC6pjMVeq0jWVLwMeiRYsW3rw+mAzDAQcc4OKCKiXMLatXr+7iBqNIKrieffZZM46ME/xMSPPivKU1D6jgIp0E0eCEE05wSeTbb7810YWqmW0JrYmYCv/555+JW+ksU6aMiTVUlW3pCnG2uO2228xc/aWXXrIY9pkzZ1qLKalafEKT8TRDasz8+fPtO6a1VFKllW+++WaL/1sWRUQ8FIXjlIT3CSGEhBwhRJY599xz3RNPPGGtNHGTpLFkqy0lcwULDw2iQTGMBVowbr31VkvQ8j0RpfT6rrvuSkQ6E5VbJP3wCCRNK3MsTIp9QbsdaRuPP/54jqcTIgY+PpguY2SbbZLmL4JBORMaBNlJkya50qVL5/vf+WzHA6q4ENmS4JGDaTiJfRiiImhx7vDvZZddZtu2tcC2JXBNUeEQVpYdffTRrnXr1t73F8I+YuCQIUNyVvLZHwhc+JfFId4Wxaq7NJ0zIVxDo0ePznWc8FyJ43pKEkl7n8Djjmrs6Hlz++23Z719fVPo+hZxICFHCFHkk200lvzp0KGDvVh07do1xwuG+OYuXbq46667znXv3t35JEnpTOyTgvBZzUAlDu0wmS1n8+bNcyeeeKKXpLOovwjH45VXXrEXUP4+0BLHiyqCj88WFiqmLrnkEjM0TwJt27a1qo4777zTJYWlS5e6OXPm2OQKgdJHC2d+vPnmmzbhpTUkvN/gGcZ97rXXXnO1atXyNpbmzZubAIjpc/TeRzUV4xgwYIBLe9VdEgSUJJ0zsGjRImvp/P77762CC6joOvDAA81TLQ5xKQnHKWnvE1TU8szieRQ9b3huIWIjZqf9+hbpQEKOECKrpE08SdJYaHshLSszwYGWohtuuMFeVn2voBUE8dJpJPRyql27dp5JDhUEtMv4pH379mbqybkTrkIjsnHOUDWF/5NvEJKiE5m4XowRAqjyoBKIaqHMSi7fSXBhZQ6+I0zsfKf0RUFEYjJD22gU2tCYzPiscttzzz0tfp24+kxfi4suusharnyShKq7JAooSTpnIPTlok079FBbvXq1a9KkiS1EIOak8Tgl7X3iqKOOsmRDhPXM+y/XWPisSOv1LVIEQo4QQmSL3XbbLfjqq6+CJJC2sRQrViyYP39+nu1ffvllULx48az+bbHltGrVKjjggAOCF154IVi6dKl9hg8fbttat27tfTx77rmnnSOZsK1UqVJex7JixYqgZs2awT/+8Y9gjz32sA/fzzzzzODHH38MfHPGGWds8sM4fbJ+/fqgWbNmwQ477GCf8H5y0003BT169Ah8w/1mwYIFebZzD+J3Ptlll12CefPm5dk+Z86cYNdddw18w/32iy++yLN97ty5NlbfVKpUKWjfvn2e7Ww7/vjjU3nOAOfGrFmz8mz/7LPPghIlSqT2OCXtfWLnnXcOFi5cmGc72+I4b5J2fYv0EK9TnxBCiKxB1QCtBZmwzbe3CLAqVdDHJ6yuUm2yqY9P6POnRJzqG/x6+DRt2tQ1atTI9ezZ0/mGlcQvv/wyz3a2+U4OwecEv5y5c+dalRAf2oh++eUXrwlR0YqOTX2i8buYgWZ7X9HqwMo86VmkaIWcffbZbsSIEc43tJzh+5UJ23zHx5988snWHhlNO6PNgbYQfucbKtlogcvPMJzqTN9QsXDNNdfk2Y6nBy2daTxngBZO7jeZ0La48847p/Y4Je19gla3yZMn59lOOyW/S/v1LdKD4seFEGI7pVevXmbwzMtNOHkhGp2Xi9dff937eDLbHDL9cnx65NBLH2Xjxo3mU4Mny+b8c7Y1TBAeeeQR16NHD/NDANpk4krTwnuAyQNjCfv9SUei/SHqpeODN954w85fSulDaK3q379/nla0JMEYs21mjiErgk21atVyXUeYbIbnkU/wyaDdgVaCU045JacNBDHylltu8ToWridadkjVCSeZiF4IXrSr+Obiiy+2awrRNrpvMGclXdE3oYCS6afkW0BJ0jkD9evXt/HgBRO995EwmdlSlKbjlLT3CQyWEfLZD9HzBn8crv20X98iRcRdEiSE2L5JWzvTlnLOOecEy5Yty/rf+f7774M777wzuPDCC+3TsWNH2xYHP//8c67PypUrgwkTJgRVq1YNJk2aFCSB559/PvjPf/4TpJn//e9/Qc+ePYP99tvP2pj48J1tf/75p/dr9tNPP82zfebMmcG//vWvIKn4uNdQsh/+jejfow3k3//+d+Cbv/76K+jdu3ew//7755w3fH/44Yftd76h9Wzw4MHBLbfcYp/HH388+PXXX4M4+P3334Obb77ZWkL++c9/2ocWkDZt2gQbNmzwPp6uXbsGJUuWDO6///5g6tSp9qEdj2333HNPas+ZNWvW2P2fcXCswuN1/vnn2zMrrccpie8To0aNCk499VRr9+XD99GjR8cylqRd3yI9yOxYCFEoaIVh5SHTXJO2jPfff9+ddtpp9jNVBi1btnQlS5Z0cZOtsdDmsaX4jNguKmCCzOorhrZxw8owJrZhvGq2oJWK1UPOh81Ff/uI+97cuR3XedugQQNLyxo+fLiZbQKmmpdffrnbY4898lRWJQUfZubcYxs3bmztZ/y9WbNmubJly9rPCxcutGqmuAjbU9RWkBsS6JJQdcerP0lIREkvW7bMtnF9UUFApUNmsmDazhnSq0LDXKoBMbKNgyQeJ5H861ukBwk5QohCgY/IDz/8kKe8l4QHtvlskwEmLvhU/Pjjj3m8KTp16pR1v5UtfaHyuV+YyO22226uevXq9jPtKKQqhK0pTISTAN4rxFxnWzzZHHho4Dsyfvx4i5zNJrQo9e3b1yYt+OEUdP74jPuOCrJ4r/BSSpQr42QigaDDOeULyvZpacAjJ/Q+YFuFChXcq6++aq0zaRVyiP4955xzLFEHUZDIbXwzENIRRytXrux8Xz+8UoaTl2+++caENu43vtvgaJEkuYpWEGjXrp0bPHiwjQVR8OCDD3ZxgkCKpxIR19G2wTiIU0BJ0jmzqef17Nmz7XyJ+3kZt9CVpPcJngE8M8P7/0cffeSGDRtmY6E1Lm6SdH2L7Zy4S4KEEEUTSo/zS40h1cB3ywPl86S27LPPPkHFihUt6SH8+Eh2ePvtt3M+zzzzTFCmTJngjjvuCMaMGWMfvu+77772O59UqFAhGDdunH0niYOy3w4dOgTVqlULmjZtGvjm888/z/WhBWT8+PHB6aefbmXRPqE0PUxB4sPPnEOcuxyzNLNkyZKgfPnyluASTUOidLx58+bex0OLBS14ffv2tc/EiRODpOOrjXPRokXBtddeG1SpUiU46qijgssvvzzf1B0f1KpVKxgwYEBOi8ree+9tyWskujz22GNex1KuXLlg8uTJ9v3999+3NrRBgwYF5513XnDBBRcEvmncuHHQr18/+0571xFHHBHstNNOwY477hi8/PLL3sfDGGg9i17zffr0Cd58883UnjNASuATTzxh32kj5bnEuw6JVW+99VZqj1PS3ieqV68eDBkyxL7/8MMP9tw++eSTLXGRdrS0X98iPUjIEUJsFbwE86EHuF69ejk/86G3/JBDDgnq1KnjdUwHHXSQ9ZAnAWKRhw0blq/3CoKFT3j5XLx4sX3v3Llz0LBhQ/s+Y8YME718wwsx503ohRB+eAHLL7ozmyCqRT+8FCIq/fTTT4FviK1mEpPJ2rVrvUdaQ4MGDYImTZpY339UkGAic/jhh3sdS1I8rbYWJhZFdeyFpXTp0hbvDfjRHHfccea39OKLL5ow6BOEm2+++ca+t2vXLrjiiivsO+Njsucb7rcI1+GzgOuICTpiBQsOvkmKgJKkcwbw5/n444/t+yuvvGILMCxO3XXXXcEpp5yS2uOUtPcJFl6IPYdHHnkk59ggcJUtWzZI+/Ut0oPix4UQW8Xuu+9uH4RgSnzDn/mUKVPGylqfe+45r2Nas2aNeUUkAVIcaBPKhG2U//pOQ6JnG0iaCEvVS5UqtVW+PtuKxYsXmwcN//KhjJ7x0QpSvnx5r2O56qqrcn2uuOIKV7du3VjK52lh+uOPP/JsJzp52rRp3sfD37zrrrvyxO0Si44/jU/wpqhZs6bdU6JR0knHR9c6cfW03XFNJQGu5bDtY8KECeb9RNspqVpc6z6hBYQ233AstWrVsu+kVtHO45u1a9fafTdsUWnYsKG1E9H6RVuwb2bOnOlq1Khh319++WV7dnOMhgwZYi2faTxnYNWqVbYvgCSmiy66yJUrV87ivmmxSutxStr7BCmTRMWHYwkTxXiPoOU/7de3SA+KHxdCbBWhXweTuttuu82VKFEi7iGZiMNLIBGhcYOPB33jRHVGeeKJJ3I8PnxBLzsmwqeeeqqJSEQVw4IFC2LxFonblyITTHSJmQ1NLYlt5oUdUdIHmNOG4G2yfPnyXN4MvBDuv//+zjd4TOXn5fTdd99592dgIsM9h/P4pptusphXjlHVqlVdkuF4hubM2ZxYYeBO7C3nyemnn+7OOOMM+zczrtiX6EYk+gUXXGAR323btrXt+Jb5NstGuLn22mvd8ccfb/e7evXq2Xa8lnh2+YZ7PyI/kz2u6xdeeCFnEQJxyTdJEVCSdM7APvvsY9fuvvvua8dpwIABOfsLX8C0HqekvU/wrB44cKAJJRMnTnTdunWz7fi4lS5d2qX9+hbpQUKOEKJQdO7c2SUFXgbvvvtu9+GHH7pjjz3W7bTTTrl+T7qDL/r06WOrMRjmhpNNXnpYlRk5cqTzyaOPPupuuOEGW8njhTQUBRgb1SdxgAnrgw8+mCOeYE5IAke46uiLTz75xNWpU8ftsssu7qSTTrJtvXv3dt27d7cX5hNOOCHrY6hUqZIZNvI588wz8/yesfXr18/5hpVWklIwhwXGhxE113w4IfYF++iRRx6x1BbMjTH15VwJV8mppNprr72yOobNpYrllzDmQ7RFHAaqpEgR5NpiP2F6zEQU4c0nmMpjjM1knPP55JNPtu1cTwgqPsF8laoyTFG574aTO5LxLr30UuebNm3aWNIalUIHHXSQCW7AceOZ5ZukCChJOmdCE3qqcLh+uO+dffbZtn369Oneq0aTdJyS9j7Rs2dP2ycPPPCAVdRWrFjRtvOMCJ/nab6+RXpQapUQolCsWLHCKnImT55sLxWZtxKf6UxE7m4KXsZ8tx4wgXrssccsjQlILaBayHdFTtKgPYYXZSbGrOrBe++9ZyklTNB5ofcFYgAvyVRP7bjjjjlJTazic77wApZtWFHluiHZCLEvKkhQbUH6WxyrwJy/iFyMDQGStkD+JQWI/ZKZVOeT33//3a4t0sVoR2M/MfHixZ7JVzbgnA1hn3C+UrUVtlAiDlDdxXkdR8IYq/YkWJHaR5seVUwIpJ9++qn3sVBVRmsDEysqB4Bzm0lnHBPhJIF4jLBEtVCY/DZu3DhXsmTJnPuhL5iMc7/lOY2AQlUDUOHFNc7kPK3nDPuG40Slb1hpQgoax6lBgwapPU5Jg31CS1e0HXrJkiXW0hTHMypJ17dIDxJyhBCFgtjbpUuXWrtDuHoVxfcLj8gf4qOZXPIvlQ284PDyx6oR5ck+QdDCQylcVQyhEgZBJazS8QHVLkx0MycKlNUzQQ+9ANIKohbl4bR/UY1DhRIrjuy3OOAl+amnnrIx0c7JKiwtRYhOXbt2tRd6Hx5U7du3dz/99JOV9YciGxMKVqqZeLJC7Is777zThBvOY66tsLXqtNNOizUqedGiRXa/YRycL7xmZj4ffHk9DRo0yITZl156ySoIhg4dasJ/GKHsG8RH/MEOO+ywHAE5LpIkoCTlnImCJ1cS2mKSdJyS9D7BM4r7H2NB7KIFjdYq9ksopKT5+hYpIW63ZSFE0YQ0m08//TRIEqTskGSwcePGWMdBusSDDz4YXHPNNfbp3bt38PPPP3sfB3HopLecffbZFhUapuj06NEjJ3HCJ4xh4cKFebazrVixYl7HQvpHfhGub7zxhv3OJ88++2yBnzTz0EMPWewtUa6kab322muWahPl22+/tZh0H5B4FKalRGFbqVKlAp+Q+Ma5yvVMsk7crFq1ylL7wnS68H5z9dVXB7fccovXsRD5y72PaHbuLeFYiAg+55xzAt+QYNOsWTM7T/mE47npppvs+MUF917ueUQmw19//ZXacyaMHL/nnnuC/fbbL9dxIrUqjCVP43FK2vsEMeykmu266665jtPNN98cNG/ePPBNUq9vsf0jIUcIUSiOOuqoYObMmUESSNJDlOhSJnTEmIax7MSFErNKTKdPqlWrZhNhiMZIT58+3cbnm8MOOywYOHBgnu3Eq/qOtW7VqpUdlxdeeCFYunSpfYYPH27bWrdu7T1KNfoh5pWJDRPQPfbYI4iDBQsWBIMGDQq6desWdO3aNdfHJ5wX9913X7Bs2bICBVwi5H3A8Rk9enSe7Wzjdz4h7pboXe4xCExMPi+99FI7bnEIO0R816lTx4S16P2GCejRRx/tdSxE/oYiaHQsPLN8RyWHE8zKlSsH06ZNs+s7HA/nTRzxxEkRUJJ0zgD3t0MPPTR47rnnTLQIx8NzgudpWo9T0t4nEPWbNGli9/7oWN566y3v7xJJvL5FepCQI4QoFFQz1K5dO1i8eHHcQ0nUQ7R69epB06ZNc1UF8f2qq64KatSo4XUs7Iuvv/7avkdfdjhmvitg4LHHHrOVvBYtWgRDhgyxD6tnjCU/gSeb8ALIecN4eEHmwzjatGkTbNiwIYgbhJSzzjrLJjS+GTx4sAmiTHgrVqxo11D4Of7444M007ZtWxNlmdBwv+FD9R1CCr+LE4Qd7jM77rijnc++4XxhDJn3G/7lXuQTJuHhsylzLHHc+w466KDggw8+yDMeKi3+9a9/eR9PUgSUJJ0z4WLDpEmT8ozniy++8C7UJuk4Je19gsWysDIycyxc+2m/vkV6UAOfEKJQEAOMjwi9wJjLZSZF4SPhC1IdiMIkkjPaV0/PNv3Tvr08oga6wPd27drlmKP6ApM9euszzaDx1Igj1rply5auTJkylqzz4osv2ja8PTh2vj2VMMmlxx/TyPAcCc/lJEB89P333++aNGmSY5rti3vvvdfSu/CDSQrca/DkwoMgynHHHed1HCSuhecw1xbgEUby2q233up1LCzGcS3jE8EHw2O8gtgn+OX4Zv369flePzwLihUr5nUsHCN8VzKjxtlHmIv7ZuXKlfkasLLP4vCCIRWKFKTM2GjuOz5jrZN0zoQJcJjgZ/LXX3+5jRs3pvY4Je19guORX6AGnmlhXHuar2+RHiTkCCEKBfHESSFJD1GM9phwZpoQkmbg+wXjkksusck4Rp/sB15+SIkibezKK690cUBkKJ+4Wbt2rb0IlipVKlc8KBMIhDff0a75wTgwb/TNmjVrLLElKdd206ZN3RtvvJHv732m4wFmo4iyfBBNIK5zhXMXI2pMUBFurrvuOktjY8IVB/ztIUOGuG7dutnP4T2nV69ermbNml7Hwr5o3bq1GWQzDq6jDz74wO59d999t/MNIj4JNq1atbKfw+cSEfJh5LZPkiKgJOmcAdLeMMk++OCD86RHxRGHnpTjlLT3idq1a9s76ODBg+1nxsO9sHPnzq5evXou7de3SBFxlwQJIcTfhZalvn375pS1huW/eORQlpxW7xXahzD7pNWCHnsMY2m5oLccU0fffPTRR8GHH36YZzvb8BbySd26dYP+/fvn69fj2wx1zJgxuT60BDKOY445xsbpG/ym+PtJ4LLLLgtOPfVUOz8o7Z8wYUIwdOjQ4MgjjwzGjh0by5holZw4caK1A/7yyy+27fvvvw/WrVvndRz8/1+7du1m/zvaMjINorPB7NmzzXyZc5aWxUaNGpmXGu0zixYtCnyCGey9996b4zfFp3jx4mZaGwe04PFsoq2UcfAsqFWrlo3vk08+8T4e7nHhvgifmZwjjRs39mpcm6RzBrj37r777sH9999vRroPPPCAPUMZG/eetB6npL1P8F5FaxnnCuPBv4eWV54LK1asCNJ+fYv0oPhxIUSRj6KkXJ44dNpQnnnmGde8eXOLkX7//ffdO++84ypXruxtLLR+0GZBPDHxmEDbGW1FtMr4WkXj1k4V0F577eVWrVrlZs+ebStWrCpSlh0HJ510klUyNGrUKNf2UaNGuZ49e7rp06d7rWZgNZHWrii0MZ166qlu9erV3sYSRsqGsJrHcTvzzDOthYfWHZ/QbkYk/LnnnmvVSpltkzfffLO3sfD/fcyYMXbuUPlC62K5cuXcq6++aqv2XPs+oZ2hbt26VnX3+++/uwULFlirDtUf/Mx1nzTYb5999pmXliIq3R599FH3+eef58TW33jjjV7PYaq0uLZpMaOagRYrxkK1RVyxxEAMOtdWdN9Q4RCtCPTFnDlz3FlnnWVjmDJlivvPf/7j5s6da5Ue7DvaTH2RhHMmChU599xzT67xdOrUyapA0nqckvg+wfsVbdnR43T55ZdbfH3ar2+RHiTkCCEKBQIJ4gmT3qlTp7ovvvjCJgqIFUy2KEX2CWISfzspD1E8PeL0XqHsuXjx4vbSF9eLViZMombNmpVnQrl48WKbdK1bt87bWEqUKOE+/PDDPOcHL6hVq1a145dWMj0QMkUmXlh9ihCcM3id0O4wbNgwu+dwziAW+z5O559/vrVIPvnkk6506dJ2v+F8xqOGdp6FCxe6pMF4w3FmC/xDELgQspJwv+HexzOpoHPZF+wbFhdo6UrCeJIioCTtnEEYuO+++1yzZs3yeNKk+Tgl7X2C84bW9bFjx+ZZiIlrPEm8vkU6kEeOEKJQ3HHHHWaKesstt+TyfqGKgJcO3yCWYDKcFBBu4lyJocqDFy4qS+J+8QqhGmnFihV5JpQYKEbNoX1AhQf99f369cu1nUmFzwquJIJIkhSOPPJIN3/+fBNy8IIZNGiQfec4xbFiz2o9lX6YZUdhTBilphWqthDckkKFChVMcEzCxIp9M3LkyFi8eTYnoHTs2DG2cSTtnOEZRJVfXP5xST1OSXuf4LzZsGGDSwpJu75FupCQI4QoFFQusDqeCe1VlN76hnL6V155xVZhgTJ6kpB8CwS8YCAOvPXWW+7HH3+0lawoM2fO9DYWKpRo8xowYIBNbOKG0vQOHTpYq8zuu+9u237++Wd35513ulq1ankdCyLk2WefbauclK7D5MmT3ccff2xJIdkGAXRLoc0pDmgTRNRBJPV9HYXQshSmQ2FkycTm+eefNyGFNkrfJC0tJUnQ2kqlEveduOH6xoQVE12EWSrwovg2qKaSi3TFtm3burhJkoCSpHMGeBZQbZyZdpb245S09wkqkmjHxkw4rmdTUq9vkS7iP/uFEEWSJEVRUu5L7/jy5cttBR94yNPP/dprr3l96bjmmmtMCMAHhqqPOKMnWVmk9YRKBia+mb3jPiPiw+jm0047zVpkwgQQvDv22WcfN3ToUK9joT2HFJsHHnjAotDZN7R3ManwseLIdbIlxHH+cM6QvvHss8/az6EPDNu4tqnG8znRC2FCjkcNPkb4cO25557ON0lLS0kStKaQEjVp0qR8xROfgmR4LHguRK8h3AT42XfaGfcUfFfwNclv3/j0nUqSgJKkcwZoF+f+xkJVfuPhfErjcUra+wQLLiy88K5F5XPmccJ3L83Xt0gP8sgRQhQKVjsxpyWKEvNRKk1om+Fhz4eJjS+Id0S0YeK5xx575EQoE1tMfDGtEL6g0uT11183oSBuwon4prjqqqtcHHGqVFRQCROKJ5deemkeQ92kwAt0ixYtYot0jqsKhhdSBAsqYEJfIyqpunTpssUi1PYIlTd16tQxQQA/HGJn+RdRCa8wKhLTanZcUFw04glmrb6gqqIgiGtPq+8UIMoS+80ENE4BJUnnTH7G85nj8S0AJuU4Je194uqrry7w94RwpPn6FulBQo4QotBtF5S30t7Ayw3lrfx72WWX2bYddtjB21gQBDBYzkzKIvGhSpUq7rfffvM2Flq6XnjhBRMoigpJEytIS6JkOq7UkrgSf0KhAOI026RiijSQatWq5TLKJf0Ho81ffvkl1W1nVBFwjSNwJSEtJQlmx1t7ju+3334FTpp9ccMNN9hKehzVXXGSNAGlKJ0zPilqxylp7xMsSCC2+0oLFcI3EnKEEH8LYngRTOKMoqTUt0+fPma0HIWXHKoLKJP2BfHrffv2NYNCJsRFAd9iRVGaePoYC74reHoQNc51FP7dW2+91UwufU9eMOrmmub/c/T/P//SGkeKis/JC9V+iCdh2yStXgjFrFAncSKTNIgNZhLsU1wvKvebJI0lieNJioCStP1COw+VtwceeKBLAkk5Tkk7VkkaSxLHI4o+8sgRQvwt8KrgEyc9evSwHmTaPqgiAKKlWWnFKydaQZBtk0tWfzA85kHNhDizZci3L82WID0/XhBrQh+EsCXv3XfftfOZc6l79+5ex8M5PG7cOCvrh9BjhCop2hizDUbh0YobxKTMtklK62vUqOHigFaqTZmZd+rUKat/+8ILL9zi/zb0iUjKZDOJ95skjSWJ46HCNAkTz6TtlyVLlliqVFJIynFK2rFK0liSOB5R9JGQI4Qo9APp5Zdf3uSExqfZXP369e3fiy66KGfSGT4wzzvvvJyfffS44/dCDPF9991nJr5xmh2LogEiBSJJ1EiT1jyMhWn98C3kcO5i+jlv3jyrhHnkkUfsO15Tm/Me2dZQpYShZSjiAN+pYMJ4mKolnzz++OOuZcuW1opTpkyZXNc337Mt5IRpb+E9jaQ+tiG+wYwZMywJbmsEHyE2hSaeRQMdJyHSiYQcIUShaNOmjRs0aJC1QcQtWERX8OOGyS5pSLR7CbElUKVVvnz5PNvZFkcFV/Xq1W11lwohWggQUvCB4bzmZ59QTYdheSZsW7dunfMNAhLCWvv27V0cRE08GQPiNW2cYdsUQjXin+94bSGEEEL4RUKOEKJQEBdN1U0SInd9J5AUBJNvn+bKouiD6Pfoo4+at1IUtsUlCB522GFWfRI3F1xwgbVRUZlz0kkn2TbS8m6//fZYqk5o62rcuLFLAsQ204IX9b7hO2bRp5xyinvggQdiHZ8QQgghsoeEHCFEoaCcPwn92CG0E+Az8sUXX9jPJFg1a9YsVyuCD6hioN2DVXuqFzI9crRSXrTAhyXbaUS9evWypK5JkybleNBQ/YJJLYaacUBlB2074fWEB0ODBg0snc4nVJvcdtttloYXelIwhmuuuSYWoQIRhwolUlnihra3L7/8MscEOoRtma2uSULtpptG+yZ/tF/E9nDeJG08ougjIUcIUSgwYu3atautCscdu0v0eJ06dWwc4ao9JqmIKWFbiC/q1q1r/5511lm5tvvy6EmqWAFTp061SoFMMYAJKS1pJCLBnXfe6UqVKrXN//7WxGaHgpsPIYWKMpKY+vfvb5NwoNqEFhmSSHwzd+5c8+tZvnx5jkiAafhee+3lXnvtNVehQgVvY8Ew/LHHHjPR5quvvsqpFipRokQsqS2HH364u/vuu81MPT+hFtN1X1CphKDFfolWKyEm87ukkiQ/jyZNmiRKXE/SvknSxDNp+yVpJOU4+XyfKIrnTdLGI4o+ih8XQhQK2odoe3jvvffcIYcckmdCQ2SwzxcHJli0goQiAeLAtdde677++msTEHyxOTNY321gCEejR4/OVanEJD2OKGL+5g8//OD23nvvXNtXr15t27ItcjHJ39IX3iQKbr6gKgjRJjMpqmnTpuZNg+iWNHzFupYtW3aTv+Pc4n7jC6puHnzwQTOj5rqCfffd17Vu3dqqApMSNx5HHPqsWbM2eYyKFy9uSYvFihVzSYNWuSpVqiRmbCTGff7557FX3/o4Z7aGYcOGWYVipqC8PR+nTS2EcE1xvu68885Z+9vbC0m7vkXRR0KOEKJQYLKJyXCjRo3yNTvu3Lmzt7Gw+vPpp5/mMYwlaYc0l19//dUlDaotiEcn/SZbLFq0yFp2qFYIKyvmz59vccTES1PZ4BOElBUrVphIEIVqFI7T1lTM/F2RjfjYO+64w8SJaDsT4gVx9ldddZXzxRtvvOF22203MxkGKnMQJWln4ns0scnX9USVG6JflDlz5thLaBI9oJIy4YyL8NqJs7oEYT8/oTQUTxDbaZHLbAWLQ7Rl4eHiiy82w37Glm3wLcqP6L5BGMhGJWKSBZQknTOQ6VOW33ioHE2KoORT6NrcNXXAAQfY85R3v2xXRh5//PGbPW8YC2EcPiiq17co+kjIEUIUClai3nzzzZzJZ5wgJGG+TBxxFMZ35ZVXmniQxgoCjKi5xT///PM5LxBUv9BOwIsWYo4PQlPaMWPGWOtZdDWKyhdWz3lRR9DwBa1vVGwRF5+50jp48GD39ttvexsLLTq0LnG8Zs+ebaIWFRUIpYiT0aQiH2Cw3KdPH3fmmWfm2j5lyhSr9mCMaRdy/vjjD7d48WITQ337BkWh8pBzlfYqJrzsh2XLltn9BXHQJ0ycqP4rWbKkq1y5ck5lJv5l3Js5PgiokydPdqeeempWx8K9hlQvTLHDtrOPPvrITLOZaLLfEHIRc6hqyjZMKNkX3O9CUQIBm4k31zgCO5M+VuwRcLNNUgSUJJ0zYcUdVYcs/kSrEWnx5Hr68ccf7R7DvZkFkbQcJxgyZIjr2LGjHbPoNcXix1133WX7jWuJa4726GzSoUMHN2DAAHt2hmP5+OOP7V2C8bGIxzlDIAcCStqub5EiEHKEEGJrOfLII4PPP/88SAKtWrUKDjjggOCFF14Ili5dap/hw4fbttatWwdJZLfddgu++uqrrP6NXXfdNZg1a1ae7Z999llQokSJwBdNmza1zz/+8Y/g4osvzvmZz/XXXx/cd999wcqVKwOf7LLLLsGCBQvybJ8/f779zicci8WLF9v3zp07Bw0bNrTvM2bMCPbZZ5/AN+PGjQuOOeaY4KWXXgq+/fZb+/D92GOPtd+tXbs255Om6wnWr18fNGvWLNhhhx3sE/7Nm266KejRo0fgkyVLlgTly5e36zw6lptvvjlo3rx54Jv27dsHLVu2DP73v//lbOM7+6ZDhw7BX3/9Zdf7qaeemvWxVKlSJXjjjTfybGcbv4NXXnklOPTQQwMf9OnTJ7jwwgtzXTM///xz0KhRo+Dhhx+286pBgwZB7dq1vYznqquuCnbffffg4IMPtnHxOeSQQ4KSJUsGF110kT3fixUrFrz77rupOWdg2LBhwRlnnBEsWrQoZ9vChQuDM888094vuBcylvAenZbjBOyDESNG5NnONn4HQ4YMsTFlm2uvvTa455578mzv1q2b/Q46deoUVK5cOUjj9S3Sg4QcIUShGDt2bFCnTp2cCWic/P777zZ52XnnnYN//vOf9uHlpk2bNsGGDRuCJOJj4rnHHnsE7733Xp7tvPTxO9906dIl+O9//xskgXLlygW33357nu1s43c+4VjMnTvXvjNJGDRokH3n2vItKgGCW/gJr6f8fubftAk53GeYHEybNs0EuPBvjh49OqhUqVLgEyYGTZo0sftf9P//W2+9FRx++OGBb/bcc08TQjNhW+nSpe07wjIT02xTvHjx4IsvvsiznW38zvf1td9+++Vc41HmzJljvwuF23A/ZZukCChJOmcAYe/TTz/Ns33mzJlB2bJl7TvP1DJlyqTqOAHXTX6LH2wLr6Ovv/7ayzX173//2wS2TNjG78JrnftiGq9vkR6UWiWEKBS051B+TGsBZceZZsc//fSTt7FgsofhJ94m0WQbxpVm6tev766//nqLZY+m2hCdjOGxb3z6Jm0OWocaNmzoxo8f76pWrZpTJr5w4UI3cuRIr2OhPZEee1oHGMOIESNySrPxHfANbQNFDV+pLbSBcHyqVauW62/iJxTee3wxbdo0M57ONBnFfP777793ccWhlytXLtd2toXm4bSD+DhWtDOQ3kWbZLh/iK9nW+ilxj6iLdcHa9eutbaczLYK2lFCfyPai2jZ8wHPBIIKol4mfG/VqpUlC953333upptusiCBtJwzgGk4Y8pvnKT4AV4069atS9VxAlrJGA/XUOYYwzYzWrd9eLpxTnDvo7UsCttCzyvM4H34XyXx+hbpQUKOEKJQPPzwwy5p4A3BBzNCDFvDyO+0gnEjpr2Y+YZCGy+kiDhxHD+8im677TbrXeelJ9OizWdSFH40iDZEW4eR3+edd56JXD68D6I8+uijZn798ssvW9///vvvb9sRmcI4e5+QrIZHBS/oYdoZL6hEXe++++4uifiy++PFPDN1DdavX+/9XsNEJb9rBnNzvHJ8c8UVV9g5gj8GptihbwWTTbzKQsPxTBPtbIBJOPc5hNDjjjvOtuHtxP4aO3as/UzCGNedD/DpaNasmXn0RPcN98Pzzz/ffkbEzRQ0tncBJUnnTOh10rx5c/fEE0+YoS4QpNCyZcsczzDOo4LS67bH4wT43zRu3NieS+GxwhSfsfDsCo8dvlPZBiGLZ/WMGTNynTcct9CfB4/ESpUquTRe3yJFxF0SJIQQf5dVq1ZZj3bY7hG2GFx99dXBLbfcEiQRX60gYbnxq6++ap/8ypF9Ubdu3eDoo48OHnvsMfOnoB0l+hHJ4OOPP7YS8P333z+44IIL7IPfFNsoD08i+GL9+eefWf87NWrUCPr27ZtzDdNKALQ60GrqEzwyrrvuulxjWbdund0L8Z/yDfv/3nvvtbaTsBWP7927d885Nt988435jPjgl19+CQYMGBC0bdvWPgMHDrRtccBxwbsj2v7Ld45f2G5KS09+bT3Z8pWjral3797WJsiH72yjfRAef/zxrLfsJO2c+eGHH4Kzzz7bxsHxCY9XrVq1guXLl9t/M2XKlODNN99M1XEK4R5zxx135DwX+B5Xe/1zzz0XVKtWzVqT+fD9+eefz/n9r7/+Gvz222+pvL5FelBqlRDib60IE3FNdQXfo1AV4wtW7hgDqzFHHXVUTnoNKzK0rMydO9clDVb4unXrltX4ceLNWRHKbDEjPvqBBx5wnTp1cj6hSoB2EF+rZJsjs+qEVV9W1eKoOqEth3Qq/qVNkKoPVj4POuggb6vRIZTpU7JOBHqYyMTKMClfVDFMnTrVS8rZlkAqiU9IHTnnnHOstfSZZ56x1XsSUijpp3IgTN7xAZU3derUsWokqstIO+Nf7ikco/wqh9ISh75hwwZvbRVbw3//+1+7hoBnlO9ksRCqOWiRoRowTHWkzYxKB9K+SNtZunSptfH4au+M+5yJQpUJra1ACpGv+POicJxE8q9vkR4k5AghCsWHH35osZfffPNNnrYGynx9tsmUKVPGRBtik6MxxDxQKavn4eoLIrR5eIex7JT4MyGmNYXvPvrHQ3jJo+c/c0JHHzvbfB4jYB8QhR6WrMcJJeFMgmnBi8aXInJNmDDBnXDCCd7GggCAOIBHDhNwhCXOX17gGWdYtu4L9gntBKGXSAiCBWIB3ljZ5Oqrr875zr3llVdeMXGNvw2U0yPCIfj4jmYHxDaODfcZ7i2cK0yqiML1DQLbCy+8YLG74Vguv/xyO4a+uffee+1v+2o7KQjEAKKbEdzOOuusXB4jcfDcc8/Z+ZpE37Y4BZQknTOhUBs+u5NG3EIX4j7XE8friCOOcHHCogJjOeOMM1wSSPL1LbZz4i4JEkIUTSpWrBg0btw4mDdvXrBmzRqLWox+fEJbQZimEG1ZokWkVKlSXsdSoUIFi2gO0zZIzyJdgrJf3+0OlIf/+OOPebZPnjzZSrN9Qzk68ZtJSDqrXr26HY+NGzfmbOM7ca+0z/iEc+Ohhx7Kc/5Onz7d2pt8s/fee+fbOkB0M7/zSbt27axkPdo2xXeSWm677TavYxEFc9xxx1lLwcknnxz0798/WLlyZWxjGTVqlEX/kqBDq07r1q3teRAX3G9JObv00kvt+eCjDbAgiGkO2wLjJEnnDOy0004W780zO78UorQeJ6Cl68QTT7T3Cv4lVptWtDj4z3/+Y+9WtPzyHIi7ZSlp17dIDxJyhBCFYtddd43VbyXKOeecE9x11125vCKI6ERoatiwodex8DAPhYrOnTvn/H28RfbZZx8vYyhZsqT1jPOCHH4PP0Rzsv2GG27wMpbMcYU95Byn6Lh8x6FvKp6Yl3ffkd+cM+HLelTI4TziZdU3+DLwgvzCCy+Y9wyf4cOH2zYmxL5fkL/88ss829nmW6QN4SX9pZdeCu655x77vPzyy7kEQZ8gYBNXz4Sva9euuT5xQNwuk2CimpkU16tXz3wr1q9fH8t48MR56qmnzONkhx12CI444ohY9g3nx2uvvRZcdtlldr3vtddedg8myjrtAkqSzhn2Q79+/YJTTjnFBAsWrHr16uXNoyfJxykaDd+pUye7lnbccUe7tp599lnv4/jpp5/s3nf66afbPsJ/D2+lOBaKknZ9i/Sg1iohRKEgwaFdu3axpOpkggcO46GtYMqUKZZWwjYi0InuJIrcF6VKlbLybNqIKNHGv4cI8CVLlti2bLelwLPPPmstKfi9kE4V9Xwhipd4YpKsfMO4CoKELV/gMzB06FBXu3btXNtp0eOYhX4EPsDb4MUXX7Q42WhrIC1FeBz5jrUmIvX22293AwcOzIniJfUMXydaiooVK+ZtLLQi4kVDKkiUMWPGuKZNm7o1a9Y4n3Bf4f5CFHHom4GXxl577eVee+01V6FCBW9joWWTY4InDu2l0eQavs+cOdPFCffeYcOGuZdeesk8a8LWkLigNZC2ENrQfLeVRuEZwLXNvpk0aZJd/76v8fBcptWV1jz8lmrVqmX7h5SduFpEknTOLF682MYyfPhw88zB94/3C98k8ThFW+y5B8V9TbFfOE5PPfWU+YTlFyGftutbpIS4lSQhRNGE0nVWQJ5++ungk08+CT7//PNcH1/88ccfltJCGwrpF1ThUKHTsWPHYNmyZYFvzjvvPEuvYaWe1cXvvvvOttOqwgqWT95+++0tqhTo0aOHtceliSRVndx6663W6kWZ+r/+9S+rdHv33XeDQw89NOjSpUsQF6yI0x7IJ66KCtKGSMui9SxMbXnwwQetUoff+YY2OK5xVoND+E6pP6vmPjnooIOC+++/P0gqtDtwbtMeSAVcHJBaM2LEiKBBgwZW3cY+a9++fRA3YeXHMcccY9UEccP9hgoCKgm4B6X5nMmsvqPSolKlSjpOEXjf4jlJ2yLV2RdffHFsY+EdkBRMqp85Z/bbb78gbpJ2fYvtFwk5QohCEUaFRj88sMJ/fcKkLvTIiRuiUs8991wriX7iiSdytrdp08bEgyTCC6GvKPRFixaZyHbJJZcEK1assG2vv/66ldf75Pfff7f41mhcKBM9jtOGDRu8jwUfGMrUuX4QABlPkyZNUt9rT4tkz5497eU8vM/wnW1x7BsmCvmdq7Nnz/Y+8fR53W4ptAgiqCPy08qEyM590LdvGn5OV155pbWS0oKHp9I777wTxAliKJHJLDRw3znssMOsJTi/Fs80CShJOWcyBZOWLVvmCCbci8ePHx+k+ThltlThd0dLFdHbcUAMPM9N2rJ333334Oqrrw4mTZoU/PXXX7GMJ8nXt9h+UWuVEKJQkFZVEAcffLC3sbRt29baPWj7EFtPtJ0nTelMYRl0WPZMC57vUnUewd9++6215qxatcrNnj3b0odI9oo7GSRpxJ3aAiTj9enTx1o5o9By0bp1azt+vrjmmmtclSpVXIsWLVwSqFatmiW/kRRI68ell17q9t9//1jGwnVcv359G0e9evWsNTBOLrnkEjd27Fgb10UXXWTjiqO9Nb/WIT7z5893p59+uiVRNmrUKFc7blrOGejQoYO1MC1btiynhYm2zjhbmJJwnIDkN+43/G3OZ9qT44JzhNZ5Wvs5Ruedd57Xlt+icH2LdLBj3AMQQhRNfAo1m4N+aHqj6UeuXLmyK1GiRK7f9+7d29tYeMligtW4ceNYIoCTzB133GFxs7fccouJRyFMih999NFYxsSLVxyx0VEhh1hXfBAQbg488MDYxpJUuL7ffvttE9yYRAATLQSd3XbbzetYevTo4W6++WbXpUsXm4SGPhH33HOP69mzZy5Pj2wLTpw3d999t/19zuFMsYJx+oSYb+7DeIHFDR5X0XtM3Oywww7mg1WnTh37HjdRAeXqq6+OTUBJ0jkDLDDgD8ZkHO+puEnKcQJEpKQsLnD/5R2rZMmSLgkk7foW6UEVOUKIQvHqq6/mux2TzeLFi9sko2zZsl7GUrNmzU3+jvH4NChs06aNrZz9/vvv9jKIqBNO+NJekcOkm4oFzovo38QIunz58mZu6Qv+Vr9+/dxbb73lfvzxR/fXX3/l+r1Po9hjjjnGPfnkk4k/T+Kq/GPVdenSpXZNYSzMOUP1Cz9jyOwTVqVDQnPh8DUq+jPfs23+WdD9lb//9ddfZ/XvFxW41jHwjhJnVVcS6Nixo1UNJEVAEfmj4ySEKAgJOUKIQk9omCxk3kLCbfxLatPo0aMteSZtFQQIXaQ0jR8/3kQtEqSuuOKKWMuR4xZykpTOxMvxhAkTrDydYxJN/IHOnTt7GwtpR7169XIDBgzwmnpUFCCZhXMFoat06dI55wwVOtddd50llPiE9sCtqc5LG6THcO9DeMsUT3xWRq5fv961b9/e7jerV6/O8/s4EnYYE+dPfvvGd/VUkkjKOZOZcJbfeEisSytcM7SVck3lt29odfIJ7dibGsuoUaOcb3R9izhQa5UQolBMnDjRVou6d+/uTjrpJNv20UcfWan/XXfdZb3bzZs3twk6k7A0seOOO7oLL7zQPlR7DB482PbLnXfeaX4NPNQzPTbSAH3kTK6IlkU4oQqGuFnOESK/fUI/++uvv25+PXHD/3e8evBfIR4+syXP9wtykpg2bZp7//33bb9EOeSQQ9z333/vfTyIMz///LPd0/B4AlbLqbzz6VcRhUkDPhp4PHHviYvJkyfbRBehjbhmREmq7RD2TzjhBK9jadeunVXbIY4ioPfv39/Ol0GDBsXipfbpp5/avZ/rnAlfqVKlzBOL1s699947loleEgSUJJ0zQBXbBRdcYJWj0YWqUOiPQwBMwnGCrl27uieeeMLdeuut9o7H+x/HisW6Tp06OZ/gY8Rzk1YmFmRq165t1Zq0VHL8fJPE61ukhLjdloUQRRNiFd9777180x5In4CJEycGBx54YJBWiOhs0aJFULJkSYu9JfHhmmuuCXbZZRdLnkgKpCz4iGpPUjrTUUcdFXz++edBEnjmmWcK/KQZrp25c+fa99122y0npYkY8r333tv7eD7++GOLQyc15oILLrAPkfVsmzFjhveUlGbNmlnSD59w39x0001Bjx49At9UqVLF7nHRY0WiDdHsjz32mNex8Nx566237DupQwsXLrTvQ4YMsfudb04//fTguuuusxS2cN8sXbo0OO2004KRI0d6Hw/pPsRGV6hQwe7HxGtzrZH+U7NmzVSeM1C/fn2Lqic+mvHMmzfP7jUnnXRSMHXq1NQeJzj00EODsWPH2nf2DQmU8MgjjwSXXnqp17Ece+yxwaOPPprrvCGtimssPJ/SfH2L9CAhRwhRKIi+JHI3k1mzZuXEYi5ZssREizRBpPaDDz5oQhcRlA0bNrTY0mgkJi+GJUqUSFXcd2ZE+7hx44IRI0bEFhvPPqhbt66do0UFJudr1qwJ0sRFF11kL8jACzJRxUz0iChu2rSp9/FUr17d/u7GjRtztvH9qquuCmrUqOF1LDfffHNQuXLlnPtJKOSMHj3aJny+iU7umGyG95jPPvssOPjgg72Ohf3BfQYQ3RDVgfPH1703ChPvL7/8Muc7AgF8+OGHwZFHHul9PEkRUJJ0zgCCbCjwE10fHrPJkyfHck0l5TgBglJ4TZUpUyZHuGZM7CvfY1m8eLF9L1WqlL13AtcVY0v79S3Sw/9z7RNCiK2AdCjSHVauXJmzje+UtBNRCfhXpC2FBx8Yyo+vuuoqK4kmUhuz1qgHCwkU4T7KJvRrk2Yzffp06xkn1hrwGfHpAZPJQQcdZGXImEHHlYJx4oknmgkqJf14sFAKHf0kkfvuuy91bVYPPfSQtd/RvsTxIrUqbKsiJco3+DLQHhhtYeI79z1+5xNaGkh7w4ssen/BPNun31QIaYFh68e+++6bawy0GfiE65p2M8BIHS+N0I8qjqQbEsVCo2xaLWiTAdrxvv32W+/joS0wbGfl/P3tt9/MjD5MX0vjORO2ToVpZ6RWkY4XpnSS2pTW4xS+2/zwww/2nTZOWpqAVC3f0d/4Lq5bt86+k+I1Z84c+07bK+1Nab++RXqQR44QolDgEdGgQQN7uIdiDQ8sXqDHjBljPyMc0EudJjIj0Endwcz3qKOOsn7uMDEF/4a0xX1TBYqwtamkKJ8GhcS4IgYgjuRndpxE0phNwP0F4RFPhFmzZtk9BT8azKozvYR8wLXLSzriQBTufb7jrhHOmTRkgkdDHOczqWvvvvuu3esQavHSwGuE69p3IhtRzZw3eBpxHzzvvPPsnrdx48ZYDHSPP/54m/AiXDMmPEUQKoYOHRqLwXl+AgoCoG8BJUnnDHAsOG9IhKtataqZ0OPPhc9dtsMAknycAO8ZPI3YL61atXJNmjSx90Duh23btvU6ltNOO818GlmoIoacFEPSSdlGpH3ar2+RHpRaJYQoNEzEWZXBZA6OPPJIV6tWrVwRvWkD0z1Mjlu0aGGrQ+wTXgR5qDOBaNmypbexJCnuG3jZwmyUuPj8xJOnn37a21gwIfzggw/MYLio4CtdTGwaTCsRZh988EFLXwMqhqhObNiwoXv44Ye9TmaYxDCp4txA6OJa52eqId944w3n2ygWoY2KQ8QkJuUYVTO54d5HVUNcIKjPmDHDEgQZn2+o1qKCgHsfIjZVFuG+eeqpp7zfh0iDO/fccy35DbN5Fl+aNm1qAgrVDixIpPGcefPNN20cPMMXLVrk6tevb+83JOaNGDHCe0hBUo5Tfnz44Yc5xwqh1CdUpvL+st9++9l7KIJbOBYWD30npSbt+hYpIu7eLiGE2J6gxz7s83/88ceD4447zgzwXnzxxaB8+fJex4I3RGhIHTWKHTVqlBkX+maPPfYwb5wkcPzxxwcffPBBUJSIHsM0gY/SoEGDgm7dugVdu3bN9fENht140+B/hVE3n2LFigVt2rQJNmzY4HUseONwTmCoji9Z69atg1q1apkHzCeffBIklWHDhgX//e9/gySAiSympEmBsAAf5xH3kdALhmPRvHlzM5C98MILE+kbFuc5s3r16lwed/Dtt9/acz3bFLXjBPXq1fMSnlAUfeV8Xd8iPagiRwixxfTt29ddf/31rnjx4va9INIat0ilBzGq+MDgAUMZNH40tF5QneOzf5sVPPxxiPsuV66cmzlzpsVzslrEx7dPDtUC48ePz9OWEgdUkhGn2r17dyvPpsc9s4UmaaSxIufxxx+3Kjb8KsqUKZOriovvnNNxwHUc+nngF8F1HweMgThtzgsqG4hsxsOHczqpcG199tlniTiPk3ZNJWnfwPDhwy0ePGwVjouk7ZekjScpxylp11TSjlPSxiOKPhJyhBBbNRGnhJQyY75vCiZYlEynEUrEr732Wusnpzea9oaTTz7ZyvopkV6+fLm3sdBbf+ONN7pnnnnGTBwxS+RfDGPZtsMOOzifPPvss7Y/KDWOw98kStj+l9nexSORbeynpJGkF2Rf0Fpxww03mDghtg+SdB4naSxJHE9SJp5J2y9JG09SjlPS9k2SxpLE8Yiij8yOhRBbTJgCkvld/D8wuUMowfwP0z1EnLACBEM8n+DNQ0XD3XffbakOrNgzhriSoqhQYuUQg1aShzKrYHxWV/gwm97W1KhRI3YBzDdr1qwxHxiRPwiOePaQbgOke2FCH03VEqKwaK23aKDjJEQ60ZNeCLHNJhQY67KC7ttoLkk0atTI4oCJ6Ywa3CHqUKUTB7R58YkbItmpTCLtIu6kKJIltgSqQYh6pbUn29cPcdLhhJyWPErlo1VTr7/+uksbiDiIoJiHi9zMnTvXzhGq/GjbBCKJ99prL4vZVlqKEEIIsf0iIUcIUSjatGljPgxEATMJJUGFFCC8IsaOHevOOOMMl1bw8uAT5aSTTkp13DeMGzfOUkEQuooKzz33nHkNZVPIIR2FtrvvvvsuZ0Leo0cPd+CBB9o+w4MlrZAyREUZCSn5eRml1YsLaOFE8KPdNRTPqWAi1QYvM1JThBBCCLF9IiFHCFEoEAiorABWf4m0xuR36NChrmPHjhbJK+IX2wqK+/YNwkQSTYTjLllHjKBnHiG0VKlStm316tV2ffE7xJy0MnjwYLfbbru5d955xz5ROJ/TLOTgiREVcYDvGHhXqVIl1rGJwhH3PVpsGTpOojDovBHbGgk5QohCsWrVqpyqE1o+aIEgGalZs2bukUceiXt4wjkT1ai6qVevnksCDz30kGvXrp0bOHCgeeSI/wOBgoqTUMQBDMVJIzr11FNdmpEX16bhfksKHVU5Uai+o5LJJ1RlIt5j9l6yZMkC/1vabzMrq+ICoRuROynI6yT550xaj9P69eu3KBXrzjvvzPUsi5Ok+cql8bwR2UVCjhCiUPDyO2/ePLfvvvtaEtGAAQNyYnl9pyGJ/Nl9990TlY5AhQnnRxjXnPli/tNPP7k0UqxYMbdu3bo82zGnxrBa/F8CG6IO546MfF1O+x0VSV26dHHVqlWzbQiCeDrhlfPLL7/k/LfZroTjnl+7dm3zeNqckIPxejbo27fvFv+3YSUXxvQ+6Ny5sy1yIEgURH73gbQIKNzvMtt/w/M2W+dMQe2uX331lbWMIwSEaYYhvPvst99+Lk3HiXc+Ags4jwtqj+7QoYPz4XFHWz8LiAUJNb595RDR58+fb99pkybYIcnXtyj6KH5cCFEomDw8/PDDJuQwOV+wYIFNSImWJimJNhERL0mK+w7Hszkz5KThIy70yiuvtMSuJ598MsdLafr06e66665zlStXtqj4tMK9pVWrVjnnDvcZjgXb9t9/f3fHHXe4tPLPf/4z53s4yQxf6aI/852KmWxz4oknmoCEsXsclC1bNtfPK1eutPMnFJZ+/vlnE5CZXH399ddex1apUiUTI8IJaMOGDe15GRfcaxkHQkWcIM7edNNN7u2333YbNmzI2e7zvI1CS+vFF1/spkyZYn9/4cKFdr9BvKBtkarSuITs/HzufIYYYMbPswhxhIpa9gnPrjgELdrGhw0b5n7//XcTlziXQzE7DhBoCEZ44YUXcs5ZxG3Opf79+9uimhDZQEKOEOJv+eR8++23tipywAEH2DYmXLw4E4Er4uW3336zpCxaHuKO+y6q+BBymGAyscJrKjxGf/75pyUSPf3005utcNiead26tZ2/iMZ169Z1s2bNsmMxZswYE5M//fRTl1YyPYO2RUrb3wHRmNX4bt26mQCZ2Ybh0x+LSd5jjz1m4mhoIM5KOeJo8+bN3eWXX+58w7nK9Tx8+HC7vi+55BKbDMfhZ3T++efbhJxKjquvvtruPwijvqF1lGkI13l+Pm4+ztsoCBMIJk888YQ76qijcu79mPTfcsstlhTnE4QkzpFM4/K4hK5QIKVtG1GHCrw6derYGHle+ayW5Bp69dVX7Z1z/Pjx1k7KOK644grv7ZIINlzf/fr1cyeffLJtYzGT8xoRF4FHiGwgIUcIsU0npGmedCYNVqpIrCISPb+XZMr9fcOKImXr+a0uxr06nB8tW7a0iWm248eB/RLGjzOJ8O1zkkSYaI4YMcJWW6OiGvvqhBNOyNU+lNZ7LmJFeN4cffTRtjodxwpwfhVCcU06acFjoeH444/PtX3GjBl2P4zTe2njxo0m2iLqIBCUL1/ejhlpYz6PWzghZyJMq9DZZ59t42ARxlc7FUbmHJNQbIsbfP84JhUrVsx1v6GCC/8n2r98C12II1QeUv2c+QxnnHGCcHH77bdbxRDPyBYtWthYqXzzCe8TGONj9M59Bl9A2ifPPPNML38f0Tq/RM5p06bZAgT+QkJkAzWaCyEKBSX0VHmwEhGKBiNHjrSXDVb6eOkR8ZK0uG/8O/Ck+Oabb/KY/vme6FE9wCQi3DeUP9MSyESY72ESUOj9lE3wNCHiHOEmKt5QUfXAAw+4Tp06ubTCZDPTZwB4MU57AgiJVUwSihcvntOS16dPH3ffffe5CRMmmNDlE0TjpPDDDz/Yin0m3GMwiI4T7n2IOUx++c695tFHH3V333233YPCZ2q22WuvvazKhA/VmQhLVDNwX8TPjFaRI444IqtjoBqJqt6kCDncV/ITIfBvi6MVjmQ6hC7EvqTA9YP4R0UOz3KEUQTA7777zt4Lec5z//HFRx99ZOcuVS88KxBEv//+e1e/fn07hx988MGsj4FwgvxEWLZFUwWF2OZQkSOEEFvLIYccErz33nv2fcKECUHJkiWDN998M7jmmmuCWrVqxT08EQTBkUceGXz++edxDyOHihUrBo0bNw7mzZsXrFmzJvj5559zfXxSoUKFYNy4cfZ91qxZQbFixYIOHToE1apVC5o2bep1LP/85z+DFStW5Nm+atUq+12aqVGjRtC3b1/7vttuuwVff/21fb/pppuCOnXqBGmmevXqdq5u3LgxZxvfr7rqKttvaaZ+/frB8ccfH8yYMSNn2yeffBKccMIJwXnnnRfLmPj7N954Y1CqVKlg3333Ddq3bx8sXLgw5/ec53vvvbf3cS1btiy4//777XlRokSJ4MorrwzOOuusYMcddwx69+6d1b+9aNGi4Oyzzw6eeeYZ2z88r6If35xzzjnBXXfdlet+87///c+eWw0bNvQ+nhNPPDGYNm1akARGjhxp19VOO+1kz/J+/frZczzzePL7bMPz8sEHHwyOOeaYYOedd7ZjM378+OCvv/7K+W/Yb5zPPhg0aJCdxz/88EPONr7Xrl07GDhwoJcxiHQiIUcIUSiKFy8eLF261L7ffPPNwfXXX2/f58+fb6KOiJ+xY8faZHfx4sVBEth1111zTVzihBe8cL907tw55yWdid8+++zjdSz/+Mc/gh9//DHP9smTJwd77rlnkGZ4GWdC1aJFC7vntG7d2oRijh8TvzTD/vjiiy/ybJ87d26wyy67xDKmqVOnBpdffnlw8sknB999951tGzJkiPfJKNcTk3KuLSZ6fBBF2ZafaOpDOEYYqVevXvDKK68Ef/75Z57/ZuXKlTZeH/zxxx/Byy+/HJx77rk28a5cuXIwYMCAYO3atTn/zahRo7L+LP/ggw+CsmXL2v/v8MNxCv/1zezZs01Mq1u3rp0zjRo1Co466ih7JiBS+IZnANfSW2+9ZcI+xyf68cm///3voHnz5sFHH320yf/m119/Dbp06ZL1sXDOli9fPujVq1e+z05g/5xxxhmBDypVqmTPKcZ12GGH2YfvbENQjn6E2JaotUoIUSgoF6Uk+sADD7Q2lXvvvde2IxDHYcAnkh/3XbVqVfM2SYL3C7He7BuYNGmSmVxCqVKlvPmucA3RHsSnXLlyuVqFuIbwY8BzIM3Q+kZ7wf333++OPfbYnJYhjCT5Oc1gHrx06dI8bRfcl/H38A2ttbTmYCRMqw6JMrB27Vpr9/IZBUzbEH+PlLMvv/zStrGfuM7iIIxtLshQGI+RTN+wbEELNH/r0ksvtdYUDFkzqVmzZtY979gn+BhhAJ2fj5tvKlSoYOcMrW5cQ9yDL7zwQnfjjTfaPvMNvkWQmQTn23eKNsUePXpY2lpBRsKkY2bbe4//75MnT7aUvILSOLk/+mr3xDxciDiQ2bEQolAQGTp27Fjrocetf8mSJdZbT59yr169lIiUAJIW9/3KK6+4u+66y8wRmYRnCks+fZVI2MCjAjNJzIwxP2WShVDAuc3LvI/jwyOYyQypTNEee4QmPKjCBAwhMsHMk2sKD4hTTjnFtpHwxfXFhItzyidMyNu2bWuiaNQolufDOeec45YvX+58wzXOtY2Y7TNRpyAyI+LjAJNj0ibxV4oTTGI5T5Ig7hfFZDqfqV4sBmGqjgF9nCBAct6SIJZtDychkk4ynmpCiCIHpppMNFn9RbhBxAlNJjGYE/HjW6jZHEwuAeEihMlMHKk2rLhynpJsg6FxuFJOjCkGsj6PT9myZXPSSQqCqhQqdNKWDMd5gWARTWYiWScpE/O4QMDhukE4CY19EUdJWuNc8Q3x3vklzyFQkq7lE6rtWrVqlSNmI8wiKrGNa51kHd+QLsZzk0hpYBLapk0bd+2113ofC5VTITzDgepa35AqFLeQM2vWrC3+b32HOPiOXy8IDNURZeMWckjH49pZvXq1hByRelSRI4QQ2xG0BVFSHH4viPC/8wUJFwUR9wti0uF40WbEhDQtsOpK9RTVHGGyDZNyWmeIcKYVIu0gWnz11Vf2PWyjjAPOSyKAaQeJVuQMGTLEhCUirn3RunVrq06iKglhlsk6YxkzZozr0qWLTUh9QvJc7969TUgKq+xoD0RQpoqJ5DqfIPx17drV9e3bNydSm8UYxkdrjK/4cc4X2rIR9/Or0uTa9yEMRBcUCqqciqNtHBEUETAUso855hjbXz6j6uHFF190HTp0sPO1cuXKVk0Vl8jFvZ8FRBZhkvAMCM+hTSG7AZEtJOQIIf4WvJzj00AJu+8XMJGXHXbYwaqiiOHc1MtFHBUwSYOVTiJTaS8oqM8+SUQnx2mBSS+iDZUVYYzrmjVrLGKWaPL3338/7iGK/x88NJ577jn31FNPuVq1aplHDeItEz+itREJfIEoPGLECFetWrVc1w0eXXgs+fLBCuEcRjTBkyYK3jDsl1WrVnkdD1Vbo0aNMgEpKiwhcuH3wQTZBzyjNoWvZ1R0gQGB77bbbrP2xOh+eeihh0w48O2F8sknn7g6derYM4qKGPj444/db7/9luMX5ov8jlVcFbU8CxCwESRpQ858hvv2/0MgjrJx40Y7l3huIZjyriFENpCQI4QoFF9//bW74IIL3OzZs3Me5hAKB2kWCeLuqQ/bdHiJoFwecSezxxzxzXfr1auvvprvds4Zet4pr6fNyAe0NAwbNswMWTEi5UWLSV+SSaOQwws6kxlWoaPMmTPHValSxSY0IhnwDMDUGEEnNBIvVqyYTYzxofIJVUmcI1wr0euGf2n/woDZJ7RDMgHPbAWhuowJuu/WM6o58LPDuygK4htik+/9kxQ4FohZ9erVy7NfECNnzJjhdTw1atSw5+Ljjz+e00qKeEE7Hu9gU6dOTWVFbdL8/zYF7xgIyplCjxDbCgk5QohCcd5555lA8MQTT9jkm+QLepZvvfVW827gBUQkpzonCseJbb7FtmgJ+6ZW9UgpGj16dE71RTbhhRhxiZdCvHF4YaZkHf+IgpI54iKNQk7FihXNVwQvjShTpkyx9hmEZJEsqM6k8oWWHfyMQv80nyDWUG1HtQvXDa1VPKf4GY8akhZ9wt+lbYj2qiiIXIiR/fv39zoe7v+I/kcddVSu7