andrewBatutin/gist:c36491d6e3e1428a9ecf73b2ae61503b

## gistfile1.txt
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Unit Economics: Edge vs Cloud AI Video Editor\n",
    "\n",
    "**The Thesis:** Local AI inference fundamentally changes the economics of multimodal applications.\n",
    "\n",
    "**The Question:** By how much, and where does it actually matter?\n",
    "\n",
    "Let's run the numbers.\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-08T16:57:09.038079Z",
     "start_time": "2025-11-08T16:57:09.035362Z"
    }
   },
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from IPython.display import display, Markdown\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# Plotting setup\n",
    "sns.set_style(\"whitegrid\")\n",
    "plt.rcParams['figure.figsize'] = (14, 8)\n",
    "plt.rcParams['font.size'] = 11\n",
    "\n",
    "print(\"✅ Imports loaded. Ready to analyze unit economics.\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ Imports loaded. Ready to analyze unit economics.\n"
     ]
    }
   ],
   "execution_count": 1
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Model Parameters\n",
    "\n",
    "**This is where you modify assumptions.** Change these values and re-run cells below to see how economics shift.\n",
    "\n",
    "The key variables:\n",
    "- **Pricing:** How much you charge\n",
    "- **Inference cost:** What cloud APIs cost per video\n",
    "- **User behavior:** How many videos they process\n",
    "- **CAC:** How much you spend to acquire customers"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-08T16:57:10.746099Z",
     "start_time": "2025-11-08T16:57:10.733154Z"
    }
   },
   "source": [
    "# ============================================================================\n",
    "# MODIFY THESE PARAMETERS TO EXPLORE SCENARIOS\n",
    "# ============================================================================\n",
    "\n",
    "# Revenue Parameters\n",
    "MONTHLY_PRICE = 20.0                # Subscription price per month\n",
    "ANNUAL_DISCOUNT = 0.25              # 25% off annual plans\n",
    "ANNUAL_MIX = 0.30                   # 30% of users choose annual\n",
    "\n",
    "# Platform Costs (both models)\n",
    "APP_STORE_CUT_Y1 = 0.30             # 30% first year\n",
    "APP_STORE_CUT_Y2 = 0.15             # 15% after $1M revenue\n",
    "SUPPORT_PER_USER_MONTHLY = 0.30     # Customer support\n",
    "CDN_PER_USER_YEARLY = 0.10          # Updates, downloads\n",
    "\n",
    "# Edge-Specific: One-Time Costs\n",
    "MODEL_OPTIMIZATION = 75_000         # Quantization, distillation\n",
    "APP_DEVELOPMENT = 200_000           # Initial development\n",
    "ENGINEERING_MONTHLY = 15_000        # Ongoing maintenance\n",
    "\n",
    "# Cloud-Specific: Per-User Costs\n",
    "INFERENCE_PER_VIDEO = 3.50          # Whisper + Vision + Processing\n",
    "VIDEOS_PER_USER_MONTHLY = 12        # Typical creator usage\n",
    "STORAGE_PER_USER_MONTHLY = 2.00     # Cloud storage\n",
    "BANDWIDTH_PER_USER_MONTHLY = 1.00   # Data transfer\n",
    "CLOUD_INFRA_FIXED = 5_000           # Base infrastructure\n",
    "\n",
    "# Customer Economics\n",
    "CAC = 80                            # Customer acquisition cost\n",
    "MONTHLY_CHURN = 0.05                # 5% monthly churn\n",
    "\n",
    "# Display current parameters\n",
    "params_df = pd.DataFrame({\n",
    "    'Parameter': [\n",
    "        'Monthly Price',\n",
    "        'Annual Price (with discount)',\n",
    "        'Videos per User/Month',\n",
    "        'Inference Cost per Video',\n",
    "        'Total Inference Cost/User/Month',\n",
    "        'CAC',\n",
    "        'Monthly Churn',\n",
    "        'Avg Customer Lifetime'\n",
    "    ],\n",
    "    'Value': [\n",
    "        f'${MONTHLY_PRICE:.2f}',\n",
    "        f'${MONTHLY_PRICE * 12 * (1 - ANNUAL_DISCOUNT):.2f}',\n",
    "        f'{VIDEOS_PER_USER_MONTHLY}',\n",
    "        f'${INFERENCE_PER_VIDEO:.2f}',\n",
    "        f'${VIDEOS_PER_USER_MONTHLY * INFERENCE_PER_VIDEO:.2f}',\n",
    "        f'${CAC:.2f}',\n",
    "        f'{MONTHLY_CHURN*100:.1f}%',\n",
    "        f'{1/MONTHLY_CHURN:.0f} months'\n",
    "    ]\n",
    "})\n",
    "\n",
    "print(\"\\n📊 CURRENT MODEL PARAMETERS\")\n",
    "print(\"=\"*50)\n",
    "display(params_df)\n",
    "print(\"\\n💡 Modify parameters above and re-run to explore scenarios\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "📊 CURRENT MODEL PARAMETERS\n",
      "==================================================\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "                         Parameter      Value\n",
       "0                    Monthly Price     $20.00\n",
       "1     Annual Price (with discount)    $180.00\n",
       "2            Videos per User/Month         12\n",
       "3         Inference Cost per Video      $3.50\n",
       "4  Total Inference Cost/User/Month     $42.00\n",
       "5                              CAC     $80.00\n",
       "6                    Monthly Churn       5.0%\n",
       "7            Avg Customer Lifetime  20 months"
      ],
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Parameter</th>\n",
       "      <th>Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Monthly Price</td>\n",
       "      <td>$20.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Annual Price (with discount)</td>\n",
       "      <td>$180.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Videos per User/Month</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Inference Cost per Video</td>\n",
       "      <td>$3.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Total Inference Cost/User/Month</td>\n",
       "      <td>$42.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CAC</td>\n",
       "      <td>$80.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Monthly Churn</td>\n",
       "      <td>5.0%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Avg Customer Lifetime</td>\n",
       "      <td>20 months</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ]
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "💡 Modify parameters above and re-run to explore scenarios\n"
     ]
    }
   ],
   "execution_count": 2
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Core Economics Functions\n",
    "\n",
    "These functions calculate the actual unit economics. The key difference:\n",
    "- **Edge:** Zero marginal inference cost\n",
    "- **Cloud:** Pays per video processed\n",
    "\n",
    "That's the entire game."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-08T16:57:13.737641Z",
     "start_time": "2025-11-08T16:57:13.732271Z"
    }
   },
   "source": [
    "def calculate_monthly_revenue(users: int) -> float:\n",
    "    \"\"\"Calculate MRR from mix of monthly/annual subscribers\"\"\"\n",
    "    monthly_subs = users * (1 - ANNUAL_MIX)\n",
    "    annual_subs = users * ANNUAL_MIX\n",
    "    annual_price = MONTHLY_PRICE * 12 * (1 - ANNUAL_DISCOUNT)\n",
    "    return (monthly_subs * MONTHLY_PRICE) + (annual_subs * annual_price / 12)\n",
    "\n",
    "\n",
    "def calculate_edge_economics(users: int, month: int = 12) -> dict:\n",
    "    \"\"\"\n",
    "    Edge deployment: High upfront, zero marginal inference\n",
    "    \"\"\"\n",
    "    mrr = calculate_monthly_revenue(users)\n",
    "    \n",
    "    # Variable costs\n",
    "    app_store_cut = APP_STORE_CUT_Y1 if month <= 12 else APP_STORE_CUT_Y2\n",
    "    app_store_fee = mrr * app_store_cut\n",
    "    support = users * SUPPORT_PER_USER_MONTHLY\n",
    "    cdn = users * (CDN_PER_USER_YEARLY / 12)\n",
    "    inference = 0  # THIS IS THE KEY DIFFERENCE\n",
    "    \n",
    "    # Fixed costs\n",
    "    engineering = ENGINEERING_MONTHLY\n",
    "    \n",
    "    # Amortize one-time costs over 24 months\n",
    "    one_time = 0\n",
    "    if month <= 24:\n",
    "        one_time = (MODEL_OPTIMIZATION + APP_DEVELOPMENT) / 24\n",
    "    \n",
    "    total_costs = app_store_fee + support + cdn + inference + engineering + one_time\n",
    "    profit = mrr - total_costs\n",
    "    margin = (profit / mrr * 100) if mrr > 0 else 0\n",
    "    \n",
    "    return {\n",
    "        'users': users,\n",
    "        'mrr': mrr,\n",
    "        'app_store': app_store_fee,\n",
    "        'support': support,\n",
    "        'cdn': cdn,\n",
    "        'inference': inference,\n",
    "        'engineering': engineering,\n",
    "        'one_time': one_time,\n",
    "        'total_costs': total_costs,\n",
    "        'profit': profit,\n",
    "        'margin': margin\n",
    "    }\n",
    "\n",
    "\n",
    "def calculate_cloud_economics(users: int, month: int = 12) -> dict:\n",
    "    \"\"\"\n",
    "    Cloud deployment: Low upfront, high marginal inference\n",
    "    \"\"\"\n",
    "    mrr = calculate_monthly_revenue(users)\n",
    "    \n",
    "    # Variable costs\n",
    "    app_store_cut = APP_STORE_CUT_Y1 if month <= 12 else APP_STORE_CUT_Y2\n",
    "    app_store_fee = mrr * app_store_cut\n",
    "    support = users * SUPPORT_PER_USER_MONTHLY\n",
    "    \n",
    "    # Cloud-specific costs (this is where it hurts)\n",
    "    inference = users * VIDEOS_PER_USER_MONTHLY * INFERENCE_PER_VIDEO\n",
    "    storage = users * STORAGE_PER_USER_MONTHLY\n",
    "    bandwidth = users * BANDWIDTH_PER_USER_MONTHLY\n",
    "    \n",
    "    # Fixed costs\n",
    "    infrastructure = CLOUD_INFRA_FIXED\n",
    "    \n",
    "    total_costs = app_store_fee + support + inference + storage + bandwidth + infrastructure\n",
    "    profit = mrr - total_costs\n",
    "    margin = (profit / mrr * 100) if mrr > 0 else 0\n",
    "    \n",
    "    return {\n",
    "        'users': users,\n",
    "        'mrr': mrr,\n",
    "        'app_store': app_store_fee,\n",
    "        'support': support,\n",
    "        'inference': inference,\n",
    "        'storage': storage,\n",
    "        'bandwidth': bandwidth,\n",
    "        'infrastructure': infrastructure,\n",
    "        'total_costs': total_costs,\n",
    "        'profit': profit,\n",
    "        'margin': margin\n",
    "    }\n",
    "\n",
    "\n",
    "def calculate_ltv_metrics(deployment: str = 'edge') -> dict:\n",
    "    \"\"\"Calculate LTV, CAC, and related metrics\"\"\"\n",
    "    \n",
    "    if deployment == 'edge':\n",
    "        variable_cost = (\n",
    "            MONTHLY_PRICE * APP_STORE_CUT_Y1 +\n",
    "            SUPPORT_PER_USER_MONTHLY +\n",
    "            CDN_PER_USER_YEARLY / 12\n",
    "        )\n",
    "    else:  # cloud\n",
    "        variable_cost = (\n",
    "            MONTHLY_PRICE * APP_STORE_CUT_Y1 +\n",
    "            SUPPORT_PER_USER_MONTHLY +\n",
    "            VIDEOS_PER_USER_MONTHLY * INFERENCE_PER_VIDEO +\n",
    "            STORAGE_PER_USER_MONTHLY +\n",
    "            BANDWIDTH_PER_USER_MONTHLY\n",
    "        )\n",
    "    \n",
    "    monthly_contribution = MONTHLY_PRICE - variable_cost\n",
    "    avg_lifetime = 1 / MONTHLY_CHURN if MONTHLY_CHURN > 0 else 20\n",
    "    ltv = monthly_contribution * avg_lifetime\n",
    "    ltv_cac = ltv / CAC if CAC > 0 else 0\n",
    "    payback = CAC / monthly_contribution if monthly_contribution > 0 else float('inf')\n",
    "    \n",
    "    return {\n",
    "        'deployment': deployment,\n",
    "        'monthly_contribution': monthly_contribution,\n",
    "        'ltv': ltv,\n",
    "        'cac': CAC,\n",
    "        'ltv_cac': ltv_cac,\n",
    "        'payback_months': payback,\n",
    "        'contribution_margin_pct': (monthly_contribution / MONTHLY_PRICE * 100) if MONTHLY_PRICE > 0 else 0\n",
    "    }\n",
    "\n",
    "\n",
    "print(\"✅ Economics functions defined\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ Economics functions defined\n"
     ]
    }
   ],
   "execution_count": 3
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. LTV/CAC Analysis\n",
    "\n",
    "**Does the unit economics actually work?**\n",
    "\n",
    "Healthy SaaS: LTV/CAC > 3x\n",
    "\n",
    "Let's see where Edge and Cloud land."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-08T16:57:16.518648Z",
     "start_time": "2025-11-08T16:57:16.465997Z"
    }
   },
   "source": [
    "edge_ltv = calculate_ltv_metrics('edge')\n",
    "cloud_ltv = calculate_ltv_metrics('cloud')\n",
    "\n",
    "ltv_comparison = pd.DataFrame([edge_ltv, cloud_ltv]).set_index('deployment')\n",
    "\n",
    "print(\"\\n💰 LTV/CAC METRICS\")\n",
    "print(\"=\"*70)\n",
    "display(ltv_comparison.style.format({\n",
    "    'monthly_contribution': '${:.2f}',\n",
    "    'ltv': '${:.2f}',\n",
    "    'cac': '${:.0f}',\n",
    "    'ltv_cac': '{:.2f}x',\n",
    "    'payback_months': '{:.1f}',\n",
    "    'contribution_margin_pct': '{:.1f}%'\n",
    "}).background_gradient(subset=['ltv_cac'], cmap='RdYlGn', vmin=-2, vmax=5))\n",
    "\n",
    "# Key insights\n",
    "print(\"\\n🎯 KEY INSIGHTS:\")\n",
    "print(f\"   Edge: ${edge_ltv['monthly_contribution']:.2f} contribution per user/month\")\n",
    "print(f\"   Cloud: ${cloud_ltv['monthly_contribution']:.2f} contribution per user/month\")\n",
    "print(f\"\")\n",
    "print(f\"   Edge LTV/CAC: {edge_ltv['ltv_cac']:.2f}x {'✅ Healthy' if edge_ltv['ltv_cac'] > 3 else '⚠️ Needs work'}\")\n",
    "print(f\"   Cloud LTV/CAC: {cloud_ltv['ltv_cac']:.2f}x {'❌ Unprofitable' if cloud_ltv['ltv_cac'] < 1 else '⚠️ Weak'}\")\n",
    "print(f\"\")\n",
    "if cloud_ltv['monthly_contribution'] < 0:\n",
    "    print(f\"   ⚠️ Cloud has NEGATIVE contribution margin!\")\n",
    "    print(f\"   They lose ${abs(cloud_ltv['monthly_contribution']):.2f} per user per month\")\n",
    "    print(f\"   Every new customer makes them poorer.\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "💰 LTV/CAC METRICS\n",
      "======================================================================\n"
     ]
    },
    {
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       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_546c0_level0_col0\" class=\"col_heading level0 col0\" >monthly_contribution</th>\n",
       "      <th id=\"T_546c0_level0_col1\" class=\"col_heading level0 col1\" >ltv</th>\n",
       "      <th id=\"T_546c0_level0_col2\" class=\"col_heading level0 col2\" >cac</th>\n",
       "      <th id=\"T_546c0_level0_col3\" class=\"col_heading level0 col3\" >ltv_cac</th>\n",
       "      <th id=\"T_546c0_level0_col4\" class=\"col_heading level0 col4\" >payback_months</th>\n",
       "      <th id=\"T_546c0_level0_col5\" class=\"col_heading level0 col5\" >contribution_margin_pct</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >deployment</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_546c0_level0_row0\" class=\"row_heading level0 row0\" >edge</th>\n",
       "      <td id=\"T_546c0_row0_col0\" class=\"data row0 col0\" >$13.69</td>\n",
       "      <td id=\"T_546c0_row0_col1\" class=\"data row0 col1\" >$273.83</td>\n",
       "      <td id=\"T_546c0_row0_col2\" class=\"data row0 col2\" >$80</td>\n",
       "      <td id=\"T_546c0_row0_col3\" class=\"data row0 col3\" >3.42x</td>\n",
       "      <td id=\"T_546c0_row0_col4\" class=\"data row0 col4\" >5.8</td>\n",
       "      <td id=\"T_546c0_row0_col5\" class=\"data row0 col5\" >68.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_546c0_level0_row1\" class=\"row_heading level0 row1\" >cloud</th>\n",
       "      <td id=\"T_546c0_row1_col0\" class=\"data row1 col0\" >$-31.30</td>\n",
       "      <td id=\"T_546c0_row1_col1\" class=\"data row1 col1\" >$-626.00</td>\n",
       "      <td id=\"T_546c0_row1_col2\" class=\"data row1 col2\" >$80</td>\n",
       "      <td id=\"T_546c0_row1_col3\" class=\"data row1 col3\" >-7.83x</td>\n",
       "      <td id=\"T_546c0_row1_col4\" class=\"data row1 col4\" >inf</td>\n",
       "      <td id=\"T_546c0_row1_col5\" class=\"data row1 col5\" >-156.5%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ]
     },
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     "output_type": "display_data",
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🎯 KEY INSIGHTS:\n",
      "   Edge: $13.69 contribution per user/month\n",
      "   Cloud: $-31.30 contribution per user/month\n",
      "\n",
      "   Edge LTV/CAC: 3.42x ✅ Healthy\n",
      "   Cloud LTV/CAC: -7.83x ❌ Unprofitable\n",
      "\n",
      "   ⚠️ Cloud has NEGATIVE contribution margin!\n",
      "   They lose $31.30 per user per month\n",
      "   Every new customer makes them poorer.\n"
     ]
    }
   ],
   "execution_count": 4
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Scale Analysis\n",
    "\n",
    "**What happens as you grow from 100 users to 500k?**\n",
    "\n",
    "Watch where the economics diverge."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-08T16:57:22.431164Z",
     "start_time": "2025-11-08T16:57:22.418249Z"
    }
   },
   "source": [
    "# Define user scales to analyze\n",
    "USER_SCALES = [100, 500, 1_000, 2_500, 5_000, 10_000, 25_000, 50_000, 100_000, 250_000, 500_000]\n",
    "\n",
    "# Calculate economics at each scale\n",
    "results = []\n",
    "for users in USER_SCALES:\n",
    "    edge = calculate_edge_economics(users)\n",
    "    cloud = calculate_cloud_economics(users)\n",
    "    \n",
    "    results.append({\n",
    "        'users': users,\n",
    "        'edge_mrr': edge['mrr'],\n",
    "        'edge_costs': edge['total_costs'],\n",
    "        'edge_profit': edge['profit'],\n",
    "        'edge_margin': edge['margin'],\n",
    "        'cloud_mrr': cloud['mrr'],\n",
    "        'cloud_costs': cloud['total_costs'],\n",
    "        'cloud_profit': cloud['profit'],\n",
    "        'cloud_margin': cloud['margin'],\n",
    "        'profit_gap': edge['profit'] - cloud['profit'],\n",
    "        'cost_advantage': cloud['total_costs'] - edge['total_costs']\n",
    "    })\n",
    "\n",
    "df = pd.DataFrame(results)\n",
    "\n",
    "# Display key milestones\n",
    "milestones = df[df['users'].isin([1_000, 10_000, 100_000, 500_000])].copy()\n",
    "\n",
    "print(\"\\n📊 ECONOMICS AT KEY MILESTONES\")\n",
    "print(\"=\"*100)\n",
    "display(milestones.style.format({\n",
    "    'users': '{:,}',\n",
    "    'edge_mrr': '${:,.0f}',\n",
    "    'edge_costs': '${:,.0f}',\n",
    "    'edge_profit': '${:,.0f}',\n",
    "    'edge_margin': '{:.1f}%',\n",
    "    'cloud_mrr': '${:,.0f}',\n",
    "    'cloud_costs': '${:,.0f}',\n",
    "    'cloud_profit': '${:,.0f}',\n",
    "    'cloud_margin': '{:.1f}%',\n",
    "    'profit_gap': '${:,.0f}',\n",
    "    'cost_advantage': '${:,.0f}'\n",
    "}).background_gradient(subset=['profit_gap'], cmap='Greens'))\n",
    "\n",
    "# Find break-even points\n",
    "edge_breakeven = df[df['edge_profit'] > 0]['users'].min() if len(df[df['edge_profit'] > 0]) > 0 else None\n",
    "cloud_breakeven = df[df['cloud_profit'] > 0]['users'].min() if len(df[df['cloud_profit'] > 0]) > 0 else None\n",
    "\n",
    "print(\"\\n🎯 BREAK-EVEN ANALYSIS:\")\n",
    "print(f\"   Edge breaks even at: {edge_breakeven:,} users\" if edge_breakeven else \"   Edge: Never profitable (check parameters)\")\n",
    "print(f\"   Cloud breaks even at: {cloud_breakeven:,} users\" if cloud_breakeven else \"   Cloud: Never profitable (negative unit economics)\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "📊 ECONOMICS AT KEY MILESTONES\n",
      "====================================================================================================\n"
     ]
    },
    {
     "data": {
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       "#T_eb443_row0_col9 {\n",
       "  background-color: #f7fcf5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_eb443_row1_col9 {\n",
       "  background-color: #f5fbf2;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_eb443_row2_col9 {\n",
       "  background-color: #d4eece;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_eb443_row3_col9 {\n",
       "  background-color: #00441b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_eb443\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_eb443_level0_col0\" class=\"col_heading level0 col0\" >users</th>\n",
       "      <th id=\"T_eb443_level0_col1\" class=\"col_heading level0 col1\" >edge_mrr</th>\n",
       "      <th id=\"T_eb443_level0_col2\" class=\"col_heading level0 col2\" >edge_costs</th>\n",
       "      <th id=\"T_eb443_level0_col3\" class=\"col_heading level0 col3\" >edge_profit</th>\n",
       "      <th id=\"T_eb443_level0_col4\" class=\"col_heading level0 col4\" >edge_margin</th>\n",
       "      <th id=\"T_eb443_level0_col5\" class=\"col_heading level0 col5\" >cloud_mrr</th>\n",
       "      <th id=\"T_eb443_level0_col6\" class=\"col_heading level0 col6\" >cloud_costs</th>\n",
       "      <th id=\"T_eb443_level0_col7\" class=\"col_heading level0 col7\" >cloud_profit</th>\n",
       "      <th id=\"T_eb443_level0_col8\" class=\"col_heading level0 col8\" >cloud_margin</th>\n",
       "      <th id=\"T_eb443_level0_col9\" class=\"col_heading level0 col9\" >profit_gap</th>\n",
       "      <th id=\"T_eb443_level0_col10\" class=\"col_heading level0 col10\" >cost_advantage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_eb443_level0_row0\" class=\"row_heading level0 row0\" >2</th>\n",
       "      <td id=\"T_eb443_row0_col0\" class=\"data row0 col0\" >1,000</td>\n",
       "      <td id=\"T_eb443_row0_col1\" class=\"data row0 col1\" >$18,500</td>\n",
       "      <td id=\"T_eb443_row0_col2\" class=\"data row0 col2\" >$32,317</td>\n",
       "      <td id=\"T_eb443_row0_col3\" class=\"data row0 col3\" >$-13,817</td>\n",
       "      <td id=\"T_eb443_row0_col4\" class=\"data row0 col4\" >-74.7%</td>\n",
       "      <td id=\"T_eb443_row0_col5\" class=\"data row0 col5\" >$18,500</td>\n",
       "      <td id=\"T_eb443_row0_col6\" class=\"data row0 col6\" >$55,850</td>\n",
       "      <td id=\"T_eb443_row0_col7\" class=\"data row0 col7\" >$-37,350</td>\n",
       "      <td id=\"T_eb443_row0_col8\" class=\"data row0 col8\" >-201.9%</td>\n",
       "      <td id=\"T_eb443_row0_col9\" class=\"data row0 col9\" >$23,533</td>\n",
       "      <td id=\"T_eb443_row0_col10\" class=\"data row0 col10\" >$23,533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_eb443_level0_row1\" class=\"row_heading level0 row1\" >5</th>\n",
       "      <td id=\"T_eb443_row1_col0\" class=\"data row1 col0\" >10,000</td>\n",
       "      <td id=\"T_eb443_row1_col1\" class=\"data row1 col1\" >$185,000</td>\n",
       "      <td id=\"T_eb443_row1_col2\" class=\"data row1 col2\" >$85,042</td>\n",
       "      <td id=\"T_eb443_row1_col3\" class=\"data row1 col3\" >$99,958</td>\n",
       "      <td id=\"T_eb443_row1_col4\" class=\"data row1 col4\" >54.0%</td>\n",
       "      <td id=\"T_eb443_row1_col5\" class=\"data row1 col5\" >$185,000</td>\n",
       "      <td id=\"T_eb443_row1_col6\" class=\"data row1 col6\" >$513,500</td>\n",
       "      <td id=\"T_eb443_row1_col7\" class=\"data row1 col7\" >$-328,500</td>\n",
       "      <td id=\"T_eb443_row1_col8\" class=\"data row1 col8\" >-177.6%</td>\n",
       "      <td id=\"T_eb443_row1_col9\" class=\"data row1 col9\" >$428,458</td>\n",
       "      <td id=\"T_eb443_row1_col10\" class=\"data row1 col10\" >$428,458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_eb443_level0_row2\" class=\"row_heading level0 row2\" >8</th>\n",
       "      <td id=\"T_eb443_row2_col0\" class=\"data row2 col0\" >100,000</td>\n",
       "      <td id=\"T_eb443_row2_col1\" class=\"data row2 col1\" >$1,850,000</td>\n",
       "      <td id=\"T_eb443_row2_col2\" class=\"data row2 col2\" >$612,292</td>\n",
       "      <td id=\"T_eb443_row2_col3\" class=\"data row2 col3\" >$1,237,708</td>\n",
       "      <td id=\"T_eb443_row2_col4\" class=\"data row2 col4\" >66.9%</td>\n",
       "      <td id=\"T_eb443_row2_col5\" class=\"data row2 col5\" >$1,850,000</td>\n",
       "      <td id=\"T_eb443_row2_col6\" class=\"data row2 col6\" >$5,090,000</td>\n",
       "      <td id=\"T_eb443_row2_col7\" class=\"data row2 col7\" >$-3,240,000</td>\n",
       "      <td id=\"T_eb443_row2_col8\" class=\"data row2 col8\" >-175.1%</td>\n",
       "      <td id=\"T_eb443_row2_col9\" class=\"data row2 col9\" >$4,477,708</td>\n",
       "      <td id=\"T_eb443_row2_col10\" class=\"data row2 col10\" >$4,477,708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_eb443_level0_row3\" class=\"row_heading level0 row3\" >10</th>\n",
       "      <td id=\"T_eb443_row3_col0\" class=\"data row3 col0\" >500,000</td>\n",
       "      <td id=\"T_eb443_row3_col1\" class=\"data row3 col1\" >$9,250,000</td>\n",
       "      <td id=\"T_eb443_row3_col2\" class=\"data row3 col2\" >$2,955,625</td>\n",
       "      <td id=\"T_eb443_row3_col3\" class=\"data row3 col3\" >$6,294,375</td>\n",
       "      <td id=\"T_eb443_row3_col4\" class=\"data row3 col4\" >68.0%</td>\n",
       "      <td id=\"T_eb443_row3_col5\" class=\"data row3 col5\" >$9,250,000</td>\n",
       "      <td id=\"T_eb443_row3_col6\" class=\"data row3 col6\" >$25,430,000</td>\n",
       "      <td id=\"T_eb443_row3_col7\" class=\"data row3 col7\" >$-16,180,000</td>\n",
       "      <td id=\"T_eb443_row3_col8\" class=\"data row3 col8\" >-174.9%</td>\n",
       "      <td id=\"T_eb443_row3_col9\" class=\"data row3 col9\" >$22,474,375</td>\n",
       "      <td id=\"T_eb443_row3_col10\" class=\"data row3 col10\" >$22,474,375</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🎯 BREAK-EVEN ANALYSIS:\n",
      "   Edge breaks even at: 2,500 users\n",
      "   Cloud: Never profitable (negative unit economics)\n"
     ]
    }
   ],
   "execution_count": 5
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Visualizations\n",
    "\n",
    "**Four views of the same story: edge scales, cloud bleeds.**"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-08T16:57:26.823213Z",
     "start_time": "2025-11-08T16:57:26.398837Z"
    }
   },
   "source": [
    "fig, axes = plt.subplots(2, 2, figsize=(16, 12))\n",
    "fig.suptitle('Unit Economics at Scale: Edge vs Cloud', fontsize=16, fontweight='bold', y=0.995)\n",
    "\n",
    "# Plot 1: Monthly Profit\n",
    "ax1 = axes[0, 0]\n",
    "ax1.plot(df['users'], df['edge_profit'], 'g-', linewidth=2.5, label='Edge', marker='o', markersize=6)\n",
    "ax1.plot(df['users'], df['cloud_profit'], 'r-', linewidth=2.5, label='Cloud', marker='s', markersize=6)\n",
    "ax1.axhline(y=0, color='black', linestyle='--', alpha=0.4, linewidth=1)\n",
    "ax1.fill_between(df['users'], df['edge_profit'], alpha=0.2, color='green')\n",
    "ax1.fill_between(df['users'], df['cloud_profit'], alpha=0.2, color='red')\n",
    "ax1.set_xlabel('Users', fontweight='bold')\n",
    "ax1.set_ylabel('Monthly Profit ($)', fontweight='bold')\n",
    "ax1.set_title('Monthly Profit: Scale Changes Everything', fontweight='bold')\n",
    "ax1.legend(loc='upper left', fontsize=12)\n",
    "ax1.grid(True, alpha=0.3)\n",
    "ax1.set_xscale('log')\n",
    "ax1.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: f'${x/1e6:.1f}M' if abs(x) >= 1e6 else f'${x/1e3:.0f}k'))\n",
    "\n",
    "# Plot 2: Profit Margin %\n",
    "ax2 = axes[0, 1]\n",
    "ax2.plot(df['users'], df['edge_margin'], 'g-', linewidth=2.5, label='Edge', marker='o', markersize=6)\n",
    "ax2.plot(df['users'], df['cloud_margin'], 'r-', linewidth=2.5, label='Cloud', marker='s', markersize=6)\n",
    "ax2.axhline(y=0, color='black', linestyle='--', alpha=0.4, linewidth=1)\n",
    "ax2.axhline(y=40, color='green', linestyle=':', alpha=0.4, linewidth=1, label='Healthy SaaS (40%+)')\n",
    "ax2.set_xlabel('Users', fontweight='bold')\n",
    "ax2.set_ylabel('Profit Margin (%)', fontweight='bold')\n",
    "ax2.set_title('Margin: Edge Stays Healthy, Cloud Stays Negative', fontweight='bold')\n",
    "ax2.legend(loc='lower right', fontsize=10)\n",
    "ax2.grid(True, alpha=0.3)\n",
    "ax2.set_xscale('log')\n",
    "\n",
    "# Plot 3: Total Costs Breakdown\n",
    "ax3 = axes[1, 0]\n",
    "cloud_inference = df['users'] * VIDEOS_PER_USER_MONTHLY * INFERENCE_PER_VIDEO\n",
    "\n",
    "ax3.plot(df['users'], df['edge_costs'], 'g-', linewidth=2.5, label='Edge Total', marker='o', markersize=6)\n",
    "ax3.plot(df['users'], df['cloud_costs'], 'r-', linewidth=2.5, label='Cloud Total', marker='s', markersize=6)\n",
    "ax3.plot(df['users'], cloud_inference, 'r:', linewidth=2, label='Cloud Inference Only', alpha=0.7)\n",
    "ax3.set_xlabel('Users', fontweight='bold')\n",
    "ax3.set_ylabel('Monthly Costs ($)', fontweight='bold')\n",
    "ax3.set_title('Cost Structure: Inference Dominates at Scale', fontweight='bold')\n",
    "ax3.legend(loc='upper left', fontsize=10)\n",
    "ax3.grid(True, alpha=0.3)\n",
    "ax3.set_xscale('log')\n",
    "ax3.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: f'${x/1e6:.1f}M' if abs(x) >= 1e6 else f'${x/1e3:.0f}k'))\n",
    "\n",
    "# Plot 4: Monthly Profit Gap\n",
    "ax4 = axes[1, 1]\n",
    "ax4.fill_between(df['users'], df['profit_gap'], alpha=0.3, color='green')\n",
    "ax4.plot(df['users'], df['profit_gap'], 'g-', linewidth=2.5, marker='o', markersize=6)\n",
    "ax4.axhline(y=0, color='black', linestyle='--', alpha=0.4, linewidth=1)\n",
    "ax4.set_xlabel('Users', fontweight='bold')\n",
    "ax4.set_ylabel('Edge Advantage ($)', fontweight='bold')\n",
    "ax4.set_title('Monthly Profit Gap: Your Edge Over Cloud Competitors', fontweight='bold')\n",
    "ax4.grid(True, alpha=0.3)\n",
    "ax4.set_xscale('log')\n",
    "ax4.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: f'${x/1e6:.1f}M' if abs(x) >= 1e6 else f'${x/1e3:.0f}k'))\n",
    "\n",
    "# Add annotation at 100k users\n",
    "if 100_000 in df['users'].values:\n",
    "    point_100k = df[df['users'] == 100_000].iloc[0]\n",
    "    ax4.annotate(f\"At 100k users:\\n${point_100k['profit_gap']/1e3:.0f}k/month advantage\",\n",
    "                xy=(100_000, point_100k['profit_gap']),\n",
    "                xytext=(150_000, point_100k['profit_gap'] * 1.3),\n",
    "                fontsize=9,\n",
    "                bbox=dict(boxstyle='round,pad=0.5', facecolor='yellow', alpha=0.7),\n",
    "                arrowprops=dict(arrowstyle='->', lw=1.5))\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"\\n📈 Charts generated. The visual story: edge scales profitably, cloud bleeds at scale.\")"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x1200 with 4 Axes>"
      ],
