diff --git "a/src/baseline.ipynb" "b/src/baseline.ipynb"
--- "a/src/baseline.ipynb"
+++ "b/src/baseline.ipynb"
@@ -2,14 +2,21 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
     "import pandas as pd\n",
+    "import torch.nn as nn\n",
+    "import torch\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from sklearn.metrics import roc_curve, precision_recall_curve\n",
     "import os\n",
     "\n",
-    "DATA_DIR = os.path.join(\"..\", \"data\")"
+    "DATA_DIR = os.path.join(\"..\", \"data\")\n",
+    "\n",
+    "sns.set()"
    ]
   },
   {
@@ -21,7 +28,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/var/folders/v8/0hd98b512cn3ms2rz146k7jw0000gn/T/ipykernel_86008/712369024.py:1: DtypeWarning: Columns (504,505,506) have mixed types. Specify dtype option on import or set low_memory=False.\n",
+      "/var/folders/v8/0hd98b512cn3ms2rz146k7jw0000gn/T/ipykernel_70481/712369024.py:1: DtypeWarning: Columns (505,506,507) have mixed types. Specify dtype option on import or set low_memory=False.\n",
       "  games_df = pd.read_csv(os.path.join(DATA_DIR, \"AllSuperDetailedGames.csv\"))\n"
      ]
     },
@@ -31,8 +38,8 @@
      "text": [
       "<class 'pandas.core.frame.DataFrame'>\n",
       "RangeIndex: 377608 entries, 0 to 377607\n",
-      "Columns: 512 entries, Unnamed: 0.1 to BaselinePrediction\n",
-      "dtypes: float64(364), int64(141), object(7)\n",
+      "Columns: 513 entries, Unnamed: 0.2 to BaselinePrediction\n",
+      "dtypes: float64(364), int64(142), object(7)\n",
       "memory usage: 1.4+ GB\n"
      ]
     }
@@ -52,16 +59,16 @@
     "# and if the seed is the same, have it be the winning percentage that determines the winner. We will compare\n",
     "# our ML models to this one to decide if performance is actually good or not.\n",
     "\n",
-    "def predict_baseline(row: pd.Series) -> int:\n",
-    "    cs, opp_cs = row[\"ChalkSeed\"], row[\"OppChalkSeed\"]\n",
-    "    if cs != opp_cs:\n",
-    "        return 1 if cs < opp_cs else 0\n",
-    "    return 1 if row[\"Win mean reg\"] > row[\"OppWin mean reg\"] else 0\n",
+    "# def predict_baseline(row: pd.Series) -> int:\n",
+    "#     cs, opp_cs = row[\"ChalkSeed\"], row[\"OppChalkSeed\"]\n",
+    "#     if cs != opp_cs:\n",
+    "#         return 1 if cs < opp_cs else 0\n",
+    "#     return 1 if row[\"Win mean reg\"] > row[\"OppWin mean reg\"] else 0\n",
     "\n",
-    "games_df[\"BaselinePrediction\"] = games_df.apply(\n",
-    "    lambda row: predict_baseline(row),\n",
-    "    axis=1,\n",
-    ")\n"
+    "# games_df[\"BaselinePrediction\"] = games_df.apply(\n",
+    "#     lambda row: predict_baseline(row),\n",
+    "#     axis=1,\n",
+    "# )\n"
    ]
   },
   {
@@ -90,6 +97,7 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
+       "      <th>Unnamed: 0.2</th>\n",
        "      <th>Unnamed: 0.1</th>\n",
        "      <th>Unnamed: 0</th>\n",
        "      <th>Season</th>\n",
@@ -99,7 +107,6 @@
        "      <th>OppTeamID</th>\n",
        "      <th>OppScore</th>\n",
        "      <th>WLoc</th>\n",
-       "      <th>NumOT</th>\n",
        "      <th>...</th>\n",
        "      <th>OppWin median tourney</th>\n",
        "      <th>OppWin mean tourney</th>\n",
@@ -118,6 +125,7 @@
        "      <th>179744</th>\n",
        "      <td>179744</td>\n",
        "      <td>179744</td>\n",
+       "      <td>179744</td>\n",
        "      <td>2023</td>\n",
        "      <td>69</td>\n",
        "      <td>3166</td>\n",
@@ -125,7 +133,6 @@
        "      <td>3266</td>\n",
        "      <td>42</td>\n",
        "      <td>H</td>\n",
-       "      <td>0</td>\n",
        "      <td>...</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.000000</td>\n",
@@ -142,6 +149,7 @@
        "      <th>65864</th>\n",
        "      <td>65864</td>\n",
        "      <td>65864</td>\n",
+       "      <td>65864</td>\n",
        "      <td>2015</td>\n",
        "      <td>131</td>\n",
        "      <td>1437</td>\n",
@@ -149,7 +157,6 @@
        "      <td>1462</td>\n",
        "      <td>52</td>\n",
        "      <td>N</td>\n",
-       "      <td>0</td>\n",
        "      <td>...</td>\n",
        "      <td>0.5</td>\n",
        "      <td>0.500000</td>\n",
@@ -166,6 +173,7 @@
        "      <th>70502</th>\n",
        "      <td>70502</td>\n",
        "      <td>70502</td>\n",
+       "      <td>70502</td>\n",
        "      <td>2016</td>\n",
        "      <td>115</td>\n",
        "      <td>1150</td>\n",
@@ -173,7 +181,6 @@
        "      <td>1427</td>\n",
        "      <td>108</td>\n",
        "      <td>H</td>\n",
-       "      <td>2</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -190,6 +197,7 @@
        "      <th>347567</th>\n",
        "      <td>347567</td>\n",
        "      <td>347567</td>\n",
+       "      <td>347567</td>\n",
        "      <td>2019</td>\n",
        "      <td>74</td>\n",
        "      <td>3434</td>\n",
@@ -197,7 +205,6 @@
        "      <td>3232</td>\n",
        "      <td>86</td>\n",
        "      <td>A</td>\n",
-       "      <td>1</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -214,6 +221,7 @@
        "      <th>10344</th>\n",
        "      <td>10344</td>\n",
        "      <td>10344</td>\n",
+       "      <td>10344</td>\n",
        "      <td>2005</td>\n",
        "      <td>47</td>\n",
        "      <td>1416</td>\n",
@@ -221,7 +229,6 @@
        "      <td>1282</td>\n",
        "      <td>56</td>\n",
        "      <td>A</td>\n",
-       "      <td>0</td>\n",
        "      <td>...</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.000000</td>\n",
@@ -238,6 +245,7 @@
        "      <th>22285</th>\n",
        "      <td>22285</td>\n",
        "      <td>22285</td>\n",
+       "      <td>22285</td>\n",
        "      <td>2007</td>\n",
        "      <td>99</td>\n",
        "      <td>1397</td>\n",
@@ -245,7 +253,6 @@
        "      <td>1261</td>\n",
        "      <td>67</td>\n",
        "      <td>H</td>\n",
-       "      <td>0</td>\n",
        "      <td>...</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.333333</td>\n",
@@ -262,6 +269,7 @@
        "      <th>247533</th>\n",
        "      <td>247533</td>\n",
        "      <td>247533</td>\n",
+       "      <td>247533</td>\n",
        "      <td>2015</td>\n",
        "      <td>17</td>\n",
        "      <td>1183</td>\n",
@@ -269,7 +277,6 @@
        "      <td>1413</td>\n",
        "      <td>63</td>\n",
        "      <td>A</td>\n",
-       "      <td>0</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -286,6 +293,7 @@
        "      <th>265381</th>\n",
        "      <td>265381</td>\n",
        "      <td>265381</td>\n",
+       "      <td>265381</td>\n",
        "      <td>2018</td>\n",
        "      <td>60</td>\n",
        "      <td>1209</td>\n",
@@ -293,7 +301,6 @@
        "      <td>1375</td>\n",
        "      <td>86</td>\n",
        "      <td>H</td>\n",
-       "      <td>0</td>\n",
        "      <td>...</td>\n",
        "      <td>1.0</td>\n",
        "      <td>1.000000</td>\n",
@@ -310,6 +317,7 @@
        "      <th>168826</th>\n",
        "      <td>168826</td>\n",
        "      <td>168826</td>\n",
+       "      <td>168826</td>\n",
        "      <td>2021</td>\n",
        "      <td>30</td>\n",
        "      <td>3235</td>\n",
@@ -317,7 +325,6 @@
        "      <td>3395</td>\n",
        "      <td>68</td>\n",
        "      <td>A</td>\n",
-       "      <td>0</td>\n",
        "      <td>...</td>\n",
        "      <td>0.5</td>\n",
        "      <td>0.500000</td>\n",
@@ -334,6 +341,7 @@
        "      <th>108588</th>\n",
        "      <td>108588</td>\n",
        "      <td>108588</td>\n",
+       "      <td>108588</td>\n",
        "      <td>2024</td>\n",
        "      <td>19</td>\n",
        "      <td>1456</td>\n",
@@ -341,7 +349,6 @@
        "      <td>1420</td>\n",
        "      <td>81</td>\n",
        "      <td>H</td>\n",
-       "      <td>0</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -356,33 +363,33 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>10 rows × 512 columns</p>\n",
+       "<p>10 rows × 513 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "        Unnamed: 0.1  Unnamed: 0  Season  DayNum  TeamID  TeamScore  \\\n",
-       "179744        179744      179744    2023      69    3166         68   \n",
-       "65864          65864       65864    2015     131    1437         69   \n",
-       "70502          70502       70502    2016     115    1150        114   \n",
-       "347567        347567      347567    2019      74    3434         82   \n",
-       "10344          10344       10344    2005      47    1416         57   \n",
-       "22285          22285       22285    2007      99    1397         70   \n",
-       "247533        247533      247533    2015      17    1183         61   \n",
-       "265381        265381      265381    2018      60    1209         64   \n",
-       "168826        168826      168826    2021      30    3235         91   \n",
-       "108588        108588      108588    2024      19    1456         96   \n",
+       "        Unnamed: 0.2  Unnamed: 0.1  Unnamed: 0  Season  DayNum  TeamID  \\\n",
+       "179744        179744        179744      179744    2023      69    3166   \n",
+       "65864          65864         65864       65864    2015     131    1437   \n",
+       "70502          70502         70502       70502    2016     115    1150   \n",
+       "347567        347567        347567      347567    2019      74    3434   \n",
+       "10344          10344         10344       10344    2005      47    1416   \n",
+       "22285          22285         22285       22285    2007      99    1397   \n",
+       "247533        247533        247533      247533    2015      17    1183   \n",
+       "265381        265381        265381      265381    2018      60    1209   \n",
+       "168826        168826        168826      168826    2021      30    3235   \n",
+       "108588        108588        108588      108588    2024      19    1456   \n",
        "\n",
-       "        OppTeamID  OppScore WLoc  NumOT  ...  OppWin median tourney  \\\n",
-       "179744       3266        42    H      0  ...                    1.0   \n",
-       "65864        1462        52    N      0  ...                    0.5   \n",
-       "70502        1427       108    H      2  ...                    NaN   \n",
-       "347567       3232        86    A      1  ...                    NaN   \n",
-       "10344        1282        56    A      0  ...                    1.0   \n",
-       "22285        1261        67    H      0  ...                    0.0   \n",
-       "247533       1413        63    A      0  ...                    NaN   \n",
-       "265381       1375        86    H      0  ...                    1.0   \n",
-       "168826       3395        68    A      0  ...                    0.5   \n",
-       "108588       1420        81    H      0  ...                    NaN   \n",
+       "        TeamScore  OppTeamID  OppScore WLoc  ...  OppWin median tourney  \\\n",
+       "179744         68       3266        42    H  ...                    1.0   \n",
+       "65864          69       1462        52    N  ...                    0.5   \n",
+       "70502         114       1427       108    H  ...                    NaN   \n",
+       "347567         82       3232        86    A  ...                    NaN   \n",
+       "10344          57       1282        56    A  ...                    1.0   \n",
+       "22285          70       1261        67    H  ...                    0.0   \n",
+       "247533         61       1413        63    A  ...                    NaN   \n",
+       "265381         64       1375        86    H  ...                    1.0   \n",
+       "168826         91       3395        68    A  ...                    0.5   \n",
+       "108588         96       1420        81    H  ...                    NaN   \n",
        "\n",
        "        OppWin mean tourney  Seed  ConfAbbrev    TeamName  FirstD1Season  \\\n",
        "179744             1.000000   NaN         NaN         NaN            NaN   \n",
@@ -408,7 +415,7 @@
        "168826           NaN        NaN           NaN                   0  \n",
        "108588           NaN        NaN          16.0                   0  \n",
        "\n",
-       "[10 rows x 512 columns]"
+       "[10 rows x 513 columns]"
       ]
      },
      "execution_count": 5,
@@ -425,17 +432,6 @@
    "execution_count": 6,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "from sklearn.metrics import accuracy_score, f1_score\n",
-    "import torch.nn as nn\n",
-    "import torch"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [],
    "source": [
     "mens_subset = games_df[games_df[\"League\"] == \"M\"]\n",
     "wmns_subset = games_df[games_df[\"League\"] == \"W\"]"
@@ -443,7 +439,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -470,124 +466,108 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.6727877259254456"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mens_base_bce = nn.BCEWithLogitsLoss()(mens_baseline_pred_T, mens_actual_T).item()\n",
-    "mens_base_bce"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.6931473016738892"
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "wmns_base_bce = nn.BCEWithLogitsLoss()(wmns_baseline_pred_T, wmns_actual_T).item()\n",
-    "wmns_base_bce"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "0.5697592193190255"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "accuracy_score(y_true=mens_actual_T, y_pred=mens_baseline_pred_T)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Mens base model BCE Score: 0.6727877259254456\n"
+     ]
+    },
     {
      "data": {
+      "image/png": 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",
       "text/plain": [
-       "0.5"
+       "<Figure size 1200x600 with 2 Axes>"
       ]
      },
-     "execution_count": 26,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "accuracy_score(y_true=wmns_actual_T, y_pred=wmns_baseline_pred_T)"
+    "mens_base_bce = nn.BCEWithLogitsLoss()(mens_baseline_pred_T, mens_actual_T).item()\n",
+    "print(f\"Mens base model BCE Score: {mens_base_bce}\")\n",
+    "\n",
+    "m_pred_arr = mens_baseline_pred_T.numpy().flatten()\n",
+    "m_true_arr = mens_actual_T.numpy().flatten()\n",
+    "\n",
+    "mfpr, mtpr, mthresholds_roc = roc_curve(m_true_arr, m_pred_arr)\n",
+    "mprecision, mrecall, mthreshold_prob = precision_recall_curve(m_true_arr, m_pred_arr)\n",
+    "\n",
+    "plt.figure(figsize=(12, 6))\n",
+    "plt.subplot(1, 2, 1)\n",
+    "plt.plot(mrecall, mprecision, label=\"Precision-Recall Curve\")\n",
+    "plt.xlabel(\"Recall\")\n",
+    "plt.ylabel(\"Precision\")\n",
+    "plt.title(\"Precision-Recall Curve\")\n",
+    "\n",
+    "# Plot ROC Curve\n",
+    "plt.subplot(1, 2, 2)\n",
+    "plt.plot(mfpr, mtpr, label=\"ROC Curve\")\n",
+    "plt.plot([0, 1], [0, 1], linestyle=\"--\")\n",
+    "plt.title(\"ROC Curve\")\n",
+    "plt.xlabel(\"False Positive Rate\")\n",
+    "plt.ylabel(\"True Positive Rate\")\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "0.3070527604567068"
-      ]
-     },
-     "execution_count": 27,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "f1_score(y_true=mens_actual_T, y_pred=mens_baseline_pred_T)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "womens base model BCE Score: 0.6931473016738892\n"
+     ]
+    },
     {
      "data": {
+      "image/png": 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YaN++PS+88AJubm7ld977fQaAxYsXX7R98eLFlJaWXrbc+iP/+zO0adMGb2/vP93/t8sCFy1aVH7532+zk/Ly8i56rdzcXN5++21OnTpFWFgY7u7ul4zJ/PnzueeeeyguLmb79u3069ePTp06lR+0/XZnvopOc2/atCndunXj448/JiUl5ZLHP/zwQ/Ly8sqnof82+y0jI6N8n+3bt1/x9xs0aBBWq5W3336bnJyc8teFK3vviIiISOW53HGL2WzmoYceYv369cycOfOS51y4cIF//OMfuLq6MmbMmPLn3HHHHaxevZqVK1de8pxNmzbx888/l6/zeDldu3alWbNmTJkyhby8vEsenzx5MiUlJQwdOhT49WRpXl7eRXcyvppjkuHDh5ORkcF7772HxWK5aDmImJgY0tPT8fT0vOiYZP369XzyySeXHKuKSPXTzCeReq579+5ER0fzwAMP8MADDxAeHs6ePXt45513iI+PL5/Sffvtt/PFF19gZ2dHTEwMu3fvZubMmTz55JPlayr9pkOHDpSVlfHggw9yzz334OzszNKlSzlz5swl60YBNGnShJEjR/LOO+9QUFBAdHQ0Bw8eZOrUqXTq1In4+PgqHYN//OMfDBs2jFdeeaX8dr7Dhg3jn//8JydOnKB169YkJiYyZcoUAgICCAkJwWKx8PDDD/PSSy/h6elJr169SExM5J133uGWW26hQYMGtG3bloULF9KqVSt8fHzYsWMHH330ESaTqXyNqop48cUXGTt2LDfddBO33347kZGRnDt3jmXLlrF48WJGjRpVfgaye/fuvPrqqzz//PPcddddpKen8957713x4qC/3dluxowZtG/f/qLZTFf63hEREZHK8/vjFovFws0338yxY8d44YUX2Lp1K4MGDaJBgwYkJCTw5Zdfkp2dzVtvvXXRSbk77riDrVu38vDDD3PTTTfRvXt3zGYzW7du5auvvqJFixY8/vjjf5jDxsaG119/nb/97W9cf/313H777URERJCbm8ucOXNYu3Ytjz/+OG3btgV+XX/pq6++4tlnn+WGG27gyJEjfP7551dcDDVr1owWLVowY8YMBg4ceNHyEtdddx1ff/01d955J/fddx++vr5s2LCBjz/+mFtvvRVbW9sKjraIVBaVTyL1nNls5qOPPuLtt9/mww8/JCcnB29vb+68887yO4gAPPHEE3h6ejJr1iw++eQTAgIC+Oc//8moUaMueU0vLy8++eQT3n77bZ599lkKCgpo2rQp7777LrGxsZfN8e9//5vg4GBmz57