bTvsO+odksjCMcENeS3X6h+8S0cMx4qOzKT6aiEJrUpFExFMkFso+UsbF8UYluz6ZpGIYQoAMqNKcsmMpUJOh8m4azGkqYi4iez5z+El4o40komTpxoVRT8y4ovH74TS04CGquLiExMbnzACifRsqyWfffdd+6yyy6zVVeqmCihRywQ8RLeTzCl5hjx4TsVVT179rQWmfAjkgGtDgg4VDfEIeIAlUF33nmntRAh2D7yyCOudu3a7umnn3bdu3f3MoZbbrkl58N9mEUP/DyopuCDJwyVFgW1F2ULkvmokgoj4oHv7Bt+5xMEJRaGENL50JY9bdo0FwcIONxzoq3ifGdbprjjyxeN6tlMMKhGoPQNXlyIkvhg8eHeHPpz+YaFqJEjR5rHEh8M8ZNUCY7oRztlGKQgRDZId+SDEKLQ8MAMXyQQc5YtW2ZmpJTXkl4i4oOJAzB5QJiImp9y3KZPn+4qVarkfVxUUGBuGUYlw1lnnWWi0vXXX2/GtpiTRlOtfEA1GRM8Wg1YqcZ/5fvvv3f169e3ZCsqzEQ8cAyA9rdQlAwrupj8hT+n3fMpLhBCtxQ8WXzBogLG4JgsI5iEfiIsQPCzDzINlTGIhXDiy3OTD/e9OI7VpEmT3AEHHGBVb0C1H6IF92Rf4Kl09dVX29jCBSBMqhnDM888Y+K6TwYOHGj3FfZLaN5LNRf3Fwx2fXPxxRdb2y/PoPC5yf7BwyfTbynbvPnmmyay8e5A+3Y4Ftpe2Tf4YvmCij/a33hOhyb4iG0swowbN85M331CBXGmUfa6devs3YtzXIhsodYqIUShoHWKNioqF3jZwoD0rrvusok6feT4E4h4qFmzZs5KJ4aNrJCH8J3YeKpefEd3UiaOT0RmygTtMazes4JFHz4rn9kuGf/xxx/d0KFDTcCh1YKXd1bJMZYMX8jeffddS7xJSlk0L66kl+y7774uLXAOF8Wo3rTAJHxL4VoTBUPF2X777ZeVKp0kHivu9Yj4GGJHoQWNaqUwqckn69evd88//7z78ssvc8bIO05mSpMPENYQbRCYqCwDWvSoNEOkxIPKF8cff7w9H/m7Ue644w4TSmlJ8/ksZPrKcSpVqpRto5q3SZMmdu0g5vgk07OHMWBwTrWxjzZxkV4k5AghCr06wwsPK2msjrByjnFj6dKlzdwt09NC+IcXd1oKfMeMF7RKThUXccS85ABeDFdeeaWdS7RWsUp84403Zr2qC0GLVTuqf6jACccThXadBg0auLfeestlG1bpmTzxL8eMyiB8ew466KA8Rr9pIzN+l7YdVql9x++KogWm7jybEG35HgUfmCTCvZpKoqT4YFFxgRdLtgQD/nepSKKlKgrHDcF/w4YNWfm7RQ0WNsJKLp5b0SpbX1A5y6JLfobdVC/5PFaIah9++GGe6jqqyqgWSsriixDZRq1VQohCwcpMCC9hrF4R+ZhZYiriI2kr4EzGEUYoW6cEOuz1Z9ISpjrwAkZlV7ZBMKLVIVxlpRKIHntWX8Nzm0mVDxGHqhPSY3gBRczCpwIhh5dS9hmeMGmFxCqqophEhPG7mB/jgeI7flcUHZjkUUXBdZ2fuXpS2/CStrbKfSmbwhLPgcmTJ+cRcrg/h88I3yCY0OIbCscI6bR9+W7XiYJw46slcFOw2MG5kCnksC0zUCHbIADSupQJ7w/RCuQ4Fxw4b1go0oKDyCaqyBFC/C1YOePFhxVOWmc2ZbArBLAyzgScVTygv53eet+GnxifUk3WokULewFjHLwArlq1ysr6KV33Be1vJOzgbRRNpsK7hzHSbpFWkhS/K/Jvt9jS+73P1gt8PMqVK+e6du1qrYiZY0zq5CppyXTZHs+AAQPMuJwJb9QDBn8cKhObN2/ukuADwz7w5QPDPZ///ywkbM6DyqfvFOEWiOi0UkWPFabzPLvw4/MFVbzcTxBOQoEf77/rrrvOFmjYf74XHFgA4h04HA9t5LSLa8FBZBMJOUKIQkE/MgakVCzwkozPCC97vJBRlfPQQw/FPUQhNgkmo1TCsGpGmky/fv3MnJQUjE6dOnn1ZiDZh5J14pGjE6clS5ZY7Gya2wsUv5tsEEq2lM6dOztfUGnHdZRZ6ZF00ibkAJWQvC+E91yqIvGFoXrTN0nwgaElmrQj9j1tvwUJpT6rbpkuUqnEsSLcAvBz4lhRseRzAY/Fl6uuusrENTyDQoEfEQ4Rx7dQqwUHERdqrRJCFArMCXmAEo0ZjeUkZYHVGQk5AnghxcyS1hi+F4TP2HoEgDB1jRd0Vj6pCqpWrZq1Y/ikZMmS7ocffjAhJwoCRtqjS8P43UwhJ674XRGfOLM1YDJKtWhRE3LSyAUXXGCfJICY9OKLL+bZzgIVIoYPouKM78qSgkCo4b2PT9jWFNc9mGcm7dgsIEZNqeO63qnIiYo4wPd27drZgoMQ2UJCjhCiUDD5pQwZv5Mo9E/7ngiL5EIp9uWXX25CDt8Lekn0KeTwwjd69GibQHAeh6kpGKP6Noe+5JJLXPv27d1LL71k+4H2M0rWSRajhDzNJCl+VxQdWrVqZamKy5cvN2+RcNU+JIyWThppa0um0ocWFEISMisuaEehmiGtPjBAaATtUwgXmUb8JIZOmTLFxUFSRHSOk+/0zfzQgoOICwk5QohCQcpQfskJGB77jMQUyWbx4sX5fo8b2qcwQ0XAOeuss8ynJhQoKa/3Cca9JHVh7okJK6lM/Mv4fBg/JxkEHCa3CFr5xe+K5MA5i1hLRQOTGqKTM58NvmjYsGFOJUUI51Ho4Saz42QIS7SP5ncsfv/9d/f999873+CxQgUpAlJ+PjC+efvtt/NcR0C77bRp0xLhh8U2FmpYHKEVrGbNmlkfy6aORXQstOaF0eTZRgsOIi7kkSOEKBT16tUzU7lu3brZisOsWbPcwQcfbNUFVBSkOWlHbBm8wOMNw3mDr5JvWK2npalixYo5ZssYDLO6lrmy5gMmv3PmzLHkDV6ak7DSmBSSEL8rNi+O4jdFJQwCZMeOHW2iTuUbv/NZcbe5qlDuOUmEFXx8R3bYYQe3PXvkvPrqq/YvVSXPPvtsLk8TngskWU2cONHNnz/f+SQpPjC8TwGmy1TdRAUJ9s8bb7zhBg0aZNeXLzp06GDm1FS4RQ19GSsCDr5lHDcqiLLtb4RYhF8R+4KgAiBAgeuGZzfnDcfq3XfftYWRbIPYxjkycODAfBcctLgpsoWEHCFEoZg7d66V/VL+zIsGJnNsY9WVlYg4ozpFMiGdhJdAVq54ASPp7IMPPrBJ+dixY90ZZ5wR9xCFEIWEez4+WOeee64JALSjhNuIAx82bJhLE5tLHIorfSgJhMJ5WCUVhQnwIYccYmJK/fr1Yxqhi9UHhv0Tikb5TdMwgcegP1px5qNa6aCDDsqTTnXvvfeacIpHDJ5Z48aNM8+YbILYRkUSfkJhK/TatWvNXLh69eo2VipaSY2idTqb8C7DOy/vNgg2WnAQPpGQI4TYajZu3Ojq1q3revToYatmrNhRRYCoQ4sIca9CZIKfEqvzmP/xL+cKqWdDhw41MZCXoTTCY5gKNvYFHj1UtKV5kieKJiRFYRbLZI9nABO60OeECjMmWr4IKz4Kar3INBfPRvpQ9BonnYnKk9D8dMaMGeYFg+DjI30oiVHxHAOqOkgRTAK0/1JRkVkNialuKDD5AGGEc4ZKKKpE8e4J2Xnnnc2vx3fVFucu52ymoTCm4lRnc31jPFylSpUcESxbEALAu2dmtQ2LibVr17a2PM5hvq9atcplG+4p3PuyfU8RIhN55AghthpeaCinpR2G8nkhtgReqMqUKWPfX3/9dde4cWNXrlw5W1V85JFHXJorlSiTp1x8n332SZ3hqdh+hFpaFRFyWI3Gbwohh4m679YCWnbyq/aI+uSwco+gnK22zqg4g5n5RRddZK0X4QSclfwbbrjBm7k6+yTqsfLYY4/ZRDj0B6NqiokwY/JFknzTgBYhnkeZQs706dOtbRDPGh+ErX+Zon6cIFa8//77eYQctvG7cLzh92yCaMSiR6aQs3LlSjOCBgyi8/MXygYVKlQwwVpCjvCNhBwhRKFo0qSJe/LJJ2U4KrYYRAr66Fmtp8effvvQ/yQpnhBxQEUSVTf4TglRVCEBDo8Mor9JjQqfEXg/halwvmC1nkWG7t275/h5UNlAWwj+PVQXNG/e3JLhGGO2eeqpp8yvI3qf4zumrZijPvDAA16j4mlBwfMFj7vM/wafHp9wzmCSTUVDGCONuH322Wc733z66afu1FNPzbO9WrVq7qabbnJxwXMzPwNxWtp9wTXdokULq8qh6gYQaRG47rzzTvuZNiZ8fbINHjwIbrTfRcfC9RwKllzvLBT5gPYy/jbXE9VJVCdG8Z2EKdKDWquEEIV+qA8ZMsRWrvJ7cPXu3Tu2sYlk0qVLF+ttR8hBvMGckJV6Jjn01+OXk0ZYxRs/fnwsBstCZAsqPFit5xlx3nnnef3brJAPHjw4J0EmhPZNUomoPJk0aZJNBpkgZxuqfp555pk8JrBjxoyxKpA1a9Y4nyBk4WOSXwsRrV++2uCoCmrdurVr1KhRrsogWk0Rd2i/9b1fqLrJTC5EvMDDLdstQ5lQ5YFASihAtMIsrNr0nb72/PPPu0cffTTHhBqjYd4F8aMBPGnC9sVsQis/4jDvoKG58I477uiuuuoqO294H8WjC3wIS6HnE0QrapOekieKPhJyhBCFoqCISR5ceJ4IkQkv6Kz40lZFKwaQWkIZdLaTLpIK//+pUELQwsRSiKIInmlU3WUasHJe0/JAe5EvuI5YoUfQicKEmAodJpz4kFD9gaicbai8YdJJ5UJYIUS7DhWtV1xxhfeFD1pc+duISFEQmzhOK1as8DIOngF33HFHnmqX/v37u/vuu897BDmCI+fO8OHDc7XAES+9fv16E9x9j4dxUPWC4E+VyerVqy0ZjqjrGjVquDSDoIPYBfgJ7bbbbrGM45133inw96effrq3sYh0ISFHCCFEbGD2iYiTZphUsupKtQBmmnhQxWE8KsTfgXOXZKrMKhgEi0suucSrHwr+N6QNIZ6ERrGISVdeeaVNyKdOnWoVOVR8+Ii4xjuEiTdeYPgIAZWJVKMwKffdWoqI07VrV0v3iQpLiG60nyGu+ICJN5UTmb4rVAZRFcNE3XcLE2mKPJNCkYR0JHxXWJzKFAazDSbQ/N3jjjvOqoUQcqiCYRvnDa1gvp/XLMYgntBKRCw6zycEXAyIfYPRMilRHDMEuLACRoi0II8cIYQQXujZs6dN9ljdBMw/R44caRMazI95WU0jlINTuo+niMyORVFl+fLl+SYWIqSE4oUv8L2hwo+KjwMPPNC2UQnIqj3tTIBIgF+OD2i9aNeunX1CM9Y4fTMQatgXCEvPPfecbaM6CYNm7su+wOOFNK/bb78913aOURzR45jnEuRA+xBpnIgDiH9UDCFa+IZqoDD+HFFn2bJlJuRghuxDgIzCfsG3CEFpyZIl5rPEPsHfjfZERFNfUJXEeUrSI89LhD/O52uuucbaGPHO8b1v8iNsM8MA3rfhu0gHqsgRQgjhBUrD6bFnxR4zUl7ERowY4V588UV7ESTlJo3Qz49JJFUEQhRV8FvBLBdBMtPMm+1hC4QvqILhnoIXFzABrlWrVi4/C5/g5YH/ChUEeIowQWdijqATV0tI3GASS6USBsNRjxyqE6k4iYpdmDMnBZK97rnnnqzHplMVxH7AwJdzBi8lxEf8nxD/58yZ43yBiEMKXa9evezcRehCPMEHi7Eh7vgCcY3UKlrOECDDsfAcpY0RDyyfcE8paAGGKlsWsEin9JHqJdKDhBwhhBBeYHWTSRUr5LQUEIHLiw3bSLrxbfiZFDA5RsxKa0WS2D5ggseHBKYzzzwzJ5GIKhQmox06dHBpBT+eunXrmmD9+++/2z2PiSf3QX4mltw3SWiT2dK4ZibJvoXAgkBgoiWMY5hNECZoBbzwwgutjYgqJc6d0qVL2yJIeJ35gEoczo/DDjssl5DDuY1IyvPcp8cT+6ZixYq5xsI5wnPUd0seFWR4S1FZFk3JozIIERsRlyo4xByESyG2FWqtEkII4QVKnmlvQMjB3JfVWGA9Ic2pDrzsMdllMkfrmRBFESYxtDxQrRDGJLP6zATHh4jTt29fS6Tib/K9IHxXdyDYkAbFhJNJeAjeWPjU+CYpbTI+fZO2Jb7WwOvUqZPzHR+hL7/80v3000/2LPXdgktrUNgWGAVhKfSh8gXi1q677ppnO/smjham7t27W5ti9Hgde+yx1tqJ5xSiDpW3oUm1ENsKVeQIIYTwAj4DY8eOtRYMTBqZQNBS8MILL9hKflpNfXkpJzmHVTteTjPNjnk5FaKowGr4F198YRV4XOu+JlZUdxCpjVBSUKVHHNUdjIkWFCoXohUE3APxZfGRnJXUNpmiSHSfZRNi4FnkyPTn4ZlA3LZPnyXEPoRaqkcZD2IgJt20fWE2/PDDD3sbS7169VzlypVdt27d7FgwFnyDMFWnpZJKM59wr+OdhuraKAhvmHYTaBDXtS62b1SRI4QQwgt9+vSxihOqcphAhL4QGKGyip9WfL4AC5FtuK6rVKni/e9GqzuSVunB5DK/qsPvvvsux8zWJ0Sz09aaCS1VmFb7grVkJt2Y1uJ5wn6KQoVQmkGYIII88/mImPLqq69aSIDPytFGjRq5vffe24QJIrU5V/A2oiLFJ7w/nHXWWSbcUv1HRSu+OAhc+Cv5BgGHJDi8i3beeWfbtnHjRtsWijvff/+9tS0KsS2RkCOEEMILVJrgxZBJ27ZtXZohtUoIkT0QUWbPnm2r9lTA+aZ27dom2DLRC6uCqFzCP4PqAt8kpU2mTZs2JijVrFlTiX35QCR8796982w/44wzXMeOHb2OhTY8QgoQSqhG4vylqovqLt8QA8+5SroYQihjwUfoxhtvzDc5L9v079/fEthopQq97rjfcN+hChmoAkzzgpXIDmqtEkII4ZV58+aZD0PooxHCi1BaYBIVlsXnN6GKEmdMsRBFEQQCPCqII2YyRevHBx98YK2LTKyYCPuEyhv8M3jlJioZvxz+JfVo6tSpVuXgk6S0yfC3iT+PQ8wqCq1V+KqQ4sW5HAWRgIAAn206+CZh1pvZKslznPZokqR8wfsDXnv5CX/8jrhv36xbt85SOaMpeWE6nRDZQkKOEEIIL7AihbknL6G8gIWPn/BlLE2Gx0yaaCljArep6FL2D9vTtF+E2BawMj569GgTTPiXlXrad4hCnzJlSiztF3hgMeFFNAmrGS6//HLz1/AN3iu0ydCawgR0v/32y2mToV0HAcEHeBmNHz8+j7dI0mnZsqX5s2Q7fpxKJapP+vXrl2s75zPn0bRp01wcz6woCIJs8/mcStJYtoZzzz3XItPjqBoS2ycScoQQQniBXn9ewHiR4QWeJAdevMIkhxo1ari08M4777hTTz3VDCufffZZW11k30TBL4LVRbVeCbF1kFxFXDOCDklWVOJQZYJ3DpHFm6uCSwvvvvtuLmHJd5sM9z4SDJ966qlYBC3g//+WErbN+ALBkWOC5xSeMDB58mTzOJowYYLXZyYLDitWrMjTekdlEoKTT1P+TY2FKHQMhUm1SnMll0gPEnKEEEJ4gdVLVsN5GabfHiGH8mO2IeaQ+pBGiurqohBJBS+cxx9/3Ca/iMYDBgyw1XAMUatXr+7WrFnjfUy0Um3K1LdTp05ex4LhPOJx3GCaS5UmggVG+JmJfT6SDMOKyLACsiDiuBd/9tlnZu6LAIDYxfOzQ4cOlgjnA1KX2C/8/WOOOcYWH6L7A3G0bt261qaXbW655Rb7l6jv6667LlcEOWPBU4jnaRwVd1uChByxrZHZsRBCCC/wohX2iyPqLFu2zIQcJl3z5893aWVTEwhWyaksEEJsHVdffbW76KKLrIWBayusNGGiF0cbD6IS7Tjc98qUKZPreue7byEH0QRBq0mTJtZiFYcBNFBtOGPGDBtHXGbH0YQzFhMw5L/99tutzQzwViKxCTElDipVquSGDRvm4gLfpFBQwucpTJsEEpo4lxo2bOhlLOFiD89MWrTDhKhwLFTb5ReoIMT2iipyhBBCeIEycCpveDHEBJBV8bvuusuSXHiZnzNnjksTRX11UYgkQ6w1lSeNGze2FquwladkyZKuQYMGXseCWE1iTfv27V0SYEKMOIBnz8qVK62iAjGF9tdMM9tsghfPm2++aaJSEjjppJNcly5d8pgv4xt0991323PKNzwL8Hn64osv7GeqYggGyGzFzTZcO5gdJ2FxAaGW52ZRCwJQRY7Y1kjIEUII4QVe2OldJyYU/4r69etbwkPp0qXdiBEj3JlnnunSBL4CoV8Oq7+Zq4usdLK66KuEXojtmZ9//tlEnDhgwklFQ9ImcEwB3n77bRN1Ro4caS1f3J/xrPEB1VG05Pj2ntkUtC7RznXUUUfl2o6IgocQrWA+4TlJSyCpZ1SvAtWrtMWNGzfOHXbYYV7HI/4eEnLEtkZCjhBCiNjAIJGy/jhK6pNCUV1dFCKp9OzZ04RQKgiANiuEClqtqK7wLRwQg45hbYsWLVxSQcBgnJj/+vKCQYwgkWngwIF2vOIGsYaUKAz5Q2GdeG3i2qkY9eHZE4XKIKZpxFoT1R56p1E9hbcP+88XnBN9+vQx4Q0TfvZLFJ9mx0Di2qbGMmrUKJdEJOSIbY08coQQQnhfZfzqq6/caaedZi+naV9PePrpp+MeghDbFQgDTH5h4sSJ9iHmmokfVW4k/vjk8MMPt9acDz/80B177LF5TH1vvvlmFwdUelCNwwehgsrA/v37e/v7CBK//vqrVZbQWpq5X3yLA5w3tJfRiheKfQhbLDS89tprzjdUa3LOhCIOUMF6//33W+qhT7p27WoCF+3RtER37NjRLVmyxNq+fHs80RJ45ZVXmmcP13Lt2rWtupckK8yzfTN16lR3yimn5DKChj///NO9//779q4Dd955Z65jKcTfRRU5QgghvMBKIivjJLfwYkyKCytTzZo1s6ocDCWFEGJbtMgwsaMFpXXr1m7Dhg1u0KBBtq1q1areU6tIztoU3Au//vprr+NhXyDe4L9Fe9Pll19uvmV4+fjkmWeeKbAaEzNk39D+iwj45Zdf2s+0WbFv8PPxDZP+sWPHmkgQheOG4ORT6EJs69u3r7V6UVlCq2C4DbHJpyEzIlvz5s3djTfemFPlwjXGNqruEJ18ouRJEReqyBFCCOGFtm3b2oorpdBRDwLaHzD+lZAjhNgWIAyHEdtvvPGGu/fee207a5dxTKqiyUhJgP1x6aWX2iScpJ+4aNq0qUsaCDbXX3+9SwL4yDGWJ5980oyYARN8WvQwPPbJ8uXLrZoMSK5au3ZtzhipNvMJFb0ISkALHOIbgiDvGHjt+RZyNpU8iZAThwAo0oOEHCGEEF6gBBrD4zBBJgQz32+++Sa2cQkhti8w7KWKgnsLk6lzzjknJ62JNqe4wMsDUYdKhsw2DJ8gpifBl+z00083Xx6SxaiiSgJDhw61iiWqpIgep0oJbxiqR32nnSG0UZVEy1vYdrZx40Ybx8MPP+x1LDy3qTo56KCD7PzleY6n0Mcff+w16SwUatetW2ff999/f2sLRGTC0JxWPZ/3GeBaQpSM7gcEY9ryMquphNiWSMgRQgjhBVbNohHbIZSH+34RFEJsvzDxxjyXqpxevXpZBQEwESUG3DdMLlu1amURzkCLF8IA25iI3nHHHVkfA5PKLcWXGfTxxx9vnkXsB9puEXWqVavm4mLAgAHm99KmTRurWgqrtxAOEE58CzmkrI0ZM8Z85cL4capZ4xAj8Z6ZPHmytSZyvPA3olIIUZBKGJ/gOYPvFeINIiDtk1OmTLFtZ511lrdx7L777jkVObR4RcVIKoU4l6+77jpv4xHpQx45QgghvCVwVK5c2XXr1s1eephYsNp5ySWXWOztyy+/HPcQhRDbEfPmzcs31cZ3WwoTTXxNEAPq1q1r9z6EHCbpXbp0sUqhbEPKEZUDm3rtD3/Hvz7bzzCEffXVV03kwpAakQLftCuuuMLts88+zidHH320u++++9z555+fK2GIio8zzjjDrVq1KutjoM14S+ndu7eLC3xxMPKl6g2/Hp+w+IPv1X777WfvDoi14VgwYkZ48wmtXAiSaqMSvpGQI4QQwgtz5861/nXKsVk9YzLFNl7KmORQri2EEH8X2mJoe5g9e7b9HL7qhu1Evn1yEKxHjBhhK/RRgYBKC+6Hv/zyS9bHsDXtq75Nj0N+/PFHN3jwYNe9e3c7Roj/JHrx3PABFRWYHPP/P3qcMOanSum3337L+hhq1qy5Rf8d5zLPUV/06NHDhDVEtihPPfWUW7lypWvfvr23sQgh/g+1VgkhhMg69PXzQk6EK+XPvCT/97//tckWyRMkTQghxLaqgKG1atKkSZZm89FHH5lXDtHJDz74oPfxMNHNTLSB0KTVB3GJM1sKx+jpp5+2aGn2FZ4j33//vZnp0g7n47hxrpDGlLmvMMyOGvRnE1Idk0iYdJbJMcccY1W1PoWc119/3ZKiiB+Pgm8PAmDoieULYs+pyKH1DDEys0ZCqVUiW0jIEUIIkXUwaqSdgJLnjh07xj0cIcR2DCa1VCvsueee1lLEp3r16lZVgKDso5UpyoknnujGjRtn3iIQijdPPPGEGdnGAck/tHqF3iu0FSGA+ayMZNKLuTACDlUvtOgMHz7cJujhPkLQoR3Nh5BDWxMLC7TtMBlHXGI8nDccqzRDalV+Cy577bWXeU/5BE+p+++/P8922qz4nW8hh3OUFk7Su9hHSTASF+lAQo4QQggvhOaI+b2ACSHEtoIVcKr+ADFn2bJl7sgjj7RKi/nz53sfD74rTC7x7MET5pFHHrHv+Hq888473sdDeiCtrZUqVXKnnnqqbaO9leoKqiZr1arlLQkJ4Yh2HSbDiAKZ0NJUpUoVL+O59tprrb0KnxUMqkk+w4eF40XVSZo58MAD7RyhaikK29hHPkH0Q3jMpHz58tau6Jt3333XTZs2za4nIXwiIUcIIYQXmMDQT0+7A6bHmcaAcRo3CiG2HypUqGD+Jkw6SdnBDJUUGfxX8DzxDdVAtOwgYpO0E0Y3UznEz76haoGkoUxRne20yPgScjKfBfj4vPLKK9bGFLbN/Pvf//babnT55ZfbByGH9t/8WuLSCOlLpHnRJh16FtFK1K5dO2tZ9AlpUfhg0T4ZBREnDsNhRC5Zzoo4kNmxEEIILxRk4ujbuFEIsf1CxQn+M3hwMbnDZ4XI79KlS5vpsC/z3KRSvHhxM4Im5ScK+4gKGFqLfFC7dm07Ri1atHA///yzVU0huJEOhbDfsmVL5xPMjJkW7brrrrmEJao/GGuaYb8g9PXt2zcnBY7zCOGPyHafNG/e3ERQjk3YCsh13rBhQ6ve8t0GhzD70EMPmY9QprgkRDaRkCOEEEIIIbZrSMfDoysu/wravZh4Rj1pGjRo4HbcccdYKggQSho3bpxr+4svvmimrfh9+IC2N1rLaOli8t2vXz/zLxo5cqSJA+G+8kXShKUkQpUSx4UWNITAYsWKeR/D2rVrzTfpk08+sfY8+O6771yNGjXcqFGjXMmSJb2Oh/sKFVxUHSMC4gmYee8RIhuotUoIIYQQQmzXlCpVKra/PXfuXPOkwTAWcQB69uxpnjB40tAK5rtN5vrrr7f2lFNOOSXH64QxYfjrCya/oZcRVQ2IKBhTE9O+NXHp24qZM2e6Pn362PeXX37ZlSlTJpewJCHHud12282bZ1FBrVX4S5GASQslohKVZKeddlos48E0XIg4UEWOEEIIIYQQWYJkKkSbZ5991lbvYc2aNWbwSzQ5k1Kf8OrP5JN2EIygAcPa22+/3VK9fFUtMfnGYPiCCy4wMYuYb/bVjBkz3LnnnmvCl0+opvjyyy/dQQcd5C666CKrFOrcubP79ttvTYBDeBJCiKQgIUcIIYQQQogsQcUAbSAIA1HmzJlj1Q14s8TFunXr7N+wMsYnVL2QDEXb2VlnnWVVOUDc99SpU9348eO9jidpwpLYNBgtUz0Vtt9hkI0Z89lnnx3LeL766iv39NNP27+knGGSzfmLKJh53Quxrfhn3AMQQgghhBBie6VcuXJuxYoVebb/+OOP7vDDD/c+HoSjsLoEAQcPDyp0QiHFF40aNTI/HkQuRJMQRJ2wxckntE/hEYRh7UknnWQiDrBfjj/+eO/jEfnz2GOPmUcO527r1q3tQ7pZvXr1XP/+/b2PB58n0uemT59uHj34CAFtX1R0CZEtVJEjhBBCCCFElnj99dctprlLly7m/wIffvihu+eeeywCnHjyECak2UamvpuGqpsffvjBVaxY0fx64KOPPrLjUr58+biHJ5wzg2MStG666aZc2xFx7rvvPvf99997HQ+CH8bh+EshLiHgHHrooXbecJ1hxCxENpCQI4QQQgghRJYIBQEI/WfC1+/oz3ynzShtaVFJJJx8h6lIIlmGy5999lmearaFCxda5VRYEeNzPLNnz3Zly5bNJeQsWbLExL8NGzZ4HY9ID0qtEkIIIYQQIku89dZbLkkkLS0qKfz111/u3nvvNRPoUAxgP916662uY8eOuQQ5ER8kwL3yyitmzh1lzJgxrn79+t7HQ9w5VVwIOVEQR/fff3/v4xHpQUKOEEIIIYQQWeL000+3FqYnn3wyp9rl6KOPdtdcc41FKfuGSobRo0ebqe+bb77p2rZtm+PZ46O1K6kg1nCMaHc79dRTbdu7775rLXFUVXTv3j3uIaaWvn375nzn2uFYvP322zk+RrQqvvfeeya6+eaSSy5x7du3dy+99JJV1SEIMhb8lq688krv4xHpQa1VQgghhBBCZAnMfDFnLV68uJnowscff2ymw1TEnHDCCbGlRZ155plu4sSJsaZFJQUi2AcOHGgVH5mVHjfccIN37xXx/8isdtkUCClff/2188kff/zhbrzxRvfMM8/YNbXjjjvav1xjbNthhx28jkekBwk5QgghhBBCZIkaNWpYFczjjz9ukzz4888/LeqaSSfiiW9k6psXhLZZs2ZZyliU+fPnu0qVKsUaEy+SDwlsc+bMsbY8vHqOOOKIuIcktnMk5AghhBBCCJEldtllF/PLyBRI5s2b50488cScKHDfLFq0yH311VfutNNOszGGhstppWrVqvaJtvFAq1atrIKK9h0hhEgK8sgRQgghhBAiS1Dlwmp9ppDz7bff5pgO+2T16tXuoosuMhNmhBvSfkjZwbNnjz32MLPfNNKrVy937rnnukmTJuV4r3zwwQd2nIiQF8mgWbNmBf7+qaeecj5BAKVdkesJnyk8cqKMGjXK63hEepD9uhBCCCGEEFni4osvNpFkxIgRJgrweeGFF6y16tJLL/U+HsyNd9ppJxOXdt1111zjfOONN1yaTakXLFhgJtCYU/Mh0YvWKtrjRDJYs2ZNrg/iyZQpU0ww4Zj5pk2bNu6KK65wixcvtihyDMyjHyGyhVqrhBBCCCGEyKIZKlHJGOnijQMIKS1btrSEpGLFinkdT5kyZSytCn8cKoI+//xzq8jBr+e4447Lid4WoqhAFQzX02GHHebatWvn9W+XKlXKPffcc65evXpe/64QEnKEEEIIIYTIMnjh4EkDTDij1TA+QbyZOXOmmbFGhRzSterUqWOtV2kBc+MtBZFLJBcqp8444wwz8fadqEXSW1pNwkV8yCNHCCGEEEKILINwc+yxx8Y9DGsTGjJkiOvWrZv9jE8OFQ14xNSsWdOlCdKo+P+/uXVt/hsipUVyQSQNK9580qVLF9e1a1fz5sE0XAhfSMgRQgghhBAiJTzwwAPuzDPPtAoc2r5oRZk7d6776aef3HvvvefSBL4momhxyy235PoZEY4qnHHjxrmrrrrK+3gwDh8+fLjbe++93SGHHGJtk1GofhMiG0jIEUIIIYQQIgVs3LjR3Xzzze61115zEydOtNYqPHEw9b3xxhvdvvvu69LEwQcfnPO9R48ebp999smTikSlxcqVK1379u1jGKHI5NNPP8318z//+U+31157Wdra5hKtsgHi0YwZM1yTJk3s/KF6SwgfyCNHCCGEEEKIlMCk9/333zePHPH/oJpi2LBh7pRTTsm1ffr06e6SSy5R9U6CvKaYvpYoUcJ+XrJkiRs9erQ76qijzOPJN4wD8/Dq1at7/9si3Sh+XAghhBBCiJRA5cCTTz4Z9zASx/Lly/OtSEL48m2gKzbN+eef74YOHWrfiRuvVq2aVeOwfcCAAd7Hc+CBB7p///vf3v+uEGqtEkIIIYQQIiVgCEu70KRJk1zlypVzKhtCevfu7dIIE3I8gkghisK2/fbbL7ZxCZfHc6ZPnz72/eWXX7Z2JtqtRo4c6Tp16mQx5D5BRMJnauDAgVbVJYQvJOQIIYQQQgiREubMmeNOOOEE+75gwYJcv0uzv8d1113n2rRpYz5CmEHD5MmTbZJ+6623xj08EWmtwtsJJkyYYP5O+ORQmfPNN9/EUuHGmA477DBLpss0O8ZEXIhsICFHCCGEEEKIlPDWW2/FPYREcvvtt7vVq1e7G264wdK8oHjx4mZy3KFDh7iHJ/5/Dj/8cPPEueCCC8ybpm3btrb9xx9/jKXF6eGHH/b+N4UAmR0LIYQQQgghhHOW4vXFF1+4XXbZxQyhixUrFveQRATaqS677DL3v//9z5111llWlROmjk2dOtWNHz8+7iEK4QUJOUIIIYQQQgghiowxNQbUFStWtLYq+Oijj6wip3z58t7H89dff7lFixZZVRDfo5x22mnexyPSgYQcIYQQQgghhBBiK/nwww+tQgh/nsxpNZ5TVA4JkQ0k5AghhBBCCCGEEFtJpUqVXLly5VzXrl0tvj7TMHz33XePbWxi+0ZCjhBCCCGEEEIIsZWUKFHCff7552bCLIRP/q+pUAghhBBCCCGEEFtM1apVzR9HCN8oflwIIYQQQgghhNhKWrVq5W699VYzYD722GPdTjvtlOv3xx13XGxjE9s3aq0SQgghhBBCCCG2kjA1Kwo+OUyxZXYssokqcoQQQgghhBBCiK1k8eLFcQ9BpBRV5AghhBBCCCGEEEIUEVSRI4QQQgghhBBCbCWvvvpqvttpqypevLilWZUtW9b7uMT2jypyhBBCCCGEEEKIQnjkhJ44m/LJqV69uhs9erTbY489Yhun2P5Q/LgQQgghhBBCCLGVTJw40VWpUsX+Xbt2rX34Tiz52LFj3dSpU93q1avdbbfdFvdQxXaGKnKEEEIIIYQQQoitpEKFCm7w4MHulFNOybX9vffec9dff72bO3eumzRpkmvWrJlbunRpbOMU2x+qyBFCCCGEEEIIIbaSr776yv373//Os51tX3/9tX0/4ogj3KpVq2IYndiekZAjhBBCCCGEEEJsJZUrV3a33367W7lyZc42vrdr185armDhwoXuwAMPjHGUYntEqVVCCCGEEEIIIcRW8uSTT7oGDRq4Aw44IEes+fbbb92hhx7qxowZYz//97//dXfddVfMIxXbG/LIEUIIIYQQQgghCsFff/3lJkyY4BYsWGA/H3nkka5WrVqWaCVEtpCQI4QQQgghhBBCCFFEUGuVEEIIIYQQQgixBfTt29cSqYoXL27fC+Lmm2/2Ni6RLlSRI4QQQgghhBBCbAFly5Z1n3zyiStdurR93xT/+Mc/cpKrhNjWSMgRQgghhBBCCCGEKCLIgUkIIYQQQgghhPib/O9//3OfffaZW7NmTdxDEds5EnKEEEIIIYQQQoitpE2bNhZBHoo4p512mjvhhBMsivztt9+Oe3hiO0ZCjhBCCCGEEEIIsZW8/PLLrmLFivb9tddec0uWLHFffvmla9u2revYsWPcwxPbMRJyhBBCCCGEEEKIrWTVqlWuTJky9v311193jRs3duXKlXPNmjVzs2fPjnt4YjtGQo4QQgghhBBCCLGV7LPPPm7evHnWVvXGG2+4WrVq2fZff/3V7bDDDnEPT2zH7Bj3AIQQQgghhBBCiKLG1Vdf7S666CK37777Wtz42WefbdunT5/uypcvH/fwxHaMhBwhhBBCCCGEEGIr6dKli6tQoYL79ttvra2qWLFitp1qnDvuuCPu4YntmH8EQRDEPQghhBBCCCGEEKKo8/PPP7uSJUvGPQyxnSOPHCGEEEIIIYQQYivp2bOnGzFiRM7PtFmVLl3aHXDAAW7WrFmxjk1s30jIEUIIIYQQQgghtpKBAwe6Aw880L5PnDjRPuPHj3d169Z1t912W9zDE9sx8sgRQgghhBBCCCG2kuXLl+cIOWPHjrWKnNq1a7tDDjnEVa1aNe7hie0YVeQIIYQQQgghhBBbyR577GFGx0D8eJhahQ0tkeRCZAtV5AghhBBCCCGEEFvJhRde6C677DJ3xBFHuNWrV7tzzjnHtn/66afu8MMPj3t4YjtGQo4QQgghhBBCCLGV9OnTx9qoqMrp1auX22233Wz7Dz/84G644Ya4hye2YxQ/LoQQQgghhBBCFJJ58+a5pUuXuj/++CPX9v/85z+xjUls36giRwghhBBCCCGE2Eq+/vpra6+aPXu2/RzWSPzjH/+wf+WTI7KFzI6FEEIIIYQQQoitpHXr1tZatWLFCrfrrru6uXPnuqlTp7oTTzzRvf3223EPT2zHqLVKCCGEEEIIIYTYSvbcc083ZcoUd9xxx7ndd9/dffTRR+7II4+0bbfeequZHguRDVSRI4QQQgghhBBCbCW0Tv3rX//KEXWWLVtm3w8++GA3f/78mEcntmfkkSOEEEIIIYQQQmwlFSpUcJ9//rkrW7asq1q1qiVX7bzzzm7w4MHu0EMPjXt4YjtGrVVCCCGEEEIIIcRW8uabb7r169eb4fGiRYtc/fr13YIFC1zp0qXdiBEj3Jlnnhn3EMV2ioQcIYQQQgghhBBiG/DTTz+5PfbYIye5SohsICFHCCGEEEIIIYQQooggs2MhhBBCCCGEEEKIIoKEHCGEEEIIIYQQQogigoQcIYQQQgghhBBCiCKChBwhhBBCCCGEEEKIIoKEHCGEEEIIIYQQQogigoQcIYQQQgghhBBCiCKChBwhhBBCCCGEEEIIVzT4/wDcXnI/E8w9NgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Only use numeric features\n",
    "numeric_df = df.select_dtypes(include=[\"int\", \"float\"])\n",
    "\n",
    "# numeric_df = numeric_df.drop(columns=[\"time_to_resolution\"])\n",
    "\n",
    "plt.figure(figsize=(12, 10))\n",
    "sns.heatmap(numeric_df.corr(), annot=True, cmap=\"coolwarm\", fmt=\".2f\")\n",
    "plt.title(\"Correlation Heatmap\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "7da09dc1-5cf1-44a1-902f-1bd46c228146",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dropped column: assigned_avg_resolution (due to high correlation with resolved_by_avg_resolution)\n"
     ]
    }
   ],
   "source": [
    "df.drop(columns=['assigned_avg_resolution'], inplace=True)\n",
    "print(\"Dropped column: assigned_avg_resolution (due to high correlation with resolved_by_avg_resolution)\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "ca98454a-df6b-40e9-bf41-657bd9894036",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 138566 entries, 0 to 141711\n",
      "Data columns (total 28 columns):\n",
      " #   Column                           Non-Null Count   Dtype  \n",
