diff --git a/examples/pytorch_minimal_demo.ipynb b/examples/pytorch_minimal_demo.ipynb
index ca65407..58a3487 100644
--- a/examples/pytorch_minimal_demo.ipynb
+++ b/examples/pytorch_minimal_demo.ipynb
@@ -24,16 +24,7 @@
      "shell.execute_reply": "2024-06-17T19:19:04.140766Z"
     }
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/opt/miniconda3/envs/ag/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
-      "  from .autonotebook import tqdm as notebook_tqdm\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Load libraries\n",
     "\n",
@@ -163,34 +154,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "epoch is 0\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "epoch is 10\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "epoch is 20\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "epoch is 30\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "epoch is 0\n",
+      "epoch is 10\n",
+      "epoch is 20\n",
+      "epoch is 30\n",
       "epoch is 40\n"
      ]
     }
@@ -260,7 +227,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -356,38 +323,38 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Accuracy</th>\n",
-       "      <td>0.846355</td>\n",
-       "      <td>0.832187</td>\n",
+       "      <td>0.847338</td>\n",
+       "      <td>0.834152</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Balanced Accuracy</th>\n",
-       "      <td>0.771054</td>\n",
-       "      <td>0.717877</td>\n",
+       "      <td>0.751879</td>\n",
+       "      <td>0.719638</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>F1 score</th>\n",
-       "      <td>0.661250</td>\n",
-       "      <td>0.587145</td>\n",
+       "      <td>0.640709</td>\n",
+       "      <td>0.590661</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>MCC</th>\n",
-       "      <td>0.563726</td>\n",
-       "      <td>0.498290</td>\n",
+       "      <td>0.552857</td>\n",
+       "      <td>0.503902</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Precision</th>\n",
-       "      <td>0.699924</td>\n",
-       "      <td>0.713866</td>\n",
+       "      <td>0.733451</td>\n",
+       "      <td>0.721481</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Recall</th>\n",
-       "      <td>0.626626</td>\n",
-       "      <td>0.498631</td>\n",
+       "      <td>0.568789</td>\n",
+       "      <td>0.500000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ROC AUC</th>\n",
-       "      <td>0.898968</td>\n",
-       "      <td>0.876756</td>\n",
+       "      <td>0.900978</td>\n",
+       "      <td>0.882202</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -395,13 +362,13 @@
       ],
       "text/plain": [
        "                   original   updated\n",
-       "Accuracy           0.846355  0.832187\n",
-       "Balanced Accuracy  0.771054  0.717877\n",
-       "F1 score           0.661250  0.587145\n",
-       "MCC                0.563726  0.498290\n",
-       "Precision          0.699924  0.713866\n",
-       "Recall             0.626626  0.498631\n",
-       "ROC AUC            0.898968  0.876756"
+       "Accuracy           0.847338  0.834152\n",
+       "Balanced Accuracy  0.751879  0.719638\n",
+       "F1 score           0.640709  0.590661\n",
+       "MCC                0.552857  0.503902\n",
+       "Precision          0.733451  0.721481\n",
+       "Recall             0.568789  0.500000\n",
+       "ROC AUC            0.900978  0.882202"
       ]
      },
      "execution_count": 12,
@@ -454,43 +421,43 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Statistical Parity</th>\n",
-       "      <td>0.223317</td>\n",
-       "      <td>0.016872</td>\n",
+       "      <td>0.166023</td>\n",
+       "      <td>0.018608</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Predictive Parity</th>\n",
-       "      <td>0.008117</td>\n",
-       "      <td>0.301545</td>\n",
+       "      <td>0.005739</td>\n",
+       "      <td>0.264864</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equal Opportunity</th>\n",
-       "      <td>0.243709</td>\n",
-       "      <td>0.261034</td>\n",
+       "      <td>0.085072</td>\n",
+       "      <td>0.299332</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Average Group Difference in False Negative Rate</th>\n",
-       "      <td>0.243709</td>\n",
-       "      <td>0.261034</td>\n",
+       "      <td>0.085072</td>\n",
+       "      <td>0.299332</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equalized Odds</th>\n",
-       "      <td>0.173466</td>\n",
-       "      <td>0.149859</td>\n",
+       "      <td>0.077089</td>\n",
+       "      <td>0.165101</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Conditional Use Accuracy</th>\n",
-       "      <td>0.041894</td>\n",
-       "      <td>0.231932</td>\n",
+       "      <td>0.056760</td>\n",
+       "      <td>0.216559</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Average Group Difference in Accuracy</th>\n",
-       "      <td>0.106414</td>\n",
-       "      <td>0.089916</td>\n",
+       "      <td>0.115661</td>\n",
+       "      <td>0.101757</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Treatment Equality</th>\n",
-       "      <td>0.549310</td>\n",
-       "      <td>2.313295</td>\n",
+       "      <td>0.135662</td>\n",
+       "      <td>2.428146</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -498,14 +465,14 @@
       ],
       "text/plain": [
        "                                                 original   updated\n",
-       "Statistical Parity                               0.223317  0.016872\n",
-       "Predictive Parity                                0.008117  0.301545\n",
-       "Equal Opportunity                                0.243709  0.261034\n",
-       "Average Group Difference in False Negative Rate  0.243709  0.261034\n",
-       "Equalized Odds                                   0.173466  0.149859\n",
-       "Conditional Use Accuracy                         0.041894  0.231932\n",
-       "Average Group Difference in Accuracy             0.106414  0.089916\n",
-       "Treatment Equality                               0.549310  2.313295"
+       "Statistical Parity                               0.166023  0.018608\n",
+       "Predictive Parity                                0.005739  0.264864\n",
+       "Equal Opportunity                                0.085072  0.299332\n",
+       "Average Group Difference in False Negative Rate  0.085072  0.299332\n",
+       "Equalized Odds                                   0.077089  0.165101\n",
+       "Conditional Use Accuracy                         0.056760  0.216559\n",
+       "Average Group Difference in Accuracy             0.115661  0.101757\n",
+       "Treatment Equality                               0.135662  2.428146"
       ]
      },
      "execution_count": 13,
@@ -532,7 +499,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -560,7 +527,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -632,38 +599,38 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Accuracy</th>\n",
-       "      <td>0.841291</td>\n",
-       "      <td>0.834575</td>\n",
+       "      <td>0.847515</td>\n",
+       "      <td>0.836295</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Balanced Accuracy</th>\n",
-       "      <td>0.766900</td>\n",
-       "      <td>0.695163</td>\n",
+       "      <td>0.748003</td>\n",
+       "      <td>0.730541</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>F1 score</th>\n",
-       "      <td>0.653061</td>\n",
-       "      <td>0.553097</td>\n",
+       "      <td>0.636186</td>\n",
+       "      <td>0.606728</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>MCC</th>\n",
-       "      <td>0.551446</td>\n",
-       "      <td>0.493792</td>\n",
+       "      <td>0.551022</td>\n",
+       "      <td>0.515458</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Precision</th>\n",
-       "      <td>0.684685</td>\n",
-       "      <td>0.782228</td>\n",
+       "      <td>0.741348</td>\n",
+       "      <td>0.713559</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Recall</th>\n",
-       "      <td>0.624230</td>\n",
-       "      <td>0.427789</td>\n",
+       "      <td>0.557153</td>\n",
+       "      <td>0.527721</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ROC AUC</th>\n",
-       "      <td>0.895597</td>\n",
-       "      <td>0.884229</td>\n",
+       "      <td>0.900819</td>\n",
+       "      <td>0.886769</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -671,13 +638,13 @@
       ],
       "text/plain": [
        "                   original   updated\n",
-       "Accuracy           0.841291  0.834575\n",
-       "Balanced Accuracy  0.766900  0.695163\n",
-       "F1 score           0.653061  0.553097\n",
-       "MCC                0.551446  0.493792\n",
-       "Precision          0.684685  0.782228\n",
-       "Recall             0.624230  0.427789\n",
-       "ROC AUC            0.895597  0.884229"
+       "Accuracy           0.847515  0.836295\n",
+       "Balanced Accuracy  0.748003  0.730541\n",
+       "F1 score           0.636186  0.606728\n",
+       "MCC                0.551022  0.515458\n",
+       "Precision          0.741348  0.713559\n",
+       "Recall             0.557153  0.527721\n",
+       "ROC AUC            0.900819  0.886769"
       ]
      },
      "execution_count": 17,
@@ -730,43 +697,43 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Statistical Parity</th>\n",
-       "      <td>0.223317</td>\n",
-       "      <td>0.048679</td>\n",
+       "      <td>0.166023</td>\n",
+       "      <td>0.048191</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Predictive Parity</th>\n",
-       "      <td>0.008117</td>\n",
-       "      <td>0.200809</td>\n",
+       "      <td>0.005739</td>\n",
+       "      <td>0.232708</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equal Opportunity</th>\n",
-       "      <td>0.243709</td>\n",
-       "      <td>0.173597</td>\n",
+       "      <td>0.085072</td>\n",
+       "      <td>0.235527</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Average Group Difference in False Negative Rate</th>\n",
-       "      <td>0.243709</td>\n",
-       "      <td>0.173597</td>\n",
+       "      <td>0.085072</td>\n",
+       "      <td>0.235527</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equalized Odds</th>\n",
-       "      <td>0.173466</td>\n",
-       "      <td>0.089706</td>\n",
+       "      <td>0.077089</td>\n",
