{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "872b2545",
   "metadata": {},
   "source": [
    "# Compliments Reference DB — Pipeline Visualization\n",
    "\n",
    "This notebook visualizes every phase output, explains each table and field.\n",
    "\n",
    "**Source:** [saraNour/compliments-brand](https://huggingface.co/datasets/saraNour/compliments-brand)\n",
    "**DB:** [saraNour/compliments-reference-db](https://huggingface.co/datasets/saraNour/compliments-reference-db)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "79e1ddf7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:09.549020Z",
     "iopub.status.busy": "2026-08-01T17:42:09.546220Z",
     "iopub.status.idle": "2026-08-01T17:42:13.226243Z",
     "shell.execute_reply": "2026-08-01T17:42:13.224915Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import json\n",
    "from huggingface_hub import hf_hub_download\n",
    "\n",
    "plt.style.use('seaborn-v0_8-whitegrid')\n",
    "COLORS = ['#2ecc71', '#3498db', '#e74c3c', '#f39c12', '#9b59b6', '#1abc9c', '#e67e22', '#34495e']\n",
    "\n",
    "def load(name, repo=\"saraNour/compliments-reference-db\"):\n",
    "    path = hf_hub_download(repo, name, repo_type=\"dataset\")\n",
    "    if name.endswith('.csv'):\n",
    "        return pd.read_csv(path)\n",
    "    return pd.read_parquet(path)\n",
    "\n",
    "def show_table(df, title, n=5):\n",
    "    print(f\"\\n{'='*60}\")\n",
    "    print(f\"  {title}\")\n",
    "    print(f\"  Shape: {df.shape[0]} rows × {df.shape[1]} columns\")\n",
    "    print(f\"{'='*60}\")\n",
    "    display(df.head(n))\n",
    "    print(f\"\\nColumns ({len(df.columns)}):\")\n",
    "    for col in df.columns:\n",
    "        dtype = df[col].dtype\n",
    "        nulls = df[col].isna().sum()\n",
    "        try:\n",
    "            uniques = df[col].nunique()\n",
    "        except Exception:\n",
    "            uniques = 'N/A'\n",
    "        print(f\"  {col:35s} {str(dtype):10s} nulls={nulls:5d}  uniques={uniques}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8baada68",
   "metadata": {},
   "source": [
    "---\n",
    "# Phase 1 — Data Quality Foundation\n",
    "\n",
    "**Goal:** Download authoritative products.parquet, validate schema, clean, produce reproducible foundation.\n",
    "\n",
    "**Input:** `products.parquet` (4,440 × 16)\n",
    "**Output:** `phase1_output.parquet` (4,440 × 14)\n",
    "\n",
    "### What Happens\n",
    "1. Schema validation (16 expected columns)\n",
    "2. Audit: nulls, duplicates, UPC patterns, brands\n",
    "3. Clean: whitespace → trim, empty → null, brand/title cleaning\n",
    "4. Drop 100% null columns: `size_per_unit`, `size_total`\n",
    "5. Output + validation + statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1bfcbb78",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:13.249272Z",
     "iopub.status.busy": "2026-08-01T17:42:13.248466Z",
     "iopub.status.idle": "2026-08-01T17:42:13.837643Z",
     "shell.execute_reply": "2026-08-01T17:42:13.833919Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "  Phase 1 Output — phase1_output.parquet\n",
      "  Shape: 4440 rows × 16 columns\n",
      "============================================================\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>upc</th>\n",
       "      <th>external_id</th>\n",
       "      <th>brand</th>\n",
       "      <th>brand_clean</th>\n",
       "      <th>title</th>\n",
       "      <th>title_clean</th>\n",
       "      <th>price</th>\n",
       "      <th>price_currency</th>\n",
       "      <th>size</th>\n",
       "      <th>size_amount</th>\n",
       "      <th>size_unit</th>\n",
       "      <th>size_qty</th>\n",
       "      <th>size_unit_norm</th>\n",
       "      <th>image_url</th>\n",
       "      <th>source</th>\n",
       "      <th>source_url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>055742522167</td>\n",
       "      <td>297608EA</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments Cold And Sinus Plus 20 Count</td>\n",
       "      <td>Compliments Cold And Sinus Plus 20 Count</td>\n",
       "      <td>9.99</td>\n",
       "      <td>CAD</td>\n",
       "      <td>20 per pack</td>\n",
       "      <td>20.000</td>\n",
       "      <td>count</td>\n",
       "      <td>1</td>\n",
       "      <td>count</td>\n",
       "      <td>https://voila.ca/images-v3/2d92d19c-0354-49c0-...</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-cold-and...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>055742335200</td>\n",
       "      <td>464324EA</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments Twister T2 Light Bulbs 23W Soft Wh...</td>\n",
       "      <td>Compliments Twister T2 Light Bulbs 23W Soft Wh...</td>\n",
       "      <td>11.99</td>\n",
       "      <td>CAD</td>\n",
       "      <td>2 per pack</td>\n",
       "      <td>2.000</td>\n",
       "      <td>count</td>\n",
       "      <td>1</td>\n",
       "      <td>count</td>\n",
       "      <td>https://voila.ca/images-v3/2d92d19c-0354-49c0-...</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-twister-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>990002600400</td>\n",
       "      <td>144288CS</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments Zero Calorie Soft Drink 12 x 355ml</td>\n",
       "      <td>Compliments Zero Calorie Soft Drink 12 x 355ml</td>\n",
       "      <td>5.49</td>\n",
       "      <td>CAD</td>\n",
       "      <td>12 x 29.583ml</td>\n",
       "      <td>29.583</td>\n",
       "      <td>ml</td>\n",
       "      <td>12</td>\n",
       "      <td>ml</td>\n",
       "      <td>https://voila.ca/images-v3/2d92d19c-0354-49c0-...</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-zero-cal...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>055742569391</td>\n",
       "      <td>312204EA</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments Kalamata Whole Olives 375 ml</td>\n",
       "      <td>Compliments Kalamata Whole Olives 375 ml</td>\n",
       "      <td>3.29</td>\n",
       "      <td>CAD</td>\n",
       "      <td>375ml</td>\n",
       "      <td>375.000</td>\n",
       "      <td>ml</td>\n",
       "      <td>1</td>\n",
       "      <td>ml</td>\n",
       "      <td>https://voila.ca/images-v3/2d92d19c-0354-49c0-...</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-kalamata...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>055742561111</td>\n",
       "      <td>259928EA</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments Sliced Almonds 250 g</td>\n",
       "      <td>Compliments Sliced Almonds 250 g</td>\n",
       "      <td>7.99</td>\n",
       "      <td>CAD</td>\n",
       "      <td>250g</td>\n",
       "      <td>250.000</td>\n",
       "      <td>g</td>\n",
       "      <td>1</td>\n",
       "      <td>g</td>\n",
       "      <td>https://voila.ca/images-v3/2d92d19c-0354-49c0-...</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-sliced-a...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            upc external_id        brand  brand_clean  \\\n",
       "0  055742522167    297608EA  Compliments  Compliments   \n",
       "1  055742335200    464324EA  Compliments  Compliments   \n",
       "2  990002600400    144288CS  Compliments  Compliments   \n",
       "3  055742569391    312204EA  Compliments  Compliments   \n",
       "4  055742561111    259928EA  Compliments  Compliments   \n",
       "\n",
       "                                               title  \\\n",
       "0           Compliments Cold And Sinus Plus 20 Count   \n",
       "1  Compliments Twister T2 Light Bulbs 23W Soft Wh...   \n",
       "2     Compliments Zero Calorie Soft Drink 12 x 355ml   \n",
       "3           Compliments Kalamata Whole Olives 375 ml   \n",
       "4                   Compliments Sliced Almonds 250 g   \n",
       "\n",
       "                                         title_clean  price price_currency  \\\n",
       "0           Compliments Cold And Sinus Plus 20 Count   9.99            CAD   \n",
       "1  Compliments Twister T2 Light Bulbs 23W Soft Wh...  11.99            CAD   \n",
       "2     Compliments Zero Calorie Soft Drink 12 x 355ml   5.49            CAD   \n",
       "3           Compliments Kalamata Whole Olives 375 ml   3.29            CAD   \n",
       "4                   Compliments Sliced Almonds 250 g   7.99            CAD   \n",
       "\n",
       "            size  size_amount size_unit  size_qty size_unit_norm  \\\n",
       "0    20 per pack       20.000     count         1          count   \n",
       "1     2 per pack        2.000     count         1          count   \n",
       "2  12 x 29.583ml       29.583        ml        12             ml   \n",
       "3          375ml      375.000        ml         1             ml   \n",
       "4           250g      250.000         g         1              g   \n",
       "\n",
       "                                           image_url source  \\\n",
       "0  https://voila.ca/images-v3/2d92d19c-0354-49c0-...  voila   \n",
       "1  https://voila.ca/images-v3/2d92d19c-0354-49c0-...  voila   \n",
       "2  https://voila.ca/images-v3/2d92d19c-0354-49c0-...  voila   \n",
       "3  https://voila.ca/images-v3/2d92d19c-0354-49c0-...  voila   \n",
       "4  https://voila.ca/images-v3/2d92d19c-0354-49c0-...  voila   \n",
       "\n",
       "                                          source_url  \n",
       "0  https://voila.ca/products/compliments-cold-and...  \n",
       "1  https://voila.ca/products/compliments-twister-...  \n",
       "2  https://voila.ca/products/compliments-zero-cal...  \n",
       "3  https://voila.ca/products/compliments-kalamata...  \n",
       "4  https://voila.ca/products/compliments-sliced-a...  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Columns (16):\n",
      "  upc                                 str        nulls=    1  uniques=3271\n",
      "  external_id                         str        nulls=    0  uniques=4440\n",
      "  brand                               str        nulls=    0  uniques=9\n",
      "  brand_clean                         str        nulls=    0  uniques=8\n",
      "  title                               str        nulls=    0  uniques=4375\n",
      "  title_clean                         str        nulls=    0  uniques=4375\n",
      "  price                               float64    nulls=    0  uniques=247\n",
      "  price_currency                      str        nulls=    0  uniques=1\n",
      "  size                                str        nulls=  215  uniques=630\n",
      "  size_amount                         float64    nulls=  307  uniques=387\n",
      "  size_unit                           str        nulls=  307  uniques=5\n",
      "  size_qty                            int64      nulls=    0  uniques=17\n",
      "  size_unit_norm                      str        nulls=  307  uniques=5\n",
      "  image_url                           str        nulls=    0  uniques=4440\n",
      "  source                              str        nulls=    0  uniques=1\n",
      "  source_url                          str        nulls=    0  uniques=4440\n"
     ]
    }
   ],
   "source": [
    "p1 = load(\"phase1/outputs/phase1_output.parquet\")\n",
    "show_table(p1, \"Phase 1 Output — phase1_output.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4f63fffc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:13.843569Z",
     "iopub.status.busy": "2026-08-01T17:42:13.842888Z",
     "iopub.status.idle": "2026-08-01T17:42:13.860602Z",
     "shell.execute_reply": "2026-08-01T17:42:13.857214Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Phase 1 Output Fields:\n",
      "--------------------------------------------------------------------------------\n",
      "  upc                  → Product barcode (3,271 unique, 774 reused, 1 null)\n",
      "  external_id          → Product-level identifier (4,440 unique — the primary key)\n",
      "  brand                → Raw brand name from source\n",
      "  brand_clean          → Cleaned brand (whitespace trim, ALL CAPS → Title Case)\n",
      "  title                → Raw product title from source\n",
      "  title_clean          → Cleaned title (whitespace normalized)\n",
      "  price                → Product price (if available)\n",
      "  price_currency       → Currency code (CAD)\n",
      "  size                 → Raw size string (e.g. '500 g', '1 kg', '2 x 250 mL')\n",
      "  size_amount          → Numeric size amount (e.g. 500, 1, 250)\n",
      "  size_unit            → Size unit (g, kg, mL, L, oz, lb)\n",
      "  size_qty             → Quantity (usually 1)\n",
      "  size_unit_norm       → Normalized size unit\n",
      "  image_url            → Product image URL\n",
      "  source               → Data source identifier\n",
      "  source_url           → Source URL for traceability\n"
     ]
    }
   ],
   "source": [
    "# Phase 1 Field Descriptions\n",
    "print(\"Phase 1 Output Fields:\")\n",
    "print(\"-\" * 80)\n",
    "fields = {\n",
    "    \"upc\":              \"Product barcode (3,271 unique, 774 reused, 1 null)\",\n",
    "    \"external_id\":      \"Product-level identifier (4,440 unique — the primary key)\",\n",
    "    \"brand\":            \"Raw brand name from source\",\n",
    "    \"brand_clean\":      \"Cleaned brand (whitespace trim, ALL CAPS → Title Case)\",\n",
    "    \"title\":            \"Raw product title from source\",\n",
    "    \"title_clean\":      \"Cleaned title (whitespace normalized)\",\n",
    "    \"price\":            \"Product price (if available)\",\n",
    "    \"price_currency\":   \"Currency code (CAD)\",\n",
    "    \"size\":             \"Raw size string (e.g. '500 g', '1 kg', '2 x 250 mL')\",\n",
    "    \"size_amount\":      \"Numeric size amount (e.g. 500, 1, 250)\",\n",
    "    \"size_unit\":        \"Size unit (g, kg, mL, L, oz, lb)\",\n",
    "    \"size_qty\":         \"Quantity (usually 1)\",\n",
    "    \"size_unit_norm\":   \"Normalized size unit\",\n",
    "    \"image_url\":        \"Product image URL\",\n",
    "    \"source\":           \"Data source identifier\",\n",
    "    \"source_url\":       \"Source URL for traceability\"\n",
    "}\n",
    "for f, desc in fields.items():\n",
    "    print(f\"  {f:20s} → {desc}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "488669ec",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:13.868003Z",
     "iopub.status.busy": "2026-08-01T17:42:13.866314Z",
     "iopub.status.idle": "2026-08-01T17:42:15.191515Z",
     "shell.execute_reply": "2026-08-01T17:42:15.189934Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Phase 1 — Brand Distribution\n",
    "fig, axes = plt.subplots(1, 2, figsize=(14, 5))\n",
    "\n",
    "p1['brand_clean'].value_counts().plot(kind='bar', ax=axes[0], color=COLORS[:2])\n",
    "axes[0].set_title('Phase 1 — Brand Distribution (cleaned)', fontsize=12)\n",
    "axes[0].set_ylabel('Count')\n",
    "\n",
    "null_counts = p1.isna().sum()\n",
    "null_counts[null_counts > 0].plot(kind='bar', ax=axes[1], color=COLORS[2])\n",
    "axes[1].set_title('Phase 1 — Null Counts per Column', fontsize=12)\n",
    "axes[1].set_ylabel('Null Count')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29f4560f",
   "metadata": {},
   "source": [
    "---\n",
    "# Phase 2 — Semantic Normalization\n",
    "\n",
    "**Goal:** Normalize brands, extract identity attributes from ORIGINAL titles, parse variants, build core titles.\n",
    "\n",
    "**Input:** `phase1_output.parquet` (4,440 × 14)\n",
    "**Output:** `phase2_output.parquet` (4,440 × 34) — 20 new columns added\n",
    "\n",
    "### What Happens\n",
    "1. Brand normalization: 9 raw variants → 2 brands + 7 product lines\n",
    "2. Identity flags extracted from ORIGINAL title (before normalization)\n",
    "3. Fat level + fat percentage extraction\n",
    "4. Flavour + formulation keyword extraction\n",
    "5. Variant attributes parsing from size strings\n",
    "6. Core title extraction (strip brand prefix + size)\n",
    "7. Deterministic identity hash"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "00e791d9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:15.204837Z",
     "iopub.status.busy": "2026-08-01T17:42:15.203705Z",
     "iopub.status.idle": "2026-08-01T17:42:15.779616Z",
     "shell.execute_reply": "2026-08-01T17:42:15.775158Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "  Phase 2 Output — phase2_output.parquet\n",
      "  Shape: 4440 rows × 34 columns\n",
      "============================================================\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>upc</th>\n",
       "      <th>external_id</th>\n",
       "      <th>brand</th>\n",
       "      <th>brand_clean</th>\n",
       "      <th>brand_norm</th>\n",
       "      <th>product_line</th>\n",
       "      <th>title</th>\n",
       "      <th>title_clean</th>\n",
       "      <th>core_title</th>\n",
       "      <th>price</th>\n",
       "      <th>...</th>\n",
       "      <th>is_plant_based</th>\n",
       "      <th>is_reduced_sodium</th>\n",
       "      <th>fat_level</th>\n",
       "      <th>fat_percentage</th>\n",
       "      <th>flavour</th>\n",
       "      <th>formulation</th>\n",
       "      <th>identity_hash</th>\n",
       "      <th>image_url</th>\n",
       "      <th>source</th>\n",
       "      <th>source_url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>055742522167</td>\n",
       "      <td>297608EA</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Core</td>\n",
       "      <td>Compliments Cold And Sinus Plus 20 Count</td>\n",
       "      <td>Compliments Cold And Sinus Plus 20 Count</td>\n",
       "      <td>Cold And Sinus Plus</td>\n",
       "      <td>9.99</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>regular</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[lime]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0|0|0|0|0|0|0|0|0|fat_none|regular|Core|lime|</td>\n",
       "      <td>https://voila.ca/images-v3/2d92d19c-0354-49c0-...</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-cold-and...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>055742335200</td>\n",
       "      <td>464324EA</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Core</td>\n",
       "      <td>Compliments Twister T2 Light Bulbs 23W Soft Wh...</td>\n",
       "      <td>Compliments Twister T2 Light Bulbs 23W Soft Wh...</td>\n",
       "      <td>Twister T2 Light Bulbs 23W Soft White</td>\n",
       "      <td>11.99</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>reduced_fat</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[lime]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0|0|0|0|0|0|0|0|0|fat_none|reduced_fat|Core|lime|</td>\n",
       "      <td>https://voila.ca/images-v3/2d92d19c-0354-49c0-...</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-twister-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>990002600400</td>\n",
       "      <td>144288CS</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Core</td>\n",
       "      <td>Compliments Zero Calorie Soft Drink 12 x 355ml</td>\n",
       "      <td>Compliments Zero Calorie Soft Drink 12 x 355ml</td>\n",
       "      <td>Zero Calorie Soft Drink</td>\n",
       "      <td>5.49</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>regular</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[lime]</td>\n",
       "      <td>[]</td>\n",
       "      <td>0|0|0|0|0|0|0|0|0|fat_none|regular|Core|lime|</td>\n",
       "      <td>https://voila.ca/images-v3/2d92d19c-0354-49c0-...</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-zero-cal...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>055742569391</td>\n",
       "      <td>312204EA</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Core</td>\n",
       "      <td>Compliments Kalamata Whole Olives 375 ml</td>\n",
       "      <td>Compliments Kalamata Whole Olives 375 ml</td>\n",
       "      <td>Kalamata Whole Olives</td>\n",
       "      <td>3.29</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>regular</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[lime]</td>\n",
       "      <td>[whole]</td>\n",
       "      <td>0|0|0|0|0|0|0|0|0|fat_none|regular|Core|lime|w...</td>\n",
       "      <td>https://voila.ca/images-v3/2d92d19c-0354-49c0-...</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-kalamata...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>055742561111</td>\n",
       "      <td>259928EA</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Core</td>\n",
       "      <td>Compliments Sliced Almonds 250 g</td>\n",
       "      <td>Compliments Sliced Almonds 250 g</td>\n",
       "      <td>Sliced Almonds</td>\n",
       "      <td>7.99</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>regular</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[almond, lime]</td>\n",
       "      <td>[sliced]</td>\n",
       "      <td>0|0|0|0|0|0|0|0|0|fat_none|regular|Core|almond...</td>\n",
       "      <td>https://voila.ca/images-v3/2d92d19c-0354-49c0-...</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-sliced-a...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            upc external_id        brand  brand_clean   brand_norm  \\\n",
       "0  055742522167    297608EA  Compliments  Compliments  Compliments   \n",
       "1  055742335200    464324EA  Compliments  Compliments  Compliments   \n",
       "2  990002600400    144288CS  Compliments  Compliments  Compliments   \n",
       "3  055742569391    312204EA  Compliments  Compliments  Compliments   \n",
       "4  055742561111    259928EA  Compliments  Compliments  Compliments   \n",
       "\n",
       "  product_line                                              title  \\\n",
       "0         Core           Compliments Cold And Sinus Plus 20 Count   \n",
       "1         Core  Compliments Twister T2 Light Bulbs 23W Soft Wh...   \n",
       "2         Core     Compliments Zero Calorie Soft Drink 12 x 355ml   \n",
       "3         Core           Compliments Kalamata Whole Olives 375 ml   \n",
       "4         Core                   Compliments Sliced Almonds 250 g   \n",
       "\n",
       "                                         title_clean  \\\n",
       "0           Compliments Cold And Sinus Plus 20 Count   \n",
       "1  Compliments Twister T2 Light Bulbs 23W Soft Wh...   \n",
       "2     Compliments Zero Calorie Soft Drink 12 x 355ml   \n",
       "3           Compliments Kalamata Whole Olives 375 ml   \n",
       "4                   Compliments Sliced Almonds 250 g   \n",
       "\n",
       "                              core_title  price  ... is_plant_based  \\\n",
       "0                    Cold And Sinus Plus   9.99  ...          False   \n",
       "1  Twister T2 Light Bulbs 23W Soft White  11.99  ...          False   \n",
       "2                Zero Calorie Soft Drink   5.49  ...          False   \n",
       "3                  Kalamata Whole Olives   3.29  ...          False   \n",
       "4                         Sliced Almonds   7.99  ...          False   \n",
       "\n",
       "  is_reduced_sodium    fat_level fat_percentage         flavour formulation  \\\n",
       "0             False      regular            NaN          [lime]          []   \n",
       "1             False  reduced_fat            NaN          [lime]          []   \n",
       "2             False      regular            NaN          [lime]          []   \n",
       "3             False      regular            NaN          [lime]     [whole]   \n",
       "4             False      regular            NaN  [almond, lime]    [sliced]   \n",
       "\n",
       "                                       identity_hash  \\\n",
       "0      0|0|0|0|0|0|0|0|0|fat_none|regular|Core|lime|   \n",
       "1  0|0|0|0|0|0|0|0|0|fat_none|reduced_fat|Core|lime|   \n",
       "2      0|0|0|0|0|0|0|0|0|fat_none|regular|Core|lime|   \n",
       "3  0|0|0|0|0|0|0|0|0|fat_none|regular|Core|lime|w...   \n",
       "4  0|0|0|0|0|0|0|0|0|fat_none|regular|Core|almond...   \n",
       "\n",
       "                                           image_url  source  \\\n",
       "0  https://voila.ca/images-v3/2d92d19c-0354-49c0-...   voila   \n",
       "1  https://voila.ca/images-v3/2d92d19c-0354-49c0-...   voila   \n",
       "2  https://voila.ca/images-v3/2d92d19c-0354-49c0-...   voila   \n",
       "3  https://voila.ca/images-v3/2d92d19c-0354-49c0-...   voila   \n",
       "4  https://voila.ca/images-v3/2d92d19c-0354-49c0-...   voila   \n",
       "\n",
       "                                          source_url  \n",
       "0  https://voila.ca/products/compliments-cold-and...  \n",
       "1  https://voila.ca/products/compliments-twister-...  \n",
       "2  https://voila.ca/products/compliments-zero-cal...  \n",
       "3  https://voila.ca/products/compliments-kalamata...  \n",
       "4  https://voila.ca/products/compliments-sliced-a...  \n",
       "\n",
       "[5 rows x 34 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Columns (34):\n",
      "  upc                                 str        nulls=    1  uniques=3271\n",
      "  external_id                         str        nulls=    0  uniques=4440\n",
      "  brand                               str        nulls=    0  uniques=9\n",
      "  brand_clean                         str        nulls=    0  uniques=8\n",
      "  brand_norm                          str        nulls=    0  uniques=2\n",
      "  product_line                        str        nulls=    0  uniques=7\n",
      "  title                               str        nulls=    0  uniques=4375\n",
      "  title_clean                         str        nulls=    0  uniques=4375\n",
      "  core_title                          str        nulls=    0  uniques=4070\n",
      "  price                               float64    nulls=    0  uniques=247\n",
      "  price_currency                      str        nulls=    0  uniques=1\n",
      "  size                                str        nulls=  215  uniques=630\n",
      "  size_amount                         float64    nulls=  307  uniques=387\n",
      "  size_unit                           str        nulls=  307  uniques=5\n",
      "  size_qty                            int64      nulls=    0  uniques=17\n",
      "  size_unit_norm                      str        nulls=  307  uniques=5\n",
      "  variant_attributes                  str        nulls=    0  uniques=631\n",
      "  is_organic                          bool       nulls=    0  uniques=2\n",
      "  is_gluten_free                      bool       nulls=    0  uniques=2\n",
      "  is_naturally_simple                 bool       nulls=    0  uniques=2\n",
      "  is_sugar_free                       bool       nulls=    0  uniques=2\n",
      "  is_unsalted                         bool       nulls=    0  uniques=2\n",
      "  is_lactose_free                     bool       nulls=    0  uniques=2\n",
      "  is_peanut_free                      bool       nulls=    0  uniques=2\n",
      "  is_plant_based                      bool       nulls=    0  uniques=2\n",
      "  is_reduced_sodium                   bool       nulls=    0  uniques=2\n",
      "  fat_level                           str        nulls=    0  uniques=3\n",
      "  fat_percentage                      float64    nulls= 4386  uniques=19\n",
      "  flavour                             object     nulls=    0  uniques=N/A\n",
      "  formulation                         object     nulls=    0  uniques=N/A\n",
      "  identity_hash                       str        nulls=    0  uniques=346\n",
      "  image_url                           str        nulls=    0  uniques=4440\n",
      "  source                              str        nulls=    0  uniques=1\n",
      "  source_url                          str        nulls=    0  uniques=4440\n"
     ]
    }
   ],
   "source": [
    "p2 = load(\"phase2/outputs/phase2_output.parquet\")\n",
    "show_table(p2, \"Phase 2 Output — phase2_output.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f162961f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:15.788105Z",
     "iopub.status.busy": "2026-08-01T17:42:15.784111Z",
     "iopub.status.idle": "2026-08-01T17:42:15.806482Z",
     "shell.execute_reply": "2026-08-01T17:42:15.804113Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Phase 2 New Fields (20 columns added):\n",
      "--------------------------------------------------------------------------------\n",
      "  brand_norm             → Normalized brand name (Compliments / Sensations)\n",
      "  product_line           → Product line (Core, Organic, Balance, Naturally Simple, Green, Little Ones, Sensations)\n",
      "  is_organic             → Boolean — organic product\n",
      "  is_gluten_free         → Boolean — gluten-free product\n",
      "  is_naturally_simple    → Boolean — Naturally Simple line\n",
      "  is_sugar_free          → Boolean — sugar-free / no sugar added\n",
      "  is_unsalted            → Boolean — unsalted product\n",
      "  is_lactose_free        → Boolean — lactose-free product\n",
      "  is_peanut_free         → Boolean — peanut-free product\n",
      "  is_plant_based         → Boolean — plant-based product\n",
      "  is_reduced_sodium      → Boolean — reduced sodium / low sodium\n",
      "  fat_level              → regular / reduced_fat / fat_free\n",
      "  fat_percentage         → Numeric fat % (extracted from title, e.g. '1% Cottage Cheese')\n",
      "  flavour                → List of flavour keywords (chocolate, vanilla, strawberry, etc.)\n",
      "  formulation            → List of formulation keywords (smooth, crunchy, creamy, etc.)\n",
      "  variant_attributes     → JSON — parsed size/package attributes (amount, unit, qty, count)\n",
      "  core_title             → Title stripped of brand prefix and size info\n",
      "  identity_hash          → Deterministic hash of all identity attributes (for grouping)\n"
     ]
    }
   ],
   "source": [
    "# Phase 2 New Fields\n",
    "print(\"Phase 2 New Fields (20 columns added):\")\n",
    "print(\"-\" * 80)\n",
    "new_fields = {\n",
    "    \"brand_norm\":        \"Normalized brand name (Compliments / Sensations)\",\n",
    "    \"product_line\":     \"Product line (Core, Organic, Balance, Naturally Simple, Green, Little Ones, Sensations)\",\n",
    "    \"is_organic\":        \"Boolean — organic product\",\n",
    "    \"is_gluten_free\":    \"Boolean — gluten-free product\",\n",
    "    \"is_naturally_simple\": \"Boolean — Naturally Simple line\",\n",
    "    \"is_sugar_free\":     \"Boolean — sugar-free / no sugar added\",\n",
    "    \"is_unsalted\":       \"Boolean — unsalted product\",\n",
    "    \"is_lactose_free\":   \"Boolean — lactose-free product\",\n",
    "    \"is_peanut_free\":    \"Boolean — peanut-free product\",\n",
    "    \"is_plant_based\":    \"Boolean — plant-based product\",\n",
    "    \"is_reduced_sodium\": \"Boolean — reduced sodium / low sodium\",\n",
    "    \"fat_level\":         \"regular / reduced_fat / fat_free\",\n",
    "    \"fat_percentage\":    \"Numeric fat % (extracted from title, e.g. '1% Cottage Cheese')\",\n",
    "    \"flavour\":           \"List of flavour keywords (chocolate, vanilla, strawberry, etc.)\",\n",
    "    \"formulation\":       \"List of formulation keywords (smooth, crunchy, creamy, etc.)\",\n",
    "    \"variant_attributes\":\"JSON — parsed size/package attributes (amount, unit, qty, count)\",\n",
    "    \"core_title\":        \"Title stripped of brand prefix and size info\",\n",
    "    \"identity_hash\":     \"Deterministic hash of all identity attributes (for grouping)\"\n",
    "}\n",
    "for f, desc in new_fields.items():\n",
    "    print(f\"  {f:22s} → {desc}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8d38aa9b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:15.812471Z",
     "iopub.status.busy": "2026-08-01T17:42:15.811941Z",
     "iopub.status.idle": "2026-08-01T17:42:17.719758Z",
     "shell.execute_reply": "2026-08-01T17:42:17.717181Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Phase 2 — Brand Normalization + Identity Flags\n",
    "fig, axes = plt.subplots(1, 3, figsize=(18, 5))\n",
    "\n",
    "p2['brand_norm'].value_counts().plot(kind='bar', ax=axes[0], color=COLORS[:2])\n",
    "axes[0].set_title('Phase 2 — Normalized Brands', fontsize=12)\n",
    "axes[0].set_ylabel('Count')\n",
    "\n",
    "p2['product_line'].value_counts().plot(kind='bar', ax=axes[1], color=COLORS[:7])\n",
    "axes[1].set_title('Phase 2 — Product Lines', fontsize=12)\n",
    "axes[1].set_ylabel('Count')\n",
    "\n",
    "flags = ['is_organic','is_gluten_free','is_naturally_simple','is_sugar_free',\n",
    "         'is_unsalted','is_lactose_free','is_peanut_free','is_plant_based','is_reduced_sodium']\n",
    "flag_counts = {f.replace('is_',''): int(p2[f].sum()) for f in flags}\n",
    "pd.Series(flag_counts).plot(kind='bar', ax=axes[2], color=COLORS[:9])\n",
    "axes[2].set_title('Phase 2 — Identity Flags', fontsize=12)\n",
    "axes[2].set_ylabel('Count')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a063a6b7",
   "metadata": {},
   "source": [
    "---\n",
    "# Phase 3 — Product Domain + Taxonomy + Grouping\n",
    "\n",
    "**Goal:** Classify food/non-food, assign taxonomy, group products by identity.\n",
    "\n",
    "**Input:** `phase2_output.parquet` (4,440 × 34)\n",
    "**Output:** 6 tables — catalog, mapping, GPC, non-food, ambiguous, unknown\n",
    "\n",
    "### What Happens\n",
    "1. Food / non_food / unknown classification (keyword rules)\n",
    "2. Taxonomy classification (19 categories)\n",
    "3. Product grouping by identity hash + domain + normalized title\n",
    "4. Ambiguous case detection\n",
    "5. Reference catalog + product mapping generation\n",
    "6. Google Product Category (GPC) mapping\n",
    "7. Non-food products table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d855318c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:17.727687Z",
     "iopub.status.busy": "2026-08-01T17:42:17.727049Z",
     "iopub.status.idle": "2026-08-01T17:42:20.242495Z",
     "shell.execute_reply": "2026-08-01T17:42:20.233231Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "  Phase 3 — reference_product_catalog.csv (one row per group)\n",
      "  Shape: 3691 rows × 8 columns\n",
      "============================================================\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>group_id</th>\n",
       "      <th>group_name</th>\n",
       "      <th>brand</th>\n",
       "      <th>product_domain</th>\n",
       "      <th>reference_db_taxonomy</th>\n",
       "      <th>identity_hash</th>\n",
       "      <th>product_count</th>\n",
       "      <th>unique_upcs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3fd7ccec-ba5b-57db-a730-359de4a6ff1b</td>\n",
       "      <td>Fat-Free 0.3% Cottage Cheese</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>food</td>\n",
       "      <td>DAIRY</td>\n",
       "      <td>0|0|0|0|0|0|0|0|0|fat0.3|fat_free|Core|lime|</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>22f55325-de25-582f-85bf-aab4917e64d3</td>\n",
       "      <td>0.4% Cottage Cheese Dry Curd</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>food</td>\n",
       "      <td>DAIRY</td>\n",
       "      <td>0|0|0|0|0|0|0|0|0|fat0.4|fat_free|Core|lime|</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8a749cd7-9083-5634-919b-613fab5137a3</td>\n",
       "      <td>0.5% Cream Hydrocortisone For Itching &amp; Rednes...</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>non_food</td>\n",
       "      <td>DAIRY</td>\n",
       "      <td>0|0|0|0|0|0|0|0|0|fat0.5|fat_free|Core|lime|</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3795532a-f103-5834-8f3f-f3d50a78a42b</td>\n",
       "      <td>0.7% Drinkable Yogurt Raspberry</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>food</td>\n",
       "      <td>DAIRY</td>\n",
       "      <td>0|0|0|0|0|0|0|0|0|fat0.7|fat_free|Core|berry,l...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1a4f80fd-2b0c-5cfd-b160-2b1a1becbf7a</td>\n",
       "      <td>0.7% Drinkable Yogurt Strawberry</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>food</td>\n",
       "      <td>DAIRY</td>\n",
       "      <td>0|0|0|0|0|0|0|0|0|fat0.7|fat_free|Core|berry,l...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               group_id  \\\n",
       "0  3fd7ccec-ba5b-57db-a730-359de4a6ff1b   \n",
       "1  22f55325-de25-582f-85bf-aab4917e64d3   \n",
       "2  8a749cd7-9083-5634-919b-613fab5137a3   \n",
       "3  3795532a-f103-5834-8f3f-f3d50a78a42b   \n",
       "4  1a4f80fd-2b0c-5cfd-b160-2b1a1becbf7a   \n",
       "\n",
       "                                          group_name        brand  \\\n",
       "0                       Fat-Free 0.3% Cottage Cheese  Compliments   \n",
       "1                       0.4% Cottage Cheese Dry Curd  Compliments   \n",
       "2  0.5% Cream Hydrocortisone For Itching & Rednes...  Compliments   \n",
       "3                    0.7% Drinkable Yogurt Raspberry  Compliments   \n",
       "4                   0.7% Drinkable Yogurt Strawberry  Compliments   \n",
       "\n",
       "  product_domain reference_db_taxonomy  \\\n",
       "0           food                 DAIRY   \n",
       "1           food                 DAIRY   \n",
       "2       non_food                 DAIRY   \n",
       "3           food                 DAIRY   \n",
       "4           food                 DAIRY   \n",
       "\n",
       "                                       identity_hash  product_count  \\\n",
       "0       0|0|0|0|0|0|0|0|0|fat0.3|fat_free|Core|lime|              1   \n",
       "1       0|0|0|0|0|0|0|0|0|fat0.4|fat_free|Core|lime|              1   \n",
       "2       0|0|0|0|0|0|0|0|0|fat0.5|fat_free|Core|lime|              1   \n",
       "3  0|0|0|0|0|0|0|0|0|fat0.7|fat_free|Core|berry,l...              1   \n",
       "4  0|0|0|0|0|0|0|0|0|fat0.7|fat_free|Core|berry,l...              1   \n",
       "\n",
       "   unique_upcs  \n",
       "0            1  \n",
       "1            1  \n",
       "2            1  \n",
       "3            1  \n",
       "4            1  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Columns (8):\n",
      "  group_id                            str        nulls=    0  uniques=3691\n",
      "  group_name                          str        nulls=    0  uniques=3685\n",
      "  brand                               str        nulls=    0  uniques=2\n",
      "  product_domain                      str        nulls=    0  uniques=3\n",
      "  reference_db_taxonomy               str        nulls=    0  uniques=19\n",
      "  identity_hash                       str        nulls=    0  uniques=346\n",
      "  product_count                       int64      nulls=    0  uniques=9\n",
      "  unique_upcs                         int64      nulls=    0  uniques=5\n"
     ]
    }
   ],
   "source": [
    "catalog = load(\"phase3/outputs/reference_product_catalog.csv\")\n",
    "mapping = load(\"phase3/outputs/product_group_mapping.csv\")\n",
    "gpc = load(\"phase3/outputs/taxonomy_gpc_mapping.csv\")\n",
    "non_food = load(\"phase3/outputs/non_food_products.csv\")\n",
    "\n",
    "show_table(catalog, \"Phase 3 — reference_product_catalog.csv (one row per group)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a113245a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:20.258330Z",
     "iopub.status.busy": "2026-08-01T17:42:20.254153Z",
     "iopub.status.idle": "2026-08-01T17:42:20.291145Z",
     "shell.execute_reply": "2026-08-01T17:42:20.285490Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reference Product Catalog Fields:\n",
      "--------------------------------------------------------------------------------\n",
      "  group_id                  → Deterministic UUID5 from group_key\n",
      "  group_name                → Most frequent core_title in group\n",
      "  brand                     → Brand name (Compliments / Sensations)\n",
      "  product_domain            → food / non_food / unknown\n",
      "  reference_db_taxonomy     → Category (DAIRY, MEAT_SEAFOOD, BEVERAGES, etc.)\n",
      "  identity_hash             → Identity hash from Phase 2\n",
      "  product_count             → Number of products in this group\n",
      "  unique_upcs               → Number of unique UPCs in this group\n"
     ]
    }
   ],
   "source": [
    "# Catalog Fields\n",
    "print(\"Reference Product Catalog Fields:\")\n",
    "print(\"-\" * 80)\n",
    "cat_fields = {\n",
    "    \"group_id\":              \"Deterministic UUID5 from group_key\",\n",
    "    \"group_name\":            \"Most frequent core_title in group\",\n",
    "    \"brand\":                 \"Brand name (Compliments / Sensations)\",\n",
    "    \"product_domain\":        \"food / non_food / unknown\",\n",
    "    \"reference_db_taxonomy\": \"Category (DAIRY, MEAT_SEAFOOD, BEVERAGES, etc.)\",\n",
    "    \"identity_hash\":         \"Identity hash from Phase 2\",\n",
    "    \"product_count\":         \"Number of products in this group\",\n",
    "    \"unique_upcs\":           \"Number of unique UPCs in this group\"\n",
    "}\n",
    "for f, desc in cat_fields.items():\n",
    "    print(f\"  {f:25s} → {desc}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1a24a5c6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:20.304053Z",
     "iopub.status.busy": "2026-08-01T17:42:20.298530Z",
     "iopub.status.idle": "2026-08-01T17:42:20.605739Z",
     "shell.execute_reply": "2026-08-01T17:42:20.603895Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "  Phase 3 — product_group_mapping.csv (one row per product)\n",
      "  Shape: 4440 rows × 28 columns\n",
      "============================================================\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>upc</th>\n",
       "      <th>external_id</th>\n",
       "      <th>group_id</th>\n",
       "      <th>group_name</th>\n",
       "      <th>core_title</th>\n",
       "      <th>original_title</th>\n",
       "      <th>brand</th>\n",
       "      <th>size</th>\n",
       "      <th>variant_attributes</th>\n",
       "      <th>identity_hash</th>\n",
       "      <th>...</th>\n",
       "      <th>is_lactose_free</th>\n",
       "      <th>is_peanut_free</th>\n",
       "      <th>is_plant_based</th>\n",
       "      <th>is_reduced_sodium</th>\n",
       "      <th>fat_level</th>\n",
       "      <th>fat_percentage</th>\n",
       "      <th>flavour</th>\n",
       "      <th>formulation</th>\n",
       "      <th>source</th>\n",
       "      <th>source_url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.574252e+10</td>\n",
       "      <td>297608EA</td>\n",
       "      <td>27b951a3-bef1-5ed4-80b7-7ef5cdca910a</td>\n",
       "      <td>Cold And Sinus Plus</td>\n",
       "      <td>Cold And Sinus Plus</td>\n",
       "      <td>Compliments Cold And Sinus Plus 20 Count</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>20 per pack</td>\n",
       "      <td>{\"count\": 20}</td>\n",
       "      <td>0|0|0|0|0|0|0|0|0|fat_none|regular|Core|lime|</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>regular</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['lime']</td>\n",
       "      <td>[]</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-cold-and...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.574234e+10</td>\n",
       "      <td>464324EA</td>\n",
       "      <td>e608ba58-8f93-59f1-9446-edb91aef79bd</td>\n",
       "      <td>Twister T2 Light Bulbs 23W Soft White</td>\n",
       "      <td>Twister T2 Light Bulbs 23W Soft White</td>\n",
       "      <td>Compliments Twister T2 Light Bulbs 23W Soft Wh...</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>2 per pack</td>\n",
       "      <td>{\"count\": 2}</td>\n",
       "      <td>0|0|0|0|0|0|0|0|0|fat_none|reduced_fat|Core|lime|</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>reduced_fat</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['lime']</td>\n",
       "      <td>[]</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-twister-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9.900026e+11</td>\n",
       "      <td>144288CS</td>\n",
       "      <td>336c79d8-796d-5682-8195-793883dd97ef</td>\n",
       "      <td>Zero Calorie Soft Drink</td>\n",
       "      <td>Zero Calorie Soft Drink</td>\n",
       "      <td>Compliments Zero Calorie Soft Drink 12 x 355ml</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>12 x 29.583ml</td>\n",
       "      <td>{\"qty\": 12, \"amount\": 29.583, \"unit\": \"ml\"}</td>\n",
       "      <td>0|0|0|0|0|0|0|0|0|fat_none|regular|Core|lime|</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>regular</td>\n",
       "      <td>NaN</td>\n",
       "      <td>['lime']</td>\n",
       "      <td>[]</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-zero-cal...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            upc external_id                              group_id  \\\n",
       "0  5.574252e+10    297608EA  27b951a3-bef1-5ed4-80b7-7ef5cdca910a   \n",
       "1  5.574234e+10    464324EA  e608ba58-8f93-59f1-9446-edb91aef79bd   \n",
       "2  9.900026e+11    144288CS  336c79d8-796d-5682-8195-793883dd97ef   \n",
       "\n",
       "                              group_name  \\\n",
       "0                    Cold And Sinus Plus   \n",
       "1  Twister T2 Light Bulbs 23W Soft White   \n",
       "2                Zero Calorie Soft Drink   \n",
       "\n",
       "                              core_title  \\\n",
       "0                    Cold And Sinus Plus   \n",
       "1  Twister T2 Light Bulbs 23W Soft White   \n",
       "2                Zero Calorie Soft Drink   \n",
       "\n",
       "                                      original_title        brand  \\\n",
       "0           Compliments Cold And Sinus Plus 20 Count  Compliments   \n",
       "1  Compliments Twister T2 Light Bulbs 23W Soft Wh...  Compliments   \n",
       "2     Compliments Zero Calorie Soft Drink 12 x 355ml  Compliments   \n",
       "\n",
       "            size                           variant_attributes  \\\n",
       "0    20 per pack                                {\"count\": 20}   \n",
       "1     2 per pack                                 {\"count\": 2}   \n",
       "2  12 x 29.583ml  {\"qty\": 12, \"amount\": 29.583, \"unit\": \"ml\"}   \n",
       "\n",
       "                                       identity_hash  ... is_lactose_free  \\\n",
       "0      0|0|0|0|0|0|0|0|0|fat_none|regular|Core|lime|  ...           False   \n",
       "1  0|0|0|0|0|0|0|0|0|fat_none|reduced_fat|Core|lime|  ...           False   \n",
       "2      0|0|0|0|0|0|0|0|0|fat_none|regular|Core|lime|  ...           False   \n",
       "\n",
       "  is_peanut_free is_plant_based  is_reduced_sodium    fat_level  \\\n",
       "0          False          False              False      regular   \n",
       "1          False          False              False  reduced_fat   \n",
       "2          False          False              False      regular   \n",
       "\n",
       "   fat_percentage   flavour  formulation  source  \\\n",
       "0             NaN  ['lime']           []   voila   \n",
       "1             NaN  ['lime']           []   voila   \n",
       "2             NaN  ['lime']           []   voila   \n",
       "\n",
       "                                          source_url  \n",
       "0  https://voila.ca/products/compliments-cold-and...  \n",
       "1  https://voila.ca/products/compliments-twister-...  \n",
       "2  https://voila.ca/products/compliments-zero-cal...  \n",
       "\n",
       "[3 rows x 28 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Columns (28):\n",
      "  upc                                 float64    nulls=    1  uniques=3271\n",
      "  external_id                         str        nulls=    0  uniques=4440\n",
      "  group_id                            str        nulls=    0  uniques=3691\n",
      "  group_name                          str        nulls=    0  uniques=4070\n",
      "  core_title                          str        nulls=    0  uniques=4070\n",
      "  original_title                      str        nulls=    0  uniques=4375\n",
      "  brand                               str        nulls=    0  uniques=2\n",
      "  size                                str        nulls=  215  uniques=630\n",
      "  variant_attributes                  str        nulls=    0  uniques=631\n",
      "  identity_hash                       str        nulls=    0  uniques=346\n",
      "  product_domain                      str        nulls=    0  uniques=3\n",
      "  reference_db_taxonomy               str        nulls=    0  uniques=19\n",
      "  product_line                        str        nulls=    0  uniques=7\n",
      "  is_organic                          bool       nulls=    0  uniques=2\n",
      "  is_gluten_free                      bool       nulls=    0  uniques=2\n",
      "  is_naturally_simple                 bool       nulls=    0  uniques=2\n",
      "  is_sugar_free                       bool       nulls=    0  uniques=2\n",
      "  is_unsalted                         bool       nulls=    0  uniques=2\n",
      "  is_lactose_free                     bool       nulls=    0  uniques=2\n",
      "  is_peanut_free                      bool       nulls=    0  uniques=2\n",
      "  is_plant_based                      bool       nulls=    0  uniques=2\n",
      "  is_reduced_sodium                   bool       nulls=    0  uniques=2\n",
      "  fat_level                           str        nulls=    0  uniques=3\n",
      "  fat_percentage                      float64    nulls= 4386  uniques=19\n",
      "  flavour                             str        nulls=    0  uniques=87\n",
      "  formulation                         str        nulls=    0  uniques=28\n",
      "  source                              str        nulls=    0  uniques=1\n",
      "  source_url                          str        nulls=    0  uniques=4440\n"
     ]
    }
   ],
   "source": [
    "show_table(mapping, \"Phase 3 — product_group_mapping.csv (one row per product)\", n=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8b47168b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:20.696786Z",
     "iopub.status.busy": "2026-08-01T17:42:20.696229Z",
     "iopub.status.idle": "2026-08-01T17:42:20.788895Z",
     "shell.execute_reply": "2026-08-01T17:42:20.774814Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Product Group Mapping Fields (28 columns):\n",
      "--------------------------------------------------------------------------------\n",
      "  upc                       → Product barcode\n",
      "  external_id               → Product-level identifier\n",
      "  group_id                  → Group UUID (same for all products in group)\n",
      "  group_name                → Group name (most frequent core_title)\n",
      "  core_title                → Normalized core title\n",