      "---  ------                           --------------   -----  \n",
      " 0   incident_state                   138566 non-null  object \n",
      " 1   reassignment_count               138566 non-null  int64  \n",
      " 2   reopen_count                     138566 non-null  int64  \n",
      " 3   sys_mod_count                    138566 non-null  float64\n",
      " 4   contact_type                     138566 non-null  object \n",
      " 5   impact                           138566 non-null  object \n",
      " 6   urgency                          138566 non-null  object \n",
      " 7   priority                         138566 non-null  object \n",
      " 8   knowledge                        138566 non-null  bool   \n",
      " 9   u_priority_confirmation          138566 non-null  bool   \n",
      " 10  notify                           138566 non-null  object \n",
      " 11  time_to_resolution               138566 non-null  float64\n",
      " 12  reassignment_count_log           138566 non-null  float64\n",
      " 13  sys_mod_count_log                138566 non-null  float64\n",
      " 14  time_to_resolution_log           138566 non-null  float64\n",
      " 15  opened_hour                      138566 non-null  int32  \n",
      " 16  opened_dayofweek                 138566 non-null  int32  \n",
      " 17  opened_month                     138566 non-null  int32  \n",
      " 18  opened_weekend                   138566 non-null  int64  \n",
      " 19  caller_avg_resolution            138566 non-null  float64\n",
      " 20  opened_by_avg_resolution         138566 non-null  float64\n",
      " 21  resolved_by_avg_resolution       138566 non-null  float64\n",
      " 22  symptom_avg_resolution           138566 non-null  float64\n",
      " 23  closed_code_avg_resolution       138566 non-null  float64\n",
      " 24  location_avg_resolution          138566 non-null  float64\n",
      " 25  category_avg_resolution          138566 non-null  float64\n",
      " 26  subcategory_avg_resolution       138566 non-null  float64\n",
      " 27  assignment_group_avg_resolution  138566 non-null  float64\n",
      "dtypes: bool(2), float64(14), int32(3), int64(3), object(6)\n",
      "memory usage: 27.2+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d27cdb0-cfcf-4092-a5d7-481af582b913",
   "metadata": {},
   "source": [
    "We dropped assigned_avg_resolution due to high correlation (0.80) with resolved_by_avg_resolution. While both represent resolution contributors, the resolved_by feature is more directly tied to the actual completion of the ticket, making it a stronger predictor of resolution time. Removing assigned_avg_resolution reduces redundancy and avoids multicollinearity in downstream modeling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "5cce1cc1-8980-4754-b5bf-37cc49e3bed4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "incident_state vs time_bin: Chi2 = 12146.05, p = 0.00000, dof = 14\n",
      "contact_type vs time_bin: Chi2 = 48.42, p = 0.00000, dof = 6\n",
      "notify vs time_bin: Chi2 = 42.17, p = 0.00000, dof = 2\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from scipy.stats import chi2_contingency\n",
    "\n",
    "# Load and bin the target\n",
    "#df = pd.read_csv(\"incident_event_log.csv\")\n",
    "df = df.dropna(subset=['time_to_resolution'])\n",
    "\n",
    "# Create bins (customize based on your data's distribution)\n",
    "bins = [0, 5, 15, df['time_to_resolution'].max()]\n",
    "labels = ['Low', 'Medium', 'High']\n",
    "df['time_bin'] = pd.cut(df['time_to_resolution'], bins=bins, labels=labels)\n",
    "\n",
    "# Now run Chi-Square test between time_bin and each categorical feature\n",
    "def run_chi2(cat_var):\n",
    "    ct = pd.crosstab(df[cat_var], df['time_bin'])\n",
    "    chi2, p, dof, _ = chi2_contingency(ct)\n",
    "    print(f\"{cat_var} vs time_bin: Chi2 = {chi2:.2f}, p = {p:.5f}, dof = {dof}\")\n",
    "\n",
    "run_chi2('incident_state')\n",
    "run_chi2('contact_type')\n",
    "run_chi2('notify')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d06a2c7-de9c-41ac-98e8-e83055e7f26a",
   "metadata": {},
   "source": [
    "\n",
    "we calculated chi-square test on original time_to_resolution. Chi-Square tests require categorical variables. Binning original `time_to_resolution` retains real-world interpretability (e.g., hours), while log values distort scale, making categories less meaningful for assessing categorical associations."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "843b79e0-5abe-4dd2-b4d1-c90289d2ca15",
   "metadata": {},
   "source": [
    "The Chi-Square test results show that `incident_state`, `contact_type`, and `notify` are all significantly associated with `time_bin` (a binned version of `time_to_resolution`), with very low p-values (p < 0.00001). This means these features have a meaningful relationship with how long incidents take to resolve. \n",
    "\n",
    "Dropping them would remove valuable information that could help the model understand patterns in resolution time. Instead of dropping, we should keep these columns as they are likely to improve the model’s predictive accuracy."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c04552f7-5836-49fc-85d2-8d02439feb98",
   "metadata": {},
   "source": [
    "#### ONE HOT ENCODING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "5c06d9f6-bcb0-4be4-84fd-dc9ca464691d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['incident_state', 'contact_type', 'impact', 'urgency', 'priority', 'notify']\n"
     ]
    }
   ],
   "source": [
    "cat_cols = df.select_dtypes(include=[\"object\"]).columns.tolist()\n",
    "print(cat_cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "d0abbf79-fc2c-492d-b931-98fe84e2df18",
   "metadata": {},
   "outputs": [],
   "source": [
    "encode_cols = ['incident_state', 'contact_type', 'notify']\n",
    "df = pd.get_dummies(df, columns=encode_cols, drop_first=True)\n",
    "df = df.astype({col: int for col in df.columns if df[col].dtype == 'bool'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "ed39d53a-ce18-497c-8d0a-160c548d14b0",
   "metadata": {},
   "outputs": [
    {
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       "\n",
       "    .dataframe thead th {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>reassignment_count</th>\n",
       "      <th>reopen_count</th>\n",
       "      <th>sys_mod_count</th>\n",
       "      <th>impact</th>\n",
       "      <th>urgency</th>\n",
       "      <th>priority</th>\n",
       "      <th>knowledge</th>\n",
       "      <th>u_priority_confirmation</th>\n",
       "      <th>time_to_resolution</th>\n",
       "      <th>reassignment_count_log</th>\n",
       "      <th>...</th>\n",
       "      <th>incident_state_Awaiting Problem</th>\n",
       "      <th>incident_state_Awaiting User Info</th>\n",
       "      <th>incident_state_Awaiting Vendor</th>\n",
       "      <th>incident_state_Closed</th>\n",
       "      <th>incident_state_New</th>\n",
       "      <th>incident_state_Resolved</th>\n",
       "      <th>contact_type_Email</th>\n",
       "      <th>contact_type_Phone</th>\n",
       "      <th>contact_type_Self service</th>\n",
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       "      <th>3</th>\n",
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       "<p>5 rows × 37 columns</p>\n",
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      ],
      "text/plain": [
       "   reassignment_count  reopen_count  sys_mod_count      impact     urgency  \\\n",
       "0                   0             0            0.0  2 - Medium  2 - Medium   \n",
       "1                   0             0            2.0  2 - Medium  2 - Medium   \n",
       "2                   0             0            3.0  2 - Medium  2 - Medium   \n",
       "3                   0             0            4.0  2 - Medium  2 - Medium   \n",
       "4                   0             0            0.0  2 - Medium  2 - Medium   \n",
       "\n",
       "       priority  knowledge  u_priority_confirmation  time_to_resolution  \\\n",
       "0  3 - Moderate          1                        0           10.216667   \n",
       "1  3 - Moderate          1                        0           10.216667   \n",
       "2  3 - Moderate          1                        0           10.216667   \n",
       "3  3 - Moderate          1                        0           10.216667   \n",
       "4  3 - Moderate          1                        0           29.200000   \n",
       "\n",
       "   reassignment_count_log  ...  incident_state_Awaiting Problem  \\\n",
       "0                     0.0  ...                                0   \n",
       "1                     0.0  ...                                0   \n",
       "2                     0.0  ...                                0   \n",
       "3                     0.0  ...                                0   \n",
       "4                     0.0  ...                                0   \n",
       "\n",
       "   incident_state_Awaiting User Info  incident_state_Awaiting Vendor  \\\n",