      "image/png": 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27NmDgIAASCQS+Pj4YOTIkUrvIxaLlVqeK7aatra2FoIPAJTmfUhOTlZJc1aKeefh4aHUk8Pd3R1HjhyBo6OjMGeBg4MDLCwsEBcXh4CAAPTq1QutW7dGw4YN4ebmho0bN+b6nnJVq1bFd999J7yWSqV49uwZbt68ibdv3wrL5UGdT2FpaYndu3fj4sWLOHr0KK5duyZ8RnIvX77EmDFjsG/fPiEfFfNn6NChSkN4TZ8+HePGjUPFihWF76CmzikiIgLPnj0DkNnav1+/fsI6CwsLfPHFF9i9ezekUin8/Pw0NmG7qakpBg0alO36MmXKCH+/efNGacgzxWCLgYEBRowYoTYAIQ8gAUCPHj2E4AMANGrUCM2bN1dpRS+fdwEAKlasKAQf5K8bN26MS5cuITExEffv30eTJk2yPQczMzN4enri2LFjyMjIwKlTpzB06FC8ePFCGHqufPnyaNasGQDNXvOKvWyyBlk+hSbuM3mVlpYm3OcAYNKkScLcQDo6OhgzZgwDEERERPTZYACCiIiICFCaGFpxPoOsFNcp7qPIyspKZZJeExMTofJP3TA1haFjx455rlR9//698HfWOQ/09PSUKuUBKM11UKlSJZXeDWKxGE5OTsJY7YrbK5K3OpdTnCRWntevX78WKhpNTU1RqVIllePUqVNHaJmv7r0sLS2VJi1WrFjMer6Kn11eKjgV804+H0LWtCkyMDDAkiVLMH36dKV5IoDMfHN3d8egQYNUJtbNTnJyMg4fPowLFy7g3r17aoMmOV3T+SESidC+fXu0b98eGRkZePjwIfz8/ODt7Y0nT54AyJyr4Y8//sCff/4JIOf8sba2VjtMjibO6d27d8Lf6enpObauz0tPl7zKT4+lyMhI4W9ra2uVSZirVq2qdj/FScHVbePo6KgSgFAM3rx+/RpOTk7Zpuv58+c5BiCAzGGYjh07BiCzd8DQoUOVej/06tVLCEpq8ppXnK8jLi4OUqk022BwfmjiPqOOuus0NjZWaT4UxWAwgByHlSIiIiIqaRiAICIiIoJyxbfiZMRZKa7LbogSxYpuOU1UkBUVxYqx7Ci2Ys+OYuV9dj1MsuaVunzK72Sv6t4ra0BIcZus6z5FXoNLHh4eOHv2LI4ePYqLFy/iwYMHyMjIgEQigb+/P/z9/XHr1i3Mnz8/x+NER0dj0KBBQm8UR0dHNG/eHG5ubjhx4gQuXrz4qacEIHPOhbdv3yIiIgIeHh5wdHSErq4uXF1d4erqiokTJ2LRokXYtWsXAOUW+orycm1p6pwUPwsdHZ0c5wPQZEv6/FC8DtVdO3nJr7wGlxS309PTUwl2KMrLddyoUSNUrlwZL1++xJ07d/Du3TucOnUKQOZ5ZQ1+auqaVwycpKWl4fnz56hRo4babSdNmoTq1aujQ4cOcHFxyfG4mrjPAFAJiMiHH8tp36z5rW4fIiIiopKKAQgiIiIiKA+LEhsbi4iICNjZ2Sltk5SUhLi4OOG1jY1NkaWvsJUtW1b4OyQkRGmdVCrF4sWLUalSJVSvXh2NGjVS6jXw6tUrJCYmKvWCkEgkePr0qfD6U8ZKL1u2LEQiEWQyGRITE/H69WulYY4ACK2pC/JenzqGfE55B2SOK29hYYHq1aujYcOGQuDK0tISAwYMwLhx45CcnIz79+/j8uXLwqTd8rH4s16HirZu3SpU1A8YMAALFiwQ1p09e/aTzivrOchbfkdHR+Pbb79V2aZp06ZCAEJxeKSyZcsKrcVDQkLg6OgorAsNDcW+fftQvXp11K5dG3Xr1tXYOcknmgYye7z4+voqVQxLJJJsezEVFcU0xsfHIyoqSum+kl3PDMX7leJk7XKK3z1171WhQgWcOXNGaX1+80MkEqFPnz7CXC+bNm0SPucmTZooDQslp4lr3tnZGTY2NsLQVV5eXmqvxwcPHuDChQu4cOECNm7ciG3btilNpJ5VQe8zWfMsJSVFKaAtn6tDkZWVFfT19YV5MUJCQpQCJJrskUNERESkbSWnKR4RERFRIapevbrQEl4mk2HZsmUqrVI3bdoktCLW19fPttWtJihWahVFa9jGjRsLf588eRIfPnwQXl+4cAE7d+7EokWLMH36dOjo6KBWrVpCECIlJQXLly9XakW+detWYfglMzMzNG3atMBps7S0hLu7u/B68eLFQsUdAJw6dUqoHNfV1YWHh0eB36sgFPPO19cXwcHBwutHjx5h/fr1WLJkCSZMmIC0tDScOnUKnp6ecHV1xfjx45GRkQFjY2M0bdoU06ZNU6q8VBxGSB35sEeA8tA079+/V5p7QbH1e26ts9Vp06aN8Pfu3btx9+5dpfUfP35UmtRbsZW6Yv7s3r1b6bP7+++/sX37dnz//ffCxMQFOSd1ypcvL1SCf/z4EXv37hXWJScno0OHDmjfvj0mTJiAoKCgHI9VWMqVKyd8j2QyGbZu3aqUxi1btqjdT/H7cOzYMeG7BgBXrlwRJupW5OzsDGNjYwCZQYtLly4J68LDw9G4cWN4enri66+/Vvr+56Rnz57CvWrfvn3Ccvnk03KavOZ1dXWV5l7YtWuXSjAlIiJCKShRqVKlXIeUKuh9xtzcXOk48nlHAODhw4d4/fq12nNwdXUVXm/btk24f2ZkZGDdunU5ppWIiIioJGEPCCIiIiJkDqfUv39/oRL12LFjuHv3Lpo0aQI9PT3cv38fDx48ELbv0qWLyrwHmqR47PDwcKEybenSpXk+hre3N168eJHjNgMGDEDFihXRsWNHrFq1CmFhYYiMjESPHj2Ecf5Pnz4tbD9kyBChAnvixImYN28eAGDPnj24d+8eXF1dERwcrDRx7uTJkz85ryZOnIgxY8ZAJpPhwoUL6NGjB5o0aYK3b9/iypUrSunL2mq5sLm7u8PNzQ137txBamoq+vfvjy+++AKGhoZKede9e3dYWFigQYMGCAsLg0QiwZ07d9CjRw80bdpUmAxZPkm5ubl5rkEuxZbwW7ZsQVhYGAwNDXHmzBkkJCQI6xR7JCh+Fj4+Pvj5559hb2+PCRMmZPs+gwYNws6dOxEZGYnU1FQMGjQILVu2ROXKlZGQkICrV68iIiJC2H706NHC38OHD8fRo0eRnp6Oa9euCef75s0bpc9u6NChBT6n7IwaNQoLFy4EACxYsAA+Pj6oUqUKrl27JlTaSyQSpXkUHj58CG9vbwCZkzMPGDAg1/dRFBcXh99//z3HbRSPO3z4cCxevBhAZuDuyZMnqFKlCv79999s5xno2LEjVqxYgaioKCQlJaF379744osvkJCQgPPnz6vdx8jICAMHDhR6G0yaNAnt27eHvb09Lly4gMTERCQmJsLc3Fypt0RO7O3t0bp1a/j4+AgBITMzM6VJ3QFo9JoHMq8vX19f+Pv7Iz09HVOmTIG7uzvq1q2L6Oho+Pj4CMcUiUSYN29enoaNK8h9xsTEBBUrVhQCDTNnzsTIkSMRGxuLnTt3Zju81/Dhw4X75KlTpxAWFoZ69erh5s2bSkE4IiIiopKOAQgiIiKi/zdjxgy8fPkSly9fBpA5yai6CsD69etj7ty5hZqWatWqwdLSErGxsQCAo0ePQkdHB7/88kueKtIA4PLly8K5ZKdVq1aoWLEi9PX1sWbNGowZMwYxMTGIiYnBoUOHlLZt3Lgxxo0bJ7zu168fXr16hc2bN0Mmk+HRo0d49OiR0j6jRo3CiBEj8pTenLRs2RLz5s3DkiVLkJ6ejhcvXqgEVzp37oxZs2Z98nsVxO+//44RI0bgzZs3SE5OVpqMFwBq1KghBJHKli2LFStWYNq0acjIyMCzZ8+UWk0DmePR//rrr9nOMyI3bNgwnDhxAmlpaZBIJDhx4oSwzszMTKiwVxymR7GVd1JSEvbs2YNGjRrlGIAwNzfH+vXrMWHCBERFRUEqlSpVyMqJRCJ89dVX6NChg7CsZs2a+OmnnzB//nxIJBK1n9348eOFFuoFOafsDB48GHfu3BGO4evrC19fX6XjrVmzRmlS8qdPn2Lz5s0AMq/5/AYgEhMThf2zo3jcYcOGwc/PT+iRcPXqVWEC6S5duuD69evCcENypqamWLp0KSZMmICMjAzExsYK31dLS0u4ubnBx8cHgPIQY1OnTsXDhw/h7+8PiUSiMqRV2bJlsXz58nydb9++fYX3kqc567wqmrzmgcweBBs2bMC3336Lc+fOAQACAgKEHgpy+vr6+PHHH5V68OSkoPeZ0aNH4+effwaQOSSdfNgwGxsbeHp6qvTQAIAOHTpg4MCBQs+Re/fu4d69ewAy59dITExEYGBgntJNREREVJxxCCYiIiKi/2doaIiNGzfi999/R8uWLWFnZwc9PT3o6enBxsYGzZs3x4IFC7Bnz54cJ3DVBH19faxduxYuLi7ChLFNmjTJcYLsT+Xs7Ixjx45h2LBhqFSpEvT09GBsbAxnZ2fMnTsX27ZtU6qoBTKDNnv27EGPHj1QoUIF6OnpwdraGh4eHtixYwfmzJmjsfQNHToUXl5eGDhwICpVqgR9fX1YWFigefPmWL16NVauXJnviWQ1xcHBAV5eXpgwYQIcHR1hYGAAAwMD1KxZE5MnT8aBAweUhhP68ssvcfz4cQwYMADVq1eHiYkJ9PT04ODggJ49e+LQoUNKlfjZqVOnDvbv349WrVoJ48pXq1YNkydPVhpy6Ny5c0JLbGdnZ/z000+oWLEi9PT0YGdnpzRkUnbq1auHU6dO4ZtvvoGbmxssLCwgFothZmaGatWqoX///jhw4AAmT56ssm/fvn2xf/9+dOrUCXZ2dtDV1YWFhQVatGiBP//8E9OnT/+kc8qOjo4Ofv/9dyxbtgxNmzaFpaUl9PX1UblyZQwYMABHjhxBvXr1cj33wiQWi7F27VrMmDEDVapUgZ6eHqpWrYq5c+fi999/z3aOklatWmHPnj1o2bIlTExMYGZmhg4dOuDgwYNK86DIh10CMu9x27dvx/z58+Hm5gYzMzMYGhqiWrVq+N///ofDhw+jUqVK+Up/27ZtYWtrK7zOOvySnKaueTkTExOsXbsW27ZtQ5cuXVCuXDno6+vDyMgINWrUwPDhw3Hy5En07ds3X+dTkPvM4MGDsXTpUtSqVQsGBgaws7ND//79cezYsRzz86effsLChQtRs2ZN6Ovro0KFCpg0aZLaey0RERFRSSWS5VZqJyIiIiIiomLjyZMn8PX1haWlJaysrNCsWTNhHgWpVIpRo0YJ80CsWbMGnp6e2kwuEREREZViHIKJiIiIiIioBElISFCaZ6J27dpo3LgxpFIp7t69K8xXY2RklOvky0REREREhYk9IIiIiIiIiEoQmUyGsWPHKs1noc7333+P4cOHF1GqiIiIiIhUMQBBRERERERUwqSlpWH//v04e/Ysnj17hvj4eIhEIlhbW8PV1RWDBw9G06ZNtZ1MIiIiIirlGIAgIiIiIiIiIiIiIiKN09F2AoiIiIiIiIiIiIiI6PPDAAQREREREREREREREWkcAxBERERERERERERERKRxDEAQEREREREREREREZHGMQBBREREREREREREREQaxwAEERERERERERERERFpHAMQRERERERERERERESkcQxAEBERERERERERERGRxjEAQUREREREREREREREGscABBERERERERERERERaRwDEEREREREREREREREpHEMQBARERERERERERERkcYxAEFERERERERERERERBrHAAQREREREREREREREWkcAxBERERERERERERERKRxDEAQEREREREREREREZHGMQBBREREREREREREREQaxwAEERERERERERERERFpHAMQRERERERERERERESkcQxAEBERERERERERERGRxjEAQUREREREREREREREGscABBERERERERERERERaRwDEEREREREREREREREpHEMQBARERERERERERERkcYxAEFERERERERERERERBrHAAQREREREREREREREWkcAxBEn7lhw4bByclJ+Ofl5aW0/tWrV0rrnZycijR9T58+VXotT8OCBQty3XfOnDlwcnKCm5ubxtKTNS9q1aoFZ2dnNG3aFP/73/9w584djb1XVjExMZg2bRrc3d1Rv3599OjRA4mJiTnmSdb8y6+UlBT8+eef6N69O9zc3ODi4oL27dtj3rx5ePXq1ScdOy88PDzg5OSE8ePHa/zYFy9exLhx49CsWTM4OzujVatWmDFjBh49eqS03Zs3b4Q83rp1q8bTUVLJv1+5/Xvz5o22k5onERERiI6OFl7/8ccfwjkoLleH1wgREalT3MvZWRVmuSsrxd/OnP7NmTMn12PJ87lr166Fnu7s+Pj4YMyYMWjatCnq1q2LJk2aYPTo0Th79my2+3xqOb0w5Va2efDgQbbXtSblVB5LTEzEu3fvhNdeXl7Ctg8ePCi0NOUkLCwMP//8Mzp06AAXFxe4u7tj8ODBOHjwIKRSqdK2hfGsWhD5+f4U5Nkw6+dU3CheY3v27MlxfXGT9R5SXK4pooJgAIKolPH398/xdVF5+vQphg8fjuXLl2vl/fNKJpMhPT0dMTEx+PfffzFixIhCC0IsW7YMp06dQmJiIj5+/Ij379/D1NRU7bZhYWGYMmUKZsyYUeD3S0pKwuDBg7FmzRoEBQUhOTkZaWlpePPmDQ4ePIiePXsiMDCwwMfXFolEgrlz52LixIm4fPkyoqOjkZ6ejvDwcJw4cQL9+/fH0aNHtZ1MKiLp6enYtm0bPD09ERYWpu3kEBHRZ6y4lLNJszZs2IAJEybA19cXMTExyMjIQGxsLK5evYrJkydj9erVStuXlOec4komk8HLywuenp64d++etpMjuHjxIrp06YI9e/bg1atXSEtLQ2JiIgICAjBv3jyMHz8eGRkZ2k5mgeX32bC4fk45WbNmDeLj47WdjFxFR0dj/vz5GDRokLaTQqQxutpOABEVrawPQjdv3tRKOiZMmICwsDC0bdtWK++fm969e2Pq1KnIyMhAYmIi9u7di3379iE1NRUrVqzArl27NP6e9+/fBwBUqFABmzdvhkwmAwBcvnwZAGBsbCxsO2fOHPj7+6NGjRoFfr89e/bg8ePHEIlEmDhxIjp27AhdXV34+Pjg999/R1JSEn799ddCOdfCtHbtWqGlVrt27TBu3DhYWFjg2rVrWLFiBZKTk/HDDz/Azc0NlStX1nJqiz8jIyN4e3tnu97Ozq4IU5N/J06cwNKlSz/pGOXKlRO+h2ZmZppIFhERfYaKSzk7O/v374dEIoGBgUGRvu/EiRMxcOBAteuMjIyKNC359eHDB/zxxx8AgMaNG+Prr79GuXLlEBISgkWLFuHVq1fYsGEDevfujYoVKwIo/s85xd3Nmzcxd+5cbSdDSXBwML755hukpqbC3t4es2bNQr169fD69WusWLECjx49wpUrV7Bp0yZMmjRJ28ktkPw+GxbHzyk3MTExWLt2Lb777jttJyVHy5Ytg5eXl9LzPwDMnTsX33zzDUQikZZSRlRwDEAQlRLly5fH27dvERYWhjdv3sDBwQHAfw9GFSpUYOtgBUZGRihbtqzw+ueff0ZAQACCg4MREBCAjIwM6Opq9haanJwMAKhevTocHR2F5Yrp0KSAgAAAgL29PaZOnSosd3R0xL1793D27FncunWrUM61sERFRWHLli0AMh8S161bBx2dzM5+jo6OsLCwwKxZs5CWloZTp05h4sSJ2kxuiSASiQrtGiwK8kDepxCLxSU6D4iIqHCVlHK2thoNmJmZldjf0bt37wqt2idNmoQmTZoAACpVqgSJRIKJEydCKpXC399fCEDQp9FE2U3TVq1ahdTUVOjp6WH79u3Cs1rlypXh4uKCTp06ISoqCseOHcPEiRNLZAVxfp8Ni+PnlBd79uzBgAEDlJ63i5vs8tbCwgIWFhZFnBoizeAQTESlhIODA+zt7QH81zorLCxMeBhyd3dXu59MJsOBAwfQr18/uLm5oUGDBhg2bBguXryotN2NGzeEsROfPn2KtWvXom3btqhXrx4GDBggFGiAzHkW5O976dKlbMcWPX/+PLp16wYXFxd06dIF//zzT47nuH37diENWYdJmj9/vjBeYkpKSo7HyU7NmjUBZA7xIx+jVD6m5rRp07BmzRo0aNAAjRo1ElpL5yX/5Hknz5PLly/DyclJaG2VdQ4IDw8P4TMMDg5W2jY/Y6Pq6+sDAN6/f49FixYpPRj/9ttv8PPzw9WrVyEWi4XlaWlpWL9+PTp16gQXFxe0bNkSkyZNwuPHj5WOHR4ejh9++AEeHh5wdnZGo0aNMGjQoBzHyVV0//59/O9//4Obmxvc3NwwbNgw+Pn55brfmTNnkJaWBgAYOXKkEHyQ69y5M5YuXQofH59sgw/79+/Hl19+CRcXF/Tu3Rv//vuv0vr09HSsW7cOnTp1gqurK9zc3NC1a1ds2rRJqdu14rXx+PFjjBgxAq6urmjRogWWLFkipFPuzZs3mDJlCho0aIDGjRvj559/RkhIiPB53rhxQ9g2ISEBv/zyC1q3bg1nZ2d4enpi/fr1SE9PVzqmn58fRowYgUaNGsHZ2Rlt27bFzJkzERISkmte5semTZuUvv+KVq5cCScnJzg7Owvfm7S0NKxZswZffPEFnJ2d0a5dOyxduhSJiYlK+yqOTTx58mS4uLigVatWGDt2LJycnODu7q6Sjx07doSTkxOGDRuGP/74Q6llVt++feHh4aGS/vj4eHz33Xdo2LAhGjZsiBkzZiAqKkpYn904yfJle/fuxalTp4T7laenJw4ePKjyPv7+/hg4cCDq1asHDw8P7Ny5E8eOHSu2484SEVHeFLScffXqVQwfPhxNmzaFs7MzWrZsiZkzZyrNr6RYtvPz84OnpydcXFyEuRMkEgnWrVsHDw8P1KtXD4MHD8bjx48xcuRIlTkW1M0Bkd/ySn7mayuInTt3CufYs2dPlXKYovz8rr548QJTpkxBo0aNUL9+ffTr1w+nTp3KNT3y8jKQWT6+fv26UDnYtm1b+Pn5wc/PTxhfP6fnnMTERCxduhQdOnRAvXr10KBBA/Tu3Rv79+8X3qNbt25wcnJCx44dldKRlpYGd3d3ODk5CWWb5ORkLF26VChPNWrUCL169VI7zr0mHT9+HL169YKLiwuaNGmCadOmqZ0fYPfu3ejRowcaNGiA+vXr48svv8Tvv/+e47OYl5cXhg8fLryeOnWq2jJSamoqli5dimbNmsHV1RUTJkzAy5cvAWQ2SKpbty6cnJwwf/58pf3u3r0rXB9HjhzJ0/kmJibCx8cHQOZnnrXi2sLCAr/99hsOHDiAU6dO5Rp8KMjztWJv5Jzm78jP9yer/Dwb5vY53b9/H+PHj0fLli3h7OyMZs2aYdKkSXjy5AkA4NGjR8I5bNy4USkdJ0+eFNbJ76ePHz/GhAkT0KRJE2Fuv4kTJ+Z7LhCRSIT09HQsWbIk123z+rwCAHv37kXHjh3h4uKCXr164dq1a/j++++FZxK5vDxHDhs2TLg2k5OTle7jWeeAKKxnMKLCUDKatBKRRjRo0ACnT5+Gv78/evfuLbTKsrOzQ6VKlVS2l8lkmDp1Ks6cOaO03N/fH/7+/vjmm2/UVuLOnz9fKQBw9+5djBs3DpcvX852ToOs/v33X+zZs0co4D979gwzZ85ExYoV4erqqnafrl27YtmyZZBIJDh79qzwwyyTyYQCnYeHR4G6estkMgQHBwPIbA1taWmptN7X11d4iNHV1UW9evUKnH9FxdPTU0jbrl27sGvXLtSsWROtW7dGhw4dVPJZ3spLsSAbERGBCxcuwM/PD7t370adOnWQnp6O//3vf0qFoPT0dNy+fRt37tzB9u3b0axZs2zT5efnh7FjxypVpvv7+yMgIACrV69Ghw4dst1XsRBar149lfW6urro2bNntvsfOHAAoaGhwutHjx5hwoQJOHfuHMqVKwcAWLhwodKDIpAZCFq+fDk+fvyIKVOmKK17/vw5hgwZIvRwSUlJwfbt22Fqaoqvv/4aQOaD0qBBgxAeHi7st2fPHmFYLkUpKSkYOnSoUIAHgNDQUKxatQqPHj3C2rVrAQAPHz5Uycd3797hn3/+wfXr13H06FHY2tpmmxdyMpkM79+/V7vOyMgIFhYW6NmzJ1atWgWJRIITJ05g+vTpwr7ywGG7du1gbW0NqVSqch29ffsW27ZtQ0BAAP7++2+lh30AWL9+PRISEgAANjY26N27N65cuYLExERcu3ZNGOLg+fPnQnClW7du+PDhQ67nBwDjx49X+txPnDiBuLg4oTdNbo4dO6Z0zwsNDcW8efNQqVIloaXk9evXMWbMGOHzCAsLwy+//AJnZ+c8vQcRERVv+S1n37x5E+PGjVNqvBAREYF//vkHd+/ehbe3t0oP1MmTJwu/h7Vr1wYA/Pjjj0pB74CAAAwfPhzW1tb5Sn9eyisFlZCQkG1Zws7OTmjssmLFCqXKyMDAQIwfP17t8If5+V0NDg7GoEGDhLwDMitIp02bhsjISKWK1KwaN24MKysrxMTECAEaKysrtGjRAm3btsWXX36Z5yGtpk6dqlT+SU1NxaNHjzB//nzo6uqiT58+6NGjB5YtW4aQkBAEBwcLw636+fkJlYTyYMe3336r1LgnPT0djx8/xs8//4zo6Og8f27qPp+sE0LLrV+/HqtWrRJey3sV+/n54cCBA8K1vnHjRqxYsUJp35cvX2Lz5s2IiIj45OExv//+e6Wym4+PD169eoWTJ0/CxsYGLVq0wOXLl3HhwgX89NNPQqOkc+fOAQAMDAxyfKZQFBgYCIlEAkD98wUAtGzZMk/HKsznw/x8f9TJ77Nhdl68eIGRI0ciKSlJWBYdHY0LFy7g1q1bOHv2LOrWrYvq1avj2bNnOHv2rFJQVP4ZlS1bFo0aNcLbt28xcuRIxMXFCduEh4fj4sWLuH79Og4cOJDnYYm7deuG48eP48qVK7h8+TLatGmjdrv8PK9k/U48fvwY48aNQ7Vq1VSOm9/nyNwU9jMYkSaxBwRRKdKwYUMA/7XMkv+fXausQ4cOCYWQDh06wMvLC7t37xYKXqtXr8bdu3dV9nv69ClWrFiB06dPo3Xr1gAyW45cunQJQGYLf3k37GbNmuHy5cvo1KmT0jFevnyJKVOm4OzZs8IPKZDZ4iY7dnZ2QsX2+fPnheV3795FREQEgMxCR16kpKTg/fv3ePv2LR4+fIj58+cLFerNmjVT+XFOSEhAnz59cPr0afzxxx+wsrLKc/65ubmpzZNRo0apTdv+/fuFAmDVqlWVtu3UqRMuX76My5cvo1atWjmeY5cuXVTG43369Cm2bNmCAQMGYMiQIXj37p2w7tixY0KBpV+/fjhx4gQ2bdoES0tLJCcnCw8Zfn5+ePHiBXR0dLB06VKcP38ea9euhVgshkwmw5UrV7JNk1QqxY8//oj09HTUqFEDu3fvxj///ANPT09IJBL8+OOPKi3xFCm2Wreyssrx/NV58+YNFixYgLNnz2LIkCEAMh/m5MGl2NhYnDx5EgAwfPhwnDt3Dvv370eFChUAQLjGFQUFBaFFixY4fvw41q5dK1QmKPbo2bRpkxB8GDFihDBvwYsXL1SOt23bNjx58gRisRgLFiyAt7c3Fi5cCLFYjHPnzgnX/smTJ5Geno4KFSpg7969OH/+PJYvXw49PT18/Pgxzy2iUlJS0KZNG7X/Fi9eDAAoU6aM8F2X5w8A3L59W2g91bt3bwCZ32H5e0+dOhWnT5/G6tWrYWxsjHv37mHv3r0qaUhISMCPP/6If/75B99//z08PDyEhynFB2/5uevp6cHT0xOjRo1S6gGxadMmlUK/fPs9e/bg6NGjqFKlCoDMIGh2D99Z3blzB5MnT8aZM2eUHhoV82Lp0qVIT0+Hvr4+Fi5ciJMnT2LChAl4+PBhnt6DiIiKt/yWsw8cOICMjAzUqFEDhw8fhre3N/r06QMAeP36tdoygLm5OQ4ePIitW7eiS5cuePLkiRB8cHJywp49e3DgwAFUq1ZNaA2eV3kprwAQypnffPNNno+9fv36bMsS8rJmeHi40Jq7fPny2LRpE44dO4ZWrVohJiZG5Zj5+V1dtGgREhISUKZMGWzatAmnTp3C4MGDAWSOtR4ZGZlt2k1MTLB8+XKlsdhjYmJw4sQJzJw5E23atFFqnZ7dc86zZ8+Ea2LWrFk4f/48duzYIZRn5L2nu3XrJlSWK5ZxLly4ACDzeadp06ZITEwUKmrHjx+PM2fO4NixY2jdujV0dHRw8eJFodI8N+o+n3Hjxqls9/r1a6HXtaenJ44fP47du3ejRo0aiImJEYIKEolEKG917twZ3t7eOHLkiBAcUldeluvUqZNSZe6CBQuEvFGUnJyMrVu34uTJk2jQoAGAzCCa/PPv3r07ACAyMhK3b98W9pPnY9u2bfPcME7x+ijI84Wigj5f5ya/3x918vNsmNPndOzYMSQlJcHOzg67d+/GuXPnhPJxXFyc0GhH/hk9fPhQOG5aWprwrNi5c2eIRCJcvHgRcXFxMDExwfbt23H+/HnhGRT47zPNi5kzZwrf5SVLlmQ7aXhen1eio6Px559/AsjM9y1btuDo0aNo2bIlgoKClI6Z1+fI1atXCz2gjIyMcPny5Wzn2ijsZzAiTWIAgqgUkT8AycenvXXrFoD/Hpiykj/QVKhQAStWrEDdunXRsGFDrF27Fvr6+pDJZGor84YMGYIuXbqgWrVqmDx5srBcXjlctmxZoaWTgYEBypYtq9IroX79+pg0aRIqV66s1HJDsYW4OvKCzKtXr4QW4vJKSUtLS7Ro0SLH/eW8vLzQpk0btGvXDn369MGBAwcAAKampvj2229VttfR0cHs2bNRrVo1YYiXvOafvr6+2jzJrlBsZ2cnBEB0dXWVtpXPXVG2bFno6enlep4///wzduzYAU9PT5iYmCitu3XrFsaPHy88vMgfguzs7PDjjz+iRo0aaNOmDRYtWoRFixZh2rRpAIDWrVvjzp07OHnyJHr27Iny5cvD3t5eOL5i65WsAgMDhQfmoUOHwsHBAebm5sJkblFRUTkOxaT4oCWVSnM9/6y+/PJLDBgwAJUrV1Z6sJZfd5aWlrh58yZOnz6N2bNno1KlSrCyshKGXYiPj1c5pp6eHpYsWQInJyd06NBBuAYVK7flBfbq1atj7ty5qFGjBnr27InRo0erHE/+kNuoUSO0adMGRkZGaN26NRo1agQgs/U+AKE1XmxsLG7duoWkpCR06dIFvr6+uHXrVo49QQqib9++ADKDOPIHPXla7Ozs0KpVK6X0V6lSBb1794axsTFcXV3x5ZdfKu2jqFatWhg8eDBq1qyJRo0awcDAAJ6engCg9IAt/663atUKFhYWMDU1hbm5uXAca2trteNfz549G+7u7qhduzYGDRoEILPlUG73GzlXV1d8/fXXqFKlCqZOnSo82MjveREREcIwZX369EH//v1RvXp1TJs2DY0bN87TexARUfGW33L2smXL4Ofnh61bt8LZ2Rm2traoXLmysF5dmWL48OGoV68eWrZsCVtbW6VGHYsWLYK7uzvq16+P5cuX53sM+ryUVwAI5UzF31dN8PPzEyoD58yZgzZt2qBWrVr47bffVJ4T8vO7GhMTIwxj2bt3bzg5OcHExATjxo2DsbEx0tLSch0itEWLFvD29sbYsWNVerPExMRg+vTpQqVxds851atXF8rHY8aMgYODA6ytrWFjYwPgv/Kxvb290HtSHmBQ7M3dsWNHiMViiMVioaz/6NEjPHv2DOXKlcOaNWtw584deHl5KQ2jqgnnz58XylyTJk2ChYUFHBwchEY7ly5dQmJiIsRiMS5evIjz589j4cKFqFq1KqytrYWKVnXXtpyRkZFS7x0LCwu184dMmjQJLVu2RPXq1fG///1PWC4vu33xxRfCs4f8883aUzavPvX5QlFBn69zk5/vT07y+myY0+c0bdo03Lp1C/v370fDhg1hZ2cnNPAB/rvWu3XrJtyn5J+Rn5+f0HNC/hnJn2lSU1Nx48YNxMTEoEWLFjhz5gxu376NCRMm5Pn87O3thd4WL168wN9//612u7w+r/j5+Qm9sGbNmoVWrVqhdu3a+P3331We5fP6HGltbS18ZvK5+HKa96Ewn8GINIlDMBGVIk5OTjA1NUViYiJOnDghVPS6u7urbTkgH3LIzc1NqcW/vb09qlatiqCgIDx79kxlP8VxMRWHKsquhYE61atXV3ptamqKhISEXI/RoUMHGBsbIzk5GWfOnEGtWrWEc+vYsWOeKuUViUQiGBgYwNraGvXr18fkyZPVTlhlY2OjMixTQfOvqDVr1gzNmjVDeno67t27h0uXLmH//v2Ij49HUFAQbty4gebNmwvXS7Vq1ZTyUV335cjISJw8eRLXr1/H48ePhe78QM4Fd8XWej/++KPabYKCgrLtLqv4GURHR6t9YJFKpSpzQ8gpXneKhUbF6y4lJQV+fn747bffcO/ePaUHc3XnljWYJC9AKh5T3kLF2dlZqcKgfv36KseTj7F7/fp1tfkgD7wNGzYMZ86cwYsXL7B8+XIsX74cFhYWaNq0Kfr375/nruLGxsYqc6qo07ZtW9ja2gqffb169XD69GkAmYFBeUtKefpDQ0PVpj8oKAgymUwpH9R953r06IFDhw4hJiYG/v7+qFatmjAEV34eKgEoddvO7nPPiWL6RCIRzM3NkZycLOyvOIaui4uL0r7169cXWkQSEVHJld9yNpD5m3fy5EkEBAQgNDRUqRyhrvV61t9D+VwROjo6qFOnjrC8YsWKsLGxybFlf1Z5Ka8U1OzZs5UqidVRHDZRcRglc3NzVK5cWWnoyfz8rr5+/VoY0nXDhg3YsGGDynsrHjs79vb2mDlzJmbOnIlXr17h33//xaFDh/Do0SNIJBL8/fffuQ5REx8fj0uXLuGXX37Bw4cPlSriFT/7Hj16wM/PD4GBgXj9+jUiIyNVenMbGRlh5syZWLJkCf7991/8+++/EIlEqFWrFr744gsMGTIkz6311X0+Dx48ECo25RTL6T169FA5TkZGBp49ewZXV1ekp6fj1q1b8PHxwd27d5U+30+txAeUy26KFeXy69XQ0BCenp7w8vLCuXPn8N133wkNVczMzLJ9llBHMR8Ve1sryun5QpEmng/VTVCcn+9PbvL6bJiTkJAQHD9+HDdv3sSzZ8+U7iPyz798+fJo1KgR/P39cfbsWYwYMUK4V1arVk24p3Xr1g1HjhxBQECA8B02NjZG48aN0aNHD3Tq1ClfAdfRo0fj4MGDePPmDf7880+1zw15fV7J7l5kamoqTN6tKL/PkXlRmM9gRJrEHhBEpYiOjo5QMN6+fTuAzB/H7IbqyanVjLzgo+4HytDQUOk9C0LxGIrHUVfgUmRsbIwvvvgCQGarIcWWLvLxUvNiyJAhCAoKwpMnT3Dv3j34+Phg1apVaitCAai0EAEKnn9FISYmBvPnz8f48eOF3h16enpo2LAhZs6cidWrVwvbyvNPnubcHkQfP36MLl26YO3atUhKSsKoUaOwbds2oXVHTvISIMqpG7FiwU/dpGSxsbFo0aIFvv32W2FsZkXZXbvyc09MTES/fv2wYMECPHr0CF27dsXq1avRvn37bNOU9VpWd13Izzu36xuAynjQWcnzx8bGBseOHcOKFSvQpUsX2NraIi4uDmfOnMH//vc/4R6gKbq6ukIPpDNnzsDPz09Ii3xIibykPzU1VSlgBUBtb6BGjRqhfPnyADK/6xcuXIBMJoOxsTHatWuXr7Qrjt2s7nPPTW6fseJ1nddjEhFRyZLfcvbKlSsxcuRIHDlyBDVq1MC8efPw008/5fgeWX8PNTled17KK0Ula0Vc1ueJ/Pyu5lbuADLLh9nZsWMHpk6dqjQ2e6VKlTB48GCl4VMU5yNQ5927d+jevTuWLVuGsLAwDBgwABs2bFA7p0CHDh2Ez+Ps2bNCxXnFihWVGqeMGDECJ0+exKRJk1CvXj2IxWIEBgbijz/+QJ8+fXLsdVwQecnLmJgYSCQSjBo1CnPmzMH169fRtm1bLFu2TGV4n0+Rl7KbvFz69u1bPHjwQMjHDh065Ou7U7duXeGZLbtJj6dNm4ahQ4di165dOQ59VdDnQ8XvRE7D0WbdFsjb83hBng2zs3//fvTv3x+7du1CmTJlMHPmTGHorqzkn9Ht27cREREh9PTp0qWLsI2hoSH+/vtvbNiwAb1790b58uWRnJyMS5cuYdq0afjll19yPT9F+vr6wqTO8fHxOHTokMo2eX1eyU/jxoI8R+ZFYT6DEWkSAxBEpYy8G7i8oO3m5pZtoUTeVfLOnTtKBZ0PHz4IhWwnJ6dPSk9hVMbJW+QEBwcLk8iWK1cu2y7wmqCu8FGc88/U1BT//PMPLl26hF27dqkEFRQLvvIWcBUrVgSQ2X05NTVVWL9z506MGjUKv/76KzIyMrBt2zYkJyfDzs4Ohw4dwpQpU9C0aVOliciyI38PAFi3bh2CgoIQFBSEgIAAHD16FA8ePFA7BJacp6enULjauXOnSgF89+7diI6OxtGjR1VapOTF6dOn8fz5cwDA1q1b8f3336Njx455HmM3O/KH14cPHyp9pgEBASrbyvOoQ4cOQv4EBQXhyJEj8PPzE4YZCA0NxZUrV2BqaooVK1bg6tWr8Pb2Rt26dQGgUMb5lLeUi4iIEMaFdXV1VQrcydNfp04dpfSfOHECV65cQVBQkEpAT12BWSQSCS2Wzp8/LzxUtm/fXqmrueK1rK3Kf/nnC6g+uKr7jImIqGTKazk7JSVFGK99+PDhWLNmTZ5arGf9PZT/vkilUjx69EhYHhoamq/eD8WBg4OD8LfiPA5xcXEqlfv5+V1VPO73338vlDsePXqEgwcP4s6dO1izZk226Xrx4gW8vb1x5swZlbH5FT9bdUOkKJY79u3bh4iICOjo6MDLywszZ85Eu3btkJKSorKfqampUoMqeatwxUrZxMREBAQECJOOHzx4ELdu3RJ6EIeFhamdO+FTyMtwIpEIt27dEvLy0qVLOHPmDAIDA9GuXTvcuHFDaOizdOlSLFiwAN27d89zUEtTZbcmTZoIDaB2795d4J6yisP4+vr6Cs8CcqGhofDx8cHNmzexb9++HM8zP8+His+X8gnI5dtmlZ/vjzoFeTbM7nP6888/IZPJ4Onpic2bN2PUqFEoV66c2vft2LEjDAwMIJVKsWLFCrXzNr59+xa+vr5ISUnB4sWL4ePjg0uXLglzHxw4cCDfz2IdOnQQ5o5UfK6Vy+vzSnb3ori4OKG3i1x+niPleZvX67+wnsGINIkBCKJSJutEeNlNjAf81yIhLCwMM2fOxKNHjxAQEIApU6YgLS0NIpEI/fv3L1A65K1O3rx5g+fPn+Pt27cFOo46zZo1E8Z59/LyAvDfJFZFqSjyLzIyEk+fPhUKlvLJs9+/fy+MR6mOnp6ekL6nT59iypQpuH37NkJDQ+Ht7Y3vv/8eQGaLE3mBWz4+ZGxsLH744QcEBQXh6tWrWLduHa5du4YnT55AV1dXeJCKiYnBxYsXERwcjB9++EEoOOfUg8LJyUkYBmnZsmW4du0aQkJCsGDBAvTs2ROurq4IDAzMdv9y5cphxIgRADInf/z6669x9+5dPHv2DOvXr8e6desAZHalHjBgQA45rJ5iq5BTp04hNDQUO3bsgK+vb67nlhP5fAbPnz/HkiVL8OzZMxw6dAh//fWXyradO3cGkDnh2s6dOxEaGoqTJ0+iX79+aNasmTAB4MKFC/HVV1/hm2++wcmTJ/H69WuEh4cLn0NeHwJlMplwTan7p/jg7OjoCDc3NwD/PfzIJz6Tkz88P378GCtXrsSLFy/g6+uLQYMGoXXr1kotDHMjDzZ++PABV69eBaD6UKnYwu3BgwfZtlwrTJaWlsKY1F5eXjh48CCePXuG3377TWliRCIiKtnyWs5OT08Xymn+/v4ICgrCtWvXlCZ1zUuF2hdffCFUgs+fPx+3b9/G7du3MX369AKeQe7kv/85jeOfVUJCQrblCHmFY/PmzYVW/7/88gsuXbqEJ0+eYPbs2SqtcvPzu2pubi6Mgb5p0yacP38eL1++xMqVK9GvXz80aNAgx0lsFVsQy8tUoaGhuHPnDqZNmyYMwSKfAw5Q/5wjLy9JpVIcP34cL168wMqVK4VKyqxlSHk5/c6dO2rnLQgODsbgwYMxb948zJs3D0+ePMG7d+/w/v17YZu89FjIjy+//BJ6enqQyWSYNWsWHj9+jMePH2PixInw9PRE27ZtkZaWpvR5nTt3DiEhITh69CiOHDkiLM+pzKxYdgsMDMT9+/cLFIjQ0dER8uzIkSOQyWTCJN5AZk8C+XX48ePHHI81Y8YM6OnpIT09HaNHj8apU6fw8uVLnD9/HuPGjRMqseXzC2QnP8+HZcqUEfbz8vJCYmIiPnz4oDZglp/vjzoFeTbM7nOSX+sPHz7E/fv3cefOHaVeCor3NjMzM+G7I39ud3FxUZoPZ8OGDRg3bhxmzpyJ3bt349WrV/jw4YPQw0csFhfoOf+7777L9nkor88rzZs3F3qmLVu2DFevXsWjR48wffp0lXzPz3OkPPj08eNH3L9/P9dhuYr6GYyoIDgHBFEpU69ePaHwBGQ/MR6QOQyRr68vrly5gjNnzuDMmTNK66dPn64y7mpe1axZEyEhIXj+/Dk6d+6MmTNnYuzYsQU6VlZisRhdu3ZVGmImvy1dNKGw8+/ff/9FbGwsunXrhkGDBuGnn37C6dOnMXfuXADAoUOHcjz+9OnTERAQgODgYFy4cEHl4UskEmHevHlCa7xevXrhn3/+wY0bN3Ds2DEcO3ZM2NbIyEjomdC+fXucP38eGRkZSpOQy+U0hJJIJMKcOXMwYcIEhISEYNSoUUrru3fvjtq1a+eYN9OmTcP79+9x8uRJtedlZGSElStXChOb50erVq2gr6+PtLQ0rF+/HuvXr1daHxcXB4lEku9hC4YMGYIDBw7gw4cP2LFjB3bs2AEgs5WUPLgkL1gPGTIER48exfPnz/HLL78oFejt7e2FAMysWbNw7949JCQkqK2IyO0BSS4lJSXHcXIXL16sVMDt06ePMGeEoaGhEDCR69ixI/bu3Qt/f3+VsZhNTU2FCcfzwtHREXXr1hVafVpZWalMNK84RvCCBQtgZGSk0oKxKHzzzTcYPnw40tLSMG/ePGG54mdMREQlW17L2ebm5mjcuDH8/f3x8OFDoeJPUdbJn9WpWLEi+vfvj3379uHJkycYNGgQAMDW1laYj0LTDXDkZYIhQ4Zg/vz5edpHXZlJrkKFCrh48SIsLS3xzTffYMmSJYiIiBDKKTo6OqhZsyaePn2qtF9+fldnzpyJgIAARERE4KuvvlJa16RJkxyHbqxfvz7Gjx+PjRs34t27d2rLVPL5teTUPed4eHhg586dkMlk+Pnnn1WOkfXzbtGiBWxsbIQ5B2rVqqU0V5mbmxt69+4NLy8vpZ6gcjVq1FAKimhCuXLlMHbsWKxbtw4+Pj7w8fER1olEIkyZMgX6+vpwd3eHpaUlYmNjcfjwYRw+fFjlWNHR0UoV7IqqVKkifI82btyIjRs34tq1awVKc/fu3YUe8QDQqVMnIWh3584dDB8+HACwevVqdOzYMdvj1KlTB7///jtmzZqF9+/fY9q0aSrbDBw4UO13WVF+ng8dHBzg7OyMhw8f4s6dO2jYsCFkMhkcHR1hZGSk1Agov98fdfL7bJjd59S+fXscOXIEYWFh6Nevn8r7ZL3Wu3fvLsxZAKgOmzxx4kRcuXIF7969w4IFC1SON2bMmAIN+1yzZk0MGjRI7UTUeX1eMTU1xfjx47F8+XK8ffsWo0ePBpA5LLS9vb1Sb5X8PEfWrFkTQGZDsH79+qF169bYvHlzjudTlM9gRAXBHhBEpYyhoaEwMZWenp7acUflxGIxNm7ciJ9++gn16tWDsbGxMOHTxo0bMW7cuAKnY/LkyWjQoAGMjIxga2urMoHzp1KcGM3R0THXSuvCUJj5N3LkSLRs2RImJiawtLSEra1tvo9hYWGBAwcOYPLkyahVqxaMjIygp6cHe3t7dOzYEbt371YqNOrq6mLz5s34+uuvhQJnmTJl0KFDB+zbt08Y2qd3796YO3cuKlWqBAMDA1SuXBnjxo3DhAkTAAC3bt3KcTimVq1aYefOnWjdujXMzc1haGiIGjVqYM6cOXka41NPTw8rVqzAqlWr0KxZM5ibm0NXVxfly5dHnz59cOzYMaHLbX5Vq1YN69atQ926dWFkZAR7e3t06dIFy5cvB5DZSqUgEwpbWVlh9+7daNeuHYyNjWFtbY0xY8bgu+++UzovIHO+kT179mDYsGGoUKGC8Jn17t0be/fuFSberlWrFg4cOIBevXoJ25mZmaFx48ZYt24devbsWaA8yE2nTp1gbGwMILN7c9ZAj46ODjZt2oRJkyahSpUq0NfXh62tLTw9PbF3795sx8rOjuKDXseOHVVa+9WsWRMTJkxA2bJlYWhoiGrVquU6dm5hcHd3x+bNm+Hs7Ax9fX1UrlwZixcvFh528zOGLBERFU/5KWfL52iysrKCmZkZXF1dsXHjRmEolbwOn/PDDz/gq6++QpkyZWBoaIjmzZtj165dwlAaJen3RT6kZ9WqVaGvr4+6detiw4YNQot1Rfn5XZWXiTw9PWFlZSVsP2nSJGzYsCHXysvp06dj3bp1aNWqFaysrKCrqwsLCwu4ubnh+++/x9atW5XeT91zTtOmTfHbb7+hevXqMDAwQIUKFTBgwAAheBIaGipMEgtklrsVh1xSN5fdokWLsHDhQtSrVw8WFhbQ09ODg4MDhg0bhl27dqnM66EJU6dOxeLFi+Hi4gIjIyOYmZnB3d0d69atE4aBsbKywubNm9GoUSMYGxvD1tYW7dq1U6pAzen6trS0xNy5c1GxYkXo6+ujRo0aOfbszomTk5NS2TK7Rml5qcDu2LEjjh8/jj59+qBcuXJC2bpZs2ZYs2aN2sBSVvl9Pvzzzz/h4eEBY2NjWFhYoF+/fvj777/V9m7Jz/dHnfw+G2b3Oc2bNw8DBw6EnZ0djI2NUbt2bSxZskTotZT1s5d/r4DMzyFrxXm5cuWwf/9+DBs2DJUrV4a+vj6MjY1Rv359/PrrrypBxfyYMmWK2nqI/DyvjBs3Dt9//z0cHBygr68PV1dXbN++XRieSd5TJD/PkT179oSnpycsLCxgZmaW7RBWior6GYwov0QyzoZIRJ+hoKAgoWJyypQpn1QwISpsAQEBkEgkKF++PMqXLy88BJ07dw5ff/01gMyuutlNgl6a7dq1C4sWLQKQOb5vYc718ikuXLgAW1tblC9fXhgiDsisPNi1axdsbW2FYaSIiIjy4v3793jy5AnKly8PBwcHofIJyOx9kZCQgLFjx2LmzJlaTGXhKA2/q0uWLMH27dshEolw8eJFlC9fXttJKpF69+6NR48eoVKlSjh37pzSuujoaDRr1gw7duwocAMl+jTp6elo27YtIiMj0bRpU7VD0BZX8fHxuHnzpnAPVqz07969O4KCgtC5c2esXLlSi6kkKh44BBMRfVbCwsKQlpYmtEDR0dHJtSsskbadPXtWGHZpwoQJ6Nu3L6Kjo4VlJiYmSmOhlnbJyclISEjA69evhe7DFStWzHFOG21bu3YtHj9+DJFIhLVr18LJyQkhISHw9vYGkNm1n4iIKD9iY2OFoVbq1q2LxYsXQ09PD6dOnUJCQgKAz/f35XP9XU1ISEBKSgoePXqEffv2AQAaNWrE4EM+RUZGQiKR4OjRo8JQnYo95IHM788vv/wCS0vLAg+LSwX34cMHyGQybN68GZGRkQBQaD20C4tIJMJXX30FmUyGcuXK4Y8//oCFhQWuXbsmDHtVUu9FRJrGAAQRfVZ69OghPHABmd2VK1asqMUUEeWuV69e2Lt3L1JTU1XG5ASAESNGaHwiwZLs5cuXKg8o48ePL/KJ5vNj4MCBmD9/PmQymUqPLJFIpDLfCRERUW5q1qyJBg0a4Pbt23j06JFKo5sqVaqgffv2Wkpd4fpcf1dv3LihdD4ikUgYxpTybuPGjdi5c6fw2tLSUpgjRS4sLAzBwcHYsmWLMJEwFZ2ff/5ZaZ6JypUrKw07VhKYmZmhS5cuOHHiBN69eycMQyZnZWWlMhk0UWnF2gwi+qy4uLjg1q1bsLS0RIcOHTB79mxtJ4koV7Vq1cLWrVuxadMmPHjwAPHx8TAwMEDVqlXRt29flQem0k4+3EJcXBwqVKiAwYMHq53krjgZMGAAdHR0cOjQIQQHByMlJQVmZmZwdnbGmDFj0Lx5c20nkYiIShgdHR2sW7cOf/zxB3x9ffH+/XvIZDKUKVMGLVu2xJQpU2BgYKDtZBaKz/V3tVKlSrCyskJKSgoqV66M8ePHo0WLFtpOVolTs2ZNmJiYQCQSwdnZGbNmzYKNjY3SNnXr1sXx48e1lEKqVasW/Pz8oK+vjwYNGmDu3LnCfAklyaJFi+Dg4IBz587hzZs3kEgksLa2RpMmTTB58mSV646otOIcEEREREREREREREREpHE62k4AERERERERERERERF9fhiAICIiIiIiIiIiIiIijeMcEFoilUqRkZEBHR2dYj1pJhERERGVfDKZDFKpFLq6utDRYRskbWD5n4iIiIiKQnEr+zMAoSUZGRl48OCBtpNBRERERKWIi4tLiZzk8XPA8j8RERERFaXiUvZnAEJL5NEnFxcXiMXiIn1vmUyG+Ph4mJubs/UVFQu8Jqk44fVIxQ2vSdIEiUSCBw8eFIsWUKWVtsr/vIdQccNrkoobXpNUnPB6JE0obmV/BiC0RH4TEYvFWglA6OjoQCwW82ZGxQKvSSpOeD1SccNrkjSJ15D2aKv8z3sIFTe8Jqm44TVJxQmvR9Kk4nINFY8wCBERERERERERERERfVYYgCAiIiIiIiIiIiIiIo1jAIKIiIiIiIiIiIiIiDSOAQgiIiIiIiIiIiIiItI4TkJdQkgkEqSnp2vkWDKZDGlpafj48WOxmYykJNHT0yvyicOJiIiIiIiIiIiIShoGIIo5mUyG9+/fIy4uDjKZTGPHlUqliIqK0tjxShORSAQLCwuULVuWARwiIiIiIiIiIiKibDAAUczFxcUhNjYWdnZ2MDEx0UiFt0wmg0QigVgsZgV6PslkMiQlJSEiIgJGRkawtLTUdpKIiIiIiIiIiIiIiiUGIIoxmUyG8PBwmJubw9bWVqPHZQCi4IyMjJCamorw8HBYWFgwD4mIiIiIiIiIiIjU4CTUxZhEIoFEIoG5ubm2k0JZmJubC58PEREREREREREREaliAKIYy8jIAADo6rKjSnEj/0zknxERERERERERERERKWMAogTgED/FDz8TIiIiIiIiIiIiopwxAEFERERERERERERERBrHsX1IK+bMmYMjR45ku97W1hZXr15Vu+7GjRsYPnw4du7ciSZNmhRWEomIiIiIiIiIiIjoEzAAUQpJpBJcfnkZH5I/oLxZebSq1ApiHXGRp8POzg5r165Vu05PT6+IU0NEREREREREREREmsQARCnjFeiFqd5T8Sb+jbDMwdwBqzuuRu/avYs0Lfr6+nB1dS3S9yQiIiLSBolUAt9XvniX8A7lzMpprQEIERERERVPEqkEV15ewfPw53As44jWlVuXyvLi51Ju/lzOQxMYgChFvAK90PdAX8ggU1oeFh+Gvgf64lD/Q0UehMiLffv2Yfv27Xj37h3q1auHPn36qGxz584d/P7773j06BEsLS0xatQo+Pj4oGzZsliyZAkAIDU1FatXr8bJkycRFRWFqlWrYuLEiejcuXNRnxIRERGVIsWpAQgRERHR56ikV/ayvJjpc8mHz+U8NIUBiBJIIpXg3od7SE5Pztc+E05MUAk+ABCWTTw5ETZGNvm6QRvrGaO+ff0C39QzMjLULheLxRCJRPj777+xcOFCjBgxAq1bt4afnx9++OEHpW2fP3+OkSNHwtnZGStWrEBMTAxWrFiB+Ph4dOnSJfMcZTJ89dVXuH37NqZMmQJHR0ecO3cO06ZNQ1paGnr27Fmg9BMRERHlpKQ2ACEiIqLSoaRX3AMlv7KX5cVMn0s+fC7noUkMQJQwaZI0tNreCv5h/ho/dnhSONr+1Tbf+zWu0Bi+o3yhL9bP135hYWGoW7eu2nWzZ8/G6NGjsW7dOnTu3BnfffcdAKBly5ZITEzEvn37hG03btwIMzMzbNmyBUZGRgCAatWqYeDAgcI2165dg6+vL1auXCn0eGjVqhVSUlLw+++/o2vXrtDV5deBiIiINEcilWCq99RsG4CIIMI33t+gh1OPEvegT0RERCVfSa+4B3Kv7N3SfQs6Ve8EiUwCqUwq/JNIs7zOx/pP2Tfr+gxpBhZeWZhjg+FRx0bh9rvbEEEEGWSQyWRq/5fKpNmuy/f/uWwjlUk18z7ytEuluPr6ao75MOjwIDQq30jtOplMpvZ1UW8jlUkRHB3M8n8WrHEtYUJiQgol+PAp/MP8ERITAidbp3ztZ2dnh/Xr16tdV65cObx48QJRUVFo166d0rpOnTopBSCuX7+O1q1bC8EHAHBzc0OFChWE135+fhCJRGjTpo1SrwsPDw8cP34cwcHBqF27dr7ST0RERJQT31e+Sg/0Wckgw+v41/B95Yu2VdoWXcKIiIgIQOkec//AowMYeGigSkXpm/g36HOgDxa0XYBmFZshQ5qBdEl65v/SdJXXOa1T+1pheZ73UfNa/t7p0nS15yc/r/8d/1+h52Vhi0+Nxy++v2g7GVqXJknD1ddXtZ2MT1Jay/8MQJQwVa2qonGFxsUqCNG4QmNUtaqa7/309fXh4uKS7fpXr14BAKysrJSW29nZKb2Ojo6GjY2Nyv62trbC37GxsZDJZGjQoIHa9woPD2cAgoiIiDTqXcI7jW5HREREmlOcW/+nS9KRnJ6M5PRkJKUnCX8npycjKS0p53UZ6rdV3D4pLQkSmSTHNMy/NL+Izpao9Clt5X8GIEoYfbE+ro2+VqA5IPod7IeI5IhstyljUgYH+h4o0jkgciIPPERFRSktj42NVXpdtmxZREZGquwfFRWFatWqAQDMzMxgbGyMnTt3qn2vypUrayDFRERERP8pZ1ZOo9sRERGRZnzKGO0Z0oy8BQLUVPyre61u2wyp+vkyqfTS09GDWEcMEUQQiURq/9cR6WS7TtP/a/q9YlNicffD3VzzoXH5xrAxtoFIJBKWiZD5t3xZ1tdFuc2HxA+4EHIh1/MobeV/BiBKILGOGA3KqW/Jn5MNXTeg74G+AKD0Iyv/sqzvsh5tqrTRTCI1oEqVKihXrhy8vb2VJon28fFR2q5Ro0bw9fVFamoqDAwMAACPHz/Gmzdv0KhR5thwjRs3xrZt2yCTyVCvXj1h38OHD+PcuXP49ddfC/+EiIiIqFSpV6YedHV0s61EEEEEB3MHtKrUqohTRkREVPpIpBJEJkfibcJbjD8xPsex5gcfHgzXsq5IyUhRCRRkN+QPZdLV0YWejl7m/2I94bXi31nX5em1muVv4t9g5331DU0VfdviW9SxqwOxSAwdkY7wT6yT5bUG1+d1X5lMBqe1Tnib8FbtNSkvL4ZMDfmshweTSCWosroKwuLDcsyHa/+7VqzzIa/nUdrK/wxAlCK9a/fGof6H1HYxXNVxVZF3MUxLS8Pdu3ezXe/k5ISZM2dixowZmDdvHjp27Ii7d+9i7969SttNmDABp06dwpgxYzB69GjEx8dj9erV0NHRESKQbdq0QaNGjTBp0iRMmjQJjo6OuH//PtasWYNWrVrB2tq6ME+ViIiIShmpTIrhR4fnGHwAgFUdVxXrhygiIqLi7GPGR4QnheND4ofM/5M+KP+d9EFYH5kcqbZCUJ1USSpuhN0o5NRrjr5YH8Z6xjDWM4aJnonwt7GeMUz0//+17n+vPyR+wI57O3I97vrO69HEoUmegwVikViptXhhk0gluBh6MdfK3l88finW5a01ndag74G+wiTTcqWpvCjWEWN1x9UlPh8+l/PQNAYgSpnetXuje83uuBx6GR+SP6C8WXm0qtRKKxd+REQEBgwYkO36o0ePomvXrtDR0cG6detw7Ngx1KxZEwsWLMD06dOF7SpXroytW7fit99+w5QpU2BjY4Px48dj/fr1MDExAQDo6Ohg06ZNWL16NTZu3IioqCjY29tj1KhR+Oqrrwr9XImIiKh0+dHnR5wMPim81hHpQCqTCq+11QCEiIhIEyRSCXxf+eJdwjuUMyunsXoFmUyG+NR4IYAgDx4If2cJMMSnxmvgbAqXno6eciAgu0BBdoGDXNYZ6xlDVyd/1XsSqQTnQ87nWnE/1n1ssa4o/Vwqe4tbg2Ft+Vzy4XM5D00SyWSyvIV/SaMkEgnu3r0LV1dXiMXqb4QfP35ESEgIqlatCkNDQ429t0wmg0QigVhctJHpwuLn5wc9PT00bNhQWBYfH4/mzZtj9uzZGD58uMbfs7A+m9JKJpMhLi4OFhYWn8U1SSUbr0cqbnhNljyHHx9G34N9hdcGYgNs7b4ViWmJeBr1FI0qNEK/Ov2K9GE4L2VPKlza+gx4D6HihtdkyZffyZslUgmiUqLy3FMhVZJalKeTraYOTVHJolKOgYLcggrGesbQE+tp+1TUks+DAagfpjuneTCKG3XXZEXziiWuslcileDKyyt4Hv4cjmUc0bpy62IfPCkMhRXgLGraPI/iVvZnDwgq8R49eoQ1a9Zg+vTpqFu3LmJjY7F9+3aYmZmha9eu2k4eERERlSIPwx9ixNERSsvmt56PWra1AAD2JvZwK+dWIh+iiIiIspu8+U38G/Q50Adda3aFhYGFUoAhIjlCqRdgUbA2skYZkzKwN7GHvak9yhiXgb2pPexN7GFjZIOJpyYiIikix9b//47697P+vf6cWmn3rt0bPZx6lPhKa7GOGG2rtIWblVupDtLK86Gk+1zOQxMYgKASb/To0UhLS8PevXvx7t07GBsbo3Hjxli8eDHndiAiIqIiE50SjR77eiApPUlYNtRlKDyre2oxVURERJ8mJT0FjyMe496He5jqPTXHeRROPD1RKGkQi8QoY1ImM6jw/4EEeYAh6zI7Ezvoi/VzPqAIJX7YHk34XCruAVb2EhVnDEBQiaejoyNMLk1ERESkDRKpBIMOD8KLmBfCssYVGmNy48laTBUVRzEpMbA1tRX+1hPrwVTfFBKpBDEfY2BhYAE9sR5S0lOQnJ4MG2MbAEDsx1jo6ujCVN8UUpkU0SnRMDcwh75YHx8zPiIxLRG2xpnHjfsYBx2RDswMzCCTyRCVEgVDE0MY6hmqbCsfP93cwBwAEJkcCVN9UxjqGiI1IxUJaQmwMbKBSCRCQmoCpDIpLAwtVLZNk6QhPjUe1kbW0BHpIDEtERnSDFgaWgIAopKjYKxnDCM9I6RL0hGXGgcrQyuIdcRITEtEuiQdVkZWADKDeYa6hjDWM0aGNAOxH2NhaWgJXR1dJKUlIU2SJmwbkxIDfbE+TPRNhG3leZicnoyPGR9hbWStkofy/Jbnobr8FovEMDMwy1N+i0QimBuYC/ltpm8GA10DlTzMS37L8zBrfivmYW75rZiHWfM7ax7mlN9Z81Axv7Nesznlt2Ie6unoISUjBRnJGbA1Ub1m5dvK8zCnazYv+S2TyfJ0zSakJkAik6i9ZuXbKl6zueV3fq7ZnPK7qO4RZvpm0BPr4UnEE9x6dwuhsaF4EP4Ad9/dxfOY53mevDk/DMQGKGtaFvam9rAytEJZ07KoYFYBtsa2MNE3QTXLaihvXh7GesYw0zcTzjW3e0RSWhL0jfSzzW8LAwv0rt0bu3vvxsxzM/E24a2QpvJm5bGm0xr0cOqByOTIUnGPkMqkcC7jLAQetH2PUJffpe0ekZKeAgtYFLt7RG75nd01y3JE0d8jihsdbSeAiIiIiKik++7Cdzj7/KzwurxZeSxpv6REtiCkwnXu+Tnh7wshF3D/w30AQFJ6ErwCvRCRHAEAeBr1VKkl8aXQS7j97jYA4GPGR3gFeuF94nsAwPPo5zj65Kiw7b+v/oV/mD8AIF2ajn+e/YOwhDAAwKu4V/AK9BKGQ/F77Qe/134AAKlMCq9AL7yKewUACEsIg1egF9Kl6QAA/zB//PvqX+F9jj45iufRzwEA7xPfwyvQCx8zPgIAbr+7jUuhl4RtTzw9gadRTwEAEckR8Ar0EnoL3f9wHxdCLgjbng4+jcCIQACZFQNegV7CA/ejiEc48/yMsO3Z52fxIPwBACAhNQFegV6ITokGADyJfIJTwaeEbS+GXMTd93cBAMnpyZn5nZSZ38HRwTgedFzY9srLKwh4FwAASJOkwSvQC+8S3gEAQmJCcCTwiLDt1ddXhfyWyCTwCvTC6/jXavP7+pvruPb6mrCvV6AXQmNDAQBvE95m5rckM79vvr2JKy+vCNseCzqG5zGZ+R2eFA6vQC+kpKcAAO68uwOfEB+1+R2VEgWvQC8kpCUI+X3+xXlhW+9n3ngU/ghAZoWJV6AXYj/GZuZ3+CN4P/MWtj3/4rxwzSakZeZ3VEoUANVr1ifEB3fe3QGQ2YLeK9AL4UnhmXkYG4JjQceU8vvm25sAgHRJOrwCvYRK4dDYUHgFegnbXnt9DdffXAeges2+jn8Nr0AvSGQSAJnX7NXXV4V9jwQeQUhMCADgXcI7eAV6IU2SBgAIeBeglN/Hg44jODoYABCRlHnNJqcnAwDuvr+LiyEXhW1PBZ/Ck8gnADIrvrwCvZCQmpnfD8IfKP0+nHl+Bo8iMvM7PjUeXoFeiEmJAQAERgTidPBpYdvCvEece3EOPiE+WHl9JXrt64XGWxrDfLE56q6vixFHR+DHSz/i0ONDeBbzLN/Bh7KmZdGqUiu4l3PHwLoD8XPbn/Grx6+Y4D4BF4ZfwLPJz3B68Gns7bMXod+E4saYGxjkPAjTmk7DL+1/wQDnAQCAxg6NUceuDt4mvIVP6H/Xt6buEU62TljssRgXh1/E5o6b8VObn7C79270rt2b9wgt3yOexzwv1feIJ1GZ22rzHqFYjvAK9GI5AiWvHFGccBJqLeEk1CUbJ6HWLE5ER8UJr0cqbnhNFn/7Hu7DoMODhNeGuob4q8dfcLR2VNn2ddxruJVzQ2XLykWZxGI3EV1pJP8MKjtVLtIeEFKpFCEfQlDBtgJ7QJSgloufew+I91HvoWekxx4QRdC6WSqT4u67u7j19hZC4zJ7Ndx7fw8fkj7k8e6Vfz4jfNC2StsSc4+wMrRCXFwcZAYylfzmPYI9IIr6HhGdHI2UpBSUty0PiUzCHhDF4B5REssRMqmsWJX9GYDQEgYgSjYGIDSLlWtUnPB6pOKG12Txdvf9XTTf2hwpGSnCsqXtl6J9tfZqt2cAovTS1mfAewgVN7wmC4dUJs0cNunDAzwIf4D7H+7jQfgDBEcFC62988vRyhEu9i5wKZP5r65dXXj+7YmwhLAcJ28OmRpSonoA8pqk4oTXI2lCcSv7cw4IIiIiIqICiEyORM99PZWCD6NdR2cbfCAiIpJIJZ884W90SjQefPgvyPAg/AEehj9EYlpigdJkY2QDF3sX1CtTTwg41C1TF6b6pirbru60mpM3ExFRvjAAQURERESUTxnSDPQ/2B8v414Ky5o7NMeEhhO0mCoiIirOvAK9MNV7Kt7EvxGWOZg7YHXH1ehdu7fK9qkZqQiMDFTp1aA4aXJ+GIgNUMeujhBkqGdfDy5lXFDWtGyeW1r3rt0bh/ofUnseqzquUnseRERUujEAQURERESUT7POzlKaELOieUX82v5X6Ih0tJgqIiIqrrwCvdD3QF+VoYvC4sPQ90BfrOuyDuXNygvBhgfhDxAUGVTg4ZOqWlYVAgzygEMNmxrQ1fn0aqDetXujh1OPT+7JQUREpQMDEERERERE+bDz3k6surFKeG2sZ4yVnivVDlVBREQkkUow1Xuq2nkT5MsmnpxYoGNbG1kLczS42Gf2aqhrVxdmBmaflObciHXEaFulbaG+BxERfR4YgCAiIiIiyqNbb29h3D/jhNciiLCw3UJUsayivURRkZBKpVi7di0OHjyIhIQENGrUCPPnz0fFihW1nTQiKuZ8X/kqDVdUEPpifdS2ra3Sq6G8WXlOVEtERMUaAxClyatXQGQkIJMBEgkgFgOKBRVbW6BSpSJP1oMHD7Bz507cvHkT0dHRKFOmDJo1a4Zx48YJD3ROTk74+uuvMXny5EJPz40bNzB8+HDs3LkTTZo0KfT3IyIiopLhQ+IH9NrfC6mSVGHZ2AZj0aZyGy2miorKunXrsGfPHixZsgRly5bFsmXLMGbMGPzzzz/Q19fXdvKIqJh6Fv0My68tz9c+VSyrCL0a6tlnTgxdw7oG9MR6hZRKIiKiwsMARGnx6hXg5AR8/AgRsvngDQ2BoKAiDULs3r0bv/76K5o0aYIZM2agTJkyePnyJbZu3YqzZ8/ir7/+Qq1atYosPURERETqpEnS0PdgX6UWrK0rtcaYBmO0mCoqKmlpadi2bRtmzpyJtm3bAgBWrlyJVq1a4ezZs+jatat2E0hExUqaJA3HnhzDptubcP7F+Tzv90enPzC8/nCYG5gXYuqIiIiKFgMQpUVkJPDxY87bfPyYuV0RBSACAgLwyy+/YMiQIfj++++F5U2aNMEXX3yBnj174rvvvoOXl1eRpIeIiIgoO9O8p+HfV/8KrytbVMbCdgs56XQp8eTJEyQlJaFZs2bCMnNzc9SpUwc3b95kAIKIAAAvYl5gc8BmbLu7DeFJ4XneTwQRHMwdMLHhRE7kTEREn50SG4CIjo7G4cOHERgYiGnTppWusVclEuDePSA5Oe/7BAXlbbs7d/J3XGNjoH79zOGc8mnr1q0wMzPD9OnTVdZZW1tjzpw5CAkJQbKa9ISHh2PlypW4du0aYmJiULNmTUycOBHt27cHALx58wbt27fH4sWL0bt3b2G/OXPmwN/fHxcvXhSW7du3D9u3b8e7d+9Qr1499OnTJ9/nQkRERJ+vLbe3YN2tdcJrEz0TrPJcBRN9Ey2miorS+/fvAQDlypVTWl6mTBlhXV5FRkZCR+e/wJWBgQHMzMwgkUgQExOjsr2trS0AIDY2FhkZGUrrzMzMYGBggI8fPyIxMVFpnZ6eHiwsLCCVShEZGYm0tDSlceKtra2ho6OD+Ph4pKWlKe1rYmICIyMjpKamIiEhQWmdrq4uLC0thXPJytLSErq6ukhMTMTHLA2gjIyMYGJigvT0dMTFxSmt09HRgbW1NYDMZz2pVKq03sLCAnp6ekhKSkJKSorSOkNDQ5iamiIjIwOxsbEqacpLHqakpCApKUlpnb6+PszNzSGVShEdHa1yXBsbG4hEIsTFxSE9PV1pnampKQwNDQuUh1ZWVhCLxUhISEBqaqrSOmNjYxgbGyMtLQ3x8fFK68RiMaysrABoNg9FIhFsbGwAADExMZBIJErrzc3Noa+vj+TkZJVnN3V5KJPJhOvO1tY21zzM6fqWyWSIiopSycOcru+85mFUVBRkMuVJo9Vd3+mSdHg/98buwN24GHYRkADI2vZPBFQpXwWhsaFACgDljwYyAxlWeq7Ex5SPKnlY2PeIguTh53aPsLGxgUwmU3t98x6RqSjvEYrykofF/R4hl5/rOyYmRul3O6c85D0iE8sR/5Ffo8VJiQxAeHt7Y86cOTA3N0daWhq8vb0xduxYTJs2DQAwb948HDx4UGmfChUqKFU6Z3X69Gn88ccfePPmDapVq4Zvv/1WaOEkr8wGAC8vL9StW1dl/06dOuHFixeFP29AWhrQqhXg7184xx9TgGEEGjcGfH2BfIx9K5PJ8O+//8LDwwNGRkZqt+ncubPa5ZGRkejbty8MDAwwbdo0WFlZwcvLC1999RV+++03dO/ePc/p+Pvvv7Fw4UKMGDECrVu3hp+fH3744Yc8709ERESft+tvruOrU18Jr3VEOvi1/a+oaFGKGr+Q8KCada4HAwMDlQfg3Bw4cECpcqZatWpo3bo14uPj1fb8HTlyJADg1KlTiIiIUFrXqlUrODo6IjAwEDdu3FBaV758eXz55ZdITU3F4cOHoa+vrxSAGDhwIAwNDXHhwgW8fv1aad+GDRvC2dkZoaGhuHTpktI6GxsbdOvWDQCwd+9elQf8nj17wtLSElevXkVwcLDSOhcXF7i7u+Pdu3c4c+aM0jpjY2P0798fAHD48GGVChZPT0+UK1cOAQEBePDggdK6GjVqoEWLFoiNjcXRo0eV1uno6GD48OEAgBMnTqhUorRt2xZVqlTBw4cPcevWLaV1FStWRPv27fHx40fs27cPWQ0ePBj6+vo4e/Ys3r59q7SuSZMmqF27Np4/fw5fX1+ldXZ2dujSpQuAzCFps+rduzfMzc1x5coVvHjxQmmdq6srXF1dERYWhnPnzimtMzMzExpTHTx4UKXipnPnzihTpgz8/f3x+PFjpXVOTk5o1qwZoqKi8M8//yit09PTw5AhQwAAx48fV6mc8fDwQKVKlfDgwQMEBAQoratSpQratm2LpKQk4RldJpMhLS0N+vr6GD58OMRiMU6fPo0PHz4o7du8eXPUrFkTT58+xbVr15TW2dvbo1OnTpBIJGrzsF+/fjAxMcGlS5cQGhqqtM7d3R0uLi549eqVSh2BpaUlevbsCQDYv3+/SoVQt27dYGNjAz8/P1y7ew1+b/3g/9YfCWkJgD2AisgMMDzJ3F5frA83eze0qdoGc4bPwYnnJzB11VTExP1XSWhpaImfRv6E9uXb4+bNm7h7967Sexb2PSItLQ179uxROW5pukcMGzYMycnJuHDhgkolIe8RmYryHqFo2LBhJfYeEZSlIXCdOnXQuHFjhIeH49SpU0rrDA0NMXDgQADAkSNHEBUVpfS73aFDB1SoUAF3797lPYLliDzdI0xNTVWWa5NIljVcV8ylpKSgefPmGD58OJo3bw5/f384Ojpi2rRp2L9/P1xdXdGvXz80b94cQ4cOFfYTi8VCJCyr69evY8yYMZg9ezZatGiBQ4cO4e+//8bRo0fh6OgoBCD09PQwevRolRb7T548Qc+ePSGTyfIcgJBIJLh79y5cXV0hzqb3wMePHxESEoKqVavC0NAwc2FQEFAc50R48iRzjok8io6ORrNmzTB27FjMnDkz1+0VJ6FetmwZ/vrrL5w5cwYVKlQQthk5ciSePXuGK1eu4O3bt7n2gJDJZGjRogWaNGmClStXCtv8+OOP2LdvX46fpdrPhgpMJpMhLi4OFhYWSg/GRNrA65GKG16T2vMu4R3cN7njXeI7YdlXDb/CKLdRBT7m67jXcCvnhsqWlTWRxDzLS9mTsnfmzBlMmTIF9+7dUyr7TZ06FWlpaVi/fn2ux5B/Bg4ODkXeAyIkJATm5ubsAVGCWi5+zq2b5T0gzM3NS1wPCBMzE5x+cRrrr63HhacXlN9UD4A+AAlQx7wOhtcbjr61+8Lc0Fzp+o6MisTVl1fxIekD7E3s0dShKawsrdi6GdrtAREXFweZTMYeEMXgHqGoNPeAUPzdZg+ITCxHZMprD4h79+4Vm7J/iesB8fz5cyQnJ6N79+5CJnfq1AlRUVGwtLSETCbDs2fPMG7cONjZ2eXpmJs3b8YXX3whRLS+/fZb3LlzB3/99RcWLFggbNesWTN4e3urBCBOnTqFhg0b4ubNmxo6yxxUrZrZ46CwekAUROPGmenKB/nFn/WHKS/8/f3h5uamFHwAgO7du2Pu3Ll48eJFnoICL168QFRUFNq1a6e0vFOnTmojk0RERFR6pGakos+BPkrBB48qHhjpOlJ7iSKtkQ+9FB4ejkoK86WFh4fDKR+NcIDMh1h1D4K6uro5Pr/k1J3eyMgo217FOjo6sLW1zTaIaWFhke1xDQ0NcyxX55ReMzMzmJmZqV2nr6+f477yiix1TE1Ns23Vp6enV+A8lFc4qSMWi3M8rrwSQJ1PyUNz8+wnIjYwMNBKHmbXqA/IrHAyMVE/NJ1iHspkMujr6ytdkznlYU7Xt0gkyjG9OV3fueWhvMIJAEJjQ7Hl9hZsu7Ptv9+FLKdqpGuEgc4DMd59PBpXaJxtowE7Wzv0tO2pdl1OeVhY94hPycPP5R4hk8kgEolgaWmZ7efGe0SmorhHqFPc7xFZfcr1bW1tDbFYrPZ3m/eITCxH/Ce74xakvrUwlbgAhLyFxPXr11G9enUAmV+GYcOGAQBevnyJ5ORkVKtWLU/Hk0qluH37NubMmaO0vEmTJjh79qzSsk6dOmHu3LkIDAxE7dq1heWnT5/GqFGjChSAkMlkKhFTxXUq2+jpAVevFmgOCNHYsbmnZ/PmfPVkUJoDIh+daczNzWFiYoK3b99me/7JyclIT08XbmbyfIiLi4ODg4PKfvKbf1xcHAwMDJT2Ec7v/1/LZDIhqikPXMkpFozz9dlQgSl+LkTaxuuRihtek0VPJpPhq1Nfwe+Nn7CsmlU1/NTmJ2F9gY8N7XyevH4+Ta1atWBqaoobN24IAYj4+Hg8fvxYqdc1EX0+MqQZOPH0BDYGbMSZZ2cgg/r7qEsZF4x3H48h9YbA0tCyaBNJRERUApS4AETZsmUxatQoLFq0CLVr14aDgwNev34tTEL99OlTAMCuXbtw5coV6OjooHXr1pg2bZrayFl8fDySk5NRtmxZpeXqJpSrUKEC6tWrB29vbyEAcf/+fcTHx6NFixYFOp/4+HilLtiK0tLSIJVKIZFIVCNX9evn740MDPL0YUvq1QMaNMjfsYHMibHzqUWLFrhx4waSk5OFgIGi/fv3Y9myZdi/fz8ACN0hzc3NERERoZIn8vEA5V3EACAjI0NpO3l3KIlEIgQ2sh5L3rVMnvfqT1cCqVSqtssj5Z9MJhO6EXJ4EdI2Xo9U3PCaLHrb7m/D1jtbhdemeqb4pcUvkKRKkJiamMOeuUtKSkJ8QjziRPmbN+BTZe2GTvmjr6+PoUOH4vfff4e1tTUqVKiAZcuWoWzZsvjyyy+1nTwi0qCXsS+x9c5WbL2zFW8T3qrdxlDXEAPqDsB49/Fo6tCUv89EREQ5KHEBCCBziCQPDw/s2LEDFy9exJkzZ9CtWzcsXboUT58+hY6ODsqUKYMNGzbg1atX+O233xAcHIy//vpLpbJfPp6Yugnl1FUsd+rUCfv37xcmvD59+jQ8PT0LPJ6Wubl5jnNAREVFQSwWf/p4Xfb2kBkaQpRl/DRFMkNDiO3tM3szFIHRo0fj3Llz+OOPP/Dtt98qrYuIiMCOHTvg6OgIFxcXAJmVLmKxGI0bN8bOnTvx/v17pWGYTpw4ATs7O1StWlUYHy08PFzIu/T0dDx8+FA4TrVq1VCuXDmcPXtWaZ6IK1euAMjsrp5dvovFYujo6MDMzIxzQGiAPGDE8c2pOOD1SMUNr8mi5fvSF99e/q9coiPSwZIvlqB62eoaOb6J1ATmZuY5dlcvDMWtG3ZJNGXKFGRkZGDevHn4+PEjGjVqhK1bt0JPT0/bSSOiT5QhzcCp4FPYGLARp4NPZ9vboa5dXYx3H4+h9YbCyij7oTiIiIjoPyUyAAEAjRo1glQqhZOTE2rVqoWZM2eifv36mDhxIgYPHiyMy1WzZk3Y2dmhf//+ePDgAepn6Tkgb3mfdcKU1NRUteOfdezYEb/99huePHkCJycnnD59GkuXLi3weYhEomwrE+TLc9omzypXzpzAOjJS6EkgFouVjiuytQUUxrQtbG5ubpg6dSpWrVqFFy9eoGfPnrCyskJwcDC2bt2K1NRUrF69WiUfRo0ahePHj2PUqFH4+uuvYWlpiaNHj+L69ev49ddfIRaLYWlpCTc3N/z999+oUqUKLCwssHPnTnz8+BHGxsbCsWbOnIkZM2bghx9+QMeOHXH37l3s3btX6f3U0ehnQwD+y0vmJxUHvB6puOE1WTTexL9Bv0P9kCH9b3K5KY2noKlDU429hwja+Sx57Xw6sViMWbNmYdasWdpOChFpyOu419hyewu23tmKsIQwtdsY6hqif93+GO8+Hs0cmvF+SkRElE8lLgDx4cMHBAQEoHPnzgAyH6a+/PJLtG7dGn5+fhg2bJjKpCA1atQAALx//14lAGFpaQljY2OEh4crLQ8PD4e9vb3K+5cvXx6urq7w9vZGcnIyJBIJGjVqhLdv1XfNLFYqVcr8J5NlDpkkFgNaLjxNnDgRderUwe7du/Hrr78iLi4O5cqVQ9u2bTFhwgRhwj9FdnZ22Lt3L5YvX45FixYhPT0dtWrVwrp169C+fXthuyVLlmDhwoWYN28eTE1N0bdvX7i7u+PgwYPCNl27doWOjg7WrVuHY8eOoWbNmliwYIHKRONERET0efuY8RG99vdCeNJ/ZUJPR08McRmixVQREZGmSaQSnAo+hU23N+FU8ClIZeqHqKttWxvj3cdjWP1hsDbKfmJdIiIiylmJC0D4+/tj5syZSpNAA0BkZCSqVauG2bNnIzw8HDt27BDWPXjwAACESasViUQiNGjQAP7+/ujXr5+w/MaNG2jYsKHaNHTs2BH79+9HUlISOnbsmO0cDpQ3bdq0QZs2bXLcJigoSOl1xYoVsWrVqhz3qVKlCrZu3aqyfOLEiUqvO3fuLAS05Lp06ZLjsYmIiOjzIZPJMOHEBNx6e0tYVtO6Jn5o/QNbuhIRfSbexL/B1ttbseXOFryJf6N2GwOxAfrV7Yfx7uPRomIL/gYQERFpQIkLQHh4eMDOzg5z5sxBr169EBsbi1WrVuHevXuYPXs2YmJiMGnSJKxduxbdu3dHSEgIFixYgK5du8LR0REAkJCQgPT0dFhbZ7ZiGDVqFMaNG4c6deqgdevWOHz4MAIDA/HLL7+oTUOnTp2wZMkShIeHq63gJiIiIqKS4w//P/DXvb+E1xYGFljhuQKGupzniYioJJNIJfB+5o2NARtxMvhktr0datnWwnj38Rhefzh7OxAREWlYiQtAmJiYYNu2bVi0aBEWLVoEAHB0dMTatWvRoEEDAMCqVauwadMmbN68GWZmZujWrRu++eYb4Ri//PIL/P39cfHiRQBAy5Yt8euvv2LdunVYuXIlqlevjg0bNggBi6zs7e3RoEEDvH//Hq6uroV6vkRERERUeHxCfDD9zH9DL4pFYvz2xW8oa1pWi6kiIqJPERYfhq13tmLL7S14Hf9a7TYGYgP0rdMX49zHoVWlVuztQEREVEhKXAACyJxYeufOnbh+/Tpu3ryJyZMnK63v1KkTOnXqlO3+S5YsUVnWs2dP9OzZU+32Dg4OKkMA7dmzJ9dtiIiIiKj4Co0NRb+D/SCRSYRl05pOg3t5dy2mioiICkIileDs87PYGLARJ56eULq3K3KyccI493EYUX8EbIxtijiVREREpU+JDEDIOTg4sJUCEREREeVbcnoyeu3vhaiUKGFZlxpdMKDuAC2mioiI8uttwltsu7MNW25vwcu4l2q30Rfro0/tPhjvPh6tK7dmPQIREVERKvEBCAcHB20ng4iIiIhKEJlMhjHHx+Du+7vCstq2tfF9q+9ZKUVEVAJIZVKht8M/Qf9k29uhpk1NjGswDiNcR8DW2LaIU0lERERACQ9AlBYymUzbSaAs+JkQERGVXMv9lmPvw73CaytDK6z4cgX0xfpaTBUREeXmXcI7bL+7HZtvb0ZobKjabfR09NCnTmZvhzaV2zCwTEREpGUMQBRjenp6AIDk5GQYGRlpOTWkKDk5GcB/nxERERGVDGefn8W3578VXuvq6OL3Dr/DzsROi6kiIqLsSGVSnH9xHhsDNuJ40HFkSDPUblfdujrGNRiHka4jeU8nIiIqRhiAKMbEYjEsLS0RHh4OADA2NtZI6w2ZTAaJRAKxWMzWIPkkk8mQnJyM8PBwWFpaQiwWaztJRERElEfPo59j4KGBkMqkwrJZzWehftn6WkwVERGp8z7xPbbfyeztEBIbonYbPR099KrdC+Pdx6NtlbbQEekUcSqJiIgoNwxAFHNly5YFACEIoSlSqRQ6OiycFZSlpaXw2RAREVHxl5iWiJ77eyLmY4ywrGetnuhTu48WU0VERIqkMikuvLiATbc34eiTo9n2dnC0csQ498zeDmVMyhRxKomIiCg/GIAo5kQiEcqVK4cyZcogPT1dI8eUyWRISEiAmZkZe0AUgJ6eHns+EBERlSAymQwjj47Ew/CHwjLnMs74tvm3OexFRESaJpFKcOXlFTwPfw7HMo5oXbk1xDpifEj8gB13d2Dz7c14HvNc7b66OrroVasXxrmPg0dVD/Z2ICIiKiEYgCghxGKxxiq9ZTIZUlNTYWhoyAAEERERffYW/7sYhwMPC69tjGywvMNy6Ik5lxMRUVHxCvTCVO+peBP/Rlhma2yLGtY1cOvtLaRL1Te4q2ZVDWMbjMUo11GwN7UvquQSERGRhjAAQURERESfrZNPT2LexXnCaz0dPSz/cjlsjG20mCoiotLFK9ALfQ/0hQwypeWRyZGITI5U2V5XRxc9nHpgvPt4tK/Wnr0diIiISjAGIIiIiIjosxQUGYTBXoOVKrzmtpwL5zLOWkwVEVHpIpFKMNV7qkrwQZ0qllUwrsE4jHIbhbKmnHOPiIjoc8AABBERERF9duJT49Fzf0/Ep8YLy/rV6YfuTt21mCoiotLH95Wv0rBL2Vn6xVLMbD6TvR2IiIg+M/xlJyIiIqLPilQmxbAjw/Ak8omwzLWsK2Y0m6HFVBERlU4vY1/mabuK5hUZfCAiIvoM8dediIiIiD4rCy4vwPGg48LrMiZlsOyLZdDVYedfIqKiFJUchWXXluVp23Jm5Qo5NURERKQNDEAQERER0Wfj6JOj+Pnyz8JrfbE+VnRYASsjKy2mioio9AmJCUGLbS3wKOJRjtuJIEJF84poValVEaWMiIiIihKbgRERERHRZ+FxxGMMOzJMadm8VvNQy66WllJERFQ6BbwNQJc9XfAh6UOO24kgAgCs6rgKYh1xUSSNiIiIihh7QBARERFRiRf7MRY99vVAYlqisGyw82B0rtFZi6kiIip9TgefRpsdbZSCD1Utq2JNxzVwMHdQ2tbB3AGH+h9C79q9izqZREREVETYA4KIiIiISjSJVILBhwfjWfQzYVnDcg0xtclULaaKiKj02Xp7K8afGA+JTCIscy/njpODT8Le1B6TGk3ClZdX8Dz8ORzLOKJ15dbs+UBERPSZYwCCiIiIiEq0H3x+wOlnp4XX5UzLYekXS1mpRURURGQyGX6+/LPSHDwA0LlGZ+zvux+m+qYAALGOGG2rtIWblRssLCwgEom0kVwiIiIqQgxAEBEREVGJdeDRASz+d7Hw2kBsgJWeK2FhaKHFVBERlR7pknRMODEB2+5uU1o+xm0M1nddD10dVjsQERGVZiwJEBEREVGJdP/DfYw6Nkpp2Y9tfkR16+paShERUemSmJaIfgf7wfuZt9Lyn9v+jB9a/8AeDkRERMQABBERERGVPFHJUei5ryeS05OFZcPrDceXjl9qMVVERKXH+8T36LKnC26/uy0sE4vE2NxtM0a5jcphTyIiIipNGIAgIiIiohIlQ5qBgYcHIiQ2RFjWtEJTfNXoKy2mioio9AiKDELH3R0RGhsqLDPVN8WhfofgWd1TewkjIiKiYocBCCIiIiIqUeacn4PzL84LryuYVcDi9os56TQRURG49voauu3thuiUaGFZWdOyODn4JBqUa6DFlBEREVFxxAAEEREREZUYu+/vxnK/5cJrI10jrPJcBTMDMy2mioiodDgSeASDvQbjY8ZHYZmTjRO8h3qjimUV7SWMiIiIii0GIIiIiIioWJNIJfB95Ytrr6/hp0s/Ka1b0G4BqlpV1U7CiIhKkbX+azHl9BTIIBOWtajYAscHHYe1kbUWU0ZERETFGQMQRERERFRseQV6Yar3VLyJf6Oy7n9u/0O7Ku20kCoiotJDKpNizvk5WHZtmdLyPrX7YFevXTDSM9JSyoiIiKgkYACCiIiIiIolr0Av9D3QV6m1raKa1jWLOEVERKVLakYqRh4biX0P9yktn9pkKpZ/uZxz7xAREVGudLSdACIiIiKirCRSCaZ6T802+AAAK66vgEQqKcJUERGVHrEfY9Fxd0eV4MPyL5djVcdVDD4QERFRnjAAQURERETFzomnJ9QOu6ToQ9IH3Hl/p4hSRERUeryOe42W21riUuglYZm+WB/7+uzD9GbTtZcwIiIiKnE4BBMRERERFRtpkjSsu7kO8y7Oy9P2kcmRhZwiIqLS5f6H++i8uzPCEsKEZZaGljg64CjaVGmjxZQRERFRScQABBERERFpnUwmw7GgY5h1bhaeRT/L8362xraFmCoiotLlYshF9NrfC/Gp8cKyiuYVcXrIadQtU1eLKSMiIqKSigEIIiIiItKqO+/uYPrZ6UpDfeSFvYk93Mq6FU6iiIhKmd33d2PUsVFIl6YLy+rZ18PpIadR3qy8FlNGREREJRnngCAiIiIirXib8Bajj42G+yZ3leCDmb4ZutfsnuP+M5rN4CSoRESfSCaTYcm/SzD0yFCl4MMX1b6A7yhfBh+IiIjok7AHBBEREREVqeT0ZCy/thxLry5FUnqS0jpdHV30rd0X49zHwdzAHC0rtcTvfr8jPClc2MbexB4zms2AR1WPok46EdFnRSKVYMrpKVh3a53S8mH1hmFL9y3QF+trKWVERET0uWAAgoiIiIiKhFQmxe77uzH3wlylyU3lWldqjWlNp6GiRUVhmUdVD7Sp3AZ33t9BZHIkbI1t4VbWjT0fiIg+UXJ6MgYfHoxjQceUln/X8jss8lgEkUikpZQRERHR54QBCCIiIiIqdL4vfTH97HTcentLZV0N6xqY0WwGGpZvqHZfsY4423VERJR/kcmR6La3G66/uS4s0xHp4M/Of2JCwwlaTBkRERF9bhiAICIiIqJC8yLmBWafm43DgYdV1tkY2eDrRl+jS80u0BFxajIioqLwPPo5Ou3uhODoYGGZka4R9vfdj25O3bSYMiKiUurVKyAyMvNvmQzixETA1BSQ90SztQUqVdJe+oqKYj6oU1Ly4XM5Dw1iAIKIiIiINC7uYxwWXVmENf5rkCZJU1pnIDbAsHrDMKL+CBjpGWkphUREpc/NsJvosqcLIpIjhGW2xrY4MegEmjg00WLKiIoYK3w/n0rSkn4er14BTk7Ax48AABEAs6zbGBoCQUHF+zw+VZZ8UKsk5MPnch4axgAEEREREWlMhjQDmwI24cdLPyIyWfVhsKNjR0xpMgVlTMpoIXVERKXXyacn0f9QfySnJwvLHK0c4T3UG9Wtq2sxZVSilPTKXoAVvsDnU0n6OZxHZGTO6Qcy10dGFt9z0ITPJR8+l/PQMAYgiIiIiEgjTgefxoyzMxAYGaiyrp59PcxqNgu17WprIWVERKXb5oDNmHByAqQyqbCscYXGODHoBOxM7LSYMipRPofKXoAVhEDe8+DtW6BMGUAmU/8PKNg6Te376FHezuPqVSAq6r9lisfIbllhrFO3LCgo5/TL3bgBREcrL1M8bkleBgDPnqlfnpWPT+a9SJ3sjp2d/G6fl31evMj/MUsBBiCIiIiI6JM8DH+ImWdn4szzMyrrypmWwzdNv4FHFQ+I5MMaEBFRkZDJZPjx0o9YeGWh0vJuNbthb5+9MNE30VLKSqHPoedAYVbcy2SAVApkZGT+S0//7++sr3Nal5dtQ0PzlqblyzM/F6lU+Z88rQX99yn7a+q9MzLylgfNmuXvcyyuBg/Wdgo+3aRJ2k5B8TBzprZTQAXAAAQRERERFUh4Ujjm+8zH5tublVrVAoCJngn+5/Y/DHQeCH2xvpZSSERUeqVL0jH2n7H4695fSsvHu4/H2s5roavD6oAiU1x6DshkmWn4+BFISfnvf8W/s/s/JSXvFfcjRwIGBvkPFBQ3e/ZoOwVERJ8FljiIiIiIKF8+ZnzE6uur8YvvL0hIS1BapyPSQa9avTCx4URYGlpqJ4FERKVcQmoC+h7si7PPzyot/9XjV8xpOYc90opaXnsO+PoCVarkLyiQn21SU4vkdPHgQdG8DxERlQgMQBARERFRnshkMhx8fBDfnv8WobGhKuubOjTFzGYzUcWySpGnjYiIMr1LeIfOezrj7vu7wjJdHV1s674Nw+oP017CPlcyGZCYmBlkiIr673/Fv4OD83asoUMLN62UP5aWmT05dHQy/4lE//1dkH+fsr+m3/vDB2DTptzzYNo0wMEhc//s/gEFW6eJfV+8yNuQPGvWANWr/7ef/NiK/6tbVhjrsi4LCgJGjcr9HP76C6itZi41dQHlkrjs8WOgf3/V5VkdOgTUqZP9+vwG2AsSkM9pn0ePgN6983/MzxwDEERERESUK/8wf0w7Mw3XXl9TWVfVsipmNJ2BphWbaiFlRDl79+4dli1bhhs3biAtLQ316tXDnDlzUKNGDWGb06dP448//sCbN29QrVo1fPvtt2imMO51TEwMFi1ahCtXrkAkEqFLly6YPXs2jIyMtHFKRNkKjAhEx90d8Sruvwk6zfTNcLj/YXRw7KDFlJUQUikQF6ccPFAXUMj6f3EcPkjT9PQAfX0gKSn3bVu1ypw7QVc385+e3n9/5/ZaU9vmtO7BA6B589zP48IFoEGDT8+74uj27bwFIIYOLd55cPt23rZr0aL4noeBQd62c3YuvuegCXntoVW1qvpATHGRmKjtFBRLDEAQERERUbZexb3C3AtzseeB6jjIlgaWmNhwInrW+j/27js8inLt4/h3Nr1DCISEJoQOIr0piIBKEaXJ0XNExf4qqIiACqIooggHUbAjR8SGImBDiiLYgNAUlQDSQSEQIAkhfXffP4ZssimQQJJJ+X2uay/2mWfKvbtDspl7nvsZiIfNw4LoRM4tPT2de+65hypVqvDGG2/g6+vL7Nmzue222/jqq68IDQ1l/fr1jB07lnHjxnH55ZezaNEi7rnnHpYuXUpUVBQADz74ICkpKbz77rskJiYyYcIEkpOTmTZtmsWvUCTbjwd+5IaPb+BU6inXssigSJb9exmX1bzMwshwn4DZ6cQjKQkCA7PvIi2JCZjtdjh58vzJg9zPHY7z79tKXl7mfBF+fnn/zW9Zcazj6wseHubF3nbtzh/jrFll+0JpYS/4ipSGsDDz/9j55ogJCyu9mKxQUd6HivI6ipkSECIiIiKSx+m000z7eRr/XfdfUjPdv0B72by4ueXN3NHmDgK9Ay2KUOT8Nm3axK5du/jhhx8IDw8HYPr06XTq1InVq1czdOhQ3n77bXr37s2tt94KwPjx49m6dSvz58/nmWeeYevWrURHR7Ns2TJXQuKZZ57hrrvu4pFHHnHtV8RKi7Yv4pbFt5Bmz76DtHn15nzzn2+oG1KCkxoXRq4JmA0gKPc655uAOSOj8KMSsp7Hx5vlkazk5QXVqoG/v1kq5nxmz4ZLLy04KeDjY97BLxdHFwgrzntQEV5H3brmz7+zSVqn00lSUhKBgYHZ8/WURJK2rMn1PuSrPLwPFeV1FDP95hIRERERF7vDzru/vsvE7ydyNOlonv5e9XvxcKeHiQiKsCA6kaJp1KgRb731lluSwGazAZCYmIjD4WDLli089thjbtt16tSJlSvNyXs3bdpE9erVXckHgI4dO2IYBps3b6Zfv36l8EpECjZr/SweWfEITrIvtnev152l/1pKVb+qFkZ2VmEnYH7+efMCe34JhcTE0on1XLIuYlarlv1vzuf5LQsKMkd5FHbkQNeuZXvkQEW42Au64AsV5yJpRXodWTE6ndgTEiAk5MLmJyjPcr4P5VlFeR3FSAkIEREREQFg9b7VPLLiEX6L/S1PX7OwZoztOpZW4a0siEzkwlSvXp0rr7zSbdmCBQtITU3l8ssvJzExkeTkZGrWrOm2To0aNTh61EzAxcbGEhHhnnDz9vamSpUqHDlypMgxOZ1OnKV4V3bW8UrzmFI6HE4Hj658lFkbZrktH9Z8GPMHzsfH08fazz011bwwuGwZhbqE9sYbJR2RizMwMG/yIDT03AkFf/8LPJgTnM5CvQfOs+uWWXXqwI4d57/YW6dO2X4dYMZYpw5gvu+ZCQk4c1/wLeuv4WLleA8KVB7eg4ryOs7S720pDmXt/FECQkRERKSS2xm3k7GrxvLlri/z9NXwr8GDnR7k2qhrs+8KFCkjDh8+TK9evQrsX7duHaGhoa72qlWr+O9//8vtt99OkyZNXEkGb29vt+18fHxIOzsZYkpKSp7+3OsURWJiomsURmlwOp0kJycD6P9wBZKamcr9K+9nyV9L3JaPbDuSyVdMJvVMKqmcZ9RBsQWTiu2vv/DYuROPHTuw7dhh/rtvH0YpzKfgCAnBGRrq9nBUq4azalWzXa2auSxHf5HnAMjIMCenvkCGtzfBPj4Y5/iZ4fTxIdHbG+dFHKdUhISYj3Mp668hF/2clLJE56MUB0cZm89ICQgRERGRSupE8gmeWfsMr216jUxHplufn6cft7e+nf9c+h98PX0tilDk3MLDw1m2bFmB/SE5LpJ99NFHPPvss1x//fWMGzcOMJMIYE5WnVNaWhp+fn4A+Pr65unPWsf/Au6IDg4OxsOj9CZtz7oDLiQkRBcyyjG7w86PB3/kSNIRArwCmPHLDH469JOr38Bg5rUzeajTQyUXRFqaOaLhzz/NR0yM+e/u3cWSaHBC3pEH5ytzFBqK4elZuBEWVgoJgZ07cZ5n5ECwSnZYQj8npSzR+SjFwW63Wx2CGyUgRERERCqZdHs6r218jWfWPsOp1FNufTbDRv9G/RnZYSTV/KtZFKFI4Xh5ebnNzVCQ6dOnM3fuXEaMGMH48eNdf9BXqVIFf39/jh075rb+sWPHXPNG1KxZk2+//datPz09nfj4eGrUqFHkmA3DKPULClnH1IWM8mlxzGIeWv4QhxMP59vv4+HDB4M/YEjzIcVzwLQ02LUrO9Hw55+wfTvs3g0leEHDiI6GDh1KbP+Wq1fPfEiZpJ+TUpbofJSLVdbOHSUgRERERCoJp9PJ5zs/Z+yqsew+uTtPf7uIdjza5VEaVWtkQXQiJSMr+TB+/HjuuOMOtz7DMGjbti3R0dHceOONruUbNmygffv2AHTo0IEZM2Zw4MAB6p29eBgdHQ1Au8JMKityERbHLGboJ0PdJpjOKcArgOW3LOeKulcUfec5Ew3bt2cnGy4m0eDhAY0aQYsW5qN5c7Om/r/+VbhtRUREpMJRAkJERESkEth6ZCuPrHyENfvX5OmrE1yHRzo/whV1ryhzd8uIXIwNGzYwd+5chg8fzoABAzh+/Lirz9/fn4CAAEaMGME999xD8+bN6d69O5999hkxMTE899xzAFx22WW0bduW0aNH8/TTT5OcnMykSZMYOHCga5SESEmwO+xM++gBWscWPJGkrbo/XWp3OfeO0tPzH9Hw118Xn2ho3jw72dCihbks9/wKW7Zc2DFERESkQlACQkRERKQC++f0P0xYPYH5v87PcwdtkHcQ97S7hxub34inTV8LpeL56quvAFiwYAELFixw6xs5ciSjRo3iiiuuYOrUqbz22mu89NJLNGzYkDfeeMNV2skwDObMmcPkyZO57bbb8PHxoU+fPjz++OOl/nqkcolet4g1zx/FL7PgdVI8jxPddxFdLv+XmWj46y/3RMOff158oqFhQ/cRDS1aQOPGhZ/IOSwMfH0h9RyTYvv6muuJiIhIhaO/NEVEREQqoOSMZP77y3+Z9vM0zmSccevztHkytNlQ7ml3D8E+wRZFKFLynn32WZ599tnzrjdw4EAGDhxYYH+1atV45ZVXijEykfNLOLznnMkHAL9MuGTMs5A42Uw0ZJ5ng4LYbO6JhqxkQ5MmhU80FKRuXXPy6rMTMDudTpKSkggMDMwedRcWZq4nIiIiFY4SECIiIiIViMPp4INtH/D4d4/z9+m/8/R3r9ud0Z1HUyekjgXRiYhIYYUFFG5EQMSGPwu/05yJhpzlk4oj0XAudetmJxicTuwJCRASYs4PISIiIhWaEhAiIiIiFcSPB37kkZWPsOmfTXn6GoU2YkyXMbSPbG9BZCIiUlRtara58I1tNoiKyn9Eg69v8QUpIiIich5KQIiIiIiUc3tP7WXcqnF8FvNZnr5qftUY2WEk/Rv3x2bYLIhORESKzOnE44cfC7dunTrQrl3eEQ1KNIiIiEgZoASEiIiISDkVnxrPcz88xyvRr5BuT3fr8/bwZvilw7m99e34eflZFKGIiBTZH3/A6NHw7beFW3/pUmjbtkRDEhEREblQSkCIiIiIlDOZjkze2vwWT615irjkuDz9faL68GCnB6kRUMOC6ERE5IKcOAGTJsEbb4DDYXU0IiIiIsVCCQgRERGRMsrusPPDgR/Yc2wPUTWi6F6vOyv3rGTMyjHExMXkWb9VeCvGdhlLs+rNLIhWREQuSEYGvP46PP00nDpldTQiIiIixUoJCBEREZEyaHHMYh5a/hCHEw+7lvl4+JBmT8uzbkRgBA93fpiel/TEMIzSDFNERC7GihVmuaWYvEnlhCva47NuE772c2zv6wthYSUXn4iIiMhFUgJCREREpIxZHLOYoZ8MxYnTbXnu5EOAVwB3trmTm1rehLeHd2mGKCIiF2PXLnjkEfj667x9zZrBSy8x1baaj5ZtIizZXPzVv78kMijSfd2wMKhbt+TjFREREblASkCIiIiIlCFxZ+K458t78iQfchvcdDD3d7ifKr5VSicwERG5ePHx8Oyz8MorkJnp3le1KkyeDPfdh9PTk0Wz7+dQFThUBdpHtifyyussCFhERETk4igBISIiImKhkykn+fHAj6zZv4a1B9ay9ejWQm13TdQ1Sj6IiJQXdjvMnQsTJ0JcnHufhwfcd5+ZfKhWDYBfj2xl76m9rlWGNhtamtGKiIiIFBslIERERERK0YnkE/xw4AfWHljLmv1r2Ba77byjHfITlxx3/pVERMR6a9bAww/Db7/l7evdG156CVq2dFu8aPsit/aQ5kNKLj4RERGREqQEhIiIiEgJikuO44cDP7hGOGyL3VYs+w3z16SjIiJl2r59MHYsfPZZ3r6GDeG//4UBA8Aw3LqcTiefbv/U1W5dszUNQxuWdLQiIiIiJUIJCBEREZFidPzMcdYeWMva/WtZc2ANfxz7o1DbeRgeNAlrQruIdny580vi0+ILXDc8IJw2NdsUU8QiIlKsTp+G55+HmTMhLc29LygInnwSHnwQfHzy3fyPY3/w18m/XG2VXxIREZHyTAkIERERkYtw7MwxM9lwdoTDn8f/LNR2njZPmlZrSrvIdnSI7MBl4Zfh5+UHwKU1LmXct+MK3HZMlzF42DyKJX4RESkmDgcsWACPPw5Hjrj3GQbceSdMmQLh4efcTe7yS0ObKwEhIiIi5ZcSECIiIiJFcDTpKGv3r3XN4RATF1Oo7TxtnjQLa0b7yPa0j2xPqxqtXAmH3HrW78mLvV9kxroZHDtzzLU8PCCcMV3G0LN+z2J5LSIiUkzWrYOHHoKNG/P2desGs2ZB27aF2tWimOwERMsaLWkS1qSYghQREREpfUpAiIiIiJzDkdNHXMmGtQfWsiNuR6G287R50rx6c9pHtKdDZAcuDb8UX0/fQh+3Z/2eXFnvSrYe2crhU4epXbU2bSLaaOSDiEhZcvgwjB8PH36Yt69uXZg+HW68Mc88DwXZfnw7249vd7VVfklERETKOyUgRERERHL4O/Fvtzkcdp3YVajtvGxeNK/enA6RHWgf2Z6WNVoWKeGQHw+bB+0i29EkuAmBgYEYhbyAJSIiJSw5GWbMgBdegJQU9z5/f7MM05gx4Jf/SLeCfLbdfcJqlV8SERGR8k4JCBEREamQ7A47Px78kSOnjxARFEG3ut3yHT1wOPGw2xwOOSf+PBcvmxcta7SkfUR72tdqT8vqLfHxzH9CURERqSCcTli4EMaNg0OH8vbfcouZlKhV64J2n7P8UtOwpjSv3vxCIxUREREpE5SAEBERkQpnccxiHlr+EIcTD7uW1Q6uzct9XqZDZAdXSaU1+9ew59SeQu3T28ObltVbuuZwaFG9hRIOIiKVyebN5jwPP/+ct69jR3j5Zejc+YJ3v+vELrbFbnO1hzYbqpFvIiIiUu4pASEiIiIVyuKYxQz9ZChOnG7LDyceZsgnQwq9Hx8PH1rUaEGHiA50qNWB5tWb4+3hXdzhiohIWXf0KEyYAP/7nzkCIqfISHPEw3/+AzbbRR1G5ZdERESkIlICQkRERMo1h9NBbFIsBxIOsPfUXu7/+v48yYfC8PHw4dIal9IhsgPtItvRonoLvDy8SiBiEREpF9LSYNYseO45OH3avc/HBx59FB57DAIDi+VwOcsvNQptRKvwVsWyXxERERErKQEhIiIiZZrD6eBo0lH2x+93PQ7EH2B/QvbzNHtakffr6+nrSji0j2xPs7BmSjiIiIg5yuHzz81JpPfuzdt/443w4otwySXFdsi9p/ay5cgWV3toc5VfEhERkYpBCQgRERGxlMPp4MjpI24Jhv3x+9mfYCYXDiQcIN2eXqzHvLftvYxoMwJPm74KiYhIDr//Dg8/DKtX5+1r3dqc56F792I/rMoviYiISEWlv7pFRETEjd1h58eDP3Lk9BEigiLoVrcbHjaPi9rfP6f/MUcrJBzIk2g4mHCQDEdGMb6C82sT0UbJBxERyRYXB5MmwZtvgsPh3le9ulmG6Y47wOPCfx+eS87yS/Wr1KdNzTYlchwRERGR0qa/vEVERMRlccxiHlr+EIcTD7uW1Q6uzct9XmZws8H5bpPpyHQlGPIrkXQw4SCZjsxijTPUN5SaQTWJDIykVnAtIoMiiQiMIDwwnJHLRnI8+XiB24YHhOvCjoiImDIy4LXX4OmnIT7evc/LCx56CCZOhJCQEgvhQPwBov+OdrVVfklEREQqEiUgREREBDCTD0M/GZpnAue/E/9m6CdDmdxjMnVD6rrKI2UlGw4nHi72BEM1v2rUDKxJZFAktYLMBENWkqFmYE18PH0K3HZs17GM+3Zcgf1juoy5qBEdIiJSQXzzDTzyCOzYkbdvwAD473+hUaMSD+OzGJVfEhERkYpLCQgREZFKIi0zjYS0BBLTEklMSyQh1XyekJZAfGo8T37/ZJ7kA+BaNmnNpGKJw8Cgmv/ZBEOuEQyRQZGEB4SfM8FwPj3r9+TF3i8yY90Mjp055loeHhDOmC5j6Fm/Z3G8DBERKa927jQTD8uW5e1r3hxmzYKrry61cBZtzy6/VCe4Dh0iO5TasUVERERKmhIQIiIiZ9kddn448AN7ju0hqkYU3et1LxN3ymc6Ml1Jg9yJg/zaBfUV90TOBTEwCPMPK3AEQ3hgON4e3iUaQ8/6Pbmy3pVsPbqVuOQ4wvzDaFOzTZn4PEVExCLx8fDMMzB7NmTmGrlXtarZd9994Fl6fyYfTjzMusPrXG2VXxIREZGKplInIE6ePMlnn31GTEwMo0ePpk6dOlaHJCJSbhX3xMWl7ULmPjgfh9NBUnqSWyLgQhIHyRnJxfUyi4XNsBHmH0ZEYAQRgRGuEQyRgZFEBEUQHhCOl4eX1WHiYfOgfWR7q8MQERGr2e3w9tvw5JPmZNM5eXjA//2fOQdEtWqlHtrimMVubZVfEhERkYqm0iYgli9fzmOPPUZwcDDp6eksX76cu+++m9GjRwMQExPDc889xx9//EFoaCi33347t956q2v7Jk2a8PzzzzN48IVdlCp1Bw9CXBx2h50tR7Zw+ORhaofWpm1EW/MCYVgY1K1rdZRSGDk+y61HtxJ3Jo6wgBx39paXz1LnpEt5v3APJXPxvjSdb+6DF3q9QLvIdgUmDgoqa3Q67XS+JY3KsylXTaF3g9542irtVwgRESlPVq+Ghx+G33/P23fNNTBzJrRoUephZclZfikyKJLOtTtbFouIiIhISaiUVw9SUlJ4/PHHue222+jatSvR0dFERUUxevRorrrqKurVq8eIESPo2bMnkydP5tdff2Xy5MkEBAQwZMgQq8MvuoMHoUkTSE3FA+hw9uHG19eshVpJLviWW7k+y3zv6y0Pn6XOSdPBg6ze+AnTf5lObFKOOvWBNRjbdSw9OwwrF6//fBfvFw1blG8SwuF0kG5PJy0zjXR7uvncnuP52eX5LSv08rPPz7VdWmYa++L3nXPug/HfjS+ZN68Y+Xj4EOAdgL+XP4FegQR4BxDoHUigdyABXgEE+wS7lgV4nf3XO8D13M/Tj5sX3+w2Z0Ju4QHhXN3g6nKXIBMRkUpo71549FFYsiRvX8OG8NJL0L8/WFju6MjpI/x08CdXe0izIdgMm2XxiIiIiJSESpmA2LNnD8nJyVx//fXEnR2C27dvX06cOEGVKlX45JNP8PLy4plnnsHT05OoqCgOHDjAW2+9VT4TEHFxkJp67nVSU831ysHFzkqtonyW5fx1OJ1OnDhxOp04nA6cnP03R/tcfQ6nA+PgIaq16UrP9EzyTod7DGaOJdP7cXb89DmptWpgd9ixO+1kOjJdz4u6zO44u/wCl7n2m7Ntz2Tl3pXnvHg/7NNhRARGkO5Id7vwb3faS/yzKg88bZ4EeJ1NHORIDuT3CPAOcEsu5EwkFMeIhEe7PMq4b8cV2D+myxglH0REpGw7fRqmTjVHNqTnmvsoOBgmTYJRo8C7ZOciKowlO5a4fYdS+SURERGpiCplAiIsLAzDMFi/fj0NGzYEwDAMhg8fDsCmTZvo2LEjnjkmH+vcuTNvvvkmcXFxhIWFue3v+PHjDB8+nIiICF5//XV8fX1L78UUgt1hpzCXi0716UGmjydOzLuAnFk3A529K8j11dgAp5FrHQzA6VqOQT774ex+cizPtczcLtfy/Jbl2m++x3LmirOg7c9y5nxdOV9WjnWz4nFfltXO3qGr7xz7K/j9yd4293b+p1Npy/n9MnIgiVX8cNrM/TkMwDBwGOZzp2HgdD3PsQxw5Ngm73bgAJw2AwfOvP1nt3c9L2Cb8OMp/F8hXsdTc4awJ9KPTBtkGk4ybZBhc2I3ICNHO6sv3XBgN8x/HTZcF/4LSgIUJWGQs10c2vwDW84zH7Bneia3zu3P1shiOWSJqRMPYeeYoiDO384h5+GCVyinbIYNfy9/ArzMUQQ5kwJBPkEEegUS6OOeUMiZMMhq+3j6WP1SXHrW78mLvV9kxroZbiMhwgPCGdNlDD3r502XiYiIlAkOB7z3Hjz+OBw96t5nGHDXXTBlCtSoYU18+chZfik8IJzL61xuYTQiIiIiJaNSJiBq1qzJiBEjmDJlCs2aNaN27docOnTINQn10aNHady4sds2Nc5+UT1y5IhbAuLkyZPcfvvt1KpVi9deew0fn6JdSIqLi8Nmyx5m6+PjQ1BQEHa7nVOnTuVZP+vY8fHxZGZmuvUFBQXh4+NDamoqSUlJruW/7vyBjkAI5kXhE/nEEQpUPX6aRCD3NdEAwA9IA07n6vMEqmS9lnz2W+XsOklA7vvd/c7uOwNIyNVnOxsTwEnMC9g5hQBewBkgJVefLxAIZALx+cSU9enFn10npyDA5+w+z+Tq8waCz8ZyMp/9VsPMEyRgvqacAs/GdSHvYVXA4+x2abnW8T/7SAcScyxvvO4QHme3heJ9Dw3M1wpwCsh9D3sw5nuVfPaRU873ML/Xmvs9HPW//a6+rPcwFfN8ysmLvOe3A7AbkGmDYBs4PMzXkmwzl9ttZp+Xh/lIBeIN9z6nDfw9zecnnZCZo89uAx9PcHpAktP8bDJz9Nk8wOZlLk92uPc5DKifVrj3sM4RiHdAqiekeUCaD6QFnD138xtEEnD23xTyfug+mCdcBnn/o3ucfYOd5P3gwPwPazt7zBwBRybCr3Mh1F7w+e3jCU1GwqH85iT2PXvsNPL+h/TCfCPs5H2tBubJz9l4neBpeOBp88TD8MDb3xMvTy88Mj3wtNvwNDzNh80Db28vfP188XR64EyFMxln+C1+R/a+C3gP72l4E+0jW1HFPxjPTA9IN5PXrtfq5UFAgD8Oh4PTiTl+gmSYj2DPQIx0g6STydgzz3CGY66fM35+Pnj7eJOenkFKsvuL9fCwERhkBpUQn/sdhsCgADw8bCQnp5CR7v4m+vh64+vrQ0ZGJsln3P+n22w2goLN/SYmJuF0mMm1RgTzWtOn2ZdxkHjHaQId/jTyq49HvI1DWzcB4O3thZ+/L/ZMO0lJuU4YA0JCggA4nXgGh8P9RPQP8MPLy5PU1DTSUt1PxALfw7OCQwIxDIOkpGTsme7/c1zvYVo6KSlp7u+hpweBgf44nU4SE3L/BIGg4ABsNhtnziSTmeG+38K+hwkJp8mdnwwM9MfD04OU5FTS091/M3j7eOHn50tmZiZnktz3a9gMgoMDAfM9tDvsJKck4+/nj4FxzvfQy9sTf38/7HYHSafzvochVczPJun0Gex298/Gz98Xb2+vYn8Pff188LnQ87sY3sOc53eWgEA/PD09SUlJJT0t137PdX5TuPcwLS2d1FzvYdb5baQlctL+D/4Z/m791apVwzAMEhISyMhwjykwMBBfX1/S0tI4fdr9ffL09KRKlSoArpG9OVWtWhUPDw8SExPz9IlUGD//bM7zsGlT3r7u3WHWLGjTprSjOqdjZ46x9sBaV3tws8EaZSgiIiIVUqVMQACMHz+enj178u6777J69WpWrFjBgAEDmDZtGqmpqXjnGpKblVhIS8v+YzI+Pp7bb7+dyMhIXn311TzbFMYnn3yC3Z79h3qDBg3o3r07iYmJLF68OM/6t99+OwDLli3j+PHjbn3dunUjKiqKmJgYNmzY4Fq+87fVZAD9MK+D5d0r3Ip5HXAdcCBXX2egFfA38G2uvjAgq7L7UvJe77wR8yL4FmBHrr7WQEfgOPBVrr4A4D9nn39D3mTAdUAk8Cfwa66+pkB3zAuhuV+rDbjr7PPV5L0I3htoAPwFrM/VVw+4FvO6bX7v4e2Y10p/BnLf63050AI4CHyfq68GMPDs8/z2exPmBemNwO5cfe3OPo4By3L1BZ/dFsz3N/f12xuAcGAbkHtKvubAFZgX7HPH5AWMOPv8W8wL6Dldi/le7QKic/U1wHyPU/LZL8CdmNeifwCO5OrrjvnZ7j/bn1MEMADz/HPbrxOww3/sEJABm4G9ubbtiPnZHMDsz6kqcP3Z5//DPbFkO3vMMOAnYHuubS8FugCxwOe5+nwx/88BrMA9eQTm/9XaQAzQ/0von6OvIdAT831/3wMybGcfZ58PCDKTFd+lmedFpkd2/yVVIDgQDqbB7iRzWVZSxDvQoEZtD1JtTvYegEwPA7vNfGR6GIS08sbu60H8QTtpp50YhoENg9D4DA7bUwjlHD8jMuGa9Lr8ftCG4bThiQ0Pw4YHNpq1iiDI35d/jsaTcDwFDwxXX71a1WhUrSZJian8sf9vPLCZ/dgI8PGlT/uWeBsefLtnO+npmbiGCgHdWzamekAQfxz4m52H3e+CvCQ8jHYN65GYnMKqrdtx4GRv8n5OO1PNXbQ7u+I+XMmYIMOXagdPU7PJUWqHpbHr71h+3+/+Pz0iNISuzRqSlpHJ99G/kdv1nVrj5enBH3/+RWy8+6feukEdoiJqcPDYCTb9td+tLzQogKtaNQXgu59zn6VwbduWBPr5sGvXPg4dd0+PNqsTQfO6kcSeSmTT9r/c+gJ9fbi2XUsAfor+jbQM9+RFj0ubUC04jN/2HWLrPzFufQ1qVqdNVF1OJSWz6Tf3Pk8PGzd0Ni/ybNz6J4m5Ljh3aRZF9dAq7Dx8lD8O/O3WVzusKp2aNCAlLZ3vN+WdLHRglzZ42Gz89vtO4hLdL4K3bViPGuFh7IuNY8tu999kYcGBXHlpE+wOB6vXbc2z337tL8XPx5udO/dyOM79p1rLerWoWbsm/5yMZ1PMHre+YH9frm5jTly6dv1WMnNdjO55WTOqBPqzb89B9h51/53dMLIGl9Wvw4nEJDb9vtOtz8fLk+s6XgbAhs1/kJSait1ux8PDAzC4onkjqlQNZvvBf4g55P7Tsk71UDo2rk9SShprtvyR57UOudw8wbdu28HJXAmKDo0uoUaNauw5coxf9x5y6wuvEswVLRqRkWln9YZf8+z3uo6X4ePlyfaY3Rw56X5bwaWX1KZxrXAOx51i0073n8JVAv3pdVkzAL7/ZQsOp3ui4Oo2zQn292PP7gPsj3X/rd2kdk1a1qvF8YTTbPpjl1ufn7cX/Tq0AuCXjdtIyZW86N6yMVVCgjh8np8Rm7a6/3S3GQaDuppjETf/FkN8rgRFpyYNqBFW9Zw/I/wzMvnm+F/4h9dx6//3v/+Nt7c3K1eu5J9//nHfb6dONGvWjD179vDjjz+69VWvXp3+/c3fFB988AG5DR48mODgYH766SciI8v4kDqRojp0CMaPh48+yttXrx7MmAFDhlg6z0NBlu5YisOZ/XtD5ZdERESkojKcTmfx1BMppzZs2MCGDRto2rQpjz76KGPHjuWTTz6he/fujB071rXe7t276d+/P0uWLKF58+Y0adIEb29vMjIyGDx4MFOnTi3Sce12O7/++iu1a9cu+REQK9+j4y2PnncExPImHhzxMch0Zl/GM5zgawMfm0GGw0mqw1wG5joeBgTazLVPZzrPbmOQVTwo0AYehkGaHdKduO4ONXDiZxj42gwynU7O2N33azMg2GZgAIl2pyuzkfVOBdjA0zBIdTjJyJX18AECzu436Wy8rnfYCVU8zP0m2Z3YcxzTcIK/DXzO7jfNkd0H5oX3IBs4nE4S7e59hhOq2MwLE0l2Z5730N8GvhikO50kO7NfK5hZwOCzfxTFZ92hmWP7Kpjv4RmHA2eGg8jE7I0LGgFx0h8MDxtVnQY2J8Q7neB0Ypw9tuGEKk4n3hikOJykAoYDbM7sG8tLegTEhY4iKewIiJxCMc+B/Eb4FPQeAm6jSE6Q5+bmYhnhU9T30AdzpI6dvMkfKNwIn+J4D51eXmbtZMMgMCnpvKOk7LfeysnatSEgAAIDXY8qNWvi6e9PUnIyqbnqNPv5+BDg50dGZiYJSe4R2wyD0JAQAE4mJOS5aBkSGIiXpydnUlJISXO/C9nX25tAf38yMzOJP7vfb//8khe2vAKAx9kqeplp2f9XH2v7IL1bDCDI3x8fb29SUlM5k2seE29PT4IDA3E4HJzM507jaiEh5t3NSUlk5Pr5Hejnh6+PD2np6ZxOdv/UPT08qBJk3nEdFx+fZ79Vg4Lw8PDg9JkzpOW6a9rf1xd/X1/SMzJIPON+sdnDZqNqcHCxvYdZDKDa2buxTyUmYs81AiI4IABvLy+SU1NJLoH3MDUtjaQU97vhvTw9CQkMxOl0ciIh9/9ICA0OxmazkZiURHqu/Rb2PTwRH5/3Z0RgIJ6enhd1fp9KTCTTbufMmTMEBARgGMY530MfLy+CAgLM7xGn844oCDv72cSfPk2m3f2nT9b5XdzvYYCvL36+vhd0fhfHe1ic5zcU7j0858+IAwc4Wb8+1HFPQJT0CIj4+Hj27t1L69atzyazpLRlff8v7c/A6XSSkJBAyNmfoRVCcjJMnw7TpkGun1cEBJhlmB55BPz8rImvEK5ZcA2r9q4CIMw/jCNjjhTLfE7lQYU8J6Vc0zkpZYnORykOVn3vLEilTEDExsayefNm+vXrx4YNG4iOjmbUqFGMHDkSh8NBRkYGVapUYfr06a5tfvnlF0aMGMEvv/xCtWrVaNKkCT169GDIkCGMGjWKd955hyuuuKLQMZTmiWDftBGPDh3Pv97GaDzadyjRWOTilOpn6XSatXQdjvM/L+K69m2/4TH0xvO/jjmz8WjYCDIzzYfdfv7n51svI8N9ee52fvvLuex8MdjtBT+X/Pn4QFBQ9iMw0Jwk8lzPs9qBgeB5kX+sHz0KgwfnnagyJ29vWLwYata8uGOJXACn00lSUhKBgYH6I6QiOHTILAVTr16pHras/RFSGSkBUQycTvj4Y3PUw6FDefuHD4fnn4datUo/tiI4kXyC8Bnh2J3m98O7297NWwPesjiq0lOhzkmpEHROSlmi81GKQ1n77l85brHIJTo6mkcffZRmzZq5LY+Li6NBgwZccsklfPzxxznKHcD69eupX78+1apVc61/7bXXcs0119CvXz+efPJJvvzySwIDA0v1tRRGYWuJquZo2Veqn6VhgIeH+ShmHvnclZvvel26QtvCTLtdDjid7gmJTZugR4/zbzdrlvlHdGpq/o+UFPOR9Tx3X+7109Kyn5cVaWnmI587dwsla1RFzkRFUJDZzu95znZAAMTHnzv5AGZ/fLwSECIiIlbZtAkeegh++SVvX+fO5nemTp1KPawL8fnOz13JB1D5JREREanYKmUComfPnlSvXp3HHnuMQYMGER8fz6xZs/jtt98YN24c9erVY+7cuUyYMIG77rqLbdu28e677zJ58uR89zdhwgT69evHiy++yDPPPFPKr6YQwsLA1/fcFxx9fc31pGyrKJ9lRXkdRWEY5p36np7Zd/wXRrduJZOEcTrNi+r5JTTOlezIvezAAVi4sPjjK4ozZ8xHbGzRt7XZwN///OuJiIiINY4cgSeegHffzdsXGQkvvgg332z+Ti8nFm1f5Hpe1bcqV11ylYXRiIiIiJSsSpmACAgIYN68eUyZMoUpU6YAEBUVxZw5c2h79kLf3Llzee655xg0aBDVq1dn3LhxDBo0KN/9hYWFMW7cOCZMmEDfvn3p0qVLqb2WQqlbF3buhLg47A47W45s4fDJw9QOrU3biLbm3fJhYeZ6Urbl+iy3Ht1K3Jk4wgLCaFOzTfn5LHVOWp+EMQwzEeLjA2frpF+QLVsKl4BYvdosN3LqlDmSIOuR1T51Ck6edO+Lj4eEhLy1nYuTwwH51HjP18iR0KCBeV7WqZP9b+3a5mclIiIixSc11RzV8NxzeX9X+/rC2LFmKaaAAEvCu1CnUk7x7d5vXe2BTQfi5eFlYUQiIiIiJatSJiAAGjduzHvvvcf69evZuHEjo0aNcutv1aoVC89xUW3nzp1u7aFDhzJ0aBkeOlu3LtStiwfQ3tmeRqonV37l/Cwpx3N2VPZzMkcSpkAVKQkTEmJevL8QaWl5ExO5ExlZyYtTp7L7EhLMf3NNiHvB4uPNhMuWLXn7wsOzExJZj7p1zeSEt3fxHF9ERKQycDph6VIYMwb27cvbP2yYOeqhlOdRKS5f7vqSDEf2RPM3Nj//vGgiIiIi5VmlTUBkqV27duW54CkiZcvZJEy5VhojOXx8zAv84eFF39bphOTkgpMXp06ZiaAPPrjw+MAs/xQbCxs3ui83DHPeiJwjJrL+rVULvHTHo4iIiMu2bfDww/D993n72rSBl182y1OWYznLL4X4hNCrQS8LoxEREREpeUpA1K5N7dq1rQ5DRKR8KusjOQzDLM0QEGBe8M/Pli2FS0AMGGCOtNi9u/DzTTidZu3qI0cgOtq9z8PDTE7kTkzUrQsREeZ8ISIiIpXB8eMwaRK89ZZZHjGnGjVg6lS4/Xbzd2c5lpiWyIo9K1ztG5regLeHRkqKiIhIxaarGyIicnEqwkiOwnj66ewJwU+fNhMRf/2V/di501x2rmRMTnY7/P23+Vi3zr3Pw8NMmOQu6VSnjpmcKOcXYERERADIyIBXXzV/xyYkuPd5eZmjISZOhOBgK6Irdl/t+op0e7qrPbRZGS7hKyIiIlJMlIAQEZHK7ULKSAUFmaUg2rTJu25CgntiImdy4tSpwsVkt8PBg+YjN09PMzmR38iJ8HCw2Qp3DBERESstWwaPPGL+jszthhtgxgxo2LD04ypBn27/1PU8yDuIq6OutjAaERERkdKhBISIiFRuucpIOZ1OkpKSCAwMzJ4jqChlpEJCoH1785HbyZPuiYldu8zH7t2QmFi4/WdmwoED5iM3b29z4uv85pyoXv38yYmjR825MQpSpYpZNkpERORCxcSYiYfly/P2tWgBs2ZB796lHlZJO512mm/++sbVHtBkAL6evhZGJCIiIlI6lIAQERHJWUbK6cSekGAmErISEMUlNBQ6dTIfOTmdZgIk98iJrOREUlLh9p+eDnv3mo/cfHzM5ER+IyfCwsx5LQYPNvdREG9vWLxYSQgRESm6U6dg8mSz5FJmpntfaCg8+yzcc0+FnQNp2V/LSLOnudoqvyQiIiKVRcX8diciIlKeGIY5QqF6deja1b3P6YRjx/IfObFnDyQnF+4YaWnm+nv25O3z8zOPfa7kA5j98fFKQIiISOFlZsLbb8OTT8KJE+59Hh7wwAPw1FNmEqICWxSzyPU8wCuAPg37WBiNiIiISOlRAkJERKQsMwxzbofwcLjiCvc+pxOOHMk/ObF377nntcgpJSX/+SZEREQuxnffmRNJ//FH3r5rr4WZM6F581IPq7SdST/Dsr+Wudr9G/fHz8vPwohERERESo8SECIiIuWVYUBkpPm48kr3PocD/v47/+TEvn3nH+1QkM8/N8s51a9/8fGLiJSyTZs2MXz4cN5991065SiHt27dOqZPn86ePXuIiIhg1KhR9O/f39WflpbGCy+8wPLly0lNTaVnz55MmDCB0Ap+1/4F27MHHn0Uli7N29e4sZl46Nev+EsdllHLdy8nOSN7xKLKL4mIiEhlogSEiIhIRWSzmXM81KkDPXu699ntcOiQe3Ji40b4+efz7/fTT83HJZfAVVdBjx7m3auV5CKSiJRfp0+fZty4cTgcDrfle/bs4d5772XEiBFMnz6dNWvWMG7cOEJDQ+nSpQsATz/9NJs2bWL27Nl4e3vz1FNP8eCDD/L+++9b8VLKrtOn4bnn4KWX8ia6Q0Jg0iQYOdKcU6gSyVl+yc/Tj76N+loYjYiIiEjpUgJCRESksvHwMBMIl1wCV19tLtuyBdq1K/w+9u+H//3PfISHm4mIq66C1q0r7ASiIlK+Pf3009SpU4e///7bbfn8+fNp0qQJo0ePBiAqKort27czd+5cunTpQmxsLEuXLuWNN96gffv2AMycOZM+ffqwdetW2rRpU+qvpcxxOODdd+GJJyA21r3PMMzJpZ991pxvqJJJyUjhq11fudp9G/Ul0DvQwohERERESpfN6gBERESknIuNhYUL4b77zJrekyfDjz+aE1+LiJQBn3/+OVu3buWJJ57I07dp0ybXSIcsnTt3ZvPmzTidTjZv3uxalqV+/fqEh4ezcePGkg28PPjpJ+jYEe68M2/yoUcP2LoV3nijUiYfAFbuWUlSepKrrfJLIiIiUtnoFkUREREpvIULYedO+Owz+O23vP0JCfDll+bD3x8uv9y8AHX55RCoOz5FpPQdPnyY5557jtdee42AgIA8/UePHqVmzZpuy2rUqEFKSgqnTp0iNjaWqlWr4uPjk2edo0ePFjkep9OJ0+ks8nYXKut4xX7Mgwdh/HiMhQvzHvOSS2D6dBg82BwBUYqvt6xZtD27/JKPhw/9GvUr1c+/LCqxc1LkAumclLJE56MUh7J2/igBISIiIhAWBr6+kJpa8Dq+vtC5MwwbBk8+aU5mvXQpLF5szh+R+0tOcjKsWmU+vLzMO2Svugq6dwdN3CoixeDw4cP06tWrwP6ff/6ZsWPH8q9//Yv27dtz+PDhPOukpqbinWtOgqx2eno6KSkpefoBfHx8SLuAkV6JiYnYbKU3EN3pdJKcbE6AbBTHfD1nzuD7yiv4vPIKRq7fGc6AAFIfeYS0++83f2ckJl788cqxtMw0Pt/5uavds15PnKlOElITLIzKesV+TopcJJ2TUpbofJTikHvOM6spASEiIiJQt645siEuruB1wsLM9bLUrw+jR5uP2Fj4/HNYsgS++w4yMty3zcgwkxQ//2xOkN26tZmMuOoqyHXnsYhIYYWHh7Ns2bIC+z/++GNSUlIYNWpUgev4+PiQnmvC5Ky2n58fvr6+efoB0tLS8PPzK3LMwcHBeHh4FHm7C5V1B1xISMjFXchwOuGjj+CxxzDySeQ4b7sNnnsO38hIfC/8KBXK17u+5nT6aVf7plY3ERISYmFEZUOxnZMixUTnpJQlOh+lONjtdqtDcKMEhIiIiJjq1nVPMBRFeLg5yeg995hlmL7+2hwZ8c035kiInBwOc9LrLVvgv/+FZs3MMk09e5pJDRGRQvLy8iIqKqrA/sWLF3Ps2DE6deoEZP9Rf/fddzNw4ECeeeYZIiIiOHbsmNt2x44dw9/fn6CgIGrWrEl8fDzp6eluIyGOHTtGeHh4kWM2DKPULyhkHfOCj7txIzz0EKxbl7evSxeYNQujY8eLC7IC+mzHZ67nXjYvrm9yvS4mnXXR56RIMdM5KWWJzke5WGXt3FECQkRERIpXSAj8+9/mIyXFLMG0eLE5L8TJk3nXj4kxH6+/DvXqZY+MaN7crB0uInKBFixYQGZmpqsdGxvL8OHDmTJlCpdffjkA7du3Jzo62m279evX07ZtW2w2G+3atcPhcLB582bXZNX79u0jNjaWDh06lN6LscI//8ATT8D8+Xn7ateGadPg5pv1szof6fZ0lu5Y6mpfHXU1VXyrWBaPiIiIiFWUgBAREZGS4+cH119vPjIy4IcfzDJNS5fC33/nXf/AAXj3XfMRHm6OjLjqKrNkk6e+tohI0dSqVcutnVX6KDw8nGrVqgEwfPhwBg0axIwZMxg0aBBr165l+fLlzJ0717Vu//79mThxIlOnTsXPz4+nnnqKjh070rp161J9PaUmNRVeegmeew7OnHHv8/WFcePMRz6Teovp+33fE58a72oPbTbUumBERERELKS/5EVERKR0eHlBr17m45VXzJIeS5bAZ5/B7t1514+NhYULzUdIiDl59VVXQadO4ONT+vGLSIXUqFEjXnvtNaZPn878+fOpXbs206dPd412AHj22WeZOnUqI0eOBKB79+5MnDjRqpBLjtNpjlgbOxb27cvbf9NN5qiHCy3XV4ks2r7I9dzT5skNTW+wMBoRERER6ygBISIiIqXPZjMTCZ06wfPPw/bt2cmIX3/Nu35CglnC6csvwd8funY1kxGXXw6Bge7rHj0K8fEFH7tKFU18LVJJ1a5dm507d+ZZ3r17d7p3717gdv7+/kyZMoUpU6aUZHjW+u03ePhhWLMmb1/btvDyy3DFFaUdVbmU6chkyY4lrnav+r0I9Qu1MCIRERER6ygBISIiItYyDGjRwnxMnAj795vJiCVL4KefzDtyc0pOhm+/NR9eXtCxo5mM6N4d0tNh8GDz34J4e5t3+CoJISICx4+bP3vnzgWHw70vPBymToXbbzcTx1Ioa/ev5UTKCVd7aHOVXxIREZHKSwkIERERKVsuuQRGjzYfsbHwxRdmMuLbb815JHLKyICffzYfNhs0bnzu5AOY/fHxSkCISOWWng5z5sAzz5ijzHLy9jZ/Bj/xBAQHWxNfOZaz/JKH4cHApgOtC0ZERETEYkpAiIiISNkVHg53320+EhJg2TJz9MI33+SdGNXhgB07rIlTRKQsOXgQ4uLM504nHklJZrk6wzBHlW3bBi+8ALt25d124ECYMQOioko15IrC7rCzeMdiV7vHJT0I8w+zMCIRERERaykBISIiIuVDSAjcfLP5SEkxR0QsXmyOkDh50uroRETKhoMHoUkTSE0FwACCCrNdy5Ywaxb06lWCwVV8Px78kWNnjrnaKr8kIiIilZ0KeYqIiEj54+cHAwbA//5nlmn67jsYORKqV7c6MhERa8XFuZIPhVKtGrz2GmzdquRDMchZfsnAYFDTQRZGIyIiImI9JSBERESkfPP0hJ49YfZss0RTYaSklGxMIiJlnYcHPPQQ/PUX/N//mT9L5aI4nA4+i/nM1e5erzvhgeEWRiQiIiJiPSUgREREpOKwFfKrzfjx8OOPJRuLiEhZtnChWXKpalWrI6kwfjn0C0eTjrraKr8kIiIiogSEiIiIVEYnT8Lo0fD449kTtYqIVCb161sdQYWTs/wSwOBmgy2KRERERKTsuKBxtqdPn2bHjh2cOHECDw8PwsLCaNasGb6+vsUdn4iIiEjhhYWBr2/h65+vWgXr15tlSG64AQyjZOMTEZEKKXf5pcvrXE5kUKSFEYmIiIiUDYVOQKSnp/PFF1/w6aef8scff+BwONz6PTw8aNu2LYMHD6Zfv354e3sXe7AiIiIi51S3LuzcWfCohpQUePddmDcPsr7LnD4NU6aY80dMmAD16pVauCIiUjFE/x3N4cTDrrbKL4mIiIiYCpWAWLVqFVOnTuXo0aM4nU4iIyNp0KABwcHBACQkJLBv3z6io6PZuHEjr7zyCmPHjqVv374lGryIiIhIHnXrmo+CXH453Hcf3H03bN2avXzLFrj5ZrjzTrj1VvDyKvlYRSqgvXv38vPPP7N9+3ZOnjyJzWajevXqtGzZkq5du1K7dm2rQxQpdiq/JCIiIpK/QiUgRo0aRevWrbn33nvp2bMnNWrUyHe9kydP8sMPP/D1118zZswYJSBERESkbGrXDqKj4aWX4KmnzJERAOnp8PrrsHIlPPkktGxpbZwi5ciaNWt4++232bJlCwBOp9Ot/9NPP8UwDDp06MBdd91Ft27drAiz4itMKTpfX3M9KRZOp9MtAdGpVifqhpwjES4iIiJSiRQqAbF48WKaN29+3vVCQ0MZOHAgAwcOZM+ePRcdnIiIiEiJ8fSEsWNh8GBzRMS332b37dkDI0bAsGFw//0QEGBdnCLlwP3338/q1avx8vKia9eutG7dmqioKIKCgoDsEdN//PEH0dHR3HPPPXTr1o233nrL4sgroFyl6JxOJ0lJSQQGBmJkzXMTFnbukWJSJJuPbOZAwgFXW+WXRERERLIVKgGRlXxwOp1kZGS45nfIyMhgxYoVxMXF0aJFCzp06ODaJioqqgTCFRERESlmUVHmiIcFC+CRR+DECXO50wkLF8KaNTB+PHTvbmmYImXZ4cOHmTx5Mv379ycwMPCc66anp/Ptt98yf/78UoquEspZis7pxJ6QACEhkJWAkGKVu/zSkGZDLIpEREREpOyxFXbF6OhounfvzurVqwFIS0tj6NChjB07lhdeeIFbb72VCRMmlFigIiIiIiXGMMx5H2Ji4D//ce+LjTUTE489VvDk1iKV3BdffMG//vWv8yYfALy9venXrx8LFy4shchESlbu8kvtItpRv2p9CyMSERERKVsKlYBIT0/nkUceIS4ujtSztUQ//vhjdu7cSd26dXnyySfp1KkTixcvZu3atSUasIiIiEiJqV4d3n8fli+HSy5x7/v2W7jxRli61BwdISLnlJKSwltvvcWoUaMYOXIkb731FsnJyVaHJVKsfov9jT2nsssPq/ySiIiIiLtCJSDeeust4uLi6Nq1KwBLly5l0aJFGIbBFVdcQUBAAL1798bpdPL++++zdOnSkoxZREREpGRdey388QeMGQO2HF+XTp+GKVPg3nth/37LwhMpD5544glmzpzJli1b+O2333j55Zd57LHHrA5LpFip/JKIiIjIuRVqDojvvvsOwzD4559/WLx4MQkJCfz111/4+fmxa9cudu3a5RoZERMTQ1paGgMHDizJuEVERERKVkAAzJgBN98Md98NW7dm923ZAv/+N9xxB9x2G3h5WRenSBnw999/U6tWLbdlP//8M2+++SZXXnmla53rr7/eivBESoTT6eTT7Z+62peFX0ajao0sjEhERESk7CnUCIi5c+dinJ2wrGfPnnh4eGAYBoMHD2bBggU88cQT+Pn5YRgGI0aM4L333ivRoEVERERKTbt2EB0NL74Ifn7Zy9PT4Y034JZb4PffrYtPpAy49tprmTJlCieyJnEHLrnkEiZPnsyYMWN49NFHuffee6lfX7XxpeL48/if7Dqxy9VW+SURERGRvAqVgKhWrRr3338/+/btY9q0aWzfvp06deowcuRIAD766COio6OpU6cON910U4kGLCIiIlLqPD1h7FizLNPVV7v37dljjoR48UU4c8aa+EQs9swzz7B69Wp69+7NrFmzSEpK4vnnn6devXqsXbuWNWvWEBYWxgsvvGB1qCLFJnf5JSUgRERERPIqVAkmgJEjR9K1a1d+/fVXwsLCuOaaa/D19QWgTZs2VKtWjTvuuIOAgIASC1ZERETEUg0awIoV5kTVo0dD1t3eTid88gmsXQvjx0P37tbGKVLKBg8ezHXXXceHH37IW2+9xUcffcQ999zDG2+8gY+Pj9XhiZSInAmIljVa0jSsqYXRiIiIiJRNhRoBkZGRAUDbtm254447uP76613JB4BBgwbx0EMPERQU5Fpmt9uLOVQRERGRMsAwYPhwiIkx/80pNhYeeQQeewzi4qyJT8Qi3t7e3H777axatYpbbrmF1157jauvvpqFCxfqbwOpcGKOx/Dn8T9d7aHNNPpBREREJD+FSkD06NGDWbNmceDAgfOue/ToUd5++2169+590cGJiIiIlFnVq8N775kjInLXtf/2Wxg6FJYsAYfDmvhEStmOHTtYvnw5hw4dYtSoUaxatYprr72W5557jn79+rFs2TKrQxQpNp/FfObWVvklERERkfwVqgTTtddey1tvvcWbb75Jw4YNueyyy7jkkksIDg7Gbrdz4sQJjh49ysaNGzl48CCGYTBs2LCSjl1ERETEetdcY05C/fTTMHNmdsIhKQmeew6++QaeeAIuucTKKEVK1Jw5c5gzZw4AhmEwatQo7r//fiZMmMDtt9/O7NmzefTRR3n77bdZsmSJxdGKXLyc5ZeahjWlefXmFkYjIiIiUnYVKgExadIkhg0bxltvvcXKlSv566+/MAzD1e90OgHw9fVl4MCBjBgxgsaNG5dMxCIiIiJlTUAATJ8ON98Md90FW7dm923ZYi6/80647Tbw8rIuTpES8sEHHzB+/HiaNGnCjh07ePvtt7n//vsBqFWrFi+88AJ33XUXL730ksWRily8v078xW+xv7naQ5sNdfv7WERERESyFXoS6qZNmzJz5kzOnDnDunXr2LlzJyfOTrwYFhbGpZdeSrt27fD39y+xYEVERETKtLZtIToaXn4ZnnwSUlLM5RkZ8MYbsHIlTJwIrVpZG6dIMXM6nRiGcc6LsA0bNuTVV18txahESkbO0Q+g8ksiIiIi51LoBESWgIAAevfurTkeRERERPLj6QljxsDgwXDffWbSIcveveZIiKFD4YEHIDDQujhFitEtt9zCCy+84EpAZI1+EKmIFsVkJyAahjakVbiSyiIiIiIFKXICQkREREQKoX59WL4cPvgAHn4Yzo4cxemETz+FtWth/Hi48kpLwxQpDiNHjuSqq67iwIED1KtXjxYtWlgdkkiJ2HtqL1uObHG1VX5JRERE5NxsVgcgIiIiUmEZBtxyC+zYAcOHu/cdO2aOlBg3DuLirIlPpJh8++23NG/enH79+hU6+fDjjz+WcFQixe+z7Z+5tVV+SUREROTclIAQERERKWlhYfDee7BihTkyIqfVq82STIsXg8NhTXwiF+nBBx+kV69ezJo1iz/++ANHPuey3W5n69atvPbaa/Tv3597773XgkhFLk7O8kuXVLmEthFtLYxGREREpOwrthJMaWlpnD59mrCwsOLapYiIiEjFcs018PvvMHkyzJwJdru5PCkJpk6Fb76BCRPgkkssDVOkqD7++GOefvpp3njjDd588028vLyoU6cOQUFBOBwO4uLiOHHiBOnp6TidTi699FI++ugjq8MWKZID8QeI/jva1Vb5JREREZHzK3IColmzZvTu3ZvZs2e7Lb/zzjs5cuQI3333XbEFJyIiIlLhBATAiy/CzTfDXXfBluxa4mzdai4fNgyuvtqc0NrpxJacDP7+ZkkngCpVoGZNS8IXyU+rVq1YvHgxP/74I0uWLOHnn39mz549buuEhYXRtWtXbrzxRjp06GBRpCIXbnHMYre2yi+JiIiInF+hEhBLly7ll19+AcDpdPLHH38wbtw4V7/D4WD79u35DrUWERERkXy0aQMbNsDLL8OkSZCcbC7PyDAnrv7gAwAMICD3tt7eZskmJSGkjOnWrRvdunXD6XRy9OhR4s7Ob1K9enVq6nyVci5n+aU6wXXoWKujhdGIiIiIlA+FSkC0bduWJ598koyMDAzD4OjRo3zxxRd51uvatWuxBygiIiJSYXl6mhNRDx4M990HK1cWbrv0dIiPVwJCyizDMIiIiCAiIsLqUESKxd+Jf/PLoV9c7SHNhqj8koiIiEghFCoBUbduXaZNm8aePXt49dVXqV+/Pv3793f1G4ZBtWrV6Nu3b4kFKiIiIlJh1a8Py5fDhx/CyJFmckFERMoMlV8SERERuTCFngOiX79+gJlsaNCggastIiIiIsXAMOA//zFHNfTubXU0IiKSQ87ySxGBEXSp08XCaERERETKj0IlIA4dOoS/vz/VqlXjhhtucC3LT506dYovOhEREZHKpmpVqyMQEZEcjiYd5ccDP7raQ5oNwWbYLIxIREREpPwoVALimmuuoXfv3syePZtrrrmmwPUMw2D79u3FFpyIiIiIiIiIlZbELMGJ09VW+SURERGRwitUAsLpdOJ0Ol3Pz7WeiIiIiIhUXikpKcybN4/ffvuNtLQ0t78RDMNg/vz5FkYnUnQ5yy/VCKjBFXWvsDAaERERkfKlUAmIr7/+mpo1awKwY8eOEg1IRERERAohM9PqCETyNXHiRJYtW5bvzUmGYVgQkciFO37mOGv2r3G1BzcdjIfNw7qARERERMqZQiUg7rzzTqKionjnnXe49dZbad++PQ8++GBJxyYiIiJS+YSFga8vpKaee71Vq6Bly9KJSaQIVq9ejc1mY9iwYTRu3BhPz0L9ySFSJi3dsRSH0+Fq39jiRgujERERESl/CvXXQFxcHEFBQezdu5fo6Gi8vLw0CbWIiIhISahbF3buhLg4wCxxmZSUROCZMxj/+hckJZnrffwxXHstNG9uYbAiefn5+dGiRQueeuopq0MRuWg5yy+F+YfRvV53C6MRERERKX8KlYCoVasWu3fvpn///gD88ssv+U5GrUmoRURERIpB3brmA8DpxJ6QACEh8Oab8J//mMvtdpg0Cd5/3xwxIVJG3HjjjSxZsoQzZ84QEBBgdTgiF+xE8gm+2/udqz2o6SA8bRrRIyIiIlIUhfr2NH78eJ566ini4uIwDKPAyaY1CbWIiIhICbr5Zvj8c/jkE7O9fz/MmQOPPmppWCI52Ww2UlNT6dOnD5dddhl+fn6uuR8Mw2DatGkWRyhSOF/s/AK70+5qD20+1MJoRERERMqnQiUgevbsSc+ePQFo2rQpvXv3Zs6cOSUamIiIiIjkYhjw+uvw449w5Ii57OOPoVs36NTJ2thEznr99dddz7/99lu3PiUgpDz5dPunrudVfaty1SVXWRiNiIiISPlU5PGj3333HX5+fgCcOHECwzAIDQ0t9sBEREREJB+hofC//0GfPtnLJk82ExHBwdbFJXLWAw884BrxIFJenUo5xbd7sxNoA5sOxMvDy8KIRERERMqnIicgatWqxdq1a5k6dSoHDx4EoEGDBjzxxBNcfvnlxR6giIiIiORy7bVw//3w2mtm+9gxePFFmDLF2rhEgFGjRlkdgshF+3LXl2Q4MlxtlV8SERERuTBFTkBER0dz//33Y7dn18Lcs2cP9957L++++y7t27cv1gBFREREJB8vvgjffgu7dpnt5cuhe3e45hpr45JKad26dVSrVo3GjRuzbt26c67bpUuXUopK5MIt2r7I9TzEJ4Re9XtZGI2IiIhI+VXkBMTs2bOx2+2MGTOGYcOGAbBw4UJmzpzJ7NmzmT9/frEHKSIiIiK5BATAggXQtStk3RjywgvQujXUqGFpaFL5jBgxgquvvprZs2czYsSIAkswGYbB9u3bSzk6kaJJTEtkxZ4Vrvb1Ta7Hx9PHwohEREREyq8iJyB+//13Wrduzd133+1ads8997B69Wq2bdtWrMGJiIiIyDl07AgTJsAzz5jtxER49ll45RVzwmqRUhIZGUnVqlVdz0XKs692fUW6Pd3VVvklERERkQtX5ASEt7c3ycnJeZafOXMGb2/vYglKRERERApp4kRYtgw2bTLb69bBokVw443WxiWVyurVq/N9Xla88847fPjhhxw/fpyGDRsybtw4Onfu7OqPiYnhueee448//iA0NJTbb7+dW2+91dXvcDiYM2cOn376KadPn6ZDhw5MmjSJOnXqWPFypITlLL8U6B3INVEqbSciIiJyoWxF3aBt27b89ddfPPXUU/z+++/8/vvvTJo0id27d9O2bduSiFFERERECuLlZZZi8vXNXjZrFuzfb1VEImXKa6+9xpw5cxgzZgxffPEFrVu35v/+7/84dOgQAKdOnWLEiBHUrVuXzz77jAceeIAZM2bw2Wefue3jww8/5Nlnn+Xjjz/G4XBw1113kZ6eXtBhpZxKSk/im93fuNoDGg/A19P3HFuIiIiIyLkUeQTEww8/zPr16/nkk0/45JNPAHA6nXh7ezNq1KhiD1BEREREzqNpU5g+HbK+i6WlwVNPwTvvgGeRv+6JXJRmzZoV2Ofl5UVYWBjXXHMNjzzySImPoE5OTubtt9/m0UcfpV+/fgBMmDCBTZs2sXnzZurUqcMnn3yCl5cXzzzzDJ6enkRFRXHgwAHeeusthgwZQnp6OvPmzePRRx+lR48eALz00kt069aNlStXct1115Xoa5DSteyvZaRmprraKr8kIiIicnGKPAKiadOmfPzxx3Tv3h1/f38CAwO5/PLLWbBgAc2bNy+JGEVERETkfO6/H66+Orv955/wv/9ZF49UWqGhoXh5eeF0OvM80tPT+eeff5g/fz6zZs0q8Vg2b95MSkoK/fv3dy3z8PDgiy++YODAgQBs2rSJjh074pkjWde5c2f2799PXFwcO3bs4MyZM3Tp0sXVHxwcTPPmzdm4cWOJvwYpXTnLL/l7+dOnYR8LoxEREREp/4p8S9w333xD+/btefPNN0siHhERERG5EDabmXBo2RLi481lc+dC167QooWloUnlMm3aNB544AEmTZrEddddh2EYfPbZZ7z88su89tprVK9enf/85z8sX76ccePGlWgs+/btIyQkhJ07dzJr1iz2799Pw4YNGT16tKt87NGjR2ncuLHbdjVq1ADgyJEjHD16FICIiIg862T1FUVWMqa05EwAybklZyTz9V9fu9r9G/XHz9NP710x0zkpZY3OSSlLdD5KcShr50+RExCTJk2iZs2afPnllyURj4iIiIhcqFq14PXX4eabzbbdDpMmwQcfuM8RIVKCnn/+eVq1asW///1v17Lbb7+dFStW8OKLL7JkyRJatWrFunXrLvpYhw8fplevXgX2P/TQQ6SmpjJp0iTGjBlDZGQkCxcu5LbbbmPp0qVERUWRmpqapxSUj48PAGlpaaSkpADku05CQkKRY05MTMRmK/JA9AvmdDpJTk4GwDCMUjtuefTl7i9Jzkh2tfvW63tBn7Gcm85JKWt0TkpZovNRioPD4bA6BDdFTkBERES4DU8WERERkTLkppvg88/h44/N9oEDMHs2jB1rbVxSaRw6dIjMzEwcDofrQrvD4eDkyZMcOXIEu91OXFxcsfxNER4ezrJlywrs/+6770hNTeWJJ57gyiuvBKBFixZs3bqV999/n6eeegpfX988k0mnpaUB4O/vj+/Z5F16errredY6fn5+RY45ODgYDw+PIm93obLugAsJCdGFjPP45kD25NO+nr4MvWwogd6BFkZUMemclLJG56SUJTofpTjY7XarQ3BT5G/93bt3Z968eVx//fW0b9+eoKAgtzt4HnrooWINUERERESK6NVX4Ycf4J9/zPbChdCtG3TubG1cUik0bdqU33//ndtuu801OmHVqlUcPHiQ5s2b8/nnnxMTE0PTpk0v+lheXl5ERUUV2P/nn38C0KRJE9cywzCIiori8OHDANSsWZNjx465bZfVDg8PJzMz07Wsbt26buvk3G9hGYZR6hcUso6pCxkFS81M5ctd2aP8+zbsS5BPkIURVWw6J6Ws0TkpZYnOR7lYZe3cKXICYu7cuQDs2rWLv/76y7Xc6XRiGIYSECIiIiJWCw2Fd9+Fa67JXvbMM+aoiOBgy8KSyuHxxx/nzjvvZOPGjWzatAkw/1bw8/PjiSeecE3cPHz48BKPpX379hiGwa+//kqfPn1csezevds1qXSHDh34+OOPsdvtrpEJ69evp379+lSrVo2goCACAwPZsGGDKwGRmJjI9u3bueWWW0r8NUjpWLlnJUnpSa720OZDLYxGREREpOIocgJi4MCBZS6LIiIiIiK5XH01jBwJc+aY7WPHYNo0eO45a+OSCq9NmzasXLmSDz74gD179pCZmUnjxo25+eabXSMKFixYQIcOHUo8lsjISIYMGcKUKVPw8/Ojbt26LFiwgMOHD7vmqBgyZAhz585lwoQJ3HXXXWzbto13332XyZMnA+bcD7fccgszZswgNDSUWrVqMX36dGrWrMk1OZN8Uq4t2r7I9dzHw4frGl9nYTQiIiIiFUeRExAvvPBCScQhIiIiIsVt2jRYtQp27jTbK1ZA9+5w7bXWxiUV2vPPP0+bNm0KHBndqVOnUo3n6aefZs6cOUycOJGEhASaN2/OvHnzaNCgAQDVqlVj7ty5PPfccwwaNIjq1aszbtw4Bg0a5NrHgw8+SGZmJhMnTiQ1NZUOHTrwzjvv4OXlVaqvRUpGWmYaX+z8wtW+tuG1BPtotJiIiIhIcSh0AuLIkSMsXbqU2NhYIiMjGThwIDVq1CjJ2ERERETkYvj7w4IF0KULZE1E9sIL0KYN6HuclJBPP/2U33//3VXyyGpeXl6MHj2a0aNHF7hOq1atWLhwYYH9Hh4ejB07lrGazL1C+m7fdySkJbjaQ5up/JKIiIhIcbGdfxXYvHkz/fr145VXXmHhwoW89NJLDBgwwG0OCBEREREpgzp0gCefzG6fPg2TJ4PDYV1MUqF17NiRo0ePEhcXZ3UoIoWSs/ySl82LAU0GWBiNiIiISMVSqBEQ06dPJyUlhcjISFq3bs3mzZuJjY3lv//9L2+88UZJxygiIiIiF+OJJ+Drr+Hs5L9s2ACffgr/+pe1cUmF5OPjw9GjR+nRoweXXHIJgYGBrsmdDcPg/ffftzhCkWwZ9gyW7ljqal8ddTVVfKtYFo+IiIhIRVOoBMSuXbsICwvjiy++IDAwkGPHjjFgwAC2bdtW0vGJiIiIyMXy8jJLMbVpAykp5rJXXoFOneCSSywNTSqeFStWAOBwONi9e7dbn2EYVoQkUqDV+1ZzKvWUq63ySyIiIiLFq1AJiNTUVNq3b09gYCAANWrUoEWLFkRHR5docFlOnjzJZ599RkxMDKNHj6ZOnTqlclwRERGRCqNJE5g+HUaONNtpaTBpEsybB56FnhZM5Lyef/55q0MQKbSc5Zc8bZ7c0PQGC6MRERERqXgK9demw+HA29vbbZmfnx/2rMkMS9Dy5ct57LHHCA4OJj09neXLl3P33XefcxK5119/nVmzZuVZvnPnzgK3WbduHdOnT2fPnj1EREQwatQo+vfv7+pv0qQJALNnz+aaa67Js/2dd97JTz/9xPPPP8/gwYOL8ApFRERESsn998MXX8DKlWZ7+3Z45x24915r45IKZdCgQQX2OZ3OUoxE5NwyHZks2bHE1e5ZvyehfqEWRiQiIiJS8RT6drd//vmHRYsWubUBPvvsM7c/JIYOLb4hqykpKTz++OPcdtttdO3alejoaKKiohg9ejRXXXUVrVu3zne7nTt3csMNNzB27NhCHWfPnj3ce++9jBgxgunTp7NmzRrGjRtHaGgoXbp0ca3n5eXFihUr8iQgTp06xYYNGy74dYqIiIiUCsMwRzxceimcOltyZN48uPxyaNnS2tikwsjIyODjjz9m7969pKWluf5WSE5O5tdff2Xt2rUWRyhiWrt/LSdSTrjaKr8kIiIiUvwKnYCIiYnhySefdFvmdDqZOHGi27LiTEDs2bOH5ORkrr/+euLi4gDo27cvJ06coEqVKgVut2vXLoYNG0b16tULdZz58+fTpEkT16iKqKgotm/fzty5c90SEF26dOH7778nLS0NHx8f1/KVK1fSunVrNmZN7CgiIiJSVtWqBa+/DjfdZLbtdrMU04cfgq+vtbFJhTBt2jQ++OADnE4nhmG43axks9ksjEzEXc7ySzbDxsCmA60LRkRERKSCKlQCokOHDiUdR77CwsIwDIP169fTsGFDwJy4bvjw4QVuk56ezv79+2nQoEGhj7Np0yZ69+7ttqxz584899xzrj+cAHr06MHGjRv58ccf3dZftmwZ/fr1u6AEhNPpLPWh6FnH1BB4KSt0TkpZovNRypoSOSeHDYPPP8f46COzffAgzpdfhnHjiu8Ykj+nM/tRqoctveOtXLkSf39/HnjgAaZPn87o0aOJjY3lww8/ZPz48aUWh8i52B12Fu9Y7Gr3uKQH1QMKdwObiIiIiBReoRIQCxYsKOk48lWzZk1GjBjBlClTaNasGbVr1+bQoUPnnIR69+7d2O12VqxYwXPPPUdaWhodOnRg7Nix1KhRI99tjh49Ss2aNd2W1ahRg5SUFE6dOkVoqFkH1M/Pjx49evDNN9+4EhBxcXFs2bKFl156icmTJxf5NSYmJpb6nWBOp5Pk5GQAV3JFxEo6J6Us0fkoZU1JnZPG1KkErV2L7WxZTePTT0nu0AG7RTeeVBbGmTPYExNxJiSU6nEdDkepHevkyZN07dqVO+64gy+//JJ69epx77338ttvv7F48WJuu+22UotFpCA/HfyJY2eOudoqvyQiIiJSMgpdgskq48ePp2fPnrz77rusXr2aFStWMGDAAKZNm4aHh0ee9Xft2gWYyYKXX36ZEydOMHPmTG699VaWLl2Kbz6lBVJTU/NMsp3VTk9Pd1vet29fHn/8cdLT0/H29mb58uV07NjRlaQoquDg4HxfR0nKugMuJCREF9ekTNA5KWWJzkcpa0rsnAwJgXffhRxzW/lNnw4ffWT2SckICIDg4FJ/j+12e6kdq0qVKvz9999kZGTQqlUr1qxZw9VXX016ejqHDx8utThEziVn+SUDg0HNCp48XUREREQuXJlPQIBZAsrhcNCkSROaNm3Ko48+ymWXXcbMmTPd1vv6668ZOHAg3bt3d0sINGrUiO7du7N69Wr69euXZ/8+Pj55Eg1ZbT8/P7flV155JU6nkx9//JFevXqxbNmyi5r3wjAMSy5wZR1XF9ekrNA5KWWJzkcpa0rsnLz6ahg1CmbPNo9z/DhMmwbPP1+8x5FshpH9KNXDlt7xunbtypdffsmrr75Kp06deOSRR1i1ahXJycnUrVu31OIQKYjD6eCzmM9c7W71ulEzsOY5thARERGRC1WmExCxsbFs3rzZlTQwDINrrrmG7t27s27dOpYuXeq2flaJpdyjEWrUqEGVKlU4evRovseJiIjg2LFjbsuOHTuGv78/QUFBbst9fX3p2bMny5cvp0WLFvz555+8+eabF/MyRURERKzzwguwahXs2GG2V62CK6+EPn2sjUvKrYkTJ3LmzBkaNmzI1VdfzWWXXcZvv/2Gp6cnDz/8sNXhibDu0DqOJB1xtVV+SURERKTklOkERHR0NI8++ijNmjVzWx4XF0eDBg2oV69enm1eeuklli9fzvLly113eh0+fJhTp065JrLOrX379kRHR7stW79+PW3bts13foa+ffsyfvx4GjduzOWXX54nSSEiIiJSbvj7w4IF0KULZGaay6ZNgzZtIDzc2tikXAoODubVV191tT/66CO2b99OzZo1CQsLszAyEVPO8ksAg5sNtigSERERkYqvyLMff/DBByQmJpZELHn07NmT6tWr89hjj7Fv3z7i4+OZNWsWv/32W4Flj66++mr+/vtvnn76afbt28fGjRsZNWoUbdu2pVu3bgCcOXOG48ePu7YZPnw427ZtY8aMGezZs4d58+axfPly7rrrrnyP0a1bN5xOJ2+88Qb9+/cv/hcuIiIiUprat4cnn8xunz4NkydDKU5cLOXbP//8U+Dj6NGjhIaGkp6ezj9nJz0XsYrD6WBRTHYComudrtQKrmVhRCIiIiIVW5FHQDz77LNMmzaNq666ikGDBtGtW7cSm0Q5ICCAefPmMWXKFKZMmQJAVFQUc+bMoW3btvlu07JlS95++21efvllBg8ejLe3N7169WL8+PGuERHz5s1jzpw57Ny5EzDniHjttdeYPn068+fPp3bt2kyfPp0uXbrkewwfHx969erFqlWruOqqq0rglYuIiIiUsieegK+/hqxRodHR8MkncNNN1sYl5ULPnj0LNc+EYRhs3769FCISyd/GvzdyODF7MnSVXxIREREpWUVOQHTt2pXo6GhWrFjBypUrCQ0NZcCAAQwcOJCmTZsWe4CNGzfmvffeY/369a7RDOfTpUuXApMHAKNGjcqzn+7du9O9e/cCt8lKVmSZPn36edcRERERKTc8Pc1STK1bQ0qKuWz2bOjcGS65xMrIpBzx9/cnJCTE6jBECpS7/NKQ5kMsikRERESkcihyAmLevHnEx8ezatUqli9fzoYNG5g/fz7z58+nUaNG3HDDDQwePJiqVasWa6C1a9cu1F1VIiIiInKBGjeGGTPggQfMdlqaWZrpf/8zExQi5+B0OklOTiYyMpJOnTrRqVMnOnToQJUqVawOTQQwz9Gc5Zc61upI3ZC6FkYkIiIiUvEVeQ4IgCpVqnDjjTfyzjvv8Morr1C9enWcTie7du1ixowZXH311WzYsKFYA61duzadOnUq1n2KiIiISC7/939w7bXZ7ZgYeOcd6+KRcuGdd97hrrvuonnz5uzZs4f333+fBx98kK5duzJw4ECef/55Vq9eXWpzyYnkZ8uRLeyP3+9qq/ySiIiISMm7oFvZfv/9d5YtW8by5cs5evQoTqcTHx8fevbsye7du/nrr7+YNm0aixcvLu54RURERKQkGQbMmweXXgonT5rL5s2Dyy+Hli2tjU3KrMsvv5zLL78cgMTERNavX8+6detYt24dO3bsYOfOnbz33nvYbDb+/PNPi6OVyip3+aWhzZWAEBERESlpRU5AXH311Rw+fBin0wlA8+bNGTJkCAMGDCA4OBin08mQIUPYs2dPsQcrIiIiIqUgMhJefx3+9S+zbbfDpEnwwQfg52dtbFLmBQcH0759e9LT00lNTeXkyZOukQ8Oh8Pi6KSyyl1+qV1EO+pXrW9hRCIiIiKVQ5ETEIcOHaJq1aoMGDCAIUOG0KRJE7d+wzCoW1d1NEVERETKtWHD4IsvzKQDwMGD8MorMH68tXFJmZSamkp0dDTr1q3jl19+YdeuXQCum5YaNmxIx44dVVJVLLMtdhu7T+52tTX6QURERKR0FDkB8corr3DVVVfh5eVV4DqzZs26mJhEREREpCyYMwfWroXDh832p59Ct27Qtau1cUmZ0759e+x2O2AmHaKiolwJh44dOxIaGmpxhFLZ5S6/NKTZEIsiEREREalcCpWAWLdunet5UFAQmzZtKnDdLl26XHxUIiIiImK9KlXg3Xehd+/sZc88Ax9/bPaJnJWZmYlhGAQEBNCuXTtCQ0NJTU1l7dq1rF271rWeYRhMnTrVwkilMnI6nXy6/VNX+7Lwy2hUrZGFEYmIiIhUHoVKQIwYMQLDMM67nmEYbN++/aKDEhEREZEyolcveOghePllsx0XB9OmwdSp5oTVImc5nU6SkpLcEg65KQEhVvjz+J/sPLHT1Vb5JREREZHSU6gERGRkZEnHISIiIiJl1fPPw8qVEBNjtletgiuvhD59rI1Lyoznn3/e6hBECpS7/JISECIiIiKlp1AJiNWrV5d0HCIiIiJSVvn5wYIF0LkzZGaay154AVq3hpo1LQ1NyoZBgwZZHYJIgXImIFpUb0HTsKYWRiMiIiJSudisDkBEREREyoF27eCpp7LbSUnmfBAOh3UxiYicR8zxGP48/qerrdEPIiIiIqWrUCMgcjp48CDPPPMMmzdvJjU11a1Pc0CIiIiIVGCPPQZffw3r15vt6Gj45BO46SZr4xIRKcBnMZ+5tZWAEBERESldRR4BMXHiRH766SdSUlJwOp1uD4fugBMRERGpuDw94b33wN8/e9ns2bBvn3UxiYicQ87yS02qNaFF9RYWRiMiIiJS+RR5BMSvv/5KYGAgM2bMoF69enh4eJREXCIiIiJSFjVqBP/9L/zf/5nttDSYNAn+9z8zQSEiUkb8deIvfov9zdUe2nwohmFYGJGIiIhI5VPkERARERG0atWKHj16UL9+ferWrev2EBEREZEK7t57oW/f7HZMDMyda108Uqb06tWLp3LOF3LWPffcQ79+/SyISCorlV8SERERsV6Rb1MbM2YMEyZM4M8//6RFCw1fFREREal0DAPeeQdatoSTJ81l8+bB5ZfDpZdaG5tY4ttvv+XPP82Jfv/++2+io6N5+eWXXf0Oh4M//viDM2fOWBWiVEI5yy9FVY3isvDLLIxGREREpHIqVAKiR48ebu3U1FSGDh1KcHAwfn5+ruWGYfD9998Xa4AiIiIiUgZFRMCbb8KNN5pth8MsxfThh5Dj+6FUDpGRkTz44IM4nU4Mw2D//v288cYbbus4nU5atWplUYRS2ew7tY/NRza72iq/JCIiImKNQiUgjh49mu/yhIQEEhISXG19oRMRERGpRIYOhVtugfffN9uHDsHLL8Njj1kbl5S65s2b8+ijj/LXX3+xZMkSIiIi6Ny5s6vfMAyqVavGsGHDLIxSKhOVXxIREREpGwqVgHjvvfdKOg4RERERKY9mz4Y1a+DwYbO9aBF062aWY5JK5Y477gDMkQ4tWrRg+PDhFkcklVnO8kv1QurRLqKdhdGIiIiIVF6FSkB07NjR9Xzjxo1UrVqVhg0buq0THR1NSkpK8UYnIiIiImVblSowfz706pW97JlnYOFCs08qBYfDgc1mA2Dq1KmuZfnJWk+kpBxMOMiGvze42iq/JCIiImKdIn/7Hz58uNuEclnmzJnDYxpuLyIiIlL59OwJDz+c3T5xAp5/HpxOy0KS0tWiRQtGjRrlel7Qo2XLlhZHKpXB4pjFbm2VXxIRERGxTqFGQMybN8+tDNOPP/7oNjG1w+Hg2LFjBAUFFXuAIiIiIlIOTJ0KK1ZATIzZ/u47+OYb6NfP2rikVDidTpxnE07OcySeztUnUlxyll+qHVybjrU6nmNtERERESlJhUpADBs2jLfffptTp05hGAapqan5Tkx93XXXFXuAIiIiIlIO+PmZk1F36gSZmeayF1+Etm2hZk1rY5MSt3TpUmrUqAHAd999Z3E0Upn9nfg3Px/62dUe0mwINkNlv0RERESsUqgERGBgIB9++CHHjh3jtttuo127djz00EOufpvNRmhoKA0aNCixQEVERESkjGvbFp5+GiZONNtJSWb7tddAdf8rtFGjRtGwYUNef/115syZQ4sWLbjlllusDksqoSU7lri1b2x+o0WRiIiIiAgUMgEBUL9+ferXr897771H1apVadSoUUnGJSIiIiLl0fjx8NVXsH692d60CT7+GP79b2vjkhJ15MgRqlatSnp6OkuWLOH06dP8u4DPXJNQS0nKWX4pIjCCLnW6WBiNiIiIiBQ6AZGlY8eObNq0iblz55KWlpanjuvIkSOLLTgRERERKWc8PWHBArjsMkhONpfNmQOdO4NGy1ZY1atX5/fff+eyyy4DzDJMLVq0yLOeYRhs3769tMOTSiI2KZYfDvzgaqv8koiIiIj1ipyAePXVV5kzZ06e5U6nE8MwlIAQERERqewaNoSZM+G++8x2ejo8+SS8+y54eVkampSM+++/n8mTJ5OZmYlhGAVONq1JqKUkLY5ZjJPsc2xo86EWRiMiIiIicAEJiA8//BCn00mjRo1o2LAhnp5F3oWIiIiIVHT33ANffAHLlpntnTvh7bfh/vutjUtKxI033siAAQM4efIkPXv25PLLL+eZZ56xOiypZBbFZJdfqhFQgyvqXmFhNCIiIiICF5CASE5OpnHjxixdulT1W0VEREQkf4YBc+fCpZfCiRPmsnffhSuugFatLA1NSoavry+RkZGuOeNq1apldUhSiRw/c5w1+9e42oObDsbD5mFdQCIiIiICQJEzCFdeeSVOp1PJBxERERE5t4gIePPN7LbDAZMmZc8NIRVSx44dyczM5M4776R169a0adOGu+++mx07dlgdmlRgS3csxeF0uNoqvyQiIiJSNhR5BESfPn2YNGkS9913H127dsXPzw/DMFz9Q4fqi56IiIiInDVkCAwfbk5MDXD4MMyaBU88YWlYUnJ27NjBv//9b1JSUlzLfvzxRzZv3szHH39M48aNLYxOKqqc5Zeq+VXjykuutDAaEREREclS5ATEww8/jGEYrF27lrVr1+bpVwJCRERERNzMng1r18LBg2Z78WLo3t0sxyQVzksvvURKSgo33XQTw4YNA2DhwoUsXLiQmTNn8sYbb1gcoVQ0J5JP8N3e71ztQU0H4WnTXIUiIiIiZUGRv5V16NChJOIQERERkYoqJMSc/6Fnz+xlzzwDn3wCVapYFZWUkE2bNtG0aVOefvpp17LJkyfz66+/snHjRusCkwrri51fYHfaXW2VXxIREREpO4qcgFiQNXxeRERERKSwrroKRo+Gl14y2ydPwtSpMG2aOWG1VCg+Pj6FWlYazpw5w4wZM1i1ahWpqam0adOGxx57jKioKNc669atY/r06ezZs4eIiAhGjRpF//79Xf1paWm88MILLF++nNTUVHr27MmECRMIDQ214iVJLjnLL1X1rUrP+j3PsbaIiIiIlKYLnkl669atvP3228ydO5dt27YVZ0wiIiIiUhFNnQrNm2e3V6+GZcusi0dKRIsWLdi2bRtvvfUWJ0+e5OTJk7z55pts27aNSy+9tNTjefbZZ9mwYQOvvPIKCxcuxMPDg7vuuou0tDQA9uzZw7333ku3bt1YvHgxN954I+PGjWPdunWufTz99NP89NNPzJ49m/nz57N3714efPDBUn8tkld8ajyr9qxytW9oegNeHl4WRiQiIiIiORV5BITdbmfcuHEsy/XH4vXXX88LL7zgNiG1iIiIiIiLry+8/z506gQZGeayF1+Edu2gZk1rY5Ni88ADDzBixAheeuklXsoa8QLYbDbuvffeUo/n22+/5aGHHqJt27aAOafdDTfcwO7du2nRogXz58+nSZMmjB49GoCoqCi2b9/O3Llz6dKlC7GxsSxdupQ33niD9u3bAzBz5kz69OnD1q1badOmTam/Jsn25c4vyXBkuNpDm6n8koiIiEhZUuQREG+//TZff/01vr6+9OjRgx49euDr68sXX3zB3LlzSyJGEREREako2rSByZOz22fOwNNPg8NhWUhSvDp16sSbb75JVFQUTqcTp9NJvXr1mDVrFl26dCn1eKpVq8ayZcs4ceIE6enpLFq0iCpVqlC3bl3AnLMid1ydO3dm8+bNOJ1ONm/e7FqWpX79+oSHh2tOizIgZ/mlYJ9gejfobWE0IiIiIpJbkUdALF68mKCgIBYvXkydOnUAOHjwIIMHD2bRokXcfffdxR6kiIiIiFQg48bBV1/BL7+Y7U2b4KOP4D//sTYuKRZbtmyhc+fOfPXVVyQkJGCz2QgKCrIsnueee45x48bRtWtXPDw88Pf3Z968ea6Yjh49Ss1cI3Bq1KhBSkoKp06dIjY2lqpVq+aZw6JGjRocPXq0yPFkJWVKS9bxSvOYpSUxLZEVu1e42tc3vh5vD+8K+Vorkop8Tkr5pHNSyhKdj1Icytr5U+QExJEjR+jQoYMr+QBQt25dLr30UjZt2lSswYmIiIhIBeThAe+9B5ddZo6AAHj1VejcGXJMDCzl0//93/8RGRnJkiVLCAkJKdFjHT58mF69ehXYv27dOnbu3EmdOnWYMmUK/v7+vP3224wcOZKFCxcSERFBamoq3t7ebttltdPT00lJScnTD+ak2lnzSBRFYmIiNtsFT8VXZE6nk+TkZIAKVy530c5FpNmzP4O+9fqSkJBgYURSGBX5nJTySeeklCU6H6U4OMrY6PIiJyCqV69OTEwM8fHxVKlSBYCTJ08SExNDjRo1ijs+EREREamIoqLgpZfgnnvMdno6PPkkzJ8PXppAtjwLDg7Gz8+vVI4VHh6eZ266nPbt28ezzz7L6tWriYyMBGDWrFn07duXefPmMWHCBHx8fEhPT3fbLqvt5+eHr69vnn6AtLS0C3qdwcHBeHh4FHm7C5V1B1xISEiFu5Dxzf5vXM8DvQMZeOlA/LxK59yTC1eRz0kpn3ROSlmi81GKg91utzoEN0VOQPTt25d33nmH66+/nt69zfqa3377LQkJCQwZMqTYAxQRERGRCuquu+CLL8xyTAC7dsFbb8EDD1gbl1yUQYMGMWfOHO677z46dOhAUFCQ2x3/Q4cW3yTBXl5eRJ1j1Mw777xDtWrVXMmHrG2aN2/OgQMHAIiIiODYsWNu2x07dgx/f3+CgoKoWbMm8fHxpKenu42EOHbsGOHh4UWO2TCMUr+gkHXMinQhIyk9iWW7s5NP1zW+Dn9vfwsjkqKoiOeklG86J6Us0fkoF6usnTtFTkCMGjWK3377jU2bNvHRRx+5MnMtW7bkAf2xKCIiIiKFZRjw9tvQsiWcOGEumz8frrjCLM8k5dIrr7yCYRisXbuWtWvX5ukvzgTE+dSsWZNTp05x7Ngx12hth8PB7t27ueKKKwBo37490dHRbtutX7+etm3bYrPZaNeuHQ6Hg82bN7smq963bx+xsbF06NCh1F6LuPvmr29IzUx1tYc2K73zSkREREQKr8gJCF9fX9577z1WrlzJpk2bsNlsXHbZZVxzzTV4abi8iIiIiBRFzZrmqIeskbQOB0yaZE5K7a+7mcujsnRR/qqrrqJOnTo8+OCDPP744wQGBjJv3jyOHDnCrbfeCsDw4cMZNGgQM2bMYNCgQaxdu5bly5czd+5cwCzz1L9/fyZOnMjUqVPx8/PjqaeeomPHjrRu3drCV1e5LYpZ5Hru7+VP30Z9LYxGRERERApS5AQEgM1mo0+fPvTp06e44xERERGRymbwYLjtNnP0A8Dff5vzQ0yYYG1cckEWLFhgdQgu/v7+vPfee7z44os88MADpKWlcemll/LRRx9Ru3ZtABo1asRrr73G9OnTmT9/PrVr12b69Omu0Q4Azz77LFOnTmXkyJEAdO/enYkTJ1rymgSSM5L5etfXrnb/Rv3x91LCUkRERKQsKlQC4vHHHy/UzgzDYOrUqRcVkIiIiIhUQi+/DN9/DwcPmu0lS6B7d+jWzdq4pNBSUlJYtWoVsbGx1KpVi549e+Lr62t1WISHh/Pf//73nOt0796d7t27F9jv7+/PlClTmDJlSnGHJxdgxe4VnMk442oPba7ySyIiIiJlVaESEEuWLHFNXpE150N+lIAQERERkQsSEgLvvQdXXQVZ3zeffRYWLoSqVa2NTc5rz5493HbbbZzImssDqF27Nu+99x4REREWRiYVUc7yS76evvRr1M/CaERERETkXIpUgikwMJB27drRsWNHquoPQREREREpTldeCY88All3q588CVOnwosvmhNWS5n13HPPERcXh7+/P40aNWLXrl0cPnyY6dOnM3PmTKvDkwokNTOVL3d+6Wr3bdiXQO9ACyMSERERkXMpVAKidevW/PHHH5w+fZq1a9fyww8/0LBhQzp16kSnTp3o0KEDISEhJR2riIiIiFR0U6bAihXwxx9m+/vv4euv4brrrI1Lzmnbtm0EBwfzxRdfULNmTfbs2cPQoUOJjo62OjSpYFbuWcnp9NOutsoviYiIiJRthUpAfPzxx5w5c4aNGzeybt06fvnlF/766y927drF+++/j2EYNGnShE6dOvHYY4+VdMwiIiIiUlH5+sKCBdCxI2RkmMteeMEs0VS9uvu6VapAzZqlHqLklZKSQpcuXah59vOIioqiVatWbNmyxeLIpKJZtD27/JK3hzfXNVZyUkRERKQsK3QJpoCAAHr06EGPHj0AOHnyJIsWLWLu3LkkJiYSExPDjh07lIAQERERkYvTurVZimnaNLOdmgqjR+ddz9sbFi9WEqIMsNvt+Pj4uC0LCAggMzPTooikIkrLTOOLnV+42tdGXUuwT7CFEYmIiIjI+RRpDoikpCTWr1/Pzz//zC+//MLBgwfdJqVu2LBhsQcoIiIiIpXQkCHZCYiCpKdDfLwSEGXEqVOnWLdunVsbYP369W5/M3Tp0qXUY5OK4bt935GQluBqq/ySiIiISNlXqATESy+9xLp16/jzzz9xOByuPyAaNmxIx44dXY/Q0NASDVZEREREKialEiUAAQAASURBVAkPD6sjkCLaunUrd9xxR57lI0aMcD03DIPt27eXZlhSgeQsv+Rl82JA4wEWRiMiIiIihVGoBMSbb76JYRgEBATQrl07V8KhWrVqrnVSU1P5559/iIyMLLFgRURERESk7NHfAFLSMuwZLN2x1NXu3aA3Vf2qWheQiIiIiBRKkUownTlzhh9++IEffvgh337d0SQiIiIiUvmsXr3a6hCkgvt+//ecSj3laqv8koiIiEj5UKgEhO5oEhEREREREavkLL/kYXhwQ5MbLIxGRERERAqrUAkI3dEkIiIiIiIiVsh0ZLJkxxJXu2f9nlTzr3aOLURERESkrLBZHYCIiIiIiIhIQX448ANxyXGutsoviYiIiJQfSkCIiIiISNkTFga+vudex9sbqlQplXBExDo5yy/ZDBsDmw60LhgRERERKZIiTUItIiIiIlIq6taFnTsh7uxdz3v2wLBh2f3DhsGtt0LNmtbEJyKlwu6wszhmsat9Zb0rqRFQw8KIRERERKQolIAQERERkbKpbl3zAdCmDTRsCLt3m+0//1TyQaQS+PnQz8SeiXW1VX5JREREpHxRCSYRERERKfsMAwYNym7/+SccO2ZdPCJSKnKWXzIwGNR00DnWFhEREZGyRgkIERERESkfBg50b69da0kYIlI6HE4Hn8V85mpfUfcKIoIiLIxIRERERIpKCQgRERERKR86d4bw8Oz2mjWWhSIiJW/94fX8c/ofV1vll0RERETKHyUgRERERKR8sNnghhuy25s2QWKidfGISInKWX4JYHCzwRZFIiIiIiIXSgkIERERESk/cs4DYbfDzz9bF4uIlBin0+mWgOhapyu1g2tbGJGIiIiIXAglIERERESk/LjqKggKym5//711sYhIidn4z0YOJR5ytYc2U/klERERkfJICQgRERERKT98fKB//+z2unWQmmpdPCJSIj7981O39pDmQyyKREREREQuhhIQIiIiIlK+DByY/TwlBaKjLQtFRIqf0+lkUUx2+aWOtTpSN6SuhRGJiIiIyIVSAkJEREREype+fcHbO7u9Zo1loYhI8dtyZAv74/e72iq/JCIiIlJ+KQEhIiIiIuVLcDD06pXd/uEHyMy0Lh4RKVY5J58GlV8SERERKc+UgBARERGR8mfQoOzn8fGwbZtloYhI8cldfqltRFsaVG1gYUQiIiIicjGUgBARERGR8uf668Ewstvff29dLCJSbLbFbmP3yd2utsoviYiIiJRvSkCIiIiISPkTHg5du2a316wBp9OycESkeKj8koiIiEjFogSEiIiIiJRPAwdmPz9yBHbtsiwUEbl4TqeTT7d/6mq3Cm9F42qNLYxIRERERC6WEhAiIiIiUj7lTECAOQpCRMqt7ce3s/PETldb5ZdEREREyj8lIERERESkfGrYEFq2zG5rHgiRci13+aWhzZWAEBERESnvlIAQERERkfJr0KDs57t3w+HD1sUiIhdlUUx2AqJ59eY0q97MwmhEREREpDgoASEiIiIi5ZfKMIlUCDvidvDHsT9cbZVfEhEREakYlIAQERERkfKrTRuoWze7rQSESLn02fbP3NoqvyQiIiJSMSgBISIiIiLll2G4j4L47Tc4edKycETkwuQsv9S4WmNa1mh5jrVFREREpLxQAkJEREREyrec80A4nfDDD9bFIiJFtvvkbn49+qurPbTZUAzDsC4gERERESk2SkCIiIiISPl2xRUQGprdVhkmkXJF5ZdEREREKi4lIERERESkfPP0hAEDstsbNsCZM9bFIyJFkrP8UoOqDWhds7V1wYiIiIhIsVICQkRERETKv5xlmDIyYN0662IRkULbH7+fTf9scrVVfklERESkYrE8AXHy5EnefvttHnnkEQ4dOmR1OCIiIiJSHl19Nfj5ZbdVhkmkXMhdfunGFjdaFImIiIiIlARLExDLly+nZ8+eLFiwgF9++YVrr72Wl156qVDbpqWlcf3117N48eI8fR988AG9evWiVatW/Pvf/2b79u3n3dfkyZPp0qULbdq0YcyYMZw8edLVP3v2bJo0acKAnEP7c/j1119p0qQJPXv2LFTsIiIiIlLM/P2hT5/s9k8/mSMhRKRMy1l+qV5IPdpFtLMwGhEREREpbpYlIFJSUnj88ce57bbbmD59Ov/5z3+YMWMGb7zxBr/++us5tz19+jT3338/O3fuzNO3ZMkSXnzxRR566CEWL15M7dq1GTFihFtCIbenn36an376idmzZzN//nz27t3Lgw8+6LaOl5cXu3btYt++fXm2X7ZsmYYJi4iIiFht4MDs50lJsHmzZaGIyPkdSjjE+sPrXe2hzVV+SURERKSisSwBsWfPHpKTk7n++utdy/r27cvEiROpUqVKgdutXr2a66+/nlOnTuXb/8Ybb3DLLbdw/fXX07BhQ6ZOnYqfnx+ffvppvuvHxsaydOlSJk6cSPv27WnVqhUzZ85k48aNbN261bVejRo1aNiwIcuXL3fb3ul0snz5ctq3b1+EVy8iIiIixe6668DDI7v9/ffWxSIi5/VZjHv5paHNh1oUiYiIiIiUFMsSEGFhYRiGwfr12Xe8GIbB8OHDueSSSwrc7ttvv+Wmm27i448/ztN34sQJ9u/fT5cuXVzLPD09ad++PRs3bsx3f5vP3hnXuXNn17L69esTHh6eZ5s+ffrkSUBs3rwZh8NBhw4dCn6xIiIiIlLyQkPhyiuz22vWgMNhWTgicm6LtmeXX6odXJuOtTpaGI2IiIiIlARPqw5cs2ZNRowYwZQpU2jWrBm1a9fm0KFD1KlT55zbTZ06tcC+o0ePAhAREeG2vEaNGuzYsSPfbWJjY6latSo+Pj55tsnaX5Z+/foxZ84c9u/f70qSfP311/Tp0web7cJyOU6nE6fTeUHbXqisY5b2cUUKonNSyhKdj1LW6JwsooEDMVavNp+fOIHzjz/g0kutjSknpzP7UaqH1fkjZcvfiX/z86GfXe0hzYZgMyydolBERERESoBlCQiA8ePH07NnT959911Wr17NihUrGDBgANOmTcMj5/D5QkpJSQHA29vbbbmPjw9paWkFbpN7/YK2iYqKonHjxixfvpz77rsPu93OihUrePXVV/npp5+KHC9AYmLiBScvLpTT6SQ5ORlANValTNA5KWWJzkcpa3ROFo1x1VWE5Ginr1pFev36lsWTm3HmDPbERJwJCaV6XIdGgkgZs2THEre2yi+JiIiIVEyWJiAAOnTogMPhoEmTJjRt2pRHH32Uyy67jJkzZ7qt9/XXXxMZGXnOffn6+gKQnp7utjwtLQ0/P78Ct8m9/rm26dOnDytWrOC+++4jOjoaX19f2rRpc8EJiODg4AtKtlyMrDvgQkJCdCFDygSdk1KW6HyUskbnZBGFhOBs3x5j0yYAvH/+Ge/Ro6GsvHcBARAcDCEh51+3GNnt9lI9nsj55Cy/FBEYQdc6XS2MRkRERERKimUJiNjYWDZv3ky/fv0A846+a665hu7du7Nu3TqWLl3qtn6NGjXOu8+s0kvHjh0jKirKtfzYsWOEh4fnu03NmjWJj48nPT3dbSREQdv069ePV155hQMHDrBs2TJX/BfKMAxLLiZkHVcXMqSs0DkpZYnORylrdE4W0cCBcDYBYRw8CAcOQFkZBWEY2Y9SPazOHSk7YpNi+eHAD6724GaDVX5JREREpIKy7FtedHQ0o0ePZt++fW7L4+LiqFKlCvXq1XN7eHqeP1dSrVo16tevz4YNG1zLMjMz2bRpU4GTRLdr1w6Hw+GajBpg3759xMbG5rtN/fr1adq0KcuWLWPlypX079+/sC9ZRERERErDoEHu7e+/tyYOEcnXkh1LcJI9L4nKL4mIiIhUXJYlIHr27En16tV57LHH2LdvH/Hx8cyaNYvffvuNoUMv/AvoHXfcwf/+9z+WLFnC7t27eeKJJ0hNTXXb5/Hjxzlz5gwA4eHh9O/fn4kTJ7Jhwwa2bdvGI488QseOHWndunW+x+jbty9z584lNDSUZs2aXXCsIiIiIlICmjWDRo2y22vWWBaKlK5Jkybx2GOP5Vm+bt06Bg8ezGWXXUafPn34+uuv3frT0tKYPHkyXbp0oU2bNowZM4aTJ08WaR9SeDnLL1X3r063ut0sjEZERERESpJlCYiAgADmzZuHj48PU6ZMYeHChXz//ffMmTOHtm3bXvB+hw0bxoMPPsisWbMYMmQIf//9N//73/8IDQ11rXPFFVcwb948V/vZZ5+lS5cujBw5kjvvvJMGDRrwyiuvFHiMfv36kZSUdNHll0RERESkBBiG+yiI7dshNta6eKTEORwOZs6cycKFC/P07dmzh3vvvZdu3bqxePFibrzxRsaNG8e6detc6zz99NP89NNPzJ49m/nz57N3714efPDBIu1DCuf4meOs2b/G1R7cbDAettKdE09ERERESo/hzJrZ0ELr169n48aNjBo1yupQSo3dbufXX3+ldevWlkxCnZCQoMkspczQOSllic5HKWt0Tl6gdeuga45JbceNg2HDrIsny6FD0KYN1KtXqoe18rtnSduzZw8TJkzgwIED+Pr60qlTJ1544QVX/6RJk4iJieHTTz91LRszZgzx8fG88847xMbG0qNHD9544w2uvPJKwCzJ2qdPHz7++GPatGlz3n0UhlWfQVn7GTJ3y1zu/vJuV3vV8FX0btDbwoiktJW1c1JE56SUJTofpTiUte/+ZWKmr9q1a9OxY0erwxARERGRiqJTJ6hZM7uteSAqrPXr1xMVFcVXX31F7dq18/Rv2rSJLl26uC3r3Lkzmzdvxul0uuaC69y5s6u/fv36hIeHs3HjxkLtQwovZ/mlan7VuLLelRZGIyIiIiIl7fwzO5eC2rVr5/vHgoiIiIjIBbHZ4IYb4M03zfbmzZCYCMHB1sYlxe4///nPOfuPHj1KzZzJKKBGjRqkpKRw6tQpYmNjqVq1Kj4+PnnWOXr0aKH2kbPc6/k4nc5STVpkHa8sJEpOppzku33fudo3NL0BT5tnmYhNSk9ZOidFQOeklC06H6U4lLXzp0wkIEREREREit2gQdkJCIcDfvwR+ve3NiYpksOHD9OrV68C+9etW3fei/+pqal4e3u7Lctqp6enk5KSkqcfwMfHh7S0tELtoygSExOx2UpvILrT6SQ5ORnA8lIOC7f/P3t3HhfT/v8B/NW+KEW0kCUhS1QIIUu2ZKuu9bq2L67lkuVa4tp3l2vncq9rdxGyJ8ulbBHJTsgeJUuU9pn5/dFvTjMtmlLNVK/n4+Ghs8yZ90yfZj7nvM/n/dmLVHGqsNypcid8/vxZiRGRMqhSmyQC2CZJtbA9Un4Qi8XKDkEOExBEREREVDy1aZM24uHLl7TlgAAmIIoYMzMz+Pn5ZbvdyMgox2Po6OhkShJIl/X09KCrq5tlEiEpKQl6enoKHSM3SpcuXehzQABQiVrSfs/Tf5fGusboatsV2hqZkz9UvKlSmyQC2CZJtbA9Un4QiUTKDkEOExBEREREVDxpa6clHHbvTlsOCgISEwFdXeXGRQrT0tKCtbX1dx3DwsIC7969k1v37t076Ovrw9DQEObm5oiJiUFycrLcKId3797BzMxMoWPkhpqaWqFfUJA+pzIvZHxO/IxT4aeE5e423aGjqfONR1BxpgptkkgW2ySpErZH+l6q1nZUYhJqIiIiIqIC4e6e/nNiInD1qtJCIeVo1KgRgoOD5dZduXIFDRo0gLq6Oho2bAixWCxMRg0Az549Q1RUFBwdHRU6BuXs6KOjSBGnCMs96vRQYjREREREVFjYWyYiIiKi4qtTp7SREFIBAUoLhZSjf//+uH37NpYtW4bw8HBs3rwZ/v7+GDp0KIC0Mk+dO3fG9OnTcfXqVdy+fRsTJkxA48aNYW9vr9AxKGf77+8Xfi6tUxrtq7VXYjREREREVFiYgCAiIiKi4svQEGjXLn35/HkgNTX7/anYqVGjBtavX4/AwEC4u7tj3759WLp0KZycnIR95s2bBycnJ4wePRpDhgxBtWrVsHr16lwdg7IXmxQL/yf+wnI3m24sv0RERERUQnAOCCIiIiIq3jw8AOlExp8/AzdvAo0aKTUkKhg7duzIcn3Lli3RsmXLbB+nr6+P+fPnY/78+dnuk9MxKHvHHx9HkihJWO5Rm+WXiIiIiEoKjoAgIiIiouKta1dAdiK2wEDlxUJUAu27v0/42UDbAB2sOygxGiIiIiIqTExAEBEREVHxZmYGNG+evnz2LCCRKC8eohIkLjkOfo/9hOUuNbtAT0tPiRERERERUWFiAoKIiIiIij939/Sfo6KAsDClhUJUkpx4fAKJqYnCMssvEREREZUsTEAQERERUfEnm4AAWIaJqJDsf7Bf+FlfSx+danRSYjREREREVNiYgCAiIiKi4s/aGqhXL3357FnlxUJUQsSnxOP4o+PCslsNN+hr6SsxIiIiIiIqbExAEBEREVHJ4OGR/nN4OPD6tfJiISoBTj45ia8pX4Vlll8iIiIiKnmYgCAiIiKikiFjGaaAAGVEQVRiyJZf0tXUhVsNNyVGQ0RERETKwAQEEREREZUM9vZAlSrpy+fOKS0UouIuMTURR8OOCsuu1V1hqGOoxIiIiIiISBmYgCAiIiKikkFNTX4UxO3bwIcPSguHqDg7HX4ascmxwjLLLxERERGVTExAEBEREVHJITsPhEQCXLigvFiIijHZ8kvaGtroUrOLEqMhIiIiImVhAoKIiIiISo7mzQETk/RllmEiynfJomQcfnhYWO5g3QFGukZKjIiIiIiIlIUJCCIiIiIqOTQ1gW7d0peDg4GvX5UXD1Ex9N/T//A56bOwzPJLRERERCUXExBEREREVLLIzgORkgJcvqy0UIiKo/3308svaaproptNt2/sTURERETFGRMQRERERFSytG8P6OunLwcEKC0UouImRZSCQ2GHhOV21dqhjF4Z5QVERERERErFBAQRERERlSx6eoCra/ryxYtpIyGI6LsFPA/Ax4SPwjLLLxERERGVbExAEBEREVHJI1uG6etX4Pp1pYVCVJzIll/SUNNA91rdlRgNERERESkbExBEREREVPJ06QJoaKQvnzunvFiIiolUcSoOPjwoLLexaoNy+uWUGBERERERKRsTEERERERU8pQpA7Runb4cGAiIxUoLh6g4uPDiAqLjo4Vlll8iIiIiIiYgiIiIiKhk8vBI//nDB+DuXeXFQlQMyJZfUldTh0dtj2/sTUREREQlARMQRERERFQydc9Qmz4gQClhEBUHIrEIvg99heVWVVrBtJSpEiMiIiIiIlXABAQRERERlUyWloCjY/ryuXOARKK8eIiKsEuvLiEyLlJY7lGH5ZeIiIiIiAkIIiIiIirJ3N3Tf371Cnj2TGmhEBVlsuWX1KAGj1osv0RERERETEAQERERUUnmkeEi6blzyomDqAgTS8Q48OCAsNyicgtYGFooMSIiIiIiUhVMQBARERFRyVWrFlCzZvoy54EgyrUrr6/gTewbYZnll4iIiIhIigkIIiIiIiq51NTkR0E8eABERma/PxFlIlt+CQA8a3sqKRIiIiIiUjVMQBARERFRySY7DwQABAYqJQyiokgikcglIJwsnWBZ2lKJERERERGRKmECgoiIiIhKtsaNAQuZevWcB4JIYdfeXMOrL6+EZZZfIiIiIiJZTEAQERERUcmmrg50756+fOMG8Pmz8uIhKkIyll/6ofYPSoqEiIiIiFQRExBERERERLLzQIjFwIULyouFqIjIWH7JsYIjqhhXUWJERERERKRqmIAgIiIiImrdGjAySl8OCFBWJERFRmhkKJ7FPBOWWX6JiIiIiDJiAoKIiIiISFsb6Nw5fTkoCEhMVF48REUAyy8RERERUU6YgCAiIiIiAgB39/Sfk5KAK1eUFgqRqpNIJNh3f5+w7GDuAOuy1kqMiIiIiIhUERMQREREREQA4OoK6OikL7MME1G27ry7gycfnwjLLL9ERERERFlhAoKIiIiICAAMDYF27dKXz58HUlOVFw+RCstYfokJCCIiIiLKChMQRERERERSHh7pP3/5Aty8qbRQiFSZbAKinmk91DSpqcRoiIiIiEhVMQFBRERERCTVtSugLtNFZhkmokzuR9/Hg/cPhGWOfiAiIiKi7DABQUREREQkZWoKNG+evnzuHCCRKC8eIhXE8ktEREREpCgmIIiIiIiIZLm7p/8cFQWEhSktFCJVJJuAqF2uNuqUr6PEaIiIiIhIlTEBQUREREQkSzYBAaSNgiAiAEDY+zDceXdHWOboByIiIiL6FiYgiIiIiIhkVasG1K+fvsx5IIgEBx4ckFvuWaenkiIhIiIioqKACQgiIiIioow8PNJ/Dg8HXr1SXixEKmTf/X3CzzVNasLW1FaJ0RARERGRqmMCgoiIiIgoo4xlmDgKgghPPj7BzcibwnKP2j2gpqamvICIiIiISOUxAUFERERElJGdHVC1avoy54EgwoH78uWXOP8DEREREeWECQgiIiIioozU1ORHQdy5A7x/r7RwiFTB/gf7hZ+rlakGe3N75QVDREREREUCExBERERERFmRnQdCIgHOn1deLERK9jzmOa6/uS4ss/wSERERESmCCQgiIiIioqw0bw6UK5e+zHkgqARj+SUiIiIiygsmIIiIiIiIsqKhAXTrlr587RoQF6e8eIiUSLb8UmWjymhUoZESoyEiIiKiooIJCCIiIiKi7MjOA5GSAly+rLRQiJTl1edXuPL6irDM8ktEREREpCgmIIiIiIiIstOuHVCqVPryuXPKi4VISXwf+Mots/wSERERESmKCQgiIiIiouzo6QGurunLly4BycnKi4dICWTLL1U0rIgmlk2UGA0RERERFSVMQBARERERfYtsGab4+LS5IEglzZw5E97e3pnWHzhwAF27doW9vT06dOiAv/76CyKRSNj+6dMn/Prrr3B0dETjxo0xZ84cJCQkyB3jxIkTcHNzQ/369eHu7o6goKACfz2q4E3sG1x6eUlY/qH2D1BX42kkERERESlGU9kBEBERERGptM6dAU1NIDU1bTkgAGjeXKkhkTyxWIyVK1di79698PDwkNt25MgRzJo1CzNmzICTkxPu3r2LGTNmIDk5GaNHjwYAeHl5ISEhAVu3bsWXL1/w22+/IT4+HkuWLAEAXLlyBZMmTcLkyZPRvHlz7N+/Hz///DMOHToEa2vrQn+9hengg4OQQCIss/wSEREVRSKRCCkpKcoOI0cSiQTJyclITEzkfEuULS0tLWhoaCg7DIUxAUFERERE9C1lygCtWwNnzqQtBwYC3t5AEer0F2fh4eH47bff8OLFC1SoUCHT9t27d8Pd3R29e/cGAFSuXBnPnj3Dvn37MHr0aISGhiI4OBh+fn5CMmHu3LkYOnQoJkyYADMzM/z9999o164dBgwYAACYMmUKQkNDsW3bNsydO7fwXqwSyJZfMjcwR7NKzZQYDRERUe5IJBJERkYiJiZG2aEoTCwW48OHD8oOg1ScsbExzM3Ni0SiigkIIiIiIqKceHikJyA+fgTu3gXs7JQbEwFIG51gbW2NdevWYdy4cZm2T5w4EWXLlpVbp66ujs+fPwMArl+/jvLly8uNZGjcuDHU1NQQEhICV1dX3LhxI1NppyZNmuDUqVP5/4JUSFRcFM6/OC8se9byhIY6E29ERFR0SJMPpqam0NfXV/mLtRKJBCKRCBoaGiofKymHRCJBfHw83r17BwCwsLBQckQ5YwKCiIiIiCgn3bsDv/ySvhwQwASEiujXr983tzds2FBuOTY2Frt374azszMAICoqKtOJm7a2NoyNjfH27Vt8+fIF8fHxMDc3l9vH1NQUkZGRuY5XIpFAIpHkvGM+kT5fXp7z4MODEEvEwvIPtX8o1NipePqeNklUENgmiy+RSISYmBiUL18+080IqkyagCDKjq6uLiQSCaKjo1G+fPlM7UXVPs+YgCAiIiIiyknFikDjxkBwcNry2bOAlxfAO9MK1OvXr9G2bdtstwcFBeXqgsLXr18xatQoJCUlYfLkyQCAhIQEaGtrZ9pXR0cHSUlJSExMBIBM+0i359aXL1+grl54kzhL75IDkOs7Kffe3iv8XE6vHOob1xdGjhDl1fe0SaKCwDZZfCUnJ0MsFkNHRwcikUjZ4ShMLBbnvBOVeDo6OhCLxfj48WOmfqqqtSEmIIiIiIiIFOHunp6AiIgAwsOB6tWVGlJxZ2ZmBj8/v2y3GxkZKXys6OhoDB8+HK9fv8Y///wDS0tLAGl3kCUnJ2faPykpCfr6+tDR0QGATPskJSVBT09P4eeXKl26dKHe1Si9A87IyChXF9bex7/HhdcXhGWP2h4wKWOS7/FRyZPXNklUUNgmi6/ExER8+PABmpqaRW5EQVGLlwqfpqYm1NXVYWhoCF1dXbltqpZwYwKCiIiIiEgRHh7AtGnpywEBTEAUMC0tLbm5GfIqPDwcQ4cOhVgsxq5du1CjRg1hm7m5Oc5I5/f4f8nJyUK9aGNjY+jr6wt1dqXevXsHMzOzXMeipqZW6Be4pM+Zm+c9EnYEIkn6yWvPOj15YY7yTV7aJFFBYpssnqS/z6L0u5UtnVNUYibl+Fb7VrW2U3hjf4mIiIiIirJatQAbm/Tlc+eUFwsp7NWrVxg4cCD09PSwZ88eueQDADg6OiIyMhIvXrwQ1gX//0iXhg0bQk1NDQ0aNBDWSV29ehWNGjUq+BegJPsf7Bd+LqtXFq2rtlZeMERERCWMi4sLbGxssvx39erVTPtfvXoVNrL9VCIVwhEQRERERESK8vAAFi9O+zksDIiMBDJMTkyqZdq0aUhOTsby5cuhqamJ6OhoYVv58uVhZ2eHBg0aYPz48Zg9ezbi4+Mxc+ZMuLu7CyMcBg8ejJ9//hl16tRBy5YtceDAATx48AALFixQ1ssqUJ8SPuHM0/RRIR61PKCloaXEiIiIiJRLJBbhwssLeBv7FhaGFnCu7AwN9YItkzRt2jS4ubllWp+bEpREqoAJCCIiIiIiRbm7pycggLQyTH36KCsaykFUVJQwcqF79+6ZtoeFhUFNTQ1r167FnDlzMHDgQOjo6MDV1RVTp04V9mvRogUWLlyI9evXY8WKFahevTo2bNiQL+WhVNHhsMNIFacKyz3q9FBiNERERMrl+8AXY/3H4vWX18I6y9KWWOW6Cp61PQvseQ0NDVG+fPkCOz5RYWECgoiIiIhIUY6OQIUKwJs3acvnzjEBoUJ27Nght2xmZoawsLAcH2diYoLVq1d/cx93d3e4u7t/T3hFxv776eWXjHWN4WLlosRoiIiIlMf3gS96+PSABBK59RFfItDDpwf299pfoEmI7MTFxWHmzJk4d+4cTE1N0bNnT7ntr169wowZMxAaGorKlSvD3d0du3btwtmzZwEA169fx8KFC/HkyRNUqVIFo0ePRseOHQv9dVDJwAQEEREREZGi1NWB7t2BP/9MWw4NBWJiAGNjZUZFlG8+J37GqfBTwnJ3m+7Q1tBWYkRERET5SyQW4VbULcSnxOe434hjIzIlHwAI60YeHwkTPZMcyzHpa+nDzswu38o2zZo1C0+fPsXOnTvx8eNHeHt7C9tSU1MxfPhwVK9eXSgbOXPmTJQpUwYAEB0djeHDh2P8+PFwdnbGzZs34e3tDRMTk2I9vxUpDxMQRERERES54eGRnoAQi4GLF4EuXZQbE1E+OfroKFLEKcIyyy8REVFxkixKhvMWZwRHBOfL8d59fYfW21ortG/jio1xYfAFhRP7s2bNwrx58+TWVahQAXv27MGJEyewfft21K1bFwAwatQozJ07FwBw5coVvH37Fj4+PjAwMED16tXx6NEjHD9+HACwa9cuNGvWDD/99BMAoEqVKnjw4AG2bdvGBAQVCCYgiIiIiIhyo1UrwMgI+Pw5bTkggAkIKjZkyy8ZahuifbX2SoyGiIgofz379Czfkg+5FRwRjGefnsGmnI1C+3t5eaFDhw5y6zQ1NfHs2TOIRCLUqlVLWF+vXj3h57CwMFhZWcHAwEBYZ29vLyQgnj59inPnzsHBwUHYnpKSAisrqzy9LqKcMAFBRERERJQb2tppCYddu9KWg4KAxERAV1e5cRF9p9ikWPg/8ReWu9l0g46mjhIjIiIiyl9WZazQuGJjpSQhGldsDKsyil/kNzExQZUqVTKt//DhQ6Z12trpoyo0NDQgkciXjZJdTk1NRdeuXTFixAi5fTQ1eZmYCgZbFhERERFRbrm7pycgkpKAK1eA1q2VGRHRdzv++DiSREnCMssvERFRcaOtoY3L/7us8BwQPff1RHR8dLb7mJYyhU8Pn0KdA6JatWrQ0tLCnTt34OTkBAC4f/++sL1GjRp4/vw54uLihFEQ9+7dE7ZbWVkhNDRULrmxefNmJCcnZ0pKEOUHJiCIiIiIiHLL1RXQ0UlLPgDAuXNMQFCRJ1t+qZRWKXS07qjEaIiIiAqGhroGGlg0UGjfDV02oIdPWkJedjJqNagBAP7s/CdaVW2V/0ECiI2NRXR05uRHqVKl0L17d8ybNw+LFi1CYmIi1q5dK2x3cnKChYUFZsyYgdGjR+Px48fYvn07jIyMAAA//vgjduzYgRUrVsDDwwN37tzB8uXLsXDhwgJ5HUTqyg6AiIiIiKjIMTAA2svUxj9/HkhNVV48RN/pa/JX+D32E5a71OwCPS09JUZERESkfJ61PbG/135ULF1Rbr1laUvs77UfnrU9C+y5Fy5ciBYtWmT6t3XrVsyYMQMODg4YPHgwvL29hQmlAUBdXR1r1qxBVFQUunfvjvXr18PT0xNaWloAgIoVK2LDhg24cOECunTpgpUrV8Lb2xvdunUrsNdCJRtHQBARERER5YWHB3DsWNrPsbFAaCjg6KjcmIjy6MSTE0hITRCWWX6JiIgojWdtT3S36Y4LLy/gbexbWBhawLmyc76UU8rO2bNnoaam9s19FixYgAULFgjL//vf/wCkzRHx5s0b/Pvvv8K2TZs2wdTUVFhu1qwZfH198zlqoqwxAUFERERElBdduwLq6oBYnLYcEMAEBBVZsuWX9DT10Kl6JyVGQ0REpFo01DXQumprZYehsJEjR2LatGlo1aoVXrx4gW3btnF+B1IalmAiIiIiIsqL8uWBFi3SlwMCAIkk292JVFVCSgKOPTomLLvVcEMp7VJKjIiIiIjyysTEBCtXrsTu3bvh6uqK3377DT/99BN+/PFHZYdGJRRHQBARERER5ZW7e9r8DwAQFQU8fAjUrq3UkIhy62T4SXxN+Soss/wSERFR0dauXTu0a9dO2WEQAeAICCIiIiKivHN3l18+d04pYRB9D9nySzoaOuhco7MSoyEiIiKi4oQJCCIiIiKivLKyAuzs0pcDApQWClFeJKUm4UjYEWHZtborDHUMlRgRERERERUnTEAQEREREX0PD4/0n58+BV6+VF4sRLl0+ulpxCbHCsssv0RERERE+UnpCYiPHz/i77//xoQJE/Dq1Stlh0NERERElDsZyzBxFAQVIbLll7TUtdC1ZlclRkNERERExY1SExD+/v5wcXHBjh07cPnyZXTs2BErVqxQ6LFJSUno1q0bfH195daLRCLUr18fNjY2cv/WrFnzzWPNmTMHTk5OcHBwwK+//oqPHz8K29esWQMbGxt07Zp1Z/zmzZuwsbGBi4uLQrETERERUTFSv35aKSYpzgNBRUSyKBmHww4Lyx2sO8BI10iJERERERFRcaOprCdOSEjA1KlTMXDgQDRr1gzBwcGwtrbG+PHj0aZNG9jb22f72NjYWIwbNw5hYWGZtj1//hxJSUk4fPgwTExMhPX6+vrZHm/27Nm4fv061qxZA21tbcyaNQteXl7YuXOnsI+WlhYePXqEZ8+ewUr2BBOAn58f1NTUcvHqiYiIiKjYUFNLGwUhvZHm7l3g/XugXDmlhkWUk7PPziImMUZYZvklIiIiIspvShsBER4ejvj4eHTr1k1Y16lTJ0yfPh3GxsbZPu7s2bPo1q0bPn36lOX2sLAwGBgYoFatWihfvrzwr1SpUlnuHxUVhUOHDmH69Olo1KgR6tevj+XLl+PatWsIDQ0V9jM1NUX16tXh7+8v93iJRAJ/f380atQoF6+eiIiIiIoV2XkgJBIgMFB5sRApSLb8kqa6JrrbdFdiNERERCTr8+fPWLx4MVxcXGBnZ4dOnTph69atEIvFAAAbGxtcvXq1QJ67f//+36wmQ5QbShsBUa5cOaipqeHKlSuoXr06AEBNTQ39+/f/5uPOnDmDPn36YPDgwahXr16m7WFhYbC2tlY4jpCQEABA06ZNhXVWVlYwMzPDtWvX4ODgIKx3dXWFv78/Ro4cKfd4sVgMR0dHHD6cPnxZURKJBBKJJNeP+x7S5yzs5yXKDtskqRK2R1I1bJNFhJMTUL481KKjAQCSgADA0zPzfhJJ+r9CxPZDGaWIUnDw4UFhuV21diijV0aJEREREamgly/TRrZmp1w5oHLlfH/aT58+oU+fPjA1NcWCBQtgaWmJO3fuYN68eXj16hVmzJiR789JVFCUloAwNzfH4MGDMX/+fNSuXRuWlpZ49eoVKlWq9M3HLVy48JvbHz16hNTUVAwZMgQPHz6EmZkZBg4ciO7ds76bJyoqCmXKlIGOjo7celNTU0RGRsqtc3Nzw9q1a/H8+XNUrVoVAHD8+HG4urpCXT1vg0m+fPmS58fmlUQiQXx8PACwdBSpBLZJUiVsj6Rq2CaLDj1XV+js2JG2cO0a4iIjAQMDuX3Uvn6F6MsXSD5/LtTYpHfKEUkFPA/Ax4T0ee961Gb5JSIiIjkvXwI2NkBiYvb76OoCYWH5noRYvnw5tLW18c8//wjXLCtVqgRdXV2MGjUKP/30U74+H1FBUloCAgCmTJkCFxcXbN26FWfPnsXJkyfRtWtXLFmyBBoaGnk65uPHjyEWi+Hl5QVzc3MEBgZi6tSpSElJQY8emTvVCQkJ0NbWzrReR0cHSUlJcuusra1Rs2ZN+Pv7Y8SIERCJRDh58iTWrVuHixcv5ine0qVL5/m15pX0DjgjIyNeyCCVwDZJqoTtkVQN22QR0rMn8P8JCLXUVBjcvg106CC/T6lSQOnSgFHhTvQrEokK9flI9cmWX9JQ00D3Wiy/REREJOf9+28nH4C07e/f52sCIjk5GcePH8fkyZMz3TDdpk0bbN26FRUrVpRbn5SUhNWrV+PYsWP4/PkzmjZtilmzZsHCwgKvX79G27Zt8d9//8HS0hIAsGbNGgQHB2PH//ddT58+jWXLliEqKgqenp7sO1K+UmoCAgAcHR0hFothY2ODWrVqYeLEibCzs8Py5cvl9jt+/DgqVKiQ4/GOHTsGkUgkzPlQq1YtvHnzBv/880+WCQhdXV0kJydnWp+UlAQ9Pb1M611dXXHy5EmMGDECwcHB0NXVhYODQ54TEGpqakq5mCB9Xl7IIFXBNkmqhO2RVA3bZBHRvn1aguHrVwCAWkAA0LGj/D5qaun/ChHbDslKFafKlV9qY9UG5fQ5aToREZUQIhFw6xbw/6OMsxUWptjxQkNzPpa+PmBnByhwE/LLly8RHx+fZel5NTU1uTLyUrNmzcKNGzewZMkSGBsbY9myZRg1ahQOHDiQ4/M9efIE48aNw6RJk+Ds7Ixt27YhJCQETk5OOT6WSBFKS0BERUUhJCQEbm5uANL+gDp06ICWLVsiKCgIhw4dktvf1NRUoePq6upmWlezZk0cOXIky/3Nzc0RExOD5ORkuZEQ7969g5mZWab93dzcsHr1arx48QJ+fn5C/ERERERUwunqAp06Afv//87yixeB5GQgi9G2RMp04cUFRMdHC8ssv0RERCVGcjLg7AwEB+ffMYcOVWy/xo2BCxdy7BvGxsYCAAwNDRU67OfPn3H48GH8/fffQnJi2bJlaN26NS5dugQrK6tvPv7AgQNo1KgRBg0aBACYMWMGzp07p9BzEymicCcfkBEcHIzx48fj2bNncuvfv38PY2NjVKlSRe6fpmbOuZIvX76gcePG8PX1lVt/584d1KhRI8vHNGzYEGKxWJiMGgCePXuGqKgoODo6ZtrfysoKtWrVgp+fH06dOoXOnTsr8nKJiIiIqCRwd0//OSEhf09uifKJbPkldTV1uNdyV14wREREhenZM+X1z4KD054/B8bGxgDSEguKeP78OcRiMezs7OSOYWVlhfDw8BwfHx4ejtq1awvLWlpacstE30tpCQgXFxeUL18e3t7eePbsGWJiYrBy5UrcunUry1JJiihdujSaNm2KFStWIDAwEM+fP8dff/2FI0eOYMyYMcJ+0dHR+Pr/Q+PNzMzQuXNnTJ8+HVevXsXt27cxYcIENG7cGPb29lk+T6dOnbBp0yaULVuWf5BERERElK5zZ0D2xpnAQOXFQpQFkVgE34fpN2y1rNISZgaZR34TEREVS1ZWaSMRlKFx47Tnz0GlSpVgaGiIe/fuZbl95MiRuHz5srCccZ4IKZFIBLFYnGUpztTUVLll6bxzUlpaWjnGSaQopZVgKlWqFDZv3oz58+dj/vz5ANImeV67di0aNGiQ5+MuXLgQa9aswaxZs/DhwwdYW1tj9erVcHZ2FvZp0aIFRo8eLSQl5s2bh4ULF2L06NEAgJYtW2L69OnZPoebmxtWrFghDE0iIiIiIgIAGBsDbdoAp0+nLQcEAN7eCtX7JSoMl19dRmRcpLDM8ktERFSiaGsDly8rPgeEIuWVNm0CbGy+vU8u5oDQ1NSEm5sbdu3ahR9++EGuZPzZs2dx9uxZ/Prrr8K6SpUqQVNTEzdv3hSuf3769AkvXryAlZWVkEyQ3owNAK9fvxZ+rlGjBkJDQ4VlsViMhw8folatWjnGSqQIpU5CXbNmTWzfvh1XrlzBtWvX5EYpKCIsi8lgDAwMMHXqVEydOlXhx+nr68slQjIaM2aMXGyVK1fOdIyM+xARERFRCeXhkZ6A+PQJuHMHyGZkLVFhky2/pAY1eNT2UGI0RERESqChAShy87O+vmLHc3BQ7Hi5MHr0aPTq1QtDhgzBmDFjYG5ujqtXr2Lp0qUYMGAAqlevLuxbqlQp9OzZE/PmzcO8efNgZGSEZcuWwdzcHM2bN4empiYsLCzwzz//YMyYMbh27RoCAgJQp04dAECvXr2wY8cO/Pnnn+jYsSP27t2LN2/e5OvroZJNaSWYZFlaWqKxsoY/ERERERHlp27d5JcDApQSBlFGYokYBx4cEJabV26OCoYVlBgRERGRCitXDtDV/fY+urpp++Wz8uXLY/fu3ahUqRImTpyILl26YNu2bfDy8oK3t3em/adMmYJmzZrBy8sLffv2hY6ODrZu3QptbW2oq6tjwYIFuH37Ntzc3ODv748RI0YIj61SpQr+/PNPHD9+HO7u7oiOjkarVq3y/TVRyaXUERBSlpaWsLS0VHYYRERERETfr2JFoEkT4OrVtOVz54CxY4Es6u8SFaarr68iIjZCWGb5JSIiom+oXDmtDNP799nvU65c2n4FwMLCAgsXLsx2u2x1Fj09PcyePRuzZ8/Oct/mzZvD399fbt2wYcPkth87duz7AibKhkokIIiIiIiIihV39/QEREQEEB4OyAyVJ1IG2fJLAOBZ21NJkRARERURlSsXWIKBqKRQiRJMRERERETFikeGuvosw0RKJpFIsP9BegKiqWVTVDKqpMSIiIiIiKgkYAKCiIiIiCi/2dgAtWqlL589q7xYiABcf3MdLz+/FJZZfomIiIiICgMTEEREREREBUF2FMSjR8Dbt8qLhUo82dEPAPBDnR+UFAkRERERlSRMQBARERERFQR3d/lllmEiJZFIJDjw4ICw3KhCI1Q1rqq8gIiIiIioxGACgoiIiIioIDRqBFSsmL7MBAQpyZ3oO3j66amwzPJLRERERFRYmIAgIiIiIioI6upA9+7py6GhwJcvyouHSqzDTw7LLbP8EhEREREVFiYgiIiIiIgKiuw8EGIxcP268mKhEkkikeDw4/QEhL25PaqXra7EiIiIiIioJNFUdgBERERERMWWlRVgYADExaUt//cf0LEj8OFD2nK5ckDlysqLj4o1kViErTe3IjwmXFjH8ktEREREVJg4AoKIiIiIqCC8fAnY2qYnHwDg/n2gSxegYcO0fzY2afsR5TPfB76ouqoqhh4dKrfeSNdISRERERGRolxcXODr65tpva+vL1xcXPLlOby9veHt7Q0gbcTkrl27styWH7Zv3w43NzfY2tqiefPmmDZtGqKjo/Pt+HFxcViwYAFatmwJW1tbdOjQAWvXrkVycvI3H/fhwwd4enoiJSVFbv3r16/h4OCAq1evyq3funUrnJ2d4eDggGnTpiEhIUHYtmvXLjRp0gQdO3bEzZs3hfXJycno0KED3r17l6vXtGLFCvj4+OTqMaqKCQgiIiIiooLw/j2QmPjtfRIT0/Yjyke+D3zRw6cHXn95nWmb1wkv+D7IfEGDiIiISq5r165h7ty5BXLs7du3459//sHEiRPh7++PNWvW4Pnz5xg6dCjEYnG+PIe3tzcePHiAlStXwt/fH5MnT4aPjw+WLFnyzcctXboU/fr1g5aWltz62bNnIz4+Xm7dyZMnsXbtWsydOxfbtm3DrVu3sHTpUgDAx48fsWTJEqxatQqenp6YM2eO8Lh9+/ahVatWMDU1zdVrGjJkCDZu3IhPnz7l6nGqiAkIIiIiIiKiYkIkFmGs/1hIIMl2n3H+4yASiwoxKiIiIlJlEkn2/YbvdfDgQQwePBguLi6wtLREgwYNsHz5cjx8+BC3b9/+7uPHxsbizJkz+O2339CgQQNYWlqiXbt2+PXXX7F///5skxyvX7/Gf//9h65du8qtP3LkCL5+/Zpp/+3bt2PgwIFo06YN6tevjzlz5uDAgQNISEjAq1evULp0aTRt2hTt27fH06dPAaSNfti+fTuGDRuWbfyvX7+GjY1NpvWlS5dGixYt8O+//+bm7VBJTEAQEREREREVExdeXshy5IOUBBK8+vIKF15eKMSoiIiIqCC8ffsWI0aMgJ2dHVxcXLB27VqIROk3Gezbtw+urq6wtbVFkyZNMGfOHLntQNoF8AEDBgAAbGxshLJDcXFxGD9+POzs7NC6dWscPXoUQNoF+iZNmiA1NVU4xsmTJ9G6dessExlqamq4fv26XDkkc3Nz+Pn5oVatWsJzTZ06FU5OTrC1tYWrqyvOnDkj7P/kyRMMGTIEDg4OqFevHn788UeEh4cLx1dTU8Ply5flnrdDhw44ePAg1NTUsnzv9u7dixYtWkBbW1tY9+nTJyxdujTTaBCRSIQ7d+6gUaNGwjp7e3ukpKTg4cOHMDc3x+fPn/HmzRvcu3cPFhYWAIADBw7A2dk516MfpFxcXLB37958GymiLExAEBERERERFRNvY9/m635ERESkmiQSCUaPHg0TExMcPHgQixYtwtGjR7FhwwYAQHBwMObPn48JEybA398fc+bMwf79+/Hff//JHcfCwgJr1qwBAFy8eBEODg4AgNOnT6Nu3bo4duwYOnXqhGnTpiE2NhZt27ZFYmIirly5IhzjxIkT6NSpU5YX+wcMGIDTp0+jVatWmDp1Kg4fPoyYmBhYW1tDV1cXALBgwQI8e/YMmzdvxrFjx9CoUSP89ttvSE5OhlgsxogRI1CxYkUcPnwYe/bsgUgkEsofGRgYwMPDA7///jtcXV2xaNEiBAYGQkNDA9WqVcs2AXHhwgU0a9ZMbt3ixYvh4eGBGjVqyK3/8uULkpKS5BIJmpqaMDY2RmRkJMzMzDBgwAC0a9cOM2fOxJQpU5CSkoJt27bh559/zvmXmY2mTZvi/fv3ePToUZ6PoQqYgCAiIiIiIiomLAwt8nU/IiKi4ig+JR4fEz4Ky58SPiEuOQ5AWjnD9/HvkSJKm5g4ISUBH+I/CPvGJMYI+4olYryPf49kUdrd/YmpiXgfnz6/1+fEz4hNis1TjLNmzYKDg4Pcv1mzZgnbr1y5gjdv3mDevHmoVq0amjRpgilTpmD79u0AAH19fSxYsAAdOnSApaUlXF1dUadOHTx+/FjueTQ0NGBkZAQAKF++vDAiwMHBAUOHDkWlSpUwatQoJCcn4+nTpyhVqhTatGkDf3//tPcnIQGBgYHo3Llzlq/D3d0df/31F2rXro2jR49i8uTJcHZ2xp9//ins4+joiLlz56J27dqoWrUq/ve//yEmJgYfPnxAYmIi+vTpA29vb1SuXBl169aFh4cHnjx5Ijx+/vz5mD59OnR1dbF161b8/PPPaNOmDQICArKMKTU1FWFhYbC2thbWXb58GSEhIRg1alSm/RP/f1432dES0mXpyI5JkyYhKCgIV65cQZs2beDr64sWLVpAQ0NDKEH1999/C4/t3LkzHBwc0KVLF+H9dnBwwMyZM4V9dHR0UKlSJdy/fz/L11FUaCo7ACIiIiIiIsofzpWdYVnaEhFfIrKcB0INarAsbQnnys5KiI6IiEg1PIh+gIfvH6Jf/X4AgP+e/YcKhhXQrFIzfE35Ct8HvuhSswsqGFbAow+PcDPyJgbaDwQABDwPQFm9smhZpSUSUxPh+8AXrtVdUdmoMsI/hiPodRCGNhgKALj48iJ0NXXRtlrbXMfo5eWFDh06yK07deoUdu/eDQAIDw9HTEwMGjZsKGwXi8VITEzEp0+fYGtrC11dXaxevRpPnjxBWFgYXrx4gRYtWij0/JUqVRJ+NjQ0BAAkJSUBALp06YLp06dj9uzZCAgIgKmpKWxtbbM9VqtWrdCqVSvExcXhypUr2LNnD1auXInq1aujffv2cHd3x5kzZ+Dj44OnT5/i3r17ANJKH+nr66Nv3744dOgQ7t69i6dPn+L+/fsoV66ccHx1dXX0798f/fv3R1RUFM6fP48tW7bAy8sLp0+fhpmZmVw8nz9/hlgsRpkyZQCkJRhmzpyJWbNmCaMyZOno6ACAXBkp6bKenp6wLE3kpKSkYOvWrdi6dStWr16N6tWrY9WqVejWrZtQZuqvv/5CamoqoqKi0L9/fxw6dAhA2ogOWcbGxvjw4QOKMiYgiIiIiIiIigkNdQ2scl2FHj49oAY1uSSEGtJKEKx0XQkNdQ1lhUhERKR0tcvXhlUZK2G5rVVbaGloAQBKaZWCZ21PGOmkXUyuaVITlqUthX1bV20NTfW0S6q6mrrwrO2J0jqlAQDWZa1hZpB+sbtF5RZQV8tbARoTExNUqVIl0zqp1NRUVKtWDevXr8/0WENDQ1y4cAG//PIL3N3d4ezsjF9++QVz5sxR+Pk1NDL3FaRzPLRs2RIikQjXrl3DyZMn0alTpyyP8fbtW2zYsAG//fYbtLW1YWBggHbt2qFt27bo06cPLl++jPbt22Py5MkIDQ1F9+7d0bdvX5QvXx69e/cGAHz9+hU9evRAmTJl4OLigi5duuDp06fYvHkzAODq1au4ceMGRo4cCQAwMzNDz5490b59e7Rq1Qo3btzIFJ+0LJN0boXbt2/j1atX8PLykttv2LBhcHd3x+zZs6Gjo4P3798LoyZSU1MRExOD8uXLZ3rdhw4dQvPmzWFmZoYbN25g4sSJKF26NOzt7RESEgJbW1tUrFhR7n3O+LuWEovFUFcv2kWMmIAgIiIiIioI5coBurrA/w/ZzpKubtp+RPnIs7Yn9vfaj7H+Y+UmpLYsbYmVrivhWdtTidEREREpn76WPvS19IXlMnplhJ811DVQTj+9f6anpQc9rfS73I11jYWf1dXU5fbV1dSFrmb6HfRGukb5HbrAysoKb968QdmyZYURCpcuXYKvry9+//137Nu3Dz/88INQtik1NRUvX75E06ZNMx0ru3kSsqOtrY327dvj9OnTuHTpEn755Zds99u3bx+cnZ3Rrl07ueczMDBA2bJlERcXh2PHjsHHxwf169cHAAQGBgJIS3gEBwfj3bt3OHr0KDQ10y5lX7x4UUiGfP78GevXr0ePHj3kkgH6+vrQ0NBA2bJlM8VlbGwMDQ0NfPr0CQBQv359nDp1Sm6fDh06YP78+WjevDnU1dVRr149hISEoEmTJgCAmzdvQlNTU5hIWyo1NRVbtmzBli1bAKSNzpDGKhKJspyo+1s+ffokN9qjKGICgoiIiIioIFSuDISFAe/fZ79PuXJp+xHlM8/anuhu0x3nX5xH+LtwWJtao2WVlhz5QEREVEy0aNECFStWxKRJkzB+/HjExsZixowZaNasGTQ0NGBsbIzQ0FCEhYVBXV0dGzduRHR0dKYyQgCEMkJ3797NNAFzdrp06YIRI0agSpUq2T7GxMQEffr0wbRp0xAdHY3mzZsjNjYWZ86cwZ07dzBv3jxoa2tDT08Pp06dQtmyZfHs2TPMnTsXQFqJI2NjY8THx+PMmTOwtbVFUFAQdu3aJZQqatOmDaytrTF48GBMmDABNWvWRGRkJLZt2wYrKys4OjpmiktdXR21atVCWFgYGjVqBF1d3SxHIJiZmQmjTn788UfMnDkTNWvWhKmpKWbPno1evXrJlWAC0kY/ODk5CWWf6tWrh6NHj8LU1BTBwcEYMmSI3P6WlpYICwvL8v2Li4tDREQE6tat+61fhcpjAoKIiIiIqKBUrswEAymNhroGWldtDYcyDjAyMsr13Y1ERESkujQ0NPDnn39i3rx56NWrF/T19eHq6oopU6YAAEaPHo2pU6eid+/eMDAwQKtWrdC3b188ePAg07FsbGzQvHlz9OnTB8uXL1fo+Zs0aYJSpUrBzc3tm/tNmzYNFStWxL///ovFixdDU1MTjo6O2LlzJypUqAAAWLp0KZYsWYIdO3bA0tISI0eOxMqVK/HgwQN06dJFKB+VlJQEGxsbzJw5E7/99huioqJgZmYmzLUwb948REdHw8jICO3atcO8efOyLV/k7OyMGzduoF+/fgq93s6dOyMiIgIzZ85EcnIyOnTogEmTJsntIx39IC0PBaT9HsaNG4eBAweif//+sLe3V+j5ACA0NBTm5uaoXr26wo9RRWqS3I77oHwhEolw8+ZN2NvbZ1lTrSBJJBJ8/vyZJyGkMtgmSZWwPZKqYZuk/KDMvmdhkp4QLl68OMvtEokEQ4cORXJyMnbs2CGsT0pKwuLFi+Hv74/ExES4uLjgt99+kxuyHxQUhKVLlyI8PBwWFhYYM2YMOnfurHBsyvod8DOEVA3bJKkatsniKzExEc+ePYOVlVWWEwurIolEApFIBA0NDZVvj3FxcWjevDmOHTsmN2F1UfHy5Ut4enriwoULmUYxqIqpU6eiUqVKGDVqVKZt32rfqtb3L9ozWBARERERUYknFouxfPly7N2795v7bdu2DRcvXsy0fvbs2bh48SLWrFmDbdu24enTp3KTEIaHh2P48OFwdnaGr68vevbsicmTJyMoKCjfXwsRERGRKpNIJPD398fMmTPh4OBQJJMPAFC5cmW0atUKR48eVXYoWfr06RMuXbqEvn37KjuU78YSTEREREREVGSFh4fjt99+w4sXL4Rh/FkJCwvDunXrMg17j4qKwqFDh7BhwwY0atQIALB8+XK4uroiNDQUDg4O2LZtG2xsbDB+/HgAgLW1Ne7fv49NmzbBycmpwF4bERERkapRU1PD0qVLhRJQRdmUKVMwbNgwuLu7Q1tbW9nhyNm8eTNGjhyJMmXK5LyziuMICCIiIiIiKrKuXLkCa2trHDt2DJaWllnuk5SUhIkTJ8LLywtWVlZy20JCQgAATZs2FdZZWVnBzMwM165dAwBcv349U6KhadOmCAkJASvaEhERUUnz33//4dSpU7C2tlZ2KN/F1NQUhw8fVrnkAwD8+uuvxWL0A8AREEREREREVIQpMnHg0qVLYWpqip9++glTp06V2xYVFYUyZcpAR0dHbr2pqSkiIyMBAJGRkTA3N8+0PSEhAZ8+fZKbKyInEomkUJMW0udjooRUBdskqRq2yeJL+jstqr/fohgzFZ5vtW9VaztMQBARERERkUp6/fo12rZtm+32oKCgHC/+nz9/HkePHsWRI0eynMwxISEhy7vedHR0kJSUBCBtkr+M+0iXk5OTc3wdsr58+QJ19cIbiC6RSBAfHw8AKj+ZJZUMbJOkatgmi6/k5GSIxWKIRCKIRCJlh6MwsVis7BCoCBCJRBCLxYiNjRX6rFKq1oaYgCAiIiIiIpVkZmYGPz+/bLcbGRl98/EfP37EtGnTMHv2bJiZmWW5j66ubpZJhKSkJOjp6QFIS0Zk3Ee6LN1HUaVLl4aGhkauHvM9pHfAGRkZ8cIaqQS2SVI1bJPFV2JiIj58+AA1NbVC/e7ND0UtXip8ampqUFdXh6GhIXR1deW2qVrCjQkIIiIiIiJSSVpaWt9VWzgwMBDR0dGYNm0apk2bBiD9bkgHBwccP34c5ubmiImJQXJystwoh3fv3glJCwsLC7x7907u2O/evYO+vj4MDQ1zFZOamlqhX+CSPicvrJGqYJskVcM2WTzp6OhAXV0db9++Rfny5aGtra3yv2OJRAKRSAQNDQ2Vj5WUQyKRIDk5GdHR0VBXV4eOjk6mtqJqbYcJCCIiIiIiKpbat2+PBg0ayK1btmwZIiMjsWzZMpiamqJhw4YQi8UICQkRJpp+9uwZoqKi4OjoCABo1KgRgoOD5Y5z5coVNGjQoFDLKREREZHi1NXVYWVlhbdv3+LNmzfKDkdhYrGY/QvKkb6+PipXrlwk2goTEEREREREVCwZGBjAwMBAbl2pUqWgq6uLKlWqAEgr89S5c2dMnz4dCxcuhJ6eHmbNmoXGjRvD3t4eANC/f394eHhg2bJl8PDwQGBgIPz9/bFp06bCfklERESUC9ra2qhcuTJSU1NVrixNViQSCWJjY2FoaKhyd7GT6tDQ0ICmpmaRaSNMQBARERERUYk2b948LFy4EKNHjwYAtGzZEtOnTxe216hRA+vXr8fSpUuxbds2WFpaYunSpcKICSIiIlJdampq0NLSgpaWlrJDyZFEIkFSUhJ0dXWLzMVlopwwAUFERERERMXCjh07ctxn8eLFmdbp6+tj/vz5mD9/fraPa9myJVq2bPld8RERERERlTSqXySKiIiIiIiIiIiIiIiKHCYgiIiIiIiIiIiIiIgo37EEk5JIJBIAUMoEOBKJBGKxGCKRiPXkSCWwTZIqYXskVcM2SflB2ueU9kGp8Cmr/8/PEFI1bJOkatgmSZWwPVJ+ULW+PxMQSiIWiwEAd+7cUXIkRERERFRSSPugVPjY/yciIiKiwqQqfX81iaqkQkoYsViM1NRUqKurM6NJRERERAVKejedpqYm1NVZhVUZ2P8nIiIiosKgan1/JiCIiIiIiIiIiIiIiCjfKT8FQkRERERERERERERExQ4TEERERERERERERERElO+YgCAiIiIiIiIiIiIionzHBAQREREREREREREREeU7JiCIiIiIiIiIiIiIiCjfMQFBRERERERERERERET5jgkIIiIiIiIiIiIiIiLKd0xAEBERERERERERERFRvtNUdgCkWpYuXYrAwEBIJBL07t0bAwYMUHZIVMItW7YM586dg7q6OkaOHAk3Nzdlh0QEAPDy8oKdnR2GDBmi7FCohBswYAA+ffoEdfW0+0o2b94MExMTJUdFREUF+/+katj/J1XEvj+pCvb9qShiAoIEAQEBCAsLw+HDh5GUlIQePXqgefPmsLa2VnZoVEJduXIFd+/exdGjR/Hlyxe4ubmhXbt20NbWVnZoVMIdOXIEV65cgZ2dnbJDoRJOIpEgIiICZ86cgZqamrLDIaIihv1/UjXs/5MqYt+fVAX7/lRUsQQTCSwsLDB+/HhoaGhAX18flStXRlRUlLLDohKsadOm2LRpE9TV1fHu3Ttoa2tDQ0ND2WFRCRcVFYU9e/agT58+yg6FCE+fPoVIJMLAgQPh4eGBU6dOKTskIipC2P8nVcP+P6ka9v1JlbDvT0UVR0CQwMbGRvj51q1buHv3LurXr6/EiIgATU1NLFq0CLt27cKIESN4AkJKN2vWLEybNg3nzp1TdihE+PLlC5o2bYrZs2fj06dP6NevH2rXro1KlSopOzQiKgLY/ydVxP4/qRL2/UmVsO9PRRVHQFAmN2/exOjRo7F06VIYGBgoOxwiTJ06FRcvXsTJkydx/fp1ZYdDJdju3btRu3Zt2NraKjsUIgCAg4MDFi9eDF1dXVhYWMDFxQVXrlxRdlhEVMSw/0+qhv1/UgXs+5OqYd+fiiqOgCA5ly5dwpQpU7B06VI4OTkpOxwq4Z49e4bk5GTY2NjA2NgYLVq0wKNHj9CoUSNlh0Yl1KlTp/D+/XucPXsW79+/h7q6OkqXLo2ePXsqOzQqoUJCQpCSkoKmTZsK6zQ12b0jIsWx/0+qhP1/UiXs+5OqYd+fiiqOgCDBy5cvMXnyZPz55588+SCV8PLlS8ydOxepqamIi4vDpUuXYG9vr+ywqATbsmULjh49isOHD6NPnz4YNGgQT0BIqeLi4vDHH38gOTkZHz9+REBAAJo1a6bssIioiGD/n1QN+/+kStj3J1XDvj8VVUyTkWDTpk1ITk7G9OnThXUTJ06Es7OzEqOikqxVq1a4ceMGunXrBg0NDfz000+oU6eOssMiIlIZ0s9Jd3d3iMViTJgwAWZmZsoOi4iKCPb/SdWw/09ElD32/amoUpNIJBJlB0H5b+PGjbh48SJ27NghrBOLxVi7di327duH2NhYODo6YubMmZyshgoF2ySpGrZJUjVsk0T0PfgZQqqGbZJUCdsjqRq2SSpJWIKpGNq1axdWrlyZaf369evx77//Yt68edizZw/EYjGGDh2K5OTkwg+SShS2SVI1bJOkatgmieh78DOEVA3bJKkStkdSNWyTVNIwAVGMREVFYcSIEVi2bBmqVq0qty05ORmbN2+Gl5cXWrdujVq1amHFihWIjIzEqVOnlBMwFXtsk6Rq2CZJ1bBNEtH34GcIqRq2SVIlbI+katgmqaRiAqIYuXfvHrS0tHDkyBHY2dnJbXv48CG+fv0qN7lc6dKlUadOHVy7dq2wQ6USgm2SVA3bJKkatkki+h78DCFVwzZJqoTtkVQN2ySVVJyEuhhxcXGBi4tLltsiIyMBABYWFnLrTU1NhW1E+Y1tklQN2ySpGrZJIvoe/AwhVcM2SaqE7ZFUDdsklVQcAVFCJCQkAAC0tbXl1uvo6CApKUkZIVEJxzZJqoZtklQN2yQRfQ9+hpCqYZskVcL2SKqGbZKKMyYgSghdXV0AyDRxTVJSEvT09JQREpVwbJOkatgmSdWwTRLR9+BnCKkatklSJWyPpGrYJqk4YwKihJAO4Xr37p3c+nfv3sHMzEwZIVEJxzZJqoZtklQN2yQRfQ9+hpCqYZskVcL2SKqGbZKKMyYgSohatWrBwMAAV69eFdZ9+fIF9+/fh6OjoxIjo5KKbZJUDdskqRq2SSL6HvwMIVXDNkmqhO2RVA3bJBVnnIS6hNDW1sZPP/2EZcuWoWzZsqhYsSKWLl0Kc3NzdOjQQdnhUQnENkmqhm2SVA3bJBF9D36GkKphmyRVwvZIqoZtkoozJiBKEC8vL6SmpmL69OlITEyEo6Mj/vnnH2hpaSk7NCqh2CZJ1bBNkqphmySi78HPEFI1bJOkStgeSdWwTVJxpSaRSCTKDoKIiIiIiIiIiIiIiIoXzgFBRERERERERERERET5jgkIIiIiIiIiIiIiIiLKd0xAEBERERERERERERFRvmMCgoiIiIiIiIiIiIiI8h0TEERERERERERERERElO+YgCAiIiIiIiIiIiIionzHBAQREREREREREREREeU7JiCIiIiIiIiIiIiIiCjfMQFBREQFysXFBTY2Nrh8+bLcel9fX9jY2KBv375KioyIiIiIiPIb+/9ERCSLCQgiIiIiIiIiIiIiIsp3TEAQEREREREREREREVG+YwKCiIhUwunTp/HDDz+gQYMGaNCgAXr27ImAgAC5fc6cOYNu3brB1tYWrVq1wooVK5Camipst7GxgY2NDXbs2IGmTZuibdu2iI+PV+jYRERERERUeNj/JyIqGZiAICIipXvy5AnGjh2LsLAw1KtXD7Vr18adO3fwyy+/4PHjxwCAwMBAjB49Gk+fPkWjRo2goaGBDRs2YO7cuZmOt3TpUtSuXRv16tXDmzdvcjw2EREREREVHvb/iYhKDk1lB0BERCWbmpoaXr58CZFIhLp16+KPP/5AuXLlcPToUYhEIpQuXRoAsGHDBkgkEvz+++9wc3NDUlISXF1dsX//fowdOxYmJibCMb28vDB06FAAwNmzZ3M8NhERERERFQ72/4mIShaOgCAiogKlpaUFABCLxXLrpcsaGhpo2rQp6tWrh9u3b6NFixbo3Lkzbt68iapVq8LMzAwAcP/+fQDA+PHjYWNjg/r16+PNmzcQiUS4c+eO3LEbN24s/KzIsYmIiIiIKH+w/09ERLI4AoKIiAqUgYEBACAuLk5ufUJCAgBAX18f+vr62L17N86fP48LFy4gNDQUu3btws6dOzF37lz07t0bWlpaSExMRNOmTVGqVCm5Y+np6WX5nNLj53RsIiIiIiLKH+z/ExGRLI6AICKiAmVtbQ0AOHToEEQiEYC0u58CAwMBAFZWVggMDMTUqVPx6NEjzJ49G4cPH8b48eMBQJgsrmbNmgCALl26YP369VixYgXMzMzQsGFD1K5dW+45NTQ0hJ8VOTYREREREeUP9v+JiEgWR0AQEVGBGjBgAE6cOIFz586hffv2qFatGp4/f45Xr15BV1cXvXr1Qnx8PE6ePInk5GScPXsWhoaGCAkJAQA0a9YMADB06FCEhIRg5syZOHLkCCIiIhAREQFbW1sMHjw42+c3MTHJ8dhERERERJQ/2P8nIiJZahKJRKLsIIiIqHi7ffs21q5di1u3biEuLg4GBgZwcHDAmDFjULduXQDAtWvXsG7dOty/fx8pKSmoWLEievfujf79+wvH8fPzw19//YXw8HCUKlUKrVu3xuTJk1G2bFkAgI2NDQDg1KlTqFKlivA4RY5NRERERET5g/1/IiKSYgKCiIiIiIiIiIiIiIjyHeeAICIiIiIiIiIiIiKifMcEBBERERERERERERER5TsmIIiIiIiIiIiIiIiIKN8xAUFERERERERERERERPmOCQgiIiIiIiIiIiIiIsp3TEAQEREREREREREREVG+YwKCiIiIiIiIiIiIiIjyHRMQRERERERERERERESU75iAICIiIiIiIiIiIiKifMcEBBERERERERERERER5TsmIIiIiIiIiIiIiIiIKN8xAUFERERERERERERERPmOCQgiIiIiIiIiIiIiIsp3TEAQEREREREREREREVG+YwKCiIiIiIiIiIiIiIjyHRMQRERERERERERERESU75iAICIiIiIiIiIiIiKifMcEBBERERERERERERER5TsmIIiIiIiIiIiIiIiIKN8xAUFUhHz9+hXr16+Hu7s7HBwcYGdnh65du2L16tWIjY0t1FgePXqk0H5v377FzJkz0bZtW9SrVw/29vbo2rUrVq1ahbi4uCwf8+LFCyQlJeVnuHmm6OtUFS4uLrCxscHw4cPzfIzLly/D3d0d9erVQ5MmTbBs2bJ8jLDo6t+/P2xsbOT+2drawsnJCUOHDsWFCxeUHWK+/P5zIy4uDm/fvi2U5/oein6mpKamYvv27ejZsycaNWoEW1tbtGrVChMmTMD9+/cLPE5pG+vSpUuBPxcRUUmS8Tvc19dXbvvLly8zfccXpoz9TWkMc+fOzfGx3t7esLGxgYODQ77Fk/G9qFWrFmxtbdG0aVMMGTIEoaGh+fZcGX369Anjx49Hw4YNYWdnh+7duyMuLu6b70lu+usikQj79u3DTz/9hGbNmqFu3brC6/Lz88vPl/LdLl++LLzu7t27QywWZ9pn3Lhxwj4HDx5UQpRZW7NmTaZ2lNW/q1evfvM4r1+/Fvb9559/Cin6zOLj4/H333+jV69eaNy4MerVqwcXFxdMmTIFDx48UFpcihCLxTh06BAGDBiAJk2awNbWFi4uLpg+fTqeP38ut6+qvN9Xr14V4vD391foMWFhYZgyZQpat24NW1tbNG7cGIMHD8bJkycLOFrlyvj5963vhOjoaHz8+LGwQiOSwwQEURHx/PlzdOvWDatWrcKDBw8QHx+PxMREPHr0COvWrYO7uzsiIyMLPI5Hjx5hwIAB+OOPP3Lc98mTJ+jWrRv27t2L169fIzk5GQkJCXj06BHWr1+PPn36yCUh4uPjsXz5cnTp0gVfv34tyJeRo4iICHh5eeHXX39VahyFLT4+HqNHj8aDBw+QnJyMmJgYpKSkKDsslZWSkoKPHz/iwoULGDp0KDZv3qzskAqFRCKBr68vOnbsiFu3bik7nGzl5jNFJBJh5MiRWLBgAW7fvo3Y2FikpKQgMjISx48fR69evXD+/PlCipyIiApScHDwN5cLS2761cokkUiQkpKCT58+4eLFixg4cGCBJSGWLl0KPz8/xMXFITExEZGRkTAwMMhy39z219+/f4+BAwdi+vTpuHbtGj58+IDU1FThdY0fPx7z5s3Lz5fzXZo1a4YOHToAAB4+fIhDhw7Jbb99+7ZwcdbBwQHu7u6FHGHJ8PLlS3Tv3h3Lli3DrVu38PnzZyQnJyMiIgKHDh2Ch4cHNm3apOwwsxQfH4+ff/4ZU6ZMwdWrV4Vzu4iICOzbtw8eHh64dOmSssP8bnv37oWHhwcOHTqEt2/fIiUlBZ8/f8bly5fh5eWFGTNmKDvEfPfx40fMnDkTffv2zXHflJQUbN68GR07dkREREQhREeUmaayAyCinCUkJGDkyJF4/fo1tLW1MWbMGLRt2xZfv37F1q1bcfz4cbx+/Rre3t7YunVrgcYyYsQIREREoHXr1jnuu2TJEnz58gWlS5fG1KlT4eDggISEBGzZsgVHjhzB48ePsWXLFowZMwYAsHnzZmzcuLFA41eUt7c3goODUaNGDWWHUqjCw8OFC7X9+vXDgAEDoK+vr+SoVIuVlRW2bt0KsViM+Ph43LlzBytWrEBUVBSWLVuGRo0aoX79+kqJbe/evRCJRNDR0SnQ57l27RqmTp1aoM+RH3LzmXLy5EkhwdC7d2/07t0b+vr6CAkJwdy5c5GUlITZs2fj7NmzBRkyEREVgowJh2vXrikljtz0q5XB09MTY8eORWpqKuLi4rB7927s2bMHSUlJWL58OXbs2JHvz3n79m0AQMWKFfH3339DIpEAAAIDAwFArl+am/66WCzG+PHjhd+1p6cnevToARMTE9y/fx9//PEHXr9+jZ07dwojtlWBt7c3zp8/j8TERKxcuRJubm7Q1dUFkJaskUgkUFdXx8yZM6GmpqbkaLN25MgRGBkZZbmtbNmyhRxN7iQlJWHEiBF4+fIlAKBXr17o2bMnjI2NcffuXSxfvhyvXr3C0qVLYWZmpjLtRmr27NnCKG1PT0/069cPOjo6OH36NNauXYv4+HhMmDABp0+fRunSpZUcbd4EBQVh1qxZkEgksLa2xsSJE2FtbY1Hjx7h999/x8uXL+Hj44NGjRqhe/fuyg433yxduhS+vr6ZztWnTp2KcePGyX0eHDt2DEuWLCnsEInkMAFBVAT4+Pjg6dOnANI6ET/88IOw7Y8//kBMTAwuXbqE69ev49WrV6hUqZKyQpVz/fp1AEDr1q3h6ekprF+8eDEuXbqEDx8+4OrVq0ICQnqCQcqTkJAg/Ozo6IiqVasqLxgVpampCXNzc2G5evXqqF27Ntzd3SESibBp0yasXr1aKbGVL1++UJ6nqPyt5ibOkJAQAIC6ujpmzJgBLS0tAGkJpydPnmDLli2IiIhQqc9YIiLKnQoVKuDNmzeIiIjA69evYWlpCSA9AVGxYkXeHSpDT09Prs8zZ84chISE4PHjxwgJCUFqaio0NfP3kkJ8fDyAtP6VtbW1sF42jrw4cuSIkHgaNmwYJk6cKGyrWrUqbG1t0blzZyQnJ2P37t0qcyG5YsWK+Pnnn7F69WpERUVhy5YtGDlyJAIDA4XX06dPH9SpU0fJkWavfPnyKp9oyM6ePXsQHh4OIHO7qVy5MhwdHdGtWzd8/PgRv//+Ozp27AhtbW1lhSvn4cOHOHz4MADA3d0dixYtErbVqFEDampqWLlyJWJiYnDu3Lkie3F+yZIlkEgkMDY2xs6dO4W2VqVKFdSqVQudOnVCSkoKDh06VGRfY1ayO88xMjLKlPArKuduVLyxBBNREXDs2DEAaXeIZBxaq6amhsmTJ2PTpk24du2a3IUxiUQCHx8f9OzZEw4ODmjQoAH69++f5R28J06cQJ8+feDg4CDUtJw1axbevXsn7GNjYyOclAUEBGRZQ1eWtPN16tQp7Nq1S5inQkNDAydPnkRQUBDWr18PIO3unrVr1wqPdXJyQv/+/YVtNjY26NWrF3bv3o0mTZrAwcEBe/fuha+vr1Af8s6dO8Ljv1U30s/PD71794a9vT0cHR3Rp08fnDp1Stju4uIidOgfP34MGxsbrFmzRtiWVY39rGq3fytuAIiNjcWCBQvQsmVL2NraomPHjvjzzz8zlTz63tq+0piXLVuGoKAg9OrVC/Xr10ebNm2wYcMGoUPi7e0tvOdAek3Z169fAwCioqIwdepUODk5oV69eujatSt27dol16GRfd/PnDkDDw8P2NraYsCAAcI+R44cgYeHhzDHxPjx44W7ijK+n+PHj8f9+/cxcOBA2Nvbo3nz5li8eDGSk5Pl9o+Li8OSJUvQtm1boW7/pEmTMh03OTkZq1evRrt27WBra4s2bdpgyZIl2c5HoqhatWrB3t4eAHDx4kW5Gr3JycnYtGkTunXrBjs7Ozg6OuLnn38WLnhLSWvluri44NWrVxg1ahQcHBzQvHlzrF69GmKxGKdPn0bXrl1Rr149dO7cOVPbzqp95va9vHTpEgYMGICmTZvC1tYWLVq0wMSJE4V24OvrK/f7HDt2rFytbEXbdVBQEAYOHAhHR0fY2tqidevWmDhxIp49e6bQe75r1y50794dDRo0gJ2dHTp06IBly5YJSbRvfaZkRfp5JRaLMXnyZOFkEwAmTJiAoKAgBAUFoUKFCsJ6iUQixFG/fn00bdoUgwYNylTPWNo+27dvj/r166NBgwbw9PQUPgty8vTpU3h5ecHR0RF2dnbo2bOnytWpJiIqCiwtLWFmZgYgfRRERESE0L9t2LBhlo9TtE8t2w969OgR1q5di9atW6N+/fro3bu33He/ov3qM2fOyH33Hz169JuvccuWLUIMGcskzZw5U+hTyt50khs1a9YEkFa6UFpLXLavsXr1ajRo0ACOjo7CqAVF3j/peyd9TwIDA+X64BnngPhWfz0r0vkR9PX1MWrUqEzbK1eujFmzZmHVqlVYsWKF3Lac+kYA5M5JpH1mR0dHNGzYEL/++iuio6Pljpmb/v2wYcOEc7y///4b7969E+ZoK1OmDMaNGyfsm5e2KtufzG4OANl1Y8aMQb169eDs7IwPHz7kGL+i3r9/jylTpgjnTBMmTMi2Xr1IJML69evh4uKC+vXr48cff8T9+/cxaNAg2NjYwNvbW25/Rc4/snLixAkAacm4kSNHZtpevnx59OvXDwDw7t07BAUFwc/PT3i/zp07J7e/j4+PsO3hw4cA0n5n27Ztg5ubm9C+ZsyYgffv38s9VtrPX7JkCWbOnAk7Ozs0bdpUOE5Gsp8VgwcPzrS9b9++WLFiBS5fvqzQhfkXL15g6tSpQh/fxcUFCxcuzPQ7ym5Os+za/IsXL/DLL7+gQYMGaNy4MWbPni0kInMSHh4uzMHh7u6eKdFVqVIlrFy5EocPH85UKjc6Ohrz58+Hi4sLbG1t4ezsjGnTpmVKQktfj7e3N4KCgtCzZ0/Ur18frq6uOHHiBEQiETZu3IhWrVrB3t4e/fv3R1hYmPB42b+1+/fvY/HixWjWrBns7e0xfPjwLM99cmqv/fv3Fz7T4uPj5dp8xvd5zZo1ciPXe/ToARcXF2E5L58ZWZ3n379/HyNGjBDmGXF2dsbIkSPlrtFQycYREEQqLjU1VfhSrVOnDjQ0NDLtU6tWLdSqVUtunUQiwdixYzNNuhQcHIzg4GCMGzdO6ESdPXsW48ePl7uQHBERgT179uDatWs4ePBgnkq6dOzYEXv37kViYiLmzp2LRYsWwcHBAc7OzujUqVOu7yIODw/HnDlzhDjt7OxyPTHsn3/+iZUrVwrLCQkJCA0NxZgxYzB//nz07NkzV8dTRFZxJyQk4KeffpLrMD5//hwrV67EvXv35C6c5perV69i8+bNEIlEAIA3b95gxYoVMDMzg4eHxzcfGx0djV69esnNM/Lo0SPMnTsXL1++zLIcj7e3t5B0krbPjO9/cnIy/Pz8EBQUBB8fH1SuXFnuGOHh4ejXr5/QCZWW8DIwMMDo0aMBpHW6+vXrJ/deRkZG4siRIwgKCsK+fftgYWEBsViMkSNH4uLFi8J+b968webNmxESEoKdO3d+1x1L0hP9r1+/4tWrV6hSpQqSk5MxYMAAuQsAiYmJCAwMxMWLF7Fw4cJMScXY2Fj07dtXOFGNj4/HunXrcPv2bVy8eFFoR0+ePMH48eNRpUoV1K5dO8f4FHkvr127hp9//hmpqanC46Kjo3H06FHcvHkzx0ngFG3Xd+/exbBhw+SSEm/fvsXRo0dx5coVHDp0COXKlcv2eTZu3Ijly5fLrXvx4gX+/vtvREdH52mIcceOHYUTEz8/P/j5+aFKlSpo2bIl2rZti6ZNm2YqbTBjxgzs27dPWE5KSkJQUBCuXbuG9evXo1WrVgDSkjSy7S4pKQn37t3DzJkzoampKTeqLaPHjx+jb9++wt8SkFaeYvz48Xj//r1cMoiIiHLWoEEDnDhxAsHBwfD09BRGP5QvXz5TPwTIXZ9a1syZM+W+/2/evImff/4ZgYGB2c5pkNHFixfx77//yn33T5w4EZUqVRJufMioS5cuWLp0KUQiEU6dOiVchJJIJMIFJRcXF+jp6SkUgyyJRILHjx8DSLuhyNjYWG77hQsXhAS5pqYm6tevn+f3L79Jfxf169fPtrxojx49Mq1TpG+UcRTI0KFD5SaGPXbsGO7evYsDBw4o/LuXpa2tjWnTpmHkyJH4+vUrBgwYIFy0/PXXX4W7nQvjvf7zzz+FPomJiQlMTExyfEx0dHSmG16kr0t6wfjr16/o16+f3KTIx48fz3Z+llmzZsn1wUJCQjBgwIAsR1rk9vxDSiwWCyXB6tWrh1KlSmW5X+PGjYWfb9++jeHDh8PY2BgxMTE4duwY2rRpI2yXJgXq1q0rnB9l7E9GR0fDx8cHV65cwf79+zPdzb5v3z7hd6Cvr4/q1atnGZf0wq+urq7czUJSxsbGcHNzy/KxGYWEhGDYsGFyc6pFRERg27ZtOHPmDHbv3i0kd3MjKioKffr0kUti7N69G2fOnFHo8bIXt7MrgduuXbtM654/f45+/frJJXnevXuHAwcO4L///sO2bdsyXV8JDQ3F0aNHhc+CZ8+e4ddff4WTk5NcPz84OBjDhg3DqVOnhHJpUlOmTJH7bAgICMCtW7dw8OBBWFhYAMh7e82LvH5mZDzPf/PmDQYNGoTPnz8L+7x79w5nz57FlStX4OPjU+JKW1NmHAFBpOK+fPkiXKQrU6aMwo/bv3+/8EXSvn17+Pr6YteuXcIX86pVq3Dz5k0AwKFDhyCRSFC3bl0cOHAAZ86cwfTp0wGkTW5048YNAGl3IkmHPzs5OSEwMBCdOnXKNoZJkybJdQRSUlIQHByMP/74Ax06dMCMGTOEzujUqVMxaNAgYd8jR45g1apVcseLi4tDy5Yt4efnh1WrVmXqFOTk5cuXQmkce3t7+Pj44MCBA7C1tQUALFu2DImJidi7d69wUmdlZYXAwMAs7xpRVFZxb968GQ8fPoSGhgbmzp0Lf39/zJs3DxoaGjh9+rRcp2vq1KkIDAzM8eJvTm7fvo0ePXrAz88Ps2fPFtZLR9hMnTpVrrMzd+5cBAYGwsLCAitWrEBkZCT09fWxcuVK+Pv7C3dbbdu2TUiSyVJTU8O2bdvw77//om/fvnj16pVwZ1rHjh1x5MgR7Nq1CzVq1MCnT5+yvGgcFhaG5s2b48iRI1i7dq1wgid7R88///wjXPAeOXIk/Pz88Mcff0BbWxvR0dHYsGEDgLQ2Je0cjh07FidOnMCqVaugr6+PW7duYffu3Xl8Z9PI1k2Vdr7WrVsnnPD26dMHhw8fxqZNm1C1alWIRCLMmDEDb968kTvOly9fYGpqin379mHdunXCa75w4QI6d+4MPz8/4b0Xi8WZ7qzKjiLvpY+PD1JTU1GjRg0cOHAA/v7+wsXxV69e4enTp+jUqVOW7QSAwu36+PHjSElJQcWKFYWTjD/++ANaWlpITEyU68RnJBKJhJEDbm5u8Pf3x8GDB4W/44CAAACKfabIsre3x4QJE+SSDC9evMCOHTswaNAgdOvWLdPdTNKTxTZt2uDQoUPYtWsXLC0tkZqait9//x1A2sUi6cnzpEmTcObMGWzduhWGhoYA0mtaZ2f+/PmIjY2Fqakp/vrrL/j5+eHHH38EkFb7NePdcURE9G2NGjUCkD4CQvp/dqMfctOnlvXo0SMsX74cJ06cQMuWLQGk9Qml31OK9KtfvHgBLy8vnDp1ChMmTBDWHzlyJNvXV758eTg5OQGAXH/y5s2bws0NipYXSkhIQGRkJN68eYO7d+9i5syZwsUzJyenTDduxMbG4ocffsCJEyewZs0alClTRuH3z8HBIcv3JLs+eG76658+fUJSUhIAZLrBIS4uDpGRkZn+SW/YUaRvlFFUVBRWrFiBo0ePCjc3PX/+HFu2bBH2yW3/3sXFRbixQZp8qF+/vlzSJK9tNTdiY2Mxa9YsHD16FL/99ptCj+nWrRtatWqV6d/YsWOFfXbv3i0kH9zc3HD48GH8+eefWZaOefjwodAHs7Gxwb///gsfHx9Uq1YNL168kNs3L+cfUjExMUI7MDU1zXY/2RKoHz58gLa2tvA3dvbsWeHmn8jISLk5SIC0ksXS1/Ljjz/Cz88PmzZtgpmZGV6+fIl169Zler7Y2FjhnOf333/PtgyadHSKkZHRd80PkpqaikmTJuHr168oXbo0lixZAj8/P0yePBmampqIiIhQuC1ktGHDBrmRVMeOHcPvv/8ul+j4Ftl+cG6ulUydOhXv378Xknt+fn6YP38+9PX1ERMTg19//VVuRDuQ9jcsPRf75ZdfAKSdl1y8eBGTJ0+Gn58f2rdvDyDtM+Du3buZnvf58+eYM2cOjh8/LlzY//Tpk3COomh7XbVqFVxdXQGkjc4JDAzMdn6+wYMHy23766+/hHOpvH5mZDzPP3v2LD5//oxSpUphy5YtOHPmDP766y8hSf3ff/9969dBJQQTEEQqTvZum9zU7pN2ZCpWrIjly5ejbt26aNSoEdauXQttbW1IJBLhi0c6uuHdu3cIDQ1Famoq+vfvjytXruDKlSvCSYy5ubkwAkNHRwfm5ubfvHvK0NAQu3fvxqJFi9C4cWO5zpFYLIaPj49Qi9LIyEjujqDsaoWOHz8e1tbWwhdubpw5c0boSMybNw92dnawtbXFvHnzMHXqVKxevRrq6uooX768cEIlrfefl7uVvhW39GTD0dERrVq1gp6eHlq2bAlHR0cA6UkBIO29MTc3z9NdJbLMzMwwe/ZsWFtbo2/fvsLdMrKdU9n3XPq8ampqQomqjh07wsHBAXp6evDw8EDVqlUhkUjk4pVyd3dH06ZN0bBhQ1hZWeHMmTNCJ37UqFEwMjKCpaWlMGw5ICAgUykkLS0tLF68GDY2Nmjfvj2aN28OAHJ3yUhjq1u3LsaNGwdra2t06dIFs2fPxpIlS4Q7xKXvedWqVeHp6Ql9fX3Y29ujQ4cOAJDla8gNdfX0r1Tp69y/fz8AwMHBAXPmzEGtWrXg7OyMP/74A0DaHS1ZlVuYOHEi6tevj3bt2gl3i2hqamLu3LmwtraWKyX06dMnheJT5L1cunQpgoKC8M8//8DW1hblypVDlSpVhO1fvnyBnp5elu0EULxdSz9zYmJicP36dXz9+hWdO3fGhQsXcP369UyjQmRpaGjg7NmzOHPmDObNmwcrKyuULVsWFStWFGKUxqXIZ4qs4cOHY9++ffD09Mx0V+ejR48wdOhQ4W4fabuTvq+1a9dGo0aNMH/+fMycORPz5s2DWCxG9erVERoaiuPHj2Po0KGwtLRE2bJlhTsGZe8UyujTp09COSdPT0/Y2NigVKlS+Pnnn6Gvr4/k5GS58nFERJQzaaJBOg+EdM4yaWIio9z0qWX169cPnTt3RrVq1YT5zoD0fpci/Wo7OzuMGjUKVapUwfDhw4XktWyJ1Kx069YNQNrNN9KbNKTJCGNjY6EPkBNfX1+0atUKbdq0wQ8//AAfHx8AgIGBAaZMmZJpf3V1dUyePBnVqlUTSnwo+v5pa2tn+Z5k1wfPTX9d9uJrxouKGzZsyPLi+Nu3bwEo1jfKaNSoUXBzc0PNmjUxe/ZsoY8ie9NIXvr3v/32m/CapXNWyb62vLbV3KhVqxZ+/PFH1KxZU+jf5QfpzSdlypTB4sWLUatWLbi4uMglKaTOnz8v/Dx//nw0bNgQdnZ2+OOPPzJdaM/L+YeU9HHAt8/DZduUdD9pkio+Pl64+Hrs2DFIJBJoa2sL5YmkfWd9fX0MGzYMpUqVQo0aNYTR6VmdnxgbG2PMmDGwtraGs7NztnFJryNkbPO5dfnyZaEs0a+//gp3d3dYW1tjyJAh6NOnD4C0G6Uy3lSlCOnvvWbNmpg+fTpq1KiB7t27KzzCV/Z3pOjrDA8PF26wHDRoEAYOHAhra2v07NlT+Kx+8uRJpnK5WlpamDNnDqytreWSnXZ2dhgyZAisra3l5r2MiYnJ9Ny9e/dGnz59UL16dYwbNw4NGjQAkP7ZoGh7LVu2rPB9oaamBnNz82wnejcwMJC7Ua5s2bJC0iyvnxkZz/Ol53ZJSUm4evUqPn36hObNm+PkyZO4ceMGRowYkWVsVLKwBBORijM2Noa6ujrEYnG2NTbFYrHcxU8AwvBoBwcHubuTzMzMYGVlhbCwMDx58gRA2l3jV65cwbt37zB//nwAaZ365s2bo1+/ftkOZ1SEpqYmPD094enpibi4OFy9ehWnT5/G4cOHIRaLsX//fkycODHbIa0ZyU5G9y1ZdRKld8RoaGjIDVWtU6fOd0/cllNyKGPc0hqOV65cEe5mkpVdLc/vYWVlJddOpJ0U2SRXVj59+iRcdD148KBQb1JWVvFmfM2ydyRlVWc0NTUVT548kSspkPFkMquYpcfNOLQ4Y1kb6Xv+/PnzLN/zsLAwSCSSPN8hJHsCWrp0aXz8+FG4K6dJkyZy+9ra2sLAwABxcXHC36EsKysr4Wfp34a5ubnws+zfi2zH+1sUeS+BtPfh+PHjCAkJwfPnz+U68zk9l6Ltun///jh58iSePn2KP/74A3/88QeMjIzQtGlT9OrVCy1atPjm86SkpOD69es4d+4cbt68iaioKGHb955k1atXD4sWLYJYLMa9e/dw/vx57N69G9HR0Xj37h38/f3Rs2dPod2ZmZnJJSucnJyEpK3Uly9fEBAQgAULFuDu3btybeVb8b569Ur4bNmwYYMwmkdWQXxWEBEVZzY2NsJ38LFjx4TP84YNG2Z5l2Zu+tSyZPtBst8TOfW7ZGUsrWJgYIDY2Ngcj9G+fXvo6+sjPj4eJ0+eRK1atYTX5urqCi0tLYVjANIucOno6KBs2bKws7MTLn5mZGJikimBn9f3Lz8ZGxtDV1cXiYmJebpImtu+Ub169YSfNTU1UadOHUREROTpuWVVqVIF9vb2CA4ORrVq1TKdo+XHe53bcxpFBAUF5XgTiLTMa40aNeRK/8q+l1LSuTfU1dXlzuEqVaoEExMTubvi83L+IWVkZCSch8uWoc1Ith8qHWFTu3Zt1K1bF/fu3cPx48fRtWtXYdSxi4uL8HcijS8+Pl6uVJPUhw8fEB0dLTfKomrVqlmWZc6oTJkyeP78OT5//gyRSJTlY7K6jpCRtF0BQNOmTeW2NW3aFDt37hT2k50rLaOs2pb0fZWOZJbK6veeFdlRD4peK8np9cjuJ5tkk00Sy56Lyf5NyJZ3y+pzOuPfbP369XHjxg3ExMQgPj7+u9prXuTH9xuQNqru4MGDCAkJEc5Z9PX10bhxY3Tv3h2dOnX6rlE4VDxwBASRitPW1hbugH7w4EGWndxdu3bBzc0Nq1atEr54v9UpkX75S78EqlWrBn9/f8yfPx9t27aFkZERoqOjcejQIfTq1StTTUBF3Lp1C97e3vjf//4n1GY0MDBA27ZtsXjxYvz8888A0u4Al95hlBMtLa1v1ujPOPFvRtLXLRaLFb5om52Mj8/q+aSyiju7obJSit7VnhsZa1Aq0nEFco4VyDrejHeh5eU4isQs/b3mdDKe0/MnJSUpPOFZVqSdMz09PVSpUkWh1wsgy86Y7ImXtMMse1dkXjpwiryXK1aswKBBg3Dw4EHUqFED06dPlyvXlRNF27WJiQkOHz6M5cuXo3PnzihXrhw+f/6MkydPYsiQIXIlCjISiUQYPHgwvL29ceXKFbRu3RpLly4V7sDKC7FYjDlz5mDkyJHCUHd1dXXUq1cPv/zyC3bt2iXsKy17oGi7e/v2Lbp164alS5ciIiICvXv3xoYNGxRK7CrShrK6u4qIiLKnrq4uXLyRft8YGBhkW9ozN31qWbLfuzld4MtOxu9u6XFyukisr68v1D0/ffo0wsPDhe+vjBPDfku/fv0QFhaGhw8f4tatWzh37hxWrlyZ7UXorG4oyuv7l9+kdfrv3bsn19+cOHEiwsLCEBYWJsyJJSsvfaOM5wUF8TqzOlZe3+uczqFkfe+o8JxkbNtZxZubOdvyeh4jfR7pPGsZbyCRFRQUJPws27+T3gx18eJF3L59W7hpRPYu+bzEp+jvQHpRPzk5Wa6MqFRYWBicnZ0xa9asb97Qoki7AjL/rnJzvpzxhhxF/1ZkExfZTXbct29fDBs2DIcOHQLw7ff8W68nu8/03JyjZffZIH3s97TXvMjrZ0bGNqirq4udO3diw4YN8PT0RIUKFRAfH4+AgACMHz8eCxYsyLeYqehiAoKoCJCeKMTExAhfnFLJycnYs2cPwsPDsXHjRuGLvmrVqgDSJkuS/aKLiooS6mva2NgIk8mdP38eVatWxfr163H16lUcOnQIFhYWkEgk2LNnT6aYcjrxkUgkOHjwIC5duiQ3qZaU7BeZdEhgTl/YWd2tJbtOdvis7J0oUtJJryUSidycBaGhoejTpw+mT58u3MEt+zqyer6MQ3W/dVdMVnFLY2nfvr1w0hMWFoaDBw8iKChIKLuiCoyMjITf0aBBg+Ti3bdvH65fv55lGaGMHSjpa1ZTU8P169eFYwQEBODkyZN48OBBlnf+5ER63IzzUCxbtgzDhg0TJj6W7lenTh2513Ds2DGcP38eYWFhCo/Eyejt27fCUN6WLVtCU1MTpUuXFu72yvj7vHv3rtCGspoUThkSEhLwzz//AAAGDBiA1atXo1+/flnWU5X9W5X9G1G0XT9//hznz5+HgYEBli9fjkuXLsHf3x9169YFgG/Ox3H16lWhfu6SJUswd+5cdOvWLcsOtKInL+rq6ggKCsLZs2exa9cuuQmfMx5HOnJE+lqjo6OFmtpA2lD6/v37Y/bs2YiJicGePXsQHR0NdXV1+Pr6YuLEiWjTpg0SEhJyjMvS0lL4+bfffhPez3v37mHfvn0IDQ0V5rUhIiLFScstSZO4Dg4O2SYJFO1Tf4/clFlVlPTu2cePH2PTpk0AAAsLi2xLTeWHrPq8qvL+Sd+PlJQULF++PMt9Mtadz03fSJZs6RaRSCRc3JX9Xi8IuXmvc3MOJUvRG2xyS9qvevTokVzst27dyrSvtKSVdLSq1PPnzzPNjfW95x/S8/CkpKQs201ERITQb5Wdf0X6WB0dHaSkpGDOnDkA0u4slx3pK42vTJkyePDggRDfqVOn8N9//+Hhw4eoWbOm3HMq+juQTTZu27Yt0/Zt27bh/fv32LNnj5CgzIrsyOyM5zSyyxnbliLny9LXn3G+hKx+71mpXbs2qlWrBiBtXjvZ0rJA2hwbN2/exPnz5+Hn5wcg/e9E0deTnzKWdZK2XxMTE+jp6eWqvUrPTxT5/Mvu3C2vn88Z2+CbN29w4cIFJCQkYNGiRTh37hwCAgKE+Y98fHy++wZQKvqYgCAqAn788Ufhy2j27NnYtGkTnj17hpCQEIwYMUK489rT01OYIEta+zUiIgITJ07EvXv3EBISAi8vLyQnJ0NNTQ29evUCAIwZMwbjxo3D+PHjERgYiNevXyMqKkq4QCZ7YU96x8nr168RHh6e7VBiOzs7Ydi4j48PVqxYgYcPH+Lx48fYtm0bNm/eDCBteKU0Ztm7WUJDQxUqLSI7IdjevXuRnJyMp0+fCidastq3by+cXM6ePRs3btzA/fv3sXjxYqFGu3TYrDSW9+/f49GjR8IXsPT57t69K3xR//nnnzl21jNyc3MDkDYh0/bt2/H8+XMcP34cPXv2hJOTk9yEaJ8/f0ZkZGSunyM/SeP18fHB4cOH8eLFC2zbtg09e/ZEo0aNsGPHjhyP0aFDB2hpaUEikWDSpEm4f/8+7t+/j5EjR6Jjx45o3bp1jnddZXdcIO0Ee8mSJQgPD4e/vz+2b9+O8+fPCzVLO3fuDAC4f/8+VqxYgadPn+LChQvo27cvWrZsCS8vL4WeLzU1VZig8NWrVwgICMDw4cORmpoKdXV1DBkyRNhX+ncYGhqKOXPmICwsDBcvXsTEiRMBpN0tIq3xqmwpKSnChPfBwcEICwvD5cuX5SaclnYcZf9WHzx4gNu3b0MikSjcrufNm4dffvkF48aNw/Hjx/Hq1Su8e/dOOFH51t04sqNUTp8+jWfPnuHQoUNypcGkoxJy85kivRvtw4cPGD58OIKCgvDixQsEBgbK1e6W1rTu2LGj8J54e3vj3r17uHHjBlasWIHg4GBcvHgRRkZGwueoWCzGkSNH8PTpU6xYsUIY8vytERSlS5cWavv+9ddfOHPmDF68eIEVK1agZ8+eaNCgASd1IyLKg4wTTmc3ATWQuz51binar84LJycnoWyL9EYRNze3Qi+DURjvX8b+elY6d+4slMT08fHB+PHjcf36dbx69QoXL17EhAkTsHXrVrnH5KZvJOuff/7BoUOH8PjxY8yfP18oGSR7obsg+ve5ea9lz6F8fX0RFxeHqKioArmxITo6OsuJviMjI4W+n/S9+fz5M3799Vfcv38f//33nzA5r6x27doJ53QzZ87EjRs3cOPGDbmJ2qW+9/yjT58+wgXu3bt3Y9KkSbh16xZevnyJw4cPo1+/fsKNKxMnTpTrexoZGQmTEksvsLu7u8v1c6XnJ58+fcKMGTPw+PFj3LhxA4MGDULbtm0zlZTNDXt7e2H+wUOHDmH69Om4f/8+Hj58iEWLFuHAgQMA0qohSOPMipOTk3CO/Mcff+Dw4cMIDw/Hli1bhPkB2rRpI8xnIm1b0tKlIpEIvr6+CA0NzXRs6e/9yZMnmD17NsLCwnDo0CGFzi2BtAvrkydPBpCWUB4wYAACAwPx/PlzHD58WJhDRE1NTajAUL16daF019atW7Fz506Eh4fjwIEDwo1rNjY2cHBwUCiG3Dhy5Ai2bduG8PBwrFu3TpiDSPo+5Ka9ShM9iYmJuH379jfLq8m2yzt37gijRfLr83nDhg34+eefMXHiROzatQsvX75EVFSUMNedhoYGSzAR54AgKgoMDAywceNGDBkyBG/fvsXSpUuxdOlSuX3q168Pb29vYblfv364cOECzp8/j5MnT2YqozRhwgShtuL06dMxYsQIREdHC1/MUpqamnIXVGvWrIlnz54hPDwcbm5umDhxIoYNG5YpZjU1NSxevBiDBg1CXFxclvXLS5UqhXnz5gnL0lJTQNqkS9bW1sKdCtlxcHCAubk5IiMjcfLkSZw6dQoSiSRTHUkgLcM/YsQIrF+/Hvfu3UPfvn3ltk+ZMkWo21izZk1cvHgRMTEx6Nq1K/r27YvZs2fD1dUVwcHBSElJQZ8+faCmpgZ1dXXUrl070x3439KvXz8cOnQI4eHhWLBggdywRDMzMwwcOFBYXrRoEQ4ePAh9ff0sO26FYdSoUfjvv/8QHR0tdPKkatasqdBFdAsLCwwbNgzr16/HuXPn5CbiU1NTg5eXV66GVEsNHToUp0+fxpMnT7B582YhuQWk1WGVXjx2dXXF7t27ERwcnKk9GhgYYNSoUQo937Nnz7Kc3wBI+7uys7MTlseOHYtr167h3r17+Pfff/Hvv/8K2zQ0NDB//vzvnlw8v5QuXRqNGzdGcHAw7t69K3RIZUnvKqpatSq0tLSQkpKCjRs3YuPGjbh8+bLC7Vp68hYbG5vlyeLw4cOzjbNhw4YwNjZGTEwMDhw4IJw8ZYzT1NQ0V58pgwYNwoULFxAcHIyQkBAMGjQo0z4jR44Ujunk5ITu3bvj8OHDuHjxojCJHpD2u5VODOni4oLt27dDIpEId79ljPVbJk6ciJCQEERHR+OXX36R29akSZM8jRoiIirp6tevL3yPAdlPQA3krk+dW4r2q/NCQ0MDXbp0kStr2LVr13w5dm4U9PuXVX89K2pqali1ahXGjRuHK1euwM/PL8s+gZaWFvr37w9zc3Noamoq3DeSVbp06UyTdFtZWRV4/z4377WlpSVsbW2Fm6oaNWoEiUQCa2tr6OnpKTRSU1FZvW9So0ePxpgxY9CjRw8cOHAAd+/exalTp3Dq1CkAaX3Or1+/IjExUXhMpUqV0KtXL+zZswcPHz4UzunKlSsnzO8ivdj5vecf+vr6+OuvvzB06FA8f/4cR44cwZEjR+T2UVNTw7hx4+Du7p7p8T/88IPcRNIZz5ns7OyE/uT+/fuxf/9+YZuWllaW/eTcWLBgAT5+/Ijg4GDs27cvU2WCsmXLYuXKld8cVaGtrY1ly5Zh5MiR+Pz5c6ZzwUqVKmHu3LnCsqurq3Bj0NixY6Gmpiacn2cc6TBs2DCcOHFCGEkiHU1Sq1Ythec5a9OmDX777TcsXLgQjx8/znQ9A0hr+7Kf80uWLEH//v0RExMjdz0CSBuNktWE5vmhXLlyWLhwodw6ExMT4Ua43LRX6cgYiUSCnj17omXLlvj777+zfF7Zc6K5c+dCT08PN2/ezLfP55EjR+L8+fN4+/atXFuQGjp0aJ5LEVLxwRZAVERYW1vjyJEjGDlyJKpXrw4dHR3o6uqibt26mDx5Mnbt2iVXi09DQwMbN27E7NmzUb9+fejr6wsTAW3cuFHui7lFixbYvXs3OnbsCHNzc2hpacHY2BitWrXCtm3b5IaSjhkzBg0aNICenh7KlSuXaaI5WfXq1cPhw4fRp08fVK5cGVpaWtDT00PVqlXRt29fHDt2TKirCQDOzs7o1asXTExMoK+vLwyv/RZtbW38/fffaNKkCXR1dVGuXDn873//w/r167Pcf+zYsfj9999Rr1496OrqwsjICA0bNsS6devkasgPGjQILVq0QKlSpWBsbCzc9dG3b194eXnBzMwMurq6aNCgAbZs2SI3QZUiSpUqhX///Rf9+/dHxYoVoaWlBTMzM3h6emL37t0wNzfP1fEKmpmZGXx8fODp6Yny5ctDS0sLFStWRP/+/bF9+3aFa5GOHTsWixYtQr169aCnpwdDQ0M0bNgQ69evR48ePfIUm4GBAXbv3o2BAwcK72WFChXg7u6OPXv2CJOhqaur46+//sKoUaNQtWpVaGtro1y5cujYsSN2796dbe3nb9HU1ISJiQnatGmDrVu3ZrpooK+vjz179uDXX3+FjY0NdHV1YWhoiFatWmHnzp1KuRDwLdI5GcqUKQNDQ0PY29tj48aNQsmAwMBAAGmTOU6dOhWVKlUS5qlJSUlRuF3XqlULPj4+8PDwEPYzNDRE48aNsX79+ixP4KTKlCmDv//+G46OjtDX10e5cuXQpk0buQ63NM7cfKZoa2tj8+bNmDZtGuzs7FCqVCloaWmhXLlyaN26Nf7880+MGzdO7jGLFy/GtGnTULNmTWhra6Ns2bJo0aIFtm3bJiSpmjZtit9//1343K5YsSJ69+6N6dOnA0grF5Cx9Jss6XvVsWNHlClTBtra2qhSpQpGjRqFDRs2sDNPRJQHurq6ws0qWlpa35yXJzd96tzKTb86L2QnMbW2tpbrdxeWgnz/suuvZ6dMmTLYvHkzVqxYAWdnZ1hYWEBLSwtly5ZFo0aN4OXlhf/++w9TpkwRLsgq2jeStWTJEvTs2ROGhoYwMDBA165dsXPnzjyX+lRUbt/rdevWwcXFBfr6+jAyMkLPnj2xc+fOAiuz9C3a2trYsmULevfuDWNjY5QqVQpdunTBjh07siztNWPGDPzyyy8wNTWFrq4umjVrhh07dgjvsexjvvf8o1KlSjh8+DCmTJkCe3t7GBoaQktLCxYWFujWrRv27duHESNGZPlYJycnof/ZoEEDuXJGUgsXLsTUqVNRs2ZN6OjowNjYGC1atMDWrVvlyjXlhYGBAbZu3Yq5c+fCwcFB6N9WrlwZAwYMwJEjRxQqNeTk5ISDBw/C09MTZmZmwrngoEGDsH//frkRNa1bt8bs2bNRuXJlaGtro06dOli9enWW5z3Gxsb4999/0alTJ+HvuG/fvtmey2dnwIAB2LdvH9zc3FC+fHloamrC2NhYOEfL2PZr1qyJo0ePon///rC0tISWlhbKly+PHj16CPO9FIRJkyZh6NChKFOmDPT09NCmTRvs3r1b7oY0Rduru7s7OnbsCCMjIxgaGsLCwiLb561ZsyZGjBgBc3Nz6Orqolq1akhOTs63z2cLCwvs3bsX/fv3R5UqVaCtrQ19fX3Y2dlh4cKFmW6iopJJTVIQBSeJiIiIiIiISGnCwsKEu8+9vLx4EagA+fr6YurUqQCA/fv353lUB+UsMjISDx8+RIUKFWBpaSmMYAfSRjPFxsZi2LBhQslTImW6evUqBgwYAABYtWqVUBaLqKRhCSYiIiIiIiKiYiIiIgLJyclC6T91dfVvlsEhKkpiYmKEcp1169bFokWLoKWlBT8/P2E+BmmNfyIiUg1MQBAREREREREVE927dxcuxAJAly5dUKlSJSVGRJR/atasiQYNGuDGjRu4d+9epuRa1apV0bZtWyVFR0REWWHhYCIiIiIiIqJiol69etDW1oapqSn69euXaZJVoqJMXV0d69evR79+/YR5BqRzEvTu3Ru7du2Cjo6OssMkIiIZnAOCiIiIiIiIiIiIiIjyHUdAEBERERERERERERFRvuMcEEoiFouRmpoKdXV1qKmpKTscIiIiIirGJBIJxGIxNDU1oa7Oe5CUgf1/IiIiIioMqtb3ZwJCSVJTU3Hnzh1lh0FEREREJYi0NjwVPvb/iYiIiKgwqUrfnwkIJZFmn+rVqwcNDY1CfW6JRIIvX76gdOnSvPuKVALbJKkStkdSNWyTlB9EIhHu3LmjEndAlVTK6v/zM4RUDdskqRq2SVIlbI+UH1St788EhJJIP0Q0NDSUkoBQV1eHhoYGP8xIJbBNkipheyRVwzZJ+YltSHmU1f/nZwipGrZJUjVsk6RK2B4pP6lKG1KNNAgRERERERERERERERUrTEAQEREREREREREREVG+YwKCiIiIiIiIiIiIiIjyHeeAUHEikQgpKSn5ekyJRILk5GQkJiaqTC0wKr60tLQKfZ4TIiIiIiIiIiIiUj4mIFSURCJBZGQkYmJiCuT4YrEYHz58KJBjE2VkbGwMc3NzJryIiIiIiIiIiIhKECYgVJQ0+WBqagp9ff18vXArkUggEomgoaHBC8JUoCQSCeLj4/Hu3TsAgIWFhZIjIiIiIiIiIiIiosLCBIQKEolEQvLBxMQk34/PBAQVJj09PQDAu3fvYGpqynJMREREREREREREJQQnoVZB0jkf9PX1lRwJUf6QtuX8ns+EiIiIiIiIiIiIVBcTECqMoxOouGBbJiIiIiIiIiIiKnmYgCAiIiIiIiIiIiIionzHOSAoX7m4uCAiIiLLbdu3b0eTJk0yrb969SoGDBiAsLCwfI1lzZo1WLt2bbbbFy1aBE9Pz2y3BwUFwdTUFNbW1jk+l7e3NwBg8eLFuQ+UiIiIiIiIiIiIqBhiAqKYE4lFuPDyAt7GvoWFoQWcKztDXa1gB75MmzYNbm5umdYbGRkV6PNm9L///Q99+vQBAISGhmLMmDG4ePGisN3Q0PCbjx80aBC2b9+uUAKCiIiIiIiIiIiIiOQxAVGM+T7wxVj/sXj95bWwzrK0JVZ2XInuNbsX2PMaGhqifPnyBXZ8RZUqVQqlSpUCkJ78UIW4iIiIiIiIiIiIiEoCzgFRTPk+8EUPnx5yyQcAiPgSgZ77euLgw4NKigyIi4vDhAkT4ODggI4dO+LOnTty21+9eoVBgwbBzs4OXbt2xT///AMXFxdh+/Xr1+Hp6Yn69euja9euOHnyZJ7i+Pz5M2bMmIFmzZqhYcOGmDRpEj5//gwAwvMNGDAAa9asAQDs27cPrq6usLW1RZMmTTBnzhyIRKI8PTcRERERERERERFRcccREEWISCzCrahbiE+Jz3G/EcdGQAJJpm3Sdb+c+AXlS5WHpsa3m4C+lj7szOygoa6R98AzmDVrFp4+fYqdO3fi48ePwvwJAJCamorhw4ejevXqOHDgAB48eICZM2eiTJkyAIDo6GgMHz4c48ePh7OzM27evAlvb2+YmJigUaNGuYpj9OjRSEhIwIYNGwAAs2fPhre3N/7880/s378fTk5OWLNmDZo3b47g4GDMnz8fS5cuRZ06dXD37l1MmjQJTk5O6NChQ769N0RERFTMvHwJvH+f/fZy5YDKlQsvHiIiIiIiKnBZlcXPz+urRQkTEEVEsigZzlucERwRnC/Hi46PRpvtbRTat3HFxrgw+AK0NbQV2n/WrFmYN2+e3LoKFSrg+PHjiI2NxYkTJ7B9+3bUrVsXADBq1CjMnTsXAHDlyhW8ffsWPj4+MDAwQPXq1fHo0SMcP34cALBr1y40a9YMP/30EwCgSpUqePDgAbZt25arBMTDhw8RHBwMf39/WFlZAQCWLl0KNzc3PH36FNWqVQOQVrqpVKlS0NfXx4IFC4Rkg6WlJbZs2YLHjx8zAUFERERZe/kSsLEBEhOz30dXFwgLYxKCiIiIiKiYyK4s/irXVfCs7anEyJSDCYgi4tmnZ/mWfMit4IhgPPv0DDblbBTa38vLK9NFeU3NtKb27NkziEQi1KpVS9hWr1494eewsDBYWVnBwMBAWGdvby8kIJ4+fYpz587BwcFB2J6SkiIkERT19OlTlC5dWu5x1tbWMDIykktASNna2kJXVxerV6/GkydPEBYWhhcvXqBFixa5el4iIiIqQd6//3byAUjb/v49ExBERERERMWAtCx+xso0EV8i0MOnB/b32l/ikhBMQBQRVmWs0LhiY6UkIRpXbAyrMopf4DcxMUGVKlUU3l9bO31khYaGBiQS+T9Q2eXU1FR07doVI0aMkNtHmuDIy3PKEolEWc7rcOHCBfzyyy9wd3eHs7MzfvnlF8yZMydXz0lERERERERERETFk0gswlj/sdmWxVeDGsb5j0N3m+4lqhwTExBFhLaGNi7/77LCc0D03NcT0fHR2e5TXr88fHr4FPocENWqVYOWlhbu3LkDJycnAMD9+/eF7TVq1MDz588RFxcnjIK4d++esN3KygqhoaFyCY7NmzcjOTk5U1LiW6ysrPDlyxe50Q5PnjxBXFxclqMp9u3bhx9++AGzZs0CkJYIefnyJZo2bZqLV09ERERERERERETF0YWXF+TKLmUkgQSvvrzChZcX0Lpq68ILTMmYgChCNNQ10MCigUL7buiyAT18egCAXNZNDWoAgHWd1qFV1VZQU1PL9zhjY2MRHZ05+VGqVCkYGBige/fumDdvHhYtWoTExESsXbtW2MfJyQkWFhaYMWMGRo8ejcePH2P79u0wMjICAPz444/YsWMHVqxYAQ8PD9y5cwfLly/HwoULcxWjtbU1WrZsiSlTpmDGjBkAgDlz5sDR0RE1a9YEAOjr6+Px48eoU6cOjI2NERoairCwMKirq2Pjxo2Ijo5GcnJyXt8mIiIiIiIiIiIiKibexr7N1/2KC3VlB0AFw7O2J/b32o+KpSvKrbcsbYl9PffBo5ZHgT33woUL0aJFi0z/tm7dCgCYMWMGHBwcMHjwYHh7ewsTSgOAuro61qxZg6ioKHTv3h3r16+Hp6cntLS0AAAVK1bEhg0bcOHCBXTp0gUrV66Et7c3unXrlus4lyxZgkqVKmHQoEEYMmQIatSogXXr1gnb+/fvj99//x1r1qzB6NGjYWJigt69e2Pw4MHQ0dFB37598eDBg+97s4iIiIiIiIiIiKjIszC0yNf9igs1ScaC+yrg48ePOHDgAB48eIDx48ejUqVKyg4p34lEIty8eRP29vbQ0JAvb5SYmIhnz57BysoKurq63/c8YhEuvLyAt7FvYWFoAefKzlBXU4dIJIKGhkaBjID4Hh8+fMD9+/fh7OwsrNu0aRMCAwOxY8cOJUZG3yOnNi2RSPD582cYGRmpXJukkoftkVQN22QRduMG0LBhzvuFhAANFBvlmlff6ntS4VDW74CfIaRq2CZJ1bBNkipheyzaRGIRqq6qmm0ZJjWowbK0JZ6NfVagc0CoWt9f5UZA+Pv7w8XFBTt27MDly5fRsWNHrFixQth+9uxZ/PDDD3BwcICLiwuWLFmCxMREYXtISAhsbGwy/bt69Wq2z/n69WsMHz4cDRo0QIsWLbBy5Uq5iYj79+8PGxsbzJ8/P8vH//XXX7CxsYG3t3c+vAP5S0NdA62rtkbfen3RumrrIjHByciRI/Hvv/8iIiICly9fxrZt2+Dq6qrssIiIiIiIiIiIiIiypKGugVWuq7LcJi2Lv9J1ZZG4PpufVGoOiISEBEydOhUDBw5Es2bNEBwcDGtra4wfPx5t2rRBamoqRo8eDS8vL7i6uuLFixeYOXMmYmJisGjRIgBA2P+xd+dhUZfrH8ffw74oIIJi4r6waIILbpmW5Z4eW7TMzKU6RztpUpaUlpp2zDTzlKfllGbaZqXH6pdbpm2KAm5lrqkpKCJuICL7/P4ghhlABRycAT6v6+Jqnu96Dz7azNxzP/eBAzRs2JBPPvnE4toFPQSKys7O5pFHHqFx48Z89tlnHD9+nClTpuDg4MCECRNMxzk7O7N+/XqmTJlSLAO5evVqZSWtpHbt2ixYsIB///vfzJ49Gz8/Px566CEefPBBW4cmIiIiUjZ+fuDmBmZflinGzS3/OBERERERqfR6N+uNAYNFT17IXxZ/Qd8F3BNyj40isx27SkAcPnyY9PR0Bg0axJkzZwDo168fZ8+excfHh4ULF9KpUyfGjh0LQOPGjYmMjGTq1KnMmDEDFxcXDh48SPPmzfH39y/VPdetW8fJkyf5/PPP8fb2pmXLlpw9e5ZXX32VsWPH4uLiAkCnTp3YsmULO3bsoL1ZKf3Ro0f5888/adWqlZV/G9XXnXfeyZ133mnrMERERESuT8OGcOAAvPACLF2av83BAX76Cdzd88d+fvnHiYiIiIhIpRdzIsYi+fC3oL8xsfNEbm14a7WrfChgVwkIPz8/DAYDW7dupXnz5gAYDAZGjBgBwJgxY3BwsFw1ysHBgezsbNLS0vD19eXAgQMWCYJriYuLo1WrVhYVEp07dyYtLY19+/YRFhYGgL+/Px06dGDt2rUW11+9ejW33XYbZ8+eLffzFhEREZEqqmFDOHKkcNy2Ldxyi+3iERERERGRCrMlfovF+J7ge7it8W22CcZO2FUCIiAggNGjRzNr1ixCQkIIDAwkPj7e1IQ6NDTU4vjs7GyWLFlC69at8fX1BeDQoUPUqlWLe+65h6SkJFq2bElkZCRt2rQp8Z6nTp0iICDAYludOnUASExMNCUgIL8a49133+X55583Lbm0Zs0annzySZYWfKutjIxGI0X7gBeMS9pnbXbYg1yqoGvN6YLtmo9iDzQfxd5oTlZyWVkQG0vBYp3GLl3ABn+Wmj8iIiIiIhXPPAFR2702Xq5eNozGPthVAgJg8uTJ9OzZkyVLlrBx40bWrVvHwIEDmTNnjkXX7pycHJ599lkOHTrExx9/DOQnDC5evEh6ejpTp07F0dGRjz76iIceeoiVK1eaqirMZWRk4OVlORFcXV0ByMzMtNjep08fZs2axc6dO2nXrh0HDx4kMTGRHj16lDsBkZqaWqyqIysri7y8PHJzcy2aYVtTXl5ehVxXpCS5ubnk5eVx8eLFYn+vIP9DkfT0dAD1UxGb03wUe6M5Wbk5xsVR0+z/fenh4WSnpNzwOPTaT0RERESkYuUZ84hOiDaNm9ZqasNo7IfdJSAAIiIiyMvLIygoiODgYCZNmkRYWJhpKaa0tDQmTpxITEwMCxcuNFU31KtXj9jYWNzd3XF2dgbg5ptvZu/evSxbtowZM2YUu5ebmxtZWVkW2wo+IPXw8LDYXrt2bSIiIli3bh3t2rVj9erV9OrVy9Qnojy8vLwsEiuQnxQ5e/Ysjo6OxfZZU0VeW8Sco6MjDg4O1KxZEzc3t2L7C76V6e3trQ/XxOY0H8XeaE5Wcr/+ajH0uPNOMFv680apqC+1iIiIiIhIvv1n9nMh44Jp3MK3he2CsSN2lYBISkpi+/bt9O/fH8j/ll/v3r3p3r070dHRjBgxgtOnT/PYY49x4sQJFi1aREREhMU1ilYzODg40KxZM5KSkkq8Z0BAAAcPHrTYdvr0aQDq1q1b7Pj+/fvz9ttvExUVxZo1a5gyZUq5ny/kP8eiHyYUjEvaZw3mJfj6IENuhNLM6YJ9mpNiDzQfxd5oTlZi0YXfgKJ+fQwNG4IN/hw1d0REREREKlbR/g+qgMjncO1DbpyYmBgiIyM5evSoxfYzZ87g4+NDSkoKI0eO5Ny5c3z88cfFkg8//fQTbdu2JT4+3rQtJyeH/fv3l7j8EuRXW+zdu5e0tDTTtq1bt+Lp6UlwcHCx43v16kVycjLLly8nJSWFrl27Xs9TFhEREZGqymiELWZvQrp0sUnyQUREREREKp55AsLNyY2AGgFXObr6sKsERM+ePfH39ycqKoqjR49y4cIFFixYwO7du7nvvvuYPXs28fHxzJ07F19fX5KTk00/ubm5tGvXjlq1ajF58mT27NnDgQMHmDx5MhcuXGDUqFFAfn+F5ORk07JLd955J/7+/kycOJH9+/ezYcMG5s+fz5gxY0pcWsnX15dOnToxd+5cevfujZOTXRWR2IWUlBReeeUVevbsSVhYGP369WPJkiUWaw8HBQWxbdu2Crn/iBEjePPNN4ttf/PNNwkKCrriz8qVK6963ejoaA4fPlyqGKKiooiKiipX/CIiIlJFHD8OJ08WjvXFFRERERGRKss8AdHCtwUOBrv66N1m7OrTc09PTxYvXsysWbOYNWsWAM2aNWPhwoWEhYUxatQosrOzGTlyZLFzv//+ewIDA1myZAnz5s3jkUceITMzk/bt2/PRRx/h5+cHwM6dO3n44YdZunQpnTp1wtXVlffff58ZM2YwdOhQvL29efDBB3n88cevGGe/fv3YvHkzAwYMqJhfhDUcPw5nzpS8z2iEWrWgSROr3/b8+fPcf//91KlTh5dffpnAwEB+++03Zs6cSXx8PC+88ILV71laY8aM4YEHHgDy58H48eP55ZdfTPtr1qx51fNHjRrF0qVLadasWYXGKSIiIlXEFssSbCUgRERERESqpjPpZzhw9oBp3Mq/lQ2jsS92lYAAaNmyJUuXLmXr1q3ExsYyfvx4075fizTxK0nDhg154403rri/U6dOHDhwwGJbo0aNWLx48RXPWbZsmcV4yJAhDBky5KrH2NTx4xAUBBkZJe42AI5ubrB/PzRqZNVbv/baa7i4uLBo0SJcXV0BaNCgAW5ubjz++OM89NBDNKmAxEdpeHp64unpCeQ38gTw9/e3SSwiIiJSDZgnIFxdoW1b28UiIiIiIiIVZmvCVotxqH+ojSKxP3ZbBxIYGEjHjh1tHUbldObMFZMPBQwZGVeukCinrKwsvv32W4YPH25KPhS4/fbbWbJkCfXr1y92XmZmJnPnzqVHjx6Eh4czduxYEhMTAUhISCAoKIiEhATT8W+++SYjRowwjb/77jv69OlDeHg4L730Erm5ueWKPyUlhRdeeIGuXbvSvn17nnnmGVJSUoD85cEAHn74YdPyTl988QV9+/aldevWdOrUiRkzZpT73iIiIlIFmScgIiKghOU9RURERESk8ouOjzY9NmCgZe2WNozGvthdBUSBwMBAAgMDbR2GfcnNhd27IT396scVqfC4op074fLlqx/j4QFhYeDoeM3LHT9+nPT0dG6++eZi+wwGA507dy7xvGnTprFjxw7mzJmDj48P8+bN4/HHH2fFihXXvOcff/zBxIkTeeaZZ7j11lv58MMP2b59O126dLnmuUU98cQTXL58mXfeeQeA6dOnExUVxdtvv82XX35Jly5dePPNN7nllluIiYlh1qxZzJ07l9DQUPbs2cMzzzxDly5d6N27d5nvLSIiIlXMpUv5r9sKaPklEREREZEqa0tC4ZePAr0C8XD24NzlczaMyH7YbQJCisjKgltvhZgYq13S8NhjpTuwY0f4+edrfmsvNTUVuHYvBXMpKSl89dVXvPfee6YExbx587jtttvYvHnzNZdrWrFiBR06dDA1GX/hhRfYtGlTqe9fYP/+/cTExLB27VrTPefOnUv//v05cuQITZs2BfKXbvL09MTDw4OXX37ZlGwIDAzkgw8+4NChQ0pAiIiICMTG5n95pIASECIiIiIiVVJ2bjYxJwo/sw3xC7FhNPZHCYjK4uhRqyYfyiQmJv/+QUFXPczHxwfAtGxRafz555/k5eURFhZmcZ0mTZpw+PDhayYgDh8+TEhI4V9qZ2dni3FpHTlyBC8vL4v7NWvWDG9vb4sERIHWrVvj5ubGG2+8wR9//MGBAwc4duwY3bp1K/O9RUREpAoq2oC6HNWZIiIiIiJi/35N+pX07MIVa1rVUQNqc3bbA0KKaNIkvxLBFjp2zL//NTRs2JCaNWvy+++/l7h/3LhxbCnyZrxor4gCubm55OXlYTAYiu3LycmxGBuNRouxs7PzNWMtyuUK1R25ubkl9nX4+eefueeeezhz5gy33norb7zxBu3atSvzfUVERKSKMn/N07w51Klju1hERERERKTCbIm3/LxTFRCWVAFRWbi45L+RLW0PiEcfveYlje+9hyE4+OoHlaEHhJOTE/379+fjjz/m3nvvtfhQf+PGjWzcuJGnn37a4pwGDRrg5OTErl27uPXWWwE4f/48x44do0mTJqZkwqVLl0znmDekbtGiBTt37jSN8/Ly2L9/P8HXel5FNGnShNTUVItqhz/++IO0tLQSqzC++OIL7r33XqZNmwbkJ0WOHz9+xT4XIiIiUo3k5UF0YRM6Lb8kIiIiIlJ1mfd/8HL1oq5nXRtGY3+UgKhMHB2hNN+y9/Ao3fXatoX27a8vpiLGjx/PkCFDeOSRRxg/fjwBAQFs27aNuXPn8vDDD9O8eXOL4z09PRkyZAgzZ85k5syZeHt7M2/ePAICArjllltwcnKiXr16LFq0iPHjxxMbG8sPP/xAaGgoAEOHDmXZsmW8/fbb9OnTh+XLl3Py5Mkyx92sWTO6d+/O5MmTeeGFFwCYMWMGERERtGyZ37Xew8ODQ4cOERoaio+PDzt37uTAgQM4ODjw7rvvkpycTFZW1nX+BkVERKTSO3gQzpk1nFMCQkRERESkyjKvgGjp27LEFV2qMy3BVBX5+YGb21UPMbq55R9nZf7+/nz66ac0aNCASZMmcdddd/Hhhx8yYcIEoqKiSjxn8uTJdO3alQkTJjBs2DBcXV1ZsmQJLi4uODg48PLLL/Prr7/Sv39/1q5dy9ixY03nNmrUiLfffptvv/2WwYMHk5ycTI8ePcoV+5w5c2jQoAGjRo3ikUceoUWLFvznP/8x7R8xYgSvvvoqb775Jk888QS1a9fm/vvvZ/To0bi6ujJs2DD27dtXrnuLiIhIFVK0/4MSECIiIiIiVVJCagLHU46bxur/UJzBWHQBfbkhcnNz2bVrF+Hh4TgWWd4oIyODo0eP0qRJE9yukUi4ouPH4cyZEncZjUZya9XCsUkTZeTkhrjWnDYajaSkpODt7a05KTan+Sj2RnOyEnr0UVi0KP+xl1d+NUQplrOsSFd77Sk3hq3+DPRviNgbzUmxN5qTYk80HyufL37/gqFfDjWNX7njFUL981duSUhNoF6NegwOGXxDY7K31/5agqmqatgw/6ckRiOU0FhZRERERKzAvAKic2ebJx9ERERERKRimC+/5GhwpLlv86scXT1pCSYREREREWs5dw7Ml2Ts0sV2sYiIiIiISIUyb0Dd2KcxLo4uNozGPikBISIiIiJiLVu3Wo7V/0FEREREpEq6nH2ZHYk7TOOCpZfEkhIQIiIiIiLWYr78ksEAnTrZLhYREREREakw2xO3k5OXYxq38lcD6pIoASEiIiIiYi3mCYjWrcHb23axiIiIiIhIhTHv/wAQ5Bdko0jsmxIQIiIiIiLWkJMD27YVjrX8koiIiIhIlWWegKjtXpva7rVtGI39UgJCRERERMQafvsN0tMLx0pAiIiIiIhUSUaj0SIBEewXbMNo7JsSECIiIiIi1rDFsgRbCQgRERERkarp8PnDJKcnm8bq/3BlSkCIiIiIiFiDeQLC3x+aNbNdLCIiIiIiUmGK9n8I8Q+xUST2TwkIsbqUlBReeeUVevbsSVhYGP369WPJkiXk5eWZjgkKCmKb+RrJVjRixAjefPPNEvetXLmSnj17lvpay5cvp3PnzrRt25Y//vjDWiHaRFZWFm+99RZ9+vTh5ptv5vbbb2fWrFmcO3eu1Nco6+9PRESkWjFPQHTtCgaD7WIREREREZEKY56AcHV0pbF3Y9sFY+ecbB2AVC3nz5/n/vvvp06dOrz88ssEBgby22+/MXPmTOLj43nhhRdsHWKZzJ07l4cffph7772XgIAAW4dTbjk5OfzjH/8gISGBSZMm0bp1a+Lj41m4cCFDhgzhk08+oW7durYOU0REpPI6eRL+/LNwrOWXRERERESqLPMERLNazXB0cLRhNPZNCQixqtdeew0XFxcWLVqEq6srAA0aNMDNzY3HH3+chx56iCZNmtg4ytK7ePEiHTt2pH79+rYO5bp89NFH7Nu3j2+++QZ/f38A6tevT7t27Rg2bBgvv/wyb7zxho2jFBERqcSioy3HSkCIiIiIiFRJKRkp7Dm9xzQO9Q+1YTT2T0swidVkZWXx7bffMnz4cFPyocDtt9/OkiVLSvwgPzMzk7lz59KjRw/Cw8MZO3YsiYmJACQkJBAUFERCQoLp+DfffJMRI0aYxt999x19+vQhPDycl156idzc3FLHHBQUxFdffcVdd91F69atefDBB4mPjzftAxg5cqTpfgcPHmTEiBG0adOGPn368PHHH1vE9fjjjzN8+HA6duxITEwMWVlZzJo1i06dOtGpUycmTZrEhQsXLJ7b+vXrufPOO7n55pv5xz/+YdoP8NNPP3H33XcTFhbGoEGDiDb7cOO7776jf//+hIWFcd999xETE3PF5/nFF19wzz33mJIPBVxcXPj73//Ohg0bOH/+fKliKjB69GhmzZplsW3s2LEsWLDgmr93ERGRKsd8+SVnZ2jf3naxiIiIiIhIhdl2YhtGjKaxEhBXpwSEWM3x48dJT0/n5ptvLrbPYDDQuXNnXFxciu2bNm0a3333HXPmzOGzzz4jJyeHxx9/3KJnxJX88ccfTJw4kWHDhrFixQpycnLYvn17meJ+8803mTJlCitXruT8+fOmD9B/+eUX0/4333yTjIwMHnvsMdq3b8/XX3/N5MmTeeutt1i1apXpWt9//z133XUXH374IW3atGH+/Pns2bOH9957j6VLl5KWlsaTTz5pcf933nmH+fPn89FHH/Hbb7/xwQcfAHDo0CHGjRtHr169TEmSxx9/nOTkZPbv38/kyZMZN24cX3/9NYMGDeKxxx7j2LFjxZ5feno6hw8fLvHPBaB9+/bk5uby+++/XzMmcwMGDGD9+vUYjfn/4F68eJFffvmFAQMGlP6XLyIiUlWYJyDatQN3d9vFIiIiIiIiFaZoA+qg2kE2iqRy0BJMlc2qVfk/AE8/DeYfKiclweTJ+Y+7dIF//MPy3Jkz4fDh/Mfvv2+57/vvYdmy/Md//3u5lg1ITU0FoGbNmqU+JyUlha+++or33nuPzp07AzBv3jxuu+02Nm/efM3lmlasWEGHDh0YNWoUAC+88AKbNm0qU9yjR4+mS5cuAAwbNsxU1VBQLeDt7Y2Pjw9ffPEFtWvXZuLEiQA0btyYEydOsHTpUgYPHgyAn58fw4YNA+Dy5ct89NFHrFixwlRN8eqrr9KpUycOHDiAp6cnABMmTKBNmzYADBw4kN9++w2AL7/8knbt2vH4448D8Pe//5309HRSU1NZtGgRQ4cOZeDAgQA8/PDDxMbG8umnnxIVFWXx/C5evIjRaMTb27vE5+/l5QVgUeVwpZjM9e7dm+nTp7Njxw7at2/Phg0baNKkCS1atLjm71xERKRKycgA8y9AaPklEREREZEqyzwBUa9GPWq6lv6z0OpICYjKJj0dzp7Nf5ydbbkvL69wX1pa8XNTUgr3F5WRUbgvM7Ncofn4+Px1m5RSn/Pnn3+Sl5dHWFiYxXWaNGnC4cOHr5mAOHz4MCEhIaaxs7Ozxbg0GjVqZHpco0YNsov+Xv9y5MgR9u/fT9u2bU3bcnNzcXQsbDJjvsRUfHw82dnZPPDAAxbXycvL488//6RVq1ZXvf/Ro0dNxxQoSH4cPnyYNWvWsHz5ctO+7OxsunXrVizugsRDcnJyic/r9OnTQOGf39ViMufl5UX37t1Zu3Yt7du3Z82aNfTv37/Ee4iIiFRp27dbvi7764sNIiIiIiJSteTm5bLtxDbTONgv2IbRVA5KQFQ2Hh5Qu3b+Y2dny30ODoX7atQofq63d+H+otzcCvcV6d9QWg0bNqRmzZr8/vvvpm/Pmxs3bhwjRoygq9m3Aov2iiiQm5tLXl4eBoOh2L6cnByLccESQAWci/5erqG0x+fk5NClSxdefPHFKx5j/nwKelF88skneHh4WBxXu3ZtU8XBle7v5HTlv565ubk89thjpsqLAm5ubsWOdXNzo2XLlvz+++/87W9/K7Z/z549ODo6EhoaSnp6+lVjKuquu+5izpw5jB8/ni1btjB16tRSnSciIlKlbLEswVYCQkRERESkatqbvJfUzFTTuLV/axtGUzmoB0RlM3gwLFmS/1N0Tf+6dQv3FV1+CeCFF/L3lbCeP3fcUXhuOZcNcHJyon///nz88cdkZWVZ7Nu4cSMbN26kTp06FtsbNGiAk5MTu3btMm07f/48x44do0mTJqYPwi9dumTab96QukWLFhbLA+Xl5bF///5yxX8tTZo04ejRowQGBtKoUSMaNWrErl27WFawdFURDRo0wNHRkQsXLpiOr1GjBrNnz+bslSpRzDRq1KjYc3nggQf49ttvadKkCQkJCabrNmrUiOXLl/PTTz+VeK0HHniAL774gqSkJIvtOTk5vP3229x55534+vqW8jdRqGfPnqYloYKCgmjYsGGZryEiIlLpmScgGjaEwEDbxSIiIiIiIhWmaP+HEP+yrcRSHSkBIVY1fvx40tLSeOSRR4iJieH48eN88cUXREVF8fDDD9O8eXOL4z09PRkyZAgzZ85k27Zt7N+/n2eeeYaAgABuueUW/Pz8qFevHosWLSI+Pp6VK1fyww8/mM4fOnQoe/bs4e233+bIkSPMmTOHkydPVshzGzRoEBkZGbz44oscPnyYH3/8kZdffpnaV6gqqVGjBkOGDGH69Ols27aNP/74g2effZZjx44RWIoPJoYNG0ZcXBwffPABx44d49133+XQoUOmnherV69m6dKlHD9+nCVLlrBkyRIaN258xWtFREQwYsQIvvvuO06ePElcXByPPfYYFy9eZMqUKeX6nbi5uXHHHXfwwQcfqPm0iIhUT0ajZQJC/R9ERERERKqsLQmFr/09nT25qeZNNoymclACQqzK39+fTz/9lAYNGjBp0iTuuusuPvzwQyZMmFCsOXKByZMn07VrVyZMmMCwYcNwdXVlyZIluLi44ODgwMsvv8yvv/5K//79Wbt2LWPHjjWd26hRI95++22+/fZbBg8eTHJyMj169KiQ51ajRg3ee+89/vzzTwYPHszUqVMZPnw4/yip2uQvUVFRdOnShQkTJjB06FCcnJz473//a9E34koaNmzIm2++yYoVK7jrrrtYt24d77zzDnXr1iU8PJxXX32VTz75hP79+/P555/z2muvERERUeK1HBwceOuttxg6dCgLFiygb9++TJo0iWbNmvHll19St27dcv9e+vfvT1ZWlvo/iIhI9XTkCPzVTwlQAqKczp07x3vvvcdTTz1FfHy8rcMRERERESmReQVEC98WOBj08fq1GIxFF9CXGyI3N5ddu3YRHh5e7MPojIwMjh49SpMmTUpc0/96GY1GU/PkknosiJTF559/ztdff81HH310xWOuNaeNRiMpKSl4e3trTorNaT6KvdGctHMffQQjRhSO4+KgfXvbxXMFV3vtaWtr164lKioKLy8vsrKySE1N5bHHHiMyMhLIX8rzP//5D0eOHKFWrVr06dOHJ5980vSaIjMzk1deeYW1a9eSkZFBz549mTJlylWXl0xISGDmzJnExsbi4eHBfffdx/jx402/mxEjRhATE8OIESNK7HH13//+l9dee427776bV155pVTP01Z/Bvo3ROyN5qTYG81JsSeaj/bt9KXT1J1X+CXe4a2Hc3/r+694fEJqAvVq1GNwyOAbEF0he3vtrybUIlIux44dMy1/NXHiRFuHIyIiYhvmyy95eECbNraLpRK6fPkyzz33HCNHjqRr167ExMTQrFkzIiMjuf3228nJyeGJJ55gwoQJ9O3bl2PHjvHiiy9y4cIFZs+eDcD06dOJi4vjzTffxMXFhWnTpjFhwoQrfjkiOzubRx55hMaNG/PZZ59x/PhxpkyZgoODAxMmTDAd5+zszPr165kyZUqxDwBWr16tDwVEREREqpno+GiLcah/qI0iqVxUIyIi5ZKQkMCUKVNo164dAwcOtHU4IiIitmGegOjYEZydbRdLJXT48GHS09MZNGiQaVu/fv2YOnUqPj4+fPbZZ3Tq1ImxY8fSuHFjevToQWRkJN988w1ZWVkkJSWxatUqpk6dSocOHWjTpg3z588nNjaWnTt3lnjPdevWcfLkSV599VVatmzJnXfeyVNPPcWHH35IVlaW6bhOnTqRnJzMjh07LM4/evQof/75J61ataqYX4qIiIiI2CXz5ZccDA60qN3ChtFUHqqAEJFyueWWW9i1a5etwxAREbGd1FT47bfCsfo/lJmfnx8Gg4GtW7fSvHlzAAwGAyP+WtZqzJgxODhYfmfKwcGB7Oxs0tLS2L59OwCdO3c27W/SpAl169YlNjaWtm3bFrtnXFwcrVq1wtvb27Stc+fOpKWlsW/fPsLCwoD83mYdOnRg7dq1tDdbVmv16tXcdtttnD171kq/BRERERGpDMwbUDfwaoCbk/WXzq+KlIAQERERESmPmBjIyyscKwFRZgEBAYwePZpZs2YREhJCYGAg8fHxNGjQAIDQUMuy9uzsbJYsWULr1q3x9fUlKSmJWrVq4erqanFcnTp1OHXqVIn3PHXqFAEBAcWOB0hMTDQlICC/GuPdd9/l+eefNy25tGbNGp588kmWLl1arudsNBq5kW34Cu6n1n9iLzQnxd5oToo90Xy0X1m5WcSeiDWNQ/xCrvnnZDQaMXLj/zztbf4oASEiIiIiUh7myy8BmH0LX0pv8uTJ9OzZkyVLlrBx40bWrVvHwIEDmTNnjkXTvJycHJ599lkOHTrExx9/DOT3kHBxcSl2TVdXVzIzM0u8X0ZGBl5eXsWOB4qd06dPH2bNmsXOnTtp164dBw8eJDExkR49epQ7AZGamlqsqqMiGY1G0tPTAdS3QuyC5qTYG81JsSeaj/Yr7lQcmbmFrxWbezfnUvqlq55zOeMylxwukZKSUtHhWcgz/5KUHVACwo7Z22QRKS/NZRERqZLMExDBwVC7tu1iqeQiIiLIy8sjKCiI4OBgJk2aRFhYmGkpprS0NCZOnEhMTAwLFy6kzV/Nvt3c3Cz6NhTIzMzE3d29xHuVdE5B4sHDw8Nie+3atYmIiGDdunW0a9eO1atX06tXrxKTHqXl5eVlkVipaAXfgPP29tYHGWIXNCfF3mhOij3RfLRfv+771WIcdlMYnh6eVz3HPccdT09Pi6U/b4Tc3Nwber9rUQLCDrm4uODg4MDJkyfx9/fHxcXFqv/oGI1GcnNzcXR01D9mUqGMRiNZWVkkJyfj4OBwXW/WRURE7EpeHkRHF461/FK5JCUlsX37dvr37w/kf9Ovd+/edO/enejoaEaMGMHp06d57LHHOHHiBIsWLSIiIsJ0fkBAABcuXCArK8vidcbp06epW7duifcMCAjg4MGDFttOnz4NUOI5/fv35+233yYqKoo1a9YwZcqU63rOBoPhhr8GL7inXvuLvdCcFHujOSn2RPPRPkUnFL7293H1oY5nnWv+GRkMBgzY5rWfPVECwg45ODjQpEkTEhMTOXnyZIXcIy8v74aWfkv15uHhQcOGDTXnRESk6ti7N78JdQElIMolJiaGSZMmERISYrH9zJkzNG3alJSUFEaOHElaWhoff/wxQUFBFse1b9+evLw8tm/fTpcuXQA4evQoSUlJFokKcxEREaxatYq0tDRq1KgBwNatW/H09CQ4OLjY8b169eKll15i+fLlpKSk0FV/1iIiIiLVitFoZEt8YfVzS7+Wdvchvz1TAsJOubi40LBhQ3JycqxeNmM0Grl48SI1a9bUXxapcI6Ojjg5OWmuiYhI1VK0/8NfH35L2fTs2RN/f3+ioqK4++67uXDhAgsWLGD37t08++yzzJ49m/j4eN5//318fX1JTk42nevr60vdunUZMGAAU6dO5V//+hfu7u5MmzaNjh07Eh4eDkBWVhYpKSl4e3vj4uLCnXfeyYIFC5g4cSKTJk0iISGB+fPnM2bMmBKrNX19fenUqRNz585lwIABODnpLZSIiIhIdRKfGs/Ji4VfEm/t39qG0VQ+evVsxwwGA87Ozjg7O1v1ukajkczMTNzc3PShsIiIiEh5mCcgfHzye0BImXl6erJ48WJmzZrFrFmzAGjWrBkLFy4kLCyMUaNGkZ2dzciRI4ud+/333xMYGMjMmTP517/+xRNPPAFA9+7dmTp1qum4nTt38vDDD7N06VI6deqEq6sr77//PjNmzGDo0KF4e3vz4IMP8vjjj18xzn79+rF582YGDBhg5d+AiIiIiNg78+oHgBD/kCscKSVRAkJEREREpKzMExBduoCWGSy3li1bsnTpUrZu3UpsbCzjx4837fv111+vcmY+Dw8PiwRGUZ06deLAgQMW2xo1asTixYuveM1ly5ZZjIcMGcKQIUOueoyIiIiIVE3mCQgnByea+jS1YTSVjxIQIiIiIiJlkZwMhw4VjtUTwCoCAwNVnSsiIiIidsc8AdHUpynOjtZdraaqUwJCRERERKQsoqMtx0pAWEVgYCCBgYG2DkNERERExORS1iV2ndplGof6h9oumEpKteIiIiIiImVhnoBwcICOHW0Xi4iIiIiIVJjYk7HkGnNNYyUgyk4JCBERERGRsjDv/xAWBjVq2C4WERERERGpMEUbUAf7BdsokspLCQgRERERkdLKzoaYmMKxll8SEREREamyzBMQ/h7++Lj52C6YSkoJCBERERGR0tq1CzIyCsdKQIiIiIiIVEl5xjyiEwqXX1X1Q/koASEiIiIiUlpbLEuwlYAQEREREamaDp49yLnL50zjVv6tbBhN5aUEhIiIiIhIaZknIOrVg0aNbBeLiIiIiIhUmKL9H0L8Q2wUSeWmBISIiIiISGmZJyC6dgWDwXaxiIiIiIhIhYmOL1x+yc3JjYZeDW0YTeWlBISIiIiISGnEx0NCQuFYyy+JiIiIiFRZWxIKv3zUvFZzHB0cbRhN5aUEhIiIiIhIaaj/g4iIiIhItXD+8nn2Ju81jUP9Q20YTeWmBISIiIiISGmYJyBcXKBtW9vFIiIiIiIiFWZrwlaLsRpQl58SECIiIiIipWGegOjQAVxdbReLiIiIiIhUGPMG1AYMtKzd0obRVG5KQIiIiIiIXMulS7BzZ+FYyy+JiIiIiFRZ5v0f6tesj6eLpw2jqdyUgBARERERuZa4OMjNLRwrASEiIiIiUiXl5OWwLWGbaRzsH2zDaCo/JSBERERERK4lOtpy3KWLbeIQEREREZEK9VvSb1zKvmQat/ZvbcNoKj8lIERERERErsW8/0PTphAQYLtYRERERESkwpj3fwAI9lMFxPVQAkJERERE5GqMRssEhJZfEhERERGpssz7P9RwqUG9GvVsGE3lpwSEiIiIiMjVHDoEZ88WjpWAEBERERGpsswrIFr6tsRgMNgwmspPCQgRERERkavZYlmCrQSEiIiIiEjVlHgxkT8v/Gkat/JvZbtgqgglIERERERErsY8AVGjBrQuRxO6nBz4+GPYsyf/sYiIiIiI2J3ohGiLcah/qI0iqTqUgBARERERuRrzBETnzuDoWPZrGAwQFATR0bB8ufViExERERERqzFffsnB4EBz3+Y2jKZqcLJ1ACIiIiIiduvCBfj998JxeZdfcnSEDh3yf0RERERExC6ZJyAaezfG1cnVhtFUDaqAEBERERG5kq1bLcfq/yAiIiIiUiVl5GSwPXG7aRziH2LDaKoOJSBERERERK7EfPklgwE6dbJdLCIiIiIiUmF2JO4gKzfLNFYDautQAkJERERE5ErMExChoeDjU/ZrHDsGe/eq+bSIiIiIiB0zX34JINgv2EaRVC3qASEiIiIiUpKcHNi2rXBc3uWXvv4a1q8HDw+YPRuaNrVOfCIiIiIiYjXmCQhfd1/8PPxsGE3VoQoIEREREZGS7NkDaWmF4/IkIIxG2Lkz/3F2NtSvb53YRERERETEaoxGo0UCIqh2kA2jqVpUASEiIiIiUpItliXY5U5ADB8OO3bkj11drz8uERERERGxqqMXjpJ0Kck0Vv8H61ECQkRERESkJNHRhY9r14YWLcp+DQcHuOOO/B8REREREbFLRfs/hPiH2CiSqkdLMImIiIiIlMS8AqJrVzAYbBeLiIiIiIhUGPMEhLODM018mtgwmqpFCQgRERERkaJOnYIjRwrH5W1ALSIiIiIids88AdGsVjOcHLRwkLXYZQLi3LlzvPfeezz11FPEx8fbOhwRERERqW7Ml1+C8iUgzpyBEyfy+0CIiIiIiIhduph5kd9O/2Yah/qH2jCaqsfuEhBr166lZ8+eLFu2jC1bttCnTx9ef/110/6NGzdy77330rZtW3r27MmcOXPIyMgw7c/MzGTGjBl06dKFtm3b8vTTT3Pu3Lmr3jMhIYF//OMftGvXjm7durFgwQJyc3NN+0eMGEFQUBCzZs0q8fz//ve/BAUFERUVdZ3PXkRERETsgvnyS05O0KFD2a+xejWMHQuPPgoHDlgvNhERERERsZqYEzHkGfNMYzWgti67qiW5fPkyzz33HCNHjqRr167ExMTQrFkzIiMjuf3228nJyeGJJ55gwoQJ9O3bl2PHjvHiiy9y4cIFZs+eDcD06dOJi4vjzTffxMXFhWnTpjFhwgQ++uijEu+ZnZ3NI488QuPGjfnss884fvw4U6ZMwcHBgQkTJpiOc3Z2Zv369UyZMgVDkfV/V69eXWybiIiIiFRi5gmItm3Bw6Ps19i5M/+/p09D3brWiUtERERERKyqaAPqIL8gG0VSNdlVBcThw4dJT09n0KBBpm39+vVj6tSp+Pj48Nlnn9GpUyfGjh1L48aN6dGjB5GRkXzzzTdkZWWRlJTEqlWrmDp1Kh06dKBNmzbMnz+f2NhYdha8ASxi3bp1nDx5kldffZWWLVty55138tRTT/Hhhx+SlZVlOq5Tp04kJyezY8cOi/OPHj3Kn3/+SatWyoyJiIiIVAmZmRAXVzguz/JLRiN07w7h4RAUBD4+1opORERERESsaEtCYQIiwDMAL1cvG0ZT9dhVBYSfnx8Gg4GtW7fSvHlzAAwGAyNGjABgzJgxODhY5kwcHBzIzs4mLS2N7du3A9C5c2fT/iZNmlC3bl1iY2Np27ZtsXvGxcXRqlUrvL29Tds6d+5MWloa+/btIywsDAB/f386dOjA2rVrad++venY1atXc9ttt3H27Fkr/RZERERExKZ27ACzL6KUKwFhMMDdd+f/qAeEiIiIiIhdyjPmER1f2P8t2C/YhtFUTXaVgAgICGD06NHMmjWLkJAQAgMDiY+Pp0GDBgCEhlo2AMnOzmbJkiW0bt0aX19fkpKSqFWrFq6urhbH1alTh1OnTpV4z1OnThEQEFDseIDExERTAgLyqzHeffddnn/+edOSS2vWrOHJJ59k6dKl5XrORqMR4w1+U1pwzxt9X5Er0ZwUe6L5KPZGc9IGNm/GfHFNY5cu159EsPGfn+aPiIiIiEhx+5L3kZKZYhqr/4P12VUCAmDy5Mn07NmTJUuWsHHjRtatW8fAgQOZM2cOjo6OpuNycnJ49tlnOXToEB9//DGQ30PCxcWl2DVdXV3JzMws8X4ZGRl4eXkVOx4odk6fPn2YNWsWO3fupF27dhw8eJDExER69OhR7gREampqsaqOimY0GklPTwdQ7wqxC5qTYk80H8XeaE7eeB4//UTBK8q8+vVJrVkTUlKueo69y8vLu/ZBIiIiIiLVTNH+DyH+ITaKpOqyuwQEQEREBHl5eQQFBREcHMykSZMICwszLcWUlpbGxIkTiYmJYeHChbRp0wYANzc3i74NBTIzM3F3dy/xXiWdU5B48CjSbLB27dpERESwbt062rVrx+rVq+nVq1eJSY/S8vLyskis3AgF34Dz9vbWBxliFzQnxZ5oPoq90Zy8wYxGiI01DQ233GKxVGeppKXlX6dmTSsHV365ubm2DkFERERExO6Y93/wcPIg0CvQhtFUTXaVgEhKSmL79u30798fyP+WX+/evenevTvR0dGMGDGC06dP89hjj3HixAkWLVpERESE6fyAgAAuXLhAVlaWRVLg9OnT1K1bt8R7BgQEcPDgQYttp0+fBijxnP79+/P2228TFRXFmjVrmDJlynU9Z4PBYJMPEwruqw8yxF5oToo90XwUe6M5eQP9+SeYLd1p6No1v59DWWzcCIsWQfPm8NhjEGL7b1Fp7oiIiIiIFGdeAdGidgscDDd2pZrqwK5+ozExMURGRnL06FGL7WfOnMHHx4eUlBRGjhzJuXPn+Pjjjy2SDwDt27cnLy/P1Iwa4OjRoyQlJRU7tkBERAR79+4lLS3NtG3r1q14enoSHFy86UivXr1ITk5m+fLlpKSk0LU8TQlFRERExD5tsSzBLlcD6p078ysgDh2CGjWsE5eIiIiIiFjVmfQzHDxb+MX0UL/Qqxwt5WVXCYiePXvi7+9PVFQUR48e5cKFCyxYsIDdu3dz3333MXv2bOLj45k7dy6+vr4kJyebfnJzc6lbty4DBgxg6tSpbNu2jV9//ZWnnnqKjh07Eh4eDkBWVhbJycmmZZfuvPNO/P39mThxIvv372fDhg3Mnz+fMWPGlLi0kq+vL506dWLu3Ln07t0bJye7KiIRERERkethnoBwd4e/XkOWSYsW0Lgx+PlBoEq4RURERETsUXR8tMU41F8JiIpgV5+ee3p6snjxYmbNmsWsWbMAaNasGQsXLiQsLIxRo0aRnZ3NyJEji537/fffExgYyMyZM/nXv/7FE088AUD37t2ZOnWq6bidO3fy8MMPs3TpUjp16oSrqyvvv/8+M2bMYOjQoXh7e/Pggw/y+OOPXzHOfv36sXnzZgYMGGDl34CIiIiI2FS02ZuQiAhwdi77NYYPz//JyCj78k0iIiIiInJDmC+/ZMBAi9otbBhN1WVXCQiAli1bsnTpUrZu3UpsbCzjx4837fv111+veb6Hh4dFAqOoTp06ceDAAYttjRo1YvHixVe85rJlyyzGQ4YMYciQIVc9RkREREQqmbQ02L27cHy9S226uV3f+SIiIiIiUmHMG1A38GqAh7OHDaOpuuwuAVEgMDBQzfJERERE5MaJiYG8vMKxen2JiIiIiFRJ2bnZxJ6INY1D/ENsGE3VZtcJiECtmSsiIiIiN0rRBtRdupTt/Kys/CWXyrNsk4iIiIiI3DC7k3ZzOeeyadzKv5UNo6na7KoJtYiIiIiIzZgnIFq2zG8iXRabN8OwYTBjBuzbZ93YRERERETEasz7PwAE+wXbKJKqTwkIEREREZG8PMsG1OVZfmnnTsjMhLg4yM21XmwiIiIiImJV5gkIL1cv6nrWtWE0VZsSECIiIiIi+/fDhQuF4/IkIHx8wNc3v/l0sL5BJSIiIiJir8wTEEG1g9SLuALZbQ8IEREREZEbpmj/h/IkIMaMgdGjITkZnPQyW0RERETEHsWnxBOfGm8aq/9DxVIFhIiIiIiIeQLC2xtCQsp3HYMB6tSxTkwiIiIiImJ10QnRFuNQ/1AbRVI9KAEhIiIiImKegOjcGRz0MllEREREpCoyX37JyeBEs1rNbBhN1ad3ViIiIiJSvZ05AwcOFI7LuvyS0Zj/IyIiIiIids88AdHYpzHOjs42jKbqUwJCRERERKq3rVstx2VNQOzaBaNGwYIFlokMERERERGxK+nZ6ew8tdM01vJLFU8JCBERERGp3syXX3JwgI4dy3b+zp1w7hx8/31+NYWIiIiIiNiluJNx5OTlmMZKQFQ8JSBEREREpHozT0DcfDN4eZXt/JwccHXNb0Ddpo11YxMREREREasxX34JINgv2EaRVB9Otg5ARERERMRmsrMhNrZwXNbllwD+/ncYPRqOHoWaNa0Xm4iIiIiIWFV0QrTpsZ+HH77uvjaMpnpQBYSIiIiIVF+//grp6YXj8iQgAJydoWVL68QkIiIiIiJWZzQaLSoggmur+uFGUAJCRERERKqvLZYl2OVOQIiIiIiIiF3749wfnEkv7NnWyr+VDaOpPpSAEBEREZHqyzwBUbcuNGliu1hERERERKTCFO3/EOIfYqNIqhclIERERESk+jJPQHTtmt9IurSOHIEJE+CDD/Ifi4iIiIiI3TJPQLg6utLIu5ENo6k+1IRaRERERKqnhAQ4frxwXNbll3bsyG88ffRofvVE06bWjU9ERERERKxmS0JhAqKZbzMcHRxtGE31oQoIEREREameoqMtx2VNQCQnF1ZMtG1rnZhERERERMTqLmRc4PfTv5vG6v9w46gCQkRERESqJ/Pll1xcoF27sp0/bhw8+CD8/jsEBFg3NhERERERsZptCdswYjSNQ/1DbRhN9aIEhIiIiIhUT+YJiPbtwc2t7Nfw9i575YSIiIiIiNxQRRtQB9UOslEk1Y+WYBIRERGR6ufy5fweDgW6dLFdLCIiIiIiUqHM+z/cVOMmarjUsGE01YsSECIiIiJS/cTFQU5O4VhVDCIiIiIiVVJuXi5bE7aaxsH+wTaMpvpRAkJEREREqp8tliXYZaqAOHMGXngB/vc/OHHCunGJiIiIiIhV7Tm9h7SsNNO4tX9rG0ZT/agHhIiIiIhUP+YJiMaN4aabSn/uzp2wa1f+T0YGDBtm5eBERERERMRaohOiLcbBfqqAuJFUASEiIiIi1YvRCNFmb0LKuvzSoUOFj9u2tU5MIiIiIiJSIcwbUHs6e1K/Zn0bRlP9qAJCRERERKqXw4chOblwXNYExLhx8Le/5VdCtGhh3dhERERERMSqzBMQLWu3xGAw2DCa6kcJCBERERGpXor2fyhrAsJggPr1839ERERERMRuJaUlcfj8YdO4lX8rG0ZTPWkJJhERERGpXswTEJ6ecPPNtotFREREREQqTNH+D6H+oTaKpPpSAkJEREREqhfzBESnTuCkomARERERkarIfPklB4MDLXy1hOqNpgSEiIiIiFQfKSmwZ0/huCzLL12+DK+9Bt9/D+fOWT82ERERERGxKvMEREPvhrg6udowmupJCQgRERERqT62bQOjsXBclgTEb7/BDz/AggXw+efWjkxERERERKwoMyeTuJNxpnGIX4gNo6m+lIAQERERkeqjaAPqzp1Lf+7u3YWP27a1TjwiIiIiIlIhdp7aSWZupmncuk5rG0ZTfWnBWxERERGpPswTEKGhUKtW6c8dPTq/YmLHDjWuFhERERGxc+bLLwEE1w62USTVmxIQIiIiIlI95ObC1q2F47IsvwT5zapbtcr/ERERERERu2aegPBx88HPw8+G0VRfWoJJRERERKqH33+HixcLx1262C4WERERERGpMEaj0SIBEVQ7CIPBYMOIqi8lIERERESkeija/6GsFRAiIiIiIlIpHE85TmJaomncyl9VzLaiBISIiIiIVA/mCQhfX2jZsnTn5ebCBx/A9u2QkVExsYmIiIiIiNUU7f8Q6h9qo0hECQgRERERqR7MExBduoBDKV8K//EHrFwJ06fDG29USGgiIiIiImI95gkIZwdnmvg0sWE01ZsSECIiIiJS9Z0+DYcPF47LsvzSjh2Fj9u2tV5MIiIiIiJSIbYkFCYgmtRqgrOjsw2jqd6cbB2AiIiIiEiFi462HJclATFoEDRqBDt3KgFRAc6dO8eKFSvYt28fkZGRNGjQwNYhiYiIiEgllpaVxu5Tu03jUD8tv2RLqoAQERERkarPfPklR0eIiCj9uZ6e+QmLf/4T/PysH1s1tnbtWnr27MmyZcvYsmULffr04fXXXy923Pnz5+nWrRvbtm2z2J6UlERQUFCxn5UrV17xnufPn+fpp58mIiKCjh07MmPGDC5fvmzaHxUVRVBQEGPHji3x/G+//ZagoCBGjBhRzmctIiIiIhUp9kQsucZc07hVHTWgtiVVQIiIiIhI1WeegAgPz08qiE1dvnyZ5557jpEjR9K1a1diYmJo1qwZkZGR3H777YSHhwP5SYZx48aRnJxc7Br79+/H1dWVDRs2YDAYTNtr1qx5xftOmDCBy5cvs2TJElJTU5kyZQrp6enMmTPHdIyzszObN28mLS2NGjVqWJy/evVqi3uJiIiIiH0p2oA6uHawjSIRUAWEiIiIiFR1WVkQG1s4LsvyS1JhDh8+THp6OoMGDTJt69evH1OnTsXHxweAL7/80mJ/UQcPHqRx48bUqVMHf39/04+bm1uJx+/cuZOYmBjmzJlDq1at6NKlCy+99BJfffUVSUlJpuNat26Nm5sbGzdutDg/LS2Nn3/+mfbt21/HMxcRERGRimTe/6GuZ1283bxtGI2oAkJEREREqradOyEzs3BclgTEN99ASAg0awb61rtV+fn5YTAY2Lp1K82bNwfAYDBYLG303XffERkZyS233MKdd95Z7BoHDhygWbNmpb5nXFwc/v7+Fud07NgRg8HA9u3b6d+/P5BfAXHHHXewdu1aiwTIhg0bCAoKokGDBpw4caLMzxnAaDRiNBrLde713O9G3lPkajQnxd5oToo90Xy8fnnGPKLjC/u/BdUOstnv02g0YuTG/3na2/xRAkJEREREqrYtliXYpU5AJCbCf/+b/7hTJ5g61bpxVXMBAQGMHj2aWbNmERISQmBgIPHx8RZNqN99910AEhISSrzGwYMHqVWrFsOHD+fo0aM0atSIcePG0b179xKPT0pKol69ehbbXFxc8PHxITEx0WJ7v379GD9+vMUyTKtXr2bAgAHs37+/3M87NTUVB4cbV4huNBpJT08H0NJRYhc0J8XeaE6KPdF8vH4Hzh3gfMZ507i5d3MupV+ySSyXMy5zyeESKSkpN/S+eXl5N/R+16IEhIiIiIhUbeYJiPr1wewD7qvaubPwcbDWja0IkydPpmfPnixZsoSNGzeybt06Bg4cyJw5c3B0dLzquTk5ORw5coTmzZsTFRVFjRo1+Pbbb/n73//OBx98QJcuXYqdc/nyZVxcXIptd3V1JdO8Sgbo2rUr7u7ubNq0iYEDB5KSkkJ0dDQzZ868rgSEl5fXNZ+bNRV8A87b21sfZIhd0JwUe6M5KfZE8/H6/XbkN4tx2E1heHrYpv+be447np6eeHvf2CWgcnNzr33QDaQEhIiIiIhUXUajZQKia9fSL6XUsWP+sTt3gtb8rzARERHk5eURFBREcHAwkyZNIiwszGIpppI4OTmxbds2HB0dTT0fWrduzaFDh1i0aFGJCQg3NzeysrKKbc/MzMTDw8NiW8EyTAVJkfXr1xMeHk7dunWv49nmf5vxRn+gUHBPfZAh9kJzUuyN5qTYE83H62O+/JKbkxsNvRva7HdpMBgwYJvXfvZETahFREREpOo6fhxOniwcl6X/g58f9OsHzz8PTZpYP7ZqLikpidWrV5vGBoOB3r170717d6Kjo69yZiFPT89iDadbtGhh0VDaXEBAAKdPn7bYlpWVxYULF6hTp06x4/v3789PP/3EpUuXWLNmjalHhIiIiIjYJ/MG1C18W+DocOMqT6VkSkCIiIiISNVVtP9DCd+Kl/IxGo2cO3eu3GvaxsTEEBkZydGjRy22nzlzBh8fn2uef+jQIdq1a8e2bdsstu/Zs8fU1LqoiIgITp06xbFjxyziAGhfQpVL586d8fDwYNWqVcTFxdGnT59rxiUiIiIitnHu8jn2nylcKrOVfysbRiMFtASTiIiIiFRd5gkIV1do29Z2sVQBx48f54svvmDz5s0cOHDA1ODOxcWFkJAQunXrxt133039+vWvea2ePXvi7+9PVFQUd999NxcuXGDBggXs3r2bZ5999prnN2vWjKZNm/LSSy8xY8YMatWqxeeff86uXbtYsWIFkL/+7blz56hZsyZubm6EhYXRrl07IiMjmT59Ounp6bz44osMHjy4xKWVnJyc6NWrF/PnzyciIgJfX98y/sZERERE5EbZmrDVYhziH2KjSMScKiBEREREpOoyT0BEREAJDYhLFB0NyckVE1MldOrUKSZMmEDfvn1577332Lt3L05OTtSuXZvatWuTl5fHrl27WLhwIb169eKpp54iMTHxqtf09PRk8eLFuLq6MmvWLJYvX86mTZtYuHAh7dq1u2ZMDg4OvPPOO7Rp04aJEydy9913s3v3bj744ANatmwJQGJiIt26dTMt9WQwGFi4cCGBgYGMHDmSiRMn0r17d6ZPn37F+/Tv35+0tDQGDBhQ+l+YiIiIiNxwW+ILX/sbMBBUO8iG0UgBVUCIiIiISNV06RLs3l04Lm3/h4sXYfbs/AbWnTrB1KkVE18l0q9fP4xGI3379uWOO+4gLCyMwMBAi2MSEhL4/fff+fHHH/n+++/5/vvv2W3++y9By5YtWbp0KVu3biU2Npbx48eXeFxgYCAHDhwott3Pz4/Zs2df8folnVe7dm3eeOONK57zyiuvWIy7dOlS7BpFjxERERER2zNPQNT3qo+Hs4cNo5ECSkCIiIiISNUUGwu5uYXj0iYgdu/OTz4A1Ktn/bgqoSeffJJ77rkHLy+vKx4TGBhIYGAgffr0ITMzk5UrV5b6+oGBgRgMBmuEKiIiIiLVUE5eDttOFPYGC/HT8kv2QgkIEREREamaytuAumlTGD4cduyAEhoTV0ejRo264r6kpCTOnj1LkyZNcHd3B8DV1ZVhw4aV+voFyQsRERERkfL4NelX0rPTTePW/q1tGI2YUw8IEREREamazBMQzZtDnTqlO++mm+CBB+DVVyE8vEJCq4xOnz7NxIkT2bx5s2nbtGnTuO2227j33nvp1q1bmaoeRERERESsxXz5JYBgv2AbRSJFWaUCIi0tjZiYGPbu3cu5c+dwcHDA39+f1q1b065dO9M3oUREREREboi8vPxG0gVKu/ySXNHYsWPZt28fERER3HLLLaxfv57ly5fj7u5O9+7d2b59Oy+++CKhoaEEB+sNn4iIiIjcOOYJiJouNQmoEWDDaMTcdSUg9u/fz+LFi1m7di3Z2dkYC9bK/YvBYMDd3Z2+ffsyZswYmjdvfl3BioiIiIiUysGDcO5c4VgJiOuyZcsW9u7dyy233ELnzp05efIky5cvx2AwMG7cOO666y6OHz/OqFGjWLFiBWPGjKGe+meIiIiIyA1inoAIqh2k/mJ2pNwJiFmzZvHpp5+Sm5tL48aNCQ8Pp2nTpqbGdCkpKRw9epTff/+dlStX8vXXXzNkyBCmTZtmteBFREREREpUtP9DaRMQBw5Agwbg4WH9mCqxMWPGYDAY2LJlCwMGDDC9oTMajcyfP5/58+djMBgwGAwsW7aMjz76iH379tk4ahERERGpDk6knuBYyjHTONQ/1IbRSFHlTkB8++23PPLIIwwePJimTZte9dhTp07xzTff8PHHHysBISIiIiIVzzwB4eUFoaV4E5KTA1OnQnY2dO4MUVEVF18ls2bNGvr160fPnj355z//ybJly1i1ahW9evXizTffJDMzkzfeeIPFixfz2GOP8fTTT9s6ZBERERGpJqIToi3GSkDYl3InIH788UdcXFxKdWxAQACPPfYYo0ePLu/tRERERERKzzwB0bkzODpe+5x9+yAjI/9xKV/nVhdNmjShR48ebNy4kU2bNgHg7u7OP//5TwBeeuklVq5ciZubG0OGDLFlqCIiIiJSzZgvv+RocKRZrWY2jEaKKncCoiD5cOjQIby8vKhbty4AR44cYcmSJSQnJ9O6dWtGjx6Nx18l7E5OVul5LSIiIiJyZefO5ScTCpR2+SUfHxgwAHbuhLZtKyS0yqygwmH37t34+fnx0EMPmZpN16lTh3bt2vHss8/SsGFDG0cqIiIiItWJeQVEI59GuDq52jAaKeq6MgJLly7llVde4ZVXXmHQoEEkJSVx//33k5aWhtFoZNOmTWzYsIHly5eXulpCREREROS6bN1qOS5tAqJBAxg7Nv+x0WjdmKoAV1dXxo0bV+K+J5988gZHIyIiIiICGTkZbD+53TQO9dPyS/bGobwnpqamMnfuXLy8vPD39wdg2bJlXLx4kR49evB///d//OMf/2D//v383//9n9UCFhERERG5KvPllwwG6NSp7Nf4q8my5Hv88ceJjo6+9oF/+fXXX3nqqacqMCIREREREdh+cjvZedmmcas6rWwYjZSk3BUQkyZNIjs7m/r16/P111/z9ddf89NPP2EwGMjOzmbRokXk5uZiNBp5//33iY2NZfbs2daMXURERESkOPMEROvW+U2o5bqcPHmSMWPGULduXe644w7CwsJo3LgxXl5e5ObmcvbsWU6dOkVcXBzR0dEkJCTQokULW4ctIiIiIlWcef8HgGC/YBtFIldS7gREnTp1MBgM1KxZk/r167N3717Onj1L3bp1afvXmrnHjh0DwM3Njfr161snYhERERGRK8nJgW3bCselXX7p1Cnw9y9ds+pqaMWKFXz66acsWrSIjz/+mE8++aTE44xGIw0aNOCFF17ggQceuMFRioiIiEh1syWhMAFR2702td1r2zAaKUm5ExBTp05l7dq1/Prrr7i7u7Njxw4MBgMjRozg0Ucf5f/+7/9Yvnw5BoOBkSNH8re//c2acYuIiIiIFPfrr5CeXjguTQLCaITJkyEzEzp2BC0dVIyjoyMPPfQQDzzwAFu3buWnn37iwIEDnD17FgA/Pz9uvvlmunbtSpcuXWwcrYiIiIhUB0aj0aICIqh2kA2jkSspdwLCzc2NuXPnMnnyZDZt2gTAgAEDGDNmDAC7du0iOTmZ3r17K/kgIiIiIjdG0T4FpUlAxMfDuXP5j1NTrR9TFeLk5ES3bt3o1q2brUMRERERkWruyPkjnL502jRuXae1DaORKyl3AgLg9ttv54cffuDIkSP4+fkREBBg2te3b1/uuOMOfQNKRERERG4c8/4P/v7QrNm1zzEaoVs32L0b/lpKVERERERE7FvR/g8hfiE2ikSuptwJiH379hESEoKHhwetWxfPLnXo0KHYtsOHD9OsNG8CRURERETKwzwB0bUrGAzXPqdRo/wlmPLy8ntIiIiIiIiI3TNPQLg4utDYp7HtgpErcijviXfffTcPPvggX3zxBecKStZLcPr0ab766isee+wxBg4cWN7biYiIiIhc3cmT8OefhePSNqAu4OAALi5WDUlERERERCqGeQPqZrWa4ejgaMNo5ErKXQGxYMECZs+ezQsvvMC0adMIDAykcePG1KxZk7y8PM6cOUNSUhLx8fEABAQEMG/ePKsFLiIiIiJioTz9H0REREREpNJJzUzlt6TfTONQ/1AbRiNXU+4ERN++fenZsycrV67kf//7H7/99hvHjx+3vLiTE+3atWPIkCH0798fF32jTEREREQqivnyS87O0L79tc+5dAk8PSsupips79697Nq1C19fX9q2bYu3tzdubm62DktEREREqoFtCdswYjSNlYCwX9fVhNrFxYUHHniABx54gAsXLvDHH39w5swZAPz8/AgNDcXDw8MqgYqIiIiIXJV5AqJdO3B3v/Y5zz8Ply/nH/+Pf5SuZ0Q1l56ezpNPPskvv/wCwB133MHx48f57LPPWLZsGfXr17dxhCIiIiJS1UUnWFY/B9UOslEkci3XlYAw5+PjU2Lj6fI4d+4cK1asYN++fURGRtKgQQOrXFdEREREqqiMDNi+vXBcmuWXLlyAI0fyHx84oORDKc2bN4+ff/6Z8PBwdu3aBUBKSgonT55kzpw5vPHGG7YNUERERESqPPMG1PVq1MPL1cuG0cjVlLsJdUVZu3YtPXv2ZNmyZWzZsoU+ffrw+uuvFzvu/PnzdOvWjW3btllsT0pKIigoqNjPypUrr3jP8+fP8/TTTxMREUHHjh2ZMWMGly9fNu2PiooiKCiIsWPHlnj+t99+S1BQECNGjCjnsxYRERGR67J9O2RnF45Lk4BITYWbbwYnJ2jbtuJiq2LWrVtH8+bN+eyzz0zbJk2aRNOmTYu9NhcRERERsbY8Y55FBUSwX7ANo5FrsVoFhDVcvnyZ5557jpEjR9K1a1diYmJo1qwZkZGR3H777YSHhwP5SYZx48aRnJxc7Br79+/H1dWVDRs2YDD7FlvNmjWveN8JEyZw+fJllixZQmpqKlOmTCE9PZ05c+aYjnF2dmbz5s2kpaVRo0YNi/NXr15tcS8RERERucHMl1+C0iUgGjaEf/0rv3rCPHkhV3Xx4kWaN29usc1gMODl5UViYqKNohIRERGR6mJv8l5SM1NN41b+rWwYjVyLXVVAHD58mPT0dAYNGmTa1q9fP6ZOnYqPjw8AX375pcX+og4ePEjjxo2pU6cO/v7+pp8rNcTbuXMnMTExzJkzh1atWtGlSxdeeuklvvrqK5KSkkzHtW7dGjc3NzZu3GhxflpaGj///DPtS9PkUEREREQqhnkComFDuOmm0p/r5gZX+bKKWAoNDSUuLo5FixYBcObMGf7973+za9cuQkJCbBydiIiIiFR15ssvAYT46TWoPbOrCgg/Pz8MBgNbt241favKYDBYLG303XffERkZyS233MKdd95Z7BoHDhygWbNmpb5nXFwc/v7+Fud07NgRg8HA9u3b6d+/P5BfAXHHHXewdu1aiwTIhg0bCAoKokGDBpw4caLMz9loNGI0Gq99oBUV3PNG31fkSjQnxZ5oPoq90ZwsBaMRtmyhoB7V2LVr/jYxseb8mTRpEmPGjGHevHkYDAZ2797Nrl27cHJyYvz48Va7j4iIiIhIScwTEB7OHtT3qm/DaORarJaA2Lx5Mw0aNKBhw4YsWLCAH374ga5du/L000/j6OhYqmsEBAQwevRoZs2aRUhICIGBgcTHx1s0oX733XcBSEhIKPEaBw8epFatWgwfPpyjR4/SqFEjxo0bR/fu3Us8PikpiXr16llsc3FxwcfHp1gJeb9+/Rg/frzFMkyrV69mwIAB7N+/v1TPsajU1FQcHG5sIYrRaCQ9PR1AS0eJXdCcFHui+Sj2RnPy2hyOHsXr9GnT+HLbtmSlpFz9pLw8uMGvwWwpLy/Patfq0KEDy5cvZ9GiRezbtw9nZ2datmzJ6NGjVQEhIiIiIhXOPAHRwrcFDobq87q+MrJKAmLVqlU899xzzJo1i+PHj/POO+8A+dUINWrU4PHHHy/1tSZPnkzPnj1ZsmQJGzduZN26dQwcOJA5c+ZcM5GRk5PDkSNHaN68OVFRUdSoUYNvv/2Wv//973zwwQd06dKl2DmXL1/GxcWl2HZXV1cyMzMttnXt2hV3d3c2bdrEwIEDSUlJITo6mpkzZ5Y7AeHl5VXqBI21FHwDztvbWx9kiF3QnBR7ovko9kZzshT27LEYuvfsibu399XPmTYNLl3Kbz59//35jairsNzcXKteLyQkhHnz5ln1miIiIiIi15J8KZlD5w6Zxur/YP+s8k5r8eLFODk54efnx9q1a3FycmLOnDnMmDGDr7/+ukwJCICIiAjy8vIICgoiODiYSZMmERYWZrEUU0mcnJzYtm0bjo6Opp4PrVu35tChQyxatKjEBISbmxtZWVnFtmdmZuLh4WGxrWAZpoKkyPr16wkPD6du3bplen7mDAaDTT5MKLivPsgQe6E5KfZE81HsjebkNURHFz728MAQFgZX+11lZuYnLbKz4fx5GD786sdXAdacO88999wV97m4uODv788dd9yhaggRERERsbrohGiLcah/qI0ikdKySgIiPj6eiIgIevTowaxZs2jVqhUDBgxg1apVxMbGlvo6SUlJFn0XDAYDvXv3pnv37kRHR18zAQHg6elZbFuLFi345ZdfSjw+ICCADRs2WGzLysriwoUL1KlTp9jx/fv35/HHH+fSpUusWbPGFKuIiIiI2Ih5A+qOHcHZ+erHnzkD9erB8eP5FRBVPPlgbf/73/9MCY2CCp2i47fffpt///vfJfZsExEREREpL/PllwwYaOHbwobRSGlYZYEsZ2dnsrKyOHnyJPHx8bRr1w6A06dPl5gQuJKYmBgiIyM5evSoxfYzZ87g4+NzzfMPHTpEu3bt2LZtm8X2PXv2mJpaFxUREcGpU6c4duyYRRwA7du3L3Z8586d8fDwYNWqVcTFxdGnT59rxiUiIiIiFSQ1FX77rXDcteu1z6lfH/7zH1iyBIYOrbDQqqo5c+bg6elJeHg4UVFRPPfcc7Ru3Ro3NzeefvppxowZg9Fo5L///a+tQxURERGRKsY8AdHAuwHuzu42jEZKwyoJiBYtWrBjxw5GjBiBwWCgR48evPzyyxw8eJDw8PBSX6dnz574+/sTFRXF0aNHuXDhAgsWLGD37t3cd9991zy/WbNmNG3alJdeeom4uDgOHz7M7Nmz2bVrF+PGjQPy179NTk4mIyMDgLCwMNq1a0dkZCS//vorW7du5cUXX2Tw4MElLq3k5OREr169mD9/PhEREfj6+pb6+YmIiIiIlcXE5DeULlCaBESB2rXhOpbSrK42bNiAr68vy5YtY9SoUYwcOZKPP/6YWrVqcfDgQZ599lnCwsI4dOjQtS8mIiIiIlJKWblZxJ4sXG0nxE9LflYGVklATJw4EVdXV06cOMFtt91G586dSUtLw8vLiyeffLLU1/H09GTx4sW4uroya9Ysli9fzqZNm1i4cKGpquJqHBwceOedd2jTpg0TJ07k7rvvZvfu3XzwwQe0bNkSgMTERLp168bq1auB/HLxhQsXEhgYyMiRI5k4cSLdu3dn+vTpV7xP//79SUtLY8CAAaV+biIiIiJSAcyXXwLo3Nk2cVQjP//8M3Xr1sXJrHG3i4sL9evXNy1t6uHhQXZ2tq1CFBEREZEqaPep3WTkZJjGrf1b2zAaKS2r9ICIiIhg06ZNnD59mhYt8tfdeuCBB3jyyScJCAgo07VatmzJ0qVL2bp1K7GxsYwfP77E4wIDAzlw4ECx7X5+fsyePfuK1y/pvNq1a/PGG29c8ZxXXnnFYtylS5di1yh6jIiIiIjcAOYJiODg/KoGqVDe3t7s2LGDzz//nL59+2I0GlmzZg3bt2+ndu3axMXFERMTg5+fn61DFREREZEqxHz5JYBgv2AbRSJlYZUExMMPP0yHDh2YMGGCaVtYWBjPP/88p06dYvHixWW+ZmBgoKmZnYiIiIhIMXl5EB1dOC7N8kv/+Q+cP5/ffLpXL3Bxqbj4qqjhw4czf/58pk2bxrRp00zbjUYjw4YNY8+ePWRnZ9O9e3cbRikiIiIiVc2WhMIEhLerN3U869gwGimtcicgtm3bRnx8PJDftDktLY2bbrrJtN9oNLJ161bOnj1brusHBgYSGBhY3vBEREREpKrbuze/CXWBayUgjMb8ionUVPj1V+jTp2Ljq6L+/ve/4+npyX//+1+SkpIAqFu3Lo888ggPP/wwS5Ys4Z577mHy5Mk2jlREREREqhLzCoig2kH68nolUe4EhNFoZOrUqRgMBgwGA/v27eOFF14odkzz5s2vO0gRERERkWKK9n+4VgIiORkK3qS0aQNOVikGrpaGDx/O8OHDuXTpErm5uXh5eZn2jRo1ynaBiYiIiEiVFJ8ST0Jqgmncqk4rG0YjZVHud12dO3fmoYce4sCBA8TGxuLj42Pq/wD5DaFr167NmDFjrBKoiIiIiIgF8wRErVoQFHT14+vUgWXL4OjR/GoIKbeUlBSOHTtGVlYWxr9+l+np6cTGxjJp0iQbRyciIiIiVU3R/g8hfiE2ikTK6rq+9jV16lQARowYQfv27Zk4caI1YhIRERERuTbzBETnzuDgcO1zDAZo2rTiYqoG1q1bx9NPP01ubm6J+5WAEBERERFrM09AODk40axWMxtGI2VhlbrzZcuWWYwzMzM5evQoTZs2xUWN/URERETE2pKT4dChwnFpGlCLVbz11lvk5OTQokULDh06RFhYGCdPniQ5OZkHHnjA1uGJiIiISBVk3oC6iU8TnB2dbRiNlEUpviZ2benp6Tz99NNER0eTnp7OoEGDuPvuu+nTpw/Hjh2zxi1ERERERApFR1uOlYC4YY4dO0Z4eDjffPMN/v7+PP3006xZswY/Pz8SExNtHZ6IiIiIVDGXsi6xM3GnaRzqH2rDaKSsrJKAmDNnDqtXr+bAgQOsXLmSY8eO4e7uTmJiIgsWLLDGLURERERECpknIBwcoGPHqx//+efwxhvwyy+QlVWxsVVxjo6OuLu7AxAeHs727dupUaMGLVq0YNeuXbYNTkRERESqnLiTceQaC5f/bOWvBtSViVUSEJs2baJOnTr069ePn3/+GR8fH7Zt20bTpk2Ji4uzxi1ERERERAqZ938IC4MaNa5+/KZN8N13MHcuZGdXbGxVXIsWLYiJieGrr76iXbt2LF26lGnTphETE4PBYLB1eCIiIiJSxRRtQB3kF2SjSKQ8rJKAOH/+PCEhIfj7+7N9+3bCw8NxdnYmMDCQ1NRUa9xCRERERCRfdjbExBSOr7X8UmoqnD6d/zgoCDw9Ky62amDixIk4Oztz8eJF+vXrR3p6Op9//jm5ubn07t3b1uGJiIiISBVj3v/B38OfWm61bBiNlJVVmlD7+vpy9OhR/u///o+0tDQ6depEUlISv/32G3Xr1rXGLURERERE8u3aBRkZheNrJSC8vODTT+H33ys0rOqic+fOrF+/HqPRSN26dfnoo49YtWoVDRo04KGHHrJ1eCIiIiJShRiNRqLjC5dfVfVD5WOVCohbb72VY8eOMXnyZJycnOjVqxcvvvgi58+fp1+/fta4hYiIiIhIvi2WJdilakDt4gJt2+b/yHVZuHAhcXFxpi8a3XzzzbzwwgsAvPPOO7YMTURERESqmEPnDnH28lnTuLV/axtGI+VhlQqIZ555hvT0dP78808eeeQRAgMDadSoEX369OGf//ynNW4hIiIiIpLPPAFRrx40amS7WKqJ5ORkMv6qOlm4cCG33HILN998s2l/Xl4eX3/9NUePHuWJJ56wVZgiIiIiUsUU7f8Q4hdio0ikvKySgPD29mb+/PkW25555hmcnZ2tcXkRERERkULmCYiuXUGNjyvcpk2bmDZtmmm8ZcuWEvs9+Pn53ciwRERERKSKM09AuDq60tC7oQ2jkfKwSgIC4NSpU7z11lvExcVhMBiIiIhg3Lhx6gEhIiIiItYTHw8JCYXjay2/9P33cOJE/tJLISHgZLWXv9XKfffdx7Jlyzh06BAGgwGj0Wix32AwULt2bSIjI20UoYiIiIhUReYJiOa+zXF0cLRhNFIeVnkHlpCQwP3338+5c+dMb0YOHz7M999/z/Lly7npppuscRsRERERqe7K2v/hu+/ym09/8QW8/z7oyzHl4uDgwDfffANAcHAwd955JwsXLrRxVCIiIiJSlV3IuMDvyb+bxq38W9kwGikvqyQgXnvtNc6ePcttt93GvffeC8CXX37Jjz/+yGuvvcZrr71mjduIiIiISHVnnoBwdb16U+mMDDhwIP/xTTcp+WAl+/fvt3UIIiIiIlINbE3YajEO9Q+1USRyPaySgNiyZQuNGzfm7bffxvDXGrx33HEH/fr145dffrHGLURERERELBMQHTrkJyGuxM0NPvgAdu2CIksGSfldvnyZxYsXs3v3bjIzMy2WYzIYDHz44Yc2jE5EREREqgrz5ZcMGGhZu6UNo5HyskoCIisrC39/f1PyAfLLtP39/Tl9+rQ1biEiIiIi1d2lS7BzZ+G4S5drn+PjA7fdVlERVUtTp05l9erVxfpAABbvB0RERERErod5AuKmmjdRw6WGDaOR8rJKAqJFixbs2LGDb7/9lgEDBgDwzTffsGPHDtq0aWONW4iIiIhIdRcXB7m5heNr9X+QCrFx40YcHBwYOnQoLVu2xEmNvUVERETEynLycth2YptpHOIXYsNo5HpY5d3CI488wpNPPsmkSZOYOnUqABkZGQCMHDnSGrcQERERkequaAPq0lRAiNW5u7vTqlUrpk2bZutQRERERKSK2nN6D2lZaaaxGlBXXg7WuEifPn146aWX8PLy4vLly1y+fBlPT08mT55Mv379rHELEREREanuoqMLHzdtCgEBVz52+3b46is4flz9H6xsyJAhHD9+nEuXLtk6FBERERGposyXXwII9gu2USRyvaxWLz106FAGDx7MH3/8gYODA02aNMH1ak0BRURERERKy2i0rIC41vJL69cXHj9/PrRoUXGxVTMODg5kZGTQt29fwsLCcHd3N/V+MBgMzJkzx8YRioiIiEhlZ56A8HT25KaaN9kwGrke152ASExMpG7dujg4OODi4kJoaChJSUnk5eVZIz4RERERETh0CM6eLRxfLQGRmwu7d+c/rlkTmjWr2Niqmbffftv0eMOGDRb7lIAQEREREWuITiisfg6qHWT6wotUPteVgFiwYAHvv/8+n3zyiUWz6TfffJP169fzwgsvMHDgwOsOUkRERESquaL9H66WgHBwgFdfhZ07ITs7fyxW889//lNvAEVERESkwpxKO8WR80dM41D/UBtGI9er3AmIr7/+mnfeeQeAX3/91SIBERsbS2pqKpMnT8bPz48uahAoIiIiItfDPAFRowa0bn3lYw0GaNgw/0esbvz48bYOQURERESqsOj4aIuxEhCVW7kTEB9//DEGg4GpU6cyfPhwi33/93//x8KFC3n33Xd5//33lYAQERERketjnoDo3BkcHW0Xi7B//36OHj1KZmamadulS5fYvn078+fPt2FkIiIiIlLZmfd/cDA40MJX/dwqs3InIA4ePEhwcHCx5AOAs7MzkZGRfP/99+zfv/+6AhQRERGRaur4cThzBi5ehN9/L9zepAns2AF+fqpysIFPPvmEmTNnXnG/EhAiIiIiUl65ebms+WONadzQqyGuTq42jEiu13UtiOvp6XnV/bVq1SItLe16biEiIiIi1dHx4xAUBO3bw223We5777387UFB+ceZO3QIfvgBUlJuVKTVzrJlyzAYDPTo0QOj0UivXr0ICQnBaDTy6KOP2jo8EREREamkVu5bSaMFjfg9ufDLR6cunbKoiJDKp9wJiKZNm7Jnzx6OF33T95fjx4/z22+/0bhx4/LeQkRERESqqzNnICPj6sdkZOQfZ+677+C11+Chh2DPnoqLrxo7ceIEHTp04J133qF+/foMHTqU5cuXU79+fXbv3m3r8ERERESkElq5byX3fX4fJy6esNiekZPBK5tfURKiEit3AuKee+4hIyODUaNG8fnnn7N//34SEhLYv38/n3/+OaNHjyYzM5O7777bmvGKiIiIiFzZzp35/3VygubNbRtLFeXm5kZubi4A4eHhxMbG4uzsTL169di7d6+NoxMRERGRyiY3L5cn1z6JEeMVj3l/5/vk5uXewKjEWsrdA+LBBx9ky5YtfP/990ybNq3YfqPRSLdu3Xj44YevK0ARERERkVIxGmHChPwkxKVL4OZm64iqpFatWrF161aWLVtG+/btmTt3Lr///jtxcXH4+fnZOjwRERERqWR+Pv4zCakJVz3mTPoZ9ibv5ea6N9+gqMRayl0BYTAYWLhwIVOmTKFp06YYjUbTT4MGDZg0aRLvvvsuDg7X1WZCRERERKR0DAa4+WZ4+GEYN87W0VRZkydPpnbt2jg7O9OvXz9cXV355ZdfALj33nttHJ2IiIiIVDaJFxNLddy5jHMVHIlUhHJXQEB+EmLEiBGMGDGCy5cvk5qaiqenJzVq1LBWfCIiIiIiYkeCg4PZuHEjGRkZeHl5sXLlStauXUuDBg3o1auXrcMTERERkUqmXs16pTrO1823giORinBdCQhz7u7uuLu7W+tyIiIiIiJih6ZNm8bQoUNp1aoVADfddBNjxoyxcVQiIiIiUlnd2vBW/Nz9OHP5zBWP8fPwI9Q/9AZGJdai9ZFERERExP4klq4M2+L4XbsgK6tCwpFCy5cv57777uOee+7hk08+IS0tzdYhiYiIiEgl5mBwwNvN+6rHPNr2URwdHG9QRGJNSkCIiIiIiP359NNrH+PmBgVNjzduhBdegGHDYMeOio2tmhs9ejT+/v7s3buXmTNncuuttxIVFUVcXJytQxMRERGRSmj1odUcPn+4xH1+Hn5E3RJF1wZdb3BUYi1WW4JJRERERMQqjh+Hzz8vHIeGwtKl+U2mzfn5QcOG+Y937sz/b1YWNG58Q8KsriZPnswzzzzD5s2bWbVqFRs3buSrr77iq6++okmTJqxevdrWIYqIiIhIJWE0Gpnx4wzT2AEHnu7yNHnk4evmS6h/qCofKjmrJCA+/vhjBg4ciJeXlzUuJyIiIiLV2SuvQHZ24XjuXGjf/urn3H03bN8O586Br5rTVTQHBwduvfVWwsLCCA8PZ+HChaSkpHD06FFbhyYiIiIilciaP9YQezLWNO7ZpCe3NrrVhhGJtVklATFz5kzmzJnD7bffzt13382tt96Ko6MyUyIiIiJSRvHx8P77heMOHaBfv2ufd8st+T9S4bKzs/nxxx/56quv+PHHH8nOzsZoNNKiRQuGDBli6/BEREREpJIoWv3gaHDkgdYP2DAiqQhWSUB07dqVmJgY1q1bx/r16/H19WXgwIEMHjyY4OBga9xCRERERKqD2bMtqx+mTy++9JLYVLdu3UhNTcVoNOLm5sbf/vY3hg4dSrt27WwdmoiIiIhUImv/WEvMiRjT+LbGt1HHs44NI5KKYJUExOLFi7lw4QLfffcda9euZdu2bXz44Yd8+OGHtGjRgr/97W/cc8891KpVyxq3ExEREZGqKD4eFi0qHHfoAP372y4eKVFKSgotWrTg/vvv529/+xs1a9a0dUgiIiIiUskYjUam/zjdNHYwODCs9TDbBSQVxsFaF/Lx8WHIkCEsWrSIN954A39/f4xGIwcPHmTevHn06tWLbdu2Wet2IiIiIlLVvPJKfhPpAtOmXbv6ISUFjhwBo7FiYxOTzz77jG+++YaHHnpIyQcRERERKZd1h9dZVj80UvVDVWWVCgiA3377jdWrV7N27VpOnTqF0WjE1dWVnj178scff3Do0CHmzJnDypUrrXVLEREREakqEhIsez+0bw8DBlz7vJ9+gv/+F7y94cknISKi4mKsxhYuXGgx/uWXX0o8zmAw8M9//vNGhCQiIiIilZTRaGT6D9NNY1U/VG1WSUD06tWLhIQEjH998yw0NJR7772XgQMH4uXlhdFo5N577+Xw4cPWuJ2IiIiIVDXlqX4A2Lkz/78pKeDvXzGxCQsXLsRQyl4cSkCIiIiIyNWsP7yebScKV8q5rdFt1K1R14YRSUWySgIiPj6eWrVqMXDgQO69916CgoIs9hsMBho2bGiNW4mIiIhIVZOQAO+9Vzhu1w7uuqt053bpAg4O+ddo1Khi4hPuuusuUwIiJyeH9evX4+HhQfv27TEYDMTFxZGXl8eoUaNsG6iIiIiI2DX1fqh+rJKAeOONN7j99ttxdna+4jELFiywxq1EREREpKopWv0wfXrpqh8AevXK/zEaS3+OlNm8efNMj//1r3/h4+PDN998g6+vLwDJyckMGjSIS5cu2SpEEREREakE1h9ez9aEraZxj0Y9VP1QxZU7AREdHW16XLNmTeLi4q54bJcuXcp7GxERERGpyk6cKH/1gzklH26Y//3vf7Rq1cqUfADw9/enRYsW/O9//yMqKsqG0YmIiIiIvTIajcz4cYZprOqH6qHcCYjRo0eXah1Yg8HA3r17y3sbEREREanKytv7QWzGwcGBnTt3snXrVjp37gzATz/9xK5du/Dw8LBxdCIiIiJir7478h3RCYVfau/RsAcBNQJsGJHcCOVOQNx0003WjENEREREqpui1Q9t28LAgaU7NyMDLl2C2rUrJja5ov79+/Ppp58yevRoatasSV5eHpcuXcJoNDJ8+HBbhyciIiIidqjE6oebVf1QHZQ7AbFx40ZrxiEiIiIi1c2cOZCZWTguS/VDTAzMnQsNG8KoURBgl5CpAACT2UlEQVQRUSEhSnFRUVEYjUa++OILUlNTAXBxcWHkyJE8+eSTZb7euXPnWLFiBfv27SMyMpIGDRpYO2QRERERsbENRzawJX6Lady9YXdVP1QTDrYOQERERESqoZMn4b//LRyHh8OgQaU/f+fO/P8ePw4uLlYNTa7O1dWV6dOnExsby6pVq/j666+JjY3l6aefxsmpbN9vWrt2LT179mTZsmVs2bKFPn368Prrrxc77vz583Tr1o1t27ZZbM/Ly+ONN97g1ltvJTw8nMcee4z4+Pir3vP8+fM8/fTTRERE0LFjR2bMmMHly5dN+6OioggKCmLs2LElnv/tt98SFBTEiBEjyvRcRURERKoro9HI9B+nm8YOBgcevPlB2wUkN1S5KyDMHT9+nJdeeont27eTkZFhsU89IERERESkmOupfgBo2hSCguDYMQgJsX58ck0eHh4EBwcDcObMGZYsWcKXX37Jd999V6rzL1++zHPPPcfIkSPp2rUrMTExNGvWjMjISG6//XbCw8MBSEpKYty4cSQnJxe7xltvvcUnn3zCK6+8QkBAAHPnzuXRRx/lm2++weUKiakJEyZw+fJllixZQmpqKlOmTCE9PZ05c+aYjnF2dmbz5s2kpaVRo0YNi/NXr15dql54IiIiIpLv+6PfW1Q/3NrwVlU/VCNWSUBMnTqVmJiYEvcZjUZr3EJEREREqoqTJ+HddwvH4eHwt7+V7RoDB+b/ZGaqAsKGfv75Zz7//HM2bdpEbm5umc49fPgw6enpDBo0iDNnzgDQr18/zp49i4+PDwBffvklc+fOpX79+sXOz8rKYvHixUyaNInbbrsNgNdff51bb72V9evXc9dddxU7Z+fOncTExLB69WqaNWsGwEsvvcSjjz7KU089Rd26dQFo3bo1hw8fZuPGjQwyq8xJS0vj559/pn379mV6riIiIiLVldFoZPoP001jB4MDD7ZW9UN1YpUExK5du6hRowbz5s2jUaNGODo6WuOyIiIiIlIVXW/1gzlXV+vEJKV2+vRpvvzyS1asWMHJkyeB/DeW3t7eDB06tNTX8fPzw2AwsHXrVpo3bw7kV0+bL2303XffERkZyS233MKdd95pcf7+/fu5dOkSXbp0MW3z8vIiNDSU2NjYEhMQcXFx+Pv7m5IPAB07dsRgMLB9+3b69+8P5FdA3HHHHaxdu9YiAbFhwwaCgoJo0KABJ06cKPVzFREREamuNh7dyOb4zabxrQ1vpV7NejaMSG40qyQg6tWrR/369U3fPBIRERERKVFiomXvh7Cwslc/yA1nNBr56aefWL58OT/99BO5ubkWlc6NGzdm1apVuLm5lfqaAQEBjB49mlmzZhESEkJgYCDx8fEWTajf/atSJiEhodj5p06dAvLfi5irU6eOaV9RSUlJxY53cXHBx8eHxMREi+39+vVj/PjxFsswrV69mgEDBrB///5SP8+ijEbjDa0SL7ifKtPFXmhOir3RnBR7UtXmY0nVD8NaD6syz+9ajEYjRm78n6e9/X6tkoB4+umnmTJlCr///jutWrWyxiVFREREpCqaMwfMe4aVtfohJyf/pwwfdMv169mzp+lDfaPRSKNGjRgwYIDpx93dvUzJhwKTJ0+mZ8+eLFmyhI0bN7Ju3ToGDhzInDlzrllVXdA4umivB1dXV1JSUq54Tkm9IVxdXck0r8oBunbtiru7O5s2bWLgwIGkpKQQHR3NzJkzrysBkZqaioODQ7nPLyuj0Uh6ejqAeleIXdCcFHujOSn2pKrNxx+P/8gv8b+Yxp1v6oyXgxeX0i/ZMKob53LGZS45XLria9OKkpeXd0Pvdy3lTkAUrXbIyMjgvvvuw8vLC3d3d9N2g8HApk2byh2giIiIiFQRiYmWvR/atCl79cPvv8P06fmNp+++GyIirBqilCwxMRGDwYCLiwuRkZGMGjXKateOiIggLy+PoKAggoODmTRpEmFhYRZLMZWkIOGRlZVlkfzIzMy0eD9S9JysrKxi2zMzM/Hw8LDYVrAMU0FSZP369YSHh5v6RJSXl5fXDV2ytuAbcN7e3lXigwyp/DQnxd5oToo9qUrz0Wg08tr210xjB4MDD4c9jKeHpw2jurHcc9zx9PTE29v7ht63rL3ZKlq5ExBXKmtOSUmxyOpU9r8sIiIiImIlr75avPqhrN8E37kzvwLit9+gb1/rxidX1LJlSw4ePEhmZiZz5szhww8/pG/fvvTr16/c10xKSrLou2AwGOjduzfdu3cnOjr6mgmIgqWUTp8+TcOGDU3bT58+TVBQUInnBAQEsGHDBottWVlZXLhwgTp16hQ7vn///jz++ONcunSJNWvWmGK9HgaD4Ya/Ryq4p96bib3QnBR7ozkp9qSqzMdNf27i5+M/m8bdGnTjJq+bbBjRjWcwGDBgm9d+9qTcCYilS5daMw4RERERqcoSE+GddwrHbdrA4MFlv06NGhAQAElJEB5urejkGr7++mv27NnDF198werVq0lMTGTJkiUsWbIEg8HAxYsXOXv2LLVr1y71NWNiYpg0aRIhISEW28+cOUPTpk2veX5wcDA1atRg27ZtpgREamoqe/fu5aGHHirxnIiICObNm8exY8do1KiRKQ6A9u3bFzu+c+fOeHh4sGrVKuLi4pg3b16pn5+IiIhIdVVS74cHb37QdgGJTZU7AdGxY0fT49jYWGrVqkXz5s0tjomJiTGtzSoiIiIi1djcuZbVDy++WPbqB4D77sv/OXMGvLysF59cU+vWrWndujXPP/88a9asYcWKFcTFxWE0Gjlx4gQ9evTgzjvvZMGCBaW6Xs+ePfH39ycqKoq7776bCxcusGDBAnbv3s2zzz57zfNdXFx46KGHmDdvHr6+vtSvX5+5c+cSEBBA7969gfzy83PnzlGzZk3c3NwICwujXbt2REZGMn36dNLT03nxxRcZPHhwiUsrOTk50atXL+bPn09ERAS+vr5l+p2JiIiIVEc//PmDRfXDLQ1u4aaa1av6QQpZpfvZiBEj+Pe//11s+8KFC4mKirLGLURERESksjp1Ct5+u3B88835/Ruuh5/f9Z0v5ebq6srgwYNZtmwZ69at4+9//zv+/v7k5OSwbt26Ul/H09OTxYsX4+rqyqxZs1i+fDmbNm1i4cKFtGvXrlTXmDBhAvfddx9Tp05l2LBhODo6smjRIpydnYH83hXdunVj9erVQH45+sKFCwkMDGTkyJFMnDiR7t27M3369Cveo3///qSlpTFgwIBSPzcRERGR6mz6j9NNjw0YGH7zcNsFIzZnMBZ0NymjxYsXm5ZhOnXqFG5ubvj4+Jj25+Xlcfr0aWrWrElsbKxVgq1KcnNz2bVrF+Hh4Te0CR3kl0GlpKRUiYY2UjVoToo90XwUe1Ml5uRTT8HrrxeOv/wS7r3XdvFUQxX92jMvL48ff/yRFStWsHDhwjKfv3XrVmJjYxk/frzVY7MXtnr9XyX+DZEqRXNS7I3mpNiTqjAff/jzB27/8HbT+NaGt/JM12dsGJHtJKQmUK9GPQaHDL6h97Xl584lKfcSTEOHDuW9997j/PnzGAwGMjIySmxMfdddd11XgCIiIiJSiZ06Zdn7oXXr8lU/GI35P+VZtkkqnIODA7fffju33377tQ8uQWBgYKV9ky0iIiIihcx7P6j6QeA6EhA1atTgk08+4fTp04wcOZL27dvz5JNPmvY7ODjg6+tbqgZyIiIiIlJFzZ0L5j3Bpk0rXxLh2DF4/nkIC4M+fdSAuooJDAwkMDDQ1mGIiIiIyHX44c8f+PHYj6bxLQ3V+0GuIwEB0KRJE5o0acLSpUupVasWLVq0sFZcIiIiIlLZJSVZ9n5o3Rruuad819q5Ey5ehF9+gdBQJSBEREREROzMjB9nmB4bMDC8taof5DoTEAU6duxIXFwc77//PpmZmRRtK/HEE09Y4zYiIiIiUpkUrX548cXyL6GUlQWennDpErRta534RERERETEKn7880d++PMH0/iWBrdQ36u+7QISu2GVBMR//vOfEpvNGY1GDAaDEhAiIiIi1U1SErz1VuG4Vavrazx9//1w333wxx9QX29kbC0+Pp4PP/yQ3bt306pVK/r06UNGRka5e0CIiIiISOVWtPrhwZsftGE0Yk+skoD45JNPMBqNtGjRgubNm+PkZJXLioiIiEhlNW+e9aofCjg6QlDQ9V1DrtuePXt4+OGHSU9Px2AwULduXTZv3szixYtZsGABvXv3tnWIIiIiInID/fjnj2z6c5Np3LVBVwK91N9L8lklU5Cenk7Lli1ZtWoVDtf7xlJEREREKrfTp+E//ykch4bmVy9IlfDqq6+SlZXFtGnTmDEj/5tubdq0wcHBgXfeeUcJCBEREZFqpljvh5vV+0EKWSVb0KNHD4xGo5IPIiIiIlK898O0aeWvfvjzTzhzxiphiXX8+uuvREREMGzYMNO23r1707ZtW44cOWLDyERERETkRvvp2E8W1Q9dAruo+kEsWKUCom/fvrz44ouMHTuWrl274u7ujsFgMO2/T994ExEREakeTp+27P1wPdUPubnw2mtw6hQ88AD87W+gpT5tztXVlcTERIxGo2lbVlYWCQkJeHh42DAyEREREbnRilY/PNTmIRtGI/bIKu/gJk6ciMFg4Mcff+THH38stl8JCBEREZFqYt48SE8vHF9P74e1a/MrIAB+/hnuvvu6w5Pr17NnT1atWsXgwYMB+O233xg4cCCnTp0ybRMRERGRqu/nYz+z8ehG01jVD1ISqyQgIiIirHEZk3PnzrFixQr27dtHZGQkDRo0sOr1RURERKQCFO39EBJyfb0fbrsN4uNhzRoYN+76m1iLVTz//PMcOXKE3bt3A5CUlARA69ateeaZZ2wZmoiIiIjcQOr9IKVhlQTEsmXLrHEZANauXUtUVBReXl5kZWWxdu1aHnvsMSIjIy2OO3/+PAMHDuS1116jU6dOpu15eXksXLiQL774gosXLxIREcGLL7541STG+fPnmTVrFj/99BMGg4EBAwbw7LPP4u7uDkBUVBT/+9//uP3223nnnXeKnf/tt9/y1FNP0bFjR6v+LkREREQqlddeK1794OhY/ut5esLYsflJDD+/649PrKJmzZosX76cLVu2sHfvXpydnWnZsiVdunSxdWgiIiIicoP8cvwXvj/6vWncObAzDbz1JXIpzqqL6O7cuZO4uDgMBgMdO3akTZs2ZTr/8uXLPPfcc4wcOZKuXbsSExNDs2bNiIyM5Pbbbyc8PBzI/5bVuHHjSE5OLnaNt956i08++YRXXnmFgIAA5s6dy6OPPso333yDi4tLifedMGECly9fZsmSJaSmpjJlyhTS09OZM2eO6RhnZ2c2b95MWloaNWrUsDh/9erVFj0vRERERKqd5GRYuLBwHBICQ4ZY59pKPtilrl270rVrV1uHISIiIiI2UKz3w83q/SAls0oCIjc3l2effZbVq1dbbB80aBCvvPJKqT+cP3z4MOnp6QwaNIgzZ84A0K9fP86ePYuPjw8AX375JXPnzqV+/frFzs/KymLx4sVMmjSJ2267DYDXX3+dW2+9lfXr13PXXXcVO2fnzp3ExMSwevVqmjVrBsBLL73Eo48+ylNPPUXdunWB/JLyw4cPs3HjRgYNGmQ6Py0tjZ9//pn27duX6jmKiIiIVElFez+88EL5qh9yciAvD67wxRGxvZCQkCvuc3Z2xs/Pj969e/PUU09d8QtAIiIiIlJ5bT6+mQ1HNpjGqn6Qq7FKAuK9997j22+/xd3dnc6dOwOwdetWvv76a5o3b85jjz1Wquv4+flhMBjYunUrzZs3B8BgMDBixAjTMd999x2RkZHccsst3HnnnRbn79+/n0uXLlmUf3t5eREaGkpsbGyJCYi4uDj8/f1NyQeAjh07YjAY2L59O/379wfy30zdcccdrF271iIBsWHDBoKCgmjQoAEnTpwo1fM0ZzQaMRqNZT7vehTc80bfV+RKNCfFnmg+ir2pFHMyORn+8x8KvnJiDA7Or34oT8xff53f82HsWGjXzqphVmfWnD++vr5cvHiRrKysYvuysrI4efIkH374IQ4ODjz77LNWu6+IiIiI2Af1fpCysEoCYuXKldSsWZOVK1eaei0cP36ce+65hy+//LLUCYiAgABGjx7NrFmzCAkJITAwkPj4eIv+De+++y4ACQkJxc4/deoUAPXq1bPYXqdOHdO+opKSkood7+Ligo+PD4mJiRbb+/Xrx/jx4y2WYVq9ejUDBgxg//79pXqORaWmpuJwgxsqGo1G0v/6hqKWjhJ7oDkp9kTzUexNZZiTbv/6F26XLpnG6U8/TXZaWpmvYzh7FvelSzFkZMDUqaS//jrGgABrhlpt5eXlWe1ac+bM4Z///Ccvvvgid911FwaDgRUrVvDvf/+bt956C39/f4YPH87atWuVgBARERGpYjYf38x3R74zjTvV70RD74Y2jEjsnVUSEImJiURERFgkCho2bMjNN99MXFxcma41efJkevbsyZIlS9i4cSPr1q1j4MCBzJkzB8drlPFfvnwZoFipt6urKykpKVc8p6TScFdXVzIzMy22de3aFXd3dzZt2sTAgQNJSUkhOjqamTNnljsB4eXldc3nZW0F34Dz9va22w8ypHrRnBR7ovko9sbu5+SZM/D++6ahMTgYj1Gjyrf8Uno6BAXB3r3Qrx9eQUHWi7Oay83Ntdq1Zs+eTZs2bXjwwQdN20aNGsW6det49dVX+d///kebNm2Ijo622j1FRERExD4U6/3QRr0f5OqskoDw9/dn3759XLhwwdSr4dy5c+zbt486deqU+XoRERHk5eURFBREcHAwkyZNIiwszGIpppK4ubkB+aXfBY8BMjMzcXd3v+I5JZWPZ2Zm4uHhYbGtYBmmgqTI+vXrCQ8PN/WJKA+DwWCTDxMK7muXH2RItaQ5KfZE81HsjV3Pyfnzwaz6wfDCC+BUzpeYN90Er7wCP/4IHTqAPT7fSsqacyc+Pp6cnBzy8vJMlbx5eXmcO3eOxMREcnNzOXPmDE7lnQciIiIiYpe2xG+xqH7oWL+jqh/kmqyy9k+/fv04f/48gwYN4qWXXuKll15i8ODBpKSk0Ldv31JfJykpyaKRtcFgoHfv3nTv3r1U36AqWErp9OnTFttPnz59xSRBQEBAseOzsrK4cOFCicmT/v3789NPP3Hp0iXWrFlj6hEhIiIiUu2cOQNvvlk4DgqC+++/vmsaDHDbbfDXcpdif4KDgzl+/DgjR45kyZIlLFmyhBEjRnD8+HFatGjBV199xb59+2jcuLGtQxURERERKypW/XCzqh/k2qySgBg/fjwdOnTg9OnTfPrpp3zyySecPn2aVq1a8c9//rPU14mJiSEyMpKjR49abD9z5oypsuJqgoODqVGjBtu2bTNtS01NZe/evURERJR4TkREBKdOneLYsWMWcQC0b9++2PGdO3fGw8ODVatWERcXR58+fUrz1ERERESqniLVD7zwQvmWXpJK5bnnnsPd3Z3Y2FjmzJnDnDlz2L59O25ubjz//POmL/dcq3pZRERERCqP6Pho1h9ebxp3rN+RRj6NbBiRVBZWqYt2c3Nj6dKlrF+/nri4OBwcHAgLC6N37944OzuX+jo9e/bE39+fqKgo7r77bi5cuMCCBQvYvXt3qRrYubi48NBDDzFv3jx8fX2pX78+c+fOJSAggN69ewP569+eO3eOmjVr4ubmRlhYGO3atSMyMpLp06eTnp7Oiy++yODBg0usmnBycqJXr17Mnz+fiIgIfH19S/+LEhEREakqilY/tGwJDzxQ9uskJ8OiRTBqFKjhdKXQtm1b1q9fz0cffcSRI0fIycmhZcuWDBs2jLp165KTk8OyZcuu+AUgEREREal8zKsfAFU/SKlZbWFWBwcH+vbtW6Yll4ry9PRk8eLFzJo1i1mzZgHQrFkzFi5cSLt27Up1jQkTJpCTk8PUqVPJyMggIiKCRYsWmRIhiYmJ3HHHHcyePZt77rkHg8HAwoULmTFjBiNHjsTV1ZW+ffvy3HPPXfEe/fv35/PPP2fAgAHlfq4iIiIildr8+ZCWVjgub/XDe+9BdDTExsLzz0MJFahif/z8/Jg4cWKJ+zp16nRjgxERERGRCrU1YSvrDq8zjVX9IGVhMBqNxvKceLUP6C1uYDDwr3/9q8zX37p1K7GxsYwfP77M51YGubm57Nq1i/DwcBxv8FIFRqORlJQUvL297bOZpVQ7mpNiTzQfxd7Y5Zw8exYaNy5MQLRsCb//Xvbm0ykpMGECnDsHPj7wzjvg6WntaIXrf+1Z0a/9qwNbvf63y39DpFrTnBR7ozkp9sRe52O/j/ux9o+1pvGbfd9UAqIUElITqFejHoNDBt/Q+9ryc+eSlLsC4n//+5/pL8LVchjlfRMSGBhoV3/RREREROQvJVU/lDX5AODtnZ90+OQTaN5cyQc7VvDav+B1f9H3AQX7lIAQERERqVq2Jmy1SD50vEnVD1I2170EU40aNWjfvj0dO3akVq1a1ogJyE9ABAYGWu16IiIiImIFZ89a9n5o0aJ8vR8KuLvDI49cf1xSocaOHWt6fOnSJT755BPq16/PrbfeisFg4KeffuLs2bM89dRTNoxSRERERKytWO+HNur9IGVT7gREeHg4e/bs4eLFi/z444/89NNPNG/enE6dOtGpUyciIiLw9va2ZqwiIiIiYmuvvw4XLxaOy1v9IJWKeb+HyZMnU7duXb755htcXV0B/r+9+46Pqkr/OP65M5NeCQkJEBAJEHpHOgIqAioqoq4FFcVeYW2oa0HsrmDvrq66NuRnByyoIL03aQISegglvc3M/f1xySRDAiQwSSbJ9707L+aee++ZZ4bjcOY+95xDTk4Ow4cPZ82aNdUUoYiIiIj42sIdC71GP/Ro1INm0c2qLyCpkU741+Knn35KdnY2ixcvZv78+cybN49NmzaxceNGPvroIwzDIDk5mZ49e3L//ff7MmYRERERqQ4HDsBLLxVvt2wJl11W8Xp+/RX69IHDF6+lZvnxxx/p0KGDJ/kAEBoaSuPGjZk5cyZPPfVUNUYnIiIiIr6i0Q/iC7aTOTksLIyBAwcyYcIEvv32W+bOncv48eOJiIjA7Xazbt06PvjgA1/FKiIiIiLV6cjRDw89VPHRD4sWWWtI3HILLF3q2/ikSoSFhbF06VK+/PJLsrKyyMjI4JNPPmHFihWEaR0PERERkVph0c5FTP9rume7R6MenBp9ajVGJDXVSY+Xz8rKYsGCBcydO5d58+aRkpLitSh1ixYtTvYlRERERKS6HTgAL75YvN2iBVx+ecXqME147z3reWoqZGf7Lj6pMhdffDGvv/46Dz30EA899JCn3DRNrrrqqmqMTERERER8RaMfxFdOOAExefJk5s+fz9q1a3G73Z6kQ4sWLTjttNM8j5iYGJ8FKyIiIiLVxBejHwzDOu+NN6xkRP/+vo1RqsTtt99OaGgoH3zwAWlpaQA0bNiQG2+8kX+czILkIiIiIuIXFu1cxA+bfvBsa/SDnIwTTkC8+eabGIZBWFgY3bp18yQc6tev7zkmLy+PXbt20ahRI58EKyIiIiLV4Mi1H5KS4IorTqyuxER4/HHIzbUSElLj2Gw2rr/+eq6//nqysrI8vwlEREREpHaY+PtEr+0rO2j0g5y4k56CKTs7m9mzZzN79uwy9xuGwZ9//nmyLyMiIiIi1WXKFMjIKN7+178qPvqhJMOA0NCTDkuqzuLFi6lXr16p6VXDw8M9z3/77TdSUlI0DZOIiIhIDbZ452K+3/S9Z7t7w+6cWk+jH+TEnfAvR41qEBEREakDDh70XvvhREY/HDgA9eppxEMNNnr0aM466yxefvllAJ566ikWL17MtGnTPMd88cUXzJo1SwkIERERkRps4uwjRj9o7Qc5SSecgJg1a5Yv4xARERERf3Tk6IeKrv2Qlwf//Kc19dJNN0Hjxj4PUapG0ZpvADt27GDdunXVGI2IiIiI+NqSXUv4buN3nu1uDbvRvF7zaoxIagNbdQcgIiIiIn7q4EErAVEkKQmurOAdUJ9/DmlpsGIFvPuuL6MTEREREREfeuz3x7y2NfpBfEEJCBEREREp24sveo9+ePDBiq/9kJwMcXHWeWPH+jY+ERERERHxiaW7lnqNfuia0JWkeknVGJHUFie9CLWIiIiI1EKHDnmPfmjevOKjHwB69oTOnWHdOtAaYiIiIiIifunI0Q+jO42upkiktlECQkRERERKmzIF0tOLtx98EAICTqyuoCArCSE12oEDB5g/f77nOcCCBQs8a0MUlYmIiIhIzbJs9zK+3fitZ1ujH8SXlIAQEREREW9Hjn449VQYrTug6rrly5dz7bXXepWNGTPG89w0TQzDqOqwREREROQklRr90FF9f/EdJSBERERExNuLL3qPfnjooYqNfvjgA3C54LLLICTE9/FJlWuk6bNEREREaqVlu5fxzYZvPNtdE7qSFKPRD+I7SkCIiIiISLFDh2Dy5OLtio5+2LYNpk0DtxsWLIDXXqv4wtXid2bNmlXdIYiIiIhIJZj4+0Sv7Ss7nsC6byLHYKvuAERERETEj7z00smt/bBlC9jt1vNBg5R8EBERERHxU8t3L+frDV97trskdKFFTItqjEhqI/0iFBERERHLkaMfmjWDq66qWB2DBkHr1vDll3DRRb6MTkREREREfOij1R9xYesLCQsMA+CK9lcQHx5fzVHVHqEBoUQHRVf56xqGQUxMjN+sz6YEhIiIiIhYXnrJSkIUqejohyING8Jtt/ksLBERERER8a30vB2M7jiQIPtpuM1sgh2BNAgzgNTqDq3WKHQ7cRhpwLwqfV3DMElIyMMwdgGVmYSwA6FAPSAaCC/zKCUgRERERMSadulkRz+IiIiIiIifcwEb2Z/zGmk535Fb+DcAbePakl0YVq2R1TZ5zlyC7cFEBidU8Sub5OdnEBwcSeUmIIo0BtoDw4DmpV5TCQgRERERKT364YEHIDCwfOf+/Tds3QoDB4KfDPMVEREREZGybCIz/9+s3feupyQyKNIzDZNIxe0s8bgBONVrrxahFhEREanrjhz9cMopcPXV5TvXNOG11+CFF6ykxYEDlROjiIiIiIicpGzgF9anfe9VmhiZWD3hSC2zBpgLFHiVKgEhIiIiUte9/DIcPFi8/eCD5R/9sGoVrFtnPT94ECIifB+fiIiIiIj4wCEy8xezJ2uPp0SjH8S31gDpXiVKQIiIiIjUZRkZ1uiFIk2bln/0A0CnTvDoo9bC0zfeeGKLVouIiIiISBXIYcP+n71KNPpBfGsHkONVojUgREREROqykxn9UKRbN2saJoe6liIiIiIi/irPmcnuzJ2e7YqMfjBNk9Q9JvENdT+7HEse1kLnxdRiREREROqqjAz497+Lt5s2hWuuObG6lHwQEREREfFraTn7vLYTIxuXedyt12Zx6bkZuN2mp+y1yXn88E1BmccX2b3TzTmne0+/c+igm3vvyGZo/3QuvyCThfMKy7Xv0nMzWL7EWe73Jv7E9NpSAkJERESkrjpy9MMDD5Rv9INpwvbtlReXiIiIiIj41NaDW8ksyPRsRwZFEBYYXuq4lL9dpB8yiW1gY8EfxQmAjHSz1LElrV3t5M4bssjK8i5/blIujRrb+HZWJHfeG8zEB3I4sN993H1SeygBISIiIlIXHbn2Q5MmMGZM+c796Se49VZ4803Izq6c+ERERERExGc+XfOp1/bR1n744ZsCevdzcPa5gXzzpTXi4ZtpBfw0vZCP3stnyjO5pc5ZPL+QiRNyuOzqIK/ynByT+XOcXHNDEAEBBj37BNChs4Pffyk85r4j/fvJXG4fm0VerncSZPcuN6d38x5xcXq3dHbvcuNymTw3KYcRgzMYNSyDpx/LoaDAOv/gATeP3Gftu/yCTGZ+X+B1/r+fzOWcgen8MrOA334u5PILMjl3UAa3XpvFxnXW9EIrlzsZ2s/7taVsSkCIiIiI1EWvvAIHDhRvl3f0Q2YmvP++NQriu+9gy5ZKC1FERERERE7e6r2rmbdjnmf7aKMfXC6TH78vZOh5gZwxJIAVy5zs2e1mxMhAzhoWwJXXBnHXfSGlzmvVxs5H/xdBr34BXuU7UtyEhxtE1yu+BN30FBspf7uPua+kd17LY9N6F8+8GEZwiFHu9zx7lpNtW9x8/n0E738eweaNLn79yUpuTHool+h6BlNnRDDx2VDeeDGPP1cXj/YICoL/+zGSPgMCeGZiDhOfDeXbWRH07OPgjZfzAOjUxcGMP6LKHU9dpgSEiIiISF2Tmem99kNFRj+EhMDIkVav/PTToUOHyolRRERERER8YuLsiV7bjY8y+mHhXCdx8TaSWtoJCzfoNzCAb6cde90HgKhoGwEBpZMDebkmQcHeZUHBBvl55jH3Ffm/z/OZ9mk+z74cSmhY+ZMPAOHhkLLNzY/TC8nLM3nzw3DOPieQ/fvcLF/i5OY7gwkMNGjRys6wEYFM/7Z45MXAswIIDDQICTEIDTX4dloB6/90ccWYIF54rXyLdksxrRYoIiIiUteUNfohKOjox5fkcMCoUVbyQQtPi4iIiIj4tTWpa5j651TObXUuYI1+CC9j9ANY0y/9vdnFhUMyAMjLMwkONhhzQzl/KxwhONggP9+7LD/PJCTUOOa+Ips3uQkLN1g418lZw8sxWruEHr0DuOE2k2+mFTDl6VzadbQz4dFQ0g+5cbvhoqEZnmNdbujSvfi3Tf36xffsP/tyGP95M4/xN2cTGmpw/W3BDD23YrHUdfrVKCIiIlKXZGbC888Xbycmln/0Q0lxcb6LSUREREREKsXE38s3+uHQQTcL5zl5+6NwIiKLkwA3X53F7F9Lr8tQHo2b2MjKNMlIdxMZZV3UT9nmpldfxzH3FbnrvmBysmHy07n06hfgFReA7fCm02nicBikHyqevmnXDjftO9s598JwDux38/Lzebz+Yi63jQ8hOAS+/TUS2+EK9qe5sdtLVHy43txck4x0k0nPh1FYaPL7L4U8+XAufU8PICKiYiMy6jJNwSQiIiJSl7z66omNfnC7j3+MiIiIiIj4jTWpa/jizy8820H2oKOOfpj5fSHtO9pp1txO/Vib53Hm0EC+nlpAQKBBdrZZ5rlHExZu0LOvg7dfzSc/32TRvEJWL3fSf1DAMfcVcTgMTj8jgKSWdt48vPZCSdExBqFh8OtPhTidJp/+twDjcF5g6SInjz+Qw8EDbiIjDQIDISLSIL6hjZbJdv7zRj6FhSb7Ut2MuynbawqmIi4nTLgrm0XzCgkIMIiKNggKLt/SeVJMCQgRERGRuqKs0Q/XXnv889LT4eab4ccfrcWnRURERETE7z0++3Gv7aigoy+aPP2bAgadFVCqfMg5AaxY6qJZcxvTvy7giYdzKhTDvf8K4UCam5FDMnjp+TwefiqU+rG24+4r6c57g5n5XQFrVjm9yoOCDO64O4R3Xstj5JBMAgIhPsHKQAw/P4AOXRxcfXEW552RQUaGyQ23WYtOPPJUKH9vdXHR2ZmMvTyLnn0cXHJF6axCeITBv54I5eV/5zG0XzovPZfHo0+HEhRksHK5k6H90iv0WdRVhmnqV2R1cLlcrFixgs6dO2P3GuNT+UzTJD09naioKAxDw4Wk+qlNij9RexR/49M2+fTTMGFC8farr8Ittxz/vBdfhJ9/tp5ffjlcdtnJxSFVrjr7nmKprr8D/bsm/kZtUvyN2qT4E1+2x7Wpa+nwegdMrEu/t3a/lafOvJLswjt8EaqUQ54zl2B7MAkRCVX6ulY7yiAqKrIavteCgGeAJE+JRkCIiIiI1AVZWd6jHxo3huuuO/55bjcUHh6OHBYGw4ZVTnwiIiIiIuIzj89+3JN8ABh06qBqjEbqMi1CLSIiIlIXvPoq7N9fvD1hQvnWfrDZ4O67YcgQOHQIoqMrK0IREREREfGBtalr+Xzt557tdnHtaBLZBNC6blL1lIAQERERqe2ysuC554q3yzv6oaSOHX0bk4iIiIiIVIojRz+M7ji6GqORuk5TMImIiIjUdq+9Vnr0Q3Bw9cUjIiIiIiKV4s99f5Ya/dA2rm01RiR1nRIQIiIiIrXZkaMfGjUq3+iHTz+FDRsqLy4REREREfG5I0c/XNnhygrXMefXQl+GJHWcEhAiIiIitdnrr0NaWvF2eUY/rFkDH38M99wD//lP5cYnIiIiIiI+sW7fOj5b85lnu11cO9o1aFfu8xfMLeSG0VlMfDCHcTdl8fcWV2WEWaM4C03S9tXctTNM02TXrupNKCkBISIiIlJbZWfDs88WbzdqBGPHHv+877+3/jRNSEionNhERERERMSnTmb0w75UNxMn5HD12CD6DwygQ2cHD/4zp9Rxf29xcVbvdHbvKn1R/sh9P/1QwNB+6V6P07ul89P0AgBWLHUy5tJMhg1I54bRWaxb4wRg+RInl56bcdRY584uZMqzueV+byfjsQdyWDzfimv6NwXceUOWz19j8OAtLFxY+rP2hWeeSePLL9Mrpe7y0iLUIiIiIrXVa695j364//7yrf1w993QujUsWgRnn1158YmIiIiIiE+s27eOT9d86tluG9u2QqMf/lztokkzO31PD2D2rEKuGBOE3Q55uSbBIQYATqfJ04/mUlBQ+vyy9p01PJCzhgd6tqd+ks+vPxUy6MwAXC6Th+/J4V9PhtC9p4Ovvijg0Qk5fPZt5HFjXfCHk76nV81l7Yx08/gH+bFDh1yEhVVvCkAJCBEREZHaKDvbe+2Hhg3h+uvLd67dDuefDyNGgGFUTnwiIiIiIuIzk+ZM8h790LFiaz/UizHY/reLvbut0QtBQQZXX+9989LH/8mnQ2c769aWnprpWPsAdu9y858383jrw3AcAQaHDrpJTzdxOa2B13Y7BAaW/u2Rts/NbddlcfHlQVz0jyDAGjlx2/hgpn9TwNzZhdhssGiek8SmNsZNCOGtl/PYsM5Fh04OHn8ulOAQg21bXbz0XB7r1zqJqW9j9NgghhxOjlx6bgbnjwri66n55OTAoLMCGD8hhLdfzWPVchd/rs7l4EGTevUMcrJNHn8wh4XznNSLMXjw8RBaty19iX3dGievTikkZWshLmcWQ4aEM2lSPHa7wYoVuTz88F62by/kvPMicR3+yJ55Zh9ZWW4efzwegP37nQwatJXffmtORoaLSZNSWb8+n+xsN716hfLccw0JD7cxevR2evQI4YcfMklLc9G3bygPPhjKZ5+l8+23GRgGHDzo4uGH43n77QNMm5bBnj2F1Ktn5+674xg+PAKADz88yJtvHsBmM7jqqmheeCGNP/9sBcDcudk8+2waO3cW0r59MBMnNqBp08BS77ssmoJJREREpDZ6/XXYt694uzxrPxxJyQcREREREb+3Pm09n6z+xLPdJrYN7Ru0r1AdHbs4GDEqkKsvzmTlcifff12A01mc0Phro4tffypk7C2lf1Mca1+Rt1/JY8TIIBo3sQMQXc/GORcEcN+dOZzZK4PXpuTxwGMhXudkZpjcfWs2I0YWJx+2bnaR0MhGULD1W2Xu706Gnx/Id79FEhFpcO9t2dx+dwhTf4hkzy43s34qpKDAqqdzNztf/RzJAxNDePn5PFYsdXpea/GCQt75JIIX3wrjxx8KWLPSyfW3BtOxi53xE0K4/Grr9TdtcNP3dAff/BJBt9McvPVKfpnv99EJOQwdYeObnyP46qtT+PXXbObNyyEvz82tt+7iiiuiWbSoBYmJAezZY8Vx3nkR/PRTludznzEji169QomJsfOvf+2lW7cQZs9uzs8/n8q2bYV8913xNFU//pjFf//bhO++O4UVK/L49dc8Lr00ivPOi+TGG2N4+OF4Fi7M4eOPD/H++41ZtqwF110Xw5NPpgIwf34Ob7xxgPfeS2T69GYsW5brSYxs317IHXfs5v7745g/P4nTTw/j1lt34XaXb3SIEhAiIiIitc2Raz+UZ/TD339DevXODSoiIiIiIhU3abb36IfRHUafUD033RHCWx+FExZu8MkH+fzzlmzcbpPCQpOnH83hnw+EeC78FznWviJ7d7uZN6eQS64svmPe5TIJCzN4/pVQZvwRydibg3nkvhzycq33UVAAE+7KpkUrO5dfE+Q5b+FcJ736Fo84OOVUG736BuBwGLTv6KBzdwctWtkJjzBo3d5O6h43q5a7ME248togAgIM2rR3cN6Fgfz4ffF8USMuCiIiwqB5CzstWtrZsb3shaeTWtoYPCQQm82g7+kO9uws+7gXXgvjzOF2srJM9u93EhVlIy3NyfLleQQFGVx6aTQBAQbXXVePevWspEzbtsHUq2dnwQJrPYgZMzI591xrdMIzzyRw3XUx5OWZ7N3rJDraTlpa8WiTCy6IpEEDBwkJAfToEcL27aVHonTsGMxnnzWlQQMHe/c6CQoy2LfPOu6bbzK4+OIoWrUKIizMxt13x3nO++GHTAYODKN371ACAgzGjKnHoUMuVq/OK/O9H0lTMImIiIjUNm+84T364XhrPzid8MwzcPAgjB4Nw4aBTfepiIiIiIj4u/Vp6/lkzRGjH+IrNvqhpKbNrAvw4+4P4bLzM1mxxMWyJU46d3fQoXPpS8kfvJ1/1H1FfplZyGm9HdSLKf6N8fsvhaT87ebW8QEAjLo8iK+mFrB0kZPQMIMD+01OTYIlC51kZphERFrJjQVzC7n7oeKREpFRxUkPmx3Cw0tsG9b0TocOuomLt2GUGOEd39Bg04bipE10veJ9dgeYZecVCI8oPs7hMHC5yh4FsHqli/dvLcDtKqRjByuJY5qQluakQYPiz8puN0hIKN4+77wIpk/PpFWrINasyePNNxsDsGlTATfcsJNDh1y0aRNEZqYL0yx+7ZgYe4k6rfd9JMOAKVPSmDUri4YNA0hKKk4IpaY66dSp+Ddj48bFMe3eXciPP2bRvftfnrLCQpNdu5x06lT251SSEhAiIiIitcmRox8SEo4/+uHbb2HHDuv5r7/C8OGVF5+IiIiIiPjMpNmTcJe4Wn5lh4qt/VDky0/zWbPKxSNPhgIQHGIQG2eQnW3y+8+F7E9zM/3r4hED1/4jk/ETQo6576xh1gXuBXMLGXGR93oB+1JNCp1eRTgc1sV/gLgGBi+8Hs79d2Xzxku53PNQKDnZJgcPmCQ2Kb7YXp5ZY+PibaTucWOapicJsXuXm+iYyplyNnWvm38/mcvL/3HQulUoCREJnH/+NgBiYx3s3u30xGKaJmlpxR/EeedFcPHF22nTJoiBA8MJDbVRUGBy1127ePnlRvTrFwbALbfsrHBc779/kD17nPz2W3NCQmysW5fHd99lAhAfb8VVpGhaqKKYL7ookkcfjfeUbd1aQKNG5Ust6NY2ERERkdrkjTcgNbV4+/77ISTk6McDDB4MZ5xhjXq45Rat/SAiIiIiUgNsSNvgNfqhdWxrOsR3OKG62rSz88dvhaxabl14XvBHIbt2uGnfyc6H0yL4YXYU3/9uPQDe+zSCs4YFHnMfgNttsnGdi3YdvC9WdzvNweoVTmbPKsTtNvnhmwLSD5l06GQdZz+cY7jj7hB++qGQNSudLFnopNtpFb+fvm17O0HBBh+9l4+z0GTdGiff/V8hg88KOO65AQFWEqYicrJNDCAwyBoh8cUX6WzYkI/TadKtWzCGAR98cIjCQpP//veQZxokgCZNAmnaNIC33z7omX6poMAkP98kNNSGaZrMmpXFnDk5OJ1HCaCEwECDrCwrQZWR4SYoyMBuNzhwwMWLL+4HrNEMI0ZE8uWX6WzalE9urpvJk9M8dQwbFsGMGVmsWJGLaZr8+GMm55+/jYMHy15w/EgaASEiIiJSW+TklB79cMMNxz8vKgruugsuvxwaNKi08ERERERExHcmzfEe/XCiaz8AtO3g4LbxwUx8IIcD+03+XO3ikadCvaZNOhHph0xycyEm1vsmpxat7Dz0eCjvvp7H04+6aZZk55mXwggL9z6uUaKNf1wVxPNP5JLc1s7gIcdPGhwpIMDgqcmhTHkml08+yCcy2uDG24Pp3f/4dZ1xdgAvPpvLoYMmjRPL91k0a27n4iuCuH1MPnbDSdeuboYODWfz5gICA2288UZjHnhgD1OmpDFoUDjJyd6jQ847L4KXX95P//7WaIfwcBsPPtiA227bhdNpkpwcxIUXRrJ5c0FZL+9lyJBw7rprNwcPurj77jjGj99Nz55/ERVl5+KLo1i2LJfNmwvo1SuUq6+ux+jROwgIsNaUCDj88SQlBfL00/E8/PBeduxw0rixg5dfbkhCQvn+LgzTLGtGKKlsLpeLFStW0LlzZ+x2+/FP8CHTNElPTycqKspr7jOR6qI2Kf5E7VH8TYXa5AsvwD//Wbw9ebKVWJA6rzr7nmKprr8D/bsm/kZtUvyN2qT4k4q0x437N9Lm1TaeBETr2NY8e+azRz0+PiyeNnFusgvvOG4cTz2Sw4THQisWvJSS58wl2B5MQkRClb6u1Y4yiIqKLPf32ubNBQQHGzRuHODZvuqq7cydm1TBVw8CngGKz9MUTCIiIiK1QVmjH2688ejHO52Ua8yuiIiIiIj4HV+t/VAWJR/qntWr87j99l0cOuQiP9/NO+8coE8f37QDJSBEREREaoM334S9e4u377vv2Gs/TJsG48bB2rWVH5uIiIiIiPjMxv0b+Xj1x57t5PrJdIzveMxz3KYbg4pPXyR1w4gREXTtGsKwYX/Tt+8WcnLcPPDAiUzP6+DIlIPWgBARERGp6XJy4Jlnirfj4489+iE1FT77DAoK4MEH4Z13IDa28uMUEREREZGT9sScJ7zXfuh4/LUfnG4nbkIxiMIkvTLDkxrIZjN46KEGPPTQya4JGAV4r2mhERAiIiIiNd1bb1Vs9ENeHjRtaj0/91wlH0REREREaohN+zfx0aqPPNvlGf0AkJGfQYErhEB7h8oMT+q81kCkV4lGQIiIiIjUZLm5FRv9AFby4d//hp9/hn79Kjc+ERERERHxmUlzTmztB5fpYn9OIY0j+5LvWgQUVFKEUneFAKcBEV6lGgEhIiIiUpO9+Sbs2VO8fe+9EFqOxcJsNhgypHzHioiIiIhItfvrwF98vKp47YdWMa3KNfqhyM6MPeQUdiIs4EYMwisjRKmzooCxQKdSezQCQkRERKSmOnL0Q4MGcNNN1RePiIiIiIhUmkmzJ+EyXZ7t0R1HYxhGuc/PLsxmbep22sX1ITSgPbAKl/kXppkDmL4PuI4zyCfQFgjUq+JXNnE4coBQoPzto+JsWKMeWgHtgHggrNRRSkCIiIiI1FRvvVX+0Q+7d8Mnn8DVV0P9+lUTn4iIiIiI+MRfB/7yWvuhoqMfimQVZLF090bqBdcjJqQnEUG9cdgqNkmOzTCwGXacbmeFX78uKXTnYzMCgbgqfmUTtzsTayqkykxAANixEh32ox6hBISIiIhITZSbC08/Xbx9rNEPpmlN1bR0KcyfD488Au3bV02cIiIiIiJy0p6Y84TX6IcrO15ZodEPJTndTvbl7GNfzr5yn2MzbMSHx9Mksgn1Q+OwGTbmbJvDobxDJxRDXbAjYwcNwxtyQZsLqvR13W4XmzZtoXPnxtjtR08MVBUlIERERERqorffLj36Iaz0cFcA9u+HjRut52Fh0KJF5ccn4kMHDhzgyy+/ZN26dYwbN44mTZpUd0giIiIiVWbzgc18uPJDz3bLmJZ0ii89135lqBdcjyZRTWgU0YgAe4CnPC0njZzCnCqJQWo2LUItIiIiUtPk5XmPfoiLO/baD7Gx1giIoUPh+ushOLjyYxTxkRkzZjB48GA+/PBD5s2bx9lnn83kyZM9+x966CGSk5O9HoMHDz5mndOnT2f48OF07NiRCy64gPnz53v27dixw1PP2rVryzx/2LBhJCcns3DhQt+8SREREZFjKDX6ocOJj34ojxBHCC1jWjLo1EH0O6Ufp0SfQoA9gNzCXDbt38SsLbOYv30+Ba6CSotBag+NgBARERGpad5+21rTocixRj8UiYiAW2+t3LhEfCw3N5cJEyZw9dVX06dPHxYtWkRSUhLjxo1j0KBBdO7cmQ0bNnDTTTdx5ZVXes471lDzBQsWcM8993DvvffSt29fpk6dyg033MBXX31FUlKS57iAgABmzpxJu3btvM5fv349W7du9f2bFRERESnD5gOb+e/K/3q2W8a0pHNCZ5+/jt2w0zCiIU2imhAbGuspd7qd7M7czfaM7ezP2e/z15XaTwkIERERkZokLw+eeqp4Oy4Obr65+uIRqUSbN28mJyeHESNGkJaWBlijD/bv3090dDSmafLXX39xww03EBdXvsX93n77bc4880yuuuoqAO677z6WL1/OBx98wMSJEz3H9e7dmxkzZjB+/Hiv83/44Qe6d+/O4sWLffQuRURERI7uyTlPVuroh9jQWJpENiEhIgGHzbpUbJomaTlp7MjYwe7M3V6vL1JRSkCIiIiI1CRHjn64556yRz+YJsyeDX37gkNdPqmZYmNjMQyDBQsW0OLw2iWGYTB69GgAtm3bRk5ODs2bNy9XfW63m2XLlnH//fd7lffs2ZMff/zRq2zYsGFMmDCBdevW0aZNG0/59OnTGTNmzAknIEzTxDTNEzr3ZF6vKl9T5FjUJsXfqE2KPzmyPW45uIUPVn7g2d+iXgs6xXc66fYaHhhOk6gmJEYmEhIQ4inPKshie/p2dqTvINeZe1KvIYf/Pqn67xd/+z7Tr1ERERGRmuLItR9iY+GWW8o+dt48eP55+OQTuO02aN++amIU8aGEhATGjBnDpEmTaNOmDYmJiWzfvt2zCPXGw4urf/jhh8yePRubzcaAAQMYN24cERERperLyMggJyeHhIQEr/IGDRqwp+Si7kDjxo3p2LEjM2bM8CQgVq1aRUZGBn379j3h95SRkYHNVnVL8ZmmSU6OtUBkZc4VLVJeapPib9QmxZ8c2R4f/eVRr9EHo1qNIif3xBZ+DrQHckq9U2hWvxmxYcVTLBU4C9h2cBtb92/VFEs+lpuXS7Ytm/T09Cp9XbfbXaWvdzxKQIiIiIjUFO+8A7t2FW8fbfSDywXvvWc937kTsrKqJj6RSnDfffcxePBg3n//fWbNmsXMmTM577zzeOaZZ9i4cSM2m40GDRrwxhtvkJKSwrPPPsumTZv44IMPSl3oz8vLAyAwMNCrPCgoiPz8/FKvPWzYMD777DPGjRsHWKMfzj777GOuMXE8kZGRJ3V+RRXdARcVFaULa+IX1CbF36hNij8p2R63HtrKp+s/9exrUa8FvU7pVaF2amDQILwBTaKakBCegM2w+kZu001qdirb07ezN2svbtO6YB0Wepx15aRCQpwhhIWFERUVVaWv63L515RZSkCIiIiI1ARHrv1wrNEPdjs8+CC8/rqVoOjZs2piFKkkPXr0wO12k5ycTOvWrbn77rvp1KkTN998M5dffjn16tUDoFWrVsTFxXHJJZewevVqOnXq5FVPUFAQAAUFBV7l+fn5hISEcKShQ4fy7LPPsn79epKTk5k+fTrPPPPMSb0XwzCq/AJX0Wvqwpr4C7VJ8Tdqk+JPitriU388hdPt9JRf2fHKco+ijAqKIjEqkcYRjQlyBHnK0/PS2ZGxgx0ZOyhwFfeH1PYrh2EYGFRP38+fKAEhIiIiUhO8+27p0Q/h4Uc/vnlzePZZyMkBP+uAipTX3r17Wbp0KcOHDwesH1NDhgxhwIABzJ8/n9GjR3uSD0VatmwJwJ49e0olIKKjowkNDSU1NdWrPDU1lfj4+FKv36hRIzp37syMGTPIycnB5XLRo0cPdpX8b1FERETEx7Ye3Oq19kNSvSS6JHQBoElUE4IdwWzav8nrnCB7EImRiSRGJRIZFOkpz3PmsTNjJzsydpCRn1E1b0CkBCUgRERERPxdfn75134oyTDKnqJJpIZYtGgRd999t9ci0ABpaWk0b96ce++9l9TUVN5//33PvtWrVwN4Fq0uyTAMunbtyqJFi7j44os95QsXLqR79+5lxjB06FA+++wzsrOzGTp0aJWu3yAiIiJ105N/POk9+qHDlRiGQVJMEm3j2uI23Ww5sAUTk4TwBJpENiEuLM5z57vL7WJP1h52ZOxgX/Y+TPxrUWKpW5SAEBEREfE3KSmQlmY9N02CPvwQY+fO4v1jx5Y9+iE9Hap4flGRyjR48GDi4uK4//77ufDCCzl06BBTpkxh5cqV3HvvvRw8eJBbbrmFV155hREjRrB161YmTpzIueeeS1JSEgCZmZkUFhYSExMDwJgxY7jhhhto27YtAwYM4Msvv2TdunU88cQTZcYwbNgwnn76aVJTU3n33Xer7L2LiIhI3eJyu5i9bTaLti3iPyv+4ylPqpdE14ZdaRrVlLZxbQFIOZRCuwbtaBTRiAB7gOfYA7kH2J6+nd2Zuyl0F1b5exApS41NQBw4cMDzY2HcuHE0adKkukMSEREROXkpKZCcbK35ABhAqZnpJ0+Gm2+Gpk2Ly3Jy4I47oFUruP56aNCgqiIWqTRhYWG89957TJo0iUmTJgGQlJTEK6+8QteuXQGYMmUKb731Fm+//TYRERGcd9553HXXXZ46nnjiCRYtWsSsWbMA6NevH08++SSvvfYakydPpkWLFrzxxhuehMWR4uPj6dq1K3v27KFz586V+n5FRESkbpq2bhp3zriTHRk7Su27ssOVNI5sTMf4jgAUuApoVq+ZZ39OYQ470q11HbILs6sqZJFyq5EJiBkzZnD//fcTGRlJQUEBM2bM4Prrr2fcuHEAPPTQQ3zxxRde5zRu3Njzo6Ms06dP5+WXX2bHjh00b96c++67j969ewOwY8cOzjjjDACmTZtGu3btSp0/bNgwtmzZwn//+196aqFHEREROVFpaZ7kw1Hl51vHlUxA/O9/cOAALFgADgfcd1/lxilSRVq1asV///tfFixYwOLFi7n99tu99g8bNoxhw4Yd9fynS05fdtgFF1zABRdcUObxiYmJbNiwwavsf//733GPERERETkR09ZNY9Tno446TVLnhM50bdjVM71SoD0Qp9vJ7szdbE/fzv7c/VUZrkiF1bgERG5uLhMmTODqq6+mT58+LFq0iKSkJMaNG8egQYPo3LkzGzZs4KabbuLKK6/0nGe3249a54IFC7jnnnu499576du3L1OnTuWGG27gq6++8roTKiAggJkzZ5ZKQKxfv56tW7f6/s2KiIiIlFerVhAdbY2EGDOmuqMR8bnExETPD28RERGR2sDldnHnjDuPuUbDaYmnleoDOWwOmkQ1odBVqASE+L0at4La5s2bycnJYcSIEZ6yYcOG8dBDDxEdHY1pmvz111+0b9+euLg4z6NozteyvP3225x55plcddVVJCUlcd9999GuXTs++OADr+N69+7NjBkzSp3/ww8/HHXROhEREZEqMWAAvPEGPPSQpl+SWikxMVEjjUVERKRWmZMyp8xpl0q6/MvL2bR/EzszdrIvex+Z+ZmeBaqDHEFVEabISalxCYjY2FgMw2DBggWeMsMwGD16NM2aNSMlJYWcnByaN29ervrcbjfLli3zTLdUpGfPnixevNirbNiwYWzbto1169Z5lU+fPp3hw4ef4DsSERER8ZGwMOjSpbqjEBERERGRctidufu4x/y+7XfeXPomy3YvY8GOBfz2929M3zSdHzb+wLLdy6ogSpGTU+OmYEpISGDMmDFMmjSJNm3akJiYyPbt2z2LUG/cuBGADz/8kNmzZ2Oz2RgwYADjxo0jIiKiVH0ZGRnk5OSQkJDgVd6gQQP27NnjVda4cWM6duzIjBkzaNOmDQCrVq0iIyODvn37ntD7MU0T0zz6MKvKUPSaVf26IkejNin+RO1Rqt2uXZRnkhnTNEHtVMpJ32kiIiIi/qdBWPlGLscEl57ZxWW6fB2OSKWocQkIgPvuu4/Bgwfz/vvvM2vWLGbOnMl5553HM888w8aNG7HZbDRo0IA33niDlJQUnn32WTZt2sQHH3yAzeY96CPv8CKPgYGBXuVBQUHk5+eXeu1hw4bx2WefeRa8nj59OmefffYx15g4loyMjFIxVTbTNMnJyQHQPLriF9QmxZ+oPUp1sq9eTdjVV5crAZGVlYX91Vcxg4IoPP98OKIvI1KS2+2u7hBEREREpIScwhxeWvjScY+LDY2lbVzbKohIpHLUyAQEQI8ePXC73SQnJ9O6dWvuvvtuOnXqxM0338zll19OvXr1AGjVqhVxcXFccsklrF69mk6dOnnVExRkzZVWUFDgVZ6fn09ISEip1x06dCjPPvss69evJzk5menTp/PMM8+c8PuIjIw84eTFiSq6Ay4qKkoX18QvqE2KP1F7lGrz448wahRGVla5Dg8/dMg6xzRh5Up48UWo4psapOZwuXSHnIiIiIi/SMtJ47xPzmPBjgXHPXZsl7HYbVV77VDEl2pcAmLv3r0sXbrUs+aCYRgMGTKEAQMGMH/+fEaPHu1JPhRp2bIlAHv27CmVgIiOjiY0NJTU1FSv8tTUVOLj40u9fqNGjejcuTMzZswgJycHl8tFjx492LVr1wm9H8MwquUCV9Hr6uKa+Au1SfEnao9S5T74AMaOBaezfMcHB2McOmQlHFwuGDgQqviGBqlZ9H0mIiIi4h82H9jMsI+HsenAJk+Z3bATGhBKZkGmpyw2NJaxXcbSp0mf6ghTxGdqXAJi0aJF3H333Z41GIqkpaXRvHlz7r33XlJTU3n//fc9+1avXg1AixYtStVnGAZdu3Zl0aJFXHzxxZ7yhQsX0r179zJjGDp0KJ999hnZ2dkMHTq0yqdQEhERkVrCNOGJJ+Bf//IuP/10ePxxCAvDNE2ysrIIDw8vvogcGwtNm8KgQfB//wcXXFDloYuIiIiISMUs3rmYcz85l9Ts4huhwwLCeOT0R2gZ05K1+9ayJ30PCVEJtItrp5EPUivUuATE4MGDiYuL4/777+fCCy/k0KFDTJkyhZUrV3Lvvfdy8OBBbrnlFl555RVGjBjB1q1bmThxIueeey5JSUkAZGZmUlhYSEyMtYDLmDFjuOGGG2jbti0DBgzgyy+/ZN26dTzxxBNlxjBs2DCefvppUlNTeffdd6vsvYuIiEgt4nTCrbfCW295l197LbzxBgQEWNumiSs9HaKi4Mi72Js2hTvvrJp4RURERETkhH2/8XsumXoJOYU5nrK40DgeH/Q4jSIaAdChQQeahzcnLDRMI1il1qhxCYiwsDDee+89Jk2axKRJkwBISkrilVdeoWvXrgBMmTKFt956i7fffpuIiAjOO+887rrrLk8dTzzxBIsWLWLWrFkA9OvXjyeffJLXXnuNyZMn06JFC9544w1PwuJI8fHxdO3alT179tC5c+dKfb8iIiJSC2Vnw6WXwvffe5c/+ig8/HDpRIOIiIiIiNRYby99m5u/vxmXWbwu16nRp/LYwMeIDo6uvsBEqoBhFq22WQMtWLCAxYsXc/vtt1d3KBXmcrlYsWIFnTt3rpZFqNPT07XAqvgNtUnxJ2qPUulSU+Gcc2DJkuIyux3efBOuu67U4V5tcssW6/xevZSkkAqpzr6nWKrr70D/rom/UZsUf6M2KZXJNE0e+e0RHp/9uFd55/jOPND/AYIdwaWOz87J1giIWmJHxg4ahjfkgjYXVOnr+lvfv8aNgCgpMTFR/zGKiIhIzbFpEwwdClu2FJeFhcEXX8CwYcc+1+2GV1+16ujWDcaPh8jIyo1XREREREROSKGrkOu/vZ4PVn7gVX7GqWdwW4/btL6D1Bk1PgGRmJhY3WGIiIiIHN+CBXDuubB/f3FZfLw1DVO3bsc/f/FiK/kAsG8fhIZWTpwiIiIiInJSMvMzGfXFKH7c/KNX+WXtLuMf7f+hG6qlTrFVdwAiIiIitd7XX8OgQd7Jh+RkmD+/fMkHgNNOg/vvh9hYuPlmcNTo+0hERERERGql3Zm7GfD+AK/kg82wcXuP27msw2VKPkido1+uIiIiIpXptdfg9tutKZSK9OkD33wD9euXvx7DgL59rUREQIDv4xQRERERkZOybt86hn08jG3p2zxlQfYg7u97P90alfPGI5FaRiMgRERERCqD222NWLj1Vu/kw4UXws8/Vyz5UJKSDyIiIiIifuePlD/o+15fr+RDZFAkT5/xtJIPUqdpBISIiIiIrxUUwLXXwscfe5fffjtMngz2ci44l54OBw9CdLTPQxQREREREd+Y+udUrpx2JfmufE9Zw/CGTBo0ibiwuGqMTKT6KQEhIiIi4kvp6TByJMya5V3+3HPwz39aUymVx6pV8PzzkJlJwJAhcM01EBLi83BFREREROTETVkwhfEzx2NiesqS6yfzyOmPEB4YXo2RifgHTcEkIiIi4is7dkD//t7Jh8BA+OQTuPvu8icfAPLzrdEPTicBv/0Ge/b4PFwRERERETkxbtPN+JnjGTdznFfyoWfjnjwx+AklH0QO0wgIEREREV9YswaGDbOSEEWiouCrr2DgwIrX16MHjBgB27eTe911BDRt6qtIRURERETkJOQ587j6q6v5fO3nXuXntDyH67tej83QPd8iRZSAEBERETlZv/5qLS6dnl5clpgIM2ZAu3blq2P7dmjSxLtszBiw2TAzMnwXq4iIiIiInLCDuQe54LMLmL1ttqfMwODqTlczss3IaoxMxD8pHSciIiJyMv73Pzj7bO/kQ8eOsGBB+ZIPeXnw0ktw663WKIqSHI6KTdskIiIiIiKVZtuhbfR9r69X8sFhc3B377uVfBA5CiUgRERERE6EacKzz8IVV0BhYXH5GWfA7NnQuHH56vn5Z/jpJ6u+f/8bcnMrJ14RERERETlhK/asoPe7vVmXts5TFuoIZeLAifQ/pX81Ribi35SAEBEREakolwvuuAPuu8+7/Mor4YcfrLUfymv4cOjQAYKDrfODg30bq4iIiIiInJSfNv/EgP8MYHfWbk9ZTEgMz531HO0btK/GyET8n9aAEBEREamI3Fy4/HJrcemSJkyAJ544/pRJpul9jM0G//ynNRVTeUdNiIiIiIhIlfjvyv9y3TfX4XQ7PWVNI5sycdBEYkJiqjEykZpBIyBEREREyistzZpiqWTywWaD116DJ588fvJhzRq4806rnpLq11fyQURERETEj5imyROzn+Dqr672Sj50aNCBZ896VskHkXJSAkJERESkPLZsgb59Yf784rKQEPi//4Obbz7++X/8AQ88AFu3Wms9uN2VF6uIiIiIiJwwp9vJzd/fzEO/PuRVfvopp/PYwMcIDQitpshEah5NwSQiIiJyPEuWwDnnQGpqcVlsLHz7LfTqVb46OnWyRjqkpVkjJXJyIDy8cuIVEREREZETkl2QzT++/AffbfzOq3xUm1GM7jga43ijnkXEixIQIiIiIsfyww9w8cVWwqBIUhJMnw4tW5a/nogIuOceWL3aqs+mgagiIiIiIv4kNTuV8z45j0U7F3nKbIaNG7veyLCWw6oxMpGaS798RURERI7mnXdgxAjv5EOPHjBv3rGTDwUF8Pnn1p8ltW0Ll16q5IOIiIiIiJ/568Bf9Hm3j1fyIdAWyAP9HlDyQeQkaASEiIiIyJFMEx59FCZO9C4/91z49FMICzv6uTt3wtNPw99/w6FDcMMNlRioiIiIiIicrIU7FnLuJ+eSlpPmKQsPDOfR0x+lVf1W1RiZSM2n2+9ERERESioshGuvLZ18uPFGa8HpYyUfis7fudN6PnOmteaDiIiIiIj4pW82fMOgDwZ5JR8ahDXghSEvKPkg4gNKQIiIiIgUycyE886D99/3Ln/iCXj9dXCUY/Bos2Ywdiw0bQovvGAtVi0iIiIiIn7n9cWvc+FnF5LrzPWUJdVL4oUhL5AQnlCNkYnUHpqCSURERARg92445xxYvry4zOGAd9+Fq646+nm7dkHDhmAYxWXDhsGZZ0JgYOXFKyIiIiIiJ8Q0TR6c9SBP/fGUV3m3ht24v+/9BDmCqikykdpHCQgRERGRdeuspMG2bcVlERHw5Zdw1llln2Oa1v4PP4Q77oAzzijeZxhKPogXl9vFnJQ57M7cTcOIhvRv2h+7zV7dYYmIiIjUOQWuAq775jo+WvWRV/mQ5kO4ufvN6qOJ+JgSECIiIlK3/fEHjBgBBw8WlzVsCD/8AJ07H/28Vavggw+s56+/Dm3bWueJHGHaumncOeNOdmTs8JQlRiby4tAXGdlmZDVGJiIiIlK3pOelc9HnF/HL1l+8yq/scCUXt70Yo+SoZhHxCa0BISIiInXX1KnWVEklkw9t28KCBcdOPgB06mSNjjAMuOACaNCgMiOVGmraummM+nyUV/IBYGfGTkZ9Popp66ZVU2QiIiIidcvOjJ0MeH+AV/LBbti5q+ddXNLuEiUfRCqJRkCIiIhI3TRlCowfb02lVGTAAPjqK6hXr/Txpum9zgPADTdYUy+1a1eZkUoN5XK7uHPGnZiYpfaZmBgY3DXjLs5PPl9D/UVEREQq0drUtQz7eBjbM7Z7yoIdwTzY70E6JXSqxshEaj+NgBAREZG6xe2Gf/4Txo3zTj5ccgnMnFl28mH3brj3Xti0ybs8OFjJBzmqOSlzSo18KMnEZHvGduakzKnCqERERETqlt/+/o2+7/X1Sj5EB0XzzBnPKPkgUgWUgBAREZG6Iy8PLrsMXnjBu3z8ePjkEyuhcKTNm61Fptevh+eeg5ycqolVarRDeYd4eeHL5Tp2d+buSo5GREREpG76dM2nnP3R2aTnp3vKGkU04oWzX+DUeqdWY2QidYemYBIREZG64cABa62GOSXuNjcMKxlx111HP++UU6BpU9i40Tr+0CEIDa3kYKWmysjP4KWFL/Hv+f/mUN6hcp3TMEKLl4uIiIj4kmmavDD/Be7+6W6v8taxrXlkwCOEBYZVU2QidY8SECIiIlK7pKRAWpp32e7dcNtt8PffxWVBQfDRRzBq1LHrczjgnntg2jS49tqyR0lInZdVkMWri17l2XnPciD3QLnOMTBIjEykf9P+lRydiIiISO3mcruYkzKH3Zm7aRDWgK/Wf8Uri1/xOqZPYh/+2fufBNgDqilKkbpJCQgRERGpPVJSIDnZmmrpWKKi4LvvoF8/73LThOnToW9f65giCQlwyy2+j1dqvJzCHF5f/DrPzH2GfTn7Su2PC41jX84+DAyvxagNrAXNpwydogWoRURERE7CtHXTuHPGncdce+v8VuczpssYbIZmoxepavqvTkRERGqPtLTjJx8A3n23dPIhIwMefxxefx0mT/ZeoFrkCHnOPF5a+BJJLyVx9093l0o+NIlswlvnvsWO8Tv48pIvaRzZ2Gt/YmQiUy+Zysg2I6sybBEREZFaZdq6aYz6fNQxkw/XdbmO67pep+SDSDXRCAgRERGpe04tY8E5txs2bbKeL10Ka9dC+/ZVG5f4vXxnPu8tf48n5jzBzsydpfY3imjEg/0f5Lou1xHkCAJgZJuRnJ98vmdagIYRDenftL9GPoiIiIicBJfbxZ0z7vQaZXqkiMAIzm15bhVGJSJHUgJCREREao/du0/83OhoGD++eFFqJR+khEJXIe+veJ9JcyaRkp5San98WDwT+k3gxu43EuwovU6I3WZnYLOBVRCpiIiISN3w29+/HXPkA0BmQSZ/7vuTDvEdqigqETmSEhAiIiJS882fb02bNHVq+c9JS7OSDo4S3aEuXeCdd6wFqkUAp9vJR6s+YuLvE9l6aGup/bGhsdzf935u7nEzoQGh1RChiIiISN2SnpfOO8ve4ak/nirX8QfyDlRyRCJyLEpAiIiISM3kdMKXX1qJh4ULK3buihXw7LNwzjkwerT3PiUfBGtI/6drPuWx3x9j04FNpfbHhMRwT597uO202wgPDK+GCEVERETqls0HNvPSwpd4b8V7ZBVklfu8mOCYSoxKRI5HCQgRERGpWQ4dgrffhpdfhu3bT6yO//4XIiLgiy+gc2fooCHZYnGbbr5Y+wWP/v4o69PWl9ofFRTFP3v/kzt73UlkUGQ1RCgiIiJSd5imyZyUOUxeMJmv1399zPUeyhIbGkvbuLaVFJ2IlIcSECIiIlIzbN4ML74I770H2dml9xsG9OsHc+Ycv65zzoHZs6F/f2je3PexSo3jNt18tf4rHvntEdakrim1PyIwgnG9xjGu9ziig6OrPkARERGROqTAVcDnaz9n8oLJLNu9rMxjooOj6digI7NTZh+1nrFdxmK32SsrTBEpByUgRERExH+ZppUomDwZvvnG2j5SaCiMGQN33mlNn5ScDHl5R68zOBguuQQGDoTu3a3EhdRZpmny3cbvePi3h1mxZ0Wp/WEBYdzR8w7+2fuf1A+tX/UBioiIiNQhB3IP8OaSN3ll8SvsytxV5jHNopoxss1I+jXth8PmoE+TPry97G325+73HBMbGsvYLmPp06RPVYUuIkehBISIiIj4n4IC+OwzK/GwfHnZxyQmwu23w/XXQ716xeUbNlgLTIM1UuKzz6zFpbt0scpiY6FpUzjllMp9D+LXTNNkxl8zePi3h1mya0mp/SGOEG7tcSv39r2XuLC4aohQREREpO7YkLaBKQum8MHKD8h15pbab2DQvVF3LmpzEW1i22CUuImoT5M+9Gzckz/3/cmBvAPEBMfQNq6tRj6I+AklIERERMR/7N8Pb74Jr7wCu3eXfUyPHjB+PFx0EQQElN7ftKn1ME3ruG3brITEeedBgwaVG7/4PdM0+WXrLzz868PM3zG/1P4gexA3d7+Z+/rdR0J4QjVEKCIiIlI3mKbJrK2zmLxgMt9v+r7MY4LsQZxx6hlc0PqCY/bN7DY7HeK1rpuIP1ICQkRERKrf+vUwZYq1OHRu6TuesNngwgth3Djo06fsaZNM07vcMKBtW/jrL+v8vXuVgKjjfv/7dx7+7WFmbys9T3CALYAbut3AhH4TaBzZuBqiExEREakb8px5fLL6E6YsnMKqvavKPCYmJIYRrUZwdtLZhAWGVXGEIuJLSkCIiIhI9TBN+Plna5ql6dPLPiYiAsaOtaZaOvXUso/ZuhV++QVWrbLqspcYaj1okLV//Hhr6iWpk+amzOXh3x5m1tZZpfY5bA6u7XwtDw54kKZRTashOhEREZG6ITU7ldcXv85rS14jNTu1zGNa1GvByDYj6Z3YW1MoidQSSkCIiIhI1crLg48/tkY8rFlT9jHNmlmLSl97LURGHru+Tz+FefOs58uXWwtLF0lKgiee0ELTddTCHQt55LdHmLl5Zql9dsPO1Z2u5qEBD3FqvaMkt0RERETkpK1JXcPk+ZP5ePXH5LvyS+23GTZ6Nu7JRW0uolX9VtUQoYhUJiUgREREpGrs3Quvvw6vvQb79pV9TN++1jRLF1zgPZIBrMTF8uXQu7d3+eDBVgLC4YCdO70TEEo81ElLdy3lkd8eKXMuYZth44oOV/CvAf+iZf2W1RCdiIiISO3nNt3M/GsmkxdM5qctP5V5TIgjhCHNhzAieQRxYXFVHKGIVBUlIERERKRyrV5tTY308cdQUFB6v8MBF19sJR569Ci7js8/tx75+fDSS97TMXXrBrfeaiUvIiIq5z1IjbBq7yoe+e0Rvlr/Val9BgaXtr+UR05/hNaxras+OBEREZE6IKcwhw9XfsiUhVNYn7a+zGMahDZgRPIIzmp+FiEBIVUcoYhUNSUgRERExPfcbpgxw0o8/Pxz2cdER8ONN8Jtt0Fi4rHrCw+3kg8Av/7qnYBwOGDoUJ+ELTXT2tS1PPb7Y3zx5xdl7h/VdhSPnP4I7Ru0r+LIREREROqGXZm7eHXRq7y59E325+4v85jWsa0Z2XokPRr10PoOInWIEhAiIiLiOzk58N//Wus7bNhQ9jEtW8Jdd8HVV0NYWHH5wYPw++8wezb8619Qr17xvv794X//s6Zf6t+/Mt+B+CGX28WclDnsztxNw4iG9G/aH7vNzoa0DTz2+2N8uuZTTMxS552ffD6PDnyUzgmdqz5oERERkTpg+e7lTF4wmU/XfEqhu7DUfrthp3eT3lzU5iKS6iVVQ4QiUt2UgBAREZGTt3MnvPoqvPkmHDhQ9jGDBsH48TB8ONhspfd/9501zRJYSYjzzy/eFxFhJTbKOk9qtWnrpnHnjDvZkbHDU5YQnkBy/WTmpMzBbbpLnTO85XAeG/gY3Rt1L7VPRERERE6Oy+3iu43fMXnBZH7f9nuZx4QFhHF20tmMSB5BTEhMFUcoIv5ECQgRERE5cUuXWtMsffYZOJ2l9wcEwOWXWyMeOne2ykwTVq2C1q0hMLD42EGDihMQW7eWrkvJhzpn2rppjPp8VKnRDXuy9rAna0+p44ckDeGxgY/RK7FXVYUoIiIiUmdkFWTxn+X/4cWFL7L54OYyj2kY3pALki9g8KmDCXIEVXGEIuKPlIAQERGRinG54NtvrcTD7NllHxMbCzffDLfcAgkJxeXz5sE778C+fXDffdCvX/G+xES46Sbo1On4a0JIredyu7hzxp1lTq10pEHNBvHYwMfof4qm5xIRERHxte3p23l50cu8tfQt0vPTyzymXVw7RrUZRZeGXbAZunFIRIopASEiIiKWlBRISzv6/uBga0Hpl16CzWXf8UTbtjBuHFxxBYSElN4fHm4lHwBmzfJOQACcc86JxS61gmmabEvfxtyUuXy+9nOvaZeO5oUhLzCu97gqiE5ERESk9jnaWlsAC3csZPKCyUz9cyou01XqXIfNQf8m/RnZZiSnRJ9S1aGLSA2hBISIiIhYyYfkZMjLO7Hzzz7bSjwMGQKFhbBoEfz6K1x8sTXVUpEOHaBBA2jaFM44wzexS43ldDtZuWclc7fPZe72ufyR8ge7MndVqI6E8ITjHyQiIiIipZS11lZiRCL/aP8P5m6fy/wd88s8LyIwguEth3NOy3OIDo6uomhFpKZSAkJERESskQ8VTT4EB8Po0db6Dm3bFpfPnQsvvGA9j4nxTkAYBrz+uvfaD1JnZORnsGDHAv5I+YO52+eycMdCsguzT6rOhhENfRSdiIiISN1xtLW2dmTu4Pn5z5d5TmJkIhcmX8jAZgMJsAdURZgiUgsoASEiIiLWug7llZAAt94KN95ojXYIC/Pe37s3BAVBfj6sW2ctOm0YxfuVfKgTTNMkJT3FGt2QYo1wWJ26GrfpLtf5QfYgTEwKXAVl7jcwSIxMpH9TrfsgIiIiUhEut4s7pt9RrrW2ADrFd+KiNhfRKb4TRsl+vYhIOSgBISIiUte4XLBxIyxZAkuXWo8lS8p37mOPWYtH79gBzzwDGzbAlVfCpZcWHxMcDGPHQsOG1pRL+pFSJzjdTlbtXeVJNvyR8gc7M3eW+/z4sHj6Nu1L3ybWo0vDLny38TtGfT4KwOsHsoHVpqYMneKZo1hEREREypbnzGPlnpUs3b2UpbuW8tu238rVT+vWsBvXdbmOxMjEKohSRGorJSBERERqs6JkQ8lEw/LlkH2C096ce641uiEy0ko+gLWY9CWXeCcahg49+djFrxVNp1SUcFi4cyFZBVnlPr9tXFv6NulLv6b96NukL83rNS91R93INiOZesnU0nMTRyYyZegURrYZ6bP3IyIiIlIb5DnzWLV3FUt3LWXJriUs3b2UtfvW4nQ7K1zXwGYDlXwQkZOmBISIiEht4XYXJxuKRjcsXw5Z5b8oXG5xcdCxI2RkwODBVqLDoW5FbZaSnuJJNszdPpdVe1eVezqlYEcwpzU+zTO6oXeT3sSExJTr3JFtRnJ+8vnMSZnD7szdNIxoSP+m/TXyQUREROq8fGe+lWzYXZxsWJO65oSSDWWJCS5ff01E5Fh0pUBERKQmcrth0ybvaZSWLat4siE4GDp1glNOgc8/r9i5Dz0EISEVO0dqBKfbyeq9qz1TKc3dPtdrBMLxNAhr4Ek29Gvajy4NuxBoP/G1P+w2OwObDTzh80VERERqunxnPqtTV1uJhl1LWbp7KatTV1c42RAaEEqzqGZsObSFPGfeUY+LDY2lbVzbkw1bREQJCBEREb9XlGw4chqlzMyK1RMUBJ07Q7du1qN7d4iIgI8/tpIXFaXkQ62RmZ9pTad0eHTDgh0LTmg6pb5N+tK3aV+S6iVpgUIRERGRE5TvzGdN6hrPqIalu5eyeu9qCt2FFaon1BHKqfVOpWVMS1rVb0WLmBbEh8VjGAbzts/j6blPH/XcsV3GasSpiPiEEhAiIiL+xO2Gv/7ynkZp2bITSzZ06mQlGho3tup1ueDqq+HUU4uP270bFi6E3FxrCiXnMe6gCg6G2NgTe1/iV7anb7eSDYenVFq5d2WFplPq0aiHJ9nQp0mfck+nJCIiIiLeClwFrN672rNA9JLdS3yebChLnyZ9uL/v/by97G325+73lMeGxjK2y1j6NOlzUu9LRKSIEhAiIiLVxe2GzZtLJxsyMipWT2AgtG5tTaMUHw+33grt2kFAgLX/66/hnXes5/36eScg4uOt84OC4O674eKLj/46sbHQtGnFYpNq53K7WJ26mrkpc/lj+x/MTZnL9ozt5T4/LjSOvk370q9JP/o27UvXhl1PajolERERkbqqwFXAmtQ1nimUluxawurU1RS4CipUT4gjhFOjT6Vl/ZYk108mqV4SCeEJFR6B2qdJH3o27smf+/7kQN4BYoJjaBvXViMfRMSnlIAQERGpCiWTDSUfFU02BARAq1bQv3/xVErt2sHEibByJezZYyUYipIP4J002HHEPP42G7z1FsTEgKbM8Tsut4vZ22azOXUzSQ2SGHDKgOP+IMwqyLKmU0opnk4ps6D8I2jaxLbxjG7o26QvLWJaaDolERERkQoqcBWwNnWt1wLRq/auqnCyIdgRbCUbYlqSHFucbLAZNp/EabfZ6RDfwSd1iYiURQkIERERXzNN72TDkiXWyIb09IrVExgIHTtaSYbOneGTTyA8HJKT4YUXvI9t2tRKQACkpECHEj8iWrWCRx+FJk0gLq7069SvX7G4pEpMWzeNO2fc6bX4c2JkIi8OfZGRbUZ6ynZk7PAkG+Zun8uKPSvKPZ1SkD2IHo17eNZv6NOkD/VD1R5EREREKqLQVcjafWu9FoheuXflSSUbiqZR8mWyQUSkOigBISIikpICaWnWc9PEnpVlXegvuuv7WFMPmSZs2VJ6GqVDhyoWQ0AAtGxprcEQHAz/+Af8859WEqLIkiWwdy9s3269bsm70vv0gQYNrCRD8+bedYeFWUkMqTGmrZvGqM9HYWJ6le/M2Mmoz0cxtutYsguz+SPlD1LSU8pdb9F0SkUJh64NuxLkCPJ1+CIiIiI1womMNi10FfLnvj+9FoheuWcl+a78Cr12sCOYZlHNaFW/FS3rt6RFvRY0jGioZIOI1DpKQIiISN2WkmKNKMjLA8AAIo48JjgYNmywLu5v3VqcaCh6VDTZYLNBdDQMGQKDBlnJgfbtITUVbrnFOsZu904+gLV+Q2amlQxxuaxFo4u0b289pMZzuV3cMf2OUskHwFP29rK3y1VX69jWnmRD36Z9aRnTUtMpiYiIiFC+0aZFyYaSC0SfSLIhyB5Es2gr2dAqphVJMUk0imikZIOI1AlKQIiISN2WluZJPhxVXh6MGgV//QUHD1as/oAAazqkovUaMjLgt9+sJMQNN1gJiCING0JUFDRqVPaIi2uuqdhri99xuV3sy9nHrsxdR338fehvDuZVsJ1h/bDt3qg7/Zr2o2+TvvRu0pvY0NhKeBciIiIiNduxRpte9PlFDE0aysG8g6zcu5I853F+KxyhKNlQcholJRtEpC5TAkJEROoe07QSCXv3WqMZymPx4uMf43BYyQa323pERcFXX3mvsbBkCcyebU3xlJtb+vyPPir325Bjc7ldzEmZw+7M3TSMaEj/pv2PO6T+RJmmyYHcA2UnFbKsP3dm7GRP1h5cpssnrxkRGMHgUwd7Rjd0a9hN0ymJiIiIHEVOYQ6p2ansytjFDd/ecMzRpjM2zyhXnUH2IE6JPsWTbGgZ01LJBhGRIygBISIiJ6fk+gllOdb6Cb5UWGjFsXev9UhNPfrz1FRrrYWTYRgQEQGnnGJNm9Stm5V8CA6G11+HH36wjktN9U5AdOgAH35oJSc0FU6lKe8CzsdjmiaZBZnszNh51MRC0aOiiwyerK//8TWDTh10/ANFREREaiHTNDmUd4jU7FT2Zu9lb9Ze7+c5qV5lWQVZJ/V6gfbA4pENMcUjGyrrBhcRkdpCCQgRETlxR6yfUKai9RNOJAmRk3PsRELJP/fvP/H3UR6tWkH//laioXt3ePllaxRFWBjceKN3MmHYMGu9hqZNrURDSUFB1kMqzfEWcJ56yVRGthlJTmHOMadCKnpkF2ZXarx2w05CeAKNIhrRKKIRCeEJfLLmEzLyM8o83sAgMTKRAacMqNS4RERERI6mskaaOt1O0nLSrKRB1l72Zu8t/fzwn6nZqZV6A0hCWAJdG3YluX4ySTFJNI5orGSDiMgJUAJCREROXHnXT0hLsy7Gm6a1YHN5kwpZJ3eXkk998gl07Vq8/Y9/WH+WlVhp1qxKQqosVTl1ka8UugrJLMjkUO4hbvn+lmMOqb906qWEOkLJKCj7Ar8vNQhr4EksNI5o7Hle8hEXGlfq8x2SNIRRn4/yihus5APAlKFT/P7vRERERGqnio40zXPmlR6dUPT8iATD/pz9ZfbjqsPtp91Oh/gO1R2GiEiNpwSEiEh18Zepi06EywXZ2bBvX/mOv+IKK5mQmgoFVTtNDQEB1iM01BrB0KABxMdbj02bYNYsWLWq4vUOH+77WP2Ar6YuOh636Sa7IJvMgkwy8jPIzM8ksyDz+H8eZV++K7/cr+10O086+RATEuOdSAgvnVhICE8gwB5wQvWPbDOSqZdMLfPvYsrQKT79uxAREZGqUxNv9ChimiafrvmUK6ZdUSpJsCNjBxd9fhFDmg8hLDDMK9mQWZBZpXHaDBuRQZFEBUURFRRFvZB61AuuR72QekQHRRMRFMFLC1/iUP6ho9YRGxpL27i2VRe0iEgtVqcTEAcOHODLL79k3bp1jBs3jiZNmlR3SJXO5XYxe9tsNqduJqlBEgNOGVBjOjty2OGL1i63i+V7lpOWnUZsWCxdErpYf5f+fNG6pBLvY9nuZew4sIPEmES6Nuxas97HiarsqYvAGm2Qk2MlCooeWVnHf16e4/LLf7EXgPXrT+w9HE1sbHEiITwcVq+2pjXq0gUuv7w4wdCgATz4IOzaBZGR8Oab3lMlbdpkreEwbpxv46uhjjd10ccjP+aM5mecdLIgsyDzpOfgrSwRgRGlEglHjlxoGNGQYEdwpccyss1Izk8+X/9ui/hQXez/S+1Qky9al1TXf49W1Y0eha5CsguzyS7IJrswm6yCrPI9P3zOsZ4fb3TCj1t+9Nn7KCnIHkREUATRQdFEB1uPosRC0XZUUBTRwdGEB4ZjHGettZu638TTc58+6v6xXcbWqbYpIlKZDNM0/WNsWxWbMWMG999/P5GRkRQUFJCRkcH111/PuMMXodatW8cTTzzBmjVriImJ4ZprruGqq67ynJ+cnMxTTz3FyJEn1klwuVysWLGCzp07Y7dXwT9qKSnMWvw5z817jr1ZqZ7i+PAG3NPnHgb3uKR2X+ytLarionVVqC3v42QsXWqtI3A8Tz1lXUivaMIgK8tKPtQURaMUHA5rTYUhQ7xHKqxbB3/8YSUbHnkETjut+NysLJg2zVoQunlz6NTJu27TPPZizykpuFq2wF5QeNRDXIEB2Df9VSXt0W26KXQVUuAqoMBVQKG7+Hl5HyXPP+bDXXx8vjOfn7b8VKGRBDXZqDaj6JnY0zuxEN6QiKCI6g6tFNM0SU9PJyoq6rg/pkWOpsr7nn6ozvX/0cXe2qKqLlpXttryPk7U0W70KJpe8d9D/k2vxF7HTwIUHj+ZUJnrIvhSWEAYUUFRRAZHehIJMcExRIcUJxOKHpVx88e87fN4e9nb7M8tXksuNjSWsV3G0qdJH5+/nkh5mKZJdk42YaFh6vvXAjsydtAwvCEXtLmgSl/X3/r+dXIERG5uLhMmTODqq6+mT58+LFq0iKSkJMaNG8egQYM45ZRTGDNmDIMHD+axxx5jxYoVPPbYY4SFhXHRRRdVd/gVd/ji2uCCQgaX2pkKL9yDK/CBKru4JiehovPt+6uTeR+mCU4nFBZaU/kUFpb9qOp9+fnFx7hcpfcVnet0Wg+Xq3yf1YQJJ/YZ+5vTT4dGjWDJEmukQvfucM01xQmG6Gj47DMraRIVBUd815p5ebgxcQXYcZtuXAXZ1p+mC5fNhfuiYbhMl1WWvr34udtVfFyJ50X7XKaLQnchd/0zAmP/gaOG74wJ5ea93+Pc7Sx9sb+CCYLjHe90Oyv376KGCbQHEhEYQURQBBGBEUQGRXqelywv+jMsMIzxM8d7/ZAsqWgB509HfaqLcCJ1SJ3r/6OLvbXF8UYnTr1kao34+/Tl+zBN0+rDuQopdBeW+rPo5opK23fE/qL+XVnnevp+zgJSc1KPuUbV+B/Hn/wH7Sfqh9SnUUQjz7RHRcmFqODipEJkYOQJT1XpK32a9KFn456s3beWPel7SIhKoF1cO/URRUR8rE4mIDZv3kxOTg4jRowg7fD868OGDWP//v1ER0fz+eefExAQwMSJE3E4HCQlJbFt2zbeeuutGvkDxJW695h39gLYCwqZvfhLsnNaYphYF3k9g2NM723TLHWMcbjcdLs9pximWeYxnm0TTNNt1VcUSIlzDLN0WcltTwxFMUGpY471+mXFeLS6rXh9WLen3jJeq+i4Up8JhGzfzRH3dpdp7ZtPkNcwFlxuDNON4TbBbWK4XdbzojKXG8PtxjBNDJcbDj/HbWK4XNZzl9t67naDGwzDLD7X5cLmdGK4DsdoM0qc78ZWWIjN6QK3iWm3Wa9jmjgycogrx/vIO70fxuHP3uZ0WQ+XuxxnSkW5DcgPtJMX7MBpNwjLKcRlN9gfHcSu+FByg+3kBtrIC7LTcf1BDLdJZpiDFS0jufbb7cetf2TPv1nfaBfh7QrIDMwnx/ELrqU/lZ0c2OvG9cRor0RBpS9EFwQ0OtYB6dzywy2VG0MtYTNsZSYGjpU0ONafgfbACscQHhiuBZxFxEtd6//XhIvWpmliYnr+PLIM8NpfVpmv6qnMustTz9Hqdrqd3PTdTce8aH3TdzcRYAvAMAzcptvrBgzPtnnEtg/3H/NcrG2n28lX67865vu47MvL6NCgA06387jJgEJXod8sUlwbOGwOAu2BBNmDCHYEE+wIJsgeREhACEGOIEIcIYQ4Qgh2BJOel84vf/9y3DrH9xpfYxZvttvsdGjQgebhzXXHuYhIJamTCYjY2FgMw2DBggW0aNECAMMwGD16NABLlizhtNNOw+Eo/nh69erFm2++SVpaGrGxsV717du3j9GjR9OwYUNef/11goMrf17oili+ZznlmOiFAaNqzx0XdV27t6ZVdwg+EZyVW90h+J08O2QHQlYguIF6eVBoh7+jYEuMVZ4dYB3TcwcU2CE1DKa3LC7PDoBmhyAmFzKC4KfmkBoOGC7ARUgBJGZY5x4McZIRnO0dRO/ip112pXNtOeL++9A21oUe3tAN/lXOwCDIEUSgPfCoj9zCXNalrTtuXeN7jad7o+5HTRqEBoRW+w83LeAsIkeqS/1/l9vFnTPuPObF3ou/uJjYkFgwqPIEgPjWvpx9jPh0RHWHcdIKXAUs3b20usPwWwYGgfZAKzngCPJKFhQ9ipIEoQGhBDmO2G8vfl6UVCg6xmEr/2Uhl9vFir0rjjrSFLR4s4iIlFYnExAJCQmMGTOGSZMm0aZNGxITE9m+fbtnEbo9e/bQqlUrr3MaNGgAwO7du71+gBw4cIBrrrmGxo0b89prrxEUFFShWEyzuGNeWfZl76vU+kVqGzfWhf78ACi0WRf4XUB0PrgM6yL/nojifYU2aJgFgU5w2WBFgnXxvmhfVD40ygCnHTbGwO4IiMuG2xcfP5Ybh1uJhUPBsLoB5Je4GdxwW6Nv3LaKv8eFx1hzMzcQNsUefX9JaaGQ64CQYyQVch3WcbVN0d1iR3sE2AKOvd8eUO5jvR4273OP9wiwBZTrbn+X28WpL53KzoydZV4gKpq66Jkznzluff6wvNSFrS9kRKsR1oKdWbtpGF68YKc/xFcRRX2Fmha3+Je63n78qf+flpaGzVb8j3dQUBARERG4XC4OHjxY6vii1z506BBOp/c/uBEREQQFBZGXl0dWVhYAc1PmsmP3DrADwYAJHLEslBs3qa5UsAF5WB2dkgKBAKybBo5cGsgGhBx+fsQ9CnD4Ne2HzzuyfxBwuG7X4dctyQCK+gs5h+Muq94C4MjB3Q6s0Yxl1QsQdvjPXKyOXklBh88vPFx3SUWfofvwuUcKPRy3rz/DkMPHHOszPF69vvwMS/7dHOszLKteX3yGx/q7KaN9A8WfYVn1luMztBk2jFwDO3Zshs162Gw4QhzYHXaMAgO7246Bgd2wY7fZsQfaCQwJxOa2QT5WuWGdn+PMYUPuBus1jvEZDjtlGI2DG3v1F8OCwwgLD8N0m+Rmlv4Qw6KtBp6bmYv7iNHiQcFBOAIdFOYXUpBZQEGJD9LmsBESHoJpmuSkl/4QQyJDsNls5GXn4Sos/hDPjD+TzzZ9dtT2fVbSWWw+uBmA7EOlG3hweDB2h538nHycBd4N3BHkICgkCJfTRV6Wd0M0bAahkVZDzMnIwXR7N3BPvbn5OPOPqDfQQVBo2fWC9Rnm5eZh7jNLf4ahJT7DXO+GaA+wExwWjNvtJjej9N9NaJR1Y05uVi5up3e9gSGBBAQF4Cxwkp/j/SHa7DZCIqz/mMv6DEMiQrDZS//dAAQEBxAYHIiz0El+tne9lfYZGhAWFXbUeoPCgnAEOCjIK6Awz/tLwhefYVl/NyfavqH8n2F2enap71lfte/cnFyvmxvK9Rm63BX/jjhG+z6Zz/Bk2re/fkdAxT9De4AdM9CkQWgD9u0rfW22fv36GIZBeno6hYXef6/h4eEEBweTn59PZmamd7wOB9HR0QCekb0l1atXr1RZdauTCQiA++67j8GDB/P+++8za9YsZs6cyXnnncczzzxDXl4egYHeUz4U/bDIzy/+D+fQoUNcc801NGrUiFdffbXUOeWRkZHh9QOkMoQZYcc/SOosZ4kblU0gz2Fd0HYb1sMwIdBl7csNsB5F+1xATJ71vMAO+0OL97kNiMiD4MPn7oqAAodVHlYAvXYeP7Z5jWFvOGyM9b7YH51n1VFoh831IDOoeJ9hWhf3Cw5f9E4NK95XaIfwfCtJkOuAfUfscxrgtGH98CiHoulciu72Lrld1r6SZR12FHL74uMPBfizWSjrTgnBho2ow/XaDJunXpths2o2jOLnR24bhiemkud7nh9xvPX/svcdef6h+EMk37aM2GOsd50WCkkdBtIvvCE2w4bdsGMYxT/WisqKftwVPff8aTvKPpsNGzavOkrWXXRuybpLHle0342b6364jrTc0v9wF/3dxYfFM/uy2QQHBHsSADajcr+7T5jbepiFJvmH/1deT/Z/kqu/vxoDo8ypi57o/wRZmVm+jrhSdanXhS71ugDUuNiLmKZJzuFF5at7dInUXG63pjD0l/7/559/jqvEWlDNmzdnwIABZGRkMG1a6VGs11xzDQA//PBDqR+v/fv3JykpiXXr1rFw4UIAlu1dBuuASKAVVoetrAFunbD6PDuAQ0fsSwQSgAxgyxH7QoGim5vXU/oidzusi7+7gSP/aU04XHc2sPGIfYFAx8PP/6L0BedWh99TKrDniH2xQLPD5xz5Xg2g2+HnWyl9sbo5EAPsx/osSooGWnD0z7Az1i/qFKzPqqSmQAMg/fDrlhQGtDn8vKx622NdXN8JHLlEVaPDj2xg0xH7goCiWW82Ujp50RoIB/YefpQUB5yCdcG+REyGYYAdHF0d2Awb7r/dkFfctzUMg4BWATjCHLgOuHDtcHntc8Q4MJIM9mfsL/u9dsX6O9oGCe4EQgNDPf202NaxRCdGk7cnjwPrD3j6f3bDTli9MJI6JWGYBht/2ejV17MZNroM6EJIaAhbl28lfXe6V/8wKTmJU1ufyqG9h1i7cC02bJ5+YWRkJAOHDcQwDGZOm4nL6X1Rre/AvkTVi2LN0jWkbE6xCk3ADc2aN6Nt57YcTDvI/Fnzvc5zBDjYH7Lf6m/+RenER0uIS4hjaOhQtqzbcrhakwIKiG0aS8deHcnOyub3Wb+X+gh7XdILgHlL53HowCGvfZ1O60Tj+Mb8velv/lz+p9e+2PhYOpzegcKCQn76+adS9Z55/pkEBgWyZO0SDuwqbogJJHBDkxuYlj6NtJ1pnu+I8MBwTm9yOi0OtKBDN6shTv9leqmLgP3P7k9EVASrN68mdUuq177mrZvTumNr9qfuZ+HihV77gkOC6XleTwBm/TGLvFzvi4Q9B/akfr36rN++ni3rvb+4mjRvQofuHchMz2TO4jle+wybQa+LepEXnMeSOUvIOOT9H3OX3l1oGN+QLRu2sH7leq99DRo1oEO/DhTkF/DzLz+X+gy7XdCNgMAAFq1axIG93v8xt+3SlmYJzdj5905WLl7ptS86JpoOZ1qf4Q8//VCq3tOHn05YeBgrNqxgX4r3vwst27WkZbuW7Nuzj8WLve94Cw0Ppedw6zP8afZPFOZ7X/DsPbg39erV489tf/L3xr+99jVNakr7bu1JP5jO3MVzvfbZHXZ6jbTa4eyFs8nK8O5zd+vbjfgG8Wxet5kNqzd47UtITKBDnw7k5eQx65dZpd5rj4t6YLfbWbBiAQf2eX+G7bu3p2lCU1K2pLBmyRqvfTFxMXQY1AGXy8XMn2eWqnfwuYMJDg1m2bpl7Nvh/Rkmd0gmqU0Se3fuZeli75FZ4ZHh9BxqfYYzfy3jO+Ksw98RW0p8RxzWrFWJ74jF3t8RAUEB9Dzfqve3eb+RfiidHEcORXNz9xjQg7h6cWxau4lNa72//Bs1bUSHXh385jsCoHWn1jRPbs7u7btZvni5177IepGcdtZpQA36jhhlfYZ/LPmDjIMV+47o0a8HYUYYH3/8MUe6/PLLCQwM5Mcff2TXrl3e8fbsSZs2bdi8eTNz5njHFBcXxznnnANQZr0jR44kPDy8VHl1Msw6fjvUwoULWbhwIa1bt+buu+/mnnvu4fPPP2fAgAHcc889nuP++usvzjnnHP7v//6Ptm3bkpycTGBgIIWFhYwcOZInn3yyQq9btBp5p06dKn01cteSxThO63nc4/aOuQRnwwTsh9IxTBPTbsdVLwoMw/Ow5eZh5OVjGuAOD8cMCrT2Abjd2LOyAAMzKBB3WBimYV3MxDCwZWZZ6wgYNqte8NRrFBRCnvUrwwwN9tRrGAam6caWnQuGgRngwAwJsZ4frtvIy7fWKDBsuMLDwGYU1+1yYRQ6rZgCAzADAjBshidmIy8f02aA3YbpuXvt8H7n4TUQDOtcbLbi91q03oVhgN2OYbd7xYTLbcVhs3mfV/RZcsS2YWAWXVMq+kyKElNF+wyDgPWbaHLNHcf9u0yZ+h6FHdtZr223g2HzxGLabVa8JeIqurhY5MgLXMfbX9E67MtX0nDQucd9H/t+n4G7a2fPD5iS9Xhd2C9vAsCHx52s8v536Vy0EHv3Hj55zcpQ3rvmt9yxxa/n3J+2bhoXf3ExUPaaAV9c/EWdmbZn2rpp3DXzLq+pi5pENmHy2ZPrzGfgb0zTJD09naioKCUg5IS5XC5WrlxJ586dK73v6e+qu/+fmJhY6SMgLvzswuPeIX5+5/NpWq8pBTkFuJ1u7wvKRXd/FjgpzC0svpHBMKw7F8NDrDtS0607LUvuDwm37swtzCvEWeAs7kNhEBgcSFBIEG6Xm7ysvOIbJTAwbAZhUWEYGNYdnEU5s8M3RoRGhOJwOKw7Fw/XW/SdGBgYaN396XSTl53neb2i/RHREVa8h+9cLNmvCwkLITAokIK8AgpyC7zeiz3Abt15bppkp2eX6i9GRkdiGAY5WTnWZ1iizxgSGkJQcBDOAic52TneF+UdDsIjwzEMg4wDGaXqjYiKwOFwkJmRybX/dy37c0pMd3PE3ftxYXH8b+T/cNgcBDgCqFevHjbDRmZ6Jph43YARFRVFUGAQuTm5FOYXel2wDw0JJTIiErfLTUZ6htcNL4ZhUL9+fQAOHjzolUADiIyMJDAwkJycHE/CvEhgYCBh4WE0m9KMnXvLuAMp1Kq/UUAjlly3xKu/WHT3Z8n27fkYAgKIiorCNE327y89HVBMTAw2m42MjAwKCryzWaGhoYSGhlJQUEBGhveFJLvd7rlzdP/+/aVGj0VHR+NwOMjKyiIvz/viVkhICGFhYRQWFpKenu61z2az8dve37j4i4sxc80yR0BMvWwqQ08ZWuoz9PV3RJGT+QzDwsIIDArkl02/8Hfq38SHxdMrsRd2m/24d+aezGcYExMDWCPRjkysR0VFERAQQHZ2Nrm53neBBwcHEx4ejtPp5NChQ6Viql+/Punp6dYC50e076LPMDc3l+xs77u1AwMDiYyMxO12c+DAkdnCyr272W63k5mZ6ZUkh/K3b19+hif7HXGyn2Ft+Y4o2b4PHjxIZGSk53v4WJ+hv35HhISEnFD79sfviPJ8hv72HQH4Vd+/TiYg9u7dy9KlSxk+fDgLFy5k0aJF3H777dx222243W4KCwuJjo7mueee85wzb948xowZw7x586hfvz7JyckMHDiQiy66iNtvv513332Xfv36lTuGoh8gVdIQli2Dbt2Of9zSpdC1a+XGIientvxd1pb3cTJSUnC1bHHMBeJdgQHYN/0FTZtWYWAVV7TQJZR98d4fFrosj2nrppVaM6BJZJM6uWaAy+2ypi7K3E3DiOKpi6R6KAEhvlClfU8/VJf6/y63i2YvNjvuzQFb79yq7/YaoDb1s2rD+zhZ6m/6J/W1xJ+oPYov+Fvf30/nj6hcixYtYty4cWzd6j0WNi0tjejoaHr06MHSpUu9srYLFizg1FNP9WR1Ac4++2yGDBnC8OHD+de//lUqWyjic7GxcLxFDoODreP8WW15HyejaVPsm/5i1tTnGDa+AV1vwPMYPj6eWVOfqxHJByhe8LdxZGOv8sTIxBr1Y3Jkm5