      "  original_title            → Original product title (for traceability)\n",
      "  brand                     → Brand name\n",
      "  size                      → Raw size string\n",
      "  variant_attributes        → JSON — parsed size/package attributes\n",
      "  identity_hash             → Identity hash\n",
      "  product_domain            → food / non_food / unknown\n",
      "  reference_db_taxonomy     → Category\n",
      "  product_line              → Product line\n",
      "  is_organic                → Organic flag\n",
      "  is_gluten_free            → Gluten-free flag\n",
      "  is_naturally_simple       → Naturally Simple flag\n",
      "  is_sugar_free             → Sugar-free flag\n",
      "  is_unsalted               → Unsalted flag\n",
      "  is_lactose_free           → Lactose-free flag\n",
      "  is_peanut_free            → Peanut-free flag\n",
      "  is_plant_based            → Plant-based flag\n",
      "  is_reduced_sodium         → Reduced sodium flag\n",
      "  fat_level                 → regular / reduced_fat / fat_free\n",
      "  fat_percentage            → Fat percentage\n",
      "  flavour                   → Flavour keywords\n",
      "  formulation               → Formulation keywords\n",
      "  source                    → Data source\n",
      "  source_url                → Source URL\n"
     ]
    }
   ],
   "source": [
    "# Mapping Fields\n",
    "print(\"Product Group Mapping Fields (28 columns):\")\n",
    "print(\"-\" * 80)\n",
    "map_fields = {\n",
    "    \"upc\":                  \"Product barcode\",\n",
    "    \"external_id\":          \"Product-level identifier\",\n",
    "    \"group_id\":             \"Group UUID (same for all products in group)\",\n",
    "    \"group_name\":           \"Group name (most frequent core_title)\",\n",
    "    \"core_title\":           \"Normalized core title\",\n",
    "    \"original_title\":       \"Original product title (for traceability)\",\n",
    "    \"brand\":                \"Brand name\",\n",
    "    \"size\":                 \"Raw size string\",\n",
    "    \"variant_attributes\":  \"JSON — parsed size/package attributes\",\n",
    "    \"identity_hash\":        \"Identity hash\",\n",
    "    \"product_domain\":       \"food / non_food / unknown\",\n",
    "    \"reference_db_taxonomy\":\"Category\",\n",
    "    \"product_line\":         \"Product line\",\n",
    "    \"is_organic\":           \"Organic flag\",\n",
    "    \"is_gluten_free\":       \"Gluten-free flag\",\n",
    "    \"is_naturally_simple\":  \"Naturally Simple flag\",\n",
    "    \"is_sugar_free\":        \"Sugar-free flag\",\n",
    "    \"is_unsalted\":          \"Unsalted flag\",\n",
    "    \"is_lactose_free\":      \"Lactose-free flag\",\n",
    "    \"is_peanut_free\":       \"Peanut-free flag\",\n",
    "    \"is_plant_based\":       \"Plant-based flag\",\n",
    "    \"is_reduced_sodium\":    \"Reduced sodium flag\",\n",
    "    \"fat_level\":            \"regular / reduced_fat / fat_free\",\n",
    "    \"fat_percentage\":       \"Fat percentage\",\n",
    "    \"flavour\":              \"Flavour keywords\",\n",
    "    \"formulation\":          \"Formulation keywords\",\n",
    "    \"source\":               \"Data source\",\n",
    "    \"source_url\":           \"Source URL\"\n",
    "}\n",
    "for f, desc in map_fields.items():\n",
    "    print(f\"  {f:25s} → {desc}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f878aeaf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:20.818109Z",
     "iopub.status.busy": "2026-08-01T17:42:20.817532Z",
     "iopub.status.idle": "2026-08-01T17:42:20.938962Z",
     "shell.execute_reply": "2026-08-01T17:42:20.926055Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "  Phase 3 — taxonomy_gpc_mapping.csv (taxonomy → GPC)\n",
      "  Shape: 19 rows × 4 columns\n",
      "============================================================\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>reference_db_taxonomy</th>\n",
       "      <th>gpc_id</th>\n",
       "      <th>gpc_name</th>\n",
       "      <th>gpc_full_path</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DAIRY</td>\n",
       "      <td>428.0</td>\n",
       "      <td>Dairy Products</td>\n",
       "      <td>Food, Beverages &amp; Tobacco &gt; Food Items &gt; Dairy...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MEAT_SEAFOOD</td>\n",
       "      <td>432.0</td>\n",
       "      <td>Meat, Seafood &amp; Eggs</td>\n",
       "      <td>Food, Beverages &amp; Tobacco &gt; Food Items &gt; Meat,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BEVERAGES</td>\n",
       "      <td>413.0</td>\n",
       "      <td>Beverages</td>\n",
       "      <td>Food, Beverages &amp; Tobacco &gt; Beverages</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BAKERY</td>\n",
       "      <td>1876.0</td>\n",
       "      <td>Bakery</td>\n",
       "      <td>Food, Beverages &amp; Tobacco &gt; Food Items &gt; Bakery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FROZEN</td>\n",
       "      <td>5788.0</td>\n",
       "      <td>Frozen Desserts &amp; Novelties</td>\n",
       "      <td>Food, Beverages &amp; Tobacco &gt; Food Items &gt; Froze...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  reference_db_taxonomy  gpc_id                     gpc_name  \\\n",
       "0                 DAIRY   428.0               Dairy Products   \n",
       "1          MEAT_SEAFOOD   432.0         Meat, Seafood & Eggs   \n",
       "2             BEVERAGES   413.0                    Beverages   \n",
       "3                BAKERY  1876.0                       Bakery   \n",
       "4                FROZEN  5788.0  Frozen Desserts & Novelties   \n",
       "\n",
       "                                       gpc_full_path  \n",
       "0  Food, Beverages & Tobacco > Food Items > Dairy...  \n",
       "1  Food, Beverages & Tobacco > Food Items > Meat,...  \n",
       "2              Food, Beverages & Tobacco > Beverages  \n",
       "3    Food, Beverages & Tobacco > Food Items > Bakery  \n",
       "4  Food, Beverages & Tobacco > Food Items > Froze...  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Columns (4):\n",
      "  reference_db_taxonomy               str        nulls=    0  uniques=19\n",
      "  gpc_id                              float64    nulls=    6  uniques=13\n",
      "  gpc_name                            str        nulls=    0  uniques=19\n",
      "  gpc_full_path                       str        nulls=    0  uniques=19\n"
     ]
    }
   ],
   "source": [
    "show_table(gpc, \"Phase 3 — taxonomy_gpc_mapping.csv (taxonomy → GPC)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f6369a15",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:20.960028Z",
     "iopub.status.busy": "2026-08-01T17:42:20.956094Z",
     "iopub.status.idle": "2026-08-01T17:42:20.975908Z",
     "shell.execute_reply": "2026-08-01T17:42:20.972890Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GPC Mapping Fields:"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--------------------------------------------------------------------------------\n",
      "  reference_db_taxonomy     → Internal taxonomy category\n",
      "  gpc_id                    → Google Product Category ID\n",
      "  gpc_name                  → GPC category name\n",
      "  gpc_full_path             → Full GPC hierarchy path\n",
      "\n",
      "GPC Source: https://www.google.com/basepages/producttype/taxonomy.en-US.txt\n"
     ]
    }
   ],
   "source": [
    "# GPC Fields\n",
    "print(\"GPC Mapping Fields:\")\n",
    "print(\"-\" * 80)\n",
    "gpc_fields = {\n",
    "    \"reference_db_taxonomy\": \"Internal taxonomy category\",\n",
    "    \"gpc_id\":                \"Google Product Category ID\",\n",
    "    \"gpc_name\":              \"GPC category name\",\n",
    "    \"gpc_full_path\":         \"Full GPC hierarchy path\"\n",
    "}\n",
    "for f, desc in gpc_fields.items():\n",
    "    print(f\"  {f:25s} → {desc}\")\n",
    "print(f\"\\nGPC Source: https://www.google.com/basepages/producttype/taxonomy.en-US.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a13a3db6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:20.983019Z",
     "iopub.status.busy": "2026-08-01T17:42:20.981208Z",
     "iopub.status.idle": "2026-08-01T17:42:21.048773Z",
     "shell.execute_reply": "2026-08-01T17:42:21.045364Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "  Phase 3 — non_food_products.csv (non-food items)\n",
      "  Shape: 394 rows × 12 columns\n",
      "============================================================\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>external_id</th>\n",
       "      <th>upc</th>\n",
       "      <th>group_id</th>\n",
       "      <th>group_name</th>\n",
       "      <th>core_title</th>\n",
       "      <th>original_title</th>\n",
       "      <th>brand</th>\n",
       "      <th>size</th>\n",
       "      <th>reference_db_taxonomy</th>\n",
       "      <th>product_line</th>\n",
       "      <th>source</th>\n",
       "      <th>source_url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>276882EA</td>\n",
       "      <td>6.748980e+10</td>\n",
       "      <td>30858e26-97e6-5354-8f74-cebf1acf3c4b</td>\n",
       "      <td>Kitchen Garbage Bags Regular 22 L 100 Bags</td>\n",
       "      <td>Kitchen Garbage Bags Regular 22 L 100 Bags</td>\n",
       "      <td>Compliments Kitchen Garbage Bags Regular 22 L ...</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>100 per pack</td>\n",
       "      <td>GENERAL_GROCERY</td>\n",
       "      <td>Core</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-kitchen-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>161468EA</td>\n",
       "      <td>8.402431e+11</td>\n",
       "      <td>4eaafe64-1991-5408-877d-472cc546c231</td>\n",
       "      <td>Cat Food Flaked Tuna Platter</td>\n",
       "      <td>Cat Food Flaked Tuna Platter</td>\n",
       "      <td>Compliments Cat Food Flaked Tuna Platter 85 g</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>85g</td>\n",
       "      <td>MEAT_SEAFOOD</td>\n",
       "      <td>Core</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-cat-food...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>349079EA</td>\n",
       "      <td>5.574253e+10</td>\n",
       "      <td>c9dbf951-b81a-56f6-822c-e60d9b13c431</td>\n",
       "      <td>Day And Night Flu Cough &amp; Cold</td>\n",
       "      <td>Day And Night Flu Cough &amp; Cold</td>\n",
       "      <td>Compliments Day And Night Flu Cough &amp; Cold 24 ...</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>24 per pack</td>\n",
       "      <td>GENERAL_GROCERY</td>\n",
       "      <td>Core</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-day-and-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>280747EA</td>\n",
       "      <td>5.574256e+10</td>\n",
       "      <td>96439cd0-42bd-51e6-96f3-9fb805d84edd</td>\n",
       "      <td>Pill and Vitamin Planner Extra Large</td>\n",
       "      <td>Pill and Vitamin Planner Extra Large</td>\n",
       "      <td>Compliments Pill and Vitamin Planner Extra Lar...</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>NaN</td>\n",
       "      <td>HEALTH_REMEDIES</td>\n",
       "      <td>Core</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-pill-and...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>691892EA</td>\n",
       "      <td>3.700031e+10</td>\n",
       "      <td>fe8b62f2-f101-5319-943e-9f02feb9402e</td>\n",
       "      <td>Maxi Pads Super Long With Wings</td>\n",
       "      <td>Maxi Pads Super Long With Wings</td>\n",
       "      <td>Compliments Maxi Pads Super Long With Wings 16...</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>16 per pack</td>\n",
       "      <td>GENERAL_GROCERY</td>\n",
       "      <td>Core</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-maxi-pad...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  external_id           upc                              group_id  \\\n",
       "0    276882EA  6.748980e+10  30858e26-97e6-5354-8f74-cebf1acf3c4b   \n",
       "1    161468EA  8.402431e+11  4eaafe64-1991-5408-877d-472cc546c231   \n",
       "2    349079EA  5.574253e+10  c9dbf951-b81a-56f6-822c-e60d9b13c431   \n",
       "3    280747EA  5.574256e+10  96439cd0-42bd-51e6-96f3-9fb805d84edd   \n",
       "4    691892EA  3.700031e+10  fe8b62f2-f101-5319-943e-9f02feb9402e   \n",
       "\n",
       "                                   group_name  \\\n",
       "0  Kitchen Garbage Bags Regular 22 L 100 Bags   \n",
       "1                Cat Food Flaked Tuna Platter   \n",
       "2              Day And Night Flu Cough & Cold   \n",
       "3        Pill and Vitamin Planner Extra Large   \n",
       "4             Maxi Pads Super Long With Wings   \n",
       "\n",
       "                                   core_title  \\\n",
       "0  Kitchen Garbage Bags Regular 22 L 100 Bags   \n",
       "1                Cat Food Flaked Tuna Platter   \n",
       "2              Day And Night Flu Cough & Cold   \n",
       "3        Pill and Vitamin Planner Extra Large   \n",
       "4             Maxi Pads Super Long With Wings   \n",
       "\n",
       "                                      original_title        brand  \\\n",
       "0  Compliments Kitchen Garbage Bags Regular 22 L ...  Compliments   \n",
       "1      Compliments Cat Food Flaked Tuna Platter 85 g  Compliments   \n",
       "2  Compliments Day And Night Flu Cough & Cold 24 ...  Compliments   \n",
       "3  Compliments Pill and Vitamin Planner Extra Lar...  Compliments   \n",
       "4  Compliments Maxi Pads Super Long With Wings 16...  Compliments   \n",
       "\n",
       "           size reference_db_taxonomy product_line source  \\\n",
       "0  100 per pack       GENERAL_GROCERY         Core  voila   \n",
       "1           85g          MEAT_SEAFOOD         Core  voila   \n",
       "2   24 per pack       GENERAL_GROCERY         Core  voila   \n",
       "3           NaN       HEALTH_REMEDIES         Core  voila   \n",
       "4   16 per pack       GENERAL_GROCERY         Core  voila   \n",
       "\n",
       "                                          source_url  \n",
       "0  https://voila.ca/products/compliments-kitchen-...  \n",
       "1  https://voila.ca/products/compliments-cat-food...  \n",
       "2  https://voila.ca/products/compliments-day-and-...  \n",
       "3  https://voila.ca/products/compliments-pill-and...  \n",
       "4  https://voila.ca/products/compliments-maxi-pad...  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Columns (12):\n",
      "  external_id                         str        nulls=    0  uniques=394\n",
      "  upc                                 float64    nulls=    1  uniques=308\n",
      "  group_id                            str        nulls=    0  uniques=332\n",
      "  group_name                          str        nulls=    0  uniques=376\n",
      "  core_title                          str        nulls=    0  uniques=376\n",
      "  original_title                      str        nulls=    0  uniques=390\n",
      "  brand                               str        nulls=    0  uniques=1\n",
      "  size                                str        nulls=   65  uniques=101\n",
      "  reference_db_taxonomy               str        nulls=    0  uniques=14\n",
      "  product_line                        str        nulls=    0  uniques=2\n",
      "  source                              str        nulls=    0  uniques=1\n",
      "  source_url                          str        nulls=    0  uniques=394\n"
     ]
    }
   ],
   "source": [
    "show_table(non_food, \"Phase 3 — non_food_products.csv (non-food items)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3a1bf2c7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:21.056249Z",
     "iopub.status.busy": "2026-08-01T17:42:21.055006Z",
     "iopub.status.idle": "2026-08-01T17:42:24.191587Z",
     "shell.execute_reply": "2026-08-01T17:42:24.187687Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Phase 3 — Domain + Taxonomy Distribution\n",
    "fig, axes = plt.subplots(1, 3, figsize=(18, 5))\n",
    "\n",
    "mapping['product_domain'].value_counts().plot(kind='pie', ax=axes[0], autopct='%1.1f%%', colors=COLORS[:3])\n",
    "axes[0].set_title('Phase 3 — Product Domain', fontsize=12)\n",
    "axes[0].set_ylabel('')\n",
    "\n",
    "mapping['reference_db_taxonomy'].value_counts().plot(kind='barh', ax=axes[1], color=COLORS[0])\n",
    "axes[1].set_title('Phase 3 — Taxonomy Distribution', fontsize=12)\n",
    "axes[1].set_xlabel('Count')\n",
    "\n",
    "catalog['product_count'].describe().plot(kind='bar', ax=axes[2], color=COLORS[3])\n",
    "axes[2].set_title('Phase 3 — Products per Group (stats)', fontsize=12)\n",
    "axes[2].set_ylabel('Count')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "082e8ac8",
   "metadata": {},
   "source": [
    "---\n",
    "# Phase 4 — Variant Assignment\n",
    "\n",
    "**Goal:** Assign variant IDs to products based on size/package attributes.\n",
    "\n",
    "**Input:** Phase 3 mapping + Phase 2 output\n",
    "**Output:** `product_variant_mapping.parquet` (4,440 × 11) + `reference_product_variants.parquet` (4,299)\n",
    "\n",
    "### What Happens\n",
    "1. Build variant key from size/package attributes\n",
    "2. Generate deterministic variant ID (UUID5 from group_id + variant_key)\n",
    "3. Build variant table (one row per unique variant)\n",
    "4. Build product → variant mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f0c1c048",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:24.200070Z",
     "iopub.status.busy": "2026-08-01T17:42:24.199466Z",
     "iopub.status.idle": "2026-08-01T17:42:28.457239Z",
     "shell.execute_reply": "2026-08-01T17:42:28.455425Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "890294e1f5414100bdbfcc9d3ef30e09",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "phase4/outputs/reference_product_variant(…): reconstructing file:   0%|          |  0.00B /  643kB            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d130d8dfbf2545b8a7c52c774071b541",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "phase4/outputs/reference_product_variant(…): downloading bytes:           |  0.00B            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "  Phase 4 — product_variant_mapping.parquet (product → variant)\n",
      "  Shape: 4440 rows × 11 columns\n",
      "============================================================\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>external_id</th>\n",
       "      <th>upc</th>\n",
       "      <th>group_id</th>\n",
       "      <th>variant_id</th>\n",
       "      <th>core_title</th>\n",
       "      <th>original_title</th>\n",
       "      <th>brand</th>\n",
       "      <th>size</th>\n",
       "      <th>variant_key</th>\n",
       "      <th>source</th>\n",
       "      <th>source_url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>297608EA</td>\n",
       "      <td>5.574252e+10</td>\n",
       "      <td>27b951a3-bef1-5ed4-80b7-7ef5cdca910a</td>\n",
       "      <td>2463d0b1-fd1e-5668-9d76-c5cfde65d5f0</td>\n",
       "      <td>Cold And Sinus Plus</td>\n",
       "      <td>Compliments Cold And Sinus Plus 20 Count</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>20 per pack</td>\n",
       "      <td>count20</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-cold-and...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>464324EA</td>\n",
       "      <td>5.574234e+10</td>\n",
       "      <td>e608ba58-8f93-59f1-9446-edb91aef79bd</td>\n",
       "      <td>1a0b7440-8644-598f-bb67-aeb45ee17a25</td>\n",
       "      <td>Twister T2 Light Bulbs 23W Soft White</td>\n",
       "      <td>Compliments Twister T2 Light Bulbs 23W Soft Wh...</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>2 per pack</td>\n",
       "      <td>count2</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-twister-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>144288CS</td>\n",
       "      <td>9.900026e+11</td>\n",
       "      <td>336c79d8-796d-5682-8195-793883dd97ef</td>\n",
       "      <td>dcea4514-bc10-50ca-90df-34fd41cd20ef</td>\n",
       "      <td>Zero Calorie Soft Drink</td>\n",
       "      <td>Compliments Zero Calorie Soft Drink 12 x 355ml</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>12 x 29.583ml</td>\n",
       "      <td>amt29.583|unitml|qty12</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-zero-cal...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>312204EA</td>\n",
       "      <td>5.574257e+10</td>\n",
       "      <td>34baf35c-0ee4-5907-9e0f-e8954e34aa11</td>\n",
       "      <td>96e75eff-a7db-59bd-a30f-d592def3e78c</td>\n",
       "      <td>Kalamata Whole Olives</td>\n",
       "      <td>Compliments Kalamata Whole Olives 375 ml</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>375ml</td>\n",
       "      <td>amt375.0|unitml</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-kalamata...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>259928EA</td>\n",
       "      <td>5.574256e+10</td>\n",
       "      <td>4ff536c8-c957-5fe8-8faa-3f539d6048ef</td>\n",
       "      <td>e06da50f-2c99-527d-a0a2-7b7c05887153</td>\n",
       "      <td>Sliced Almonds</td>\n",
       "      <td>Compliments Sliced Almonds 250 g</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>250g</td>\n",
       "      <td>amt250.0|unitg</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-sliced-a...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  external_id           upc                              group_id  \\\n",
       "0    297608EA  5.574252e+10  27b951a3-bef1-5ed4-80b7-7ef5cdca910a   \n",
       "1    464324EA  5.574234e+10  e608ba58-8f93-59f1-9446-edb91aef79bd   \n",
       "2    144288CS  9.900026e+11  336c79d8-796d-5682-8195-793883dd97ef   \n",
       "3    312204EA  5.574257e+10  34baf35c-0ee4-5907-9e0f-e8954e34aa11   \n",
       "4    259928EA  5.574256e+10  4ff536c8-c957-5fe8-8faa-3f539d6048ef   \n",
       "\n",
       "                             variant_id  \\\n",
       "0  2463d0b1-fd1e-5668-9d76-c5cfde65d5f0   \n",
       "1  1a0b7440-8644-598f-bb67-aeb45ee17a25   \n",
       "2  dcea4514-bc10-50ca-90df-34fd41cd20ef   \n",
       "3  96e75eff-a7db-59bd-a30f-d592def3e78c   \n",
       "4  e06da50f-2c99-527d-a0a2-7b7c05887153   \n",
       "\n",
       "                              core_title  \\\n",
       "0                    Cold And Sinus Plus   \n",
       "1  Twister T2 Light Bulbs 23W Soft White   \n",
       "2                Zero Calorie Soft Drink   \n",
       "3                  Kalamata Whole Olives   \n",
       "4                         Sliced Almonds   \n",
       "\n",
       "                                      original_title        brand  \\\n",
       "0           Compliments Cold And Sinus Plus 20 Count  Compliments   \n",
       "1  Compliments Twister T2 Light Bulbs 23W Soft Wh...  Compliments   \n",
       "2     Compliments Zero Calorie Soft Drink 12 x 355ml  Compliments   \n",
       "3           Compliments Kalamata Whole Olives 375 ml  Compliments   \n",
       "4                   Compliments Sliced Almonds 250 g  Compliments   \n",
       "\n",
       "            size             variant_key source  \\\n",
       "0    20 per pack                 count20  voila   \n",
       "1     2 per pack                  count2  voila   \n",
       "2  12 x 29.583ml  amt29.583|unitml|qty12  voila   \n",
       "3          375ml         amt375.0|unitml  voila   \n",
       "4           250g          amt250.0|unitg  voila   \n",
       "\n",
       "                                          source_url  \n",
       "0  https://voila.ca/products/compliments-cold-and...  \n",
       "1  https://voila.ca/products/compliments-twister-...  \n",
       "2  https://voila.ca/products/compliments-zero-cal...  \n",
       "3  https://voila.ca/products/compliments-kalamata...  \n",
       "4  https://voila.ca/products/compliments-sliced-a...  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Columns (11):\n",
      "  external_id                         str        nulls=    0  uniques=4440\n",
      "  upc                                 float64    nulls=    1  uniques=3271\n",
      "  group_id                            str        nulls=    0  uniques=3691\n",
      "  variant_id                          str        nulls=    0  uniques=4299\n",
      "  core_title                          str        nulls=    0  uniques=4070\n",
      "  original_title                      str        nulls=    0  uniques=4375\n",
      "  brand                               str        nulls=    0  uniques=2\n",
      "  size                                str        nulls=  215  uniques=630\n",
      "  variant_key                         str        nulls=    0  uniques=631\n",
      "  source                              str        nulls=    0  uniques=1\n",
      "  source_url                          str        nulls=    0  uniques=4440\n"
     ]
    }
   ],
   "source": [
    "p4_map = load(\"phase4/outputs/product_variant_mapping.parquet\")\n",
    "p4_var = load(\"phase4/outputs/reference_product_variants.parquet\")\n",
    "\n",
    "show_table(p4_map, \"Phase 4 — product_variant_mapping.parquet (product → variant)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d0c7e114",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:28.467134Z",
     "iopub.status.busy": "2026-08-01T17:42:28.466545Z",
     "iopub.status.idle": "2026-08-01T17:42:28.482430Z",
     "shell.execute_reply": "2026-08-01T17:42:28.480762Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Product Variant Mapping Fields:\n",
      "--------------------------------------------------------------------------------\n",
      "  external_id       → Product-level identifier\n",
      "  upc               → Product barcode\n",
      "  group_id          → Group UUID\n",
      "  variant_id        → Variant UUID (deterministic from group_id + variant_key)\n",
      "  core_title        → Normalized core title\n",
      "  original_title    → Original product title\n",
      "  brand             → Brand name\n",
      "  size              → Raw size string\n",
      "  variant_key       → Variant key string (amt500|unitg, amt1|unitkg, nosize, etc.)\n",
      "  source            → Data source\n",
      "  source_url        → Source URL\n"
     ]
    }
   ],
   "source": [
    "# Variant Mapping Fields\n",
    "print(\"Product Variant Mapping Fields:\")\n",
    "print(\"-\" * 80)\n",
    "vmap_fields = {\n",
    "    \"external_id\":   \"Product-level identifier\",\n",
    "    \"upc\":           \"Product barcode\",\n",
    "    \"group_id\":      \"Group UUID\",\n",
    "    \"variant_id\":    \"Variant UUID (deterministic from group_id + variant_key)\",\n",
    "    \"core_title\":    \"Normalized core title\",\n",
    "    \"original_title\":\"Original product title\",\n",
    "    \"brand\":         \"Brand name\",\n",
    "    \"size\":          \"Raw size string\",\n",
    "    \"variant_key\":   \"Variant key string (amt500|unitg, amt1|unitkg, nosize, etc.)\",\n",
    "    \"source\":        \"Data source\",\n",
    "    \"source_url\":    \"Source URL\"\n",
    "}\n",
    "for f, desc in vmap_fields.items():\n",
    "    print(f\"  {f:17s} → {desc}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9944b64c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:28.493101Z",
     "iopub.status.busy": "2026-08-01T17:42:28.492509Z",
     "iopub.status.idle": "2026-08-01T17:42:28.663031Z",
     "shell.execute_reply": "2026-08-01T17:42:28.658805Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "  Phase 4 — reference_product_variants.parquet (one row per variant)\n",
      "  Shape: 4299 rows × 21 columns\n",
      "============================================================\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>variant_id</th>\n",
       "      <th>group_id</th>\n",
       "      <th>group_name</th>\n",
       "      <th>brand</th>\n",
       "      <th>product_line</th>\n",
       "      <th>product_domain</th>\n",
       "      <th>taxonomy</th>\n",
       "      <th>core_title</th>\n",
       "      <th>variant_key</th>\n",
       "      <th>size</th>\n",
       "      <th>...</th>\n",
       "      <th>size_unit</th>\n",
       "      <th>size_qty</th>\n",
       "      <th>flavour</th>\n",
       "      <th>formulation</th>\n",
       "      <th>fat_level</th>\n",
       "      <th>fat_percentage</th>\n",
       "      <th>product_count</th>\n",
       "      <th>unique_upcs</th>\n",
       "      <th>source</th>\n",
       "      <th>source_url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>00030337-9c4f-5885-8300-471956e7fe5b</td>\n",
       "      <td>3cedb57a-5ab0-57b2-8bfe-0c16478aef5a</td>\n",
       "      <td>2% Anti-Itch Cream Diphenhydramine Hydrochloride</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Core</td>\n",
       "      <td>non_food</td>\n",
       "      <td>DAIRY</td>\n",
       "      <td>2% Anti-Itch Cream Diphenhydramine Hydrochloride</td>\n",
       "      <td>amt30.0|unitg</td>\n",
       "      <td>30g</td>\n",
       "      <td>...</td>\n",
       "      <td>g</td>\n",
       "      <td>1</td>\n",
       "      <td>[lime]</td>\n",
       "      <td>[]</td>\n",
       "      <td>regular</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-2-anti-i...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0007523d-4602-58ee-8629-f749a8f368f9</td>\n",
       "      <td>7281f6c9-675f-5a59-a190-6101a4a5b57c</td>\n",
       "      <td>Seasoning Montreal Steak Rub</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Core</td>\n",
       "      <td>food</td>\n",
       "      <td>MEAT_SEAFOOD</td>\n",
       "      <td>Seasoning Montreal Steak Rub</td>\n",
       "      <td>amt275.0|unitml</td>\n",
       "      <td>275ml</td>\n",
       "      <td>...</td>\n",
       "      <td>ml</td>\n",
       "      <td>1</td>\n",
       "      <td>[lime]</td>\n",
       "      <td>[]</td>\n",
       "      <td>regular</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-seasonin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>00105f30-fcbc-53bb-ac22-06cccf3d02e7</td>\n",
       "      <td>76f81bfc-a44f-53f5-8d1e-b381dcddb996</td>\n",
       "      <td>Regular Nail Polish Remover</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Core</td>\n",
       "      <td>non_food</td>\n",
       "      <td>PERSONAL_CARE</td>\n",
       "      <td>Regular Nail Polish Remover</td>\n",
       "      <td>amt300.0|unitml</td>\n",
       "      <td>300ml</td>\n",
       "      <td>...</td>\n",
       "      <td>ml</td>\n",
       "      <td>1</td>\n",
       "      <td>[lime]</td>\n",
       "      <td>[]</td>\n",
       "      <td>regular</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-regular-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>001761dc-85c4-5207-8abc-f8215bade3eb</td>\n",
       "      <td>53b3f131-976c-5501-b330-1f751175e906</td>\n",
       "      <td>Sandwich Spread Sriracha Mayo</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Core</td>\n",
       "      <td>food</td>\n",
       "      <td>GENERAL_GROCERY</td>\n",
       "      <td>Sandwich Spread Sriracha Mayo</td>\n",
       "      <td>amt300.0|unitml</td>\n",
       "      <td>300ml</td>\n",
       "      <td>...</td>\n",
       "      <td>ml</td>\n",
       "      <td>1</td>\n",
       "      <td>[lime]</td>\n",
       "      <td>[]</td>\n",
       "      <td>regular</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-sandwich...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>003fae72-9ee3-5273-a3b7-f5e413383a97</td>\n",
       "      <td>83d52dd1-4a30-5e5a-888d-835742dc77e0</td>\n",
       "      <td>Whole Hazelnuts</td>\n",
       "      <td>Compliments</td>\n",
       "      <td>Core</td>\n",
       "      <td>unknown</td>\n",
       "      <td>GENERAL_GROCERY</td>\n",
       "      <td>Whole Hazelnuts</td>\n",
       "      <td>amt100.0|unitg</td>\n",
       "      <td>100g</td>\n",
       "      <td>...</td>\n",
       "      <td>g</td>\n",
       "      <td>1</td>\n",
       "      <td>[lime]</td>\n",
       "      <td>[whole]</td>\n",
       "      <td>regular</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>voila</td>\n",
       "      <td>https://voila.ca/products/compliments-whole-ha...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                             variant_id                              group_id  \\\n",
       "0  00030337-9c4f-5885-8300-471956e7fe5b  3cedb57a-5ab0-57b2-8bfe-0c16478aef5a   \n",
       "1  0007523d-4602-58ee-8629-f749a8f368f9  7281f6c9-675f-5a59-a190-6101a4a5b57c   \n",
       "2  00105f30-fcbc-53bb-ac22-06cccf3d02e7  76f81bfc-a44f-53f5-8d1e-b381dcddb996   \n",
       "3  001761dc-85c4-5207-8abc-f8215bade3eb  53b3f131-976c-5501-b330-1f751175e906   \n",
       "4  003fae72-9ee3-5273-a3b7-f5e413383a97  83d52dd1-4a30-5e5a-888d-835742dc77e0   \n",
       "\n",
       "                                         group_name        brand product_line  \\\n",
       "0  2% Anti-Itch Cream Diphenhydramine Hydrochloride  Compliments         Core   \n",
       "1                      Seasoning Montreal Steak Rub  Compliments         Core   \n",
       "2                       Regular Nail Polish Remover  Compliments         Core   \n",
       "3                     Sandwich Spread Sriracha Mayo  Compliments         Core   \n",
       "4                                   Whole Hazelnuts  Compliments         Core   \n",
       "\n",
       "  product_domain         taxonomy  \\\n",
       "0       non_food            DAIRY   \n",
       "1           food     MEAT_SEAFOOD   \n",
       "2       non_food    PERSONAL_CARE   \n",
       "3           food  GENERAL_GROCERY   \n",
       "4        unknown  GENERAL_GROCERY   \n",
       "\n",
       "                                         core_title      variant_key   size  \\\n",
       "0  2% Anti-Itch Cream Diphenhydramine Hydrochloride    amt30.0|unitg    30g   \n",
       "1                      Seasoning Montreal Steak Rub  amt275.0|unitml  275ml   \n",
       "2                       Regular Nail Polish Remover  amt300.0|unitml  300ml   \n",
       "3                     Sandwich Spread Sriracha Mayo  amt300.0|unitml  300ml   \n",
       "4                                   Whole Hazelnuts   amt100.0|unitg   100g   \n",
       "\n",
       "   ...  size_unit size_qty  flavour formulation fat_level fat_percentage  \\\n",
       "0  ...          g        1   [lime]          []   regular            2.0   \n",
       "1  ...         ml        1   [lime]          []   regular            NaN   \n",
       "2  ...         ml        1   [lime]          []   regular            NaN   \n",
       "3  ...         ml        1   [lime]          []   regular            NaN   \n",
       "4  ...          g        1   [lime]     [whole]   regular            NaN   \n",
       "\n",
       "   product_count  unique_upcs  source  \\\n",
       "0              1            1   voila   \n",
       "1              1            1   voila   \n",
       "2              1            1   voila   \n",
       "3              1            1   voila   \n",
       "4              1            1   voila   \n",
       "\n",
       "                                          source_url  \n",
       "0  https://voila.ca/products/compliments-2-anti-i...  \n",
       "1  https://voila.ca/products/compliments-seasonin...  \n",
       "2  https://voila.ca/products/compliments-regular-...  \n",
       "3  https://voila.ca/products/compliments-sandwich...  \n",
       "4  https://voila.ca/products/compliments-whole-ha...  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Columns (21):\n",
      "  variant_id                          str        nulls=    0  uniques=4299\n",
      "  group_id                            str        nulls=    0  uniques=3691\n",
      "  group_name                          str        nulls=    0  uniques=4000\n",
      "  brand                               str        nulls=    0  uniques=2\n",
      "  product_line                        str        nulls=    0  uniques=7\n",
      "  product_domain                      str        nulls=    0  uniques=3\n",
      "  taxonomy                            str        nulls=    0  uniques=19\n",
      "  core_title                          str        nulls=    0  uniques=4000\n",
      "  variant_key                         str        nulls=    0  uniques=631\n",
      "  size                                str        nulls=    0  uniques=631\n",
      "  size_amount                         float64    nulls=  284  uniques=387\n",
      "  size_unit                           str        nulls=  284  uniques=5\n",
      "  size_qty                            int64      nulls=    0  uniques=17\n",
      "  flavour                             object     nulls=    0  uniques=N/A\n",
      "  formulation                         object     nulls=    0  uniques=N/A\n",
      "  fat_level                           str        nulls=    0  uniques=3\n",
      "  fat_percentage                      float64    nulls= 4251  uniques=19\n",
      "  product_count                       int64      nulls=    0  uniques=4\n",
      "  unique_upcs                         int64      nulls=    0  uniques=4\n",
      "  source                              str        nulls=    0  uniques=1\n",
      "  source_url                          str        nulls=    0  uniques=4299\n"
     ]
    }
   ],
   "source": [
    "show_table(p4_var, \"Phase 4 — reference_product_variants.parquet (one row per variant)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2c160c4a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:28.679860Z",
     "iopub.status.busy": "2026-08-01T17:42:28.675595Z",
     "iopub.status.idle": "2026-08-01T17:42:28.727785Z",
     "shell.execute_reply": "2026-08-01T17:42:28.715984Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reference Product Variant Fields:\n",
      "--------------------------------------------------------------------------------\n",
      "  variant_id             → Variant UUID\n",
      "  group_id               → Group UUID\n",
      "  group_name             → Group name\n",
      "  brand                  → Brand name\n",
      "  product_line           → Product line\n",
      "  product_domain         → food / non_food / unknown\n",
      "  reference_db_taxonomy  → Category\n",
      "  core_title             → Normalized core title\n",
      "  variant_key            → Variant key string\n",
      "  size                   → Size string\n",
      "  size_amount            → Numeric size\n",
      "  size_unit              → Size unit\n",
      "  flavour                → Flavour keywords\n",
      "  formulation            → Formulation keywords\n",
      "  fat_level              → Fat level\n",
      "  fat_percentage         → Fat percentage\n",
      "  product_count          → Products in this variant\n",
      "  unique_upcs            → Unique UPCs in this variant\n"
     ]
    }
   ],
   "source": [
    "# Variant Table Fields\n",
    "print(\"Reference Product Variant Fields:\")\n",
    "print(\"-\" * 80)\n",
    "var_fields = {\n",
    "    \"variant_id\":         \"Variant UUID\",\n",
    "    \"group_id\":           \"Group UUID\",\n",
    "    \"group_name\":         \"Group name\",\n",
    "    \"brand\":              \"Brand name\",\n",
    "    \"product_line\":       \"Product line\",\n",
    "    \"product_domain\":     \"food / non_food / unknown\",\n",
    "    \"reference_db_taxonomy\": \"Category\",\n",
    "    \"core_title\":         \"Normalized core title\",\n",
    "    \"variant_key\":        \"Variant key string\",\n",
    "    \"size\":               \"Size string\",\n",
    "    \"size_amount\":        \"Numeric size\",\n",
    "    \"size_unit\":          \"Size unit\",\n",
    "    \"flavour\":            \"Flavour keywords\",\n",
    "    \"formulation\":        \"Formulation keywords\",\n",
    "    \"fat_level\":          \"Fat level\",\n",
    "    \"fat_percentage\":     \"Fat percentage\",\n",
    "    \"product_count\":      \"Products in this variant\",\n",
    "    \"unique_upcs\":        \"Unique UPCs in this variant\"\n",
    "}\n",
    "for f, desc in var_fields.items():\n",
    "    print(f\"  {f:22s} → {desc}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d064b003",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:28.741869Z",
     "iopub.status.busy": "2026-08-01T17:42:28.741111Z",
     "iopub.status.idle": "2026-08-01T17:42:30.108128Z",
     "shell.execute_reply": "2026-08-01T17:42:30.101391Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Phase 4 — Variant Distribution\n",
    "fig, axes = plt.subplots(1, 2, figsize=(14, 5))\n",
    "\n",
    "variant_counts = p4_map.groupby('group_id')['variant_id'].nunique()\n",
    "variant_counts.value_counts().sort_index().plot(kind='bar', ax=axes[0], color=COLORS[4])\n",
    "axes[0].set_title('Phase 4 — Variants per Group', fontsize=12)\n",
    "axes[0].set_xlabel('Number of Variants')\n",
    "axes[0].set_ylabel('Number of Groups')\n",
    "\n",
    "p4_var['product_count'].describe().plot(kind='bar', ax=axes[1], color=COLORS[5])\n",
    "axes[1].set_title('Phase 4 — Products per Variant (stats)', fontsize=12)\n",
    "axes[1].set_ylabel('Count')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6e42644",
   "metadata": {},
   "source": [
    "---\n",
    "# Phase 5 — Nutrition Integration\n",
    "\n",
    "**Goal:** Match nutrition data to products, normalize per-100g, validate 1:1 relationship.\n",
    "\n",
    "**Input:** nutrition.parquet + Phase 3 mapping + Phase 4 mapping\n",
    "**Output:** 3 Parquet files — per-100g, cleaned, product-nutrition mapping\n",
    "\n",
    "### What Happens\n",
    "1. Load nutrition data (4,440 × 21) from HuggingFace\n",
    "2. Clean & validate (flag MISSING, SUSPICIOUS)\n",
    "3. Normalize to per-100g/mL (direct, scaled, or not normalized)\n",
    "4. Match products to nutrition by external_id (100% deterministic)\n",
    "5. Join with Phase 3 (group_id) and Phase 4 (variant_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ff632e58",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:30.121826Z",
     "iopub.status.busy": "2026-08-01T17:42:30.121160Z",
     "iopub.status.idle": "2026-08-01T17:42:32.554196Z",
     "shell.execute_reply": "2026-08-01T17:42:32.550930Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0bcb1d9b5ebe40aebd2074de10cfc6c3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "phase5/outputs/nutrition_per_100g.parque(…): reconstructing file:   0%|          |  0.00B /  138kB            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f617083bcfee49918ed379c11e1594de",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "phase5/outputs/nutrition_per_100g.parque(…): downloading bytes:           |  0.00B            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "  Phase 5 — nutrition_per_100g.parquet\n",
      "  Shape: 4440 rows × 24 columns\n",
      "============================================================\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>external_id</th>\n",
       "      <th>upc</th>\n",
       "      <th>serving_size</th>\n",
       "      <th>serving_amount</th>\n",
       "      <th>serving_unit</th>\n",
       "      <th>normalization_method</th>\n",
       "      <th>normalization_reason</th>\n",
       "      <th>calories_per_100g</th>\n",
       "      <th>carbohydrate_g_per_100g</th>\n",
       "      <th>sugars_g_per_100g</th>\n",
       "      <th>...</th>\n",
       "      <th>polyunsaturated_fat_g_per_100g</th>\n",
       "      <th>omega6_g_per_100g</th>\n",
       "      <th>omega3_g_per_100g</th>\n",
       "      <th>monounsaturated_fat_g_per_100g</th>\n",
       "      <th>sugar_alcohols_g_per_100g</th>\n",
       "      <th>fibre_g_per_100g</th>\n",
       "      <th>protein_g_per_100g</th>\n",
       "      <th>calcium_mg_per_100g</th>\n",
       "      <th>iron_mg_per_100g</th>\n",
       "      <th>cholesterol_mg_per_100g</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>not_normalized</td>\n",
       "      <td>serving_size is missing</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>not_normalized</td>\n",
       "      <td>serving_size is missing</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>144288CS</td>\n",
       "      <td>990002600400</td>\n",
       "      <td>355 mL</td>\n",
       "      <td>355.0</td>\n",
       "      <td>mL</td>\n",
       "      <td>scaled_to_100g</td>\n",
       "      <td>scaled from serving_size to 100g/mL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  external_id           upc serving_size  serving_amount serving_unit  \\\n",
       "0    297608EA  055742522167          NaN             NaN          NaN   \n",
       "1    464324EA  055742335200          NaN             NaN          NaN   \n",
       "2    144288CS  990002600400       355 mL           355.0           mL   \n",
       "\n",
       "  normalization_method                 normalization_reason  \\\n",
       "0       not_normalized              serving_size is missing   \n",
       "1       not_normalized              serving_size is missing   \n",
       "2       scaled_to_100g  scaled from serving_size to 100g/mL   \n",
       "\n",
       "   calories_per_100g  carbohydrate_g_per_100g  sugars_g_per_100g  ...  \\\n",
       "0                NaN                      NaN                NaN  ...   \n",
       "1                NaN                      NaN                NaN  ...   \n",
       "2                NaN                      NaN                NaN  ...   \n",
       "\n",
       "   polyunsaturated_fat_g_per_100g  omega6_g_per_100g  omega3_g_per_100g  \\\n",
       "0                             NaN                NaN                NaN   \n",
       "1                             NaN                NaN                NaN   \n",
       "2                             NaN                NaN                NaN   \n",
       "\n",
       "   monounsaturated_fat_g_per_100g  sugar_alcohols_g_per_100g  \\\n",
       "0                             NaN                        NaN   \n",
       "1                             NaN                        NaN   \n",
       "2                             NaN                        NaN   \n",
       "\n",
       "   fibre_g_per_100g  protein_g_per_100g  calcium_mg_per_100g  \\\n",
       "0               NaN                 NaN                  NaN   \n",
       "1               NaN                 NaN                  NaN   \n",
       "2               NaN                 NaN                  NaN   \n",
       "\n",
       "   iron_mg_per_100g  cholesterol_mg_per_100g  \n",
       "0               NaN                      NaN  \n",
       "1               NaN                      NaN  \n",
       "2               NaN                      NaN  \n",
       "\n",
       "[3 rows x 24 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Columns (24):\n",
      "  external_id                         str        nulls=    0  uniques=4440\n",
      "  upc                                 str        nulls=    1  uniques=3271\n",
      "  serving_size                        str        nulls= 1505  uniques=566\n",
      "  serving_amount                      float64    nulls= 1975  uniques=133\n",
      "  serving_unit                        str        nulls= 1975  uniques=88\n",
      "  normalization_method                str        nulls=    0  uniques=3\n",
      "  normalization_reason                str        nulls=    0  uniques=4\n",
      "  calories_per_100g                   float64    nulls= 3005  uniques=406\n",
      "  carbohydrate_g_per_100g             float64    nulls= 3146  uniques=449\n",
      "  sugars_g_per_100g                   float64    nulls= 3423  uniques=322\n",
      "  sodium_mg_per_100g                  float64    nulls= 3184  uniques=531\n",
      "  potassium_mg_per_100g               float64    nulls= 3220  uniques=294\n",
      "  fat_g_per_100g                      float64    nulls= 3317  uniques=366\n",
      "  saturated_fat_g_per_100g            float64    nulls= 3412  uniques=276\n",
      "  polyunsaturated_fat_g_per_100g      float64    nulls= 4383  uniques=17\n",
      "  omega6_g_per_100g                   float64    nulls= 4405  uniques=11\n",
      "  omega3_g_per_100g                   float64    nulls= 4413  uniques=8\n",
      "  monounsaturated_fat_g_per_100g      float64    nulls= 4405  uniques=10\n",
      "  sugar_alcohols_g_per_100g           float64    nulls= 4383  uniques=1\n",
      "  fibre_g_per_100g                    float64    nulls= 3593  uniques=152\n",
      "  protein_g_per_100g                  float64    nulls= 3142  uniques=279\n",
      "  calcium_mg_per_100g                 float64    nulls= 4321  uniques=33\n",
      "  iron_mg_per_100g                    float64    nulls= 4314  uniques=41\n",
      "  cholesterol_mg_per_100g             float64    nulls= 3850  uniques=177\n"
     ]
    }
   ],
   "source": [
    "p5_100g = load(\"phase5/outputs/nutrition_per_100g.parquet\")\n",
    "show_table(p5_100g, \"Phase 5 — nutrition_per_100g.parquet\", n=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "26b1b2f7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:32.562252Z",
     "iopub.status.busy": "2026-08-01T17:42:32.559472Z",
     "iopub.status.idle": "2026-08-01T17:42:32.580594Z",
     "shell.execute_reply": "2026-08-01T17:42:32.577366Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nutrition Per 100g Fields:\n",
      "--------------------------------------------------------------------------------\n",
      "  external_id                         → Product-level identifier\n",
      "  upc                                 → Product barcode\n",
      "  serving_size                        → Raw serving size string (e.g. '30 g', '100 mL')\n",
      "  serving_amount                      → Parsed numeric amount\n",
      "  serving_unit                        → Parsed unit (g, mL, etc.)\n",
      "  normalization_method                → direct_100g / scaled_to_100g / not_normalized\n",
      "  normalization_reason                → Why this method was used\n",
      "  calories_per_100g                   → Calories per 100g\n",
      "  carbohydrate_g_per_100g             → Carbohydrates per 100g\n",
      "  sugars_g_per_100g                   → Sugars per 100g\n",
      "  sodium_mg_per_100g                  → Sodium per 100g (mg)\n",
      "  potassium_mg_per_100g               → Potassium per 100g (mg)\n",
      "  fat_g_per_100g                      → Total fat per 100g\n",
      "  saturated_fat_g_per_100g            → Saturated fat per 100g\n",
      "  polyunsaturated_fat_g_per_100g      → Polyunsaturated fat per 100g\n",
      "  omega6_g_per_100g                   → Omega-6 per 100g\n",
      "  omega3_g_per_100g                   → Omega-3 per 100g\n",
      "  monounsaturated_fat_g_per_100g      → Monounsaturated fat per 100g\n",
      "  sugar_alcohols_g_per_100g           → Sugar alcohols per 100g\n",
      "  fibre_g_per_100g                    → Fibre per 100g\n",