       "0                                  0                               0   \n",
       "1                                  0                               0   \n",
       "2                                  0                               0   \n",
       "3                                  0                               0   \n",
       "4                                  0                               0   \n",
       "\n",
       "   incident_state_Closed  incident_state_New  incident_state_Resolved  \\\n",
       "0                      0                   1                        0   \n",
       "1                      0                   0                        1   \n",
       "2                      0                   0                        1   \n",
       "3                      1                   0                        0   \n",
       "4                      0                   1                        0   \n",
       "\n",
       "   contact_type_Email  contact_type_Phone  contact_type_Self service  \\\n",
       "0                   0                   1                          0   \n",
       "1                   0                   1                          0   \n",
       "2                   0                   1                          0   \n",
       "3                   0                   1                          0   \n",
       "4                   0                   1                          0   \n",
       "\n",
       "   notify_Send Email  \n",
       "0                  0  \n",
       "1                  0  \n",
       "2                  0  \n",
       "3                  0  \n",
       "4                  0  \n",
       "\n",
       "[5 rows x 37 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "ec6e15dd-55a9-4673-b752-9df59ff60f96",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "incident_state: 7 new columns\n",
      "contact_type: 3 new columns\n",
      "notify: 1 new columns\n"
     ]
    }
   ],
   "source": [
    "# Re-run just to be safe\n",
    "encode_cols = ['incident_state', 'contact_type', 'notify']\n",
    "\n",
    "# Count how many new one-hot columns exist for each\n",
    "for col in encode_cols:\n",
    "    one_hot_cols = [c for c in df.columns if col + \"_\" in c]\n",
    "    print(f\"{col}: {len(one_hot_cols)} new columns\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f6e5e809-8e3a-451a-bd40-fade1ed6762e",
   "metadata": {},
   "outputs": [
    {
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       "      <th>4</th>\n",
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      ],
      "text/plain": [
       "   reassignment_count  reopen_count  sys_mod_count      impact     urgency  \\\n",
       "0                   0             0            0.0  2 - Medium  2 - Medium   \n",
       "1                   0             0            2.0  2 - Medium  2 - Medium   \n",
       "2                   0             0            3.0  2 - Medium  2 - Medium   \n",
       "3                   0             0            4.0  2 - Medium  2 - Medium   \n",
       "4                   0             0            0.0  2 - Medium  2 - Medium   \n",
       "\n",
       "       priority  knowledge  u_priority_confirmation  time_to_resolution  \\\n",
       "0  3 - Moderate          1                        0           10.216667   \n",
       "1  3 - Moderate          1                        0           10.216667   \n",
       "2  3 - Moderate          1                        0           10.216667   \n",
       "3  3 - Moderate          1                        0           10.216667   \n",
       "4  3 - Moderate          1                        0           29.200000   \n",
       "\n",
       "   reassignment_count_log  ...  incident_state_Awaiting Problem  \\\n",
       "0                     0.0  ...                                0   \n",
       "1                     0.0  ...                                0   \n",
       "2                     0.0  ...                                0   \n",
       "3                     0.0  ...                                0   \n",
       "4                     0.0  ...                                0   \n",
       "\n",
       "   incident_state_Awaiting User Info  incident_state_Awaiting Vendor  \\\n",
       "0                                  0                               0   \n",
       "1                                  0                               0   \n",
       "2                                  0                               0   \n",
       "3                                  0                               0   \n",
       "4                                  0                               0   \n",
       "\n",
       "   incident_state_Closed  incident_state_New  incident_state_Resolved  \\\n",
       "0                      0                   1                        0   \n",
       "1                      0                   0                        1   \n",
       "2                      0                   0                        1   \n",
       "3                      1                   0                        0   \n",
       "4                      0                   1                        0   \n",
       "\n",
       "   contact_type_Email  contact_type_Phone  contact_type_Self service  \\\n",
       "0                   0                   1                          0   \n",
       "1                   0                   1                          0   \n",
       "2                   0                   1                          0   \n",
       "3                   0                   1                          0   \n",
       "4                   0                   1                          0   \n",
       "\n",
       "   notify_Send Email  \n",
       "0                  0  \n",
       "1                  0  \n",
       "2                  0  \n",
       "3                  0  \n",
       "4                  0  \n",
       "\n",
       "[5 rows x 37 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a83b710-a730-4370-a924-11649c505b3f",
   "metadata": {},
   "source": [
    "#### Label-encoding. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "eefb15f8-105c-4a80-8d70-34023f0abdc3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the ordinal order for each column\n",
    "impact_order = [\"3 - Low\", \"2 - Medium\", \"1 - High\"]\n",
    "urgency_order = [\"3 - Low\", \"2 - Medium\", \"1 - High\"]\n",
    "priority_order = [\"4 - Low\", \"3 - Moderate\", \"2 - High\", \"1 - Critical\"]\n",
    "\n",
    "# Apply label encoding based on order\n",
    "df[\"impact\"] = pd.Categorical(df[\"impact\"], categories=impact_order, ordered=True).codes\n",
    "df[\"urgency\"] = pd.Categorical(df[\"urgency\"], categories=urgency_order, ordered=True).codes\n",
    "df[\"priority\"] = pd.Categorical(df[\"priority\"], categories=priority_order, ordered=True).codes\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "7e9d5f01-7888-4e6e-b128-2dc3cc27e9d5",
   "metadata": {},
   "outputs": [
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       "   reassignment_count  reopen_count  sys_mod_count  impact  urgency  priority  \\\n",
       "0                   0             0            0.0       1        1         1   \n",
       "1                   0             0            2.0       1        1         1   \n",
       "2                   0             0            3.0       1        1         1   \n",
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       "4                   0             0            0.0       1        1         1   \n",
       "\n",
       "   knowledge  u_priority_confirmation  time_to_resolution  \\\n",
       "0          1                        0           10.216667   \n",
       "1          1                        0           10.216667   \n",
       "2          1                        0           10.216667   \n",
       "3          1                        0           10.216667   \n",
       "4          1                        0           29.200000   \n",
       "\n",
       "   reassignment_count_log  ...  incident_state_Awaiting Problem  \\\n",
       "0                     0.0  ...                                0   \n",
       "1                     0.0  ...                                0   \n",
       "2                     0.0  ...                                0   \n",
       "3                     0.0  ...                                0   \n",
       "4                     0.0  ...                                0   \n",
       "\n",
       "   incident_state_Awaiting User Info  incident_state_Awaiting Vendor  \\\n",
       "0                                  0                               0   \n",
       "1                                  0                               0   \n",
       "2                                  0                               0   \n",
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       "4                                  0                               0   \n",
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       "0                   0                   1                          0   \n",
