diff --git a/.gitignore b/.gitignore
index e69de29..43401bf 100644
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1,12 @@
+.venv
+.venv/
+__pycache__/
+*.pyc
+.env
+.env.local
+.env.*.local
+.DS_Store
+.vscode
+logs/
+*.log
+data/
\ No newline at end of file
diff --git a/README.md b/README.md
index 911f5c9..6df7519 100644
--- a/README.md
+++ b/README.md
@@ -1,4 +1,4 @@
-# 📘 End-to-End Insurance Risk Analytics & Predictive Modeling
+# Insurance Risk Analytics & Predictive Modeling — ACIS Project
 
 A complete, modular, production-ready machine learning pipeline for
 insurance analytics.
diff --git a/dvc.lock b/dvc.lock
deleted file mode 100644
index db673e1..0000000
--- a/dvc.lock
+++ /dev/null
@@ -1,4 +0,0 @@
-schema: '2.0'
-stages:
-  track_raw_data:
-    cmd: dvc add data/processed/insurance_cleaned.csv
diff --git a/dvc.yaml b/dvc.yaml
deleted file mode 100644
index de604e8..0000000
--- a/dvc.yaml
+++ /dev/null
@@ -1,3 +0,0 @@
-stages:
-  track_raw_data:
-    cmd: dvc add data/processed/insurance_cleaned.csv
\ No newline at end of file
diff --git a/notebooks/analysis/hypothesis_tests.ipynb b/notebooks/analysis/hypothesis_tests.ipynb
index e69de29..b979a3b 100644
--- a/notebooks/analysis/hypothesis_tests.ipynb
+++ b/notebooks/analysis/hypothesis_tests.ipynb
@@ -0,0 +1,802 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "a6a843ce",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "import pandas as pd\n",
+    "from insurance_analytics.core.registry import settings\n",
+    "from insurance_analytics.hypothesis.metrics import claim_frequency, margin, claim_severity, attach_metrics\n",
+    "from insurance_analytics.hypothesis.segmentation import split_control_test\n",
+    "from insurance_analytics.hypothesis.balance_checks import check_balance\n",
+    "from insurance_analytics.hypothesis.statistical_tests import run_hypothesis_tests\n",
+    "from insurance_analytics.hypothesis.interpert import hypothesis_summary_generator\n",
+    "from insurance_analytics.viz.ab_plots import (\n",
+    "    plot_claim_frequency_by_feature,\n",
+    "    plot_claim_severity_box_by_feature,\n",
+    "    plot_margin_box_by_feature,\n",
+    "    plot_top_zipcode_frequency\n",
+    ")\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "94968f2a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\user\\AppData\\Local\\Temp\\ipykernel_10596\\2225260617.py:8: DtypeWarning: Columns (31) have mixed types. Specify dtype option on import or set low_memory=False.\n",
+      "  df = pd.read_csv(processed_path, sep=\",\")\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data loaded successfully: 1000098 rows, 50 columns\n"
+     ]
+    }
+   ],
+   "source": [
+    "name = \"insurance_cleaned.csv\"\n",
+    "processed_path = settings.DATA[\"processed_dir\"] / name\n",
+    "report_path = settings.REPORTS[\"reports_dir\"]\n",
+    "plots_dir = settings.REPORTS[\"plots_dir\"]\n",
+    "\n",
+    "# Load data with error handling\n",
+    "try:\n",
+    "    df = pd.read_csv(processed_path, sep=\",\")\n",
+    "    print(\n",
+    "        f\"Data loaded successfully: {df.shape[0]} rows, {df.shape[1]} columns\")\n",
+    "except FileNotFoundError:\n",
+    "    print(f\"Error: File not found at {processed_path}\")\n",
+    "    sys.exit(1)\n",
+    "except ValueError as e:\n",
+    "    print(f\"Error loading data: {e}\")\n",
+    "    sys.exit(1)\n",
+    "except Exception as e:\n",
+    "    print(f\"Unexpected error: {e}\")\n",
+    "    sys.exit(1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "f483eb51",
+   "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>UnderwrittenCoverID</th>\n",
+       "      <th>PolicyID</th>\n",
+       "      <th>TransactionMonth</th>\n",
+       "      <th>IsVATRegistered</th>\n",
+       "      <th>LegalType</th>\n",
+       "      <th>Title</th>\n",
+       "      <th>Language</th>\n",
+       "      <th>Bank</th>\n",
+       "      <th>AccountType</th>\n",
+       "      <th>MaritalStatus</th>\n",
+       "      <th>...</th>\n",
+       "      <th>CoverCategory</th>\n",
+       "      <th>CoverType</th>\n",
+       "      <th>CoverGroup</th>\n",
+       "      <th>Section</th>\n",
+       "      <th>Product</th>\n",
+       "      <th>StatutoryClass</th>\n",
+       "      <th>StatutoryRiskType</th>\n",
+       "      <th>TotalPremium</th>\n",
+       "      <th>TotalClaims</th>\n",
+       "      <th>LossRatio</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>145249</td>\n",
+       "      <td>12827</td>\n",
+       "      <td>1425168000000000000</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Close Corporation</td>\n",
+       "      <td>Mr</td>\n",
+       "      <td>English</td>\n",
+       "      <td>First National Bank</td>\n",
+       "      <td>Current account</td>\n",
+       "      <td>Not specified</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Windscreen</td>\n",
+       "      <td>Windscreen</td>\n",
+       "      <td>Comprehensive - Taxi</td>\n",
+       "      <td>Motor Comprehensive</td>\n",
+       "      <td>Mobility Metered Taxis: Monthly</td>\n",
+       "      <td>Commercial</td>\n",
+       "      <td>IFRS Constant</td>\n",
+       "      <td>21.929825</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>145249</td>\n",
+       "      <td>12827</td>\n",
+       "      <td>1430438400000000000</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Close Corporation</td>\n",
+       "      <td>Mr</td>\n",
+       "      <td>English</td>\n",
+       "      <td>First National Bank</td>\n",
+       "      <td>Current account</td>\n",
+       "      <td>Not specified</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Windscreen</td>\n",
+       "      <td>Windscreen</td>\n",
+       "      <td>Comprehensive - Taxi</td>\n",
+       "      <td>Motor Comprehensive</td>\n",
+       "      <td>Mobility Metered Taxis: Monthly</td>\n",
+       "      <td>Commercial</td>\n",
+       "      <td>IFRS Constant</td>\n",
+       "      <td>21.929825</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>145249</td>\n",
+       "      <td>12827</td>\n",
+       "      <td>1435708800000000000</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Close Corporation</td>\n",
+       "      <td>Mr</td>\n",
+       "      <td>English</td>\n",
+       "      <td>First National Bank</td>\n",
+       "      <td>Current account</td>\n",
+       "      <td>Not specified</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Windscreen</td>\n",
+       "      <td>Windscreen</td>\n",
+       "      <td>Comprehensive - Taxi</td>\n",
+       "      <td>Motor Comprehensive</td>\n",
+       "      <td>Mobility Metered Taxis: Monthly</td>\n",
+       "      <td>Commercial</td>\n",
+       "      <td>IFRS Constant</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>145255</td>\n",
+       "      <td>12827</td>\n",
+       "      <td>1430438400000000000</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Close Corporation</td>\n",
+       "      <td>Mr</td>\n",
+       "      <td>English</td>\n",
+       "      <td>First National Bank</td>\n",
+       "      <td>Current account</td>\n",
+       "      <td>Not specified</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Own damage</td>\n",
+       "      <td>Own Damage</td>\n",
+       "      <td>Comprehensive - Taxi</td>\n",
+       "      <td>Motor Comprehensive</td>\n",
+       "      <td>Mobility Metered Taxis: Monthly</td>\n",
+       "      <td>Commercial</td>\n",
+       "      <td>IFRS Constant</td>\n",
+       "      <td>512.848070</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>145255</td>\n",
+       "      <td>12827</td>\n",
+       "      <td>1435708800000000000</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Close Corporation</td>\n",
+       "      <td>Mr</td>\n",
+       "      <td>English</td>\n",
+       "      <td>First National Bank</td>\n",
+       "      <td>Current account</td>\n",
+       "      <td>Not specified</td>\n",
+       "      <td>...</td>\n",
+       "      <td>Own damage</td>\n",
+       "      <td>Own Damage</td>\n",
+       "      <td>Comprehensive - Taxi</td>\n",
+       "      <td>Motor Comprehensive</td>\n",
+       "      <td>Mobility Metered Taxis: Monthly</td>\n",
+       "      <td>Commercial</td>\n",
+       "      <td>IFRS Constant</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 50 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   UnderwrittenCoverID  PolicyID     TransactionMonth  IsVATRegistered  \\\n",
+       "0               145249     12827  1425168000000000000             True   \n",
+       "1               145249     12827  1430438400000000000             True   \n",
+       "2               145249     12827  1435708800000000000             True   \n",
+       "3               145255     12827  1430438400000000000             True   \n",
+       "4               145255     12827  1435708800000000000             True   \n",
+       "\n",
+       "           LegalType Title Language                 Bank      AccountType  \\\n",
+       "0  Close Corporation    Mr  English  First National Bank  Current account   \n",
+       "1  Close Corporation    Mr  English  First National Bank  Current account   \n",
+       "2  Close Corporation    Mr  English  First National Bank  Current account   \n",
+       "3  Close Corporation    Mr  English  First National Bank  Current account   \n",
+       "4  Close Corporation    Mr  English  First National Bank  Current account   \n",
+       "\n",
+       "   MaritalStatus  ... CoverCategory   CoverType            CoverGroup  \\\n",
+       "0  Not specified  ...    Windscreen  Windscreen  Comprehensive - Taxi   \n",
+       "1  Not specified  ...    Windscreen  Windscreen  Comprehensive - Taxi   \n",
+       "2  Not specified  ...    Windscreen  Windscreen  Comprehensive - Taxi   \n",
+       "3  Not specified  ...    Own damage  Own Damage  Comprehensive - Taxi   \n",
+       "4  Not specified  ...    Own damage  Own Damage  Comprehensive - Taxi   \n",
+       "\n",
+       "               Section                          Product StatutoryClass  \\\n",
+       "0  Motor Comprehensive  Mobility Metered Taxis: Monthly     Commercial   \n",
+       "1  Motor Comprehensive  Mobility Metered Taxis: Monthly     Commercial   \n",
+       "2  Motor Comprehensive  Mobility Metered Taxis: Monthly     Commercial   \n",
+       "3  Motor Comprehensive  Mobility Metered Taxis: Monthly     Commercial   \n",
+       "4  Motor Comprehensive  Mobility Metered Taxis: Monthly     Commercial   \n",
+       "\n",
+       "  StatutoryRiskType  TotalPremium TotalClaims  LossRatio  \n",
+       "0     IFRS Constant     21.929825         0.0        0.0  \n",
+       "1     IFRS Constant     21.929825         0.0        0.0  \n",
+       "2     IFRS Constant      0.000000         0.0        NaN  \n",
+       "3     IFRS Constant    512.848070         0.0        0.0  \n",
+       "4     IFRS Constant      0.000000         0.0        NaN  \n",
+       "\n",
+       "[5 rows x 50 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "a303133d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0          0\n",
+       "1          0\n",
+       "2          0\n",
+       "3          0\n",
+       "4          0\n",
+       "          ..\n",
+       "1000093    0\n",
+       "1000094    0\n",
+       "1000095    0\n",
+       "1000096    0\n",
+       "1000097    0\n",
+       "Name: ClaimFrequency, Length: 1000098, dtype: int64"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "claim_frequency(df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "a8a5cc9f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0         NaN\n",
+       "1         NaN\n",
+       "2         NaN\n",
+       "3         NaN\n",
+       "4         NaN\n",
+       "           ..\n",
+       "1000093   NaN\n",
+       "1000094   NaN\n",
+       "1000095   NaN\n",
+       "1000096   NaN\n",
+       "1000097   NaN\n",
+       "Name: ClaimSeverity, Length: 1000098, dtype: float64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "claim_severity(df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "dec7075b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0           21.929825\n",
+       "1           21.929825\n",
+       "2            0.000000\n",
+       "3          512.848070\n",
+       "4            0.000000\n",
+       "              ...    \n",
+       "1000093    347.235175\n",
+       "1000094    347.235175\n",
+       "1000095    347.235175\n",
+       "1000096      2.315000\n",
+       "1000097      2.315000\n",
+       "Name: Margin, Length: 1000098, dtype: float64"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "margin(df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "efd84673",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = attach_metrics(df)\n",
+    "# df[['ClaimFrequency', 'ClaimSeverity', 'Margin']].head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "b0cb4f57",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Control group size: 42817\n",
+      "Test group size: 6755\n"
+     ]
+    }
+   ],
+   "source": [
+    "control_group, test_group = split_control_test(\n",
+    "    df, feature=\"Gender\", group_a_values=\"Male\", group_b_values=\"Female\")\n",
+    "\n",
+    "print(f\"Control group size: {len(control_group)}\")\n",
+    "print(f\"Test group size: {len(test_group)}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "4e586bdd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "       feature         type  chi2  p_value  balanced\n",
+      "0  VehicleType  categorical   NaN      NaN     False\n",
+      "1     Province  categorical   NaN      NaN     False\n"
+     ]
+    }
+   ],
+   "source": [
+    "confounders = [\n",
+    "    'VehicleType',\n",
+    "    'Province'\n",
+    "]\n",
+    "\n",
+    "balance_df = check_balance(control_group, test_group, confounders, plot=True)\n",
+    "print(balance_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "23b8dcfb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Province\n",
+    "plot_claim_frequency_by_feature(df, \"Province\")\n",
+    "plot_claim_severity_box_by_feature(df, \"Province\", log_scale=True)\n",
+    "plot_margin_box_by_feature(df, \"Province\")\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "42711374",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:matplotlib.category:Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n",
+      "INFO:matplotlib.category:Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# PostalCode\n",
+    "plot_top_zipcode_frequency(df, top_n=20)\n",
+    "\n",
+    "# Gender\n",
+    "plot_claim_frequency_by_feature(df, \"Gender\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "499347bc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "d:\\10Acadamy\\Week 3\\Tasks\\Predictive-Modeling\\.venv\\Lib\\site-packages\\insurance_analytics\\hypothesis\\statistical_tests.py:53: SmallSampleWarning: One or more sample arguments is too small; all returned values will be NaN. See documentation for sample size requirements.\n",
+      "  F_stat, p_value = stats.f_oneway(*groups)\n"
+     ]
+    },
+    {
+     "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>feature</th>\n",
+       "      <th>kpi</th>\n",
+       "      <th>test_type</th>\n",
+       "      <th>statistic</th>\n",
+       "      <th>p_value</th>\n",
+       "      <th>reject_null</th>\n",
+       "      <th>description</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Province</td>\n",
+       "      <td>ClaimFrequency</td>\n",
+       "      <td>chi2</td>\n",
+       "      <td>104.190881</td>\n",
+       "      <td>5.925511e-19</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Claim frequency differences across provinces</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Province</td>\n",
+       "      <td>ClaimSeverity</td>\n",
+       "      <td>anova</td>\n",
+       "      <td>4.830166</td>\n",
+       "      <td>6.304917e-06</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Claim severity differences across provinces</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Province</td>\n",
+       "      <td>Margin</td>\n",
+       "      <td>anova</td>\n",
+       "      <td>3.222613</td>\n",
+       "      <td>1.145008e-03</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Margin differences across provinces</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>PostalCode</td>\n",
+       "      <td>ClaimFrequency</td>\n",
+       "      <td>chi2</td>\n",
+       "      <td>1454.467610</td>\n",
+       "      <td>3.152172e-30</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Claim frequency differences across zip codes</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>PostalCode</td>\n",
+       "      <td>ClaimSeverity</td>\n",
+       "      <td>anova</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Claim severity differences across zip codes</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>PostalCode</td>\n",
+       "      <td>Margin</td>\n",
+       "      <td>anova</td>\n",
+       "      <td>0.870747</td>\n",
+       "      <td>9.976860e-01</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Margin differences across zip codes</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Gender</td>\n",
+       "      <td>ClaimFrequency</td>\n",
+       "      <td>chi2</td>\n",
+       "      <td>7.255926</td>\n",
+       "      <td>2.657025e-02</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Claim frequency differences by gender</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Gender</td>\n",
+       "      <td>ClaimSeverity</td>\n",
+       "      <td>anova</td>\n",
+       "      <td>2.411104</td>\n",
+       "      <td>8.990443e-02</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Claim severity differences by gender</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Gender</td>\n",
+       "      <td>Margin</td>\n",
+       "      <td>anova</td>\n",
+       "      <td>0.311618</td>\n",
+       "      <td>7.322610e-01</td>\n",
+       "      <td>False</td>\n",
+       "      <td>Margin differences by gender</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      feature             kpi test_type    statistic       p_value  \\\n",
+       "0    Province  ClaimFrequency      chi2   104.190881  5.925511e-19   \n",
+       "1    Province   ClaimSeverity     anova     4.830166  6.304917e-06   \n",
+       "2    Province          Margin     anova     3.222613  1.145008e-03   \n",
+       "3  PostalCode  ClaimFrequency      chi2  1454.467610  3.152172e-30   \n",
+       "4  PostalCode   ClaimSeverity     anova          NaN           NaN   \n",
+       "5  PostalCode          Margin     anova     0.870747  9.976860e-01   \n",
+       "6      Gender  ClaimFrequency      chi2     7.255926  2.657025e-02   \n",
+       "7      Gender   ClaimSeverity     anova     2.411104  8.990443e-02   \n",
+       "8      Gender          Margin     anova     0.311618  7.322610e-01   \n",
+       "\n",
+       "   reject_null                                   description  \n",
+       "0         True  Claim frequency differences across provinces  \n",
+       "1         True   Claim severity differences across provinces  \n",
+       "2         True           Margin differences across provinces  \n",
+       "3         True  Claim frequency differences across zip codes  \n",
+       "4        False   Claim severity differences across zip codes  \n",
+       "5        False           Margin differences across zip codes  \n",
+       "6         True         Claim frequency differences by gender  \n",
+       "7        False          Claim severity differences by gender  \n",
+       "8        False                  Margin differences by gender  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#  Run hypothesis tests\n",
+    "hypotheses = [\n",
+    "    # Risk differences across provinces\n",
+    "    {\"feature\": \"Province\", \"kpi\": \"ClaimFrequency\", \"test_type\": \"chi2\", \"description\": \"Claim frequency differences across provinces\"},\n",
+    "    {\"feature\": \"Province\", \"kpi\": \"ClaimSeverity\", \"test_type\": \"anova\", \"description\": \"Claim severity differences across provinces\"},\n",
+    "    {\"feature\": \"Province\", \"kpi\": \"Margin\", \"test_type\": \"anova\", \"description\": \"Margin differences across provinces\"},\n",
+    "\n",
+    "    # Risk differences across zip codes\n",
+    "    {\"feature\": \"PostalCode\", \"kpi\": \"ClaimFrequency\", \"test_type\": \"chi2\", \"description\": \"Claim frequency differences across zip codes\"},\n",
+    "    {\"feature\": \"PostalCode\", \"kpi\": \"ClaimSeverity\", \"test_type\": \"anova\", \"description\": \"Claim severity differences across zip codes\"},\n",
+    "    {\"feature\": \"PostalCode\", \"kpi\": \"Margin\", \"test_type\": \"anova\", \"description\": \"Margin differences across zip codes\"},\n",
+    "\n",
+    "    # Risk differences by gender\n",
+    "    {\"feature\": \"Gender\", \"kpi\": \"ClaimFrequency\", \"test_type\": \"chi2\", \"description\": \"Claim frequency differences by gender\"},\n",
+    "    {\"feature\": \"Gender\", \"kpi\": \"ClaimSeverity\", \"test_type\": \"anova\", \"description\": \"Claim severity differences by gender\"},\n",
+    "    {\"feature\": \"Gender\", \"kpi\": \"Margin\", \"test_type\": \"anova\", \"description\": \"Margin differences by gender\"}\n",
+    "]\n",
+    "\n",
+    "results = run_hypothesis_tests(df, hypotheses)\n",
+    "results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "e832fdbc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reject H0 for Province on KPI ClaimFrequency: p=0.0000\n",
+      "Reject H0 for Province on KPI ClaimSeverity: p=0.0000\n",
+      "Reject H0 for Province on KPI Margin: p=0.0011\n",
+      "Reject H0 for PostalCode on KPI ClaimFrequency: p=0.0000\n",
+      "Fail to reject H0 for PostalCode on KPI ClaimSeverity: p=nan\n",
+      "Fail to reject H0 for PostalCode on KPI Margin: p=0.9977\n",
+      "Reject H0 for Gender on KPI ClaimFrequency: p=0.0266\n",
+      "Fail to reject H0 for Gender on KPI ClaimSeverity: p=0.0899\n",
+      "Fail to reject H0 for Gender on KPI Margin: p=0.7323\n"
+     ]
+    }
+   ],
+   "source": [
+    "for idx, row in results.iterrows():\n",
+    "    if row['reject_null']:\n",
+    "        print(f\"Reject H0 for {row['feature']} on KPI {row['kpi']}: p={row['p_value']:.4f}\")\n",
+    "    else:\n",
+    "        print(f\"Fail to reject H0 for {row['feature']} on KPI {row['kpi']}: p={row['p_value']:.4f}\")\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/exploration/eda.ipynb b/notebooks/exploration/eda.ipynb
index ff19aac..5a1c3a3 100644
--- a/notebooks/exploration/eda.ipynb
+++ b/notebooks/exploration/eda.ipynb
@@ -15,6 +15,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import sys\n",
     "from insurance_analytics.core.registry import settings\n",
     "from insurance_analytics.preprocessing.cleaner import cleaning\n",
     "from insurance_analytics.data.load_data import load_data\n",
@@ -22,7 +23,7 @@
     "from insurance_analytics.eda.exploration import (\n",
     "    dataset_overview, duplicated_rows, detect_outliers_iqr,summarize_missing\n",
     ")\n",
-    "\n",
+    "from insurance_analytics.utils.io_utils import write_csv\n",
     "from insurance_analytics.viz.plots import ( plot_histogram,\n",
     "plot_bar,\n",
     "correlation_matrix,\n",
@@ -45,16 +46,35 @@
    "execution_count": 2,
    "id": "cc7d4732",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data loaded successfully: 1000098 rows, 52 columns\n"
+     ]
+    }
+   ],
    "source": [
-    "name=\"MachineLearningRating_v3.txt\"\n",
-    "raw_path = settings.DATA[\"raw_dir\"]/f\"{name}\"\n",
-    "report_path= settings.REPORTS[\"reports_dir\"]\n",
-    "plots_dir= settings.REPORTS[\"plots_dir\"]\n",
-    "processed_dir= settings.DATA[\"processed_dir\"]\n",
+    "name = \"MachineLearningRating_v3.txt\"\n",
+    "raw_path = settings.DATA[\"raw_dir\"] / name\n",
+    "report_path = settings.REPORTS[\"reports_dir\"]\n",
+    "plots_dir = settings.REPORTS[\"plots_dir\"]\n",
+    "processed_dir = settings.DATA[\"processed_dir\"]\n",
     "\n",
-    "\n",
-    "df = load_data(raw_path)"
+    "# Load data with error handling\n",
+    "try:\n",
+    "    df = load_data(raw_path)\n",
+    "    print(f\"Data loaded successfully: {df.shape[0]} rows, {df.shape[1]} columns\")\n",
+    "except FileNotFoundError:\n",
+    "    print(f\"Error: File not found at {raw_path}\")\n",
+    "    sys.exit(1)\n",
+    "except ValueError as e:\n",
+    "    print(f\"Error loading data: {e}\")\n",
+    "    sys.exit(1)\n",
+    "except Exception as e:\n",
+    "    print(f\"Unexpected error: {e}\")\n",
+    "    sys.exit(1)"
    ]
   },
   {
@@ -970,9 +990,7 @@
       "D:\\10Acadamy\\Week 3\\Tasks\\Predictive-Modeling\\src\\insurance_analytics\\viz\\plots.py:173: UserWarning: Creating legend with loc=\"best\" can be slow with large amounts of data.\n",
       "  plt.tight_layout()\n",
       "D:\\10Acadamy\\Week 3\\Tasks\\Predictive-Modeling\\src\\insurance_analytics\\viz\\plots.py:176: UserWarning: Creating legend with loc=\"best\" can be slow with large amounts of data.\n",
-      "  plt.savefig(save_path, dpi=300)\n",
-      "d:\\10Acadamy\\Week 3\\Tasks\\Predictive-Modeling\\.venv\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Creating legend with loc=\"best\" can be slow with large amounts of data.\n",
-      "  fig.canvas.print_figure(bytes_io, **kw)\n"
+      "  plt.savefig(save_path, dpi=300)\n"
      ]
     },
     {
@@ -1050,6 +1068,14 @@
    "id": "b612a002",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "d:\\10Acadamy\\Week 3\\Tasks\\Predictive-Modeling\\.venv\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Creating legend with loc=\"best\" can be slow with large amounts of data.\n",
+      "  fig.canvas.print_figure(bytes_io, **kw)\n"
+     ]
+    },
     {
      "data": {
       "image/png": 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@@ -1073,14 +1099,6 @@
    "id": "4dce20fe",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "d:\\10Acadamy\\Week 3\\Tasks\\Predictive-Modeling\\.venv\\Lib\\site-packages\\IPython\\core\\pylabtools.py:170: UserWarning: Creating legend with loc=\"best\" can be slow with large amounts of data.\n",
-      "  fig.canvas.print_figure(bytes_io, **kw)\n"
-     ]
-    },
     {
      "data": {
