From fc7f487d14fca66745e5d20cca86965e9ac12c1c Mon Sep 17 00:00:00 2001
From: dadams <david@dadams.io>
Date: Mon, 25 Nov 2024 08:09:41 -0800
Subject: [PATCH] ok - have to start with secondtake now

---
 .../overview_hypotesting_20241031.ipynb       | 670 +++++++++++-------
 initial_view/secondtake.ipynb                 | 659 +++++++++++++++--
 2 files changed, 1022 insertions(+), 307 deletions(-)

diff --git a/initial_view/overview_hypotesting_20241031.ipynb b/initial_view/overview_hypotesting_20241031.ipynb
index 5926c324..3296ea98 100644
--- a/initial_view/overview_hypotesting_20241031.ipynb
+++ b/initial_view/overview_hypotesting_20241031.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -28,7 +28,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -49,7 +49,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -62,7 +62,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -76,7 +76,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -425,7 +425,7 @@
        "[8 rows x 82 columns]"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -437,7 +437,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -489,7 +489,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -707,24 +707,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/tmp/ipykernel_846869/3534785368.py:18: FutureWarning: \n",
+      "/tmp/ipykernel_1046044/3534785368.py:18: FutureWarning: \n",
       "\n",
       "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
       "\n",
       "  sns.barplot(data=plot_data,\n",
-      "/tmp/ipykernel_846869/3534785368.py:28: FutureWarning: \n",
+      "/tmp/ipykernel_1046044/3534785368.py:28: FutureWarning: \n",
       "\n",
       "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
       "\n",
       "  sns.barplot(data=plot_data[mask],\n",
-      "/tmp/ipykernel_846869/3534785368.py:38: FutureWarning: \n",
+      "/tmp/ipykernel_1046044/3534785368.py:38: FutureWarning: \n",
       "\n",
       "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
       "\n",
@@ -824,7 +824,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
@@ -1006,7 +1006,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
@@ -1032,7 +1032,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/tmp/ipykernel_846869/2919179271.py:33: FutureWarning: \n",
+      "/tmp/ipykernel_1046044/2919179271.py:33: FutureWarning: \n",
       "\n",
       "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
       "\n",
@@ -1096,7 +1096,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
@@ -1300,7 +1300,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
@@ -1473,7 +1473,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/tmp/ipykernel_846869/3616794259.py:63: UserWarning: Tight layout not applied. The bottom and top margins cannot be made large enough to accommodate all Axes decorations.\n",
+      "/tmp/ipykernel_1046044/3616794259.py:63: UserWarning: Tight layout not applied. The bottom and top margins cannot be made large enough to accommodate all Axes decorations.\n",
       "  plt.tight_layout()\n"
      ]
     },
@@ -1558,7 +1558,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -1851,7 +1851,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
@@ -2168,197 +2168,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "Total Investment by Program (Top 10):\n",
-      "                                                     count           sum  \\\n",
-      "Program Name                                                               \n",
-      "Transit and Intercity Rail Capital Program             245  101461750666   \n",
-      "Low Carbon Transit Operations Program                 1003    8777590799   \n",
-      "Affordable Housing and Sustainable Communities ...     151    8492944393   \n",
-      "Low Carbon Transportation                           105965    3759508172   \n",
-      "Community Air Protection                              5514    1211608583   \n",
-      "Climate Smart Agriculture                             1688     886514974   \n",
-      "Forest Health Program                                  258     837651776   \n",
-      "Funding Agricultural Replacement Measures for E...    8554     771297976   \n",
-      "Waste Diversion                                        265     643549843   \n",
-      "Fire Prevention Program                                600     614281793   \n",
-      "\n",
-      "                                                            mean  \n",
-      "Program Name                                                      \n",
-      "Transit and Intercity Rail Capital Program          4.141296e+08  \n",
-      "Low Carbon Transit Operations Program               8.751337e+06  \n",
-      "Affordable Housing and Sustainable Communities ...  5.624466e+07  \n",
-      "Low Carbon Transportation                           3.547877e+04  \n",
-      "Community Air Protection                            2.197331e+05  \n",
-      "Climate Smart Agriculture                           5.251866e+05  \n",
-      "Forest Health Program                               3.246712e+06  \n",
-      "Funding Agricultural Replacement Measures for E...  9.016811e+04  \n",
-      "Waste Diversion                                     2.428490e+06  \n",
-      "Fire Prevention Program                             1.023803e+06  \n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/dadams/Repos/california_equity_git/.venv/lib/python3.12/site-packages/matplotlib/text.py:1465: FutureWarning: Calling float on a single element Series is deprecated and will raise a TypeError in the future. Use float(ser.iloc[0]) instead\n",
-      "  x = float(self.convert_xunits(x))\n",
-      "/home/dadams/Repos/california_equity_git/.venv/lib/python3.12/site-packages/matplotlib/text.py:1467: FutureWarning: Calling float on a single element Series is deprecated and will raise a TypeError in the future. Use float(ser.iloc[0]) instead\n",
-      "  y = float(self.convert_yunits(y))\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "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",
-      "text/plain": [
-       "<Figure size 1500x1000 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "Program Performance Analysis:\n",
-      "\n",
-      "1. Top 5 Programs by DAC Funding Ratio:\n"
-     ]
-    },
-    {
-     "ename": "KeyError",
-     "evalue": "\"[('Total Project Cost', 'sum')] not in index\"",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[27], line 62\u001b[0m\n\u001b[1;32m     60\u001b[0m \u001b[38;5;66;03m# Top programs by equity\u001b[39;00m\n\u001b[1;32m     61\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m1. Top 5 Programs by DAC Funding Ratio:\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 62\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43mclean_data\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnlargest\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mDAC_funding_ratio\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\n\u001b[1;32m     63\u001b[0m \u001b[43m    \u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mDAC_funding_ratio\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mGHG_per_dollar\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mTotal Project Cost\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43msum\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m     64\u001b[0m \u001b[43m]\u001b[49m)\n\u001b[1;32m     66\u001b[0m \u001b[38;5;66;03m# Top programs by GHG efficiency\u001b[39;00m\n\u001b[1;32m     67\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m2. Top 5 Programs by GHG Reduction Efficiency:\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
-      "File \u001b[0;32m~/Repos/california_equity_git/.venv/lib/python3.12/site-packages/pandas/core/frame.py:4108\u001b[0m, in \u001b[0;36mDataFrame.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   4106\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m is_iterator(key):\n\u001b[1;32m   4107\u001b[0m         key \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(key)\n\u001b[0;32m-> 4108\u001b[0m     indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_indexer_strict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcolumns\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m[\u001b[38;5;241m1\u001b[39m]\n\u001b[1;32m   4110\u001b[0m \u001b[38;5;66;03m# take() does not accept boolean indexers\u001b[39;00m\n\u001b[1;32m   4111\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mgetattr\u001b[39m(indexer, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdtype\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m) \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mbool\u001b[39m:\n",
-      "File \u001b[0;32m~/Repos/california_equity_git/.venv/lib/python3.12/site-packages/pandas/core/indexes/multi.py:2763\u001b[0m, in \u001b[0;36mMultiIndex._get_indexer_strict\u001b[0;34m(self, key, axis_name)\u001b[0m\n\u001b[1;32m   2760\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(keyarr) \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(keyarr[\u001b[38;5;241m0\u001b[39m], \u001b[38;5;28mtuple\u001b[39m):\n\u001b[1;32m   2761\u001b[0m     indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_indexer_level_0(keyarr)\n\u001b[0;32m-> 2763\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_raise_if_missing\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindexer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis_name\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   2764\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m[indexer], indexer\n\u001b[1;32m   2766\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39m_get_indexer_strict(key, axis_name)\n",
-      "File \u001b[0;32m~/Repos/california_equity_git/.venv/lib/python3.12/site-packages/pandas/core/indexes/multi.py:2781\u001b[0m, in \u001b[0;36mMultiIndex._raise_if_missing\u001b[0;34m(self, key, indexer, axis_name)\u001b[0m\n\u001b[1;32m   2779\u001b[0m cmask \u001b[38;5;241m=\u001b[39m check \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[1;32m   2780\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cmask\u001b[38;5;241m.\u001b[39many():\n\u001b[0;32m-> 2781\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mkeyarr[cmask]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m not in index\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m   2782\u001b[0m \u001b[38;5;66;03m# We get here when levels still contain values which are not\u001b[39;00m\n\u001b[1;32m   2783\u001b[0m \u001b[38;5;66;03m# actually in Index anymore\u001b[39;00m\n\u001b[1;32m   2784\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mkeyarr\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m not in index\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
-      "\u001b[0;31mKeyError\u001b[0m: \"[('Total Project Cost', 'sum')] not in index\""
-     ]
-    }
-   ],
-   "source": [
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "import seaborn as sns\n",
-    "\n",
-    "# Let's first get a clear view of our data\n",
-    "print(\"\\nTotal Investment by Program (Top 10):\")\n",
-    "investment_by_program = data.groupby('Program Name')['Total Project Cost'].agg(['count', 'sum', 'mean'])\n",
-    "print(investment_by_program.nlargest(10, 'sum'))\n",
-    "\n",
-    "# Calculate our key metrics\n",
-    "program_metrics = data.groupby('Program Name').agg({\n",
-    "    'Total Project Cost': ['count', 'sum', 'mean'],\n",
-    "    'Total Project GHGReductions': ['sum', 'mean'],\n",
-    "    'Total GGRFDisadvantaged Community Funding': ['sum', 'mean'],\n",
-    "    'Is Benefit Disadvantaged Communities': 'mean'\n",
-    "}).round(2)\n",
-    "\n",
-    "# Add efficiency metrics\n",
-    "program_metrics['GHG_per_dollar'] = (program_metrics[('Total Project GHGReductions', 'sum')] / \n",
-    "                                   program_metrics[('Total Project Cost', 'sum')]).round(4)\n",
-    "\n",
-    "program_metrics['DAC_funding_ratio'] = (program_metrics[('Total GGRFDisadvantaged Community Funding', 'sum')] / \n",
-    "                                      program_metrics[('Total Project Cost', 'sum')]).round(4)\n",
-    "\n",
-    "# Clean data for visualization\n",
-    "clean_data = program_metrics[\n",
-    "    (program_metrics['GHG_per_dollar'] != float('inf')) & \n",
-    "    (program_metrics['DAC_funding_ratio'].notna())\n",
-    "]\n",
-    "\n",
-    "# Create visualization\n",
-    "plt.figure(figsize=(15, 10))\n",
-    "\n",
-    "# Basic scatter plot\n",
-    "scatter = plt.scatter(clean_data['DAC_funding_ratio'],\n",
-    "                     clean_data['GHG_per_dollar'],\n",
-    "                     s=clean_data[('Total Project Cost', 'sum')]/1e7,\n",
-    "                     alpha=0.6)\n",
-    "\n",
-    "# Add labels for major programs\n",
-    "for idx, row in clean_data.iterrows():\n",
-    "    if row[('Total Project Cost', 'sum')] > 500000000:  # Only label major programs\n",
-    "        plt.annotate(idx[:30] + '...' if len(idx) > 30 else idx,\n",
-    "                    (row['DAC_funding_ratio'], row['GHG_per_dollar']),\n",
-    "                    xytext=(5, 5),\n",
-    "                    textcoords='offset points',\n",
-    "                    fontsize=8)\n",
-    "\n",
-    "plt.xlabel('DAC Funding Ratio')\n",
-    "plt.ylabel('GHG Reduction per Dollar')\n",
-    "plt.title('Program Performance: Equity vs. Climate Impact\\nSize = Total Investment')\n",
-    "\n",
-    "plt.tight_layout()\n",
-    "plt.show()\n",
-    "\n",
-    "# Analysis of key metrics\n",
-    "print(\"\\nProgram Performance Analysis:\")\n",
-    "\n",
-    "# Top programs by equity\n",
-    "print(\"\\n1. Top 5 Programs by DAC Funding Ratio:\")\n",
-    "print(clean_data.nlargest(5, 'DAC_funding_ratio')[\n",
-    "    ['DAC_funding_ratio', 'GHG_per_dollar', ('Total Project Cost', 'sum')]\n",
-    "])\n",
-    "\n",
-    "# Top programs by GHG efficiency\n",
-    "print(\"\\n2. Top 5 Programs by GHG Reduction Efficiency:\")\n",
-    "print(clean_data.nlargest(5, 'GHG_per_dollar')[\n",
-    "    ['DAC_funding_ratio', 'GHG_per_dollar', ('Total Project Cost', 'sum')]\n",
-    "])\n",
-    "\n",
-    "# Investment distribution\n",
-    "print(\"\\n3. Investment Distribution Summary:\")\n",
-    "print(clean_data[('Total Project Cost', 'sum')].describe())"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Collecting scikit-learn\n",
-      "  Using cached scikit_learn-1.5.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (13 kB)\n",
-      "Requirement already satisfied: numpy>=1.19.5 in ./.venv/lib/python3.12/site-packages (from scikit-learn) (2.1.2)\n",
-      "Requirement already satisfied: scipy>=1.6.0 in ./.venv/lib/python3.12/site-packages (from scikit-learn) (1.14.1)\n",
-      "Collecting joblib>=1.2.0 (from scikit-learn)\n",
-      "  Using cached joblib-1.4.2-py3-none-any.whl.metadata (5.4 kB)\n",
-      "Collecting threadpoolctl>=3.1.0 (from scikit-learn)\n",
-      "  Using cached threadpoolctl-3.5.0-py3-none-any.whl.metadata (13 kB)\n",
-      "Using cached scikit_learn-1.5.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.9 MB)\n",
-      "Using cached joblib-1.4.2-py3-none-any.whl (301 kB)\n",
-      "Using cached threadpoolctl-3.5.0-py3-none-any.whl (18 kB)\n",
-      "Installing collected packages: threadpoolctl, joblib, scikit-learn\n",
-      "Successfully installed joblib-1.4.2 scikit-learn-1.5.2 threadpoolctl-3.5.0\n"
-     ]
-    }
-   ],
-   "source": [
-    "# install sklearn library\n",
-    "!pip install scikit-learn\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -2528,7 +2338,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
@@ -2596,64 +2406,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Requirement already satisfied: seaborn in ./.venv/lib/python3.12/site-packages (0.13.2)\n",
-      "Requirement already satisfied: numpy!=1.24.0,>=1.20 in ./.venv/lib/python3.12/site-packages (from seaborn) (2.1.2)\n",
-      "Requirement already satisfied: pandas>=1.2 in ./.venv/lib/python3.12/site-packages (from seaborn) (2.2.3)\n",
-      "Requirement already satisfied: matplotlib!=3.6.1,>=3.4 in ./.venv/lib/python3.12/site-packages (from seaborn) (3.9.2)\n",
-      "Requirement already satisfied: contourpy>=1.0.1 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (1.3.0)\n",
-      "Requirement already satisfied: cycler>=0.10 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (0.12.1)\n",
-      "Requirement already satisfied: fonttools>=4.22.0 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (4.54.1)\n",
-      "Requirement already satisfied: kiwisolver>=1.3.1 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (1.4.7)\n",
-      "Requirement already satisfied: packaging>=20.0 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (24.1)\n",
-      "Requirement already satisfied: pillow>=8 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (11.0.0)\n",
-      "Requirement already satisfied: pyparsing>=2.3.1 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (3.2.0)\n",
-      "Requirement already satisfied: python-dateutil>=2.7 in ./.venv/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (2.9.0.post0)\n",
-      "Requirement already satisfied: pytz>=2020.1 in ./.venv/lib/python3.12/site-packages (from pandas>=1.2->seaborn) (2024.2)\n",
-      "Requirement already satisfied: tzdata>=2022.7 in ./.venv/lib/python3.12/site-packages (from pandas>=1.2->seaborn) (2024.2)\n",
-      "Requirement already satisfied: six>=1.5 in ./.venv/lib/python3.12/site-packages (from python-dateutil>=2.7->matplotlib!=3.6.1,>=3.4->seaborn) (1.16.0)\n"
+     "ename": "KeyError",
+     "evalue": "'total_investment'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "File \u001b[0;32m~/Repos/california_equity_git/.venv/lib/python3.12/site-packages/pandas/core/indexes/base.py:3805\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3804\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3805\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3806\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n",
+      "File \u001b[0;32mindex.pyx:167\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
+      "File \u001b[0;32mindex.pyx:196\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
+      "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7081\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
+      "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7089\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
+      "\u001b[0;31mKeyError\u001b[0m: 'total_investment'",
+      "\nThe above exception was the direct cause of the following exception:\n",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[37], line 72\u001b[0m\n\u001b[1;32m     70\u001b[0m \u001b[38;5;66;03m# 4. Geographic Distribution (Enhanced)\u001b[39;00m\n\u001b[1;32m     71\u001b[0m ax4 \u001b[38;5;241m=\u001b[39m plt\u001b[38;5;241m.\u001b[39msubplot(\u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m2\u001b[39m, \u001b[38;5;241m4\u001b[39m)\n\u001b[0;32m---> 72\u001b[0m top_15_counties \u001b[38;5;241m=\u001b[39m \u001b[43mcounty_analysis\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtotal_investment\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241m.\u001b[39mnlargest(\u001b[38;5;241m15\u001b[39m)\u001b[38;5;241m/\u001b[39m\u001b[38;5;241m1e6\u001b[39m\n\u001b[1;32m     73\u001b[0m colors \u001b[38;5;241m=\u001b[39m plt\u001b[38;5;241m.\u001b[39mcm\u001b[38;5;241m.\u001b[39mviridis(np\u001b[38;5;241m.\u001b[39mlinspace(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m0.8\u001b[39m, \u001b[38;5;28mlen\u001b[39m(top_15_counties)))\n\u001b[1;32m     74\u001b[0m bars \u001b[38;5;241m=\u001b[39m ax4\u001b[38;5;241m.\u001b[39mbarh(\u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(top_15_counties)), top_15_counties, color\u001b[38;5;241m=\u001b[39mcolors)\n",
+      "File \u001b[0;32m~/Repos/california_equity_git/.venv/lib/python3.12/site-packages/pandas/core/frame.py:4101\u001b[0m, in \u001b[0;36mDataFrame.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   4099\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_single_key:\n\u001b[1;32m   4100\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcolumns\u001b[38;5;241m.\u001b[39mnlevels \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[0;32m-> 4101\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_getitem_multilevel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   4102\u001b[0m     indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcolumns\u001b[38;5;241m.\u001b[39mget_loc(key)\n\u001b[1;32m   4103\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m is_integer(indexer):\n",
+      "File \u001b[0;32m~/Repos/california_equity_git/.venv/lib/python3.12/site-packages/pandas/core/frame.py:4159\u001b[0m, in \u001b[0;36mDataFrame._getitem_multilevel\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   4157\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_getitem_multilevel\u001b[39m(\u001b[38;5;28mself\u001b[39m, key):\n\u001b[1;32m   4158\u001b[0m     \u001b[38;5;66;03m# self.columns is a MultiIndex\u001b[39;00m\n\u001b[0;32m-> 4159\u001b[0m     loc \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   4160\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(loc, (\u001b[38;5;28mslice\u001b[39m, np\u001b[38;5;241m.\u001b[39mndarray)):\n\u001b[1;32m   4161\u001b[0m         new_columns \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcolumns[loc]\n",
+      "File \u001b[0;32m~/Repos/california_equity_git/.venv/lib/python3.12/site-packages/pandas/core/indexes/multi.py:3040\u001b[0m, in \u001b[0;36mMultiIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3037\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m mask\n\u001b[1;32m   3039\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(key, \u001b[38;5;28mtuple\u001b[39m):\n\u001b[0;32m-> 3040\u001b[0m     loc \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_level_indexer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3041\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m _maybe_to_slice(loc)\n\u001b[1;32m   3043\u001b[0m keylen \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlen\u001b[39m(key)\n",
+      "File \u001b[0;32m~/Repos/california_equity_git/.venv/lib/python3.12/site-packages/pandas/core/indexes/multi.py:3391\u001b[0m, in \u001b[0;36mMultiIndex._get_level_indexer\u001b[0;34m(self, key, level, indexer)\u001b[0m\n\u001b[1;32m   3388\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mslice\u001b[39m(i, j, step)\n\u001b[1;32m   3390\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 3391\u001b[0m     idx \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_loc_single_level_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlevel_index\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3393\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m level \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lexsort_depth \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m   3394\u001b[0m         \u001b[38;5;66;03m# Desired level is not sorted\u001b[39;00m\n\u001b[1;32m   3395\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(idx, \u001b[38;5;28mslice\u001b[39m):\n\u001b[1;32m   3396\u001b[0m             \u001b[38;5;66;03m# test_get_loc_partial_timestamp_multiindex\u001b[39;00m\n",
+      "File \u001b[0;32m~/Repos/california_equity_git/.venv/lib/python3.12/site-packages/pandas/core/indexes/multi.py:2980\u001b[0m, in \u001b[0;36mMultiIndex._get_loc_single_level_index\u001b[0;34m(self, level_index, key)\u001b[0m\n\u001b[1;32m   2978\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[1;32m   2979\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 2980\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mlevel_index\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/Repos/california_equity_git/.venv/lib/python3.12/site-packages/pandas/core/indexes/base.py:3812\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3807\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(casted_key, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[1;32m   3808\u001b[0m         \u001b[38;5;28misinstance\u001b[39m(casted_key, abc\u001b[38;5;241m.\u001b[39mIterable)\n\u001b[1;32m   3809\u001b[0m         \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m casted_key)\n\u001b[1;32m   3810\u001b[0m     ):\n\u001b[1;32m   3811\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n\u001b[0;32m-> 3812\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m   3813\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m   3814\u001b[0m     \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[1;32m   3815\u001b[0m     \u001b[38;5;66;03m#  InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[1;32m   3816\u001b[0m     \u001b[38;5;66;03m#  the TypeError.\u001b[39;00m\n\u001b[1;32m   3817\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n",
+      "\u001b[0;31mKeyError\u001b[0m: 'total_investment'"
      ]
-    }
-   ],
-   "source": [
-    "# install seaborn library\n",
-    "!pip install seaborn\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [
+    },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 2000x1500 with 4 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "Program Scale Categories:\n",
-      "\n",
-      "Investment Scale Categories (in Millions $):\n",
-      "Small Programs: < $20.0M\n",
-      "Medium Programs: $20.0M - $97.0M\n",
-      "Large Programs: $97.0M - $587.9M\n",
-      "Mega Programs: > $587.9M\n"
-     ]
     }
    ],
    "source": [
@@ -2760,7 +2549,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
@@ -2920,7 +2709,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
@@ -3184,7 +2973,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
@@ -3428,14 +3217,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/tmp/ipykernel_846869/2239187850.py:43: SettingWithCopyWarning: \n",
+      "/tmp/ipykernel_1046044/2239187850.py:43: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
@@ -3597,6 +3386,357 @@
     "    ['County', 'Program Name', 'Total Project Cost', 'Total Project GHGReductions']\n",
     "].round(2))"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total funding in dataset:\n",
+      "130.205367663 billion\n",
+      "\n",
+      "Top 5 largest projects:\n",
+      "                                      Program Name       County  \\\n",
+      "100692  Transit and Intercity Rail Capital Program  Los Angeles   \n",
+      "117879  Transit and Intercity Rail Capital Program      Alameda   \n",
+      "127522  Transit and Intercity Rail Capital Program      Alameda   \n",
+      "62286   Transit and Intercity Rail Capital Program  Los Angeles   \n",
+      "62287   Transit and Intercity Rail Capital Program  Los Angeles   \n",
+      "\n",
+      "        Total Project Cost Date Operational  \n",
+      "100692          5767700000       2025-06-01  \n",
+      "117879          3536400000       2024-03-01  \n",
+      "127522          3409000000       2031-10-11  \n",
+      "62286           2049700000       2025-03-31  \n",
+      "62287           2049700000       2025-03-31  \n",
+      "\n",
+      "Multi-county projects total: $18.31B\n",
+      "\n",
+      "Program totals:\n",
+      "Program Name\n",
+      "Transit and Intercity Rail Capital Program                101.46\n",
+      "Low Carbon Transit Operations Program                       8.78\n",
+      "Affordable Housing and Sustainable Communities Program      8.49\n",
+      "Low Carbon Transportation                                   3.76\n",
+      "Community Air Protection                                    1.21\n",
+      "Name: Total Project Cost, dtype: float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Basic data validation\n",
+    "print(\"Total funding in dataset:\")\n",
+    "print(data['Total Project Cost'].sum()/1e9, \"billion\")\n",
+    "\n",
+    "# Check for potential duplicates or data issues\n",
+    "print(\"\\nTop 5 largest projects:\")\n",
+    "print(data.nlargest(5, 'Total Project Cost')[\n",
+    "    ['Program Name', 'County', 'Total Project Cost', 'Date Operational']\n",
+    "].round(2))\n",
+    "\n",
+    "# Verify multi-county totals\n",
+    "multi_county_total = multi_county_data['Total Project Cost'].sum()/1e9\n",
+    "print(f\"\\nMulti-county projects total: ${multi_county_total:.2f}B\")\n",
+    "\n",
+    "# Look for potential data anomalies\n",
+    "print(\"\\nProgram totals:\")\n",
+    "program_totals = data.groupby('Program Name')['Total Project Cost'].sum().sort_values(ascending=False)/1e9\n",
+    "print(program_totals.head().round(2))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Original row count: 141429\n",
+      "After removing duplicates: 102799\n",
+      "\n",
+      "Cleaned funding totals:\n",
+      "Total funding: $ 34.153615975 billion\n",
+      "\n",
+      "Program totals after cleaning:\n",
+      "Program Name\n",
+      "Transit and Intercity Rail Capital Program                13.01\n",
+      "Low Carbon Transit Operations Program                      7.93\n",
+      "Affordable Housing and Sustainable Communities Program     4.89\n",
+      "Low Carbon Transportation                                  2.47\n",
+      "Climate Smart Agriculture                                  0.82\n",
+      "Name: Total Project Cost, dtype: float64\n",
+      "\n",
+      "Cleaned multi-county total: $7.16B\n",
+      "\n",
+      "Top 5 largest projects after cleaning:\n",
+      "                                      Program Name  \\\n",
+      "117879  Transit and Intercity Rail Capital Program   \n",
+      "42458   Transit and Intercity Rail Capital Program   \n",
+      "60309        Low Carbon Transit Operations Program   \n",
+      "90114        Low Carbon Transit Operations Program   \n",
+      "75208        Low Carbon Transit Operations Program   \n",
+      "\n",
+      "                                       County  Total Project Cost  \\\n",
+      "117879                                Alameda          3536400000   \n",
+      "42458              San Francisco, Santa Clara          1980252533   \n",
+      "60309                             Santa Clara          1980252531   \n",
+      "90114   San Francisco, San Mateo, Santa Clara          1980252531   \n",
+      "75208                           San Francisco          1578300000   \n",
+      "\n",
+      "       Date Operational  \n",
+      "117879       2024-03-01  \n",
+      "42458        2020-12-31  \n",
+      "60309        2022-08-22  \n",
+      "90114        2022-08-22  \n",
+      "75208        2008-11-01  \n"
+     ]
+    }
+   ],
+   "source": [
+    "# Data cleaning steps\n",
+    "# 1. Remove future dates\n",
+    "current_date = pd.to_datetime('2024-11-01')\n",
+    "data_clean = data[pd.to_datetime(data['Date Operational']) <= current_date].copy()\n",
+    "\n",
+    "# 2. Check for duplicates\n",
+    "print(\"Original row count:\", len(data))\n",
+    "duplicates = data_clean.duplicated(subset=['Program Name', 'County', 'Total Project Cost', 'Date Operational'], keep='first')\n",
+    "data_clean = data_clean[~duplicates]\n",
+    "print(\"After removing duplicates:\", len(data_clean))\n",
+    "\n",
+    "# Recalculate totals\n",
+    "print(\"\\nCleaned funding totals:\")\n",
+    "print(\"Total funding: $\", data_clean['Total Project Cost'].sum()/1e9, \"billion\")\n",
+    "\n",
+    "print(\"\\nProgram totals after cleaning:\")\n",
+    "program_totals = data_clean.groupby('Program Name')['Total Project Cost'].sum().sort_values(ascending=False)/1e9\n",
+    "print(program_totals.head().round(2))\n",
+    "\n",
+    "# Identify multi-county projects in cleaned data\n",
+    "multi_county_clean = data_clean[data_clean['County'].str.contains(',', na=False)]\n",
+    "print(f\"\\nCleaned multi-county total: ${multi_county_clean['Total Project Cost'].sum()/1e9:.2f}B\")\n",
+    "\n",
+    "# Show top projects after cleaning\n",
+    "print(\"\\nTop 5 largest projects after cleaning:\")\n",
+    "print(data_clean.nlargest(5, 'Total Project Cost')[\n",
+    "   ['Program Name', 'County', 'Total Project Cost', 'Date Operational']\n",
+    "].round(2))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Projects with same rounded cost:\n",
+      "                                             Program Name  \\\n",
+      "42458          Transit and Intercity Rail Capital Program   \n",
+      "60309               Low Carbon Transit Operations Program   \n",
+      "90114               Low Carbon Transit Operations Program   \n",
+      "62257          Transit and Intercity Rail Capital Program   \n",
+      "62258          Transit and Intercity Rail Capital Program   \n",
+      "42455          Transit and Intercity Rail Capital Program   \n",
+      "123885                          Low Carbon Transportation   \n",
+      "62267          Transit and Intercity Rail Capital Program   \n",
+      "127550  Affordable Housing and Sustainable Communities...   \n",
+      "123883                          Low Carbon Transportation   \n",
+      "\n",
+      "                                       County  Total Project Cost  \\\n",
+      "42458              San Francisco, Santa Clara          1980252533   \n",
+      "60309                             Santa Clara          1980252531   \n",
+      "90114   San Francisco, San Mateo, Santa Clara          1980252531   \n",
+      "62257                               San Diego           350322000   \n",
+      "62258                               San Diego           350322000   \n",
+      "42455                               San Diego           350322000   \n",
+      "123885      Alameda, Los Angeles, San Joaquin           102998742   \n",
+      "62267                             Los Angeles           102790000   \n",
+      "127550                          San Francisco            90791292   \n",
+      "123883    Los Angeles, Orange, San Bernardino            90694994   \n",
+      "\n",
+      "       Date Operational  \n",
+      "42458        2020-12-31  \n",
+      "60309        2022-08-22  \n",
+      "90114        2022-08-22  \n",
+      "62257        2018-02-01  \n",
+      "62258        2018-10-18  \n",
+      "42455        2020-03-31  \n",
+      "123885       2020-05-01  \n",
+      "62267        2019-06-30  \n",
+      "127550       2024-04-30  \n",
+      "123883       2020-12-01  \n",
+      "\n",
+      "Yearly funding totals (billions):\n",
+      "Date Operational\n",
+      "2011    0.000012\n",
+      "2012    0.002328\n",
+      "2013    0.049519\n",
+      "2014    0.074858\n",
+      "2015    0.074986\n",
+      "2016    0.132640\n",
+      "2017    0.771875\n",
+      "2018    1.886977\n",
+      "2019    2.555229\n",
+      "2020    6.432072\n",
+      "2021    2.510380\n",
+      "2022    6.643319\n",
+      "2023    3.967999\n",
+      "2024    6.875842\n",
+      "Name: Total Project Cost, dtype: float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Additional cleaning\n",
+    "# 1. Remove pre-2010 data\n",
+    "data_clean = data_clean[pd.to_datetime(data_clean['Date Operational']).dt.year >= 2010]\n",
+    "\n",
+    "# 2. Check for near-duplicates (same amount, different counties/dates)\n",
+    "def round_to_million(x):\n",
+    "    return round(x, -6)\n",
+    "\n",
+    "data_clean['Cost_Rounded'] = data_clean['Total Project Cost'].apply(round_to_million)\n",