H8feffzLpqFm8PfZtZV81i651ba0z8vmS32RnYbCCXdbiMgc0G6gKViNR4dan/b7fZeXHoi0AZI1QPb08ZOkXf7TVEbepn1Yb3cbKK+pu/Xv0r/xv5P369+tc6298UEZG6o06OgMjOzubss8+mcePGXHjhhWzatImIiAjefPNNPv74Y0455RSGDRvG4MGDGTt2LKtWreLRRx/lscce48ILLwQgOTmZp556ipEjR5KWlsbw4cMZOnQoEydOLFcMVZqJSkmB5GTIK72QikdwMGzYUCMudtZ5KSmQlobL7WL5nuWkZacRGxZLl4Qu1g/J2Nia8fdY4n0s272MHQd2kBiTSNeGXWvW+/CB2nK3eW15H7rjRPyN2qT4gr/dBVXV6lz/H91pXdvUln6Wy+1i9rbZbE7dTFKDJAacMqBGvg+pXdTXEn+i9ii+4G99/zqZgADYuHEjkyZNYtmyZQAkJSVxxx13cMYZZwCwatUqnnjiCf7880/i4uK49tprufLKKz3nl/wBAjB16lQefPBB3n//fXr37n3c16/yhnD4Yi9YX2ZZWVmEh4cXf5nVoYu94n/0D6z4E7VH8Tdqk+IL/vYjpDrUuf4/utgr/kn/rom/UZsUf6L2KL7gb33/OpuAKLJgwQIWL17M7bffXqWvW50NQV9m4m/UJsWfqD2Kv1GbFF/wtx8h1amu9f/1HSL+Rm1S/I3apPgTtUfxBX/r+zuqO4DqlpiYqP+gRURERETqCPX/RURERESqjhIQiYkkJiZWdxgiIiIiIlIF1P8XEREREak6tuoOQEREREREREREREREah8lIERERERERERERERExOeUgBAREREREREREREREZ9TAkJERERERERERERERHxOCQgREREREREREREREfE5JSBERERERERERERERMTnlIAQERERERERERERERGfUwJCRERERERERERERER8TgkIERERERERERERERHxOSUgRERERERERERERETE55SAEBERERERERERERERn1MCQkREREREREREREREfM5R3QHUVaZpAuByuarltd1uNy6XC8Mwqvz1RY6kNin+RO1R/I3apPhCUZ+zqA8qVa+6+v/6DhF/ozYp/kZtUvyJ2qP4gr/1/ZWAqCZutxuA1atXV3MkIiIiIlJXFPVBpeqp/y8iIiIiVclf+v6G6S+pkDrG7XbjdDqx2WzKaIqIiIhIpSq6m87hcGCzaRbW6qD+v4iIiIhUBX/r+ysBISIiIiIiIiIiIiIiPlf9KRAREREREREREREREal1lIAQERERERERERERERGfUwJCRERERERERERERER8TgkIERERERERERERERHxOSUgRERERERERERERETE55SAEBERERERERERERERn1MCQkREREREREREREREfM5R3QGIf3nuuef4/fffMU2TSy+9lKuuuqq6Q5I67vnnn+fXX3/FZrNx8803M3z48OoOSQSAO+64g06dOnHddddVdyhSx1111VUcPHgQm826r+S9996jfv361RyViNQU6v+Lv1H/X/yR+v7iL9T3l5pICQjx+O2339iwYQNff/01+fn5jBo1ir59+5KUlFTdoUkdtWDBAtasWcO3335LRkYGw4cP58wzzyQwMLC6Q5M67ptvvmHBggV06tSpukOROs40TXbu3MnPP/+MYRjVHY6I1DDq/4u/Uf9f/JH6/uIv1PeXmkpTMIlHw4YNGTduHHa7ndDQUJo2bcrevXurOyypw3r16sU777yDzWYjNTWVwMBA7HZ7dYclddzevXv59NNP+cc//lHdoYiwZcsWXC4XV199NRdeeCE//vhjdYckIjWI+v/ib9T/F3+jvr/4E/X9pabSCAjxSE5O9jxfuXIla9asoWPHjtUYkQg4HA6eeuopPv74Y2666Sb9AJFq98gjj/DAAw/w66+/VncoImRkZNCrVy8effRRDh48yBVXXEGbNm1o0qRJdYcmIjWA+v/ij9T/F3+ivr/4E/X9pabSCAgpZcWKFdx2220899xzhIeHV3c4IkyYMIE//viDmTNnsmTJkuoOR+qwTz75hDZt2tC+ffvqDkUEgC5duvD0008THBxMw4YNGTx4MAsWLKjusESkhlH/X/yN+v/iD9T3F3+jvr/UVBoBIV7mzp3Lfffdx3PPPUfv3r2rOxyp47Zu3UpBQQHJyclER0fTr18/Nm7cSPfu3as7NKmjfvzxR9LS0pg1axZpaWnYbDYiIyO5+OKLqzs0qaOWLl1KYWEhvXr18pQ5HOreiUj5qf8v/kT9f/En6vuLv1HfX2oqjYAQj5SUFO69915ef/11/fgQv5CSksLEiRNxOp1kZWUxd+5cOnfuXN1hSR32n//8h2+//Zavv/6af/zjH1xzzTX6ASLVKisri3//+98UFBRw4MABfvvtN/r06VPdYYlIDaH+v/gb9f/Fn6jvL/5GfX+pqZQmE4933nmHgoICHnroIU/Z3XffTf/+/asxKqnLTj/9dJYtW8aIESOw2+1ceeWVtG3btrrDEhHxG0XfkxdccAFut5vx48cTHx9f3WGJSA2h/r/4G/X/RUSOTn1/qakM0zTN6g5CfO/NN9/kjz/+4MMPP/SUud1uXnnlFb744gsyMzPp0aMHDz/8sBarkSqhNin+Rm1S/I3apIicDH2HiL9RmxR/ovYo/kZtUuoSTcFUC3388cdMmTKlVPlrr73G//73Px5//HE+/fRT3G43Y8eOpaCgoOqDlDpFbVL8jdqk+Bu1SRE5GfoOEX+jNin+RO1R/I3apNQ1SkDUInv37uWmm27i+eefp1mzZl77CgoKeO+997jjjjsYOHAgrVu3ZvLkyezZs4cff/yxegKWWk9tUvyN2qT4G7VJETkZ+g4Rf6M2Kf5E7VH8jdqk1FVKQNQia9euJSAggG+++YZOnTp57Vu/fj3Z2dlei8tFRkbStm1bFi9eXNWhSh2hNin+Rm1S/I3apIicDH2HiL9RmxR/ovYo/kZtUuoqLUJdiwwePJjBgweXuW/Pnj0ANGzY0Ku8QYMGnn0ivqY2Kf5GbVL8jdqkiJwMfYeIv1GbFH+i9ij+Rm1S6iqNgKgjcnNzAQgMDPQqDwoKIj8/vzpCkjpObVL8jdqk+Bu1SRE5GfoOEX+jNin+RO1R/I3apNRmSkDUEcHBwQClFq7Jz88nJCSkOkKSOk5tUvyN2qT4G7VJETkZ+g4Rf6M2Kf5E7VH8jdqk1GZKQNQRRUO4UlNTvcpTU1OJj4+vjpCkjlObFH+jNin+Rm1SRE6GvkPE36hNij9RexR/ozYptZkSEHVE69atCQ8PZ+HChZ6yjIwM/vzzT3r06FGNkUldpTYp/kZtUvyN2qSInAx9h4i/UZsUf6L2KP5GbVJqMy1CXUcEBgZy5ZVX8vzzzxMTE0Pjxo157rnnSEhIYMiQIdUdntRBapPib9Qmxd+oTYrIydB3iPgbtUnxJ2qP4m/UJqU2UwKiDrnjjjtwOp089NBD5OXl0aNHD959910CAgKqOzSpo9Qmxd+oTYq/UZsUkZOh7xDxN2qT4k/UHsXfqE1KbWWYpmlWdxAiIiIiIiIiIiIiIlK7aA0IERERERERERERERHxOSUgRERERERERERERETE55SAEBERERERERERERERn1MCQkREREREREREREREfE4JCBERERERERERERER8TklIERERERERERERERExOeUgBAREREREREREREREZ9TAkJERERERERERERERHxOCQgREalUgwcPJjk5mXnz5nmVT5s2jeTkZC677LJqikxERERERHxN/X8RESlJCQgREREREREREREREfE5JSBERERERERERERERMTnlIAQERG/8NNPP3HRRRfRtWtXunbtysUXX8xvv/3mdczPP//MiBEjaN++PaeffjqTJ0/G6XR69icnJ5OcnMyHH35Ir169OOOMM8jJySlX3SIiIiIiUnXU/xcRqRuUgBARkWr3119/ceedd7JhwwY6dOhAmzZtWL16NbfeeiubNm0C4Pfff+e2225jy5YtdO/eHbvdzhtvvMHEiRNL1ffcc8/Rpk0bOnTowK5du45bt4iIiIiIVB31/0VE6g5HdQcgIiJ1m2EYpKSk4HK5aNeuHf/+97+JjY3l22+/xeVyERkZCcAbb7yBaZo8++yzDB8+nPz8fIYOHcrUqVO58847qV+/vqfOO+64g7FjxwIwa9as49YtIiIiIiJVQ/1/EZG6RSMgRESkUgUEBADgdru9you27XY7vXr1okOHDqxatYp+/fpxzjnnsGLFCpo1a0Z8fDwAf/75JwDjxo0jOTmZjh07smvXLlwuF6tXr/aq+7TTTvM8L0/dIiIiIiLiG+r/i4hISRoBISIilSo8PByArKwsr/Lc3FwAQkNDCQ0N5ZNPPmH27NnMmTOH5cuX8/HHH/PRRx8xceJELr30UgICAsjLy6NXr16EhYV51RUSElLmaxbVf7y6RURERETEN9T/FxGRkjQCQkREKlVSUhIAX331FS6XC7Dufvr9998BOPXUU/n999+ZMGECGzdu5NFHH+Xrr79m3LhxAJ7F4lq1agXAueeey2uvvcbkyZOJj4+nW7dutGnTxus17Xa753l56hYREREREd9Q/19ERErSCAgREalUV111FdOnT+fXX3/lrLPOonnz5vz9999s376d4OBgLrnkEnJycpg5cyYFBQXMmjWLiIgIli5dCkCfPn0AGDt2LEuXLuXhhx/mm2++YefOnezcuZP27dszZsyYo75+/fr1j1u3iIiIiIj4hvr/IiJSkmGaplndQYiISO22atUqXnnlFVauXElWVhbh4eF06dKF22+/nXbt2gGwePFiXn31Vf78808KCwtp3Lgxl156KaNHj/bU88MPP/DWW2+xefNmwsLCGDhwIPfeey8xMTEAJCcnA/Djjz9yyimneM4rT90iIiIiIuIb6v+LiEgRJSBERERERERERERERMTntAaEiIiIiIiIiIiIiIj4nBIQIiIiIiIiIiIiIiLic0pAiIiIiIiIiIiIiIiIzykBISIiIiIiIiIiIiIiPqcEhIiIiIiIiIiIiIiI+JwSECIiIiIiIiIiIiIi4nNKQIiIiIiIiIiIiIiIiM8pASEiIiIiIiIiIiIiIj6nBISIiIiIiIiIiIiIiPicEhAiIiIiIiIiIiIiIuJzSkCIiIiIiIiIiIiIiIjPKQEhIiIiIiIiIiIiIiI+9//mI13cCzAhugAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "📈 Charts generated. The visual story: edge scales profitably, cloud bleeds at scale.\n"
     ]
    }
   ],
   "execution_count": 6
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Cost Breakdown at 100k Users\n",
    "\n",
    "**Where does the money actually go?**"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-08T16:57:35.657827Z",
     "start_time": "2025-11-08T16:57:35.565153Z"
    }
   },
   "source": [
    "TARGET_USERS = 100_000\n",
    "\n",
    "edge_detail = calculate_edge_economics(TARGET_USERS)\n",
    "cloud_detail = calculate_cloud_economics(TARGET_USERS)\n",
    "\n",
    "# Create pie charts\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 6))\n",
    "\n",
    "# Edge breakdown\n",
    "edge_costs = {\n",
    "    'App Store (30%)': edge_detail['app_store'],\n",
    "    'Support': edge_detail['support'],\n",
    "    'CDN': edge_detail['cdn'],\n",
    "    'Engineering': edge_detail['engineering'],\n",
    "    'One-time (amortized)': edge_detail['one_time']\n",
    "}\n",
    "edge_costs = {k: v for k, v in edge_costs.items() if v > 0}  # Remove zero costs\n",
    "\n",
    "colors1 = ['#ff6b6b', '#4ecdc4', '#45b7d1', '#96ceb4', '#ffeaa7']\n",
    "ax1.pie(edge_costs.values(), labels=edge_costs.keys(), autopct='%1.1f%%',\n",
    "        colors=colors1[:len(edge_costs)], startangle=90)\n",
    "ax1.set_title(f'Edge Cost Breakdown @ {TARGET_USERS:,} Users\\nTotal: ${edge_detail[\"total_costs\"]:,.0f}/month\\nProfit: ${edge_detail[\"profit\"]:,.0f}/month ({edge_detail[\"margin\"]:.1f}%)', \n",
    "              fontweight='bold', fontsize=13)\n",
    "\n",
    "# Cloud breakdown\n",
    "cloud_costs = {\n",
    "    'App Store (30%)': cloud_detail['app_store'],\n",
    "    'Support': cloud_detail['support'],\n",
    "    'Infrastructure': cloud_detail['infrastructure'],\n",
    "    'Storage': cloud_detail['storage'],\n",
    "    'Bandwidth': cloud_detail['bandwidth'],\n",
    "    'Inference': cloud_detail['inference']\n",
    "}\n",
    "\n",
    "colors2 = ['#ff6b6b', '#4ecdc4', '#45b7d1', '#96ceb4', '#ffeaa7', '#d63031']\n",
    "ax2.pie(cloud_costs.values(), labels=cloud_costs.keys(), autopct='%1.1f%%',\n",
    "        colors=colors2, startangle=90)\n",
    "ax2.set_title(f'Cloud Cost Breakdown @ {TARGET_USERS:,} Users\\nTotal: ${cloud_detail[\"total_costs\"]:,.0f}/month\\nLoss: ${cloud_detail[\"profit\"]:,.0f}/month ({cloud_detail[\"margin\"]:.1f}%)',\n",
    "              fontweight='bold', fontsize=13)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# Print detailed comparison\n",
    "print(f\"\\n💰 AT {TARGET_USERS:,} USERS:\")\n",
    "print(\"=\"*70)\n",
    "print(f\"\\nEdge:\")\n",
    "print(f\"  Inference costs: ${edge_detail['inference']:,.0f}/month (0.0% of costs)\")\n",
    "print(f\"  Total costs: ${edge_detail['total_costs']:,.0f}/month\")\n",
    "print(f\"  Profit: ${edge_detail['profit']:,.0f}/month ({edge_detail['margin']:.1f}% margin)\")\n",
    "\n",
    "print(f\"\\nCloud:\")\n",
    "print(f\"  Inference costs: ${cloud_detail['inference']:,.0f}/month ({cloud_detail['inference']/cloud_detail['total_costs']*100:.1f}% of costs)\")\n",
    "print(f\"  Total costs: ${cloud_detail['total_costs']:,.0f}/month\")\n",
    "print(f\"  Loss: ${cloud_detail['profit']:,.0f}/month ({cloud_detail['margin']:.1f}% margin)\")\n",
    "\n",
    "print(f\"\\nCompetitive Advantage:\")\n",
    "print(f\"  Monthly advantage: ${edge_detail['profit'] - cloud_detail['profit']:,.0f}\")\n",
    "print(f\"  Annual advantage: ${(edge_detail['profit'] - cloud_detail['profit']) * 12:,.0f}\")\n",
    "print(f\"  Cost advantage: ${cloud_detail['total_costs'] - edge_detail['total_costs']:,.0f}/month\")"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x600 with 2 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "💰 AT 100,000 USERS:\n",
      "======================================================================\n",
      "\n",
      "Edge:\n",
      "  Inference costs: $0/month (0.0% of costs)\n",
      "  Total costs: $612,292/month\n",
      "  Profit: $1,237,708/month (66.9% margin)\n",
      "\n",
      "Cloud:\n",
      "  Inference costs: $4,200,000/month (82.5% of costs)\n",
      "  Total costs: $5,090,000/month\n",
      "  Loss: $-3,240,000/month (-175.1% margin)\n",
      "\n",
      "Competitive Advantage:\n",
      "  Monthly advantage: $4,477,708\n",
      "  Annual advantage: $53,732,500\n",
      "  Cost advantage: $4,477,708/month\n"
     ]
    }
   ],
   "execution_count": 7
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7. Scenario Testing\n",
    "\n",
    "**What if the assumptions change?**\n",
    "\n",
    "Let's stress-test the thesis with different scenarios."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-08T16:57:39.054318Z",
     "start_time": "2025-11-08T16:57:39.047225Z"
    }
   },
   "source": [
    "def run_scenario(name: str, modifications: dict, target_users: int = 100_000) -> dict:\n",
    "    \"\"\"\n",
    "    Run a scenario with modified parameters.\n",
    "    \n",
    "    modifications: dict of parameter changes like {'INFERENCE_PER_VIDEO': 0.35}\n",
    "    \"\"\"\n",
    "    # Save original values\n",
    "    original = {}\n",
    "    for key, value in modifications.items():\n",
    "        original[key] = globals()[key]\n",
    "        globals()[key] = value\n",
    "    \n",
    "    # Calculate economics\n",
    "    edge = calculate_edge_economics(target_users)\n",
    "    cloud = calculate_cloud_economics(target_users)\n",
    "    edge_ltv_temp = calculate_ltv_metrics('edge')\n",
    "    cloud_ltv_temp = calculate_ltv_metrics('cloud')\n",
    "    \n",
    "    result = {\n",
    "        'Scenario': name,\n",
    "        'Edge_Profit': edge['profit'],\n",
    "        'Cloud_Profit': cloud['profit'],\n",
    "        'Gap': edge['profit'] - cloud['profit'],\n",
    "        'Edge_Margin': edge['margin'],\n",
    "        'Cloud_Margin': cloud['margin'],\n",
    "        'Edge_LTV_CAC': edge_ltv_temp['ltv_cac'],\n",
    "        'Cloud_LTV_CAC': cloud_ltv_temp['ltv_cac']\n",
    "    }\n",
    "    \n",
    "    # Restore original values\n",
    "    for key, value in original.items():\n",
    "        globals()[key] = value\n",
    "    \n",
    "    return result\n",
    "\n",
    "\n",
    "# Define scenarios\n",
    "scenarios = [\n",
    "    ('Baseline (Current)', {}),\n",
    "    ('Inference -90%', {'INFERENCE_PER_VIDEO': 0.35}),\n",
    "    ('Inference -97% (near zero)', {'INFERENCE_PER_VIDEO': 0.10}),\n",
    "    ('Power Users (20 vids/mo)', {'VIDEOS_PER_USER_MONTHLY': 20}),\n",
    "    ('Light Users (5 vids/mo)', {'VIDEOS_PER_USER_MONTHLY': 5}),\n",
    "    ('Premium Pricing ($30)', {'MONTHLY_PRICE': 30.0}),\n",
    "    ('Budget Pricing ($12)', {'MONTHLY_PRICE': 12.0}),\n",
    "    ('High CAC Market ($150)', {'CAC': 150}),\n",
    "    ('Low Churn (3%)', {'MONTHLY_CHURN': 0.03}),\n",
    "]\n",
    "\n",
    "# Run all scenarios\n",
    "scenario_results = []\n",
    "for name, mods in scenarios:\n",
    "    scenario_results.append(run_scenario(name, mods))\n",
    "\n",
    "scenario_df = pd.DataFrame(scenario_results)\n",
    "\n",
    "print(\"\\n🔬 SCENARIO ANALYSIS @ 100,000 USERS\")\n",
    "print(\"=\"*100)\n",
    "display(scenario_df.style.format({\n",
    "    'Edge_Profit': '${:,.0f}',\n",
    "    'Cloud_Profit': '${:,.0f}',\n",
    "    'Gap': '${:,.0f}',\n",
    "    'Edge_Margin': '{:.1f}%',\n",
    "    'Cloud_Margin': '{:.1f}%',\n",
    "    'Edge_LTV_CAC': '{:.2f}x',\n",
    "    'Cloud_LTV_CAC': '{:.2f}x'\n",
    "}).background_gradient(subset=['Gap'], cmap='Greens'))"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🔬 SCENARIO ANALYSIS @ 100,000 USERS\n",
      "====================================================================================================\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x12b97b390>"
      ],
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_da3b8_row0_col3, #T_da3b8_row5_col3, #T_da3b8_row6_col3, #T_da3b8_row7_col3, #T_da3b8_row8_col3 {\n",
       "  background-color: #4eb264;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_da3b8_row1_col3 {\n",
       "  background-color: #f1faee;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_da3b8_row2_col3 {\n",
       "  background-color: #f7fcf5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_da3b8_row3_col3 {\n",
       "  background-color: #00441b;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_da3b8_row4_col3 {\n",
       "  background-color: #cbeac4;\n",
       "  color: #000000;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_da3b8\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_da3b8_level0_col0\" class=\"col_heading level0 col0\" >Scenario</th>\n",
       "      <th id=\"T_da3b8_level0_col1\" class=\"col_heading level0 col1\" >Edge_Profit</th>\n",
       "      <th id=\"T_da3b8_level0_col2\" class=\"col_heading level0 col2\" >Cloud_Profit</th>\n",
       "      <th id=\"T_da3b8_level0_col3\" class=\"col_heading level0 col3\" >Gap</th>\n",
       "      <th id=\"T_da3b8_level0_col4\" class=\"col_heading level0 col4\" >Edge_Margin</th>\n",
       "      <th id=\"T_da3b8_level0_col5\" class=\"col_heading level0 col5\" >Cloud_Margin</th>\n",
       "      <th id=\"T_da3b8_level0_col6\" class=\"col_heading level0 col6\" >Edge_LTV_CAC</th>\n",
       "      <th id=\"T_da3b8_level0_col7\" class=\"col_heading level0 col7\" >Cloud_LTV_CAC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_da3b8_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
       "      <td id=\"T_da3b8_row0_col0\" class=\"data row0 col0\" >Baseline (Current)</td>\n",
       "      <td id=\"T_da3b8_row0_col1\" class=\"data row0 col1\" >$1,237,708</td>\n",
       "      <td id=\"T_da3b8_row0_col2\" class=\"data row0 col2\" >$-3,240,000</td>\n",
       "      <td id=\"T_da3b8_row0_col3\" class=\"data row0 col3\" >$4,477,708</td>\n",
       "      <td id=\"T_da3b8_row0_col4\" class=\"data row0 col4\" >66.9%</td>\n",
       "      <td id=\"T_da3b8_row0_col5\" class=\"data row0 col5\" >-175.1%</td>\n",
       "      <td id=\"T_da3b8_row0_col6\" class=\"data row0 col6\" >3.42x</td>\n",
       "      <td id=\"T_da3b8_row0_col7\" class=\"data row0 col7\" >-7.83x</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_da3b8_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
       "      <td id=\"T_da3b8_row1_col0\" class=\"data row1 col0\" >Inference -90%</td>\n",
       "      <td id=\"T_da3b8_row1_col1\" class=\"data row1 col1\" >$1,237,708</td>\n",
       "      <td id=\"T_da3b8_row1_col2\" class=\"data row1 col2\" >$540,000</td>\n",
       "      <td id=\"T_da3b8_row1_col3\" class=\"data row1 col3\" >$697,708</td>\n",
       "      <td id=\"T_da3b8_row1_col4\" class=\"data row1 col4\" >66.9%</td>\n",
       "      <td id=\"T_da3b8_row1_col5\" class=\"data row1 col5\" >29.2%</td>\n",
       "      <td id=\"T_da3b8_row1_col6\" class=\"data row1 col6\" >3.42x</td>\n",
       "      <td id=\"T_da3b8_row1_col7\" class=\"data row1 col7\" >1.62x</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_da3b8_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
       "      <td id=\"T_da3b8_row2_col0\" class=\"data row2 col0\" >Inference -97% (near zero)</td>\n",
       "      <td id=\"T_da3b8_row2_col1\" class=\"data row2 col1\" >$1,237,708</td>\n",
       "      <td id=\"T_da3b8_row2_col2\" class=\"data row2 col2\" >$840,000</td>\n",
       "      <td id=\"T_da3b8_row2_col3\" class=\"data row2 col3\" >$397,708</td>\n",
       "      <td id=\"T_da3b8_row2_col4\" class=\"data row2 col4\" >66.9%</td>\n",
       "      <td id=\"T_da3b8_row2_col5\" class=\"data row2 col5\" >45.4%</td>\n",
       "      <td id=\"T_da3b8_row2_col6\" class=\"data row2 col6\" >3.42x</td>\n",
       "      <td id=\"T_da3b8_row2_col7\" class=\"data row2 col7\" >2.38x</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_da3b8_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
       "      <td id=\"T_da3b8_row3_col0\" class=\"data row3 col0\" >Power Users (20 vids/mo)</td>\n",
       "      <td id=\"T_da3b8_row3_col1\" class=\"data row3 col1\" >$1,237,708</td>\n",
       "      <td id=\"T_da3b8_row3_col2\" class=\"data row3 col2\" >$-6,040,000</td>\n",
       "      <td id=\"T_da3b8_row3_col3\" class=\"data row3 col3\" >$7,277,708</td>\n",
       "      <td id=\"T_da3b8_row3_col4\" class=\"data row3 col4\" >66.9%</td>\n",
       "      <td id=\"T_da3b8_row3_col5\" class=\"data row3 col5\" >-326.5%</td>\n",
       "      <td id=\"T_da3b8_row3_col6\" class=\"data row3 col6\" >3.42x</td>\n",
       "      <td id=\"T_da3b8_row3_col7\" class=\"data row3 col7\" >-14.82x</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_da3b8_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
       "      <td id=\"T_da3b8_row4_col0\" class=\"data row4 col0\" >Light Users (5 vids/mo)</td>\n",
       "      <td id=\"T_da3b8_row4_col1\" class=\"data row4 col1\" >$1,237,708</td>\n",
       "      <td id=\"T_da3b8_row4_col2\" class=\"data row4 col2\" >$-790,000</td>\n",
       "      <td id=\"T_da3b8_row4_col3\" class=\"data row4 col3\" >$2,027,708</td>\n",
       "      <td id=\"T_da3b8_row4_col4\" class=\"data row4 col4\" >66.9%</td>\n",
       "      <td id=\"T_da3b8_row4_col5\" class=\"data row4 col5\" >-42.7%</td>\n",
       "      <td id=\"T_da3b8_row4_col6\" class=\"data row4 col6\" >3.42x</td>\n",
       "      <td id=\"T_da3b8_row4_col7\" class=\"data row4 col7\" >-1.70x</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_da3b8_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
       "      <td id=\"T_da3b8_row5_col0\" class=\"data row5 col0\" >Premium Pricing ($30)</td>\n",
       "      <td id=\"T_da3b8_row5_col1\" class=\"data row5 col1\" >$1,885,208</td>\n",
       "      <td id=\"T_da3b8_row5_col2\" class=\"data row5 col2\" >$-2,592,500</td>\n",
       "      <td id=\"T_da3b8_row5_col3\" class=\"data row5 col3\" >$4,477,708</td>\n",
       "      <td id=\"T_da3b8_row5_col4\" class=\"data row5 col4\" >67.9%</td>\n",
       "      <td id=\"T_da3b8_row5_col5\" class=\"data row5 col5\" >-93.4%</td>\n",
       "      <td id=\"T_da3b8_row5_col6\" class=\"data row5 col6\" >5.17x</td>\n",
       "      <td id=\"T_da3b8_row5_col7\" class=\"data row5 col7\" >-6.07x</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_da3b8_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
       "      <td id=\"T_da3b8_row6_col0\" class=\"data row6 col0\" >Budget Pricing ($12)</td>\n",
       "      <td id=\"T_da3b8_row6_col1\" class=\"data row6 col1\" >$719,708</td>\n",
       "      <td id=\"T_da3b8_row6_col2\" class=\"data row6 col2\" >$-3,758,000</td>\n",
       "      <td id=\"T_da3b8_row6_col3\" class=\"data row6 col3\" >$4,477,708</td>\n",
       "      <td id=\"T_da3b8_row6_col4\" class=\"data row6 col4\" >64.8%</td>\n",
       "      <td id=\"T_da3b8_row6_col5\" class=\"data row6 col5\" >-338.6%</td>\n",
       "      <td id=\"T_da3b8_row6_col6\" class=\"data row6 col6\" >2.02x</td>\n",
       "      <td id=\"T_da3b8_row6_col7\" class=\"data row6 col7\" >-9.22x</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_da3b8_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
       "      <td id=\"T_da3b8_row7_col0\" class=\"data row7 col0\" >High CAC Market ($150)</td>\n",
       "      <td id=\"T_da3b8_row7_col1\" class=\"data row7 col1\" >$1,237,708</td>\n",
       "      <td id=\"T_da3b8_row7_col2\" class=\"data row7 col2\" >$-3,240,000</td>\n",
       "      <td id=\"T_da3b8_row7_col3\" class=\"data row7 col3\" >$4,477,708</td>\n",
       "      <td id=\"T_da3b8_row7_col4\" class=\"data row7 col4\" >66.9%</td>\n",
       "      <td id=\"T_da3b8_row7_col5\" class=\"data row7 col5\" >-175.1%</td>\n",
       "      <td id=\"T_da3b8_row7_col6\" class=\"data row7 col6\" >1.83x</td>\n",
       "      <td id=\"T_da3b8_row7_col7\" class=\"data row7 col7\" >-4.17x</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_da3b8_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
       "      <td id=\"T_da3b8_row8_col0\" class=\"data row8 col0\" >Low Churn (3%)</td>\n",
       "      <td id=\"T_da3b8_row8_col1\" class=\"data row8 col1\" >$1,237,708</td>\n",
       "      <td id=\"T_da3b8_row8_col2\" class=\"data row8 col2\" >$-3,240,000</td>\n",
       "      <td id=\"T_da3b8_row8_col3\" class=\"data row8 col3\" >$4,477,708</td>\n",
       "      <td id=\"T_da3b8_row8_col4\" class=\"data row8 col4\" >66.9%</td>\n",
       "      <td id=\"T_da3b8_row8_col5\" class=\"data row8 col5\" >-175.1%</td>\n",
       "      <td id=\"T_da3b8_row8_col6\" class=\"data row8 col6\" >5.70x</td>\n",
       "      <td id=\"T_da3b8_row8_col7\" class=\"data row8 col7\" >-13.04x</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 8
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-08T16:57:41.713202Z",
     "start_time": "2025-11-08T16:57:41.568334Z"
    }
   },
   "source": [
    "# Visualize scenario comparison\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 6))\n",
    "\n",
    "# Plot 1: Profit comparison\n",
    "x = np.arange(len(scenario_df))\n",
    "width = 0.35\n",
    "\n",
    "ax1.bar(x - width/2, scenario_df['Edge_Profit'], width, label='Edge', color='green', alpha=0.7)\n",
    "ax1.bar(x + width/2, scenario_df['Cloud_Profit'], width, label='Cloud', color='red', alpha=0.7)\n",
    "ax1.axhline(y=0, color='black', linestyle='--', alpha=0.4)\n",
    "ax1.set_ylabel('Monthly Profit ($)', fontweight='bold')\n",
    "ax1.set_title('Profit Across Scenarios (100k users)', fontweight='bold', fontsize=13)\n",
    "ax1.set_xticks(x)\n",
    "ax1.set_xticklabels(scenario_df['Scenario'], rotation=45, ha='right')\n",
    "ax1.legend()\n",
    "ax1.grid(True, alpha=0.3, axis='y')\n",
    "ax1.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: f'${x/1e6:.1f}M' if abs(x) >= 1e6 else f'${x/1e3:.0f}k'))\n",
    "\n",
    "# Plot 2: LTV/CAC comparison\n",
    "ax2.bar(x - width/2, scenario_df['Edge_LTV_CAC'], width, label='Edge', color='green', alpha=0.7)\n",
    "ax2.bar(x + width/2, scenario_df['Cloud_LTV_CAC'], width, label='Cloud', color='red', alpha=0.7)\n",
    "ax2.axhline(y=3, color='orange', linestyle=':', label='Healthy (3x)', alpha=0.6)\n",
    "ax2.axhline(y=0, color='black', linestyle='--', alpha=0.4)\n",
    "ax2.set_ylabel('LTV/CAC Ratio', fontweight='bold')\n",
    "ax2.set_title('Unit Economics: LTV/CAC Across Scenarios', fontweight='bold', fontsize=13)\n",
    "ax2.set_xticks(x)\n",
    "ax2.set_xticklabels(scenario_df['Scenario'], rotation=45, ha='right')\n",
    "ax2.legend()\n",
    "ax2.grid(True, alpha=0.3, axis='y')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x600 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 9
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8. Key Insights & Summary\n",
    "\n",
    "**What do the numbers tell us?**"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-08T16:57:57.800414Z",
     "start_time": "2025-11-08T16:57:57.795111Z"
    }
   },
   "source": [
    "# Get baseline scenario for summary\n",
    "baseline = scenario_df[scenario_df['Scenario'] == 'Baseline (Current)'].iloc[0]\n",
    "cheap_inference = scenario_df[scenario_df['Scenario'] == 'Inference -90%'].iloc[0]\n",
    "power_users = scenario_df[scenario_df['Scenario'] == 'Power Users (20 vids/mo)'].iloc[0]\n",
    "\n",
    "summary_md = f\"\"\"\n",
    "## 🎯 EXECUTIVE SUMMARY\n",
    "\n",
    "### At 100,000 Users:\n",
    "\n",
    "**Edge Deployment:**\n",
    "- Monthly Profit: ${baseline['Edge_Profit']:,.0f}\n",
    "- Margin: {baseline['Edge_Margin']:.1f}%\n",
    "- LTV/CAC: {baseline['Edge_LTV_CAC']:.2f}x (healthy)\n",
    "- Break-even: ~{edge_breakeven:,} users\n",
    "\n",
    "**Cloud Deployment:**\n",
    "- Monthly Loss: ${baseline['Cloud_Profit']:,.0f}\n",
    "- Margin: {baseline['Cloud_Margin']:.1f}%\n",
    "- LTV/CAC: {baseline['Cloud_LTV_CAC']:.2f}x (unprofitable)\n",
    "- Break-even: Never\n",
    "\n",
    "**Competitive Advantage:**\n",
    "- Monthly advantage: ${baseline['Gap']:,.0f}\n",
    "- Annual advantage: ${baseline['Gap'] * 12:,.0f}\n",
    "- Edge profitable while cloud burns cash\n",
    "\n",
    "---\n",
    "\n",
    "### Key Findings:\n",
    "\n",
    "**1. Inference Cost Sensitivity**\n",
    "   - Even with 90% cheaper inference, cloud still loses ${abs(cheap_inference['Cloud_Profit']):,.0f}/month\n",
    "   - Edge advantage shrinks but remains: ${cheap_inference['Gap']:,.0f}/month\n",
    "   - Cloud needs inference at <$0.10/video to break even (97% reduction)\n",
    "\n",
    "**2. Usage Pattern Impact**\n",
    "   - Power users (20 vids/month): Gap widens to ${power_users['Gap']:,.0f}/month\n",
    "   - Cloud loses ${abs(power_users['Cloud_Profit']):,.0f}/month\n",
    "   - More usage = worse cloud economics (anti-SaaS dynamic)\n",
    "\n",
    "**3. Cost Structure**\n",
    "   - Edge inference costs: 0% of total costs\n",
    "   - Cloud inference costs: {cloud_detail['inference']/cloud_detail['total_costs']*100:.1f}% of total costs\n",
    "   - Cloud's biggest cost line item is inference\n",
    "\n",
    "**4. Unit Economics**\n",
    "   - Edge: ${edge_ltv['monthly_contribution']:.2f} contribution per user/month\n",
    "   - Cloud: ${cloud_ltv['monthly_contribution']:.2f} contribution per user/month\n",
    "   - Edge can profitably acquire customers, cloud cannot\n",
    "\n",
    "**5. Strategic Window**\n",
    "   - Edge profitable from day 1 at scale\n",
    "   - Cloud needs continuous funding to cover losses\n",
    "   - 18-24 month window before big tech potentially copies\n",
    "\n",
    "---\n",
    "\n",
    "### The Bottom Line:\n",
    "\n",
    "**Edge deployment isn't just more efficient—it's the only viable business model for multimodal AI applications at scale.**\n",
    "\n",
    "Cloud competitors either:\n",
    "1. Charge 2-3x more (pricing problem)\n",
    "2. Limit usage heavily (product problem)\n",
    "3. Raise funding perpetually (business model problem)\n",
    "\n",
    "You can:\n",
    "1. Price aggressively for market capture\n",
    "2. Encourage unlimited usage\n",
    "3. Be profitable and fund growth organically\n",
    "\n",
    "Different game. Different economics. Different opportunities in the gaps.\n",
    "\"\"\"\n",
    "\n",
    "display(Markdown(summary_md))"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ],
      "text/markdown": "\n## 🎯 EXECUTIVE SUMMARY\n\n### At 100,000 Users:\n\n**Edge Deployment:**\n- Monthly Profit: $1,237,708\n- Margin: 66.9%\n- LTV/CAC: 3.42x (healthy)\n- Break-even: ~2,500 users\n\n**Cloud Deployment:**\n- Monthly Loss: $-3,240,000\n- Margin: -175.1%\n- LTV/CAC: -7.83x (unprofitable)\n- Break-even: Never\n\n**Competitive Advantage:**\n- Monthly advantage: $4,477,708\n- Annual advantage: $53,732,500\n- Edge profitable while cloud burns cash\n\n---\n\n### Key Findings:\n\n**1. Inference Cost Sensitivity**\n   - Even with 90% cheaper inference, cloud still loses $540,000/month\n   - Edge advantage shrinks but remains: $697,708/month\n   - Cloud needs inference at <$0.10/video to break even (97% reduction)\n\n**2. Usage Pattern Impact**\n   - Power users (20 vids/month): Gap widens to $7,277,708/month\n   - Cloud loses $6,040,000/month\n   - More usage = worse cloud economics (anti-SaaS dynamic)\n\n**3. Cost Structure**\n   - Edge inference costs: 0% of total costs\n   - Cloud inference costs: 82.5% of total costs\n   - Cloud's biggest cost line item is inference\n\n**4. Unit Economics**\n   - Edge: $13.69 contribution per user/month\n   - Cloud: $-31.30 contribution per user/month\n   - Edge can profitably acquire customers, cloud cannot\n\n**5. Strategic Window**\n   - Edge profitable from day 1 at scale\n   - Cloud needs continuous funding to cover losses\n   - 18-24 month window before big tech potentially copies\n\n---\n\n### The Bottom Line:\n\n**Edge deployment isn't just more efficient—it's the only viable business model for multimodal AI applications at scale.**\n\nCloud competitors either:\n1. Charge 2-3x more (pricing problem)\n2. Limit usage heavily (product problem)\n3. Raise funding perpetually (business model problem)\n\nYou can:\n1. Price aggressively for market capture\n2. Encourage unlimited usage\n3. Be profitable and fund growth organically\n\nDifferent game. Different economics. Different opportunities in the gaps.\n"
     },
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     "output_type": "display_data",
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      "display_id": null
     }
    }
   ],
   "execution_count": 10
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 9. Build Your Own Scenario\n",
    "\n",
    "**Want to test your own assumptions?**\n",
    "\n",
    "Modify the parameters in the cell below and run it."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-08T17:00:20.053371Z",
     "start_time": "2025-11-08T17:00:20.044593Z"
    }
   },
   "source": [
    "# ============================================================================\n",
    "# CUSTOM SCENARIO - Modify these and run\n",
    "# ============================================================================\n",
    "\n",
    "CUSTOM_MONTHLY_PRICE = 20.0\n",
    "CUSTOM_INFERENCE_PER_VIDEO = 3.50\n",
    "CUSTOM_VIDEOS_PER_USER = 12\n",
    "CUSTOM_CAC = 80\n",
    "CUSTOM_TARGET_USERS = 100_000\n",
    "\n",
    "# Run custom analysis\n",
    "custom_result = run_scenario(\n",
    "    'Custom',\n",
    "    {\n",
    "        'MONTHLY_PRICE': CUSTOM_MONTHLY_PRICE,\n",
    "        'INFERENCE_PER_VIDEO': CUSTOM_INFERENCE_PER_VIDEO,\n",
    "        'VIDEOS_PER_USER_MONTHLY': CUSTOM_VIDEOS_PER_USER,\n",
    "        'CAC': CUSTOM_CAC\n",
    "    },\n",
    "    CUSTOM_TARGET_USERS\n",
    ")\n",
    "\n",
    "print(f\"\\n🎯 YOUR CUSTOM SCENARIO @ {CUSTOM_TARGET_USERS:,} users:\")\n",
    "print(\"=\"*70)\n",
    "print(f\"\\nParameters:\")\n",
    "print(f\"  Price: ${CUSTOM_MONTHLY_PRICE}/month\")\n",
    "print(f\"  Inference: ${CUSTOM_INFERENCE_PER_VIDEO}/video\")\n",
    "print(f\"  Usage: {CUSTOM_VIDEOS_PER_USER} videos/user/month\")\n",
    "print(f\"  CAC: ${CUSTOM_CAC}\")\n",
    "print(f\"\\nResults:\")\n",
    "print(f\"  Edge Profit: ${custom_result['Edge_Profit']:,.0f}/month ({custom_result['Edge_Margin']:.1f}% margin)\")\n",
    "print(f\"  Cloud Profit: ${custom_result['Cloud_Profit']:,.0f}/month ({custom_result['Cloud_Margin']:.1f}% margin)\")\n",
    "print(f\"  Monthly Advantage: ${custom_result['Gap']:,.0f}\")\n",
    "print(f\"  Annual Advantage: ${custom_result['Gap'] * 12:,.0f}\")\n",
    "print(f\"\\nUnit Economics:\")\n",
    "print(f\"  Edge LTV/CAC: {custom_result['Edge_LTV_CAC']:.2f}x\")\n",
    "print(f\"  Cloud LTV/CAC: {custom_result['Cloud_LTV_CAC']:.2f}x\")\n",
    "print(f\"\\n{'✅ Edge model works' if custom_result['Edge_LTV_CAC'] > 3 else '⚠️ Edge needs optimization'}\")\n",
    "print(f\"{'❌ Cloud model unprofitable' if custom_result['Cloud_LTV_CAC'] < 1 else '⚠️ Cloud marginally viable'}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🎯 YOUR CUSTOM SCENARIO @ 100,000 users:\n",
      "======================================================================\n",
      "\n",
      "Parameters:\n",
      "  Price: $20.0/month\n",
      "  Inference: $3.5/video\n",
      "  Usage: 12 videos/user/month\n",
      "  CAC: $80\n",
      "\n",
      "Results:\n",
      "  Edge Profit: $1,237,708/month (66.9% margin)\n",
      "  Cloud Profit: $-3,240,000/month (-175.1% margin)\n",
      "  Monthly Advantage: $4,477,708\n",
      "  Annual Advantage: $53,732,500\n",
      "\n",
      "Unit Economics:\n",
      "  Edge LTV/CAC: 3.42x\n",
      "  Cloud LTV/CAC: -7.83x\n",
      "\n",
      "✅ Edge model works\n",
      "❌ Cloud model unprofitable\n"
     ]
    }
   ],
   "execution_count": 12
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 10. Export Results\n",
    "\n",
    "Save your analysis for sharing or further work."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-08T17:00:20.961784Z",
     "start_time": "2025-11-08T17:00:20.953960Z"
    }
   },
   "source": [
    "# Export to CSV\n",
    "df.to_csv('unit_economics_full_analysis.csv', index=False)\n",
    "scenario_df.to_csv('unit_economics_scenarios.csv', index=False)\n",
    "ltv_comparison.to_csv('unit_economics_ltv_cac.csv')\n",
    "\n",
    "print(\"✅ Data exported:\")\n",
    "print(\"   - unit_economics_full_analysis.csv\")\n",
    "print(\"   - unit_economics_scenarios.csv\")\n",
    "print(\"   - unit_economics_ltv_cac.csv\")\n",
    "print(\"\\nYou can now share these files or use them in presentations.\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ Data exported:\n",
      "   - unit_economics_full_analysis.csv\n",
      "   - unit_economics_scenarios.csv\n",
      "   - unit_economics_ltv_cac.csv\n",
      "\n",
      "You can now share these files or use them in presentations.\n"
     ]
    }
   ],
   "execution_count": 13
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "## Next Steps\n",
    "\n",
    "1. **Modify parameters** in Section 1 to match your specific assumptions\n",
    "2. **Re-run all cells** to see how numbers change\n",
    "3. **Test scenarios** to stress-test your thesis\n",
    "4. **Export results** to share with team/investors\n",
    "\n",
    "**Key takeaway:** The numbers show edge deployment isn't just more efficient—it's the only economically viable model for multimodal AI applications at scale. Cloud competitors will burn cash while you're profitable.\n",
    "\n",
    "That's your 18-24 month window."
   ]
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": ""
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