       "image/png": 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RERER8SvNghckf/75J1wuFxISEoK1CiIiIiIiIiIiWZaUlISYmBg0aNAg3ccqAypIGHziLZxx/U+fPh32f4eIL2h/ENH+IKLjg4jOmUSi7RrClYnYhjKggsTKfKpTpw7C1YkTJ7B69WpUrVoVefLkCfbqiASV9gcR7Q8iOj6I6JxJJNquIVasWJHhxyoDSkRERERERERE/EoBKBERERERERER8SsFoERERERERERExK8UgBIREREREREREb9SAEpERERERERERPxKs+CJiIiIiIiISNg5e/YskpKSEK4SExNTvsbGhl5+UEJCAuLi4nz2fApAiYiIiIiIiEjYcLlc2LVrFw4dOoRwlpycjPj4eOzYsSMkA1BUqFAhlCpVCjExMdl+LgWgRERERERERCRsWMGnEiVKIE+ePD4JjgQrgysxMRE5c+b0aaaRr4J8J06cwJ49e4zvS5cuHVkBqE2bNqFdu3YYPHiw8ZVWr16N4cOHY+XKlShSpAg6d+6Mjh07pooYjhs3Dp988gmOHj2KRo0aYciQIShXrlzKYwLxHCIiIiIiIiLi/6CNFXwqWrRo2P8tlCtXrpALQFHu3LmNrwxCcXtndx1DJseLdZv9+vUzImyWgwcPokuXLihfvjw+++wz9OjRA6NGjTL+bxk/fjymTZuGZ599FtOnTzeCSd26dcPp06cD+hwiIiIiIiIi4l9WzydmPon/WdvZF722QiYD6rXXXkO+fPlS3ffxxx8bTa+GDRtm1EVWqVIFW7ZswYQJE9C+fXsjQPTOO+8YgauWLVsaPzN27Fg0a9YMc+bMwQ033BCQ5xARERERERGRwAnXsrto3s4hkQG1ZMkSfPTRRxg5cmSq+5cuXYrGjRsbQR9LkyZNsHnzZuzbtw9r1qzB8ePH0bRp05TlBQoUQK1atYznDNRziIiIiIiIiIhkt+9SJAt6BtSRI0fQv39/DBo0KE1TKzYWq1atWqr7WHdIO3fuNJaT58/xMdayQDxHsWLFstXUK1ydPHky1VeRaKb9QUT7g4iODyI6ZxL/Y9Nuts1h/ySrh1JG/e9//zOSS0aMGIFQCji5XC68/vrrRuVV165djfsGDBiA33//HXPnzg3qunMbc3vzeodf7f6GjGZJBT0A9fTTT6NBgwa48cYb0yw7deoUcuTIkeo+doe33nTWBZ/dYw4fPhyw58gq1lCyuXm4YyaYiGh/ENHxQUTnSyK6hpBAYHVSVq7F2cs5b968xjV+KElMTMSrr76KBx54IGXdGPhhcMf6PljrznU7c+YMNm7c6PgYz3hJSAagZs6caZS3ffnll7bL2QneagRusd5kbITF5cTHWP+3HmN1aw/Ec2QVo5tVq1ZFuGLwjsGnihUrpmwrkWil/UFE+4OIjg8iOmcS/+O1+I4dO4ykEPdr+IyoX78+QonL5TL+HivBhYE162/ijHPMLLK+D+a6c704KZu1nu7Wr1+f8edBEHEWuf3796c0/7YMHToU33zzDUqVKmVM9+fO+r5kyZJGFM66jxvD/THVq1c3/h+I58gqvpkioXM/g0+R8HeI+IL2BxHtDyI6PojonEn8JzY21rgxQMNbZrRq1cooY2P/6a+++sqYWIxJFbyeveKKK/D4449n+hr/119/Ncrn1q5dawRq+Dyc5Mxq88MJ18aNG2csd8d4w8MPP4xu3brhoosuMu4bP368ceNjGS/gzfob3dedGLh65ZVX8PXXXxtxlUqVKuGhhx5CmzZtUv29LN3j8/35559G5dnw4cMz9ffx93N78zrHLuCXmSblQW1CzhQyBpqYCWXdqFevXsZGadSoEf74449UdZ2LFi0yNmzRokVRo0YNY+a8xYsXp+optWrVKuNnKRDPISIiIhHo6FE2gjS/ioiISMTg9T17UV9zzTV4++238dRTTxnX+H379s3U8zCGcd999xnBpjFjxhjPw0DPHXfcYQSFMurDDz80vt56663GBG0ZyZzq0aMHpk+fji5duuCNN94wWhv17t07Ja5imTp1KurUqWMEtvj8wRTUDCinyCKDOlzWvn17TJw4EQMHDjSigsuXL8fkyZPxzDPPpNQZdujQwQhkFSlSBGXLlsVLL71kZCzxjUSBeA4RERGJIAw4rVoFPPus+bVWLWDwYPNr/vzBXjsRERHxQQCK2TzsuWT1LypUqBBWrFiR4ababMjNOAIznkaPHp1y/8UXX2xkIU2aNMkIcmVEvXr1jK+MQ2Sk1O63337Dzz//jLFjx6ZkPDVr1sxoC8J1uuGGG4xsLCpTpoyRkRUKgt6E3BsGohj4YTZU27ZtUbx4ceMF5P8tzJZiGR1n0WMzLmYr8YVmf6VAPoeIiIhEgKQkYNYsoEOH8/dt2gR8/TXwwQfA7beziWMw11BERESyidf8DN4wUHPttdeiRYsWRiCJXzNq06ZN2Lt3b5qsKbb2YTYSZ7Dzl4ULFxpBMq6v1VbIKrmbNWsW1q1bh5o1axr3WV9DQcgFoDzrIuvWres1BY31iKzT5M1JIJ5DREREIsDOncBDD9kve/hhDi/yzDLQayUiIiI+xAAR+z+xsundd981/l+sWDE8+OCDuPfeezP0HIcOHTK+8uc88T629fGXQ4cOGZlazLayw57VVuAplPo1h1wASkRERCRoOMmIU8+nI0eA3bsVgBIREYkALFmzytbY/+m9997Dc889Z5TDMQElPSzZo3379qVZxsyowoULG/+3yvnOnj2b0lD8+PHj2Vr3/PnzG4ElrrOdChUqIBQFtQm5iIiISEiJjc3echEREQl5L7zwgtHrmVlEnN3tyiuvxBNPPGEs27FjR4aeg5OSsT0PZ9Nzt23bNvz1118p2Umc9Ix2cWITtx5UnjjTXEZxNrwTJ04Y688G49bt33//NWbkcy/LCyU6ixIRERGxFC/OvHn77cH7S5TQthIREQlzTZo0wT///IMnn3wSv/76K3766Scj+4lZTVyWEQwY9enTB7/88ovRB2r+/PnGDHScla5gwYLGV7L6Sg0ZMsRoHv7ZZ5/h6aefRt68eVM9X4ECBbBs2TIsWbLECCx5w+dkH6uHH34Y06ZNw+LFi43Z/Pi8XC9OsBaKFIASERERsZQpA7z/PhtEpt4m/J73c7mIiIiENQZwOFscm3X37NnTCCQxE4olbVZpXUa0a9cOr776qtGQvEePHhg5cqTRX+rTTz81sqOsTClmXG3fvt2YdY+/49lnn0UJj0Et9p9auXIl7r//fuxkT0ovGGRi36rrr78eb731Frp27Yrp06cbQS82Vw9VMa70QmviF5zekZgmF66Y8rd69WqjuVkoNTYTCQbtDyIRtD+cOmXOfPf668DffwOcDpkNyCtVAnLlCvbaSZgJ+/1BxMe0T0h2ceZ6BnwY2MkV5sfls2fPGn8P/w6rP1S4be/MxDbUhFxERETEHU+uOHMMRxBPnOD0MUBCgraRiIhIFGCODgND6WHAyGowLhmjAJSIiIiIHQadChbUthEREYkiv//+Ozp27Jju455//nmjBE8yTgEoEREREREREREAF110kdHDKT0XXHCBtlcmKQAlIiIiIiIiIgIgX758Yd2rOZRpFjwREREREREREfErBaBERERERERERMSvFIASERERERERERG/UgBKRERERERERET8SgEoERERERERERHxKwWgRERERERERETEr+L9+/QiIiIiItErJiYGVfLkQa61a4HERKBECaBkSSBv3mCvmoiIBFmnTp2wZMkS22X33XcfnnjiCa8/v3jxYnTs2BHz5s3DBRdcgFCnAJSIiIiIiD+4XMi5di1yt20LbN587uw7HujbF+jTxwxGiYhIVLv66qsxaNAgxMXFpbo/d+7ciDQKQImIiIiI+MPWrYi98krg0KHz9505A7zwAlC+PPDQQ0yR0rYXEQmigweB3buBw4eBQoXMsYHChQP3+3PlyoXixYunCUBFIvWAEhERERHxh0WLUgef3D37LLBjh7a7iEgQbdsG3HknULMm0KQJUKOG+T3vDwWHDx82sqOaNWuGiy66CE2bNjW+P3nypO3jN2/ejK5du6Jhw4Zo0KCB8f+1LAE/5+jRoxg8eDCaNGliPIbleytWrAjY36MAlIiIiIiIP/z1l/OyXbuA06e13UVEgpj51K0bMGdO6vv5Pe/n8mB78sknsWrVKowbNw6zZ8/GU089hZkzZ+Kjjz6yfXyfPn1QsmRJfPbZZ/jkk08QGxuLnj17GstcLhfuv/9+bNu2DW+99RY+/vhj1K9fH3fddZfxOwJBJXgiIiIiIv5w8cXOy8qWBXLm1HYXEQkSlt15Bp8svJ/LA1GK9+2332Lu3LnGpBUWZidNnDgRl19+ORo1aoTq1asb97PR+AcffIB///3X9rm2bt2Kyy67DGXLlkVCQgJGjBiBjRs3Ijk52WhY/tdff2HRokUoxFrDcwGrZcuW4b333sPIkSP9/rcqACUiIiIi4g+XXgoULQrs35922dChQOnS2u4iIkHCnk/ZWe4rzZs3x+OPP56qBxT7QtHdd9+NH374AZ9//rlRXrd+/Xps374dlStXtn2u3r17G0GnadOmoXHjxkbp3g033GBkQv3zzz9GFtSV7E3o5vTp00jkLK0BoACUiIiIiIg/lCuH5B9+QOyttwLr1pn3MevpySeBW25RA3IRkSAqWDB7y30lb968qFChQpom5Mxa6t69O9atW2cEkdq0aWP0gWIPJyf33HMPWrdujfnz52PhwoV49dVX8cYbbxhle3y+fPnyYcaMGWl+LkeOHAgEBaBERERERPwhJgaJF16Ik198gUJJSYjlCHOxYkCpUpxfW9tcRCSISpYErrnGvgyP93N5MK1evRoLFiwwejXVq1fPuC8pKckosytXrlyax+/fvx+vv/46HnjgAbRr18647d6928iw+v3331GtWjUcO3bMeI6qVaum/BybmteoUQMdOnTw+9+kAJSIiIiIiJ+w3GHTiROoWbMm8uTJo+0sIhIi2N9p4sS0jcgZfOL9gej/5E2xYsUQHx9v9IgqUqQIDh06hDfffBN79+41yuY8FSxYED/99JMRoOrbt29KthN7QdWuXdvoC8VjEcv0Bg4ciNKlSxulenzMpEmTEAgKQImIiIiIiIhI1GEi0fTpZsNx9nxi2R0zn4IdfCLOZsfG4K+99hqmTp2K4sWLo2XLlujcubPRF8oTg1Vvv/02XnjhBeMxJ0+eNAJOEyZMQPny5Y3HvPPOO3jppZfw2GOPGcurVKlizLDXtGlTBIICUCIiIiIiIiISlRhsClbAacqUKTh16pTj8htvvNG4eXrqqaeMr5deeinWrl2bcj8DSgw4OWEm1fPPP49giQ3abxYRERERERERkaigAJSIiIiIiIiIiPiVAlAiIiIiIiISPs6eBY4cAWwaMYtI6FIPKBEREREREQl9Z84AmzcDnLHrl1/Y8AZ47DHza/78wV47EUmHAlAiIiIiIiIS+v78E2jRAjh50vyeQagpU4DJk4Hbbwdy5w72GoqIFyrBExERERERkdC2ezfQqdP54JO77t2BXbuCsVYikgkKQImIiIiIiEho278fWL3aflliIuA2Fb2IhCYFoERERERERCS0JSen3x9KREKaAlAiIiIiIiIS2ooUASpUsF8WFwfUrBnoNRKRTFIASkREREREREJbmTLm7HcMNnl67jmgZMlgrJWIZIJmwRMREREREZHQd9llwLJlwPDhwNKlQPnywKBBQIMGQL58wV47kUx58skn8fnnn3t9zNoI622mAJSIiIiIiIiEvty5gbp1gXfeAY4eBXLlAgoVCvZaSbg7eNCcZfHwYfP9VKIEULiw33/twIED8dhjjyExMRE5c+ZEixYtMGDAALRp0waRSgEoERERERERCR9585o3kezatg3o1g2YM+f8fddcA0ycCJQr59ftmz9/fuTJkwenTp1CLgZTz91XvHhxRCr1gBIRERERERGR6Mt88gw+Eb/n/VweRDNmzMDVV1+N5557Dg0bNsTDDz+MxYsXo3r16ti+fXvK4zzvc7lcePvtt3HVVVehXr16uPnmmzFr1iyEAmVAiYiIiIiIiEh0YdmdZ/DJwvu5PACleN5s3boVe/bswcyZM41MqQMHDiA9Y8eOxVdffYUhQ4agcuXKWLJkCZ5++mkcPXoU99xzD4JJASgRERERERERiS7s+ZSd5QHy8MMPo9y5ckBmO3lz4sQJTJ48GWPGjEHLli2N+8qXL4///vsPkyZNCnoAKuglePv378fjjz+OJk2aoEGDBnjggQewYcOGlOWDBg0y0sncb61atUpZnpycjFdffRXNmjVD/fr1cf/992Mb6zjdrF69Gh06dDCW82ffe++9VMt98RwiIiIiIiIiEiYKFsze8gCpWLFihh+7fv16o6l53759jfiKdWNJHoNQzKKK6gyoHj16GAGgCRMmIG/evHjllVfQuXNnzJkzB7lz5zamHXzwwQeN4I8lLi4u5f/jx4/HtGnTMHLkSJQqVQovvfQSunXrhi+//BI5cuTAwYMH0aVLFyNo9Mwzz+Cvv/4yvvJ3tW/f3mfPISIiIiIiIiJhomRJs+G4XRke7+fyEJDrXINyJ2fPnk35P/s/0csvv2yU33lifCNqM6AOHz6MsmXLGk216tatiypVqhjpZaxxXLdunbHxGMGrXbu20QneuhUpUsT4+dOnT+Odd95Br169jPSyGjVqGPWOu3btMgJY9PHHHyMhIQHDhg0znp8BIwa4GPDy1XOIiIiIiIiISBhhfyfOdsdgkztrFrwg93+yw7gEHTt2LOW+zZs3p/yfQaf4+Hjs2LEDFSpUSLnNnz/fKMGLjQ1uEVxQf3vBggUxevRoVKtWzfieDbVYr8gspKpVqxoNt1jDaBe5ozVr1uD48eNo2rRpyn0FChRArVq1jEZbtHTpUjRu3Nh4ESws9+OLtG/fPp88h4iIiIiIiIiEGfZWmj6dPXeARYvMr/z+XM+lUFOtWjXkyZPHSIZhvOTnn3/Gu+++m7I8f/78uPPOO43Ksi+++MJoLfTpp58aVV4lSpRAsAW9BM8yePBgI9OIKWFvvPGGsVH//fdfY9n777+PBQsWGNG65s2bo3fv3saGZZYSlS5dOtVzccNay/jVCnC5L6edO3f65DmKFSvm020hIiIiIiIiIgHATKcQzHayky9fPiOYNGrUKLRp08ao4HriiSeM1kaWp556CoULFzaCUKwuY6yDFV9sMxRsIROA6tSpE+644w5MnTrV2HjsycQAFINODPa8+eabRoTvxRdfNMrzpkyZgpMnT9rWMebMmdMo7yM22bJbTmzO5YvnyCqWGDLDK1xZ2876KhLNtD+IaH8Q0fFBROdM4n+8BmcfafY+cu9/FI5c53o28euqVauM/1t/080332zcPP/GK6+80ri5c//ZmJgYPPTQQ8bNHbdZVvA5+bO83rF7Dq47f2dYBaBYckfDhw/H33//jQ8++MD4/913321E74hZSOwBdfvtt2PFihUpzbjYx8m9MRffkGxgTryfy91ZQSNmWfniObIqKSnJmF0v3LnXnIpEO+0PItofRHR8ENE5k/gX2+NkJxkk1CSG8N/CdTtz5gw2btzo+JiMNjcPagCKPZ8WLlyIa6+9NqW/EjOeGIxiqhj/bwWfLBdeeGFKWZxVNsfHli9fPuUx/L569erG/9lPit+7s74vWbKksSGz+xzZaSBmBd7CESOgvNjmtJBWsE4kWml/ENH+IKLjg4jOmSQwARE22WZVUnozxIU6l8tl/D38WzKaRRQMjNcwXmJVgrnjxHEZfh4EERt49+nTBxMnTkSzZs1SsoKYPtaqVSv079/fCPSwMbmFmU/EwE25cuWMGsjFixenBI+OHDli/HyHDh2M7xs1aoTp06cbaWNxcXHGfYsWLUKlSpVQtGhRo5dUdp8jq/gGy04GVahg8CkS/g4RX9D+IKL9QUTHBxGdM4n/MFGFN16bW9fn4ersufI6xgZC9W/henF78zrHLuCXmcBZUGfBY0kdm4o/99xzxoxz7Pn05JNPGgGgzp07G5lRzJAaN26c0f+JUwcOGDAAN9xwA6pUqWKkeTFIxAZc8+bNM2a0Y4NyZixdc24qxfbt2xtTFA4cONCIzM2YMcMIaHXv3t1Y7ovnEBERERERERGREO4BNWbMGIwePdoI+hw9ehSXXHKJ0Yi8TJkyxu3ll182phh8++23jWylG2+8EY899ljKz7ObO8voBg0aZDQLZ7bSpEmTjPI2YoYSM6zYT6pt27ZGDylmVvH/vnwOERERERERERGxF+Oy2q5LQFmlhHXq1AnbLc8Z/NhEvWbNmirBk6in/UFExwcRnS+J6BpC/I9JI5s2bYqIXsRnz541/h6WtoVqCZ7V65YtiOxK8DIT2whqCZ6IiIiIiIiISEZZlUocABb/s7aztd3DugRPRERERERERCQjmClUqFChlJnpOSFWKM8gl14GVGJiovH/UMuAYrEcg0/cztzevlg/BaBEREREREREJGxw0jCyglDhKjk52ehHHR8fb8w0F4oYfLK2d3YpACUiIiIiIiIiYYMZT6VLl0aJEiWQlJSEcHXy5Els3LgR5cuXD8l+Viy782VmlgJQIiIiIiIiIhJ2GBwJtdK1zGZAUc6cOW0bfEea0MzxEhERERERERGRiKEAlIiIiIiIiIiI+JUCUCIiIiIiIiIi4lcKQImIiIiIiIiIiF8pACUiIiIiIiIiIn6lAJSIiIiIiIiIiPiVAlAiIiIiIiIiIuJXCkCJiIiIiIiIiIhfKQAlIiIiIiIiIiJ+pQCUiIiIiIiIiIj4lQJQIiIiIiIiIiLiVwpAiYiIiIiIiIiIXykAJSIiIiIiIiIifqUAlIiIiIiIiIiI+JUCUCIiIiIiIiIi4lcKQImIiIiIiIiIiF8pACUiIiIiIiIiIn6lAJSIiIiIiIiIiPiVAlAiIiIiIiIiIuJXCkCJiIiIiIiIiIhfKQAlIiIiIiIiIiJ+pQCUiIiIiIiIiIj4lQJQIiIiIiIiIiLiVwpAiYiIiIiIiIiIXykAJSIiIiIiIiIifqUAlIiIiIiIiIiI+JUCUCIiIiIiIiIi4lcKQImIiIiIiIiIiF8pACUiIiIiIiIiIn6lAJSIiIiIiIiIiPiVAlAiIiIiIiIiIuJXCkCJiIiIiIiIiIhfKQAlIiIiIiIiIiJ+pQCUiIiIiIiIiIj4lQJQIiIiIiIiIiLiV/H+fXoRkSA6cAA4eND8f9GiQKFCejlEREQkNOzfD+zbB5w5Y56jlCkDxMQEe61ERPxGGVAiEnl4IvfXX8ANNwBVq5q3du2Af/4BkpODvXYiIiIS7VavBm68EahRA6hdG2jcGPjiC+DIkWCvmYiI3ygAJSKRZ+NG4LLLgIULz9/344/mfZs3B3PNREREJNrxXKR589TnKTt2AG3bAn//Hcw1ExHxKwWgRCSyJCYCL78MnDyZdhlHFadMAc6eDcaaiYiIiAA//GCW3tl54gmzNE9EJAIFPQC1f/9+PP7442jSpAkaNGiABx54ABs2bEhZvnr1anTo0AH169dHq1at8N5776X6+eTkZLz66qto1qyZ8Zj7778f27ZtS/WYQDyHiISI3bvNEzsns2cDR48Gco1EREREzps713lrLFtmP4gmIhIBgh6A6tGjB7Zs2YIJEybg008/Ra5cudC5c2ecPHkSBw8eRJcuXVC+fHl89tlnxmNHjRpl/N8yfvx4TJs2Dc8++yymT59uBJO6deuG06dPG8sD9RwiEkIZUCVKOC8vVQrIkSOQayQiIiJyHvs+ObngAiBe80SJSGQKagDq8OHDKFu2LJ577jnUrVsXVapUwcMPP4w9e/Zg3bp1+Pjjj5GQkIBhw4YZy9q3b28EpxisIgaI3nnnHfTq1QstW7ZEjRo1MHbsWOzatQtz5swxHhOI5xCREPLrr0DHjs7LH3sMyJMnkGskIiIict4ddwBxcfZbZMAAc7BMRCQCBTUAVbBgQYwePRrVqlUzvj9w4AAmT56MUqVKoWrVqli6dCkaN26MeLdRAJbqbd68Gfv27cOaNWtw/PhxNG3aNGV5gQIFUKtWLSxZssT4PhDPISIhhP2dDhwAunZNu6x3b6BChWCslYiIiIipfHlg5kwgd+7UW6R7d3MGXxGRCBUy+Z2DBw82Mo1y5MiBN954A3ny5DGykKzglKXEudKanTt3GsupdOnSaR5jLQvEcxQrVswHW0BEfIKzylSvDvTpA3z1FcBAMkcZGzYE1q4FihTRhhYREZHgYeDpmmvYZNa8sTdl3bpAyZJAoUJ6ZUQkYoVMAKpTp0644447MHXqVKPHEnsynTp1yghIucuZM6fxNTEx0egTRXaPYXkfBeI5ssrlcuHEiRMIV9a2s76KhIK4IkWQ4+WXEfPoo8ArrwA1a3KmAWDcOCTPn49TCQmAH/Y77Q8i2h9EdHyQTCle3LjFxMQY1wWGML42yCidM4lE1v7Azy9+joVVAIoldzR8+HD8/fff+OCDD4yG5FYjcIsV8GGGFJcTH2P933pM7nMprYF4jqxKSkoyZtcLdyxFFAklpf73PxRbuBAJb7+N2P/+w5lrr8Xp667DxjNnkOjnfU77g4j2BxEdH0R0ziQSTdcQOTI4yVNQA1Ds+bRw4UJce+21Kf2VYmNjjWAUG5GzFxS/urO+L1myJM6cOZNyH2eoc39MdZbgGBNe+f85soqNza3AWzhilJY7SsWKFVOCdSKh4iz/ee014MwZuPiBmJyMyn78fdofRLQ/iOj4IKJzJpFou4ZYv359hh8b1AAUG3j36dMHEydORLNmzVKyglatWoVWrVoZvZWmT5+Os2fPIu7cTBGLFi1CpUqVULRoUeTPnx/58uXD4sWLU4JHR44cMX6+Q4cOxveNGjXy+3NkFdPUspNBFSq4o0TC3yHiC9ofRLQ/iOj4IKJzJpFouYaIyWD5XdBnwWNj7+bNm+O5554zZpz7999/8eSTTxoBoM6dO6N9+/Y4duwYBg4caETVZsyYYcyS150zRJxL82KQaNSoUZg3b54xo13v3r2NjKVr2NgPCMhziIiIiIiIiIhICPeAGjNmDEaPHm0EfY4ePYpLLrnEaERepkwZYzmzo9gXqm3btihevDj69+9v/N/Sq1cvo4xu0KBBRrNwZitNmjTJKG8jZigF4jlERERERERERMRejCtlygUJpBUrVhhf69SpE7YbnjP4sYl6zZo1wzZdUMRXtD+IaH8Q0fFBROdMItF2DbEiE7GNoJbgiYiIiIiIiIhI5FMASkRERERERERE/EoBKBERERERERERUQBKRERERERERETCV9BnwRMREZHIUyJ3buTatg1YtgyIiwMuvhgoVQrIly/YqyYiIiIiQaAAlIiIiPhUwtGjKD19OmKfew6wJttlEGr0aKBTJ6BQIW1xERERkSijHlAiIiLiU3HLlyP+2WfPB5/o7FngsceAtWu1tUVERESikAJQIiIi4juHDyPm+eedl48ZA5w8qS0uIiIiEmUUgBIRERHfOXUKMTt2OC/fuhVITNQWFxEREYkyCkCJiIiI7xQoANdllzkvb9FCjchFREREopACUCIiIuI7uXPD1bcvkCNH2mV58gDdugHxmgNFREREJNooACUiIiI+dbpcOZz+/nugVq3zdzZoACxYAFSsqK0tIiIiEoU0BCkiIiI+lRwfj3WFC6Pm998j/sgRIDYWKFIEKFZMW1pEREQkSikAJSIiIj53+vRpnC5UCPFlymjrioiIiIhK8ERERERERERExL+UASWBxam3Dx0ym9MWLqytLyIiIiIiIhIF1IRcAuPsWWD9euCJJ8wpuK+/HpgxA9izR6+AiIiIiIiISIRTBpQExtq1QJMmwNGj5+9r3x64915gzBg1phURERERERGJYMqAEv87fBjo1y918Mny/vvAtm16FUREREREREQimAJQ4n8HDwLffee8fNYsvQoiIiIiIiIiEUwBKPG/mBgg1stbLV6VoCIiIiIiIiKRTAEo8b8iRYCbb3ZeftNNehVEREREREREIpgCUOJ/+fMDI0faNxp/7DGgbFm9CiIiIiIiIiIRTLVPEhgXXggsWQJMn272fGIwqk8foHZtM0NKRERERESiQo4cOZBw6BCwfbvZqqNoUaBw4WCvloj4mQJQEjgVKwKPPw48+CCPOkCePNr6IiIiIiJRJPbMGVQ/dAgJHToAy5ebd7ZoAYwfD9SsafaPFZGIpACUBFZcHFCokLa6iIiIiEgUyrFlC2KvugpISjp/5/z5wOWXA8uWAZUqBXP1RMSP1ANKRERERERE/O/4ccSMGJE6+GRhSd6nnwIul14JkQilAJSIiIiIiIj43+HDiPnlF+fls2cDJ07olQi0ffuANWuAFSvMvlzJyXoNxC8UgBIRERERERH/y5kTKFnSeXm5cmavWAmcVauA1q3N/lt16wINGwKffGIEC0V8TQEoERERERER8b+iRZH81FPOy3v2BBIS9EoEyubNQPPmwB9/nL9vzx7gzjtT3yfiIwpAiYiIiIiISEAkX3YZzj70UOo7Y2OBV18FqlbVqxBIP/4I7N9vv6x/f7M0Lz0HDwJr1wJLlwLr1wNHjvh8NSVyaBY8ERERERERCYjTBQvi0COPoFSPHoj97TcgVy6gaVOgVCkgXz69CoEOQDn5+2/g5EnvP791K3D//cCcOecDicyeeukloEwZ366rRAQFoERERERERM6eBXbsAA4cMPsQFSsGFC+u7eIHO0+cQKGaNZHnoou0fYOpVi3v/bi8lUPu3QvcfTfw66/n72Pz8mnTzJ8bN04BRUlDJXgiIiLhiGnxu3YBp08He01ERMLfoUPmhXODBkD9+uaFORszs0GzSKRq3x6Id8hJGTzYzEpzsnt36uCTuw8+MJeLeFAASkREJJzs3Am89x5w9dXAFVcAbOa6cSPgcgV7zUREwtfvvwMdO6buh7NsmdmgecuWYK6ZiP+ULw98/XXqTKWYGLMZ/PXXe/9ZDoJ5yybULHpiQyV4IiIi4YKjiV27At9+e/6+MWOAd98FFi8GLrwwmGsnIhKeWErEhst2GJD66SegU6dAr5WI/+XMCVx5JbByJbBhA3DsGFCzJlCiBFCwoPef5WOcMIhVoIDPV1fCnzKgREREwgVnmXEPPrnPQDNsGHDiRDDWSkQkvJ06BSxf7rx8wYJAro1IYLFfU4UKQKtWwE03mYNZ6QWfqGRJs1zVTrt23gNUErUUgBIREQkX7E/i5NNPzca5IiKStQtwJ6HQKJs9qv79F/jzT2DTpvRnJxPxNwagZswAGjZMff911wEvv6wMKLGlEjwREZFw4W02GqcmoiIi4h0bLQ8caE4n74mz4TErJJg41f1DDwHffHO+bKpHD7NskEEAkWCpVMl8X7KMldnYnDmSmU9Fiug1EVvKgBIREQkX997rvIz9STRduIhI1jDI9MgjZu8aC8uQWPbMRs3B7P3Hmcqs4BMlJpr9/8aONf8vEkwMODFLkBOj1Kih4JN4pQCUiIhIuKhc2WxC7qlcOaBfP3NUXEREsnYR/dxzZq+9r74C5s83+0JxFjxmQQXLf/8BS5faL3v1VXNmVBGRMKF8fRERkXDB1Pbnnwfuugt45RVziuM77gBuuCG4I/QiIpGAs3bxFkozirLfkxP2gTp6NJBrIyKSLQpAiYiIhBOW2V11FXDZZcCZM0D+/MFeIxER8ZcyZZyXxcUBefNq24tI2FAJnoiISDjKnVvBJxGRSMfs1ooV7ZcxG1ZT3YtIGAl6AOrQoUMYMmQImjdvjosvvhh33XUXlrrVOXfp0gXVq1dPdbvXrQlrYmIinnnmGTRt2hQNGjRA3759ccBjGuqFCxeiXbt2qFevHlq3bo2vv/461XJfPIeIiIiIiIhPlS0LfPcdUKVK6vuvuQYYORLIly/sNnisy4XqefIg14oVwKJFwJYtaqYuEiWCHoDq06cP/vzzT4wZMwafffYZatasia5du2Ljxo3G8rVr1+Lpp5/GL7/8knJ77bXXUn7eWsb7pkyZYvxcr169UpZv2LAB3bt3R7NmzTBjxgzcdttt6N+/vxFQ8uVziIiIiIiI+Fz16sDPPwNLlpiz4a1cCUydaganws3Jk8jx00/Id/nliG3SBGjaFKhVC/jgA7OvoYhEtKD2gNqyZQt+/fVXTJs2DQ0bNjTuGzx4MH7++Wd8+eWX6NChA/bv329kHRW3mVp69+7dmDlzJt58801ccsklxn0MZDFDiUEtZjMxoMSsqd69exvLq1SpglWrVmHixIlGxpMvnkNERERERMRvSpc2b+Fu0ybE3nwzcPbs+ftOnAC6dQNq1AAuvzyYaycikZwBVbhwYUyYMAF16tRJuS8mJsa4HTlyxMh+4v8rVapk+/N//PGH8bUJo+fn8LElS5bEEo4QgLOWLk0TJOLj+bMul8snzyEiIhI1Dh0ypyn/+GNzJH7zZuD0af/8Lh5jt28H/v3XLNE4dco/v0dERPwvKQkYPz518MndM88AR47olZDIsns3+/kw0wYYNQpYsyaq3+dBzYAqUKAAWrRokeq+2bNnG5lRAwYMwL///ov8+fNj2LBhRqZUnjx5jMykhx9+GDly5DCylxjEypkzZ6rnKFGiBHbt2mX8n19LlSqVZvnJkydx8OBBnzxHkSJFsvT3M3h1ghH/MMW/3/2rSDTT/iDRIMehQ4h75hnETJhw/s7cuZE8fTqSmjfH2Rw5fLY/JBw9ivhvvkHMgAE8EAM5c8LVuTOSBw5EYtGi2f9jRAJExwcRUzzL79j3ycm//+LM4cM4Ha+J2iUy5DxwALFduiBm7tzzdz7+OJJHj8aZe+/Fmbx5I+IYwbgGE4cyIqT27mXLluGpp57CNddcg5YtWxpBKDYIr1u3rtGMfPXq1XjxxRexY8cO4ytfJAaiPDGYxJ+jU6dOpXmM9f3p06d98hxZlZSUZPxN4W4zR79FRPuDRDQOAlVdsCB18IlOnkRsu3ZwLVuG1Rzd9sHxIV+ePKgyfz5iHnro/J2JiYh56y3ErlmDk2++ic3Hj2fpuUWCRedLEu0K5suHSg0aIG7BAtvlrtq1sfv4cezasyfg6ybia8a5zJdfpg4+nRPbty9czZphTVxcSkVVuB8j7GIqIR2Amjt3Lvr162fMhDeKqWmAkfn0xBNPoGDBgsb31apVQ0JCgtGLiU3Ac+XKZRsAYuAoN6enPhdI8nyM9T0f44vnyCr+LVWrVkW4YvCOO0rFihWztR1EIoH2B4l0OQ4cQPwLL9gvPHsWOWbOxEX9+yM5OTnb+0POvXsRN2SI7bKY+fNR+Phx5K5ZM9PPKxIMOj6InBfTvbtZhucxYEGuwYNRuHx5FNYGkwiQY/9+xI8b57x86lTUGjkSx48fD/tr6vXr12f4sSERgPrggw8wfPhwo7zuhRdeSImexcfHpwSfLBdeeGGqsrhDhw4ZwSD3iNuePXuMHk5UunRp43t3/J4juSzv88VzZBXT1Pgc4Y47SiT8HSK+oP1BItaBA8B//zkujl271hjU8cn+wOymvXudf9fKlchzbvISkXCh44MIgMqVkfzdd4jt0AHYudPcJIULA2+8gdhatXRNIf7BgCfPLRjg8Wi949fzJt4cxOzciVw5cxoDd+F+jMho+V3Qm5ATZ8B79tlncc899xizz7kHge69916jJM/dihUrjMwhRgg5cx5fMKuROG3atMno69SoUSPje85s9/vvv6d6jkWLFhmZVrGxsT55DhERkYjHk7aLL3Ze/r//+e53MZAVF+e83KMvo4iIhAm2OWnaFEfmzUPysmWc7Qn4+2+gfXsgGwP7IrbYUoctb/r2Ba67DnjwQfP9Fogy/gIFgFatnJffeisjN4g2QY2eMNAzYsQIXH311ejevTv27duHvXv3GrejR4/i2muvxRdffIEPP/wQ27ZtwzfffGP0furatSvy5ctnZChdf/31GDRoEBYvXozly5ejT58+aNy4MerXr58SxOL9LOvbsGED3nnnHXz33Xfoxqk+AZ88h4iISMRj4+8XX7RfVry495OszCpRwrwYscPMaJXfiYiELfa8WXfiBE5Vrw4wm7VcOZa+BHu1JBJx9rl69YDXXmMGCTB5MtCgAfDVV/6bwdc9APXcc+y7k3ZZ5cpAkyaIRkHd0znjHRtxf//998bNXdu2bTFy5Egjnev99983AlXFixdH586d8cADD6Q8jtlTXNazZ0/j++bNmxvBJPeSvfHjx+Oll17ClClTcMEFFxj/b9q0qU+fQ0REJOJxYOaLL4AePYDt2837Lr8cmDgRqFDBd78nXz7gpZeAtWvNkUoLR8e/+w4oW9Z3v0tEREQiz44dQMeOafuNsel3165mAMiX5y52atQwA1+9ewNsvp8jB8Dy08GDzcBrFIpxWW3XJaBYSkh16tQJ2y1/4sQJYxa/mjVrhm29qoivaH+QqMHTBvbtYF8DnkgVKwYUKeKf/YG/Z9MmgGXy5cubAbALLvBenicSYnR8ENE+IUGwfLmZ/eTk55+BK64IzLrwnOnIEYDte5g17tZsPBKOEZmJbSjXUURERDKO/QrKlDFv/la6tHm77DL//y4RERGJHOnl2Zw9G6g1MQfqPAbropUCUCISfnjAYFotRxNYV82RBN5ERERERETYu5KTluzaZT/Zib/L78SWpnATkfBy+DDwySdm00qW41x0kTn7FlM/VVEsElk4NTGDzdu2AQcPBnttRCQasEzmv/+AvXuDvSYikh3M1GaPSrtZ6195RTPqBokCUCISXjhl7113pT4xZI138+bAli3BXDMR8SWOWPIEsXFjoEoVc1a8JUvYLEHbWUR87+RJ4K+/OP21OcB11VXA9OnAnj3a2iLhiIGnK680rx1uvx2oVg1o0wb49VfgjjvMLCgJOJXgiUj42L8fePJJ+2WHDpmzYz34YKDXSkR8jQHm7t2BWbPO3/fjj+aMNfzKgLOIiC8xwN2q1fm+MPv2mQNe/Cx6/nmgcGFtb5Fww6bebET+zjvAsWPm95xRV4JGGVAiEl6jk8x2csILUxEJf9u3pw4+uZfk9eihjAQR8a3du81Ak11T4rfesu8hIyLhI29eoGRJBZ9CgAJQIhI+2HDcW8PADEz9KRLyF0HsZ/bbb8C//5o9z6LR/PnOy1aujN7tIiL+wSzqNWucly9apC0vIuIDCkCJRAI232bDzI0bzcyBQE4rGkgcuRgyxH5ZfLxZzy0SrtavB66+GqhbF7j8cqBGDbOkdOdORJ0CBZyXxcWZ+7uIiK/wc8Wb3Lm1rUVEfEABKJFwxx4FrGu2GvU2aGA27mUmRSTiBXr//qlntGAt99dfA+XKBXPNRLKOM721bm1mP7kHltkA97nnzPLTaMIeT3az1tAttwDFigV6jUQkkhUpArRo4RycatQo0GskIhKRFIASCWeJicCECUC3buYFrBWQ6tsXePZZ4OjRYK+h7xUvDgwcCKxdawadfvrJvGhn41DNZiHhautWYMMG+2WTJkVf/5HSpYF33wViYlLfX7488OKL6uEgIr4PQL3xBlC0aNplPM8qVUpbXETEB5TDLhLOWJrD7Ag7PJF67LHIvFBjeQ5vVasGe01EfGPzZu+B5uPHo69ZaLt2ZtbBtGnm9rnhBuCyywKf6cjG55yVj1+ZecVedCISeVj2vHSpOQHC7NlAxYpmGTS/8jNJRESyTQEokXC2f79zaQ4vlpgVpSCNSOirVMl5GTP7ovHiJ18+oGZNM5szWNhT76OPzFmwkpKAO+80Z8riBamIRBZmXHLf7tXL3M8ZbHYqBRYRkSxRAEoknKVXcsYLOBEJfSwt4+i73SxMDz1klqRJYHFih+uvB5YvP3/fyJHAlCnmLIUKQolErpw5g70GEu3OnDH7uXJAmdUMhQoFe41EfEJhfZFw74fEGbPsXHCBehaIhAsGmL75xpxMwL3xLfu7sem++psF3s8/pw4+uZc+v/22mRElIiLijwGQYcPMc3wOdtx2G/Dnn2ZJvkiYUwaUSDgrUcKcJevKK1PPelewoNnDoEyZYK6diGS2DI+N9dlv6NgxsyluyZLKZAyGEyfM2UWdfPgh0LOnMtNERMS3OMhx663AokXn75s71xyg4n0NG2qLS1hTAEok3LFHypIl5sjIH38AF10EXHpp4Bv1ikj2sck1bxJc7PvirQQnRw71hhEREd/jLM/uwSf3kjzOcv3550DhwtryErYUgBKJBAw28XbTTcFeExGR8MeSxx49gK++sl/OBsXMQBUREfElVjA4mT8fOHpUASgJa+oBJSIiIuKpQQP7oH69emY/Ds6YJSIi4kvesqDz5FH2rYQ9nwSg9u7di3/++Qdnz571xdOJiKc9e4CFC83U24EDgb/+Ag4c0HYSEfEX9t966y3gu++AG28Err0W+Ogjs08XJ3kQERHxtbZtnZdxYhJOQCQSTSV4x44dw/Dhw1G7dm3cc889+Pbbb/H4448bwaeKFSvinXfeQWlNFy3iO7t2Afffn7oUZMQI4LHHzGCU+sWIiPhHqVLmrUULcypsjj6LiIj4S9mywKuvAr16pb6fPV779fPen1AkEjOgRo8ejdmzZ6MgZ9kCMGrUKNSoUQPjxo1DfHy88b2I+NDs2fZ9SF5+GVizRptaRCQQPaEUfBIREX8rUADo1AlYuRIYNMjMemLmLa8HNMGQRGMG1Lx58/Dkk0/ihhtuwMqVK/Hff/+hf//+uOqqq3DmzBkMHTrUP2sqEo04HfuYMc7LOULSqJFGQ0REREREIiUIxYynZ58N9pqIBD8D6tChQ6hcubLx//nz5xtZT5dffrnxPbOiEhMTfb+WItGKU64eOuS8fP9+ICkpkGskIiIiIiIi4v8AVNmyZbF27Vrj/3PnzkX9+vWRL1++lIDUBWrMKeI7hQsD113nvJwzMZ3b/0REREREREQiJgB15513YuTIkWjTpg1Wr16Nu+++27i/Z8+emDx5srFcRHzYd4Qz39kFmRjsbdNGm1pEREREAuf0aWDzZuDLL4H33jP7FTErX0TE1z2gOnXqhKJFi2LJkiVG0ImBKEpISMDTTz+NO+64I7NPKSLesOT199+BAQOAWbOA+HigQwezMWH58tp2IiIiIhIYp04BP/4ItGtn/t89K5+9STlzqIiIrwJQxAbkvLkbO3ZsVp5KRNITFwfUrGmOMB08CMTEAMWKAblza9uJiIiISOBs3w7cdJPZp9TdJ58AjRsDffoAsZkushGRKJGlANSKFSvw559/4siRI2mWxcTEoEePHr5YNxFxlz+/eRMRERERCQaW3XkGnywvvQTcdRebBgd6rUQkUgNQU6ZMMXpAuVwu2+UKQImIiIiIiESg9eudl+3ZA5w9G8i1EZFID0C9++67uPrqqzFs2DAUKlTIP2slIiIiIiIioaVVK2D8ePtl9eqpRYSIeJXpAt3Dhw/jnnvuUfBJREREREQkmrDPE2ditjN6NFC8eKDXSEQiOQB1xRVX4HfOyCUiIiLmdNRsyrptG3D0qLaIiIhErnLlgJ9+Aq691pwYx7pvxgygUaNgr52IRFoJ3pAhQ9CxY0fs2LEDderUQZ48edI85pZbbvHV+omIiIQuBp1efhmYOBE4eRK4/npg+HCgWjUgPkvzfIiIiIS2KlWA6dOB/fvNQZiCBYEyZYK9ViISBjJ9dvzTTz9h69at2LRpEz7//HPbJuQKQImISMRj1tPVVwNr156/b+ZMYM4c4I8/gBo1grl2IiIi/sNewOoHLCL+DkCNHz8eTZo0waOPPoqiRYtm9sdFREQiw6JFqYNPlhMngGefBSZMAPLmDcaaiYiIiAidOQPs2GFmrR8/DlSuDJQsCeTPr+0TDgGoAwcO4Pnnn0fdunX9s0YiIiKhjtNMT5vmvPybb4BDhyIvAMUptg8eBGJjgcKFgWLFgr1GIiIiIvZYIvrLL0D79uZ5GfEcpl8/86am+aHfhLxevXpYazfiKyIiEi148lKkiPPyAgXMx0TSCRwzvv73P7O0kD2u2rQB/v7bDMaJiIiIhJqtW4HWrc8Hnyg5GXjxRWD27GCuWdTKdAbUQw89hH79+hmZUPXr10e+fPnSPKaRZkAQEUkfS7V27QI2bAASEoCKFYHSpYGcObX1Qh1n/uneHZg0yX55z55menek4Hu0RQszEGVZsoRT4wJ//WU2pBUREREJJZ99BiQl2S8bNszs5RlJ52uRGIDq0qWL8fWtt95KaTpucblcxverV6/25TqKiEQeljG98w7w1FPnD4ycVXTyZOC66wCb4L6EGAZd+Po9/3zq+y+7DLj77sjJgOLsfhwpdA8+WY4dM9+zTz8NxMUFY+1ERERE7C1f7rxlNm92Dk5J6ASg3nvvPf+siYhINFm2zKw998yIuuMOs6ypTp1grZlkFEvwHn8cuP12YOpU4PBh8/WrVcvMZIsUR46Y/ROczJsH9O2r2ZBEREQktDRv7tyzk+fauXIFeo2iXqYDUI0bN476jSYiki2sQ+csaXZcLuD114HXXjPL8iS0sRE3b/XrI2KxJLRMGWD9evvl5cvrBE5ERERCzzXXmANk7j2gLCNHajKVUA1AjRs3DrfddhtKlixp/N8bluD16NHDV+snIhJ5WNK0aZPzck70cOqUAlASGnjixlLDBQvsl/fpowCUiIiIhB72V50/H7jnHmDlyvMZ7GPHsnF1sNcuKmU4ANW8eXMFoEREfIH9nRo0MGfmsNO0qdkPSiRUXHIJMGAAMGLE+fvY42rUKHNGPBERkUA6cABITAQKFtQ5kzhjv+q6dc12AXv3mj2fGIAqW1a9K0M5ALVmzRrb//vCoUOHMGbMGPz00084duwYqlevjr59++ISnuwCWLhwIV566SVs2LABpUuXxiOPPILrr78+5ecTExMxcuRIfPfddzh16hRatWqFgQMHoojb9NiBeA4RkQzLnx8YMgSYNcssuXPHWvT77tNBUUJLsWJA//5Ap07AokVAfDxr8s2ZY/h+FhERCQQGEX791RwQ2b3bnKGVWbqcGCRHDr0GYq9ECfMmQefzKXoYRMqMPn364M8//zSCUJ999hlq1qyJrl27YuPGjUawp3v37mjWrBlmzJhhlAH279/fCAZZnn76afzyyy947bXXMGXKFOPnevXqlbI8UM8hIpIp1asDX36Zull11arAjz+a6cIioYajzMx26tjRnOWP71cFn0REJJAzCA8bBrRtCyxZYmaSv/++2Yfxr7/0OohEYhPy06dPG0Ga33//3fi/69zoPb+eOHEC69evx9+cwSkDtmzZgl9//RXTpk1Dw4YNjfsGDx6Mn3/+GV9++SX2799vZET17t3bWFalShWsWrUKEydORNOmTbF7927MnDkTb775ZkrGFANZrVu3NoJaDRo0MNbV388hIpJpefMCbdqYJ1D795vlTMwyKVVKG1NERETE086d7A2TdrucPg08+CAwezZQvLi2m0gkZUC9+OKLGD16tBG4YWbQf//9h5MnT2L58uVYvXq1kSmUUYULF8aECRNQx226cTYx5+3IkSNYunRpmgBPkyZN8McffxgBL3617rNUqlTJ6FW1hBd1QECeQ0Qky3XprEFnbXrt2go+iYiIiDj55RfnbfPnn/YznYlIeAeg5syZgy5dumDWrFno0KEDateujU8++cS4v2zZskhOTs7wcxUoUAAtWrRADrd63dmzZxuZUSx327VrF0p5ZAOUKFHCCHgdPHjQCIIxiJWTU0R7PIY/S4F4DhERERGRqHL4MLBjh5nFKxII6fV4Yja5iERWCd6BAweMGfGoWrVq+Pjjj43/M2PogQcewLvvvouePXtmaWWWLVuGp556Ctdccw1atmxpNAR3D06R9T3L/xgA8lxODCaxsTgF4jmyyipbDFfcdu5fRaKZ9gcR7Q8i0XB8iDt5Eglr1yJmyBDErFhh9C1MfvppnL34YiSpL5z4cZ/IddlliGX2uE0FiuvKK3GmQAEkhfG1lUSnkxFwjGBcg1VsfglA5c+fPyXoUqFCBezcudNoPJ4vXz5UrFjR+D4r5s6di379+uHiiy/GKE7rfC4I5Bngsb7PnTs3cuXKZRsAYuCIywP1HFmVlJRklC2Gu82bNwd7FURChvYHEe0PIpF6fMibOzeqLF+O2LvuOn/nnj2IbdMGyc8/j9033YQDYXwRJaG9TxTLlQtlX3wR8Y8/nnpBoUI4PXo01uzYgTNnzvh2JUUCZHOYHyPsknp8EoBio+73338fjRs3NgJQDMAweHTLLbcYTbsZiMqsDz74AMOHDzcaf7/wwgspK1+6dGns2bMn1WP5fZ48eYxAGMviDh06ZASD3P9gPoYZWYF6jqxKSEhAVc4iFKYYpeWOwsBjdgJxIpFA+4OI9geRSD8+5Ny7F3GPPGK7LH7IEFS47TaUrFjRyFKJSUqCKyEByeqXKj7cJ5I7dUJy8+aIee01xGzfjuRrrwVuuw3JpUvjQm1pCUMnI+AYwYnoMirTASiW191zzz1GuR0DUXfffbcxc917772HtWvX4i73EZEM4Ax4zz77LO69914MHDgwVeoWg12cbc/dokWLjCyp2NhYY+Y89pxiM3CrSfimTZuMvk6NGjUK2HNkFf9WBrHCHXeUSPg7RHxB+4OI9geRiD0+sPfpvn32y5KSEHvwIPIkJQHvvAMsXw5ceilw770sm+DIa6DXViJxn+DjOdPdpEnG7Hex/D42FuF52e5n7GfMfZbXq0WLmrMtS8jKHcbHiIyW32UpAFW9enV8++23+Pfff43v+/bta2Q9sX9Tq1atjMBURjHQM2LECFx99dXG7Hn73A5oLI1jUKpt27ZGSR6/zp8/H9999x0mTpxoPIYZStdffz0GDRpkPA9ftKFDhxrZWfXr1zceE4jnEBERERGJePFeLh04ozRbcbRrB1hlULNncwpt9toALr88YKspUYCVKxks+Yk6p04BTJ7o1g1Yt868r0EDMzDM2efj4oK9hhLFYlzsGBUkb775JsaOHWu7jIGekSNHYsGCBXjppZeMtLQLLrgAjzzyCNq0aZPyODbxZuCIs+cRG6QzmMSZ7SyBeI7MWsGmjeBnQB2EK2439rCqWbNm2EZrRXxF+4OI9geRiD8+MMDUrBmwYUPaZZyYiAPRhw6lXcYMqN9+A8qUCchqSpTuE2yZwuAnr+HCtJTJJ3idyYDT2bOp72ernL/+AqpUCdaaSYQeIzIT28hQAGrcuHGZSr/q0aNHhh8frRSAEokskXDwEPEV7Q8iEbw/LF4MXHklG5ecv4/ldd9/D7Rs6fxzf/8N1K0bkFWUKNsnWGr23XfA6NFmydnVVwNPPmkGWrxl7UWi48eBrl2Bjz6yX/7MM8DAgcqCCiEnIuAYkZnYRob2SAWgREREREQEDRua/Z2mTQMWLgRq1TJLfZx6Q1k0O5n4w969wMMPA59/fv6+yZPNAAyDpWFcbZIlR46wWbHz8h9/BHr35tT2gVwrkcwFoNasWZORh4mIiIiISCRjRglncR48GEhMNPvwsMnxpk1AzpzmfZ5YEsXG0SK+xvede/DJwgy9fv3MQFShQtGz3XPlAsqWBbZssV9esaK5n4oESaancDvFpmYemDImIiIiIiJRgrMe8WLXmhG6VCmz4bgdtvNQ/yfxh6++cl42Z459T7JIxmAvS+ycPPKImrdLeASg1q5di/bt2+Pdd99Ndf+RI0eM+2+++WZjVjsREREREYkybPp8773mRX/TpkCJEmavqF9+AW64QT1nxD8YBPWWrWcFSKPJpZeaQSgGid23xYQJZvaiSBBlaI/cvn07OnbsiH379qFSpUqpliUkJKB///44dOgQ7r77buzevdtf6yoiIiIiIqGcfcEG0MxKWbYMmDEDuPxyoECBYK+ZRKqbbnJedscdQLFiiDpFiwL9+zODBJg+3dwP+f977tG+KOERgJowYQIKFSqEzz//HK1bt061LHfu3OjcuTM+/fRT5MyZE2+99Za/1lVEREREREJdkSJmH5po6r0jwXHBBfYlZyz55IxvYTqrWLYx6HvhhWYQrm1boHLl6N0WEn4BqIULF6Jbt24owoOJg+LFi+O+++7Dr7/+6sv1ExEREREREUmLQc4+fcyZ35jhwwy8N98EfvsNqFJFW0wkHGfB27NnDyqyY346qlWrhl27dvlivURERERERES8Y5IE+x5dfDGQlKRMH5FwD0Ax84lBqPQcPHgQBQsW9MV6iYiIiIiIiGRMQoJ5E5HwLsFr1KgRZrB5WTpmzpyJWrVq+WK9REREREREREQkmgJQ9957LxYvXoyRI0ciMTExzfLTp0/jxRdfxIIFC3APa29FRMT9QxLYsgX46Sdg9mxgwwbg2DFtIRERERERiRoZKsGrU6cOnnrqKYwYMQJffPEFmjZtigsuuABnz57Fjh07jOAUy+8effRRNGvWzP9rLSISLk6eBObNA+6663zQKS7OnLHlkUeic3pgERERERGJOhkKQBEzm2rUqIFJkyZh3rx5KZlQefPmxRVXXGHMgFevXj1/rquISPhh5tMttwBnz56/j/8fNgxo0MBcJiIiIiIiEuEyHICihg0bGjc6cOAA4uPjUaBAAX+tm4hIeHO5gMmTUwef3DEIdcUVyoISEREREZGIl6kAlOfMeCIi4gWnAl61ynn55s3AqVPahCIiIiIiEvEyFIBq1aoVYmJiMvSEfNzcuXOzu14iIuEvRw6AffG+/NJ+ef36rGMO9FqJiIiIiIiEZgCqcePGGQ5AiYiIm1tvNUvt7Ga9e+45oHDhyN9cR46Yf3/u3NHx94qIiEhkS04GYjM0obyIZDYANXLkyIw8TEREPJUvDyxYAHTocL4cr2RJYPx4TjEa2duLQafVq4GhQ4G//gIqVDD/36gRULRosNdOREREJHP++w/4/Xfgww/Nc5lu3YBKldifRltSxF89oDgD3tq1a3H69Gm42GTXCAIn4+TJk1i6dCn69euXlacVEYk8cXHmbHc//ADs2wecOWOesJQpE9kjZzw2/PQTcNNN5v9p507guuuA4cOBRx9V+aGIiIiEj23bgNatU/f3fPNNYOBAoG9fZXmL+CMAtXjxYjz66KM4fPiw7fK8efMqACXpO3oU2L0b2LMHyJPHzAgpXVpbTiIX3+O8RdMI4QMPnA8+uWMW1J13ApUrB2PNJJrxffnvv8CaNUDVqkCNGkC5csFeKxERCYeJZV57zX5yGQ6sseWC2gyI+D4ANXbsWBQuXBjPPvssZs2ahdjYWLRr1w4LFizAhx9+iLfffjuzTynRhoEn9sThiAHrp4kXAjNnAhddFOy1ExFfOHDAzHiywywwBgEUgJJAWrcOuPpqYMuW8/dx4GPePKBmTb0WIiLijIPmEyY4L//gA3NyGRHxKtP1Hyy969mzJ66++mpceeWV2LlzJ1q0aIHBgwfj1ltvxRtvvJHZp5RowgvPiRPN/jdW8InWr+d0i8DWrcFcOxHxZemhNzlzaltL4Ozda2bduQefiEHSm28Gdu3SqyEiIs543XLihPPyQ4e09UT8EYBir6eS58pIKlSogHUcUTzn2muvxSq7tEQRy44dwKhRziMLK1dqW4lEAva5YnmTHZbdKvtJAh2AWrbMfhnPY5iZKyIi4qRgQeD66523Dwc5RMT3Aajy5csbWVBUqVIlo/H4xo0bje/PnDmD48ePZ/YpJZokJnofIeCMWSIS/kqVAt5/3ww2uYuJMe9XzzcJpPTOTThjo4iIiJMCBcxeT7lzp1126aVqIyLirwDUjTfeiFGjRuGDDz5AkSJFULt2baMf1A8//IDXX38dVdnLR8RJrlzepymtXVvbTiRSsBfC338DTz9t9t7p2RNYscKcQSZHjmCvnURbRl5Cgv0yBkVLlAj0GomISLipVg344w/gjjuA/PnNGY1HjAA++0wDayL+akLerVs3HDx4EH///Tc6dOiAoUOH4v7778fDDz+MfPnyqQeUeMcP6gEDgH797JepCblEcgkQ+wfwQjg+0x+94Yl/JwclBg8GTp0y+z6l1xtKxF8Zeb16AaNHp13WubMCUCIikrHzGk5aMWmSWdERG2seP3RuI5Jhmb4K4qx3TzzxRMr3derUwdy5c40yvMqVKxtBKBFH/IC+917zYnzMGHNKU/ONBHzyCXDBBdp4Enl9z776Cnj9dbMElaNm993HJnqIGjxB8yzFEwkkvv8ef9zMwH3xReDwYYDnKwxKPfKI2dtDREQkI/LmNW8i4v8SvI4dO2LDhg2p7mPQqW7duti+fbtRoifiFUcKhgwB1qwBfv/dbDw+dy5Qvbo2nERe8OnWW4Hu3YHlyzmNKDBsGNC0KbB5c7DXTiS6cAKV/v3NfZHHHx57hg41s6NERCQyMQN70ybzM59f+b2IhHYG1NKlS+FyuYz///7771iyZAkOHDiQ5nE//vgjtm3b5vu1lMhjzYKlmbAkki1dCixcmPZ+Tv3OjCj2DXDqSyMi/imfKF9eW1ZEJBrwfItZr2++aQae2Iv2wQfNwQhNhiISugGoTz75BF988QViYmKM2zPPPJPmMVaA6oYbbvD9WoqIhJvTp80eAU6mTQN69zZ7n4mIiIiI7xw5YvadnTz5/H0MQr38stm/6ZVXzJntRCT0AlCDBg1C+/btjSBTp06dMGTIkDSz3bE3VIECBXDhhRf6a11FJFQdPWr2VGGPL5azcFapaMdt4K3ZOJdpO4mIiIj43p49wHvv2S/j/QxOKQAlEpoBqPz586Nx48bG/9977z3UqlVLzcZFxMzy+fdfc5azefPMBr+PPgrceadSm1laxzTvGTPs3yldu2rmLRERERF/2L/fnH3YDu+3aScjIiE4Cx4DUez/NGrUKKMf1JEjR1C4cGFccskl6Ny5M4pyinERiQ7//AM0aWIGoqxMqD59gG++AT74wGz6G83q1gVuvhn44ovU9zNTtEsXTdsrIiIi4g/pzcyumdtFwmMWvF27dqFdu3aYMmUKcubMaWRDxcfH491338Utt9yC3bt3+2dNRSS0cOSIPYys4JM7zmq4cWMw1iq0MADHxpdffQVcey3QooXZF4rZYuXKBXvtRERERCJ31u0GDeyX8X4uF5HQz4B66aWXEBcXh2+++Qbl3C6gOPvdfffdh7Fjx2LkyJG+Xk8RCcXmjvPnOy9n0KVp00CuUWhiT6zrrwdatgTOnlW/ARERERF/K16cM2kB110HrFt3/n72Mf74Y3O5iIR+AOqXX37BgAEDUgWfiN/36NEDL3KqSxGJfGw4niOHfQYUFSwY6DUKbXnzBnsNRERERKJHlSrATz8BW7eamfmVKwMVKqhPqUg4BaDOnj1r9HyyU6RIERw7dswX6yUioa5YMaBDB+Cdd+yX33hjoNdIREREwtmpU+bXXLmCvSYSKcqUMW/sWRrJ/vuPvXLMWakvuMAsMSxUKNhrJZL9HlDVq1fHl19+abvsiy++QLVq1TL7lCISjnLnBoYMASpVSruMmZA82IuIiIikZ+dOc8KO9u3N26xZ5n0ikr4VK4DLLgMuuQS46ipesANPPw3s2GHOBsgWECLhlAHVsWNHDB06FFWqVMHDDz+Mrl274vDhw2jTpg2KFy+OvXv34uuvvzbK81599VX/r7WIv504YY4isNF2njxmnbhqxdNiGjP7QP32m1lnX7o00LUrULGiSvBEIsm+febo6qJF5ohqo0ZmkFlZCiKSXbxIvusuYMGC8/dxNl1O3DFtWvgOaPGi/+BBID5emSjiP9u2mUGnvXvPt8gYM8YcKL7nHrNna9u2ZtUCz89FwiEA9fvvv+P48ePG/y+//HKjyfioUaOwwO1AUaxYMYwYMQJXX321/9ZWJBA4k+NLLwEMpiYlmfc1bAhMn242LpTU2A/ujjuA224DYjOdVCkioY5ZCA8/DMycef6+hATgo4+A1q3Nk1wRkaz64YfUwScLB7h4/513ht+23bwZeP994NNPgXz5zFmDr7jCnJhExJdWrjwffKJhw8x9Z8aM8/ctWwa89po5YMy+WBIajhwxrjtzHTyIi3LmRBxbGTHxIcJlugcU3XLLLbj55puxceNGIxOqYMGCqFy5MmJiYny/hiKBxIDT228Do0envv+PPwAGV3/5BShbVq+JHQWfRCJPcrJ5EeUefLI+K2+9FVi9GlDpvYhkFTOEXn/defm4cWagO5x62WzaZM4CzAFNCy/8b74ZeOstoGTJYK6dRJr168//P39+85g8cGDax+3ZAzz3nLm/RUGQIywyP/v1MxIcYl0usOud65prgIkTzcH9CJbldAUGm1iSd/HFFxtfFXySiBnpZ/aT02iW+zSuIiKRjqXIngF59+CUZ2BKRCQz+DniNJsuJSaajwmnJuojR6YOPlnY40rnkeJrtWuf/z8Dn99/7/xYlrSyvYgE19GjQP/+wIcfAi5Xyt0xc+YAd99ttj2IYBnOgOrRowdycMr1dDAQNXfu3Oyul0hwnDxppkM64Wh/y5aBXCMRkeD2MOGoqRNOay2SHp5gs4cYm+EyW56zqIZrXx/xrSJFzN40LBGy06kT4DD7dkjihSNbNjh5912zFE/EV5jxxN5OHCjPCLeAhwTJ7t1m8MkOq224nMfJaA9A1apVC0V4kBCJZGyomzcvcK7nWRoXXhjoNRIRCR72d+KsOkuX2i9nuriINzyeso8PJ6iwZjXjBBbvvWdOi56BwU2JYAxIspyX/WlYuuaucmWzbC2SWnyoXYH4GluDMOvp3nvNiUK6dQMmTLB/LHu2Fi2q1yDYjhzxntnJANRFFyFSZSoDqm7dun5dmbfeesuYSe999ps4Z9CgQfiEs2u5KVu2LH5gw0IjczcZ48aNMx5z9OhRNGrUCEOGDEE5t9rJ1atXY/jw4Vi5cqURROvcubMxs5/FF88hEYKzuD3yiJk+bbeM05qKiEQLjsBxNp3mzdMuK1/enA1PxBuWHN1wQ+qT7S1bgP/9D1i+HKhRQ9sv2vF8+6efgClTgMmTzYBT586chjv8eqHwM5MZXePH2y/n3yXia5wk6csvzzcjZ6CJE4V4vjeHDFH/p1CQP7/5OeeUjRbhM6+HzJRVU6dOxcsvv5zm/rVr1+LBBx80AlPW7VPOKHHO+PHjMW3aNDz77LOYPn26EUzq1q0bTp+rJz948CC6dOmC8uXL47PPPjMCaZzBj//35XNIhOBI7KOPmicI7iNu/GCfNy/8ToRERLKrfn3g22/Pz5zDEfybbgJ+/FGfiZJ+9tOIEfYjvWxk/8Yb52eblejGgPaAAcCvv5olKE89Zd4Xjpn0bCxsV2Lavr0y6cV/GGCqWdO8vfKK2aOxWTOgXj3g6aeBJUs0m3eoKFECaNvWfhlnXo/wiQqyNAueL+3evRtDhw7F4sWLUZH1q25cLhfWr1+PBx54AMVtIoEMEL3zzjvo168fWp7ryzN27Fg0a9YMc+bMwQ033ICPP/4YCQkJGDZsGOLj442G6Vu2bMGECRPQvn17nzyHRBhOkctgKE+EmAJZoID5QaGpc0UkWkfqOAvVzz+baeMJCeaJLj8bRbzhlNJ//eW8nBdEDFKF0wxn4j9xcZFxrlWpkjnr3ccfm7d8+YDevYFLLzXPJ0X8jQEMlq/y2pZBfvZR4/4loaFgQTNIyOPf7Nkpd7saNUIMPzMi/HMiQxlQbdu2RWE/NQD8559/jODOrFmzUI8RWjdbt27FiRMnUJk14DbWrFmD48ePoyk7/p9ToEABo1/VEp7UgG0rlqJx48ZG4MjSpEkTbN68Gfv27fPJc0iEfjCw3xMbRbL0NBJOiEREssMqQ+YxWcEnyQhO9W1lztnh+4l9xkQiDfuc9e1rXlxy9jtmjUZ4VoOE6PUMB4wUfAo9F1xgzkq4ejWSFyxA4h9/4Ayz1jwScqI2A+r555/32wq0atXKuNn5999/ja/sCbVgwQLExsaiefPm6N27N/Lnz49dnB7aOCcunernSpQokbKMX6txdgCP5bRz506fPEexLHapZ4YXA2zh6iRnjHP7KhLNtD+IaH8QD3FxyDVgAGK/+y7tpomJQfKjj+IUZ1oM43OhjNDxIYqxJI8i/D2eGZwxPXb/ftSMj0eOrVuRVLgwkphpKxKNnw/ly+Nk8eJGYkvFnDmRO0w/KxjX4L4dFiV43jAAxaATgz1vvvmmkRH14osvYt26dZgyZUrKAT2HxwwqOXPmxOHDh43/nzp1ynY5JSYm+uQ5siopKclobh7uuMOIiPYHER0fxFOpokVR8rXXEM++ONY5U968SHrrLezIkQP7IuA8KKN0viTRLn/OnKh48CBy9OxpTkLAC9fLLkPya69hQ44cOJmN6yqRcLc5zK+pPeMlYRmAeuihh3D33XenlP8xC4m9oG6//XasWLECuc6NKrCPk/V/KyiU+1xKN++3mom7L6c8efL45DmyiqWHVdncOkwxeGdEaytWTNlWItEqo/sDg+ocIeBIASc8EIlEOj6Iu7MdOiC2TRtz9ru4OLguuABnixVD8fh4RPZcPybtDyKmXJs2Ifaqq1JNPhDz22/IeeWVqPHHHzjl0HZFJJKdjIBravbtzqiQDkDxQs2z99SF7MtzrizOKpvbs2ePMUOdhd9XZ18Bo590KeN7d9b3JUuWxJkzZ7L9HFnFi9DsBLBCBXeUSPg7RPy6PzDYxIuvr782Z/hp0MCcEYefOxkcMRAJNzo+iIGfiWw07nZxGY3tcLU/SFRjadGLL9rPfHnkCGI//BB5OAGQ+hVJlModxtfUGS2/y3AT8mDp378/OnfunOo+Zj4RM4dq1KiBfPnyGTPoWY4cOYJVq1ahUaNGxvf8+scff+Asewycs2jRIlSqVAlFixb1yXOIiKTr77/NqXAfeQT46CPgySeBiy4yZ8px+2wRERERiTicRZWzqTqZO9ecFUxEIlpIB6CuvfZaLFy4EOPGjTP6P82fPx8DBgzADTfcgCpVqhh1hh06dMCoUaMwb948Y0Y7NihnxtI111xjPEf79u1x7NgxDBw40EgNmzFjBiZPnozu3bsby33xHCIiXnFCgzvuAI4eTX0/S3tvvRXYsUMbUERERCIX++d6m1W6XDnzMSIS0UK6BO+qq67Cyy+/jAkTJuDtt982Zr678cYb8dhjj6U8plevXkYZ3aBBg4xm4cxWmjRpktFfiZihNHHiRAwfPhxt27Y1ekgxs4r/9+VziIg42rsXWLfOftn+/WYAiideIiLiP6dOmZ+3v/4K7NsHXHEFUKECpzbWVhfxN7ZVYYndjTfaL+/VSwEokSgQ42InXAk4q5SwTp06Ybv1T5w4YcziV7NmzfCrV2WK78GDxjTQKF5cPXjEv/vDsmVAw4bOP/zTT0CLFnoVJGKE9fFBIhNnPf7uO+D224Fz/T8NrVoB778PlCnjt1+t/UHkHAZ+R4wAxo49v0liY4HRowG2XWGvOJEocyICzpkyE9sI6RI8EZ9jI+h//wUeeIDTKpo9eJ54Ati6Nf2fZeN5BhI+/tgcPf3vP71AkjHFigEFC9ovi49X9pOIiL9t326WPLsHn+iHH4A330x7v4j453xoyBAkr1qFpLfeQvKUKcDatUDXrgo+iUSJkC7BE/G5jRuBxo2Bw4fPj4i+/DIwa5aZheJUBsUAVbt2wB9/nL+Pj50zB6hRQy+UeMeRdY7udeuWdtnAgZxOU1swWmYA2r3bzMDMlw/gTK7qdyHR4MABsxSZTYhZhsOStwIFArsOnIGUg1B2Xn3VHJi64ILArpNINCpUCKdy5MDGs2eNnr7hOu28iGSNMqAkuno/jBlzPvjkGZjiKKgdPv6hh1IHn2jbNuC669RAWtLHLKf27YHZs4GLLwZy5QJq1TKz6Xr2BPLm1VaMdOw707u3GbBmejKzL4cONRvUi0QyDuDcdpv53ucAUPXq5jE10JMveMt05nFes5GKBFRiYiLUCUYk+igDSqIHez59+aXz8mnTzN4QniMxLL379lv7n9m82SzF82PviLDBGd44ws1AX/785jaJiwv2WoUO9jXgzJoMQHEbcZIDZT5Fz2dPjx7AzJmps6FeeMHMwnz+eSBMa/5FvOIxgcfVxYvP38csJB5vc+QAXnvNzAYMhKuvTt13xl2DBtoHRUREAkAZUBI9GAzxdqLLAIFdwITlMt569fMEO9pxZPm++4ALLzQzOxhkmTTJnOFN0vY/YJmHgk/Rg0Fs9+CTuzfeUBaURC5m+LkHn9yx8TdLUgOlbl3zGGWH2dGckCRaMSi4c6fZJ+vYsWCvjYiIRDAFoCR6sOfEo486L2cpFEdkPbF5NEumnJQvj6jGk9YbbgA+/fR8fw3OctK9u9lbSxNtSrTjPuIkKcnMkBKJRN7K7FjyZlcS7y9lywLffw/cfbdZFk2cjISl0d5mKY2G12jUKLM8kgNIHExavVpN2UVExC8UgJLocvPNQMuWae9/8EGgZk37n2Gj4F69nFP6S5VCVGP/rHNTb6YxYIB6ZImkN610oEqQRALN2/GRU68HuhF5hQrAhAnAunXmjLjz55ul0Swbj9YMtTvvNGcDZvYTm8R/8omZxbxmTbDXTkREIpB6QEl0YTDpww/N0T2m/7PvSqdOQOXKQNGi9j/D7Kc+fcyePewfwd4tHD296y6zdwtLqqLZsmXeT25ZwigS7RfhzLTgBa+n5s2ju/RHIv+9X68e8PffaZexMTkzkwONkz5o4gcTg0w//5x2G7FP4VNPAVOnBj5IKCIiEU0BKAkMptozzXvTJuDQIfNijD1wOB1zME6Iebvyyoz/DNd18GCgWzez2TZPXnlfVk5iuR2YNcQT8kqVgNq1gXLlgJgYhCVvJYgM3tmVNYpEE37ecAIEZlps2XL+fpa7TJkCFCkSzLUT8R8eJz//3Aw2uc8ke/31wOjRCm4EG0vnnXzzjVkiqQCUiIj4kAJQ4n9nzgBLlph9gg4cOH//PfeYfQfCpYQtZ06gYsXsPQdnzWvdGli79vx9vPicN88cJQ7HIFT9+mb5AgNznrp0CZ/XV8SfGHT/9VczAMVblSpm8Fb7h0Q6DrRwJlk24+cAFLONgzUAJWl7XDrhjMDheE4iIiIhTT2gxP/YV+B//0sdfCKmdr/zjpkdFQ3YaJiNud2DT8Ttct11wH//ISxxRjc2dvU8kWWvrYEDvTdwF4kmbIJ82WVm+S4b/ir4JNGCZabM+Lv8cqBGDQWfQsUddzgvY8a3yoNFRMTHlAEl/vfLL2bfJDvMgOrY0QxiRDrODDdnjnOvpG3bwnM7xMUBl1wCLF9u9pPg31Knjvm36OTVfF03bDC/8sKLWS8c/c8qNollJgEDl2xezR4q0d6HTEREMo/l/0OHAs88kzZjk70vmfktIiLiQwpAif95Zvx4ZgWdPh0dr4JTEM6ydy/CFoNQDKx46wcVjTg7IGdK3L37/H0NGgAzZ2ZtW+3cCTz+ODBtGuBymfc1aWJ+zzIXEQkfPPZxP9ZFvgQLyyAffRS46Sbg7bfNgTLOinfppeE5ICYiIiFPASjxP14gO2FPJfYZiJap2JmxcuyY/fKqVQO9RuLv0lP2+3IPPtGffwI9emR+diEGMJ9+2vw5d4sWATffbGbXqaRLJPTxM4HB6TfeAJKSgK5dgUaNgDJlgr1mEq1BKN74fkxOBmLVnUNERPxHRxnxPzbXdhpJe/55oHTpyHoVtm41Z7biKCJ7ILEs7fhx8+Ji0CD7n7nxRgUPIg3fB5zx0M7XX5tldJnB0sZ337VfxotZp98lIqGD+/GDD5qZkTNmmLMj3nIL0L59+PYBlMih4JOIiPiZAlDifww+/fgjcMUVqbOBxo83pyWPJOvWmanrnTsDH30EjBgB1KoFfPWVORvgffcBr7xizgJEzP5i+vubb2oq9kjjLcDEspv0SjI9cZZBZks4YY8pEQltf/xhluB6YiYjg1GBwCxcZmgy4BUtJfAiIiISElSCJ4HB8rIvvjD7HCUmmgEozgjF3kGRgtNL9+xpjnB7BhvuvdfMhKpc2Sy/atvWDEBwhjiWTUVbDxBe+PC9wIAKm2gzCy5HDkSUKlWcl+XNm7nyO8qfH4iPNwOZdtSvQyS08TP/tdecl3NQhplQ/pq8gTPOcpCETad5PObxh4Mijz2m/n0iEr342cjAPM9Do6UtiEgQKQNKAqdIEaB6daBuXfNkN5KCT+nNcsdAC0e+iX83Z57htqhQIbqCTwyecKS/aVOzGTenoufU3BMnmg3pIwmDav/7n/2y/v0z3++FM+d16mS/jNuQAd1gYEB5yxYzwMosLJ7IiUha3De4vzg5dcrsweMvGzeavaY+/thcj8OHgbFjgauuUgaliEQfDhBv2gSMHAm0aQN06GDO3L1/f7DXTCSiKQAl4itOmSmWI0e0rRmoaNUq9cUO+2MxK2zx4sjaPsWKAZMnA126AAkJ5n3MemJZJnvAZDbji1lTw4YBd9wBxMScv79hQ7N0JxgNyNl36okngJo1zRuDiq+/Ht4zOor4C7MYO3Z0Xs6+gVZ5tq+dPAm88IL9JBjr1wM//+yf3ysiEsqzdPMciv1Zf/vN7MvXrJnZKoNVDZGOA7///mv2EdUAogSQAlAivlKwoPeZ7LzNBhgteHDnhZAdNmxnFlkkYVbSuHHmSc7KleZBvl8/s+wwK5g19dZbZrYRM8n4nN9+C1SqhIDjCOFDD5knatZryvvY02zSJO/9qkSiFZuPM/vVLmOSs+GxzNZfFxrsRehk2jTv2VkS2vjasbSdvb0y219QJBoxA7R3b/vs+2efTdtOI9Jw4KFdu/OVKQzEcZblSKtGkJCkAJSIr/ACgj083LNTLEzrDUaGSihhaQmDJk4YpGEJSqTJk8cMELFMjqWnVjZUdgKd1aqZze75nP7qF5ORqeRnzbJfNny4ZuUTcerV9v335gUOS7AZpH78cXP0nd/7c3YzZmA5KVw48srioymzmGXdnPCEx4YHHjB7fbG8SETsHTgAzJ7tvHWcWmpEAmY7tWwJ/PTT+fuYuc42D8qGlQBQAEqib2ayVauAv/82Rwp93W/jssuAhQvND3Y2MmTggTPcjRrlv9KKcMELIPZ8cnLhhdHVDysSRs+csMzHKX2d9zODi/sFb6tXR0equ4iFPQCfeso8Vvz+uxmwrVjRv9uHPeQeecR5+cMP+y/7Svxn61bzfOPVV80yf2ajMouBvb7Y80tE7DFA6y1IG8lZ3MuWmRmTdjggwgFGET9SAEqiAwNNy5ebTaGZNVK/PnDxxcCnn/q2NxP79DAzhaVmrKvmqHb37ubJvwC33mrOvGSHGQHByuaRzEvvtWLmlyeW6DEYy35RLN/jjaP27IsVaeWXIt4w24hZsyyrzW5WZEYwM5efv+xv4olls8yckfDDDI7Nm+3LizjjosoqRZyzPps3d94611wTuVuOjdad8NrFqVWGiI8oACXRk6LOAw178Linm7Kh859/pv/zbJTNLI2MZkzxwMZSi2gvu/PEEjSWn7hvFwakxowxs8ckvLI4nN7f7HPDJuyeuP8x28PTSy8Bf/3l+3UUkfMY7OIMePPmmf2mGHji7KyDBytDNxzxvOSjj5yXz5ypfi4SOOw9xhnl2E6B2TWhXgLK83RmDrJawRPLWIM1s3AgeBtw4LlbIAZFJKop31pCr0SOkXeWAvDi1lc9Kb75xhwRtMNSCDZnLVIk7TIGqViuxwAJG/O1bQvcfrv/yyUiFQ9ql18OLFlivtanT5uvM29OmVESmnhyxgbonMKdvRQsbGjJRuk8ufO8WGL2kxNOg8wSTc4UKCL+YX3ecjZSCW88T/L2ecmeX+rrlXHMwuVAI7MFeT7oeQwT7z2FGMjmZAYsXeMA7IsvAq1bh/Z2ZEUEB7/GjgXmzjUzuzmzb9Om9tcEkYLnbWx5YZchyYlyNHgufqYAlIQGlsEtXgz07WtmSfCDn/+/777sfxAya+nHH52XM8DEkRvPgw3LhXhA5cW0hU20R48Gfv3V+4x34owndzw54U3C+3WsV8/MIPznH7PfCL+vXNnMtPDEE52dO52fjz0HVC4iIpIxvIDs1Qv4/HP75Y89prL2jOBAGFs0PPigmRFIV15pzmDLcnG7iWXkPM4Wd/PNqasJ2GP17ruB6dPNSoNQDuIyG4gBKA5S58gR2gEzX2aws3z3pptStyHha8ZG5Apci58pACWh4YcfzOwiCzMqBg40M2Xeftu+nCczza9r1wY++8x+OWce4kHHrmzPPfhkYebO008DEybY97kRiRY8MWdZJW/p4Wg8S/PY/NJpRI4z/ImISMYzOFguxPMRd+x32aaNtmJGbNhgZmYzEGXhoCXv4/GKk8mIM5bdObWyYEPrK64I/XI2ZuBHUxa+VY3AAX/OmMkKD36WsF9tJGd+SchQDygJvh07zFE8px4G3rImMopRfacZfoYOBUqUSHv/J584Px/7aDBDSnyLfQN4MGTwT9kwkXfCc//9QL58aZcxkNujh30gWERE7LFkiH31OJtiz55mby9Orf7++2aTe/GOLR9Y/u0efLKwHI8ZPL6eLTnSsHrBW2keKwwkczjQzXNhZpY7tQ/JLl4TcfCQg3+coILZfgo+SYAoACXBxw9XHqScMAsqu/ghO2uWmYXhnhnFWm+nXhhnzzo/H09IQr3BYjjh6MuHH5p190yH5oGwf38zOCmRg73TODOk+8wzHIXjfaEyynzsmBkA5c2XM2R6frbwM4+li+vXZ+z3MCuUwXj20hIRsTBDvFEjc9a7iROBFi3UwyWjGGRasMB5OcuU9Jnrnbd2CiwTVUPrjDt1Cli40MwW57kwW32whJGN3UUiiAJQEnzMevBWY1+0aPZ/B1NrmZLOdFOODrIpOT/QWebnNJ08RwSc3HKLRgp8hcG8L780s9SsQCRHJTk7SYcOZiN4iQzsK1CnjtmzhIEX3hgYZu8opwzFQOKIY5cuQJUqZkDsrruA1at9OwLOzMl33gEaNDBLg3mSec899lOpW41xOUkCy2kuvdTMcODnGE9URcIBg6fcj+bMMXvs+CKrWcQXGCCxy4C3sJ8hHyPOGja0n0mOOnc2y7okY/791xygY08y4kA3g6DNmpmDYiIRQgEoCT4GgJx6FTBwVLeub34PR2HY74mjg9ddZ44suGdEeeIFqF3zxEKFzJR3u1IiyTxmOTHbyQ77MLCZpUQWpnkzyMNbqKR8MwDEbKxPPzUzlHjix0A1gz5Mg/cFPidnDmTPFquEl/cxwMTZgjwz/pgd+tJLwI03mmUODNBy2vWLLwaWLvXNOon4u6yaAwm1agHXXgtcconZE2bNGm13X+NEDgz0MbNSQb6M4fGHMyE7YSN3lYan39CaxzXPnqhNmpgT+TgFpyS1o0fN/rJnzqTdMhyI5fmISIRQAEqCj9MIM9uFwSF3zIiYMSN4zQsZGHvlFfOClKVhNWqYDRU5gsusBfHdQZcnzk44Ra6IPzHDiX3d7LLt+P58/XXf9CTjReGTT9ovY0YmRz/dcb/gVNaeeILKflre9hsJLSyzZIAxmnoHsvcLL0B5ceqOAV0Goxickuzj5wFbFbCdAAN9zKxkxgSzvZUpmT4OPLB/ljtm5fOz98IL9Q5ND8/VuQ0Z+GR2M4+XHDBhD9dQbz6eVRwc4uCoL4/BPEb8/LPz8q+/Vm9UiRghUPMgAiBvXuC778wDGOvxmRnBrCjWlgdz9Impw+3bmyd2SUnm9KyqZ/ctprezNMup55bSt8XfGGT64gvn5Rx5ZOAou+9F9hLxdtHNi8iWLc9/7y3LiRkkLG3S/hHa+JrztWIghjNqMVtgyBBzUCM7s7uGy/TsbIZtZ+tWM+swUi9QAz0LGTO7WbruPrMb+8hwdjIGpMT7YOOwYcBDDwHz55vnnCyD4mcrB0glY0Eo9njkLdKD6vw8Z/uORYvMRv/MoGNA3VspZ0bw2oLvOZbd2+GxIxRaFYj4gDKgJPhWrjRHT9h4uk8fMxOAo3YsjwuVaVEZeOLBRcEn/5z8tW1rv4xljpwaVsSfuF97CwawTMMX+z6DrZ5lCu48G7GnF3xn4FZCF8srOaDCBtHMAuJoOYOKN91kNoxm4DPSg2925SQWb5OPSMZw+779durgk/syzvCmWcgydo7H7DEGodhnj5lPCj6JJ2Z28fOcA+ZsYM+S144dgUGDzMl0soPXGE4Z0vTggzrmS8RQAEqCi6OgV15pjtZZ37PhHmenmzzZ+0x0krkSI2ZecKQ01HpDMNA4alTaQBMv1HnRphFy8Te+13r3dl7O0ltf9Kri6CYvcJyCreyP4469npyCTI0b+2aCBvEfltyx35fdjKnPPWdOtR3J+NnuLeDKPoyS/Vk7f/nF+wVzpAc6xfd47s1zRX6GMftfzIxOBoHsJiVhEJjLs4tZi506pb6PM3azrDFUZgoW8QEFoCS4ONODU7op6+89m/JK5nHU/eWXzVm3KlcGLrsMmD49tHqRsP/X99+b2QJsusx+PMyMYxNLpRxLILBM5dFH097PGerYNNkXmAHFLE9OguCuYEFzhjDP6awZsBo/Pu3zcGSeJ7zBCEDxYpazF/LClvtopAdRsoMlkk6TKPAiZtUqRDSWp7CJs5369c2SEskeNnhmywJvx1Y1gZbMYGbi88+bZcIc6BgwwHmW1mjCjCfPPo3uWJKXXTzmjx5tznTLoBNnzGVVCLOslJEnEUTFpBJcvIDxdvLui8a/0YyNEocOBd566/x9PJHg9PJs/M7RnFApK+TFCm9snioSaCzBY2+e++4DZs0yR31vvhkoX963vXo4rfd775mjy/z8YwkqJzVgpp9nthN74915p5nyz5It7rvsR3f33cHptcERXs7Sw+CXNQrMzEVOFqGJGdJKL3ge6dO78+/r1Qs4fdp8/1rHc/ZL4TFJ/ct8s40Z5PvgA/vlDB74+8KVA4W8OOfnF4Pikd7bLJIxYM4sHAY9LMxQnzoV+O23yO/xlJ3Pc1/NjM19iDf1bpMIpgCUBFfdus7LeBIT6Sfo/sbshAkT7JexZp29SDxnH8xuOQAzrhg8ZOkFa9p5gS0SDlhmx5u3zyVf4Gcbb3XqpP9YXjwye5EX7LyA537FlPxAY0COI7LuwWzixBH/+x+wcKHKZT1ZFxF2Ay3MSomGoB2DTFaDZw6IMKjK40KhQsFes8jBfkUMCj/88PlyKQaDWObJTDN/9vj69Vege/fzGTIsI2bWBt/3nElOwsvcuamDTxYOmPB15SCNj7LSY2JikDucsvP4ec5JQji7pCduk4YNg7FWImFJASgJLl6AlSplXzvNkTtmC0jWseeTXf8Ra8pXBop8FYBi4IknvG++eb7xLHvYfPRR4Hp9sDyIJZ3sX8CyJgW/oi/gytJSvufZVJYZdf4Y7ed7jL+DQSR+RgXiQouZisHMVuTfzVJep5KNdesiKwDFz5LsTobBQAuz3TijFoPzFr5f2OOQx75owItMln+LfzBIzazIq64yA8I8/jEAxPcf37/+wtnAWrdOfY7BJvvMYubse+pZE36feVOmOC9n64YePbKfuchA9M6dyPX997jw1CnEMSOS5ee+6LPoTzyneOMN8/3t2TqEwTl/nG+IRCj1gJLgYg+IH39M3YCaMz9xJgj2XtEsT9mTXuq9twsrjnjNm2c2hB871qx954int+yIceNSz3rEacevucb71PO+wkb2bN7IYBdHhJlGztFZu9mBJLLwPffHH2YmDmcy4ucJL/o5pTaDCL7AMiI2+2UPtXr1zMwCazacaJhlin+jexDFk92oeTjiTEbsRXf77eYEGT17mjMd8fXPCmbT/f23GZznZ+Ejj5j9Pa6/PnRmeZXwx8xIBnxuuMEsHWZfKH8GnxhEGDzYfoCLy1iWK+GF59veqg64LLvZtxz05EBGzZqI6dULCf37I5bHU57zh0M/wRo1gCVLzN6MrCDg5CX8POdMzuGUzSUSZMqAktD4QP/hB/Pgw2ABswo4MqwP8+xjRgKzgPbuTbuM6cJOGULMaOAFEg+slr59zT4APOiyjMIzO4JBKqcsLAaH/JkdwdkTW7RIHejiRR/v+/13MxNLIhfLPxhwcg8EsVE2A1IcifdFLwW+j5lh4B6IYJCWF3wMfvmz1CVULnDZ48IpCFW9OsIe/7ZJk8xZDy3MKGEWEwdKLr88axd1zP5hRi8b0HOARQMrEgn7CrOdnPCcjsFbtVEIr894Bsg5E7UdZj9lN6ucWXPsI+iJJaScnIOBnFDHPlgsKe7WzSy983cGNAfReK7B83geP5jZqOqQ9PF6kgFPBk2ZtReM1gXiSK+GhAZ+oPIikRkFHMVT8Mk3GPRhQ2XPgBEDfAwm2TUL5cFu5MjUwSfiSGeHDvYzEzIzylt2hLeZQ3yBmS52WVYsReCFH0dkJTLxNWb6u10WEjOjOJtPdjOUmOHH0lK7LBg24x4xwjk7MFLwhJejvXbYqJ1Zh+GOZcQcibd7/dmcPjvTbPMihcc1BZ8kEjCw5O0imJnIoTLBiWQcByaZQeeJMxLfeGP2tiTPLZ3KuOmFF8yAQbjg+9vfwSe2FOAEDszsvvRSsx8kXwsOrPLcR9LiduE1B3vicWCQszmOGaNZ1UOMMqBEIhkj/mwKymDSzz+b037zIMaTDF402mEmGi/o7fBim9PFe15sMsDF0TOnC31/9oDiOn35pfNylk2xtwF7QknkYeCHJVNOFi82+53x/ZlVfF/zhM8Js6z4HvMM9EYSnmzzhI69LzixgXXyyz5+n34aGf2f+DnpdFLPE1peHEVL36ZIwuwBlohyMIZ9Ztq3N9+vmtY86zh4xRK8W29Nu4wX5fffr4yDcMTPN040wUwolplx0IWvJc8js5t1w+fivuiEx5asljpHKjY8798/bYUCZ8Ndvly99eww+53vV2tQnO8rZjWzLPizz0KzV9fJk4hPTESuKCrLVwBKJNIxRZhZZRltCMoLMG99c+zq9HnSwhMWjmDZ9fnyZ3YEg2xOwTRiyngoZR0wGMKblRYcSusWriPxLHFivy87fP9lN6OSP88SM05DbYe/PzsBrnDB/fzFF81SMo7MWjOa8RYJ0kvRD7VZvfg5YpWuM8DOC0QfzVAVMZgZy4ATA9EWBk5eeQXo3Dm4QahwPxaw7Jml+cwusHpBsUTo3XfVgDyc8b3IG5tt83X1VRklS7jZ2oGDgnYYVNHsmKkzcvlZ5TTw9u23ZlmkpN4uQ4faV2Rwpl7OSBtKAahdu8wBzNdfR47ERFS7917Esneft2uaCBFSJXhvvfUW7r333lT3rV69Gh06dED9+vXRqlUrvMdeDG6Sk5Px6quvolmzZsZj7r//fmxjdDjAzyERiBkNGzeaNet2ZWeRiicJbArphH11PPEE5bHHgC5dUl+k1awJfP+9/7MjeCHhpF+/0Mha4MgeMyzYXJ8NYplKPXx4YBq0RzLrvedk4MDsZ7/xourRR50DEIMGRU82BT8fmNHITEprpq1Iwb/HKYDDEohQmqVpyxaA50vVqpmNzpmJ9uqraWdnimYswWXprHvwycL92eM8LyjHAu5LLBMJx2MBB3d4gczsso8/NjOReb7Url1kZ4NGCx73fNnDi4HWO+6w/xzlIA+DmZGcAcJrCvZxSkzM+OeEt/YVbIYeKMwC5/XQX3+ZGUYMnIfqJCLMdHXC1iOhFHzq3h1o0wb4+mtg7lwkdOqEWPYV3b4dkS5kAlBTp07Fyx61wQcPHkSXLl1Qvnx5fPbZZ+jRowdGjRpl/N8yfvx4TJs2Dc8++yymT59uBJO6deuG0+fSOAP1HBJh2HCYQQ1m7jCIwpmvvvjC9x+6zDbiSTAPMvwaCjXdPKlkzbndxXbjxs7ZTAzycB/m38JMEaYHs3FvIJoTc7SATSw9MxjY0JKj36GQucCZtJgW/NVX5okFMxc4UsMShuz0lokGPGnjAdlplhxexLEszL3nCN8Lzz7ruwb0DBpOm5Y604kn6Jz5kRf/Ev74GWY3mQIvwliWnN3px32Fnxc8SeWJtpV5wmMTL+A++ig0jiOhkkHA2Vm9TSsfDAzSWMcCXozy843HAh6rvJUohSIG93lOcNtt5nuSmdaRHESQ7DfwZrZy69Yp52UuTu7Ac0YeY0MhaM1Jc3gcuPtuM1OSgRf32Z0zi6Xb7FPKmVU5kQl7KTJoy96C3vD8ggMMTtgzNxD4mcSBXE4YxYFTntOzJ2IoBkmsXotO/DkzaGb9/bdtsCyGgxMffmi2F4lkriDbtWuXq3v37q769eu7Wrdu7erQoUPKsjfffNN1xRVXuJKSklLuGz16tOuaa64x/p+YmOhq0KCBa+rUqSnLDx8+7Kpbt67ryy+/DNhzZMXy5cuNWzg7fvy4a+nSpcbXiLJ9u8tVuTJP69PeZs/23e/ZvdvlevFFl6tIEfO5Cxd2uUaONO8PtmPHXK6ff3a5GjY01y1fPperXz9z24Sqo0ddrnXrXK633+YO6nL9+afLtXdvaOwPBw+6XFdfbf+e4u3HHwO2nmFl/36X66uvXK569VyunDldrosucrk++8zl2rcv7WO53TdscLm++MJ8DN8LR474dn0SE12uzZtdrvnzXa4ffnC5Nm50uU6c8O3viBBhe3w4dMjlWrTI5Wrf3vz8e/RRl2vtWpfr9GlXyPjtN+fPkqJFXa6tW4O9hqGB2yE21nlbdesW8P3hNI9J117rvE7z5gVsnUSC5tAh15n1613HVqxwnQ6Fc15KTjY/W3PnTr1P5s3rci1enLXnPHzY5Ro+PO1+zvOZ339P/+c//TTtz1ar5nLxWnnHDldArgW6d7f/rGrVyv5cLJh4nO7f3/nzdckSV0g4dcrluukm5/WsWpUBEle4yUxsI+gZUP/88w8SEhIwa9Ys1PMo+1m6dCkaN26MeLeU+CZNmmDz5s3Yt28f1qxZg+PHj6MpO9yfU6BAAdSqVQtLzqUmBuI5xEc4EsiRAm/9hwKBmTsc8bDD3idOWRiZrVNmvyQ2F7Rm/WDqKGdg4oxa3maUCwSmz19xBfDdd2Y2GJuXs0QglBsNW6VBnBqXrxPLGuxm+QtW6vXcuWnv58gfS0FCcSQp2JglxgwFjqpzpIifD//8Y2YJMNuNfW/cMTOJvZhuusksAeF7wdejXRyRrFDB7H1y5ZWasTMSMaOD5YUss+eECy+9ZI5Ch9KMXjxGOWFvrmAfP0IF93/2lXHCz4kAi+Wxn+8rJ8qsDyxmtjADjedf/sJ9kscuZryxHDTcSi39oWBBJJYujTWJiUjiuVsoYKsNZqR7nltwn2WGX1ZacTALkyX6nng+w3PV9K4nWrY0rxWYVcgMXZa69uplnh+xHyOzZfw5yzOzbSdNsl/2ww/m3xdKeJzu2dO+8oLn2hnthetvycneG+4zO87Kbo5QQe9WyX5KvNnZtWsXqnmkH5Y4129i586dxnIq7dFQjI+xlgXiOYpl8SLX5XLhRHanBw+ik+c+pK2vWRV75gxybNuGmNdfR8zSpXBVqwZX795IqlgRZ7PbPDiz6xIbi5w//ADHgq1//sHZY8eQeO6AmXDkCOKYnsqfyZMHrlatkFSsWLrrnWvnTsSyX4edceOQ3KMHToVCsIcX9VbJEU/UspOGbCPHgQOI5fZjAKZ8eSSXKoXThQsj0vaHnMnJiON25IkMMYjB0i2ejP74I1zr1sFVqhTOXnQRkjRbn7nNdu1CnOfsL5ann0bybbfhVCg1kxS/HB+Ciif9PBFMr1QiwHKVK+fcPyFnTpzNkQOJYXxukVmxMTGI40VYTAzOnOvFFnf8uHEcj3vhBcQyoOhx7HLVro3k2rUDtp2s/eAsjwUc4HEIErqKFEHiqVNGKwjxH743cu7ciZhJkxDDMpgCBZDcpw+SL7sMp33YCDvn/v2I7d4dMWwYbSlbFsnffIPECy80rgOiVagdI3Lt2oVYpyDT1q1I3r0bpzLx3oiJiUHOP/6AkYNpZ/lyJO/fj1PeAnC5cyOue3ck3HYbYk6dQgybuHNQ2PLyy3C9+ipO33UXzvphIpRchw4Z12hOkrdvxymWVYaSokWRc84cxCxahNipU+EqXBiu7t1xtlIlJPHaLASOjTF8b3TpglgO8ttw3XknTufLh7MhsK6Zwc8z/m1hEYDy5tSpU8jBEWc3Oc81xEtMTEz50LJ7zOFzEeFAPEdWJSUlGc3Nwx0zwbKKU05euGMHYtmE7dyHXMySJYiZOhWxkydj2yWX4HAAM6Jy586NC8uVg+NYd6FCOJ6YiHWrV6NKvnzIOXQoYtlz4xzueHGjRmFv69bY7eWgWvvkSeR0+lA/exZndu3C6hBq8sfAnC9PiJlNWD0hAfEcbXLbB2Lr1EHSRx9hbWIizoZpHxO7/aFw3ryo0LUr4hh05EUtpzlmw/Zz/T74cR3zzTdwdeuGY336YFuYHXT8ofapU8ZFpK3ERJz57z+sPnQo0KslATw+iL36zPRjoN4ma8N1zz04GBuLLRFwbpGR40jVXLkQ99VXSGBz2fz5jeMveyzFMksyORlnGMT+9VfEPPEEYjileZ48ONu1KxJ79sS/+/fjrC8ymjNhe2IiKnTrhjiPnqeW07fcglWrVkV1YCIQ5zO1EhIQ26LF+Qx03n/bbXDdeitODBuGLT44BhfLmxflxoxJHXyi//5D7DXX4MyPP+JfHetD5hhR58QJpL7SSy3p+PFMXbOxuqcGB9i9PIbXkBl5zmL58qHc888jxj34dE5Mr15wtWiB1X4YKKmVIwdyM6Dg8HmUVKhQyF7H5qxVC/lGj8ZZlwtHjh1DMjMPQyj78MK6dZH/4osRs2xZ6gWlS+NUp05YxT5hYcgzXhKWASgGJ6xG4BYr4JMnTx5jOfEx1v+txzCQEKjnyCp+OFVlmUiYYvCOB46KFSumbKvMyrFvH+K7drXNrEl4+GFUWrECiQFOmYy77jqzmavNOiU/+ihylC+PWrGxyDV9OmLcgk8GlwvxffuiTMuWKMLm5Q4SOIuEF/EFCqCmU7PvAGEwLWHfPsQyxZalpuXK4WzRokjywew2CYcOIYGlVZ4HrhUrkOv++3HRp58iKcxmFUt3f+jTB665cxHD5rNTptg2m42bOBHFundHPs64FeUSvM3+wn0kTx7U9LKPZefihLwFXOM5EnnyJJJ5MevLWYIiiC+OD2L/uRzD0gd+hvDYyfIhS8uWiLnxRhR2uZDHD/tGqMm5dy/iOCurdTx97z3Esvzi999THhN/881wtWwJ1+TJ5j4dG4sznIUrLg5e2vv6bX8oyEk+HnsMru+/RwzLstwk8wKzfHnUyOIxlpkWCXv3Iub0abhy5kRS8eJQHlVacYmJyMHp692CTynLPv0URfr2RR7OLJlNzLCK5X5qZ/du5N25EzWbNEG0CrVjRDzPyXg8t0ssyJMH8WXKoGYmZ1SO59/Fcwq784l69RBfogRqZiCrKufu3Yj1MmlCjnnzUOvBB30euI4/fhyuNm0Qw1naPNWqhbiyZVEzDKoWQjVXPvnzzxE7cyZiOFsrB97vuAMuHtf5XgvDQYj16Vzbhk0AqlSpUtjjMTplfV+yZEmcORcg4H2coc79MdXP1X8G4jmycyKZnQBWqOCBI8t/BzMYnKZCPnECcdu3Iw9HewOpXDlzZgLOoOZ+ILruOiOVOhdPDvn6szeIg9gJE5CHs+/Exdk/gO8bXiDYjRxUq4bYkiWD/97gyTHTfTnd9zmxt9+OBI7cZrf0iT22/vzTdlHMr78i4eBBJGTyQB/y+wPL7tj7g8E8loQ4YEZdHi/vrajBMmemdtuNjpYsidhSpXy7j7Dket06czpcllXfeKNxEpCqjxSzEjmD1XPPmbM98iLlqafMHkGadtz3xwexx/fexInnZ+xjjxnuK/zMvusuxP39d+Rvc17QcQDIOuHl8ZTbwS34ZGHmEzNM8dBDxvcOR+WA7Q9xRYsCs2ebx8BPPjFnnu3YEbHlyyNHoUJeMyYccaCI7wlmgPG8qnhxxLH3zF13mc8v5/F98umnjluEF/p5fBEY4vmjlz4vsVu2II+3HmVRImSOETzeDxsGPPFE2mUjRhjBljyZHXDieezzz6d9TiY8TJyIhDJlnCsuPHnJcIo9csQ/QTy+Lm+8YX6OcPZCC2fEmzUL8WXLhnYgIdSVLw888ghw5504c/o0Nh0/jrKlSyNPCARksyKj5XcU0u+bRo0aYfr06UYpTty5C/lFixahUqVKKFq0KPLnz498+fJh8eLFKcGjI0eOGOnLHTp0CNhzSDakF+ENRh8EHhg4VSqDQ0yNtAIG7MlkncjxQOA+8uyJPY0Y3PQWgGKzUZ58nOs1lnLR/fnn5kErmDgNLbeBZ4NBNkDkduABNTuZH2zKnZ3l4Yrbju9pb+WFIdZvJqgng3y/sdm3eyke90/uO1zuK+z7wCmS3U+wHn/cPPHiVMzMxuOFxMyZQKdO5x/DFGleyHCfZUaf0/4u4kuXXWZOtMBzFPYP4fuTgyI85jBjOJSmmvYXHpcnTz7//TXXmPuhkwkTzEbCoTIxBY8FvPFzI7sYGB861CzttvD8hE13+XXgQPNzU847l+lqy1ef49w32dPRqUm0Mp1DCy/62Ric1QeDB5sDUkxE4AQ8nDAmK+e8/Cy+/37z52fMMCf34X18b/B8n5/ZbhNcOeJnPIOiixbZL2flhj8H5fnZymsVXtvw+oSD0MG+TokUMTHGe+H0iRM4sns3QqD7b0AEfRY8b9q3b49jx45h4MCBRlrXjBkzMHnyZHTv3j2lzpBBolGjRmHevHnGjHa9e/c2Mpau4clIgJ5DsoEng04XkjxhYtZIMLCGlSfynHGLrzNnVHMfReRJBfsHOOFMXOkdrDhiy9Fa9gdgxgszL5YuDf5JCS9kOAOk0+wWTBV1D5plhbfALU8MWSLhywsV/i2h0lOK6cp8Xzm5885Ark1ou/hic8YvZt3dcYe5n6xcaQaEvV1AZAZPAHnh5h58sjBjwpqhkOn5Dz9sH0TnSWtWZsgRyQpmO1kz97KZNd97Vsn4mDHZz1AN15N4bwNWXBaGJQ0ZPmaz55UdfmbalHtHJGYcMWOWAwPMrHc65vP8w9tx1lfHYJ7bcmZjO7VrB+/8Vpzx3JPVDyxzZnYlZy9mNnR2zkl5ztewIXDttcCDDwJXX21+fvO6goNaGRlw5XuWPUTtglV8Xn83Auf1T506ZqCrQQMFnySyA1DMLpo4cSI2bdqEtm3bYty4cejfv7/xf0uvXr1w6623YtCgQbiLqedxcZg0aZLRXymQzyHZOEC/8479xeQrr4TuiTRHL55+2n5qbmY38YCQ0ZGF1q2Bfv0ANmLn98G2das58uOEzdWzO2sJR36cgjD33mtuw+ziRRlPytkjhMFCpla7lRMG9b3DdbGr++dnSqBLTkMZR6K5PTiSz/4H3E+qVMnYiGFGMTj52mvOy60+b3w/OTVFZ5CTN8kcZpWxkXYAJ5qICPx8ZHYg+x1ZqfrsJ/nll2bGYLQMXrFXhmXePODmm50ff999oZP95GsMMDkF3xiUYclZpOPnM8ucOIDH8iAOXjCD1e5zmWVFzHCxO89ghquv+o7yOMX3Hc8V3UvMeM731Ve6iA9lPEfl+fi5Gc+9Bn/ZUoLnzd6OY3wMW1q4t3PhsY+Z1+n0u0zBkv8//jCfh+8nrh8HHN59N/31FAkxMS5NtREUK1asML7WYUQ5TJ04ccKY/YCNgLNVv81gBkcaXnjBLHnjifSAAWaGUChPSc8TO2ZnMCuCmUsMonGkhD0Ywri5PHr3Zt0pcM899sv5mvDvduuZluUTRp4EvveeOXrPYB4vKIYMyX7g0a6kivi8v/3ml9GiTO0PHInnbCY8QWa/MW5TNr5noExpzYHBE0Huwyx5ZMq90wXcAw+YGVKLF5sp8E742cWRQWKGIE8uGUDjyGmkXvhmdX9g4Ikn5OyTx+3KHlosKePr4FQ+xtmiuF8z0MALbgZa+HOhOkgRCHz/8r3Gz0/2IIu2zw5mJzKbgH3Z6MMPzfJwHp/csZycJXgMIHN/5/7I943dAFKony/ZYS8pBlycMGv0oosQsdhMvHNnMwDrieeVPKexe62ZLcUBBpZG8RjMxzFTxdcX89xP+ZnFUjwGjPn8GWg8Hen8uk/4G7OWWMHAwTH23mPFBt+DvHbxHEjmZ85jjwHjx9s/1y23AO+/bw5OZgTfR/z9PL/gZ34m+u5I6DoRzvtDFmIbId0DSqIED8h8s/IEkeUE3PEy+kEcTCyxY6CGJXRs+smDAdNkw2z2NtvgCEdyGESzm9GA01r7ov8On4MpxexPwdedrzkPpr744OUokV1JFU8CeRLAmv4AXnykwRMGZvaMGGFm9XBdfFl2KM6YDTB/vhn85MjjyJFm4O/HH+0fb2VV8IKV+zb7rXji+5Yp6txvWL7Kng/WFLqc9ZDNgfkZ56uywXDHoBODAla/M26zqVPNYDT79Hj2q2HwiZ+zLMO0ymqeeca8WGQJwwUXICrxGBTNZTx83b//HmCDcWZSsycUZx1buNDMfmVQmb3cGKhk1omV2ctgw+jRZhZuJAQCmMnD94Fdhm+9epGfHcHjul3wiThhBD837PYTDkTx+MtBBmYr+at3GvfT7Ax68ZjD80tNdBE6eMxidr2Fx362p+Cxje003AdGGPh2mHQnJUDMx2T0uoefX6E8OC+SATobltDBwANPlMIh+OSOo6kM1jBtO9yDT8TMJ47ijBtnNk608KKQWTpduviuBIonVAzEMLWYX30RfGJ2BS/4nUyb5r2BfCAx8MSLBwWfAoPZlnxv8MJz1Sozc8QaIbdrPMtyDl7AEU8oeYHrOdrIn2PghA2FeYHLiQWs4BMxO7JZM/vZ/AKNGUQMunFdsltGm52LxY4d7Zvts9+eXX85rrd78Mk90MzXz27abImeIBQDCAxQMpuFfVXYu42BKfZvYa8VBjvdy8qZQcC+bTYz5oUlDuYwAOPZW5H3c5tE+ix43qb+ZqaIUxNw6/ObPXpCsXE/M/wYWGWjeg6EfPFF9PTzCvXsaWY+2WGgybOkjue17PnlhCWjYZrxkikcaOYER/xc5gAxyxat3oUSdRSAEolUHDXjhSZv3k7APDEQxJMdzv7FE3ee9HCqaN540A31khcGCLxlN/GEUynL0YnBDc4W5Y7BSGbFsQyDs4tZWZksreVFLQNLxPcUJ6b46y8zCNu4sdlQlOU+DDAxS4ej7XYnVLwIYuAzGLN6EjM0OYsNA8qc1Yc3Tv3LRr2Bxp4sTsE4BsVYmuqJZXdODYUnTXKeMIF/N4OBzJBh6S3/Xn+9Bvy85YWJ+lkFB4MI7lkBDMZwcIivvVOT36eeipzebbzAZRkwS7oZlOVnF2fM4r4e6dILsIXjlOZWeSnbEvz8s/kZyFIt9pTK7iQwkv1ACrOWnLCBueekRr16OWdAswog0AFQXhMwUMZsUf4t7r2p/IGfs5wQgZ9HfF9zNkAOPHNb6ZgZlRSAEok0LKHjRRen6GYwiTf2Q2LGR0ZmguOJOy+kOb3833+bTQ55kc6DRSg0SU8PAwUMDDjhCV2klyREI2bUMI3d20xXDFTYZct89535nmHZDgMg3H9YouPZ54wZe9wP2LuLP8OJEpglxexABiCcpkgmnmg5NTH3t59+Atq1Ox/4YZYgAze8oAn0xUx6M5HZBYi8jfozaGUX9ONrzcw2ji6zaSuDb+yTw9IJX86Iyf4zLN+89VagZUuzMfjq1eY2luB/Jvzyi/Ny9m6JlIsfDqrw84p9KFkmz5LDcDhe+wL/bqeJSzhoEG4ZYPx8+uCD873N3PG4462cS/yPFQDeMpbsWlTwPJyDQO4lv6z2YPZ0oGe+ZkYxs0Z5bOSgG9sDcOIkZif5C9secPId92Mvg2A8NjMTSqKOAlAikYYXmSw7YEo+L/Z4mzPHbKBsl11ghydsbPLLmcf4PCxpyG7T8UDiAZUn4p7Y5JjZK3blVhKe2OybQQWW1DBzj0EhpwwbjkQ6YZCDF6zs1cELN88+RJ49PZhx4f58vM9bbzQ+Lx8TaPy72ODbDjMm/HnS6RTgtrLKPHF72s0C6W1mN2Z+eJZt8ySXMwOxZNJzFJZZnb464WVmDYORLLtkyRcDTwzssQyM5YESXOyJ5G1GM77XgtkLUHyDnycMzHiWsrP3FyeQCLc+Xxzw89ZGgJ85kRI4DUcMdvJ8ww7PLd17Q1kYsOJM1xzUZekvB6uYecTS8kC27mCmNvsnchZV98EgZnaz1NMfJZ7MruJMkBaeO7Gdx2efmRNHhMLs1BJwCkCJZAYj9jw5sOtfEgp44cXZNHhRbnexxFKjzIzM8yI8FHsjZOQEgU3tOdUxR0CbNzcvDJnGHi2jwtGAWUc8UWc5HEcS+fpaszi692Fyf184BYnYpDY7I+W8+GEqvROWvHkLgPmzXMBb4Jkp+IHE7c/gkF0Q+OWX7Wdy44UkG47bYcDRM6ORJ9FM97fDLDSW4/kCs6w4a6cnfsbyAsWpNFAC89nAwCs/+532O16IOWXOSHhlf7FXHzODWHLJ/pULFpiZiX6Y8dYr7vNcD5578KI+K6VNDAx4KxVmxmd6maTiPxxI4uQGnGDEHY9pDOw4nWMwc4oDuTw/ufRS85wj0OcEzHjm8dcOM+5Y+ulrPB5ag4JVqphBJwbimDXMSUc4EQCPyQqqRhUFoEQygicRzARiVg1H49mkm5kDwerp4u2kmzNwOOEoIfui+AO3BS/8eADjRW+w8UKW6b3s7cPXjr0TFHyKLHy/sdzEEzNdePHpOWMdTwxZWurZE4Sldexxlt3ZHZll+MQTqXuM8aSTo/A88QoGZnh4y+ZyykbyF24b9n/gRRonPLBK5NiUlH3n7Pq1sO8cZ7tjeZu1nJlPLGtk8NHuhJelcU7sSluyghlkTscAljx7WwfxL+77DEAwEMmZ8dwbdHOf5OcGSyYlskoQr7sO6NHD7Mvni9l6M4OBfva3YakvzxUbNDDXJ7MZHhwI4WehE86ymp2+VvzM4nkaG/MzGzRUB1RDffIDnleyPxdLy1i+z0Evvt6h3HOM5+beXm9/lMMx+4tVCcSWHvfeazYit4Ko7KPJmYg9m7dLRPPRVFYiET5tO5uVcjYS994RzLBhGm3NmggZHE3xlsXBk3B/jLiwppw9C157zTzxZ/8Jptyy5M1XM+ZllaYujly8wHTCJrzcd93T23mRwtHHFSvMk0fOUMegEQMgdiWmPFHne5uBBAZy2NTY2/7F5fysYLCTJVjc11iOxWBoMN6HHCnn/sg0f16E243k8u8PNJ6g84SUJ+3MzOT36WVa8oR/1Chz5Jl/F8vunHq58fmcpqUnjj77glNTWUskTHbAixW+RgxihtNMTcxG4PGOnxHcB5gpx7+Bo+xsVs5M5nDrDSShi+8nZnPw2OIZpOYFN/v/eM5S6ITnTAwyMavXc6IIfnZl5/OL68ksHWb/8f88Pj72mNlmwS77NFzwOM2BJ37mcjsHIvjI7cUbB1TCBY+zPC9xqoTgcdPXmB0+YoSZ6cRgk90s1Dymc4IYvufDsepCMk0BKJH08ATAPfhk4UktR1EZeHGffSeYeJHL2mqnLChmZ/DCjSN1LFdiII0XoLxl9cDDLBRe4Lo3e+UJDi/wWevubfpZkezwlrLtVMbAk3tmI/Gk2xvu38wYZOmcVUbBEW2eIF10kXNwgZ8FvLFsLNj++88cWeQ6c19nwM3Ci3Huo4HOgPIMFGVmtJgBs4z0omPGFE94mWHliRcmLNfxBb4fGOiwa2rO35HRC85QDTzxOMGybWan8fjA4B8z1kLleOcNLwxZjsv9nMFgTsrB14r7PyciYAmIiC9L75z6vjFLhhfdmfk84P7Gn2NLBc6gyqABZ2blYElWgyt837/5ZuqyYR7nmMHDYD2DtOGwb3ueA/Dzib09rWAdyy7Z/4/ntcHouxjqn4sMbr7+etplPK/hQI8/8FjJEvuRI50fw/c7348KQEUFleCJpIcXaU4Y6PFXSVtWMbPArukwe5KwOTkvQhkU4kGIB4Q77zRr2VkykhUsZ7GbaYizUzEbxLMMKpywlxbTglkuxBp2uxnUJHjY/NkJR4mz03yWI9cMrLr38OD7gD1lwqVpJi+y+fnEco7OnYGPPjL7VHG/Z5CYQbJg9KUKBM7qwwsq9ww4XpAwI8ZXpbjsH8SSAk8MqrE3mT8zbPhZxHKJjRv902uK73UG0bgNecxgw1huPw64BGs2x8xggJizv7IkxsJAIbfbq6/6Z6RfohezBLOz3A7fozyH4iymnOSAM5dlZ8CAg4XPP2+/jIMUQehZFxsbi3juk9bss8xkygy2wuBnvXumGM/VWArJz0ZJe2ziOQDPB9wzePnZzmsdf2XBMbDJ3+FtAInHU00KETWUASWSnTKLUCyxYBnQoEFmGRADZDzp5qgZT1wYFLrpJnMmDHdMXb7rLrMuO7MXTeyp44QNQdm4PZCzfPgKT4gYtGOfGWL5CTPemKruVPojgcX3NE+kPGc7Y1CFjWizmoHC0j1mCzoFJTmrJC8GQhn3e2ZAWX0f2D+JI4uc+Yv7JE/SOWtbJOHfzM84nmTztee+ypkRGYRjxhc/G32ZlcRs0o4dzWAnywMZEGKAku8Nb7OvZRdfVwa+2FuMwSBmJY0da06p7YvPWl6IMqPALsOQGUUM6tjNVhhqmAnHzwYGjJnNyG3DdedFVjgekyR0ec7A53kOyZm/soJZe74632ApOT8fnTKG2RcqwJm7NfLkQQJ7drEHI8uwGHTjAAl7raaXjcW/hT3e3DNQOSjVqZN5vsbPMQY81IYh7ecig/AMRPE9YZWz8/joT8w+7d7dnMXRzpNP6tw6iigAJZIeTk3KgI4dXtx4O/EIFp7s8MaUWneLF9vXXxNrs5ntkdkAlLcTeZ4EhGKQLiMjhbxQcZ9JjUE79rXiyQxLO+xm8ZLAYjDhhRfMEdAXXzTf2wwA8MSqatWsPy9PbL2V6HBEOlQDUDyJZ3Bp6tS0M8dxFN76u1jGESmp7gyUMMjAgAwzd5juzxNdXsxYN39hlh0DUMwg4HrwZN6fo7i8qGLWqnvWKbNQ+XnFmbc42JBdvChxyojl+4t9bsIhAEW8sOKNvd9E/Pk+a9vW7PXkiftrKAxapVfuHOCgbM79+xF3yy2pJ4Xg5zi3IwdP27Tx/gQcWHEvKx892gzIswKAg0g8V3vwQbMtBYMu0YDn8Mwo4/kp/2an828e+4Nx/OfADGfh4+AXM6Kshvg85+aM1RI1VIInkh6WazB7wBMDT6xnDqeLuPRmp/NWYsYsKfY4YDCOzQJ5IcsLFZ5cOenaNTROvDKLqdvuwSd3w4efzyyR4OP7i+9BZiWx5xgbW9eqlbq0jCOkTO3P6AyN1nTJTjwDu6GEAZi6dc1gKcsTnJqMM2AX6Fmi/IEnsAzGsKyYWUAMDvIrv+f9gZqplBd3DPr7u4SAwUW7kmcrO4kn8tmV3hTvWd2m/DkG8hnEEvEHlvzzc2/lSjMj0a4/mz9w32fWLRuOW4NTPI7wHIhZOqGQccfBRbtZQ4m9fwIcpInhOZbTjKQMIu3alf5nrhUI53Znpiv7WzH4ROz/9NtvZmCKmct2fe74fomEzyP+7czyvOoq89yFrzMzjXxdVsnrgPXrzXPkrLQf4X7AViA8T2nXDrj1VnM9GXwKp2spdzymcXuwGoQDUQyu2b3fJBUFoETSw0ATD2qswecoM0dSOYMIR144y1s4YSaAU0khP/ydylN4EHv0UbNXFAMwbFrJ2b0YiGLarntTS0v16uZJRDj2mGHDZic86HqWMIYanrjxIpWvE7NCeMLglHofKfg+5Am050xdDBYyS4r7LQNHLKvkSa+3k06W6AwebL+MFxWc7SgUcT9lSZj1WjMTjD1EWJJgNWNlQP3DD83R5XDMTvTEwCJ7XHm+nvyeTcgz21Mk1PGCygn384wEWDNyzHMqxeHFNQOcmcEgAIMC7D/DjAceS5hFFQ69pCR8MHuGgQiel7EXJjMhOVuxFZDwNwb02bSfgRVeYPM4wx5qoRLo5zGSPdw8e+AxeMbsyUBPSLFggfMybsP0zrOYbTpggPl/nmsy0GQFOfi6c1ZmDsDw84yBeaukmMdHBgn4MzfeaE6uwO+9TWoSyvj5yteP1ycMvFrnqb16mefmWe1Ty2Mog7hsDs5G7wsXmtnm3L84kQt77DkFEO3wXIyVFpwYhddT7q81e3ZltQ9tMPF4O2OGeb3D80Kea3EAlOWE7v1DJQ2V4Eno4ocmo+38EGQteDBTaDly9L//mQczTl/K9QnHEiw2+WM2F+u/PTGw5HSixGAGZ2LxxBE/pkvzgoLliMw+4WvGjBSWpfhrRg1/89a/hb1keAsF1lS67kE+ZvlwVInllha+V6dPN4MO4TSVenbxpJOjbMyMsrARN5ttMoBcs6bzz7ZubZZash+FlRHCE172qsjITGzBwAst9xNCXuDzvcAbR+ZYlsjgWqhcEPkCT/Kcyoq5jLdw/Rxy+gx3wuwrX2Rg8T3CmV/Zh4VZAu4YRPK2DnZ40dGs2fmAEy8+OOrNMlEeP0Ll81TCl1U2797XjhnanDmO7y/2CgxEwJ3HCN5CFYMHDCTwYp9Z7Lxw5mQDvpqYIRNivB1HM1rKzP53s2aZ550MWPFn+LnCAaS//jr/OA6WMkOFgQ4Gvthaw8qO4/c8l2UGET/zvPV9DdX3vtUWgkEnXqvwuMdAHDO8uB9kdkIWnlsy6MTPZx4DOAkF+8e6Hw/4OX7FFea5FGce9IbnpVxHDgTaZWUxO5YDZjw/y87kMf7C9xf7wvI8igFMzqrK9x7PuRj09sQAKI95fJzYCrO9TKIGZx5jdJ0HS14k8kNu9mzfjO5mBw+KHE0Jx+CTleXED3mO0lkXobwo5YxYzCKwO+AzlZQNdp2w3IUneBdfbF5U8ADSvn14X/TxwOLUC4uzB/prppDMnHCwRwJHXLiffPutmfXEEko2J3YPPhFPtDijW7SVDjLLwj34ZOGJKktJvc1MxNefJ638LGLAis3oObrIFPdQvWC2K43iCSMznvj6830TScEnSq/EJlAlOIHC8gWnrFJmfPmq5JkXCrxA5ecdR3R5cT9/vplBmJkLbF4IcVTYM9uJQV02Ok+vzEYkI9atc55Ugec80Xbs84aZTgzE9OtnZgAxEBSEbFhXy5bOQSb2bsrIeRaDFcx0swIjHGxhsMQ9+EQcyOYyvg/4Oel5XAjnjFkGmBgI4aAB1599APnZyvNwnucw4JNeWbUnzirIQThOWMIJiiZNSjsYQfy9zADy9vzcthyc5nvN89zUHQOjwb7Gs8MBLm5HljUyUMltwUAlM+w4262TESOUBeWFMqDEN1FMK6LNi7bsjh4wjZopmu4npqyv5QkwI/I8AZes4wUKD+7MWOIBhaU53g70fIy3emYegDhaYmXWhNvokR2OBs6bZ2YMceTGwm3G1NpgBiCskiNeDFq++MI8oWQAkCV3TsEJ9kkKt7LR7GAw1AlT1pll6a3vADMdectOQ/NAYnCc7133KaktDJozsBqJn2cMiNiduPK1DccedN4wgMhGx/wsci87ZHkpS8N9leHIIBcHf5gty0AtP/Oy0qODxwcGgu0wYM6MvfRGz0XSw5I3Jwy8h3rZfKDxvI7nEtw/WVbOc/cAVxmcLlECcZ9/jgQGStz7j/LintkyGc3mZPCMwXIOVPNzkdludvh5yb+ZARs7vI5hsCHcBk95Ds/rI24Dz3MeBtwYkOL+kZnJOJhVZmXYs5+it0FoDoBy0g+n2QY5CMFjCLe/t2sNLuN70Rf4d/O6kaXfPOdlVUNWB9+YLWh3Xs3zLAbovH3uWNtQ0lAASrIsJiYGNfPlQw5+MLGunIEHjo6y/Co7H+CsN7YbFWWEnbXa/GAMxZnnwgkP2Bn9MOYIEwMxTk252dMjFBps+hp7SCxaZB7IeJLGiySWngT7vcdMHPfgk3s6NA+G3k60w3F0Lzu8TePMk6VICJa64z7NETmejHpmQz33XOZLp8IBL5o4Kml30cH7I232I15scKpxBm5+/NEMkHPAhsFFf/yt2S05Ti8DzdvEFyIZ5e3ims2qrR54Yg68MEuIPZBYokVs5s0yfWayByjDPzk+HlsrVEDVf/5BLAMkDACxzQUHUTIzcMDepTxHY5YKP0+89XJKLyAQjhmz/Ps5Ky/7P9rhADIzwjITgPLsg8pzB6csQl7veev1ynMRDpAyOMjBEw6U2mVMPfGEb6oLmLXOpuZMZrBwEJElluxdlRl8P9m1LLECU2zxwGtSO2xDEq6N1QNAASjJshy7dyOODencd3IGiDjFJsvlshqEYjTdyZIlZip/sIMA0YQHlh49zLRT62TFwlEzloBF2oW8e6p6oBtzesMTCV5Ue+u1wn4OHAmzw94AkYb1+Dxx5YklM2HcA6uszWeJqB2esIVLdgz7D3AUkSNqbCTLkzSnYBL7DnC2Sgac2JuB5RVsRMoLC2+lUwxeMvDPzD+edPG9wm3pNDFBKH0+MQjOPnXMAGIZDjN3WD7JkdtwnAQhPQwI8UTa82SaF2EMSDFIzYtuBqr4XgnmAAGP1XwPspmtJx43+BqJZBfLsHixZ1dWHQpl86GE59EcLHbHbBFmHvEcwppZLgCOJibiVOXKyJPZwIDn5yGz+lnixfNUfv47lWMySM/BJ7sJEDhgFS7nBO54TsDt53l+7s5pANlJ8+Zm0Iq9tBiw5DUAZ3S0w76y3rLVeA7B57LaAbBZPK8V3YN9LH9kX67s4rkgzwfcr0utCTpYSsjWFU7tNewwa8spy8k6z7ICoJ7HNvbV9TYIGuUi9KpR/C45GTEcLXHfybnDsUkdZ6VgpkVWezt4KxHiwcNXKZqScUxfZTYQX1++zhwhY08Zzsik8onA4UiSt4yBmTPNgItdPwfOXBVpJVhMgeaJERup8nbZZWajUWvWF474cRY4T3zvMgDFoE6ol2YwoMD1ZYkVg0KcfZJfecFgh4EHPmbyZLOnAssz+XhvQXsrsMn3B7cnR8b5fuGIZDjM5MKTvMsvNxvEs+cXv/L7aDr544k3G9Dytefr99BD5j7BCzJvZQL+xiAmG7LafSaxN084XvBJ6OGA59y55oxu7jhIys8xZUCZeKFszRxnYYCa2TMso1q2zLevC8vd+JwsqWPQi68RB1J8jUEz9mrk8zMTyg5ncWbwwWkQj5k54dojkZUK3jKceVzIDA5ecBCHTbSZXcyAHQM47viZzmBSesFDnpNYg9RsEM+m7zwv4bkqAzh83Thjsy8ytHm+4hR8ZODVacISJwxWsqrHCQf5WLXDLGT3a1hWJHib5EaYBSfBsHz5cuMWtvbscbkuuohJlOYtZ06X65NPXK6ePV2u/PnN+6pUcblmzHC5Dh7M3HOvWeNyxcaef2732/jxLldysu/+jlOnXK6NG12uP/90udauTbuu/F3bt7tcGzaYX8+edUW1w4ddrs2bXa4tW1z/Z+8uoC07qryB12uLEhIihECChCCBECwhuDtBBgk6uNuHB3cGlxlgcB88AwMMw+CD26AxkgwuARIggY60nW/93umdV11dde69z7pf59VaZ3W/9+49p07Vrr3/+7937er+/vdt3Zvtqq1du7b73ve+N/3vgjXy9/KX19eG61/+pev+9reu+9KXuu6ww/rf7bxz1z3ykV336193O1T7/e+77lrXqo/Dccf1nzEWPve973XdIx7Rdfe+d9f96Edd9/rXd90hh3Tdvvt23X3v23UnndR169d3213761+77h/+of6O9O/pp49/r9/9ruu++tX+3T/5yX4dhz775jfbMhVjuT2uh+U209797vYcfv/723ak2Ir//d+uO/rorrvEJbruyCO77lOf6rozzuguLG2HWw8bNvSY6Fe/6ro//7nbbvoEm3zhC133gQ/0uv5Pf9rWvdq+Ghyw224zuuHRj+51/F3v2nXXvW7X/b//13Wnnjo/9vDMM7vuKU/ZWh9d73pd99vfLsyagOm942c+03WHHto/b5ddet8kMBC7+vWvd92tb911l750193udl33rW913dlnd0u2seX8o5r+P/DAyfGfz++338w9pqa67thje+zwwhd23Vvf2nWnnDL+mPGxyn5d5jJdd8Urdt2NbjR/tuBrX2vbQdd3vjP5Pek4fS3vddGLdt1pp83IuvE48cQec5ZzQ1fSTQP6aO0OYCMm4TaWCaht1JY8AWURXf3qMwvxJS/pupvfvL7g3//+yUgjiw+ZtXr1lvfhKE7icI1qf/hD1z372b1ximcwSByzINne9KYeMPsbZfy61/Xfu7A1xgio+9d/7bovf7lXpstt2xgPRuygg7ZeZ5e9bG8oo5FTxKnPn3vu/PeDDDD2gD6CZz7X5jgNgKzpmz326LqPfrTr/u3fuu6mN+310sc+1gMEfbzVrbb+Dh3wk590211DjAF+LTAF1I3TyMFVr7rld/faqwdjAPs979l+xhFHzAoc7ghgqurgkqPtzVGx1vOAUHk95CF938vGxgHMZP+3v12cAIbnGMMLWduh1oM5hPkQ+PTTDW/Ydd/+do/dltv23djAq12t1wvHHNN1z3/+1vpi1117wniujUy0dNLLX96du9BrwrsGBmLnavoIWeDfHaHR5y9+cT9/Mc7IfsTIpK0VlOKXwRLGdZIGQ9zvflvfT/LCfAZIvGsLM61aNUMYTdr4hY9/fI8vBXUFMyUtjEpKIF+CxkHmXeMaXffFL1YxxI5gI5YJqCXQljwBJTkIGREK5OMfbxsaBM4khAWyisHg1L7tbX1WB0eLcp2vtm5dr6hr/ZU5wnA997n1vz/xiX1mxYWlcVAOOGDryIUo2YWpAd0Mx/Oe13XveEdvgM8/f9sYD8bwmc/sI1vIqOc8p18zi9VOOKHrLnWpLWVCNpI+RBQaqKDjZN4sRHvFK+rr80Mf6rprXnPr39/+9l33la+09dRtb9tHRren9o1vDEfzRHlHNVmdd7hD/3mRb9HeO9+518scSLJ04xvX7y8T9Ta3mVUWwY4AprawSTJlrX1yfstb9mM/nzZpLo19zaPVNdnOSWig+Yc/7LrDD5/5DF3y6U8vZ7YuUIv1cK55cHFArD1ytZQIOWQn+a/pCvp1uW2fjU2GWx72sJlsSVmIK1fWdQZHeS76jY558IPbOumgg7r1v/71jmMjtpeGaPv5z3v8BbvPNrPov/5rGHvMhjTiVwlYSl6AHxFS+sgfm68Gw0lWqPVZtt9cdm5Edp1rnPsY+7vdrd6X//iPHRIzTcJtLBfTWW6zbptuf/u04trXTlPqh7T23Gr2e6tBMW4x5+OP7wvgqePiO/YPH3tsf9KA389HDSg1ql72si33jzv1TD8Vs1X096UvrX/3da9L6VGPGi7ou6M0dbwU9CtPT/vFL/p90QrGT1LQb6k2BXRvc5st5VxxY3vXb3KT+Sl0bI892R6nVoXaRs97Xl+vRzMHi1UbjSw4FVFtorIgoxNO1Bp6/OP7ukJx+ojCk4rEzsfpOmpY2Mev8GbZrnWtvthkrY6FYuX//u/t+zohxfrfXuoGKdip3pd5VQiz1sapmUD/Kryp7ofxsWaNhQKZioAaT8c0lycrPvCBKd3tbr0+fve7+zpS6qxs70XJF6KdempK173ulsd3q/GgZopx3NZjQmbVoFD7qtYU581PsqO/FavPCzarp0YO1NBSK2W5zf+pwbvumnZyTDq84WQlNfusbfXK/Ly9FM0n5y41B9VUym082SH7ZfPZxz62/9uFARMspaZeIOwcp5ipc/SSl/S/b5365lQ6MjDbuSQPub4sG91TntQ6l+Ze1tL2sH62ZYMf1WWda23WoUL0iv3P5iAoeIXfAEvAN+zWrrumeW3u+YpX9PjwTW/qT0RUx0l9RJf/z2VsJzlcC1ZWk7TWHve43s4u1Zpj89CWi5Avt1m38/feO/3tve9NmxShG1pEis+NWwBSAbl733umiDCDyaHknN/1rvN3jLz7OTFCUXPF1BVIRCg5QQwoZDhbxZ4ZbAVfLwzNezrStNYQDpMW9FuKjawgQEuS1alrjpVtHU07buP4ve1tPdHnJBBEAAJ0VENMkN/FLsyPeCpPGNGQxQoKK2Ya5JNm/SLpat+ZtFmz5oHjz+kvj4e/7W3bBh/gGRonwLVWKHlbNWDaGqMPa03B9bLgbkt+FWWlW+lQsqYQ6IMe1BeHRgre/e5bkijAEblCSCjg++Qn90VMEYsXFt2XO0oK2decqTe/uV+/27qxXU46rJ1EZE0ijKOJvyKqaqeF+Zv7zHfRcvdlu+mA2R5OslQbO/GrX6WdTzst7XqTm6QpBZ+taXoqiOWvf70nOBGd27KZJ8evs2sK6Spif/Ob94cZBB5ywmKrOX116CSu5bb47e9/74MPOU4RvLIeR52OOReCiK1t2S7t9rdPG+fjdE6+ArJMUJh9e8c76iduLrfJGrsBI9TaC184N+IEOQRfzDf5FM2Jl//0Tz1WpM9cZH6xT8JUoLzVfvnLbXs4yHbQlgmo5Tanduraten8W90qpRvcoM0sOzltKIqCoRaJ4RQBYCLuLUMzX2CfcXRqxDvf2ZMLIneeL7vJUaClY1u2hVKc2yN4GWrb6gQxzuDJJ/dgGPhYiFNVonHcW5kFZHcup8YwQiKTjol2estxx/VkDSdwHBJqW7TWqWhOShHFb5Eg3m0+5h0p4xSVV76yB5v5WkV2t7KFvv3tlG55y/a9EWe1rKpt1WR+0ptOcXISTWSPIcn8zvuPkwElIohYRzzVToWREXXQQb0TjMBDZpBBEfKyObnGuuNUX1gaMlVQotWMybZowCsyRxAAKSwibQ6POGLLU2ll9MqYjIZI+PKXh0HzKL0/qb4QiRbtFZVHanoGvSmD1HreUUkpc/S+96X0hjekKceOW68wTpk9qllTnKT5HPtJm+wm2VhkJtpPftJn1wkkaEOZD3DV8inF21eDI2pBmTe8oScZWkGXQw+dXZZL3o46qicxa/j5Wc9KG+earYTshAGuec0+GPCpT6X04Af3ZO7//d/c7r0jNrYC5qR/WjgpGv8IBrATJOTgwANTes97ejxSC3ZsTw0uZG/IMfu3LTLjjGGrTU1d6LP1lgmo5Tbnppj9tGICJstMJ1E0R222Ih0ceI63478ptVFAlCM712b7CQBuC54MAKCrVFycvdYRmpTZhSXFfAigMEBzBShDTYQe6P3GN1L68Y9nSCaRO5EZ8yM6C3wAyBzjhWgcgyFjPduMEI6gVOFS/uI44Nrvt4fWSu2+7GVTOvHE9vc4x6NAz6gmivvhD/f/R0IZJ1taEF+yfMgDPdKaRzJbO6LZmhYlRvrMdyO3sgh//vPJncub3rQ/Clm/EHiIUISHrXR00CiiXOP0DpEkyAEyzFGwVfKnP+23O5ftSU9K6V3v6gG/SDPy/sIQaWbfhtp8biMZp8U2cXJBL9KF7OeRR/bEDmeT3nS99729Dc6bNXCFK7Tvz5aPI1fjOoi2KMpOsA6QoY7dlsFIhhFkiClHfgtC7WgNycYhNjef/WyfRZiTO2UTUFmMqDjbwxnNs+DIsWzw2vNlj5pHASdzFUeql+2YY5Y2NmJfzAHH21iwwZPaLFuaBUrhlNb2tsVs5rXWD3rNlnkZrmWjI9761vECHEPNdiVbMmXQcsaRAGwHPXXwwWnOjU5hl8pm7AWWtyWZuz016/wLX+i3vsFvyo1Yz6MCt+bf3MlsROh961sp3e9+fbY0zCD4S4Zs217IIPBSbfR9a/fPbW6zfQU8t0Vb8IpUy22HLUK+VcE0BZkV1FTgUAHvz31u9Mk6Clk7mSA/Mc/pTK2CuLM9wSBvCvQpxquIXv7suBTYfMYz+oKs++yz5d/23LPr/vM/tz5mc6gpOGpcFOh0cpfCo1nx6u26Kej3gAfU58NxvQt5esmjHtXPeTzv8pfv518RzUZRywU5nY8MO6q3VYzxu9+dXQFBhQx33719XydubI9NQepaEVpH8+ZFjctLofS5NutHEejy3ubHyT6O87XWDj546884ktmYK/jrdB5yrTD5u961MAXcFRlW5PVyl+ufr9iro671bzanr1zkIl23Zk1/ctHJJ48+fSWa47TvdKf2vFzsYluum3PO2fqkQMU7n/Skrb+rcHXjfXaEgprTzQlJQ+M3nyf4jGrshoM52CWy5QCQsj/WwCj7dPzx7ZOCnBg5X42+znW4U2f1r/ZcumOxT9JcyPbnP3fdDW7Qv5tTff2r+H/LnroOOWRhx4D80B2PeER/kpVTf51qSyc6WMWpoa2+sa/kSvFdGK+UHzoXtlqKzbiQVRjDuxgbBw686lX9QRp06Khm/JwKe9RR/dg4FOClL124QzjGbQohX+967XlVBPqzn+26m9yklz/y6ZCR+cSoikyzMU7pzU7/GstGRFFtp/Lpa34ghlOpW+/F3i5VeZzvxlbUxsgBI7MpNA+TKFJf6q4L28FEoxrZ/eQnty70rwD7aaftkJhp+RS8JdB2SAJqNu1Nb9pyYTKCr351XVk+9albHl2JHAGkX/CC3jn6n/8ZjxgCwNzvuOPqz3Fi1P3v33VXuEIPHN/wht4B/Od/7r8DKOfH3Y86gcppgY7tjPsjHdxnqSgZY3rssT1pp/+OITXmCwWUgb3WCYVOjuCEt0AHALgQrSUrTg9zKhBb86c/def+5Cfdxo9+tDc6HHPOfKuRoZoDGReibaGatcPpcLrXbBow+Y//OEPgko3Xvrbr/v3f20f3OrJ2rg1R9KxntceMwxCnaP7TP3Xdla7UE0+veU1PPuXNaX21o5nnq33hC/U+IqQmJUrj9BUyM5sTOD/84faYcThKXeTk0fi7OSbPk3x/BwFTFzSOj+BD7d1ne8rQbBqHyhHbbOEQWcAWDjUkgtMic7uEKBJ4mcWJh80mCJX3a0iOXEscE23RrPG99+7fiz1DnJs7BF/r/d/85oXtE+K9ZnP0D9EK97T65jj3OK2PDjrppK57/vO77iEP6U9BLvXrUmjsIGIDocYZZ6fe/vaue+Ure5wnsGFMrH/2Yqh9/vN1UleQY1uflukda7gJIRp9MxYw3RBmmefWtBEwFZLDBWvusstMn484outOOaX/HBs/pE+cVHxhbwjQy152/gIodMDNbla/F6w1SXD+wtAkICDmYNNHPrL3JRr+49odADMtE1BLoC0TUJubo+RLJfbYx3bde97TM+ycH8z6e9+7pRFH7Iguld8VXR2VdQUYOoL8ZS/rsybKe+y/f9e9851bRv6uf/0ZJS4aDqyN07761bqiBlSWEtgWDQMGgE7/zuexqWWjnGvOnmvIkXb9278tTJ+AM84TWQzC5clPnpG1M87oNpHlHIACfOS4RRhwAmWzzNaJLBuAHFHG1rHewAjHU2QekBNBHJdMrfUfwCPHHGMywhnnzADy8R4yGkVY54PsMZYyzmoZaX6XZzLJEAJk6Y3ZEm2zbZ45lA0mIrmYjXOIjCv7gQyvEYPmUwTfZ6573Z7waL2Lua5kkO0IYOoCW8NB/cxnuu4xj+m6ww7r7cz73jf7tTPb9q1vjacHn/CE8YCxeXbcNlIESB7Xrk3a37giE6h1sZc7SqODrZ3IFDTG1gp8U8M9cEU4b77LtsznfNCFMnuGssu/97323MxnZtz20NgvwcF4N7b7Fa/oiaiankRCtRri5opXnD8nf74b2yxY60h4pKjg6lvess3Jgq1sBJz13//dyykd2wpEyiCBdYbkVSbaYgYHttcWAffW9cY3zu/9fvSjbkGbADUcS3ZHkcJLrK3dATDTMgG1BNoyAZVFjWpKDNkj84iDW8u0+eEP+89x8hBJMqk4Bxe9aP/z0PYUziiHwjMA+XyLQFwieiJ+5e9FYhjycRpjWm5lKTNclspWvHGacQUKgK3vfGdrosqcjENCcIhbY4Y8EUVu/V2EdyEbo0cmOdz53LVSnEcZZMaczJbfucUtJgOHnBXbXmP7KsKU85cbMka7tnXOOpjPLWhBTH3pS133zW/29x5nC8MkhABnQNYjx84lc4O8bS9NX+ZKEMx3Q5Y87Wm9A0KP3fOevfy1QJx1ePTRfVYqp3nofSpjP+9gSj+9AzINcUIOFqMhPMNJl81gG5n5E5iQ8beYLfqCaM+zAspLZsr20MzXvvvO9OsTn6jb27jI447U8gywm9+8J/tkndi+DvvI4DBX5hVpLftMoENwQCDsdrfr/0anzrUJHg2t4Q9+sMcsMr3LOZIBvq2zeOa7IdxiawwcKLN7iNgdCjwOYRaXMd0emgAOjLadbHXdwkbAjzlB/Y53zARBaheiikz+wz9s/TdE7+bSCBfahsSGw6z7IZ1L5kcR13A1XSVDE6YbknW4b6EanIG8v8xl+u2y+rQUMy8bbe0yAbXcFqMtE1CZ4yxts6bIZE20GkAkgvPyl/eRfY43sKY+073vPToLinKW5WQbEbJJtEW2lcwoUTDOP0MtAnPAAX0E7O537/fGj+tMu0fUf6ldslAAvqXYEEmMASLAvwCEjB3jF++nZo0xZsBkySAIOXCybjiQrawUTktsXSgvNXRa2RhXucq2ieiRpRpZGdfDH96WGaSczANjw6EV+XvrWyerGwFM2gpYPhfoyDMK1DRr9RF5NZ8k0WI0Mkf2rNPtre9AUSuLz4Vc3xYtanHo3zhOLYfLWrW1tfUuyNIKGTSvYMq6pu859Lb80Pn0py25m7fALth4sRGtd7/2tRc3yo7MVbNL5uRQLaFxgyRD826bi7qFAgqj7Gmr0W/f+MZM0OBxj+u6+92v3uc73rGvm7QjNe9jrQdZCEcgzgXQSlulvAA9XI6LzBy6e6EJKLWgzDkCjMPJdrNFvrdYZO9iNoRbvLtM5bvcpa872Rof9rQVqLHdvqzzkl/uv9z6lgU8trAR7BKsnRMjQ/Iq0KxZR+RUBhrcCCP+5Cc7VnB3kgYLCXpGrT0y3aphKEt/aJsiHMq+599hc2u1cxc6iGDtyXwrnwcL7CAk1NplAmq5LUZbJqCyxokE8mPbjm1OAFde7ylviAtb8hiaUhlRjPbYjuPAA8cUl+gVJ0s/AO08e4qx9Dufm7T2CsdEtLOlqJ/4xK23sgH+EeVfTAMa7wkEjMpSippQ4VQgmjgZtRoDQB1wUP6eE9VKadcXNRhqY3bJS/ZzJQMhf556KNuq4KRx06/WPIt8j3L2jTmZnY0zPRSRso1VlJAscfBan7N9bVsXS92RGhlWxLbmTHIyZachUukA/19IEmU+mv4h+Mv3UU+GM72QYIoTj8RlE6IOXX75W2vL6VzbqMLMsu9GrZvIDBW8QDbPJejAuTAOajf5N7YE55eo8FwIA4S27Nx8O7GIsyDCbLay6jMHXUYDO2ErI/Is7D3HHSm1EAdIbA9tcxHljd/8ZnfeN7/ZbYAzahnaZcH2Us5mSwKOsy34oQ/t677lcy54Zm0NBXXYFfed762bi9Fkwce7CuAgpAQ2W2sd3mhtuYVVa3g0MOlcahHRf0hA652thw0Xe0v5XBsbAO/JwIWJX//66TVxTm4j6Md83GxxrmWH50RIqbfokNnUSNyRGhI53yXAZsq8LIPh9C6yuYX3YZjaFkgBoFatOBnTC2GL9UWmaEsWHCSzA7S1ywTUcluMtkxAbQamALmiwk7QUrSXMzNOXY0hpxvImitYm2vjlCg4x0jWClMCM3mkwFiIWlPgAAtSR5r+YtQY8QzOsuiClGcnXrUAE6BVnkJnW5fIdm0ubE1rRUtEaFoRbw4vBz2vJSQ7CBDTFMrk1CiuaRwZPWMoSsKh5+gs1mmDxmSIaCTb455YNpvm/p4DdNz3vl339Kd33X3uMxN1N5dAxhABJftqRySgkMBkgj5YyHoBts6QQ/IZZJLxvO1ttxxn2ZUPfvDW4895GXL0IkLsM9vK+fBsW53VD3EK273u1TsVjXpw8wamjCnHxVbAmuzSs8gR2wPUdNGn+crYMNYi7a11I9t26P2QTQ4lCIKaLSATcznNle7zjta5jF/g+x736LdJ/uAHc3t3OvRFL6q/q+yCuWzVpSfJDMfngQ/sty/KcpCBjJTdXovXxpZfGXhINA7eLAiXkethMQq0q5lTbt1EIsuU9Xu2XQDPVihBPsWGEVOlzgnshrCRwY6k5eSOs02PrtSPpzxlhoDfFtv7opaN4vDeWQZYq2Zn67AFZIe1rOQAPYWozb+DUFQ2YLY60Joo60TKMrfOlwoJBXsY35Jc3WuvbuOPf9z96Ec/6tcEecr/LuBRO3l183cXfMt9nL7HJ1mI+ngL1WfZ9OV4XfziPaGHZDWmtoR6J3UAWw3eyLdP58QV3SCzKg40gPElESyU34VcrNWwzH2JpTA/I9raZQJquS1GWyagNp/MUavnI2V9lMF24tYQWItTMrZF4yCEEVBnRQZQrshFM4GdnBwBcGs1PTh7C5le2ipOzMGsHa9uXHMgoW6CSKLjnMt7eM+hY3JdQ8e2kgHkCXAnpXooS8RnOTT6k0d+OGeLYZgAwlr02paLuTib4zTrxfZQDgywKuuJ3PnZvwHUhupUIYHncxtbnPwB6CBS9WWh06TJB+IRGeqoerUIrnOdGXkWzZtvkg2pZe45MTlRiiCP7ABbmMwRR5uTNkktBnPCUQLukMPqHnAIt2U9log0j8jqmzcwZdxaxavJbS1rgXNbnuY2WwKSHqxtpxREELUfarJ9WhmHc10PZAOp49/5ckaHDoBwWcezbfTBUC2SbV2oudasM/or7ycS0db/CYm+ketBTZshWzlK1sZpZEXGtwxiOkvgBPYQ7GEfEOGxlUyWMjIS1irJQU55DbtZi0PbKI1nScB7ZpA/iCnrYlTAxjOQoeR1todbmD+Z1nCDgJ++OC215sDbGlYG5ehBTniMF2JIwJEeR+SxN3T3bOt3sR9I5m1FwMxXoz/z0zbz6wEP6M4/+eRuoy2fArB5jUrrDH6DafIgrkDpQhNw5tbYR7/pLbWmZhMQ1k9zRS6e85y+4P1siHz4BpZ0r9ZJhT4zVAzfCd/jZoh515a+9nvBKHNru5+1MR916mpNgAtuqx0YFRe5WajnL2Jbu0xALbfFaBd6AmooHZxBH5Wy7KjcljJirLbl8auUcn7UMSdYDQCRcJGgEkiOOg3N9xaqiWS0nitSkpNknE4R9/g7ooODpShvDbRJ+a2dVJhfkdE018YI1jLNXCKsC93OOafbqGZZftwt+QaUFvqkDlE6JGf5/kCCqFc4PMCLujk1Z7hGNs62kRlyUma+iQ7P53PyxkGKYqRIW0Waa/Ig+2RS8kYWC+IVuVUSoZzq2rYw5ES5xdQ8qIE2zjHn0YDy3NHjNHIUbbNCSiGj6LrtrQbWfIIpteUQUOV8IvXNc2s8o4YgsK+eDWebgyyTZBJSmgNBZ+db8eg+TtNQhiU5UZdu3C0k27IF2R+He4yquzKbRhcO3ZvO2N7aUFbShHZl5Hqgx1uOOlJ70m26HEj22SlX1lCencCpo2v0BdkDl+Qken695CVbFq32vRvecHb1x0qSTUFh+CHHS4h2/a2tLWSTwGVkQwrawR7ezfjRz5M4w2xiuc3LVp/3v7+3J9a87WIl2WP8WluC4L35CBDQWwJYC0EGL2Zr1Z6UkY1gioNTkKJ0qsBl7gvAoXSHov0Kiy/0Vl0yVjul0uVUy0nXob6XpD4ZbxHKURoEIe+7/m89OH01sIVsvBqJhVStYby41IKy5ukGO04EjwV4a0XpkbxRR2pbnIopex3mkjVrVwZyeCnY0jm0tcsE1HJbjHahJ6BGFcQcdbpQmYlTpu5uy3RMDs7Qu5WZDgzM0F53QGghtnAxREOn9OXbsoBO4+oUI38DGIFJAAlIADLy7XIBHoaybkRq5mPbBcBgS0frObY1LkJdgHPOOaf7y4kndhuBYPK9WFkqgHeAuPISxQY2vD9DDnC8+tU9SL761XugZU7nM0urJGBL0LkQa9M2h3gGoDIUBeTAjNs4NsYtJz+QD8YL6aMWWus5Iv15pBI4vN71htdDDgSNE9mNvyPWAK3SKUFQcYYXa0tG1DRC+pL1Rtr9vIEp8ktOS12lPk2tLlUua+xEXtg2Ltv1JtUJALl5d89x1vb2eBJirXGonvzkXn8j6mrbLuJCaMy2IQaGitc2aolts2a+OZyt/goaTZB9M3I9yBqlx0qi1XpH6hg/+tuWa9mdQ9mcMEg5jwcf3A7MuV/rPWWP5vUV3WM2J75Zb7e5zZYBKpmqtXuwH7XsaDJS4gzbbpEUEQggY2rU5EQFMguGKeerlXXGbnLyreGaXuX859nWkxygM26jZ4bG+VWv6pZEE0At+45EgRkje8zPcIjsJmsAaaouma25iGmB0oUO5EUj6+VuBP1DegpgsXnjNrYRjq7Nn62rJfFDN3hfW+Z8xtZtRE8tmAYP1Mi4IcyNbLKGSt2AfK4RWgjBmp9l7S5kRru1att9/kzbB2skuTkZ0oVstXlYAhlSay9kBNSKtNyW27ZoVMdQ27Bh+O+XuERKb3zj1r+/+MVTeu1rU9pjj7TN2u67p7RmTfvvl770lj+vXDnc3332SWnFAixVz9111/bfd9ll5rl//GNKn/50SqeemtJhh6V097un9J73pPT3v6e0cWM/5u96V0r77jvz/Z12SmnnnVN6xCO2vrf7/uu/prT//nN/j3PPTenEE9t//+lPU1q7Ni1067ou/d8556TzLne5lK50pS3HYiHbGWek9Je/1P/25z/3c+czH/5wSve/f0pve1tKN75xSre/fUpf+UpKd7xjSv/93/PXnx/8IKXzz6//7VOfSulPfxp9j7/9LaXTTkvpO99J6YQThr/jHV/1qpmfL3Wpfs5b7atfTWPL1QtfmNIHPrClvvJ+xu73v0/py18efs7ZZ8/8bI3f5S7tzx99dEoXu9jMz2ed1a+5aE96UkqPf3y/5vJ2zjkp3fWuKf3ud2nBmzH53OdSOuqolA4/vNcF179+/67r1i3MMw84oJfRJz4xpT33nPm9///hD/Xv3PzmKT3/+Sk9+cn1cXnkI1M6/fTJ+rHXXikdfHBKhxwy3tpetWrL+Sybe23rRnfT2698ZUrr1/c6/TGPqX/2kpdM6SpXmf2z2OYHPrD+tyOO6G369tTosJZ8aeSqpedm09hKeuUnP+nn4Fa3SulFL0rp+ONT+u1vU7rylXv9/exnp3TTm/Z//9Wvtr6Pz7pPqTP/7//679OXZTvllHa/2A46ZtzWwirkK7dTZOH1r69/1riyV3mjD489tr9PtGOO6W0//R82HnZ897tTetCDetvHfjz2sSnd9rY9Fvnxj2fep6UzjZF14Z5TU3U9mOv2sp18cppzg7+G9Mw1rpGWRGMjyjG83e1SOu64Xv9oN7lJSp/5TEq/+U0/py9/eUq/+EVKn/xkL8tPecrwWpzPZl7Nb7RHPzqlj340patdrddR+sX2j9P0ubZGNXJbrlH4Gg6Id33IQ1J66Uu3xB8HHdTbtuc+tz4mRx5Z1+HPelbvS9z61ls/93//N6UnPGFrmTZ3//M/va3XVq9O6b73TekLX+hx1kI1cvCyl235O2NhHb/jHf1aNk7wkZ9rtsPYvP/9Kd3iFild61opPfjBvS5dKJyy3CZvC06HLbdqu9BnQMl8aWUpYPuHagPlGQKi8NIzZQqIam8P++JlPYjO195N1KJk62U3DRW6VRdhoZq05qFIZkT/HMftd/vv30fBRS7VPCijKLYayl6THi4TRsRRhP0DH+hTiBWytQ9denFrH/ukTXRTIeLWe9ztbosS/dhm0QtRraFIqbT1UVFrWyXnq9VOPcyv1umHuW540IO2jLzJ1mrpBPKV1zETcZ2PI7HJb+1kx/w91N5q/d32jfLEM/rJGio/K0W/zE4QYcwjsSKhQ+O6GDV06NtaRLQ8VGG+14NsM5lQtiSozSGDT3RcraeyL7a+0jci7EM1h8jpQjbvHQcElJcsjoWuDTdOE/UusyfV/FH3KM9itP7UDpprY/tkluTz4pTQuRQ3X6jGPulrS35e8IKJsjImWg/u63Psby2j1FY9mRWyROJ+9CasYLvOkJ6oHZPeqlUWsppvnZbJOXQyZGtbfYlzFHQf2mLmBN0889v6L7OfbB1sbVu89rX7bJLSFsCXMAqdQme2ni9LpFXzh7zmWesOI5Cdaquwf+nJuTbvrnZgPEMmp6wnNfH033qcLwy1kI0NLOuowexOHoyfHaIg07g1F+R/oWtI1k6jVE9SfbSyP0cdNd5WwK99bTQ2i2Ydk6Nyt0T+M7/CtnOybS3IarSNsdwWKINI1iRdbpu+NWndBo6vXd65hbFkERkX2WGLgW/Vyqr1Ua1Z6wtWktXUOABlevteTXcbM3h5O21rL2QZUMsE1DZqF3oCSlN0sgQULieyKa46bgPSWopoW6XuS9NFfOSps0B8y+mgTK9//XqR3YU6YlxjuEqj5+Lg5QY231YoTZphHdrm5BQ2AA+Qjvo0jJh7LsQWLP2rbe8w/pNsuVqKxqMEwyWx4e8KMh9xRHu+5nOMhurIqDc1dFIKwrJ18g2wVfuutZ+naz/iEVueSsgBAXCBLw6atHIAZtQ8jdpKixCy9W3SbRh0AHCEtNE3JBZnotzqYUtOTqy2CnHHpfD5fDXrlvOlr9asvtUAcn45hS3Tw9bBySef3J033+SvvtGx7qt/UUA4LoDcFgZzPTRetqIuVEMGcLLUkinrfiEVOfyzLZ48n43c1caGM0i+1QlRq2Q+txOz7RwdzhcyZKho9bZuSOYaCU3fTlhnctb2Id9ebGuYmkRIdmQEohU5ZB1c+co9oYPYGZL7mq6vEZFDp79xbmtb0J7xjOHi7BzY2F4E53Gkx603VjuVa0gnCjSotVP7m/nzzvBPq86NUw9bBGN+WqSTTREsuZywVUiouW6Ltu7U+1MDjM6IOkBByqiftS0PpBi36SNdaNsZfW3runp8xsw4fu5zw/VIbbMqgzkL1egneAGxiexo9UlwYRQBTc+1gmHunxO7ZNH4lLYs6kfZvm/t1+5F/sbB1SWhtRAnbc5HK0k/OF7Rc3IT40H/qMNWq181hN0EyssDSraTtnaZgFpui9EudASUSA1lC3QCtBQAAA7IKKZ7yCH9HmtOG/Z6qTbARGQdsabGh0wgSt/+dtG4obojosNf/GLvQHOogd/FMLoMn6gpp4Pjrs+lo+8zCLRQ4siM1nHdiCDzqq6EOhkimd593BPIjKFMEc6PSJ/oTctJ4YQ6WUzNBwAmzy6RbeX7i7T3e5sZD+NVK9LsZxHiIABFfmqEr/mZT4PsXnntokmKRdbqL+TX179e/x5nMBwotUCAdQXhgV2yh5wBYmOMjIMTjFo1yGTVlc4nueasqDuEhDWenC1ERp7R4RkcgyE9FoVAoz5Xq1kHUdieLLfGhjMyXwXeATonOMV4irzLeOSwDZHOSOtYp+vXdxtPOaVbD6TTKbJF1DQZKto9m8YBYEdzJ9J8q9PFluQ6q7wWiphm65BxIWccbTpVliFygFMy3+Mw2zaqls1caj7tCM08WefXvObMmMjcYN8mrMs4a/sQJ8maJ7YuJyGiBlIu5/lBIeVFf+T1nKJ5F9isJKE4vbXME5+ncwXIYAH63kl242A3ZNn97tef6KmmVaufEayjY+EPhDw9UtqT1uEjbN+Qsy0QQdcJIsCgkWUGQ8Bwo97Fd5GArYNW5uukOjJIZ9QyZ10yXBaiRuhCNPNIntgJ5DNyNU5QltnDDyjfjw5d7Ppw+ii7trWTwYVIHQqmBZlVZn/FxS6Q6Whwah44c6mZFt9HqLbq8427a2QoOAgrbQ87SDR4Le+bGq+tuRCkKxMW7N4YWvvjjNU2aGuXCajlthjtQkVAMTq2TeTOnMhXKAGAnTFfrAjHtspGGUpxrUWInWDG6HDcFmNsgJih07QATpG4AAUcvFoqvsKejlYuf+/knFEGWwYFIFs6RQBiLdLBOQgAyulURJejLnpv3BarcOW2Nh7Ai+0ECD9z5F8/5+QGwpfOAXJEkTgAtq3ORyH4siEbEZQi9uaG0yTKOSpKx7EbAg6t7XMizeYbiUo2ZVohc42BEzOlzNfuJ0ulNl+cMaAnjgxHcCru+cQn9hkBiIQgfIwxZ0mRTGtWP+Yzyw9JhVzlfLVIXydVjbMdoywgXs49Z8/2x9ozvP9Q0e/73ncmq8fpNUGWcdgRWLI2yN9cnSWyxUHISdMoEE5vciiRqrZPtLZjcpgXCmzTk2XWDJlEJMrImI/tOfPV6FuOUMvBms2x4ztiI2vWNRmbZUbyrO1DbLGGoW52s63nKQ4GiUvwymlXtTm1taWVeWddwi/suswLGYQ1m5s3eMF4TBrkCQIeGSazId+KZ2uhNezZyDS4AfHttDvjn2eKI98EFmrvaqvakC0RCOXUWpsytgUKBXLodsTaUCZXNOOlUHTrGWzCfLShwtJ0ymJtT5vPds453aZ8q5Vi9+abrY1tlYLSAgXbgrCHuclFa9z1cZxx5/84GCWy8QR0ZNfVMteQorUgIiJ4VAb0OKciema+9TG/ZNptLztJjJlSHbmOax1gUfOrjO/2ekr6QFu7TEAtt8VoFxoCCgHw8pfXFQGgsdBHqi52G6opMM7pKBwp45VH9VoZFZOeyjQfDYHEgQLeOHhOK7ENwL8ynhiCIbA0qu4Kw9A6Qe2Vr9zSeQUQh07xEzm+sBkPzyYLQ31AcAJOyAfkiUikjBcAX9bZuJlqo5q1b31z9Mc9unhUBhTHhAwCqggPmSYAajiFHCGOjfdDyJDJoTR6zkcJRjibCHLEhaisOgq1KLd0+cWsXQOE6xty1bMBL44Zx2mczAMyIYMid5iQkMiiAJ62ZLUyCpB6yOFRNajMjwwx48eR5cwF+NZvYHIc565sZIhz6AQeYFRWClKzVmcLMe65nFP6SJQdqW1rDL3gnRGIk2z1HrepU5WPi/FGXMoGu+c9e9ndnhpHnyOeZ/HJRKDLjRHHxhpiaxbhNNEdolmrxfarWdsHcu9o9ZoeM2dIjlKnsckyqZ2QGdk47Of2uF2L7rFmkf4yNOgP2IY9Kt8XScFeydi2VZvDrtZbmelI/8ApsqBrugrhJbO6tT2KDhyn5pn1MYT3kIEhD2zTbLfksc9LMKNjsLHRsZ0ql13BM9v1yMO23p47hB2QvOMGmuBW7wtrxJb2WnM/NjPWrUvWExIazhmSAVgnf16reb4gWmTDmwPbSLc33QCfCh5e5Sp9ULn13uwrf0RZEGPnX9nrLRwjq2w7TXZYuz34EHNsO1wNqNNPP727whWusNV1HGZ4epv+id197nOf7vDDD+9uetObdu+W1pu1jRs3dq973eu6G9zgBtOfechDHtL9qojszcc9JmkXGgLKGLVqC7g4vDtSowiHjATHZ6j5e+u7nC2N8fKcPJIBgHHOFypSZB4546IS+hFbcUTJZTwphgrU2daUH7VcXle72rChk5HT+i5DnBOW/j8kW45hX8TI2ZIzHgCxzBpODAeZo85JET0CvvP08MVqnmnram0+kQcAv0y3Wu2RWmaCQtVD0TAXwiBvwHz8TSbLUCFR6d/bYpw4pdbkqAyFvHnPWlFuhC8SW0OQD40VYKcORZ7hgzCUmRZkTqT5q9egDl7tPjLFJsmEAsxjW1t5cVbye1nziG5Ejyg1HaHeiCwszqqsKJkkCDX6jKMzn8RKXsRWxhrSjK6mM2094hiPijR7XyTdXGvIjNsi65b90T/OUmwlj3HmrCNiF7Im4ajGIUUccAyRENbAIma5Djb94GCqXUSukA/6ujkzcU72ga1rrc1awMdcyUJGTpnP7WmcxmlDmbAyooKYgHk40Lbc8Adsh6YPOKLev7Y13cXujTq8g94f1ZBlMlqGtozbTiQzV7F92+Vmk3k5dACFLOOlmKko2DQ0/rbAbetm3SFAajZTBvFCNBmKxob8kR/ywqbBzTXsE9vn6GwBMbLN7rK/7Lp7+VuOU+ggWIof4TtDOx+2dYN1yqBOXLal8j+iTEFcyGnbY1sE9nba1i41H+LCQEB9+ctf7g477LDuD3/4Q/fHP/7xguvcc8/t/vznP3fXuc51uqc//endaaed1n30ox+d/qx/o/3Lv/zL9Ge+9KUvdSeddFL3oAc9qLvVrW7Vnb/ZOZ2Pe0zaLjQEVKvI6TbKUlkUZVnWaBgXKBhHW0daYwXAcEwYjjJy5OIsMCjz3RgomRKewWmT9h7PBPBy5S9q2Urxjcj60JYvRMiQvOTgzVjHlsDaxQgtlgO3FI0HcMJRRihwjPOxQzCoz7At3oV82P6WkyWIS2sHoTRJTR8gZCh6Vkvf5kSG06K+CXKr9X0ER7mmyaisJA4oMAgAbusaHQiWFhnkUvQTCC23ANQIqKjnh4i2zdH75eAWocMBHsqERFxPsm2ErLYimojp8l4inBxMREXUzUBI1zIJ4lSs+XLQkTnGmi6UhVJzXvLTj/Im+5AjTYfaNmptbgvncqiAuznfFo1eKLfEsKlIs+3BgaJ/ylPdYh2sWzd3+4DYrGUH0zNlofu4ZDosRJbfQreoe9W6ImvVOsrXlcynfA7oK5mZiko7KdX2c3rBmCAHh54xDj6HL1pBMzr1mc+sO82TnoDJprSyuRCei00uItDhQvh+tuSm4InC+a3x314yRb0fLEmu4AUBVqTuttgWiJiNsgY57neaNZki/36HNItSGLCcjCpZrrX6b0vZr0I4t/wttt5aV1LATgk6ZTt//7VLzYe4MBBQb3nLW7qj1WyotDe96U3TWUnrMwDyqle9apoc0hBE17jGNbp/k72xuZ111lnd1a52te6Tm/fMzsc9Jm0XGgKKkRo6ane2RU4jpRVQFmHiEM3lSNr5dBBFRsrMHOBIxHbIUIvqHXlke6wYa1ttWkUvXQD6fCov0Zi8iCKCLI7LRf6U2ytlYtlL3uqfbTFDzsIQWXCFK2yd8VFuP8idytmScbY5ibjIBkK2AVljgPglZzy8G2LHe7bGEIDfFg3RinQQ4baeABDRyNapRi4Of9lEu2wPbRXPRhSUafTIiyiMqrh1bStIfuWgBkAsHQXRSXpqEcnQqvNeRgnzyxYf40CnXuIS9c/YljhOsXrOEsLa1sW5OnjR2Nmhe7XqKskiAsxlZZHl1pHtNRJrLo2syu6d5CQec1SrZyPzbzG3etL5Q6cd3uIWC3OS6VBjN21hrPWHc7WtHQt2CcExUNx3zvYBvnnyk7e+P2xB1tRJjC1lnFIO56TbqeEgWT2c7m15UpRMoXEIKP1sETP0WGRMy/ZlQ/JMR+933evWvwvbjJtdKjMF0ZRnC8IqQ+UYbDObpG4W20HHXeYyM/dAhqhhOEkW7Hw0ekpJiDh9FNZFgo27zT5rG2Wk1saHrdrWda1iayhimQ0hc+Rtrtu3fB+24bcEtplEDug62bx0NKztXuxcBJhsT0c+1YLUCKrFtCXz2eDwst7a0IELLjafvzEX33AR29ql5kPMkdtYkZZA++lPf5oOPvjg6t++973vpSOPPDKtWrXqgt8dddRR6Re/+EU644wz0sknn5zWrl2brnvd617w9z322CMdeuih6bvf/e683WO5NdolLpHS//t/Mz9f//opve99KX3kIyn9x3+kdMghkw/d+vUpff3rKV3rWild+9opmZcrXzmlf/mXlM48c/z7/PnPJj+lRz4ypXvdK6WPfSyl3/527lN5lauk9P3vp/TOd6b04Aen9NrXpnTCCX0/V65sf+8iF0nppjdt//1GN0ppxYqUPvOZ9me++tWUzjorzVv7059Sesc7Zn5euzalPffs/3+d66T0xS9u+fkf/rCf08tffut7Xfzi/XjEOvvrX1M6/fT+ntHMJ5mptVe8or9H3m52s5Qe//gtf7fTTil98IMpXfrSaeKmP496VErXuEZKT35yLxtXulI/l/M5rttDs1bud7+U3vrW+t+Z8He/O22TtscevRyRsateNaX99uv78/e/t79TW/uXvGQvr697XT+Ppey85jX9s/J20Yv2n99775SOPz6l612v/Uxr2rrV/vCHlO5xj6378be/pXSnO6X0u9+lbdZ22SWly1ym/fcrXjGlnXfux+tTn9p6TA44IKV/+7eU9tln9LN89pnP7MdxqFmn47bddhv++5o19d+b+/3379fuiSemdN55bT13xhlp3ppx/L//a//9f/83pb/8ZWvd+V//tfVn3eftb09p48a0oM39jRN5/dnP2p/75S9TOvfctKjN2nn1q+t/O+eclL7xjbRNG9k5+eT634ynMZuPNcwmPfvZM+th9eqU7nvfXre98Y0p/fznKZ10Ui/rxqtlS1u275//ubfBbOetb53Sl77U93+x281v3v7bLW6R0sUuNqNr3v/+GUwRzbjQV/6uGS82ZPfdZz5Dl/kM7Jg3vsa///vWWKPV9t03pWc8g6OS0re+1a9j+PSzn21/56MfnUzfTE2ldLWr9ff9wQ9S+trX+uf90z+N38/5aGef3ev2F75wRi7osac9rZe3CfXChmtfO63/wAdSutSl+l/At0cfndIXvjDzu23R+AZveUuPPfgZ8Owd7tBj1tI2TtJ+//uUHvOY3t7CDocdltKtbpXSaaeNLwfsOBxNdo89tsdJ+sV/0Yzfccf1vyvbb37T23dYaqm1K1yhX1/WFZ/qv/97NMYgo3QD3TmX5j7miL9o3ZW2e7nNqhVae/tsp5xyStprr73Sfe5zn/Tzn/88XfrSl06PfOQj041udKN0+umnpysQzKztx9BMr/XfT/9du0RhiH0m/jYf91hujQYIPPrRveLbtKlXugiDcNIAHQDiiCP6z47TgLlb3jKl88+f+Z3/M4KA2B3vOJ6BeeUrewMe7cMf7skjTsCBB85+SsNIPOAB/TVuoygf8pCUXv/6LUmZcNae8IQeSA31DRhpOWOzbeG0eS+K+M53Tulf/7UHG+F85w2Bg7QCIj70oZQ2bOgJPvNuXMw9gu5FL0rp17/uSQYAjiH1bv/zPyk98IE92AqgaK4QcDXw9/zn988E/HbdtZ9Da5VDPWn7z//sydG8Mdb67vlXv3raIRoDeuMbp3TqqcPEiL9bt4Dhtm7IhNvdrgfvtXaf+2z9Ow4H4IgcIrPexdqidzgnLUIFQAQ2ADl66aijevCTN2QyAgtRFSQGx6/WENv6gJjYFg1Qe85zeoeybNb14x43ozfI+I9+lJLgCqcaAAeUx9GJ5Ip+3m231B1ySJoy/jXS8CY3GY/Mina5y/W6puYMX/Oaw/dCInJaBT6G2nzLeOkU18Y92rp1vcPTau96V0qPeMRkhMK4jX7+xS96nU33IkvZ6VLeo1kLc3HCZtMEnYZAf4v8WaxmDIfafBF27PuznpXSgx7Uryv2DsHqXzoGdkFEkad737sPMIwTiGGT4QuBm2hsNJJeoHAcTDVX8pMd8k6cRevZe8IIteBABMHoYHb5Jz/p1w+9RV9x0C972S3XWK35jCAaHILohU8OOmiGuBq3GX/3ckVrkd3xvrMhAfRr0r7NZ2PDBONqjS18+MO3HIMRbcNuu6VfHn54OuTrX0+r2GU2CKZbbP1SNnoQUZQ3xC7MZF0MBXPKdU+2EJp77dXLZ2mH/O62t03pK1+ZvX4nTxGgOPLIlN72tvZnYXJ6oYbdt/eGlHTx/zSkkDVeW0t0Q2Cz2TRzx4bDdXxLfir8qHm+MaYrltuOS0Bt2LAh/exnP0uXv/zl07HHHpt233339J//+Z/pYQ97WHrnO9+ZzjvvvLSmcLh32hxZPf/889O5mw1/7TNnbc5omI97zKbZAnmO6N0Sbd3ZZ6crr1mT1pxyStp40Yum9fvumzbVQPwee6RVr3xlWn3yyWnqBjfY8m+clZvdLG368Y/TeWNEPFasWJHWfOQjaUVOPuXt2c9O6484Iq0fwYzv/POfpxU5+RTthBNS94Y3pHXPelbauA2c7hX775/WfPWraQVDHtl1hx+eNr3lLWndAQekTRs2pJ0f85i04r3vrX5/09Ofns7fddfUzZNcrdp117T6jndMUxQvUMcpAUJe/OI+I4lTXxI2f/zjdBSm+/jH06anPjVNnXNO6lauTBs5pWeemVa/4Q1pxXOfO/N5UduPfCRt+tzn0vlHHZW6S14yrT7uuLSSw3H++anbc89etny29l4IgktdKk0deOD0muoHYlP9swNt9V/+klZ7p0brzMGrXpU2NoBj6In4d77aiqmptIqDsHFj2rTbbmkDsDvLtvKcc9KaP/whTYmWcUwAfg48wFVp3a1ulc4zB9tDxGzFirTz85+fVnz601vNbWeNXO1q6fzanAMiBxyQVmzWL5sCRGhDMrLffmnFox6VVpx3Xlp1neukqbe+NU0hh//619Td+Mape8Ur0rpDDkmbNt9j53PPTUMaY9Pf/57OG1MmpzY7TvM57qsPPTStfPWr0wpgikOv7bJL6t7+9rTuUpdKG/O+7bdfmrrDHdKUddxv1R+5nlb/7W9p1etel6Y269UpRIYo7d3v3hNvsgk5J2vWpE2HHZbOQxCPOR4r9t47rfnoR9MKZGL0XbvYxdKm97wnnU+3VO61+u9/T6ue/OQ05TvGtEViHXhg2rDXXmndPNrjna93vem1WwPH3fWvnzZc5CJp/ebnrdy0Ke00lOG0adM0FprP/oWc7XTCCWkFxyru/e1v90Q83V460atWpU1PeUo6ryEP5H8lTDQ1lTZc9KLzJr9rVq9Oq+irRibRputcJ51/7rnbTE/ttOeeaaWgJdtXtpUr06aDD55f++BZm4Ok08//9a/TirvdLU195zszn5Ep9Za3pE3/8z/pvBFZMjv//vdpRU4+5e2xj00brn71tG4SwniCtvqss9KqD384Tb3gBX1g8JhjUiegdPjhaeq441L3rnelqT/+MXW3uU3q7ne/dP4lLrH1Wj/ooLTyRS9KU+efnzbttFOPFZCCo4hBDdlxlaukqatedUZ+5mGd7Xy726UVz3ve1n+wLu5//7Rhjz0uWP9LpU3LSWuNrVuXNp1xxkhZy5u1wAc6a7/90i65fG3DcZnGgQKitfaXv6Tuy19O55HREbpmxfr1ac3nP59WyIqGOQTO8t0EeTvttLTpF79I543K6Gn1GU6H45Bj9MsAgQdPr+u6Le39Em2r9twzrb7//dOUAE3Rugc/OK3fa6+0YYL3ZA/h4xWf+1yve/7hH6aza6dK0vBzn0vdve6VNnz0oyN9zUnauQvkQyxmsy4Cvy55Asq2uG9/+9tp5cqVaefNGQ1XvepV06mnnpre/va3T/9unWhP1pBG2q677nrBd3wm/h+f2WVzWt583GM2bf369ekkrPoSa+biirvsknZ+2tPSik9+sleue+yRumc+M/316KPTLysLfv/ddksHSNutNQ7uO9+ZfvuAB6Szh7bYpJT22nPPdDnbF1rttNPSuX/5Szp1IKvD9snLvec9zb9zNM+7//3TafOgoC3EA3bZJe25fn1a8ac/pW6PPdLa3XdPv163btqhqLXVq1en/d/97nSRdet6knKnndLvOR+nnDL99/133z1d/FWvmnascudm46Melf565SunX7SyMCZoiD798PwrvfCFabUoodTecN4f/vDUyRjzDg9/eJp685tnvrzffmnTve6VNgF0H/94Wi01m1K//vVT9/KXpxUylsq2cWNa8bCHpfM+8Yn0s3LcparP5/aYRjt4553TnqIdjTb1m9+k3//mN+lMaegDzdbd+Whk5/K77552/a//SqukHJ9xRupEe5/3vPSrXXdNZw1FWCuNLrvihg1p6m53k1baR5rNIbAl+lYCqn32Sefe6EbppHmQpyH9vs9OO6XVmzalv69Ykf6KrBwAdrvutFM6+JvfTKtf+MI0xUneffe08WEPS+f/4z+mU848M22sOYDz1Pa4973Tfve6V1o5NZX+3nXpD9Zwljp/pd12S7sZ0xp4WLkynb/33iP1/e4775wOnJpKK3/ykzR1+ulp07Wvnc69+MXTFOL5z3/uHbEDD0xn77pr+s15521BpgnO0M3AS2nPol3s1rdO+9/61mkl0nfVqrThoIPS7zZtSmf5eY764tBzz72AfJpuMieslS9+MXV/+1uaeupT+0wFhOCd75xWvOAF6ZQNG6bt4Dhtj0teMh34/e+nVZ/4RFp50klpww1vmNbf8Ibp55s2pfMaMnrF3XZLq2N7FvKQLkLu5yTkmjVp3TvfmU49++x03jzKz3677JIu8YIXpFWIABlfos4cgzPPnO73SaefnjbIDN4c3LriAx+Y1nziE9V7bbzPfdIv165Nf51n+b70rrumXWTd5joXEcZW2xpDN4TMHnxwWvemN6VfrVyZzirk2Dq+/E47pVWf/GRahXQ0xw95SDrvZjebtqNbkL6zaHDWIS94wbSzsVW71KXS2oMPTqcsoJ4a1Xbbddd08Otel1bL9C3ahmc8I/1u3br0p812Yb7sQ8jNJWGx731vS/Ip2q9/nTa9/e3pt/e9bzq7zKrO7nHF7343NfOmf/WrtP6MM9JJA7Zxtm3P3XZLl/7Yx9JUOPyI0FvcIk0pRUBm9t47Td3lLikdemjacKc7pVPOOy+dt0Qw80G7754udre7pZWRscs2vPzlPXF4wgnTTu2Km940nb5iRTpzQls+3+0iu+2WLmbdT02lM9m3Bva96s47p+bGaXpk113Tqm9/O3W77DJNpvx648YLfKmhNp9rYq5t2mYMZFR23/hG+s31r5/OHoEDD91ll7SCPgjdB9cMjAUscdpuu41tD7daw695TVojY1G2lZ0XtmpW2vpHPSqd/POfN/2PpdYOefrT02577ZVWvulNPfbadddpX+jvD31oOm0CXANvH7rrrmml7KbNdnkKEd7InJ76xjfSpt/9Lp20AKUVfrEdrYfZtDJZZ8kSUNpulfoPhxxySPra176W9t9///THApTFzxe/+MUvWGR+d1CWLufnK9pmwaGfh3vMpnHwZXYttbbmL39JK0XHbXmKdvbZadXTnpb23mmntPtDHpI2FQzomjPPTFOcj0Zb+b3vpUs/9alpw4htHhydTUcdlVbYGlNrV7pS2uViF0tXHogAcNJWDBmPTZvS7rvtlq6cpa5TTqvPPDOtkInSdWnTxS42nZUzKgqy05//nFY87nF9xkn87tBD054f+1g6P8/YqbT4i3yXsgLaxvvfP604+ug0ZZsaAu8GN0ib9t037bL77qmoaDCr+V3x61+nqf/939TJLJJu/NjHbum0vfnNaertb0/dP/1T2vi856UVD31omuI8AZC77ZamdtstrXzmM9NUFlWd+sEP0pRMm5Yzctpp6aIbN6YrlzUZFqmtEkG/yU3SFANead3RR6eLX+pSKeJ75dxx/BmOy1zmMhMR02RrxWbCYNOaNRfcdzoyjNxD8sZnP/3ptOazn02X++pX0/mHHz5RxH/NWWelFbIaNhOZ08ba1gqRZ+/8xCf22Wje7QY3SN2b3jQ999Pn1CxAkzGz8sQT09TLXz5N7u17wxum7nGPS+suecm0qVErTUbLyu9/P02ph6HvK1emqUtcIq3eY490hUWsGUG7lBpm5YYNadNznpNWPP3pW32+e/zjp7Mbr5zJxbROOeOMtGJznYJNe+6ZVhx/fJ/lEyTWQQelNe9+d5qSfei7CJ5169I+f/tb2ueSl0zrpOyvW5dWy0r80IfS1K9+lbrb3S5117pWOn/ffbd8xurVaeM++6QNO++cNmRbCGzoyDd1rNi0Ka3+05/SlAzEnXdOG/faa2SUb6XMVDqitv2N7udExrpHNh93XNr5O99JV/nKV9L5WSbHOK17zGPShjVr0obNpUaHNnywO9NbOowPktWzrCdO4f/9X+qucY3UPfKRadMBB6TLDtXnm2XrHvaw1N31rtMZnlMyzxDpl7nMtLweerObpfXZNogVe+01nVk3rSPzduCBaerhD0+XuPjF03xvwNtZRpEtIGVjV37/+9R96EPTzqS527TXXmnj3nsnh86Xm4B2+tOf0krbHDNCdvWjHpVWXfva6WrHHZfOn4/smb33Tt0b39iTFZvrm3R0xtvellYdeOAFeuoCmZdNM4Gtnmtjfzd97Wtp6lnPSlPG9DKXmdYH3VFHpX322CPtVrEP+jq99QiZjEyfYPu8TJQ1J5+cVpDlGvm0ua16//vTZR/xiLQuw64y1VZZ3xs3Tq/vVSMctZ3ginnWr9PZd7/5zZaZ6HSI7fehK6zfzduJVn/4w+mKX/lKWn+5y01nqUxjsQ0bUrd5fudGcS5M61772tTd6U5pCvH9ghdM4yWO69Rm52vV1FS69DvfmS5xhzukjXOtUzPLttMf/5im3vvePqt+xYp0sQc9KHXHHDNtP8q20pjbDl3WiEPuy6Q8/PC0ZnMm504HHpgu8vGPp/OvfOULsGzZZouZok2vn7/+te+XgC1Z2Gef+k6MMdsaeoN9bJAAU4cfni51qUs19cnK9evT6r/+NU2p05WTSXwiCQwNsnHVIYfMyR/ctH592vSd7/T6x9whUj73uS0+08HpV7taOmQes3a2h7ZBpuGjH93vtrBLYJ990upVq6q+kGzjVfANv2nnndN6AfPN87ZGveLN5NN0g8sHMpPZmSvf8Ibz9h7nznE9bA/ttEFB7MIAAQAASURBVHHrmS0FAkqm0zHHHJP+9V//NV1HrZjN7fjjj59erJzVD37wg2njxo3TxIL2rW99K132spdNe++9d7rIRS4yHRmWRRXkEeb6xBNPTPdVvDEpP3TEnO8xm0Z5ykpYcg2RlJNPWZNGvTNno9wbayEr7thii69ylbRmjz3SmnGcAPe3hasWpXnxi9Pq/fdPg9WkEIqcgjJtU7FhCmj16rTyhBPSrshFDgKAyBipu7AZqK245CXTKsBIRkrMIVKLo+NfCl6dAtk+viP11u82F1Je8dSnpl3Uahi1nx/QRoZyIN1PerO6Kp5pf/PmIu4ADZM7ZhWtdrNf3fhuzjKbdvRlzNRIo0MPTVP77JNWqT1hy6oIv7o5nBeFFYN8uv3t+0i6Po9QTitWrpy/NWHeRJyM+zhy5bkMGQcVcFDoVD0cZMCvfpWmbn3rtIt3tQ2R428u/M3e/otfPK3euDFdZdWqtMb2Tt+N2hzGjtxHFhdwYN4BEr93P4XAgSZZItaOTEBXRj5Nj7HsjVvcIq344x/TLr/6Vd+PceslmNuMCJ1u5FFRSmSOZ22uwzB1kYukqQMOmMwIqocnSm7sOJzesVUHxxrxzoorqz1y0EHTWT5I6p0ZfHW8yua+H/94PwZZI/e2OqyWEWi+9cHYmZeYg8VqosC2m6lfYn48/9nPns462ymvR2CcrRN1fTaD+RVqplkrAKpaVxyxy162z1hjZ+gs29i+9a3p9U4P7GT86NZ//McLMtgQw763q3pPsgXU4BOJPfLItOL730+rrQc1J8hOCUSBb+tW/2Uh3O1uacUee6TV9ExRJ3GLZs5qReBFYmXv1fTHr3+dVn7zm2nXStZIs06R+iMymq50pbTae9nSN1SgnN5Uvy0yLDjr5Nw4H3ZYmnrCE9LUpS+dqtXi2BcyzVGnc5FXZEpfFJMlZ+Tbem7V7iCzr3pVL+d00EMfOl2TDPhd/YtfpNUcjpAL88imIMpEc8mBOj73vndacdBB04GIRW0/+1ma+vnP05QtlEFa1D5nbtUVqej2qe99L638xjfSrve852TPto7ZPv/SFf6lU6yJWCPuL7PunHPSLvFZ64oNRthudiBtvV3F/tr+v5Cgnp7RR2Q+2dlpp7Rin322sst06rSNs9ZsmbGdndOjdgvymkyMU79QzSL4w9gO2beVK9MqWxhDD7JhMl+RBueck1bZKksH584xIuxhD+ud2BUrpsmuXcn9fNXmoavgSNgotsR6pvXSKnr+859Pk3Wr4CH1/mSp2H7/+MenlXQIHQQjWaeL6WDTe3QB2Qu7b24jY8wY0re2J5fF8q973enf7UTX5vaB3oEX6ISaLTVPPuPZZNo7z4bkZaM8OyNbprdov+tdaVfFnkvSkQwJNMq0iaC9dWX9CW7Fz+zUmjXTgcxdzEXjEKmt1kQ0a5mO9X7kko6tBSoc7kMWgkS3FVa9UFun6OrZNP3gX9A1W3c0Td32tm1cRPfIcvv853vcnDd6gZ2u1fq74hXTiktfeu7YF3HmMCZy48An+FImq7V13/tOBxRXI2dq36Vnzakt1ObMeG/rWlyTtKyvTW1oPOg9YwQj7r33dKB8Gl9ZU+o85c24weWNoLmg4lhzVmIJ8nyxzQcpjLMellAbd/vddOu287Zx48burne9a3e7292u++53v9uddtpp3Ute8pLuqle9avfTn/60O+OMM7ojjjiie9rTntadeuqp3XHHHdcddthh3b87zn1ze/WrX90deeSR3ec///nupJNO6h70oAd1t7rVrbp1jtnsunm5x0IeVbjdNUeADh19ecIJWx876kja97+//nlHB5ffGWqO1fz2t7vu0peeucfuu/fHyv/5z6O/f9JJXfeOd/RHYcf3Hbv+nvd03R579D/vskvXffzj/dGmn/lM161Zs3W/HYPreG/NkbE+6+h6f3vTm7ruq1/tujvesev+7d+67oADZr63//5d9653tY8Oj+bI19vdbstxetCD+mN3HS/sCNLHPa7rXvGK/ojSuR7defbZM0e5xnW963XdE57Qj+9Tn9p1n/hE133kI133P//Tj49jXX3usY/tupe8pD8W+CpX6brnPrf//ZOe1M/9TW7S/+w49fy44vy62tXqR9KaU8epmjMy5EjcoSOMHa/8xS923e1v3x8d/5zn9EfoOsJ2nCPIv/vd/jnm7ZGP7LpnPKOXGfLl6GFj4N4x1/vt13Vf/3q36aY3nXkX7/j4x/dHFv/Xf/VzHn8jC5/7XD+/Rx0183tjZGzJtX4b7/ib4+M/9rGuu8tderkL+bvHPWaOmh7VTj21P166POLd+z7rWf1x5vH7ww/vjx8+//zxjkj32UMO6d/TceCPeUzXffSj/fHAteboYPNNHq54xZnnWn/kufZOjkSOo5/Ly3Pds5wD68McLHZzNLfxJqu148y/9a0Z+XFd7nJd95rX9P8nb46c32efXh5uc5uu+8Y3uu7AA7d+bzog5KEcD3/zjNe9ruvuda+tP/O853XdmWdu2a8PfajXfccd1x/jHjKhf/rSmk/N38tn0KmOiW/ZCkdJj9OMlzWQf9e7eWZNRq118mD9fvCDXXeLW2xtc6xj71P7PpmhyxxpHd+5+c37I7DphYtdbMu5Y4/YpbLRy/rpee97X7828nuyO/SAi07xO2uUDHzgA70cjbP+6DdH1xvPV72ql7taf2rvma+/0r6R4VGNzr7ydP5R/aLX2JZx2saN/TPJP7t76KEz97H2X//6fkwcM36JS/S/f/7ze3vj2HG6tmZfjP82xltbHLFtPLxj2U+y8ZWvjDfnz3xm/x164a1v3fI+5NPv3e+lL+3HVfvtb7e0Ofm4sufGCdax/mGB0C1k+K537XHOfDTryHx5ZuhB6/u9723LkQsOgEVCv9NX97xn3+/o59FH9+up1mIcRjU6YZz1Y91d//oz/bvznbuO35DjPXIKJ3rf+N2VrtR1n/pUb3fppvvdr+u+971eH/n38pef+azvvfvdM7qX/NPduT6EF+i7SZqxeNnL2mP99re3v2t8rU+2BY69+MX77zzwgV33xjd23d57z9znspft7VdlPKvHzrOXr3xl1+2225bY0NyXeCB/Tn7BFf0Dev00hBdrzRg/7WkzcuXad99pnNeUi3PPncFsbB7ZLvUpG0BH5zabH0KO5tpKWbSO6cUhmx2t9F/0D2YYF1suhfa73/VjX5MXPgKd5P3JHfwKb5vvf/iH+ndgZL5Y2ciae7Fj/u7iQ+U+pLE95ZReRszRhz88Lc/n1NbDEmuTcBvbPQGl/elPf+qOPfbY7vrXv/40MXTMMcdMk1HRfvSjH3X3uMc9pkmpm970pt17GbGsbdiwoXv5y1/eHXXUUd3Vr3717qEPfWj368KQzsc9LjQEFPDXMloW2c9+tiVQQkAwok95Sm84c4eEw8lYnHPO5P0Aphh2ssAYjSIDzzijJ4UQA0AXoKBPSBTGNHcMOACcAwTSwx7Wfl8EAAUTzoPrDnfo7wvEffrTM/dlwAAU99xrr96pajVG+AY32Pp5QMc3v9l1V7jC1sYNGJvNOEbjtJTOrH5y8jizt7zlzByXQN9YIhz0DxEB2BjX73ynBw/e/dnP7sE1Iqd8L44u4FU24IEjXDoTwFHp1JiHk0/uuic/eev7X/SiWwOYIbnKx947/cd/9P8nvznJ4QK4SmIn3sn71giCI4/cchy8kzGNtWHMPCv+DtiQq5oMkqlxQIbxesELtvwu5/y1r63fF6gcxwG13q1v90Gs3ulOPWkCnP7kJ/XvAGLWfRC+5YUcyBs9wslvrUMO1GGH1f8GSCIWFxPovPzl/fgBNEcc0cvB3/42Q6iWMnTNa/b9RN6GXPi+9+KokPfyvTgxnMvaO9NfwCiC8Q1vaI8bxyAnI5ApCMAb3aj+efLSInLp4JLMQIrUiLO4nv708cbTe9S+b415btl++cse9IW+Mh90lHExHuSaDJJTpO7nPz9DfnMknvjErZ/FkaTTW/2gP8tmTfv7/e/fBw/y71jrnOcvf7nrbnjD+n0f/ODRzhP7lztrobOA53EcbjaxRtogdsYhjowbuW2NC/0Usj+qIezoasCc7SnvhxylB8IxvMY1ZvQXR6Ec4/zifCw2sPc8dumvf93S2SZ/NbvgYj9HkeZnnbWljRLwutnNenKJHRasefWre1yTrw94JH8W3eQzbAtc4v90b8vpgnPGCfKNatae+1ln1mCu92vBPpdgnHUcPz/qUf36qX3WWMB7uT5A4iDR4IPjj6/LNkwv+OQ973Ofrvva1+oBhMAJ5ipfc8Y3Jy3iyjEzcpBeCBKbjYA16Ur9CoKtvATVrOd//uf63+nZSXwSJEsNt8TFfggej2P/fR7GI3u1exmbCpaoElAhG+Ul0Gceo73zne2+kyt4Ej5HjpNnenJcIlyjs+h0+hmONbZD+tQ45KTgi17Udbe97Zb9IhsCGz/4Qa/HBN5b8jVJK2Uxv/RjyDeynlvYEik1jgwshcYPbcmLeTN/sIA1jMSmn/0eTrU+88+zO7mfG42upTfC50NkHXvslt+95CX79b/fflv+fs89u43f/373k5/8ZJmAWm4L25Y0AcUItCIPAHNOgoQzFn9nCDjzoshYX4CjlvUy302fkCJAS+78ASock4gmxsXp8y8n5rrXbSsukSqgIf8dAMOxBl7ue9/e0QAukJp+fsADekfO+8dYUfIYcYYOiSKqVHsegM2o1v7GuNWcoHEbsqB2Xw4KoJrPoUhX/hkkVZ4BgbBCdlDeDCOFK5vK3x7ykP73xgKINvbASS2yJAugNfZ5Bpn35sTHvNUuRmSUMUV0MNj59zhQ8b7l/RmoWuZHOJ13v3v9b8i4q1995mdAhWzGz0ApQxgRKePVei8XmRnVACgOXp6tAKRFFlvtQmqOahxA2TuMdvl9pJBoUN441KJL5TjnFwIusj+ARuslSMAaeGgB33Bayz4sVAMmEXC1fnDuYh7ybLPN4GNab3AaA0giBTjiHA+ZhOX9gCCESu1ZdA294+/IztbY0CVBzhmjyLRrfR54KqOiQDlyF/Cy7hH2CP5Vq7qNT31qt8k7te5Hd85WL8XFQSgbgF+SMsacgw701xwvzixbBFjWsrYAyVpQIK4Xv3jrfiD4/I2NyUke2VR0ooyooYAOIDuk0zkeMgz0VxYF8hLx6/6y4MZxSM2/edAXul3wBGFaZse1GkIysvdy2aS7yTQ7Rz+NIsnpBZFhxKoMiNp4