+       "      <td>0.124479</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Conditional Use Accuracy</th>\n",
-       "      <td>0.041894</td>\n",
-       "      <td>0.180334</td>\n",
+       "      <td>0.056760</td>\n",
+       "      <td>0.193359</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Average Group Difference in Accuracy</th>\n",
-       "      <td>0.106414</td>\n",
-       "      <td>0.121237</td>\n",
+       "      <td>0.115661</td>\n",
+       "      <td>0.098722</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Treatment Equality</th>\n",
-       "      <td>0.549310</td>\n",
-       "      <td>0.680241</td>\n",
+       "      <td>0.135662</td>\n",
+       "      <td>2.014920</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -774,14 +741,14 @@
       ],
       "text/plain": [
        "                                                 original   updated\n",
-       "Statistical Parity                               0.223317  0.048679\n",
-       "Predictive Parity                                0.008117  0.200809\n",
-       "Equal Opportunity                                0.243709  0.173597\n",
-       "Average Group Difference in False Negative Rate  0.243709  0.173597\n",
-       "Equalized Odds                                   0.173466  0.089706\n",
-       "Conditional Use Accuracy                         0.041894  0.180334\n",
-       "Average Group Difference in Accuracy             0.106414  0.121237\n",
-       "Treatment Equality                               0.549310  0.680241"
+       "Statistical Parity                               0.166023  0.048191\n",
+       "Predictive Parity                                0.005739  0.232708\n",
+       "Equal Opportunity                                0.085072  0.235527\n",
+       "Average Group Difference in False Negative Rate  0.085072  0.235527\n",
+       "Equalized Odds                                   0.077089  0.124479\n",
+       "Conditional Use Accuracy                         0.056760  0.193359\n",
+       "Average Group Difference in Accuracy             0.115661  0.098722\n",
+       "Treatment Equality                               0.135662  2.014920"
       ]
      },
      "execution_count": 18,
@@ -808,7 +775,7 @@
     {
      "data": {
       "text/plain": [
-       "(-1.778, 0.8525)"
+       "(-1.52, 1.256)"
       ]
      },
      "execution_count": 19,
@@ -924,31 +891,31 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Accuracy</th>\n",
-       "      <td>0.834575</td>\n",
+       "      <td>0.836295</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Balanced Accuracy</th>\n",
-       "      <td>0.695163</td>\n",
+       "      <td>0.730541</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>F1 score</th>\n",
-       "      <td>0.553097</td>\n",
+       "      <td>0.606728</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>MCC</th>\n",
-       "      <td>0.493792</td>\n",
+       "      <td>0.515458</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Precision</th>\n",
-       "      <td>0.782228</td>\n",
+       "      <td>0.713559</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Recall</th>\n",
-       "      <td>0.427789</td>\n",
+       "      <td>0.527721</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ROC AUC</th>\n",
-       "      <td>0.884229</td>\n",
+       "      <td>0.886769</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -956,13 +923,13 @@
       ],
       "text/plain": [
        "                          0\n",
-       "Accuracy           0.834575\n",
-       "Balanced Accuracy  0.695163\n",
-       "F1 score           0.553097\n",
-       "MCC                0.493792\n",
-       "Precision          0.782228\n",
-       "Recall             0.427789\n",
-       "ROC AUC            0.884229"
+       "Accuracy           0.836295\n",
+       "Balanced Accuracy  0.730541\n",
+       "F1 score           0.606728\n",
+       "MCC                0.515458\n",
+       "Precision          0.713559\n",
+       "Recall             0.527721\n",
+       "ROC AUC            0.886769"
       ]
      },
      "execution_count": 22,
@@ -1015,35 +982,35 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Statistical Parity</th>\n",
-       "      <td>0.053119</td>\n",
+       "      <td>0.044486</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Predictive Parity</th>\n",
-       "      <td>0.214987</td>\n",
+       "      <td>0.216116</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equal Opportunity</th>\n",
-       "      <td>0.133063</td>\n",
+       "      <td>0.263228</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Average Group Difference in False Negative Rate</th>\n",
-       "      <td>0.133063</td>\n",
+       "      <td>0.263228</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equalized Odds</th>\n",
-       "      <td>0.069230</td>\n",
+       "      <td>0.136986</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Conditional Use Accuracy</th>\n",
-       "      <td>0.185445</td>\n",
+       "      <td>0.188366</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Average Group Difference in Accuracy</th>\n",
-       "      <td>0.118119</td>\n",
+       "      <td>0.106678</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Treatment Equality</th>\n",
-       "      <td>0.587310</td>\n",
+       "      <td>2.120472</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1051,14 +1018,14 @@
       ],
       "text/plain": [
        "                                                        0\n",
-       "Statistical Parity                               0.053119\n",
-       "Predictive Parity                                0.214987\n",
-       "Equal Opportunity                                0.133063\n",
-       "Average Group Difference in False Negative Rate  0.133063\n",
-       "Equalized Odds                                   0.069230\n",
-       "Conditional Use Accuracy                         0.185445\n",
-       "Average Group Difference in Accuracy             0.118119\n",
-       "Treatment Equality                               0.587310"
+       "Statistical Parity                               0.044486\n",
+       "Predictive Parity                                0.216116\n",
+       "Equal Opportunity                                0.263228\n",
+       "Average Group Difference in False Negative Rate  0.263228\n",
+       "Equalized Odds                                   0.136986\n",
+       "Conditional Use Accuracy                         0.188366\n",
+       "Average Group Difference in Accuracy             0.106678\n",
+       "Treatment Equality                               2.120472"
       ]
      },
      "execution_count": 23,
@@ -1090,7 +1057,13 @@
     "fpred_standard = oxonfair.DeepFairPredictor(val['target'],\n",
     "                                              val_output,\n",
     "                                              groups=val['groups'], use_fast=True)\n",
-    "# 2. Single threshold. This adjusts the global bias only, without considering group membership.\n",
+    "# 2. A classifier that enforces fairness by using the actual group labels instead of inferred.\n",
+    "fpred_true_groups = oxonfair.DeepFairPredictor(val['target'],\n",
+    "                                              val_output,\n",
+    "                                              groups=val['groups'], use_fast=True,use_actual_groups=True)\n",
+    "\n",
+    "\n",
+    "# 3. Single threshold. This adjusts the global bias only, without considering group membership.\n",
     "# It works surprisingly well for criteria like recall.min, but is less useful for fairness\n",
     "fpred_thresh  = oxonfair.DeepFairPredictor(val['target'],\n",
     "                                              val_output,\n",
@@ -1100,6 +1073,27 @@
   {
    "cell_type": "code",
    "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(<function oxonfair.learners.fair.DeepFairPredictor.<locals>.square_align(array)>,\n",
+       " False)"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fpred_standard.inferred_groups, fpred_true_groups.inferred_groups"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-06-17T19:20:00.046278Z",
@@ -1119,13 +1113,14 @@
    ],
    "source": [
     "fpred_standard.fit(gm.accuracy,gm.demographic_parity,0.05)\n",
+    "fpred_true_groups.fit(gm.accuracy,gm.demographic_parity,0.05)\n",
     "fpred_thresh.fit(gm.accuracy,gm.demographic_parity,0.05)\n",
     "\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 27,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-06-17T19:20:00.067975Z",
@@ -1137,7 +1132,17 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "text/plain": [
+       "(0.75, 0.8533906633906634)"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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d6r5V5EEt7rYY+9DXZGANCvi5k5PLe34ipdhEqCgpQQSBJMV5oM/R1QpdvAQuc00ha7km7eMg0KvzJoKKaouQq6E59Hu3V9qKl7atE+/KY8JUxpdOlW5jJ7qOHCuLl3/TqJOmBxQYADQ1lF2lwdYgSTK3LFdiWDyR/UMfSz7Oj5hf+m5sVZENVSi+O0pkm9enkk/lzHLp8lAKSYQPyh/ua9+3zbFVElSvjykqKyaoJ3yQ+4BPdZR0FnX9X9CfjEzUAF5nNTmwIYTUleXvBfZRkJOsJnsbenQs0kxMfVSiKDC2snXQdcRPUoqBhT36qCUliZh+55j8KFa8XGSOrlb6Gvf1MPTAn7j605ufGefxIiFJIoJAynolhanVE7BYRZl3d2UE/Ey3Grkamh4TplI+9HTk5BRkWY1rq4ACA4Ampaa4DPRNwTXtHyJJpKhzsarIirJ4RNwlkpKSwsPDqX3HPB6vY/eOnCqOFHkSuW/fK32oaUZJoCXoN6BfR9RRSiQOoU9Gg7gJSPE4WDukc03aS2SGMFc9Su3fGUIpBhb26KOWlCTS9fshGgaGsszRyXBrTOzQHxu1GXER6yOXrTjyfdkxJb1SVdPCwlSuiIrq5OTSoatTTet2AAXEQgSABkZ6uPGa4zIQmmWaU8yndDfp/knx06Trk0RbkEizTJMlYBVk980oNSe/NJr+nNJdpfzjqVOnxHuuZFTKCSV4ZpOILCHlz8vLKbY7jhAivqwfZznOw8hDxmBRDRgu9qu6Ep8hxOAZQn5UZNivm2oayHvOInPnHgdmTpKo5LgampN3HWIwmPWMxCHC87MzhYJyiyG7GXIKVRWlcSd+rKpiGDktARUlEYiFCABNyrWU62vurcurqN4AJItdhRDS/6xvl2OnJFB6kfniReQLBSUFfY4+jnYh0gAhhFDRZ8WE+5VGacL/Jug+Fpbcux0uUSR5obzEcgIRL6u0K8sNVPN+VNS5WFBZ/R7XVdKl1pBkpAHdBGTvqtYZQukGFkdVjcFg9vafKlEFUgtODTtHZzH0N+pYToHtNP5EQ/X8bQIKDAAaBoFQ8L8bW699+J2kWTMfSz5SwZZqisuAIzbRSypKKrqXdI/RjsE6TLyBEqr0kH9zuxJROky+JJeaOZQdX2fzJZY23Uy9EZpbzxC9DegmIGNXtc4QGlhac9Q1azKwsEdfJyeXQTIvOAEtDVBgAPAV1DQ9eCP1RtDdNYVVOUhsqg6HG/cw9MgqztIs1WQJWGXMsmxWdnW7fyM2iU/xVUdsQhIaYP+4bvLp6eVqCBG6Kqx2XEKCv0FtuFsbmZpiVcGsT9SlZkG6C0Zxfp4sBhaCBafWDCgwAJCVmtJ2VK9skWRNe4UzSzIvx1xOikpy++yGS0qYJQkaCR+UP+CITeKXVEdsKtVEBJLcgEAcVKHDKPoo5AX5WPGUvzowK4/HMzY2/tqrWg61zhAimQ0sBoNpaG3beKICjQQoMOCbRsZNwQKhYN+TfXsS9tALcSz2zW6bN8ZuJBFJWVTY1YJuZul/1n907YvwCmwBu3tW9xjtGAYpLR6pYqU6wSyR0kBPCQX72nvZ6AmFQh6PJ3EWkc1mS4yC6OXlJZ5LpRUhywwhAgOrTQMKDPh2kejw1s9KW2SS8EbqjaCooMJKUd1AkqRWmdaBawcEQgFiIUSIuFr8a2YpfZAS1j1WU9rMX2WeXyl6h1BRTQ02j+7eob0eQojBYHh5eUn0QvTx8UEIibjXi2RRaRWIR4SSZYYQgYHVdgE3euAbJezpuznnziK5IrKKKygxRYhBIMTkPtM1Daf88XSUdLxNvUMSQxASNa30S0R1VbpyulmhGaItVmGHw0SVJJsCa3EBMJE6kV2zu4pHbEII8Xg8y34jZhx/PFwxQQlVEmLGIY/HmzdvHt2KEt8HRimqWvNYtnBqigglUg4uGG2JWt/noMCAtoYss4LXUq4vvLWKZObjU2GlSvlHH4QQy+AYgZD4UpaIaVXOKFcQKiAxXYXEfDFIRFYQFYqkYk3S2va2LRGUvI58LV7l5+dnZWUV/ixjz/nILpXPkdhWLdxA5KrWrqgkIn2/l5RYvUCrBhQY0GaR+KYOe/ou6NqlvPIcbFfpqSiJb4O9lnJtQeQCHMgHg78EpECJYJaIGzqUF7uIupIe311GJkyYYGpqKsVyQggJhOTFyAeJ9+9Uln2W2KBtIxQKat1u3PRSAU0AbGQG2g5004pb9vHaVdE3/uWcxNAXOxiaBWyEEELCSpVPH31+OlZGDxV4LeXaojuL0JfWDPZKZ8hJcpeQ5Ob+taqrJjcKyg/QysrKwsKiJsuJySB8PZwGuXVte6aVLNS63wvWt75ZQIEBrQChUPhXxOMT0S8zStBHIdeQkeeh8IauQwoLC0+dOnVP6x6hXEAVEnIFLINjZe/HrrzIwqECb6TeWBC5QOIQ4oYXpiY396/CyckpIiJCvJzuB8hgMExNJSclkbFBW6XW/V5NJgnQ0gAFBrQsxCcGk5KSzl+8XFH62Q4hOwX0mZRj4jm8L1UOiUi7XDt6+CVsVynqXMx4bfUgObebqer6B+u/Vh7piYllgcfj9erVS1tbuw34ATYNIuEHZdnvBXybgAIDWhDiS0E2NjbR0dF0baWEqiRaS9U7f8s0s9n/TTcRBCLkC5hKyVlF9jVFcqJDXxjDSE9MLAvYzJI+SQhQRB47TA8AH3n0sP3AwbLs9wK+QUCBAS2FpKQkkW1MhYWF0dHR6Etbq6a5PoxEg4mQK9Lmsj6VfJJyIUlWO3HQbTsCETmsHIJFCMuEsqx7ubi4PHv2rCYz65udA5SdyGOHH148Sy8hSWHcpXMdHJ0kKjDxHI/ANwUoMKARyHmDyosEJJn4vjC3pEJdScHagMckCKTIRRodJF4hFArDwyUHU/8qJBpMaooa3UzVH2VpSb+2PHMoQkhkH9jibov1P+tL3CBMd82gdFXfvn3BzKobVVUVcZfOS6x6+yh24Lz/Rf5+GPZ7AXRAgQENTc4btNMeIcRESIJz2OxHSKMDfaGrnWG7+Oz4N2/f1CGYOh0SkaXM0mzWF7/TSRKRVSor+3/PZBD22vY6SjpZJVmSEkUSZe9HaTEcg3ys+lktFA/X6+fnJ76CJXFKEMysOpNwNYyaORSBFAo/5+ZO+e0Q7PcC6IACAxqacglxj4SISEUGxUiZk/y2JLPs6tWrlDIolyt/pP6IQTKckNNXjUMiUmRjVoJGgsg8H4HQBPO53p3bIYSYDOaSbksCIgJwGCd6s5HGgX169qd2PYvHZa9pBQt0VQOS/zFTei1EhAJEaPT5jd27d5uamrJYLAcHh3/++Udim+PHj9vZ2SkpKenp6f344485OTkiDU6cOEEQhK+vb2NLC9SfV+XkE06neI5ZOKfHWU6/cE6Pc5zeSziLdrD9zyDvI5ei/vrrL7qxpVCl0D2rO6dSWtp7EUhEljPKS5n/7awqZZZS2bPojLEcu6jnD9RpX+O+W923aitpUyW6Srrb3Lct8xjl3EFDeg5GbFp17tzZ1NQUJgYbA1Ud3TrXAt8mjRuJ4+TJk+PGjdu9e7erq+u+ffsOHjyYlJRkZGREb3P37l03N7dt27b5+Pi8f/9++vTpnTp1OnfuHNUgNTXV1dW1ffv26urq58+flz4iROJoXt6WlLvc59dUO/LBddXSz+LlJCJLGaWIQOIhAcVDNOGSGO2YD0ofxOO+i3DY87C4OVVTTi+geamqqvh17HCJs4gEgzHn6Gk5OYWmlwpoRmp9nzfuD8mtW7dOmjRp8uTJlpaW27dvNzQ03LNnj0ibmJgYExOTOXPmmJqa9ujRY9q0aQ8fPqRqBQLBmDFjVq5c2b59+0YVFWgQigUCKbWVTMlT1gQilIRKydxkRNNY1PFL3kvJxhaBstnZ7zjvcpVyCTHfRAIRukq69tr24sMxGcyuul2923t31e0K2qspEQoF6YlP+FGR6YlPhELRPxU5OQWH730lXugw0Be0FyBOI66BVVRUxMXFLVmyhCrp378/9oqm4+LisnTp0rCwsAEDBmRlZZ0+fXrgwIFU7apVq7S0tCZNmlTT9CNCqLy8vLy8HB/X0xHgm0XGtFg1QTllvCqte3jAYvniGO0YeszcUmYpzvr4TP2ZRGMLm2UTrCaEJobSV7Zw+eJui0E/tRxqCidPb+M2diJCiL4PjGAwHAb64nIAEKERFVh2drZAINDR0aFKdHR0MjNF12ldXFyOHz8+YsSIsrKyqqqqQYMG7dy5E1dFRUUdOnQoPj5e+kDr1q1buXJlg8r+bSExLZZIAFwp0Hcff+KoIAePuolRxizLZmdLnBhUY6llE9UvPgbBEP77dsNu7n2N+9pq2YrkSsbldZMEaHDEw8kX52Zf2LoWh5Onl7uNneg6ciw9EgfYXkBNNLoXIn1uhyRJ8amepKSkOXPmrFixwtPTMyMjY9GiRdOnTz906FBRUdHYsWMPHDigqakpfYjAwMCAgAB8XFhYaGho2LC30LYJf5bx07FH9IXQzIKyn449ogfAFYHuBF9SUvLXX3/VU4YvPOAJ9EUoDUToKOlcHnI5ITsBr1rZadpRx9QKVl/jvh6GHrCy1TIRCgW3QvdLrLp9ZH+Hrk4iDvFycgoOA32bQjKgldOICkxTU5PJZNJNrqysLLpBhlm3bp2rq+uiRYsQQra2tsrKyj179lyzZs3Hjx9TUlJwMlmEkFAoRAjJycm9ePGiQ4cvNsMqKioqKtaYbwmQgkBIrryYJOLGg09XXkzCAXBFLhGJ9oS+dGeXEVk84BFtJlBBToHuiyHul4H+Xdn6KjGApgHCyQONRCM6cSgoKDg4OFy/fp0quX79uouL6M75kpKSLzJHMJkIIZIkLSwsnj59Gv8vgwYN8vDwiI+PBwOrAXmQnJtRUEYgUpdRaMrI0WUUEv8uI2UUlD1IzhVp/yzx2alTp0QWGuugveinNXnAI4R0lHS2um+FmcDWDoSTBxqJxp1CDAgIGDdunKOjo7Oz8/79+9PS0qZPn44QCgwMfP/+/e+//44Q8vHxmTJlyp49e/AU4rx587p166avr48QsrGxobpSVVUVKQHqT2ZhmREj10k+TZmoxCWfSfn7lUZpQnVcS7UUCAX7n+xPvZSqiBTrmcixlFmaoJ5QwayoyQN+pt1MI54RzAS2GSCcPNBINK4CGzFiRE5OzqpVqzIyMmxsbMLCwnD6voyMjLS0NNzG39+/qKho165dCxYsUFVV7d2794YNGxpVqm8ZoVCYnJKa8DazhJRrb2KS/ualh/wbegMlVOkh/+Z2JUoTqucWV/t23ki9ERwdLF8g71blJr1/eUGVlNoklTjEeV/Tni2EkK6SLjhftD0MLK0hnDzQGDTuRuamBzYyS4FKrIVPP5NycgRSIEWzk5AIfSblz5TbbfXrMsS+3Y3UG/Mj5iOE2hW3c/pUe7SnfLZyJUOOEMorFRsjRhUhlJer4hCIuN3+QKFCgnh7HbbOcLPhYHK1bcS9EDHiXogAQFHr+xxiIbY+8J6tj4Ul8iW57bgEj8uVEvWc8hjMycmJiIig57tSQlUEEk0LiQs4RKW+8hNdFWeBUEAlgZQxM5ZqyWeEEC/fSrFcmZICIaRQkYMUEEJIVVF1efflaiw18BhsAwiFAlkC7HZychkU8DN9HxiEkwfqDyiwVgbesyVf9AEvXMUihGpO7yviMUh+mUxLemItnto/Rcyuj7JUqc1V2azsEmaJxGhPJCIZ/zoEMYSKnMIOiuWimx+GWvki1YquOl0h/kWbQZa9yRSdnFw6dHWCcPJAAwJTiK0JvGfLkJGLF65ENJCfnx9dh4nnh/wqInUj5TTk5trPDbwbSBXqf9bvntUdiUcm1IrBThlyVazPzPJ5jvN4Cry8sjw1lpqFugWTwZRXZKrqKNVZGKAFArOCQGMDU4htB7xnCyHSST4NSbKfwsPDLSws8FxiffJD/retuATllX/h4vxB+UNN0Z7wqa6S7s/ghfEN8LV7kwGgMQAF1mrAe7Z0GUWUy7sIhYWFqampOENVamqq7GEhpWwrVlNUE0kC+UH5g0i0Jx0lnZlm4Pj+bQF7k4GWACiwVkNWURlCiI0kay9McXGxyIF0SERWMCoEhKAmi0pHWUdCEkgCZbOzleWVh3Yc6mHkAUrrGwT2JgMtAVBgrQOhUCj3OduUkcOuwfzCcDgckQMpYIX0SPORxPi5OAghVk5b3bfSQ+WqKKiMtRw7xXYK6K1vFtibDLQEQIE1OvXMVIJozoRuCgghJCQRIWkNjKXMuph7kcgnuup07WLQpVyuXKFKQdxjkCqhG1v0+LkUVDoSCJX7LSCjQzwG9iYDLQFQYI1LPTOVIEnOhFj/0Hd0YVvqtvLtD88+IIT2o/3K8soq6irds7qLr28lqiYWyxdLyWKMEFJnqS/vvpzuiwGhcts2X+UQjxBiMJi9/adK9EL0mDAVPDiApgHc6BsR8UwlWF/ImKkEh93avn27uDsGSSISIcqWK2GW0BeuKPQ/69M9BkWaMQgGSZIioXURQmqKajeG31CAJEzfDHV2iBdRe7A3GWhYwI2+2ah/phIej2dvby/RmZAgEIFQvFp8uVy5FFtK3GOQnsu4pkTGK5xXgPb6dqiPQzzsTQaaF1BgjQX2epdYhTOVOHfQoBeKTxUWFhZGRERIGaJcrvwd510tchAS1rd0lHSWdFsCiYwBVG+HeAaDCR7zQHMBCqyxoOciqbW2bvuOZQxOKMJMu5mUAyF4ZwDgEA+0XkCBNRZULhJZaqXvOxZPefxfsIzaUFNUo6JpSExWAt4Z3zjgEA+0XkCBNRbqytKWkURqa913LCVYhhR0lHTChoQlZCeAgQXUBDjEA60XyTk4gPqjq8KWvVb6vuMk1aRSZil1WsosjdGOEfc5FGdJtyUKcgpddbt6t/eGGPCARLBDvMQqcIgHWjhggYlS/33HmG6m6noqLIl+HHoqrG6m6vQSY2NjLo9bVFgk0hJPFT5Xff5c9blEZ8KaUFVUDXIOAneMb5Cv2o+MgWRdQCsFFNgX1H/fMQWTQQT5WInsA0MIEQit+N4iLTUFb/ZqZ9guPjv+dtrt+9z7NoU2SCxTCTVVKDFYhgh9jfq2V20PObe+Wb52PzIFOMQDrRHYyPwfddh3LEufIhpxtj0rM/E+5bJRLlf+SP0Rng+Uvu+4Vra4belv0r9ucgJtAEjQBbQxan2fgwKrRiAke2y4JT7jRyCkq8K6u7i39LlEkQgaOCkX1TM1J8kt+3j6ry82e1UnhKTWtEj0VVOFGInuhcA3hVAoODBzUk2+GJN3HQKLCmh1QCQOWalp3zFZw75jOuIRNLy8vKjkyEwGga8VCoXbtoeKXIsDYdjl2H1Q+oAIyfuOxcFXzbSDLFxANZCgC/gGAQVWDc62VYdaiRE0Tp065efnh3WYQCh4+PHhg4wHaalpyoXK4j0QiFASKGmWacqiujAQMgMQAfYjA98goMCq0eQo1qFWSgSN8PBwCwuLW+m3gqODCyoKEELtits5IaeahmAJWNIl3NRrkwZbA3Z0tXmEQkF64tP0pKcEQu2sOxtadZZl9g/2IwPfIKDA/kX6UmANtVIiaBQWFu68tfPg+4NUifTIT1JqYYnr2+HV/ehr+3eWFf+7oeLsSRaH23/q7Fq9MGA/MvANAgqsmuzP0iI/1VQrPYJG+ItwRNugnM3KLmGWsAXsWuNCwRLXt4lEN8Ky4qILW9fW6kkICbqAbxCIxFGNNlfaDF5NtdIjaIgaVQRK0EhA/3oeYiTGhdJR0tnmvm16l+kQQePbQSgU3AzZV1PtrSP7hUKB9B7wfmSOuiZVwtXQBB96oA0DFlg1OHBGZkGZ+L5j3X8DZ4j7yrczbMdgMQRlAhmD7X5Q/hCjHUPf7FXKLKU2e6kpqn3f/nsPIw8wub5B3vMTP+fl1FRbLJsnIexHBr4pQIFVQwXOIGgLXlgpBflYMRmEuK+8noPejnc7VHgq3cu6yx5st6Ykk/QsJ8A3SK2OgjJ6EkKCLuDbAaYQ/8PLRm/PWHtdlf9mC3VVWDgMB/aVp/trFBQWPL/9XKVABRtVXxdsl0DZ7Ox3nHfZ7GxEIF0lXTxhCNrrW6ZWR0HwJAQAEcAC+wIvG71+VroPknMzCz8XCF9qqpZpKL+rrNIU95Wnb0CuyaiSDkwYflPUGmPXwNJaWU2jpllEDngSAoAYoMAkEJcdcfTVthJBAT41I806F3YWb/bFBmTZImgghJTllYd2HAp665tClhi7DAazz4/TJLoRIoR6gychAIgBCuwLwp9l/ByxroJzm6CZUCWfS6RcUusGZIp+Rv38zP3Aq/BbQ9w5vjg3W6JnPHYj/GIfGEIsLq//lFngSQgA4oAC+4/wZxmz/g5lGdwWKa/DBmRVBVVFOcWPJR/xKexE/mYRCgW3QvdLrLp9ZH+Hrk4idhV2I6xDJA4A+AYBBVaNQEgGX3ymqPv3f7YXFRieUSbjBmQMgYgglyAPQ49HWY8g8tM3Th1i7DIYTOPOXYw7d2l04QCglQMKrJoHybmfKvlKcp/xqUhqrnKGaCSOmnzl6amQu+p2bWyxgRYOxNgFgMYDFFg1WUVlhFz1woP+Z/3uWd3ptQpCBYSQvKJ8ZXklLqFvQKbwMvFa33M9GFsABcTYBYDGAxRYNdpcFkMhGyGESGSXY4cQok8YYqd5lgLL3N388KPDZcyyT6xPdNtLWV55lcsqSIgMiAAxdgGg8YCNzNU4GKsoqseSJNIs01QSKBFiO7kIRBQVFTnoOgR8H8DQYFD1KgoqM+1mRo2MAu0FiINj7Eqsghi7AFBPwAKrJiH7MWIWELW5xRcXF/ft3BccNIBaNyZTYOd4+j4wroamxwTRfWAAAHwtoMCq+VTyCR9Id5rH4eeZDCY4aHzLyLIxmQ7E2AWAxgAUWDVaSlr4oKasXQghHo9nbGzc5KIBLQvZNybTgRi7ANDgwBpYNfba9jpKOgQiJGbtwnh5eTEY8MS+aaRvTK41ZRcAAA0IvI6rYTKYS7otQQgRiBAPMM/j8fz8/KysrJpPQKBFUOvG5CaWBwC+ZWAK8T/6Gvfd6r51/f31glwBg2TEasaqs9SHmwzvbtIdp69sbgGB5gc2JgNAywEU2Bfof9Yf8G5AUWH1jmYuj2vnZGdqatq8UgEtB9iYDAAtB7Aq/gNnraS0F0KoqLDo1KlTSUlJzSgV0KLAG5MlVsHGZABoYkCBVSMUCsWzVmLCw8OFQmETywO0TGBjMgC0HECBVZOamlpYWCixqrCwMDU1tYnlAVoseGMy3Q7jamhK96EHAKAxgDWwaoqLi+tcC3xrwMZkAGgJgAKrBofYqFst0AaQPTQUBjYmA0CzAwqsGmNjYx6PJ3EWEQJwtHm+NjQUAAAtAVgDq4bBYHh5eUmsggAcbRscGoq+PRmHhnp1P7oZpQIAoFbgvfwfVlZWfn5+PB6PKoEAHG0eCA0FAK0XmEL8AisrKzMzs9jY2Ly8PDU1ta5du8rJwSNqy9QaGgoWugCgxQJv5y9ISkoKDw+nVsLu3bvn5eUFFlgbBkJDAUDrBaYQ/wNH4qD7cRQWFkIkjrYNhIYCgNYLKLBqIBLHtwmEhgKA1gsosGogEse3CYSGAoDWCyiwaiASxzcLhIYCgFYKOHFUA5E4vmUgNBQAtEYa3QLbvXu3qakpi8VycHD4559/JLY5fvy4nZ2dkpKSnp7ejz/+mJOTg8sPHDjQs2dPNTU1NTW1vn37PnjwoPHkxJE4JFZBJI7WiFAoSE98wo+KTE98Ist2LhwaytLVzdDaFrQXALQKGleBnTx5ct68eUuXLn38+HHPnj0HDBiQlpYm0ubu3bvjx4+fNGlSYmLiX3/9FRsbO3nyZFwVERExatSo27dv37t3z8jIqH///u/fv28kUSESR1vi1f3oAzMnnVr1c9ivm06t+vnAzEkQVgMA2h4ESZKN17uTk5O9vf2ePXvwqaWlpa+v77p16+htNm/evGfPnjdv3uDTnTt3bty4MT09XaQrgUCgpqa2a9eu8ePHSxmxsLBQRUWloKCgJnNKOiL7wHg8HuwDa3Xg0FDi5bCsBQCti1rf541oWFRUVMTFxfXv358q6d+/f3S06A9hFxeXd+/ehYWFkST58ePH06dPDxw4ULy3kpKSyspKdXV18ary8vJCGvUUm67RG1W7A40BhIYCgG+HRlRg2dnZAoFAR0eHKtHR0cnMzBRp5uLicvz48REjRigoKOjq6qqqqu7cuVO8tyVLlhgYGPTt21e8at26dSr/YmhoWGeB8UbmoqIiqqSoqAg2Mrcuag0N1cTyAADQeDT60g5BENQxSZL0U0xSUtKcOXNWrFgRFxcXHh6enJw8ffp0kTYbN278888/z549y2KxxIcIDAws+BfxuUcZgY3MbQMIDQUA3w6N6EavqanJZDLpJldWVhbdIMOsW7fO1dV10aJFCCFbW1tlZeWePXuuWbNGT08PN9i8efPatWtv3Lhhays5rKqioqKiomI9pa11I7OpqWk9hwCaAAgNBQDfDo1ogSkoKDg4OFy/fp0quX79uouL6Cp6SUkJ3cePyWQi2uLTpk2bVq9eHR4e7ujo2HiiItjI3FaA0FAA8O3QuFOIAQEBBw8ePHz4MJ/Pnz9/flpaGp4eDAwMpJwJfXx8zp49u2fPnrdv30ZFRc2ZM6dbt276+voIoY0bNy5btuzw4cMmJiaZmZmZmZmNp0hgI3PbAEJDAcC3Q+NG4hgxYkROTs6qVasyMjJsbGzCwsLwjuCMjAxqQ5i/v39RUdGuXbsWLFigqqrau3fvDRs24Krdu3dXVFQMHz6c6jAoKCg4OLgxRMUbmSXOIsJG5tYFDg11K3Q/5c3B1dD0mDAVfOgBoI3RuPvAmp767APDXoji5ZCUuTUiFAogNBQAtGpqfZ+DAvsC2MgMAADQQqj1fQ7BfL/AysrKwsIiNTW1uLiYw+EYGxtDEKkWQlVVRcLVsPyPmao6unae3nJyCs0tEQAAzQxYYEArIPLY4bhL50myejceQTAcvvd1GzuxeaUCAKBRAQsMaPVEHjv88OJZeglJCnEJ6DAA+JaB+TFRhEJhcnLy06dPk5OTIQBHs1NVVRF36bzEqrjL56uqKppWHAAAWhBggX0BOHG0NBKuhlEzhyKQQmHC1TCHgb5NKxEAAC0FsMD+A7vR07eCFRYWQjDf5iX/o2j0Z9lrAQBo24ACqwaC+bZMVHV061wLAEDbBhRYNbUG821ieQCMnac3QUj+KyUYDDtP7yaWBwCAlgMosGoKaWnAvrYWaDzk5BQcvveVWOUw0Bd2gwHAtwwosGreFUnbDye9FmhU3MZOdPQZSrfDCAbD0Wco+NADwDcOeCFWU6mk/pmUV0KVIhk3SRJ9RgqVSurNJBeAEEJuYye6jhwLkTgAAKADCqwaHZ7S/UojD/k3JIkoHYajlDyoNBzGU2pG2QCE5xLBYx4AABqgwKrpZqpeydV/VlxsLfeRssFIhBKrdCq5+t1MwQJrYCBaPAAA9QQUWDVMBjHbnvUi+iO9kEDIRu7jMHtbJoOo6UKgDry6H03P18VR1+ztD/m6AAD4OsCJoxqhUJiZeJ8gEH0NDJ9mJt6HfWANyKv70Re2rqW0F0KoODf7wta1r+5HN6NUAAC0OkCBVQP7wJoGoVBwK3S/xKrbR/YLhYImlgcAgNYLKLBqiouL61wLyM57fiLd9qJTlJP9np/YxPIAANB6AQVWDYfDqXMtIDvF+Xl1rgUAAKADCqwaY2PjmnKm8Xg8Y2PjJpanrcJRVatzLQAAAB1QYNUwGAwvLy+JVV5eXgwGPKiGwcDSmqOuKbGKq6FpYGndxPIAANB6gffyf1hZWfn5+dHtMB6P5+fnB/nAGhAGg9nbf6rEKo8JU2E3GAAAskOQZJuK8ldYWKiiolJQUFDTfGCtCIXC1NTU4uJiDodjbGwMtldjILIPjKuh6TGhhe4DEwqFFRWQ9xkAGhcFBQXxl22t73NQYEDz0CoicVRUVCQnJ8MuQABobBgMhqmpqYLCFzFOa32fQyQOoHlgMJiG1rbNLYU0SJLMyMhgMpmGhoZgiANA4yEUCj98+JCRkWFkZEQQXxH2CBQYAEimqqqqpKREX19fSQlCOQNA46KlpfXhw4eqqip5eXnZr4LflQAgGYFAgBASmdMAAKAxwF80/KWTHVBgACCNr5rQAACgbtTtiwYKDAAAAGiVgAIDAAD4An9/f19f3+aWAqgdmRSYiYnJqlWr0tLSGlsaoPVSmV1a8b64LL0g/c7jF5cj0+88LksvqHhfXJld2tyitW6IGvD392/wsTIzM+fOnduxY0cWi6Wjo9OjR4+9e/eWlJQ0+EB1w93dXeQhVFVV1b/blJQUgiDi4+Opkh07doSGhta/Z6CxkckLccGCBaGhoatWrfLw8Jg0adKQIUMUFRUbWzKgFVGZXfpx80N8TCCkjBgIFWejJ7hEZ6GjvCa7+aRrUgRC8kFyblZRmTaX1c1Uvf6pUDMyMvDByZMnV6xY8eLFC3zKZv/3SCsrK7/Kd0sib9++dXV1VVVVXbt2befOnauqql6+fHn48GF9ff1BgwaJNG6QEevAlClTVq1aRZ3KyX3xBquoqGgQpxsVFZWvak+SpEAgEBEGaAJkssBmz54dFxcXFxdnZWU1Z84cPT29WbNmPXr0qLGFA1oLZLk03yHptW2J8GcZPTbcGnUgZu6J+FEHYnpsuBX+LKOefer+i4qKCkEQ+LisrExVVfXUqVPu7u4sFuvYsWPBwcFdunShrtq+fbuJiQl1GhISYmlpyWKxLCwsdu/eLXGgGTNmyMnJPXz40M/Pz9LSsnPnzsOGDbt8+bKPjw9uQBDE3r17Bw8erKysvGbNGoTQnj17OnTooKCgYG5ufvToUdxMxKDJz88nCCIiIgIhFBERQRDE5cuX7ezsWCyWk5PT06dPcbPU1FQfHx81NTVlZWVra+uwsDCJQiopKenSQAiZmJisWbPG399fRUVlypQpCKEzZ85YW1srKiqamJhs2bKFutbExGTt2rUTJ07kcrlGRkb791fnpTM1NUUIfffddwRBuLu7oy+nEEmS3LhxY/v27dlstp2d3enTp3E5vperV686OjoqKir+888/tXyQQCPwFWtgdnZ2O3bseP/+fVBQ0MGDB7t27WpnZ3f48OE2FssDqAPSE1F+I2kqw59l/HTsUUZBGVWSWVD207FH9ddhNbF48eI5c+bw+XxPT08pzQ4cOLB06dJffvmFz+evXbt2+fLlR44cEWmTk5Nz7dq1mTNnKisri1TR3cOCgoIGDx789OnTiRMnnjt3bu7cuQsWLHj27Nm0adN+/PHH27dvyyL2okWLNm/eHBsbq62tPWjQoMrKSoTQzJkzy8vL79y58/Tp0w0bNnxVAqNNmzbZ2NjExcUtX748Li7Oz89v5MiRT58+DQ4OXr58OX0ycMuWLY6Ojo8fP54xY8ZPP/30/PlzhNCDBw8QQjdu3MjIyDh79qxI58uWLQsJCdmzZ09iYuL8+fPHjh0bGRlJ1f7vf/9bt24dn8+3tW3Ru/LbKl9h81ZWVp47dy4kJOT69evdu3efNGnShw8fli5deuPGjT/++KPxRARaPp+S30qZKfuU/NbQ8Lumk6Y5EAjJlReTRH7KkQgRCK28mNTPSrf+c4nizJs3b+jQobU2W7169ZYtW3BLU1PTpKSkffv2TZgwgd7m9evXJEmam5tTJZqammVlZQihmTNnbtiwAReOHj164sSJ1LG/v/+MGTMQQgEBATExMZs3b/bw8KhVnqCgoH79+iGEjhw50q5du3Pnzvn5+aWlpQ0bNqxz584Iofbt29d07e7duw8ePIiPp02bhg2s3r17L1y4EBeOGTOmT58+y5cvRwiZmZklJSVt2rSJWi/09vbGAi9evHjbtm0REREWFhZaWloIIQ0NDWzS0fn8+fPWrVtv3brl7OyMBbt79+6+ffvc3Nxwg1WrVuF7AZoFmRTYo0ePQkJC/vzzTyaTOW7cuG3btllYWOCq/v379+rVqzElBFoBJUWFyjVb8yVFhU0pTLPwIDmXbntRkAhlFJQ9SM517qDR4IM6OjrW2ubTp0/p6emTJk3C02sIoaqqqprWeOjG1oMHD4RC4ZgxY8rLyyWOyOfzp079L7GAq6vrjh07ZBEbKwOEkLq6urm5OZ/PRwjNmTPnp59+unbtWt++fYcNG1aTQTNmzJilS5fiY1VVVYlSDR48mC7V9u3bBQIBk8lECFHd4snYrKws6aImJSWVlZXRVVRFRcV33/33a0yWjwBoPGRSYF27du3Xr9+ePXt8fX1FVm6trKxGjhzZOLIBrQYlLg+hYqm1bZysIgnaS8baOkOf7mMwGPTJfDwvhxDCkYgPHDjg5ORE1eK3OZ2OHTsSBIGn1DDYDKK7ioiMiL5UeCRJ4lMcN5IShpKkJvBVkydP9vT0vHz58rVr19atW7dly5bZs2eLN1ZRUenYsaNIIV0qSgzqlN6S/voiCKLWMM24weXLlw0MDKhCugub+Iwr0JTItAb29u3b8PDwH374QdzvSFlZOSQkpBEEA1oTWqY1zvnUWts20Oay6lzbIGhpaWVmZlLva8qHQkdHx8DA4O3btx1pYLcFOhoaGv369du1a9fnz59lHNHS0vLu3bvUaXR0tKWlJZYE0Zwn6e7pmJiYGHyQl5f38uVLajrH0NBw+vTpZ8+eXbBgwYEDB2QUQwQrKysRqczMzMQVNh0pQYysrKwUFRXT0tLoT8/Q0LBusgENjkwWWFZWVmZmJv0X3P3795lMJpjPAEZ6MpSWmSqlYelmqq6nwsosKBNZBiMQ0lVhdTNVb2wB3N3dP336tHHjxuHDh4eHh1+5coXKQBEcHDxnzhwejzdgwIDy8vKHDx/m5eUFBASI9LB7925XV1dHR8fg4GBbW1sGgxEbG/v8+XMHBweJIy5atMjPz8/e3r5Pnz4XL148e/bsjRs3EEJsNrt79+7r1683MTHJzs5etmyZyIWrVq3S0NDQ0dFZunSppqYm9vebN2/egAEDzMzM8vLybt26hXVhHViwYEHXrl1Xr149YsSIe/fu7dq1qyavSwptbW02mx0eHt6uXTsWi0WfX+VyuQsXLpw/f75QKOzRo0dhYWF0dDSHwxFZQQSaC5kssJkzZ6anp9NL3r9/P3PmzMYRCWh9EIrSVJT02rYBk0EE+VghhOiuGvg4yMeqMTw4RLC0tNy9e/dvv/1mZ2f34MEDyqkBITR58uSDBw+GhoZ27tzZzc0tNDRU3AJDCHXo0OHx48d9+/YNDAy0s7NzdHTcuXPnwoULV69eLXFEX1/fHTt2bNq0ydraet++fSEhIdgHHSF0+PDhyspKR0fHuXPnYod7OuvXr587d66Dg0NGRsaFCxcoA2jmzJmWlpZeXl7m5ua1ap2asLe3P3Xq1IkTJ2xsbFasWLFq1apad3zLycn9+uuv+/bt09fXp6+fYVavXr1ixYp169ZZWlp6enpevHhR4tMDmgWZElpyOJwnT57QXYOSk5NtbW2LiooaU7a6AAktm4vK7FKyXCAUCj4lvy0pKlTi8rRM2zMYTEKR2Up3MZeVlSUnJ5uamrJYsk4Ahj/LWHkxifLm0FNhBflYednoNZqMrYyIiAgPD4+8vDzK/wIAMBK/bg2T0FJRUfHjx490BZaRkQHbzgE6lJZq8x7zUvCy0etnpduwkTgAAKgJmZRQv379AgMD//77bzw7nJ+f//PPP8PuBwAQh8kgGsNjHgAAcWRSYFu2bOnVq5exsTHeABEfH6+jo0NFjgEAAJAFd3d3CNwDNCAyKTADA4MnT54cP348ISGBzWb/+OOPo0aNapZQngAAAACAkXUdS1lZmb7rHmjDCIWC9/zE4vw8jqqagaX1t+AEDwBAa+QrHDGSkpLS0tIqKiqoEvEkC0Br59X96Fuh+4tzs/EpR12zt//UTk4uzSsVAACAODIpsLdv3w4ZMuTp06cEUe12j4O1SNy7DrReXt2PvrB1Lb2kODf7wta1gwJ+Bh0GAEBLQ6aNzHPnzjU1Nf348aOSklJiYuKdO3ccHR1xgh+gzSAUCm6F7pdYdfvI/m8kJQoAAK0ImRTYvXv3Vq1apaWlxWAwGAxGjx491q1bN2fOnMYWDmhK3vMTqZlDEYpyst/zE5tYHgAAAOnIpMAEAgHOL6epqfnhwweEkLGxMZXaHGgbFOfn1bkWAFoR7u7u8+bNa6TOcabm/Pz8RuqfDj35dVOO23KQSYHZ2Ng8efIEIeTk5LRx48aoqKhVq1ZJSToHtEY4qmp1rgUaD6IGag3xVwcyMzPnzp3bsWNHFoulo6PTo0ePvXv3lpSUNPhAdcPExGT79u30ku3bt5uYmDTGWK1OH7i4uGRkZNSU6Q3TqJq7WZDJiWPZsmU4ycKaNWu+//77nj17amhonDx5spFlA5oUA0trjrqmxFlEroamgaV104vUysh5g8olRQdV5CKNDnXulcpLcvLkyRUrVlAzH/RMXZWVlfXfl/n27VtXV1dVVdW1a9d27ty5qqrq5cuXhw8f1tfXF/c3bpARAYnU7dkqKCiIZ5RuECoqKnDA5RaITBaYp6cnzkfevn37pKSk7OzsrKys3r17N7JsQJPCYDB7+0ve6ucxYSrsBquFnDdopz3a7ybh3057lPOmzh3r/ouKigrOI6yrq1tWVqaqqnrq1Cl3d3cWi3Xs2LHg4OAuXbpQV4mYJiEhIZaWliwWy8LCoqZA7zNmzJCTk3v48KGfn5+lpWXnzp2HDRt2+fJlHx8f3IAgiL179w4ePFhZWRnHmN+zZ0+HDh0UFBTMzc2p0Dz0eS2EUH5+PkEQ2OcLmzWXL1+2s7NjsVhOTk5Pnz7FzVJTU318fNTU1JSVla2trcPCwr72Qfn7+/v6+q5cuVJbW5vH402bNo3a8/P58+fx48dzOBw9Pb0tW7bQrzp27JijoyOXy9XV1R09ejTO0ZySkuLh4YEQUlNTo4xdkiQ3btzYvn17NpttZ2d3+vRpqpOwsDAzMzM2m+3h4ZGSklKThARB7NmzZ8CAAWw229TU9K+//qI/MfqniWr+yB48ePDdd9+xWCxHR8fHjx9T5SImY1RUlJubm5KSkpqamqenZ15enr+/f2Rk5I4dO7AFj+WMjIzs1q2boqKinp7ekiVLqqqq8OXu7u6zZs0KCAjQ1NRsyVEDa1dgVVVVcnJyz549o0rU1dXpOU+BNkMnJ5dBAT9z1DWpEq6GJvjQy4RE20vG2rqyePHiOXPm8Pl8T09PKc0OHDiwdOnSX375hc/nr127dvny5UeOHBFpk5OTc+3atZkzZ4qnGKZ/2YOCggYPHvz06dOJEyeeO3du7ty5CxYsePbs2bRp03788cfbt2/LIvaiRYs2b94cGxurra09aNAgnLJ55syZ5eXld+7cefr06YYNG/Ci+9dy8+ZNPp9/+/btP//889y5cytXrqRGvH379rlz565duxYREREXF0ddUlFRsXr16oSEhPPnzycnJ2NdZWhoeObMGYTQixcvMjIyduzYgRBatmxZSEjInj17EhMT58+fP3bs2MjISIRQenr60KFDvb294+PjJ0+evGTJEikSLl++fNiwYQkJCWPHjh01ahSfz6eq6J9mTR/Z58+fv//+e3Nz87i4uODgYHrSHDrx8fF9+vSxtra+d+/e3bt3fXx8BALBjh07nJ2dp0yZkpGRkZGRYWho+P79e29v765duyYkJOzZs+fQoUP03DdHjhyRk5OLiorat29fHT6LJoKUgfbt28fHx8vSstkpKChACBUUFDS3IK0YgaAq7VlC0t2ItGcJAkFVc4vTbJSWliYlJZWWlsrU+v1jMohX47/3j+svT0hIiIqKCj5OTk5GCG3fvp2qDQoKsrOzo063bdtmbGyMjw0NDf/44w+qavXq1c7OziKd4yzJZ8+epUo0NDSUlZWVlZX/97//4RKE0Lx586gGLi4uU6ZMoU5/+OEHb29vSrbHjx/j8ry8PITQ7du3SZLEGu7EiRO4Kicnh81mnzx5kiTJzp07BwcHS38CxsbG27Zto5fQb3PChAnq6uqfP3/Gp3v27OFwOAKBoKioSEFBQWTQuXPnivf/4MEDhFBRURElal5eHq4qLi5msVjR0dFU40mTJo0aNYokycDAQEtLS6FQiMsXL15Mv5AOQmj69OnUqZOT008//URK+jRr+sj27dsnco/Uo6YLPGrUKFdXV3EB3Nzc6Df+888/m5ubU5L/9ttv+Inhll26dBHvofGQ+HWr9X0u6xpYYGDgsWPH1NUbPbEs0OwwGExDa9vmlgKoHVlSon/69Ck9PX3SpElTpkzBJVVVVTUt9dONrQcPHgiFwjFjxpSXl0sckc/n08PLubq6YkulVpydnfGBurq6ubk5tkLmzJnz008/Xbt2rW/fvsOGDbO1rctfoJ2dnZKSEjVKcXFxenp6fn5+RUWFyKDUJY8fPw4ODo6Pj8/NzRUKhQihtLQ0KysrkZ6TkpLKysrok2kVFRU4uDmfz+/evTv16KiBpN87PqYmWhHt2Ur5yPh8vsg9ShwlPj7+hx9+kCIGhs/nOzs7U5K7uroWFxe/e/fOyMgIyfbX1ezIpMB+/fXX169f6+vrGxsb02cYHj161GiCAQBQC/QvI4PBIGmB3vG8HEIIv5QPHDjg5ORE1TKZoiuaHTt2JAji+fPnVAl2M6a7ioiMiL5UeCRJ4lMGg4FPRSSpCXzV5MmTPT09L1++fO3atXXr1m3ZsmX27NkiLXk8Hv5JTpGfny/d744KHiSRz58/9+/fv3///seOHdPS0kpLS/P09KRHy6PAj/Hy5csGBgZUoaKiIv1O6wD9AVLPVspHJuNYIp9aTVAfGXVKF0l8MrkFIpMC8/X1bWQxAACoF1paWpmZmdQrifppr6OjY2Bg8Pbt2zFjxki5XENDo1+/frt27Zo9e7aMby5LS8u7d++OHz8en0ZHR1taWmJJEEIZGRlU9iWRC2NiYvBv/Ly8vJcvX1pYWOByQ0PD6dOnT58+PTAw8MCBA+IKzMLCIjY2ll4SGxtLN6cSEhJKS0vx6zsmJobD4bRr105dXV1eXl5kUDc3N4TQ8+fPs7Oz169fb2hoiBB6+PAh1RX2u6Oi5VlZWSkqKqalpeEL6VhZWZ0/f55+d1IeWkxMDPXEYmJi8CMSQcpHZmVldfToUfo9ShzF1tb25s2b1BIg/abo8f+srKzOnDlD/c1ER0dzuVy6hm75yKTAgoKCGlsOAADqg7u7+6dPnzZu3Dh8+PDw8PArV65QWdiDg4PnzJnD4/EGDBhQXl7+8OHDvLy8gIAAkR52797t6urq6OgYHBxsa2vLYDBiY2OfP3/u4OAgccRFixb5+fnZ29v36dPn4sWLZ8+evXHjBkKIzWZ37959/fr1JiYm2dnZy5YtE7lw1apVGhoaOjo6S5cu1dTUxL+P582bN2DAADMzs7y8vFu3bmFdKEJAQICrq+uqVauGDx+OEDpz5kx4eHh0dDTVoKKiYtKkScuWLUtNTQ0KCpo1axaDweBwOJMmTVq0aBE1KLYREUJGRkYKCgo7d+6cPn36s2fPVq9eTXVlbGxMEMSlS5e8vb3ZbDaXy124cOH8+fOFQmGPHj0KCwujo6M5HM6ECROmT5++ZcuWgICAadOmxcXFhYaGSvmY/vrrL0dHxx49ehw/fvzBgweHDh2S2Kymj2z06NFLly7F95iSkrJ582aJlwcGBnbu3HnGjBnTp09XUFC4ffv2Dz/8oKmpaWJicv/+/ZSUFA6Ho66uPmPGjO3bt8+ePXvWrFkvXrwICgoKCAigHk7roLGW5JoJcOIAGoqW78RBOUpg9uzZY2hoqKysPH78+F9++YXybiBJ8vjx4126dFFQUFBTU+vVqxfdWYPOhw8fZs2aZWpqKi8vz+FwunXrtmnTJsplACF07tw5evvdu3e3b99eXl7ezMzs999/p8qTkpK6d+/OZrO7dOly7do19KUTx8WLF62trRUUFLp27Up5h82aNatDhw6KiopaWlrjxo3Lzs6WKOH169d79uyppqampqbWo0eP69evU1UTJkwYPHjwihUrNDQ0OBzO5MmTy8rKcFVRUdHYsWOVlJR0dHQ2btxI92X4448/TExMFBUVnZ2dL1y4QH+qq1at0tXVJQhiwoQJJEkKhcIdO3aYm5vLy8traWl5enpGRkbilhcvXuzYsaOiomLPnj0PHz6Manbi+O233/r166eoqGhsbPznn3/icomfZk0f2b179+zs7BQUFLp06YJdJcWdOEiSjIiIcHFxUVRUVFVVxW70JEm+ePECfy4IoeTkZNysa9eueA/Z4sWLKysr8eUi7h5NQN2cOGRSYARBMCQhy7W//fYb/vuwt7e/c+eOxDbHjh2ztbVls9m6urr+/v70v93Tp09bWloqKChYWlrW9K2jAwoMaCi+ToFlv5amwLJfN7KwrQORl2zDghVYY/TcUIj/AgAoGtEL8dy5c9RxZWXl48ePjxw5Ij7BKs7JkyfnzZuHpyb27ds3YMCApKQkPBNNgafRt23b5uPj8/79++nTp0+ePBmPeO/evREjRqxevXrIkCHnzp3z8/O7e/cufWETAFoKGh3Q7EeNEYkDAIAaqZu2PH78+KBBg2pt1q1bN/q+BwsLiyVLloi02bRpU/v27anTX3/9tV27dvjYz8/Py8uLqvL09Bw5cqT0EcECAxqKr7PAABkACwwssJqomwVWx/U6JycnvGArhYqKiri4uP79+1Ml/fv3p6+4YlxcXN69excWFkaS5MePH0+fPj1w4EBcde/ePfrlnp6e4pcjhMrLywtp1O2Ovh2EQkF64hN+VGR64hPI8gU0Je7u7iRJqqqqNkbnoaGhdG/AFghJkuDR3bDINIUoQmlp6c6dO9u1aye9WXZ2tkAg0NHRoUp0dHQyMzNFmrm4uBw/fnzEiBFlZWVVVVWDBg3auXMnrsrMzKz1coTQunXrZJnPBBBCr+5H3wrdT0Xs5ahr9vafCpGiAABojchkgampqan/i5qaGpfLPXz48KZNm2S5VuJWRzpJSUlz5sxZsWJFXFxceHh4cnLy9OnTZb8cIRQYGFjwL+np6bJI9W3y6n70ha1r6fHmi3OzL2xd++q+BLsWAACghSOTBbZt2zZKczAYDC0tLScnJzW1WhJEaWpqMplMus2UlZVFt6gw69atc3V1XbRoEULI1tZWWVm5Z8+ea9as0dPT09XVrfVyhJCioiLeEg9IQSgU3ArdL7Hq9pH9Hbo6Qbx5AABaFzIpsLqlzlNQUHBwcLh+/fqQIUNwyfXr1wcPHizSrKSkRE7uPzHoEVOcnZ2vX78+f/58XHXt2jUXF5jsqiPv+YkSc30hhIpyst/zEyH+IQAArQuZFFhISAiHw6FHh/zrr79KSkomTJgg/cKAgIBx48Y5Ojo6Ozvv378/LS0NTw8GBga+f//+999/Rwj5+PhMmTJlz549np6eGRkZ8+bN69atm76+PkJo7ty5vXr12rBhw+DBg//+++8bN27cvXu37vf6bVOcn1fnWgAAgBaITGtg69ev19TUpJdoa2uvXbu21gtHjBixffv2VatWdenS5c6dO2FhYcbGxgihjIyMtLQ03Mbf33/r1q27du2ysbH54YcfzM3Nz549i6tcXFxOnDgREhJia2sbGhp68uRJ2ARWZziq0qZ8pdcCAAC0QKSFaqZgsVjPnz+nJ3hNSUmxtLQsLS1tRNHqRGFhoYqKSkFBARUIDsAIhYIDMydJnEXkamhO3nUI1sBEKCsrS05ONjU1ZbFYzS1LW4AgiHPnztXHj9zd3b1Lly7bt29vMJm+koiICA8Pj7y8vEbaCfAtI/HrVuv7XCYLTFtb+8mTJ/SShIQEDQ2N+ogLNDEMBrO3/1SJVR4TpoL2asn4+/sT/6KhoeHl5SXyfWyBBAcHd+nSpWnGCg0NJb7k4MGDDdKzu7v7vHnzqFMXF5eMjAzpCVyApkQmBTZy5Mg5c+bcvn1bIBAIBIJbt27NnTt35MiRjS0c0LB0cnIZFPAzR/2/2WCuhuaggJ9hH1gDIhAKYjNjw96GxWbGChpun7iXlxfOBH/z5k05Obnvv/++oXpuG/B4vAwaIolIas1JJiM46K3EzTw1ITG7GNBgyBLko7y83M/PjyAIeXl5eXl5JpP5448/lpeX1zlqSOMBoaRqRSCoSnuWkHQ3Iu1ZgkBQ1dzitFzqEErqesr1Pqf62ITa4H99TvW5nnK99stqQyRI0p07dxBCWVlZ+PR///tfp06d2Gy2qanpsmXLKioqcHl8fLy7uzuHw+Fyufb29rGxsbg8KiqqZ8+eLBarXbt2s2fPLi4uFh8xKCjIzs7u0KFDOLz99OnTq6qqNmzYoKOjo6WltWbNGqplfn7+lClTtLS0uFyuh4cHji4fEhJCf8mEhISQJIkQOnDggK+vL5vN7tix499//011UlNM9OLi4nHjxikrK+vq6m7evLmmEOn0OP3it2BqakoQhFAoTE1NHTRokLKyMpfL/eGHH3D6NKrl77//bmxszOPxRowYUVhYiB87/S6Sk5NFQmHV9CSNjY1Xr149YcIEHo83fvx4aR8t8C+NGI0e8/Lly1OnTl28eDElJaXuYjYyoMCAhuJrFdj1lOudQztT2ssm1KZzaOfOoZ3rr8PoCqyoqGjatGkdO3YUCAS4ZPXq1VFRUcnJyRcuXNDR0dmwYQMut7a2Hjt2LJ/Px99crFqePHnC4XC2bdv28uXLqKio7777zt/fX3zEoKAgDoczfPjwxMTECxcuKCgoeHp6zp49+/nz5zhdyL1790iSFAqFrq6uPj4+sbGxL1++XLBggYaGRk5OTklJyYIFC6ytrbE9VFJSQpIkQqhdu3Z//PHHq1ev5syZw+FwcnJySJJ89+6dkpLSjBkz+Hz+uXPnNDU1g4KCsBg//fRTu3btrl279uTJk++//57D4XyVAlNWVvb09Hz06FFCQoJQKPzuu+969Ojx8OHDmJgYe3t7Nzc3+s0OHTr06dOnd+7c0dXV/fnnn0mSzM/Pd3Z2njJlCr6LqqoqugKT8iSxIty0adOrV69evXr11Z/3N0mjK7BWASgwoKH4KgVWJaii2150Hdb3VN+q+lm6EyZMYDKZysrKOFeynp5eXFycxJYbN250cHDAx1wuNzQ0VKTBuHHjpk6dSp3+888/DAZD/B6DgoKUlJSwIUKSpKenp4mJCaUyzc3N161bR5LkzZs3eTwelXaLJMkOHTrs27eP/NesofeJEFq2bBk+Li4uJgjiypUrJEn+/PPP5ubmQqEQV/32228cDkcgEBQVFSkoKJw4cQKX5+TksNnsmhQYQkj5X3R0dLAA8vLylJ167do1JpOZlpaGTxMTExFCDx48EL/ZRYsWOTk54WMRm4+uwKQ8SWNjY19fX3E5ASk0YjqV4cOHOzo6LlmyhCrZtGnTgwcP/vrrr7rMWgJAm+NR1qOPJR/Fy0lEZpZkPsp61FW3a3369/Dw2LNnD0IoNzd39+7dAwYMePDgAd6Ucvr06e3bt79+/bq4uLiqqory1woICJg8efLRo0f79u37ww8/dOjQASEUFxf3+vXr48ePV4tHkkKhMDk5WTwDsomJCZfLxcc6OjpMJpPK1aujo5OVlYV7Ky4upvtzlZaWvnnzpqa7sLWt3iyP5/FwJ3w+39nZmVpYcnV1LS4ufvfuXV5eXkVFhbOzMy5XV1c3NzevqWcul/vo0SN8TMlpbGyspaWFj/l8vqGhoaGhIT61srJSVVXl8/ldu3YVuVk9PT0smHSkP0lHR8daewDqj0wKLDIyMigoiF7i5eVVUzZrAPgG+VTyqc61sqCsrNyxY0d87ODgoKKicuDAgTVr1sTExIwcOXLlypWenp4qKionTpzYsmULbhYcHDx69OjLly9fuXIlKCjoxIkTQ4YMEQqF06ZNmzNnDr1zkRR9GHl5eeoYr3/TT4VCIUJIKBTq6elFRETQL5TiYi6xE/LLGKckSeJaUoYdPhQMBoN6PhTYYKW6FXG+oJdIFEw60p8kfWig8ZBJgRUXFysoKNBL5OXlIXEJAFBoKWnVufZrwRnS8S7MqKgoY2PjpUuX4qrU1FR6SzMzMzMzs/nz548aNSokJGTIkCH29vaJiYni7/q6YW9vn5mZKScnR98kilFQUBAIZHLCtLKyOnPmDKVOoqOjuVyugYGBmpqavLx8TEwM1gp5eXkvX750c3Orm6hWVlZpaWnp6enYCEtKSiooKBC3O2W/i4Z9kkDdkMmN3sbG5uTJk/SSEydOWFlZNY5IAND6sNe211HSIZCogzWBCF0lXXtt+3r2X15enpmZmZmZyefzscObj48PQqhjx45paWknTpx48+bNr7/+SiVPLy0tnTVrVkRERGpqalRUVGxsLH5ZL168+N69ezNnzoyPj3/16tWFCxdmz55dZ6n69u3r7Ozs6+t79erVlJSU6OjoZcuWPXz4ECFkYmKSnJwcHx+fnZ1dXl4upZMZM2akp6djD5G///47KCgoICCAwWBwOJxJkyYtWrTo5s2bz5498/f3p+YG6yaqra3tmDFjHj169ODBg/Hjx7u5udU60WdiYnL//v2UlJTs7GwRs6xhnyRQN2SywJYvXz5s2LA3b9707t0bIXTz5s0//vjj9OnTjSwbALQamAzmkm5LAiICCESQqHruC+uzxd0WM+u9Tzw8PFxPTw8hxOVyLSws/vrrL3d3d4TQ4MGD58+fP2vWrPLy8oEDBy5fvjw4OBghxGQyc3Jyxo8f//HjR01NzaFDh+Kceba2tpGRkUuXLu3ZsydJkh06dBgxYkSdpSIIIiwsbOnSpRMnTvz06ZOurm6vXr1wyohhw4adPXvWw8MjPz8/JCRESkBwAwODsLCwRYsW2dnZqaurT5o0admyZbhq06ZNxcXFgwYN4nK5CxYswEv6dRb1/Pnzs2fP7tWrF4PB8PLyovIOSmHhwoUTJkywsrIqLS1NTk6mVzXskwTqhqwTzZcvX167dm18fDybzbazswsKCuLxeE220152IJQU0FDUIZTUjdQb6x+sp7w5dJV0F3db3Ne4b6PJCABthLqFkpI1I/PAgQMHDhyIEMrPzz9+/Pi8efMSEhJknOMGgG+EvsZ9PQw9HmU9+lTySUtJy17bvv62FwAANSGrAkMI3bp16/Dhw2fPnjU2Nh42bNihQ4caTywAaKUwGcx6eswDACAjtSuwd+/ehYaGHj58+PPnz35+fpWVlWfOnAEPDgAAAKB5qcWrx9vb28rKKikpaefOnR8+fJBl2RNodqqqKuIun795eG/c5fNVVRBLFACAtkktFti1a9fmzJnz008/derUqWkEAupJ5LHDcZfOk2S1y2/k0cMO3/u6jZ3YvFIBAAA0OLVYYP/8809RUZGjo6OTk9OuXbs+fapvQAGgUYk8dvjhxbOU9kIIkaTw4cWzkccON6NUAAAAjUEtCszZ2fnAgQMZGRnTpk07ceKEgYGBUCi8fv16UVFR08gHyE5VVUXcpfMSq2AuEQCAtodMO9uVlJQmTpx49+7dp0+fLliwYP369dra2oMGDWps4YCvIuFqGN32okMKhQlXw5pYHgAAgEbl60KzmJubb9y48d27d3/++WcjCQTUmfyPmXWuBQAAaHXUJbYYk8n09fW9cOFCg0vTEsA5EZ4+fZqcnCxLUOqWg6qObp1rgbZESkoKQRDx8fHSm4WGhkqJHN9QozQUOBZU048LtGS+YiPzt0BSUlJ4eDgVaJ/H43l5ebWWTW92nt6RRw9LnEUkGAw7T++mFwloKNLT04ODg69cuZKdna2np+fr67tixQp6Ii46hoaGGRkZmpqa0vscMWKEt3fr+6uQ5e78/f3z8/OxwgPaMHWP7tz2SEpKOnXqFD1NTGFh4alTp5KSkppRKtmRk1Nw+N5XYpXDQF85OQWJVUCDIywry967T1hW1lAdvn371tHR8eXLl3/++efr16/37t178+ZNZ2fn3Nxc8cYVFRVMJlNXV1dOrpafp2w2W1tbu6GErAOVlZV1uErGu6sDFRXg6NTKAAVWjVAoDA8Pl1gVHh7eWuYS3cZOdPQZShD/fawEg+HoMxT2gTUlRdeufdq+vej69YbqcObMmQoKCteuXXNzczMyMhowYMCNGzfev39PpQEzMTFZs2aNv7+/iorKlClTRCbZLly40KlTJzab7eHhceTIEYIg8vPz0ZdTiMHBwV26dDl69KiJiYmKisrIkSMpT+Pw8PAePXqoqqpqaGh8//33UhIuU5iYmKxevXr06NEcDkdfX58eAIEgiL179w4ePFhZWXnNmjUIoYsXLzo4OLBYrPbt269cubKqqgq3fPXqVa9evVgslpWV1XXawxS5u8TExIEDB/J4PC6X27Nnzzdv3gQHBx85cuTvv/8mCIIgCJxv8+nTp71792az2RoaGlOnTi0uLsaX+/v7+/r6rlu3Tl9f38zM7Ks/G6BZAQVWTWpqak0pOgsLC0XyBLZk3MZOnHPstPv4yV08v3cfP3nO0dOgvZqYwivh1P/1Jzc39+rVqzNmzGCz2VShrq7umDFjTp48SWWT2LRpk42NTVxc3PLly+mXp6SkDB8+3NfXNz4+ftq0aZTOE+fNmzfnz5+/dOnSpUuXIiMj169fj8s/f/4cEBAQGxt78+ZNBoOB0zrXKvamTZtsbW0fPXoUGBg4f/58ugYKCgoaPHjw06dPJ06cePXq1bFjx86ZMycpKWnfvn2hoaG//PILQkgoFA4dOpTJZMbExOzdu3fx4sUSR3n//j1Wcrdu3YqLi5s4cWJVVdXChQv9/Py8vLwyMjIyMjJcXFxKSkq8vLzU1NRiY2P/+uuvGzduzJo1i+rk5s2bfD7/+vXrly5dqvW+gBYFrIFVQ/0iq0NtS0NOTsFhoG9zS/FtUZWdnXvkCFlZhRD6fPcuQujzP/98XL8BIUTIy6n7+8vVsF5VK69evSJJUjx3sKWlZV5e3qdPn/A0YO/evRcuXIirUlJSqGZ79+41NzfftGkTQsjc3PzZs2dYQ4gjFApDQ0O5XC5CaNy4cTdv3sQthw0bRrU5dOiQtrZ2UlKSjY2NdLFdXV2XLFmCEDIzM4uKitq2bVu/fv1w1ejRoydOrP5RNW7cuCVLlkyYMAEh1L59+9WrV//vf/8LCgq6ceMGn89PSUlp164dQmjt2rUDBgwQH+W3335TUVE5ceKEvLw8HguXs9ns8vJyXd1qx6UjR46Ulpb+/vvvysrKCKFdu3b5+Phs2LABpy5TVlY+ePCgSNJ5oFUACqwaDodT51oAqPr0KffI72RFBWIQiGAghEihMPf3I0hIEgoKPG/vOiuwmsC2F0FU54CuKbnwixcvunb9Lzp+t27daurQxMQEay+EkJ6eXlZWFj5+8+bN8uXLY2JiqKzEaWlptSowZ2dn+vH27dupU7qocXFxsbGxlE4VCARlZWUlJSV8Pt/IyAhrL5He6MTHx/fs2RNrLynw+Xw7OzusvRBCrq6uQqHwxYsXWIF17twZtFcrBaYQqzE2Nq4pZxqPxzM2Nm5ieYDWBcvS0vTMaYX27REiEM6TJxAgRCi0b2965jRLzH6SnY4dOxIEIe5J9Pz5czU1NcoZj3o7i0CSJKXk0L9qTyJ0NUAQBDVP6OPjk5OTc+DAgfv379+/fx/VydmBLgNdVKFQuHLlyvh/efr06atXr1gsloic9Mvp0KdVpSDyEET6rOnRAS0fUGDV4CzjEqu8vLwYDHhQQC0odupk8ucfiP7mJUmTP/9QrF8gbA0NjX79+u3evbu0tJQqzMzMPH78+IgRI2p6s1NYWFjExsZSpw8fPvyq0XNycvh8/rJly/r06YMnLWW8MCYmhn5sYWEhsZm9vf2LFy86fgmDwbCyskpLS/vw4QNudu/ePYmX29ra/vPPP+LejAoKCvR0u1ZWVvHx8Z8/f8anUVFRDAYDXDbaAPBe/g8rKys/Pz8uzQ7j8Xh+fn6tZR8Y0OyUPHwoosBK4uLq3+2uXbvKy8s9PT3v3LmTnp4eHh7er18/AwODmlaz6EybNu358+eLFy9++fLlqVOnQkNDUc0GjThqamoaGhr79+9//fr1rVu3AgICZLwwKipq48aNL1++/O233/7666+5c+dKbLZixYrff/89ODg4MTGRz+efPHly2bJlCKG+ffuam5uPHz8+ISHhn3/+qcn3ZNasWYWFhSNHjnz48OGrV6+OHj364sULhJCJicmTJ09evHiRnZ1dWVk5ZswYFos1YcKEZ8+e3b59e/bs2ePGjcPzh0CrBhTYF6QJ1U6X2YZXmEdWtA+vMP+rzDZNqNbcQgGthsJr1xFCbAd7kxN/su3tqZJ60qlTp4cPH3bo0GHEiBEdOnSYOnWqh4fHvXv31NXVa73W1NT09OnTZ8+etbW13bNnD9YEioqKMg7NYDBOnDgRFxdnY2Mzf/587AwiCwsWLIiLi/vuu+9Wr169ZcsWT09Pic08PT0vXbp0/fr1rl27du/efevWrXi6nsFgnDt3rry8vFu3bpMnT65JVWtoaNy6dau4uNjNzc3BweHAgQN4InTKlCnm5uaOjo5aWlpRUVFKSkpXr17Nzc3t2rXr8OHD+/Tps2vXLhlvBGjJEFLmxFsjhYWFKioqBQUFNS1oSSH8WcZPxx7RHwf+mbpnrL2XjV5DSQi0FsrKypKTk01NTVksloyX5P5+lKwoV//xR4LJJAWC3JAQQkFRffy4RpXzq/jll1/27t2bnp7eqKOYmJjMmzdv3rx5jToK0JaQ+HWr9X0OXojVCITkyotJIsqcRIhAaOXFpH5WukyGrLMuwDcLXVcRTKbG5MnNKAzF7t27u3btqqGhERUVtWnTJvoWKABo1YACq+ZBcm5GgYTYPyRCGQVlD5JznTs0sBs0ADQNr169WrNmTW5urpGR0YIFCwIDA5tbIgBoGECBVZNVJC1ynfRaAGjJbNu2bdu2bU05In0nNQA0HqDAqtHmSlvnkF7bXAiFgvf8xOL8PI6qmoGlNYPBbG6JAAAAmg5QYNV0M1XXU2FlFpSJLIMRCOmqsLqZ1u7u1cS8uh99K3R/cW42PuWoa/b2n9rJyaV5pQIAAGgywI2+GiaDCPKxQv96HmLwcZCPVUvz4Hh1P/rC1rWU9kIIFedmX9i69tX96GaUCgAAoCkBBfYfXjZ6e8ba66r8N1uoq8JqgT70QqHgVuh+iVW3j+wXCgUSqwAAANoYMIX4BV42ev2sdB8k52YVlWlzWd1M1Vua7YUQes9PpNtedIpyst/zEw2tbZtYJAAAgKYHFJgoTAbRwj3mi/OlxaOTXgsAANBmgCnE1gdHVVp0K+m1ANBcEARx/vz5+vTg7u7eqNE96CmqGwMTExN6WplGhf6smnLcJgYUWOvDwNKao64psYqroWlgad3E8gCNjb+/P/EvGhoaXl5eT548aW6haiE4OLhLly7NNVZ+fj5BEBEREY0xXKvTB7GxsVOnTpXSoLE1d+MBCqz1wWAwe/tL/nP0mDAVdoM1F/kfSz6lFYn/y/9YUv/Ovby8MjIyMjIybt68KScn9/3339e/T6B1UYc0bBgtLS0lJaWGFQYhJBAIqKRxzQUosFZJJyeXQQE/0+0wrobmoICfYR9Yc5H/seR4UMyptbHi/44HxdRfhykqKurq6urq6nbp0mXx4sXp6emfPn3CVYsXLzYzM1NSUmrfvv3y5cup5FgJCQkeHh5cLpfH4zk4OFCZwKKjo3v16sVmsw0NDefMmUNlyaKDbZrDhw8bGRlxOJyffvpJIBBs3LhRV1dXW1ubHhu+oKBg6tSp2traPB6vd+/eCQkJCKHQ0NCVK1cmJCRgqxHncEEIZWdnDxkyRElJqVOnThcuXKA6iYyM7Natm6Kiop6e3pIlS6qqqnD558+fx48fz+Fw9PT0tmzZUrdHFxERQRDE5cuX7ezsWCyWk5PT06dPqdrQ0FAjIyMlJaUhQ4bk5ORQ5W/evBk8eLCOjg6Hw+nateuNGzdwubu7e2pq6vz58/GtSX+kWVlZPj4+bDbb1NT0+PHjNUno7+/v6+u7cuVK/BinTZtG6Sp3d/dZs2YFBARoamr269cPIZSUlOTt7c3hcHR0dMaNG5ednV3rs6KbjPn5+VOnTtXR0WGxWDY2NpcuXYqIiPjxxx8LCgrwHQUHByOE8vLyxo8fr6ampqSkNGDAgFevXlGPS1VV9dKlS1ZWVoqKiqmpqXX5SBoOUGCtlU5OLlN+O+S3Yq33nEV+K9ZO3nUItFczUlkubfeC9Nqvori4+Pjx4x07dtTQqHY14nK5oaGhSUlJO3bsOHDgABU1asyYMe3atYuNjY2Li1uyZAnOM/L06VNPT8+hQ4c+efLk5MmTd+/erSm275s3b65cuRIeHv7nn38ePnx44MCB7969i4yM3LBhw7Jly3C+SpIkBw4cmJmZGRYWFhcXZ29v36dPn9zc3BEjRixYsMDa2hpbjSNGjMB9rly50s/P78mTJ97e3mPGjMnNzUUIvX//3tvbu2vXrgkJCXv27Dl06NCaNWtw+0WLFt2+ffvcuXPXrl2LiIiIq0dytUWLFm3evDk2NlZbW3vQoEFYzd+/f3/ixIkzZsyIj4/38PCgxsXP2dvb+8aNG48fP/b09PTx8UlLS0MInT17tl27dqtWrcK3Jv2R+vv7p6Sk3Lp16/Tp07t3787KyqpJvJs3b/L5/Nu3b//555/nzp1buXIlVXXkyBE5ObmoqKh9+/ZlZGS4ubl16dLl4cOH4eHhHz9+9PPzk/1ZCYXCAQMGREdHHzt2LCkpaf369Uwm08XFZfv27TweD9/RwoULseQPHz68cOHCvXv3SJL09vamfhiVlJSsW7fu4MGDiYmJ2tradf5EGgaybVFQUIAQKigoaG5BgFZPaWlpUlJSaWmpLI2zUgt3TbtZ07+s1ML6SDJhwgQmk6msrKysrIwQ0tPTi4uLk9hy48aNDg4O+BgrNpEG48aNmzp1KnX6zz//MBgM8XsMCgpSUlIqLKwW29PT08TERCAQ4FNzc/N169aRJHnz5k0ej1dWVkZd2KFDh3379uEe7Ozs6H0ihJYtW4aPi4uLCYK4cuUKSZI///yzubm5UCjEVb/99huHwxEIBEVFRQoKCidOnMDlOTk5bDZ77ty54nctPhbOHH379m2SJG/fvo0QEunn5MmTJEmOGjXKy8uLumrEiBEqKiri/ZMkaWVltXPnTnxsbGy8bds2qqqmR4pTa8bExOByPp+PEKJfSDFhwgR1dfXPnz/j0z179uAnQJIkVldUy+XLl/fv3586xWlxXrx4If1ZUQJfvXqVwWC8ePFCRICQkBD6jb98+RIhFBUVhU+zs7PZbPapU6dwS4RQfHy8xKdUHyR+3Wp9n4MbPQC0Ajw8PPbs2YMQys3N3b1794ABAx48eIBzP54+fXr79u2vX78uLi6uqqqiMicFBARMnjz56NGjffv2/eGHHzp06IAQiouLe/36NTWdRZKkUChMTk62tLQUGdHExITL5eJjHR0dJpPJYDCoU2xMxMXFFRcXU7YgQqi0tPTNmzc13YWtbfUORWVlZS6Xizvh8/nOzs7UdJyrq2txcfG7d+/y8vIqKiqcnZ1xubq6urm5eR0fH0Ii/WB1wufzhwwZQm8THh6Ojz9//rxy5cpLly59+PChqqqqtLQUW2Di1PRIX758KScn5+joiMstLCykOErY2dlRy1TOzs7FxcXp6en486V6wGPdvn2bw+HQr33z5k1paakszyo+Pr5du3ZmZmY1iYHh8/lycnJOTk74VENDg3piCCEFBQXqc2x2QIEBQCtAWVm5Y8eO+NjBwUFFReXAgQNr1qyJiYkZOXLkypUrPT09VVRUTpw4Qa1/BAcHjx49+vLly1euXAkKCjpx4sSQIUOEQuG0adPmzJlD79zIyEh8RDzliCEIQuQUr94LhUI9PT0RZz8pr2mJnZAkSWkvfIprSZlz7fJ4PPxTnSI/Px8hpKKiUtMleEQpQyxatOjq1aubN2/u2LEjm80ePnx4TT4UNT1SbIHRb+2roC7EZjc1lo+Pz4YNG+gt9fT0qDUq6bDZbFmaiT8W+mfEZrPrfFMNDigwAGhlEASBJ6kQQlFRUcbGxkuXLsVVIovqZmZmZmZm8+fPHzVqVEhIyJAhQ+zt7RMTEyldWE/s7e0zMzPl5ORMTExEqhQUFAQCmVb+rKyszpw5Q70io6OjuVyugYGBmpqavLx8TEwM1q95eXkvX750c3MT78HCwuLdu3eZmZm6urq4JDY2lsFg0G9TpB8LCws8NF7Mo9pQx//884+/vz+2z4qLi+kJYkRuraZHamlpWVVV9fDhw27duiGEXrx4gdWqRBISEkpLS7GCiYmJ4XA47dq1E29mb29/5swZExMTObkvXt0dO3aU5VnZ2tq+e/fu5cuXIkaYyB1ZWVlVVVXdv3/fxcUFIZSTk/Py5UtxG70lAE4cANAKKC8vz8zMzMzM5PP5s2fPLi4u9vHxQQh17NgxLS3txIkTb968+fXXX8+dO4fbl5aWzpo1KyIiIjU1NSoqKjY2Fr+AFi9efO/evZkzZ8bHx7969erChQuzZ8+us1R9+/Z1dnb29fW9evVqSkpKdHT0smXLsLujiYlJcnJyfHx8dnZ2eXm5lE5mzJiRnp4+e/bs58+f//3330FBQQEBAQwGg8PhTJo0adGiRTdv3nz27Jm/vz81hylC//79LS0tR44cGRUVlZyc/Pfffy9cuHD69OnUFChCaNWqVVQ/mpqavr6+CKE5c+aEh4dv3Ljx5cuXu3btouYP8YM9e/ZsfHx8QkLC6NGj6f7iJiYmd+7cef/+PfYArOmRmpube3l5TZky5f79+3FxcZMnT5ZiAFVUVEyaNCkpKQmby7NmzZJ4szNnzszNzR01atSDBw/evn177dq1iRMnCgQCGZ+Vm5tbr169hg0bdv369eTkZOykg++ouLj45s2b2dnZJSUlnTp1Gjx48JQpU+7evZuQkDB27FgDA4PBgwdL+RCbC1BgANAKCA8P19PT09PTc3Jyio2N/euvv9zd3RFCgwcPnj9//qxZs7p06RIdHb18+XLcnslk5uTkjB8/3szMzM/Pb8CAAdixzdbWNjIy8tWrVz179vzuu++WL1+up1f3WNUEQYSFhfXq1WvixIlmZmYjR45MSUnR0dFBCA0bNszLy8vDw0NLS+vPP/+U0omBgUFYWNiDBw/s7OymT58+adKkZcuW4apNmzb16tVr0KBBffv27dGjh4ODg8Qe5OTkrl271r59+zFjxlhbWy9ZsmTy5Mlbt26lt1m/fv3cuXMdHBwyMjIuXLigoKCAEOrevfvBgwd37tzZpUuXa9euUeMihLZt26ampubi4uLj4+Pp6Wlvb09VrVq1KiUlpUOHDlpaWkjqIw0JCTE0NHRzcxs6dCjebFDTQ+jTp0+nTp169erl5+fn4+ODfdnF0dfXj4qKEggEnp6eNjY2c+fOVVFRwbpKxmd15syZrl27jho1ysrK6n//+x82vFxcXKZPnz5ixAgtLa2NGzdiyR0cHL7//ntnZ2eSJMPCwujTvy2Hr5hobhUUFhaqqKgUFBRQS9kAUDfKysqSk5NNTU1ZrNrTmeJ9YDXVjlnZXVWn4XeSArIQERHh4eGRl5fXYoNN+Pv75+fn1zPOVmtH4tet1vc5rIEBQAOgqqM0ZmV3ifu95BWZoL0AoDEABQYADQNoKQBoYkCBAQDQlnF3d2/hCyVUqC3gawEnDgAAAKBVAgoMAAAAaJWAAgMAAABaJbAG1nIRCgXv+YnF+XkcVTUDS2tI9AUAAECn0S2w3bt3Y9d+BweHf/75R7wBPdssxtr6v5zC27dvNzc3x4l25s+fX1ZW1tgCtxBe3Y8+MHPSqVU/h/266dSqnw/MnPTqfnRzCwUAANCCaFwFdvLkyXnz5i1duvTx48c9e/YcMGCAeETnHTt2ZPxLenq6urr6Dz/8gKuOHz++ZMmSoKAgPp9/6NChkydPBgYGNqrALYRX96MvbF1bnJtNlRTnZl/YuhZ0GAAAAEXjKrCtW7dOmjRp8uTJlpaW27dvNzQ0xCkh6KioqOj+y8OHD/Py8n788Udcde/ePVdX19GjR5uYmPTv33/UqFFUVtk2jFAouBW6X2LV7SP7hcIGS40ItAEIgqhPBAecebk+AuB8x1LC1NYZnPz3qy5JSUkhCCI+Pl68qvHklB13d/d58+Y1owBtj0ZUYBUVFXFxcf3796dK+vfvHx0tzYY4dOhQ3759cRYchFCPHj3i4uIePHiAEHr79m1YWNjAgQPFryovLy+k0aA30Qy85yfSbS86RTnZ7/mJTSwP0OxkZWVNmzbNyMhIUVFRV1fX09Pz3r17uCojI2PAgAFNKUzbewubmJjQlzAkhoGvA+Iq8+zZs6tXr26QzgFMIzpxZGdnCwQCHNkTo6Ojk5mZWVP7jIyMK1eu/PHHH1TJyJEjP3361KNHD5Ikq6qqfvrppyVLlohfuG7dOnoG7tZOcX5enWuBZqcxXG+GDRtWWVl55MiR9u3bf/z48ebNm7m5ubiKSiDSwqmsrGyZ0WAxq1atmjJlCj5mMkU/soYSXl1d/avaCwQCnDqn/kO3VRr90YikqpOSCQ3PGOA0B5iIiIhffvll9+7djx49Onv27KVLlyT+fgkMDCz4F5xju1XDUVWrcy3QvDSG601+fv7du3c3bNjg4eFhbGzcrVu3wMBAaiqCmkLEs2dnz5718PBQUlKys7OjrDSE0IEDBwwNDZWUlIYMGbJ169aapuZCQkIsLS1ZLJaFhcXu3bvFG/j7+0dGRu7YsQMbK1SWrLi4OEdHRyUlJRcXF5zIEf07P3n48OH27dsrKiriDPE4KDuPx+vdu3dCQgJumZCQ4OHhweVyeTyeg4MDfaXg6tWrlpaWHA7Hy8srIyMDFwqFwlWrVrVr105RUbFLly70NCh0wsLCzMzM2Gy2h4cHPaGXOFwul1rIwDHmCYLYu3fv4MGDlZWV16xZgxDas2dPhw4dFBQUzM3Njx49Sl1LEMTBgweHDBmipKTUqVOnCxcu4I/Dw8MDIaSmpkYQhL+/P/rSeK2oqPjf//5nYGCgrKzs5OREJQXFr8FLly5ZWVkpKiqKJHgDRGhEBaapqclkMukmV1ZWFt0go0OS5OHDh8eNG4fTHGCWL18+bty4yZMnd+7ceciQIWvXrl23bh09MQ9GUVGRR6Mx7qUpMbC05qhrSqziamgaWFpLrAKanUZyveFwOBwO5/z589KzamGWLl26cOHC+Ph4MzOzUaNGVVVVIYSioqKmT58+d+7c+Pj4fv36/fLLLxKvPXDgwNKlS3/55Rc+n7927drly5cfOXJEpM2OHTucnZ2nTJmCva4MDQ2pcbds2fLw4UM5ObmJEydS7V+/fn3q1KkzZ87gdamBAwdmZmaGhYXFxcXZ29v36dMHm5Jjxoxp165dbGxsXFzckiVLKHOnpKRk8+bNR48evXPnTlpa2sKFCykxtmzZsnnz5idPnnh6eg4aNEg8JXF6evrQoUO9vb3j4+MnT54scfJGOkFBQYMHD3769OnEiRPPnTs3d+7cBQsWPHv2bNq0aT/++OPt27eplitXrvTz83vy5Im3t/eYMWNyc3MNDQ3PnDmDEHrx4kVGRsaOHTtEOv/xxx+joqJOnDjx5MmTH374wcvLi7qFkpKSdevWHTx4MDExUUoGFgAhhMjGpFu3bj/99BN1amlpuWTJEokt8V/D06dP6YX29vb/+9//qNM//viDxWJVVVVJGRFnFi8oKKif4M3My5iozX4Dxf+9jIlqbtG+IUpLS5OSkkpLS2VpLBBU7Z0+QeKntu+nCQKBtD/aWjl9+rSamhqLxXJxcQkMDExISKCqEELnzp0jSTI5ORkhdPDgQVyemJiIEOLz+SRJjhgxYuDAgdQlY8aMUVFRwcdBQUF2dnb42NDQ8I8//qCarV69GueCEsHNzW3u3LnUKf7m3rhxA59evnwZIYQfWlBQkLy8fFZWFq66efMmj8crKyujru3QocO+fftIkuRyuaGhoSIDhYSEIIRev36NT3/77TcdHR18rK+v/8svv1Atu3btOmPGDOohPH78mCTJwMBAS0tLoVCI2yxevBghlJeXJ35HxsbGCgoKyv+yY8cO/GDnzZtHtXFxcZkyZQp1+sMPP3h7e+NjhNCyZcvwcXFxMUEQV65coZ4MfUTq0b1+/ZogiPfv31NVffr0CQwMpO46Pj5eXM62jcSvW63v88adQgwICDh48ODhw4f5fP78+fPT0tKmT5+OEAoMDBw/fjy95aFDh5ycnGxsbOiFPj4+e/bsOXHiRHJy8vXr15cvXz5o0CDxGeq2Rycnl0EBP9PtMK6G5qCAnzs5uTSjVIAUGtX1ZtiwYR8+fLhw4YKnp2dERIS9vX1N4V9tbW3xAc6pmJWVhRB68eIFzmqPoR9TfPr0KT09fdKkSZx/WbNmzZs3b2SUUOK4CCFjY2M8I4cQiouLKy4u1tDQoIZITk7GQwQEBEyePLlv377r16+nD6qkpNShQweqZ9xtYWHhhw8fXF1dqWaurq58Pl9EJD6f3717d2rNwtnZWYr8ixYtiv8X6tXk6OhI703KiNTtKysrc7lc6vZr4tGjRyRJmpmZUY8iMjKSunEFBQWqQ0A6jRuJY8SIETk5OatWrcrIyLCxsQkLC8MehhkZGfQNYQUFBWfOnBG3spctW0YQxLJly96/f6+lpeXj41PT7Efbo5OTS4euThCJo7XQ2K43LBarX79+/fr1W7FixeTJk4OCgvCyigjU5Bt+ceP5dvLLtWdSUmh23PLAgQNOTk5Uoew/FiWOixBSVlamD6Gnp0ct9mDwalxwcPDo0aMvX7585cqVoKCgEydODBkyhN4t7pkuea2L6xJvsyY0NTU7duwoUkgXXvqIInKKL3OIIBQKmUxmXFwc/QlzOBx8wGazpfgKAHQaPZTUjBkzZsyYIVIo8vtRRUWlpKRE/Fo5ObmgoKCgoKDGE68lw2AwDa3hh1jroCldb6ysrL5q75eFhQXei4KRuJlSR0fHwMDg7du3Y8aMkd6bgoICzkP/tdjb22dmZsrJyZmYmIjXmpmZmZmZzZ8/f9SoUSEhIViBSYTH4+nr69+9e7dXr164JDo6WtysFHlKMTE15suWBUtLy7t371LGWXR0tKWlpfRL8HK+xGf13XffCQSCrKysnj171kcqAGIhAkADgF1vJM4i1tP1Jicn54cffpg4caKtrS2Xy3348OHGjRsHDx4sew+zZ8/u1avX1q1bfXx8bt26deXKFYk/8IODg+fMmcPj8QYMGFBeXo6jCgQEBIg0MzExuX//fkpKCofD+Sq/8L59+zo7O/v6+m7YsMHc3PzDhw9hYWG+vr7W1taLFi0aPny4qanpu3fvYmNjhw0bJr2rRYsWBQUFdejQoUuXLiEhIfHx8cePHxdpM3369C1btgQEBEybNi0uLq6eObcWLVrk5+eHHU8uXrx49uzZGzduSL/E2NiYIIhLly55e3uz2WzKwEIImZmZjRkzZvz48Vu2bPnuu++ys7Nv3brVuXNnb2/v+gj5DQI7DACgAWAwmL39p0qs8pgwtT7TvxwOx8nJadu2bb169bKxsVm+fPmUKVN27dolew+urq579+7dunWrnZ1deHj4/PnzWSyWeLPJkycfPHgwNDS0c+fObm5uoaGhpqam4s0WLlzIZDKtrKy0tLTEI8NJgSCIsLCwXr16TZw40czMbOTIkSkpKTo6OkwmMycnZ/z48WZmZn5+fgMGDKh1W+ecOXMWLFiwYMGCzp07h4eHX7hwoVOnTiJtjIyMzpw5c/HiRTs7u717965du1Z2UcXx9fXdsWPHpk2brK2t9+3bFxIS4u7uLv0SAwODlStXLlmyREdHZ9asWSK1ISEh48ePX7Bggbm5+aBBg+7fv0+5dAKyQ3zVTHHLp7CwUEVFpaCgoA340wPNS1lZWXJyMg5FLeMlr+5H3wrdT9lhXA1NjwlTW5rrzZQpU54/fy4xsjYANBcSv261vs9hChEAGowW63qzefPmfv36KSsrX7ly5ciRIxI3KQNAqwMUGAA0JC3T9ebBgwcbN24sKipq3779r7/+Onny5OaWCAAaAFBgAND2OXXqVHOLAAANDzhxAAAAAK0SUGAAAABAqwQUGAAAANAqAQUGAAAAtErAiaOZaYz8hwAAAN8CoMCaE5F9rxx1zd7+LW7fKwAAQMsEphCbjUbKfwh8U1AZmesGTppcHwEiIiIIgsjPz69PJxLBuYm/6hKclhonzxSh8eSkMDEx2b59eyN1XoenUWfoz6opx60DoMCaB6FQcCt0v8Sq20f2C4V1ifYNtFWysrKmTZtmZGSkqKioq6vr6el57949XJWRkTFgwICmFMbd3X3evHlNOWJjI/4jYN68ebWGOqwbLVwfiDNixIiXL19Kb9Oomls6MIXYPNSa/7AFRnMApFOZXUqWS/jlQSgy5TXZ9el52LBhlZWVR44cad++/cePH2/evJmbm4urdHV169Nzk1FZWUlPmgU0MSRJCgQCObmvfuGz2Ww2u15/vTVRUVGBM87UB7DAmofGzn8INDGV2aUfNz/M2vlY/N/HzQ8rs0vr3HN+fv7du3c3bNjg4eFhbGzcrVu3wMDAgQMH4lrKesCzZ2fPnvXw8FBSUrKzs6OsNITQgQMHDA0NlZSUhgwZsnXr1pqMgJCQEEtLSxaLZWFhITFeor+/f2Rk5I4dOwiCIAgiJSUFl8fFxTk6OiopKbm4uLx48QIX4vnJw4cPt2/fXlFREWeInzp1qra2No/H6927d0JCAm6ZkJDg4eHB5XJ5PJ6DgwM9Y9nVq1ctLS05HI6Xl1dGRgYuFAqFq1atateunaKiYpcuXcLDwyXeTlhYmJmZGZvN9vDwoET9Wtzd3WfNmjVr1ixVVVUNDY1ly5ZRAdCzsrJ8fHzYbLapqalIPpetW7d27txZWVnZ0NBwxowZxcXFCKGIiIgff/yxoKAAP73g4GCEUEVFxf/+9z8DAwNlZWUnJyd6ws/Q0FAjIyP8qeXk5EgUD3/uJ06ccHFxYbFY1tbWVA94JvDq1auOjo6Kior//PMPSZIbN25s3749m822s7M7ffp0rc9KxGS8cOGCo6Mji8XS1NQcOnQofj6pqanz58/HN4WbnTlzxtraWlFR0cTEZMuWLdTlJiYma9as8ff3V1FRmTJlytd9EpIABdY8NGX+Q6AJkGh7yVgrHZxy/vz58+Xl5bU2Xrp06cKFC+Pj483MzEaNGlVVVYUQioqKmj59+ty5c+Pj4/v161dTWvMDBw4sXbr0l19+4fP5a9euXb58+ZEjR0Ta7Nixw9nZecqUKRkZGRkZGVQGkKVLl27ZsuXhw4dycnITJ06k2r9+/frUqVNnzpzB61IDBw7MzMwMCwuLi4vDubWwKTlmzJh27drFxsbGxcUtWbKEstVKSko2b9589OjRO3fupKWlLVy4kBJjy5YtmzdvfvLkiaen56BBg169eiUianp6+tChQ729vePj4ydPnrxkyZJan15NHDlyRE5O7v79+7/++uu2bdsOHjyIy/39/VNSUm7dunX69Ondu3dnZWVRlzAYjF9//fXZs2dHjhy5devW//73P4SQi4vL9u3beTwefnr4dn788ceoqKgTJ048efLkhx9+8PLywvdy//79iRMnzpgxIz4+3sPDY82aNVIkXLRo0YIFCx4/fuzi4jJo0CC6tvvf//63bt06Pp9va2u7bNmykJCQPXv2JCYmzp8/f+zYsZGRkbI/q8uXLw8dOnTgwIGPHz++efOmo6MjQujs2bPt2rVbtWoVvimEUFxcnJ+f38iRI58+fRocHLx8+XJ6MrZNmzbZ2NjExcUtX768bh/HF5Bti4KCAoRQQUFBcwtSCwJB1d7pEzb7DRT/t++nCQJBVXMLCJClpaVJSUmlpaWyNC5/V5S++E5N/8rfFdVHktOnT6upqbFYLBcXl8DAwISEBKoKIXTu3DmSJJOTkxFCBw8exOWJiYkIIT6fT5LkiBEjBg4cSF0yZswYFRUVfBwUFGRnZ4ePDQ0N//jjD6rZ6tWrnZ2dxYVxc3ObO3cudXr79m2E0I0bN/Dp5cuXEUL4oQUFBcnLy2dlZeGqmzdv8ni8srIy6toOHTrs27ePJEkulxsaGioyUEhICELo9evX+PS3337T0dHBx/r6+r/88gvVsmvXrjNmzKAewuPHj0mSDAwMtLS0FAqFuM3ixYsRQnl5eeJ3RD1Dirlz57q5uVH3K9KPpaUlSZLY0IyJicHlfD4fIbRt2zbx/k+dOqWhoUHdFPXwSZJ8/fo1QRDv37+nSvr06RMYGEiS5KhRo7y8vKjyESNG0C+kwLe8fv16fFpZWdmuXbsNGzaQ/34058+fx1XFxcUsFis6Opq6dtKkSaNGjZL+rOgCOzs7jxkzRlwGY2Nj+o2PHj26X79+1OmiRYusrKyolr6+vuI9kDV83Wp9n4MF1jw0Xv5DoO0xbNiwDx8+XLhwwdPTMyIiwt7evqb8wra21Uunenp6CCFsE7x48aJbt25UG/oxxadPn9LT0ydNmsT5lzVr1rx580ZGCSWOixAyNjbW0tLCx3FxccXFxRoaGtQQycnJeIiAgIDJkyf37dt3/fr19EGVlJQ6dOhA9Yy7LSws/PDhg6urK9XM1dUV6w86fD6/e/fu1KSWs7OzjPcijkg/r169EggEfD5fTk4OWyEIIQsLC/pU2+3bt/v162dgYMDlcsePH5+Tk/P582fxnh89ekSSpJmZGfVMIiMj8RPg8/l0maXLT9VikehPg5IwKSmprKysX79+1Fi///47NZYszyo+Pr5Pnz5SxMDw+XyRTwc/MRF5GgRw4mg2Ojm5DAr4ueXnPwRaAiwWq1+/fv369VuxYsXkyZODgoL8/f3Fm1GTb/hlJBQKEUIkSVLvJnwqfiFueeDAAScnJ6qQyZT1h5TEcRFCysrK9CH09PToazwIIfzSDw4OHj169OXLl69cuRIUFHTixIkhQ4bQu8U90yUXuSP6qZTblAiXy8W/9Cny8/NVVFSkX4X7Fx8XIZSamurt7T19+vTVq1erq6vfvXt30qRJlZWV4i2FQiGTyYyLi6M/ag6H81Xyi0OXivoI8Idy+fJlAwMDqlZRUVH2sWT05pD+90b/k6g/oMCakxab/xBoyVhZWX3V3i8LC4sHDx5Qp3QXCQodHR0DA4O3b9+OGTNGem8KCgrUr+mvwt7ePjMzU05OzsTERLzWzMzMzMxs/vz5o0aNCgkJwQpMIjweT19f/+7du7169cIl0dHR4malyFOKiYmpqUMLC4vY2NgJEybgU5Ik4+Li6JsT6NfGxMR06tSJyWRaWlpWVVU9fPgQD/3ixQtqk9nDhw+rqqq2bNnCYDDQl7lsRJ7ed999JxAIsrKyevbsKS6/yLg1yY9r8dOoqqqKi4ubNWuWeBsrKytFRcW0tDQ3NzfxKlmela2t7c2bN3/88UeRcpGbsrKyunv3LnUaHR1tZmYm+4+hrwIUWDPTMvMfAi2HnJycH374YeLEiba2tlwu9+HDhxs3bhw8eLDsPcyePbtXr15bt2718fG5devWlStXJNoNwcHBc+bM4fF4AwYMKC8vf/jwYV5eXkBAgEgzExOT+/fvp6SkcDgcdXV12cXo27evs7Ozr6/vhg0bzM3NP3z4EBYW5uvra21tvWjRouHDh5uamr579y42NnbYsGHSu1q0aFFQUFCHDh26dOkSEhISHx8v4gSIEJo+ffqWLVsCAgKmTZsWFxdX06QrQmjhwoUTJkywsLDo379/aWnp/v3737x5M3PmTKpBeno67ufRo0c7d+7EbnXm5uZeXl5TpkzZv3+/nJzcvHnzKAOlQ4cOVVVVO3fu9PHxiYqK2rt3L/3pFRcX37x5087OTklJyczMbMyYMePHj9+yZct3332XnZ1969atzp07e3t7z5kzx8XFZePGjb6+vteuXavJ0xLz22+/derUydLSctu2bXl5eXQ/Ggoul7tw4cL58+cLhcIePXoUFhZGR0dzOJwJEybI+KyCgoL69OnToUOHkSNHVlVVXblyBTunmJiY3LlzZ+TIkYqKipqamgsWLOjatevq1atHjBhx7969Xbt2NWIG8JoWx1oprcWJA2j5tBAnjrKysiVLltjb26uoqCgpKZmbmy9btqykpATXoi+dOLD/AkmSeXl5CKHbt2/j0/379xsYGLDZbF9f3zVr1ujq6uJyuhMHSZLHjx/v0qWLgoKCmppar169zp49Ky7Pixcvunfvjl/WycnJ2FOAco54/PgxLhfvnCTJwsLC2bNn6+vry8vLGxoajhkzJi0trby8fOTIkYaGhgoKCvr6+rNmzcLPXMTf4dy5c9T7SiAQrFy50sDAQF5e3s7O7sqVK7hc5CFcvHixY8eOioqKPXv2PHz4MKrBiYMkyRMnTjg6OvJ4PG1tbU9Pz4cPH1JVbm5uM2bMmD59Oo/HU1NTW7JkCeXskJGRMXDgQEVFRSMjo99//53uy7B161Y9PT02m+3p6fn777/Th54+fbqGhgbWByRJVlRUrFixwsTERF5eXldXd8iQIU+ePMEtDx061K5dOzab7ePjs3nzZilOHH/88YeTk5OCgoKlpeXNmzdxlchHQ5KkUCjcsWOHubm5vLy8lpaWp6dnZGSk9Gcl8imcOXMG/4VgN3pceO/ePVtbW2o2kiTJ06dPW1lZycvLGxkZbdq0ibpcxN2DTt2cOL6YVm4DFBYWqqioFBQU8Hi85pYFaN2UlZUlJyebmpqyWKxaG+N9YDXV6ix0rOde5gZkypQpz58//+eff5pbkNaBu7t7ly5dmivSRK2kpKSYmpo+fvy4niHBmh2JX7da3+cwhQgADYC8JltnoWMjReKoP5s3b+7Xr5+ysvKVK1eOHDnSiFM6ANCEgAIDgIah2bWUFB48eLBx48aioqL27dv/+uuvkydPbm6JAKABAAUGAG0fuiMc8FWI+P23NExMTNrYMtBXARuZAQAAgFYJKDAAAACgVQIKDAAAAGiVgAIDAAAAWiWgwAAAAIBWCSgwAAAAoFUCCgwAvl1wPl+cbbLBwRmBqRC3LQd/f39fX9/mlgJoAECBNTxCoSA98Qk/KjI98YlQWPdUvACAECJqQGI6lVaNu7u7yD3ijNL1RFxJ79ixQ0psX6AVARuZG5hX96PpKb446pq9/SHF1zeEUChMTU0tLi7mcDjGxsY4oUZ9wGnaEUInT55csWIFTgSMZE7O1LqYMmXKqlWrqFM5uS9eUBUVFQoKCvUfpdZcXyKQJCkQCESEAVoCYIE1JK/uR1/YupbSXgih4tzsC1vXvrof3YxSAU1GUlLS9u3bjxw5cubMmSNHjmzfvj0pKamefer+i4qKCkEQurq6Ojo6nTt3vnHjBm7QpUsXbW1tfHzv3j15efni4mKEUFpa2uDBgzkcDo/H8/Pz+/jxY01DvH371sPDQ0lJyc7O7t69e1R5dHR0r1692Gy2oaHhnDlzqJzCx44dc3R05HK5urq6o0ePpvIvI4TCwsLMzMzYbLaHh0dKSgpVnpqa6uPjo6ampqysbG1tHRYWJlESJSUlXRoIIRMTkzVr1vj7+6uoqEyZMgUhdObMGWtra0VFRRMTE5zZBGNiYrJ27dqJEydyuVwjI6P9+/fjclNTU4TQd999RxCEu7s7+nIKkSTJjRs