Nxx9/jJeXF7fffjsPPPDAJeVWZQsLC+O2227js88+Y+bMmdx66628+uqrfPjhh8yaNYuMjAw8PT0ZNGgQEyZMKD9IuuWWW3BycuLTTz/lm2++wcfHh7vvvrt8SvvEiRN5+eWXefnllwEICQnhxRdfZMGCBWzbtq3Cef38/Pjmm2/48ssvWbRoER999BF2dnaEhYUxefLk8jvPAYSGhvLaa68xbdo07rnnHsLDwy/KdCWGDx/OihUrys9c/uZK3zsiIiJSeS533AK/llLx8fFMnz6dF154gfz8fHx9fenRowdjx44tX+fpN7a2trz//vt88803zJ8/nyVLllBUVERgYCAPPPAAt9566yVrL/1eixYt+P777/n888+ZOXMmmZmZODk50bx5cz755JOLTiB26dKFp556iq+++ooffviBVq1aMXXq1MseS/6R4cOHM3HixItmYsOva0RNnz6dyZMn88Ybb3DmzBn8/f15/PHH+dvf/nbFry8iVcdkreiqtyIiIiIiIiIiIn9Baz6JiIiIiIiIiEiVUfkkIiIiIiIiIiJVRuWTiIiIiIiIiIhUGZVPIiIiIiIiIiJSZVQ+iYiIiIiIiIhIlVH5JCIiIiIiIiIiVUblk4iIiIiIiIiIVBkbowPUBFarlbIya5W9vtlsqtLXl8vTuBtD424MjbsxNO7GqMpxN5tNmEymKnntukTHTnWTxt0YGndjaNyNoXE3Rk04dlL5BJSVWcnNPVclr21jY8bd3Zn8/POUlJRVyfeQS2ncjaFxN4bG3Rgad2NU9bh7eDhjsah8+is6dqp7NO7G0LgbQ+NuDI27MWrKsZMuuxMRERERERERkSqj8klERERERERERKqMyicREREREREREakyKp9ERERERERERKTKqHwSEREREREREZEqU6PKpw8//JDbbrvtT/fJy8vj8ccfJzo6mpiYGF588UUKCgqqKaGIiIiIiIiIiFwNG6MD/Gb69Om89dZbREVF/el+48ePp6CggC+++IL8/HyeffZZzp8/z2uvvVZNSUVERERERERE5EoZXj5lZmbyr3/9i82bNxMSEvKn++7cuZMtW7awZMkSwsPDAXjppZcYN24cjz32GN7e3tWQWERERERERERErpThl93t378fW1tbFixYQGRk5J/uu23bNho3blxePAHExMRgMpnYvn17VUcVEREREREREZGrZPjMp169etGrV68r2jczMxNfX9+LttnZ2dGwYUPS09OvKYeNTeX3cIVFpSxam0iLME9aBDaoku8hl2exmC/6t1QPjbsxNO7G0LgbQ+MuIiIiUvsYXj5djYKCAuzs7C7Zbm9vT2FhYYVf12w24e7ufC3RLmv7oUzm/HwMfj5Gk4AG3DKgBR0jvDCZTJX+veTy3NwcjY5QL2ncjaFxN4bG3RgadxEREZHao1aVTw4ODhQVFV2yvbCwECcnpwq/blmZlfz889cS7bJCvJwZ2S2MZZuTOJp6mhc/2USTgAbc0D2clqEelf795P9YLGbc3BzJzy+gtLTM6Dj1hsbdGBp3Y2jcjVHV4+7m5qhZVSIiIiKVrFaVTz4+PqxYseKibUVFRZw6dQovL69reu2Skqr54DCyWxjX927G9KUHWbEthaOpp5k4fQcRQQ0Z2S2MpgENq+T7yq9KS8uq7L+t/DGNuzE07sbQuBtD4y4iIiJSe9SqU3vR0dFkZGSQlJRUvm3Lli0AdOzY0ahYf6mBiz2j+zTltfvi6N0xABuLiUPJp3j16x28+e0uEtPzjY4oIiIiIiIiIlIlanT5VFpaSnZ2NhcuXAAgMjKSDh068Oijj7Jnzx42bdrE888/z4gRI/D29jY47V9r6GLPLX2b8eo9cXRv54fFbGJfQi4vf7mNd77fQ3LmGaMjioiIiIiIiIhUqhpdPqWnp9O1a1eWLFkCgMlkYurUqQQEBDB27FgmTJhAt27deOGFF4wNepU8GzgwdkAE/767E51b+2Aywa6jJ3nh861Mm7ePtJPnjI4oIiIitcCHH37Ibbfd9qf75OXl8fjjjxMdHU1MTAwvvvgiBQUF1ZRQREREpIat+TRx4sSLvg4ICODw4cMXbfP09OSdd96pzlhVxsvdiXFDWjI4Lpj56xLZcjCLrYey2HY4i9iWPgzvGoKXe8UXUhcREZG6a/r06bz11ltERUX96X7jx4+noKCAL774gvz8fJ599lnOnz/Pa6+9Vk1JRUREpL6rUeVTfeXr6cx9w1szJO4s89YlsuNINhv3Z7D5QCZd2/owtHMong0cjI4pIiIiNUBmZib/+te/2Lx5MyEhIX+6786dO9myZQtLliwhPDwcgJdeeolx48bx2GOP1YplC0RERKT2q9GX3dU3AV4uPHRdG/45Noo2YZ6UWa2s2Z3OMx9t5Ovlh8k7U2h0RBERETHY/v37sbW1ZcGCBURGRv7pvtu2baNx48blxRNATEwMJpOJ7du3V3VUEREREUAzn2qkUF83Hr0pkqOpp5m7NoGDSXms3HGCtXvS6dnen0Gxwbg52xkdU0RERAzQq1cvevXqdUX7ZmZm4uvre9E2Ozs7GjZsSHp6elXEExERkRrmzPkioyOofKrJmgQ04InR7TmYlMfctQkcTT3N8q0p/LwrjT5RAfSPCcLF0dbomCIiIlJDFRQUYGd36Qkre3t7CguvbUa1jU3VTKC3WMwX/Vuqh8bdGBp3Y2jcjaFxr34lpWV8/91yth49zU3X9aBj88aGZVH5VAu0CHYnIqgD+xNzmbMmgeMZZ1i8MYmVO1LpFx1Ev+hAHO31n1JEREQu5uDgQFHRpWc7CwsLcXKq+E1NzGYT7u7O1xLtL7m5OVbp68vladyNoXE3hsbdGBr36lFcUsobX29n42EzsQ65BDZ2qPL/d/8ZNRa1hMlkonWYJ61CPdh19CRz1ySSmn2W+esSWbEthYGxwfTuEIC9ncXoqCIiIlJD+Pj4sGLFiou2FRUVcerUKby8vCr8umVlVvLzz19rvMuyWMy4uTmSn19AaWlZlXwPuZTG3Rgad2No3I2hca8+FwoK+GjOLrYlnsPGYqLvmDH4Nm5AXt65Sv9ebm6OVzSbTeVTLWMymWjftDGRTRqx7VAW89clkp5znu9XH2P5lmQGxQbTo70/drYqoUREROq76OhoJk2aRFJSEsHBwQBs2bIFgI4dO17Ta5eUVO0Hh9LSsir/HnIpjbsxNO7G0LgbQ+Netc6fPUvyNxPpWniBwzb9uf+mKGJa+ZCXd87QcdfFlrWU2WQipoU3L9/ViXFDWuDV0JH888XMWnmUpz/cyModqZSoTRYREalXSktLyc7O5sKFCwBERkbSoUMHHn30Ufbs2cOmTZt4/vnnGTFiBN7e3ganFRERkcp0Lv80qTNfwb80FV/LaR4Z4EPrME+jYwEqn2o9s9lE59a+vHJ3J+4YGIGnmz2nzhbx9fIjPPPhJtbuTqO0TCWUiIhIfZCenk7Xrl1ZsmQJ8OuM6alTpxIQEMDYsWOZMGEC3bp144UXXjA2qIiIiFSqM7k5pM96GV9rBuetdlzoNp6w1m2MjlVOl93VETYWM90i/Yhr5cOa3Wks2nicnPwLfL70EIs3JTG8ayidWnhjNpuMjioiIiKVZOLEiRd9HRAQwOHDhy/a5unpyTvvvFOdsURERKQancrOInfuq3iTx1mrA2W9HiWwaXOjY11E5VMdY2tjpnfHAOLb+rJq5wmWbEoiK6+AjxceYPHGJEZ0DaVD88aYTSqhRERERERERGqznLQ0zi6cSGNTPvlWJyz9Hsc/NNzoWJdQ+VRH2dla6B8TRPd2fvy0PZVlm5NJO3mO9+ftI9DLhZHxYUQ28cSkEkpERERERESk1snMO8/n83Zyu7mIPFxxHPwEjQOCjI51WSqf6jgHOxsGx4XQs30Ay7cms3xrCilZZ3ln9h5Cfd0Y2S2UViEeKqFEREREREREaokTJ88xadZOTp91ZJbHMO4Y2g4PXz+jY/0hlU/1hJODDSPiw+gTFciyzcms2J5CYno+b36zm2YBDRjZLYzmQe5GxxQRERERERGRP3HiyEG+/2E3p8954d/Ymbtu7kIDF3ujY/0plU/1jIujLTf0CKdvdCBLNyWxcscJjqSe5rUZO2kZ4s7I+DDC/RsYHVNEREREREREfidp/24c173HrXalODiP4JbR8bg42hod6y+pfKqnGjjbMap3U/rHBLFo43HW7ErjwPE8DhzfTttwT0bGhxHs42p0TBEREREREREBEndtxXXzh9ibSkgz+3LrDd1xrgXFE6h8qvfcXe25rV9zBsYEsXDDcdbvzWDPsRz2HMuhY7PGDI8PJaCxi9ExRUREREREROqto1vX477jM+xMpaRaAggZ9QyOzs5Gx7piKp8EgEYNHblzUAsGxQazYH0im/Znsv1INjuOZBPT0pvhXUPx8XAyOqaIiIiIiIhIvXJkwyoa7/0KG1MZKTahhI9+EntHR6NjXRWVT3IRbw8n7h7aikFxIcxfl8i2Q1lsPpDJloOZdG7tw7AuoTRuWLve5CIiIiIiIiK10Z5Nmwna+18sJitJdk1pPuYJbO3sjI511VQ+yWX5N3LmgRGtSc48w7y1iew6epL1ezPYtD+T+La+DOkcgoebg9ExRUREREREROqktbvT+O/qM4x1CaRBAxdajH4UG5vascbT76l8kj8V5O3K+BvakpCWz9y1CexPzGX1rjTW7U2nRzt/BscF1/hbOoqIiIiIiIjUJj9tS2H6il8AMwnhN3NL/wgsZovRsSpM5ZNckTA/Nx6/uR1HUk4xd00Ch1NOsWJ7Kmt2p9GrYwADOwXh6lT7pv6JiIiIiIiI1CR7Fkyn9HgiJuLoExXEqN5NMJlMRse6Jiqf5Ko0C2zIk2PaczApj7lrEjiWls+yzcms2nmCvlGBDIgJxMmhdk4DFBERERERETFKWVkZe+d9QdjJNYQ6gEOTjsTXgeIJVD5JBZhMJlqGeNAi2J29CTnMWZNAcuZZFm04zsrtqfSPCaRPVCCO9np7iYiIiIiIiPyVsrIy9n7/EWGnNgGQ6N2bboMGGpyq8qgdkAozmUy0DW9EmzBPdhw5yby1CZw4eY65axP5cVsqA2OD6NUhAHvb2ntdqoiIiIiIiEhVKi0rZd+s9wg7uwOA4/6DaDv4JoNTVS6VT3LNTCYTHZs3pn3TRmw5lMn8dcfJzD3Pd6uO8cOWFAbHBdOjnR+2NiqhRERERERERH5TUlLCgZlvEVawjzIrpISOoE2/EUbHqnQqn6TSmM0mYlv6EB3hxcZ9mSxYn8jJ0xeYueIXlm1OZmiXELq28cXGYjY6qoiIiIiIiIihSkrLmD13Nf3P76cUE2nNbqJ1z7pzqd3/Uvkklc5iNtO1rS+xrbxZtyedhRuOk3emkP8uO8ySjUkM7xpKbCtvLGaVUCIiIiIiIlL/FJeUMm3efnYdM5Nt342+0UG07Nrb6FhVRuWTVBkbi5ke7f3p0saH1bvSWLwxiZOnL/Dp4oMs2pjE8K4hxLTwxlwHVu4XERERERERuRIXzp/ni3lb2ZVciq2NmW7DhtI8vJHRsaqUyiepcrY2FvpGBdIt0o+VO1JZuimZzNzzfLTgAIs3JjGiaxgdmjWqE7ePFBEREREREfkj58+cIfmbVxlQfJrjdoMYe31nWgS7Gx2ryql8kmpjb2thYKdgerTzZ8W2FJZtSeFE9jnem7uXYG9XRnYLpU2Yp0ooERERERERqXPOnDpFxnf/wd+aRYHZjvv6BRBSD4onUPkkBnC0t2Fol1B6dQzghy0p/LgthaTMM7z13R7C/dwY2S2MFsHuKqFERERERESkTsjPOUn27FfxIYdzVntKuj9CSERLo2NVG5VPYhhnB1uu6xZG36gAlm5OZuX2VI6l5TNp1i4ighoyIj6MZoENjY4pIiIiIiIiUmF5mRmcmj8RL05xxuoIfR4lILyZ0bGqlW43JoZzdbLjpp5NeO2+OPp0DMDGYuJQ8ikmTt/Bm9/sIiEt3+iIIiIiIiIiIlft5IlUzsz7N404xWmrM5YBT+JXz4on0MwnqUEauNgzpm8zBnQKYtGG46zdk86+xFz2JebSrkkjRsSHEuTtanRMERERERERkb+UkXueqfMOc5vJAhZXnIY8RSP/AKNjGULlk9Q4Hm4O3D4gggGxwSxcn8iGfRnsOnqSXUdPEhXhxfCuofg3cjY6poiIiIiIiMhlpWafZdKsXeSfMzHbYxj3D2+Ju7eP0bEMo/JJaiyvho7cNbglg2KDWbD+OFsOZLLtUBbbD2UR28qbYV1D8XZ3MjqmiIiIiIiISLmUQ/v56ceN5J8LI9DLhYduboebs53RsQyl8klqPF9PZ+4d1orBccHMX5vI9iPZbNyfyeYDWXRp48PQLiE0auBodEwRERERERGp547v3Ynzhve53r4YW+cGDB8dj4ujrdGxDKfySWqNgMYuPHhdG45n5DNvbSJ7juWwdk86G/Zl0K2dH0PiQnB3tTc6poiIiIiIiNRDCds347btY+xNJaSZ/Rh54wCcVDwBKp+kFgrxcWPCjZEcPXGauWsSOJiUx6odJ1i7O51eHfwZFBuMRwMHo2OKiIiIiIhIPfHL5rV47vocW1MZqZYgQsc8jYOjlon5jconqbWa+DfgidHtOZSUx9y1CfySeprlW1NYvesE/aKDGDOwhdERRUREREREpI47tPYnvA9Mx8ZURrJtOE1HP4GdgyZE/C+VT1LrRQS783RQB/Yfz2XumgQS08+waMNxVu5IpV90IH06BuLkoLe6iIiIiIiIVK4dm3cRfuBrzCYrx+2bEzHmcWxt6/fi4pejT+RSJ5hMJlqHetIqxIPdR3OYty6B5MyzzFubyI9bUxjQKYjeHQNwsNNbXkRERERERK7d6l0n+GpVDoMdW9HEE1qNehSLjcXoWDWSPolLnWIymWjXtBEdIhpzMOU0Xy05SNrJc8z+OYHlW1MYFBtMz/b+2NnqLwQRERERERGpmOVbjjNrZQJg4lzEEFr1bYrFrM+Zf0Tlk9RJZpOJrpH+tAhowPo96cxfn0hWXgHfrDzKsi3JDIkLoVukH7Y2ZqOjioiIiIiISC2ye95/8TxxAFt60btTGDf2CMdkMhkdq0ZT+SR1mtlsIq61DzEtvdiwN4MF6xPJyS9k+o9HWLY5iaFdQunc2gcbi0ooERERERER+WNlZWXsnfMZYbnrwBbubFNAJxVPV0Tlk9QLFrOZ+Eg/Ylv5sHZPGos2HCcnv5Avlh5iycYkhncNpVNLb8xm/aUhIiIiIiIiFysrK2Pvt9MIy98KQKJvX2IHDzc4Ve2h8knqFVsbM706BNC1jS+rd55g8aYksk4V8PGiAyzaeJwR8WF0bN4Ys5prERERERERAUpLS9k3613Czu0C4HjQUNoOuN7YULWMyiepl+xsLfSLCaJbOz9+2p7Kss3JpOecZ9q8fQQ0dmFkt1DaNWmk6ZMiIiIiIiL1WElJMQdmTiGs4ABlVhOp4dfRps9Qo2PVOiqfpF5zsLNhcFwIPdsH8OO2FJZvTSY1+yzvzt5LqK8rI+PDaBXqoRJKRERERESknikpLWP63E30P3eUUpOJjIhRtOre3+hYtZLKJxHAycGG4V1D6d0xgB+2JLNiWyqJ6Wd489vdNAlowHXxYUQEuxsdU0RERERERKpBUXEp783dx96EYpLt+nBTnBcRcT2MjlVrqXwS+R8ujrZc3z2cvlGBLNmUxKqdJziaeprXZ+6kRbA7I+PDaBLQwOiYIiIiIiIiUkUKzp1l5px17D1hh52NmZEje9M81NPoWLWayieRy3BztmNU76b0jwli8cbj/LwrjYNJeRxM2k6bME9GdgslxMfN6JgiIiIiIiJSic7lnyb124kMLT1JukN/briuN82DdBXMtVL5JPIn3F3tubVfcwZ0CmLRhuOs25PB3oQc9ibk0KFZY0Z0DSXAy8XomCIiIiIiInKNzuTlkvH9q/hZsynAjtv6NidIxVOlUPkkcgUaNXDkjoEtGBgbzIJ1x9m0P4MdR7LZeSSb6BZeDO8aiq+ns9ExRUREREREpAJOZ2eRM3ciPuRy1upAWc9HCGrWwuhYdYbKJ5Gr4O3uxN1DWzI4Lpj56xLZeiiLLQez2Hooi86tfBjaNRSvho5GxxQREREREZErlJueRv6C12hsOk2+1QlL38fxDws3OladovJJpAL8Gjlz/4jWDM48w7y1iew6epL1+zLYdCCTrm19Gdo5BA83B6NjioiIiIiIyJ/IOnGCwkWv4mk6yymrCw6DnqBxYLDRseoclU8i1yDI25XxN7QlIS2feWsT2JeYy8+70li/N53u7fwZHBdMQxd7o2OKiIiIiIjI76TnnOPNuUe5ATdKbS24Dn0KTz8/o2PVSSqfRCpBmJ8bj93cjiMpp5