      "  protein_g_per_100g                  → Protein per 100g\n",
      "  calcium_mg_per_100g                 → Calcium per 100g (mg)\n",
      "  iron_mg_per_100g                    → Iron per 100g (mg)\n",
      "  cholesterol_mg_per_100g             → Cholesterol per 100g (mg)\n"
     ]
    }
   ],
   "source": [
    "# Nutrition Per 100g Fields\n",
    "print(\"Nutrition Per 100g Fields:\")\n",
    "print(\"-\" * 80)\n",
    "n100_fields = {\n",
    "    \"external_id\":          \"Product-level identifier\",\n",
    "    \"upc\":                  \"Product barcode\",\n",
    "    \"serving_size\":         \"Raw serving size string (e.g. '30 g', '100 mL')\",\n",
    "    \"serving_amount\":       \"Parsed numeric amount\",\n",
    "    \"serving_unit\":         \"Parsed unit (g, mL, etc.)\",\n",
    "    \"normalization_method\": \"direct_100g / scaled_to_100g / not_normalized\",\n",
    "    \"normalization_reason\": \"Why this method was used\",\n",
    "    \"calories_per_100g\":    \"Calories per 100g\",\n",
    "    \"carbohydrate_g_per_100g\": \"Carbohydrates per 100g\",\n",
    "    \"sugars_g_per_100g\":    \"Sugars per 100g\",\n",
    "    \"sodium_mg_per_100g\":   \"Sodium per 100g (mg)\",\n",
    "    \"potassium_mg_per_100g\":\"Potassium per 100g (mg)\",\n",
    "    \"fat_g_per_100g\":       \"Total fat per 100g\",\n",
    "    \"saturated_fat_g_per_100g\": \"Saturated fat per 100g\",\n",
    "    \"polyunsaturated_fat_g_per_100g\": \"Polyunsaturated fat per 100g\",\n",
    "    \"omega6_g_per_100g\":    \"Omega-6 per 100g\",\n",
    "    \"omega3_g_per_100g\":    \"Omega-3 per 100g\",\n",
    "    \"monounsaturated_fat_g_per_100g\": \"Monounsaturated fat per 100g\",\n",
    "    \"sugar_alcohols_g_per_100g\": \"Sugar alcohols per 100g\",\n",
    "    \"fibre_g_per_100g\":     \"Fibre per 100g\",\n",
    "    \"protein_g_per_100g\":   \"Protein per 100g\",\n",
    "    \"calcium_mg_per_100g\":  \"Calcium per 100g (mg)\",\n",
    "    \"iron_mg_per_100g\":     \"Iron per 100g (mg)\",\n",
    "    \"cholesterol_mg_per_100g\": \"Cholesterol per 100g (mg)\"\n",
    "}\n",
    "for f, desc in n100_fields.items():\n",
    "    print(f\"  {f:35s} → {desc}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "44bfc980",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:32.586178Z",
     "iopub.status.busy": "2026-08-01T17:42:32.585609Z",
     "iopub.status.idle": "2026-08-01T17:42:33.377842Z",
     "shell.execute_reply": "2026-08-01T17:42:33.373904Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "  Phase 5 — product_nutrition_mapping.parquet\n",
      "  Shape: 4440 rows × 27 columns\n",
      "============================================================\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>external_id</th>\n",
       "      <th>upc</th>\n",
       "      <th>group_id</th>\n",
       "      <th>variant_id</th>\n",
       "      <th>title</th>\n",
       "      <th>serving_size</th>\n",
       "      <th>calories</th>\n",
       "      <th>carbohydrate_g</th>\n",
       "      <th>sugars_g</th>\n",
       "      <th>sodium_mg</th>\n",
       "      <th>...</th>\n",
       "      <th>sugar_alcohols_g</th>\n",
       "      <th>fibre_g</th>\n",
       "      <th>protein_g</th>\n",
       "      <th>calcium_mg</th>\n",
       "      <th>iron_mg</th>\n",
       "      <th>cholesterol_mg</th>\n",
       "      <th>match_method</th>\n",
       "      <th>match_confidence</th>\n",
       "      <th>nutrition_quality_status</th>\n",
       "      <th>nutrition_quality_flags</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>297608EA</td>\n",
       "      <td>055742522167</td>\n",
       "      <td>27b951a3-bef1-5ed4-80b7-7ef5cdca910a</td>\n",
       "      <td>2463d0b1-fd1e-5668-9d76-c5cfde65d5f0</td>\n",
       "      <td>Compliments Cold And Sinus Plus 20 Count</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>external_id_exact</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>MISSING</td>\n",
       "      <td>all_nutrition_fields_null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>464324EA</td>\n",
       "      <td>055742335200</td>\n",
       "      <td>e608ba58-8f93-59f1-9446-edb91aef79bd</td>\n",
       "      <td>1a0b7440-8644-598f-bb67-aeb45ee17a25</td>\n",
       "      <td>Compliments Twister T2 Light Bulbs 23W Soft Wh...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>external_id_exact</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>MISSING</td>\n",
       "      <td>all_nutrition_fields_null</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>144288CS</td>\n",
       "      <td>990002600400</td>\n",
       "      <td>336c79d8-796d-5682-8195-793883dd97ef</td>\n",
       "      <td>dcea4514-bc10-50ca-90df-34fd41cd20ef</td>\n",
       "      <td>Compliments Zero Calorie Soft Drink 12 x 355ml</td>\n",
       "      <td>355 mL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>external_id_exact</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>VALID</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  external_id           upc                              group_id  \\\n",
       "0    297608EA  055742522167  27b951a3-bef1-5ed4-80b7-7ef5cdca910a   \n",
       "1    464324EA  055742335200  e608ba58-8f93-59f1-9446-edb91aef79bd   \n",
       "2    144288CS  990002600400  336c79d8-796d-5682-8195-793883dd97ef   \n",
       "\n",
       "                             variant_id  \\\n",
       "0  2463d0b1-fd1e-5668-9d76-c5cfde65d5f0   \n",
       "1  1a0b7440-8644-598f-bb67-aeb45ee17a25   \n",
       "2  dcea4514-bc10-50ca-90df-34fd41cd20ef   \n",
       "\n",
       "                                               title serving_size  calories  \\\n",
       "0           Compliments Cold And Sinus Plus 20 Count          NaN       NaN   \n",
       "1  Compliments Twister T2 Light Bulbs 23W Soft Wh...          NaN       NaN   \n",
       "2     Compliments Zero Calorie Soft Drink 12 x 355ml       355 mL       NaN   \n",
       "\n",
       "   carbohydrate_g  sugars_g  sodium_mg  ...  sugar_alcohols_g  fibre_g  \\\n",
       "0             NaN       NaN        NaN  ...               NaN      NaN   \n",
       "1             NaN       NaN        NaN  ...               NaN      NaN   \n",
       "2             NaN       NaN       20.0  ...               NaN      NaN   \n",
       "\n",
       "   protein_g  calcium_mg  iron_mg  cholesterol_mg       match_method  \\\n",
       "0        NaN         NaN      NaN             NaN  external_id_exact   \n",
       "1        NaN         NaN      NaN             NaN  external_id_exact   \n",
       "2        NaN         NaN      NaN             NaN  external_id_exact   \n",
       "\n",
       "   match_confidence  nutrition_quality_status    nutrition_quality_flags  \n",
       "0              HIGH                   MISSING  all_nutrition_fields_null  \n",
       "1              HIGH                   MISSING  all_nutrition_fields_null  \n",
       "2              HIGH                     VALID                             \n",
       "\n",
       "[3 rows x 27 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Columns (27):\n",
      "  external_id                         str        nulls=    0  uniques=4440\n",
      "  upc                                 str        nulls=    1  uniques=3271\n",
      "  group_id                            str        nulls=    0  uniques=3691\n",
      "  variant_id                          str        nulls=    0  uniques=4299\n",
      "  title                               str        nulls=    0  uniques=4375\n",
      "  serving_size                        str        nulls= 1505  uniques=566\n",
      "  calories                            float64    nulls= 1661  uniques=73\n",
      "  carbohydrate_g                      float64    nulls= 1876  uniques=89\n",
      "  sugars_g                            float64    nulls= 2466  uniques=53\n",
      "  sodium_mg                           float64    nulls= 1959  uniques=131\n",
      "  potassium_mg                        float64    nulls= 1891  uniques=39\n",
      "  fat_g                               float64    nulls= 2311  uniques=53\n",
      "  saturated_fat_g                     float64    nulls= 2467  uniques=30\n",
      "  polyunsaturated_fat_g               float64    nulls= 4343  uniques=20\n",
      "  omega6_g                            float64    nulls= 4368  uniques=15\n",
      "  omega3_g                            float64    nulls= 4377  uniques=15\n",
      "  monounsaturated_fat_g               float64    nulls= 4352  uniques=21\n",
      "  sugar_alcohols_g                    float64    nulls= 4329  uniques=2\n",
      "  fibre_g                             float64    nulls= 2852  uniques=19\n",
      "  protein_g                           float64    nulls= 1887  uniques=45\n",
      "  calcium_mg                          float64    nulls= 3225  uniques=19\n",
      "  iron_mg                             float64    nulls= 3281  uniques=27\n",
      "  cholesterol_mg                      float64    nulls= 3309  uniques=40\n",
      "  match_method                        str        nulls=    0  uniques=1\n",
      "  match_confidence                    str        nulls=    0  uniques=1\n",
      "  nutrition_quality_status            str        nulls=    0  uniques=3\n",
      "  nutrition_quality_flags             str        nulls=    0  uniques=4\n"
     ]
    }
   ],
   "source": [
    "p5_pn = load(\"phase5/outputs/product_nutrition_mapping.parquet\")\n",
    "show_table(p5_pn, \"Phase 5 — product_nutrition_mapping.parquet\", n=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "a90819f4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:33.383530Z",
     "iopub.status.busy": "2026-08-01T17:42:33.382755Z",
     "iopub.status.idle": "2026-08-01T17:42:33.400099Z",
     "shell.execute_reply": "2026-08-01T17:42:33.397011Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Product-Nutrition Mapping Fields:\n",
      "--------------------------------------------------------------------------------\n",
      "  external_id                    → Product-level identifier\n",
      "  upc                            → Product barcode\n",
      "  group_id                       → Group UUID (from Phase 3)\n",
      "  variant_id                     → Variant UUID (from Phase 4)\n",
      "  title                          → Product title\n",
      "  serving_size                   → Raw serving size\n",
      "  calories                       → Calories (raw, as-is)\n",
      "  carbohydrate_g                 → Carbohydrates (raw)\n",
      "  sugars_g                       → Sugars (raw)\n",
      "  sodium_mg                      → Sodium (raw)\n",
      "  fat_g                          → Total fat (raw)\n",
      "  saturated_fat_g                → Saturated fat (raw)\n",
      "  protein_g                      → Protein (raw)\n",
      "  fibre_g                        → Fibre (raw)\n",
      "  match_method                   → external_id_exact (100% deterministic)\n",
      "  match_confidence               → HIGH\n",
      "  nutrition_quality_status       → VALID / MISSING / SUSPICIOUS\n",
      "  nutrition_quality_flags        → Quality flags\n"
     ]
    }
   ],
   "source": [
    "# Product-Nutrition Mapping Fields\n",
    "print(\"Product-Nutrition Mapping Fields:\")\n",
    "print(\"-\" * 80)\n",
    "pn_fields = {\n",
    "    \"external_id\":          \"Product-level identifier\",\n",
    "    \"upc\":                  \"Product barcode\",\n",
    "    \"group_id\":             \"Group UUID (from Phase 3)\",\n",
    "    \"variant_id\":           \"Variant UUID (from Phase 4)\",\n",
    "    \"title\":                \"Product title\",\n",
    "    \"serving_size\":         \"Raw serving size\",\n",
    "    \"calories\":             \"Calories (raw, as-is)\",\n",
    "    \"carbohydrate_g\":       \"Carbohydrates (raw)\",\n",
    "    \"sugars_g\":             \"Sugars (raw)\",\n",
    "    \"sodium_mg\":            \"Sodium (raw)\",\n",
    "    \"fat_g\":                \"Total fat (raw)\",\n",
    "    \"saturated_fat_g\":      \"Saturated fat (raw)\",\n",
    "    \"protein_g\":            \"Protein (raw)\",\n",
    "    \"fibre_g\":              \"Fibre (raw)\",\n",
    "    \"match_method\":         \"external_id_exact (100% deterministic)\",\n",
    "    \"match_confidence\":     \"HIGH\",\n",
    "    \"nutrition_quality_status\": \"VALID / MISSING / SUSPICIOUS\",\n",
    "    \"nutrition_quality_flags\":  \"Quality flags\"\n",
    "}\n",
    "for f, desc in pn_fields.items():\n",
    "    print(f\"  {f:30s} → {desc}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c7784459",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:33.407022Z",
     "iopub.status.busy": "2026-08-01T17:42:33.405394Z",
     "iopub.status.idle": "2026-08-01T17:42:33.857435Z",
     "shell.execute_reply": "2026-08-01T17:42:33.855306Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Phase 5 — Normalization + Quality\n",
    "fig, axes = plt.subplots(1, 2, figsize=(14, 5))\n",
    "\n",
    "p5_100g['normalization_method'].value_counts().plot(kind='pie', ax=axes[0], autopct='%1.1f%%', colors=COLORS[:3])\n",
    "axes[0].set_title('Phase 5 — Normalization Method', fontsize=12)\n",
    "axes[0].set_ylabel('')\n",
    "\n",
    "p5_pn['nutrition_quality_status'].value_counts().plot(kind='pie', ax=axes[1], autopct='%1.1f%%', colors=COLORS[:3])\n",
    "axes[1].set_title('Phase 5 — Nutrition Quality Status', fontsize=12)\n",
    "axes[1].set_ylabel('')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f173a91f",
   "metadata": {},
   "source": [
    "---\n",
    "# Phase 6 — Nutri-Score 2023 + Agribalyse Mapping\n",
    "\n",
    "**Goal:** Calculate Nutri-Score 2023 for eligible food products, map to Agribalyse categories.\n",
    "\n",
    "**Algorithm:** Nutri-Score 2023 (Eurofins referencing Santé Publique France FAQ v21.Dec.2023)\n",
    "\n",
    "**Input:** Phase 5 outputs + Phase 3 + Phase 4\n",
    "**Output:** 3 Parquet files — scores, agribalyse, exclusions\n",
    "\n",
    "### What Happens\n",
    "1. Merge nutrition per-100g with domain/taxonomy/variant data\n",
    "2. Compute eligibility (food + VALID + all 6 required fields)\n",
    "3. Estimate FVL from taxonomy (PRODUCE=90%, default=0%)\n",
    "4. Calculate Nutri-Score 2023 (negative - positive points → grade A-E)\n",
    "5. Map to Agribalyse categories (CIQUAL codes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d9246429",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:33.879123Z",
     "iopub.status.busy": "2026-08-01T17:42:33.873804Z",
     "iopub.status.idle": "2026-08-01T17:42:37.637457Z",
     "shell.execute_reply": "2026-08-01T17:42:37.634429Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cf800c0389204551b51bbe4d6960b3cf",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "phase6/outputs/phase6_product_scores.par(…): reconstructing file:   0%|          |  0.00B /  511kB            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      },
      "text/plain": [
       "phase6/outputs/phase6_product_scores.par(…): downloading bytes:           |  0.00B            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "  Phase 6 — phase6_product_scores.parquet\n",
      "  Shape: 4440 rows × 31 columns\n",
      "============================================================\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>external_id</th>\n",
       "      <th>group_id</th>\n",
       "      <th>variant_id</th>\n",
       "      <th>upc</th>\n",
       "      <th>core_title</th>\n",
       "      <th>product_domain</th>\n",
       "      <th>taxonomy</th>\n",
       "      <th>nutrition_quality_status</th>\n",
       "      <th>nutrition_quality_flags</th>\n",
       "      <th>score_eligibility</th>\n",
       "      <th>...</th>\n",
       "      <th>fvl_confidence</th>\n",
       "      <th>fvl_source</th>\n",
       "      <th>negative_points</th>\n",
       "      <th>positive_points</th>\n",
       "      <th>nutri_score_raw</th>\n",
       "      <th>nutri_score_grade</th>\n",
       "      <th>nutri_score_algorithm</th>\n",
       "      <th>nutri_score_version</th>\n",
       "      <th>nutri_score_calculated</th>\n",
       "      <th>normalization_method</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>297608EA</td>\n",
       "      <td>27b951a3-bef1-5ed4-80b7-7ef5cdca910a</td>\n",
       "      <td>2463d0b1-fd1e-5668-9d76-c5cfde65d5f0</td>\n",
       "      <td>055742522167</td>\n",
       "      <td>Cold And Sinus Plus</td>\n",
       "      <td>unknown</td>\n",
       "      <td>GENERAL_GROCERY</td>\n",
       "      <td>MISSING</td>\n",
       "      <td>all_nutrition_fields_null</td>\n",
       "      <td>NOT_ELIGIBLE</td>\n",
       "      <td>...</td>\n",
       "      <td>LOW</td>\n",
       "      <td>not_in_data</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>nutri_score_2023</td>\n",
       "      <td>2023</td>\n",
       "      <td>False</td>\n",
       "      <td>not_normalized</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>464324EA</td>\n",
       "      <td>e608ba58-8f93-59f1-9446-edb91aef79bd</td>\n",
       "      <td>1a0b7440-8644-598f-bb67-aeb45ee17a25</td>\n",
       "      <td>055742335200</td>\n",
       "      <td>Twister T2 Light Bulbs 23W Soft White</td>\n",
       "      <td>unknown</td>\n",
       "      <td>GENERAL_GROCERY</td>\n",
       "      <td>MISSING</td>\n",
       "      <td>all_nutrition_fields_null</td>\n",
       "      <td>NOT_ELIGIBLE</td>\n",
       "      <td>...</td>\n",
       "      <td>LOW</td>\n",
       "      <td>not_in_data</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>nutri_score_2023</td>\n",
       "      <td>2023</td>\n",
       "      <td>False</td>\n",
       "      <td>not_normalized</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>144288CS</td>\n",
       "      <td>336c79d8-796d-5682-8195-793883dd97ef</td>\n",
       "      <td>dcea4514-bc10-50ca-90df-34fd41cd20ef</td>\n",
       "      <td>990002600400</td>\n",
       "      <td>Zero Calorie Soft Drink</td>\n",
       "      <td>food</td>\n",
       "      <td>BEVERAGES</td>\n",
       "      <td>VALID</td>\n",
       "      <td></td>\n",
       "      <td>NOT_ELIGIBLE</td>\n",
       "      <td>...</td>\n",
       "      <td>LOW</td>\n",
       "      <td>not_in_data</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>nutri_score_2023</td>\n",
       "      <td>2023</td>\n",
       "      <td>False</td>\n",
       "      <td>scaled_to_100g</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  external_id                              group_id  \\\n",
       "0    297608EA  27b951a3-bef1-5ed4-80b7-7ef5cdca910a   \n",
       "1    464324EA  e608ba58-8f93-59f1-9446-edb91aef79bd   \n",
       "2    144288CS  336c79d8-796d-5682-8195-793883dd97ef   \n",
       "\n",
       "                             variant_id           upc  \\\n",
       "0  2463d0b1-fd1e-5668-9d76-c5cfde65d5f0  055742522167   \n",
       "1  1a0b7440-8644-598f-bb67-aeb45ee17a25  055742335200   \n",
       "2  dcea4514-bc10-50ca-90df-34fd41cd20ef  990002600400   \n",
       "\n",
       "                              core_title product_domain         taxonomy  \\\n",
       "0                    Cold And Sinus Plus        unknown  GENERAL_GROCERY   \n",
       "1  Twister T2 Light Bulbs 23W Soft White        unknown  GENERAL_GROCERY   \n",
       "2                Zero Calorie Soft Drink           food        BEVERAGES   \n",
       "\n",
       "  nutrition_quality_status    nutrition_quality_flags score_eligibility  ...  \\\n",
       "0                  MISSING  all_nutrition_fields_null      NOT_ELIGIBLE  ...   \n",
       "1                  MISSING  all_nutrition_fields_null      NOT_ELIGIBLE  ...   \n",
       "2                    VALID                                 NOT_ELIGIBLE  ...   \n",
       "\n",
       "  fvl_confidence   fvl_source  negative_points  positive_points  \\\n",
       "0            LOW  not_in_data              NaN              NaN   \n",
       "1            LOW  not_in_data              NaN              NaN   \n",
       "2            LOW  not_in_data              NaN              NaN   \n",
       "\n",
       "   nutri_score_raw  nutri_score_grade  nutri_score_algorithm  \\\n",
       "0              NaN                NaN       nutri_score_2023   \n",
       "1              NaN                NaN       nutri_score_2023   \n",
       "2              NaN                NaN       nutri_score_2023   \n",
       "\n",
       "   nutri_score_version  nutri_score_calculated  normalization_method  \n",
       "0                 2023                   False        not_normalized  \n",
       "1                 2023                   False        not_normalized  \n",
       "2                 2023                   False        scaled_to_100g  \n",
       "\n",
       "[3 rows x 31 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Columns (31):\n",
      "  external_id                         str        nulls=    0  uniques=4440\n",
      "  group_id                            str        nulls=    0  uniques=3691\n",
      "  variant_id                          str        nulls=    0  uniques=4299\n",
      "  upc                                 str        nulls=    1  uniques=3271\n",
      "  core_title                          str        nulls=    0  uniques=4070\n",
      "  product_domain                      str        nulls=    0  uniques=3\n",
      "  taxonomy                            str        nulls=    0  uniques=19\n",
      "  nutrition_quality_status            str        nulls=    0  uniques=3\n",
      "  nutrition_quality_flags             str        nulls=    0  uniques=4\n",
      "  score_eligibility                   str        nulls=    0  uniques=2\n",
      "  score_exclusion_reason              str        nulls=    0  uniques=37\n",
      "  calories_per_100g                   float64    nulls= 3005  uniques=406\n",
      "  energy_kj_100g                      float64    nulls= 3005  uniques=406\n",
      "  sugars_g_per_100g                   float64    nulls= 3423  uniques=322\n",
      "  saturated_fat_g_per_100g            float64    nulls= 3412  uniques=276\n",
      "  sodium_mg_per_100g                  float64    nulls= 3184  uniques=531\n",
      "  salt_g_100g                         float64    nulls= 3184  uniques=531\n",
      "  fibre_g_per_100g                    float64    nulls= 3593  uniques=152\n",
      "  protein_g_per_100g                  float64    nulls= 3142  uniques=279\n",
      "  fvl_percent                         int64      nulls=    0  uniques=2\n",
      "  fvl_method                          str        nulls=    0  uniques=1\n",
      "  fvl_confidence                      str        nulls=    0  uniques=1\n",
      "  fvl_source                          str        nulls=    0  uniques=1\n",
      "  negative_points                     float64    nulls= 4076  uniques=34\n",
      "  positive_points                     float64    nulls= 4076  uniques=14\n",
      "  nutri_score_raw                     float64    nulls= 4076  uniques=38\n",
      "  nutri_score_grade                   str        nulls= 4076  uniques=5\n",
      "  nutri_score_algorithm               str        nulls=    0  uniques=1\n",
      "  nutri_score_version                 str        nulls=    0  uniques=1\n",
      "  nutri_score_calculated              bool       nulls=    0  uniques=2\n",
      "  normalization_method                str        nulls=    0  uniques=3\n"
     ]
    }
   ],
   "source": [
    "p6_scores = load(\"phase6/outputs/phase6_product_scores.parquet\")\n",
    "show_table(p6_scores, \"Phase 6 — phase6_product_scores.parquet\", n=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "f4fe03b9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:37.645516Z",
     "iopub.status.busy": "2026-08-01T17:42:37.644415Z",
     "iopub.status.idle": "2026-08-01T17:42:37.669442Z",
     "shell.execute_reply": "2026-08-01T17:42:37.666753Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Phase 6 Product Scores Fields:\n",
      "--------------------------------------------------------------------------------\n",
      "  external_id                    → Product-level identifier\n",
      "  group_id                       → Group UUID\n",
      "  variant_id                     → Variant UUID\n",
      "  upc                            → Product barcode\n",
      "  core_title                     → Normalized core title\n",
      "  product_domain                 → food / non_food / unknown\n",
      "  reference_db_taxonomy          → Category\n",
      "  nutrition_quality_status       → VALID / MISSING / SUSPICIOUS\n",
      "  score_eligibility              → ELIGIBLE / NOT_ELIGIBLE\n",
      "  score_exclusion_reason         → Reason for exclusion (if any)\n",
      "  calories_per_100g              → Calories per 100g\n",
      "  energy_kj_100g                 → Energy in kJ per 100g (calories × 4.184)\n",
      "  sugars_g_per_100g              → Sugars per 100g\n",
      "  saturated_fat_g_per_100g       → Saturated fat per 100g\n",
      "  sodium_mg_per_100g             → Sodium per 100g\n",
      "  salt_g_100g                    → Salt per 100g (sodium × 2.5 / 1000)\n",
      "  fibre_g_per_100g               → Fibre per 100g\n",
      "  protein_g_per_100g             → Protein per 100g\n",
      "  fvl_percent                    → Fruits, Vegetables, Legumes % (90 for PRODUCE, 0 for others)\n",
      "  negative_points                → Nutri-Score negative points (energy + sat fat + sugar + salt)\n",
      "  positive_points                → Nutri-Score positive points (protein + fibre + FVL)\n",
      "  nutri_score_raw                → Raw score (negative - positive, range -10 to 40)\n",
      "  nutri_score_grade              → A / B / C / D / E\n",
      "  nutri_score_calculated         → boolean — was score calculated?\n"
     ]
    }
   ],
   "source": [
    "# Product Scores Fields\n",
    "print(\"Phase 6 Product Scores Fields:\")\n",
    "print(\"-\" * 80)\n",
    "p6_fields = {\n",
    "    \"external_id\":          \"Product-level identifier\",\n",
    "    \"group_id\":             \"Group UUID\",\n",
    "    \"variant_id\":           \"Variant UUID\",\n",
    "    \"upc\":                  \"Product barcode\",\n",
    "    \"core_title\":           \"Normalized core title\",\n",
    "    \"product_domain\":       \"food / non_food / unknown\",\n",
    "    \"reference_db_taxonomy\":\"Category\",\n",
    "    \"nutrition_quality_status\": \"VALID / MISSING / SUSPICIOUS\",\n",
    "    \"score_eligibility\":    \"ELIGIBLE / NOT_ELIGIBLE\",\n",
    "    \"score_exclusion_reason\":\"Reason for exclusion (if any)\",\n",
    "    \"calories_per_100g\":    \"Calories per 100g\",\n",
    "    \"energy_kj_100g\":       \"Energy in kJ per 100g (calories × 4.184)\",\n",
    "    \"sugars_g_per_100g\":    \"Sugars per 100g\",\n",
    "    \"saturated_fat_g_per_100g\": \"Saturated fat per 100g\",\n",
    "    \"sodium_mg_per_100g\":   \"Sodium per 100g\",\n",
    "    \"salt_g_100g\":          \"Salt per 100g (sodium × 2.5 / 1000)\",\n",
    "    \"fibre_g_per_100g\":     \"Fibre per 100g\",\n",
    "    \"protein_g_per_100g\":   \"Protein per 100g\",\n",
    "    \"fvl_percent\":          \"Fruits, Vegetables, Legumes % (90 for PRODUCE, 0 for others)\",\n",
    "    \"negative_points\":      \"Nutri-Score negative points (energy + sat fat + sugar + salt)\",\n",
    "    \"positive_points\":      \"Nutri-Score positive points (protein + fibre + FVL)\",\n",
    "    \"nutri_score_raw\":      \"Raw score (negative - positive, range -10 to 40)\",\n",
    "    \"nutri_score_grade\":    \"A / B / C / D / E\",\n",
    "    \"nutri_score_calculated\": \"boolean — was score calculated?\"\n",
    "}\n",
    "for f, desc in p6_fields.items():\n",
    "    print(f\"  {f:30s} → {desc}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d76e5a9b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:37.677655Z",
     "iopub.status.busy": "2026-08-01T17:42:37.676538Z",
     "iopub.status.idle": "2026-08-01T17:42:39.729520Z",
     "shell.execute_reply": "2026-08-01T17:42:39.725866Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "phase6/outputs/phase6_agribalyse_mapping(…): reconstructing file:   0%|          |  0.00B /  190kB            "
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     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "  Phase 6 — phase6_agribalyse_mapping.parquet\n",
      "  Shape: 4440 rows × 11 columns\n",
      "============================================================\n"
     ]
    },
    {
     "data": {
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>external_id</th>\n",
       "      <th>group_id</th>\n",
       "      <th>taxonomy</th>\n",
       "      <th>product_domain</th>\n",
       "      <th>agribalyse_category</th>\n",
       "      <th>agribalyse_ciqual</th>\n",
       "      <th>mapping_method</th>\n",
       "      <th>mapping_confidence</th>\n",
       "      <th>mapping_source</th>\n",
       "      <th>mapping_version</th>\n",
       "      <th>mapping_note</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>297608EA</td>\n",
       "      <td>27b951a3-bef1-5ed4-80b7-7ef5cdca910a</td>\n",
       "      <td>GENERAL_GROCERY</td>\n",
       "      <td>unknown</td>\n",
       "      <td>Multiple categories</td>\n",
       "      <td>Various</td>\n",
       "      <td>deterministic_taxonomy</td>\n",
       "      <td>LOW</td>\n",
       "      <td>agribalyse_v3.2</td>\n",
       "      <td>3.2</td>\n",
       "      <td>Category-level proxy. Not a product-specific LCA.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>464324EA</td>\n",
       "      <td>e608ba58-8f93-59f1-9446-edb91aef79bd</td>\n",
       "      <td>GENERAL_GROCERY</td>\n",
       "      <td>unknown</td>\n",
       "      <td>Multiple categories</td>\n",
       "      <td>Various</td>\n",
       "      <td>deterministic_taxonomy</td>\n",
       "      <td>LOW</td>\n",
       "      <td>agribalyse_v3.2</td>\n",
       "      <td>3.2</td>\n",
       "      <td>Category-level proxy. Not a product-specific LCA.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>144288CS</td>\n",
       "      <td>336c79d8-796d-5682-8195-793883dd97ef</td>\n",
       "      <td>BEVERAGES</td>\n",
       "      <td>food</td>\n",
       "      <td>Boissons</td>\n",
       "      <td>14xxx</td>\n",
       "      <td>deterministic_taxonomy</td>\n",
       "      <td>HIGH</td>\n",
       "      <td>agribalyse_v3.2</td>\n",
       "      <td>3.2</td>\n",
       "      <td>Category-level proxy. Not a product-specific LCA.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>312204EA</td>\n",
       "      <td>34baf35c-0ee4-5907-9e0f-e8954e34aa11</td>\n",
       "      <td>GENERAL_GROCERY</td>\n",
       "      <td>food</td>\n",
       "      <td>Multiple categories</td>\n",
       "      <td>Various</td>\n",
       "      <td>deterministic_taxonomy</td>\n",
       "      <td>LOW</td>\n",
       "      <td>agribalyse_v3.2</td>\n",
       "      <td>3.2</td>\n",
       "      <td>Category-level proxy. Not a product-specific LCA.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>259928EA</td>\n",
       "      <td>4ff536c8-c957-5fe8-8faa-3f539d6048ef</td>\n",
       "      <td>GENERAL_GROCERY</td>\n",
       "      <td>unknown</td>\n",
       "      <td>Multiple categories</td>\n",
       "      <td>Various</td>\n",
       "      <td>deterministic_taxonomy</td>\n",
       "      <td>LOW</td>\n",
       "      <td>agribalyse_v3.2</td>\n",
       "      <td>3.2</td>\n",
       "      <td>Category-level proxy. Not a product-specific LCA.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  external_id                              group_id         taxonomy  \\\n",
       "0    297608EA  27b951a3-bef1-5ed4-80b7-7ef5cdca910a  GENERAL_GROCERY   \n",
       "1    464324EA  e608ba58-8f93-59f1-9446-edb91aef79bd  GENERAL_GROCERY   \n",
       "2    144288CS  336c79d8-796d-5682-8195-793883dd97ef        BEVERAGES   \n",
       "3    312204EA  34baf35c-0ee4-5907-9e0f-e8954e34aa11  GENERAL_GROCERY   \n",
       "4    259928EA  4ff536c8-c957-5fe8-8faa-3f539d6048ef  GENERAL_GROCERY   \n",
       "\n",
       "  product_domain  agribalyse_category agribalyse_ciqual  \\\n",
       "0        unknown  Multiple categories           Various   \n",
       "1        unknown  Multiple categories           Various   \n",
       "2           food             Boissons             14xxx   \n",
       "3           food  Multiple categories           Various   \n",
       "4        unknown  Multiple categories           Various   \n",
       "\n",
       "           mapping_method mapping_confidence   mapping_source mapping_version  \\\n",
       "0  deterministic_taxonomy                LOW  agribalyse_v3.2             3.2   \n",
       "1  deterministic_taxonomy                LOW  agribalyse_v3.2             3.2   \n",
       "2  deterministic_taxonomy               HIGH  agribalyse_v3.2             3.2   \n",
       "3  deterministic_taxonomy                LOW  agribalyse_v3.2             3.2   \n",
       "4  deterministic_taxonomy                LOW  agribalyse_v3.2             3.2   \n",
       "\n",
       "                                        mapping_note  \n",
       "0  Category-level proxy. Not a product-specific LCA.  \n",
       "1  Category-level proxy. Not a product-specific LCA.  \n",
       "2  Category-level proxy. Not a product-specific LCA.  \n",
       "3  Category-level proxy. Not a product-specific LCA.  \n",
       "4  Category-level proxy. Not a product-specific LCA.  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Columns (11):\n",
      "  external_id                         str        nulls=    0  uniques=4440\n",
      "  group_id                            str        nulls=    0  uniques=3691\n",
      "  taxonomy                            str        nulls=    0  uniques=19\n",
      "  product_domain                      str        nulls=    0  uniques=3\n",
      "  agribalyse_category                 str        nulls=    0  uniques=13\n",
      "  agribalyse_ciqual                   str        nulls=    0  uniques=13\n",
      "  mapping_method                      str        nulls=    0  uniques=1\n",
      "  mapping_confidence                  str        nulls=    0  uniques=4\n",
      "  mapping_source                      str        nulls=    0  uniques=1\n",
      "  mapping_version                     str        nulls=    0  uniques=1\n",
      "  mapping_note                        str        nulls=    0  uniques=1\n"
     ]
    }
   ],
   "source": [
    "p6_agri = load(\"phase6/outputs/phase6_agribalyse_mapping.parquet\")\n",
    "show_table(p6_agri, \"Phase 6 — phase6_agribalyse_mapping.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c3ca07fb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:39.742062Z",
     "iopub.status.busy": "2026-08-01T17:42:39.739324Z",
     "iopub.status.idle": "2026-08-01T17:42:39.757633Z",
     "shell.execute_reply": "2026-08-01T17:42:39.753896Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Agribalyse Mapping Fields:\n",
      "--------------------------------------------------------------------------------\n",
      "  external_id               → Product-level identifier\n",
      "  group_id                  → Group UUID\n",
      "  reference_db_taxonomy     → Category\n",
      "  product_domain            → food / non_food / unknown\n",
      "  agribalyse_category       → Agribalyse category name (French)\n",
      "  agribalyse_ciqual         → CIQUAL code pattern (e.g. 19xxx)\n",
      "  mapping_confidence        → HIGH / MEDIUM / LOW / NONE\n",
      "\n",
      "Mapping source: Agribalyse v3.2 (CIQUAL database)\n"
     ]
    }
   ],
   "source": [
    "# Agribalyse Mapping Fields\n",
    "print(\"Agribalyse Mapping Fields:\")\n",
    "print(\"-\" * 80)\n",
    "agri_fields = {\n",
    "    \"external_id\":          \"Product-level identifier\",\n",
    "    \"group_id\":             \"Group UUID\",\n",
    "    \"reference_db_taxonomy\":\"Category\",\n",
    "    \"product_domain\":       \"food / non_food / unknown\",\n",
    "    \"agribalyse_category\":  \"Agribalyse category name (French)\",\n",
    "    \"agribalyse_ciqual\":    \"CIQUAL code pattern (e.g. 19xxx)\",\n",
    "    \"mapping_confidence\":   \"HIGH / MEDIUM / LOW / NONE\"\n",
    "}\n",
    "for f, desc in agri_fields.items():\n",
    "    print(f\"  {f:25s} → {desc}\")\n",
    "print(f\"\\nMapping source: Agribalyse v3.2 (CIQUAL database)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "7c35c07d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:39.764526Z",
     "iopub.status.busy": "2026-08-01T17:42:39.762402Z",
     "iopub.status.idle": "2026-08-01T17:42:41.852151Z",
     "shell.execute_reply": "2026-08-01T17:42:41.850787Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e1cdd9e6b4fe4cdf9def2765050082c3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "phase6/outputs/phase6_score_exclusions.p(…): reconstructing file:   0%|          |  0.00B /  171kB            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5d811f995c8b4823b22a7ad45e5257fd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "phase6/outputs/phase6_score_exclusions.p(…): downloading bytes:           |  0.00B            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "  Phase 6 — phase6_score_exclusions.parquet\n",
      "  Shape: 4076 rows × 6 columns\n",
      "============================================================\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>external_id</th>\n",
       "      <th>group_id</th>\n",
       "      <th>product_domain</th>\n",
       "      <th>taxonomy</th>\n",
       "      <th>nutrition_quality_status</th>\n",
       "      <th>score_exclusion_reason</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>297608EA</td>\n",
       "      <td>27b951a3-bef1-5ed4-80b7-7ef5cdca910a</td>\n",
       "      <td>unknown</td>\n",
       "      <td>GENERAL_GROCERY</td>\n",
       "      <td>MISSING</td>\n",
       "      <td>UNKNOWN_DOMAIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>464324EA</td>\n",
       "      <td>e608ba58-8f93-59f1-9446-edb91aef79bd</td>\n",
       "      <td>unknown</td>\n",
       "      <td>GENERAL_GROCERY</td>\n",
       "      <td>MISSING</td>\n",
       "      <td>UNKNOWN_DOMAIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>144288CS</td>\n",
       "      <td>336c79d8-796d-5682-8195-793883dd97ef</td>\n",
       "      <td>food</td>\n",
       "      <td>BEVERAGES</td>\n",
       "      <td>VALID</td>\n",
       "      <td>MISSING_REQUIRED_FIELDS: calories, sugars_g, s...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  external_id                              group_id product_domain  \\\n",
       "0    297608EA  27b951a3-bef1-5ed4-80b7-7ef5cdca910a        unknown   \n",
       "1    464324EA  e608ba58-8f93-59f1-9446-edb91aef79bd        unknown   \n",
       "2    144288CS  336c79d8-796d-5682-8195-793883dd97ef           food   \n",
       "\n",
       "          taxonomy nutrition_quality_status  \\\n",
       "0  GENERAL_GROCERY                  MISSING   \n",
       "1  GENERAL_GROCERY                  MISSING   \n",
       "2        BEVERAGES                    VALID   \n",
       "\n",
       "                              score_exclusion_reason  \n",
       "0                                     UNKNOWN_DOMAIN  \n",
       "1                                     UNKNOWN_DOMAIN  \n",
       "2  MISSING_REQUIRED_FIELDS: calories, sugars_g, s...  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Columns (6):\n",
      "  external_id                         str        nulls=    0  uniques=4076\n",
      "  group_id                            str        nulls=    0  uniques=3387\n",
      "  product_domain                      str        nulls=    0  uniques=3\n",
      "  taxonomy                            str        nulls=    0  uniques=19\n",
      "  nutrition_quality_status            str        nulls=    0  uniques=3\n",
      "  score_exclusion_reason              str        nulls=    0  uniques=36\n"
     ]
    }
   ],
   "source": [
    "p6_excl = load(\"phase6/outputs/phase6_score_exclusions.parquet\")\n",
    "show_table(p6_excl, \"Phase 6 — phase6_score_exclusions.parquet\", n=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "764b0395",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-01T17:42:41.869610Z",
     "iopub.status.busy": "2026-08-01T17:42:41.869035Z",
     "iopub.status.idle": "2026-08-01T17:42:45.236429Z",
     "shell.execute_reply": "2026-08-01T17:42:45.234313Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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mTeP69evUqlULSHn9fvLkSaWu6OhorTGTHZrXygEBAcr2KPqOl9wYm7nV7pz0uRBCCCGEEEJ86rL9biY5OVnrDXNsbCyvXr2iYMGCrF27FhsbG+VclSpVtN5EOjk5ASgz4XTte+Ti4oJKpeL169c4OjpSsGBBVqxYQUxMDHXq1KFIkSJKUgng6dOnhIWF0aJFC6166tSpg4WFBVevXtWZ5EpISABSZk9u3LhRmQ3q5uZGhw4d2Ldv30fdH6lAgQIMHz6cVatW0a5dO0qUKJGr9VeoUCFHiVqNAQMG0Lt3b65fv86tW7e4desWO3fuJG/evIwfP57OnTvj5eVFeHi48qZbI3/+/Mqfvb29iYiIoFGjRlplqlSpgrW1Nbdv36Z37946Y87ps9csc6ZrGbi0HwblyZOH48ePKz/r6resxnF4eDhxcXHUqFFDq0z9+vWVD75y2hZ9aL4AoKu9+vyOZUbfcVSlShUlUQsp/aNZNi63ZGcsVapUSWtGQdq/m4QQQggh9JE2mfj27VvCw8OpWLEiixcv1lpet379+lrJJEdHRyDl9Yetra3W+ygNFxcXPD09gZT9Yy0sLJg6dSrffPMNtWrVwt7enl69einlb9y4gUqlomXLllr1NG3alIULF3Lt2jWdyVrNe6NKlSoxf/585XjhwoWZOHEiV65coU6dOtnpmlxha2tL3759dZ5LnQivVKkSw4cPZ968eeTLl49OnTrRtGlT5fytW7eUrUhSS/16MCf0eSZp/fPPP6jV6nSvWTUrx3h6eipxZjVmMpJ2XKpUKkJCQlCr1QwePFhZ1lnf8ZIbYzO32p2TPhdCCCGEEEKIT122k7WGhoYMHjxY+dnExITChQtTuXJlTE1NtcpaWVlp/az5sEKTPHr16hU7d+7E09OTsLAwEhMTiYiIUMqYmpqyd+9eli9fzpIlS3j79i3FixdX9qo0MTFRll9ev349P/30k9b9EhMTlW+Jp2VpaQlAzZo1tZJY5cuXx9HRMcMkUkbf7M6Oc+fO6VWuX79+HDt2jNmzZ7Njx453vm9qWX0w4enpyfjx45WfbW1t2bdvn1YZU1NT6tevT/369YGU5d7mzp3LtGnTKFGiBPHx8UD6cZCa5vnp+rDB1tZWGQ+6Ys7ps7ezs8PY2JiXL1+mO6fZRwrgypUrygcQGcUAWY9jzZJnaT/kSJ20zmlb9OHr6wv8/4Rkavr8jmVG3w+4NLMaUrOyslKWRM8N2RlLaZ9F2r+bhBBCCCH0YW9vr/XeKE+ePBQrVowKFSqk+6Jc2tfEmvOa1x/e3t7s2bOHR48eERERQWJiotYXyQoXLszu3btZtWoVU6ZMISEhgfLly9O3b1/atWsH/P/XQxMmTNBKdmnuERwcrLMdmu0/ateurXW8SZMmQMps4bTJ2ufPnzNo0KAM+0YfxYsXZ8uWLRmez58/v95JuEGDBrFjxw58fHzSvXfS9Etm70tyQp9nkpYmlrSvjzXvDVJvM6OZyaqRdsxkJO249PT05MCBA/z4449aK2HpO15yc2y+a7tz0udCCCGEEEII8anLdrLWwMBAK6GVUwkJCfTu3ZvY2FiGDRtGiRIlMDMz4+LFi2zYsEEp5+TkxKJFi0hKSuL+/fucPn2aFStWEBwczNSpU5Wka/v27alevXq6++hKEkFK8iZv3rxER0enO2diYkJsbKzO66ZPn56T5uaIiYkJs2bNomfPnpw4cQIjI6Msr8ko7rSyqsvBwUHrOafevzU5OZnExERluWMNW1tbZs6cycmTJ/n777+VJG7afW1T09SrK2kXGRmpdd+0Mef02RsZGVGzZk0uXbpEfHw8ZmZmyrnUH2rEx8enS9amjUGfcaz5EoNmxoJG6n7JaVv0cerUKUxNTTNc3jer37HM6DMmQfe4fPv2baZLjes7ljWyM5aEEEIIIXJDvnz5cuW9UWBgID169KBAgQIMGjQIJycnTE1N2bFjBxcvXlTKlStXjo0bNxIXF8e///7L4cOHmThxIgkJCXTu3Fl5TTlkyBAKFiyY7j66ZtVCytYbQLr9aTWv9XS9LnNwcHjn90aaeHPD9u3bAXB2dmbVqlX88MMPyjnN68CIiIh3Wl0I0vdFVs8kLU2b075m1fycG69Z045LDw8PPD09WbBgAYcPH1ben+gzXnJ7bOZGu7Pb50IIIYQQQgjxqftom7o8fPiQZ8+esWrVKlq1aqUcP3TokPLn0NBQHjx4QMOGDTE2NqZKlSpUqVKFsLAw/v77bwBcXV2VN5uaJZT0VadOHf78808SExOVGYQBAQEEBgYqS0Olld17vCs3Nzc8PDxYuHAh7u7uWud0zUy8d+9erty3YMGCWolLjYiICJo0aULLli21lkjT8Pb2BlLebJcqVQoTExNu376Nh4eHzvu4urpiYmLCnTt3tMq8fPmS8PBwypUrl2GM7/Ls+/bty+DBg1m4cKHWfrqp6drjNS19xrHmw6+nT59qLTGWOhH8Lm3JzB9//MHJkyfp1q2bzpkE+vyO5YZHjx6RnJysfOAXFhZGWFiYsrx3bozldxlLQgghhBAf019//cWbN2/YvXs3JUuWVI4HBgYqf/b19SUkJAQ3NzfMzc2pXbs2tWvXxsvLi7/++ovOnTtToUIFIOW1eHZeUxYsWBAXFxcuXryobBsBKUvXApQpUybdNZaWlh/8vVFGHj16xOrVq5k7dy7Ozs7069ePxo0bKzODNXub/vvvv5QvX16vOi0sLDA0NMz0Nao+zyQtzWtST09PrVg09b6P16wmJibMmzePrl27snr1amUFJX3Gy4EDB3JlbOZWu3PS50IIIYQQQgjxqUu/ieUHolmG9NatWyQkJBAeHs7mzZt59uwZACEhITx79ozBgwfz448/Eh4eTkJCAg8fPuSff/5R3sxZWlrSqVMndu3axZkzZ4iNjSUmJoaTJ0/So0cPJXmoy+DBgwkJCWHixIk8e/aMBw8eMHbsWPLkyUOnTp3eex/oa+LEiSQmJnLgwAGt42XKlOHq1avcv3+fqKgoLl68yOnTp7XKWFhYEBQURHBwsNYysDmVL18+OnTowKFDh5g2bRq3bt3i5cuXeHl5cejQIcaOHYuNjQ1ff/01efPmxd3dnSNHjvDrr78SERHB8+fPGTVqlJIIzps3Lx06dODw4cOcO3eOhIQEXr58yYwZM7C0tMwwaQ7v9uwbNmzIoEGD2L17NwMGDOD8+fN4eXlx//59Dh48SI8ePTh8+DB9+vTJtD/0GceOjo5Uq1aNXbt2ce3aNSIjI7lw4QInTpzIlbZo+Pv74+/vj5+fH7du3WLevHmMGDGCihUrMmHCBJ3X6PM7Bu8+jmJiYli6dCkRERFERESwePFiVCoVbdq0AXJnLL/LWBJCCCGE+Jg0S8Feu3aN5ORkgoKCmDlzJgYGBsTFxREZGcnly5cZMGAAp06dIjo6mvj4eK5cucKLFy+U123ly5enevXqrFixgps3b5KYmMibN2/Ytm0b/fv3V7bn0GX48OFcuXKFZcuW4e/vz/Xr15k1axbFixenYcOGH6Qf0kpISMDb2zvD/yIiIkhISGDChAnUqVMHDw8PatWqRZcuXZg2bRphYWEAVK5cmcqVK7NhwwauXr3K27dvuX//Pr1792bu3Lk6721sbIyrqyunT5/Gz8+PyMhI9u/fz+3bt5Uy+jyTtCpWrMiXX37Jhg0b+Pfff0lMTOTRo0csXbr0vfZ15cqV6dWrFz/++KPSBn3GS26Nzdxqd076XAghhBBCCCE+dR9tZm2xYsUYMWIEmzdvZufOnZibm9OjRw9Wr16Nu7s7AwYM4Pvvv2fmzJls2LCBRYsWpQRsbEyzZs2YMWOGUtfkyZMxNjZm8uTJxMTEACnLcvXr10/r279pVapUiTVr1jB37lxat24NQKlSpdiyZYvO/T0/Fjs7O8aMGcOsWbO0lof67rvvePr0qZKEqlq1KlOmTKFnz56oVCoA2rVrx7lz52jQoAE9e/bU6recmjp1KsWKFWPPnj1aCWQLCwsaNmzImDFjlP7TLI02adIkEhMTgZQPCmbNmqVVH8C4ceNISEhArVZTvnx5tm3bluVzyOmzBxg/fjxVqlRh+/btjBw5Uukza2tr6taty4EDB6hcuXKmdeg7jhcsWMCoUaPo27cvkDILdOrUqQwePJikpKR3bktycjJNmzbVOubs7MzQoUMZMmRIuv2kNWrWrKnX79i7jKPk5GS++uor4uPjqVu3LomJiVhaWjJr1ixllkNujeV3GUtCCCGEEB9L48aNadu2LXPmzGHOnDnky5ePUaNG0b17d7p3706zZs1YtWoVvXv3ZsaMGVpLx3bs2JGBAwcqda1Zs4ZZs2bxzTffKK+/ixUrxujRo7G2ts4wBnd3dyIjI1mzZg2bN28GoHr16ixYsCDD15Lv27Nnz5Qv9+kyefJkgoODCQwMZOvWrcrxiRMncvnyZaZNm8b69esBWLduHVOnTqV///6oVCoMDQ2pV6+eVt+lNX36dMaNG0ezZs0wMDCgWbNmjB49mjFjxpCcnEyPHj0ICgrK8pmktXbtWqZNm6a81jUwMKBWrVrMmTNHWfHpfRg9ejQXLlxg0qRJHDt2DDMzsyzHS26Ozdxod077XAghhBBCCCE+ZQZqtVqtb+GwsDCioqKUZV0zExgYiLGxMQ4ODsqxxMREAgICsLe3V/asSUhI4PXr19jZ2Wnt7RkeHo6dnR3Gxin5ZM2sv9TH0kpMTOTVq1eYmZmRP39+DAwM9GqXWq0mNDQUIyOjd9ob9F2FhYURHx9PgQIF0p1TqVT4+flhZGRE4cKFtc6Fh4ejVquxtbUlOTkZf39/HBwclMSu5hvHtra2gO5nAynL/pqZmWWrDzTPz8jICHt7ewwNdU/Wjo+P5/Xr1+TLly/DvakSEhJ49eoVFhYWyoxVjYxi1sjps9dISkri9evXmJiYZHh9ZjHoO45fvXoFgL29vfKsUv8+5KQtYWFhWsuzGRgYKHsy65LRc87qdyyn48jf3x9LS0vy589PbGws4eHh2Nvb6/zQL7tjOaO2ZHcs6fq7SQghhBAiM0FBQajVap2v3dN68eIF+fLl03pdEhMTQ2hoKAUKFFBeF8XExBAZGYm9vb3yeiwmJoaoqCjltbZKpSIsLAy1Wo2dnV2Gr7/j4uJ4/fo1efPmJV++fHq3Kzk5mdDQUPLkyZOt63JbUFAQ8fHxmZaxtbXlzZs3mJubp3tNqnmNXLhwYWUrDkjZlzcyMhJbW1vMzc2V42q1Gl9fX/Lnz58uqR0aGoq5uTlWVlbExcURHBxMwYIFlQRjZs8ks3pjYmIIDw8nX7586V676ztmdPVbZuNS0y9OTk5a7c9qvOTm2MyNdut7LyGEEEIIIYT4HGQrWSuEEEIIIYQQQgghhBBCCCGEECJ3yNdPhRBCCCGEEEIIIYQQQgghhBDiI5BkrRBCCCGEEEIIIYQQQgghhBBCfASSrBVCCCGEEEIIIYQQQgghhBBCiI9AkrVCCCGEEEIIIYQQQgghhBBCCPERSLJWCCGEEEIIIYQQQgghhBBCCCE+AuOPHYDIWFJSEhEREZiZmWFoKHn1/0tUKhXx8fHky5cPY2P5NRVCCCGEEO+HvOf4v03edwghhBBCCCHExyfvxnJArVZz9uxZXFxcKFOmTIblrl27RnJyMnXr1tU6/ujRI7y8vHBycqJatWoZfigSERHB8+fPczN08ZkpXrw4dnZ2HzsMIYQQQgjxHyXvOQTI+w4hhBBCCCGE+JgkWZtNUVFRjB8/nr/++ovvvvsuw2Stj48PgwcPpnr16lrJ2jlz5nDy5EmqVavGo0ePKFq0KJs3b8bU1DRdHWZmZkDKG+c8efJkGVtycjJPnjyhdOnSGBkZ5bCFWfsv3edTbUtsbCzPnz9XxoAQQmRkxowZBAQEsG7dunR/Zzx8+JBFixbRunVrunbtCsDatWsxNzdn4MCBSrlbt25x8uRJAgMDMTExwcXFhU6dOlG0aFG9y6Std8aMGURGRrJ06VKtmTr+/v5MmzaN7du3K8cSEhI4ceIE165dIyIiAltbW+rUqUPr1q0xMTHJVl/4+voqPxsaGuLo6EiDBg1o3bo1BgYGOsul1qFDB9zd3ZW4jh8/zvXr14mIiMDOzo769evTokULrTaNHTuWNm3a0KxZM626njx5wvz581m/fj0WFhY6+yi34k1dxsjICDs7O9zc3Pj666/1eg2RUR+m9uOPP2JoaJhlOzKKz83NTenbzO6bVfz6jNcP5erVqxw6dIilS5eSmJjIoEGDmDlzJi4uLh88lg8tICCAVatWkZiYyKJFi5S2Fy5c+P9UP+SWjzl+NP92FC1aFEtLyw9679zyoV7Tv28fox3yvkMIIYQQQgghPj5J1mZTnz596NKlC2FhYRmWUavVzJgxgypVqmgdv3XrFkeOHOHYsWMULVqUqKgoOnTowMGDB+nRo0e6ejQzbvPkyYOFhUWWsSUnJwNgYWHx3hOP/5X7fOptkaXohBBZ8fT0xNfXlwsXLtCmTRutc4cOHcLT05Ny5copx548eaL1b8qBAwdYtGgRw4YNo0mTJsTFxXH69Gk6dOjAkSNHKFKkiF5l0tbr6emJt7c3O3fu5JtvvlGOx8TEcPXqVeXnsLAwvvnmG2JjY+ncuTPOzs68ePGCxYsXc/jw4Qy/0JRRX7i6utK6dWsg5e/eZ8+eMXPmTO7du8fEiROVciVLlqRFixbp6ihVqpRWXHFxcUpcAQEBLF26lF27drF582by5s0LpPz7/uWXX6arKzIykqtXr5KUlKSz73Mz3tR1xcfH8/z5c7Zt28bGjRvZunUrJUqU0LsPM7qXJnmsqx36xOfs7JzpffWJX5+x+CGFhITwzz//ACn/Zjdq1Ahra+sPGsPHsn79ep4/f87YsWO12q5Sqbh69SpRUVEfO8SPbs+ePZQqVQo3N7csy37M8aN5vWlubq7Xe45P0Yd6Tf++fcx2yPsOIYQQQgghhPh4JFmbTVOnTqVatWocPnw4wzIHDx7E0NCQxo0b8+effyrHL168SJ06dZSZH3nz5qVt27ZcuHBBZ7JWCCGE0EfNmjU5evSoVrI2KSmJU6dO6UwiprZ3714GDRrEgAEDlGPNmzfn0KFD2SqjS69evVi7di1t2rTByclJZ5m5c+cSHx/PkSNHtGZ0dezYkXbt2nHgwAF69uyZ6X1SK1myZLoZro6OjsyePZtx48YpH367urrSqlWrDOuZNWsWSUlJHD58WCuuLl260L59e5YtW8bMmTP1jut9x6urrkGDBjFs2DBGjRrFsWPH9P4gXp975cY1aekTf07H4odgZGREv379PnYYH0xAQAB16tShZs2aAErb4+PjP2JUn5bz58+TP39+vcr+Xxs/QgghhBBCCCGE+P/k67PZVK1atUzPv3r1ilWrVun8ANfHxyfdEn1FixbFx8cnV2MUQgjxf0v9+vW5fv06r169Uo799ddfFCxYEEdHx0yvzZMnD//++y+JiYlaxzt27KjMUtSnjC6VK1emadOmLFq0SOf5qKgozpw5w/Dhw9MtvVmgQAGOHTuWK19mKlSoEPHx8cTExOhVPiwsjN9++43vvvsuXVw2NjYMGzaMo0ePEhcX986x6ZLdeDNiamrKtGnTePLkiTL783OiK359xuLq1avZvHlzhvX+73//Y8qUKQwePJjJkydz69Yt5Vx8fDxbt25l1KhRjBs3jl27dikzoyFlJu3cuXMZOnQoK1asIDY2VjmXmJhIv3798PHxISYmhn79+uHv76+cv3TpEpMnTwZApVLRr18/Hj58yJw5cxgyZAibN28mISGBTZs2MXToUObNm8ebN2/06quc1BcSEsK8efMYOnQo69ev5+bNm4wePVqv+82fP5/79+9z/Phxhg8frtV2jbCwMKWvli5dytu3b4GUL5L069ePO3fuMG7cOM6ePQukLDu+fft2Ro0axYQJEzh69KheseRGe+Lj4+nXrx/37t3LVsyZjZeFCxfyzz//sG7dOlasWJFlG1P3oeZ5enl5sXjxYoYMGcIPP/xASEjIB+kPIYQQQgghhBBCfFgyszaXzZ07l06dOlGiRAkuX76sdS4mJibdvmsWFhZER0dnWmdycrKyJFZW5VL//335L93nU23L+45HCPHfYmNjQ+3atfn111+VmVnHjx/H3d2dBw8eZHrt+PHjGT58OE2bNqV+/fpUr16devXqYW9vn60yuqjVaiZMmEDr1q25evUqtWvX1jrv7e1NcnIyFSpU0Hl9gQIF9Gh95pKTkzl06BBlypTByspKOX7kyBFu3LiRrvzatWt5/PgxarWaypUr66yzcuXKxMTE4OvrS+nSpd85xneNV7Mcsy4uLi5YWVnx+PFjvZZizamcxpeVtPHrMxZbtGiR4fKhAQEB9O/fn+nTp1OyZEkePXrEoEGDOHjwICVLlmTw4MEYGRkxdOhQEhMTWbZsGXfu3GHx4sWoVCr69u1L+fLlGTJkCM+fP2f9+vVK3amX/7Wzs+Pq1ataCfeQkBD+/fdfIGW50atXrzJ//nz69OlDXFwcU6ZM4eLFi3z99df06tWLefPmYWBgwJQpU7Lsp+zWp1Kp6NOnD6VLl2bAgAE8evSIKVOm6P36Q5O4LF++PH369NG59PGyZcvo378/DRo0YM2aNTx48EDZ9/jq1assW7aMOnXqUKhQIQC+/fZboqOjGTVqFPHx8SxevJjnz5/rlWB81/ZAyv7DM2bMYODAgXrHnNl46dOnD0ePHqVz587KEuGZtTF1H2ruN3XqVLp37079+vVZsmQJc+bMYe3ate+tP1Qq1Wf7GvRDvaZ/3z5GOz73PhNCCCGEEEKI/wJJ1uaiP/74g3v37rFw4UKd583MzEhISNA6Fh8fj5mZWab1PnnyJFtx3L17N1vlc+q/dJ//UluEEP83eXh4sHHjRvr160d0dDSXLl1i6tSpWSZrq1atytmzZ/ntt9+4evUqy5cvZ8qUKbRt25ZZs2ZhYWGhV5mMODg4MHLkSH744QeOHTumdU4zOzJ1Ms/Hx4fZs2crP9vb27N06VK9+yF10lClUvHixQvMzMxYvXq1VrnKlSsre8WmZmpqqsSVOlmamuZ4Vl+2+lDxZsXKyipbH8brSrw6OTllOEP6XePLSur49RmLZcuWzbCuqKgokpKSKFGiBF988QVffPGFkux98OAB165d488//1RmpJuamtK7d2+mTp3Ks2fP8PHxYe/eveTLl48vvvgCLy8vTp8+neO2derUiebNmwMp+5sWLlxYWfb7q6++0pr1m5v1eXp68uLFC/bu3YuNjQ3Vq1fn0aNHWvtJZ6ZgwYKYm5uTP39+ihcvrnPp427duuHh4QGApaUlPXr04NWrV0pivXHjxsqXSx49esSlS5e4dOmSsrexsbExw4YNY8SIEZiYmGQaz7u2R6Nr167KcvJZxZzVeClYsCBGRkY4Ojri7OycZRt16dChg9KHffr0Sff3Qm73h5eXl171f8r+K6+1/yvtEEIIIYQQQgihH0nW5qIffviB2rVrc+rUKSDlTXZISAiHDx+mbdu2FCpUiMDAQK1rXr58mekSkgClS5fO9INwjeTkZO7evUulSpUynFGSG/5L9/lU2xITE5PtJL0Q4v+2Jk2aMGPGDB4/fsyDBw9wc3PDzs5Or2utrKzo2LEjHTt2BFJmmI0dO5ZNmzYxZswYvctkpFevXhw6dIjt27fTsGFD5bhm5uyLFy+UPW3z589P+/btgZR/Ry9evJiNXkhJ5mmSLXfv3uXevXscPnw4XV/o2itWQ5N48fPzo1y5cunOv3z5EkCJ2cjISGupXA3NF7SMjTN+uZUb8WYmJiaG0NBQChYsqPc1FSpUUBJ+GmmXg04rp/FlRVf87zIWS5cuzeTJkxkzZgxqtZpatWrRqVMnihQpwosXL7CystJaOrx48eKo1WoCAgIIDAzE2tqafPnyaZ1/F6m3x8iTJw+FCxfW+jm7+7/qW19gYCD58uXDxsZGOV+pUqVsJzczk3rWebFixQAICgpSEp9lypRRzvv4+GBoaMikSZOUYwkJCcTGxhIUFJTla+Xcak+pUqX0jjmr8ZJ6nOjTRl1L1pcsWVL5s7m5ud7jIaf94erq+k4z4T+mD/Wa/n37GO2Q9x1CCCGEEEII8fFJsjYXNWrUiMTERG7fvg2kfJj79u1bbt++TatWrahTpw4zZ84kOjoaS0tLVCoV58+fz/LDTSMjo2y9Wc9u+Zz6L93nU2vL5/whkxDi4zA1NaVVq1acPHmSe/fuKYmsnKhduzYNGzbk8ePH71RGw8jIiBkzZjBo0CCtJY8LFSpE6dKl2bdvHzVq1ABSlnRu164dkLIiRXaTtS4uLjRu3BhI+Xf5xo0bzJkzh1WrVuldR5kyZXBycuLQoUNMmzYt3fnjx4/j6uqqJBALFCjAs2fP0pV78uQJ9vb2mX7hKjfizcyxY8cwMjKiVq1ael9TunRpvvrqq1y5/7vSJ/7sjEVI+fJAr1698Pb25tKlSwwZMoSVK1diZWVFXFwcarUaAwMDAGUZ47x582Jubq61Ry2gtexvaprr1Wq1ckzXHsSachn9nF361mdmZpYu8RcREfFO904rdf2afkudCEw9W9ba2hojIyPGjRuXrp6slluH3GtP6uer2ZM6o5izGi9pvWsbsyOn/WFoaPjZvwb9UK/p37cP2Y7/Qn8JIYQQQgghxOfO8GMH8DkJCQlh165d7Nq1i1evXvHvv/+ya9cuZSbt9OnTmTNnjvJfq1atKFmyJHPmzMHCwoKmTZtSrFgx+vfvz/bt2xk+fDhv3rxRlqcTQggh3oWHhwe//fYb9+/fp2nTplmWDw0NZfLkyTx8+FDr+MuXL7l27RoVK1bUq4w+3NzcaNasWbok5Pfff8/p06f56aeftGanent7s3v3br1nB+tiYGDA7NmzuXDhAmfOnMnWdePGjWPv3r3plm4+cuQIR48eZeLEicqxDh06cPToUa2lgx8+fMiWLVvo2rXre49XF7VazdmzZ1myZAkjR4787GbL6Yo/N8bihQsXmD17Nmq1mpIlS9K/f38qVKjA06dPqVChAqamply4cEEpf+bMGQoVKkTBggUpU6YMSUlJyuzEhIQEzp49q/M+efPmxdTUFB8fH6XsuXPnctodua506dLExsbi6ekJvJ/4Utf3119/kT9//gxneFesWBFzc3PCwsKoVKkSlSpVIj4+nvPnz5MnT54s75Vb7clOzFmNF0j5ndYsq/6ubcyOD/F8hRBCCCGEEEIIkXtkZm02xMTEcO/ePQBlBtC9e/eUZRzTcnV1RaVSKT8bGhry008/sW/fPry9valatSoLFizIcE88IYQQIju+/PJLVCoVTZo0wdzcPMvyDg4OFCxYkN69e2NnZ4etrS3R0dH4+fnh7u7OoEGDMDMzy7KMviZOnEirVq20jtWrV48NGzYwf/581q1bR8GCBYmIiCAyMhJ3d3fGjh2b7X5IrWTJkgwZMoQ5c+ZQo0YNbG1tgZT9PM+fP5+ufLly5Zg3bx7t2rUjMTGRxYsXs3TpUpydnQkMDMTY2Jjly5drLefcqVMnAgICGDRoELa2thgaGhISEkKXLl0YPnz4B4kXYN++ffzxxx+oVCqCgoJISkpi1KhR9O3bN1sx5IQ+8ekqM2rUKKUvs4pfn/EKsHr1aszNzRk8eHC6eKpWrcratWtp06YNxYsXJzg4mMTERNzd3cmfPz9z585l+vTp7N+/n9jYWF68eMGyZcswMjKiUKFCDBw4kGHDhlG1alWCg4OpWrUqQUFB6e5jYGBAt27dmDp1KgcPHuTVq1c0aNAgw+Tuh1akSBF69erFwIEDqVGjBqGhoVSpUoXff/9dKbN27VqMjIwYNmxYturWvPZNSEigW7duWFtbc/PmTWbOnJnhHsb58uVjwYIFTJ48mTJlymBoaMj9+/eZOXPmB23P27dv6datG/ny5ePGjRuZxpzVeAEoW7YsS5Ys4cqVKyxYsOCd2pgd+vSHEEIIIYQQQgghPh0G6tTrs4lPSkxMDA8fPqRcuXJ671l7+/Ztqlat+t73X/2v3OdTbUt2n70Q4v8uT09PChUqpCyj6eXlhZWVlbKfqpeXF8bGxsremo8fP8bIyAhXV1eljsTERJ49e0ZkZCR58+alSJEi6WZiZlUmbb1p49J48uQJr169ok6dOuna8uLFC0JDQ7G0tKRkyZIZJkky6ws7OzutfTohJWl069YtSpYsiZOTE56enkRHR+usw8rKikqVKmm129vbm+HDh9OkSROmTJmCoaHuhUmio6Px8vJCrVZTokQJrK2ttc7r6qPcijd1GQMDA/Lnz0+JEiVyrQ+zakd24kutVKlSODg4ZCv+rMbio0ePMDIy0tp/NC1vb2/CwsKwtbXV2hcUUv4NfvbsGSYmJri4uKSLITAwkJcvXyrXeXl5Ub16dVQqFdeuXaNy5cpKPD4+Prx+/ZqyZcsqcVerVg2AK1euaJV9+PCh0h6AgIAAXr9+rTUeM5OT+vz8/AgJCaFs2bKcOnWKHTt28Ouvvyr1HT9+nIULF+q834MHD7CysqJIkSJabc+TJw/Xr1/nyy+/5M2bN7x8+RIXFxfliweauitVqpTuC4txcXE8e/aMxMRESpUqle3XQDltT3x8PJUrV+bQoUPY29tnK+bMxktcXBz379/H2dmZQoUKZdrGtOMn7f1ev36Nj48Pbm5uudIfadvw8OFDSpcu/dl+ifRDvaZ/3z5GO+R9hxBCCCGEEEJ8fDKzVgghhMgFnp6exMfHKysvpBYTE8Pt27cpWLBgpklTSEkEaWZwFi1aFBsbm3T1pS5TrFgxrTLJycm8fftWSdZGR0dr7VtZpkwZrZjq1KmDiYmJclylUuHt7U1ERAT58+fHxcUFQ0NDrTK6pD6nSbw9efKEJ0+eYGBggKOjI8WKFaN06dKULl1aq1xaCQkJhISEaCUMU8dlZ2dH8eLF0+3HmZiYiLFx+pc2mr0bNUsqm5ubY2lpqTPZ+PbtW65evarEa2JiQtmyZWnXrh379++nVq1aOj/MLlq0qBKvZiUOIyMj7OzsKFGiBIaGhun6r0qVKjr70tTUFEtLS7y9vfH29k53vnbt2hgYGChjSFOXph1qtZqwsDDCwsLSxadPMtbX1xdfX9908WukbkdgYCDJycnkzZs3w/GaWVv1PZ+akZERr1+/1kpMpla2bNlMr1epVAQHB2d4vYWFRaZLKhcoUEBrVZXq1asDKSuopP0SgouLCy4uLsrPmkQtkK5suXLltH4uWLBghkvw6pKd+tRqNdOnT+err76idu3aqNVqLl26pNV3YWFhmf7Oly9fXvlz2rZr/uzs7Iyzs3OWsWqYm5tr1auv3GiPpp7sxqwZL6Ghody9e1frGZubm2v9rDmmaaO3tzfR0dFUrlw5wz7UsLOz03tZeH36QwghhBBCCCGEEJ8OSdYKIYQQuWDGjBk8evSIX3/9Nd2MvuPHjzNz5kz69+/P999/D8C6deuwsLBQZnkFBQUxevRo/Pz8KFGiBHFxcTx+/Jivv/6aOXPmYGRkpFeZtPXOmDGDp0+fcvjwYa0P6v39/fnmm294/PixcuzIkSMsW7aMxMREHB0dCQwMxNrammnTptGkSZNs9cWbN2+UhHFycjL+/v7ky5eP5cuXK4mwGTNmEBYWhoODQ7o6evToQadOnQDYunUrK1euRK1WY2pqSnx8vDJb2NbWFhMTE7Zs2cLYsWMZPHgwvXr10qrr8ePHfPPNN9y8eRNra2udfZRVvAMHDmTbtm2MHDkSc3NzihUrppXA1MSbuq74+Hh8fX0xMzNjyJAh9OvXL12CObM+zKhvDhw4kOGzzuiali1bcvXq1QyTtZo+1Dd+fcbi+5KYmMg333zDwYMH9Z51mlpSUhITJkxg27Ztn0XyytfXlxkzZmR4XvPsssPAwABXV1e+/fZbvvjiC4KDg0lKSmLz5s1KmTJlytC4ceMcx51bfH19mThxIkZGRpiYmKQ7r2l/brQnIiIix3FeuXKFVatWcfHiRb3K7969m0WLFlG3bl3Wr1+fZXk/Pz8sLCyIjo7Wazxk1R9CCCGEEEIIIYT4dEiyVgghhMglrq6uHD16lAkTJmgdP378OCVKlMj02rlz52JnZ8cvv/yiJLqeP3/OkCFDuHXrFjVr1tSrjC5ly5Zlzpw57N69O8P7Hz16lOnTpzNnzhzat2+PgYEBCQkJbN26lW+//Zb9+/dnOtswra5du2rt15qQkMDkyZOZMGECp0+fVo537949031dDx8+zIoVKxg1ahRNmzYFUmaNnTx5ko0bNzJz5swM250dWcVraWlJ8eLF+eKLL+jevTtlypTJMPGatq4TJ04wZ84cwsPDs7UHb1Z9k51rEhISaNasGSNGjKBevXp0795d63zqxLM+8ed0LH4KTE1N+fvvvz92GHpzdnZm+vTpGZ7PaFnurPTr1w93d3d8fHywtrbGxcVFa2Z6ZstIf0jOzs7Y2tpSs2ZN6tWrl+68pv3v0h4TExPq1KnDq1evcr8BGbh8+TJdu3ZlypQpepVfu3YtjRs3pkmTJnqNh6z6QwghhBBCCCGEEJ8OeccuhBBC5JKGDRty4sQJxo0bp3xg7u/vj7e3N40aNcr02hcvXtCmTRutGYnFixfn7Nmz2SqjS58+fVi9ejVHjx7Fw8Mj3Xm1Ws3KlSvp2rUrHTp0UI6bmpoyfPhw4uPjM9yTVF+mpqZ07tyZvn378vbtW732RUxKSmL58uX06dOHwYMHa50bNWoUQUFB7Nq1i27dur1TbPrGa2BggJOTU7ZnY3799dckJCQwc+ZMevbsqczg/ZBMTU0pWbIkZmZmOvdpzYyu+PUZi/rsHRsdHY23tzfm5uaUKlVKKwEeERGBj48PpqamuLq6Zrr/bkxMDD4+PhgZGeHi4oKZmRmQMravXr1KtWrVeP78OTY2Njg4OKTbWzY2NpZnz55hampK8eLF083gfP78Oa9evcLOzk5rWWN96Lo2KSmJGzduULVqVWVZ7eDgYAICAvjiiy+Ua0NCQvD398fV1RWVSsXTp0+VZZdT99GDBw+0+khXuzXjLm08qfdlzUpW8eSkL9K2Je3zfvLkCc+ePVP2/XV1dc207/Lnz8/Vq1cpWrQo3t7eWm3P6B4PHjwgMDAQX19fHj16pPyOZzUugoOD8ff3z/aYuHv3LsHBwVhbW3Pjxg1l+fyM4rt3756yD3jx4sX1/jsoKSlJ+XsrKioq289LCCGEEEIIIYQQH4Yka4UQQohcUqFCBc6dO8fVq1epW7cukDKrtmXLliQkJGR6bcOGDdm6dSvm5uY0adKEYsWK5aiMLqampkyePJmZM2fStGnTdIlSHx8fAgMD+frrr3VeP2bMGL3ukxV/f3/Mzc219nz18/PjypUr6cpWr16dJ0+eEBoaSrt27XTW1759ew4fPkxAQEC29vZ8X/HqWqJV4+uvv2b69Olcv34dd3f3XI/1XePLStr49RmLv/32m5KE1eXkyZP88MMPuLq68vr1a8zNzdmyZQv29vbs3LmTtWvXUrlyZcLDwwkKCmLbtm069xz99ddfmTt3LhUrViQxMZGnT5+ycOFCGjRoQHJyMt988w39+/fn0KFDfPfdd3Tu3FlrGeVz584xY8YMKlSoQHx8PC9fvmT16tVUrFiRhIQEBg0aREhICMWLF8fb2xsnJye2bNmCubl5pn2W2bUJCQl88803nDhxQtnD+fLly2zbto0zZ84AKTMpt23bhpubG8HBwXz55Zf88ccf/PHHHwCZ9pGudnfp0iXHbdEnnpz2hbm5eaZtuXLlCgEBAcoy5gULFsy073S1vVevXtm6R9myZTMdFwDr16/nxx9/pHr16gQHB1OkSJEs+0Hj77//JjQ0FJVKxalTp6hRo0a243ufz0sIIYQQQgghhBAfliRrhRBCiFzk7u7O0aNHlWTtiRMn+OGHHzh48GCm140ZMwZ7e3v27NnDwoULcXR0pEGDBvTu3Vv5YF6fMrqo1WqaN2/Ovn37WLlyZbolNF+/fg2glfCMiorizp07ys9mZmZUq1ZN735InTRUqVQ8e/aMdevWMWDAAK3ZmFeuXMHb2zvd9du2bVOWJE27v6qG5nhISMg7J2tzI97MkqGmpqY4OTkpfZ3dmDTMzc358ssvM7wmp/FlJW38+ozF7777LsP6wsPDmTZtGqtWraJBgwao1Wpmz57NzZs3ad26Nffu3WP58uXK79HQoUP56aeflP15NcLCwpg+fTpLliyhWbNmAPz0009MnTqV33//XVn2NSQkhGvXrmFoaEh8fLxy/Zs3b5g0aRI//PADbdq0AWDTpk3MmDGDw4cP8/DhQ/755x/++ecfTExMSEpKYuHChcrs0sxkdq2jo2Om1wYFBbFhwwa2bdtGrVq1iI+Pp1u3blpLHmfWR7ra7enpmeO26BNPTvvC1dU107YMHjyYHTt20LNnT1q1akVkZGSm99LV9qz6K+09shoXwcHBrFu3jh07duDm5oZKpWLAgAF69YXm3teuXaNatWqMHDky2/FlJafPS6VSkZycrHc7PiWauD/X+DU+Rjs+9z4TQgghhBBCiP8CSdYKIYQQucjDwwN3d3eio6N59uwZ8fHxVKtWLctkrZGREf369aNfv34EBQVx7do1jh8/TqdOndi0aRN169bVq0xmpk2bhoeHBx07dtTau1CzFGx4eLiSRAoMDGT+/PlASuLW0NCQixcv6t0P165d4/nz50BK0iQ8PJx58+bRunVrrXJp90dNzdLSEkhZGlQTY2qapI1mydusZLTHbG7Fm5Xo6Gisra31Lv/nn3/y4MEDrWMFChRg48aNGV7zLvFlJXX87zoW7927R1JSEg0aNABSns2sWbOU84sWLSI8PJz79+8TExODpaUloaGh6eq5f/8+iYmJyn7GAM2aNWPhwoUEBARQtGhRAFq3bq0zUXX37l1iYmKwsrJSEuP29vbcv3+f8PBwXF1dlZmcLVu2pHbt2kybNk2v/srs2qwSjo8ePcLExIRatWoBKWO8efPmWn+P6NNHqdv9Lm3RJ56c9oW+bcmutM88O/fIalw8fPgQIyMj3NzcgJR9Yps0acJPP/2U43hzsw9y+ry8vLxydL9Pyd27dz92CLniv9IOIYQQQgghhBD6kWStEEIIkYuKFCmiLKF5//593N3dM00S6uLs7IyHhwceHh4MGDCAAwcOpEt+6VMmreLFi9O3b1/mzJnDnDlzlOMuLi5YWFjwzz//KMvMlipVil9//RWAM2fOsHjx4my1oXPnzkrSMDg4mNatW5OUlJStOlxdXTE2Nub27dsUKlQo3fm7d++SJ08eSpQoAaQkncPDw9OVCw0NxdjYWEn+vq94M/PgwQMiIiKUJVT10aNHj/eWeM2uzOLPyViMiorKMMmekJDA+PHj8fT0pFq1alhYWPDs2TOde6tGRUVhbm6u9TumWdI39T7LNjY2Ou8VHR2NoaEhBw4c0DresmVLYmNjyZ8/P0eOHOH8+fNcuXKFTZs2UbhwYdatW4ednV2mbbS0tMzwWl2znFUqlVZcefLk0Tqf+n769lHqdmcWT1ZtySqerGR2bysrK72fd0ZS951G6rZnZ0xB1uMiJiYm3fjV90sjumQ3vqzk9Hm5urrq/GLM5yA5OZm7d+9SqVIlrdUQPjcfox0xMTE8efLkg9xLCCGEEEIIIYRukqwVH13k3zYZnisFRF9Lf9y67pv3FY4QQrwzDw8Pzp8/j6enJzt27MiyfFJSEn5+fhQrVizd7D9jY2OMjIz0KqOPoUOHcvz4cU6ePKkcMzc3p0OHDqxfv56WLVumSxAEBwfrVXdGnJycGDt2LHPnzqV27drY29vrdZ2NjQ0tW7Zk7dq1NGrUSCvZGhUVxaZNm+jYsaOSJPnyyy+5cOECI0aM0OqjkydP4ubmpveSrTmNNyMJCQksXLiQatWq6dxz9VOXNv7cGIvFixfn7du3BAUF4ezsDIC3tzempqZ4eXnxxx9/cOXKFSVxNH78eJ2JeE09wcHBODk5ASmzAw0NDfXaQ9TFxYXk5GRmzZqljPvY2FgiIyNxcnIiKCiI8PBw3N3dcXd3JzExka5du3Lo0CEGDx6cad2ZXdu3b18A4uLilPLPnj1T/uzo6EhERARRUVFKH9y/f185//fff+vdR/rEk1VbsoonK5ndu1SpUtlqi+b3PaO+0yW7/ZXVuAgICODt27eEh4eTP39+gHdKduXkeWYmp8/L0NDws050Qsqs/8+9DfBh2/Ff6C8hhBBCCCGE+NxJslYIIYTIZa1bt2bx4sW4uLgosz4zExkZSe/evalQoQItWrTA1taW6OhoLl26xI0bN9ixY4deZfSRJ08eJk+ezIQJE7SOjxs3Di8vL9q1a0e3bt0oVqwYERER/PXXX1y7do3JkyfnqC80evTowfHjx5k1axZr165Vjnt5eXHmzJl05fPnz0/NmjWZOnUq/fv3p2PHjvTo0YMCBQoQEBDA7t27cXR0ZOzYsco13377LZ07d6ZXr160bdsWIyMjzp8/z+3bt9m1a9cHiRdSko7nz59HpVIREBDAoUOHSEhIYOvWrdmKISf0iU9XmcqVKyv7/mYVv75j8dGjRxgZGVGqVKl08ZQrV45atWoxYcIE+vfvT3BwMCtWrGDGjBkULFiQpKQk/vjjD+zs7Dh37hzBwcHKf6lnTJYrV466desyZcoUhg0bRkxMDEuWLKFr1656zRAsU6YMDRs2ZPz48QwaNAhDQ0N+/PFH1Go1mzdv5vHjx0ycOJHvv/8eFxcXgoODCQoKonTp0gA8fvwYAwMD5efUMrvWzMyMEiVKsHnzZvr06cPjx4/53//+p1xbtWpVHBwc+OGHH+jRowcPHz7k1q1bynkbG5tM+0iTuNY3nqxkFc+79EW+fPmybIulpSVXrlzB3t4eNze3TPtOF336K+09MhsXX3zxBYUKFWLGjBl0794db29v/vjjjyz7MTfjy4w+z0sIIYQQQgghhBCfDknWCiGEELmgSpUqygxMa2trevbsqZW0cHV1xcrKSvm5dOnSynKttra2/Prrrxw9epQrV64QGRlJ3rx5KVmyJGfOnFESL/qUSV1v2rg0WrRowZUrV5Q9WgEsLCz48ccfOX/+PJcvX8bT0xNLS0vc3NyYM2cODg4O2eqLwoULax0zNDRkzpw5LFy4kIcPH1KuXDmqVKmCr68ve/fuTVdH6dKlqVmzJnZ2duzbt49jx45x48YNFi9eTMWKFRk2bBht27bV2nvX2dmZY8eOsW/fPv7++2/UajUVK1Zk7ty5WskrXX2UW/FqyuzatQsDAwPy589Pt27d8PDwyHQZZn36UNc907ZD3/jSlsmXLx8FCxbUK359x+tvv/2Gubm5zmQtwKZNm9ixYweHDh3CzMyMefPm0axZMwDmzJnD6dOnMTExoV27dgwZMoQFCxawfft2xo4dS+3atZVk7IYNG9i5cyc///wzJiYm9OnTh44dOyr3qV27ttZewYaGhlrXr127lt27d7Nv3z4SExNxc3OjT58+ADRs2JAlS5Zw6tQpTp8+ja2tLfPnz6dRo0YAnDp1Cj8/P5YvX56ufVldu2bNGrZt28a2bdtwc3Nj0qRJ7Nu3DwATExN+/vlntm3bxoYNG6hevTqDBw9mzZo1AHzxxReZ9tH333+frt1ZxZOZrOJ5177Iqi0TJ07k4MGDXL16FTc3t0z7Ttcz16e/0t4js3FhZGTEzp072bJlCzt27KBs2bL88MMPWjFkpXz58srs75zE967PSwghhBBCCCGEEJ8OA7Varf7YQQjdYmJilA+ILSwssiyfnJzM7du3qVq16ntdziq375PZMsgZya1lkD/VPsvusxdCiP8rhg0bhrGxsSQdxCfh3r17HD9+nClTpuRqvWq1Gi8vLwoUKKAkldetW8fVq1ezPUv8Q8XzvvpCZF92x4/mdWfp0qW1vlT0OflQr+nft4/RDnnfIYQQQgghhBAfn8ysFUIIIYReoqOj8fT0zPC8oaEhtWrVeq8xDBgwgN69e7N27VoqVapE3bp1tWbXfuo+VB+OGzcOf39/fvrpp3Qfvt+5c4dZs2bRrl07Ze/UJUuWkCdPHr799lul3MWLFzl58iRBQUEYGxvj4uJCt27dKFu2rN5l0tY7btw43rx5w4YNGzA1NVXq8fX1ZfTo0Rw+fFg5Fh0dzYEDB7h27Rpv3rzB1taWunXr0rFjR60Zxfr0hY+Pj/KzoaEhjo6ONGjQgE6dOinjJ2251Hr06EGnTp2UuPbv38/169fx9vbG2dmZvXv30r59e2U/VYDBgwfj4eFBmzZttOp69OgRU6ZMYefOnVhaWursIx8fH7y9vTE2NsbBwQELCwt8fHz4/vvvM2yXrnhTlzE2NsbW1hY3Nzc6deqkLCetz5g8cOAA58+fx9jYGHt7exITEwkKCsLJyYnk5GSMjIxYuXKlsv9wduKrXbu20rdp6RO/hj7j9UPI6e94QkIC3bp1Y8mSJZQsWfKd6580aRIODg7079+foKAgdu7cybhx47LXGCGEEEIIIYQQQnwQn8+nm0IIIYT4qCIiIjh+/HiG542Njd97stbNzY3169dz5MgRfHx8qF279nu9X277UH3o5eWFv78/v/32Gx4eHlrnDh48yIsXLwgKClKO+fn5aSV1t2/fzqZNmxg7diylS5cmNjaWU6dO0bVrV44cOUKJEiX0KpO2Xi8vL54/f87WrVsZPny4cjwuLo779+8rPwcHB9OnTx/y5MlD9+7dcXZ25sWLF/z4448cO3aMHTt2kCdPHr37okKFCrRr1w4AlUrFs2fPWLNmDY8fP2bmzJlKufLly/P111+nq6No0aJKXL1798bS0pLu3bvTvXt3AgIC+Pnnn9m7dy87duwgX758QEpSNiwsLF1dUVFR3L9/n+TkZJ19r4l32LBhnD17Fl9fX1QqFUZGRjx+/FirXFbxpm57fHw8L1684NChQ2zfvp0tW7ZQrlw5vcakl5cXTZs2BcDf3x8LCws8PDxwc3PD0NAQSFlKPSkpKdvxZZaY1Cd+0G+8fiip+/Pp06fky5cPR0dH5XxGv+NGRkb06tULW1tbvevXRVP/li1b2L59Oz/++CNWVlbMnj2bli1b5rBVQgghhBBCCCGEeJ8kWSuEEEIIvRQsWJCFCxd+7DBo3LgxjRs3/thh5MiH7MNatWpx7NgxrWRtQkICZ8+ezXLPy+PHj9O/f386d+6sVV/9+vWVxKI+ZXTp168fW7ZsoV27dhQqVEhnmTlz5mBqasq+ffu0Zqu2bduWr776iiNHjtCjR49M25Ba4cKFqVmzpvKzZk/TKVOmMHXqVGV2bZEiRahTp06G9UyfPh1LS0v27dunNTPY3d2d9u3bs3DhQhYsWKB3XJnF27x5c5o3b64cO3HiRLbj1dSVuu09evRg1KhRjB49mpMnT+o1Jtu1a4erq6tWgl0f+sSXlaziNzY2zvFYfB9S9+c333xDly5daNWqVZbXGRkZ0aFDh2zVnxlbW1vGjh2bdcBCCCGEEEIIIYT46Aw/dgBCCCGEECL31a9fn3/++Yfg4GDl2OXLlylRokSWs/esra25evUqsbGxWsebN2+uLHWrTxldypQpw9dff828efN0no+MjOTixYsMGzZMK1ELKQmo06dPZytRmxF7e3sSEhKIi4vTq3xoaCiXLl1i5MiRWolaAEtLS4YNG8apU6eIiYl559h0yW68GTEyMmLSpEk8f/6cmzdv5lJ0H46u+PUZi4sWLWLVqlU664yLi6NDhw7cunWLiRMn0qNHD2bMmMHr168BSExMpEOHDty8eZPBgwcrM1ujoqJYsWIF/fv3Z9CgQaxfv155PjNmzOB///sfS5cuZf78+UDK3qBr1qyhf//+DB06lJ07d6JSqYCUL1J06NABb29vkpOT6dChA/fu3WP69Ol0796dCRMm4Ofnp3c/+fn5MWnSJHr27MmiRYu4fPkyAwcO1Pt6IYQQQgghhBBCfDgys1YIIYQQ4j/IysqKhg0bcuzYMQYPHgzAsWPHcHd3z3TPS4BJkyYxfPhwGjRoQO3atalevToNGjSgWLFi2Sqji1qtZuzYsbRs2ZI//viDRo0aaZ1/9uwZKpVKWeI2rbR7leZEQkICu3fvplKlSuTNm1c5vmfPHs6fP5+u/I4dO/Dy8gKgQoUKOuusUKECcXFx+Pr65vo+qTmJ18rKKsP6ChcuTL58+fD29n6vS4nnNL6spI1fn7HYvXt3DAwMdNZnYGDA/fv3mT9/PmPGjMHKyoply5YxcuRIdu/ejZGREffv32fNmjW0atWKsmXLolarGTBgAPb29kycOJGEhAQWLFjAw4cPWbNmDWPHjuXcuXMMGTJEWX54yJAhmJmZMXHiROLj4/nhhx/w9/dn8uTJqNVq7t+/T0xMjHK/OXPmMGTIELp27cr8+fOZO3cumzZtyrJ/kpKS6Nu3LzVr1mT69Ok8evSIWbNmZXmdSqVSluf+3Gji/lzj1/gY7fjc+0wIIYQQQggh/gskWSuEEEII8R/Vrl07li9fzuDBg4mMjOTKlSv88MMPWSZry5Yty+nTp7l8+TJXr15l7969zJ07l8aNG7N48WKsra31KpMRGxsbxo4dy9y5c9MlCzUzDc3NzZVj3t7eTJgwQfnZ0dGRjRs36t0PqZOGarUaf39/ihQpwrJly7TK1a9fX9nbNjVzc3NlP9aM9srVLLebdnZnTuRGvFmxsLBArVbnKCaNAgUKsG7dugyveZf4spI6fn3Gomaf3Mz07NmT+vXrAzB+/Hi6dOlCSEiIsudsixYtlFndd+/e5fbt21y9elWZqT5hwgS6d+9OeHg4+fPnx9DQECsrK6ytrbl37x43btzg77//xt7eHoDvv/+e/v37M27cOJ3xdOvWTdkruGvXrqxcuVKvvrl9+zaBgYFMnTqVvHnzUrZsWW7fvs3ly5czvU7zhYTP2d27dz92CLniv9IOIYQQQgghhBD6kWStEEIIIcR/VIMGDZg2bRr37t3jwYMH1K5dW++ZqWZmZlr7pt6/f58hQ4awceNGJk6cqHeZjHTu3JkDBw6wefNmrT09CxYsCMDz588pUKAAkJKcHTlyJAD//PMPJ0+e1L8TgEaNGilJw3v37rF69Wo2bNiAk5OTVrm0+6OmpllO98WLF1SqVCndeX9/f634jY2NSUxMTFcuPj4eABMTk/cab2aioqIIDQ3NcM9gXerUqcNXX32ldSyr/WBzGl9WdMX/LmNRo0SJEsqfNXWnTta6uroq5/38/LC2ttZaUlyTEA4MDCR//vxadfv6+mJoaKjMcoeUGbAJCQkEBgbqXDo8dYLZzMyMhIQEvdoREhKCjY2N1izscuXKZZmsdXV11brmc5KcnMzdu3epVKkSRkZGHzucHPsY7YiJieHJkycf5F5CCCGEEEIIIXSTZK0QQgghxH+UiYkJX331FadOneLu3bv07t07x3VVqFCBevXq8ezZs3cqo2FoaMiMGTPo06cPlStXVo47OztToUIFdu/ercy6tbKyonHjxkBKsjO7ydoCBQrg5uYGgJubG3/++SczZszQa0lZjVKlSlGoUCH279+vM1l78OBBypcvryRUCxUqpDMB8uDBA5ycnDKcoZtb8Wbm4MGDmJqaZmsJ5GLFitGgQYNcuf+70if+7IxFjaioKOXPmhnSqZdrNjb+/2+dbGxsiI2NJTk5WUmqvX37FoB8+fKlqzt//vwYGRmxfPnydMsxFyhQIFuznLOSJ0+edHsba/bfzYyhoeFnneiElD2NP/c2wIdtx3+hv4QQQgghhBDic2f4sQMQQgghhBDvT7t27fjtt994+vRpuv1hdQkNDeXbb7/l5s2bWsefPHnCX3/9xZdffqlXGX1UrlwZd3d3VqxYoXV8ypQpXLx4kVWrVhETEwOkLAf877//8uOPPyqzV3Nq1qxZXL9+naNHj2brusmTJ3P48GF27dqlLIucmJjIjh07OHv2LJMnT1bKdu3alRMnTnDhwgXl2M2bN9m6dSu9evX6IPGmlZSUxIEDB1i+fDkTJkzINGH8KdIVf26NRUDrSwAXLlzAwcEhw7FWsWJFLCwstK45evQoLi4uyoxwAwMDZSa1Zr/hBw8eUKxYMYoVK8aLFy/45ZdfMDU11TtGfZQpU4a4uDiuXbsGpCSef/vtt1y9hxBCCCGEEEIIIXKPzKwVQgghhPgPq1SpEqamprRo0UKvpJCDgwNubm6MGTMGlUqFra0t0dHRvH37lu7du/PNN99gYmKSZRl9jRkzRmsZZEiZTbpjxw4WLFjAli1bcHBwICIiAnNzczp27MiwYcOy3Q+pFSlShBEjRjB//nzq1KmjLHO7Y8cOjhw5kq58xYoVWbFiBc2bN2f58uUsWbKE5cuX4+DgQGhoKAULFmTjxo3UqFFDuaZt27a8evWKyZMno1KpMDQ0JCkpiT59+jBw4MAPEi/Azz//zPHjx1Gr1YSEhJA/f35mz55N+/btsxVDTugTn64y33//Pc2aNdMrfn3GK8CiRYswNzdn1KhRGcZrYmKCu7s7lpaWPHr0iEWLFmW4XLW1tTWLFy9m2rRp7N69m9jYWGJjY1m6dCmGhinfh61atSrz58/nwoULrF69mqVLlzJ16lS2bduGkZERAQEBzJs3L5u9mrWCBQsyZMgQhg4dSqVKlYiJiaFOnTqcOXMm1+8lhBBCCCGEEEKId2egzs01t0SuiomJ4eHDh5QrVy7LPcEgZY+j27dvU7Vq1fe6nFVu3yfyb5tsX2Nd98073xc+3T7L7rMXQgghUvPy8sLBwUFZjtXf3x9LS0tlH01/f3+MjY2VfTL9/PwwMDCgcOHCWvUEBgYSERFB3rx5cXJy0pm4yqxM2nrTxpW63Js3b3QuLxwWFkZoaCiWlpYUKlQo3RKy+vSFtbW1kuDUSEpK4uHDhxQsWBA7Ozu8vLyUpW/TsrS01NrPVK1WExgYyDfffEOTJk34/vvvM7x/YmIifn5+qNVqihQpki5hrquPcive1GUMDAzInz8/BQoUUJKJ+soopqzakZ34UitSpAg2NjbZjj+zsejr64uBgQFFihRJd118fDyVK1fm0KFDFC1alODgYIoUKYK5ublS5u7du5QoUQJLS0uta5OTk3n58iUmJiY4Oztrjc+kpCR8fHxwcHBQ9opWqVS8fPmSxMREihYtqiytrFaruXfvHq6uruTJkyfd/SIiIggMDKRs2bI6267LmzdvCA0NpXjx4hw5coSdO3dy4sSJdOU0rztLly6ttezz5+RDvaZ/3z5GO+R9hxBCCCGEEEJ8fDKzVgghhBBZunbtGnFxcTqX0Y2KiuLatWsUK1aMUqVKAXDnzh2MjIyoUKGCVllvb28CAwMxNjbGxcVF2d9T3zJp67127RqGhoZaMxpTx6SZnaeRkJDAw4cPefPmDba2tpQpUybbS5Beu3ZNa29LAwMDHB0dKV26NGZmZhmWS61kyZK4uLjojMve3p6yZcum+6D+zz//pHjx4umSTW/evOHWrVs0bNgQExMTpY80CdHM4tUoUqQI165d49GjRxnGa2JiolWXkZERdnZ2lC1bVln2Na20sbq6umbaN8HBwTRt2hQDAwOtZ21ra5tlfC4uLly7dg0nJyetvtXcM+19NfFrklOpy2loxmJ0dDSWlpbKWDQwMKBgwYJ4eHjwyy+/MHDgQOzs7HTGZmJiopXo1beP0jI2NtZKZmdUTp+6sktXPUFBQXh5eVGvXj1Av3bcuXOH6OhopR1ZxZfd+AsUKJDhWCxatGiW16vVaqytrbG2tk53TtcXCSBlHGVUt7GxsfJ3ooahoaHOhLFarSY4OJhixYqRJ0+edPfLly+fzr1wM2rH2LFjadu2LU2bNiU5OZnffvuNihUr6nW9EEIIIYQQQgghPixJ1gohhBAiSwsWLODx48ccOXKEcuXKaZ07duwYc+bMoX///soMw61bt2JhYcHChQuBlFl3I0aMIDo6mlKlShEbG4unpyeNGzdm8eLFmJiY6FUmbb0LFizgyZMnHDhwQCsRERAQwIgRI3j8+LFy7JdffmHVqlVYWFjg7OyMv78/KpWKadOm0aZNm2z1RUxMDIUKFQJSZkL5+voCsGLFCmWPzAULFvD27VulXGodO3ZUEoq//PILK1euVGYDBgQEoFKpmDBhAu3atVOumTp1KoMHD06336mXlxcjRozg5s2bGfZRbsWbuq74+HhevHhBXFwc/fv3Z9iwYXrPBMvsXo0bN8bIyEhnO1JfExsbi7e3NwD58+fHxsYGb29vrK2tcXBwwNTUlL1796a7rz7x6zMWAfr378/ff/9NixYtKFSoEPv27cuVfWC9vb2V8fC+eHt7Ex4ezvz58zMso6sPNa5fv86qVau4ePGiXvfbvn07q1evpnHjxtSuXVuv+N53H7xv2WlDUlISixYtYt26dTqTxRo+Pj6MGzcuw/OaZ1a3bl0mTZpEiRIlCA0NxdbW9r0suSyEEEIIIYQQQoh3J8laIYQQQuilVKlSHD16VGeyNu3ssbTmzZtHyZIlWb58ubJMaEBAAN9++y23b9+mevXqepXRpXLlysyePZt9+/ZluDzq/v37WbhwIUuWLFH2R1WpVPz888+MGzeOAgUK8MUXX+jdF+3bt2f48OHKz8nJyUyfPp3vv/+ec+fOKcc7deqkVS6tPXv2sGjRIpYuXUqLFi2U40ePHmXy5MnkyZNH63hO5Va8uuq6cOECU6dOJTIykilTpugdkz73yuyapKQkwsPDtc7369ePRo0a0a9fvwyXS9Ynfn3HopmZGTt37sTPzw9jY+NcSdQCbNiwgWbNmqXbyzc3bdiwgcaNG7Np06YMy2R3yenMXLt2jS5dujBp0iS9yn+IPtAwNTXl4MGDuTYTWSM7bTA1NdX6XcxIkSJF9HpmnTp14quvvsLf3x9ra+vPOukthBBCCCGEEEL812VvwyohhBBC/J/VqFEjfv31V5KTk5VjL168wNfXN8vlNV++fImrq6tW8qdgwYIcPnxYSXzpU0aXHj16EBERwYEDB3SeV6lUrF69ml69emklTQwNDenXrx+jR49GrVZn3vgsGBkZ0a5dO3x9fYmMjNTrmsTERFatWkW/fv3SJWQ9PDzo1KkTy5cvf6e4MpKTeDPStGlTpk6dyq5duwgICMilCLNmbGyMg4OD1n/GxsZYWlri4OCAvb29XvXoil+fsejp6cm9e/cwMDCgaNGiFCxYUKtetVrNgwcPuHTpEvfv3083xkJCQrhy5Qq3bt0iOjpaOX7r1i08PT25e/cut2/fJjExkfPnz2stG/3y5UuuXr0KpIzv8+fPExsby7///oufn5/e93jw4AEvX75U+s/MzIznz58TEBBA3rx50/Xh8+fP+fPPPwkMDNSrb1PfLyAggODgYP74449s94G+Xrx4wV9//UVoaCivX7/m8uXLel2XnJxMcHAwAM+ePePPP//UGsuZ9fGbN2+4efMm//zzD2/fvs2yDZGRkdy8eRNPT0+t/Xo194iMjNS6n5+fH5cvX1Zmkesa96n/S/3MQkJCCA4OxtDQMFv9IYQQQgghhBBCiA9LZtYKIYQQQi9ly5bFysqKv/76i4YNGwJw/PhxWrdurZV00KV58+Zs2bIFtVpN06ZNKVOmTLpZsPqU0cXY2JipU6cyceJEWrRoQf78+bXO+/j4EBoaSuvWrXVeP2TIkCzvoY/nz59jYWFB3rx5lWPe3t6cP38+XdkGDRrw+PFjwsPDadu2rc763N3d2bdvH/7+/hQuXDhXYnyXeDPb27dVq1Z8//333LhxAw8Pj1yP9V3jy0ra+PUZi9euXcPMzEznFxXi4uLo06cPSUlJuLi48OTJE8zMzPj555+xsLBgy5YtbN26lVq1ahEeHs7jx4/ZunUrlSpV4v79+4SGhvL48WMKFy5MiRIlGDFiBCdOnFD2Gb5y5Qrbtm3jzJkzqFQqRowYQa9evTh37hwjRoyga9eu2bpH1apVOX78OPPmzaNmzZokJCTw4MEDVq5cqSyTvWzZMvbv30+9evV4+fIlNjY2evfvvXv3iIiIwM/Pjxs3btCoUaNsx5eVpUuXsm/fPurUqYOfnx9lypTh6tWrWsnhjCQlJTFixAjc3d15+fIlVlZWXL16le+//56ePXtm2McHDhxg6dKl1KxZk8TERP755x/mzZtHs2bNst3HiYmJjBgxgoMHD1KxYkVGjBhB7969uXv3Lvb29ly+fJkxY8bQv39/vfr8XfpDCCGEEEIIIYQQH5Yka4UQQgiht3bt2nHs2DElWXvixAkWL16c4b6WGiNHjqRAgQLs2bOHtWvXYmVlRb169ejTp4+y/LA+ZTLSsGFDqlWrxvLly/nhhx+0zoWFhQHg7OysHIuMjOTGjRvKz+bm5tSrV0/vfkidNFSpVDx79oytW7cybNgwraTenTt3eP36dbrra9WqpRxPOyNTQ7M3a2ho6Dsna3Mj3sySoSYmJjg7O6dblljfmDQsLCyoU6dOhtfkNL6spI1fn7GYWZL/0aNHPHz4kH///RdjY2NUKhUrV64kMDCQkiVL8vLlS9auXavM0h05ciQ7d+5k8eLF9O3bl82bN9OpUydatWqV5cxnY+OUl/NRUVFcunRJmQ2cnXuEhYUxc+ZMlixZQrNmzYCUPWZnzpzJiRMnCAgIYNu2bezZs4cqVaqgVquz9SWHfv368ccff1CtWjVGjhyZ7fiy8vLlS7Zt28Yvv/yiJD579Oih15c94P8vHWxpacnu3bsB2LdvH4sWLaJjx46Ym5sD2n386tUr5s6dy5o1a2jQoAGQsv/0jBkzaNiwYbb7WFc8CQkJ7Nu3D4BNmzZx+PBhvZK1Oe0PlUqltXLC50QT9+cav8bHaMfn3mdCCCGEEEII8V8gyVohhBBC6M3d3Z2vvvqKqKgovLy8AKhatWqWyVoDAwM6d+5M586dlWVDjx07Ro8ePVi/fj2NGzfWq0xmpkyZwtdff03nzp2V5AqAlZUVkJK0dXR0BFISoJs3bwYgIiKCxMRELl68qHc/3Lt3jzdv3gAQGBhIUFAQK1asUJLYGmn3R01NM6M1PDxca3arhiZxqO8+qJntL5ob8Wbl7du35MuXT+/y//zzT7plk52dnTNN1r5LfFlJHf+7jsUyZcpQvHhxunbtSosWLahduzZjxoxRntGsWbMICAjg5s2bxMTEYGBgoDMJnR0tW7bUGgPZuce9e/eIi4tTlt+FlAT2kydPCAsL4/Hjx5iYmFClShWlfxo0aKD8HZATudkHT548wdzcXJkFbGJiQtOmTdm/f3+26km9HHndunWJjo7m5cuXlCxZEtDu4wcPHqBSqahfv75yTYMGDZgzZw4vX76kePHiWnVn1ceWlpaZxlO0aFHldzgrOe2Pd3men4q7d+9+7BByxX+lHUIIIYQQQggh9CPJWiGEEELorVChQlSqVIkzZ87w4MED3N3ds12HjY0NzZs3p3nz5gwZMoQjR46kS37pUyatwoULM3DgQGbNmsWCBQuU4y4uLuTNm5ebN29StmxZAEqWLKkkLs6cOcPixYuz1YZ27dopScNXr17Rpk0bQkNDs1VHmTJlMDEx4Z9//qFIkSLpznt6emJhYUGJEiWAlKSzrmRWSEgIJiYmOpM9uRlvZu7cuUNkZKSSzNNH586d31viNbsyiz8nYzFPnjwcOnSIy5cvc+XKFcaNG0eePHnYsmULNjY2jBgxghcvXlCzZk0sLCwICgpSvlSgD5VKle6YtbW18uf4+Phs3SMuLg4jI6N0X1ho3749CQkJxMbGppu5bGJione8aWU3vqzExsZiZmamdSw7yzRrpK5D8+f4+HjlWOo+jomJwczMTCtBrrkmLi4uXd1Z9bGu39/UXzoxMDDQe2/tnPaHq6urzi+OfA6Sk5O5e/culSpVwsjI6GOHk2Mfox0xMTE8efLkg9xLCCGEEEIIIYRukqwVQgghRLa0a9eO8+fPc+/ePWXJ0MzEx8fj5eVF2bJl0334nJSUhLW1tV5l9DFo0CCOHj3K0aNHlWNmZmZ06dKFDRs20KJFC5ycnLSu8fPz06vujNjb2zN+/HgWLlxI/fr109WfESsrK9q2bcvatWtp3LixVhsjIiLYtGkTXbt2VZJkbm5unDt3juHDh2slyo4ePUrNmjX1XvI1p/FmJCYmhvnz51O7dm1lBuLnJG38uTEW/fz8eP36Nc2aNaNZs2aoVCq6du3KsWPHcHV15ebNm1y9ehULCwsARo0aRVRUlM66dCUAnz59mun9//7772zdo0SJEiQmJjJ+/Hjs7e2BlCV/Q0NDcXZ2xtnZmcjISF6/fo2dnR2QstRzTmU3vqw4OjoSERFBZGSk8nxyMjPR29ubatWqAfDixQsMDAwoUKCAzrIlSpTg7du3BAYGKmWePHmCsbGxzmXLs+rj1Enhd5XT/jA0NPysE50ARkZGn30b4MO247/QX0IIIYQQQgjxuZNkrRBCCCGypVWrVixYsIBSpUpRtGjRLMvHx8czcuRIChUqRIsWLbC1tSU6OppLly7h6enJzp079SqjD1NTU6ZNm8a3336rdXz06NH4+PjQrl07OnbsSLFixXjz5g1///039+/fZ+bMmTnqC43OnTtz7Ngxpk+friyvDPDw4UMOHz6crrydnR0NGzZk0qRJDB48GA8PD7p06YKzszOBgYHs37+fkiVLMnr0aOWakSNH0rVrV7p27UqbNm0wMjLiwoULPHv2jF27dn2QeCElSXfs2DHUajUBAQEcOXIEc3NzVq5cma0YckKf+HSVqV69ujJ7Oav49R2Lnp6eGBkZUbFixXTx+Pv7M2rUKL777jtcXFwIDg7Gz8+PChUqYG1tTWJiIr/++it2dnacP3+e6Ohonj9/jq+vL0WLFiVv3rz8/vvv5M2bl3r16lG6dGnWrFlDz549efz4Mffu3cu0nxwcHLJ9j5YtW/Ldd9/Rv39/jIyM2L59O/ny5WP16tVUrVoVFxcXJk2aRNeuXfH29ubvv//O9vN7l/gyU7VqVQoWLMj06dPp1q0bDx8+5M6dO1pl7ty5g4GBAZUqVcqwnj179mBubo6NjQ1r1qyhefPm5M+fX2fZ0qVL06RJEyZMmMCgQYOIjY1l5cqV9O7dW5mdmp0+zk369IcQQgghhBBCCCE+HZKsFUIIIUSWatasqczAzJs3LwMGDMDV1VU5X758ea3lMytVqqTMCLS2tub48eOcPn2au3fvEhERQd68eXFzc2Pu3LlKMkSfMqnrTRuXRsOGDenduzfPnz9XjpmZmbFhwwb++usvZWlaS0tLWrVqxerVq7O112rNmjVxcXHROmZgYMCcOXNYtmwZjx49omzZstSsWRN/f39lf8rUXF1dadiwITY2Nvzyyy+cOXOGGzdusG7dOqpWrcqUKVNo2rSp1mxZe3t7jh07xqFDh7h37x5qtZqGDRuyevVqbG1tdfZ9bserKXP27FkMDAzInz8/I0aMoHXr1umWXc1uH6alqx36xpe2TOHChSlSpIhe8es7Xq9du4aZmZnOZG3t2rVZt24dp0+f5ubNm9ja2rJq1Spq1qwJwNKlS/n9998xMTHB3d2d0qVLs2zZMo4cOcKoUaOYNm0aR44c4cGDB9SrV49169bx888/c+zYMdzc3JgyZQoHDx5U7te0aVOtpGKlSpWyfY8VK1Zw+PBhLl68SGJiIi1atKBLly5AyozLnTt3sn37dk6ePEm5cuWYP38+hw4dyvQZpvbll18qS3rnJL7MGBsbs2vXLnbs2MGBAweoXr06AwYMYO3atUqZP//8k2fPnrFs2bIM6xk7diw3btzg5cuXNGnShG+++SbDPgZYs2YN+/fv58yZM5iYmDBy5Ei++uor5Xx2+7hp06bK30Vp7+fk5ESDBg2y6ma9+0MIIYQQQgghhBCfDgO1vpsfiQ8uJiaGhw8fUq5cOWWJuMwkJydz+/Ztqlat+l6Xs8rt+0T+bZPta6zrvnnn+8Kn22fZffZCCCH+G7777jsSEhLYuHHjxw5FiM+GWq3mzp07FCtWTNmbdc2aNdy4cUOZCX3nzh1OnTrFpEmT0l0fHx9P5cqVOXjwYKYzbz8X+vRHaprXnaVLl87xvsEf24d6Tf++fYx2yPsOIYQQQgghhPj4ZGatEEIIIf4zRowYga+vL3v27NGa6Qvwv//9j6lTp9KxY0cGDRoEwNy5c8mTJw/jxo3j7du3XL9+nZs3b/K///2P8PBwjIyMcHJyomHDhpQoUYImTZoA8Ouvv3Ly5EmCgoIwNjbGxcWFXr16Ubly5XT1auJ6/fo127dvx9zcXInp+fPnDB06lDNnzgAwcOBAunXrRvfu3YmMjMTQ0BA7Ozvq1KlDjx490rUpq77w9vZWfjY0NMTR0ZEGDRrQq1cvZS/ctOVS69u3L927dwfgzZs37Nq1i+vXrxMREYG9vT316tWja9euWFpaAvD27Vu6d+9OnTp1qFGjhlZdvr6+bN++nVOnTpE3b16dfZRb8aYuY2xsjK2tLW5ubnTv3h0HB4cc92FqJ0+exMjIKMt2ZBRfvXr1lL7N7L5ZxZ/VWHzfNL83kJIQ/f333xk1ahSJiYnMnz+fIUOG0KtXr1ypXxdDQ0OaNGnCwoULMTc3p2/fvgQFBfHzzz8zbdo0pZy3tzfu7u45jiMrT58+Ze7cuSQnJ/Pjjz/i7u7OmjVrKFasmPLnUqVKvfN9cqs/hBBCCCGEEEII8emQZK0QQggh/jP8/f0JCgrizJkzdOrUSevc4cOHef36NWFhYcqxkJAQZSZRTEwMW7Zs4fHjx3z55ZcULVqUpKQkfH19WbZsGV9//TVNmjRh8+bN7Ny5k0mTJlG6dGliY2M5ffo0PXr04MiRI5QqVUqrXk1cvr6+bNy4UWsf2oSEBHx8fJSf7ezssLGx4fnz55QqVYphw4bx8uVLtm3bxsmTJ9m9e7eSGNWnL2rVqkXHjh0BUKlUPHv2jJUrV+Ll5cX8+fOVcjVq1KBDhw7p6ihQoIBSpnfv3jg5OdGrVy+cnZ15+fKlsszqL7/8gq2tLTExMfj7+3P//n2SkpK06goJCSE4OBiVSpWu799HvJq64uPjefHihRLn5s2bqVKlit59mNG9NLPedLVDn/jCw8Mzva8+8eszFt+3mJgYrly5AoCPjw8vX77kypUrqNVqypQpw9OnT3Otfl2MjY1p0qQJmzZtYvfu3Rw/fhwrKyuWL19O/fr1lXLt27fPsI60SxDnxJYtWzAyMmL27NkYGxszevRoHB0dUavV+Pj4EBcXl+O6U8ut/hBCCCGEEEIIIcSnQ5K1QgghhPhPqV27NseOHdNK1sbHx3Pu3Dnc3NwyvM7JyYn4+Hi+/fZbBg4cqHXu77//pkyZMgCcOnWKvn37au1NWblyZerVq5duT8vUBgwYwLZt22jfvj3FihXTWWbWrFk4Ozuzb98+TExMlOPNmzenbdu2nDhxgm7dumXeAak4OjpqLetapUoVzMzMmDhxIrNnz1bu4ezsTNWqVTOsZ/r06Tg4OLBr1y6MjVNePrq5udGqVSs8PDyYN28ey5Ytw8nJCWtra1q3bp1uNuWtW7c4d+7cB4k3bV1ubm506NCB8ePHM2bMGM6ePavVv5nR5165cU1a+sSf07GYm5ycnJgxYwYAx44d48WLF8rPuV1/ZqytrRk6dGiO7mFiYsL69etzdK1GaGgoX3zxBcWLFwegVatWQMrfPbnpQ/SHEEIIIYQQQgghPizDjx2AEEIIIURuqlevHnfv3uXly5fKsYsXL1KmTBll/8aM2NnZ8ccffxAZGal1vG7dutjb2+tdRpcSJUrQsWNH5syZo/P8mzdv+PPPPxk6dGi6RGK+fPn47bffspWozYiNjQ2JiYl6J5GCg4O5cuUKI0aMUBK1GmZmZgwbNozffvuNqKiod45Nl+zGmxEDAwMmTJjAy5cvuXnzZi5F9+Hoil+fsThnzhwWL16cYb1nz55lwIABuLu7079/f86ePaucCwsLY+7cuXTr1o2ePXuydOlSrefs7e3NyJEj8fDwYNKkSVqzhRMSEmjVqhVPnz4lKiqKVq1a8fz5c+X8mTNnlOXIk5OTadWqFdeuXWP48OG0a9eOOXPmEBERwezZs/Hw8OC7774jKChIr77KSX1eXl589913tG/fnhkzZnD+/Hm9l28eN24c//77L7/88gudOnXSaruGn58f3377LR4eHowfP165d2JiIq1ateLvv/+mV69eHDp0CIDIyEgWLVpEt27d6N27N5s2bSIxMVGveN61PUIIIYQQQgghhPiwZGatEEIIIf5TLC0tadKkCcePH2fYsGEAHD9+HHd3d/73v/9leu2UKVP49ttvqV+/Pm5ubtSoUYMGDRpQrly5bJXRRa1WM2rUKFq1asVvv/1GixYttM4/e/ZMWTpWlzx58ujT/ExFR0ezfft2vvjiC639b3/++WeOHz+ervz+/fuVvVMzal+5cuVISEjA39+fsmXLvnOM7xqvtbV1hvU5OztjY2ODt7c3derUydVYU8tpfFlJG78+Y3HIkCEYGBjorM/Hx4fx48ezYcMGSpYsyaNHjxg/fjyFChWifPnyDBw4EBcXFxYvXkxiYiI//PAD48aNUxKHAwYMoEWLFkyZMoXnz58zffp0pe7Uy/+qVCp8fHxISEhQzr99+xY/Pz8gZUlpHx8f1q9fz/jx44mPj2fw4MHcunWLUaNG0bNnT77//nvWr1+f4ZcdUstufQkJCQwYMIDGjRszYcIEHj16xLx58zLst7TmzZtHSEgIX3zxBUOHDtW59PGWLVuYOHEidnZ2LFq0iJEjR3LgwAGMjY3x8fFh06ZNdOrUiSpVqqBWqxk0aBAODg4sXryY+Ph4Zs6cSWBgILNmzcoynpy2R6VSkZycrFebPzWauD/X+DU+Rjs+9z4TQgghhBBCiP8CSdYKIYQQ4j+nXbt2zJ8/n2HDhvHmzRtu3LjB4sWLs0zWlixZkhMnTnD9+nWuXr3K+fPnWbFiBTVq1GDlypXY2trqVSYjVlZWjB8/nvnz52e4f2TqWbVPnz5l5MiRys9OTk7s2LFD735InTRUq9UEBwdTsWJFli1bplWuVatWyl6xqVlYWCgf5JuZmem8h7m5OUCu7MmZG/FmxdzcXO8kXNqYNAoVKsS2bdsyvOZd4stK6vj1GYtOTk4Z1mVgYEBycjKRkZHY2trSuHFjLl++jKWlJZ6enty/f58ff/xRmZE+duxYOnfuTFhYGN7e3gQHBzN69GgsLCwoUKAA7u7uHD16NMdt69GjB5UrVwagYsWKFC9enKZNmwLQtGlTrl279l7q8/T0JDQ0lAkTJmBpaUmRIkW4du0av//+u173MTc3x8jICBMTEywsLHTOAu/duze1a9cGYPTo0XTq1Ing4GDl+bRu3RoPDw8A7ty5w+3bt7l69ary98n48ePp06cPU6ZMwdTUNNN4ctoeLy8vvdr7Kbt79+7HDiFX/FfaIYQQQgghhBBCP5KsFUIIIcR/Tr169YiOjlYSTvXq1cPKykqva42Njalbty5169YFUpZ6HTBgAJs2bWLy5Ml6l8mIh4cH+/fvZ/369bi7uyvHCxUqBKTMdixYsCAABQoUYPbs2QDcvHmTw4cPZ6MXoE2bNnTu3BlISQAtXLiQRYsWKffSSLtXbGqaWF68eKEkvlLTzI7UlDM2NtaaQamhSeZmlmjKjXgzExERQWhoKIULF9b7mubNm9OuXTutY5oEdUZyGl9WdMX/LmOxePHirFq1iq1btzJlyhQqV65M586d+frrr3n58iXW1tZaS4drnnFgYCAhISFYW1trJaA153PK2dlZ+bOpqSmOjo7Kz2ZmZtlaBjg79YWEhJAvXz4sLS2V82XKlNE7WauP1PtUa/opJCRESda6uLgo5/39/TEwMKBHjx7KMZVKRWJiIgEBAcq+uBnJaXtcXV21ZrB/TpKTk7l79y6VKlXCyMjoY4eTYx+jHTExMTx58uSD3EsIIYQQQgghhG6SrBVCCCHEf46RkRFfffUVp06d4u7duwwcODDHdZUsWZJatWrx4sWLdyqjYWBgwMyZM+natStVq1ZVjjs5OVG5cmV+/vlnJfGWN29eatasCaC1H6i+7O3tlSVxy5Urx6VLl5g6dSrbt2/Xu46SJUtSvHhxdu/erTNZu2/fPipXrqwkwooUKcKjR4/Slbt79y4FCxbMNNGZG/FmZt++fVhYWCgzHPVRoEAB3NzccuX+70qf+LMzFiElGd28eXPevn3Ln3/+yezZszEyMiJ//vzExMSQlJSk7FUcEREBgK2tLa9evSI6Ohq1Wq3M9M1ojBoaGgIps6U13r59q1d8H4KlpSWxsbFax0JCQnL1Hqn3+tX8OXUiPPV+0La2thgbG7Njxw6l7zTy58+f5b1y2h5DQ8PPOtEJKX/3f+5tgA/bjv9CfwkhhBBCCCHE584w6yJCCCGEEJ8fDw8Pzp07x/PnzzNccji10NBQ+vfvz6VLl7SSSp6enly6dImaNWvqVUYfZcuWpXPnzqxYsULr+PTp07ly5QoLFixQEl+JiYn8/fffrF+/Xmt2Xk7MmDGDO3fusG/fvmxdN2XKFE6cOMHmzZuVGbKxsbFs2LCB33//nalTpyple/bsycmTJzlx4gTJycmoVCouXbrEtm3b6Nu37weJN634+Hh27NjB6tWrmTp1aoZLOn+qdMWfG2Px1KlTDBs2jISEBKysrGjdujVFixYlJCSESpUqYWVlxZEjR5TyBw4coHTp0jg7O1O+fHkAzpw5A6QkIHXt0wspXzrIkycP9+7dA1IStadOncpxf+Q2zb7Lly5dAlLacvbs2Vy9x9GjR1GpVACcPn0aZ2dnChQooLNspUqVyJcvH3/99RcODg44ODjw77//snbtWq2kbkY+RHuEEEIIIYQQQgiRe2RmrRBCCCH+k8qVK0fevHlp1KiR1j6wGXFwcKBVq1bMnTuXV69ekT9/fqKjozEyMqJPnz707dsXQ0PDLMvoa9SoUekSVpUrV2b37t0sXryYunXrYmVlRXR0NI6OjnTu3Jn+/ftnux9Sc3Z2ZvTo0SxatIj69esry7Fu2bKFX375JV35ypUrs2HDBho2bMj69etZunQpa9aswcbGhjdv3lC2bFl++uknrRnCLVq0YObMmSxevJjJkydjYGCApaUlgwcPznayNqfxAmzbto29e/eiUqkIDw+nWLFiLFu2jJYtW2YrhpzQJz5dZWbMmKHEl1X8+oxXgDlz5mBubs7EiRPTxdOgQQOOHz9O/fr1KVSoEKGhoZQpU4aOHTuSN29eVqxYwdSpU9m5cyexsbFYWFiwZMkSDAwMcHBwYOLEiXz//fesWrWKpKQkmjdvnmESdvjw4cyePZvt27djYGBA27ZtOXjwYM47ORc5OTkxevRovvvuO1xdXTEwMKBJkyacOHFCKTN37lyMjY2ZNGlSturWJGiLFi1K27ZtMTY2JigoiCVLlmSYeLW0tGTlypVMnTqVrVu3YmRkRExMDPPnz8+19gghhBBCCCGEEOLTYaBO/VV88UmJiYnh4cOHlCtXTms/sIwkJydz+/Ztqlat+l6Xs8rt+0T+bZPta6zrvnnn+8Kn22fZffZCCCFS+Pv7Y2Njo+y7GBoaSp48eZSfQ0JCMDY2xtbWFoDg4GAMDAy09rKElOVeIyMjsbS0VMqmlVmZtPWmjUsjJCSEt2/fUrJkyXT1x8bG8urVq0xjyKovLC0t0y2bqlKp8PHxwd7ennz58uHv7098fLzOOvLkyZNuH9I3b97Qo0cPmjRpwvjx4zO8v1qtJiQkBLVajYODQ7p//3T1UW7Fm7qMgYEB+fPn12v52LQyiimrdmQnvtScnJzImzdvtuPPzljUJSoqivDwcPLnz69zz9JXr15hYmJCvnz50p1LSEhQ9l5NTEwkNDSUYsWKoVarefbsGYULF1ZmMkdFRfHmzRsKFixIXFwcr169omjRokDKXrupywYFBWFqaqq0582bN8TExOi9L25O6ouLi+P169cUKFCAAwcO8MsvvyizhT09Pdm3b1+GCdPAwEDMzMywtbXVaruJiQk+Pj4ULVqU5ORkXr9+jbOzs9bvg7e3N4UKFdK5RHhYWBiJiYk4Ojoqy03rK7P2pKZ53Vm6dGm99/b+1Hyo1/Tv28doh7zvEEIIIYQQQoiPT2bW5lBERAQmJiYZvqGNiorC0tJS54cqarWayMhI8ubN+1l/mCCEEELocuHCBaKjo3F3d0937s2bN1y8eJFSpUpRqVIlAK5fv46RkZHWvqDJycncuXOHwMBATExMcHFxwdXVVauurMqkrffChQsANG3aVCnj5OREZGQkhw8fpkOHDsrxfPnyYWhoyO3bt4mIiMDW1pbKlStrJbLy5cunM3mlqVdzT80+n5CyJ6Sjo6OyxKyjoyOOjo7pyqVWvnx5rQTc27dvlbjs7Oz44osv0iV5Tp8+TenSpSlcuLDW8devX3Pp0iXatm2Lqampzj7KLF5I2WdTMwPYzs4uXR+UL1+esmXLcvHiRaUuIyMj7OzsqFy5MtbW1lp9pJE2Vo3ff/89w75p3749BgYGSjs0Se/Hjx9n2p9ly5blwoULFCpUiLJly+osl7ovdMWv4eTkRHJyMv/++2+m41Wftup7XiM5OZljx47RuHFjihQporNM2n7O7vWQspdwRkxNTZV4TUxMlKW6DQwM0n0JIW/evMrvkIWFhZKoBdKVdXZ21vrZxsZGa4/XrGSnPrVazbBhw3B3d6dNmzYkJCRw8uRJqlSpopR//PgxFStWzPB+SUlJeHp60qpVq3Rt1/zZxMSEQoUKKfe8cuUKMTExNG/ePMN6c/JFDX3aI4QQQgghhBBCiE+HJGtzYNeuXSxYsIBRo0YxePBgrXNHjx5l6dKlvH37FoCOHTsybdo0DA1Ttgc+e/YsP/zwA2/fvsXIyIhhw4YxaNCgD94GIYQQ4n1ZvXo1jx8/pnjx4lSuXFnr3NGjR1m4cCHffPONkqz95ZdfsLCwUBKGXl5eDBkyhLx581K6dGni4uK4fv06lSpVYv369ZiZmelVJm29mrh27dqllRgOCgpi8uTJWsnaDRs2sGnTJooUKYKzszO+vr6EhoYyadIkunTpkq2+SE5OpkSJEkBKcszHx4fXr1+zYsUK6tSpo5RLTEykePHi6erIkycPZcuWRa1Ws3HjRtavXw+kJBCTkpJISkrC1tZWSSKampry5s0bBg8enC5h5ePjw+TJk2nWrBmmpqY6+0ifeB88eIBarWbx4sWYmZlRs2ZN5QtomnhT1xUfH8/z588JCAigR48ejBs3DlNTU737MKO+8fDwwMDAQGc7MutPExMTRo8ejaWlpc4EoKmpKQYGBnrFr89YfF+SkpKYPHkyBw8ezNHM4eTkZHbt2kWVKlVydP2Hcv/+fWxsbChUqBDe3t6MGDEiw7KmpqYZ7p2bEQMDA6pWrcqsWbPYsGEDr1+/pmTJkowaNUop07Bhw0z76J9//mHVqlW0atVKr3tu2rSJn376idatW2earNXQ9EFcXJxe7W/bti1z5szJsD1CCCGEEEIIIYT4dEiyNpumTZtGRESEzuUK79y5w7Rp01i3bh0NGzbE29ubHj16ULZsWbp06YKfnx/jx49n4cKFtGnThrt37/LNN99QpkwZGjRo8BFaI4QQQrwf5cqV4+jRo+mStcePH6dMmTKZXrtw4UJq1KjBggULlGNhYWGMGTOGe/fuUa1aNb3K6FK9enXmzJnDkSNHMlzdYvv27WzatIn169cryUmAw4cPM2XKFIoWLUqtWrWy7AONNm3aMHz4cK1jc+fOZcqUKfzxxx/KsbZt26Yrl9pPP/3E5s2b2bhxo9YesX/88QcTJ05k1KhRtG3bFgMDA70TRjmN18DAgEGDBtGlSxeMjY0znPGYtq4bN24wbtw4YmJi+OGHH/SOKau+ye41KpWK4sWL07RpU51fmjMwMKB79+56xZ/TsfgpMDU15fDhwx87jCxt27aNFi1aUKhQIVxcXDh06FCGZbO7VLDGkydPmDlzJlWrViVfvnzploPObIZyTvz777907NhR517Cumj6oEWLFnq1v23btrRs2ZKQkBCd7RFCCCGEEEIIIcSnw/BjB/C5KVSoEKtXr9a5p5RarWbKlCk0bNgQSFnyrFatWty7dw9AWX7sq6++wsDAgMqVK9OuXTuOHDnyQdsghBBCvG+NGjXi5MmTJCYmKse8vb0JCQmhfPnymV4bEhKSbslSW1tbduzYoSS+9CmjS9euXVGpVOzatUvn+eTkZDZu3Ejfvn21ErUAHTp0YPr06bmyp2OLFi0IDAwkMjJSr/IJCQls2LCBgQMHUrduXSwtLZX/vvrqK3r06MGWLVuwtLR8L3sOZhSvvb19tpamrVGjBjNmzODAgQP4+fnlcpT6MzQ0xNDQEFNTU62+1PyXUR/qil+fsXj16lVu3bqVaUwvX77k3LlzXL58Od1+tj4+Ppw5c4aLFy8SFhaWaT0BAQFcuHCBS5cuERISohxXqVQcPnyYqKgoLl26hLe3N8nJyRw+fJjw8HClXHBwMBcuXODPP//kzZs3WnUnJSVx7do1fv31V65evUpSUlKmsWTn2ozaePnyZW7fvs2NGzeU686ePUtycrLyvEJDQ7ly5QqWlpaYm5una6e+9/jf//6Hr6+vktjMrC8g5Yuap06dwsvLS+9+ALh06RL+/v48f/6cEydOZKsPrl+/rnPM6hq7jx49wtPTk9evXxMcHMypU6eyFacQQgghhBBCCCE+DJlZm03Dhg3L8FyVKlW09oJSqVQ8e/YMDw8PIOUDk7T7opUrV45t27a9l1iFEEKIj8XV1RVHR0cuXbpEs2bNADh27Bht2rTJMkHZtm1bVq9eTUxMDE2aNKFq1arplpLVp4wuBgYGTJ8+nREjRtCmTRscHBy0znt7exMeHq7EnFbPnj2zvIc+Hj9+jJWVlVbi9+HDhzpnObZt25aHDx8SGRlJy5YtddbXqlUrfv75Z/z8/DLde/RDxZvZEseNGzfG2NiYW7duvZdY3zW+rKSNX5+x+PTpU8zMzLSW307t559/ZsOGDdSpU4dXr14xY8YMdu7cSZEiRVixYgWHDh2icePGhIeHM378eDZv3qyzru3bt7NhwwaaN29OYmIi48ePZ/r06bi7u6NSqZg8eTL/+9//uH37NoMGDaJw4cJayyjv3buXFStW0Lx5c+Lj45k0aRJLly6ldu3axMTE0KVLF2xtbSlZsiSPHj0iIiKC/fv3ZzlrM6trM2tjcHAw4eHhvHr1ipCQEOLi4pg8eTIVK1ZUlv6+efMm27Zto3nz5jrbWbJkyWzdA8i0LwBmzZrFxYsXadq0KYcOHSI5OVnvMRQcHExsbCwRERH4+/sDZDu+rMycOZPz58/TpEkTdu3ahaOjI56enrRp00bvOIUQQgghhBBCCPFhSLL2PVq1ahXx8fF07doVgIiICFxcXLTKWFtbExERkWk9ycnJen0ApCmTnQ+LcuJD3UefGHKrnk+tzz5m3wohRG5xd3fn2LFjNGvWDLVaza+//sqaNWvYuXNnptcNHjyYokWLsmfPHnbv3g2kzGjs168f9evX17tMRmrWrEnDhg1ZtGgRS5cu1TqnmT2XeqZkeHg4v//+u/KzhYVFtpYZTp001HyRa8+ePYwfP15ryVYfHx+dS7i2aNFCmflYoEABnfcoWLAgAK9evXrnBGhuxJtZMtTY2BhHR0edMxX1iUkjb968tGjRIsNrchpfVtLGr89Y7NOnT4b1hYSEsGTJEmXvWICNGzfy7NkzihQpQlJSEuvXr1eWFB8zZgx79uxJl6wNDg5m6dKl/Pjjj9SoUQOAQ4cOMW/ePFq1aqW02dDQkJMnTwJozeANDQ1l/vz5bNiwgbp16wKwe/duZs2axdmzZ3n69CkvXrzg8OHDSl1btmzh9evXWSZrs7o2szZ27tyZlStX0qZNG1q1apXllz2MjY3TtRPI1j2y6gs/Pz/27t3L0aNHlS9ifvfdd5nGlVqXLl04deoU1apVU74Imp34suLr68u+ffs4dOgQFSpUQKVS0bt37yyXiFapVJ/ta9BP4f1JbvgY7fjc+0wIIYT4f+zddVRU2/s/8PfQIqG0ioEgiAqiqICAiq2kgV3Yce1uvea1rpjY2IGFKCpi4VXEVlRCEMFABCnpmPn9wXfOj2HqDCHq53mt5Vpwzj77PPs5Gxxmz96bEEII+RPQYG0V4HK5WLt2Le7evQtfX1/mDSw5OTlwuVyhsnJyklejjo6Olun+4eHhsgVcTpV1nybluObFixeVcm++3y1nhBDyO3Bzc8OOHTuQnp6Od+/eQUVFBc2bN2d1bc+ePdGzZ0/k5+fj+fPn8Pf3x7hx47BlyxZmZhibMuLMmzcPvXr1wqNHjwSW8dXU1ARQMnDFn3WbkZHBDPp8//4dmZmZMg3WfvjwAffu3QNQMogSFxeH/fv3Cy3XLGqvWD7+DMLv37+jZs2aQue/f/8OAMwSqNIGZSSdr4x4JeHxeMjIyEDt2rVZX/Pu3TsUFBQIHNPT05M4WFve+KQRFX9F+uLbt28hJycnsDrLxIkTma/nzp2LyMhI3Lx5Ezk5OcjNzRVYXpwvIiICcnJyzEAtUPLBhPT0dHz69AmNGzcGAHTp0kVkHG/evEFhYSG+fv3KDIxnZWXhw4cP+P79O5o2bYrmzZvDzc0NXbp0gZ2dHUaNGgVFRUWpOZN2Lds2yqJsO2W5h7RcREdHQ0VFRWDFHBsbG2brk/KozBy8e/cOqqqqzO9bOTk5dOzYEadOnZJ4nazLOf+K/pTX2n9KOwghhBBCCCGEsEODtZWssLAQM2bMQHJyMk6fPg0tLS3mnI6OjtA+YykpKUJLMJZlamrKav+54uJihIeHw8LCAvLy8uVrAAuVfZ/sh7JfY2VlVeH7Ar9uznJycmQepCeEkF+Nvr4+rK2tce3aNbx58wbu7u4y16GsrAxbW1vY2trix48fuHr1qtDgF5syomKbMmUK/v77b4HZtUZGRtDU1ERoaCizt26jRo2YLQuuXbuGDRs2yNSGXr16MYOG6enp6NWrF96+fStxb92yzMzMoKSkhLCwMDRo0EDo/LNnz6Curs4MyGloaCA5OVmo3NevX6GoqChxJmRlxCvJ06dPkZWVhVatWrG+xs3NrUoGXstDUvzl6YsFBQViXxtkZ2dj9OjRyMvLQ/v27VGzZk1kZ2eLnBlcUFDAzCrl4w+Glh70E/fsCwsLIS8vj8jISIHjI0aMQFFREZSVlXHixAk8efIE9+/fx+bNm/Hjxw/4+vrC0NBQYhslXVu7dm3WbRRH1MzA0u2UJY9sciEq1xV5HSlrfNLk5+cLXStt9jNQsnw9m3K/op/1mr6qVUc76O8OQgghhBBCCKl+NFhbyRYvXoysrCwcPnwYNWrUEDjXsmVLHD9+XODY48eP0bp1a4l1ysvLy/THuqzly+tn3UfcvSu7vl8pZ7/zm0yEEFKau7s7AgIC8ObNG5w7d05q+ezsbLx69QrW1tYCgw382YyGhoasyrAxcuRInD9/HqdPn2aOKSkpYciQIdizZw+6desmNDD67t07VnWLU6tWLSxcuBDLly9Hp06dWC9ZXLNmTfTt2xc7d+6Ek5MTdHR0mHPJycnYu3cvhg4dygzO2dra4urVq5g0aRJUVFQAlAwCnD59Go6OjlJn3lY0XnEyMjKwdu1aODk5oWHDhhWqqzqUjb8y+qKxsTGys7MRFxfHbJfx5MkT1KhRA4mJiYiKisKjR4+Y+t+8eSM0y7h0PQkJCUy/jYiIgKKiIqvnZmJigsLCQowePZpZbjsjIwPx8fHQ19dHTEwMkpOTYWdnh3bt2mHmzJkYNGgQrly5ggkTJkisW9K1xsbGrNsIACoqKuBwOMjOzmaOvX37VuL9Q0NDZbqHtFzUq1cPP378QFJSEvT19QGgQrNqZY1Pmjp16iAjIwOpqanMB0fZrEojJyf3278Grc6/TyrTz2zHn5AvQgghhBBCCPnd0WCtDPLz8/H161cAJbMX0tLSEB8fDyUlJdSpUwchISG4ceMGjhw5gm/fvjHXKSsrw8DAAK6urtixYwf++ecf9O/fH/fv30dISIjQHmyEEELIn6J79+5YtWoVzM3NmX1VpVm9ejWUlZXRpUsXaGlpITs7GyEhIXj//j1WrFjBuow0CgoKWLp0KcaMGSNwfMqUKfj06RPc3d3h6uqKBg0aICMjA/fv30dSUhJWr14tSwqE8PfyXbRoEY4cOcIMnL548QK+vr5C5fX19dGrVy/MnTsX8fHxcHNzg4eHB+rUqYMvX77g4sWLaNu2Lf766y+BNoSGhsLd3R09e/aEnJwcbt++jczMTBw5cuSnxAsAr169wrFjx8DlcpGYmIiAgADUq1cPa9eulSmG8mATn6gyjo6OMDY2BsAufjZ9MTQ0FIqKikL7zAIlg6y9e/fGtGnTMGTIECQlJeHo0aPYsmULDA0NUVBQgCNHjkBHRwe3bt2CoqIiIiIiEBERwcyk5tfj4uKCGTNmYPTo0cjNzcXu3bsxYcIEViu0GBkZoW/fvpg8eTJGjBgBOTk5HD9+HI0bN4alpSUyMjIwdepUjB49GkZGRkhKSkJcXBxmz54NAAgLCwOHwxFYhplP0rXq6uoS22hubg5NTU0EBgaCw+GgR48eaNasGTZv3owBAwYgKioKcXFxEtsmLY+i7iEpFxYWFjA3N8esWbPQr18/xMbG4unTp1JzXJnxSdKyZUs0atQI8+bNg6enJyIiIv6IJY4JIYQQQgghhJA/FQ3WyiAqKgqTJk1ivr906RIuXbqEJk2awNfXF2FhYVBVVRXYZwwAmjdvjr1790JdXR2+vr7YsGEDxo4di7p168LHx0fgjTZCCCHkd9e5c2dmRmGNGjUwbdo0NGrUiDlvbW0tsO+qjY0NM5usZs2auHDhAm7duoXw8HB8/foVampqcHNzg7OzM7NqBZsypestGxefra0tpk6dig8fPjDHFBUVsWnTJrx8+RIhISFISEhAzZo1MWbMGHTu3Flo5QxpuSi9ryXfihUrsHPnTkRFRaFp06bo3LkzEhMThZZdBYC8vDwAJcuYHjp0CCEhIQgLC8PmzZvRpk0b/Pvvv7C1tRW4platWjh37hwCAwPx+vVr8Hg8DB48GM7OzgLLnIrKUWXFyy/z+vVrcDgc1KpVCytXrkSnTp1kmsklLqbSRLWDbXxly/D3jmUTP9v++u7dOygrK4scrAWAzZs349KlS3j9+jWUlJRw6NAhWFpaAgB8fHxw9+5dpKSkYNy4cWjQoAF2796N+/fvw8TEBH369GH2z920aROuXLmCV69eQVFREStWrECHDh2Y+/Tp00dgVracnJzA9evWrcP169fx/PlzFBYWYvjw4XB2dgZQ8nN79OhRXLt2DQ8ePICWlhYOHjzI7Iv6+vVrvH37VuRgrbRrJbXR3Nwcf//9NwICApCSkgIA2L17N06dOoUnT56gbdu2cHFxwaVLl8S2s2nTpjLfQ1IuOBwOjhw5gpMnT+LFixcwNzfHxo0b4e/vL/L5iuLg4MD8XixPfJLwB5dPnjyJBw8eoF27djAyMsKOHTtYx0cIIYQQQgghhJCfh8Pj8XjVHQQRLScnh/k0Pds9a1+8eAErK6sq33+1Mu+Teb+WzNdo2KdX+L7Ar5szWZ89IYSQ/z2zZs1CWloaDh06VN2hEIJnz54hODgY8+bNq+5Q/ufxeDz8999/MDc3Zwat//33X7x48QKHDx8WKs9/3Wlqagp1dfWfHW6l+Fmv6atadbSD/u4ghBBCCCGEkOpHM2sJIYQQ8j9v1KhRiIuLw6VLl6CpqSlwLjQ0FHPmzMHgwYOZpYbnzZuH5ORkuLq6AigZHAkLC8OrV6+Qnp4OeXl5WFhYYOTIkbCzswMAcLlcnDp1CoGBgUhMTISCggKMjIwEyixZsgQqKipYsmQJE1dycjJOnz4tMCP2/fv3uH//PrKzs7FkyRJYWlrCwcEBR44cwcOHD5GRkYHatWvD3t4eo0ePZmZOss1F6b15ORwO9PT00KFDB4wfP555M79sudLGjRuHUaNGAQCSkpJw8OBBhIWFISMjA9ra2nBwcECfPn0Elo7dvn077OzsmNmncnJy8PDwwKtXrzBp0iRcv34dampqInNUWfGWLiMvLw9tbW1YW1tj5MiRMu3XK+leISEhkJeXl9oOcfF16tSJya2k+0qKn01flOb169dYtmwZiouL4efnh/Hjx2Pt2rUoKCiAk5MTDhw4IHVG9J8oPT0dt27dEnue36/LYps3tvX7+voiOzsbQ4YMwdevX3HkyBFs2LBBprYQQgghhBBCCCHk56DBWkIIIYT8z0tLS0NeXh4CAwMxePBggXMXLlxAUVERsrOzmWMZGRn4/v074uPjAQCPHz9GdHQ0HB0doa2tDQDQ0tLCmDFj4Ofnh+bNm2PHjh3w9/fH8uXLYWZmhtzcXAQGBgqUyczMRFFRkUBc3759w86dOzF//nzmeFFREdLT03H27FkEBATg5cuX+Pfff9GsWTPMnDkT+vr6SEhIgI+PD4KCguDn5wcNDQ3WuXBxccGQIUMAlMz0ev/+Pf755x8kJCRgy5YtTLnevXtj0KBBQnVoaWkBAGJjYzF8+HCYm5tj5syZMDAwwJcvX3DgwAGcP38e3bt3Z5bEzsjIQFJSEpNTRUVFACWDWCkpKeByuQAgMkeVFW/puvLz8xEfH48zZ87Azc0Nu3fvFlpuWlIOxd2LP1tOVDvYxJeTkyPxvmziZ9MXpTl06BD09PSwZs0aKCgoYNu2bbC0tASPx0NKSgoKCwul1vEnKiwsZPrwo0ePoK+vj4YNGzLn+f26LAUFBWzcuFFoqXZJ9YvCr3/Hjh04f/48nj59Cg0NDRw6dAhWVlYytoYQQgghhBBCCCE/Aw3WEkIIIYQAsLe3h7+/v8BgbW5uLm7fvg0bGxuBssrKyszAKAC4ublh0qRJGDNmjEA5BwcHZkZjcHAwhgwZIrCH6OTJkwXKiDJ27Fjs3r0bffv2RZMmTQTOWVhYwMLCAiNGjEDDhg2xb98+yMnJASjZB9PBwQFubm4ICgpC//79WedCU1NTYICpcePG4PF4mDFjBgoKCpj9YWvXrg1jY2Ox9SxduhTGxsbYv38/OBwOAMDMzAwODg7o378/vn37hm3btgEoGRR3cnLCsGHDWMdZ2fGWrcvU1BTdunXDkiVLMHfuXAQHB0NZWZlVTGzuVRnXlMUm/vL2xdJSU1PRqlUr5sMJ7du3BwDk5+dXKP7fna6uLvN7Yfjw4ejZsyd69uwp9To5OTkmh2zrl6RGjRoYOnSo9IAJIYQQQgghhBBS7eSqOwBCCCGEkF9B+/btERUVJTBrLTg4GC1atJC6j2PdunVx7do1JCUlCRy3tLRkZrSyKSNK/fr1MWzYMPz9998iz3///h1hYWEYP348M1DLp6qqiuvXr8s0UCuOiooKioqKBGaDSvLlyxc8ffoUkyZNYgZq+RQVFTFx4kTcunULP378qHBsosgaryQzZszAt2/fEBYWVgmR/Xxl42fTFxcuXCi2z/3111948uQJfH194ezsjIKCAtjb2yMyMpIp8+7dO4wYMQKdO3fGhAkT8OHDBwAlM0Pt7e0RHBwMNzc3nDx5EgCQkpKCxYsXo3fv3vDw8MDGjRuRl5fHuo2vXr3CqFGj0KVLF8ycOROXLl0SudywKLm5ubC3t8eNGzdkivnr16+YP38+evfuDVdXVyxbtgypqakAgGnTpuHp06dYvnw5FixYILWNpXNYXFwMe3t73L9/H+PGjUPnzp0xfPhwgfxWZT4IIYQQQgghhBDyc9FgLSGEEEIISmaidevWDf7+/swxf39/uLu7g8fjSbx28eLF4HK5cHJywoABA7Bx40aEhYUJXMemjCg8Hg+TJ09GQkKCQGx8/AGlsrNu+fjL7lZEamoq9u7dC1tbW2YPWADYt28f7O3thf6lp6fj/fv3AEpmd4piamqKwsJCfPz4scLxVUa8kujo6EBLS4vJdVUpb3zSlI2fTV9cuHCh2BmcO3bsgLW1Nby8vHDlyhWRSx8fP34c8+fPx4kTJ6CkpITp06cDKFnuNyUlBceOHcOMGTPQoUMHFBcXY+zYsSgsLMTx48exZ88eREREYOXKlazal5+fj4kTJ6J58+Y4d+4cBg4ciC1btiAzM5PV9XJyckhJScH+/fuxdOlS1jGPGTMGSkpKOH78OA4cOIBv375h1qxZAIBt27ahdu3aWLlyJdavXy+1jaVzKC8vj5SUFGzfvh0zZszAmTNnULNmTaxbt65K88HlclFcXPzb/gNQ7TH8ru0ghBBCCCGEEFK9aBlkQgghhJD/4+HhgaVLl2Lq1KlITU3F8+fP4e3tjYcPH0q8rn79+jh37hxevXqFhw8fIiwsDIcPH4apqSl8fHygp6fHqow4qqqqWLBgAdasWYMuXboInOMPxpaevRoZGSmwJLOBgQHOnTvHOg/79u3D8ePHAZQM4Pz48QOOjo5YtWqVQLkBAwYwe8WWpqGhwcQjbrCYv7dmZextWhnxSqOgoCDTwHfpmPgMDQ1x+vRpsddUJD5pSsfPpi9W9J4jRoxg9r6dPHkyPDw8kJiYiDp16gAAnJ2d0blzZwDAixcvEBkZiSNHjjD3nTFjBgYNGoQVK1ZIXXr6xYsXyMjIwNSpU6GiogJbW1v06NEDN27ckDlm/ocepMX87NkzxMbG4vTp01BTUwMATJ06FX379kVKSgp0dHQE6g4PD5fYRlGGDx/O5NDFxQUbN25k1Y7y5iMmJoZV/b+y8PDw6g6hUvwp7SCEEEIIIYQQwg4N1hJCCCGE/B9bW1sUFRXh6dOnePPmDZycnFCzZk3W11taWsLS0hLjx4/H169fMWzYMOzZswdLly6VqYwovXr1wpkzZ7B161YMHDiQOW5oaAgOh4PY2FgYGhoCABo1aoT9+/cDAB48eCA0aCjNoEGDmP0uX716hYULF2LevHlCA1Bl94otrV69egCAuLg41K5dW+g8f7lpfsyKiooil73NyckBAIkDdpURrySpqalISUlBgwYNWF/Tr18/DBgwQOAYf+9cccobnzTi4i9vX2SD/1wBMB9ESElJYQY+S7fzy5cvAEr6OB9/lufnz5/RuHFjifdKSUmBpqYmVFRUmGMmJiYyD9bWrVuXdcxfv36FhoYGM1ALlHwogn+ubN+T1kb+z0tp+vr6zNcKCgqsl/Qubz5MTEwE2vM7KS4uRnh4OCwsLCplNYHqUh3tyMnJQXR09E+5FyGEEEIIIYQQ0WiwlhBCCCHk/8jJycHV1RVXr17Fq1evMHXq1HLXZWBgAGtra3z+/LlCZUpbsmQJ+vbtC2tra+aYjo4O2rRpg0OHDqFjx44ASvZrNTc3BwCBPXjZUldXZwbbDA0NcfPmTSxatAjHjx8X2hdXnEaNGqFJkyY4cuQIWrduLXT++PHjaNOmDbS1tZnyb968ESr34sULNGjQQOJgbWXEK8mxY8egqakJGxsb1tdoaWmJXQL6Z2MTv6x9UZrSexHzl9+tVasWc6z0c9HV1YWCggJu3LghNEAlbYAbANTU1JCVlQUej8fM6E5MTJQ55oyMDNYxa2trIysrCwUFBUyM/P1qdXV1heqW1saCggKZ4xWnvPmQk5P7rQc6gZKZ/L97G4Cf244/IV+EEEIIIYQQ8rujPWsJIYQQQkrx8PBAUFAQEhMTYW9vL7V8cnIyPD09ERAQgPz8fAAlM+bu3buHW7duwdHRkVUZNoyNjTFs2DBs3bpV4PiSJUvw8uVLLFy4kNkD9sePH7h69Sq2bNmCpk2bypABYYsWLUJsbCyOHDki03VLly5FcHAwNm3ahLS0NAAlA1r//PMPwsLCsGTJEqbsiBEjcP36dRw/fhxZWVnIyclBQEAADh06hHHjxv2UeMtKTU3Fjh07sHfvXqxYsYLVwOGvRFT8ldUXpTl9+jSzxPWFCxdgaGgoMHO1NAsLC+jo6MDPzw/KyspQVlZGQEAAli5dKrC8tzjNmjUDl8vF9evXAQDfv3/H1atXZY75zJkzTMz+/v4SY7a0tISWlhZOnDgBoGTP2aNHj6J58+bMrFx5eXlkZWVVShtlUVn5IIQQQgghhBBCyM9BM2sJIYQQQkoxMTGBrq4u2rZty2rGka6uLry8vLB//34sWLAANWrUQF5eHurVq4cZM2Ywy/OyKcPGlClTcPnyZYFjTZs2xdmzZ7FlyxY4OzujqKgIXC4XZmZmGDlypMCyyeWhra2NuXPnYvXq1XBycmKWg925cyd2794tVL5169Y4fPgwbGxs4Ovri3///ReOjo5QUFBAcXEx2rVrh5MnTwoMInfs2BGbNm3C9u3b8ffff4PD4aBevXqYP3++0HLCVRUvAOzatQv79u0Dl8tFQUEBWrZsiT179rAauK8oNvGJKrNu3Tq4uLiwip9tf124cCFq1KiBZcuWydQGLpcLAGjVqhVcXFxQUFAAHo+HDRs2iP15UlFRwY4dO7B8+XIcOHAAQMmS0GvWrGF1T11dXSxcuBCLFy/Gli1boKWlBVdXV5w9e5Yps2TJEsjJyeHvv/8WW0+TJk3g4uKCwsJCcLlciTHXqFEDO3bswLJly3DkyBEUFBTAyMgIW7ZsYQZfO3bsiBUrVuDy5cvw9fWtUBtlwSYfhBBCCCGEEEII+XVweDwer7qDIKLl5OQgIiIC5ubmUFVVlVq+uLgYL168gJWVVZUuZ1XZ98m8X0vmazTs0yt8X+DXzZmsz54QQkjFpKWlQVVVlVlqNysrC4qKisz3P378AIfDYfZzzMzMBIfDgbq6ukA9xcXF+PHjB2rWrAlFRUWR95JUpmy9ZePiy8rKQm5ursjlVnk8HjIzM6Gqqio2Bmm5UFZWFvr/h8fjISUlBTVr1oSqqirS0tLE7qGpqKgosHwsABQUFMDT0xMODg6YO3euxBhycnLA4/FE7hcsKkeVFW/pMhwOB5qampWaQ2ntkCW+0jQ0NKCsrCxz/LL0xbIyMjKgoKDAPKPk5GTUrl0b8vLySElJgZaWFjgcDrKzs4XqSE5ORq1atUTGVlBQgKKionK9/uHxeMjKyoK6ujpOnjyJ06dP4+LFiwCAyMhIHDt2DKtXrxa6Lj8/H5aWljh37hyaNWsmc8x5eXmQl5cXee7Hjx9QU1MTmD0rro38HCooKAjdr6CgAFlZWdDS0qqUfJTGf91pamoq9nn/6n7Wa/qqVh3toL87CCGEEEIIIaT60cxaQggh5DcXGBiIzMxMDBo0SOhcamoqAgMDYW5uzuxzGhISAkVFRdjZ2THlCgoK8PjxYyQmJkJBQQGNGzeGhYWF0ACDpDJl6w0MDASXy2Vm/PGlp6fj8uXLGDZsmMDx79+/48mTJ8jIyICWlhasra1Ru3ZtmXPB3zcSKBmw0tfXR+vWrQUGOcqWK61ly5awsLBgvk9JScHTp0+RkZEBbW1ttGvXDhoaGgLXnD9/Hs2bN4eZmZnAIOW3b98QFBSEAQMGQElJSWSOJMXLbz+beEuXkZeXh7a2NqysrJglWdkKDQ0Ve6+hQ4eCw+FIbYeo+IKDg9G+fXucOXMG/fv3h5GRkUA5tvFraGigoKAA9+/fl9hfORyOwGA2m74ka3+rSD1l+1BlxCdr/PLy8kKD6nxl4ytLU1NT4HtdXV3ExcXh5cuX8PDwQHFxMU6cOIHevXsLXSvqQwZ8SkpKMi83zePxMHLkSDg7O2PgwIHIycmBv7+/wN7OT548QcuWLaXWIycnJ3LAUlLMKioqKC4uxo0bN5CTkwMXFxecPHkSvXv3hqamJo4fP47evXszv4PEtbH0PcreT0lJifVALZt8EEIIIYQQQggh5NdBg7WEEELIb27Pnj2Ijo6GqakpWrduLXDu/Pnz2Lx5M0aNGsW8UX/27FmoqqoyA20REREYN24c6tevD1NTU+Tl5WHTpk1o2LAh9u/fjxo1arAqU7bePXv2IDIyEtra2gIDw9++fcOqVauYwVoul4t///0Xvr6+aN68OfT19ZGQkICYmBjMnj0bo0aNkikXcnJyMDMzA1AyS+n9+/eIi4vD5s2b4eTkxJQDSpY9LcvAwAAWFhZCcRkYGODLly+YNWsWpkyZgvHjxzPXbN26FePHj2fuy5eQkIBVq1bBzc0NSkpKInNUWfGWris/Px/x8fGIjo5Gnz59sHjxYnz69AmjR48WmztlZWXcuHFD4r2GDBkCDocjsh1s4uvWrRs6dOgAFxcXaGho4ObNm8xMLmnxq6ioAGDXX6tKTEwMqxz+r3r16hW2bdvGDNZev34d7du3l2k2aFlsc+7l5YWVK1di165dyMnJQbt27TB16lSmnJubm8iZ2pVl165dOHXqFNzc3NCrVy+m7TVr1sSqVavQsmXLCuWBr7LyQQghhBBCCCGEkF8HDdYSQgghf4DmzZvj4sWLQoO1/v7+MDc3l3jtxo0b0blzZ4G9HDMzMzF//nxERkaiVatWrMqI4uDggFWrVsHf31/scqz79+/H8ePHceTIEYF6rl27hpkzZ6Jx48bo0KGD1BzwdevWDZMnTxY4tmHDBixduhT//fcfc6xHjx5C5Urbs2cPTpw4gaNHj8LKyoo5HhoaigkTJqBWrVoy76ValfGKqis8PBzTp0/HsmXLsGHDBoSEhLCKic29ynONnJwcNm/ejDVr1ohcNlZa/AC7/lpVTExMWOfwf52SkhKOHj1a4XrY5tzJyQlOTk748eMHVFVVhZaQlTRTWFlZGf/991+FZlaHh4ejT58+mDNnDgAwbc/Pzy93naJUVj4IIYQQQgghhBDy65Cr7gAIIYQQUnGdOnXCtWvXUFBQwByLiopCRkaG0GzPslJTU4WWQtXQ0MDu3buZgS82ZUTp27cvlJSUcOjQIZHni4qKsH//fowePVqonp49e2Lt2rWoU6eOxPjZ6NSpE5KTk5GRkcGqfH5+Pvbt24cJEyYIDNQCgJ2dHYYPH47du3eDx+NVODZRZI1XHAsLCyxfvhz+/v748OFD5QRXCVRUVFjtBSsqfjZ98e7du7h//77YevPz83Hr1i2cOXMGN2/eRF5eHoCSpb6PHTuG9PR0pmxMTAwuXbokcH1YWBjOnj2LyMhIfPnyBWfPnhU4/+bNG5w/fx6XL1/G169fmeNcLpep/+rVq4iMjJQYD1vS4pFE2r3fv3+PgIAABAYG4uPHjwLneDweHj58CD8/P4SHhwucKy4uxrFjx5Camio1r/y8/PjxAw8ePICfnx+ioqIAANHR0fDz80NYWBir9qirq4PD4chcn66uLp4+fVquPAYFBSEhIQFRUVE4c+aMQNtLCw0NhZ+fH54/f84cE9cnACA+Ph4BAQG4fv06kpKSWMVSWlhYGK5fv453797J3C8IIYQQQgghhBDy89DMWkIIIeQPYGRkhLp16+LWrVvo2bMngJJZtc7OzkhLS5N4bd++fbF+/XqkpaWhc+fOaNOmjdCejWzKiLNs2TKMGTMGbm5uMDAwEDgXGxuLjIwMdOrUSeS1ffr0YXUPaV6/fo1atWoJzK579eoVjh07JlTW09MTERERyM7ORpcuXUTW16VLF+zfvx8JCQlo2LBhpcRYkXiVlZXF1uXg4ABFRUU8ffoUjRo1qvRYKxqfNGXjZ9MXk5KSxO57mpWVhT59+sDY2BjGxsa4fv061q1bh3PnzoHD4WDVqlVo164dMyD8/PlzHDhwAG5ubgCAefPm4dGjR+jRowcCAwOhpKSEqKgo9O/fHwCwdu1aBAUFoUePHkhLS8OSJUuwe/du2NnZgcvlYtWqVXj58iU+fPiAkSNHwtDQUGw8ZfeFFUVaPJJIyoWmpiZ8fHxw5MgRuLi4oLCwEMuXL8e8efPg6ekJAFi4cCEeP36Mnj174u7du/j+/TtTd1FREbP8b8OGDSXmlZ/3sLAwqKqqIi8vDytXrsSYMWPw5s0bGBoaYu3atZg9e7bQXteilKe+iuQxLy8PXC4XhYWFyMnJEWi7qakpAGDTpk1QV1eHlpYW1q1bh5EjR2L69Oki+0TTpk3h6+sLHx8fuLm5IT8/HytXrsTatWvF/q4sqyLtIYQQQgghhBBCyM9Fg7WEEELIH8LDwwMXL15Ez549weVyceXKFezZswe+vr4SrxsxYgQaNWqEkydPYs6cOcjJyYGVlRW8vLzQvXt31mXEad26NTNLdtu2bQLn+DNH9fX1mWOpqakIDAxkvldTU4OHhwfrPJQeNORyuXj//j0uXLiAJUuWgMPhMOWSkpLw+vVroev79OnDzAAsO7jMx5/t+/379woP1lZGvJIGQ+Xl5aGnp4cfP36UKyY+dXV1uLu7i72mvPFJUzZ+Nn1R0vLUsbGx+Pr1KwICAph9cI8fP47MzEypg6NxcXHw9/dHQEAATE1NwePxMGrUKIHnxJ/ly19+nMvlws/PD3Z2dlBQUGDK+Pn5AQBevnxZpfFIIikXOTk52L59O44fP87MLm/VqhVWrlwJNzc3JCYm4sKFCwgMDISxsTEAYPbs2eWaAcqPt3nz5pg4cSKAkj1mnz9/jiNHjgAomY0dEhLCerBWlvoqmkc3NzecP38e1tbWGDVqlMilj5s3b4558+YBAGxtbbFgwQKMHTuW2Ue3dJ9ISkrCpk2bcOjQIbRt2xYA0KJFC6xatQodO3aUGld528PlclFcXMyqzb8afty/a/x81dGO3z1nhBBCCCGEEPInoMFaQggh5A/h4uKCf//9F6mpqYiKioKmpiaaNm3K6toOHTqgQ4cOKC4uxps3b3Dp0iVMmzYN69evZwZK2ZQRZ86cOejZsyf+++8/6OnpMcf5e0QmJSVBV1cXAJCdnY1Hjx4xx5OTk2UarP327RsiIiIAlAxaREZG4uTJk2jWrJlAOVF7xfLxB8mSk5OZwZTSUlJSAICZ0SluEIS/TLKcnPidJyojXkm4XC7S09OFlg6W5PPnz3j69KnAMR0dHYmDteWNTxpR8VekL5qbm8Pa2hq9evVCp06dYGdnh759+6JGjRrIzMyUeG1sbCzU1NSY2ZIcDgeOjo44ceIEU2by5Ml48eIFAgICkJOTI3Jme+k9mCXFIw2beMqbi9u3b0NBQUFgGfA2bdogKysLnz59QlxcHFRVVZmBWgCwtrYWWOJXVtbW1szXurq6aN68ucD3L1++rJL6KppHNhwcHJivrayskJ+fj8+fPzP3LN0n3r59i+LiYkRGRjLLN6elpeHTp09ISUlhfleKU972xMTElKttv5Kyy3H/rv6UdhBCCCGEEEIIYYcGawkhhJA/hI6ODmxsbBAYGIg3b94wy7bKQl5eHpaWlrC0tERycjKCg4OFBr/YlClLW1sb06dPx6pVq7B161bmuJGREWrXro3//vsPLVq0AADUr1+fmYF77do1bNiwQaY2dO3alRk0/PHjB3r37o0HDx4IDX5K0rRpU6ioqCA0NFTk0sGPHz9GrVq1YGRkBKBkcPfbt29C5RITE6GsrCxywLcy45Xk0aNHyM7OFhi4kqZXr15VMvBaHpLiL09fVFJSgq+vL16/fo0HDx7A19cXq1evxpEjR6ClpSVUvqioiPm6sLCQmR3LV3pQNSsrC0OGDIGqqiocHBygqqoKHo8nNJhfuj9IikfastXS4pFG0r2LioqEPmQgLy8PoGQmXmFhocQPIUhTOq98ZfcxZrOvsSRs66toHtkovSw3/15cLpc5VrpPFBcXQ15envlQCB9/lrA05W2PiYkJ1NTUWN3jV1NcXIzw8HBYWFgw/fR3VB3tyMnJQXR09E+5FyGEEEIIIYQQ0cr/DgshhBBCfjnu7u64efMmbt26BVdXV6nlf/z4gZs3byIvL0/gOJfLRVJSEjQ1NVmVYWPw4MFQUVERWF5XQUEBI0eOxL59+4RmdfF4PJHL6spCXV0dS5YswbZt2/D+/XvW19WoUQMDBgzAzp078fXrV4FzX758wd69ezFixAhmQMTe3h6XL19GVlYWU66goAAnTpxAp06dWC+nWt54xfn+/TvWrFmDHj16oH79+hWu72crG39l9MXIyEjcvn0bLVq0wPjx43HixAnUr18f169fh4qKCjgcjsCS0aVnuNWrVw8ZGRkCg2jPnj1jvg4NDUVCQgKOHj2Kv/76C15eXlIHNCXFI420eKSRdO8mTZogJydHoB+Gh4dDWVkZ9evXh6GhIbKyspCYmChwXhRpea1uFc0jG2/fvmW+fvfuHRQUFFCvXj2RZU1NTVFUVIT+/ftj5syZmDlzJkaOHAk7Ozups2qB8rdHTk4O8vLyv+0/ANUew+/aDkIIIYQQQggh1Ytm1hJCCCF/kK5du2LFihVo0aKFwD6w4igoKGDnzp3YsmULOnXqBC0tLWRnZ+PevXtISUnBxo0bWZVhQ15eHsuWLcOIESMEjo8fPx6JiYno27cvunXrhoYNGyIjIwP3799HQUEB1qxZU65c8PXo0QMXLlzAokWLcOLECWbw7PHjx9i1a5dQ+bp168LDwwOzZs3Cp0+f4OrqCmdnZ9SpUwdfvnzBlStX0LVrV4FZblOmTMGjR4/g6uqKLl26QF5eHnfv3gWPx4O3t/dPiRcAnj59ir1794LL5eLLly+4fv06zMzMsGrVKpliKA828Ykq07VrV2a5Vmnxs+2Ld+/ehYKCAuzt7YXiKSgowNy5czFo0CAYGRkhKSkJ7969w5w5c6CkpAQrKyusX78e/fr1Q1RUlMAerBYWFjAzM8PMmTPRt29fRERE4PPnz8z5Ro0aobCwELt374a2tjbu3buHWrVqISwsDM+ePUPr1q1likcaafEAQEhICOTk5ASW4WVz70aNGmHAgAGYNm0aRowYgZycHOzfvx9//fUXatSoAQsLC7Rs2RJTp06Fh4cHYmNjxX64Qlpeq1tF88jG5cuXkZeXh1q1auHAgQPo06cPs4x6WQ0aNMDQoUMxceJEDBkyBHJycjh16hRatWoFW1vbSmkPIYQQQgghhBBCfh00WEsIIYT85pydnZnlUpWVlTF37lyBWZR2dnYCS2w6OjoyS3LWqFEDZ86cwYMHDxAeHo5v375BTU0NXl5e6Nq1K1OOTZnS9ZaNi8/a2hrz5s1DfHw8c0xeXh5///03hg8fjpCQECQnJ6NWrVqYP38+7O3tBepkkwtzc3Oh48uXL8e+ffvw7t07mJmZwdnZGV+/fhVaZhQAVFVVmdzs3r0bjx8/RlhYGHx8fGBra4tDhw7BwsJC4Bo1NTWcOnUKt27dwuvXr8Hj8TBlyhR069YNKioqInNf2fHyy3z9+hUcDgd6enrYunUrbG1tWc/slRRTaaLawTa+smX4s2TZxM+2vyYlJYntN5aWljhz5gyCg4MRHR0NLS0tnDx5ktl7ddeuXTh37hzi4+Ph6OgIQ0NDZpYrh8PB0aNHcf78eURHR8POzg7NmzfHzp07AQBNmjTB4cOHcffuXXz//h2zZ89GnTp1cPDgQURERKB169YYOnSowAcppMUjibR4ACA+Ph4vXrwQOcgo7d6rVq3CrVu38OrVKygqKmLr1q1o06YNc/2hQ4dw/vx5fP78GVZWVhg0aBACAwMBlPxcDx06FNra2lLzCgBDhw6Fjo4O833nzp1haGjIfN+sWTOZZgDKUl9F8wiUfOiA/3u3dNs5HA6GDh2KsWPH4vbt24iLi8PEiRMF9n8u2ycAYOnSpbh37x6eP3+OwsJCTJs2DZ07d2bVdjbtIYQQQgghhBBCyK+Dw+PxeNUdBBEtJycHERERMDc3Z97olKS4uBgvXryAlZVVlS5nVdn3ybxfS+ZrNOzTK3xf4NfNmazPnhBCSNWbN28eEhMTcfTo0eoOhVQTHo+HoKAgWFlZMYNrGzduREREBA4ePPhLxvP48WPcvXuX1Uzd/1V/Wh5l7af8152mpqZiZ/v+6n7Wa/qqVh3toL87CCGEEEIIIaT60cxaQgghhPzyUlNTmRl7osjLy2Pw4MFVGsOECRPQp08fzJo1C5aWlhg6dCgUFRWr9J6V6VfI4e+Ow+Hg4sWL8PHxwcCBA/H161ecOHECW7duZcoUFRXB19cXgYGBSExMhIKCAoyMjDBq1ChmZmSPHj0wevRoDBw4UKD+58+fY/To0QgJCUFhYSECAgIQFhaGN2/eIDMzE3JyctDW1oatrS3Mzc0xePBgLF26FJmZmVBQUACPx0NRURGaNGmCkJAQdOjQAampqYiNjcWyZcvw999/M/f68uULfHx8EBoaiszMTOjp6aFbt24YM2YMMxN/7ty5qFGjhsB1Hz9+xJ49exAWFobMzExoa2vDwcEB48aNE9hPlU0b1dXVWeWrNFH9+NChQ/jx4wfGjx+PmjVrMv04NjYW/fv3x/PnzyXG9OLFC8ycORMmJiaoUaMGXr9+jaKiIigrK6NVq1bMc5WTk4OjoyNsbGwwaNAgREVFCfQNPT09dOjQAVOnTmUGPUvncMGCBRL3Ivbx8YGNjY3EvD948ACpqamoWbMmGjduDHt7e6ipqTHlfH19UVxcDBMTE4F+euzYMdBndAkhhBBCCCGEkF8TDdYSQggh5JfH4/GQk5Mj9vzPmIFkbGyMc+fO4cqVK8jKyqry+1W2XyGHfwJvb28EBgYiKioKGhoaOHnyJJo2bcqc37p1K4KDg7F69WqYmZkhNzcXgYGBmDJlCk6ePAkrKyvk5uaisLBQqO7i4mLk5OSAx+OBx+Phxo0biImJQffu3aGrq4vCwkJERUXhzJkzGDp0KABAX18fVlZWqFu3LtTU1NC6dWu8e/cOkyZNwsmTJ9GjRw9cuXIFBQUFzH1iY2MxZMgQtG7dGuvWrYOenh6io6OxdetW3L17FydPnoSSkhLy8/MF+kVERASGDx8OOzs7rFu3Dvr6+vjy5Qv27dsHDw8PnDp1ilkKmE0b2earNFH9OD8/H/n5+bhx4wa6d+8udC8+STEVFxdj8ODBePfuHdq0aYP27dvjw4cP2LhxI65du8aU1dLSYuoaOnQoRo4cCQDgcrl4//49Vq1ahS9fvmDHjh1MbPwcLliwADNmzAAA3Lx5U2zdkvK+ePFiPH36FJmZmXj8+DH27NmDwYMHo1atWgBKlhUvLCxE3bp14ezszPTTDRs2YNq0aUJtJ4QQQgghhBBCSPWjwVpCCCGE/PK0tbUxfvz46g4DTZo0YQZbfje/Sg5/d0pKSvDw8BB7PiQkBJ6enszerurq6hg1ahQcHBxQt25d1vfR1tZGZmYmxo0bhzFjxgici4mJYeqSk5ODlZUVJk+ezJzv3LkzgoODERQUBEtLS6G6//77bxgbG2PXrl3MfsANGjRA69at0b9/fzx79gy2trZC1y1ZsgQtW7bE9u3bmWP169dH27ZtMWDAAKxevRp79uxh3UZA9nyJ6sdXrlyBl5cXduzYgeXLl8t0/9KcnZ2hoaHBfJ+eng4OhwMDAwOR5VVVVQVmE+vr62POnDn466+/kJ+fD2VlZYHy/AFV/teS6i6tbN67dOkCoGSAeMCAAYiNjWXyfuXKFbi5uWHHjh0YOHAg01ejo6OlJ4AQQgghhBBCCCHVQq66AyCEEEIIIeRP0aBBA1y+fBkJCQkCx01MTGTeD7IidSkqKopc9jY1NRVhYWEYN24cM1DLp6WlhVu3bokcqP348SNev36NCRMmCJ2Tk5PDhAkTcO/ePWRkZLBpGqOy8lWnTh14eXlh5cqV1brcr7y8PLhcLrhcbqXUV568/yq5IIQQQgghhBBCCDs0WEsIIYQQQkglWbJkCdTU1NCtWze4uLhg5cqVuH37NoqLi39KXUVFRQgMDMTLly/h5OQkdP7jx4/g8XgwMTGRKZYPHz4AgNjrTExMUFxcjI8fP8pUb2Xli8fjYcKECUhJScHZs2dlurayfPnyBbt374aDgwNq1KhRKXWWJ+/lzQWXy2WWhP4d/wGo9hh+13YQQgghhBBCCKletAwyIYQQQgghlcTAwABHjx5FbGwsQkNDERYWhpkzZ6JOnTo4cOCATEshs61r165d2LdvHwCgoKAA+vr6WLNmDbO0cGlycuX7rKa0PY35s3TLztaVpjLzpaysjEWLFmHx4sXo1q2bTHGUR+m88wc6e/TogaVLl1baPcqb9/LkIiYmpnxB/kLCw8OrO4RK8ae0gxBCCCGEEEIIOzRYSwghhBBCSCUzNjaGsbExhg0bhtTUVAwZMgR79uzBypUroaSkhNzcXKFrsrOzAQAqKiqs6wKA0aNHY9SoUcy1kpYPrlevHjgcDt69e4f69euzbk+DBg0AlAzotWvXTuj8hw8fIC8vj3r16gFApbeRrS5duuDMmTPYsmULhg8fLnBO1pikKZ338PBw/PXXX5gwYYLA3rQVJWveS5OUC1FMTEygpqZW8aCrQXFxMcLDw2FhYSF1gPtXVh3tyMnJoT2NCSGEEEIIIaSa0WAtIYQQQgghVUhLSwuWlpZISkoCADRu3FjkzLmnT5+iUaNGUFJSYl0XUDLIqKWlxTqWNm3aYN++fXBychKYkcnlcjFt2jR4enqiY8eOAtcZGhqiefPmOHDggMhBwyNHjsDe3p4ZqKzsNspi8eLFcHNzE5pZXJGYRCmd944dO8LFxQULFy7EmTNnKm2gTda8lyUuF6LIycn91gOdQMlM5N+9DcDPbcefkC9CCCGEEEII+d3RnrWEEEIIIYRUguTkZLi4uOD06dPIyMgAAOTm5uL69esIDg5Gly5dAABeXl4IDg7Gvn378O3bN3z//h2nT5+Gr68vJk2aJFNd5bFkyRJERUVh+vTpiIyMRFZWFl6/fo2JEyfi7du3sLS0FHndypUr8ejRIyxevBhxcXHIy8vD+/fvsWjRIrx58wZLlixhylZnGxs0aAAvLy9s3bpV4DibmCpi3rx5+PLlC/bv31/hukqTJe9licsFIYQQQgghhBBCfh00WEsIIYQQQkgl0NXVxZw5c3D58mV07NgRzZo1g62tLXx8fLB06VJ4enoCAOzs7LBr1y5cu3YNnTp1goODA44dO4bVq1fDw8NDprrKo2nTpvDz8wOHw8HQoUNhbW2NcePGwcDAAGfPnkXt2rVFXmdhYQE/Pz/8+PEDnp6eaNmyJQYPHoyCggKcO3cODRs2ZMpWdxsnTJggdIxNTBVRu3ZtLFiwADt27KjU/V9lybsoonJBCCGEEEIIIYSQXweHx+PxqjsIIlpOTg4iIiJgbm4uce8xvuLiYrx48QJWVlZVupxVZd8n834tma/RsE+v8H2BXzdnsj57QgghhPx6CgoKpC6ty+VywePxpL4+EFdXXl4e5OXloaioKPba/Px8cDgcsbEUFRVBQUF4dxRp1xUWFkq8L19F2yhNXl4eFBQUhNpQUFCAwsJC1KxZs1wxFRUVoaCgQORrMUl5z87OhpKSEhQVFcXmUFLdFcl7eXLBf91pamoKdXV1kfX+6n7Wa/qqVh3toL87CCGEEEIIIaT60Z61hBBC/mh+fn5IS0vDuHHjBPZmBICkpCScO3cOrVq1gp2dHQDg+vXrUFRUROfOnZlyWVlZuHfvHr5+/QoFBQUYGRnBxsZG4M1yaWXK1uvn54fCwkIMGTJEIKbU1FScOnUKkydPFjiekJCAsLAwZGRkQEtLC7a2tqhbt67MuUhOTma+l5OTg56eHmxsbFCvXj2x5Upr166dwN6H8fHxePToETIyMqCjowM7Ozvo6+sLXHPkyBG0atUKFhYWAscTExNx4cIFjB07FkpKSiJzVFnxli6joKAALS0tWFtbw8jISGLOypJ0r0mTJoHD4Uhth7j4jIyMxO4rKUv8bPrr/7Lo6Gg8evQIw4YNY1W+oKAAAQEByMvLw9ChQ2W6F5uBRzk5dgvdiKtLRUVF6rXKysoSz/MH9krnpri4GAcOHED//v2hp6cn8jq2faqibZRGXA6UlJTE1skmJlGDntLuCUBgQFRc7svWXVxcjD179kjMN5+kvJcnF4QQQgghhBBCCKletAwyIYSQP9qxY8ewdetWPHr0SOjc+fPnsWPHDoSEhDDHrly5gqCgIOb7Z8+eoXPnzrh48SJSU1MRHx+PFStWYMCAAcjKymJdpmy9x44dw8qVK3Hnzh2BmFJSUuDt7c18X1RUhOXLl8PZ2RlBQUGIj4/HxYsX0a1bN2zbtk3mXISEhCAtLQ1paWlITk5GQEAAevXqhcDAQIFyd+7cQUpKitC/3NxcgbhcXFxw48YNJCQkICAgAF26dMGmTZtQeuGO/fv34+XLl0LxfP78Gd7e3sjLyxObo8qKt3Rdnz59QkBAAFxdXTF9+nTmGbHNobh78dssqh1s4hPVR0XlQlL8bPpiVXr48CFiY2N/6XtERETg4MGDrMtv374d27dvZ/ZUleZn5KCqlM4Nl8vF69evmZ/P6hATE4MOHTqI/detW7dqi40NWfrCr5BvQgghhBBCCCGEVA+aWUsIIeSPZ2lpiYsXL8LGxkbgeEBAAFq0aCHx2n///Rfu7u5YvHgxc2z27NlYsWIF3r9/D0tLS1ZlROnatStWr14NOzs7sbOvdu7ciatXr+Ls2bMwMzNjjt+/fx/jx4+Hubm5TAMWHTp0EJq1u2PHDvz999/o3bs3c6xTp05C5Urbvn07rl27hvPnz6NJkybM8VevXmHkyJHQ0dHBqFGjWMdV1fGKqis2NhaTJ0/GwoULsX37dtYxsblXZVxTFpv4y9sXK8uJEyfQu3dvGBsb/9b3KC0yMhJubm6sn9/Pjq+qKCoqYteuXdUag4mJicCHaX43svSFXyHfhBBCCCGEEEIIqR40s5YQQsgfr1OnTggKChKYsRQeHo68vDypb6JnZ2cLLZdZo0YN/PPPP8zAF5syojg7O0NbWxt79+4Veb6wsBCHDx/GuHHjBAZqAcDe3h7e3t5o2rSpxPjZaNeuHdLS0ljPHMzNzcXhw4cxefJkgYFaoGRg3MvLCwcOHACXy61wbKLIGq84xsbGWLFiBYKCghATE1NJ0f08ouJn0xevXr2K4OBgsfVmZmbi4sWL2L9/Py5evCiQZx6Ph9DQUPj6+uLEiRMCswYvXryIZ8+eISgoCIGBgSgoKMCuXbuQmprKlImIiMDJkycBlCz7umvXLqSkpODMmTN49eqVzPfge/v2LY4fPw4/Pz/Ex8cLtKe4uBg3btzAwYMH8eDBA3bJLXW/Dx8+4MWLFzhw4EC545OkuLgYwcHBOHToEJ48eYKEhAT4+vqyjlHS8wJKPkBx/PhxnD59GpGRkUL3Fpcb/vP59u2b1GfJ5XKxa9cupKWl4dq1azhw4ACePXsGoGS298GDBxEcHCww416S8tRXkTyWbl9QUBAOHjwoMEgsrq8C4vMra18tnW9++zMzM3H37l0cOHAA169fR3FxMav2VDQfhBBCCCGEEEII+bloZi0hhJA/Xv369dG4cWPcuHEDrq6uAIBLly7B1dUVSUlJEq8dMmQIli5diq9fv6Jz585o164d6tSpI3MZUXg8HpYtW4ahQ4fC3d0dDRo0EDgfExOD7Oxs2Nvbi7y+a9euUu/BxrNnz6CtrQ1NTU3m2OPHj0XO8ho9ejTevn2L3NxcdOjQQWR9HTt2xM6dOxEfHy/znrBVEa+kvSVtbGygpKSE58+fw8TEpNJjrWh80pSNn01fLCoqEtq/mS8zMxPOzs6ws7ODsbEx7t69i82bN8Pf3x9aWlpYunQpHj9+DFdXV6Snp2P9+vXw9vaGk5MT1NXVkZubCzU1NdSsWRN5eXnw9vZG165doaWlBQB4/fo1Dh8+jMGDBwMAvL29ERkZiezsbNSuXRsAZLoHUDLT+tSpUxg0aBDy8/Px77//YunSpejVqxcAYMaMGYiLi4OrqysCAgIQFRXFOr9qampQUFBAjRo1UKtWrXLFJ820adMQExMDV1dXHD58GJmZmUhISGA1M13a89q0aRMCAgLg6emJwsJCbNmyBZMmTWLqlpSboqIieHt7w9HRESoqKhKfJYfDgbe3N168eIEGDRogPz8fmzZtwuDBg5GamooGDRpg9+7dmDBhAsaOHSu1XeWpryJ55HK58Pb2xoMHD2BsbAx1dXXMmzcPbm5uWLRoEQDRfVVSfmXtq6XzraurC29vb7x8+RJaWlrQ19fH8uXL8fjxYyxZskRqe8qbDy6XK9OA8K+EH/fvGj9fdbTjd88ZIYQQQgghhPwJaLCWEELI/wQPDw9cvHgRrq6uKC4uxtWrV3H48GHs27dP4nX9+/eHsbExTp06hc2bNyMpKQlNmjTBqFGj0L9/f9ZlxGnevDk8PDywevVqoRm2/D1GdXV1mWPfvn3D2bNnme81NDQwbNgw1nkoPWjI5XIRFxeHGzduYP369QLlcnNzkZaWJnQ9l8tl4tLT0xN5D/7xtLS0Cg/WVka8ksjJyUFXVxfZ2dnliolPU1MTQ4cOFXtNeeOTpmz8bPoi/wMLonz48AHp6elYunQp1NXVAZQsF56fnw+gZFlaLy8vZkZ6dnY2/P394eTkhC5dukBFRQXt27dHx44dkZmZKTF2eXl5AEC9evUwf/585rgs9/j8+TN27dqFU6dOMTOHTUxMsH79evTs2RPv379HUFAQbty4wXwYYuHChQgLC2OV365du+LYsWNo0aIF+vXrJ3N80sTExCA4OBjXr19Ho0aNAADjxo0TO5helqTn9fHjRxw4cADnz5+Hubk5AKBZs2ZYsGABBg0ahM+fP1coN6Xx47Wzs4OXlxeAksHchIQE7N+/H0DJ4G9YWBjrwVpZ6qtoHvnlbG1t8ddffwEArKysMGPGDEybNg1qamoABPuqtPzK2ldFxWNhYcHEo6enh8OHD7NqT3nz8TuuMFBWeHh4dYdQKf6UdhBCCCGEEEIIYYcGawkhhPxP6N27NzZs2IBv374hMjIS+vr6rPeUbNWqFVq1agWgZHDE398fy5cvR1FREQYNGsS6jDgzZ85Ejx49EBwcLDC7lj+DLTExkRmwLSwsxOfPnwEAnz9/RkJCgkyDtXl5efjx4wcA4N27d3j27BkuXryIxo0bC5QTtVcsH3+GYVJSktB1QMmAMgBm5iuHwxG5/Cn/WNlleys7XkmKi4uRlpbG5JqNHz9+4OvXrwLHCgsLJV5T3vikERV/Rfpis2bN4OTkhG7dusHe3h52dnbo1q0b8yyHDBmC0NBQPHz4EDk5Ofj06ROUlJQq1AY7OzuB72W5R2RkJHg8Hv777z/8999/AEpmm379+hXfvn3D+/fvoaqqKvBz1bJly3INSJYnPmni4uKgrq7ODKgBQPv27QWWVpZE0vO6efMmlJWVmYFEoGSZcn7McXFxlZ4bCwsL5mstLS00b96c+V5bWxvPnz+vkvoqmke+du3aMV+3aNEChYWF+PTpE7PcfOm+Gh0dLTG/ZWfqS+ur/N+rpVlbWwu0n/9BGWnKmw8TExNmYPp3U1xcjPDwcFhYWDAfBPkdVUc7cnJyEB0d/VPuRQghhBBCCCFENBqsJYQQ8j+hdu3asLe3R2BgIF6/fg03N7dy1dOoUSNMnz4d8fHxCAkJETn4xaZMaZqampg9ezbWrl2Lbdu2CdSjq6uL27dvMzOx6tWrhzVr1gAArl27hg0bNsgUv6OjIzNomJubC2dnZ1y5cgVTp05lXUfTpk2hqqqKkJAQkYO1oaGh0NbWZmbV1q5dW2hwEwA+ffqEGjVqSBwcqIx4Jbl//z5yc3MFBmmk6dy5c5UMvJaHtPhl7YsKCgrYtm0b4uPj8eDBAwQHB2Pjxo04evQo9PT04OnpiQYNGqBDhw6oVasWatasKXWgujRRZVVVVZmv09PTZboHh8OBvLw8lJWVmWO6urqYN28eFBQUwOVyhWYTVmTJT1njk6a4uFjowwoKCuxfnkt6XjweT+JMyormRlSby8YuS1tEYVtfRfPIVzof/K9LHyvdV6XlV1TdkvqqKIqKiqzrL628+ZCTk/utBzqBkhn7v3sbgJ/bjj8hX4QQQgghhBDyuxM/lYUQQgj5w3h4eCA4OBj37t2Di4uL1PLp6em4ePGi0GymoqIixMfHQ1dXl1UZNvr37w9dXV0cOnSIOSYvL4+xY8fC19cXr169Eqr/8ePHEmelSlOjRg0sX74ce/bsQWRkJOvrlJWVMWzYMPj4+CAuLk7gXGxsLA4cOICxY8cysXXs2BGXLl1CamoqUy4nJwdHjx5Ft27dqjxecb58+YLVq1fD3d0dBgYGFa7vZysbf2X0xVevXuHy5cto2LAhBg8eDB8fH5iZmeH27dt49OgRUlJSsHfvXowcORJ9+vRBTk6OwKzp0rOoa9SoATk5OWRkZDDnnz17JvH+st7DzMwMXC4XTk5OGDNmDMaMGQMXFxc0bNgQ2traaNCgAbKzs5GQkMA6hsqMTxpDQ0NkZmYK7J396NEj1vFIel5mZmbIy8sT2If2xYsXUFVVRf369WXKTXme5c9U0Tzylf49GxkZCUVFRdSrV09kWWn5BWTrq5WpsvJBCCGEEEIIIYSQn4Nm1hJCCPmf0alTJyxduhQtW7Zk9ea4qqoqzp07B29vbzg6OqJ27drIzs7G/fv3IScnh0mTJrEqwwaHw8GyZcswYMAAgeMjR45ESkoKhgwZgvbt26NBgwbIyMhAWFgYNDQ0sGXLlnLlgq9jx47o1q0bFi5cCD8/P2b21b1795jlh0szNDTE0KFDMXXqVCQlJcHDwwNdu3aFgYEBEhMTcfPmTQwYMIDZZxIAJk6ciGfPnsHZ2RkdOnSAnJwcHjx4AC0tLSxcuPCnxAuUzELNyckBl8tFYmIibt++DXt7eyxbtkymGMqDTXyiyri4uDBLv0qLn21fvHr1KhQVFdG1a1eheJSUlLBy5Uo8evQIjRs3RlJSEiIjIzF//nyoqqqisLAQ69atg46ODh4+fIhGjRoxH4BwdHSEjo4OTp48idTUVAwdOhRt27bF33//DVdXV0RHRyMnJ0dinpo0aSLzPcaNG4exY8fC09MT8vLyOHv2LLp3746uXbvC3Nwctra2mDRpEpydnREbG4sPHz6wHkytjPgkadGiBaysrDB58mS4ubkhMjJSaK/f69evQ05OTuQHGyQ9r/r162PUqFGYMmUKBg0ahNzcXBw/fhxz5sxhlu9lmxtFRUWZn+XPVNE88l29ehXp6emoVasWjh07hiFDhoid+S8tvwBk6quViU0+CCGEEEIIIYQQ8uugwVpCCCF/tAEDBjB7ByopKWHZsmWoW7cuc75z585QUVFhvu/Rowez9KSSkhKOHDmCly9fIjw8HBkZGTA0NMTixYvRvn17ZuYomzKl6y0bF1/z5s2xatUqxMfHM8c4HA7mzJmDoUOH4r///sO3b99gaGiIgQMHonXr1jLNrB0wYACaNGkidHzx4sU4evQo4uLi0KRJEwwYMIDZd7as0rnZsGEDRo8ejUePHmH79u1o3749/P39BfZJBEpm5R0+fBhhYWEIDw8HAPTs2RP29vYCS3OKylFlxVu6jIKCAqysrDB27FiBPTDZEBdTaaLaIUt8pfGXp2QTP9v+WlRUJHb51qZNmyIgIAC3b9/G9+/fUb9+fVy6dImZeXz27FmEhIRASUkJq1evho6ODho3bozv378DADZt2oQbN25AR0cHALBr1y5cuXIF379/x8CBA6GtrY07d+4w95s4caLAz6ORkZHM95g5cyacnJzw4sULFBQUYM2aNWjbti1T5759+xAYGIgvX77AxcUFjRo1wo0bN0S2XxQ3NzfUqVOn3PFJc+jQIQQGBuLbt2/o168fPn36hN27dzPnMzIy8OjRI5GDjNKe1/z589GlSxe8evUKtWrVgq+vL7P/qrTcyMvLY+LEidDT0wPA7lmWnqHu6uoKfX195nsrKyuoq6uzykl56qtIHvmWLFmChIQEfP78GYsXLxYYRC3bVwHp+ZWlr5bNd9n7GRsbY+TIkeySxyIfhBBCCCGEEEII+XVweOWdWkCqXE5ODiIiImBubi6wR5Y4xcXFePHiBaysrKp076HKvk/m/VoyX6Nhn17h+wK/bs5kffaEEFLdFi1ahJiYGJw+fVqmfRwJ+V/G4/Fw7tw52NjYMEvnrl27Fu/fv8f+/fsBlOwB/fDhQ8ycObM6Q/2lVTSP+fn5sLS0xNmzZ2FhYfFTY68KbPJRGv91p6mpqUwD6r+Sn/WavqpVRzvo7w5CCCGEEEIIqX40s5YQQmTk7u6OmJgYhISECC2lGxwcjClTpmD06NGYP38+AGDatGlQVVXF+vXrAQAFBQXw8fHBlStXkJSUBHl5eRgZGcHLywvOzs6sy5St193dHV+/fsW1a9dQu3ZtJqbo6Gi4uroK7Kv3/v177Ny5E2FhYUhPT4eWlhbs7e3x119/id2fT1wuSu8dyuFwoKenhw4dOmD27NlMHGXLlTZ9+nRMnjwZQMl+p7t27WLi0tHRgYODAyZPniwww6hDhw4YP348hg0bJlDXkydPMHToUDx+/BgaGhoic1RZ8ZYuIy8vDy0tLbRp0wZjx45FixYtyp3D0t68eQMFBQWp7SjNzs4O7dq1w/Hjx9GkSRO0a9cOCgoKGD9+vNj7SoqfTV8EgEmTJsHDwwPjx4+HhYUFJk6cCCUlJdZ5EKWiAyiyXJ+SkoIzZ86IPS8qh+T3Vt5n7u/vD29vb9y6dYtV/Z8+fcK1a9cAAGPHjhWqPzQ0FPv370ffvn2RlJSE8+fPC8yAzMvLg6enp6zNqxalcyPu568qftY4HE615/HRo0eYPXs2gJLXAvy2m5qaVupAMNv8ScsHIYQQQgghhBBCfh00WFsOb968wcqVK+Hp6Sn0pk98fDx27NiB2NhY6OnpYdy4cbC2tmZ9nhDye6hduzYCAgIwatQogeOXLl2Crq6uxGs3bdqE0NBQbN26FU2aNEFeXh6uXr2KOXPmQE9PD23btmVVRhQFBQVs3rwZq1evFnv/169fY/jw4ejatSv27NkDAwMDxMfHY/v27Rg4cCAuXrzIevlOAJg8eTIzAMHlcvH+/XssW7YM8+bNw759+5hyEydOxJgxY4Su5y9BHB4ejhEjRqBbt27Yu3cvDAwM8PnzZ+zduxd9+vTB6dOnhZbXLY/Kird0Xfn5+YiPj8eZM2cwaNAgbNmyBd27d2cdk7h7lV4iWNI16enpuHnzJoCSZXXl5eUhLy8PFRUV1K5dW2w9bOJn2xfr168Pf39/BAUFQUFBQablmauKkpISAgIC0LBhQ6ll5eXlBT7kUJakZ0Eqz8qVK2FjY4OePXtW+T1sbGyq9Jnz+9SNGzdgZGSEfv36Ccw659e/YcMG3LlzB9HR0WjcuDG6du2K9PR0ppyTk1OF4qgu4n7+qupnrWweL126xMwqBSTnsewSxOVx/Phx5v9vDofD+nePrNjmT1o+CCGEEEIIIYQQ8uugdx5lFBAQgD179iAnJwdpaWkC57KysjBs2DB07NgRixYtwtOnTzFmzBicO3cOxsbGUs8TQn4fDg4O8Pf3Fxis/fHjB+7fvw8HBweJ14aGhsLDwwPm5uYAADU1NXh6eqJ9+/bMG8Vsyogybtw4eHt7w9PTEy1bthRZZuXKlWjdujU2btzIHNPW1sbevXsxdOhQPHjwAG5ubqzyAJQMDtasWZP5vmXLlpg1axYmTpyIvLw8ZnBTWVkZGhoaYutZunQpbGxssGHDBuaYlpYWtm3bhiFDhmDVqlU4cOAA67iqOt7SddWsWRNaWlpo1aoVatWqhaVLl8Le3l7gPpKwuZekazQ0NODl5SVw/tSpU7C0tMTgwYMrFL8sfdHQ0BCjR4+WqR1VicPhwNTUlFXZ2rVrS8wV+TkiIyNhY2PzU+5R1c+cX39QUBBat26NIUOGiCwnLy+PLl26oEuXLgCAy5cvV1lMP5O4n7+qynvZPMpCQUGhwstMZ2ZmCuwjzm97fn5+heoti23+KpIPQgghhBBCCCGE/FzVP+3lN+Pv748jR46InHV25coVqKurY9WqVWjTpg0mTJiAjh074vjx46zOE0J+HzY2Nvj06ROio6OZY9euXUPbtm2l7vdlbGyMCxcuCC1jW69ePSgqKrIuI4qenh4mTpyIlStXgsvlCp1PSkrCq1evhAb2gJKBuzNnzsg0UCsOl8uFLFuix8fHIyIiQmCJUD4Oh4OxY8fiwYMHArPNKpOs8UoyadIkpKenIywsrFLq+9nKxs+mL06ePBlz5swRW2dsbCy8vLzQtm1b2Nvb459//kFxcTEA4Pnz5xg0aBBsbGxga2uL6dOnIyMjQ2Q9MTExGDNmDBwcHODo6IjJkyfj06dPAEqWazYzM8P58+fRvn17HDx4EPn5+TAzM0N4eDgA4MOHD5gwYQIcHR3RqVMnzJ8/X6BP7dmzB507d0bbtm3RqVMnmZYMFXdtZmYmzMzMBH5X+Pn5Ccwc/e+//+Di4oJ27dph+PDhOHr0KDp06MCcl5QjUe2uaFukxVPeXEhry7Rp0/DixQssX74cCxYskJo7cW2X5R6A9H5x//59ODs7w8bGBgMHDsSHDx9Y5+Kvv/7CkydPcOjQIWbZcFnjk6Yqn5eknzlAcm5K//xJe5bFxcUwMzPDxYsX0bt3b1haWmLUqFF4//49Ro4ciVatWsHFxUVgOX9JylNfRfJY9jmX/d0DlDz33r17o1WrVujbty9zTlw/ltYvpalovyCEEEIIIYQQQsjPQ4O1MvLx8YGWlpbIc8+fP0fr1q0Flrhr06YNnj9/zuo8IeT3oaSkhF69euHixYvMsUuXLsHd3V3qoN+SJUtQr149uLu7o3Pnzpg/fz6uXLmCgoICmcqIwuPx4OXlhezsbJw8eVLoPP9NdiMjIxlayx6Xy0VMTAy2b9+Ozp07CywZ7O3tDTMzM6F/qampSEhIAAA0btxYZL0mJibgcrkCgwTVGa8kGhoa0NXVxcePHys11rLKG580ZeNn0xd37dqFTZs2iayvoKAAEyZMgLW1Ne7fv4+zZ8/i1q1bOH36NICSGdUODg54+PAhgoKCEB8fL3JgsaCgAOPHj0fz5s1x9+5d3Lx5E2pqasxsOP7A8ZUrV+Dj44M+ffqIjKNhw4a4ffs2rl+/jry8PCxbtgwAEBERgR07duDo0aN4/PgxfH19ERAQgDdv3kjNWUWuzcrKwsyZM+Hh4YGHDx9i+fLlOHjwoMBSsJJyJKrdVR1PRXIhqS3btm2DlpYWVq5cyezPLIm4Zy7LPaT1i+zsbMycORMDBw5EWFgYtm3bhuvXr7PKBQDs2LED1tbW8PLywpUrVyo9B1X5vKT9zFU0N6XJy8sDAK5evYrTp0/j1q1biIyMxKRJk7BixQqEhYVBX18f+/fvr5L6KppHUc+5rKtXr+LQoUMICwtD06ZNMWfOHHC5XJH9WFq/lKa87eFyuSguLv5t/wGo9hh+13YQQgghhBBCCKletAyyjCS9yZGcnIwWLVoIHNPW1sa3b99YnReH7R/Rpf+4r0o/6z5sYqisen61nNGbJr8Hd3d3zJgxA3PmzEFSUhKioqLQuXNn3L17V+J1Ojo62LNnD758+YKHDx8iLCwMK1aswObNm+Hr64sGDRqwKiOOkpISlixZglmzZqFXr14C5/hvCpfuY+Hh4ejfvz/zfb169XDr1i3WefD29oa3tzfzvbKyMjw8PDBv3jyBcqX3ii2tZs2azBvr4ga6+bOERc0WllVlxMuGkpJSuWMCgAYNGuDGjRtir6lofNLw469IXwSAly9f4suXLxg/fjyUlJRQp04dgQGd0ku+amhowN7eXmD2Xel6EhMTMXnyZGZP3jFjxsDNzQ1JSUnQ19cHALi6usLS0hKA4PKjr169QkJCAmbMmAEFBQUoKChg0qRJ8PDwQG5uLrS0tMDhcHDhwgX06tULxsbGCAwMZJUrSddmZmZKvDY8PBy5ubkYOXIk5OTkYGJiAmdnZ4F7S8oR/wNgpdtdUFBQ7rawiae8uZDWFlmJarus95DWL16+fIns7Gxm2Vl9fX14eHjg1KlT5YpZ1vikqcrn9fjxY4k/c7GxsZWem8GDB0NdXR3q6uowMzNDkyZNmA8XtWvXDvfu3auS+iqaRzaGDx/O/J7y8vLCuXPn8OXLFxgaGgIQ7MdPnjyR2C9r1Kgh8V7lbU9MTEwltLR6lZ7N/Dv7U9pBCCGEEEIIIYQdGqytRMXFxcw+VXzy8vICA3WSzosj6xt4P+uP+8q6T5NyXPPixYtKuTff75Yz8muwtraGiooKHjx4gLdv36Jbt25QVlZmfX3dunXRt29f9O3bFz9+/MDgwYOxd+9erF69WqYyojg6OsLW1hYbN24U2EO0fv36kJOTQ3R0NDPIZm5ujv/++w8AcOfOHZmWSwVKln8cP348ADBLLA8cOBBqamoC5cruFVsaP5aYmBhoa2sLnY+LiwOHw0HDhg0BlAyw5uTkCJXLysoCh8MRmCFbFfFKkpSUhJSUFJlmL0+YMEFg/2Pg/88ME6e88UkjLv7y9sXk5GSoqamJHbw+deoUzpw5g+zsbABAWloaLCwsRNajrq4u8Gz5WxIkJyczgyD16tUTeZ9v376Bx+MJLQOqpqaGr1+/wsjICKdOncLRo0fh5eUFLpcLT09PTJkyRepsNH19fbHXSvP9+3doaGgILG/O7+d8bHJUut2S4pHWFjbxSCLt3myftyzKPnNZ7iGtX6SmpkJNTU0gH+JWWGGrMnNQlc9L2s9cVeSmVq1azNcKCgrQ1NQU+F7WD7Oxra+ieWTDwMCA+Zqfp7S0NGawtnQ/ZvP7SpLytsfExETo/8LfRXFxMcLDw2FhYSH1/89fWXW0Iycnp9wfGCGEEEIIIbL777//BCYjcDgc1KpVCw0bNoSGhgZzPCsrC8+ePUOLFi0q/LfWz/Dt2zd8+PABtWrVQpMmTQRWF60OcXFx+PjxI8zMzJj3jCpDTk4Onjx5gmbNmkFHR4f53tzcHLq6uhWut6L1VJXMzEy8f/8e+fn50NHRQcOGDVmvRlUeCQkJ+PLlC4yNjVGzZk2BnIvz8eNHxMXFwdHRsdr7X3nQYG0l0tTUxI8fPwSOZWZmMm8USTsvjqmpqdQ9MIGf98d9Zd8n+6Hs11hZWVX4vsCvmzN60+T34e7ujuvXr+Ply5dYsmRJuetRV1dHs2bN8P379wqVKW3hwoVwdnZG27ZtmWO1a9eGvb09s0ehnJwcFBQUmBcB5Rn8k5eXZwap27Zti379+mHhwoU4d+6cxP11SzM0NISlpSX2798PGxsbofOHDh2Co6Mj80a7sbGxyCXkw8LCYGxsLHFWa2XEK8n+/fuhr68vkHdpVFRUfpkX3mzil6Uv6urq4sePH8jJyRH6v+z58+dYuXIlTp48yfxeX716NeLi4oTq0dPTw48fPwRmlfFXpij9olvcizF9fX3Iy8sjNDRU7HM2MTHBunXrAIBZMlVfXx+DBg2S2k5x17q4uAAQnBWekpLCfM1/bVBcXMz8/1B6uW+2OSrb7vK2RVo8bIi7t5mZGevnDYD5gJu43PGVbrssfQqQ3i8+f/6MHz9+oKCggPm98vXrVykZEE/W+KSpyudlYmIi8WcuPT2ddW7YPsvqUhl5lKb0EvVpaWkAIPDhpNL9mM3vK0nK2x45ObnfeqATADML/Hf3M9vxJ+SLEEIIIeR3Mn78eHC5XIFJXfzX7v369cOCBQtQs2ZNxMXFYdy4cfDx8YGTk1M1RixZcXExVq5cCT8/PygoKKCgoACmpqbw8fER+4H6n2H27Nl48+YN+vbty/zNWxkSExMxbtw4eHt7o2fPnsz3W7ZsgbOzc4XrrWg9lS0hIQFr165FSEiIwAeotbW1MWjQIEyePLnSB22PHz+Ov//+G+rq6pgxYwbs7OwEci5OQEAAvL298ebNmyodSK4qtGdtJTIzM0NUVJTAsbdv38Lc3JzVeXH4f6yz+Sdr+fL+q8z7lMev2pbKvA/5Pbi7uyM4OBhZWVmsBueSk5PRpUsXHDp0CImJicjPz0dqaiouXLiA69evo2fPnqzKsFG3bl1MmDABW7duFTi+fPlyfP78GZMmTcLz58+RmpqK9+/f4+jRo1izZo3IwVJZzJkzB6mpqUIzdPPz85GZmSn0jz+7bPny5Xj69CkWLFiAmJgYZGVl4d27d5g7dy6io6OxePFipq6xY8ciJCQE3t7e+PDhAz5+/IhDhw7h6NGjrGYzVka8AFBYWIjs7GxkZWUhOjoay5cvx6lTp7B27doq/zlmE5+oMoWFhazjr4y+2LJlS9SpUwfbtm1DXl4eEhIS4ObmhgMHDiA9PR1KSkqoW7cuCgsLERwcjPv374tcOtjS0hL16tWDj48PuFwu8vPzsWfPHrRr147VJw4tLS1haGiIHTt2oKioCEVFRfDx8cGkSZMAAOfPn0e/fv2YwSYDAwPWH16QdK2amhpq1arFLC0eGxuLq1evMtfyP8Tj5+cHAPjw4YPAeVlyxCYeaaTFI42ke7Npi4KCAlJSUlBYWCg1d6LIeg9p/aJly5ZQUVHB4cOHUVxcjNjYWPj7+7POR0Xjk6Yqn5e0nzlZclOeZ/kzVTSPbBw/fhxZWVngcrk4evQoTExMUKdOHZFlpfVLaX5GewghhBBCCCHl169fP7x9+5b5Fxoainnz5sHPz0/qCma/ml27duHy5cvYv38/wsPDERwcjLy8PCxatKjaYnr79i0zUHvt2jVkZWVVWt0NGjRAUFCQ0EpIf6IPHz7A09MTr1+/xqpVq3D//n08f/4cAQEBcHd3h4+PD2bNmlXp97127RqaNm2KsLAwDBs27H8m5zRYW4mcnZ3x/PlzhISEAChZvvjSpUvo27cvq/OEkN9P/fr1YWRkBBcXF1bLK+jq6mLt2rV4+PAh+vXrB2tra/Tq1Qtnz57Fhg0b4O7uzqoMW6NHjxba265+/fq4cOECDAwMMHv2bHTo0AGDBw/GnTt3sGzZsgp/2kxdXR2LFy/G3r17ERERwRz38fFB27Zthf7x911t0aIFTp8+jdzcXAwfPhzW1tYYPnw45OTkcP78eTRq1Iipq02bNjhw4ACePHmCPn36wM3NDdevX8fWrVvRu3fvnxIvUPKCtHXr1rC2tsaIESPw/ft3nDp1Cvb29uXMHnts4hNVpvSehdLiZ9sXJ0+ejDlz5oiMU0lJCXv27EFERAQcHBwwcOBAtGnTBsOHD4ejoyO6du0KZ2dnODk5ISwsDOvWrUNCQgJmz54tsp7Xr1+jQ4cO6Nq1KzgcDjZt2sQqX4qKitizZw+ioqLQqVMn2Nvb49GjR5g7dy4AwM3NDQ4ODhgwYADatm0Ld3d3tG/fHv369QMATJs2DTNnzhRZt7Rrly1bhjNnzqB169ZYs2YNhg8fznwasVatWli7di32798POzs7rFmzBkOGDGHqliVHbOORRFo8FckFm7a4u7tjw4YNzKCUpNyJIus9pPULdXV1bNq0CWfPnoW1tTUWLlyIQYMGsRpIrYz4pKnK5yXtZ07W3Mj6LH+miuZREn4be/bsicGDB8PW1havX7/Gpk2bxL5ukNYvK6M9hBBCCCGEkF+HlpYWRo0aBScnJ1y9ehU8Ho85x+FwUFxcjFevXuH58+ciBx6zsrLw6tUrPHr0SOyqOl+/fsWTJ0/w4sULsR8ALy4uZgaPP378KDXu/Px8HDx4EKNHj2beS6pfvz52797N+u+XqnDq1Ck0atQIc+bMQUFBAa5cuSKyXFpaGsLCwpgJdklJScwM0uzsbISEhCA9PR2pqal49OgRioqKUFhYiPj4eJHbsxUWFjLPoewKqwCQm5uL169fIywsDAkJCWLjz8rKQkhIiMjVqz59+oSQkBDk5+czx5KTk/Hs2TM8e/aMWcmpLC6Xi6ioKISGhrJe3WvZsmUoKCjA0aNH0a9fP+jo6EBVVRWmpqaYP38+Vq1aBVNTU+Tm5jLXFBcXIyIiAqGhoXj37p3ACls5OTlMTnk8Ht6+fYunT58iIyMDAFBUVISQkBB8+/YNSkpKuH//Pj59+iQ256mpqQgLC0NERITAzwzbdkuLp7SioiK8efMGYWFhYn/GypNjATzC2qtXr3hOTk48JycnXvPmzXlt2rThOTk58caOHcuUuXDhAq9Vq1Y8R0dHnoWFBW/nzp0CdUg7X1p2djbvyZMnvOzsbFbxFRUV8Z48ecIrKioqXwNZquz7ZPynKfO/yvKr5kzWZ0/In8jT05O3atWq6g6DEB6Px+PFxcXxli5d+lPudeTIEV7fvn1/yr3YKBvPz8wFkR09r8rxp+VR0u8V/uvOzMzMnxxV5flZr+mrWnW0g/7uIIQQQgj5uczNzXmLFi0SeW7lypU8U1NTXm5uLu/Vq1c8U1NT3rFjx3hdu3bl2djY8Jo3b86ztrbmhYaGMtds2bKF16JFC167du149vb2PFNTU97o0aOZ13d5eXm8SZMm8czNzXlOTk48W1tbXosWLXjbt28XuPfDhw95HTt25DVv3pzn5OTEa9q0KW/UqFG89PR0sW25f/8+z9TUlBcTE8PLzMzkPX78mBceHl6tr8uzs7N5rVq14u3Zs4fH4/F4kydPFvm30IkTJ3jNmzfnWVlZ8RwdHXmDBw/m7dy5k2dqasrLz8/nxcTE8ExNTXnHjx/ntW7dmmdqasr7/v07c/zq1as8Ho/HfL9r1y5ep06deG3atOGZm5vzrKyseNeuXWPud+DAAV7Lli15bdq04Tk6OvLMzMx4gwYN4qWmpgrUc/nyZV5+fj7P1taWN2fOHKG4//rrL16XLl14XC6XV1RUxJs7dy7P3Nyc17FjR569vT2vefPmvLVr1/K4XC5zzatXr3jdunXjNWvWjOfk5MQzNzfnDRgwgPf161exeYyPj+eZmpry1q9fzzr3jx494nXq1InpQ+bm5rzu3bvz3rx5I1Dn2bNnea6urrx27drxLC0teS1btuQFBQXxfvz4wXNzc+NZWlryWrduzXNzc+NduHBBKOc8Ho936tQpXvPmzXmtWrXi2dvb89zd3XmrV6/mmZqa8goLC1m1W1o8fE+fPuV17NiRZ25uzrOxseGZmZnxhg0bxktOTq5Qjsv6/RZurkYmJibw8fEROq6iosJ87eHhgV69eiExMRE6OjpQU1MTKCvtPCGEkBIDBw7EqlWr0KtXL1hYWEjch5b8HEeOHEFqaiqmTZsmsLcKAHz58gUnTpxA27Zt0bFjRwDApUuXoKioiF69ejHl0tLScOvWLSQmJkJRURFGRkbo0KGDwP+l0sqUrffIkSMoKCgQmFUMlOyJ6evrKzTrNyoqCg8fPkRGRga0tLRgZ2cHY2NjiW0PCgoSWOr8yJEjzP6dQMlej3p6emjfvj0aN24stlxpDg4OsLGxgYeHB7p164bOnTvj9u3bOH78OMzMzJCQkIAGDRoIXMNfhrZVq1YCxz9//oyTJ09i6tSpUFZWFpkjNvEePnwYPj4+MDIyQqtWrZCbm4urV6+ifv36ePjwIWxtbbF+/XoAwKZNmyAvLw9tbW20adMGzZo1k5jDsiTlZtasWZCTk5PajrL5tLW1xZEjR2BqagpbW1up95UWP5v+Wp14PB7TfyZPnozv37/Dz89PYGmgsn2XCKuMPEZERODevXsYP348q3vm5ubi7NmzyMvLw7hx4yrchtLYtIcQQgghhBDya+FyuXj27Bnq1asn8Denr68vtmzZAgsLC6SmpsLT0xNbt27FqVOnkJ6ejvj4eCxduhQDBgwAAISGhsLLywv79u3D9OnTcf78edy9excBAQHMex8XL17EggUL0KNHDzRp0gTJycmYPHkymjVrhoCAAKirqyM2NhbDhw/HihUr8O+//4qMOTY2FgDw8OFDbNq0CcrKykhLS0PDhg2xa9cumJiYVHHWhF25cgX5+fnMaqaenp6YMGECIiMj0bRpUwAl72GtWbMGXbp0waZNm6CoqAg/Pz+sXbsWQMl7Jvz3IY8ePYqVK1eidevW0NTUFDtz9fDhw/j3339hZ2eHzMxMjBs3DkuWLEGHDh0gJyeHN2/eYPr06Rg1ahQ4HA5ev36NQYMGwdvbGytWrBCoS0lJCR4eHjhx4gSWL1/OjCFlZWXh7t27mDhxIjgcDm7cuAF/f3+cPn0aVlZWAIDbt29j0qRJ6NKlC9q1a4esrCxMnDgR+vr6CAkJgba2Nj59+oSRI0di/vz58PX1Fdme8PBwAED79u1Z5T0zMxN//fUXTE1NcenSJairqyMlJQVeXl7466+/EBQUxLyXuG3bNvzzzz+wtbVFTk4Ohg8fjk2bNuH69evw9/dH3759oauriz179gD4//2M7+vXr1i1ahW6du2KzZs3Q15eHnfv3sXUqVOZMmzaLS2ebt26ISsrC1OmTEHLli1x+fJlqKmpISEhARs3bsT9+/fh7u5e7hyXRYO1MqhRowZMTU2lllNWVhZYrlPW84QQUt1iYmIwevRoseeVlZVx48aNKo2hb9++iI6OxsSJE6GgoIBbt24JLen8K/sVcljZzp07h9jYWLRr107oxdr58+fh6+uL4uJiZrA2ODgYqqqqzEDbw4cPMWnSJHTq1AmmpqbIycnBtm3bmD8yNDQ0WJUpW++5c+cQGRmJ+vXro0ePHkxMqamp2LdvHzNYW1BQgMWLFyMoKAidOnWCgYEB3r59i/Xr12PYsGFYsGCB2LaXHYA5d+4cNDQ00Lp1awAlf1SFhoZi/fr1+Pvvv5k/Cs6dOwc1NTWhwVU+DoeDRYsWYdq0adi+fTvzGqFGjRpwdnaGp6cnlixZwryAPH78OGrWrClUX2JiIvbt24fx48dDWVlZZI4UFRXx/v175pqioiLk5+dDQ0MDNWrUgLKyMlRVVaGrq4uEhASEh4dDQUEBDRs2FLhfYmIiNDQ0IC8vj4KCAoSGhmLLli1o27YtNm3aBE1NTbF5LJtDSbkBhPsQm2vOnTuHHj16iB2sLf3sJMUvrS9++/atSn/G2f4O4S9f7+vrCxUVFXTp0gWTJ09myrEdPPyVhYSEwMDAAKamplXyu5XD4cDd3Z35PVaePEZHR+PUqVOs871t2zYEBQVh+PDhrMrzcyAnJ1cp/YIQQgghhBBSfb5+/cpslQiUvH8REBCAiIgI5gPSfH379oWFhQWAkuWSnZycEBAQAKBkC5StW7cKlLezs4ORkRFev37N1M3j8QQ+dO/h4YGePXsyg8JXrlxBVlYWFi9eDHV1dQCAsbExRowYgW3btiE9PR21atUSakdGRgY4HA4CAgJw7do16OvrIzY2FuPGjcP8+fNx9uxZVtvGVabTp0/DyckJOjo6AEq2IzIwMICfnx+WLl0KALhz5w4KCwsxbdo0KCoqAigZ1D1//jyePXsGAEzcVlZWcHFxkXrfbt26wc7ODgCgoaGB8ePHY/LkyXjy5AkcHR2xefNmgfItWrSApaUl85zKGjhwIA4ePIjAwEBmID44OBiFhYXo06cPgJJnWzpWAHBycsKLFy+YZxscHIyUlBRs2rQJ2traAABDQ0OMHz8ey5Ytw8ePH1G/fn2h+6enpwMAk0dpgoODkZ6ejlmzZjF9SEdHB+PGjcPcuXPx7Nkz1K1bl8kV/z0bVVVVODk5YdeuXSgqKoKCgvQhy9u3b6OwsBATJ06EvLw8AKBjx46wtbXF3bt3WbebnzdJ8QQHByM1NRWzZ89mBs0bNGiA7du3C7S9PDkuiwZrCSGECDExMRF40VgdOBwOFi5ciIULF1ZrHOX1K+SwKlhaWuLixYtCg7WXLl1CixYtJF67Y8cODB48GPPmzWOOTZkyBevWrcPHjx/RvHlzVmVE6dWrF9atW4cOHTqIHdT39vbGvXv34O/vL/ChqSdPnmDUqFGwsLCAs7OztBQw7OzshAY/9u7di/Xr1wvsR29vby9xkOT27duQl5fHjRs3BGbSRkVFYciQITAwMKiUAbfOnTvj7NmzQvHu37+f6avu7u7o2bOn1EGdsm3/9OkTJk6ciLlz52Lv3r2sY5KWm8q6piw28bPpi1X5M872d4i1tbXQc/3TnDlzBi4uLjA1Na2y363Pnj3DX3/9hZ49e1Z63aK8e/cOLi4uGDVqFKvy/Bz07NmT+gUhhBBCCCG/udDQUDx69Ij5XlNTEyYmJjh06JDQ+y1NmjQR+F5FRUVo786srCzEx8cjKysLRUVFkJOTQ15eHgCgf//+uHLlCtzc3GBjYwM7Ozt06tRJYIWx6OhoyMvLIykpSWA1Ky6Xi+LiYkRHR6Ndu3Yi28Lj8TBt2jTo6+sDKBnknTRpEpYsWYLY2Fih2bVJSUnMHrHlpa+vDzMzM6HjkZGRCA8Ph52dncDfTS1atMClS5cwb948KCsr49OnT+BwODAyMhK43tramhms5TM3N2cVE3/WLh//fafPnz8zx3JycvDhwwfmOXG5XOY5ldWoUSO0a9cO58+fZwZrAwMD0b59e9SpUwcA4OzsjHPnzmHo0KFo06YN7Ozs0LFjR4FY3r17B6Bk8LV0Tvh73r59+1bkQCJ/YDI7O5tV+/mTA8pOduQ///j4eGawtmyfrlGjBoqLi5Gfn89qsJa/n3LDhg0FjhsbGzODtWzazX+PUVI8MTExACDUV0orb47LosFaQgghhLDWqVMn7N69Gzk5OVBVVQUAvHjxAjweT+ILF6DkRWnZF6FKSkpYvny5TGVE6d69O1JSUrBr1y7Mnj1b6HxBQQFOnDiB6dOnC61u0aZNG/j4+Ai9OCsPKysrZGRkICMjg9UM0+zsbJw4cQILFiwQWvLYzMwMY8eOxeHDhzFmzBjm04KVSdZ4xTE0NMSKFSswdOhQgaWFfhei4mfTFy9evAglJSX07t1bZL0pKSkICgpCSkoKtLW10b17d+jq6iI/Px/bt2/HqFGjmE+pvnr1Ck+fPoWXlxcAoLCwEIGBgfj48SMsLS1haGiIoKAgTJw4EQBQXFyMO3fuICoqCkpKSrCzs2P+0CguLsa///6LYcOG4dq1a7CwsIC1tbXYeNiQFo80ku4tqS2nT5/Gs2fPwOPxkJubi969e0vMnbi2y3IP/qeUnzx5gufPn0NJSQm2trYCbwYUFhbiypUr+PTpk8z9/eTJk3j//j2ys7OxY8cO/PXXX+WKT5KKPi9CCCGEEEJI1enTpw/WrFnDqqyk9wIKCgowf/58XL9+HXp6eqhduzYUFRWRmJgILS0tACUDmxcuXEBwcDDu3LmDw4cPY8OGDXB2dsaGDRugoKCAoqIi8Hg8rF69WugeDRo0QFFRkcj7165dm7lHafwBuk+fPgkN1r58+RIbN25k1XZxunfvjrlz5wodP3XqFOTl5XHs2DEcO3ZM4FxOTg6uXbsGd3d3FBYWQkFBQWiLL1FbHrHdxrJmzZoC3/PrLi4uBpfLxfLly3HhwgXUrl0b2traUFJSQnx8vMS/yQcOHIjZs2cjNjYW2traePDgATZs2MCc19TUxKlTp3Dnzh3cvn0bp0+fxpYtW9CxY0d4e3ujRo0azLPbsmWLUP0NGjRAcXGxyHvzB0Jfv36NNm3aSG1/YWEhgJLVnkrjf19QUMAc489mLq/CwkJwOByhyRqlt9CTpd2S4ikdtzjlzXFZNFhLyB+Ox+Nh06ZNuHv3LjIzMwXODRo0iJbEI4TIpF69ejAzM0NQUBA8PDwAlMyqdXV1xZcvXyRe6+Xlhfnz5+Pjx4/o3Lkz2rVrJ7RXLJsyovB4PCxbtgwDBgyAh4eH0DUxMTHIyckRuzSug4OD1HuwERYWBj09PYGBz/v37wt96hUomaUZERGB/Px82Nvbi6zP3t4eW7duRXx8vMDespVF1nglLUVubW0NZWVlvHr1qkoHa8sbnzRl42fTF1VVVcW+qE9LS4Obmxu6d+8OY2NjvH37Fjt37oS/vz+UlZWxb98+uLm5MQOOUVFROH36NDNYO3HiRCQnJ6NPnz64cuUK4uPjkZSUxAy2zZ8/H9HR0ejTpw/S0tIwZMgQbNiwgVkKfN++fXj//j3k5eXRsGFDifGwGbCVFo8k0u4tqS2GhoYoKChAnTp1ULduXeTn50vNXdm2S8tX2XsAwMaNGxEYGIjhw4cjJycHY8aMwZw5c5jfe/y9YPv06SP0qXhp6tevD1VVVWhrazM/17LGVxXPi/+p+d8RP+7fNX6+6mjH754zQgghhJD/ZUeOHMG1a9fg4+PDbEkFQGC1L6BkwMzZ2RnOzs7g8XgICAjA3Llz0aFDB3h4eEBPTw8cDgeBgYEyDaQ1a9YMABAXFyfw9zJ/X1dRA53du3dH9+7dZWonG7m5uQgICMC4ceMwc+ZMofNDhw7F2bNn4e7uDg0NDRQWFiIrK0sgxtKzYGWVnJws8P33798BlCxdfeHCBZw5cwYbNmyAu7s7U2bMmDFISkoSW2f37t1Rq1YtXL58GXXr1kXNmjXRtWtXgTKKioro1q0bunXrBqBk9bYpU6bg1KlT8PLygp6eHoCSgWz+Er1stGzZEjzaMNwAAQAASURBVAYGBjh58iSGDBkiMBDKV1BQgLS0NOjr6zPvKyQlJaFevXpMGf5MbX4clUFTUxM8Hg+pqanMhxKAkm27+Ni0+9OnT1LvJa5dpZU3x2XRYC0hf7iQkBD4+flhypQpQmvMV8Ub/4SQP5+HhwcuXrwIDw8PFBYW4urVqzh58iR8fHwkXufq6oomTZrg9OnTOHz4MFasWIF69eph1KhRGD58ODgcDqsy4piammLgwIFYtWoVfH19Bc7xl20p/aIpKSkJR48eZb7n7ynCVulBQy6Xi/fv3+PBgwdCn6STk5MT+0lYflzi9gDhv+Dj7xVSEZURryQcDgc6OjoiB1LZxMRXu3ZtjBkzRuw15Y1PmrLxs+mLkv7A/PjxI378+IFp06YxfzwEBweDy+VKjSUqKgr//fcfgoODmaVyJk+eLLAcVdu2bTF16lRmMPL79++4cuUKevToweTHxMQEs2bNAlAy+7Qq45FEWi4ktcXe3h7Kyspo06YNbGxshD54Vpaotst6j48fP+LgwYM4d+4c8+ZDw4YNsXbtWri5uSEmJgYhISG4desW88fa0qVLcf/+fVb5cHBwgI6ODszMzJhZ2bLEJ015nxd/eaffWXh4eHWHUCn+lHYQQgghhJCq9eHDB9SsWVNgoPbp06eIiopCy5YtAQD//vsvlJSUMGXKFAAlf/v26NEDCxcuREZGBoCSfV337duHa9euwdXVlakrOTkZRUVFzLK7ZbVs2RKGhobw9fVFx44doaioCB6PhzNnzkBDQ0PqdlmVib/vbun4S3N1dcXy5cvx4cMHZmnjBw8eMH/Xp6Sk4MaNG+W+/40bNzB27FjmfSv+crwtW7bEyZMnweFw0KtXL6Z8dHQ0nj59Kja3QMlMUQ8PDwQGBkJPTw+urq4Cg6b79u1Damoq5s+fzxzr2LEj1NXVBZ7thg0bcOXKFYwYMYIpl5aWhqysLLHL83I4HMybNw+zZs3C7NmzsW7dOoGB7dTUVCxYsADPnz/HtWvX4ODggI0bN+Ly5cuYMGECU+7q1atQUlJCmzZtWC+pLI2lpSWAknEP/geqMzMzcefOHaZMedtdlr29PTZt2gR/f3+BSW/Pnz+HhoYGjI2NK+1eNFhLyB8uISEB/fv3x8iRI6s7FELIH6J3795Yv349vn79irdv36JBgwZCSwuL07RpU2YZ2W/fvsHf3x8bN24Eh8PB8OHDWZcRZ+rUqejZsycCAwMFltrhDxAlJiYyn4rjcrnM/hEJCQl49+6dTIO18vLyzHIuUVFRePToEQIDA2FoaChQTtTetnz8JYO+fv0qcgbx169fAQC1atUCUPJiWdTgGv9Y2SV8KjteSYqKipCamip24FkUUTP5pM3yKm980oiKvyJ9sXnz5nB2dkb37t3Rtm1b2NnZoVevXtDV1ZU64BgfHw8NDQ2BF/Q2NjaIjIxkvnd1dcWdO3cQFBSEnJwcxMbGCi271LZtW1bxSMMmHkmk3ZtNW2RVuu2y3oO/f1JgYCACAwMBAD9+/EBycjKSk5OZN0RKf6q2RYsWrAdrRanMHJT3eZmYmLBe4utXU1xcjPDwcFhYWFTJhzl+lupoR05ODqKjo3/KvQghhBBCSOWysbGBn58fZs+ejZYtWyI2Nhbx8fHw8PDAtWvXEBgYiAYNGmDx4sV49+4dLCwsUFRUhJs3b0JTU5OZjWljYwM3NzcsXLgQT58+RePGjfHt2zdcuHABLVq0gI+Pj8gPz8vJyWHVqlUYP348Bg0aBFtbWzx//hzPnj3D+vXrRS4rXFXOnDkDc3NzoWWX+Xr27InVq1fDz88P06dPh5GRERYsWIA3b95AQ0MDFy9eRPv27XH9+nWZ7svj8QCUzF728vJCx44d8fnzZ5w4cQJ9+vRB3bp1YWNjg71792L69Omws7NDQkICXr9+jYEDB+L48eO4dOmS2K3FBgwYAF9fX3z48AGLFy8WOGdiYoIpU6YgLi4O1tbW4PF4uHfvHoqKiuDi4gKgZGLDyJEjsX79ekRGRsLMzAypqam4dOkSDAwMcPToUbH7xDo7O+P79+/4559/0LlzZ9ja2kJTUxNfv37Fo0ePoKmpiR07dkBbWxva2toYOnQotm7dii9fvsDIyAgvX75EYGAgFi1ahNq1a1faYK29vT2aN2+O5cuX4+3bt1BVVWW2Qfrvv//A4/FYtZuNZs2awdPTE9u3b0d8fDyMjIwQERGBoKAgrFu3DsbGxhXKcWk0WEvIH87Y2BivXr2q7jAIIX8QDQ0NdOjQAZcvX8abN2/g5uZWrnr09PQwbtw4REZG4sGDByIHv9iUKU1NTQ1z587F+vXrsWPHDua4kZER9PX1ERQUxHwCr06dOswL3WvXrgns+8GGra0tM2iYn58PNzc3nDp1CnPmzGFdR9OmTaGmpoZbt26JHKy9d+8edHV1mcFwbW1tgWVd+BISEqCqqipxoKUy4pXk7t27yM/PR7t27Vhf4+jo+Mssxy8tfln7ory8PNavX49v374hNDQUd+/ehbe3N44ePSo0QA4I7oPC4/GE/hDm/wEIlHyCtU+fPrC0tESHDh1Qr149vHv3Drm5uQLXlF4WWlI8/Nmj4kiLRxpJ9zYwMGDVFklE7SFTuu1s81U6Xnl5eaEljlasWMF8Urxs+/n785SHrPFJU97nVVWz1n8m/rP73f3MdvwJ+SKEEEII+Z04ODigSZMmUsupq6vDwcFBaFlVIyMjZislV1dX8Hg83L17F0+ePIGlpSUWLlyIlJQU5Ofn48aNG1izZg0aNmyIa9eu4dmzZ1BWVkanTp3Qv39/gaVpN2zYACcnJ4SEhODBgweoXbs25s2bBxcXF4mrnLVv3x7nz5/HmTNnEBsbC2NjY8yePRvW1tblzJDsvn//Dg0NDbGzaoGSD8F7eXkhOTkZSkpKOHbsGA4ePIioqCjo6+tj48aNuHv3Lq5fvw4OhwMVFRU4ODgI7cdbs2ZNZrUkoGSQ1sHBATNnzkRCQgKCg4OZvYSHDBkCoOSZ79y5E9evX8ejR4/QrFkz7N+/H3l5ecjMzMTNmzcxfvx4ODg4CH2g2tjYGC1atACPxxPacsrJyQmnT5/G5cuX8erVK8jLy6NNmzZYt26dwPsOixYtgo2NDW7evInQ0FBoaGhg8uTJcHd3lzqIOGLECHTv3h2XLl1CTEwMvn//jjp16uDvv/9G165dBT5kvHTpUrRr1w63b9/Gw4cPoaenh6NHjzLvs4jLqaGhIRwcHJhYWrduDQ0NDbE5l5eXx6FDh3Do0CFERUVBU1MTy5cvZ94b4E9okNZutvGsWrUKtra2uHPnDl6+fIk6derg2LFjAn28Ijnmo8FaQv5wlpaWOHHiBHbs2AEbGxuBfQf09PRY731GCCGleXh4YO/evXj//j2WLVsmtXxqaiquXr0KFxcXgf1RCwoKEBsbC2tra1Zl2HB3d4efnx/279/PHJOTk8PEiROxfv16ODo6Ciwlmp+fj//++4/1iydRlJWVsWLFCowdOxbdu3dnBoSlUVJSgpeXF/bu3QtHR0eBF94RERE4dOgQZs+ezcyY7dy5M06cOIFRo0YxLyYzMzNx+PBh9OzZs8rjFefDhw9Ys2YNPD09K3Ufkp+lbPyV0RefPn2K9+/fw9PTE+7u7nB3d8fIkSNx7949jBkzBvLy8khNTWXKP378mPm6QYMGyMjIwOfPn5kBw4cPHwqUzczMhLe3N+Tk5FBQUICjR49K/NSypHikDdZKi6ciuWjUqJHUtnA4HGawUVVVVWLuRGGTr9L3MDc3B4/Hg7W1NUxNTQGU7GXz/PlzaGlpwcjICDk5OXj//j2zpYQse9ZWND5pKvq8CCGEEEIIIVVn7969rMo1atQIBw4cEDrer18/9OvXj/nezc1N6EP0hoaG2LRpE/N9mzZt0KZNG4n343A46N27N7NViyxMTU2xZMkSma+rLNra2gLvAYkze/Zs5msdHR3MmzdP4Py5c+egpaUFeXl56OjoiMy/gYGBwPH69esz37do0UJs/rp27Sq036yamhrWrVvHfC/qftnZ2YiLixOIvTQLCwtYWFiIPFdaly5d0KVLF6nlRDEwMGC1Eh2Hw0HPnj3Fvj8lLqc9evRAjx49mO/L9qWyOQdK9q2dMWOGUF2llwQHJLebbTwcDgcuLi7MbGVxKpJjgAZrCfnjnT59Gjdu3MCNGzewfft2gXOjR48WWNOeEELY6tChAxYvXgxra2tmKV9JNDQ0EBISgp07d8LOzg5aWlrIzs7Gw4cPUbt2bUyaNIlVGbaWLl2Kvn37ChwbMmQI0tPTMXbsWLRs2ZIZ0Hjy5Anq16+Pbdu2yZyH0uzs7ODq6opFixbh/PnzzD4it27dYpYzLq1hw4YYM2YMJk6ciJSUFHh6esLe3h516tRBYmIiHjx4AC8vLwwdOpS5Zvz48QgPD4ezszPs7OwgJyeHR48eoVGjRli4cOFPiRcA7ty5g5SUFHC5XCQmJuL+/fvo1asXFi1aJFMM5cEmPlFl+vfvzwxKS4ufbV+8ePEilJSURP4xVqtWLWzatAlhYWEwMjJCUlISIiMjsWjRIigoKMDOzg7Lly9Hr1698O7dOygpKQkMFtra2mLixIno3bs3oqKiBJa/Njc3R3FxMZYsWQIdHR08f/4clpaW8Pf3x40bN5ilrNjGI420eADg0qVLkJOTE/nHi6R716hRQ2pb9PX1cfjwYSQmJmL06NEScycuflnvMXXqVIwdOxbu7u6Qk5ODv78/+vfvD6DkjYhOnTphwoQJ6NGjB2JjY5GRkSHTbOOKxietPmnPixBCCCGEEEL+V2VlZWHDhg2wt7dnBuUKCwtx584dqR9m/tkOHToEeXl5uLu7V3copIpxeOV9V4FUuZycHERERMDc3ByqqqpSyxcXF+PFixewsrKq0uWsKvs+mfdryXyNhn16he8L/Lo5k/XZS1JUVCRyOTygZKaZpP0NCSGktHPnzsHKyopZrjc4OBgGBgZo0aIFgJIBMBUVFdja2jLnFRQU0KlTJ6aO6OhohIeHIzMzE2pqajA2Nkbr1q0F7iOtTNl6y8bFFxgYiE+fPgl9+i81NRWhoaFITk5GzZo10aJFC5ibm8ucCyMjI6HY09LS4Ofnhy5dusDY2Bjnzp3D9+/fRdZhYGAg8OnX+Ph4PH78GBs3boSDgwPmzp0LAwMDkde+fPkSr1+/Bo/Hg5mZGaytrQV+n4vKUWXFW7ZM7dq1YW1tzcwwZEtcTKWJaoes8fE5OTmhSZMmMsUvrS8GBQVBUVERTk5OImNKTU3FvXv3kJqaitq1a6NDhw7M/sn5+fkICgrC9+/fYW1tDU1NTdy/fx+DBw8GUDKL9+bNm/j27RvatGmDd+/eYffu3cz+OXFxcXjw4AEUFRXRqVMn1KpVCxcvXoSGhgZ69uyJvXv3ws3NTaAPSYpHGmnxXLhwAffv3xf49DbbXEhrS0JCAm7fvo1GjRqhY8eOUnMnqu2y3gMo2bv25cuXKCwshJWVFZo3b87UV1RUhNu3b+Pz588wNzdH3bp1cffuXQwbNoxVPq9cuQJ9fX3m0+3lia8iz6s0/utOU1NTqKurs4r/V/OzXtNXtepoR2X+3UEIIYQQQsjvYsqUKXjw4AEGDhwILS0t3LhxA9HR0Th69GiFVx+rDIGBgXj48CH8/PywfPlyDBo0qLpDIlWMBmt/YTRYKx4N1squoKAAX758AZfLhaGhITODihBSdbKysgBA5D6iXC4XWVlZUFZWhrKyMgAw+xOW3muRr6CgQOoeduLKlK03KysLcnJyQr9f+DGV3heitLy8PInLrEqSlZUlMLNLTk5OZF7KlitNRUVF5O8uSXFlZWVBSUlJ6Lri4mJkZ2dDXV0dHA5HZI4qK97SZeTl5QX28xBl2bJleP36Nc6ePSswACvpXvxnJq0d4uITlSNR92UTP8CuvxLxeDwejh07BgcHBxgZGQEA/v77b3z+/Bl79uz5JeO5d+8enj9/jmnTprGqs7CwEPn5+RL3WS6Ly+WiqKjol30NUzq+zMxM1KxZE/Ly8gJf/wyy9h8arP110GAtIYQQQgghP0dBQQH8/f3x6NEj5Ofno2HDhhgwYADq169f3aEBAHbt2oW3b9+iZ8+eUpffJX8GWgaZkP8BJ06cwObNm5mBI1VVVcyZM0dgaU1CSOUbOnQooqOjcefOHaHN6oOCgjB9+nSB5cjnz58PVVVVrF+/HkDJwNvmzZsRGBiI3NxcFBUVoW7duhg1ahQzg4xNmbL1Dh06FJ8+fcLVq1cF9heNiYmBq6sroqKimGOvX7/Gtm3bEBYWhry8PKiqqqJ9+/aYNWuW0ExWNrngz/Ln8XhQUVGBo6MjFi9ezORn6NChiIyMFFnH9OnTMXnyZCYub29vhIWFIT8/HzVr1oSDgwOmT58uEFfv3r0xfvx4odluz58/x9ChQ/H48WNoaGgwOZo1axaOHDmCc+fOITU1VSBeBQUFNGjQAL6+vjLFW7rtXC4XysrKaNOmDcaPHy+wdy7f5MmT4e7ujhEjRqBFixaYNWsWlJSUJN7rzZs3UFBQEPms2cTXo0cPJrdlsY2f3xcvX76MHz9+gMvlQk1NDRYWFgLLCCkoKIjcV4T8fxwOB5GRkTh06BDc3NyQlJSEoKAg7Nu3j9X1BQUF4HA4AvvUi/Pt2zccOXJE7Hn+8xIVz+7duwXKDhw4kFV8QMmnhL29vXHr1i1W5e/evYuZM2dCU1MTt2/fllpelhxUBn58ampqcHZ2xsGDB+Hh4QEtLS3ma11d3Qr3/4o8L7b9hxBCCCGEEEL+dEpKSvD09ISnp2d1hyKSuPdoyJ+LBmsJ+cO9f/8eW7duxYoVK2BlZQUOh4OXL19i1apVQkv6EUIqn56eHi5duoRx48YJHL906ZLYJW751q9fjzdv3uDMmTMwNDREcXExbty4gdmzZ6NRo0aws7NjVUYUdXV1/PPPP9i8ebPY+z958gReXl7w9PTE0qVLoa+vj4SEBHh7e2PIkCG4ePEi6tSpwzoXU6dOZV5s8ng8xMXFYeHChZg7d67A4EPpQVlRHj9+jDFjxmDAgAFYtmwZDAwM8OXLF/j4+KB///44deoUzMzMWMdVmrKyMpo0aQJlZWX06NEDXbp0Yc4lJyfjzJkzMsdbuu0FBQX4+PEjzpw5gzFjxmD16tXw8PAQKGtgYICAgADcunULCgoKArOr2NyrrPJcU574+X3x0KFDiI6OBpfLxevXr3HixAk0b94cJiYmAPBbz3r7mVavXo2HDx8iOjoaDRs2xIwZM4Q+9CHp2vbt26Nnz55Sy/L7vDj851U2nsLCQqSmpjLlHB0dWcVWXufOnUOPHj2wbt06VuVlyUFl4Me3YMEC3LlzB4sXL4aamhqzj22DBg1gaGhY4f5f3uclS/8hhBBCCCGEEELIz0WDtYT84V6+fIl+/frB1dWVOWZoaIiPHz8iLCyMBmsJqWKOjo7w9/cXGKxNT09HWFiY1H0Hnz17Bnd3dxgaGgIoeRO+Z8+esLOzg6am5v9j76yjo7q6PvzMRCACCQGCS5BAgAR39xQLFCjuWoIUSqFQXNpiBVooUmiRAi1Q3K1QoGiRBJcEiYe428z3R765byaZzNyJEOQ8a7FWcufIb++zZ8jcfc8+stvoYtSoUaxcuZLr16/ToEEDnW0WLVpEixYtmDNnjnStUqVKrF69mlGjRnH79m2jkrVpUSgUVKhQgfHjxzNq1ChiY2Nll1+cN28ebdq0YdasWdK1cuXK8d133+Hv78+iRYvYvn17lnTZ2Njg5ubGr7/+StWqVXFzc9N6vUqVKkbrTYu5uTkVK1ZkxowZWFlZsWjRItq2bZuh9Ki9vf07eR6JPv2aWHRycpLOAO7RowcTJ06UYjE2NlbnGerpSV/aWq1WExUVhbW1tVQaOjExkcTExAxldBMTEzE3Nyc5OZn4+Hidr5uammY4s11zLq1KpUKhUGgl1bJTAtyQnsxQKBQ0btyY2rVrZzq3LltiYmJ4+PAhderUITY2FgsLC72+s7GxoXXr1pnanpiYiEqlQqlU0rhxYxo3bkxMTAw7d+4kPj4+w3shOTkZpVKZwb/p/WEMMTExhIWFUbZsWaKiorTeL3J8YMx7NSvrlVafUqnEzc1NKn2cnJzMzJkzadGiBc7OziQmJmbory/20vtT8xllCE381K1bV7InOjraqLLTAoFAIBAIBAKBQCAQCN4Ouu+iCASCD4bk5GSdJQAtLS1JSEjIA0UCwcdFvXr1ePPmDffv35euHTt2jKZNm0pn1WaGk5MTu3fv5saNG1rnjqZNwsppo4tChQoxfvx4FixYQHJycobX/fz8ePjwYYbywZB6fuvmzZvp1KmT3jnkkJCQgEKhwNTUVOtaZGRkhn9qtZrnz5/z7NkzhgwZonO8YcOGcePGDa0dfzmJsXr1MXz4cKKiorh69WquaM2uPkOk1y8nFmfPnp3pzki1Ws2yZcto1KgR7du3p2HDhixZsgSVSkVUVBT169fn2bNnUvuDBw/Sq1cv6fdTp07RokULWrVqRa9evdiyZYtWjP7777906tSJ1q1b06BBA4YPH05ISAiQen5q/fr1+eOPP6hXrx6bN2/Wq0cOhvTow9Dc+mxZtGgRDx48YNWqVSxbtsyg73TZbuwcAI8ePaJfv360bt2ali1b8vnnnxMUFCTNefr0aZo3b07btm3p1q2bVrl1Q8yfP5979+7x119/SQ++GKvPENlZr/T6EhISqF+/Pg8ePJDaXLlyhVatWklreuPGDSBz/xvyZ27aIxAIBAKBQCAQCAQCgeDtIpK1AsEHTo0aNdi/fz8PHz6Urnl5ebFz505cXFzyUJlA8HFgZmZG586dOXDggHTt0KFDdOvWzWCy7JtvvsHFxYWhQ4fSqFEjPv/8c3bt2iWdPy23jS7UajUDBw5EoVCwdevWDK/7+fkBUL58eelaSkqKVrLP0BzpSZs0DA8P59atW6xcuZJOnTpp7bTbuHEjjRo1yvAvPDwcX19fABwcHHTO4eDggFqtxsfHxyhtuaVXH9bW1tjb20s2GatJ7jpkVZ8h0uuXE4srVqxgwYIFOse7f/8+27Zt49ixY1y8eJHDhw9z+/btTM/cTUtkZCTTp0/H3d2df//9l9WrV7Nr1y6tpPrKlSvp27cvly9f5tKlS0RHR0tnrmoeavr77785cOAAAwYMyHU9+jA0tz5bvvvuO2xtbfn666+ZO3euwbl02W7sHPHx8YwbN45GjRpx8eJFzp8/j62tLbNnzwYgKiqK6dOnM3nyZC5evMi2bdu4ePGiLF8ALF26lJo1a9K/f3/++OOPHPdBdtdLl770XLp0iSNHjvDff//RsmVLpk+fTkpKik7/G/JnbtmjUqlISUl5b/8Bea7hfbVDIBAIBAKBQCAQCAR5iyiDLBB84Dg5OfHpp5/y6aefYmFhgYmJCVFRUfTr14+mTZvmtTyB4KPAzc2NsWPHMn36dPz9/fH29qZFixacOXNGbz8bGxuWL1/O7NmzuXHjBlevXmXdunWsWbOGrVu3UqlSJVltMsPU1JS5c+cyevRounTpovWaJhmZdgf+gwcPtHYylipVinPnzsn2w6ZNm/j111+B1BvR5ubmDBgwgIkTJ2q1S3u2bXo0iY2kpCSdr2d2PSvkhF5DqFQqLCwsZLdfv34969ev17pWtmxZTp8+nWmf7OgzRFr92YlFgBIlSmBmZsaGDRtwdXXF2dlZSnxFRkbq7evp6UlSUpIUn6VKlaJLly4cPnxYarNnzx5Js1qtplatWnh7e2uN4+bmJj2goE+PIeTo0YehueXYYixpbTd2Dg8PD/z9/enfv7+0Vr169aJ///7ExMTg4eFBQkKCVL7X1tYWNzc3du7cmWW9OemD7K6XHAYOHCiVIO7Xrx/bt2/Hz8+PMmXKANr+v379ul5/WllZ5Yo9aXdfv694enrmtYQc4UOxQyAQCAQCgUAgEAgE8hDJWoHgI2Dy5Mn06tWLR48ekZKSQpUqVTLdlSYQCHIeFxcXbG1tuXjxIg8ePOCTTz4x6sxGGxsb2rVrR7t27fjyyy/p378/mzdv1ionK6eNLurVq0ebNm347rvvcHd3l66XK1cOU1NTHj58KCUQatSogYeHB5Ba0vSHH34wwgvg7u4uJQ3v379Pnz59aNu2rcFy0GnRfHY9efKEokWLZnj9+fPnKJVKqV3+/PmJiYnJ0C4yMhKFQqE3UZoTevXh5+fHmzdvqFixouw+EyZMYOzYsVrX5JwBmxtkpj+rsVi4cGH++usvdu3axezZs/H396dHjx5MmzbNoJawsDAKFiyoddan5hxnDRs3buSvv/5CqVSSL18+3rx5Q5UqVbTaFCtWTJYeQ+9fOXr0YWhuObYYS1rbQZ6/NLx58waAPn36aF0vVaoUb968ISwsDGtray1/GCrVboic9EF210sORYoUkX62tbUFUs8v1yRr0/rfkD8NJWuzak+lSpXe2zNtU1JS8PT0xNnZWcvu9428sCM2NpYnT568lbkEAoFAIBAIBAKBfAICAnj06BGtWrXK8Nq///5LqVKlKFeuHBEREdy4cYMWLVpkuF/h4+PDixcvMDU1xcHBIcN3f7lzCHIfkawVCD4CIiIiMDExoX379nh7e3P27FkaN25M9erV81qaQPDR4ObmxqlTp7h79y6LFy/O8jgWFhZUrFhR705DOW3SMn36dFxdXWnYsKF0zcbGhlatWrF+/Xrat2+PqakpCoVCSlRm97zT6tWrM3DgQGbMmMGhQ4dkJ0CLFy9OvXr1WL9+PU2aNNFKVKrVajZv3kzbtm0pUKAAAFWqVOH69euMGTNGa5zLly9TpUoVnWd656Refaxdu5ayZctSp04d2X2USqXs0qy5jRz9xsSiWq2mSJEizJw5E0j9QjFs2DDKly9Pjx49ALTKdQYGBko/FypUiMjISJKSkqQ1ffHihfT69evXWbVqFQcPHqRy5coALFiwgJcvX2ppSB9PmenRdZZzWgzpyY4vHB0dZdmiQZPwycx3GtLaLtdfGkqWLIlCoeD48eNanxGaMf38/IiKiiIhIUF63Zjy3+kxVp8hsrteckh73qwmGZv2gZO0/jfkT0Nk1R6lUvleJzohNd7fdxvg7drxIfhLIBAIBAKBQCD4ELl27RoLFy7k5s2bGV6bO3cuffv2ZcSIEXh7e+Pu7s6VK1ews7MD4NWrV8yYMQNPT08cHR1JTEzEy8uLtm3b8u2330oPAcudQ5D7iDNrBYIPnOjoaLp3787ly5eJiYlh4MCBnD17lqFDh+bImY4CgUAe3bp149y5cyQlJVG7dm2D7YODg2nUqBGrV6/m8ePHBAcH8+LFC7Zu3cqJEydwc3OT1UYORYsWZcKECfz0009a12fPnk1kZCRDhw7lwoULvHjxgrt377J27VoWLFhAmzZtsuQLDRMnTiQpKYlVq1ZpXY+KisLHxyfDv+DgYADmzZvHkydPGD9+PLdu3cLf35///vuPcePG4e/vLyW4AEaPHs3169dZtGgRHh4e3L9/n9WrV/Pnn38yefLkt6IXUj+LAwIC8PPz4+bNm0yZMoVjx47x/fffo1Tm7p9jcvTpahMbGytbv9xYjI2NJS4uTqfOffv20atXL548eSKVs1YqleTPnx8rKyuKFCnC0aNHiY2N5fbt25w6dUrq6+Ligrm5OVu2bCEpKYl79+5pvR4XF4epqSlmZmZER0ezb98+rl+/TlhYWKZ+06fHEIb0aDRlxRdybDE3N+fVq1eEh4cb9J0ujJ3D2dmZihUrsmzZMqKiooiOjmb58uUMHz5c8oeVlRXr1q0jMjKS27dvZ6vEsLH6DJHd9ZLD77//TmBgIHFxcWzevJlq1apRvHhxnW0N+TMn7BEIBAKBQCAQCAQCwYdJVFQUQ4YMwdbWlkuXLrF3714OHTrEkSNHePToETNmzMhriQIdvBtbMwQCQa7xzz//UKVKFXr37s3hw4epXLkyW7ZsYfny5Zw5c4ahQ4fmtUSB4IPFyspK2tVUokQJatWqpZWozZ8/v9YOTQsLCykRVLRoUTZt2sSWLVuYOHEikZGRWFtbU7FiRTZu3EiTJk0AZLVJO256XRoGDhzIkSNHSExMlK4VL16cffv28euvv/LDDz8QHByMlZUVNWrU4Mcff6Rx48ZG+SL9blRLS0vmzJnD9OnT6datG05OTlhZWbFnzx7pPMq01KpVi02bNlG5cmX27t3Lxo0bmTFjBi9evKBkyZK0bduWhQsXapUbdXZ2ZufOnaxfv54JEyagVqupUqUKmzZtolGjRjp9n9N6rays2L17N7t370ahUFCoUCHq1q3LX3/9RYUKFbLlw/ToskOOPl1tFixYQKdOnWTplxuvs2fPxsrKigULFmTQ8+mnnxIUFMSUKVMICQnBzs6Orl278umnnwKwcOFCVq5cyf79+6lXrx6jRo1i8+bNABQoUICVK1eyevVqtm3bRr169RgyZIh05nDz5s359NNPGTJkCGZmZri5ubF8+XLGjx/Pl19+yYoVKyhQoIDWrmVDevRhSA+kPqGanJyss5y4obkN2dK3b1+2bdvGvXv3+PHHH/X6TqM3re1y/JV+jl9++YUVK1bQo0cPkpKSqFWrFosWLQJS4/Cnn35ixYoV7Nmzh6pVqzJq1Ci2bdtm0JcaLC0tpfjPir7cXK/0+hQKheTTlJQUChQoQN++fZk0aRI+Pj5UrlxZa5z0/jcxMdHrT0PIsUcgEAgEAoFAIBAIBB8mu3fvJjo6mm+//ZaCBQtK18uXL8/SpUu5evUqKSkposrOO4ZCnd06hoJcIzY2locPH+Lk5ISlpaXB9ikpKdy5c4datWrl6hstp+eJvGxrdJ+CTcOzPS+8uz4zdu31sX37dsLCwpg4cSLffPMNlStXZujQoezcuZPAwECjd5YJBALBu0b//v2pXLky8+fPz2spgjxErVajVqulncpbtmzh6NGjOhPV74IeLy8vtm7dKuL2HeFDWy9j3g+avzsdHR2lEvLvG2/rb/rcJi/syMnvHQKBQCAQCAQCgSDnOHjwIHPnzmX58uUZXps3bx7Dhg1jxIgR3Llzhz59+khlkEePHo2FhQWrV6/OsTkEuY/YWSsQfOAULlyYO3fuEBsby4ULF6SdtJqdaAKBLjZu3MibN2+YPn16hpuFr1+/5rfffqNJkya0a9cOgD179mBubq5VdjcwMJBTp07h7++PmZkZDg4OtGvXDmtra9lt0o+7ceNG4uPjmThxopamoKAg1q9fz5w5c7Su3759m6tXrxIREYGdnR1NmjShRo0aRvsiICBA+l2pVGJvb0+zZs2oVq1apu3S0rp1a5o3by79fuvWLa5du0ZERASFCxemefPmVK1aVavPqlWraNq0KfXr19e6rvH/tGnTyJ8/v04f5ZTetG1MTEwoXLgw9erVo169elLblJQUYmJidDuP1B1mu3btynSuWbNmoVQqDdqRmT4nJycGDBjA119/TevWrXFxcaFQoUIoFApZ+jXIidfcQo4P39cEyttCrVbj6upKmzZtmDBhAgEBAfzxxx906tQpx+e6ffs2Z86cyXAOsgaFQoG1tbWkZ/jw4WzatIkDBw4wYMAAqd358+dp1qxZjuvLSzw8PDh//jwTJ04kOTmZb7/9lpEjR+r9eyO341/O+GnXK7P4MbRe0dHR7Nixg4SEBMaNGyfZbm9vL8sPb9segUAgEAgEAoFAIBC8+yQmJrJx48YM1yMiIjLtExoamuHe182bN7WOCXJ2dqZYsWJZnkOQ84hkrUDwgdOiRQuWLFlCkyZNaNiwIZUrV+b06dPs27eP/fv357U8wTvK0aNHef78OU2bNqVly5Zar+3du5fdu3eTL18+KVl78eJFLC0tpUTbhQsXmDRpEp07d8bR0ZH4+Hi2b9/OmjVr2L17N3Z2drLapB/36NGjPH78GAcHB7p27SppCg8PZ8eOHVKyNj4+ni+//JIrV67QsWNHihcvzuPHj1mzZg3du3dn/vz5KBQK2b4oUqQIDRs2BFJvlD99+pQff/yRmTNn0r9/f6mdnZ1dhuQqpJamTavr6tWrkq7nz5+zdu1aXF1dWbRokVQKc9++fRQpUiTDeIGBgezYsYMvvviC/Pnz6/RRTulNO1ZCQgJPnz7ll19+wcnJiR9//BE7OztevnyZIXmeFnNzc1JSUjKdS7MOuuyQoy85OZlx48bh7e3NggULMDMz4+DBg+TPn1+WfpAXr7mJHB/u27cvVzW8K5w5c4ZSpUrh5ORkVD+FQsGqVatYtmwZHTp0oECBArRv315nQjWrc2i4efMmW7Zs4cKFCzpf16yXRk/79u1JTk6mUaNGWnoyO380u/ryEm9vbw4cOCDFc3JyssE+uR3/csc3FD+Gzov98ccfuXDhgvTEscb2lJQUduzYQY8ePXIkWZtT9ggEAoFAIBAIBAKB4N3H0tKS3bt3Z7jevn37TPsULFiQkJAQrWtHjhzhwYMHADx48IDly5fj6uqa5TkEOY9I1goEHzjW1tYcOnSI58+fSzsKixUrxm+//UaZMmXyWJ3gXaZ27docPHhQK1mrVqs5cuQINWvW1Nt3/fr1DBkyRKvM9ogRI1i5ciVBQUHY2dnJaqOLbt26sWTJElq3bp3prscVK1Zw9+5djhw5onVz3NPTk/79+1O7dm169Oghyw8AdevWZfTo0VrXqlWrxooVK+jXr5+UcKxfvz7jxo3LdJwlS5bg6enJ0aNHKV68uHR97NixfPbZZ6xfv57x48fL1pXbenWNFRQUxJgxY5g8eTJbt26lQoUKHDlyRO8Ybm5usuZKjzF9xo8fr9N3hvSDvHjNTeT48GNh37590nnAxuLk5CTrTM7szAFgb29PsWLFDK6ZRs+IESOoUaOG7GMHsqvvXcHU1FTn2cTpye34lzu+3PjJjOfPn+Pq6spnn30GINmekJCQ5TF18bbsEQgEAoFAIBAIBALB+0mNGjU4duwYycnJ0qaQefPmSa+3adMmj5QJ9CGStQLBR4CNjQ116tSRfndxceH69evs3buXXr165aEywbtMq1at+Omnn4iOjpaSov/99x9mZmaULVtWb9/k5OQMT3CZmpry1VdfGdUmM11v3ryRdoqmJyEhgd27d/PVV19l2MXk7OzMb7/9RqVKlfTOIYfq1asTHR1NZGQkNjY2BttHR0ezZ88e5s6dq5WoBShfvjyjRo1i06ZNjBkzBjMzs2zry67ezLC3t2fevHl89tlnPHjwQKu08vuALv1yYnH37t2Ym5vTvXt3neP6+vpy/Phx3rx5Q+HChenUqROlSpUiPj6epUuXMnbsWOzt7YHUMrpXrlyREtHx8fHs37+f169f4+LiQsWKFTly5IiU3EtMTOTkyZM8fvwYc3NzGjduLO041pSaHTZsGIcOHaJu3bo0atQoUz1yMKTHEPrm1mfL1q1b+e+//0hMTCQsLIwePXro9V1mthszR79+/QD4559/uH37Nubm5jRp0kTrgZT4+Hj27dvH69evqVq1Kmq1WpYfIPWc0GfPnhEREUFSUhLTpk3Lkj595OZ6AZw7dw5PT09MTEyoU6cOTZo0keWbtGWQ7ezs9K6lSqVi0aJFjB49mjNnzuDr60vdunVp164dp0+f5tatW5QtW5aePXtibm5u0KasjJcdP6Zf5ylTpki2Fy5cGEiN/R07duDj40PlypVxc3PDxMQk0zgG/XFpiOzGhUAgEAgEAoFAIBAI3k969+7Ntm3b+PXXXzNs5ggNDdV7tI4g7xDJWoHgI+DSpUscOHCAqKgoIHV35MOHD7XOzhMI0lO8eHGcnZ05ceKElNQ/dOgQ3bp149WrV3r7jho1iilTpuDt7U2bNm2oX78+NWrUQKlUGtVGF2q1mlmzZvHpp5/Ss2dPqlSpovX606dPiY+P11k+F9B5XmlW+OeffyhZsqRW4vP8+fO8efMmQ9upU6fy6NEjkpKSpPLE6WnUqBHLly/n1atXVKxYMUc0ZkevpaVlpmO5uLhgYWGBp6dnriZrs6rPEOn1y4nFYsWKSU8jpic0NFSKx8qVK/Po0SM+/fRTDh48iKWlJTt27KBv375SkurZs2ccOnRIStaOHDmShIQEevXqxbVr19i4cSPh4eFSUmXq1Kn4+fnRu3dvwsLCGD16NAsWLKBr164oFAp27NiBr68vtra21KxZU6+e9A8K6MKQHn0YmlufLdWrV0elUlGlShWcnJyk5FZmvtNluyF/pZ8DUndAXrp0ieHDh5OQkMCECRNwd3enT58+QOpnVUpKCj179uTZs2ecPXvWoB801KhRAxsbG8qUKUODBg2ypC8v12vGjBl4eHgwaNAgkpKSmDFjBt27d5fG1uebtOV/ra2t9a6lUqlkx44dPH/+nCZNmpA/f34mTJhAhw4dKFq0KGXLlmXt2rW8efOGCRMmGLQrK+Nlx4/p1zmt7Zpk7aJFi2jevDnFihVjzZo1XLt2jSVLlmQax4bi0hBZsUelUpGSkiJr/HcNje73Vb+GvLDjffeZQCAQCAQCgUAg0KZMmTIsWbKEr7/+mlu3btG0aVNMTEx4+vQpR48epV69ejRt2jSvZQrSIZK1AsEHzuvXrxk3bhzt27cnLi4OMzMzEhMTadasGYMGDcpreYJ3nG7dunHw4EF69eol7Qbbu3cva9eu1duvQ4cOHD58mL1793L06FGWL19OoUKFGDx4MKNHj0apVMpqkxkVKlRg0KBBLFiwgB07dmi9FhcXB0ChQoWka35+fmzatEn63dbWVu+Zf+lJmzRUqVR4eXnh6enJjz/+qNWuQIECOpNhSqVSempNc+M+PUWKFAEgIiJCtq7c1KsPhUKBnZ2d5GtjNWmws7PTW/Y5q/oMkV6/nFhMf3ZzWvz8/IiJiWHIkCEUK1YMgNatW2ea3E3Lw4cPuXHjBhcuXJBsnThxIuHh4VKb9u3bU6dOHWm3o5+fH6dPn6Zr166YmJgAqTunNTF97969XNWjD0O+0GdLvXr1MDc3x9nZmVq1ahEZGal3Ll22GzvHixcv2LlzJ4cPH6Zy5coAlChRgjlz5tC7d28eP37M9evX+eeffyR7oqKi+Oeff2T5o169etjZ2VGhQgVatWpltD5D5OZ6eXl5sW/fPo4fP06FChWA1C9848ePZ/To0bx69SpbvtFFx44dpXO1L126REpKCrNmzQIgJCSEO3fu5Mp42fVj+nXWVfr4k08+kZ5orlixImPGjGHmzJnSAzRp49hQXBr6DMyqPc+ePZNl77uMp6dnXkvIET4UOwQCgUAgEAgEgo+Z0KRoQpIjMVeYYW2SH0uTfFgoDVeL0lCiRIlM70c1adKEcuXKAalVNdu2batViapjx47UqlWLgwcPcu/ePZKTkyldujS//PKLVtUmuXMIch+RrBUIPnCuXbuGm5sbCxcuZOvWrZiamtKnTx9GjRpFaGgoVlZWeS1R8A7zySefsHjxYnx9fXnw4AEVK1aUfdaxg4ODVEY2MjKSw4cPs2zZMszNzRk+fLjsNpnx+eef06lTJw4cOKC1u1OT9PTz85N2cJmYmFCgQAEAvL29OX/+vFHJ2oIFC0qJlYcPH3Lv3j1OnDghJSg06DorVoPm3FN/f3+dZZj9/f212imVSlQqVYZ2mh0w+m7W54RefSQmJhISEiL5Vw758+fXSqBrdOojq/oMoUt/dmKxWrVqfPbZZ7i6uuLi4kLjxo3p2rUrRYoUMZhwfPXqFTY2NlpJ6fr163Pv3j3p9xYtWnD69Gl8fX2JjY3lwYMHGUpZpy11r0+PIeTo0YehueXYYixpbTd2jqdPn6JQKNi1a5d0LSYmhrCwMAIDA3n16hXW1tZa7x0nJ6dsJSRz0ge5uV63b9/G0tJSStRCqu1JSUn4+Pjkim/SVkooWLCg1mdlwYIFiY2NzZXxsutHOaT9Muzo6EhKSgp+fn7S2qeNY0NxWaJECb1zZdWeSpUqZXoW/LtOSkoKnp6eODs7Sw9yvI/khR2xsbE8efLkrcwlEAgEAoFAIBB8SIQnx/A41hf/xHACEsPwTwwjIDEc/8QwAhPDiVcnZehjghJLE3MslfmxMsmHlUk+ipnZUtWyFE6WpXGyLE1hs9R7mA0aNJCqdKVn/vz50s8ODg78/PPPGdoUK1bM4H01uXMIch+RrBUIPnASExOl5I+lpSXh4eGYmprSrFkzjh8/niuJEMGHg7W1NW3atOHIkSPcv38fNze3LI1TsGBBBgwYwO3bt7l+/brO5JecNmmxtLTk66+/ZuHChVo7fcuXL0/JkiU5fvy4tDOtWLFiUunHEydOGH0Dvk6dOowYMQJIfU/16NGDTZs28c0338geo2rVqtjY2HDq1Cmdydrz589TokQJ6Ym1woUL4+vrm6Hdy5cvsba21ntDPSf06uPcuXN6SzrrolGjRlLZ37zGkH5jY1GpVDJnzhy++OILrl+/zvnz5+nSpQtbt26lfPnyGdqn3XWnUCgyJOWTk5Oln4ODg3Fzc6NZs2a0atUKS0tLgoKCMiSB8+fPL0uPi4uLXlsM6TGEvrlLlCghyxZ96NqxmNZ2uf7SYG5ujomJSYazQJs0aYKlpSVKpTJDidDExETZetNjrD5D5OZ6mZqaZhg7KSn1i6aZmVm2faNrLdMnp7KbrJI7Xnb9aCyaudKeT542jg3FpSGyao9SqXyvE52Qusbvuw3wdu34EPwlEAgEAoFAIBC8LR7H+nIx4iEXIx7gEfMSFWqj+qegIiolnqiUePj/XK4nrzgT7iG1KW5mS70ClahfoBINClSiZD67nDRB8I6SvTqCAoHgncfR0ZHjx4/z7NkzSpcuLZUBDA0NzdYNZ8HHg5ubG6dPn+bq1au4uroabB8aGsovv/xCSEiI1vW4uDgePXpE2bJlZbWRg6urK46Ojqxfv166plAoGD9+PDt27ODChQta7aOjozl79qxWWRBjMTc3l8ov//fff7L7mZmZMXLkSDZt2sTdu3e1Xrt9+zbbtm3D3d0dhUIBpJYrOXDgAK9fv5bahYSE8Ouvv9KlS5dc15sZjx49YvHixfTv3z/Tks7vMun150QsXrt2jW3btlGwYEHatWvHokWLqFmzJleuXMHS0hJTU1OCg4Ol9leuXJF+LleuHFFRUVrnQF+6dEn6+datW8TFxbFkyRI6depEw4YN8fHx0bnrWo4eQxjSkx1fyLElbZLJkO90YewcVatWBVJ3FLq5ueHm5kbNmjVJTEzExsaGChUqEBcXp7Xr7PLly7L9kV19hsjN9XJyciIlJUWr9PD169extbWldOnSRvkmK2v5NsmuH+Vw48YN6ee7d+9iYWEhVUBIj6G4NMTbsEcgEAgEAoFAIBAIPgbiVImcD7/Hgpe76eCxgM8eruAnv2PciXlhdKJWLgFJ4RwJvcncl3/wyb1FdL33HZsDzhKaFJ0r8wneDcTOWoHgA6devXo0atSIc+fOMXz4cObNm0eDBg1ISEhg586deS1P8B7QrFkzvvnmGxo2bCjrJrGNjQ0PHjxg48aN0jl+MTExXL9+nYoVK/L5559TsGBBg23kMnv2bLp166Z1rWfPnkRFRfHFF1/g4OBA2bJliYiI4M6dO9SoUYN169YZ7Ye01K1bl169ejFz5kwOHjwo7Yg6efIkXl5eGdo7ODjg7u7OyJEjCQ8PZ+DAgdSuXZsSJUrg5+eHh4cH7u7u9O7dW+ozbNgwHjx4QLdu3ahTpw5KpZLbt2/j4uIilevNbb0Ap0+f5tWrV6hUKvz9/bl9+zY9e/Zk2rRpRmnICnL06WrTv39/qaSoIf1y4hVg9+7dmJub07179wx6ihcvzuTJk7l69SoODg4EBgby+PFjZs+ejampKS1btmT27Nm0a9eO58+fU7RoUdTq1D/oq1SpQqtWrRg5ciQdO3bk6dOnWjvnatSoAcDkyZMpUqQIDx48oEmTJuzatYtDhw5liH1DegxhSA/Anj17UCqV9OzZ06i5NXGnz5ZSpUqxadMmvL29cXd31+s7XcjxV/o5pk6dyujRo3F1dUWpVHL8+HGGDRsGpJ4t6urqyqhRo2jbti1eXl4oFAq9GvSRFX36yM31Kl68OBMnTsTd3Z2uXbsSGxvLiRMnmDt3Lubm5kb5xtD7IK/Jrh/1obHxv//+Y8aMGdjY2LB//35Gjx6NhYWFzj7FihXTG5c5YY9AIBAIBAKBQCAQCDLnVrQX2wMvcCniIYnq3Ku8JIdXCcH86HuUdX4naGfrwmdFm1KnQAXDHQXvFQr1u3KXRJCB2NhYHj58iJOTk6wbLJrdD7Vq1crVclY5PU/kZVuj+xRsGp7teeHd9Zmxay8HtVqNQqEgPDycK1euUKlSJSpXrpwjYws+PI4dO0a1atWkEq6XLl2iaNGi0vl/V65cwdzcnLp16wLwzz//YGZmRuPGjaUxfHx88PT0JDIyEmtraypVqqR1fqCcNunHTa9Lw99//42vry8DBw7Uuh4dHc2NGzcIDg7GysoKZ2dn2bt20/qiTJkyODs7a12PjIzk0KFDNG3aFAcHB44dO0ZoaKjOMezt7enQoYP0e2BgIP/99x8LFy6kZcuWTJs2TSpXnp6nT59y79491Go1VapUoXr16lqv6/JRTulN20ahUFCoUCEpyWwMmWkyZIcx+tKiy0ZD+g3F4oULFzA1NaVp06Y6NUVHR3P16lVCQkKws7OjcePGUqnqpKQk/vnnH0JDQ6lduzYWFhbcuHFDSvympKRw6dIlgoKCqFOnDnfv3mXjxo2cOHECSD3P+OrVq5iZmdGsWTOsra05ceIEBQoUoGXLlvz+++906NBB6wxefXoMYUjPkSNHuHDhAsuWLTPaF4ZsCQgI4OLFi5QrV44GDRoY9J0u242dA1LP+PTw8CApKYlatWrh4OAgjadSqbhy5Qp+fn5UrVoVOzs7rly5Qq9evWT588yZM9jb20slqLOiL6/WC8DLy4t79+5hZmZG7dq1tc5B1eeblJQUdu3aRadOnbCzs5O1lq6urtL5xufOnaNIkSKS3x4+fMjr16+1Pkv1Yex42fVj2nVOa3uBAgX4888/cXNz4969e/j4+ODo6KhV4lhXHIP+uDSEIXvSovm709HRUTrf/X3jbf1Nn9vkhR258b1DIBAIBAKBQCB4H1GpVZwN92Rb4Hk8Yl7mtRy9VMpfnM+KNqVL4bpYmeQ33EHwziOSte8wIlmbOSJZmzU0SYvMkkICQXYJCQkhJSUlww1nSD0v782bN1hZWUk3g8PDw1EoFDp37GrOV9aXYMqsTfpxQ0JCUCgUGWJfoylt8kFDYmIi0dHR2NjYZOnzISQkRDrfEVKThYULF8bU9H9FLRYuXMiVK1fYuHGj1nUNus6mNaRLk5hO/9mRmJhIaGgoxYoVkx7cSO8jQ3p1tdOlN20bExMTbGxsslR6Wt9cmjUzZEdm+vLly5dpbGVFv5x41YVareaXX36hVatWODo6AjBnzhyCg4OzvQM8K8jRc/78ee7du8f48ePfur73mbi4OKKjoylatKjsPgkJCcTHx2da1SCv1yutvoCAAAoXLoyZmZnWz+8Dee1HDTnlN2M/V0Sy9t1BJGsFAoFAIBAIBIK3j1qt5lTYXX72O8GLhKC8lmMUlsp8uBWuz7iSrhQ0FX/Pv8+IMsgCwUfAuXPnWLx4MT4+PkyaNAlnZ2f+/fdfpk+fntfSBB8Yw4cP5/Hjx5w7d46SJUtqvXbixAm+/PJLhg8fLsXenDlzsLS05PvvvwdSd3h9++23nDhxAktLS+Lj48mfPz/Dhg1jxIgRstukH3f48OG8evWKY8eOSbsqAwMDWbJkCUePHmXAgAGSzqCgIO7evUtwcDCmpqaoVCoaNmzI9OnTpXME5frC29tbSvKlpKSQmJhI48aNmT9/PqVKlWLs2LHs2rWLdu3aYWJigpmZmXRmLcC4ceMYNWoUADdv3mTlypXcvn0bpVKJWq2mcePGfPnllzg5OUl9evbsyejRozPsMvbw8GDAgAHcuHGDggUL6vSRIb2ads+fP8fMzAyVSkVy8v9KwdSoUYPq1atz9OhRIiMjMTExQalUkpycjIuLC2PHjqVVq1ZG+VAzV3pu3ryJiYmJTjsy66Px5/Dhw+nYsSPjxo3LdF6NLxITEzPVLycWDaFQKAgKCmLEiBF88sknBAQEcPXqVTZv3iyrvzEEBgayYcOGTF83NTVl5syZBvXkz5+fvn375ri+7BAdHY2pqalUavltzCHXnxpOnTrF6tWrOXfunKz59u7dy+zZs7G2tqZr166Zjq9Zr3bt2hEcHMz169ffynqdOXOGKVOmULp0afbv30/Lli3Zu3cvjo6O0s/6dtNnFWP9Lgc578Os+NGYuExISJDlt5x6HwsEAoFAIBAIBAKBAC5GPGCN73EexfnmtZQsEatKYFfwJU6G3WFqaTc6F66b15IEWUQkawWCDxw/Pz9mzZrF5MmTefHiBQCOjo4sWrSI5s2b06RJk7wVKPjgKFmyJAcPHsxw7uyhQ4cyJHDT8+233+Lt7c3p06cpXLgwkFoed9y4cVSrVo3GjRvLaqMLOzs7vvvuO3788UcALC0tqVmzJkePHpXeB48ePeKPP/6gTZs2tG/fHjc3N/z8/Fi5ciUDBgzgwIEDlClTRrYvxo4dq5UQDAwMZOrUqUydOpVdu3ZRtGhRKlSoQIUKFXB1daVjx446d9JcvnyZMWPGMHz4cH766Sfs7OwIDg5mw4YN9OnTh507d0pnYWYHQ3o1jBs3jnHjxhEVFcW1a9cyjHP+/HmaNWtG586dad26NQEBAezevZvx48cza9YsoxIemrmMISt90qPxhVqtzlR/VmMxPbNmzaJbt248fvyYunXrMm/evFypgGBpaan3M1+pVMrS06hRoxzXll2WLFlC06ZNcXV1fWtzyPVnVjl9+jSNGzemf//+esfXrNeSJUtwdnZmwYIFb2W9Dhw4gJubGwsXLgTgxo0bWFlZaT3AkRvklt9zI+6Nict8+fJJPtRHTr2PBQKBQCAQCAQCgeBjJjw5hnkv/uTviHt5LSVHCE2OZuaLHRwKucGscr0ok69IXksSGIlI1goEHzg3btygS5cu9O7dm82bN5OQkECxYsXo27cvt27dEslaQY7TvHnzDMna0NBQ/vvvP4O7Kj09PenWrZuU+AJo0aIFt27dknZ8ymmji9GjR/PDDz9w6dIlmjVrRoECBaRkWrt27QBYtWoVHTt2ZOXKlVK/kiVLsnTpUiZNmsSjR4+MStamp1ixYowdO5YRI0YQExODlZUVJiYmVK1alU6dOunso1arWbBgAZ06dWLKlCnS9aJFizJr1ixevnzJ4sWLtZKpOYUuvWkpUKCA5Lu0/PTTT1SsWJE2bdoAUKJECSZNmkS+fPlYsmQJn3zySaZlXd81FApFpvrlxGJYWBhKpVKvvSkpKZQuXRonJydpR7BarSYwMJAiRYpIpajj4uKIiYmRzuDUEB4ejo2NDUlJSYSHh2coQx4ZGYmZmVmG9QoICKBo0aIkJCRgYmJCvnz5MtVjDIb06CMlJYWIiAgKFCigc26NLRYWFtK10NBQ7t+/T40aNQgLC8PW1tag7zKzXe4chQoVkvwZGxuLqampzs8ftVpNeHg4tra2sn2gmS8qKgpnZ2ecnZ0pVqyYXn2lS5cmLi4OBwcHrd35csjKeoWGhhIaGkqpUqUIDAykWLFixMbGamlSKBSkpKQQGRlJoUKFtPrr878+f0Lmnztp7VGr1UbZo3m/Va9enerVq2dJc/prumLGkI0aH5qYmEjzacrW29raolQqDdqfFhcXF8qWLSutb1BQkFHvR4FAIBAIBAKBQCD4ELkW+ZRvXuwgOCkyr6XkOFejntDz/lJGlWjP0OJtMFO8v8fEfGxk75F/gUDwzpOUlKSz/J5arX5vzpITvF/UrVuXqKgoPDw8pGtHjx6lRYsWBs/9dHZ2ZufOnVy4cIHExETpetp+ctrookCBAkyaNImFCxdq9dPg4+PD06dP6devX4bXFAoFP/74I+3bt9c7hxyioqJQKpVa77/o6GgCAgIy/FOpVDx//pwXL15kKGusYfDgwdy6dYs3b95kW1tO6NXH4MGDiYuL4+rVq7miNbv6DJFev5xYXL58OT/99JPO8VQqFfPnz6dJkyb069ePJk2aMHfuXFJSUoiKiqJly5Z4eXlJ7Y8cOaIVBwcPHqRBgwb07NmT7t27s2nTJnr37i29fu7cOVq3bk2PHj1o1aoVffv2JTAwEEj9v6Fly5Zs376dBg0asHXrVr165GBIjz4Mza3Plh9//JEnT57w66+/snHjRoO+02W7sXNAamlxNzc3unbtSocOHRgyZAi+vv8rm3To0CEaNWpE37596dq1K56enrJ8AakPjjx+/Jjjx4/z9ddfZ0mfIbKzXun1aUr4Pnr0SGrz999/07p1a7p06ULTpk25dOkSkLn/DfkzN+2Jj4+nZcuWbNq0ifbt20uaL1++rFfzzZs36dy5s6T5008/lXxgbMyk9aFKpaJly5b8+eefdOzYkR49elC/fn3Onj37VvwhEAgEAoFAIBAIBB8iSeoUVvocZuzT9R9kolZDgjqZNX7H+ezBcm5FexnuIHgnEDtrBYIPHBcXF1atWqW1C+P169f8+eefzJ8/Pw+VCT5UTExM6Ny5MwcOHMDFxQVITVq4u7tz4sQJvX1nzpzJ0qVLmTBhAkqlkpo1a9KiRQt69OghlW+U00YXarWavn37snfvXjZv3pyhTHNAQAAAZcuWla4lJSUREhKiZVvRokVl+0KTNITUZJSXlxc//PADbm5uWgm933//nd27d2fof+bMGelGfrly5XTOUb58eSC15Hn6HZfGkhN69e0gtLS0xN7eHn9//yxp0mBoHbKqzxDp9cuJxcWLF2c63r1799i7dy9XrlzB2tqa8PBwpkyZwtOnTw2WDA8LC2Pu3LnMmzeP7t27ExwcTP/+/bXKaP/222+4u7vTq1cvkpKSGDJkCOvWrWPevHlS8v3q1aucO3cOW1tbvXoMndcsR48+DM2tz5Z58+Zx+vRpJk+ejKurK5GR+r9w6bLdkL/SzxEbG4u7uzuDBg1i9OjRqNVq5s+fz+zZs/n1118JDw9n7ty5LF68mE6dOhEdHc2gQYNk+QJgwYIFvHr1irp16zJhwgSj9Rkiu+uVXl9CQkKGNnfu3OH06dPky5ePZcuW8c0333D27Fmd/jfkz9y2R1M6+NatW5w4cQJzc3OWLVvGzJkzM9UcExPDxIkTGTNmDEOGDAFSS6NPmTKFI0eOGB0zuvScP3+ew4cPkz9/fhYuXMjPP/9M27Ztc80fKpVK9sMZ7xoa3e+rfg15Ycf77jOBQCAQCAQCgUAOL+ODmeH9O/djX+e1lLeGV3wgIx6vZWoZNwbYt8hrOQIDiGStQPCB4+joSP/+/enbty8KhQKlUslPP/3EwIED38lzBwUfBt27d2fYsGHMmDEDX19ffH19adasmcFkrbW1NQsWLGDGjBncvn2ba9eu8ccff7Bhwwa2bt2Kk5OTrDaZoVQqmTt3LkOHDqVbt25ar2nKV8bGxkrXHj9+zGeffQakJntLlCjBuXPnZPth586d/PXXX0DqrimFQsHIkSMZPXq0Vrv0Z8Xq0hUfH6+zlK4mSWJs6dPc0muI5ORkLC0tZbffunUr27dv17pWtmxZjh49mmmf7OgzRFr92YlFSC1da2lpyZIlS3B1daVOnTpS0sZQwvH+/fukpKRIcVy0aFG6dOnCwYMHpTYav8XFxREbG0vVqlV59eqV1jjdunWTyqLq02MIOXr0YWhuObYYS1rbjZ3Dw8ODN2/e4OrqKj1M0LFjR4YOHUp0dDSenp4kJSVJiVNra2u6du3K77//nmW9OemD7K6XHPr16yd9fvXs2ZNNmzbh5+cnPRCT1v+a6gCZ+dPa2vqt2NOnTx/pwZRevXoZ1BweHq51pnCfPn3YunUrAQEBGR64MBQzuqqd9O3bV6qOUrduXU6ePCnLjqz649mzZ7LGf5cxZgf7u8yHYodAIBAIBAKBQPAucODNdZa83k+sKuODxh86KtQsfX2AwMRwJpfqmiP3DwW5g0jWCgQfAePGjaNbt248ePAAgCpVqmS6S08gyAmqVauGvb09Fy5c4MGDB3Tq1Ek6O1IOFhYWNGnShCZNmuDu7k7//v357bffWLp0qVFtdFGzZk06derE4sWLmTx5snS9fPnymJmZ8eDBAypUqABAjRo1pPfNiRMnDI6dntGjR0tJwydPnvDpp59St25do0qQV6hQAYVCwaNHj7TOrdTw9OlTTE1NcXBwAFL9EhUVlaFdeHg4SqVS60zJ3NCrj9evXxMSEkLlypVl93F3d8+1xKuxZKY/q7FoZ2fHvn372LNnD6tXr+bp06e4uroyZ84cg1rCw8MpUKCAtAMPyJAcWrVqFQcOHMDW1hZLS0v8/f2l2NaQNlmpT4++uJGrRx+G5pZji7GkP7vTmDlCQ0MBMsRm5cqVCQ0NJSIiAisrKy1/FChQIFt6c9IH2V0vOaStdKB50CTtQwhp/W/In4aStTllT9pzZQsWLGhQs7W1tdbno8bOsLCwDPMbslHX57tGA6Q+bKRWq2XZkVV/VKpUyaCv31VSUlLw9PTE2dlZ9o7qd5G8sCM2NpYnT568lbkEAoFAIBAIBIK3zQ8+h9gaeD6vZeQ5WwPPE5QYwcLy/TBTirTgu4hYFYHgA+fhw4e8fv2aDh06ULp06byWI/iIcHNz49SpU9y9e5dly5bJ6pOSkpLh5qS5uTlly5YlLi5OdhtDfPnll7i6uvLvv/9K1woUKEC7du34+eef6dChQ4YzcOPj42WNnRmOjo4MHz6cb775hsOHD8veXWpvb0+jRo1Yt24dzZs317r5npKSwi+//EL79u2lG+xOTk5cuXIlQ5nnf/75BycnJ9mJ16zq1cfq1aupUKECtWrVyvZYeUF6/dmNxcTERPLnz88XX3zBF198wZs3bxg4cCC7d++WzpZMTk6W2vv5+Uk/29nZERkZSWJiohSrac9ovXLlCr/88gvHjx+XdgXOnTsXHx+fLOnRlHnNDEN6suMLR0dHo2zRPBiSme90Yay/NP+f7tmzR0pkq1Qq1Go1JiYm+Pr6EhkZSVxcnPT669dZL7WUlfXUR3bXSw5py5cHBQUBZFq+3JA/DZFT9vj7+1O7dm0AgoOD9WouWbIkkZGRREVFSYl4TZyVKFEiQ3tDNuoqJZ1VsuoPpVL5Xic6IbVM/vtuA7xdOz4EfwkEAoFAIBAIBLpY5XNEJGrTcDzsNiHJ0fxQcSgFTPQ/lC94+ygNNxEIBO8zjx8/zlBCVCB4G3Tr1o2///4bhUIhnV2rj+DgYBo0aMB3333H7du3efnyJQ8ePGDdunWcOnWKnj17ymojBzs7OyZNmsTPP/+sdX3WrFmkpKTQv39/jh8/zoMHD7hy5QrLli1j/vz5dOrUKUu+0ODu7o6JiQkrVqzQuh4aGsqTJ08y/NMkd+bNm4ePjw+jRo3i0qVLPH/+nIsXLzJy5EgiIiKYOXOmNNbYsWPx8PBgxowZXL16lRs3bvDdd9+xb98+pk6d+lb0QurOsufPn/Ps2TP++ecfxo4dyz///MPSpUtzveSKHH262qTdkWxIv9xYDAsLIyIiQqfOY8eO0bt3b+7cuUNERAShoaEkJydjY2ODpaUlxYoVY9++fbx584bLly9z9uxZqW/NmjXJnz8/GzZsICoqiuvXr2u9npKSglKpJDo6msDAQH7//Xdu377NmzdvMvWbPj2GMKQHUnf7hYeHGz23HFvy5cvHs2fPCAgIMOg7XRg7R40aNXBycmLRokUEBgYSHBzM4sWLGT58OAC1atWiYMGCrF69moCAAC5fvsyRI0cM+jGn9Bkiu+slh+3bt+Pl5UVoaCjr16/HxcVF5+5RwKA/35Y927ZtkzRv2LBBr2YXFxccHR1ZsmQJoaGh+Pj4sHLlStq1ayftKjYmZnISOf4QCAQCgUAgEAgEgg+Zn3yP8Vug/KPMsoPqVSQp1/0zXg+MIeVGACmeb1DHJ+voqY36TRwp1/1T2yertF8Liyflv0BUgbEZ+qkCY0l5ECJL6/Wopwx7vIbAxHBZ7QVvD7GzViD4wGnZsqWUYGjatClWVlbSa/b29jle9lDwcVOkSBHpfD17e3uaNm1KzZo1pddtbGy0SoHa2tpKO4yKFi3Kn3/+ybZt21i4cCERERFYW1tTqVIltm/fLu12ktMm7bjpdWno168fJ0+e5MWLF1rt/vrrL7Zv3862bdsIDg7GysqKGjVqsHXrVllJ57RjpS8nmS9fPubPn8+MGTPo1asXTk5OFClShFOnTnHq1KkMY7i4uLBmzRrKly/PX3/9xa+//sqKFSt4+PAh5cqVw9XVlVWrVmkl06pWrcqePXvYuHEj8+fPR61WU6VKFXbs2KG1Frp8lFN6ixQpwsmTJzl58iQKhYJChQpRr149Zs2aZdQOf12a0qPLDjn6dLWZPXs27du3l6VfbrwuX74cCwsLZs2alUFP9+7diYiI4NtvvyUkJAQ7Ozv69++Pm5sbAN9//z0//vgj/fr1o169eowfP57ffvsNACsrK9auXctPP/3E4cOHqV+/PsOGDeOXX34BoGnTpgwaNIgvv/wSMzMz3NzcWLlyJZMnT+bLL79kxYoVFCtWTGsHuSE9+jCkR+OL2NhYfvjhB6N9YciWIUOGsGPHDl6/fs2SJUv0+g7IYLscf6WfY9OmTaxevZpRo0aRlJRErVq1WL58OZBaGnvDhg2sXLmSQYMG4eTkxMSJE9m2bZtBX2qws7OT4j8r+nJzvdLrUygUFCtWDDMzM1QqFcWKFWPEiBEsWrQIHx8fKleuzKpVqzL1v1Kp1OtPQ+SEPZB6Tu3ChQvx9fWVrXnVqlUMGTIEMzMzGjZsiLu7u9TGmJhJ60Nd81lYWGQo3Z0dfwgEAoFAIBAIBALBh8pav+NsCjjzVuZSxyeTuPwmJKkwafC/KktJux6ScvYVyip2qMPiUb+Jw3x6A5QVbXWOk3zuFcm/P0BZuRDqsHhQqTGf3RiFTT5UgTEkLbuBSdtyJO99gtlIZ2kctUpN0k+3MO1TRbbmp3H+DH70Ixscx1I+v7zvmYLcR6GWe/iR4K0TGxvLw4cPcXJyklV+MiUlhTt37lCrVq1cLWeV0/NEXrY1uk/BpuFG9/GfW9Go9iXmPzd6jsww1mfGrr0+Nm/enOm5icOHD2f69OnZGl8gELx9Bg8eTJkyZVi8eHFeSxHkIYmJiSiVSqns76+//srJkyf5888/30k9z549Y8eOHcydOzdP9Am0+dDWKzv2JCQk4OLiwt69e3F2dn6runMLYz4fNH93Ojo6Zvts5bzibX0Pym3ywo6c/N4hEAgEAoFAIBDkNev9TrLO/+Rbmy9p+wNU3hGo/WPIv64dAKrn4STO+xfzZS1RFk/dOJW4+hYkqzD/sl6GMdSRiSRMPIvZpLqY1LZPTcAuuY7C3hKzEc4kH3iKOlmNWS9Hks+9Qv0yErNhNQBIPu6NyjsC83G1jNZe0tyO36tOorDZ+/k98END7KwVCD5whgwZwqBBg7TOudSg69rHysqVKwkKCmLBggUZzvT08vLi559/plWrVnTp0gVILZWYL18++vTpo9Xu+PHjBAQEYGpqioODA507d6Zw4cKy26Qfd+XKlcTExPDNN99olY4NCAhg+fLlWruO1Go1//zzD1evXiUiIgI7OzuaNm1Ko0aNjCo7u3LlSnx9faXflUol9vb2NG/enIYNG2baLi2urq60a9dOp64iRYrQrFkzGjRooNVn0aJFtG7dmqZNm2pd9/b2Zu3atSxcuBALCwudPsopvWnbmJqaYmdnR7169WjZsqV00zQpKYmQkMxLiygUCnbu3JnpXEuXLkWpVBq0IzN9zs7ODBo0iMmTJ9O0aVOcnZ0pVaoUSqVSln4NcuI1t5Djw8xKjwpSUavVdO7cmWbNmuHu7k5AQAA7d+6kV69eOT7X9evXOXjwIBMmTND5ukKhwN7eXtIzYMAAfvnlF86cOcOoUaOkdpcuXaJly5Y5ri8vuXXrFidOnGDmzJkkJSUxY8YMJk2aRJkyZTLtk9vxL2f8tOuVWfwYWq/Q0FA2b95MYmIi06ZNk2wvXry4LD+8a/bkNTkZP3L8IRAIBAKBQCAQCAQfGr/4n36riVqVVzgpNwIwG1qdpF88peuKYlaYL2wqJWoBFLb5UAdlLGEMoPIMhoL5MKmdustVoVRg0rYsSb/dx2yEM+qwBBRlCkjjqG7HA6AOiSP5uDf5FjXVOa4h/BJDmfz8N35x/Jx8SjPDHQS5ikjWCgQfOJodFfrYtm0bJiYmDBgw4C0oejc5f/483t7etG3bVkoyati7dy+nTp2iaNGiUrL25s2bWFpaSom2EydO8PXXX9OvXz/q1KlDXFwcJ06cYOPGjezbtw97e3tZbdKPe/78eZ4+fUqVKlXo3bu3pCkyMpLDhw9Lydro6GjGjRvHs2fP6Nq1K5UrV+bly5e4u7vTsmVLli9fLnuHxvnz5ylZsiQtWrQAQKVS4eXlxejRoxk/fryUfDl//jwlSpSgWbNmGcbQJBrS6urWrRuOjo74+voyfvx46tevz8qVK6Uyj6dOnaJ8+fIZkrUhISEcPnyYOXPmYGFhodNHOaU37VgJCQm8fPmSWbNmYW9vz/r16ylevDi+vr5MmzYtU/+Zm5sTFRWV6VyaxLkuO+Toy5cvH+PGjePLL79k3bp1mJqa8scff5AvXz5Z+kFevOYmcnz4+++/56qGd4UjR45QtmxZo0psQ2ocrV+/npUrV9K/f38KFChAz549GTFiRI7NocHDw4ODBw/y9OlTna9r1kujp2/fviQmJtK2bVstPUOHDtXZP7v68pLXr19z5swZZs6ciUKhoHjx4lqla3WR2/Evd3xD8ZPZemlYs2YNN27c4PPPP9eyXaVScfjwYYYMGZIjydq3YU/6EsQ5hTGxndPxI/fzQSAQCAQCgUAgEAg+BA6+uc4av+NvbT51ioqkXzwxG+gE+bXvvyuszVBY26AOjyflbjDqV1GoPIIxm1Bb51gq/xiUxbSr3CiKW0FEAurYJLA0hbj/P/M2NgmFVep316Tf7mHaszIoFKT8F4iimCXK0sbtkr0b84K5L/7g+wqDjOonyHlEsjaHiY2N5dixY/j4+FCkSBE6duxI0aJFpdeTk5M5duwYz58/x97enm7dur235cYEHw5JSUmoVCrDDT9w6taty8GDB7WStSqViqNHj1KrVi29fX/77TdGjhzJ+PHjpWt9+/bll19+ITIyEnt7e1ltdNGrVy9WrFhB+/btsbW11dlmyZIlvHr1isOHD2vtjBw4cCC9e/dm7969WruADeHs7Ey/fv20rlWoUIHly5czcuRIKeHo4uLCwIEDMx1n8eLF+Pj4cOTIEezs7KTrI0aM4NNPP+XHH39k6tSpsnXltl5dY02ePJnRo0fzxRdf8Mcff1C+fHl2796tdww3NzdZc6XHmD7Dhg1j2LBhRusHefGam8jx4cfCkSNH6N69e5YSlRUrVmTNmjW5Ogekns9rb29vcM00ekaMGIGzszNffPGFrPGzq+9dwdTUVNbnWW7Hv9zx5cZPZrx8+ZK2bdvSqVMnAMn2hISELI+pi7dhj7m5Of/880+W+urDmNjO6fjJ7voKBAKBQCAQCAQCwfuCT0II37/e/1bnTDnmjcI2HyYNSpDyQHf1I3VEIqp//VAHxaKoXAiFTT7dg8UnZ0j4ku//f49LxqSWPUlb76N0LkLKBR9MOpQn5bo/JKRgUrcYibMvY9KyNMn7n2LaozImdY2r1nU87DZVA0oxtHgbo/oJchaRrM1BQkND6dWrFy4uLjRs2JDnz5/TsWNHdu7cSdWqVVGr1YwcOZKQkBDatGnDyZMn2bp1K3v37qVgwYJ5LV8g+Ohp2bIlK1euJCIiAhsbGwCuXbtGwYIFKVWqlN6+CoWCFy9eoFarpcSgUqlkzJgxRrXRRaNGjQgODuaHH35gwYIFGV6Pi4tj//79zJkzJ0MJ20qVKrFz504cHBwMO8AAlSpVIjY2lqioKFmfWZGRkRw6dIjFixdrJWoBihcvzpgxY1izZg0TJ040uJPobejNjIIFCzJ37ly6d++Oh4fHe5dQ0qVfTixu2bIFc3Nz+vfvr3Pc58+fc+jQIYKDgylSpAjdunWjUqVKxMXFMXv2bKZOnSrt5L127RoXLlyQdoNFR0ezc+dOXr9+jYuLC9WrV+evv/5i9uzZQOqDT/v37+fx48eYm5vTuHFj2rZtC6Q+9PT111/z+eefs2fPHpo0aUKLFi0y1SMHQ3oMoW9ufbasW7eOmzdvEhUVhZ+fH/369dPru8xsN2aO4cOHo1arOXbsGLdv38bMzIymTZtq7eiOjo5mx44dvH79mqpVqxp1huHatWt5/PgxQUFBhIaGsmDBAqP15eV6qVQqDh06xL179zAxMaF27dq4urrK8k3aMrZFihTRu5YqlYpp06YxceJEjhw5gq+vL3Xr1qVHjx7s27eP27dvU7ZsWQYNGoSFhYVBm7IyXnb8mH6dZ8+eLdmuedgjNjaW9evX4+PjQ6VKlejfvz/m5uaZxrGhuDREduxJSEjgm2++Yfz48Zw4cUK2Zn3xYux7L238lCpVimnTpjFlyhROnjzJs2fPKF26NAMGDJD9/1l23ycCgUAgEAgEAoFA8D6QolbxjfcOYlU5++CwPlSBsSQffo75Iv3fWZXlCmI+oyFqlZrkjR4krr5FvnlNMjY0U0JSuo1UySn//5oJyip2mPaoTMrZV5i0KI2yemESZ17CbHoDVLeCUFa1w7R7ZRTlbEg589LoZC3AT77HqGntQG3r7N9DFmQNcWBlDnLmzBkg9dzBfv36MWvWLGrXrs1ff/0FwN9//83jx4/ZsWMHkydP5rfffsPGxoYdO3bkpWyBQPD/FC1alDp16nDs2DHp2qFDh+jWrRtqtVpvX3d3d86ePYubmxsrV67k8uXLGXYXyWmjC7VazTfffMPhw4fx8PDI8PqzZ89ISkqidm3dpTScnJzInz+/wXkMcerUKcqVK6d1o/jkyZNMnTo1w7+YmBgePnxIcnIy9erV0zlevXr1iIyM5NWrV9nWlhN69eHk5ISlpSX379/PFa3Z1WeI9PrlxGK1atWoWrWqzvGCgoLo3bs3FhYWtG7dGjMzM/r27cvr169JSkri8OHDREZGSu1fvXrFuXPnpN+HDBnCpUuXaNy4MT4+PkybNo2///5ben3ixImcOHGCRo0a4eDgwPTp09mzZw+QmlQ+fPgw3377LcnJyeTPn1+vHjkY0qMPQ3Prs6VVq1YolUoaN25M06ZNDfpOl+3GzgEwffp0NmzYQJ06dXB0dGTOnDls2bJFmnPYsGFcv36dli1bEhsby4YNG2T5AqB169bY29tTvXp1unXrliV9hsjN9friiy/Yvn07derUwcnJiZUrV7Jo0SJZvtGU/w0PD5e9lt988w22trZUqlSJWbNmMWrUKHx8fKhXrx67du1i3bp1suzKynjZ8WP6dU5ru4Zvv/0WExMT6tSpw59//intGs0sjg3FpSGyYw/A4cOHmTJlChYWFrI164sXY997aX2omW/q1KkkJyfTsGFDDhw4wPz583PVHyqVipSUlPf2H5DnGt5XOwQCgUAgEAgEgveVzQFnuRPz4q3OmbzzIcoKtqifhJJyySf1zNmkFFIu+aAOj0etVqOOT5baK5QKlM1KoX4ahjo5Y3VLRRFL1CFxWtfUwXFgYQoFUksem9QvjtkIZ0yalyb5j0eYtCqNsoQV6rB4KJT6HVVRKB/q0Pis2YSK6V7bCUuOzlJ/QfYRO2tzkEKFChEXF0diYiL58qVuaY+OjpZ26F2+fJnGjRtLiQMTExPatWvHP//8w+eff55nugUCwf9wc3Pjjz/+oF+/fiQkJHDmzBkOHz7MqlWr9PZr3rw5x48f5+DBg1y5coUtW7agVCrp168fkydPxszMTFabzChdujQjRoxg/vz5UpJDgybJpvmsgdRzFFevXi39bmdnx8yZM2X74eTJk3h5eQGpyWIvLy/8/PxYu3atVruSJUtSt27dDP1NTU2Jj0/94yCz0s2a3bZpkxlZJSf0GqJQoUIkJiZmSZOGokWLMn369Ez7ZEefIdLqlxOLDRo0yHSsN2/ekJiYiKurK+XLl6d9+/a0aNFCVll/T09P7t+/z8WLFylatCidOnXC19eXW7duSW0GDhyIk5OTdFbvs2fPuHDhAr1790apTH3OrH79+owdOxaABw8e5KoefRjyhT5bnJycMDMzo1KlSlSpUsXge0GX7cbO8fz5cw4ePMjJkycpX748kBobX331FYMGDeLBgwd4eHhw+fJlihQpAqQmONMm2/VRrVo1qRqB5kENY/QZIjfX6+nTp5w8eZIzZ85IZ60WKVKEMWPG8MUXX+Dt7Z0t3+iiW7du0nnkJ0+exNramkmTJgGpZYbv3r2bK+Nl14/p11nXg0c9evSQzoktUaIEw4YNIywsjEKFCgHacWwoLg2duZ5dezR0796dwYMHy9JsKF6Mfe/pwtXVVdKTlJQkO3mfVX88e/ZM1vjvMp6ennktIUf4UOwQCAQCgUAgEAhyk/sxr9ngd/Ktz6usYIM6MBbVg1AA1OHxkKxC9SAUhYMNqqv+JB/1It/K1ihMU+/lqH2joWA+6Xet8WoUJvm3e6ln15awAkB1IwClcxGpIp4G1ZMwVI/DMF/8/7t6Lc0g/P+/k8clo7DK+j3EwKRw5rz4g58qjczyGIKsI5K1OUjbtm25efMmAwYMwMXFBW9vb4oVKybdqPLx8aFy5cpafUqWLImPj4/eceU+8Zz2Sezc5G3NI0fD+zKHsT4TT7jnHR06dGD+/Pm8fPmS+/fvU61aNamEpSE0pX3HjBlDYmIiJ0+eZN68eRQsWFC6uSunTWaMHj2agwcP8ueff2ol9DTnYvv4+EjlJy0sLHBycgLgyZMnnDlzxqhkbenSpWnYsCEA9+/f5+XLl5w+fTpDmWVdZ8Vq0CQz/Pz8cHR0zPC6r6+vln6lUqkz9pOTU59E03ezPif06iMhIYHg4GAp2SSHYsWKUaNGDa1rhspXZlWfIXTpz04sOjk5SecOly9fnkaNGtGjRw9sbW0NJhx9fX2xsbHROs+9du3aWkmEqlWrcuzYMXx9fYmJieHevXsZztFNW45anx5DyNGjD0Nzy7HFWNKX4jZmjmfPnqFUKrXOsoyPjycyMpKAgAB8fHwoWLCg9P4FqFKlSrYSkjnpg9xcr2vXrmFtbS0l3gAcHR1JTk7Gx8cnV3xTsWJF6WcrKyutkvXW1tbExcXp6pbt8bLrRzlUr15dS5darcbf319KfKaNY0NxaegogpyyJ63mSpUq6dXs5eWlN17SVyYwZGPauNKQdgwrKyvZ8ZBVf1SqVAlra2tZc7xrpKSk4OnpibOzs8Hk/rtMXtgRGxvLkydP3spcAoFAIBAIBAJBThGnSmSm9w6SybhTNbcxddM+divlQQgq70jMRqd+Z1TY5CPluDdJ319D2aAE6vAEUk6+wPSz/z2knnIrEEURC5RlC6IsZoVJy9IkLb2OSftyqANjSbnih/kC7Qpk6mQVSb96YjaihpT0VboUJemYF6pWZUj++zXKuvLuY2fGPxEPuBzxiKY2uqvtCXIPkazNQWJiYnj06BElSpSQbpZdv36doKAgrK2tiY+Pz3AuY758+aTdZ5lh7Jfnt/Ukdk7NU9lwkwzcuXPH6D4l38IchhBPyb/7WFpa0qFDBw4fPsy9e/dwc3PL0jjm5uZ07dqVixcvZhpLctqkb//NN98wffp0rR2j5cqVo2zZshw8eJA6deoAqYnSESNGAHDixAlu3LhhlP7q1atLu7M+/fRTPDw8WLVqFQsXLpQ9RtWqVSlUqBBHjx7Vmaw9ffo0ZcqUkW5029vb6yxb6+XlhY2NDVZWVrmqVx8nTpxArVbTqFEj2X1q1aolPayT1xjSb2wsKhQKJk+ejLu7O7dv3+b8+fP07t2bX375RWfp5LT/z5mYmEgJeA1pExD+/v5069aNbt260apVKywtLVGpVLx58yaDZjl66tevr9cWQ3oMoW/u0qVLy7Il7Vjp0fU3Qlrb5fpLg4WFBSYmJnTu3Fnres+ePSlYsCBmZmYZdpAbmzBMi7H6DJGb65U/f36SkpK02mt2jFpYWBjlG7lrqdktndnvxiJ3vOz6UQ5px9f8rKk8A9pxbCguDZFT9qRdX83PmWk2FC/pyYqNWY2HrPpDqVS+14lOSLX9fbcB3q4dH4K/BAKBQCAQCAQfHyt9DvMiISivZQCgsDHHpMH/kqQKa3PMv21Oyj8+qF9FgaUp5lProXT636YS1ZMwlMkqKJv6fdB0hDOqS76oHoWCtRnmi5qhLKn9MK36eTgmzUujdLSTrimLWWI60pmUsy9RVrLFpH25bNuz0vcwjQs6olSIU1TfJiJZm4Ns3bqVuLg4tm7dKl1bsGABy5cv5+eff8bCwiLDjZLY2Fi9CQhIfUrf0tLS4Pxv60nsnJ4n5qrxfWrVqmV0n6BDuT9HZhjrM/GEe97SvXt3vv/+e/z9/Vm+fLnB9m/evGHbtm306dNHa/dPREQEd+/epV27drLayKFVq1bUqVMnQ3nfyZMn89VXX1GvXj26du2qpe3IkSMGP2f0YWJiwoIFC+jTpw+urq6yz5U0MTHB3d2dFStW0KBBA61+Fy9eZOfOnXz//ffStc6dO/Pjjz/y2WefScldX19fNm3aRPfu3XNdb2b8999/fPfddwwfPlzWTs13jfT6cyIWL126xN27d3F3d6dhw4Y0bNiQBw8ecPv2berUqYOZmRn+/v44OjqiVqu5cOGC1LdChQpER0fz7NkzKlWqhEql0nrdw8OD5ORkZs2ahUKhIDIyksePH2uV+TZGj6FkrSE92fFFaGioQVsUCgUqVepToJaWlnp9pws5/ko7R/Xq1TExMaFgwYLSDv1Hjx5x9epVWrduTaVKlYiPj5f+z1Kr1Uad+5ldfYbIzfXq0aMHAFevXpUebLh48SJFihShVKlSqNVq2b7Jylq+TbLrRzn8+++/NG7cGICbN29ibW1N6dKldbY1FJeGyCl70mq+ffu2Xs3VqlUDMo8XMO69J+cMe7m8jfUVCAQCgUAgEAgEgrzidrQ3fwZfzmsZEspSBVAO066up7Ayw/QTh0x6gFlf7c0OCqUCkxalMWmh+zsogLKKHcoqdhmum1Qvgkn1jNWassrTOH8OhtygR5GGOTamwDAiWZuDeHt7U6mS9hZ4BwcHrl27BkD58uV59eqV1usvX77UKlGnC2OfrH5bT2Ln5ZPrb8u+3BhTzrhv269ubm46dwF9rDRs2JCIiAiaNWsmqxxg4cKFCQ8Pp0uXLlSvXh07OztiYmK4c+cOjRo14vPPP8fKyspgG7nMnDkzw86cTp06ER8fz6JFi/jxxx8pW7Ys4eHhPHnyhBYtWrBx40aj/ZCWGjVqMGDAAGbPns2hQ4ckvxw6dEjnmYqVKlWSzuGLiYlh/PjxlC9fnuLFi+Pv78/r168z2DFo0CCeP39Oz549qVq1KiYmJjx8+JCWLVsyZcqUt6IX4MiRI9y7dw+VSoW/vz/e3t4MGTJEOvcxN5GjT1eb4cOHS2WgDemXE68AW7ZswdzcnP79+2fQU6FCBWbPns3Vq1dxcHAgMDCQFy9esGjRIkxMTHB1dWXmzJm0aNGCFy9eULVqVWnXdMWKFencuTPDhw+ndevWvHjxguLFi0tlsWvVqoWZmRkjR46kcOHCvHr1ik8++YSNGzeya9cunWWi9ekxhCE9ANu2bcPExIQBAwYYNbe5ublBW8qVK8eaNWu4d+8e06ZN0+s7XcjxV/o5Zs2ahbu7O82bN8fExIS///6byZMnA6l/q/Ts2ZNRo0bRrFkzXr58SdGiRWUnU3NCX16tl+ZM6S+++II2bdoQFxfHv//+y7fffoupqalRvjH0PshrsutHfajVaiD1HFp3d3dsbGw4ceIEkyZN0tqlmpbChQvrjcu3Zc+DBw9wd3fH1taW48eP69VsKF4Ao957OYkcfwgEAoFAIBAIBALB+8oa32N5LeGDZ63fcVztamOhNDfcWJAjKNSaOyqCbLNmzRpOnjzJoUOHpMTX9OnTiYmJYc2aNVy7do2xY8dy7NgxSpQoQUxMDD169GDYsGE6bz7Hxsby8OFDnJycZO+svXPnDrVq1cr1nbU5OU/kZVuj+xRsGm50H/+5FQ03SkOJ+c+NniMzjPWZsWuvD7VazfLly7lw4UKGsyT79u3LuHHjsjX+h8KFCxeoVKmStBvmv//+o3DhwpQvXx5I3WFjbm4unWd38+ZNTExMqF27tjRGeHg49+/fJyIiAmtraypWrJjhnD1DbdKPm16XhuvXr+Pv75+hTHNiYiIeHh4EBwdjZWVFjRo1sLPL+MSVIV+UKFEiQ+ni2NhYTp8+Te3atSlbtiwXLlwgPDxc5xiFCxemWbNm0u+RkZF4eHjw9ddf07p1a2bMmJFpbAcEBHDv3j0g9TzItOcBgm4f5ZTetG0UCgWFChXC2dnZ6B21mWkyZIcx+tJSp04dypQpY5R+Q7F4/fp1TE1NpdLa6UlMTOT27duEhIRgZ2dHnTp1pBKharWamzdvEhISQs2aNVEqlXh6ekq7dtVqNXfu3CEoKIiaNWty+fJlNm3axPHjxwEIDQ3l1q1bmJmZUb9+ffLnz8/FixexsrKiXr16HDx4kObNm2vFtj49hjCk58yZM5w6dYqlS5ca7QtDtoSFhXH9+nVKly5N9erVDfpOl+3GzgEQHBzMgwcPSEpKwsXFJcMZsh4eHvj5+VGlShUsLS25c+cOHTt2lOXPK1euUKhQIakkdlb05dV6AQQGBvLw4UPMzMyoXr16hvdPZr5RqVQcPnyYli1bYmtra/Rapvfb8+fP8ff31/os1Yex42XXj2nHT2u7lZUVx44do127drx48QIfHx8qVaqkdZ6urjgGw3Gpj+zYk5CQgIuLC3/99ReQWtVBrmZ98WLMey99/KSfz8/PD09PT9nvQ0P+SIvm705HR0cKFCgga/x3jbf1PSi3yQs7cvJ7h0AgEAgEAoFAkNtcj3rKqCfr8lrGR8HnJToytqS876CC7COStTlIVFQU/fv3p2DBgjRs2BBvb2+uX7/Oli1bqFw59WTW6dOnc/XqVZo1a8adO3ews7Nj8+bNOm8oi2Rt5ohkrXwuXLjAV199hbu7O0WKaJdDqFChAk5OTtkaX/Dh4ePjQ0pKCuXKZTzjIDExkdevX1OoUCHpBnJgYCAKhSLDTfWkpCSCg4MxNTWlcOHCmJiY8P3333P+/HkOHTqEubm5zjYa0o/r4+ODUqmkZEntE6g1mtLeVNcQGRlJREQEdnZ2WSoF7ePjo1WaUqlUUrRo0Qw7rtO3S4udnR2FChXSqatw4cI63+OvXr3C1tY2wzmG8fHx+Pr64uDggFKp1OmjnNKbto2pqSl2dnZZuomffi61Ws2WLVto2rQpn3zyCQATJ04kPj5e2gEuV5+VlVUG3+qaV59+tVrNDz/8QOvWrSlevDimpqYsX76c+Ph4fvzxRyA1yfPs2TPGjh1rtP0fAtHR0YSGhlK2bFnZfSIiIoiLi6N48eKGGxuBZr3at2+Pi4sLkPq3VVxcXJ6sV1rfqNVqvLy8KF26dKa7Md8VcsqPmnUuVqyYZLu5uflb90N27dEka/fu3Yuzs/Nb0ZyenIwfOf5Ii0jWvjuIZK1AIBAIBAKBQKCfYY/XcCvaK69lfBRYKvNxpMZMCpu9n98T3zdEGeQcpECBAuzfv5/Lly/j4+ODo6MjCxcu1LpJvmTJEq5cucKzZ89o06YNLVu2lEqlCQS5watXr+jVqxdDhgzJaymCPMbPz48ffvgh09fNzMz47rvvcHd35/Hjx5w+fTrDrtZjx44xffp0hg8fzvTp0wFYvHgxlpaW0vmzERERzJ07lwsXLlC0aFHi4uKIj49n8ODBjB49mtOnT9OlSxcSEhKIiIjA3t5eq8348eNRKBQZxnV3d8fb25ujR49q6Xrx4gVdu3bl8ePH0rXLly+zYsUKHj9+jJWVFZGRkdSsWZOZM2dSs2ZN2T5zd3eXkoKQmoAODQ3Fzs6OWrVqSdcvXLhATEwMpqamGW50jxo1iqFDhwKp52VqdBUoUICoqChq1arFV199pbVLe+DAgYwePZqBAwdqjXXv3j0GDBjAjRs3KFiwoE4fpdWrUqkICQmhdu3afPvtt9JOcXd3d169eqXzpqxGb9qxEhISCA8Pp0qVKowdO5ZOnToZ5cP0c8XExLB3717Onz9PUFAQN2/epHnz5nr76NLXsWPHTKsDaMZQqVSkpKSQlJREgQIFcHR0lBL+ZmZmfP3115w9e5aNGzdiZWVFYmIiycnJ9O3bF7VajUKhoEiRItIZkzlNaGgo5ubmskqu59UcZ8+eZfXq1fz++++yPkOOHTvGtGnTqFq1Knv37pWtLzIyUtb4SqWSUaNG0aZNGwICAnj69Cm//vqr1C431ys9Gt+cO3eOxMREOnXqlOMJP7mf3cagUCiy7ce067xjxw7JdkdHxxz1g1z736W40GDMe09u/OSUPwQCgUAgEAgEAoHgfeM/vxhMXrakRKFk/JWvDHcQZItYVQJr/Y4zp9xneS3lo0BkCXMYU1NTWrZsqbdN48aNady48VtSJPjYqVixIh4eHnktQ/AOYGNjQ+/evTN9XalUSj+XLl2agwcPMn78eK02hw8fpnTpzA+6B1i0aBGhoaH8888/UuLy5s2bjBo1inr16nHo0CE+//xzwsPDOXToEDY2NhnaZPYZWaJECRYvXsz69esznf/8+fO4u7vj7u7Otm3bsLa2JiwsjFWrVjFkyBD2799v8KzwtIwYMUJKCMbExHDt2jXWrl2Lt7c38+fPB+DOnTu0b9+eHj16UL9+fZ3jnDt3jgkTJjBhwgR+//13rKysiIqK4pdffmHQoEFs375dK2GbVdLqhdTk+ZQpU5g6dapW4mzUqFEGy6CnHSsyMpI///yTGTNmEBQUJCWg5aBrLm9vb548eULBggWxsLDIsItYjj5DDBkyRIql2NhYzp07x/79+6lSpQqurq4olUoWLVpEkSJFWLp0Kb6+vhQsWJCUlBQmTJhAx44dady4MbVq1cqWDn2sWLGC5s2b4+rq+s7PIfcz5OjRo/Tq1Yt58+YZpa958+ayxp88eTLdu3eX4sfFxUVr53xurpc+8uXLx/3793P8ITxjPruNIbt+TL/OGtsz2xWfVeTanx17zMzMWLp0aYYHlLKLMe89ufGTU/4QCAQCgUAgEAgEgveNHR4R3H1pgcmLLtQtk8ibIhd5qXxsuKMgyxx8c50JpTpRyDT3NhkIUhHJWoHgA8fFxYWdO3eyZs0aGjZsiJmZmfSavb19hpKygg8XKysrGjZsKKtty5YtMyRrg4ODuXv3rsEHUh49ekTXrl21dpjWq1ePW7duSed5h4WF0bVrVylRq6uNLkaOHMkPP/zAuXPnaNOmjc423333HZ07d9ZK9BUqVIj58+eTkJDAixcvjErWpsXKyoo2bdpgYWHB0KFDqV69OtbW1lhZWVG6dOlME7VqtZrFixfTvXt3rRKcBQoUYMqUKTx//pxvv/2WPXv2ZEmXPmxsbBg5ciRDhw4lOjo6y7srCxYsyKhRozA1NWXlypV069bN6POQ0+Lg4CCtw65du7I8jj7Mzc21Yr5169ZUqFCBVatWMWHCBOzs7FiwYAFdu3alRo0a1KhRQ2qbNhYzK/WdlpiYGEJDQylUqFAGH6ekpBAcHIy5ubmWz/z8/Lh37x5VqlQhICAAe3t7vL29KVOmjHQ8QlRUFOHh4ZQpU0Yqk1q2bFmioqK0duzJnSNtWeKQkBDMzMwyJMohdRd5UFCQls1yPkP8/PwICQmhWLFivHjxQtrNLUdfVFSU7M8oTalYe3t7kpKSePnypc7S7Zmhb70g1TcmJiY6z3vW5RtIfZ+/fPmS0qVLY2ZmJnstk5OTCQkJkcpwp6SkEBAQQJEiRciXL58svxszXk74Mf06lytXTrJdg0KhID4+XtKiKemqL441vk8bl8b835WduKhRowZWVlZZ1pw+Xox976WNH00paU157aCgIIoWLSo7HnLCHwKBQCAQCAQCgUDwLvEyPJFLL2MBSFGD5ytzFK/aUrNkK+Lsr/HE9E7eCvxASUbF6bC7fFa0aV5L+eDJ2qP47ynLli0jLCwsw/WpU6cSGhqaB4oEgtznzz//5PTp0/z0008MHDiQPn36SP+2b9+e1/IE7yi1atUiPj6e//77T7p25MgRWrdurZXw10WdOnXYtm0bx44dIyYmRrqeNgkrp40urKysmDp1KosWLSI+Pj7D669fv+bFixd89pnu8hzff/89rVu31juHHEJDQzE1NdVKfISFhfH8+fMM/1JSUnjy5Ak+Pj7069dP53gDBgzAw8ODoKCgbGvLCb366NevHwkJCVy9ejVXtGZXnyHS65cTixs2bGDLli06x0tJSWH69Om0b9+eSZMm0bZtW7766iuSk5OB1FKxLVq0YNSoUfTo0YNu3brh4+MDwLZt23j+/Dl79uxh165dREdH06lTJ168eCGNf+LECUaNGgVAcnIynTp14rfffqN58+bs3LnT6DkAbty4Qfv27Rk6dCi9e/emd+/evHz5Uppz9+7dNGzYkAkTJtCjRw+tzwFDbNmyBW9vby5cuMDSpUuzpM8Qf/75Jw0aNGDMmDH06NGDDRs2MHjwYFl9Da3X5cuXadOmDUOHDqVPnz64urpqVafQ5xtNGdsnT54YXEu1Wk2nTp3YvHkz3bt3p2/fvnTo0IF///2XHj16MHz4cBo1asSVK1dk2ZWV8bLjx/TrnNZ2DcePH8fV1ZWhQ4fSoEEDzp49C2Qex4bi0hDZsSchIYFOnTrx888/06VLF4YOHUrDhg0NatYXL8a+99L6ULOev//+O126dGHUqFE0bNiQY8eOvRV/CAQCgUAgEAgEAsG7xpHHUajTXVMDD/1MeHGnCdVfjaNGUpO8kPbBczz0dl5L+Cj4KHbW3rhxg4iICM6cOUP58uUpVKiQ9FpCQgKXLl0iKCgoWzuEBIJ3lSFDhjB48GCdSbCslk4UfPgolUq6du3KwYMHpTP+Dh06xJQpUzh69Kjevl9//TWWlpbMmTOHuLg4qlWrRosWLfjss88oVqyY7Da6UKvVfPrpp+zevZsNGzYwadIkrdcDAwMBtEpZJiQkSIkhSC13WbZsWdm+0CQNNfN7eXmxYsUKevfurZW43rdvHydPnszQ//DhwwQEBABkuqNJo0ezuzI75ITetDue05M/f36KFStmVGI5rSYN5ubmekuOZlWfIdLrlxOLc+bMyXS8+/fvc+zYMa5fv46FhQUxMTFMnz6dZ8+eUbVqVfbt28fMmTPp3LkzKpWKoUOHsnHjRhYsWMDXX3/N4cOHcXd3x9XVlcjISL3aNet3584drl27JpU0NWaO6OhoJk2axOeff86gQYOA1IcYZs2axfbt2wkNDWXRokX88MMPtGvXjvj4eKmdHGbOnMmTJ0+oW7cuEyZMMFqfIUJCQli8eDFLly7F1dWV8PBw+vbtK+2ANIS+9SpVqhRTpkzhyy+/lB74+OGHH/jqq684fvw44eHh2fJNWjT//3p5eXHixAmSkpLo0KEDixYtYvfu3VhbWzN16lR27dol6+gMY8fLrh/Tr7Ou0sfPnz/n9OnTmJmZ8dNPPzF37lxatGihM44NxaUhsmuPxn9Pnz7l5MmTmJiYGNQcFRWlN16Mfe/p0nPjxg2OHDmCubk5S5YsYdOmTbLODM+qPzRnfL+PaHS/r/o15IUd77vPBAKBQCAQCAQfB2e9ovW+/jQICKpFZbvaWJV6hIf5OVSK9OldQVa4He1NQGIYxc0LGW4syDIfRbL23r17/P333/j7+7Ns2TKtpJVSqaRmzZpUqFAhDxUKBLmH5uyzxMRE/Pz8UKlUUok9gUAf3bt3Z8CAAcyaNYvXr18THBxMkyZNDCZrLSwsmD59Ol9++SX37t3j2rVrHDlyhN9++40tW7bg4uIiq01mKBQK5s6dS//+/enevXuGuQGio6OlRJuXl5d0Yzw5ORk7OzvOnTsn2w8HDhyQdldFRUWRnJzMpEmTMiRp0p8Vm5b8+fMDqeempi0PrSE2NrWMS048QJETeg2RmJho1NmHe/bs4dChQ1rXypQpo3WGbnqyo88QafVnJxYhNQFfsGBBZs2ahaurKw0aNGDNmjXS65s2bUKtVhMSEkJsbCzly5fHz88vW/q7deumVYLVmDk8PT0JCwujfv36UgK9YcOG/Pbbb0RFRXHv3j1UKhVt27YFUmO3c+fObNu2Lct6c9IH9+/fB6Bjx44A2Nra0qlTJw4cOCCrv771unLlCtHR0fTs2VNqr9mR6Ofnh5eXV477xs3NDYVCgbm5OQ4ODlStWlVaW0dHRy5cuJAr42XXj3L47LPPpCRn165dWbNmDb6+vlJp7LRxbCgudX1upiWn7OnVq5eU0OzWrRtr1qzBz89PetAmreZ79+7pjZf057sbslHX32WfffaZdN3Z2ZnDhw/LsiOr/nj27Jms8d9lPD0981pCjvCh2CEQCAQCgUAgEOQEj4LjeR2ZJKvty1A1hFahTEEnipbx4m7+0yQp5PUV6EaNmuOhtxlWXPeRdIKc4aNI1g4bNoxhw4YxZ84cvvjiC7GDVvDRsXPnTlasWEF0dOoTSJaWlkydOpUBAwbksTLBu4yjoyOlS5fm3LlzPHz4kC5dusjepQSpDwrUqlWLWrVqMXLkSAYMGMC2bdtYvny5UW10Ua1aNXr06MHChQuZPn26dL1cuXKYm5vj6elJxYoVAXBycuLmzZtAahlSTWlWuQwbNkxKGnp7e9OtWzcqVKhglC8qVqyIUqnk/v37OncOP3nyBDMzM+nBIQsLC527LMPCwlAqlVhaWuaqXn14e3sTGhpKlSpVZPcZPXp0riVejSUz/VmNRRsbGw4cOMD+/fvZsWMH06ZNo0WLFixevBgrKyu+++47jh49Srly5bC0tOTVq1d6dxTLoUiRItLParXaqDnCw8NRKBQZdgvXrFmT8PBwoqKisLKy0nqwzZjEfHqM1WeIyMhIrK2ttfSVKFFCdn996xUWFoalpaXWe0WTJIyIiMhx36Tvn/69bWJigkqlypXxsutHOaQ9v1XjR83fIaAdx4bi0lCyNqfsSbtrX5OUjYqK0qnZULykT9YaslFXVYW0D2UolUrUanlPhWfVH5UqVcryueZ5TUpKCp6enjg7O+fY/3d5QV7YERsbq1XCXCAQCAQCgUAgeNc4/Vz/rlpd+Eeq8L9fniKWYyhT1g9Pq5PEKWIMdxTo5HjoLZGszWU+imSthgULFuS1BIHgrePl5cWqVauYN28etWrVQqFQcPfuXRYuXEitWrWoXr16XksUvMO4ublx+vRp7t69y08//SSrT2xsbIZkoomJCcWKFSMxMVF2G0N88cUXuLq6au08s7a25pNPPuHnn3+mQ4cOGeZImyjICg4ODowZM4bZs2dz9OhR2Te1ixQpQrNmzVi7di0tWrSQdrwDJCUlsWHDBjp16iTprVGjBpcuXcqQ4Dx37hzOzs5a/XNDb2aoVCp++OEHqlSpYnDH6buILv3ZjcWYmBiSk5MZPXo0o0ePJioqin79+rFnzx4qV67Mzp07OXPmDMWLFwdg1qxZ+Pv76xxLswsxKel/T3ymLeGti8uXLxs1R+nSpVGr1fz6669SPCQnJ5OSkkK+fPnw8/MjMjKSmJgYKfGX9txVYzFWnyEKFy5MREQECQkJ0hnMxiQZ9K1X3bp1iYyMJDw8XEo0vnr1CoBSpUoRHR0t2zdZWcu3SXb9KAc/Pz/q1KkDIK13ZmXeDcWlIXLKHl9fX2rXrg0gla/Xp1lfvOhqr89GXaWks0pW/aFUKt/rRCekfn6/7zbA27XjQ/CXQCAQCAQCgeDD5oyBEsj6CIlVEfKoOAXyDcWlXAiPrE8RoQzNQXUfB4/j/HgeF0BFi+J5LeWD5aNK1vr7+7No0SIeP36c4Qbs+vXrqVatWh4pEwhyj7t379KzZ0+6du0qXStdujSvX7/m2rVrIlkr0IumdGXx4sVxcnIy2D44OBhXV1c6deqEq6srdnZ2xMTEcOHCBc6ePcuGDRtktZGDjY0NX375Jd9//73W9RkzZjB48GD69OnD0KFDKVeuHOHh4Vy+fJl9+/YxevToLPlCw+jRozl27Bjff/89ixYtkq4HBARw586dDO2tra2pVKkSc+fOZdCgQQwePJihQ4dSvHhx/P39+e2330hOTubrr7+W+owbN47PPvuMSZMm4ebmhomJCWfOnOHo0aP8+uuvb0UvQFBQEJ6enqjVavz8/Ni1axdPnz41WkNWkKNPV5uyZctKFTQM6Zcbi4GBgSgUCp1Jm/Pnz7NkyRK+//57HBwcCAwMJCYmBnt7e+kGuI+PD3FxcZw+fZoHDx6QmJhISkoKJiYm5MuXj/v371O1alXKly9PyZIl+eOPPxg1ahSPHz82WAbX2Dlq1KhBzZo1mTt3Lu7u7piYmLBhwwZ8fHzYtm0btWvXxs7OjqVLlzJ48GC8vLw4fvy4/IXLpj5NidzMqFWrFtbW1qxevZohQ4bw8OHDDD7SnF2taxe7vvVydnamRo0aLFq0iEmTJhEXF8eKFSvo1KkTtra2RvnGwsLC6LV8m2TXj3LYvn075cuXx8bGhjVr1lCnTp1ME5+G4vJt2bNt2zbKly+Pra0ta9eu1avZULwARr33chI5/hAIBAKBQCAQCASC94HHbxLwi0rO9jhRCWpuP7HDwrQfDcpF4WVzijfKgBxQ+PFwPPQW40t1ymsZHywfVbL2xx9/JCQkhHHjxmV4Sj+nS78JBO8KycnJ0g6ftFhaWhITI0o/CDJSunRpaddP4cKFad++PTVq1JBeL1q0KAULFpR+t7e3l86KLVq0KAcOHGDnzp2sW7eOiIgIKbm2d+9eqlatCiCrTdpx0+vS0LNnT86cOaO1u61QoULs3r2b3bt3c+zYMYKDg7GysqJGjRrs2bMHR0dHo3xRqFAhrWvm5uYsWLCA2bNn8/DhQ5ycnChdujTXr1/n+vXrGcaoXr06K1asoHTp0vz1119s376drVu3cuvWLSpWrEjXrl0ZOHCgVvnSihUrsn//fjZv3szatWtRq9VUqVKF3bt3S/7JzEc5qffq1atcvXoVhUJBoUKFqFevHsuWLcs0eSHXh+nRZYccfbraTJs2jTZt2sjSLzdeN2zYQP78+Zk2bVoGPZ07dyY2NpaNGzcSEhKCnZ0dY8aMoXPnzgCMHTuW7777DjMzM9zc3Fi5ciXTp09nxowZLF26lDFjxrBr1y4iIyOZP38+y5Yt4+eff2bChAnUr1+fL774QiuR4+DgoOWrxo0bGz3Hxo0bWbduHTNnziQpKYnatWvz448/AqnxsnnzZlavXs2UKVNwcnLiq6++YseOHXrXMC0lSpSQ1jwr+vRhYWHBxo0bWbt2LWPGjKF+/fqMGjWKdevWSW02bNhAeHg4P/zwg9HrtWnTJtauXcvUqVMxMzOjUaNGjBo1SpZvFAoFDg4O0hnVctZS0za93yC1jHDJkiVl+92Y8bLrx/Tjp7VdpVLh4ODA+PHjWb9+PT4+PlSuXFmrwk36OFYoFHrj0hA5YQ/AgAEDWLduHb6+vlSuXJl58+bp1awvXgCj3nvp4yf9fNbW1tLZuTnhD4FAIBAIBAKBQCB4H/AIjM/R8eKS1dx5bo2Z8lPql43Hz+5vfJXeOTrHh8rlyEciWZuLKNRyDz/6ABg4cCDTpk17b0o3xsbGSjfW9Z1PqCElJYU7d+5Qq1atXC1nldPzRF62NbpPwabhRvfxn1vRqPYl5j83eo7MMNZnxq69Ph4+fMjo0aPZuHGjtDPSy8uLcePGMXv2bJo2bZqt8QUCQdYYPnw4RYsWZcmSJXktRSB4r4iKiiJfvnyYm5sDqQnWM2fO8McffwCp5V7/+OOPDGeDCrT50PyYHXsSEhJwcXFh7969ODs7v1XduYUhf6RF83eno6OjwfOB31Xe1veg3CYv7MjJ7x0CgUAgEAgEAkFOM+/vQI4+icq18ZUKqFYqmfCil/EyuZ9r83wI5FeYcaX2dygVyryW8kHyUe2srVChAkFBQXktQyB4qzg5OfHpp5/y6aefYmFhgYmJiXRGn0jUCvKSb7/9loCAAJYvXy7dTNbw5MkTVq1aRbt27fj0008B+OWXX8iXLx+DBw+W2t2/f59jx44REBCAqakpDg4OdO/eXTobM7M2nTp1ks6S3LNnD+bm5ri5uQGwceNGYmNjWb16NUrl//748PPzY9GiRfz888/StZSUFE6dOsXVq1eJiIjAzs6OJk2a0KZNG62+uhg8eDDjxo2jXr16XL9+nejoaBQKBZB6bqC9vT0tWrSgVatWWj7L7NzLrl278sknn0i6Tp48ybVr14iIiJDOzG3RooWWrm+++YYOHTrQsmVLrbGeP3/OihUrWL58OZaWlhl8/+233/Lq1Svi4uIkvXZ2dtSvX5/69etL13bt2mVQb1qbTE1NsbOzo169enTo0CFDXOhDn2/WrFmDUqnUaYccfbVr15Z8q29eQ/rlxGtukJSUxKRJk/j6668pW7ZslvtPmTJFilFdKJVKHBwcsqwzMTGR169f6x2/fPny9OrVizp16vD5558TEBDA77//zqBBg6R2169fp127dlnW8a4hxy/G+l2tVue5H69fv87hw4dZuHCh3nYa+0NDQ9m1axdJSUl88cUX0uvvSlwEBQWxbt06EhMTmTdvnvSeK1GiRLbef+nJqfeJQCAQCAQCgUAgELwP3A/K2Z216VGp4Z6PKfi0xLl4c5KK3+SR6c1cnfN9JV6dhE9CCGXzF81rKR8kH1Wytn///sybN4/o6GjKlSundcOxcuXKWiUoBYIPicmTJ9OrVy8ePXpESkoKVapUydYNdYEgJ7h27RovX77k77//pmPHjlqv/fXXX1y+fFmr5KOnp6fWjo+DBw8yb948hg8fTocOHYiLi+PEiRNs2bKFAwcOULx48UzbbN68mcqVK2Nubs7jx48xMTHBw8MDSD3nOS4ujl27djFgwABpvujoaM6ePSv9HhkZyahRowgMDKRHjx5Uq1aNly9f8s0331C7dm3WrFmDqWnm/822atWKuXPnsnfvXh4/fkzTpk3p0KEDACqVCi8vLyZPnszw4cOZMGGC5LOyZcvSunXrDONp3tMRERGMGjWKoKAgPv30U6pXr46vry+zZs2iSpUqrFmzRiqtefHiRZ1nEYeFhXH27FmSk5N1+v7atWsULVqUN2/eSNdevnzJsWPHKFmyJGXKlMHMzIygoCCDeq9du0a5cuVo27YtiYmJvHjxguXLl7N27Vo2btxImTJlMvVhWvT5RvP/vS475OjTnD+Z2bxy9MuJ19xCpVJx9uxZPv/88yz1VyqV1KhRg6ioKFavXp1pOzMzM3755ZesyiQgIEBv4k4z/qZNm/jpp5+YOHEiBQoUYNiwYQwcOFBql/bnDwG5fknLvn37cHBwoHbt2jr7aEr4ZsePhuYwhL+/P5cvXzbYTmO/l5cX0dHRlClTRssfmcVF3bp1qVWrlix70pcgzgpr1qzh3r17TJw4UXrPaMpCZ+f9l56cep8IBAKBQCAQCAQCwbtOVEIKL8OT3tp8jwOUENAApyINMC15j3tmF1ErPprCtLJ4Fh8gkrW5xEeVrJ0zZw53797l9u3bGV77888/tW7oCATvM6GhocTExFCmTBlCQ0MJDAwEUs+BBIiPj+fhw4fY2dlRrFixvJQq+MipV68eBw4c0ErWpqSkcPToUerUqaO37++//86oUaMYN26cdM3NzY3ff/9d2vGpr02zZs1wcHBg4sSJWFpa8v3330uv16tXj9WrV+Pq6krhwoV1zv/tt98SEhLCwYMHsbGxka737duX7t27s3v3bvr376/Xhj59+tCnTx/c3NyoXr26tLtXQ5kyZfj2229xd3eXdsRqdstnxoIFC4iIiODQoUNaZwsPGjSI7t27s3LlSmbOnKlXlxzq1Kmj5VeA3bt38+2333L69GmUSiVubm4G9QJUrVpVy3Z3d3fGjBnDpEmT+Ouvv/Tu5kyLnLlyok965OiXE6/vKiYmJpLuLVu25No8ZcuWlTV+mTJlWLp0aa7peNeQ65e0HD9+nJ49e+ptk10/ypkjJ9DYP2LECJydnbV21aYlvT2jRo0iODhY1hzm5uacOHEiWzp9fX21qiFo3jMJCQnZGjc94n0iEAgEAoFAIBAIPhYeBCeQF6nS52+ANzWoYOuMTemneOQ7S7IiJQ+UvHs8iwugje2HcXzQu8ZHlaz9/fffMy1LqW/3k0DwvrF//37+/fdfNm/ezP79+zO9WTd8+HCmT5/+ltUJBP+jZcuWLF++nNDQUOzs7AC4cuUKRYsWNbjT0NTUVNotrjnXTaFQaJV5lNNGF3Xr1iUkJIRly5ZJSdy0xMTESOU70yZqIfVG+l9//SU9HJEdypUrR1xcHDExMbLOEQwPD+fYsWMsX75cK1ELUKRIET7//HN++OEHvvzyS/Lly5dtfdnVmxmWlpbMmTOHLl26cPv2bYOJ+3cNXfrlxOKGDRvIly8fQ4cO1TlucnIyf/75Jx4eHuTLl49u3bpRr149IPV8yj/++IPHjx9jbm5O48aN6dKli85Ed1JSEnv27MHT0xNTU1Nq165N9+7dUSqVJCcnM3HiRCZOnMjOnTtp2bIlLVq00CrjmpKSwr59+7h16xbm5uY0a9aM9u3bS+Pfv3+f/fv38+bNG4oUKUKPHj2oXr26LN9l1jc2NpapU6cya9YsSpYsCcC///7LmTNnpDNIw8LC2LJlCz4+Pjg7O1O7dm3++OMPvvvuO4M+0mV327Zts2WLIT1Z9YUhW1auXMl///1HWFgY3t7eDBkyRK/vMrPdmDk+//xzg3Gh8cfr16+pWrUqhQoVkuUHgB9++IEHDx7g6+vL69evWbFihdH6cnO90uv7/vvvpfeM5qG4qKgofvjhB3x8fKhUqRJDhw7F0tIyU/8b8mdu2iMQCAQCgUAgEAgE7wLPQnP24VdjeR2u5nV4JUpYO1Ks7Es8LE6RqMhbTXnNszj/vJbwwfJRZSiNOftOIHifGTx4sFTqbvDgwfTt21dnOzMzs7cpSyDIgJ2dHQ0aNODo0aNS0urgwYN069aNx48f6+07efJk3N3d+eSTT2jZsiUNGjSgUaNGWklCOW10oVar+frrr/nkk0/o3bs3devW1Xr9+fPnJCcn4+LiorN/TpQZV6vVHD58mIoVK2rpPXLkCPfu3cvQfunSpTx69AiVSpVppYg6deoQHR3Nq1evqFy5crY1ZlevtbV1puNpjid49OhRriZrs6rPEOn1y4nFRo0aSYlcXYwfP57Y2Fj69evHmzdvGD16NKtXr6Z58+a4u7tjZmbG4MGDCQsLY9GiRURGRmqV8k47TlRUFKNHjyYpKYnVq1dz+/ZtFi5ciFKp5OzZs8TFxeHi4oKdnV2GMq6TJ0/Gz8+P8ePHk5CQwPLly3n+/Dljx44lMDCQgQMHMnnyZFq3bs2jR48YNGgQ+/bto3z58np9pq+vnZ0dZ8+e1dpV6evry7///gukxt/gwYMpUaIEAwYM4NGjR0ybNk06mxrQ6yNddmfHFjl6suqL8uXL67XFzc2NP/74g44dO9KhQweSk5P1+k6X7Yb8lX4OQ3GhVqsZOnQopUuXpn///rx48YKNGzfK8gVA9+7duXLlClWrVpUqFhirLzfXK72+tO8ZTbL2+++/p0+fPlSrVo1169bh4eHB+vXrM/W/Pn/mlj0qlYqUlPfzaXGN7vdVv4a8sON995lAIBAIBAKB4MMlOObd+Fs1MFpF4IMyFLIYRbmyAdy3PkmMIiqvZeUJz+IC8lrCB8tHlaz98ssvdd78V6lUrFixQue5fQKBMQR0bZ7pa6UAXcX4ih++mOM60iZhzczMiI2NJSYmhpIlS+Lt7c3Zs2dp3Lix7N1BAkFu0r17d3799VcGDRpEXFwcf//9N1999ZXBZG2DBg04efIkR48e5cqVK3zzzTfExsbSq1cvZsyYQb58+WS1yYzixYvz+eefs2DBAvbt26f1WmJiIoBWou3Vq1dau3ALFy6s91zB9KRNGqpUKry9vYmLi2PNmjVa7SpVqkTbtm0z9Dc3N5fKbabf7atBcz0qKvt/UOaEXkPY2trKTpak16ShaNGizJ8/P9M+2dFniLT65cRizZo1Mx3r8ePH/P3331y+fJkiRYoAULNmTWkHtbu7O5UqVZLKdt+7d4/Lly9nSNY+evSI8+fPc/78eUqUKAEgnWc5bdo0KaabNm3KyJEjAe0yrk+ePOHkyZOcOXNGOo/X0tKSSZMmMXLkSMLCwkhKSqJBgwZUrVqVpk2b0rx5c0mzPvT1ValUevt6eHjw9OlTtm7dip2dHS1btsTb25vr169LbfT5SFN5Ja3djx49yrItcvRk1ReGbKlQoQKmpqaUKVOGcuXKERkZqXcuXbYbO4ehuHjw4AGPHj3it99+w87OjqZNm/L69WtOnTolyx8VKlTAysoKe3t76e91Y/QZIrvrlV6frtLHvXv3lt6PdnZ2DBo0SKuqRFr/G/KnoYpAWbXn2bNnsux9l/H09MxrCTnCh2KHQCAQCAQCgUCQHUJik/NaghZhcSrCHttjZT6YGuXCeFzwFOGKN3kt663yMiGYJHUKZorMNxsIssZHlax1dXWVygVCahnLU6dO0bx5c6ksnEDwoREdHU337t0ZN24cnTp1YuDAgZQtW5YNGzawf//+HCnVKhBkh3bt2jF37lyeP3/O/fv3qVmzJvb29rL6am54Dxo0iJSUFM6fP8+MGTMoUqQI48ePl90mM4YNG8b+/fv5/fffady4sXRds1Pq9evX0s/W1tY0b576wMbDhw+5dOmSUX5wdHSUSlzeu3eP69evc+bMGelGvob056OmReM3Hx8fqlatmuF1Pz8/rXYmJiYkJ2f8w1eTYNSXEMgJvfqIj48nKChISijKwcHBQTovUoOh3bFZ1WcIXfqzE4ve3t4ULFhQK1GYdmd38eLF2bVrF76+vsTGxvL48WNKlSqVYZwXL15QoEABLV0VKlRApVLh4+MjJcIye5jHy8sLpVKpVUo1ISGBmJgYAgICqFq1KhMnTmTIkCHY2trSuHFjevbsKWuXsr6+hhKOfn5+2NjYaMWfi4uLVnJKjo/S2p0dW+To0YehueWutzGkX3Nj5jAUF76+vhQsWFDLHxUrVsyW3pz0QXbXSw5pHwrVVF/w9/eX5kzrf0P+NPS3W1btqVSpUrYqCuQlKSkpeHp64uzsrLdCwbtOXtgRGxvLkydP3spcAoFAIBAIBAKBMYTEvRs7a9MTk6jm9lNb8pn0oUG5aF7aniFQ6ZvXst4KyeoUXse/oYJFsbyW8sHxUSVrdZ3z1L9/f/r378+YMWPyQJFAkPv8888/VKlShd69e3P48GEqV67Mli1bWL58OWfOnMn0bESB4G2RL18+OnbsKO2K7NatW5bGMTExoW3btrRu3VpnWVu5bdJiZmbG7NmzmThxolbys0yZMjg4OPDXX39JDwHZ2dnRr18/AE6cOJGlZG3nzp0B+OSTT7h16xbff/99pmdO66JKlSoULVqUgwcP6kzWHj16lPLly0s3+osVK8bLly8ztHv27BmFChXC0tIyV/Xq48iRIygUCq0kuSGqV69O7969c2T+7GJIv7GxaGlpSVxcHGq1OsM5tD4+PnTv3p2BAwfSq1cvrKys2L59OwEBGUvTWFpakpCQoDWOZheglZWV1C6zMvnW1taYmJgwZMgQreujR4+WziAdPXo0I0eO5P79+1y4cIFBgwaxbt06WWuZWd8aNWpkaBsXF6elN/0u7OjoaOlnuT5Kb3dWbTGkRw6ZzV2mTBnZ6w3oPLc4re/SatZgTEyB4bhIu/NfQ0xMjEEfZIax+gyRE+tliLTja6ozWFhYaGnQIOd9po+s2qNUKt/rRCekfra+7zbA27XjQ/CXQCAQCAQCgeDDJCT23UzWakhIUXPHywoThRv1yiQQWOQCr5Xvf8UiQ0Sr4vNawgeJMq8F5DWWlpZYWlri5eWV11IEglwhJCSEatWqAXD16lVp11nJkiUJCwvLQ2UCwf9wc3Pj9OnTeHh46HywJj3BwcEsWrQow2f3mzdvuHnzJlWqVJHVRg5NmjShadOm/PTTT1rXv/rqKw4ePMiff/6JWq2Wrvv6+vLXX39J5WmzglKpZMGCBRw7doy///7bqH4TJ07k999/58yZM1qvnTx5kj179vDVV19J17p168aBAwfw8PCQrnl5ebFp0yZ69eqV63oz4+LFiyxZsoSxY8caPF/4XSS9/pyIxerVq2NiYsLZs2elaz/99BNHjx7l/v37QOoZl3Xr1sXe3h4PDw+dJaRr1KiBiYkJFy/+rwT/2bNnKV68uKxdidWqVcPMzAyVSkXDhg1p2LAhFhYW3Lp1CysrKy5cuMCyZctQKpU4Ozszfvx4XFxcZJX01NfXysoKMzMzXr16BaTuPjt37pzUt1KlSsTExPDw4UOdrxvjIzl6DGFIT3Z8IccWhUIhnUNpyHe6MHYOQ3Hh6OhIYmIi//33n6QhbSwbi7H6DJHd9ZLD+fPnpZ+vXLmCjY1NpjtkDfnTEG/DHoFAIBAIBAKBQCDIbULi3q0yyJmRogaPV/kIutWBWv5jqJjsYrjTe0yiSv6RZQL5fFQ7a319fYmP1876P378mPv378t6Sl0geB8pXLgwd+7cITY2lgsXLkg7aV+8eCHKfwveGerXr09sbCwtW7bUu5tTQ9GiRTEzM6Nnz544ODhQqFAhYmJiePz4Me3atWPMmDFYWloabCOXGTNm8Mknn2hda9u2LStWrOD777/np59+onTp0kRERODj44Orq6tW+cqsUKVKFYYNG8acOXM4evSolPzdu3cvV65cydDe0dGR2bNn89lnnxEfH8+MGTNYtmwZxYsXx9/fn6ioKBYtWkS7du2kPv369ePVq1cMGDCAsmXLolQqefHiBV26dGHixIlvRS/A/v37uX79OiqVCn9/f0JCQhg1ahRjx441SkNWkKNPV5uxY8fStGlTWfrlxCvAhg0byJcvn86KB4ULF2bWrFl8/fXX1KxZk6CgIGJjY9myZQsWFhZYWloycOBA7OzsePPmDb169WLVqlVs2bJF2vENqTvAZ8+ezVdffUXjxo2Ji4vD09OTpUuXytpdZWdnx4IFC6QkmYmJCdeuXWPGjBlAavne7777jitXruDg4EBQUBCBgYF06dIFgF9++QUTExOGDx+eYWx9fZVKJT169OCbb77h0KFD+Pn5Ua9ePfz9/QEoX748vXr1Yvjw4TRr1gwfHx8qVapEUFAQAHXr1tXrI10+N2SLPgzpyY4vzM3NDdpSsWJFVq5cyX///cecOXP0+k4XcvyVfg59cVGmTBkGDhzImDFjaNCgAT4+PlSsWJHXr18b9GVO6cvN9dKH5mGe4OBghg0bho2NDRcuXODrr7/O9GxsQ+8zQ8ixRyAQCAQCgUAgEAjedWISVXktwSjUwANfE/BtRo1iTVEVv80Ds6t5LSvHSVS/2zue31cU6rTbgT5wPvvsM+7evat1zczMjCFDhmjtNHpXiI2N5eHDhzg5OclKXqSkpHDnzh1q1aqVq+WscnqeyMu2Rvcp2DTc6D7+c407G63E/OdGzxHQtbnRfYofvpjhmrFrr4/o6Gg6d+5MREQEDRs2ZMOGDZw+fZoZM2awf/9+ypQpk63xBYKscvXqVRwcHKQzX+/fv4+tra20u+/+/fuYm5tTuXJlADw8PDAxMdE6109zTmFkZCRWVlY4ODhQuHBhrXkMtUk/bnpdadsFBQVpJTsBVCoVjx8/JigoCCsrK5ycnGTtfErvi2LFiknnGGqIj4/n0qVLODk5UapUKa5evZppKUtbW1utc9nj4uJ4+PAhkydPpk2bNsyYMSPTxEBYWBiPHj1CrVZTuXJlihYtmsH29D7KKb3p2xQqVChLn32ZaTJkh7H6NNSo8X/snXd4VMX3h98t6ZWQAoEQIBBaKEqR0IsYkN6kV6UXld6VIkV6UwEBEUWRIgQpYkRq6Bg6AUJLSIVAes/+/sgv12x2syWFAN95n8fH7L1nZj5z7uyye8+dc7woVaqUUfr1rcWrV6+iUCi0pvzNJjo6msDAQMzMzKhVq5ZUVzg+Pp7r169jYmJCrVq1MDU15dKlS5iZmVGjRg2OHTtGgwYNpCD6ixcvuHfvHiYmJnh6eqqtWT8/P+rVq4e9vT2QtcZzt4+NjeXu3bukpaVRvXp17OzspPaZmZncvHmT6OhoSpQoIe0Khqwdo4cOHWLJkiVa56erLWR9Ljx//hwvLy8yMzO5c+cOTZo0kc5nvxe9vLz4+++/2bp1KwcPHtTro5o1a2rM2xA9+tClpyC+0DeX+Ph4/v33X1xdXaXasLp8p23u+RlD17oACAoK4unTp3h6emJiYsLNmzdp1qyZQb68cuUKdnZ20lj50VeU1yunvpzvGUtLS44fP06jRo2k+r0eHh5qD8xp878h/izIfHKS/b3T09PzjcxmAK/ud1BRUxzzKMzfHQKBQCAQCAQCQWHivek+6W9WvFaDCg4yzMvc4obJcVSytyMUt7LSx7Swr6HfUGAU/1PB2ri4OI30aHZ2dsjlr2c2aBGszRsRrDWOmJgYgoKC8PLywtTUlGvXriGTyahZs2aB+xYI3gQCAwNJTU3VuuaTk5O5c+cOzs7O0s3zR48eIZfLKVeunJrty5cvCQ8Px8TEBFdXV7V6g4bY5O43MDAQhUJBpUqVtGqqU6eORv9Pnz4lJiYGBwcHSpUqpXfuy5cv58iRI+zfvx9LS0sCAwPV6lXK5XKcnZ1xcXFRq22Z2y4npUuX1ghmZ+sqWbKkxjmAW7du4ezsjKOjo9rx+Ph47t+/T82aNVEoFFp9VFh6c9ooFApKliyZrwwDusbKvmb65pGXPnt7e63+y92HIfoNWa+vmsOHDxMSEsKwYcMKtV+VSsVXX31Fu3btqFu3LgATJkxApVKxcuXKQh2rsPQUlS+MJTo6mvDwcKlkgiGEhoaSkJAgPUzzppPX9UpJSWHMmDFUr16dw4cPc+HCBSZPnvzaB7SMfT+IYO3rgwjWCgQCgUAgEAgE//E2BGuzOfh0HlZez1DFnTeqXUKKjLBY7fGrio4ZyGVaTwEQnSAjJV2Gi22mmp1KBeFxckpaZmKaK/duchpExskp55C3483f/wmle7s8zwvyx/9UGuTsmw9xcXGEhoZib2+vdqNXIHhbsbOz491335Ve16r1dufNFwhyM2XKFO7cucPhw4epWLGi2rkDBw4wa9Yshg4dytSpUwFYsWIFlpaWLF68GMiqLTp16lSuXbtGuXLlSE5OJiQkhI8++ojp06cjl8u12jx58gQXFxc8PT0BuH79OgqFQgqKXLhwgeTkZPbv36+28+vJkyf06tWLwMBA6diRI0dYvnw5z549w8HBgaioKMqWLcvs2bPx9vbOc+7Dhw/n77//pkOHDlSqVElK0+vg4ABk3RgODw+nbNmyLFu2TKqfOmXKFCIiIjR2egEMGjRISq175MgRli5dSnR0NCVLluTZs2e4ubkxdepUtR2PI0eOZPjw4fTv31+trzt37tCvXz8uXryIra2thu8/++wzgoODpV3BKpWKlJQUzM3N8fLyokSJEqxevdogvVOmTCEqKgoHBwdSUlIIDQ3F2dmZkSNH0qtXrzx9mBtdYx08eBCFQqExD0P1+fj4MHr06DzHNUS/Ieu1uChXrpzauigsZDIZjo6OjBw5Em9vbyIiIoiKiuL7778v9LGCg4N1pjk3MTFh9erVODo6Mnz4cBo0aEB0dLSGnsLyRXh4OObm5lrXliGcOnWK1atXG1zTdM+ePXz55ZfUq1ePrVu3Flifof7ML8Zcr9zrp0+fPowdO5Zjx45RunRpfv/9d3r27GlUYLuwKch8iuL9IBAIBAKBQCAQCARFhVIuIz3zzd9rWEaWSOa/D4n7F0y8WmD+TjyquEsGtb0ZrmTeYWu1Y+mZEBWv4MSnz7E20/RPchrM+sOGi09MsDRRYaKEld1i8XDMIDkNRvxqR7kSGQRGKpnfPo4qLv+lNV5xzAoX20w+9ta+4QAAuYlhExcYxf9UsDYlJYVp06Zx6NAh6ZiHhwdLly5VS6spELxN7N27ly1btmg916lTJ4YPH/6KFQkExUP58uXZv38/n3/+udpxX19fypcvr7PtggULkMvlnDlzRgoaBgYG8sknn9C6dWsaNmyo1ebatWsMHz6cpk2b4uXlxbJlyzA3N2fUqFFAVkpQU1NT5s+fzw8//JDn+IcPH2bSpElMnz6dXr16YWJiQlJSEuvXr2fYsGHs2bNHCrLmxsbGht9//52rV6+iVCr58ssv6d+/v1pAMCkpiSlTpjBp0iQOHDggHR84cGCegUOAQ4cOMWXKFKZPn85HH32EiYkJqampbNu2jeHDh7N582adgWRDUCqVdO/enR49ekjHUlJSWLNmDWFhYVKA3RC9gNrc09LS2Lt3L0uWLOHZs2eMGTPGYF2GjFUYbXJjiH5D1mtxUZTft0aOHEmXLl24d+8etra2VKtWLc/U3wXByclJeg9rIzsYPnLkSG7fvk358uVp1aqVhp7C8sXq1atp3rw5bdu2LZT+9OHn50evXr2YNWuWQfb69Bnqz/xizPXKvX4OHz4s2dWpU4eAgIACaSkMCjKfong/CAQCgUAgEAgEAkFRYa6UkZz+5gdr66oipb/TbkSSdgNM322FWY3nqOKu6mgJDdzT+GPkC7Vj605aEhoj1xqozTpvRWS8nMOjorE0hWV/W7HtvAXz2sdz4r4pbiUymN8hniO3TPn5UtZxgIAQJVdDTfjp/Ze6JyT/nworvjL+p7y6bds2QkND+emnnyhXrhzx8fHs27ePCRMmcOTIEbHLVvBWUr16dfr16ye9Tk9P5+rVq8TFxdGiRYviEyYQvGJatGiBr68vn332mfR5Hx4eTmBgIM2bN9fZNigoiA4dOqjd6K5SpQqnTp3SaVOrVi3OnTsnvbazs8PS0lJKx2xubs6gQYNYtWoVhw4d4sMPP9Q6/tKlS+nevbvarlQLCwsmTZpESkoKz549yzNYC2BmZkaDBg0AtP5bZ2FhQd++fRk8eDDx8fFYW1tr2OQmIyODxYsX06tXL7XPGFNTU4YNG8adO3dYvHgx+/fv19uXLuRyOS4uLhoprEeNGsXgwYNxd3fPd98mJib06tWLjIwMFi5cyEcffaRRr/d1Ji/9hqzXhw8folAoNFJ95yQyMpJnz56ppbbOyMjg+vXrVK1aFXNzcyArjW5kZCRVq1aV2sbFxfH06VPc3d1JT0/n8ePHarV4k5KSpB3TZcuWlWrvqlQqrl69SvXq1YmIiMDS0lKq66tNT25KlSqlNT24Pj36yD12zvWY11zu37/P/fv3qV69OjY2NigUCgICAvL0na656xrj2rVrlC9fngcPHkiZA9LT0yV7V1dXjfd9bGwsoaGhRtetv3//vrS7+/r165IfjNWXE3Nzc433d+7rdePGjUK7Xtm+USqVuLq6qqWaLVWqFJaWloSGhqqVToH/1qanpydmZmY63wc5r2V8fDwRERGUL18eCwsLkpOTefToES4uLpQoUcKg+eTsLzExEaVSaVB/VlZWODk54e7uTkpKCnfv3jXKjwKBQCAQCAQCgUBQnFgo5bzkzc+DXC01QuNY6pVwUq+AWYPWmFYJRxV306C+Hj1XsCfAnN+GvNR6Pi0DfK+bMbd9PJb/f1toUusE6XzISwVl7bN8WrZEJsFXFFK7hUetmekTj4meiiwyM3uDtAqM438qWHvlyhWmT58u1ZNzcXFh4sSJnD59mtDQUMqUKVO8AgWCIqBq1apqN9ABBgwYwPTp04mOji4mVQLBq6dmzZr89ddfnD9/XtpZ6OvrS+vWrdFXvt3b25stW7Zgb29Pq1attAb0DLHRhrm5OVOnTmXRokU0b94cKysrtfOPHj3i6dOndOnSRWv7mTNnGjSOPiIiIjA1NZUCD5AVzNa2k8zLy4t79+4RERGhtuM1Jz179mTQoEGEh4cbVFu3qPVmB4+00aNHD+bPn8/58+fp0KFDoWstqD595NZvyFrcvXs35ubmjBs3TuNcWloa48ePJzAwEDc3Nx4+fEj16tVZs2YNycnJ9OrViwMHDkjpvf/++282b97MkSNHANiyZQtr1qyhRo0axMbG0qhRI/7880+OHz8OwK5du1i2bBmVKlXixYsXpKSksGnTJipWrEh6ejq9evVi1KhRbN26lc8//5x+/frlqceQnYL69OhCly9MTU11zuXQoUM8efKEY8eOIZPJ6N27t07faZv74MGDjRpj+PDhnDhxgpkzZ1KuXDlSUlJISEhg9erV0gMdW7duZc2aNdSqVYsXL15ofEfQxR9//EFoaCiJiYmkp6ezZMkSo/UV5/Xy8/Njzpw5lC9fnrS0NCIiIli6dCnvvfeeXt+kpqbSq1cvdu/ejbu7u85rqVKp6NWrFyNGjODEiRMkJSURHx/P3LlzWbt2LaampgQGBrJ27VqDHpzLT38F8aNAIBAIBAKBQCAQvA7YWygIi08vbhkFplxCWJ7nUi6EkXIBzJu0waT8Y1Txd3X2teaEJX3qJuFkoz2I/ei5goRUOfXLpRGbLCMhRUYp20yyn+E2U6pISM16kZoO5iZZ90S3nbfgnbJp1C6TTmScHBvzTCzyyHYstyqrZ8aC/PA/FaxNT0/HxERzhVlaWpKSklIMigSC4qNq1apqQSuB4G1HJpPRsWNH9u/fL637AwcOMHPmTPbt26ez7aRJk7C3t2f9+vXSjf5mzZrRt29fKlSoYLCNNlQqFe3bt2fnzp2sW7dOLa0vQFRUFIDaA0WJiYncvfvflzdTU1OjaijmDBpmZmby4MEDVq1axYABA9SChn5+fly5ckWj/Y4dO4iMzErhktfOvOzjERERBQ7WFoZeW1vbPPs3NTXFxcWFZ8+e5UtTNmZmZlSrVi3PNvnVp4/c+g1Zi5MnT86zv1u3bnH69GkuX76MqakpqampfPHFFzx69EjvtYyMjGTFihWsX7+e5s2bk5CQQO/evdVS2Z4+fZpFixbRqlUrAD755BO+//57Fi5cKH1Pe/jwIRcvXsTU1JSrV6/mqSc7UFYQPbrQ5QtPT0+dcxk/fjw7d+5kyJAhtG3bltjYWJ1jaZu7Pn9pG2PKlClMnTqVbt26AbBmzRpmz57Nb7/9RlRUFMuXL2fDhg00btyY9PR0Bg8ebJAvIKuGdEBAAHXr1pUC/cbo00dRXi9nZ2emTZvGl19+KT2U8d133zF9+nSOHj3KixcvCuSbnGTrffnyJfv37yczM5M2bdqwZs0adu3ahbm5OTNmzGD37t0GBWuN7S+/fszMzCQjI0OnzetKtu43VX82xTGPN91nAoFAIBAIBIK3l7K2JtyOevPjNiVfhOq1ST79lOQzSsxb+GDiehdVwkMNmzsRCi4Hm0hpi7XxLEGOqULF5rMWnLhvSkq6DJUKFnaMo07ZdGqXSWfJX1akNoZTQaa8UzaNJ9FyfG+Y8/PAl4zbZYuJQsWTFwomtU6gYXn1rFMoLZFZOBrtA4F+/qeCtV5eXnzzzTcsWLCAEiVKoFKpOHz4MI8ePdKZBlAgeJN5+fIlz58/VzsWGxvLvn376Nq1azGpEgiKhy5dutC9e3fmzJnDo0ePiIuLo0GDBnqDtaampowePZrRo0cTFBTE+fPn8fX1pXPnzmzevJn69esbZKOLOXPm0L17dynAkk32TtvY2Fgp9WtwcDATJkwAstKPWlhYcOzYMYP9cOzYMa5ezaqJER0dTUJCAjNnztQYO3dt25xYWFgAWelKtaVNjouLA9D6kJQ2dJUiKAy9+khKSjIo/XM2f/75J2fPnlU75urqyrZt2/JsUxB9+sipv6Br0cPDAycnJ8aOHYuPjw8NGzZk0aJFAHoDjrdv30ahUEipxa2srPDx8WHv3r2SzerVq0lKSuLhw4ckJibi6OgoBf+zyZnGWZcefRiiJ7++MHQuxpI7hbUxY1y/fp3Y2FjKlSsnPUzg4eHB+vXriYmJ4datW8hkMho3bgxk1YRu06aNznWrj8L0QVFerzNnzpCcnKyWbv7DDz9k5cqVhIWF8eDBg0L3Tbt27YCsYKu7u7ta2uQKFSrwzz//FEl/+fXj/fv3jdLzOnL9+vXillAovC3zEAgEAoFAIBAICoKbrWH3lF53LKOCDTNUQfI/wSTLLbFo7YPS6RaqxP/a7rxiQbvqKXnWqs0mLQOcrDPZ+8lLANYct2TmHzYcHPmCmq7ptKuewujf7KhQMp3hjRL5fK8tnzZP4P4zBUlpMtb2jOVKsJLvTlvRsHyMWt8yK1etY4aEhGBjY4OdnZ3a8cTEROLi4rSWs4qLiyMlJQUHBwetDxcb2mdISEievnB0dFTLyvc68z8VrP3kk08YOnQo3t7e2Nvbk5iYiKmpKUuWLClQ+kGB4HVmz549fP3112rHZDIZderUoXPnzsWkSiAoHipUqICHhwd+fn7cunWLjh07GrxjKxsPDw88PDzo06cPgwYNYseOHRrBL0NsclOpUiX69u3LvHnzmDNnjnS8fPnymJubExAQQOXKlYGs+qPZwdkjR45ovMf10bdvXyloGBISQocOHbC2tjaqdnulSpVQKBRcu3aN0qVLa5y/ffs2ZmZmUo1KKysrXr58qWH37NkzFAoFlpaWRapXF3fv3uXly5dG7U4eNGhQkQVejUWX/vysRWtra/bt28ehQ4c4ceIES5YswcvLi5UrV2r1ec404vHx8RrX0tnZWfo7PT2d2bNnc+rUKby8vLC0tOTevXtqNoBa7U1denJ/Yc+NPj360DW2lZWVQXPRhbYU7Dnnbqi/somLi0Mul/Ptt9+qHW/SpAlxcXHEx8dLD1pko+u9pw9j9emjKK9XbGwsFhYWap/5OR86KahvtF3LnP3JZDK113K5XG8K/vz2l18/VqpUyaiHVl4nsutp16xZU60O8ZtGccwjd7YOgUAgEAgEAoHgdaGMjmCtKi0F5HJkCu02qrRkkCmQKXUHfDOTYiFTPdWyTGmGzOy/MmWqtGRkJpoBP1VmBqrkeOSWed+bsCUV2TPNmrW6RalI+isYlHZYflAdhd1VMhLDOXHPlK+7xOlsWtIqExUy2lb7b0dyl1rJbLtgSWScHGebTPrVT6Zf/WQgq76thYmK1lVSOXDDjHIlsjLvuNln8jha856p3Fp7hr3WrVtTrlw5Dh48qPYA+l9//cWWLVvYv3+/dOz3339nw4YNPH78GFNTU1QqFe+//z5TpkxRy+hmaJ+tW7fG0tJS62+olStX0rRpU50+e134n4pQWltbs3PnTq5evUpwcDC2trbUrl0be3v74pYmEBQZ/fr109hBa2VlhZmZWTEpEgiKly5duuDn58fVq1fZtGmTQW0iIiI0ngCTyWTY2NhIwStDbPQxduxY2rZty59//ikds7S0pFOnTnz77bf4+PhopMstaO3psmXLMm7cOObOnUuDBg3UAkW6cHBwoHXr1qxbt44WLVqofaYkJyezYcMGOnfuLD29Vrt2bY4fP86YMWPU/HH06FHeeecdg29K51dvXqSnp/P1119Tq1Yto4K1rwva9Bd0LUZHR/Py5Ut69+5N7969pTq1u3bton///gBq5SMePXok/e3o6EhMTAyJiYlSsOjOnTvS+TNnzvDHH39w8uRJ6dpNmzZNSvdtrJ5PPvlE51z06SmILypXrmzUXLJ/WOTlO20Y6y93d3cyMjJYuXKl9FmRmppKUlISdnZ2hIWFERsbS2xsrHS+ILsp83M9dVGU18vb25vY2FieP39OyZIlgSz/y2QyypYtS0JCgsG+yc+1fJXk149yufyNDnQCKBSKN34O8Grn8Tb4SyAQCAQCgUDwduJmpxlozYh6RPJfa8iIeghkoihdDQufz5HbZd0HSQ+5QfLf35AZGwGZGZhUaYZ5m3F5BnUTdnyOKj4acjzYa1K5MRZtJ6DKzCDJd0FWUDYhGot2k1A4lpfsUs7+DGnJmLcYnucc6sqeg5EP6kqkZ5J4KBjMnAny8iAhNZDaZdJ0NqlQMgMbs0yCnilxsMqyfZEkR4YKG3P1OrcvEmVs8rdkU5+s3bNmShVp/18lJS0TzLS4TJZHsBayHmLeuHEjY8eOzdNm48aNfPPNN8ycOZMOHTpgYWFBcHAwixYtonv37uzbtw8nJyej+gRYsWIFLVu21GnzuvM/E6w9e/Ys3t7e0o7COnXqEBAQQHx8vAjWCt46oqOjiYjQ/8SOg4OD1hQEAsHbTPv27VmxYgXlypWTdqrqIioqik6dOuHt7Y2Pjw8ODg4kJCRw4sQJTp06xZYtWwyyMQQrKyumTp3K7Nmz1Y5PnTqVjz/+mG7dutG/f3/KlStHTEwMp0+fxs/PT0qJnF8GDx7MH3/8wYIFC1i+fLl0/PHjx5w8eVLD3s7Ojtq1azNr1iwGDRpEr1696N+/P6VLlyY0NJTt27djaWnJlClTpDZjxoyhZ8+efPLJJ3Ts2BGFQoGfnx8nT55k+/btr0QvZKWQ9vf3JzMzk7CwMHbu3Mnz588NvkYFwRB92myqVq0q7YrTp9/Qtfjw4UMUCoXWMhBXrlxhzpw5zJkzhwoVKhAREcHz58+lXd7u7u788MMPDBkyhMDAQM6dOye1feeddyhRogRLliyhf//+3L59G39/f+m8lZUVmZmZ/Pvvvzg6OnL06FEePXrEy5cv1YJkhurRhz498F/Azt3d3aixDZmLhYUFly5dws3NjRo1auj0nTbyM0bDhg2ZMmUKo0aNQi6X8/333xMXF8eWLVuoU6cOLi4uzJs3j/79+xMUFISfn59ePxamPl0U5fWqUaMG9erVY/bs2YwdO5bExEQWL15M165dsbW1Nco3+t4HxY0hfhQIBAKBQCAQCASC153caZBVmRkk7vsSk0qNsOz1NWSkknhgEcnHvsGy61xUKQkk+X6F6TsdMW3YB1VSLIm/zyHl3K+YNx6gfZDURCy7zEHp/o7GqfRHlwGw6jaPtMCTpF7YhcWHkwHIeP6EtDsnsR6wVuccvNLC8zHzXKSkc+dYKKVNlCiVPmByHlJfSqdDY+SYyMHJJhMTBQx8L4lFR62Y/H4CJgpYccwKn2opWOQKvq78x4q+9ZIoZZsVxK1ZOp31J61ITIXTQaa8W1YzMCy398xT5sSJE5kxYwadO3fGzU0zqPv8+XPWrl3LxIkT6dmzp3Tczc2NVatW0b59e9atW8fcuXMN7vNt4q0P1mZmZjJx4kT++usvTp48iYODg3Tun3/+4aeffuK3337Dw8OjGFUKBIXL77//blBa1KFDhzJ16tRXoEggKF6qVKki7fqyt7enW7duVKtWTTrv5uamFiQqX768tFPUycmJAwcOsHv3bnx9fYmNjcXa2hoPDw/++OMPKdhliE3OfnPryqZDhw6cPHlSbZeWtbU1P/30k7SDzc/PDysrK7y8vDh48CBly5Y1yhc5U4pA1q6aefPmsWDBAm7fvk21atWoUqUKDx8+ZN26dRp9VK1aldq1a+Pi4sLu3bvZtWsXfn5+nDp1iqpVq9K7d2969OihlqLEzc2N/fv389NPP7F//35UKhVVqlRh//79agFDbT4qLL1VqlQhKCiIVatWIZPJKFGiBD4+Pnz00Ud60+nq82FutM3DEH3abMaNG4ezs7NB+g1dr7t378bc3Jxx48Zp6Hn//ffJyMjg4MGDPH/+HAcHB2bMmMH7778PZKWQ2bhxI0uWLKFevXpMnjyZHTt2AFk7Drdu3cqGDRuYN28eDRo0YNiwYXzzzTcA1KtXj6lTp7J9+3ZMTEzo3Lkzffv25csvv2TlypV88cUX1K5dWy0Vqz49utCnB+C3334jPDycFStWGO0LfXP57LPP2LlzJwcPHqRGjRo6fQdozN0Qf+Ue47vvvmPr1q2sX7+etLQ06tSpI+1ANjExYdu2bXz77bcsX76cqlWrMmfOHH755Re9vsymUqVK0vrPj77ivF4bN25k8+bNrFixAhMTEzp27CjtFtfnG5lMRu3ataWdqoZcy+ya45CVkjzn54azs7NBDwzlpz9D/CgQCAQCgUAgEAgErzuOVkqcrRREJvz/ds/URExqtMGsbhdkCiUolJhWb03yiazMeRkR91GlJWL6Xi9kMhkySzvMGvQi+fjGPIO1qtREZKbaS+BkvniK3CErQCh3cCPj4u6sNioVyX+txbzlcGSmFlrbZlMhsRCCtUCmCjxNFST8HozMpiKWPiWRyc5BWhybz1pSyjaDYY2SABjyXhJWpio2+VuikEGLyikMei9Jrb/7UQrikmX0ejdZOlbaLpPhjbNq2DpaZTKpdYKGDoVzvTw1VqlShc6dO/PVV1/x3XffaZw/ffo0GRkZ9OnTR+OcqakpH330ET/88INasFZfn9k8f/5co3atUqnUe//udUKmMrZY0hvGoUOHmDt3Ltu3b8fTUzPqv3DhQm7fvm30rp5XQWJionQT2pCaWRkZGQQEBFCnTp0iTWdV2OPEnrE3uo1t45dGtwn7wriAfOm5QUaPEd7R+PznpQ6c0jhm7LXPTVpaGqmpqXrtTExM1IIpAoFAUBCGDx+OlZUVK1euLG4pgmLk6dOnlChRQvr3a8OGDZw4cUItkPU66bl9+zZ79uxh1qxZxaJPoI64XoWDMe/D7O+dnp6e2NjYvGqphcKr+h1U1BTHPAr6u0MgEAgEAoFAIChKvjgWwaF7eddpTT7zIxnB17HqvZT0pzdJ/G0aNmN3STVm0x//S+KeWdiM3onM3FqtrSojjbjVXbAa9C1ye1fIzEBm8t+D96n/HiAzJhzzFsPICL9H8j/fYdVnOanXDpP++F8sO87Iqp2rNM2z7NTPwd9je/VMIXhCE1kJS6za2EPGGchI0mtfYBRmWA14hEyhGU+oUqUKhw4dwtHRER8fH7766itat27N/v37pfqyGzZsYOfOnRw7dkxr935+fowZM4br169jampqUJ/ZY1tbW6NUqu9NdXZ25sCBA4XvhyLird9Z6+fnx6BBg7QGaiFrt4q3tzfR0dFqu24FgjcZExMTTEz+y2sQFBTEs2fPeO+99wC4fPkyMpmMd999t7gkCgSCQiYpKYnAwMA8z8vlcmrVqlWkGoYMGcLQoUOpWbMmtWrVMqoWbU5mzpxJaGgo3377rVTzNpubN2+yePFi2rVrR9++fQFYs2YN5ubmDB/+X42Qc+fOcejQIcLCwlAqlVSoUIGePXtSoUKFPG3c3NyoU6cOrq6uQNYOPlNTU7p06QJkBTuUSqW0Ky+b4OBgZsyYofbgV0pKCvv37+fcuXPExMRQokQJGjduTPv27Y16SGbmzJk8efJEei2TyXB2dqZZs2Z07NhR+jGQ2y4n3bt3l+aQkpLCvn37OH/+PDExMZQsWZImTZrQrl07tTmNHz+ejh070qZNG7W+AgMDWbBgAd999x1WVlYavp8xYwaHDh3CwsKC0qVLk5qaypMnT2jXrh0qlcoovTltFAoFJUuWpG7dunTu3BkrKyuD1nzNmjXp2rUrCoVC0vPo0SNcXV0ZMGAAP/zwA1evXiU+Pp6NGzdK8zBUX/369SXf5kaf/pwYsl6LmqL+DDH0eo0aNYoKFSowbNgwwsPD+fHHHxk9erRkd/XqVdq2bZtvHcZw5swZdu/ezcqVK0lNTeXjjz9m7ty5VKxYsdDGKAq/q1QqvX4UCAQCgUAgEAgEgjeBemUs8gzWpj+9SeqV/Vh2mweAwqUyMhsnkv/+BjPvfmQmvCDlXFa2JFVKgmawNiURgOS/vyEj8j6kpyF3qojFB+NQOFVEXqoyqbeOoVJlkh58FUXpKmQmRJNy4Tesei8n6c9VZL4IQZUcj3nrMSjdampotH4WonGssFC9SCT+t0TkTjWxbG0Fqf6QmVJk48md6moN1ObEzs6OiRMn8tVXX9G4cWO1c+bm5iQmJubZNjExEaVSqRF01dVnNsuWLRM1a193IiMj+fDDD/M8b2NjQ8mSJYmIiBDBWsFbycuXL+nbty+fffaZFKyNiYlh0qRJ7N+//63P9S4Q/K+gr+6qiYmJWn3XosDb25vly5ezd+9eLly4wJo1a/IVrL1x4wZPnjzBz8+PDh06qJ3bs2cPN27cwMvLSzp2//59td1Av/76K8uXL2fMmDG0a9eOpKQkDh8+TPfu3aXPPW02e/bs4aeffqJRo0ZYWloSEBCAQqEgOjoagEuXLpGcnMyPP/7Ixx9/LI2XlJTEhQsXpNfPnz9n8ODBpKWl0atXL1xcXHjy5AkrVqxg7969bN682eCA7Y0bN/D09JS+y2RkZPDgwQO++uorbt26xbRp0yS7SpUq0a5dO40+sks9ZOtKT0+XdIWGhrJ69Wp27NjB999/L6XgDQgIoEGDBhp9xcXFceHCBTIyMrT6/ubNmzRt2pS0tDSePn2KpaUlLVu25J9//mHJkiVG6c0595SUFB4/fsz27dvZtGkT33//PWZmZgateUdHRzIyMkhNTcXS0pLevXvz3nvvIZPJkMvl9O7dG39/fx48eKDmd0P0lSlTJs/x9enP7seQ9foqKOrPEEP737RpE5s2bWLJkiXY2toyadIktYB47969863BWJ49e8bVq1eBrIC7j48P9vb2hTpGUfhdJpPp9aNAIBAIBAKBQCAQvAnUd9WeZjgt6BxJR1Zi0XYCyjJZJXdkSlMsu80j5dQWEnZPR16iLKZ1OpD09CYoTDQ7kckwqdUOpfs7KCs1gvQUkv3Wkei7AOshm1CWropJxfok/joZmWUJzD8YlxUIbvARqqQYMiLvYz1gHekhN0g58yPKXuplCU3IQB7xtNB9kpvMqHjif41H4foOFi3MIfkMZGrWmy0oStdmBtn16NGDXbt2sWHDBrWH0CtVqsSLFy8ICwujdOnSGu3u3r1LxYoVkcvlBvf5NvHWB2utra159uxZnueTk5OJjo7WqBkoELwtHD9+nIYNG6rlgm/VqhUdOnTg6NGjagEHgUDw5lK2bFnWrFlT3DL48MMPdT4kZSjvvfce+/btUwvWpqenc/jwYerWrauz7W+//cawYcMYPHiwdKxVq1bs27fPIJu6devi5ubG+PHjsbS0ZPHixQB07tyZRo0asX79ejp06ICLi4vW8efPn096ejp79+5VC2R27dqVTp06sWvXLvr162ewLypUqKDxdKCTkxNffPEFkydPlgLiHh4eOuu4fvHFFwDs3bsXC4v/fuz07NmTLl268PXXXzNv3jyDdeVFtWrVNHbw/f7770brBc25DxkyhLFjxzJ+/HgOHDhg0Jo3MTGhQ4cORu8qNESfPvTpl8vlBq3XV0FRf4YY2r+Li8trmeJYoVBI9W0Lk6Ly++vqR4FAIBAIBAKBQCAwhlI2JrjZmhAc+1/wMfXaYVJO/4hl59koy3qp2SscymLZeY70Ou3BBVCYILO00+hbbmGLxftj/ztgYo5ZowGkbR5K5stQFA5umHn3xcy77//3dRFVfDQmNduSfu80codyWf2ULEfm82CN/uvIoiE9vUDzN4aM0Fjid8SidK+PRRM5qsSzoMootP4VBgZrZTIZc+bMoV+/fmr3Yt577z1cXV1ZvXq1dK8tm+joaH799VfGjh2buzudfb5NvPXB2oYNG7Jjxw66du2KmZmZxvlNmzZRtmzZN6rQsEBgDCkpKTg7O2scL1WqFMnJyVpaCAQCQfHTrFkzlixZQlRUFE5OTgCcOnWKsmXLSq/zwsrKisuXL5Oamqq2gzXnrjJDbLRRs2ZNXrx4waJFi1i1apXG+fj4eI4ePcqSJUs0av+5uLjg6+ur9TPZWEqVKkVKSgqJiYkG1Zh8/vw5fn5+rFmzRi1QC2Bra8uoUaNYuHAh06dP1zhfGBirNy9MTU2ZOXMmH3zwAZcvX6Z+/fqFqLLo0abfkLW4cuVKzM3NGTVqlNZ+L1y4wJ49e3j27BklS5akR48eNGjQgISEBEaOHMnChQulHbrHjx/n0KFDfP111hO/ERERbNiwgeDgYGrVqkWDBg34+eefpQBidHQ0P/zwA4GBgZiamkoPgMnlctLT0xkyZAiTJk1i69at+Pj40K5duzz1GII+PfrQNXZycjLbtm3j+vXrKBQK3nnnHfr16yelAI+IiOC7774jODiYqlWrqu2czpkG2cXFRadfMzIyGDx4MNOmTWPnzp08ffqUunXr8vHHH/P999/z77//Uq5cOcaNG2fQA6P56a+gfhQIBAKBQCAQCASC14UGZS0IvpUVrE27e5oU/5+w/GgRCsfyanaqzAwyI4OQO5ZHpsz6fZ0edB5FWS9kcs3MbxkvnpJ+/xxm9bv/10dyVsplmVmulMlpyaQc34hF59lZJZ7kSlBlZp3MzAAtmeVqZ0Tme84FIf3xS+Ieg7JSIywapqOKPweoCtSnzNIFuVM9g+29vLzo0qULmzdvlnbRKpVKli5dyogRI0hJSaFr167Y29tz7949NmzYwLvvvsuAAQOM6jObkJAQbt++rdHGwcEhz80WrxtvfbC2Z8+e/PLLL/To0YNRo0bh5eWFhYUFjx494qeffuLo0aN8++23xS1TICgyatSowbfffkvv3r2llIv3799n7969zJ49u5jVCQQCgXbs7Oxo3LgxBw4cYOjQoQD4+vrSuXNnbty4obPt5MmTGT16NK1ataJJkybUr1+fJk2aqH05M8RGGyqVismTJ9O2bVv8/f1p1KiR2vmgoCAyMjKoUaOG1vaF8QUxPT2d3bt3U7VqVbXA5+7duzl79qyG/TfffMPdu3dRqVTUrKlZPwWygtCJiYk8efKEKlWqFFhjQfXqCui6u7tjY2PD3bt3izRYm199+sit35C12L59+zxTij99+pRPPvmEefPmUbFiRQIDAxkxYgS7du3C2dmZCxcukJSUJNlHRUVx7do1ICsIOHDgQKpVq8aoUaO4c+cOM2fOJDMzU7IfOXIkLi4ujBgxghcvXjBnzhxSU1MZMmQIcrmcCxcusGLFCpo2bYq7u7tOPZUqVdLpG0P06ELf2MOGDcPMzIxRo0aRlpbG0qVLuX79OsuXLyczM5OBAwdSq1Ytxo8fz6NHj9QCmyqVigsXLpCQkEBGRoZOvyoUCi5cuMDixYsZMmQIycnJTJ06lePHj9O9e3c+/vhj5s+fj0KhYObMmXrnZWx/+fVjZmamlOL8TSNb95uqP5vimMeb7jOBQCAQCAQCwdtPu8o27LkViyolgeRj32L2Xm9kClMyX4RKNjI7F5DJSTq8DEW5dzBr0IOM0Nuk3f4Hy65zJTtVcjzIZMjMrJCZWJBy/hdUiS8xrf0hmYkxJP+zAWWF+sit1B+sTfH/CWWVZihKZu2mVTh7kHxiM6r0NDJCrqMoVVVDd8Wk8CLyiGGk339O3H0wqdYM83pJqOIu6G+UB0qPj7QGvLMpU6aM9CB0Np9//jmXL19W27RQr1499u3bx7Zt21izZg0JCQm4uroybNgwunfvrpYC2dA+y5Qpw9atW9m6dauGri5dujB+/Hij51scvPXBWisrK7Zv386CBQuYOHGi2k2KSpUqsWHDBpo1M2z7tkDwJuLl5UWnTp3o2LGjtMsrPj6ejz76iObNmxezOoFAIMibLl26sG7dOoYOHUp8fDwnT55k9uzZeoO1tWrV4siRI/j5+XHu3DnWrVvHrFmz+PDDD5k3bx5WVlYG2eRFyZIlGT9+PPPmzcPX11ftXPr/p7fJ2f7BgwdSCmIAR0dHVq5cabAfcgYNMzMzefz4MdbW1ho75OrWras1BbW5uTlpaVlPoGbXpM1NdvAxMTHRYF1FqVcfNjY2RgUYtAVenZ2dddYCLYg+feTUb8ha9PT0zLOvxMREMjIyKFOmDLVq1aJWrVo0atQIR0dHUlJSdOq4evUqT5484bfffsPOzo53332X27dvc+bMGclm7ty5lClTBltbWwDOnTvHhQsXpGAtQMuWLaU0zvfu3ctTjz4M0aMLXb64efMmFy5c4PTp09Lu/OnTp9O/f39mz57NgwcPePz4Mbt27cLW1pZatWpx9+5dDh06ZNDY2ujZsyetWrUC4Oeff6Zs2bL06tULyEoZf/HixSLpL79+vH//vlF6XkeuX79e3BIKhbdlHgKBQCAQCAQCQWFQu5QF5e1NuH8t6zdLyvlfSTn/q5qN1cBvkFvaYdFpFiknt5CwcwpyKwcs2k9B6fbfg+vJ/3yHzNwG85YjkFs7YNVjESnndpCwZxYyMyuU7u9g9l4vtb4zXjwlI/Q2lj3/S90rt3XGrF5XEnfPAFMLLFprpuZ1jQsrTDfkm7TbUaTdBtPaLTGr9RJV3L9G92FSubfO88eOHdM4Zm9vzx9//KFx3M3NzaCyPYb2qc3uTeStD9ZC1s24NWvWEBsby4MHD8jIyMDFxYWyZcsWtzSB4JUwYcIEevbsyZ07d8jIyMDT05OKFSsWtyyBQCDQSYsWLZg9ezZ37tzh5s2b1K9fHwcHB4PaWltb06VLFymV7MWLF/n000/ZuHEjn3/+ucE2edG3b192797NDz/8QIsWLaTj2WUVHj9+LO2MLFmyJL17Z32pvXr1Kn5+foa6AID69evTvn17IOsG/u3bt9m3b59G8EtbbdtssrUEBwdTvXp1jfNPnz5V069UKqXAc05SU1MBNJ5sLGy9ukhISCAqKgpXV1eD29SpU4cPPvhA7VjuNNW5ya8+fWjTX5C1WLlyZWbNmsXUqVNJSUmhYcOG9OjRgzJlyugN1oaHh2NnZ4ed3X+1e2rUqKER1Fu/fj1Pnz4lMTGRR48eUaFCBbXzOXdj69KjD0P15IWusZ88eYKtra1aGnV3d3dUKhWhoaGEh4dja2srBaWzzxeE7BTJkBXkz+kDCwsL6f1U2P3l14+VKlXK84GO152MjAyuX79OzZo189yF/iZQHPNITEzk7t27r2QsgUAgEAgEAoEgv3SqYsual7WxGfmzTjtFyXJYdv0yz/MW7Sap25eqjGWXL/Kw/n+bEmWw6qP5sLdp7faY1m6fZzu75yE6+33VpF6NIPUqmNZrjVm1SFRxhj0kKnd8B3kJzZ3DgsLlfyJYm42trS116tQpbhkCwSvl4sWLVKhQATc3N7WbfI8fP+bq1at06tSpGNUJBAJB3piamtK2bVsOHjzIjRs36NmzZ777ql+/Ps2aNSMwMLBANtkoFArmzJnDJ598opbyuEyZMnh6evLrr79KdTLt7Oyk4KVCoTA6WOvu7i5lAWnWrBnnz59n3rx5RtWe9PT0pFSpUuzZs0drsHbfvn14enpKNT9Kly5NUFCQhl1gYCBOTk4669oWhl5d7Nu3D6VSibe3t8FtKlWqRNu2bQtl/IJiiH5j1iJAnz596NOnD48fP+b48eOMHj2alStXUrduXSArhW82CQkJ0t9mZmYaAd2XL19Kfz969IhevXoxduxYevTogaWlJZs2bSI4OFitTe7gfV56cj7YoA19egwhr7FtbGxISkoiMzNT2hGcvZPcxsYGCwsLtbTGkJWJRBsymQzI26+57fJ6bSyG9pdfP8rl8jc60AlZn7Fv+hzg1c7jbfCXQCAQCAQCgaBoefnyJXFxcWr3lvMiNTWVyMhILC0tNR64j46OJiEhQaOfyMhIVCqVRumokJAQqZ8PPW1Yf/E5GYZVyXktUIYH6zcqBlIvhZF6CcwavY9pxRBU8Xd02iv17KoVFA5y/SYCgeBNJiQkhM6dO+Pv7y8dO3DgAN27dzd6R4dAIBC8arp06cLRo0e5desWrVu31msfFRXFlClTNFJIBgcHc/bsWWrWrGmQjSHUrVuXDz74gFWrVqkdnz59OkeOHGHTpk1S+mHICnT+/PPPajv78sPcuXP5559/jErPKpPJmDx5Mjt37mTv3r1SkEmlUrFr1y58fX2ZOnWqZN+9e3f27dunljr4xo0bbNq0SdolXJR6taFSqTh06BDLli3j008/1Zmq+nVEm/7CWIt+fn7MmTMHlUqFu7s7gwYNonr16ty/fx9ra2tMTU158OABkPWj+ejRo1JbT09PkpKS+Pfff6Xzf/31l3Q+MDAQhULB0KFDqVy5slSjVtf3B1169KFPT0F84eXlhZmZmdrDEgcPHsTNzQ1XV1eqVKlCenq6tPs0NTWVw4cPax1Hn1+Lm4L6USAQCAQCgUAgEAhysmfPHoYNG6bTJiIigs8++4y6devSpUsXWrRoQfPmzdmyZYt0D+LUqVN07NhR4zfl6NGjGT58uNqxtLQ0OnbsyIkTJwAoaamkabk35z5AFVksqsQEMnI85Ftc5KUhxT+UuJ/kpEd/gMy6kvbGCnNMPLoXoTpBNv9TO2sFgv9Funbtio2NDVOmTKFbt248e/aMc+fO8c0330i7vgQCgeB15Z133gGgdevWmJmZ6bV3cnKifPnyDB06FDs7OxwcHEhISCA0NJRu3boxbNgwTE1N9doYypQpU/Dx8VE71qhRIzZs2MCiRYv45ptvcHV1JSYmhsTERLp27cqnn35qnBNyUaFCBUaOHMn8+fNp2LCh9KTqjh07+PPPPzXsq1evzqJFi+jQoQPp6eksX76cZcuWUapUKcLCwrCwsGDVqlU0adJEatOtWzfCwsIYPXo01tbWKBQKoqOj6d27N6NGjXolegF++eUX/Pz8UKlUhIeHI5PJmDRpEv369TNKQ34wRJ82mwkTJkg14fXpN2S9AqxcuRJzc3Otvn/33Xf59ttvadu2Le7u7kRERCCXy+ncuTMymYx+/foxY8YMfvvtN6Kjo2nRogVHjhwBstLqDho0iE8++YT69evz/Plz3nnnHaneS4MGDXBwcKBbt27Y29uTmZnJkCFDWLBgAevWrWPs2LFG6dGHPj0Aa9asQS6XGz22vb09X331FV988QU7d+4kMTGRsLAwli1bhkKhwNXVlREjRjB69Ghq1apFZGQk9erVIzIyUmMcfX4tbgzxo0AgEAgEAoFAIBAUFi9fvqRPnz64u7tz4MABypcvT0ZGBqdOnWL69Ok8ffqU2bNn07RpU5KTk7l8+bKUberly5c8ePAApVLJ8+fPKVmyJAABAQEkJSWp3av4yMuO4480sxq9jpSPusqAR9HYK+SsK1dC7dzd5DTWRcVzNzkdpQza21kwwtEKeR7Zk3TZZ6pULAqPIyI9g0xgZilbSpv8lz1n+/MEItMzmOhiq7VvgOSTISTLzbBo5YPS+Q6qxMfSORPPfsjMSuTZVlB4yFSq1yC0L9BKYmIit2/fplq1anrrqkFWjaOAgADq1KlTpOmsCnuc2DP2RrexbfzS6DZhX3gYZV96rmb6R32Ed2xqdJtSB05pHDP22hvCgwcP6N69O6ampvj6+mqklRAIBILXhevXr+Pq6ip9QQ8KClKrNRkUFISJiQnlypUD4N69e8jlcjw8/vucT09P5/Hjx8TExGBtbU3ZsmU1Pk/12eTuN7eubIKCgnj27BnvvfeexlxCQkKIiorCysqKChUq6Kz1mpcvHBwcNOp9pqam8u+//1K+fHlcXFy4fv26lNI1NzY2Nmqpj9PT03n06BEjRoygdevWTJ8+Pc90qklJSQQFBaFSqahQoYJGPUttPiosvTltZDIZJUqUoHz58oXmQ33zMEZfTjw8PHB0dDRKv761ePfuXRQKhdoaz83jx495/vw5Dg4OlC9fXu1ccHAwz58/p3LlyqSlpfHo0SO10iBhYWFERkbi6enJH3/8wbZt2/jjjz+ArGt39+5dTExM8PT0RCaTERgYiImJCRUrVuT8+fNUr14dGxsbg/XoQ5ees2fP4uvrKwXMjfVFcnIyjx49kj5Dcl+PyMhIQkNDpbq8QUFBvPvuu2RmZnLx4kVq1KghvQ90+fX8+fNqtnfu3JGubfYcX7x4oTUtuTby058uP+Yk+3unp6enxnV8U3hVv4OKmuKYR1H87hAIBAKBQCAQvF1s3ryZXbt25fmA6ooVK9i9ezdHjx7VuG/w559/Mn78eA4dOoSHhwfdu3fH29ubSZOyascePnyYn3/+GVNTU7p160aHDh0AWLVqFSdOnOD3339X62/4/hD+DU8uglkWHmkPL2H9z2qqpSfwIj1TLVibkJFJ/0fRtLE1Y3BJKyLTMpkdGkN7Owt6O2h+H9dnfy4hhb0vkvi6rD0HY5K4lZzG5P8PzIakpjPp6Uu+L+eAtcLAJLtyOZZtyqBwuIEqJQrLnpeQW+d9P0VQeIidtQLB/wDHjh3jiy++YMCAAcTExNC3b1+WLFlCvXr1iluaQPDac/XqVVJSUrTuRE9MTCQgIABXV1cpIJCdNrRSJfX0IWFhYYSFhaFUKilXrhz29vYa/emyyd3v1atXkclk1KpVS6umRo0aqR3PzMwkKCiImJgYSpQoQYUKFaS6jcb4ImddRplMhrOzM+7u7iiVyjztclKuXDkpuJBbV8mSJSlfvrxG6tcXL16opbzNDljFxcVx/fp1GjRogFKpVPORUqkkPj6e5ORkkpOTefbsmYZepVKJh4cHV69e5dmzZzx79kyr3pxzyh6jZMmSVKxYUQrw5RVEK1u2rNp8dfnG29tbCoRlz6NmzZpcvXqVx48fa22TnWY5MzOTMmXKqI2Vk5zjZuvv3Lkze/fuZcyYMdjZ2anZG7JeASpXrqz2Oq+0vaampmrBbEPS+xqajrow+jF0HpCVavvy5ctSPVhDxg0KCiIhISHPQHP2WswLT09PnWNBVq1gd3d3redy163PDiiqVCpmzJhB+/btadKkCSqVin/++Ydq1apJtqampnh5ean1V6VKFenvnNc1KiqKJ0+eULduXdzc3Hj69CmOjo56tWdjiJ6oqCi18bWhyxfm5uZUrVo1z7bOzs44OztLr999910gq55r7gcycvvVxsaGa9eu4eXlRUZGBpD13jx37hy1atVSu2lRunRpqUa0IeQeO/cccvZniB8FAoFAIBAIBAKBoLA4fvw4HTp00AjUAvj4+ODk5MQ///yDh4cHzZo14/jx41Kw1t/fn/r162NiYsKZM2ekYK2/vz/NmjXT6G9YPQdG/xFatBMqIJlRD/mydSuuHD/MhXT1lM93UtKJz8xkuKM1SpmM8mZyBpa0YtvzBK3BWn32j1IyqGSWdU/Ow0zJHzFJUtsVkXGMcLQ2PFALkJlJ4p/BYOKA7YhhIlD7ChHBWoHgLWffvn0sXbqUpUuXSsGbP//8kzFjxjB16lS6detWzAoFgtebOXPmcOfOHf744w+NgI6vry9ffPEFQ4cOlep9rl+/HktLSxYvXgxAeHg4n332GcHBwVSsWJHk5GQCAwPp2LEj8+bNQ6FQGGSTu985c+Zw79499u7dq3bTPiQkhCFDhhAYGCgd+/3331m+fDlpaWk4OzsTFhaGra0ts2bNolWrVkb54uXLl9LO/IyMDEJCQrCzs2PFihVSQGfOnDlER0drrc3at29fevTooaHLxcWF8PBwbG1tmTZtGu+//77UZsKECQwfPpz+/fur9RUYGMiQIUO4ePEitra2Wn1UWHpz9pWSksKTJ08wMzNjxIgRDB48OM+dqdp8GB0dja2tLaGh6j8uatSogUwm4969e5iYmHDq1Cmj9Pn4+DB69Og8x82t39TUFAsLCyll7A8//MDLly/1rsWiJDg4GEtLS43dy9p4/Pgxs2bNyvO8iYkJW7ZsKdAY2vD392f16tUGp5TdsWMHS5YsoXHjxnzzzTd67QuqzxhkMhk1atTgs88+o2bNmlLa4O+++y5f/eX0TXp6OpMnT2bz5s1UrVrV4OulT0+NGjWMCnK+KnJe51WrVklzr1ChAkOGDGH37t1aHwLI7zrWRWFfV4FAIBAIBAKBQCDQRURERJ4PzELWg65hYWEANGvWjG+//Zbo6GgcHBzw9/dn4cKFKJVKfvvtNyDr4fwbN24wZcoUjb7ql7GkYVkLzoUkaZx7XTBr0JPKd1dyxUB7e4WckLQMkjNVmMv131/KaS+TQXbqXBUgJ6v9kZgkTGUyWtqY52sOMqUpZg2KvgSV4D9EsFYgeMspU6YM+/fvV9vZ4uPjQ40aNbh69WoxKhMI3hwqVarEvn37mDx5stpxX19fKlasqLPtggULKFmyJD///LMU6MpOQXvp0iXee+89g2y0UbVqVebNm8eOHTvyHH/fvn3Mnj2befPm0bVrV2QyGampqXz//feMHTuW3377TWPXnC569eqlFhBMTU1l+vTpTJ48mcOHD0vH+/Tpk2fgEGDv3r3MmTOHBQsWSLU1MzMz+eWXXxg/fjzffvutVPezIBSWXm19HThwgHnz5vHixQsmTJhgsKY+ffrwySefSD9UcjNv3jyNVJSG6NOHNv1z587Fx8eHIUOGYGZmlu+1WFisW7eOli1b0rZtW722pUuXZsGCBXmez2vnuDFjFAYnT56kV69ezJgxwyD7V62vf//+dOzYkUePHmFjY4O7u3uhBOVNTU05c+aM9NrQ66VPj64dyMVJ7uucPfeUlBSd7fK7jvVRVNdVIBAIBAKBQCAQCHJjYWGRZxYxyMoCZ26eFTSsXbs2dnZ2+Pv7U6tWLZ49e8Y777yDXC4nJiaGBw8e8ODBA6ysrNTK9+RkfENHLuwJJvM1LvBpFhGs9Xg1cyXWcjkbn8UzuKQVz9Mz2RGdgAqIy8jEXK4wyr6ymZIf47N8fyMpDU9zJS8zMtn6PIE1biX4JiqOgMSsrGyTXGzwNDestJRV1z4oSjjke/4C48nfr3+BTlJTUwkICODOnTtoKwn87NkzLl26RHCw9jesQFCY1K9fXwrURkdHEx0dDWSl5mzfvn1xShMI3hiaN2/OgQMHyMzMlI6FhIQQFBSkkYY4N48fP8bLy0vtJnn58uX5888/pcCXITbaGDhwIOHh4ezbt0/reZVKxapVq+jVqxfdunWTdn+ampoyevRohg0bpvPLtCGYmprSs2dPHjx4QFxcnEFt0tPTWbFiBQMGDKBLly6SLrlcTr9+/ejcuTNLly4tkK7C1JsXHTt2ZNq0aWzZsoWIiAijdWSnas39n5WVlVra56KiY8eOTJ8+nf3792NjY4NMJjNoLd65c4d79+7p7PvRo0dcunSJhw8fapyLiYkhICCAW7dukZr6XzqgGzducPXqVe7evcudO3dIT0/H399frS5sREQE//77L5C14/Dp06eUKlWK5ORkzM3NJR/a29vz/PlzvWNkk5SUxM2bN7l3756UWjonERERXL58Wfo31FCuX79OREQEL1++5MKFC0b7wFAiIyO5cuUKsbGxvHz5kosXLxql88WLF6SlpSGTyTQCeomJidy8eZM7d+5oDTzm5ZvMzEz8/f2Jj48nPT2dS5cu4eTkJF0jc3NzoqOjcXd3p1y5cgQHB5OcnExoaCj37t2jQoUKVKxYkcTERC5fvkx4eLjB81GpVPj7+0v9Xbp0idjYWCDrCe28+suvH3Nf55xzz0YmkxEeHq7hK13r2NnZmdjY2DzXpT5SUlLIyMjA0dGRuLg4o9eFQCAQCAQCgUAgEBhCpUqVuHHjhtZzSUlJPHnyRMpWJ5fLadSoEefOnePcuXPUq1cPU1NTlEol9erV4/z58/j7++Pt7a1WcisnlUua0bmqbZHNp6C4yhIh5oXWc5ZyOQtd7bielEb3B89ZEBbL+7ZZgWyllqxt+uzfsTChnKmSkU+iOZuQQn8HS76JiqdHCUsSMlVcSEjlu3IlGFrSik3PDLsHKHcoiWXX3vmcvSC/iJ21hcy1a9cYPXo0Tk5OxMTEYG9vz9atW6VacBs2bOCbb77Bw8ODx48f07p1axYvXpzvp+YFAkM4duwYX331FSEhIXz66afUrFkTf39/KW2rQCDQTY0aNfjrr784e/YsjRs3BrJ21fr4+KgFWrTRvHlzvv/+e8zNzWnVqpXWtDCG2GjD1NSU6dOn88UXX9C6dWtsbGzUzj98+JCwsDA6duyotf3nn39u0Dj6CAkJwdzcXG03aHBwMP7+/hq29evX5+7du0RFRdG5c2et/XXt2pW9e/cSGhqKq6troWgsiN686oxCVsBz9uzZnD9/nk6dOhW61oLq00du/YasxaNHj2Jubq6RFhyyHlgbNmwYkZGRlC9fnqCgIFxcXNi0aRPm5uZs376ddevWUatWLV68eEF4eDibN2+mSpUq+Pv7ExoaKqW1dnV1ZciQIRw4cECq2Xry5Ek2b97MkSNHyMjIYMiQIQwdOpQ9e/Ywfvx4+vfvb9QYVatW5a+//mLOnDnUqFGDlJQUnj59ypo1a6Qd59988w1btmyhfv36REREqNUo1ceZM2eIiooiMzOTQ4cO0aBBA6P16WPdunVs3ryZevXqERERwbvvvsvx48c5fvy43rb6rtcff/zBggUL8PLyIi0tjXv37rF48WKpbpAu36SlpUnpf93d3XVeS4AhQ4YwcOBArl27RlJSEmFhYcycOZNt27ZhY2PDlStXWLFiBR988IFBvje2v4L4Mfd1rl27tjT37Pn+/PPP3LhxA3t7ewICApgzZw49e/bMcx3rW5f6KMh8BAKBQCAQCAQCgcAYunXrxsSJE7l+/bpG+ZfNmzdjbm6uVu6qWbNmbNq0ibS0NBo2bCgdb9iwIZcvXyYwMJBBgwbpHPPTho6cD0kkNC69cCdTCNRVRek8X83ChG/L/bdr9Vx8CqYysFVoT4Gsy14mkzHB5b/7gVcSU3mUks5UFxuOx6VQyUyJXCajsrmSoBTDfGU7ZjJycwuDbAWFhwjWFiJpaWl89tlnDBgwgBEjRpCRkcHYsWM5ffo07du35/bt26xbt45ffvkFLy8voqKi6NatG76+vnTp0qW45QveUkJDQ5k1axaff/45jx49AsDT05MFCxbQtGlTqY6tQCDQTadOndi3b58UrD1w4ADz589n9+7dOtt9/vnnODo68ssvv7B48WKcnZ1p1qwZAwYMkAIxhthoQ6VS0aZNG3bu3MmqVauYPXu22vnnz58DqAU84+PjuXbtmvTazMyMunXrGuyHnEHDzMxMHjx4wPr16/n444/VduT5+/sTFBSk0X7z5s08e/YMyNrhr43s45GRkQUO1haGXl3BUFNTU1xcXCRfG6spG3Nzc95999082+RXnz5y6zdkLY4fPz7P/m7fvs2VK1e4cuUKJiYmpKens3jxYkJCQqQnbVesWCG9j0aOHMnWrVtZvHgxw4cPZ9u2bfTr14+2bdtKOyHzIvsJ28jISM6dOyc9+GbMGC9fvmTatGnMnz+fDz/8EMh6sG7OnDns3buXiIgI1q9fz7Zt26hXrx6ZmZl8/PHHBvt35MiRnDt3jrp16zJu3Dij9ekjPDycb7/9ls2bN9OwYUNSUlLo3bu3wQ8B6rpeDg4OzJ49m6VLl0o/qrdu3crMmTP5559/eP78eYF8k5Ps3fUqlYqdO3eiUqnw8fFh27Zt/Pbbb5iYmDBnzhz27dtnULDW2P4K6sfc11nbDuT09HQOHDgAwI8//sjSpUvp1KkTZmZmgPo61rcu9ZHf+WRmZpKRkWHQnF83snW/qfqzKY55vOk+EwgEAoFAIBC8GrKziebExsYGDw8PPvzwQ/z9/fn444/55JNPqFOnDklJSfz9998cOHCANWvWYG1tLbVr2rQpM2bMIDY2loEDB0rHvb292bp1K9HR0TRt2lSnHitTOXNauDDqwFNet2zI1VLzzr6mUqkIT8/ESSmXdtL6J6TiZW6CQsvOWmPsUzJVrIyMY3YpWxQyGbm7018NFyw79cS8QWMDLAWFjQjWFiLnzp3j+fPnDBgwAACFQsG3334rnT9y5AgNGzaUnoh3cnKiS5cuHDlyRARrBUXGxYsX6dChAz179mTz5s2kpKTg4uJC7969uXLligjWCgQG0qVLFzp16kRCQgIPHjwgJSWFunXr6g3WKhQKBg8ezODBgwkPD+fcuXP4+vrSo0cPNmzYQOPGjQ2y0cWsWbPo0qUL3bt3V0sRk/1F+MWLFzg7OwMQFhbGwoULgazArVwu59ixYwb74dy5c9KDH5GRkbx48YKvvvqKdu3aqdnlro+ak+wUvzExMWpf1rPJDtJlBzH0IdPyZbYw9eojISEBW1vD0++cOnWKW7duqR0rXbo03333XZ5tCqJPHzn1F3QtVqpUSdoR6+Pjg7e3N7NmzZLOL1myhBcvXnDz5k0SExOxsrIiKkr3E6f6aNeunVoQypgxrl+/TmJiIjY2NlIA3dHRkZs3b/LixQtu376NQqGgXr16QFa6platWrF169Z86y1MH9y5cwcTExPpSWQzMzPatGmj93MpG13X69SpU6SlpdG6dWvJ/v3332fx4sWEhoby4MGDQvdN9lgymYyyZctSrVo16WEENzc37t+/XyT9FdSPhtChQwfp75YtW0oZT7Jr8OZcx/rWZYkSJXSOld/5GOvf15Hr168Xt4RC4W2Zh0AgEAgEAoHg7cDe3h5TU1OmTZumdrxevXosWLAAgAULFtCiRQt8fX05fPgwZmZmeHl5sXfvXipUqKDWztHRkebNmxMZGUm1atWk49WqVcPFxYUaNWrg4uKiV1ddVwv61LRjx/WYQphl4eH44hFxGZmkqlRkoCIuI6usmrVcRgYwLvgF7W3N6etgxbWkVP6MTWKBq53UPvP/S2vKZYbZZ/NjdAKNrMykurSVzJRse55AhkrFzaR0PM11hwOVHp7YDB5VOE4QGI0I1hYit27dokaNGpiZmXH9+nVMTU3x8PCQbpwHBQVRsWJFtTYVK1bk8OHDxSFX8D9CWlqaVMA9JyqVqkC7sQSC/zXc3NyklKk3b96kU6dOOoOE2ihVqhRdunShS5cufPzxx+zatUsj+GWITW7Kly/PoEGDmDdvHvPmzZOOV6hQAUtLS65cuUKVKlUAqFy5Mn/88QeQ9RDR119/bdQcevbsKQUNIyIiaNeuHenpxqWcqVSpEkqlkoCAAMqUKaNx/vr161hYWEj/ZlpbW/PihWatj6ioKJRKpc76roWhVxe3bt0iJibG4NSkAH379i2ywKux6NKfn7VoZWXF77//jp+fH/7+/mzYsIGyZcuyfv16bGxsmDRpElevXqVu3bpYWlry4MEDHBwcdPaZk5x1o7Oxt7eX/k5NTTVqjISEBORyObt27VI77uPjQ1JSEomJiRoPDRj6EIE2jNWnj4SEBCws1FMTlSxZ0uD2uq5XfHw85ubmap9z2d8nEhISCuwbbdcy51xkMpna9xe5XI5KZdzz0ob2V1A/GkLOB1Oyx0pOTpaO5VzH+talvmBtfudTqVIlrQ/QvAlkZGRIKddy111+kyiOeSQmJnL37t1XMpZAIBAIBAKB4M2ke/fudO/eXa/d+++/r5buWBfaHliXyWTs2bPHKG2jG5TkbHAiD1+mGdWuKJmyawcJqf/p6RyUlWFuZ4WSOJkomFfajtWRcex8kURJpZwJLjbUt/rv9/T00BiclHImudiilMn02gM8SknnZHwKm3KkSy5nqqSljTljg1+gkMmY5KxePi0nMgtL7KfMRSbiBcWGCNYWItHR0QD06dMHKysrgoODMTc3Z9OmTZQuXZr4+Hi1+niQdZMsLi5OZ78ZGRkGpad6VWmzXoc0Y69i7Fc1P23jFObYtWrVYtWqVWr/UAYHB7Nz507mzp1baOMIBP8LdOnSBT8/P65evcq2bdv02qenpxMcHIy7u7tG+kmlUolCoTDIxhBGjhyJr68vBw8elI6Zm5vTrVs3vvnmG3x8fDQCQhEReadlMQQXFxcmTJjAggUL8Pb2xtHR0aB29vb2+Pj4sG7dOlq0aKEWbI2Pj2fDhg10795dCvy8++67/P3334wZM0bNRwcPHqRevXoGpyrNr968SE1NZfHixdStW1cKhr9J5NZfGGsxPDycFy9e0KlTJzp16kRaWhq9evViz549VK5cmePHj+Pv7y8FhCZNmqQ1EA//Bf5yBrQePHigc/wzZ84YNUaFChXIyMjgyy+/lN4fSUlJxMbG4uLiQmhoKHFxcWq7GQsS1DBWnz6cnZ2JiYkhPj5e6u/mzZsGt9d1vZo2bUpcXBwRERHSE833799HLpfj5uZGQkKCwb7Jz7V8lRTUj4bw6NEjKeX8kydPgKwd9drQty71kd/5yOXyNzrQCVnZAd70OcCrncfb4C+BQCAQCAQCwf8uZko581uXYtj+EJLSX4+EyL71qyOLCsvzfHULEza45/3Q9pIy9kbZA5Q3U7K9vOZDuoNLWjG4ZN6bHLKxHT0Rpav2cmWCV4MI1hYyt2/f5sCBA5QtW5b09HSGDx/OihUrWLp0KUqlUmM3T1pamt7djcbeFHxVabMKa5zK+WiTOz++IRhb9TA/Y2juDyuacYzB09OTvn370rt3b2QyGXK5nLVr19K/f3+1Au4CgUA/7dq14+uvv6ZChQoamRK0ERsby4ABA6hRowYffPABDg4OJCQkcOLECS5cuMC2bdsMsjEECwsLpk+fzuTJk9WOT5w4kfv379O5c2d69+6Nu7s7MTExnD59mnPnzjF9+vR8+SKbvn374uvry5dffsm6deuk4/fv3+fIkSMa9iVKlOC9995j5syZDB06lO7du9O3b19Kly5NaGgoO3bswNnZmQkTJkhtxo4dS8+ePenfvz8dOnRAoVDg5+dHQEAAP/300yvRC1kZMvz8/MjMzCQ0NJQ9e/aQmprK999/b5SG/GCIPm02tWrVkur+6tNv6Fq8c+cOCoWCypU1/wUPDAxkypQpTJ06lQoVKhAREUF4eDienp7Y2dmRnp7O8ePHKVmyJH/99RcRERHSfy4uLlhZWeHv74+joyP16tWjYsWKbNy4kYEDBxIYGMjly5d1+sne3t7oMZo3b86kSZMYNmwYcrmcLVu2oFKp2LhxI++88w5lypRhzpw59OnTh6CgII4fP2709SuIPl3UqVMHJycn5s+fT9++fbl9+zaXLl3SuCYymQxPT0+N9rquV7Vq1WjcuDEzZsxg1KhRJCYmsnTpUnr16oW1tbVRvjEzMzP6Wr5KCupHQ9ixYwd2dnbY29uzYsUKWrRokeeO6ipVquhcl4UxH4FAIBAIBAKBQCB4W6jiaMbC90sx6c8wMoo5XmsjS0P2vGCbI141Fq3bYdHig+KW8T+PCNYWIi4uLpQvX56yZbOeQFAqlbRu3ZpffvkFyHp6PjIyUq1NWFiYdBM1Lzw9PTV25GrjVaXNKuxxEs4Z36ZOnTpGt4n0Lfox8lNxTts4hZ2ObPTo0XTq1EmqkVilShXc3d0LrX+B4G2mdu3a0g5MW1tb+vXrp3azvlKlStjY/JdGxNPTU0q16eDgwB9//MG+ffvw9/cnNjYWa2trPDw8OHLkiLRDyhCbnP3m1pXNBx98gL+/v1SjFcDS0pItW7bg5+fHyZMnuXr1KlZWVtSrV4958+bh5ORklC+y/43LRi6XM2/ePBYvXszt27epVq0atWvX5smTJ/z6668afXh6evLee+9RsmRJdu7cyf79+7lw4QJff/01Xl5ejBo1ig4dOqjV3i1VqhT79+9n586dnDlzBpVKhZeXFwsWLFDbZabNR4WlN9vmp59+QiaTUaJECXr37k2XLl10pmE2xIfaxsw9D0P15baxs7PD1dXVIP2GrtejR49ibm6uNVjbvHlzli5dyqFDhzh8+DAODg4sXLiQFi1aADBv3jwOHz6MiYkJnTt3ZsSIESxatIgffviBqVOnMmXKFHbv3s3Zs2epV68ea9euZfPmzWzevJl69eoxbdo0du7cKY3n7e2tVi/4nXfeMXqMdevWsWPHDnbu3ElaWhr16tVj4MCBQNaOs+3bt7Np0ya2bdtG1apVmT9/vpoGfVSvXh03N7d869OFiYkJP/74I5s3b+bbb7+lfv36DB8+nLVr10o2hw4dIjg4mBUrVhh9vb799lu2b9/Ojz/+iImJCQMHDpRSX+nzjVwux9vbW9rZaci1zPlZmtNvAK6urtSsWdNgvxvTX0H9mLv/nHNXqVR4e3szceJE9u/fT0hICHXr1mXEiBFqWnPXvda1LvVhyHwEAoFAIBAIBAKB4G2iibsVkxo7seR0fu7QFx51iQItZX9eV5QentiM/Ly4ZQgAmcrY4k+CPLl+/TqDBg3ixIkT0s2hr7/+mlu3bvHDDz/g6+vLypUrOXr0qLSbduDAgbzzzjt8/rnmGyIxMVG6kWxosDYgIIA6deoUebC2MMeJPWNvdBvbxi+NbhP2hYdR9qXnBhk9RnjHpka3KXXglMYxY699Qfnxxx9RKBT069evyMcSCAQCbYwaNQqlUimCCQKBEahUKu7fv0/p0qWloOj69es5e/astOv8xo0b+Pr6MmPGjOKU+lrztvnRkPnkJPt7p6enp1qA+03iVf0OKmqKYx6v+neHQCAQCAQCgUBQlKw594ztV18W2/hj0wPwObK62MY3BmWlqjjMX4Hc+s38Hfi2IXbWFiI1a9akYcOGjB49mkGDBhESEsKOHTukJ/Dbtm3Lhg0bGDduHF26dMHf35/79+/n+YS+QPCqSEtLI/MNeuJHIBAUDhMnTiQkJIT169dr7OZ/8OABP/74I40aNaJt27Y0bNiQpUuXYmFhwdixYyW7Y8eOcfDgQcLDw1EqlVSoUIHevXtTtWpVg22WLl1KiRIl+P3331m3bh3nz5/HxMSE7777DlNTU6mfJ0+e8Nlnn7F3717pWEJCArt27eLcuXO8fPkSBwcHGjduTPfu3dV2pxrii4cPH0qv5XI5zs7ONGvWjB49ekg7fXPbZZORkYG3tzfNmjUDsmpznjhxgtu3bxMfH4+9vT2dOnWia9euUv1OgOHDh9OlSxc+/PBDtf7u3LnDjBkz2L59O1ZWVhq+L6heyEoJ3aNHDzUbpVKJg4MD9erVo0ePHtjb2+fbhznZtWsXCoVC7zzy0uft7U2PHj30jqtPvyHr1VASEhK4evVqnuflcnmByg0Y2v+0adNwcnJi6NChhIeHs337diZOnCjZ3b59m/bt2+dbR148evSIJUuWkJ6ezvr16+nduzdLly7Fzc1N+tvDw7gH5QyhKPwuk8mKzY/ZpKamGuS3wloXAoFAIBAIBAKBQPA2Mu7kCcvzAAEAAElEQVS9kkTEp3M0KL5Yxq+QmHet2tcJk8rVKDFvuQjUvkaIYG0hs3LlSrZt28bu3bspUaIEGzZskGrJmZqaSuni9u7di6urKzt37tRIYykQCAQCwavg/v37hISEcODAAQIDA9XO/fvvvzx9+pSLFy+Snp5Ow4YNCQ4OVtt188MPP7BhwwYmTJiAp6cnSUlJHDp0iF69evH7779TsWJFg2yy+/3mm2/4/fffuXPnDikpKXz//feMHj1aGi85OZmbN29KryMiIhg4cCAWFhb06dOHUqVK8fjxY7Zs2cL+/fvZtm0bFhYWBvuiRo0adO7cGYDMzEwePHjA2rVrCQwM5IsvvpDsqlevTseOHdXaP3/+nKNHj+Lr60tSUhKnTp1CqVRSsWJFnJ2dSUlJ4ccff+TXX39l27Zt2NnZAVlB2ejoaA098fHx3Lx5k4yMDAAN3xdUL0C5cuU0+kpJSeHx48fs2bOHH374gU2bNlGtWjWDfZjXWHK5PM95GKJPV/DKUP2GrEVjiImJwdc37xoLSqWyQMFaQ/vftGkTP/zwA1u2bMHGxoa5c+fi4+Mj2fXs2TPfGnSxYcMG4uPjmT59OgqFgv79++Pg4IBKpeLmzZskJiYWybhF5fei8OPWrVupWrUq3t7eem1z+lAXhbUuBAKBQCAQCAQCgeBtRCaTMa+VC2ZKGQcC4175+C6xoa98TGMx8axGiXkrkFtZF7cUQQ5EsLaQMTMzY/jw4Xmed3BwYOrUqa9QkUAgEAgEedOwYUNOnjzJ1q1bpWOpqak0bdqUJk2aULFixTz/3fL19WXo0KFqQYyGDRvStGlTKSBniE02LVu2pGXLlnTu3JkWLVqwadMmOnfuTJkyZbSOP2/ePExNTdm5c6fabtUOHTrQvn17fv/9d/r27WuwL8qWLSs9YAX/1ZGcMWMGM2fOlHarurm50ahRI4322QHH4cOH4+7uzs6dO9V2BickJNC1a1cWL17MokWLDNZVVHp19dW3b18+/fRTPvvsMw4ePKhWQ1gXhoxVGG1yY4h+Y9aiIbi6urJ48eIC6S6M/h0cHJgwYUKR6ciLiIgI6tevT/Xq1QHo1q0bACkpKUU6blH5vSj8ePLkSUqXLm2QrUKhkHyoi6JcFy8mDsdm4y9GtREIBAKBQCAQCASC1w2FXMacFi44WCjYFvDylY5tExXySsczFpMqNbJ21FpaFbcUQS7kxS1AIBAIBAJB8dG0aVOuXLlCRESEdOzkyZNUrFhR7w4vW1tbzp49S1JSktrxNm3aUKpUKYNttFGlShU6duzIV199pfV8bGwsx44dY9SoUWqBWsgKUhw+fNioQG1eODo6kpqaSnJyskH2UVFRnDhxgnHjxqkFagGsrKwYNWoUhw4dKrJdh8bqzQuFQsG0adN49OgRFy9eLCR1rw5t+g1Zi0uWLGH16rxry2Rf2969ezN27FhOnDgBZAXiu3XrxpMnTyRbPz8/xo8fL70ODg5m2rRp9OvXjyVLlnDy5Ek++eQT6XxERAQLFixgwIABfPzxx2zatIn09HQgq1xBt27duHjxIsOHD5d2VualxxD06dHFzJkzCQgI4LfffmPAgAGkpqbSrVs3goKCJJvw8HCmTJlC3759mTNnDs+fP9c5l8TERNauXcvQoUMZOXIk27dvN6pEQ0Hmk5ycTLdu3bh06ZJRmuPj41m5ciVDhw5l2LBhfPPNN9J7b86cOVy+fJlly5axcOFCvXPM6cOMjAy6devGjRs3mD17Nn369GHy5MkEBwe/En8IBAKBQCAQCAQCwdvA2Pcc+dzbEdkrGs+ETOQRT1/RaMZjUtVLBGpfY8TOWoFAIBAI/oexsbGhefPm7N+/X8oMsX//fjp16qSzLiLAtGnTGD16NM2aNcPb25v69evTrFkz3N3djbLRhkqlYsKECfj4+HD8+HFatGihdv7BgwdkZmbmmaLXmFqreZGamsqOHTuoWbMm1tb/pYb55Zdf8PPz07Dftm0b9+/fB6BGjRpa+6xRowbJyck8efIkX3VSC1uvjU3etUnKli2LnZ0dQUFBBqVxzS/51aeP3PoNWYt9+vRBJtP+My44OJixY8eyfPlyPDw8uHPnDp9//jk7duzA1dWVmzdvqgXJX7x4IdWCTk9PZ9CgQbz33nvMnj2bO3fu8OWXX6r1P3LkSCpWrMjMmTN58eIF06ZNQ6VSMXz4cBQKBTdv3mTt2rW0bduWqlWr6tSjb20ZokcXkydP5tGjR9SqVYtPPvlEa+rjdevWMX78eEqWLMny5csZN24cO3bs0DoXgBEjRmBmZsaUKVNISUlh/vz5hISEMH36dL16CjofmUzGzZs3WbhwIZ9//jk2NjZ6NatUKj7++GMcHR2ZMmUKqampLFq0iNu3b7N27VomTJjAX3/9xYgRI6T0w7rmmNOH2ePNmzePESNG0KtXLxYuXMiCBQvYsGFDkfojO/X6m0a27jdVfzbFMY833WcCgUAgEAgEAoEu+tayp4SFgvnHI0gz/HngfFFbFg3paUU7SD6xaNMem+GfIjc3rFyY4NUjgrUCgUAgEPyP07lzZ1asWMHw4cOJjY3F39+f+fPn6w3WVq1alcOHD3Py5EnOnj3Lr7/+yoIFC2jZsiVff/01tra2Btnkhb29PRMmTGDBggUawcLs3Wjm5ubSsaCgICZPniy9dnZ25rvvvjPYDzmDhiqVipCQENzc3Fi+fLmaXdOmTaVasTkxNzeXdkLmVSs3O91u7t2d+aEw9OrD0tISlUqVL03ZlC5dmvXr1+fZpiD69JFTvyFrMbtOrjZSU1PJyMjAzMyM8uXL4+HhIaWe1rdTOiAggLCwMGbOnIm1tTVVq1YlICCAkydPSjarVq2iZMmSUqC9bdu2XLlyBfiv5u8HH3wg7RjP3oGpTY8+DNGjC3t7e0xMTLC0tKRkyZJaUx/379+f1q1bAzBp0iQ++ugjIiIicHFx0ZjLjRs3uHDhAmfOnMHR0RGAqVOnMnToUCZOnKixS72w55NNv379aNq0qZrmyMhInJ2dNTRfv36dgIAAzp49K2UhmDx5Mn369OHFixeUKFECuVyOjY0Ntra2eueojd69e0s+7NWrF6tWrTJoHgXxR0BAgEFjvK5cv369uCUUCm/LPAQCgUAgEAgEgteBdpVtKG9vwgy/CEJiiy6YWisjssj6zi8yK2vsxk7BvEnL4pYi0IMI1goEAoFA8D9Os2bNmDVrFjdu3ODWrVt4e3sbvDPVzMyMNm3a0KZNGwBu3rzJiBEj+O6775gyZYrBNnnRs2dPdu3axcaNG2nbtq103NXVFYBHjx5JNSGdnZ0ZN24cAFeuXOHgwYOGOwFo0aKFFDS8ceMGa9as4dtvv5WCS9nkro+ak+x0uo8fP6ZmzZoa50NCQtT0K5VK0tI0fyhkB79MTEyKVK8u4uPjiYqKyrNmsDYaNWpE+/bt1Y7pqwebX3360Ka/IGvRw8ODhQsXsmzZMiZMmED9+vXp2bOnFEzTRWRkJPb29mo7nqtVq6YWPIuOjub777/n6dOnJCYmEhISQpUqVdT6qVSp0ivTU1AqVqwo/Z19DaKioqT1mXMuT548QS6XS7v7IWt3aGpqKmFhYXp34hfWfLRpzhmszak5ODgYW1tbtXTx2cH+sLAwSpQooda3vjlqSwuf8+EBMzMzUlNTDZpHQfxRp04dg8Z43cjIyOD69evUrFkThUJR3HLyTXHMIzExUcoCIBAIBAKBQCAQvK1UczJne3c3Fp6M5K+g+CIZo1JSWJH0m19MqtfCfuIcFM4u+o0FxY4I1goE/0NER0cDaNSh7Ny5c55pHwUCwduPiYkJ7du359ChQ1y/fp0BAwbku68aNWrQpEkTHjx4UCCbbORyOXPmzGHgwIHUqlVLOl6qVClq1KjBjh07pF23NjY2tGyZ9aRgSkqK0cHa0qVLU69ePQDq1avHqVOnmDNnjkFpR7OpXLkyZcqU4bffftMarN29ezfVq1eXAlZlypTRepP81q1buLi45LlDt7D06mL37t2YmpoalQLZ3d2dZs2aFcr4BcUQ/casRYAuXbrQpUsXIiMjOXHiBFOnTmXx4sVSsDnnLuT4+P9+/FlYWGjUEc6uhwpZu2QHDBjAtGnTGDlyJJaWlqxfv56HDx+qtVEq1b+656Xn/fff1zkPfXoKg5y7jbN3kudMa51zLiVKlEChULBixQqN7yPZD2PoorDmk/Oa6dNsb29PUlISGRkZUlAtLi4OADs7O42+9c3RmB3s+iiIP97kQCdk6X/T5wCvdh5vg78EAoFAIBAIBAJDsDaVs/D9UjQvH8fXp6OITSncvMilY1+TYK1cgXXvQVh9NBCZ+L7/xiAvbgECgaDoOXbsGK1bt8bb25tff/2VU6dOsWTJEum8o6MjJUuWLEaFAoGguOncuTNHjx7l3r17GvVhtREVFcXYsWO5ePGi2vG7d+9y+vRp3n33XYNsDKFWrVp06tSJlStXqh2fMWMGx44dY/Xq1VJgSKVS8e+//7JlyxZp92p++fLLLzl//jz79u0zqt306dPZu3cvP/30k5QWOS0tjW3btvHnn3+q1eDs1asXBw4c4O+//5aOXbx4ke+//57+/fu/Er25SU9PZ9euXaxYsYLJkyfrDBi/jmjTXxhr8c8//2TixIlkZGTg7OxMz549qVSpEk+ePMHa2hpzc3MCAwOBrEDlkSNHpLZVqlQhOTmZc+fOAVmBwKNHj0rng4KCMDEx4aOPPqJMmTLExsZy+vRpremFDdGjD316CoOcD0v4+fnh5OSU53syu87yrVu3cHd3x93dncePH/Pzzz/rTYEMhTefnJr//vtvnZq9vLywtLRUa7Nv3z4qVKggBZhlMpl0DQs6R2PIrz9KLN9YqDoEAoFAIBAIBAKB4HXEp5INv/YsR3tPGwpz+5Jd9NNC7C1/JDmVInL4BFJ9OmsN1D59+pTbt29L5cXi4uK4ffu21v/u3LmjYXPnzh0eP36sNfNTSkoKt2/fls69fPkyzyw+T548ISIiQq3/7I1m+jS/rYidtQLBW05oaCizZs3i888/59GjRwB4enqyYMECmjZtSqNGjYpXoEAgeC2oWbMmpqamfPDBBwYFDpycnKhXrx6ff/45mZmZODg4kJCQQFxcHH369GHIkCGYmJjotTGUzz//XC0NMmTtJt22bRuLFi1i06ZNODk5ERMTg7m5Od27d2fUqFFG+yEnbm5ujBkzhoULF9KoUSMpFeq2bdv4/fffNey9vLxYuXIlbdq0YcWKFSxdupQVK1bg5OREVFQUrq6ufPfddzRo0EBq06FDB549e8b06dPJzMxELpeTnp7OwIED+eSTT16JXoAff/wRX19fVCoVkZGRlChRgrlz59K1a1ejNOQHQ/Rps5k6daq0g1SffkPWK8CSJUswNzfn008/1dDTsGFDfvrpJ1q2bEm5cuWIjIzE0dGRLl26IJPJGDp0KLNnz+bnn38mKSkJHx8ffH19gay01yNGjGDkyJHUrFmTxMREGjVqJAV0GzZsSOnSpenQoQO2trZYW1szZswYZsyYwbJly5g0aZJRevShTw/A0qVLUSqVfP7553r7y0n2jycbGxs6deqEpaUlgYGBLFmyJM+03tbW1ixbtoyZM2eyefNmFAoFoaGhfPXVVwaNWVjzMTExoVOnTlhZWXHnzh2dmm1tbfn666+ZNWsWO3bsICkpiaSkJJYtWybVGK5Tpw4LFy7k77//Zs2aNQWaozEY4g+BQCAQCAQCgUAg+F/GyUrJly1d6FPTnlVnn3EpNKnAfZpEBBeCsvwhty+BVa9BXDexZuz48XTs2JFly5ap2ahUKgYOHEhISAhXrlzBysqK8+fPM2bMGK0lsBQKBX/99Zdkk12q59mzZ2RkZNCmTRumTp0q3X96/PgxXbp04e+//6Zs2bL89ddfLFu2jPPnz2v0PWfOHCpXrszMmTOl/g3V/LYiUxVmzi1BoZKYmMjt27epVq2a3npvkFXjKCAggDp16hRpOqvCHif2jL3RbWwbvzS6TdgXHkbZl54bZPQY4R2bGt2m1IFTGseMvfa62L9/Pzdv3mTGjBls3ryZlJQURo8ezdatW0lISGDs2LEF6l8gELy53L9/HycnJyllZ0hICFZWVlKtxZCQEJRKpVRLMTg4GJlMRtmyZdX6CQsLIyYmBmtra1xcXLQGN3TZ5O43t66cdi9fvtSaXjg6OpqoqCisrKwoU6aM0and79+/j62trfQFM5v09HRu376Nq6srJUuW5P79+1J61NxYWVmp1bxUqVSEhYUxZMgQWrVqxdSpU/McPy0tjeDgYFQqFW5ubhoBc20+Kiy9OW1kMhklSpSgdOnSUsDJUPLSpG8exujLiZubG/b29kbr17UWnzx5gkwmw83NLc85REVF8fz5cxwcHDTm+uzZM6KjoylfvjwpKSmEhoaq1Z19+fIlUVFRlC9fnt9//53t27dz4MABIOv71ePHjzExMZHGDw4ORqlUUrp0aa5fv07FihU1fpjo0qMPXXouXbrEnj17WLRokda2Dx8+xNLSEhcXF1QqFTdu3KBSpUqYmppy69YtaXdnREQEbm5umJubS23zmktmZiZPnz4lLS2NcuXKaaR9Lqr5pKSkUKtWLfbs2UO5cuWM0pyRkcHTp08xMTGhVKlSap896enpPHz4ECcnJ6kOeF5zzOlDCwsLjfFiYmIICwujatWqheKPnGR/7/T09FRL+/wm8ap+BxU1xTGPwvzdIRAIBAKBQCAQvKmceZLAmnPPefBCc8eoIXjKYlh+4LPCFWUAMitrrDp/hGWXXsgtLPHz82PhwoXExMRw8uRJtd+wly5dYvr06Tx58kQKfPr5+TF+/Hhu3bqV5xi5bVQqFffu3WP+/PmEhISwZ88eHBwcuHv3Lh07dpSCtbt27cozWDt48GApWGus5rcVsbNWIHjLSUtLU7vZmI1Kpcpzt4hA8Lrj7+9PYmKi1rqMcXFxnDlzhgoVKkhBkoCAABQKhUaQLzAwkPDwcJRKJeXLl9f6FJkum9z9+vv7I5PJNGpkxsfHc/r0aY2doSkpKdy4cYOYmBgcHByoXr260ekw/f39iY2NlV7L5XKcnZ2pWrWq2ns/t1029+/fp3Llynh4eEgBtJy6stOk5wwgAZw4cYIKFSpQrlw5SpcuLaX9fPHiBefPn6d169aYmJio+ah06dL4+/tz48YNrXqzqVSpUp56ASwtLfHw8FCzUSqVODg44O7ubnSgVtdYPj4+1KxZk4CAAEJDQ9WutbY2d+/elfx59uxZXFxc6NKlCz///DOffPKJWsp5bfrzWgNubm4EBgZy4sQJaS1qC8wplUq1dV6pUiW98zfExhAM6Sd3ELQw9BmrP+d6zU32U6K6cHJywsnJCcjKXnHv3j2aN29OZmYmly5dwtvbG1NTU0xNTaXPIJVKxYQJE+jQoQOtW7cmIyODo0eP4uXlJfWrUCjUgv2g7i9tDynk1mMohuh58uQJ1atXz7OPChUq8O+//3L//n28vb15+vQp5cqVw8zMTPrbzs4OW1tbjbZ5zUUul+sMlBflfLL7sbW1NUqzQqHIc90olUoqV66sdiyvOapUKslvFhYWGuPZ2dlprYWb1zz0+UMgEAgEAoFAIBAIBP/RuJwVDctacuJRArtuxhi90/adzKgiUqYdeQkHLDt/hGW7rshzPXRpaWmJm5sbf/75J926dZOO+/r60rhxY4PKJ+lCJpPh6enJhg0b+PDDD9m4cSPTpk0rUJ9FrflNQARrBYK3nFq1arFq1Sq1oFZwcDA7d+5k7ty5xahMIMg/S5YsITAwkL1792rcfN+3bx9fffUVQ4YMkXYybtmyBUtLSxYvXgxk3bQfPXo0qampVK5cmeTkZK5cuULTpk1ZtmwZpqamBtnk7nfJkiXcvXuXnTt3UqtWLUlTaGgon376qVTPErLSuq5duxY7OztKlSpFcHAwKSkpzJo1i44dOxrli+TkZCnQmpmZyePHj0lLS2PlypXUq1dPsktMTNQakO7WrRseHh6SrjVr1lCiRAlKlSpFaGgoSUlJTJ48We3L0uzZsxk+fLhGXdWgoCA+/fRTLl68iImJiVYfFZbenH2lpqby6NEj4uPjGTx4MGPHjkWhUPDw4UMmTpyYp/9MTU1JSkrKc6wPPvgAmUymdR6G6PPx8eHjjz/mzJkzfPDBB5QpU4adO3diYWFhkH4wbL0WJYb48Ndffy1SDa8rFy9eZPXq1Rw7doz09HRWrVqFh4eHRlBNJpPRuHFjpk2bRsWKFYmKisLBwaFIUuAaer306alfv77Onbpbtmxh/fr1vP/++9SvX1+ae3Ya6d27d+cZ4Hwd51MU3Lt3D1tbW1xcXPTa6lo/OSksfwgEAoFAIBAIBAKBQB2FXEarita0qmjNo5ep7L0Vwx+BccSl6q+VWiUlvOgFKpWY1noX8yatsGj+PjJTM61mGRkZtG/fnn379kn38lJTU/nzzz9ZvXo1v/zyi0ab27dvaxxzcHDQ+XvW0tKSTp068ddffxU4WJsfzW8bIlgrELzleHp60rdvX3r37o1MJkMul7N27Vr69+9Pw4YNi1ueQJBvPD092bdvn0aw1tfXV2MnU24WLlxIlSpVWL58uXQsIiKCsWPHcu3aNerVq2eQjTZq167N3Llz2bVrV55pWH/55ReWL1/OihUrpAcpVCoVP//8M5MnT8bV1ZW6desa5AeAzp07M3r0aOl1ZmYmX3zxBdOmTcPPz0863rVrVzW73Pz888+sWLGCFStW0Lp1a+n4gQMHmDZtGhYWFrRr185gXUWtV1tfJ06cYPr06cTFxTFr1izc3NzYsGFDnu1lMhkff/yxQWPlxtA2ZmZmbN++XUppa2FhYbB+MGy9FiWG+FCQFSTTVRO0R48etG/fnpCQEIMDePnB0OulT4++Ha4XLlzgo48+kh6KyZ57SkpKQeRr8CrmY2pqyu7duwttl3k2GzZs4P3339fIqpCXBkNqyhaWPwQCgUAgEAgEAoFAkDfl7U2Z0MiJ0fVLcuxhPKceJ3LhaSKxKdoDt2Xjw4pEh8zMHNN3G2Du3QyzBo2RW1nrbaNSqWjXrh0LFy4kNDQUV1dXTpw4QcWKFTVKm0FWoHT8+PEaxzt37qy3hGK5cuWIjIw0fEKFpPltxLhiZAKB4I1k9OjRHD16lJUrV7J8+XKOHDnCzJkzi1uWQFAgWrRowcGDB0lPT5eOPXr0iJCQEGrUqKGz7dOnT6lQoYLaMRcXF3bt2iUFvgyx0Ubfvn2Jj49n586dWs9nZmayfv16+vfvr7bjXSaT0b9/fyZNmlTgOnVyuZwOHToQHBycZ3rf3KSlpbFmzRoGDx6sFqgF6NixIz169GDVqlUF0pUX+dGbF82bN2fWrFns2LGDp0+folQqpTSx2v5zdHQspFnoRiaTUa5cOVxdXY3SD4atxX///Zdr167l2a9KpeLatWscO3aMa9euoVKpgKzrfuTIEeLj4yXbkJAQTp8+Lb1WKpXExsZy69YtMjMzkclk3LhxQ82H4eHhnDx5knPnzqn1lZmZyZEjR0hMTOTSpUtS2pq89BhKUFAQJ06cICIigmfPnvHPP/8Y3Fbf2NHR0Zw9e5aLFy8SExOjdezjx48TEhKidjx7rjExMXn69fLly1SuXBknJyfJL4GBgfzzzz9EREQAWYH448ePExQUZPCccvo5KCiIGzdukJmZiZOTE5mZmdy8eZPY2FiNNR8aGkpoaCiAUX48f/48T58+JTQ0lL///ltt7tnIZDLu37/P8ePHCQ4O1qo155qArDTqZ8+e5fLlyyQkJAAY9R7O73yy686qVCqjNee1Xi5cuEBAQABXr17l8uXLOueYc4yYmBjp76SkJB4/fsw///zDvXv3itwfLyYON8hfAoFAIBAIBAKBQPC/grmJnA89bVnUphRHB1Zgc+cyfPJuCWo4myHP8ey6Q3RI3p0YidzRGfPmbbCfNh/nnw5QYsZXWLT0MShQm42NjQ0tWrTA19cXyNrc0rlzZ622CoWCv/76S+M/fYFayHpg29racF05yf3wvzGa30bEzlqB4C3n9u3bBAcH88EHH/zPPIUi+N+gSpUq2Nracvr0aVq0aAFk/SP+4Ycfqt0A14aPjw+bNm0iIyODVq1aUb16dY0AqSE22lAoFMyaNYtJkybh4+ODg4OD2vkHDx4QFRWV506rTz75RO8YhvDgwQMsLS3VvjDdv39f686tVq1acefOHV6+fEmHDh209texY0d+/fVXQkJCiuSzxFi9ulL/tmnTBplMxsWLF7WmKS4s8qtPH7n1G7IWL126hJmZmVr67WySk5Pp168fcrmcihUrcvfuXWQyGdu3bycjI4NPP/2UAwcO4OnpCcDZs2fZvHmzNLclS5awZ88emjZtytq1a/Hw8OD8+fO0bNkSgO+++44ffviBxo0b8+LFC27cuMH3339PrVq1yMzM5NNPP6Vv376cOHGCUaNG4ezsnKceKysrvf7Rp0cXunxhZWXFzp07WbFiBY0bNyYtLY0LFy4wb948fHx8pLH37dtHs2bNCAkJUVuvaWlpUvpfd3d3nX6VyWR8+umn9OjRg/DwcJKTk7l58yaTJk3iwIEDODk5cfz4cb766iuDfpjkp7+C+DEwMJC4uDjCwsIICAigSZMm0tyz57tx40YiIyNxcHDg9OnTTJw4kUGDBmldE+XKlWPfvn0sWrSIxo0bk5KSwrVr19RSo+ujIPNJT0/n008/pX379kRFRWFjY8Pp06eZNGkSAwcOzFOzrvVy9+5dnj17xoMHDwgKCqJu3bo655hz/Xh5efHpp5/Sp08fAgMDpes3btw4hg0bVuT+EAgEAoFAIBAIBAKBJgq5jFqlLKhVyoIR9UuSlJZJUHQq96JTsLaqh7yELRkRoWSEh6FK1lPz1sQUpWtZFGXLoSzrjvL//68o44bcwlJ3WwPp0qULS5YsoW/fvvj7+7NgwQLi4uIKpe9sLl68SLVq1bSes7S0JCEhgYyMDI37WM+fP8fGxqZYNL+uiGCtQPCWExgYyJ49e/jggw+KW4pAUOh07tyZffv2ScHaAwcOsGzZMr11DMaMGYOrqyu//PIL3333HZaWljRu3JiBAwdKgQFDbPKiadOm1K9fn2XLlrFw4UK1cy9evACgVKlS0rGYmBjOnj0rvbawsKB58+YG+yFn0DAzM5MHDx6wdetWxowZo5aK+ebNm1p3CjZp0oTo6GgASpcurXWM7KBnVFRUgYO1haFXVzDUxMQEFxcXydfGasrG0tKSZs2a5dkmv/r0kVu/IWtRVwDnzp073L17l3///RelUklmZiZr164lIiJC787ikJAQfvjhB3755Rfq1KlDeno6ffv2VbtOUVFRrFu3TtIyfvx4tm/fztKlS1Eqs75qJicnc+zYMQACAgLy1FOxYsUC69GFLl/Y2Njw1Vdf8c0339CkSRMgK2X5l19+ScuWLYmKiuKHH35Qq0k9cuRIg8bNTfbToznriLZr1w5fX19+/fVX5HI58+fP5/DhwwYHa43pr6B+HDhwIMeOHaNu3bqMGzdOa+pje3t71qxZA8CuXbtYtGgRvXr1wtzcHFBfE8+fP+fLL79k5cqVUjBx27ZtfPnll/zxxx969RR0Ptn+s7e3Z8WKFWqaP/roI62ao6KidK6X/v378+2339K1a1fatm1r1BxzPl2c/e/Zxo0b2b9/v0HB2oL4IyMjQ6/N60i27jdVfzbFMY833WcCgUAgEAgEAkFxYWEix8vFHC8Xc6g2RO2cKjUFshN55cjopfr/gzJTM2QG/mbNL02aNGHGjBls3LgRb29v7OzsCjXw+e+//3L06FHWrl2r9byXlxdpaWn4+/vTtGlT6XhQUBAPHjzg3XfffeWaX2dEsFYgeMtp3rw5J0+e5Ouvv6Zx48Zqu5acnZ31puQUCF5nOnfuzHfffUdcXBz37t1DLpdTu3ZtvcFamUxGt27d6NatG3FxcVy8eJH9+/czYMAA1q5dy/vvv2+QjS5mzJhB+/bt6dmzp9r7LvupsejoaJydnYGsQMW2bdsAePnyJSkpKVJAwBBu3bol7SbOTk26du1aGjdurOGvvGqsZu8QfPHihdb0JdmBw+x6q/rqlOo6Xxh69REbG4u9vb3B9gEBAURFRakdc3Z21hmsLYg+feTUX9C1WLVqVTw8POjZsyfvv/8+3t7ejBs3Drlcrjft9L179zA3N6dOnTpAVgrW1q1bq6X5nj17NsHBwZw9e5bExERUKpUU/M+mTZs2BunRhyF68uuLEydOoFKppMAbZP1I+PLLLwkNDeXBgweYmpqq7V5u0qQJd+/eNWhsbeQcy9XVlWrVqkl+KF26NLdv3y6S/grqR0PIec29vb1JSEjg6dOneHh4aJy/ceMGKSkpJCUlSQ9NyOVy7t27R3R0tEaGgtwU1nxyvpcaNWqkU/OtW7d0rpfy5cur9a1vjtp2leccz83NjZcvXxo0j4L4IyAgwKAxXleuX79e3BIKhbdlHgKBQCAQCAQCwf8qMlMz7cdfoQalUkn79u3Zvn07y5Yty9NOpVJx/vx5reeqVq0q/X3p0iUAkpKSuHTpEj/++CP9+/fXKKeWjbu7u1Tybfjw4VSqVIng4GA2bdpEy5YtadSoUb41v42IYK1A8Jazd+9eDh48CMDmzZvVzg0dOpSpU6cWhyyBoFAoXbo0tWrV4siRI9y6dYtOnToZ3YeNjQ2tWrWiVatWjBw5El9fX43glyE2uXF1dWX48OHMmzePxYsXS8crVqyIjY0N58+fl77wVKxYUQowHzlyhK+//tqoOXTq1EkKGj5//pwPP/xQqndqKFWrVsXExITLly/j5uamcT4gIAArKytp56ONjQ3Pnj3TsIuMjMTExERnOtvC0KuLq1evEhcXpzUlcF706NGjyAKvxqJLf37Worm5Obt27eLMmTOcOXOG6dOnY2Jiwvfff4+lpWZqnczMTOnvpKQkzMzUf2DY2tpKfycnJzNq1ChCQ0Np2LAhlpaWREVFaVz/nG106cm541wb+vToQ9fYycnJGjuis8dKTk7Wej5757Ah5PRr7v61vZbJZEbX8jW0v4L60RCyH+zIqSM1NVXreCkpKSgUCs6cOaPWR48ePdTa5EVhzSdnH9nXOi/N+tZLbvTNUdtnZn7XQ0H8kR3gfdPIyMjg+vXr1KxZs8B134uT4phHYmJigR46EQgEAoFAIBAIBK8P1tbW0gPHAN27d+fatWtSBj8TExOqVq0q/d6wtrbG09NTIzNgNvPmzcPa2prKlSszf/58IOu3qpubG6tXr1bb5GBubi7dX8xm9uzZ1K5dmyNHjnDkyBEcHBwYPXo0PXv2lDZ6GKv5bUUEawWCt5xBgwYxYMAArTuWDE0PKBC8znTp0oWjR49y/fp1fv31V732ycnJ3L17l+rVq2sEWlJSUrC1tTXIxhA+/vhj9u3bx969e6VjpqamfPTRR3z33Xf4+PhoBKeePHliUN95UbJkSSZPnsyiRYto2rRpnmmNc2NtbU3Hjh1Zu3YtLVu2xM7OTjr34sULNmzYQK9evaTgRP369Tl69ChjxoyRvoSpVCr27NmDt7e3wZ8v+dWbFwkJCSxcuJAmTZqofdF7U8itvzDW4uPHj3n27BktWrSgRYsWzJgxg169euHr68vgwYORyWQkJf1XSyUwMFD628XFhZiYGGJiYqQ1kXPH15kzZ7hy5Qrnz5+XUsWOHz9eZ91oXXqGDx+ucy769BTEFy1btiQ+Pp6nT59Kab8DAwNRKpW4ubmRlJREbGwsz549k9JH57Xz1dzcXKdfi5uC+tEQgoKCpNTYjx49QiaT5fn+9vDwIC0tjc8++wwnJycA4uPjCQ8P1xvAh8Kbz/3796lbty6QtVZ0aa5YsaLO9WLsHLWlks4v+fVHieUb3/gfvwqF4o2fA7zaebwN/hIIBAKBQCAQCARZNGzYkIYNG0qvq1atqpZlycXFhf3796vZ53ydF4bYlCtXTqtdp06ddG6wMVbz24oI1goEbznZN/dTU1MJDQ0lMzOTsmXLFqieokDwOuHj48NXX32Fp6en1hvkuUlLS2PixIk4OzvTpk0bSpQoQUJCAidPnuTmzZv8+OOPBtkYgqmpKTNnztTYsfnZZ5/x+PFjOnfuTNeuXSlXrhwxMTGcOXOGu3fv8uWXX+bHFRI9evRg//79zJo1S21H/c2bN9m1a5eGvaOjIy1btmT69OkMHz6czp0706NHD0qXLk1YWBi7du3C09OTzz77TGozduxYTp8+TY8ePfjwww+Ry+X8/fffhISE8NNPP70SvZAVLNu7dy+ZmZmEhYWxb98+rK2tpVqZRYkh+rTZvPfee5QrV84g/YauxX///ReFQqF1N25YWBjjxo1jzJgxVKhQgcjISB4/fkzNmjUxNTWlSpUqrFmzhj59+hAYGKgWgKxTpw5lypRh1qxZfPTRR9y+fZsbN25I511cXEhLS2Pv3r04Ojri5+dHcnIyDx8+5MGDB1pr0OrSow99eiBrF7hMJqN27dpGjV25cmXatGnDpEmTGDZsGElJSaxZs4ZBgwZhZWVF7dq18fDwYOrUqfTs2ZOgoCDOnTunVac+vxY3BfWjIfz222+YmppiZ2fHunXr+OCDD/JMTe7h4cGHH37IuHHjGDJkCAqFgm3btlGyZElWrVr1yubz66+/Ympqir29vV7N+tYLZO2E9/Pzk+qQF2SOxmCIPwQCgUAgEAgEAoFAIBC8PohtdQLB/wA7duzA29sbHx8f2rVrx3vvvcfPP/9c3LIEgnzTqFEjabeVlZUVI0aM4OOPP5bO16xZkypVqkiv69SpIwWCbGxs2LdvH927d+fx48ecPHmSO3fu0KhRI/z8/KhatapBNrn7za0rm2bNmjF06FB8fHykY6ampqxfv55Vq1Yhk8m4fPkyYWFhdO7cmb///psPP/zQKF9o20E6d+5crKysuHPnjmSnUCg4deqUxn9Xr14FstJk/vTTT0yZMoVnz54xd+5cLl68yBdffMHGjRvV0mqWLFmS33//nY8++ohHjx4RFBSEj48PBw4cUKvVqM1HhaW3UaNGyGQyjh8/zsmTJ3n27BmfffYZu3btwsXFpcA+zIm2eRiiT5tNZGSkwfoNXYuXLl3Ks9Zkw4YN2bBhA0+fPsXX15fAwEDWr1+Pt7c3AOvWraNSpUocOXIER0dHZsyYIZ1TKBT8/PPPlCtXDl9fX0qUKMHQoUOlndNeXl6sXLmS69evc/r0aXr27MnixYtp0qQJhw4dArIeqChRooTBenShTw/A2bNn83ygQt/Yq1evpmvXrhw7doxLly7x+eefM2XKFCArG8X27dvx8vLCz88Pc3NzFi9eLNValsvl+Pj4SME9XX7N9kvOQGC9evXU1mGFChV477339PokP/0V1I+5+889dx8fH5YsWcKTJ084fPgwbdu2ZenSpWpac64JgOXLl9OrVy/OnDnD33//TYcOHQyuT1MY8wGYOHEijx8/5tChQ/j4+OjVrGu9AMyZMweZTEZQUJDeOWrzYc7xSpUqJT0EUhj+EAgEAoFAIBAIBAKBQPD6IFMZWwxL8MpITEzk9u3bVKtWTWtNudxkZGQQEBBAnTp1ijSdVWGPE3vG3ug2to1fGt0m7Avj0mGWnhtk9BjhHZsa3abUgVMax4y99rp48OABvXv3Zvbs2dSpUweZTMbVq1eZP38+mzdvpkaNGgXqXyAQvL2MHz+e5ORkNm7cWNxSBMWESqXiypUrVKxYUQocrV69mkuXLrF9+/bXUs/Vq1c5cuSIqMmug7fNjwWdT0pKCrVq1WL37t0G7fB+3TH2fZv9vdPT0xMbG5tXLbdQeFW/g4qa4phHYf7uEAgEAoFAIBAIBAJB/hBpkAWCt5yrV6/SvXt3OnbsKB0rW7YswcHBnD9/XgRrXyFjxozhyZMn/PLLL1hbW6udu3z5MjNnzqR79+4MGzYMgAULFmBhYcHEiRMluz/++IODBw8SHh6OUqmkQoUK9O/fXy31qT6b3P2OGTOG58+f88MPP0g1JyGrxuDIkSM5cuSIdCwmJoaffvqJc+fOERMTg4ODA40aNaJv374ac9Lni+ydRpC1o8jZ2ZlmzZrRv39/KU13brucDBo0iD59+gDw8uVLfvrpJ86fP09MTAyOjo40adKEXr16SekoAQYMGEDPnj016iTcvHmTiRMnsnv3bqytrbX6qLD05rRRKpU4ODhQr149+vTpI9UxBIiLi+PMmTN5+nDz5s3ExcVpPXfw4EEUCoXeeeSlr0mTJvTp04fhw4fz0UcfsXDhQmrVqkXbtm359NNPDdIPhq3XoiA1NZVOnTqxePFiwsPD87RTKBS0adMmz/Zr166lcuXKRSn1tUcmk7Fy5UrkcjkDBw4kIiKC7du3FzhVtzb0rfns66VPz8OHD3XWQikujh07xrZt29i2bZtB9vfu3WPBggWkpKQwePDgPO3yWse6MOS66vNjtr6MjAy2bNkivWfc3d0L9f3ztq+LbAz93CksfwgEAoFAIBAIBAKBQCB4fRDBWoHgLSc9PR0TExON45aWliQkJBSDov9dQkJCCA8P58iRI/To0UPt3N69e3n+/DnR0dHSscjISLUdDhs3bmT79u1MmzYNT09PkpKSOHz4MP/H3n1HRXW8jx9/L1URUZpg74Uo2Cto7GIDrDH2EntsEY3GXmM0JmqM3dh714glxlhiwWhEMbH3giiCqKCUZX9/8Nv7ZWHZAtjyeV7ncI5779y5z8ydXZVnZ6Zjx47s2LGDkiVLmlQmdb0PHjzg3r17LFq0SGdP0vj4eG7fvq28fvjwIZ07d8bNzY1OnTrh7u7O3bt3Wb58OXv37mX9+vU6iVFjfVGjRg3atGkDQFJSErdu3WLOnDncuHGD6dOnK+WqVatG69at09SRN29epUyXLl1wc3Ojc+fOuLu78/DhQ1atWsWWLVtYt24dTk5OANy9e5cXL16kqev169fcvn2bpKQkvX2f1fFq64qLi+Pu3btKnEuWLFH2U4yNjeXcuXMG+7BRo0Z676WdjaOvHabEFxUVBSQvcbtq1Sp27drF2bNnady4scnxmzIW3xaNRsPt27d5/vy5wT60srLSm+SysrJi6NCh5MmT563F+DFZtGgRGzZs4MCBAzg4OPDTTz+ZtGSxuYyNee3z0hfPxYsX+fPPP/Hx8SEgICDLYwNYvHgxZcuWxcfHJ0PXv3z5kvv375tcfunSpVhaWhIYGMiBAwfSLaftF3PjM/ZcjfWjNr5JkybpvGe07783b96YFIcxmRkXprYn9RLEWcWcZ2Lq505W9YcQQgghhBBCCCE+HJKsFeI/rly5csybN4+mTZvi4eEBJC+NvH79esaNG/eeo/vfU7NmTXbt2qWTrI2Li+O3336jSpUqBq8NCgqiW7duNG/eXDnm5eWFj4+PssyhKWX06dWrF8uXL6dVq1YULlxYb5mJEyfi6OjImjVrlC8AVK1alUaNGtGiRQv27NlDhw4djHfC/5cnTx6d5SbLly+Pra0tI0eOZNKkSco93N3dqVChQrr1jBs3DldXV9auXYuVVfJfa1WqVMHX15eAgACmTZvG7NmzTY7rbcebuq4qVarQunVrAgMDGTZsGAcOHMDa2ho3NzfGjBmTbh1nzpwx6V6pmXtN1apVqVq1qtnxZ3QsZiVnZ2eDfZgeCwsLfH1930JEHyd7e3tlxv/bZGzMG4pn0aJF6X52ZZWTJ0++9Xuk9PTpUypWrEiVKlWM/v0A5seX2eeqjU+7R7X2PRMXF5fhOvXJzLgwlbW1NfPmzcvQtYaY80xM/dx5m/0RNbwPOZdsMOsaIYQQQgghhBBCZJ7F+w5ACPF2eXh40Lp1a1q3bk2lSpWoWrUqzZo1o2bNmnh7e7/v8P7n+Pj4EBoaysOHD5Vjhw8fpnTp0kZn9Dg7O3PkyJE0M0O9vb1xcXExuYw+xYoVo02bNkyePFnv+efPn3P8+HH69euXZqZ2rly5OHjwoFmJ2vTkzp2bhIQEk3/ZHx4ezsmTJxk4cKCSqNWytbWlf//+HDx4kFevXmU6Nn3MjTc9KpWKESNG8PDhQ/76668siu7d0Re/KWNx8uTJzJw5M916o6KimDJlCu3ataNLly5s2bJFOXf//n1Gjx5N69at6dChA3PnziU+Pl5vPZGRkUydOpUOHTrQqVMnvv/+e2VMJCQk4Ovry4kTJ+jcuTPbtm0jPj4eX19frl+/DsCLFy/47rvv6NChA126dGHx4sUkJCQo9R84cIBevXrh5+dHz549Dc6CTC29a1+9eoWvry937txRyu7fv18n+XLjxg0GDx5Mq1atGD9+PIcOHaJz584m9ZG+dme2LcbiyWhfGGvLyJEjOXfuHNOmTWPChAlG+y69tptzDzA+Lm7evMmgQYMICAhg1KhRyox1UwwfPpzz58+zbt065cs95sZnTGaeV+r4Ur9ntPF++eWXBAQEEBgYqCxJnl7/G+vPt9me169f4+vry59//mlWzIY+W8wdMyn7UK1W4+vry7lz5xg+fDj+/v4MHDiQW7duvZP+EEIIIYQQQgghxLslM2uF+B8wbNgw2rZty5UrV1Cr1ZQuXZqiRYu+77D+J+XIkYP69euze/du+vfvD8Du3bvx8/MzuKwhwDfffMOXX35J7dq1qVKlCtWqVaNOnTrKjGlTy+ij0WgYMmQIvr6+HDx4kMaNG+ucv3XrFhqNhtKlS+u9Pnv27KY036CYmBhWrlxJxYoVdfa/Xb16Nbt3705TfvPmzcreqem1z8PDg/j4eB48eECZMmUyHWNm43VwcEi3Pnd3d3Lnzs3NmzepVatWlsaaUkbjMyZ1/KaMxb59+6JSqfTWp9Fo6NWrF6VKlWLq1KlEREQQGBiItbU1AQEB9O/fn/LlyzN37lyioqIYOnQoVlZWDBw4UKeepKQkvvjiC4oWLcrMmTNJSEhgypQpDB8+nMWLF2NlZcXt27dZvHgxbdu2pXz58jrLuGo0Gnr37o2rqyszZ84kLi6OCRMmEBYWxsSJE7l9+zaBgYEsXLiQ4sWLc+XKFQIDA8mfPz/lypUz2GeGri1UqBC3b9/WSUCnXEY3Pj6eXr16Ua9ePUaMGMGVK1eYNm2aTn8a6iN97c5MW0yJJ6N9Ua5cOYNtmTx5Mn/++SeBgYH4+voSFxdnsO/0td1Yf6W+h7FxkZCQQK9evWjcuDHffPMNd+7cMWs1i2nTpvHkyRMqVqxIv379zI7PmMw+r9Tx6Vv6eOnSpYwcORJnZ2e+++47Bg0axJYtW9J9zxnqz7fdHgsLC27fvs2PP/7IN998Q86cOfnuu+8YPHgwmzdv1huzsc8Wc8dMyj60tLTk9u3bzJw5k6FDh+Lm5sbkyZOZNm0ay5cvf6v9oVarTeqzD4027o81fq330Y6Pvc+EEEIIIYQQ4r9AkrVC/A+4efMmERERyt6M586dIyoqikqVKr3nyP43+fv7M336dPr378/z5885c+YMM2fONJqsLV68OHv27CE4OJhTp05x6NAhfvzxR6pVq8acOXNwcnIyqUx6cubMSWBgINOnT6d27dp6y6ScVXv9+nUGDRqkvHZzc2PVqlUm90PKpKFGoyE8PJxy5cqlWbLY19dX2Ss2JTs7O+UXjLa2tnrvkS1bNoAs2TsxK+I1Jlu2bCYnF1LHpJU/f36Dv8zPTHzGpIzflLHo5uaWbl2hoaH8+++/rF69Gnt7e0qXLs2ePXuUZ71ixQpy5sxJtmzZKFiwII0bNyY0NFRvPf/88w+//PKLMnv9q6++ol27dkRGRirviaZNmyp7WqacKR0aGkpISAinTp1SygYGBtK1a1e++eYbVCoVarWaFy9e4OTkRL169Th27JhJ+zcbulbf3sopXbhwgadPnzJixAhy5MhBwYIFOX36NH/88YdSxlAfaZ9TynbfuXMnw20xJZ6M9oWxtmjHna2tLba2tkZnuutru7n3uHjxosFxceHCBcLDwxk6dCh2dnbkzZsXPz8/du7caVJ/ZMuWDUtLS6ytrZX3pjnxGZPZ55U6Pn193qVLF2WP1KFDh9K2bVvCw8OV933K/jfWnzY2Nm+1PSljrly5skkxX7hwwehnizljRp/PP/9c6cM2bdqYvKR/ZvojJCTEpHt8qPT9PfAx+q+0QwghhBBCCCGEaSRZK8R/3PPnz+nYsSNDhw6levXqAERHRxMYGMiuXbsoWLDge47wf4+Pjw8xMTHKL3p9fHzImTOnSddaWVnh7e2tLGF98+ZNevXqxeLFixk9erTJZdITEBDA5s2bWbBgAX5+fsrx/PnzA8mz3/LlywdA3rx5mTRpEgB//fUX27dvN6MXoFmzZrRr1w5I/kX9jBkz+O6775R7aaXeKzYlbSx3797Fy8srzXntTDptOSsrK71L5WqTuYYSAlkRryHR0dE8ffqUAgUKmHxNo0aN8Pf31zmmTVCnJ6PxGaMv/syMxQcPHuDg4KAzaznlUt43btxg69atPHz4kJiYGJ4+fUrZsmXT1PPw4UMcHBx0lhnXjoewsDAlaZLeagMPHjxApVLRsWNH5VhSUhIJCQk8evSIIkWKMHfuXJYtW8Y333yDl5cX7dq1o2XLlgbbB2Tq2idPnpArVy6dRGrp0qV1kjGm9FHKdr/teAwxdm9Tn7c5Uj9zc+5hbFw8efIEBwcHnS9BaMddRmVlH2T2eZki5V6t2rY/efJESXym7H9T3meGZFV7zInZ1M8WU9uYN2/eNPGk/Dy1trY2eVnozPSHufugfyjUajWhoaF4enpiaWn5vsPJsPfRjtjYWK5du/ZO7iWEEEIIIYQQQj9J1grxH3fkyBFq1KjB559/rhyrX78+LVq04ODBg/Tq1es9Rve/ydLSkubNmxMUFERoaChffPFFhusqXrw4NWrU4O7du5kqo6VSqZgwYQKfffaZzi9s3dzc8PLyYvXq1Urizd7eXvkCgDl7MWq5uLgoS+J6eHhw9OhRxowZw8qVK02uo3jx4hQpUoT169frTdZu2rQJLy8v8uTJA0DBggW5cuVKmnKhoaHky5fPYKIzK+I1ZNOmTdjZ2SmzqEyRN29eqlSpkiX3zyxT4jdnLDo6OhITE0NCQkKafZKvXbtGr169mDp1KvXq1SNHjhz8+OOPen/Z7OjoSGxsLImJicq+xtHR0QA6yZTUex5rOTk5YWVlxapVq7CwsEhTNyQnzRs1asTLly85fvw4kyZNwtLSkmbNmhltZ3rX1qlTB0iexa318uVL5c85cuTg9evXOnU9efLE7D5K3e6MtsVYPKZI794lSpQw+XkDynNKr++0UrbdnDEFxsfF3bt3iYmJQaPRKDN5M/I5mdH4jMmK52VMyr3CtX9OmdhM2f+mvM8Myar2pJzRHhMTYzBmUz9btIy1MSuXos1Mf3zMiU5Ijv9jbwO823b8F/pLCCGEEEIIIT52FsaLCCE+ZnFxcUqiKiV3d/csWRpWZExAQAC//fYbd+7cSXfJ4ZSePn1Kz549OXr0qE4C4sKFCxw9epTq1aubVMYUZcqUoV27dvz44486x8eNG8fJkyf59ttvlaRDQkICJ06cYMGCBTozkjJi/PjxXLx4kU2bNpl13TfffMOePXtYsmSJMqZfv37NwoUL+eOPPxgzZoxStlOnTuzdu5c9e/agVqtJSkri6NGjLF++nG7dur2TeFOLi4tj1apVzJs3jzFjxpi0hOmHRF/8WTEWPT09sbe3V/o3ISGBYcOGsWHDBu7cuYOtrS3NmzdXEmOHDx/W+5nm6elJzpw52bFjh3Jsy5YtlCpVCnd3d5PiyJUrF3/++Seurq64urpy/vx55s+fj5WVFUFBQfTv35/4+Hhy5sxJ06ZNKVSokEmJEUPX2tvbkz17di5dugQkJxuDgoKUa7X7MR89ehRIToYdOHBAOW9OH5kSjzHG4slMX5jSFgsLC+W1sb7Tx9x7GBsXn3zyCQD79+9X+kPfXtGmMjc+YzL7vEyxc+dOkpKSANi3bx/u7u56Z4+C8f40JqvakzLm/fv3G43Z2GeLOWMmK2W0PxxnL8nSOIQQQgghhBBCCGEamVkrxH9c2bJlWbhwIR06dKB48eJA8lKK27dvZ9y4ce85uv9dHh4e2NvbU7du3TSzBvVxdXXF19eXqVOnEhERocw6tLS0pGvXrnTr1g0LCwujZUw1ZMiQNMkNLy8v1q9fz8yZM/H29iZnzpzExMSQJ08e2rVrR8+ePc3uh5Tc3d0ZOnQo3333HbVr11aWk1y6dCnr1q1LU97Ly4uFCxfy6aefsmDBAr7//nt++ukncufOzfPnzylTpgwrVqzQmSHcuHFjJkyYwMyZMxk9ejQqlYocOXLQp08fs5O1GY0XYPny5WzcuJGkpCSioqIoXLgws2fPpkmTJmbFkBGmxKevzPjx45X4jMVvyngFmDx5MtmyZWPkyJFp4rG3t2f27Nl88803/PLLL0RGRlKhQgWaNm2KlZUVRYsWpVGjRtjb21OgQAECAwP56quvmDp1KiNGjNCp58cff2TMmDGsWbOG169fY2dnx6xZs0zaHzhHjhzMmTOHMWPGsGzZMiwtLYmNjWX69OkA1KlTh927d1O7dm3y58/P06dPKV26tLIv8NSpU7GysmLUqFFp6jZ27YABA5g0aRIrV65EpVLRokULtm7dCiTPdh86dCiDBw+mRIkSqFQq6tevz549ewCoVauWwT4aO3as2fEYYiyezPSFSqUy2pZq1aoxadIk9u3bx+LFiw32nT6m9FfqexgaF66urowcOZKvv/6auXPnkpiYSKNGjYwmjbMyvrf5vAzRJjsLFSpEixYtsLKy4vHjx8yaNSvdpKSx95kxWdUeFxcXmjdvjo2NDWFhYQZjNuWzxZwxk5VM6Q8hhBBCCCGEEEJ8OFSalFNexAclNjaWy5cv4+HhobPnWXrUajUhISFUqFDhrS5nldX3eXEit9nXOHg/N/uasAnFzSqfd9JNs+/xuKXxGZKpue85nuaYuc/emB9++IFly5Ypdb169Yr27dszefLkTNctTPfgwQNy586t7MH59OlTsmfPrrx+8uQJVlZWyvKJ4eHhqFSqNDOjo6OjefHiBTly5NC71KKxMqnrTR2X1pMnT3j58qWS5E/p9evXREREGIzBWF/kyJEjzfKWSUlJ3L59GxcXF3LlysWDBw+Ii4vTW0f27NnT7AGp3aO5fv36BAYGpnt/jUbDkydP0Gg0uLq6pvks09dHWRVvyjIqlQpHR0eTlvlMLb2YjLXDnPhScnNzw97e3uz4zRmLhtpha2ursxyp9hlaW1sr9UZERGBpaUnu3Lm5desWBQoU0JmpHBERgbW1Nbly5dKp/+bNm+TPn19ZBluj0ei9PjIykoSEBPLkyZMm0fvq1SuioqJwdHTUeS9duHCBTZs2GUzIpHet9tzz58/Jly8fb968ISIigkKFCinn37x5w7Nnz8ibNy9btmxh3bp1ygxOQ33k6OiYpt2mxGOMoXgy0xfG2pKUlERYWBguLi7KMzPUd/ranpF7gOFxER8fr+x5mpCQwNOnT01ehSAsLAxbW1sllozGZ0hmnlfK+FK+Z6ytrbl9+zaFChVCrVbz7Nkz3N3ddT5n0xt7YLg/31Z74uLi8PLyYtu2bZQoUcLsmNP7bDFnzKT+3El9v1evXvHs2TOzVrEw1B8paf/dWapUKXLmzGly/R+Sd/X/oLftfbQjq//fIYQQQgghhBDCfDKzVoj/AV999RXt2rXjypUrqNVqSpUqRbFixd53WP9zChQooPPa1dVV53XqhJWbm5veenLlypXmF8LmlEldb+q4UsaTXhIte/bsFCxY0GAMhqR3TwsLC53kcHrl0pM7d25at27N8uXL6dy5c7rL3KpUqnT7F0zvo4zEa26bMlOPqe0wp4y58ZszFtOjr5y+Z+ji4qL8Wd+XDFKeTyl1WZVKpfd6Q19MsLe315vYvHr1KuXKlUv3OkPXAgQHBxMTE0OBAgWws7NTko0ajYbevXtToEAB2rRpg6urK3v37iVv3rycPXuWKlWqKH2kVqs5f/48YWFhWFtbU7RoURwdHXXaqFaruXjxok6ZlDEFBwdjaWmp7JH8+++/A9CgQQMlnv79+9OwYUMsLCxo0aIFe/fupXz58kDyUsS//vorACdPnsTLy0tvm9PrC5VKxaVLl5Q9QSH5/ZcnTx5lOdr8+fMrsaUsl1JsbCxlypRR2v7y5UtCQkKIjo7G2dmZihUr6iTjXFxc2LdvH6VKlaJ48eLKPQCePXvG0aNHadGiBTY2Nnr7SF+8Tk5OOgkxQ/F+8sknODk56ZSxtLTE2dkZLy8vnTFtYWGhE58+2no0Gg1r1qyhQoUKeHl5kZiYqDwvbTtu3bpFuXLlTIrv8OHD5M+fX0lIavvX2tqa/Pnz643f1dVVb+IzV65cXLx4kXPnziljsUSJEgbbpR1/fn5+NGvWjPj4eJ3xB6a9FzUaDdmyZVP68f79+/zzzz/4+vpSpEgRdu3aRb169dJ8QSW9z5b0nom+z5LUnzupP4MMfU7oa4ex/hBCCCGEEEIIIcSHQ5K1QvwPiI6OxtLSkkaNGnH79m1+//13Xr9+TdmyZd93aOI/5ubNmwwcODDd8zY2Npnat9EUXbt2JTg4mMaNG5MnTx527979Uc0U+RD6UGSdTz/9NEMzp7XmzZvH1atXKVKkCF5eXspx7azmDRs2sH//fp0vDmzdulVJGN64cYO+fftib29PqVKlePPmDcHBwXh6erJgwQJsbW2Nlnnw4AH9+/dHpVIpXzJ5+PAh8fHx5M2bFwcHB3bv3k2LFi2YNGkSL1684Pvvv6d48eIMGTKEhQsXsnjxYvLmzUu+fPmYNGkST58+ZdSoUbRv396svlCr1cqXjdRqNbdv3+bZs2f8+OOP1KpVSymXkJBAkSJF0tSRPXt2ypQpg0ajYdGiRSxatIjChQvj7u7Oo0ePCAsLY9iwYXTu3Fm55ttvv6VPnz5pkme3b99m9OjRNGzYEBsbG9atW4ednZ3S9+nF++TJE3LkyEH27NmVvtRoNMqS+BYWFsq+ztp4U9YVFxfHnTt3ePToER07dmT48OHY2NgocRn6DHn48CEAtWvXxsLCgq1bt7J7927i4+OpWLEiQ4YMYfLkydjZ2TFs2DAcHR1p166d0f6cN28eTZo0oUyZMkafnaH49Y3FkydPolarcXNz0zvTVvuZ2KJFCyZPnszChQt59uyZMv60MvJe/Pvvv5k7dy6+vr6o1WrWrl1L+fLlM/WezixT/44w1h9CCCGEEEIIIYT4cEiyVoj/uFevXhEQEMCAAQNo1qwZnTt3plChQixevJgdO3Zk2Sw/IQCKFi3Ktm3b0j1v7pKWGWFjY8PSpUuJiIjAysrqo0rUwofRhyLrmDp72BAPDw927typk6yF5KRN6dKlKV++PF9//TX29vYMHjxYp8yMGTOoVq0a3377rXIsMjKSYcOGcenSJSpXrmy0TMWKFalRowZ2dnZMmjQJgA4dOpAzZ05evHih7G/cokULihUrRqtWrTh48CD29vasXLmSxYsXs2DBAiWZCrB9+3a++eYbChUqRI0aNUzui2bNmjFgwACdY1OnTuWbb77hyJEjyrEWLVqkKZfSihUrWLJkCYsWLaJmzZrK8d9//50hQ4Zgb29PQECAyXGZE++UKVP47bfflPd5hw4daNCgAb179waS3+P6PrdS13XmzBmGDx9ObGwsU6ZMUY4b+gzp0KEDDRs2VJJ2CQkJPHnyhFy5cqWZtZly7BrrT1OYEr++sRgREcHQoUPp37+/zh7kWtrPxBYtWtCkSROT2pOajY0NQUFBBv9NZGNjw/bt201q69tk6t8RxvpDCCGEEEIIIYQQHw6L9x2AEOLtOnbsGKVLl6Zdu3YcPnyYkiVLsmHDBj777DMOHTr0vsMT/zEWFhbkyJEj3Z93mTh1cXHR2eP0Y/Eh9aH4MNStW5e9e/eSkJCgHLt58yZPnjyhbNmyBpdHffLkSZrlwJ2cnFi1ahWVK1c2qYyFhQVWVlZYWVkp49DCwoKOHTsC6CSwrKySvwdob2+PWq1m0aJFdOvWTSdRC9C6dWvGjRuXJftjNm7cmLCwMF68eGFS+fj4eBYuXMgXX3yhk6iF5GWdP//8c+bPn5/puNLTpEkTwsPDUavVSl/a2NiY/R6vVq0a48ePZ8uWLdy/f185bugzxMLCQpnBC/+3TPH7SOTpi1/fWHRxcWHt2rV4e3uTI0cOLl68yOXLl/X2l7W1NW5ubly6dIlff/2VU6dOkZiYqFPfo0eP+P333zl69ChPnjwB/m8JYltbWy5evEhQUBA3btzQuU6tVrN9+3aioqKIj49n+/btOmPuzp07/Pbbb0DyXrXbt2/n1atXhISEsHfvXu7duwckL60cFBTExYsXTe6rlPVdvHiRI0eO8OzZM3LkyEFkZCRHjx7l5s2bafrjypUrXLhwgWfPnhEeHk5QUJDB+0QN78PjlrVNjksIIYQQQgghhBBZQ2bWCvEf9+zZMz755BMATp8+Td26dQHIly8f4eHh7zEyIYQQpihRogR58uTh6NGjNGzYEIBdu3bRrFkzownKFi1aMG/ePGJjY6lfvz4VKlRQ9hU1p4w+KpWKcePGMXDgQJo1a5ZmH+6bN28SFRWlxJxap06djN7DFFevXiVnzpw6id/Lly/rnQXZokULLl++zIsXL2jSpIne+nx9fVm9ejX379/P1N7cWRVvyiWOU6tXrx5WVlacPXv2rcSa2fiMSR2/KWPx+vXr2NraKstNpxQbG0v79u1xcnKiePHiXLlyhejoaDZv3qzM9F64cCGNGjUiISGBwMBAxo0bh5+fHwATJ07k8OHDNGjQgG3btqFWq5W6ExMTGT16NFu3bqVw4cKMHj2acuXK4eDgAMBff/3F8uXLadSoESqVitGjR3PixAni4+N58+YNo0aNYtCgQRw/fpy8efOyf/9+xo0bR7t27Yz2U0bqmzBhAocOHaJ+/fqsXbuWPHnycOHCBZo1a5bh5yWEEEIIIYQQQoi3Q5K1QvzHOTs7ExISQmxsLEePHqV79+5A8gyQfPnyvd/ghBBCmMTPz49du3bRsGFDNBoNv/76Kz/99BNr1qwxeF2fPn0oVKgQGzZsYP369UDyjMbu3btTu3Ztk8ukp3r16nz66ad89913fP/99zrnnj9/DqAzUzIqKoo//vhDeW1nZ4evr69pnYBu0jApKYlbt26xYcMGAgMDdZYIv337tt4lwxs3bkxUVBQAefPm1XsP7d+NERERmU6AZkW8hpKhVlZW5MmTR+lrc2PSsre3p3Hjxulek9H4jEkdvyljsWvXrunWd/36de7evcv27duVuJYuXcqzZ8+IiYnh+++/55dffqFatWoAbNu2jWnTpuHr60t4eDgbN25k586dyt67qZcVN5W2r4oUKcKgQYOA5MT2kSNHWLduHSqVily5cvH777+bnKw1p7579+6xadMmtm3bRtmyZUlKSqJLly4mL6OfMkn9sdDG/DHGntL7aMfH3mdCCCGEEEII8V8gyVoh/uPq1KnDd999R61atahevTolS5bkt99+Y/v27ezYseN9hyeEEMIEfn5+zJ8/n+fPn3P9+nWyZctG2bJlTbrW19cXX19f4uLiOH/+PLt27aJ379788MMPyiw7U8qkZ+TIkTRt2pQzZ87oLD2eK1cuAJ4+farMuo2Ojmbv3r1A8soPL168MCtZe+fOHY4fPw7AvXv3uH37NsuWLVOWdNbSt1eslnYmpHYZ2dSePXsGoCwnayzBZeh8VsRriEajITo6GkdHR5OvuX79OvHx8TrH8uTJYzBZm9H4jNEXf2bGYpkyZShbtix+fn40aNCAmjVr0r17d6ytrTly5AgWFhZKohaSv2zw/PlzHjx4wO3bt8mWLZuSqNWev3TpUobbV716deXPbm5ufPLJJ8p4cXNz459//nkr9V2/fh07OzvlM8LCwoJPP/2UjRs3mnSfkJAQs+L6kISGhr7vELLEf6UdQgghhBBCCCFMI8laIf7j7O3t2b17Nzdv3qRcuXJA8i/0VqxY8VaXTBRCCJF13NzcqFy5Mvv37+eff/7B39/f7DpsbW2pUaMGNWrU4OXLl+zbty9N8suUMvpiGzhwIJMnT9aZXVu0aFFy5crFqVOnlOX4ixQpwvLlywHYv38/M2fONKsNTZs2VZKGz58/p2nTpvz7779pkp+GlC5dGhsbG4KDgylUqFCa83///Tc5c+akWLFiQHJy9+nTp2nKPX78GGtra4P7vWZFvIacO3eOV69eUbFiRZOv8fPzeyuJ14wwFH9GxqKtrS3r16/n7NmznDhxgtmzZ/Py5UtWrlxJfHy8sqeylnb/3oSEBL3nLS0tTW6LvtmJqWcdp3ytUqnQaDQm129OfXFxcWnKmrMvcYUKFcyK60OgVqsJDQ3F09PTrOf2oXkf7YiNjeXatWvv5F5CCCGEEEIIIfSzeN8BCCHevly5clGpUiXlF3deXl54enq+56iEEEKYw9/fn0OHDnHo0CFatmxptHxMTAynTp1KM4tSO5vR3t7epDKm6NatGxqNhk2bNinHbGxs6NixI4sXL+bevXtprrl+/bpJdacnd+7cjB49mh9++IH79++bfF2OHDlo3bo1P//8MxERETrnnj59ypIlS+jUqZOSyKtRowb79u3jzZs3Sjm1Ws2mTZuoXbu2yUvLZjTe9ERHRzN9+nTq1atH4cKFM13fu5Y6/qwYizdu3CA4OJhq1aoxbNgwduzYgYuLC3v37qV48eLExMTojMXLly9jbW1NwYIFyZ8/Py9fviQ8PFw5n96s2mzZsqFSqYiJiVGO/fvvv+Z2wVuTN29eoqOjiYyMVI6ZMlvWcfYS3Pccx9LS8qP8Ad57DB9rO4QQQgghhBBCvF8ys1YIIYQQ4iPQuHFjpkyZgoeHh8l7jk+dOhVbW1saNGiAk5MTMTExHDt2jFu3bjFx4kSTyxhjZWXFuHHj6NWrl87xgQMH8uDBA/z9/WnZsiWFChUiOjqaEydOEB4eztSpU83pgjS0e/l+8803rF69WkmchoSEsHLlyjTl3dzcaNq0KSNGjODu3bv4+fkREBBA3rx5efToETt37qRq1ap8+eWXOm04deoU/v7++Pr6YmFhwR9//MGLFy9YvXr1O4kX4OLFi6xdu5akpCTCwsLYs2cP+fPnZ/r06WbFkBGmxKevTO3atSlevDhgWvymjMVTp05hbW1NlSpV0sQTHR3NoEGD6NmzJ0WLFiU8PJzbt28zfPhwihcvTosWLRg6dCg9e/bk9evXLFy4kL59+2JnZ4enpyceHh589dVXtGnThps3b3Lu3Dm9/WFjY8Mnn3zC7Nmzad++PVevXuX27dsZ6Nm3o3z58hQpUoSRI0fSrl07Ll++zI0bN953WEIIIYQQQgghhEiHJGuFEEIIIT5Q9evXp0CBAgBkz56dwYMHU6RIEeV85cqVdfZdrV69urKKQo4cOdixYweHDx8mNDSUx48fY29vj5+fH82bNyd79uwAJpVJWW/quLRq1KjBoEGDuHPnjnLM2tqa77//ngsXLnDs2DHu3btHjhw56NWrF/Xr11fqN7UvUu4nqjVx4kR+/vlnrl69SpkyZahfvz5hYWFcuXIlTVnt7Fh7e3tWrFjBsWPHCA4OZvbs2VSpUoUff/yRGjVq6FyTO3dutm3bRlBQEJcuXUKj0fD555/TvHlzndme+vooq+LVlrl06RIqlYrcuXMzadIk6tata9asuPRiSklfO0yNL3WZ8uXLmxy/qeP1+vXr2Nra6k3WVq5cmTVr1rB//35OnjyJk5MTv/zyi7J36/fff8/evXu5ePEi1tbWTJw4kTp16gDJywivXr2aDRs2EBISgoeHB7NmzWLXrl1A8r6vrVq1UvbXXbhwIRs3buTs2bNUrVqVFi1asHv3biWWVq1a4eTkpLz29vbWWXa7ZMmSJCQkGHwWKZlTn4WFBevWrWPDhg2cPHmSatWqUbRoUebPn2/y/YQQQgghhBBCCPHuqDTmbpYk3pnY2FguX76Mh4cHdnZ2Rsur1WpCQkKoUKHCW13OKqvv8+JEbrOvcfB+bvY1YROKm1U+76SbZt/jccvaZl/jvud4mmPmPnshhBBCZNxXX31FVFQUK1aseN+hCJFpGo2GP//8Ew8PD1xcXAD48ccfCQkJYdWqVWnKa//dWapUKXLmzPmuw80S7+r/QW/b+2iH/L9DCCGEEEIIId4/mVkrhBBCiLeue/fu3L59m927d5MrVy6dc6dOnSIwMJDPP/9cWX527NixZMuWjbFjxwKQlJTExo0bCQoKIiwsDCsrK4oWLUq3bt2oWbOmyWVS19u9e3eePn3Kpk2bdGZJ3rp1iy5dunDixAnl2JMnT/jll184ffo00dHRODo64u3tTc+ePZXZdqb2Rcr9WlUqFXny5KFOnTr06dNH+WV56nIp9e7dm+7duwMQHh7OL7/8QnBwMNHR0Tg7O+Pj40P37t3JnTu3ck2rVq3o3Lkzbdq00anr4sWL9O/fnwMHDmBvb6+3j7Iq3pRlLC0tcXZ2ply5chQuXFhn1mBKFhYWBAQEGOzDlI4dO4alpaXRdqTk7+/PwYMHqV27NpUrV2bWrFnKnrXp3Vcbf+XKlenWrRsFCxZUypkyFrPS8+fPOXz4cLrn9fXh+3bgwAGWLFnCtm3bTCp/6dIlxo8fj1qtVma7fkhSxrdlyxbq1avH8uXLKVasmPJnfbOa38azU6lUrFy5kpiYGDp27Mjjx49ZvXo1M2fONLdZQgghhBBCCCGEeAckWSuEEEKIty4qKoo3b94QFBTE559/rnNux44dJCYmEhMToxx78eIFiYmJyuv58+eza9cuJkyYQOnSpXn9+jVBQUH06tWLLVu2ULZsWZPKpK43KiqKJ0+e8PPPP/P1118rxxMTE4mIiFBe37p1i86dO+Ph4cGwYcNwc3Pj3r17LFq0iIMHD7JlyxYcHBxM7osWLVrQsWNHIHkm1a1bt/juu++4d+8eP/zwg1KuWbNmdOjQIU0d2sTmzZs36dKlixKXu7s7jx49Yvny5ezatYuNGzfi5uYGwLNnz3j9+nWauuLj44mIiCApKUlv32dlvCnriouL4+7du6xdu5bt27fTtGlT8ufPn+ZafUlTQ/fSzkbT1w5D8TVt2pTevXvz5MmTNOf19YU2/s2bN+Pn58fChQuVJZRNGYtZKSEhgbt37yqvz5w5g5ubG4ULFwb092Fm/fjjj1SoUIF69epl6Po3b94QFRVlcvkVK1aQJ08epk2b9k7iM1fK+KysrJg1axYFChRAo9EQERGR7pLHqZ9dahl9dvPnz2f79u2cO3cOBwcHVqxYQYUKFTJUlxBCCCGEEEIIId4uSdYKIYQQ4p3w9vZm165dOsna169f88cff1C9enWD1x46dIiOHTsq+0sCDBgwAB8fH2VGoyll9Pniiy9YuHAhrVu3pmTJknrLTJw4kUKFCrF06VIsLCwAKFOmDD4+Pvj5+XHw4EHatm1rvBP+v1y5cimJNIBixYqh0WgYOnQo8fHxyp6hjo6OFC+e/jL+48aNo3jx4ixbtgyVSgVA6dKl8fHxoW3btkybNo158+aZHNfbjjd1XaVKlaJRo0aMHTuWo0ePcujQIWxtbU2KyZR7mXONo6Mjbm5u+Pj4GEyQpRf/iBEjlPgzOhYzytXVlWHDhimvu3Tpgq+vL76+vll+L62///4bDw+Pt1Z/apGRkVSsWBFnZ2eTyr/v+GrVqgVAXFycwetSP7uskj17djp16mTWNVHD+xAT9gDQv02HEEIIIYQQQggh3g6L9x2A+LCVP/dVmp9KISPoyToqhYxIc04IIYRIT61atbh69arOLLJDhw5Rrlw5o/sk5suXj/379xMeHq5z3MvLS5nRakoZfQoWLEjnzp2ZPHmy3vPPnj0jODiYPn36KIlaLTs7Ow4cOGBWojY92bJlIzExUWc2qCGPHj3i3Llz9O/fX0nUallbW9OvXz8OHz7My5cvMx2bPubGa8jQoUN58uQJwcHBWRDZu5c6flPG4ujRo9MdcwBbt26lXbt21KtXj7Zt27Jlyxbl3M2bN/nyyy9p1KgRzZs3Z+rUqcqs6cGDB3Pu3DkmTJjAqFGjePXqFd7e3ty6dUu5fs+ePcpM6YSEBLy9vTl06BB+fn5s2LDB7HsAREREMGbMGJo1a0ZAQACzZs3izZs3yj1DQ0Pp1q0b9evXZ8CAAWn6xpAvv/ySs2fPsnLlSpo3b56h+Iy5ePEi3bt3p0GDBgwbNozdu3ebvPxw6vji4+Px9vbmypUrSpnr16/TtWtX6tevT9++fblz5w6Qfv8b68+32R4hhBBCCCGEEEK8W5KsfUvi4+Np3rw5ffr00Tl+9uxZ2rRpQ4UKFWjSpMkHueeWEEII8TZkz56dRo0a6fzdt2vXLvz9/dFoNAavHTNmDElJSdSrV4/27dsza9YsgoODda4zpYw+Go2GAQMGcO/ePb1/L2uTKunNutUuu5sZkZGRLFmyhBo1aih7wAIsXboUb2/vND/Pnz9Xkm+lSpXSW2epUqVISEjg/v37mY4vK+I1xMXFBScnJ6Wv35aMxmdM6vhNGYujR49Od0bljRs3mDhxIuPGjWPPnj2MGjWK77//nkuXLgHQv39/8ubNy5YtW5g/fz5//vknixYtAmDevHk4OjoyadIkZsyYQVJSEhERETpJ9Tdv3hAZGQmAlZUVERERrF27lqFDhyqzgc25h1qt5osvviAhIYF169axePFiLl++zKRJk4Dkfxf369ePSpUqsXv3bgYMGMDWrVtN7t/58+dTuXJlevTowd69e82Oz5i4uDj69etH2bJl2bZtG5999hk//PADL168yFB8+pY+XrduHV9//TXr16/HxsaGIUOGAPr731h/vu32QPJy5x/bz8ca94fQDiGEEEIIIYQQ75csg/yWLFy4kOfPn+Pu7q4ce/r0KX369GHgwIG0atWKc+fOERgYSMGCBalUqdJ7jFYIIYR4NwICAhg3bhyDBg0iMjKS8+fPM3fuXE6fPm3wuoIFC7Jt2zYuXrzI6dOnCQ4OZtWqVZQqVYpFixaRJ08ek8qkx87OjlGjRjFt2jQaNGigc06bjE05e/XKlSv06tVLee3u7s62bdtM7oelS5eybt06AJKSknj58iW1a9dmypQpOuXat2+vzIBMycHBQYknvWSxdinf9PbKNEdWxGuMlZWVWYnvlDFpFShQgE2bNqV7TWbiMyZl/KaMRUP3zJYtGxqNhsuXL1OoUCGqVKnCqVOnlJnde/bswcLCAmtra3Lnzk29evV0ZnGaQzuOmjdvTv369ZXj5twjNDSUK1eusHr1aqVdQ4cOpUOHDkycOJGQkBAiIyPp168ftra2lCtXDn9/f7PeM6llZR+EhIQQHR3NoEGDyJYtGzVq1KBJkyb89ttvGY4vta5duyp7FQ8YMICAgADCwsLImzcvoNv/ISEhBvvT2FLhWdGekJCQDLTy/QsNDX3fIWSJ/0o7hBBCCCGEEEKYRpK1b8GNGzfYvn07HTp00PlFx6+//krx4sWVX+42atSIFi1asHnzZknWCiGE+J9Qo0YNEhMTOXfuHP/88w/16tUjR44cJl/v5eWFl5cXffr04fHjx3Tu3JnFixczbtw4s8ro07RpUzZv3sycOXP47LPPlOMFChRApVJx8+ZNChQoAECRIkVYtmwZACdPnkyTNDSmQ4cOyn6SFy9eZPTo0YwcORIXFxedcqn3ik0pf/78ANy+fRtHR8c057XLTWtjtra21ruMamxsLIDBBFBWxGtIZGQkERERFCpUyORr2rRpQ/v27XWOaffOTU9G4zMmvfgzOhYLFCjA0qVL+eWXX5gxYwZFihShbdu2dOzYEZVKxbFjx9i8eTOPHj0iMTGRqKgoPD09M9WG1P1izj0ePXoEJL+HtJKSklCr1Tx8+JCIiAgcHBx0xpibm1um4s3KPoiIiCBXrlxky5ZNOVaiRIksTdZq34eA8sWRiIgIJVmbsv+N9WexYsUM3isr2lOhQgWTy34I1Go1oaGheHp6ZslqB+/L+2hHbGws165deyf3EkIIIYQQQgihnyRrs5hGo2HcuHEMGzYszZJ6ly5doly5cjrHPD09Wbt27TuMUAghhHh/LCwsaNmyJfv27ePixYsMGjQow3W5u7tTuXJlHj58mKkyKY0dO5bWrVtTuXJl5ZiLiwtVqlRhxYoVfPrpp0DyzEcPDw8AnT14TZUzZ04leVOgQAF+//13vvnmG9atW5dmX9z0FClShJIlS7J69Wq9X/pat24dVapUwdnZWSn/zz//pCkXEhJCoUKFDCZrsyJeQ9auXUuuXLmoXr26ydc4OTmluwT0u2ZK/OaOxVq1alGrVi3i4+MJDg5m1KhR5MiRg1KlSjF48GB++ukn6tati5WVFd999126yRbt80lKSlKO6Vv2OeVz/Pfff826h6urK1ZWVvz2229pEkw2NjY8ePCAmJgY1Gq1cv7Zs2cm9YM+5sZnjL29Pa9evUKj0SgzjcPCwjIcnz4p947WLkecO3du5VjK/jfWn8ZkRXs+1oSnpaXlRxt7Su+yHf+F/hJCCCGEEEKIj53sWZvFNmzYgJWVFQEBAWnORUVFkStXLp1juXPnVvYMS8/73OPIXO9qj6T/hbYIIcR/VUBAAAcPHiQsLAxvb2+j5Z8+fUq7du3Ys2cPcXFxQHLi6fjx4xw+fJjatWubVMYUxYsXp3PnzsyZM0fn+NixY7lw4QKjR49W9oB9+fIl+/bt44cffqBMmTJm9EBa33zzDTdv3mT16tVmXTdu3DgOHTrE999/T1RUFJA8y/O7774jODiYsWPHKmW7du3KgQMHWLduHa9evSI2NpY9e/awYsUKevfu/U7iTS0yMpL58+ezZMkSJk6caFIi6kOiL/6sGIu7d++mc+fOvHr1ChsbG6pXr46bmxvR0dE8evRIWdrWysqKkJAQDh8+rMyQhuTky6tXr4DkxF2OHDk4d+4ckDzrMigoyOD9zb2Hp6cnLi4ubNmyBVtbW2xtbdmzZw/jxo1DpVJRrlw5LCws2Llzp9Jv2j9nhLnxGfPJJ5+QlJTEgQMHgORE8r59+zIcnz6bNm1SliTfsWMHBQoUIF++fHrLGutPYzLaHsfZS3Dfcxz3PcfNaJkQQgghhBBCCCEyS2bWZqHw8HDmzZtn9lKIxpg7S+B97nGUkf2tSr6j++j/dVjW3iO/2Vd8vHuCCSFERpUoUQJXV1eqVq1q0oweV1dXevTowbJlyxg1ahTZs2fnzZs35M+fn6FDhyrL85pSxhQDBw7k119/1TlWpkwZtm7dyg8//EDz5s1JTEwkKSmJ0qVL061bN51lkzPC2dmZESNGMHXqVOrVq6csifrzzz+zcOHCNOUrVarEqlWrqF69OitXruTHH3+kdu3aWFlZoVarqVatGhs2bNBJIn/66ad8//33/PTTT0yePBmVSkX+/Pn5+uuv0ywn/LbiBViwYAFLly4lKSmJ+Ph4ypcvz+LFi01K3GeWKfHpK/Ptt9/SokULk+I3dbyOHj2a7NmzM378+DTxNG7cmOPHj1O3bl1y587Ny5cv8fb2pn379qhUKjw9PalXrx52dnZUqlSJcePGMWDAAEaPHs23337Lp59+ysSJE/n1119ZuXIlw4cPZ+bMmSxZsgRnZ2cCAgIM/nvVx8fH7HvMnz+fCRMmsHz5ciB5yelp06YBybOgJ0yYwIwZM/jhhx+wt7enWbNmGd6zNiPxGeLq6sro0aMZM2YMP/zwA05OTrRs2ZKtW7cqZcaOHYuFhQWTJ082K1btjOaKFSvSokUL4uPj0Wg0zJw5M93Pv2zZshnsT2NMaY8QQgghhBBCCCE+HCqNRqN530H8V3z55ZeULFmSIUOGALBy5UqOHz+u/JJl+PDh2NvbM2nSJOWa9evXs2HDBvbs2ZOmvtjYWC5fvkypUqWws7Mzev+3scdRpZARZpX/u8Iss+8Rc9rZ7Gty1DB/6bwnk81bKjHPePOX0nsaUNfsa1x3HklzTLt3lIeHh0nPXgghPnRRUVHY2dkpS+2+evUKa2tr5fXLly9RqVTY29sDycuEqlQqcubMqVOPWq3m5cuX5MiRA2tra733MlQmdb2p49J69eoVr1+/xtXVNU39Go2GFy9eYGdnl24MxvrC1tY2zee7RqMhIiKCHDlyYGdnR1RUFImJiXrrsLa21llCFSA+Pp527drh4+PDiBGG//6OjY1Fo9Ho3S9YXx9lVbwpy6hUKnLlypWlfWisHebEl5J2v1Vz4zdnLOqTlJTEixcvcHBwSLPcdGxsLJaWlsrYff36NZaWlsrs5JcvX2Jvb6/MxFSr1cTExODg4EB8fDyvXr3CyckJSJ69njt37jQxmnsPSB6HiYmJ6T4bbXvi4+N5+fKlsky3MdHR0VhZWemM2YzEZ4hGo+HVq1fkzJmTDRs2sGnTJmUG8JUrV1i7di1Tp041Kb6nT5/i6OiIpaUlERERODk5oVKpiImJSfPM0+t/MN6fGW1PSin/z2FoPH7I1Go1ISEhVKhQ4aNe1vd9tEP7/OX/HUIIIYQQQgjx/sjM2ix04sQJjh49yrJly4DkX7AlJSXh6enJsWPH8PT0ZPfu3TrXhISE4OnpabBec/csep97Nf2X9lZ6n235mH/JJIT4sAUFBfHixQs6dOiQ5lxkZCRBQUF4eHgoe7YeO3YMa2tratasqZSLj4/nr7/+IiwsDCsrK4oVK4anp2eahI2+Mlp///23Tr3Hjx8nKSlJmb3o4OAAJO+t+euvv9K5c2cg+fMxd+7cPHv2jLNnzxIdHY2TkxOVK1fG0dFRp4w+2nq1fZFyKwKVSoWbmxuVKlXCyclJSRynLpdS+fLlddoVERHBuXPniI6OxtnZmWrVqqVJfvzxxx+ULVuW0qVL6xx/+vQpBw8eVGa5hoaG6vSRsXhtbGxo27Yts2fPxsbGRm8STBvvkSNHlLosLS1xdnamQoUK5MmTR6ePAKVfU1OpVPz111/p9k2nTp1QqVQ6Y8jR0dGk/gwKCqJgwYLp/hvp1KlT6cavpW2HKePVWFtNPZ+aqWMxPRYWFulenzqpkj17dp3XqcedpaWlck8bGxslUXv79m0uXLigdwsPffdQq9X89ttvxMbG4u/vn+YaGxsbg8tZp4zB1EQtkGYrkfTiS8nUxKNGo6Fbt240b96czz77jNjYWHbt2kXJkiXZuXMnAQEBnDlzhtevXxMZGan0naH4Un7RI+Wf9cWk70shWsb605z2pNyLWwghhBBCCCGEEB8OSdZmofPnz+u8Tj2ztkWLFsybN4+VK1fStm1bTp48yYEDB1i7du37CFcIIcT/oMWLF3Pt2jVKlSpFpUqVdM5t376d2bNn0717d+WX+lu3bsXOzk5JGF6+fJnevXtTsGBBSpUqxZs3b/j+++8pXLgwy5YtI3v27CaVSV3v4sWLuXLlCs7OzjqJ4SdPnjBlyhQlWZuUlMSPP/7IypUrKVu2LG5ubty7d48bN24wfPhwunfvblZfWFhYKElTtVrNrVu3uH37NrNnz6ZevXpKOYCSJdMu3O/u7o6npydJSUmMHz+eLVu2YG1tjYWFBUlJSSQkJCh7htra2vLbb78xZ84c+vTpkyZZe+/ePaZMmYKfnx82NjZ6+8hYvB07dmTevHksWLAAGxsbGjRogJWVVZp4U9YVFxfH3bt3uXbtGq1atWLMmDFky5bN5D5Mr286duyISqXS2470rtFoNAwcOJBnz56RLVu2NDN/tX1oavymjMW3KSQkBCcnJwoVKvTB3uPixYvMmzdPb7JWnwULFrBx40b8/Pz0JmvNje/GjRv07Nkz3eu1zzyjTK2/R48eTJo0iQULFhAbG0u1atWoVKmS0jfNmjXj4MGDPH/+XG+y9l3JTHsGDRr0DiMVQgghhBBCCCGEqSRZ+w65uLiwaNEipkyZwsyZM8mbNy/ffvut0Zm1QgghRFYqW7YsO3fuTJOs3bVrFx4eHgavnTVrFvXr19fZt/HFixd8/fXXXLlyhYoVK5pURh8fHx+mTJnCrl270l1adtmyZaxbt47Vq1fr1LN//36GDRtGsWLFqFOnjtE+0GrUqBEDBgzQOTZz5kzGjRvHn3/+qRxr0qRJmnIpLV68mH379rFp0yYqVKigHD916hR9+/blyy+/NHtf2IzEa2lpSb58+ejSpQv9+/c3uERv6rpCQ0MZMmQI48ePZ+bMmSbHZKxvzL2mS5cu+Pv7G63XlPgzOhazysqVK/H19X2rydp3cY+UQkNDadWqFYGBgSaVNxZfiRIlOHbsWFaGmKH669WrR7169Xj58iV2dnZYWlqya9cu5byLi8sH8QXLzLRHCCGEEEIIIYQQHyYL40VERnXr1o2lS5fqHKtWrRp79uzh33//5ffff6dZs2bvKTohhBD/q+rWrcv+/fuJj49Xjl29epXo6Og0sz1Ti4yMTLMsq4ODAwsXLlQSX6aU0ad169bY2NiwYsUKvecTExNZtmwZPXv2TFOPr68v06dPJ2/evAbjN0XdunV5+vQp0dHRJpWPi4tj6dKl9O3bVydRC1CzZk26dOnCwoUL0Wg0mY5NH33xWllZmb0XrKenJxMmTGDXrl3cuXMni6N8+/TFb8pYPHr0KCdOnEi33ri4OA4fPszmzZv5/fffefPmjc75f/75h+3bt/Prr7/y+PFj5fhvv/3G+fPnOX78OEeOHCE+Pp61a9fy/PlzpcyNGzeULTKSkpKU8/v27ePKlStm30Pr7t277NmzhwMHDhAeHq4Tr0aj4fTp02zZsoXQ0ND0O1SPgwcPcu/ePa5evcrmzZszHJ8xwcHBbN26lStXrvDo0SO2bt1q8rXGntetW7fYs2cPQUFB3L9/X+ecRqNR2pK6b9RqNWvXriUyMtLkZ/ny5UtOnjzJli1buHr1KgDXrl1jy5YtBAcHm9ymjNYXHBzMgQMHuH79ukn9GDW8D49b1uZxy9omxyaEEEIIIYQQQojMk5m1b5FKpdK7H5oQQgjxPhUtWpR8+fJx+PBhfH19geRZtc2bNycqKsrgta1bt2bGjBlERUVRv359qlSpkmYPRlPKpGf8+PH06tULPz8/3N3ddc7dvHmT6Oho6tatq/faVq1amXQPYy5dukTu3Ll19hS9ePGi3ll17dq14/Lly8TExNCgQQO99TVo0IBly5Zx7949ChcunCUxZiZeW1vbdOvy8fHB2tqac+fOUaRIkSyPNbPxGZM6flPGYnh4eLp7gr569YpWrVpRvHhxihcvzoEDB/j222/Ztm0buXLlYvr06Rw8eJAmTZoQFRXF2LFjWbhwITVr1uTNmze8ePGCuLg43rx5w5s3b5gyZQrVqlVTEsjnz59n+fLl+Pn5kZSUxJQpU7hw4QJ37tyhW7dulClTxqx7QPJM1kWLFuHn50dcXByTJk1i+vTpyvtm9OjR/PXXX/j6+nL06FGePXtmcv++efNGWd47NjYWwOz4jBk5ciRnzpyhSZMmBAUFYWNjw9WrV2nbtq3Ra409r0WLFrF69WpatGhBQkICEyZMYOTIkbRr185o3yQmJjJlyhTKly9P4cKFDT5LlUrFlClTCA4Oxs7Ojjdv3jBp0iR69erFP//8Q4ECBZg+fTrDhw9Xlng3JCP1ZaYfhRBCCCGEEEII8W5JslYIIYT4HxQQEMDOnTvx9fUlKSmJvXv3snjxYlauXGnwuq5du1KkSBE2bNhAYGAgsbGxVKhQgR49etC4cWOTy6SnUqVKyizZefPm6ZzTzhx1c3NTjkVGRhIUFKS8tre3N3nvTdBNGiYlJXHr1i127NjB2LFjdb5wFR4ezqVLl9Jc36pVK2V2XerkspZ2tu+zZ88ynazNingNJUMtLS3JkycPL1++zFBMWjlz5jS4n2lG4zMmdfymjEVDy1PfvHmTx48fs2fPHmUf3HXr1vHixQty5cqlzNLVLh+elJTEli1bqFmzJi1btmTGjBk0bNgQX19fXrx4YTB27d7CDg4ObNmyRTluzj3Cw8P5/vvvWbFiBVWrVgWgXLlyTJkyhU8//ZS7d++yY8cOgoKCKF68OADDhw9PM/s2PX5+fmzfvp3KlSsr+0ObE58xt2/fZteuXezZs4dSpUqh0Wjo3r27yV9+NPS8YmNj+emnn1i3bp0yA75ixYpMmjQJPz8/wsLCMtU3KWnjLVu2LP369QOS++78+fOsXr0agGzZsnHs2DGTk7Xm1JfZfoTkmcQfE228H1vcqb2PdnzsfSaEEEIIIYQQ/wWSrBVCCCH+B7Vo0YIff/yRyMhIrl69Sq5cuShTpoxJ19apU4c6deqgVqv5559/2L17N4MHD2bGjBlKotSUMukJDAzE19eXP//8kzx58ijHHR0dgeREn6urKwAxMTGcOXNGOf706VOzkrVPnjzh8uXLQHKi6MqVK2zYsIFPPvlEp5y+vWK1cuXKBcDTp0/JkSNHmvMREREAyozO9BIm2mWSLSzS36UiK+I1JCkpiefPn6dZOtiQhw8fcu7cOZ1jLi4uBpO1GY3PGH3xZ2Ysenh4ULlyZZo2bUrdunWpWbMmrVu3Jnv27AAMGDCAkJAQ9uzZQ2xsrNGZ6aZIveeyOff4999/UavVXLlyRVkmNyoqigcPHhAREcGNGzews7NTkpEAlStX5vz58xmONyv74ObNm9jb21OqVCkg+b1Su3Zt1q9fb9L1hp7XH3/8gZWVlc5S5VWqVOHVq1c8ePCA27dvZ3nfVK5cWfmzq6srZcuW1Xl94cKFt1JfZvsRICQkxKzYPhTmLu39ofqvtEMIIYQQQgghhGkkWSuEEEL8D3JxcaF69eoEBQXxzz//4OfnZ3YdlpaWeHl54eXlxdOnTzl06FCa5JcpZVJzdnZmyJAhTJkyhTlz5ijHixYtiqOjI3/++SflypUDoGDBgsoM3P379zNz5kyz2tCwYUMlafjy5UuaNWvGyZMn0yQ/DSlTpgzZsmXj1KlTepcO/uuvv8idOzdFixYFkpO7T548SVMuLCwMW1tbvQnfrIzXkDNnzhATE6OTFDKmadOmbyXxmhGG4s/IWLSxsWHlypVcunSJkydPsnLlSqZOncrq1atxcXGhY8eO2NnZ4ePjg52dHRqNxqzZi4mJiWmOpXz+r169MusearUaS0tL5QsCWtrZmAkJCQa/DGAuc+MzJiEhQZlhrKVNjJvC0PNKTExM03ZLS0sgud8y2zf6nmXqfaPN3Uc6o/Vlth+BNPtvf+jUajWhoaF4enoqz/Vj9D7aERsby7Vr197JvYQQQgghhBBC6CfJWiGEEOJ/lL+/P1u3buXff/9l6NChRsu/fPmSM2fO4O3trSwxCsmzGcPDwylevLhJZUzx+eefs2XLFp3lda2srOjWrRtLly6lYcOGlChRQjmn0Wj0Lqtrjpw5czJ27FhGjBhB/fr1KVasmEnXZc+enfbt2/Pzzz9Tr149neWQHz16xJIlS+jatauSPPH29ubXX3+lT58+2NvbAxAfH8/69eupW7euyYmujMabnmfPnjFt2jSaNGlCwYIFM1XX+5A6/qwYi1euXCEsLIx69epRrlw5+vTpQ6dOnThw4ADFihXj3r17/PXXX1hbW6PRaDh58qQyQzq1bNmyoVKpdJaYNjZ77tSpU2bdo1SpUiQmJtK2bVvlGUZGRnLt2jVcXV0pUKAAr169IiwsTFmeOzMz+MyNz5j8+fMTHR1NREQELi4uAPz9998mX2/oeTVp0oTY2Fhu3bqlvFdCQ0OxtbWlYMGCxMXFmdw3GXmW71JG+9Fx9hKT9xf/UFlaWn7UyVqtd9mO/0J/CSGEEEIIIcTHTpK1QgghxP+ohg0bMnHiRMqVK6ezD2x6rKys+Pnnn/nhhx+oW7cuTk5OxMTEcPz4cSIiIpg1a5ZJZUxhaWnJ+PHj6dq1q87xPn36EBYWRuvWrWnUqBGFCxcmOjqaEydOEB8fz7Rp0zLUF1pNmjRhx44dfPPNN6xfv16ZaffXX3+xYMGCNOXz5ctHQEAAX331FQ8ePKBly5Y0b96cvHnz8ujRI/bu3UvDhg2VmY0AAwcO5MyZM7Rs2ZIGDRpgaWnJ0aNH0Wg0zJ07953EC3Du3DmWLFlCUlISjx494sCBA5QuXZopU6aYFUNGmBKfvjINGzZUlnY1Fr+pY/Ho0aNYWVnh7e2dJp74+HhGjBhBhw4dKFq0KOHh4Vy/fp3AwEDs7e1JSEhg4cKFODs7c/z4cXLnzk1wcDB///03lSpVwsnJiZ07d/LmzRsCAgKoUKECM2bMoE2bNly9etXofqhFihQx+x6dOnWiX79+dOzYEQsLCzZu3EjFihWpUaMGnp6elC9fnkGDBhEQEMDNmzcz9SWHjMRniKenJ6VLl2bYsGG0bt2ay5cv8/DhQ50yx44dw8LCAh8fnzTXG3peRYoUoX379gwePJiuXbsSGxvLsmXL+PLLL8mePbtZfWNjY2P2s3yXTOlHIYQQQgghhBBCfDgkWSuEEEL8D2nevLmyVK+trS0jRozQmUVZs2ZNnWVYa9eujY2NDZA8g3Tz5s2cPHmS0NBQnjx5gr29PT169KBhw4ZKOVPKpKw3dVxalStXZuTIkdy9e1c5ZmlpyeTJk+nSpQvHjh3j6dOn5M6dm6+//hpvb2+dOk3pCw8PjzTHJ0yYwNKlS7l+/TqlS5emefPmPH78OM3SsgB2dnZK3yxcuJC//vqL4OBgFi1aRI0aNVixYgWenp4619jb27Nx40YOHz7MpUuX0Gg0DBw4kEaNGunMANXXR1kVr7bM48ePUalU5MmThzlz5lCjRg2zlrBNL6aU9LXD1PhSl3nz5o3J8Zs6XsPDw9MdN15eXmzevJlDhw5x7do1nJyc2LBhgzIrd9WqVRw9epRnz54xfPhw8ubNyy+//MLly5epVKkS06dPJygoiKSkJAAWLFjAtm3buHv3LrVr16ZAgQIcOHBAuV+nTp10vjhRsmRJs+8xbtw4jh8/zvnz50lISGDw4MHUr19fqXPFihVs376dhw8fUqFCBTp06EBQUJDBZ5hSw4YNlc+MjMRniEqlYs2aNWzfvp1r165Rs2ZNypYty88//6yUuXv3LiEhIXqTtcae15QpUzh8+DAXL17E2tqaOXPmUKVKFZP6xtLSkk6dOuHs7AyY9iy1s1oB6tevT4ECBZTXn3zyiVkzGs2pz5R+FEIIIYQQQgghxIdDpcnoOmXirYuNjeXy5ct4eHgov7w0RK1WExISQoUKFbJsOavy574yq/yFyj+YfY8XJ3KbfY2D93OzrwmbYNrSm1p5J900+x6PW9Y2+xr3PcfTHDP32QshhPiwjBw5krCwMNasWfO+QxHio6HRaDh48CAVKlRQktazZs3i8uXL/PLLL0DyjOujR48SGBj4PkP9oJnSjylp/91ZqlSpj3YZ5Lfx/6D34X20Q/7fIYQQQgghhBDvn8ysFUIIId6CDh06cPPmTQ4ePIijo6POuWPHjjFkyBC6du3KsGHDABgxYgTZs2dn8uTJACQmJrJy5UqCgoIICwvDysqKokWL0r17d2WWnCllUtfboUMHwsPD2bVrFw4ODkpMN2/epG3btpw/f1459uDBA5YsWcLp06eJjo7G0dERb29v+vbtS548eczqi6tXryqvtTMh69Spw6BBg5TkQOpyKQ0YMIDevXsDcP/+fZYsWUJwcDDR0dE4Ozvj4+ND7969cXV1JTIykqCgIH7++Wdq1qxJpUqVdOp69OgRGzZs4NixY+TMmVNvH2U23s8++4z9+/dTvXp1YmJisLKywsrKCmdnZypXrkzPnj119tw1tw9TOnv2LJaWlkbboa8/O3ToQIMGDZS+1dL24YoVK5TlXS0sLMiRIwcFCxbEx8eHwYMHK+VNGYv/67Rjcu/evSaVP3/+PKNGjVISb2+b9pmnx9LSks8//1xvfL/++ivVq1dn3bp1lChRQvnzJ598Ynb9O3fuZNGiRXz22Wc8fvyY9evXM2fOHJ162rRpk7nGfkC0/ZKYmMj3339P9+7ddfa9Tt3vplCpVEb7UQghhBBCCCGEEB8OSdYKIYQQb8Hr16+xsrJi7969dO7cWefcrl27yJYtG/Hx8cqxuLg4nVk0c+bM4dChQ0ydOpXSpUvz+vVrgoKCGDhwIBs2bKBChQomlUld7+vXr4mNjWXOnDmMHz9eOa5Wq4mNjVVeX7t2jc6dO1OtWjWmTZuGu7s7d+/e5eeff6ZDhw5s3boVJycnk/uiU6dOdOvWDYCkpCRu3brFlClTePToEfPnz1fKff7552n2qYXkpYMBrly5QteuXalevTrTp0/Hzc2NR48esXTpUlq1asXGjRvJnj07sbGxxMfHK+1NHU9sbCzaxUX09VFWxNumTRu6deuGl5cXs2fPRq1Wc/fuXTZv3kzr1q356aef+PTTT03uw/TupY1dXzuM9efr169JSEhIc16j0RAbG0tcXBwVKlSgUqVKqNVqoqKiCA0NZdGiRZQvX16J35Sx+DZ99913VK5cmYYNG36w90hISOD169cml1+9ejWlS5dmxowZ7yQ+7TNPT+pZfinjs7a2ZsWKFRQpUkSpR61WZ6j+uXPnEhQUxNWrV3FwcGDDhg2UKVNGKdekSZOMNO+9MOWZaPtFo9HQtm1bsmXLptNPGZ1daawfhRBCCCGEEEII8eGQZK0QQgjxlnh7e7Nz506dZG1MTAxHjx6lVq1aBq89duwY7dq1U/ZTzJkzJ927d8fHx4d8+fKZXEafPn36MH/+fNq2basz8y2liRMnUqZMGSUxCVCwYEGqVq1K27ZtOXr0KK1atTKtI0jei9TV1VV57ebmRmBgIF9++SVxcXHY2toCyUnElLPKUhs3bhyenp789NNPaeJq3749U6dOZdGiRfTp04e1a9fi7e2dJll+9uxZ1q9f/9bjLVmyJK6urvj4+JA3b14AChQogLe3N1OnTmX06NH8/vvvZM+e3WAsWsb6JquuAXB2dqZPnz7s3buXWrVqMWDAAJ3zqePP6FjMKhcvXqR8+fIf/T1Sev78OZUqVTJ5WdLMxqd95qZKHZ82IR8XF5ep+m1sbAgICDA5jg+ZKc/E3H43VUb6MWp4H2LCHiiv9W3VIYQQQgghhBBCiKxn8b4DEEIIIf6ratWqxe3bt7l58//2wD548CAVK1YkR44cBq8tVKgQv/76K/fu3dM5XqJECSU5YkoZffLmzUuPHj2YNGkS+rauf/r0KefOnaNXr15pztna2rJnzx6zErXpsbS0JCkpiaSkJJPK379/n4sXL+pNbFhYWNCnTx+OHTtGdHR0pmPTx9x4DRk4cCDPnj0jODg4CyJ791LHb8pY/OqrrxgzZky6da5Zs4bmzZtTvXp1mjVrxqpVq5Rz//77Lz179sTHx4d69eoxevRoXr16BcDgwYM5f/48EyZMYNSoUbx8+ZKKFSvqvO927NhB69atgeQZrhUrVmTv3r00bNiQ1atXm30PSF5Oe9iwYdSvX58mTZowadIkpTwkfymgXbt2eHt70717dx4+fGhy/3755ZecPXuWFStW0Lx58wzFZ8zZs2dp3749tWrVom/fvmzZssXkWaup44uPj6dixYr8+++/Spl///2Xtm3bUqNGDbp06cK1a9eA9PvfWH++zfbExsZSsWJFdu/ebVbM9+7dY9CgQdSvX5+GDRsSGBioLBtu7phJ2YdqtZqKFSvy+++/06lTJ6pXr06bNm24ePHiO+kPIYQQQgghhBBCvFuSrBVCCCHeEltbW5o0acKuXbuUY7t378bf319vkjSlsWPHYm9vT6NGjWjRogWTJk3ijz/+0Fla1JQy+mg0Gvr27UtERARbt25Nc16bcCtWrJg5zTXLo0ePWLhwIT4+PjozSxcsWEDFihXT/ERFRXHnzh0gecaqPiVKlECtVvPgwQO95991vIY4Ojri4uLC3bt3szzWlDIanzGp4zdlLH777bdMmDBBb31Xr15l5syZzJ07l1OnTjF79mxWrFjBpUuXABg6dChly5bl8OHDbNy4kdDQUBYuXAjAvHnzcHR0ZNKkScyYMUPvMryJiYnK0rJWVlbExsaydetWpk6diq+vr9n3SExMpHfv3uTMmZO9e/eyZcsWwsLClPa9fv2aL7/8kkaNGnH06FHGjx+v8zlgzPz586lcuTI9evRQ9rg1Jz5jYmNjGThwIHXq1OHIkSMMHDiQn3/+We+S2KbEp6/Pt23bxqxZszh48CB58uRh2LBhaDQavf1vrD/fdnssLS2JjY1lw4YNzJ0716SYExIS6N27N+7u7gQFBbFz504SEhKUfcjNHTMp+1Abz/Lly5k6dSp//PEH+fPnZ+bMme+kP7TUavVH9fMxxvyhtEMIIYQQQgghxPslyyALIYQQb1FAQAAjR45k2LBhPH36lNDQUBYsWMCff/5p8Dp3d3fWrFnDzZs3OXXqFMHBwQwbNoy8efOyfPly8uXLZ1KZ9Nja2vLNN98wZswYGjVqpHNO3x6J//77L506dVJe58uXT0kimWLBggUsXboUSN4DVq1W06RJE8aNG6dTrnv37spesSnlzp3b6N6N2vOJiYkmx/U24zVGpVJhbW2doZi0ChYsyO7du9O9JjPxGZMyflPGonbpaH0cHBzQaDQcP36cHDly4OHhwZEjR5TzBw4cQKPRYGFhgZubG