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       "2                   0                   1                          0   \n",
       "3                   0                   1                          0   \n",
       "4                   0                   1                          0   \n",
       "\n",
       "   notify_Send Email  \n",
       "0                  0  \n",
       "1                  0  \n",
       "2                  0  \n",
       "3                  0  \n",
       "4                  0  \n",
       "\n",
       "[5 rows x 37 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "972a0795-d809-48d6-896e-dbd881c96662",
   "metadata": {},
   "source": [
    "#### Boolean encoding "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "9349f21d-3aef-4d7b-8ed3-7a247696dc01",
   "metadata": {},
   "outputs": [],
   "source": [
    "bool_cols = df.select_dtypes(include=\"bool\").columns\n",
    "\n",
    "for col in bool_cols:\n",
    "    df[col] = df[col].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "55d5723a-43be-4b6e-b626-baa1de64cf25",
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "   reassignment_count  reopen_count  sys_mod_count  impact  urgency  priority  \\\n",
       "0                   0             0            0.0       1        1         1   \n",
       "1                   0             0            2.0       1        1         1   \n",
       "2                   0             0            3.0       1        1         1   \n",
       "3                   0             0            4.0       1        1         1   \n",
       "4                   0             0            0.0       1        1         1   \n",
       "\n",
       "   knowledge  u_priority_confirmation  time_to_resolution  \\\n",
       "0          1                        0           10.216667   \n",
       "1          1                        0           10.216667   \n",
       "2          1                        0           10.216667   \n",
       "3          1                        0           10.216667   \n",
       "4          1                        0           29.200000   \n",
       "\n",
       "   reassignment_count_log  ...  incident_state_Awaiting Problem  \\\n",
       "0                     0.0  ...                                0   \n",
       "1                     0.0  ...                                0   \n",
       "2                     0.0  ...                                0   \n",
       "3                     0.0  ...                                0   \n",
       "4                     0.0  ...                                0   \n",
       "\n",
       "   incident_state_Awaiting User Info  incident_state_Awaiting Vendor  \\\n",
       "0                                  0                               0   \n",
       "1                                  0                               0   \n",
       "2                                  0                               0   \n",
       "3                                  0                               0   \n",
       "4                                  0                               0   \n",
       "\n",
       "   incident_state_Closed  incident_state_New  incident_state_Resolved  \\\n",
       "0                      0                   1                        0   \n",
       "1                      0                   0                        1   \n",
       "2                      0                   0                        1   \n",
       "3                      1                   0                        0   \n",
       "4                      0                   1                        0   \n",
       "\n",
       "   contact_type_Email  contact_type_Phone  contact_type_Self service  \\\n",
       "0                   0                   1                          0   \n",
       "1                   0                   1                          0   \n",
       "2                   0                   1                          0   \n",
       "3                   0                   1                          0   \n",
       "4                   0                   1                          0   \n",
       "\n",
       "   notify_Send Email  \n",
       "0                  0  \n",
       "1                  0  \n",
       "2                  0  \n",
       "3                  0  \n",
       "4                  0  \n",
       "\n",
       "[5 rows x 37 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "ae681af8-6cf3-4f2f-8e57-e28afc8282aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns=[\"knowledge\",\"impact\",\"urgency\",\"u_priority_confirmation\" , \"time_to_resolution\"], inplace=True) #dropping original column. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "5a8cef41-a520-4778-af96-79f95eb7235a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns=[\"time_bin\"], inplace=True)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "1a70d5ca-9a2b-47a1-98cc-f09e467b8c85",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 138566 entries, 0 to 141711\n",
      "Data columns (total 31 columns):\n",
      " #   Column                             Non-Null Count   Dtype  \n",
      "---  ------                             --------------   -----  \n",
      " 0   reassignment_count                 138566 non-null  int64  \n",
      " 1   reopen_count                       138566 non-null  int64  \n",
      " 2   sys_mod_count                      138566 non-null  float64\n",
      " 3   priority                           138566 non-null  int8   \n",
      " 4   reassignment_count_log             138566 non-null  float64\n",
      " 5   sys_mod_count_log                  138566 non-null  float64\n",
      " 6   time_to_resolution_log             138566 non-null  float64\n",
      " 7   opened_hour                        138566 non-null  int32  \n",
      " 8   opened_dayofweek                   138566 non-null  int32  \n",
      " 9   opened_month                       138566 non-null  int32  \n",
      " 10  opened_weekend                     138566 non-null  int64  \n",
      " 11  caller_avg_resolution              138566 non-null  float64\n",
      " 12  opened_by_avg_resolution           138566 non-null  float64\n",
      " 13  resolved_by_avg_resolution         138566 non-null  float64\n",
      " 14  symptom_avg_resolution             138566 non-null  float64\n",
      " 15  closed_code_avg_resolution         138566 non-null  float64\n",
      " 16  location_avg_resolution            138566 non-null  float64\n",
      " 17  category_avg_resolution            138566 non-null  float64\n",
      " 18  subcategory_avg_resolution         138566 non-null  float64\n",
      " 19  assignment_group_avg_resolution    138566 non-null  float64\n",
      " 20  incident_state_Awaiting Evidence   138566 non-null  int64  \n",
      " 21  incident_state_Awaiting Problem    138566 non-null  int64  \n",
      " 22  incident_state_Awaiting User Info  138566 non-null  int64  \n",
      " 23  incident_state_Awaiting Vendor     138566 non-null  int64  \n",
      " 24  incident_state_Closed              138566 non-null  int64  \n",
      " 25  incident_state_New                 138566 non-null  int64  \n",
      " 26  incident_state_Resolved            138566 non-null  int64  \n",
      " 27  contact_type_Email                 138566 non-null  int64  \n",
      " 28  contact_type_Phone                 138566 non-null  int64  \n",
      " 29  contact_type_Self service          138566 non-null  int64  \n",
      " 30  notify_Send Email                  138566 non-null  int64  \n",
      "dtypes: float64(13), int32(3), int64(14), int8(1)\n",
      "memory usage: 31.3 MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
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   "id": "aa126145-5cb5-4a70-848a-5270002928be",
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   "source": [
    "#### Pre-processing Takeaways\n",
    "1. Outliers were handled using IQR-based capping to reduce skew without removing valuable data.\n",
    "\n",
    "2. Log transformation was applied to time_to_resolution to normalize their distributions.\n",
    "\n",
    "3. Datetime parsing was done early to extract useful temporal features.\n",
    "\n",
    "4. Missing values were detected and imputed to ensure data completeness.\n",
    "\n",
    "5. Target encoding used the log-transformed target for consistency with modeling.\n",
    "\n",
    "6. Highly correlated features (r > 0.70) were dropped to reduce redundancy and multicollinearity.\n",
    "\n",
    "7. Chi-Square tests confirmed strong associations between categorical features and resolution time using binned time_to_resolution values.\n",
    "\n",
    "8. One-hot encoding was used for nominal categorical variables with few unique values.\n",
    "\n",
    "9. Label encoding was applied where ordinal relationships existed or for use in tree-based models.\n",
    "\n",
    "10. Boolean encoding was used for binary features like notify to simplify categorical representation.\n",
    "\n"
   ]
  }
 ],
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