sBl5Nh8yMTKh9XtI1t13MbCGxq7Dd/oKI9z85t3GL3yh+92JJ3bn+FuLyIxrVEa4DB3zFZ83/9at9VcSGEgXOMw6zQkb64FOynURe4OMzbMzy0s28Fzb//t//b301TqI9cjhjezp/NIfATskWfyOPWiRePkYWj95RlJcCIyc3IVry8BeOJE5mRUNLso/Z65rGRYcTbgucKRgUmBQJBQMDGeyn3BB632uc51eNyF6Wp/57GfHnwPvZJ2OylxEyHsuWYFDjGdOKNNB7ALSpwys5Jd5LQicrQgocprvbCgvdl6D41pkM5z5lrfUZZg+GmfXCp1W4lG/o0+ta2ugJI5KzE62zQccHMEo+onc5ONH7siyviGlZoNVSlnML75IEHfGzTtE5o53GrKv+gwzbk+NDJE57zROhrBG7/M5W+/JhtLJEhpgzxI/Wpf0D7tovGp2BC4qSUD4ucQhMpRbxO+BB3Z/PfHECw0BtfjnzC+3pd8UClfcrtyTbS+5mkf5/mg1chSizfdBqzlgf7X6Fv4/xikZs272Qtvfrs7Kc57T78PNCvA6oWm65slPfzrzO3tYo76U/fxDhQHtbd9cEPWCpi6B/dRqNDiZxwlx3luNJCcqqD2lbsNHPtLXCVCTQe0YNafUgTjiiL4+Qq3d5jZb1/GJpgaC+iFz2UOthkLe1JZQz+C73535nbor5YlD6jbYqx+1KLyjvhp3e/LtfY/6B+qceH/9tR+bzBjjsl6QsXnJS9r9Na72ZptTcuT/6im1mpoG3mWouZf94XkzJvb22w9ezrW93OooaPZ2P+5x/fyosWFOWyczGae8QGU5psyR/ehxcuSoY1nLfpVNLaBrX7uvjaAmwD//c0pq6tnfnhddzJs96GoC2Dev1oJ7lCch6af1rd5CXq8qGjlWHybfQ2+M6ZChU6v8LeqRuAd5Mc61taj2ResdYuwW68hha9npb7X2mMf0dS3IeVn7zfypSaDO0qmn9r8jH3SIMc4ORLig0VnXutbWvzen9E/UeBo6vcpchP6lt65xjS31de39ygMc1HE56qiUnH6mlpjnWdcf/GDa8LCHpU2OobY+yz6q51TWCqy1gSKg0612apA6FuWpX2RAjT86uPaO7AA5p8tqNqmm9/L2zW/29iZvaqiQT/Vzop/mWB0zY8UuGNO8XfWqKalnph7c4Yf379JqxloNLHVZrDG1u17xipQcya2O1Dinh6otx46phaFuiHVHT467ZthL9U4OPbT/+brX7e+lRhcbb/6vdKV+7OnRVlMfg+4cGmd/M0fRYBCF1LXStpdN8eRxakCZK7VnRpzIO9jIgrVE16qN9YUvpBU3v3na9xOfSCvIVqs2XrRRdTTYIrXNormn9Uu/l/12YIsaZPRIXlfE3KjDF/Ns7NhUffPZWKdklW5n0+i2UetxnKa2oqavavjQjewEeVdf6L//u69vZf2oh/ftb6ekHqW1EU0/h05XjHqc6lvVao+qE0ZmNGuT3Y8DOvJGl5VFt7XypLSW3HoOHPOUp/Tjye6qz6e94Q0pHXtsSq95TY8fctkum7+ZqyF9XjtQoNXUnFKDUFOjiv6DSdVZ1Cfjpvmdg2HgOSchw6nGKrAUOwPDjdKPsNkorE/3xHqutcCh1mfLdtA7+h8ynDeyPHRqGTvs9Dinn6l9pzC72pnkiG6Cz8mh8TBm5iSeQw8H/r3znXt5Zms8z3fhl//6r75GlrnWfN9zrGfj45RPupRthBXGbQOn9l1QQ8/YeZb6mk5lVQ+RHcx9n7J5t1HYcjGb9aqmJPsGE6k1y4cbcSLh9Pu3dD+/hU0277DMj3+8NX6Ewx0OQ0fSQbV6ZL4X2C2a9V7iEBg2xx/77dfLK/z09KenXeZ4YuxSassE1HKbvAFHV7962vid76TzP/e5tInhYvgoXAV4a8CvbIA6oGdBjwJjs20MJLLjsMN6RU8JObodSMsBHifPZ3KlS1lxAjQAugUIAf6y2GF8H2hxMhDAEIAjbww7B4GhZwyMhfu96EU98VVr+jF0TOtcjko2d4pwl+RLabAZxnJOFVY0jwqYx7shBRg7oKTsF6UMnAOeNQeL0mdUAiDWGmLRWOiP+TU2Q8q7BkjGMbiMBQebzNaKNiMTgDnvTJYUiyYzQEeLvHTSVYxVa0yBF+8I9LfkIdpQsUhjSOYBcuME/CPjgB3OZ3naDceEwxHOoOL8jC4HU0FVBxDEOBtzDgLQ2mqcnPyUUYXqP/3pGYe11jyXQ2UuEMcakO40oezksAtkCSgsGzBoDXsWUOukKM7+OHIw2zZEgHJEybS5rJyUN+2gWIP5SaCAvWKVdEM5x5wR8mZONPMInCE1OG7enV5GKrSauQswzJFQNHyomK0xJTPR6FQOWgBAzim52QykV3zkI2k9/UgGFFyOgtxALzBczmWt6U9L/slIXuCWTUGUum/eT83P1hi902oK6XIkajaJHqzZsmhsiP7kzXxaS0BunMzkpC8EDd1lDqP4sHkAQo2dE5S+/OVeRwytbe9rTOkb3+WY0btIKIV0xzlVzRwqgG89PulJvXPJgeIojXuMNXlDGrC3imoLtpRk/7vfndJ73jNMYBi/oXEu/0Y/OAxCI/d0V6spRD8kb/QCm+1UUI4N+TQu45B4ZR8dWFJ5z1XPetb0yUnT+rSFe8jROAWl2RbrypixsxygloNPd7IDiuBH40x7v7iXQ1EQJdFvut18uid5CCLZGNeImkma03JjLsgJIgRRw+HnqBt/do/Otl4F5WAqgSzjZs5H2URjaD3AfLXGhllnGvtEL7VaeWCNVspozYZriEjvQvZh5Cgwj8jx3CBtRukXf/PdIX0w6ancCvqbY8EpRecdSGJ8YQR62zwb81yuyIe1RJ9rxhhZyGYP9Z/Mj9JH/h7ruXWPkBkyUSvWT8+3Ao2CCy0SHA5FwAZ5D9N4d3rAoTxwXU4KwTHeOwgz/T7mmB4rWifIOvokDnhBwMPJbDa9bT1aU8gNOl9QEJHkWfQHWzyEf/M2NO7eRz/0S+IAW+05Ls8p7WTZ5lqInJ0zRp7HNg8FC4caOUO6s1Exh7DozW/ek1AhmwhDAQDvaqw3nwA8bWtz0pLsm2Pyb26M08BJ7dN2YCgoAVOXjQ4tZT4PUt3pTr1M6C8ZeNGL0ur//M/p09MvFG3B87GW2463BW9zkyb4/e9/v08pbzWpilK6ywKyeRr0QrV8u1S+rcS2E1sV8tRIqetqT8TPaq9EyqatDfbdS8W0tUQ6rffxGSmtUkHzwp7HHNPXUZEuLPV6KM35C1/o01z/6Z+67s1v7lN0pTP7bi1NU/pmXpi1vKTwtprUY3uU7YWWQlxLK5dW7L1ii6UxKreISNmXip2nONv+J4WYTEcatnR26butbWiR3ppvE5H27DvSq9WHyYuwl5etJnldC7Ujhraq2W45ahuI2hrlvn3zbSuNotC2htjqV8owWbHFo9xWNbTVwraUgw6a6XuroLS/+WyrLo/6MbW5HGfvuyLNeR0hafK2CHjX1hYHqeV50UzyPzRPtvhJrY+mMLXfq2XWKlBtPDWp1lHg1GXbonUtrd12EnWybN8kQ5e5zMznyKZtaGVRfVsxbM8apyD9bJqtgq1xMJYxblLgy22stmjRlfRAWYtD0XpbNfKxiG2e1rRtkD6T18GyDcGWJVsnrLOyP7Z/lHUM9EuaeblFMC5rOd8+4PO1bStxXe963fnjpsm3mrky57UtFdZjnq5ufPXdduZyi4Y0e9sZo3h17VILg07Ptzfl32/VHbFVrrUNlk4zzqEHS51Aj9H1ap8oJlzem75vbaXz+1ZhVVd2kEqztbYcumwLohPn65ASeqX1LrYCOszC58x3TWZtJ7HlMn62JVKtqvjZ9nbbAfPvejd1+kZtv7aNNC8UHZftYpPUPRqxZXSjdyOz5TofqoXYau5D5m3BKWsf2oJp+yu9YSuILWm2iURNRXIX9dnYbrrFdnMHjLDhthLHVrnysk1qLgWKbaNxcEVeH47+s2V4SF/YDsbe0/swWV4/Kr/YCdgTzhmYiwswRG1bdKlna4W4c10CG5aFp110RtQzM26wBExI/+d2M7bdtw5pgWFhuNoWxdDneY2kcZqSA1FTyiEy5jtqWMHJtlW3xkTxdLYnDnh4xCPa2+Tds1KDc6steOTCnNTuAXfE9jQyb4ug7b35gRBs7NCWZhdMXmv6V34W/vWMoTIc7Gw0cgTH6RNbrDxD6fuQM9u5bNmzbbNma+LyOe/qGWrXwhe1moelLOYX+1+roUgvxNbx8mCCHDOPuxW71nzXGNiKSJZgNOU86KNaAe+hVpY6yS96BMaku0p5UL6A/mZ3zQ0bpEwAHy2fG3JTq7WZ25Gh7ZG1UgN8RzapXMeee7nL9eNQwdib1KCbK27aRm2HK0K+I7YdhYAaq2I/QsHit/Bzg6Rmw6RKaNxm8TqlIJ6nAGXuvKmRoU8cXY4qEM4xDdIHIZSfkqcOgL8jODgK/o+sAXA4DeoYhPPg3fwdcUD5tooDutwPCeAq6wYwHOFQAtT2JiMHKPOaM8Yg53uTOQ7hLMbJInl9CI5trcg0UMKgMcjGhVEtnUxOj/ob7ud9OQUUrToFX/pST4Rxfny3VafGpT5GXnAVSA5iECEIrNeKeiLIwhjYtx2/Nz6lwg/wMu56c78AgUgwRImCvn4PICJ0clLRHLVAD0PHMOUOkfcD+BlnjrIaWJxbNaCiflhu9NQPQ5wBHiVQMN41QBLN+mqBwrj0AXg0F3GaEnkvibj8AlaDxFGPpFU41MUxyusucNT9HqFmfQTZab7VkCM3QagZoxr4QwIqGGlsyGvomZBTjnPLeeIMTArUx230QcuBKJ35ON2RbqKLrDUOljVszHK55wy4t7UVDiVHN+pQmOeS6AZsyC8Qqx5dEJh0B8enRZjoFzKrJCUQrKWsmR8y2Jj7TUcf3Z03ToH8UU2tFo65GjDApndB1pXEQNQbpJ+8X14zBjBF+KtB15JVzobGuS5rmnl/9U8QtvkcIy2sf3NXNnOJkKED6R916EoCSk0XBAJZbvXL32qkKT3dqsfoskZifbTaEElOViapK0i+nTw5pG9qxVujkS+6kJ7Tr7xQq/VgXXA0kNhBGCCXkI0B5OktdtWckBHPG3U4B3JqSN+1DlOoNTZs4P03wgoxVmSaY6ZujbXaqoU4acAN0Q4/5EEsc8nhpfvIG+JObRPygyQxvhGIY+fcr1UQu1V7bdImwMCeImU42uOcVsaWGCfrTh/LwAzyib3W2LahQttxmFHUH2t9jj5szTVHMj4HeygIH7JJV5FZ9eOMM1vMdtLhUXMtf46DXmDSvAA/XePExLCJ8JLn5BjQc+CTmo6wXsx5Wdje/ehIuJxuKw+rQAa3gl4uuKUsAu89nSiWF5InT+SqsgarPgSd6dm5Y45MNVehy3yefYfRYSbEDPKA3MKerTpZ+lKz/bUTAfkL1pC+twLoYZvzFoelWFMtUsh8kVG2oUZ6hxx7dknEe7fagTqlLLrMD7tTuz9c6984PTSv8+qik+aKk/SfLq6NH509FDgtWwQuW5cxaQVSzAWfkA+EJIajys+QJXq+dvhFYPkhO0LXhMxa64J/cLUxyOuCCkTxU17xivbBOS4E/RJsywTUEmgXKgIqiveJPFB0FBJlMaljQlkxTuMANM/LlRGQB5CWipDxDcNGQVG4mPb8uF8ZJhy+PEMqQEkUt6S0KBTvRrmFI8SJiahu7WKs4rj08m/AN8XJ8WSsZD/5GaDG9AfhxYAw+sBcvDunFngQwRD1L49pjksGzjiFagG+vHi1sUU6ADAc//KkOu+DSGHUGMZWsVCn9UQDyMvTOPxs7PNnI9rMD7lCQgEJUXzWc409w+79ZQ8AKvo/yhGLhlABigF0shEnVAE6SDvGxVwAkcbZHOaF9ssrnH2gHxHAyQIKEU5AP6eU7HCk/I0Mmm9z7P1yo0dGGUmOtH9HRUmADP3MT3isFTk29sYoSFdRSKCv9h0Zek67I5fey5okQ7VMPzJcOpycvYjW+w45Mi7kVMFccm3OyBVno0Xu1aKqQDbyl26tnbBnTQP+5sw8z2fTVyCeA1LKu3VmTsctLqn4q3mhS/ITeMiwe5SyPJR1YY7JFLKIk2c+RmW1GBufQ86LkJqb0C9laxXhT6k7/zOfmd+CmsbF2qnZDuODcInnA310D8eMjjXnZAqBX3NQyGIOuI0XGbfW3CMcOO9jbDjg1pfv1GySMUY+s3n6Yt34mX0pCX3kw5CzJ/hQOy0pCgAPZW6MOgmvZRviGuf0UM8wPsa3dsppXBykPBuy1pBq7MJDH9qPnYw8c2A9xClWsqXoylyncgDIaayXUVmO9JB3Qyham0OFt+n3cZu+tLICd9qp21gSet5FX8a1T63mnSOjlv0rndG4BBfYFDLrO4gXtg75EeQh3cn+DMmFDK5t1ciQd6XPHWaBiGKL2TprTABRs26RyqU+hgMRQdYxGZBVRJZqNkOW3ZDM+hu8QEbZQzgVgW2dwy765/9kOXAMXIYcrZG/sAysAV/SMTViLg6tIe9IzJpupi847ZEZLMCEqAk7AMsYG38zXiVRB5cMYVfPrgUH2Xa61vtZVy39OORDWOfwyNB6FnSRCSfzDB5FGAlqwyOIqHLO4RljxbH3dxjBWMBYxrs8+dTvrCGkxVAQ2drJm/76/dBhHi4yQffmGTv5hYhsBReQUzn2Y2vInHn1fiGLAjTkpPw+XG59RwYi/4WO479YR/4d5wTkoWZ+rMU4fKh2TeIDR8ZW7YIZhw47EdSwTo0ZGyXTs/yMsbDevHs57nyOUWQcnQoL0SvmDrlMp8LS9Iz5IM90hXt961vD8kHulmBbJqCWQLtQEVDjNiAW+LRQGYWIKEfEk3PMgIvajTopIo6G5nxxlhkJ23GAAGSNbXIUFrDoXv7uCHFGWLTZ72OrFXBTEleMBkVdKg0GmYKJbRGMIIKkZkgAKEZjCLDHkcDlM0TSIrLlHmHgGeqSVWfkhradxOlcoxoHA6CjpClxKeSUNqPeOjo5DG2knea/R1rlGXDepUZUMf62VXDGGdPIeqDUgQ6gkYMpq43CN6+iYd7L3AbRwPhIexYBofxbDnU0jkJk35AlpFPZN+9kHocygMqj4jkajFTtsxzj+czOETkVLRWJqT2PwxHglhyFnFpjZUTMZQ0y0PlWIWMDcFq7jCagG5HfVrYDcGxdGV99qxF4xtY8mW9jHzJmnQKLyME4wa1sJehyL8cfWzf0gPcgf5yPWubKbBpSRDYQcEMen/a0ngCwpZUjgshcqIzPUc5iRPoXonmnSvbApsc+tvvjSSct7okutmbWdDI9gWDiHNJhSCjzT07pFw5ovq10PhrZrx0r73nWUP5763CIgKLTa2QzXWKNt74ns2RUyzNIy4vzOkpP0hsIdM6a7EWy3rI3sbV2nEZu5pskztdqvvXYlvchAspnx21sHWKhEvXf9Pa3d+cu5LHmZFjQC9EQmY5sE8cIhmIfOeu5XmbXrQekVe6YuUd5glN+scfbqiEj6NVSx/vXe8dJfZEFaR3CB97HViakJpuSn5YmY16ww7YZ+sK2JVubR8l/rcEZObHALuQ4D3GG3NdPz6uRUHPZ4mjttLbqIdqCUEFAGTeBzTLbDRaDl2tbYf0tMn3y8Y+AhcCf8UN2IjIaJPicfYgoK8GO+zfwADIA7pTtCqvQr4IReSBT4JYMwzwwZJBxLnYhtsiSixr2C9tSnhKnH+43EJiZvvQHTpVZU/6Nbcj7U7u8M/3vPa1zcixbjjzl6xt+Km2L4KexMe+l3jOPyP88MG2c4WFrznfp8VE41d9HjYFxHbfFKb21+/DpZM+3nuMdzQvfDratZR7B5DACH5DfRZb5EvwF2XHjnAZIl9awNgKszB7/2c/qBG5c9PESbMsE1BJoOzwBxcHkBIrMc36CtGhlPfk8Ax2RaYqG8bJIgaZycQIIQ6n8GhDIISmzaji90mZFCiiFvA5BGBVRVVFYyohBLZ+P1S+PnnYBcJ6ZEwyioYANUoqRZ/gYxFBILSWNdRcZbynUcgsNUFbbPz/KkNWOD2fYItsAEIrIc3ncqAgZZ3vo/uYBMDBfHC/HcwNe5fYZBEaZQstwIvq8A0cpsoE4JvkWKwoeIHrWs/o6C+oOSXMNotK9yyPUfW4ouk8+4rPIhIGtRtPz2wLr+pkTJQBZK83XhZiZryaryj1l5sR2Cz/7Vwp9voasTTIX4wmc5/0KMrX2noAPQAVoIiTIzTjHHYtA0gutDC1A1v3Mu7n0DMCAM+GydmoOAvAk+4qcIqBFY2v7+z3X36wdUUT359A7Fhs4LbctDDVzLO06xoqOQB5HJoKI8qT1dMZttfoVOYlA5jhF1ggntQX4rXtjPWmNLPobEU2mOD4//GG37vTT5zdAMU5jc1pkOCc03pHuRW5yxvKtjPPR3F9AQCBClkGtL2rs0GdIUaCXU9yqL+XiCLfmhKxzktgEMiabQdYF0mSc9/KZfItAbcxazdrLiWrkizVHT+Tbhdk8NnGuUfX5amVdPGQ5fdIa/3GxGn1hvbM1xsDWenrAVpiPf7xb/x//0Z1bEt5khbNm/VijozLERjUEFx0Jv6h/EpnbCBHrkxNZbimkY+lSGSXxzrIJW9spYaZxMqeRpnST94oszrk2Y8UBRo5w3ulrBKLL+5HBCKrAGLZWsnfGAlYxLtYK2S63S8MfdDgS1XNmUyvQmoAt8vvCsje+8YxtiEx59s16hYmQ+LIm4KVJyCefNb6u+B4dX9sKLlsor1MIk9oKBRvU8I01bDxz4sa7ISwREjle49zHO+YXMqax3Xteg9jkC1ngfdggGNNagDHMiUBZ3i82/la3mvkZ2RA6wO9zQgOudt+crBFYhNXK9Qz3kM9a0DUuGIoNEiiHM0t54SeQiZY+crEf7F0Nj9mZkRMexiIvgSJ4jJglc+QN7jNP5JGtgZnCdrBnCNsSm7vfEH6mxwT8hoh9MjNug/mt3xIrygC2Vq3r1nNkjEUNKbthattt6Y9cxhGQ1ild4N/WNtxa9lt50cH0FR2P3BIw/M1vej+09nk6YnuxlRO2ZQJqCbQdmoCiDOxzBcDKwsyAWAmwALAamYNkGirqy4BwmhmXGtAW7Y7MANtuKEMgC/DAaAMkDG95X6SHvyEdRA1LRptT4d1qW4MoVNFfz8j3diOyGCvGhpObR7OBhZoDjgAoiw7nF+BVy/oqPweMltsHW4QHwIWUkCqKELT1AynIQWHwGHRR7jzyQLG2CIRRhdHzxvHN67MAEZwozpo+epYtWkAy0iKPsjMetW0PYZzKYtS5oWlFOIGs+BxgO1RM/h//sdvEmS3HGZDJ748IGyqUPul2j7JZW4iaWGMASgAA4AqwsAaQep6Tb+8D4BjZnJjMazFwSMpCt/kl02pUrZVaG1WjKkAOgx1bLfMLoCCzALG5RgRxdIBAgAUYA7JaRWbJiHkpdRAiA6E8SQQ8Jy3LC4hbqEbXIR/KZ1oTdGC+NqxV85jXi+OwAWjm231kshnvOWwLqtoHepoekZVpTshqK4ttkqb/5lCf6a4cbJtHemSSehOTNGNEL1pznErZtfQNh3BIrukx765fxkjfa0XI2VDvNor4gCdsQUEAcSTI87iOrL4jiGLcAHbbOEYRpqUuE32XWcZm0N8cQvoG6GZrJynmvVCNjSttOnLGthwOejn+SKRxC/Gap9C3AlmCXwIQHP1dd+02PuAB3Xm5vMMviMewG2SV7NB5s60FpVnLtcwalwyGMntBv809Oxu4xXuwF+6TZybDMqOyAYwxkiu3mbAMXZ8HsyZtsFIEDJEd1nq+ZjjSnpsTR+xaFCsnj0gBNqHMoCqv2TqAtUM/rIkgOxBiZWa7gJR5R0gLFpk/zy/lztiFjUV8WKN5ANX//U7mY+2d2IE8oMoWmBN6q4VLZIuwrXCrsQ17qB8wuM+QHTizNZZwf6W+17wRUMiWWqFtpIQ6qLUszzLr0dqTLWg3BKwD88XffA6JSEeYH/gJtmplaJonY5UfkFD6CaEH2A/ji+QiJzCL+SMDLfIGWUS317Kn4iLf+Tpga5UHgOXp5sC3AnXshowbdpLtsO5z3dAKmFrfrSCHZ1ufOclXXpGpOG4j89YFspAeM4dhG71fq5+2gobcy+gzj2X2UWyHtUb8XaY9ko6dhpfIw6gMdjJSPhtBaE7zmsKuy1++J2ZL8nFqqtvEJoxTD287bMsE1BJoOywBBUwjDCiwqEdQXqJqedSA8agRJEissshhXJwkJBCjDUzYLgfoltsUnPAhCwTgzCNCADZnsWa0pLBHJgNCJI9EcGIRLogeSk2mSP7dOFkmCCeAiJKUZZGTcRQ3oBI1XUr2nuFhIFq1k6JveeNQ5pGquKTnItTK34vUBiHH+TCejKYsovJkDn1nTDj1thXlc8SZbJ3ERIlP4sAzIuTGdiXGUPYGYFQ6BqI0IV/GsrWlzcWYD41jiyDLQQvS0bi07vEv/9Kdt3Zt97cTT+w2IiYBGd/P5ZHMAxjWRmtvP2ARpxTK0BjKGsyb58jwkfnFwAKGCDGOJbBUAhlOah4h8xw1EkTGAKxwRKVik0Myr0+1/fyeafzNE5026Taz2slB+QX4arUMJlFK40nOYn1y+KIeAnBl3beiif5OfmVp5mvcliIRzChaOW40HPDUnzxa6PnkdT6KcYdDRbdw6MmZNRP1XOjDkHUAi2PRKsiKoEDUAcKifGTEuwPHfga6gFiAbxYOwlb2gSzmRcFdxqkWRZ6kcQSQPpwpl8xH8mxOZbKOU4R6Ns2YGxtZqpwv5Hj+buzLEDFfI5rJLVuAaAVYrcVR5JNmLVuH5TPoxnFJKLbIZ8n6OCfwkJ2S2Cfr9BeHJiLzHDvZA6O2zS9WM2+1jK/YgoVwYr/Zbo7IJKcRtYJAm691b3rTlqcGs6nxdzobGcBWI4Lhi9mehERXt2ye+SjrUAVZGrgliCP3EIiLQuHj6vfSGRQk4ISRZ7plqOA4vOBZPiejILJQEQlxkiS9Aa/Uig7DkuV2WsSnNcKO+QzcVhadnqtzHE2gobwXrBIZxdZ37YRZWXN+nxNqfoeMtCZlZCDd4FMkk7mo6Re/K7fHxWVOymLOMJ1nwsjwa751EO6jx1qZa+aGrArU1A5/yfV8JWOObTj11FO3JGUnbexLjknzwBJHng2sBbnyjJf8onttDbMmyjliI9lTursMzoQtLccHfhDIhcv4HXRKjdBG9pP5sNfIyNa2Mj6NddLysVz8sPzE2mhBbNMtZe3W8BfyJAE4cmidDGVBeYa1XKtzhZwrtyPDAWyQd5s0+BWkd17LDJkO38FlefAU+Qs75fUTzSl8aw4kIdAv1gR9zh9B3pGloX7V5gseLXfhxHXta/e6mB8miP3MZ3bn/fCH3XlzOXlwG7dlAmoJtB2WgGK0kQUiPC2FJQKVg9HWKQ0AfY3YQJwwHjXjS2nnUVZKxMkctfsjp8JxLe+fR8ds/wpFRcHoF8ILow6w5sy26BYHKNKXpVzKKom+GhtOmHuILBkHToxx81kOP0POeWKoho5/LY/YbtUWYjSBjjzt1PsgFvIMK06DI3Xz03RctoeIDjB6FHNerJHDYQz0pXQuAfpxQJwoUg7Kga04yYTjXmbRuWzLDFINoRmFwmvXqAwbAKHWAO182577lISjC4n5q1+NjuZFyroCpLXMO8DZnJRp7KJxQyQeIB/kGEMH6EvtRSZxcJAo1gFHGeBAOOZOKWOXjx8jzKG2xrxzFFBEeJYOZ9SEinppLvMFtIxLKhiX1l540SggTh/L7BDAoJV2DWBEhiKHq6aPgCLjYr1F5MpnvXO5dQohNwTE8+a9jVkQd0Nb3iZtdEVJNCCNgDzrP4rJcxjplqFCqNYXpyBqKwDb1nGpc/wegTdhRG6L9aBvta3MeSH82TTjXCNz/W7UFu1WA9CRPr4/tAWTPBh7xC3SseyDKDNirDX+Q7qRDRs3Y0t/a/okLlnE4zSyQxa89zhkqbVQBioAdmQDnQXIA9ZshywaOnuhstDysdB/650tpP9qhEkrW4Me8j36drbbZVvFcvfcs1t74okz9sFYxFoTXRfRL7/DsZ9kG3A0xOskR9HnW3hhA2NAF5g/xD9sMkmL+jmBK7xfruOt+TjdNW+I49LGBk5yxT3IWCvo5VIGIRzFyOoWVAjyxfODjJptsfxWo39r5B+ZY5esi7IsQotQ0092LAqJx+Xdy7WXX+7VOpzAeozscbYaxoq/wXcIKbaf7eBwj7J55NlYDRUsh3tLAuoPf+g2fuUr3caHPKTbBFvADHlW7rgNsVhuN4xTpGPcSkwb+rk8VTi/YB5jVfoZsuly2UDyID7i5GB4i7zlAStEjPdvZQshSMqT2eB2uxBsp475EjjUJ3ioPOm7vJC1o4i92DqP/KZ/zEGpL/khQ7pEoLWFg9g4+lA2l/cgX2yiwztyksVYwQAyumAtsougGmebb94QWtYf/eYZ/h/+BdI277exk/UFL/ssnU8PsuXeuXYgAV8jTgavzWXtdD3+xdA2xG/M1Gm0PXvRyxbMc1smoJZA22EJKFkb40SXKKRolERtgXIiGMPy9xR8sNyAAsVPgUZ2ichFFCQEaFrHnCIX8kKk+QUkRGqkKANj5vMUFseNcopoBbDGaQUq/Av8MRScY/1CBng/W8gAOg6viA3FjYgKsKKfAJKMD+/O6DA2tbFhWGuRceRNjSRBFPgbo0q5lgUZA5hIC1WTIB8jmRLAG7IOACyNOcIiTp/xNw4P0MT4DG0jYEBtD0JqyGiTqWPe9C0AdL7drzTOiA99ErFGnLVkbdQxuuSl1YBekSSf42h6PxFhY0z2vCsZ+/KXu41f+9p0BtS5tagTWcydgijmmAMnoL1FODLaLYco6j2Islkv5oh8mM+4PxlDqgBPjoTPSVr9H1qryAwZgWQ+jxq6J6NeO6obaMvX+FAz57VUdX0HiDTGvtwCyYGpZTB6tnnKt9QB02UxVVtYAVDEaWQ8Wpstx0ZkdDbO4KimZgTw495IHo5pDTgCbGUds5xMq+mDskA1GRHpo5sQ5XRCEHWco5YTYb2NU4SzZR8Qnq3Tflwi75M2Dmar0K7L3yaNonIskDmRkYsApT9KR5nuMpY+g+iVlVA+HznlRMayxqCL3ZmvYtQchto6iItuHEUemlvvELbIdl34ZNQ2sDI6zv4NFVaNbMaFaPoq+yTWOdtMH5J12IADxCbRz9ZKufUhCOhx9Var0a2i5Uh9No0N+8Qnuk0nndT97NRTZ/CSNUHOXEOlBvLtMJw6NgmxJqu6ld03VFi+Ng/kWXZG7bP0/iQHY3Amg3g1B0O1bDh+0ei/WkDQxQbDLvEzjFKTeTaDPvf32OrHqYxsLHaBfRCMI9+h90tdN+7BLLXmuSWZKGjAVsqCgnngpTwzVX9qWybVhBKULH8v4DREPsjwg8VL20zWzL0LfhGwDXxTu2DEcUmhVv0bF7uS2zQ6q8wYjfed1MbCP+V92LhcnmVClRgRvoYha9hQxiY7bL25Pz0iYC3okGclWnu1A2iMc1lnrdXoAf1r2XaYkF6Dk8qxqR2EFBe8OR8tL+NQXtZVTTewu3ng3WX8ZQPRTWU2OfIpz5iEtdlv65U+HqeWobEps/D4UdY58tfay0s4ILkEKhDsfDN6ilxam7VyBvASWwKHsu3kS/9yIk0fBJjHybRLGTZdqIO9tkFbJqCWQNthCSggQeo9cqa14KIAXzRAXNpn7bOczDLrAokjUkShyMqJLX+MTmwdoiBkyAwdT+5iUMrjZ12cUIrXswFqjiqDLloQIEk6ee2kMH1g4Dl2HA1AyT5ijkp8BmlVy9oBCPLtAaIYlGSQRfqiT0MnNjEIsZdb9JBC9S7kLY6yzrPOGAljhWgAyvPjTBFiCDgZWWFMgDaEVG6UOFmUs/f2rFEGw9/L9F8ATL8BAgAbmBw6RYNxMb8U/FABX2ASaVT7mzkYtc2BgQFigWXyzRllaDgxxkE/jY1o4jWv2W3ksJZOAacBcZqDRu8rCivby/gO1Q8aKkqoXz4j1dg8cJpt3wgHGRnF+eLkcPRlK+Vp06PWiL5FlgkgSZbJIYPcKpIfUepRhlQkCVnrXuRcvQCy7rvel+MMrLjKGk0t2UBIWmt5lJl+Mf755yJTwZjF9giyVEZTbcUBVM01UCTKNUl0PE6DsbZFm71XgHFyITXc+4uUyRwBbOKEvhy0jyIKazWmIvvPWkV62lpAf3FMZNqZ+xgna70W9YvL+8/WPtD3Q30HTCdtdEjLaXZZa5MUF/fZqMvCviCiAEy6BdGSZyEiMuI5ora1gzKAYfKCCDZ2CB6/Azg5oXOp8ZM3oLnluLtE5Ye2ILIJtSwydpourxXMpgetAU5Onlk76sALTvh8Ns6bCDI516dwuNkQgZby+HTrgDNCJpE3AkGx3q0HNnA+Tt5Dcnl+nmG8997dug9/eGZ7BXmji+m62Fo2dAIiu83ZzYl0hJl1XRKk5qZFSrILNZvH0StJYmPDkZxUVuM0SkRMzZnLCYewEaNIM3ozghDseRmsgYusV+uRHRHUMMf58+E6dsS7wgU+DzcKvMGMsCSZnmv9FWsE+S9rl7zRzXS7PsCbbGp+8iv7XKthKeBZq2sjY6h1cECMhXdgX+ACNhE+83NkNJERNmWo+L75scaQUN7JRbZjuy77HUQfwsZzynvAH+UJYEOZuWVm/6hGlsvgVJn1Drez4cYMlqIv2Tt6GO6iB/TTfMEA45Ju5KtW7N2lqPuojE/rllyYo6E6rUjV8lAXAUkkNP1ey9SZ7fbdsvHPYJdav8hnLcgTNeVq30Eu5ZlNSL78/nQiDJ2vb/NiDlt6SB9qyQTsQATM2TNyZwdHHJRRbmGkBwSNSsLNzoLWabP0SY7TrCvBZDgW8cymtOqPpi0zyJYJqOW2KG2HJaDi1BEKNTeogKFMJcbFiXgUVFkgr8zIkRFE6XD2KSQgX7YNIgjxFIZTmnprmx0SqFZYNAfEDCmQwNEEXDimed0BfdUPClUmUWwl8U4MnW15AQqREEiFAIucS85vTsgBja0UeY5qmb5tHJFCwD2wrU/GjkMEENS2GAAZjKi+AzcBzN0b2EVQxM+iOwCLKACizVhHFFt/kHvAS350qdpcPoeMoNCB1Elq/5RFMvXD/RgGcwZUI7q8cytzAukTRByDVttnTV7Mr76RkZgnz/POk6b45s08M1TIO0aOgWIEvUdJFjEysqai1k7Mq3uIyujXUDTLBSgNFT0FpoBbQCvqKnEAyDaA5p2BLNmJeeQ5ToxrPbfcFsHh1G9k49DWRxHWUdHMPMNNRBgQQQZx+GVqWTvIGc4lEAsg5GulBv7Ij3eVvp6Ty0gdZAA5Qc7mpzcaI/qnJLW8n3Vcnqzm++NkBXDg1ajLvxvbVoFXUViguJYx6nPmNJehIfmgi8qmj8ZVJma5ZYNOoOvIrvEaRR5MSBJtYR/yjKHZnLZW028Iuji1sXYhFCbZRhXja9w5IaXjzKGP05zyLUu2gtaO6QZwQ4+SQ/qMrQJGET5DtZ2QFGTHc0aRncaidUy4i5y3vkdPWWet71qPAa7pUIGTyChmNxAsfuf/7Ap7OrTdYD4xj3vF2iLjMEc8B9HXqh+Zk/lk0xqBP+azQDrdWMsEm5rqNubb2aw9emkog5cTQwZqxa3jikzRsg+lXhf1r2UycuDgBTLHqSSrbFmQ5fnWXoRlLcs3b3GyKQK2FuDLnc1w0vN6WC3ZgRsiwzc/pVXWAftZYif2hTzSPewB/Q4z0KtxOinbaP3AOQIqsNlcMhCsXeNH38KqdDwCKpcHOFPGkCCm+YUTaxkwyO8afkVWRNHkuRz8otUCOUgv9oDtE3BhM42tte9dYEWyBbcgqcgacoCe93e6AF6HG0s9h9AYwg3+FtmhyGByx8m3TgSpanYXns3nPn8nMmZu9VUADWlDjhAhQVIIBsqAmSTTb5z6lY3T/7YKKsGOQxltdHTrxFfYwVzR1VFHzpbXkvSbS6MbrJ/Y1gkreU5LZ+Y1NWsXPRKNHxNbDOOk5VpWvXVATwcZnzcYNoIocDV5IQPWcl6XKU6Ktf5bMoiAKvXI0CE25KpW39CY0dv0TV62JL9udKMtgjy24J188snLGVDLbWHbDktAhTKg0OMoZoaKwyq6HAubIuOM55E7ixWQkvXEiaZA8/3nQI/PU3p5DQeKpnYUqUvUOT/NIr8YoNw4Umq1yJf3yU9cA3Qi4g1kMbaMF2UXBky/GUXvCZTn23oY5VYNCu9SnsyBlAnFL6pXGgPRHMx+WbhOxKRVd0V9Go6WvkfUKk7vQzBEdI6xljXD8QdM83voJ6OJCMwVMEApswJABBgo4IjAmzsAXIpzfi+ZZOaJnHAmpGczUj4LpNXeAQjKgTCyA7HC4YrMotwIR20eW+6AmrmcxmOsEUeyavLMthgXpJ93BcoAduSR3yO9zLGIDvCSR4mGTsfz3VYGFAPOEbd2GEog0b8ArbTx2v3UagmQR1ZbNduAaM5HnhUXDp5sntLJY6RF9EQUjcuoWjLlFgiyXtsuB7yTResL4AKAEIq1bQsI7gDRshAAjlhT1oyxcR/jGVl9SE5yg0jNCc84Nak2NtZJ6AuyF1sbgnQz/63tDUinqNtlzdWK6boQf0FA6HNrO/FQTSHR/vxEx3wOyaO1qM6brIVaRmdcE25L2co+5Ccs5hdnskUEc0BirvIMJL+je8IJJXeivuYLGEcgcf4maVHHybjUtuZEthxC2xznARa2LK9Vp2+1uiMl0K01pFNeg8z4kOMhp9/45QGCuASDWiQwvaw+T+1ggXw9Ip7MYQmic8LSmrEe2LVaRD7GZNIDClqN3c7JFWRCvnVc31qZCS5b5EY14013uxf9yFEYh9Aks7XivpuvTZGdEnbEmEXGUO2S7cJWDdX8Mea1vhknskN/I71r68zv2CvZzzAA/ZrPE3lnj0OH0pl0+xAxytZ67tBactE7kXGWb7ErL3NJXt0XLrCVnJMZp+YiFGoOIj3AFtlmYx3BiZxj+Kn1LPZi3ML9tcYGBM6jL7x/SZC4kLcCqfpDR9dqh7FvtSPjXTK9yHFun/zfu05CvNOrJfnFRiLtyEyemePetdOA2et866o5Db2P3CSH9Br8RbaGThSWOUS/G5e8jEA+biWx41kIPTjIOOennMGVeW1Uurp1CAwbMklB9KGts+NsOY5i8fRsTqDnl/eoEVm5TUfOeHekSmCJnOSZjzYq6F17r3Fq0LFPQQbTY7UyAFEU3Hpn56x/OC98HnLlc8hQvljYYmukRu4PEYd8nzK7cGgnRkn4kn1+h3c0B/xCAXWB1CCT6dBjjulJPL4BffPpT3ebHvWobv1zntNttJbm4p9sw7a8BW8JtB2agNI4npwGRgfLn2cu5Bene9JmgecKolX0k1GU3u75FFcOAPRn3HoUkS2UgyFbKiglBgt4c69wtqXWAziiVxShz0V/kUWUUau2kSwD0THPcF+KEonkO5SVMW3VaZH2maeoUoKt7C9glvPBGOfOvrRXih4wYsQpzwAnFKg+iWgy6IA5A2yOgyhkmIx5/izKViQNKNJHBEX5GQbGOwKkARzdmwOOIOMAIHwASGNpThidPMWZw2CMcrIQURGpu4A2Yow8zDXazWBw1gHAllFCdOkn4s44x3G0QCn5yCO4YfhaBACnhUHyDgyWdwLqIv3ZHJCVKP4qkmtdtNKgORP59hpkFNIuotXIWQA/gAbgkUeMOCk+m6fSy3D0M8Av08O7I1/NHxlmVMuU9CjY7+J0M9oBRsoLEAZ+yJp+xbaA3PEma8YmB2Yc5zgOnswGUcMJzLcM+K6MvtiqJzI9dFS3z3s+4i/Xb5wz75r3I9cdZBLJjsDQv3z7KB0lo8bYBjkWtSTIcIuMtZ5KmbbeADQyUiO8bTGLsROBlcXSKphJj03olG1lH/TH+ozaO97V1oLWdmIyRz4iGup7wKV3CpIRCUqXIXsEG6LvHDHbdCYhPIIwqjk9tdoa5j3miENjvZE16ztqArbu4SprDcVW39qa9V6jCDW6wRwKCADo3qdFPpEJwQzkY3l4RJ5Vwk6xOXRmOSbWeikrSAA2vYwuc2aHto1P2pDR+f05XblTMcphoI+GGltu7edZK94VaTxqW411yIluPRsGyOVScKaWKRnjGSehDhVMpktmQ+6Rmdqpfcg99pVM1raXuuj5IVJUAAwGQbSWGaQxZ3k2lnFrbSuDeXKcyV7pe2wLaxUUp8vzTCF2jf0cOhzAmEdATZ/00Tv43TjkBF3rfUMGrUO2sczQplNlTyMeEJ1kuiQu6TE2EcFLL8TnZafBtNa3eZI95vL/2ZwoStfSrbAenQDfmou8P+SzdhJtXGx+6TTDwoJgQfgYFzgHjmzdh56L06NrmTCBFWonhZkvuIitijpcZCcKaZPrMpA6TjZLqw2RpjJmR2WvxlZuuNs8y2DKdQ58QJ+Wcwr7jCoOvpD19kY1676VFGCbfx4YhufIm7/JBMzrNLkQx2xNLUjHDyFzxllQt7RJ5IifU36vZZutUbZbhlQeiBzaMpqTffQ0DJ6/e8wTO8un8Wx29aEP7eWbfa3pYPdZgiTUMgG1BNqOQEA5TvgPJ57YbaBMhvZMR5HbFnCatOggEEBRMJCyFoCD8r6cEQtf9Ei0BVHAkeM02GoxSQ2XFlnEOADaeWYKYB9ZJzJ5kDmKkIfRk0pLwSIgyvoUrkhxRlhwIvK/UcD63triEA76qNMF4+Ig145YBRKMG6MAfOVgGvFgXKP2CiXNeY3xLEkVlywQY4iQMWYiWOWpUd6bYxcECCMQW9LMMyIDkKTo/R54AxaAcmNC8ct+irHh8ABPQDIyBrjKiSmGqaxvMknzPDJVGsv8Mk5AEEfYe+cED2OUk3CIJ84r0qbMSPBZgMr386i/sWcYESn+LtoTkXRgtdzmOA75G6QOQFqefmOdSseXPRWnpfk/Zw4Yzk/i4gjbAoWMMQ5AJ9Ds/fJMFmuSsWZsGedRKe2+Xzayp18canUdyEjLaSK3eaaQd0JyBAlrjZE9GQNkCyHV6ovPkuncMZcpQC5yByTIFuNDRskrogH5Qy6iiClZ4ayYQ8/1f9mHOVgDupGxyBjf9x2AJnc+/d84Gn9bht2jpsOsjby+HrKX82S+Yruc95DCPunWhKEARZw2g5CoReo5rt4h6jGVV4C4GFeZVa0sHms/ovE1x4wtiWwU48z5HEVeGP/4LhJJlgICUqSVbHGMjT8d3qrrgYTM54zjhPBoZayyJdZYrXC594taaRpSwPvGSXq19zbubBfHsMx+NKYcTWPn74ioWgYdJ7KW7QRUW+/WBqfav/OV+RSt5gjTL5FxyE4NbWkZReYNFVQelQlILsqs2OzaxJ7ViBvrQbYMfcKOsf/kC/FsTURwpnbJRJ3NtrFaAWUXnUwXeH7rmRzlHPtwlhAgMENgOttl4BAYMK9TZguzOSjr2iAP6JvQqfQy/dzClz4PF7TeAwGVn9CKMJatIHDYei+BhyB28gxWuoFeHlVbh11lm9kBZDSSnNNNbuAc92Gn4lh35JTvsCf6BdNaWzL66GKZ3ggqes5apFOMn3vM5tS4oRbEnrXDDuVZnflhHbWLrcgz7MhtWbcxLgGE2AKXXzCR7ZDGqVXXE7aB/0cFRMyh7CfEmHE2dsZtyKaPs22uHC9B4/IeYZdGNfZcv9h6ss4m+7/sOXqZnattT7eerM9W6QQ4Z0hO2QTrlJzZncE/mYR4i2Ao7FU7JZFNahF98Hu57s0lAomNKwMi/JBadm+Mc+gg2FAgO/87PQo3l4F4GKK0zcaS3XZPdg1+lmUPm/t961RJfkXIYnnSnov+amGZV7yiXV9rUlncTtoyAbUE2pInoP7yl24jJShiIs2aImNUakVfW1vg4ppNZDS26jFUnLr86HqEE+Vcq8EAqIybYkvBuk9r60iA7dxB5KjlRSMBEY4xh4vxi2KTokkASZkZBvRTqLVTwTyrdex8XHnarXEdOpEIyz+UJeVC7kW6Oqe09XyAwL3K7BVgmyECuvLTINyzdBqNcxQeJEvGAgD0fUZBxCA/XUZGEYAmwsVAIB2QW57DAeEQIkhapAbDMVSHZVTjWNVOUoqL4QOyY2sAWfDeHFNGGMBTBBHhgcSTucCZJc+MH4KQPAE5HIFGTZHpOefQiFzmQDyvcVS7jPFcWmSMIFjz+iSABDkXeTKHJWHKqEcWgXcLR9XnRjn/o/oMRBlzfSuL1AIxdFY555xxAB8Z5vvAGfDsc0MkHlnMTygyP8Y8Mi2tlSA9EWzWO3IZueW7iCGywCFSKyV3ijif4XzI8AHGcz2jv9YFYEP/ugfCgUNSK2jsXmUWAicTuC3nxxpGIBgPzxwqYD3QJi6oCcxaM4iEKKzfWrcRdOBQ5gVn9R3Jr//GmDzR4XQFYItIQYYA5zIGpOyrM0Zm2BS6w3eGioYaa2MCwOurNY1UZM+BTVkKUU/Ps8vMIeQToiqPbvouEkF/yuhvnOQm+4Z8hfxaQ0C3YAHdwR6yWf5u/PQLkCZbCJXcIWEDgwDX1xwEi8K7J3tFbqzjMohExq1ZOrssds2Rsk7nq8h6rdXkgwNv/mQ1iihbW+W2pwg+DBFixqZVP8oFa4zaWkynNQJFG4P8Mh+ycegGNspaIxN0vv+XZCNnpJZJ5B2HTnKNRj9wlCJT0rqsEfXGj64SECqLOdNxdI6gin7LsoD5kDVkN8Yb2cRmRdaPYBt9Z37ct9wK6L3di8NNP1qn1iMM494IdESO30Wwy7sgSNhOn89P3IqrdhiONVsLvOVOIZK8VhTchSAZOl1Tf+kPa4d9j+3r1pNx5aSyTYJixomc5BkZxth7GTN/E7Sy7mvyRMfNZ+0yLer10WW5DaVD4anWuME3OSlEjlsEPL120kndJkFCuNbl/4KCAiHIqbJ8gPVNx8E4bB49RY+Sh5LQoHsQUOw5GwfrkmV4ZGjbXK02n3diK2Qf03fl340Xm4H0MZ+IRRiePLMLxmFIF7p/vn3YBZPH1koYMw+YCzbAB5GBXmYaCVZ4dhSht4Zyvww5RDbL9eLd88Npas132Sq21JyFfNcC+nSkcYfh+TtslHWX6zXrDHZkx4wZ+1/qnFGnyJnPWHc1/cgftH7yA0tgqpIcJRsSF9zP3/yfbqGv6BckJuwBp8lC9N4ytoy14A8yMd86H5d5NE+Ck8YLxne95z29Ti/LTZQE+hJrywTUEmhLmoCiTEUgARXAgAOKiLIwAd0yutfa2+wSGZpNIWiKMmoQceRzMoezlme7tNKrhxojEwAkyIHa/USsc+NXnigGkCEbGEtOMeMUYB+j7mcRvIiGGU/9rxXeplyHThcs027NQwtIM/BhuGtkl4tjwUCYH2NhW15ejDouEQKKkjLNHTdAKt+Ln6exUroiPBFlMxZIi3g/QIODbTzinrlzL7ODYxbRYkbMO3le7hABm2X0hEFA1gAN5HWSbLi8cQCHIoKcsHL7pgtgAC6BGY5dufXCeDJ6xofsIaKi1kUOxhgxYMw9gFBOiO+I4EZ6ch79LQFOZLVEgVmyOwos5Q2o4Zxag/mJPsac8z0kqxEdBBIZ/tgSYU5b9RnMNZDRakgZYymiDMwCdSLLnHeghgPDaYr1CjjqBydJNgiZKwt3InRychu5DGQANcipXLbUDgFI4mcAgwwDPhwMxEUeUSaz5BgYyut/0aXmtQSIIr8AtzEoT28JXdRyrABW41A6MeRK3/LaUt7RWp3jUcBjE1AiqPQtQoQeRyCVNcdc+g4UknG6xjuZZ46cv9FB9KiMTaA9ivKX9/F9keb4mX0K/Y6cQG7U0vZdHDMyizAIvYboJlehm8hgbIUlE3QSUoqMc2QAas4cuTInZAwJhAzIt1dHkKLUD/QcR60M7Hg+oMzhIp/eBaDnNJJv74y4i4yvPMtHdg0ZtBbpG/bHdyOYwinPM4rMA+cX4U/O2SwZnJxzz5/t1vpxtw+Zg9rcmhPjax1zvOjfcAoiGJRnYNYaB6nmSMQFZ7QILLaS3CHnrKvcAd9tt279O97RnUdv6kN5XDebiJzIT+GLTDaEh99b375H1t2fbMFCdDcyC7YpT/HjCMIW9AodQjfTexwm85j3AfFIj5h7Njkvb+D7fs85836c0Nh6ilDI72MNDtW1yuufsTd0Y7n9ju2it8ttWPSl+Y2tddYB3Z1v545LRnaZJaLfyOPcZsVFD0Qt0lbfrYmhwJXxV7+I7FnnOXkER8UBPQi5uGcry96FSK7hroXKkiCfsBgcBfPluGkoQ5nuGMLC5Tr91Ke6888+uzvrhBP6XRSIXzrJ+NJlZQ09eiYOnYBr6Ri23jxa8yH7MIxsYzYssvf5A2SXXTE3rVNDYYScXKRnS1vrXjWixtpnO6x/a0wgCJ4hp9ZfjSikx+jMEt+xDd4XRvUeubxZz0EMworWiIArf8w6sLZhIfY0MAScoW/069D2OPcbOjmWjilJHnJBlmET65rezW2+/tJ3JWlPPnK5tkYEJ32WDoo1M4qAgjM161bGYf4394CD3QOmYk+tbeMDvwsQxXfMk7VaI575C8aPbUTAs31hW+FH64SstLArfBWntdJzMMgTnzg64Go8llhbJqCWQFvSBBQFD8zWtgtQbHmBOY1CqjHTAR7K6MU4LU6NAnwYDUAYmKdkammQtRoe8S6MhO1LjBNHnJKOAsGhYAEE7xz7kBlJILBMc/X9POpKcUU6fhRHRBTkDh/HGjjmSHmPIaVEcbWUXC3tllEsC0yKijMWFK53ZkwpwzxSb2sZJR2NASxBmc8j15AkQDmjn59KVTpUIkhltJzBQxQAWQwIgyySahxEUBnhICpzIpPhiHHgbAErnLwyQleeFGOczQHSVP/dA3Ais7XtLaOasavJtvklW2StFpl1keGSwOLkkbUACPqpb3ltKDKPdJI6TTbJpPsgJnyW/Ps8oORdS3nx3hzVOFJdTa6QWeNMrsc9vh6oIBtxRC3jzEiTp9K5yS9OFOKLUSc34dyS1VbdJeCqdFDJC0AFtAT5A3QgAGR+kCMOjMwY6ysyr7xfWQjfhbwrCWr3BgTck65AJnPI6bV4RxkXwJf5iigkGUWQcESsnbyIMwIy3pPuMW5IQUCOTLUAIqJC9Lf2N33JM7LKC2HJ5ngXawxZ410j2wswj9pio0hIcwdwDZyKNZKAEjWMY8LpBuDQfNGt5faL2BZmDI0TmUfwIvg44n6fb3sSda05pAiBnBilj8q6WuSHrAgU5Gubc0rWrLO8HkWtaL7fkYHoO4cC+Cy3Vbv0W//piZxk5+jXakNYv8aq/D0ZsnY5ZHGiY6mbIsuQo2btkrd4nuezpcaHLs2LtyK9PDPAOt2VZ7ty8jldUW+Nc8jBGOcocJ/htHHYjI91M05mqrnw+XBUrBmkR/lMREvUhRnKXInmM0NZ2wiQWlag4E9OFtoOYhys/29+s9vws591pxx/fHeebJ+cqM4vckW+6CdkJecmyBy/t+7Mg2yaOEU1J+KMARkIPWeeI2uZjMZJoNaMtV5mtpE/23LDIYYP6GbrhF3yTPMbNo0tykmKuHyvVcvPZW2VtcvKz1QIvGnZNTecbYQuIoMNYc9sraIjyCF5Rf7IOM1PGPVe+ua+1r0xgD/YLyRYEItDRcqHDnzQzC/bE7jR+FhPvqffkemcbzWCo+i+2rNGbUuHeeezsWP0V9QrjaxMthHZWDs1EzFfBpLZhTID0Vr1fbbmO9/pNn3pS93GH/+4Wx/BUDovnmc+o/A+bCuwFdjB/CDJlHKgp8goUgCxSO7gn5IAJbOyUGBo8xc1OV3k2rrIMSA90iqWXpYOoUvJJfk0bvAoWYvgKUIbBsjxCz3Dh7KWczLU+HjXqAVoDJEWERwTsIk6lXHR92weQgfmzAlh4xOZvXRRq17aKEITgVZucfN+QarkdoSeGQrswp2t+qSCBMbTXNJd3qd1gm6+BQ+eYL/yv5uTPNgUF2wcwUz4jqyyEXlN0PwyrvQxfQPjhSzyk+BB+ozstgIX/JgYO4RmbCF/7nOH6wXmpyAvkbZMQC2BtqQJKCw4Bdva3kVp5yAQCBIxK0E6ImRUNLLVRD7iPoxipKtyXlpFycsjixmhcBJc9ooDYABNmUEF9HPyKXFghwKtgVkAMd9GAYAGWNNnjhWnAoj0PGPISUAmRES6lrWTj62xLE/mosxbRQdF2IEKjgXABZTlDi5QwLFleAADDnCNgCgBBWCXH1VuLGMPtZ9FYPKoJhBbi2gC3foUe8n1l6EUvYzoB9nJQWoeMaTYKXLzlmeOAe/eO681EOPv/xxUjqYtOMZVBh+nepKtI2TbvGVAZRMSzlz4m/dtZaEBeeX2HHMU70COOIhkIz8Jh4zW6idE+rjxY5Slf3MCvZP3ZogRJ37WNwCqVSfFc0v55nRZr2X03+/Js3nwHOAaMBw6UQ1g4iQhQYDcfIzUAOF8cNrJtft6F+sOwYhACQIVELRWrekyciXrA0FhzUqrzk+4HDqlBZAtt+ka17IIsPHWJ/Lr3yik729IopB9cktG8hoCSKcAwOQQMCa/gEpZHy2/vEeLzEdA5UcOl5d1F05CrW7DuM09OKnh+NNhlVOxRhJQ9A1Z9/4c8hz8WffI0PgZsVYShmwQ3QqkloSMqHIta4DOzU8Tk/lTgurQifS9+9KJ+cEFuUPI3uT1iBAi7A+nUMQzZJKMtmqaIKujUCkShsNqjsutCHGRw1qGFvAt0k6/WVdlVkouB+HMIA7pCv1F/JBBOsj4l9lygLPPcJbJM8cp/zvZZ+Ny+eQ45oWmy8bOWAtlHxG049Qd46jQZ/RDLftnto2tq5HA9HXNztKLre3YZOIvf7lgPWzQzxbB7EKsBmGRX7Y2584j/ddy4mJbSmyxR7iwG2xK4Db2mp2NLbvWC8eW3Y2ghftbA3RSZEHnNoPtrBHiSOXa9iuyLuAjSGLO9M/85bXoQreW2/3dM2ouei6dgEzSP8EuNoPt5XTavsW5pyPIH/2qP2VASvCF7YA/2AS6jb4aqls6qlC194m1Q17YXdsujb81iijwbnkNSA42O1XiOg6+cWr1xUUfzVdDAsEIxh/GQgbQJRxhDrhMGrIJuyAZYBMYt1aPCRFn3PO+Io6MNWwWY7RmTbcJGQe3IG0iEOFftlMGC7kMopVuYjNKvRFb//3fv6V+yi94g49C97FD5MS7wBd0G2wyVP/MlW97hZnpWzrQPNYCB2wVWxKNrAXWM4dsCflu1c2SPR3+knVT2+VhDGDa+NnatBYCcwsUtA4yiavll5L58rNIwjKTMy7rs3aqOKJoiFQta9lqxq12GjHiLrayG096L7b9WqdDmYXGJg8k+H7rlGHPCRLMOhZosAaQnEqJIJXZ0FrZC7KQZ3Sz3UFUHbD5PjVfmp2ftD7ydtCWCagl0JY0AUXZykaYhEUHDCkwoBpgRwyMEx31PSA5CqyKUMR94lkcCIYqFNSoLXiUN+CbM8/AAMVPETC4rSwjF7A0FEmlPENZMdrxPeRP9ItBYOwoTAYDSAkCClFTO7XKBeQyQrIvGHPMu3cvtw7VGqcTsM5rPhk7oMzzXMBa6+QF5BrA5nsAdAnmXACuCJMokPFFbJVp9Yw9wyWCSbEDAa0suBzMMeycUj/n6dkMPxAEJIWh5fh4H+8XfQC4g5xkfNSxKPvPaCFYJ21//GO38eSTu7U//nG3LgqDklvOBANTbuEE9pFDuZNnbHLgG9kQ+uT9fBYpA8C3ZFM20bgEGlDcug9gRM443Qgn6xnJgPjiiAAxQTiQF2sOMUouEDIAQ04SlxfwKhroHcmL+czHAgBlqCO1OSd/jGVEoFzWDqe4Rdq6kD05GGr1DcDWJzpAHxFYgElNVlwKkJob4FWGlPUO5AEmMedIDplC+VYQQDuyYThTHH9zb3yHTt6zBlqHEJizfCtfDRDOsp7TBQ0wz0nn/EI8ZrpjkICix6OANYeRQ5ZvdQCkORoRQbZuc5AmEye2sADApT3i6NWKhnKIguykNzjgQwcJ0OMlGR+HI7jMVwB+uo9OJv9kl5ONEPIMpAXyi/5CoHofcwkgkx3OdYwrgoy80Ge1PgGvtYLUiAPPQt7UdHN+cQLLZn3Qi+zJ0Kk/1h6nJs8wEGVvZQ3JnGhtsx/SQdbcbLKj56Ox7zAKfRD94dAa31oNyaGi5a6f/vSC9bCRPmt9DmEh4l/7G1I1nGpZHjU9QZdw7uhUW3GiVhY9mtdAyZ1iRCm9JVuZo5QTUGE3I/uZXs+/z/mqZRrCJWXh3ciiy7c0wyLsYB6ooheMQV7EuCRw2USkLWIsnMzY1kZvkP8goa0jesu4589BeHtvz6GrBUy8C/svOyIPTpY6f6iOaKvGEJsm08rcIBLLLeoCJt6JfUcKmgs4D05uHbKA7B3alj5pg1nyLBIYDqZAzuUBZP83TwJjQ2QcLBzBOQSS+Q+CAGlo7owH550/BNez9eRMMAUuMD+eD/tGGYqanZOJEuNEnw5tWzTf3hVxFn4ArCUDm4yYp6E6hOWBKPSheyLvWoGD0JMRyMgJHSRFYKFWseuyBibZMEb8HmvLGicrEaxka0KPW+fIWUQfnNHCEO7T0tXmsgx+ldskS90Suyj4b+7Ld/TercM2Mn25RYNp/c7ag5PNER2Rb2uMU2nZJXNAN9SI/Hzt5Jm2+hc+pPGBl8gZOx0nGvPNkKHWaU2+6GQYIA8wkKUcYyBU850gt9uss61/z91zz26TLLgJTx3eXtoyAbUE2pImoDjYQ05SLUWZs8lQiuYgHEaRT9LmGQDKVMSIc0cBRco9g5UX8EY0RJ0XRq2VocV5AB7y41OBvlyRemYeJS8vymdUw1zrf35C3yiQCoxHFJVhAQTDKWMcZTjMFmwgCwDNfHuf+wF1WH+OGaNA8Q1twfJ8jhsnjiNVew/kEyBIvo1zLRIK2I9TuwDpFQAXuJAhIipLjhiLyBQQ/eQARVQRyRnbITi3SEOEgnuRH3PYMsIM3Lhb0LK2lcPNGWcMgRKRRMYMMIpTewBvxicMHoc1tjMAJPlRxdJ+fdc7thxm92DEan1HJnFIZJqYG4Z3qDYbWWAUASbfq0XsAa6I0JCjHHgZQxHC2vfMW8w9UAOwc8LJe17A3//dU3Zb/n0gLY9UyYwBTIaOdi5PkqkVUyW3tQw9DvlQoX5gmfMChNJJQDbiIbZ+eA/R1Hx7nHUedYKMMXlFWpjDoeLxxiLfOlBeiI4gifML+TWbwx7KBkC2np2nw9fWg2wV826+6cVYf3S3dy5PBeWImA+BgTLDCYCLwq2+F8c4x4XsqWXWANj0gfHgBMZpn/F3hBcShvyTKXauzBYzxvF5c+pd8u1zyFnynD+XjNKZnplHjJFVMu6Q5YA5vYDIJct0XG37bov8p7fJh36PqptBPnMdy8Ejv0gwpJufa04vIiAIOI5g6CJ6uVa3MC4ZgrU2tGWUnt/WIJwuJbPwzFDh8lFHov/gBxesh/UcnXIrelz0CAel9rfcdpMhDnf+d6Q20iWcKJlKnGT6bCgTADESNVrYbLaynBfyhOCBUXK7Sd7zbaNxcX6NSZ7hy0bXtuV5rzg9F/EPJyEfc0xmPZdryprhiA5l+0XAUYM5IzNF/8h4mXkVOoJdQgJHPcW4kMyjakaOquvC9iKZBMZqGavmscx8oHPK9WUe6NJx66aN0+hqODGfT+9c1ijKL3IYRHEtMOtd4pAHejyySwUN8pqhbHSMCX1BrsLOmyc6lL4kV/mJu3EJKlkX7m9u8wNrygs5Qa+HjYaFPQ8+1DfryJiXGeq53OcnQLJRCDb2cUin+V6QHvRJXhMS1q/VDB0qSi2gRL4RU+YJURI1ZuNEOYEha8k88WvgOVi4dn/3QRrRF2yMd4zt9Z6VZyEjIfNgTO3SHyQRzMZ28N98Jy+6X9P7rS3Y5AyZXMusyk9zJSfef0gG+If5c9wzglOwsXcNH9JYkCuZ+/Bg3Jf8mm9rno6kixDdbIZ1FHX58i2E5iPf0ZA262C+14c+1G388pe782unpO6A3MaKtNyW26Rtv/1SuvGNU5qaqv/9SldKaa+9Zn7+059SeulLUzr00JSufvWUDjkkpVvdKqWf/rT+/bPOSukNb0jputdN6QMfSOlLX0pp111Tus1tUvrMZ/ol+4QnpPT616d0z3umtHp1Sl/5SkrPeEZKRx7ZP+Pf/i2lT34ypXvdK6WrXS2lBz4wpe98p///L36R0jnnzDzvZjdL6T//c+bn445L6T73Sekyl0npOc/p7/ORj/T/vvzl/f1Htf33T+moo1I699z+/m98Y9/P1php+vS+96W0Zk1Kb397/x3v5Nnf/W5K7353Spe9bJq4/fGPKX3sYyn9+7+ndNpp/e9WrkzpEY9I6V/+JaUPfaifL/f/4hdT2nnnlH71q/q9PP9zn0vpmGP6Oak18/qkJ6W0xx79XJubww+f+fslLpHSs56V0gEHjO67ezzlKX0fzz47pY9/PKXPfz6lT3yiHxv9MD4PeUhK17teSo9+dP8urt/9rr/HQx+a0uUvn9LjHtf/nkycfnovR7X2/e+n9Oc/p0nbihUr0h76G+0iF0npcpdL6YQTUrrWtfqx/d73UjrzzF4Ovva1lF7xipR22y2lm988pU9/OqVLX7r/rrG1DrRVq/q1YNzuetd+TMr2yEem9KlPpfSP/9g/g4yvW9f/7de/7tfOHe+Y0r779s8gy9ZxrZELY3fnO/dr+bWvTWnt2q0/p/9/+EN//5vcpB/TfAwf85i+T9ZBtGtcI6WvfrUfF+1Sl+plY/36Xv6se3JqDZL/885L6a1v3fK51tFf/zrzs3d2D3N8xBFb9/N2t0vp2tfe8nf3vnf/74oV/d+tg3e+s+/z3/++5Wetx7/9LTWb+bzTnXqdY33d974pbdrU9+c61+nlVH+f+MSU9tmn/84vf9n/S48akxNPnJHJz342pfvff+b+xuiFL0zpox9N6S536XXQLrts3Y/b3ra/v3Ezfje4QT8uvvvtb8+M+VwaXd5q3jmfl1IHPfvZ/Tow1uefP7P+6AcyTZfn7Vvf6sfV5/fee8u/Gb+rXrX/vzFnW3LdSr7/4R9SuvjFt/yeMba2XvKSlF796n6c2QR6jRwYY7L+rnel9OMfp3TFK279TnQ7+6A96lH9Pc0JvaRPdP7737/ld9iwxz42pac+tdcD0YyD+Tr++L6v5OEnP+n17z//c0oPetDWY6l/9DddkDfj8I1vpHTLW6a0YcPW7x5tp51m9Izn06nk9D3vSen61+/f+7nPTelVr9pSzsjXhz+c0nvf2/+sbw9/eEpveUv/rCGd6f3KZv5zO1y2XEa2VbOeyAA92BpPLcaz1tjTi170gh/Xk+VXvnLLzxx8cD/e9J91VGsbN/b3CttyhSvM/M3P5JfdpTO1F72ol4mb3rRtz2NNk9n/9/9Sesc7UjrooJQe//gt7TMdxwadckqP3aLpK6yi3+xUNLb6t7/t1za7TIftvntKP/vZ1s9/8Yt7vcA++/foo1N62ct6nXjDG24etPVb6zw6zbu+7nX9+qOn80YfsB3Wq+b5gd2s3zPO6Nd73uAD32HzyLYxZJfhDf3xN3Z4qNHn1mfrb+bKGnzBC/q+0dXwiz6xQWwY2c/bla+c0v/+bz/OdKJ5tqbucIcZmZiPxp6zieYkGt0KO7ead4X5nva0lO52t5T+9V97/BFr1zvSL/A03WUe73GPXh/m6987x5iQPdg7dC8dBev5rquGo2H4u989pSc/uf9/4J2ywaTwinele2EvWMfnyREMbnzf/OYeT9YafyLHT7e4RUqnntrP6557tseKHiDLGn0C/0WzRmGpFq7WjGHeYDy2yvvATT//eY/1tEtesn/Xww7r5eQ1r+l1vPVrLXs/egeeInM/+EGP2+g7tpN9offe9KaU/vKXftzNSfgg1t7Qu2p0HdsHb/3+9/368zuyQSfU2rHHtn0DffV9mLkcB3orlyU+z61v3e6bOc/7754winen5+hCOlejx4wbfWpMrNkDD+zHnG7kU8DdPk/f+gy5gmmNm79H46/AHWsyfUUWYZKHPCSt23fftMEavDC0BafDltuOlwGl/fWv3aa8UHdcIrZ5er8oQytbSoZKjekuo+wiUnmdDay0tEYRC1Ewz5NtEfeKwtUYehkxIi2Y/XzLHYY/Uqyx0WXWgC0gshbydHHRC9GRSepWifyI5kTtpVb2gqh21OaR6SV1VDqw9xR9FRV0iXZMUudCtAATLwISRTEje0UGk4h8LbtDxKk2N6IjUoTjyPlWdMGY5lEK0UfzSuZFtWNL5STNPUSPRSdFkGXzGNdICyZ7tqZ4Rq3Gj8iFyL93FuEaitxMcrKMSNbXvtZtevSjuw2PfWy30bMjC8m7ikTrm0w+kTbZL66oI2beRW9Ev2U4iVqZk4gSyUyItHUR2Xxrgsu7iGjlkWmRGRlMshv8TSRPOnZe70b0tBZVzU/tsb2ozCS0Hm3DMc4RlZR27Ocyq8wal/0lk8V6qmU+0hFkvLbtldyWGUl5/YCo0yMDK2pQiUIZL1FzuiAvpp/PmYi6d1X7i0zX0sllcpGxoW1a1qX7iI7F70TEzKcoekS/RP+MgULN5p9cWJuuqNUQcyATTnTWNlXvSx/lkV5j7d3pMJkJUcQ/bzIayOHQdmG6jLxaEzJuRuk2zx1z3UTGxzkip+RIZodIor7SiXmGjfE3NrWaZLIzrZVyiyX9FacniuyWUXEp8rYbyCyTISHDTYasd5R9KJpsWxJ5jmO6y4wj60hkM9dldLBsRtmNouSy3kTvRU9tKa6dsET35tuxa/rfO4qAR1SZHJBl7xmZALJJjZ9MVHaCvBszWxJtaxa5pSNkG9AptSxP9jC2YorO5ltrjEEUQ5aBJiuTbLK/xldmWFnfROTefOY1u0qdUtvypw3V2vFc0XOZe9aAeRCRb20R35aNnY1s1vKS7XLuuVtmBFqbMsjIPV1F1xtX+qq1jZZNjYwZGZzmJnSjscprT9Jb5FNWhgzNobpyIvJ0YPzsvt6FPpSJZI2wq7a8RPmE8mQ57+A5+k++2Hr21hqUlUe3kM9WH2QykcUyw4LN8jtZEWVWH/sV2JJtZQdkPTohjG6H+fKi0ubIu8WBBrXsCHiylG+2kx0bKjyeN7oidHmpS2J7v3/ztW+82asonh4nhtl6VOK9SWpUTtq8o3VPD8k0st6t3drhCS7b8OCRUs+w5VErjbzTbS7jD5PX6mLmxe1r+C1qp7KLrUwhaydOfKSX6RdrhvzIwGF76Sq7OGAzv/fcWn0h78ReyUaNLH7rDUbLM9RkoMHK7IxnDx2CJDs1MilhYGNC5qKmJ9xdy86OZ5fbHc1X/hnrRakE2cHe29yVcwMvsBlwmX7D1HacDGVf5frbd+gufYV7aqeRusiM98uzHq05csVmmMt8WzAcGSepT9rIGr0T94vtm+QhsHN+sVUlxjen5JKuKndt+Fl/zZMMZbiLLxUZkuStzMKOS1YeDJqf0Gc75Mc+tiXeud71uo0//GF3wvHHjz45eDtuy1vwlkBb8gSUbMjTT+/WfepT3SaOH0KAYeFE5PvjKbcSrIzazpYfTxuLO695QamUBoyxoQw5F3kxW8qXc1WCY/eM53AQYztHXPbft46wp9xqKaC1xkmQXs6IIbMotzJdHIFiHPJxAzIAJn3PC40iJhgsxMJQA9wZX+mhyILYnkRJeveoWdOq5+IqDYFnAkn5ONRISEp5Prb7tBoHJOpL1IoZxslY5V56jhwZ4cjmJMuoIvpDjdGqnfYGNEctKGsAIAWgOKdAXVlkEeBksIFdjmNs/zHeZTFW6d6xdcA9a2DXBWiTP+DK2iyLxfouxzmvdQEY5PV0yFqeJh8nO5HL2ANvnPUReGiBJ4TMEOnob5xqzpq0dIQPB8N6LguZkuUgZJA3xho483l/M44cJ84QQNjaMkFGYxuv8cxr7ng34w+UxQk55TaTGEN9JAf5iY8+D6SVteiQeZwtzpHvxJhYq2Q23/KBoEFg14qO+1yc7DW0NWioAUUIDOQQYM5hBc5j7QJB/q9v0vbNj7FsnQzk/fVJfzZsuMDhXmd88uKg3pO9IEc58LdVkR60DY1jw6H23Hg/Tm0O4swHsiaONecAWNd0G12L8NJnDpx+u0+MNyc6d/SROuX2IGMCZFo31qF1aTwCNHLUgFh6JAqNcmxrRIx1NYr0tlbJRRmkoKOtQ2uII0DmQ048lz4h58hG429sjY3ghfuRN/Is6ODn/Djsst6QMQC06TT3IHvWEWfF363vfI1zGDnnatbkpzzGZS7IDyLN+Bj3fIuweSlPaXUh3Mgn25mTgvqkL3HK2/bUyDmbGNt26CSky2b53WpLKln0/uwsvUDPWicc3HKLRqwPwQrrj86jb9k/ThHbluMV+izIWfNJH7W2ESNG83WYb6XmKFlHygnY0sLhNV/sBl3LDnN4fcf8B4EtIGhdcE7NO6xLBlqyb6ys7zIgYu5hPboUmR86FsFBT9BdURfLZ8k624mIKgMP+iDQiIyzFksCqnWiX1y2NrXq2dEzdANHPn6HRLF1np5gj5CnQR5ZA3kR8rjIAHIcdmCPfJ/eRL7NdjsqgsSaF4iAnfy/ZYvpD/IEE8cJgWxxXtg6v8x761AM+ts7C5RYE+TXHNqiXDv5i0wHAdna0mp8yKH75qRpzD9cIhhB/hHp5BQRSnf7N+pHwcdIePcYkkuXMYHX6HrBh9huaC79Tn/IDltK7hEfcSpwfsEsAgOeK+hmLGAn8gE/sYv0M5KptAEIEHq/JB/LguIwC0xD7/LF8uLXsc0QgUfHsG1R0oM/k9dHKy8yWG4Li63p1lkefHMhgY2Zv+W/J1uIanNlfsgXGWLbEDL0XitY0WrG05yzGfF+Mf50g+cZX2U/jA39oF/l1vrAf60ttGyoPpIfNjc/XZNOKf1cc0A/ux+58Ez4lu2GY171qplAEr1+5pmjD25ZAm2ZgFoCbUcgoCySH/3oR906zjpnqrZoGIoh5Q7clC0/ktTFIQ1FSnGW0TzKkWGhbACt/PvY51YhOpkEvsfYUhShQIDBoUKCeXG9oUZhc2wAqwDwQI+fGUTGz3vl2Vt587nWSYMAYTzD+Od1ACjkOEkDWBX1jzGJqCIjyaC1SBiX/fh5oyxLJ9wYRtSFATM345xeNEkDnNzTODH4QF4Ur+Wg5EQTso7DxEkEUPPxM79Rh4ujEHKBFELMAQAMeus0wVqrHR8dF+c5GsBnngDLVkaKz/ueORERJSPkrCzmag6A/zDaQ6e9ALP+9W750fFxAQ7GiZNiLXj3vDgqJyaIK04CgGe95Ce1AOZxZDtSl0wjBDg1wBWgMy5JAtwZowDymj7lDhLgoh/mE6DLj9kF8qw1eoXjDrC2imqSHc6ztW49AS/ANFk2r/4eZAPHxRiGk6c/MsvydQtIhAMFfJRFZvML6Zf3i2yoAWAekC9kwLjXnJS4AKDZnmbneYiBMrOLbOkD3eP+HAd95UB5f6CZTOY1DTi25gNxCXh6j09+stv46193P/nJT7r1nNIgX8gDgBkgVR84KMCdvnAArXH6LI/8c5xkLFnbQYggnxAzZID9MZ6cK9/z+aGx4UjkNSPK7Ap6rbQbZKkszo2gjDoe/kZnxlrIL2snf155GWeOB0yQF76Oi7xxQkRfc0I4v8ixRleaL7oQ0OUYAbh5Nki0WsFr82lN0y+cGDZclkYEc+gpJFvUtfPenFXyzxkLGyH4wcEobQydkmcQkA+yQ2fQ5Z7NmY/Cr5PUlNrWLUhb45Y7q62i/II6UYyfcyaYYLzoVwEiZA8dbSytFfOItKKvYB263/ySw7z2jEL1UaPRuqUXzVMZ2bcGy8LipQPGNoYezGuxkVO6l90P/cy+emd9YaO8jxpt1io7UD6ffZbxC49Y90OHv8jUQtx4d/odfkJqwG7IZ1mlCH8yaKxy/UqfRLZUnBQWeiiXy7wmFEfR7zibCBHfp3v0M0gchFzUJY3xpCNj3oP8qWUtsYkxN4hfgVOyY21wqNki/5J18+u9xw2MaZ4LJ3HqvS+bhoSmg2HCEqchuJD57De9mmdnyH5UQ4iM+j/ZM2dDNo68lTW0jCf7UauThCAxduaPHJXfjctYWwdkwTwrZi7zRd/JAd1EhummWs0xcxREqfFmV/K/G3f903/zwxbWDu+AR8uTvY0dHUn/Rk0phD2MJTCq3xrd0DpxzXqDgQSrfa88dVvfjSE5yQvGu9hR8+Le+h+HpwjiwbalPwEj0ScI/VZgycXeD8mevpg764QNi8/qd5nBrl9sfu059H8Lr7WadRQ19eiXsGlwfZwYTYcKlrNH/q2RuZFBTfZrdWvjsg7NQR54LnUmHEw/5eSsMeRD+a5r/dY6YZmAWm6L0nYoAooC4IhZXJQ1Ax0KyO/zwsI1I1W2vHB3XJQxw8Iw5SdiUbQMTShWQJYBiOLHwGztmO24RMoZA0pY30Ue3DOKYo46gnUoq4NSRh7oEyPCKaWogEqRHs+gIAGo/DQHDYAZOkWMMeF4ub8ouPtx1GVRmYcgG6JIaF4o1N+w/ca0RXC5RBHGIRMZYSBynOLs+scoMfzjkBLGheHOI6MyQ3yfoTB/ecacuY5xMzb6xIkHUGQx5LKFzDSGSLOI4EQkaxygx2jnW6NcnEPPBWQRCJNEMgCqcs6BvvIEvdLxr0W2yb/38r4M31DRRxdZjAbchFxwjCPbSVTZGBrPPBMO6MvHwfOAOk4Ho44EngQ4l42hRqQhmvVLVF3UnsMrygykDTkt5RyYN2tddN+7GV/9FWkHIGOLY0k2yGLhjFjD0uw5mbElFIHBWeAoGB8OYHkCZHnlRUyjX2wCfQBE0aP5yXDlpf+zLVZpjqNYaX4B/0BanOQEoIoiW2f0B11uDJAl9Ae9Zh5sNyQfHBO6gAzc5z7dxh/8oNtAv8o6NCbum5P7dJHxQnYhrkQoayn4uUzqg/UaOgFxFeTTuI1+zU9gy4t6k/k4LTO/ODP56Yuhi8IJA4I5GGSjRuwjoFpOFUKcnHI8RGjj99ZVnJRKLsrgTH4Z41hn3g/INi5DJx+am9pBAS7krHvEMfAcPVku7Jf1KMPBXJp3eo98yKJjG62DnEDiBPibNWX9GPu8saPsAWDOaWePW06KizxOMt/bQas6F+YnMubIXZ7Ri1CxzRzRZ6w5RfkWHLISmeCRORDZYnHQBgcIsWFNcjDZAVl61jhCiL6jCxFI1hTii80ot2XG/0cVt4dBBLZsu9P3+L1+cvysqwj0WU/0r6wm+gO5mmevlxedHw25nG95YWO8C8KLs80mRnAA5nDvkmhAyOSEk35ENq0xQmjAFvBbuTXXGqW/a4X380M2xmn0PnmPbFNjYj3BbHSJNU93OmCEbRo6dS4aAj6Ctsj/2jYktiUKtFt3QXyH7S4/LzhgTccR8sjtVvY1vNUqpm+u6ZS8wLf/R9F6mIGcyVqp6VGOfU6me1fYid4g5z6DLGRPWrJE9jWkTui3sEdsgfUUc24NsZV5JjVcmpfnyOc+grv6yX4KJiK0kJUIZ3ihlVHmIlO1gLSgHKwTWcB8ldrBRvARPYsooWsjqFSOpTkiGzAwGcwzuMsLiTZ08mOrsUPlCcLGU9/Yk1IeJwn+RmMHwseTWRfEO3vb2n1Tw+aRTYZUb2E3NpHOpn/yQ06Md/hXcFlruzGCvFVgvVsmoJbbIrUdgYA696yzuvO/8Y1uk4UIOEXEBIFDuYisiUa3DBFHopYtQxlyHONznBJgQXoq4yBSmhsjESggDiChTAEH/bHYkT6Ril67RENy8ocy4+wMnVjHsFGglDJghQCr1U5hFAEawM/nW9Eixq7cUsBQ1bYmuKRl50dg50bcGJXHd3OMOTHxnUj/9HO5vSm/SvkEeIeOugdchxpnBnCLCL7MAYBraDth6zjxcI4AKEQAwOR3xjo3HgCB8TVn5oKMRNYHcFA6lHGJXI2qNQKQ5LKIiAFsOJPmCIAKgDduAzI4cKLHHA9kYgvkheGrASFAhWwDQ+YeqTa0FRZgiiYdO09L5zwCMuRKVoWId76dD/jPnY18jswFMsU6H3WkepzowomvracAb2Q8onVISM5CfrJYrl/Kuh3WJCfH2tU3/+YnLLl3kD41Z4ueoVtsCRatj9pT8XeOmwwqcj108pS+DQCR6QYYlwRnfunzJPXg8gbolcQlgoe8AKL0t3nP63LklyBAZLFYoxycGjmyalW3yXuIbHJkrUe6p6yzEhcZrUVAOWX554BvNkEtFUBTDRhkkIzTUeMajf6IrQ4c7yCh6d3adjJ2LeoL5ldkmNKl9LztaOUprZxH6wdxUx7fbOxyeUfoIRvIlbWbnwRFr7TkgfM0afSY/NScIXMu0wkxZD1yXugjGTfWC6KcQ9qST3MeZLpx5VxyPOPvbBAyoiRQEWicflsVWvYvyIvypLClSEAh3fLTH9knerv2zkidcr3HVi1yKSPTXIb+ohNhDmPNAY2t/P5FllqL7LExjwwN9oycsWW16L77tWp90RvsALtK5+fRf//XB+uUzo4tdWSD7aZrkZZseb7NNi4ZqGXAyjppyYe+hMOMsAligI5D7Bkv78zueTYMR57962dkjO+URDQCmc6AeYdOXYU1hojfvPmc5wRWoT/oE+R+rb4O+Ri1HQ+G5RCzUUNZ2rI8yZRnxe/Y9jLrWp/guzybxf1rdRPj/aNuFPmmlyOjyPgaO+RazLVskjiZjfPOl2Df2FD4hj6McgPu0Tr5LzKC4Lpc/5YXGY35gbni1GvkRfnueXAm9BWysHVvsq7fdDEiElEJu/g5glM1+5Jf5Q4LRFmcmhsXjIGsyzPAXQJqxpqNR2LCO7m/QJcj6OgaYwSzsDVwZy1L3vuMW/+s1ti2stQHHeR57CEZEkisyTR/zO9bAUzjggyKzEzkj10m5KVmq3NfqTxRnJ3jd9Kh9JP5zrEP25ePA/0Vf0NQBvkJE+ZlLcprIFC/dnkL3nJbjLYjEFAKpl2Q8hjbbRgXCxCgp/woUsCBwc63bzE8vt/KIPId4JujGfUlgFJKMz8SlqPsXp4V+8oZKIYcAcCwl4RMflF+refXjL8+1DKT9LME/xxutTkYHcqqdDzyC/AaNwNKn2tOYRh7JFzNeHKOOBXuy2kHJqKgXvl5xF6+DSqae9dq4YjQ5rU9ojEciBpGqAWsWwqZgzEEIvLsOXLEUDH4Irp5HxGRyAZA2hiYC+8+BKYB1aFtlhE5i4gtIFfWJHCRoXEd4lpDyOhnflyvy3oDkumQsngkkjDIAOuRUQX2WkUSZauUzhzAxLkHRskLmQO6OCgIxJxcia05uRwhYazJyFY03pyaABnGz7jE8czuDYAGAJKJ5hlllkNZVJMj5TmcCe8nqkdmEEsAWGufP53B+UB42AITW2RzZwtoLtesdROFLj17qGYIEru1pQQpP1QcnPMESLUOcMi34ZaNg0sXuVqkn3VS3i9qlXAOzDNwmxcKLy9jyREwfrITauCVrJBFhG5sw+PEmbMyewAQNie1rXOIwficSCVCWaChlh1o/sfdBmyMEEfmkrxZVxz3Vi0zchZFuvMLKUPeYpsdx1rmBHlyX3YD6Aa46UKZBBwIuqoMPtBl7AHbkY8p+yZrc5wMqEkap4pO5PCJ1tMZgHaQxrINkGQyWGxB5dCaw6EovvmOmiJscC1TpCS+yXxEjjmvQxF5fd3e6mRE1hm9VgleNJ2L/FCJ2OZMJsOGyVAzLlFTsDWHHCBOOkc1jlH3L+LX+iRTbIn5QDjQAfQ8/Vs6axx9+pSs5xnm1lusY0QXu6r/+kem6WafJbvlnAXpiEgjS+wl2w+zwGx0sf8LXHo2ebcWvUeNbDTOeY2buIxB7lxGBhcSy9gY3zwT0f2DHKXzw1n3+Qi06Ftsy4alrOuhzHr2a1yCFJEW44sI8Vz6bqhmnL4MtcgKhssiuFK72Cf6J8gfF7yaF7SH8WGMGh6VoV0SIC5EuXdBUBv/3I6ScRmvv/99t/6Xv+zO/fa3u41kMYJI/hZb52AKuIGuZzPpVSRDKziIbETYu0dO7JbkA7tq3OEP64Is0ddDhyLkmNB3azg4LvKbN3pZvyMwN7TDAl4tyRj9y3Uo/B+ZtjLW3A+xZT6sRzrDe1rnbE6+5RHpXJsz8kzu8uCQ8aajZxvoyt8fgckno0/M01AxffNL5owZ+WPbrLmwb8ZHcMxaoU/MB/IwCFfrL6/RNI7PhZAMXWFcBZLpK88lF2UwGTYNTG286TKYPM+srl2yTxtt7TIBtdwWoy15Auqss7pNUuQx18glUQqEURlVB6QAbkBHJIDTAuyOe5IcUgPwAqQYlDAS8RyLmYOTp3NyZDgpjDDDClCLjJQGA5gfKmYKxOSFPUPJtBQLEFY6lXGyUSuTJy6k3agaUJwkynUoDZ7RIVc1wA8EMFqMGYMvshHF2zlInM2op9WKpAPPiAlRQM4lRW+sS7DlZ1vAGA7kSStS5jKvNbDGSA2NmWhrrcng4RyZb4CZoQryyzsDzRysqLmUAwxGJyJ1CKYW0DGGQClZBCjKYugcWRET48Mwjsr+aTVGDwhjGL0vQgvY8FxkCGNOxvxdPzzb8yLLy/ubH1FfUSLEcMiG8QEUvYu1CfhHfYv8+XFaGEAZ2VgI4TzrSb/IufWmL4jNGkADSBGSHJTohzUdmRTeVR/dg1OExIk1CnzU6hSIlvq8dcGZMm/6Xa5FDm6e8Yc4RwpEbSPzT88EwQWI0SHxHoBhFIRH0ABrre2REdUtDx1wL6RlRPPJapBFeYq736slRG+VdaD0j+4qiU3EDSDm89amLCvEaI2MMd9l9gqwJ5KHPJQFMWrbJsdAn+ngErhbZwAgvYfIosvyrAo6wTrjQFpztvVZkzkotWYQk+QX8chxIYPGj6yXxflLkMduiLKaU2RdK2uAbRL9RCC5YgtIS1fRoeUBB/QhvdgqYBoXZ2DcVst8pKvLuiNlDajZNpnA7HNsxQnSmK0mQ3QFW0sukAOt2opBatNTcRpb63NkLjKQ8xP5YttIrd4V52uScVyMZi3Sh5wlNhj5RpYyeW46F3RBrHF6G8awdsIOIUysgyBmOUrsZRkgGjrFilNEx3BQ6WqOlc/TTzKQQp6Nu7XIfnLs2BdrN7abWHfuBff5DOJGEEeGQ05IDuEktpidIT/0MTII8VM6w4ICxpSeqq1dWAgGtSbIKWKIToClcoImJ9e8d561zEbnJBZbF/Vk3C/qCJqD+L3Lc4eyx43LuIXy84LViBfzYXxrJ4LGBW8PZY7HFjp9rJ04FxcbAWPDf/E7uCYfMzZBoLeW7cgWsd+yFul0ssAmwhJRV7G1xffTn54+IdWaONeaCPuAVMi3N5WXvrQa8j6yalqndMO3xiTsvPVAp8tqHpJbl/fS2IvWqZf552J9l0FhvpK1BJex8bE1OWpXlYH5qOVZEtXxs/vABPR3HqCDPfgDQXJHSY5Wv5FY/B622Lqf7QEnc2nevSx/EBc5he0iCEhOBAFhM9jTu8F1Mi2HbDE9XeIi75rrhvKyJstmDdJlMCvdQS7Y4aGyMwN2eu0yAbXcFqMteQIKmAHSMcDApoVfi4CPE+0fp1EWonGUi4g75StKykgzdPnzOLHIFBfHgLMlQih6IUINhFAajA5lwGlr1ZPg9GLKPdc7tyLjLv2rEWue31KocXHUyia7gGPnfaKgHmMpGjR0L88DIPIsKf3mjDHKlLWIPdAXxgrgExkRlRwn3dZ4GQ9kQmksjVl5JHTsy25dUZwxb+4fWTUAMpATEQkAA8nRahx4823e8loDORmX7/03VmSDgxvjxljbvhngl7HhCOhrgH0RIpHfqKfjWeTdfCMkGSagZtwTbIyd8SdzQdwiMsyT1HBESQkEyZ0+eQadQp5zogZYNm4cSHKAeOMskxNj7J1zssj6ipNfyhMbkYqRou6dgSUAXpRMhJSR9s5lceu4vAc5jO0ZiOTYmgr4cjrzAtcuRIx3A4xa8uN5QJ9IHzDm/c1nDqCC1InvAKEyNYJER+hxePIjpzmScZSvaLjIIaAdpG1t+2NcZIMTYh5F/4DQOPWE/JgrmZr0JkAp4ymv76E/xktWkj5wCGUnebZ5KGsykPda8Uwkc05WcVzpTOsnB6six5zIINr9v0V2xDYHzfuUZBXiLoIC3s+aqEWX6TVOHplDGJF3YybiiuALm0I/cSwRvdaYrL7WqT36TI5se8t/L2MDqB7VkAbGq0Yu0ht0gHc2n9Y550CfrUEy18r2CaI9dBNHngy0MiVqtobzjlDLCTDvaw3O9WS40nnJM+OsI/2km+hfAB9R0ZIN82Y8kIW5LSgvch/BjvxoeheSi33O9YExJBetLTjbotFN5SlQMS9RLPnkk7uNxx/f/fmEE6ad7q2auSNHbEmNdLOuOV7Gnx6il40P+YvMKDaZM5sHrfyfPqbL6Uj21Dq0PmAnuCN31MxpmTHDNvgcfUcveH55ajBckusARFAERFpriE1ia8k0YqwlI64yG9m7Ri0i7xhYL04dRQAFQceWxn3Kw2VgnlxPIH3jHraAyrTk2CJFyvkYIuhreK7V8nITQU4gL4fKHehz7VCBcnsibFCr5xQXG86OlGuPPok6j+QHOdTamhZkXQRSAkvrX6vEgevqV+/W/e53M6RsBEXNJxmtOfFs+zgZ5TJ/yFeZBUV2BVjiZ/rOWohtzrXaf/kV2Ni6zre1ljJlPDXkOj1eZkpbv+yHfubZ7fCQ7KySXPa8/PtsIEyRY1vrtkY2IkbII3LTmixPGR+VGaSxWfo0Vz+uvKd1DbcZ17BfZMj2/1rf4LcIaBjDsv6n+aSLYRtrqHWSuUBKmYE1VOOWzMBMZC9OQDe3/J/8RPTAPS1/h7wMZGevXSaglttitCVPQHGUgZ2opzIERqVFDjngFI+/DxlUjfOGNEE+iZrLwohtVZ4D+AM+DC4jACQhKvKithwbxFO59QrIGEpx1xAtQ9GkHEznjYLiMEaKMQdP/xl50XZRuHI/crTYqsRxiho+nNEaqeJicI2luQEWkQLGwhiVKeOcX+ODdEJyMEwcYIAE2KXA4+dJWnmqjj61tn+5gI5arSTvzlAwNIx9DvKBFHI3FKHhzNaKb8ZFLuIEOXLcSlVHOgB0yA1RWQAxByqyRSKlmQNaHqFrrsjpUE0I7wpQRGQnDKytE+YeQLIlJfaZlxfQHLJHTsutCWQO0EW4xJZHpGwtFdtlbdUiiN5FdF5GirnhDOo3pwmBon9DkSegPq/RxbmM53AOWrWBjLE1UiNEGHWkTOm4kRHkWr41NN/uoq90cGzL41SbVyQfoBufoyu8GxlAUCFmOHL6WtsC0jqljs40/uQdwK6dgoMkCYBi3cdWBOPOISGvZf0o8+jnfBtFeam7Es1nOQy2NucOPtLA+5Nx4NhFT40C44gUxFCchGWOY05luMh2A6qtN4RTeR/zRGd4ts8DjQjNkkyjo2KuzGt+Ck3pVOVF8svxHZcMBi7pUevQXHkn7xpbvckiUjcKDnO8RNHpgFI/sw2ITvqKPs6DAxyQkhhjE1uOIxmgg5AV+kNHz5WQIZsl8ZtfiPz8s8jRqKlT+zyygu6ylkLmEeER5bcOEVvePewuearNl3WEdOPUzXfdJ5iDE2Rtj7L/rdaq9WY8jUEeMDj44G6jAEDNFrCzrW33soRa21zZrnBYYQ3kjvXo8n+/iwwMuhdWs/b9HCepxgEDrW2VHDvrWFCFM1vqWo59vmWUjBqX8nMcbPPI3kWf6Np8q7EMPGuEzjX/5Ymh4fzFOqxdAhCh942NDDNrrsxEt6aDyHLBd7lNZFe8R03OyXWe1RkX3TqJLJXrnN5DAuT2F4bm2Ap4WEvWz1Cj4/TPd41trUYicop8GB/4LD4fOplto8sQ/1FzrzXe7FmtDdVf3Wmn6QMqfvjDH3br4xAg8ogkgfXc0/fpWTYY/hmnpmYUIyc35luGGVlhl+jgXDfHwQrxs3duEX/wc6wz+lnf6ED3R6CaL/23RsKGeydrooaJyFbrJDxrN29sS4krYbB8SzZsUlsTMDBCBIZmN3MMVF76E0HWOMnTukY+0mP8lTwbc5JG5/mu9U/nwu+5HUSqwngClK3+8VFi+6xgXOvkPnrMfBtjOCECrHSL90H2e8e8/i87WpY2kfVo3Nh5647sWAfmnd6gu2zrhYHJa5QskP1LJ+aBXcR7HF7VaGuXCajlthhtyRNQwBLFRskjdIZOL3HVTu6gxDkdlIL7cJAphZajTnkhmTg6QILMCYqdswLYcKzLWjkUBmURe5gpvrw4Zn6JUkQ2D6ArS4EDgvDyPcYkwAhGPNJmOXGcHobMezLaHDfAOSKglK5oB+Cnn5F6LlIHWPpcXnejbHmRSBHlWmF37xWOAkcHQcBxd//cACIjZEUAnMZHKnwoYu/NqEXaNAAJZOUngIxqMjXKvpmDFmk2VLBTf0QzWtFUznJrexvQ2kr/dgG41qBxIIctZ0qmH3DG8DDCxtl8xOdjaxYCozzxIy6GiJPTamS7PK42vkfuGGbyOFR3IHcSc/Iiv/SRjEY0vXxnRpLMMOBl9lMJsq0JgC0yhoyT/pH/1lHxDHk4Py4GHKiwzuiR1vPc19qo1YUxN94rfkYMIXz1x9pEEHhnjrNxifcC/AHQ8sCBOEUG2e09rWPRMWsAgHXv+CwyuLZVwjiWka58W0Rex668AJpo7mF90ntkWV0QxLBtaQh2/zemxrC1RlyyjIKk8C4ha/opSi2aj9SgM7wfhxMRJEuwRgrSlbEFhEMNoAbJrG8ydMwzgjK2kJIp45cDQpFOcpuTv96z5exEBgPHtFVHIz+RZpLaWbXGHph3Dp2xLgkAep/uIJcIFgCT7qfj6U1zTR9aw2xQKyOAMxikInnlBLE1tQh7yN18tqGiui5OVWm7zYU5KHUI4sV6Y9cRVeyPz7LvYXvJKt2BhMjvmZ9wW9YPGnfb/riNPubU5Vtx9GcSMo8jluuz/CIDtRqDZBMxVzakRYlf4uLk5kXcy2vU6VGRNWBt0IvhaHHQOa62E3mPoQCb7CDBpJozTeZlC1n7MZ6cYXbfs+ElOoMdC+eVzMW2Nv1ATpN578q5k+1AF5qTmsNbbtvLL/Ykz8yGhziI9E+e5Ufn5UEEGCUPDliH+WmO5SVzFobggCKD2ZL8HcdpbHF5QAjMiYTw/CgnIQCG4Pa38gTVEjMhYIwj8sg4ek/jJQuOPreeA5OTHc+kw6xTWB5hJ9MexrZOzKP5rWWqsU+1+p/aUB2eq1xlOgPqXLpR/+h0ugOWIgeuCIQYo3EDoQIyUW/JZd3QxfB5mQHndzlpE2UVykCJwGDuw8Ccxs12QGsKZibD1nW+lTwIXXowP9GWrhnKDmN7ySy7w/6QJ3KVYzoZunSre8OlyKVawIi+ITO+S17LUy7jYrPZa1hBUJoslwSrdWl3BTs3yZyQSaQy/U/HtHaSwHH5zoTyIsNRV5PM1DJ24TFjy1ZbM3Az/ytIojwrDqkYwR9ZeOXJq3R4vjb5KjlhaR3xIwKHho7WL+/ITsfJv2ShPO28aMsE1HJblLbkCagNG7pNcXIERyhPhaQM/Q4IkGXD4JWZKmrrRCYEAkCEnnIBgkTyGf08DRU4iy0cFjfA5DtRIA4Qbu3Jp4giw0g6cW6YKCgKEYGFEKLsOQKRukmZcTBC8VO+lAkCLAgVCh7AEjHg3ALaCCKKCginrEV0gB8R/PgeEMjRYvDDYQdYAYdyvMoTMCg9Bk+kX1/9zHHJiwVG9pTfAy6cWGPM2dQ/DjGywL5n48Nw145md2Hzh2oO5K1Mz3cB+oBFGWEAsEalVA8VhjRerZRWc1k7UScuBhFIjShP7TOACMNRFoNm6MPwuESVjOvQ6RfAWK0BF0Mn6thqZL0MRYZcHIu8GRf3RTaG44DkiSyrPBocxRs5CQgN4HeIgAJIrQnvHM5+3A+BFQSLtWc9B1mLTMzXoMua4AQAUkPvB9whFcu06twhst70HbFBDq0baw/wsZa9P8cH2I7+Alo15w45FtsR6SJr3L0jhZ2TgnwBlBGhZNmzkJDeKQflAFjoECTP0IEEQFh+Opg1Hdsb4lhlnwNsYo4ArqH6BaK1QdQC0i2ylW7LCXq6mZ4g395fBBTwznVBnI5ElxoLEUNzJKuJ7jf/9A49i1wK3UV26PCSeCSLLedSRDMydfSpdrDB0OmDIaeTNuC0zBb0vmVRcDrWO3Ga2A1jY+7pGXLUqg3BJpBvYDiIRPMJAEeUlzwie817a8v4bBtdERlstYteKBv74nvsnjowMgA4RPQuWaV79ZVeah1AYc3nzjrHOs8+DHkYETmedW29sj/WBQdoklZzpkTf87o65YUgKO2pbKxWYetRtcXYp6EWp5rG9vX4HnlCLFmzyIVW5qAL+Y0gq60vNkYfIiuEPqJL6EEEBuxTCxRFJjGHnBzVgibGqpbpbD0FUUDPeCadANvUshw9CyZjn3yHnqMLyGgeRJC9BXMgYeh4hHxNt9LDMA0HNycO4/TQUafo5g1Gy+eeDSFXfIQ8Qysu9qblzHJ643MwLYJI1hsHGcEgEBNbqeimvGgyey0oA3MEdoogDvmIOjvuB1uY16GsJEGqll457rhu3R/+0G0ig60Tosc5ECYanaifdGbr5GCymwdC4bgyS978sT9kAwnHjuXyF4cL+TuyBt6n45Be9D997W8I81i37HRe/N4zw38qL1iE/PGdyB/iSnDHXJFrwU/jT25jpwIc773prtoBRdaVsaGT4oCmEgPoq2dZQ/pW1m0lczBsHMKBxOJXjAoMIPRzIstYkQkYCBaMbcBx0rmxb2Xjmi8kkP8jZvPDBOJCqJNh/feu1rm5kahQC0yxL0EuGs9Y67IG836bw7y2KTud14pE7tbqHcbnyWTr0K3NbZmAWm6L0pY8AcVvzmsvAZ5ACCWCQGGQMeoUGaVYRoTimNg4yjW2QuUXcB9GVpQ8jgT3DEAitmhQZFIqWyfDhXLVRAB8PraaUFQcI3+PU7ryPfk+FwXPRUoQUPke8rjiVBdGxv04/JQeIi22J3I8c6CTg6HyAhryrCDvX37G+1PGiLwhI4Bcohj1rTzZD7vPcPm+OWk5puZpKOqWt7zmQn4x1tKGGXWRA0Z8nMyqFpiIK7bAlI3MDW2Ryp2a2qlgkW0GnNecFfe2v548IcKs56F+crxbzm1em4gDZqzIG7JVhpX5YRxrWVK194kGaAIuyJA8iy5k2/0BMqAyj/ohDFt1OTjRUQAT8AmAyTiTe+sQCGaQrVmkcsgVohXgzd/D2gMkhuovuGeA0ChiLiJLNvJThIBl6xUhXttC6EJW25ZiPDmKyGx9Kg9QcAFDPkumrVc6KQqVAl8IqgAfZJrui7pQedFKzlIAEZ8Z2u6k3kgtCyNfn2QOAIvvkJU4ya925ZkmUVesBsRaWUXmxzjVyF7zEWNtHdDP5iEK89N/iLpatJKclVsHfa5WKDUAn/WoP2TJPNOriEdOKOfTWh6qXVUSDONkK3jHPIJNHocOVkDkl3NY1vHIL2MWjkH+e2sfiarPPmOcOVHjnvI3btPX1hbOSXR/NP2T1UbWhw7NEHH2WVc4eWwwUpJ+Ncb+NgK4T9yGsmesjXGDLVotQyYKWLeewcmtkSStAsGjDjHJsyZzRxl+YpfgB7pDRgyHOuocuRAd1qsxL2uq5Bfnk71r1XdCvHK+ZfzltZSsRYR/DaMYZ7pBEE5AqPVsfas1ehXJ5XkwJEzEltK9UZuF7CBEBQei1qN35lAiTqOeEz2FOBegIbeIJdksgp+l7XQZC3q1lWXNpkzSzFUchmCsPDffrl5eUWcob9653KqVX+xOnCRGPgQU3KdVt85Fn5LlONnW2rGmzYnM16FsTM8wRpGFxEaxb4JDZ5zRbTS+1sIojDdEQMM39FMePBXwKonswGC5nmPz4uTS8oqt8jU7DDcg4Nj9Mjgc9sH863eebWz9IY48s4ZN2c/W4QuIyBwve2+6h52NmoKC8O6dEzMII3oUzjQf7uG75tVaFXD0HWOGdIFxyEkue/ykvFh+fsFArQy48D9yEhLeM250Tl5Ww1q0/hCf+ltmj9JfZM0asWZly9b6hICiLyNz21wI7Ayti5zAp5fNuzUvmYLsGmN+S2S/GzN6tCxEzzbXyOqyDmejrV3egrfcFqPtCATUutNP7zbESTgUHpCcR3FEUyxUiqyscRRAC9jLM0nKSwSZg4DIso9ZJK9WfLYWIeQoh/IPBUP5U/C1InciRJzZILJkNHBoKBQKkbJmdGskDWWlD+U2M055RMlLIG4Mak5ZGD+ZGtEYjVZ6vujIUHFAgEN0vaWAgUkgH2gbAgH5kdmjIlE15x8gHSeSVbbytLpRp1nkzbjlJyTGJTsvrzkG/OUkUFzAkjlsPR/gBgJ+9avpegbVk2LiYuBrTbo2QGx8IlUesYhgQXYggmTgAA+tWmtIj6Ej2AGO0jC6r0gcgqhM3SaXkeVUc66Mn/9zMoOwFb2K03PMC6enVnsCyEBYRyp0pMWLYLcyJWSb5MUe8yZbCJGLQLMWokZVa8snoilkhsxbz94DWKSrZCDJdpEZFY5obAvwffODyBW1ba3f0CfROBNRW4LOHCoEatxrLQe65q1WvDZqEOQX566UDU5OCXLpxBoBZWzMESfNmNQcSbrKuCNqXeY+nGaOZau2TI2ActEfZYSYfAD+iCCOMjDoc9YVZ5Fet0ZsCygzk+LyfWNhu5e5J8tsFPKzfC86gT0ANOmtOB3OBfyW221jW4UIsr8BsnShe7BjgHMtAypAP8fXms//xmlhJ0oH0da8WrHYuTQAuQxQkG9zV57cNtTomqj3xLGpZXfSK2wSnQEzcOKtX3M621pM4zYZhUO1AY31uHXCNLq5lDeZREPbbOnAmtNGNmvbjK2/mn2KOcq3d9NZxlbQKbaNs93Gln71tzILlTwh1JERtS3FAlXWOEdfUIZMlpkt1j2cF7ahttZbjqrvDW0htkZrx7ZbX7W6WVGzip6na3MbTt+7HzwWNeVc1rf1Zy4R+uxH4FY2hk0J+w6L+W6tBlT+vqPqmpbNOjN/sfV3KIO7FtCSdTV0MAYMEESvsWELEUStGp3sao6JQ1ZyPcZWDjXPM9YIFCQhgoAcbdrUbYSdjPPQIT0IzFoJD+uY3keAIC/y78BScCNSFHnAFnkGjEbP009hu9mQWrDN+JZ2088ygtk6Y4lQioyg/ELg8AnYaGswzyqm66x/pEgZKCHLQ8Xeg4gll3nQHhYJGwFnIEu8cwRsRulvY0mWvQ9Sjg5ATsb96fFWvSrXkC9bEvSRJV3ijzwA6fl0jD7w94wLfCYozx8kPzCr/pa1W2XU5feSuel5QyfTsQf57hEtTv/UX3NG7mEw/oSMYONVZs5HuQGZZuwZGUG2jlM4v1smoJbbIrUdgYDC1v7uhBO6jQCNyEZ+FD1mWJYEBcywS80GbmJrSQACKfhDikHWAYXDEFKMrf34nMKIeAB+lBdnigGiiOPYZoqgRmD5LmOWpyNTSoxQftpFKxWek1IjiDw7lGGeuh7F7Frv7fKueWOE85OZKHBZF6MAO4eA8i6dZX2Q3s5B5czUMpei0K7o0iTkUZy0JY2dwpatMU4ByVoTvSyPPY9LBCSAKafSOyBtzEc4lACQeUUuMEYiP7X0+DgpKMZWn833UA0IF6A7XWPxnO78FllFvqKQqmdzcPJ5029yVm57A1wQC5FNAQAxaBEdAgytsVrx+1HZF+aWbCI8AgwA50g3hh14QTiI1DG0nHdAx3gGgax/1jlDa62Zb5/x+aGMJpEv8uS9AVwENjCsLzlhqD8A7qhMOffiGDH8HK0W4VGuLYCGbCAUrA96yjotix2b49iCRV+RMfPVIrlcwBNi2Fy7X2yNEDk3RjVyzvgZxxrZlqd3K9gZ5L+LPCDo6WLPIRNITfNXc/qsGdFn4M37kE/9ArpyPSG7iA7OATRSJAIDeeM4mUuBCE4NMgapQnfmjl5+mfPcbngPNgHIB+A9n15FOLlnHjhwX0A/ajSQmwDaZJQzGQBfFg8bQv9zpGtbjZHJsY58Lo9uApP56aNIkyAKjBcn1zoh196BjTGWuSyzJ5GlZt0CsNYRIozDxJEpC8QCujUSOPo030W56UyOGydR0IbeaBG/rRa6AaFBHktSE5hnj1qniJkbxEJs8YsaeJOQYEONc9/aah66aVISDFlpTViTHCOOop9nsw3UvRDEZMocWKeIDONQw0rWWRDlxii2MtMjCEX6wJiTSXqLTkCOu3/YVcFC+s3ceY7AG6LXGoOBrBnZFdaEvnkmvU+G3Zfu8T02fiibppXJQu5aJ1+56PYaAdXKXGY32GLvYG3RSbX7G99a9r0LMV7WpqRLyaR1h2jLT0wtL3ppXCIzsqyML7vADtKltazcuOizWvZmmUWZXzBQBCvj1C9kJD0LQ0dNLlibLaWb4c5WLTqXuW81+rR2uIsA1UkndRvIVZzi2To5lx6v1RqyLtilWkYxG8U+y9wKeyYjBoloTq0Xuo3tj4wz8ovIMh5wSXkSnWYteR5siGxoZXcigTzL/82ndQWr803IHN1n/PkceXY93DK0k0MgDgbMiQ/rLa9LmV/ubfyMlXmsZXbS79ayNR86Ga7Jt3LmNrp2+V6tmV/3yYP2yLtardSaPUAEhw9R1m40j9YXW+39fF/mUtSxjXvQd+xo64Abl90rZc04vpbvhs6FkemROHCFbLFxtfshgRFRcOuokwNPP72/75e/3G088cTu9yee2J8KeSHgNtKC92a57dAE1AVHqGqUY7DXyJWaIqVgMc2ASmyhaBUFd8kE0RhkBr08zjQujg6gCxgBl/leX+CL0qCwavVP4thuyosiiEice1KeOenTcqpFGGu/15+ohcUQ5Blio5R67cjwiMoDt+OcUAfIA45l8UXEEzDKIMr44GQyiHl9nah5wwBQqBxqn6kBwVaTkTAbZQpYIWoiKgFo5gbEHHIAI5oH6JTHpnPc4qSucRsgCCQDJTFXDFt+Ol1+AYibiTXr4BfHH99tNK5Sbv2dHCJ0GGJzZc0D0wAeRwfR4x0A26i/QV45qmRe5Mm/eTacMfVMpGqccjSqceBq69EaBIKANGAFUBL1ido/QIksRYABSAwSGQiPYpAAPiAWpxpFzYKhY6pdZJhseFcA2O9kLHKOghhDFJF3IKOMUJUNGEF0iDyP2rJS6l7kpfXkObU15d75tjXzzsErs5By+TQ3QCgCUfYkHSGD09iQJ9sO6En11ehOYwikWq9lH6y5vE6Z+0cGJeKC/gLS4mfZQ35XA9F5Izt5oVMANbJwRPtbkfE4Fn5I3qwBeod+5VzVSGRrmNxYI97JvOcZGDK6kBgAPec+Ly5bXkBn7pAZQ3NqPdNb1pi5GKqng+QD8POi9nGZr5hv7+9ekeFV1ocSKa05tn7vnX2XHgibGGvT7/OIeqm3R8lxyLK1hahGKnKmJqkZxcbQt+QHOUa3jrsFDlGeR/BFrvUxd6Tj8Ida/Y64zBeCJMgMDpF1Mklm0lAbqqdH781HoydlhOYk9dRUt4mtHcpWbTVzYF2ZV7bJVn8OdF4LiM6J59GBdGvp2NNB7DwnFmayHuhqdp7et645TVF83/2REfQNWWUfNr/LdD8CH8hwGSog7GLPao1ub235dsXJrWVrBRrok+gnQkHGS+1wFDYP7ssdejbb54eCHubWmAydPOqecbT8UCMLZDv0XZxWFtkfo8pKlM16rZ02yk7n2eJx3H3YD2SaNee+SCx9IE9kYWh7dwR3y8b2yHBsfe8ud+nWn3FGt4He9ix6Ci4NwoiTD3fU6n/lW4b5BGWJBNlONcKRjaltXRynsR8IEQEqfonM8VbmFn1eBiMFONjoqP9o7bJX5gHRYayQYrWDC+ISGIii8TnOrRV7t+6t2cCx5BqGKQ/DMX+R8c4+hV72LO8p8xIOG8r23hyE3aLBduTaPAlix2cFvGvZnHyt1uEhk24Djy3W7LRxJV9l1ueQHTXG5iG3v+QstsCH/kPclaf1BoYfp7+nnLIVTth49NHdhjEzppY6t7EqLbflNsu2ct26dNWLXjSt+fnPU1qxIqWdd+7/8LjHpfTUp6a0YUP/873uldIxx6S0fn1KO+2U0m9+k9KlLpXS+96X0pe+lNKtbpXSpz5Vf8g979n/e+ihKV31qintscfM3y53uZTe9KaUrnCFlNatS2nNmpS+9rWUPvShlN7xjv6zlrR+/OIXKf3sZylNTaW0cWP/70tf2j/b/9/61pRud7uU/uM/Unra01J6/ONT+uEPU7rkJVP6whf6e3uvK14xpVveMqXPfS6lF784paOP7r9fNu/35CendMQRKW3alNIuu6R0neukdI97pHTTm6b0l7+k9LvfpXTwwSn93//NfO8qV0npZS9L6cAD+36fdtqMajJ+Z52V0q67prT//v2lub97/elPKe2+e0qrV6d0zjkpnX12/7Ox/X//r/+e39/4xind5z593488MqXLX76/77e/ndK7353Sgx6U0otelNKvf93/67132y2li188pb/9LaUTT+zHw3f8/qIX7ftBBozt2rUzY/z3v/dzvu++fX/103v5u3sZl/jOnnv2n/nDH1L6wAdS+tGPUrrvfVO60pX65/37v/ff0S5ykf7e+mhcjj22nyft9rdP6YEP7MfM+OmjduaZ/XMudrH+Oe51xhl9P/XvgANS2m+/lPbeu5+Dr3yl/5zPvO1t/bybt2jGmRwY/5NPTrusXJkOWrmyl9VPfjKlP/+577d7HnRQSt/6VkqvfnX/Tve+dz/3+uae+vqJT/Q/f/CDKb3ylSk997kzzyI75PrSl+6fq8/G23j6/j779H/TzLsx/Otf+3HyfBfZe//7+/VyhzuktGpVSl/+ci/z3s28v+AFKd35zin993+n9IpXpPTpT/fzf73rpXTeef06M+b64DM+e4MbpHTlK/dzefjhKZ1+et+/S1xi63VhTdzvfjNrxrq0jqy/Zz6zX8/ubQ7M70c/2j+DjJBdv/N342r+vJ//mwOX9RrzbE4966EPnVk7+vjHP6a0114p/fKXM3J6/vn9/7Xf/rb/e4zl/2/vPMA0qcp8/9YXuicxOQFDUpK6EiUqrLgLa8J0dVdcRFAUFUVAUbyyShAvj4AKIiqKiAi6XhcURHkQdBGEKyAsQ1JymGECTA4dvlD3+Z363u7qmvpCD/QwM/3/PU9PT39f1alz3vOmc+qcqvHjE/khs1tuSXwDdkNff/GLid7RD+jcJz6RnMc59MEnP2n2+tebHXdc4h/vvjvpB/cntHP//ZNro2OnnZb4SvSW9mE7tOnRR5Ofvfc2++tfk+Ox1QsuSPr9+OOTdp9+utmeeybtoc3YKv3D/2kvugzoy/bbJ9dAT+lbfqgP8nrd65Iy8ON5IMtbb02uzXELFiT+x219+nSLjznGov/zf8yuuSap8//9v4mPPeggs6OPTmwCn/zGN5p961uJrNA37B4oCz+FLd1/v1lPj9m3v53orINs0NkDDkhsCBtDP7BbfDBtdB54ILGtdAw5+eTEHtEXoP30JXGJ/vrUpxJ/SX8iM+pO/+MbsCPsBj/6T/+UnI/sP/vZpG3I3nnzm83OOivxwfgn7Bt/BrQNHSB20f+/+IXZsccm/Y1sAR39yEfM3vGO5DNkQ3vo1zToHPHriiuSMtDZRx4ZjBHu/zif/kam6BJ2ga7jg7/85URO8NrXJuURIzgHX08ZnEc8wB/wt8d+ZM+1nIsuSvzQr35l9s53JvZLTMdHkAfkQUxGZ9Av/AL9iq2hY6eckugK9tgOdBt54B+Jgw29DOCb8DXoXLq+H/qQ2b/8y+DfxCrX7XScwPe6n6VN+CFkgkzRPeqMXe21V9JPDz1k9d5e63/Na6wwe7Z1IUd8H+Xzw7H4Y2QK+Dr6lt/UmfKxOT5DfugccqXfqD/n0z/kLGmdoP88juCH3ve+pCxkiCypJ9elDGIo/oz2uq+nTOqAD8G3YYvICLvGlul3zuV4j0v8UC5gN/h8rovMqDN5Bv1HjsO1wf0hekf7sEnk6vGTutx++6Bf5jtk6HrnfYrt7bRT0kfYHLZLu086KdEldJv4TL9QJrqBzv/XfyV/04ee11A39NT7Hlm4bLGZHXZIysYP49/xBdQPG6dc9IDziTeUhXz4nrJdp9Br7OfHP07qTB8Q75An/YQvIM7yN3ZLO/Af9Dv6fe+9SXnIA9AVyiEvoV6/+13ia/FVfEddyK2QPX6XePHxjyf1v+yypM7UibrSNvSKNuCHb7jB7I47htoY+Qxl0a+Ujey4jueC11/f3D5//WuLzj/fah/+sBWuucYirkdd8RX4Yfw09fCysRP6HFtGJ9EHoE+Ix34tdJ64Qr0d2kqcQJfo4z//OZEnsqJvKR97Rs6eq9IWZIx8OQc9JzdAJvhS+oI4jT6lfb37DfooDX3lIB+XE8fRJvQPyMOwzzzoB+9rh3rRfqCf0XHiEKBL+DjsgvKRJ3kduRaxEdl95zuJvd55Z+J7OZa2EaP4QT+wS/wiOuAgN/oIfSeXzUI+Qr7JcZyP3IjP2Cd1vummoccT+486KinvLW9J+gL7RuaMAagj+RMyox/dDwMyob+xO+qEv0KP3bfyN3GTfJDY6GCX3//+0DwBuBZ9wtgW0Ed0D9mi834M+RE5Kjkx/ck10CvkwfcPPpjIgbL4nryA+qBvhUJiy+hQisJ111nMseQ6PnbZXBnx6TCxea6A4u0VrI7hrhKrKJjx9VUH6dUHbHny12/6Z8z4MsPMDDkrVFiBkffQWGbwWU7J0ku2YXCXjjuX3BVl9QgrhLjTyx0NvzvHbDurCvzuB9elnqwqYEUPdyW4I8AdebY7MHvNdhjuuvPcEq7DnXbudnMngDtvlMGsN3cpuEvAHTNm/FmGy1J76sFKB18lw7NtOM+383AXgZlurucPt/O3UXCeP6yTbTXIgtUg3LmmPhzLXXGOT8uIa6A/rOriGNpLO5AHv/mbMqinv9qY5fIstecYtlMhM9//Thls/+LOKH3D3SjuInI3mJVn3Bnjzj135VilQZ8jO8qgTdxV4a45sqauXDt9JwdZcQeCu6WUybW445F+LhV3ctg6x3l8z1057sRRd/7PCihWKPD8IL9Lw7506uqr2lg9w/H+YFDuOnGHh7uRyI8VDMiTlXfp7QzcBWTrCXfW/M4gK3m4LrqBvnE3hL6h33gWE9u+uNPC/6k3d+u428Kqt/RDtmkLx3LnmeXq1M23OiBT+txX0FFGs2d1sU2MrRjImaX0rg+UxzJv+pWl5NwZT9+toj6c46tx6Ev6H/viziY2SJ+zxYj2cpcPfaAN9JHfrWIFFDrEZywj5+45Osq5tB/5sZqF/mHlDO1LbylkdQu6iX2yYoQ+42/6BDmycpG+4m9sGXunPpRL3elL5IMO0GbuJnLHne+QIbLlji06ii3iK/ieO+G+wgR9oc6sXvLn8uAT0BnkxEoNdA5fkV4xhv5QNnLhbj+6io0jG/QCO8M/IFPuxiJvnk3BdWgv/evbfrjTzLXTz2tCp6grdzKRna8YYTsPZbHajPYiH9rjWyaxJa7P99yNo0xW72DXyIr+4q43PiB9l5g+pr7pO+X4amSDjbJ6Ke/FB+kf/Dp3+Klv2jfxzB/8J3ZBv6KblIVe4ss5HlmjK64f/KYv3G7wU/52HOzQH3zPijz0l35kuwh9zyodVpmm/Y2/UtrfvMXqEZbLcyfWX/zAtgXuYGP73GH1F0zQZ7QHX0a/oO/oo6/GIR5gy/gz+tW3vNCv6Cy+MP1QXVaZ4qvREdrA3eS0vFgRQxyhDug2OoDc6Ff0hBUtbKsijqR1khVq2RWerKKjHPQCO0KetMMflo9csCl0nrvTxEXqzxYbVluwFcHLR4+wT1YE4285x2Mc9s8dcuSA7SMf6seWr7yt5dgP7cHv4i9avdmUVTLEGI8z/jkrBygjb2VwFlavYDvp1c7YBiuI+A4dpA7IAp/uK07RJV+xyyoX7Ca9pcxf084dauK7xwiXC7ruMuNv+g6/dO+9cf3++8NDl+vUH19KHyE/11tiAXqDX/HVvKwCQUdZGcLKMfwc7UIPWHGEbyTeIn/iYHqFOHrr20Xw+/hFttoSt9ExyuJv9Bk9Q1/wEe5HqCOrD/E5XBP7ZIUp7af/sT3iGLEdO6AM/u9bV9E93w6fXdmHTLFtfyQDK0FYMUP/EIeoIz6N/qBNviKXOnqf0l+0mfr7W8b8OXuU4a+c91Xr2DK6RTtY4YSdcK5vW8Y/eJ5KHoivxz+yMpmVyvhv2u3PwsHW+Izz8SnovW9pRi5suaWO5KS0B1tj1Uv6eT3U0Vdq5a1Wo48pi9U2tI//4yvwffgb7CktV66ND2L1OKtmaT/b45Gh+z1iP6szuC6r6bAz2kJZyJj+pm/TK1FpM33PtckXiZfoMStmyZd8pZa/nZpxAeU026LET7EY1556Kq5jP/zNNjr0n7jtb5JGtuQT+GX8KP8njrBKF5+Gv8L3p1fPoLfkrn4d/BKxBl1Kr7zBBxOP0rk7P7SPNhCz8Nv0Pe1H78m7qB/l0R/kdXyefTkMdeF69Fte22kPfcRqQ+rnOk2Og3/MW8GGnWMj6W3y2C/yo474c3w09oZd+AtT/EHf6CCxmfbSl+QzyBdfg3+mTfyffANdpE3ES8olH6G9lEVd8f20m7IoA1/CeenVmLTN+wRZY+8cR2zLW1GV9kP+gipWZOGD0cv0NlD8lD9YnTEiuuwy5Hz0k/EW/pfz0SvyGuqNDZF/8Bn1ya42YrUwuksfuO9Ar12XOd/bRZ3IM/zZpdSBvIW4jL9Or37F7sgNkDE+4PomL5zgB/+e3vWwCaEteJsAm/QEFEtySVpxeqlgEhw2QcL3RfubIvIMjESOwIXDIiHE4HF2OD0mZHAgbIfCYD1ZJ0iQQOBQcO4kb8iQBI/AT51wxukknaSOwE8yQ/LKdXHQBDI/hoDN3m8Ci2/xIOFiwED5tIGycbY4SRyZb+Ug8cMR87BIEhYSZtqPg8T5U3fqSULE3/7gTiabeEYLAZQy+I5r4WiZBMLxkewgh+xDPWkDiR7toS3InjbSJhJS2o8MSXb43rcO0UZ/2036LRM4Qgb0lMPxBGWcKJ/zGTIhocAhpx+ETBLvz48iKBL8SASzbxUhgSN4MqiknZTpD3tOH0ebmWTx5JLzaL8nrwQMEt3sGzV8qTNJWXYvPINsJutIBmkP/drs7VX+tgwSVOpKEpLeJkLAJFCzdQYdpN9J7gjcTGqiL2mb8B+SEAKSLwFm8oW+JmmjTj6hQ/3T++7TP5RPfdhS5G8/o199YMsAlX5AN7PnkhjwHDZkk7eFCb2nz7k2gzz6mWuQhPgDTdFX+oJBDDZOX6HrJLL+fB50HV1m8EKCwwQI9sg2HAI91/DniaWTKk9ASTg5l8ERSTHnMBmMzpBoMSniz8hBh/AB/E25JEjoBnJkQpptQMichCPdVnSTpJtExx9cTeLrb3/CjtIPAeY6TPzgXxjMMXHD5yQQnvhjr5SFLvBcAPqBOiAnJkTpI3SYJJaEhPZQX/wCfULChP8jOU4P3kluqCeJny/3xj/6m27QQX/uDO1m4hLd5proHH1Iv5DsZbcd46N8CyU/tIuBbvrByZyffvNb9gd9yb4+m4m59DNI0CV8CjaIfPAfDGyoe3orHO3wLZw+uYX9IyvkTPtIzvkOHUaenIMvy3uFN3LySS3f4oO9oEe+BQn98VjB4NS3dKDbyJABG/40+7IIBqeUQR+iP/Sh9yvJKHL07afYBBOL/I2vxEent6YSJ5ADAyb6l3ZmfSIJe7OBHD7Dn3XH4IQBLBMjxBa3r/Tb2Igv2AzJMfaLvngyjU75QIrPqA/xjv5ikOG6QALN5CLf0370199gxuANeWUfzsoPMZJBCYNW4kuzZ75QZt6bpbxf6ff0FlISdX+NN/kCcsh7kDdtwq8gm3S78SvcFKMP6Wd/SyI2nLfthLLRF/6PT/YHRWNjLjOPJ+gmPhlbITYwKGSiE5+TnoQjzuCD8LHkTf45/ovYRTzHp2Lr+CN0DbsmllAOPga95HPqzA/2RE7G9fDf6TZwnE/uMTnhuk+MpW7oDXKmbH77oJQBN76DfICyaa9PrOJ/6B8fqHI8cSn74hbyFyaAGIQTb5kgx+cTV9PbljjXH1PApIPrND/EJQbq+DlsBt1Nv9kPudCPTFLQ1wy+yX1oT9rHkZeRF2Vfn+4Tj9gv5+OL08/w5Ae/hG9DF7ABfz08eRH6j9xdr6gffedvnkVHsEP0wt+q3Ox5QtSD+MJEADkdeZv7m2bPCyLv8edxoRfpHJK+TD8/kBtJ3LDAz+AT8XnpvMfrim4wEEdX8HmUz2CdyVE/jjpRN+KZv1mtWfw488y4TvvRb/wJNxaoF/JAj4jfyIt8j7iCfHxA7/k89sff5FJcD19FG1xX6Dd0ym88p6/vkxHpB73zf+zQH9Sf3kKInfjb9qgP1yFfJZbQbibFaAvfY5vEHnSQ9ni9kRH5EGMeJl/TE/7u74lb5FHoNXEBXcZfkt8waYXO+WQiPo+bCsiLPA4fwTgEu6Isv+lEvaiT+wHXH2wW3UC/sD8mZsgFiJX0HbmMT84hS/QAf4Cup7f3eazne/wxN3747ZPR6Ai+kGvSF8Qf5Jm+EeOTjP43vhI/QXvy/DD+GxlzAyf9OTLFhxL3sF1kRNyjfxjD4RfxSeSN2Tdo0yfIlz4lx8AvMNFLvPfnVtF2roFeYo/pLXT0Ff3kz6DCV6OX9B/+ipiHHRPPL3wRb37cTOY2GuvXhBgGLD9l68XXvz74GdtKfvKTZIkh37GEleW0LCPMgyWULF//X/8rWUrJForddkuWgd51V3IuS2xZRszyV2BLAUvEL7kkWZrNdhS2KbB9ge1JLGlkW4Nv/QOWRbOcn6XNF1+cLLlkiSRbyxyW2rLFgGW0bLngeJZzs7ySpdIsd2cJJ1tIWMbKFhWWcbI0lC1HlEX7n3km2R7CkmqWjLJcFFhazJaNP/whWVYKLO1luSxbXVimec89yTJOtiyw1YJlq8gQebLNxmFpJnLmOH6zfJalzizNZbkqS7ZpP3Jj+SyujC14LJ9lWSjLi1kOyhJclhyzdJcl8dSZZfWcy/9ZcspSbcpmyT3XYWmw1wVZI3+2hCATZMhyb5bPc2wa+u3CC80+/elkqTt1QKZsc6Gd731vci7LYFmiy/JhlgZzDMtbKZutjyyB5XyXIXJFzrSDZcwsHf7mN4duz/Eti9SLurIE+bvfzddJ2s6y4L//PVm6zN9sE2GJOfpFf6LP//EfSdnIkDYhL7ZOsKzW9Z16URfqz7Jdlhz7smr6iiXkLL3lGpdemtSJ47xtDvrF1jy2ZaG7bKGi3DPOSLauURbL4lnazzJk+iwNsqVeLPdneXB6+xKwjQBbQq7UhSXHyB9don/ZcgbYIzrHVkD0n+Xs2BTLnuk3lr/TB5TBMm7OZ6kyeo0toS/oDvVheyxwzHvek9ilL53H5tlaSxnIjvaxZJntY2n943tkiF6cf37SDi/zf//vpExsF1/h0E62uL7pTWYPP5xsqeA32568XPSE/oB3vzuRPdfAB+E3sBX8FXqF/wJ8Btdiay1Lx6kXsmbpO+3GPrBDbJ4tUcia/7O0HRnSbs7HFtO2Q7toD36BrSToJn3M+WzhZOskdcXfoo8sm2cbC+XhV9jSR/9ge7690PscH87ScAfZsmQ9vTydtrNFLQ9skW2X2EAatiG6DbBlGh1AVvhprkFd2BKE/mIT9AE2yQ/+EZsG+oj2sT0GP4Ad+BYGdBhb9y1qLjPqg87Qp5RFPbg2fpq+/+d/TvQIPWWLLfLxWEEcwmcCW9Y4ln5Hf1miT/+lZYW+YJNsv0Te+Bb8A/UlhrH9D5/Akn/6D7umzziPvmB7DbDVCNsn5tBX9LlDf3Bd7JG6uly+9rXE9g8+ONm+zXYTQM/wD9gYW3oAebKFB6ibx030Btujv+kH+pM6+/YO2s+WCOIiW9WJjcQ3YJsE9cfGkBXbCLx+2AA2hN5Qzz32SLaosN2LdlJHtkjQV+gANpWG6+JP0JM8qB9b8wC/zxYP+oktXvgK/k9d03bPdqsrr0ziDTaN7XGeb73DD+P36Au2IaEv2Ab1T/d7OqcgHlB3yqB/ve74Qd9KQ9/zN3EX3cJ/IytsAhugDx38AHpMX7MV08HuKQN5EBOJR+QaxEvyEbaEsmWVvvnb35LtS/gj+oFcCL3CX7nMgHwJP4uf8r9pNzaIDiBH7Bi98niB/roekyewvc23jpGvEdNvvDHpH+SIfeIL8bfoGDpP+2k7W4A4F11FVugo2zx5VIPLxPXUfQn26ToNyI9tVMiA9hPj8aEO12LrFnJi2xB1pg/wk+RNrsfknegysc2hv5AncYc8AF1Bp9M6Bfh/2oAucByPlMDfo4PEXOSLLiILjkHvfEspMuAz4qpv+cxu2QJyQOqLXNFd+gO99ziSznXTYN/0MW2g7i47fBV6hE8D5MFjIsjH8af0B/qf3h7rdSW24BM4l22V6CHHEScAP42+0UY+p4/Zeo0dZCGPfd/7LGLLKPKiTWxtRhewVXJv6k5sRueIpfS5b4HEPtEp7zdiBTkJNstn2Bmgy2zLQk7k4A75EvpJ/7n9Av2BHqHT5BiU5+Dr6FfyF9pEbCFfJUawHZVcCZ9APCb+4OOQLTku8iNWYKO0Df1GzsgKnSGWcE3iMltzsQXyReI/1yEH54e6MT7A32HnxD/K4Vqcj0xoE8ehn5RN/yA/ftwPUF/8A1s18RXUl7wXX02OQ66BDaFjjEGAchmr0MfkaMgGmXIctkH5rhvEQPQWnWG8QTygH7E52kjsoBxsC93kfI71GIwvItdkHIJvyvphvifmIhvPHwF54e/wm8Q97IQ4wzZotoBTf98yjz3hP/iOcgBdQcfpU+pFTkbsIpfB1wL9j73Q38gkvf3SYyO+nO2tnEOORDvoJ+RCvYmXc+ZYU8iLPEfYjNEElBg+nkDjTAEHQ5DF4TCIxsGSaJPU+iAtDQ4ZIyZhIykEAizBhgSMwI2zYDCBw3BI6BlAMJgmucDxERQImtSJ/6edAQGdZJckESeL4+O6DCYZpDg4AsojaBI8SAaZVGJfPEEPx0mA9PbSLspmQETZOC8CJ8Ec5009cM4EVxwywY82cz6/cU4MRvhN0CQAk7Q1niUUnJtPRCAP34dMMGHygfpRf+rqdeIc6sHnHEebuBZtZaLLnx+CEwR/zgr7sSmDvcYM8kgaOA+Hme5fHG36erQVmSBfT/b4Ln2MD3YZ+HAMQXXu3CTo0o/UkSSJCR0Chz/vhESEwRxl8znyJPgSYCmb4IOukWSQ1BHcaR99wPe0n0SCz0mqCNQkuDwnhyCZrl8akhIGfciMZ2YxuKP+BCnqRtAnWScxJlBxHM8WYODIcdSLsqkLE6X0IYkG+oyO0mYPLpzPxBbHcA56TjJAYEf+tJvEHVmgtyRV9A8JGN97AkI9ScQZTFJW+nkmwEQEyTS25oliGibQ0E/s0JNO39PvyR5JMANRf5YF+kCdSVawW+TN30w0ITN0gHN9zzsBGJtBN/nMJ5RJSugf2k57/flalMf5lI+O+QA7rVsMSGgvdsgAg+84luuQZKOvXIfPHHwK5XId/BLfIUt02cvFx9BfJCgkqCQryJ5kGL8D9Bs6CSSOJEroADJm8Egf+CSVP0cD3aXMrH1wHvIm6USv/DvsHH3Er1G/7HkuD5IgfBv9QkKJb+DZNug7/omEOPt8CvqEZNNBH10X0XMGl+gKPokknASMYxx0nYSVfko/v4Bj8Cf0F36WxI9rkcyl+89/M2hgcMSNB/QIv8BzkrBBf44Muo89ZZ8XRH2RL7pLWUyKkrDj65jwJnGk7xgAcA3KwXaRB4ku57tcuBZ6Q/uZ1PEJWMpAX7Jypx+9HfQ9k1nECtpOWdyswP+QwKIfDAaQCe3iPOyROqRlgu9Ab93X4zdIrH2CA5vj+TvoCOXi/9AtZOgTQ/hZ+g7d8/jhtgbYJ3qC7tPPfm3kQ+JPTGciIV0v9IkJKOwUaAPtdHtDj/jMJ664Lj4ZX0/8Rg6czwAJnfDnsjDJhI9Bf5EfcmJwhPzxM818NNci1gC+5mMfW3cQjrw9luCfmXygXfhxdIa+T5fPJAkTN9i9P28HmfJsrjwo2208/fzGrI2if9wQQAeJdfQhPoRjqI8fS59xDGV52xzqgn1wLfqHOIiuIScm1rAXznc7ZCBHLoDPpXx8AAO9NPhyz3+wT9pDfMLfIAP0Cr/jMZ228jl2gazdd/B/fzYOfeYwOcDkuj/jytvJRAYTKLSBvqYe1BdfzfOl8Pd+LPpB2Wl5pm/O4KfJJQD/wkRAGuTt8YSJT+wGe0dPaSsDVGzXn/GXrn/aP2Z9lsOAFLmmnz9IufhqZEXfoNv4Awah2KmXQd8ja5/AI74y4cfn9Gsa5EMuSd3Jydxn5cWDND75A5znz/7DdpGB2ys+mn5CXsgBf5f26V5XchPAJzIpQW7CDU4fuAP5GH2I38YG0VsmFJEV7SSW+IDeb25iY+SlfnMOeSJHJnmpi/cx+pAeC7iepWXA/9ED8m5sHX3jPOIrMdhtnWsTX8kd0pNP9BXyp46e26fHCfhP9AW9xHelJzyBPIyck5uPjIFoH21AVtwYRi+Iy/Q1MY2ysD3kSR5H3Rk/OPQDdcU30V/4YH4jEybWiGU+viJ2oEf4F2SIDIg56A9lUxcmPxzXH2Ii1yc3RTZ+Uwp7pM+YMPZJFX8eJ5Ph5KK0F/Cv5AvoKfECX0Y8Jbdn/MMNUs6nHvgmz+fQKSaByEGRC+1FXvgZ6ooPZnKWCaI0np+QS9J+9wvInc/RKfrRn/VIrsakJtelXfg1JsnQXybamKTCJ3Ed4q/HOvJKv0lDP1G233DDpyCztP/nxic2xLHEO/SOeIfc8BUep/0mf7Wa3KDJIWackvcM1c0MTUCJ4YOTwMhJIEjwmAXHqPkcZ8JkFANpHBpOgqTXkw7Ow8Ax5myy5YMbjiOpIEFwAyV5w7gJlAQT/saA/YGTDIYwWAwfGKATgDkGh0awYMBOQORY6u7gDCib5BanSPKBgyYA8duv5efg8PgMJ8ugiySYIE9iSNBlAEIw4cHNJEGUQ1DmfCYUCDJM1FEXAhb1RHbUn2MIAgyASLIIkCTMJLMMQEiOCC7AZBLH48RJFDieySzkThDCiXFd2o3jpA2U68GYwEKdCV4EDSYhaA/nUm/KAgInSYhfDxgc4WD9geMMfvgufQwQiAm0/MbZk2zQv5THgwkZeHFdf5gmded89IBgi6wJ9gQTAibfcWeBwMyEJUkEK7wYFPpkG4GTgEe56AdJEYNbjuU7jklDYCS5IUihzwRyghOTN/wm0JA0kJgje3QYeZP80xbkTqKDfAmO9D/n8EOduS5Jld/xoG7IC1nRty5n7qByt5vJFVZCUGdkzwCOfuJ7v4tMooFcSSx99RE6mX0gPvXlurQr724+9oLeEzT9Thf1ItGlD9AREg50Bh3nBx3hPOTKNV23fTUUkwX0JZOsvjKCc9Az2u2rq/ieJIVz6Wd/wCy+A92i7+hT16e0blEWsvCHePKdP6iXCRnsnc+pB9dmwO+TySQk9B86xR1wt23aQvv84dPYKuUz2Kf/+Q785QHYDEk1CRY+hkEGd0bRacr0CUF8AfKjPGTkbaAO6DA6gx7ga/gO2eAP8AP0Db6QviDBAtrEhAt2z2oX9Jy+I2njeE8MAd/o+k5Sj92g0yTZ6AqrWBl0IyvazUQANkq59Cvn0J8k0PywyoEfZO39zbXpZ+yHfiG5x9b5jtjgeu/95/JmkMBEBfqM7PGHDNqYfPaVMfgi6ucvOgDqjW6QzNJe5Ecizd9MatJ+jqFvGITQXuybPsWHkjyT7FKG+zKfAEJPuDvMJAplpP0goEN87r6OvkAuTOhjD9SH+pLsYvP8pl7IwuMOPo6+Jhl2fSCJx1+gB9QPGWD79B/9wIoG9If2oL/EKM5hAEmcBPqPwZ2/kIPY6W0E4gvlo5O0l+MYNDJxyqoufIpPjPmDXymTxNx1CFnRF/h870/qh72mV3FQPj7LH2pM/zLRhQ0R96kDsRaZEweYsMDPMRmFL0rHEIdBGzZGnfDBvkoK2aI7xAEmgKkr1wduJGGHTD4jC+qB/VI+fUeMxCbQe3wkMsLn4XuzdcBf8D3X9wnS9AAi7Z9oK3EBO8aH0d/4APwqx/B/fqMTyJzBDnaU1nPvU/IL9BebY+IX2fm5DJCQp68ABfwV/Y8e+YPE0xBf8N/kIMRS+s4f9szn6D79S124jr/MhEkbysX38ZuJC3wDky4+cQnYgU8+46MpA1lg0+g7+Y/7SnQA+6GOfixQD66R9pX8DcicvnPZ48uI1WnoY2IN0BaOx18jQ65DvzNgRF/pH/ft2X7E/rED2umf0X50lZjAuegCOs7gnIEp7eRz9IXr+USFl8uEFPbLilVWEeGn6GNukDGA5zxkTY6MX/GX4RDb3J7T9XHc5qkvMZBjaTf5CANyf0EKfUmf853LFRvC36AHaV2irv7gafJZ4hXnMSmCL/A+AfSN/Jf+5FroOv6dyQX0gRhJnoZMiAme+/lLQLghi53QP/RZ+gHzeS/6yeaawEQin2EDxF3kwBiE3AK/yyQJcYCJceyXyTGHSTDskmtTRlofPS+h7dQL3fcXBjjoIatnXF70A/kmn3E9/DZ+gTwSX0Mf4NOJD76KNH09fCc3v7AV4ha+zeVADGVyx3MCZIu9UT9snj7kGtga+uc5v4NeIw/0Ad9Cn5GP+aQH/2fSxFcvE/MZp6A75OV+Yw+94dq0kRsM5PmUQT/4anl0nOP9xh/XTOM3vdEHcgdWReF//aHzaZkQ57EVxkPICxmig9gHfhz5kocw6UMc9hXVxBVfKc3kHfrADTbyDSaGyFOIAcgpHe+xCXQde2YyDx/pq+2YuCM+A7bMtf3FSsQ+JqfwtbTDbwwA7STHmzgx8SPYulMqWfyxj1mdMXRa/zdTNAE1DOr1ul144YV20EEH2R577GEf/ehH7dn0DPpogIQaJ4JjZJUHQdwdEs4WQ8Wp47wxRAbpDAhwGhggCSGOnzthJFAYKsHU30DBYA4HgmMjMWYVgm+toGwCIM4fR0iSjhPFUBmM+WQMK2pIxAneOEYSA5a/+tYunJ2/rQpHgEP0bRo4FbY5MDFEO32rD84CB8VkBQGUQRqJKnUmqHI8ThMnSBBloEI5DLIIxDhOkmDKIzgymcBggLv1JGJ+h5z2seTU30yD02SggRPnfI5xSACYWKJ9OHyCOMchG+pOvX2wRxDherSVBAnnizwYvCEz2k7gTW/LYVCArJgk4I4B9SJpJdHHiaL7rLrwN+EhH5wzegEMaghC9CnXwGlzt4GBFkkB51E+/YvukATikAkqJIuURaAhSaLvGQgxOKQNLK1HPiQBJIIkNARoBmgECYIMk5AEYgI5yQhBiAlSEj1PJOl3gi1BgD5Cl7kWeoB+EtTpL5JA+hQ5+l0q6o8d8Jt2ch3aThKKzP0OK9Bvrjvoq0+mIgfqjxwIUiRs6ADfcfeN5BF9J9CRPHE8baJc5O1L6wl0vm0RfLuEv12Hc/w78C2A1BkdwT5JNrhzi5zoJ1/hhU6RXJFIoh9ch7qwPQL5o7vIkGTPkxEGFPQhwR0do32cjy5xLRIN2oC9MBgAAjZ9Q72RD4kRAy4GqbQBG2PAhH2h3/QNgwzskAlM9ARfgt/Bz+BvuBbXoH+ZoKEe9BlJhr/ViKSD61In/kbvfUKOu43YC+2nDsgHWeOb6E/sD7unX5nMQkewBZJA9J42kphj5/gQJkhIgNFjEhv6BJ1DX0jyfGDk23GoB/bAAAubxdeQWGGP6Cjn+3Y2rp9+6xB9jJ/lekwIUWeOQc6+DQcdoI/RVdqHHPjhmiR12IfLD99FEk6/oDMkm9QVvaUsysDf4bupH/aLX6I/6TP8B/3HRAcJG2DztIeEEN1C1zmOO5HoIMkz8YQkFbvHB2IXxBX+ZrKBATx6ArST+jPxy8QWiT36S58gc3QIX4RsiT0kqEzikjwz6UubkBNxhXbg59AHQM84l7Zi50yc+IQBCTz1woZoH5Ml9C/+wgeC/gZF2sS16XfqSlvwzfh5Yhfxj8EK8cO3OvodbSDJZYCNH+XuLL4CPfE3ORJbKJcBFbbAJCLH4Q/9jYq+8ozPfEKfQTG+CTvFV1MGdUT3GdgiB/SHPsbW6Cv8E/pAe4ABETKn7dgi9afeDICJmb4aFr1CR2g3A22fBMFm0C10GrBj/BDHU19iAJMu6DntZ2Dn2yGxU87F1/E5NoRMGNRjj9xNp53YCvUljmF3rBhkoITOoTO0B19AXwB+jO+oA7+RBXaKTGmvv42WspEZ52EnxFTahF3RZmSCbqNjtAvbwa7QJ65BPTkWeeMvsFOuRZxioga9YQIHG8Ae8DnYMXaOHGkLdoDdESeIgUxe08cO56HX7t/xb/gl/Le/YQz9RY+xWfyLx2nyKdpBG/3mDuUjA3wpbSEnYWBITMN/omvIijyOviMe4bt9hSw+FL0n7uEbsSvkhoyoA76Lc7BR7A/5YcP4Ffwq8Z5y8AX8xq/TT8iWv/GXDOaoP+X7ljTiMeUTN/gM3UaetJG8EjtHV9FZ6kDfoiMcg7/nM/SOvkEfGZxzk5U8lX7ARsnrkLFPhDExQWynfdg25eHb8FXYHatkkQUyxYbwUQzG6V/6DbvDN2ErTEjQLr8Bg16QZ3J9fAV2ivyZpCAmYQ/EAvqdNtA/9Am5Ev6ZCW6fMOQ3cR194HyfzMUvkLtjO8gAv4G/oU70A/XEx5Ef0R++fZrr8hk27RP8xE36gHpxTfJx2oVN+9Y+zqePgd/oOmCf1Bl7oQ7oLDkHOkFegu4Qp9FTZI18aAO5JTkpcYZ2++QB9svkGjEI/0O7fSWX57L0KdfHFojD6CT6ha3i0/Fx2DTxiJwHX8XNHXQeeeJ/6DPqgW7SXiZqfMs6Okg/oUtcA59IHEAW/jgPzkVPfIIEPfE3HPtNZ2SJj+cc2kE56CCfOf62XOwAv0lbKRubxDegl+gbfhJf6jsNiNXUA3n5zUKf7KFP6QNiFWWhq+RJyIa44m+rwx4pE9njM4hjyAs/RP5AjoGOYh9MfuKLsCvqj0/G5/p2QsrFz6JTjO/QVfQCO8P3YZuMT7gGvgq9wc59QtTfIk3cxtdyLLLF56JTXJc4jN/FP1N34iG6iF577ojPw18wJsHHo2/IEV3DV9E++gIfTV6AbpCDHnNMIn/GF26Hq1db9K1vWeQreDdzIh4E9XJXYlPhoosusp/+9Kd2zjnn2OzZs+3cc8+1efPm2XXXXWdd6TsBHXB/Y3n3axlcbSoQbK691moHHGjFr51t9c+dYoVS0eKzz7b4rLMsWrXK4qhgUb1mla22CfOb5QXPms2cYfELL1h11iwrY2jz51t0zjlWv+giq07CkQ1OqpSWLLTCUUdZ/cc/tgLHnn221c/+WnC89e6xVuxba9VpM6209PnEqAlYt9xi8Qc+YNHNf7D4n95kEQ5l0iSLTjrJ+n91nZVWLbeIwdrrXmfRtGkWM9j48IetsuU2VuhZY8X+5BXCcaViha9/3frPPseKa1Zb4YnHLJ69pRlvvF+0yGKc3fz5VtlxFys//YTF48Zb9MQTFm05O6nDQQdZNH68xc88Y9FWW1k9KljhIx+2GMe2cqVVp0yz0vXXWfVd77ISgQnn+opXWG3adCs+/phF/f0Wz5pl1TnbWmnFcrO1ayw69FCLb7jBojlzrD/qsvKTj1i0zTZWKXZbsdJj0eLFFk2ZYvELSyx6+qkQDPov/I6VH5hrUV+vVXbfw0pPPG7RjBlW7+m12oxZVrJacKqUU+2rWfH+e6267/5WuvtOq+z9OiuvTF73XBszxuLucRaXSlZa8kIi9yWLLVqzyuKZMy068USLmWxZvNgKN99s8Xvfa/HyFVYfM9bqEydbafkLFj36qEWvfrXFjz1m0dKlVn/1q61A4CRBwOEuW2b94U5mkuSU1iy3aMUKi37zG+v/2HFWXLrUalNnWBTXrPTAXKvtvIsVf3CJVT71aY4O55QXzw8BPrrpJosPO8yiri7rn86gILLyouRZBNGECVadOMWK115jtbcebvUJW1ip1mfRM89YbYcdrG5lKy1dZBFB7D3vsWjHHcOEc/T44xZ1d1t9zBiLenqsut32Vlqz2ioTp1n5qsut8oEPWJkgRJ3R/7FjLeIuBoMakpp997XKlnOsvGSx1QsFi/j+ssss/vCHLSIBe/LJ0O91BnT83P+ARTu+MgTImIS5v98Kzzxj9VfsaIV77rbK295upfnzLPLVU/vsY/3z2NYSWfmRBy3afnvr7xp8dWvU32tRsWDF311v0b77Wv9M7nAVrPzsE1bZZgcrLl9qhZXLQ/JXmT47sVfqsWRJ8nyGAw+0/i2S1SjIsjp7jpUevM8iksXlyy2eM8fi7m6LFiywys67NPqkGvqtUC4lCRyTQOWyRSS1J5xg9QsusKix/DzabjuLn3/BKtty1zWy8ooXLDrzTKuc/00r/fIXVj/sMCvccYdV/uXNVlq+jIAV7DRavjz0c8xA6NBDrTZpihXGdFnUGNxEs2dbrbfPomol2AfJfXX/N1jpGex1S6tVq1YgqVq1KvR57ZTPW1QuW+FnV1n93//dojvusOg1r7F6qWQF+qer26r044olRsCsTppm5YfmWrTDDlYpjbHiiiUWPfigRTvtZJWtt7HSc/OCDtfxSw88YDG2ttW2FtXrVqz2WjRvnlXwJ1a28gP3Bjkgp9rF37Wot8cK8+YFGwu6u2KF1V/xSitMnmTxkiXBt5bv/atV9tzbSvOetsIPf2jx8cdbdO+9Fl9xhVWuuCr0cXHp81Z8x9utfvU1Fs2YbvHCRVabPiPoRJEk9LHHrPKmw4LcQ/8+93RI4ipn8Hy8gpUv/6FVPnR06NNCpc+KC+ZZjIwmTrT4/vstet3rrL5oUfi7WoutuGKZRdOnW8wgZK+9LPrIRyz+6letsudeLCpP2rpk4cDzEOItt7To8Scs6mo8A+qII6z+0ytDOysTJlgJf4jNvPBCkEFMcrhmjVUmTLEorltp0fwkYSOFYbBCsvgP/2DxihVWnbGlRYW6Fc84w6pnnW2lxQsteuopq+x3YCizfMdtwX7iri4rXH219X/8U1ZGr/G/Y8ZZjH+4+cZQXnTxxVb5yplJzPnpTy0igdx9d6sVS1ZYvcqimTOt0j3eSic2tvoyEb733hZNnmz9U6Zaobcn+MTEVy0Kg5LokEOCPy8tXmDxxC2scPpXrPYfX7biqpXJYBbfSDLPwHnGDIve+lbrv/MeK/asstrYicHnVWamBhUNyg/8T4hHbMTFH4Wke7/9rDJ9pkW12OJiZOUH77d4++0t+vvfg84zGIiJpXfdZZUDDhzwq+gJ+oXPivFV2Pzvf2/1NxxkxfvnWrz77ladNsNKxMlp06w6aXpSh2WLg27Rvwxkq+Vxjf6nVkUrLltihYcfsGi//ay2arUV1q4xu/U2swMPCD4JfeSY2hT8TmSlep9Fjzxq8ZytrV7qtuKSxRZPnWoRk36HH26VqVOtjC7vmKx+LsX9YdAV2oYd7767VSZPt9Kfb7Fon32sXquFuInPKS18zgonnWj1886zwqRJ1j9hykAcqlsx+La4VBzIUQqrVlhxXHcyITJ1qlVC26pWWNtn8dgxVnrk4RBbawxYimUrVvqSAR++7+ijrXrVfwY9qszY0oovLLJ4+gwr3XiD9R/2FistmBcGtSGOoM+1WpBdef5Tob4xKwj4/c+HWuGzJ1v8la8kfrjx7BbilUWFMHCuztrSCpVei9b2WhzFIR7ThtLi56ywaGEywNp+e4ufeMIqr9zFymtWWL1Wt8JDDyZyYxC85ZbB14Y8BR9PPtZ4Zlt1znahH6pbbWUlrvuNb1jM4K6726pjeHZJbOUnH00G3w88YPVXvtKKjVWq/Vux0jayqFa10l/+bNHrX2/xX/9q0T/8g9VWrkoUuVC0aN4zYeAZPf20VXff00pLnrd69xgrPP2U1Xbbw4qXXxbKjw8+2KrFMRbV+ywulEOf1mZvFeJaYdxYs7vuNps106JHHrHqga+3InHp0ccsetWuVo/jENcZBlUnTxnU/bgaBuCl2/4U8sbK+EnB1usTxln5wQeCn6vMnG2lKLYYP7VilRXjmtWmTLEafbZkYcibqpOmWmnhAivMmhH0rt7XZ/GEiVa6+fcWvfGN1l9Ar0pWnvtXi3bd1ao9fVafhPzKVn7mcYve9S7rv2duw0dXrLRsecgj8c9RX0/QT3xIvWuM1Scn9oK+2P/cZ7bvPmGATE5Q6+m1QndXMoBm0oDBL75zyRKLJ04M7alVaxZ3dVshrll1/AQr9fZYdcx4K99+m1UOfIOV/3CT2ROPW+XY4yyKCla67b+t8vqDrbRiqdnaHosWPGfRzTdb/ZRTrFapWoHyJ24R+gaKy16wqGeNVbfaxkprV1l03XUWHXaYxeSi6DETY//2b1a/7jqrk98+vyDJS6bMtNLCeSFOVKYOrjqiPIvicG61a5xFtYqVaom+1qZMs6h3rRUnTLD4nnuCbOO5c60StjgmuWb5b/cH390/dZqVl7xg0ZFHWv2SS6zAOeg0cfUjH7FqI5cs1Hqt+POfW/yOd1h1i6lWWLnMiuWixUuXWnXrra1cr1uMb7n8covf+jarzZhhpWLBbP5zFs171voPyGyvpA6PPWzRJz9p1V9ebfWJk6y8fInVY7PChPHBt9Du6uzZVp4/z6ozZoT+Ka9aaZUtplr5qUeTGDN5ipWfmx9iJOOzmImlZctCfs/EUPWPfwq2EM2cYdVKLdiH1eoWTZ9m8cKFQX79c+ZYFBes9LOfhpsFEZOZ+EryavK0+fOt/4DXWyEqWHHuvcnkG/kJk9133mn1k0+2In3562stIk9hS/ehh4Y8uh97ePaJZEz07DyzCeOtit8LujzdCiuWWB07wTf9v/8XxpfILurpt0LvaitWq9Y/Y3YSwxcvCuX0T2U1URTsJsRHJpMOPthqt9+R6Fzwy40Ydv//WP2VO1nxgm9a/1dOt/Jtt1l04AFWX7YixK/iyqWhzyuF7uDf4/FjrbBypdUmY2eDK+/KSxdZHG6ULTUb023R3Xdb9ZB/stJNN4aJR2y1cs99VrruV2HymPEO+UN9wUIr1KpW2WZbK61elcQOxguvetVArs48GKbJHDRTCQyPxo+PBjYlbEoMZ25DE1Ad0t/fb/vvv7997nOfsw9wtyg8A3NlWA119tln29uZtR2hTtpoWLLE+reYMmCUpflPW31rHly6KhgsAyyccpLsRBZFkRX711i1TACqW7HSnwTnnpXhs8HEbtDIS4vnW33KFCsuWhgms2pMZMV1iwslK1Z7rFYaa6Vqj1VLYxur4P35DyUrkqj6Esg1a6w6ZUajbI4phIkokqx6yrF4WRBFNV6t0PiuZlGtZnGxy0rLnjebuEVIaqsTJltU67M4BNWalSp9FnPNas2iNWusPnmKFXrXWnXLba1glfBZbXzjDligYsUly6ywdrVVtmEAWrVCX8UK3aUwQVQfu0VIoKtRkdhqUa3fisWiVSImOCMrVNdavTTWCj0rLVrTY4XustUmTAqTXWFwTgLaSMIpIyTzS18IbQ4Dr55VVmEAE/eHMosrliaD93rN6gWzYq1qcV+/1cOWilJj4BA1fuIwGGAipR7+TsovMKCYON5qxW6LG3JFBvGYrtDnyK1e7rL62DEMJ6xU7bX66rVW6CpZJVynPNgfcZ9Fzz1nla23b8gruW7SN8UhAxk/J4piKz39uFW23d7Ka1ZZZUDekZWXLEgGrdu+0oqLF1gtTMBY0MvQzi0mhOsHXV32fEhCi7WKxSRQtWoIvpWpM60YV6wWlcJEUmXabCuQsI8fZwX6fPxkK69eZpUJk6w0/1mLt5hoVuX5SZHVpk4faEOhtzdMUMVMpjHpuXRZmCSsbr+jFer9FlfqVigXrFboMosrnGFRrW4xA5nVK0I/F1fzQM26xWPHhQS5PtYnmyIrVdc2dDm9XD2RVzmuNnTIrIT9jU32x0dcJ+hJIdhToW9NSKIKTN5YHJK/cFyl3+Jycj6D37i3z+Lx460+dboVXlgcEoZEXwavXehhIrNm9YlTrLR6mVXD4K4eEqAgu1LJ6lHR6mOSNtAHhWpfGNgX46rVmMCN6+GYAgl0VzH0QVwoWnnpYqtX62YTxllt3CQrVNZajP4VCo0BfzIwLPX3mS1fYdWZW1mhd5XF3WPDgKy0aHGYGA+DtQL6V7DSvKesGraLxWHyg6S2vPi5MJkRUzdkYHWLy43JhNDnU+hlixnchfPJGAph8FDZFvuOLKr0DJxTtIrZ8lVWm5wMMkK/rV1utfETeM1iuHaRyeda1WpTZ1lpwTPBl5T711h9ba/VJk8JyX8cYwMFK6xYZjE6+/TjVg3ZivcBdvmC1adMtXK9PyRXiS6ge31hkq46ftLgsdV+i4pxkG+yMDoZ8Hh5pZUvhAncMj60t98Kk7awStf4AT8S5NG7yqr4r2XPWx3dKJYtLkQDZRT6Vluhq2zVqMsKtb4wyChX1oZJwLi/EiY3KaMyZmyoI/NKte7xVu5bHSaKmPCsuj5GNSsw8T2m2+KVq6y+zXZW6F1j9f6a1Seg2xUrLlpstVmzgy+y8hirFxN/Vly7xmL83YTJVnrumRC3imtXhYGX+45CX4/Vu7uCHTB5hM9iYqs2bdaAD8UXBv1h8BtFFvXj55JYV16x1Crh5ko8MKgt9q6y2hj3713hHPrRfwfbxDYYZI/tTgaIY8darVq3+qQpFlUqwQaLa9CXQR+XprTi+TARxORcbfbWFsf0YWLfid/kd3LPsVztDb45HjOmkbBXMzZcs2K9EuRWeP55i2fMDAN2BtT0FeXh0xJbcyIrRpVkAozvuiekYnCx0dbYytUeq5TKVly21GpTkkFAbaJvg/Lrx1as9Vq9xOT/aquPmRBsLJ49y2pMRD2/yGozpltx2QqrTUkmv4pxv9WY2Fu1NAxoGWAHf01s610TdBZdr5cS22PSNUzohv5Kyij0UW/f/lAbEmvKtR6rxbEVqtXGRMtgXUuLkr6rT540MGEV1StGSlFavDj4IGzDdTjJkeKGDhSC7613jbVCjVhQDe1N/Edfw/dSl8jKtf5wA6qMDa1ZGyZZmARnUjbiPCZ0w7H8pv/LQ+Mh+dHYsVZf02O1YCuJDyg/81i4wUIuECb5mZzBhuZsa0UmdbaaY8XnnrXqVts1YshYK5HfTJgc2lBYs8rqwacwUbfMbOyYMMlPe7mxiC5XxvkWw8F4Hy9dboXxY60yIE+0J2hQ4nPLXSEWBn1ctcJqW0wJN4/iZcvNJk0MOeXQnI321q1U6Q3+wLrKoc+rY5FnqJ2V8KfEz4FrJvo5eP0o9Gc0bYpVGvmh20eiu11WYqKmkZch1+oWky3uQm8iK1bWNOrVsIm+1VYLWyFLQb7FqGaVkKs1/GvvSquG/uYa5XDDjaoQVwblVUttWmnkWf29Vg83vz3vSia7yYXj/lqIo8FXrV4WdMu6uolgSYwK7ShZedmygTjvupxMtg32B/oZ4fsnJDED3+dx0/WyFFeTCNOIIcXK2lTfWEMXC+GGTrDVcsGqha6Qw5fxA4Wy1SclY4d1cd+U9g9VK/SsDTlz6O++tQwVrNbIiQZy3VqvVUK+7raA3ZkVlyy06tQZQUaFhQut0oizNWTOZOHYbN3djhpa1NsT4lKw71rF6v1Vqwcda+RctUq4bnKz7xWZukM93PDjuqGnw6T7NCv1r7VqmJhI9DIZ57jvDpJL2rfgmXBuIYqTm0N9/RZPnBR8ITGzyg3kkDOn7I3PuyeEG311JpWLRauGFW7kwPVwgyzcWGRSsr+S5MzbcYOW8wupHLpixReWWm06E4LcDFpotZmzrfjsk2FCCFsr9621SsP/R7Ves1J3yH0THegLk6bpfuUGZ2XWVg35pXZ6DIxBalbu6wk3e4JN1fusRi6IzpMb0ZeNGOvtLb6woFFHt/GSldHdqJwslkAPqr2NSdJBXz5IKp/FV8WFkO/VQz5Vt+KSF6w+fboVn5tvVRY0FJKdUlG1agxvyY1YkBF0pK8nGZdyw6SnJ+gm5TMvzyIqFmD7ciAWsvE3CzBZTLUpoQmoEWDu3Ln2vve9z2644QbbIbVH+ogjjrCdd97ZzvAl45vxBFR9+WAASiYF6o0Jm8RqojoP2y40BrSRRWtXh1VCnvgymcKETrRmpcXj3Ulkg40HWZxhLdxZiSdMCHfLONevva6zaAzyqwTeqsVhYiNKJXmWfBcVLQ4DkfT5jYmMuNaYwPFrkNAxMCtavVAOiWG92DXwO5zDHRgS1i4GITz0lYmXdOCKw52ZdN2T80thdQYTV9yNsO6uIXdaI4Jp99DEPtMbA/9LEr/GA/dSshhMgMtWYHBEApIpo7BmdePcrEzjxkA3fe28xZJER+68kiz2NgZgSdJSICiHdqdkHOpTCpMbyWRVVgdiK8RVq4ckJv05yWU92SOdqlOBySxWqZBMFsoWVXotbtSBiULqlVyPktMTV7EVGFwVBhOSJMhn6sLqoHAXvNToQ2/L0N+h70l+C1FIMKlkkCL63k+iMjajCyk5VysWl7otYvXDuDHhe2QQV5I7koP97baW1YV1dTl8yqCZcofIOpGlTzIk8uIakRX61zZ0JLaoHjcmD/wnkQ13FZkcicdPyFzX7Waofg1OFqbrVmtM3G0RBv3e15QdN1aKUC/rIoEa7ItwTM8ai0OCWW9Mmvrg2tbRv8Hr+f+HJn/J+eUBG0nXEd0I78ItFi3CpgcSS5d3+hqNujX829DBQnZw4xOohZTepQcW3j+hFinZ2oC/db0dsO21q6we/GxmcGLVsIpjqGzCtGgy8RDa1LDLINcxmX50edQbA52x60wAFypMuiC7YqgPXyV+DDuoDtjXYHk2VGacw7apcsnioAdZBv13ejI8YsI29D3/rwY5RPj3MLHQ0Icgp8Yxjcmb8DkDKSaJh0zK1MNkJ3e+g83y/4FY0ND9Ad8y6FeH2l/Sj4MTSv551u4a7epdbXGYfB3018HPVZJBc7I4Pcrtj3x7G9T1MInRXw0rCAb9ZUq/wwTg4GRlWt6DxGE1XvB/wcENtiMijhJTUz40nI3PLSVyXjd2DB1EJ/FyTZBBtpwhdQj/DvrbqNof/Fq+POJ8PQu60fBza1dafVx24iEt67S/yPpb4mL6cXrpMoh5ySB80A8M9RFDr+OPkuLmxJrGRHx6oJknP///YH8z6YT9RBl/mF//+oBPYUKuNqB/UE08TqNvB8pnwnbAv+THv6F1HOxnci5WrSU5z7o3HEOMDf4r6Y/ByUFWL/SY9VWSGzqNa7ECvjaQFw2dHPT8j+s55D2hNkNyn7S95ckpzvHbjb4Pdp+Vsdel4dODL03ngOk+iywKTtJvFjb0YGCSsXFM8PVZ/7Fu7CdmkxMN2k5SZ/w9yjUoC/LOSkjVkuukZZDyqyEXyd54bNQi1a5Bn5z+f0qiA/4xdX7jOFaXDfr6qJF3p681tI2Jr8/zDdVGNQcnK4rEuXDjIz2B4WWm8lBW8Y8fN+iLBurUyPvDatGhk/HJzbD0Z8n4IMmfhspxqA9K5wJOIz/nuzhKJkOqbLsqNGJYSucaN7iGtiW5/qCupNs46D/CGAO5E9O4SUK/EG+L3MhLx9uGbw3+eGyykjJ3HDDov0OMKTDeKzXkl25jfl8mN24HxxuDepKMZwbjbl4eEluBGxEDeUs8NN8foofoFf3jeUvWZzVu4OWMNbgZnI1Fg5+5/2zkVeF8+q4W+s1vsOT5lIibauHmwFDf8ZvfJDv48mB3NrtpNyU0ATUC3HjjjfbpT3/a7rvvPhuTejjYZz7zGevt7bXv+2tNh9FJKOqOeQ/b3Ejp7vYgnpcIpSdFhibug7hzzEvO08c4eQlcXrJgmeQzm1BnA222DesmEUPPSdc7PSjMK7dZ3Qs57ctJlAcmC/La0UxO6yYL65aflXmrujvZgU52oJzt22w7Oyk7r5xm7c07J9uu9DHZSYhsUMu2I2+CLd2OrPzyg9q67chLbpvpiaV0Kzuwapb4p+uaHWyk7a2dzufpSPYct/G8fm2lf81kak30q5nupJLIIRNr2X7K+p7swC57jeygpNUgNJ0cDtYhSRSz/ZW9Tr7eMSiJm9avkWzl+oahSeHQeqY/z7Y/q9N5Pjmta+18XJ4NZOuTZxNpfcr2QfYa6fKy/ZtXl2w56w641q1b1odl5ZtH5/28rk7m1bfV381s39rYaTOZ57Wjlc9tFnuzbWrW9vTvrExa2XsnupiuU/a7tKzz4nxeXbP/z5af1zZrEe9b+e1WbcqTSZpkfcK6/iPveq3yhjzZZY/LtjV9nXSds7LIG4Rn2561tXSZrfs+8Y3p66Wvn65Xto7Z/+fpRjvdyl4n74bH4PdJnLCMPJrlZ9kysm1vFtvz/Go6R2um+3n59rptaP//bLnp89PH5vntdm1sVZ90G7PXSZed9VPN2tLK17WKd+38dZ4/Sn/Wqc61krnLApKVO4mPyNpcup7N/FDetfLs0zpsd6ty023I2mPWF+Xl9elz0/LMXms4dtYqn2h2flZ/suVG4VGtPFIs/d6YNB/4QGwXXRRbd3fqDaAbOY/xuJUo6mhxTd4tR5FDT+N1xtlnPXV3d9uK9KtIh0GlUrGH06/53MjZMzzLI2phhNkVGulEwFp8bsMos9k57f6f/rtZWXlBLuuk887Nc6jNrpcXWKJMoMg62Va0a5OTlxC3+hzy7iJ1UpdOjl+f75oFumbnRi3a0ura2fLbtduPSwfKvInWZv3azC6arXLolHZ669fIHt/s7/Tn7RLPTuuVPq/VXcu8ZIdkvllbml2z1Wdp20z3RSsbSZeC7a4vnNsqEUv+P9jioT6jeRKX1sc8OQ7Hz+bXKduO4ZHnM1vJYLiftbpWs2NafdZqYDBc8gYArY4dro21OqdTTS2ux3U7PW44cW59rpE+NtuHw4lVI1Gvl+JaQ+0/yRuGc15WDq18SPrvduVmP/c6tjovG6taxcr8uDCYN6VJx+H4JbbJZrTKb6GYrILKve5L4Ve8DpaTT3RCMz/5Uuv3S+XXs7SKh+ljOs2t212rHa1sBoZuk+ucaJg2iN6tOwnSPN9tJ588GWb9S7N6N6tnO/+TLbeVzLIr79tdfzjkTU4Oh+RcdqOyBa8Z8+ZFtnp1bE88senME0Cnz8TWBFSH+KonngWVXgHV19dnY/3Vw8OkXC5vUiug2B7cnGxS0MzoOx3kNCs/7/Nmx3daRvb7Zg46/f9OnE42icpLjtJ3bNJ3LDq9RrN6pz/Pu8vQaVvyJhTbBZBWsk8PiFvpQit5tSo3fW62ntnA2OlgdDgBJmsDnd51yZaRLe/F2kwndtdJYM7eQVvfJK5Z3ToJ7K2u7d9ldTVvMjzbJ60Sm2Z1SZfbqV20qru1sJFmetXOfptdczi+uBM7bbeKrlXZ6xsXvA7pctrRrp+ydWmXaKc/Gw7t/KW9iES5lSzy2tPOJ2Xrlb3Oixm0t8ob8q7fym7zjsv+PZzJ1nblNiMrk3Z0MiBO1yH9u50PaFVGp/Jrlhd10rZOYkTWb+fVoZPymtllp/GqnW68FINXL+elKDfbj+3a2s7O87ZZrg+t2pOtQzvd76SsZvnJ+tCu7zspt11/ZvUsL0dZH1qNMfLym1Y5VPq4djE+79jhxp5seenj88Yg7a6V1570dfKul/6smb9rZx/N6rbu5xMmJC/Y44WyeRx4YGzTp8c2bVrygo1NZQVUp2gCqkO25I0uxktIFtu2qUfT8/cu/lrMYcIytXHhWUWbDmwfbh0Amxlzq4G4tTknb7DazKmkj7MWx7QbJLVy0Nlzsg40S6fBM9uG7LHZstPLTztJmFolK3n1aVfvVnLMS4Ty+qdZ+a3k2Oy7Zu3ID5LpZzPlJ2/t+j77u11S2WzwlGcjeXrZLonuJCg2u3b2u+EMOJrVt13C1uycbD3Sf+ed38on5MmsXZKepwdp3crTtVbXblV2tg+y/Z09bziDhmZbUTrVn1Y2nL1Gng0004dO9ThdRvbvdvqY91menuVds9kxzcjqQzM5tNL39P+b2X0r35BtR971WrWn3XfNfEK7c1v5hE7q14m95Olsnpw67c9WPj3vGp32R97frerVync2u0Y8TL/cyg46lYP/v1lb0/9v5ROzn6Xbkf6sXZxsJZdW8amZD89eO+/8djrR7PtWfdPMP+a1MftZu7a2Or/V53nf513HyZPBSzHRkr1uqzq3a3uzuNSqXdnP8vqzlW62a0vW7vLqlK1HK/1td+28nKZZ/Vv1XzubzLtm3jnN+iuvjFZtadfOVtdr1r707/Tn7drrxw0eO3Om2amnml1zzbpjayanjjoqsrFjWcm16cwTMK/RKZqA6pBdd93VJkyYYH/5y18GJqB4C95DDz1kR7KJc5TQehVUnjNvlRQ2c/Z5pI9tZeytnFK7pCt9nH+elxA0a0fWoWUddbvkrF3ykT2/3fNy8tqXd71sW/Ou2+yYVgl+1EFAbZaANfu8VfvyAkqL/islb5LrLCnNq2+z4Jlue7tEtFkbmvVP8v+IN3I03j7WPHmxDus+3Dq2CuDtzsnSygfk6U+nv5vJ1MvK1j9PPnllNCvT2nzWTiZZ35Mmz192IhProI7t+quZbrWSc9qmWtlxO5vOXtP/38y22/nQPJvqxFbyrpF3fp68sse1s4dmcmjW5k6vl1dWVh7Z52l02let6py+Xt61O5FHXps76cdO/E7W7pr1bTt/nVe3Vv61VZ3SdKorzfzA+vjlVrLNO7ZZPfLa0axfWulEq+fW5LU9fc3stVtdN8+vt1rxG69Hv8frcXwze8y2oVU/tWp7Wlad+pi8+mVlknftZn69WdtaXcs/z26xzLOjVuenaRY7st8169NOYoStx3dZP5Wte6trp4/N88Ot+izq8Ob3i/XncYfPhmzla5t9n21Ps3q067dm/rnZ8c3anq6PGWtbbrjB7Pjjzf7+9+TbvfYy++53zbbZxjZrNAE1jD2NTDSdd955NnXqVNt6663t3HPPtdmzZ9thhx1mowW2dlZ4I2mglTPM0mkCsz5lvBTn5gXIZt9lA0HeeXnnpH9nnaP/blWPZvVKl9GuDdm/mz3fJq/sPCe+PtdOf9Ys+c+jXVBrVvdsuanv48hKUdWq67jCZslus+tGw7CHTtrXTH8an0XdjVdU5785rHkdbQTq2OoarcrKft8subYWdpJ96H32+1Zld1rHZrJplqS2Oq6dnDq1pXaybyWDZmV3ct1Wcs4bTKWv26ruecflHdOpbqfrljco7cQm8q7RahDQinbxsdM6ZOvT6fXy7hxFw3x2SqdtbVZ+s7KGE+va+Z/s3636ajjxZjgxtdl3nejNcGWcd26r3KNTuQ+3fzo9d7jX7NSHDdcm8j7PK6/ZpMZw9XCk/m73+fqe12n8HK5NZY9rFS87bXs2h82Ly+3q1Mm18nINj3WtzotegtynXTntrp2V89B+Kix93gpLnrfqTru2iJvp8ouph5pnj1kff56NsZ3ae/b/zT4bju0Pp1zLxNZOJqGGljN9utnBB5tdd52F5z0VCmZbbGH2ile8mFiwaaAJqGFwwgknWLVatdNOOy28+W6fffaxSy+9NDzLaTThzV27tic8RP1Vr3rVMLcSbuqGtT71X5/E6KUq/8Wev77JzYu97ktBJ3UvW5mnAS5dasaromfMWK8rrb89rGc7Bl7bvLkQbaQ6+mLLHM61R9IXjLSfiV6kPbxUfTTcxP3FlL2pMJwH9G+qbcxj42nLyMaHTUMGm15bXsxE3OZEtAFtYn2vtaH65+XMJUao/AXzecuU5Y5kp00zu/fenOU4nb7YZ7hsanY23Bev5LPTToP2MHv2qzapbXfriyaghkGxWLRTTjkl/AghNrOlfbNnv9y1EEIIIYQQYsPwwAPNv1uyhOfNqCfERjp1J4QQQgghhBBCiE2DVjdf2ROWevO7EC8VmoASQgghhBBCCCFGEzvvbDZlSv5373538ro2IV5iNAElhBBCCCHEhmTBArNHHzV76imznh7JXgix4ZkzJ3kV28SJQz9/7WvNzj8/eSq2EC8xegaUEEIIIYQQGwKeqfKnP5mdeKLZ448nzyA88kiz00/f/N+9LYTYuGCb3d57m913n9n995s980x4KLntsIPZllu+3LUTmymagBJCCCGEEGKEiaLI7LbbzA4/fPBD3sL6ox+Z3X13shJBgz4hxIaEN0Bvv33yI8QGQFvwhBBCCCGEGGHKS5eanXRS/pdz5yZb8oQQQojNGE1ACSGEEEIIMdJJ99q1Zo880vyAW29VHwghhNis0QSUEEIIIYQQI0xcKpmNHdv8gK23Vh8IIYTYrNEElBBCCCGEECNMddo0s2OPzf+yXDY7+GD1gRBCiM0aTUAJIYQQQggxwtRYAfWFL5gdcMDQL3gT3rXXagWUEEKIzR69BU8IIYQQQogNAdvsrr7a7KmnzG6/3WzWrGRCis+7u9UHQgghNms0ASWEEEIIIcSGYvbs5Gf//SVzIYQQowptwRNCCCGEEEIIIYQQI4omoIQQQgghhBBCCCHEiKIJKCGEEEIIIYQQQggxomgCSgghhBBCCCGEEEKMKJqAEkIIIYQQQgghhBAjiiaghBBCCCGEEEIIIcSIogkoIYQQQgghhBBCCDGiaAJKCCGEEEIIIYQQQowomoASQgghhBBCCCGEECOKJqCEEEIIIYQQQgghxIiiCSghhBBCCCGEEEIIMaJoAkoIIYQQQgghhBBCjCiagBJCCCGEEEIIIYQQI4omoIQQQgghhBBCCCHEiKIJKCGEEEIIIYQQQggxomgCSgghhBBCCCGEEEKMKFEcx/HIXkLkcc899xii7+rq2mQFRP0rlYqVy2WLoujlro4QLyuyByFkD0IoPgihnEmI0TaG6O/vD3Xfa6+92h5b2iA1EuuwqSpXtg2b8gSaEC8lsgchZA9CKD4IoZxJiNE2hoiiqOP5Da2AEkIIIYQQQgghhBAjip4BJYQQQgghhBBCCCFGFE1ACSGEEEIIIYQQQogRRRNQQgghhBBCCCGEEGJE0QSUEEIIIYQQQgghhBhRNAElhBBCCCGEEEIIIUYUTUAJIYQQQgghhBBCiBFFE1BCCCGEEEIIIYQQYkTRBJQQQgghhBBCCCGEGFE0ASWEEEIIIYQQQgghRhRNQAkhhBBCCCGEEEKIEUUTUEIIIYQQQgghhBBiRNEElGhKvV63Cy+80A466CDbY4897KMf/ag9++yzTY9ftmyZffazn7V99tnH9t13XzvjjDOsp6dHEhaj0h4effRR+9jHPmb77befHXDAAXbCCSfYc889t0HrLMTGYg9prr32Wttll11s3rx56iAxKu2hUqnY+eefP3D8kUceaQ8//PAGrbMQG5NNLFmyJIwh9t9//5A3nXTSSbZo0SJ1ktjs+P73v28f/OAHWx6zuY+pNQElmnLxxRfbVVddZWeddZb9/Oc/D8Hk2GOPtf7+/tzjGWA//fTT9uMf/9guuOACu+WWW+z000+XhMWoswcCxzHHHGNjxoyxK664wn7wgx/Y0qVLw/F9fX0vS/2FeDnjgzN//nw788wz1RliVNsDudHVV19tX/va1+y//uu/bOrUqWGAvmrVqg1edyE2Bps48cQTw026yy67LPzw/+OPP16dIzYrrrzySvvWt77V9rjNfkwdC5FDX19fvOeee8ZXXnnlwGcrVqyId9ttt/i6665b5/h77rkn3nnnnePHHnts4LNbb7013mWXXeKFCxdKxmJU2cMvfvGLcHxPT8/AZ88991ywkdtvv32D1VuIjcEenFqtFh9xxBHxUUcdFWzh2WefVQeJUWcPzzzzTMiN/vjHPw45/pBDDlF8EKPSJviOmHDzzTcPfHbTTTeFz5YtW7bB6i3ESMFY+Ljjjov32GOP+M1vfnN85JFHNj12NIyptQJK5PK3v/3N1qxZE7YOORMnTrRXv/rVdtddd61z/N13320zZsywV77ylQOfsWQwiiL761//KimLUWUPHMfdP1ZAOYVC4m5Xrly5gWotxMZhD873vve9sPXouOOOU9eIUWsPf/7zn22LLbawgw8+eMjxf/jDH4aUIcRosQlypfHjx9uvfvUrW716dfj59a9/bTvssEM4T4hNnQcffNDK5XJ4BMHuu+/e8tjRMKYuvdwVEBsnCxcuDL+33HLLIZ/PnDlz4Ls07NPOHtvV1WWTJ0+2BQsWjHBthdi47GHOnDnhJ80ll1wSkiz2cwsxmuwB5s6daz/60Y/sl7/8pZ7rIUa1PTz55JO2zTbb2I033hjiAvkTA/NTTz11yIBDiNFiE4wXzjnnHPvyl79sr3vd68JAm2N/+tOfDty8E2JT5k1velP46YRFo2BMLasWufiDzlD4NN3d3bnPsOH47LGtjhdic7aHLDwHikTqc5/7XHjWhxCjyR7Wrl0bdJ+f7bfffoPVU4iN0R5Y3cGzPVgle/LJJ9t3v/tdK5VK9oEPfCA8iFmI0WYTcRyHh/Dvueee4Rk5l19+uW211Vb2yU9+MtiLEKOJnlEwptYElMjFtw5lHxaI4o8dOzb3+LwHC3L8uHHjJGUxquwhnVTxsMGvfvWr9olPfKLtWy+E2BztAf1nK8X73//+DVZHITZWe2CyiUH1N7/5TXvDG95gu+22W/g/XHPNNRuo1kJsPDbxu9/9LtykO/fcc23vvfcO243Yss1LK1g1K8RoYswoGFNrAkrk4kv/Fi9ePORz/p41a9Y6x8+ePXudYzGe5cuXh2W0QowmewCedXPKKaeEJOqLX/xieMOLEJsDw7UH3vJ1++23h7vb/PC2L3j7298e7EOI0ZYvMQmV3m7HgINtefPmzdsANRZi47IJnnnDTYoJEyYMfDZp0qTwGasFhRhNzB4FY2pNQIlcdt111xAI/vKXvwx8xsOTH3roodxn2PAZ+7rTgeLOO+8Mv7mbIcRosgf4/Oc/bzfccIOdf/75dvTRR2/A2gqxcdkDz7r5zW9+Ex4wyw8rooDn32hVlBiN+VK1WrX7779/4LPe3l579tlnbbvttttg9RZiY7EJBtyMH9Lbi9i6zYSstm2L0cY+o2BMrYeQi1zYe3rkkUfaeeedF55Zs/XWW4elsQSJww47zGq1mi1dujS8yYU7dzzRf6+99rKTTjrJTj/99BA4eJjgu971rqYrRITYXO3h6quvtt/+9rdhEoql5M8///xAWX6MEKPFHrKDan8ILc/44KGaQowme+AhywceeKB94QtfsDPPPDPYwIUXXmjFYtHe+c53vtzNEWKD2wRjhUsvvTSsFP/MZz4TyuDxBTzz5j3veY96RGzW1EbhmForoERTTjjhBHvve99rp512mh1xxBEhOSJA8BpJnsLPswsYZANvrLjooovCm78+9KEPhSDCK4YxHCFGmz2w2gO+/vWvh8/TP36MEKPFHoTY3BmuPXz7298ONyc+9alPhfN4JtRPfvITvaRCjEqbYFvRVVddFZ6byRjimGOOCcfxGYNyITZnFozCMXUUY+1CCCGEEEIIIYQQQowQWgElhBBCCCGEEEIIIUYUTUAJIYQQQgghhBBCiBFFE1BCCCGEEEIIIYQQYkTRBJQQQgghhBBCCCGEGFE0ASWEEEIIIYQQQgghRhRNQAkhhBBCCCGEEEKIEUUTUEIIIYQQQgghhBBiRNEElBBCCCGEEEIIIcQo4Pvf/7598IMfHPZ5v/rVr+ytb32rvfa1r7W3ve1t9rvf/W7YZWgCSgghhBBiI+Pb3/627bLLLi+6nFNPPdXe9KY3vSR1EkIIIcSmzZVXXmnf+ta3hn3er3/9a/vSl75k//7v/27XX3+9vf3tb7eTTz7Z7r333mGVUxr2lYUQQgghhBBCCCHEJsGiRYvsK1/5iv3lL3+x7bfffljnxnFsF1xwgR111FFhAgo+8YlP2N0y1kZXAAAF7ElEQVR332133nmn7bnnnh2XpRVQQgghhBBCCCGEEJspDz74oJXLZbv22mtt9913X+f7P/7xj/ae97zHdtttNzv00EPDKqn+/v7w3ZNPPmnz58+3ww8/fMg5l156qR133HHDqocmoIQQQgghNmKuvvpqe/WrX2333Xef/du//Vt49sIhhxwSEr80K1assC9+8Yu277772j777GPnnnuu1ev1dcq76aabQpJJOa9//evtq1/9qq1duzZ8t3r16lD2m9/85oHEkzuf3PXk2KVLl26gVgshhBDipYLt+Gzv32abbdb57k9/+pOdeOKJ9q//+q/2m9/8JqyU4vlOp5xyysAEFJArfOQjH7EDDjjA3ve+99kf/vCHYddDE1BCCCGEEBs5TCSRHPLwz0suucT22msv+/rXv2633nrrwPfHHnus3XLLLfaFL3zBzjnnHLvnnnvst7/97ZByrrvuOjv++OPtFa94hX3nO9+xT33qU+Fu6Cc/+ckw0TRhwgQ7++yz7amnnrLvfe974Zyf/OQnYcn+1772NZs6derL0n4hhBBCjAzEeyaf3v/+99u2225rb3jDG+yMM86wG264webNmxduTgH5Bc9++tGPfhRuSpE73HHHHcO6lp4BJYQQQgixkcPkEIkedxxh7733tt///vf23//933bQQQeFu5dz5861H/zgB3bwwQeHY7hDmX4AOWWcd9554Xh+OzwL4uijjw6TV2984xvtwAMPDCutmOhimf43vvGN8MyHf/zHf3wZWi6EEEKIkeShhx4KOcQvf/nLITkDPP7442HrHrD66d3vfnf4/6te9apw3mWXXRbyjU7RBJQQQgghxCZA+iGfXV1dYTWSb53jQaAkiEwuOePGjQuTRnfddVf4+4knnrCFCxeG5zVUq9WB49iux8qnP//5z2ECCj7/+c/bbbfdZh//+Mdthx12CH8LIYQQYvOj3lhF7ZNLaWbMmGEPP/xw+P/OO+885Lsdd9wx3AgbDtqCJ4QQQgixCTBmzJghfxcKhYE7lDz/afLkyRZF0TqJo7N8+fLwm2X1r3nNa4b8sLx+8eLFA8eOHz/eDjvssJCUcmcze20hhBBCbB7stNNO4TlP22233cAPN6zY6r9mzZqQJ5AX8CzKNI888kjYsjcctAJKCCGEEGITZ8qUKbZs2TKr1WpWLBbXmXSCiRMnht+sZuJB5VkmTZo0JKm84oorwhL7n/3sZ/aOd7wj9605QgghhNi0+ehHPxqeM3nRRRfZ2972tjD59KUvfcnmzJkzcCOLFVI8O3LWrFnhTXnXX399WDn94x//eFjX0gooIYQQQohNHFYpsa2ON9w5vMWO5NDhwePTpk0LDxTlDXj+QzJ5/vnnh2c5AOWceuqp4a7mz3/+c9t1113Dg0f7+vpelrYJIYQQYuTgzbff/OY3Qw5x+OGHh7ff8SByJqQcnkP56U9/OhzHC1F4QDlv1dtvv/2GdS2tgBJCCCGE2AwmoEgWTzvtNFuyZIltvfXW4e11S5cuDZNOwMqok046yb785S+H/x9yyCG2cuVKu/jii23RokVhib2/DYfJqKuuuipsvTvrrLPCw89JOpmYEkIIIcSmyznnnLPOZ295y1vCTyuOOeaY8PNi0ASUEEIIIcRmAHcqebvdhRdeGFYrcYeS1yrffPPNA8cwkcRzHH74wx/af/7nf4YHle+1117hvG222cb+9re/hQmoI444InwOTEwdddRRdvnll9uhhx4a3sAnhBBCCDFcotifXimEEEIIIYQQQgghxAigZ0AJIYQQQgghhBBCiBFFE1BCCCGEEEIIIYQQYkTRBJQQQgghhBBCCCGEGFE0ASWEEEIIIYQQQgghRhRNQAkhhBBCCCGEEEKIEUUTUEIIIYQQQgghhBBiRNEElBBCCCGEEEIIIYQYUTQBJYQQQgghhBBCCCFGFE1ACSGEEEIIIYQQQogRRRNQQgghhBBCCCGEEGJE0QSUEEIIIYQQQgghhBhRNAElhBBCCCGEEEIIIWwk+f+Vy/zN84ymVQAAAABJRU5ErkJggg==",
@@ -1102,10 +1120,21 @@
    "execution_count": 17,
    "id": "1a18ab20",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[IO] CSV file is saved sucessfully\n",
+      "[IO] CSV saved successfully\n"
+     ]
+    }
+   ],
    "source": [
-    "df_clean.to_csv(processed_dir /\n",
-    "          \"insurance_cleaned.csv\", index=False)"
+    "path =  processed_dir /  \"insurance_cleaned.csv\"\n",
+    "         \n",
+    "write_csv(df=df_clean,path=path)\n",
+    "print(f\"[IO] CSV saved successfully\")"
    ]
   }
  ],
diff --git a/src/insurance_analytics/core/registry.py b/src/insurance_analytics/core/registry.py
index d91b99b..683b73e 100644
--- a/src/insurance_analytics/core/registry.py
+++ b/src/insurance_analytics/core/registry.py
@@ -21,7 +21,6 @@
         "model_dir": "src/insurance_analytics/models",
         "checkpoints": "src/insurance_analytics/models/checkpoints"
     },
-    "artifacts": {"artifacts_dir": "artifacts"},
     "docs": {"docs_dir": "docs"},
     "notebooks": {"notebooks_dir": "notebooks"},
     "scripts": {"scripts_dir": "scripts"},
@@ -91,10 +90,6 @@ def REPORTS(self) -> Dict[str, Path]:
     def MODELS(self) -> Dict[str, Path]:
         return self.paths.models
 
-    @property
-    def ARTIFACTS(self) -> Dict[str, Path]:
-        return self.paths.artifacts
-
     @property
     def DOCS(self) -> Dict[str, Path]:
         return self.paths.docs
diff --git a/src/insurance_analytics/eda/stat.py b/src/insurance_analytics/eda/stat.py
new file mode 100644
index 0000000..bce77e0
--- /dev/null
+++ b/src/insurance_analytics/eda/stat.py
@@ -0,0 +1,58 @@
+# src/insurance_analytics/eda/descriptive_stats.py
+
+import pandas as pd
+from typing import List, Optional
+
+
+def descriptive_statistics(
+    df: pd.DataFrame,
+    numeric_cols: Optional[List[str]] = None,
+    round_digits: int = 2
+) -> pd.DataFrame:
+    """
+    Generate descriptive statistics (count, mean, median, std, min, max)
+    for selected numeric columns in a DataFrame.
+
+    Parameters:
+    -----------
+    df : pd.DataFrame
+        Input dataset.
+    numeric_cols : Optional[List[str]]
+        Columns to summarize. If None, all numeric columns will be summarized.
+    round_digits : int
+        Number of decimal places to round the statistics.
+
+    Returns:
+    --------
+    pd.DataFrame
+        DataFrame containing descriptive statistics.
+    """
+    if numeric_cols is None:
+        numeric_cols = df.select_dtypes(include='number').columns.tolist()
+
+    stats = df[numeric_cols].agg(
+        ['count', 'mean', 'median', 'std', 'min', 'max'])
+    stats = stats.round(round_digits).T  # Transpose for easier reading
+    stats.index.name = "Column"
+
+    return stats
+
+
+def summarize_for_markdown(df: pd.DataFrame, numeric_cols: Optional[List[str]] = None) -> str:
+    """
+    Convert descriptive statistics to a markdown table string.
+
+    Parameters:
+    -----------
+    df : pd.DataFrame
+        Input dataset.
+    numeric_cols : Optional[List[str]]
+        Columns to summarize.
+
+    Returns:
+    --------
+    str
+        Markdown table of descriptive statistics.
+    """
+    stats_df = descriptive_statistics(df, numeric_cols=numeric_cols)
+    return stats_df.to_markdown()
diff --git a/src/insurance_analytics/hypothesis/balance_checks.py b/src/insurance_analytics/hypothesis/balance_checks.py
new file mode 100644
index 0000000..df0a6dc
--- /dev/null
+++ b/src/insurance_analytics/hypothesis/balance_checks.py
@@ -0,0 +1,88 @@
+
+"""
+-------------------
+Check if Control and Test groups are comparable on key confounders.
+Supports numeric and categorical features.
+"""
+
+import pandas as pd
+import numpy as np
+from scipy import stats
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+def check_balance(df_control, df_test, confounders, plot=False):
+    """
+    Check balance between control and test groups on specified confounders.
+
+    Parameters
+    ----------
+    df_control : pd.DataFrame
+        Control group
+    df_test : pd.DataFrame
+        Test group
+    confounders : list of str
+        List of columns to check balance
+    plot : bool
+        If True, plot distributions for numeric features
+
+    Returns
+    -------
+    pd.DataFrame
+        Summary table with balance check results
+    """
+    balance_report = []
+
+    for feature in confounders:
+        if df_control[feature].dtype in ['int64','float64']:
+            # Numeric feature
+            mean_a = df_control[feature].mean()
+            mean_b = df_test[feature].mean()
+            t_stat, p_val = stats.ttest_ind(
+                df_control[feature].dropna(),
+                df_test[feature].dropna(),
+                equal_var=False
+            )
+            balanced = p_val > 0.05
+            balance_report.append({
+                'feature': feature,
+                'type': 'numeric',
+                'mean_control': mean_a,
+                'mean_test': mean_b,
+                'p_value': p_val,
+                'balanced': balanced
+            })
+
+            # Plot distribution if requested
+            if plot:
+                sns.kdeplot(df_control[feature].dropna(), label='Control')
+                sns.kdeplot(df_test[feature].dropna(), label='Test')
+                plt.title(f'Distribution of {feature}')
+                plt.legend()
+                plt.show()
+
+        else:
+            # Categorical feature
+            contingency = pd.crosstab(df_control[feature], df_test[feature])
+            try:
+                chi2, p, dof, expected = stats.chi2_contingency(contingency)
+            except ValueError:
+                chi2, p = np.nan, np.nan  # Handle low counts
+            balanced = p > 0.05 if not np.isnan(p) else False
+            balance_report.append({
+                'feature': feature,
+                'type': 'categorical',
+                'chi2': chi2,
+                'p_value': p,
+                'balanced': balanced
+            })
+
+            # Optional bar plot
+            if plot:
+                df_concat = pd.concat([df_control[feature].value_counts(normalize=True),
+                                       df_test[feature].value_counts(normalize=True)], axis=1)
+                df_concat.columns = ['Control', 'Test']
+                df_concat.plot(kind='bar', figsize=(6,4), title=f'Distribution of {feature}')
+                plt.show()
+
+    return pd.DataFrame(balance_report)
diff --git a/src/insurance_analytics/hypothesis/interpert.py b/src/insurance_analytics/hypothesis/interpert.py
new file mode 100644
index 0000000..15935c8
--- /dev/null
+++ b/src/insurance_analytics/hypothesis/interpert.py
@@ -0,0 +1,23 @@
+import pandas as pd
+def hypothesis_summary_generator(results_df):
+    """
+    Generator that yields a summary of hypothesis test results row by row.
+
+    Parameters
+    ----------
+    results_df : pd.DataFrame
+        DataFrame containing hypothesis test results with columns:
+        ['feature', 'kpi', 'p_value', 'reject_null', 'description']
+
+    Yields
+    ------
+    str
+        Human-readable summary line for each hypothesis
+    """
+    for _, row in results_df.iterrows():
+        if pd.isna(row['p_value']):
+            yield f"Cannot compute test for {row['feature']} on KPI {row['kpi']} ({row.get('description','')})"
+        elif row['reject_null']:
+            yield f"Reject H0 for {row['feature']} on KPI {row['kpi']}: p={row['p_value']:.4f}"
+        else:
+            yield f"Fail to reject H0 for {row['feature']} on KPI {row['kpi']}: p={row['p_value']:.4f}"
diff --git a/src/insurance_analytics/hypothesis/metrics.py b/src/insurance_analytics/hypothesis/metrics.py
new file mode 100644
index 0000000..b7985fe
--- /dev/null
+++ b/src/insurance_analytics/hypothesis/metrics.py
@@ -0,0 +1,120 @@
+import logging
+from typing import Optional
+
+import numpy as np
+import pandas as pd
+
+logger = logging.getLogger(__name__)
+logging.basicConfig(level=logging.INFO)
+
+
+def _require_columns(df: pd.DataFrame, cols: list[str]) -> None:
+    missing = [c for c in cols if c not in df.columns]
+    if missing:
+        raise ValueError(f"DataFrame is missing required columns: {missing}")
+
+
+def claim_frequency(df: pd.DataFrame) -> pd.Series:
+    """
+    Compute claim frequency flag per policy.
+    Returns a Series of 0/1 integers (1 = at least one claim).
+    """
+    _require_columns(df, ["TotalClaims"])
+    # Treat missing TotalClaims as 0 (no claim) unless you prefer to keep NaN
+    freq = (df["TotalClaims"].fillna(0) > 0).astype(int)
+    freq.name = "ClaimFrequency"
+    return freq
+
+
+def claim_severity(df: pd.DataFrame, keep_na: bool = True) -> pd.Series:
+    """
+    Compute claim severity per policy *conditional on having a claim*.
+    For rows where TotalClaims <= 0 or is NaN:
+      - if keep_na=True -> return NaN
+      - if keep_na=False -> return 0
+
+    Returned Series aligns with df.index.
+    """
+    _require_columns(df, ["TotalClaims"])
+    total_claims = df["TotalClaims"]
+    # Create series filled with NaN then set positive claims
+    severity = pd.Series(np.nan, index=df.index, name="ClaimSeverity")
+    positive_mask = total_claims.notna() & (total_claims > 0)
+    severity.loc[positive_mask] = total_claims.loc[positive_mask].astype(float)
+    if not keep_na:
+        severity = severity.fillna(0.0)
+    return severity
+
+
+def margin(df: pd.DataFrame, fillna: Optional[float] = None) -> pd.Series:
+    """
+    Compute margin = TotalPremium - TotalClaims.
+
+    Parameters:
+    - fillna: if not None, fill missing TotalPremium/TotalClaims with this value
+              before computing margin. If None, preserve NaNs.
+
+    Returns a Series aligned to df.index named 'Margin'.
+    """
+    _require_columns(df, ["TotalPremium", "TotalClaims"])
+    if fillna is not None:
+        tp = df["TotalPremium"].fillna(fillna)
+        tc = df["TotalClaims"].fillna(fillna)
+    else:
+        tp = df["TotalPremium"]
+        tc = df["TotalClaims"]
+    m = tp - tc
+    m.name = "Margin"
+    return m
+
+
+def margin_rate(df: pd.DataFrame, eps: float = 1e-9) -> pd.Series:
+    """
+    Compute margin rate = Margin / TotalPremium.
+    If TotalPremium is zero or NaN, result is NaN.
+
+    eps: small number to avoid division-by-zero; zeros are treated as NaN.
+    """
+    _require_columns(df, ["TotalPremium", "TotalClaims"])
+    tp = df["TotalPremium"]
+    m = margin(df)
+    # treat too-small premiums as NaN to avoid huge/inf rates
+    safe_tp = tp.where(tp.abs() > eps)
+    rate = m / safe_tp
+    rate.name = "MarginRate"
+    return rate
+
+
+def attach_metrics(
+    df: pd.DataFrame,
+    *,
+    keep_severity_na: bool = True,
+    fillna_for_margin: Optional[float] = None,
+    include_margin_rate: bool = True,
+    inplace: bool = False,
+) -> pd.DataFrame:
+    """
+    Attach ClaimFrequency, ClaimSeverity, Margin (and optional MarginRate) to df.
+
+    Parameters:
+    - keep_severity_na: if True, ClaimSeverity is NaN for non-claim rows; otherwise 0.
+    - fillna_for_margin: if not None, fill missing TotalPremium/TotalClaims with this value before computing Margin.
+    - include_margin_rate: whether to compute MarginRate.
+    - inplace: if True, modify the input df; otherwise work on a copy and return it.
+
+    Returns the DataFrame with new columns added, aligned to the original index.
+    """
+    if not inplace:
+        df = df.copy()
+
+    try:
+        df["ClaimFrequency"] = claim_frequency(df)
+        df["ClaimSeverity"] = claim_severity(df, keep_na=keep_severity_na)
+        df["Margin"] = margin(df, fillna=fillna_for_margin)
+        if include_margin_rate:
+            df["MarginRate"] = margin_rate(df)
+    except Exception as exc:
+        logger.exception("Error attaching metrics: %s", exc)
+        raise
+
+    return df
diff --git a/src/insurance_analytics/hypothesis/pipeline.py b/src/insurance_analytics/hypothesis/pipeline.py
new file mode 100644
index 0000000..6758280
--- /dev/null
+++ b/src/insurance_analytics/hypothesis/pipeline.py
@@ -0,0 +1,81 @@
+# src/insurance_analytics/hypothesis/pipeline.py
+
+import pandas as pd
+from pathlib import Path
+
+from insurance_analytics.hypothesis.metrics import attach_metrics
+from insurance_analytics.hypothesis.segmentation import segment_binary
+from insurance_analytics.hypothesis.statistical_tests import (
+    t_test_numeric,
+    chi_square_frequency
+)
+from insurance_analytics.hypothesis.assumption_checks import evaluate_hypothesis
+
+
+def run_ab_tests(df: pd.DataFrame):
+    """
+    Run all A/B tests for provinces, zip codes, and gender.
+    Returns a dictionary of results.
+    """
+    try:
+        df = attach_metrics(df)
+        results = {}
+
+        # ---- 1. Province ----
+        provinces = df["Province"].value_counts().head(2).index.tolist()
+        A, B = segment_binary(df, "Province", provinces[0], provinces[1])
+
+        results["Province Risk"] = {
+            "Claim Frequency": evaluate_hypothesis(chi_square_frequency(A, B)),
+            "Claim Severity": evaluate_hypothesis(t_test_numeric(A, B, "ClaimSeverity")),
+        }
+
+        # ---- 2. ZIP risk ----
+        zips = df["PostalCode"].value_counts().head(2).index.tolist()
+        A, B = segment_binary(df, "PostalCode", zips[0], zips[1])
+
+        results["ZIP Risk"] = {
+            "Claim Frequency": evaluate_hypothesis(chi_square_frequency(A, B)),
+            "Claim Severity": evaluate_hypothesis(t_test_numeric(A, B, "ClaimSeverity")),
+        }
+
+        # ---- 3. ZIP margin ----
+        results["ZIP Margin Difference"] = evaluate_hypothesis(
+            t_test_numeric(A, B, "Margin")
+        )
+
+        # ---- 4. Gender ----
+        A, B = segment_binary(df, "Gender", "Male", "Female")
+
+        results["Gender Risk"] = {
+            "Claim Frequency": evaluate_hypothesis(chi_square_frequency(A, B)),
+            "Claim Severity": evaluate_hypothesis(t_test_numeric(A, B, "ClaimSeverity")),
+        }
+
+        return results
+
+    except Exception as e:
+        print(f"Pipeline error: {e}")
+        return {}
+
+
+def save_results(results: dict, output_dir: Path):
+    """
+    Save A/B test results to a JSON file.
+    """
+    try:
+        output_dir.mkdir(parents=True, exist_ok=True)
+        out_path = output_dir / "ab_test_results.json"
+
+        import json
+        with open(out_path, "w") as f:
+            json.dump(results, f, indent=4)
+
+        print(f"A/B testing results saved at: {out_path}")
+        return out_path
+
+    except Exception as e:
+        print(f"Failed to save results: {e}")
+        return None
+
+
diff --git a/src/insurance_analytics/hypothesis/segmentation.py b/src/insurance_analytics/hypothesis/segmentation.py
new file mode 100644
index 0000000..16fd3d3
--- /dev/null
+++ b/src/insurance_analytics/hypothesis/segmentation.py
@@ -0,0 +1,189 @@
+"""
+Module for insurance data segmentation and control of confounders for A/B testing.
+"""
+
+from typing import List, Optional, Tuple, Union
+import pandas as pd
+import numpy as np
+
+
+def split_control_test(
+    df: pd.DataFrame,
+    feature: str,
+    group_a_values: Union[List, str, int],
+    group_b_values: Union[List, str, int],
+    copy: bool = True
+) -> Tuple[pd.DataFrame, pd.DataFrame]:
+    """
+    Split dataframe into Control (A) and Test (B) based on values of a feature.
+
+    Parameters:
+        df: pandas DataFrame.
+        feature: column name used for segmentation.
+        group_a_values: value(s) in feature for Control group.
+        group_b_values: value(s) in feature for Test group.
+        copy: if True, return copies; else return views.
+
+    Returns:
+        df_a, df_b: Control and Test dataframes.
+    """
+    if feature not in df.columns:
+        raise ValueError(f"Feature '{feature}' not found in DataFrame")
+
+    # Ensure lists
+    if not isinstance(group_a_values, list):
+        group_a_values = [group_a_values]
+    if not isinstance(group_b_values, list):
+        group_b_values = [group_b_values]
+
+    df_a = df[df[feature].isin(group_a_values)]
+    df_b = df[df[feature].isin(group_b_values)]
+
+    if copy:
+        return df_a.copy(), df_b.copy()
+    else:
+        return df_a, df_b
+
+
+def check_balance(
+    df_a: pd.DataFrame,
+    df_b: pd.DataFrame,
+    confounders: Optional[List[str]] = None,
+    threshold: float = 0.05
+) -> pd.DataFrame:
+    """
+    Check for confounders across Control and Test groups.
+    Returns a summary dataframe with mean or proportion differences.
+
+    Parameters:
+        df_a, df_b: DataFrames for Control and Test.
+        confounders: list of columns to check balance. If None, uses all except target.
+        threshold: absolute difference threshold for flagging imbalance.
+
+    Returns:
+        pandas DataFrame with columns:
+            - feature
+            - type (numeric/categorical)
+            - value_a
+            - value_b
+            - difference
+            - imbalanced (bool)
+    """
+    if confounders is None:
+        # Exclude known KPI columns if they exist
+        confounders = [c for c in df_a.columns if c not in [
+            "ClaimIndicator", "ClaimSeverity", "Margin", "MarginRate", "PolicyID"]]
+
+    summary = []
+    for col in confounders:
+        if pd.api.types.is_numeric_dtype(df_a[col]):
+            val_a = df_a[col].mean()
+            val_b = df_b[col].mean()
+            diff = val_b - val_a
+            summary.append({
+                "feature": col,
+                "type": "numeric",
+                "value_a": val_a,
+                "value_b": val_b,
+                "difference": diff,
+                "imbalanced": abs(diff) > threshold
+            })
+        else:
+            # categorical: compare proportion of each category
+            prop_a = df_a[col].value_counts(normalize=True, dropna=False)
+            prop_b = df_b[col].value_counts(normalize=True, dropna=False)
+            all_values = set(prop_a.index).union(prop_b.index)
+            for val in all_values:
+                p_a = prop_a.get(val, 0)
+                p_b = prop_b.get(val, 0)
+                diff = p_b - p_a
+                summary.append({
+                    "feature": col,
+                    "type": "categorical",
+                    "value_a": p_a,
+                    "value_b": p_b,
+                    "difference": diff,
+                    "imbalanced": abs(diff) > threshold
+                })
+
+    return pd.DataFrame(summary)
+
+
+def filter_balanced_confounders(
+    df_a: pd.DataFrame,
+    df_b: pd.DataFrame,
+    confounders: Optional[List[str]] = None,
+    threshold: float = 0.05
+) -> Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]:
+    """
+    Returns Control and Test groups, along with a balance report for confounders.
+
+    Parameters:
+        df_a, df_b: Control and Test groups.
+        confounders: columns to check balance
+        threshold: maximum allowed absolute difference
+
+    Returns:
+        df_a, df_b, balance_report
+    """
+    balance_report = check_balance(
+        df_a, df_b, confounders=confounders, threshold=threshold)
+    return df_a, df_b, balance_report
+
+
+def summarize_groups(
+    df_a: pd.DataFrame,
+    df_b: pd.DataFrame,
+    kpi_columns: Optional[List[str]] = None
+) -> pd.DataFrame:
+    """
+    Compute simple summary statistics (mean, median) for Control/Test groups.
+
+    Parameters:
+        df_a, df_b: Control and Test groups.
+        kpi_columns: columns to summarize; if None, use ClaimIndicator, ClaimSeverity, Margin
+
+    Returns:
+        pandas DataFrame with summary stats.
+    """
+    if kpi_columns is None:
+        kpi_columns = ["ClaimIndicator",
+                       "ClaimSeverity", "Margin", "MarginRate"]
+
+    summary = []
+    for col in kpi_columns:
+        if col not in df_a.columns or col not in df_b.columns:
+            continue
+        summary.append({
+            "kpi": col,
+            "control_mean": df_a[col].mean(),
+            "test_mean": df_b[col].mean(),
+            "control_median": df_a[col].median(),
+            "test_median": df_b[col].median(),
+            "control_count": df_a[col].count(),
+            "test_count": df_b[col].count()
+        })
+    return pd.DataFrame(summary)
+
+
+# -------------------------
+# Example usage (not executed)
+# -------------------------
+_example_usage = """
+import pandas as pd
+from segmentation import split_control_test, filter_balanced_confounders, summarize_groups
+
+df = pd.read_csv("insurance_data.csv")
+df = attach_metrics(df)  # from your KPI module
+
+# Split by feature, e.g., Gender
+df_a, df_b = split_control_test(df, feature="Gender", group_a_values="Male", group_b_values="Female")
+
+# Check confounders (e.g., Age, Province)
+df_a, df_b, balance_report = filter_balanced_confounders(df_a, df_b, confounders=["Province", "VehicleType"])
+
+# Quick KPI summary by group
+summary = summarize_groups(df_a, df_b)
+print(summary)
+print(balance_report)
+"""
diff --git a/src/insurance_analytics/hypothesis/statistical_tests.py b/src/insurance_analytics/hypothesis/statistical_tests.py
new file mode 100644
index 0000000..5298c6c
--- /dev/null
+++ b/src/insurance_analytics/hypothesis/statistical_tests.py
@@ -0,0 +1,117 @@
+"""
+hypothesis_tests.py
+
+Run statistical tests for insurance A/B hypotheses.
+"""
+
+from typing import List, Optional, Tuple
+import pandas as pd
+import numpy as np
+from scipy import stats
+
+
+def chi2_test_categorical(df: pd.DataFrame, feature: str, kpi: str = "ClaimFrequency") -> Tuple[float, float]:
+    """
+    Chi-square test for independence between a categorical feature and binary KPI.
+    
+    Returns:
+        chi2_statistic, p_value
+    """
+    contingency = pd.crosstab(df[feature], df[kpi])
+    chi2, p, dof, expected = stats.chi2_contingency(contingency)
+    return chi2, p
+
+
+def t_test_numeric(df: pd.DataFrame, feature: str, kpi: str) -> Tuple[float, float]:
+    """
+    Two-sample t-test for numeric KPI across two groups defined by a binary/categorical feature.
+    If feature has more than 2 levels, caller should subset the groups.
+    
+    Returns:
+        t_statistic, p_value
+    """
+    levels = df[feature].dropna().unique()
+    if len(levels) != 2:
+        raise ValueError(
+            f"T-test requires exactly 2 groups; found {len(levels)} in feature '{feature}'")
+
+    g1 = df[df[feature] == levels[0]][kpi].dropna()
+    g2 = df[df[feature] == levels[1]][kpi].dropna()
+
+    t_stat, p_value = stats.ttest_ind(g1, g2, equal_var=False)
+    return t_stat, p_value
+
+
+def anova_numeric(df: pd.DataFrame, feature: str, kpi: str) -> Tuple[float, float]:
+    """
+    One-way ANOVA for numeric KPI across multiple levels of a categorical feature.
+    
+    Returns:
+        F_statistic, p_value
+    """
+    groups = [g[kpi].dropna() for name, g in df.groupby(feature)]
+    F_stat, p_value = stats.f_oneway(*groups)
+    return F_stat, p_value
+
+
+def run_hypothesis_tests(df: pd.DataFrame, hypotheses: Optional[List[dict]] = None) -> pd.DataFrame:
+    """
+    Run predefined hypotheses tests.
+    
+    hypotheses: list of dicts, each with:
+        - "feature": column to test (e.g., 'Province')
+        - "kpi": which KPI to test ('ClaimFrequency', 'ClaimSeverity', 'Margin')
+        - "test_type": 'chi2', 't', or 'anova'
+        - "description": optional string description
+    
+    Returns:
+        pandas DataFrame with columns:
+        - feature, kpi, test_type, statistic, p_value, reject_null (bool), description
+    """
+    if hypotheses is None:
+        # Default based on your business problem
+        hypotheses = [
+            {"feature": "Province", "kpi": "ClaimFrequency", "test_type": "chi2",
+                "description": "Risk differences across provinces"},
+            {"feature": "PostalCode", "kpi": "ClaimFrequency", "test_type": "chi2",
+                "description": "Risk differences across zipcodes"},
+            {"feature": "PostalCode", "kpi": "Margin", "test_type": "anova",
+                "description": "Margin differences across zipcodes"},
+            {"feature": "Gender", "kpi": "ClaimFrequency",
+                "test_type": "chi2", "description": "Risk differences by gender"}
+        ]
+
+    results = []
+    for h in hypotheses:
+        try:
+            if h["test_type"] == "chi2":
+                stat, p = chi2_test_categorical(df, h["feature"], h["kpi"])
+            elif h["test_type"] == "t":
+                stat, p = t_test_numeric(df, h["feature"], h["kpi"])
+            elif h["test_type"] == "anova":
+                stat, p = anova_numeric(df, h["feature"], h["kpi"])
+            else:
+                raise ValueError(f"Unknown test_type '{h['test_type']}'")
+
+            reject_null = p < 0.05
+            results.append({
+                "feature": h["feature"],
+                "kpi": h["kpi"],
+                "test_type": h["test_type"],
+                "statistic": stat,
+                "p_value": p,
+                "reject_null": reject_null,
+                "description": h.get("description", "")
+            })
+        except Exception as e:
+            results.append({
+                "feature": h.get("feature"),
+                "kpi": h.get("kpi"),
+                "test_type": h.get("test_type"),
+                "statistic": np.nan,
+                "p_value": np.nan,
+                "reject_null": False,
+                "description": str(e)
+            })
+    return pd.DataFrame(results)
+
diff --git a/src/insurance_analytics/utils/io_utils.py b/src/insurance_analytics/utils/io_utils.py
index 0b30925..da9c848 100644
--- a/src/insurance_analytics/utils/io_utils.py
+++ b/src/insurance_analytics/utils/io_utils.py
@@ -37,6 +37,7 @@ def write_csv(df, path):
     try:
         os.makedirs(os.path.dirname(path), exist_ok=True)
         df.to_csv(path, index=False)
+        print(f"[IO] CSV file is saved sucessfully")
     except Exception as e:
         print(f"[IO] Failed to write CSV: {e}")
 
diff --git a/src/insurance_analytics/viz/ab_plots.py b/src/insurance_analytics/viz/ab_plots.py
new file mode 100644
index 0000000..0d95f0f
--- /dev/null
+++ b/src/insurance_analytics/viz/ab_plots.py
@@ -0,0 +1,123 @@
+# insurance_analytics/visualization/plots.py
+
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+sns.set(style="whitegrid")
+
+
+# ---------------------------------------------------------
+# 1. Claim Frequency by Feature
+# ---------------------------------------------------------
+def plot_claim_frequency_by_feature(df: pd.DataFrame, feature: str, top_n: int = None):
+    """
+    Bar plot of Claim Frequency across categories.
+    ClaimFrequency must already exist (0/1 indicator).
+    """
+
+    data = df.copy()
+
+    # Limit to top N categories (for large PostalCode sets)
+    if top_n:
+        top_vals = data[feature].value_counts().nlargest(top_n).index
+        data = data[data[feature].isin(top_vals)]
+
+    freq = data.groupby(feature)["ClaimFrequency"].mean().reset_index()
+    freq.rename(columns={"ClaimFrequency": "Frequency"}, inplace=True)
+
+    plt.figure(figsize=(10, 6))
+    sns.barplot(data=freq, x=feature, y="Frequency")
+    plt.xticks(rotation=45, ha="right")
+    plt.title(f"Claim Frequency by {feature}")
+    plt.ylabel("Claim Frequency")
+    plt.tight_layout()
+    plt.show()
+
+
+# ---------------------------------------------------------
+# 2. Claim Severity Boxplot
+# ---------------------------------------------------------
+def plot_claim_severity_box_by_feature(df: pd.DataFrame, feature: str, top_n: int = None, log_scale: bool = False):
+    """
+    Boxplot of Claim Severity (only where TotalClaims > 0).
+    """
+
+    data = df[df["TotalClaims"] > 0].copy()
+
+    if data.empty:
+        print(f"No severity data available for feature '{feature}'.")
+        return
+
+    if top_n:
+        top_vals = data[feature].value_counts().nlargest(top_n).index
+        data = data[data[feature].isin(top_vals)]
+
+    plt.figure(figsize=(10, 6))
+    sns.boxplot(data=data, x=feature, y="ClaimSeverity")
+    plt.xticks(rotation=45, ha="right")
+
+    if log_scale:
+        plt.yscale("log")
+        plt.ylabel("Claim Severity (log scale)")
+    else:
+        plt.ylabel("Claim Severity")
+
+    plt.title(f"Claim Severity by {feature}")
+    plt.tight_layout()
+    plt.show()
+
+
+# ---------------------------------------------------------
+# 3. Margin Boxplot
+# ---------------------------------------------------------
+def plot_margin_box_by_feature(df: pd.DataFrame, feature: str, top_n: int = None):
+    """
+    Boxplot of profit margin (TotalPremium - TotalClaims).
+    """
+
+    data = df.copy()
+    data["Margin"] = data["TotalPremium"] - data["TotalClaims"]
+
+    if top_n:
+        top_vals = data[feature].value_counts().nlargest(top_n).index
+        data = data[data[feature].isin(top_vals)]
+
+    plt.figure(figsize=(10, 6))
+    sns.boxplot(data=data, x=feature, y="Margin")
+    plt.xticks(rotation=45, ha="right")
+    plt.title(f"Margin by {feature}")
+    plt.ylabel("Margin")
+    plt.tight_layout()
+    plt.show()
+
+
+# ---------------------------------------------------------
+# 4. Top Zip Codes by Claim Frequency
+# ---------------------------------------------------------
+def plot_top_zipcode_frequency(df: pd.DataFrame, top_n: int = 20):
+    """
+    Shows the top N postal codes ranked by claim frequency.
+    Useful when PostalCode has many categories.
+    """
+
+    if "PostalCode" not in df.columns:
+        print("PostalCode column not found.")
+        return
+
+    freq = (
+        df.groupby("PostalCode")["ClaimFrequency"]
+        .mean()
+        .sort_values(ascending=False)
+        .head(top_n)
+        .reset_index()
+    )
+
+    plt.figure(figsize=(10, 6))
+    sns.barplot(data=freq, x="PostalCode", y="ClaimFrequency")
+    plt.xticks(rotation=45, ha="right")
+    plt.title(f"Top {top_n} Zip Codes by Claim Frequency")
+    plt.ylabel("Claim Frequency")
+    plt.tight_layout()
+    plt.show()