7Vr1+b69esZjhugZcuW1KhRI0P3uHDhAjdv3mTTpk1kz56d7NmzM2jQINq2bcu0adO4cOECL168oHv37lhZWVGsWDECAgLYsmVLhmI2Nz5jLl68yKtXr+jTpw82NjZ4eXnRtGlTDhw4kOH4UuvWrRtFixYFoHfv3vj7+/Po0SPy588P6Pb/uXPnDPZntmzZ3kl7unbtqsTXp08f/Pz80o357Nmz3L17l6FDhyrx9evXj4CAAJ48eUKePHl06jY2ZrTjMqUuXboofdikSRO+++47k9qRVf0REhJiVvkPQWho6PsOIUv8V9ohhBBCCCGEEMI0kqwVQggh3qKqVatiYWHB6dOnuXz5Mg0bNjR5j1KA4sWLU7x4cTp37kxkZCQdO3Zk8eLFTJo0yawy+jRo0IDNmzfzww8/0KVLF+V4oUKFUKlU3Lhxg4IFCwLJs1Z37twJwPHjx/nll1/M6AXo2bMn3bt3B5J/Cf3ll1/St2/fNEnD1HvFpqSN5datWzg5OaU5r515qy1nY2PD69ev05SLiYkBMJgAyop4DYmIiODZs2cUKVLE5Gu6dOmikzAHjCZ7MxqfMenFn9GxmDdvXlavXs3KlStZuHAhjo6OtG3bll69emFhYcHu3bvZvHkzERERAERFReHp6ZmpNhQoUEDntTn30C51W7duXeWYRqNBpVLx8OFDIiIiyJkzJzY2Nsr5zD6HrOyDiIgIcuXKpRNfVs+k1+7TDP/X9sjISCXxmbL/jfVn8eLFDd4rq9qTMmYXFxeDMT958gQHBwedJe21CVp9yVpjbUw9HkF3zFhaWpo8AzKr+kO7D/HHQK1WExoaiqenp9Ev9nzI3kc7YmNjlSW/hRBCCCGEEEK8H5KsFUIIId4ilUpFy5Yt2b9/P6GhoYwYMSLDdTk5OeHl5aX80j+jZVIaM2YMfn5+VKlSRaeOGjVqsHTpUurVqwckJz4LFy4MoLMvpamyZcumJFg//fRTWrRowejRo9m8ebPJv5AuWLAgHh4e/PLLLzrxaq1evZqaNWsq9ylWrJje2Unnzp2jSJEiOomMtxGvIStXrsTZ2Zlq1aqZfE3OnDn1JnTeB1PiN3csVqxYkUqVKpGUlMT58+cZOnQojo6OlCpViq+//ppffvmFWrVqAclLKt+4cUNvPRYWybt8pNxbWN+yz9pykDwT0Zx75MmTBysrK06fPo2VVdp/Tj969IhXr16RmJionH/y5Ikp3aCXufEZ4+DgwMuXL0lKSlL6wZw9dU2Rss+fP38OoPMli5T9b6w/jcmq9kRGRpocs4uLCy9fviQ+Pl75LNEm0lMnarXHDLUxLi7O7HjTk1X98TEmPS0tLT/KuFN7l+34L/SXEEIIIYQQQnzsZM9aIYQQ4i0LCAjg0KFDREREUL16daPlnz59SosWLdi0aRPR0dFA8h6YBw4c4NChQzRo0MCkMqYoVKgQPXr0YM6cOTrHx40bx/Xr1xk6dChXr17lzZs3hIeHs23bNr777jvKly9vXiekMnLkSB49esSyZct0jiclJZGYmJjmRzujbPz48Zw4cYLJkyfz6NEjNBoNDx8+ZMKECVy4cIGxY8cqdfXo0YNDhw6xdOlSnjx5wrNnz9i0aRMrV66kf//+7yTe1GUfPHjAd999x8qVK5kyZUqGElPmMCU+fWX07amcXvxZMRZ37txJmzZtiIyMxMLCAg8PDxwdHYmLi+Pp06dky5aNTz75BI1Gw8mTJzly5IgyQxqSkw3ae9vb2+Pg4MCpU6eA5CSVsSW7zb2Hl5cXbm5uLFu2DI1Gg0ajYfXq1QwZMgQAT09PrK2t2bRpE5CcvDVnz9rMxmdMuXLlUKlUyhLaYWFh7Nu3L8Px6bNx40YlAbl582aKFCmiM3M1JWP9aUxWtWfDhg1KzFu3bjUYc/ny5XF3d2f58uVA8ozIX375hYoVKyrJWnPGTFbKaH84zl6C+57jyo8QQgghhBBCCCHeDUnWCiGEEG9Z0aJFyZ8/Py1atNCZmZUeV1dXAgMD+fXXX/n000/55JNPqFGjBosWLWLcuHG0a9fOpDKm6tu3b5pjxYsXZ/v27VhbW9O1a1fKly9Po0aN2Lp1K0OGDGH27Nlm9UFqjo6OjBo1ivnz5+vMDvzpp58oW7Zsmp/OnTsDUKlSJdatW8f9+/dp3rw5ZcqUoWXLlkRGRrJ582ZKlCih1FWzZk0WLFjA/v37qVu3Lj4+Pqxdu5apU6cSEBDwTuIFmDt3LqVLl8bDw4PmzZtz9epVVq1apcxafptMiU9fmZT74BqL39Sx+NVXXzFmzBi9cTZr1gxPT0+aNm1KrVq1aNCgAV5eXrRr147atWtTo0YN6tevj7e3N3v37mXKlClcvXqVwMBAABo3bsykSZOUpatHjRrFwoULqVatGoGBgXz22WcGl5A19x42NjYsXLiQEydO4O3tTc2aNQkKClK+BJA7d26mT5/OokWLqFixIn379iUgICDD+ylnpA8McXJyYuLEicyaNQsfHx++/vpr2rZtq1NmxIgRjBo1yuxYtf3s4+ODn58fNWrU4NixY8ycOTPdzz9j/fmu2lOxYkUl5iNHjhiM2dbWlgULFnD06FF8fHyoU6cOz58/1/lsNGfMZCVT+kMIIYQQQgghhBAfDpVG39QJ8UGIjY3l8uXLeHh4YGdnZ7S8Wq0mJCSEChUqZNlyVuXPfWVW+QuVfzD7Hi9O5Db7Ggfv52ZfEzbB8H5nqeWddNPsezxuWdvsa/TNXDD32QshPjxv3rzByspKmTkZHx+PhYWFzmtAWT4zLi4OlUqld2nelMtspie9MqnrTR1XyusTEhJ09l9MKSEhwej+qOl58+YNlpaWeq+PiYnBxsYGa2tr3rx5k25CzdLSMs0esxqNhjZt2lCtWjWjSZikpCQ0Go3evx/19VFWxZuyjEqlyvBnuqGYDLXDnPhSsrW1xcrKKkPxmzoW05PeWFOr1VhYWKBSqdJ9nfr5apchVqvVxMfHK/tFx8TEkD179jSJuIzcQ7vccnpJvZQxxMXFmTwG9PVXRuIzRhvfunXr2LZtG9u3bwfgxo0brFq1iilTppgUX8o+jYmJwc7ODpVKpbMUtFZ6/Q/G+/NttCcuLg4vLy+2bdtGuXLlMhRzevGaM2ZS92HK+6Uew6ZKrz9S0v67s1SpUuTMmdOs+j8Ub+P/Qe/D+2iH/L9DCCGEEEIIId4/2bNWCCGEeAtSJxZTJ6hSv7a1tU23LmPJLUNlUtebOq6U1xu6T0YTtYbuCegkhw2V00elUtG+fXtmzpyJv78/Hh4e6ZY1lPgxtY/A/HjNbVNm6kndjj179hAVFUXv3r2VZJ5WeHi4smRrzZo1AThw4ADW1tbUr19fKZeYmMjx48d5/PgxVlZWFC1alOrVq+uMh1evXhksk7reLVu2kJCQQMeOHXViioyMZOPGjQwYMEDn+L179wgODiY6OlrZTzlfvnxpEhn6EhvahNv27dt5+vSpctzCwoI8efJQvXp18ufPrxxPXS6latWq6eyVfPfuXc6cOUN0dDQuLi7UrFkTNzc3nWtWr15NxYoV8fT0xNLSUkmEhIWFsWPHDr744gtsbGz09lFWxZuyLisrK5ycnKhUqRKjR4/G19eXHj168OLFC7Zt20bVqlWV648fP07lypWV16ljSql///7kyJHDaDvSi69o0aJK36Z+r+qLv3LlyhQtWlQpo9Fo6NChA/Xq1aNw4cLcuXOHTZs2Ua5cOSX5n7o9+mi/w6pvefL0vsiiL+aU9I3L9MqnvEfq+1laWpqcqNX2h6HnK4QQQgghhBBCiA+HJGs/UmV29Ej/5D39h6+0WvF2ghFCCPE/6caNG/Ts2TPd87a2tvz2229vNYb27dvzzz//0L59e7Jnz87Ro0fNnnn2Pr3NPly7di3Xr1+nfPnyafZK3r59O/Pnz6dbt25Ksnbv3r3Y2dkpiba///6bfv36UbFiRUqVKsXr169ZtWoVOXPmZM2aNdjb25tUJnW9a9eu5cqVK+TLl4+6desqMUVERDB37lwlWZuYmMiUKVPYvn07NWrUwN3dnWPHjjFu3Dj69u3L4MGDzeqL7Nmz4+npCSTPbAwODmbixInMmDGDZs2aKeVsbW0pV65cmjpev36dJq6aNWvi7u7OqVOnGDt2LN27d2f48OFKcnzZsmX06dNHuS8kP/POnTsTFRXFhg0bUKlUPH/+HJVKRa5cubC1tcXOzi7D8UZHR/P777+zevVqbGxsePbsGSqVCmtrazQaDUlJSSQlJVGhQgU2bdrEokWLAKhTpw6DBg1S6unYsaPOFzgM9Y1Go0GlUul91sb6c+3atTRp0kQnEZ7S8uXLefDggRK/doapra0tuXLlIlu2bPz22280b96cb7/9FgsLCywtLcmXLx///vsv7du3Z82aNWna87Ey9TNj6NChTJkyJd3nK4QQQgghhBBCiA+HJGuFEEIIkSElSpTg2LFj7zUGCwsLpkyZwsSJEz/KpS/fdh96eXmxc+fONMnaPXv26E2gpfTjjz/i7++vs8/s8OHDmThxIrdu3cLLy8ukMvo0bNiQqVOnUrNmzXRnlf/888/s27ePrVu3Urp0aeX4iRMn6NOnDx4eHjRq1MhoH2jVqVMnzazd+fPnM3nyZCX5CVC3bt005VL66aef2L9/P9u3b6dkyZLK8YsXL9KtWzdcXFwM7htbokQJ5s+fT6dOndi7dy8ODg4MHjwYOzs7ZsyYAYC/v3+Wxevv70+TJk10yty8eZMBAwZQqlQpfvzxR70zSfU9F2P30icj16SOY8CAAenG/9NPPwHw22+/0blzZ77++mulPa9fvzY6FrX3+Pvvvz+KL3qY+pmh3RNX35LOQgghhBBCCCGE+LBkbDMoIYQQQogPyMeYqH0X6taty8GDB3nz5o1yLDQ0lDdv3lC8uOG93GNiYtIs15o9e3a+++47JfFlShl9mjdvjrOzM0uWLNF7PiEhgVWrVtG7d2+dRC2At7c3c+fOpUyZMgbjN0W1atWIiooiOjrapPLamcMDBgzQSdRCcmK8R48eLF++XNmTNKuZG296ihcvzsSJEzl48CB37tzJmuDeoZTx37hxA/i/sZgyMZl6LO7bt49Dhw7prTNHjhy8evWKnTt3smzZMnbu3Kn0c3x8PAsWLCAyMlIpf/nyZTZs2KC8VqvVHDp0iBUrVnD27Fnu3bvHypUrlfMajYZTp06xcuVK1q9fz82bN3WuXbBgAREREWzevJmLFy8C8OLFC73xmEIbz5o1a/TGo0/U8D48bllb50cIIYQQQgghhBBvn3zNWgghhBDiP6pgwYIUK1aM3377jZYtWwKwe/duWrZsSXh4uMFrO3bsyLhx43j8+DH169enWrVq5M2b1+wy+mg0GsaPH0+nTp3w9/enUKFCOudv3LhBTEwM3t7eeq9v2LCh0XuY4u+//8bZ2ZlcuXIpx/766y8WLFiQpmzPnj35999/ef36NXXq1NFb36effsrPP//M3bt3dfZUzSrmxmtor+Pq1atjY2PD+fPnKVGiRJbHmtn4jEkdvyljMTExMc3+zVovXrygefPm1KxZk+LFi3P06FFmz57Nrl27sLKyYu7cuTRs2BAnJycALl26xKpVq/j8888BGDx4MDdu3KBly5asWrWKFy9ecO/ePWWW9bhx4/jrr79o2bIlz58/Z8aMGcydO5d69eoBMHfuXK5cuUJMTAyOjo4G49HGYIixeEylVqvNKv++aOP8WOJNz/tox8feZ0IIIYQQQgjxXyDJWiGEEEKI/7CAgAB27txJy5YtUavV7Nu3j1WrVrF06VKD17Vt25bixYuzceNGZs+eTXh4OCVLlqR79+60bdvW5DLpKVu2LAEBAUydOjXNDNtXr14B4Orqqhx78uQJW7duVV47ODjQuXNnk/shZdIwKSmJ27dv89tvvylLD2u9fv2aqKioNNcnJSUpceXJk0fvPbTHo6KiMp2szYp4DbGwsMDV1ZWYmJgMxaSVK1cuOnXqlO41GY3PmNTxmzIWtV9Y0OfOnTs8f/6ccePGkTNnTiB5ufC4uDijywjfuHGDQ4cOceDAAYoUKQJA7969dRLDJUqUoEePHsqM9piYGHbt2kW9evWUlQHy58/P119/DSQvq51ePMaYEo+pQkJCzL7mfQoNDX3fIWSJ/0o7hBBCCCGEEEKYRpK1QgghhBD/Yc2aNWPmzJk8efKEK1eu4ObmZnQJZK2KFStSsWJFIDmZtWvXLiZMmEBiYiIdOnQwuUx6hg0bRpMmTTh06JDO7FrtzMGwsDAlYZuQkMDDhw8BePjwIffu3TMrWfvmzRtevnwJwPXr1/n777/ZuXMnxYoV0ymnb69Yrdy5cwMQHh6e5jpITigDysxXlUqFRqNJU057LPUS0lkdryFqtZqoqCiTZmlqvXz5ksePH+scS0hIMHhNRuMzRl/8mRmLn3zyCfXq1aNRo0Z4e3tTs2ZNGjVqRK5cuXjx4oXBa2/fvk3OnDmVxChArVq1dJY67tixI6dOneL06dPExsby4MEDbGxsdOqpWbOmSfEYY0o8pqpQoYLZ17wParWa0NBQPD09P+pl8d9HO2JjY7l27do7uZcQQgghhBBCCP0kWSuEEEII8R/m6OiIt7c3QUFBXLp0CT8/vwzVU6RIEYYMGcLdu3c5duyY3uSXKWVSypUrF8OHD2f69OnMmzdPpx5XV1f++OMPZb/R/PnzM23aNAD279/PzJkzzYq/du3aStLw9evXNG/enL179zJo0CCT6yhTpgx2dnYcO3ZMb7L21KlTODs7K7NqHR0d0yQ3AR48eED27Nmxt7d/q/EacuLECV6/fk21atVMvqZ+/fpvJfGaEcbiN3csWllZMW/ePO7evcvJkyc5dOgQs2bNYs2aNbi7u6cpnzJJrVar0yTeU87Gff78Oe3ataNQoULUqVOH3LlzkyNHjjSJbjs7O5PiKVWqlMG2GIvHHB9b4tPS0vKji1mfd9mO/0J/CSGEEEIIIcTHLv2v8wshhBBCiP+EgIAADh06xPHjx2nRooXR8s+fP2fnzp3Ksr9aiYmJ3L17F1dXV5PKmKJt27a4urqyYsUK5ZilpSVffPEFK1eu5OLFi2nq/+uvvwzOSjUme/bsTJgwgcWLF3PlyhWTr7O1taVz584sWrSI27dv65y7efMmy5cv54svvlBi+/TTT9m9ezeRkZFKudjYWNasWUOjRo3eerzpefToEVOnTsXf319vIvJDlzr+rBiLFy9e5Ndff6Vw4cJ8/vnnLFq0iNKlS/PHH3+QPXt2LCwsiI6OVsr//fffyp8LFCjAixcvdPaBPnPmjM6fIyIiWLJkCd26daNVq1bExsbqnXVtSjzGGIsnPY6zl+C+57jOjxBCCCGEEEIIId4+mVkrhBBCCPEfV7duXcaNG0f58uVxdnY2Wt7Ozo5t27Yxd+5cateujaOjIzExMZw4cQILCwv69+9vUhlTqFQqxo8fT/v27XWOd+vWjYiICDp27EitWrUoVKgQ0dHRBAcH4+DgwA8//JChvtD69NNPadSoEaNHj2bLli3KzMPjx48ryw+nVKBAATp16sSgQYMIDw8nICCAhg0b4u7uTlhYGL///jvt27enR48eyjX9+vXj77//pnnz5tSpUwcLCwtOnjyJk5MTo0ePfifxQvIs1NjYWJKSkggLC+OPP/7A29ub8ePHmxVDRpgSn74yLVq0oGzZsibFb+pY3LdvH9bW1jRs2DBNPDY2NkyaNIkzZ85QrFgxwsPDuXLlCl9//TXW1tZUrVqVyZMn07JlS65du0ZsbKxybbly5ahQoQIDBgzAz8+PK1eu6CydXLJkSRISEvj2229xcXHh9OnTFClSRPkCRe3atc2Kxxhj8QghhBBCCCGEEOLDIslaIYQQQoj/oPbt21OiRAkgOfEzfvx48uXLp5yvX78+2bJlU143adIEa2trpfzq1au5cOECoaGhREdHU6BAAcaMGUOtWrWUmaOmlElZb+q4tMqWLcuUKVO4e/euckylUhEYGEinTp34888/efLkCQUKFOCzzz6jUqVKZs2sbd++PSVLlkxzfMyYMaxZs4bbt29TsmRJ2rdvr+w7m1rKvpk5cyY9e/bkzJkz/PTTT9SqVYtdu3bp7BEKyTNiV61aRXBwMKGhoQD4+vri7e2tsyytvj7KqnhTlrGysqJChQp88cUXSiLUVOnFlJK+dpgTX0rapVlNid/U8ZqYmIhKpdIbT5kyZdizZw9//PEHz549o2DBguzevVuZebxgwQL27t3Ls2fP+Oyzz3B2dubIkSPK9StWrCAoKIgnT57Qpk0bHjx4wMKFCwEoWrQoW7du5dixY9jY2DB16lRcXFwoVqwYz549A5IT+ynfn8biMcZQPEIIIYQQQgghhPiwqDSG1t8S71VsbCyXL1/Gw8NDZw8rgDI7eqRzVfqutFphvFAq5c99ZVb5C5XNn+Xy4kRus69x8H5u9jVhE4qbVT7vpJtm3+Nxy7QzI4zRt8ScoWcvhBBCiA/HN998w40bN9i0aVO6iUDx36bRaNi2bRvVq1enYMGCAEyfPp1bt26xbNmyDz4e7b87S5UqRc6cOd91uFlCrVYTEhJChQoVPuo9WN9HO+T/HUIIIYQQQgjx/snMWiGEEEIIM/n7+3Pjxg2OHTuWZlnhQ4cOMXDgQHr27KksWTp48GDs7OyYMWMGAPHx8SxatIi9e/cSHh6OpaUlRYsWpUePHjRv3tzkMqnr9ff35/Hjx+zfvx9HR0clpmvXrtGyZUuuXr2qHLt16xY///wzwcHBPH/+HCcnJ7y9vfnyyy/Jnz+/WX2Rch9VlUpFnjx5qFOnDsOHD1fiSF0upSFDhjBgwAAgee/XBQsWKHG5uLjg4+PDgAEDdGYe1qlTh44dO5KUlKRT18OHD9m6dSv9+vUjR44cXLp0KU0fZVW8KcuUKVMGOzs7ateuTZ8+fShXrlyG+zClf/75BysrK73P2pT4mjRpovStofuqVCqyZ89O/vz5qVKlCnny5AGSZ7N2797d6Fj8X6ZSqdiyZQsTJkxgyJAhhIeHs337doMzWc+cOcPw4cOB5GWgTRUREcHmzZvTPW9lZUWfPn04deoUy5Yto3Xr1ibFI4QQQgghhBBCiPdHkrVCCCGEEBng6OjInj176N69u87x3bt34+rqavDa77//nlOnTjFnzhxKlizJmzdv2LdvH4GBgeTJk4eqVauaVEYfKysrZs+ezdSpU9O9/6VLl+jSpQsNGzZk8eLFuLu7c/fuXX766Sc+++wzdu7ciYuLi8l9MWDAAL744gsAkpKSuHXrFuPHj2fkyJEsXbpUKdevXz969eqV5nrtcsyhoaF07dqVRo0asWTJEtzd3Xn48CFLliyhVatWbNq0SWepYQsLC3LlyqVTl3Zvzty5c2Nvb/9W49XW1axZMw4cOMCLFy+Ijo6mQ4cO/PDDDzRu3Nhgv6WU3r1SLpds6jUp4zOmZ8+euLu7k5CQQGRkJOfOnWPTpk20a9cODw8PrKysMjwWs8qkSZOoXr06vr6+H+w9OnTowMyZM1Gr1RQrVozdu3crs1r1WbdunfI+Nye+6tWr63wRIzXteJk5cyZHjhzh2rVrJsUjhBBCCCGEEEKI90eStUIIIYQQGeDj48OuXbt0krUvX77kxIkT+Pj4GLz21KlTBAQE4OHhAYC9vT3t2rWjVq1ayoxGU8ro07t3b+bOnUu7du0oX7683jKTJk2iUqVKzJo1Sznm7OzMkiVL6NSpEydPnsTPz8+kfoDk/Udz5MihvC5fvjxfffUV/fr1482bN0ry0NbWFgcHh3TrGTduHNWrV2fmzJnKMScnJ+bNm0fHjh2ZMmUKy5cvV87Z2dnx+eef69Rx9uxZVqxYQZs2bXBwcNA7azGr4tXWVbJkSZ39XJ2cnBg3bhze3t469zHElHtlxTWp5cyZk27duukc++6779i+fTtff/01OXLkoGXLlhkai1nlypUrVK9e/YO+h4WFBdmzZ6d///4mlX/x4oVZey9r43N0dEwz5vWxtLSkQYMGNGjQwKT6AaKG9yEm7EGa4/q27BBCCCGEEEIIIUTWMe23A0IIIYQQQkf16tV58OAB165dU47t37+fqlWrGt33r3jx4uzYsSPNMrb58+fH2tra5DL65MmTh379+jFp0qQ0SwQDhIeHc/HiRXr06JHmnLW1NZs3bzYrUZuepKQkNBqNyeXv3r3L5cuXlRmvKalUKr744gtOnjzJ8+fPMx2bPubGa0j//v15/vw5wcHBWVLfu5Y6flPG4oABAwgMDEy3zsWLF1O/fn2qVq1K3bp1dZbkPX/+PB06dKB69erUqFGDIUOGEB0dDSQv9R0SEsKECRMYNWoUL168oHTp0jrvuy1btigzYuPj4yldujTbt2+nVq1a/PLLL2bfA+DOnTv07duX2rVrU7duXb7++mudsXfixAmaN29O9erV+eyzz7hz547J/fvll18qXyrQLiNtbnzG/Pnnn7Ro0YJq1arRpUsX1qxZQ506dUyOUQghhBBCCCGEEO+OJGuFEEIIITLAxsaGpk2bsnPnTuXY7t278ff3N5r0Gzt2LPnz58ff35/69evz9ddfs3fvXuLj480qo49Go6FHjx7ExMSwYcOGNOcfPEieOVe0aFEzWmu6pKQkbty4wU8//UT9+vV1luSdO3cupUuXTvMTGRnJvXv3AChWrJjeekuUKEFSUpIS//uO1xAHBwdcXV25f/9+lsaaWkbjMyZ1/KaMxQULFqS7pO/ly5eZP38+a9as4a+//mLlypXs2bOHf/75B0ieUe3j48Pp06c5ePAgd+/eVZK58+bNw8nJiUmTJin79RqiTR7v3buXRYsW0apVK7PvER8fT9++fSlcuDB//PEHBw4c4M2bN4wfPx6AmJgYhg0bxmeffUZwcDDz5s3jwIEDJvfv/PnzqVy5Mj169GDv3r1Z3gevXr1i2LBhBAQEcPr0aSZMmMAvv/xicEltQ9Rq9Ufx8zHF+qG1QwghhBBCCCHE+yXLIAshhBBCZJC/vz9Dhw4lMDCQ8PBwrl69Sv369Tl69KjB61xcXFi8eDGPHj3i9OnTBAcHM3HiRGbPns3KlSspVKiQSWXSY2Njw9ixY/nqq69o2rSpzjltMivlL+hDQ0Np27at8jp//vwcPnzY5H6YO3cuc+fOVV7b2toSEBDAyJEjdcql3Cs2pRw5cmBpaQmQbqJbO0tY32xhc2VFvKawsbHJcEwAhQoV4rfffkv3mszGZ4w2/syMRUheFlqlUrFjxw6aNm1K8eLFCQoKUs7/+uuvyp8dHBzw9vbWmTlrDpVKBUDLli3x8vLK0D0uXrzIvXv3GDp0KFZWVlhZWdG/f38CAgJ4/fo1Fy5cICYmRlmO2M3NjYCAADZu3JihmM2Nz5jQ0FBev35Nt27dsLCwoESJEjRv3lynz80REhKSoeveh9DQ0PcdQpb4r7RDCCGEEEIIIYRpJFkrhBBCCJFBlStXJlu2bJw8eZJ///2XRo0aYWtra/L1+fLlo3Xr1rRu3ZqXL1/y+eefs2TJEqZOnWpWGX1q165NjRo1mDVrFj179lSOFyxYEAsLC65du6Yk2Tw8PPjzzz8BOHLkiM4Stab48ssv6dOnD4CyxPJnn32Gvb29TrnUe8WmpI3lxo0bODs7pzl/+/ZtVCoVhQsXBpITrLGxsWnKvXr1CpVKpTND9m3Ea0h4eDgRERFmzV7u27evzv7HgJLATk9G4zMmvfgzOhbd3NzYuHEja9asoUePHiQlJdGuXTsGDhyIlZUVGzduZPPmzcTExAAQFRWFp6dnptqQP39+ndfm3OPJkydoNJo0ywbb29vz+PFjIiMjsbe311mO3MnJKVPxZmUfPHv2DAcHB534tO+bjKhQoUKGr31X1Go1oaGheHp6Gn3ffMjeRztiY2Mz/MUAIYQQQgghhBBZQ5K1QgghhBCZ4O/vz4EDB7hw4QJjx47NcD05c+bkk08+4dmzZ5kqk9Lo0aNp3rw5VatWVY45Ojri7e2t7CFqYWGBlZUVrq6uQMZmZVpaWipJ6qpVq9KmTRtGjx7Ntm3bDO6vm1KBAgXw8vJi2bJlVK9ePc35FStWULt2bXLlygUk76N6/vz5NOWCg4MpXry4wVmtWRGvIcuWLcPNzU2n343Jli1bphN+WcWU+M0diyVKlODbb78F4MqVK/Tv3x83NzdKly7NpEmT2LBhg5IUnDp1Krdv39Zbj4VF8i4uKWdYR0REpCmnnWELyfvBmnMPNzc3LC0tOXXqlN7x8PDhQ16+fEl8fLwyzh4/fmykB9JnbnzG5MqVi5cvX6JWq5WEX2aWD/+Ykp+WlpYfVbzpeZft+C/0lxBCCCGEEEJ87GTPWiGEEEKITPD39+fQoUO8evXKpOTc06dPadCgAStWrCAsLIy4uDgiIyPZsWMHBw4cwNfX16QypsiXLx99+/Zlzpw5OscnTJjAw4cP6d+/P+fPnycyMpJbt26xZs0apk2bpjdZao7AwEAiIyPTzNCNi4vjxYsXaX60swknTJjAuXPnGDVqFDdu3ODVq1dcv36dESNGcO3aNcaMGaPU9cUXX3Ds2DHmzp3LnTt3uH//PitWrGDNmjUMHDjwncQLkJCQQExMDK9eveLatWtMmDCBjRs3Mn369LeeBDElPn1lEhISTI4/K8bi9u3badOmjZLQdHd3V74U8Pz5c2xsbMiXLx8JCQkcOnSIEydO8OLFC+V6KysrIiIiSEhIwN7enty5cyvLdN+8eZN9+/YZvL+59/Dy8qJAgQLMnz+fxMREEhMTWbRoEf379wegfPnyZMuWjVWrVqFWq7l58ya7du0y2g9ZFZ8x2lmZW7ZsAeDOnTtG+wjAcfYS3PccT/MjhBBCCCGEEEKIt0uStUIIIYQQmVCwYEGKFi1KixYtdGbzpcfV1ZXp06dz+vRp2rRpQ+XKlWnatClbt25l5syZ+Pv7m1TGVD179iR79uxpYt6xYwfu7u4MHz6cOnXq8Pnnn3PkyBHGjx+vzIDMqJw5czJmzBiWLFnC5cuXleOLFi2iatWqaX60+66WK1eOTZs28fr1a7p06ULlypXp0qULFhYWbN++nSJFiih1ValSheXLl3P27FlatWqFn58fBw4cYM6cOTRr1uydxAuwYMECKlWqROXKlenatSvPnj1j48aNeHt7Z7D3TGdKfPrKpNy71Fj8po7FAQMGEBgYqDdOPz8/fHx8aN++PVWrVsXf359atWrRpk0bateuTcOGDWnevDn16tUjODiYb7/9lnv37jF8+HAg+QsRM2fOVJKl48ePZ/PmzVSqVIlp06bRpUsXnT2YUzP3HtbW1ixevJirV69St25dvL29OXPmDCNGjACSx8v333/P1q1bqVy5MqNHj6ZDhw4mJVKzIj5jcufOzfTp01m2bBk1a9Zk2rRpdOzYMUOxCSGEEEIIIYQQ4u1TaTQazfsOQugXGxvL5cuX8fDwwM7OTudcmR09zK7vSqsVZl9T/txXZpW/UPkHs+/x4kRus69x8H5u9jVhE4qbVT7vpJtm3+Nxy9pmX6NvxoKhZy+EEEL8r2jfvj1eXl6ZWl5aCAFr1qxh586dbNu2Lc057b87S5UqRc6cOd9DdJmnVqsJCQmhQoUKH/Wyvu+jHfL/DiGEEEIIIYR4/2TPWiGEEEIIoWP16tVERkYyePBgZY9QrUePHrF+/XqqVq3Kp59+CsDu3buxtramadOmSrmoqCgOHz5MWFgY1tbWFC1alDp16pAtWzaTy5QuXZpNmzbRtGlTPD092bhxI/Hx8TozRyF5z9KVK1emmdl59epVTp8+TXR0NE5OTtSsWZPixc378tbq1at58uSJ8trCwoI8efJQq1YtihUrlm65lHx8fKhRo4by+sqVKwQHBxMdHY2zszO1a9emUKFCOtcsXryYatWqUbFiRZ3jDx8+ZMOGDQwaNAhbW9s0fZ+V8aYsY2lpibOzM1WqVOGTTz4x2GepGbrXV199hYWFhdF2pBdfqVKldPo2vfsai9+U8WrI69ev2bp1K2/evKFHjx7MmTOHLl264OzsrPzZzc3NpLoyS6PREBAQQKNGjRgwYADPnj1jy5Yt1KlT553cXwghhBBCCCGEEOaRZZCFEEIIIYSObdu2sXTpUmrVqkWdOnV0flq0aMHSpUuV5VkBDh06xNGjR5XXp0+fpn79+vz5559YWloSGxvLvHnzaN26tbIPpyllnj9/TsGCBenXrx+ffvopW7ZsYdasWRw4cEAn3sjISJYuXaq8jo+PZ8SIEbRv356///6bmJgY/vzzT/z9/ZkxY4bZfXHhwgUsLS2xtLREo9Fw6tQp/Pz82L59u0658+fP61wbFRXF+vXrGTp0KHXq1KF27dqUL18ef39/Zs+ezerVqwkODqZ58+ZMnjyZpKQk5dp169bxzz//pIknLCyMpUuXEhcXp7fvMxOvobbHx8dz6tQpOnbsSO/evYmOjjarD43dS187TInv77//znT8poxFY+bNm8fKlSuJjo6mfv36rFmzhtatW1OvXj2WLl1KQEAAderUoVGjRibVl54bN26keU+m/GnUqBEqlYrx48dz5MgRqlWrRqtWrahYsSIDBgzI1L2FEEIIIYQQQgjxdsjMWiGEEEIIkUb58uUpUKAAM2fO1DneuHFjSpUqlWbGZ0rz58/n888/Z+TIkcqxgQMH8u2333L//n3Kli1rUhmVSoWXl5eSYPX396dp06Z8++231KlTJ81evFpz587l+PHj7Nq1S2ef27Nnz9K9e3c8PT1p3ry5yX1Rs2bNNImuJUuWMGPGDFq3bq0c8/b2TlNu2rRpyp9nzJjB7t272bNnj85M2qtXr9KxY0fc3d3p06ePyXG9jXiN1fXgwQP69evHiBEjWLJkickxmXKvrLgmNVPiN2UsGnP9+nVatGjBsGHDdGZ4x8XF4eXlxZIlS/D09MxUWwBKlCjBsWPHjJarXLkyW7duzfT9hBBCCCGEEEII8fZJslYIIYQQQqRRt25dFi5cSGxsrLKPYUhICBqNhqJFixq8NjY2ljdv3ugcs7GxYcKECWaV0adx48ZERESwYMECndm9WvHx8axfv54hQ4boJGoBqlSpwqJFiyhZsqTBe5iiQoUKREdHEx0dTa5cuYyWj4mJYf369YwaNSrNkselS5fmiy++YNWqVfTq1eut7FVpbrzpKVCgABMnTqRTp05cuXKFMmXKZGGUb5+++E0Zizt37sTGxoZmzZqlqXPDhg3cunWLmJgY5s+fT79+/ZSlj3Pnzg0k70W6c+dOHjx4QIkSJWjSpAkqlQq1Ws2PP/5I586d2b9/P56enlSuXBlI/nLB+fPnsbGxoUaNGpQuXdrkdiYkJBAUFMT9+/fx8vKiQIECHDx4kH79+qV7TdTwPsSEPTD5Hu57jptcVgghhBBCCCGEEOmTZK0QQgghhEgjf/78lC5dmoMHDxIQEAAk703bsmVLHj16ZPDaHj168PXXX3P//n3q169PtWrV0uwVa0oZfTQaDePHj6d9+/YEBASkuebGjRvExsamu4+pj4+P0XuYIjg4mDx58ugkPk+cOEFsbGyasgMHDuTy5cvExcXh7e2ttz5vb2/mzJnD3bt3dfaWzSrmxpverGVInrVpa2vLxYsX32qyNqPxGZM6flPGop2dHdbW1nrrK1iwIHZ2djg7O1OsWDHUajVLly6lSZMmSrJ26tSpVKhQAScnJ6ZNm8bJkyeZPHkyAEuXLuXWrVtYWlpSuHBhAGbNmkVQUBBdunQhNjaWXr16ERgYqLwXjenXrx9Pnz6lVatW7N27l7t37xIeHm4wWWsutVqdZXVlljaWDymmjHgf7fjY+0wIIYQQQggh/gskWZvFnj17xrp167h58ybOzs60atVKZ8mzqKgoVq1axc2bN3Fzc6NLly7KL2WEEEIIIT4kAQEB7Ny5k4CAABISEti3bx8bNmxg0aJFBq9r2bIlJUuWZNOmTaxatYqJEyeSP39+unfvTpcuXVCpVCaVSU+pUqX47LPPmDJlCitXrtQ5FxMTA4Czs7NyLDw8nDVr1iivHRwczFpuOGXSMCkpiVu3bnHy5El++OEHnXIWFhbpzorVxuXi4qL3fJ48eYDkfXozKyviNUSlUuHi4qI3kWpKTFqOjo706tUr3WsyGp8xqeM3ZSw2btw43fp8fHxwcXGhdOnSNGvWTNlPOKX69esryzF/8sknDBw4kBEjRpAzZ04geXnjr776CoD79+/zyy+/sG3bNj755BMAChcuzPTp0/Hz88PCwsJg+65evcqff/7JoUOHKFiwIAADBgzgyZMnZvaUYSEhIVlaX1YIDQ193yFkif9KO4QQQgghhBBCmEaStVkoMjKSNm3a4OXlRaNGjfj333/p0KEDGzZswMvLi/j4eDp37kzevHlp2bIl586do3379uzatQt3d/f3Hb4QQgghhI5mzZoxY8YMHj9+zL///kuhQoXSLC2cnjJlyijLyD558oRdu3Yxa9YsVCoVXbp0MblMegYNGoSvry9BQUGUKFFCOe7k5ARAWFgYrq6uQHLCUptAu3fvHtevXzcrWWtpaYmtrS2QnAg7c+YMQUFBFChQQKecvr1itRwdHQF4/Pix3hnEjx8/BlBmYqpUKpKSktKU0x4zlLDLingNSUxMJDIyMt3Esz5JSUlpZvAZm9GX0fiM0Rd/ZsaiKSpVqqT82cPDg8TERB4+fKjMTK5atapy/urVqwAEBQURFBQEwMuXL3n69ClPnz7Fzc3N4L3u3r2Lg4ODkqgFqF69OleuXMl0O1KqUKFCltaXGWq1mtDQUDw9Pd9Kgv9deR/tiI2N5dq1a+/kXkIIIYQQQggh9JNkbRY6efIkrq6uzJkzBwsLC1q2bMnly5fZu3cvXl5e7Nu3j9evX7Nw4UKsra3x9/fn4cOHrF69mpEjR77v8IUQQgghdDg4OFCnTh1+/fVX/vnnH/z8/DJUT548eejduzdXrlzh5MmTepNfppRJyd7enhEjRjBjxgzmz5+vHC9atChubm4cPHgQLy8vAPLmzcuYMWMA2L9/PzNnzjQr/ho1aihJw7i4OPz8/Ni4cSOBgYEm11GmTBns7e05fPiw3mTt8ePHcXV1VZLhzs7OhIWFpSl379497OzssLe3f6vxGnL06FHi4uKoVq2aydfUrl37rSReM8JY/OaORVOkTK5rNBoAnWRcymWdLS0tsbS0JH/+/Dp1TJw4Md2lmFPSaDRpZqZr75mVPsSkqLbvPnbvsh3/hf4SQgghhBBCiI+d4TW0hFlatGjBli1bdH4Zky1bNuWXI3/99RfVqlXT+SWLj48Pf/311zuPVQghhBDCFAEBARw6dIgTJ07QrFkzo+UjIyNZt24d0dHROsfj4+O5efMm+fLlM6mMKfz9/1979x0V1fH2Afy7S+9SFCwgKiLYQgRFLFhiQY2CLSoQey9gi2iU2EuKYiy/qLGbGHsCGgUksfcCdiUqSlURFaS3ff/wcF+WXdhdqiTfzzmcyNy5M8/M3jXCszPjDisrK2zdulUoE4vFmDhxInbv3o0rV65I1c/KysL58+ehrl76zytqaWlh0aJF2LFjB27fvq30fZqamhg1ahS2bNkis8LxwYMH2LFjByZNmiT8O7Jr164IDAzEy5cvhXopKSnYtWsX3NzcKjze4jx79gzLly/H4MGDha2bq5Oi8ZfXs6hIeHi48Oe7d+9CS0tLJhlbwN7eHhKJBI6Ojhg2bBiGDRuGjh07Ql9fX1g5XhIrKyskJycjLi5OKLt8+bLC+4xXb4HF0XNKfxERERERERFR+eDK2goUERGBS5cuYfr06QA+bG9XcO5UAXNzc7mrJgrLy8tTuE2cMsqjjY+hj8rqpyrHUll9ExERKeLq6or58+fD0dFR2Mq3JIaGhjh79iw2btwIFxcXmJiYIC0tDZcvX4axsTEmTZqkVB1l+fv7Y8CAAVJlnp6eePfuHcaOHYtPPvlESF5dv34dlpaWWLduncrzUJiLiwv69u2Lr7/+GkeOHIGmpiYA4O+//xa2My6sfv36GDNmDCZOnIjXr19j8ODBaN++PWrXro2EhARcvHgRo0aNgpeXl3DP+PHjcefOHfTp0wcuLi4Qi8W4evUqrK2tMW/evEqJFwBOnz6N169fIz8/HwkJCbhw4QJ69eqFr7/+WqUYSkOZ+OTVGTRokLCqWlH8yj6Lf/zxBzQ1NZX6wEJhBR/aPHfuHF69egUjIyPs378fI0eOhK6urtx7LCwsMG3aNIwdOxbu7u4Qi8UIDAzEoEGDlOrT3t4ebdu2xcSJE9G7d288evRI7pbaRERERERERPRxYLK2gty6dQuTJ0/GggULhLOocnJyZLaZUldXR05OToltldcZQhEREeXSTnn30biS+lF1XURp+pC/PqL8+yEiIqpIw4cPF/79oq6ujqVLl8LCwkK47ubmBm1tbeH7fv36CatV1dXVsXnzZkRGRuLOnTtISUmBvr4+Bg0aJHVupzJ1CrdbNK4CTZo0wffff4/Y2Fip8smTJ2Po0KG4dOkSEhMToaenh6lTp8Le3l7luWjQoIFMuZ+fHw4ePIiYmBg0atQIw4cPR1JSktw2Cs7OVVdXx6JFizBq1Chcu3YN33//PTp06IDQ0FCp+QU+rMTdvHkzbt26hbt370IikcDb2xuOjo5Su7jIm6PyirdonWbNmsHPzw8NGzYsbrrkKi6mwuSNQ9X4ChRsKaxM/Mo+r7q6uiVuQTx48GDhLFl1dXXMmjULFhYWEIvFmDVrFgYPHoybN28iNjYWP/zwA1xcXIR7Z82aJXOe8MSJE9GlSxfcunULOTk52LhxI5o1a1Zs/0X9/PPP+Ouvv/Dq1SuMGzcO//zzD3766Sel7yciIiIiIiKiyiOSVMQBRv9xoaGhWLBgARYtWiT16fupU6eiTp06UisRDh8+jE2bNuHkyZMy7aSnp+PBgwewtbWV+eR9s6CxKsd1r99WxZWKaBXxlUr1bzp8r3IfaZdNVb5Hr638X96V5NUSW5Xq1/pG9SR5okdnle+p+cdpmbL09HRERkbC3t6+2FUXRERUvlJTUwFA7lmg+fn5SE1NhZaWFrS0tAAAGRkZAKTPmiyQnZ2t8MzB4uoUbTc1NRVisVjm/wcFMRkaGsptPzMzUyqhqorU1FSplXhisVjuvBStV5i2trawglPZuFJTU6GpqSlzX15eHtLS0mBgYACRSCR3jsor3sJ11NTUoKenJ7e+IiX1VfCazZ8/H/fu3cORI0cgFouVjk/eHMnrV9n4lXleSbH8/Hzk5uZCU1MTKSkp0NPTg5qamtSfK4NEIsEvv/yCDh06CEnyJUuWIC4uDps3b5apX/hnDgMDg0qJsbzl5eUhIiICDg4O1fo5ropxFLz+/LmDiIiIiIio6nBlbTkLCwuDv78/Nm7ciNatW0tda9SoEe7evStV9vjxYzRuXPLa0vL65Vll/MBfWb9U+LePpTr/komIqLry8vJCZGQkTp8+LayQKxAaGgpfX1+MHj0afn5+AD6sVNTV1cWqVasAfEiyrl69GsePH0dGRgZyc3NRp04djBw5EsOGDVO6TtF2vby8EBsbixMnTkidEfr48WP07dsXjx49Esru3r2LdevW4cqVK8jMzISuri7atWuHmTNnolGjRirPhUgkAvAh+aOtrY2OHTti/vz5wvx4eXnJnL9awNfXF5MnTxbi+vHHH3HlyhVkZWVBT08PHTp0gK+vr1RcvXv3xvjx4+Ht7S3VVnh4OLy8vHDt2jUYGhrKnaOyxuvo6IhWrVrh8OHDePPmjdCWlpYWnJycMH78eDg7O6s0h8X1de/ePairqyMxMRFPnjzB8OHD0bx5c1y4cKHYHVUK5tPLyws9e/YU5lZevwVzkZ+fX2z8yjyLirx69Qq7d+8u9rq6urpwHMi/3ZkzZzBjxgwYGRkhODgYrVu3xqFDh2Brayv8uUWLFmXuR9k5f/jwIXbs2IF+/frh5cuXCA0Nxc8//1zm/omIiIiIiIio/DFZW45evnwJPz8//O9//5NJ1AJAr169sG3bNty/fx9NmzbFy5cvERQUhPnz51dBtERERFRUrVq1EBQUhHHjxkmVBwUFyWxTW9SqVatw7949HDhwAPXq1UNeXh5OnjyJWbNmwdraGi4uLkrVkcfAwADffvstVq9eXWz/169fx6hRozB48GD4+/vD3Nwc0dHR+PHHH+Hp6Yk//vgDtWvXVnoupk2bJiQEJRIJoqKiMG/ePHz11VdSyaLCSVl5rl27hjFjxuCLL77AN998AwsLC8THx2PTpk0YNGgQ9u3bhyZNmigdV3nFm5ycjNOnT8u0o6WlhZ49e6JHjx7o0aMHYmJicODAAYwZMwbLli2Dh4eH0jEpmhttbW189tlnaNu2LdTV1XHx4kWF9yijYC6ys7OLjb+0z2JhWlpaJX7o8L/04bPDhw+jZ8+eWLlyJYAPyVtTU9NyPytW2TlftmwZLl++jMjISNSvXx/Tp0+X+RAKEREREREREX0cmKwtR7t27UJeXh42bNiADRs2COWNGjXCokWLYGdnh6lTp8LLywt2dnZ4/PgxevTogV69elVh1ERERFSgY8eOCAwMlErWvnv3DleuXEGnTp1KvPfmzZtwd3cXzp5UU1ODm5sbXFxcYGRkpHQdecaNG4eAgABcvXoVbdq0kVtn2bJlcHV1xTfffCOU2djY4Mcff8S4ceMQHh6uUrK2MJFIhIYNG2Lq1KkYN24c0tPTld4uc9GiRejatSsWLFgglNWvXx8rV65EQkICli1bhj179pQqrrLEa2RkBHd3d5l7t2/fDjs7O3z++ecAPvw7bt68edDT08OyZcvw2WefletWsdra2hg6dCgAlPs8aGpqFhu/Ms9ieno6RCKR3K2+gf+fw6JbW0skErx//15qK+rs7GxkZ2fLbE+dnZ0NTU1N5ObmIjMzU+51dXV1qXN6AQhny+bn50MkEkklhsuyBbiieORJS0vD27dvYWVlhffv38PAwAC6uroQi8UyydqC9pUdS25uLsRisTD+4p7bokQiEVxcXODo6CiMJzU1tcTxvJ01HmkJscVeV8Ti6LlS30tERERERET0XyZWXIWU5e7ujoCAAIwePVrqq2/fvkKdiRMn4vjx45g6dSoOHDiA5cuXC9vsERERUdVycnLC69evce/ePaHs+PHjaN++vXBWbXHs7e1x4MABXLt2TSpBUzgJq0wdeYyNjTF16lQsWbIEubm5Mtfj4+Px4MEDme2DgQ/nt27btg29e/cusQ9lZGVlQSQSQV1dXaosJSVF5ksikeDJkyd4/PgxRowYIbe9UaNG4dq1a3jz5k2ZYyuPeEsyevRovH//HpcvX66QWMsanyJF41fmWfT39xdWihYlkUjw/fffo23btujevTucnZ3x7bffIj8/H+/fv0fr1q3x+PFjoX5gYCAGDRokfB8aGgpXV1d07twZgwYNws6dO6We0YsXL6J3797o0qUL2rRpg9GjRyMpKQkAkJOTg9atW2Pfvn1wcnLCtm3bSoxHGYriKcnixYtx9+5dHD58GOPGjUNWVhZat26N+/fvC3UuXbqEzp07C/Fdu3at2LEAwMOHDzFs2DB06dIFnTp1wqRJk/Dq1Sul4inreIiIiIiIiIiocnFlbTlq0qSJUtv41a5du9QrW4iIiKjiaGhooE+fPvjjjz/QrFkzAB+2QB47dizCwsJKvHf+/PlYunQpRo4cCT09PTg6OsLV1RV9+/YVVrMpU0ceiUQCb29vHD58GLt27cKYMWOkrsfHxwMArK2thbK8vDykpaUJ34vFYqVWCRYoSBoCQH5+Pp4+fYqAgAD07t1bamXgli1b5J6FeeHCBcTFxQEAGjRoILePBg0aQCKRIDY2FiYmJkrHVlHxGhsbF9u+vr4+atWqJYxJ1ZgKKHodShufIkXjV+ZZLGnb7Xv37mH37t04c+YMTExM8OrVK/j4+ODhw4fCat3ipKSkwM/PD3PnzsWQIUMQFxeH4cOHSyXVAwICMHToUAwfPhyZmZkYPnw4fvrpJyxYsAAaGhoAgFOnTuGPP/5AzZo1S4ynadOmZY6nJN999x1GjhwJR0dHTJs2DVlZWTJ1zp8/j2PHjkFPTw/Lly+Hn58fTp48KXcsmZmZmDx5Mtzd3eHr64u8vDwsWLAA/v7+2Lx5s8J4yjqe0srLy6vQ9pXpuypjKA9VMY7qPmdERERERET/BkzWEhERERXi7u6OiRMnws/PDwkJCYiKioKrq6vCZK2RkRF++OEH+Pv749q1a7h8+TJ++uknbNiwAbt27YKNjY1SdYqjrq6OhQsXYvz48cIWvQUKkpGFk0T379+XWslYt25d/P3330rPw9atW7F9+3YAH36Zr6mpCS8vL/j4+EjVK3xWbFEFiaicnBy514srL43yiFeR/Pz8YrcElmfTpk3YtGmTVJmVlRVOnjxZ7D1liU+RwvGX5VkEPnz4UENDA5s3b4abmxtatGiBffv2AYBMgrqoO3fuICcnR3g+69ati88//xxHjx4V6hw8eFCIWSKRwMHBAVFRUVLtuLu7Cx9QKCkeRZSJp6y8vb2FJPiwYcOwZ88exMfHw9LSUmYsV69eRUJCAjw9PYW5HDRoEDw9PZGWlgY9Pb0qH488ERERFdq+Mu7cuVPVIZSLf8s4iIiIiIiISDlM1hIREREV0rJlS9SoUQPnzp3D/fv30atXL5kzJktiZGSEbt26oVu3bpg1axY8PT2xbds2qe1klakjj5OTE7p27YqVK1diypQpQnn9+vWhrq6OBw8eCAmf5s2b4/bt2wCAkydPYs2aNSrMAjBlyhQhaXjv3j0MGTIEn332mcLtoAsrWFEbGRmJmjVrylx/8uQJxGKxUE9bW1tqNXCBlJSUEs9OLa94SxIfH4/Xr1+jUaNGSt8zbdo0TJw4Uaqsqo6/KC7+0j6LpqamOHz4MH777Tf4+/sjISEB/fv3x5w5cxTG8vbtWxgaGkqdzVp0Ne6WLVtw+PBhiMViaGlp4fXr1zI72JibmysVj6L3rzLxlJWZmZnw5xo1agD4cB52QbK28Fhev34NABgyZIhUG3Xr1sXr168VJmsrYzzyODg4VHgfxcnLy8OdO3fQokULqXFXN1UxjvT0dERGRlZKX0RERERERCQfk7VERERERbi7uyM0NBS3bt3C8uXLS92Ojo4OGjVqVOJKQ2XqFObn5wc3Nzc4OzsLZUZGRujcuTM2bdqE7t27Q11dHSKRSEhUlvW802bNmsHb2xvz5s1DUFCQ0glQCwsLODk5YdOmTWjXrp1UolIikWDbtm347LPPYGBgAODDkRJXr17FhAkTpNq5cOECmjRpIqzUrah4S7Jx40ZYWVmhVatWSt8jFosrfOtZZSkTvyrPokQigZmZGb7++msAQGxsLEaNGgVra2v0798fgPT2qi9fvhT+bGxsjJSUFOTk5Aiv6bNnz4TrV69exdq1axEYGIjGjRsDAJYsWYLnz59LxVD0eSouHnlnORemKJ7yUPi82YJkbOEPMBQeS506dSASiXDixAmp97Cyif7KGI88H0OSVE1N7aOIo6wqcxz/hvkiIiIiIiKq7j6O3x4RERERfUT69esHDw8PGBoa4tNPP1VYPzExEX379sWwYcPg5uYGExMTpKWl4cyZMwgODsaaNWuUqqOMmjVrYtq0aVi/fr1Uub+/P4YNG4aRI0di3LhxqF+/PpKTk3H+/Hns3LkT7u7upZqLAj4+PggNDcXatWvh5+cnlL9//x6xsbEy9bW0tFCzZk0sWrQI3t7emDp1KsaMGYPatWsjPj4eW7duRUJCAgICAoR7xo8fD09PTyxbtgz9+vWDmpoawsLCsH//fmzYsKFS4gWA1NRUvHjxAvn5+YiPj8fevXtx6tQpbN26FWKxWKU4VKVMfPLqmJiYQFdXV6n4lX0W09PTi13RfOTIEWzZsgXr168XVkaLxWJoa2tDT08PZmZm+PPPP1G/fn08evQIoaGhwr0tW7aEpqYmdu7ciZEjR8pcz8jIgLq6OjQ0NJCamorQ0FBcvXq1xBWyJcWjiKJ4CmICoNI22IX98ssv+PTTT2FoaIht27ahadOmsLCwkFu3RYsWaNSoEb7//nv4+vpCJBLhp59+woMHD4Stvss6HnmMV28RPjhBRERERERERJWHyVoiIiIiAHp6esIqtNq1a8PBwUEqUautrS21QlNHR0dIBNWsWRNbt27Fzp074ePjg5SUFOjr66NRo0bYsmUL2rVrBwBK1SncbtG4Cnh7e+PYsWPIzs4WyiwsLHDkyBFs375dSA7r6emhefPmWLduHVxcXFSai6KrUXV1dfHNN9/Az88P/fr1g729PfT09HDw4EHhfNHCHBwcsHXrVjRu3BiHDh3Cli1bMG/ePDx79gx16tTBZ599hqVLl0ptD9uiRQvs3bsXmzZtwrRp0yCRSNCkSRNs3boVbdu2lTv35R2vnp4eDhw4gAMHDkAkEsHY2BiOjo44fPgwGjZsWKY5LEreOJSJT16dJUuWoHfv3krFr+zz6u/vDz09PSxZskQmngEDBuDVq1eYOXMmkpKSYGJigr59+2LAgAEAgKVLlyIgIAC///47nJycMG7cOGzbtg0AYGBggICAAPz444/YvXs3nJycMGLECCER2bFjRwwYMAAjRoyAhoYG3N3d8cMPP2Dq1KmYNWsWVq9eDQMDA6lVy4riKYmieABg4cKFyM3NLfZDFbq6usLrLRKJhPjy8vJgYGCAoUOHwtfXF7GxsWjcuLFUO0XHoqamhp9//hmrV69G//79kZOTAwcHByxbtkzhWJQdDxERERERERF9PESSsu6LRxUmPT0dDx48gL29vbBSooDd76NUbu9h/x0q3/PJjZkq1b/lqNp5eACQcqGGyvcYtn+n8j0JC5U/Yw4Aai9+onIfL/p2VPkei6PnZMpKeu2JiIiqM09PTzRu3BiLFy+u6lCoCkkkEkgkEmGl8s6dO/Hnn3/KTVR/DPE8ffoUu3btqjbPrSrzW/DvTltb22q7sjYvLw8RERFwcHCo1tv6VsU4+HMHERERERFR1ePKWiIiIqL/iLy8PKSlpRV7vWBFYEXy8vLC3Llz0aVLF7Rs2RLGxsZKn8X5MfgY5rC6k0gkcHNzQ9euXTFt2jS8ePEC+/btQ+/evZVu46effkJmZiZmzJghVf7y5Uts3LhRWA1c8HrduHEDN27cQEpKCkxMTODi4gJ7e3uIRCLo6+vDzc0NpqamcHBwwKBBg6TiefnyJebOnYtx48YpHVtCQoLca4sWLZLaSvvq1au4cuUKkpOTYWZmhg4dOqB58+Zy77169SouXbokrBwuGENh27dvR1JSEo4fPw5LS0t06tQJ1tbWKs8vEREREREREVUeJmuJiIiI/iOeP38OHx+fYq9ramriyJEjFRpDnz59EBUVhSVLlkBDQwOBgYFKnSv6sfgY5rC6E4lEWLt2Lb7//nv06NEDBgYG6N69OyZMmKB0G8HBwYiMjETDhg2lzmNOTk7G/v37hWTto0eP4OXlhczMTOjr60NdXR25ubnYtGkT9PX1YWlpid9//x1r166Fp6cnbty4gaNHj8LDw0OIJzk5Gbdu3UL37t2Vjs3MzAzOzs5yxw58WM3o6+uLiIgI9OrVC+bm5oiJicGXX36Jrl27YtWqVcL254Xrtm/fHleuXJEag7m5udBudHQ02rRpg4EDB+LUqVPYsWMHcnJyULNmTQwcOFDp+SUiIiIiIiKiysNkLREREdF/RMOGDXHs2LGqDgNTp07F1KlTqzqMUvlY5rC6s7e3L/MZqu7u7vj+++/RtWvXYlcz79u3D4aGhggODoa5ublQHh0djcGDB6NTp05CPFZWVrC3t8f58+cxfvx4hWcOl8TR0RHjx48v9vqqVasQGRmJY8eOScU1YcIEDB48GBs3bsT06dNLrFswhu7duwt13d3d0apVK0yePBlff/01ACApKQnjxo3D3LlzsWfPnmJjejtrPNISYks95ooi78gQIiIiIiIion8TseIqREREREREHxdXV1fY2dnhxx9/lHv9/fv3OHLkCHx8fKSSnABgZWWF8ePH47fffkNOTo7SbZYHVeIqzRiKMjU1xaJFi3D16lXcvXu3QsZERERERERERKXHZC0REREREVU7EokECxYswKFDh/Dw4UOZ6w8ePEBOTg7atGkj935nZ2e8e/cO0dHRSrdZHlSJqzRjkKdFixbQ0dGplsnavLw8pb5Uqfsxf1XFOIiIiIiIiKhqcRtkIiIiIiKqlqytrTFixAgsXrwYe/fulbqWkZEBADA2NpZ7r6mpKYAPK12VbVNZf//9N168eCHTn6+vr0pxlXYMRYlEIpiYmCAzM1P5QXwkIiIilK57586digukEv1bxkFERERERETKYbKWiIiIiIiqrYkTJyIoKAi///47mjdvLpSbmZkBAOLj42FraytzX3x8vFQ9ZdpUloGBASwsLKTKjIyMVI5LQ0Oj1GMoLDs7G0lJSahVq5aKI6l6Dg4OCuvk5eXhzp07aNGiBdTU1Co+qApSFeNIT09HZGRkpfRFRERERERE8jFZS0RERERE1ZaOjg7mzZuHhQsXYuPGjUJ5kyZNYGxsjBMnTshNdP7111+oX78+6tWrp3SbymrdujUmT54s95oqcVlYWJR6DEXr5ebmom3btiqPpaqpkrRUU1Or1snaApU5jn/DfBEREREREVV3TNYSEREREVG11qNHD+zfvx+bN28WytTV1TFp0iQEBATA2dlZKlF56dIl/Prrr1ixYoVKbZYHVeIq6xgA4P79+1i+fDm8vb1hYmJSbD3j1VtgYGBQxtERERERERERkaqYrCUiIiIiomrP398fn3/+uVTZ8OHDkZGRgQkTJqBx48aoXbs24uPjERUVBT8/P/Tp00flNsuDKnGpOoaQkBA8ffoUEokE8fHxuHPnDoYMGYLZs2eX+ziIiIiIiIiIqOyYrCUiIiIiompl0qRJaNq0qVSZtbU1/ve//yEuLk4oE4lEmDhxIjw9PXHjxg28ffsWpqamcHJygp6eXqnaVCY2S0vLEuuoEpeqY3j79q1wn7GxMRwcHGBubq50/ERERERERERUuZisJSIiIiKqZpKSkpCXl4datWrJXMvNzcXr16+hp6cnbGv77t07iEQiGBkZydR/9+4d1NXVoa+vX2x/xdUp2m5SUhJEIpHMdrsFMVlYWMi0nZ2djdTUVBgZGSl9fqabm5vw58J9urq6yu3T0NAQzZs3h56eHnR1dWX6f/PmDXr27Ink5GS8ePFC6rqtrS1sbW3x4sULmJiYQFNTE0lJScjJyRHqiEQimJqaQl1dXSq2wvPz7t07ZGZmyozF3t4eAIS2i3utDA0N0b59+xLnqnXr1irPPxERERERERFVLSZriYiIiIiqmdGjR+PRo0f4+++/UadOHalrwcHBmDVrFkaPHg0/Pz8AwDfffANdXV2sWrUKAJCamooVK1YgODgYurq6yMzMhLa2NkaNGoUxY8YoXadou6NHj0Z0dDSOHz+O2rVrCzE9ffoUffv2xaNHj4Sy69evY+3atbh58ybEYjHy8/Ph7OwMPz8/2NnZqTQXyvQ5cOBAjB8/Ht7e3lL33759G15eXrh27RpWrVqFkJAQAB8SnNnZ2UJyNz8/Hy4uLqhVqxZCQkKQkpIiJEwlEgny8vLQoUMHLF68GHXr1pWZn5LaBoBNmzbB2dlZZk4B4OrVq1i7di0iIiIgFoshkUjg4uKCmTNnSq0GVmX+iYiIiIiIiOjjIK7qAIiIiIiISHV16tRBYGCgTHlQUJBMAreoFStWICoqCidPnsT58+dx/fp1rFixAgEBAbh06ZLSdeQxMTHBypUrS+z/0qVLGDlyJBwcHHDu3DncvXsXYWFhMDMzg5eXF2JiYpSYAdX6VMaqVasQHh6O8PBwrFq1Crq6usL3Fy5cwJAhQ9ClSxfo6+ujT58+WL9+PdavX48NGzbg22+/RVZWVrFnw5bUdnh4OJydneXed+7cOYwePRpOTk44f/487t69i9OnT8Pa2hpDhgzB7du3K2QuiIiIiIiIiKhycGUtEREREVE11LFjRwQGBmLSpElC2Zs3b3Djxg107ty5xHvv3LmDfv36wdTUVChzdXXFzZs3oampqXQdecaPH481a9bg/Pnz6NChg9w6y5cvR/fu3aUSm3Xq1MF3330HX19fPHz4UOG5r6r2WVb6+vro0qULAGDt2rVo2LCh8H0BMzMzjBkzBmlpaTLnyZaGRCLB0qVL0bt3b8ycOVMor1mzJhYsWIDnz59jxYoV2Ldvn3CttHPxdtZ4pCXEljnmimRx9FxVh0BERERERERU7riyloiIiIioGnJ0dMT79++lVlb++eefcHV1LTGZCgAtWrTA3r17cebMGWRnZwvlhe9Tpo48BgYG8PX1xdKlS6XuKxAbG4t//vkHw4YNk7kmEomwbt06dO/evcQ+VO2zsrx//x5isRgaGhrl0t7jx4/x/Plzma2bCwwfPhzh4eFITEwUyj6WuSAiIiIiIiIi5TBZS0RERERUDampqaFPnz74448/hLKgoCC4u7tDIpGUeO/XX3+Njh07Ytq0aWjTpg1GjBiBbdu24c2bNyrVkUcikWDo0KHQ09PDtm3bZK6/ePECAGBlZSWU5eTk4MWLF8JX4eSjMhT1WRFSU1OFeOPj43H+/HmsWbMG7u7uChPayoqPjwcAWFtby71eUJ6QkCCUVcVcVJa8vLxivxRdry5fVTEOIiIiIiIiqlrcBpmIiIiIqJry8PDAqFGjMG/ePMTFxSEuLg4dOnRAcHBwiffp6+tjyZIlmDdvHsLDw3HlyhXs27cPmzdvxq5du2Bvb69UneKIxWIsXLgQI0eORL9+/aSuaWlpAQDS09OFskePHuGLL74A8CHZWLt2bfz9998qzUVJfVaEvXv34vDhwwCArKwsiEQijB07FuPHjy+3PrS1tQEAGRkZMDQ0lLmelZUFQHa1c2XPRWWJiIgo8fqdO3cqJ5AK9m8ZBxERERERESmHyVoiIiIiomqqadOmqFWrFs6cOYP79++jd+/eUFdX/p/4Ojo6aNeuHdq1a4cpU6bA09MTO3bswHfffadSHXk++eQT9O7dG8uXL8eMGTOEcmtra2hoaOD+/fto2LAhAKB58+a4f/8+ACA4OFhh26r2WTCO9+/fy9zz7t07iMVi6OjoqNTX+PHjMXnyZABAZGQkBgwYAEdHx3LbAhkAGjZsCJFIhAcPHsDc3FzmemRkJDQ1NeWe71vSXFRXDg4Ocsvz8vJw584dtGjRAmpqapUbVDmqinGkp6cjMjKyUvoiIiIiIiIi+bgNMhERERFRNebu7o7Q0FD8+eefSq+ilLf1qaamJqysrJCRkaF0HUVmzZqF69ev4+LFi0KZgYEBunXrhv/9739yz1TNzMxUqm1V+gQAe3t7XLp0Sab+2bNnYW9vX6Ykq62tLUaPHo358+dLrRguq5o1a6J9+/bYuHEjcnNzpa7l5ubi559/Rq9evaCnpyf3/uLmorpSU1Mr9kvR9eryVRXjICIiIiIioqrFlbVERERERNVYv3790KdPH5iamqJly5YK6ycmJsLNzQ2DBg2Cm5sbTExMkJaWhjNnziA0NBQbNmxQqo4yTExM4Ovri3Xr1kmVL1iwAF5eXvD09MSYMWNQv359JCcn4/z589i7dy+8vLxKNRcl9Tlx4kQMHToU8+bNg7u7O9TU1BAWFoYjR45gy5Ytpe6vwJQpUxAcHIzVq1fD39+/zO0VWLx4Mby9vTFq1CiMHDkStWvXRnx8PHbt2oXMzEzMnTu32HuLmwt5jFdvgYGBQbnFTURERERERETKYbKWiIiIiKiaMTMzE84zrVWrFtq3b49PPvlEuG5kZCSVeKtRo4awzW/NmjWxf/9+7N69G0uXLkVycjL09fVhY2ODPXv24NNPPwUApeoUbrdoXAWGDRuGkJAQPHv2TKre4cOHsWfPHuzevRuJiYnQ09ND8+bNsWvXLqWSzqr2aWdnh4MHD2LLli1YvHgxJBIJmjRpgl9//VVq7gpoa2ujVq1axfapr68vVaalpYXFixdj3rx5GDRoEOzt7WXmR5m2i95Tr149HDlyBLt378bmzZvx9u1bmJqawtXVFcOHD5eKQ9m5ICIiIiIiIqKPh0gikUiqOgiSLz09HQ8ePIC9vT10dXWlrtn9Pkrl9h7236HyPZ/cmKlS/VuOa1TuI+VCDZXvMWz/TuV7EhY2Uql+7cVPVO7jRd+OKt9jcfScTFlJrz0RERERUXkp+Henra1ttV1Zm5eXh4iICDg4OFTrbX2rYhz8uYOIiIiIiKjqcWUtESkUEBCAV69eYcmSJTLnuT19+hT/+9//0LlzZ3z++ecAgN27d0NLSwtDhgyRqnfixAm8ePEC6urqaNCggbBlo7J1irYbEBCAtLQ0zJ8/HyKRSGjnxYsX+OGHH/DDDz8IZRKJBGfPnsXly5eRnJwMExMTtG/fHm3btpW6V5m5iIuLE74Xi8WoVasWOnbsCGdn52LrFebm5oZu3brJjcvMzAwdOnRAmzZtpO5ZtmwZunTpgvbt20uVR0VFYePGjVi6dCl0dHTkzlF5xVu4jrq6OkxMTODk5IROnTqp9AvFkvr67rvvIBaLFY6juPhatGghzG1J/SqKX5nntSLk5ORg3rx58PX1haWlZaXfTyTPzZs3ERwcjK+//lqp+m/evMG2bduQnZ2N+fPnV3B0Vavw3PzX3n+FX+c5c+YIY7ewsCi3ecjJyUFSUlKx10UiEczNzcvUx8fiv/b8EBEREREREdH/E1d1AET08Tt9+jT+/PNPnDlzRubaoUOHEBoainv37gll169fR3h4uPB9cHAwBgwYgNTUVLRq1QqNGzdGWFgY3N3d8erVK6XrFG339OnT2Lt3Lw4dOiQVU0pKCo4ePSp8n5qaihEjRmDevHnIz89H48aNkZqaiilTpmDmzJnIy8tTaS7S0tLg6OgIR0dHfPLJJ8jIyMD48ePx888/S9VLTU2Fg4ODzFfBL5YLxyWRSGBra4uMjAxMnToVU6ZMQXZ2ttBeaGgooqKiZOJJSkrC0aNHkZOTU+wclVe8hduys7NDRkYGFixYgIEDB+LFixcqzWFxfRUkzuWNQ5n4IiMjlXrtSopfmWexouTn5+Po0aN49+5dqe4XiUSwsLCApqZm+QZGFebYsWO4ffv2R91HTEwMwsLClK6/YcMGnD17VtgmV5HKmIOKUnhu/mvvv8Kvc+Gxl/XvscLi4uLg4+NT7NesWbPKPpAKpMqz/V97foiIiIiIiIjo/3FlLREpxdHREYGBgVKrFvPz8/Hnn3/CwcGhxHt37NiBsWPHYurUqULZ0KFD8fPPPyMlJQW1atVSqo48gwYNwurVq9G9e3fUqFFDbp1vv/0W0dHROHr0qNTKSG9vbwwePBiHDh2SWgWsSIsWLTBs2DCpsoYNG+KHH37A2LFjhYRjy5Yt4e3tXWw7y5cvR2xsLI4dOwYTExOhfMyYMRgwYADWrVuH2bNnKx1XRccrr60ZM2Zg/PjxmD59Ovbt26d0TMr0VR73FKVM/KV9Fj8G6urq5fLMUOU5duwYPDw8VDqf82Pso7Dnz5/js88+Q+/evZWqX9nxVZT/2vuv6OtcMPasrKxy68Pa2hoHDhwot/YqmyrP9sfw/LydNR5pCbFVGkNZ1AWQWNVBlIOKGoe8o1eIiIiIiIjo48BkLREppVOnTggICEBycjKMjIwAAFeuXIGhoSHq1q1b4r0ikQjPnj2DRCIREoNisRgTJkxQqY48bdu2RWJiItasWYMlS5bIXM/IyMDvv/+Ob775RmYLWxsbG+zduxcNGjRQPAEK2NjYID09He/fv4ehoaHC+ikpKQgKCsLy5culErUAYGFhgQkTJmDDhg3w8fGpkFU2qsZbHENDQyxcuBAeHh64fft2tUu2yItfmWdx586d0NTUhKenp9x28/PzERgYiNu3b0NbWxt9+vRB8+bNAXw4G+7333/Ho0ePoKmpCRcXF3z22WfFthMUFIS7d+9CTU0Nn376Kdzc3AAAubm5mDt3LiZNmoSDBw+iXbt2cHFxkdpGUyKR4Pjx4wgPD4eGhgbat2+PDh06CO0/efIEQUFBSExMhJmZGfr16wcbGxul5q64ezMyMuDv74/Zs2fDwsICwIe/K86cOYM5c+YA+LCqfO/evYiJiUHLli3RrFkzHD58GP7+/grnSN64XV1dyzQWRfGUdi4UjeWnn37C9evX8f79e8THx2PYsGElzl1xY1elj9GjRyt8LlJTU/Hrr78iJiYGdnZ2Kp1huHHjRjx69AivXr3CmzdvsGTJEpXjq8rXq6T3nKK5KbyNrZmZWYmvZX5+PubMmQMfHx8cO3YMcXFxcHR0RP/+/XHkyBGEh4fDysoKX375JXR0dBSOqTTtlWUei77O/v7+wtgLPtCSnp6OTZs2ITY2FjY2NvD09ISmpmaxz7Gi51KRsownKysL8+fPx9SpUxEcHKx0zCU9L6q+9wo/P3Xr1sWcOXMwc+ZMhISE4PHjx6hXrx68vLyU/n92Wd8nRERERERERFR5uA0yESmlZs2aaNWqFY4fPy6UBQUFoV+/fpBIJCXeO2XKFPz1119wd3dHQEAALly4ILPyRpk68kgkEsyfPx9Hjx6Vu9Xg48ePkZOTU+x2nPb29tDW1lbYjyKhoaGoX7++1C9RQ0JCMHv2bJmvtLQ0PHjwALm5uXBycpLbnpOTE1JSUhAdHV3m2Moj3pLY29tDV1dXaivsilDa+BQpGr8yz2LTpk1hZ2dXbJszZ87E/v370bx5c9SoUQNffvklLl++DADw8fFBcHAw2rZtiwYNGsDPzw8HDx6U28706dOxZ88etGrVCvb29ggICMCyZcsAfEggHz16FCtWrEBubi60tbVlth/18/PD5s2b0apVK9ja2uKbb77Bzp07AQCvXr3C4MGDoaOjgy5dukBDQwNDhw5FTEyMwjkr6d6cnBwcPXoUKSkpQv3o6Gj8/fffwvcjRozA+fPn4eLigtjYWMyZMwenTp0Srpc0R/LGXZaxKBNPaedC0Vg6d+4MsVgMFxcXtG/fXuHcyRu7qn0AJT8XADBq1ChcvXoVnTp1Qnp6OjZv3qzUXABAly5dUKtWLTRr1gz9+vUrVXyKVOTrVdJ7TtHcFH7/Kftazp8/HzVq1ICNjQ0WLFiAcePGITY2Fk5OTvjtt9/w008/KTWu0rRXlnks+jrL2/p4xYoVUFNTQ6tWrbB//35h1Whxz7Gi51KRsowHAI4ePYqZM2dCR0dH6ZhLel5Ufe8VnsOC/mbPno3c3Fw4Ozvjjz/+wOLFiyttPujfJy8vr9gvIiIiIiIiqlpcWUtESnN3d8e+ffswbNgwZGVlISwsDEePHsXatWtLvK9jx444ceIEAgMDcenSJezcuRNisRjDhg3DjBkzoKGhoVSd4tSrVw9jxozB4sWLZZJeBUm2gtXAwIczBn/88UfhexMTE3z99ddKz0NISAiePn0K4EOy+OnTp4iPj8fGjRul6tWpUweOjo4y96urqyMzMxMAit26uWC1beFf9JdWecSriLGxsdQZu6rEVKBmzZrw8/Mr9p6yxKdI4fiVeRbbtGlTbFuPHz/GiRMncPbsWeE83VatWgmvtbe3N+zt7YVrjx8/xpkzZzB48GCpdv755x+EhIQgLCwMlpaWAAAzMzNMmDAB06dPh76+PgCgdevWmDhxIgDp7UefPHmCwMBAhISEwNraWhjnV199hS+//BKvX79GdnY23NzcYG1tje7du8PV1RUGBgYK56ss9965cwf37t3DuXPnULNmTfTu3RtxcXG4efOmUKekORKLxTLjvn//foXGU5a5KGks9vb20NDQgI2NDZo0aaLw/S5v7Kr2oei5uH//Pm7fvo0LFy7AzMwMwIcEZ+Fke0maNm0q7LhQ8GEUVeJTpCJfL0XvuaioqDLNjTz9+vUT3vshISHQ19eHr68vgA/bDN+6datC2ivrPBZ9neV9uKp///4YOXIkAKB27doYNWoU3r59C2NjYwDSz7Gi51JNTa3EeMo6ngIeHh4YPny4UjErel5Ufe/J4+bmJsSTk5OjdPK+vOaD/l0iIiKqOgQiIiIiIiIqBpO1RKS0Hj16YPHixXj+/Dnu3buHpk2bCts7KlKwte+ECROQnZ2NkJAQLFq0CIaGhsIvPpWpU5zx48cjMDAQ+/fvl0ro1axZEwAQGxsrbM2oo6MDe3t7AEBkZCTCwsJUStbWq1cPzs7OAIB79+7h+fPnOHnypMw2y/LOii1Q8Iv++Ph42NraylyPi4uTil8sFstd+ZCbmwsAJf4iuzziLUlWVhYSExOFRIwyzM3NhW2BCyja2rG08SkiL/6yPItPnjyBgYGBVHutW7cW/mxnZ4fjx48jLi4OaWlpuHv3rtxzcJ8+fQp9fX0hCQAAtra2yM3NRWxsrLCyt7itpx8/fgyxWIwNGzYIZZmZmUhJScGLFy9gb28vnI9sbW2Ntm3bon///sV+gKCwku5VlHCMi4uDkZGR8GwDwKeffiqVRFBmjgqPuyxjUSaekijqW9nXWxVFX3NV+lD0XMTGxsLQ0FD4OwoAmjRpUqaEZHnOQUW+XleuXCnxPVcRc9OoUSPhz3p6elLb8uvr6yMjI6NC2ivrPCqjWbNmUnFJJBIkJCQIic/Cz7Gi51LRcQvlNZ7CMdvY2JQYs7J/Rys7xsLPVYHCbejp6Sn9PFTG60vVj4ODg9zy9PR0REZGVm4wREREREREJIXJWiJSmq6uLnr06IGjR4/i7t27cHd3L1U7mpqa6Nu3L86dO1fsp/yVqVO0/vz58+Hn5ye1YrR+/fqwsrJCYGAgWrVqBeBDonTMmDEAgODgYFy7dk2l+Js1ayasXBowYABu376NtWvXYunSpUq3YWdnB2NjY/z5559yk7UnT56EpaWl8EvgWrVqyd3S9enTpzAyMoKenl6FxluS4OBgSCQStG3bVul7HBwchBVXVU1R/Ko+i9ra2sVu4Z2QkIB+/fqhX79+6Ny5M3R1dZGfn4/Xr1/LbScnJ0eqrKDdwmdYFnemsY6ODtTU1NCnTx+p8oEDB8LQ0BAikQgzZszAlClTEB4ejtOnT2Pw4MH4+eefpZLL8pR0r7ztoQtWkgMfPlhQ8CGDAoUTEMrOUeFxl2UsiuJRpKS+69Wrp/TrXdBWUYXnrkDhsavyTAGKnwsNDQ2ZVfKqJgwLUzU+RSry9VL0nlNlbpR9LQtWSxf3vaqUba+s86iMwu0X/FlLS0soK/wcK3ouFSmv8RR+fQv+XFzMyv4dXaA0Yyzt81AZry9VP8V9sE/RynUiIiIiIiKqeEzWEpFKPDw8sGrVKiQkJOCHH35QWP/169fYvXs3hgwZIrUyJjk5Gbdu3UK3bt2UqqOMzp07o1WrVjLb+86YMQNfffUVnJyc0LdvX6nYjh07VmKiUxE1NTUsWbIEQ4YMgZubm9JnLqqpqWHKlClYvXo12rRpI3XfuXPnsHfvXqxatUoo69OnD9atW4cvvvhCSO7GxcVh69at8PDwqPB4i3Pjxg2sXLkSo0ePVmoV48emaPzl8SwWrNo+d+4cOnbsCADYunWrkHjPzc3FggULIBKJkJKSgkePHklt012gadOmAIDLly8LieRz587BzMxM4Soz4EOSXk1NDYaGhsJq84cPH+Ly5cvo0qULzp8/j1u3bmHKlClwdnaGs7Mz7t+/j/DwcIUJzpLubdWqFTQ0NJCQkABbW1tIJBKcOXNGuLdhw4ZITU3F48ePYWNjg/z8fKnrt2/fVnqOlIlH0VgUxaNISX2/efNG4VhEIhHy8/MBfPhATElzJ48y81W4D0XPhY2NDTIzM3Hnzh20aNECEomkTOdcqhqfIhX5evXv3x9A8e85iUSi9NyU5rWsTGWdR2VcvHgRLi4uAIDr169DX18f9erVk1tX0XOpSHmNp3DM4eHhJcaszN/Rqrz3ivuQT2mUdj6MV29Ravv4j1FeXh4iIiLg4OBQrZOP/5ZxEBERERERkWqYrCUilTg7OyM5ORkdOnQQzswsiampKd69e4fPP/8czZo1g4mJCdLS0hAREYG2bdti0qRJ0NPTU1hHWV9//bXMqpXevXsjMzMTy5Ytw7p162BlZYV3794hMjISrq6u2LJli8rzUFjz5s3h5eUFf39/BAUFCfMSFBQk97xBGxsb4Yy6tLQ0TJ06FdbW1rCwsEBCQgJiYmJkxvHll1/iyZMnGDhwIOzs7KCmpoYHDx6gU6dOmDlzZqXECwDHjh3D3bt3kZ+fj4SEBERFRWHEiBHCmYgVSZn45NUZPXq0sA20oviVeV4BYOfOndDU1ISnp6dMPLVq1cJXX32FGTNmoF27dnj58iXi4uKwe/du6OnpQUNDA2PHjoWpqSmio6PRq1cvbNmyBb/99hsGDBggtFNwhu/06dPRtWtXZGRk4OLFi1ixYoVS5/SamppiwYIFmDJlCjp27Ag1NTWcOnUKM2bMAPDhl/n+/v64fPkyGjRogJcvX+LZs2dYtmwZAGD37t1QU1ODl5eXTNsl3aumpgY3Nzd8/fXXcHV1xbNnz2BnZyesDG/UqBH69OmD0aNHo0uXLnj27BksLCyErb8dHBxKnCN5W2ErGktJFMVTlrnQ1NRUOJb69etjw4YNuHv3LubMmVPi3MmjzHwV7aOk58La2hoDBw7EuHHj0KFDBzx//hw1a9ZUOplaHvFV1eul6D2nytwoeh9UtbLOY0kkEgmAD1vCT5kyBUZGRggODoavr6/UKtXCFP19VVnjuX//PqZMmYIaNWrgxIkTJcaszN/Rqrz3ypMy80FEREREREREHw+RpOA3KvTRSU9Px4MHD2Bvbw9dXV2pa3a/j1K5vYf9d6h8zyc3VEsC3XJco3IfKRdqqHyPYft3Kt+TsLCR4kqF1F78ROU+XvTtqPI9FkfPyZSV9NpXhTNnzsDGxkZYKXLjxg2YmprC2toawIfVJ5qamsJZb9evX4eamho+/fRToY13797h3r17SE5Ohr6+Pho1aiSzOlBRnaLtFo2rwNWrV5GQkCCzTXN2djZu376NxMRE6OnpoXnz5jAxMVF5LmrXri2zdXF6ejpOnjyJTz/9FFZWVjhz5gzevXsntw1TU1N06NBB+D4lJQW3b9/G3Llz0aVLF8ybN6/Y1/3Fixe4e/cugA9nJRY+Kw+QP0flFW/hOiKRCMbGxmjRooXKK2qLi0nROFSJr7BWrVrB0tJSpfgVPYtXr16Furq6sLW2PPHx8Xjw4AG0tLTg5OQEbW1tAMCbN29w8+ZNaGhooHXr1tDW1sa5c+egp6eHVq1a4ejRo+jUqZMQ18uXL/HgwQNoaGigWbNmUvEGBgaiY8eOwnOcn58vc39iYiLu37+PnJwctGzZUuqs0OzsbISHhyMpKQkmJiZo1aqVsM1nWFgYQkND8d1338kdX0n3SiQSXL9+HUlJSfjkk08gFotx584dYWWyRCJBREQEXr16hU8++QQXLlzA1q1bceLECYVz5OTkJDNuRfEooiiessyForG8ffsWV69eRb169dCsWTOFcydv7Kr2oei5AD6siI2Pj0eTJk2gq6uLiIgI9OzZU6n5vHTpEoyNjYUtsUsTX1W9XkDJ77mS5qbo+0/V17LovD158gQJCQlS/78oiartlXUeC7dfeOx6eno4fvw4unXrhmfPniE2NhY2NjZS5+nKe44Bxc9lScoynqysLLRs2RKHDx8G8GHnCmVjLul5UeW9V/T5KdpffHw87ty5o/T7UNF8FFbw705bW1uurK1iVTGOj+3nDiIiIiIiov8iJms/YkzWFo/JWvo3WrVqFU6fPo2goCClk0xEFSUsLAyPHz/GxIkTy7VdiUSCNWvWoHv37mjZsiUAwM/PDxkZGVi3bl259lVe8VTUXJDq+Hop5+nTpzAxMZFJNGdkZCAmJgaNGjXC2rVr0bJlS9jZ2cHS0lJqHrOzs/Hbb78hIyMDEydORHR0NPT19WUSlU+ePIGBgQFq1aqF6OhoiEQimQ8RZWdn49mzZ3I/oPPmzRukpKTA1NRUJkkYFRUFIyMjmT7/+ecf1K5dW2p3j6ysLCxZsgQDBw6EmZkZRCIRNmzYIPVcnDhxAjdu3MCCBQtk4ihI1h46dAgtWrQAAERHRwvnDKupqcHU1FThh5NKGk9Bmzk5OVJJ4KLzZGxsjJo1a0pdy8/Px+PHj2FqagpTU1OpawkJCRCLxTA3Nxf6AICDBw9KvU+++uorvH79Gjt2yP48wGTtx4PJWiIiIiIiov8mboNMRIQPK1bWrCn+wwYaGhpYuXJlhcYwYcIEnDx5Ev369YOdnR2+/fbbYrdf/Bh9DHNI5cfMzEw4V7E8iUQiiMVijBs3Dl27dsWLFy/wzz//YPv27eXel7LPpKJ4KmouqpuKfo/z9ZKvNPM+cuRIjB8/Ht7e3lLl9+7dg5eXF65duwaxWAxfX19IJBI4ODggJiZGmMdnz55hxYoVuHz5MgBg2rRp6NmzJyZPniy0tWHDBuzbtw979+4V6kRFReHYsWOwsrIS6j179gx9+/bFo0ePhLJTp05hzZo1iIqKgqGhIZKTk9G8eXPhfHkAWL58OUxMTDB9+nRh/KmpqTh16hTs7e1hY2MjjL9jx444cuQIwsLCIJFIkJKSAmNjY+zatUvoMycnB3v27JGbrJVn2rRpiI+Ph4GBAbKysvD69WvY2Nhg4sSJ6Nu3r1RdZcZT0ObDhw9x8uRJqTkCgOPHj8PPzw+jR4+Gn5+f1LXz589jwoQJcHFxwbJly6Seh+vXr0NdXR0ODg4AgLNnzyIzM1PYsrvgffLgwQO8fftWqbETERERERERUeVispaICICRkREGDx5c7HWxWFzhMRgbGyMoKAjXrl2Duro6NDQ0KrzP8vQxzCGVn4Jf/FeEGTNmwMPDA5GRkTA0NETLli2hp6dX7v0o+0wqiqci56I6qej3OF8v+Spq3mfMmIHQ0FCkpqYiNzcXISEhMu9DY2Njuff+8ssv+OWXX7Bnzx6ppGOdOnWwbNmyEs+CDw0NxYwZMzB9+nR4e3tDR0cHqamp2LZtG0aMGIFdu3bByclJOFN+4cKFwvhDQ0NhbGwMNTU1oUwsFiMwMBDt2rXDggULMHr0aOjo6MDGxkZqNW/BdtDyaGho4LvvvpNZFTxq1CghQZ2amoqDBw/C398fiYmJGD16tErjKWBlZYXAwEBMmzZNqq/AwECZ/gscOnQIw4YNw4EDB5Ceni71PLx48QJaWlpC2a1bt2BiYoK4uDjs27dPeJ/o6uriiy++KHYOiIiIiIiIiKjqMFlLRARAT08Pzs7OVR0G9PT00Llz56oOo1Q+ljmk6qFBgwZo0KBBhfahyjNZGfFUdxX9HufrJV9FzrumpiZ8fHwQEBCAS5cuCefpliQoKAg//vgjduzYgcaNG0tdGzNmDAICAhAWFia3rfz8fKxcuVJY9VlAX18fvr6+ePz4MVasWIEjR46gY8eOWL58OWJjY4Xx79ixAyNGjMCmTZvw6aefCkcG+Pn5Yfjw4WjQoAEMDQ3h7e1dYhxFicVimXPui9LX18eoUaMgEomwZs0aeHh4oEaNGkqPp0CnTp1kkrWvXr3CnTt35P7/PykpCX///TcCAwPx/PlznDhxQureX3/9Fbq6usIc6erqCuN/8uSJcMZtZGSkwnl4O2s80hJiFdb7WNUFkFjVQZSDihyHvONXiIiIiIiIqOpxmRMRERER0X+Unp4evvrqK6xYsQIZGRkl1j1z5gyWLFmCn376Cc2bN1e5rcjISMTHx2PIkCFy2/f09MS9e/fw8uVLNGjQAJaWlrhw4QIAIDc3F1evXkWvXr1Qp04d3LhxA8CHbZbj4uLQsWPHUo1JVcOGDUN2djYuX76s0ngKfPLJJ8jOzsb169eFsmPHjqFr165QV5f9HO3vv/+OJk2aoFGjRvDw8MCRI0eQn59fYowVOX4iIiIiIiIiKn9M1hIRERER/UdJJBJ4eHjA3NwcmzZtKrZeREQEfHx8ULt2bbmJWmXaKkhaFj2vtUDBNsAvXrwAALi6ugrJ2lu3bsHAwADW1tZwdnbGxYsXAQAXL15E3bp10ahRI5XHVBpaWlowNzfHq1evVB4P8GEVb9++fREYGCiUBQUFFbuy99ChQxgwYAAAoHv37khJSRHmpDgVOX6q3vLy8uR+ERERERERUdVisrYKXL16FXv37sVff/2FnJycqg6HiIiIiP5DRCKRzPcLFy7Erl27EBUVJfeeBw8eYNOmTRCLxZg/f36JbRfXlq6uLoAP57/Kk5aWBgDQ1tYG8CFZe/36dWRnZ+PixYtwcXEBALi4uAgJy0uXLsHV1VWlOMoqKysLenp6Ko+nQP/+/XHixAlkZWXhn3/+QVJSkjC2wq5du4bnz5/D1tYWkZGRiI6ORuvWrXHo0CGFMVbk+Kn6ioiIkPlSZotsIiIiIiIiqlhM1lay2bNnY/bs2bh9+zYCAgLg5eWFzMzMqg6LiIiIiP4ldHV1oK6slQAAGBdJREFUkZycLFP+5s0bqKmpQUdHR+aanZ0dBg4ciGXLlskkc4EP2/+6uLhgw4YNOH/+fIkrNotrq1GjRlBTU8Pdu3fl3vfw4UPo6OgIK1WdnZ2Rn5+P8PBwXL58WUhoOjs749GjR3j37h2uXLkiN1mrzJhK4+nTp3j79q2wNbEq4ylgY2MDKysr/PXXXwgKCsLnn38OsVj2x7KDBw/CyMgI/v7+8PHxgY+PD6KiovDXX3/hzZs3CmOtiPFT9ebg4CDzZWtrW9VhERERERER/ecxWVuJLl26hNOnT+PAgQNYtWoVDh06hLS0NOzbt6+qQyMiIiKif4nmzZvj3LlzMuV//fUXWrZsKfdsVACYPn06Hjx4gFOnThXbtqWlJdasWYP169fjr7/+KraevLZMTEzQuXNnbNiwAdnZ2VL1s7OzsWXLFvTt21dIJuvo6KB169a4cuUK7ty5IyRra9SogcaNG+PAgQNIT09H27ZtVYqjtPLz87F69WrY29ujZcuWKo+nMHd3d4SFheH48eNyt0B+//49QkJCsHr1agQHBwtfISEhqFu3LoKCgpSKuTzHT9Wfmpqa3C8iIiIiIiKqWvJ/U0MV4vTp02jXrh0sLCwAfNgSrVevXjh16hRGjhxZtcERERER0b/C5MmT8cUXX2Dq1Klwd3eHWCxGWFgYgoODsX379mLvMzAwwOzZs7F8+fIS22/fvj18fX0xe/Zs7N+/X+7KvOLaWrhwIYYPH46hQ4di+PDhsLCwQEJCAvbs2QMtLS3MmTNHqr6rqyu2bt0KS0tL1KpVSyh3cXHBnj174OTkJGxHXJYxyfPixQtEREQgPz8fCQkJ2LdvH6KioqTmUNXxFOjbty/WrVuHOnXqwM7OTuZ6UFAQatSoIXd75P79++Pw4cNK/fygyviNV2+BgYGBwnofo7y8PERERMDBwaFaJx//LeMgIiIiIiIi1TBZW4meP3+Ohg0bSpVZWlri8OHDVRQREREREf3bNGzYEL///jt27tyJrVu3QiKRoEmTJjh06BAaN24s1Ktfv75Mcq5///74+++/8ezZM6l6pqamUvXGjx+P6OhorFmzBuvWrVO6LXNzcxw+fBgHDhzA0aNH8fbtW5iZmWHAgAEYPHgwtLS0pNro1KkTDh06hF69esmUnzt3Dr1795YqVzYORerXr4+bN2/i5s2bEIlEqFGjBpycnBAQEAAzM7NSjadwbCYmJujduzeaNm0q1ZaRkREAIDw8HN7e3nK3R3Z3d8eff/6JqKgo1K5dW+pM3PIaPxERERERERFVHpFEIpFUdRD/FSNGjICjoyN8fHyEstDQUPj7++PKlSsy9VNTU/Ho0SNYWVlJ/RIGAAafWapy/wc7+at8j2fkWpXq77WdrnIfGXe6qnyPTou/Vb7nzc/9VapvMu53lft4O2u8yvcYr94iU5aZmYno6Gg0adIE+vr6KrdJRERERKSMwj9z6OnpVXU4pZKXl4fIyEjY2tpW6xWpVTGOjIwMPHv2jD93EBERERERVSGurK1E2trayMrKkirLzMyUScQWKKgbHR0tc2157SEq9x8ZGanyPYvQW3GlMvYBrU2q31Oafjp9q1L116XpY8JslW9JLKGfrKws/tKEiIiIqJxkZWXh+fPnxV4Xi8WwsbGpxIiqXkk/c1Q3pfpZ5CNUFePgzx1ERERERERVh8naSmRpaYm4uDipspiYGFhZWcmtb2RkBGtra2hpacndAo3+vfLz85GVlSVshUdEREREZffq1St8+23xH+DT0NDApk2l+CBhNcafOf7b+HMHERERERFR1eM2yJXo9OnT8PPzQ2hoKIyMjJCTk4OBAwfC3d0dY8aMqerwiIiIiIiIiIiIiIiIiKgSMVlbiSQSCcaOHYtXr16hR48euHr1Kt6+fYsDBw5AV1e3qsMjIiIiIiIiIiIiIiIiokrEZG0ly83NxdGjR/H48WPUqVMHHh4e0NPTK9c+0tPTERwcjJCQEGzevLlc2waAjIwMxMTEoG7duuUae15eHtTU1GT60tHRKbc+Krrt9+/fQ0tLC5qamsXWOXPmDJo1awYzM7Ny7ZuIiIiISBWXL19GeHg4DAwM0LNnT9SsWbOqQ5Jy/vx5XLt2TapMQ0MDU6dOFb5PTExEaGgoUlJS4ODgABcXF6n6iq5XlOzsbOzevRtNmzZFu3btpK5JJBL89ddfiIyMRM2aNeHm5gYDA4Nyu05ERERERETVCw8lqmTq6uro378/vvrqK3h5eZVrsvPWrVvw9/dHhw4dsHr1atja2pZLm9988w0CAgKQkpKCK1euoHPnzujbty+cnZ2xZ8+ecogcOHjwIAYNGiRT7uPjgyVLlpRLHwBw9+5dTJgwAQ4ODnBwcEDLli3x5ZdfIiwsrFzanzx5Ms6ePSt8v27dOty9e1eqzpo1a/DkyZNy6Y+IiIiIqDRWr16NmTNnIikpCZcuXcLnn3+OqKioqg5LyqlTp3DmzBnk5eUJX7m5ucL1J0+eoE+fPjh//jzevHmD2bNnIyAgQOnrFeXVq1cYPnw4Nm3ahCtXrshcnz59OlatWoWUlBQEBQWhf//+ePv2bbldJyIiIiIioupFvaoDoLJ58+YNgoKCcOjQIURFRUEkEmH9+vXo2LEj1NXL9vK+ffsWI0aMgJ2dHSQSCR4/fozY2Fj4+fnByckJN2/exMKFC9GhQwc0aNCg1P1cuHABixYtwsyZM5Gfnw+x+P8/QzBnzhyMHj0aDRs2hLe3d5nGc+XKFYwdOxYODg6YM2cO6tWrh/fv3+P8+fPw9fXFxIkTMW3atDL1UdS1a9fQokWLcm2TiIiIiKgs4uPjsX37dhw8eBBNmzYF8OHf3evXr8eaNWuqOLr/l5qaCmdnZ8yePVvu9XXr1qFr165YtWoVAMDDwwNffPEFhg0bBgsLC4XXK8qkSZMwadIk/PLLLzLXrl27hrNnzyIkJAS1atVCfn4+vL29sWvXLkyfPr3M14mIiIiIiKj64craakgikeDcuXPw9fWFq6srgoKCMGTIEJw4cQIaGhro0qVLmRO1AHD27Fk0adIE+/btw/79+5GZmQlLS0sMGDAAVlZW8PDwQOfOnXH58uUy9fPLL79g9OjRGDNmjFSiFgAaN26MRYsWYffu3WXqAwAWL16MoUOHYs+ePfD09ISrqyv69OmDlStXYvv27diyZQsePXpU5n6IiIiIiD5mFy9ehKWlpZCoBYA+ffpI7RDzMUhNTS1xJ6Lz58+jd+/ewvfNmjVDvXr1cPHiRaWuV5SAgAB069ZN7rVz586hTZs2qFWrFgBALBbDzc1NmPuyXiciIiIiIqLqhytrq6H3799j7Nix6NevH/744w/Y2NgAAFJSUsq1n8TERKlf4LRo0QJZWVlSderWrYtXr16VqZ+nT59i4sSJxV5v164doqOjy3TG7JMnT5CQkIAZM2bIve7s7IzPP/8cx48fR5MmTUrVBxERERFRdRATE4O6detKldWtWxfv37/H27dvYWxsXEWRSUtNTYWamhr++OMPvHz5EtbW1ujWrRvU1NTw5s0bpKamyh1HdHS0wusVycrKqthrMTExqFOnjkxMMTEx5XKdiIiIiIiIqh+urK2GtLW18fnnnyMkJAR+fn7Ys2dPhZxRlJ2dLbVCV1NTE2pqalJ1xGIx8vPzy9RPbm6uzIrawvLy8iCRSCASiUrdR0xMDBo0aABdXd1i67Ro0QKxsbGl7oOIiIiIqDrIysqCpqamVJmWlpZw7WORmpqKrVu34tq1a0hOTsZ3330HLy8vZGdnC3EWHYempiaysrIUXq8qmZmZwlwX0NLSQmZmZrlcJyIiIiIiouqHK2urIU1NTaxevRrJyckIDAzEwYMH8e2336Jdu3aQSCQy576WRVZWFt68eQPgwy8GMjMzhe8LykramkwZtra2OHPmTLFnu4aGhqJ+/frQ1tYudR+ZmZkKVwhoa2sjJyen1H0USE1NFeYoJydH6nsAZU5uExERERGVhba2tkxyLyMjAwBKvZNNRVizZg309fVhamoKABg3bhx69OiB48ePo1OnTgAgM47MzEzo6OgIPzsUd72q6OjoCHNdIDMzU/hQaVmvExERERERUfXDZG01ZmRkhOHDh2P48OG4ffs2Dhw4AJFIhM6dO6Nfv37o378/GjVqVKY+9u/fj/3790uV7dmzR+r7krYwVoanpycmT54MCwsLDBgwQEg0SyQSHD9+HMuWLcPMmTPL1AfwYQVv4aRpUenp6WXuAwD8/Pykvg8PDy+XdomIiIiIyoO1tTWOHTsmVfb8+XMYGxvDyMioiqKSVb9+fanvjY2NYWVlhYSEBCHWmJgYNG7cWKjz/PlzDBgwQOH1qlK/fn3cvn1bquzZs2ewtrYul+tERERERERU/TBZ+y/RsmVLtGzZEvPmzcPx48dx8OBB7N+/H9euXSt1mwMHDkS7du0U1rOwsCh1HwDQsWNH+Pr64ptvvsG6detgY2MDkUiEp0+fIj4+Hl9++SW8vb3L1AcAXL58GS4uLiXW6dmzZ5n6WLhwIVJTUxXWKzhnmIiIiIiosrVv3x4LFizAjRs34OjoCAA4fPgwPvvssyqO7P/l5ubCw8MDEyZMQN++fQEAL1++xJMnTzBlyhQAQKdOnRAYGIiuXbsCAC5duoSkpCR06NBBqetVoXPnzti2bRvi4uJQt25dZGdn4+jRo+jTp0+5XCciIiIiIqLqRySRSCRVHQRVjKioKDRo0KCqw1Da8+fPERwcjGfPnkEkEqFu3bro1q0bmjRpUua23717h2fPnimsV6NGDX4qnYiIiIj+9TZv3ozt27ejZ8+eiI6OxrNnz7B//36Ym5tXdWiC3bt3Y/Xq1ejduzd0dXUREhICR0dH/PjjjwCAmJgYDBs2DLa2tqhXrx6Cg4MxZcoUjBgxQqnrFeHly5fYunUrAODkyZOoWbMmHBwcYGJigkmTJgEA5s+fjwsXLqBLly64ffs28vPz8euvvwpbGZf1OhEREREREVUvTNYSERERERH9B0VERODGjRswMjJCjx49YGhoWNUhyXj8+DGuXLmC/Px82Nvbw8nJSer6u3fvcPLkSbx//x6tW7dGixYtVLpe3l6/fo0DBw7IlBsZGcHLy0v4/vz583j48CHMzc3Ro0cPaGlpSdUv63UiIiIiIiKqPpisJSIiIiIiIiIiIiIiIiKqAuKqDoCIiIiIiIiIiIiIiIiI6L+IyVoiIiIiIiIiIiIiIiIioirAZC0RERERERERERERERERURVgspaIiIiIiIiIiIiIiIiIqAowWUvlTiKR4ODBg/D09ISLiws6duyIESNG4OTJkxXSX8+ePRESElIhbRMRERERERERERERERFVFPWqDoD+febMmYMLFy5g+vTpaN26NXJychAWFoYZM2Zg7ty58Pb2Ltf+MjIykJubW65tEhEREREREREREREREVU0JmupXJ0+fRpBQUHYv38/HBwchHJbW1sYGhrijz/+wNChQ6GuzkePiIiIiIiIiIiIiIiI/tuYMaNyFRwcjNatW0slagt4e3tLrapdvXo1UlNTkZqaivDwcISFhSEvLw/r1q1DcHAwkpOTYWlpiWnTpsHV1RUAkJmZiZUrV+L06dPQ0tLCl19+CbH4/3fzlkgk+O2333DgwAEkJSUJ97u4uFT42ImIiIiIqHI9fPgQW7duxe3bt5GdnQ1LS0t4eHhg4MCBVR0aERERERERkVJ4Zi2Vq+joaDRs2FCpuvn5+Th9+jQaNmyI9evXAwCOHDmC33//HVu3bsW5c+fQp08f+Pj4ID09HQCwdetWXL58GQcOHMCxY8fw+vVrJCYmCm0ePnwYGzZswPLly3HmzBmMGzcOEyZMQExMTPkPloiIiIiIqszZs2cxePBg6OrqYuXKldi0aRPc3Nzw7bff4ptvvqm0OMaNG4eEhIRK64+IiIiIiIj+XZispXKlpqYmUzZx4kR8+umnwldISAgAQCQSQUtLC5MmTYK9vT0AYPDgwTh16hQsLS2hoaEBd3d3ZGRkCMnWM2fOwMPDA+bm5tDU1MSUKVOk+jpy5Ai++OILNGvWDGKxGF26dIGTkxMCAwMreORERERERFRZsrOz8fXXX2PgwIFYsmQJHB0dYWdnBy8vL2zcuBFhYWF4+fJlhcchkUhw48YN5OXlVXhfRERERERE9O/EbZCpXFlZWeGff/6RKlu8eDEyMzMBACNHjkRubq5wrV69elJ14+PjsX79ety9exfZ2dnIz88HAOG/r1+/hqmpqVBfU1MThoaGwvcvXrzAjh078Msvvwhl2dnZMDc3L6cREhERERFRVbt27RoSExMxadIkmWutW7fG+fPnheNSbt++jfXr1+PJkycwNDRE586dMWnSJGhpaeHatWuYNWsWzp49K9z/7bffIj09HYsXL8bdu3fh6+uLZcuWYfXq1UhMTETTpk2xdOlSmJmZoWfPnkhLS8PQoUMxZswYjBo1qtLmgIiIiIiIiP4dmKylctWnTx+MGjUK169fh5OTEwBIJUqLrrwt+v28efNgYGCA3377Dfr6+khKSkK7du2E60ZGRnj37p3wfVZWFpKTk4Xva9WqhWHDhmHcuHHlOSwiIiIiIvqIPHv2DEZGRsV+KLMgUfvy5UuMGDECX331FdatW4dXr15h6tSpyMrKgp+fH3JycvD27Vupe9PS0oRjWCQSCRISEnDo0CGsX78eEokEY8aMwfbt2zFnzhzs3r0bnTp1wr59+2Q+iEpERERERESkDG6DTOWqXbt2GDBgAHx9fXHs2DEkJycjLS0NERERmDVrFt69e1fimbaJiYlo0qQJ9PX1kZKSgh9//BEikQipqakAgDZt2uDo0aNITk5Gfn4+Nm/eLHV/nz59cPjwYWHLs4SEBAwZMgS3b9+uuEETEREREVGlEovFEIlECuuFhITA3Nwcnp6e0NHRQf369fHll1/izz//VLqvvLw8+Pr6onbt2qhTpw46deqE58+flyV8IiIiIiIiIgFX1lK5W7FiBfbu3YvNmzdj7ty5yM3NRe3atdG5c2cEBQWhTp06xd7r6+uLRYsW4bfffkONGjWwbNkyxMfHY9asWVi/fj0mTpyIqKgodOrUCdra2hg6dCisra2FrZU9PT3x9u1bDB48WNg6eejQoWjRokWljJ2IiIiIiCpe3bp18e7dO7x+/RpmZmbF1ktISJD5+cPc3ByJiYmQSCRK91d4Ba+6urrU0S5EREREREREZcFkLZU7kUgELy8veHl5IT8/H/n5+VBXl33UfHx8ZH5B0rNnT/Ts2RM5OTnQ0NAAAGzduhW5ublCGz///DPy8vKET9NPnDhRuKampgYfHx/4+PhI3UNERERERP8ezs7OMDAwwNatWzF37lypa+/fv4evry/8/f1hZmaGS5cuSV1PSkqCqakpRCIRRCKRzM8kycnJws8iRERERERERBWN2yBThRKLxcUmTDU1NaGlpSX3WtFfjhRtQ01NTdj2TFtbW24fTNQSEREREf07aWlpYcGCBdi9ezfWr1+PV69eISsrC9evX8eIESOQlZUFKysrdOnSBY8fP8bly5cBfDiP9sCBA+jWrRsAoHbt2sjJyUFERAQA4N69e7h69arScaipqQGAcGwLERERERERkaqYzSIiIiIiIqJqx8PDA8bGxvjpp5+wadMm5ObmombNmvDw8MC0adOgpqaGhg0b4vvvv8eCBQuQn5+PzMxMdOzYEbNmzQIAWFtbw9PTE8OHD4ehoSE++eQTeHh44OXLl0rFYGZmhpYtW2LIkCEYNmyYzCpfIiIiIiIiIkVEElUO6iEiIiIiIiL6yOTl5SE7Oxs6OjrF1snMzISWlpawQ09hubm5yM3Nhba2NjIzM5Gbmwt9fX3k5uYiJSUFJiYmQt2MjAzk5eVBX19fqqykvomIiIiIiIiKw2QtEREREREREREREREREVEV4Jm1RERERERERERERERERERVgMlaIiIiIiIiIiIiIiIiIqIqwGQtEREREREREREREREREVEVYLKWiIiIiIiIiIiIiIiIiKgKMFlLRERERERERERERERERFQFmKwlIiIiIiIiIiIiIiIiIqoCTNYSEREREREREREREREREVUBJmuJiIiIiIiIiIiIiIiIiKoAk7VERERERERERERERERERFWAyVoiIiIiIiIiIiIiIiIioirAZC0RERERERERERERERERURX4P6OByN+IZ7A3AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1800x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Phase 6 — Nutri-Score + Agribalyse\n",
    "fig, axes = plt.subplots(1, 3, figsize=(18, 5))\n",
    "\n",
    "# Grade distribution\n",
    "scored = p6_scores[p6_scores['nutri_score_calculated'] == True]\n",
    "grade_order = ['A','B','C','D','E']\n",
    "grade_counts = scored['nutri_score_grade'].value_counts().reindex(grade_order, fill_value=0)\n",
    "grade_colors = ['#27ae60','#2ecc71','#f1c40f','#e67e22','#e74c3c']\n",
    "grade_counts.plot(kind='bar', ax=axes[0], color=grade_colors)\n",
    "axes[0].set_title('Phase 6 — Nutri-Score Grade Distribution', fontsize=12)\n",
    "axes[0].set_ylabel('Count')\n",
    "axes[0].set_xlabel('Grade')\n",
    "\n",
    "# Exclusion reasons\n",
    "p6_excl['score_exclusion_reason'].value_counts().plot(kind='barh', ax=axes[1], color=COLORS[2])\n",
    "axes[1].set_title('Phase 6 — Exclusion Reasons', fontsize=12)\n",
    "axes[1].set_xlabel('Count')\n",
    "\n",
    "# Agribalyse confidence\n",
    "p6_agri['mapping_confidence'].value_counts().plot(kind='pie', ax=axes[2], autopct='%1.1f%%', colors=COLORS[:4])\n",
    "axes[2].set_title('Phase 6 — Agribalyse Confidence', fontsize=12)\n",
    "axes[2].set_ylabel('')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
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    "---\n",
    "# Pipeline Summary\n",
    "\n",
    "| Phase | Input | Output | Key Metric |\n",
    "|-------|-------|--------|------------|\n",
    "| 1 | products.parquet (4,440 × 16) | phase1_output (4,440 × 14) | 2 null cols dropped |\n",
    "| 2 | phase1_output (4,440 × 14) | phase2_output (4,440 × 34) | 20 new columns |\n",
    "| 3 | phase2_output (4,440 × 34) | catalog (3,691) + mapping (4,440) | 19 taxonomy categories |\n",
    "| 4 | phase3 mapping + phase2 | variant mapping (4,440) + variants (4,299) | 4,299 variants |\n",
    "| 5 | nutrition + phase3 + phase4 | per-100g (4,440) + mapping (4,440) | 100% match |\n",
    "| 6 | phase5 outputs | scores (4,440) + agribalyse (4,440) | 364 scored (8.2%) |\n",
    "\n",
    "---\n",
    "\n",
    "## Final Entity Counts\n",
    "\n",
    "| Entity | Count |\n",
    "|--------|-------|\n",
    "| Products | 4,440 |\n",
    "| Product Groups | 3,691 |\n",
    "| Variants | 4,299 |\n",
    "| Non-food Products | 394 |\n",
    "| Unknown Domain | 1,232 |\n",
    "| Food Products | 2,814 |\n",
    "| Nutri-Score Eligible | 364 |\n",
    "| Nutri-Score A | 31 |\n",
    "| Nutri-Score B | 42 |\n",
    "| Nutri-Score C | 135 |\n",
    "| Nutri-Score D | 83 |\n",
    "| Nutri-Score E | 73 |"
   ]
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