i3NoFDyaf4aXsqa3en0atDAANig3BzsjM6poiIiIiIiADJmWeY/M0uzpwvZZnnIB4Z0ZyGjRsbHavOUvkkUomaBTbkyTEdOHg8lzlrEzh2Ip9lW5JZtesEfaMC6B8ThLODrdExRURERERE6q3kA3vZuXIFZ863JdjbjcdujsRVkwWqlMonkSrQIsSDfwS7szchl7lrEkjKPMOiDUn8tP0E/WMC6RsViKO9fv1ERERERESqU+Lu7bhs+oBedsXg7U7f0bfgpAkCVU6ffkWqiMlkom24J23CPNj5y0nmrk3gRPY55q1NZMW2VAZ2CqJXhwDs7SxGRxUREREREanzjm3bSMPtn2BnKuWEJYB+N92Ao4qnaqHySaSKmUwmOjRrTLumjdh6MIv56xLJyD3Pd6uP8cPWFAbHBtOjvR+2NiqhREREREREqsLhjT/jtedLbExlpNiEED76KewdHY2OVW+ofBKpJmaTiU4tvYmKaMym/ZnMX5fIydMXmPnTLyzbksyQziHEt/XFxmI2OqqIiIiIiEidcXDNcnwPzsRispJk14Rmo5/Azl53Ja9OKp9EqpnFbKZLG186tfRm/d50Fqw/Tt6ZQr764TBLNyUxrEsoca29sZhVQomIiIiIiFyLzVsP0uzgLCwmK8cdWtBizGPY2OhSu+qm8knEIDYWM93b+dO5tQ8/70pj8cYkTp6+wGdLDrJ4UxLDu4QQ08Ibs9lkdFQREREREZFaZ+WOVL7+KZ1ouzi6eJ+l1c3jsWi5E0OofBIxmK2NhT5RgcRH+rFqxwmWbEoiM/c8Hy08wOKNSYyID6VDs8aYTCqhRERERERErsTyDb8wa00KAA3adKdNn6b6TGUglU8iNYS9rYUBnYLo3s6PFdtT+WFzMidOnuO9ufsI8nZhZHwYbcM99RemiIiIiIjIHygrK2Pv/P8SlrEDV1N/usVGcF23MH2OMpjKJ5EaxtHehqGdQ+jdwZ8ftqSwfFsKyZlnefv7PYT5uTGyWxgtg931l6eIiIiIiMj/KCsrY+/sjwnL2wgWuK3VBaK6hxsdS1D5JFJjOTnYMrJbGH2iAli2OZmftqeSkJbP5Fm7aB7YkJHdwmgW2NDomCIiIiIiIoYrLStl3zfvE3ZmOwCJ/gOJGny9wankN7qdlkgN5+pkx409m/DafXH0iQrAxmLicMopJk7fweRZOzmWdtroiCIiIiIiIoYpLSll/4y3CDuznTIrJIUMp+3gm42OJf9DM59EaokGLvaM6dOMATFBLNqYxNrdaew/nsf+49uJDPdkRHwYwT6uRscUERERERGpNsXFRRya8SahhYcos5o40ewmWvccaHQs+R2VTyK1jIebA7f3b87ATkEsXH+c9fvS2X0sh93Hcohq3pjh8WH4N3I2OqaIiIiIiEiVKi4p4/N5O+hz/gSlZhMZLW+hZXwfo2PJZah8EqmlGjd05G+DWzAoLpgF6xLZfCCTbYez2X44m06tvBneJRRvDyejY4qIiIiIiFS6wuJSps7Zy/7E8xy16c+4eHciOnUxOpb8AZVPIrWcj4cT9wxrxaC4YOavS2T74Ww27c9ky4EsOrfxYVjnEBo1dDQ6poiIiIiISKU4f/Ys82YvZ396Q+xszdxxfWeahXgYHUv+hMonkToioLELD45sQ1LGGeauTWDPsRzW7Uln474MukX6MaRzCO6u9kbHFBERERERqbCzp0+R9u2rDC7L4rRTD/pcN5ymAQ2NjiV/QeWTSB0T7OPKhBsjOXbiNHPXJnDgeB6rdp5g7Z50erb3Z1BcMA2c7YyOKSIiIiIiclXyc3LImv0qvpzkPPYM6duRQBVPtYLKJ5E6Kty/AX8f1Z7DyXnMXZPAkdTT/LgthZ93n6B3xwAGdgrGxdHW6JgiIiIiIiJ/KS8zk7z5E/EmjzNWR+g1gcCmzY2OJVdI5ZNIHdc8yJ2nbunAgeN5zFmTQGJ6Pks3JbNqxwn6RQfSLzoIJwf9VSAiIiIiIjXTybRUzi18ncamfE5bnbHp/zg+IWFGx5KroE+cIvWAyWSiVagHLUPc2X0sh3lrEkjOOsuC9cf5aXsq/WOC6BMVgIOd/koQEREREZGaIzM9k+KFr+JhOkee1RWnIU/RyD/A6FhylfRJU6QeMZlMtGvSiLbhnuw4nM28dYmknTzHnDUJLN+awqDYYHp18MfO1mJ0VBERERERqedOZJ9l0vdH6GMNoKVDJg1HPI27t4/RsaQCVD6J1ENmk4moCC86NGvM5oOZzF+XSFZeAd+uOsoPW5MZEhdCt0g/bG3MRkcVEREREZF6KCnjDJO/2cXZgmI2N+pJ1+ua08DD3ehYUkEqn0TqMbPZRFwrH2JaeLFhXwYL1h0nJ/8C0388wtLNSQzrEkrn1j7YWFRCiYiIiIhI9Ujat4ukNQsoKIgj1Lchj97UTjdLquVUPokIFrOZ+LZ+xLXyYe3uNBZuOE5ufiFfLD3E4o3HGdYllLhWPpjNJqOjioiIiIhIHZawcytuWz6kvU0JRd6N6DLqHhztVV3UdvovKCLlbCxmenYIoEsbX1bvSmPJxuNkn7rAp4sPsmRTEsO7hhIV4YXZpBJKREREREQq19Et6/HY+Rm2plJSLYF0vekOHFQ81QmGX0tTVlbGO++8Q3x8PO3atePuu+8mJSXlD/fPycnh8ccfJzY2lk6dOvHoo4+SmZlZjYlF6j47Wwv9ogN57b7O3NAjHGcHG9JzzvPB/P288NlWdh7Jxmq1Gh1TRERERETqiMPrV+K581NsTaUk24YRfsuzODg7GR1LKonh5dP777/PjBkzePnll5k1axZlZWWMGzeOoqKiy+4/YcIE0tLS+Pzzz/n8889JS0vjwQcfrObUIvWDvZ2FQbHBvH5/Z0Z0DcXR3kJq9lnenbOXl7/cxt6EHJVQIiIiIiJyTQ6uXob3vq+wMZVx3L4ZzW59GjsHB6NjSSUytHwqKiris88+Y/z48fTo0YOIiAimTJlCRkYGy5cvv2T//Px8tmzZwt13302LFi1o2bIl99xzD3v37uXUqVPV/wOI1BOO9jYM6xrKa/d1ZnBcMPa2Fo5nnGHKt7t59esdHEzKMzqiiIiIiIjUQuu3H8Xz0GwsJiuJjq1occsT2NraGR1LKpmh5dOhQ4c4d+4ccXFx5dvc3Nxo2bIlW7duvWR/BwcHnJ2dmTdvHmfPnuXs2bPMnz+f0NBQ3NzcqjO6SL3k4mjL9d3Dee3+OPrHBGJrY+boidO8MXMnr8/YwZGUU0ZHFBERERGRWuLHbSl8+mMyH5/tyVHXaFrd8hg2NrqrXV1k6MpdGRkZAPj6+l603cvLq/yx/2VnZ8fEiRN5/vnniYqKwmQy4eXlxddff43ZfG09mo1N1fRwlv9/i3qLblVfrTTuVcvDzYFb+jVnUFwIC9cnsmrHCQ4ln+KVL7fRISKZkfGhBHu7Gh2z3tD73Rgad2No3H9dL3Pq1Kl89913nDlzhujoaJ5//nkCAwMvu39OTg7/+c9/WL9+PVarlc6dO/P000/j7e1dzclFRET+z/I1e5m1IRuAJh2iadezCSbd2KjOMrR8KigoAH4tlf6Xvb09p0+fvmR/q9XKwYMHad++PePGjaO0tJQpU6bwwAMPMHPmTFxcXCqUw2w24e7uXKHnXik3N8cqfX25PI171XJ3d+aRIA9GD2jBtyuO8OOWZHYcymLHoSxiW/swpn8EoX4NjI5Zb+j9bgyNuzHq87j/tl7mxIkT8fHx4Y033mDcuHEsXLjwkmMq+HW9zJKSEj7//HOsVisvvvgiDz74IN9//70B6UVEpL4rKytj9+xPaZu9mZ8t/YmObc/wrqEqnuo4Q8snh/+/gFhRUVH5nwEKCwtxdLz0oHLp0qV8/fXXrFq1qrxo+uCDD+jZsyfff/89d9xxR4VylJVZyc8/X6Hn/hWLxYybmyP5+QWUlpZVyfeQS2ncq5ctcEufpvSPDmTRxiRWbU9h074MNu3LoFNLb0Z2C8OvUdUWvPWZ3u/G0Lgbo6rH3c3NsUbPqvptvcy///3v9OjRA4ApU6YQHx/P8uXLGTJkyEX7/7Ze5rRp02jRogUA99xzDw888ACnTp2iYcOG1fwTiIhIfVZWVsbOWdMIO7UZzHBDi1Lax4cZHUuqgaHl02+X22VlZREUFFS+PSsri+bNm1+y/7Zt2wgNDb1ohlODBg0IDQ0lKSnpmrKUlFTtB4fS0rIq/x5yKY179WrUwIFHR3egX1QAc34+xpaDWWw+kMmWg5nEtfJhWJcQvNx1u9Sqove7MTTuxqiv4/5X62X+vnz63/UyY2JiALRepoiIGKK0rJQ1708k7PR2AI4HDqH9wBsMTiXVxdDyKSIiAhcXFzZv3lxePuXn53PgwAFuvfXWS/b38fFh8eLFFBYWYm9vD8D58+dJTU1l2LBh1ZpdRP6YXyNn7hvemsFxZ5m3NoGdv5xkw74MNh/IpEsbX4Z2DsGzgW6dKiJytbReplQVjbsxNO7G0LhXv5KSYvb8901Czu+nzAonmlxP+/7DjY5VL9SU97uh5ZOdnR233norkyZNwsPDA39/f9544w18fHzo168fpaWl5Obm4urqioODAyNGjODTTz9lwoQJPPLIIwC89dZb2Nvbc9111xn5o4jIZQR6ufDw9W1JTM9n7toE9iXksmZ3Ghv2pdM90p/BnYNp6GJvdEwRkVpD62VKVdO4G0PjbgyNe/UoKixk43v/JqTgMKVWE6fa3Ub3ISqeqpvR73dDyyeA8ePHU1JSwnPPPceFCxeIjo7m008/xdbWltTUVHr37s2rr77Kddddh5eXFzNmzOCNN95g7NixmM1moqKimDFjBq6uurOWSE0V6uvGYze145fUU8xdk8Ch5FP8tCOVNXvS6NXBn4Gxwbg5XbpIroiIXEzrZUpV0bgbQ+NuDI179SkqKeX973bQJf8UJTZmzsbcRfPY7uTlnTM6Wr1RU9bLNLx8slgsPPHEEzzxxBOXPBYQEMDhw4cv2hYeHs4HH3xQXfFEpBI1DWjIk2M6cPB4LnPXJnL0xGl+2JLC6p1p9IkKYECnIJwdbI2OKSJSY2m9TKlqGndjaNyNoXGvWoVFpbwzew8Hk05zxKYP4/u4E9e3J3l55zTuBjD6/a6LXEWk2rUI8eCZWzvw6E2RBPu4UlhcyuKNSTw5bSML1iVSUFhidEQRkRrpf9fL/M1v62VGR0dfsr+Pjw9JSUkUFhaWb/ttvcyQkJDqiCwiIvXQufx8ls6YzsGkPOztLDx4UxQRUTFGxxIDGT7zSUTqJ5PJRJswT1qHerDrl5PMXZtAavY55q1L5MdtKQyMDaZ3hwDs7SxGRxURqTG0XqaIiNR0Z06dIuO7/9DbmsUF5xiir7uFcP8GRscSg2nmk4gYymQy0b5ZY174Wwz3DW+Fr6cT5y6U8P3qYzz1wQaWb02huKTU6JgiIjXG+PHjueGGG3juuecYPXo0FoulfL3M9PR0unbtypIlSwDK18u0Wq2MHTuWO++8E1tbW62XKSIiVeL0yZNkffsSPtYszlkd6Nqvh4onAcBktVqtRocwWmlpGbm5VbPgmY2NGXd3Z13XWs007saojHEvK7Oy6UAG89clkn3qAgDurvYMiQsmPtIPG90S9xJ6vxtD426Mqh53Dw9nw29FXBvo2Knu0bgbQ+NuDI171cjNSCd/wWt4cop8qxPmvo/hG9ak/HGNuzFqyrGTLrsTkRrFbDbRubUvMS282bAvgwXrE8nNL+Sr5UdYujmZoV1C6NzaB4tZHw5FRERERGqC7NQUCha/jqfpDKesLtgP+jtegSFGx5IaROWTiNRINhYz3SL9iGvlw5rdaSzacJyTpy/w+ZJDLNmYxLCuoXRq4Y3ZbDI6qoiIiIhIvZWemUPp4om4m86Ra3XDeeiTNPILMDqW1DCaOiAiNZqtjZneHQOYeF8cN/VsgoujLZl5BXy88ADPf7aFbYeyKNPVwyIiIiIi1S4l6yyvfXOA5edbcRJ3Glz3nIonuSzNfBKRWsHe1sKATkF0b+fHT9tTWbY5mbST53h/3j6CvFwY0S2MyHBPTCbNhBIRERERqWqJaad589vdnLtQQrJXFJ43jsXN1dnoWFJDqXwSkVrF0d6GIZ1D6NXBn+VbU1i+NYXkrLO88/0ewvzcGBkfRssQd5VQIiIiIiJVJHHPDvLXf4O1sAfhfo159KZInBxsjY4lNZjKJxGplZwcbBkRH0afqECWbk7ip+2pJKTlM/mbXTQLaMDIbmE0D3I3OqaIiIiISJ1ydPsm3Ld9QiNLCaO9DtHh5r442qtakD+nNZ9EpFZzcbTlxh5NeO2+zvSNCsTGYuZI6mlem7GTSbN2cuzEaaMjioiIiIjUCUc2rcFj20fYmUpIsQmm46h7VTzJFdG7RETqhAbOdozu05T+MYEs3pjEmt1pHDiex4Hj22kb7snI+DCCfVyNjikiIiIiUisdWrsCnwPTsZisJNk1odnoJ7Cztzc6ltQSKp9EpE7xcHPgtv7NGdgpiAUbjrNhbwZ7juWw51gOHZs3ZkTXUPwbuxgdU0RERESk1ti/cjEBv3yP2WTluEMLIkY/iq2tndGxpBZR+SQidVKjho78bVALBscGM399Ipv3Z7L9cDY7DmfTqaU3w7qG4uPhZHRMEREREZEa7edtiQQfXoLZYiXRqS2tRj2CxcZidCypZVQ+iUid5u3hxD1DW/1aQq1LZNvhbDYdyGTLwSw6t/ZhaJcQGjd0NDqmiIiIiEiN88OWZL5ZmUhjc19uDMmm/Q1/w2JW8SRXT+WTiNQL/o1deGBkG5IyzjBvbQK7j+Wwbm86G/dnEB/px5C4YDzcHIyOKSIiIiJiuLKyMlau3s43W84AEB3Tho7dwzCZTAYnk9pK5ZOI1CvBPq48cmMkx9JOM29NAvuP57F65wnW7UmnR3s/BscG08BFCyeKiIiISP1UVlbG3tmf0DF3EzttexIR25UhnUNUPMk1UfkkIvVSuF8DHh/VniMpp5izJoEjKadYsS2VNbvS6N0xgIGxwbg42hodU0RERESk2pSWlbLv22mE5W8DE/SPsKNtl1CjY0kdoPJJROq1ZoENeWpMew4k5TF3TQIJafks3ZzMqp0n6BsVSP+YQJwcVEKJiIiISN1WWlLKvm/eJuzcHgCSgofRtv91BqeSukLlk4jUeyaTiVYhHrQMdmfPsRzmrk0gOfMsCzcc56ftqfTvFESfjgE42uuvTBERERGpe4qLizg0cwphFw5SZjWR2vQGWvcabHQsqUP0SUpE5P8zmUxENmlEm3BPdh7JZt7aRE6cPMfcNQn8uDWFQbHB9Ozgj72t7vAhIiIiInVDUWERR2a+TkjRUUqtJjJa3kKr+D5Gx5I6RuWTiMjvmE0mOjb3on3Txmw5mMn8dYlk5hXw7aqj/LAlmcFxwXRv54+tjdnoqCIiIiIiFVZYXMp78/bT9owVfzsz2ZFjiYjtbnQsqYNUPomI/AGz2URsKx+iW3ixcV8mC9YncvL0BWas+IVlW5IZ2jmELm18sbGohBIRERGR2qWgsIR3vt/D4ZRT/GLbhaDuw2nWtq3RsaSOUvkkIvIXLGYzXdv6EtvKm7V70lm04Ti5+YV8uewwSzYlMaxLKLGtvLGYVUKJiIiISM13Lv80G76fzpGsZjjY2TLhxkiaBTY0OpbUYSqfRESukI3FTM/2/nRt48PqnWks3pRE9qkLfLr4IIs3JjG8ayjRLbwwm0xGRxURERERuaz83Byyvn+VWE5S5nqWZtfdR6ivm9GxpI5T+SQicpVsbSz0jQ6kW6QfK3eksnRzMhm55/lwwX4WbzzOiPgw2jdthEkllIiIiIjUIKeys8ib+yre5HHW6kDrfsPxV/Ek1UDlk4hIBdnbWRgYG0yP9v78uC2FH7akkJp9jqlz9hLs48rI+DDahHmohBIRERERw+WkpXF24UQamfLJtzpj6f84/iFhRseSekLlk4jINXK0t2FYl1B6dwzghy3J/LgtlaSMM7z13W7C/d24Lj6MFiEeRscUERERkXoqK+U4hUsm4WE6S57VFafBT9IoINDoWFKPqHwSEakkzg62XNctnD5RgSzblMxPO1I5diKfN2btIiKoISPiw7SQo4iIiIhUqxNZ+RQveRNP01lyaIDb8Kfx8PE1OpbUM7o1k4hIJXNzsuOmXk147b44encMwMZi4lDyKSZO38Gb3+wiMT3f6IgiIiIiUg8kZZzhtZm7+fZsNBk0xv26f6p4EkNo5pOISBVp6GLPLX2bMSAmiEUbj7NuTzr7EnPZl5hLuyaNGBEfSpC3q9ExRURERKQOOpaSy5Tv93G+sIQLPhH43HQTrk72RseSekrlk4hIFfNs4MDYAREMjA1m4bpENuzPYNfRk+w6epLoCC+Gdw3Fr5Gz0TFFREREpI5I3LUV06avcC7uhV9AIBNuiMTJQR//xTh694mIVBOvho7cNaQlg+KCmb8ukS0Hs9h6KItth7OIbenDsK4heLs7GR1TRERERGqxo1vX477jM+zMpdzY6BBtbhqKvZ3F6FhSz6l8EhGpZr6eztw3vDVD4s4yb10iO45ks3F/BpsPZNK1rQ9DOofQqIGj0TFFREREpJY5vGEVXnu/wsZURrJtKG1HT8BOxZPUACqfREQMEuDlwkPXtSExPZ95axPZm5DDmt3prN+bQfd2fgyOC8HdVdfli4iIiMhfO/DzD/gdmoXFZCXJrhnNx/wdWzs7o2OJACqfREQMF+rrxqM3RXI09TRz1yZwMCmPlTtOsHZPOj3b+zMoNhg3Zx04iIiIiMjl7V+xkIBjszGbINGxFS1HT8DGxtboWCLlVD6JiNQQTQIa8MTo9hxMymPu2gSOpp5m+dYUft6VRp+oAPrHBOHiqIMIEREREfk/P21LwuvIz5htINGlHa1GPYzFrEvtpGZR+SQiUsO0CHYnIqgD+xNzmbMmgeMZZ1i8MYmVO1LpFx1E36hA3a1ERERERFiyKYnvVx/DydSb25qcJHrkLZjNZqNjiVxCn15ERGogk8lE6zBPWoV6sOvoSeauSSQ1+yzz1yWyYlsKAzoF0adjoO5cIiIiIlIPlZWV8fOPa/h+ZxkAveKaExM/AJPJZHAykctT+SQiUoOZTCbaN21MZJNGbDuUxfx1iaTnnGf2zwn8uDWFQbHB9IkONDqmiIiIiFSTsrIy9n7/IVGnNnPcPgav2EEMjgsxOpbIn1L5JCJSC5hNJmJaeBPV3IvNBzKZvy6RrFMFzFp5lB+2pnBz3+bENG9kdEwRERERqUKlZaXsmzWVsLM7AYhq3og2Kp6kFlD5JCJSi5jNJuJa+xDdwosN+zJYuD6RnPxCPpizh+8bODC0cwid2/hg0bX+IiIiInVKSUkxB2a+TVjBPsqskBo2kjZ9hxsdS+SKqHwSEamFbCxmukX6EdfKh/X70lm04TgnT1/g86WHWLwpieFdQunU0huzWdf9i4iIiNR2xcVFHJoxmdDCw5RaTaQ3v5lWPQYYHUvkiunUuIhILWZrY6ZPVCAf/aMvo/s0xdXJlqy8Aj5edIB/frqZbYeyKLNajY4pIiIiIhVUVFzMka8nElJ4mBKrmczWt9FCxZPUMpr5JCJSB9jbWhgYG0x8W19+2p7Kss3JpOec5/15+wj0cmFkfBiRTTx1BxQRERGRWqSwqJR35+zD73QDfB0t5LS7k+aduhodS+SqqXwSEalDHOxsGBwXQs/2ASzfmszyrSmkZJ3lndl7CPV1Y2S3UFqFeKiEEhEREanhCgpLeOu73fySeppjtu2I7jaYpi2aGB1LpEJUPomI1EFODjaMiA+jT1QgyzYns2J7Conp+bz5zW6aBjTgum5hNA9yNzqmiIiIiFzGmVOn2PP9RySfbIujvROP3hRJE/8GRscSqTCVTyIidZiLoy039Ainb3QgSzclsXLHCX5JPc1rM3bSItidkd3CdCAjIiIiUoPk55wke/artCWHOxqcw2fk3wn2cTU6lsg1UfkkIlIPNHC2Y1TvpvSPCWLRxuOs2ZXGwaQ8Dn61nbbhnoyMD9NBjYiIiIjB8jIzOD1/Il6c4ozVkaB+t+CrYzSpA1Q+iYjUI+6u9tzWrzkDOwWxcP1x1u/NYM+xHPYcy6Fjs8YMjw8loLGL0TFFRERE6p2TJ1I5t+g1PE1nOG11xm7AE3gFhxgdS6RSqHwSEamHGjVw5M5BLRgUF8yCdYls2p/J9iPZ7DiSTUxLb4Z3DcXHw8nomCIiIiL1QmZSIsXLJuFhOkeu1Q3noU/SyC/A6FgilUblk4hIPebt7sTdQ1sxKC6E+esS2XYoi80HMtlyMJPOrX0Y1iWUxg0djY4pIiIiUmelZp7h/NJ38TWf4yTuNBzxNO7e3kbHEqlUKp9ERAT/Rs48MKI1yZlnmLc2kV1HT7J+bwab9mcS39aXIZ1D8HBzMDqmiIiISJ3y692Id+FW3IXRDXcSdP2juHl4Gh1LpNKpfBIRkXJB3q6Mv6EtCWn5zF2bwP7EXFbvSmPd3nR6tPNncFwwDVzsjY4pIiIiUusdPZ7JlLmHKCgsxdsvmNCbhuHsYGt0LJEqofJJREQuEebnxuM3t+NIyinmrkngcMopVmxPZc3uNHp1DGBgpyBcneyMjikiIiJSKx3bvhnnrZ/hX9odc2AEj9zQFkd7fTyXukvvbhER+UPNAhvy5Jj2HEzKY+6aBI6l5bNsczKrdp6gb1QgA2ICcdIZOhEREZErdmTTWhrt/hxbcxlDPBJoftPN2NtajI4lUqVUPomIyJ8ymUy0DPGgRbA7exNymLMmgeTMsyzacJyftqcyICaQPlGBOlsnIiIi8hcOrf0J7wPTsTGVkWwbTsSYJ7BT8ST1gD4piIjIFTGZTLQNb0SbME92HDnJvHUJnMg+x9y1ify4LZWBsUH06hCgM3ciIiIil3Fg1RL8j3yH2WTluH0EEWMew9ZWyxhI/aDySURErorJZKJj88a0b9aIrQezmLcukczc83y36hg/bElhcFwwPdr5YWujEkpEREQEYN/yuQQmzsdsgkSnNrQaNQGLjpWkHlH5JCIiFWI2mejU0puoiMZs2p/J/HWJnDx9gZkrfmHZ5mSGdgmhaxtfbCxmo6OKiIiIGGb5lmTsD+8i2B4SXDvQ+uYHsZhVPEn9ovJJRESuicVspksbXzq19GbdnnQWbjhO3plC/rvsMEs2JjGsSyhxrb2xmFVCiYiISP2ycMNx5q5JwEJXbIPaEjt0JGYdE0k9pPJJREQqhY3FTI/2/nRp48PqXWks3pjEydMX+GzJQRZvSmJ41xBiWnhjNpmMjioiIiJSpcrKyli/ZAnz9jkCJoZ2bUJclxBMOg6Sekrlk4iIVCpbGwt9owLpFunHyh2pLN2UTGbueT5acIDFG5MY0TWMDs0a6eBLRERE6qSysjL2fjuNdvlbuc6pOZZOtzCgU5DRsUQMpfJJRESqhL2thYGdgunRzp8V21JYtiWFE9nneG/uXoK9XRnZLZQ2YZ4qoURERKTOKC0pZf837xB2bjcAQc2a0UbFk4jKJxERqVqO9jYM7RJKr44B/LAlhR+3pZCUeYa3vttDuJ8bI7qF0TLYXSWUiIiI1GolJcUcnPEmoRcOUmY1kdrketr0HmJ0LJEaQeWTiIhUC2cHW67rFkbfqACWbk5m5fZUjqXlM3nWLpoHNmRktzCaBTY0OqZIlTl27Bjr168nKyuL2267jZSUFCIiInBxcTE6moiIXKPioiIOz3iDkKJfKLWaSG8xmlbd+hkdS6TGUPkkIiLVytXJjpt6NqF/dCCLNyaxetcJDqecYuL0HbQK9WBkfBhhfm5GxxSpNGVlZTz//PPMnj0bq9WKyWRi4MCBvP/++yQnJ/P111/j4+NjdEwREamgwqISjkx/jZDiY5RYzWS3HUuLuO5GxxKpUXSPRxERMUQDF3vG9G3GxHvj6NHOD4vZxP7EXF757zbe+X4PyZlnjI4oUinef/99Fi5cyCuvvML69euxWq0APPHEE5SVlTFlyhSDE4qISEVdKCrh7e/3sDI3gAtWW3I73k0zFU8il9DMJxERMZSHmwO3D4hgQGwwC9cnsmFfBruOnmTX0ZNERXgxvGso/o2cjY4pUmGzZ89m/PjxXH/99ZSWlpZvb9GiBePHj2fSpEkGphMRkYo6f6GYKd/t5tiJfBzswjjVpx9Nw/2NjiVSI6l8EhGRGsGroSN3DW7JoNhgFqw/zpYDmWw7lMX2Q1nEtvJmWNdQvN2djI4pctVOnjxJixYtLvuYt7c3+fn51ZxIRESu1ZncHI7OnkpuXnuc7Bvy2M3ttGyAyJ/QZXciIlKj+Ho6c++wVrx4VwwdmzXGCmzcn8mzH23m8yUHOXm6wOiIIlclODiYn3/++bKPbdmyheDg4GpOJCIi1+JUdhbZ379CE2sif3Nbx5OjVTyJ/BXNfBIRkRopoLELD17XhqSMM8xdm8CeYzms3ZPOhn0ZdGvnx5C4ENxd7Y2OKfKXxo4dy/PPP09xcTE9e/bEZDKRlJTE5s2b+eyzz3j66aeNjigiIlcoNz2N/AWv0dh0mnyrE5797sXHR8WTyF9R+SQiIjVasI8rE26M5OiJ08xbm8CB43ms2nGCtbvT6dXBn0Gxwbg52xkdU+QP3XjjjeTm5jJt2jRmzpyJ1Wrlsccew9bWlnHjxjF69GijI4qIyBXITkniwpI38DSd5ZTVBYdBT9A4ULNXRa6EyicREakVmvg34O+j2nMoKY+5axP4JfU0y7emsHrXCfp0DGRApyBcHG2NjilyWffeey+33HILO3fu5NSpU7i5uREZGUnDhg2NjiYiIlcgI/EYpcsn09B0nhxrA9yGPYWHr5/RsURqDa35JCIitUpEsDtP39KBx26OJNTXlaLiMpZsSuKpDzYwb20C5y+UGB1R5CLPPPMMKSkpuLi4EB8fz9ChQ+nevTsNGzYkISGB++67z+iIIiLyJ5Izz5C+7FPcTOfJxh33655V8SRylTTzSUREah2TyUTrUE9ahXiw+2gOc9cmkJJ1lgXrj/PT9lQGdAqid8cAHOz0vzkxRlpaWvmf582bR58+fbBYLJfst2bNGjZs2FCd0URE5CocSzvNlG92Yynqwq0eu4i44X5c3T2MjiVS6+ioXEREai2TyUS7po1o28STHYezmbs2gfSc88z+OYHlW1MYFBtMz/b+2Nle+qFfpCq9+OKLrFmzpvzrhx566LL7Wa1WunTpUl2xRETkKvzySzJvLkyksKiUcH9vWt34JE4OusRfpCJUPomISK1nNpmIivCiQ7PGbD6Yyfx1iWTlFfDNyqMs25LMkLgQukX6YWujq82lerz00kts2LABq9XKP/7xD+6//36CgoIu2sdsNuPm5kanTp0MSikiIn/k6LYNuG//jEhiyA+KYvwNbTWjWuQa6LdHRETqDLPZRFwrH2JaeLFhbwYL1ieSk1/I9B+PsGxzEkO7hNK5tQ82FpVQUrW8vb0ZOXIk8OsMve7du+Phocs0RERqg8MbV+O157/YmMro6p5B0xvaYq/iSeSa6DdIRETqHIvZTHykH7GtfFi7J41FG46Tk1/IF0sPsWRjEsO6hhDb0gez2WR0VKkHRo4cSWFhIXv27KGoqAir1QpAWVkZBQUFbNu2jb///e8GpxQREYCDa5bje3AmFpOVJLumNB/zBLYqnkSumX6LRESkzrK1MdOrQwBd2/iyeucJlmxKIutUAZ8sOsjijUkM7xpKVIQXZpNKKKk6mzdv5pFHHuH06dOXfdzZ2Vnlk4hIDbB/xSICjs3GbLJy3LElLUY/io2N1ngSqQwqn0REpM6zs7XQLyaI7u38+WlHKks3JZGec54P5u8nYEMSI7uF0q5JI0wqoaQKTJkyBXd3d15++WUWLFiA2WzmuuuuY82aNcycOZOPP/7Y6IgiIvXe3mWzCUleCCZIdI6k1ejxWMy6YYlIZdGiFyIiUm/Y21kYFBvMa/d1ZnjXUBztLaRmn+Xd2Xt55b/b2JeQU35JlEhlOXz4MA899BB9+/alZ8+epKen0717d/75z39yww03MG3atKt6vbKyMt555x3i4+Np164dd999NykpKX+4f3FxMZMnTy7f/9Zbb+XgwYPX+mOJiNQZSzcncfjwcQAS3KJpPfoRFU8ilUzlk4iI1DtODjYM7xrKa/d1ZnBcMPa2FhLTz/Dmt7t5dfoODiXlGR1R6pCysjK8vb0BCA4O5pdffil/rH///hw4cOCqXu/9999nxowZvPzyy8yaNYuysjLGjRtHUVHRZfd/4YUXmDNnDv/5z3+YPXs2Hh4e3H333Zw5c6biP5SISB1gtVqZvy6R71YdY0lBO3b4j6LNTfdjNutjskhlM/y3SmfvRETEKC6OtlzfPZzX7oujX3QgtjZmjqae5vWZO3lj5k6Opl5+jR6RqxEUFMThw4cBCA0NpaCggISEBABKSko4d+7cFb9WUVERn332GePHj6dHjx5EREQwZcoUMjIyWL58+SX7p6SkMHv2bP79738THx9PeHg4r7zyCnZ2duzbt69yfkARkVqorKyM9XO+Ycm6X08IXNctnO6DB6h4Eqkihv9m6eydiIgYzc3ZjlG9mzLx3jh6dfDHYjZxMCmP/3y9nSnf7uZ4Rr7REaUWGzp0KJMmTeLrr7/Gw8OD1q1b8/LLL7Ny5Uree+89mjRpcsWvdejQIc6dO0dcXFz5Njc3N1q2bMnWrVsv2X/9+vW4urrSrVu3i/ZfuXLlRa8hIlKflJaVsmba67TKXMLfXFYzqlc4QzqHGB1LpE4zdMHx387e/f3vf6dHjx7Ar4tyxsfHs3z5coYMGXLR/r+dvfvggw+Ij48H4JVXXmHEiBHs27dPB1EiInJN3F3tubVfcwZ0CmLRhuOs25PB3oQc9ibk0KFZY0Z0DSXAy8XomFLLjBs3jry8PHbv3s2tt97Kv/71L+6++24eeOABXFxcrmrNp4yMDAB8fX0v2u7l5VX+2P9KTEwkMDCQ5cuX89FHH5GZmUnLli15+umnCQ8Pv6afy8amas5hWizmi/4t1UPjbgyNe/UrLSllz1dvEnJuL2VWcG0eQ5fOoUbHqhf0fjdGTRl3Q8unvzp79/vy6c/O3omIiFSWRg0cuWNgCwbGBrNg3XE27c9gx5Fsdh7JJrqFF8O7hhLo7Wp0TKklzGYzTz31VPnXbdq0YcWKFSQkJBAWFoaLy5UXmgUFBQDY2dldtN3e3p7Tpy+9TPTs2bMkJSXx/vvv8+STT+Lm5sa0adMYM2YMS5YswdPTs4I/kwl3d+cKPfdKubk5Vunry+Vp3I2hca8exUVFrH/vVULOH6TUaiIv8ha6Dx1pdKx6R+93Yxg97oaWTzXp7J2IiMjvebs7cffQlgyOC2b+ukS2Hspiy8Esth7KonNrX+4Y2gp7nbyTCnBxcaFt27akp6fz7LPP8vbbb1/R8xwcHIBfZ4//9meAwsJCHB0vPai0sbHh7NmzTJkypfxYacqUKXTv3p25c+cybty4CuUvK7OSn3++Qs/9KxaLGTc3R/LzCygtLauS7yGX0rgbQ+NefQoLL3Doq9cIKjpGidXMmag7iejck7y8K193T66N3u/GqOpxd3NzvKJZVYaWTzXl7B1o6nhdo3E3hsbdGBr3qhfk48rDN7QlOfMMs38+xs4jJ1m/N51N+zPo3s6foV1C8Gzg8NcvJNestrzfS0tLeeutt5gzZw4mk4kRI0bw6KOPYrH8euvuoqIiPv74Yz755BMuXLhwxa/72wm7rKwsgoKCyrdnZWXRvHnzS/b38fHBxsbmopN0Dg4OBAYGkpqaWtEfD4CSkqr94FBaWlbl30MupXE3hsa9ahUWl3Lgq0k0KTlGsdVMXoe/ETtgIHl55zTuBtD73RhGj7uh5VNNOXunqeN1l8bdGBp3Y2jcq567uzORET4cSc5j+g+H2HEoi5U7UlmzO40BccHc2LsZHm4qoapDTX+/v/POO3z88ce0a9cOFxcXPv30U1xcXLjvvvvYvn07zzzzDMnJyQQHB/OPf/zjil83IiICFxcXNm/eXF4+5efnc+DAAW699dZL9o+OjqakpIS9e/fSpk0bAC5cuEBKSgqDBw+unB9WRKQGKygs4e3vdlOQ04S7XVMpih5L805aK1ikuhlaPtWUs3eaOl73aNyNoXE3hsa9+jV2tePxm9uRmnOeLxbt5+DxPBatS2T5piR6RwUyOC4YN2e7v34huWo1Zer4X/nhhx8YOnQob7zxBgAff/wxM2fOpHnz5jz88MPY2try+OOPc8cdd2Bra3vFr2tnZ8ett97KpEmT8PDwwN/fnzfeeAMfHx/69etHaWkpubm5uLq64uDgQFRUFJ07d+app57ipZdeomHDhrzzzjtYLBaGDx9+zT+niEhNduZ8EW99t4fE9Hwc7b25MPAlmgQ3MjqWSL1kaPlUk87eaep43aRxN4bG3Rga9+rXMtSTZ27tyN6jJ5mzNoFjJ/JZuimJlTtS6RsVQP+YIJwdrrxYkCtX09/vmZmZPPPMM+VfDxs2jMmTJ/Pkk0/SsWNHXn31Vfz8/Cr02uPHj6ekpITnnnuOCxcuEB0dzaeffoqtrS2pqan07t2bV199leuuuw6Ad999l0mTJvHQQw9x4cIFOnTowH//+188PDwq5WcVEamJ8nNOkjp7MmWn2+Hs4Mvjo9oR4uNmdCyRestktVqtRgaYMmUKs2bN4j//+U/52bvU1FQWLVqE2Wy+6OwdwJ133klmZuZFZ++2bdvGokWLKnwQVVpaRm5u1Sw0Z2Njxt3dWdcTVzONuzE07sbQuBvj9+NutVrZm5DL3DUJJGWeAcDR3ob+MYH0jQrE0d7Q8z11RlW/3z08nCtl5lNERATffvstbdu2BaC4uJg2bdrQp08f3n33XUwm0zV/DyPp2Knu0bgbQ+NeNfIyMzk1/1UacYrssgbYXfcyAV7/Vzxp3I2hcTdGTTl2Mny1zvHjx3PDDTfw3HPPMXr0aCwWS/nZu/T0dLp27cqSJUvK93/33XeJiYnhoYce4oYbbuDs2bM6eyciIoYzmUy0Dffk+TuieOi6Nvg3dqagsIR5axN5ctoGlm5KorCo1OiYYhCz+ddDrjvuuKPWF08iIjXZyROpnJn3Co04xWmrM84DJ1xUPImIMQw/DWuxWHjiiSd44oknLnksICCAw4cPX7TNxcWFF154gRdeeKGaEoqIiFw5k8lEh2aNade0EdsOZTFvbSIZuef5bvUxftiawuDYYHq098PWxmJ0VDHA5W6oIiIilSMr6ThFy97A3XSOPKsrTkOeopF/gNGxRIQaUD6JiIjURWaTiZgW3nRs3phN+zOZvy6Rk6cvMPOnX1i2JZkhnUOIb+uLTSVc4iW1h2Y9iYhUjbRjv8CKN2lgKuAkDWk44mncvX2MjiUi/5/KJxERkSpkMZvp0saXTi29Wb83nQXrj5N3ppCvfjjM0k1JDO0SQufWPljMKqHqmptvvvmSbddff/0l20wmEwcOHKiOSCIidVJSxhmSfviG9jYFZOFJ4+ufwc1Td7UTqUlUPomIiFQDG4uZ7u386dzah593pbF4YxInT1/g8yWHWLIxieFdQ4lp4Y3ZrJkxdcFDDz1kdAQRkXrh6InTTPl2NyWFMdDYifbX/w3Xhg2NjiUiv6PySUREpBrZ2ljoExVIfKQfq3acYMmmJDLzCvho4QEWb0xiRHwoHZo11uVZtZzKJxGRqvfLgcO8uTSdwuIymgV4En3jeN1dVqSG0m+miIiIAextLQzoFET3dn6s2J7KD5uTOXHyHO/N3UeQtwsj48NoG+6pEkpEROQyftmyHs+dn9HPJoIEv948dH0k9na6mYdITaXySURExECO9jYM7RxC7w7+/LAlheXbUkjOPMvb3+8hzM+NkfFhtAxxVwklIiLy/x1evxKvfV9jYyqjmVsBg69vjZ2KJ5EarcLl05kzZ9i0aRPnz5/HarVe8viIESOuJZeIiEi94uRgy8huYfSJCmDZ5mR+2p5KQlo+k7/ZRbPAhoyMD6V5kLvRMUVERAx1YPUy/A5/g8Vk5bh9cyLGPI6trZ3RsUTkL1SofFq7di3jx4/nwoULly2eTCaTyicREZEKcHWy48aeTegXHcjiTUms3pnGkZRTvDZjJ61C3BnRLYxwvwZGxxQREal2+5bPIzBxHmYTJDq2ptXoR7HYaMaTSG1QofJp8uTJhIWF8cwzz+Dt7Y1Zt4cWERGpVA1c7BnTpxkDYoJYtDGJtbvT2H88j/3HtxMZ7smI+DCCfVyNjikiIlIt9iz5jtDUxWCCBJf2tB71EBaziieR2qJC5dOxY8d4//33iYqKquw8IiIi8j883By4vX9zBnYKYuH646zfl87uYznsPpZDVPPGDI8Pw7+Rs9Ex5S/k5uby6aefsmHDBrKzs/nkk09YsWIFERER9OnTx+h4IiI12uKNx0k6dIpgZzjuHkubG+7RBAiRWqZCv7F+fn6cPXu2srOIiIjIH2jc0JG/DW7Bv++OJbalNyZg2+Fsnv9kMx8t3E9m7nmjI8ofSElJYdiwYXz77bd4e3uTk5NDaWkpiYmJjB8/ntWrVxsdUUSkRrJarcxZc4zZPyewrSicbaHjVDyJ1FIVmvl077338t5779GmTRsCAgIqO5OIiIj8AR8PJ+4Z1opBccHMX5fI9sPZbNqfyZYDWXRu48OwziE0auhodEz5H6+99hqenp589dVXODk50bp1a+DXZQwKCwv54IMP6NGjh7EhRURqmLKyMrbN+Yo1xzwBJ27sEU7v2GCjY4lIBVWofFq4cCGZmZn07dsXDw8PHBwcLnrcZDKxYsWKSgkoIiIilwpo7MKDI9uQlHGGeWsT2H0sh3V70tm4L4NukX4M6RyCu6u90TEF2LhxI//5z39wc3OjtLT0osduvvlmJkyYYEwwEZEaqrSslH2z3qXF2V3c79qQE9ET6BWt4kmkNqtQ+eTj44OPj09lZxEREZGrFOzjyiM3RnLsxGnmrU1g//E8Vu08wdo96fRs78+guGAaOOsW1Eazsbn8IVdRUREmk6ma04iI1FwlJcUcmDmFsIIDlFlNlDTrTa/oEKNjicg1qlD59Oqrr1Z2DhEREbkG4f4NeHxUew4n5zF3TQJHUk/z47YUft59gt4dAxjYKRgXR1ujY9ZLUVFRfPjhh8TFxWFv/+tsNJPJRFlZGTNnzqRDhw4GJxQRqRmKi4o4NGMSoUVHKLWaSI8YRavu/Y2OJSKVoELl02/WrFnDli1byM/Px93dnaioKOLj4ysrm4iIiFyl5kHuPHVLBw4cz2POmgQS0/NZuimZVTtO0C86kH7RgTg5qISqTo8//jijR4+mX79+dOrUCZPJxKeffsqxY8dISkpixowZRkcUETFcYcEFjs56jZDiREqsZrLb3EaLzj2NjiUilaRC5VNRUREPPPAA69atw2Kx4O7uTl5eHh999BGxsbF8+OGH2Nlpir+IiIgRTCYTrUI9aBnizu5jOcxbk0By1lkWrD/Oim2pDOgURJ+oABzsrukclFyhZs2a8f333zN16lQ2b96MxWJhw4YNREdH89prr9G8eXOjI4qIGOpCUQm7Z02lZXEixVYLuR3+RrPoLkbHEpFKVKGjznfffZft27fz+uuvM3jwYCwWCyUlJSxatIgXX3yRadOm8cgjj1R2VhEREbkKJpOJdk0a0Tbckx2Hs5m3LpG0k+eYsyaB5VtTGBQbTK8O/tjZWoyOWqeVlpYSGhrK5MmTjY4iIlLjnL9Qwlvf7eZkdnPucz2BbdwYmrSLNjqWiFQyc0WetGjRIh566CGGDRuGxfLrAauNjQ0jRozgoYceYuHChZUaUkRERCrObDIRFeHFS3+L4Z6hLfFyd+RsQTHfrjrKUx9u5KftqRSXlBkds87q2rUrr7zyCnv37jU6iohIjXLm3AXemLWToydOU2TbAMuw5wlV8SRSJ1Vo5lNubi4tW7a87GMtW7YkMzPzmkKJiIhI5TObTcS28iG6hRcb9mWwYN1xcvIvMP3HIyzdnMTQziF0aeOLjaVC56bkDwwZMoRly5Yxffp0goODGTFiBEOHDsXf39/oaCIihjmdnU323NdwP9uSHMem/H1UO4K8XY2OJSJVpEJHl0FBQWzfvv2yj23duhVfX99rCiUiIiJVx2I2E9/Wj1fvjeW2fs1o6GJHbn4hXy47zLMfb2L93nTKyqxGx6wznn32WdasWcNnn31GVFQUn3/+OX379uXWW2/lu+++48yZM0ZHFBGpVrkZ6eTNfQVvTjLSeQdPjWqj4kmkjqtQ+TRq1Cg+/PBDPvnkE9LT0ykuLiY9PZ2PP/6Yjz/+mOuvv76yc4qIiEgls7GY6dkhgIn3xjGqd1PcnGzJPnWBTxcf5J+fbmbLwUzKrCqhKoPJZCIuLo5XXnmFdevW8f777+Pr68uLL76oOwWLSL2SnZrM2fn/wZPTnLK6YD/oCfy9GxodS0SqWIUuuxs9ejQHDhxg0qRJFy2eabVaGTlyJPfcc0+lBRQREZGqZWdroV90IN0j/Vi5I5Ulm5JIzznPB/P3E7AhiZHxobRr2giTyWR01FqvpKSEdevWsXTpUtasWQNAXFycwalERKpHRuIxSpZPxt10nlyrGy5Dn8bTz8/oWCJSDSpUPpnNZv79739z5513smXLFvLz82nQoAExMTGEh4dXdkYRERGpBvZ2FgbGBtOjvT8/bk3hh63JpGaf5d05ewnxcWVEfBhtwjxUQl0lq9XKpk2bWLx4MT/++COnT5+mbdu2jB8/nkGDBuHu7m50RBGRKnfil8OYV06hgekCJ3HH/bpnaNjYy+hYIlJNKlQ+/aZJkyY0adKksrKIiIhIDeBob8OwrqH06hjAD1uSWbEtleMZZ3jru9008W/AyG5htAhWYXKl4uPjycnJwc/PjzFjxjB8+HBCQkKMjiUiUm0S0/PZt3wxPWwvkEkjvG94BlcPT6NjiUg1uuLyqXfv3rz33ntERETQq1evPz3raTKZWLFiRaUEFBEREWO4ONpyffdw+kYHsnRTEit3nODoidO8MXMnEUENGdktjKYBDY2OWeP16tWLYcOGERUVZXQUEZFqdyTlFG99t5vCokhsvFzodsPNOLs1MDqWiFSzKy6fYmJicHZ2Lv+zptyLiIjUD25Odtzcqyn9ooNYsjGJn3ef4FDyKV79egetwzwYGR9GqK+b0TFrrJdeesnoCCIihvhl9y7e/jGHCyUmIoLc6XH933C0v6aLb0Sklrri3/xXX321/M8TJ06skjAiIiJSc7m72nNLv2YM6BTEwg3HWbcnnX0JuexLyKV900aMiA8j0MvF6Jg1wv/OGO/du/ef7qsZ4yJSFx3ZuIZGe75gtEMAWxuP4MHrIrGztRgdS0QMUuHa+ezZs5w7dw5vb2+Ki4v56quvSEtLo3///kRHR1dmRhEREalBPBs4cMfACAbFBrFg/XE27s9g5y8n2fnLSaIjvBjeNRS/Rs5GxzTU/84Yj46O1oxxEalXDq75Ed+DM7CYrDR0sePBEa1UPInUcxUqn3bv3s24ceMYNWoUjz/+OK+88grffPMNbm5uzJgxg3ffffcvz/KJiIhI7ebl7sS4IS0ZHBfM/HWJbDmYxdZDWWw7nEVsSx+Gdw3By93J6JiGuJoZ46WlpVUdR0Sk2uxfuZiAX77HbLJy3KEFEaMfxdbWzuhYImIwc0We9NZbbxEeHs5NN91EQUEB8+fPZ8yYMWzZsoUbbriBDz74oLJzioiISA3l6+nMfcNb8+LfYmjftBFWK2zcn8E/PtrMF0sPkXP6gtERDdW7d28OHTp02cf27NlD586dqzmRiEjV2LdsDkFHv8NsspLo3JaWY/6u4klEgGuY+TRlyhQCAwNZsWIFhYWFDB8+HIBBgwaxYMGCSg0pIiIiNV+glwsPX9+WxPR85q1NZG9CDmt2p7FhXzrdI/0Z3DmYhi72RsesFosWLaKkpASAEydOsHz58ssWUBs3bqS4uLi644mIVLpdi78j/MRiABLcomh90/1YzLrUTkR+VaHyyWw2Y2//68Hj2rVrcXNzo23btsCva0E5ODhUXkIRERGpVUJ93Xj0pkiOpp5m7toEDibl8dOOVNbsSaNXB38Gxgbj5lS3z4Tv3buXL7/8Evh1QfH333//D/e98847qyuWiEils1qtLNxwnD0HS7jf1UKqRyfaXD8Os7lCF9mISB1VofKpdevWfPfddzg4OLBs2TJ69OiByWQiJyeHjz/+mNatW1d2ThEREallmgQ04InR7Tl4PJe5axM5euI0P2xJYfXONPpEBdA/JggXR1ujY1aJxx9/nNtvvx2r1UqfPn2YOnUqLVq0uGgfi8WCi4sLLi66Q6CI1E5Wq5Xvfz7G0k3JgDc7mj9In+7tdZMFEblEhcqnJ554gnHjxrF48WI8PDy4//77ARgyZAhlZWV8+umnlRpSREREaq8WIR5EBLuzLzGXOWsSSMo4w+KNSazckUr/6CD6RgfiaF/hG/DWSHZ2dvj7+wPw008/4eXlha1t3SzaRKR+Ki0rZfd3n7A7uRHgzqheTegbE2R0LBGpoSp0pNeqVSt+/PFHjh07RtOmTXFy+vVONi+88AIdOnSgcePGlRpSREREajeTyUSbME9ah3qw65eTzF2bQGr2OeatS+THbSkMjA2md4cA7O3qxvogU6dO5cYbb8Tb25u5c+f+6b4mk4kHH3ywmpKJiFy70pJS9s96i6bn93K/qwPHop6kW5SKJxH5YxU+zeji4kJkZORF2/r373/NgURERKTuMplMtG/WmMimjdh2KIv56xJJzznP96uPsXxLMoPiQujZ3g9bm9pdQk2dOpVu3brh7e3N1KlT/3RflU8iUpsUFxdxaOYUQi8cpMxq4nSzoXSLCjM6lojUcFdcPvXu3Zv33nuPiIgIevXq9afX8ZpMJlasWFEpAUVERKTuMZtMxLTwJqq5F5sOZDB/XSLZpy4w66df+GFLMkPigomP9MPGUjsXrP3fO9td7i53IiK1UVFhIUdmvE5I8TFKrSYyWt5Cy/g+RscSkVrgisunmJgYnJ2dy/+sReRERETkWpnNJjq39iWmhTcb9mWwYH0iufmFfLX8CEs2JTOsSwid2/hgqWN3TcrOziYrK4uIiAgslto9y0tE6ocLBedJmPkawSVJFFvNnIy8g4jYbkbHEpFa4orLp1dffbX8zxMnTrzk8ZKSEmxs6tZioSIiIlI9bCxmukX6EdfKhzW701i08Tg5+Rf4fOkhlmxKYljXUDq18DY6ZoWcPXuWf//737Ru3ZpbbrmFpUuX8sQTT1BaWkpISAifffYZvr6+RscUEflDBYUlbJ31Ce1Lkiiy2nAqahzNOsYaHUtEapEKn0b86KOPuOeee8q/3r59O127duXrr7+ulGAiIiJS/9jamOndMYDX7o3j5l5NcHG0JTOvgI8XHuD5z7aw9WAmZWVWo2NelcmTJ/PDDz/QoEEDACZNmkRERARTp07FxsaGSZMmGZxQROSPnbtQzORvdjEzszmHS/zJj32AcBVPInKVKlQ+ffbZZ7z11luEhISUbwsKCmLAgAFMnDiR7777rrLyiYiISD1kZ2uhf0wQr98fx3XdwnCytyHt5Dnenb2XR9/6mZzTF4yOeMV++uknnn76aYYMGcK+ffs4ceIEd999N7179+ahhx5i/fr1RkcUEbms/PwzvDFjJwlp+dg4OOI58ilCIzsYHUtEaqEKlU+zZs1iwoQJ/OMf/yjf5uvry3PPPcdDDz3EF198UVn5REREpB5zsLNhSOcQXr8/jmFdQnCws5Bw4jR7juUYHe2KnTp1irCwX+8E9fPPP2NjY0OXLl0AaNCgAYWFhUbGExG5rLysLHJmPU/z/A24Odny1JgOhPq6GR1LRGqpCi3SlJmZSZs2bS77WGRkJNOmTbumUCIiIiL/y8nBlhHxYfTvFERWfhEhXk5Yy4xOdWX8/f05fPgwUVFRrFixgnbt2uHi4gL8WkYFBAQYnFBE5GIn005wbuFrNDLl082xiB7DbsHXy8XoWCJSi1Vo5pO/vz8bN2687GNbt27Fx8fnmkKJiIiIXI6rkx1RLbxr1d3vRo0axcSJExk0aBAHDx5kzJgxAOWzxUeNGmVwQhGR/5OVcpyCha/iYconz+qK/eCn8fVtbHQsEanlKjTz6aabbuKNN96guLiYPn364OnpSW5uLqtWreLzzz/n8ccfr+ycIiIiIrXS2LFj8fT0ZOvWrTz00EMMGjQIAFtbW1544QVuvvlmgxOKiPwq/dgvlK2YQkPTeXJogNvwp/Hw0d04ReTaVah8uuOOO8jMzOSrr766aH0ni8XC2LFjufPOOysrn4iIiEitN2TIEIYMGXLRtilTphiURkTkUqmHD2Cz+h3cTBfIxgPP6/5Bg0aNjI4lInVEhcongKeeeooHHniAXbt2cerUKdzc3Gjbti3u7u6VmU9ERESk1ktMTOSdd95hy5Yt5Ofn4+7uTlRUFA8++CDh4eFGxxOReu7YidOsXb6e6+0vkGHywufGZ3BtqM91IlJ5Klw+ATg7O9O4cWOsVisdOnSgpKSksnKJiIiI1AlHjx5l1KhRWCwWevXqRaNGjcjOzmbVqlWsXr2a7777TgWUiBjmUFIeb8/eQ2FROM6uLgy6bjDObrqrnYhUrgqXT/Pnz2fy5MlkZ2djMpn47rvvePfdd7G1tWXy5MnY2dlVZk4RERGRWmnSpEkEBATw1Vdf4erqWr79zJkzjB07lilTpjB16lQDE4pIffXLts18+HMehcV2tAh2Z9j13bG3sxgdS0TqoArdKmbJkiU89dRTxMbG8uabb1JW9uu9jvv27cvPP//M+++/X6khRURERGqrrVu3ct99911UPAG4urpyzz33sHXrVoOSiUh9dnj9Khpt/5Bxjj/SMcyFCTe2VfEkIlWmQjOfPvjgA0aNGsULL7xAaWlp+fbrr7+e3Nxcvv32WyZMmFBZGUVERERqLRsbG+zt7S/7mJ2dHUVFRdWcSETquwM/L8Pv0DdYTFbKnD25Z0Q7bG1UPIlI1anQzKfExET69u172cciIyPJzMy8plAiIiIidUWbNm2YMWMGVqv1ou1Wq5Xp06fTunVrg5KJSH2078cF+B+ahcVkJdGxFS1ueQJbLZkiIlWsQjOfPD09OXbsGF26dLnksWPHjuHp6XnNwURERETqgkceeYTRo0czbNgwBgwYQOPGjcnOzmbZsmUkJiby+eefGx1RROqJvUu+IyR1MZggwaU9rUc9hMWsGU8iUvUqVD4NGjSId955By8vL7p37w6AyWRi3759vP/++wwZMqRSQ4qIiIjUVm3atOGTTz5h8uTJTJ06FavVislkonXr1nz88cdER0cbHVFE6oEdi7+n6YnFACQ06ESbG+/FbK7QhTAiIletQuXThAkTOHLkCBMmTCj/C+u2227j/PnzREVF8cgjj1RqSBEREZHaLDY2lu+++46CggLy8/Nxc3PD0dHR6FgiUg9YrVbmrU1kw35bHnFzJKdxFG1G3qniSUSqVYXKJzs7Oz755BPWr1/Ppk2bOHXqFK6ursTExNC9e3dMJlNl5xQRERGpVXJycpgzZw5paWkEBwczdOhQPD09VTqJSLWxWq18s/Ioy7emAK7sb/Uw/eNbGh1LROqhCpVPd911F+PGjaNLly6XXfdJREREpD47evQot9xyC6dPny7f9v777/Pee+/pMjsRqRalZaXs/eZ9TqQ1AAIY06cpfaICjY4lIvVUheZa7tixQ7ObRERERP7AW2+9hYuLC19//TW7d+9m7ty5BAQE8PLLLxsdTUTqgZKSYvZPn0L4me3c4fIz43r7q3gSEUNVqHyKj49nwYIFFBcXV3YeERERkVpv27ZtPPbYY0RFRWFvb0+LFi34xz/+wS+//EJubq7R8USkDisuLuLg9EmEFuyj1Goiq/mNdI5ubnQsEannKnTZnb29PQsWLGDp0qWEh4fj5OR00eMmk4kvv/yyUgKKiIiI1DZnzpzBz8/vom0RERFYrVZOnjyJh4eHQclEpC4runCBX2a+TkhxAiVWM1mtb6VFl15GxxIRqVj5lJGRQfv27cu/tlqtFz3++69FRERE6pPS0lIsFstF235baFwzx0WkKlw4d57EWa8SVJpCsdVCbvu/0TxG6/OKSM1w1eXTnj17GDNmDEFBQbRq1aoqMomIiIiIiMgVKigs4edvp9OlNIVCqw35MffSpL1ubiAiNccVl0/5+fnce++97Nq1q3xb+/btmTx5Mr6+vlWRTURERKTO0U1bRKQynS0o5s1vdpGUGYrF9STNug8irHWk0bFERC5yxeXTW2+9xYEDB3j44Ydp3bo1CQkJfPDBBzz//PN8/PHHVZlRREREpNa5+eabL7v9+uuvv+hrk8nEgQMHqiOSiNQxp3NzeXPOYVJOFuDiaE+z6x8i2MfV6FgiIpe44vJp1apVPPbYY4wdOxaAbt264e3tzd///nfOnz9/yaLjIiIiIvXVQw89ZHQEEanjcjPSyV/wGt0LPVjk3JPHR7XHv7GL0bFERC7risun7OzsS9Z46tSpE6WlpaSnpxMeHl7p4URERERqI5VPIlKVTqamcH7x63iazmBjV8xTQ5rgreJJRGqwKy6fSkpKsLOzu2hbgwYNACgsLKzcVCIiIiIiInKJjOMJlPwwGXfTOXKtbjgPfZJGflqDV0Rqtqu+293lWK3WyngZERERERER+QNpvxzGtHIKDUwXOIk7DUc8jbu3t9GxRET+UqWUT7pri4iIiIiISNVJObgPuzXv4mQqJItGNL7hGdw8PI2OJSJyRa6qfHrhhRdwcfm/a4l/m/H0z3/+E2dn5/LtJpOJL7/8spIiioiIiIiI1F+/pJ5i8Y97GGtfTLrJG7+bnsGlQUOjY4mIXLErLp+io6OBSy+xu9x2XYYnIiIiIiJy7Q4cz+Wd2XsoKvZhYcMR3HBdL5xctLi4iNQuV1w+ffXVV1WZQ0RERKTOys3N5dNPP2XDhg1kZ2fzySefsGLFCiIiIujTp4/R8USkhjqyeR3T1+VQVOxKq1APbr6uO/a2FqNjiYhcNbPRAURERETqspSUFIYNG8a3336Lt7c3OTk5lJaWkpiYyPjx41m9erXREUWkBjq09ica7/qM+5x/oEuYPeOvb6viSf5fe/ceFmWd/3/8NTMwgBxEVETFA1pA4gE802qZlbVlpmblea3EDm5Yq1i2bpn6TVNZ04o8rNSueahVV83UzE7b1uahTC0PmZLiAVBBUU4DM/P7ox9sBJoow83A83FdXOY9n/ue9/1mcj68+Nz3AG6rUm44DgAAgPK9/PLLql+/vpYuXao6deqobdu2kqTExEQVFBRowYIF6tWrl7FFAqhW9n38vpoeWiWzyalz3s01ckAXeXqwbgCA++JfMAAAABf673//qyeeeEIBAQFlPiH4wQcf1KFDhwyqDEB19N0H/1LTQ/+U2eRUSp12ajMsQZ6eVqPLAoBrQvgEAADgYh4e5S82t9lsZQKp3+JwODR//nz17NlT0dHRiouLU2pq6hXtu379ekVEROj48eMVek4AVWPvhpVqcXSdzCbpiH8nRQ19ShYPLrUD4P4InwAAAFyoc+fOWrhwoXJzc0u2mUwmORwOrVixQh07dqzQ8ZKSkrR8+XJNmzZNK1eulMPh0OjRo2Wz2S6734kTJzR16tSrOgcArrfj/X+p5cnNkqQj9W5UuwfHymImeAJQMxA+AQAAuND48eN1+PBh9enTRxMnTpTJZNKSJUs0cOBAff3113r66aev+Fg2m03JycmKj49Xr169FBkZqblz5yotLU1btmy55H4Oh0MJCQmKioqqjFMCUImcTqf++fGPeus7bx0vqqcjDXup3X2jZTbzoxqAmoN/0QAAAFwoPDxcq1evVrdu3bRt2zZZLBZ9+eWXat68uVauXKkbbrjhio914MAB5eTkKDY2tmRbQECA2rRpox07dlxyvwULFqiwsFCPPvroNZ0LgMpldzi0eN13eu/Ln5Tn9FJqzB/VYcAogicANQ6fdgcAAOBiLVu2VGJi4jUfJy0tTZLUuHHjUtuDg4NLHvu1PXv2KDk5WatWrVJ6evo111DMw0WfvGWxmEv9iapB36uevciuPW+/oux0q6Qb9IffR+rWTqFGl1Ur8Ho3Bn03RnXpO+ETAACAC508efI3xzRp0uSKjpWXlydJslpLf/KVl5eXzp8/X2Z8bm6uJkyYoAkTJqhly5aVFj6ZzSbVq+dbKce6lIAAH5ceH+Wj71WjqLBQ/3ltmlrmfq9mdUzqcsftuvnmCKPLqnV4vRuDvhvD6L4TPgEAALhQ7969f/MT7fbv339Fx/L29pb0872fiv9bkgoKCuTjU3ZSOX36dIWFhWnw4MEVqPi3ORxOZWfn/vbAq2CxmBUQ4KPs7DzZ7Q6XPAfKou9Vx1Zg076lL6uF7ZDsTpPOd/yDYmLaKCsrx+jSag1e78ag78Zwdd8DAnyuaFUV4RMAAIALvfTSS2XCp9zcXO3cuVPbtm3TSy+9dMXHKr7cLiMjQ82bNy/ZnpGRoYiIsqsmVq9eLavVqpiYGEmS3W6XJPXt21ePPfaYHnvssQqfT7GiItf+4GC3O1z+HCiLvrtWQV6eflzxsloU/aQip1lno0cp9q67lZWVQ98NwOvdGPTdGEb3nfAJAADAhQYOHFju9mHDhmnGjBl677331KtXrys6VmRkpPz8/LRt27aS8Ck7O1v79u3T8OHDy4z/9Sfg7d69WwkJCVq0aJHCw8MrdiIArknuxYs69s5MNbcfl81p0blOoxXZ/XdGlwUAVcLwO305HA7Nnz9fPXv2VHR0tOLi4pSamnpF+65fv14RERE6fvy4i6sEAACofL1799ann356xeOtVquGDx+uOXPm6KOPPtKBAwf09NNPKyQkRH369JHdbtfp06eVn58vSWrRokWpr0aNGkn6+R5TgYGBLjgjAOXJzS/Uxn+uU1P7ceU7PZXd/Qm17hz72zsCQA1hePiUlJSk5cuXa9q0aVq5cqUcDodGjx4tm8122f1OnDihqVOnVlGVAAAAlW/37t3y8KjYQvT4+HgNGjRIkydP1pAhQ2SxWLRkyRJ5enrq1KlT6tGjhzZu3OiiigFU1IVcm2at2KWN6Y21ydZZeT3iFdahk9FlAUCVMvSyO5vNpuTkZE2YMKFkufncuXPVs2dPbdmyRX379i13P4fDoYSEBEVFRemrr76qwooBAAAqZtKkSWW2ORwOpaWlaceOHRo0aFCFjmexWJSQkKCEhIQyj4WGhurgwYOX3Ldbt26XfRxA5Tp3OkOvrj2gY2eL5F/HU7EPjFKzYD+jywKAKmdo+HTgwAHl5OQoNvZ/S04DAgLUpk0b7dix45Lh04IFC1RYWKg//vGPhE8AAKBa27ZtW5ltJpNJfn5+iouLu6abfgOovs6eOqkL619WvyKrlvvdpaeGdFTj+r5GlwUAhjA0fEpLS5P0v09uKRYcHFzy2K/t2bNHycnJWrVqldLT011eIwAAwLVYvHixWrdubXQZAKrQ6dSjyt84W/VNF2X28NeEvuFqSPAEoBYzNHzKy8uT9PPNM3/Jy8tL58+fLzM+NzdXEyZM0IQJE9SyZctKDZ88PFxz+yuLxVzqT1QN+m4M+m4M+m4M+m4Md+z70KFDNWnSJPXv39/oUgBUgbQjh2X/MFGBplydVV0F9HtGQY2bGF0WABjK0PDJ29tb0s/3fir+b0kqKCiQj49PmfHTp09XWFiYBg8eXKl1mM0m1avn2t9EBASUPR+4Hn03Bn03Bn03Bn03hjv13dPTU/Xq1TO6DABV4MQP+2X+ZJ4CTPk6rSDVHzBJdRs2NLosADCcoeFT8eV2GRkZat68ecn2jIwMRURElBm/evVqWa1WxcTESJLsdrskqW/fvnrssceu+p4JDodT2dm5V7Xvb7FYzAoI8FF2dp7sdodLngNl0Xdj0Hdj0Hdj0HdjuLrvAQE+lb6qaty4cZo1a5YuXLigyMhI1alTp8yYJk1YFQG4u6Pf75HPf16Tj8mmNFNDhdz/nPwDCZ4BQDI4fIqMjJSfn5+2bdtWEj5lZ2dr3759Gj58eJnxW7ZsKfX33bt3KyEhQYsWLVJ4ePg11VJU5NofHOx2h8ufA2XRd2PQd2PQd2PQd2O4U9+nTJkiu91e7qfTFdu/f38VVgSgsh08lqUVHx7Ro94mnbQ0VugDk+QbEGB0WQBQbRgaPlmtVg0fPlxz5sxRUFCQmjZtqtmzZyskJER9+vSR3W5XZmam/P395e3trRYtWpTav/im5E2aNFFgYKABZwAAAHB506dPN7oEAC70XcpZvbZ6r2xFAXq/wf0aNqC7fHz9jC4LAKoVQ8MnSYqPj1dRUZEmT56s/Px8denSRUuWLJGnp6eOHz+uW2+9VTNmzNDAgQONLhUAAOCKjBw5Ui+88IJat26tAQMGGF0OABc5+OWn2vjVSdmKQtS+dX2N7N9WVk+L0WUBQLVjePhksViUkJBQ7lL00NBQHTx48JL7duvW7bKPAwAAGGH79u3KyckxugwALrT/31vUeP8KPexr0eZmwzR4YDt5uNEncQJAVTI8fAIAAAAAd/L91vcUeniNzCanUn3CNXhAD4InALgMwicAAAAAuEJ7N61Wy9T3JJOU4hetqMFPymLmUjsAuBzCJwAAABcYO3asrFbrb44zmUzaunVrFVQE4FrteW+Zwk59KEk6EtBV7R54TGYzK54A4LcQPgEAALhAmzZtFBQUZHQZACqB0+nUlxs3qn1x8FS/h9oNeJjgCQCuEOETAACAC4wdO1bt27c3ugwA18jpdOqfnxzWlr1eetgvVH6h4erQf6TRZQGAWyF8AgAAAIBy2B12Lf/wkD7ZdVKSWTld43Rj1xZGlwUAbofwCQAAAAB+xV5k1/cr56pBpk0mddPIOyN1c3RTo8sCALdE+AQAAFDJBgwYoHr16hldBoCrVFho04HliQorOKjmXiaFdO2jGIInALhqhE8AAACVbMaMGUaXAOAq2fLzdWjFbLUsPKwip1kZUcMU072z0WUBgFsjfAIAAAAASfl5uUpZPlPN7cdU6LTobPQoRXTraXRZAOD2CJ8AAAAA1Hq5Fy4o9Z0ZCnWcVIHTQ9ld4nR9x25GlwUANYLZ6AIAAAAAwEgX8wr17qqtamQ/pXynp3Ju/KNaETwBQKVh5RMAAACAWis7x6bEd75VakZd2Xxv1u9v76wWkW2NLgsAahTCJwAAAAC1UlZ6mhav26PUTA8F+Fp11+BBCm3oZ3RZAFDjcNkdAAAAgFrnzInjurD2/3S/fb2a+xfp2WEdCZ4AwEUInwAAAADUKulHf1L+hhmqZ7ogi9mkP/Zvo5CgOkaXBQA1FpfdAQAAAKg1Th7+Qdo6V3VNeTqjQAX2f1b1GoUYXRYA1GiETwAAAABqheMH9snjs3nyNRUoQ/XV8L5JCqjfwOiyAKDGI3wCAAAAUOP99N1e1fniVfmYbEozBSvk/ufkHxhodFkAUCtwzycAAAAANdr+nzL12pYTOu/w0UlzEzUd/BeCJwCoQqx8AgAAAFBj7Tl8Vq//a68Ki6z6MOR+PTygo7x9uLk4AFQlwicAAAAANdLB/3ykbTsPq7DoOkVf10Bx/aPk6WExuiwAqHUInwAAAADUOPs+2aQmP7yrB3ycqt+0mfoNaCsPC3cdAQAjED4BAAAAqFG+27JWzVLWymySUuq01b0D+shC8AQAhiF8AgAAAFBj7H3/XbU8sVEySUf8O6rtg2NlMXOpHQAYifAJAAAAQI2wZ+0/FJbxsSTpSGCs2g2Kk9nMiicAMBr/EgMAAABwa06nU59u2vq/4KnhzQRPAFCNsPIJAAAAgNtyOp1a+dGP+nC3Sed92iisVVN1uGeY0WUBAH6B8AkAAACAW7I77Fq+eZ8+2XNakkl+PYaqfadQo8sCAPwK61ABAAAAuJ2iokLtW5aoyJTl8jTZ9dBdkbqV4AkAqiVWPgEAAABwK4U2mw4un62WtkOye5j0x56+ate+idFlAQAugfAJAAAAgNsoyMvT4RWz1KIoRUVOs063G6F2N95odFkAgMsgfAIAAADgFvJyLuqnlTPVzH5cNqdFWZ0eUXhngicAqO4InwAAAABUeznZ2Tr+7gyFOk6pwOmhC90e03XRnY0uCwBwBbjhOAAAAIBq7WJeod5a9YXqFZ1RntOqnB7xCiN4AgC3wconAAAAANXW+YsFmvPOtzpx2ku5vndo6B1RahF+g9FlAQAqgPAJAAAAQLWUeeqk3n5vh05k+quun1XDBv9eTRr4Gl0WAKCCCJ8AAAAAVDunjx9T/vuz9KCzQIUB92jEkNsUXK+O0WUBAK4C4RMAAACAaiUt5bDsWxIVaMpVpgI0qn9n1Sd4AgC3RfgEAAAAoNo4ceigzB/PVYApX6dVT0EDJymwYbDRZQEArgHhEwAAAIBq4dj3e+X1n1dVx2RTuhqq0aBn5R9U3+iyAADXiPAJAAAAgOGOfP+9/P8zX96mQp0yh6jpA5PkG1DX6LIAAJXAbHQBAAAAAGq371My9ddNp3S0qIFOWJqq2ZDJBE8AUIOw8gkAAACAYb49dEZJa/eqyG7WfxvcpzH9ouTl42N0WQCASkT4BAAAAMAQ+//9oX76dreK7DHqGB6sR/tFydODizMAoKYhfAIAAABQ5fZ9tEFNf1ytUG+nrCGtdEf/W2QxEzwBQE1E+AQAAACgSn23ebVaHHtPMkkpvu11x8B7CZ4AoAYjfAIAAABQZfa8t0Jhpz6QJB0J6KJ2DzwuM8ETANRohE8AAAAAXM7hcOi7df9Q2OlPJUlHgn6ndgMfIXgCgFqAf+kBAAAAuJTT6dSWD75Ui4xPJUlHgnurw6A4gicAqCVY+QQAAADAZRxOp1Z8eEgf7bbpmFesYsMD1eHuB40uCwBQhQifAAAAALiEvciuFZt26+Pvz8kkKbxXX7WLaWp0WQCAKkb4BAAAAKDSFRbadGD5X9Ut95S2m+/Q4LtidGPbxkaXBQAwAOETAAAAgEplKyjQoeWz1LLwsOxmkx7r4a82BE8AUGsRPgEAAACoNPl5uTqy4mU1LzqqQqdZZzqMUpvuPY0uCwBgIMInAAAAAJUi9+JFHVv5kpo5Tsrm9NC5zqMV3qm70WUBAAxG+AQAAADgml08f04n352hps505Ts9lRP7uFq372h0WQCAasBsdAEAAAAA3Ft2rk0LVn0jz6Ic5Tq9lH/TOLUkeAIA/H+sfAIAAABw1bIuFGjOyl06dVa66HuXxtzZWs2ujzC6LABANUL4BAAAAOCqnDl5XOvXf65T5xqpnr+XHh3cTY3r+xpdFgCgmiF8AgAAAFBhGUd/km3zbA005aqw7h0aOOReNQz0MbosAEA1RPgEAAAAoEJOHT4k59a/qq4pT2cVqPsH3KwggicAwCUQPgEAAAC4YscP7JPHZ/PkZypQhuqrwcBJqtuggdFlAQCqMcInAAAAAFfk6HffyueLJPmYbEozBSvk/ufkHxhodFkAgGqO8AkAAADAb/px30EFfvGavExFOmlurNAHnpNvgL/RZQEA3ADhEwAAAIDL2nvkrF7beFIDrGFq4ZuvsMGT5O1bx+iyAABugvAJAAAAwCV9fSBDC9Z/L7vDqYPN71bveyNl9fI2uiwAgBshfAIAAABQrv2fblbed/+V09FTnSNDNOaeNvKwmI0uCwDgZgifAAAAAJTx3Yfr1ezIGoVapWFhEbqpX29ZzARPAICK490DAADAjTgcDs2fP189e/ZUdHS04uLilJqaesnxhw4d0pgxY9StWzfFxsYqPj5eJ0+erMKK4Y72bvynWqSskdkkHfGL0U33P0jwBAC4aryDAAAAuJGkpCQtX75c06ZN08qVK+VwODR69GjZbLYyY7OysvTQQw/J29tbS5cu1eLFi5WZmanRo0eroKDAgOrhDnavf1stj78vSTpSt5vaDX5SFrPF4KoAAO6M8AkAAMBN2Gw2JScnKz4+Xr169VJkZKTmzp2rtLQ0bdmypcz4rVu3Kjc3V7NmzVJ4eLjatm2r2bNn6/Dhw/rmm28MOANUZw6HQ9+8+ze1StsqSTrS4Ca1u/9RmVnxBAC4RryTAAAAuIkDBw4oJydHsbGxJdsCAgLUpk0b7dixo8z42NhYJSUlydv7f59MVhwkZGdnu75guA2n06kVa75Qk9NfSpJSQm5Xh4EPEzwBACoFNxwHAABwE2lpaZKkxo0bl9oeHBxc8tgvhYaGKjQ0tNS2RYsWydvbW126dHFdoXArDqdTb286qI+/ydQ3Hrfo7igvtf/9IKPLAgDUIIRPAAAAbiIvL0+SZLVaS2338vLS+fPnf3P/pUuX6u2339bkyZMVFBR0TbV4eLhmRYzFYi71J1yrqKhQ767fro/358lkkm6+6zbFtG/82zuiUvB6NwZ9NwZ9N0Z16TvhEwAAgJsovnzOZrOVupSuoKBAPj4+l9zP6XRq3rx5euONN/T4449rxIgR11SH2WxSvXq+13SM3xIQcOnzQeWwFRTov6//n27O+Ul7Pe7UsAd76+aOob+9Iyodr3dj0Hdj0HdjGN13wicAAAA3UXy5XUZGhpo3b16yPSMjQxEREeXuU1hYqEmTJmnDhg2aNGmSRo0adc11OBxOZWfnXvNxymOxmBUQ4KPs7DzZ7Q6XPAekgvx8HVg6Q80LU1RkMuuhmxootmMofa9ivN6NQd+NQd+N4eq+BwT4XNGqKsInAAAANxEZGSk/Pz9t27atJHzKzs7Wvn37NHz48HL3mThxoj788EMlJibq7rvvrrRaiopc+4OD3e5w+XPUVvk5uUpZOUPN7akqdFqU2fFhRcb2lETfjULfjUHfjUHfjWF03wmfAAAA3ITVatXw4cM1Z84cBQUFqWnTppo9e7ZCQkLUp08f2e12ZWZmyt/fX97e3lqzZo02btyoiRMnqmvXrjp9+nTJsYrHoHbJyc7W8XdnKNRxSgVOD2V3fVTXxXDzeQCAa3GnLwAAADcSHx+vQYMGafLkyRoyZIgsFouWLFkiT09PnTp1Sj169NDGjRslSRs2bJAkzZo1Sz169Cj1VTwGtceFc+d08p3pauI4pTynVTm/e1KtCJ4AAFWAlU8AAABuxGKxKCEhQQkJCWUeCw0N1cGDB0v+npycXJWloRo7n2PT/FXfqZ/NqRwPbxX1ileLiDZGlwUAqCVY+QQAAADUYJnZ+Xp52TdKOWPTCufv5eyToFCCJwBAFWLlEwAAAFBDnTmeqk82bFLauetUP8BLTw+JUaN6dYwuCwBQyxA+AQAAADVQ2k9HZP8gUXeac+QItOjWIUPVoK6P0WUBAGohwicAAACghjlx6KDMH89VgClfZ1RPd9x3jwIJngAABjH8nk8Oh0Pz589Xz549FR0drbi4OKWmpl5y/KFDhzRmzBh169ZNsbGxio+P18mTJ6uwYgAAAKD6St3/nTw+TpSfKV8ZaqD6gyYrsGGw0WUBAGoxw8OnpKQkLV++XNOmTdPKlSvlcDg0evRo2Wy2MmOzsrL00EMPydvbW0uXLtXixYuVmZmp0aNHq6CgwIDqAQAAgOrjpz3fyPvf81THZNMpUyM1GvwXBQTVN7osAEAtZ2j4ZLPZlJycrPj4ePXq1UuRkZGaO3eu0tLStGXLljLjt27dqtzcXM2aNUvh4eFq27atZs+ercOHD+ubb74x4AwAAACA6uHAwZ/k998keZsKdcLcVKFD/iK/gLpGlwUAgLHh04EDB5STk6PY2NiSbQEBAWrTpo127NhRZnxsbKySkpLk7e1dss1s/vkUsrOzXV8wAAAAUA3t/vGM/rr+J23MjVaqRwu1HPZn1fHzM7osAAAkGXzD8bS0NElS48aNS20PDg4ueeyXQkNDFRoaWmrbokWL5O3trS5dulxTLR4ersnhLBZzqT9RNei7Mei7Mei7Mei7Meg7UNbO/Wla+N5+2R1OnW91k667p42sVj5XCABQfRj6rpSXlydJslqtpbZ7eXnp/Pnzv7n/0qVL9fbbb2vy5MkKCgq66jrMZpPq1fO96v2vREAAny5iBPpuDPpuDPpuDPpuDPoO/Oz7j9+X94GPZXXervZtmumRu2+QB+EsAKCaMTR8Kr58zmazlbqUrqCgQD4+l55UOp1OzZs3T2+88YYef/xxjRgx4prqcDicys7OvaZjXIrFYlZAgI+ys/Nktztc8hwoi74bg74bg74bg74bw9V9DwjwYVUV3MZ3H/xLLY6ukzykYS1OqXvfO2Q2m4wuCwCAMgwNn4ovt8vIyFDz5s1LtmdkZCgiIqLcfQoLCzVp0iRt2LBBkyZN0qhRoyqllqIi1/7gYLc7XP4cKIu+G4O+G4O+G4O+G4O+o7bbu2GlWp7cLEk6EtBZ3R4YSfAEAKi2DP3VXmRkpPz8/LRt27aSbdnZ2dq3b98l7+E0ceJEbd68WYmJiZUWPAEAAADuwOFwaM/av/8veKp3o9o98IQsZovBlQEAcGmGrnyyWq0aPny45syZo6CgIDVt2lSzZ89WSEiI+vTpI7vdrszMTPn7+8vb21tr1qzRxo0bNXHiRHXt2lWnT58uOVbxGAAAAKAmcjgc2rv6b2qV9aUkKSX4FrXrN6Lk058BAKiuDH+nio+P16BBgzR58mQNGTJEFotFS5Yskaenp06dOqUePXpo48aNkqQNGzZIkmbNmqUePXqU+ioeAwAAANQ0DqdTa7bsVtDZbyVJKU3uUPv+fyB4AgC4BcM/g9VisSghIUEJCQllHgsNDdXBgwdL/p6cnFyVpQEAAACGczic+scHB/Tv3Vnaab5dQ6PNat/nXqPLAgDgihkePgEAAAAoX2Fhodat/0z/PmSWySTd8/vuat+usdFlAQBQIYRPAAAAQDVkKyjQDytm69aCI0qx3qped92uLpHBRpcFAECFET4BAAAA1UxBXp4Or5ipFkVHVSiz7r2xmcIJngAAborwCQAAAKhGci9e1LF3ZqiZ/YRsTg9ldR6t8E7djS4LAICrRvgEAAAAVBM52ed14p2X1NSZrnynpy52f1zXdehodFkAAFwTwicAAACgGrhw7pzS352uxjqjXKdVtpueVNgN7YwuCwCAa2Y2ugAAAACgtjt3sUCz/rlfqQX+uuj0VlHv8WpG8AQAqCFY+QQAAAAY6Oz5fM1euUsZWXl63+8W3fD7lmravLnRZQEAUGkInwAAAACDZKT+pG/fX63T5zqoQd06mjAkRsGBPkaXBQBApSJ8AgAAAAxw6siPcnz4V8Wac2UPsqrb4DgFBXgbXRYAAJWO8AkAAACoYid+2C/LJ/MUYMrXaQXpxoFDVJfgCQBQQxE+AQAAAFXo6Pe75fOf1+VjsinN1FAh9z8n/8B6RpcFAIDLED4BAAAAVSTl2x3y37ZQXqYinTQ3VugDk+QbEGB0WQAAuBThEwAAAFAFvv/hhBpsWywvU5GOW0IVNvg5efvWMbosAABcjvAJAAAAcLFdP5zWG+t+UIS5h/oEHVX44Any8uFT7QAAtQPhEwAAAOBC2/ematHGH+VwOuVzXYwi7xkmTw+L0WUBAFBlCJ8AAAAAF/l+63qFHNqseqY7FN7mej18d6QsZrPRZQEAUKUInwAAAAAX2LtplVqmbpAs0gPN09Wpbz+ZTSajywIAoMoRPgEAAACVbM/6ZQpL+1CSdKRuV3W6fzTBEwCg1iJ8AgAAACqJw+HQ3rVvqdWZf0uSjtTvqXYDHpKZS+0AALUY4RMAAABQCRwOh/auWqRW576SJKU0ulUd7h1hcFUAABiPX8EAAAAA18jhdGrlB9/L88wPkqSfQu9Se4InAAAksfIJAAAAuCYOh1NvbtqvL/ae1lem2zS6i1nte99pdFkAAFQbhE8AAADAVSostGnTmk36IsVfZpNJQ/p2VPuoEKPLAgCgWiF8AgAAAK6CLT9fh1bM0i2FR3TGu7s6/P4+dYpoaHRZAABUO4RPAAAAQAXl5+UqZflMNbcfU6HTop6xbXU9wRMAAOUifAIAAAAqIPfCBaW+M0OhjpMqcHoou+ujuj6mi9FlAQBQbRE+AQAAAFfowrlzSvvnS2rizFCe06q83z2hVm2jjS4LAIBqjfAJAAAAuALZ5y/q9LvTFKKzynF6qejmcWoR2cbosgAAqPbMRhcAAAAAVHdZFwr08rvfaUduM11w+shx2wSFEjwBAHBFWPkEAAAAXMaZc3mavXKXTp/LV0FAZ93Sb6gaNQ42uiwAANwG4RMAAABwCelHU5Sy6R86f667Ggb6K2FIjBrU9TG6LAAA3ArhEwAAAFCOk4d/kLbOVZQ5T0ODvNVuyFOq5+9ldFkAALgdwicAAADgV1IPfCfrZ6+qjqlAGaqv6EGjFUDwBADAVSF8AgAAAH7h6J5dqvPfJHmbCnXK1EhNHpgkv7qBRpcFAIDbInwCAAAA/r8jX29T3Z2LZTUV6YS5iZoPfk51/PyMLgsAALdmNroAAAAAoDrYcyhNlh3/kNVUpFSP5mo5bDLBEwAAlYCVTwAAAKj1dh7I0ML1+9XIdIvua3hEUUPGyerFPZ4AAKgMhE8AAACo1bbv+lGLtqTK4XQq9IZItes7UB4WLhAAAKCyED4BAACg1vpuy78UlvK+WlpuVZMbojXq95Eym01GlwUAQI1C+AQAAIBaae/776jliU2SSbor9Jyi74qU2UTwBABAZSN8AgAAQK2zZ+0/FJbxsSTpSL1YRd8XR/AEAICLED4BAACg1nA4HNq7ZolaZX4hSUpp2Evt7h0ps5l7PAEA4CqETwAAAKgVHA6H9r6bpFbZOyVJKY37qP09Qw2uCgCAmo9f8QAAAKDGczicWrr5gC6eSZck/dT8HoInAACqCCufAAAAUKPZHQ4teX+/vvo+XV+YbtLY9p7qcFMvo8sCAKDWIHwCAABAjVVos+mTVf/UV8dCZDGbNfqe9upwQyOjywIAoFYhfAIAAECNVJCXp8MrXlZs0U/K941SsztHKeb6hkaXBQBArUP4BAAAgBonL+eijq6cqWb247I5LYqK7aHWBE8AABiC8AkAAAA1Sk52to6/O0NNHaeU7/TUxW6PqnV0Z6PLAgCg1iJ8AgAAQI1xIfOs0lfNVBOdVp7TqvweTyosqp3RZQEAUKsRPgEAAKBGOJ+dp9OrZqiRzuii01uOW8apefgNRpcFAECtZza6AAAAAOBaZWbna+aKb7Xp4g065/SV6fYENSV4AgCgWmDlEwAAANxaRmaOZq/crbPZ+SoKuEFeA+9TcMNAo8sCAAD/H+ETAAAA3FZaymGd+WCRii70UKN6DZQwJEZBAd5GlwUAAH6B8AkAAABu6cQP+2X+ZJ5amPM1rN43un7os6rr52V0WQAA4FcInwAAAOB2jn2/V97/eVU+JpvS1VAR9z8pf4InAACqJcInAAAAuJWU3V/L76sF8jYV6qQ5RKEPTJJvQF2jywIAAJdA+AQAAAC3cXjnfxX49d9kNdl13BKqloOflY+vn9FlAQCAyyB8AgAAgFv49ocMee34p6wWu1I9wtR6yER5+fgYXRYAAPgNhE8AAACo9rbvT9fi9/bJ19lbQxofUcfBj8nTajW6LAAAcAUInwAAAFCt7di+Vws/OS2nU2oTFabOd98li9lsdFkAAOAK8a4NAADgRhwOh+bPn6+ePXsqOjpacXFxSk1NveT4rKwsjR8/Xl26dFHXrl314osvKi8vrworvjZ7N69W+K6/qpPnEd3UoYlG392G4AkAADfDOzcAAIAbSUpK0vLlyzVt2jStXLlSDodDo0ePls1mK3d8fHy8jh49qrfeekvz5s3TZ599pilTplRt0Vdpz3vL1fLYezKbnLqxqU1/uDNCZrPJ6LIAAEAFET4BAAC4CZvNpuTkZMXHx6tXr16KjIzU3LlzlZaWpi1btpQZv2vXLm3fvl0vv/yyoqKiFBsbq6lTp2rdunVKT0834AyujMPh0K5VyQo79fM5HQn6ndrf/5hMJoInAADcEeETAACAmzhw4IBycnIUGxtbsi0gIEBt2rTRjh07yozfuXOnGjZsqNatW5ds69q1q0wmk77++usqqbmiHA6HPv/bPLXM+FSSlBLcWx0GxcnMpXYAALgtbjgOAADgJtLS0iRJjRs3LrU9ODi45LFfSk9PLzPWarUqMDBQp06dcl2hV8nucGjPytcVlv1zMJbS9Pdqf/eDBlcFAACuFeETAACAmyi+UbjVai213cvLS+fPny93/K/HFo8vKCi4plo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       "text/plain": [
-       "0.0"
+       "<Figure size 1200x600 with 2 Axes>"
       ]
      },
-     "execution_count": 28,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "f1_score(y_true=wmns_actual_T, y_pred=wmns_baseline_pred_T)"
+    "wmns_base_bce = nn.BCEWithLogitsLoss()(wmns_baseline_pred_T, wmns_actual_T).item()\n",
+    "print(f\"womens base model BCE Score: {wmns_base_bce}\")\n",
+    "\n",
+    "w_pred_arr = wmns_baseline_pred_T.numpy().flatten()\n",
+    "w_true_arr = wmns_actual_T.numpy().flatten()\n",
+    "\n",
+    "wfpr, wtpr, wthresholds_roc = roc_curve(w_true_arr, w_pred_arr)\n",
+    "wprecision, wrecall, wthreshold_prob = precision_recall_curve(w_true_arr, w_pred_arr)\n",
+    "\n",
+    "# Plot Precision-Recall Curve\n",
+    "plt.figure(figsize=(12, 6))\n",
+    "plt.subplot(1, 2, 1)\n",
+    "plt.plot(wrecall, wprecision, label=\"Precision-Recall Curve\")\n",
+    "plt.ylim(0)\n",
+    "plt.xlabel(\"Recall\")\n",
+    "plt.ylabel(\"Precision\")\n",
+    "plt.title(\"Precision-Recall Curve\")\n",
+    "\n",
+    "# Plot ROC Curve\n",
+    "plt.subplot(1, 2, 2)\n",
+    "plt.plot(wfpr, wtpr, label=\"ROC Curve\")\n",
+    "plt.plot([0, 1], [0, 1], linestyle=\"--\")\n",
+    "plt.title(\"ROC Curve\")\n",
+    "plt.xlabel(\"False Positive Rate\")\n",
+    "plt.ylabel(\"True Positive Rate\")\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
    ]
   },
   {
@@ -597,7 +577,7 @@
    "outputs": [],
    "source": [
     "# save the data with baseline predictions and overwrite the one made in preprocessing\n",
-    "games_df.to_csv(os.path.join(DATA_DIR, \"AllSuperDetailedGames.csv\"))"
+    "# games_df.to_csv(os.path.join(DATA_DIR, \"AllSuperDetailedGames.csv\"))"
    ]
   }
  ],