3tm/fns1m29nZnT59Gpfj+c+rV686OjoqKipC7OOWCSiwBkMoFNwK3S+x6vaR/TCX2OZJSko6depUYWEhVVJYWHjq1Kn66zARCILo1asXDnGUl5eXlJRUWVmJR4mIiHBwcOBwOCRJ+vr65ubmRkZGXr9+/c2bNyNGjKipw6VLly5cuDA+Pt7MzGzUqFF44u7p06eenp5Dhw598uTJyZMn7969S6VJrKioWL16dUJCwvnz55OTk6nJzPT09KFDh3p7e8fHx0+ePHnJkiXUEDNnziwvL79z587Tp083bNiAkw7LyKZNm2xsbOLi4pYvXx4XF+fn5zdy5MinT58GBwcvX76cPhm4ZcsWR0fHx48fz5gx46effnr+/DlCCCfzvHHjRkZGxtmzZ0U6X7ZsWUhIyJ49exITE+fPnz927NjIyEiq9n//+9+6dev4fL6tLSTta4mAUdxgvOcn0m0vOkU52e/5iZC4sg0jFAprSjkYHh5uYWFR/7lEOu7u7tjCuHPnjp2dnZGRUUREhJWVVUREBDYybty48eTJk+TkZENDQ4TQ0aNHra2tY2Nju3btKt7bwoULBw4ciBBauXKltbX169evLSwsNm3aNHr06Hnz5iGEOnXq9Ouvv7q5ue3Zs4fFYlH5EnFo4G7duuEp0z179rRv337btm0EQZibm2NdhVumpaUNGzasc+fO+Kqa7mv37t0HDx7Ex9OmTcMGVu/evRcuXIgLx4wZ06dPn+XLlyOEzMzMkpKSNm3aRGlQb2/vGTNmIIQWL168bdu2iIgICwsLLS0thJCGhgY26eh8/vx569att27dcnZ2xoLdvXt33759VM7iVatW9evXT+aPBWhqwAJrMIrz8+pcC7R2UlNT6bYXncLCwtTU1IYdzt3dPTExMTs7OzIy0t3d3d3dPTIysqqqKjo6Gr98+Xy+oaEh1l4IISsrK1VVVT6fL7E3yrzQ09NDCOEpQZyZl/Mvnp6eQqGQyhg5ePBgY2NjLpeL9WVaWhoetHv37lS6Z6wVMHPmzFmzZo2rq2tQUNCTJ09quq8xY8bE/0tgYCAudHR0pBrw+XxXV1fq1NXV9dWrV1Q+e+pG8FwrfW5TIklJSWVlZf369aNu8/fff3/z5g3VgD400AIBC6zB4Kiq1bkWaO3gZae61dYBGxsbDQ2NyMjIyMjIVatWGRoa/vLLL7GxsaWlpT169EAIkSRJKRKMeAmFvLw8PsANhEIh/n/atGlz5syhtzQyMvr8+XP//v379+9/7NgxLS2ttLQ0T0/PiooKPERNAk+ePNnT0/Py5cvXrl1bt27dli1bZs+eLd5MRUWlY8eOIoXKyso13YXIiNSN4HvBNyIF3ODy5csGBgZUIc4sLD400AIBBdZgGFhac9Q1Jc4icjU0DSytm14koMmQvqjzVUs+soCXwf7+++9nz5717NmTy+VWVlbu3bvX3t6ey+UihKysrNLS0tLT07ERlpSUVFBQYGlpKfsQ9vb2iYmJ4urk6dOn2dnZ69evxz0/fPhfHmorK6vz589TpzExMfQLDQ0Np0+fPn369MDAwAMHDkhUYLViZWV19+5d6jQ6OtrMzIzJZEq5BDsuUlaaSG+KioppaWnUnCHQuoApxAaDwWD29p8qscpjwlQGQ9p3DGjtGBsb15T1nMfjGRsbN/iI7u7uf/zxh62tLY/Hw/rs+PHjeEIPIdS3b19bW9sxY8Y8evTowYMH48ePd3Nz+6oJscWLF9+7d2/mzJnx8fGvXr26cOECVjlGRkYKCgo7d+58+/bthQsXVq9eTV0yffr0N2/eBAQEvHjx4o8//qC7V8ybN+/q1avJycmPHj26devWV6lSOgsWLLh58+bq1atfvnx55MiRXbt2UctjNaGtrc1ms8PDwz9+/FhQUECv4nK5CxcunD9//pEjR968efP48ePffvvtyJEjdZMNaHpAgYmCJ/qfPn2anJxc6xSECJ2cXAYF/MxR16RKuBqagwJ+hn1gbR4Gg+Hl5SWxysvLq2E9ODAeHh4CgYDSWG5ubgKBgLIkCII4f/68mppar169+vbt2759+5MnT35V/7a2tpGRka9everZs+d33323fPlyvEKmpaUVGhr6119/WVlZrV+/fvPmzdQlRkZGZ86cuXjxop2d3d69e9euXUtVCQSCmTNnWlpaenl5mZub7969u253bW9vf+rUqRMnTtjY2KxYsWLVqlW1buiWk5P79ddf9+3bp6+vP3jwYJHa1atXr1ixYt26dZaWlp6enhcvXsRu90CrgGhj2TwLCwtVVFQKCgpq+jksnaSkpPDwcGo1nsfjeXl5WVlZfVUnQqHgPT+xOD+Po6pmYGkNtlcrpaysLDk52dTUlMViyXhJg/z9AMA3iMSvW63vc1gD+w+8j4degvfx+Pn5fdU7iMFggsf8t4mVlZWFhUXDRuIAAKAmQIFV08T7eIC2CoPBgDkoAGga4KVcTRPv4wEAAADqCSiwapp4Hw8AAABQT0CBVdPE+3gAAACAegIKrJqm38cDAAAA1AdQYNU0/T4eAAAAoD7Ae/k/rKys/Pz86HYYTqQE+3gAAABaIKDAvsDKymrevHkTJkwYNmzYhAkT5s2bB9oLaHWkpKQQBBEfHy+9WWhoqKqqamOP0lDg2CJNPy7QkgEFJgrex9O5c2dTU1OYOQRaCOnp6ZMmTdLX11dQUDA2Np47d25OTk5NjQ0NDTMyMmxsbKT3OWLEiJcvXza0pI2OLHdHz7kMtGHgBQ0ALZ23b986Ojq+fPnyzz//fP369d69e2/evOns7JybmyveuKKigslk6urqysnVEqaAzWZra2s3jsgyUVlZWYerZLy7OoCTwgCtCFBgANDACARlKSm7BYKyhupw5syZCgoK165dc3NzMzIyGjBgwI0bN96/f7906VLcwMTEZM2aNf7+/ioqKlOmTBGZZLtw4UKnTp3YbLaHh8eRI0cIgsjPz0dfTiEGBwd36dLl6NGjJiYmKioqI0eOLCoqwlXh4eE9evRQVVXV0ND4/vvv6fkea8LExGT16tWjR4/mcDj6+vo7d+6kqgiC2Lt37+DBg5WVldesWYMQunjxooODA4vFat++/cqVK6uqqnDLV69e9erVi8ViWVlZXb9+nepB5O4SExMHDhzI4/G4XG7Pnj3fvHkTHBx85MiRv//+myAIgiAiIiIQQk+fPu3duzebzdbQ0Jg6dSq1sxPbauvWrdPX1zczM/vqzwZoVkCBiSIUCtITn/CjItMTnwiFEnIIAYB0sj6Fv3m75dOnqw3SW25u7tWrV2fMmMFms6lCXV3dMWPGnDx5kgrGvWnTJhsbm7i4uOXLl9MvT0lJGT58uK+vb3x8/LRp0yidJ86bN2/Onz9/6dKlS5cuRUZGrl+/Hpd//vw5ICAgNjb25s2bDAZjyJAhsmRp2LRpk62t7aNHjwIDA+fPn0/XQEFBQYMHD3769OnEiROvXr06duzYOXPmJCUl7du3LzQ09JdffkEICYXCoUOHMpnMmJiYvXv3Ll68WOIo79+/x0ru1q1bcXFxEydOrKqqWrhwoZ+fn5eXV0ZGRkZGhouLS0lJiZeXl5qaWmxs7F9//XXjxo1Zs2ZRndy8eZPP51+/fv3SpUu13hfQsiDbFjjfT0FBQd0ufxkTtXv6+PX+I9dNHrfef+Tu6eNfxkQ1rIRAa6G0tDQpKam0tPRrL4yPn3LjZvv4hKkNIgZOC3nu3DmR8q1btyKEPn78SJKksbGxr68vVZWcnIwQevz4MUmSixcvtrGxoaqwAsvLyyNJMiQkREVFBZcHBQUpKSkVFhbi00WLFjk5OYkLk5WVhRB6+vSpyCgiGBsbe3l5UacjRowYMGAAPkYIzZs3j6rq2bPn2rVrqdOjR4/q6emRJHn16lUmk5meno7Lr1y5Qj0E+riBgYGmpqYVFRUiAkyYMGHw4MHU6f79+9XU1IqLi/Hp5cuXGQxGZmYmbqmjo1NeXi5+F0BTIvHrVuv7HIL5/ser+9FnDuwu1zEk5atzipdVlp85sHsYQpDQC5BOeUV2etphkqxCCOXk3kEI5eREvnq1FiFEEHJGRhMVFDRr6eIrIUkSIUQQBD6tKVnlixcvunbtSp1269atpg5NTExwNmeEkJ6eHtZVCKE3b94sX748JiYmOzsb215paWm1eog4OzvTj7dv306d0kWNi4uLjY3FVhdCSCAQlJWVlZSU8Pl8IyOjdu3aifdGJz4+vmfPnvLy8tKF4fP5dnZ2ysrK+NTV1VUoFL548UJHRwch1LlzZ5y1GWh1gAKrRigUnAk9UGbQgV5IyimUGXQ4E3rgf12dIK0XIIWK8qy09BCSrECI8a9SEaalhyAkJAgFHZ3v66zAOnbsSBBEUlKSiFvd8+fP1dTUNDWru6XeziKQJEkpOfSv2pMIXQ0QBEHNE/r4+BgaGh44cEBfX18oFNrY2NTB2YEuA11UoVC4cuXKoUOH0huzWCwROemX06FPq0pB5CGI9FnTowNaPo2+BrZ7926co8zBweGff/4Rb+Dv7098ibW1NVWbn58/c+ZMPT09FotlaWkZFhbWSHK+efK4XF0PIYTof+gEgRAqV9d98+RxI40LtA24XKtuXf9WUuqAECJJAfW/klKHbl3/5nLrvptQQ0OjX79+u3fvLi0tpQozMzOPHz8+YsSImt7sFBYWFrGxsdTpw4cPv2r0nJwcPp+/bNmyPn36WFpa5uXlyXghnvmkji0sLCQ2s7e3f/HiRccvYTAYVlZWaWlpHz58wM3u3bsn8XJbW9t//vlH3Jvx/+3deVgT19oA8AMhCyEB2UFkUVSWyiJEARGBylKvtth+LShWwYpVWxV3wVqhiopb3YpYuSwuBRdQsIoIVaE+IEURQSCCshhsoYoimxq2+f44t3NzwxYlCQTf39OnT2bOmTPvDMe8zMxhDo1G6+z87wNsc3Pze/futba24sXs7Gx5eXkYsjEMSDaBnTlzZtWqVd99911BQYGTk9OMGTN4PJ5QnYMHD9b+o6amRk1N7YsvvsBFbW1t7u7u1dXViYmJZWVlUVFRenp6Egr1csZlgkpD3b8O5OQIKv1yxmUJ7RcMGyzWeI7tOYQELx0Iju05FmugX5Q//fQTn8/39PT8/fffa2pq0tLS3N3d9fT0yDtvfViyZMmDBw82btxYXl5+9uzZuLg41PsFTXeqqqrq6urHjh179OjR9evX16xZI+KG2dnZu3fvLi8vj4iIOHfuXGBgYI/VtmzZcuLEidDQ0JKSEi6Xe+bMmc2bNyOE3NzcTExMFixYUFhYePPmzd7GnixfvrypqWnOnDl37tx5+PDhyZMny8rKEEJGRkZFRUVlZWX19fXt7e3z5s1jMBh+fn7FxcU3btxYsWLF/Pnz8f1DINMkm8B+/PHHRYsWBQQEmJmZHThwQF9fPzIyUqiOioqKzj/u3LnT0NCwcOFCXBQTE/PixYvk5GRHR0dDQ8OpU6daWVlJKNSWtr4GPfddCgD28mWeUAJ7+fJ2r7VFNm7cuDt37hgbG/v4+BgbG3/99deurq63bt1SU1Prd9vRo0cnJiaeP3/e0tIyMjISZwI6nS7iruXl5U+fPp2fnz9hwoTVq1fv2bNHxA3Xrl2bn58/ceLEbdu27du3z9PTs8dqnp6ely5dysjImDRpkr29/Y8//ohfnC0vL3/hwgU+nz958uSAgIDeUrW6uvr169dbWlqcnZ1tbW2joqLwjdDFixebmJhwOBxNTc3s7Gwmk3n16tUXL15MmjTp888/nz59+k8//STigYChTK6Pe+ID1NbWxmQyz5079+mnn+I1gYGB9+7dy8rK6m2Tjz/+mM/np6en48V//etfampqTCYzJSVFU1PT19d348aNFIrwsyg+n8/n8/HnpqYmfX39xsbG3l4t35vDx488r3raW6n6aK0Vft+8VYNA1r1586aqqgrfABdxk5LSdXV1F1RUOOPGBj18tLOxMV9H57MPzEX90peC7du3Hz16tKamRqJ7MTIyWrVq1apVqyS6FzCc9PjPrampSUVFpY/vcwlegdXX13d2dgpep2tra9fV1fVWv7a29sqVKwEBAeSaysrKxMTEzs7O1NTUzZs379u3r8dfxHbu3KnyD319/XeLdpHPQtTOR93TOUGgdv4in4Xv1ix4ryizJ4w13mBrE6+iMtHWJmGs8QZl9gf9byZhR44cuX37dmVl5cmTJ/fs2ePn5zfYEQEgHhIfhSg0AqqPm+/4vQCCQ626urq0tLSOHTtGoVBsbW3/+uuvPXv2bNmyRWjD4OBg8tY8vgJ7hziZDEX6SBX+09eIIP77JIwgEEL0kSpMhkiDncB7Tl/fn/wsJ0cxNFwyeLH818OHD8PCwl68eGFgYLB27drg4ODBjggA8ZBgAtPQ0KBQKIKXXE+fPu3twSlBEDExMfPnzxf8gwxdXV0qlUreMzQzM6urq2traxP6ow06nS76Pf0+BH8btDMinF/biBT+aa2jjT5SJfjboIE3DsBg2b9///79+6W5x+rqamnuDry3JJjAaDSara1tRkYG+QwsIyPDy8urx8pZWVmPHj1atGiR4EpHR8f4+Piuri78Vvjy8nJdXV2J/slh8LdBr968jjkX1/C8XlVd46sv/OHaCwAAhibJ3kJcs2bN/PnzORyOg4PDsWPHeDze0qVLEULBwcF//vnniRMnyJrR0dF2dnZCf96/bNmyw4cPBwYGrlix4uHDhzt27Fi5cqVEA0YIMRmKy+cvk/ReAAAADJBkE5iPj8/z58+3bt2K5+9JTU3FY2Rra2sF/yCssbExKSnp4MGDQpvr6+unp6evXr3a0tJST08vMDCwt3d6AgAAeN9IcBj9oOh32CUAInqHYfQAgHcz5IbRAwAAAJIDCQwAAIBMggQGwPtLaHZj8crMzCRnf5YmFxcXyb0ERJoHJfjTGayTOcRBAgNgSJPrhb+//2CHJmZGRkaC04YhhA4cOGBkZCSJfclcPpgyZUptba2KikofdSSauYcmmA8MgCGttrYWfzhz5syWLVvw29aRyFNhgaGmvb293xk4u6PRaDo6OpKIp/urIWQIXIEBIB6Vr/hFza+6/1f5ij+QZsm5GlRUVOTk5HR0dLS1tS0sLH777TdcwdraWktLC3++desWlUptaWlBCPF4PC8vLxaLpays7O3t/ffff/caeWWlq6srk8m0srISnHkrJydn2rRpioqK+vr6K1euJOfTOnXqFIfDYbPZOjo6vr6+5NzNCKHU1NTx48crKiq6uroKvo/j8ePHH3/8saqqqpKS0gcffPAOE/v5+/vPnj37hx9+0NLSUlZWXrJkCTmvZmtr64IFC1gslq6u7r59+wS36jHU6upqV1dXhJCqqip5LUsQxO7du8eMGaOoqGhlZZWYmNjvQQmRk5OLjIycMWOGoqLi6NGjz507h9fjO4Fnz551cXFhMBinTp1CCMXGxpqZmTEYDFNT0yNHjpCN5OXlTZw4kcFgcDicgoL/TkModMmYnZ3t7OzMZDJVVVU9PT0bGhr8/f2zsrIOHjyIL9BxnFlZWZMnT6bT6bq6ukFBQR0dHXhzFxeX5cuXr1mzRkNDw93d/W1/FkMIMbw0NjYihBobGwc7ECDzXr9+XVpa+vr1a1EqV7S+0b5e0Nt/Fa1vBh5PbGysiooK/vzZZ58tX76cIIgXL15QqdQRI0aUlJQQBLFjxw47OzuCILq6uiZOnDh16tQ7d+7k5uba2Ng4Ozt3b7OqqgohZGpqeunSpbKyss8//9zQ0LC9vZ0giKKiIhaLtX///vLy8uzs7IkTJ/r7++OtoqOjU1NTKyoqbt26ZW9vP2PGDLyex+PR6fTAwMAHDx6cOnUKvzeuoaGBIIiZM2e6u7sXFRVVVFT8+uuvWVlZ3YMxNDTcv3+/4Jr9+/cbGhriz35+fiwWy8fHp7i4+NKlS5qamps2bcJFy5YtGzVqVHp6elFR0axZs1gsVmBgYB+hdnR0JCUlIYTKyspqa2tfvnxJEMSmTZtMTU3T0tIqKipiY2PpdHpmZmbfByUEIaSurh4VFVVWVrZ582YKhVJaWkqeZCMjo6SkpMrKyj///PPYsWO6urp4MSkpSU1NLS4ujiCIlpYWTU1NfIy//vrrmDFjEEIFBQUEQdy4cYPcb0FBAZ1OX7Zs2b1794qLiw8fPvzs2bOXL186ODgsXrwYz63Y0dHx5MkTJpP5zTffcLncCxcuaGhohISE4FCdnZ1ZLNb69esfPHjA5XJ77nDS1eM/t36/zyGBAdCzt0pghU2tfSSwwqbWgccjmMAOHTo0YcIEgiCSk5M5HM5nn30WERFBEISHh8fGjRsJgkhPT6dQKDweD9cvKSlBCOXl5Qm1ib9b//3vfwtWw99o8+fP//rrr8maN2/elJeX73428vLyEELNzc0EQQQHB5uZmXV1deEi/NoB/J1rYWERGhra9wH2m8DU1NRaW/9zJiMjI1ksVmdnZ3NzM41GO336NF7//PlzRUVFMoH1FqpgPiAIoqWlhcFg5OTkkJUXLVo0d+7cvg9KCEJo6dKl5KKdnd2yZcuIf07ygQMHyCJ9ff34+Hhycdu2bQ4ODgRB/Pzzz0LH2GMCmzt3rqOjY/cAnJ2dBQ9806ZNJiYmZOQRERH4jOGa1tbW3VsYRO+WwOAWIgCyx8XFpaSkpL6+Pisry8XFxcXFJSsrq6OjIycnx9nZGSHE5XL19fXJmRnMzc1HjBjB5XJ7bM3S0hJ/0NXVRQjh+2z5+flxcXGsf3h6enZ1deHv4oKCAi8vL0NDQzab7eLighDCL9bhcrn29vbkjBMODg7kLlauXBkWFubo6BgSElJUVPRuR21lZcVkMsnGW1paampqKioq2trayH2pqamZmJiQm/QWqpDS0tI3b964u7uTx3vixImKioq+D6o7wVIHBwfBE87hcPCHZ8+e1dTULFq0iNxXWFgYuS+hY+xxL/fu3Zs+fXofYWBcLtfBwYGM3NHRsaWl5cmTJ0LxyDQYxAGA7JkwYYK6unpWVlZWVtbWrVv19fW3b99++/bt169fT506FfU0dVH3NSRyTAGu0NXVhf+/ZMkSobePGhgYtLa2enh4eHh4nDp1SlNTk8fjeXp64sdRRO+v9QkICPD09Lx8+XJ6evrOnTv37du3YsUKoTrKysr4N27Sy5cv+x53JyfX17uE+ghVCD7ky5cv6+npkSvxHBd9tN8vwROupKQkuK+oqCg7OzuyFM+5IeK+RBy/I/QTx42Ta8h4ZBpcgQEge+Tk5KZNm5aSklJcXOzk5GRhYdHe3n706FEbGxs2m40QMjc35/F45MzLpaWljY2NZmZmou/CxsampKRk7P+i0WgPHjyor68PDw93cnIyNTUVHMFhbm6em5tLLgp+Rgjp6+svXbr0/Pnza9eujYqK6r5HU1PT27dvC665ffu24OVUYWHh69evycZZLNaoUaPGjh1LpVLJfTU0NJSXl+PPfYSKx911dnaSkdPpdB6PJ3iw+Pq174MSIlTT1NS0ex1tbW09Pb3KykrBfY0ePRrvS+gYe9yLpaXltWvXuq+n0WjkEeHW8E1RvJiTk8NmswUz9HAgsVuagwOegQFxGcrPwAiCOHToEIVC4XA4eHH27NkUCmX9+vV4EQ/icHJyys/P/+OPP2xtbfsYxIGfshAE0dDQgBC6ceMGQRCFhYWKiorffPNNQUFBeXl5SkoKHjby9OlTGo22fv36ioqKlJSU8ePHky08fvyYRqOtXr36wYMHv/zyCx72jR/bBAYGpqWlVVZW5ufnT5482dvbu3swt27dkpeX/+GHH0pKSkpKSrZu3SovL5+bm4tL8SCOuXPnlpSUpKamamtrBwUF4aKlS5caGBj89ttv9+/f/+STT8hBHH2E+uTJEzk5ubi4uKdPn+KnYt999526unpcXNyjR4/u3r37008/4YEVfRyUEISQhoZGdHR0WVnZli1b5OXl8cgaoZNMEERUVJSiouKBAwfKysqKiopiYmL27dtHEERzc7OGhgY+xsuXL48dOxb19AysrKyMRqMtW7assLCQy+UeOXLk2bNnBEEsXrx40qRJVVVVz5496+zsxIM4vv32Wy6Xm5ycLDSIo8fHhIMIBnEQBCQwID5DPIHdv38fIbRu3Tq8iKesvHTpElnh8ePHn3zyiZKSEpvN/uKLL+rq6rq32UcCIwgiLy8PPxZSUlKytLTcvn07Xh8fH29kZESn0x0cHC5evCjYwq+//jp27Fg6ne7k5BQTE0N+5y5fvtzY2JhOp2tqas6fP7++vr7HY8zIyHByclJVVVVVVZ06dWpGRgZZ5Ofn5+XltWXLFnV1dRaLFRAQ8ObNf8Z2Njc3f/nll0wmU1tbe/fu3YLfzn2EunXrVh0dHTk5OT8/P4Igurq6Dh48aGJiQqVSNTU1PT09yaGSvR2UEIRQRESEu7s7nU43NDRMSEjo8SRjv/zyi7W1NY1GU1VVnTZt2vnz5/H6W7duWVlZ0Wg0a2trPFSyewIjCCIzM3PKlCl0On3EiBF