diff --git a/docs/content/tutorials/snmCATseq_glmPCA_analysis.ipynb b/docs/content/tutorials/snmCATseq_glmPCA_analysis.ipynb
index cd23905..93add7a 100644
--- a/docs/content/tutorials/snmCATseq_glmPCA_analysis.ipynb
+++ b/docs/content/tutorials/snmCATseq_glmPCA_analysis.ipynb
@@ -9,15 +9,18 @@
     "\n",
     "\n",
     "\n",
-    "Starting from the publicly available single-cell methylation data from [snmCATseq](https://www.sciencedirect.com/science/article/pii/S2666979X22000271?via%3Dihub) , we re-processed a subset of the data to extract methlated/unmethylated reads in small genomics bins (10kb), yielding non-Gaussian data. \n",
+    "Starting from the publicly available single-cell methylation data from [snmCATseq](https://www.sciencedirect.com/science/article/pii/S2666979X22000271?via%3Dihub) , we re-processed a subset of the data to extract methlated/unmethylated reads in small genomics bins (10kb), yielding non-Gaussian data (see tutorial on preprocessing [here](https://sincei.readthedocs.io/en/latest/content/tutorials/snmCATseq_preprocessing.html)). \n",
     "\n",
+    "This data was stored as pickle files `snmC2Tseq_eckerlab/10k_bin/processed_data_*_2024_06_13.pkl`, which we will import here.\n",
+    "\n",
+    "Another file named `mmc5.xlsx` contains metadata for celltype identification.\n",
     "\n",
     "The data is losely following a Beta distribution, and we thus employ GLM-PCA with Beta distribution to find a lower-dimension representation.\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "id": "487f311a-b03e-4998-9d61-53341a7f63ae",
    "metadata": {
     "scrolled": true,
@@ -53,7 +56,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "id": "6457d315-2dcd-48ee-8a4e-6d40e00c38f4",
    "metadata": {},
    "outputs": [],
@@ -141,9 +144,9 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
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     {
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       "should be replaced with\n",
       "Q, R = torch.linalg.qr(A, 'reduced' if some else 'complete') (Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/aten/src/ATen/native/BatchLinearAlgebra.cpp:2422.)\n",
       "  q, r = torch.qr(X + G)\n",
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      ]
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      ]
     },
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      "name": "stderr",
      "output_type": "stream",
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       "\n"
      ]
     },
@@ -600,87 +603,87 @@
      "name": "stderr",
      "output_type": "stream",
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       "\n"
      ]
     },
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      "name": "stderr",
      "output_type": "stream",
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       "\n"
      ]
     },
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      "name": "stderr",
      "output_type": "stream",
      "text": [
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       "\n"
      ]
     },
@@ -864,87 +867,87 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n"
      ]
     },
@@ -952,87 +955,87 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
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+      " 67%|████████████████████████████████████████████████████████████████████████████████████████████████████▌                                                 | 335/500 [01:32<00:45,  3.65it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 67%|████████████████████████████████████████████████████████████████████████████████████████████████████▊                                                 | 336/500 [01:33<00:49,  3.32it/s]\u001b[A\u001b[A\n",
+      " 67%|████████████████████████████████████████████████████████████████████████████████████████████████████▊                                                 | 336/500 [01:32<00:44,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
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+      " 67%|█████████████████████████████████████████████████████████████████████████████████████████████████████                                                 | 337/500 [01:33<00:44,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
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+      " 68%|█████████████████████████████████████████████████████████████████████████████████████████████████████▍                                                | 338/500 [01:33<00:44,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 68%|█████████████████████████████████████████████████████████████████████████████████████████████████████▋                                                | 339/500 [01:34<00:47,  3.38it/s]\u001b[A\u001b[A\n",
+      " 68%|█████████████████████████████████████████████████████████████████████████████████████████████████████▋                                                | 339/500 [01:33<00:43,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
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+      " 68%|██████████████████████████████████████████████████████████████████████████████████████████████████████                                                | 340/500 [01:34<00:43,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 68%|██████████████████████████████████████████████████████████████████████████████████████████████████████▎                                               | 341/500 [01:34<00:48,  3.27it/s]\u001b[A\u001b[A\n",
+      " 68%|██████████████████████████████████████████████████████████████████████████████████████████████████████▎                                               | 341/500 [01:34<00:43,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
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+      " 68%|██████████████████████████████████████████████████████████████████████████████████████████████████████▌                                               | 342/500 [01:34<00:43,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
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+      " 69%|██████████████████████████████████████████████████████████████████████████████████████████████████████▉                                               | 343/500 [01:34<00:42,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 69%|███████████████████████████████████████████████████████████████████████████████████████████████████████▏                                              | 344/500 [01:35<00:52,  2.98it/s]\u001b[A\u001b[A\n",
+      " 69%|███████████████████████████████████████████████████████████████████████████████████████████████████████▏                                              | 344/500 [01:35<00:42,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 69%|███████████████████████████████████████████████████████████████████████████████████████████████████████▍                                              | 345/500 [01:36<00:49,  3.12it/s]\u001b[A\u001b[A\n",
+      " 69%|███████████████████████████████████████████████████████████████████████████████████████████████████████▍                                              | 345/500 [01:35<00:42,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
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+      " 69%|███████████████████████████████████████████████████████████████████████████████████████████████████████▊                                              | 346/500 [01:35<00:41,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 69%|████████████████████████████████████████████████████████████████████████████████████████████████████████                                              | 347/500 [01:36<00:53,  2.85it/s]\u001b[A\u001b[A\n",
+      " 69%|████████████████████████████████████████████████████████████████████████████████████████████████████████                                              | 347/500 [01:35<00:41,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 70%|████████████████████████████████████████████████████████████████████████████████████████████████████████▍                                             | 348/500 [01:37<00:49,  3.05it/s]\u001b[A\u001b[A\n",
+      " 70%|████████████████████████████████████████████████████████████████████████████████████████████████████████▍                                             | 348/500 [01:36<00:41,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 70%|████████████████████████████████████████████████████████████████████████████████████████████████████████▋                                             | 349/500 [01:37<00:47,  3.21it/s]\u001b[A\u001b[A\n",
+      " 70%|████████████████████████████████████████████████████████████████████████████████████████████████████████▋                                             | 349/500 [01:36<00:41,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
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+      " 70%|█████████████████████████████████████████████████████████████████████████████████████████████████████████                                             | 350/500 [01:36<00:40,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 70%|█████████████████████████████████████████████████████████████████████████████████████████████████████████▎                                            | 351/500 [01:38<00:44,  3.35it/s]\u001b[A\u001b[A\n",
+      " 70%|█████████████████████████████████████████████████████████████████████████████████████████████████████████▎                                            | 351/500 [01:37<00:40,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 70%|█████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                            | 352/500 [01:38<00:43,  3.42it/s]\u001b[A\u001b[A\n",
+      " 70%|█████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                            | 352/500 [01:37<00:40,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 71%|█████████████████████████████████████████████████████████████████████████████████████████████████████████▉                                            | 353/500 [01:38<00:42,  3.47it/s]\u001b[A\u001b[A\n",
+      " 71%|█████████████████████████████████████████████████████████████████████████████████████████████████████████▉                                            | 353/500 [01:37<00:40,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 71%|██████████████████████████████████████████████████████████████████████████████████████████████████████████▏                                           | 354/500 [01:38<00:44,  3.26it/s]\u001b[A\u001b[A\n",
+      " 71%|██████████████████████████████████████████████████████████████████████████████████████████████████████████▏                                           | 354/500 [01:37<00:39,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 71%|██████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                           | 355/500 [01:39<00:43,  3.32it/s]\u001b[A\u001b[A\n",
+      " 71%|██████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                           | 355/500 [01:38<00:39,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 71%|██████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                           | 356/500 [01:39<00:42,  3.40it/s]\u001b[A\u001b[A\n",
+      " 71%|██████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                           | 356/500 [01:38<00:39,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 71%|███████████████████████████████████████████████████████████████████████████████████████████████████████████                                           | 357/500 [01:39<00:43,  3.30it/s]\u001b[A\u001b[A\n",
+      " 71%|███████████████████████████████████████████████████████████████████████████████████████████████████████████                                           | 357/500 [01:38<00:38,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 72%|███████████████████████████████████████████████████████████████████████████████████████████████████████████▍                                          | 358/500 [01:40<00:45,  3.10it/s]\u001b[A\u001b[A\n",
+      " 72%|███████████████████████████████████████████████████████████████████████████████████████████████████████████▍                                          | 358/500 [01:38<00:38,  3.67it/s]\u001b[A\u001b[A\n",
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+      " 72%|███████████████████████████████████████████████████████████████████████████████████████████████████████████▋                                          | 359/500 [01:39<00:38,  3.67it/s]\u001b[A\u001b[A\n",
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+      " 72%|████████████████████████████████████████████████████████████████████████████████████████████████████████████                                          | 360/500 [01:39<00:38,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 72%|████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                                         | 361/500 [01:41<00:42,  3.27it/s]\u001b[A\u001b[A\n",
+      " 72%|████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                                         | 361/500 [01:39<00:37,  3.67it/s]\u001b[A\u001b[A\n",
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+      " 72%|████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                         | 362/500 [01:40<00:37,  3.66it/s]\u001b[A\u001b[A\n",
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+      " 73%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                                        | 364/500 [01:40<00:37,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
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+      " 73%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                        | 365/500 [01:40<00:36,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 73%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                        | 366/500 [01:42<00:38,  3.50it/s]\u001b[A\u001b[A\n",
+      " 73%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                        | 366/500 [01:41<00:36,  3.68it/s]\u001b[A\u001b[A\n",
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+      " 73%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████                                        | 367/500 [01:41<00:36,  3.67it/s]\u001b[A\u001b[A\n",
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+      " 74%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                                       | 368/500 [01:41<00:35,  3.67it/s]\u001b[A\u001b[A\n",
       "\n"
      ]
     },
@@ -1040,87 +1043,87 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
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+      " 75%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                                      | 373/500 [01:43<00:34,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 75%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                                     | 374/500 [01:44<00:36,  3.43it/s]\u001b[A\u001b[A\n",
+      " 75%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                                     | 374/500 [01:43<00:34,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 75%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                     | 375/500 [01:45<00:37,  3.36it/s]\u001b[A\u001b[A\n",
+      " 75%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                     | 375/500 [01:43<00:34,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 75%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                     | 376/500 [01:45<00:36,  3.41it/s]\u001b[A\u001b[A\n",
+      " 75%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                     | 376/500 [01:43<00:33,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 75%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████                                     | 377/500 [01:45<00:35,  3.48it/s]\u001b[A\u001b[A\n",
+      " 75%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████                                     | 377/500 [01:44<00:33,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 76%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                                    | 378/500 [01:46<00:34,  3.49it/s]\u001b[A\u001b[A\n",
+      " 76%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                                    | 378/500 [01:44<00:33,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 76%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                                    | 379/500 [01:46<00:34,  3.52it/s]\u001b[A\u001b[A\n",
+      " 76%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                                    | 379/500 [01:44<00:32,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 76%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████                                    | 380/500 [01:46<00:33,  3.55it/s]\u001b[A\u001b[A\n",
+      " 76%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████                                    | 380/500 [01:44<00:32,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 76%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                                   | 381/500 [01:46<00:33,  3.58it/s]\u001b[A\u001b[A\n",
+      " 76%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                                   | 381/500 [01:45<00:32,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 76%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                   | 382/500 [01:47<00:32,  3.59it/s]\u001b[A\u001b[A\n",
+      " 76%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                   | 382/500 [01:45<00:32,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 77%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                                   | 383/500 [01:47<00:32,  3.60it/s]\u001b[A\u001b[A\n",
+      " 77%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                                   | 383/500 [01:45<00:31,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 77%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                                  | 384/500 [01:47<00:32,  3.56it/s]\u001b[A\u001b[A\n",
+      " 77%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                                  | 384/500 [01:46<00:31,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 77%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                  | 385/500 [01:47<00:32,  3.52it/s]\u001b[A\u001b[A\n",
+      " 77%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                  | 385/500 [01:46<00:31,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 77%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                  | 386/500 [01:48<00:32,  3.55it/s]\u001b[A\u001b[A\n",
+      " 77%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                  | 386/500 [01:46<00:31,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 77%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                                  | 387/500 [01:48<00:31,  3.55it/s]\u001b[A\u001b[A\n",
+      " 77%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                                  | 387/500 [01:46<00:30,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 78%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                                 | 388/500 [01:48<00:31,  3.54it/s]\u001b[A\u001b[A\n",
+      " 78%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                                 | 388/500 [01:47<00:30,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 78%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                                 | 389/500 [01:49<00:31,  3.54it/s]\u001b[A\u001b[A\n",
+      " 78%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                                 | 389/500 [01:47<00:30,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 78%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                                 | 390/500 [01:49<00:30,  3.56it/s]\u001b[A\u001b[A\n",
+      " 78%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                                 | 390/500 [01:47<00:29,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 78%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                                | 391/500 [01:49<00:30,  3.59it/s]\u001b[A\u001b[A\n",
+      " 78%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                                | 391/500 [01:47<00:29,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 78%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                | 392/500 [01:49<00:30,  3.58it/s]\u001b[A\u001b[A\n",
+      " 78%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                | 392/500 [01:48<00:29,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 79%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                                | 393/500 [01:50<00:30,  3.55it/s]\u001b[A\u001b[A\n",
+      " 79%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                                | 393/500 [01:48<00:29,  3.59it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 79%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                               | 394/500 [01:50<00:30,  3.53it/s]\u001b[A\u001b[A\n",
+      " 79%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                               | 394/500 [01:48<00:29,  3.58it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 79%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                               | 395/500 [01:50<00:29,  3.56it/s]\u001b[A\u001b[A\n",
+      " 79%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                               | 395/500 [01:49<00:29,  3.57it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 79%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                               | 396/500 [01:51<00:29,  3.50it/s]\u001b[A\u001b[A\n",
+      " 79%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                               | 396/500 [01:49<00:28,  3.60it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 79%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                               | 397/500 [01:51<00:29,  3.51it/s]\u001b[A\u001b[A\n",
+      " 79%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                               | 397/500 [01:49<00:28,  3.63it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 80%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                              | 398/500 [01:51<00:28,  3.52it/s]\u001b[A\u001b[A\n",
+      " 80%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                              | 398/500 [01:49<00:28,  3.64it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 80%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                              | 399/500 [01:51<00:28,  3.54it/s]\u001b[A\u001b[A\n",
+      " 80%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                              | 399/500 [01:50<00:28,  3.57it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 80%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                              | 400/500 [01:52<00:28,  3.53it/s]\u001b[A\u001b[A\n",
+      " 80%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                              | 400/500 [01:50<00:27,  3.60it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 80%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                             | 401/500 [01:52<00:29,  3.41it/s]\u001b[A\u001b[A\n",
+      " 80%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                             | 401/500 [01:50<00:27,  3.62it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 80%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                             | 402/500 [01:52<00:28,  3.45it/s]\u001b[A\u001b[A\n",
+      " 80%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                             | 402/500 [01:50<00:27,  3.61it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 81%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                             | 403/500 [01:53<00:28,  3.46it/s]\u001b[A\u001b[A\n",
+      " 81%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                             | 403/500 [01:51<00:26,  3.62it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 81%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                            | 404/500 [01:53<00:27,  3.51it/s]\u001b[A\u001b[A\n",
+      " 81%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                            | 404/500 [01:51<00:26,  3.64it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 81%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                            | 405/500 [01:53<00:27,  3.51it/s]\u001b[A\u001b[A\n",
+      " 81%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                            | 405/500 [01:51<00:26,  3.65it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 81%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                            | 406/500 [01:53<00:26,  3.54it/s]\u001b[A\u001b[A\n",
+      " 81%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                            | 406/500 [01:52<00:28,  3.31it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 81%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                            | 407/500 [01:54<00:26,  3.57it/s]\u001b[A\u001b[A\n",
+      " 81%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                            | 407/500 [01:52<00:27,  3.42it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 82%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                           | 408/500 [01:54<00:25,  3.57it/s]\u001b[A\u001b[A\n",
+      " 82%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                           | 408/500 [01:52<00:26,  3.48it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 82%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                           | 409/500 [01:54<00:25,  3.55it/s]\u001b[A\u001b[A\n",
+      " 82%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                           | 409/500 [01:52<00:25,  3.54it/s]\u001b[A\u001b[A\n",
       "\n"
      ]
     },
@@ -1128,87 +1131,87 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      " 82%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                           | 410/500 [01:55<00:26,  3.45it/s]\u001b[A\u001b[A\n",
+      " 82%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                           | 410/500 [01:53<00:25,  3.57it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 82%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                          | 411/500 [01:55<00:26,  3.39it/s]\u001b[A\u001b[A\n",
+      " 82%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                          | 411/500 [01:53<00:26,  3.32it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 82%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                          | 412/500 [01:55<00:26,  3.38it/s]\u001b[A\u001b[A\n",
+      " 82%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                          | 412/500 [01:53<00:25,  3.42it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 83%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                          | 413/500 [01:55<00:26,  3.32it/s]\u001b[A\u001b[A\n",
+      " 83%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                          | 413/500 [01:54<00:24,  3.49it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 83%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                         | 414/500 [01:56<00:26,  3.25it/s]\u001b[A\u001b[A\n",
+      " 83%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                         | 414/500 [01:54<00:24,  3.54it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 83%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                         | 415/500 [01:56<00:25,  3.31it/s]\u001b[A\u001b[A\n",
+      " 83%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                         | 415/500 [01:54<00:23,  3.58it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 83%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                         | 416/500 [01:56<00:25,  3.25it/s]\u001b[A\u001b[A\n",
+      " 83%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                         | 416/500 [01:54<00:23,  3.60it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 83%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                         | 417/500 [01:57<00:24,  3.34it/s]\u001b[A\u001b[A\n",
+      " 83%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                         | 417/500 [01:55<00:22,  3.63it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 84%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                        | 418/500 [01:57<00:23,  3.43it/s]\u001b[A\u001b[A\n",
+      " 84%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                        | 418/500 [01:55<00:22,  3.64it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 84%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                        | 419/500 [01:57<00:23,  3.48it/s]\u001b[A\u001b[A\n",
+      " 84%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                        | 419/500 [01:55<00:22,  3.65it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 84%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                        | 420/500 [01:58<00:22,  3.51it/s]\u001b[A\u001b[A\n",
+      " 84%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                        | 420/500 [01:56<00:21,  3.65it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 84%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                       | 421/500 [01:58<00:22,  3.54it/s]\u001b[A\u001b[A\n",
+      " 84%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                       | 421/500 [01:56<00:21,  3.65it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 84%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                       | 422/500 [01:58<00:21,  3.57it/s]\u001b[A\u001b[A\n",
+      " 84%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                       | 422/500 [01:56<00:21,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 85%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                       | 423/500 [01:58<00:21,  3.58it/s]\u001b[A\u001b[A\n",
+      " 85%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                       | 423/500 [01:56<00:20,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 85%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                      | 424/500 [01:59<00:21,  3.58it/s]\u001b[A\u001b[A\n",
+      " 85%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                      | 424/500 [01:57<00:20,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 85%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                      | 425/500 [01:59<00:20,  3.60it/s]\u001b[A\u001b[A\n",
+      " 85%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                      | 425/500 [01:57<00:20,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 85%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                      | 426/500 [01:59<00:20,  3.60it/s]\u001b[A\u001b[A\n",
+      " 85%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                      | 426/500 [01:57<00:20,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 85%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                      | 427/500 [01:59<00:20,  3.59it/s]\u001b[A\u001b[A\n",
+      " 85%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                      | 427/500 [01:57<00:19,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 86%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                     | 428/500 [02:00<00:19,  3.60it/s]\u001b[A\u001b[A\n",
+      " 86%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                     | 428/500 [01:58<00:19,  3.65it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 86%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                     | 429/500 [02:00<00:19,  3.61it/s]\u001b[A\u001b[A\n",
+      " 86%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                     | 429/500 [01:58<00:19,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 86%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                     | 430/500 [02:00<00:19,  3.60it/s]\u001b[A\u001b[A\n",
+      " 86%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                     | 430/500 [01:58<00:19,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 86%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                    | 431/500 [02:01<00:19,  3.60it/s]\u001b[A\u001b[A\n",
+      " 86%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                    | 431/500 [01:59<00:18,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 86%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                    | 432/500 [02:01<00:18,  3.60it/s]\u001b[A\u001b[A\n",
+      " 86%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                    | 432/500 [01:59<00:18,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 87%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                    | 433/500 [02:01<00:18,  3.60it/s]\u001b[A\u001b[A\n",
+      " 87%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                    | 433/500 [01:59<00:18,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 87%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                   | 434/500 [02:01<00:18,  3.61it/s]\u001b[A\u001b[A\n",
+      " 87%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                   | 434/500 [01:59<00:17,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 87%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                   | 435/500 [02:02<00:17,  3.62it/s]\u001b[A\u001b[A\n",
+      " 87%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                   | 435/500 [02:00<00:17,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 87%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                   | 436/500 [02:02<00:17,  3.62it/s]\u001b[A\u001b[A\n",
+      " 87%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                   | 436/500 [02:00<00:17,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 87%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                   | 437/500 [02:02<00:17,  3.61it/s]\u001b[A\u001b[A\n",
+      " 87%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                   | 437/500 [02:00<00:17,  3.69it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 88%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                  | 438/500 [02:03<00:17,  3.61it/s]\u001b[A\u001b[A\n",
+      " 88%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍                  | 438/500 [02:00<00:16,  3.69it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 88%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                  | 439/500 [02:03<00:16,  3.61it/s]\u001b[A\u001b[A\n",
+      " 88%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                  | 439/500 [02:01<00:16,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 88%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                  | 440/500 [02:03<00:16,  3.62it/s]\u001b[A\u001b[A\n",
+      " 88%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                  | 440/500 [02:01<00:16,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 88%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                 | 441/500 [02:03<00:16,  3.62it/s]\u001b[A\u001b[A\n",
+      " 88%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                 | 441/500 [02:01<00:16,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 88%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                 | 442/500 [02:04<00:16,  3.62it/s]\u001b[A\u001b[A\n",
+      " 88%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                 | 442/500 [02:02<00:15,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 89%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                 | 443/500 [02:04<00:15,  3.58it/s]\u001b[A\u001b[A\n",
+      " 89%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉                 | 443/500 [02:02<00:15,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 89%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                | 444/500 [02:04<00:15,  3.58it/s]\u001b[A\u001b[A\n",
+      " 89%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏                | 444/500 [02:02<00:15,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 89%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                | 445/500 [02:04<00:15,  3.59it/s]\u001b[A\u001b[A\n",
+      " 89%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                | 445/500 [02:02<00:15,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 89%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                | 446/500 [02:05<00:15,  3.59it/s]\u001b[A\u001b[A\n",
+      " 89%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                | 446/500 [02:03<00:14,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 89%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                | 447/500 [02:05<00:14,  3.59it/s]\u001b[A\u001b[A\n",
+      " 89%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                | 447/500 [02:03<00:14,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 90%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍               | 448/500 [02:05<00:14,  3.58it/s]\u001b[A\u001b[A\n",
+      " 90%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍               | 448/500 [02:03<00:14,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 90%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋               | 449/500 [02:06<00:14,  3.51it/s]\u001b[A\u001b[A\n",
+      " 90%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋               | 449/500 [02:03<00:13,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 90%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████               | 450/500 [02:06<00:14,  3.46it/s]\u001b[A\u001b[A\n",
+      " 90%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████               | 450/500 [02:04<00:13,  3.67it/s]\u001b[A\u001b[A\n",
       "\n"
      ]
     },
@@ -1216,87 +1219,87 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      " 90%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎              | 451/500 [02:06<00:14,  3.41it/s]\u001b[A\u001b[A\n",
+      " 90%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎              | 451/500 [02:04<00:13,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 90%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌              | 452/500 [02:06<00:13,  3.44it/s]\u001b[A\u001b[A\n",
+      " 90%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌              | 452/500 [02:04<00:13,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 91%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉              | 453/500 [02:07<00:13,  3.46it/s]\u001b[A\u001b[A\n",
+      " 91%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉              | 453/500 [02:05<00:12,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 91%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏             | 454/500 [02:07<00:13,  3.39it/s]\u001b[A\u001b[A\n",
+      " 91%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏             | 454/500 [02:05<00:12,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 91%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌             | 455/500 [02:07<00:13,  3.37it/s]\u001b[A\u001b[A\n",
+      " 91%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌             | 455/500 [02:05<00:12,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 91%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊             | 456/500 [02:08<00:12,  3.44it/s]\u001b[A\u001b[A\n",
+      " 91%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊             | 456/500 [02:05<00:11,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 91%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████             | 457/500 [02:08<00:12,  3.49it/s]\u001b[A\u001b[A\n",
+      " 91%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████             | 457/500 [02:06<00:11,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 92%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍            | 458/500 [02:08<00:11,  3.52it/s]\u001b[A\u001b[A\n",
+      " 92%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍            | 458/500 [02:06<00:11,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 92%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋            | 459/500 [02:09<00:11,  3.55it/s]\u001b[A\u001b[A\n",
+      " 92%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋            | 459/500 [02:06<00:11,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 92%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████            | 460/500 [02:09<00:11,  3.57it/s]\u001b[A\u001b[A\n",
+      " 92%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████            | 460/500 [02:06<00:10,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 92%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎           | 461/500 [02:09<00:10,  3.58it/s]\u001b[A\u001b[A\n",
+      " 92%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎           | 461/500 [02:07<00:10,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 92%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌           | 462/500 [02:09<00:10,  3.61it/s]\u001b[A\u001b[A\n",
+      " 92%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌           | 462/500 [02:07<00:10,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 93%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉           | 463/500 [02:10<00:10,  3.62it/s]\u001b[A\u001b[A\n",
+      " 93%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉           | 463/500 [02:07<00:10,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 93%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏          | 464/500 [02:10<00:09,  3.62it/s]\u001b[A\u001b[A\n",
+      " 93%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏          | 464/500 [02:08<00:09,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 93%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌          | 465/500 [02:10<00:09,  3.62it/s]\u001b[A\u001b[A\n",
+      " 93%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌          | 465/500 [02:08<00:09,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 93%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊          | 466/500 [02:10<00:09,  3.62it/s]\u001b[A\u001b[A\n",
+      " 93%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊          | 466/500 [02:08<00:09,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 93%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████          | 467/500 [02:11<00:09,  3.61it/s]\u001b[A\u001b[A\n",
+      " 93%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████          | 467/500 [02:08<00:09,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 94%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍         | 468/500 [02:11<00:09,  3.55it/s]\u001b[A\u001b[A\n",
+      " 94%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍         | 468/500 [02:09<00:08,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 94%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋         | 469/500 [02:11<00:09,  3.36it/s]\u001b[A\u001b[A\n",
+      " 94%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋         | 469/500 [02:09<00:08,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 94%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████         | 470/500 [02:12<00:08,  3.37it/s]\u001b[A\u001b[A\n",
+      " 94%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████         | 470/500 [02:09<00:08,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 94%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎        | 471/500 [02:12<00:08,  3.41it/s]\u001b[A\u001b[A\n",
+      " 94%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎        | 471/500 [02:09<00:07,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 94%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌        | 472/500 [02:12<00:08,  3.37it/s]\u001b[A\u001b[A\n",
+      " 94%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌        | 472/500 [02:10<00:07,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 95%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉        | 473/500 [02:13<00:08,  3.23it/s]\u001b[A\u001b[A\n",
+      " 95%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉        | 473/500 [02:10<00:07,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 95%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏       | 474/500 [02:13<00:07,  3.31it/s]\u001b[A\u001b[A\n",
+      " 95%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏       | 474/500 [02:10<00:07,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 95%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌       | 475/500 [02:13<00:07,  3.38it/s]\u001b[A\u001b[A\n",
+      " 95%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌       | 475/500 [02:11<00:06,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 95%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊       | 476/500 [02:13<00:06,  3.44it/s]\u001b[A\u001b[A\n",
+      " 95%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊       | 476/500 [02:11<00:06,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 95%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████       | 477/500 [02:14<00:06,  3.48it/s]\u001b[A\u001b[A\n",
+      " 95%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████       | 477/500 [02:11<00:06,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 96%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍      | 478/500 [02:14<00:06,  3.52it/s]\u001b[A\u001b[A\n",
+      " 96%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍      | 478/500 [02:11<00:05,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 96%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋      | 479/500 [02:14<00:05,  3.54it/s]\u001b[A\u001b[A\n",
+      " 96%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋      | 479/500 [02:12<00:05,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 96%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████      | 480/500 [02:15<00:05,  3.51it/s]\u001b[A\u001b[A\n",
+      " 96%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████      | 480/500 [02:12<00:05,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 96%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎     | 481/500 [02:15<00:05,  3.54it/s]\u001b[A\u001b[A\n",
+      " 96%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎     | 481/500 [02:12<00:05,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 96%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌     | 482/500 [02:15<00:05,  3.57it/s]\u001b[A\u001b[A\n",
+      " 96%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌     | 482/500 [02:12<00:04,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 97%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉     | 483/500 [02:15<00:04,  3.59it/s]\u001b[A\u001b[A\n",
+      " 97%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉     | 483/500 [02:13<00:04,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 97%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏    | 484/500 [02:16<00:04,  3.59it/s]\u001b[A\u001b[A\n",
+      " 97%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏    | 484/500 [02:13<00:04,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 97%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌    | 485/500 [02:16<00:04,  3.56it/s]\u001b[A\u001b[A\n",
+      " 97%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌    | 485/500 [02:13<00:04,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 97%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊    | 486/500 [02:16<00:03,  3.57it/s]\u001b[A\u001b[A\n",
+      " 97%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊    | 486/500 [02:14<00:03,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 97%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████    | 487/500 [02:16<00:03,  3.58it/s]\u001b[A\u001b[A\n",
+      " 97%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████    | 487/500 [02:14<00:03,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 98%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍   | 488/500 [02:17<00:03,  3.53it/s]\u001b[A\u001b[A\n",
+      " 98%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍   | 488/500 [02:14<00:03,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 98%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋   | 489/500 [02:17<00:03,  3.55it/s]\u001b[A\u001b[A\n",
+      " 98%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋   | 489/500 [02:14<00:02,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 98%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████   | 490/500 [02:17<00:02,  3.54it/s]\u001b[A\u001b[A\n",
+      " 98%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████   | 490/500 [02:15<00:02,  3.68it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 98%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎  | 491/500 [02:18<00:02,  3.49it/s]\u001b[A\u001b[A\n",
+      " 98%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎  | 491/500 [02:15<00:02,  3.67it/s]\u001b[A\u001b[A\n",
       "\n"
      ]
     },
@@ -1304,25 +1307,25 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      " 98%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌  | 492/500 [02:18<00:02,  3.47it/s]\u001b[A\u001b[A\n",
+      " 98%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌  | 492/500 [02:15<00:02,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 99%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉  | 493/500 [02:18<00:02,  3.46it/s]\u001b[A\u001b[A\n",
+      " 99%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉  | 493/500 [02:15<00:01,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 99%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏ | 494/500 [02:18<00:01,  3.50it/s]\u001b[A\u001b[A\n",
+      " 99%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏ | 494/500 [02:16<00:01,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 99%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌ | 495/500 [02:19<00:01,  3.52it/s]\u001b[A\u001b[A\n",
+      " 99%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌ | 495/500 [02:16<00:01,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 99%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊ | 496/500 [02:19<00:01,  3.47it/s]\u001b[A\u001b[A\n",
+      " 99%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊ | 496/500 [02:16<00:01,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      " 99%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████ | 497/500 [02:19<00:00,  3.42it/s]\u001b[A\u001b[A\n",
+      " 99%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████ | 497/500 [02:17<00:00,  3.66it/s]\u001b[A\u001b[A\n",
       "\n",
-      "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍| 498/500 [02:20<00:00,  3.41it/s]\u001b[A\u001b[A\n",
+      "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍| 498/500 [02:17<00:00,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋| 499/500 [02:20<00:00,  3.28it/s]\u001b[A\u001b[A\n",
+      "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋| 499/500 [02:17<00:00,  3.67it/s]\u001b[A\u001b[A\n",
       "\n",
-      "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [02:20<00:00,  3.55it/s]\u001b[A\u001b[A\n",
-      "  9%|█████████████▎                                                                                                                                         | 44/500 [02:36<27:04,  3.56s/it]\n",
-      "  6%|█████████▎                                                                                                                                             | 31/500 [02:49<42:41,  5.46s/it]\n"
+      "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [02:17<00:00,  3.63it/s]\u001b[A\u001b[A\n",
+      "  9%|█████████████▎                                                                                                                                         | 44/500 [02:33<26:34,  3.50s/it]\n",
+      "  7%|███████████▏                                                                                                                                           | 37/500 [02:48<35:02,  4.54s/it]\n"
      ]
     },
     {
@@ -1337,7 +1340,7 @@
     }
    ],
    "source": [
-    "# Imputes zeros\n",
+    "# Imputes zeros with mean\n",
     "X_glm_data = X_data.copy()\n",
     "for idx in tqdm.tqdm(range(X_data.shape[1])):\n",
     "    non_zero_mean = X_glm_data[X_glm_data[:,idx] != 0,idx].mean()\n",
@@ -1367,7 +1370,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1395,7 +1398,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      " 21%|███████████████████████████████▋                                                                                                                       | 21/100 [00:03<00:12,  6.54it/s]"
+      " 21%|███████████████████████████████▋                                                                                                                       | 21/100 [00:02<00:11,  7.04it/s]"
      ]
     },
     {
@@ -1428,7 +1431,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 15,
    "id": "63539801-37f1-4736-b789-4ae574deacd0",
    "metadata": {
     "tags": []
@@ -1439,16 +1442,16 @@
      "output_type": "stream",
      "text": [
       "UMAP(angular_rp_forest=True, metric='cosine', min_dist=0.3, n_epochs=1000, verbose=True)\n",
-      "Thu Jul 25 18:58:05 2024 Construct fuzzy simplicial set\n",
-      "Thu Jul 25 18:58:05 2024 Finding Nearest Neighbors\n",
-      "Thu Jul 25 18:58:05 2024 Finished Nearest Neighbor Search\n",
-      "Thu Jul 25 18:58:05 2024 Construct embedding\n"
+      "Thu Jul 25 19:39:46 2024 Construct fuzzy simplicial set\n",
+      "Thu Jul 25 19:39:47 2024 Finding Nearest Neighbors\n",
+      "Thu Jul 25 19:39:47 2024 Finished Nearest Neighbor Search\n",
+      "Thu Jul 25 19:39:47 2024 Construct embedding\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "d06218bf7861468c80bf6d9248c0dba1",
+       "model_id": "02ac7e801b954cb998677974f9d62b4f",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1473,25 +1476,18 @@
       "\tcompleted  700  /  1000 epochs\n",
       "\tcompleted  800  /  1000 epochs\n",
       "\tcompleted  900  /  1000 epochs\n",
-      "Thu Jul 25 18:58:07 2024 Finished embedding\n"
+      "Thu Jul 25 19:39:48 2024 Finished embedding\n"
      ]
     },
     {
-     "ename": "ValueError",
-     "evalue": "Could not interpret value `label` for `hue`. An entry with this name does not appear in `data`.",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[10], line 12\u001b[0m\n\u001b[1;32m      6\u001b[0m umap_embeddings \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame(\n\u001b[1;32m      7\u001b[0m     _umap_clf\u001b[38;5;241m.\u001b[39mfit_transform(X_project\u001b[38;5;241m.\u001b[39mdetach()\u001b[38;5;241m.\u001b[39mnumpy()), \n\u001b[1;32m      8\u001b[0m     columns\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUMAP 1\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUMAP 2\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[1;32m      9\u001b[0m )\u001b[38;5;241m.\u001b[39mreset_index()\n\u001b[1;32m     10\u001b[0m \u001b[38;5;66;03m#umap_embeddings['label'] = cell_labels['snmCAT-seq Baseline Cluster'].values\u001b[39;00m\n\u001b[0;32m---> 12\u001b[0m g \u001b[38;5;241m=\u001b[39m \u001b[43msns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrelplot\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mumap_embeddings\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mUMAP 1\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mUMAP 2\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43mhue\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mlabel\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m     13\u001b[0m figure_name \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUMAP_glm_pca_\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m_metric_\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m_\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m%\u001b[39m(\n\u001b[1;32m     14\u001b[0m     n_pc, \n\u001b[1;32m     15\u001b[0m     metric,\n\u001b[1;32m     16\u001b[0m     family\n\u001b[1;32m     17\u001b[0m )\n",
-      "File \u001b[0;32m~/programs/miniconda3/envs/sincei/lib/python3.8/site-packages/seaborn/relational.py:748\u001b[0m, in \u001b[0;36mrelplot\u001b[0;34m(data, x, y, hue, size, style, units, weights, row, col, col_wrap, row_order, col_order, palette, hue_order, hue_norm, sizes, size_order, size_norm, markers, dashes, style_order, legend, kind, height, aspect, facet_kws, **kwargs)\u001b[0m\n\u001b[1;32m    746\u001b[0m         msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe `weights` parameter has no effect with kind=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mscatter\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    747\u001b[0m         warnings\u001b[38;5;241m.\u001b[39mwarn(msg, stacklevel\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m)\n\u001b[0;32m--> 748\u001b[0m p \u001b[38;5;241m=\u001b[39m \u001b[43mPlotter\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    749\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    750\u001b[0m \u001b[43m    \u001b[49m\u001b[43mvariables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvariables\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    751\u001b[0m \u001b[43m    \u001b[49m\u001b[43mlegend\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlegend\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    752\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    753\u001b[0m p\u001b[38;5;241m.\u001b[39mmap_hue(palette\u001b[38;5;241m=\u001b[39mpalette, order\u001b[38;5;241m=\u001b[39mhue_order, norm\u001b[38;5;241m=\u001b[39mhue_norm)\n\u001b[1;32m    754\u001b[0m p\u001b[38;5;241m.\u001b[39mmap_size(sizes\u001b[38;5;241m=\u001b[39msizes, order\u001b[38;5;241m=\u001b[39msize_order, norm\u001b[38;5;241m=\u001b[39msize_norm)\n",
-      "File \u001b[0;32m~/programs/miniconda3/envs/sincei/lib/python3.8/site-packages/seaborn/relational.py:396\u001b[0m, in \u001b[0;36m_ScatterPlotter.__init__\u001b[0;34m(self, data, variables, legend)\u001b[0m\n\u001b[1;32m    387\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39m, data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, variables\u001b[38;5;241m=\u001b[39m{}, legend\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m    388\u001b[0m \n\u001b[1;32m    389\u001b[0m     \u001b[38;5;66;03m# TODO this is messy, we want the mapping to be agnostic about\u001b[39;00m\n\u001b[1;32m    390\u001b[0m     \u001b[38;5;66;03m# the kind of plot to draw, but for the time being we need to set\u001b[39;00m\n\u001b[1;32m    391\u001b[0m     \u001b[38;5;66;03m# this information so the SizeMapping can use it\u001b[39;00m\n\u001b[1;32m    392\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_default_size_range \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m    393\u001b[0m         np\u001b[38;5;241m.\u001b[39mr_[\u001b[38;5;241m.5\u001b[39m, \u001b[38;5;241m2\u001b[39m] \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39msquare(mpl\u001b[38;5;241m.\u001b[39mrcParams[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlines.markersize\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m    394\u001b[0m     )\n\u001b[0;32m--> 396\u001b[0m     \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__init__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvariables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvariables\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    398\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlegend \u001b[38;5;241m=\u001b[39m legend\n",
-      "File \u001b[0;32m~/programs/miniconda3/envs/sincei/lib/python3.8/site-packages/seaborn/_base.py:634\u001b[0m, in \u001b[0;36mVectorPlotter.__init__\u001b[0;34m(self, data, variables)\u001b[0m\n\u001b[1;32m    629\u001b[0m \u001b[38;5;66;03m# var_ordered is relevant only for categorical axis variables, and may\u001b[39;00m\n\u001b[1;32m    630\u001b[0m \u001b[38;5;66;03m# be better handled by an internal axis information object that tracks\u001b[39;00m\n\u001b[1;32m    631\u001b[0m \u001b[38;5;66;03m# such information and is set up by the scale_* methods. The analogous\u001b[39;00m\n\u001b[1;32m    632\u001b[0m \u001b[38;5;66;03m# information for numeric axes would be information about log scales.\u001b[39;00m\n\u001b[1;32m    633\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_var_ordered \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mx\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28;01mFalse\u001b[39;00m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124my\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28;01mFalse\u001b[39;00m}  \u001b[38;5;66;03m# alt., used DefaultDict\u001b[39;00m\n\u001b[0;32m--> 634\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43massign_variables\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvariables\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    636\u001b[0m \u001b[38;5;66;03m# TODO Lots of tests assume that these are called to initialize the\u001b[39;00m\n\u001b[1;32m    637\u001b[0m \u001b[38;5;66;03m# mappings to default values on class initialization. I'd prefer to\u001b[39;00m\n\u001b[1;32m    638\u001b[0m \u001b[38;5;66;03m# move away from that and only have a mapping when explicitly called.\u001b[39;00m\n\u001b[1;32m    639\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m var \u001b[38;5;129;01min\u001b[39;00m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhue\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msize\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstyle\u001b[39m\u001b[38;5;124m\"\u001b[39m]:\n",
-      "File \u001b[0;32m~/programs/miniconda3/envs/sincei/lib/python3.8/site-packages/seaborn/_base.py:679\u001b[0m, in \u001b[0;36mVectorPlotter.assign_variables\u001b[0;34m(self, data, variables)\u001b[0m\n\u001b[1;32m    674\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    675\u001b[0m     \u001b[38;5;66;03m# When dealing with long-form input, use the newer PlotData\u001b[39;00m\n\u001b[1;32m    676\u001b[0m     \u001b[38;5;66;03m# object (internal but introduced for the objects interface)\u001b[39;00m\n\u001b[1;32m    677\u001b[0m     \u001b[38;5;66;03m# to centralize / standardize data consumption logic.\u001b[39;00m\n\u001b[1;32m    678\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minput_format \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlong\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 679\u001b[0m     plot_data \u001b[38;5;241m=\u001b[39m \u001b[43mPlotData\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvariables\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    680\u001b[0m     frame \u001b[38;5;241m=\u001b[39m plot_data\u001b[38;5;241m.\u001b[39mframe\n\u001b[1;32m    681\u001b[0m     names \u001b[38;5;241m=\u001b[39m plot_data\u001b[38;5;241m.\u001b[39mnames\n",
-      "File \u001b[0;32m~/programs/miniconda3/envs/sincei/lib/python3.8/site-packages/seaborn/_core/data.py:58\u001b[0m, in \u001b[0;36mPlotData.__init__\u001b[0;34m(self, data, variables)\u001b[0m\n\u001b[1;32m     51\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m     52\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m     53\u001b[0m     data: DataSource,\n\u001b[1;32m     54\u001b[0m     variables: \u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, VariableSpec],\n\u001b[1;32m     55\u001b[0m ):\n\u001b[1;32m     57\u001b[0m     data \u001b[38;5;241m=\u001b[39m handle_data_source(data)\n\u001b[0;32m---> 58\u001b[0m     frame, names, ids \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_assign_variables\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvariables\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     60\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mframe \u001b[38;5;241m=\u001b[39m frame\n\u001b[1;32m     61\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mnames \u001b[38;5;241m=\u001b[39m names\n",
-      "File \u001b[0;32m~/programs/miniconda3/envs/sincei/lib/python3.8/site-packages/seaborn/_core/data.py:232\u001b[0m, in \u001b[0;36mPlotData._assign_variables\u001b[0;34m(self, data, variables)\u001b[0m\n\u001b[1;32m    230\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    231\u001b[0m         err \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAn entry with this name does not appear in `data`.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 232\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(err)\n\u001b[1;32m    234\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    235\u001b[0m \n\u001b[1;32m    236\u001b[0m     \u001b[38;5;66;03m# Otherwise, assume the value somehow represents data\u001b[39;00m\n\u001b[1;32m    237\u001b[0m \n\u001b[1;32m    238\u001b[0m     \u001b[38;5;66;03m# Ignore empty data structures\u001b[39;00m\n\u001b[1;32m    239\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(val, Sized) \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(val) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n",
-      "\u001b[0;31mValueError\u001b[0m: Could not interpret value `label` for `hue`. An entry with this name does not appear in `data`."
-     ]
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 689.875x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -1504,10 +1500,10 @@
     "    _umap_clf.fit_transform(X_project.detach().numpy()), \n",
     "    columns=['UMAP 1', 'UMAP 2']\n",
     ").reset_index()\n",
-    "#umap_embeddings['label'] = cell_labels['snmCAT-seq Baseline Cluster'].values\n",
+    "umap_embeddings['label'] = cell_labels['snmC2T-seq Baseline Cluster'].values\n",
     "\n",
     "g = sns.relplot(data=umap_embeddings, x='UMAP 1', y='UMAP 2',hue='label')\n",
-    "figure_name = 'UMAP_glm_pca_%s_metric_%s_%s%s'%(\n",
+    "figure_name = 'UMAP_glm_pca_%s_metric_%s_%s'%(\n",
     "    n_pc, \n",
     "    metric,\n",
     "    family\n",
@@ -1524,7 +1520,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 13,
    "id": "8ee85f64-f3bd-478f-81ed-2d5bb135cb3f",
    "metadata": {},
    "outputs": [],
@@ -1535,7 +1531,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 16,
    "id": "3b2f5efb-a47f-4343-bf66-1487239ad66a",
    "metadata": {
     "tags": []
@@ -1546,16 +1542,16 @@
      "output_type": "stream",
      "text": [
       "UMAP(angular_rp_forest=True, metric='cosine', min_dist=0.3, n_epochs=1000, verbose=True)\n",
-      "Thu Jul 25 18:58:17 2024 Construct fuzzy simplicial set\n",
-      "Thu Jul 25 18:58:18 2024 Finding Nearest Neighbors\n",
-      "Thu Jul 25 18:58:18 2024 Finished Nearest Neighbor Search\n",
-      "Thu Jul 25 18:58:18 2024 Construct embedding\n"
+      "Thu Jul 25 19:39:54 2024 Construct fuzzy simplicial set\n",
+      "Thu Jul 25 19:39:55 2024 Finding Nearest Neighbors\n",
+      "Thu Jul 25 19:39:55 2024 Finished Nearest Neighbor Search\n",
+      "Thu Jul 25 19:39:55 2024 Construct embedding\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "84f94e6222e64e1a8fd784f817b11988",
+       "model_id": "7e733fc20cd944d28e339c490f601e53",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1580,25 +1576,18 @@
       "\tcompleted  700  /  1000 epochs\n",
       "\tcompleted  800  /  1000 epochs\n",
       "\tcompleted  900  /  1000 epochs\n",
-      "Thu Jul 25 18:58:19 2024 Finished embedding\n"
+      "Thu Jul 25 19:39:56 2024 Finished embedding\n"
      ]
     },
     {
-     "ename": "ValueError",
-     "evalue": "Could not interpret value `label` for `hue`. An entry with this name does not appear in `data`.",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[12], line 11\u001b[0m\n\u001b[1;32m      5\u001b[0m umap_embeddings \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame(\n\u001b[1;32m      6\u001b[0m     _umap_clf\u001b[38;5;241m.\u001b[39mfit_transform(X_pca), \n\u001b[1;32m      7\u001b[0m     columns\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUMAP 1\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUMAP 2\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[1;32m      8\u001b[0m )\u001b[38;5;241m.\u001b[39mreset_index()\n\u001b[1;32m      9\u001b[0m \u001b[38;5;66;03m#umap_embeddings['label'] = cell_labels['snmC2T-seq Baseline Cluster'].values\u001b[39;00m\n\u001b[0;32m---> 11\u001b[0m g \u001b[38;5;241m=\u001b[39m \u001b[43msns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrelplot\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mumap_embeddings\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mUMAP 1\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mUMAP 2\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43mhue\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mlabel\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[0;32m~/programs/miniconda3/envs/sincei/lib/python3.8/site-packages/seaborn/relational.py:748\u001b[0m, in \u001b[0;36mrelplot\u001b[0;34m(data, x, y, hue, size, style, units, weights, row, col, col_wrap, row_order, col_order, palette, hue_order, hue_norm, sizes, size_order, size_norm, markers, dashes, style_order, legend, kind, height, aspect, facet_kws, **kwargs)\u001b[0m\n\u001b[1;32m    746\u001b[0m         msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe `weights` parameter has no effect with kind=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mscatter\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    747\u001b[0m         warnings\u001b[38;5;241m.\u001b[39mwarn(msg, stacklevel\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m)\n\u001b[0;32m--> 748\u001b[0m p \u001b[38;5;241m=\u001b[39m \u001b[43mPlotter\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    749\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    750\u001b[0m \u001b[43m    \u001b[49m\u001b[43mvariables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvariables\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    751\u001b[0m \u001b[43m    \u001b[49m\u001b[43mlegend\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlegend\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    752\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    753\u001b[0m p\u001b[38;5;241m.\u001b[39mmap_hue(palette\u001b[38;5;241m=\u001b[39mpalette, order\u001b[38;5;241m=\u001b[39mhue_order, norm\u001b[38;5;241m=\u001b[39mhue_norm)\n\u001b[1;32m    754\u001b[0m p\u001b[38;5;241m.\u001b[39mmap_size(sizes\u001b[38;5;241m=\u001b[39msizes, order\u001b[38;5;241m=\u001b[39msize_order, norm\u001b[38;5;241m=\u001b[39msize_norm)\n",
-      "File \u001b[0;32m~/programs/miniconda3/envs/sincei/lib/python3.8/site-packages/seaborn/relational.py:396\u001b[0m, in \u001b[0;36m_ScatterPlotter.__init__\u001b[0;34m(self, data, variables, legend)\u001b[0m\n\u001b[1;32m    387\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39m, data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, variables\u001b[38;5;241m=\u001b[39m{}, legend\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m    388\u001b[0m \n\u001b[1;32m    389\u001b[0m     \u001b[38;5;66;03m# TODO this is messy, we want the mapping to be agnostic about\u001b[39;00m\n\u001b[1;32m    390\u001b[0m     \u001b[38;5;66;03m# the kind of plot to draw, but for the time being we need to set\u001b[39;00m\n\u001b[1;32m    391\u001b[0m     \u001b[38;5;66;03m# this information so the SizeMapping can use it\u001b[39;00m\n\u001b[1;32m    392\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_default_size_range \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m    393\u001b[0m         np\u001b[38;5;241m.\u001b[39mr_[\u001b[38;5;241m.5\u001b[39m, \u001b[38;5;241m2\u001b[39m] \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39msquare(mpl\u001b[38;5;241m.\u001b[39mrcParams[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlines.markersize\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m    394\u001b[0m     )\n\u001b[0;32m--> 396\u001b[0m     \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__init__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvariables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvariables\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    398\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlegend \u001b[38;5;241m=\u001b[39m legend\n",
-      "File \u001b[0;32m~/programs/miniconda3/envs/sincei/lib/python3.8/site-packages/seaborn/_base.py:634\u001b[0m, in \u001b[0;36mVectorPlotter.__init__\u001b[0;34m(self, data, variables)\u001b[0m\n\u001b[1;32m    629\u001b[0m \u001b[38;5;66;03m# var_ordered is relevant only for categorical axis variables, and may\u001b[39;00m\n\u001b[1;32m    630\u001b[0m \u001b[38;5;66;03m# be better handled by an internal axis information object that tracks\u001b[39;00m\n\u001b[1;32m    631\u001b[0m \u001b[38;5;66;03m# such information and is set up by the scale_* methods. The analogous\u001b[39;00m\n\u001b[1;32m    632\u001b[0m \u001b[38;5;66;03m# information for numeric axes would be information about log scales.\u001b[39;00m\n\u001b[1;32m    633\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_var_ordered \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mx\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28;01mFalse\u001b[39;00m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124my\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28;01mFalse\u001b[39;00m}  \u001b[38;5;66;03m# alt., used DefaultDict\u001b[39;00m\n\u001b[0;32m--> 634\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43massign_variables\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvariables\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    636\u001b[0m \u001b[38;5;66;03m# TODO Lots of tests assume that these are called to initialize the\u001b[39;00m\n\u001b[1;32m    637\u001b[0m \u001b[38;5;66;03m# mappings to default values on class initialization. I'd prefer to\u001b[39;00m\n\u001b[1;32m    638\u001b[0m \u001b[38;5;66;03m# move away from that and only have a mapping when explicitly called.\u001b[39;00m\n\u001b[1;32m    639\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m var \u001b[38;5;129;01min\u001b[39;00m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhue\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msize\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstyle\u001b[39m\u001b[38;5;124m\"\u001b[39m]:\n",
-      "File \u001b[0;32m~/programs/miniconda3/envs/sincei/lib/python3.8/site-packages/seaborn/_base.py:679\u001b[0m, in \u001b[0;36mVectorPlotter.assign_variables\u001b[0;34m(self, data, variables)\u001b[0m\n\u001b[1;32m    674\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    675\u001b[0m     \u001b[38;5;66;03m# When dealing with long-form input, use the newer PlotData\u001b[39;00m\n\u001b[1;32m    676\u001b[0m     \u001b[38;5;66;03m# object (internal but introduced for the objects interface)\u001b[39;00m\n\u001b[1;32m    677\u001b[0m     \u001b[38;5;66;03m# to centralize / standardize data consumption logic.\u001b[39;00m\n\u001b[1;32m    678\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minput_format \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlong\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 679\u001b[0m     plot_data \u001b[38;5;241m=\u001b[39m \u001b[43mPlotData\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvariables\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    680\u001b[0m     frame \u001b[38;5;241m=\u001b[39m plot_data\u001b[38;5;241m.\u001b[39mframe\n\u001b[1;32m    681\u001b[0m     names \u001b[38;5;241m=\u001b[39m plot_data\u001b[38;5;241m.\u001b[39mnames\n",
-      "File \u001b[0;32m~/programs/miniconda3/envs/sincei/lib/python3.8/site-packages/seaborn/_core/data.py:58\u001b[0m, in \u001b[0;36mPlotData.__init__\u001b[0;34m(self, data, variables)\u001b[0m\n\u001b[1;32m     51\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m     52\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m     53\u001b[0m     data: DataSource,\n\u001b[1;32m     54\u001b[0m     variables: \u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, VariableSpec],\n\u001b[1;32m     55\u001b[0m ):\n\u001b[1;32m     57\u001b[0m     data \u001b[38;5;241m=\u001b[39m handle_data_source(data)\n\u001b[0;32m---> 58\u001b[0m     frame, names, ids \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_assign_variables\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvariables\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     60\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mframe \u001b[38;5;241m=\u001b[39m frame\n\u001b[1;32m     61\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mnames \u001b[38;5;241m=\u001b[39m names\n",
-      "File \u001b[0;32m~/programs/miniconda3/envs/sincei/lib/python3.8/site-packages/seaborn/_core/data.py:232\u001b[0m, in \u001b[0;36mPlotData._assign_variables\u001b[0;34m(self, data, variables)\u001b[0m\n\u001b[1;32m    230\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    231\u001b[0m         err \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAn entry with this name does not appear in `data`.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 232\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(err)\n\u001b[1;32m    234\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    235\u001b[0m \n\u001b[1;32m    236\u001b[0m     \u001b[38;5;66;03m# Otherwise, assume the value somehow represents data\u001b[39;00m\n\u001b[1;32m    237\u001b[0m \n\u001b[1;32m    238\u001b[0m     \u001b[38;5;66;03m# Ignore empty data structures\u001b[39;00m\n\u001b[1;32m    239\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(val, Sized) \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(val) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n",
-      "\u001b[0;31mValueError\u001b[0m: Could not interpret value `label` for `hue`. An entry with this name does not appear in `data`."
-     ]
+     "data": {
+      "image/png": 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G0TaylOySPSTbopi1813Si3byTO+vSQppVKvPJwiCIJyZwsJCCgur/8JvMpmIj4+/wBEJlxrR5S1UIWm0yNZQOhfu5t4GjZl2oBR3QCXUoOGFTvG8tiGH7fknxkGGGTW82CmejJKTL/uj/PHdJaDCJzsK6dAnkliLlXm7J5FetJNoSwoWfUhtPpogCIJwFsLCwggLC7vYYQiXMJFQCtWSm7XH/M4TXF+/JVd1HIBDNhESFcUHO/IrJZMAhe4AL63J5M0eSUhAdU3eiVY9Ba7Ku+HklvqYt/1ZynwlhJliubvDG2glseCsIAiCIPzdiDGUQrWkkAj0976INj+T8E9foO6CTyn0BvjtaEm15QvcAUp9AW5uEFrlnEaCO5tH8kNaUaXjUWYLNzb7P+7v/B4PdPkvGklLZklarTyPIAiCIAi1R7RQCtWSZBkpLhn9Xc+iltgpkvR4VYmTLCPJ3iI30WYdr3VL4Os95UsKNQo1MrBuCDP3F3HYcWKHnBizDpQckkIaEqSzsT1nBfUjWpFWsIXGUR0vwBMKgiAIgnC+iIRSAEANBMBRhOooRFUUJFsYkjUEyWJDstggvxA9EmadTKmvmr1ngTiLnoXpxbSPNjOiURjJVhUFhVfW5bGj4MT4ykiTlmfaadmR/T9cvhL6pI7g222vcl3je0kOaVLttQVBEARBuHSJWd5/cSXO8la9bpR92/F99yF4/hgfqdOjve4ONC06IZnMuArzKcs/xi8uGx/utle5RpMwI2NbRQHw+a4CusQaqGvZyYr0H2gaMxiToQFZpSqRJhlZzeLXva/TI+UG1hz5idaxvTlQuJVc52Ee7TaZKEvihXx8QRAEQRDOkWihFFAL8/B98Tb8+buFz4v/h0+QYxJRQyLR52ag93oYFqSgaxzMlLQySn0KGgl6Jli5q3kkL6/NYkTjCNbllHJ9PT+zd77LkCZj+WT9k+hkA1ZDGGU+B25/KVZ9KNHWZLIcaRi1QVzf9CEmrx2HVhb/JQVBEATh70ZMyrnCqX4//hXzKyeTf5BCI0GS8P/8Fb7P38b3zX/RrfiJG61Ovmqp4fO2Br68KpYEi44jTi87CtwEVBUVkAmQV3qE7bkrGNPu31gMoRS6snH7S6kX3opR7Sbww/Z3AAg2hLMjdwV3dngVvcZ0gX8CgiAIF49SmIdv/rd4v3oP3/xvUQrzavV+I0eORJIk7rnnnirnxo4diyRJjBw5suJYTk4ODz30EKmpqRiNRqKjo+natSuTJk2irOzERhYpKSlIklTl9dprr50ypvT09Ep1wsPDueaaa9i8eTMAzZs3rzZegC+++AKDwUB+fn7FsX79+qHRaFi/fn21zz906NAaY/nzc2g0GuLi4hgzZgxFRUU11hHKiYTyCqe6XaDVIdVtDNrKS/Zoh4zE+/nbKJtXQMAPioKyexO+6W8QrpSR8OlzxM75EL3iw/7HNo0BpXy9ykKPhvCgWNZk/Mi6o79wV4fXuavD69zT8U0aRbRn2obnyCs9AkDPOjfye/pMfk+fTUDxV4lREAThchTY8BveNx4msGQ2ytZVBJbMxvvGIwQ2/Far901MTOTbb7/F5TqxBJzb7ebrr78mKSmp4tjBgwdp3bo1CxYs4N///jebN29m9erVjBs3jh9//JFFixZVuu748ePJzs6u9HrggQdOO65FixaRnZ3Nr7/+itPpZMCAARQXFzNmzJgq8R43bdo0rrvuOiIiIgDIyMhg1apV3H///UydOvVMfzSVniMjI4OvvvqK5cuX8+CDD57Vta4kon/xCqYU5KI6HchxSRAVh9TnRlRJAo8b1VGAcvQQOKr5VuZ2oWxfi9y0HZSWcG2cEakkn2/6xqNoJO5qHsEPB+z8M/UB/rftabbn/E6jyPYcse9jTcaPlS51Vb1bMeoslHrtbMxcQK+6N2M1hiJLmlp5ZlVVUVWQZalWri8IgnA6lMI8fN9/DMpfJjkqAXzfT0aq2xg5LKpW7t2mTRsOHDjAzJkzGT58OAAzZ84kKSmJOnXqVJS777770Gq1bNiwAbPZXHG8bt26DBkyhL9OwbBarcTExJx1XOHh4cTExBATE8Obb75J165dWbt2LSNGjOCJJ57ghx9+YMSIERXlDx06xLJly/j5558rjk2bNo1BgwZx77330qlTJ95++21MpjPr+frzc8THx3PHHXfwzTffnPVzXSlEC+UVSjmWg5p7FMqcSFFJyPVbIlltkJ8DhbnIKY1QDuyouX7aDjQtO0PrbtiWziBkxrsUFyzjg1XDaB+tMrxRMJnuxtzQ/EWCDRF8v/0dQoxRPNL1Y4Y1fZBBje7m/s7vEh+cym8H/wdAQPVT4inA4S4478/rKAmQlR1g914/uXkKjhIFZ2n1s9UFQRBqW2DdkqrJ5HFKoPx8LRo9ejTTpk2reD916lRGjRpV8b6goIAFCxYwduzYSsnkn0lS7X0xP54Eer1eIiIiGDJkSJUWx+nTp5OQkMA111wDlDcYTJs2jREjRtCoUSNSU1P5/vvvzymOzMxM5s2bR8eOYjm7UxEJ5RVIdTrA60aVZNQSO8r+rQQ2Lcf79uP4f5iMf+5nKCt+RjJZar6IyQzWEDThUUg711F60wi+PzyVlNBmHCz4nTVp9xFj3E2stTH3d5nEk72+oE5oU7ZkL2Fb9m9syVrCj3smE2wIZ0PmAgDirPUoKMtBrXavnbNXXKwwe66HH392I0kShYUKGzf7OHAgQEFhAK9XJJaCIFxYasHJx0qqtTyWcsSIEaxYsYLDhw9z+PBhVq5cWan1Ly0tDVVVadiwYaV6ERERWCwWLBYLTzzxRKVzTzzxRMW546/ff//9jGMrLi5mwoQJWCwWOnToAMCYMWNYtmwZhw4dAsqTx88++4w77rgDWS5PZRYtWkRZWRn9+vWreMZPP/30jO9//DlMJhMJCQlIksTbb799xte50ogu7yuQ4vOiFhegHtpDYO0idDffg++LdyqVCezciG7wP1F2baj2Gpou/VA1Wjy2SBz3PsLU3a+S58zghmYP88m6J/ErXo5uexoJmTphzagT1pwWMT2oG9YSqyGMaEsyTm8xn254Br/iQ0JiQMMx7C/YhFF7kkT2DLlcKvMXeihxqgzsb2DZci/FdhWtFmQJ/AEYfK2BxATQasX3K0EQLgwp/OTd2VItdXcfFxkZycCBA5k+fTqqqjJw4MCKcYgns27dOhRFYfjw4Xg8nkrnHn/88UoTeqC8y/h0denSBVmWKS0tpW7dunz33XdER0cD0LdvXxISEpg2bRrjx49n8eLFZGRkVGpVnTp1KrfccgtabXlqc+utt/L4449z4MAB6tWrd9pxHH8OVVU5cuQITz/9NAMHDmT58uVoNLUzHOtyIBLKK5Dk8yLZwvCu+Am5ZWcC29ZULVTqQC0uQNO+N4H1Syudkhu1BiUARw+iC7JgSEjmiGM/Jp2FMq8Dv1K+I077hH50TBzI/oJNlHlLKCzLJjmkKfXDW/Nb+g/8dvA73P5SUkKbck39O9iStZT+DUdh0lXfvXI2ylwqObkKLZtr2bbDj9ks0bunHr1eQpJAI8PRzAAmk4TVomA2i6RSEITap+lwFYFl88o/S/9K1qDpcFWtxzB69Gjuv/9+AD744INK51JTU5Ekib1791Y6XrduXYBqxyVGRESQmpp61vF89913NGnShPDwcEJCQiqdk2WZkSNH8tlnn/Hiiy8ybdo0evfuXRFPYWEhs2bNwufzMWnSpIp6gUCAqVOn8sorr5x2HH9+jvr16zNx4kQ6d+7M0qVL6dOnz1k/3+VOJJRXIrm8qxtFQTKaUfOOVlvM/+t3aPrfiu6eF1C2rQFFQU5thlqUh3/mp2AKQnfdHRhXL+XmRg8y78BUFLX8w7Fd/DWkhDblg9UPVXRh/57+A3HWVEa0fobm0d1pEN4Gt7+UrJIDbMpczDX1byciKOG8PabPp5Z/8+5vwBYssXaDjw7tdTidKuuXeykuVtHpoEkjLcnJEkXFCrIMJpNIKgVBqF1yWBS6G+/C9/3kykmlrEF30921NiHnz/r374/X60WSpIpu4uPCw8Pp27cv77//Pg888ECN4yjPp8TExJO2JI4aNYqXX36ZmTNnMmvWLKZMmVJx7quvviIhIYHZs2dXqrNgwQLeeustxo8ff9ati8frVTfLXDhBJJRXoiArGIoBUHKPICc3gAO7qpZTVdScDJTCXNT8bJBkfFtWgPuPX6rSEtDokFf+Qus2z/CdbyI2YwRGjYU+qSNYnbGYbim3sjN3KYWubACyStJYm/EjPeOuI6PkENHWOuVd4aEtmLxuHA93m0Sk9tyTSqdTYdUaL3v2BVAUGNjfQNtWWgqKVBYvPbGnuM8HW7f7yS8ob8XMyvbTrImWoCCRVAqCULs07Xoi1W1MYN0S1MI8pLAoNB2uuiDJJJQnSrt376749199+OGHdO3alXbt2vHiiy/SokULZFlm/fr17Nmzh7Zt21YqX1JSQk5OTqVjQUFB523XuTp16nDVVVdx1113YTAYuP766yvOffrpp9x44400a9asUp3ExESeeuop5s+fz8CBAwGw2+1s2bKlUrnw8HASExMrPcfxLu9x48YRGRlJly5dzstzXK7EX80rkKQzIgWHgtmKenA3cp1G5ZNs/kqjRdv9WgKbfkc5sAslbceJZPI4WQIlgKasDJ2sJ1S18FSPn9hWEMGqwqFstN9Mt/rvc3PL19HK5etcrsr4Ea9GIUGfQLQUys97pvDuqvvIL8tkR86Kc34+t1tl0VIvu/YEKiZRarUqXh+s3+Crtk5mloLRKLFug49tO30EAmJHUkEQap8cFoWu/z/Q3/Yguv7/uGDJ5HHBwcE1Jnz16tVj8+bN9OnTh6eeeoqWLVvSrl07/vvf//LYY48xYcKESuWff/55YmNjK73GjRt3XuM9vsj4bbfdhtFoBGDjxo1s3bqVG264oUp5m83G1VdfXWlyzrJly2jdunWl10svvVTlOeLi4hg0aBBms5kFCxYQHh5+Xp/lciP28v6LK2EvbyXfiX9fDppID75pryGFR6MdOILAb3NR/miplOLroB0yCoLM+N5/tmoiCUhRcWg69cU/9zM097+ETyvjUC08urWMdIe3UtmOMXoGJqYxY9tTANzV4XUmr3uCOGs9bmj2MJPXP4HHX0b7hAH8q/3pj3WpTmGhwudfV463Y3stsTEaZs/z1FALenTTYYopxOErJTbEQnRQKAaN/pxiEQRBEIQrgejyvgIpB/IJzN2J/EAr9A/8m8DuLQR2bUbT+3q0Q0ajusuQjCb8y+ahFuSgGzIK34yPK4/zMZjQXjsc/9zPkMKikTUG9GVlLLB7qySTAGtzvPRPbkCIMQqbMYLcksMAZJUcYNmh/9E1eQhLDnxDSmiTc36+EmfVZYDcbhWzWaJbFx0ZRxQyjlQdCK8z+XlsxyvkuPLRyzpG1L2WW+sOIMxgO+eYBEEQBOFyJrq8r0Cq3YUUGoTkkvEvmIFalIsUm4Sybyve/z4DTjveqa+jbFqOengfga2r0Y18HE33a5GbtkfT9wZ0wx/Ev/B7VHcZ2qEjwWnHrsC87Oq7lAEWH9HQOKo7Qxrfy9bsZRXHd+SspGFEO3QaIy1je57z8xkMJxbbNRrLlwXS62V+nu9hx04/4eESQwYZiIyUad7WR7seLpq28mML93FzygCujumIoipMTZvDvCO/EahuFqYgCIJwWu65554q61Mef9W0R7fw9yO6vP/iSujyDhzMx//jDqSkEOTEICS9ncCaBaheD5oWnZCCQ/F99W7lSpKEXK8pJNRF07ILysbfkCJikKISUI9lgcFIIK4Od2z0kFFS3kJp02sYXEdH03BwByCjxMiABDeh61fjjo1mm5TOvIwvSQppzKCGdyLLWpJDGqORz77h3FmqkJ0dYMVqH3a7yrX9DKxZ56WwqPJ/87ZdvGjjMvk0bSbZ7jzqBydzW52B/JZ9CI/ip09cA97ZOY1cTyFf93iVuKDIs45JEAThSpaXl4fD4aj2XHBwMFFRF3bcqFA7/lYtlMuXL2fw4MHExcUhSVKV5QFUVa0YTGsymejTpw/79++/OMFewqQIM6pWQlMvEt/0rahKLJpe/0Q7cBSqJQTlwM6qlVQVJW0HyrK5YM9HyTqMZAkpb8Fc8Qv+n75C+m0un7TS0yRUT/toPa909uFx/odvN93Mr7tGEy7PwqgG0KxYgPnb6TQx9+DmVt/g0z/B4sxYypR65LvObdeaI0cVflvho3cPPSlJMo4SpUoyWbd+gH3Gldy//hU2F+0mx1XA77mbuG/NyzQICWafPZen1s/h4aaj8Ct+8tyFOLzOc4pLEAThShUVFUVqamq1L5FMXj7+VgllaWkpLVu2rLIA63FvvPEG7733Hh999BFr167FbDbTr18/3G73BY700iYHm9Df2h4sBqRoK77pa1EzPajFOiQ1EUJjaq4cZEUtdaJp1p7A6gX4f/2uvIWypBhl43J0k57l9UYaRjX2MGXtKPbkr0FRA5R67fy6fwqfbH0B17BbcQx/nJcPanj09yJmHSjjs91F3LXoMN/tKyKvtOZu85NxuxW2bPXhdKosXualbRsdh9KrdlenNClj8sFvqxxXUflwzzfcXKcNTr+HmelbGZJ4FUUeBzuLDwDgDfjJLbOTXVpMkaf0rOIUBEEQhMvN32pSzoABAxgwYEC151RVZeLEiTz77LMMGTIEgM8//5zo6Ghmz57NP/7xj2rreTyeSttH1dQsf7mRQ4NQtDL6u7ri/2UXvtlbQa9F0zIebe9WBH79ptodHDQdeqPs3ICmVZfqWzK9HixL/oezcxIB1V/ldLp9N7l1tOwtDWNjfkmV89/uLaRXgpUos+60n8XjUXGWKjgcKv4/lvspKVFJOxBA/stXJp0O8gN5+NXqx0Xme4oI0pX/WqzI2c+HXW/F6fNh1VrILbPjDvjwKgF8ih/VA/luJwnmUExaMRtcEARBuHL9rVooT+bQoUPk5ORU2hbJZrPRsWNHVq9eXWO9V199FZvNVvE6vrDplUC2GsGsRzOwKYZxfTA82Att30YoehO6EQ+BtnJSJzdug6ZNd7DaUA5WsxD6H9Q9m4nV19zKuaV4A9tLa/6vN+9gMcppDu31eFX27PPzxdduNm/1kZx0YnHe9MMBUutV/s6kqqCRTv496viUHo0sY9NZiTDYMOuMvLtrIbcsncRtyz5iwpa5lPo97CrOJNd1ZXwJEQRBEISaXDYJ5fHV+Y9vJH9cdHR0lZX7/+ypp57CbrdXvI4cOVKrcV5qZLMBTYQFOS4EOSEEOcqKbDSiGkzohj+EduhotIP+iW7seOTEVLwzPkbT+RowBtV8UY0WlZrHQpr1wRS5a5457fAGTjuhLHWqLP2tfBJQxhGFxHgNZnN5Smh3qGhkSIg/8d/c7wcb4Rg1hmqvlxAUTf4fa24OiG9OoacMSZJ4av0MFmbuJKCWP1eaI48HVn9JojmMbYUZovtbEARBuKJdNgnl2TIYDBU7BZxsx4AriWwxI4dFoZYU41+3BOXQLiRk/EvnwNEDUFJcvl1jTfXbdKeQmiextAnrQrCm5oSzV4IV7V/7qmuQdrByt/rS37wMHqSjcTMFkwnWbvDRvr2GawfoSEnSkJSoQa8aeb7F3UhIleoaZB0PNbmd7w5uJNoYzFXxTRi/eQ4uv5eWYUlV7q2gMmn3EurbYnB4xR6vgiAIwpXrskkoY2LKu1hzc3MrHc/Nza04J5w+OTwauXlH9Lc9iPaq61GDLGiHjgJJQtmzGaw2NF37V6knhUai7X4tTYyNibfWq3L+pgb3YT2cyT8bh2LQSFXOx1t0tIo8SevnX7hclVsyHSUqB3OK2RQyg/p9DtBlcB57pY1sYDEpXY5Sr0smC8t+JN4cybRuL3FdYi/ahTfhjnrX8UGn59mQl82AhBaMa3Etr2yZR7bLzrMbf6BnbMNq77+t8CjegP+0E2BBEARBuBxdNn8F69SpQ0xMDIsXL6445nA4WLt2LZ07d76Ikf19yWYrclQccmI95NAIpMhYdKPGgd6IhITcqDW6Ox5DbtUFuVErtAOHox00Au8n/8ZUUsaD8Q/zQLu36JY8jAENRvNcr69JCW3BcnM6O/P+x8SeNjrGGJEAvUZiaN0QJvZMJNZy+hNc6qZUHQ95LCOIUF0IJpPKIxvf4KlN7/HWrs8Zs/o5ntk6kWviujB9/1zuWjUBp7+MOpZ4rorpxE8ZO0GSWJ6zl/9b923F2Mg8dwnugI961iiiTZVbsEMMQahAkLb6LnRBEIST8RdnUvzbB+TPfpri3z7AX5xZq/cbOXIkQ4cOrfbc5MmT6dWrF8HBwUiSRHFx8SmvV1BQQP/+/YmLi8NgMJCYmMj9999/RhNcvV4vb7zxBi1btiQoKIiIiAi6du3KtGnT8PnKV/3o1asXDz/8cJW606dPJyQkpOL9LbfcQocOHQgETgyr8vl8tG3bluHDhwOQnp7OmDFjqFOnDiaTiXr16vHCCy/g9Vbd5U04fX+rWd5Op5O0tLSK94cOHWLLli2EhYWRlJTEww8/zMsvv0z9+vWpU6cOzz33HHFxcTX+8ginT9JqITQCMg4gN2lLIGM/si0c34xJyA1bIVlCCGz8HTUnAwD/z19jad2V+hvSaNS6H1JAxffRB2iGP0CSryls24IStpSXOlxDSetIir3HWJ8xjS1HI7HVvQmLIeS04goLk4iKlMk7dqILPT0dBnftwuOb/8Mxd1Gl8tmufCZsnUy/+C4szV3Pkux1ALSPaMOcjC1Vnxv4Z2pXIo3BDExsiV6jJS4ohNmHN7I8Zx+31OlAiM5IsN50Nj9WoRZ5fWW4PEXlCb8hBL3OfLFDEoRKnNvmUfjzBPjTqhOONZ8RNuA5LC0GX/B4ysrK6N+/P/379+epp546rTqyLDNkyBBefvllIiMjSUtLY+zYsRQWFvL111+fsr7X66Vfv35s3bqVCRMm0LVrV4KDg1mzZg1vvvkmrVu3plWrVqf9DB9++CFNmzbltdde45lnngFgwoQJZGdns2jRIgD27NmDoih8/PHHpKamsmPHDu68805KS0t58803T/teQmV/q4Ryw4YN9O7du+L9o48+CsAdd9zB9OnTGTduHKWlpdx1110UFxfTrVs35s+fj9FovFghX1Y0tnCUGA/+Fb8gpzZHOXoA3C6UrVVn0avZh5Guvh7WLYH4LEhpiH7EI/i+fAe16FhFOf3SuYQNGYFSL4HuyQOYsuFZ4m2ptIrrXeWa1TGbZQYPNLB1u49t2/14vRAfJ+NVPaQ7s6qUt2iDuCa0AzeYutGzfmNKdT4WOTcSFxTBmx3+QUANICHx45Gt7Cw6yl2NerEp/zCjf//0xM9Bknm46TU0scXRMaoemwqPkBIsFue9VAR8CkWlh1i9czJBxjCSojui1egJDopFlvUY9EEEGUIvdpjCFc5fnFklmQRACVD4ywSMSW3QhsRf0JiOtwAuW7bstOuEhoZy7733VrxPTk7mvvvu4z//+c9p1Z84cSLLly9nw4YNtG7duuJ43bp1uemmm8641TA8PJzJkydz0003MXjwYLxeL6+++ipz5swhNLT89/540vzne+3du5dJkyaJhPIc/K0Syl69enGynSIlSWL8+PGMHz/+AkZ1ZZEj49D1vxXVaUfJO0nXzB9jCqXEVIivAyYz/kUzKyWTAOj0BLKykRq2Z1/hah7uOonVGQuoF94K62n+0bdaZFJblGJILMKr+NlZspcsd9Vxs6H6YD5p+AQxs8pg7x6iAfQyd13TnTWmIsbtnolNb+LpOv15IaIvkuwFv55Qi4ENhnQKPOUTjQKqwts75vNVz7t5esP39IprdFpxCrVP8anYXUdYu/sLOja9lzU7P2TuysdQVQWdNoj2jW4nMqQBcRHNMRvDL3a4whXMuXV21WTyOCWAc+tsQnqOvaAxnQ9ZWVnMnDmTnj17nlb5r776ij59+lRKJo/T6XTodKe/JvFx1113Hf/4xz+4/fbb8fl83HHHHVx77bUnrWO32wkLCzvjewknXDZjKIULRzIFofr9yA1agFR1Yg2A3KQtStp2NG264Z89DfVIGnJCnUpllJRG5Nz9KhPj+zF2pYNvD7ZgU34QbRNvwRM4/e86uWUF/J61HQNBBAVC6WhrR2JQDPJfZnE/X2cUsdMdsPdPC6p7Ffgxi1ZpZq6OaczkxrfRZYaK7j/70H6ajvbNfXT+xs/kRrcSZjjRZaoCP6Vv4ePGt9E7UiSUlwq/24vdoyEl+V52pf9CUvxtXN3pS67qMImUmG4cK96Hz19GoSPjYocqXOH8RScfK1nbYynPt1tvvZWgoCDi4+MJDg5mypQpp1Vv//79NGp0/j9DJ06cyL59+ygoKODtt98+adm0tDT++9//cvfdd5/3OK4kIqEUzopkMhPITEd7/b+qnguNRNOlP3L9lgSW/wwFOfi/n4zqdiE3a19eyGLj6LV3MnJtCT9nlHLM5Wd/sYcJa4/x8fZ8XP6auzn8ARWHQyHjSICD6X50HhvK1vYsmR3Mbz+ZWTrbRnGGjUGJJ74hm7UmUr3RqDnVL+9jXFTAo3G9iZ1RhJpZVumcmusm6stjPJjYq9Lxo55iTIvyqe8OOb0fmlDr7IqPb7aFEmwys999K6+urM8LyxKZuL4ZcujzNK47iiN5m9DIMiVlx059QUGoJdrQk3dnX+ju7tMxYMAALBYLFouFpk2bVjr3zjvvsGnTJubMmcOBAwcqhqSdysl6Hc/FN998gyRJ5Ofns2fPnhrLZWZm0r9/f2666SbuvPPOWonlSvG36vIWLh1ySBgk1sO/bgm6u55F2bMF1WlH06gVUlQ8ypEDBH6bh5p/YlH5wIpf0P1jLMqO9ZR1uZaJ+714A1U/TJYccTO4joRB9hJlia10zu9XOZoZ4Kf5Hnw+6NZFx9p1AXLzKl9n1XItNw+5kTBDMP87tIBIYyi63KpbQf5ZiD4IVSOjaCXwV76eerSMlvrKa1F2NqcgHXWjzDqC+q/6SEHi1+lic/j0NIyCL7f4WZNR3lUmAT1SvNQNcaAqZTSrMxiv383OQz/SMnUYptOcACYI55Ol5VAcaz6rdotbZA2WlkMveEynMmXKFFyu8i/lf+2KjomJISYmhkaNGhEWFkb37t157rnniI2Nre5SFRo0aHDShO+44OBg7HZ7lePFxcXYbLZKxw4ePMi4ceOYNGkSS5cuZeTIkWzevBmDofJqHFlZWfTu3ZsuXbowefLkU8YgnJz4CyicNSkuGW23gShH0pGikpFbxYPXg3fik9VX8Hngj51myhIbs2Wzu8Zrb85TCJIPVkkoS5wqc3/yoPwxqTssTCY3z1elvqrCr7ONDLt1AA2tjTBoNAQVhAD5lQtqJUpujSUz2svS3N8x9dZw9dAGRGzzYppfuazGoyIjoaASog+ikz4R9UgGqgyqJyASykvA/nyVlFANn2868YXgoS6llBV8yvwVP6D+8f/PYori2s4vU1KWJxJK4aLQhsQTNuA5Cn+ZUDmplDWEXfv8JdlCGR9/ejEpf3xAezyeU5a97bbbePrpp9m8eXOVcZQ+nw+v14vZbKZhw4YsWLCgSv1NmzbRoMGJjTYURWHkyJFcffXV3H777QwZMoRmzZrx/PPP8/rrr1eUy8zMpHfv3rRt25Zp06Yhi7WEz5n4CyicNUmSIDQcKeBHyc4GuwPJdPI1JKXQCOT6LSDYhiwVotTQ26HTwFH7PprHdK10fN9+f0UyqdWC233y7hLFo+ejPSs4UlrI5KbDaWTVQsmJlkrHnQmMdyxm3c70imNTWcXIpM78Y3Bdguad6Bb1msqTybZhyTyR2JfwqXmoACbxa3SpCDPJ5Jed+D/RPAYk13x2p8+oVM7pymPO749yfY/3UFW1/P/yBeZ1BfB7yr/8GIIktAbxB+1KY2kxGGNSG5xbZ+MvzkQbEo+l5dBaTybtdjtbtmypdCw8PBydTkdOTk7F8nzbt2/HarWSlJRU44SVn3/+mdzcXNq3b4/FYmHnzp08/vjjdO3alZSUlFPG8vDDD/PTTz9x9dVXM2HCBLp164bVamXDhg28/vrrfPrpp7Rq1Yp7772X999/nwcffJB//etfGAwGfvrpJ7755hvmzZtXcb13332XnTt3snPnTgBsNhtTpkxh0KBB3HDDDXTo0IHMzEx69epFcnIyb775JseOnficFxuhnD3xl1A4J5JWixwVi2Q0gqMI1WCC4FBwFFUtG5uEcng/UmwiWpNK11gLv2dVv0VjiwiV0jJbleOFhSfWm/T7wWiUkKTyP8pV7idBQOPn5jodiDJZ+TR9Nc/c3YfQT7NQi7xIKWaWyxmsK0yvUnf6kdX0bJZKvYUacAeQW4dh1Rv5ofEYLPs9mN7PQnWWJ6aaXjFIwWc+E1E4/xJCNfj/9H+kXz0727ZPr7asx+ekqCSD2PAWFzSh9LkC+DxQeFhBowONDuxeleBoDcYQCa1WJJZXEm1I/AWfzb1s2bIqrYFjxowhISGBl156qeJYjx49AJg2bRojR46s9lomk4lPPvmERx55BI/HQ2JiItdffz1PPllDT9VfGAwGFi5cyDvvvMPHH3/MY489RlBQEI0bN+bBBx+kWbNmQPnSPsuXL+eZZ56hT58+eL1eGjVqxIwZMyqWANq3bx/PPPMMU6ZMqZQY9uvXj1GjRlV0fS9cuJC0tDTS0tJISEioFE9tjem8Ekiq+OlV4nA4sNls2O12sa/3WVBVFTXzEN7JE8D9pwkwFhu6EQ8TWL0QOT6Fvak2TJZ2PLA0kyJP5TFEIxqZsEk/cnXdIcRYEyud27HTx6KlXiQJWjbX0qihFqdTRZKhpERlwyYfTmf5f+m69eBQ3Bq+TF9BmMHMi62HMnnvMu6N7UZjIim1KIzd+S0ZpYXVPsuguJaM29YYSafBfrWN0N1eAt9Xnh0sJQehv7sBcphY2PxS4AuoHClWGL/YQ5FL5fleBSxdPbTG8h2bjKF9vTsxmk9/d6ZzVVoUwFOiImsljqUFcOYrWMJlohtr0OhUTDZZdL8JgvC3I1oohfNKkiSIS0H/yBsoh/aiZh5CiohBstoI7NmCts8wfD9MwZDYkw2F03j/qtGsyipibY6fEANck6hwrOR3Em2dKfbaiAgoaDUn/rgmJWowmaB7Vz2HMwJ8O+PEOMzQEIk+vfUs+c1LWJhKdLNCXt9Svuh6oaeUyXuX8Vyr69DKGvaU2bHojJT4ah7HaQ+48A2LpVB1U+wvwlTXie6RSKSdPnCB2khLmSYD+9F9RARfh0Zsv3jR6TQSCTaJZ64y8NIiNw6PDospCqcrr9ry0SFN2PJDgCb9AhhtEnpj7SZyboeCGgC/F7Z+5ybgA2u0TFR9CVeRis4kgQomm4pczV73giAIlyrRQvkXooXy/FI9blSnAzU/G8qcqAE/gTWLcPa+mlcPv8xLnb5GKT6G22qmzFeM4nUSaohADopln0tDnFlDnPVE65+qli8ZtGWbn81bq87atpglBl2nYVbWWr5MX473LzMov+x5F9P3r2Rp9m6uTWyBx+9jQdbOamN/uuUgfs/Zyz2NehHjLmTfrLtRFT+WmObIWiOlx/bidxUia400Hz4DQ3Dc+f3hCWetzOmhyA/FLnCV/MyyTROqlDEbIxjUfDo7v7NhMEs0v06PJULGaK29pNJdEsBTAptnenA7VMJTZBJa6di9yEtwtExsYw06k4RGD6YQGa0O9EGitVL4+2ratCmHDx+u9tzHH39csb+28PcnWiiFWiUZjEgGI0rAh/eLt8EYhO76fxG0cAZP3PIe2rWLUZfOQQdY6jSh8JoRrDym5ZCnhHrhZoINGtLtHuIsOvQaGUmSkCSJHbuqXwLIWapytLCMH46sqZJMAmS77Cz6I4FckLmD/3S4heW5+3AHKs8UjwsKob41ki35hwlXvGi1BvTWGNxF6ZRkba5UVvG78Zbmi4TyEqLX6wkU78Sm0RET1RZ30zvZuOcLfIHyFumokIb0bfkKWb+HoTUE8JSqeEpU8g/6qN9Dj0ZXO62DshZ8bhW3QwUJUjrq2P6jh5ZDDEgaidJ8hcKMANZIGYMZDm72EhKjJTRRxmAWiWV13N4S3F4HPr8LrcaA2RiOXhd0scMS/vDzzz/j81VdiQMgOjr6Akcj1CaRUAoXhBQRi/7BV/Ev+gH/yvnorx1OmEeH7/efAVBjkzjQ/188tNGBy//HUhMHSggzani7ZyK5pT4Sg8u7lP1+qOHzCYBSh0SowYzdV3kRc5vehPtPC6Z7An4+3rOM19vfxP8OrmdV3n70spYBcY24Nbou/rXv839t/knW8jdw24+Q1OUhcrd9R0nWJgC0xhBCUrojaw2gKnideegtYk/vS4FWLxEanMiOQ3OIDW1Ns4SbaZw0AJfbgVY2oZVM5Bam4am/gpS2zZCd8XhKQyk4FCCprUpQyPlNKP1elYBPRQ1UrJxFRIqG/AMBml1rQFVhyw9ufH9aU18fBO1uNbL5Bw8RdTTU76VDb7pyk0qn6xguTzGqqmIy2LCYoigpy8Vemsmxov1oNHqiQhtyrDiNuIhmWEyRFztkgfK9vYUrg0gohQtCkmWkqDh0N9yJ6i4Fnw9fmRP85ZlhcZ/hPLHFiesvC4oXugO8ui6HB1tFEW0ub6VUNX70evDWsJlOZJiWgtyqs8f/1aAnsw5vqnRsZ1Emb2z7mffb3YA3vj6Krwz/gUUUrPkPquLDfmg59Qe9xYH5T3Ng4XPUH/gWJfO2kdDpHvTWGArTFqE4cyg9tgckGa0pFFkjZnxfCqzBNlrUG4bLV4gTI0ZPMFlLwwntsIefNt6BP3Bi/GykrQGDO73D4Q3BBE7yZeVMectUHLkK6Wt8eF0qLYfqMAZLaHRgtEkEfKA1Suz40VMpmSyvC1tne2h4tZ4tP3hIbq9FfwXO/QoEfOQU7mT/0aXER7ZCVQM4XUY83hL8io8ydwFBxlA0Gj2rd35CXERzQq2J6LUW9Lor8AcmCBeJSCiFC+p4F7jqcSP5fOXrOGq05AeFUeSpfgmhvUVuZFnC5VdwB8qYlb2QVi37s269UqVssFUi3Krjzga9+OLASo65S6hrjWRso96YJZmmyS3QJzRE0ejJ8PtpFmQjWKPFk7uNrIXPAeUtjzpzOL7SfFTFR97276l7zQQ89qN4S3Koc/VzOI6u4+jq9yvu6zi6Hr01lkZDP8QYklQlLuHiMFusmLFS6lFYechPy94Ovln+UKVkEuCYfR+r93xI+xseQHOekhCvS+HASh+H158YnrFvqZ963bSkdtdRkK4Q21SD4lMpK6p+KHtpgYohqLy1tPCwgiVCc15i+zuxl2ZhL80C4FjxfsKsyShygCLnUX5e8yw+f3kmrtUY6dLsbhylWRQ7j6CV9eh14ndREC4UkVAKF4VkMKIJsqCmNELNPkyZ/+Rzw3yKikEjk+N2cNSdS9ukHBq5wtm3S1Ox0HlkpEyHnmWkBwrpHlOfrjGpeP1uyNxAmCsHe+ZG8rd/j0tVqNvneSyFh8jZ/j2u5C6oqoI1rjXRrYbjd9sJeJ2YQpJx5u4gd9t3RDYdRvamLwip25OIhgM4tOiFKjF6S7LJ2fINCZ3GojVaauPHJpwls0Gmc4qOzNy9VZLJ4/Ye+ZVWqTeiDbIB5z5j31OiVkomAXL3BkhsoyU4ViYoTMZkA7fj5NcJ/PG7IV95uSS+gI/sgp14/aXEhjdj/Z4vWF00GYspkhZ1h3F1m3H8un4CqhrAH3Cz49Bc+nd4gcz8bUiqjFZrwhokur4F4UIQCaVw0WhsoUj/uA/fp68Sq1eRgOrSSrNOJtyowa+6OeYupFdMW8ZueIH7GtzGgMbt8Hpk/JKH3WV7uG/rd0zsMI4IoxWjVocjbzd5R9biMAZzbHv5bikxrYZTnL6Swv3l23gpPhfW+LbogsI5uOBZFP+JhCOkbi9Sej+DITiO5B6PoTFY8Jbmo7dEY4qojz4oArf9KCWZGwGV/D0/EtPyNjQG80XZfUWomdUoUebJrXI8xJJIg8Sr0WlNqCiUevLQ6xOrucKZOXagmj2agS0zPTQdYEDWqiiqhNEmIcknxlb+mfSnIZOhSVdeRlnichNqTaDQkc68VU+cOF6Wy8odH1E/4So6Nh7JzvQf6d36MRyl2WzY+yUWUxSJUW1weYpQFB82i5gwJwi1TSSUwkUlh0Whu/t5QlwehtTRMPtQSZUyo5tGYDPAnIxlJJqjCdKY+E/7J1mbl86HhxaQZAmlQ2QySzJ+p9Brp8hrx6itC4AGibDUqzmw4LmK6wUndmDfvIcr3tuPrCO+033s+t8/UZXKLUrFB5dhjmxMWcEhstd/DIA5uhmp1/6H4vRVqKqP6JRuJHZ7mOz1n1J8eCVeZy5abRhaq7kWfmLCuYgJa1bxb0nScHWbcaio7Er/GY+vBLfHTovUG1BVBUk6twkwNS3I5veUj43seLsBjSwhaVUSW2vJ2Fh15YLk9lqydwRodLUOg/nK+oKiqirHynSE6oys2vlxtWX2H11C8x7vER/ZlgXrX6Kk7MQXhk37vqZP26cxGUIo8xQRbquDXitmfwtCbREJpXDRycGhBAfDv2x+kmwmvthdQJEnQJxZx90tImkbHUSe5yhv7/qCCa3GopdtPL7uW3zHlwXKhe8PbeSlNkOw+0oJN4RUXFtrCsFTko0aKJ85LmuN+N3F/Lkt1BRWB/vhVVWSyeNyt31LYpcHKt6X5u5g75yxNL5hCsd2zCRz7UdoDcFEt7iFiKbDKEhbhL5FDFpEQnmpCTbHEhfegqyCbXRtfi/pOWtIy1xacb7QcYgdh+Zya59pRNjqndO9Iutp2L+s+hk+4XU05O4JUFasUqeDlqR2WozBEofW+vCVlc/wrtNJhzlCxmCWCAqV0BqurITSG4Bt2TI9ElUcpdk1lit2ZpJfvK9SMnnc4k2vMbzv59idmahqgLiIFrUZsiBc0a7cNSiES06YUcvNDcOY3q8OPwyqx8d9kumbbMNm0DDj0EIAtLKBFzfNrkgmNZJMv9hGvNuiH3GKn7ea/Ysww4k9wPXmyPL1IaXy7kIl4EXWVU70dKZQPI6jNcbldxWh0VeuE/CUULh/EaV5u3AVpFGStYm0+U9QuP9X9JbISt3mwqXDYorg2s4v07LejYRZUyolk8d5fE5WbH2fMk/V/ejPhDFYIrF11e/sGj006KUjLFlDo6v1WGM06IwysU01dLrdSNc7jXS8w0h8Kw0RdTTYYsvPX2m0MpT6VDTyybfFDDKEcDB7ZbXnVFUhu2AHBp2FZVsm4vLYayPUc+KxZ3Jk9QekzX+aI6s/wGPPrPV75uTk8MADD1C3bl0MBgOJiYkMHjyYxYsXV5TZvHkzt9xyC7GxsRgMBpKTkxk0aBDz5s2r2O86PT29Ym3gv77WrFlz0hjeeustQkNDcburflaWlZURHBzMe++9B0BKSgoTJ06sOJ+SklJxH7PZTJs2bZgxY8Z5+MkI5+LK+5QSLmmyJBEZpCPWoifcVL78TkAJcOyPP+462UCBpxQAo0bHR20G80/nQfj5YZyz76Lgp8fQHt2Ct7AQ5WgpgdX56B2hhKX2Lb+BqhBw29FbYiru6So+TFBEwxpjMoWnVvshX3ZsD8aQlErHCvb8RFB4KrLoWrtkhVgS6NzsbrILttdY5kD273i8VYdfnAm9SaZ+Tz1tbjYQliRjiZRI6ail6xgTwTEyUfW1BIXKaPUSBrOEKViDOUyDNVKDOVSD3qi5ordf1MgSV9XTUlAWSlJ0hxrK6AkLTql2a82YsGb0avUIEbZ6hFgSsJccwRdwVXOVi+fY7nls/WIY2RumUrj/V7I3TGXbl8M4tnterd0zPT2dtm3bsmTJEv7zn/+wfft25s+fT+/evRk7diwAc+bMoVOnTjidTj777DN2797N/PnzGTZsGM8++yx2e+XEfNGiRWRnZ1d6tW3b9qRx/POf/6S0tJSZM2dWOff999/j9XoZMWJEjfXHjx9PdnY2mzdvpn379txyyy2sWrXqLH4iwvkiuryFS55eo6NndFtW5m0hoJyYufBEg65o1/wXe/aWimMex1EOzH+celf9G/OcWNSMUtBKJNx/J353EY4ja8naOI2U3k9xcOEL+N3FeB1ZaE0h6C3ReJ1Vu81i2/yTzHVTqhzXmSPxlR6rctyZs43g2E7n5+GFWmExhZ900pSEjNdXhqM0h2BzTI3lauJzKwR8IGskolLLd7pR/KAzSld0knimoqwyW0ssXNXmCWYsvZtSd37FOUnSMKDjeJBkIkPqc6x4P1CeZA7o+BKOshy2pH2Px1tCUnR7ruv+FnDp/Ow99kwOLZ4AauXJW6oSIH3JBILj2mCwxZ/3+953331IksS6deswm0/0vDRt2pTRo0dTWlrKmDFjGDhwYJVkr3HjxowZM4a/7tgcHh5OTMyZ/Z5ERUUxePBgpk6dym233Vbp3NSpUxk6dChhYWE11rdarcTExBATE8MHH3zAl19+ybx58+jSpcsZxSGcP6KFUvhb6BLVkghDCBoZDBotRo2ORno9ZX9KJv/syLr34Lo/lu7xq+DwE1KnJw0GTSSu7SiQtDS47j1SrnqOhM5j0RhsNBjyX4ITTrSE6MyR1O07npLsbXjsR/5yB4nQOj2wZ1TTrSPJaEznvuyMULvqJ1xV47nUhF5sSfsfWw/8gLMsv8Zyf+X3qBRnBtg808PKKS42fOsmb78fNSBhMMsimTxNDrdKtkOh2KXSOEpGo0vk5qs+YUDH8TRNGUSXZvcy4povOJC1nOKSI/Ro+RDSH8Naru00ge0H57B867sUO4/g8haz98hCZiy9G/cl1OWdt2t2lWTyOFUJlJ8/zwoLC5k/fz5jx46tlEweFxISwoIFCygoKGDcuHE1Xud8rWAxZswYlixZUmmv74MHD7J8+XLGjBlz2tfRarXodDq8Ne12IVwQooVS+FuIDYrkk64vsChzHQ81vprvD29CLkyrsbzXmYMSHUAO06OWBfCai8hY8gYgodGbUfxuVMWPzhyBMSSZ4KQu5O/+kaCoRkS3vOWPCToSQYbGlPp3Vrq2JOtI7vEYpcf2Ed95LFpDMB7HUYoPLsNVeJCQZPEN+e/AYoykaZ3r2HlobqXjQYYwmtcdxtwV/0dA8dMk+VqUMongoPCTXk9VVQrSA2z+wVNxzOdS2DTDQ2p3HSkddWj1IqE8GZ9f4VCRyuR1XvbnK0hAqziZf7U3kBCSjLMsl4Dip3ndIWTlb6drs3vIyNvAjkNzGNrtLQ5lr8Kot3E4t+oXPX/Aw29b3mFw1zcw6q0X/uH+4lRjJT2O8z+WMi0tDVVVadSoUY1l9u3bB0DDhieGAa1fv57evXtXvP/2228ZNGhQxfsuXbogy5Xbp5zO6jeq+LN+/foRFxfHtGnTePHFFwGYPn06iYmJXH311af1TF6vl7feegu73c5VV9X8JVGofSKhFP42kswx3FKnL67SfJL1JiyuHGpqO5JkLYriRbopFGmOA5dj7x9nVALeEx90ssaA4nOBJGNL7sbeWXeR88e5xNYPEfRbJNENBhHZbwhljv3IGgOmsAZghYC3hMK0xRTsnousMxHV/CaMIYlIGtE6+XdgNUfTucm/aJTYl037v8XtLSEpuh3xES1ZtPFVfH8sgG4vzSTI6MFqCj3pUkLuEpWd86tvITmwwkdcM61IKE8h06Hy1Hw3/j9GtqjA5iyFJ+e7eGugCa+/lNSEXqzc8RGqEiDYHM2GPZ9TWJJOdv52bu71MdvTZ9d4/cO5a/H4nJdEQnmq7mxD8Pnv7v5rV/XpatGiBVu2bAGgfv36+P2VV8T47rvvaNy48RlfV6PRcMcddzB9+nReeOEFVFXls88+Y9SoUVUS1L964oknePbZZ3G73VgsFl577TUGDhx4xjEI549IKIW/FbPOhKwqmNe+i6X3M8haY7UzqkPq9sLjyMYQHIvGE8AQFFvpvCWmObFtR+FxZOErPYa/9BiGkESiW/+T3M1fAJQnD4qKutiOtAQsIbGokQZ8A/NQpQAHFjyH31VYcc3S3J0EJ3UmpecTCH8PRn0wZlMk1qAYwoJTyDy2hbW7plYqI0sa/H43Rc4cwqw1L5Dtc6l4S6v/g62qUFakEBQqRhnVpKhMYeYOX0Uy+WclHliZ7iOafaz+05qUyTGdcHmLSYhoQ++2jwESupNMiNPIOqRLZBxlVJOh5Gz6DFWp2u0tyRqimgw97/esX78+kiSxZ8+ek5YB2Lt3L506lY8FNxgMpKam1lgnMTHxpOdPZvTo0bz66qssWbIERVE4cuQIo0aNOmW9xx9/nJEjR2KxWIiOjhYbSVwCREIp/O3ogkIJSeqCx36UOle/wMFFL6AGTrQMmcLqEdl4MAFfGR5HJkFKGAZi0RpD8LuLMUc1Iab1CA78+nRFMpq96TOMoSnUu+YVbEmdKNz7Cz6pGLldMIHMMlBBLfLCUCsFWT+i+l2VksnjHBmrcduPYgiOQ7oS98r7m9HrzGg1eo7kbaCo5HCV8yZ9CCZjGDmFuzAawih2HkVCxqgPxqCvvL2mJJ/8D5oYP3lypT6VnXnl2aTNCAMa6qgTJqMoYNar2N1gUpLRaYwEmSLo1GQ0ZmMYV7V5nPDgeuQU7mTp5jcZ1Pm1Gu/RKKk/pj+tU3sxGWzxpFz1HOlLJlRKKiVZQ52rnq+VCTlhYWH069ePDz74gAcffLDKOMri4mKuueYawsLCeP3115k1a9Z5j+Gv6tWrR8+ePZk6dSqqqtKnTx+Sk5NPWS8iIuKsk1ihdoiEUvjb0RqCCW90LdkbP8OW2IHUAa/jKc7AW1ZAUEQDFL+HrPWfEtFkCEGmOlDqQt4CDQd/wL6fHyK27R0cWjyhSsumuyidzHWTCanXGzQGwhsOQPLZkFYVox4rLxsIdmOxNCJj5cQa4yvY+zPmqCboTLYaywiXBn/AQ1FJJv3aP8/M3x/C6zsxHEIj6+nT7mn02iB0GgNefynTfxkOSNSN60avVo8SFnziD58+CMzhEqUFVVspNXowhYiE8mRUFUKMEloZ7u6o59utPvYcUxjSRMvv6QoZxQpx1h706z4Ls3yUX9Y8R0lZTkX9unHd6d/hRQ7nrKFdwxFs2PtlpesHm2Pp2GQUsnTp/NmLbDyY4Lg25O2ajceRiSE4nqgmQ2slmTzugw8+oGvXrnTo0IHx48fTokUL/H4/CxcuZNKkSezevZspU6Zwyy23MHDgQB588EHq16+P0+lk/vz5QHlX9Z8VFBSQk5NT6VhISAhGo/G0YhozZgx33nknUD6GUvh7unR+swThDBiD44hv/y/83lLsh1dQuO9XkCTyd8/DEt2MuA53kr3xM0K6jUdzjx5lnwPZo5LU7VGQtJXGUf5ZcfrvRLf8B/q6oRxaPB6PI4sG/3wb7b5w2FiGqlFQFU6+LZ8kwynG/wiXBo2s52jeeprWvY6ben1Ies4aCuwHsFniSY7uSJAxnNyCXVhMUew48MMftVQOZv1OdsF2br16GjptENagSHxaaHadgQ1fugn8eYMcCVpeZ8BgEQnlyagqXJWqJcwk8e4KL8FGuK6xjleWeCq6wfceg04JAZZufZIyd0FFXZ3GSJAhFJCICW+KUW+jUVI/3D4nAcWHz+fCZolFUQIUOTOIsNW9OA9ZDYMtnsTOYy/Y/erWrcumTZt45ZVX+L//+z+ys7OJjIykbdu2TJo0CYBhw4axatUqXn/9dW6//XYKCwux2Wy0a9euyoQcgD59+lS5zzfffMM//vGP04rphhtu4P7770ej0TB06NBzfkbh4pDUsx2le5lyOBzYbDbsdjvBwcEXOxzhNHjLinAXHcTvKkKStTiObsBTkk1S+4dQX8uBsj+6k9pY8HQvxuVK50iNLYwSzW79ml3f/wvFV1px1BrXjrC4qwhu0ImsjVOQtQaO7ay+O6jhkA8whTdAb655DTXh0pFvP8is3x+mf4cXMeqsKChISKhqAJ/fgyRJyBoj3yz8J4paeTJCr1b/R4g1FbOlMcsOGdibq3B7Yx2+DAVnpoI5QiKhpRaTTUajEwnlyWQ7AqQVKDi98NEaL2M76/nfNh/H/jQu1WqARztsZ8m6+yqOtW04gqYpgyrWqLSYIlm36zN2Z/wMgNkYQe/WjxFQfMSEN2XT3m/o2eoh9Dqx+YAgnE+ihVL429MHhaLVN8NXmo/fW0JU85uQtQY0PjOBRmUom/7YQm+TE6M/BO2wmndwCKnbk8K0JZWSSYCSrA2UZG0gXnMP1vh26C2R2A+vxuv8SzdPnV7oLNEo/jJAJJR/BzZzHFe1fpzZvz+C2RhOaHAyPr+bBglXkRTdkcKSI8xbeXelZFIj6+jd+v8IMoSx7cA3KIqfpkl96ZXUnL0FFpa5rLRrpqFtogZtkIxGK5LJU1JVQo0SW7LKvwBaDVKlZBIg2CDhLMuqeN+24XDiwpsxY9k9uDzFQHkC2bPVw3h8Dg5mr6DUnc+Pq5/kxp4fUlB8kIZJ1+DxlYiEUhDOM5FQCpcFWWvAYIvnrwv2aP5RD6VXGYEVeaCoaLpGIRu9BCd1wlHNouSRTa8nZ9PnNd7n2K7ZNBj8X/yuIur0eQFn9hbsh1cj60xENhmCITgen7MAY2jtjYESzi+d1khKbGfu6P8tpe4C/AEvsqxh35HFKKrKjoOzCCiVlwPq3fox0jJ/Iz1nFeHBdWiSMhBUhcy8VdQJbURs8wSeXmglKlimxK3QIEpM0DoVjSwRaYG44PLku7qus0KXis1SBwC91kyDhKv5ZvGYSqVL3fnMX/siw3pM5HDuWgJK+fiDFds/oE/bpzDoLBWLoAu1q2nTppUWLf+zjz/+mOHDh1/giITaJBJK4bImBevQBNuQ6weDWj4TVwPUueo5sjd/Qf6uOSg+F3pLDLHtRqPRW9CbI2q8ni4ogoCnhOyN04nreDe2lB5YE9oT8DiRtUayNk4npuWt6EyhF+4hhXOmkbUEm2MJNpcvL+UPeLCZ45FlLSaDjZ9WP1VR1hoUgyxrSc9ZRa9Wj6CR9Ww98D1uXyn14roTF9ECo8bOJ0NVilwSvx8OIdYmYTWIcbUnE2mRybQHaJeg4estPtw+lVCTRJHrRLLo8kGRL5Ywawrxka3ZuPdrqks9FdXPviOLqBffi31HFgKQV7yXUnc+hSXpNErqf6Ee64r2888/4/P5qj0XHR19gaMRapsYQ/kXYgzllaM0Pw2fMxe9JQqfs4CCtF8JS+2LJGvYO+e+auvUufoFvK4iTLYE0n55AmNoMsaQJPyuIpw5O0ju9QQhdXpgsIgPy8tFqbuQ37a8w670nwBoXncYTldeefKpquxK/4l+7V8gJDgRj8+JRtJiMoaiBAIczFlBeEhbwmyNCQsS399PR54zwFG7yvfbfFxdX8v7q7wof/orZTPCq30LKSrewrrd0ygsSa/2OjFhzejT9knmrRqHvTQLmyWBgZ1eYcPeL+nd+lGsQeJ3VBDOJ5FQ/oVIKK8cAZ+L0rw9ZG2YSnLrh5DKtEgZoKZoKXatJOP3tyrttRvTegTRLf4BkgY14CHgLSF70xe4Cg9isCUS2+af6C0xGKziD9XlxuUpxlGazYHM5USHNWbjvm9o13A4s35/hJuv+hiHM5vft72H03UMgPDguvRt9zSyrGfp5v8woNO/CbOKYRCnyx9QKShTsbsVFFVi7i4fh4oUYqwSNzSF/LxvaZ06gMUbXuVg9u/VXqNx8gD0WjOpCb2YufxBurd4gP1HFtO52V0EB8UQESLWMBSE80kklH8hEsorj6+skICvDFljQKsNRtLp8HmKCbjtlB7bjRrwY4lpgc4cjtZQecu2gM+F4nMj60xodKe35prw96SqKsXOo/gDbnIKdhJQvBzJ20jzetfz/bL7+GvXq05r4rY+n5FdsB1Z0tCs7nUXJ/DLgNun4var6GQVvy+XYucRgozhFJdkMGflY9XUkBjWfSLzVj1BszrXYbMmopN1LNr4Gp2a/ovmdYdhM8dWU08QhLMlBvUIVzxdUBhGWwJ6SySy0YCkkdEHhWEKq0NEw2uJbHIdprCUKskkgEZnQhcUKpLJK4AkSYRaE7GYokiMaoteZ6ZV/ZtZv+czqhvH5/O72JuxgOTojhQ60i94vJcTo04ixCRjNmiwWeJwuvJxlGaRnrOGq9s+iU5rqiir11no2+5pdh/+GX/AzcGs3wmzJLFo4+sAOEpzMOpFY4EgnG9iUI8gCMIZMBlseP0uYsKa4vWVcqx4f41lcwp30aTOIOrEdbuAEV7+UmI6sffIIjy+Enx+F0O7vYPba0eSJFRVZUva/ziStxEAjUZHgeMgx5P+pKh2GHTmk1xdEISzIRJKQRCEM2Qzx1DszEKrUQgOiqm0a8ufhVgSyczbQlxE8wsc4eXNbAqnUdI1JEW3Y96qJwkyhPLr+vEAqKpSqWyDxL4czCofZ2kyhJAY3f6CxysIVwLR5S0IgnAWQixxGI02OjQeVe15SZJpXm8ISze/ic/vusDRXf6CjKFE2Opxffd3sZpjqBPTtUoyGWGrT0xYY44e20R0aGNu6T1ZjJ0UhFoiEkpBEISzZDGGExnSgM5N7qy0WLZOY2Rg53+z4+BcTIZg9KKLtdbYLHEkRralT7unuKHH+9SL60lKTGf6tnuWazuNx6gL5vZ+3zKk21uX5MzuMkcme9d/wOYlT7N3/QeUOTJr9X4jR4485X7ZqqoyYMAAJEli9uzZJy2bnp6OJElVXmvWVN04ojovvvhitfUXLVpUUaawsJCHH36Y5ORk9Ho9cXFxjB49moyMjIoyt9xyCx06dCAQOLEyh8/no23btpUWUP/zPWw2G127dmXJkiUV51999VXat2+P1WolKiqKoUOHsnfv3tN6liud6PIWBEE4B6HWBJrVHUq9hF44SrPQaPQYtBbW7PqU9JxVXNvpFSymqIsd5mVNljUEm2MINscQHdYYr6+UElceLq8Dmzkeg96MSW+72GFWcXTfPLYvn4D6p+XJDm79jOY9niOhweCLFtfEiRORpDPbLnTRokU0bdq04n14ePhp123atGmlBBIgLKx869rCwkI6deqEXq/no48+omnTpqSnp/Pss8/Svn17Vq9eTd26dfnwww9p2rQpr732Gs888wwAEyZMIDs7u8q1p02bRv/+/cnPz+eZZ55h0KBB7Nixg7p16/Lbb78xduxY2rdvj9/v5+mnn+aaa65h165dmM3ii+HJiIRSEAThHNkssUilMnszFrDj0DxcnkJCLIlc1/VN4iJaoNeZTn0R4bwIMoYSZAwlxJpwsUM5qTJHZpVkEkBVA2xfPoGwmDYEBV/4tUu3bNnCW2+9xYYNG4iNPf3hAeHh4cTExJzVPbVabY11n3nmGbKyskhLS6sok5SUxK+//kr9+vUZO3Ysv/zyC+Hh4UyePJmbbrqJwYMH4/V6efXVV5kzZw6hoZV3LgsJCSEmJoaYmBgmTZpEfHw8Cxcu5O6772b+/PmVyk6fPp2oqCg2btxIjx49zur5rhQioRQEQTgPgs3RdG1+L63r34w/4EWnNWENEi2TQvWO7J1dJZk8TlUDHNk7m4btx17QmMrKyrjtttv44IMPzjg5vO6663C73TRo0IBx48Zx3XXnvu6qoih8++23DB8+vEo8JpOJ++67j2effZbCwkLCwsK47rrr+Mc//sHtt9+Oz+fjjjvu4Nprrz3pPUym8i97Xq+32vN2ux040WIq1EyMoRQEQThPtBo9weZYwoKTRTIpnFRZycnHSp7qfG145JFH6NKlC0OGDDntOhaLhbfeeosZM2bw008/0a1bN4YOHcrcuXNP+xrbt2/HYrFUvDp06ADAsWPHKC4upnHjxtXWa9y4MaqqkpaWVnFs4sSJ7Nu3j4KCAt5+++2T3resrIxnn30WjUZDz549q5xXFIWHH36Yrl270qxZs9N+niuVaKEUBEEQhAss6BRbcZ7q/Pk2d+5clixZwubNm2ss07RpUw4fPgxA9+7d+eWXX4iIiODRRx+tKNO+fXuysrL4z3/+c9qtlA0bNqyUgBoMhkrnz2RDv2+++QZJksjPz2fPnj0Vyemf3XrrrWg0GlwuF5GRkXz66ae0aNGiSrmxY8eyY8cOVqxYcdr3v5KJhFIQBEEQLrDEhkM5uPWzaru9JUlDYsOhFzSeJUuWcODAAUJCQiodv+GGG+jevTvLli3j559/xufzASe6iqvTsWNHFi5ceNr31uv1pKZWnYEfGRlJSEgIu3fvrrbe7t27kSSpou7BgwcZN24ckyZNYunSpYwcOZLNmzdXSVDfeecd+vTpg81mIzIystpr33///fz4448sX76chIRLezzupUJ0eQuCIAjCBRYUHE/zHs9VWm4KypPJ5j2ev+ATcp588km2bdvGli1bKl5QnnxNmzYNgOTkZFJTU0lNTSU+vub4tmzZckYTemoiyzI333wzX3/9NTk5OZXOuVwuPvzwQ/r160dYWBiKojBy5Eiuvvpqbr/9diZOnEhJSQnPP/98levGxMSQmppabTKpqir3338/s2bNYsmSJdSpU+ecn+NKIVooBUEQBOEiSGgwmLCYNhzZO5uykkyCrPEkNhxa68mk3W6vSBiPCw8Pr3acYFJS0kmTqs8++wy9Xk/r1q0BmDlzJlOnTmXKlCnnJdZ///vfLF68mL59+/LGG2/QrFkzDh06xLPPPovP5+ODDz4A4N1332Xnzp3s3LkTAJvNxpQpUxg0aBA33HBDtV3f1Rk7dixff/01c+bMwWq1ViSyNpvtpK2ygkgoBeGsKAE/vrJjeEvyUBUf+uBYdKYwNGJ5GEEQzkBQcPwFn829bNmyigTwuDFjxpx1EjhhwgQOHz6MVqulUaNGfPfdd9x4443nI1TCw8NZs2YN48eP5+677yYnJ4ewsDAGDBjAl19+SVJSEvv27eOZZ55hypQplWaD9+vXj1GjRtXY9V2dSZMmAdCrV69Kx6dNm8bIkSPPyzNdriT1TEa7XgEcDgc2mw273U5wcPDFDke4BAV8bhxH13NwwbMEvE4AJFlLQuf7CavfD1lnQme0XuQoBUEQBOHCES2UgnCGvCXZ7P/p/0ANYE3ti67JUPwGG0H6IHzOInQBHz6tD4wyur8McBcEQRCEy5FIKAXhDKhKgLyds0ANENLlYX43RLL0wBb+3aAjulIZeXUAZd1RFJ+C1MiKfL2MHGtB0or5b4IgXHksFkuN53755Re6d+9+AaMRapNIKAXhDKiKD3fhQYIiG7HHmsRHu5fx35YDCCkJIH9bhprrPlF2dwne13dheLo5UpzYA1YQhCvPXyf//NnJZooLfz8ioRSEMyBp9JhjmlNmiWVK+mbMWj0xBNAV2FBzC6tW8Kv45h1Bf0d9JKOm6nlBEITLWHXrSwqXJ9EPJwhnQJJkIhpdi2yOIttlx6I1opck5F01z21TdtlRXf4LGKUgCIIgXFiihVIQzpDeEotFlYk0WinwOMEUhmpWaq5g0kJALKYgCIIgXL5EC6UgnCFZoyXaFse/GnTHryqsL8qGtkE1ltf2iEakk4IgCMLlTCSUgnAWJEmid1wTbk/twjtpqykOkZEGVN3GS65nQW4XjlTiuwhRCoIgCMKFIRY2/wuxsLlwJvJdJaQ789GqEnU0NsxlMsqmInApyE1CUGQVd4QWi9aAHGG82OEKgiAIQq0QYygF4RxYdEZmHd5IrtPBS8kDkDaUIqeYcSXKlOlc+IEI2YJk0V3sUAVBEASh1ogub0E4B0atjttTu7LNfoT7D8wg/SqJF/mGa9c/wvWrHuO5He+zP3CUgkDJxQ5VEIRLUElJJps3v8/vy59i8+b3KSnJrNX7jRw5kqFDh560jKqqDBgwAEmSmD179mldNz09HUmSKl7h4eFcc801bN68uaJMr169ePjhh096naVLl3LttdcSHh5OUFAQTZo04f/+7//IzCz/uSxbtgxJkiguLq5SNyUlhYkTJ1a8nzx5Mr169SI4OLjGOsL5IxJKQThHiZZw/t3uRh5qehVPbHqbXcUHuLvhTbzR7mH+1WAYq/O2kecuIKCeZCa4IAhXnAMH5jFn9lB2bJ9Kevqv7Ng+lTmzh3HgwLyLGtfEiRORJOms6i5atIjs7Gx+/fVXnE4nAwYMOO1E7uOPP6ZPnz7ExMTwww8/sGvXLj766CPsdjtvvfXWGcdSVlZG//79efrpp8+4rnDmRJe3IJyjIK2eDpEpLMtZT3xQFCPqDeTTfbOYtPcgAO3Dm9I5qgXHXIXEBEVc5GgFQbgUlJRksnrVeFQ1UOm4qvpZvWoCUVFtsFov/E4yW7Zs4a233mLDhg3Exsaecf3w8HBiYmKIiYnhzTffpGvXrqxdu5Z+/fqdtN7Ro0d58MEHefDBB3nnnXcqjqekpNCjR4+zal083hq6bNmyM64rnDnRQikI54XK2mPbGFN/KE9tfI9d9oMVZ9YX7OTxDe/gCnguYnyCIFxK0tJmVUkmj1NVP2lpsy5wROUterfddhsffPABMTEx53w9k8kEgNfrPWXZGTNm4PV6GTduXLXnQ0JCzjkeoXaJFkpBOA/MWhOdo1ry49HleJWqSwQ5fKUszl7LaMtQZEl8jxOEK53zFGMlnSVZFyiSEx555BG6dOnCkCFDzvlaxcXFTJgwAYvFQocOHU5Zfv/+/QQHB592q2hCQkKVY2VlZWccp3D+iIRSEM4Djayhsa0eH+/9ocYy6/J3cGudAZh1pgsYmSAIlyLLKbqzLda4CxRJublz57JkyZJKk2jORpcuXZBlmdLSUurWrct3331HdHT0KeupqnpG4zZ///13rFZrpWO9evU603CF80gklIJwnmh8QYQZbGS5jlV7PsIQihrQgFhBSBCueKmpw9i543NU1V/lnCRpSU0ddkHjWbJkCQcOHKjStXzDDTfQvXv30x6H+N1339GkSRPCw8PPqJu6QYMG2O12srOzT6uVsk6dOlWur9WKlOZiEn1vgnCeeAutjKgzuMbzNyUNICP97GZOCoJwebFa4+nc5TkkqXISJElaOnd5/oJPyHnyySfZtm0bW7ZsqXgBvPPOO0ybNu20r5OYmEi9evXOeMzjjTfeiF6v54033qj2vFjy59In0nlBOE+iozQUZNRjWEIfZh1dVHFcQuKe1FtQ8iNZvc5HcqIGs1l8lxOEK129eoOJimpDWtosnCVZWKxxpKYOq/Vk0m63VySMx4WHh9OsWbMqZZOSkqhTp855u/exY8eq3Ds2NpbExETeeecd7r//fhwOB7fffjspKSkcPXqUzz//HIvFcsZLB+Xk5JCTk0NaWhoA27dvx2q1kpSURFhY2Pl6JOEPIqEUhPPEYpGIs9nokn09A9v0ZZt9N1pZQ6uQxliwMWemhKKoKGI5SkEQ/mC1xtO69f0X9J7Lli2jdevWlY6NGTOGKVOm1Pq9v/76a77++utKxyZMmMCzzz7LfffdR4MGDXjzzTcZNmwYLpeLlJQUBg0axKOPPnrG9/roo4946aWXKt736NEDgGnTpjFy5Mhzeg6hqstqL+8XX3yx0n8egIYNG7Jnz57TvobYy1s4F4GASkGhQla2ggSE2CQKi1VWrvbi90NYqMSNw4wEBYkWSkEQBOHycdm1UDZt2pRFi050N4pBusKFpNFIGA0SO3f5UFWwO1R8f1pFqFsXvUgmBUEQhMvOZfeXTavVVqzSHxMTQ0TEyXcm8Xg8OByOSi9BOBdWq0T/vkaAimTSoIere+mJiz0/v3JKqQ+lwI1S6EH1iT50QRBq1z333IPFYqn2dc8991zs8IRLwGXX5f2f//wHm82G0Wikc+fOvPrqqyQlJZ20zl+7yQHR5S2cs7IyBZe7vBvcaJQwB0loNOc2y1v1BQjkeyjJt6O1GgnS6ZA0MqpJi8amP0+RC4IgVJaXl1djg0twcDBRUVEXOCLhUnNZJZS//PILTqeThg0bkp2dzUsvvURmZiY7duyosgDqcR6PB4/nxJZ4DoeDxMREkVAKl6RseyGLs3aRGhZDqNHMrqIsTBodjYJjiVBNmAxaNCbjxQ5TEARBuMJcVgnlXxUXF5OcnMzbb7/NmDFjTquOmJQjXKoynUXcuXIar7e/mbmHNzM7Y1PFOa0k82TLgfQMqUuQVkVvDr2IkQqCIAhXmstuDOWfhYSE0KBBg4o1qATh78ob8PNl2irahidzqORYpWQSwK8qvLxlHjmqC8XtJuBzX6RIBUEQhCvRZZ1QOp1ODhw4cNqbzQvCparYW8b8zO0MS2nHNwfX1FhuzuFNSAYtPlfRBYxOEARBuNJdVgnlY489xm+//UZ6ejqrVq1i2LBhaDQabr311osdmiCcMxUwarTku52VjstIdIlK5aY67Yk0WrHn7gRVzPwWBEEQLpzLapHGo0ePcuutt1JQUEBkZCTdunVjzZo1REZGXuzQBOGc2PRBXBPfjHy3k8YhsazOOwBAy7BExjTowcq8/aQ58vAG/BTGNcSAhJiaIwiCIFwol/WknLMhJuUIl6rM0iJe2TKXuxr15u4V00kwh3J/kz48t3EmHsVfUU4CXmkzjJ5xTdFrNBcvYEEQ/rZSUlJ4+OGHefjhhwGQJIlZs2YxdOjQixqXcOm6rLq8BeFyFm8O5dnWQ/ArAd7q+A9GNejOf3ctqpRMQnnX+PitP1LgKbk4gQqCcNqKnZn8vu19flz1FL9ve59iZ2at3/PIkSOMHj2auLg49Ho9ycnJPPTQQxQUFNRYJzs7mwEDBtR6bMeNHDkSSZKqXTR97NixSJJUaT/u4+WPv8LDw+nfvz/btm2rVPfPZWw2G127dmXJkiW1/ThXBJFQCsLfSFxQCK3Dk2lijaJ+cBRHSgurLecO+DjszMeRW4RvaTaBPXaUIk+1ZQVBuDh2HJrHpz8NZe2uqezJ+JW1u6Yy9adh7Dg0r9buefDgQdq1a8f+/fv55ptvSEtL46OPPmLx4sV07tyZwsLqP1NiYmIwGAy1Fld1EhMT+fbbb3G5XBXH3G43X3/9dbUblvTv35/s7Gyys7NZvHgxWq2WQYMGVSk3bdo0srOzWblyJREREQwaNIiDBw/W6rNcCURCKQh/MxpZJjTIBqcYrVLkKWGdfy/2OBXvxF14vzqApzCb0rzdOHN2UFp0mMKSPEpdxRcmcEEQKhQ7M/l13XhUNVDpuKL6WbBuQq21VI4dOxa9Xs+CBQvo2bMnSUlJDBgwgEWLFpGZmckzzzxTbT1Jkpg9e3bF+1WrVtGqVSuMRiPt2rVj9uzZSJLEli1bKsr89ttvdOjQAYPBQGxsLE8++SR+v7/qxWvQpk0bEhMTmTlzZsWxmTNnkpSUROvWrauUNxgMFdsut2rViieffJIjR45w7NixSuVCQkKIiYmhWbNmTJo0CZfLxcKFC087LqF6IqEUhL8hSZIINVqJMFqqPa+VZCw6LU9sepevA8soe7ku7quK2DV7JDu/G8GuGXew9/tRKFmb8Lnt5DnzcflEC6YgXCjbD86qkkwep6h+th+cdd7vWVhYyK+//sp9992HyWSqdC4mJobhw4fz3XffcaqpFQ6Hg8GDB9O8eXM2bdrEhAkTeOKJJyqVyczM5Nprr6V9+/Zs3bqVSZMm8emnn/Lyyy+fUcyjR49m2rRpFe+nTp3KqFGjTlnP6XTy5ZdfkpqaSnh4eI3ljv8cvF7vGcUlVCUSSkE4j1SPD9XtuyD3ijRaeablYKrbHfz2+p35+egyAL45+AtaHOxf+ii+0vyKMn63nYMLnkEtSkfK3YHTVYxbLIguCBeE/RQtkHZn1nm/5/79+1FVlcaNG1d7vnHjxhQVFVVp0furr7/+GkmS+OSTT2jSpAkDBgzg8ccfr1Tmww8/JDExkffff59GjRoxdOhQXnrpJd566y0U5fSXNRsxYgQrVqzg8OHDHD58mJUrVzJixIhqy/74449YLBYsFgtWq5W5c+fy3XffIcvVpzplZWU8++yzaDQaevbsedoxCdW7rJYNEoQLSVVVVEcRlDlBFwSKDlVSQVaQSlQwmJGDa2/xHkmSaBuRwqfdR/PZ/pXstecQG2RjaHJLDpaksSB7FQDdolpSsHMmqlJ9V1PezpkYrHHogsJZWHCU3vFNsOhN1ZYVBOH8sFniT3E+rtbufa6Lu+zdu5cWLVpgNJ74fOvQoUOlMrt376Zz585I0omvvF27dsXpdHL06NFqx0BWJzIykoEDBzJ9+nRUVWXgwIFERERUW7Z3795MmjQJgKKiIj788EMGDBjAunXrSE5Orih36623otFocLlcREZG8umnn9KiRYvTfn6heqKFUhDOgup1o+zZjH/tUvAF4d9fCAEH6p5VKL/NQtm/EZy5KMXFtRqHSavHptcyskEHbqnXiKZhJt7bM4VpB050lyUbw3Hn76vxGu7CdPTWaNz75lM/JIbMGib6CIJw/jSvOwxZqr5NR5a0NK877LzfMzU1FUmS2L17d7Xnd+/eTWho6CW3dvPo0aOZPn06n332GaNHj66xnNlsJjU1ldTUVNq3b8+UKVMoLS3lk08+qVTunXfeYcuWLeTk5JCTk8Mdd9xR249wRRAJpSCcBTUvi8C2tWhSu+JbuA9NlB/vB8/in/c5gTUL8c+einfyy1Cci+p2nfqC58CqDUKWYN6RJXx+YA7H3JW3XczzOTGE1q2xvsGWgM95DH/xYXx+N6ok4xTjKQWhVoVY4rmmw3NVkkpZ0tKvw/OEnKIF82yEh4fTt29fPvzww0ozpwFycnL46quvuOWWWyq1KlanYcOGbN++HY/nxOfE+vXrK5Vp3Lgxq1evrtQaunLlSqxWKwkJCWcUd//+/fF6vfh8Pvr163fa9SRJQpblKs8aExNDamrqJZc4/92JhFIQzpDqceFfPBNNl8H45+1G2zcR31fvgvdPSZjBCO4yfDOnoJbYazWeUKMNg6TjhVb3YNZW7qqWkWgX0Rx9owEgVf/rHtV0GAX75mOMbsbMw9vIddlxirGUglDrmtUZzOiBs+jYZDSNkvrTscloRg+cRdM6VZe6OV/ef/99PB4P/fr1Y/ny5Rw5coT58+fTt29f4uPjeeWVV055jdtuuw1FUbjrrrvYvXs3v/76K2+++SZARTJ63333ceTIER544AH27NnDnDlzeOGFF3j00UdrHNNYE41Gw+7du9m1axeak2zW4PF4Klodd+/ezQMPPIDT6WTw4MFndD/h7IgxlIJwpjxuVCTwKSiZxUhKGTjtIMtoug1ATm2OWlKEZAgCnwfF6wZVRT7Ft/5zEaOP42iWj6ldxrMwexX7HBnEmiLoEtWS2RlLMES3pe21/+HwohcJ/LHguawzEd/hbhxH16P43ZhT+7BmwxzmZ+3gs553EhYwo9eIjwhBqE0hlni6t7j/gt2vfv36bNiwgRdeeIGbb76ZwsJCYmJiGDp0KC+88AJhYWGnvEZwcDDz5s3j3nvvpVWrVjRv3pznn3+e2267rWJcZXx8PD///DOPP/44LVu2JCwsjDFjxvDss8+eVdyns3Pd/PnziY2NBcBqtdKoUSNmzJhBr169zuqewpkRWy/+hdh6UTgVtcyJf+lc5AadUPYUIzfQ4Jv6Grqb7iGwbyvKllUnCgeHovvnI9gjUwgL0tdaTIcO+5kzz0NcvErrbmVsdW5nt+MA2aX5/LPeYBrYklAVlRJ7JqEBF4rHAcCxnbPw2I9i7T4OuzmWe1Z/TkBVuT6lLfc07E2o0VxrMQuCcPn46quvGDVqFHa7vcqSRMKVQTQ/CMIZkoIsyPWboQacyI1DkPQKcv0WKLlHKyeTAI4ifJ++RtCDr0FQVK3E43KprF5bvlRRVqZE7vdm6qR2oEd4K7yqBkN2EOHRegJKgIXZJSw6uoPRSc2JkFTUlv8k0+tmQ1Ee0W4PgT++X+6z5+BXT39pD0EQriyff/45devWJT4+nq1bt/LEE09w8803i2TyCiYSSkE4Gzo9kiwjaTU4HE6Crr2NwMfjqy/rLkPOOggRtZNQ+gMqxcUnkr9AANL2ykB511O9OgqtWqhoZA09YupjlPW8vG8p+W4nJo2OgYkt6RSVygubTswMTzKHY9Vd2G3WBEH4+8jJyeH5558nJyeH2NhYbrrpptMafwmQkZFBkyZNajy/a9eu015WSLh0iIRSEM6CZI3Eo8IBv5b3MxWeMErEukprLp93/hcpPk6rgdAQmdy86lsUo6NlZLl8/KbJb0Xa0Yj3uyXjxs3R0kJ+y97L1H3LiTRaySorRgIGJ7XCFfBi1NZeN70gCH9f48aNY9y4cWdVNy4urtIWjdWdF/5+REIpCGdAsTtx5RViR4OqQozbxfMNbOR5PcQGh4KjqPp6cUlkOg4QYozArLed15hMJpkunXTMmlt1qR+NBhqknvg1d5dpSD/sI7mJzLKyHVwVncwtcUkUFpei10VhtvbEoeoo8DiJ94eCaKQUBOE802q1pKamXuwwhPNMJJSCcJrUkjKySzxMyQGtzkffJAWTzUeYvpQkyUrZVTcSNPuTqhVt4bgi4tmUOYdYa10aR3bEbDi/SWV0lMxVvfT8vtKL74+dHy0WiWv7GbBaT8wu9/nKx0geTdPTr3UKO3d/wOHsFRXnZVnLtR1fITSsLbL4eBAEQRBOk/iLIQinKden8MCmQu5vaSC3+Hs+W/89fsWLhEyb+D5c1/QBZNdwjEu/r1iTUkpM5djgu8j0a9mdt5a9xzYA0CCiLcHG8PMSl8+noqrQqIGGlGQTLpeKLIHJJGGxVF7vLTi4/L3XBfZjqyolkwCK4uenNU8xss836LSx5yU+QRAE4fInEkpBOE0bcsvoFKMjp+hbfjv0bcVxFYWNmQtweovp1ug5glNaEa/xUuCX2ViqYfoWN69303CgcCsA+ws20TruKm5r9TTBhlOv+VYTt1uhsEhlwyYfDodKbKxM65Y6IsJlNJrq17wMMkGLZlpi4wpZuvPLP52RSInuSIylHk5fEYeOLKV5RB8cRiPBBvExIQiCIJyc+EshCKfB7ffz2zEPoxrDB6t+qLbM3mPrGNrExbeZQZT5DCw5Ur6A+OimNiS1oFLZzVlL6Jv6z9NOKFW3F9VZCqUu0OvwW6zsPqhh714f8ZF+zHqZtDSFXbv83DDMSFxs9btJGAwynTvq8Hp8lG0qH+8ZHdKYwU0eR79jG5rdB1Ft4Sid2qPJy8RjsEHk+WlJFQRBEC5fIqEUhNPg8NgJM8hopBL8iq/GcoWuHIbVa8sTvx+hcZiRW+priTYdo8RddZb36owfqRfesspx1elADfggEEBVVSRZg3/1bpTFa+CPdSI9D99FcqhCowYH0exejerx0q5Df9JdsSxcLHHj9UbMQdVvb+b0uvD6tcSENcVqjqd/0mjUyf/+YwegcvLWtdD/FkzxPgpcPsJNujP/oQmCIAhXDJFQCsIpFLtdePylDEgOQq8JQkJCpfoNpiz6UHYXuHixcxyFzt/AX0R6YQmFruwqZaW/bMWolJVCSSFqsRM0JiStFowaFF8pmqRg1JRY1ENZyC0bYDGUou5Yi1p0DKleE9ToBIyrFlBfa8ZfZyhutxFzUOX7BRSVnFIvxT4JjRxK77ZPo/UF4H/TwVN1727/ghnom3ag1B8AREIpCIIg1OzMdmgXhCuMLxBgnyOfPfZ8Dhb8iIqVJtHdqi0bbUlGpw3nva15aGUXK9OnE2VNpn54KzYeXVilfKfEgRX/VlUVpSgfNd+Hf2Uxgc15+DdmE1iRhayxoVpMaK9ph5QSi6ZdMr53n8T/6/8IrFtKYMkcnHkHsA8YhPOaq0htXIZWG+BYmY9jZT48fh+5ziwOFB3GFVD5Jd3O3YsO41CM+MvsqEcPVv/wikIgMx2DJHZnFYTakl+ayeyd7zNl/VPM3vk++aWZtXq/kSNHIkkS99xzT5VzY8eORZIkRo4cWXEsJyeHhx56iNTUVIxGI9HR0XTt2pVJkyZRVlZWUS4lJQVJkqq8XnvttVPGlJ6eXqmOXq8nNTWVl19+mT/vDj1z5kzatWtHSEgIZrOZVq1a8cUXX1S5XlpaGqNHjyYpKQmDwUB8fDxXX301X331FX6/v0r5u+++G41Gw4wZMyqOVfcsf369+OKLbN26lVtvvZXExERMJhONGzfm3XffPeXzXq5EC6UgnESuy8kjq3+iVXgMvUM97M1bwtCm4yj1FJNevL2iXJQ5kVtavcn2AgNXJViQlWPc0eYlgnTBTN3wND6l8hqRbeP6EmVJrHivFh1DKpNQnR40DX0oOxeDoiA16oRyLBgpLpo8k5+wW/rg++Bp8PtAb0BJrk/hdYMpkdyk5y7FF/BQL7wlNo2Pt9ZKaGSV2xsWMXXDwzzQ5Vt+PWxnZloxCRYdh4q201ITetLnl1UFm0ksbi4ItWH14Xl8vnk8ihqoOPbr/s+5vfVzdE4eXGv3TUxM5Ntvv+Wdd96p2CrR7Xbz9ddfV9qh5uDBg3Tt2pWQkBD+/e9/07x5cwwGA9u3b2fy5MnEx8dz3XXXVZQfP348d955Z6V7Wa3W045r0aJFNG3aFI/Hw4oVK/jXv/5FbGwsY8aMASAsLIxnnnmGRo0aodfr+fHHHxk1ahRRUVH069cPgHXr1tGnTx+aNm3KBx98QKNGjQDYsGEDH3zwAc2aNaNlyxNDjcrKyvj2228ZN24cU6dO5aabbgIgO/tEr9J3333H888/z969eyuOWSwW/ve//xEVFcWXX35JYmIiq1at4q677kKj0XD//fef9nNfLkRCKQgnsTo3A5+isP5YFkOTurA360uc3mKGtXiFMq+dIlcOFkM4Ok04XiUMq97DmGZWJNWM1WjGotdzZ4fXWHfkVzZlLcKoDaJP6gjqhDbD+ucJOT4F1esnsPF/qOm7kaITkGKTUA9uIuBYiu6G+3l5n4/nouwYO/bH0aQzOT6JxOgAW7MXMm/3R5W64dvEXc2jbR4ky+njk3X34w24kWUbP+w/AoBFp6HUe4wjmjIiohNQc49WfXhJgoR6SJrqJ/gIgnD28kszqySTAIrq5/PNE6gf8f/s3Xd8FGX+wPHPzGzfTTa9Agkh9N4RRJqIChZOxYKniGev2D1PRc96lrNhuZ80e1dQEaWIivQSeodQ0vsmu9k2M78/VgJLEmpCfd6v175e7DzPzHwnpHz3qd2Is6c2yr27devGtm3b+Oabbxg9ejQQav1r1qwZzZs3r6l3++23YzAYWLZsGXa7veZ4RkYGl1xySVjrIYSSx6SkpKOOKzY2tub8tLQ0Jk+ezIoVK2oSyoEDB4bVv+eee5g6dSrz589n2LBh6LrOmDFjaNWqFX/++SeyvK8TtmXLllx99dW1Yv7yyy9p164djzzyCCkpKezevZumTZuGPYfT6USSpFrPNnbs2LD3GRkZLFy4kG+++eaMTChFl7cgHER2VXnNv59YsQir8xKax/eksGoDVpOTzNjeRFsSSXVEk2jz0y1ewWq0kRwZjcMUatmLtaUwrNV13Nt3Arf3+S+dkwfUsQalEVw56OWFGK+7D6XHQAgGkJyxGM+7HL0sj+taRiMnpvJ2VB+uXuxmbrlGua+A6RveqTWmc0XuHLaVLMKmuPCrofGRPk2jOvjXwuZVflKdnflh96e4h48MbalzAP2cEXjM9lrHBUE4dvOzv62VTO6l6UHmZ3/bqPcfO3YskydPrnk/adIkbrjhhpr3JSUl/PLLL9xxxx1hyeT+DhwH3pCWLVvG8uXL6d27d53luq4zZ84cNm3axDnnnANAVlYWGzZs4IEHHghLJg8W88SJE7n22mtxOp1ccMEFTJky5ZjirqioICbm6JeDO5WJhFIQDqJr7L7FvVVd472Na7hr0SJe3pDHq2uXUOnbQZxVItHhICUimmirk2hL7QkssqRgN0dhNTrqvpFJRtu0GONlNxOYNoXgjx+hrV2KungOgSkvQWkunR1BfirU+GG3Bx3om2Rkye6f6o39t+1fYDfti8UfKMb4157eVQGNEl8cFoODTwo/purmcWhdeiPFJCClt0a/fhxbOgzBaLPVd3lBEI5BsefgYyWLPbVXhmhI1157LfPnz2fnzp3s3LmTP//8k2uvvbamfOvWrei6TuvWrcPOi4uLw+Fw4HA4ePjhh8PKHn744Zqyva8//vjjsGPq27cvDocDk8lEz549GTVqFNddd11YnYqKipo6w4cP580332To0KEAbN68GSAs5sLCwrB43n777ZqyLVu2sGjRIq688sqar8nkyZNrtWIergULFvD5559z8803H9X5pzrR5S0IB9EhJpFYs5USX3XNMVXXyK+u4sHO/WkXn4YsNcDnMrMJKaMt6sJfoKK0VnHwp08xtO3OZ5vdNcf8Grh8tevuVekrxSBbat4v2/0xF6aPZdr2CgDeWOXj2bOeY23uBzy77gF6thxE6+4DiYtsw4pKJ31inThMYna3IDSGONvBu7PjbCmNev/4+HiGDx/OlClT0HWd4cOHExcXd8jzlixZgqZpjB49Gp8vfGz4gw8+GDahByA19fC77T///HPatm1LIBBg7dq13HXXXURHR4dN7ImIiCArK4uqqirmzJnDfffdR0ZGRq3u8L1iY2PJysoCQl3mfr+/pmzSpEkMGzas5rkvvPBCbrzxRubOncuQIUMOO26AtWvXcskll/Dkk09y3nnnHdG5pwuRUArCQSTZIni3/6U8vWIua0oLAIgyWbinY1+6xKY0TDIJyDY7ZLTF/+NHdVfQddTt64i1ZlLhD3WTzdwV5PzkPqwtmF/nKZmxXakKmImzpVLsyWHpnumM6XEBpd54/sh14w5oPDi/mssyx/DAOWPR9AB+1YSuRHG2E+Jt1gZ5NkEQajs7fSQ/b/kATa8961iWDJydPrLRYxg7dmzNWL8JEyaElWVmZiJJUthEFAiNEwRqJvPsLy4ujszMzKOOp2nTpjXnt23blm3btvH4448zfvx4LJbQh2NZlmvqdOnShQ0bNvD8888zcOBAWrZsCcCmTZvo2rUrAIqi1NQ3GPalPKqqMnXqVPLz82sdnzRp0hEllOvXr2fIkCHcfPPN/Otf/zrq5z/ViYRSEA4hLSKaV88aTrmvGr+mEmm0EGe1oTRQMlnDZK5ZuLxOPi/3dUuk2Btk3u5K/sip5NYO/YgwT6LygJZKWTJwbst/8M+FPh7t8Qa/bX2ZDUUL+WD57QxrfS9j259PRcCA02Qg1mIgziZaIgXheIqzp3Jd18f5YOW/w5JKWTJwXbcnGm1Czv7OP/98/H4/kiTVzJLeKzY2lqFDh/LWW29x11131TuOsjEpikIwGMTv99cklAfSNK2mpbRr1660adOGl19+mVGjRtU7jhJgxowZVFZWsnLlSpT9xpCvXbuWG264gfLycqKiog4Z47p16xg8eDDXX389zz777JE94GlGJJSCcBicJgtOU92/0BqKZItASk1Hz8mus7yiSVvu/303sgTD0pw8168JTy0u5PHe7/HzptdZV/AnOjpNnW24ouN9rC+LoVW0H02K4u/dniWouQiqfixGB9HWSGRJzN4WhBPprLSLaBnXjfnZ31LsySXOlsLZ6SOPSzIJoYRtw4YNNf8+0Ntvv02/fv3o0aMH48ePp1OnTsiyzNKlS9m4cSPdu3cPq19ZWUl+fn7YMZvNRmRk5GHFU1JSQn5+PsFgkDVr1vD6668zaNCgmvOff/55evToQYsWLfD5fMyYMYMPP/yQd955BwhNuJk8eTJDhw6lX79+PProozVd6L///jtFRUU1zzlx4kSGDx8etoQQQLt27Rg3bhwff/wxd9xxx0HjXbt2LYMHD2bYsGHcd999Nc+uKArx8fGH9cynE5FQCsJJQnJEYrz0RvzvjActfPZnsF1PFrjN+NTQGMrvtpWzuczLpZnRvLGqkoe7P87gFlsJan4KqnYSZ29Cy9h4hmeAIu+d1Rh1XJ9HEIRDi7Oncmn7E7fEzMGSvRYtWrBy5Uqee+45Hn30Ufbs2YPZbKZdu3Y88MAD3H777WH1n3jiCZ544omwY7fccgvvvvvuYcVy7rnnAqGELDk5mQsvvDCs1c/tdnP77bezZ88erFYrbdq04aOPPqqZVAPQp08fli9fznPPPccdd9xBfn4+drudzp0789///pexY8dSUFDAjz/+yCeffFIrBlmWGTlyJBMnTjxkQvnVV19RVFTERx99xEcf7RuulJaWRnZ29mE98+lE0o92OtNpyuVy4XQ6qaioOOxPVYLQUPSAH7Uwl+DMzyB7E5I9kuq+F7IxuQMPrnChHvDT+tagJsR4FAoCi5i07gHibKnc3OtFmka1Fi2QgiAIwnEjEsoDiIRSOBm4K6twVbpRFJlHV1WxobT2XtsAN3eIob/LiaVNMUHZQ5Q5Gqf1zOtqEQRBEE4ssQ6lIJyE7BEOkpIT8Foj2Vruq7detMFIUlsjqTFNSItqJZJJQRBOOrfeemut9Sn3vuraU1w4NYkWygOIFkrhZOILary6PJ/vd1TUKlMk+GRYBqkRJmSl8XasEARBOBaFhYW4XK46yyIjI0lISDjOEQmNQUzKEYSTmNkgc0OHONaXetlWsa+lUpHgmb6pxDuMIpkUBOGklpCQIJLGM4BooTyAaKEUTkbF1QGyXX6WF7iJtxroleQg3mrAbBCjVgRBEIQTT7RQCsIpIM5qJM5qpEfi8V9cWBAEQRAORTRvCIIgCIIgCMdEJJSCIAiCIAjCMREJpSAIgiAIgnBMREIpCIIgCIIgHBORUAqCIAjCCZLjKWTChs/55/I3mLDhc3I8hY1+z/z8fO666y4yMjIwm800bdqUiy66iDlz5tTUWblyJVdeeSXJycmYzWbS0tIYMWIE33//PXsXh8nOzkaSpDpfixYtOmQcU6ZMISoq6rBibtOmDWazmfz8/FplAwcORJIkXnjhhVplw4cPR5Ikxo8fX6u+JElYLBbatWvH22+/XVM+b968Op+prnsL+4iEUhAEQRBOgO93/8bIueOYtPU7fs5dyKSt3zFy7n18v/u3RrtndnY23bt3Z+7cubz00kusWbOGmTNnMmjQIO644w4Apk2bRp8+faiqqmLq1Kls2LCBmTNnMnLkSP71r39RURG+0cLs2bPJy8sLe3Xv3r3BYp4/fz7V1dVcfvnlTJ06tc46TZs2ZcqUKWHHcnJymDNnDsnJybXq33TTTeTl5bF+/XpGjRrFHXfcwaeffhpWZ9OmTWHPJNbSPLgjWjZoxowZfPPNN8TExDB27FjatGlTU1ZWVsZll13G3LlzGzxIQRAEQTid5HgK+feq/6HqWthxVVf596r/o1tsW1JtDZ/A3H777UiSxJIlS7Db9y1D1r59e8aOHYvb7ebGG29k+PDhfPPNN2Hntm3blhtvvJEDl6+OjY0lKSmpwWPda+LEiVxzzTUMGDCAe+65h4cffrhWnREjRvDFF1/w559/0q9fPwCmTp3Keeedx65du2rVt9lsNTGPHz+eTz75hOnTp3P11VfX1ElISDjsFlThCFooP/nkEy6++GLy8/NZuHAhXbt25eOPP64p9/v9/PZb432qEgRBEITTxXc7f62VTO6l6irf7fy1we9ZWlrKzJkzueOOO8KSyb2ioqL45ZdfKCkp4aGHHqr3OpJ0/Hbnqqys5Msvv+Taa69l6NChVFRU8Mcff9SqZzKZGD16NJMnT645NmXKFMaOHXtY97Farfj9/rBjXbp0ITk5maFDh/Lnn38e24OcAQ47oXzppZd49dVX+eGHH/jjjz+YOnUqt9xyCxMnTmzM+ARBEAThtJPjKTh4eXXDj6XcunUruq6H9S4eaPPmzQC0bt265tjSpUtxOBw1rx9++CHsnL59+4aVOxyOBov5s88+o2XLlrRv3x5FUbjqqqvqzTvGjh3LF198gdvt5vfff6eiooIRI0Yc9PqqqvLRRx+xevVqBg8eDEBycjLvvvsuX3/9NV9//TVNmzZl4MCBrFixosGe63R02F3eW7Zs4aKLLqp5P2rUKOLj47n44osJBAKMHDmyUQIUBEEQhNNNqi3x4OXWhu/uPtqdljt16kRWVhYALVu2JBgMhpV//vnntG3b9ljDq9OkSZO49tpra95fe+21DBgwgDfffJOIiIiwup07d6Zly5Z89dVX/Prrr/z973/HYKg7zXn77bd5//338fv9KIrCuHHjuO2224BQMr1/Qt23b1+2bdvGf//7Xz788MNGeMrTw2EnlJGRkRQUFNC8efOaY4MGDeKHH35gxIgR7Nmzp1ECFARBEITTzaVpg5i67XtUXa1VpkgKl6YNavB7tmzZEkmS2Lhx40HrQGhCSp8+fQAwm81kZmbWe07Tpk0PWn601q9fz6JFi1iyZEnYuElVVfnss8+46aabap0zduxYJkyYwPr161myZEm91x49ejSPPfYYVquV5ORkZPngHba9evVi/vz5R/8wZ4DD7vLu1asXP/30U63jAwYM4Pvvv+e1115ryLgEQRAE4bSVakvg8c43oUhK2HFFUnii882NMiEnJiaGYcOGMWHCBNxud63y8vJyzjvvPGJiYnjxxRcb/P5HauLEiZxzzjmsWrWKrKysmtd9991Xb7f3Nddcw5o1a+jQoQPt2rWr99pOp5PMzExSU1MPmUwCZGVl1TlbXNjnsFsox40bx4IFC+osGzhwIN9//z0ffPBBgwUmCIIgCKezi5oOoFtsW77b+Ss51YWkWhO4NG1QoySTe02YMIF+/frRq1cvnn76aTp16kQwGGTWrFm88847bNiwgffff58rr7yS4cOHc/fdd9OyZUuqqqqYOXMmAIoSngSXlJTUWqMxKioKi8VyyHhUVa3pTt9rb4vohx9+yNNPP02HDh3Cyv/xj3/w6quvsm7dOtq3bx9WFh0dTV5eHkaj8XC/JLW89tprNG/enPbt2+P1enn//feZO3cuv/zyy1Ff80xw2AnlgAEDGDBgQL3lgwYNYtCghm+iFwRBEITTVaotgTvaXnnc7peRkcGKFSt49tlnuf/++8nLyyM+Pp7u3bvzzjvvADBy5EgWLFjAiy++yHXXXUdpaSlOp5MePXrw2Wef1Zrocu6559a6z6effspVV111yHiqqqro2rVr2LEWLVrw4osvUlJSUuf8jLZt29K2bVsmTpzIq6++Wqv8WJf68fv93H///eTk5GCz2ejUqROzZ88WOc4hSPrRjtI9TblcLpxOJxUVFURGRp7ocARBEARBEE56YqccQRAEQRAE4ZiIhFIQBEEQhAbXvn37WutT7n3tvzGKcHo4oq0XBUEQBEEQDseMGTMIBAJ1liUmHnwdTuHUc0QJZXZ2NrNmzcLv9zNgwIBaM68EQRAEQRAA0tLSTnQIwnF02Anlr7/+yogRI6iurg6daDDUWsFeEARBEARBOPMc9hjKxx9/nKFDh5KTk0NJSQk33XTTQTePFwRBEARBEM4Mh71sUFRUFAsWLKhZed7j8dRsxxgbG9uoQR5PYtkgQRAEQRCEI3PYLZQul4u4uLia9zabDavVSkVFRaMEJgiCIAiCIJwajmhSzs8//4zT6ax5r2kac+bMYe3atTXHLr744oaLThAEQRAEQTjpHXaX9+Fsni5JEqqqHnNQJ5Lo8hYEQRAEQTgyh93lrWnaIV+nejIpCIIgCKe7/Px87rrrLjIyMjCbzTRt2pSLLrqIOXPm1NRZuXIlV155JcnJyZjNZtLS0hgxYgTff/89e9uhsrOzkSSpzteiRYsOGceUKVOQJInzzz8/7Hh5eTmSJDFv3ryaY/tf226307JlS8aMGcPy5cvDzp03bx6SJNG+fftaOUlUVBRTpkypeZ+enl4r7iZNmhzul1E4QIPtlKNpGj/88ENDXU4QBEEQTns57jLeXj+Hx5Z9zdvr55DjLmvU+2VnZ9O9e3fmzp3LSy+9xJo1a5g5cyaDBg3ijjvuAGDatGn06dOHqqoqpk6dyoYNG5g5cyYjR47kX//6V625E7NnzyYvLy/s1b1798OKx2AwMHv2bH799ddD1p08eTJ5eXmsW7eOCRMmUFVVRe/evfnggw9q1d2+fXudxw/09NNPh8W9cuXKw4pbqO2Yd8rZunUrkyZNYsqUKRQVFdW7Kr4gCIIgCPv8sCuLZ7Kmo+438uyDrQv4V5eLGNGsS6Pc8/bbb0eSJJYsWYLdbq853r59e8aOHYvb7ebGG29k+PDhfPPNN2Hntm3blhtvvJEDR8rFxsaSlJR0VPHY7XZGjRrFI488wuLFiw9aNyoqquY+6enpnHfeeVx//fXceeedXHTRRURHR9fUveuuu3jyySe55pprMJvN9V4zIiLiqGMXwh1VC2V1dTUffPAB55xzDq1bt2bBggU88cQT7Nmzp6HjEwRBEITTTo67rFYyCaDqGs9kfd8oLZWlpaXMnDmTO+64IyyZ3CsqKopffvmFkpKSg64zLUlSg8Y1fvx41qxZw1dffXXE544bN47KykpmzZoVdvzee+8lGAzy5ptvNlSYwiEcUUK5dOlSbrnlFpKSknjttde45JJLkCSJt99+m1tvvVXszSkIgiAIh2HazhW1ksm9VF1j2s4VDX7PrVu3ous6bdq0qbfO5s2bAWjdunXNsaVLl+JwOGpeBw5v69u3b1i5w+E4orhSUlK45557eOyxxwgGg0d07t5nyc7ODjtus9l48sknef755w+6vOHDDz8cFvcbb7xxRPcX9jnshLJTp05cccUVxMbGsmDBAlasWMH999/f4J9UGsKECRNIT0/HYrHQu3dvlixZcqJDEgRBEIQaOZ7yg5bnHqL8aBzmoi61dOrUiaysLLKysnC73bWSvs8//7ymfO/rSD388MMUFRUxadKkIzpv7zPVlYvceOONxMbG8uKLL9Z7/oMPPhgW93XXXXdkgQs1Djuh3LRpE+eccw6DBg2q2S3nZPT5559z33338eSTT7JixQo6d+7MsGHDKCwsPNGhCYIgCAIAqbaog5anHKL8aLRs2RJJkti4ceNB60Dob/5eZrOZzMxMMjMz6zynadOmNeUHq3cwUVFRPProozz11FN4PJ7DPm/Dhg0ANG/evFaZwWDg2Wef5fXXXyc3N7fO8+Pi4sLijoqKOuLYhZDDTii3b99O69atue2222jSpAkPPPAAK1euPOlaKF999VVuuukmbrjhBtq1a8e7776LzWY74k89giAIgtBYLknrhiLV/SdYkWQuSevW4PeMiYlh2LBhTJgwAbfbXau8vLyc8847j5iYmIO26jWWu+66C1mWef311w/7nNdee43IyEjOPffcOsuvuOIK2rdvz1NPPdVQYQr1OOyEMjU1lccee4ytW7fy4Ycfkp+fT79+/QgGg0yZMqVm3MWJ5Pf7Wb58edg3lizLnHvuuSxcuLDOc3w+Hy6XK+wlCIIgCI0p1R7Nv7pcVCupVCSZx7tcTKo9up4zj82ECRNQVZVevXrx9ddfs2XLFjZs2MAbb7zBWWedhcPh4P333+fHH39k+PDh/Pzzz2zfvp3Vq1fzn//8JxSjooRds6SkhPz8/LCX1+s94tgsFgtPPfVUveMYy8vLyc/PZ+fOncyaNYvLL7+cTz75hHfeeeegLYsvvPACkyZNqjOJFhrOUc3yHjx4MB999BF5eXm89dZbzJ07lzZt2tCpU6eGju+IFBcXo6pqrclBiYmJ5Ofn13nO888/j9PprHk1bdr0eIQqCIIgnOFGNOvC10Pu5IaWZzMstQM3tDybr4fcyfBmnRvtnhkZGaxYsYJBgwZx//3306FDB4YOHcqcOXN45513ABg5ciQLFizAZrNx3XXX0bp1awYPHszcuXP57LPPGDFiRNg1zz33XJKTk8Ne33333VHFd/3115ORkVFn2Q033EBycjJt2rThtttuw+FwsGTJEq655pqDXnPw4MEMHjz4iCf8CEfmsLdePJSsrCwmTZp0QmdI5ebmkpqayoIFCzjrrLNqjj/00EP89ttvda5x5fP58Pl8Ne9dLhdNmzYVWy8KgiAIgiAcpmNe2HyvLl26nPDp9nFxcSiKQkFBQdjxgoKCehcuNZvNB130VBAEQRAEQTi4w04oBw8efMg6kiSF7QV6vJlMJrp3786cOXO49NJLgdCWkHPmzOHOO+88YXEJgiAIwpmmffv27Ny5s86y9957j9GjRx/niITGdNgJ5bx580hLS2P48OEYjcbGjOmY3HfffVx//fX06NGDXr168dprr+F2u7nhhhtOdGiCIAiCcMaYMWNGvdsxi41QTj+HnVC++OKLTJ48mS+//JLRo0czduxYOnTo0JixHZUrr7ySoqIinnjiCfLz8+nSpQszZ84U37yCIAiCcBylpaWd6BCE4+iIJ+UsXLiQSZMm8cUXX9C6dWvGjh3LNddcc9pMYHG5XDidTjEpRxAEQRAE4TAd9Sxvj8fDl19+yYQJE1i/fj25ubmnRQImEkpBEARBEIQjc1TrUAKsWLGC3377jQ0bNtChQ4eTelylIAiCIAiC0HiOKKHMzc3lueeeo1WrVlx++eXExMSwePFiFi1ahNVqbawYBUEQBEEQhJPYYU/KufDCC/n1118577zzeOmllxg+fDgGQ4MtYykIgiAIgiCcog57DKUsyyQnJ5OQkIAkSfXWW7FiRYMFdyKIMZSCIAiCIAhH5rCbGJ988snGjEMQBEEQhEY2ZswYysvL691re+HChTz22GMsXrwYRVHo0qULP//880GHtU2ZMuWQaz3v2LGDKVOm8N1335GVlVVnnYEDB/Lbb7/VOn7LLbfw7rvvhh3z+Xz07t2bVatWsXLlSrp06XLQ+wuNTySUgiAIgnCC5LhdTMteT67HRYotkkvS25FqPzG9YwsXLuT888/n0Ucf5c0338RgMLBq1Spk+eDTLa688krOP//8mvd/+9vf6NChA08//XTNsfj4+MOK4aabbgo7D8Bms9Wq99BDD5GSksKqVasO67pC4xODIAVBEAThBPhh50aeXfkr6n4jzz7cksVjXQcyIq3NcY9n3Lhx3H333TzyyCM1x1q3bn3I86xWa1gLpslkwmazkZSUdMQxHM55P/30E7/88gtff/01P/300xHfQ2gchz3LOzo6mpiYmFqv5s2bM2zYMGbNmtWYcQqCIAjCaSPH7aqVTAKousazK+eR43Yd13gKCwtZvHgxCQkJ9O3bl8TERAYMGMD8+fOPaxyHUlBQwE033cSHH35YZ8ulcOIcdgvla6+9Vufx8vJyli9fzogRI/jqq6+46KKLGio2QRAEQTgtTcteXyuZ3EvVNaZlr+f29n2OWzzbt28HYPz48bz88st06dKFDz74gCFDhrB27Vpatmx5XOJ4++23ef/998OOvffee4wePRpd1xkzZgy33norPXr0IDs7+7jEJByew04or7/++oOWd+nSheeff14klIIgCIJwCLmeg7dA5noqj1MkIZqmAaEJMHsn2HTt2pU5c+YwadIknn/++eMSx+jRo3nsscfCjiUmJgLw5ptvUllZyaOPPnpcYhGOzFHvlHOgESNGsHHjxoa6nCAIgiCctlJsB594k2KLOE6RhCQnJwPQrl27sONt27Zl165dxy0Op9NJZmZm2CsiIvS1mDt3LgsXLsRsNmMwGMjMzASgR48eh2z0EhpfgyWUPp8Pk8nUUJcTBEEQhNPWJentUKS6/wQrkswl6e3qLGss6enppKSksGnTprDjmzdvJi0t7bjGUp833niDVatWkZWVRVZWFjNmzADg888/59lnnz3B0QkNNst74sSJYh0oQRAEQTgMqfZIHus6kGdXzkPVtZrjiiTzr24DG3XpoIqKilprQcbGxvLggw/y5JNP0rlzZ7p06cLUqVPZuHEjX331VYPdu7q6uta9IyIiaNGiBQAej4f8/PywcrPZTHR0NM2aNQs77nA4AGjRogVNmjRpsBiFo3PYCeV9991X5/GKigpWrFjB5s2b+f333xssMEEQBEE4nY1Ia0PXuJS/1qGsJMUWcVzWoZw3bx5du3YNO3bjjTfy/vvv4/V6GTduHKWlpXTu3JlZs2bVJHsNYfPmzbXuPWTIEGbPng3A//3f//F///d/YeXDhg1j5syZDRaD0DgOe+vFQYMG1Xk8MjKS1q1bc9ttt9G8efMGDe5EEFsvCoIgCIIgHJnDTijPFCKhFARBEARBODINNilHEARBEITT03PPPYfD4ajzdcEFF5zo8ISTgGihPIBooRQEQRCEcKWlpZSWltZZZrVaSU1NPc4RCScbsZe3IJxmAn43Pnch+dlz8VWXkZjWH0d0BhZb/IkOTRCEU9Te7ZYFoT4ioRSE04i/yoe3rAxV8pPa4iJUzYMaqCbgq0JHxmqLPdEhCoIgCKchkVAKwmlA8+v4CzQqV+jYWichWcvYsfpjdm3+Ek31ohisNGt7Oc3aXYHFHo+iiE0IBEEQhIYjEkpBOMXpuk5BRRXlqhfjWTK4IGfLBHJ3fF9TRw1Ws2PNhwQDbjI6j8EeKcY7CYIgCA1HJJSCcArzBP0sL8zlhVW/UeR1A/BJnwHk7vihzvp7Nk0jvcPVeD3FWGxxxzNUQRAE4TQmEkpBOIVlV5bxwOIZ7L9UQ9BXAdS9eIOuq/jchSgG63GJTxAEQTgziHUoBeEUVRXw8e76JbVTR8Vy8BMlBU31N1ZYgiAIwhlIJJSCcIqqDgbZXFFc6/gWbwBHdEad50TGtUGxp2IwORo7PEEQBOEMIhJKQThFGWWZJFtErePvbN1AUt8nsTqSw47bIprQZcBzvL/VjSsgEkpBOBnkuqt4Z10W/1oyn3fWZZHrrmrU+40ZM4ZLL730oHV0XeeCCy5AkiS+++67g9bNzs5GkqRar0WLFh0ylvT09DrP3fsaM2ZMTd0ffviBAQMGEBERgc1mo2fPnkyZMqWmfNWqVZhMJqZPnx52j6+//hqLxcLatWsPGY9wbMQYSkE4RUWZrfyjdQ/uWzQj7Hix18NLWzbz+nnvU124B3fVHuz2plhcicj/NXPN9bGUVPiJ0Y0YosRnSkE4UX7cuZ1nVyxC3W/Dug83r+exbn0YnlZ3L8Px8NprryFJ0hGdM3v2bNq3b1/zPjb20GveLl26FFVVAViwYAGXXXYZmzZtqtmlzmoNjfV+8803uffee3n44Yd55513MJlMTJs2jVtvvZW1a9fy8ssv07lzZ5544gluvvlm+vXrR2xsLIWFhdx666089dRTdOjQ4YieRzhyIqEUhFNYh5gEbmrZmUlbV9f8UbIoBp5tdS7SC16sVU2wRTRDd2ng1dEJEjO5GuVWO/5SHUPUiY1fEM5Uue6qWskkgKrrPLtiEV3jEkixH/+ehKysLF555RWWLVtGcnLyoU/4S2xsLElJSUd0r/j4fbt37d2FJyEhgaioqJrju3fv5v777+fee+/lueeeqzl+//33YzKZuPvuu7niiivo3bs3jz76KNOnT+eOO+7gs88+45ZbbqFly5Y88MADRxSXcHRE84QgnMIcfg/DC5bzabd+vNyxN2/1uYCP+19GjNeCXqRCtY5eqIJ33x8tPSdIlKoQLNJOYOSCcGablr21VjK5l6rrTMveepwjAo/HwzXXXMOECROOODm8+OKLSUhI4Oyzz67V7XwsvvrqKwKBQJ1J4S233ILD4eDTTz8FQFEUpk6dyrRp07jmmmv4+eefmTJlCoqiNFg8Qv1EQikIpzQNbc005I9vIOP7B2hRupY/Z/4Nv8d10LPkajAmiB9/QThRcg4xVrKxx1LWZdy4cfTt25dLLrnksM9xOBy88sorfPnll/z444+cffbZXHrppQ2WVG7evBmn01lna6nJZCIjI4PNmzfXHGvbti333nsvn376KePHj6dVq1YNEodwaKLLWxBOYbLFieO8B1CtdoKaH9keT6dON0OkAaRA3ctRGkCXJAxRRzZGShCEhpN6iO7s493dPX36dObOncvKlSvrrdO+fXt27twJQP/+/fnpp5+Ii4vjvvvuq6nTs2dPcnNzeemll7j44osbPe4DVVVV8fnnn2Oz2fjjjz946KGHjnsMZyqRUArCKazaX86KvJnk5PwBgCTJtMi8hNJEAxEDzBjn+Wqdo55rJZgIFkPd3W2CIDS+S9Iz+XDz+jq7vRVJ4pL0zOMaz9y5c9m2bVvY+EWAyy67jP79+zNv3jxmzJhBIBAA9k2YqUvv3r2ZNWtWg8TVqlUrKioqyM3NJSUlJazM7/ezbds2Bg0aVHPswQcfxGKxsGDBAvr06cMHH3zAdddd1yCxCAcn+rwE4RTl9Zbz5/wnapJJAF3XcFfl8eXOPWT1DuK71Ar2v1oiI2S8l9tY1NFHhV6JTy0/MYELgkCK3cFj3fqgHDCbWpEk/tWtz3FvoXzkkUdYvXo1WVlZNS+A//73v0yePBmAtLQ0MjMzyczMJDU1td5rZWVlHdGEnoO57LLLMBqNvPLKK7XK3n33XdxuN1dffTUAs2bN4v3332fq1Kl07tyZZ555hnvvvZe8vLwGiUU4ONFCKQgnQMBfhab6MZocyIrpqK7h9ZZSULC01nFNC2KUNB5Zs4k+CVFcc1cKESi49CAf5u9kzcZKPjAo+HOWoJ41BsUaeayPIwjCURielkHXuASmZW8l111Fit3BJemZjZ5MVlRU1CSMe8XGxta5tE6zZs1o3rx5vdeaOnUqJpOJrl27AvDNN98wadIk3n///QaJtVmzZvznP//h/vvvx2Kx8Pe//x2j0ci0adP45z//yf3330/v3r1xuVzceOONPPjgg/Ts2RMIjQn99ttvufnmm/n+++8bJB6hfiKhFITjKOBz4XHl4XbtwmKPJxhwI0kK1ogUTGYnJovzsK/l9ZbWebyoaDX92hv4eCssKixnUWF5WPnFTaMwbvoK97ofsHe4UCSUgnACpdgd3Na+y3G957x582oSwL1uvPHGo04C//3vf7Nz504MBgNt2rTh888/5/LLL2+IUAG49957ycjI4OWXX+b1119HVVXat2/PO++8ww033FBTx+l0Mn78+JrzZFlm8uTJdOnSRXR9HweSrtezbsEZyuVy4XQ6qaioqFlcVRCOVTBQjc9TTGn+Cgqyf6NJq4uQJJmd678g4HORkDaQhGZ9sTqSMVmiDuuaZWVb+OH7K+ssa9HuFlYYhvDx5vCuniSbmTf6ZqJPvhT8biL630b02f84xqcTBEEQznSihVIQGoGuqXg9RbhKtlBdlUtkTEs8rhw2LHyV9A5Xk589l9ytM0hIH0RGx6twVe4ht2AZSXIfdEnBbK69peKBLJZYYmLaUFq6sVZZdcVa/tbjctrHRvHrnmKqAkG6J0SR6rDwvw253Dzkn+g/PYYerD1pRxAEQRCOlEgoBaGB6ZpKRckmNi56DZ+3BHd5NgCRsW3oMuR5NDXA1pX/R2qrizHFNmfOvPvR9WDN+a1bX0mnzjdjsUQf9D5WawznDHiJ3397kNLSjciygZiYNsTEtqV58xF8sjWfH3ZVMCI9kaHN4jEpEnuqvMiKgerEjkRlngMZ/QlWFmOIiGvML4kgCGcoh6P+8aA//fQT/fv3P47RCI1JJJTCMdNVFb3ah2RQkCzmEx3OCVftLkANemnW7goUoxWTJYrtWVMp2DmX8oJVqEEfsmImvvkg5sy7t9b5mzZ9TkJCF1JiOuLV/bgqd2KzJ2G1xmG1hu+PGxGRyuAhb6G5gxjdNvQ1Knoe6HFmLk9VibWVEG0x8e6abHRd55mO0Qw0rkNbsgJjUluMFjuerb9hbzkQxXHovXcFQRCOxIGTf/Z3sJniwqlHjKE8gBhDefi0QBDKXKiLV6Nt3IFks6AM7ImcloLksJ3o8E4Ir7sQjysHxWilNH8lPk8R0YmdsdqT2LnhGzwV2Tjj21Pl2knA7mTr1u/qvE50TGv6xA1Fd5fiSW3B70ueISamDQMGvoTDEb4Wm1ahom72E/yiMrTd4l69zJRdauby+Svok+Dk361NlH92G5p3v110ZAOxI8ajOJtgadKxEb4igiAIwplArEMpHBWtogqKyyAQQOnVAeXC/mhlFQQmfkPgx9/R3NUnOsTjTtOC+LzlVLsL2JY1Gasjiaj49ui6TlXFTjI6X09l2XYS0voTEdUCj6ew3mtVe4rAbKd6yafYsteT2Xw4paUbWPDnU/i9VegVKlpRkOACD/53ylHneTBcYMc01gnGvy6yxEdUNpzbJIan21ipnPFUeDIJoAUp/fkF9IAHLehvtK+NIAiCcHoTXd7CEdFVDT2vkMAXP6PvKQBASk3AMHwAhutH4pN1+OIXKK0Ae/07KZyOqqvy8VeX4q7YiSMqnay5j6GpoUkvFnsiHfo/RrchLyHLRhKTzyMgR5Cbu6DOa8XHdUIvDm1xVr36ezKveIGc/MX0yLwPfaaK2jxA4KtK9N37xl5q6/zIrU2YrnXin1wBgPyzh/tvS0VxrSJQuLnOe+m+KnS/m7r3aRQEQRCEQxMtlKcRXdMJVmn48lVcSwJUrQ4SKNHQAg2XKOgl5fjf/KQmmQTQcwoJTP4Wye3BtG0PeaMGU11Q1GD3PFWoQR/+6jIstni2rny/JpkE8LoLWDn7IYzmKOT8ZlgNzUiJGoTJVHs2tyQpdGx7E4FdK/66cAA5GGBo73dQc+KpzNDR9gTCksm9tE1+dFVHildCB9w6Bk0HLXCI6HVkgxj/KgiCIBwdkVCeBlSPhi9PxV+kU/S1n90vein81E/+ZB+7XqjGs1FF8x97UqmrKuqClRConcgQCKJlbUTfkUOywUJB01h07cxq8dK1ACZLNDvXfV5nuRr0UrRnPiajBb0E7MZEhvSZSHxcl5o6kZHpDOr9DsbSaPTqir+OSgTjO7DA5+Mu/y8sUnJRF3rrjUNd7kXpGEoOg20NeGUPuhpAtkbVfYIkY4jNOIonFgRBEIQQ0eV9ilM9Gu6NKoZI8O3WcWepYeV6EPKn+Gj6gAVTkox0wL6xR0J3V6Nt31NvubY7D7ljK6TcQn4xuhgbn4gJ5ajvd6qRZCMmWzRVFdkAKAYr0UldkCSF8sI1BHwVVJRsIHVTFepiL3JzI5GXNaVXwktoLSrR0aDEjufbCAyX5qJWhsZYGs9/jPe3reePgl3c1OYsulqbgHqQMaoqoY+KJgn/ECuBYDHqyq9xnn0TZbNeqlXd0eMqJNOZOYlKEARBaBgioTzFBct0TPESmg/Kf6unW1ODqiwVY7KGLUPBEHmUDdOqihRhr3eknRTpAE81gaAKZij1ekiyHXqB7tOFGvAgy0YczuakNL2YmMhz8K2LgKBMiy6VuPU1qIFS9MJQ0q/tCKC9UorjnhhyPrGiunSQIG6kh6rVoS3QDHGZuNN689vCmTzd/UJez8phnnk7T/VsimV6HS3FgNLVTHBPgIoHHHidKglEUF6RR6Akm9iLn6Fyycf4C7dgcCYT2ed6DHEtMDjEOpSCIBy7MWPGUF5eznfffQfAwIED6dKlC6+99toJjUtofCKhPIWpbhU9qIMsoVbqoYSkHsFSHVtbhaKv/cSOMBEo1lBsEganhCHqMBPMoIbSswPahu11Fis92hOY/iv6WR0ZZE3iTFuRymSJhYCRLv1eompeBCVLjPsKFzuxtOxL8kgFdUfFvuM6qDMqibsgkuo9XiJ7yWCoxBjVn8izrkGKjGdxcTHXZvbgvTV5ZLs8ZAMlPdJpskBBLw5vkZaaGvB1MDIntYLmMQ4STCa0slLiR71B2S8vUr1tPo5OlxDR53oUeyxqtQujMxlJPnNakgXhZJLr9jBtx05y3R5S7DYuaZ5Gir1xewx2797Nk08+ycyZMykuLiY5OZlLL72UJ554gtjYw1uPNjs7m+bNm7Ny5Uq6dOlSb71vvvkGo9FYb7lw+hAJ5SlIV3UCZTpoUL1Tw9JMwRgjYW4q49ul1XmOuamMa2EAc4pMoESj4vcAvj0akkEi+WYL5uRDJ5V6MIgOKEN6o85dvG9SsATKgJ5ohaXIfbpQbICf92zhqoxODffQpwCjEovqUqBax72k9hI83i0y3g0KpmYG9F1/tS5aJfTsAOa4XKp3/pfCTxcRNfheInteXXOeraKKOIuDd8q21hy7b+0GXr29LbFZKtalAZAl9AEW1C4mSi0q58TGE20xAaApafhLdhBx1g0YHHHo/mqQFSSDGWNsOoo9pnG/MIIg1OnH7N08t3wV6n4fvj/atI1/du/M8PSmjXLP7du3c9ZZZ9GqVSs+/fRTmjdvzrp163jwwQf56aefWLRoETExDfc74VivpaoqkiQhy2LKx8lO/A+dgvyFoXGTmh/8e3RyJ3jJn+IjenDdnwIVZ6glsnKJirmpjH+PhrW1QsLVZhLHmCmZ6SNQXnciGqbKg2Q0giRhuu0qDFddgOFv52K85UpwWJGbp+Lp3pr3d6zmp12bUPXDuOZpxGg3oTgkXPPVeutULFORelqRB4PhYS/8YyvSnTlgD6J5y0ELIpvCl1tqH5NA4IAJTsVeP9ctW8X46D38fGWAyrsdLGvro9oBzSJtNckkgGxxYEntiDmlA7I1CkN8BuaU9pgSMkUyKQgnSK7bUyuZBFB1neeWryLX7WmU+95xxx2YTCZ++eUXBgwYQLNmzbjggguYPXs2OTk5PPbYYwBIklTTbb1XVFQUU6ZMAaB58+YAdO3aFUmSGDhwYJ33GzhwIPfee2/Ne5/PxwMPPEBqaip2u53evXszb968mvIpU6YQFRXF9OnTadeuHWazmV27djXU4wuNSCSUp5igSyNQomNOlCj8zE/l0iB6EILlOu61KglXmTDE7Jt4Y20lkzjaRPG0UIuZ5tMxZ8iY4mX0IFRvVYm90ITqOXj3tK7pYDYR+GwGckIsWlEpWm4hWMxIZiNSfAxSfDTb/FXMytlKUNdRzrBPlJIkoXtDX+P6aF6QWkt44j4jf9ooin+5h6Ifb6Hg0xuJ6HE1lvQ+mJt1r6kfdBVgL95Kss1GXdOplhaV85/N2yk3qXRPjCLeVv/SP4olAkNEPIq5/r11BUE4Pqbt2FkrmdxL1XWm7djZ4PcsLS3l559/5vbbb8dqDf/gmpSUxOjRo/n8888Pa7jSkiVLAJg9ezZ5eXl88803hxXDnXfeycKFC/nss89YvXo1V1xxBeeffz5btmypqePxeHjxxRd5//33WbduHQkJCUfwlMKJIrq8TzFaQMe9IYijvQF/TngLYOWyIL5cmZgLjBhjZNQqHV+OFko4y3SsmTIGp0zxd358uzWQwNZKwdpCQYnUUb0aiqXuJNBb7cGwORula1sCn/yIFONEapaMtmoTwS07MQzpjZoYy9Pr5gMwNDWTKJOl0b8eJxO1WkPz6dhaKlRvrrt11tZSRlPXU7Xqo7Djuq+Kkh+eJPH6KSj20ASZYEUehZ/cSrB8DxG3/MyQpnHM3l1c65qDm8ThDgSxm8SPsyCcKg7VApnXCLuNbdmyBV3Xadu2bZ3lbdu2paysjKKiQ68jHB8fD0BsbCxJSUmHdf9du3YxefJkdu3aRUpKaAvZBx54gJkzZzJ58mSee+45AAKBAG+//TadO3c+rOsKJ4czqwnpNCAB9nYGfHvqTlj8uRqFH/tRXTr5k32U/RLAn6thbiYRPdRIztveUDIJoINnk0re+150v0RVVpCgq+7r7vFWEcwpRIpxYrh4EEBo3cmiUgyXDEK3mJlfnkeep5IYs5XRLTtjUkIJTlDT8AYPtbD2qU9XoXqbhrmZjCG6dnuibAHnIJmyP56r+wJaEO+OxcgmK1rQT8XCKQTLQ8s0qcU7OLdpPMPTEzDIoWsbZYnh6YkMaBKHxSAm1QjCqeRQE2+SG3GnsRM1YXLNmjWoqkqrVq1wOBw1r99++41t27bV1DOZTHTqdGaNwT8diCaNU4yuSVStDE2uqY9khP1/X/jzdSLPMlKxMBhao/AAmhvcm1S2tCrgz207yXDG0DOxCYlWBwZZptTr4b8bFvF4r7ZE/993SE0SUQb2RHLY0MsrUX9fjntIT74u3M6Ylt24tFlbkq2RuPxedrsr+GrbWkp8Hs5Jbs7ZSWmHXEqo0u+jKuADScJpNGMzmg5a/2ShWP9KIiVIHG2mcoWfymUaugq29hoR5wZQTcUEy3bXe41AYWjijeYpw7Pmh5rjNtVNnNXExc2TGNUyFXcgiDuoMm9PCV9u2cML/do36rMJgtCwLmmexkebttXZ7a1IEpc0T2vwe2ZmZiJJEhs2bGDkyJG1yjds2EB0dDTx8fGhITwHxBYIHFvDQFVVFYqisHz5chQl/EOww7FvKI7Vaj2mNZOFE0MklKcQtVqj+Ds/nvUqEV0NoFBngujoasC9dt8ahaYkCXMTmdKf6v9l4N2g0bF9EqvlPJ5bNQ+LYmBCv4tpH5NIVcBP74h47BERKEPPQp21kOB+Wy+qvTpgTUviyaoUbNNA2lxN1b9NfFW0jnc3LKmpt6hwNxM32vi/c0bSxOGsFUNQ09hZWcbSwt0gyeR5XHjVIFdndibZ6sBsOLmXnpAUiYiuBnL/V030EBOOHkYi+wfRpAB+ysgtX4ZWXEJUQiaB/I11XsOS9tf4SV1HV0PjXg2XvMqX/qZ89uvqmsk5LZw27uzUHIsi81SftsRYTo2kWxCEkBS7jX9271xrYo4iSTzWo3OjLB0UGxvL0KFDefvttxk3blzYOMr8/Hw+/vhjrrvuOiRJIj4+nry8vJryLVu24PHs66Y3mUK/c1S1/kmIB+ratSuqqlJYWEj//v0b4ImEk4lIKE8hahV4NoR+eMt/D5BwpYnCz/1hSaW5iYyjk0Le5L/2kVbA3F4moKgoDqnetSqVCAnXzyrXdO9G+85J3LvqB+5fNIMPB40Cr4+R+SqmqR9Cn84Yb7oMfXcBuqaht2/BFt1Lqxkm7L/+NeZHhqJqd1gyuVeJz8OEdYt4vNtgbAesTVboqcKnqXg1FR2V/snpqLrGiqJcWjhjiLPYSLXXTkRPJsYYmZR/WCmd7cczQ8UYK2PJNKL0DLBk8bPY7UkM6nMHge8er3WuZInA0rw38NfM7Iyz0AI+fpOb8+GmnXSNi+Daplacik6lJvHDjjwub9kE+QybTS8Ip4vh6U3pGh/LtB07yXNXk2y3Nvo6lG+99RZ9+/Zl2LBhPPPMM2HLBqWmpvLss88CMHjwYN566y3OOussVFXl4YcfDltPMiEhAavVysyZM2nSpAkWiwWn8+C/n1u1asXo0aO57rrreOWVV+jatStFRUXMmTOHTp06MXz48EZ7bqHxiYTyFKJV6zVrP4YmfQRJvsGMv1BHD+iYm8gES3XyP/SBCrIVHNfKjN/2J9V6kCcG9MP/ad3XtndUKPjYh3u1SpfbU+gV14QlxXso9FbRzKti+nkhAOqiVaiLVyMlxYIkEyh3kXpuX9SVvppryc2MLCiuf5mHeXnbuTtwVlhCWeJ1M2XLCr7LXh9W94ZW3WgeEYM3GOTLrWu4IrMTqfbIo/sCHifGOJn4v5nR/po575UK2ZY9G9Bxu/PYXrGG5ufdj+ePiWjV5aFz4jOJuujfBG0JGADZ7CBq0L0UVAeYujKXpzol0rl8GYEZk9E8pTitUdzW/Vp0PRqXz0KiQ2ydKAinohS7jds61D1JpjG0bNmSZcuW8eSTTzJq1ChKS0tJSkri0ksv5cknn6xZN/KVV17hhhtuoH///qSkpPD666+zfPnymusYDAbeeOMNnn76aZ544gn69+8ftvxPfSZPnswzzzzD/fffT05ODnFxcfTp04cRI0Y01iMLx4mkn2nbmRyCy+XC6XRSUVFBZOTJlbj48lR2v+yFAxqkjHESslUi7nITmkcPJZ4RsFUq462dK1lbHpoZ/Ey7s2mzLB7f8v3+yyWIHmpEq9ap+CPUTR53uYntKUXcmvUdkwdcRosV22DG/LqDUhTk2y9ErXQjZaWizQW5hZFPRuzg3eyl9T7Ld+ddS8p+ieGvudt5ePHMmvdtouIZ0aw1MWYbaY4oHAYzOho5nkq6xaWcUksSud1FbN70OWvXTqo5lpDQjY4tLsOEARQDtugMCCaBKmG0yhidBnKqqslzeymvKKVbzo/4shdjSmqL7q+mett8dF8Vlm5XQve/E2s1odgPb4cLQRAEQWhoooXyFKH5dJDB0VWhann4mJVAsY6lhUT1JpXSGQFMw3VerlzM4uL8sHpPrP+TOzt25aIBLQhs05GCEuYUmaoslcql+8ZcquU6Uc2sSEC8xY7sCxyYw4YSya4dUNp2ACIIBtehd89Gys1E2x7krLim9SaU3WJTcOw30cbl9/LRlpU17+/vdDZ+VeWTravI81SSGRnLbe16o6GT5oii0u8lynLqtMiZzRGkpPYNSygLC1cwp3AFALGx7Tgn7WXkt8rAqxNsZkC/OoKf3Pn0SbVytlNFozOKyY5v90pkSwQxF/yLQMEmXIs+IL7r39D8Kor9RD2hIAiCcKY7dZp5znDBCp3cd33YOxhwdFP2/c9JYGunED3ISNmc0KQbrYlWK5kE0NB5Y9sKJpau5oPoNXhb+8mb6AtLJgFMyTIVgWoua9YeS9CA0j4z/EImI8a/X4Ve2R3fWzK+p9wwJQNlT3OMo0xglUiKiGBISotaMZhlhfs6nU3kfmtUBjSNUl9o/OVlzduz1VXCm+sWkuupRAe2uEq4b9EMir0eCqqrcJ9iSxAZDBZstgQSE3vUKpMkhe7dHqLcZKf8VjsMMKMXqQRfLGO0JYlUxY8sSZT98gIVv7+Nd8dCPBt+oeS7R9AC1UT0uBK9IhdJFp8NBUEQhBNHJJQnOV3XCZRolPzkR3PreLerOPsaSb3TQtP7LaTeYybmfCMFn/jQ9w5j1CSMB+kSNioK68pK+LF4O+bM8KUZjIkSUoROleTnKq0b5nwFKTIKuXV6TR3DsHMJTDOhLgzsmxDk0lA/1dF3SJjHxxIdZeeBzv0Z330ILSJDE2oubNqKDwePIiMyutYz9ohLBaBfUjrTszfUGfc76xcR3C/5PJXYbAl07nIbHTreiNUajyybSErqxaDzpjBlt8JctZjtiS7mDCpiwxMqFfeYYZYHh9+Aa9FU1MrCWtesWvYZlvReyCY7sthCURAEQTiBRLPGSc5foBMo0PBsUEn8u5nKpUFyJnhDk3MUiOhuILKXgilFxrs11DEtr5IZ1rw5P+Ruq/OaXWIT+GTLBrxqkPPaNofN8r6WznONqCaV9K8S8O3Q0f6ug8OE4aoL0VZvQv1zJUSnoG3z13ntwHfVWLqG+l5jLTYubNaasxKbEdQ0HEYT1v2W/tF0nS0VxTy+bBbP9DyP+XnZlHo91Deot8Lvo1oNouoaAU3FKJ86i3krigmLLZFK1246dvoHdnsSxXIaty7O5cHu6Xy8bRFvbcwFQEZiUEoGd1/Ti3hDFGpVMcb4TAJFW2td17trBRE9rkY2iGWDBEEQhBNHJJQnsWClRvG3PiLPMhI9yEjFHwGqt+w3mlGFyiVBkCBmmJG83aFWysAKuL5fe5aX55PncYdd87pW7fgzPwdV17EpRqydZGIzzEgyKGYJX7ZK0WcB0EI7u7ia+iiVPFT7gwRbJ5DQaSRRRSZMJj/UlVNWalCtEVokMyTaXHvHh0q/jxKfh1v/mIY76KfK72PC2RdT7Dv4dmQGWWZR4W76Jjb8or+NzRmRQvsud1NUsIQqKZqHl+TQPzWa2bnrWFkSSiYHJTTh1qbpWHYuRvOmsFSOJKvDnSQadLrZZYwL30Pd8ee+i0oShkixz60gCIJwYomE8iSmVulUb9YwJarYOxsonVn32MHKpUEieigkXmVGtkug6ciyxJuthrBKLuSP/BwijCb6J6eyoqiA2Xt28lSPvrSKimZtZTFGo0Kuu4qEoI2MWXGhWeQSmG9V2am7+GjzShYV7tvd5ZzENB4Y15fI/3prJ5UyYDz4DgcVfi8zdm0iqGm4g34yI2OINlt5Ies3Ls/oSITRTGXAV+u8ls5YsivLsBlMp9Qs7/0FDTHocYMJajou/2r6JUfy2LJ5APSISeTuaCval3cRuOJt7l9fwO6q7JpzDZLEiz1vJ10PomYvBsDWatAJeApBEARBCHdq/lU+A6heDbUy1PlblRVEDxxkdScNUCF/qo/CT33IERKlP/oJTJTpXp1El9h4yv1eHl/6J5UBP2/1H0J2ZQWfbd1IVSBAVSBAVkkhzWOcOPoqSEZw9JbZaSxl6uYVYckkwO8FO3m5dAHeC2p3syo9LUiRB/+22lJRwqLC3eysKufKFp14vNtgHlw8k5UleXyyNYuHOp9TMwZUApKsDlo6Y7m9XR++3LaGwSkZp+ze4Il2CxFGCatBQQI0NIJ/LUx+W1om2k9Po3S8mHd3VbK7Krx1Oajr/HPVNoJ9bgHAknkOhugmx/sRBEEQBKEW0UJ5ktKqdYLlOuamMv4iDdly8FY/2R4qD5bpyH6d2NgAUj8T1U6dXvZkUuwOesYnYTEYuH7uTzXjFGfv2cmLHQbwUERvqn/Q0OyQeocFvyWAhMzSoj113u/3wp3c2ak3lmn7jklpMobLrUiW+hNKT8DPx1uyKKyuYnjT1pT43Ox2V7CrqhyAdWWFTMtez396X4A74CfR6mBnVTmyJGGSFW5t14tyvxefqmI5ybdirE+sxcpudyW9EqMIahIRRjOqruH0lqP7PfhbDOK3rNw6z/VpGlsCRs66+DnMzbqh2KLrrCcIgiAIx5NIKE9SklHClCwTO8JIwWd+JGNoT25/fu2WSmtrBdkMji4K3t0a+lY/6g9u+MGNKcOI6W4Tzy5fxKv9BvGPeT/XJJMS8FrHwTi/sVOyZ+/SQRoV84JEDTUgdzt4jFUOL8n/0KFcQkrVCAS3oJs7ApZ6z/FrGsVeN9tcpTSPjGbKshUMbRK+LNGy4hw6xCSi6/D4slk18cpI3NquF2bFgO0UTSYBrEYDGZGRjOuWwUcbdjMqozNfbl+FHvQiAQGksL19D1ShK1gyz0Yxi4UnBUEQhJOD6PI+SWl+ncJPfJTNCpB8Q2jSTNwlJowJ4S2V5mYyUecYUD1gbakQ9zcj2u/7ukr17QGsu3X6JaeyuCAvbAZ17/hkotbZCOypnbyUzwoSZzp4wmLxlVK04kZKcu+hYO5ofKXLkG1RBz3HYTTSK6EpAHmeSgqqq0i0OsLqxJittIiMYeqWFWHxaui8vX4xsRYblQEfFX7vQe/VkHRVJ+jSCLo0dPXYN5eSJZnfcjdxbpqTAcktuLJFZzRnKkgyFk8RybbaE5n2ahdpE7O6BUEQhJPKaZVQpqenI0lS2OuFF1440WEdFc0F/nyd6q0ahZ/60PxQ8KmfqP5Gkm4wEz/KRPKNZhxdDBR86CP411qVRqeMFB2+nI79Ix+jW7SlMhA+g+bS+JaoS+rvSrcVmOkWk1xnWZ/4Jlh2LUFzlxAsyUZxJBB51vWHTnQ8EpektMNmMKLqOpUBH7IkEbffzjdDUlvw465N9V7ioy1ZfLF9Dfcu+IFZe7ZQ4j34zPBjFSjTKJ0dYM8bXva85qX0lwCB0lp7Bx0RvxpkSdEe7l34HXnVpSRZ7QQtTmw9R2NYOoW7W6bWeV7PuCgS7HYk5dRtoRUEYZ/cKi/vrsnmiYUbeXdNNrlVjftBecyYMVx66aW1jpeWlnLXXXfRunVrrFYrzZo14+6776aiouKwr71161YiIiKIioo67HPGjx9f8/daURSaNm3KzTffTGlpaa26CxYs4MILLyQ6OhqLxULHjh159dVXUdXw3eP2zwEiIyPp2bMn06ZNC6szZcqUsHoOh4Pu3bvzzTffHHbsQrjTKqEEePrpp8nLy6t53XXXXSc6pKMSKN/XCubP09HcOmqVTtHXfvKn+ij5wU/eZB8l0/1oXlAiZQwREv58DdqGJ3V6gUpC0MLZyeETOCyKIbSlYz3kLANPZvaiW0xS2PGesSn8s1VvnPYYbB2GE3f5qyRc/Q6GyKR6rhSiVmuUzQqgTzbwbqeRGCWZKJOF/21YwuPdBpNiC+3t7TRZKD5IklhU7UbTddaVFfLY0lm8tOp3yhppsfNAmUbu217KZgYIlugEy3TKfgmQ85aXQNnRJ5VGWaF5ZDSqrvPPJbPYWFFEflDF2/lvWHtfR+uChbzStSXpEaHWW7vBwHUtmvB4tw7EOE6uPeYFQTg6P2YXMOqnpUzdsJtZu4uYumE3o35axo/ZBcc9ltzcXHJzc3n55ZdZu3YtU6ZMYebMmdx4442HdX4gEODqq6+mf//+R3zv9u3bk5eXx65du5g8eTIzZ87ktttuC6vz7bffMmDAAJo0acKvv/7Kxo0bueeee3jmmWe46qqr0A8YJjR58mTy8vJYtmwZ/fr14/LLL2fNmjVhdSIjI2tyhZUrVzJs2DBGjRrFpk31N2gI9TvtxlBGRESQlHTwxOZkpqkawTIwJUg0uc+C6tEpnxXAvU7F0VmhaqUKGmj75VvmZjKqSyOipwFTigxa+OcEqbkRdblMUhM7nWPjWVVSBMDSijwubeXEv7bupNLeWseY6+XZxC5UpMtUBgNEyAac23OJ+O53DKOGEdH1b4f9bGolVPweGqtpft9K8wstPNX1XO5bMoMXs37j+lbdiLHYsCoGSn3VbHWV1HmddtEJZFeW1byfm7uda1t2rXO9y2Oh6zrudSqB4tpfn2CZTlVWkKgBRiT54BOm6qLIMiPT2/PltrWousaX29fy5fa1ADSPiOa1LkPpbbHSOiEJnwaKpBNjVDBZRTIpCKeD3Covzy/dzIEjaFRd5/mlW+ga5yTFUf949IbWoUMHvv7665r3LVq04Nlnn+Xaa68lGAxiMBw8XfjXv/5FmzZtGDJkCAsWLDiiexsMhpq/26mpqVxxxRVMnjy5ptztdnPTTTdx8cUX87///a/m+D/+8Q8SExO5+OKL+eKLL7jyyitryqKiokhKSiIpKYl///vfvP766/z666907Nixpo4kSTX3TUpK4plnnuHll19m9erVtG7d+oieQTgNWyhfeOEFYmNj6dq1Ky+99BLBYPCg9X0+Hy6XK+x1ogRdGq4/VXLe9LL7JS957/vw7dKIGW5EV8HRyYC9qxKaTfMXa6ZMzDAjRV/6KZkeIO//fOiJZpRH4lBGOpA7mZEviqBisYrvQ4nHk/oypmV7HEYjv5fsxnmhgYSrTMRcaMQYv+/CpiQJyWQkb0Yy3l+TSC6Pos2SnaS8+SX2H/8EswmkI0ukfDn7WvTUKqj+QiLlx1g+7DqKQfEtmJu7nbWl+cRb7FyR0RFTHTvhmBUDg1Iy+CN/Z9jxOTm1d5E5Vlq1TuWy+r9/KpepqJ6jH0+ZbIvgxd7DwiYYGSSZEc3aYIuMx+CIIy4iilRnFEmR0SKZFITTyPQd+bWSyb1UXWf6jvzjG1AdKioqiIyMPGQyOXfuXL788ksmTJhwzPfMzs7m559/xmTa19P2yy+/UFJSwgMPPFCr/kUXXUSrVq349NNP67xeMBhk4sSJAGHXPJCqqkydOhWAbt0OMSNVqNNp1UJ59913061bN2JiYliwYAGPPvooeXl5vPrqq/We8/zzz/PUU08dxyjrpvl1yn8PUD5nXwKjunRKZwRw9jcQ2Vshb7KPuMuMRA82ovtA8+p4d2oUfOhD+2vYTbBMp/y3AJIiYWtnJeg0YXYoOHqAZ62KfzJcNqANV/dri6FYofxLP/48HUO0RNQAI1ogtFyRraVCwSc+NA8EyyFns5HEy3pjKilC374bpV9XpEhH3Q9TD7mOn+XAemCjmctbdyFqlAGr04gsSQQ1lf+dcynPrpjHlr9aKls547ipbU/+b+MyVD28u1mRGuGzkQSSApIRInoYsLVRQANdg8oVQdRK/Uhz6jBWg5G+iWl8OuRK8j1VBDWVFLuTWLP1lF0SSRCEw3OosZK57uM36bAuxcXF/Pvf/+bmm28+aL2SkhLGjBnDRx99RGTk0X3oXbNmDQ6HA1VV8XpDz73/3+3NmzcD0LZt2zrPb9OmTU2dva6++moURaG6uhpN00hPT2fUqFFhdSoqKnA4Qn/HqqurMRqN/O9//6NFixZH9RxnupM+oXzkkUd48cUXD1pnw4YNtGnThvvuu6/mWKdOnTCZTNxyyy08//zzmM3mOs999NFHw85zuVw0bdq0YYI/AsFyjfJ5dbeGVSwIYu+o0OQeK7IZ9AC41gQo+6Xu+lWrVBJHmyn81EfiaDO57/iIGW4kepgRJULCEAW+bJ38D/ftRuPP0yn6yk/UuQYM0RJ5E30cuKl20U8yqZedjZS2AWKsSEeYTZmSZSQD6AeGrYHmkbAYQ8kkgEFWaBedyJtnX4TLH4ple2Upr6z6g/zqqlrXPnDpoYagWGWcA4zIClQuC5I/1QcaSGaIOtuIbaiMYj+2RNaoKCTbIkm2idZHQTiTHKo7O8V+/Lq7D+RyuRg+fDjt2rVj/PjxNcfbt2/Pzp2h3qH+/fvz008/cdNNN3HNNddwzjnnHPX9WrduzfTp0/F6vXz00UdkZWXVOf/hwHGSB/Pf//6Xc889l+3btzNu3DjeeOMNYmJiwupERESwYsUKADweD7Nnz+bWW28lNjaWiy666Kif50x10ieU999/P2PGjDlonYyMjDqP9+7dm2AwSHZ2dr3jIcxmc73J5vESrNBQqwC1ngoqaN5QC5/BEUpgaiVl+9NAkkH3h7ptZSuU/higyX0WAsUaaBLF39a1ETeUzw2SfKO5VjIJoXGbelQ81QWfY/c3QyH+iJ5TiZBIHG0m/4PwZFW2QcJVJhR77QQ1xmwjxhyaAW5QZAJa7Ykwf0tvT5I14ohiOVyWpjIFH/rw7th3X90HZXMCSGYjliY6knIMzZSCIJyRLm6exEcb99S55qwiSVzc/MTMBaisrOT8888nIiKCb7/9FqNxX2/JjBkzCARCu5RZraEx63PnzmX69Om8/PLLQCjp0zQNg8HA//73P8aOHXvIe5pMJjIzQ40CL7zwAsOHD+epp57i3//+NwCtWrUCQo1Hffv2rXX+hg0baNeuXdixpKQkMjMzyczMZPLkyVx44YWsX7+ehISEmjqyLNfcF0INUb/88gsvvviiSCiPwkmfUMbHxxMff2SJy15ZWVnIshz2DXQy0VUdX65GwQc+4q84+HI7sglk077Exd7RQPncurNKa0sZ785QAqT5QoukU61TtUrFu1UlapAxlMDWRQt1tcsWarrRw2LW/VRmfYqt8/mH9Yxhz2CUsLVTaPqQhcrFQQLFOtZWCvb2CoboQydlTexOJg38G7/m7ODXvG1EGMxcndmZTGcsTnPDf5rXtdDM+v2Tyf2VzQng6K5giqk91lMQBOFgUhwWHu3ZkueXbglLKhVJ4p89Wx7XCTl7uVwuhg0bhtlsZvr06Vgs4TGkpaXVOmfhwoVhy/ZMmzaNF198kQULFpCaWvfyZ4fyr3/9i8GDB3PbbbeRkpLCeeedR0xMDK+88kqthHL69Ols2bKlJvmsS69evejevTvPPvssr7/++kHvvbebXDhyJ31CebgWLlzI4sWLGTRoEBERESxcuJBx48Zx7bXXEh19cm5PFygLjVeMHWFCMkkY46Q6ZxQb4yQUp4Rs3pd0GWMlbG1lPBvCkx3JCFEDjBR87Ks5d++e4LpPRzIQNqmnLpJJQq+jtVRxSkhmHcloQbHH1K5wGGSThDlJwXyJgq6GWvd0NfR10DwakkFCtksYHHUHmWyL5KrMTlyU1gajLDfqWMNAiY43u/6lgXQfqB7g6L4UgiCc4YanJ9I1zsn0Hfnkur2k2C1c3Dyp0ZPJiooKsrKywo5FR0dz5ZVX4vF4+Oijj8ImqcbHx6ModX9wPnBc47Jly5BlmQ4dOhx1fGeddRadOnXiueee46233sJut/Pee+9x1VVXcfPNN3PnnXcSGRnJnDlzePDBB7n88strjY880L333svIkSN56KGHahJdXdfJzw9NfqqurmbWrFn8/PPPPPHEE0cd+5nstEkozWYzn332GePHj8fn89G8eXPGjRsXNj7yZKFrOv48jYJP/PhzQwmLJV0m8e9mct/zhi0JJNsgYbQZY3T4WD1DhEzCVWbca1XK5wXQqnWsmQqRvQ2UzgygecDRVaF6q1bTvWxprlC5PEiwTK93G0fJDMb4OhJKBeIuNRF0bSBq0N3I9thj/jpIioTq1qhapVLyvb+mRdTcRCbxWjOmxLrHJ8qSRISpcYcpBCs1Smb4cXQ8yI+IBJqiUeUJ4rCd2GETgiCcmlIcFm7tmH5c7zlv3jy6du0adqxFixZs27YNIKwbGGDHjh2kp6cfr/AAGDduHGPGjOHhhx+madOmXH755fz66688++yz9O/fH6/XS8uWLXnssce49957Dzmm//zzz6d58+Y8++yzvP3220CoRTY5ObR5h9lsJi0tjaeffpqHH3640Z/vdCTpRzLK9QzgcrlwOp01yyU0Bn+xxp5Xqmt1KRsTJZKuN+PL0fDna5iSZczJMpquYU2tvyUuUKahunXca4KU/xZEtkg4+xpQIiWKvvCDDpYMGUcXA8Xf+DFES8RfZiL/Qx+6b78LyZB4gwnvDg1bpoJ7jUqgWMOUIGNrrxCs8GJuthNjdFOUY1zCRq/WQAbPDo2893y1yhUHNLnPWiuRPh7Uao1gqc7uV7wkXGOm5Hs/qqv2j4m9g4J+QZCgXaOZU0yqEQRBEM5cp00L5alCrdapWhmsc3xioECneFoAS4aE6gZjVKgV0RBz8KTKGC1jjAZDlExk79DSP65FQcpmB1AiJZz9DJiSZQo+CCVuwTKdkp8CJF1nxrtTw5+rYYiRcHQ2UGirwh40kzfFh72VgjFeJlCm41oYIO5SEwZnu2OahKKVBlHX+1HnV4MBDL1tJP7NQMG0YNikJLUKvNnaiUkoqwj9ZEhQ9oufhKtMFH4WnlSam8pEnWvki+KtdDEmkKTaMdXTJSQIgiAIpzvRQnmAxmyh1Pw6/iKV0h+DeDbUPaVbtkPs+SZkm0TlitCkm4QrTRgijiyxUr0amhf0oI5ncxDFolDwYe2WQOcgA5ZmMq6FQWztDHizVYxxEpG9jPhzQy2flhQJdvnR5rhROpgxDLAhxStHvGyQVhrE91IZel74ZCK5gwl/LweF34Yfd/Y3EP+349+V7M0JolaB688g7jUqxniJmPNMIEHQpWOMlTDESFToPl7es5QrMlqh6jrd4xNFUikIgrCfves81uWnn346qq0ahZOTaKE8jtRKHc0Hhqj6EzFjtIwSLREs03F0UbC1Uo44mQRQLDLKX+O6DREywSqN5FvMlHwfwJ+roTggso8RU2JoWRxJhrhLZEqmhbrInWcZsbeQCMzxoJdUQTM/ykgJfb2K98VqLA/GIiUd3rePTw1SVu0lYr6KlFd7Zrq21o/5LA0lUgprBTQlHf/WyWCFhu4LteJGn2fEu0MlUKRT8LEPyQyKNTRT3TFQYUbxNpo5IrAbjSwrzKdZRASp9sZZvkgQBOFUdODkn/0d7Sxw4eQkEsrjKOjS0dyhsXeuRcE613qMOteAuZmMNU1CqWem85GSzRIms4LRqWMcI6G6IFCkUbks1C0u2yD+CjNVWUHiLjMSKNGQzBCo1NG6GFHdpVQu+y/+3NVYmvcn6ua7CMwyY7oiEsly8KQvqGmsLC6kVSAS+Q9fXY8MgL6sGntrG66loZZbyQi21se/tU/1hJZZ8mwIUj4nQMLVZrzbNaq3qsg2CWd/A0TrXLXke/okJzMkNY3sShfRZgtV/gAVBh/OE7yuqSAIwsniwAk+wulLdHkfoDG7vL27VdxrVHR0jE6Z4ml+9MBfhRI4zzbgHGDEFNt4LXNqQMO7WQVJIujSQ2tbSuDLV7G3VkCRqFoRRKsGezsFf4FGxYIg0YM96OoPVC5+E9kWTcK5kzAkpSDHHvwzSb7HzY7dZfQojib4jRu9pJ6u/s5mXEk2XEtUZBsk/8OCpZl83BcN9xdqBCt0ct/eN8jV2kLG3FQOrelp1gmcE2RtVTFbKsqwG420dEbz1bbNlPq89IhP5JqWbYm1WI9r3IIgCIJwIokWyuNIiZCoWhsk7iITFYuCJP7djObR0QNgiJGQjGCIaNwESq+G4mkBAkWhxcuNyTKxFxhRXVDwiR/FJhHR04AkQf4HPiJ6GHD2M1D8nZW4v43AmDSXQP46vEXzsafWv+6Xruvo5Rrlqpf0CjvaUh9KFzPBOZ466yv9rUQmGYgaYES2gRIpI8nHfwea0P9RaAKSbAZfTqglt3qbhmQC460aDy6bR3ZlaH02GYk7WmfySGYiJTmL0YJF+F0OqvU4rFaxQKUgCIJwZjj+g9TOQLquo6p+lEidxFFmSn7w4+xlwJ+n4d6s4i/VUCIkLM2UsN1wGicY0P7addEQJxF3qULe+z4qFwUJluj4dmsUf+PHs1UlZpiRyqVBjAkyshXK59pwdPoHAN68+Ujmurdv1FQNLTuA79lizH6ZqOU66qpQQilF1f6Wk5sbUZoZUTb70KaWE5xcgbbeh+6qby/KxqMHdCQkyv8IUDzNT6BUJ/HvZqwtZUy94L38rJpkEuCJTu1oW/gDy6f/nezlb7Fr2eusnHY1ezZ8jc9TctzjFwRBEIQTQbRQNiJfdSlu127yts0CdBKbnYMlKonEf8RTvUZD03QiexowJUsYIo5Pi5xsl3B0VHAtDRJzTYCSb3T0OvJC9yqViO4GJCO41wSxtVaoylKRLaFtLGVHHJJp33aRuqqjezVQJChX8b1UCh6dCN0IyRqmMRZ0wPxwLMHfPKhZXjBIGPpZkTuY0V0aUqwCMmirfPhW+VD6WjBdFYkUeXzGUgardAo/9+NZvy+R9axX8WxSSbreTKm1ml/X7K4pS4+IpLWWy8atP9a61pbl7xKb0guz7dgXgBcEQRCEk51IKBuJ11PM+gUvk79jVs2xnes+I6XF+aR3GE1Ev0wU5fhP3pANElEDjGgWD36fC+/WuHrrendomFJkdD/IllCXvP7XSugR3UchKYZQ13aRirqgGnW1D5wyhoE2DEPtBKdV4dgKSqKBwJeVKF0saIoPqa0JUy8LWCTUzT58TxVDELBLGC90ILcxoS73om0OoBWqKMcroSzVwpLJGiqUzw3guMIYtufuZU2SyV3333qvt3P950TFt0VWDr5PuyAIgiCc6kRC2UjKC1ZjtsXR/bxX0TWVgp2/kbd9FrnbZhLXpA8mixNbZP1LJuR73GwqL2Wbq5yWzmhaOqNJstkbJDZDrIStnwd3USVIcXXONgdC+35rYG2tUPFbgIjuQaq3fIXznDswRDcDQM8L4n2mBDz7LuJf6cMwxIbxMgeSJON/rwKpiQFlqBUqddStAYILvKjrfBh6WzHdFo3/vTJw6wS+rMQ01ok00AYaoOroQR3J0Pitt56N9Xexe7M1YhQjyTY7eR43AJkRdsqry+s9x19dit9fhUWMpRQEQRBOc2IMZSPwVbuwRqTi8xSyYtZDZP36GAA9L3gTqyOZ3G0/4/dW1Hv+Nlc518/9iYcW/c5761fzwMLfuOHXmexw1X/OkZAkCWSNPUVzsbarf5K/tYWMruooVgnFqePs68fZZywR3UehWCPRPBr+T1xhyeRe6mofci8Lal4Aua8F041O9GKNwA9u1EXVYJMw3x6Nlhsg+HMVpuud8FdDZOC7SuTmRiSjhP/TSrRtAfRg4y9GIB2sIVEGyVfAhJ5deLtnB17u1gEUM9FJXeo9JTqxC5L4ERME4SByq/y8u7qQJxbk8O7qQnKr6h6b3lDGjBmDJEnceuuttcruuOMOJElizJgxNcfy8/O55557yMzMxGKxkJiYSL9+/XjnnXfwePZNskxPT0eSpFqvF1544bBj+/rrrxk4cCBOpxOHw0GnTp14+umnKS0tDatXXV1NTEwMcXFx+Hy1N+xIT0/ntddeq/Me2dnZYfGZTCYyMzN55pln2H/Rm3Xr1nHZZZfVPFd91xP2ES2UjSDgK2Xxj7cQ9FcCoKuQs+UHinMW0Xngv9m8/D2M1kiq3QVISBjNUSiGUDZT7PXw0MLfKPeH/5CU+rw8uvh33u5/LjENsCSN0eSgpHI1GUPK8O+MCW03uJ+oIQqaTyfxajNauUp8VxltCqA6MN5vBQvg1tDWHfDLzyJhujYS3a8T+KQSSQbDOVbw6fhfLwt1bQPqriDqwmpMt0WjrvUhpRkxPxMHXh29LLTPt7rDh3G4ncAPlZiudyLFNd63a6BEO+hC6rE3udleMYd1Cz/A5yvHZIoko81oWne7iYLseWhq+F6aJksU8U37YjTZGi1mQRBObTN2lPP8kjzU/T4vf7yhhEd7JXNh86hGu2/Tpk357LPP+O9//4vVGvp74vV6+eSTT2jWrFlNve3bt9OvXz+ioqJ47rnn6NixI2azmTVr1vC///2P1NRULr744pr6Tz/9NDfddFPYvSIiDm+zh8cee4wXX3yRcePG8dxzz5GSksKWLVt49913+fDDD7nnnntq6n799de0b98eXdf57rvvuPLKK4/4azB79mzat2+Pz+dj/vz5/OMf/yA5OZkbb7wRAI/HQ0ZGBldccQXjxo074uufiURC2cACPjc7131ek0zuz+cpxlOZS/u+D7F95WTyts8GICXzfDI6X48tIoUyr4897qpa5wLsqHRR5vM1SEJpsUTTvdu9zF9wL2fd8ALalmiCW+xINg3bWV5MUVYq50NUkyD6pHLUvetlKqAHQIJQV/kBDYemG5wEZ7rRdgRqjqkrfcgdTBhHRxKYum+GNAEIfFuJ8VIHwV/cKG3NBH6oQs8JglnCcJYVDBLG8+1ou4PIjZRQql6Nom/9KHaJ6GFGyn4OhJVHDFDZUfUZ69ZPqTnm97vYuPodNF8xvUe8x8ZFr1JWsAokmfgmZ5He/mpM1lgxflIQhDrlVvlrJZMAqg7PL8mjS7yNFEfj/P7o1q0b27Zt45tvvmH06NEAfPPNNzRr1ozmzZvX1Lv99tsxGAwsW7YMu33fkKuMjAwuueQSDlzGOiIigqSkpCOOZ8mSJTz33HO89tprYYljeno6Q4cOpby8PKz+xIkTufbaa9F1nYkTJx5VQhkbG1sTa1paGpMnT2bFihU1CWXPnj3p2bMnAI888sgRX/9MJPrjGpjfW0JxzuJ6SiXskU1ZOvMudm/6jmCgimCgil0bvmLh9LG4K3YT1FRGt2zL/Z17cF2rdsQfkDz61IZbSic6phVnn/UC63a+yzrDM5T1/Qpp6HrkZBeqVoakgb7GB/vlV1K8grR3joxdQu5mDnVPR8nIzY3ohWpYMrmXttaPJEuhmdz70XcHQZFQ2pjwv1ceSiYBfDrBeR6C06tABV1uvC5v1R2azV25JIhWpZM01kxkHwP2jgpxl5iwnuNiw8aP6jx3y+ZvwGimSeuRdDv3JboNeZG4Jn0x2+KwOY78F6sgCGeG6dvLayWTe6l6qLwxjR07lsmTJ9e8nzRpEjfccEPN+5KSEn755RfuuOOOsGRyf5LUMGPbP/74YxwOB7fffnud5VFRUTX/3rZtGwsXLmTUqFGMGjWKP/74g507dx7T/ZctW8by5cvp3bv3MV3nTCcSygam6xoGY90/fHGpvSjaswB/de31CX2eInK2zUSRYGN5KVM2rWVVSRF3dujKNZltADBIMk5zw31iVRQTZpOdzh1upGPba4iLTWPPuo+Z/+XlrF7yCPZhJWgrq8POMV7iQHL+lRT6dAz9bcjtTBgvjcA4OpLgkuo67hQSXFqN0qn2zHbJLhH43o2cacR4bSSmm50YLrRDhIy2I4AeBDmhERvTVWpaWiv+DFL6sx9TRw+OoR602Ap83nI0rfYe5AC6ruKqyCavbB1GWywWRxIxSV0xmp1I8vHfOlIQhFNDblXtD977yztE+bG69tprmT9/Pjt37mTnzp38+eefXHvttTXlW7duRdd1WrduHXZeXFwcDocDh8PBww8/HFb28MMP15Ttff3xxx+HjGXLli1kZGRgNBoPWXfSpElccMEFREdHExMTw7Bhw8IS48PVt29fHA4HJpOJnj17MmrUKK677rojvo6wj+jybkB+r4uAv5Jm7S5nze9P1yqPSuhIwc7f6j2/aOdvtGo2mLvToilSE/jftt08uWwBt7TrzDnJTUiPiCTW3HBb+gUD1Wi6F7+nhD2bp6NrAZpkXky7Xg+yJet9tq58j5Zn3wGzQmMaDRfYUTqGEkItL4jvxRL0cq3mesarIuBgk2eC1Ey82UtqYgh1a19kRy9UCf7kRnepyC1MmMY6Uf/woO0KYGh96F80R0syhWa+B0t0HEOrqU5fzW+b38TnqyAyMo3uSfcd9HxZMbJp8xdktBgOyBjNkVgdCY0WryAIp74Ux8F/pyUfovxYxcfHM3z4cKZMmYKu6wwfPpy4uPqXkdtryZIlaJrG6NGja02IefDBB8Mm9ACkpta/msleh7sDtKqqTJ06lddff73m2LXXXssDDzzAE088gSwffhvZ559/Ttu2bQkEAqxdu5a77rqL6OjoI5pEJIQTCWUD8ntL2bjwNTr0/yfxTc+maPf8sHJbZBMMxvonaShGOyb85M5/HE0L8kS/J3hzj5Epm9bybv9zSbI5sBga7r/MV13CpiVvUbhrX5JbuOsPnLHt6dzvP+Rmz0A/P4ClSzyeZIliJcja4mI6uRzEvu0JSyZxyugGULpZCP7orvv5OpsJLtivBdMIxr9FgAzBRV601ft+OWkb/fg3+THdFoWu6cj2Y2vt0zwaVGrg18EqIUUpSAYJLaDjz9eIGWbEtcxPeco8Nm/5jM5dbkMNevFUFxMMeOh39jMsXfIi/gPGxkZENMXjKaRps8FYLXHYHIlIkmj4FwTh4C7OiOLjDSV1dnsrUqi8sY0dO5Y777wTgAkTJoSVZWZmIkkSmzZtCjuekZEBUDOZZ39xcXFkZmYecRytWrVi/vz5BAKBg7ZS/vzzz+Tk5NQaM6mqKnPmzGHo0KGHfc+mTZvWxNq2bVu2bdvG448/zvjx47FYLEf8DILo8m5Q/uoyygqzKM5ZSkanv9N1yAs0bfM3mrW9gm5DXybgryKlxfn1np/S4jw2Ln6DjE7X4a8uYevc+3mqXQbXN08jqOvENOA3ua+6jIriDWHJ5F4VJeso3PM7TZtdg66oVGXKfJqTy5U/L+ffSzajuTT0Pfu6gI2XOjBdGYG2wofS3owUXfvbSko2oHQ0I8UoSM0MKENsmJ+IQ93kA1nC0N+K6Y4olL7Wfa2YOgSmVyGnH9snda04iP+9cryPFOF9vBjv08Wou/1o+UH0giCSWyNYrhPxtwq27ZlGt+73sGTxCyxYMJ6slW8xe/ZtrF/3If3PeRGDYd8vUYslml69H0GWjfTq9TD2iGSRTAqCcFhSHCYe7ZWMcsAwREWCf/ZKbrQJOfs7//zz8fv9BAIBhg0bFlYWGxvL0KFDeeutt3C7624kaCjXXHMNVVVVvP3223WW752UM3HiRK666iqysrLCXldddRUTJ048phgURSEYDOL3N+6yTacz0ULZgGRDKOHbsOglegx7g10bvkWSZXRNJWfL96hBL93Pe5WEtHMo3Pl72LkJzfqj6xoluUto0WUMALoWpGDrDM6Pa4/VUPcYvqOlBqvJ2fxDveV7dnxJtGkgtowYNpRXMXnDvi0H5f2G9hgG2dA9GoH/hWam+/PLQ13Vq3yoK7ygSBgGWFHOsqJLYLwmAtw6ugEwS8jRCr4XS6BKByMova2Ybo/G/24ZBAglrsfw862Vq/j+W1Yz2Ufub8Y0PJLA91X4F1eHuuEjZByXOAgEzLRrfw0LFzyFz1cedp2ysk1s2vQFQwe+QV5xFs6oFjidzVEUC8nJfRpscLogCGeOC5tH0SXexvTt5eRVBUh2GLk4I+q4JJMQSqI2bNhQ8+8Dvf322/Tr148ePXowfvx4OnXqhCzLLF26lI0bN9K9e/ew+pWVleTn54cds9lsREZGHjSO3r1789BDD3H//feTk5PDyJEjSUlJYevWrbz77rucffbZXHPNNXz//fdMnz6dDh06hJ1/3XXXMXLkSEpLS4mJCW0kkZOTQ1ZWVli9tLS0mn+XlJSQn59PMBhkzZo1vP766wwaNKgmVr/fz/r162v+vfd6DofjqFphzwSSfriDF84QLpcLp9NJRUXFIX8IDuRx5bB05l24K3aiGKy06/sA6FC0+08kxUhqy+FUle0gJqkbHtcuivYsBCTim/bF6y5g05K30PUgPS+YgKt4A5uWvkVck7NI7zAar6eI1MzzURpgGRpPZT4BfwUbF/2XktylddaxRTaha/f3MMVH8tDKbSwrLK8p+6BrJ1Jf9IAK5nuj8f23LPxkCeROZpSeFpQ2plCrpCyhlasEF1ejLqhGilKQWxoJflV7iSS5rQmlnZnA15UggfmpOOQo+aj29FZ3+tHW+5HiFDCCFK0Q+NCFtrX2gHfD9Q7yMpbw+28P1nktSZK5sP9ryLvXE9X/5iOORRAE4UQbM2YM5eXlfPfdd3WWX3rppURFRTFlyhQA8vLyeO655/jxxx/Zs2cPZrOZdu3accUVV3D77bdjs4WGcaWnp9c52/qWW27h3XffPazYvvjiCyZMmMDKlSvRNI0WLVpw+eWXc9dddzFx4kSeeeYZCgsLa3WL+/1+EhMTeeqpp7j77rvrjeXDDz/k7LPPDlsaSVEUkpOTueCCC3j22WeJj48HQgug719vrwEDBjBv3rzDep4zjUgoD3AsCWXAX43HtYslM24n8FcLl8WeRFxqHzI6X4erZCPr/vwPvS6cwNKf7iI6sRMApfkrCPhC6zNKkkKPYa/jKt1EQfZvOOPb4q7YRXqHa3BENccWkXxMz+f1FLNrwzdY7PFoqp/1C/5TZ7309lfTNO06lOhIbvx9HdmufTsiXNwkgdt2JmBeGcAw0Ebgi9prbu5leSEeOSnUEK7lB/G9UYZhiA3JIeOfXAHeur/9zPdG43uzDKWTGamDCUM3K3L0kSWUukdD3eQn8HUlcqoBw0UO9EIV/xtlddaXUhXyb1jG/AX/qvea5/f9D1avD0eH4UcUiyAIgiCczkSXdwPyuHax5o9n6Nj/MbyeItwVO7FHNiMmuRsbF7+O111AzwveoKxgNYlpA9i96dta12jS+hIkWUGSjDRtcwkWWwLL1t9LVEJHHFHpxxyju3wnsmzAVbyB5IzzcEQ1p6p8R1gdsy2OhGZnI1s0DGYTXeMjwxLK6XsK6dEpip6JNgy1d72qnwx6aRCljQm9VK03mQTQilWkJgYMFzgIzKpCOuvId5xRN/nxv16G4Twbkl1GL9PQ8+sfOqDnqzidGfWWG40OFF3C0rTbEcciCIIgCKczMYOggXjdRayc8zCu4vWsmP0gO9Z8jKtkM9lrP2XpzLtISh+Iq2QTaqCa9Qv+gzO+HS26jMVgCm1LZTBFkNF5DFHx7Vky43aqK3cTldCJHWs+RtdVgn43kqSgqUc/ltLrKaG8aC1edz5+bwUBv5vWve4io/P1WCNSsdgTadb2CjoNGE9F0UYMZgsmReaqlqmYlfBvlSfWbeZZw07kTua/ts2pTc4wIjn2O08Bw2URaJUqRCv1ngcgJSoYL3Hgf68M44gIJNuRfatq5SqBj12hxddbmgh8VwV+DSnqINfRwaREk5jYs87iDh3GYotvjcF5bK3EgiAIZ5Jbb7211vqUe1917SkunJpEl/cBjrbLu6J4I39+O7re8m5DX6EsP4uohA6snBNaDLbL4BeQZQO6rqKpfnK3/kTRngU15/S/7HP++HY0aEF6XvAORrMDr7uQypLN2CJTiU7qgsWWiKwcvKFZ04K4ijcRDFQjK0bcFdlExGRSUbSR8sLVeN0FJDQ7GySF0txlVFXspPvQV3BEhQYwB1WNLRVuXli2hc3lodl+7WMieKhbJmmrQSrSai8VZJYwPxKD0nzfmE+tOAhBHTXLh16moeUG0dbU0cQZKWN+KAb/hHJM10eGduIxH2FCmRfE+2gRygArVGioWT5M90UjRSv4XigBd/i3vdTEgDbAQl43qPYVU7b9A3Znz0DTApjMTjLa3IA/qj+dk1NxmMR2ioIgCIersLAQl8tVZ1lkZCQJCWLd3tOB6PJuIGrAc5BSCasjiUJ/Fbq+b+tEWZZZMfuBes8qzc+iSeZwqqvysDoSWP7LONwVu/adr1jodu6LlBetwxnXFmdcGyz2fT+YmhrE7y1FDXopL1pHdGJntmVNpiR3MQZTBGltL6dZ2yuorswhf+evqIFqkpoPITO2FT5vOQ5CCaVBkWkbE8Fr53SgMqAiAZEmAxEVEt4pRRiG2zHdFoW6sBq9QkNubkTpZkGv0sIfSAW9SEXbGsBwjhVDPyu+MjVsCSLsEuabnOiyjvmhaOToo/wWVQAJpAgZde9WkFUagYUeTDdG4X+/HDw6UoxM+Y12VlDJn+V7uNifyEMLcji/6WWcd85VyATwaEY+zvaydPMePh6WKBJKQRCEI5CQkCCSxjOASCgbiGywoBgsqEFvrbKEZudQkP0rezZ9S1xKD4zmqL8m7Rx8qRldV0nKGILZFs/Gxa+FJZMAmupl5dxH6TLwGZb/Mg5HdAbdh76KYrSj60F2rf+KXRu+BEmh6+BnWTj9BjQ11CIY8LnYuOR1YpN70rbfQ2TGtMBgtON1F7J56QTa9BkXuodfRw/oyBaJaIuJaMv+9w8lgsEf3WCXUHpYkFMM6LlBfK+WYhzr3PcsAR11tTe053czA77Xy8AiYboiEmwSepkaWmw8UUHLCSDHKkefTBJKJJVuZvQCFTnNiLorCBYZbaGPoFGi8uEIKFTxpSm8smE7/VNiuSA9gapAkICm8/3OMr6vY3vYXLeXGLORSHPj7mIhCIIgCKcSMYaygcgGKxmdb6izrHnHa8he+xkA21d/QMf+j6EYLFSWbcMZ36HOc5BkImNb4SreRMBbTuGu+XVWUwMedD2I1ZFCTFJ3PJU5BH0uNi97h21ZEwn4XDRpOYLtq6Zii0ihVY/baNf3IZq1vRyD0U5J3lKqSreQt30W2Ws/YdH3Y3HEZGKUEqjeppL/gY/c93yU/uQnUKyha/t1FdskpOS/Zl67ddTfqgnOcKNm+UADpcW+pEuvUpGbGZGiDUhNjCj9rODV8U+pwD+pguA8D1gk8OrITU3Isce2M45klTFeFYm2O4ChlxWMsHdLCsmlMzE3hy+Mxax2V3JOaiyfbs7h0QXrsR5kJyKTLOFXNcp8jbvHriAIgiCcakRC2UDMZicmSzSdBz2D3dkMAGtECm37jEOSDQQDofUWXSWb2L56Kl0GP4fJEk2b3vdgMNprXa9l138AEtuyJqIYLED9Q139vko6DXwKr6eQlbMfZunMO7HaE+ky+HlkxUxUQgcS0gbQrO3l5G2fzdaVE/G6C+ky+DnimpxFad4KygtWk9DsbLoNfYW41POoWmAg5y0vnnUqvt0aZXOC7Hq5Gn/Bvm5s2algut4Z/l1kllB6WjDe5ISoUFKolakEvq7E959SfM+U4J9QBiqYbo4KdU17dfQ8FfWPakhQkJsajnjMZF3keAPmh2PRzWC+Ozq0BYVNQtsTpF9kFP1SYijx+nl5xTZy3V5UHba73HSKrXvs7GWZKfy6pxiXv2EXmRcEQRCEU53o8m4gZlsMCWn9yds2i65D/kMw4EYNelEUM0ZTJAZTBMG/9oEuL1zL8l/uw+5MJyqxE30unkTO5u8pL1qL2RZPSsZ5yAYzezZ9hxr0IstGTNZY/NUldd47MqYli2fchhoITYwJBqrYuvL/iEnqRpved2O2xVOwcx65W3+qOadw1+8U7V5Al8HP4q7YSWXZNiqKNxKbdg5Gdzx5s9Ra99F9UPS1n8TrTBj/WmRczjBiHh9H4NtK5GQDcisT6jIv6sJq8GjQ1ULgUxfq8v0m36ig/lkNQR3DIBvB2aHxp3qJimSSGnTXGTlaqVm/UnWpGEdGEPjYRWu/A5dR4qONe8LqT1m/m6f7tGba9nz+zCtF08GsyIxonsglLZJ4ZP56bIZjaz0VBEEQhNONSCgbkNWeQFq7y/F5ipGNVtBCLVl+n5vmna5ly7J3wuq7K7JRgx6atr6UZm0uJyFtALJsJOBzsWv9lxTu+gOAgL+SFp3HsGHRK7XuGdekD5Vl22uSyf2V5q+gWbsrQNfDksm9TNZofH4XMc36YYlOx2yJJjd3AUkll9T7jN5tGp7yEgK+YiLsTTG6rUiA6YoItFIV/9vl4Am1pmpr/chJhvBkcj/qEi/me6JrEkrpKGZzHwklUoEuZoyOSJzTPJTdZaEqEJ44e4Iqjy3cyMUZSUw6twvF1X7irWYqfAHc/iAP92iJSRbbLAqCIAjC/kRC2cAUgxlbZCqq6sdbVYDHtZuArxKzJYZmba9g96Zv0f9KNCNiMuky+Dm87qJQC2PQTULaINLbX4nBFInJGovRHIGmBjDbYmnf71G2r55KdWUuitFGk5YjaNb2cv787tp64ynNX0l0Qu1xmnZnOq363sfyrLcoW7IJAJMpgo4db4LESqD+JZO83lI85Tux5ycRcJaj20Itr7IUiemJOIIlO5E0oNiO7jvIqlR6aLIOAAYwDrEhGRs3WZOjFAqarEa5qT1mqe7k1adqfLkll7OSonls4Ub+3acND/25nq7xTq5v24SALlooBUEQBGF/YgxlI1EUE3ZnU+Kb9iW+WX9ikroS3+Qseg9/j94j/sfZf/uEXhe+Q0R0C2JTenDWJZPoN/Jj2vS6E2dcazqc/Shnj/yIPiP+R0KzfkQndsHj2k1Gx7/TdciLdDz7MdSgHx3toHEYDFaQaidALXvdwR9/Pk5Z6aaaY35/JcuXv0q1LRtrK7nOSejmdPDq+SRVd0NvtoXiJTdR+MPfQ685N+AvWIJucFPw499xez9Fij/4t5hklJDildAYx/jGT9Qko0RB8UqKpXxQoF1MRJ31nCYDlf4gPlXDr2lIwMqiCna6qjErCp6AGEcpCMKxK6jU+HCFn5d/8/LhCj8FlQf/nd5QFi5ciKIoDB9++NvIZmdnI0kSWVlZjRfYX8aPH48kSbVes2fPrqnjcrl4/PHHad++PVarldjYWHr27Ml//vMfysr2bbE7cODAOq8VDAZr7tWmTRvsdjvR0dGce+65LF68OCye/c+LjIykZ8+eTJs2rdG/DqcSkVAeB0aTDUd0cxLTBxCT1IXY5O5ExrbGbI0BQJYNWO0J2CJSao4ZjFYs9gTM1lgArI5EWnS9kdjUXhjNEdidzcjs9g9kxUJK5gX13jsh7RysjiTYrzXO7kzH5c7F99d+43s1b34hg/+/vfuOjqJqAzj8m63ZZLPZ9AKpJKGE0HsTFSmCBRGQjkFsFFEEBAsIAioo6Cdio1nBAhZUEAVEpZcAgdADoSSk983W+f6ILCxJKJKA4H3O2XPI3Dt33tmF8O5tc8fbFBaewHTnGowjMvBof34bJEkDHt3ycfOIxBFeSNZ3o7EXZTrLHSU5ZP08FoWHjsBen+GeOQjHQStSeMUd4YoYNRgUqLp7INVQodBcn7+OAf4NyDn5M7mlZp5tUgs/N9d9Jd2UCp5rFsNnB0+hkMBNqXQuifr1ZCZmm4NVJzIpEkmlIAjXYO0RK4+vMPH1Xit/HLfz9V4rT6wwsfZI9e8ksWDBAkaNGsWGDRs4c+ZMlbZtsViqpJ24uDjS0tJcXh06dAAgJyeHVq1asWjRIp599lm2bNnCzp07mT59Ort27eLzzz93aWv48OHl2lL9vatHbGws77zzDnv37uXPP/8kIiKCzp07k5mZ6dLGokWLSEtLY/v27bRt25YHH3yQvXv3Vsm93grEkPdNRKM1oNEaXJ7pXVCQSkBUJ3LO7KCk0HWBSWTDoUhKDdmnN1O72ZMc3PYOAO6GmuTkHXWpW6dufzRqPevWjUGWz39DjotNIKzPQ1hPqvHuoOVg+s+ovO7Dsf095xxRF7KDgm2fYHAbCykydq0JzSADloUFyGfO15fCVKjv9cS6ohBNXwOS9/UbRjZ6x5K5ZSbxoXeicovkfx3rsz+niOScQoLc3Qg36FiSfJJDecV0DvNny9nz33TNdgeSJLMxLYeG/gb0XuKfkCAIV+9soYP/bbTguGhWkF2GdzZaiAtUEuhZPV+yi4qKWLZsGdu3byc9PZ3FixczadIkAHJzcxk5ciS//PILRUVF1KxZk0mTJvHwww8TGRkJQOPGjQG47bbbWL9+PUOHDiUvL4/mzZszb948tFotKSkp7N27l6eeeopNmzbh7u5Or169ePPNN9Hr9VcUp0qlIigoqMKySZMmkZqayqFDhwgJCXEeDw8Pp3Pnzlz8EEB3d/dK2+rfv7/Lz2+++SYLFixgz5493Hnnnc7jRqORoKAggoKCmDZtGm+99Rbr1q0jPj7+iu7nVif+N7zJubl5c+TId0S1HIGtJJvcMztQaz3xC++AQuXGwa1vYSpMo37bibS9/1NSDyxHoVAjGc8/j1qt1hMQ0JgNv48r1/6+Qwvx7xiPJsqLbE1N3MJ6s/PUaW7PPFRpTNbMQ0h3F2P23Izp5DqUh2piHPkEUokncraM5K8EtYScZUfZQgfuCqTruNDFwyOAOzq9x86dbxPecAJHCx346zSYDe78kHKW5NwiQjy0PBEfTm1vPR8knUCibOOmO0P9mLPrKEPrhbMmNYNa8ZHXLW5BEG4dvxy2lUsmz7HLZeWDmlTPU7m+/PJL6tSpQ+3atRk4cCBjxoxh4sSJSJLEiy++yP79+/n555/x8/PjyJEjmEwmALZu3UqLFi349ddfiYuLQ3PBU8N+++03DAYDa9asAaC4uJguXbrQunVrtm3bRkZGBo888ggjR45k8eLF1xS/w+Fg2bJlDBw40CWZvNA/3S3EYrHwwQcf4OXlRcOGDSusY7PZWLBgAYDLe/BfJxLKm5xG40lsbC+OH/+FM2c2oXPzxc3NHYvDgmR1EFznflRqd/xDWwMQ5/scssNGiSmTxMR3sdvNhIZ25HhK+VXg5+xP/oSWrSaTk38MmzacY8V2OnqHQdq+CuurvMMoPvwthZuX/H1kKyW7l+PZaCg6c28cH8qo2rkjBSmxLi3EXkuN9ilvJMN17KX0CqVx8+dRWYpxaOGsXUmUlzvTmkdgdBRRYFeRapbYmp5LhxBfHokLZ8fZPOp4ezJ/7wl83dJoE+Rz3eIVBOHWcrm5khkXP7q2Ci1YsICBA8sWc3bt2pX8/Hx+//13OnbsSGpqKo0bN6ZZs2YAREREOM/z9/cHwNfXt1xvn4eHBx999JEzwfrwww8pLS3l448/xsOjbK/ld955h3vuuYfXXnuNwMDAy8a5d+9el97MevXqsXXrVjIzM8nLy6N27dou9Zs2bcrBg2XrAu655x6++OILZ9m7777LRx995Pz5scce4403zu+csnLlSh566CFKSkoIDg5mzZo1+Pn5ubTfr18/lEolJpMJh8NBREQEffr0uex9/FeIOZS3ADc3P5BlwsLuIDSsIzqdL7t2zWPDhnFs+Ot5VNrzC08UCmXZSnT3IO7sNA+NxoBW64XJlFVp+6aSTNLT/mL7+sexW/L49Uw+tgZ9qOzRkZ5NelGUuLzc8cLExUixeQBlT8ZRlT1px3HUipx/fSaiX8igUmJa8yruXyUQcWwlNS1n8Ty+ntyCfMbvOM2YjYf55mg6KbkF7EtLo0OgnppyPi/U9+d4oYl4L/H4RUEQ/pnLDWcH6Kvnv+eDBw+ydetW+vXrB5QNK/ft29fZ4/bEE0+wdOlSGjVqxPjx49m4ceMVtRsfH+/SW5ecnEzDhg2dySRA27ZtcTgczqTvcmrXrk1iYqLz9c0331yy/ooVK0hMTKRLly7OXtVzBgwY4NLWxIkTXcpvv/12EhMT2bhxI127dqVPnz5kZGS41JkzZw6JiYn8/PPP1KtXj48++ggfH9GxcI7oobwFqFQaIiI7s+rnh8slhjVr3obBEF7uHKVShY9PXdp3eBWFQolCoSIzc0+F7fv61Scrq6w3Ujal4u3mxafpMoO7TcXx20xky9/7SKrc8LprPKbDfyCXFlbYlinzd3SdH8T+kwXb+hJUbdyxflOII9uOIvT6JmiO0gJKj20CZKTNH6ALjCA/NZHPzTEcKTDRJcRAQk0V6qRvkI6mIKfH4NXkQVqd/pH4uF5oCk+Bt/hlIgjC1esco2JFkvXcE2FdKKWy8uqwYMECbDaby1CxLMtotVreeecdunXrxokTJ/jpp59Ys2YNd955JyNGjGD27NmXbPfCxLGqaDQaoqOjyx339/fHaDSWS0zDwsqeUufp6UleXp5LmZeXV4VtnePh4UF0dDTR0dG0atWKmJgYFixY4JJ4BgUFOessWrSIu+++m/379xMQEHANd3nrED2Utwi9vgZduy2mUeORePvUxj+gER1um0Wr1s+j+3ul+MVk2c6ePR+w9renCApuiUrlXq6OQqGmVq0epJ4o26ohNfk9JsT7sup0IbPyQsh7YAHSg+8h9ZqPfsjnaCNaULTr60rjdJjzcTQ4htQC5Fw70t/f0iXjDfir6HBw7pGWuugOlCSvwRbfi59O5dPYV8+jxkxYOhTr3u+wnN6Ddfc3ZC0ZhFuNeDySv0VTmHb9MrJ8uwAAZwJJREFUYxYE4ZYQ6KlgZBsNyosGepQSjGyrqZYFOTabjY8//pg33njDpbdu9+7dhISEOIeI/f39GTJkCJ9++ilz587lgw8+AM7PF7Tbyz9J7WJ169Zl9+7dFBeff+jGX3/9hUKhKDdUfbUUCgV9+vTh008/rfIV6uc4HA7M5oofygHQokULmjZtyvTp06vl+jcj0UN5C9HrQ4iLG0JMzANIkhKttuI9Fs9Rq92pWbMDmRmJ7Nr1P9p3mMnePR+SlZUEgLd3DM2aj2Pvng+x28v+YRXkp+B7aikL7hzFD8cz+eBECSEeXnSs6UepyUoD2YRbZCtKUzZVeE1ddHuyvh1HQLePkIu8caTbkIKVSMbrM3+ywGzF5pDRa5Qo3fSog+pgTT+Awt2INfMoNq9QzPYkHo3ywL5iDMgXDcU7bOT++gbG20eh9q6B7LAhKcQ/I0EQrt4d0WriApX8cthGRpGDAL2CzjGqalvdvXLlSnJzcxk2bBheXl4uZb169WLBggWcOXOGpk2bEhcXh9lsZuXKldStWxeAgIAAdDodq1atombNmri5uZVr55wBAwYwefJkhgwZwpQpU8jMzGTUqFEMGjToiuZPXs6MGTNYv349LVq0YOrUqTRr1gwPDw/27NnDpk2bqF+//AM9KlJcXMz06dO59957CQ4OJisri3nz5nH69Gl69+59yXPHjBlDz549GT9+PDVq1Ljme7rZiR7KW4xCocTNzXjZZBJAkhRERHRGqzWSk53M5k2vUKNme27rOJtOd82ncePROBx2zp7d5XKeb3hPnliXRGqhiVBPHXlmGxP+2s+kLYfYU6LC0HYYklpX7npuUW3KjjuslOZsQ93LE/tRC9oxPiiqOaHMKbWw7lQmz/yxj8fX7eGd3cc569Dh03kiKDXYsk+gq9WOAouNGC8PfOxFyOaiCttyFGeh0LiD7MBeWPncU0EQhMsJ9FQwqImGsR3cGNSkenomz1mwYAGdOnWqMAns1asX27dvR6VSMXHiRBo0aECHDh1QKpUsXboUKJtv+fbbb/P+++8TEhLCffdV/phed3d3Vq9eTU5ODs2bN+fBBx/kzjvv5J133qmSe/H19WXr1q0MHjyYWbNm0aJFC+Lj45kyZQp9+/blww8/vKJ2lEolBw4coFevXsTGxnLPPfeQnZ3NH3/8QVxc3CXP7dq1K5GRkaKX8m+SfPFmTf9xBQUFeHl5kZ+fj8FQ+eMHbyX5+SfYuXMup0/9gSw7CApqQbPmz6LR6Dl0aDmlpiyOHPkWAB+fuuRHPs//9mVX2FakwZ3ZNfPx9nCnOOlHzCd2oHDzxCO+BypjTSStHrm0AGveKdTeEaj9o1EZA6u1ly/PbGXurqOsTj2/SW20QcfoGC/idBYU1lKQJJQevryfaqFBgA8RJSnw9WOVtun3wCyUXjWQzUW4hTetttgFQRAE4WYgxuoEvLzCadv2FSyWfAA0aj0abVkyXbv2g5jN+Wg0Bg4d+hoPjyC2X7DepkWgkfuiyva0VEpQZLUhKdzIXPYI7nXuxLNFf2RrKcX7V+N790vkrJqO5UwS2rCmKOq6I9tKcNii0fhFVltSebbE7JJMNvL14IVwB/KPI8kq/ruHUaHC976Z+OpqEaZT4akJpEitQ7aayrWn0HmhcPdB4eaJrYJyQRAEQfivET2UF/kv9lBeTrbJzNrUdOp52gh0V/PrWYm3dh+nV3QwNTzc+GhfKiW2skna/joNU1rEErThFWxH1pc1oFDh02MK5uNbKdm/Gp8eL2M9e5DipB9xmArQhjXG67YRqH0jUajdqjz+j/adYMG+VOfPn7QKQrtsKLKt1KWeKrAOtl7vg7WEpceyGaY5RPHPUy9qTcKnx8uojDWR7WZUhmDUPqFVHrMgCMKt7FJPy/n5559p3779dYxGqAqih1K4LLsM7+07TYnNznPNoon0cqOGhxsN/bx4afMBl7qZJgtP/7GPRXdNwbfFEbBbUHsGoDAXkrPvZ7zvGEPRjmWYT56fl1l6bBOlx7cROGgh2pBLz1n5J9QXPIWnrrcet1ObcVyUTCr9Y8i+cxrLk0/yZKiS0yUWPiOKB3p/gHrnx9hzTqDyr4V7i6FkuwVgSPoKW95JPJs+JBJKQRCEq5SYmFhpmVjgcnMSCaVwWQaNirsjAvBSWghQFhGkhplt6vLGrqMV1rc4ZFanZlFg9qBXdAwJvyXy0+0R6KLaovTwc0kmnRw28tbOwfe+mag8/as0/nbBvry39wQAATotHpKM5p6pSCot1txTFCUux97+acbtOkuJzc5jIT48FuXJo1tO8+MZFfdGPUrNehLHTQ627jMzu7kEsg21Xy2QL799hiAIguDqUntCCjcnscpbuCyFo5QBNYqpmT6HExuHseevMSjzNtG9ZvmV3OccyiumXQ1f8ixW3mgfx/KzdtbXH4kpbX+l55hP7sJenIXsqNokzd9dQ7/YGmiVCoZGuIMpl5xfXidrxQRK9q/GePsoMnTB5FtsWB0y24sUeB/+kXeahxDkruXTYznMSs4mo9TBq01D0GyeT+GWT1B5BUM1DNELgiAIws1GzKG8iJhD6UqWZU6eXM/v68eWK4uuO4SN3MHXKXnlynrHhNAjPIAjBSVM33YIhwxxPp68rNmB/a93K76YUkNQwuegVKHU6lG6e1fZfeSZrViLcrCteglr6nbXy+r9ONB9AS9sTwHAXaXknWaB+B34GrMxGotPLZQSeFrzURdnkPvLqwBoazbCp8fLqL1rVlmcgiAIgnAzEj2UwiWVlGSwdcvMCsuOHviErjW05Y6rFBJtgrxBkpjxdzIJcDC3EK/Yyidae8R1w2HKw557CntJPrb89Cq5BwCjVo3enFUumQSwl+QRqrY6f9apFCTmWVA16ktARANCNA78zJnY937rTCYBbIVnkZTied6CIAiCIOZQCpdksRSUez74ObLsQG0+jb/OnUyTBQBvrZoxjaLILrWQWmhyeU5tY38DlpyTGNoNp+BP101nVd418WwxkPTFA5EUKvRNeqNv1BN7cQ5Kj2t/XrYsy5Sc2FlxocOG+6mNtAlqgFK28VSohOKvNyj8cRdFah0e9e9GF92e0pOu52uC6qFwu/wG8oIgCIJwqxMJpXBJknTpJ9i4aXRMaBqN2e5AKUmY7A62nc1hUJ0wfjvlmoj2CXGj5KcZuNfphP+DczAd/QtHaT7a0CYodEZKDvyGNqgu5lOJFG5ejL0oE692j1ZJQplbasWkrjz5c/w1n+ce/RFlXipFXzyC3WEDQLaaKNr1DebTe/C+8xlyfvp7GyFJiVebYWVPzBEEQRCE/zgx5C1cklKpwds7psIylUqHTmsgWmeiwGLjQG4RGoWCJgHeZJaWEuHpmmzp1QocpnyKdn1N5ooJ2PJPIzscFG77jOzvJmLPP42kPb83WUnST9hyT2LNOXnN91Fks1EaEAeVbJ7uXqsdXrZ8rBvehr+TyQtZMw6DpEDh4YfSWAP/Pm+h8o245rgEQRAE4VYgEkrhks6m76RR45Go1a6b0EqSkubNx7Frx1w2rnuCOh4mNqXlMH3bIaZuPYRSUuKv09DQ7/zCpuRCK+oa8WU/2C2UHtuE6eBv2HJPAaAJqY8168KtiGQcpQUUbF6CrTCTa6FWKFh0vBjV3dPgol5XlU84Hg3vRXLYMZ+sZFgcsKTtI2DA+/j3fgt1UB0U6vLzRwVBEK5GfoGDvzZZ+Gl1KX9tspBf4Kj2a6anpzNq1CiioqLQarWEhoZyzz338Ntvvznr7Nq1i759+xIcHIxWqyU8PJwePXrwww8/cG4t7/Hjx5EkqcLX5s2bK73+lClTkCSJrl27liubNWsWkiTRsWNHl+MFBQW8+OKLxMXFodPp8PX1pXnz5rz++uvk5uY663Xs2LHCeB5//PErfn/WrVvH3Xffja+vL+7u7tSrV4+xY8dy+vRpANavX48kSeTl5ZU7NyIigrlz5zp/3r17N/feey8BAQG4ubkRERFB3759ycjIcL4Pl3oBFBYWMmbMGMLDw9HpdLRp04Zt27Zd8f1cL2LIW6iUw2Hl5Mm1FBen06HDq+TkHiIzczd6j2BCarTl8KHlnD1btsglI+UranrczcG8YqBsYc53R9MYUjeU7Wfz+D4lnS9OFHJHu5Gw7DHAdXMBlbEmCjdP7PlpLscltRsl+1fhUa8LjtICNP61/tG9+GhVDI4yYsYT74QvKTm5C7KOYavZFHwiKNgwB++OI5A0HsiW4grbUOiMIDvA4UBVhSvQBUH4b9qfbGXNWgvn91qxs2OXlU63a6hXt3oW/B0/fpy2bdtiNBqZNWsW8fHxWK1WVq9ezYgRIzhw4ADfffcdffr0oVOnTixZsoTo6GjMZjMbN27khRdeoH379hiNRmebv/76K3Fxrg+l8PX1vWQcwcHBrFu3jlOnTlGz5vmdMhYuXEhYWJhL3ZycHNq1a0dBQQHTpk2jadOmeHl5cfDgQRYtWsTnn3/OiBEjnPWHDx/O1KmuTzlzd7+y6Unvv/8+Tz75JEOGDOGbb74hIiKC1NRUPv74Y9544w3efPPNK2oHIDMzkzvvvJMePXqwevVqjEYjx48f5/vvv6e4uJhnn33WJdFt3rw5jz76KMOHD3dp55FHHiEpKYlPPvmEkJAQPv30Uzp16sT+/fv/VZvAi4RSqJQkqdDra3Lq1AaSkz8nMLApapUH+fnHOXjwK+QLNvU+c3wld7W6n99Og6dahSzLdIsIxCHL3B0RQD1fTyTgoN1M44fmU/Tr61izjoFChS7mNvSNepK9crLL9VXeNbEXZoIkIct2Mj4bTuCQj1G6e6PQelzxfdiKszHvX43HpiU4irMwBcSgbDeSjbr6fH48j8lBPsTc9gQOayke9e+maOdXFbbjHtsRSa1DZQj6R++nIAjCOfkFjouSyTIOB/y6zkKNGkq8DFU/iPjkk08iSRJbt27Fw+P879G4uDgSEhIoLi5m2LBhdO/eneXLl7ucW7duXYYNG8bFuw36+voSFHR1vxcDAgJo2rQpS5Ys4fnnnwdg48aNZGVl0bt3b/bvP79n8aRJk0hNTeXQoUOEhIQ4j4eHh9O5c+dy8bi7u191PACnTp1i9OjRjB49mjlz5jiPR0RE0KFDhwp7JC/lr7/+Ij8/n48++giVqizdioyM5Pbbb3fWufARlEqlEk9PT5fYTSYT33zzDd999x0dOnQAynp4f/jhB+bPn88rr7xy1fdZXURCKZRjs5ViMmVjsRRQK/oeDhz4AoVCRX7BcVJSfqrwHLvdiurv7vmh9UL580wOP6ScpUt4ABqFxMcHTjnrTm0VS6MH3sbgMKOQQKVUkvnlUziKs511FO4+eN81npzVM3Gv0xlJ447DlI/p4G9Yc0+hi26HNrg+Sv2lvwXbTfnkrZ1LSdL5uK0Zh2H5U9x+70zadeyAt5sGpRyNLT8NXe07MJ/ei/Ws6yMlvTqOQtLqUXsFX/X7KQiCcLGkfbZyyeQ5DkdZedvWmiq9Zk5ODqtWrWL69OkuyeQ5RqORFStWkJ2dzfjx4ytt59xQ7LVKSEhg/PjxzoRy4cKFDBgwwKWOw+Fg2bJlDBw40CWZrI54vvrqKywWS6X3fmGv7JUICgrCZrOxYsUKHnzwwX8Up81mw2634+bm+hANnU7Hn3/+edXtVScxh1JwUWrKYe/ej/j+uwf4ZfUwMjP30rrNS+TkHCQi/K5KzwsJ7ciBApjeug5RBne83TTMaFMXi93hkkx2Cw+gpt6Ng2Y1++xebDXpOGT1wK/3W/je/xqGtsPxufslvO96ltw1s5BtVgwtByBJKnRx3TGf2YdsLiLr62fIWfM69uKcS96PozjbJZm8UPHaN/G25UNRBrb800hqDSpDEIYWA/Dt8TL6Rg/g2XIw/n3+hy6mPSrjv2doQRCEm9vl5koWVMNcyiNHjiDLMnXq1Km0zqFDhwCoXbu289i2bdvQ6/XO18qVK13OadOmjUv5hb1ul9KjRw8KCgrYsGEDxcXFfPnllyQkJLjUyczMJC8vzyUegKZNmzqv1a9fP5eyd999t1w8n3322WXjOXz4MAaDgeDgK+s4qFmzZrnrpKamOstbtWrFpEmT6N+/P35+fnTr1o1Zs2Zx9uzZK2ofwNPTk9atWzNt2jTOnDmD3W7n008/ZdOmTaSlpV2+getI9FAKTg6HnZTjq0jauxBPz1BatHyOw4dX4LDbad/hNWzWYgICmpCR4bpwRa3W06jBcALs/sT9vQgn1tvCymPptAryxk2lQJahob+BQ7nF2BwSv5/O4ceUs86ZlJ5qFV/cVh+d2o3iPd9hL0jHvV4XtCHxZHw5GkdpIYY2Cai9Qyn8e0i69Ohf2ArTL7mtkCXjSKVl9qJMbHmnyVr+LA5TPgo3A4YOT6CLaoutIB1tuBql3h+VVzBKQ2CVfQsWBEEoG86u/DGzhmoY7v6nD8Zr0KABiYmJAMTExGCzue6EsWzZMurWrVvuvNTUVOrVq+f8edKkSUyaNMn5s1qtZuDAgSxatIhjx44RGxtLgwYNriimFStWYLFYmDBhAiaTyaVswIABzl7PcwIDAy/bpizLV/V7/o8//sDT03U7uosXE02fPp1nnnmGtWvXsmXLFt577z1mzJjBhg0biI+Pv6LrfPLJJyQkJFCjRg2USiVNmjShX79+7Nix44pjvR5EQik4mUxZ7N3zEQDNm4/jrz9foLS0bPVcRMSdbNs2m+YtxhES0ppjKT9hsxYTFNySyMiupGXsJc+zPYfziog0eGBQqyiy2XlhUzJ1vD1BguVH04gyuGPUqlmZ4voNrdBq4/61R1h6R138bwvFdPBXSo9tpuCvj5x18te9jU/3ySBLeHeZiFJnxJyaiMNUiNo3HKVn+aRPob30N2VHaQEOU77zz3m/vIat2UMYO4xAoRV7TAqCUD3qx6nYscuKo4KOSIWirLyqxcTEIEkSBw4cuGQdgIMHD9KqVSsAtFot0dHRlZ4TGhpaYXlISIgzEQXw8Sn/5T8hIYGWLVuSlJRUrncSwN/fH6PRyMGDB12On1u44+npWW5uo5eX1yXjrUxsbCz5+fmkpaVdUS9lZGRkuWHwc3MlL+Tr60vv3r3p3bs3M2bMoHHjxsyePZslS5ZcUVy1atXi999/p7i4mIKCAoKDg+nbty9RUVFXdP71Ioa8BSe73YzZnEdgYDPOnt3hTCYBFEoNZnMef/7xPCdPrqNWrR7UixuMw25h3doxFBUc46sjZ3hs7W7SiktRKRU8UCsYHzcNe7IL2JNVgNnuoFtEIF8cOlXh9W0OmU1nsrGkJZH/+7sVbuGT/8f7GO94iqJdX5P17QTyfnuDzKVPkr5wANaMQ+W+gav9IpHUbuXaAdCGNsFyJqnc8aIdX2EvufRQuiAIwrXwMijodLsGxUX/CysU0OkOTbUsyPHx8aFLly7MmzeP4uLyu1nk5eXRuXNnfHx8eO211675eiqViujoaOerooQyLi6OuLg4kpKS6N+/f7lyhUJBnz59+PTTTzlz5sw1x3QpDz74IBqNhtdff73C8qtdlFMRjUZDrVq1Knz/L8fDw4Pg4GByc3NZvXo199133zXHU5VED6XgpFRq0Gg88fWrx9mzrl3peXnH8POrT1ZWEtnZ+8nO3u9SHhzSlrB0HQdzi1lx9AxPxEcS5OHG/NsbsDEth41pORRb7TT0MzA30VxpDEWosWZeYpi6IB1HSW7ZwpoLOEx5ZCwbRdDQT1AZzg9tKD388HtgNplfjXHZsFyp98PQJoHs718ofxHZjqMkF7xrli8TBEGoIvXqqqlRQ0nSPhsFBQ4MBgX141TVkkyeM2/ePNq2bUuLFi2YOnUqDRo0wGazsWbNGubPn09ycjIfffQRffv2pXv37owePZqYmBiKiopYtWoVULYa+ULZ2dmkp6e7HDMajeUWklRm7dq1WK3WShe9zJgxg/Xr1ztjbtasGR4eHuzZs4dNmzZRv359l/olJSXl4tFqtXh7X3q7t9DQUObMmcPIkSMpKChg8ODBREREcOrUKT7++GP0ej1vvPHGFd0TwMqVK1m6dCkPPfQQsbGxyLLMDz/8wE8//cSiRYuuuJ3Vq1cjyzK1a9fmyJEjjBs3jjp16vDwww9fcRvXg0goBSedzo+69QZhMmWi1rjOCzlyeDnNm49nw4bxyLLrGI3RGIPDrQZKpZlnGtfCTSlhtjtQyRIBJhX3FvnQQzKiiFFRqIZoLw8O5VX87Szc4I7aUXk3vuTmiaPk/GpwtX80+kY9Uer9cFhKsJfkuSSUkkqNNqwpwY9+jenIH9hyUtGGNUMTEE3GspE4THkVX6eSXk1BEISq5GVQVPlq7kuJiopi586dTJ8+nbFjx5KWloa/vz9NmzZl/vz5APTs2ZONGzfy2muvMXjwYHJycvDy8qJZs2YsXbqUHj16uLTZqVOnctf54osveOihh64opopWnF/I19eXrVu38tprrzFr1ixSUlJQKBTExMTQt29fxowZ41L/ww8/5MMPP3Q51qVLF2dCfClPPvkksbGxzJ49m549e2IymYiIiKBHjx4888wzV3Q/59SrVw93d3fGjh3LyZMn0Wq1xMTE8NFHHzFo0KArbic/P5+JEydy6tQpfHx86NWrF9OnT0etrp69Sv8pSf6ns3RvUQUFBXh5eZGfn4/BYLj8CbcYkymb/fs+xcsYyaaNU1zKQkM7EhnVnX1Ji8nO3odK5UZY1H0Ywnoz70AhL8VHY7RJkGxHVQLKOC32zSZsq0ucbSjvdGd3JwdP/VF+qNlLo2LRnfH4WbJIXzQQ2WoqV8fQ7lEc1lJM+1fhUb87SkMghVs+xZZ3CoXOiGeLAbjHdUNSqpGUapQ6rwrv016cQ+ZXY7Ck7StXpvKJIHDA+yj1flf57gmCIAjCf5NIKC/yX08oASyWIkpL89iXtJAjR751KYut3ZeoOoNwOGwcLSjl51NmZByMivXg1NEfKShJwV/fkFDj7Wg+16GsrQMF2H4+3yNZ+ownWwzF/G93CrlmKwB1vPW82CQc95XPgOzA0Pphcn5+xaUH0b1eFzyb9ad47/e41WqPLf80eWtmlYvfI/4eDK0TKEpaiS6iBerA2ijdynpcHdZS7MXZ2HJPgiwjO2wU7fiS0mMbAVB4+BLQ/z00fv+uyc6CIAiC8G8mEsqLiITyvNLSPEqK0zlx4ldk2U5YeCf0+hBMkgdP/Z7E4bximvnpebYOOMxnUShUWCyFHD3yHbm5R+jc4n3c3/NH3dcTy4J8KP37r5qngiPPaDDpZIxaDW5KBXpHMaWfDsZemAGAumYTvG97EtlWimwtRWkIxHRgLQVbPgbZju99M8hZPRNJoUJbowGy7MCcugPZUtYbGjRsKUgKslaMx9ByMB71u+OwlFCc9CN5a+c651NKKi3eXZ5DcjOgUGpQ+0eJJ+EIgiDcgmbMmMGMGTMqLGvfvj0///zzdY7o1iISyouIhLKM3W5Blh2oVOXnEp4sNNHn5+2oFBJf3xnGmZQfOHlyHQUFJ3Bz86ZuvYE47BZSUlZxh2EummwDNh8FUrIFeY8FzDLHJrkxdv8BprSsTUs/d3J+foWSfT+jNARhvPNplB6+2IuyUBmCkLSenP14KLK50BmDX89Z2EuyUWjcKU3ZAko1uqjWWLOOkf/HB/jeOw11QG1kHGR8/jjBD3+GLe80GZ8NL3c/AEEJn6MJrF1hmSAIgnDzy8nJISen4h08dDrdv+q52DcjsShHcGEy5ZCff5SDB5Zhs5VSu05f/Pzq4+Z2fnWcQpKQgJeaBCObM9Drg4mJ6YmnIYKMjB3s2vk28Q2G4+Nbj/y6nmxPL2JDTg4+TdT07BxIUIqE3kPJ2Ma12JNVQLCiFG3GYZRewfh0fZ6c1TOx5512Xk8b0RLfHlPI+vY5sJcNkat8wyjc/oXL1kLFu7/FPa4bXreNAIUKe2EGDnMBAb3n4rCUkH/BnpYXK9z2Od5dn0ehun6T4wVBEITrx8fHp8Kti4SqIRJKwam0NIedO+Zy7NhKjMYYGjV+kvy8Y6Se+A1f33qE1GiLh0cgXhoVj9YNIkZ5gr1J3xEcO4RC2ZNsm0xgjXtpF9iKbX+9QIu7vuCJPw+QabI4r7HyZAaP1Qsn0Kpl+rbD2GWZghIfBvpE4BXdjpyfX8Fe4Lrdg/n4FpTuRjzqd6d497dogupSemI75pO7yt1Dyb6f8b33lbLN3GQ7Ku8IZGsJCrUbjuLMSu/dmnMS2WYBkVAKgiAIwlUTQ94X+S8PeWec3cXq1cPQ62vQvMV4/vzjeazWIme5SuXGXZ0/wNc3jtz8E+zeu5jS4AHM2pOByVa2lZBaIfFk/Ro09cjhk1M61pzMrvBa79/RgEKLjS1n8/gx5SxLGuvxNqWT/d3EioNTqPC7/1UKty/FeNuIso3HHTZAonDX15iPb3VW1dW+A3VIA7T+tbDknKBoyydow5qib/xApRume7YchPG2kUhK8R1LEARBEK7WTfOknOnTp9OmTRvc3d0r3fw0NTWV7t274+7uTkBAAOPGjSv3zFGhYrLs4NCh5QDUrTeQ7dvecEkmAWy2Utave4bS0lxOn1yPT9RApu1MdyaTAFaHzFt7TpGvjiAxs5DKbEzLZcG+VCSgd0wIP+Sqsdsq3/Achw2FzoB73bvIWDaSrG/GkrViAtk/TsE95jY84u85fy/mYrTB9VC4eyOX5ODT7XlsualkfPEkni0HotT7u7at1KBv1FMkk4IgCILwD900CaXFYqF379488cQTFZbb7Xa6d++OxWJh48aNLFmyhMWLF/PSSy9d50ivP7O5gLzcI+xLWkJS0iJycg5RWHiKnJyDFBaewlrBfo4Xk2UZu72snodHIIWFqRXWM5mysNstKFQ6fjxVSmXd20sOnObOMP9KSsFsd6BWKPjy8BlijB78cDKPEkNYpfUV7t5ISg25q19Ftpzfgki2lJC7Zha62I5Ifz+3W1enEyrvUBymPDSBtbHlncHrthGoDIEUbFyEZ4uBzvNV3jUJ7P8eKq+QSq8tCIIgCMKl3TRdMi+//DIAixcvrrD8l19+Yf/+/fz6668EBgbSqFEjpk2bxoQJE5gyZQoaza05N660NJd9SYvZv/8T57FdO/9HdPR9RMc8wKGD3+DrW5fQsNtxczNW2o5CoaRW9H2kpq7F4ai8V1eSVDgkFR7GOE6lOyqtd7q4lG7hAZWWN/Qz8P2xsrmS605m0SLQmz2lEvGBdbCePVCuvvGOMRRu/wIqSWGL9/yA8Y6nUXr4oPIKxpadQu5vc7BlHUXlHYqh7XCMncaS9dUYfLpPJiiyJUgSSp1RbGAuCIIgCNfopumhvJxNmzYRHx9PYOD5x+516dKFgoIC9u0r/zSUc8xmMwUFBS6vm0le7hGXZPKcI0e+w2TKxMsrgtzcQ2RlJZGffwKTqeI5jQA+PnXw84tHQuHcLsjNzRsvryjU6rLevxo121NgKkDS+BFrqPz7SIyXB7EGBRqFhEohEeSuxUtTVr9tsDceaiU9IgPx1qrJt9hwV6tYk2nD94FZuEW2Pt+QUoO+aR9UhiCsOScqvZ4t7xSSSkPW8nGkL3iI3DWv49V6KO5x3bDlniRnZVlPtconEgnQBMSg8Y8WyaQgCEIlOnbsWO6xhje7oUOHcv/999/oMG5Jt0xCmZ6e7pJMAs6fL35I/IVmzpyJl5eX8xUaGlqtcVYlq9XE/v2fVlqevP8LvIyR6D1rsH3bbH5c+RDr1z3D2fQdWCzln6Xt7u7PbR1ngQSNGj9F+w6v0rjJaMIjOtOy1SRat5lMTPT9WEoz+Da1mHuiaqBWSOXakYDBdUOxWs18fFcj5ravT5+YEEY3jGJhp0YMqlOTN3ceI6WghGeb1GJo3ZpEeeroGxtCgdKAoe0j+D34Jn49X8Pvvhk4TAUUJa5A7RtZ6b2qfCPKFub83btqyz5O9g8voovugNIrGID8dW/j02UCRft+xpp76irfbUEQhKpXkufg0HoLid+Wcmi9hZK8ykd+qsLQoUORJInHH3+8XNmIESOQJImhQ4cCsHz5cqZNm1at8VRGkqQKX0uXLr0h8VxsypQplcZ47tWpUye6dOlS7tx3330Xo9HIqVOnWL9+vcs5/v7+3H333ezdu7fceSdPniQhIYGQkBA0Gg3h4eE89dRTZGe7dhR17NjRpc3AwEB69+7NiRPnO2WOHz/uUsfX15fOnTuza1f53VOu1A1NKJ977rnLfiAHDpQf/qxKEydOJD8/3/k6efJktV6vKjkcFkpLy2/SqlZ7oFRqCQpuxsnU9ezY/iaFhanY7Waysvbyyy/DSUvbxMUL/EtL85BlB35+DQgIaMDWLa+yaePL7Nn9Hn/+MYl9SYvx8oqgOHcfbYKNvJ90ktfb1iXYQ+tsw8dNzZSWtdmUlstJi5a39xxn5O97eXt3CtO2HWLk+r1kmKz4uKnZdjaP5zcd4EBuEbHeegLcVLjnHcNenE3e2rlkrZhA1vJnKdm/CtOhdXjEdQOpgr+ykgJ9fA9KDvxarqhg8xK8u0wESYk16xgKvQ9FO7+kcNvnOGyW8m0JgiBcJ6f3WPljvoljG62k77dzbKOVP94zcXqPtVqvGxoaytKlSzGZzs+vLy0t5fPPPycs7Pxcdh8fHzw9Pf/RNWRZvuZFsYsWLSItLc3l9W/pXXz22Wdd4qpZsyZTp051ObZo0SK2bNnC+++/7zwvJSWF8ePH87///Y+aNWs6jx88eJC0tDRWr16N2Wx2rgk559ixYzRr1ozDhw/zxRdfcOTIEd577z1+++03WrduXW7D9uHDh5OWlsaZM2f47rvvOHnyJAMHDuRiv/76q/O6RUVFdOvWjby8vH/0ntzQhHLs2LEkJydf8hUVdWXPVA4KCuLs2bMux879HBRU+aP0tFotBoPB5XXzUBAadgfBwa0IDm5Fk6ZPc1fnD2nWfByt20wmPLwTubkHKzxz29bXMZnK9mW02UrJzNzLurVjWP7N3aSnb2Xd2jGYzXku5xQUnGDzlumEhXXCV1GIl1bNW7uPM6hOKK+2qcvMNnUZ1yQaHzc1+3IKOZhbxMa0XJc2Smx2Xtl6kP61z/9Dej/pBAVWG8/8eYAslRFbdgq+3V9G3+iBsoU2ChVuES2R3Az43jMVhfv5jWkV7t743jOVor0rkStYfGQ9ewClhy+Bgxfi98AsJBRoAutQkrzG5TnhgiAI11NJnoOkHy1cvHGf7ICkn6q3p7JJkyaEhoayfPly57Hly5cTFhZG48aNnccuHvI2m81MmDCB0NBQtFot0dHRLFiwAMDZ0/bzzz/TtGlTtFotf/75J2azmdGjRxMQEICbmxvt2rVj27ZtVxSn0WgkKCjI5eXmVjYda/HixRiNRlavXk3dunXR6/V07dqVtLQ05/l2u51nnnkGo9GIr68v48ePL9eR8k/j0+v1LnEplUo8PT1djoWGhvLWW2/x7LPPkpKSgizLDBs2jM6dOzNo0CCX9gICAggKCqJJkyaMGTOGkydPunSojRgxAo1Gwy+//MJtt91GWFgY3bp149dff+X06dM8//zzLu25u7sTFBREcHAwrVq1YuTIkezcWX7LPF9fX4KCgmjWrBmzZ8/m7NmzbNmy5fIfTgVu6KIcf39//P0rXwl8NVq3bs306dPJyMggIKBsMciaNWswGAzUq1evSq7xb2Iy5ZCdvR8/33q4uwfg4x3L0aPf8+vOt5Dlv/eEVOtp0fI51Go9Z85svOj8LMzmfNzdA8jJOcAvqx9Blh0oFGqUCjUmUyYajYHY2r3x84vDYbciyw6OHPkOkFHrAuhXW6bAYuO7o2mY7A46h/pidsAr2w4xtnEt5uw6VmHsFofM0fxiogzuHCsoweooayfXbGXOoXwmBsZi2fop+mZ9ca/XBbspD41/LAWbFmLNSsH7zmdQGUOQ7VYUOiPmtH2YKuidBJC0euwFZ8lbOweVsQYOiwn32NtwC2+OJJUfrhcEQbgeTiXayiWT58iOsvLYjtW3mDQhIYFFixYxYMAAABYuXMjDDz/M+vXrKz1n8ODBbNq0ibfffpuGDRuSkpJCVlaWS53nnnuO2bNnExUVhbe3N+PHj+ebb75hyZIlhIeH8/rrr9OlSxeOHDlyzU+tKSkpYfbs2XzyyScoFAoGDhzIs88+y2effQbAG2+8weLFi1m4cCF169bljTfeYMWKFdxxxx3ONqozPoAhQ4awYsUKEhISeOCBB0hKSrrkuo78/HznsP65xcQ5OTmsXr2a6dOno9PpXOoHBQUxYMAAli1bxrvvvlvh/2s5OTl8+eWXtGzZ8pKxnmv7wp7Rq3HTrPJOTU0lJyeH1NRU7HY7iYmJAERHR6PX6+ncuTP16tVj0KBBvP7666Snp/PCCy8wYsQItFrtpRu/CZWUnGX/vo+JiOyCn188ubkHSU7+zKWO1VrEpo1T6Hj7HM6c2cTFK6QVChVmcz57dr/vTEJVKh0WSyE6nT9t2k4hae9CkvaWfQPVaDypV28wDlnm+U0HOJxXzOy29TA7ZJoHGCix2Zm+/SgAWqWCQmvlwx2ZJgteWvX5WCQJhyyz5WweZ+s1wLuhntKvn0bf6AEc5kIkSQlKNZ4tByJJErLdSv4f72HNOk5A//llQ+Fy+W/0hlaDUWh0eDbtiyXrKFqvGqj9onDIMqjd/9F7LwiCcK0u1wNpqua5lAMHDmTixInOeXV//fUXS5curTShPHToEF9++SVr1qyhU6dOABWOIE6dOpW77roLgOLiYubPn8/ixYvp1q0bAB9++CFr1qxhwYIFjBs37pIx9uvXD6VS6XJs//79zmF5q9XKe++9R61atQAYOXIkU6dOddadO3cuEydO5IEHHgDgvffeY/Xq1c7ya43vSn3wwQfExcWxYcMGvvnmmwo70s4NfxcXl61vuPfee6lTpw4Ahw8fRpZl6tatW2H7devWJTc3l8zMTGeH2rvvvstHH32ELMuUlJQQGxvrcu8Xy8vLY9q0aej1elq0aPGP7vOmSShfeukllixZ4vz5XLf8unXr6NixI0qlkpUrV/LEE0/QunVrPDw8GDJkiMtfrluFyZTL2fQd1IsbgrvOl9ycAyTtW1JhXYfDxtn07QQENibj7Pnubh+fujgcdlKO/UR4RGdiYh5gz56PyMs7gs7dnyZNn2LzplcoLj4/fGCxFJKYOA+tLgCVVPaX3yLLrDuVxc6MPEY3Ov/LJdNkIcxTR2phxXtg1vb2YEdGHlCWfOpUCkrtZb9AM0utvHFEZlrXaRR+9zT+fd6m5NB61N6hZH/7HACSSovvva9gNxVQmrIV7y7PkfvL685FOQC62nfiFtmazGWjXIa3JbUbvvfOwFGSh1LrcRXvvCAIQtVwNyoAe6XlOmP1zkjz9/ene/fuLF68GFmW6d69O35+le96kZiYiFKp5Lbbbrtku82aNXP++ejRo1itVtq2bes8plaradGiBcnJyQA8/vjjfPrp+cWlRUXnH6gxZ84cZ/J6TkjI+T2D3d3dnckkQHBwMBkZGUBZT19aWppLr5xKpaJZs2bOYe8ria8qBAQE8Nhjj/Htt99WOgf0jz/+wN3dnc2bNzNjxgzee++9cnWu5sGGAwYMcA6Dnz17lhkzZtC5c2d27NjhMi+2TZs2KBQKiouLiYqKYtmyZeUWOF+pmyahXLx4caV7UJ4THh7OTz/9dH0CuoFsthIMXhE4HBY2bJhAfIPhFBelVVq/qOgMOjdf588arRet27yEyZTN4cMryMs7gkZjoG27aezc8RZ5uUfw0Ae7JJMX2rtnPi90eJ+deYHYHQ5ivDw4nF+MSpLw12nINFn47lg6A2vXZMb2w+XOD/bQEmXwoF9sDby0amwOO98eLVuJ761VY7Y7OJhfwrHIQOqENadQ6Ymj2cO4q8DXEEj+nx9iy04hb/3/8OkxlfwN7+IW1ZaghM+xnN6DvSQHTVAcSs8Asr+bWG6upGwtJefnaQQM/OgfvPuCIAjXrmYjFSmbrRUNrCApysqrW0JCAiNHjgRg3rx5l6x78VBrZTw8ru5L+tSpU3n22WcrLAsKCiI6OrrSc9VqtcvPkiRdVdJ1PalUKlSqyj/TyMhIjEYjtWvXJiMjg759+7JhwwagbCRWkiSSk5Pp2bNnuXOTk5Px9vZ26fn08vJyvnfn5roGBwezbNkyHnnkEWe9ZcuWUa9ePXx9fSt9CuGVumW2DfovUSjU5OUdRaXSUVh4kqLCU3h7V/6Pzt+/AUHBLQmP6EyjxiNp02YKZ88mkrz/U1q0mEBAQBMslgI2bXyZ+vEJnD79JwX5xyttr6Q4nfzSEj4+cJL9OUVMblUbHzc17yedYFLzWMI9daQUlHAkv5hnGtfC163sH70EtAo0Mr5pDBP+2s+M7Yd5afMBSm0yOlXZsMbAOjX5IaVsMdWqTDtpHV9ixgmJ8bvSmZKUTWZAM4xdJhKU8AW+972Kwt0Hz2YPITts2PNOU7jrG0oOrCVrxThsualYM49UeA+Oklwcpvx/9gEIgiBcI3ejgvp3a8ptXCEpoH53zd89mNWra9euWCwWrFZrhdvbXCg+Ph6Hw8Hvv/9+xe3XqlULjUbDX3/95TxmtVrZtm2bc21DQEAA0dHRzldV8fLyIjg42GWBic1mY8eOHVcV340wYsQIkpKSWLFiBVC2cOauu+7i3XffdVmZD2XbIn722Wf07dv3kusCzk0duPj80NBQatWqdc3JJNxEPZTCeQpJQakpm/z8FACOHP2eJk1G8+cfk8rVVav1BAQ04sDBZciygxPHfyEx9xB+fvUJCGzK2rWj6dzlI376cQClpTlIksI5h7IyarWeYnvZsPYXh06zOT2XtzvE8+G+E3yw9zhD6oYS4uFGqd2Bm1LB5Ba1KbU78HFT89vJLF7clEyRtWyox2x3MH37Id5sX59mAV6klZjZlVmW6DULMILGg9bBMgpJoobejY+PZNAnoia+m9+m9MgG1EH18GqbgMrDh5zVM7EXZpwP9BJP/IGynkpBEIQbpUYDNd5hSk4l2jDlOdAZFdRspLouySSUJRnnhnYvnqt4sYiICIYMGUJCQoJzUc6JEyfIyMigT58+FZ7j4eHBE088wbhx4/Dx8SEsLIzXX3+dkpIShg0bdtn48vLyyu0j7enpecW9oE899RSvvvoqMTEx1KlThzfffNNlS5xrja+6uLu7M3z4cCZPnsz999+PJEm88847tGnThi5duvDKK68QGRnJvn37GDduHDVq1GD69OkubZSUlDjfu7NnzzJt2jTc3Nzo3LlztcUtEsqbkAzUDL0Ds7lsM9OS4nTOnt1B8xYT2LP7fed2P0ZjNI2bjMJmt3IydT1W6/m5KUqlGw6HFZvNRHbOIVre9SUmUzpqtYLY2n0JCGyMSuWOzVZS7vph0X1Znmp2/pxSUMLB3CKG1wtFq1ICEu/uTWH9qWznMqAn4iN4PymDo/nl23PIsDk9Bzelkp+Pl/VODqkbSp7Fyoj1e3D83YhSghHx4RiKT6Ey1sD37slIOi8KN3+Mvkkv12Ty7zdK0ni4PPvbSVKgMorndwuCcGO5GxXVupr7cq5mq7z58+czadIknnzySbKzswkLC2PSpPIdGRd69dVXcTgcDBo0iMLCQpo1a8bq1avx9va+7PUefvjhcsdmzpzJc889d0Xxjh07lrS0NIYMGYJCoSAhIYGePXuSn39+dOpa4qtOI0eO5M033+Srr76iT58+xMTEsH37diZPnkyfPn3IyckhKCiI+++/n8mTJ5dbkf7hhx/y4YcfAuDt7U2DBg346aefqF27drXFLMn/1gkHN0hBQQFeXl7k5+f/a/ekLC3NodSUh91hZu1vo5ybmwcENCY2thcKpQat1gtzaR4HD31Ds2ZP8+PKfi5ttGg5kf37PqGo6BSRtQew1HQXR/KKGVQ7hB7hRg4lLSAwqBGbNk3DYj7/jy849E7cIh9j/NY0lzXjrYO8mdCsFj+mZJBdaqGejyduKiX/252Cm1LB041r8cIFPZMXax/iw/1RwaSXmKmh12J1yIz7c3+Fdd9rHoz/mufQdnkJjSGAohVjMbQcRPb3rvtwudVqi7ZGA/I3zC/Xhr7pQxhvexKFWJQjCIIgCNdM9FDehGRZxmorQqPxpG3bqWzePJ3i4jQyMnaRkbGL0LA7CA/vxNEjK2nU6EmOHXNdqBQc3ApJUlBUVPb4QXevuuTmWulS00Btj1LMpiwMXqEcOfwdLVqMB0CSNFi0Nfgr08GCbelc/C1Ep5SQSzMoNFtYfjSd5UfTCdBpmNUujv05BZwsNBFj1DuHsy8WY9SzYH8q+3MK6RsTQkpB+Z7Mc/aUKOn1wBvkH/wdleRAE1QHhZu+3NZBpUf/QhNYB+8uEync+im23JMo9f4YWj+MW622IpkUBEEQhCoiEsqbkJubDxZLASdTNxAQ2JAGDR9Hq9Fjd9jw9KyJLDtQKd2IjOyCSuWGj08dwsI7ISFRo2Z7rNYitm19/e+2vFEY6vJ8QztpB97nQPJ6kmU7RmMM8Q2GkZLyMzZrCZFR97K1SOKDA9kVxnR3DTVbNoyhd4f/sfKEkiKrnQyThf/tTqGOj54fU84yvmk0iZn55ZJRvVpJPR9PFu5PBcCgUZNhqnhj1SB3LQ/4mMle8iiypZh8pRr/3nMxHd6AR/w9FO/5zqV+wcYFGDs9i7HTs6g8/ZGRQKFCodVf24cgCIIg3NIu3tLoQgMHDqxwa5//MjHkfZGbYcgbyp6Uc/DAUrRabwKDGlNYeAqzOR8vQwQarRdKpRZZtpOWtgWLpYDw8C4UFKSwfdtsiopOA+DtHUtM08mUouHoptHltgmSJAW3dZxNevo2CgpSCa83gplJJvbnFrnU61rTi+5eh0jeMYPb7/qQg7YwCi025u89ToHFxqtt6vLcxmQ6h/nTPNDIh0knnAljbW89w+PCmb83xTm/snOYPwpJYtWJi+ZEAp+0j8Rj5TNYs446j2lrNsLQ7lEktQ7LyV0UbP0UR0kOSs9ADK2GoPKNIHPpk3i1fwxtRCss6fsxNHuoSj8PQRAE4daSkZFBQUFBhWUGg8G5ibhQRvRQ3qR0Oh+iY3py8uTvbPj9OYKCmqFzD0QhaTCqdBQXnUGhVFOnTl/nOWq1O7d1nI3JlIXazZ8NGXbeOWzlqZrHK9xzUpYdJO//jMio7tisJRzeNZOp7edRaLEj/73XhUO2o5FLyTz+J2q1B8WmfGbtOYKfTsOUlrWZtDEZ+9/fWX5JzeR4QQnD4sLxc9Pg66ZmR2Y+r+04TOYFPZLrT2XxWrs4fjuZidVx/vtOuKeOAMlE3gXJJIAutiO2/NMU71qO0hCET/eXUBmCsBWcpeCvDzF2HAWA6fAGdHXuwl7o+sx3QRAEQbhYQECASBqvguihvMjN0kN5jiw7KCw8jd1etuq6qOgMqSfWEhF5F/7+DdFoKh7aPVtcwuPrkhhWNwivM+9zPOXnCuspFGq63/M1doed48UO5iXn0zrYB41S4vODpymw2JCA1kFeDI9Wo1Vq+fKkHZVCQqWQUCsUhHnqmL7NdYPzFgFGHq0fTpHNTpHVxtazefxyIsP5tJymAV4MrhPKW4nHOPb3fMpJzWJopszC+vkQZzv6Zg8h28wUJ65wDVxS4nvvK+T/8R4+XZ8n4/NH0YTUx9D+MVR6PzQBsf/k7RYEQRAEoQKih/ImJ0kKDIZQ7HYLpaYcjMYo/Pzi0Ol8L3leoIc7s9vHIVlzyM42VlrPzc0bs8NBvsOTMZuTqeutx0Ndtnr7HBnYmJ7P6WIdL7esydmSE5jtDloGedOhhi9vJbr2KMb7epJQP4z5ScfZkZGPUpLoUMOXV9vW49Xth0kvMXM4rxiDRsXTjaPwUKtQShI6JZzMKCDE3QdHSQ5ICnRRrcn88qnygct28v94H8/m/UBVtrG6vmFPbLmn0QbXv+L3VxAEQRCEyxMJ5S1CqdTgoQ+6qnNqeXmQlXMGTUgrDhz4osI6sbX7YlH6siQ5FZtD5p7IID5IOlFh3ROFJs6azPSODsFkt6NRKvjrTDZ9Y2qw9WweDrnsud2P1Y/gqd+TMP/dG2n/+3ngSdkFPNskmk8OnOThemFM3XqIlIIStEoF01rVodRu59c0M2PveJbSlZNQGoKwZqVUGAuALec4av9oivf+hCYkHm1oYxTu3ih1//6eZ0EQBEG4mYhHL/7HuWn0nExdT9NmzyBd9Ayw4JDW1AjvzJF8E7uzyiYme6iVZJVWvAIb4HBeMe8nHef5TQcY9+d+tqTnYdCoSagbSpTBnamt6rAyJd2ZTF4o02Qho8TM3RGBTN92yLl1kNnuYOb2w3iolDQN9OGTkhC0fd5DHVgHSXXpDYEVGg/cQhvh98As1L7hIpkUBEEQhGogeij/43Q6fzw9Q8nM3EPH2+eQl3cEq7UEP996lFqKSLN4cLywAG+thuxSKw4Z3JQK51zHixm1anLNVufP2zLyKN51hBdbxHJHqD/FVhvbMyp/hvafZ7IJcNeSU2p1OZ5rtmJxyDQJMHK8oIRH9hXTu9ZQ7g/WgUJV4WMWNTUagFKNJrw5Kv2lpwAIgiAIgvDPiR7K/zilUkV0zH34+MTx5x/Pc/ToStLObOZY6u9Y9A3ZnVXEmtRMukcGAmUrsLuGV7zqzV2lxM9NU24Pyf05RRSYbfx5Jof0EgsGTeXfYwwaNSZbxcmqWgKdrZgwTx0vtqhNTEAAOWgx3jW+XF1Jq8fYcST24mxU7sYrfDcEQRAEQfgnREIp4ObmTXSdfrTr/CkRjV8mqMELbNM+yLSdGQS5a0gpKEGjUHBHTT/Wn86ieaA3zQOMLm0YNCpeahnLouSTFV7jTHEp3x9Lx8dNzYMxlT9D+/ZQPzam5ZQ7rpSghsqCe8ZevjxyhpnbD2O2Q6CHDreI5gQOWYJHw/txi2iJoe2jBPT5Hwp9ANqQeCSF8preH0EQhOpizXaQ/aOF9I9Lyf7RgjW74i/UVWXo0KHcf//9l6wjyzLdunVDkiS+/fbby7YpyzKzZ88mNjYWrVZLjRo1mD59+hXFs3jxYoxG4yXjlSQJSZJQq9VERkYyfvx4SktLXeqdqyNJEgaDgebNm/Pdd64PuqjoWsnJyYSGhtK7d28sFgtpaWn079+f2NhYFAoFY8aMuaL7EMSQt/A3nVpDoLEmSjcLmSUm7qhRTNeAs6g1+bgpFbyx6whD64bRNbweh/KKGFCnJo83iCC1sARPtYoQDzembDnIobziCtsP9nBjSN1Q3FRKmgV40SHEhw1nXBPHwXVq4q6UKLGVf953nwgf1Ds/wS5bebnlKE4VlRLjrUen1wE+yLKM0bcWyFZkSYlSpUFSqqvjrRIEQagSBVutZCyzgDOHtJO71kpAXw2GFjfu99fcuXORJOmK6z/11FP88ssvzJ49m/j4eHJycsjJKd8x8E917dqVRYsWYbVa2bFjB0OGDEGSJF577TWXeosWLaJr164UFBTw7rvv8uCDD7Jz507i4+MrbHfbtm1069aNnj178v7776NQKDCbzfj7+/PCCy8wZ86cKruH/wKRUApOaqWCYA83PBQyxYVnUbkZyC3MZHqraCZsOszC/amoFRKRBnf2ZBXwaP1w1pzIZE92Ad0jAgnT6ypMKCMM7hzJL2b2zrLtg1oHGXkiPpKuEYHszsxHrVRwe00/juUVE6FTML1xMB8cyeNEoYkgdy1DIg00Nx/CnvgltHsCjVJB0wAjAe5a5zUkSUKp1QG66/V2CYIg/GPWbMdFyeTfHJCxzIKulhK17/UfRExMTOSNN95g+/btBAcHX7Z+cnIy8+fPJykpidq1awMQGRlZpTFptVqCgsp2MQkNDaVTp06sWbOmXEJpNBoJCgoiKCiIadOm8dZbb7Fu3boKE8q1a9dy33338eSTT7q0ExERwVtvvQXAwoULq/Q+bnUioRTKMeh0OBxBFOYfozT/MN7uhSzqGM+uHBuniq3U8vJAp1IycWOy8wk3K46m8d4dDSmy2dmcnutsq5aXOyMbRjFt60HnsU3peRg1pxgW48tOWSYpIx+NQmJHRj6rT8BLnoeZ5a9Gjq4BxVlotv0PS9p+QMKr3l34eXte77dEEAShShVstpVPJs9xlJX7dr/0LhZVraSkhP79+zNv3jxnAnc5P/zwA1FRUaxcuZKuXbsiyzKdOnXi9ddfx8fHp8pjTEpKYuPGjYSHh1dax2azsWDBAgA0mvLv4YoVK+jfvz9TpkxhwoQJVR7jf5VIKIUKGT2MqNTxONxCQTYjKZQczC2kwGrjvqggPth7guy/tw8yaFT0janBjow8WgZ582j9cE4WmgjRu7Evu5CpWw66rPwG+OVkFoODZR43ZPO7LoD/HUpncotYpm49xPGIxoRsnoP9+CYALOB88o3SUzwGSxCEm9/l5kpac6p3LmVFnn76adq0acN99913xeccO3aMEydO8NVXX/Hxxx9jt9t5+umnefDBB1m7dm2VxLVy5Ur0ej02mw2z2YxCoeCdd94pV69fv34olUpMJhMOh4OIiAj69OnjUqeoqIjevXszadIkkUxWMZFQCpXSa9TojH5klVqQ7VYS6qjIL8nDWpLK6IbhPBgTTLHVTpC7lnf3Hmfr2TwAGvkZGB4XxrH8EuYmHquwbbssU2p3kP3VGDr2m8+vRg/e2HWUl1rUJrO4EEXrsUS2K0ZxZjcqnRfa0EYo9X4o1G7X8R0QBEGoHmXD2eXnizvLfa7vcPf333/P2rVr2bVrV6V14uLiOHGi7MEW7du35+eff8bhcGA2m/n444+JjS17pO2CBQto2rQpBw8edA6DX4vbb7+d+fPnU1xczJw5c1CpVPTq1atcvTlz5tCpUyeOHTvG008/zdtvv12ul1Sn09GuXTs+/PBD+vXrR926da85PqGMWOUtXJJSIRHoriXIU0+Ily+1fIMI0ntTbMrFqFHjrlLiQKZjTT/clGV/nRKzCpi85SDhnpXPZ9QqFegcZkCm8I/3eDrWk0yTBQ9LDk13vE4DTwU+ofUxthyAvkEP1N41RTIpCMItw9BKVfn/wIq/y6+jtWvXcvToUYxGIyqVCpWq7Pq9evWiY8eOAPz0008kJiaSmJjIRx99BEBwcDAqlcqZTALOJC01NbVKYvPw8CA6OpqGDRuycOFCtmzZ4hzSvlBQUBDR0dF07tyZRYsW0bdvXzIyMlzqKJVKvv32W5o0acLtt99OcnJylcQoiB5K4SppNB5oNB4Y9DI5JgsalYIP9p4gzFPHB3c25GyJGbtDxiGDUgG1jR4crGChTp8IbzRJn2EFzGn78FfJLG4RgGbdDMynEyl7QrggCMKtSe2rIKCvpvzCHAUEPKS57gtynnvuOR555BGXY/Hx8cyZM4d77rkHoMJ5i23btsVms3H06FFq1aoFwKFDhyqtf60UCgWTJk3imWeeoX///uh0FXdctGjRgqZNmzJ9+nTnIptztFoty5cv58EHH+T2229n7dq11KtXr8pj/a8RCaXwj0iShK+7Fl9gTKMoThaZOFtsRqWQsP2dDCqAUY2i+DT5JJv/Hg7XKCQeCPfmXs0ZrMmrAVB6+KJ0WFB8NhCb7MAtqg0K96qfzC0IgvBvYmihRldLScFmG9YcB2ofBYZWqmpPJvPz80lMTHQ55uvrS/369cvVDQsLu+Sq7U6dOtGkSRMSEhKYO3cuDoeDESNGcNddd7n0Wl6K3W4vF49Wq610OLp3796MGzeOefPm8eyzz1ba7pgxY+jZsyfjx4+nRo0a5dr/5ptv6N27tzOpjIuLA3DGUlRURGZmJomJiWg0GpF0XoZIKIVr5ueuxV2tJMdspchiw12lRKcq20xcqZCY2rouOcXFFOWewQML2n3fYE36nnO9kPrGD2A5exhkB27Rt+HTZYJ45rYgCP8Jal/FdV/NvX79eho3buxybNiwYc5h7KuhUCj44YcfGDVqFB06dMDDw4Nu3brxxhtvXHEbRUVF5eKpVasWR44cqbC+SqVi5MiRvP766zzxxBN4eHhUWK9r165ERkYyffp03n333XLlGo2Gr7/+mj59+jiTyvr167vEsmPHDj7//HPCw8M5fvz4Fd/Tf5Eky7IYW7xAQUEBXl5e5OfnYzCIpKaq2M2FmA7/Qc6PL7s8d1sX0xHj7aOw5ZxEofdF5R2K0k1sCyQIgiAINxORUF5EJJTVx15aiL0oC/OpRBylhWhrxCOp3Mj5aSqS1gO/+2ai8vS/0WEKgiAIgnCVxJC3cN0o3TzLXno/7IVZFCf9iC3rKF63PYkmqA4qvUgmBUEQbiUXbjV0sffff58BAwZc54iE6iJ6KC8ieiivH9luRZZlFKrrO39IEARBuD5OnDiB1WqtsCwwMBBPTzHF6VYheiiFG0ZSqpFudBCCIAhCtamOrYOEfyexsbkgCIIgCIJwTURCKQiCIAiCIFwTkVAKgiAIgiAI10QklIIgCIIgCMI1EQmlIAiCIAiCcE1EQikIgiAIgiBcE5FQCoIgCMIN4si0Yfm6APP8XCxfF+DItF3+pGswdOhQ7r///grLOnbsiCRJLq/HH3/8sm3Ksszs2bOJjY1Fq9VSo0YNpk+ffkXxLF682HkthUJBzZo1efjhh8nIyHDWuTAeDw8PYmJiGDp0KDt27HBpKyIiolz8F77ObbB+4X26ubkRGxvLzJkzuXBb7uPHjyNJEgEBARQWFrpcp1GjRkyZMqXC+3n88ceRJIm5c+de0f3fSsQ+lIIgCIJwA9j+LMGyMB8cFxz7uRjNw16o2rnfkJiGDx/O1KlTnT+7u18+jqeeeopffvmF2bNnEx8fT05ODjk5OVd8TYPBwMGDB3E4HOzevZuHH36YM2fOsHr1amedRYsW0bVrV0pLSzl06BAffPABLVu2ZOHChQwePBiAbdu2YbfbXdrOy8vjzjvvpGnTpoSFhZW7T7PZzNq1a3n00UcxGo088cQTLucXFhYye/ZsXn755cvex4oVK9i8eTMhISFXfO+3EpFQCoIgCMJ15si0lUsmAbCDZVE+itoaFP7X/79od3d3goKCrrh+cnIy8+fPJykpidq1awMQGRl5VdeUJMl5zZCQEEaPHs2LL76IyWRCp9MBYDQanXUiIiLo3LkzQ4YMYeTIkdxzzz14e3vj7+/6+F6Hw8HQoUPx8vLis88+Q5LOP0rjwvt8+OGHeeedd1izZk25hHLUqFG8+eabjBgxgoCAgErv4fTp04waNYrVq1fTvXv3q7r/W4UY8hYEQRCE68z2e0n5ZPIc+9/lN8Bnn32Gn58f9evXZ+LEiZSUXDqOH374gaioKFauXElkZCQRERE88sgjV9VDeTGdTofD4cBmu/Tw/9NPP01hYSFr1qypsPy5555jy5YtfPfdd5U+4lGWZf744w8OHDiARlP+McD9+vUjOjrapdf2Yg6Hg0GDBjFu3Dji4uIuGfOtTCSUgiAIgnCdyZn2S5dnXbq8OvTv359PP/2UdevWMXHiRD755BMGDhx4yXOOHTvGiRMn+Oqrr/j4449ZvHgxO3bs4MEHH/xHMRw+fJj33nuPZs2aXfY533Xq1AHK5jte7IsvvuDNN99k6dKlxMTElCt/99130ev1aLVaOnTogMPhYPTo0eXqSZLEq6++ygcffMDRo0crjOO1115DpVJVeP5/iRjyFgRBEITrTPJXXrrc79Ll1eHRRx91/jk+Pp7g4GDuvPNOjh49Sq1atYiLi3MubGnfvj0///wzDocDs9nMxx9/TGxsLAALFiygadOmHDx40DkMfin5+fno9XocDgelpaW0a9eOjz766LLnnVtEc+FQNsDOnTsZNmwYr776Kl26dKnw3AEDBvD888+Tm5vL5MmTadOmDW3atKmwbpcuXWjXrh0vvvgin3/+uUvZjh07eOutt9i5c2e5OP5rREJ5kXN/QQsKCm5wJIIgCMK/jaenZ5UkDqrb3LH9XAwVdUQqy8pvtJYtWwJw5MgRatWqxU8//YTVagVwzm0MDg5GpVI5k0mAunXrApCamnpFCaWnpyc7d+5EoVAQHBzsbPtykpOTAdc5m5mZmfTs2ZNevXrx7LPPVnqul5cX0dHRAHz55ZdER0fTqlUrOnXqVGH9V199ldatWzNu3DiX43/88QcZGRkuC37sdjtjx45l7ty5Ffae3qpEQnmRc9sDhIaG3uBIBEEQhH+b/Px8DAbDNbej8FehedgLy6J816RSCZoErxuyIOdiiYmJQFnSCBAeHl6uTtu2bbHZbM5eTIBDhw5VWr8iCoXCmdxdjblz52IwGJxJoNVq5cEHHyQgIIAPP/zwitvR6/U89dRTPPvss+zatavCLwwtWrTggQce4LnnnnM5PmjQoHJJaJcuXRg0aBAPP/zwVd/TzezG/439lwkJCeHkyZNV9i20OhUUFBAaGsrJkyer5Bfcv9l/5V7Ffd5axH3eei43r+9qqNq5o6itwfZ7CXKWHclPieo292pPJvPz853J4oXHNmzYwN13342vry979uzh6aefpkOHDjRo0KDStjp16kSTJk1ISEhg7ty5OBwORowYwV133eXSa3mt8vLySE9Px2w2c+jQId5//32+/fZbPv74Y4xGIwBjxoxh9+7d/Prrr+Tl5ZVrw8fHp8KFNwCPPfYY06ZN45tvvql0/uf06dOJi4tDpTr/+fj6+uLr6+tST61WExQUdEW9s7cSkVBe5NzGqjcTg8Fwy/8SP+e/cq/iPm8t4j6Fyij8VWgevL7v2fr162ncuLHLsYSEBI4cOcLcuXMpLi4mNDSUXr168cILL1yyLYVCwQ8//MCoUaPo0KEDHh4edOvWjTfeeKNKYz7X2+fm5kaNGjVo164dW7dupUmTJs467777LgDNmzevsI1169bRsWPHCst8fHwYPHgwU6ZM4YEHHqiwTmxsLAkJCXzwwQfXcCe3Lkm+cGt44aZSUFCAl5dXlQ3B/Jv9V+5V3OetRdynIAj/FWLbIEEQBEEQBOGaiITyJqbVapk8eTJarfZGh1Lt/iv3Ku7z1iLuU/ivi4uLQ6/XV/j67LPPbnR4QhUSQ96CIAiCIFSLEydOOLcaulhgYGCVLnISbiyRUAqCIAiCIAjXRAx5C4IgCIIgCNdEJJSCIAiCIAjCNREJpSAIgiAIgnBNREIpCIIgCIIgXBORUN5CIiIikCTJ5fXqq6/e6LCu2bx584iIiMDNzY2WLVuydevWGx1SlZsyZUq5z65OnTo3OqxrtmHDBu655x5CQkKQJIlvv/3WpVyWZV566SWCg4PR6XR06tSJw4cP35hgr8Hl7nPo0KHlPt+uXbvemGCvwcyZM2nevDmenp4EBARw//33c/DgQZc6paWljBgxAl9fX/R6Pb169eLs2bM3KGJBEK4XkVDeYqZOnUpaWprzNWrUqBsd0jVZtmwZzzzzDJMnT2bnzp00bNiQLl26kJGRcaNDq3JxcXEun92ff/55o0O6ZsXFxTRs2JB58+ZVWP7666/z9ttv895777FlyxY8PDzo0qULpaWl1znSa3O5+wTo2rWry+f7xRdfXMcIq8bvv//OiBEj2Lx5M2vWrMFqtdK5c2eKi4uddZ5++ml++OEHvvrqK37//XfOnDlT6aPsBEG4hcjCLSM8PFyeM2fOjQ6jSrVo0UIeMWKE82e73S6HhITIM2fOvIFRVb3JkyfLDRs2vNFhVCtAXrFihfNnh8MhBwUFybNmzXIey8vLk7VarfzFF1/cgAirxsX3KcuyPGTIEPm+++67IfFUp4yMDBmQf//9d1mWyz4/tVotf/XVV846ycnJMiBv2rTpRoX5r2bPNMmWFSdk84cHZcuKE7I901Tt10xLS5NHjhwpR0ZGyhqNRq5Zs6bco0cP+ddff3XW2blzp9ynTx85KChI1mg0clhYmNy9e3f5+++/lx0OhyzLspySkiIDFb4u93nPnj1bNhqNsslU/n6Li4tlT09P+a233pJlufz/beHh4c7ruLu7y40bN5a//PLLK7r3yZMny4DcpUuXcmWvv/66DMi33XZbufrnXgaDQW7Xrp28fv16l3OvJaZbheihvMW8+uqr+Pr60rhxY2bNmoXNZrvRIf1jFouFHTt20KlTJ+cxhUJBp06d2LRp0w2MrHocPnyYkJAQoqKiGDBgAKmpqTc6pGqVkpJCenq6y+fr5eVFy5Ytb8nPd/369QQEBFC7dm2eeOIJsrOzb3RI1yw/Px8AHx8fAHbs2IHVanX5TOvUqUNYWNgt+ZleK9umDMwv7cK26jT27dnYVp3G/FIitk3VNwJz/PhxmjZtytq1a5k1axZ79+5l1apV3H777YwYMQKA7777jlatWlFUVMSSJUtITk5m1apV9OzZkxdeeMH5uZ/z66+/uvS+p6Wl0bRp00vGMWjQIIqLi1m+fHm5sq+//hqLxcLAgQMrPf/caNyuXbto3rw5ffv2ZePGjVf0HgQHB7Nu3TpOnTrlcnzhwoWEhYWVq3/h6NGmTZuIiYmhR48e5d6Ha4npViASylvI6NGjWbp0KevWreOxxx5jxowZjB8//kaH9Y9lZWVht9sJDAx0OR4YGEh6evoNiqp6tGzZksWLF7Nq1Srmz59PSkoK7du3p7Cw8EaHVm3OfYb/hc+3a9eufPzxx/z222+89tpr/P7773Tr1g273X6jQ/vHHA4HY8aMoW3bttSvXx8o+0w1Gg1Go9Gl7q34mV4rR1Yp1k+OguPiAhnrJ8dwZFXPtI8nn3wSSZLYunUrvXr1IjY2lri4OJ555hk2b95McXExw4YNo3v37vz444907tyZqKgo6taty7Bhw9i9ezdeXl4ubfr6+hIUFOTyUqvVl4wjICCAe+65h4ULF5YrW7hwIffff7/zi0pFPD09CQoKIjY2lnnz5qHT6fjhhx+u6D0ICAigc+fOLFmyxHls48aNZGVl0b1793L1VSqV877q1avH1KlTKSoq4tChQ1UW061AdaMDEC7tueee47XXXrtkneTkZOrUqcMzzzzjPNagQQM0Gg2PPfYYM2fOFM/Y/Zfr1q2b888NGjSgZcuWhIeH8+WXXzJs2LAbGJlQFR566CHnn+Pj42nQoAG1atVi/fr13HnnnTcwsn9uxIgRJCUl3RJzfW8E+58Z5ZPJcxwy9j8zUNxfvrfsWuTk5LBq1SqmT5+Oh4dHuXKj0ciKFSvIzs6+ZGeEJElVEs+wYcPo0aMHJ06cIDw8HIBjx46xYcMGVq9efcXtqFQq1Go1Fovlis9JSEhg/PjxPP/880BZEjtgwIDLnmc2m1m0aBFGo5HatWtXaUw3O9FD+S83duxYkpOTL/mKioqq8NyWLVtis9k4fvz49Q26ivj5+aFUKsutED179ixBQUE3KKrrw2g0Ehsby5EjR250KNXm3Gf4X/x8o6Ki8PPzu2k/35EjR7Jy5UrWrVtHzZo1nceDgoKwWCzk5eW51P8vfKZXS75MD6ScXfU9lEeOHEGW5UvuIHGu1+3CZGnbtm3o9Xrna+XKlS7ntGnTxqVcr9dfUTxdunQhJCSERYsWOY8tXryY0NDQK/6iZbFYmDlzJvn5+dxxxx1XdA5Ajx49KCgoYMOGDRQXF/Pll1+SkJBQYd29e/c670un0zF79my++OILDAZDlcZ0sxM9lP9y/v7++Pv7/6NzExMTUSgUBAQEVHFU14dGo6Fp06b89ttv3H///UDZMNtvv/3GyJEjb2xw1ayoqIijR48yaNCgGx1KtYmMjCQoKIjffvuNRo0aAVBQUMCWLVt44oknbmxw1ezUqVNkZ2cTHBx8o0O5KrIsM2rUKFasWMH69euJjIx0KW/atClqtZrffvuNXr16AXDw4EFSU1Np3br1jQj5X0vyc7t0ue+ly/8JWZb/0XkNGjQgMTERgJiYmHJz85ctW0bdunWvul2lUsmQIUNYvHgxkydPRpZllixZwsMPP4xCcen+rgkTJvDCCy9QWlqKXq/n1VdfrXC4ujJqtZqBAweyaNEijh07RmxsLA0aNKiwbu3atfn+++8BKCwsZNmyZfTu3Zt169bRrFmzKovpZicSylvEpk2b2LJlC7fffjuenp5s2rSJp59+moEDB+Lt7X2jw/vHnnnmGYYMGUKzZs1o0aIFc+fOpbi4mIcffvhGh1alnn32We655x7Cw8M5c+YMkydPRqlU0q9fvxsd2jUpKipy6YVLSUkhMTERHx8fwsLCGDNmDK+88goxMTFERkby4osvEhIS4vwCcbO41H36+Pjw8ssv06tXL4KCgjh69Cjjx48nOjqaLl263MCor96IESP4/PPP+e677/D09HTOi/Ty8kKn0+Hl5cWwYcN45pln8PHxwWAwMGrUKFq3bk2rVq1ucPT/Lsp2Adh+OQOOCpI8hYSyXdV3BMTExCBJEgcOHLhkHSj7InDuM9NqtURHR1d6Tmho6CXLLyUhIYGZM2eydu1aHA4HJ0+evKLf7+PGjWPo0KHo9XoCAwP/0TB8QkICLVu2JCkpqdLeSSjr3Ljw/ho3bsy3337L3Llz+fTTT6s0ppuZSChvEVqtlqVLlzJlyhTMZjORkZE8/fTTLvMqb0Z9+/YlMzOTl156ifT0dBo1asSqVavKLeS42Z06dYp+/fqRnZ2Nv78/7dq1Y/Pmzf+4d/rfYvv27dx+++3On8/9fTzXKzF+/HiKi4t59NFHycvLo127dqxatQo3t6rvnalOl7rP+fPns2fPHpYsWUJeXh4hISF07tyZadOm3XRzm+fPnw9Ax44dXY4vWrSIoUOHAjBnzhwUCgW9evXCbDbTpUsX3n333esc6b+fws8N9aAorJ8cc00qFRLqwbVQXKYH85/w8fGhS5cuzJs3j9GjR5ebR5mXl0fnzp3x8fHhtddeY8WKFVUew8Vq1arFbbfdxsKFC5FlmU6dOjnnU16Kn5/fP05iz4mLiyMuLo49e/bQv3//qzpXqVRiMpmqPKabmUgobxFNmjRh8+bNNzqMajFy5Mhbfoh76dKlNzqEatGxY8dLDrNJksTUqVOZOnXqdYyq6l3uPq9mgcG/2ZUMmbq5uTFv3rxLbvIulFG1DkARY8D+ZwZydimSrxvKdgHVkkyeM2/ePNq2bUuLFi2YOnUqDRo0wGazsWbNGubPn09ycjIfffQRffv2pXv37owePZqYmBiKiopYtWoVUJZMXSg7O7vcKn6j0XjFXwyHDRvG8OHDgbI5lNfT2rVrsVqt5XYmuJDNZnPe37kh7/379zNhwoTrFOXNQSSUgiAIgnCDKPzcqnw196VERUWxc+dOpk+fztixY0lLS8Pf35+mTZs6e6B79uzJxo0bee211xg8eDA5OTl4eXnRrFkzli5dSo8ePVzavHDf0XO++OILl90NLqVXr16MHDkSpVJ53ae7VLTa/WL79u1zznd2d3enVq1azJ8/n8GDB1d3eDcVSf6ns3QFQRAEQRAEAbFtkCAIgiAIgnCNREIpCIIgCEKVi4uLK7c/5bnXZ599Vi3XrOx6er2eP/74o1quKZQRQ96CIAiCIFS5EydOYLVaKywLDAzE09Ozyq95qYcF1KhRA51OV+XXFMqIhFIQBEEQBEG4JmLIWxAEQRAEQbgmIqEUBEEQBEEQrolIKAXhJtWxY0fGjBlT7vjixYtdNumdMmUKkiTRtWvXcnVnzZqFJEnlnnwCZU/v0Wg01K9fv8LrS5LkfHl5edG2bVvWrl1babylpaUMHTqU+Ph4VCrVTfd4RUEQBKFyIqEUhP+A4OBg1q1bx6lTp1yOL1y4kLCwijdVXrx4MX369KGgoIAtW7ZUWGfRokWkpaXx119/4efnR48ePTh27FiFde12OzqdjtGjR1e4EbIgCIJw8xIJpSD8BwQEBNC5c2eWLFniPLZx40aysrLo3r17ufqyLLNo0SIGDRpE//79WbBgQYXtGo1GgoKCqF+/PvPnz8dkMrFmzZoK63p4eDB//nyGDx9OUFBQ1dyYIAiC8K8gEkpB+I9ISEhweU7uwoULGTBgABqNplzddevWUVJSQqdOnRg4cCBLly6luLj4ku2f247DYrFUadyCIAjCv59IKAXhP6JHjx4UFBSwYcMGiouL+fLLL0lISKiw7oIFC3jooYdQKpXUr1+fqKgovvrqq0rbLikp4YUXXkCpVHLbbbdV1y0Iwi3HkVWM9Ye9WBZtxvrDXhxZl/7idq2GDh2KJEk8/vjj5cpGjBiBJEkMHTrUeSw9PZ2nnnqK6Oho3NzcCAwMpG3btsyfP5+SkhJnvYiICJd51eder7766mVjWr9+PZIkkZeXV64sIiKCuXPnOn+WJAk3NzdOnDjhUu/+++93iftc7KNGjSIqKgqtVktoaCj33HMPv/32m7NOx44dy8V84Xtz/PhxlzKNRkN0dDSvvPIKYtdFV6obHYAgCNeHWq1m4MCBLFq0iGPHjhEbG0uDBg3K1cvLy2P58uX8+eefzmMDBw5kwYIF5X5h9+vXD6VSiclkwt/fnwULFlTYpiAI5dm2HMf6+XZwnE9MbL8eRN2/GaqWEdV23dDQUJYuXcqcOXOcIwulpaV8/vnnLnOqjx07Rtu2bTEajcyYMYP4+Hi0Wi179+7lgw8+oEaNGtx7773O+lOnTmX48OEu16qOzcslSeKll15ymcJzsePHjztjnzVrFvHx8VitVlavXs2IESM4cOCAs+7w4cOZOnWq82d3d/dy7f3666/ExcVhNpv5888/eeSRRwgODmbYsGFVe3M3MZFQCsJNymAwkJ+fX+54Xl4eXl5eFZ6TkJBAy5YtSUpKqrR38vPPP6e0tJSWLVs6j8myjMPh4NChQ8TGxjqPz5kzh06dOuHl5YW/v/813pEg/Hc4sorLJZNlBTLWz7ejqOWPws+jWq7dpEkTjh49yvLlyxkwYAAAy5cvJywsjMjISGe9J598EpVKxfbt2/HwOB9LVFQU9913X7keOk9Pz+syP3rkyJG8+eabjBs3rtJdKJ588kkkSWLr1q0uscfFxZX73efu7n7ZuH19fZ11wsPDWbRoETt37hQJ5QXEkLcg3KRq167Nzp07yx3fuXOnS9J3obi4OOLi4khKSqJ///4V1lmwYAFjx44lMTHR+dq9ezft27dn4cKFLnWDgoKIjo4WyaQgXCX7pmPlk8lzHHJZeTVKSEhg0aJFzp8XLlzIww8/7Pw5OzubX375hREjRrgkZBeSJKlaY6xM27Zt6dGjB88991yF5Tk5OaxatarS2C/cVg3gs88+w8/Pj/r16zNx4kSXofyKbN++nR07drh86RZEQikIN60nnniCQ4cOMXr0aPbs2cPBgwd58803+eKLLxg7dmyl561du5a0tLRyv1QBEhMT2blzJ4888gj169d3efXr148lS5Zgs9n+ccz79+8nMTGRnJwc8vPznQmrIPzXyJeZKylnV+9cyoEDB/Lnn39y4sQJTpw4wV9//cXAgQOd5UeOHEGWZWrXru1ynp+fH3q9Hr1ez4QJE1zKJkyY4Cw79/rjjz+qJf6ZM2eyatWqCts/F3udOnUu207//v359NNPWbduHRMnTuSTTz5xeR/OadOmDXq9Ho1GQ/PmzenTpw+DBw+uknu5VYghb0G4SUVFRbFhwwaef/55OnXqhMVioU6dOnz11VcVbmJ+TmW9DVDWO1mvXr0KfxH37NmTkSNH8tNPP7nMm7oad999t8tk+saNGwOIye3Cf450meFsybd6hrvP8ff3p3v37ixevBhZlunevTt+fn6XPW/r1q04HA4GDBiA2Wx2KRs3bly5edY1atSoyrCd6tWrx+DBg3nuuef466+/XMqu5vfJo48+6vxzfHw8wcHB3HnnnRw9epRatWo5y5YtW0bdunWxWq0kJSUxatQovL29r2jR0X+FSCgF4SbWvHlzfvnll0vWmTJlClOmTKm0/MIVlP/73/8qrRcUFITdbnf+/E+SwOPHj1/1OYJwK1K2jsL268GKh70VEsrWUdUeQ0JCAiNHjgRg3rx5LmXR0dFIksTBgwddjkdFlcV1bjHPhfz8/IiOjr7qOAwGAwD5+fnlRk4uNSf85ZdfJjY2lm+//dbleExMDJIkuSy8uVLnhrGPHDniklCGhoY6761u3bocPXqUF198kSlTpuDm5nbV17kViSFvQRAEQbjOFH4eqPs3A8VF8xAVEur+zaptQc6FunbtisViwWq10qVLF5cyX19f7rrrLt55553L7kF7rWJiYlAoFOzYscPl+LFjx8jPz690TnhoaCgjR45k0qRJLl92fXx86NKlC/Pmzasw9oq2Jzrn3BSc4ODgS8asVCqx2Wxi390LiB5KQRAEQbgBVC0jUNTyx77pGHJ2MZKvB8rWUdclmYSypCg5Odn554u9++67tG3blmbNmjFlyhQaNGiAQqFg27ZtHDhwgKZNm7rULywsJD093eWYu7u7sweyMp6enjzyyCOMHTsWlUpFfHw8J0+eZMKECbRq1Yo2bdpUeu7EiRP58MMPSUlJoW/fvs7j8+bNo23btrRo0YKpU6fSoEEDbDYba9asYf78+SQnJ3P06FE+//xz7r77bnx9fdmzZw9PP/00HTp0KLf9WXZ2Nunp6dhsNvbu3ctbb73F7bffftl7+0+RBUEQBEH4TxgyZIh83333VVp+3333yUOGDHH+fObMGXnkyJFyZGSkrFarZb1eL7do0UKeNWuWXFxc7KwXHh4uA+Vejz322BXFZTKZ5MmTJ8t16tSRdTqdHBkZKT/66KNyZmamSz1AXrFihcuxGTNmyIBL3OdiHzFihBweHi5rNBq5Ro0a8r333iuvW7dOlmVZTk1NlTt06CD7+PjIWq1Wjo6OlseNGyfn5+c720hJSXG5H6VSKdesWVMePny4nJGRcUX39l8hybKYDS8IgiAIgiD8c2IOpSAIgiAIgnBNREIpCIIgCEK1efzxx8vtT3nuVdEzxYWbkxjyFgRBEASh2mRkZFBQUFBhmcFgICAg4DpHJFQHkVAKgiAIgiAI10QMeQuCIAiCIAjXRCSUgiAIgiAIwjURCaUgCIIgCIJwTURCKQiCIAiCIFwTkVAKgiAIgiAI10QklIIgCIIgCMI1EQmlIAiCIAiCcE1EQikIgiAIgiBcE5FQCoIgCIIgCNdEJJSCIAiCIAjCNREJpSAIgiAIgnBNREIpCIIgCIIgXBORUAqCIAiCIAjX5P/I/yhf1GeQzwAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 689.875x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -1610,7 +1599,7 @@
     "    _umap_clf.fit_transform(X_pca), \n",
     "    columns=['UMAP 1', 'UMAP 2']\n",
     ").reset_index()\n",
-    "#umap_embeddings['label'] = cell_labels['snmC2T-seq Baseline Cluster'].values\n",
+    "umap_embeddings['label'] = cell_labels['snmC2T-seq Baseline Cluster'].values\n",
     "\n",
     "g = sns.relplot(data=umap_embeddings, x='UMAP 1', y='UMAP 2',hue='label')"
    ]
@@ -1626,7 +1615,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 17,
    "id": "5aefdbf3-6d97-4f39-899e-54d56a9065d7",
    "metadata": {
     "scrolled": true,
@@ -1635,7 +1624,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1645,7 +1634,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1670,7 +1659,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "11387c89",
+   "id": "c5429461",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1707,6 +1696,19 @@
        "text_color": null
       }
      },
+     "02ac7e801b954cb998677974f9d62b4f": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HBoxModel",
+      "state": {
+       "children": [
+        "IPY_MODEL_5c60398d4bc84457980ebe73687f8b2b",
+        "IPY_MODEL_da9ba7c0cee14eb7ba9b75d35924e91a",
+        "IPY_MODEL_d4059344fea442268e888cc815dd1822"
+       ],
+       "layout": "IPY_MODEL_8e97650fde364ba1a930d0551a44bdc9"
+      }
+     },
      "05bfb712f79146bca182fb2e51c48f9f": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
@@ -1739,6 +1741,46 @@
        "value": "Epochs completed: 100%| "
       }
      },
+     "1459b6a0c5db40c0ae15df51fcadf90f": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "2.0.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "145c1b3ae80843228ad54fc7aa1f405f": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "2.0.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "1bf671a71737450ba8c6699581462b7d": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "description_width": ""
+      }
+     },
+     "1f69e7d2d9684366b72e1c5e43d989a4": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "ProgressStyleModel",
+      "state": {
+       "description_width": ""
+      }
+     },
+     "21d9452d8d6647d19cdeedaaf72c397f": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "FloatProgressModel",
+      "state": {
+       "bar_style": "success",
+       "layout": "IPY_MODEL_cc9da61d791f464d94097783ba65e32a",
+       "max": 1000,
+       "style": "IPY_MODEL_1bf671a71737450ba8c6699581462b7d",
+       "value": 1000
+      }
+     },
      "268d826aff6c4a0f9e86b6cd1bb4d0f9": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
@@ -1767,6 +1809,48 @@
       "model_name": "LayoutModel",
       "state": {}
      },
+     "3114092d208f4f61a9cad8d5d17b4c6a": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "2.0.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "35c4aee5be5e436f9040f2ec8792adfb": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "381d77de03e8474a8f75d7ad17991f10": {
+      "model_module": "@jupyter-widgets/base",
+      "model_module_version": "2.0.0",
+      "model_name": "LayoutModel",
+      "state": {}
+     },
+     "39872519a22d4b47b45b49f9a96ca660": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLStyleModel",
+      "state": {
+       "description_width": "",
+       "font_size": null,
+       "text_color": null
+      }
+     },
+     "3a25e1f23d234174a2b30187c11c83c1": {
+      "model_module": "@jupyter-widgets/controls",
+      "model_module_version": "2.0.0",
+      "model_name": "HTMLModel",
+      "state": {
+       "layout": "IPY_MODEL_de3f88dcf121435d98d36bb0d8e1e07a",
+       "style": "IPY_MODEL_35c4aee5be5e436f9040f2ec8792adfb",
+       "value": " 1000/1000 [00:01]"
+      }
+     },
      "3deb127f236742b881d73727c023d08e": {
       "model_module": "@jupyter-widgets/controls",
       "model_module_version": "2.0.0",
@@ -1775,6 +1859,36 @@
        "description_width": ""
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diff --git a/docs/content/tutorials/snmCATseq_preprocessing.ipynb b/docs/content/tutorials/snmCATseq_preprocessing.ipynb
index 8742b1c..070c08d 100644
--- a/docs/content/tutorials/snmCATseq_preprocessing.ipynb
+++ b/docs/content/tutorials/snmCATseq_preprocessing.ipynb
@@ -9,6 +9,12 @@
     "\n",
     "This notebook uses a subset of data from the snmCAT-seq protocol presented in [Luo et. al (2022)](https://www.sciencedirect.com/science/article/pii/S2666979X22000271)\n",
     "\n",
+    "We have pre-processed the dataset to aggregate the methylation counts in 10-kb bins, which we provide on [figshare](https://figshare.com/articles/dataset/snmCAT-seq_testdata_package/26372467)\n",
+    "\n",
+    "Users can rename the downloaded and unzipped folder to **snmC2Tseq_eckerlab**\n",
+    "\n",
+    "The the zip file contains a subfolder named **luo2022_snmCATseq_10kbinned.tgz**, which can be untared and the underlying files can be moved to another subfolder `snmC2Tseq_eckerlab/10k_bin/binned_10kb_all/`.\n",
+    "\n",
     "\n",
     "**NOTES**:\n",
     "- unmeth is not a proper column naming, it actually corresponds to the total number of reads. It can be seen as the ratio of meth/unmeth maxes out at 0.5."