+    "potential_dupes = data_clean.groupby('Cost_Rounded').filter(lambda x: len(x) > 1)\n",
+    "\n",
+    "print(\"Projects with same rounded cost:\")\n",
+    "print(potential_dupes[['Program Name', 'County', 'Total Project Cost', 'Date Operational']].sort_values('Total Project Cost', ascending=False).head(10))\n",
+    "\n",
+    "# Let's see the yearly totals\n",
+    "yearly_totals = data_clean.groupby(pd.to_datetime(data_clean['Date Operational']).dt.year)['Total Project Cost'].sum()/1e9\n",
+    "print(\"\\nYearly funding totals (billions):\")\n",
+    "print(yearly_totals)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total funding: $29.30B\n",
+      "\n",
+      "Program totals:\n",
+      "Program Name\n",
+      "Transit and Intercity Rail Capital Program                12.305412\n",
+      "Affordable Housing and Sustainable Communities Program     4.888931\n",
+      "Low Carbon Transit Operations Program                      3.978571\n",
+      "Low Carbon Transportation                                  2.442087\n",
+      "Climate Smart Agriculture                                  0.742955\n",
+      "Name: Total Project Cost, dtype: float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Basic cleaning steps\n",
+    "data_clean = data[\n",
+    "    (pd.to_datetime(data['Date Operational']) >= '2010-01-01') & \n",
+    "    (pd.to_datetime(data['Date Operational']) <= '2024-11-01')\n",
+    "].copy()\n",
+    "\n",
+    "# Remove exact duplicates\n",
+    "data_clean = data_clean.drop_duplicates(subset=[\n",
+    "    'Program Name', \n",
+    "    'County', \n",
+    "    'Total Project Cost', \n",
+    "    'Date Operational'\n",
+    "])\n",
+    "\n",
+    "# For transit projects over $100M, keep only one instance\n",
+    "large_transit = data_clean[\n",
+    "    (data_clean['Program Name'].str.contains('Transit', na=False)) & \n",
+    "    (data_clean['Total Project Cost'] > 100_000_000)\n",
+    "].drop_duplicates(subset=['Total Project Cost'], keep='first')\n",
+    "\n",
+    "other_projects = data_clean[\n",
+    "    ~((data_clean['Program Name'].str.contains('Transit', na=False)) & \n",
+    "      (data_clean['Total Project Cost'] > 100_000_000))\n",
+    "]\n",
+    "\n",
+    "data_clean = pd.concat([large_transit, other_projects])\n",
+    "\n",
+    "# Show results\n",
+    "print(f\"Total funding: ${data_clean['Total Project Cost'].sum()/1e9:.2f}B\")\n",
+    "print(\"\\nProgram totals:\")\n",
+    "print(data_clean.groupby('Program Name')['Total Project Cost'].sum().sort_values(ascending=False).head()/1e9)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total Project Costs vs CCI Funding:\n",
+      "Total Project Costs: $130.21B\n",
+      "Total GGRF Funding: $11.02B\n",
+      "\n",
+      "Sample projects with large cost vs funding differences:\n",
+      "                                     Program Name  Total Project Cost  \\\n",
+      "16004       Low Carbon Transit Operations Program           153300000   \n",
+      "27303       Low Carbon Transit Operations Program           177986175   \n",
+      "27602  Transit and Intercity Rail Capital Program           146660494   \n",
+      "27607  Transit and Intercity Rail Capital Program           128037000   \n",
+      "27611  Transit and Intercity Rail Capital Program           211600000   \n",
+      "\n",
+      "       Total Program GGRFFunding  Total GGRFDisadvantaged Community Funding  \\\n",
+      "16004                     935322                                   935322.0   \n",
+      "27303                    1948597                                  1948597.0   \n",
+      "27602                   38494000                                 38494000.0   \n",
+      "27607                    4000000                                  4000000.0   \n",
+      "27611                   41181000                                 41181000.0   \n",
+      "\n",
+      "      Date Operational                                 County  \n",
+      "16004              NaN  San Francisco, San Mateo, Santa Clara  \n",
+      "27303       1900-01-01                                Alameda  \n",
+      "27602       2036-10-01                            Los Angeles  \n",
+      "27607       2033-08-01                              San Diego  \n",
+      "27611       2036-03-01                          San Francisco  \n"
+     ]
+    }
+   ],
+   "source": [
+    "# Relevant columns for funding validation\n",
+    "key_columns = [\n",
+    "    'Program Name',\n",
+    "    'Total Project Cost',\n",
+    "    'Total Program GGRFFunding',  # Actual CCI funding amount\n",
+    "    'Total GGRFDisadvantaged Community Funding',\n",
+    "    'Date Operational',\n",
+    "    'County'\n",
+    "]\n",
+    "\n",
+    "# Compare total costs vs actual CCI funding\n",
+    "print(\"Total Project Costs vs CCI Funding:\")\n",
+    "print(f\"Total Project Costs: ${data['Total Project Cost'].sum()/1e9:.2f}B\")\n",
+    "print(f\"Total GGRF Funding: ${data['Total Program GGRFFunding'].sum()/1e9:.2f}B\")\n",
+    "\n",
+    "# Show sample of differences\n",
+    "print(\"\\nSample projects with large cost vs funding differences:\")\n",
+    "diff_data = data[abs(data['Total Project Cost'] - data['Total Program GGRFFunding']) > 1e8].head()\n",
+    "print(diff_data[key_columns])"
+   ]
   }
  ],
  "metadata": {
diff --git a/initial_view/secondtake.ipynb b/initial_view/secondtake.ipynb
index 61ea0c0a..2f3fbf06 100644
--- a/initial_view/secondtake.ipynb
+++ b/initial_view/secondtake.ipynb
@@ -18,16 +18,135 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Importing the necessary libraries\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## set directory\n",
+    "import os\n",
+    "os.chdir('/home/dadams/Repos/california_equity_git')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# read in the data\n",
+    "data = pd.read_csv('data_raw/cci_programs_data.csv', low_memory=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
    "outputs": [
     {
-     "ename": "ModuleNotFoundError",
-     "evalue": "No module named 'scipy'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[2], line 5\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpyplot\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mplt\u001b[39;00m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mseaborn\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01msns\u001b[39;00m\n\u001b[0;32m----> 5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mscipy\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m stats\n\u001b[1;32m      7\u001b[0m \u001b[38;5;66;03m# Read the data (I see you already have this loaded as 'data')\u001b[39;00m\n\u001b[1;32m      8\u001b[0m \n\u001b[1;32m      9\u001b[0m \u001b[38;5;66;03m# 1. First, let's create our core analytical metrics\u001b[39;00m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcalculate_program_metrics\u001b[39m(df):\n",
-      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'scipy'"
+     "data": {
+      "text/plain": [
+       "Index(['Project IDNumber', 'Reporting Cycle Name', 'Agency Name',\n",
+       "       'Program Name', 'Program Description', 'Sub Program Name',\n",
+       "       'Record Type', 'Project Name', 'Project Type', 'Project Description',\n",
+       "       ...\n",
+       "       'Net Density  DUA', 'Applicants  Assisted', 'Invasive Cover 12 Months',\n",
+       "       'Invasive Cover 36 Months', 'Project Acreage', 'IS IAE',\n",
+       "       'Intermediary Admin Expenses Calc', 'PRIMARY_FUNDING_RECIPIENT_TYPE',\n",
+       "       'TRIBAL AFFILIATION', 'PROJECT PARTNERS'],\n",
+       "      dtype='object', length=127)"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "          Tract    ZIP         County    ApproxLoc  TotPop19    CIscore  \\\n",
+      "0  6.083002e+09  93454  Santa Barbara  Santa Maria      4495  36.019653   \n",
+      "1  6.083002e+09  93455  Santa Barbara  Santa Maria     13173  37.030667   \n",
+      "2  6.083002e+09  93454  Santa Barbara  Santa Maria      2398  31.213140   \n",
+      "3  6.083002e+09  93455  Santa Barbara       Orcutt      4496   6.639331   \n",
+      "4  6.083002e+09  93455  Santa Barbara       Orcutt      4008  14.022852   \n",
+      "\n",
+      "    CIscoreP     Ozone     OzoneP     PM2_5  ...  Elderly65  Hispanic  \\\n",
+      "0  69.162885  0.034190  10.566273  7.567724  ...    12.5028   68.9210   \n",
+      "1  70.637922  0.035217  11.561917  7.624775  ...     5.3519   78.6229   \n",
+      "2  61.069087  0.034190  10.566273  7.548835  ...    12.8857   65.7214   \n",
+      "3   5.988401  0.036244  13.615432  7.660570  ...    14.4128   22.9537   \n",
+      "4  23.121533  0.036244  13.615432  7.663210  ...    18.8872   33.4082   \n",
+      "\n",
+      "     White  AfricanAm  NativeAm  OtherMult    Shape_Leng    Shape_Area  \\\n",
+      "0  20.8899     0.4004    0.2670     1.3126   6999.357689  2.847611e+06   \n",
+      "1  13.2240     2.5051    0.0000     0.9489  19100.578232  1.635292e+07   \n",
+      "2  30.6088     0.9591    0.0000     2.1685   4970.985897  1.352329e+06   \n",
+      "3  69.1948     0.9342    0.7117     2.5356   6558.956012  2.417717e+06   \n",
+      "4  59.7804     0.6986    1.4721     1.3723   6570.368730  2.608422e+06   \n",
+      "\n",
+      "     AAPI                                           geometry  \n",
+      "0  8.2091  POLYGON ((-39795.07 -341919.191, -38126.384 -3...  \n",
+      "1  4.6990  POLYGON ((-39795.07 -341919.191, -39803.632 -3...  \n",
+      "2  0.5421  POLYGON ((-38115.747 -341130.248, -38126.384 -...  \n",
+      "3  3.6699  POLYGON ((-37341.662 -348530.437, -37252.307 -...  \n",
+      "4  3.2685  POLYGON ((-39465.107 -348499.262, -38244.305 -...  \n",
+      "\n",
+      "[5 rows x 67 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "import geopandas as gpd\n",
+    "\n",
+    "# Load the shapefile\n",
+    "shapefile_path = '/home/dadams/Repos/california_equity_git/california_enviroscreen/calif_enviroscreen_shape/CES4 Final Shapefile.shp'\n",
+    "gdf = gpd.read_file(shapefile_path)\n",
+    "\n",
+    "# Print the head of the GeoDataFrame\n",
+    "print(gdf.head())import geopandas as gpd\n",
+    "\n",
+    "# Load the shapefile\n",
+    "shapefile_path = '/home/dadams/Repos/california_equity_git/california_enviroscreen/calif_enviroscreen_shape/CES4 Final Shapefile.shp'\n",
+    "gdf = gpd.read_file(shapefile_path)\n",
+    "\n",
+    "# Print the head of the GeoDataFrame\n",
+    "print(gdf.head())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Total GGRF Funding: $8.13B\n",
+      "Number of projects: 131428\n"
      ]
     }
    ],
@@ -35,49 +154,505 @@
     "import pandas as pd\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
-    "import seaborn as sns\n",
-    "from scipy import stats\n",
     "\n",
-    "# Read the data (I see you already have this loaded as 'data')\n",
+    "# Basic cleaning\n",
+    "data['Date Operational'] = pd.to_datetime(data['Date Operational'])\n",
+    "data = data[\n",
+    "    (data['Date Operational'] >= '2010-01-01') & \n",
+    "    (data['Date Operational'] <= '2024-11-01')\n",
+    "].copy()\n",
     "\n",
-    "# 1. First, let's create our core analytical metrics\n",
-    "def calculate_program_metrics(df):\n",
-    "    metrics = df.groupby('Program Name').agg({\n",
-    "        'Total Project Cost': ['count', 'sum', 'mean'],\n",
-    "        'Total Project GHGReductions': ['sum', 'mean'],\n",
-    "        'Total GGRFDisadvantaged Community Funding': ['sum', 'mean'],\n",
-    "        'Is Benefit Disadvantaged Communities': 'mean',\n",
-    "        'Is Low Income Communities': 'mean'\n",
-    "    }).round(2)\n",
-    "    \n",
-    "    # Add efficiency metrics\n",
-    "    metrics['GHG_per_dollar'] = (metrics[('Total Project GHGReductions', 'sum')] / \n",
-    "                                metrics[('Total Project Cost', 'sum')]).round(4)\n",
-    "    \n",
-    "    metrics['DAC_funding_ratio'] = (metrics[('Total GGRFDisadvantaged Community Funding', 'sum')] / \n",
-    "                                   metrics[('Total Project Cost', 'sum')]).round(4)\n",
-    "    \n",
-    "    return metrics\n",
+    "# Remove rows with no GGRF funding\n",
+    "data = data.dropna(subset=['Total Program GGRFFunding'])\n",
     "\n",
-    "program_metrics = calculate_program_metrics(data)\n",
+    "# Add derived columns\n",
+    "data['Year'] = data['Date Operational'].dt.year\n",
+    "data['is_multi_county'] = data['County'].str.contains(',', na=False)\n",
+    "data['partnership_size'] = data['County'].str.count(',').fillna(0) + 1\n",
     "\n",
-    "# Display top programs by different metrics\n",
-    "print(\"\\nTop 5 Programs by Total Investment:\")\n",
-    "print(program_metrics.sort_values(('Total Project Cost', 'sum'), ascending=False).head())\n",
-    "\n",
-    "print(\"\\nTop 5 Programs by GHG Reduction Efficiency:\")\n",
-    "print(program_metrics.sort_values('GHG_per_dollar', ascending=False).head())\n",
-    "\n",
-    "print(\"\\nTop 5 Programs by DAC Funding Ratio:\")\n",
-    "print(program_metrics.sort_values('DAC_funding_ratio', ascending=False).head())"
+    "# Quick validation\n",
+    "print(f\"Total GGRF Funding: ${data['Total Program GGRFFunding'].sum()/1e9:.2f}B\")\n",
+    "print(f\"Number of projects: {len(data)}\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 2000x1500 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Key metrics by period:\n",
+      "     Total Program GGRFFunding                          \\\n",
+      "                         count         sum        mean   \n",
+      "Year                                                     \n",
+      "2011                         1       11500    11500.00   \n",
+      "2012                        98     2328417    23759.36   \n",
+      "2013                      3379    50726172    15012.18   \n",
+      "2014                      7281    76042854    10444.01   \n",
+      "2015                      6235    61034095     9788.95   \n",
+      "2016                      8001   105685277    13209.01   \n",
+      "2017                     12745   368260901    28894.54   \n",
+      "2018                     18071   641426028    35494.77   \n",
+      "2019                     21131  1131373505    53540.94   \n",
+      "2020                     18281  1555581678    85092.81   \n",
+      "2021                     15957  1147697486    71924.39   \n",
+      "2022                     12906  1187728536    92029.18   \n",
+      "2023                      6825  1114799921   163340.65   \n",
+      "2024                       517   686268968  1327406.13   \n",
+      "\n",
+      "     Is Benefit Disadvantaged Communities is_multi_county        \\\n",
+      "                                     mean           count  mean   \n",
+      "Year                                                              \n",
+      "2011                                 1.00               1  0.00   \n",
+      "2012                                 0.29              98  0.00   \n",
+      "2013                                 0.28            3379  0.00   \n",
+      "2014                                 0.40            7281  0.00   \n",
+      "2015                                 0.48            6235  0.01   \n",
+      "2016                                 0.59            8001  0.00   \n",
+      "2017                                 0.45           12745  0.00   \n",
+      "2018                                 0.44           18071  0.00   \n",
+      "2019                                 0.35           21131  0.00   \n",
+      "2020                                 0.30           18281  0.01   \n",
+      "2021                                 0.27           15957  0.01   \n",
+      "2022                                 0.23           12906  0.01   \n",
+      "2023                                 0.00            6825  0.01   \n",
+      "2024                                 0.00             517  0.07   \n",
+      "\n",
+      "     partnership_size  \n",
+      "                 mean  \n",
+      "Year                   \n",
+      "2011             1.00  \n",
+      "2012             1.00  \n",
+      "2013             1.00  \n",
+      "2014             1.00  \n",
+      "2015             1.02  \n",
+      "2016             1.00  \n",
+      "2017             1.01  \n",
+      "2018             1.01  \n",
+      "2019             1.01  \n",
+      "2020             1.06  \n",
+      "2021             1.02  \n",
+      "2022             1.03  \n",
+      "2023             1.03  \n",
+      "2024             1.32  \n"
+     ]
+    }
+   ],
+   "source": [
+    "# Temporal analysis of GGRF funding\n",
+    "temporal = data.groupby('Year').agg({\n",
+    "   'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
+    "   'Is Benefit Disadvantaged Communities': 'mean',\n",
+    "   'is_multi_county': ['count', 'mean'],\n",
+    "   'partnership_size': 'mean'\n",
+    "}).round(2)\n",
+    "\n",
+    "# Visualize key metrics\n",
+    "fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(20, 15))\n",
+    "\n",
+    "# Projects per year\n",
+    "ax1.plot(temporal.index, temporal[('Total Program GGRFFunding', 'count')], \n",
+    "        marker='o', linewidth=2)\n",
+    "ax1.set_title('Number of GGRF Projects by Year')\n",
+    "ax1.grid(True, alpha=0.3)\n",
+    "\n",
+    "# Average funding per project\n",
+    "ax2.plot(temporal.index, temporal[('Total Program GGRFFunding', 'mean')]/1e6,\n",
+    "        marker='o', linewidth=2)\n",
+    "ax2.set_title('Average GGRF Funding per Project (Millions $)')\n",
+    "ax2.grid(True, alpha=0.3)\n",
+    "\n",
+    "# DAC benefit rate\n",
+    "ax3.plot(temporal.index, temporal[('Is Benefit Disadvantaged Communities', 'mean')],\n",
+    "        marker='o', linewidth=2)\n",
+    "ax3.set_title('DAC Benefit Rate')\n",
+    "ax3.grid(True, alpha=0.3)\n",
+    "\n",
+    "# Multi-county projects\n",
+    "ax4.plot(temporal.index, temporal[('partnership_size', 'mean')],\n",
+    "        marker='o', linewidth=2)\n",
+    "ax4.set_title('Average Number of Partner Counties')\n",
+    "ax4.grid(True, alpha=0.3)\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n",
+    "\n",
+    "print(\"Key metrics by period:\")\n",
+    "print(temporal)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2024 Projects by Program:\n",
+      "                                                   Total Program GGRFFunding  \\\n",
+      "                                                                       count   \n",
+      "Program Name                                                                   \n",
+      "Affordable Housing and Sustainable Communities ...                         8   \n",
+      "Climate Adaptation and Resiliency Program                                  1   \n",
+      "Community Air Protection                                                 220   \n",
+      "Fire Prevention Program                                                   12   \n",
+      "Fluorinated Gases Emission Reduction Incentives                           15   \n",
+      "Food Production Investment Program                                        30   \n",
+      "Forest Carbon Plan Implementation                                          5   \n",
+      "Forest Health Program                                                     20   \n",
+      "Low Carbon Transit Operations Program                                     18   \n",
+      "Low Carbon Transportation                                                  4   \n",
+      "Safe and Affordable Drinking Water Fund                                   10   \n",
+      "Transformative Climate Communities                                        10   \n",
+      "Transit and Intercity Rail Capital Program                                29   \n",
+      "Urban and Community Forestry Program                                     132   \n",
+      "Waste Diversion                                                            1   \n",
+      "Wetlands and Watershed Restoration                                         2   \n",
+      "\n",
+      "                                                                            \n",
+      "                                                          sum         mean  \n",
+      "Program Name                                                                \n",
+      "Affordable Housing and Sustainable Communities ...  176615877  22076984.62  \n",
+      "Climate Adaptation and Resiliency Program              299000    299000.00  \n",
+      "Community Air Protection                             80955408    367979.13  \n",
+      "Fire Prevention Program                               7806649    650554.08  \n",
+      "Fluorinated Gases Emission Reduction Incentives       1000001     66666.73  \n",
+      "Food Production Investment Program                   70824290   2360809.67  \n",
+      "Forest Carbon Plan Implementation                     1108131    221626.20  \n",
+      "Forest Health Program                                57230331   2861516.55  \n",
+      "Low Carbon Transit Operations Program                11165512    620306.22  \n",
+      "Low Carbon Transportation                            10744732   2686183.00  \n",
+      "Safe and Affordable Drinking Water Fund              10457866   1045786.60  \n",
+      "Transformative Climate Communities                   38277301   3827730.10  \n",
+      "Transit and Intercity Rail Capital Program          189696000   6541241.38  \n",
+      "Urban and Community Forestry Program                 18561997    140621.19  \n",
+      "Waste Diversion                                       3950527   3950527.00  \n",
+      "Wetlands and Watershed Restoration                    7575346   3787673.00  \n",
+      "\n",
+      "Largest 2024 Projects:\n",
+      "                                             Program Name         County  \\\n",
+      "117879         Transit and Intercity Rail Capital Program        Alameda   \n",
+      "90922          Transit and Intercity Rail Capital Program    Los Angeles   \n",
+      "136661  Affordable Housing and Sustainable Communities...    Los Angeles   \n",
+      "141400  Affordable Housing and Sustainable Communities...  San Francisco   \n",
+      "100763  Affordable Housing and Sustainable Communities...  San Francisco   \n",
+      "\n",
+      "        Total Program GGRFFunding Date Operational  \n",
+      "117879                  107100000       2024-03-01  \n",
+      "90922                    40000000       2024-09-23  \n",
+      "136661                   29889806       2024-04-01  \n",
+      "141400                   29269952       2024-08-01  \n",
+      "100763                   25424799       2024-01-01  \n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"2024 Projects by Program:\")\n",
+    "print(data[data['Year'] == 2024].groupby('Program Name').agg({\n",
+    "    'Total Program GGRFFunding': ['count', 'sum', 'mean']\n",
+    "}).round(2))\n",
+    "\n",
+    "print(\"\\nLargest 2024 Projects:\")\n",
+    "print(data[data['Year'] == 2024].nlargest(5, 'Total Program GGRFFunding')[\n",
+    "    ['Program Name', 'County', 'Total Program GGRFFunding', 'Date Operational']\n",
+    "])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2023 vs 2024 Program Comparison:\n",
+      "                                                        Total Program GGRFFunding  \\\n",
+      "                                                                            count   \n",
+      "Year Program Name                                                                   \n",
+      "2023 Affordable Housing and Sustainable Communities ...                        20   \n",
+      "     Climate Adaptation and Resiliency Program                                  6   \n",
+      "     Climate Change Research Program                                            3   \n",
+      "     Climate Ready Program                                                      4   \n",
+      "     Climate Resilience Planning                                               36   \n",
+      "     Climate Smart Agriculture                                                363   \n",
+      "     Community Air Protection                                                1926   \n",
+      "     Fire Prevention Program                                                   11   \n",
+      "     Food Production Investment Program                                        20   \n",
+      "     Forest Carbon Plan Implementation                                         83   \n",
+      "     Forest Health Program                                                     27   \n",
+      "     Funding Agricultural Replacement Measures for E...                       539   \n",
+      "     Low Carbon Transit Operations Program                                     99   \n",
+      "     Low Carbon Transportation                                               3187   \n",
+      "     Low-Income Weatherization Program                                         26   \n",
+      "     SB 1383 Local Assistance Grant Program                                    12   \n",
+      "     Safe and Affordable Drinking Water Fund                                   22   \n",
+      "     Sustainable Agricultural Lands Conservation Pro...                        15   \n",
+      "     Training and Workforce Development Program                               136   \n",
+      "     Transformative Climate Communities                                       142   \n",
+      "     Transit and Intercity Rail Capital Program                                14   \n",
+      "     Urban Greening Program                                                    42   \n",
+      "     Waste Diversion                                                           18   \n",
+      "     Water-Energy Efficiency                                                   51   \n",
+      "     Wetlands and Watershed Restoration                                         1   \n",
+      "     Woodsmoke Reduction Program                                               22   \n",
+      "2024 Affordable Housing and Sustainable Communities ...                         8   \n",
+      "     Climate Adaptation and Resiliency Program                                  1   \n",
+      "     Community Air Protection                                                 220   \n",
+      "     Fire Prevention Program                                                   12   \n",
+      "     Fluorinated Gases Emission Reduction Incentives                           15   \n",
+      "     Food Production Investment Program                                        30   \n",
+      "     Forest Carbon Plan Implementation                                          5   \n",
+      "     Forest Health Program                                                     20   \n",
+      "     Low Carbon Transit Operations Program                                     18   \n",
+      "     Low Carbon Transportation                                                  4   \n",
+      "     Safe and Affordable Drinking Water Fund                                   10   \n",
+      "     Transformative Climate Communities                                        10   \n",
+      "     Transit and Intercity Rail Capital Program                                29   \n",
+      "     Urban and Community Forestry Program                                     132   \n",
+      "     Waste Diversion                                                            1   \n",
+      "     Wetlands and Watershed Restoration                                         2   \n",
+      "\n",
+      "                                                                    \\\n",
+      "                                                               sum   \n",
+      "Year Program Name                                                    \n",
+      "2023 Affordable Housing and Sustainable Communities ...  334283890   \n",
+      "     Climate Adaptation and Resiliency Program             3374200   \n",
+      "     Climate Change Research Program                        396119   \n",
+      "     Climate Ready Program                                 4368244   \n",
+      "     Climate Resilience Planning                           5041046   \n",
+      "     Climate Smart Agriculture                            43068601   \n",
+      "     Community Air Protection                             45727103   \n",
+      "     Fire Prevention Program                               9456431   \n",
+      "     Food Production Investment Program                   42815128   \n",
+      "     Forest Carbon Plan Implementation                    22524961   \n",
+      "     Forest Health Program                                37902075   \n",
+      "     Funding Agricultural Replacement Measures for E...   40805691   \n",
+      "     Low Carbon Transit Operations Program               114507056   \n",
+      "     Low Carbon Transportation                           169989768   \n",
+      "     Low-Income Weatherization Program                     4226240   \n",
+      "     SB 1383 Local Assistance Grant Program                5969666   \n",
+      "     Safe and Affordable Drinking Water Fund              11621901   \n",
+      "     Sustainable Agricultural Lands Conservation Pro...   24711311   \n",
+      "     Training and Workforce Development Program            7332437   \n",
+      "     Transformative Climate Communities                   40263894   \n",
+      "     Transit and Intercity Rail Capital Program          118568000   \n",
+      "     Urban Greening Program                               26722800   \n",
+      "     Waste Diversion                                        213843   \n",
+      "     Water-Energy Efficiency                                 73165   \n",
+      "     Wetlands and Watershed Restoration                     743216   \n",
+      "     Woodsmoke Reduction Program                             93135   \n",
+      "2024 Affordable Housing and Sustainable Communities ...  176615877   \n",
+      "     Climate Adaptation and Resiliency Program              299000   \n",
+      "     Community Air Protection                             80955408   \n",
+      "     Fire Prevention Program                               7806649   \n",
+      "     Fluorinated Gases Emission Reduction Incentives       1000001   \n",
+      "     Food Production Investment Program                   70824290   \n",
+      "     Forest Carbon Plan Implementation                     1108131   \n",
+      "     Forest Health Program                                57230331   \n",
+      "     Low Carbon Transit Operations Program                11165512   \n",
+      "     Low Carbon Transportation                            10744732   \n",
+      "     Safe and Affordable Drinking Water Fund              10457866   \n",
+      "     Transformative Climate Communities                   38277301   \n",
+      "     Transit and Intercity Rail Capital Program          189696000   \n",
+      "     Urban and Community Forestry Program                 18561997   \n",
+      "     Waste Diversion                                       3950527   \n",
+      "     Wetlands and Watershed Restoration                    7575346   \n",
+      "\n",
+      "                                                        Is Benefit Disadvantaged Communities  \n",
+      "                                                                                        mean  \n",
+      "Year Program Name                                                                             \n",
+      "2023 Affordable Housing and Sustainable Communities ...                                 0.00  \n",
+      "     Climate Adaptation and Resiliency Program                                          0.00  \n",
+      "     Climate Change Research Program                                                    0.00  \n",
+      "     Climate Ready Program                                                              0.00  \n",
+      "     Climate Resilience Planning                                                        0.00  \n",
+      "     Climate Smart Agriculture                                                          0.00  \n",
+      "     Community Air Protection                                                           0.00  \n",
+      "     Fire Prevention Program                                                            0.00  \n",
+      "     Food Production Investment Program                                                 0.00  \n",
+      "     Forest Carbon Plan Implementation                                                  0.00  \n",
+      "     Forest Health Program                                                              0.00  \n",
+      "     Funding Agricultural Replacement Measures for E...                                 0.00  \n",
+      "     Low Carbon Transit Operations Program                                              0.00  \n",
+      "     Low Carbon Transportation                                                          0.00  \n",
+      "     Low-Income Weatherization Program                                                  0.00  \n",
+      "     SB 1383 Local Assistance Grant Program                                             0.00  \n",
+      "     Safe and Affordable Drinking Water Fund                                            0.00  \n",
+      "     Sustainable Agricultural Lands Conservation Pro...                                 0.00  \n",
+      "     Training and Workforce Development Program                                         0.00  \n",
+      "     Transformative Climate Communities                                                 0.00  \n",
+      "     Transit and Intercity Rail Capital Program                                         0.36  \n",
+      "     Urban Greening Program                                                             0.00  \n",
+      "     Waste Diversion                                                                    0.00  \n",
+      "     Water-Energy Efficiency                                                            0.06  \n",
+      "     Wetlands and Watershed Restoration                                                 0.00  \n",
+      "     Woodsmoke Reduction Program                                                        0.00  \n",
+      "2024 Affordable Housing and Sustainable Communities ...                                 0.00  \n",
+      "     Climate Adaptation and Resiliency Program                                          0.00  \n",
+      "     Community Air Protection                                                           0.00  \n",
+      "     Fire Prevention Program                                                            0.00  \n",
+      "     Fluorinated Gases Emission Reduction Incentives                                    0.00  \n",
+      "     Food Production Investment Program                                                 0.00  \n",
+      "     Forest Carbon Plan Implementation                                                  0.00  \n",
+      "     Forest Health Program                                                              0.00  \n",
+      "     Low Carbon Transit Operations Program                                              0.00  \n",
+      "     Low Carbon Transportation                                                          0.00  \n",
+      "     Safe and Affordable Drinking Water Fund                                            0.00  \n",
+      "     Transformative Climate Communities                                                 0.00  \n",
+      "     Transit and Intercity Rail Capital Program                                         0.00  \n",
+      "     Urban and Community Forestry Program                                               0.00  \n",
+      "     Waste Diversion                                                                    0.00  \n",
+      "     Wetlands and Watershed Restoration                                                 0.00  \n",
+      "\n",
+      "Percent Changes 2023-2024:\n",
+      "       Total Program GGRFFunding  Is Benefit Disadvantaged Communities\n",
+      "count                     -92.42                                   NaN\n",
+      "sum                       -38.44                                   NaN\n",
+      "mean                      712.66                                -100.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "# Compare 2023 vs 2024 by program\n",
+    "years_comparison = data[data['Year'].isin([2023, 2024])].groupby(['Year', 'Program Name']).agg({\n",
+    "    'Total Program GGRFFunding': ['count', 'sum'],\n",
+    "    'Is Benefit Disadvantaged Communities': 'mean'\n",
+    "}).round(2)\n",
+    "\n",
+    "print(\"2023 vs 2024 Program Comparison:\")\n",
+    "print(years_comparison)\n",
+    "\n",
+    "# Calculate percent changes in key metrics\n",
+    "print(\"\\nPercent Changes 2023-2024:\")\n",
+    "metrics_2023 = data[data['Year'] == 2023].agg({\n",
+    "    'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
+    "    'Is Benefit Disadvantaged Communities': 'mean'\n",
+    "})\n",
+    "\n",
+    "metrics_2024 = data[data['Year'] == 2024].agg({\n",
+    "    'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
+    "    'Is Benefit Disadvantaged Communities': 'mean'\n",
+    "})\n",
+    "\n",
+    "pct_change = ((metrics_2024 - metrics_2023) / metrics_2023 * 100).round(2)\n",
+    "print(pct_change)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2023-2024 Changes (excluding Low Carbon Transportation):\n",
+      "                                                    2023          2024\n",
+      "Total Program GGRFFunding            count  3.638000e+03  5.130000e+02\n",
+      "                                     sum    9.448102e+08  6.755242e+08\n",
+      "                                     mean   2.597059e+05  1.316811e+06\n",
+      "Is Benefit Disadvantaged Communities mean   0.000000e+00  0.000000e+00\n",
+      "is_multi_county                      count  3.638000e+03  5.130000e+02\n",
+      "                                     mean   2.000000e-02  7.000000e-02\n",
+      "partnership_size                     mean   1.050000e+00  1.320000e+00\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Filter out Low Carbon Transportation\n",
+    "data_filtered = data[data['Program Name'] != 'Low Carbon Transportation'].copy()\n",
+    "\n",
+    "# Recalculate temporal analysis\n",
+    "temporal_filtered = data_filtered.groupby('Year').agg({\n",
+    "   'Total Program GGRFFunding': ['count', 'sum', 'mean'],\n",
+    "   'Is Benefit Disadvantaged Communities': 'mean',\n",
+    "   'is_multi_county': ['count', 'mean'],\n",
+    "   'partnership_size': 'mean'\n",
+    "}).round(2)\n",
+    "\n",
+    "# Compare 2023-2024 without LCT\n",
+    "years_comparison = data_filtered[data_filtered['Year'].isin([2023, 2024])].groupby(['Year', 'Program Name']).agg({\n",
+    "   'Total Program GGRFFunding': ['count', 'sum'],\n",
+    "   'Is Benefit Disadvantaged Communities': 'mean'\n",
+    "}).round(2)\n",
+    "\n",
+    "print(\"2023-2024 Changes (excluding Low Carbon Transportation):\")\n",
+    "changes = pd.DataFrame({\n",
+    "   '2023': temporal_filtered.loc[2023],\n",
+    "   '2024': temporal_filtered.loc[2024]\n",
+    "})\n",
+    "print(changes)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAB8YAAAXRCAYAAADsS/daAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3hUZd7G8Xtm0jvpoQUSkN5RQFFRkIAsiqIoCgKiWLCg61pWXcCyuuv62hYVy4IrIKKiLiIiKqgUlS5dSEIPKYT0PnPeP0KGhCSQQJKT8v1cl9c7c+bM5DeTh33znHue32MxDMMQAAAAAAAAAAAAAACNlNXsAgAAAAAAAAAAAAAAqE0E4wAAAAAAAAAAAACARo1gHAAAAAAAAAAAAADQqBGMAwAAAAAAAAAAAAAaNYJxAAAAAAAAAAAAAECjRjAOAAAAAAAAAAAAAGjUCMYBAAAAAAAAAAAAAI0awTgAAAAAAAAAAAAAoFEjGAcAAAAAAAAAAAAANGoE4wCAOrdq1SpZLBZ9+umnZpdSJYmJibrhhhsUFBQki8WiV1991eySNGPGDFksFrPLqLZDhw7Jw8NDa9asMbWO2vj8KnrNNm3aaOLEiTX6c+q748ePy9vbW19//bXZpQAAAABoIubOnSuLxaL9+/ebXUq9s3//flksFs2dO9d5rD5cU7j66qt155131shrnT73LrnutGrVKuexiRMnqk2bNmWeZ7FYNGPGjBqpoTZNnDixzHspbefOnXJxcdH27dvrtigAaKAIxgGgkSqZFHp4eOjIkSPlHh80aJC6du1qQmUNz0MPPaTly5friSee0Icffqhhw4ZVeq7FYnH+Z7Va1bx5cw0dOrTSCUx99fXXX9fK5PCZZ55Rv379dMkllziPTZw4scznVvo/Dw+PGq+hqbBYLLrvvvuqdO7nn3+u4cOHKzg4WG5ubmrevLnGjBmjH374QVLxRYbKfkel/5s7d66CgoJ0xx136Omnn67NtwcAAADUG2+++aYsFov69etndin1zulzidDQUF166aX6/PPPzS6tWtauXasZM2YoLS2tSuefaZ77zTff1G6xDcCaNWv07bff6rHHHnMeKwmzLRaL5s2bV+HzLrnkElksFq5nldK5c2eNGDFCf/vb38wuBQAaBBezCwAA1K78/Hy9+OKLeuONN8wupcH64YcfdO211+qRRx6p0vlXXXWVbrvtNhmGofj4eL355pu68sortXTpUg0fPrxGanrqqaf0+OOP18hrVeTrr7/WrFmzajQcT05O1gcffKAPPvig3GPu7u567733yh232Ww19vPNsGfPHlmt9fd7iIZh6Pbbb9fcuXPVq1cvPfzwwwoPD1dCQoI+//xzDR48WGvWrNGrr76qrKws5/O+/vprffTRR3rllVcUHBzsPH7xxRdLku6++269/vrr+uGHH3TllVfW+fsCAAAA6tL8+fPVpk0b/fbbb9q3b5/atWtndkn1Ss+ePfXnP/9ZknT06FHNnj1b119/vd566y3dfffdNfIzxo8fr5tvvlnu7u418nqnW7t2rWbOnKmJEycqICCgSs+pbJ7bo0ePGq6u+mr7msLZvPTSSxo8eHCF/1Y8PDy0YMECjRs3rszx/fv3a+3atRV+gf5c5965ublycan/EUlRUZHy8/Mrffzuu+/W1VdfrdjYWEVHR9dhZQDQ8NT//9UHAJyXnj176t1339UTTzyh5s2bm11OncrOzpa3t/d5v05SUlKVJ76SdMEFF5SZwF133XXq3r27Xn311UqD8by8PLm5uVV5Iufi4tIgJm+lzZs3Ty4uLho5cmS5x1xcXMpNehuD2rooU1NefvllzZ07V9OmTdP//d//lWml9+STT+rDDz+Ui4uLRo0aVeZ5x44d00cffaRRo0aVa0UnSZ06dVLXrl01d+5cgnEAAAA0avHx8Vq7dq0WL16su+66S/Pnz9f06dPrtAaHw6GCgoJ623GrRYsWZeZ7t912m9q1a6dXXnml0mC8qKhIDodDbm5uVfoZNput3n2xuj7Pc828ppCUlKSlS5fq7bffrvDxq6++Wv/73/+UkpJS5ovYCxYsUFhYmNq3b68TJ06Uec65zr3r678ZSUpPT9e0adP06aefKisrS/Pnz5ePj48uvvhiffzxx2WuUw0ZMkTNmjXTBx98oGeeeca8ogGgAai/S5gAADXir3/9q+x2u1588cUznlfRnlMlTt9zqWQvqj/++EPjxo2Tv7+/QkJC9PTTT8swDB06dEjXXnut/Pz8FB4erpdffrnCn2m32/XXv/5V4eHh8vb21jXXXKNDhw6VO+/XX3/VsGHD5O/vLy8vL11++eXl9qguqWnnzp265ZZb1KxZMw0cOPCM7zkuLk433nijAgMD5eXlpf79+2vp0qXOx0va0RuGoVmzZjlbelVXt27dFBwcrPj4eEmn2oMtXLhQTz31lFq0aCEvLy9lZGRIkj755BP16dNHnp6eCg4O1rhx48q1w69sP7B58+Y5nxsYGKibb7650s/06quvVrNmzeTt7a3u3bvrtddek1Tc8m3WrFmSyraGL7Fw4UL16dNHvr6+8vPzU7du3ZzPPZMvvvhC/fr1k4+PTxU/uVMMw9AVV1yhkJAQJSUlOY8XFBSoW7duio6OVnZ2dpXeX0WqM/4lafXq1brwwgvl4eGh6OhozZ49u8LXPX2fs5IxtWbNGj388MMKCQmRt7e3rrvuOiUnJ5d5rsPh0IwZM9S8eXN5eXnpiiuu0M6dO2ts3/Lc3Fy98MIL6tixo/71r39VOJ7Gjx+viy666Jxe/6qrrtKSJUtkGMb5lgoAAADUW/Pnz1ezZs00YsQI3XDDDZo/f77zscLCQgUGBmrSpEnlnpeRkSEPD48yncny8/M1ffp0tWvXTu7u7mrVqpUeffTRcitFS7ZNmj9/vrp06SJ3d3dne+5//etfuvjiixUUFCRPT0/16dNHn376abmfn5ubqwceeEDBwcHy9fXVNddcoyNHjlQ4/zly5Ihuv/12hYWFyd3dXV26dNF//vOfc/7MwsPD1alTJ+ccuWQ+9q9//UuvvvqqoqOj5e7urp07d0oq7uJ26aWXytvbWwEBAbr22mu1a9euMq9Z2R7jy5Ytcz7X19dXI0aM0I4dO8rVtHv3bo0ZM0YhISHy9PRUhw4d9OSTT0oqnn//5S9/kSS1bdvWOUc+n/3MK9oDu/RnUXpuOnHiRPn4+OjIkSMaNWqUfHx8FBISokceeUR2u73M89PS0jRx4kT5+/srICBAEyZMqLD9e0XXFErG1RdffKGuXbs6f9cVtX5ftWqV+vbtW2ZOXNV9y5cuXaqioiINGTKkwsevvfZaubu765NPPilzfMGCBRozZkyFX4A413lyReN98+bNGj58uPz8/OTj46PBgwfrl19+KXNOdeb2GzZsUExMjIKDg+Xp6am2bdvq9ttvP2ttDz74oObPn6+HH35YV111lZ555hnNmDFDWVlZZa5/SJKrq6sGDRqkL7/8stqfAQA0NQ1rqRkAoNratm2r2267Te+++64ef/zxGl01ftNNN6lTp0568cUXtXTpUj333HMKDAzU7NmzdeWVV+of//iH5s+fr0ceeUQXXnihLrvssjLPf/7552WxWPTYY48pKSlJr776qoYMGaItW7bI09NTUvEEePjw4erTp4+mT58uq9WqOXPm6Morr9TPP/9cLrS78cYb1b59e/39738/YyCXmJioiy++WDk5OXrggQcUFBSkDz74QNdcc40+/fRTXXfddbrsssv04Ycfavz48c726OfixIkTOnHiRLkWYc8++6zc3Nz0yCOPKD8/X25ubpo7d64mTZqkCy+8UC+88IISExP12muvac2aNdq8efMZV64///zzevrppzVmzBjdcccdSk5O1htvvKHLLruszHNXrFihP/3pT4qIiNCDDz6o8PBw7dq1S1999ZUefPBB3XXXXTp69KhWrFihDz/8sMzPWLFihcaOHavBgwfrH//4hyRp165dWrNmjR588MFKayssLNT69et1zz33VHpOSkpKuWNubm7y8/OTxWLRf/7zH3Xv3l133323Fi9eLEmaPn26duzYoVWrVjm7A5zt/Z2vbdu2aejQoQoJCdGMGTNUVFSk6dOnKywsrMqvcf/996tZs2aaPn269u/fr1dffVX33XefPv74Y+c5TzzxhP75z39q5MiRiomJ0datWxUTE6O8vLzzfg9ScbifmpqqadOm1crKij59+uiVV17Rjh072P8NAAAAjdb8+fN1/fXXy83NTWPHjtVbb72l9evX68ILL5Srq6uuu+46LV68WLNnzy6z+vmLL75Qfn6+br75ZknFX4y95pprtHr1ak2ZMkWdOnXStm3b9Morr+iPP/7QF198Uebn/vDDD1q0aJHuu+8+BQcHOzs5vfbaa7rmmmt06623qqCgQAsXLtSNN96or776SiNGjHA+f+LEiVq0aJHGjx+v/v3768cffyzzeInExET179/fGZqGhIRo2bJlmjx5sjIyMjRt2rRqf2aFhYU6dOiQgoKCyhyfM2eO8vLyNGXKFLm7uyswMFDfffedhg8frqioKM2YMUO5ubl64403dMkll2jTpk0VdrAq8eGHH2rChAmKiYnRP/7xD+Xk5Oitt97SwIEDtXnzZudzf//9d1166aVydXXVlClT1KZNG8XGxmrJkiV6/vnndf311+uPP/4ot51USEjIWd/r6fNcV1dX+fv7V+8DU/HCgpiYGPXr10//+te/9N133+nll19WdHS0c55tGIauvfZarV69Wnfffbc6deqkzz//XBMmTKjyz1m9erUWL16se++9V76+vnr99dc1evRoHTx40Pn72rx5s4YNG6aIiAjNnDlTdrtdzzzzTJU+D6m4LX1QUJAiIyMrfNzLy0vXXnutPvroI+d727p1q3bs2KH33ntPv//+e5XfT3Xt2LFDl156qfz8/PToo4/K1dVVs2fP1qBBg/Tjjz+qX79+Zc4/29w+KSnJef3g8ccfV0BAgPbv3++8pnEmS5cu1cSJE50t/C+99FINGjTIuS3B6fr06aMvv/xSGRkZ8vPzO/8PAwAaKwMA0CjNmTPHkGSsX7/eiI2NNVxcXIwHHnjA+fjll19udOnSxXk/Pj7ekGTMmTOn3GtJMqZPn+68P336dEOSMWXKFOexoqIio2XLlobFYjFefPFF5/ETJ04Ynp6exoQJE5zHVq5caUgyWrRoYWRkZDiPL1q0yJBkvPbaa4ZhGIbD4TDat29vxMTEGA6Hw3leTk6O0bZtW+Oqq64qV9PYsWOr9PlMmzbNkGT8/PPPzmOZmZlG27ZtjTZt2hh2u73M+586dWqVXleSMXnyZCM5OdlISkoyfv31V2Pw4MGGJOPll18u8/6joqKMnJwc53MLCgqM0NBQo2vXrkZubq7z+FdffWVIMv72t7+Ve78l9u/fb9hsNuP5558vU8+2bdsMFxcX5/GioiKjbdu2RmRkpHHixIky55b+jKdOnWpU9GfCgw8+aPj5+RlFRUVV+jxK7Nu3z5BkvPHGG+UemzBhgiGpwv9iYmLKnDt79mxDkjFv3jzjl19+MWw2mzFt2jTn41V9f6d/ftUZ/6NGjTI8PDyMAwcOOI/t3LnTsNls5T6zyMjIMmO/5N/lkCFDytTz0EMPGTabzUhLSzMMwzCOHTtmuLi4GKNGjSrzejNmzDAklXnNypxt3L722muGJOPzzz8/62ud7qWXXjIkGfHx8ZWes3btWkOS8fHHH1f79QEAAICGYMOGDYYkY8WKFYZhFM85WrZsaTz44IPOc5YvX25IMpYsWVLmuVdffbURFRXlvP/hhx8aVqu1zBzVMAzj7bffNiQZa9ascR6TZFitVmPHjh3laio9xzSM4nlm165djSuvvNJ5bOPGjYakMnMpwzCMiRMnlpv/TJ482YiIiDBSUlLKnHvzzTcb/v7+5X7e6SIjI42hQ4caycnJRnJysrF161bj5ptvNiQZ999/v2EYp+Zjfn5+RlJSUpnn9+zZ0wgNDTWOHz/uPLZ161bDarUat912m/NYyVyrZI6SmZlpBAQEGHfeeWeZ1zt27Jjh7+9f5vhll11m+Pr6lpnjGUbZOWRV5kClVTbPvfzyyw3DOHVdYOXKlWWeV9HctOS1nnnmmTLn9urVy+jTp4/z/hdffGFIMv75z386jxUVFRmXXnppudc8fU5sGMXjys3Nzdi3b5/z2NatW8vN5UeOHGl4eXkZR44ccR7bu3ev4eLiUuF1hNMNHDiwTN0lSj6TTz75xPjqq68Mi8ViHDx40DAMw/jLX/7i/Pdy+vUswyg/967o850wYYIRGRlZ7j2fPt93c3MzYmNjnceOHj1q+Pr6GpdddpnzWFXn9p9//rnz2lx1hYWFGbfeequz9tPHyukWLFhgSDJ+/fXXav8sAGhKaKUOAE1AVFSUxo8fr3feeUcJCQk19rp33HGH87bNZlPfvn1lGIYmT57sPB4QEKAOHTooLi6u3PNvu+02+fr6Ou/fcMMNioiI0Ndffy1J2rJli/bu3atbbrlFx48fV0pKilJSUpSdna3Bgwfrp59+ksPhKPOale1Pdrqvv/5aF110UZl26z4+PpoyZYr279/vbNl2Lt5//32FhIQoNDRU/fr1c7bWOv2b9BMmTHCujJeK22slJSXp3nvvLbPP1YgRI9SxY8cybd5Pt3jxYjkcDo0ZM8b5OaWkpCg8PFzt27fXypUrJRV/szs+Pl7Tpk0rt/q8Ki3PAgIClJ2drRUrVlThkzjl+PHjkqRmzZpV+LiHh4dWrFhR7r/TtwCYMmWKYmJidP/992v8+PGKjo7W3//+d+fj5/v+zsZut2v58uUaNWqUWrdu7TzeqVMnxcTEVPl1pkyZUqaeSy+9VHa7XQcOHJAkff/99yoqKtK9995b5nn333//eb6DU0pa95f+N1iTSn7XFXUCAAAAABqD+fPnKywsTFdccYWk4jnHTTfdpIULFzpbXF955ZUKDg4u0x3qxIkTWrFihW666SbnsU8++USdOnVSx44dy8zprrzySklyzulKXH755ercuXO5mkrPMU+cOKH09HRdeuml2rRpk/N4SWvss803DMPQZ599ppEjR8owjDJ1xcTEKD09vczrVubbb79VSEiIQkJC1KNHD33yyScaP368swtZidGjR5dZdZyQkKAtW7Zo4sSJCgwMdB7v3r27rrrqKue1g4qsWLFCaWlpGjt2bJm6bTab+vXr5/w8k5OT9dNPP+n2228vM8eTzn8OWdE8t7Kt5qri9Osdl156aZlrLV9//bVcXFzKdGqz2WzVmkcOGTJE0dHRzvvdu3eXn5+f8+fY7XZ99913GjVqVJmOhO3atdPw4cOr9DOOHz9e6bWBEkOHDlVgYKAWLlwowzC0cOFCjR07tsrv41zY7XZ9++23GjVqlKKiopzHIyIidMstt2j16tXOeXSJs83tS65LfPXVVyosLKxWPZMmTXK2j9+5c6eOHj16xvOZgwNA1dBKHQCaiKeeekoffvihXnzxxSrtB10Vp08a/f395eHh4WwrVvp4STBaWvv27cvct1gsateunXOfrr1790rSGdt+paenl5lQtW3btkq1HzhwoFwLLKk44Cx5/FzbP1977bW67777ZLFY5Ovrqy5dujjbfJd2eq0lE6cOHTqUO7djx45avXp1pT9z7969Mgyj3GdawtXVVZIUGxsrSef83u69914tWrRIw4cPV4sWLTR06FCNGTNGw4YNq9LzjUra29tstkr3Fzvd+++/r+joaO3du1dr164tc+HnfN/f2SQnJys3N7fCz7lDhw5nvDBT2un/dkrG8IkTJySdGgunt98PDAw86wWEqipprZaZmVkjr3e6kt91TXwhAQAAAKhv7Ha7Fi5cqCuuuMK5V7Yk9evXTy+//LK+//57DR06VC4uLho9erQWLFig/Px8ubu7a/HixSosLCwTjO/du1e7du2qtB11UlJSmfuVzX2/+uorPffcc9qyZUuZvclL/11+4MABWa3Wcq9x+vwjOTlZaWlpeuedd/TOO+9Uqa6K9OvXT88995wsFou8vLzUqVOnCrcJq84cuVOnTlq+fLmys7MrnG+XXE8o+WLB6UrmQyWBb23MIaszzz0bDw+PcmOjWbNmzjmkVPx5RUREyMfHp8x5FX1+lTl9rnr6z0lKSlJubm65sSKVHz9nUtm1gRKurq668cYbtWDBAl100UU6dOiQbrnlliq//rlITk5WTk5OpePN4XDo0KFD6tKli/P42eb2l19+uUaPHq2ZM2fqlVde0aBBgzRq1Cjdcsstcnd3P2M9zz//vNq0aaP33ntPmzZt0q233qqHH35Yf/7zn/XnP/9ZVmvZNY/MwQGgagjGAaCJiIqK0rhx4/TOO+/o8ccfL/d4ZX84l3zLvSIV7Utc2V7FZ5v0VKRkNfhLL72knj17VnjO6RO+0iGpWVq2bFmlyW9N1upwOGSxWLRs2bIKfwenf07nKjQ0VFu2bNHy5cu1bNkyLVu2THPmzNFtt92mDz74oNLnlexFVnrSfq5WrVrlvMCzbds2DRgw4Lxf81zG//moyX8n56pjx46Sij/DUaNG1fjrl/yuT/+iDAAAANAY/PDDD0pISNDChQu1cOHCco/Pnz9fQ4cOlSTdfPPNmj17tpYtW6ZRo0Zp0aJF6tixo3r06OE83+FwqFu3bvq///u/Cn9eq1atytyvaD75888/65prrtFll12mN998UxEREXJ1ddWcOXO0YMGCar/Hkjn5uHHjKv3Cevfu3c/6OsHBwabMkaXifcbDw8PLPe7iYu5l8erOQSubQ9a0upirBgUFVenawC233KK3335bM2bMUI8ePSrskGC2s31eFotFn376qX755RctWbJEy5cv1+23366XX35Zv/zyyxmv1VitVt1111266667NHHiRHXs2FGbNm3So48+KrvdXu7aHnNwAKgagnEAaEKeeuopzZs3r1y7MunUt1rT0tLKHC/5hnZtKPkGdwnDMLRv3z7nxLqkfZefn1+Nfcu6RGRkpPbs2VPu+O7du52P17WSn7lnz55y32rfs2fPGWuKjo6WYRhq27atLrjggjOeJ0nbt28/42d6pm8Yu7m5aeTIkRo5cqQcDofuvfdezZ49W08//XSl3xBv3bq1PD09y6ykOBcJCQm6//77NXToULm5uemRRx5RTEyM87Op6vs7XVXHf0hIiDw9PcuNXUkVjqdzVfJ+9u3bV2bVxPHjx2vkywWSNHDgQDVr1kwfffSR/vrXv9b4hZaS33VJFwYAAACgMZk/f75CQ0M1a9asco8tXrxYn3/+ud5++215enrqsssuU0REhD7++GMNHDhQP/zwg5588skyz4mOjtbWrVs1ePDgc17x+dlnn8nDw0PLly8vsxp1zpw5Zc6LjIyUw+FQfHx8mW5Y+/btK3NeSEiIfH19Zbfba3xOXhWl58in2717t4KDgytcLS6dmhuGhoaesfaSltnbt28/Yy01vQq3Nq7BREZG6vvvv1dWVlaZwLUm56qhoaHy8PAoN1ak8uOnMh07dtRnn3121vMGDhyo1q1ba9WqVRVex6ppISEh8vLyqnS8Wa3Wcl9Qqar+/furf//+ev7557VgwQLdeuutWrhwYZktCqvyGo8//ri6d++uTz/9tFwwHh8fL6vVesZrQgAAiT3GAaAJiY6O1rhx4zR79mwdO3aszGN+fn4KDg7WTz/9VOb4m2++WWv1/Pe//y3TxvnTTz9VQkKCc1+qPn36KDo6Wv/617+UlZVV7vnJycnn/LOvvvpq/fbbb1q3bp3zWHZ2tt555x21adPGlG8i9+3bV6GhoXr77bfLtLxbtmyZdu3apREjRlT63Ouvv142m00zZ84s901uwzCcrex79+6ttm3b6tVXXy03AS/9vJKLC6efc3pLfKvV6vwiQ+maT+fq6qq+fftqw4YNlZ5TFXfeeaccDofef/99vfPOO3JxcdHkyZOdtVf1/Z2uquPfZrMpJiZGX3zxhQ4ePOg8vmvXLi1fvvy83ltpgwcPlouLi956660yx//973/X2M/w8vLSY489pl27dumxxx6r8POZN2+efvvtt3N6/Y0bN8rf379MmzkAAACgMcjNzdXixYv1pz/9STfccEO5/+677z5lZmbqf//7n6TiedMNN9ygJUuW6MMPP1RRUVGZNuqSNGbMGB05ckTvvvtuhT8vOzv7rHXZbDZZLJYyq47379+vL774osx5MTExksrPd954441yrzd69Gh99tlnFQbH5zMnr4qIiAj17NlTH3zwQZn53fbt2/Xtt9/q6quvrvS5MTEx8vPz09///vcK93YuqT0kJESXXXaZ/vOf/5SZ40lVmyOfq8jISNlsthq9BnP11VerqKiozDzSbreX+72ej5L28F988UWZPa/37dunZcuWVek1BgwYoBMnTpTZH70iFotFr7/+uqZPn67x48efV91VYbPZNHToUH355ZfOLf4kKTExUQsWLNDAgQOdLfir6sSJE+Xm2iUdEc90DaXkuaczDEN2u73C7gobN25Uly5d5O/vX60aAaCpYcU4ADQxTz75pD788EPt2bOnXGB1xx136MUXX9Qdd9yhvn376qefftIff/xRa7UEBgZq4MCBmjRpkhITE/Xqq6+qXbt2uvPOOyUVXzx47733NHz4cHXp0kWTJk1SixYtdOTIEa1cuVJ+fn5asmTJOf3sxx9/XB999JGGDx+uBx54QIGBgfrggw8UHx+vzz77rNxeTXXB1dVV//jHPzRp0iRdfvnlGjt2rBITE/Xaa6+pTZs2euihhyp9bnR0tJ577jk98cQT2r9/v0aNGiVfX1/Fx8fr888/15QpU/TII4/IarXqrbfe0siRI9WzZ09NmjRJERER2r17t3bs2OEMd/v06SNJeuCBBxQTEyObzaabb75Zd9xxh1JTU3XllVeqZcuWOnDggN544w317NnzrCuDr732Wj355JPKyMgoN5ksKirSvHnzKnzeddddJ29vb82ZM0dLly7V3Llz1bJlS0nFF27GjRunt956S/fee2+V319Fqjr+Z86cqW+++UaXXnqp7r33XhUVFemNN95Qly5d9Pvvv5/xM6iqsLAwPfjgg3r55Zd1zTXXaNiwYdq6dauWLVum4ODgKq9W2LBhg5577rlyxwcNGqSBAwfqL3/5i3bs2KGXX35ZK1eu1A033KDw8HAdO3ZMX3zxhX777TetXbv2nN7DihUrNHLkSPY3AwAAQKPzv//9T5mZmbrmmmsqfLx///4KCQnR/PnznQH4TTfdpDfeeEPTp09Xt27dys2fxo8fr0WLFunuu+/WypUrdckll8hut2v37t1atGiRli9frr59+56xrhEjRuj//u//NGzYMN1yyy1KSkrSrFmz1K5duzJzlT59+mj06NF69dVXdfz4cfXv318//vijc/5T+m/4F198UStXrlS/fv105513qnPnzkpNTdWmTZv03XffKTU19Zw+w6p66aWXNHz4cA0YMECTJ09Wbm6u3njjDfn7+2vGjBmVPs/Pz09vvfWWxo8fr969e+vmm29WSEiIDh48qKVLl+qSSy5xfvH49ddf18CBA9W7d29NmTJFbdu21f79+7V06VJt2bJF0qk58pNPPqmbb75Zrq6uGjlyZKUr1s/G399fN954o9544w1ZLBZFR0frq6++qtKe7ZUZOXKkLrnkEj3++OPav3+/OnfurMWLFys9Pf2cX7MiM2bM0LfffqtLLrlE99xzj+x2u/7973+ra9euzs/rTEaMGCEXFxd99913mjJlyhnPvfbaa3XttdfWUOVn99xzz2nFihUaOHCg7r33Xrm4uGj27NnKz8/XP//5z2q/3gcffKA333xT1113naKjo5WZmal3331Xfn5+Z/xih1R8nWfSpEkaNGiQkpKStGrVKr3++uvauXNnuS/RFxYW6scff9S9995b7RoBoMkxAACN0pw5cwxJxvr168s9NmHCBEOS0aVLlzLHc3JyjMmTJxv+/v6Gr6+vMWbMGCMpKcmQZEyfPt153vTp0w1JRnJycrnX9fb2LvfzLr/88jI/a+XKlYYk46OPPjKeeOIJIzQ01PD09DRGjBhhHDhwoNzzN2/ebFx//fVGUFCQ4e7ubkRGRhpjxowxvv/++7PWdCaxsbHGDTfcYAQEBBgeHh7GRRddZHz11VflzpNkTJ06tUqvWZVzS97/J598UuHjH3/8sdGrVy/D3d3dCAwMNG699Vbj8OHDZc4peb+n++yzz4yBAwca3t7ehre3t9GxY0dj6tSpxp49e8qct3r1auOqq64yfH19DW9vb6N79+7GG2+84Xy8qKjIuP/++42QkBDDYrE4f9ann35qDB061AgNDTXc3NyM1q1bG3fddZeRkJBw1s8mMTHRcHFxMT788MMyx0vGY2X/xcfHG4cOHTL8/f2NkSNHlnvd6667zvD29jbi4uKq/P4q+vyqOv4NwzB+/PFHo0+fPoabm5sRFRVlvP322xW+ZmRkpDFhwgTn/cr+XZaMiZUrVzqPFRUVGU8//bQRHh5ueHp6GldeeaWxa9cuIygoyLj77rvP+FkbhnHGz/TZZ58tc27J7zUwMNBwcXExIiIijJtuuslYtWpVha/90ksvOX83Fdm1a5chyfjuu+/OWicAAADQ0IwcOdLw8PAwsrOzKz1n4sSJhqurq5GSkmIYhmE4HA6jVatWhiTjueeeq/A5BQUFxj/+8Q+jS5cuhru7u9GsWTOjT58+xsyZM4309HTneWead77//vtG+/btDXd3d6Njx47GnDlzKpyrZGdnG1OnTjUCAwMNHx8fY9SoUcaePXsMScaLL75Y5tzExERj6tSpRqtWrQxXV1cjPDzcGDx4sPHOO++c9bOKjIw0RowYccZz4uPjDUnGSy+9VOHj3333nXHJJZcYnp6ehp+fnzFy5Ehj586dZc4pmWudPkdZuXKlERMTY/j7+xseHh5GdHS0MXHiRGPDhg1lztu+fbtx3XXXOa8PdOjQwXj66afLnPPss88aLVq0MKxW6xnnQ4ZR+fWR0pKTk43Ro0cbXl5eRrNmzYy77rrL2L59uyHJmDNnzllfq6Lf6/Hjx43x48cbfn5+hr+/vzF+/Hhj8+bN5V6zoudWNq5On9cahmF8//33Rq9evQw3NzcjOjraeO+994w///nPhoeHxxnfc4lrrrnGGDx4cJljZ7tWUuL0a0wV1VjRHHvChAlGZGRkmedVNN/ftGmTERMTY/j4+BheXl7GFVdcYaxdu7bMOVWd22/atMkYO3as0bp1a8Pd3d0IDQ01/vSnP5UbfxV55513jMGDBxvh4eGGxWIxPD09ja5duxpvvvlmuXOXLVtmSDL27t171tcFgKbOYhhn6CsKAADqpaefflovvPCCioqKzC6lWiZPnqw//vhDP//8s9mlNEhpaWlq1qyZnnvuuXJ7EtYn06ZN008//aSNGzeyYhwAAABoILZs2aJevXpp3rx5uvXWW80up1ref/993XHHHTp06JCzwxjq1qhRo7Rjxw7t3bv3rOf+/PPPGjRokHbv3l1mn3tUbOLEiZo4caIGDRpU4eOjRo2SxWLR559/XreFAUADxB7jAAA0QAkJCQoODja7jGqbPn261q9frzVr1phdSr2Xm5tb7tirr74qSZVOhuuD48eP67333tNzzz1HKA4AAADUU5XNN6xWqy677DITKjo/CQkJslgsCgwMNLuUJuH08bN37159/fXXVZ6rXnrppRo6dOg5tSdHWbt27dJXX32lZ5991uxSAKBBYI9xAAAakLi4OH3++ef65JNP9Kc//cnscqqtdevWysvLM7uMBuHjjz/W3LlzdfXVV8vHx0erV6/WRx99pKFDh+qSSy4xu7xKBQUFKSsry+wyAAAAAJzBP//5T23cuFFXXHGFXFxctGzZMi1btkxTpkxRq1atzC6vyhITE/Xpp5/q7bff1oABA+Tl5WV2SU1CVFSUJk6cqKioKB04cEBvvfWW3Nzc9Oijj1b5NZYtW1aLFTYuo0aNUps2bSp8rFOnTg2umyAAmIlW6gAANCBz587VAw88oEGDBundd99VWFiY2SWhlmzatEmPPvqotmzZooyMDIWFhWn06NF67rnn5OPjY3Z5AAAAABqwFStWaObMmdq5c6eysrLUunVrjR8/Xk8++aRcXBrOWqpVq1bp6quv1kUXXaR3332Xttx1ZNKkSVq5cqWOHTsmd3d3DRgwQH//+9/Vu3dvs0sDAOCMCMYBAAAAAAAAAAAAAI0ae4wDAAAAAAAAAAAAABq1htMXp5ocDoeOHj0qX19fWSwWs8sBAAAAADRBhmEoMzNTzZs3l9XauL6bzrwbAAAAAGC26sy7G20wfvToUbVq1crsMgAAAAAA0KFDh9SyZUuzy6hRzLsBAAAAAPVFVebdjTYY9/X1lVT8Ifj5+ZlcDWqaw+FQcnKyQkJCGt2qC9QfjDPUFcYa6gLjDHWFsYa60JDGWUZGhlq1auWcozYmzLsbt4b07wwNF+MMdYWxhrrAOENdYayhrjSUsVadeXejDcZL2rj5+fkxQW+EHA6H8vLy5OfnV6//MaJhY5yhrjDWUBcYZ6grjDXUhYY4zhpjq3Hm3Y1bQ/x3hoaHcYa6wlhDXWCcoa4w1lBXGtpYq8q8u/6/CwAAAAAAAAAAAAAAzgPBOAAAAAAAAAAAAACgUSMYBwAAAAAAAAAAAAA0agTjAAAAAAAAAAAAAIBGjWAcAAAAAAAAAAAAANCoEYwDAAAAAAAAAAAAABo1gnEAAAAAAAAAAAAAQKNGMA4AAAAAAAAAAAAAaNQIxgEAAAAAAAAAAAAAjRrBOAAAAAAAAAAAAACgUSMYBwAAAAAAAAAAAAA0agTjAAAAAAAAAAAAAIBGjWAcAAAAAAAAAAAAANCoEYwDAAAAAAAAAAAAABo1gnEAAAAAAAAAAAAAQKNGMA4AAAAAAAAAAAAAaNQIxgEAAAAAAAAAAAAAjRrBOAAAAAAAAAAAAACgUSMYBwAAAAAAAAAAAAA0agTjAAAAAAAAAAAAAIBGjWAcAAAAAAAAAAAAANCoEYwDAAAAAAAAAAAAABo1gnEAAAAAAAAAAAAAQKPmYnYBAAAA1WF3GPotPlVJmXkK9fXQRW0DZbNazC4LAAAAAAAAABoFu8PQr3HHte9wqtpl2dQvKrhRXIMlGAcAAA3GN9sTNHPJTiWk5zmPRfh7aPrIzhrWNcLEygAAAAAAAACg4St/DTa+0VyDpZU6AABoEL7ZnqB75m0qE4pL0rH0PN0zb5O+2Z5gUmUAAAAAAAAA0PA19muwBOMAAKDeszsMzVyyU0YFj5Ucm7lkp+yOis4AAAAAAAAAAJxJU7gGSzAOAADqvd/iU8t9S7E0Q1JCep5+i0+tu6IAAAAAAAAAoJFoCtdgCcYBAEC9l5RZ+R9k53IeAAAAAAAAAOCUpnANlmAcAADUe34erlU6L9TXo5YrAQAAAAAAAIDGp6rXVhvyNViCcQAAUK8dScvVP77ZfdbzIvw9dFHbwDqoCAAAAAAAAAAal4vaBirCv/LQ26KGfw2WYBwAANRbGw+c0LX/Xq3dxzLPeu7lHUJks1rqoCoAAAAAAAAAaFxsVoumj+xc4WMlV12nj+zcoK/BEowDAIB66YvNRzT23V+UklUgSWoT5KXpIztX+q3FTzYc1qo9SXVZIgAAAAAAAAA0GsO6RmhIp9Byx8P9PfTWuN4a1jXChKpqjovZBQAAAJTmcBh6ecUezVoZ6zw2ICpIb43rrQAvN902oI1+i09VUmaeQn099MOeRL37U7zsDkP3LdisT+8ZoI7hfia+AwAAAAAAAABomBzGqdt/vqKV+kRHqF9UcINeKV6CYBwAANQbOQVFevjjrfpmxzHnsbEXtdIz13aVq6240Y3NatGA6CDn4/3aBurQ8Vx9s+OYsvKLNHnuBn0+9WKF+la+Hw4AAAAAAAAAoLy45CxJkrebTTd0D1FYWJCsjSAUl2ilDgAA6omE9Fzd+PY6ZyhutUh/+1Nn/f26bs5QvCJWq0Wv3NRT3Vv6S5KOpOXqzv9uVG6BvU7qBgAAAAAAAIDGIL/IroOpOZKktiHeslgaRyBegmAcAACYbsuhNF3z7zXacTRDkuTr7qL/TLxQtw9sW6U/vjzdbHrvtr5qfnL/8a2H0vTwoi1ylO77AwAAAAAAAACo1IHjOc5W6tEhPuYWUwsIxgEAgKn+t/Wobpq9TsmZ+ZKk1oFeWnzvxRrUIbRarxPq56H/TLpQPu7FO8Us235ML327p8brBQAAAAAAAIDGKDYpy3k7KtjbxEpqB8E4AAAwhcNh6P9W/KEHPtqs/CKHJOmitoH6Yuolah/me06v2THcT2/c0kslW968tSpWi9YfqqmSAQAAAAAAAKDRikvJdt6ODiEYBwAAOG+5BXbd/9Fmvf79XuexMX1bat7kfgr0djuv176iQ6hmXtPFef+vn2/T2n0p5/WaAAAAAAAAANDYlVkx3tRbqc+YMUMWi6XMfx07dnQ+npeXp6lTpyooKEg+Pj4aPXq0EhMTy7zGwYMHNWLECHl5eSk0NFR/+ctfVFRUVOacVatWqXfv3nJ3d1e7du00d+7cc3+HAACgXjmWnqcxs9dp6bYESZLFIj01opP+Mbq73Fxq5jt74we00aRL2kiSihyG7p63UftK/VEHAAAAAAAAACgrNrn4GqrFIrUJ8jK5mppX7avPXbp0UUJCgvO/1atXOx976KGHtGTJEn3yySf68ccfdfToUV1//fXOx+12u0aMGKGCggKtXbtWH3zwgebOnau//e1vznPi4+M1YsQIXXHFFdqyZYumTZumO+64Q8uXLz/PtwoAAMy27XC6rp21WtuOpEuSvN1seu+2vrrj0ihZLJYa/VlPjeiswR2L9ynPyCvS7XPX63hWfo3+DAAAAAAAAABoDAzDUFxycSv1ls085eFqM7mimudS7Se4uCg8PLzc8fT0dL3//vtasGCBrrzySknSnDlz1KlTJ/3yyy/q37+/vv32W+3cuVPfffedwsLC1LNnTz377LN67LHHNGPGDLm5uentt99W27Zt9fLLL0uSOnXqpNWrV+uVV15RTExMpXXl5+crP//Uxe6MjAxJksPhkMPhqO7bRD3ncDhkGAa/W9QqxhnqSlMZa19vS9Ajn/6uvMLi99mymafeHd9HHcJ9a+W9WyS9elMP3fTOL9qZkKmDqTma8uFGzbv9Qrk3wj/qzqapjDOYj7GGutCQxllDqBEAAAAAgOTMfGXmF3f5jm6EbdSlcwjG9+7dq+bNm8vDw0MDBgzQCy+8oNatW2vjxo0qLCzUkCFDnOd27NhRrVu31rp169S/f3+tW7dO3bp1U1hYmPOcmJgY3XPPPdqxY4d69eqldevWlXmNknOmTZt2xrpeeOEFzZw5s9zx5ORk5eXlVfdtop5zOBxKT0+XYRiyWmum7S5wOsYZ6kpjH2uGYWjOb8f0zrqjzmPdm3vrxT9Fq5k1V0lJubX681+8uo0mL9yt5OxCbTxwQg8u2KCZw9rU+Ar1+q6xjzPUH4w11IWGNM4yMzPNLgEAAAAAgLPal3xqK0qCcUn9+vXT3Llz1aFDByUkJGjmzJm69NJLtX37dh07dkxubm4KCAgo85ywsDAdO3ZMknTs2LEyoXjJ4yWPnemcjIwM5ebmytPTs8LannjiCT388MPO+xkZGWrVqpVCQkLk5+dXnbeJBsDhcMhisSgkJKTeXwhDw8U4Q11pzGMtr9CuRz/bpq9+T3AeG927hZ4b1UXuLnWzajs0VHp/oq9ueudX5Rba9e2eVHVsEahpQ9rXyc+vLxrzOEP9wlhDXWhI48zDw8PsEgAAAAAAOKvYk23UJSkqxNvESmpPtYLx4cOHO293795d/fr1U2RkpBYtWlRpYF1X3N3d5e7uXu641Wqt9xdKcG4sFgu/X9Q6xhnqSmMca0kZebrzw43aeihNkmSxSI8N66i7Lqv5/cTPpnurZnrt5p66a95GGYb0+g/71DbEW9f1almndZitMY4z1E+MNdSFhjLO6nt9AAAAAABIUlwTWDF+XjP0gIAAXXDBBdq3b5/Cw8NVUFCgtLS0MuckJiY69yQPDw9XYmJiucdLHjvTOX5+fqaH7wAAoGq2H0nXtbPWOENxLzebZo/ro7svjzathfnQLuF68upOzvuPfbpNv8WnmlILAAAAAAAAANQnpVeME4xXICsrS7GxsYqIiFCfPn3k6uqq77//3vn4nj17dPDgQQ0YMECSNGDAAG3btk1JSUnOc1asWCE/Pz917tzZeU7p1yg5p+Q1AABA/fbN9mO68e11SkjPkyS1CPDUp3dfrKFdwk2uTJo8sK1u7ddaklRgd+iuDzdof0r2WZ4FAAAAAAAAAI1bbFLxinFfDxcF+7iZXE3tqFYw/sgjj+jHH3/U/v37tXbtWl133XWy2WwaO3as/P39NXnyZD388MNauXKlNm7cqEmTJmnAgAHq37+/JGno0KHq3Lmzxo8fr61bt2r58uV66qmnNHXqVGcb9LvvvltxcXF69NFHtXv3br355ptatGiRHnrooZp/9wAAoMYYhqFZK/fp7nkblVtolyT1bh2gL6Zeos7N/UyurpjFYtGMa7ro0vbBkqQTOYW6fe56peUUmFwZAAAAAAAAAJgjt8Cuo+m5kopXi5vV9bO2VSsYP3z4sMaOHasOHTpozJgxCgoK0i+//KKQkBBJ0iuvvKI//elPGj16tC677DKFh4dr8eLFzufbbDZ99dVXstlsGjBggMaNG6fbbrtNzzzzjPOctm3baunSpVqxYoV69Oihl19+We+9955iYmJq6C0DAICalldo18OLtuql5Xucx0b1bK4Fd/ZXiK+7iZWV52qzatatvXVBWHE7oLiUbN09b6MKihwmVwYAAAAAAAAAdS8+JVuGUXy7sbZRlySX6py8cOHCMz7u4eGhWbNmadasWZWeExkZqa+//vqMrzNo0CBt3ry5OqUBAACTJGfm664PN2jTwTTnsb/EdNC9g8zbT/xs/Dxc9f6EC3Xdm2uUklWgX+JS9dfPt+mlG7rX25oBAAAAAAAAoDbEJmc5b0eHeptYSe06rz3GAQBA07YrIUOjZq1xhuKerja9Pa63pl7Rrt4HzK0CvfTubX3l7lL859CnGw/rzVWxJlcFAAAAAAAAAHWrdDAeFdx4V4wTjAMAgHOyYmeiRr+1VkfSiveeifD30Cd3D9CwrhEmV1Z1vVo30/+N6em8/9LyPVr6e4J5BQEAAAAAAABAHYtLznbebseKcQAAgGKGYejtH2M15cMNyimwS5J6tArQl1MvUdcW/iZXV30jukfoLzEdnPcfXrRFmw6eMLEiAAAAAAAAAKg7JSvGbVaLWgcSjAMAACi/yK6/fPq7Xly2W4ZRfGxkj+b6eEp/hfp5mFvcebh3ULRu7NNSkpRf5NCU/27QodQck6sCAAAAAAAAgNrlcBjOFeOtA73k5tJ44+PG+84AAECNOp6Vr3Hv/apPNx52Hnv4qgv0+s095eFqM7Gy82exWPT8dd3UPypQkpSSVaDb565XRl6hyZUBAAAAAAAAQO05lpGn3MLizqDRIY13tbhEMA4AAKpgz7FMXTtrjdbvL24x7uFq1axbeuuBwe1lsVhMrq5muLlY9fa4PooKLv7jb29SlqbO36RCu8PkygAAAAAAAACgdpS0UZek6BAfEyupfQTjAADgjH7Ynajr31yjwydyJUlhfu5adNcAjegeYXJlNS/Ay03/mXihmnm5SpJ+3pui6f/bIaOkbzwAAAAAAAAANCKxSQTjAACgiTMMQ+/9HKfJH2xQdkFxK51uLfz15dSB6t4ywNzialGbYG+9c1tfudmK/0xa8OtBvb863uSqAAAAAAAAAKDmxZ7cX1ySomilDgAAmpqCIoce/2ybnlu6SyWLpUd0i9CiuwYo3N/D3OLqwIVtAvXPG7o77z//9S59u+OYiRUBAAAAAAAAQM2LS2HFOAAAaKJSsws07v1f9fGGQ85jDw5urzfG9pKnm83EyurWqF4t9ODg9pIkw5AeXLhF2w6nm1wVAAAAAAAAANSc2KTiFeOB3m5q5u1mcjW1i2AcAAA47U3M1KhZa/RbfKokyc3FqtfH9tJDV10gq9VicnV1b9qQ9rq2Z3NJUm6hXZM/WK+E9FyTqwIAAAAAAACA85eVX6RjGXmSpKjgxt1GXSIYBwAAJ63ak6Tr31yrg6k5kqQQX3ctumuArunR3OTKzGOxWPSP0d3VN7KZJCkpM1+3z92grPwikysDAAAAAAAAgPMTX2p/8cbeRl0iGAcAoMkzDENz1sTr9rnrlXky8O3S3E//u+8S9WwVYG5x9YCHq02zx/dR60AvSdKuhAw98NFm2R2GyZUBAAAAAAAAwLmLTS61v3goK8YBAEAjVmh36K+fb9fMJTtVkvMO6xKuT+4eoAh/T3OLq0eCfNz1n4kXys/DRZL0w+4kPbd0p8lVAQAAAAAAAMC5Kx2MRwWzYhwAADRSaTkFuu393/TRbwedx+67op3evLW3vNxcTKysfmoX6qO3x/WRy8m91ues2a//rttvblEAAAAAAAAAcI7iSrdSDyUYBwAAjVBscpZGzVqjdXHHJUluLla9elNPPRLTQdaTwS/Ku7hdsP5+XTfn/Rn/26GVu5NMrAgAAAAAAAAAzk3JinFXm0WtmjX+DqIE4wAANDE/703WqFlrtP94jiQp2MdNH93ZX6N6tTC5soZhzIWtdM+gaEmSw5DuW7BJuxIyTK4KAAAAAAAAAKrO7jAUl1K8YrxNkLdcbI0/Nm787xAAADj9d91+TZyzXpl5RZKkjuG++mLqJeoT2czkyhqWvwztoOFdwyVJ2QV2TZ67XkkZeSZXBQAAAAAAAABVc+RErgqKHJKkqBBvk6upGwTjAAA0AUV2h57+Yrv+9uUO2R2GJGlIpzB9ds/FatnMy+TqGh6r1aL/G9NTPVoFSJKOpufpjv9uUE5BkbmFAQAAAAAAAEAVxKZkOW9HhzT+/cUlgnEAABq99JxCTZyzXh/+csB57O7Lo/XO+D7ydncxsbKGzdPNpndv66MWAcV77/x+OF0PfbxFjpNfPAAAAAAAAACA+io2iWAcAAA0IvEp2bruzTVavS9FkuRms+pfN/bQ48M7ymq1mFxdwxfq66H/TLxQPie/YLB8R6L+sXy3yVUBAAAAAAAAwJnFJmc7b9NKHQAANGhr96Vo1Kw1iksp/gMnyNtNC+7spxv6tDS5ssalQ7ivZt3aW7aTXzSY/WOcPvrtoMlVAQAAAAAAAEDl4pJPrRiPYsU4AABoqOb/ekC3/ec3pecWSpI6hPnqi6mXqG+bQJMra5wuvyBEM67p4rz/9BfbtXpviokVAQAAAAAAAEDlSlaMh/i6y9/T1eRq6gbBOAAAjUiR3aEZ/9uhJz/frqKTe11f2TFUn94zQK0CvUyurnEb3z9St1/SVpJU5DB0z/yN2puYaXJVAAAAAAAAAFBWek6hUrLyJUnRTaSNukQwDgBAo5GRV6jbP9iguWv3O49NuSxK797WV74eTeMbf2Z7ckQnDekUKknKzCvS7R+sd/6BCQAAAAAAAAD1QWxK02ujLhGMAwDQKBw4nq3r31yrn/5IliS52iz65+ju+uvVnZx7X6P22awWvXZzL3Vp7idJOpSaqyn/3aC8QrvJlQEAAAAAAABAsbiTbdQlKZpgHAAANBS/xB3XtbPWaF9S8bf8mnm5at7kfhpzYSuTK2uavN1d9P6ECxXm5y5J2nQwTX/59Hc5Tra2BwAAAAAAAAAzxSafWjFOK3UAANAgfLz+oMa996vScgolSe1DffTl1IHqFxVkcmVNW7i/h96fcKE8XW2SpCVbj+rV7/4wuSoAAAAAAAAAkGKTSgfjrBgHAAD1mN1h6Lmvduqxz7ap6ORK5MsvCNFn916s1kFeJlcHSerawl+vj+0ly8lO9q//sE+fbTxsblEAAAAAAAAAmry4lOJW6u4uVjUP8DS5mrpDMA4AQAOTmVeoOz5Yr/dWxzuP3X5JW70/oa/8PFxNrAynu6pzmJ4a0dl5//HFv+vXuOMmVgQAaKx++uknjRw5Us2bN5fFYtEXX3xxxvMXL16sq666SiEhIfLz89OAAQO0fPnyuikWAAAAAGCaQrtDB44XB+Ntg71ls1pMrqjuEIwDANCAHErN0ei31mrlnmRJkovVor9f101/G9lZLjb+33p9dPslbTSuf2tJUqHd0F3zNir+5DcyAQCoKdnZ2erRo4dmzZpVpfN/+uknXXXVVfr666+1ceNGXXHFFRo5cqQ2b95cy5UCAAAAAMx0KDVHhfbiLqRNqY26JLmYXQAAAKia9ftTddeHG5WaXSBJ8vd01Vvjeuvi6GCTK8OZWCwWzRjZRYdSc/XjH8lKyynU7XPXa/E9F6uZt5vZ5QEAGonhw4dr+PDhVT7/1VdfLXP/73//u7788kstWbJEvXr1qvA5+fn5ys/Pd97PyMiQJDkcDjkcjuoXjXrN4XDIMAx+t6hVjDPUFcYa6gLjDHWFsYbztS8p03k7Ktir0rHUUMZadeojGAcAoAH4ZMMh/fXzbc5v8kWFeOv9CReqbbC3yZWhKlxsVv37ll664a112pOYqfiUbN01b6PmTe4nNxdW+gMAzOdwOJSZmanAwMBKz3nhhRc0c+bMcseTk5OVl5dXm+XBBA6HQ+np6TIMQ1Yrf6+gdjDOUFcYa6gLjDPUFcYaztfv8YnO28HuDiUlJVV4XkMZa5mZmWc/6SSCcQAA6jG7w9A/v9mt2T/FOY9d2j5Y/76lt/w92U+8IfH1cNX7E/tq1Ky1SsnK12/xqXp88e96+cYesliazj4+AID66V//+peysrI0ZsyYSs954okn9PDDDzvvZ2RkqFWrVs59ytG4OBwOWSwWhYSE1OuLYGjYGGeoK4w11AXGGeoKYw3nKzH3VDDeKzpCoaH+FZ7XUMaah4dHlc8lGAcAoJ7Kyi/StIVb9N2uU3+oTBgQqaf/xH7iDVXLZl56b0Jf3TR7nfKLHFq86Yiigr1135XtzS4NANCELViwQDNnztSXX36p0NDQSs9zd3eXu7t7ueNWq7VeXyTBubNYLPx+UesYZ6grjDXUBcYZ6gpjDecjLiXbeTs61PeM46ghjLXq1FZ/3wUAAE3Y4RM5uuGttc5Q3Ga16NlRXTXz2q6E4g1cz1YBeuWmns77//r2Dy3ZetS8ggAATdrChQt1xx13aNGiRRoyZIjZ5QAAAAAAallccpYkKcLfQ97uTWsNNVfWAQCoZzYeSNWoWWu0+1jx3ih+Hi76YNJFGt8/0uTKUFOu7hahx4Z1dN7/8ydbtfHACRMrAgA0RR999JEmTZqkjz76SCNGjDC7HAAAAABALUvNLtCJnEJJUnSIj8nV1L2m9TUAAADqGbvD0K9xx7XvcKraZdl0NC1Pf/18uwrsDklS22BvvTehb5P8I6Wxu/vyKMWnZGnRhsMqKHJoyn836Iupl6hVoJfZpQEAGqCsrCzt27fPeT8+Pl5btmxRYGCgWrdurSeeeEJHjhzRf//7X0nF7dMnTJig1157Tf369dOxY8ckSZ6envL3r3h/OQAAAABAwxZ7crW4JEWFeJtYiTkIxgEAMMk32xM0c8lOJaTnnTwSX+bxS9oFadYtvRXg5Vb3xaHWWSwWPTeqmw6l5mpd3HEdzy7QpLnr9dk9F8vf09Xs8gAADcyGDRt0xRVXOO8//PDDkqQJEyZo7ty5SkhI0MGDB52Pv/POOyoqKtLUqVM1depU5/GS8wEAAAAAjU9cqWC8KS7GIhgHAMAE32xP0D3zNsmo5PFL2wfrPxMvlCv7iTdqbi5WvT2uj657a43ikrO1LylLU+dv0pxJ/O4BANUzaNAgGUZlf1moXNi9atWq2i0IAAAAAFDvxCZnO283xWCcK64AANQxu8PQzCU7Kw3FJWlfUpasFkud1QTz+Hu5as7ECxXoXdwZYPW+FP3ty+1nDDcAAAAAAAAAoLpik0qtGA9teq3UCcYBAKhjv8WnlmqfXrGE9Dz9Fp9aRxXBbJFB3npnfB+5nVwl/tFvh/Tuz3EmVwUAAAAAAACgMSnZY9zLzaZwPw+Tq6l7BOMAANSxpMwzh+LVPQ+NQ982gXrpxu7O+y8s261vth8zsSIAAAAAAAAAjUV+kV2HTuRKkqJCvGVpgh1LCcYBAKhjob5V+yZeVc9D43FtzxaaNqS9JMkwpGkfb9bvh9PMLQoAAAAAAABAg3fweI7sjuLtG5vi/uISwTgAAHXuoraBivCvPPS2SIrw99BFbQPrrijUGw8Obq/rerWQJOUVOjT5gw06mpZrclUAAAAAAAAAGrKSNuqSFBVMMA4AAOqAzWrR9JGdK3yspHnN9JGdZbM2vVY2kCwWi14c3U0XtmkmSUrOzNftc9crK7/I5MoAAAAAAAAANFSxydnO29Gh3iZWYh6CcQAATDCsa4QCvdzKHQ/399Bb43prWNcIE6pCfeHuYtPs8X0VGeQlSdp9LFP3LdikIrvD5MoAAAAAAAAANESlV4w31VbqLmYXAABAU3QsPU+pOQWSpE7hvhrbM1jtWoaoX1QwK8UhSQr0dtN/Jl6o62atUUZekVbtSdZzS3dpxjVdzC4NAAAAAAAAQANTsmLcYpHaBrNiHAAA1JFNB084b1/RMVRDOwaqf1QQoTjKiA7x0dvj+8jl5LiYu3a/5q6JN7kqAAAAAAAAAA2JYRiKSypeMd4iwFMerjaTKzIHwTgAACbYsP9UMN67dYB5haDeuzg6WH+/vpvz/jNf7dQPuxNNrAgAAAAAAABAQ5Kcla/M/CJJTbeNukQwDgCAKTaWWjHei2AcZzGmbyvdOyhakuQwpPsXbNbOoxkmVwUAAAAAAACgIYhNynbeJhgHAAB1Jq/Qrh1H0iVJ0SHeaublZnJFaAgeGdpBI7pFSJKyC+ya/MF6JWbkmVwVAAAAAAAAgPouNjnLeTsqpGnuLy4RjAMAUOe2HkpTkcOQJPWNDDS5GjQUVqtFL4/poZ6tAiRJCel5mvzBeuUUFJlbWCNldxhaF3tcX245onWxx2U/+W8WAAAAAAAAaGjiklkxLkkuZhcAAEBTU7qNep/IZiZWgobGw9Wmd2/rq1Gz1uhIWq62H8nQgwu36O1xfWSzWswur9H4ZnuCZi7ZqYT0UyvyI/w9NH1kZw3rGmFiZQAAAAAAAED1lV4xHh3KinEAAFBHNh04FYz3JhhHNYX4umvOpAvl6178/cYVOxP1j292m1xV4/HN9gTdM29TmVBcko6l5+meeZv0zfYEkyoDAAAAAAAAzk1JMO7r7qIQH3eTqzEPwTgAAHXIMAxtPBmMB3i5KroJ7+eCc3dBmK9m3drbuUr8nZ/itODXgyZX1fDZHYZmLtmpipqmlxybuWQnbdUBAAAAAADQYOQV2nUkLVeSFBXqI4ul6XaeJBgHAKAOxaVk60ROoSSpT+tmTfqPEJyfyy4I0TPXdnHef/rL7fp5b7KJFTVMdoehQ6k5WrMvRS98vavcSvHSDBXv7f5bfGrdFQgAAAAAAACch/iUbBkn13k09YVa7DEOAEAd2kgbddSgW/tFKj45W++tjpfdYejeeZv02b0X64IwX7NLq1dyC+w6mJqjA8ezT/7fHB1IzdGh1BwdPpGjQnv1VoAnZVYengMAAAAAAAD1SZn9xUN8TKzEfATjAADUoY37TwXjfQnGUQOeuLqT9h/P0Xe7EpWZX6RJc9bri6mXKMS36ewVZBiGUrMLdCA1RwePlwTf2Tp4PEcHU3OUlJlfoz8v1NejRl8PAAAAAAAAqC2xSdnO26wYBwAAdWbjweJg3MVqUfeWAeYWg0bBZrXo9bE9dePb67TjaIaOpOVqyocb9NGd/eXhajO7vBpTZHcoIT2vTOhdeuV3Vn5RtV/Ty82m1oFeigzyUutAL7UM9NJrK/YqNaeg0ud4u9t0YRu+1AIAAAAAAICGIS6FFeMlCMYBAKgjaTkF2pdU/EdIl+Z+8nRrPKElzOXl5qL3J1yoUbPW6FhGnjYfTNOfP9mqN27uJau14exjn1NQ5Gx1fvBkAH7g5KrvIydyVeSoXstzSQr2cVdkkJciA73U+mQAXhyEeyvYx00WS9nPJ8zXXffM2ySpeE/x02Xn2/XCst16akSncs8FAAAAAAAA6puSVuo2q0Wtg7xMrsZcBOMAANSRTQdPtVHvExloYiVojML9PfT+xL668e11yimwa+nvCWob5K1HYjqYXZqTYRhKySrQwdQcHSwJvU+u+j5wPEcpWdVvee5itahFM09n4B0Z6K1WpVaBe7tX78/dYV0j9Na43pq5ZKcS0k/tJe7v6ar03EJJ0vsn93SfPrIz4TgAAAAAAADqLYfDcLZSb9XMU+4uTXuxFsE4AAB1ZOOB0sE4rZhR87o099cbY3vpzv9ukMOQ/r1ynyKDvHRj31Z1VkOR3aEjabnOld7FK8CLQ/BDqTnKLrBX+zW93WxqHeStyJLAu2Tld6C3mgd4yMVmrdH3MKxrhK7qHK7f4lOVlJmnUF8PXdQ2UJ9tPKzHFv8uw5Dmrt2vIodDz1zTtUGtygcAAAAAAEDTcSwjT7mFxdfjmnobdYlgHACAOkMwjrowuFOYnhrRWc98tVOS9NfPt6m5v6csFkP7DqeqXZZN/aKCZTuPMDc7v+hk8J19qvX5yf97JC1X9nNoeR7i6+5sdx4Z6K3IIC/nyu8g7/Itz2ubzWrRgOigMsfGXNhKNqtFj3y6VYYhzfvloOwOQ8+P6kY4DgAAAAAAgHonLjnbeTs6lGCcYBwAgDpQaHdo66F0SVKLAE+F+3uYXBEas0mXtNH+49n677oDKrQbGvf+r6X2y45XhL+Hpo/srGFdIyp8vmEYSs7KL25zfrLV+aGTK78PpuYoJaug2jW5WC1q2cyz7MrvQC9FBnmrVaCnvNwaxp+lo/u0lM1q0cOLtshhSB/9dkhFdkMvju5+Xl82AAAAAAAAAGpayf7ikhQV7G1iJfVDw7gCCQBAA7crIcPZsobV4qhtFotFf/tTZ23Yf0I7EzJ0+vrtY+l5umfeJs28posig7118GSr85LW5wdTc5RzDi3PfdxdnHt9l1753TrQSxH+Nd/y3CyjerWQzWrRtI+3yO4w9MnGw7Ibhl66oQfhOAAAAAAAAOqN0sE4K8YJxgEAqBO0UUdds1gsOp6dX+FjJUH53/63o9qvG+rrfjLsLg69S6/8bublWuctz80yskdz2awWPfDRZhU5DC3edER2h6GXb+zRaL4AAAAAAAAAgIatTCt19hgnGAcAoC4QjKOu/RafqsSMioPxM3G1WdSymdepld8nQ+/IIC+1auYlTzdbLVTbMF3dLUJWi0X3LdikIoehL7ccld1h6NWbehKOAwAAAAAAwHQlK8abebkq0NvN5GrMRzAOAEAdKAnGvdxs6hjua3I1aAqSMvOqdN7gTqEa0ilMkYHF7c8j/D1pB14Nw7qG661xfXTv/I0qtBv66vcEOQxDr93cS66E4wAAAAAAADBJdn6REtKLrxFGsVpcksTVOgAAatnRtFznHyA9WwWwkhR1ItTXo0rn3TEwSmMvaq2L2wWrZTMvQvFzcFXnMM0e30duJ/9tf73tmO5bsEkFRQ6TKwMAAAAAAEBTFZ9Suo26t4mV1B9cmQcAoJaVbqPelzbqqCMXtQ1UhL+HKou5LZIi/D10UdvAuiyr0bqyY5jeua2P3FyK/7xeviNR987fqPwiu8mVAQAAAAAAoCkqaaMusb94CYJxAABqWelgvDfBOOqIzWrR9JGdJalcOF5yf/rIzqwQr0GDOoTq/Ql95X4yHP9uV5Lu/nCj8goJxwEAAAAAAFC3YpNOBeO0Ui9GMA4AQC0rHYz3ak0wjrozrGuE3hrXW+H+Zduqh/t76K1xvTWsa4RJlTVel7YP0ZyJF8rDtfjP7JV7knUX4TgAAAAAAADqWGwyrdRP52J2AQAANGY5BUXamZAhSbogzEf+nq4mV4SmZljXCF3VOVy/xqVo3+FktWsZon5RwawUr0UXtwvW3EkX6fa565VTYNePfyTrzv9u0Dvj+8rTzWZ2eQAAAAAAAGgCSlqpu9osahXoZXI19QMrxgEAqEVbDqXJ7jAkSX0i2csZ5rBZLeofFaShHQPVPyqIULwO9I8K0txJF8n7ZBD+894UTf5gvXIKikyuDAAAAAAAAI2d3WEoPqV4xXhkkLdcbUTCEsE4AAC1alOpNup92F8caFIuahuo/06+SD7uxU2a1sYe16Q565WdTzgOAAAAAACA2nM0LVf5RQ5JUlQwbdRLEIwDAFCLNhKMA01an8hAfTj5Ivl6FIfjv8anauKc35RFOA4AAAAAAIBaUtJGXZKiQ31MrKR+IRgHAKCWOByGMxgP8nZTmyD2cQGaol6tm2n+Hf3kdzIcX7//hG57/1dl5hWaXBkAAAAAAAAao9jkbOft6BCC8RIE4wAA1JLY5Cxl5BWvCu0d2UwWC/s6A01V95YBWnBnfwV4uUqSNh1M07j3f1N6LuE4AAAAAAAAalbpFeNRIbRSL0EwDgBALaGNOoDSurbw14I7+qvZyXB866E0jXvvV6XlFJhcGQAAAAAAABqT2KRSrdSDWTFegmAcAIBasqFUMN6XYByApM7N/fTRlP4K8naTJG07kq5b3/tVJ7IJxwEAAAAAAFAz4lKKW6kH+7jL/+QiDRCMAwBQazadDMZdbRZ1beFvcjUA6ouO4X5aOKW/gn3cJUk7jmZo7Lu/6HhWvsmVAQAAAAAAoKFLzy1UcmbxdSbaqJdFMA4AQC1IzS5wfiuvawt/ebjaTK4IQH3SPsxXC6f0V6hvcTi++1imbnn3V6UQjgMAAAAAAOA8xJXaXzw6hDbqpRGMAwBQCzbRRh3AWbQL9dHCKf0V5lccju9JzNTYd35RUmaeyZUBAAAAAACgoYpLznbejmbFeBkE4wAA1ILS+4v3IRgHUImoEB99PGWAIvw9JEl7k7J08zu/KDGDcBwAAAAAAADVF1t6xXgoK8ZLIxgHAKAWlF4x3ptgHMAZtAn21sdTBqhFgKek4m/13vzOLzqWTjgOAAAAAACA6ikTjAcTjJdGMA4AQA0rKHJo6+E0SVLrQC+F+nqYWxCAeq91kJcWTumvls2Kw/H4lGzd9M46HU3LNbkyAAAAAAAANCSxJ1upu7lY1eLktSYUIxgHAKCG7TiarvwihyTaqAOoulaBXvr4rgFqHeglSTpwPEc3vbNOh0/kmFwZAAAAAAAAGoIiu0MHjhcH41HB3rJZLSZXVL8QjAMAUMM20kYdwDlqEeCpj+/qr7bB3pKkQ6m5umn2LzqUSjgOAAAAAACAMzt0IleFdkOSFBXibXI19Q/BOAAANWzTwVPBeF+CcQDVFOHvqYVT+jsnL0fScnXT7HXOb/sCAAAAAAAAFYlNKrW/eAj7i5+OYBwAgBpkGIY27C8Oxn3cXXRBmK/JFQFoiML8PLRwSn+1Cy2ewBxNz9NNs39RfArhOAAAAAAAACoWl0IwfiYE4wAA1KDDJ3KVlJkvSerVOoA9XACcs1Df4nC8w8kv2BzLyNNNs9cpNjnrLM8EAAAAAABAUxSbdGpRBcF4eQTjAADUoNJt1PvQRh3AeQr2cdeCO/upY3hxOJ6Uma+bZv+ivYmZJlcGAAAAAACA+qb0goq27DFeDsE4AAA1qKSNukQwDqBmBPm466M7+6tzhJ8kKSUrX2Pf/UV7jhGOAwAAAAAA4JSSYDzcz0M+7i4mV1P/EIwDAFCDNh4oDsatFqlnqwBziwHQaDTzdtOCO/upWwt/SVJKVoHGvvuLdh7NMLkyAAAAAAAA1Aep2QU6kVMoSYoOZbV4RQjGAQCoIVn5Rdp9rDik6hDuJ18PV5MrAtCYBHi5ad4d/dTj5JduUrMLdMt7v2j7kXRzCwMAAAAAAIDp4kq1UY8KZn/xihCMAwBQQ7YcTJPDKL7dJzLA1FoANE7+nq76cPJF6tU6QJKUllOoW979Rb8fTjO1LgAAAAAAAJir9P7i0ewvXiGCcQAAakhJG3WJ/cUB1B4/D1f99/aL1Pfk/85k5BXp1vd+1ZZDaeYWBgAAAAAAANPEJWc7b0eHsmK8IgTjAADUkI0HSwXjrQNNrARAY+fr4aoPbr9IF7Ut/t+azLwijX/v1zJf0AEAAAAAAEDTUXrFeFQIwXhFCMYBAKgBdoehzScDqRBfd7UK9DS5IgCNnbe7i+ZOulADooIkSZn5Rbrt/V+1fn+qyZUBAAAAAACgrsWeXDHu6WpThJ+HydXUTwTjAADUgL1JmcrML5Ik9WndTBaLxeSKADQFXm4u+s/ECzWwXbAkKbvArgn/+U2/xh03uTIAAAAAAADUlYIihw6m5kiSokK8ZbVyfboiBOMAANQA9hcHYBZPN5vem9BXl10QIknKKbBr4pz1WhubYnJlAAAAAAAAqAsHU7NldxiSpGjaqFeKYBwAgBpQJhhvQzAOoG55uNr0zvg+uqJDcTieW2jX7XPXa/VewnEAAAAAAIDGbl9StvN2VIi3iZXUbwTjAADUgJJg3M3Fqi7N/UyuBkBT5OFq09vj+2hIp1BJUl6hQ5M/WK8f/0g2uTIAAAAAAADUptjkLOdtVoxXjmAcAIDzlJyZrwPHi/dv6d7CX+4uNpMrAtBUubvY9OatfTS0c5gkKb/IoTv/u0ErdyeZXBkAAAAAAABqS1zyqRXjBOOVIxgHAOA8bTpIG3UA9Yebi1Wzbu2t4V3DJUkFRQ7d9eFGfbcz0eTKAAAAAAAAUBtKrxhvG0wr9coQjAMAcJ7K7C/emmAcgPlcbVa9PraX/tQ9QpJUYHfonvkbtXzHMZMrAwAAAAAAQE0yDMMZjLcI8JSnGx1NK0MwDgDAeSodjPeOJBgHUD+42qx69aaeurZnc0lSod3Q1PmbtGxbgsmVAQAAAAAAoKakZBUoM69IkhQdShv1MyEYBwDgPOQX2bXtcLqk4hY1wT7uJlcEAKe42Kz6vzE9dX2vFpKkIoeh+z7arK9+P2pyZQAAAAAAAKgJpduoR4fQRv1MCMYBADgP24+kq8DukCT1po06gHrIZrXopRt76MY+LSVJdoehBz7arC+3HDG5MgAAAAAAAJyv0sF4VAgrxs/kvILxF198URaLRdOmTXMey8vL09SpUxUUFCQfHx+NHj1aiYmJZZ538OBBjRgxQl5eXgoNDdVf/vIXFRUVlTln1apV6t27t9zd3dWuXTvNnTv3fEoFAKBWlNlfnDbqAOopm9Wif4zurpsvbCVJchjSQx9v0eJNh02uDAAAAAAAAOcjNinbeZsV42d2zsH4+vXrNXv2bHXv3r3M8YceekhLlizRJ598oh9//FFHjx7V9ddf73zcbrdrxIgRKigo0Nq1a/XBBx9o7ty5+tvf/uY8Jz4+XiNGjNAVV1yhLVu2aNq0abrjjju0fPnycy0XAIBaUToY79uGYBxA/WW1WvT367rp1n6tJRWH43/+ZKsWbThkcmUAAAAAAAA4V3Epp1aMt2PF+Bm5nMuTsrKydOutt+rdd9/Vc8895zyenp6u999/XwsWLNCVV14pSZozZ446deqkX375Rf3799e3336rnTt36rvvvlNYWJh69uypZ599Vo899phmzJghNzc3vf3222rbtq1efvllSVKnTp20evVqvfLKK4qJiamwpvz8fOXn5zvvZ2RkSJIcDoccDse5vE3UYw6HQ4Zh8LtFrWKc4WwMw9CG/cXBuK+Hi6KCvM5pvDDWUBcYZyjxzDWdZbNY9N9fDsgwpEc//V1FdodzNfn5YqyhLjSkcdYQagQAAAAANFwlrdR93F0U4utucjX12zkF41OnTtWIESM0ZMiQMsH4xo0bVVhYqCFDhjiPdezYUa1bt9a6devUv39/rVu3Tt26dVNYWJjznJiYGN1zzz3asWOHevXqpXXr1pV5jZJzSrdsP90LL7ygmTNnljuenJysvLy8c3mbqMccDofS09NlGIas1vPaEQCoFOMMZ3M4LV/HswskSV3CvJSSknxOr8NYQ11gnKG0e/oFKT8vVx9vSZIk/fXz7UpLz9D13UPO+7UZa6gLDWmcZWZmml0CAAAAAKCRyiu06/CJXEnFbdQtFovJFdVv1Q7GFy5cqE2bNmn9+vXlHjt27Jjc3NwUEBBQ5nhYWJiOHTvmPKd0KF7yeMljZzonIyNDubm58vT0LPezn3jiCT388MPO+xkZGWrVqpVCQkLk5+dX3beJes7hcMhisSgkJKTeXwhDw8U4w9msOXLEefvi9mEKDQ09p9dhrKEuMM5wur/fGCo/3z169+d4SdI/fzgoL28f3TYg8rxel7GGutCQxpmHh4fZJQAAAAAAGqn9x7NlGMW3o2mjflbVCsYPHTqkBx98UCtWrKh3k3t3d3e5u5dvD2C1Wuv9hRKcG4vFwu8XtY5xhjPZeDDNebtvm8DzGieMNdQFxhlO99erO8nFZtVbq2IlSTOW7JTdkCYPbHter8tYQ11oKOOsvtcHAAAAAGi4YpOynbejQrxNrKRhqNYMfePGjUpKSlLv3r3l4uIiFxcX/fjjj3r99dfl4uKisLAwFRQUKC0trczzEhMTFR4eLkkKDw9XYmJiucdLHjvTOX5+fhWuFgcAwAybDhTvL26zWtSjVYC5xQDAObBYLHo0poPuv7Kd89izX+3Uuz/FmVgVAAAAAAAAqqJkf3GJFeNVUa1gfPDgwdq2bZu2bNni/K9v37669dZbnbddXV31/fffO5+zZ88eHTx4UAMGDJAkDRgwQNu2bVNSUpLznBUrVsjPz0+dO3d2nlP6NUrOKXkNAADMlpFXqD2JxXuGdorwlbd7tXcnAYB6wWKx6M9DO2jakPbOY89/vcu5ihwAAAAAAAD1U5lgPJRg/GyqdRXf19dXXbt2LXPM29tbQUFBzuOTJ0/Www8/rMDAQPn5+en+++/XgAED1L9/f0nS0KFD1blzZ40fP17//Oc/dezYMT311FOaOnWqsxX63XffrX//+9969NFHdfvtt+uHH37QokWLtHTp0pp4zwAAnLfNB9Oce7f0ad3M3GIAoAZMG3KBbBaLXl7xhyTpH9/slt3h0H1Xtj/LMwEAAAAAAGCGuOTiVupWixQZ5GVyNfVfjS9ve+WVV2S1WjV69Gjl5+crJiZGb775pvNxm82mr776Svfcc48GDBggb29vTZgwQc8884zznLZt22rp0qV66KGH9Nprr6lly5Z67733FBMTU9PlAgBwTjaebKMuSb0jCcYBNA73D24vm82if36zR5L0r2//UJHD0LQhF5hcGQAAAAAAAEozDMO5YrxVoJfcXWwmV1T/nXcwvmrVqjL3PTw8NGvWLM2aNavS50RGRurrr78+4+sOGjRImzdvPt/yAACoFZtKBeN9CMYBNCL3DmonF6tFf/96tyTp1e/2yuEw9NBVF8hisZhcHQAAAAAAACTpWEaecgrskthfvKqqtcc4AACQ7A5Dmw8WB+Phfh5qEeBpckUAULOmXBatp//U2Xn/9R/26aXle2SU7CEBAAAAAAAAU5W0UZek6BBvEytpOAjGAQCopt3HMpR98pt4fSKbsYISQKM0eWBbzbymi/P+m6ti9eKy3YTjAAAAAAAA9UBJG3VJimLFeJUQjAMAUE2b2F8cQBMx4eI2enZUV+f92T/F6bmluwjHgXrop59+0siRI9W8eXNZLBZ98cUXZ33OqlWr1Lt3b7m7u6tdu3aaO3durdcJAAAAAKgZsUmngnFaqVcNwTgAANW0sVQw3pdgHEAjN75/pF64vpvz/vur4zVzyU7CcaCeyc7OVo8ePTRr1qwqnR8fH68RI0boiiuu0JYtWzRt2jTdcccdWr58eS1XCgAAAACoCXEptFKvLhezCwAAoKHZcDIY93C1qnNzP5OrAYDaN/ai1rJZLHps8e8yDGnu2v0qcjj0zDVdZbWynQRQHwwfPlzDhw+v8vlvv/222rZtq5dfflmS1KlTJ61evVqvvPKKYmJiaqtMAAAAAEANKVkxHuDlqkBvN5OraRgIxgEAqIbEjDwdPpErSereMkCuNpqvAGgaxlzYSjarRY98ulWGIc375aDsDkPPj+pGOA40QOvWrdOQIUPKHIuJidG0adMqfU5+fr7y8/Od9zMyMiRJDodDDoejVuqEeRwOhwzD4HeLWsU4Q11hrKEuMM5QVxhrkKTs/CIdTc+TJEUFe8swjBrv7tdQxlp16iMYBwCgGjbRRh1AEza6T0u52Cx66OMtchjSR78dUpHd0Iuju8tGOA40KMeOHVNYWFiZY2FhYcrIyFBubq48PT3LPeeFF17QzJkzyx1PTk5WXl5erdUKczgcDqWnp8swDFmtfBkUtYNxhrrCWENdYJyhrjDWIEm7k3Kct5v72JSUlFTjP6OhjLXMzMwqn0swDgBANWwoFYz3IRgH0ARd27OFrBaLpn28RXaHoU82HpbdMPTSDT0kSb/GHde+w6lql2VTv6hgAnOgEXniiSf08MMPO+9nZGSoVatWCgkJkZ8f28s0Ng6HQxaLRSEhIfX6IhgaNsYZ6gpjDXWBcYa6wliDJP2ScNR5u0vrYIWGhtb4z2goY83Dw6PK5xKMAwBQDRtLBeO9WxOMA2iaRvZoLherRfd/tFlFDkOLNx3RodQcHUrN1bGMklWj8Yrw99D0kZ01rGuEqfUCKC88PFyJiYlljiUmJsrPz6/C1eKS5O7uLnd393LHrVZrvb5IgnNnsVj4/aLWMc5QVxhrqAuMM9QVxhriUk6tGI8O8am1sdAQxlp1aqu/7wIAgHomr9CuHUfTJUnRId5q5u1mckUAYJ7h3SI069becrUVrwhfv/9EqVC82LH0PN0zb5O+2Z5gRokAzmDAgAH6/vvvyxxbsWKFBgwYYFJFAAAAAICqik3Oct6ODvUxsZKGhWAcAIAq+v1wugrthiTaqAOAJMV0Cdessb0rfdw4+X9nLtkpu8Oo9DwA5y8rK0tbtmzRli1bJEnx8fHasmWLDh48KKm4Dfptt93mPP/uu+9WXFycHn30Ue3evVtvvvmmFi1apIceesiM8gEAAAAA1RCXnC1JcrFa1DrQy+RqGg6CcQAAqmgj+4sDQDm+nq5nfNyQlJCep9/iU+umIKCJ2rBhg3r16qVevXpJkh5++GH16tVLf/vb3yRJCQkJzpBcktq2baulS5dqxYoV6tGjh15++WW99957iomJMaV+AAAAAEDVOByG4k6uGI8M8pKrjbi3qthjHACAKiobjAeaWAkA1B9JmXlnP0nS6n3J6tumGZM1oJYMGjRIhlF5Z4a5c+dW+JzNmzfXYlUAAAAAgJp2JC1X+UUOSVJUCG3Uq4NgHACAKjAMQ5sOFgfjAV6uigr2NrkiAKgfQn09qnTerJWx+u+6A7qiQ6iGdA7ToA4h8vM482pzAAAAAAAAlFVmf3GC8WohGAcAoAriU7KVml0gSerdupmsVovJFQFA/XBR20BF+HvoWHqezraLeGZekf639aj+t/WoXG0W9Y8K0pBOYRrSOUwtAjzrpF4AAAAAAICGrGR/cUmKDmEBV3XQxxAAgCpgf3EAqJjNatH0kZ0lSad/Zchy8r/JA9vq2p7N5edx6nu5hXZDP+9N0fT/7dAlL/6gq1/7Wa+s+EPbj6SfsR00AAAAAABAU1Z6xTit1KuHFeMAAFQBwTgAVG5Y1wi9Na63Zi7ZqYT0U3uOh/t7aPrIzhrWNUKSVGh3aH18qr7dmagVOxN1JC3Xee7OhAztTMjQa9/vVYS/h4Z0CtNVncPUPypIbi58nxcAAAAAAEA6vZU6K8arg2AcAIAqKAnGXawW9WgZYG4xAFAPDesaoas6h+vXuBTtO5ysdi1D1C8qWLZSW0+42qy6uF2wLm4XrOkjO2v3sUx9tzNRK3Yl6vfD6c7zEtLz9OEvB/ThLwfk4+6iyzuE6KpOYbqiQ6j8vdiXHAAAAAAANF0lrdSDfdwU4OVmcjUNC8E4AABnkZ5TqL1Jxd/C69LcT55uNpMrAoD6yWYt3jc8yseu0NAgWa2nN1c/xWKxqFOEnzpF+On+we11LD1P3+1K1He7ErV233EV2B2SpKz8Ii39PUFLf0+QzWrRRW0CdVXn4tXkrQK96uqtAQAAAAAAmC4jr1BJmfmSpKhg2qhXF8E4AABnsenQqTbqvWmjDgC1ItzfQ+P6R2pc/0hl5Rfp5z+StWJnon7Yk6S0nEJJkt1haF3cca2LO65nvtqpjuG+zpbr3Vr4nzGIBwAAAAAAaOhKVotLUnQobdSri2AcAICz2Lif/cUBoC75uLtoeLcIDe8WoSK7QxsOnHC2XD9wPMd53u5jmdp9LFP/XrlPYX7uGtwpTFd1CtOA6CB5uNLdAwAAAAAANC6xSaX3F2fFeHURjAMAcBYl+4tLBOMAUNdcbFb1jwpS/6ggPTmik/YlZenbnYlasTNRWw6lOc9LzMjXgl8PasGvB+XlZtNl7UN0VecwXdkxVM282W8LAAAAAAA0fHEpBOPng2AcAIAzKLI7nMFLiwBPRfh7mlsQADRhFotF7cN81T7MV1OvaKekzDx9vytJ3+1M1Op9KcovKt6XPKfArm92HNM3O47JapH6tgnU0M5hGtIpTG2CaTMGAAAAAAAaptikU63Uo0K4xlFdBOMAAJzBroRM5RbaJbG/OADUN6G+Hhp7UWuNvai1cgqK9PPelOJ9yXcnKTW7QJLkMKTf4lP1W3yqnlu6S+1CfXTVyZC8V6sA9iUHAAAAAAANRmxy8YpxN5tVLZt5mVxNw0MwDgDAGWw8kOq83ad1gHmFAADOyMvNRTFdwhXTJVx2h6FNB0/uS74zUXEpp75NvS8pS/uSsvTWqlgF+7hrcMdQXdU5TAPbB7MvOQAAAAAAqLeK7A4dOJ4jSWob7C0bX/avNoJxAADOYOPBNOftvm0CzSsEAFBlNqtFF7YJ1IVtAvXE1Z0Um5ylFTsT9d3ORG08eEKGUXxeSla+Pt5wSB9vOCQPV6suLbUvebCPu7lvAgAAAAAAoJTDJ3JVYC/eRo426ueGYBwAgDPYuL94xbinq00dw31NrgYAcC6iQ3wUfbmP7r48WilZ+fphd5JW7EzUz3uTlVdYPKHMK3RoxckV5haL1Kd1Mw3pHKarOocpOsTH5HcAAAAAAACaupI26pK4VnGOCMYBAKjE0bRcHU3PkyT1bBUgF5vV5IoAAOcr2MddY/q20pi+rZRXaNfqvSn6bleivtuVpJSsfEmSYUgbDpzQhgMn9OKy3YoK9i7el7xzmHq3bkarMgAAAAAAUOfKBOOhrBg/FwTjAABUYtPBE87bfds0M7ESAEBt8HC1acjJwNvhMLTlcJqz5frepFOTzbiUbM3+KU6zf4pToLebrjy5L/ml7YPl5caUCgAAAAAA1L645GznbVaMnxuu4gAAUIkN+08F470jCcYBoDGzWi3q3bqZerdupseGdVR8Sra+35Wob3cmasP+VDlO7kueml2gTzce1qcbD8vdxaqB7YI1pHOYBncKVaivh7lvAgAAAAAANFqlV4y3DWbF+LkgGAcAoBKlV4z3bkUwDgBNSdtgb91xaZTuuDRKJ7ILnPuS/7Q3WTkFdklSfpFD3+9O0ve7kyQVb7tx1cl9yduH+shioeU6AAAAAACoGbEnV4yH+bnL18PV5GoaJoJxAAAqkFNQpB1HMyRJF4T5yN+LPzQAoKlq5u2m0X1aanSflsortGtd7HGt2FXccj0pM9953pZDadpyKE0vLd+jyCAvDelUHJL3jWwmF5u1wte2Owz9Fp+qpMw8hfp66KK2gexhDgAAAAAAyjiRXaDU7AJJtFE/HwTjAABUYOuhdNlP9s3tQxt1AMBJHq42XdExVFd0DNVz13bVtiPpxfuS70rU7mOZzvMOHM/R+6vj9f7qeAV4uerKDqEa0jlMl10QIh/34mnYN9sTNHPJTiWk5zmfF+HvoekjO2tY14g6f28AAAAAAKB+iks51UY9KoQ26ueKYBwAgAqUaaPemmAcAFCe1WpRj1YB6tEqQI/EdNDB4zn6bleiVuxM1G/7U51fsErLKdTizUe0ePMRudmsGhAdpOYBHvrot0PlXvNYep7umbdJb43rTTgOAAAAAAAkSbFJ2c7brBg/dwTjAABUYOOBU8F43zaBJlYCAGgoWgd56faBbXX7wLZKzynUyj1JWrErUT/uSVZWfpEkqcDu0I9/JFf6GoYki6SZS3bqqs7htFUHAAAAAACKLbVinGD83BGMAwBwGofDcAbjgd5uahPkZXJFAICGxt/LVaN6tdCoXi2UX2TXr3GpzpbrpVunV8SQlJCep9/iUzUgOqhuCgYAAAAAAPVW6RXjtFI/d1azCwAAoL6JS8lSem6hpOI26hYLq/UAAOfO3cWmyy4I0bOjumrt41fqLzEdqvS8pMwzB+gAAAAAAKBpiEsuXjHu4WpVc39Pk6tpuAjGAQA4Tdk26uwvDgCoORaLRb1bV+3/t4T6etRyNQAAAAAAoL4rKHLoQGqOJCkq2EdWtl07ZwTjAACcpnQw3ieSYBwAULMuahuoCH8PVTaNtUiK8PfQRW0D67IsAAAAAABQDx1MzZHdYUiSokPZX/x8EIwDAHCaDSeDcVebRd1a+JtcDQCgsbFZLZo+srMklQvHS+5PH9lZNr4BDgAAAABAkxd7so26JEUFs7/4+SAYBwCglNTsAsUlZ0uSurbwl4erzeSKAACN0bCuEXprXG+F+5dtlx7k46a3xvXWsK4RJlUGAAAAAADqk9LBOCvGzw/BOAAApWw+WKqNehX3gAUA4FwM6xqh1Y9dqdv6RzqPPTC4PaE4AAAAAABwKlnIJUnRIawYPx8E4wAAlLKB/cUBAHXIZrXomp7Nnfd3HMkwsRoAAAAAAFDflF4x3pZW6ueFYBwAgFI2EowDAOpYl+b+KtlO/Pcj6eYWAwAAAAAA6g3DMBSbVByMtwjwlJebi8kVNWwE4wAAnFRod2jroTRJUqtAT4X6eZz5CQAA1ABPN5suCPOVJP2RmKncArvJFQEAAAAAgPogJatAGXlFkqQo2qifN4JxAABO2nE0Q/lFDknsLw4AqFvdWvhLkuwOQzsTaKcOAAAAAACkuFJt1KNDfEyspHEgGAcA4CTaqAMAzNK9VYDz9rbDaabVAQAAAAAA6o/Y5Gzn7WhWjJ83gnEAAE7aVCYYDzSxEgBAU9P95IpxSfr9MPuMAwAAAAAAKZYV4zWKYBwAAEmGYWjDgVRJkrebTR3CfU2uCADQlHSM8JWrzSJJ+v0IwTgAAAAAADitlXoowfj5IhgHAEDSkbRcJWbkS5J6tW4mm9VickUAgKbE3cWmjuF+koq/DZ6VX2RyRQAAAAAAwGwlrdS93WwK9XU3uZqGj2AcAACxvzgAwHzdWha3UzcMaTurxgEAAAAAaNLyCu06dCJHUvFqcYuFxVzni2AcAAARjAMAzFd6n/Ft7DMOAAAAAECTtv94tgyj+Db7i9cMgnEAAHQqGLdYpJ6tA8wtBgDQJHVvGeC8zT7jAAAAAAA0bXEn26hLUlSwt4mVNB4E4wCAJi87v0i7EjIkSR3CfOXn4WpyRQCApqh9mI/cXYqnaL8fTjO3GAAAAAAAYKrYpCzn7ehQVozXBIJxAECTt+VQmhwnW9LQRh0AYBZXm1Wdm/tJkg4cz1F6TqHJFQEAAAAAALPEJpcKxmmlXiMIxgEATR77iwMA6osepdqpb6OdOgAAAAAATVZcSnErdatFigzyMrmaxoFgHADQ5JUOxvtGBppYCQCgqevWwt95eyvt1AEAAAAAaJIMw3C2Um/ZzEserjaTK2ocCMYBAE2aw2Fo08HiYDzYx12tAj1NrggA0JR1b3kqGN92mBXjAAAAAAA0RYkZ+cousEuSokO8Ta6m8SAYBwA0aXuTspSZVyRJ6hMZIIvFYnJFAICmLCrER95uxd8Cp5U6AAAAAABNE/uL1w6CcQBAk0YbdQBAfWKzWtTlZDv1I2m5SsnKN7kiAAAAAABQ1+JKBeNRBOM1hmAcANCklQ7Ge0c2M7ESAACKdW9BO3UAAAAAAJqy2ORs521aqdccgnEAQJO28UCqJMnNxaquLfxMrgYAAKl7qwDn7d8JxgEAAAAAaHLKtFIPZcV4TSEYBwA0WSlZ+dp/PEdS8eo8dxebyRUBAFB2xfjvh9PMKwQAAAAAAJgi7uSKcX9PVwV5u5lcTeNBMA4AaLI2lWqj3oc26gCAeiIyyEt+Hi6SpN+PpMswDJMrAgAAAAAAdSWnoEhH0nIlSVEh3rJYLCZX1HgQjAMAmiz2FwcA1EcWi0XdWwZIkpIz83UsI8/cggAAAAAAQJ2JK7O/OG3UaxLBOACgydrIinEAQD3VrWXpdursMw4AAAAAQFMRl0IwXlsIxgEATVJ+kV2/HykOGtoEeSnYx93kigAAOKVHqWB8G8E4AAAAAABNRmxSlvN2VIi3iZU0PgTjAIAmafuRDBUUOSTRRh0AUP90O9lKXZK2Hk4zrQ4AAAAAAFC3YpNPBeOsGK9ZBOMAgCZpE23UAQD1WHN/DwV5u0mSth1Jl2EYJlcEAAAAAADqQuzJPcZdrBZFBnmZXE3jQjAOAGiSSu8v3jcy0MRKAAAoz2KxqPvJduppOYU6fCLX5IoAAAAAAEBtczgMxacUrxhvHeglVxtRbk3i0wQANDmGYWjDyWDc191F7UNpRwMAqH9opw4AAAAAQNNyND1XeYXFW4BG0Ua9xhGMAwCanEOpuUrJypck9YpsJqvVYnJFAACU172Fv/P2tsPpJlYCAAAAAADqQkkbdUmKDvU2sZLGiWAcANDkbDyY6rzdl/3FAQD1VEkrdUn6nWAcAAAAAIBGLy45y3k7mhXjNY5gHADQ5GzYf2p/8T4E4wCAeirUz0Phfh6SpO1H0uVwGCZXBAAAAAAAalNsmWCcFeM1jWAcANDkbDy5v7jVIvVoFWBuMQAAnEG3k6vGM/OLFH88+yxnAwAAAACAhiw26dTcPyqYFeM1jWAcANCkZOYVak9ipiSpU4SffNxdTK4IAIDK9WjJPuMAAAAAADQVJSvGg7zd1MzbzeRqGh+CcQBAk7LlUJqMk51oaaMOAKjvurUMcN7eejjNtDoAAAAAAEDtyswrVFJmviQpijbqtYJgHADQpLC/OACgIenWghXjAAAAAAA0BXHJp9qoR4fQRr02EIwDAJqUTQcJxgEADUegt5taBXpKknYczVCR3WFyRQAAAAAAoDaUtFGXCMZrC8E4AKDJsDsMbT6YJkkK83NXiwBPcwsCAKAKurcIkCTlFtq1r9QkGQAAAAAANB5lVoyH0kq9NhCMAwCajD3HMpWVXySpeLW4xWIxuSIAAM6uW8tT7dR/p506AAAAAACNUukV41HBrBivDQTjAIAmY2OZNuqBJlYCAEDVdW/JPuMAAAAAADR2JcG4m82qls3odlobCMYBAE3GpgPsLw4AaHi6tii9YjzNvEIAAAAAAECtsDsM7U/JkSS1CfaSi40ItzbwqQIAmowNB1IlSe4uVnWO8DO5GgAAqsbPw1VRwcV7i+1KyFRBkcPkigAAAAAAQE06fCJHBfbi+T5t1GsPwTgAoElIysjTodRcSVKPVgFyc+H/BQIAGo6SduoFdof+SMw0uRoAAAAAAFCTSu8vHh3qbWIljRupAACgSdh0kDbqAICGq1vLAOftrbRTBwAAAACgUYlNynbejg5hxXhtIRgHADQJG/aXCsZbE4wDABqWkhXjkrTtcLqJlQAAAAAAgJoWl3JqxXgUwXitIRgHADQJG0utGO/NinEAQAPTpbmfrJbi278TjAMAAAAA0KiUXjEeFUIr9dpCMA4AaPTyCu3afqQ4RIgK8Vagt5vJFQEAUD1ebi5qH+orSdqTmKm8QrvJFQEAAAAAgJpSssd4qK+7/DxcTa6m8SIYBwA0etuOpKvQbkiijToAoOHqdrKdut1haGdChsnVAAAAAACAmpCWU6Dj2QWS2F+8thGMAwAavY0HTrVR79uGYBwA0DD1KLXP+O+H0swrBAAAAAAA1JjYZNqo1xWCcQBAo1c6GO/D/uIAgAaqW8sA5+3fj7DPOAAAAAAAjUFJG3WJFeO1jWAcANCoGYahTSeDcX9PV0UF84cFAKBh6hThK1ebRZK07TDBOAAAAAAAjUGZYDyU69e1iWAcANCo7T+e49yfpXfrAFmtFpMrAgDg3Li72NQh3FeStC85S1n5RSZXBAAAAAAAzldc6VbqwbRSr00E4wCARq3s/uKBJlYCAMD569YiQJJkGNIO2qkDAAAAANDglawYd3exqkWAp8nVNG4E4wCARq10MN67NfuLAwAath4t/Z23txGMAwDw/+zde3yU9Z33//fM5DA5Tsg55EQSQAgkICiQerYotpbWrd211aq3tVop9G7L79663KtSbHftdnd72K3F1mp1V11te/eEWqwFQakIAkLCWZJASMiRkMl5ksxcvz8mmWQknJO5Ziav5+Phw2+u65rwGXJpknnP5/MFAAAIaf1uj2pOdkuSCtPimXg6zgjGAQBhbeexVkmSzWrRnFzHOa4GACC4lYwIxvewzzg+4sknn9SUKVNkt9u1cOFCbd++/azX/+hHP9Jll12mmJgY5ebm6pvf/KZ6e3sDVC0AAAAAoKa1WwMeQ5JUlMYY9fFGMA4ACFvOnn4dbvSOoZk1OVGxUREmVwQAwKWZnpGg6Ajvr3EVtW3mFoOg8sorr2jlypVavXq1du3apTlz5mjJkiVqamoa9fqXXnpJ//AP/6DVq1frwIEDeuaZZ/TKK6/o//7f/xvgygEAAABg4qps6vStC9PiTaxkYiAYBwCErQ9qGKMOAAgvkTariicnSpKOnuyWs7vf5IoQLH7wgx/ogQce0H333afi4mI99dRTio2N1bPPPjvq9e+++66uuuoq3XnnnZoyZYpuvvlmfeELXzhnlzkAAAAAYOxUNnf51nSMjz9a5wAAYWvk/uLz8wnGAQDhoTTboQ9q2iR59xm/elqquQXBdH19fdq5c6dWrVrlO2a1WrV48WJt3bp11Md87GMf0wsvvKDt27drwYIFqqqq0uuvv6677777jH+Oy+WSy+Xyfdze3i5J8ng88ng8Y/RsECw8Ho8Mw+Bri3HFfYZA4V5DIHCfIVC418LLkaYO37owNTaovq6hcq9dSH0E4wCAsDUyGL9iCsE4ACA8lOQkSTomSSqvayMYh1paWuR2u5WRkeF3PCMjQwcPHhz1MXfeeadaWlp09dVXyzAMDQwM6KGHHjrrKPUnnnhCa9asOe14c3Mze5OHIY/HI6fTKcMwZLUycBDjg/sMgcK9hkDgPkOgcK+Fl8P1bb51vNGtpibXmS8OsFC51zo6Os590SCCcQBAWBpwe7T7eJskabLDrixHjLkFAQAwRubkOHzrilqniZUglG3atEn//M//rJ/+9KdauHChjhw5oq9//ev6zne+o0cffXTUx6xatUorV670fdze3q7c3FylpaUpMTExUKUjQDwejywWi9LS0oL6RTCENu4zBAr3GgKB+wyBwr0WPgzDUE1buSQpy2FXfnaWyRX5C5V7zW63n/e1BOMAgLB0sKFD3X1uSdI8xqgDAMJIYVq8YqNs6u5zq5xgHJJSU1Nls9nU2Njod7yxsVGZmZmjPubRRx/V3XffrS9/+cuSpJKSEnV1denBBx/UP/7jP476okd0dLSio6NPO261WoP6RRJcPIvFwtcX4477DIHCvYZA4D5DoHCvhYeWTpecPf2SpKnp8UH59QyFe+1CagveZwEAwCXwG6NOMA4ACCM2q0WzJ3u7xuvaetTSGTxj1mCOqKgozZ8/Xxs2bPAd83g82rBhg8rKykZ9THd392kvHthsNknergUAAAAAwPiqau7yrQtT40ysZOIgGAcAhKWRwfj8/GQTKwEAYOyVjhynXkfXOKSVK1fq6aef1vPPP68DBw5o2bJl6urq0n333SdJuueee7Rq1Srf9UuXLtXatWv18ssvq7q6Wm+++aYeffRRLV261BeQAwAAAADGT2Vzp29dlB5vYiUTB6PUAQBhaSgYj4m0aUZWgsnVAAAwtkpGBOPlx5264bJ0E6tBMLjjjjvU3Nysxx57TA0NDZo7d67Wr1+vjIwMSVJNTY1fh/gjjzwii8WiRx55RHV1dUpLS9PSpUv1T//0T2Y9BQAAAACYUCqbRgTjaQTjgUAwDgAIO/XOHtW19UiS5uYmKdLGgBQAQHgpzUnyrSvq2kyrA8FlxYoVWrFixajnNm3a5PdxRESEVq9erdWrVwegMgAAAADAR/l1jBOMBwRJAQAg7Ow61uZbz2d/cQBAGJqSEqsEu/d9zuW1jFIHAAAAACDUVLV49xiPi7IpIzHa5GomBoJxAEDY2XGs1bcmGAcAhCOLxeLbZ7ypw6UGZ6/JFQEAAAAAgPPV2+/W8dZuSVJhWrwsFovJFU0MBOMAgLCza3B/cUmal0cwDgAITyXZSb51eW2baXUAAAAAAIALc+xktzyGd12UFmduMRPIBQXja9euVWlpqRITE5WYmKiysjL96U9/8p3v7e3V8uXLlZKSovj4eN1+++1qbGz0+xw1NTW69dZbFRsbq/T0dP393/+9BgYG/K7ZtGmT5s2bp+joaE2dOlXPPffcxT9DAMCE0tPn1r4T7ZKkaenxcsRGmlwRAADjY85gx7gkVdQxTh0AAAAAgFBRNWJ/8UL2Fw+YCwrGc3Jy9L3vfU87d+7Ujh07dOONN+ozn/mM9u3bJ0n65je/qXXr1unXv/61Nm/erBMnTuizn/2s7/Fut1u33nqr+vr69O677+r555/Xc889p8cee8x3TXV1tW699VbdcMMN2r17t77xjW/oy1/+st54440xesoAgHC2p7ZNA4NvtWOMOgAgnJWMCMb3sM84AAAAAAAho3JEMF5EMB4wERdy8dKlS/0+/qd/+ietXbtW7733nnJycvTMM8/opZde0o033ihJ+uUvf6mZM2fqvffe06JFi/TnP/9Z+/fv11/+8hdlZGRo7ty5+s53vqOHH35Y3/72txUVFaWnnnpKBQUF+vd//3dJ0syZM7Vlyxb98Ic/1JIlS85Ym8vlksvl8n3c3u7tFvR4PPJ4PBfyNBECPB6PDMPga4txxX0WmnYcHd5ffF5eUkh8/bjXEAjcZwgU7rXAyUqMVnJspFq7+1VR2ya32z1h9iQLpfssFGoEAAAAAARWZXOXb12Uzij1QLmgYHwkt9utX//61+rq6lJZWZl27typ/v5+LV682HfNjBkzlJeXp61bt2rRokXaunWrSkpKlJGR4btmyZIlWrZsmfbt26fLL79cW7du9fscQ9d84xvfOGs9TzzxhNasWXPa8ebmZvX29l7s00SQ8ng8cjqdMgxDVusFDT4Azhv3WWja+uHwFh5T4j1qamoysZrzw72GQOA+Q6BwrwXWZekx2nq0X6e6+7XnSK0mO6LNLikgQuk+6+joMLsEAAAAAECQGeoYt1ikKSkE44FywcF4RUWFysrK1Nvbq/j4eP3ud79TcXGxdu/eraioKCUlJfldn5GRoYaGBklSQ0ODXyg+dH7o3NmuaW9vV09Pj2JiYkata9WqVVq5cqXv4/b2duXm5iotLU2JiYkX+jQR5DwejywWi9LS0oL+hTCELu6z0GMYhvY1lEuSJsVGav703JDonONeQyBwnyFQuNcC64qCNm096p2WdaI3QnOnpZtcUWCE0n1mt9vNLgEAAAAAEEQMw1DVYMd4zqQY2SNtJlc0cVxwMH7ZZZdp9+7dcjqd+s1vfqN7771XmzdvHo/aLkh0dLSio0/vjrBarUH/QgkujsVi4euLccd9FlqONHWqradfknd/cZstdH6g4F5DIHCfIVC41wKnNHeSb11xol2fmpNtYjWBFSr3WbDXBwAAAAAIrKYOlzpdA5LYXzzQLjgYj4qK0tSpUyVJ8+fP1/vvv68f//jHuuOOO9TX16e2tja/rvHGxkZlZmZKkjIzM7V9+3a/z9fY2Og7N/TvoWMjr0lMTDxjtzgAAJK069gp33p+frKJlQAAEBilOQ7fuqLWaWIlAAAAAADgfFQ2dfrWBOOBdclvXfd4PHK5XJo/f74iIyO1YcMG37lDhw6ppqZGZWVlkqSysjJVVFT47ff65ptvKjExUcXFxb5rRn6OoWuGPgcAAGey0y8Yn3SWKwEACA8ZiXZlJHonZ1XUOuXxGCZXBAAAAAAAzqaypcu3Lkxjf/FAuqCO8VWrVukTn/iE8vLy1NHRoZdeekmbNm3SG2+8IYfDofvvv18rV65UcnKyEhMT9bWvfU1lZWVatGiRJOnmm29WcXGx7r77bn3/+99XQ0ODHnnkES1fvtw3Bv2hhx7ST37yE33rW9/Sl770JW3cuFG/+tWv9Nprr439swcAhJUdx1olSZE2i18HHQAA4aw0J0lv7m9Uh2tAR092qZB3mwMAAAAAELToGDfPBQXjTU1Nuueee1RfXy+Hw6HS0lK98cYbuummmyRJP/zhD2W1WnX77bfL5XJpyZIl+ulPf+p7vM1m06uvvqply5aprKxMcXFxuvfee/X444/7rikoKNBrr72mb37zm/rxj3+snJwc/eIXv9CSJUvG6CkDAMLRqa4+VTZ732k3a7JD9sjQ2V8cAIBLUZrt0Jv7vdtRldc6CcYBAAAAAAhilc0E42a5oGD8mWeeOet5u92uJ598Uk8++eQZr8nPz9frr79+1s9z/fXX64MPPriQ0gAAE9wHxxmjDgCYmEpGTEkpr3XqtsuzTawGAAAAAACcTdVgg1eCPUKp8VEmVzOxXPIe4wAABIMdRwnGAQATU2lOkm9dUddmWh0AAAAAAODsevrcqmvrkeTtFrdYLCZXNLEQjAMAwsLOYwTjAICJKTkuSjmTYiRJe+vaNeD2mFwRAAAAAAAYTVULY9TNRDAOAAh5/W6P9tS2SZJyJsUoI9FubkEAAARY6eA49Z5+tyoHR7IBAAAAAIDgMvJ39qL0OBMrmZgIxgEAIW//iXb19nu74+gWBwBMRCPHqZcPvlkMAAAAAAAEl6rm4Y7xwlQ6xgONYBwAEPJGjlG/gmAcADABlWY7fOvyWqeJlQAAAAAAgDMZ2TE+lY7xgCMYBwCEvJ01w8H4PIJxAMAENGtkMF5HMA4AAAAAQDCqbPJ2jNusFuUlE4wHGsE4ACCkGYahnUe9wXhclE2XZSSYXBEAAIHniIlUYar3F+oD9e3qG/CYXBEAAAAAABjJ4zFU3eLtGM9LjlVUBDFtoPE3DgAIaSecvWpo75UkXZ43SRE2vrUBACamkhxv13jfgEeHGztMrgYAAAAAAIxU396rnn63JKkojW5xM5AeAABC2sj9xRmjDgCYyErYZxwAAAAAgKA1NEZdkorS4k2sZOIiGAcAhLSdR1t96/kE4wCACWxObpJvXVHXZlodAAAAAADgdJXNBONmIxgHAIS0nTXejnGLRbo8L8ncYgAAMFFxVqKsFu96z3E6xgEAAAAACCZVzV2+dSGj1E1BMA4ACFldrgEdqPfuoXpZRoIS7ZEmVwQAgHnioiM0Nd37jvPDjR3qHdy3DAAAAAAAmI+OcfMRjAMAQtae2ja5PYYk9hcHAECSSnOSJEkDHkMH6tvNLQYAAAAAAPgMBePJcVGaFBdlcjUTE8E4ACBk7Tx6yre+gmAcAACV5jh86/JaxqkDAAAAABAMOl0Damx3SZIKUxmjbhaCcQBAyBraX1yS5hOMAwCgkmyCcQAAAAAAgk0VY9SDAsE4ACAkeTyGdh3zBuOp8VHKS441uSIAAMw3MytREVaLJKmirs3cYgAAAAAAgKSP7C+eTse4WQjGAQAh6Uhzp9p7ByRJ8/ImyWKxmFwRAADms0fadFlmgiTpSFOnulwDJlcEAAAAAAAqm7p8azrGzUMwDgAISTuPjdhffApj1AEAGDK0z7jHkPadaDe5GgAAAAAAUNUy3DFeSDBuGoJxAEBIGhmMs784AADDSnOSfOvy2jbT6gAAAAAAAF5DHeORNotyJ8WYXM3ERTAOAAhJQ8F4lM2qWZMdJlcDAEDwKMke/r5YXus0sRIAAAAAAOD2GKo+6Q3Gp6TEKcJGPGsW/uYBACHnZKdL1S3eHyRKchyyR9pMrggAgOBxWWaCoiK8v+pV1BGMAwAAAABgprpTPeob8EiSCtPiTK5mYiMYBwCEnF01bb41Y9QBAPAXabOqOCtRklTd0iVnT7/JFQEAAAAAMHFVNg/vL17E/uKmIhgHAIScHcdafet5eQTjAAB8VGnO8Dj1vXSNAwAAAABgGoLx4EEwDgAIObsG9xeX6BgHAGA0pTlJvjX7jAMAAAAAYJ6RwTij1M1FMA4ACCl9Ax7tGXyBPz8lVmkJ0SZXBABA8BnZMV5R12ZeIQAAAAAATHCVzV2+dSEd46YiGAcAhJS9J5zqG/BIkuYzRh0AgFEVpcUrNsomSdpznI5xAAAAAADMUjXYMZ6WEC1HTKTJ1UxsBOMAgJDiN0Z9CsE4AACjsVktmj3Z2zVe19ajk50ukysCAAAAAGDicXb3q6WzT5JUxBh10xGMAwBCyk72FwcA4LyUjBinXl5H1zgAAAAAAIFW2TJyf3HGqJuNYBwAEDIMw9COwWA8ITpC09ITTK4IAIDg5bfPeC3BOAAAAAAAgVbZNByMFxGMm45gHAAQMmpP9ai5wzsK9vL8SbJZLSZXBABA8CrNSfKtywnGAQAAAAAIuMrmLt+aUermIxgHAIQMvzHqeYxRBwDgbPKTY5Vgj5Aklde2mVsMAAAAAAATUFUzHePBhGAcABAy2F8cAIDzZ7VaVJLtHafe1OFSY3uvyRUBAAAAADCxVA4G49ERVk1OijG5GhCMAwBCxtD+4laLNDcvydxiAAAIAYxTBwAAAADAHP1uj46d7JYkFaTGsTVoECAYBwCEhI7efh1qaJckzchMVHx0hMkVAQAQ/EpzHL4149QBAAAAAAicmtZuDXgMSVJROmPUgwHBOAAgJOw57tTgzxCMUQcA4DwNjVKX6BgHAAAAACCQqpq7fOui1DgTK8EQgnEAQEjYcazVt75iCsE4AADnI2dSjJLjoiRJFXVOGYZhckUAAAAAAEwMQ/uLS3SMBwuCcQBASNg5uL+4JM3LIxgHAOB8WCwWX9d4a1efak/1mFwRAAAAAAATQ2XTiGA8jWA8GBCMAwCCnttjaHdNmyQpPSFaOZNizC0IAIAQMnKf8Yo6xqkDAAAAABAIVS3Do9QLGKUeFAjGAQBB73BjhzpcA5K8Y9QtFovJFQEAEDpKc5J8a/YZBwAAAABg/BmGoSODHeNZDrvioiNMrggSwTgAIAQwRh0AgIs3smO8vLbNvEIAAAAAAJggWrv65Ozpl8QY9WBCMA4ACHq7RgTj8/MJxgEAuBAZiXalJ0RL8o5S93gMkysCAAAAACC8VTYPj1EvTGOMerAgGAcABL0dg8F4dIRVsyY7znE1AAD4qKFx6h29AzrW2m1uMQAAAAAAhLmq5k7fmo7x4EEwDgAIak0dvaoZfAF/Tk6SoiL41gUAwIVinDoAAAAAAIFTSTAelEgXAABBbdexNt96HmPUAQC4KCV+wbjTxEoAAAAAAAh/I0epF6UzSj1YEIwDAILazmOtvjX7iwMAcHFKs4eD8QqCcQAAAAAAxtXQKPXYKJsyE+0mV4MhBOMAgKC2c3B/cYlgHACAi5USH63spBhJ0t4TTrk9hskVAQAAAAAQnlwDbt/2oIVpcbJYLCZXhCEE4wCAoNXb79beunZJUmFqnJLjokyuCACA0DW0z3h3n9tvrzMAAAAAADB2jp3s1tD70dlfPLgQjAMAgtbeOqf63B5J7C8OAMClKs1J8q3ZZxwAAAAAgPFR2TT8ZvTCVILxYEIwDgAIWiPHqF9BMA4AwCUZ6hiXpPLaNvMKAQAAAAAgjFW1dPnWRelxJlaCjyIYBwAELfYXBwBg7MzOHhmM0zEOAAAAAMB4GNkxzij14EIwDgAISoZhaFeNNxhPtEfwAwQAAJfIEROpglTvO9X317erf3C7EgAAAAAAMHYqm73BuMUi3+/hCA4E4wCAoHTsZLdaOvskebvFrVaLyRUBABD6Sga7xvsGPDrU0GFyNQAAAAAAhBfDMFTV7B2lnp0UI3ukzeSKMBLBOAAgKDFGHQCAsTdyn/GKOsapAwAAAAAwlpo7XOpwDUhijHowIhgHAASlnTXDwfg8gnEAAMZEaU6Sb80+4wAAAAAAjK0jzewvHswIxgEAQWnnUW8wbrNaNDc3ydxiAAAIE7MmJ2pod5Ly2jZTawEAAAAAINxUDo5Rl6TCNPYXDzYE4wCAoOPs6dfhJu++p8VZiYqNijC5IgAAwkNcdISmpnvfsX6ooUO9/W6TKwIAAAAAIHxU0TEe1AjGAQBBZ/fxNhmGd83+4gAAjK2S7CRJ0oDH0IH6dnOLAQAAAAAgjIzsGC9Kp2M82BCMAwCCzs6jrb41wTgAAGOrNMfhW1fUsc84AAAAAABjpbLJ2zGeEB2htPhok6vBRxGMAwCCzs6aU741wTgAAGNrZDBeXkswDgAAAADAWOjpc+uEs0eSVJgeL4vFYnJF+CiCcQBAUBlwe7S7pk2SlOWwa3JSjLkFAQAQZmZmJSrC6v3lvLy2zdxiAAAAAAAIE9UtXb4tQovSGKMejAjGAQBB5WBDh7r63JLoFgcAYDzYI22anpEgSTrS1Kku14DJFQEAAAAAEPoqmzt966K0eBMrwZkQjAMAgsouxqgDADDu5uR6x6l7DGl/fbvJ1QAAAAAAEPqqmrt8azrGgxPBOAAgqOw8RjAOAMB4K8lO8q33HG8zrQ4AAAAAAMIFHePBj2AcABBUdhz1BuMxkTbNzEo0uRoAAMJTaY7Dt66oc5pYCQAAAAAA4WEoGLdZLcpLiTW5GoyGYBwAEDQanL2qa+uR5B3xGmnj2xQAAONhekaCoiK832cragnGAQAAAAC4FB6P4RulnjspRtERNpMrwmhIHAAAQYP9xQEACIyoCKtvMktVS5ecPf0mVwQAAAAAQOhqaO9VT79bEmPUgxnBOAAgaLC/OAAAgVOaPTxOfR/j1AEAAAAAuGh++4unE4wHK4JxAEDQ2DEiGJ+XRzAOAMB4GrnPeDnBOAAAAAAAF62yaUQwnhZnYiU4G4JxAEBQ6O13+7rVpqbHKyk2yuSKAAAIb6U5Sb51eW2baXUAAAAAABDqqlq6fOtCRqkHLYJxAEBQKK91asBjSJLm0y0OAMC4K0qLU0ykTZL3+zAAAAAAALg4fqPUCcaDFsE4ACAo7DjW6lvPn0IwDgDAeIuwWTU7O1GSVHuqR61dfSZXhEv15JNPasqUKbLb7Vq4cKG2b99+1uvb2tq0fPlyZWVlKTo6WtOnT9frr78eoGoBAAAAIHxUNnk7xifFRio5jmmowYpgHAAQFHaN2F98fj7BOAAAgVCSneRbM049tL3yyitauXKlVq9erV27dmnOnDlasmSJmpqaRr2+r69PN910k44eParf/OY3OnTokJ5++mllZ2cHuHIAAAAACG2drgE1tPdKYox6sIswuwAAAAzD0M7BYHxSbKQKU+NMrggAgImhNMfhW1fUOnX9ZekmVoNL8YMf/EAPPPCA7rvvPknSU089pddee03PPvus/uEf/uG065999lm1trbq3XffVWRkpCRpypQpZ/0zXC6XXC6X7+P29nZJksfjkcfjGaNngmDh8XhkGAZfW4wr7jMECvcaAoH7DIHCvRZ8Kps6fOvC1Liw+dqEyr12IfURjAMATFfV0qVT3f2SvN3iFovF5IoAAJgYRgbj5XXsMx6q+vr6tHPnTq1atcp3zGq1avHixdq6deuoj/njH/+osrIyLV++XH/4wx+UlpamO++8Uw8//LBsNtuoj3niiSe0Zs2a0443Nzert7d3bJ4MgobH45HT6ZRhGLJaGTiI8cF9hkDhXkMgcJ8hULjXgs8HlSd964wY44yTu0JNqNxrHR0d575oEME4AMB0O0eMUZ/HGHUAAAJmSkqcEqIj1OEaYJR6CGtpaZHb7VZGRobf8YyMDB08eHDUx1RVVWnjxo2666679Prrr+vIkSP66le/qv7+fq1evXrUx6xatUorV670fdze3q7c3FylpaUpMTFx7J4QgoLH45HFYlFaWlpQvwiG0MZ9hkDhXkMgcJ8hULjXgk/LnjbfurQgQ+np4TGNLVTuNbvdft7XEowDAEznt794HsE4AACBYrVaVJLj0LuVJ9XY7lJje68yEs//F0qELo/Ho/T0dP385z+XzWbT/PnzVVdXp3/91389YzAeHR2t6Ojo045brdagfpEEF89isfD1xbjjPkOgcK8hELjPECjca8GluqXbt56anhBWX5dQuNcupLbgfRYAgAljx2AwHmG1aE5ukrnFAAAwwZR8ZJ9xhJ7U1FTZbDY1Njb6HW9sbFRmZuaoj8nKytL06dP9xqbPnDlTDQ0N6uvrG9d6AQAAACCcVDZ3SpIibRblJseaXA3OhmAcAGCqtu4+HWny/uAwK9she+Toe1oCAIDxUZqd5FszTj00RUVFaf78+dqwYYPvmMfj0YYNG1RWVjbqY6666iodOXJEHo/Hd+zw4cPKyspSVFTUuNcMAAAAAOHA7TFU1dIlScpPiVOkjeg1mPHVAQCY6oOaNt+aMeoAAARe6YiO8fI6OsZD1cqVK/X000/r+eef14EDB7Rs2TJ1dXXpvvvukyTdc889WrVqle/6ZcuWqbW1VV//+td1+PBhvfbaa/rnf/5nLV++3KynAAAAAAAhp+5Uj/oGvG84LkyNM7kanAt7jAMATLXjWKtvfcUUgnEAAAItZ1KMJsVG6lR3vypqnTIMQxaLxeyycIHuuOMONTc367HHHlNDQ4Pmzp2r9evXKyMjQ5JUU1Pjt+9abm6u3njjDX3zm99UaWmpsrOz9fWvf10PP/ywWU8BAAAAAEJOZUunb12UHm9iJTgfBOMAAFPtHNxfXJLm5xOMAwAQaBaLRSU5SXr7cLNOdvWprq1HOZPYEy0UrVixQitWrBj13KZNm047VlZWpvfee2+cqwIAAACA8FXZNCIYTyMYD3aMUgcAmKbf7dGe496RrdlJMcpItJtcEQAAE9OcEePUK2oZpw4AAAAAwPmobO7yrQvTGKUe7AjGAQCmOVDfrp5+tyTGqAMAYKaSbPYZBwAAAADgQlU1j+gYT6VjPNgRjAMATMMYdQAAgkNpTpJvXV7bZlodAAAAAACEkqGO8dT4aDliI02uBudCMA4AMM3IYHxeHsE4AABmyXTYlZ4QLUkqr3XKMAyTKwIAAAAAILg5e/rV0umSJBUxRj0kEIwDAEyzazAYj4uyaUZmgsnVAAAwsZUO7jPe0Tugoye7Ta4GAAAAAIDgNnKMemEaY9RDAcE4AMAUJ9p6dMLZK0mam5ekCBvfkgAAMFNJdpJvzTh1AAAAAADObmiMukTHeKgghQAAmMJvf3HGqAMAYLrSXIdvXVHrNLESAAAAAACCX+WIjvGidDrGQwHBOADAFH77i+cTjAMAYLaS7OFgvJxgHAAAAACAs6psGhGMpxKMhwKCcQCAKYaCcYtFupyOcQAATJcaH63spBhJ0t4TTrk9hskVAQAAAAAQvKpavKPUoyKsyp4UY3I1OB8E4wCAgOvuG9D++nZJ0vT0BDliIk2uCAAASFJpjrdrvLvPraoRI+EAAAAAAMCwfrdHx056g/HC1DjZrBaTK8L5IBgHAATcnuPDXWiMUQcAIHiU5AyPU9/DOHUAAAAAAEZ1vLVb/W7va9yFaXEmV4PzRTAOAAi4ncdafesrCMYBAAgapdlJvnVFbZtpdQAAAAAAEMyqmrt866I09hcPFQTjAICAG9pfXJLmE4wDABA0SrKHO8bL6+gYBwAAAABgNJUjth8jGA8dBOMAgIDyeAztqmmTJKXERSk/JdbcggAAgI8jNlJTBr837z/Rrn63x+SKAAAAAAAIPgTjoYlgHAAQUJXNnXL29EvydotbLBaTKwIAACOV5CRJklwDHh1u7DC3GAAAAAAAglDliFHqBewxHjIIxgEAAcUYdQAAgtucnOFx6hW1jFMHAAAAAOCjqgY7xjMT7YqPjjC5GpwvgnEAQEARjAMAENxG7jO+h2AcAAAAAAA/rV19OtXtnYpalE63eCghGAcABNRQMB5ls2r2iBfeAQBAcJiV7dDQTicVdW2m1gIAAAAAQLAZub94YSr7i4cSgnEAQMC0dvWpqsW798rs7ETZI20mVwQAAD4qPjpCU9O8v9gfauhQb7/b5IoAAAAAAAgeVSOC8SL2Fw8pBOMAgIDZxRh1AABCQsngPuP9bkMHGzpMrgYAAAAAgOBR2dzlWxel0zEeSgjGAQABs8MvGE82sRIAAHA2c3KSfOuK2jbT6gAAAAAAINhUNo3sGCcYDyUE4wCAgBnZMT4vP8m8QgAAwFkNdYxLUnmt08RKAAAAAAAILkN7jMdE2pSZaDe5GlwIgnEAQED0DXi0Z7DjLC85VukJ/MAAAECwKs5KVITVIolgHAAAAACAIa4Bt46f6pEkFabFyTr4uzNCA8E4ACAg9te3yzXgkSRdwf7iAAAENXukTdMzEiRJHzZ1qLtvwOSKAAAAAAAwX83Jbrk9hiTGqIcignEAQEDsONrqW88jGAcAIOiVDo5T9xjS/hPtJlcDAAAAAID5hsaoS96OcYQWgnEAQEDsqhneX3w+wTgAAEFv5D7jexinDgAAAACAKpu7fGs6xkMPwTgAYNwZhqGdx7zBeEJ0hG80KwAACF5zcpJ864raNtPqAAAAAAAgWIzsGCcYDz0E4wCAcVd7qkeN7S5J0ty8JNmsFpMrAgAA5zI9I0FRNu+vjOV1dIwDAAAAADCyY7wglVHqoYZgHAAw7hijDgBA6ImKsGpmlnfKS1Vzl9p7+02uCAAAAAAA8xiGoaomb8d4dlKMYqJsJleEC3VBwfgTTzyhK6+8UgkJCUpPT9dtt92mQ4cO+V3T29ur5cuXKyUlRfHx8br99tvV2Njod01NTY1uvfVWxcbGKj09XX//93+vgYEBv2s2bdqkefPmKTo6WlOnTtVzzz13cc8QAGC6oTHqEsE4AAChpHTEOPW9dI0DAAAAACaw5k6XOlzePLMonTHqoeiCgvHNmzdr+fLleu+99/Tmm2+qv79fN998s7q6hscGfPOb39S6dev061//Wps3b9aJEyf02c9+1nfe7Xbr1ltvVV9fn9599109//zzeu655/TYY4/5rqmurtatt96qG264Qbt379Y3vvENffnLX9Ybb7wxBk8ZABBoO456g3GrRZqbm2RuMQAA4LyV5Dh86/JagnEAAAAAwMRV2TSchxalMUY9FEVcyMXr16/3+/i5555Tenq6du7cqWuvvVZOp1PPPPOMXnrpJd14442SpF/+8peaOXOm3nvvPS1atEh//vOftX//fv3lL39RRkaG5s6dq+985zt6+OGH9e1vf1tRUVF66qmnVFBQoH//93+XJM2cOVNbtmzRD3/4Qy1ZsmTU2lwul1wul+/j9vZ2SZLH45HH47mQp4kQ4PF4ZBgGX1uMK+6zsdHpGtDBBu//ky/LTFBclI2/04/gXkMgcJ8hULjXwsvsyYm+dfnxtqD5uobSfRYKNQIAAAAAzq2yudO3LkyjYzwUXVAw/lFOp7djIDk5WZK0c+dO9ff3a/Hixb5rZsyYoby8PG3dulWLFi3S1q1bVVJSooyMDN81S5Ys0bJly7Rv3z5dfvnl2rp1q9/nGLrmG9/4xhlreeKJJ7RmzZrTjjc3N6u3t/dSniaCkMfjkdPplGEYslovaPABcN64z8bG+zXt8hje9cw0u5qamswtKAhxryEQuM8QKNxr4SVRhuwRVvUOeLS7pjVovo+H0n3W0dFhdgkAAAAAgDFQ1UzHeKi76GDc4/HoG9/4hq666irNnj1bktTQ0KCoqCglJSX5XZuRkaGGhgbfNSND8aHzQ+fOdk17e7t6enoUExNzWj2rVq3SypUrfR+3t7crNzdXaWlpSkxMPO16hDaPxyOLxaK0tLSgfyEMoYv7bGxUVgyPXb16RpbS09NNrCY4ca8hELjPECjca+FnVrZDO4+d0on2PkXEJSk5LsrskkLqPrPb7WaXAAAAAAAYAyM7xqfSMR6SLjoYX758ufbu3astW7aMZT0XLTo6WtHR0acdt1qtQf9CCS6OxWLh64txx3126XYdHw7Gr5ySwt/lGXCvIRC4zxAo3GvhpTTHG4xL0r76Dl03Pc3kirxC5T4L9voAAAAAAOdnKBiPj45QWsLpmSSC30X9hr5ixQq9+uqreuutt5STk+M7npmZqb6+PrW1tfld39jYqMzMTN81jY2Np50fOne2axITE0ftFgcABCePx9AHgy+kpyVEK2cS/w8HACDUzMlJ8q0rattMqwMAAAAAALP09rtV19YjyTtG3WKxmFwRLsYFBeOGYWjFihX63e9+p40bN6qgoMDv/Pz58xUZGakNGzb4jh06dEg1NTUqKyuTJJWVlamiosJvb7o333xTiYmJKi4u9l0z8nMMXTP0OQAAoeFwU4c6XAOSpCvyJ/HDAgAAIagkx+Fb76l1nuVKAAAAAADCU3VLlwzDuy5ijHrIuqBR6suXL9dLL72kP/zhD0pISPDtCe5wOBQTEyOHw6H7779fK1euVHJyshITE/W1r31NZWVlWrRokSTp5ptvVnFxse6++259//vfV0NDgx555BEtX77cNwr9oYce0k9+8hN961vf0pe+9CVt3LhRv/rVr/Taa6+N8dMHAIynobGrkjQ/f5KJlQAAgItVkBKnhOgIdbgGVEEwDgAAAACYgEbuL16UTjAeqi6oY3zt2rVyOp26/vrrlZWV5fvnlVde8V3zwx/+UJ/61Kd0++2369prr1VmZqZ++9vf+s7bbDa9+uqrstlsKisr0xe/+EXdc889evzxx33XFBQU6LXXXtObb76pOXPm6N///d/1i1/8QkuWLBmDpwwACJSRwfg8gnEAAEKS1WrR7Gxv13hDe6+a2ntNrggAAAAAgMCqbOryrQtT40ysBJfigjrGjaEZAWdht9v15JNP6sknnzzjNfn5+Xr99dfP+nmuv/56ffDBBxdSHgAgyAwF41ERVs2e7DjH1QAAIFiV5ji0teqkJKm81qnFxXaTKwIAAAAAIHCqWugYDwcX1DEOAMD5au5w6djJbknSnByHoiL4lgMAQKgauc94eR3j1AEAAAAAE8vQKHWrRcpPiTW5GlwsUgoAwLjYVcMYdQAAwsWcnCTfuqK2zbQ6AAAAAAAINMMwVNXsHaWemxyr6AibyRXhYhGMAwDGxa4R+4tfkZ9sYiUAAOBS5UyKUVJspCTvKPXz2WYLAAAAAIBw0NDeq+4+tySpKI0x6qGMYBwAMC52jAjG5+UlmVcIAAC4ZBaLRSXZ3nHqJ7v6dMLZa3JFAAAAAAAERmVTl29dlBZnYiW4VATjAIAx5xpwq6LWu/9oQWqcUuKjTa4IAABcKsapAwAAAAAmoqH9xSWpkI7xkEYwDgAYc3vr2tXn9kiS5rO/OAAAYaEkx+Fb7xl8AxwAAAAAAOFuZDDOKPXQRjAOABhzO4+1+tYE4wAAhAf/jnGCcQAAAADAxFDVzCj1cEEwDgAYcztH7C9OMA4AQHjISIxWWoJ3e5Ty2jYZhmFyRQAAAAAAjL+hjvGk2Eglx0WZXA0uBcE4AGBMGYahncfaJEmJ9ghNZbQMAABhwWKxqDTbO069vXdAx052m1wRAAAAAADjq8s1oHpnrySpMDVOFovF5IpwKQjGAQBjqqa1Wy2dLknSvPxJslr5QQEAgHBROmKcenkd49QBAAAAAOGtumXkGHWawEIdwTgAYEz5jVHPY4w6AADhpDTH4VtX1LaZVwgAAAAAAAEwNEZdkorSCcZDHcE4AGBMsb84AADhq2REML6nlo5xAAAAAEB4q2waDsYLU+NMrARjgWAcADCmhoJxm9WiOblJ5hYDAADGVGp8tLKTYiRJ++qccnsMkysCAAAAAGD8VDaPGKVOx3jIIxgHAIwJt8fQhgONOtjQIUmakRmvuOgIk6sCAABjrSTb2zXe1edWdUvnOa4GAAAAACB0DY1Sj7BalJcca3I1uFQE4wCAS7Z+b72u/peNuv/5Hb5j1S3dWr+33sSqAADAePAbp36cceoAAAAAgPDk9hiqbvF2jOenxCrSRqwa6vgKAgAuyfq99Vr2wi7VO3v9jnf3ubXshV2E4wAAhJk5OUm+dUUdwTgAAAAAIDydaOuRa8AjSSpMY4x6OCAYBwBcNLfH0Jp1+3W23UXXrNvP/qMAAISRoVHqklRe22ZeIQAAAAAAjKOhMeqSVEQwHhYIxgEAF217detpneIjGZLqnb3aXt0auKIAAMC4csRGKj/Fu6/avhPt6nd7TK4IAAAAAICxV9nc5VsXpcWZWAnGCsE4AOCiGIahLUeaz+vapo4zh+cAACD0lA6OU3cNePRhY+fZLwYAAAAAIASN7BhnlHp4IBgHAFwQj8fQ+r31uu3Jv+rJtyrP6zHpCfZxrgoAAARSKePUAQAAAABhrrJp5Ch1OsbDQYTZBQAAQkPfgEe//6BOT71dqaoRI2TOxiIp02HXgoLk8S0OAAAEVEnOiGC8zqnPm1gLAAAAAADjoarF+zp4anyUkmKjTK4GY4FgHABwVl2uAf3P9hr94p1qNbT7j0QvzkpUWVGKnt1SLcm7p/gQy+C/Vy8tls1qEQAACB+zsx2yWCTDkCpqnWaXAwAAAADAmHL29Ku5wyWJMerhhGAcADCq1q4+PffuUT3/7lE5e/r9zi0qTNay66fq2mmpslgsunLKJK1Zt1/1zuHgPNNh1+qlxbpldlagSwcAAOMsPjpCRWnxOtLUqYMN7XINuBUdYTO7LAAAAAAAxkRVM2PUwxHBOADAT11bj55+u0ovv1+j3n6P37mbijO07Poizcub5Hf8ltlZuqk4U9urW9XU0av0BO/4dDrFAQAIX6XZDh1p6lS/29DB+g7NyU0yuyQAAAAAAMbEyO1Ei+gYDxsE4wAASdLhxg49tblSf9x9QgOe4aHoEVaLPjM3Ww9dV6hpGQlnfLzNalFZUUogSgUAAEGgNMeh335QJ8m7zzjBOAAAAAAgXFT6dYwTjIcLgnEAmOB21ZzS2k2VenN/o9/xmEibPr8gV1++plDZSTEmVQcAAIJVSU6Sb11+vE1alG9aLQAAAAAAjKWRwXgho9TDBsE4AExAhmFo8+Fmrd1UqW3VrX7nHDGRuvdjU/S/PjZFyXFRJlUIAACCXXFWomxWi9weQxV1TrPLAQAAAABgzAyNUo+yWZUzKdbkajBWCMYBYAIZcHv0+t4Grd1UqQP17X7nMhPt+vI1BfrCgjzFRfPtAQAAnF1MlE3TMxJ0oL5dhxs71NPnVkyUzeyyAAAAAAC4JANuj46e9AbjBalxslktJleEsULyAQATQG+/W/9vV61+/naVjp3s9jtXmBanh64r0m1zsxUVYTWpQgAAEIpKsx06UN8ujyHtO+HUFVOSzS4JAAAAAIBLcvxUj/rdhiTGqIcbgnEACGMdvf164b0aPbOlWi2dLr9zpTkOffX6It1UnMk73gAAwEUpyXHolR3HJUnltQTjAAAAAIDQV9k0vL94UVq8iZVgrBGMA0AYau5w6Zd/rdZ/v3dMHb0Dfueunpqqr15fpLKiFFksBOIAAODizclJ8q3ZZxwAAAAAEA6qWkYE4+l0jIcTgnEACCM1J7v183cq9asdteob8PiOWyzSJ2Zn6qHrilQ64gVsAACASzE9M15RNqv63B7tqW0zuxwAAAAAAC5ZZVOXb03HeHghGAeAMHCgvl1Pba7Uuj0n5DGGj0faLLp9Xo4evLZQhXwDBwAAYyw6wqYZWQkqr3WqqrlLHb39SrBHml0WAAAAAAAXrbJ5uGO8IJWO8XBCMA4AIcowDL1/9JTWbjqitw41+52Li7LpzoV5uv/qQmU67CZVCAAAJoLSHIfKa71j1PfWtausKMXkigAAAAAAuHhVLd6O8YzEaN78HWYIxgEgxHg8hjYebNLazZXaeeyU37nkuCjd97EpurssX0mxUSZVCAAAJpLS7CRJNZKk8to2gnEAAAAAQMhq7epTa1efJMaohyOCcQAIEf1uj14tP6GnNlXpUGOH37nspBg9eG2h/u6KXMVE2UyqEAAATESluQ7furzOaWIlAAAAAABcmqoRY9QL0xijHm4IxgEgyPX0ufWrHcf187erVNfW43dueka8HrquSEvnTFakzWpShQAAYCKbmhYve6RVvf0eVdQSjAMAAAAAQtfI/cXpGA8/BOMAEKSc3f367/eO6pd/PaqTg6NbhszLS9JXr5+qG2eky2q1mFQhAACAFGGzatZkh3YeO6Wa1m6d6urTpDi2dAEAAAAAhJ6q5i7fmmA8/BCMA0CQaWzv1TNbqvXie8fU1ef2O3fDZWladv1UXTllkiwWAnEAABAcSnO8wbgkVdQ5de30NJMrAgAAAADgwvl1jKcTjIcbgnEACBLVLV362eZK/XZXnfrcHt9xq0X6VOlkPXRdkYonJ5pYIQAAwOhKc4b3GScYBwAAAACEqsrBjnF7pFVZiXaTq8FYIxgHAJNV1Dr11OZKvb63XoYxfDwqwqq/uyJHD15TpLyUWPMKBAAAOIeS7CTfes/xNtPqAAAAAADgYvUNeFTT2i1JKkyNZxvTMEQwDgAmMAxDWytPau3mSr3zYYvfuYToCH2xLF/3XTVF6Qm8Iw0AAAS/wtQ4xUdHqNM1oIo6p9nlAAAAAABwwWpau+T2eLvXGKMengjGASCAPB5Df97fqLWbK0/rpkqNj9b9VxforkV5SrRHmlMgAADARbBaLZqdnaj3qlpV7+xVU0cvb/ADAAAAAISUI01dvnVhapyJlWC8WM0uAAAmgr4Bj36147gW/3CzHnphp18onpccq3/6m9na8vANWnZ9EaE4AAAISaU5Sb51RS1d42Z48sknNWXKFNntdi1cuFDbt28/r8e9/PLLslgsuu2228a3QAAAAAAIYpXNnb41HePhiY5xABhHXa4B/c/2Gv3inWo1tPf6nZuZlahl1xfpk7MzFWHjfUoAACC0leY4fOvyWqc+PjPDxGomnldeeUUrV67UU089pYULF+pHP/qRlixZokOHDik9Pf2Mjzt69Kj+z//5P7rmmmsCWC0AAAAABJ+q5uGO8aI0OsbDEcE4AIyD1q4+Pf/uUT2/9ajauvv9zi0sSNay64t03fQ0WSwWkyoEAAAYW6XZSb41+4wH3g9+8AM98MADuu+++yRJTz31lF577TU9++yz+od/+IdRH+N2u3XXXXdpzZo1euedd9TW1nbWP8Plcsnlcvk+bm9vlyR5PB55PJ6xeSIIGh6PR4Zh8LXFuOI+Q6BwryEQuM8QKNxr46eyucO3zk+OmfB/x6Fyr11IfQTjADCG6tp69It3qvTy9uPq6Xf7nVs8M0PLri/S/PxJJlUHAAAwfnKTY5QUG6m27n6V17bJMAzeBBggfX192rlzp1atWuU7ZrVatXjxYm3duvWMj3v88ceVnp6u+++/X++88845/5wnnnhCa9asOe14c3Ozent7R3kEQpnH45HT6ZRhGLJamXCF8cF9hkDhXkMgcJ8hULjXxodhGDrS6B2lnpkQpc62VnWe4zHhLlTutY6OjnNfNIhgHADGwJGmDj21uUq//6BOAx7Dd9xmtegzcyfroeuKND0jwcQKAQAAxpfFYlFJtkPvfNiils4+1Tt7NTkpxuyyJoSWlha53W5lZPiPr8/IyNDBgwdHfcyWLVv0zDPPaPfu3ef956xatUorV670fdze3q7c3FylpaUpMTHxompH8PJ4PLJYLEpLSwvqF8EQ2rjPECjcawgE7jMECvfa+GjucKmzz9vsNi0z8axbUk0UoXKv2e32876WYBwALsEHNae0dlOl/ry/0e+4PdKqz1+Zpy9fU6CcSbEmVQcAABBYpTneYFySymvbCMaDVEdHh+6++249/fTTSk1NPe/HRUdHKzo6+rTjVqs1qF8kwcWzWCx8fTHuuM8QKNxrCATuMwQK99rYqz7Z7VsXpcXzdzsoFO61C6mNYBwARuH2GNpWdVJHals1tdOmhYWpslm9o0ANw9DbH7Zo7aYjeq+q1e9xjphI3VuWr3s/NkUp8ae/aAgAABDOSkbsM15e69Qts7PMK2YCSU1Nlc1mU2Oj/5s1GxsblZmZedr1lZWVOnr0qJYuXeo7NrQnW0REhA4dOqSioqLxLRoAAAAAgkhl8/Dg9KK0OBMrwXgiGAeAj1i/t15r1u1XvXNon8RqZTnsevTWYnlkaO2mSu070e73mIzEaD1wTaE+vyBP8dH8rxUAAExMc3IdvnVFndPESiaWqKgozZ8/Xxs2bNBtt90myRt0b9iwQStWrDjt+hkzZqiiosLv2COPPKKOjg79+Mc/Vm5ubiDKBgAAAICgUdnU5VsXpcWbWAnGE+kNAIywfm+9lr2wS8ZHjtc7e/XVl3addn1hapy+cl2hbrs8W9ERtsAUCQAAEKQyE+1KjY9WS6dL5bVOGYYhi8VidlkTwsqVK3Xvvffqiiuu0IIFC/SjH/1IXV1duu+++yRJ99xzj7Kzs/XEE0/Ibrdr9uzZfo9PSkqSpNOOAwAAAMBEUNUyomM8nWA8XBGMA8Agt8fQmnX7TwvFR1OS7dBXry/SzbMyfSPWAQAAJjqLxaLSHIc2HmySs6dfNa3dyk9hBF0g3HHHHWpubtZjjz2mhoYGzZ07V+vXr1dGRoYkqaamJqj3hAMAAAAAMw2NUo+Lsik9gW1SwxXBOAAM2nSoacT49DP7x0/O1JevKaD7CQAAYBRDwbjk3WecYDxwVqxYMerodEnatGnTWR/73HPPjX1BAAAAABACevvdqj3VI8nbLc5r/+GLYBzAhHWqq0/bj7Zqe3WrtlWf1L669nM/SFJ6YjTfGAEAAM6gNGd4n/Hy2jYtnTPZxGoAAAAAADi7oye7ZAyOkmV/8fBGMA5gwmjq6NX26sEgvKpVhxo7LurzpCfYx7gyAACA8FGSneRbl9c6zSsEAAAAAIDzUNnU5VsXpTH1LJwRjAMIWyfaerSt+qQvCK9q6TrjtRaLND09XsdP9ai7zz36NZIyHXYtKEgep4oBAABCX1pCtCY77Drh7NXeOqc8HkNWK9N2AAAAAADBaWh/cUkqpGM8rBGMAwgLhmGoprVb26patW1wNPrQniCjsVqk2dkOLSxI1oKCFF05ZZKSYqO0fm+9lr2wy/s5R1w/9FLu6qXFsvHCLgAAwFmV5Dh0wtmrrj63qlo6NTU9weySAAAAAAAYVdWIYJxR6uGNYBxASDIMQ5XNnXqvaniP8MZ21xmvj7RZVJqTNBiEJ2t+/iQl2CNPu+6W2Vla+8V5WrNuv+qdvb7jmQ67Vi8t1i2zs8bl+QAAAIST0pwkvbGvUZJ3nDrBOAAAAAAgWFU2e6fNWi1SfkqsydVgPBGMAwgJHo+hgw0dvtHo26tbdbKr74zXR0dYdXlekhYWpGhhQbIuz5ukmCjbef1Zt8zO0k3FmdpW1aIjtc2ampOmhYWpdIoDAACcp9Ich29dXuvUZ+flmFgNAAAAAACjG2rCk6ScSbGyR55fjoDQRDAOICgNuD3ad6LdLwhv7x044/WxUTbNz5+kRYUpWlCQrNIch6IjLv4bmM1q0aLCFBXGu5WensK+mAAAABegJHtkMN5mXiEAAAAAAJxFQ3uvuvvckqSitDiTq8F4IxgHEBRcA25V1DoH9wdv1c6jreoa/GY0mgR7hBZMSdbCQu8e4bMmJyrSZg1gxQAAADiTpNgo5afE6tjJbu070a4Bt0cR/KwGAAAAAAgyVYNj1CX2F58ICMYBmKKnz60Pjp/StsE9wnfVnJJrwHPG65PjokYE4cmakZnIaHMAAIAgVpLt0LGT3XINePRhU6dmZiWaXRIAAAAAAH6GxqhLUiHBeNgjGAcQEJ2uAe08dkrbqryj0ffUtqnfbZzx+vSEaC0s9O4PvrAgWVPT42WxEIQDAACEitIch14tr5fkHadOMA4AAAAACDaVTcPBOKPUwx/BOIBx4ezu1/tHW317hO890S6358xBeHZSjBYWJmtRgXeP8PyUWIJwAACAEFaak+Rbl9c6dceV5tUCAAAAAMBoqlpGjFJPp2M83BGMAxgTLZ0uvT+4P/i26lYdbGiXceYcXIWpcVpQ4B2NfuWUZOVMig1csQAAABh3syYnymKRDEOqqHOaXQ4AAAAAAKcZ6hh3xEQqJS7K5Gow3gjGAVyUBmevtlWf1LZq7x7hR0aMGxnN9Ix4LSxI8e4RPiVZ6Yn2AFUKAAAAMyTYI1WYGqfK5i4dqG+Xa8Ct6Aib2WUBAAAAACBJ6nIN6ISzV5JUmBbHFNsJgGAcwDkZhqHaUz3ebvCqk9p+tFXHTnaf8XqrRSqenKgFU7xj0RcUJCuZd1oBAABMOHNyklTZ3KV+t6FDDR1+49UBAAAAADBT9cgx6mmMUZ8ICMaBCcDtMbS9ulVNHb1KT7BrQUGybNYzv/PJMAxVtXRp+1AQXt3qe9fUaGxWi0qyHVpYmKyFBcm6YkqyEu2R4/FUAAAAEEJKchz67Qd1krz7jBOMAwAAAACCRWXz8CRcgvGJgWAcCHPr99Zrzbr9qh8RbGc57Fq9tFi3zM6SJHk8hg43dQwG4d49wls6XWf8nFE2q+bmJnnHohcka17eJMVF878TAAAA+CvNcfjW5bVtkvJNqwUAAAAAgJEqm4c7xgvT4kysBIFCkgWEsfV767XshV0yPnK8wdmrh17Ypc/Ny5azd0DvH21VW3f/GT+PPdKq+fmTtLDAOxp9bm6S7JHsDwkAAICzK85yyGa1yO0xVF7rNLscAAAAAAB86BifeAjGgTDl9hhas27/aaG4JN+x3+yqG/Wx8dERumLKcBBeku1QVIR13GoFAABAeIqJsmlaerwONnTow6ZO9fS5FRPFGywBAAAAAOarGuwYj7BalJ8Sa3I1CASCcSBMba9u9RuffjZJsZG6cop3f/CFBSkqnpx41j3IAQAAgPNVmuPQwYYOuT2G9tc7NT8/2eySAAAAAAATnMdjqGqwYzwvJVaRNpoDJwKCcSBMNXWcXyj+8C2X6SvXFslKEA4AAIBxUJqTpF/tqJUkldcSjAMAAAAAzFfX1iPXgEeSVJjKGPWJgrc/AGEqPcF+XtfNzZ1EKA4AAIBxU5rj8K0r2GccAAAAABAE/PYXT48zsRIEEsE4EKYWFCQrM/HM4bhFUpbDrgUFdOwAAABg/FyWmaBIm/eNmHtq28wtBgAAAAAADe8vLklFaXSMTxQE40CYslktWjona9RzQ/3hq5cWs5c4AAAAxlV0hE0zsxIlSVUtXero7Te5IgAAAADAROfXMZ5Gx/hEQTAOhCnDMLTlyMlRz2U67Fr7xXm6ZfbowTkAAAAwlkqyvePUDUPaW9ducjUAAAAAgIluZDDOHuMTR4TZBQAYHxsPNulAvfdFx9LsRK365Ew1dbiUnuAdn06nOAAAAAKlNMehF7d51xV1bSorSjG3IAAAAADAhDY0Sj0lLkqT4qJMrgaBQjAOhCHDMPSfG4/4Pl5x4zSVFaWaWBEAAAAmstKcJN+6vNZpXiEAAAAAgAmvvbdfTR0uSVIhY9QnFEapA2Hor0dOavfxNknSjMwELZ6ZYW5BAAAAmNCmpccrOsL76yfBOAAAAADATEPd4pJUlMYY9YmEYBwIQz9560PfevkNU2VlbDoAAABMFGGzatbkRElSTWu32rr7TK4IAAAAADBRVY3YX5xgfGIhGAfCzPtHW/VeVaskqTA1Tp8syTK5IgAAAMB/nHpFHV3jAAAAAABzVI4MxtMZpT6REIwDYeYnI/YWX3Z9kWx0iwMAACAIlOY4fGvGqQMAAAAAzFLZNDxKvTCVjvGJhGAcCCPltW3afLhZkpSdFKPbLs82uSIAAADAyz8YbzOvEAAAAADAhDbUMR5lsypnUozJ1SCQCMaBMPLkW/7d4pE2/hMHAABAcChMjVdclE2SVEHHOAAAAADABANuj46d7JYkTUmNVQQ5yoTCVxsIE4caOvTGvkZJUnpCtD43P8fkigAAAIBhVqtFs7O9XeMnnL1q7nCZXBEAAAAAYKKpPdWjPrdHEmPUJyKCcSBMjOwWf/DaQtkjbSZWAwAAAJxuTm6Sb11R12ZaHQAAAACAiWlojLokFaXHmVgJzEAwDoSB6pYuvVp+QpKUHBelOxfmmVwRAAAAcLqS7JH7jDNOHQAAAAAQWFXNXb51URod4xMNwTgQBtZuOiKP4V3ff3WBYqMizC0IAAAAGEVpDsE4AAAAAMA8fh3jBOMTDsE4EOJqT3Xrt7vqJEkJ9gjdXZZvckUAAADA6PKSY+WIiZTkDcYNwzC5IgAAAADARDIyGC9MY5T6REMwDoS4n22u0sBgu/h9H5uiRHukyRUBAAAAo7NYLL6u8ZZOlxrae02uCAAAAAAwkVQOjlJPT4hWAnnKhEMwDoSwpvZevbLjuCQpNsqm+64qMLkiAAAA4OxG7jO+5zjj1AEAAAAAgXGqq0+tXX2SGKM+URGMAyHs6Xeq1DfgkSTdvShfk+KiTK4IAAAAOLvSnCTfuqKuzbQ6AAAAAAATS1ULY9QnOoJxIES1dvXphfdqJElREVbdfw3d4gAAAAh+Q6PUJe8+4wAAAAAABEJlU5dvTcf4xEQwDoSoZ7dUq6ffLUn6wpW5Sk+wm1wRAAAAcG5ZDrtS472TjirqnDIMw+SKAAAAAAATQeWIjvGidILxiYhgHAhBzp5+Pf/uUUlSpM2iB68rMrcgAAAA4DxZLBbfOPW27n4db+0xtyAAAAAAwIQwsmO8MJVR6hMRwTgQgv5761F1uAYkSbfPy1F2UozJFQEAAADnryR7xDh19hkHAAAAAARAVbO3Yzw6wkquMkERjAMhpss1oGe2VEuSrBbpIbrFAQAAEGLYZxwAAAAAEEh9Ax4da+2WJBWmxctqtZhcEcxAMA6EmJe21ehUd78k6dNzJmsK4z4AAAAQYkr8gvE28woBAAAAAEwINa3dcnsMSVJRGrnKREUwDoSQ3n63fv5Ole/j5TdMNbEaAAAA4OKkJ9iV5bBLkvbWtcsz+OIEAAAAAODM3B5D71Wd1J8Ptuq9qpO+oBfnVjk4Rl3ydoxjYoowuwAA5+/XO46rucMlSbplVqamZSSYXBEAAABwcUqyHap39qrTNaCqli5NTeeFCQAAAAA4k/V767Vm3X7VO3sHj1Qry2HX6qXFumV2lqm1hYKRwTgd4xMXHeNAiOgb8OipzcPd4itupFscAAAAoWtObpJvXVHXZlodAAAAABDs1u+t17IXdo0Ixb0anL1a9sIurd9bb1JloaOqucu3LqJjfMIiGAdCxO8/qFNdW48k6YbL0jQ723GORwAAAADBq2TEz7N7jjtNrAQAAAAAgpfbY2jNuv0abWj60LE16/YzVv0c/Eep0zE+UTFKHQgBbo+hn2464vt4xY3TTKwGAAAAuHQjg/GKOoJxAAAAABjN9urW0zrFRzIk1Tt7dfX3Nio3JVbpCdFKG/wnPcHuXcdHKz0xWsmxUbJaLYErPkgYhqHKJm8wPtlhV2wU8ehExVceCAGvlp/Q0ZPdkqSywhTNz59kckUAAADApZkUF6W85FjVtHZr3wmnBtweRdgYagYAAAAAkjfMff/oKf3bnw+e1/X17b2qbz9zgC5JNqtFqfFRw2H5UHCeEH1aoB4TZRuLpxEUWjr71N47IEkqSmeM+kRGMA4EOY/H0JNvDXeLf429xQEAABAmSnIcqmntVm+/Rx82dWpmVqLZJQEAAACAqZw9/frdrlq9uK1GHzZ1nvsBg+yRVvX2e856jdtjqLHdpcZ21zk/X3x0hC8oH9l1nhbv342eHBclW5B3oVeNGKPO/uITG8E4EOT+vL9Rhxu9/9Oel5eksqIUkysCAAAAxkZptkOvlddLkipqnQTjAAAAACYkwzBUXuvUi9uO6Y97TpwWcFssknGGLcQtkjIddm15+Ea5Btxq6ehTU0evmjtcau50qandNbwePN7S2XfOPck7XQPqdA2ouqXrrNfZrBalxEWd3nkeH630RLvfMTNGmLs9ht7c3+j7eEpqbMBrQPAgGAeCmGF8tFt8miyW4H7nFQAAAHC+SnOSfOvyujb93ZW55hUDAAAAAAHW5RrQH3af0Evbj2lvXftp5xcUJOuuhXmyWqT//T+7JXn3FB8ylBasXlosm9Wi2KgI5aVEKC/l7OGvx2OotbtPzR0uNXUMBucdw8H5yH86XANn/Vxuj6Gmwc9zLnFRNm9YHh/t343+kVHuKXHRY9KFvn5vvdas2++3R/t/bDiizES7bpmddcmfH6GHYBwIYpsPN6uizilJmjU5UddflmZyRQAAAMDYmZ093CFeXus0sRIAAADg4rk9hrZVndSR2lZN7bRpYWFq0I+WhrkO1LfrxW3H9PsPTqjzI8Fzgj1Ct8/L0V0L8zQtI8F3PNJmPS3kzXTYtXpp8QWHvFarRanx0UqNj9bMczy0p8892HHeO0qQPiJE73Sdswu9q8+t6pauc3ahWy1SSvxo49ujlZbg34UeFz161Ll+b72WvbBLH62otatPy17YpbVfnEc4PgFdcDD+9ttv61//9V+1c+dO1dfX63e/+51uu+0233nDMLR69Wo9/fTTamtr01VXXaW1a9dq2rRpvmtaW1v1ta99TevWrZPVatXtt9+uH//4x4qPH57rX15eruXLl+v9999XWlqavva1r+lb3/rWpT1bIIQYhqGfbBzuFl9xw1S6xQEAABBWEuyRKkyLU1Vzlw7Ut8s14FZ0hM3ssgAAAIDzdnpHarWyLjKsRHjr7XfrtfJ6vbjtmHbVtJ12fk5uku5amKelpZMVE3X670W3zM7STcWZ2lbVoiO1zZqakxaQN2HERNmUlxJ7Xl3op7r7Rg/OO11qau9Vc+dgF3rv2bvQPYZ8n2N//dnri42y+XWbpyfYlRIfpV+8U31aKD7SmnX7dVNxJm9imWAuOBjv6urSnDlz9KUvfUmf/exnTzv//e9/X//xH/+h559/XgUFBXr00Ue1ZMkS7d+/X3a7XZJ01113qb6+Xm+++ab6+/t133336cEHH9RLL70kSWpvb9fNN9+sxYsX66mnnlJFRYW+9KUvKSkpSQ8++OAlPmUgNGyrbtWOY6ckSVPT47VkVqbJFQEAAABjb05Okqqau9TvNnS4oVMlOQ6zSwIAAADOy5k6UhucvXSkwqeyuVMvbavRb3bWytnT73cuNsqmz8zN1l0L8zQ7+9y/C9msFi0qTFFhvFvp6SmyBlGoa7ValBIfrZTz7EJv6RwKznvPEKS71NLp0sA5utC7+9w6erJbR092n3ethqR6Z6+2V7eqrCjlvB+H0HfBwfgnPvEJfeITnxj1nGEY+tGPfqRHHnlEn/nMZyRJ//Vf/6WMjAz9/ve/1+c//3kdOHBA69ev1/vvv68rrrhCkvSf//mf+uQnP6l/+7d/0+TJk/Xiiy+qr69Pzz77rKKiojRr1izt3r1bP/jBD84YjLtcLrlcw/sXtLd792LweDzyeDwX+jQR5DwejwzDCOuv7X9u/NC3/ur1hZIMec7xDQBjayLcZwgO3GsIBO4zBAr3Gi7U7MmJ+t0HdZKk3cdPadbkhHM8IrTus1CoEQAAABfO7TG0Zt3+UTtSDXn3fqYjdeLqG/Doz/sb9OJ7NdpadfK08zMyE3TXonzdNneyEuyRJlRorpgom3KTY5WbfH5d6EOd5k3truH1iFC96Ty60EfT1NF77osQVsZ0j/Hq6mo1NDRo8eLFvmMOh0MLFy7U1q1b9fnPf15bt25VUlKSLxSXpMWLF8tqtWrbtm36m7/5G23dulXXXnutoqKifNcsWbJE//Iv/6JTp05p0qRJp/3ZTzzxhNasWXPa8ebmZvX2cmOHG4/HI6fTKcMwZLVazS5nzO2t79Rfj3i/WWY7orQgM0JNTU0mVzXxhPt9huDBvYZA4D5DoHCv4ULlxg0Hx9uPNOimAvs5HxNK91lHR4fZJQAAAGAcbK9u9dvr+aOGOlK/v/6g7r+mQOkJ5/45F6HveGu3/md7jX6147haOvv8zkVFWPWp0izdtTBf8/KS2Dr1PIzsQp9xjqG6vf1uX0i+5cMW/fAvh8/5+fnvcuIZ02C8oaFBkpSRkeF3PCMjw3euoaFB6enp/kVERCg5OdnvmoKCgtM+x9C50YLxVatWaeXKlb6P29vblZubq7S0NCUmJl7iM0Ow8Xg8slgsSktLC/oXwi7GS+trfOsVN07X5MyMs1yN8RLu9xmCB/caAoH7DIHCvYYLdVVSiqyWQ/IY0pHWvtN+XxxNKN1nQ1uKAQAAILxUt3Se13U/e7tKP3u7SqU5Dt04I103zkjX7MmOoBqBjUsz4PborUPNenHbMW0+3CzjI2MEClPjdOfCPH1ufo6SYqNG/yS4ZPbI4S70ublJevn9GjU4e0ed6mCRlOmwa0FBcqDLhMnGNBg3U3R0tKKjo087brVag/6FElwci8USll/ffSec2niwWZKU5bDr9vm5YfccQ0m43mcIPtxrCATuMwQK9xouRJzdqukZCTrY0KHDjZ1yDRiKibKd83Ghcp8Fe30AAAC4MB6Pod/srNU/v37ggh5XXutUea1TP/rLh0pLiNYNl6XpxhkZunpaquKjwyaqmVAanL165f3jevn9mtOmB0RYLVoyO1N3LcxTWWEK3eEBZrNatHppsZa9sEsWyS8cH/pKrF5azDYHE9CY/t82M9M7x6CxsVFZWVm+442NjZo7d67vmo+OhB4YGFBra6vv8ZmZmWpsbPS7ZujjoWuAcPXTtyp964euK1JUBC+kAQAAILyV5jh0sKFDbo+h/fXtmp9/+pQwAAAAwGwH6tv16O/3asexU+e81iIpOT5Kd1yRq7cONetAfbvvXHOHS7/aUatf7ahVlM2qhYXJvm7y/JS4cXwGuFQej6F3jrToxfeOacPBJrk9/v3IOZNidOfCPP3t/FylJZzezInAuWV2ltZ+cZ7WrNvv98aFTIddq5cW65bZWWd5NMLVmAbjBQUFyszM1IYNG3xBeHt7u7Zt26Zly5ZJksrKytTW1qadO3dq/vz5kqSNGzfK4/Fo4cKFvmv+8R//Uf39/YqMjJQkvfnmm7rssstGHaMOhIsjTR16fW+9JCk1Plp3XJlrckUAAADA+CvJSdKvdtRKkipq2wjGAQAAEFQ6XQP60ZuH9ct3j/oFoVfkT9KOY6fO2JH6T7fN1i2zs/StW2boRFuP3jrUpLcONmnLkRb19nskSX1uj975sEXvfNiiNev2qygtTh+fmaEbLkvXFVMmKdJG41QwaOl06dc7avU/22tU09rtd85qkT4+M0N3LczTtdPSGJMfRG6ZnaWbijO1vbpVTR29Sk/wjk+nU3ziuuBgvLOzU0eOHPF9XF1drd27dys5OVl5eXn6xje+oe9+97uaNm2aCgoK9Oijj2ry5Mm67bbbJEkzZ87ULbfcogceeEBPPfWU+vv7tWLFCn3+85/X5MmTJUl33nmn1qxZo/vvv18PP/yw9u7dqx//+Mf64Q9/ODbPGghSP32r0rf/yAPXFMgeee4RkgAAAECoK812+NbltU4TKwEAAACGGYah1ysa9Pir+9TY7vIdL0yN0+Ofma2rp6Vq/d768+pInZwUo7sW5uuuhfnq7Xdra+VJbTzYpI0Hm1TX1uO7rrK5S5XNVfr521VKsEfo2ulp+viMdF1/WbqS49ifOpAMw9C26la9uK1G6/fWq9/t3x2ekRitz1+ZpzuuzNXkpBiTqsS52KwWlRWlmF0GgsQFB+M7duzQDTfc4Pt45cqVkqR7771Xzz33nL71rW+pq6tLDz74oNra2nT11Vdr/fr1stvtvse8+OKLWrFihT7+8Y/LarXq9ttv13/8x3/4zjscDv35z3/W8uXLNX/+fKWmpuqxxx7Tgw8+eCnPFQhqNSe79Yc9JyRJSbGRumtRvskVAQAAAIExIytBkTaL+t2GyusIxgEAAGC+6pYuPfaHvXrnwxbfsegIq1bcMFUPXleo6AhvU9NQR+q2qhYdqW3W1Jw0LSxMPWtHqj3SphtmpOuGGel63DB0uLFTGw426q2DTdp57JSGmtI7egf0Wnm9Xiuvl8UiXZ6bNDhyPUMzsxLYt3qcOLv79f921erFbcdU2dx12vlrp6fproV5+viMdEXQ0Q+ElAsOxq+//noZhnHG8xaLRY8//rgef/zxM16TnJysl1566ax/Tmlpqd55550LLQ8IWWs3V/rG8Nz3sQLFR4/pTgcAAABA0IqOsGlGZqIq6pyqbO5Up2uAn4cBAABgit5+t9ZuqtTazZXqG/D4jt9wWZrWfHq28lJiT3uMzWrRosIUFca7lZ6eckGjtC0Wiy7LTNBlmQn66vVTdaqrT5sPN2vjwSZtOtSk9t4BSZJhSLtq2rSrpk3/9ufDynLYdcOMdH18Rro+VpSqmCimj14KwzC0+3ibXtxWo3V7Tsg14msvSSlxUfrbK3L1hQW57AMPhDBeaQCCQL2zR7/ZeVySFB8dof/1sSnmFgQAAAAEWEmOQxV1ThmGtLfOqUWFjLoDAABAYG061KTVf9ynYyeH95Ce7LBr9adn6ebijIB0aE+Ki9Jtl2frtsuzNeD2aFdNm6+b/HBjp++6emevXtpWo5e21Sg6wqqPFaXoxsEu9JxJp4f3GF2na0B/2F2nF9+r0f769tPOLyxI1l2L8rVkVoZvSgCA0EUwDgSBn22u8u1Pck9ZvhyxkSZXBAAAAATWnByHXtrmXVfUEowDAAAgcE609eg7r+7Xn/Y2+I5FWC26/5oCff3j0xQbZU6UEmGzakFBshYUJGvVJ2bqeGu33jrUpA0HmrS16qSvo9014NFbh5r11qFm6Q/7NCMzwddNfnnepLOOdZ+o9p1w6qVtNfr9B3Xq6nP7nUu0R+j2+Tm6a2GepqYnmFQhgPFAMA6YrLnDpZffr5Ek2SOtuv/qApMrAgAAAAKvJDvJt2afcQAAAARCv9ujX/61Wj/6y4fqHhGOLihI1ndvm63pGcEViuYmx+qesim6p2yKuvsG9NcjJ7XxYKM2HmxSY7vLd93Bhg4dbOjQ2k2VSoqN1PXT03TjzAxdNy1tQjdl9fS59Wr5Cb24rUa7j7eddv7yvCTdtTBft5ZkMZoeCFME44DJntlSrd5+7zv77lyQr5T4aJMrAgAAAAJvWka8oiOscg14VF7bZnY5AAAACHPvH23VI7/bq0ONHb5jKXFR+sdbZ+pvLs8OyNj0SxEbFaGbijN0U3GGDMPQvhPt2niwSRsPNmlPbZsM74BStXX36/e7T+j3u0/IZrVofv4k3TjYTT41PT7on+dYONLUoRe31ej/7az17dk+JC7Kptsuz9adC/M0a7LDpAoBBArBOGCitu4+/ffWo5KkKJtVD15baG5BAAAAgEkibVbNmpyoXTVtOnayW87u/gndzQIAAIDxcbLTpSf+dFC/2VnrO2axSF9cmK//c/NlIfkzqMVi0exsh2ZnO/S/Pz5NLZ0ubTrUrI0HG/XO4RZ1uLxhsNtjaHt1q7ZXt+p7fzqonEkx+vjgvuSLClNkjwyfLmnXgFtv7GvUi+8d07bq1tPOz8xK1BcX5ekzc7MVH01UBkwU/NcOmOiXfz3q27/kb6/IUabDbnJFAAAAgHlKc5K0q6ZNklRR59TV01LNLQgAAABhw+Mx9PL7x/Uv6w/K2dPvO16S7dB3b5utOblJ5hU3xlLjo/W5+Tn63Pwc9Q14tONoq6+bvKqly3dd7akePb/1mJ7fekwxkTZdPS1VN85I140z0pWRGJqvVdec7NZL22v06x3HdbKrz+9cdIRVS+dM1l0L8zQ3N2lCdMsD8EcwDpiko7dfz717VJJks1r00HVF5hYEAAAAmKwke3h04Z7aNoJxAAAAjIm9dU794+/3as+IfaUT7BH61pLLdOfCfNms4RuQRkVY9bGpqfrY1FQ98qliVbd0DYbkjdpe3ap+t3fmek+/W2/ub9Sb+xslSbMmJ+rjM9J148wMlWY7ZA3iv6MBt0cbDjbpxW01evtw82nni9LidNfCfN0+LyckJwIAGDsE44BJXnivxvfOxNvmZis3OdbkigAAAABzzckdDsYrap0mVgIAAIBw0N7brx/8+bD+a+tReYzh45+9PFurPjlTaQnR5hVnkoLUON1/dYHuv7pAHb392vJhizYebNJbh5rU0jncYb3vRLv2nWjXf2w8otT4KF1/mbeT/JppqUqwB0e4XO/s0f9sP65X3q9RY7vL71ykzaJbZmfproV5WliQTHc4AEkE44Apevrc+sU7VZK8+9d89Qa6xQEAAICC1HjFRdnU1edWRR3BOAAAAC6OYRj6454T+u5rB9TcMRyYTk2P13c+M1tlRSkmVhc8EuyR+kRJlj5RkiWPx1BFnVMbBrvJ99a1+65r6ezTb3bW6jc7axVhtWhBQbJv5HphWnxAa3Z7DL39YbNefK9GGw82+r3hQZJyk2N054J8/e0VOUqNn3hvfABwdgTjgAlefr/Gt7/JrSVZKgrwDw8AAABAMLJZLZqV7dD26lbVtfWopdPFi1kAAAC4IEeaOvXYH/bq3cqTvmMxkTb9749P0/1XFygqwmpidcHLarVoTm6S5uQmaeVN09XY3qu3Bvcl33KkRd19bknSgMfQu5Un9W7lSX33tQMqSI3zheRXTkket7/f5g6XfrXjuP5ne41qT/X4nbNZLVo8M113LszXNVNTg3rsOwBzEYwDAeYacOtnm6t8Hy+/YaqJ1QAAAADBZU6ONxiXvOPUb5iRbnJFAAAACAU9fW795K0P9fO3q3z7ZkvSTcUZWr20WDmT2MryQmQk2vX5BXn6/II8uQbc2lbVqo0Hm7ThYKOOtw4H09UtXXpmS7We2VKt+OgIXTMtVTfOSNf1l6Wfc1S922Noe3Wrmjp6lZ5g14KCZL/93g3D0Naqk3pxW43+vK/B7+sqSZmJdn1hQZ7uuDJXmQ772P4FAAhLBONAgP2/nXVqaO+VJC2emaGZWYkmVwQAAAAEj5KcJN96T20bwTgAAADOacOBRq3+4z6/TuKcSTH69tJZWlycYWJl4SE6wqZrp6fp2ulpWr20WJXNndpwwNtNvuPYKbkH55l3ugb0p70N+tPeBlksUmlOkj4+2E0+a3Ki3z7f6/fWa826/ap39vqOZTnsWr20WIsKU/SbnbV6aVuNqlq6/GqxWKTrpqfproX5uuGyNEXYmAAA4PwRjAMBNOD2aO3mI76PV9xItzgAAAAwUmm2w7euqGWfcQAAAJxZ7alurVm3X2/ub/Qdi7RZ9JVri7T8hqmKibKZWF14slgsmpqeoKnpCfrKdUVydvfr7Q+btfFgk9461KS27n5JkmFIe463ac/xNv3gzcPKSIzWDZd5Q/LuPre++cpufWR7cNU7e/XQC7sUYbVo4CObh6fGR+nvrsjVFxbkKTeZ7n8AF4dgHAigP+454Rszc820VM3NTTK3IAAAACDI5KfEKtEeofbeAZXXOWUYhl9nCQAAANA34NEvtlTpPzZ8qN5+j+/4x4pS9PhnZmtqeryJ1U0sjthILZ0zWUvnTJbbY2j38VO+bvKDDR2+6xrbXXr5/eN6+f3j5/ycI0PxssIU3bUoTzcXZ7I/PIBLRjAOBIjbY+jJt4a7xb924zQTqwEAAACCk8ViUWlOkrYcaVFzh0sN7b3KcsSYXRYAAACCxLuVLXr093tV2Tw8YjstIVqP3DpTn54zmTdVmshmtWh+frLm5yfrW7fMUF1bj9466A3J/3qkRa4Bz7k/yaBPzs7Uypsv400OAMYUwTgQIOv3Nvh+WFswJVkLCpJNrggAAAAITiU5Dm050iJJKq91EowDAABATR29euL1g/rdB3W+Y1aLdE/ZFK28eboS7ZEmVofRZCfF6IuL8vXFRfnq6XNra1WLnnmnWn+tPHnOxy6ZnUkoDmDMMXcCCADDMPSTt9hbHAAAADgfc3LYZ/xiPPnkk5oyZYrsdrsWLlyo7du3n/Hap59+Wtdcc40mTZqkSZMmafHixWe9HgAAwCxuj6H/2npUH//3zX6h+NzcJP1xxdX69qdnEYqHgJgom26ckaEV5zlJNT3BPs4VAZiICMaBANh4sEkH6tsleV/ku2ZaqskVAQAAAMGrJCfJt95T22ZaHaHklVde0cqVK7V69Wrt2rVLc+bM0ZIlS9TU1DTq9Zs2bdIXvvAFvfXWW9q6datyc3N18803q66ubtTrAQAAzLDneJtue/KveuwP+9TROyBJcsRE6p//pkS/XfYxzc52nOMzINgsKEhWlsOuMw28t0jKctiZuApgXBCMA+PMMAz958bhbvHlN0xlnxsAAADgLCY77EqNj5IkVdQ5ZRiGyRUFvx/84Ad64IEHdN9996m4uFhPPfWUYmNj9eyzz456/YsvvqivfvWrmjt3rmbMmKFf/OIX8ng82rBhQ4ArBwAAOJ2zu1+P/L5Ct/30r6qoG54g9Lfzc7Tx/7tOdy7Mk9XKa6yhyGa1aPXSYkk6LRwf+nj10mLZ+PoCGAfsMQ6Ms78eOandx9skSTMyE7R4Zoa5BQEAAABBzmKxqCTbobcONautu1+1p3qUmxxrdllBq6+vTzt37tSqVat8x6xWqxYvXqytW7ee1+fo7u5Wf3+/kpPP3Jnjcrnkcrl8H7e3e6dieTweeTyei6wewcrj8cgwDL62GFfcZwgU7rXQYRiGfvfBCT3xp4M62dXnOz49I17f+cwsXTnF+7NKMH4tuc/O383FGXryzsv1+KsH1NDe6zue6bDr0Vtn6ubiDP4ez4J7DYESKvfahdRHMA6Ms//c+KFvvfyGqbyTEQAAADgPJTlJeutQsyTvOHWC8TNraWmR2+1WRob/m3AzMjJ08ODB8/ocDz/8sCZPnqzFixef8ZonnnhCa9asOe14c3Ozent7R3kEQpnH45HT6Z3YYLUycBDjg/sMgcK9FhqqTvboXzfW6IO6Tt+xmEirvrxosu6Ym64I28AZt4kJBtxnF2ZeulX/738Va3ddp0529SslLlJzs+Nls1qC+uscDLjXECihcq91dHSc97UE48A4ev9oq7ZVt0qSClPj9MmSLJMrAgAAAELDnJzh/SIrap36VOlkE6sJb9/73vf08ssva9OmTbLb7We8btWqVVq5cqXv4/b2duXm5iotLU2JiYmBKBUB5PF4ZLFYlJaWFtQvgiG0cZ8hULjXgluXa0D/ufGInv3rUQ14hrfQ+cTsTD1y6wxlOWJMrO78cZ9dnKxMJqxeKO41BEqo3Gtn+z32owjGgXH0kxF7iy+7voh9UQAAAIDzVJI9HIyX1zrPciVSU1Nls9nU2Njod7yxsVGZmZlnfey//du/6Xvf+57+8pe/qLS09KzXRkdHKzo6+rTjVqs1qF8kwcWzWCx8fTHuuM8QKNxrwccwDL2xr1GPr9unE87h6TP5KbFa8+lZuv6ydBOruzjcZwgU7jUESijcaxdSW/A+CyDElde2afNh7+jH7KQY3XZ5tskVAQAAAKEjPdGuzETvu7731jnlGdE9BH9RUVGaP3++NmzY4Dvm8Xi0YcMGlZWVnfFx3//+9/Wd73xH69ev1xVXXBGIUgEAACRJNSe79aXn3tdDL+z0heJREVZ9/ePT9MY3rg3JUBwAEPzoGAfGyUe7xSNtvA8FAAAAuBClOQ417O9Vh2tA1Se7VJQWb3ZJQWvlypW69957dcUVV2jBggX60Y9+pK6uLt13332SpHvuuUfZ2dl64oknJEn/8i//oscee0wvvfSSpkyZooaGBklSfHy84uP5ewYAAOPDNeDWzzdX6SdvHZFrwOM7fs20VD3+mdkqSI0zsToAQLgjGAfGwaGGDv15v3eMYUZitD43P8fkigAAAIDQU5rj8P1cXVHrJBg/izvuuEPNzc167LHH1NDQoLlz52r9+vXKyPDu2VhTU+M3Xm7t2rXq6+vT5z73Ob/Ps3r1an37298OZOkAAGCCeOfDZj32h32qbunyHctMtOuxpcX6xOxMWSxsQwkAGF8E48A4ePKt4W7xB64plD3SZmI1AAAAQGgqyUnyrffUtrE90TmsWLFCK1asGPXcpk2b/D4+evTo+BcEAAAgqbG9V995db9eLa/3HbNZLfrSVVP09cXTFR9NTAEACAy+4wBjrKq5U6+Wn5AkJcdF6c6FeSZXBAAAAISm0myHb11R6zSxEgAAAFyoAbdH/7X1mH7w5mF1ugZ8x+fnT9J3b5utmVmJJlYHAJiICMaBMbZ2U6U8hnd9/9UFio3iPzMAAADgYkyKi1JucoyOt/Zo34l2Dbg9irBZz/1AAAAAmGrnsVN65Pd7daC+3XdsUmykVn1ypj43L0dWK2PTAQCBR2IHjKHaU9363Qd1kqREe4TuKcs3uSIAAAAgtJVmJ+l4a496+t060typGZl0FgEAAASrU119+pf1B/Xy+8f9jn9hQa6+tWSGJsVFmVQZAAAE48CY+tnmKg0Mtov/r49NUYI90uSKAAAAgNBWmuPQaxXe/SjLa50E4wAAAEHI4zH0653H9b0/HdSp7n7f8eKsRH33b2ZrXt4kE6sDAMCLYBwYI03tvXplh/edkLFRNt13VYHJFQEAAAChryTHf5/xv7si18RqAAAA8FEH6tv1yO/3auexU75j8dER+v9unq67F+WzFQ4AIGgQjANj5Ol3qtQ34JEk3b0on7FAAAAAwBiYnT0cjJfXtplXCAAAAPx0ugb0wzcP67l3j8o9OEVTkpbOmaxHbp2pjES7idUBAHA6gnFgDLR29emF92okSVERVt1/Dd3iAAAAwFhItEeqMC1OVc1dOlDfob4BjyJoOgIAADCNYRh6raJe33l1vxrbXb7jhalxevwzs3X1tFQTqwMA4MwIxoEx8OyWavX0uyVJX7gyV+kJvBsSAAAAGCul2Q5VNXepz+3R4cYOFWclmF0SAADAhFTd0qXH/rBX73zY4jsWHWHV126cqgeuLVR0hM3E6gAAODuCceASOXv69fy7RyVJkTaLHryuyNyCAAAAgDBTkpOk3+8+IUnaU9tGMA4AADCO3B5D26tb1dTRq/QEuxYUJKvf7dFPN1XqqU2V6nN7fNfeOCNdaz49S7nJsSZWDADA+SEYBy7Rf289qg7XgCTp9nk5yk6KMbkiAAAAILzMyRneZ7yi1qkvXJlrYjUAAADha/3eeq1Zt1/1zl7fsUmxkbJZLWrp7PMdm+ywa/WnZ+nm4gxZLBYzSgUA4IIRjAOXoMs1oGe2VEuSrBbpIbrFAQAAgDFXPDlRVovkMaTyWqfZ5QAAAISl9XvrteyFXTI+cvxUd79vHWG16MvXFOp/f3yqYqOIFwAAoYXvXMAleGlbje8Hw0/PmawpqXEmVwQAAACEn9ioCE1LT9Chxg4dauxQb7/b7JIAAADCittjaM26/aeF4iNF2Sz644qrNSMrMWB1AQAwlqxmFwCEqt5+t37+TpXv4+U3TDWxGgAAACC8lQ6OU3d7DB2obze5GgAAgPCyvbrVb3z6aPrchl/3OAAAoYZgHLhIv95xXM0dLknSJ2ZnalpGgskVAQAAAOGrdMQ+44xTBwAAGDuHGzv0w78cPq9rmzrOHp4DABDMGKUOXIS+AY+e2ky3OAAAABAoJTlJvnVFXbs+MTXWvGIAAABCnGEY2l7dqp+9XaWNB5vO+3HpCfZxrAoAgPFFMA5chN9/UKe6th5J0g2XpWl2tuMcjwAAAABwKWZmJSjSZlG/21BFnVNSptklAQAAhBy3x9Cb+xv01OYq7T7e5nfOIp1xj3GLpEyHXQsKkse5QgAAxg/BOHCBBtwe/XTTEd/HK26cZmI1AAAAwMQQHWHTZZkJ2lvXriPNnerqc5tdEgAAQMjo7Xfrt7vq9PQ7Vapu6fI7N9lh1/3XFColLkrffGW3JP+A3DL479VLi2WzWgQAQKgiGAcu0GsV9Tp6sluS9LGiFM3Pn2RyRQAAAMDEUJqTpL117TIM6XBTtwpyzK4IAAAguDm7+/XCtmP65V+PqqXT5XduRmaCvnJdoT5VOlmRNqskyR5p1Zp1+1XvHN5LPNNh1+qlxbpldlZAawcAYKwRjAMXwOMx9ORbI7rF2VscAAAACJjSbIdeGlwfaOrWElOrAQAACF51bT16dku1/md7jbo/MmnnY0Up+sp1Rbp2WqosFv8O8FtmZ+mm4kxtr25VU0ev0hO849PpFAcAhAOCceAC/Hl/ow43dkqS5uUlqawoxeSKAAAAgImjJMfhW288fEqLpp/UwsJUXqgFAAAYdLChXT/fXKU/7jmhAc/wQHSrRfpESZa+cm2hSnOSzvo5bFYLr3sCAMISwThwngzD0E/e+tD38ddunHbaOyoBAAAAjJ+R+2HubejSnb/YrixGewIAgAnOMAxtrTqpn79dpU2Hmv3ORUdY9XdX5OrL1xQoPyXOpAoBAAgOBOPAedp8uFl769olSbMmJ+r6y9JMrggAAACYONbvrdfXXvrgtOMNzl4te2GX1n5xHuE4AACYUNweQ+v3Nuhnb1eqvNbpdy4pNlL3lE3RvWX5SomPNqlCAACCC8E4cB4Mw9B/bvTfW5xucQAAACAw3B5Da9btlzHKOUOSRdKadft1U3EmY9UBAEDY6+1369c7a/WLd6p07GS337nspBg9cE2B/u7KXMVG8fI/AAAj8Z0ROA/vVbVq57FTkqSp6fFaMivT5IoAAACAiWN7davqnb1nPG9Iqnf2ant1K/thAgCAsHWqq0///d4xPf/uUZ3s6vM7N2tyor5yXZE+OTtTETarSRUCABDcCMaB8/DkW/7d4la6UAAAAICAaeo4cyh+MdcBAACEkuOt3XpmS7Veef+4evrdfueumZaqr1xbpKumpjDhEgCAcyAYB85hV80pbTnSIknKS47Vp0rZtxAAAAAIpPQE+5heBwAAEAr2nXDq529X6dXyerk9w5vKWC3Sp0on68FrCzU722FihQAAhBaCceAcnhyxt/hXry9iFBEAAAAQYAsKkpXlsKvB2TvqPuMWSZkOuxYUJAe6NAAAAsrtMbS9ulVNHb1KT/B+77Mx2TCsGIahdytP6qnNlXrnwxa/c/ZIqz5/ZZ7uv7pAucmxJlUIAEDoIhgHzmLfCac2HGySJGU57PrsvByTKwIAAAAmHpvVotVLi7XshV2ySH7h+FAUsHppMcEAACCsrd9brzXr9qveObx1SJbDrtVLi3XLbCYchroBt0ev723Qz9+u1N66dr9zyXFRurdsiu4uy1dyXJRJFQIAEPoIxoGz+Olblb71Q9cVKSqCbnEAAADADLfMztLaL847LRDIJBAAAEwA6/fWa9kLu06bnNLg7NWyF3Zp7Rfn8b0wRHX3DejXO2r19DtVqj3V43cuLzlWD1xToM/Nz1VMlM2kCgEACB8E48AZHGnq0Ot76yVJqfHRuuPKXJMrAgAAACa2W2Zn6abiTG2ratGR2mZNzUnTwsJUOsUBAGHN7TG0Zt3+UbcTMeSdnrJm3X7dVJzJ98QQ0trVp+ffPar/2npUp7r7/c6VZDv0lesKdcusTLZ1BABgDBGMA2fw07cqZQz+xvHANQWyR/KuTAAAAMBsNqtFiwpTVBjvVnp6iqwEAACAMLe9utVvWspHGZLqnb3aXt2qsqKUwBWGi1Jzslu/2FKlX+04rt5+j9+566an6SvXFaqsMEUWCz/jAAAw1gjGgVHUnOzWH/ackCQlxUbqrkX5JlcEAAAAAACAiaip48yh+Ehr1u3TzbMydXleki7PTVJSLHtRB5OKWqd+9nalXq+ol2dE+7/NatGn50zWA9cUqnhyonkFAgAwARCMA6NYu7lS7sGfUL90VYHio/lPBQAAAAAAAIHV5RrQG3sbzuvagw0dOtjQ4fu4MDVOc/OSdHneJF2em6QZmQmM5Q4wwzD09oct+vnblfrrkZN+52KjbPr8lXn60tVTlDMp1qQKAQCYWEj7gI+od/boNzuPS5LioyN0b9kUcwsCAAAAAADAhPOX/Y167A97deIsY9SHWC3y60KWpKqWLlW1dOm3u+okSTGRNpXkOAY7yifp8rwkZSTax6P0Ca/f7dHrFfV6anOVDtS3+51LjY/S//rYFH1xUT5d/QAABBjBOPARP9tcpX639zeJe8ry5YiNNLkiAAAAAAAATBQNzl59+4/7tH7fcKd4hNWiAY8hi7x7ig8Z2oX6yTvnaXa2Qx8cb9MHNae0+3ib9tW1q889vId1T79b26tbtb261XdsssPu7SjPS9LleUmaNdkhe6RtfJ9gGOtyDeiV94/rmS3Vqmvr8Ts3JSVWD1xbqNvn5fB3DACASQjGgRGaO1z6n+01kiR7pFX3X11gckUAAAAAAACYCNweQy+8d0z/+sYhdboGfMevnpqq7942Wwcb2rVm3X7Vj+ggz3TYtXppsW6ZnSVJyk2O1afnTJYkuQbc2n+iXR/UtPkC89pT/mHtCWevTlTU67WKeklSpM2i4qzE4bA8d5Jyk2NksViEM2vpdOn5d4/qv7Yek7On3+/cnNwkLbuuUDcVZ8pm5e8RAAAzEYwDIzyzpVquAe87ae9amK+U+GiTKwIAAAAAAEC423fCqf/72wrtqXX6jqXERenRTxXrM3Mny2KxaEpqnG4qztT26lY1dfQqPcGuBQXJZwxboyNsgwH3JN+xpo5e7R4RlJfXOtXd5/ad73cb2lPr1J5ap557d7iOywf3Kp+bm6TSHIcS7ExYlKSjLV16+p0q/WZnre81xSE3zkjXV64t1IKCZN5YAABAkCAYBwa1dffpv7celSRF2ax68NpCcwsCAAAAAABAWOvuG9AP3zysZ/96VO4Rm4R//spc/cMnZpy2B7XNalFZUcpF/3npCXbdPCtTN8/KlCQNuD063Nip3YNB+QfH23SkqdPvMSe7+vSXA036y4EmSZLFIk1PT/CNX788b5KmpsXLOoG6ofccb9PP3q7Un/Y2yBgx2z7CatFn5mbrwWsLdVlmgnkFAgCAURGMA4N++dej6hp8h+zfXpGjjES7yRUBAAAAAAAgXG082KhHf7/Pby/qqenx+ue/KdGCguSA1BBhs6p4cqKKJyfqzoV5kiRnT7/2HG8bHMF+Sh/UtPmNBzcM6VBjhw41dujl949LkhKiIzQnN8kXls/NnaTkuKhR/8xQZRiGNh1u1s82V+q9qla/c3FRNt25ME/3XVWgyUkxJlUIAADOhWAckNTR269f/rVakvedtw9dV2RyRQAAAAAAAAhHje29WrNun16vaPAdi4qw6ms3TNVXritSVITVxOokR0ykrp2epmunp0nyBsLVLV2DXeXesPxAfYdfh3uHa0BbjrRoy5EW37H8lFhdnpvk2698Rmai6c/tYvQNeLRuzwn9/O0qHWrs8DuXlhCt+66aorsW5ssRw3h5AACCHcE4IOmF92rU3jsgSfqby7OVmxxrckUAAAAAAAAIJ26PoZe2HdP31x9Sh2vAd/yqqSn67m0lKkiNM7G6M7NYLCpMi1dhWrw+Oy9HktTT51ZFndM7fr2mTbtqTqmpw+X3uGMnu3XsZLd+v/uEJCk6wqqSbIdv/PrleUnKcgRvd3Wna0Avb6/RM1uqVe/s9TtXmBqnB68t1G2XZ8seaTOpQgAAcKEIxjHh9fS59Yt3qiR590hadj3d4gAAAAAAABg7+0+0///s3Xd4FFXbx/HfbiqkAWkEElLoTZr0rigqgiBIUZRiQYo8qI+FR18Re8MOIhYQQSkKKFhRQbr0XgSS0CGhJaGk7c77R8jKkgAJJrubzfdzXbncOdPumT3BnLnnnKP/zd2ijQdO28oq+Hnr/26vre4NK8tkKlnzc5fx9lCz2Aq2Id8Nw9CRlPScHuUX5irfcihFmdlW2z4Z2Vat3XdKa/edkpQzcmPFQN8LQ6/nJMvrVw5SGW/nJpqT0tI1ZXmipq3aZ+tIk6txlXIa0r6qbqodXqrmVAcAwF2QGEep9/Xq/TpxNlOS1KV+hKqG+js5IgAAAAAAALiDc5nZeu+33fp0WYLd0OO9r4/U6Ftrq7ybzMNtMplUqVwZVSpXRl2ui5CUMwT5zqOpdsnyfSfO2e13NDVdP209qp+25gwr72E2qXZEgBpFlbf1LI8JLuuQFwf2Jp/Rp0vj9e26Q8q0WO3Wdaodrofbx+n6GMfM/Q4AAIoHiXGUahnZFk1aEm9bHt6xmhOjAQAAAAAAgLtYtCtJ/zdvqw6eOm8rqxrqp5d71FeLuGAnRuYY3p5mXRdZTtdFltOAVjGSpBNnMuzmKt90IEVnLhpW3mI1tPVQqrYeStWXq/ZJksqV9bKbq7xBVDkF+hZ8Pm+L1dBf8Se05+BJVTvjoeZxIfK4qLf3+v2n9PGfe/Xr9mMy/nl3QV4eJvVoVFkPtYtTtbCAf3czAACASyAxjlLt23WHdDQ1Z46gTrXDVTsi0MkRAQAAAAAAoCRLSk3X2AXb9cPmI7Yybw+zRtxQTUPax8nHs/TOSR3s76Mba4frxtrhknKS1nuTz9jmKt+w/7T+TkqzS1CfPpelRbuStWhXsqScqRCrhvrbJctrhAfYJbtz/bz1iMbO337RHOEJigjy1f91qSMfL7M+/jNeqxNP2u0T4OOpu1tU0eDWsQoP9C2W+wAAAJyDxDhKrSyLVRMW77Etj7iB3uIAAAAAAAC4Nlaroemr9+uNn3Yq7aJe0C3jgvVyj3qKY/q+PDzMJtUID1CN8AD1aVpFkpSWnqXNB1P+SZYfOK2TF6ZBlCTDkPYkndGepDOave6gJMnP20PXRZazDb/eMKqc1u07qaHT1su45JxHUtI17Kv1eWIJD/TR4Nax6te8SqF6pAMAgJKDxDhKre83HrYNZdW2eogaRpVzbkAAAAAAALiAqw07DCCvnUdTNXrOFm3Yf9pWVr6sl57tUkd3Nq7skDmy3UWAr5daVwtR62ohkiTDMLT/5DnbXOUbD5zWtsOpyr5ozvazmRatjD+hlfEnbGUeJuVJiuenWpi/HmoXpzsaVirVvfkBACgNSIyjVLJYDbve4o/cUN2J0QAAAAAA4BouN+zwmK51dEu9CKfGBrii85kWvff7bn26NN4uUdurSaT+d1ttVfDzdmJ07sFkMik62E/RwX7q3qiyJCk9y6Jth1Nsw69v2H9Kh23/buWwFCAr/kTnGhravprMvPwDAECpQGIcpdLPW49qb/JZSVKzmApqFlvByREBAAAAAOBcP289ku+ww0dT0jV02np91L8xyXHgIot3Jen/vtuqAyfP28riQvz0co/6alk12ImRuT9fLw81ia6gJtH/PNM7mpKujQdyhl//bfsx7T1+9qrHiSxflqQ4AAClCIlxlDqGYeiDP3bblplbHAAAAABQ2lmshsbO357vsMOGJJOksfO366Y6FRlWHaVeUlq6XlywQ/M3HbaVeXuYNaxjVQ3tUJXhuJ2kYpCvbgmK0C31ItShZpj6fbLqqvuEBfg6IDIAAOAqSIyj1Pl9R5J2Hk2TJDWIDFLb6iFOjggAAAAAAOdanXDyouHT8zIkHUlJ1+qEk/SERalltRr6es1+vfbTTqWlZ9vKm8dW0Ms96qtamL8To8PFmsVWUESQr46mpOf7wo9JOYl0RpEEAKB0MTs7AMCRDMPQh4v+mVt8xA3VZTLxpjsAAAAAoPRKSk3X58viC7TtT1uPKD3LUswRAa5n19E03fXxSj0zd6stKV6urJfe7HWdZjzUgqS4i/EwmzSmax1JOUnwi+Uuj+lahxEwAAAoZegxjlJl+Z4T2njgtCSpVsUA3VgrzLkBAQAAAADgJLuOpumTpfH6buMhZVny61OZ19SV+/TdxsPq0aiy+jSNUu2IwGKOEnCu9CyL3v99tyYtiVe29Z/fk56NI/W/22op2N/HidHhSm6pF6GP+jfW2Pnb7UbEqBjkqzFd6+iWehFOjA4AADgDiXGUKhfPLT68YzWZeSsUAAAAAFCKGIahZXuO65OlCVryd/I1HSPlfJamrEjUlBWJui4ySH2aRqlrg0oK9PUq4mgB51ryd7KenbdV+0+es5XFhvjp5e711KoaU/OVBLfUi9BNdSrqr/jj2nMwWdUiQ9U8LoSe4gAAlFIkxlFqrEk8qb8STkqS4kL8dFt93goFAAAAAJQOmdlWfb/psD5dGq+dR9Ps1gX6euqeFtGKrlBWo+dskSS7OXlz00eP3lRDicfP6setR5SeZZUkbT6Yos0HU/Tigu3qUr+S+jSNUtOY8kxbhhItOS1DL/2wXd9tPGwr8/IwaWiHahrWoap8vTycGB0Ky8NsUou4YMX5WxQWFkxHGQAASjES4yg1Pvzjn7nFh3WsxpuhAAAAAAC3l3IuS9NX79MXKxJ1LDXDbl1UhTK6v3Ws7ro+Sn4+OY+IypX1uuqww2O61dX3mw5r1poD2nIoRZKUnmXVt+sP6tv1BxUX4qfeTaPUs3GkQgMYZholh9VqaObaA3r1xx1KvTCPuCQ1i62gV3rUU7WwACdGBwAAgH+LxDhKhc0HT+vPC0PERZYvozsaVnJyRAAAAAAAFJ8DJ8/ps2UJmrX2gM5lWuzWNYwqp4faxalz3Yp5XhovyLDDQWW8dG+LaN3bIlrbDqdo1poDmrvhkC2RGH/8rF77aafe+mWXbqgVpr7NotSueqg8PczFf+HANdp9LE3/m7tFaxJP2cqCynjpmdtqq1eTSHoZAwAAuAES4ygVLu4t/nD7qvKiMQ4AAAAAcEMb9p/Sp0sT9NPWI7JeNB66ySTdXCdcD7aNU5PoKw91Xphhh+tWCtLYO4I0+rba+mXbUc1YfUAr409IkrKthn7dfky/bj+m8EAf3dUkSr2vj1KV4LJFdr3Av5WeZdGHf+zRx0v2Ksvyzy/NnY0q639daivEn1EPAAAA3AWJcbi9nUdT9ev2Y5Kk8EAf9WoS6eSIAAAAAAAoOharod92HNMnS+K1dt8pu3W+Xmbd1SRKg9vEKjbEr9hi8PXy0B0NK+uOhpW178RZzVp7QN+sO2gbvv1YaoY+XLRHHy7ao1ZVg9WnaZQ6163IXM1wqmW7j+uZeVu078Q5W1lMcFm91L2+2lQPcWJkAAAAKA4kxuH2Jizaa/v8YNs4Gt0AAAAAALdwPtOib9Yf1GdL45V4UWJPkkL8fTSgZbT6t4hWeT9vh8YVHeynJzrX0qOdaujPv5M1c80B/b4zSZYLXdhX7D2hFXtPKKiMl3o0qqze10epTqVAh8aI0u34mQy9/MMOzd1wyFbm5WHSw+2ranjHajw7AgAAcFMkxuHW4pPPaMHmw5KkCn7eurt5FSdHBAAAAADAv5OclqGpKxM1bdU+nTqXZbeuepi/Hmwbp24NKzk9uefpYdaNtcN1Y+1w7KkT7gABAABJREFUJaWla876Q5q55oASjp+VJKWcz9KUFYmasiJR10UGqff1UerWsJICfb2cGjfcl9VqaPa6A3rlx51KOf/P707TmPJ6pUd9VQ8PcGJ0AAAAKG4kxuHWPlq81zan2v1tYlXWmyoPAAAAACiZdh9L06dLEzR3wyFlWqx261pXC9YDbePUoUboFecPd5awAF893L6qhrSL0+qEk5q59oB+3HJE6Vk517H5YIo2H0zRSz9s1231I9S3aRU1jbnyXOhAYexJStP/5mzV6sSTtrJAX0/977ba6n19lMxm6hoAAIC7I0sIt3Xw1DnbkFiBvp66r2W0kyMCAAAAAKBwDMPQyr0nNGlpvBbvSrZb52k2qWuDSnqgbazqVgpyUoSFYzKZ1DwuWM3jgvV8t7r6fuNhzVxzQFsOpUiS0rOsmrP+kOasP6S4ED/1bhqlOxtXVliAr5MjR0mVnmXRhEV79NGfe5VlMWzl3RtW0jNd6ig0wMeJ0QEAAMCRSIzDbX38Z7yyL3QXH9gqRgEMxQYAAAAAKCGyLFb9sPmIJi2J1/YjqXbrAnw8dXfzKhrYOkYRQWWcFOG/F+jrpf4tcuZB33Y4RbPWHNDcDYeUmp4tSYo/flav/bRTb/6ySzfWClOfplFqXyNUnh5mJ0eOkmL5nuN6dt5W2/D9khQdXFYvda+nttVDnRgZAAAAnIHEONzSsdR0zVx7QJJU1ttDg1rHOjkiAAAAAACuLjU9S1//tV9TViTqSEq63brK5cpocJtY9WkaJX8f93qkU7dSkMbeEaTRt9XWL9uOauaaA1qx94QkyWI19Ov2Y/p1+zGFB/qoV5NI9b4+StHBfk6OGq7qxJkMvfzjDs1Zf8hW5mk2aUj7OD1yQ3X5enk4MToAAAA4i3u1ooALPlkSr8zsnHnK7m0RrfJ+3k6OCAAAAACAyzt46pwmL0/UzDUHdCYj227ddZFBerBtnG6tV9Hte0v7ennojoaVdUfDytp34qxmrz2o2esO6FhqhiTpWGqGxi/aq/GL9qplXLD6NotS57oVSXRCUs7UA7PXHdQrP+7Q6XNZtvIm0eX16p31VSM8wInRAQAAwNlIjMPtnDybqel/7Zck+XiadX9beosDAAAAAFzT5oOn9cnSBP245YgsVsNuXafa4XqwbayaxVaQyWRyUoTOEx3sp/92rqlRnarrz7+TNXPNAf2xM8k2bdrK+BNaGX9Cgb6e6tGosvo0raI6lQKdHDWcZU/SGT0zd4v+SjhpKwv09dTTt9ZW36ZRMptL3+8QAAAA7JEYh9v5fFmCzmdZJEl9m0YpLMDXyREBAAAAAPAPq9XQHzuTNGlpvFZflMSTcl7w7tkkUve3iVXVUH8nRehaPD3MurF2uG6sHa6ktHTNWX9IM9ccsM0bnZqerS9W7tMXK/epfuUg9WkapW4NKynQ18vJkcMR0rMs+mjxXn20eK8yLVZbebcGlfTs7bV5LgQAAAAbEuNwKynns/TFikRJkpeHSQ+1r+rcgAAAAAAAuCA9y6Jv1x/UZ8sSFJ981m5dsJ+37m0ZrXtbRCvY38dJEbq+sABfPdy+qoa0i9OaxFOasWa/ftxyROlZOQnRLYdStOVQil76YbtuqxehPk2jSm2P+9Jgxd7jenbuVsUf/+f3KapCGb3Uvb7a1wh1YmQAAABwRSTG4VamrkhU2oW52Ho2jlTlcmWcHBEAAAAAoLQ7fiZDX67cpy9X7dPJs5l26+JC/fRg2zj1aFSZebILwWQyqVlsBTWLraDnu9XV9xsPa9baA9p8MEWSlJ5l1ZwNhzRnwyHFhvip9/VR6tmkMr2H3cTJs5l6+Ycd+nb9QVuZp9mkB9vFaeQN1VXGm98lAAAA5EViHG7jbEa2Pl+eIEkym6ShHegtDgAAAABwnr3JZ/Tp0gR9u/6gMrOtdutaxFXQg23j1LFmGHMf/0uBvl7q3yJa/VtEa/vhVM1ae0BzNxxSyvksSVLC8bN6/eedeuvXXbqhVpj6XB+lDjVD5elhdnLkKCzDMPTt+kN6+YftOnUuy1beuEo5vXJnfdWqyBzzAAAAuDwS43AbX/2139Yo6tagkqKD/ZwcEQAAAACgtDEMQ38lnNSnS+P1244ku3UeZpO61I/Qg23jVD8yyEkRurc6lQL1fLe6evrWWvpl21HNXHNAK/aekCRZrIYWbj+mhduPKSzAR3ddH6ne10fx/KCE2Jt8Rs/M3aJV8SdtZQG+nnrqllq6u1kVXjABAADAVZEYh1tIz7Jo0tJ42/LwjtWcGA0AAAAAoLTJslj145Yj+nRpgrYcSrFb5+/jqb5NozSoTSxTfjmIr5eH7mhYWXc0rKz9J85p1toDmr3ugI6lZkiSktIyNH7RXo1ftFct44LVp2mUbqlXkeHsXVBGtkUTF8dr/KI9yrT8M/LC7ddF6Lnb6ygskOHxAQAAUDAkxuEWZq09oOS0nMbtrfUqqnp4gJMjAgAAAACUBmnpWZq55oAmL0/UodPn7dZFBPlqUOsY9W1WRYG+Xk6KEFWCy+q/nWtqVKfqWrI7WTNWH9AfO5OUbTUkSSvjT2hl/AkFfuep7o0qq0/TKNWtRI9+V7Aq/oT+N3eL4pPP2soiy5fRi93rqWPNMCdGBgAAgJKIxDhKvMxsqz7+k97iAAAAAADHOXz6vKasSNTXf+1XWka23bq6lQL1ULs43VY/Ql7MY+0yPD3MuqFWuG6oFa6ktHTNWX9Is9YcUPzxnKRranq2pq7cp6kr96le5UD1aVpF3RpUUlAZXmpwtFNnM/XKjzs0e91BW5mH2aQH2sZq1I01VMabnv0AAAAoPBLjKPHmbThkeyu/Y81Q1avMW90AAAAAgOKx9VCKPl0arwWbj9h6HOfqWDNUD7aLU8u4YJlMzHfsysICfPVw+6oa0i5OaxJPaeaaA/phy2GlZ+UM1b31UKq2HtqqlxZsV5f6EerdNErNYyvwvRYhi9XQX/EntOfgSVU746HmcSEym6S5Gw7ppR926OTZTNu2DaPK6dU766t2RKATIwYAAEBJR2IcJVq2xaoJi/fYlkfcUN2J0QAAAAAA3JHVaujPv5M1aUm8VsafsFvn7WHWnY0r6/42sUzrVQKZTCY1i62gZrEVNKZbHc3fdFgz1xzQ5oM588RnZFs1Z8MhzdlwSLEhfrrr+kj1ahyZZ15ri9XQ6oSTSkpLV1iAr5rFVpCHmST65fy89YjGzt+uIynpF0oSFOrvowp+Xtp17IxtuwAfTz15ay3d3awK9xMAAAD/GolxlGg/bDmqxBPnJEmtqgarSXR5J0cEAAAAAHAX6VkWzdtwSJ8uS9CepDN268qX9dK9LaJ1b8sYhQb4OClCFKVAXy/d0zxa9zSP1vbDqZq19oDmbjiklPNZkqSE42f1xs+7NO7Xv9WxZpj6No1Sh5qh+m3HsUuSvDnzy4/pWke31Itw1uW4rJ+3HtHQaetlXFKefCZDyWcybMtd6kfoua51FH7JSwgAAADAtSIxjhLLahj6aPFe2/II5hYHAAAAABSBk2czNW3VPk1dmajjZzLt1sWG+On+NrHq2TiSeY7dWJ1KgXq+W109fWst/bLtqGatPaDle3JGC7BYDf2245h+23FMgb6eSk3PzrP/0ZR0DZ22Xh/1b+xSyXGr1VC21ZDFaijbar3wX+Of/1rylmdZ8tnOalW2xci/3LbfRcuWnPVZFqu+WJGYJyl+MQ+T9PG9TdSpTkWH3RcAAACUDiTGUWIt2Xtaf194Y79xlXJqWTXYyREBAAAAAEqyhONn9dmyeH2z7qBtrulcTWPK68G2cepUO1xmhnQuNXy9PHRHw8q6o2Fl7T9xTrPXHdDstQd1NDWnd3h+SXFJtsTvk99s1r4T52Q1ZJc0zjfpbMmbXM4vGZ2dT3Laftv8jmkoy2qVcaWMtIuwGJKfj5ezwwAAAIAbIjGOEsdiNbRq73G9t+SgreyRG6rLZOLBBAAAAACgcAzD0Np9pzRpSbx+23HMLnFoNkm31o/Qg23j1DCqnNNihGuoElxWj99cU6M61dCSv5M1YfEerUk8dcV9UtOz9epPOx0UoftISku/+kYAAABAIZEYdyKL1dDqhJNKSktXWICvmsVWkAdvnV/Rz1uP5Jm3y9NsUnqWxYlRAQAAAABc1eXa3tkWq37edlSfLE3QpgOn7fYp6+2hPk2jNLh1rKIqlHVO4HBZHmaTOtYKU2p61lUT48XJ02ySh9lk+6+Xh/mfZQ+TPM1mu/X//PdCuccl5R7mS7a9ZNnjMuWXntt27Lzb/X3sjF75ccdVry0sgHnFAQAAUPRcOjE+fvx4vfnmmzp69KgaNGigDz74QM2aNXN2WEUivwRvRJCvxnSt41JzT7mSn7ce0dBp6/PMQ5VtNTRsuuvN2wUAAAAAcK782t7hgT5qVz1UK+NP6OCp83bbhwf6aGCrWN3drIqCyjKUM66soMnbUZ2qq3ZE4NUT02azPD3ySWDbJaVzys0mlciR89pWD9Xk5Qk6mpKe7zzjJkkVg3JeYAEAAACKmssmxmfOnKnHHntMEydOVPPmzfXuu++qc+fO2rVrl8LCwpwd3r9yuQTv0ZR0DZ3mOgleq9WQxTBkNQxZrZLFyJmTymrNKbNcVG4rs/1Xts+XllsvbG+5qPzi4+SWG0bOMSyGoWyLVa/9tDPfRlOusfO366Y6Fel1DwAAAKBUKuzL5bNnz9b//d//KTExUdWrV9frr7+u2267zYERF6/Ltb2PpWZo9rqDdmW1KgbowbZx6tqgkrw9zY4LEiVas9gKigjyvWqS95EbqvOs4gIPs0ljutbR0GnrZZLs7lvuHRrTtQ73CwAAAMXCZRPjb7/9th588EENGjRIkjRx4kT98MMP+vzzz/X00087ObprZ7EaGjt/e74NptyyR2du0o9bjshqyJZUtlhz5j2z2CWZjZxtchPY1n+S1bb9bElrXbLfRWWXJqMvfC5JDElHUtK1OuGkWlYNdnY4AAAAAOBQhX25fMWKFerXr59effVV3X777frqq6/UvXt3rV+/XvXq1XPCFRStK7W9L9a2eoiGtKuq1tWCS2TvWzgXSd5rc0u9CH3Uv3Ge0RwqMpIiAAAAiplLJsYzMzO1bt06jR492lZmNpvVqVMnrVy5Mt99MjIylJGRYVtOTU2VJFmtVlmt1uINuBD+ij9h90d/fs5nWfT9piMOisi9HEs971LfN0o2q9UqwzCoUyh21DU4AvUMjkJdgyOUpHrmqBgL+3L5e++9p1tuuUVPPPGEJOnFF1/UwoUL9eGHH2rixIkOibk4rU44edW2tyQN61CNl6vxr5DkvTa31IvQTXUq6q/449pzMFnVIkPVPC6ElwgAAABQrFwyMX78+HFZLBaFh4fblYeHh2vnzp357vPqq69q7NixecqTk5OVnn71xrCj7Dl4stiObZJkNkseJpNMppz/mk2mvGVmyWwy2T6bZJLHhTKzKeeNZ5Ny/mtXZjumZDabLjlPblnOcf4514X9c8suLJtNpkvOk1v2TxzmC/F7mKUDpzI0ff2xq94Dr+zzSkpKKrZ7jNLFarUqJSVFhmHIbGY4RRQf6hocgXoGR6GuwRFKUj1LS0sr9nNcy8vlK1eu1GOPPWZX1rlzZ82bN++y5ykpL6RLOS9NF3Q7V4vdVZSkF1Cc7eY64bqxVpjWJJ5UUlqGwgJ81DSmgjzMJu7fFZgkNYspr1i/bIWGlpdJOaMaAsWBf9PgCNQzOAp1DY5SUupaYeJzycT4tRg9erRdoz41NVVRUVEKDQ1VYGCgEyOzV+2Mh6SEq273Tu/r1CS6vC2B/M9//0lK501cu+9btRarod/3LNax1CvP23VzozjeLkaRsVqtMplMCg0NdfkHrijZqGtwBOoZHIW6BkcoSfXM19e32M9xLS+XHz16NN/tjx49etnzlJQX0qWcl6YLuh0vV+evJL2A4iri/KU4f09JFp04nuzscEoE6hkchboGR6CewVGoa3CUklLXCvNCuksmxkNCQuTh4aFjx+x7CB87dkwVK1bMdx8fHx/5+PjkKTebzS71ZTWPC1FEkK+Oplw5wdutYSQJ3ouYzdLz3a4+b5eXp4cTooM7M5lMLvfvCNwTdQ2OQD2Do1DX4AglpZ65enyFUVJeSJekm0NCVXHhfl6u/hdK0gsoKLmoZ3AU6hocgXoGR6GuwVFKSl0rzAvpLpkY9/b2VpMmTfT777+re/fuknJu/u+//64RI0Y4N7h/ycNs0piuV0/w0jDPi3m7AAAAACCva3m5vGLFioXaXio5L6RLvFxdVErKCygo2ahncBTqGhyBegZHoa7BUUpCXStMbC57FY899pg++eQTffHFF9qxY4eGDh2qs2fPatCgQc4O7V/LTfBWDLJ/g6FikK8+6t+YBO8V3FIvQsueukFfPdBML9wSq68eaKZlT93APQMAAABQal38cnmu3JfLW7Zsme8+LVu2tNtekhYuXHjZ7Usi2t4AAAAAgIu5ZI9xSerTp4+Sk5P13HPP6ejRo2rYsKF+/vnnPHOglVS31IvQTXUqanXCSSWlpSsswFfNYivQU7wAPMwmtYgLVpy/RWFhwTJzzwAAAACUco899pgGDBig66+/Xs2aNdO7775r93L5fffdp8qVK+vVV1+VJP3nP/9R+/btNW7cOHXp0kUzZszQ2rVrNWnSJGdeRpGj7Q0AAAAAyOWyiXFJGjFiRIkfOv1KPMwmtawa7OwwAAAAAAAl3NVeLt+/f7/d8HKtWrXSV199pWeffVb/+9//VL16dc2bN0/16tVz1iUUG9reAAAAAADJxRPjAAAAAACgYK70cvnixYvzlN1111266667ijkqAAAAAABcg8vOMQ4AAAAAAAAAAAAAQFEgMQ4AAAAAAAAAAAAAcGskxgEAAAAAAAAAAAAAbo3EOAAAAAAAAAAAAADArZEYBwAAAAAAAAAAAAC4NRLjAAAAAAAAAAAAAAC3RmIcAAAAAAAAAAAAAODWSIwDAAAAAAAAAAAAANwaiXEAAAAAAAAAAAAAgFsjMQ4AAAAAAAAAAAAAcGskxgEAAAAAAAAAAAAAbo3EOAAAAAAAAAAAAADArZEYBwAAAAAAAAAAAAC4NRLjAAAAAAAAAAAAAAC3RmIcAAAAAAAAAAAAAODWSIwDAAAAAAAAAAAAANwaiXEAAAAAAAAAAAAAgFsjMQ4AAAAAAAAAAAAAcGskxgEAAAAAAAAAAAAAbo3EOAAAAAAAAAAAAADArZEYBwAAAAAAAAAAAAC4NRLjAAAAAAAAAAAAAAC35unsAIqLYRiSpNTUVCdHguJgtVqVlpYmX19fmc2834HiQT2Do1DX4AjUMzgKdQ2OUJLqWW6bNLeN6k5od7u3kvR7hpKLegZHoa7BEahncBTqGhylpNS1wrS73TYxnpaWJkmKiopyciQAAAAAgNIuLS1NQUFBzg6jSNHuBgAAAAC4ioK0u02GO762rpy3GA4fPqyAgACZTCZnh4MilpqaqqioKB04cECBgYHODgduinoGR6GuwRGoZ3AU6hocoSTVM8MwlJaWpkqVKrn0G/bXgna3eytJv2couahncBTqGhyBegZHoa7BUUpKXStMu9tte4ybzWZFRkY6OwwUs8DAQJf+ZYR7oJ7BUahrcATqGRyFugZHKCn1zN16iuei3V06lJTfM5Rs1DM4CnUNjkA9g6NQ1+AoJaGuFbTd7V6vqwMAAAAAAAAAAAAAcAkS4wAAAAAAAAAAAAAAt0ZiHCWSj4+PxowZIx8fH2eHAjdGPYOjUNfgCNQzOAp1DY5APQOKH79ncATqGRyFugZHoJ7BUahrcBR3rGsmwzAMZwcBAAAAAAAAAAAAAEBxocc4AAAAAAAAAAAAAMCtkRgHAAAAAAAAAAAAALg1EuMAAAAAAAAAAAAAALdGYhwAAAAAAAAAAAAA4NZIjMMpXn31VTVt2lQBAQEKCwtT9+7dtWvXLrtt0tPTNXz4cAUHB8vf3189e/bUsWPH7LYZOXKkmjRpIh8fHzVs2PCK59yzZ48CAgJUrly5Ir4auCpH1jPDMPTWW2+pRo0a8vHxUeXKlfXyyy8X16XBxTiyrv3yyy9q0aKFAgICFBoaqp49eyoxMbGYrgyupijq2qZNm9SvXz9FRUWpTJkyql27tt57770851q8eLEaN24sHx8fVatWTVOmTCnuy4OLcFQ9mzNnjm666SaFhoYqMDBQLVu21C+//OKQa4RrcOS/abmWL18uT0/Pq7YdAHdAuxuOQtsbjkC7G45CuxuOQtsbjkC7Oy8S43CKP//8U8OHD9eqVau0cOFCZWVl6eabb9bZs2dt2zz66KOaP3++Zs+erT///FOHDx/WnXfemedYgwcPVp8+fa54vqysLPXr109t27Yt8muB63JkPfvPf/6jTz/9VG+99ZZ27typ77//Xs2aNSuW64LrcVRdS0hI0B133KEbbrhBGzdu1C+//KLjx4/nexy4p6Koa+vWrVNYWJimTZumbdu26ZlnntHo0aP14Ycf2rZJSEhQly5d1LFjR23cuFGjRo3SAw88QMOplHBUPVuyZIluuukm/fjjj1q3bp06duyorl27asOGDQ69XjiPo+partOnT+u+++7TjTfe6JDrA5yNdjcchbY3HIF2NxyFdjcchbY3HIF2dz4MwAUkJSUZkow///zTMAzDOH36tOHl5WXMnj3bts2OHTsMScbKlSvz7D9mzBijQYMGlz3+k08+afTv39+YPHmyERQUVNTho4Qornq2fft2w9PT09i5c2exxY6Spbjq2uzZsw1PT0/DYrHYyr7//nvDZDIZmZmZRX8hcHn/tq7lGjZsmNGxY0fb8pNPPmnUrVvXbps+ffoYnTt3LuIrQElQXPUsP3Xq1DHGjh1bNIGjxCnuutanTx/j2WefvWrbAXBXtLvhKLS94Qi0u+EotLvhKLS94Qi0uw2DHuNwCSkpKZKkChUqSMp5AyUrK0udOnWybVOrVi1VqVJFK1euLNSx//jjD82ePVvjx48vuoBRIhVXPZs/f77i4uK0YMECxcbGKiYmRg888IBOnjxZtBeAEqO46lqTJk1kNps1efJkWSwWpaSk6Msvv1SnTp3k5eVVtBeBEqGo6lpKSortGJK0cuVKu2NIUufOnQv9/2C4h+KqZ5eyWq1KS0u74jZwb8VZ1yZPnqz4+HiNGTOmGCIHSgba3XAU2t5wBNrdcBTa3XAU2t5wBNrdkqezAwCsVqtGjRql1q1bq169epKko0ePytvbO8+8ZOHh4Tp69GiBj33ixAkNHDhQ06ZNU2BgYFGGjRKmOOtZfHy89u3bp9mzZ2vq1KmyWCx69NFH1atXL/3xxx9FeRkoAYqzrsXGxurXX39V7969NWTIEFksFrVs2VI//vhjUV4CSoiiqmsrVqzQzJkz9cMPP9jKjh49qvDw8DzHSE1N1fnz51WmTJmivRi4rOKsZ5d66623dObMGfXu3bvI4kfJUZx1bffu3Xr66ae1dOlSeXrSBEbpRLsbjkLbG45AuxuOQrsbjkLbG45AuzuHa0eHUmH48OHaunWrli1bVuTHfvDBB3X33XerXbt2RX5slCzFWc+sVqsyMjI0depU1ahRQ5L02WefqUmTJtq1a5dq1qxZ5OeE6yrOunb06FE9+OCDGjBggPr166e0tDQ999xz6tWrlxYuXCiTyVTk54TrKoq6tnXrVt1xxx0aM2aMbr755iKMDu7CUfXsq6++0tixY/Xdd98pLCzsms+Fkqu46prFYtHdd9+tsWPH2v5OA0oj2t1wFNrecATa3XAU2t1wFNrecATa3TkYSh1ONWLECC1YsECLFi1SZGSkrbxixYrKzMzU6dOn7bY/duyYKlasWODj//HHH3rrrbfk6ekpT09P3X///UpJSZGnp6c+//zzoroMuLjirmcRERHy9PS0+0e/du3akqT9+/f/u+BRohR3XRs/fryCgoL0xhtvqFGjRmrXrp2mTZum33//XX/99VdRXQZKgKKoa9u3b9eNN96ohx56SM8++6zduooVK+rYsWN5jhEYGMhb66VIcdezXDNmzNADDzygWbNm5RlKEKVDcda1tLQ0rV27ViNGjLC1CV544QVt2rRJnp6e9DBEqUC7G45C2xuOQLsbjkK7G45C2xuOQLv7HyTG4RSGYWjEiBGaO3eu/vjjD8XGxtqtb9Kkiby8vPT777/bynbt2qX9+/erZcuWBT7PypUrtXHjRtvPCy+8oICAAG3cuFE9evQosuuBa3JUPWvdurWys7O1d+9eW9nff/8tSYqOjv6XV4GSwFF17dy5czKb7f/X7eHhISmn9wTcX1HVtW3btqljx44aMGCAXn755Tznadmypd0xJGnhwoWFqq8ouRxVzyTp66+/1qBBg/T111+rS5cuxXNBcFmOqGuBgYHasmWLXZvg4YcfVs2aNbVx40Y1b968eC8ScCLa3XAU2t5wBNrdcBTa3XAU2t5wBNrd+TAAJxg6dKgRFBRkLF682Dhy5Ijt59y5c7ZtHn74YaNKlSrGH3/8Yaxdu9Zo2bKl0bJlS7vj7N6929iwYYMxZMgQo0aNGsaGDRuMDRs2GBkZGfmed/LkyUZQUFBxXhpciKPqmcViMRo3bmy0a9fOWL9+vbF27VqjefPmxk033eTQ64XzOKqu/f7774bJZDLGjh1r/P3338a6deuMzp07G9HR0Xbngvsqirq2ZcsWIzQ01Ojfv7/dMZKSkmzbxMfHG2XLljWeeOIJY8eOHcb48eMNDw8P4+eff3bo9cI5HFXPpk+fbnh6ehrjx4+32+b06dMOvV44j6Pq2qXGjBljNGjQoDgvDXAJtLvhKLS94Qi0u+EotLvhKLS94Qi0u/MiMQ6nkJTvz+TJk23bnD9/3hg2bJhRvnx5o2zZskaPHj2MI0eO2B2nffv2+R4nISEh3/PSQC9dHFnPDh06ZNx5552Gv7+/ER4ebgwcONA4ceKEg64UzubIuvb1118bjRo1Mvz8/IzQ0FCjW7duxo4dOxx0pXC2oqhrY8aMyfcY0dHRdudatGiR0bBhQ8Pb29uIi4uzOwfcm6Pq2eX+zRswYIDjLhZO5ch/0y7myg10oCjR7oaj0PaGI9DuhqPQ7oaj0PaGI9DuzstkGIYhAAAAAAAAAAAAAADcFHOMAwAAAAAAAAAAAADcGolxAAAAAAAAAAAAAIBbIzEOAAAAAAAAAAAAAHBrJMYBAAAAAAAAAAAAAG6NxDgAAAAAAAAAAAAAwK2RGAcAAAAAAAAAAAAAuDUS4wAAAAAAAAAAAAAAt0ZiHAAAAAAAAAAAAADg1kiMAwAAAAAAAAAAAADcGolxAAAAAAAAAAAAAIBbIzEOAAAAAAAAAAAAAHBrJMYBAAAAAAAAAAAAAG6NxDgAAAAAAAAAAAAAwK2RGAcAAAAAAAAAAAAAuDUS4wAAAAAAAAAAAAAAt0ZiHAAAAAAAAAAAAADg1kiMAwAAAAAAAAAAAADcGolxAECJsnjxYplMJi1evNjZoZRqHTp0UIcOHWzLiYmJMplMmjJlitNimjVrlipUqKAzZ85c0/7PP/+8TCaTXVlMTIwGDhxoW86v/g0cOFAxMTHXdE5HWrx4sd21XKpFixZ68sknHRcQAAAAADhQhw4dVK9ePWeHUWBffvmlatWqJS8vL5UrV87Z4cABSsrzBQAoyUiMAwCuymQyFeinIMnqV155RfPmzSv2mHMlJCRoxIgRqlGjhsqWLauyZcuqTp06Gj58uDZv3pzvPps3b9agQYMUGxsrX19f+fv7q2HDhnryyScVHx9vt+3AgQPt7oGPj49q1Kih5557Tunp6XmOfbl7V7FixSteR25CNr+fvn37XvsNchMWi0VjxozRI488In9/f1t5TEyM3b3y9fVV9erV9cQTT+jkyZNOjNj1PPXUUxo/fryOHj3q7FAAAAAAlzZhwgSZTCY1b97c2aG4nNw22COPPJJnXW679ptvvnFCZCXLzp07NXDgQFWtWlWffPKJJk2adNltc1/yzv3Jfe7x7LPPKjU1tchiOnz4sJ5//nlt3LixyI5ZHObOnatbb71VISEh8vb2VqVKldS7d2/98ccfzg5NUsm5jwDgrjydHQAAwPV9+eWXdstTp07VwoUL85TXrl37qsd65ZVX1KtXL3Xv3r0oQ8zXggUL1KdPH3l6euqee+5RgwYNZDabtXPnTs2ZM0cfffSREhISFB0dbdvnk08+0dChQxUSEqJ77rlHtWrVUnZ2trZu3aqpU6fq3Xff1fnz5+Xh4WHbx8fHR59++qkkKSUlRd99951efPFF7d27V9OnT88T10033aT77rvPrqxMmTIFuqaRI0eqadOmdmWu8DZxdHS0zp8/Ly8vL6ecf/78+dq1a5ceeuihPOsaNmyoxx9/XJKUnp6udevW6d1339Wff/6p1atX27Z79tln9fTTTxf63J988omsVuu1B+8gWVlZysrKktVqldmc993IO+64Q4GBgZowYYJeeOEFJ0QIAAAAlAzTp09XTEyMVq9erT179qhatWrODsnlfPLJJxo9erQqVark7FBKpMWLF8tqteq9994rcP366KOP5O/vrzNnzujXX3/Vyy+/rD/++EPLly/PMzratTh8+LDGjh2rmJgYNWzY8F8fr6gZhqHBgwdrypQpatSokR577DFVrFhRR44c0dy5c3XjjTdq+fLlatWqlVPjvNJ9LCnPFwCgJCMxDgC4qv79+9str1q1SgsXLsxT7kr27t2rvn37Kjo6Wr///rsiIiLs1r/++uuaMGGCXYJwxYoVGjp0qFq3bq0FCxYoICDAbp9x48bp5ZdfznMuT09Pu3sxbNgwtWrVSl9//bXefvtthYeH221fo0aNa753bdu2Va9eva5p3+KU2xvbWSZPnqzWrVurcuXKedZVrlzZ7n4/8MAD8vf311tvvaXdu3erevXqknK+R0/Pwv9p5KyXAQrq888/19ixY7V//35J0syZM1W7dm298sor6tq1q207s9msXr16aerUqRo7dmyRPDgBAAAA3E1CQoJWrFihOXPmaMiQIZo+fbrGjBnj0BisVqsyMzOd2ga7krp162rXrl167bXX9P777zs7HIcqqu8mKSlJkgo1hHqvXr0UEhIiSXr44YfVs2dPzZkzR6tWrVLLli2vOZbs7GyXSNZe7d6OGzdOU6ZM0ahRo/T222/btWmfeeYZffnll9fU5nckV3++AADugKHUAQBF4uzZs3r88ccVFRUlHx8f1axZU2+99ZYMw7BtYzKZdPbsWX3xxRe2Ib5y5zzet2+fhg0bppo1a6pMmTIKDg7WXXfdpcTExGuK54033tDZs2c1efLkPElxKScJOnLkSEVFRdnKcpOB06dPz5MUlyRfX1+9+OKLdr3F82MymdSmTRsZhpFn6PXidOl82LkunQ88d/i6WbNm6eWXX1ZkZKR8fX114403as+ePXn2nzRpkqpWraoyZcqoWbNmWrp0aZ5t8ptjfODAgfL399ehQ4fUvXt3+fv7KzQ0VP/9739lsVjs9j9x4oTuvfdeBQYGqly5chowYIA2bdpUoHnL09PT9fPPP6tTp05X3O5iuUPXX9wozm+O8YLIbw6wgvw+SDl1ZcSIEZo3b57q1asnHx8f1a1bVz///LPddmlpaRo1apRiYmLk4+OjsLAw3XTTTVq/fv0VY1u8eLHuv/9+1a5dW2PHjtWNN96oiRMnqnHjxtq7d2+e7W+66Sbt27ePId0AAACAy5g+fbrKly+vLl26qFevXnajhGVlZalChQoaNGhQnv1SU1Pl6+ur//73v7ayjIwMjRkzRtWqVZOPj4+ioqL05JNPKiMjw27f3HbD9OnTVbduXfn4+NjaDG+99ZZatWql4OBglSlTRk2aNMl3qPLz589r5MiRCgkJUUBAgLp166ZDhw7JZDLp+eeft9v20KFDGjx4sMLDw21tlM8//7zA9ygmJkb33XefPvnkEx0+fPiK215uTuX82me592H27NmqU6eOypQpo5YtW2rLli2SpI8//ljVqlWTr6+vOnTocNnnCevWrVOrVq1UpkwZxcbGauLEiXm2KYrv5nImTJhg27ZSpUoaPny4Tp8+bVsfExNje9kiNDQ03++oIG644QZJOS9zZGZm6rnnnlOTJk0UFBQkPz8/tW3bVosWLbLbJ7dt/9Zbb+ndd99V1apV5ePjowkTJthGrxs0aJDtmU5uez13/vbt27erY8eOKlu2rCpXrqw33ngjT1zFcW/Pnz+vV199VbVq1dJbb72Vb9v+3nvvVbNmzWzL8fHxuuuuu1ShQgWVLVtWLVq00A8//GC3z5QpU2QymfLUpdznKhdPKViQe7B48eIr3sf8fh+sVqveffdd1a1bV76+vgoPD9eQIUN06tQpu+3Wrl2rzp07KyQkxFa3Bw8enO/9AoDSzLVfkQIAlAiGYahbt25atGiR7r//fjVs2FC//PKLnnjiCR06dEjvvPOOpJwh2R944AE1a9bMNuR11apVJUlr1qzRihUr1LdvX0VGRioxMVEfffSROnTooO3bt6ts2bKFimnBggWqVq1aged8O3funP744w916NBBkZGRhTpXfnIbTeXLl8+zLj09XcePH7crCwgIkI+Pz1WPm5aWlmffChUq5Ds09tW89tprMpvN+u9//6uUlBS98cYbuueee/TXX3/Ztvnss880ZMgQtWrVSqNGjVJ8fLy6deumChUq2L1UcDkWi0WdO3dW8+bN9dZbb+m3337TuHHjVLVqVQ0dOlRSTiOva9euWr16tYYOHapatWrpu+++04ABAwp0HevWrVNmZqYaN26c7/qsrCzbPUtPT9eGDRv09ttvq127doqNjS3QOQqjoL8PuZYtW6Y5c+Zo2LBhCggI0Pvvv6+ePXtq//79Cg4OlpTztv8333yjESNGqE6dOjpx4oSWLVumHTt2XPa6JemHH36Qv7+/vvvuO61cuVLx8fF64IEH9MADD+S7fZMmTSRJy5cvV6NGjYrojgAAAADuY/r06brzzjvl7e2tfv366aOPPtKaNWvUtGlTeXl5qUePHpozZ44+/vhjeXt72/abN2+eMjIy1LdvX0k57aBu3bpp2bJleuihh1S7dm1t2bJF77zzjv7++2/NmzfP7rx//PGHZs2apREjRigkJMSWPHvvvffUrVs33XPPPcrMzNSMGTN01113acGCBerSpYtt/4EDB2rWrFm699571aJFC/35559263MdO3ZMLVq0sCUlQ0ND9dNPP+n+++9XamqqRo0aVaD79Mwzz2jq1KlF3mt86dKl+v777zV8+HBJ0quvvqrbb79dTz75pCZMmKBhw4bp1KlTeuONNzR48OA880qfOnVKt912m3r37q1+/fpp1qxZGjp0qLy9vW1JxKL6bvLz/PPPa+zYserUqZOGDh2qXbt22erQ8uXL5eXlpXfffVdTp07V3LlzbcOjX3fddYW+V7kvQwcHBys1NVWffvqp+vXrpwcffFBpaWn67LPP1LlzZ61evTrPkN6TJ09Wenq6HnroIfn4+KhHjx5KS0vTc889p4ceekht27aVJLthyU+dOqVbbrlFd955p3r37q1vvvlGTz31lOrXr69bb721WO/tsmXLdPLkSY0aNeqqnRmknHreqlUrnTt3TiNHjlRwcLC++OILdevWTd9884169OhRwLts72r3oHbt2nrhhReueB8vNWTIEE2ZMkWDBg3SyJEjlZCQoA8//FAbNmyw1ZmkpCTdfPPNCg0N1dNPP61y5copMTFRc+bMuabrAAC3ZgAAUEjDhw83Lv5fyLx58wxJxksvvWS3Xa9evQyTyWTs2bPHVubn52cMGDAgzzHPnTuXp2zlypWGJGPq1Km2skWLFhmSjEWLFl02vpSUFEOS0b179zzrTp06ZSQnJ9t+cs+7adMmQ5IxatSoPPucOHHCbp+MjAzbugEDBhh+fn62dXv27DHeeustw2QyGfXq1TOsVqvdsSTl+zN58uTLXs/F153fT0JCgmEYhhEdHZ3vvW3fvr3Rvn37PMeqXbu23bW89957hiRjy5YthmEYRmZmphEWFmY0bNjQbrtJkyYZkuyOmZCQkOc6BgwYYEgyXnjhBbt4GjVqZDRp0sS2/O233xqSjHfffddWZrFYjBtuuKFA9+bTTz+1i/ti0dHR+d6z1q1bG8ePH7fbdsyYMcalfxpdek/zq38DBgwwoqOjbcuF+X2QZHh7e9uV5dbFDz74wFYWFBRkDB8+/Ir3IT9PPfWUUaZMGSMlJcVYtGhRvvXjUt7e3sbQoUMLfS4AAADA3a1du9aQZCxcuNAwDMOwWq1GZGSk8Z///Me2zS+//GJIMubPn2+372233WbExcXZlr/88kvDbDYbS5cutdtu4sSJhiRj+fLltjJJhtlsNrZt25Ynpkvb0pmZmUa9evWMG264wVa2bt26fNu7AwcONCQZY8aMsZXdf//9RkRERJ72Ut++fY2goKB82+4Xi46ONrp06WIYhmEMGjTI8PX1NQ4fPmwYxj/tqdmzZ9u2v7Q9lSu/9pkkw8fHx9YGNgzD+Pjjjw1JRsWKFY3U1FRb+ejRo+3ay4aR0zaWZIwbN85WlpGRYTRs2NAICwszMjMzDcMouu/mUklJSYa3t7dx8803GxaLxVb+4YcfGpKMzz//PM/1JycnX/W4udvu2rXLSE5ONhISEoyPP/7Y8PHxMcLDw42zZ88a2dnZdu16w8h5PhIeHm4MHjzYVpbbtg8MDDSSkpLstl+zZs1l2+i59/bi5zcZGRlGxYoVjZ49e9rKiuve5j7PmDt37lW3NQzDGDVqlCHJLo60tDQjNjbWiImJsX0/kydPzlOPDCP/ZwMFvQdXuo+X/j4sXbrUkGRMnz7dbruff/7Zrnzu3LmGJGPNmjUFun4AKM0YSh0A8K/9+OOP8vDw0MiRI+3KH3/8cRmGoZ9++umqxyhTpoztc1ZWlk6cOKFq1aqpXLlyVx0u+lKpqamSJH9//zzrOnTooNDQUNvP+PHjr7pPXFyc3T7ff/+93fqzZ8/a1lWrVk3//e9/1bp1a3333Xf5Dt91xx13aOHChXY/nTt3LtC1Pffcc3n2zR0WvLAGDRpk14Mh903l3OHf165dq6SkJD388MN22w0cOFBBQUEFPs/DDz9st9y2bVu7IeZ//vlneXl56cEHH7SVmc1mWw+Aqzlx4oSk/HvnS1Lz5s1t92rBggV6+eWXtW3bNnXr1k3nz58v8HUUVGF/Hzp16mQbOUGSrrvuOgUGBtrdo3Llyumvv/666jCEl7rnnntksVjUsmVLTZ06VadOnbrqNZcvXz7PqAQAAAAAcnqLh4eHq2PHjpJyhnru06ePZsyYYZsu6oYbblBISIhmzpxp2+/UqVNauHCh+vTpYyubPXu2ateurVq1aun48eO2n9zhry8d4rp9+/aqU6dOnpgubkufOnVKKSkpatu2rV07Onf46WHDhtnt+8gjj9gtG4ahb7/9Vl27dpVhGHZxde7cWSkpKYVqnz/77LPKzs7Wa6+9VuB9rubGG2+06zWcO0pcz5497aZEyy2/dHozT09PDRkyxLbs7e2tIUOGKCkpSevWrZNUdN/NpX777TdlZmZq1KhRdqO+PfjggwoMDMwzjHdh1axZU6GhoYqNjdWQIUNUrVo1/fDDDypbtqw8PDxs7Xqr1aqTJ08qOztb119/fb7fac+ePRUaGlqo8/v7+6t///62ZW9vbzVr1szuOyiue5v7TCe/afHy8+OPP6pZs2Zq06aNXfwPPfSQEhMTtX379gId51IFuQeFMXv2bAUFBemmm26yu19NmjSRv7+/7X7lzkW/YMECZWVlXdO5AKC0YCh1AMC/tm/fPlWqVClPA6R27dq29VeTOx/U5MmTdejQIbu5mFNSUgoVT24cZ86cybPu448/Vlpamo4dO2bXWLnSPt99952ysrK0adMmu/ngcvn6+mr+/PmSpIMHD+qNN95QUlKS3QOKi0VGRhZqPuyL1a9f/5r3vVSVKlXslnMTy7nzVOV+b9WrV7fbzsvLS3FxcQU6h6+vb57GdPny5e3mwtq3b58iIiLyDJdfrVq1Ap0j18V15mIhISF296xLly6qWbOmevXqpU8//TTPw6B/q7C/D5d+D1Lee/TGG29owIABioqKUpMmTXTbbbfpvvvuu+r3UL9+fa1atUovvviivvnmG6WlpalcuXK64447NG7cuHyHwzcM45rmWgcAAADcmcVi0YwZM9SxY0clJCTYyps3b65x48bp999/18033yxPT0/17NlTX331lTIyMuTj46M5c+YoKyvLLjG+e/du7dix47LJx6SkJLvly00DtWDBAr300kvauHGj3RzNF/9Nv2/fPpnN5jzHuLTNlZycrNOnT2vSpEmaNGlSgeK6kri4ON17772aNGmSnn766QLvdyWXtp9yX9q+tG2TW37pPMyVKlWSn5+fXVmNGjUk5UyJ1qJFiyL7bi6V2xasWbOmXbm3t7fi4uIK9OzkSr799lsFBgbKy8tLkZGRdi9gS9IXX3yhcePGaefOnXbJ0/ziv5ZpxyIjI/O0JcuXL6/Nmzfblovr3gYGBkrKmX6uIPbt25fv1HsXt9vr1atXoGNdrCD3oDB2796tlJQUhYWF5bs+9361b99ePXv21NixY/XOO++oQ4cO6t69u+6+++4CTdsHAKUJiXEAgEt45JFHNHnyZI0aNUotW7ZUUFCQTCaT+vbtK6vVWqhjBQUFKSIiQlu3bs2zLrfhkzsHeK5q1arJ09Mz333at28vKefN8vx4eHjYJV47d+6sWrVqaciQIXl6lxenyyUzLRZLvnNsXW7ercslmK9FQeb2+rdy5+E+depUgeeHv/HGGyVJS5YsKfLEeGEV5Hvo3bu32rZtq7lz5+rXX3/Vm2++qddff11z5syxzdV2OY0aNdKcOXO0ePFivf7662rfvr1efvllbd++XRs3bsxTr0+fPq2QkJB/f2EAAACAG/njjz905MgRzZgxQzNmzMizfvr06br55pslSX379tXHH3+sn376Sd27d9esWbNUq1YtNWjQwLa91WpV/fr19fbbb+d7vksTvfm9eL106VJ169ZN7dq104QJExQRESEvLy9NnjxZX331VaGvMbft3b9/fw0YMCDfbQo71/UzzzyjL7/8Uq+//rq6d++eZ/2V2rH5uVz7qSjbt0Xx3ThDu3btLtuWmzZtmgYOHKju3bvriSeeUFhYmDw8PPTqq6/a5iK/2LVcU0G+g+K6t7Vq1ZIkbdmyJd96dq2Kqn5e63MWq9WqsLAwTZ8+Pd/1uS8YmEwmffPNN1q1apXmz5+vX375RYMHD9a4ceO0atWqfEdHBIDSisQ4AOBfi46O1m+//aa0tDS7XrI7d+60rc91uUbFN998owEDBmjcuHG2svT0dJ0+ffqaYurSpYs+/fRTrV69Ws2aNbvq9n5+furQoYP+/PNPHTp0SJUrV76m80pSRESEHn30UY0dO1arVq1SixYtrvlYhVG+fPl879e+ffsK3MP7Yrnf2+7du23Dmkk5Q90nJCTYPdT5N6Kjo7Vo0SKdO3fOrtf4nj17CrR/bgM4ISFB9evXL9A+2dnZkvIfIeDfKszvQ2FERERo2LBhGjZsmJKSktS4cWO9/PLLV02MXyw8PFxPP/20vL299fjjj2vnzp12b8EfOnRImZmZtrfkAQAAAOSYPn26wsLCbNNxXWzOnDmaO3euJk6cqDJlyqhdu3aKiIjQzJkz1aZNG/3xxx965pln7PapWrWqNm3apBtvvPGaR2z69ttv5evrq19++cWuV+jkyZPttouOjpbValVCQoLdiGCXtrlCQ0MVEBAgi8VSZCOVVa1aVf3799fHH3+cbw/dK7Vji8Phw4d19uxZu17jf//9tyTZhmgviu8mP7ltwV27dtm10TMzM5WQkFBk9zw/33zzjeLi4jRnzhy7axozZkyBj1EU96K47m2bNm1Uvnx5ff311/rf//531Zf0o6OjtWvXrjzll7bbc0fWu7SO/pv6WZjrrlq1qn777Te1bt26QC8JtGjRQi1atNDLL7+sr776Svfcc49mzJihBx544JrjBQB3wxzjAIB/7bbbbpPFYtGHH35oV/7OO+/IZDLZJe78/PzybfR6eHjkeYP2gw8+uOxbuFfz5JNPqmzZsho8eLCOHTuWZ31+b+s+99xzslgs6t+/f74J08K84fvII4+obNmyRTqX2tVUrVpVq1atUmZmpq1swYIFOnDgwDUd7/rrr1doaKgmTpxod8wpU6Zc8wsL+encubOysrL0ySef2MqsVmu+D5zy06RJE3l7e2vt2rUFPmfu0PdFldy/WGF+HwrCYrHkmU4gLCxMlSpVshsqMT+XDhuYK3fYvEsb1rlz6rVq1apQMQIAAADu7Pz585ozZ45uv/129erVK8/PiBEjlJaWZhsxzGw2q1evXpo/f76+/PJLZWdn2w2jLuWMCnXo0CG7dtDF5zt79uxV4/Lw8JDJZLJrNycmJmrevHl223Xu3FmSNGHCBLvyDz74IM/xevbsqW+//Tbf0dSSk5OvGlN+nn32WWVlZemNN97Is65q1apKSUmxG2r6yJEjmjt37jWd62qys7P18ccf25YzMzP18ccfKzQ0VE2aNJFUNN9Nfjp16iRvb2+9//77ds8XPvvsM6WkpKhLly7XdNyCyE0UX3zev/76SytXrizwMXJfJvg3zwOK696WLVtWTz31lHbs2KGnnnoq3+c306ZN0+rVqyXltNtXr15td/1nz57VpEmTFBMTY5vXPHc4+iVLlti2s1gsl51qoCAKcx979+4ti8WiF198Mc+67Oxs2zFOnTqV55obNmwoSVd9bgAApQ09xgEA/1rXrl3VsWNHPfPMM0pMTFSDBg3066+/6rvvvtOoUaPs5rVq0qSJfvvtN7399tuqVKmSYmNj1bx5c91+++368ssvFRQUpDp16mjlypX67bffbMNkF1b16tX11VdfqV+/fqpZs6buueceNWjQQIZhKCEhQV999ZXMZrPd0Ntt27bVhx9+qEceeUTVq1fXPffco1q1aikzM1N///23pk+fLm9vb1WsWPGq5w8ODtagQYM0YcIE7dixwyE9cB944AF98803uuWWW9S7d2/t3btX06ZNyzOvWEF5eXnppZde0pAhQ3TDDTeoT58+SkhI0OTJk6+pB/rldO/eXc2aNdPjjz+uPXv2qFatWvr+++918uRJSVd/m9rX11c333yzfvvtN73wwgt51h86dEjTpk2TlPPQY9OmTfr4448VEhJSLMOoF+b3oSDS0tIUGRmpXr16qUGDBvL399dvv/2mNWvW2I2wkJ/HH39cJ06c0J133qnTp0/r4MGDeuGFF/TGG2+oRYsWeb7HhQsXqkqVKmrUqFGhrxsAAABwV99//73S0tLUrVu3fNe3aNFCoaGhmj59ui0B3qdPH33wwQcaM2aM6tevn6dNeO+992rWrFl6+OGHtWjRIrVu3VoWi0U7d+7UrFmz9Msvv+j666+/YlxdunTR22+/rVtuuUV33323kpKSNH78eFWrVs0u0dykSRP17NlT7777rk6cOKEWLVrozz//tPWUvrjN9dprr2nRokVq3ry5HnzwQdWpU0cnT57U+vXr9dtvv9naaYWR22v8iy++yLOub9++euqpp9SjRw+NHDlS586d00cffaQaNWpo/fr1hT7X1VSqVEmvv/66EhMTVaNGDc2cOVMbN27UpEmT5OXlJalovpv8hIaGavTo0Ro7dqxuueUWdevWTbt27dKECRPUtGlT9e/fv6gv1+b222/XnDlz1KNHD3Xp0kUJCQmaOHGi6tSpU+CR1KpWrapy5cpp4sSJCggIkJ+fn5o3b16o+ciL695K0hNPPKFt27Zp3LhxWrRokXr16qWKFSvq6NGjmjdvnlavXq0VK1ZIkp5++ml9/fXXuvXWWzVy5EhVqFBBX3zxhRISEvTtt9/KbM7pT1i3bl21aNFCo0eP1smTJ1WhQgXNmDHDNgrdtSjMfWzfvr2GDBmiV199VRs3btTNN98sLy8v7d69W7Nnz9Z7772nXr166YsvvtCECRPUo0cPVa1aVWlpafrkk08UGBio22677ZpjBQC3ZAAAUEjDhw83Lv1fSFpamvHoo48alSpVMry8vIzq1asbb775pmG1Wu2227lzp9GuXTujTJkyhiRjwIABhmEYxqlTp4xBgwYZISEhhr+/v9G5c2dj586dRnR0tG0bwzCMRYsWGZKMRYsWFSjWPXv2GEOHDjWqVatm+Pr6GmXKlDFq1aplPPzww8bGjRvz3WfDhg3GfffdZ1SpUsXw9vY2/Pz8jOuuu854/PHHjT179thtO2DAAMPPzy/f4+zdu9fw8PCwi1+SMXz48ALFfrHc6549e/YVtxs3bpxRuXJlw8fHx2jdurWxdu1ao3379kb79u2veqyEhARDkjF58mS78gkTJhixsbGGj4+Pcf311xtLlizJc8z89r3cvRkzZkye+pOcnGzcfffdRkBAgBEUFGQMHDjQWL58uSHJmDFjxpVvjmEYc+bMMUwmk7F//3678ujoaEOS7cdsNhthYWFGv3798nyX+cVVkPo3YMAAIzo62m6/gv4+XK4+XHzejIwM44knnjAaNGhgBAQEGH5+fkaDBg2MCRMmXPW+rFmzxhg0aJBRtWpVw8fHxzCbzUZkZKRx//33G0ePHrXb1mKxGBEREcazzz571eMCAAAApUnXrl0NX19f4+zZs5fdZuDAgYaXl5dx/PhxwzAMw2q1GlFRUYYk46WXXsp3n8zMTOP111836tata/j4+Bjly5c3mjRpYowdO9ZISUmxbXelduRnn31mVK9e3fDx8TFq1aplTJ48Od+2zdmzZ43hw4cbFSpUMPz9/Y3u3bsbu3btMiQZr732mt22x44dM4YPH25ERUUZXl5eRsWKFY0bb7zRmDRp0lXvVXR0tNGlS5c85bt37zY8PDzybYv++uuvRr169Qxvb2+jZs2axrRp0/K9hvzuQ25b9M0337Qrz6/d2759e6Nu3brG2rVrjZYtWxq+vr5GdHS08eGHH+aJtyi+m8v58MMPjVq1ahleXl5GeHi4MXToUOPUqVN22+Ref3Jy8lWPV5BtrVar8corrxjR0dGGj4+P0ahRI2PBggV52rOXu5+5vvvuO6NOnTqGp6en3TOA3Ht7qfzay8V5bw3DML755hvj5ptvNipUqGB4enoaERERRp8+fYzFixfbbbd3716jV69eRrly5QxfX1+jWbNmxoIFC/Icb+/evUanTp0MHx8fIzw83Pjf//5nLFy4MM+zgcLcg8vdx/y2NQzDmDRpktGkSROjTJkyRkBAgFG/fn3jySefNA4fPmwYhmGsX7/e6Nevn1GlShXDx8fHCAsLM26//XZj7dq1hbt5AFAKmAyjEOPCAgAAOMi8efPUo0cPLVu2TK1bt77ithaLRXXq1FHv3r3zHWIM0uLFizVlyhRNmTIl3/Xz5s3T3Xffrb179yoiIsKxwQEAAABwuI0bN6pRo0aaNm2a7rnnHmeHAwAAUOyYYxwAADjd+fPn7ZYtFos++OADBQYGqnHjxlfd38PDQy+88ILGjx9f4GHgYO/111/XiBEjSIoDAAAAbujSNpckvfvuuzKbzWrXrp0TIgIAAHA85hgHAABO98gjj+j8+fNq2bKlMjIyNGfOHK1YsUKvvPKKypQpU6Bj9OnTxzafH/KKiYlR9+7dL7t+5cqVjgsGAAAAgEO98cYbWrdunTp27ChPT0/99NNP+umnn/TQQw8pKirK2eEBAAA4BEOpAwAAp/vqq680btw47dmzR+np6apWrZqGDh2qESNGODs0AAAAACjxFi5cqLFjx2r79u06c+aMqlSponvvvVfPPPOMPD3pOwUAAEoHEuMAAAAAAAAAAAAAALfGHOMAAAAAAAAAAAAAALdGYhwAAAAAAAAAAAAA4NbcdgIZq9Wqw4cPKyAgQCaTydnhAAAAAABKIcMwlJaWpkqVKslsdq9302l3AwAAAACcrTDtbrdNjB8+fFhRUVHODgMAAAAAAB04cECRkZHODqNI0e4GAAAAALiKgrS73TYxHhAQICnnJgQGBjo5GhQ1q9Wq5ORkhYaGul2vC7gO6hkchboGR6CewVGoa3CEklTPUlNTFRUVZWujuhPa3e6tJP2eoeSinsFRqGtwBOoZHIW6BkcpKXWtMO1ut02M5w7jFhgYSAPdDVmtVqWnpyswMNClfxlRslHP4CjUNTgC9QyOQl2DI5TEeuaOQ43T7nZvJfH3DCUP9QyOQl2DI1DP4CjUNThKSatrBWl3u/5VAAAAAAAAAAAAAADwL5AYBwAAAAAAAAAAAAC4NRLjAAAAAAAAAAAAAAC3RmIcAAAAAAAAAAAAAODWSIwDAAAAAAAAAAAAANwaiXEAAAAAAAAAAAAAgFsjMQ4AAAAAAAAAAAAAcGskxgEAAAAAAAAAAAAAbo3EOAAAAAAAAAAAAADArZEYBwAAAAAAAAAAAAC4NRLjAAAAAAAAAAAAAAC3RmIcAAAAAAAAAAAAAODWSIwDAAAAAAAAAAAAANwaiXEAAAAAAAAAAAAAgFsjMQ4AAAAAAAAAAAAAcGskxgEAAAAAAAAAAAAAbo3EOAAAAAAAAAAAAADArZEYBwAAAAAAAAAAAAC4NRLjAAAAAAAAAAAAAAC3RmIcAAAAAAAAAAAAAODWSIwDAAAAAAAAAAAAANwaiXEAAAAAAAAAAAAAgFsjMQ4AAAAAAAAAAAAAcGskxgEAANycxWpoVfwJ/brzpFbFn5DFajg7JAAAAAAAAAAuyl2fJ3o6OwAAAAAUn5+3HtHY+dt1JCX9QkmCIoJ8NaZrHd1SL8KpsQEAAAAAAABwLe78PJEe4wAAAG7q561HNHTa+ov+iM1xNCVdQ6et189bjzgpMgAAAAAAAACuxt2fJ5IYBwAAcEMWq6Gx87crv0GOcsvGzt/uNsMgAQAAAAAAALh2peF5IolxAAAAN7Q64WSeNzsvZkg6kpKu1QknHRcUAAAAAAAAAJdUGp4nkhgHAABwQ0lpl/8j9lq2AwAAAAAAAOC+SsPzRBLjAAAAbigswLdItwMAAAAAAADgvkrD80QS4wAAAG6oWWwFRQRd+Y/UiCBfNYut4KCIAAAAAAAAALiqqz1PNKnkP08kMQ4AAOCGPMwm/ffmmlfcplFUOXmYTQ6KCAAAAAAAAICr8jCbNKZrnXzX5T5BHNO1Tol+nkhiHAAAwE0ln8m44vqftx3VqvgTDooGAAAAAAAAgCu7pV6E2lYPyVNeMchXH/VvrFvqRTghqqLj6ewAAAAAUPSyLFZ9sSLRtvzWXdfpXFqaqkWGat3+0xr369+yGtKjMzfqp/+0Vbmy3s4LFgAAAAAAAIBLsFgN2+enb6yi62IrqnlcSInuKZ6LHuMAAABu6JdtR3UkJV2SdGOtMN3ZqLJurlVBLeKCNaxDNbWMC5YkHUlJ11PfbpZhGFc6HAAAAAAAAIBSIPH4WUlS+bJe6l4/VC3igt0iKS6RGAcAAHBLny9LsH0e3CbWbp2H2aR3+jRU+bJekqRfth3T9L/2OzQ+AAAAAAAAAK7lfKZFhy90tokN8XNyNEWPxDgAAICb2bD/lNbvPy1JqhkeoFZVg/NsUzHIV2/2amBbfnHBdu06muaoEAEAAAAAAAC4mMQTZ22fSYwDAADA5X2+PNH2eXCbGJlM+Q911KlOuAa0jJYkZWRbNfLrDUrPsjgiRAAAAAAAAAAuJuH4P4nxmOCyToykeJAYBwAAcCNHUs7rxy1HJEkV/Lx1R8PKV9x+9G21VatigCRp17E0vfzDjmKPEQAAAAAAAIDruTgxTo9xAAAAuLSpK/fJYjUkSf2bV5Gvl8cVt/f18tAH/RrJ1yvnz8IvV+3Tr9uOFnucAAAAAAAAAFxLfDKJcQAAAJQA5zMt+uqv/ZIkLw+T+reILtB+1cMD9H+317EtP/ntZh1JOV8sMQIAAAAAAABwTQnHz9g+RzOUOgAAAFzVt+sPKuV8liSp63WVFBboW+B9725WRbfUrShJOn0uS4/O3GjreQ4AAAAAAADA/SWeOCdJigjyVVlvTydHU/RIjAMAALgBq9XQ5OUJtuVBrWMLtb/JZNJrPesrIignmb4q/qQ+WrynSGMEAAAAAAAA4JpOn8vUybOZktxzGHWJxDgAAIBbWLI7WXsvzAHULKaC6kcGFfoY5cp6690+DWU25Sy/89turdt3qijDBAAAAAAAAOCCEo7/M794DIlxAAAAuKrPlyfaPg9uU7je4hdrHhesETdUlyRZrIb+M2ODUtOz/m14AAAAAAAAAFzYxYnxOBLjAAAAcEW7j6Vpyd/JkqTI8mV0U53wf3W8kTdU0/XR5SVJB0+d1//mbJFhMN84AAAAAAAA4K4uTowzlDoAAABc0sW9xQe2ipFH7ljo18jTw6x3+zZUgK+nJGnB5iOave7gvzomAAAAAAAAANcVT2IcAAAAruzU2UzNWZ+TtPbz9lDvplFFctzI8mX12p3X2Zaf/36b9iafKZJjAwAAAAAAAHAtiRcS4x5mk6IqlHVyNMWDxDgAAEAJ9tXq/crItkqS7ro+SoG+XkV27C7XRajvhUT7uUyLRn69QRnZliI7PgAAAAAAAADnMwzDNpR6lQpl5eXhnilk97wqAACAUiDLYtXUlYmSJJNJGtQ6psjP8VzXOqoamjN00rbDqXrz511Ffg4AAAAAAAAAzpOUlqFzmTkdYmKC3bO3uERiHAAAoMT6ccsRHUvNkCR1qh2u6OCin/unrLenPujXWN4X3hL9dFmCFu9KKvLzAAAAAAAAAHCO+OSL5xf3d2IkxYvEOAAAQAlkGIY+X5ZgWx7cOrbYzlWnUqBG31bLtvzf2ZuUlJZebOcDAAAAAAAA4Di5w6hLUmxo0Xe+cRUkxgEAAEqg9ftPadPBFElS7YhAtYirUKznG9gqRjfUCpMkHT+TqcdnbZLVahTrOQEAAAAAAAAUv4TjZ2yf40JIjAMAAMCFfL4s0fb5/jaxMplMxXo+k8mkN3tdp9AAH0nS0t3H9dlFPdYBAAAAAAAAlEwJx8/ZPseSGAcAAICrOHjqnH7aekSSFOLvra4NIhxy3mB/H73Tu6Fyc/Bv/LJTWy70WgcAAAAAAABQMuX2GPf1MqtioK+Toyk+JMYBAABKmC9X7lPuKOb9W0TLx9PDYeduUz1EQ9pVlSRlWQw98vV6ncnIdtj5AQAAAAAAABSdbItV+0/m9BiPCfaT2Vy8I1M6E4lxAACAEuRsRra+Wr1fkuTtYdY9zaMdHsPjN9dQg8ggSVLiiXMa8902h8cAAAAAAAAA4N87dPq8siw5vXDceRh1icQ4AABAifLt+oNKS8/pod2tYSXbnN+O5OVh1vv9Gsnfx9MW03cbDzk8DgAAAAAAAAD/Tvzxs7bPJMYBAADgEqxWQ5OXJ9qWB7eOdVos0cF+erF7XdvyM3O3av+Jc06LBwAAAAAAAEDhJSSTGAcAAICLWfx3khIuvMHZMi5YdSoFOjWeHo0idWejypKkMxnZGjljg7IsVqfGBAAAAAAAAKDgEk/8kxiPCyUxDgAAABfw+bJE2+fBbZzXW/xiL3Svp+jgspKkjQdO652Ffzs5IgAAAAAAAAAFlWA3lLq/EyMpfiTGAQAASoCdR1O1bM9xSVJ0cFndUCvMyRHl8Pfx1Pt9G8nTbJIkffTnXq24ECdKH4vV0Kr4E/p150mtij8hi9VwdkgAAAAAAAC4gvgLQ6kHlfFS+bJeTo6meHk6OwAAAABc3eSLeosPbBUjjwuJaFfQIKqc/tu5pl77aacMQxo1c6N+HtVOFfy8nR0aHOjnrUc0dv52HUlJv1CSoIggX43pWke31ItwamwAAAAAAADIKz3LosMp5yVJMSF+Mplc55ljcaDHOAAAgIs7cSZDczcekiQF+HjqruujnBxRXg+1jVObaiGSpKS0DD35zSYZBr2FS4uftx7R0GnrL0qK5ziakq6h09br561HnBQZ4B6WLFmirl27qlKlSjKZTJo3b94Vt1+2bJlat26t4OBglSlTRrVq1dI777yTZ7vx48crJiZGvr6+at68uVavXl1MVwAAAAAAcEX7TpxT7iO8uBD3nl9cIjEOAADg8r76a78ys62SpD5No+Tv43qD/pjNJr3du4Gtl/hvO5I0deU+J0cFR7BYDY2dv135vQaRWzZ2/naGVQf+hbNnz6pBgwYaP358gbb38/PTiBEjtGTJEu3YsUPPPvusnn32WU2aNMm2zcyZM/XYY49pzJgxWr9+vRo0aKDOnTsrKSmpuC4DAAAAAOBiEo6fsX2OJTEOAAAAZ8rMtmrqqpwEs9kkDWgV49yAriAs0Ffj7mpgW375xx3acSTViRHBEVYnnMzTU/xihqQjKelanXDScUEBbubWW2/VSy+9pB49ehRo+0aNGqlfv36qW7euYmJi1L9/f3Xu3FlLly61bfP222/rwQcf1KBBg1SnTh1NnDhRZcuW1eeff15clwEAAAAAcDEJx8/ZPpeGxLjrdTcCAACAzYLNh5WcliFJurlORUVVKOvkiK6sY60wDWodo8nLE5WZbdUjX2/Q/BFtVMbbw9mhoZgkpV0+KX4t2wEoehs2bNCKFSv00ksvSZIyMzO1bt06jR492raN2WxWp06dtHLlysseJyMjQxkZGbbl1NScl5+sVqusVmsxRQ9nsVqtMgyD7xbFinoGR6GuwRGoZ3AU6hqKUnzyPz3GY4LL2NWrklLXChMfiXEAAAAXZRiGPluWYFse3CbWidEU3NO31tJf8Se1/Uiq9iSd0Ys/bNcrPeo7OywUlwKOkB4W4Fu8cQDIIzIyUsnJycrOztbzzz+vBx54QJJ0/PhxWSwWhYeH220fHh6unTt3XvZ4r776qsaOHZunPDk5WenpvPzibqxWq1JSUmQYhsxmBhxE8aCewVGoa3AE6hkchbqGovT3kdO2z37Wc0pK+udl6JJS19LS0gq8LYlxAAAAF7Um8ZS2Hc7pjVe/cpCaxpR3ckQF4+Ppoff7NVLXD5bpfJZFX/21X+2qh+iWehHODg1FbPPB03phwbarbuftYVbVUPcfjgtwNUuXLtWZM2e0atUqPf3006pWrZr69et3zccbPXq0HnvsMdtyamqqoqKiFBoaqsDAwKIIGS7EarXKZDIpNDTUpR+CoWSjnsFRqGtwBOoZHIW6hqJ0MGWLJCkswEcxkfbP7kpKXfP1LXhnDBLjAAAALupzu97iMTKZTE6MpnCqhfnr+W519NS3OX9cP/nNZtWPLKfK5co4OTIUlUU7kzT8q/U6l2m56raZFqu6j1+uifc20XWR5Yo/OACSpNjYnJFG6tevr2PHjun5559Xv379FBISIg8PDx07dsxu+2PHjqlixYqXPZ6Pj498fHzylJvNZpd+SIJrZzKZ+H5R7KhncBTqGhyBegZHoa6hKKScz9KJs5mScuYXz68+lYS6VpjYXPcqAAAASrEDJ8/p1+1HJUmhAT7qUr+SkyMqvN7XR6lL/Zw3TVPTs/XojI2yWAs47jZc2ozV+/XA1LW2pHizmAoad9d1igiyf0M32M9bgb457+IeTklXr4krNWvNAYfHCyDnTf/c+cG9vb3VpEkT/f7773brf//9d7Vs2dJZIQIAAAAAHCjx+Fnb57hSMtIfPcYBAABc0JQVicrNId/XIlreniXvfUaTyaRX7qyvjQdO69Dp81qdeFIf/rFH/+lU3dmh4RoZhqF3ftut93/fbSu7rX5Fvd27oXy9PNS9UaT+ij+uPQeTVS0yVM3jQnT8TIaGTV+vdftOKTPbqie/3ayNB09rTNc68vH0cOLVACXHmTNntGfPHttyQkKCNm7cqAoVKqhKlSoaPXq0Dh06pKlTp0qSxo8frypVqqhWrVqSpCVLluitt97SyJEjbcd47LHHNGDAAF1//fVq1qyZ3n33XZ09e1aDBg1y7MUBAAAAAJwi8cQ/ifHYEBLjAAAAcIK09CzNvNCr1tvTrLubV3FyRNcuqIyX3uvbUL0/XimrIb33+99qVS1YTWMqODs0FFKWxarRc7bom3UHbWX3t4nVM7fVltmcM8y/h9mkFnHBivO3KCwsWGazSeGBvvr6wRZ66YftmrpynyTpq7/2a/vhVH3Uv7EighheH7iatWvXqmPHjrbl3Hm+BwwYoClTpujIkSPav3+/bb3VatXo0aOVkJAgT09PVa1aVa+//rqGDBli26ZPnz5KTk7Wc889p6NHj6phw4b6+eefFR4e7rgLAwAAAAA4TXzyxYlxfydG4jgkxgEAAFzMN+sO6kxGtiTpzkaVFeyfdz7XkuT6mAoa1amG3l74t6yGNGrGRv04sq2Cyno5OzQU0JmMbA2bvl5L/k6WJJlM0jO31dYDbeMKtL+3p1kv3FFP10WW0zNztygj26qNB06r6wfL9OHdjdUiLrg4wwdKvA4dOsgwLj8VxZQpU+yWH3nkET3yyCNXPe6IESM0YsSIfxseAAAAAKAESjhe+nqMl7wxOQEAANyYxWpoyopE2/Kg1rHOC6YIDe9YTc1ic3qJHzp9XqPnbr5ikgeuIyk1XX0+XmlLint7mvVhv8YFTopfrFeTSH07tJUql8vpJX78TKbu+fQvfbo0nvoAAAAAAADgQLmJcbNJqlKhrJOjcQwS4wAAAC7kj51J2nfinCSpTbUQ1awY4OSIioaH2aR3+zRUUJmcXuI/bjlqGy4ermtPUpp6TFihbYdTJeUMjT/t/ubqcl3ENR+zXuUgLXikjdpWD5GU8zLISz/s0H9mbNS5zOwiiRsAAAAAAACXZxiGLTEeWb6svD1LR8q4dFwlAABACfHZsnjb58FtYpwXSDGoVK6MXu95nW35+fnbtCcpzYkR4UpWJ5xUz49W6tDp85KkyuXK6NuhLW09//+N8n7emjKomYZ1qGor+37TYd05YYUSLxrGCwAAAAAAAEUv+UyGbSrH0jKMukRiHAAAwGVsO5yiVfEnJUlxIX7qUCPMyREVvVvqVdQ9zatIktKzrHrk641Kz7I4OSpc6ofNR9T/s7+Ucj5LklS3UqDmDmulamFFN4KBh9mkJ2+ppYn9G8vP20OStPNomrp+uEx/7DxWZOcBAAAAAACAvcTj52yfSYwDAADA4SYvT7R9HtQ6RmazyXnBFKP/u72OaoT7S5J2HEnVaz/tdHJEuNhnyxI04uv1ysy2SpLa1QjVzCEtFRboWyznu6VehL4b0UZVQ3MaYWnp2br/i7V697e/ZbUy7zgAAAAAAEBRSzh+xvY5LpTEOAAAABwoOS1D3288LEkK9PXUnY0jnRxR8fH18tD7/RrZ5i6asiJRv++gh7CzWa2GXlywXS8u2C7jQj76riaR+mzA9fL38SzWc1cL89e84a3VuW64JMkwpHd/260Hp6619VoHAAAAAABA0Yi/aCo7eowDAADAoaat2qdMS04P3X7NqsivmBORzlarYqD+r0tt2/IT32xWUmq6EyMq3dKzLHrk6w36bFmCrew/N1bXG72uk5eHY5oMAb5emti/iZ68paZyB0v4fWeS7vhwmXYeTXVIDAAAAAAAAKVBQvI/ifGYYBLjAAAAcJD0LIum/7VPUs68y/e1inFuQA7Sv0W0bqqT00P45NlMPTprI0NnO8Hpc5m697O/9MOWI5Jy6uBrd9bXozfVkMnk2OH8TSaThnWopi8GN1O5sl6SpMQT59Rj/Ap9v+mwQ2MBAAAAAABwVwkXeox7e5pVqVwZJ0fjOCTGAQAAnGz+psM6fiZTknRLvYqqXEr+GDWZTHqj53WqeGHu6uV7TujjJfFOjqp0OXDynHp+tEJrEk9Jksp4eejT+65X32ZVnBpX2+qhmj+ijepWCpQknc+yaOTXG/TSgu3KvjCyAgAAAAAAAArPYjW078Q5SVJMcFl5mB3bMcKZSIwDAAA4kWEY+nx5om15cOtY5wXjBOX9vPV2nwbK7Zg87tdd2njgtFNjKi22HkrRnR+t0N4LQ2eF+Htr5pAW6lgrzMmR5YiqUFbfDm2lno0jbWWfLktQ/8/+0vEzGU6MDAAAAAAAoOQ6fPq8bUrH0jS/uERiHAAAwKlWxZ/UjiM58yc3iCqnxlXKOTcgJ2hVNUTDO1STJGVbDY38eoPS0rOcHJV7W/J3svp8vFLJaTkJ5rgQP80Z2lrXRZZzbmCX8PXy0Ft3XacX76grzwtvL6+KP6nb31+mDftPOTk6AAAAAACAkid3GHVJig3xd2IkjkdiHAAAwIk+W5Zg+zy4dYzD53R2Ff/pVF2NLrwUsP/kOT333TbnBuTGZq89oMFT1uhspkWS1CS6vL4d2kpVgss6ObL8mUwm3dsyRjOHtFBYgI8k6Whquvp8vEpfr97v5OgAAAAAAABKlosT43H0GAcAAIAjJB4/q993HpMkVQz01W31I5wckfN4eZj1ft9GCvDxlCTN3XBIc9YfdHJU7sUwDL3/+2498c1mZVsNSVLnuuGa/kBzlffzdnJ0V9ckuoIWjGyjpjHlJUmZFqtGz9mip7/drPQsi5OjAwAAAAAAKBkuTozHkBgHAACAI0xZkSgjJz+p+1pFy8ujdP9pFlWhrF6+s75t+f/mbVXiRX+o49plX0giv73wb1vZgJbRmnBPE/l6eTgxssIJC/DVVw+20MBWMbayGWsOqM/HK3X49HnnBQYAAAAAAFBCxNsNpU5iHAAAAMUsNT1Ls9cekCT5epnVr2kVJ0fkGro1qKS7mkRKks5mWjRyxgZlZludHFXJdjYjWw9OXasZaw7Yyv53Wy09362uPMwlb+h+Lw+znu9WV+/0aSBfr5zmzKaDKbr9g2Vasfe4k6MDAAAAAABwbQnHz0iSAnw8FeLv+qMIFiUS4wAAAE4wa80B2xzPdzaOLBFDWTvK893q2uY32nwwReMW7nJyRCVXclqG+n2ySot2JUuSvD3Mer9fIz3UrmqJn8++R6NIfTu0laIqlJEknTybqf6f/qVJS/bKyB2KAQAAAAAAADYZ2RYdOpUz6l5sqF+Jfz5UWCTGAQAAHMxiNTRlRaJtedBFw0JD8vPx1Pv9GsnLI+cP84//jNfS3clOjqrkiU8+ozs/Wq7NB1MkSQG+nvpicDN1a1DJyZEVnbqVgjR/RBu1rxEqSbIa0is/7tSIrzfobEa2k6MDAAAAAABwLQdOnpP1Qn+C0jaMukRiHAAAwOEWbj+qgxfezGxXI1TVwwOcHJHrqVc5SE/dUsu2/NisTTp+JsOJEZUs6/adVM+PVujAyZx6FhHkq2+HtlLLqsFOjqzolSvrrc8HNtUjN1Szlf2w+Yh6TFiu+OQzTowMAAAAAADAtcQnl975xSUS4wAAAA73+bJE2+f728Q6LxAXN7h1rK0ncHJahp6YvYkhsgvg561Hdfcnf+nUuSxJUq2KAZo7rLVquPELGB5mkx6/uaYm3dtEAT6ekqS/j53RHR8u18Ltx5wcHQAAAAAAgGtIOE5ivNgtWbJEXbt2VaVKlWQymTRv3ryr7rN48WI1btxYPj4+qlatmqZMmVLscQIAABS3LQdTtDrxpCSpWpi/2lUPcXJErstsNumtuxooxN9HkrRoV7ImL090blAu7osViRo6fZ0ysq2SpNbVgjXr4ZaqGOTr5Mgc4+a6FTVvRGtVD/OXJKVlZOvBqWv19q+7ZLHyUgUAAAAAACjdSIw7wNmzZ9WgQQONHz++QNsnJCSoS5cu6tixozZu3KhRo0bpgQce0C+//FLMkQIAABSvycsTbJ8HtY6RyWRyYjSuLzTAR+N6N7Atv/bTTm09lOLEiFyT1Wro1Z92aMz325Tbqb5Ho8qaPLCZAn29nBucg1UN9dfc4a11W/2KtrL3/9ij+79Yo5QLvegBAAAAAABKo/iLEuMxJMaLx6233qqXXnpJPXr0KND2EydOVGxsrMaNG6fatWtrxIgR6tWrl955551ijhQAAKD4JKWma/7mw5KkoDJeurNRpJMjKhna1wjVg21zhpzPtFg1csYGncvMdnJUriMj26JRMzfq4z/jbWXDO1bV270byNuzdM6c5O/jqfF3N9boW2vJfOHdk8W7ktX1w2XafjjVucEBAAAAAAA4SW6P8RB/n1LXmUKSPJ0dQH5WrlypTp062ZV17txZo0aNuuw+GRkZysjIsC2npuY88LJarbJarcUSJ5zHarXKMAy+WxQr6hkchbpWekxdmagsS0533n7NouTjaXLY917S69njN9XQyvgT2nooVfHJZ/X899v02p31nR2W06Wez9LD09ZrVULO8PxmkzS2W13d07yKDMNwypzsrlTXHmwbqzoRAfrPjI06eS5L+0+e050fLderPerrjoaVnB0e/gVXqmdXUxJiBAAAAAC4vzMZ2UpOy8mlxpXC3uKSiybGjx49qvDwcLuy8PBwpaam6vz58ypTpkyefV599VWNHTs2T3lycrLS09OLLVY4h9VqVUpKigzDkNlcOntCofhRz+Ao1LXSIT3bqmmr9kmSPMzSbdX8lJSU5LDzu0M9e65TlAZ8tUPns6yatfagrgvzUqcaFZwdltMcS8vUo/N2K/5Ezt+6Pp4mvXhrnNrF+jq0bl3K1epa9UDp8761NPqHvdpx7JzSs6x6dNYmrfr7iB5pGylPD6YzKIlcrZ5dSVpamrNDAAAAAABAiaV8fnHJRRPj12L06NF67LHHbMupqamKiopSaGioAgMDnRgZioPVapXJZFJoaKjLPwhDyUU9g6NQ10qHmWsP6PT5nOG/b6sXoXpVHTuMujvUs7Aw6YU7zHrimy2SpNf/OKB2dasosnxZJ0fmeDuOpOqh2Vt1LDXnLd8KZb306YDr1TCqnHMDk2vWtbAwac6wCD33/XbNXndQkjRzY5LiT2fpw36NFBrg4+QIUViuWM8ux9fX19khAAAAAABQ6ucXl1w0MV6xYkUdO3bMruzYsWMKDAzMt7e4JPn4+MjHJ+8DLbPZ7PIPSnBtTCYT3y+KHfUMjkJdc2+GYWjK8n225fvbxjnlu3aHetarSZSW7j6h7zcdVlp6th6dtVkzH2ohT4+Se02FtXzPcQ35cp3OZOS8aBEdXFZfDGrmUg0aV6xrZXzMeqPXdWpUpbzGfL9VWRZDaxJPqdv45ZpwTxM1iS7v7BBRSK5Yz/Lj6vEBAAAAAEqHhGR6jLtkC71ly5b6/fff7coWLlyoli1bOikiAACAa7d8zwntOpYzlG7jKuVcoldvSWUymfRSj3qKqpDzsuS6faf0/u+7nRyV48zdcFADJ6+2JcUbRJXTnKGtXCop7spMJpPubl5FM4e0VMXAnF68x1Iz1HfSSn25ap9T5mQHAAAAAABwhITjZ2yf40JL57MkhyTGz5w5o40bN2rjxo2SpISEBG3cuFH79++XlDMM+n333Wfb/uGHH1Z8fLyefPJJ7dy5UxMmTNCsWbP06KOPOiJcAACAIvX58gTb58FtYp0YiXsI9PXSe30bycOcMzf0h4v2aFX8CSdHVbwMw9D4RXv06MxNyrLkJG871Q7TjAdbKNifYcALq3GV8pr/SBs1i82Zoz7LYuj/5m3VE99sVnqWxcnRAQAAAAAAFL2EC0Opm0xSlQqlb2pCyUGJ8bVr16pRo0Zq1KiRJOmxxx5To0aN9Nxzz0mSjhw5YkuSS1JsbKx++OEHLVy4UA0aNNC4ceP06aefqnPnzo4IFwAAoMjEJ5/RHzuTJEmVgnx1S92KTo7IPTSuUl6P3VRDkmQ1pEdnbtTpc5lOjqp4ZFusenbeVr35yy5b2T3Nq2hi/yYq4+3hxMhKttAAH01/oLnuv+hllW/WHVSviSt08NQ5J0YGAAAAAABQtAzDsCXGK5crI1+v0vlMySFzjHfo0OGKwxJOmTIl3302bNhQjFEBAAAUvykrEm2fB7SKKVVzYRe3h9tX1bLdx7Uy/oSOpKTrqW83a2L/JjKZTM4Orcicy8zWyK836LcdSbayJ2+pqaHtq7rVdTqLl4dZ/3d7HV0XGaSnvt2s9Cyrth5KVdcPlumDfo3VpnqIs0MEAAAAAAD4106ezVRqes7UfKV1fnHJRecYBwAAcAcp57I0e+1BSVIZLw/1bVrFyRG5Fw+zSe/0aajyZb0kSb9sO6bpf+2/yl4lx4kzGer3yV+2pLiXh0nv9GmgYR2qkRQvYnc0rKy5w1orOjhnGLFT57J03+d/6aPFe5l3HAAAAAAAlHi5vcUlEuMAAAAoBjPW7Nf5C/MV92oSqaALCVwUnYpBvnqzVwPb8osLtuvvY2lOjKhoJB4/q54frdCmA6clSQE+npoyqJl6NIp0bmBurHZEoL4f3kYda4ZKyhmi//Wfd2rY9PU6k5Ht5OgAAAAAAACuXTyJcUkkxgEAAIpFtsWqLy4aRn1Q6xinxeLuOtUJ14CW0ZKkjGyrHvlqg9IvvJBQEm3Yf0p3frRCiSdy5rkOD/TRrIdbqnU1hvUubkFlvfTZgKb6z43VbWU/bT2q7uOXa0/SGSdGBgAAAAAAcO3oMZ6DxDgAAEAx+GXbMR1OSZck3VArTHGh/k6OyL2Nvq22alUMkCTtOpamV37c4eSIrs3C7cfU75NVOnk2U5JUI9xfc4e1Vu2IQCdHVnqYzSY9elMNfTbgegX4ekqS9iSdUffxy/XLtqNOjg4AAAAAAKDwEpL/SYzHhZTe55QkxgEAAIrB58sTbJ8Ht451YiSlg6+Xhz7o10i+Xjl/3k5duU+/lrAk5rRV+zTky7VKz7JKklrEVdDsh1upUrkyTo6sdLqxdri+H9FGNcNzXrg4k5GtIV+u05u/7JTFyrzjAAAAAACg5Eg8kZMY9/IwqXL50vusicQ4AABAEdt44LTW7TslKafHb+tqwU6OqHSoHh6g/7u9jm35yW836+iFXvuuzDAMvfHzTj07b6ty861dG1TSF4ObKagM89I7U2yIn+YMa6Xbr4uwlY1ftFcDJ6/WqQu9+gEAAAAAAFyZ1WrYhlKPDvaTh9nk5Iich8Q4AABAEft8mX1vcZOp9P6x6Wh3N6uiW+pWlCSdPpelUTM3uHTv3sxsqx6ftUkTFu+1lQ1pH6f3+jSUj6eHEyNDLj8fT33Qr5Ge7VLb1nBcuvu4un64TFsPpTg5OgAAAAAAgCs7kpqujOycEQpjgkvv/OISiXEAAIAidSTlvH7cckSSVMHPW90bVXZyRKWLyWTSaz3rKyLIV5K0Kv6kJv659yp7OUdqepYGTVmtORsOSZJMJmlst7oafWttmUvxm7uuyGQy6YG2cZp2f3MF+3lLkg6eOq+eH63QnPUHnRwdAAAAAADA5dnNLx5KYhwAAABF5MuV+5R9oYfyPc2ryNeLXr+OVq6st97t01C5ueW3F/5tG9reVRxNSVfviSu1fM8JSZKPp1kf3dNEA1rFODcwXFHLqsFaMLKNGkSVkyRlZFv12KxNGvPdVmVeePMaAAAAAADAlSQcP2P7HBtCYhwAAABF4HymRV+t3i9J8vIwqX+LaCdHVHo1jwvWiBuqS5IsVkP/mbFBqelZTo4qx66jaeoxYbl2Hk2TJJUr66WvHmyuW+pVdHJkKIiIoDKaNaSF+jWrYiv7YuU+3f3JKiWluv6c9gAAAAAAoHSJP/5Pj3ES4wAAACgSczcc0ulzOcnX26+rpPBAXydHVLqNvKGaro8uLyln2Ov/zdkiw3DufOMr955Qr4krdCQlJ4EaVaGMvh3aSk2iKzg1LhSOj6eHXr2zvl67s768PXKaVGv3nVKXD5ZpbeJJJ0cHAAAAAADwj8SLEuNxJMYBAADwbxmGoc+XJ9iWB7eOdWI0kCRPD7Pe7dtQAb6ekqQFm49o9jrnzQf9/abDGvD5aqWlZ0uS6lcO0pyhrVU11N9pMeHf6dusimY93NI2p31yWob6TlqlqSsTnf4SBgAAAAAAgCQlXEiM+3l7KDTAx8nROBeJcQAAgCKwZPdx7UnKma+nWUwF1Y8McnJEkKTI8mX12p3X2Zaf/36b9iafucIeRc8wDE1aslcjv96gTEvOPNQda4ZqxkMtSn1jxB00jCqn+Y+0Ucu4YElSttXQc99t0+OzNyk9y+Lk6AAAAAAAQGmWmW3VgVPnJUmxoX4ymUxOjsi5SIwDAAAUgc+XXdRbvE2M8wJBHl2ui1DfplGSpHOZFo38eoMysh2TsLRYDY2dv12v/LjTVta3aZQ+ue96+fl4OiQGFL8Qfx99eX8zPdQuzlY2Z/0h3TlhhQ6cPOfEyAAAAAAAQGl24NQ5Waw5o9rFBJfuYdQlEuMAAAD/2p6kNP35d7IkKbJ8Gd1Up6KTI8KlnutaR1VDc/7433Y4VW/+vKvYz5meZdGw6es0ZUWireyxm2ro1Tvry9ODP8PdjaeHWf+7rbY+vLuRynp7SJK2H0lV1w+XacmFfx8AAAAAAAAcKSGZ+cUvxhM5AACAf+nz5Ym2zwNbxcjDXLqHJHJFZb099UG/xvK+kJD+dFmCFu9KKrbznTybqbs/WaVfth2TJHmaTXqz13UaeWP1Uj9klbu7/bpKmjustWIvNDZPn8vSgMmrNX7RHuYdBwAAAAAADpU7v7iUM5R6aUdiHAAA4F84dTZTc9YflCT5eXuo94Uhu+F66lQK1OjbatmW/zt7k5LS0ov8PPtPnFOvj1Zo/f7TknLqxWcDm+qu66kbpUXNigGaN7y1OtUOkyQZhvTmL7s05Mt1SkvPcnJ0AAAAAACgtEg4cVFiPMTfiZG4BhLjAAAA/8LXa/YrPcsqSbrr+igF+no5OSJcycBWMbqhVk6y8viZTD0+a5Os1qLrxbv54Gnd+dFyxV94Gzc0wEczh7RU+xqhRXYOlAxBZbw06d7r9dhNNZQ7SMCv24/pjvHLtftYmnODAwAAAAAApcLFQ6nHMsc4iXEAAIBrlWWxauqKfZIkkykn6QrXZjLlDGkeGuAjSVq6+7g+W5ZQJMdetDNJfSet0vEzmZKkqqF+mjuslepVDiqS46PkMZtNGnljdX0+oKkCfT0lSfHJZ9V9/HL9tOWIJMliNbRy7wl9t/GQVu49IUsRvqgBAAAAAABKt9yh1IP9vBVUlg49ns4OAAAAoKT6aetRHU3NGYr7xlrhignhrcuSINjfR+/0bqh7P/9LhiG98ctOtYgLVv3Ia09gz1i9X8/M22pLajaNKa9P7rte5cp6F1XYKME61grT/EfaaMiX67TzaJrOZlo0dPp63VwnXJsPptj+HZGkiCBfjelaR7fUi3BixAAAAAAAoKQ7m5Fte+bAc8sc9BgHAAC4BoZh2PU0HtwmxnnBoNDaVA/RkHZVJUlZFkOPfL1eZzKyC30cwzD09sK/9fScLbak+G31K+rL+5uTFIed6GA/zRnWSnc0rGQr+3X7MbukuCQdTUnX0Gnr9fPWI44OEQAAAAAAuJFEu/nFSYxLJMYBAACuyfr9p7XpwGlJUq2KAWoZF+zcgFBoj99cQw0u9BJPPHFOY77bVqj9syxWPfHNZr3/+25b2f1tYvVhv8by9fIo0ljhHsp6e+rdPg31bJfal90mdyD1sfO3M6w6AAAAAAC4ZrnDqEskxnORGAcAALgGny//p7f4/W1iZTKZnBgNroWXh1nv92skf5+c2YW+XX9Q3208VKB9z2Rk6/4v/p+9Pw+P8y7v/u/PzGgZ7ftqy5a8W5LjeI/jAAlkseF2IbSQJoFQs7SkCQ0Y+mvdQlKXljy9CRDapgRSUkPThAClSXMTOwkOIZuDLTsOlmQ7tjWybGvf923mev4YaTTCmyRr5jvL+3UcOY5rRtdIp60r8mg+c55nhX5+8Kwk7475r35oub72f0plt3Mt4OJsNpvKCi89tt+S1NA1qP2u9uAUBQAAAAAAIo6rZSIYX0AwLolgHAAAYNrOdQ5oT2WjJCk7OU5bVxZe5hEIVfOzkvT1j5T5bv/t/1Sqrq3/ko9p7h7Ubd/fp1ffbZEkxcXY9a+3r9Zn37MgoLUicjT3DF7+pGmcBwAAAAAA8Ptc/qPUcwjGJYJxAACAafvxvlrfiOM7N8xnbHaYu3XVXH101RxJ3k7wv/jJ2xpxey547snmHt36b2+qqr5bkpSWEKsnPrNBH7qqIGj1Ivzlpjhn9TwAAAAAAIDf5z9KvTiLYFwiGAcAAJiWvqFRPfXbOklSnMOuO6+ZZ7gizIa//0i55mclSpIOn+nUt148rn2n2vTs4XPad6pNbo+l/a52/eH39ulc54AkaU56gv777o1aX5JpsnSEofUlmSpIc+piQ/dtkgrSnFxbAAAAAABgxsaD8cI0J409Y2JMFwAAABBOfnHorLoHRyVJW1cW0tEZIZLjY/TPf7xKf/i9NzXqsfTob2r06G9qfB9PT4xV7+CoRscmBZQVpuo//mSdclP5/mP6HHabHthaqrufOCSbvDvF/VmSHthaKgf76gEAAAAAwAx09A2rs39EEmPU/dExDgAAMEUej6X/eKPWd/vT1xUbqwWzb2VR+kX3xXf2j/hC8fcuydHTf7aRUBxXZHN5gb73idXKTzv/OlqWn6LN5YznBwAAAAAAM1PjN0a9JJtgfBwd4wAAAFP0m3dbfE8qr1mQqbLCNMMVYTa5PZb2nWq75DkJsQ794JNrGD+FWbG5vEA3leZrv6tdDZ0DenDPUbX0DOtYY4/ePNWqaxdmmy4RAAAAAACEIdekYDzZYCWhhY5xAACAKXr8DZfv+NObSgxWgkDY72pXY/fgJc8ZGHHr7brO4BSEqOCw27RxYZY+umaudmxZ7rv/oReOy7J+f8g6AAAAAADA5dX6BeML6Bj3IRgHAACYguONPXrtRKskaV5moj6wPM9wRZhtzT2XDsWnex4wXR++eo4W53rfxX2orlO/Pt5suCIAAAAAABCOXIxSvyCCcQAAgCn4D79u8W2biuWw2wxWg0DITZnazvCpngdMl8Nu05dvXuK7/dAL78rjoWscAAAAAABMz/g6yBi7TXMzEgxXEzoIxgEAAC6jrXdIv3j7nCQpJT5GH1tbZLgiBML6kkwVpDl1sbc82CQVpDm1viQzmGUhytxSlq8Vc9IkSdUN3Xq+ssFwRQAAAAAAIJx4PJZvlPq8zETFOIiDx/E3AQAAcBlP7a/T8KhHkvTxdUVKjo8xXBECwWG36YGtpZJ0Xjg+fvuBraVMC0BA2WyTu8a//dK7GnV7DFYEAAAAAADCSVPPoAZG3JIYo/77CMYBAAAuYXjUox/vOy1JstukP7m22GxBCKjN5QX63idWKz9t8rj0/DSnvveJ1dpcXmCoMkST9y3J0fpi72SCmpY+38QKAAAAAACAy3G1sF/8Ymh3AgAAuIRfHqlXc8+QJOmm0jwVZSYargiBtrm8QDeV5mu/q13NPYPKTfGOT6dTHMFis9n0lVuW6uPf3ydJ+u6vTujDVxcqPsZhuDIAAAAAABDqXG1+wXgOwbg/OsYBAAAuwrIs/fB1l+/2Z65bYLAaBJPDbtPGhVn68NVztHFhFqE4gm59SabetyRHknSuc0BPHzhjuCIAAAAAABAO6Bi/OIJxAACAi6g43aHKc92SpPI5qVpXnGG4IgDR5Cs3L/Ud/8vLJzUw7DZYDQAAAAAACAeuVoLxiyEYBwAAuIjH/brFP72pRDYbXcMAgmfF3DRtLsuXJLX0DOlH+2rNFgQAAAAAAELeeDCeEOtQXorTcDWhhWAcAADgAs609+uFqkZJUk5KvD50VYHhigBEoy/fvETj78n53iun1D04YrYgAAAAAAAQskbcHtW190uSirOTZGc94CQE4wAAABfwozdr5bG8x5+8Zr7iYxxmCwIQlRbnpejWq+dIkroGRvTvr7ku8wgAAAAAABCtznYMaHTsRc0FjFE/D8E4AADA7+kdGtXTB85IkuJi7LpzwzzDFQGIZl+8cYlixt7h/cPXatTeN2y4IgAAAAAAEIpq2S9+SQTjAAAAv+fnFWfUMzQqSbr16jnKSo43XBGAaDYvK1G3rSuSJPUNu/W9V04arggAAAAAAISiGoLxSyIYBwAA8OPxWPqPN2t9t7ddV2ysFgAY94X3L1Z8jPfXtx/vO63GrkHDFQEAAAAAgFDjau31HRcTjJ+HYBwAAMDPy8eadbqtX5K0aVGWluWnGq4IAKT8NKfu2jhfkjQ06tG/vHzCcEUAAAAAACDUuPw6xtkxfj6CcQAAAD8/fN3lO/70phKDlQDAZHdfv0hJcQ5J0tMHzqhu7E08AAAAAAAAkuRq8Qbj6YmxykiKM1xN6CEYBwAAGFNd3619NW2SvDt4bliaa7giAJiQmRSnz7xngSRp1GPp4b3vGq4IAAAAAACEioFht+rHVq+xX/zCCMYBAADG/McbE93i2zYVy263GawGAM732feUKC0hVpL0P2+f04mmHsMVAQAAAACAUHC6fWKMOsH4hRGMAwAASGrtHdKzh+slSSnOGP3h6rmGKwKA86U6Y/X59y2UJFmW9O2X6BoHAAAAAAATY9Ql9otfDME4AACApP96q07Dbo8k6fb185QUH2O4IgC4sE9dO185KfGSpN2VjTpytstwRQAAAAAAwLSa1olgvJhg/IIIxgEAQNQbGnXrP986LUmy26S7Ns43XBEAXFxiXIzuvWGR7/ZDLx43WA0AAAAAAAgFrlZGqV8OwTgAAIh6z73ToNbeIUnSlvICzc1INFwRAFzaH68v0pz0BEnSb95t0X5Xu+GKAAAAAACASf7BeHEWwfiFEIwDAICoZlmWHn/d5bv96euKzRUDAFMUH+PQfTcu9t1+6IXjsizLYEUAAAAAAMCk8WA8P9XJmsiLIBgHAABR7beudlU3dEuSVs5N0+p5GYYrAoCp+eiqOVqQ430H+P7adr16otVwRQAAAAAAwISu/hG19w1LYoz6pRCMAwCAqPbDSd3iJbLZbAarAYCpi3HYtf2mJb7bdI0DAAAAABCdXG1++8VzCMYvhmAcAABErdNtffrV0SZJUl5qvLaUFxiuCACm54PlBVpekCpJOnKuSy9UNRquCAAAAAAABJurtdd3XMJ+8YsiGAcAAFFr15u1Gm+uvGtjseJieGoEILzY7TZ95eaJrvFvvfiu3B66xiPNq6++qq1bt6qwsFA2m03PPPPMJc//xS9+oZtuukk5OTlKTU3Vxo0b9cILL0w65+/+7u9ks9km/bds2bIA/ikAAAAAAIHiavHrGGeU+kXx6i8AAIhKPYMj+lnFWUlSfIxdd6yfZ7giAJiZ9y/L1ep56ZKkE829evbwObMFYdb19fVp5cqVeuSRR6Z0/quvvqqbbrpJzz//vA4ePKgbbrhBW7du1dtvvz3pvLKyMjU0NPj+e/311wNRPgAAAAAgwGpaGaU+FTGmCwAAADDhpxVn1Ts0Kkn66Oq5ykiKM1wRAMyMzWbTV25Zqjse+60k6eFfndDWlYWKdfA+6EixZcsWbdmyZcrnP/zww5Nuf+Mb39Czzz6r5557TqtWrfLdHxMTo/z8/Cl/3qGhIQ0NDflud3d3S5I8Ho88Hs+UPw/Cg8fjkWVZfG8RUFxnCBauNQQD1xmChWsNF+IaC8YddpvmpDln5foIl2ttOvURjAMAgKjj9lja9abLd/vTm4rNFQMAs+Dahdm6blG2Xj/Zqrr2fv204ozu3DDfdFkIER6PRz09PcrMzJx0/4kTJ1RYWCin06mNGzfqwQcf1Lx5F5+g8uCDD2rnzp3n3d/S0qLBwcFZrxtmeTwedXV1ybIs2e280QaBwXWGYOFaQzBwnSFYuNbw+yzLkqvFu2O8IDVOne2ts/J5w+Va6+npmfK5BOMAACDqvFTdpDPtA5Kk9y7J0eK8FMMVAcCV+8otS/X6Se8vv/+894T+cPVcOWMdhqtCKHjooYfU29urj3/84777NmzYoF27dmnp0qVqaGjQzp079Z73vEeVlZVKSbnwv4s7duzQ9u3bfbe7u7tVVFTk22WOyOLxeGSz2ZSTkxPSL4IhvHGdIVi41hAMXGcIFq41/L7m7kH1j3i7phflpSo3N3dWPm+4XGtOp3PK5xKMAwCAqPP4G3SLA4g8Vxel68blefrV0SY1dQ/pibdO67PvWWC6LBj25JNPaufOnXr22WcnvTjiP5r9qquu0oYNGzR//nz99Kc/1Wc+85kLfq74+HjFx8efd7/dbg/pF0kwczabje8vAo7rDMHCtYZg4DpDsHCtwV/tWAOQJJVkJ83qdREO19p0agvdPwUAAEAAVJ7r0n5XuyRpYU6S3rs4x3BFADB7vnzzEtls3uN/e+WUeodGzRYEo37yk5/os5/9rH7605/qxhtvvOS56enpWrJkiU6ePBmk6gAAAAAAs2F8v7gkLchOMlhJ6CMYBwAAUcW/W3zbphLZ7TaD1QDA7FpekKqtVxVKktr7hvX4667LPAKR6qmnntK2bdv01FNP6UMf+tBlz+/t7dWpU6dUUFAQhOoAAAAAALPFPxgvyU42WEnoIxgHAABRo7l7UM+9Uy9JSkuI1UdXzzFcEQDMvi/dtESOsTf9PPZqjTr7hw1XhCvV29urw4cP6/Dhw5Ikl8ulw4cPq66uTpJ39/ddd93lO//JJ5/UXXfdpW9961vasGGDGhsb1djYqK6uLt85X/nKV/Sb3/xGtbW1evPNN3XrrbfK4XDo9ttvD+qfDQAAAABwZWpa/ILxHDrGL4VgHAAARI0n3jqtEbclSbpjwzwlxsUYrggAZl9JdpI+tmauJKlnaFSP/qbGcEW4UhUVFVq1apVWrVolSdq+fbtWrVql+++/X5LU0NDgC8kl6Qc/+IFGR0d1zz33qKCgwPfffffd5zvn7Nmzuv3227V06VJ9/OMfV1ZWlt566y3l5LBiBAAAAADCiau1V5IUH2NXQarTcDWhjVeDAQBAVBgcceuJ33pDA4fdprs2zjdcEQAEzhc+sFi/OHROw26Pdr3p0qevK1ZuCr8ch6vrr79elmVd9OO7du2adPuVV1657Of8yU9+coVVAQAAAABMc3ss1bX3S/K+UZ61kZdGxzgAAIgK/3u4Xu193nHCH1xRoIK0BMMVAUDgzElP0J3XzJMkDY549MjLJw1XBAAAAAAAZtu5jgHfhMySbMaoXw7BOAAAiHiWZenxN1y+25/eVGyuGAAIkj+/fpESYh2SpCf31+lsR7/higAAAAAAwGyqGRujLknFBOOXRTAOAAAi3pun2nSssUeStGpeulbNyzBcEQAEXk5KvD59XbEkacRt6Z/3njBbEAAAAAAAmFWu1j7fMR3jl0cwDgAAIt7jr090i3/muhKDlQBAcP3pexYqxRkjSfr5wbM61dJ7mUcAAAAAAIBw4R+MLyAYvyyCcQAAENFcrX3ae6xZklSY5tTmsnzDFQFA8KQlxurP3rtAkuSxpO+89K7higAAAAAAwGyhY3x6CMYBAEBE2+W3W/yua4sV4+DpD4Dosm1TibKS4iRJ/+93Daqq7zJcEQAAAAAAmA3jwXiqM0aZY7/74+J4ZRgAAESsroER/ezgWUlSQqxDf7yuyHBFABB8SfEx+vMbFvluf/tFusYBAAAAAAh3gyNunesckCSV5CTLZrMZrij0EYwDAICI9fSBOvUPuyVJf7hmjtITedckgOh054Z5KkhzSpL2HmvWwdMdhisCAAAAIofbY+mtmja9eKxdb9W0ye2xTJcEIArUtffLGvtxU5KVaLaYMBFjugAAAIBAGHV79KM3T/tub9tUYrAaADDLGevQX3xgsXb84ogk6aEXjuupP73GcFUAAABA+NtT2aCdz1WroWtw7B6XCtKcemBrqTaXFxitDUBkq2nx3y+ebLCS8EHHOAAAiEgvVjf5RgndsDRHC3N4cggguv3RmrmaP/YO8n01bXrjZKvhigAAAIDwtqeyQXc/ccgvFPdq7BrU3U8c0p7KBkOVAYgG4/vFJakkJ8lgJeGDYBwAAESkx193+Y4/fR3d4gAQ67Br+01LfLe/+cJxWRYjHgEAAICZcHss7XyuWhd6Rj1+387nqhmrDiBgXK29vuMF2QTjU0EwDgAAIs47ZzpVMbY/d3Fusq5blG24IgAIDVuvKtTSvBRJ0uEznfrV0WbDFQEAAADhab+r/bxOcX+WpIauQe13tQevKABRpba133dcTDA+JQTjAAAg4jz+xuRucZvNZrAaAAgddrtNX755omv8Wy8el4cOFgAAAGDamnsuHorP5DwAmK6asVHquSnxSo6PMVxNeCAYBwAAEaWxa1C//J13h1dGYqxuXTXHcEUAEFpuKs3TyqJ0SdKxxh4997t6swUBAAAAYSg3xTmr5wHAdHQPjqi1d0gS3eLTQTAOAAAiyn++VavRse7HOzfMlzPWYbgiAAgtNptNX/HrGn/4Vyc06vYYrAgAAAAIP+tLMlWQ5tTFZtTZJBWkObW+JDOYZQGIErVj3eIS+8Wng2AcAABEjIFht578bZ0kKcZu0yc3zjdcEQCEpusWZeuaBd4X6FytffrvQ2cNVwQAAACEF4fdpge2ll7ynAe2lsphZ70bgNnn8gvGSwjGp4xgHAAARIxnDp9TR/+IJOn/XFWgvFTGlQHAhdhsNv3lLUt9t7/7qxMaGnUbrAgAAAAIP5vLC/S9T6y+YPj9rY+v1ObyAgNVAYgGNS0E4zNBMA4AACKCZVl6/HWX7/ZnrltgsBoACH1r5mfq/ctyJUn1XYO+iRsAAAAApu69S3LkHlvp5i8zKc5ANQCiRW2b3yj1HILxqSIYBwAAEeG1E6060dwrSVpXnKEVc9MMVwQAoe/LfrvGH/n1SfUPjxqsBgAAAAg/xxp7fMfpCTG+44raDhPlAIgS46PU7TapKDPRcDXhg2AcAABEhMffmOgW//SmEoOVAED4KCtM04dWeMc7tvYO6z/eqDVbEAAAABBmquq7fccfLs/2He+vbTdRDoAoYFmWXGOj1OdkJCg+xmG4ovBBMA4AAMLeyeZevXK8RZI0Jz1BN5XmGa4IAMLHl25aovGViN//zSl1DYyYLQgAAAAII9V+wfi1JWmal5kgSXrnTKeGRt2mygIQwVp7h9Uz5J34VpKdbLia8EIwDgAAwt6uNye6xf/k2mLFOHiKAwBTtSg3WR9dPVeS1D04qsderTFcEQAAABA+quu7JEk2m7QoO0Fr52dKkoZGPao8132phwLAjIyPUZekBdnsF58OXjUGAABhrbN/WP998JwkKSnOodvWFxmuCADCz30fWKxYh7dt/PE3XGrtHTJcEQAAABD6Rt0e347x+ZmJSopzaG1xhu/jFYxTBxAArtZe33EJwfi0EIwDAICw9tT+MxoY8Y4m+9jaIqU6Yw1XBADhpygzUbevnydJ6h92699+fcpwRQAAAEDoq2nt09CoR5JUVpgqSVo7fyIYP1DbYaQuAJHN1drvOyYYnx6CcQAAELZG3B79eF+tJO/Isk9dW2y0HgAIZ/fesEjOWO+viE/89rQaugYMVwQAAACEtqqxMeqSVDoWjC/MSVJGovdN+wdPt8vjsYzUBiBy0TE+cwTjAAAgbO2pbFRD16Ak6QPLcnkiCABXIDfV6XuD0fCoR/+896TZggAAAIAQV+W3Q7y0wBuM22w2rRnbM97RP6IavwALAGbD+I7xOIddhekJhqsJLwTjAAAgbD3+hst3/OlNJQYrAYDI8Pn3LlRKfIwk6acVZ1Q79ss2AAAAgPNVN5wfjEvSumLGqQMIDLfHUm2bd5T6/KxEOew2wxWFF4JxAAAQlg7Vdejtuk5J0rL8FG1cmGW2IACIABlJcfrsexZI8v6y/fCv3jVcEQAAABCaLMtSVb03GM9JiVdOSrzvY2uLM33HB2rbg14bgMhV3zmg4VGPJMaozwTBOAAACCtuj6V9p9r09eeqffd9+roS2Wy8OxIAZsOnryv27UR89p16HW/sMVwRAAAAEHrOdQ6oa2BEklRWmDrpY+VzUhUf441fKugYBzCLXH6T3UpyCMani2AcAACEjT2VDbrun17W7Y+9pbfPdEqS7DbJGcNTGgCYLSnOWN19/UJJkmVJ33rxuOGKAAAAgNBTXT8xRv33g/H4GIdWFqVLkura+9XUPRjM0gBEsNq2iWB8AR3j08aryAAAICzsqWzQ3U8cUkPX5F8mPZZ0308Oa09lg6HKACDy3LWxWHmp3lGQL1Y36Z2xNyMBAAAA8Kqq998vnnbex9czTh1AANS0+HWMZycbrCQ8EYwDAICQ5/ZY2vlctaxLnLPzuWq5PZc6AwAwVc5Yh+59/2Lf7YfoGgcAAAAmqbpEx7gkrS3O8B0zTh3AbPEfpV6cnWiwkvAUtGD8kUceUXFxsZxOpzZs2KD9+/df8vyHH35YS5cuVUJCgoqKivSlL31Jg4OMGwEAIBrtd7Wf1ynuz5LU0DWo/S7egQ0As+W2tUUqykyQJL12olVv1bQZrggAAAAIHUcbvMF4cnyM5mWeH06tnp8hm817TMc4gNkyHownx8coJznecDXhJyjB+NNPP63t27frgQce0KFDh7Ry5Urdcsstam5uvuD5Tz75pP76r/9aDzzwgI4ePaof/vCHevrpp/U3f/M3wSgXAACEmOaeqb05bqrnAQAuLy7Gri9+YInv9kMvHJdlMZkDAAAA6Ogb1rnOAUnS8oIU2e22885JdcZqWb63k/xoQ7d6BkeCWiOAyDM06tbZjn5JUkl2kmy283/24NKCEox/+9vf1uc+9zlt27ZNpaWlevTRR5WYmKjHH3/8gue/+eab2rRpk+644w4VFxfr5ptv1u23337ZLnMAABCZclOcs3oeAGBqPrJqjhbleneWVZzu0CvHWwxXBAAAAJhX3eA/Rv38/eLj1o2NU/dY0tt1nYEuC0CEO9Per/FNkiXZSWaLCVMxgf4Cw8PDOnjwoHbs2OG7z26368Ybb9S+ffsu+Jhrr71WTzzxhPbv36/169erpqZGzz//vD75yU9e9OsMDQ1paGjId7u72/sPk8fjkcfjmaU/DUKFx+ORZVl8bxFQXGcIFq61y1s7P135qU41dl+4I9wmKT/NqbXz0/l7vAiuMwQL11pksUn60o2Ldc+Tb0vy7hp/z6KsC3bEBFM4XWfhUCMAAACmp9pvv3jpBfaLj1tbnKkf7zstSaqobdd7l+QEvDYAkaumZWK/OMH4zAQ8GG9tbZXb7VZeXt6k+/Py8nTs2LELPuaOO+5Qa2urrrvuOlmWpdHRUX3+85+/5Cj1Bx98UDt37jzv/paWFnaTRyCPx6Ouri5ZliW7PSiDDxCFuM4QLFxrU3Pfewu14//VXPBjlqS/eE+h2lrpZLwYrjMEC9da5FmdY9PS3EQdb+5XVX23nn7zXX1gSYbRmsLpOuvp6TFdAgAAAGZZVX2X77i04OLB+HjHuCQdqO0IaE0AIl9t20QwviCHYHwmAh6Mz8Qrr7yib3zjG/q3f/s3bdiwQSdPntR9992nr3/96/ra1752wcfs2LFD27dv993u7u5WUVGRcnJylJp68X+YEJ48Ho9sNptycnJC/oUwhC+uMwQL19rUbE7J0N/+ssY3LmhcQZpTX/vQcm0uzzdTWJjgOkOwcK1Fpr/+oF3bdlVIkh4/0KSPX7tEDoNd4+F0nTmdrPkAAACINOOj1GMdNi3JS7noeQVpCZqTnqBznQN6+0yHRtwexTpC+/krgNDlap0IxouzCMZnIuDBeHZ2thwOh5qamibd39TUpPz8C7+A/bWvfU2f/OQn9dnPflaStGLFCvX19elP//RP9bd/+7cXfOEjPj5e8fHx591vt9tD/oUSzIzNZuP7i4DjOkOwcK1d3t5jLb5Q/IPl+bqlPF+5KU6tL8k0Gs6EE64zBAvXWuS5fmmu1hVn6EBth0619OnZdxr0R2vmGq0pXK6zUK8PAAAA0zM44tapsXHGi3NTFBdz6ed764ozdO7wgAZHPKqq79bVRelBqBJAJPIfpV7MKPUZCfhv6HFxcVqzZo327t3ru8/j8Wjv3r3auHHjBR/T399/3osHDodDkmRZ1oUeAgAAItzuIw2+48+8p0QfvnqONi7MIhQHgCCw2Wz6ys1Lfbcf/tW7Gh5ldzYAAACiz7HGHrnH3rl/qf3i49YWZ/qOK2rbA1YXgMg33jGenRyntIRYw9WEp6C8dX379u167LHH9KMf/UhHjx7V3Xffrb6+Pm3btk2SdNddd2nHjh2+87du3arvfe97+slPfiKXy6WXXnpJX/va17R161ZfQA4AAKJHz+CIXjvRKknKS43XqiKzu20BIBptWJCl9y7JkSSd7RjQ0wfqDFcEAAAABF91fbfvuGwKwfg6v2B8v4tgHMDM9A6NqrlnSJJUQrf4jAVlx/htt92mlpYW3X///WpsbNTVV1+tPXv2KC8vT5JUV1c3qUP8q1/9qmw2m7761a/q3LlzysnJ0datW/WP//iPwSgXAACEmJePNWvY7e1M3FyWLztd4gBgxFduXqJX322RJP3zyyf1R2uKlBDHm5cBAAAQParqu3zHZYVplz1/cW6y0hJi1TUwoorTHbIsSzYbr2sAmJ5av/3iBOMzF5RgXJLuvfde3XvvvRf82CuvvDLpdkxMjB544AE98MADQagMAACEut1HGn3Hm8sLDFYCANHtqrnp2lyWrz1VjWrpGdKP99Xqz9630HRZAAAAQNBU+XWMLy9Iuez5drtNa+dnaO+xZrX3DaumtU8Lc5IDWSKACOSaFIzzM2SmgjJKHQAAYKb6h0f1yrvNkqSspDitL8m8zCMAAIG0/eYlGm9w+d5vTqlncMRsQQAAAECQuD2WjjV6g/H5WYlKcU5txy97xgFcqcnBeKLBSsIbwTgAAAhprxxv0eCId4z6zWX5cjBGHQCMWpKXoo9cPUeS1Nk/on9/zWW4IgAAACA4XK29vtcoSgsuv1983LriDN/xgdqOWa8LQOSjY3x2EIwDAICQtrtyYoz6lvJ8g5UAAMZ98cbFihl7o9IPX3epvW/YcEUAAABA4PmPUS8rnHowvmJumuJivHEMHeMAZqJmLBi32bwTKzAzBOMAACBkDY649fLRJklSWkKsNi7MMlwRAECS5mcl6ePriiRJvUOjevQ3pwxXBAAAAARe9aRgPG3Kj4uPcWjlXO/5tW39au4ZnPXaAEQuy7LkaumVJBWmJcgZ6zBcUfgiGAcAACHrtROt6ht2S5JuKs1TrIOnLgAQKv7i/Yt9XS8/erNWTd28uAcAAIDI5t8xXjqNjnFp8p7xg4xTBzAN7X3D6h4clSQtyEkyXE1449VlAAAQsnZXNviOP7iCMeoAEEry05y665r5kqShUY/+9eWThisCAAAAAseyLFXVd0mSspPjlJsSP63Hs2ccwEzVtvnvFycYvxIE4wAAICQNj3r0UrV3jHpKfIw2Lco2XBEA4Pfdff1CJcV5R7g9tb9OZ9r7DVcEAAAABEZj96A6+kckSaWFabLZbNN6/Jp5Ex3jFafZMw5g6mpaJoLx4iyC8StBMA4AAELSm6da1TM2Iuj9y3MVH8PuHAAINVnJ8frMdSWSpFGPpYd/dcJwRQAAAEBgVJ3zG6NeML0x6pKUlhirpXkp3s9V362+odFZqw1AZHO1+nWMM0r9ihCMAwCAkLT7SKPveEt5gcFKAACX8tn3LlBaQqwk6X/ePquTzT2GKwIAAABmn/9+8bJp7hcft3ZsnLrbY+ntus7ZKAtAFPAPxhcwSv2KEIwDAICQM+r26MVqbzCeEOvQ+5bkGK4IAHAxqc5Yff59CyVJHkv69kvvGq4IAAAAmH3VDV2+45kG4+tLJsapH6hlnDqAqRkPxmMdNs1JTzBcTXgjGAcAACFnv6vdt7fr/ctylRDHGHUACGWfuna+spPjJUnPH2lU5bmuyzwCAAAACC/jHeOJcY4Z7/hdW8yecQDT4/FYvmB8XmaiYhxEu1eCvz0AABBynq9s8B1vLs83WAkAYCoS42J07w0LfbcfevG4wWoAAACA2dU1MKKzHQOSpOUFqbLbbTP6PHPSE1SY5pQkvV3XqRG3Z9ZqBBCZGrsHNTTq/VlRkp1suJrwRzAOAABCittj6YWqJklSXIxdNyzLNVwRAGAqbt8wzzfS7ZXjLapgNCQAAAAiRPUs7BcfN9413j/s1tGG7sucDSDa+e8XL8lONFhJZCAYBwAAIeXg6Q619AxJkt63JEfJ8TGGKwIATEV8jEP3fWCx7/b/feG4LMsyWBEAAAAwO6rqJ1YFlRZcWTC+rjjDd3ygtuOKPheAyFczKRinY/xKEYwDAICQsttvjPoWxqgDQFj56Oo5WpDt3be439Wu1060Gq4IAAAAuHLVDf4d42lX9Lkm7RlnyhKAy3C1+AfjSQYriQwE4wAAIGR4PJb2VDZKkmIdNn1geZ7higAA0xHjsOtLNy3x3X7oRbrGAQAAEP7GR6nH2G1anHdlHZtL8lKU4vROxztQ28HzZQCX5Grt9R0vyCEYv1IE4wAAIGS8c7ZTDV2DkqRNi7KVlhBruCIAwHR9aEWBlo+Nl/zd2S69UNVkuCIAAABg5gZH3DrR7A2mFuUmyxnruKLP57DbtGa+d5x6a++QTrf1X3GNACLX+I7xxDiHclPiDVcT/gjGAQBAyBjvFpekD5YXGKwEADBTdrtNX7l5omv82y8dl9tDFwwAAADC04mmXt/z2dLCK9svPm6d3zj1A4xTB3ARI26PznQMSPKOUbfZbIYrCn8E4wAAICRYlqXnx/aLO+w23VTKGHUACFfvX5arVfPSJUnvNvXquXfqzRYEAAAAzFBVfZfv+Er3i49bO9YxLkkVtR2z8jkBRJ4z7f2+N+awX3x2EIwDAICQUFXfrTPt3ndAXrMgUxlJcYYrAgDMlM1m01/estR3+9svvasRt8dgRQAAAMDMVI3tF5ek0oLZ6RhfWZSuWIe385OOcQAXMz5GXSIYny0E4wAAICT4j1Hfwhh1AAh71y7M1qZFWZKkuvZ+/azirOGKAAAAgOmrbvALxmdplLoz1qGr5qZLkmpa+9TaOzQrnxdAZCEYn30E4wAAwDj/Meo2m3RzGWPUASASfOXmia7xf957QoMjboPVAAAAANPj9lg6OhaMz81IUFpC7Kx97rXFjFMHcGk1BOOzjmAcAAAYd6K5VzUt3id664ozlZviNFwRAGA2rJqXoRuXe9/s1Ng9qCfeOm24IgAAAGDqatv61D/sfXNn2Sx1i49bNz/Td1zBOHUAF+BqIRifbQTjAADAuOePNPiOt5TnG6wEADDbvnzzEtm86xP1vVdOqXdo1GxBAAAAwBRV++0XLytMm9XPvWb+RMf4gdN0jAM4X22bNxjPTIpTemKc4WoiA8E4AAAwzn+/+GaCcQCIKMsLUrX1qkJJUlvfsP7jdZfhigAAAICpqfILxksLZrdjPCMpTotzk71f51yX+od5AymACf3Do2roGpREt/hsIhgHAABG1bT06lhjjyRp1bx0FaQlGK4IADDbvnTTEjns3rbxH7xWo87+YcMVAQAAAJdXVd/lOy6bM7vBuCStLfaOUx/1WDp8pnPWPz+A8FXb2u87Ls4iGJ8tBOMAAMCo3X7d4oxRB4DIVJKdpD9aPVeS1DM4qu+/WmO4IgAAAODSLMvyjVLPTIpTfqpz1r/GuuKJceoVtYxTBzDB1TqxX3xBDsH4bCEYBwAARu2ZFIwXGKwEABBIf3HjYsU5vL+C7nqjVs09g4YrAgAAAC6uuWdIbX3eSUelBamy2Wyz/jXWjXWMS9KB2vZZ//wAwpertdd3zCj12UMwDgAAjDnT3q8j57xjycrnpKooM9FwRQCAQJmTnqA7NsyTJA2MuPVvvz5luCIAAADg4qr99ouXFc7+GHVJmpuRoLzUeEnSodMdGnV7AvJ1AISfGr+OcYLx2UMwDgAAjKFbHACiyz03LFJCrEOS9ORv63Suc8BwRQAAAMCF+e8XLw1QMG6z2Xx7xvuG3TrW2BOQrwMg/NT6BePsGJ89BOMAAMCY5ysbfMfsFweAyJeTEq9tm4olScNuj/75VyfMFgQAAABcRFUQOsYlad38iT3jjFMHMG58x3hhmlMJcQ7D1UQOgnEAAGBEQ9eA3q7rlCQtzUvRgpxkswUBAILiz967UCnOGEnSzw+dVU1L72UeAQAAAARfdYM3GE+IdagkO3CvWawrmdgzXlHbEbCvAyB8dPQNq6N/RJJUzBj1WUUwDgAAjHjBf4z6CrrFASBapCXG6s/eu0CS5PZY+g5d4wAAAAgx3YMjOt3WL0laVpAih90WsK+1LD9VyfHeN44eqG2XZVkB+1oAwoOrjf3igUIwDgAAjHie/eIAELW2bSpRVlKcJOm5d+pV7TemEgAAADDtqN/z09KCwI1RlySH3abVY+PUm3uGdKZ9IKBfD0Doc7UQjAcKwTgAAAi6lp4h396sBTlJWpLHGHUAiCZJ8TG6+/qFvtvffum4wWoAAACAycbHqEtSWWFawL8ee8YB+BvfLy55XzvF7CEYBwAAQfdCVaPGJ4NtKc+XzRa4kWQAgND0iWvmqyDNKUn61dFmHapjnyIAAABCQ1W9fzAe2I5xSVpb7Ldn/DTBOBDt/IPxkmwaimYTwTgAAAi6PYxRB4Co54x16AvvX+y7/a0X6RoHAABAaBgPxh12m5bmpwT8611dlK6YsT3mB2p5wygQ7caD8Ri7TXMzEgxXE1kIxgEAQFB19A1rX02bJKkoMyEo77wGAISmj62dq/lZiZKkN0626c2TrYYrAgAAQLQbHvXoZHOPJGlhTpKcsY6Af82EOIfK53hHtp9s7lV733DAvyaA0GRZli8YL8pMVKyDKHc28bcJAACC6qXqJrk93jnqW8oLGKMOAFEs1mHXl25c4rv9zRePyxrftQEAAAAY8G5Tj0bc3uekpQXBezP/uuKJPeMHT9M1DkSrpu4hDYy4JUkl2ewXn20E4wAAIKh2Vzb4jreU5xusBAAQCrauLNSSPO/OtLfrOrX3aLPhigAAABDNqiftF08L2tedtGe8lj3jQLSqae31HROMzz6CcQAAEDRdAyN6fWxMbkGaUyvnppstCABgnMNu05dvXuq7/dCLx+Xx0DUOAAAAM6ob/IPx4HWMr50/0TG+n2AciFrjY9QlgvFAIBgHAABB8/KxJt84slvK8mW3M0YdACDdXJqnlXO93TjHGnv0yyMNl3kEAAAAEBhV9V2+49IgBuNZyfFamOMNwSrPdWlg2B20rw0gdLhaJoLxBQTjs45gHAAABM3zRxp9xx9cUWCwEgBAKLHZbPrKLRNd49956V2Nuj0GKwIAAEA08ngs3yj1OekJSk+MC+rXXzc2Tn3Ebemds51B/doAQkNtm1/HeA7B+GwjGAcAAEHRNzSqV99tkSRlJ8drjd+IMAAArluUrQ0l3hcCa1r79ItD5wxXFDpeffVVbd26VYWFhbLZbHrmmWcuef4vfvEL3XTTTcrJyVFqaqo2btyoF1544bzzHnnkERUXF8vpdGrDhg3av39/gP4EAAAA4aGuvV99Y53awewWH8eecQA1Y6PUnbF25aU4DVcTeQjGAQBAUPz6eLOGRr3df5vL8+RgjDoAwI/NZtNf+nWNf3fvCQ2NMj5Skvr6+rRy5Uo98sgjUzr/1Vdf1U033aTnn39eBw8e1A033KCtW7fq7bff9p3z9NNPa/v27XrggQd06NAhrVy5Urfccouam5sD9ccAAAAIeVX1E/vFSwuCH4yvK55oIjhQ2xH0rw/ArFG3R3Vt/ZKk4qwk1lAGQIzpAgAAQHTY7TdGfUs5Y9QBAOdbW5ypG5bm6NfHW3Suc0BP/bZOf7KpxHRZxm3ZskVbtmyZ8vkPP/zwpNvf+MY39Oyzz+q5557TqlWrJEnf/va39bnPfU7btm2TJD366KP65S9/qccff1x//dd/fcHPOzQ0pKGhId/t7m7vC8cej0ceD6PvI43H45FlWXxvEVBcZwgWrjVM1aT94gUp07pmZuM6m5vuVE5KvFp6hnTwdIdGRt00FuA8/EyLXHXtfRr1WJKkkuwk49/jcLnWplMfwTgAAAi4gWG3fn3c24GWkRjrG5ULAMDv+/LNS/Xr497VG//661P6+LoiJcbxq+uV8Hg86unpUWam99/f4eFhHTx4UDt27PCdY7fbdeONN2rfvn0X/TwPPvigdu7ced79LS0tGhwcnP3CYZTH41FXV5csy5LdzsBBBAbXGYKFaw1T9XZti+84L25kWtN0Zus6W5GfoJd7htQ7NKq3jp7W4pzEGX8uRCZ+pkWuw66JN+fkJsj4RK9wudZ6enqmfC6vLgAAgID7zbst6h/b0XVzab5iHKH7RAoAYFb5nDR9aEWBfnmkQa29Q9r1Zq3+/PpFpssKaw899JB6e3v18Y9/XJLU2toqt9utvLy8Sefl5eXp2LFjF/08O3bs0Pbt2323u7u7VVRU5Ntljsji8Xhks9mUk5MT0i+CIbxxnSFYuNYwVSfbKiVJaQmxWrFwjmy2qXdrz9Z1tmlJv14+0SlJOtVt06ay3Bl/LkQmfqZFrvYTfb7j8vk5ys01+/9/uFxrTufUd7ETjAMAgIDbU9ngO968It9gJQCAcPClm5Zod2WDPJb0/d/U6M4N85WWEGu6rLD05JNPaufOnXr22Wev+EWV+Ph4xcfHn3e/3W4P6RdJMHM2m43vLwKO6wzBwrWGy2nuGVRLj3dtTFlhqhwOx7Q/x2xcZ+tLsnzHB+s6WS2EC+JnWmQ63TbgO16QkxIS399wuNamU1vo/ikAAEBEGBp1a+9R79ifFGeMNi3MNlwRACDULcpN1q2r5kqSugZG9O+v1RiuKDz95Cc/0Wc/+1n99Kc/1Y033ui7Pzs7Ww6HQ01NTZPOb2pqUn4+b2ADAADRqbq+23dcVmhuGs7yghQlxnlD+QOudlmWZawWAMHlap3oGC/JTjJYSeQiGAcAAAH1xslW9QyNSpJuWp6nuBiefgAALu+LNy5WrMM7uvLx111q6x0yXFF4eeqpp7Rt2zY99dRT+tCHPjTpY3FxcVqzZo327t3ru8/j8Wjv3r3auHFjsEsFAAAICVV+wXipwWA8xmHX6nkZkqTG7kGd7Ri4zCMARIrxYDwtIVYZiUxNCwRemQYAAAG1+0ij73jLigKDlQAAwklRZqL+eN08SVLfsFvfe+WU4YrM6e3t1eHDh3X48GFJksvl0uHDh1VXVyfJu/v7rrvu8p3/5JNP6q677tK3vvUtbdiwQY2NjWpsbFRXV5fvnO3bt+uxxx7Tj370Ix09elR33323+vr6tG3btqD+2QAAAEJFdYN/x3iawUqktcUZvuOK0+0GKwEQLIMjbp3r9L4RpiQ7STabzXBFkYlgHAAABMyI26MXq71jWpPiHHrPYsaoAwCm7gvvXyRnrPfX1h+/dVoNXdHZLVNRUaFVq1Zp1apVkryh9qpVq3T//fdLkhoaGnwhuST94Ac/0OjoqO655x4VFBT4/rvvvvt859x222166KGHdP/99+vqq6/W4cOHtWfPHuXl5QX3DwcAABAixkepx8fYtcDwCOP1xZm+4wO1HQYrARAstW0TY9RN/wyKZDGmCwAAAJHrrZo2dQ2MSJJuWJYrZ6zDcEUAgHCSm+rUpzYW6/uv1mh41KN/efmkvnHrCtNlBd31119/yd2Su3btmnT7lVdemdLnvffee3XvvfdeQWUAAACRoXdo1DfCeFl+imIcZnsKr56XLofdJrfHUkUtHeNANHC1sF88GOgYBwAAAfO83xj1DzJGHQAwA59/30Ilx3vf0/3TA2d02u9d9AAAAMBsONbgv1/c7Bh1SUqMi1H52J7zd5t61dk/bLgiAIHm8vtdtySHYDxQCMYBAEBAuD2WXqr2BuPOWLuuX5pjuCIAQDjKSIrTZ99TIkka9Vh6+FcnDFcEAACASFNV7x+MpxqsZMJav3HqB08zTh2IdP4d48VZBOOBQjAOAAAC4kBtu1p7ve9ovn5JrhLj2OACAJiZz1xXoozEWEnS/7x9Tj87eEYvHmvXWzVtcnsuPmIcAAAAmIqq+i7fcVmIBOPrijN8x+wZByLf+DoHiVHqgcQr1AAAICB2H2nwHW9ZkW+wEgBAuEtxxuru6xfqG88fkyT91X9Xjn3EpYI0px7YWqrN5azsAAAAwMxUj41St9uk5fmhEYyvmT/RMc6ecSDyjQfjeanxSoonvg0UOsYBAMCs83gs7anyjlGPc9j1/mW5hisCAIS7/FTnBe9v7BrU3U8c0p7Khgt+HAAAALiUEbdH7zb2SvJ2aSbEOQxX5JWTEu/rGv3d2S4NjrgNVwQgULr6R9TW5528Sbd4YBGMAwCAWff2mQ41dQ9Jkt6zOFspzljDFQEAwpnbY+nB3ccu+LHxQeo7n6tmrDoAAACm7URTr4bdHklSWWGa4WomWzvfO0592O3RkXNdlzkbQLhytfmPUU82WEnkIxgHAACzbveRRt/x5nLGqAMArsx+V7saugYv+nFLUkPXoPa7GDEJAACA6Rkfoy6Fzn7xceuKJ8apH2CcOhCxav32iy+gYzygCMYBAMCssixLuyu9wXiM3aabSvMMVwQACHfNPRcPxWdyHgAAADCuqn6iE7s0xILxtcUZvuMDvAkUiFg1fsF4McF4QBGMAwCAWXXkXJfOdQ5IkjYuzFJ6YpzhigAA4S435cL7xWd6HgAAADCuqt6/Yzy0RqmXZCcpO9n7ukrF6Q55WB0ERCRXq/8odYLxQCIYBwAAs2q8W1ySPriiwGAlAIBIsb4kUwVpTtku8nGbpII0p9aXZF7kDAAAAOB8lmXp6FgwXpDmVGZSaL2532azae1873PcnsFRvdvcY7giAIHgau2VJNlt0rzMRMPVRDaCcQAAMGssy9LuIw2SvE/kbmaMOgBgFjjsNj2wtVSSzgvHx28/sLVUDvvFonMAAADgfGfaB9QzNCpJKi0IrTHq4yaNU6/tMFgJgECwLEuuFm/HeFFmouJiiG4Dib9dAAAwa4419qi2rV+St7svKznecEUAgEixubxA3/vEauWnTR6Xnp/m1Pc+sVqby5lSAgAAgOmpbpjYL14WYvvFx60rnpiKVFHLnnEg0rT0DKlv2C2JMerBEGO6AAAAEDkYow4ACKTN5QW6qTRfv61p1cmzLVo0N0cbFmTTKQ4AAIAZ8d8vXhpi+8XHlRamKiHWoYERtyroGAciDvvFg4uOcQAAMGvGx6hL0i1l+QYrAQBEKofdpmsWZOnmZZm6ZkEWoTgAAABmzD8YD9WO8ViHXavmpUuSznUO6FzngNmCAMwqgvHgIhgHAACz4mRzj04090qS1s7PUF6q8zKPAAAAAAAAMKd6LBhPdcZobkaC4Woubi3j1IGIRTAeXATjAABgVuw+MjFGfXM53eIAAAAAACB0tfUOqbF7UJJ3XLnNFrqTiNYVZ/iOGacORJYagvGgIhgHAACzwn+/+Bb2iwMAAAAAgBA2ab94QWjuFx+3al6GxjcIHaBjHIgo4x3jcTF2FaaF7uSKSEEwDgAArtjptj5VN3h/oVw5N01z0nkSBwAAAAAAQtf46xhS6O4XH5ccH6PSsRqPN/Woa2DEcEUAZoPbY6murV+SVJKVJLs9dCdXRAqCcQAAcMX8u8U3l9MtDgAAAAAAQpt/x3jZnNAOxiVp7XzvnnHLkg6dZpw6EAnqOwc07PZIYox6sBCMAwCAKzZpjDr7xQEAAAAAQIirqu+S5B1fvDAn2XA1l7euONN3zDh1IDJM2i+eQzAeDATjAADgipzrHNA7ZzolScsLUlXMuxsBAAAAAEAI6x8e9e31XZqXolhH6Ecl64ozfMcVtXSMA5HA1dLrOy7J4jXVYAj9n/YAACCk7fHrFv8g3eIAAAAAACDEHW3okWV5j0sLQn+MuiTlpjo1PytRknT4bKeGRt2GKwJwpVx0jAcdwTgAALgiu480+I63rCAYBwAAAAAAoa16bIy6FB77xceN7xkfHvWo8lzXZc4GEOomjVJnCmdQEIwDAIAZa+4e1ME67/iuRbnJWpSbYrgiAAAAAACAS6tu6PYdlxWGTzDuP079AOPUgbA33jGe4oxRVlKc4WqiA8E4AACYsReqGn2jxxijDgAAAAAAwkFVvTcYt9mkZfnhE4yvLc70HVfUthusBMCVGhxx61zngCRpQXaSbDab4YqiA8E4AACYseePTOwX31xeYLASAAAAAACAyxtxe3SssUeSVJKVpKT4GMMVTd3CnCRlJMZKkipOd8jjsQxXBGCmzrT3+xqOGKMePATjAABgRtp6h/RbV5skqTgrUcsLGKMOAAAAAABCW01Ln4ZHPZKk0jAaoy5JNpvN1zXe2T+iUy29hisCMFP++8WLCcaDhmAcAADMyIvVTRp/Y/Lm8gLG/QAAAAAAgJBXVd/lOw63YFxizzgQKVx+wTgd48FDMA4AAGZkd+XEGPUPrmC/OAAAAAAACH3VY/vFJamsMM1gJTPjv2f8AHvGgbDlapkIxhdkJxusJLoQjAMAgGnr6h/RmydbJUlz0hO0Yk74/SIJAAAAAACiT5VfMF5aEH4d4+WFaYqP8UY7BONA+HJNGqWeaLCS6EIwDgAApu2lo00aHZujvrk8nzHqAAAAAAAg5FmW5RulnpsSr5yUeMMVTV9cjF1XF6VLks52DKiha8BsQQBmZHzHeE5KvFKcsYariR4E4wAAYNr2VDb4jhmjDgAAAAAAwsG5zgF1D45KksrCcL/4uPUlE+PUK9gzDoSdnsERtfYOSWK/eLARjAMAgGnpGRzRq+96x6jnpcZrVVGG4YoAAAAAAAAuryrM94uP898zXsE4dSDs1Lb2+45LsgjGg4lgHAAATMvLx5o17PZIkjaX5ctuZ4w6AAAAAAAIfZP2i4dxx/jqeekafznmAB3jQNipae31HZfkEIwHE8E4AACYlt1HGn3Hm8sLDFYCAAAAAAAwddWTOsbDNxhPccZqWb63/mON3eoeHDFcEYDpcI3tF5cYpR5sBOMAAGDK+odH9cq7zZKkrKS4STutAAAAAAAAQll1fZckKSU+RkUZiYaruTLrir2r7TyW9HZdp9liAEyLfzC+gGA8qAjGAQDAlP3meIsGR7xj1G8uy5eDMeoAAAAAACAMdPQNq75rUJK0vCA17FfDsWccCF/jwbjNJs3LCu836YQbgnEAADBlz1dOjFHfUp5vsBIAAAAAAICpq26IjP3i49aOdYxL0gGCcSBsWJblC8bnZiQoPsZhuKLoQjAOAACmZHDErZePNkmS0hJitXFhluGKAAAAAAAApqZqbIy6FBnBeEFaguZmJEiSDp/p1PCox3BFAKairW9YPYOjkqTiLMaoBxvBOAAAmJLXTrSqb9gtSbqpNE+xDp5GAAAAAACA8FBVP9ExXhYBwbgkrRsbpz444lGlX/APIHSxX9wsXtEGAABTsruywXfMGHUAAAAAABBOqseC8ViHTYtzUwxXMzv8x6mzZxwID66WiWC8hGA86AjGAQDAZQ2PevSrau8Y9eT4GF23ONtwRQAAAAAAAFMzMOzWqZZeSdLi3BTFxURGNDLeMS5JB2o7DFYCYKpq/DrGS3KSDVYSnSLjpz8AAAioN0+1qnts980HlucqPsZhuCIAAAAAAICpOdbYLY/lPY6UMeqStCgnWemJsZK8HeOWZRmuCMDluFp7fceMUg8+gnEAAHBZeyobfcdbygsMVgIAAAAAADA91Q2Rt19ckux2m9bO945T7+gf0Sm/Ec0AQlNta78kKc5hV2F6guFqog/BOAAAuKRRt0cvVHmD8YRYh963JMdwRQAAAAAAAFNXVT8RjJcWphmsZPat9Runzp5xILR5PJZcbd43sMzLSpTDbjNcUfQJWjD+yCOPqLi4WE6nUxs2bND+/fsveX5nZ6fuueceFRQUKD4+XkuWLNHzzz8fpGoBAMC4/a52dfSPSJLevyxXCXGMUQcAAAAAAOGj2i8YX16QYrCS2beuOMN3zJ5xILTVdw1oeNQjSSphjLoRMcH4Ik8//bS2b9+uRx99VBs2bNDDDz+sW265RcePH1dubu555w8PD+umm25Sbm6ufv7zn2vOnDk6ffq00tPTg1EuAADws9tvjPrm8nyDlQAAAAAAAEyP22PpWKM3GC/OSlSKM9ZwRbOrfE6a4mLsGh71qOI0HeNAKHO1Tqw7YL+4GUHpGP/2t7+tz33uc9q2bZtKS0v16KOPKjExUY8//vgFz3/88cfV3t6uZ555Rps2bVJxcbHe9773aeXKlcEoFwAAjPF4LO0ZG6MeF2PXDcvOf0MbAAAAAABAqKpp6dXgiLdDszSC9ouPi49x6Oq56ZKk0239au4eNFsQgIvyD8bpGDcj4B3jw8PDOnjwoHbs2OG7z26368Ybb9S+ffsu+Jj//d//1caNG3XPPffo2WefVU5Oju644w791V/9lRyOC49vHRoa0tDQkO92d7f3HWAej0cej2cW/0QIBR6PR5Zl8b1FQHGdIVhC+Vo7UNuulh7vv6/vW5ytxFh7SNaJywvl6wyRhWsNwRBO11k41AgAABDJqhsmxqiXRdh+8XFrizO0f2y/eMXpDn1wRYHhigBcSE0LwbhpAQ/GW1tb5Xa7lZeXN+n+vLw8HTt27IKPqamp0csvv6w777xTzz//vE6ePKk///M/18jIiB544IELPubBBx/Uzp07z7u/paVFg4O8QyrSeDwedXV1ybIs2e1BGXyAKMR1hmAJ5WvtF/vP+I6vnZeo5uZmg9XgSoTydYbIwrWGYAin66ynp8d0CQAAAFGtym+/eCR2jEvSuuJMSackSftd7QTjQIiqbfMLxnMIxk0Iyo7x6fJ4PMrNzdUPfvADORwOrVmzRufOndM3v/nNiwbjO3bs0Pbt2323u7u7VVRUpJycHKWmRuY/dtHM4/HIZrMpJycn5F8IQ/jiOkOwhOq15vFYetVVJUmKddh06/pFSk2IrD1c0SRUrzNEHq41BEM4XWdOp9N0CQAAAFGtqr7Ld1xWEJlZwep5GbLZJMsSe8aBEDY+Sj0pzqGc5HjD1USngAfj2dnZcjgcampqmnR/U1OT8vPzL/iYgoICxcbGThqbvnz5cjU2Nmp4eFhxcXHnPSY+Pl7x8edfRHa7PeRfKMHM2Gw2vr8IOK4zBEsoXmvvnO1QQ5d36sqmRdlKT+LJWrgLxesMkYlrDcEQLtdZqNcHAAAQySzLUvVYx3h2crxyUyPzTYtpibFampeiY409qq7vVu/QqJLjQ7IvEohaw6MenWnvl+TtFrfZbIYrik4B/w09Li5Oa9as0d69e333eTwe7d27Vxs3brzgYzZt2qSTJ09O2sX27rvvqqCg4IKhOAAAmH17Kht9x1vKL/xmNgAAAAAAgFDV0DWojv4RSVJZhI5RH7e2OEOS5LGkt+s6DFcD4PfVtffLY3mPS7KTzRYTxYLy1vXt27frscce049+9CMdPXpUd999t/r6+rRt2zZJ0l133aUdO3b4zr/77rvV3t6u++67T++++65++ctf6hvf+IbuueeeYJQLAEDUsyxLu8eCcYfdpptKCcYBAAAAAEB4iYb94uO8e8a9DtQSjAOhZnyMuiSVZLNf3JSgzNK47bbb1NLSovvvv1+NjY26+uqrtWfPHuXl5UmS6urqJo2XKyoq0gsvvKAvfelLuuqqqzRnzhzdd999+qu/+qtglAsAQNSrqu9W3dhon2sWZCoziYktAAAAAAAgvFT7BeOR3jHuH4xX1LJnHAg1rtZe3/ECgnFjgrZk4t5779W99957wY+98sor5923ceNGvfXWWwGuCgAAXMjkMeoFBisBAAAAAACYmar6Lt9xWWGawUoCrzA9QXPSE3Suc0Bv13VqxO1RrCMoQ4MBTIGrtd93TMe4OfxUBAAAk1iWpecrGyRJNpt0c1me4YoAAAAAAACmb3yUelKcQ/MzEw1XE3jje8YHRtyTuuUBmOffMV5MMG4MwTgAAJjkRHOvalq8O2/WFWcqN8VpuCIAAAAAAIDp6eof0bnOAUnS8oJU2e02wxUF3tpJe8YZpw6EkvEd41lJcUpLiDVcTfQiGAcAAJPsPuI/Rj3fYCUAAAAAAAAzU9UwMUa9NML3i49bN9YxLkkVtR0GKwHgr29oVE3dQ5IYo24awTgAAJhk99gYdUnaTDAOAAAAAADCkP8o8bIoCcaX5KYoxRkjSao43S7LsgxXBECa6BaXCMZNIxgHAAA+NS29OtbYI0laNS9dBWkJhisCAAAAAACYvsnBeJrBSoLHbrdp7Xxv13hr7/CkMA6AOZOC8RyCcZMIxgEAgM/uSsaoAwAAAACA8Fc1FozH2G1anJdsuJrg8d8zzjh1IDTU+gXjC+gYN4pgHAAA+OyZFIwXGKwEAAAAAABgZgZH3DrZ0itJWpSbrPgYh+GKgmedXzB+oLbdYCUAxvl3jBcTjBtFMA4AACRJZ9r7deRclySpfE6qijITDVcEAAAAAAAwfe829cjt8e7XjpYx6uOumpumOIc3+qk4Tcc4EApq/IPxLIJxkwjGAQCAJLrFAQAAAABAZKjy2y9eWphqsJLgc8Y6dNVc75sBXK19aukZMlwREN0sy1LN2ASLOekJcsZGzwSLUEQwDgAAJEm7Kxt8x+wXBwAAAAAA4araLxgvi7JgXJq8Z/zgacapAyZ19I+oe3BUklTCGHXjCMYBAIAaugZ0qK5TkrQ0L0ULcpLNFgQAAAAAADBDVfVdvuNo6xiXpHXFGb7jA7WMUwdMcrX2+o4Jxs0jGAcAAHrBf4z6CrrFAQAAAABAeHJ7LB1t6JEkFWUmKNUZa7ii4FszfyIYr6ilYxwwqaZlYr84wbh5BOMAAEDPs18cAAAAAABEgNq2Pg2MuCVJZQVphqsxIz0xTkvyvNMAK+u71T88argiIHrVthGMhxKCcQAAolxLz5AOjL17eEFOku8XJwAAAAAAgHBTFeX7xceN7xl3eywdHlufByD4XK0E46GEYBwAgCj3YnWjLMt7vKU8XzabzWxBAAAAAAAAMxTt+8XHsWccCA3jo9Rj7DbNzUgwXA0IxgEAiHK7jzBGHQAAAAAARIbqSR3j0TlKXZLWzs/0HR9gzzhghMdj+Uapz8tKVIyDWNY0vgMAAESxjr5h7atpkyQVZSZE9YgxAAAAAAAQ3izL8gXjWUlxykuNN1yROXMzEpSf6pQkHarr0KjbY7giIPo0dg9qcMT7/94CxqiHBIJxAACi2EvVTXJ7vHPUt5QXMEYdAAAAAACErabuIbX1DUvyjlGP5tc5bDab1o6NU+8fdutoQ4/hioDow37x0EMwDgBAFNtd2eA73lKeb7ASAAAAAACAK1PdwH5xf+tLGKcOmOQfjBcTjIcEgnEAAKJU9+CIXj/ZKkkqSHNq5dx0swUBAAAAAABcgapzE/vFSwsIxv33jFecJhgHgo2O8dBDMA4AQJTae7RJI27vGPVbyvJlt0fveDEAAAAAABD+quongvGywjSDlYSGpfkpSomPkSQdqO2QZVmGKwKii38wviA72WAlGEcwDgBAlNp9pNF3/MEVBQYrAQAAAAAAuHLVDd5gPCHWQXemJIfdptXzvXvGW3qGVNfeb7giILqMB+MJsQ7lpcYbrgYSwTgAAFGpb2hUv3m3RZKUnRyvNWO/JAEAAAAAAISj7sERX/C7rCBFDibjSZLWFU+85nOgtsNgJUB0GXF7fD+TSrKTZLPxMykUEIwDABCFfn28WUOjHknS5vI8flkEAAAAAABh7eikMersFx+3tthvz3gte8aBYDnT3i+3x7u+oCSHCRahgmAcAIAotLtyYoz6lnLGqAMAAAAAgPDGfvELWzk3XbEOb0PEAYJxIGhq2/z3ixOMhwqCcQAAoszgiFu/PtYsScpIjNWGkszLPAIAAAAAACC0+QfjpQV0jI9LiHOofI73jQKnWvrU1jtkuCIgOtS0TATjxVkE46GCYBwAgCjzm3db1D/sliTdXJqvGAdPBwAAAAAAQHirbvAG4w67TUvzUwxXE1rW+Y9TP82ecSAYXK0TwTij1EMHr4QDABBldh9p8B1vXpFvsBIAAAAAAIArNzTq1ommHknSopxkOWMdhisKLWvnZ/iO2TMOBId/MM4o9dBBMA4AQBQZGnVr71HvGPUUZ4w2Lcw2XBEAAAAAAMCVOdHUq1GPJUkqLWSM+u9b69cxfqCWjnEgGMaD8YzEWKUnxhmuBuMIxgEAiCJvnGxVz9CoJOmm5XmKi+GpAAAAoe7VV1/V1q1bVVhYKJvNpmeeeeaS5zc0NOiOO+7QkiVLZLfb9cUvfvG8c3bt2iWbzTbpP6fTGZg/AAAAQIBV++0XLyMYP09mUpwW5SZLkirPdWlgbMUegMAYGHaroWtQklRCt3hI4dVwAACiyO4jjb7jLSsKDFYCAACmqq+vTytXrtQjjzwypfOHhoaUk5Ojr371q1q5cuVFz0tNTVVDQ4Pvv9OnT89WyQAAAEFVVd/lO6Zj/MLWFXvHqY96LB0+02m2GCDC1bb57RfPTjZYCX5fjOkCAABAcIy4PXrpaJMkKSnOofcsZow6AADhYMuWLdqyZcuUzy8uLtZ3v/tdSdLjjz9+0fNsNpvy8/OvuD4AAADTqvw6xksLCMYvZO38TD21/4wk757xjQuzDFcERC7//eIl2YkGK8HvIxgHACBKvFXTps7+EUnSDcty5Yx1GK4IAACY1Nvbq/nz58vj8Wj16tX6xje+obKysouePzQ0pKGhId/t7m7vC9Aej0cejyfg9SK4PB6PLMvie4uA4jpDsHCtRTaPx9LRBu/zkjnpCUp1xhj5Xof6dbZmfrrv+EBte8jWicsL9WsN0qmWXt9xcVZi2H6vwuVam059BOMAAESJ3ZUTY9Q/yBh1AACi2tKlS/X444/rqquuUldXlx566CFde+21qqqq0ty5cy/4mAcffFA7d+487/6WlhYNDg4GumQEmcfjUVdXlyzLkt3OJj4EBtcZgoVrLbLVdQyqb2xn9qKseDU3NxupI9Svs3jLUnZSrFr7RlRxul0NjU1y2G2my8IMhPq1BunomTbfcZp9yNjPpSsVLtdaT0/PlM8lGAcAIAq4PZZerPIG485Yu65fmmO4IgAAYNLGjRu1ceNG3+1rr71Wy5cv1/e//319/etfv+BjduzYoe3bt/tud3d3q6ioSDk5OUpNZWRppPF4PLLZbMrJyQnpF8EQ3rjOECxca5HtQGOD7/jq4mzl5uYaqSMcrrP1JfV6vrJR/cMedXgSVJrPc7hwFA7XWrRr7DvlO161eK4S48Izjg2Xa83pdE753PD8TgAAgGk5UNuu1t5hSdL1S3LD9skYAAAIjNjYWK1atUonT5686Dnx8fGKj48/73673R7SL5Jg5mw2G99fBBzXGYKFay1yHW2c6BQsn5Nu9Hsc6tfZupJMPT82UfBgXafK56abLQgzFurXWrQb3zFekOZUsjPOcDVXJhyutenUFrp/CgAAMGv2+I1R37Ii32AlAAAgFLndbh05ckQFBaxbAQAA4aWqvtt3XFpIB/SlrCvO9B3vr203WAkQuTr7h9XRPyJJKslOMlwNfh/tYgAARDiPx9LuSu9YsTiHXe9fZmakGAAAmJne3t5Jndwul0uHDx9WZmam5s2bpx07dujcuXP68Y9/7Dvn8OHDvse2tLTo8OHDiouLU2lpqSTp7//+73XNNddo0aJF6uzs1De/+U2dPn1an/3sZ4P6ZwMAALhS48F4emKsCtOmPk43Gi3LT1FSnEN9w25V1LbLsizZbOwZB2bTeLe4JBUTjIccgnEAACLc22c61dQ9JEl6z+JspThjDVcEAACmo6KiQjfccIPv9vie70996lPatWuXGhoaVFdXN+kxq1at8h0fPHhQTz75pObPn6/a2lpJUkdHhz73uc+psbFRGRkZWrNmjd58801fcA4AABAOmnsG1drrfc2jrDCVkPcyYhx2rZ6foddOtKqpe0hnOwZUlJlouiwgovgH4wsIxkMOwTgAABFu95EG3/HmcsaoAwAQbq6//npZlnXRj+/ateu8+y51viR95zvf0Xe+850rLQ0AAMCoSWPUCxijPhVr52fqtROtkqQDte0E48As8w/GGaUeetgxDgBABLMsS7vH9ovH2G26qTTPcEUAAAAAAACzo9ovGC8rTDNYSfhYV5LhOz5Q22GwEiAy1RCMhzSCcQAAIljluW6d6xyQJG1cmKX0xDjDFQEAAAAAAMyOycE4HeNTcXVRumLs3pHzFbXthqsBIo+rxRuMO+w2JjKEIIJxAAAi2POVE2PUP7iiwGAlAAAAAAAAs6uqvkuSFB9jpzNzihLjYlQ2x9tdf6K5Vx19w4YrAiKHZVmqbfMG4/MyExXrIIYNNXxHAACIUJZl+faL223SzYxRBwAAAAAAEaJ3aFS1bf2SpGUFqYohgJqydfMnxqkfPM04dWC2NPcMqX/YLUkqzqJbPBTxLwUAABHqWGOP7xfE9SWZykqON1wRAAAAAADA7DjawBj1mVpbnOk7PnCacerAbKlp8d8vnmywElwMwTgAABFqd2Wj75gx6gAAAAAAIJJUnevyHZcWEIxPx9riiY7xilo6xoHZ4mr1C8ZzWO8QigjGAQCIUONj1CXplrJ8g5UAAAAAAADMrmo6xmcsOzleC8Z2sv/ubKcGR9yGKwIig6u113c8/v8YQgvBOAAAEehkc69ONHufiK2dn6G8VKfhigAAAAAAAGZPVb03GLfbpGX5BOPTNd41PuK29M6ZTrPFABFiUsc4wXhIIhgHACAC7amc6BbfXE63OAAAAAAAiBzDox6929QjSVqQk6yEOIfhisKP/57xitOMUwdmw3gw7oy1K59GpZBEMA4AQAR6/sjEfnGCcQAAAAAAEElONvdqxG1JYoz6TK3zC8YP1LYbrASIDKNuj+ra+yVJxVlJsttthivChRCMAwAQYU639fn2bK2cm6a5GYmGKwIAAAAAAJg9VfVdvmOC8ZkpzkpUdnKcJOng6Q65PZbhioDwdq5zwPeGHcaohy6CcQAAIszuSv9u8QKDlQAAAAAAAMy+8f3iklRakGawkvBls9l8XeM9g6O+0fQAZqaG/eJhgWAcAIAI4x+Mb2GMOgAAAAAAiDDjk/IkOsavxKQ944xTB66Iq4VgPBwQjAMAEEHOdQ7onTOdkqTlBakq5kkYAAAAAACIIB6PpaNjHeOFaU5lJMUZrih8rSvO8B0fqO0wWAkQ/lx+HeMLcnhNNlQRjAMAEEH2+HWLf5BucQAAAAAAEGHOdPSrZ2hUklRKt/gVKS1IVWKcQxId48CVck0apZ5ssBJcCsE4AAARZE9lg+94ywqCcQAAAAAAEFmq/feLF7Jf/ErEOOxaNS9dklTfNahznQNmCwLC2HgwnuqMUUZirOFqcDEE4wAARIjm7kFVnPaOvVqUm6xFuSmGKwIAAAAAAJhdVf7BeAEd41dq7Xz2jANXanDErfou7xtLSnKSZbPZDFeEiyEYBwAgQrxQ1SjL8h4zRh0AAAAAAESiqvou33EZo9Sv2LriiWB8v4tgHJiJ0239vtdlF2SzXzyUEYwDABAhdvvtF99cXmCwEgAAAAAAgMCobvB2jKc6YzQ3I8FwNeHv6nnpcti93a0VtR2GqwHCk6u113dcQjAe0gjGAQCIAG29Q3qrpk2SVJyVqOUFjFEHAAAAAACRpbV3SE3dQ5Kk0sJUxhXPguT4GN9I+uNNPerqHzFcERB+asb2i0sE46GOYBwAgAjwUnWTPGPjejaXF/CLIQAAAAAAiDjVfvvFywrTDFYSWdYWZ/iOD9YxTh2YLlcLwXi4IBgHACACPO83Rn0L+8UBAAAAAEAEqpoUjLNffLb47xk/wDh1YNpq2yaC8WKC8ZBGMA4AQJjr6h/RmydbJUlz0hN01VzeMQ0AAAAAACJPVX2X77iUYHzW+HeMV9TSMQ5Ml2tslHpuSryS42MMV4NLIRgHACDMvXS0SaNjc9Q3l+czRh0AAAAAAESk6gZvx3hcjF0Lc5INVxM5clOcKs5KlCS9c6ZLgyNuwxUB4aNrYEStvcOSGKMeDgjGAQAIc3sqG3zHH1zBGHUAAAAAABB5+oZGfV2Zy/JTFOsg3phNa8fGqQ+7Pao813WZswGMq22dGKO+IIdgPNTxLwcAAGGsZ3BEr57wjlHPS43XqqKMyzwCAAAAAAAg/Bxr7JblHZin0gLGqM+2dX7j1NkzDkydyy8Yp2M89BGMAwAQxl4+1qzhUY8kaXNZvux2xqgDAAAAAIDIU13f7TsuY7/4rBvvGJfYMw5MR82kYJwVD6GOYBwAgDC2p7LRd7y5vMBgJQAAAAAAAIFT5ReMlxamGawkMi3ITlJmUpwkqeJ0hzwey3BFQHionRSMJxqsBFNBMA4AQJjqHx7Vr483S5KykuK0viTzMo8AAAAAAAAIT+PBuM3m3TGO2WWz2bR2vnecetfAiE409xquCAgP46PU7TapKJNgPNQRjAMAEKZ+c7xFgyPeMeo3l+XLwRh1AAAAAAAQgUbcHh1v6pHk3eGbFB9juKLItM5vnPoBxqkDl2VZli8Yn5uRqPgYh+GKcDkE4wAAhKndfmPUt5TnG6wEAAAAAAAgcE619Gp41NscUMYY9YBZW5zhO2bPOHB5Lb1D6h0aleR90w5CH8E4AABhaHDErb1HmyRJaQmx2rgwy3BFAAAAAAAAgVF1zm+/eEGqwUoiW1lhmpyx3tjoQG2H4WqA0Odq8d8vTjAeDgjGAQAIQ6+faFXfsFuSdFNpnmId/JMOAAAAAAAiU3XDRDBeVkgwHihxMXZdXZQuSTrXOaD6zgGzBQEhbnyMuiQtyCEYDwe8ig4AQBh6vrLBd8wYdQAAAAAAEMmq6rt8x6UE4wG13m/PeMVpusaBS3G1TQTjxVkE4+GAYBwAgDAzPOrRr6q9Y9ST42N03eJswxUBAAAAAAAEhmVZqq73doznpcYrOznecEWRba1/MM6eceCSGKUefgjGAQAIM2+ealX34Kgk6QPLcxUf4zBcEQAAAAAAQGCc7RjwvQ5SVphmuJrIt2peuuw27zF7xoFLGx+lHhdjV2F6guFqMBUE4wAAhJk9lY2+4y3lBQYrAQAAAAAACKyq+on94qUFjFEPtBRnrJaP/T0fa+xW9+CI4YqA0OT2WDrd1i9JKs5KlGP8HSUIaQTjAACEkVG3Ry+OjVFPiHXofUtyDFcEAAAAAAAQONUNE8F4GfvFg2Ld2Dh1y5IOsWccuKD6zgENuz2SGKMeTgjGAQAII/td7WrvG5YkvX9ZrhLiGKMOAAAAAAAiV3V9l++YUerBsbY4w3d8gD3jwAXVtPrvF082WAmmg2AcAIAwsttvjPrm8nyDlQAAAAAAAATe+Cj1lPgYzc1gh28wrJ2f6TtmzzhwYbV+wfgCOsbDBsE4AABhwuOxtKfKG4zHxdh1w7JcwxUBAAAAAAAETnvfsBq6BiVJywtTZWeHb1DkpzlVlOl9E8I7Zzo1NOo2XBEQelx+wXgxwXjYIBgHACBMHKzrUEvPkCTpfUtylBwfY7giAAAAAACAwKmuZ7+4KevGusaHRj2qPNd9mbOB6DN5lDrBeLggGAcAIEzsPjIxRn0LY9QBAAAAAECEq/LbL15aQDAeTGuLJ8apV7BnHDiPq7VXknfNQ3ZynOFqMFUE4wAAhAHLsrSnskGSFOuw6QPL8wxXBAAAAAAAEFjVDf4d42kGK4k+64ozfMfsGQcmGxp162zHgCSpJCdJNhtrHsIFwTgAAGHgnbNdqh/bqbVpUbbSEmINVwQAAAAAABBYVWOj1OMcdi3KTTZcTXRZlJusjETv608HT7fL47EMVwSEjrq2fllj/0swRj28EIwDABAGdh9p8B0zRh0AAAAAAES6gWG3alq8o4oX5yUrLoY4I5hsNpvWjO0Z7+gfUc3Y2GgAkov94mGLf0kAAAhxlmVpd6V3v7jDbtNNpQTjAAAAAAAgsh1r7NZ4k3JZIfvFTWCcOnBhBOPhi2AcAIAQV93Qrbr2fknSNQsylZkUZ7giAAAAAACAwBofoy6xX9yUtcWZvuMDte0GKwFCC8F4+CIYBwAgxO0+0ug73lJeYLASAAAAAACA4PAPxkvpGDeifE6q4sdG2FfQMQ741PgF48UE42GFYBwAgBBmWZaer/TuF7fZpJvL8gxXBAAAAAAAEHjVDRPB+PICgnET4mMcWlmULkmqa+9XU/eg2YKAEDHeMZ6dHK9UZ6zhajAdBOMAAISwE829qmnxPtFaV5yp3BSn4YoAAAAAAAACa9Tt0bGxYLw4K1HJ8TGGK4pek/eMM04d6BkcUUvPkCRpAd3iYYdgHACAEDZ5jHq+wUoAAAAAAACCo6a1T0OjHknsFzfNf88449QBqba133fMfvHwQzAOAEAI2z02Rl2SNhOMAwAAAACAKFDNfvGQsXpehmw27zEd44DkamO/eDgjGAcAIES5Wvt0rLFHkrRqXroK0hIMVwQAAAAAABB4VfVdvmOCcbPSEmK1NC9FknS0oVs9gyOGKwLMcrVMBON0jIcfgnEAAEKUf7c4Y9QBAAAAAEC0qG6Y6BgvIxg3bn2Jd5y6x5Lerus0WwxgmKu113e8IIdgPNwQjAMAEKIm7xcvMFgJAAAAAABAcFiWpaqxUeo5KfHKTXEargiT94wzTh3RzdXq7Ri32aR5mYmGq8F0EYwDABCCzrT368g579iw8jmpKuJJFgAAAAAAiAL1XYPq7PeO6y4toFs8FKwrzvAdH6jtMFgJYJZlWaoZC8bnpCfIGeswXBGmi2AcAIAQtKeSbnEAAAAAABB9qusZox5qCtISNCc9QZL09pkOjbg9hisCzGjrG1bP4Kgk9ouHK4JxAABCEPvFAQAAAABANKqq7/IdlxWmGawE/sa7xgdHPL5R90C0qR3rFpcIxsMVwTgAACGmsWtQh+o6JUlL81K0ICfZbEEAAAAAAABB4h+6ltIxHjL894wfcLFnHNGphmA87AUtGH/kkUdUXFwsp9OpDRs2aP/+/VN63E9+8hPZbDZ95CMfCWyBAACEiD3+3eIr6BYHAAAAAADRY3yUenJ8jOZnJhquBuPW+QfjtQTjiE4ugvGwF5Rg/Omnn9b27dv1wAMP6NChQ1q5cqVuueUWNTc3X/JxtbW1+spXvqL3vOc9wSgTAICQsJv94gAAAAAAIAp19g/rXOeAJGl5QYrsdpvhijBucW6yUp0xkqSK0x2yLMtwRUDwuVomgvEF2Uz5DEcxwfgi3/72t/W5z31O27ZtkyQ9+uij+uUvf6nHH39cf/3Xf33Bx7jdbt15553auXOnXnvtNXV2dl7yawwNDWloaMh3u7vb+64yj8cjj8czO38QhAyPxyPLsvjeIqC4zhAs/tdaS8+Q9o+967YkO0mLchK5BjEr+JmGYOFaQzCE03UWDjUCAACEimr/MeoFjFEPJXa7TWuLM/XysWa19w2rprVPC1n/hygz3jEe67BpTkaC4WowEwEPxoeHh3Xw4EHt2LHDd5/dbteNN96offv2XfRxf//3f6/c3Fx95jOf0WuvvXbZr/Pggw9q586d593f0tKiwcHBmRWPkOXxeNTV1SXLsmS3B20jAKIM1xmCxf9ae7ayTeNvuH1vSYpaWlrMFoeIwc80BAvXGoIhnK6znp4e0yUAAACEjeqGiWC8rDDNYCW4kLXFGXr5mHcScEVtO8E4oorHY6m2zRuMz89KkoOJFmEp4MF4a2ur3G638vLyJt2fl5enY8eOXfAxr7/+un74wx/q8OHDU/46O3bs0Pbt2323u7u7VVRUpJycHKWm8s6ySOPxeGSz2ZSTkxPyL4QhfHGdIVj8r7U36up89//h+gXKzeWXQMwOfqYhWLjWEAzhdJ05nU7TJQAAAISNKv+O8UJe1w81k/eMd+i2dfMMVgMEV0P3oIZGvRPBirPYLx6ugjJKfTp6enr0yU9+Uo899piys7On/Lj4+HjFx8efd7/dbg/5F0owMzabje8vAo7rDMFis9nUNTiqfTXeMepFmQlaMTddNhvvPMTs4WcagoVrDcEQLtdZqNcHAAAQSqrquyRJMXabFufRjRxqrpqbprgYu4ZHPaoYWwUIRItJ+8VzCMbDVcCD8ezsbDkcDjU1NU26v6mpSfn5+eedf+rUKdXW1mrr1q2++8Z3ssXExOj48eNauHBhYIsGAMCAXx1tltvjnaO+pbyAUBwAAAAAAESNwRG3To0FT4vzUhQf4zBcEX5ffIxDK+em6UBth2rb+tXcM6jcFCYkITq4Wnt9xyXZBOPhKuBvXY+Li9OaNWu0d+9e330ej0d79+7Vxo0bzzt/2bJlOnLkiA4fPuz77w/+4A90ww036PDhwyoqKgp0yQAAGLG7stF3vKX8/DePAQAAAAAARKrjjT2+hoEyxqiHrLV+49QP1nYYrAQIrprWiY5xgvHwFZRR6tu3b9enPvUprV27VuvXr9fDDz+svr4+bdu2TZJ01113ac6cOXrwwQfldDpVXl4+6fHp6emSdN79AABEit4ht9442SpJKkhzauXcdLMFAQAAAAAABNGk/eIFBOOhal1xhr43dnygtkNbVhQYrQcIFpdfML6AYDxsBSUYv+2229TS0qL7779fjY2Nuvrqq7Vnzx7l5eVJkurq6ti7BgCIaq/VdGrE7X1X9C1l+bLbGaMOAAAAAACiR3VDl++YjvHQtWbeRMd4xWn2jCN6jAfjSXEO5aTEG64GMxWUYFyS7r33Xt17770X/Ngrr7xyycfu2rVr9gsCACCEvHKy03f8Qd5pCwAAAAAAoox/x/hygvGQlZYYq6V5KTre1KOq+m71DY0qKT5oURNgxPCoR2c7BiRJxdlJstloagpXtGkDAGBY39Co3qr1vis6Ozlea+ZnGK4IAAAAAAAgeNweS8caeiRJ8zITleqMNVwRLmVtsfe1K7fH0tt1nWaLAYLgTEe/3B7vtE/2i4c3gnEAAAxyeyw99mqNhsbGqN9clisHY9QBAAAAAEAUcbX2aWDELYkx6uFgXfHEOPUDtYxTR+RztbBfPFIw3wIAAEP2VDZo53PVauga9LuvSe9d3KDN5YxTBwAAAAAA0aGqfmK/eGkBwXioG+8Yl9gzjugwvl9ckkpyCMbDGR3jAAAYsKeyQXc/cWhSKC5JHX3DuvuJQ9pT2WCoMgAAAAAAgOCqbpjYL142h2A81M1JT1BBmlOS9HZdp0bcHsMVAYFV4x+MZycbrARXimAcAIAgc3ss7XyuWtYFPjZ+387nqn17awAAAAAAACJZdb1fMF6YZrASTIXNZtPasXHq/cNuHfV7YwMQiVytvb7jkiw6xsMZwTgAAEG239V+Xqe4P0tSQ9eg9rsYRQUAAAAAACKbZVmqGgvGs5LilJsSb7giTMV6v3HqB2o7DFYCBF5ta78kKTMpTmmJsYarwZUgGAcAIMiaey4eis/kPAAAAAAAgHDV1D2k9r5hSVJpYapsNpvhijAV4x3jklRRS3MHIlff0Kgau72v05Zk0y0e7gjGAQAIstwU56yeBwAAAAAAEK6q6rt8x4xRDx9L8lKU4oyR5O0YtyxWAiIy1bb57xcnGA93BOMAAATZ5d73bJNUkObU+pLMy5wJAAAAAAAQ3qr89ouXFqYarATT4bDbtGa+d5x6a++QTrf1G64ICAxXK8F4JCEYBwAgiGpb+3T3fx286MfHQ/MHtpbKYWd0GAAAAAAAiGzVfsF4GcF4WFnnN059P+PUEaFcLRPB+AKC8bBHMA4AQJB09Y/o07sOqKN/RJK0vCBF+amTx6Xnpzn1vU+s1ubyAhMlAgAAAAAABFVVg3eUemKcQ8VZhE7hZO1Yx7jEnnFErkkd4zn8jAp3MaYLAAAgGgyPevT5Jw6qZuyJ1OLcZD39ZxuVFBej39a06uTZFi2am6MNC7LpFAcAAAAAAFGha2BEZ9oHJEnL8lN4TSTMrCxKV6zDphG3pYraDtPlAAHh8tsxPj+TYDzc0TEOAECAWZalrz5zRPtq2iRJ2clxevxP1inVGSuH3aZrFmTp5mWZumZBFr8AAgAAAACAqHG0wX+MeprBSjATzliHVszxft9qWvvU2jtkuCJg9o13jBemOZUQ5zBcDa4UwTgAAAH26G9q9NOKs5KkuBi7fnDXWhVlJhquCgAAAAAAwKwq9ouHPf8943SNI9J09A2rc2wtJmPUIwPBOAAAAfT8kQb9055jvtvf+thKrZ6XcYlHAAAAAAAARIeq+i7fcSnBeFhaOykYZ894oLk9lt6qadOLx9r1Vk2b3B7LdEkRrcZ/v3g2wXgkIBgHACBADp/p1JeePuy7/ZWbl2jrykJzBQEAgLD06quvauvWrSosLJTNZtMzzzxzyfMbGhp0xx13aMmSJbLb7friF794wfN+9rOfadmyZXI6nVqxYoWef/752S8eAADgEqrHOsYddpuW5KUYrgYzsXb+RAPIgdN0jAfSnsoGXfdPL+uOf9+v+/e4dMe/79d1//Sy9lQ2mC4tYrkmBePJBivBbCEYBwAgAM51DuizP6rQ0KhHkvTR1XN0zw2LDFcFAADCUV9fn1auXKlHHnlkSucPDQ0pJydHX/3qV7Vy5coLnvPmm2/q9ttv12c+8xm9/fbb+shHPqKPfOQjqqysnM3SAQAALmpo1K2Tzb2SpEU5yXLGsrs3HGUkxWlxrjcwrDrXpf7hUcMVRaY9lQ26+4lDauganHR/Y9eg7n7iEOF4gLhae33HC+gYjwgE4wAAzLKewRF9ZtcBtfYOSZLWl2TqwY+ukM1mM1wZAAAIR1u2bNE//MM/6NZbb53S+cXFxfrud7+ru+66S2lpaRc857vf/a42b96sv/zLv9Ty5cv19a9/XatXr9a//uu/zmbpAAAAF/VuY69Gx8ZAs188vI2PUx/1WDp8ptNsMRHI7bG087lqXWho+vh9O5+rZqx6ANS29vuOiwnGI0KM6QIAAIgko26PvvDU2zrW2CNJKs5K1Pc/sUbxMbzrGQAAhI59+/Zp+/btk+675ZZbLjmmfWhoSENDQ77b3d3e0acej0cejycgdcIcj8cjy7L43iKguM4QLFxroamyvtN3vLwgJey/P9F8na2dn66n9tdJkg642nVNSeZlHoHp+G1N23md4v4sSQ1dg/ptTauuWZAVvMKiQM1Yx3iM3abCtPio+/87XH6uTac+gnEAAGbR1/9ftV453iJJSkuI1eN/sk4ZSXGGqwIAAJissbFReXl5k+7Ly8tTY2PjRR/z4IMPaufOnefd39LSosHBi79Qh/Dk8XjU1dUly7JktzNwEIHBdYZg4VoLTQdPNfmOCxM8am5uNljNlYvm66wkeSKUevPdJt1WzgSA2XTibNuUzjt5tkULkt0BriZ6eCxLrhbvjvHCtDh1tLUarij4wuXnWk9Pz5TPJRgHAGCW7HrDpR/tOy1JinXY9P1PrtGCnGTDVQEAAMyOHTt2TOoy7+7uVlFRkXJycpSayoufkcbj8chmsyknJyekXwRDeOM6Q7BwrYUmV2eN7/ja0nlKS4g1WM2Vi+brLCfHUl7qCTV1D6mysU+ZWdmKcUTX30Gg9A6N6oUTrimdu2hujnJz6RifLQ1dAxoc9b7pY1FeqnJzcw1XFHzh8nPN6XRO+VyCcQAAZsHLx5r09/+v2nf7G7euYHQRAAAIWfn5+Wpqapp0X1NTk/Lz8y/6mPj4eMXHx593v91uD+kXSTBzNpuN7y8CjusMwcK1Flo8HkvHGrxrWeZmJCgj6fznGOEomq+ztcWZ+uXvGtQ37Na7zX0qn5NmuqSwd7ShW/f81yHVtPZd9ty81HhtWJAtu90WhMqiw+m2Ad/xguzkqPz/WgqPn2vTqS10/xQAAISJow3d+sKTb8tjeW/fc8NCfWxtkdmiAAAALmHjxo3au3fvpPteeuklbdy40VBFAAAgmtS29alv2DvyubSAyTORYN38DN/xgdp2g5WEP8uy9JP9dfrII2/4QnFnjDfOu1jsnRjn0GiI74EON/5vSCjJSTJYCWYTwTgAAFeguXtQn9l1wPfL3IdWFOjLNy01XBUAAIgkvb29Onz4sA4fPixJcrlcOnz4sOrq6iR5R5zfddddkx4zfn5vb69aWlp0+PBhVVdPTLe57777tGfPHn3rW9/SsWPH9Hd/93eqqKjQvffeG7Q/FwAAiF7VY93iklRWSGdxJFhbnOk7rqjtMFhJeOsbGtX2n76jv/7FEQ2NjfEuK0zVni++V49+YrXy0yaPjHaMJeWu1n793f9W//6nwxVw+Qfj2QTjkYJR6gAAzNDAsFuf/XGF6rsGJUlXF6XrWx9fycgiAAAwqyoqKnTDDTf4bo/v+f7Upz6lXbt2qaGhwReSj1u1apXv+ODBg3ryySc1f/581dbWSpKuvfZaPfnkk/rqV7+qv/mbv9HixYv1zDPPqLy8PPB/IAAAEPWq6v2DcTrGI8Gy/BQlx8eod2hUB2rbZVmWbDZeI5uO4409+vP/OqhTLROB7Cevma+//dByOWMdKs5O0k2l+fptTatOnm3Rork5SoqP1ce/v09Dox49tb9OK+ak6Y4N8wz+KSJHLcF4RCIYBwBgBjweS196+rB+d7ZLkjQnPUGP3bVWzliH4coAAECkuf7662VZ1kU/vmvXrvPuu9T54z72sY/pYx/72JWUBgAAMCP+wXgpwXhEiHHYtWpeul470armniGdaR/QvKxE02WFBcuy9LOKs7r/fys1OOLtEk+Oj9GDH12hrSsLJ53rsNt0zYIsLUh2Kzc3S3a7XQ9+dIW2//QdSdID/1uppfkpWuM32h4zM94xnhDrUF6K8zJnI1wwSh0AgBn4vy8c156qRkneJ6qP/8k65aTEG64KAAAAAAAg9FWPBeMZibEqSCNwihTr/Maps2d8avqHR/Xln76j/++/f+cLxUsLUvXcF647LxS/mI+unqttm4olSSNuS3c/cVDN3YOBKjkqjLg9qmvvlyQVZycxITSCEIwDADBNTx+o06O/OSXJ+y7NR+5craX5KYarAgAAAAAACH3N3YNq7R2S5N0vzrjtyOEfjFecJhi/nOONPfqDf31Dv3j7nO++OzfM0y/+/Nppj+7+mw8u14YS799/c8+Q7v6vQxoe21GO6TvbMaBRj3cK1wLGqEcUgnEAAKbhzZOt+tv/qfTd/rs/KNP7luQYrAgAAAAAACB8MEY9cl1dlK6Ysc7aA7UdhqsJbT+rOKMPP/K6Tjb3SpKS4hz659tX6R9vXTGjVY2xDrseuXO1CscmMBw83aGdz1XNas3RxNXa6ztmv3hkIRgHAGCKTjb36vNPHPS9W3DbpmJ98pr5hqsCAAAAAAAIH9UNE8F4GcF4REmIc6h8Tpok7+to7X3DhisKPeOj0//y5xOj05flp+i5L1ynP5ji6PSLyU6O16OfXKO4GG/091+/rdNP9tddcc3RqKalz3dMMB5ZCMYBAJiC9r5hfXrXAXUPjkqS3r8sV1/9UKnhqgAAAAAAAMJLVX2X75hgPPKsK87wHR88Tde4vxNNPfrwv76h/z501nff7evn6Zl7NmlBTvKsfI2r5qbrG7eu8N2+/9kqHarj+zBdtW0TwXgxwXhEIRgHAOAyhkbd+tMfV6iuvV+StLwgVf98+yo57OzAAgAAAAAAmI7xUerOWLtKsmcnDEToWOu3Z/xALXvGx/33wbP6g399QyfGRqcnxjn03T++Wg9+dGaj0y/lj9bM1Z9cWyxJGnZ7dPcTB9XcMzirXyPSuVongnF2jEcWgnEAAC7Bsiz91c9/p4qxd7jmpsTrh59aq+T4GMOVAQAAAAAAhJeewRGdbvM2HizLT6XpIAKtnT/RMU4wLg0Mu/WXP3tHX/7ZOxoYcUuaGJ3+4avnBOzr/u2Hlmv92JsUmrqHdM9/HdLwqCdgXy/SuMZGqacnxiojKc5wNZhNBOMAAFzCP+89qWcO10uSEmId+uGn1qkwPcFwVQAAAABCidtjad+pNj17+Jz2nWqT22OZLgkRimsN4e5oQ4/vuJQx6hEpKzleC3K8HbaV57o0MOw2XJE5J5t79OFHXtfPDvqPTi/SM/ds0sJZGp1+MbEOux65c7UK0pySpAO1HfqHX1YH9GtGioFht+q7vB327BePPLS7AQBwEc8ePqfv/OpdSZLNJj38x1drxdw0w1UBAAAACCV7Khu087lqNXRNjCgtSHPqga2l2lxeYLAyRBquNUQC9otHh3XzM1XT0qcRt6V3znbqmgVZpksKul8cOqu//Z9KX5d4YpxD37h1hT6yKnBd4r8vJyVej35ijT72/X0aHvXox/tOq3xOmj6+tihoNYQj//3iBOORh45xAAAuoKK2XX/5s9/5bu/Ysky3lOUbrAgAAABAqNlT2aC7nzg0KaiUpMauQd39xCHtqWwwVBkiDdcaIkX12H5xSSorpPkgUq0tnhinXhFl49QHht36q5//Ttt/OjE6fWleiv733uuCGoqPW1mUrn/4SLnv9lf/p1KHz3QGvY5wwn7xyEYwDgDA76lr69ef/udBDbu9e3duX1+kz71ngeGqAAAAAIQSt8fSzueqdaFB1uP37XyumlHXuGJca4gkVWPBuN3mDQsRmdaN7baWvCO8o8XJ5l595JE39HTFGd99t631jk5flBvY0emX8vG1RfrkNfMlScNujz7/nwfV0jNkrJ5Q5x+MFxOMRxyCcQAA/HQNjGjbrv1q7xuWJG1alKW//3C5bDab4coAAAAAhJL9rvbzunf9WZIauga13xVdnXKYfVxriBTDox6daPbuGF+Yk6yEOIfhihAo87MSlZ0cL0k6dLojKt6488zb5/QH//q6jjd5r/GEWIe+9bGV+qc/uiokrvWv/Z9SrRvr5G/sHtQ9Tx7SyFhTECbzD8YZpR55CMYBABgz4vboz//roE61eJ/8LMxJ0r/duUaxDv65BAAAADBZc8/Fg8qZnAdcDNcaIsWJ5h6NuL0BKfvFI5vNZtP6Em8I2zM0quONPYYrCpzBEbd2/OJ3+uLTh9U/7B2dviQvWc99YZP+cM1cw9VNiIux65E7Vysv1fuGhf2udv3jL48ario0TeoYzyIYjzS80g8AgCTLsvS1Zyr1xsk2SVJmUpz+40/WKy0h1nBlAAAAAEJRbopzVs8DLoZrDZGiym+/eCnBeMRbO39inHrF6cicaHGqxTs6/an9E6PTP7Zm7tjo9NBbFZCb4tSjn1ijuLEmoF1v1urnB88arir0jAfj+alOJcXHGK4Gs41gHAAASY+9VqOfHPA+iY2Lseuxu9ZoXlai4aoAAAAAhKr1JZkqSLt4EGmTVJDm1PqSzIueA0zF+pJM5abEX/TjXGsIF9V+wXhZYZrBShAMkb5n/NnD5/QH//K6jo11wztj7XroYyv1zY+tVGJc6Iapq+Zl6OsfKfPd/pv/OaLfne00V1CI6ewf9q3YZIx6ZCIYBwBEvT2VjXpw9zHf7W/+0VVaM58XFAAAAABcnMNu0/3/p/SiH7ckPbC1VA67LXhFISI57DatLEq/6Me51hAu/IPx0gI6xiPd8oIUJY7t1j7gapdlRcaece/o9CO67yeH1Tc2On1xbrL+997r9EchNDr9Um5bN093bpgnSRoe9ejz/3lQrb1DhqsKDZP2i+cQjEcignEAQFQ7crZLX3z6bY0/N//SjUv04avnmC0KAAAAQFhIcV589VJinEObFmUHsRpEqrbeIb1+ovWiH89PdeoDy/OCWBEwfR6PpeoGbzBemOZURlKc4YoQaDEOu1bP8+4Zb+we1NmOAcMVXbmall7d+m9v6qn9db77Prp6jp69d5OW5IXe6PRLeWBrmdbM935/6rsGdc9/HdKI22O4KvNq2/yCcfaLRySCcQBA1GroGtBnfnRAgyPeJ323rpqjv/jAIsNVAQAAAAgX//56je/4izcu1nf/+Gq9d7E3DO8fdutHb9YaqgyR5LHXXBoY8XYlfvKaeXrqc9fou7ddrcW53hfsG7sH9eRv6y71KQDjznT0q3doVJJUyhj1qLG2OMN3HO57xp97p15b/+V1HR17g4cz1q5v/tFV+vbHrw7p0ekXExdj1/fuXO1b1fFbV7u+8fxRw1WZ52rxC8YZpR6RCMYBAFGpb2hUn95VoeYe75igdcUZ+v/94QrZbIyeAwAAAHB5J5t79MrxFknSnPQE3XvDIn346jna+eFyjU+0fuw1l3oGRwxWiXDX1jukH++rlSTFOey654bF2rgwSx9eNUf/949W+s77zq/eVWf/sKEqgcurmrRfnDHq0SIS9owPjrj1t/9zRF946m3f6PSFOUl69p7r9LG1RYaruzK5qU597xNrFOvwPnH5jzdq9YtDZw1XZVYNo9QjHsE4ACDquD2W/uKpt33v8JyXmajvf3Kt4mMchisDAAAAEC5++Hqt73jbpmLFOLwvs5VkJ+kjq7zrmboGRugaxxV57DWX+seCmNvXFyk/zen72Kp5Gbp17Frr7B/Rd/eeMFIjMBVV9V2+41KC8ahxdVG6HGPvFquoDb+O8drWPn30397Uf/lN5bh11Rz9773XaWl+eI1Ov5g18zO08w/Kfbd3/OKIKs91XeIRkW18x7jDblNRRqLhahAIBOMAgKjzj788qr3HmiVJqc4YPf4n65TJbisAAAAAU9TeN+zrqEqOj9Ft6yZ3jH3h/Yt9XeP//jpd45iZ9r7hSd3in79+4Xnn/H+bl8oZ632J9z/3ndbJ5t5glghMWTUd41EpKT7G9/1+t6k3rCZb/L/f1ev//Mvrqh5rrImPseuf/nCFvv3xlUqKD7/R6Zdyx4b/f3t3Hh9Vff1//D3ZAySB7AESkrAHZN8ioKIoKFLXilgU16p1t/1a7U+l1LZWq60bat1XVGitC1hQWRQURFaFsCdhTcISspA9M/f3xySTBMISyNw7y+v5qI/OndyZORM+JHzm3HNOiiYPS5EkVdU6dOu7q3TwcJXFUZnPMAxXYjy5Q7hCgkih+iL+VAEAfuXdZbl647scSVJQgE0vTxmsbvHtLI4KAAAAgDd5f/kOVdU6JEmThiYrIiy4ydfTYtvq0gENlbzvLNtheozwfq8uyXZVi189LFlJUeFHnZMUFa7bznYmzGsdBvNh4bHqW6lHhQerU/uj1zJ815AuDe3UV+3w/HbqlTV2PfLJet05c40OV9VKktLj2urTO0dq0tAUnx3D+MdfZGhgSntJ0p6iCt05c41q7Q5rgzLZvtIq1+9d5ov7LhLjAAC/sXjzPv3x8yzX8Z8v7aszu8VaGBEAAAAAb1NVa9c7y52J7gCbdP2Zqc2ed+e53RrNGs+mahwtUlhW7WrDHxIYoNubqRavd+tZXZVU12J94aZ9+mbLfjNCBE7a/tIq7St1Vp9mJEX6bGIRzRua2sF129PnjO84WKYrXvpe7y5vuKDt0gEd9fmdo9Qr0bc7HYQGBerlKYMVFxEqSVqWfVB/+98mi6MyV06j+eKpJMZ9FolxAIBf2JxfqjtnrpHdYUiSbj07XVfXtQgCAAAAgJP1+bo87a9L8Izvm6jk6ObnT6bHtaNqHKescbX4pKHNV4vXCw8J1O/H93Id/3lOlt9V+cGz1beilmij7o+GpDZUjHvynPG5P+Xp4ueWurobhAYF6G+Xn6F/Thrgc63TjyUhMkwv/WqQggOdF6+8tjRHn67dY3FU5mmcGE8nMe6zSIwDAHzevtJK3fjWj672R+P7JOr343qd4FEAAAAA0JRhGHp9aY7r+KZRacc9/8iq8fo9CXA8hWXVeuckq8Xr/aJ/Rw1Ibi9J2rrvsD5YsdONEQIts2Fvset2n04kxv1NXESoqy31T7uLVVljtziipqpq7Xr00/W6Y+Zqlda3To9tq0/uGKmrh/lu6/RjGZIarWkT+7iOf/+fn5r8HfZljRPjabGM3vRVJMYBAD6tssauW95ZpT1FFZKkfp2j9M9JAxQQ4F//qAUAAABw+pZtP6iNdZWPA5Lba1BKh+Oenx7XTpc0qhqvb40NHM9rS7JV1qhavONJzGMOCLDp0YkZruN/fLVFxeW074dnqK/AlaSMpCgLI4FVhnRx/r6stjv08x7PSbLuOFimK19a1qSryy/6d9Rnd41S7yT/vYjjV8NTNGlIsiSpssahX7+zSoVl1RZH5X7Z+xslxuOoGPdVJMYBAD7L4TD021nrtG5XkSQpKSpMr103ROEhgdYGBgAAAMArHVktfjJVZFSNoyUONZotHhxoO6lq8XqDUjrokgEdnc9TXqPnFm51R4hAi22sS4yHBAWoK8kmvzS0UTv1FTme0U79fz87W6fXJ+pDggL018vO0LNXD1A7P2mdfiw2m03TL+mj/nWdSPYUVeiuD1b7/JiOnAOHJTnb6CdFhlkcDdyFxDgAwGc9/dVmzf05T5LUNiRQr08dqnj+UQMAAADgFGzff1gLNu2TJHVqH64L+yae1OO6HlE1/s6yXHeFCB/w2tKWV4s39vvxvRQW7PzI9+3vc5W9/3Crxwi0RFlVrXIOOqsweyVGKCiQlIQ/GpLa0GHF6jnjVbV2/fGzDbr9/YbW6WmxbfXJb0bqmuH+1zr9WMKCA/WvKYMV2y5UkvTdtoN6cv5mi6Nyn1q7QzsLyyU51wPdRn0Xv4UAAD5p9spdmrFouyQpwCY9f81AZXT03xZIAAAAAE7Pm981VItPPbNLi5I7TarGv6VqHM07VFatt77LleSsFv/NOd1a/Bwd24fr12c5q8xrHYb++sXG1gwRaLFN+SUyDOftPnwu47fSYtsqpm2IJGnljkNyOAxL4thVWK5fvrxMbzUabXJxvyR9dudIPjdsRmJUmF781SAF1f0j5pVvs/XZur0WR+Uee4sqVWN3rsvUGDpb+DIS4wAAn7Ns+0H94b8/u44fvThD5/ZKsDAiAAAAAN7sUFm1/r1qtyRnN6pJQ1Na9Piuce30i/4NLa6pGkdzTrdavN5tZ6crIdJZ4ff1xn1auvVAq8UItFST+eIdmS/ur2w2m6tqvLSyVlv2lZoew7z1+brouSX6aXdD6/Q/X9pXz08eqIiwYNPj8RbD0qL16MQM1/ED/16nrEZ/r31F9oGGDivMF/dtJMYBAD4le/9h3fbeKtcVflMzu+j6kWkWRwUAAADAm81csVOVNc65mr8ckqyo8JZ/gH7nud2bVI2XUTWORpyzxXdIqp8t3vJq8XptQoL0+/G9XMePzcny+bmw8Fwb9jRKjCdRkevPGs8Z/zH3kGmvW13r0PTPN+i291aptNL5uzc1po0+vv1MTRnRhdbpJ+HaEV30y8GdJUmVNQ7d+t5KHSqrtjiq1pVzoMx1Oy2WxLgvIzEOAPAZh8qqdeNbP6q4okaSdE7POD1yccYJHgUAAAAAx1Zd69DbdS1XbTbpxlO88LZbfDtNbFI1vqO1QoQPeH1pjqvF/lVDktXpFKvF6106oJP6d3ZW524uKNVHK3eddozAqcjKcybGbTapd1KExdHASkMaJcbNmjPubJ3+vd6sG1MhSRPOSNLnd41S3050MDhZNptNj13aV/3qfq/sKqzQ3R+ukd2ilvju0Dgxnk5i3KeRGAcA+ISqWrtufXeVcg+WS5J6JUbo+ckDWzT3DwAAAACONOenvdpXWiVJuiAjQSkxbU75ue46t7vqC9Ne+XY7VeOQJBWVV7vm3QYH2vSbMadeLV4vIMDWpPXt019uUUllzWk/L9ASNXaHNuc7W2anx7ZVm5AgiyOClfp0jFR4cKAkaaUJFePzN+RrwnNLtK6+dXpggB67tK9euIbW6aciLDhQL08ZrNh2zlnxS7Ye0N/nb7Y4qtZDxbj/IFsAAPB6hmHooY9/1oq6q01j24Xq9euH8o9cAAAAAKfFMAy9vjTHdXzz6PTTer5u8U1njb+7nKpxNK0W/2UrVIvXG9wlWhf3S5IkFZZV64WF21rleYGTtW3fYVXXtfFnvjiCAwM0MKW9JGlPUYX2FFW45XWqax16bE6Wbn13lUrqWqenRLfRx785U9fSOv20dGwfrhnXDFJQ3WyYl7/Zrjk/7bU4qtaRvd+ZGI8MC1J02xCLo4E7kRgHAHi9GYu26ePVeyRJYcEBen3qkFb7IAEAAACA/1qeXagNe51tgPt1jtKQLh1O+zmbVo0za9zfFZVXu1r8Bgfa9Jtzurbq8z94YS+FBDk/An7zuxzlNqqIA9wta2/DfPE+HZkvDve3U999qFxX/WtZk4vaLjojUXPupnV6axmeHqOHJ/R2Hf/f7J+0Kb/kOI/wfJU1du0tdl6okRbblosnfByJcQCAV/t83V499eUW1/E/rxqg/sntrQsIAAAAgM9o/MH6TaPSWuWD0m7x7TSxn7NqvLCsmqpxP3dktXjnDqfeqr85nTu00a/rOh3U2A399YuNrfr8wPFsIDGOIwxNbbjArLXbqX+VVaCLnl2itbuKJDlbp//pkj6acc0gRdJVslVNPTNVlw/qJEmqqLHr1++sUlF5tcVRnbqdheUy6sal00bd95EYBwB4rdU7D+m3s9e5jn8/vpcuPCPJwogAAAAA+IqcA2VasKlAkpQUFaaLWnGvcfd53agah9urxevdfk5XxUWESpK+zCrQ99sOuOV1gCNt2Fvsup2RRGIc0sCUDqrrwq0fW6livMbu0F/mZumWd1a6WqcnR4frP7efqesyU6n+dQObzaa/XnaGzqirwt9ZWK67P1wru8OwOLJTU99GXZLSYttZGAnMQGIcAOCVdhWW69fvrFR1rXNW1VVDOuu2s09v3h8AAAAA1HvzuxxX9dDUM1MVHNh6H6N1i49oUjX+HlXjfumNRtXiVw5u/Wrxem1Dg/TAuJ6u4z/NyfLa5AW8h2EYyspzVownRoYppl2oxRHBE7QLDVJGXfeAzQWlKi6vOa3n21NUoav+tUyvLmno8HJh30TNuWu0zuhM63R3CgsO1MvXDnbN4/52y349/eVmi6M6NTmNxoykxVEx7utIjAMAvE5JZY1uevtHHTjsbNGTmR6jP196BleAAgAAAGgVReXVmr1ytyQpPDhQk4emtPprNK4a/9e32SqvpmrcnzSuFg8KsOmOMe6pFq93xaDO6tvJmYzalF+qWSt3ufX1gN2HKlRaV71LG3U0NqSLc864YTi7QZ6qBRudrdPX7CyS5Oy88ceJGXrxV4MUFU7rdDN0ah+uGdcMUmBdG4AXF2/XFz/nWRxVy+UcOOy6nU4rdZ9HYhwA4FVq7Q7d8f5qbSlw/oMlPbatXp4yWCFB/EoDAAAA0Do+WLFLFTV2Sc7uVFFtWv8D9m7xEbq48azxZVSN+5M3luao1I2zxY8UEGDToxf3cR0/NX+zSipPr1ITOJ4mbdRJjKORoanRrtun0k69xu7QX7/YqJveXqniCufPseTocP37tjN1/cg0CmdMltk1Rv/vot6u49/NXqfN+aUWRtRyjSvGU0mM+zyyCAAAr2EYhqZ9tkFLtjrnobVvE6w3rh/qlg+pAAAAAPinGrtDb3+fK0my2aQbRixt7w0AAF8ESURBVKa57bXuPrfprHGqxv1DcXlNk2pxd80WP9KwtGhNOCNJknSwrFozFm0z5XXhn7L2lrhuUzGOxoakdnDdXpnbsorxvUUVmvSvZXrl22zXfeP6JGjOXaPVP7l9a4WIFrphZKouG9hJklRebdev31152m3yzVSfGI+LCFW70CCLo4G7kRgHAHiNN77L1fs/7JTkbI/0yrVDuIoPAAAAQKv64uc85ZdUSpLG9k5w656je0JEk0Qls8b9w+vfNa4W76zkaPdWizf24IW9XB3X3lyaqx0Hy07wCODUbGiSGGfWMxokRIYppe7n3trdRaqqtZ/U4xZuKtBFzy3R6kat0x+9OEMvTxlM63SL2Ww2/fWyM1wXwew4WK57Ploju8OwOLITK6mscY3rTONzZr9AYhwA4BW+zirQn+dmuY6fuKKfhqVFH+cRAAAAANAyhmHotSU5ruObRrmvWrze3ed1b5g1/g1V476uuLxGby51rjFntXg3U18/ObqNbq5b19V2hx7/YpOprw//UZ8YjwgLUucO4RZHA09TXzVeXevQ+j3Fxz23xu7Q4//bqBvfWqmiuirkTu3DNfu2M3XjKFqne4rwkED969rB6lDX2XPx5v165ustFkd1YrmN2qgzX9w/kBgHAHi89XuKdfeHa2TUXWR497nddPmgztYGBQAAAMDn/Jh7SD/XfUDft1OkhptwMW6PI6rG31++0+2vCeu80aha/MrB5laL1/vNmG6KbRcqSZq3IV/Lth80PQb4toOHq1ydNzKSIklc4ihN54wfu5363qIKTX5luf71TUPr9PMzEvTF3aM1gNbpHqdzhzaacc0gBdT9lX9+4TbNW59nbVAn0Hi+OBXj/oHEOADAo+UXV+rmt1eqvNrZVmli/4667/weFkcFAAAAwBe9tqThg/ebTKxCa1I1/u12qsZ9VHFFjd74rqFa/I4x5laL12sXGqQHxvV0HT82J8sr2t3Ce2TlNbRRz2C+OJrRODG+Mrew2XMWbd6nCc8t0codzsR5UIBND0/orVeuHayoNrRO91RndovVHy7q7Tr+7ax12lpQamFEx5e9n8S4vyExDgDwWGVVtbrp7R9dVxkPSmmvv1/ZjyuNAQAAALS6HQfL9NXGAklSQmSoJpzR0bTX7pEQoYvqqsYPHKZq3Fe9sTRHpZXWVovXu2JwZ9cs2Ky8Ev171S7LYoHvyWK+OE6ga1xbV8vtlTsOydHo4pxau0NPzNukG978UYeatE7P1M2j0/lc0AvcNCpNlwxw/juqrNquX7+7SiWVNRZH1bzGFePpcSTG/QGJcQCAR7I7DN3z4VrXTKrOHcL1ynVDFBYcaHFkAAAAAHzRm9/lusY3TT0zVSFB5n5sdve5TavGK+q6ZsE3eEq1eL3AAJseuTjDdfz3+Vt0uIpOBWgdG5okxqkYx9FsNpuG1FWNF5XX6NUl2Vq2/aD2HKrQ5FeX66XF213nju0dr7l3j9LAlA5WhYsWstls+tvl/dQ7yfn3P+dAme77cG2TCyA8RX1iPMAmSy9Yg3lIjAMAPNLf/rdRX9dVa0SEBunN64e6ZqABAAAAQGsqrqjRrJXOitnw4EBdMyzF9Bh6Jh5RNf7DDtNjgPu8+V1DtfgVg6ytFq83Ij1GF/ZNlCQdOFylFxdtszgi+IoNe4slSSGBAeoW387iaOCpIsKCXLcf/98mTX51uUY9udA1c7y+dfqr1w1R+zYhVoWJUxQeEqhXrh2s9nWdARZs2qdnFmy1OKqmDMNQbl1ivFOHcIUGUZDlD0iMAwA8zvs/7NCrS5xX0gcG2PTilEHqnhBhcVQAAAAAfNWHK3aqvK5C+8rBnS37AP7uc7u7br/8DVXjvqK4okavL/WcavHGHrqwt0ICnR8Rv7Y0R7sKyy2OCN6uvLpW2XWJph6J7RQcSAoCR5u3Pk8fr95z1P31nVs6tAnWR7fSOt3bJUe30QuTBymg7o/wuQVb9eWGfGuDauTA4WqV1nVLSYvlIh5/wW8lAIBHWbJ1vx79dIPr+LFL+mp09zgLIwIAAADgy2rsDr39fa7r+IaRqZbF0jMxQhOoGvc5R1aLp8RYXy1eLyWmjW4clSZJqq516G//22RxRPB2m/JLXcnNPknMF8fR7A5D0z/POu45IUEBGpDc3pyA4FajusfqwQt7uY7vn7VO2/YdtjCiBk3mi8cyX9xfkBgHAHiMrQWl+s17q2Wvmzdzy+g0XTPc/BaGAAAAAPzH/9bna29xpSTnHNP0OGsrhu4+r3HVeDZV416uuKJGbyxt6IjmSdXi9e4Y01Wx7ZxdEub+nKcVOYUWRwRv1ni+eAbzxdGMFTmFyqv7vXssBSVV/CzyIbeMTtfF/ZwX/h2uqtWv312pksoai6OScg40JOjTSIz7DRLjAACPcOBwlW5460dX+5rzMxL04IW9LY4KAAAAgC8zDEOvL8l2HddXzlrJOWu8Ye4zVePe7a3vclXiqhbv5FHV4vUiwoL12wt6uo7/NGeDHHUXrAMtldUoMd6HxDiasa/0+Enxlp4Hz2ez2fTklf3UK9E5KjN7f5nu/2id5b9rshtVjJMY9x8kxgEAlqusseuWd1Zq96EKSc6N07NXD1BgADOEAAAAALjPqh2HtG53sSQpIylSmekxFkfkRNW4byiprNHrS50XXgQG2HTnmO4neIR1rhqS7EpYrN9Tov+s3m1xRPBWWXudP1NtNqlXEolxHC0+IqxVz4N3aBMSpFeuHaKo8GBJ0tcbC/Tcwq2WxpSzn8S4PyIxDgCwlMNh6Hez12nNziJJUmJkmF6fOlRtQoKsDQwAAACAz3u9rsW1JN00Kk02m2dcnNsrMbJJ1fjMFTstjginonG1+OUDPbNavF5ggE2PTsxwHT85f7PK6jq6ASer1u7QpvxSSVJqTFu1C+WzHRxtWFq0kqLCdKzfuDZJSVFhGpYWbWZYMEFKTBs9P3mg6muhnvl6q77KKrAsntyDzsR4SGCAOrYPtywOmIvEOADAUs98vUVzfsqTJLUJCdRrU4coMYorQgEAAAC4167Ccs3fkC9Jio8I1cT+HS2OqKmmVePbVVlD1bg3Kams0WtLGlWLn+t5s8WPdGbXWF2QkSBJ2l9apZcWb7c4Inib7ANlqqp1SGK+OI4tMMCmaXUX4hyZHK8/njYxg06SPuqsHnH6v3G9XMf3f7RW2/cfPs4j3MPuMJR7sFyS1CWmDevNj5AYBwBY5j+rduu5hdskOVtsPXf1QPXtFGVxVAAAAAD8wZvf5ap+tOV1mV0UEuRZH5P1SozUhX2dVeP7S6v0/g9UjXuTI6vFu8R4R4vWP1zUW8GBzuTAK0uytftQucURwZtsqGujLjFfHMc3vm+SXpoy6KjimMSoML00ZZDG902yKDKY4baz0zXhDOefcWlVrX79zkqVVtaYGsPeogpV113IQxt1/+JZ/+IHAPiNFTmFevDjn1zHD0/I0Ni6K9MBAAAAwJ1KKmv00Y/ORHNYcICuGd7F4oiaR9W4d/LGavF6qbFtdcPINElSda1Df/vfJosjgjfZsKfEdTuD+eI4gfF9k7T09+fqg1tG6NmrB+iDW0Zo6e/PJSnuB2w2m568sp96JkRIkrbvL9NvZ62To/6KRRPkHGg0XzyOxLg/ITEOADBd7oEy3fruStXYnf/Y+dXwFN04MtXaoAAAAAD4jVk/7lJZtTPJfPmgzopuG2JxRM3rndS0anwmVeNe4e1G1eKXeVG1eL07z+2mmLq/E3N+ytPK3EKLI4K3yMprSIz36UhHQJxYYIBNmV1jdMmATsrsGkM7az/SNjRIr1w3WJFhQZKkL7MKNGPRNtNev3FiPJ2Kcb9CYhwAYKri8hrd+NaPOlTubI8zunus/viLPrLZ+IcvAAAAAPertTv05ne5ruMb66pjPVXjqvGXqBr3eCWVNXptaY6kumrxMd5TLV4vMixY91/Qw3X8pzlZplbxwTsZhqENe52J8fiIUMVFhFocEQBP1yWmrZ6bPFD1Hwv/4+stWripwJTXblIxHtvOlNeEZyAxDgAwTXWtQ7e9t0rZdf/w6B7fTjN+NUjBgfw6AgAAAGCO+RsKtKeoQpI0pmecusV79oehvZMiNb4PVePe4u3vclVc4bwQ/LKBnZTqpVVok4Ykq1eis8XtT7uL9d81eyyOCJ5uT1GFa+1nMF8cwEk6p2e8fndBT0mSYUj3fLi2SdLaXRq/RmpsG7e/HjwHmQgAgCkMw9DDn/ysZdkHJUmx7UL0xvVDFRkWbHFkAAAAAPzJa0uzXbdvHp1uYSQnj1nj3qHUB6rF6wUFBuiRizNcx0/O36SyqloLI4Kny9rbuI06iXEAJ+8353R1jY4prazVr99ZqcNu/p1TnxhvFxqkuHZ0uPAnJMYBAKZ4+ZtszVq5W5IUEhSgV64bouRorsYDAAAAYJ5VOw5pzc4iSVKvxAid2TXG2oBOUkbHSI3rkyBJ2ldapQ9WUDXuid7+vqFa/NIB3lstXm9kt1iN7e1cdwUlVfrXN9stjgiebMNe5osDODU2m01P/bK/eiQ4u/hs3XdYv5u1TobhnjEeVbV27T5ULklKi23LiE8/Q2IcAOB2X/ycpyfmbXIdP/3L/hqU0sHCiAAAAAD4ozfqqnkl6aZRaV71QWiTWeOLqRr3NKWVNXp1SUO1+F3nem+1eGP/b0JvBQc6/57869ts1xgC4EhZeQ2J8YwkKsYBtEzb0CD969ohiggLkiTN25CvFxe754KsXYXlctTl3NO8/CI2tByJcQCAW63dVaT7PlrrOv7dBT00sX9H6wICAAAA4Jd2FZbrf+vzJEmx7UL1iwHetS/p0zGqSdX4h1SNe5R3lu1wVYtfMqCj11eL10uLbaupmamSpKpah55sdNE70Fh9K/V2oUFKoUMggFOQFttWz109UPXXLT715WYt2ryv1V8ne3/DfHES4/6HxDgAwG32FFXo5rdXqqrWIUm6fFAn3eHFM9YAAAAAeK+3v891VQddl9lFoUGB1gZ0ChpXjb9I1bjHcFaLO2fXB9iku87tfoJHeJe7zuuuDm2CJUmfrt2rVTsOWRwRPM2hsmpXN4HeSREKCPCebhwAPMuYXvH67fk9JEmGId3zwRrlHig7waNaJqfR86XHkRj3NyTGAQBuUVpZo5ve+lEHDldJkoalRevxy8/wqlaFAAAAAHxDaWWNPvpxlyQpJChAvxqeYnFEp6ZPxyhdkEHVuKd5Z9kOFZXXzRYf2Mnnqs+iwoN1/wU9XcePzcmSw+Geua/wThvzmC8OoPX85pxuri45JZW1+vW7K1VWVdtqz597sCExnhrjW7+zcWIkxgEArcLuMLRs+0F9unaPlm7drztnrtam/FJJUmpMG/1rymCvrMgAAAAA4P1mrdyt0roPVK8Y1Ekx7UItjujUNZk1/g1V41Y7XFXr09Xi9SYPTVaPhHaSnCPTPlu31+KI4Ek27G00X7wj88UBnJ6AAJuevmqAusU7f+9sKTis//v3OhlG61yU1biVuq+MPsHJIzEOADht89bnadQTCzX51eW658O1mvL6Cn2z5YAk55Xlb1w/VB3ahlgcJQAAAAB/ZHcYevO7HNfxjSPTLIzm9PXt1FA1XlBS5aqEhzXe/j63oVp8gO9Vi9cLCgzQwxMyXMd/+98mlVe3XvUevNuGvcWu2xlJJMYBnL52oUF65drBiggNkiR98XO+Xv4mu1Weu76Vemy7EEWFB7fKc8J7kBgHAJyWeevzdPt7q5VXXNns128alab0uHYmRwUAAAAATl9uyNfuQ87Zt2f3iFP3hAiLIzp9TWeNb6Nq3CJHVovfeW43iyNyr7N6xOncXvGSpPySSr3ybeskKOD9supaqQcH2tTDB37GAvAM6XHt9MzVA1zHT87fpG+27D+t5zxcVat9pc7Rn756MRuOj8Q4AOCU2R2Gpn+epeM1sflgxU7ZmT0GAAAAwCKvL22oFr9plHdXi9fr2ylK51M1brkjq8X94aLwP1zUW0EBNknSy99sV15xhcURwWqVNXZtr2tL3D0+QiFBpBwAtJ7zeifovrE9JEmGId01c7V2NJoR3lK5BxoeS2LcP/FbCgBwylbkFB6zUrxeXnGlVuQUmhQRAAAAADRYu6tIK3cckiT1SGin0d1jLY6o9dzTeNb4YmaNm+1wVa1e86Nq8Xrd4tvp2swukqTKGoeenLfZ4ohgtU35pa6CCOaLA3CHu87t5rogsKSyVre+u+qUx3lkN0mM+/4FbTgaiXEAwCnbV3r8pHhLzwMAAACA1nRktbjNZrMwmtbVt1OUxvZ2fkicX1KpWSupGjfTO8tydaiuWvwSP6kWr3fPed3Vvo1zJut/1+zRmp2HLI4IVsraW+K63YfEOAA3CAiw6R9X9Vd6nLPCe1N+qf7v3z/JMFrepbRpxXibVosR3oPEOADglMVHhLXqeQAAAADQWvYUVeiLn/MkSTFtQ3TJgE4WR9T67h3baNb4ou2qqqVq3AxlVbV69Vv/qxav175NiKutrST9aU7WKSUn4Bs27C123e7TMcrCSAD4soiwYL1y7RC1Cw2SJM39KU+v1P0ubokcKsb9nmmJ8RkzZig1NVVhYWEaPny4VqxYccxzX331VY0ePVodOnRQhw4dNHbs2OOeDwCwxrC0aNdV4s2xSUqKCtOwtGjzggIAAAAASe98n+tq7ztlRBeFBQdaHFHrO6pqnFnjpnhn2Q5Xtfgv+ndUVz+qFq93zfAUdYt3vu81O4v02bq9FkcEq2xoVDHeOynCwkgA+Lpu8e30z0kDXMdPzNukJVv3t+g56lup22xSlxgqxv2RKYnxjz76SPfff7+mTZum1atXq3///ho3bpz27dvX7PmLFy/W5MmTtWjRIi1btkzJycm64IILtGfPHjPCBQCcpD2HKlRZ3XxFQn2DwmkTMxQY4DvtCgEAAAB4vrKqWs1csVOSFBIUoCkjulgckfs0njU+g6pxtyurqtUr326XVF8t3v0Ej/BNwYEBenhCb9fxE//bpIpjfD4A32V3GNqU70yMd4lpo4iwYxdPAEBrOD8jwfVvH4ch3fXBGu0qLD+pxxqGoZz9hyVJHaPCffKiSZxYkBkv8o9//EO33HKLbrjhBknSyy+/rLlz5+qNN97Qgw8+eNT577//fpPj1157Tf/5z3+0YMECXXfddc2+RlVVlaqqqlzHJSXOX8gOh0MOh6O13go8hMPhkGEY/NnCrVhnx1dVa9dvZq5SZa3z+xMWHKDKmobvVWJUmB6Z0FsXZCTwPTwB1hrMwDqDWVhrMIM3rTNviBHwRbNX7lJpZa0k6dIBHRUXEWpxRO5zRucoje0dr6837nNVjV+bmWp1WD7ryGrx+qppf3ROz3id0zNOizfv197iSr26JFt3n+efFwr4q5wDh12fBTFfHIBZ7jmvu9bvKdaCTftUVF6jW95ZqY9/c6bahBw/5VlYVq2Sun8f1s8rh/9xe2K8urpaq1at0kMPPeS6LyAgQGPHjtWyZctO6jnKy8tVU1Oj6Ohjt+J9/PHHNX369KPu379/vyorK1seODyaw+FQcXGxDMNQQIBpEwHgZ1hnx/ePxbu0fo/zIqTO7UP1xqRe2nqgQgfLahTTNlgDOrVTYIDtmN1B0IC1BjOwzmAW1hrM4E3rrLS01OoQAL9jdxh647tc1/FNo9KtC8Yk95zXQ19vdO69Xly8XVcNTVZoEFVQrY1q8aM9PKG3lmw9ILvD0EuLt+uqIclKjAqzOiyYpHEb9YwkEuMAzBEQYNM/rx6gS1/4TtkHyrQpv1QP/udnPXv1ANlsx+5c2nS+OIlxf+X2xPiBAwdkt9uVkJDQ5P6EhARt2rTppJ7j97//vTp27KixY8ce85yHHnpI999/v+u4pKREycnJiouLU2Qkv5R9jcPhkM1mU1xcnMd/EAbvxTo7tvkb8jVrrfNDl5CgAL00ZbC6dYxSN9/tTuhWrDWYgXUGs7DWYAZvWmdhYSQHALN9vbFAO+taao7uHqueib4/87Zx1XhecaVmrdyta324fbxV3l3eUC0+0c+rxet1i4/QtSO66K3vc1VRY9eT8zfpH1cNsDosmCSrUWK8T8coCyMB4G8iw4L1ynWDdckL36ms2q7P1u1Vv85Runn0sS+IbJwYT40hMe6vTGmlfjr+9re/6cMPP9TixYuP+4FCaGioQkOPbosVEBDg8R+U4NTYbDb+fOF2rLOj7Sos1wP/+dl1/MjFGTqjcwcLI/INrDWYgXUGs7DWYAZvWWeeHh/gi15fkuO6fdOoNAsjMVeTqvFF23TVkM5UjbciZ7V4tiTJZpPuolrc5Z7zuuu/a/aouKJGH6/eo6mZqeqf3N7qsGCCDU0S4xSnATBXt/gIPX3VAN323ipJ0l+/2KjeSZEa2S222fObVIzTSt1vuX2HHhsbq8DAQBUUFDS5v6CgQImJicd97FNPPaW//e1v+vLLL9WvXz93hgkAOAnVtQ7dOXO1a1bfhH5JmjI8xeKoAAAAAMDpp91FWpFbKEnqFt9OZ/eIszgi85zROUrn9YqXJFfVOFrPu8t3qLCsWhKzxY/UoW2I7h3bcKHAY3OyZBiGhRHBDIZhKCvPmRiPbReiuIiji9YAwN3G903UXed2kyQ5DOnOmau1q65z0JEaJ8bTaaXut9yeGA8JCdHgwYO1YMEC130Oh0MLFixQZmbmMR/35JNP6rHHHtO8efM0ZMgQd4cJADgJT8zbpHW7iyVJXWLa6G+Xn3HcuS0AAAAAYKbXlzatFve3/co9jZKTLy3apqpau4XR+I7y6iOrxbtZHJHnmTKii9Lrqu9W7jikuT/nWRwR3C2/pNJ1sUhGxyi/+3kLwHPcN7aHxvR0Xgx5qLxGt767ShXVR/8bqD4xHhxoU6f24abGCM9hSk+3+++/X6+++qrefvttbdy4UbfffrvKysp0ww03SJKuu+46PfTQQ67zn3jiCT3yyCN64403lJqaqvz8fOXn5+vw4cNmhAsAaMaXG/JdHzKFBAZoxjWDFBEWbHFUAAAAAOCUV1yhuT85k3HRbUN02cBOFkdkvn6d2+vcuqrxvcWVmk3VeKt4d1lDtfjEfh3VLd7359a3VHBggB6ZkOE6fvyLTaqs4cIMX7ZhT0Mb9Ywk2qgDsE5AgE3PXD1QqTFtJElZeSV66OOfmnQvcTgMV2I8JbqNggIZeeWvTPmTnzRpkp566ik9+uijGjBggNauXat58+YpISFBkrRz507l5TVcRfjSSy+purpaV155pZKSklz/PfXUU2aECwA4wq7Ccv1u9jrX8cMX91bfTlEWRgQAAAAATb39/Q7VOpwfgE4ZnqKwYP+cr33PeQ1V4y9SNX7ajqwWv/s8qsWP5ZyecTqrbnzBnqKKJh0c4Hvq26hLzBcHYL2o8GC9ct0QtQ1x/vvvk7V79cZ3ua6v55VUqqrWIUlKi2Ucij8z7ZKIO++8Uzt27FBVVZV++OEHDR8+3PW1xYsX66233nId5+bmyjCMo/774x//aFa4AIA61bUO3fXBGpXUzRW/6IxEXTuii8VRAQAAAECDsqpazfxhhyRnh6spmf67Z+mf3LRq/N+rqBo/He8t36GDddXiF1Mtflw2m00PT+itwABnS+0Zi7ZpX0mlxVHBXTbsLXbdJjEOwBP0SIjQ01f1dx3/9YuN+n77AUlSzv6G+eJpsW1Mjw2eg14BAIDj+vv8TVq7q0iSlBwdrr9d0Y+5UQAAAAA8yn9W73ZdzPuLAR0VHxFmcUTWalw1PmPhNlXXVUihZcqra/WvbxpVizNb/IR6JETommEpkqTyarv+Pn+zxRHBXTbsdVaMtwkJVGpMW4ujAQCn8X2TdMeYrpIku8PQnTPXaPehcuUcbJwYp2Lcn5EYBwAc09dZBXp1ibP1WXCgTTOuGaRI5ooDAAAA8CAOh6E3GrVsvnFkmoXReIb+ye01pqezpfXe4krNXrXL4oi805HV4t0TqBY/Gfed30MRYUGSpH+v3q2fdxef4BHwNsUVNdp9qEKS1DspUgEBFFAA8Bz3n99T59T9O6iwrFq3vrtSizfvc329SzQV4/6MxDgAoFl7iir020Zzxf9wUW/169zeuoAAAAD81LfffquJEyeqY8eOstls+uSTT074mMWLF2vQoEEKDQ1Vt27dmowvk6Q//vGPstlsTf7r1auXe94A4GYLNu1T7sFySdLIbjHKoKWvJOmesT1ct19ctJ2q8RY6arY41eInLbptiKtrgWFIj83JkmEYFkeF1pS1l/niADxXYIBNz04aqC4xzgT4hr2lWrCxITF+36y1mrc+z6rwYDES4wCAo9TYHbpr5moVV9RIksb1SdD1Z6ZaGxQAAICfKisrU//+/TVjxoyTOj8nJ0cTJkzQmDFjtHbtWt177726+eabNX/+/Cbn9enTR3l5ea7/li5d6o7wAbd7fWm26/ZNo6gWrzegUdX4nqIKZo230PvLd+rAYWe1+IQzkqgWb6HrMlOVFutsr70it1D/W59vcURoTY3ni2ckkRgH4Hmi2gTruszUZr+2v7RKt7+3muS4nyIxDgA4ylNfbtbqnUWSpM4dwvXklf2ZKw4AAGCRCy+8UH/+85912WWXndT5L7/8stLS0vT000+rd+/euvPOO3XllVfqn//8Z5PzgoKClJiY6PovNjbWHeEDbrV+T7GWZxdKktLj2uqcHvEWR+RZGleNz1jErPGTVV5dq399u11SXbV4o5ntODkhQQH6fxf1dh3/9YuNqqyxWxgRWlNWXuOK8SgLIwGA5tkdhl5bkt3s1+p7mEz/PEt2Bx1N/E2Q1QEAADzLwk0F+tc3zn80BAfa9MI1gxQVzlxxAAAAb7Fs2TKNHTu2yX3jxo3Tvffe2+S+rVu3qmPHjgoLC1NmZqYef/xxpaSkHPN5q6qqVFVV5TouKXF+KO5wOORwkGzzNQ6HQ4ZhePyfbeNq8RvOTJVkyMEHnC79OkXq7B5x+mbLfu0pqtDslTs1edix/56bzVPX2XvLdjRUi/dNUre4th4XozcY0zNWI7vF6LttB7X7UIVeX5qt28/uakksnrrWvNWGulbqQQE2dYtrw/e1DusMZmGtndgP2QeVV1x5zK8bkvKKK/VD9gGNSI8xLzAv4y1rrSXxkRgHALjkFVfot7Ma5oo/eGFvDUhub11AAAAAaLH8/HwlJCQ0uS8hIUElJSWqqKhQeHi4hg8frrfeeks9e/ZUXl6epk+frtGjR2v9+vWKiGi+XfDjjz+u6dOnH3X//v37VVl57A+d4J0cDoeKi4tlGIYCAjyz4eC+w9X6bN1eSVJkWKBGdw7Rvn37TvAo/3PtwBh9s2W/JOn5BVt1VnKIggM948/UE9dZZY1DL32zTZJkk3TNgA6sq9Nw+4gELdt+UA5DmrFwm85JCVNMW/MvvvfEteatqmod2lZQKknqEh2m4kMHLY7Ic7DOYBbW2olt2114kuftV3o7Opoci7estdLS0pM+l8Q4AECSVGt36K6Za3So3DlX/PyMBN04MtXaoAAAAOAWF154oet2v379NHz4cHXp0kWzZs3STTfd1OxjHnroId1///2u45KSEiUnJysuLk6RkcwX9TUOh0M2m01xcXEe+yHY22s2y15XHDJlRKpSOiVaG5CHOjdeOnvNAX2z5YDyS6u1ZHeNrh6abHVYkjxznb22NEeHymslSRedkagRvbtYHJF3i4+Xrh5aqpkrdqm8xqG31xTqb5efYXocnrjWvNXPe4plr2vM0T85WvHxjLCoxzqDWVhrJ9btcKCknBOf1zlO8fFUjB+Lt6y1sLCwkz6XxDgAQJL09FdbtHLHIUlSp/bh+vuV/ZgrDgAA4IUSExNVUFDQ5L6CggJFRkYqPDy82ce0b99ePXr00LZt2475vKGhoQoNDT3q/oCAAI/+kASnzmazeeyfb3l1rT74cZck5wioqWememScnuKesT30zZYDkqQZi7brysHJCgnyjO+XJ62zimq7XvnW2Z7fOVu8h0fE5e1+e0FPfb4uT6VVtZq9areuy0xV307mz6X2pLXmzTbmNVTl9ekUxffzCKwzmIW1dnzD02OVFBWm/OJKNTdkxyYpMSpMw9NjFRDAZ+DH4w1rrSWxee67AACYZvHmfXpp8XZJzvlQz18zUO3bhFgcFQAAAE5FZmamFixY0OS+r776SpmZmcd8zOHDh7V9+3YlJSW5OzygVfxn9R4V1XW7mtivoxIiT75KxB8NSumgs3vESZL2FFXo49W7LY7IM73/Q8Ns8Yv6JqlnYvOjJdAyMe1Cdfd53SVJhiE9NidLhtFcmgLeoH6+uCRlJNExBoBnCgywadrEDEnOJHhj9cfTJmYokKS43yExDgB+Lr+4Uvc3miv++/G9NCilg4URAQAAoLHDhw9r7dq1Wrt2rSQpJydHa9eu1c6dOyU5W5xfd911rvNvu+02ZWdn64EHHtCmTZv04osvatasWbrvvvtc5/zud7/TN998o9zcXH3//fe67LLLFBgYqMmTJ5v63oBT4XAYenNpQ2vMG0elWRiN97hnbHfX7RcWbVN1rcPCaDxPRbVdL3+T7TquT+SidUw9M1WpMW0kST/kFGr+hnyLI8KpysprlBjvSGIcgOca3zdJL00ZpMSophdQJkaF6aUpgzS+LxcF+yNaqQOAH6u1O3T3B2tUWOa8In5s73jdPJoPlQAAADzJypUrNWbMGNdx/ZzvqVOn6q233lJeXp4rSS5JaWlpmjt3ru677z49++yz6ty5s1577TWNGzfOdc7u3bs1efJkHTx4UHFxcRo1apSWL1+uuLg4894YcIoWbd6n7ANlkqQR6dGWtGT2RoNSOuisHnH6dst+7T7krBq/eliK1WF5DGe1eJUkacIZVIu3tpCgAP3hot769burJEl//WKTxvSKV2hQoMWRoSXsDkMb6xLjydHhigoPtjgiADi+8X2TdH5GolbkFGpfaaXiI8I0LC2aSnE/RmIcAPzYM19v1YrcQklSx6gwPfXL/swVBwAA8DDnnHPOcVvOvvXWW80+Zs2aNcd8zIcfftgaoQGWeL1RtfjNo9ItjMT73HNed327Zb8kZ9X4FYM7KziQhpKVNXb961uqxd3t/IwEndk1Rt9vP6idheV667tc3Xp2V6vDQgvkHixTebVdEm3UAXiPwACbMrvGWB0GPAT/8gUAP/Xtlv2asXibJOc/DpgrDgAAAMDTbdhbrO+3H5QkpcW21bm94i2OyLsM7uKsGpfkqhqH9P4PO7W/1FktftEZiVSLu4nNZtMjF2eovkjv+YXbXN93eIesRvPF+3SkWwcAwPuQGAcAP1RQUqn7Plqr+sKjB8b11OAu0dYGBQAAAAAn8MbSXNftG0emKoA2mC12T6Nq6OcXblON3b9njVfW2PXyN9tdx1SLu1fvpEhNGups4X+4qlb/+GqLxRGhJTY0SoxTMQ4A8EYkxgHAz9TPFT9YN1d8TM843TKa9oMAAAAAPNu+kkp9tm6PJCkqPFhXDO5scUTeaXCXDhrdPVYSVePS0dXivRJJ9rnbby/ooXahzgmfH/24s0kVMjxbVl6jivFO/F0BAHgfEuMA4GeeW7BVP+Q454onRobp6asGUGUBAAAAwOO9u3yHauzOtlfXDE9Rm5AgiyPyXveObaiKfmGR/1aNUy1ujdh2obrz3G6SJIchPTYnS0Z9Szt4LMMwlLW3WJIU3TZEiZFhFkcEAEDLkRgHAD+ydOsBPb+o6Vzx6LbMFQcAAADg2Spr7Hpv+Q5JUlCATVMzU60NyMsN7hLtqhrfVVih/67eY3FE1pjZqFr8wr5Ui5vphpGpSoluI0laln1QX2UVWBwRTmRfaZUOHHZ2H8xIipTNRpEFAMD7kBgHAD+xr7RS9zaaK/7bC3poaCpzxQEAAAB4vo9X79Gh8hpJ0sX9kpQYRaXi6Woya3zRVr+rGq+sseslqsUtExoUqD9c1Mt1/JcvNqqq1m5hRDiRxi3v+3TkIhIAgHciMQ4AfsDuMHTPB2t14LDzSvize8TptrO6WhwVAAAAAJyYw2Ho9aXZruObRqVbGI3vGJJ6RNX4Gv+qGv9gRUO1+Pg+ieqdRKLPbOP6JGp4mvOC/R0Hy/XO9zssjgjHs6GujbokZZAYBwB4KRLjAOAHnl+4VcuyD0qSEiJD9Y+r+jNXHAAAAIBX+Gbrfm3fXyZJGpYWrTM6R1kcke9oXDX+wkL/mTVeWWPXS4upFreazWbTIxdnqL4j93MLtupg3QX98DwbqBgHAPgAEuMA4OO+33ZAzy7YKkkKsEnPXT1QMe1CLY4KAAAAAE7O60tyXLdvGpVmYSS+Z0hqtEZ1c1aN7yws95uq8Q9W7NS+RtXiVL9ap2+nKF01OFmSVFpVq398tcXiiHAsWXnOxHh4cKDSYttZHA0AAKeGxDgA+LD9pVW6p8lc8Z4anh5jbVAAAAAAcJI25Zdo6bYDkqQuMW00tneCxRH5nnvGNlRLz1i0TbU+XjVOtbjn+e24HmobEijJedHCpvySEzwCZiuprNGOg+WSpF5JEQqkCyEAwEuRGAcAH2V3GLrvo7WumWmju8fq9rOZKw4AAADAezSuFr/hzFSSMW4wNDVaI7s5L6DecdD3q8Y/bFQtPq5PAtXiHiA+Ikx3nNtNkuQwpMfmZMmov8IfHmFjozbqGUn8nQEAeC8S4wDgo2Ys2uaqrIiPCNU/Jw1grjgAAAAAr7G/tEqfrt0rSYoIC9IvhyRbHJHvuue8Hq7bL/hw1XhljV0vUi3ukW4cmabOHcIlSd9tO6gFG/dZHBEaq2+jLkl9OkZZGAkAAKeHxDgA+KDl2Qf1zNfOuVwBNunZqwcqlrniAAAAALzIu8t3qLouQXvNsBS1DQ2yOCLfNSzNP6rGj6wWJ8HnOcKCA/WHi3q7jv/yxUZV1/rmBRreaMPexolxKsYBAN6LxDgA+JgDh6t09wdr5KjrOnbv2B7K7MpccQAAAADeo7LGrveX75AkBQbYNPXMVGsD8gO+XjVeWWPXS99QLe7JLuybqGGp0ZKknANlemdZrrUBwaU+MR4YYFPPxAiLowEA4NSRGAcAH+KomytefwX8yG4xumNMN4ujAgAAAICW+WTNHh0sq5YkXXRGkjq2D7c4It83LC1aZ3ZtqBr/pK6Nva/46MddKihx7pUvyKBa3BPZbDY9cnGGbHVT4J5bsFWFdT8HYJ3qWoe27SuVJHWNa6uw4ECLIwIA4NSRGAcAH/LSN9u1ZKtzrnhcRKiemTRQgcwVBwAAAOBFDMPQ60tzXMc3jUqzMBr/ck+jKurnF271mapx52zxba5jqsU91xmdo3TloM6SpJLKWteYOFhnS0GpauzOtoRcUAIA8HYkxgHAR6zIKdTTX26WJNls0rOTBigugrniAAAAALzLt1sPaOu+w5KkoakdNCC5vbUB+ZHh6TFNqsY/9ZGq8VkrG6rFz89IUN9OJPc82f+N66k2Ic6q5Pd/2KktBaUWR+TfshrNF89IYr44AMC7kRgHAB9w8HCV7vpgtWuu+D3nddeZ3WKtDQoAAAAATgHV4tbytarxyhq7XlzUMFv8HqrFPV58ZJhrLJzdYeixOVkyDMPiqPxXVl5DYrxPRxLjAADvRmIcALycw2Ho/lnrXFe/n9k1Rnedy0YfAAAAgPfZUlCqb7fslyQlR4fr/IxEiyPyP8PTY5SZ7qwaz/WBqvFZK3cpv6RSEtXi3uSmUWnq1D5ckrRk6wEt3rzf4oj814a9xa7bGSTGAQBejsQ4AHi5l7/drm/qPjiKbReiZ64ewFxxAAAAAF7pjUbV4jecmcbexiL3jG242PqFRdu8tmq8qpZqcW8VFhyoBy/s5Tp+bG6Warx0HXozh8PQxjxnK/tO7cPVvk2IxREBAHB6SIwDgBf7MbdQT3+5RZJzrvgzkwYqPiLM4qgAAAAAoOUOHK7Sx2v2SJIiQoN01dBkiyPyXyPSYzQiPVqSlHOgTJ+t886q8Vk/NlSLj+1Ntbi3ubhfkgZ36SBJyt5fpveW77A4Iv+zs7Bch6tqJVEtDgDwDSTGAcBLFZZV6+4P1sheN1j8rjHdNKo7c8UBAAAAeKf3l+9Uda2zIvTqYclqFxpkcUT+7Z7zerhuP7/Q+6rGq2rtmtGoWvzesVSLexubzaZHL85wHT/z9VYdKqu2MCL/s2Fvw3zxjCQS4wAA70diHAC8kMNh6Lez1iqv2Hnl+/C0aN0ztscJHgUAAAAAnqmyxq53l+dKkgIDbJp6Zqql8UDK7OrdVeNUi/uG/sntdfmgTpKk4ooaPbtgq8UR+ZesvIb54n2oGAcA+AAS4wDghV5dkq1Fm51zxWPahui5yQOZvQcAAADAa322bq8OHHZWgo7vm6jOHdpYHBGkplXjL3hR1XhVrV0vLma2uK94YFwvhQcHSpLeXb5D2/aVWhyR/2hcMd6Hi0sAAD6AxDgAeJlVOwr15PzNkpxzxf85aYASIpkrDgAAAMA7GYahN5bmuI5vHpVmYTRoLLNrjIanOavGsw+U6fOfvKNqfNbK3a4Oa2N7x+uMziT0vFliVJhuP6erJMnuMPTnuRstjsh/1CfGo8KD1TGKz54AAN6PxDgAeJFDZdW6a2bDXPE7zumms3rEWRwVAAAAAJy677Yd1KZ8ZwXooJT2GpjSweKI0Ni9jcZ2Pb9gm2s/6qmqau16cdE213Hjqnd4r1tGp7sSs4s379eizfssjsj37Sut1P7SKknONuo2G50KAQDej8Q4AHgJwzD0u9nrtLfuqvdhqdG6dyzt4AAAAAB4t9eWZrtu3zw63cJI0JyjqsY9fNb47EbV4uf1olrcV4SHBOr3F/ZyHf9l7kbVeElrf29kdxj6z6rdruPeSREWRgMAQOshMQ4AXuK1JTlasMl5RXR03VzxoEB+jAMAAADwXtv2lWrx5v2SpE7tw3VBRoLFEaE59zS6KPu5BVs9tmr8qGpxLib3Kb/o31EDU9pLkrbtO6yZP+y0NiAfNW99nkY9sVBPzNvsuu/fq/Zo3vo8C6MCAKB1kFEBAC+weuchPTFvk+v4H1f1VyKznQAAAAB4udeX5rpu3zAylYt/PVRmeoyGeUHV+OyVu11d1s7rFa9+ndtbGxBalc1m06MXZ7iO//n1FhWVV1sYke+Ztz5Pt7+32tV1oV5xRY1uf281yXEAgNdjtwEAHq6o3DlXvLbuivzbz+mqc3rGWxwVAAAAAJyewrJqfbza2aq3XWiQJg1NtjgiHIvNZmsyyuu5hZ5XNV5d66Ba3A8MTOmgywZ2kiQVldfo2QVbLY7Id9gdhqZ/nqXj/c2e/nmWx/3dBwCgJUiMA4AHc84V/0l7iiokSUO6dNBvz+9hcVQAAAAAcPreX75DVbXOGcGThiYrIizY4ohwPJnpMRqWWlc1vr9Mc37yrKrx2at2uarFz6Va3Kc9ML6nwoKdH2u/u2yHtu8/bHFEvmHJ1v1HVYo3ZkjKK67UipxC84ICAKCVkRgHAA/2xne5+npjgSSpQ5tg5ooDAAAA8AlVtXa9s3yHJCnAJl1/Zqq1AeGEjqwaf9aDZo1X1zo0Y2GjavHzqBb3ZUlR4brt7K6SpFqHob/O3WhxRN6pvLpWS7bu19/nb9IVL32vG9/68aQet6/02MlzAAA8XZDVAQAAmrd2V5H+9r+Gzd0/rhqgju3DLYwIAAAAAFrH5+vytL+0SpI0vm+ikqPbWBwRTkZmV2fV+IrcQlfV+CUDOlkd1lHV4v2T21sbENzu1rO66qMfdymvuFILNu3Tt1v266wecVaH5dHKq2u1aschLc8+qOXZhVq3q8g1tq8l4iPC3BAdAADmIDEOAB6ouKJGd85crRq7c4Ny61npGtOLueIAAAAAvJ9hGHp9aY7r+KZRaRZGg5aorxq/5rUfJEnPLdiqi/t1VGCAzbKYnLPFt7uOqRb3D+Ehgfr9+F6696O1kqQ/z83SF11H02WvkYpqe6NE+EGt213k+pypOWmxbVRQUqXyanuzX7dJSowK07C0aDdFDACA+5EYBwAPYxiGHvj3Ou0+5JwrPiilvX43rqfFUQEAAABA61i2/aA25pVIkgYkt9eglA4WR4SWyOwao6GpHfRj7iFt94Cq8X+v2q09Rc7985iecVSL+5Ff9O+ot77P1dpdRdpScFgf/LhL147oYnVYlqmotmv1zkNatv3kEuHpcW01Ij3G+V9atOIjwzRvfZ5uf2+1JOdM8Xr1l75Mm5hh6YUwAACcLhLjAOBh3v4+V/M3OOeKR4UH6/lrBimYK54BAAAA+Igjq8VtNpIs3sRZNd5Dv/KAqvHqWodmLGo0W3xsD9NjgHUCAmx6dGKGLn/xe0nSP77crF/076io8GCLIzNHfSK8viJ87a4TJMJj22p4eoxGpEdrRHqMEiKPbok+vm+SXpoySNM/z1JeccMs8cSoME2bmKHxfZPc8l4AADALiXEA8CA/7S7SX75omCv+9C/7qxNzxQEAAAD4iO37D2vBpn2SpE7tw3Vh30SLI8KpOPOIqvG5P+fpF/07mh7Hf1Y3rRYfQLW43xmU0kG/6N9Rn63bq0PlNXp+wVY9fHGG1WG5RWWNXasbzQhfu6tI1XbHMc9Pi23rSoIfKxHenPF9k3R+RqJW5BRqX2ml4iOc7dOpFAcA+AIS4wDgIYoranRHo7nit4xO09iMBIujAgAAAIDW8+Z3DdXiU8/swjxgL2Wz2XTPeT005fWGqvEJZySZmjirrnXohYVUi0P6/YW9NH9DvqpqHXrr+1xdMzxF6XHtrA7rtJ1OInx4WowSo04uEd6cwACbMrvGnPLjAQDwVCTGAcADGIahB//zk3YVOq90H5DcXg+M72VxVAAAAADQeg6VVevfq3ZLktqGBGrS0BSLI8LpGNktRkO6dNDKHYe0bd9h06vGG1eLn0O1uF/r1D5ct56VrucWblOtw9Bfv9ik16YOsTqsFqusqW+NXuhsjb7z+Inw1Jg2rmrw4enRSoqi4yAAACdCYhwAPMC7y3fof+vzJUmRYUF64ZqBzBUHAAAA4FNmrtipyhpnkueXQ5L9Zg6wr6qfNV5fNf68iVXjR80WP6+7218Tnu3Ws7vqo5W7VFBSpa83Fmjp1gMa1T3W6rCOq7LGrjU7i7Ssfkb4CRLhXWLaaERajDK7kggHAOBUkRgHAIut31OsP89pmCv+1C/7q3OHNhZGBAAAAACtq7rWobe/z5Uk2WzSjSPTrA0IrWJktxgN7tJBq3Yc0tZ9h/XFz3maaELV+Merd2v3IWe1+Nk94jQwpYPbXxOerW1okB4Y10u/nb1OkvTYnCzNvXuUR41rqE+EL69LhK/ZVaTq2hMnwkd0jdbwtBh1bE8iHACA00ViHAAsVFrpnCtef0XwjSPTdEGfRIujAgAAAIDWNffnvdpXWiVJuiAjQSkxXAzsC5xV49117esrJDXMGg9wY9V4jd2hFxpXi4+lWhxOlw3spLeX5eqn3cXaXFCqj1bu0q+Gd7Esnsoau9bucibCl20/cSI8JbqNRqRHOyvCSYQDAOAWJMYBwCKGYejBj3/WjoPlkqT+naP04IXMFQcAAADgWwzD0GtLclzHN49OtzAatLZR3WKbVo2vz9PF/dxXNX5ktfggqsVRJyDApkcvztCVLy+TJD395RZN7N9RkWHmjG1onAhfnn1Qq3eeXCLcOSM8Rp1IhAMA4HYkxgHAIu//sFNzf8qTJEWEBemFawYpJMhzWnwBAAAAQGv4IadQG/aWSJL6dY7SkC4kMn3JkVXjz369VRf1dU/VeI3doecXUi2OYxuSGq2L+yVpzk95Kiyr1gsLt+kPF/V2y2tV1dq1dmeRlmcX1iXCD6nqOInw5OhwZ2v0dOeMcMboAQBgPhLjAGCBDXuL9ac5Wa7jv1/ZX8nRbIgAAAAA+J7G1eI3jUqTzea+NtuwxqhusRqU0l6rdxa5tWq8cbX4WVSL4xgevLCXvswqUHWtQ29+l6NrhqUoJfr0q7Grau1at6tYy7YfPKlEeOcO4RqRHqNMEuEAAHgMEuMAYLLDVbW6c+YaVzut689M1fi+zBUHAAAA4HtyDpRpwaYCSVJSVJguOiPJ4ojgDs6q8R667o2GWeOtXTV+VLX4eVSLo3mdO7TRr0en64VF21RjN/TXLzbq5SmDWvw89Ynw+tboq3acXCJ8RHqMhqdFUwABAIAHIjEOACYyDEN/+Phn5RwokySd0SlKD13EXHEAAAAAvunN73JkGM7bU89MVXAg46N81ejuDVXjWwoO63/r8zWhX+tdCPHf1XuaVIsPpiU/juP2c7rqo5W7tL+0Sl9mFej1pTkKdVSp2+FADU+PVWAzF21U1dr10+5iLd9+UMtOIhHeqX19Itw5J5xEOAAAno/EOACY6IMVu/TZur2SpIjQIM24ZpBCgwItjgoAAAAAWl9xeY1mr9wtSQoPDtTkoSkWRwR3stlsumdsD02tqxp/dsEWXdg3sVWqxmvsDj2/aKvrmGpxnEjb0CA9MK6n/u/fP0mS/vLFprqv5CgpKkzTJmbo3F4JWre7SMu3H9TyHGcivLKGRDgAAL6MxDgAmCRrb4n++PkG1/GTV/ZTSgybKAAAAAC+aeaKnaqosUuSrhrSWVFtgi2OCO52VvdYDUxprzWtXDX+39V7tKvQWS0+unss1eI4KW1Dmv/oO6+4Ure9t1rBgTbV2I1jPr5jVJhGdI1xzQnv3CFcNlvrjQcAAADmIzEOACZwzhVf7Zorfl1mF13IbD0AAAAAPqrG7tDb3+dKkmw26YaRadYGBFPUzxqf2mjW+OlWjdfYHXphUcNs8XvHUi2OE7M7DD02N+u45xyZFE+KClNmeoxGdCURDgCAryIxDgBuZhiGHv7vz8qumyvet1Ok/nBRb4ujAgAAAAD3+eLnPOWXVEqSxvZOUGpsW4sjglnO6h6rAcnttXZXkTYXlGrehnxddBoXhv93zR7tLCyXVF8tHt1aocKHrcgpVF5x5QnPG90tVhP7d6xrjU4iHAAAXxdgdQAA4OtmrdylT9Y654q3Cw3SC5MHKSyYueIAAAAAfJNhGHp9aY7r+KZRVIv7E2fVeENV97Nfb5XDcex21cdTY3fohYUN1eLMFsfJ2ld64qS4JF05pLOuGpqslJg2JMUBAPADJMYBwI025Zfo0U8b5or/7YozqJQAAAAA4NN+zD2kn3YXS3J2zBqeRoWvvzm7R5wGJLeXJG0uKNX8Dfmn9DyfHFEtPiSVtYSTEx8R1qrnAQAA30BiHADcpKyqVne8v1pVdXPFp4xI0cX9OlocFQAAAAC41+tLs123bxqVRhWmHzqqanxBy6vGa4+YLU61OFpiWFq0kqLCdKyfPjY5Z4oP48IdAAD8ColxAHADwzD0yCfrtX2/c654RlKkHp6QYXFUAAAAAOBeOw6W6cusAklSQmSoJpzBxcH+6uwecepfVzW+Kb/lVeP/XbNHOw46q8VHdaNaHC0TGGDTtInOz2GOTI7XH0+bmKHAAC7cAQDAn5AYBwA3mL1qtz5es0eS1DYkUDN+xVxxAAAAAL7vze9yZdQVBl+XmaqQID568lenUzV+VLX4WKrF0XLj+ybppSmDlBjVtF16YlSYXpoySOP7JlkUGQAAsEqQ1QEAgK/ZUlCqRz9d7zp+/Ip+SmOuOAAAAAAfV1xRo1krd0mSwoMD9avhKRZHBKudU1c1vm5XkTbll+rLrPyTSkZ+snZvk2rxoVSL4xSN75uk8zMS9UP2AW3bvV/dOsdpeHosleIAAPgpLtsFgFZUXu2cK15Z45wrPnlYin7Rn9aBAAAAAHzfhyt2qrzaLkm6YnAntW8TYnFEsJrNZtO9jWaDP/P1iavGa+0OPb9wq+uYanGcrsAAm0akx+iCXtEakR5DUhwAAD9GYhwAWtGjn27Q1n2HJUm9EiNc86wAAAAAwJfV2B16+/tc1/GNI9OsCwYe5ZyecerfOUqSXFXjx9O4WnxktxiqxQEAANBqSIwDQCv596rd+veq3ZKkNswVBwAAAOBH/rc+X3uLKyVJ5/WKV3pcO4sjgqdwzhrv4Tp+dsG2Y1aN19odeqFxtfh5PZo9DwAAADgVJMYBoBVsLSjVI580zBX/62VnqCsfBAEAAADwA4Zh6PUl2a7jm0ZTLY6mzukZp351VeMb80r0ZVZBs+d9unavcuuqxc/sGqNhaVSLAwAAoPWQGAeA01RRbdcdM1erosY5S+/qocm6dGAni6MCAAAAAHOs2nFI63YXS5J6J0UqMz3G4ojgaZxV4w2zwp9dcPSs8aNmi5/HbHEAAAC0LhLjAHCa/vjZBm0pcM4V75kQoWkT+1gcEQAAAACY5/WlOa7bN49Kk81mszAaeKoxPeObVI1/tbFp1fhn65pWiw/nAgsAAAC0MhLjAHAa/rtmtz5auUtSw1zx8BDmigMAAADwD7sKyzV/Q74kKS4iVBP7d7Q4Ingqm83WpAr82a+3yjCcVePOavFtrq9RLQ4AAAB3IDEOAKdo277D+n//bZgr/udL+6pbPHPFAQAAAPiPN7/LVX1H7KmZXRQSxEdNOLZze8XrjE7OqvGsvBJ9tXGfJOnzn/KUc6BMkpSZTrU4AAAA3IPdCgCcgsoau+6cuVrl1c654r8c3FmXD+pscVQAAAAAYJ6Syhp99ONOSVJoUICuGd7F4ojg6Y6cNf74Fxv1v40H9eT8za777hlLtTgAAADcg8Q4AJyC6Z9v0Kb8UklSj4R2+tMlfS2OCAAAAADMNevHXSqru1j4isGdFd02xOKI4A3O7RWvlOg2kqQdhRWaPj9XBSVVkpz76xFUiwMAAMBNSIwDQAt9unaPPljhnCseHhyoGdcwVxwAAACAf6m1O/Tmd7mu4xtHplkXDLzK/A352llY3uzXthQc1rz1eSZHBAAAAH9BYhwAWiB7/2H94eOfXcd/uqSPuidEWBgRAAAAAJhv/oYC7SmqkCSN6RmnbvHtLI4I3sDuMDT986xjft0mafrnWbLXD64HAAAAWhGJcQA4SZU1dt0xc01Dq8BBnfXLIckWRwUAAAAA5nttabbr9k2j0i2MBN5kRU6h8oorj/l1Q1JecaVW5BSaFxQAAAD8BolxADhJj83J0sa8EklSt/h2euzSPhZHBAAAAADmW7XjkNbsLJIk9UqM0MhuzITGydlXeuyk+KmcBwAAALQEiXEAOAmfr9ur93/YKUkKCw7QjGsGqU1IkMVRAQAAAID53lia47p946g02Ww2C6OBN4mPCGvV8wAAAICWIKsDAM2wOwz9kH1Q23YXqt3eGj3yyQbX1/70i77qmchccQAAAAD+Z1dhuf63Pk+SFNsuVJcM6GhxRPAmw9KilRQVpvziSjU3RdwmKTEqTMPSos0ODQAAAH6AxDgAHGHe+jxN/zyr2blnlw3spF8O6WxBVAAAAABgvbe/z5WjLqN57YguCg0KtDYgeJXAAJumTczQ7e+tlk1qkhyv7zswbWKGAgPoQgAAAIDWRyt1AGhk3vo83f7e6maT4pJ0do842gQCAAAA8EullTX66MddkqSQoABNGZFicUTwRuP7JumlKYOUGNW0XXpiVJhemjJI4/smWRQZAAAAfB0V44AfsDsMrcgp1L7SSsVHOFuScfX10ewOQ3/8PKvZdm71npi3SRP7d+T7BwAAAMDvzFq5W6VVtZKkywd2Uky7UIsjgrca3zdJ52ck6ofsA9q2e7+6dY7T8PRY9toAAABwKxLjgI9rri14UlSYpk3M8MqrsO0OQxU1dlVU1/1XY1d5dW3DfTV2lVfbVVn3//X3VVQ3vr/580sra1VV6zju6+cVV2pFTqEyu8aY9I4BAAAAwHp2h6E3v8txHd84Ks3CaOALAgNsGpEeo/R2dsXHxyiApDgAAADcjMQ44MPq24IfWQGdX1yp299b7ZYWZdW1jiOSzrXHTFI3n8yuVUWNQxV1yevy6qbnVJ8gcW2GfaXNt1kHAAAAAF/15YZ87T5UIUk6q0eceiREWBwRAAAAALQMiXHAR9kdhqYfoy14/X2PfLpBiZHhqqo9VpLa3qQ6u7zG3mzCunH1dq3jeI3IPYvNJoUHBzr/CwmUYRjaU3TipHd8RNgJzwEAAAAAX/L60oZq8ZupFgcAAADghUiMAz7icFWt8ooqlFdcqfziSv2Qc7BJ+/Tm7C+t0qUvfmdShC0XFGBTeIgzcd0mJFBhdf/vvC9I4SGBalOX1G72vODG9wcpPCRA4SFBrvNCgwJkszW0arM7DI16YqHyiyubvaDAJikxyjmjHQAAAAD8xdpdRVq545AkqUdCO43uHmtxRAAAAADQciTGAS9QWlmjvOLKuqR3hfYWOZPfeSWVyiuqUH5xpUqrak2PKzQooGkCOiRQbYKDFHYqCev6RHej84IDA0x9P4EBNk2bmKHb31stm9QkOV6fPp82MUOBzD0DAAAA4EcaV4vfNCqtyQXGAAAAAOAtSIwDFjIMQyWVtc4kd3FFk+R3w+1KHXZj0vuCjASlxbZtJoF9dMK6cUI7PDhQAT6YIB7fN0kvTRmk6Z9nNam4T4wK07SJGa0+kx0AAAAAPNmeogp98XOeJCmmbYguGdDJ4ogAAAAA4NSQGAfcxDAMlVTUKq+kLsld1DThnVfsrPQuq7af1uuEBgWoY/twJUaGKSkqTEntw5QYFa6EdqH6wyc/6+Dh6uO2BX9pymAqoI8wvm+Szs9I1A/ZB7Rt93516xyn4emxfJ8AAAAA+J13l+2Q3eHcVU4Z0UVhwYEWRwQAAAAAp4bEOHAKDMNQcUWNK8FdX9l95HH5aSa9w4ID1DEqXIlRYUqMCnPdTooKU1JUuJKiwtS+TfAx29g5ZNAW/BQFBtg0Ij1G6e3sio+P8cnqeAAAAAA4nvJquz74cZckKSQoQFNGdLE4IgAAAAA4dSTGLWR3GFqRU6h9pZWKjwjTsLRokpQnwe4w9EP2QW3bXahuhwNbvZLXMAwVlR+d9N5bV+FdnwCvqDm9pHd4cKCS2juT3ImR4erYPuyopHdU+LGT3ieDtuAAAAAA/B1775ar33e/991OlVY6R3tdOqCj4iJCLY4MAAAAAE4diXGLzFufd1SyMolk5Qkd/X3LadH3zTAMHSqvcSa8iyqVV1LX3ryobp53iTMZXlnjOK0424QENklwJ0U525vXJ8KTIsMVGR50Wknvk1XfFpwPggAAAAD4G/beLdfc90ySeiZGWhQRAAAAALQO0xLjM2bM0N///nfl5+erf//+ev755zVs2LBjnj979mw98sgjys3NVffu3fXEE0/ooosuMitct5q3Pk+3v7f6qLnP+cWVuv291XppyiA26M040fftxV8N0rC0aNcM7/ziCu11VXhXuCq9q2pPL+ndNiRQSe2PSHg3qvROjApTZJg5Se+TFRhgU2bXGKvDAAAAAHAKvv32W/3973/XqlWrlJeXp//+97+69NJLj/uYxYsX6/7779eGDRuUnJyshx9+WNdff32Tc1q6T/c27L1b7ljfM0n685wsdWofxvcMAAAAgNcyJTH+0Ucf6f7779fLL7+s4cOH65lnntG4ceO0efNmxcfHH3X+999/r8mTJ+vxxx/XxRdfrJkzZ+rSSy/V6tWr1bdvXzNCdhu7w9D0z7Oa3WTW3zft0w3q2ylKATabDEkOh/MrhiEZMur+31n9bNTdLxlyGEec0+h2/eMdrsc0fWzDc9adU/dYNbq/8Ws7jPqvNX6tk4ip7pzG78fhaPpYHXW+VOtw6Kn5m4/7fbv9/dWn+KfSICI0qPl53nWJcGfSO/i0XwcAAAAATlZZWZn69++vG2+8UZdffvkJz8/JydGECRN022236f3339eCBQt08803KykpSePGjZPU8n26tzmpvfdnGzQwpQPdtOrYHYYe/XRDs9+zetM/z9L5GYl8zwAAAAB4JZtRn6V0o+HDh2vo0KF64YUXJEkOh0PJycm666679OCDDx51/qRJk1RWVqY5c+a47hsxYoQGDBigl19+udnXqKqqUlVVleu4pKREycnJOnTokCIjPafd1/Lsg7rmtRVWh+GXIsKClBTZMMe7IQEepsS6+yNIeqMRh8Oh/fv3Ky4uTgEBAVaHAx/GWoMZWGcwC2sNZvCmdVZSUqIOHTqouLi4VfamNpvthBXjv//97zV37lytX7/edd/VV1+toqIizZs3T1LL9+mS9+y7Jfbe7jTz5mEakU5HMrQOb/p5Du/GWoMZWGcwC2sNZvGWtdaSfbfbK8arq6u1atUqPfTQQ677AgICNHbsWC1btqzZxyxbtkz3339/k/vGjRunTz755Jiv8/jjj2v69OlH3b9//35VVlY28whrbNtdaHUIPq1bbLj6JLZVfLtgxUeEKL5diOIjghXfLkRtQwKP8ShDUoUqSipUUWJmtPB0DodDxcXFMgzDo3/ow/ux1mAG1hnMwlqDGbxpnZWWlpr+msuWLdPYsWOb3Ddu3Djde++9kk5tny55z75bYu/tTtt271d6O7vVYcBHeNPPc3g31hrMwDqDWVhrMIu3rLWW7Lvdnhg/cOCA7Ha7EhISmtyfkJCgTZs2NfuY/Pz8Zs/Pz88/5us89NBDTZLp9Veux8XFedSV690OB0rKOeF5Q1M7KLZdqAJskk021f1PNpuzQsB1W7a6+xrdVsM5anQccMQ5auFzNTyu/rmafk1HnBdgs7meq0n8Rz53c69zRPw5B8r0r29P/H3706VncOU6Wo3D4ZDNZvP4q6Hg/VhrMAPrDGZhrcEM3rTOwsLCTH/NY+2pS0pKVFFRoUOHDrV4ny55z75bOvm996CU9opuG+L+gLxAYVm1Vu8sOuF53TrHKT6efTdahzf9PId3Y63BDKwzmIW1BrN4y1pryb7blBnjZggNDVVoaOhR9wcEBHjUH9bw9FglRYUpv7iy2bldNkmJUWH68NeZzOxqxO4w9Nm6vBN+34anxyqA7xtakc1m87ifI/BNrDWYgXUGs7DWYAZvWWeeHl9LeMu+Wzr5vffs285k713H7jA06omF7LthOm/5eQ7vx1qDGVhnMAtrDWbxhrXWktjc/i5iY2MVGBiogoKCJvcXFBQoMTGx2cckJia26HxvEhhg07SJGZLqqq8bqT+eNjGDjfkR+L4BAAAAwMk51p46MjJS4eHhp7RP9zbsIVuO7xkAAAAAX+f2xHhISIgGDx6sBQsWuO5zOBxasGCBMjMzm31MZmZmk/Ml6auvvjrm+d5mfN8kvTRlkBKjmpb2J0aF6aUpgzS+b5JFkXk2vm8AAAAAcGIn2lOfyj7dG7GHbDm+ZwAAAAB8mSmt1O+//35NnTpVQ4YM0bBhw/TMM8+orKxMN9xwgyTpuuuuU6dOnfT4449Lku655x6dffbZevrppzVhwgR9+OGHWrlypV555RUzwjXF+L5JOj8jUStyCrWvtFLxEWEalhbNldcnUP99+yH7gLbt3q9uneM0PD2W7xsAAAAAn3X48GFt27bNdZyTk6O1a9cqOjpaKSkpeuihh7Rnzx698847kqTbbrtNL7zwgh544AHdeOONWrhwoWbNmqW5c+e6nuNE+3Rfwd675dh3AwAAAPBVpiTGJ02apP379+vRRx9Vfn6+BgwYoHnz5ikhIUGStHPnzib9388880zNnDlTDz/8sP7whz+oe/fu+uSTT9S3b18zwjVNYIBNmV1jrA7D6wQG2DQiPUbp7eyKj49hthkAAAAAn7Zy5UqNGTPGdXz//fdLkqZOnaq33npLeXl52rlzp+vraWlpmjt3ru677z49++yz6ty5s1577TWNGzfOdc6J9um+hL13y7HvBgAAAOCLbIZhGFYH4Q4lJSWKiopScXGxIiMjrQ4HrczhcGjfvn2Kj49vclEF0JpYZzALaw1mYJ3BLKw1mMGb1pkv7019+b3Bu/6ewXuxzmAW1hrMwDqDWVhrMIu3rLWW7E09910AAAAAAAAAAAAAANAKSIwDAAAAAAAAAAAAAHwaiXEAAAAAAAAAAAAAgE8jMQ4AAAAAAAAAAAAA8GkkxgEAAAAAAAAAAAAAPo3EOAAAAAAAAAAAAADAp5EYBwAAAAAAAAAAAAD4NBLjAAAAAAAAAAAAAACfRmIcAAAAAAAAAAAAAODTSIwDAAAAAAAAAAAAAHwaiXEAAAAAAAAAAAAAgE8jMQ4AAAAAAAAAAAAA8GkkxgEAAAAAAAAAAAAAPo3EOAAAAAAAAAAAAADAp5EYBwAAAAAAAAAAAAD4NBLjAAAAAAAAAAAAAACfRmIcAAAAAAAAAAAAAODTSIwDAAAAAAAAAAAAAHwaiXEAAAAAAAAAAAAAgE8jMQ4AAAAAAAAAAAAA8GkkxgEAAAAAAAAAAAAAPo3EOAAAAAAAAAAAAADApwVZHYC7GIYhSSopKbE4EriDw+FQaWmpwsLCFBDA9R1wD9YZzMJagxlYZzALaw1m8KZ1Vr8nrd+j+hL23b7Nm/6ewXuxzmAW1hrMwDqDWVhrMIu3rLWW7Lt9NjFeWloqSUpOTrY4EgAAAACAvystLVVUVJTVYbQq9t0AAAAAAE9xMvtum+GLl63LeRXD3r17FRERIZvNZnU4aGUlJSVKTk7Wrl27FBkZaXU48FGsM5iFtQYzsM5gFtYazOBN68wwDJWWlqpjx44efYX9qWDf7du86e8ZvBfrDGZhrcEMrDOYhbUGs3jLWmvJvttnK8YDAgLUuXNnq8OAm0VGRnr0X0b4BtYZzMJagxlYZzALaw1m8JZ15muV4vXYd/sHb/l7Bu/GOoNZWGswA+sMZmGtwSzesNZOdt/tW5erAwAAAAAAAAAAAABwBBLjAAAAAAAAAAAAAACfRmIcXik0NFTTpk1TaGio1aHAh7HOYBbWGszAOoNZWGswA+sMcD/+nsEMrDOYhbUGM7DOYBbWGszii2vNZhiGYXUQAAAAAAAAAAAAAAC4CxXjAAAAAAAAAAAAAACfRmIcAAAAAAAAAAAAAODTSIwDAAAAAAAAAAAAAHwaiXEAAAAAAAAAAAAAgE8jMQ4AAAAAAAAAAAAA8GkkxmGJxx9/XEOHDlVERITi4+N16aWXavPmzU3Oqays1B133KGYmBi1a9dOV1xxhQoKCpqcc/fdd2vw4MEKDQ3VgAEDjvua27ZtU0REhNq3b9/K7waeysx1ZhiGnnrqKfXo0UOhoaHq1KmT/vKXv7jrrcHDmLnW5s+frxEjRigiIkJxcXG64oorlJub66Z3Bk/TGmtt3bp1mjx5spKTkxUeHq7evXvr2WefPeq1Fi9erEGDBik0NFTdunXTW2+95e63Bw9h1jr7+OOPdf755ysuLk6RkZHKzMzU/PnzTXmP8Axm/kyr99133ykoKOiEewfAF7DvhlnYe8MM7LthFvbdMAt7b5iBfffRSIzDEt98843uuOMOLV++XF999ZVqamp0wQUXqKyszHXOfffdp88//1yzZ8/WN998o7179+ryyy8/6rluvPFGTZo06bivV1NTo8mTJ2v06NGt/l7gucxcZ/fcc49ee+01PfXUU9q0aZM+++wzDRs2zC3vC57HrLWWk5OjSy65ROeee67Wrl2r+fPn68CBA80+D3xTa6y1VatWKT4+Xu+99542bNig//f//p8eeughvfDCC65zcnJyNGHCBI0ZM0Zr167Vvffeq5tvvpmNk58wa519++23Ov/88/XFF19o1apVGjNmjCZOnKg1a9aY+n5hHbPWWr2ioiJdd911Ou+880x5f4DV2HfDLOy9YQb23TAL+26Yhb03zMC+uxkG4AH27dtnSDK++eYbwzAMo6ioyAgODjZmz57tOmfjxo2GJGPZsmVHPX7atGlG//79j/n8DzzwgDFlyhTjzTffNKKiolo7fHgJd62zrKwsIygoyNi0aZPbYod3cddamz17thEUFGTY7XbXfZ999plhs9mM6urq1n8j8Hinu9bq/eY3vzHGjBnjOn7ggQeMPn36NDln0qRJxrhx41r5HcAbuGudNScjI8OYPn166wQOr+PutTZp0iTj4YcfPuHeAfBV7LthFvbeMAP7bpiFfTfMwt4bZmDfbRhUjMMjFBcXS5Kio6MlOa9Aqamp0dixY13n9OrVSykpKVq2bFmLnnvhwoWaPXu2ZsyY0XoBwyu5a519/vnnSk9P15w5c5SWlqbU1FTdfPPNKiwsbN03AK/hrrU2ePBgBQQE6M0335TdbldxcbHeffddjR07VsHBwa37JuAVWmutFRcXu55DkpYtW9bkOSRp3LhxLf4dDN/grnV2JIfDodLS0uOeA9/mzrX25ptvKjs7W9OmTXND5IB3YN8Ns7D3hhnYd8Ms7LthFvbeMAP7binI6gAAh8Ohe++9VyNHjlTfvn0lSfn5+QoJCTlqLllCQoLy8/NP+rkPHjyo66+/Xu+9954iIyNbM2x4GXeus+zsbO3YsUOzZ8/WO++8I7vdrvvuu09XXnmlFi5c2JpvA17AnWstLS1NX375pa666irdeuutstvtyszM1BdffNGabwFeorXW2vfff6+PPvpIc+fOdd2Xn5+vhISEo56jpKREFRUVCg8Pb903A4/lznV2pKeeekqHDx/WVVdd1Wrxw3u4c61t3bpVDz74oJYsWaKgILbA8E/su2EW9t4wA/tumIV9N8zC3htmYN/t5NnRwS/ccccdWr9+vZYuXdrqz33LLbfommuu0VlnndXqzw3v4s515nA4VFVVpXfeeUc9evSQJL3++usaPHiwNm/erJ49e7b6a8JzuXOt5efn65ZbbtHUqVM1efJklZaW6tFHH9WVV16pr776SjabrdVfE56rNdba+vXrdckll2jatGm64IILWjE6+Aqz1tnMmTM1ffp0ffrpp4qPjz/l14L3ctdas9vtuuaaazR9+nTXv9MAf8S+G2Zh7w0zsO+GWdh3wyzsvWEG9t1OtFKHpe68807NmTNHixYtUufOnV33JyYmqrq6WkVFRU3OLygoUGJi4kk//8KFC/XUU08pKChIQUFBuummm1RcXKygoCC98cYbrfU24OHcvc6SkpIUFBTU5Id+7969JUk7d+48veDhVdy91mbMmKGoqCg9+eSTGjhwoM466yy99957WrBggX744YfWehvwAq2x1rKysnTeeefp17/+tR5++OEmX0tMTFRBQcFRzxEZGclV637E3eus3ocffqibb75Zs2bNOqqVIPyDO9daaWmpVq5cqTvvvNO1J/jTn/6kdevWKSgoiApD+AX23TALe2+YgX03zMK+G2Zh7w0zsO9uQGIcljAMQ3feeaf++9//auHChUpLS2vy9cGDBys4OFgLFixw3bd582bt3LlTmZmZJ/06y5Yt09q1a13//elPf1JERITWrl2ryy67rNXeDzyTWets5MiRqq2t1fbt2133bdmyRZLUpUuX03wX8AZmrbXy8nIFBDT91R0YGCjJWT0B39daa23Dhg0aM2aMpk6dqr/85S9HvU5mZmaT55Ckr776qkXrFd7LrHUmSR988IFuuOEGffDBB5owYYJ73hA8lhlrLTIyUj///HOTPcFtt92mnj17au3atRo+fLh73yRgIfbdMAt7b5iBfTfMwr4bZmHvDTOw726GAVjg9ttvN6KioozFixcbeXl5rv/Ky8td59x2221GSkqKsXDhQmPlypVGZmamkZmZ2eR5tm7daqxZs8a49dZbjR49ehhr1qwx1qxZY1RVVTX7um+++aYRFRXlzrcGD2LWOrPb7cagQYOMs846y1i9erWxcuVKY/jw4cb5559v6vuFdcxaawsWLDBsNpsxffp0Y8uWLcaqVauMcePGGV26dGnyWvBdrbHWfv75ZyMuLs6YMmVKk+fYt2+f65zs7GyjTZs2xv/93/8ZGzduNGbMmGEEBgYa8+bNM/X9whpmrbP333/fCAoKMmbMmNHknKKiIlPfL6xj1lo70rRp04z+/fu7860BHoF9N8zC3htmYN8Ns7DvhlnYe8MM7LuPRmIclpDU7H9vvvmm65yKigrjN7/5jdGhQwejTZs2xmWXXWbk5eU1eZ6zzz672efJyclp9nXZoPsXM9fZnj17jMsvv9xo166dkZCQYFx//fXGwYMHTXqnsJqZa+2DDz4wBg4caLRt29aIi4szfvGLXxgbN2406Z3Caq2x1qZNm9bsc3Tp0qXJay1atMgYMGCAERISYqSnpzd5Dfg2s9bZsX7mTZ061bw3C0uZ+TOtMU/eoAOtiX03zMLeG2Zg3w2zsO+GWdh7wwzsu49mMwzDEAAAAAAAAAAAAAAAPooZ4wAAAAAAAAAAAAAAn0ZiHAAAAAAAAAAAAADg00iMAwAAAAAAAAAAAAB8GolxAAAAAAAAAAAAAIBPIzEOAAAAAAAAAAAAAPBpJMYBAAAAAAAAAAAAAD6NxDgAAAAAAAAAAAAAwKeRGAcAAAAAAAAAAAAA+DQS4wAAAAAAAAAAAAAAn0ZiHAAAAAAAAAAAAADg00iMAwAAAAAAAAAAAAB82v8HG87xRWu44y4AAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 2000x1500 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(20, 15))\n",
+    "\n",
+    "# Projects count \n",
+    "ax1.plot(temporal_filtered.index, \n",
+    "         temporal_filtered[('Total Program GGRFFunding', 'count')],\n",
+    "         marker='o', linewidth=2)\n",
+    "ax1.set_title('Number of Projects (Excluding LCT)')\n",
+    "ax1.grid(True, alpha=0.3)\n",
+    "\n",
+    "# Average funding\n",
+    "ax2.plot(temporal_filtered.index,\n",
+    "         temporal_filtered[('Total Program GGRFFunding', 'mean')]/1e6,\n",
+    "         marker='o', linewidth=2)\n",
+    "ax2.set_title('Average Project Funding (Millions $)')\n",
+    "ax2.grid(True, alpha=0.3)\n",
+    "\n",
+    "# Total funding\n",
+    "ax3.plot(temporal_filtered.index,\n",
+    "         temporal_filtered[('Total Program GGRFFunding', 'sum')]/1e9,\n",
+    "         marker='o', linewidth=2)\n",
+    "ax3.set_title('Total GGRF Funding (Billions $)')\n",
+    "ax3.grid(True, alpha=0.3)\n",
+    "\n",
+    "# Partnership size\n",
+    "ax4.plot(temporal_filtered.index,\n",
+    "         temporal_filtered[('partnership_size', 'mean')],\n",
+    "         marker='o', linewidth=2)\n",
+    "ax4.set_title('Average Number of Partner Counties')\n",
+    "ax4.grid(True, alpha=0.3)\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
   }
  ],
  "metadata": {