4GD1BEGVlZfb29vgGY1VVFa42adIk/DdkGzduxONLiWGUwOBt9AD07K3eRl/U/MrjTnlvpemc8ZZsplije+/4+/u/fPkyOTl5sAPplZyc3IULF2bPnj3YgcgkeBs9AIOGRaG8cykA4N3AKEQAxGAMk55jZ9Yi8AidxKJQxjDp0g8JgGEPEhgA4gFZSqLi4uIGO4R+DLPHMTIBbiECAACQSZDAAAAAyCRIYAD0Be4LASAF7/YPDRIYAD3Db/fp8c1DAADxwv/QKG85XhcGcQDQMwUFBSaT+ezZMyqVKi8Pv+oBICldXV3Pnj1jMpkKCm+XkiCBAdAzOTk5XV3dqqqqx48fD3YsAAxz8vLyBgYGvb1vujeQwADoFY1GGzduHNxFBEDSaDTaO9zngAQGQF/k5eVFeZUUAED64M4+AAAAmQQJDAAAgEyCBAYAAEAmDbdnYPiv4ZqamgY7EAAAAAOCv8n7+Bvn4ZbAmpubEUJ4LnAAAACyrrm5WUVFpcei4TahZVdX119//cVms9/27wkENTU16evr19TUDPFZMWUlTiQ7oUKcYicrocpKnEh2Qh14nARBNDc3jxw5srcR9sPtCkxeXn7UqFFiaUpZWXmI9w9MVuJEshMqxCl2shKqrMSJZCfUAcbZ27UXBoM4AAAAyCRIYAAAAGQSJLAe0On0kJAQOn2oT7ArK3Ei2QkV4hQ7WQlVVuJEshOqFOIcboM4AAAAvCfgCgwAAIBMggQGAABAJkECAwAAIJMggQEAAJBJ70UCO3LkyOjRoxkMhq2t7c2bN3usk5WVZWtry2AwxowZc/ToUcGipKQkc3NzOp1ubm5+4cKFt21ZOnFGRUU5OTmpqqqqqqq6ubnl5eWRRaGhoXICdHR0BhjnAEONi4uT+19v3rx5q5alE6eLi4tQnDNnzsRFYj+l/cZZW1vr6+trYmIiLy+/atUqoVKpddEBhirNXjqQOKXZRQcY6pDqpefPn3d3d9fU1FRWVnZwcLh69apgqUR6KTHcnT59mkqlRkVFlZaWBgYGKikpPX78WKhOZWUlk8kMDAwsLS2NioqiUqmJiYm4KCcnh0Kh7Nixg8vl7tixQ0FBITc3V/SWpRanr69vREREQUEBl8tduHChiorKkydPcFFISMgHH3xQ+4+nT5++c5BiCTU2NlZZWblWwFu1LLU4nz9/TkZYXFxMoVBiY2NxkXhPqShxVlVVrVy58vjx49bW1oGBgYJFUuuiAw9Var10gHFKrYsOPNQh1UsDAwN37dqVl5dXXl4eHBxMpVLv3r2LiyTUS4d/Aps8efLSpUvJRVNT06CgIKE6GzZsMDU1JReXLFlib2+PP3t7e3/00Udkkaen55w5c0RvWWpxCuro6GCz2cePH8eLISEhVlZW7xyY2EONjY1VUVF555alFqeg/fv3s9nslpYWvCjeU/pWR+3s7Cz0FSa1LjrwUAVJtJcOME6pddGBhypo6PRSzNzc/IcffsCfJdRLh/ktxLa2tvz8fA8PD3KNh4dHTk6OULVbt24J1vH09Lxz5057e3uPRXhzEVuWWpyCXr161d7erqamRq55+PDhyJEjR48ePWfOnMrKyncLUoyhtrS0GBoajho1atasWQUFBW/VsjTjJEVHR8+ZM0dJSYlcI65TOvCjlk4XFXuDkuulYolTCl1U7A0OqV7a1dXV3NxM/nwl1EuHeQKrr6/v7OzU1tYm12hra9fV1QlVq6urE6rT0dFRX1/fYxHeXMSWpRanoKCgID09PTc3N7xoZ2d34sSJq1evRkVF1dXVTZky5fnz5+8Wp1hCNTU1jYuLu3jxYkJCAoPBcHR0fPjwoegtSy1OUl5eXnFxcUBAALlGjKd04EctnS4q9gYl10sHHqd0uqh4GxxqvXTfvn2tra3e3t54UUK9dLi9jb5HglOrEATR40wrQnUE1/SxuSgtSy1ObPfu3QkJCZmZmQwGA6+ZMWMG/mBhYeHg4GBsbHz8+PE1a9YMVqj29vb29vZ4vaOjo42NzeHDhw8dOiR6y9KJkxQdHT1hwoTJkyeTa8R+Sgd41FLrouJqUAq9dCBxSrOLiqvBIdVLExISQkNDU1JStLS0RNn8nc/AML8C09DQoFAogvn86dOngtke09HREaqjoKCgrq7eYxHeXMSWpRYntnfv3h07dqSnp1taWva4IyUlJQsLC/zr5OCGisnLy0+aNAnHMzRP6atXr06fPi34i62QAZ7SgR+1dLqoGBuUdC8V74FLrouKscEh1UvPnDmzaNGis2fPkpfXSGK9dJgnMBqNZmtrm5GRQa7JyMiYMmWKUDUHBwfBOunp6RwOh0ql9liENxexZanFiRDas2fPtm3b0tLSOBxObzvi8/lcLldXV/fd4hRXqCSCIO7du4fjGYKnFCF09uxZPp//5Zdf9rajAZ7SgR+1dLqouBqUQi8V74FLrouKscGh00sTEhL8/f3j4+PJ0fyYpHqpiIM9ZBceoxkdHV1aWrpq1SolJaXq6mqCIIKCgubPn4/r4LHUq1evLi0tjY6OFhxLnZ2dTaFQwsPDuVxueHh499Gf3VselDh37dpFo9ESExPJUbPNzc24aO3atZmZmZWVlbm5ubNmzWKz2QOJc+ChhoaGpqWlVVRUFBQULFy4UEFB4Y8//ui75UGJE5s6daqPj49Qy+I9paLESRBEQUFBQUGBra2tr69vQUFBSUkJXi+1LjrwUKXWSwcYp9S66MBDxYZIL42Pj1dQUIiIiCB/vi9fvsRFEuqlwz+BEQQRERFhaGhIo9FsbGyysrLwSj8/P2dnZ7JOZmbmxIkTaTSakZFRZGSk4Obnzp0zMTGhUqmmpqZJSUn9tjwocRoaGgr9ahISEoKLfHx8dHV1qVTqyJEjP/vsM6GuL/1QV61aZWBgQKPRNDU18YijflselDgJgigrK8O/LQo1K/ZTKkqcQj9fQ0NDskhqXXSAoUqzlw4kTml20QGGSgylXurs7CwUp5+fH7m5JHopTKcCAABAJg3zZ2AAAACGK0hgAAAAZBIkMAAAADIJEhgAAACZBAkMAACATIIEBgAAQCZBAgMAACCTIIEBMBzExcWNGDGixyJ/f//Zs2dLM5jQ0FBra2tp7hG8nyCBgfeIv78/nl6dSqVqa2u7u7vHxMR0dXUNdlySdfDgwbi4ONHrC56lMWPGrFu3rrW19a32uG7dumvXrpGtSTl9gvcHJDDwfvnoo49qa2urq6uvXLni6uoaGBg4a9asjo6OwY7rP9ra2sTepoqKSm8XZ73BZ6mysjIsLOzIkSPr1q0TcUOCIDo6OlgsVveZBwAQO0hg4P1Cp9N1dHT09PRsbGw2bdqUkpJy5coV8gKlsbHx66+/1tLSUlZW/vDDDwsLC/F6fE8sJibGwMCAxWItW7ass7Nz9+7dOjo6Wlpa27dvJ9vn8XheXl4sFktZWdnb2/vvv/8mi8LCwrS0tNhsdkBAQFBQEHmTDV+j7Ny5c+TIkePHj0cInTp1isPhsNlsHR0dX1/fp0+f4pqZmZlycnKXL1+2srJiMBh2dnb3798XPLqrV6+amZmxWCycgQTbx5+7urp27do1duxYOp1uYGAgGHn3s6Svr+/r6ztv3rzk5OR+o7p69SqHw6HT6Tdv3iRvIYaGhh4/fjwlJQVf0mVmZn744YfLly8nd/T8+XM6nX79+vW3+RkC8B+QwMB77cMPP7Sysjp//jxCiCCImTNn1tXVpaam5ufn29jYTJ8+/cWLF7hmRUXFlStX0tLSEhISYmJiZs6c+eTJk6ysrF27dm3evDk3Nxe3MHv27BcvXmRlZWVkZFRUVPj4+ODNf/nll+3bt+/atSs/P9/AwCAyMlIwjGvXrnG53IyMjEuXLiGE2tratm3bVlhYmJycXFVV5e/vL1h5/fr1e/fuvX37tpaW1ieffNLe3o7Xv3r1au/evSdPnvz99995PF6Pl03BwcG7du36/vvvS0tL4+PjRZl4SVFREe+i76g2bNiwc+dOLpcrOMvXunXrvL29cTatra2dMmVKQEBAfHw8n88nT8vIkSNdXV37DQOAHgzg3cQAyBg/Pz8vLy+hlT4+PmZmZgRBXLt2TVlZ+c2bN2SRsbHxzz//TBBESEgIk8lsamrC6z09PY2MjDo7O/GiiYnJzp07CYJIT0+nUCg8Hg+vLykpQQjl5eURBGFnZ/ftt9+SLTs6OlpZWZFRaWtr8/n8HmPOy8tDCOFpR27cuIEQOn36NC56/vy5oqLimTNnCIKIjY1FCD169AgXRUREaGtrCx11U1MTnU6PiooS/Sz98ccf6urq3t7e/UaVnJxMloaEhAgeneA5f/PmjZqaGo6ZIAhra+vQ0NC+4wGgN3AFBt53xD9TmOfn57e0tKirq7P+UVVVVVFRgasZGRmx2Wz8WVtb29zcXF5enlzE99O4XK6+vr6+vj5eb25uPmLECC6XixAqKysTnO5d8DNCyMLCgkajkYsFBQVeXl6GhoZsNtvFxQUhxOPxyFIHBwf8QU1NzcTEBLePEGIymcbGxvizrq4ueYuPxOVy+Xz+9OnT+z0nly5dYrFYDAbDwcFh2rRphw8f7jeqPiaoFESn07/88suYmBiE0L179woLC4Wu5AAQncJgBwDAIONyuaNHj0YIdXV16erqZmZmCpaSwx8Ep2nGI/QEF/FQRjIXkgTXCBYR/zuNkZKSEvm5tbXVw8PDw8Pj1KlTmpqaPB7P09Ozj8EdZLNCIRHdZkpSVFTsrREhrq6ukZGReCop3Gy/UQkeQt8CAgKsra2fPHkSExMzffr07pOEASAiuAID77Xr16/fv3////7v/xBCNjY2dXV1CgoKYwVoaGiI3pq5uTmPx6upqcGLpaWljY2NZmZmCCETExN82w27c+dOb408ePCgvr4+PDzcycnJ1NS0+4UUft6GEGpoaCgvLzc1NRUxvHHjxikqKpID3PugpKQ0duxYQ0NDMin2G1VvaDRaZ2en4BoLCwsOhxMVFRUfH//VV1+J2A4A3UECA+8XPp9fV1f3559/3r17d8eOHV5eXrNmzVqwYAFCyM3NzcHBYfbs2VevXq2urs7Jydm8eXMfmaY7Nzc3S0vLefPm3b17Ny8vb8GCBc7Ozvje2ooVK6Kjo48fP/7w4cOwsLCioiKhazUSngv48OHDlZWVFy9e3LZtm1CFrVu3Xrt2rbi42N/fX0NDQ/S/smIwGBs3btywYcOJEycqKipyc3Ojo6NF3LbfqHpjZGRUVFRUVlZWX19PjjcJCAgIDw/v7Oz89NNPRWwHgO4ggYH3S1pamq6urpGR0UcffXTjxo1Dhw6lpKRQKBSEkJycXGpq6rRp07766qvx48fPmTOnurpalHF6JDk5ueTkZFVV1WnTprm5uY0ZM+bMmTO4aN68ecHBwevWrbOxscFD+BgMRo+NaGpqxsXFnTt3ztzcPDw8fO/evUIVwsPDAwMDbW1ta2trL168KPjwrF/ff//92rVrt2zZYmZm5uPjI/qFVL9R9Wbx4sUmJiYcDkdTUzM7OxuvnDt3roKCgq+vb28nAQBR9HCjHAAgae7u7jo6OidPnnyrrTIzM11dXRsaGt72D5OHmpqaGiMjo9u3b9vY2Ax2LECGwSAOAKTh1atXR48e9fT0pFAoCQkJv/32W0ZGxmAHNQja29tra2uDgoLs7e0he4EBggQGgDTg+5NhYWF8Pt/ExCQpKcnNzW2wgxoE2dnZrq6u48ePT0xMHOxYgMyDW4gAAABkEgziAAAAIJMggQEAAJBJkMAAAADIJEhgAAAAZBIkMAAAADIJEhgAAACZBAkMAACATIIEBgAAQCZBAgMAACCT/h+bLstzHxPJMwAAAABJRU5ErkJggg==",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1148,10 +1153,82 @@
    ],
    "source": [
     "# Plot of curves on validation data\n",
-    "fpred_standard.plot_frontier(prefix='Base method ', new_plot=False, show_original=False)\n",
+    "# This shows that the first three approaches are basically interchangable\n",
+    "fpred_true_groups.plot_frontier(prefix='True Groups ', new_plot=False, show_original=False)\n",
+    "fpred_standard.plot_frontier(prefix='Base method ', new_plot=False)\n",
     "fpred_thresh.plot_frontier(prefix='Single threshold ', new_plot=False, show_original=False)\n",
-    "fpred.plot_frontier(prefix='Two heads ', new_plot=False)\n"
+    "fpred.plot_frontier(prefix='Two heads ', new_plot=False)\n",
+    "plt.ylim(bottom=0.75)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'target': array([False,  True,  True, ..., False, False, False]),\n",
+       " 'data':            age  workclass    fnlwgt  education  education-num  marital-status  \\\n",
+       " 4     1.383055   2.747460  2.410016   1.290191       1.166193        1.323453   \n",
+       " 5     2.474940   2.747460  1.701862   3.870572       3.498579        1.323453   \n",
+       " 6     1.164678   2.747460  2.764848   3.870572       3.498579        1.323453   \n",
+       " 8     0.072792   2.747460  2.298162   3.870572       3.498579        2.646906   \n",
+       " 13    1.747016   2.747460  2.448812   3.870572       3.498579        0.000000   \n",
+       " ...        ...        ...       ...        ...            ...             ...   \n",
+       " 9740  0.800716   2.747460  1.251551   2.064305       3.887310        1.323453   \n",
+       " 9743  1.892601   1.373730  0.714200   3.870572       3.498579        0.000000   \n",
+       " 9747  0.873508   2.747460  1.244875   3.870572       3.498579        2.646906   \n",
+       " 9762  0.727923   2.747460  1.737887   3.870572       3.498579        2.646906   \n",
+       " 9768  1.819809   0.686865  0.278374   2.838419       3.109848        1.323453   \n",
+       " \n",
+       "       occupation  relationship      race  capital-gain  capital-loss  \\\n",
+       " 4       1.419319      0.000000  4.670472           0.0           0.0   \n",
+       " 5       2.838638      0.000000  4.670472           0.0           0.0   \n",
+       " 6       0.709659      0.000000  4.670472           0.0           0.0   \n",
+       " 8       1.419319      1.874259  4.670472           0.0           0.0   \n",
+       " 13      0.709659      0.624753  4.670472           0.0           0.0   \n",
+       " ...          ...           ...       ...           ...           ...   \n",
+       " 9740    0.709659      0.000000  4.670472           0.0           0.0   \n",
+       " 9743    2.602085      2.499012  4.670472           0.0           0.0   \n",
+       " 9747    2.838638      1.874259  4.670472           0.0           0.0   \n",
+       " 9762    0.946213      0.624753  4.670472           0.0           0.0   \n",
+       " 9768    3.311744      0.000000  4.670472           0.0           0.0   \n",
+       " \n",
+       "       hours-per-week  native-country  \n",
+       " 4           3.189289        1.034387  \n",
+       " 5           3.189289        0.000000  \n",
+       " 6           4.824822        5.042635  \n",
+       " 8           2.371523        5.042635  \n",
+       " 13          3.679949        5.042635  \n",
+       " ...              ...             ...  \n",
+       " 9740        3.352842        5.042635  \n",
+       " 9743        3.189289        5.042635  \n",
+       " 9747        3.189289        5.042635  \n",
+       " 9762        3.189289        5.042635  \n",
+       " 9768        3.189289        0.000000  \n",
+       " \n",
+       " [12211 rows x 13 columns],\n",
+       " 'groups': array([' Male', ' Male', ' Male', ..., ' Female', ' Female', ' Male'],\n",
+       "       dtype=object)}"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/src/oxonfair/learners/fair.py b/src/oxonfair/learners/fair.py
index 88b0a79..a22ad1d 100644
--- a/src/oxonfair/learners/fair.py
+++ b/src/oxonfair/learners/fair.py
@@ -1077,7 +1077,7 @@ def capped_identity(array):
             use_fast = 'hybrid'
     if use_actual_groups is True:
         fpred = FairPredictor(capped_identity, val_data, threshold=0, use_fast=use_fast, logit_scaling=logit_scaling)
-    if use_actual_groups == 'single_threshold':
+    elif use_actual_groups == 'single_threshold':
         fpred = FairPredictor(capped_identity, val_data, inferred_groups=single_threshold,
                               threshold=0, use_fast=use_fast, logit_scaling=False)
     else: