"
       ]
@@ -288,7 +312,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Batch processing\n",
+    "#### Batch processing\n",
     "\n",
     "BraTS allows to run an algorithm for a single set of input images (t1n, t1c, t2f, t2w of the same patient) or for multiple subjects.\n",
     "Each of the available classes provides methods for both: \n",
@@ -316,7 +340,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 8,
    "metadata": {
     "scrolled": true
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@@ -325,46 +349,137 @@
      "name": "stderr",
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-      "\u001b[32m2024-08-30 15:08:43.567\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m46\u001b[0m - \u001b[1mInstantiated AdultGliomaSegmenter with algorithm: BraTS23_1 by André Ferreira, et al.\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:08:43.569\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m163\u001b[0m - \u001b[1mFound 2 subjects: BraTS-GLI-00001-001, BraTS-GLI-00001-000 \u001b[0m\n",
-      "\u001b[32m2024-08-30 15:08:43.594\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m172\u001b[0m - \u001b[1mStandardized input names to match algorithm requirements.\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:08:43.595\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m276\u001b[0m - \u001b[1mRunning algorithm: \u001b[92mBraTS23 Adult Glioma Segmentation [1st place]\u001b[0m\u001b[1m\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:08:43.595\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m279\u001b[0m - \u001b[1m\u001b[34m(Paper)\u001b[0m\u001b[1m Consider citing the corresponding paper: https://arxiv.org/abs/2402.17317v1 by André Ferreira, et al.\u001b[0m\n"
+      "\u001b[32m2025-03-06 13:23:06.497\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m48\u001b[0m - \u001b[1mInstantiated AdultGliomaPreTreatmentSegmenter with algorithm: BraTS23_1 by André Ferreira, et al.\u001b[0m\n",
+      "\u001b[32m2025-03-06 13:23:06.499\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m198\u001b[0m - \u001b[1mFound 2 subjects: BraTS-GLI-00001-000, BraTS-GLI-00001-001 \u001b[0m\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
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-      "\u001b[32m2024-08-30 15:08:44.146\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m329\u001b[0m - \u001b[1mStarting inference\u001b[0m\n"
+      "\u001b[32m2025-03-06 13:23:06.551\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m207\u001b[0m - \u001b[1mStandardized input names to match algorithm requirements.\u001b[0m\n"
+     ]
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+    {
+     "data": {
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+       "──────────────────────────────────────────────── Citation Reminder ────────────────────────────────────────────────\n",
+       "
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+       "\u001b[92m──────────────────────────────────────────────── \u001b[0m\u001b[1;31mCitation Reminder\u001b[0m\u001b[92m ────────────────────────────────────────────────\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Please support our development by citing the relevant manuscripts for the used algorithm:\n",
+       "\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "Please support our development by citing the relevant manuscripts for the used algorithm:\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "                                              BraTS Package | N/A                                         \n",
+       "------------------------------------------------------------+---------------------------------------------\n",
+       " Challenge (Adult Glioma Segmentation (Pre Treatment) 2023) | https://arxiv.org/abs/2107.02314            \n",
+       "------------------------------------------------------------+---------------------------------------------\n",
+       "                         Algorithm (André Ferreira, et al.) | https://doi.org/10.1007/978-3-031-76163-8_8 \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[36m \u001b[0m\u001b[36m                                             BraTS Package\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mN/A                                        \u001b[0m\u001b[37m \u001b[0m\n",
+       "------------------------------------------------------------+---------------------------------------------\n",
+       "\u001b[36m \u001b[0m\u001b[36mChallenge (Adult Glioma Segmentation (Pre Treatment) 2023)\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mhttps://arxiv.org/abs/2107.02314           \u001b[0m\u001b[37m \u001b[0m\n",
+       "------------------------------------------------------------+---------------------------------------------\n",
+       "\u001b[36m \u001b[0m\u001b[36m                        Algorithm (André Ferreira, et al.)\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mhttps://doi.org/10.1007/978-3-031-76163-8_8\u001b[0m\u001b[37m \u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
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+       "───────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
+       "
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+       "\u001b[92m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m2025-03-06 13:23:06.556\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m329\u001b[0m - \u001b[1mRunning algorithm: \u001b[92m BraTS 2023 Adult Glioma Segmentation (Pre Treatment) [1st place]\u001b[0m\u001b[1m\u001b[0m\n",
+      "\u001b[32m2025-03-06 13:23:07.049\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m381\u001b[0m - \u001b[1mStarting inference\u001b[0m\n"
      ]
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+    {
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+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2024-08-30 15:12:50.584\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m349\u001b[0m - \u001b[1mFinished inference in 246.44 seconds\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:12:50.586\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m189\u001b[0m - \u001b[1mSaved outputs to: /home/ivan_marcel/tutorials/BraTS/batch_out\u001b[0m\n"
+      "\u001b[32m2025-03-06 13:26:34.594\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m404\u001b[0m - \u001b[1mFinished inference in 207.54 seconds\u001b[0m\n",
+      "\u001b[32m2025-03-06 13:26:34.595\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m225\u001b[0m - \u001b[1mSaved outputs to: /home/marcelrosier/tutorials/BraTS/batch_out\u001b[0m\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['BraTS-GLI-00001-000.nii.gz', 'BraTS-GLI-00001-001.nii.gz']\n"
+      "Inferred segmentations: ['BraTS-GLI-00001-000.nii.gz', 'BraTS-GLI-00001-001.nii.gz']\n"
      ]
     }
    ],
    "source": [
     "output_path = Path(\"batch_out\")\n",
     "\n",
-    "segmenter = AdultGliomaSegmenter()\n",
+    "segmenter = AdultGliomaPreTreatmentSegmenter()\n",
     "segmenter.infer_batch(\n",
     "    data_folder=segmentation_data_path,\n",
     "    output_folder=output_path,\n",
     ")\n",
     "\n",
-    "print([path.name for path in output_path.iterdir()])"
+    "print(f\"Inferred segmentations: {[path.name for path in output_path.iterdir()]}\")"
    ]
   },
   {
@@ -381,55 +496,133 @@
     "By default the algorithm that won the most recent challenge will be run on the first available GPU. This behavior and other options can be adapted, e.g.:\n",
     "- Select a different algorithm from the available constants (Enum classes for each challenge) with the `algorithm` parameter\n",
     "- Select a specific GPU if multiple are available with the `cuda_decives` parameter\n",
-    "- Force CPU execution with the `force_cpu`flag (will cause an exception for many algorithms since many do not support CPU execution)\n",
+    "- Force CPU execution with the `force_cpu`flag (will cause an exception for many algorithms since many do not support CPU execution, check our [overview tables](https://github.com/BrainLesion/BraTS?tab=readme-ov-file#available-algorithms-and-usage) to find CPU capable algorithms)\n",
     "- Save the generated logs in a log file with the `log_file` parameter"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2024-08-30 15:14:13.367\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m46\u001b[0m - \u001b[1mInstantiated AdultGliomaSegmenter with algorithm: BraTS23_3 by Fadillah Adamsyah Maani, et al.\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:14:13.371\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.utils.data_handling\u001b[0m:\u001b[36madd_log_file_handler\u001b[0m:\u001b[36m41\u001b[0m - \u001b[1mLogging console logs and further debug information to: /home/ivan_marcel/tutorials/BraTS/segmentation.log\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:14:13.372\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_single\u001b[0m:\u001b[36m121\u001b[0m - \u001b[1mPerforming single inference\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:14:13.383\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m276\u001b[0m - \u001b[1mRunning algorithm: \u001b[92mBraTS23 Adult Glioma Segmentation [3rd place]\u001b[0m\u001b[1m\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:14:13.384\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m279\u001b[0m - \u001b[1m\u001b[34m(Paper)\u001b[0m\u001b[1m Consider citing the corresponding paper: N/A by Fadillah Adamsyah Maani, et al.\u001b[0m\n"
+      "\u001b[32m2025-03-06 13:31:01.989\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m48\u001b[0m - \u001b[1mInstantiated AdultGliomaPreTreatmentSegmenter with algorithm: BraTS23_3 by Fadillah Adamsyah Maani, et al.\u001b[0m\n",
+      "\u001b[32m2025-03-06 13:31:01.999\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.utils.data_handling\u001b[0m:\u001b[36madd_log_file_handler\u001b[0m:\u001b[36m41\u001b[0m - \u001b[1mLogging console logs and further debug information to: /home/marcelrosier/tutorials/BraTS/segmentation.log\u001b[0m\n",
+      "\u001b[32m2025-03-06 13:31:02.001\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_single\u001b[0m:\u001b[36m155\u001b[0m - \u001b[1mPerforming single inference\u001b[0m\n"
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     },
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+       "Please support our development by citing the relevant manuscripts for the used algorithm:\n",
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\n"
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+       "                                              BraTS Package | N/A                                          \n",
+       "------------------------------------------------------------+----------------------------------------------\n",
+       " Challenge (Adult Glioma Segmentation (Pre Treatment) 2023) | https://arxiv.org/abs/2107.02314             \n",
+       "------------------------------------------------------------+----------------------------------------------\n",
+       "                Algorithm (Fadillah Adamsyah Maani, et al.) | https://doi.org/10.1007/978-3-031-76163-8_24 \n",
+       "
\n"
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+       "------------------------------------------------------------+----------------------------------------------\n",
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+       "------------------------------------------------------------+----------------------------------------------\n",
+       "\u001b[36m \u001b[0m\u001b[36m               Algorithm (Fadillah Adamsyah Maani, et al.)\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mhttps://doi.org/10.1007/978-3-031-76163-8_24\u001b[0m\u001b[37m \u001b[0m\n"
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+       "Output()"
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+       "\n"
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-      "\u001b[32m2024-08-30 15:21:19.623\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m349\u001b[0m - \u001b[1mFinished inference in 345.79 seconds\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:21:19.625\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_single\u001b[0m:\u001b[36m144\u001b[0m - \u001b[1mSaved output to: /home/ivan_marcel/tutorials/BraTS/segmentation.nii.gz\u001b[0m\n"
+      "\u001b[32m2025-03-06 13:33:55.200\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m404\u001b[0m - \u001b[1mFinished inference in 172.53 seconds\u001b[0m\n",
+      "\u001b[32m2025-03-06 13:33:55.201\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_single\u001b[0m:\u001b[36m179\u001b[0m - \u001b[1mSaved output to: /home/marcelrosier/tutorials/BraTS/segmentation.nii.gz\u001b[0m\n"
      ]
     }
    ],
    "source": [
-    "segmenter = AdultGliomaSegmenter(\n",
-    "    algorithm=AdultGliomaAlgorithms.BraTS23_3,  # Use the 3rd placed algorithm of the Adult Glioma BraTS 2023 challenge\n",
-    "    cuda_devices=\"4\",  # Select GPU device with ID 4\n",
+    "segmenter = AdultGliomaPreTreatmentSegmenter(\n",
+    "    algorithm=AdultGliomaPreTreatmentAlgorithms.BraTS23_3,  # Use the 3rd placed algorithm of the Adult Glioma BraTS 2023 challenge\n",
+    "    cuda_devices=\"1\",  # Select GPU device with ID 4\n",
     "    force_cpu=False,  # default, could be set to True to force CPU\n",
     ")\n",
     "\n",
@@ -450,15 +643,15 @@
     "## Algorithms from other Challenges\n",
     "\n",
     "BraTS provides the algorithms from all available recent BraTS Challenges, i.e.:\n",
-    "- Adult Glioma Segmentation\n",
+    "- Adult Glioma Pre Treatment Segmentation \n",
+    "- Adult Glioma Post Treatment Segmentation\n",
     "- BraTS-Africa Segmentation\n",
     "- Meningioma Segmentation\n",
     "- Brain Metastases Segmentation\n",
     "- Pediatric Tumors Segmentation\n",
-    "- Inpainting\n",
     "\n",
     "The package provides a separate class and algorithm constants for each of the challenges.
\n",
-    "The examples above were demonstrated using the class and constants of the Adult Glioma Segmentation challenge.\n",
+    "The examples above were demonstrated using the class and constants of the Adult Glioma Pre Treatment Segmentation challenge.\n",
     "\n",
     "In an identical way you can use:\n",
     "- `MeningiomaSegmenter` class with `MeningiomaAlgorithms`\n",
@@ -470,41 +663,126 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2024-08-30 15:24:09.444\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m46\u001b[0m - \u001b[1mInstantiated MeningiomaSegmenter with algorithm: BraTS23_2 by Ziyan Huang, et al.\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:24:09.448\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.utils.data_handling\u001b[0m:\u001b[36madd_log_file_handler\u001b[0m:\u001b[36m41\u001b[0m - \u001b[1mLogging console logs and further debug information to: /home/ivan_marcel/tutorials/BraTS/test.log\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:24:09.449\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m163\u001b[0m - \u001b[1mFound 2 subjects: BraTS-GLI-00001-001, BraTS-GLI-00001-000 \u001b[0m\n",
-      "\u001b[32m2024-08-30 15:24:09.478\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m172\u001b[0m - \u001b[1mStandardized input names to match algorithm requirements.\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:24:09.479\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m276\u001b[0m - \u001b[1mRunning algorithm: \u001b[92mBraTS23 Meningioma Segmentation [2nd place]\u001b[0m\u001b[1m\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:24:09.479\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m279\u001b[0m - \u001b[1m\u001b[34m(Paper)\u001b[0m\u001b[1m Consider citing the corresponding paper: N/A by Ziyan Huang, et al.\u001b[0m\n"
+      "\u001b[32m2025-03-06 13:47:14.189\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m48\u001b[0m - \u001b[1mInstantiated MeningiomaSegmenter with algorithm: BraTS23_2 by Ziyan Huang, et al.\u001b[0m\n",
+      "\u001b[32m2025-03-06 13:47:14.199\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.utils.data_handling\u001b[0m:\u001b[36madd_log_file_handler\u001b[0m:\u001b[36m41\u001b[0m - \u001b[1mLogging console logs and further debug information to: /home/marcelrosier/tutorials/BraTS/test.log\u001b[0m\n",
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      ]
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+       "Please support our development by citing the relevant manuscripts for the used algorithm:\n",
+       "\n",
+       "
\n"
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+       "Please support our development by citing the relevant manuscripts for the used algorithm:\n",
+       "\n"
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+       "                            BraTS Package | N/A                                          \n",
+       "------------------------------------------+----------------------------------------------\n",
+       " Challenge (Meningioma Segmentation 2023) | https://arxiv.org/abs/2305.07642             \n",
+       "------------------------------------------+----------------------------------------------\n",
+       "          Algorithm (Ziyan Huang, et al.) | https://doi.org/10.1007/978-3-031-76163-8_13 \n",
+       "
\n"
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+       "\u001b[36m \u001b[0m\u001b[36m                           BraTS Package\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mN/A                                         \u001b[0m\u001b[37m \u001b[0m\n",
+       "------------------------------------------+----------------------------------------------\n",
+       "\u001b[36m \u001b[0m\u001b[36mChallenge (Meningioma Segmentation 2023)\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mhttps://arxiv.org/abs/2305.07642            \u001b[0m\u001b[37m \u001b[0m\n",
+       "------------------------------------------+----------------------------------------------\n",
+       "\u001b[36m \u001b[0m\u001b[36m         Algorithm (Ziyan Huang, et al.)\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mhttps://doi.org/10.1007/978-3-031-76163-8_13\u001b[0m\u001b[37m \u001b[0m\n"
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-      "\u001b[32m2024-08-30 15:24:10.041\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m329\u001b[0m - \u001b[1mStarting inference\u001b[0m\n"
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+      "text/plain": [
+       "Output()"
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+       "\n"
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-      "\u001b[32m2024-08-30 15:24:56.671\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m349\u001b[0m - \u001b[1mFinished inference in 46.63 seconds\u001b[0m\n",
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+      "\u001b[32m2025-03-06 13:47:57.705\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m404\u001b[0m - \u001b[1mFinished inference in 42.95 seconds\u001b[0m\n",
+      "\u001b[32m2025-03-06 13:47:57.748\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m225\u001b[0m - \u001b[1mSaved outputs to: /home/marcelrosier/tutorials/BraTS/men_output\u001b[0m\n"
      ]
     }
    ],
    "source": [
     "# e.g. for the Meningioma Algorithms\n",
     "from brats import MeningiomaSegmenter\n",
-    "from brats.utils.constants import MeningiomaAlgorithms\n",
+    "from brats.constants import MeningiomaAlgorithms\n",
     "\n",
     "segmenter = MeningiomaSegmenter(\n",
     "    algorithm=MeningiomaAlgorithms.BraTS23_2, cuda_devices=\"1\"\n",
@@ -526,34 +804,119 @@
   },
   {
    "cell_type": "code",
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\n"
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+       "                    BraTS Package | N/A                                          \n",
+       "----------------------------------+----------------------------------------------\n",
+       "      Challenge (Inpainting 2023) | https://arxiv.org/abs/2305.08992             \n",
+       "----------------------------------+----------------------------------------------\n",
+       " Algorithm (Juexin Zhang, et al.) | https://doi.org/10.1007/978-3-031-76163-8_21 \n",
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+       "----------------------------------+----------------------------------------------\n",
+       "\u001b[36m \u001b[0m\u001b[36m     Challenge (Inpainting 2023)\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mhttps://arxiv.org/abs/2305.08992            \u001b[0m\u001b[37m \u001b[0m\n",
+       "----------------------------------+----------------------------------------------\n",
+       "\u001b[36m \u001b[0m\u001b[36mAlgorithm (Juexin Zhang, et al.)\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mhttps://doi.org/10.1007/978-3-031-76163-8_21\u001b[0m\u001b[37m \u001b[0m\n"
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+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5f0263422713483a8612c30375409821",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2024-08-30 15:33:01.399\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m349\u001b[0m - \u001b[1mFinished inference in 15.22 seconds\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:33:01.401\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_single\u001b[0m:\u001b[36m144\u001b[0m - \u001b[1mSaved output to: /home/ivan_marcel/tutorials/BraTS/inpainting.nii.gz\u001b[0m\n"
+      "\u001b[32m2025-03-06 14:15:29.139\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m404\u001b[0m - \u001b[1mFinished inference in 12.63 seconds\u001b[0m\n",
+      "\u001b[32m2025-03-06 14:15:29.140\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_single\u001b[0m:\u001b[36m179\u001b[0m - \u001b[1mSaved output to: /home/marcelrosier/tutorials/BraTS/inpainting.nii.gz\u001b[0m\n"
      ]
     }
    ],
@@ -577,12 +940,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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ptKmcKKiV2Wo2mwWWikqLKUtUcpyb3k/vr7m16jzlWC1/zTHq9TqWyyWazWahZZ9HTZj7OxgM0G638dlnn0WeayAQuDXodDqphoHECvUC03qq1SrOzs4SWaJtV3PGPkkZGuZ6XCMSGj0ALusaQtOJeF61WsVyuUykDokrvQ+AVAzNphbUEV6ozXuqg6K6idEBjVzTodH0KhZpM1WW9RIcT8fv9/u4d+8eer0eKpUKjo+Pr7WJXeDtRTgOgS8MHiYGgB/90R/F4eFhcgoYtu33+8l5mM1mqTORhob5OtcJg4qB76uQ9bQgn2Oul7cKXmWxeD+tV6CgVsdBj5V1bmIOqioizWfl/DxsrhEaMmir1QrNZjNFHzTnlSF+1kEwajIejzGZTCIsHQgEXgk89Wg4HOKnfuqnMJvNsFgsklxrtVoYjUaFbniTySQROtQxGjHWSARlv26kpka4OwPa/lqdEZ6Tq3nQmjdGO1ReAxeOg6bLquPg9XbUEarDVD9wTvosqnu0aLzRaKTicEb1NcJNB2N/fz8RWrPZLMilwE6E4xD4wvDgwQP86I/+KAaDQQoL1+t1nJyc4Pz8POV5HhwcFHI8yTRtNpuUYlOpPG8ld3x8nNrxDQaDglClAOW+C0CRKVLBrEY4hTSVCt8HLhSHCmIeIwvG1CAWbfMeGuHQcTUq4vdT9kyjI1qwp0V7nEer1UKv18N0OsV0OsVnn32WlItGPNbrNQaDQSqS++ijj/AHf/AHX+jnHggEAlfBT/3UT+Hw8DDVcgHA8fFxgQVnGqh20WOOP2Uszz87O0tkFNuV0jjWaK5HZX0jUOoGGv/aqEPlM691HcG/6fBUq1Xs7e2h2+2m9FQn1rRjk7Z5VccjF/ngWB4B18Jt1kEwtfXx48epDlDH4bp885vfxP379/Hs2TP8j//xP2J36sBWhOMQ+FxgPv5oNMLR0dGl7hYUrI1GIykDnuOCrtVqJVaExjYLglksrIwVcBGWJjwNSR0Hh6cR6Y8Xqmm4l+lLmquaG0vnqGFiV1j64/PT9Cd/n6jVaqmFLIvjdGwqisFggLt37+Ib3/hG6rJxcnJS/uEGAoHA5wSjy4PBAIPBINWpaUEzGXvWjWldAskS7nHTbrexXC4LnYQWiwVarVZKHyKoH7Qw2iOuORmsEWlCySk1+qvVakFnqc5jpCEXXdB7a02GRr3dOfG5aQQ+F2GnDp7P58nh8mgKX7fbbezv7+PrX/96agn+7NmziFAHLiEch8ALo1J53lni8PAQ3/zmN5OAnE6nKXzLH01PIkvvhi1blTLyQHaHfbMp/LRYmgKaEY6cUFYHQHcB1ZC5h5+BiyK4zWZzqZZAw9N6T47D+2vqlTJWvL8zRTmloEybz5ehcHZb4ly9cJAb5rVaLRwcHOD//b//h0ePHmE8HkdRXCAQeCmoVqs4ODjA0dERvvSlLwFAku+MOrMVdbPZxHA4TOmfOTKm2Wyi0+mgWq1iNpsl2TafzwtttHkN76Fyme+p7iEh5E061LDXaAN1AM/RTTuBYoSEjouz/LyO68RzVJ+oHHdw/tpyVs9jATc7MLGekE6XOhok5QaDAX7iJ34CT548wSeffJJat4aOCCjCcQi8EBqNBr75zW/i4OAAe3t7BeFKxoh9q9kNiUI0l7evefkUuLwPw8bT6bSQH6q7MLtBriFdZ1b4tyqBXF2F9sjebDaYzWZJiDLi4CwVr6VQVicmh0qlkvJ0KehdCXh/bn0WRj8ODw9TChML3FzhKCv25S9/GXfv3sVoNMJHH32Ek5OTKIwLBAJfGA4ODnD//n3cv38fjUajUBPAdCTqCcr8XK0A9QONXzZ7YEtsds3jPg3tdrvQ5IJGvOb3q3xVB4LOgOoHNei1hbfus0BdwTantVotFUSr/vE6N+BylFyh0Qg6Gdq5j+/zOuokvb5Wq2Fvbw+tVgsAMJlMUp2IRr85t81mg6OjI+zt7aHX6+HJkyf4+OOPcXZ2FjtQBwCE4xB4ATAPdX9/P+WVUljW63X0ej00m0202+1CS1RNM8ql56jw1tZ3QLG4WLsfAcWC4lxOqBvQdDw8UpD7W1/T8OazeKqVhsL1+Zyp0hxbKqncs+jfXszHtdF0KBYV6k6i+qyst9Axj46OUkEiAMzn89g4LhAIvDAqlQr29/dxeHiIg4ODtDuyRgDYppQd9ihPXdY5CaTnAMUOSmpg8zovNNY5ekRaZaW37QYupyrlIs2s61MZrjrJIx8ACk5KTj/4Gujz6zrpevkPU17ZWMPP5z05ZyWkGIlhnQR34Q68vQjHIXBtvPPOO3j33XdxeHiYjHluxDMYDJKi8DamOUENXAhi7Uakr1WYMiVHmSEKarIt7jz4WBTcnjq0LRzLaALTg3hPrbvQ8DbnpsXRGo5WcAdsz1kFUHC6VBkBF+yUOlka5tfUJs2fbTQamE6nqFaruHv3LtrtNk5PT9FsNvHpp5/i+Pj4Gv8NgUAgcIFqtYqvf/3r2NvbQ7/fT/KPOfTs5kM5R3nl+sGjuZqGxCg23+Pv8/PzAnECXERpdaM3JXw8ssFnAC5kq7YxLQP1k3ba45z0ntQjfE6NXvAZcylRTDGiTuN46qh4JEXXp1KpFNJaVQfrvki1Wi2lBx8cHKDX62EwGKDT6eDJkyf48MMPX+TfIvAGIRyHwJVAx+D9999P3SKq1WraAK3T6aRQszNIrhCAoiGeK3xWwU8G3JkedxAcXlCsTgMjCNohg9B7axoRz9dnYB9tZ70oyDWUvFqtkvICirmunmvLeg+va3CnQ1k2vs8uVApv38d9MGazGfb39wtRpM8++wx//dd/HUVxgUDgSqhUKuj1ejg8PMTR0VFyEKrV592FqBdoUNNxcCfBUzQp96gDNBKrbLnrCG1L7eerc+AFxXzfCSXKaO2Qx/sxEs0ffZ+yn4Y+9R7HYwqXpi/l6iGoM/ibUX4SVDy3TOdpZynqoLLovEavZ7NZ+uy63S5OTk7Q6/Xw4Ycf4uzs7IX/XwKvN8JxCGwFhUmv18NwOMT+/n4hv5RdlegsKPPhKTi50C8FmqfsqDLRaEAu7UfDuepA5KIWGhHY9sy5+fr7/rcqGx73Qmh/fh+Xz65pTCrUNZzuz+Zz82M5JUqFxc+LXUmePHmC6XSa8oYDgUAgBzLgg8EAo9Eo6Qg2xqC+0CiDsuM5skgNZyVjcik6aowDeYJJDWz9rQY9r1WiJofr6gd9Hk+DckfH76l/69owfYjP4fovN46nPSk8XUsdJR7v9/uoVqtpbwgA4Ty8pQjHIbAVdBru3buXIg3clZIFV3Qi3GlQIQ/kC4XJ1qjjoAIux9ZQoGkuqBe3uWIBLhgsZV+IXPSCYWKOT8Pb6w1c8eimdfrsGl72eyr4HHw2pkapse/rqWugyladOS2o05/pdIrN5nn+8f3793H37l1sNht88MEHEZYOBAJb0Ww20e128eDBAwyHw7RfD1lq7gDNwmc1Up1Y0ogucJH+ozLdCZFK5aIjH4BUZ8CUG56rKaXA5f0SyqLZfF8Nfs7D9R3ThnKpVpqqxHkwis1ogSPn0HDuHvHW59ONUTlfdQw0yqH6jfNm9ISpTefn50nnj0YjNJtNfPLJJ/jjP/7jz/W/E3g9EY5DoBRkiw4ODnBwcIDRaIThcJjYJDoM/NFQJ38r+04oO0/hq92SNOTqkQgABQbKWapcVIPX8LXnder16pTwXD4PnZzcPFXYsvuFtmvlfhS66Z3mqKoiyLXXyzFPfK7lcpk6ZahTRKeD66vMm3bH4DMsFovU7vBb3/pW2pTvk08+ibSlQCBwCc1mE4PBAHt7ezg6OkKv10tprXQWtO2qG6qampOLNlDukZiiHHbiRomdslQl/lZCyyPZek5Z5ECvAYppoBqhdR2lBjuNem0Vq/V7TPOifuS5XCvtJqXrpdEUTWOdzWZpPyQl6qh7tF7EPwu+Tyes3W7jq1/9KkajEZ49e4YnT56kCETg7UA4DoFSVKvVgmIYDocYDAaF4mAt3HWB684CoU6Ds+U5waU/WqOg7/NYLlWHr7cxSjn4eHQMysYn1LFRpagtV/3+np6kysafV+/DMReLxdZuUwxtc0xtE1ir1VKNBBVSu93GyckJnj17hqdPn2I+n4fzEAgEEmhUdrtdDIdDDIfD1C2Jhi/PUYfBI7auL5Ts0fvkIhQenfaIbE4X8Xq911X0g95bZaGORdKIc/NotKclUV6rU6F7SegcVT/wHp7+6s/CMbl/g9bCuX7wegqep8066LRwg767d+9iPp9jsVgU9rEIvNkIxyFQCrZWfe+99/Dee++lvs7KbCvb4Qx5TvhuNsXN1HwvBFcQAC45I8pSaQqOzsMjB3xvtVol1kXnSSOfx7Q2gQqBIXN9TnUmdM7c70GL75QFUigDRQHO51Dlwh8qAM5puVzi7Owsvd9ut9PYuQJ1Rhj4mmOdnZ0lxd5oNPD++++j2Wwm5yF2mQ4EAkSl8nx/hIODA3zpS1/C+++/j06ng2azmWS85/M78eEGPYAUtaVc9s3gtABY5WIuNVbJLR4Diqk+qiOo2yjrcwQVx1HHRqPNlON8Rj6Tzo0ylwa4dkbyOXkkROeUm+N6vU6GPOc0mUywXC4LUWjqJ4+ucINWoLiP0tnZWdJL3NT129/+dprDo0ePtv6/BN4chOMQuAQKvl6vh9FohPv376cUJRU8yozkcjpV4LngZ25nWYTAFU5ujnquHlcHQFkbClF1fJSZ0ZAxmRoqBYagNQdUQ8vOpFHYLhYLbDabpLyoYFiE7JEaLaTm3DR3lc4P588dtZnipE6BzpehbipSrlW1Wk3tEZvNZprfdDpFpfK8U8qDBw9Sy1ju6B0IBN5eUA/0+30cHR3h3XffTelJNPa11goojyzoe8BF5yTKV0Uuykv9UyaXlIGnHKUhr7qDMp86QnWC6gnVIbwnGX2NhNBQpzPgDo7qGhrkqh+oN5w00+fQdVAHxjel8/RZ1TucD9ddiTi+32w2Uwco7tS9XC7R7XZx9+5drNfrtEFq7AP05iMch8Al0MjUTkrcrEfDmyqoykLNHkpVVn2bAVqWBpRjmnwcKoMyRohKQR0fD+3yN/BcgS0Wi0sGvjoWZf2zdTMiKggqhlzo3dfPn0vHYAh6sVgUCqA9JYDjar2G3pPt+cgUsmaiVquh0+ng6OgIy+USx8fHmM1msXtoIPCWg3nv7KS0t7dX2I9B9zBQg5pwo19BuZVLfVGjuSw11Q1tIC9LfTzqB2297Y4Dz9OUIgApVVTlq76vOkLnpbtZ6/10T4ecjmDEwHUfx1MHZDabFaIvrsPVoVHHhp8F9QrJo8VikfbK6HQ62N/fx/n5OT799NPkDAXebITjELgEOg1f//rX8eDBA4xGIwAXDkUuJOx5mXyfAkuvofBSA1oZdp7njAiP+6ZoCo8gcAwaxNPptGCA63nKKBGnp6c4Pj7G8fExGo1G6iilzA/PZ7EagEKoerFYAChu9MbzNZXJlaEK89lsVmC5zs/PkyG/Xq8xHA7TZ8M1dqaLYHRCw/h0bMhI3bt3D9PpNEUYGo0GlsslxuNxOA6BwFuOdruN0WiEb33rW3jw4AH29vYAFMkJyh41iIHLjTL4W41iN+ZVTmouvspIgnJNZRuhhrzWDjB6O51OC52OPGKixBKARLJQFvd6vVQnpvdkeqw+rxJo6/U6FYDX6/UUqW61Wtnouxv3jG5z7sBz3cUoQL/fT+1xudbaiUrHI+FHZ0H1M/C8UP3w8BCr1QonJycpO+HJkydYr9dRKP0WIByHQAGDwQCDwQB37tzBwcEB+v1+wZBl9wXgctEWUFQK+remM+m5GrbleV5zoOk7PnZOKejfdAToOGgbV4aD9Xz+zfqB8XicOhZptEHrH9RBUvbIj2udBHCRy+usWa44WiMmjIAw3UmL1XWdODdfV49M+Hpyvvysh8Nh6t39wx/+sOAMBQKBtwe1Wg39fh937tzB4eEhRqNRyoln9JJ58VrHpqRIDpqW6frBCSmPHijZkpNnu3QE9cJ8Pk9OgaaEKjT6sFgsMJ1OcXJyUtjVmc/uBdAkZXQsJdQ0hVVJKXU2co6DR0GoH9T5oCPlkXp3SPgZa92FO3p8xnq9jm63m9bo/v37ODs7w8nJCWazWfZzDrwZCMchAOCCAdnb28P+/j7u3buX6hr0/UajAQAF45ldeYhcClIu9UhZF3ccvHBOlUJOIeSgjgMLipVF8hxadxym0ylOT08xnU5TG1Y+uypGXsu10bFUSDNNis+ghXQqwFVB8JgrBj4PIyC+uRuvU0VGaO9xXqNrzLlzXDopZK7YRSMQCLw9YD3U/v5+chx6vV6hZkpbP2vTB/5N5NJPFV4TkLvWIxjeetVfa3qUpjtpowlNUaLj4OQLX89mM0wmE5yenpY6DpyDR8819YnvU8dQL3FennLq66fpTUouUdfQcfAmI9QPAArrm9ugT9eSz8hUJT7n3bt38fDhQ3Q6nUIDlMCbh3AcAgCAw8NDPHjwAIeHh4nBprDXegSms/AcClfPueS1OQaIr8uYdw/n8jUL8nTfA+1W4QKeDJIa22RCvMZBmSYqhPF4nIq9tCgOQJovC8Y2mw0mk0lhPwo+HxUrlRHnq8XVPg9tkce58z405LnPBg18dwBUKazXxY2CqGw011WdN51ns9nEcDhEtVrFu+++m5Qc06QCgcCbj69+9avY39/H/v5+YqQ9nYcyijqC0UnKH5UX3mlIGXDKGELbiKpOUblH2cZUIRYbE6ojvI01dRBruNTx8bQlMvpPnjxJzL7WKmhEQudBXaI6wx0i14XL5TLVjuicgItULW21Sj01m83SenS73UtOg+pWACllWNO71KlRHeXzqNfr6HQ6eOedd/D48WOMx+NENEW9w5uJcBwCAJDCjtqqzTtHUAkwpKz5rCpkPbTsjJJGHJxVyhX1atciZUM09Ul/KOCpFNgFgr99Liqw2dqU5/P+7XYblUqlkOKTU27qROWcGb+n5svyPc+p5Wt+JmSKNJycgzsv6mDk0pp8DQmyiGQbp9Mpnjx5cmktA4HAm4tWq5WaZAAX7a1V9mvkWeutPH1HZSGwW0cwdZVkR45g0qYQSohwPDd8mcKqOoJkk8+FRBOjrdxQjZGRVqtVcGy0LkBJGI++6DGP1HM9dTNUN9y9m5TqE09hdbh+UL3qDTZy+kGfl5vWDYdDHB4e4tNPP036NPDmIRyHQGLy2+12gX3WPQ8ooMgyc5MwNUC94FjrFDwnk1A2wzenocDapRQ4poaYtViMaUdkQXQcgkzSdDpN7ev4DBSK5+fnhaJiAIlNo0ClMc9n1uiDK0yusTsOGonRdVKFw7SBXJqTr4d2xXDFpkpBn0M/Iz4vi+Km0yk+/PDDSykEgUDgzQTlDQt4NfpJY5VpNpQJGpn2iCplFY+rzNf3gXytg0cetFuQElqqIzTFlLpB2XoWEvNZ9HpeN5vNMJvNUvoqcNFhis/He9fr9UJdXc5Z4viMMruu8DoLXUf+rWvH9aUz43pSoZEijdKoM6Dzy+kJPbfRaGA4HOLo6AitViuIpTcY4Ti85ajVavjOd76Dfr+PTqeDTqeTBLqmogwGA7RaLbTb7cLmMlQMNKidMSfbokLYGSoKKGUnaHxrYbQe83amKmjJCNFZWCwWODs7S8JWN7jhdUxjYiqTMvHEbDbDYrFI66Rs//n5Oc7OztKeCADSs9Mho2PB9dF2rlp47ffVNWN6FNePCo7KWa+lU6ab5KlSJXJOgyobOhwAcOfOHaxWK3z22WfpmUNBBAJvLtg9aTAYoNlsot1uJxlzenoKAJhOp6kla6PRSBHbxWKR5J+mwKjj4Hn8auBT7jHKoew9ZSnHolzjmDTGCR1zOp2mtqJMqTk7OwPwXEbqJpquV7Q2TdN4KQ95reoHjXqrw7BcLpP+5L10szpNXVL96vUGWnOoqbGa9qrpwfzNNVMZn9MPriP4Gej56/Uao9EI5+fneOedd9L6sB1s4M1BOA5vMbhPw3A4RKfTQavVQrfbLRjy1Wo1sTE0alUQAResR66Ii0LQO/3kGCVtYeqCxhkmjuXnUMAzpMzX7Gak7ehUCCprpIpHn5HPob21tVCMBcOMVPA+ZOn4bExRorDVAjx9Ni0QVCiDp8yaKgauh4b6c5EWZ8L44yFwrg87LL3zzjs4Pj5OjJqmtAUCgTcD+/v7ODw8xGAwSLtCd7vdguFLXUEWnoQS5ThTegBcIkho6Lqc88JiJUEAXDJgVcZ5iqhCaxT4w7QjpgU5aUT5zig75Tz39nFnSGvwdG5MddLIL+fpxr5GljVFyyPWlNU6X00P89oGhesHX0NdZ11HfS69Z6PRQK/Xw/n5Oe7du4flconT09PChqWBNwPhOLzFODw8xHvvvYder4d2u412u429vb0URVDWaDqdpr9ZkKuGL3ARmlZBqoLYuxG50OM+B2pY54q6PEUJuGA/yCAxerBYLNJeBAyn5qIJ7E7UbrcLEQE+I9vkNZtNdDqddJ0+G9eHBXB0hpSp4VppRyd/Vj1XHSpdU10DXxN1yDhHPruvnSsGdxzUKazX6xiNRsmZ/PTTT1OqVmwMFwi8WahUKnj//ffTBqDdbhftdjvtGQMgkTLn5+c4PT1Fs9lMzoV2maMc1PRWEiMql3KkEWUsZZhu4On6gefmiBQa76ob2Gaahm0u/RMo1ohNp1MAFzKcjhN1GKPOKn8BpHtzPK0p8PQkJddUPxAqs/246gyuha6LGv76fm5fIb2X/mhKM8dptVqoVp9vJPq1r30Ny+UST548STZEdOJ7cxCOw1uIWq2GBw8e4M6dO+j1emi1Wuj3+xgOh+j3+0nIMBSsefzn5+cYj8eoVCoYDAZot9totVqFNKOyTXco5Nm+Vdl3su4akuVYvqEQx1Ajl52HTk9Pk6DlBmbj8ThFVLS4Wdl61jTU63UMBoNLEQQqlU6nkwqlCc5pb28vrdPp6WkhhM11pNPBewIXCkg3DdJ1ZNSCa+GFdT4XVQzak5vjlxX/lY3Bvxn27vV6ePDgAb75zW+i0+ngT//0Ty+xWYFA4PVFv9/H0dER9vb20O120Wq10uterwfgudxoNpuXoo6r1QpPnz5N8rLf7wO46CTnUVKOBVykvWjHPi26ViNYjWQavFqPx3N4n+l0mlpsU55x87bNZpOcGt1clH9rtzvOQckS6iamsSq5xPv3+/0UPdCW1lwXRjw4D32Pa6PQNdQiaE1b4nk5aARaG22o86ZpSvo5KaFEqCP47rvvpv+LP/qjP4oi6TcM4Ti8ZaAwHw6HKdJAY5iRBAofzSHVois1iDU/1Ytuc+FR4LLwVweA75eFTV3ZKDtPB4es/9OnT1MUgP3GPSyrXaH4bIy4cB0ApAJpOh/uDNG4p9DWfuA+X96LLJy2gtU18N/amtYFt95H19D3bCByLFIO6jiocu90OhiNRhiPx4ld03a3gUDg9US328VgMEgprNQNSr64zHCjlT9sha3MvcrgXZFSHd9TKFVHAJdloM9R21ovFgucnp7i8ePHyWDXXZKVXNKIr5IxGiXhcXadyqUq6fkcX1OyOFeN4nvLW9ervn4atXfix8/358zp65x+8Pu7fqADNRgMcHBwgFarleyEqHd4MxCOw1uGg4MDHB4e4vDwMEUYRqNRYpJc8JLNUOGjtQDeq5nsRS6fXpkMjyxQ6egxCjQXShyLc2Tu6HQ6RbVaxWKxwOPHj/GDH/wAlUoFd+7cQbfbTf2sdV7qPHBMDdlSALdarRRhocHP65WRpwIZDAaX8jq1/Sq7b3AsMmq+u6d/Fux+kVME+hm4g+ThcGWStikFD4MDF6zgwcEBptMphsMhgOeK+Yc//OHlf7pAIPBaoFKp4P79+6n2bTAYoNfrYTQaod/vX0pFLSMdVL5MJhM0Gg10Op1CYbGy94TKS3UIVAcpueLRaB7XOVHGMSWpVqvh2bNnePjwIX7wgx/g3r17GI1GGAwGl5wH3oPyl2k62gyENR1M9WV0mPrMoyrV6vPi62azWWhf66QTnRl1wDT1V8fm+CS9fB1zTp7qCD6jd0/aljrGtXYdRD01HA5x584d7O3tpYYhH374YaQsvQEIx+EtAwugO50Oer0eBoMBut0ums0mgKLhylAj03goNBUULNotgkKI3X9ckBPqPNBBUWZFmRBlY5yVZ0s9jTrU63V885vfRLPZTMKcykA7QfG5lDnJRVcAFJgm3S01FwEBivUPXFtPR6Iz4Q4S31PlqOvr9/bCszLmjXPXzla6ns7gaWRDP5/NZpPSELrdLk5PT6O7UiDwmqNSqSSShd/vXq9XaJqhbDsbaGjXN49u8r3FYlFoluER07L5UDZSduu9NJqqaTS8lvdn2hOj0dVqFaPRCN/+9rcTK65Og6a1UifwOTUiwPFVL/DZckXfmvajUWfqVtWvdIg0Gq6EFedCnaJRA3UqPCLAY663fE6q/3TsXB0Ez1Hno9FopP8fphFHgfSbgXAc3jKQ+WERGwualf3RsDNweU8Ah4ZS1RhVgVQm1JVd93CpCz9Cx6LTonPgc45Go1Sop4qGz8t6ARVm+qwaBdH5lIWgXSnwGk9rUqijso29KwtN6310TXIKy6/z0L4rE73W15z5viwWPzs7S8oiOmgEAq8v2HabOoJRTmWnKddUbun7CpUdrit43PUDcFlOuYOQM5D9fsDFRmp6b6YVMS2LRq/WWFAfaVRA5Z8/nztN+rc+hxvqrlPc4FfHQZ9Nj7kc3/Y7F60uW3e/voyQcnBOqh/o5PCZAq8vwnF4y9Dv93FwcJAYJYZVtUhKhZ+3SFWGR1twljEYmpeZYz34W43z3HjKPKngZscjbZ9Kx0DnyWhBp9MpKATuSeFKkPfX9CM+A3Ni6XzklIAKRn8mfzZ2YcopAT4jxykz7nPIFcXlnlOVkUaXdK5UvlqsSGbu8PAQZ2dnWCwW2N/fx3g8Tp1HAoHA64NKpYL9/X0Mh8PU+EKJJc/vVwJF0y/d6C0zOvUcfY9jExqZ1uYbKgv1vuqYaG0Dx2DxskaFa7Ua2u12ku26o7Q6Ozo/jUZwLG20oU6Wzlk3dnPnxwkmdRx8fSqVSmGNNaKdW0c9/iL6QYkunS/XmRF0rkGtVsNoNMJ8Psfx8XFq5318fHzp3oHXB+E4vCVot9v4+te/juFwiPV6nYre6DjQOKRw0BBqjiEiqEi02EuVgheu5YSYG+nbogtuXPM6T3ECLoq/GGXg7sc8l06DMlJaqMzx9f46J2XXck5Rjl3Tc6lkyei58nDHwOdQ1rLWoyA5RZdTsAp39rTYUVv0rlYrjEYjzGYz1Ot1/PCHPww2KRB4DXF0dIR33303yQ92U6LjAFwQSF77pLsjq8FJIscj2Tkd4c4Ax/ZjZUy5klV6HufHOepctMaN0RXqsdVqdUkv+J4EOTmr8+T4fg51h0fK9Tyeo/qB72mBus+Bx9QxUZ3gqUa+xrm5aA0Jz9XzeY46W2x7OxwO0/Ef/vCHhQhO4PVEOA5vCWq1Gu7cuZOKlFQhOPNQxlDwtRu4XgS9CyoAfTw/x+fhApvHVfh54bP24Fbj2cPX6jSUGe3uyPCeVIg6t1wURv9Wp8Zb2ObG87mogM/VPfBcR+45PNKRcxq4Rt4Fqt/vY29vD+fn5/jwww8vtY0NBAK3H91uF0dHR0kuefvqMvKHKCN3vAh62/U5g7Tsvq4jVKaV6TAeV8eBkQF3kHbpCJ9HmX7Qc5zgKTOiVT+wNq4scpP72/WDXle2/jqGOmFlTpE+s+oG1RGbzQbdbjc5E5988kl6rtAPry/CcXiLsFqtUrES9ypQBoasizJIDH9qCgtQ3JPBGX4VwISnLOVyY9WoBi4b3sr0kHGh8aqGM++nCoHnM8rAHxVwrix0LFUg3lvcO13o+nBO/kwaqVFGjs+aUygcz2sinOXLfU4Ej+sYHl1QpeGOAvecaDQaaTdZ1sl0Oh18+umniWl69OhR1nEJBAK3D/y+s3EG918ALkdvKQ/5nst7NXJ9IziVeTlixWXRZrMpyHeVKV7b5VEFzpHylmNoW1hu+lar1VK6DdObqCOUQGGBtUIjGk5AueGv6+Md/dTZ4o9HbHg/h66dNvgguL5KjKlDp+vokZBczaJGclxX0AZg6hfb+T569CjVHT558iT2d3hNEY7DWwJ+yVutFnq9HhaLRRL4FA4uvClUtDe0Qh0ODctqaFZrEbxwTO/JYzl2I6co9Li/T4GstRucCxWCCnqdh66BdrVYLpfo9/uoVCqFXUE1P5dC2aMeng+aY3yuGg7OfUbbIkTb/tbrPIfXoy5UYOy+xWdlXjOf68GDB/j000+xXC5x7949nJ6e4vT09NLzBgKB2wV+n3u9HprNJubz+aVCaI82szagUqkU2nTrOSoPNYLBe6qMVKiT4DrC4VEO1y+5Obk81vQkTWP1cZyUOT8/x2QywWazQb/fT44I15P6SPWK3l9JNf3J6SZfH10TnavOL7dWuTXOQddRdUTOZqBu8DnReazVanj33XfRaDTwwx/+EIeHh1gul3j8+HHp/QO3E+E4vEUgC99qtbBYLAq9qHMCWo1SMiZlTLh2o1BB7IwQz9d76H1dQLoyyAlTF7iqrFRBMZrgeao6nh7j2iyXSywWi5THTwHJMV056rp4iD93TplCUFzVafA102P6Oze2M2s6Ph1Id2b4GXOMu3fv4vT0FOPxOO1lEY5DIHD7we8+Dd/FYoFWq3VJ9uQcCACFHZYJl8tKMmhkc5tRzLnpPP21Gtu5a3weKrOVBNJotDLuOUJFaza4sRl1BO+lEWqdV85R0LnpOQRlrZNL+tnpseukD++KDOf0AyM7vGez2byk0/ncdJzu3LmD1WqFjz/+OLVpDcfh9UM4Dm8RaARPJhOsVivs7e2lTd/4M5/PC5EDCoyylBe+73n6FLR0NHLhUIfuMKrn54q51LAli1XWto77OzDErB029N76HoDU6Wg6naYQ62q1QqfTSeuh3SO4OZxu0EYF4EJU2xtuE9rOIvlrZa/cEfJz/biyRx6+1lC5OylqLCjTWKvV8LWvfQ3T6RSLxSKNEwgEXg9sNs839SS58s4776QUH37nZ7NZgShSGehyCCjuR6MpR2qYu4zJ6QjqE2XueY7rCE1Z8jRWoFgAzHlwPyDqCZWHdCpms1mSlXze8/NzPH78OLU31+59nC+AlNJJ4onz43Mwok+Zqu9t+7xUdqte5N5KTmzpeLl0Jv1xHUFwTJJJ+v/Bz4Pnq0Px3nvvodFo4OHDhzt1X+D2IhyHtwjqCBAuZHPOgTLKahTnNpyhQuD5Kqy8zoHwtB4V2C5Qc0z6LjafoWffpEgFJBUMnSse54Z5w+EQlcrzTfFms1nqRqWKgfN0FoyvvV1gTmDrWuq4+ozuFOSiDoQrcRfUXueg8FQ0ZfQ0kqN5sM1mE4PBAHt7e3j69CmazSZGoxGOj49DSQQCtxiUgTQ4gQu5nTPE+T6vddmq53qOvjP3Kot9bJejOTniKaNOILl807/pJC0Wi0tz4lz5XIyqcD24HwT1A3UNi8v1OVgQzLx+n5Ouq0cP/Fl0fvrsuShDLgKja1wml/0zKYuo51KiXI/xfe7rsL+/n1qy7u/v4/T0NOodXiOE4/CWgMw8DXGySM4k5FrHqWD3gjMX1i6wKWy0noDj62tlV1TQ8FqOpcVkrhRywkvrGhjqdaFLBUAoy9JsNtHr9dL9z8/PMZvNCsKSrBOv0zapqjh1bSjs/bgqAFWSOUZOj28T/jlnMAdXDP4Mej89X+fWaDTQ6/Wwt7eXWLjRaITxeBxdNAKBWwwaxtQJJFLKdARQNKqV0FCZnpPNSljQoL4quZSLRGgajxMdhMpOlV1aDK330bE1Uuzzb7fbqc35ZnOxQzYj1pyLRsQ5Tyff9J46D59LzpFyQqyMaHOojsitbZnzpfd0p8znxr8ZjeF+P5XK831DGO0JvB4Ix+EtQbVaRbfbTcZvu91O4VmGRbUVHVDO9KiQUWHlBdTaccmLbzlOLkzrrUVVGOaYenUGNFqgaUcaDVG4wOb9F4sFJpNJ2vyH6UlUHLxPt9tN86HC8NC4F8PxXuqAKfgec2W1Y4V+Hs7U5RyLsqiEOnY+Dx3TN/mjMZEbn882Go0AAA8fPkw7hgYCgduNer2Obreb5DTTkBhJdHkOXG4DndMRalhqjZxGNNVByaUvbdtQk/PQRhwqnyi3KOtYv0D5pvfLySqV2VyPer2Ok5MTLBaLpEPViCbBxK5CPMZ15TPnui2pXGfzCZfrXu+Qc/C4tvp5laUMb9MPHFsj5joP1T2eDpXTD61WCw8ePMDx8XHUwL2mCMfhLUC/38dwOCwwMtxUBigWuRK5EKYKNz1WpjRUyJSFRLcJLz/HhVHZOCrs+J4LZL2uDJVKpdBFiJEJzVHNFVhrBEMZpdz9tt2fcDavzDnYBl9DVZb+ufM44XUW/rmqQ8j/I4ak5/M5NpsNOp1OUrKBQOD2oFKpYG9vL5EgNLRpDAMXOkLlvOsMjpVjpbcdU/mRk81ebO0o0w9lclF1Qa4ZxrZrHUxJUoOZulVlIt/TiAYdGd9LKbcGOYdMn0dlshNrLrdzyK2hk1GK3D2o93wdczUYjUYj7Uw+Ho/RarWSsxW4/QjH4S3AaDTC4eEhgAvWmJ0zNISqDAWFHIVHTogom8Ox/TxlkXLCLycA/f1c0a9e46w7UMy5VUWh4+YUjTsgbL1arT7frIc5rcyH9RC7PysLx8uiHXr/MgFdtl67rtX12RbxcRaJz87xNQ1L39OULl7P/yWmLDHi0O/3MZlMwnEIBG4ZqtUq7t69i8FgkP7mviwaKXASBLhcQ+VEEvXINgfDN1UrM3xz4/OcXBMJhesIJ5E8mlrmhOj7fC7d1Zn7YFSrVSwWi0J9CO9DA5spWmUyWOV+jqzz17nPI7cmPpbqWV9HL4zXZ3fdQj1Q9p6ew5QlZj60221Uq9VwHF4ThOPwFoAtWPv9PjqdTiraorFLwb1cLhN7os6ACtRc/qiyUTSQc9EJwhkKCnJ3LsqUSW4swovacoKMoWpvL8d5a7tWbt7DsH2lUimwSToHLT7X0L4Ww+UKC91Z8fXls5Q9vzsXubCzOjm8j352uu5cA5+fpwDo+c5QVatVDAYDnJ2dYTwe4/T0tHSX1EAg8GpBBrjf76Pdbqf8fOCi7TRru1S2qQzPGfi7dIQbwSoLtX4iZ9RTd+0iT/waN2o1Es9jvmO0R1z4PiMzWj9Iooi6h8+i9X66zxBThlV2+vwVTszlIukOH9PBzziX2quEEH+o0/S+2nY2R0L53Hu9HubzOdrtNmazWZBKrxHCcXgLwDZwNIC1zabm7SsoWL0YzV9T0HixL5Avjsox5irIgctdNpxdUuh7ufuqse5OSI4toZDkD1kjOgzKGOkzlDFT+oyq2MrSwnJrvYtVKmOqrvK3K2O9h89FPyNV6ursqIPVarVSi0IvoAsEArcHzWYzGcDUEVqD4HVblAU0LnPyzAkHNdJdBhE5HaFjKil1FR3hzkiOude5K7nhTLz+rbskVyqVFGXQvW50x+yylFZHLpLgz5VLEdNrfWxft6voByeEfF39GfzzKXPmWItCB5Q6Qus4Arcf4Ti8BWi1Wuh0OgX2nPsuaPcHFUhuKHphlAoMLZACLrMbajgrU0I4q+GKQMfR3/7a4UV0m80m7eeg9/Y2quzjvVgsMJ/PU03DYDBI7Qq5fjxfGSldP2XknHnJPYMzcS7sddycg5Vjd5xFciWfU1BlisE7I7mDxmgFQ9EMR3Mn2kAgcLtAw7fVahV0BB0JkkuU08r+qxzX5goaCaC8VVmhUWCfi+oAHY8y1lNjFTkCp+yZVR6qrPV2tHwWNdypH9brddo1mvKO0VrWiGw2m8K+EBxX9aanc6nuyslh1Ss8z8fWaIfq5pyuLlsL1d1lel/v6+vtjUHoTHFzQdUP6mgFbjfCcXiD0Wg0MBwOMRgM0Ol00pc6t1EbcNEujcdzxq0KIe2ExJDrcrlMbFVZYXCZ0NwWoXDWRFHGhHB+uW5BLuSUQW+32+naxWJReJYc1ECnU8aUL7/G1zXHMOUiAiq4/f3c+XwmwiNHGuXJ1Z9se+0Ggzojm80GjUYD6/XzHWjb7TY6nU7B0QoEArcD3W4Xg8EA/X4/EUhl8hi4aInt8sLlqssXXssUF4965/SREh6647RC5+gEFqFz1Rx+kkbuiKh+coOdRFu73U4tptnGdZt807HVUPZn1zm7A5Ujnlx/+xro6zI9zPdURyjBp5+hvpeLJhDaAVDH53mMNlBHaLOWwO1HfFJvMGgE80vpxql/sf0YoeHHMsdBBa6OofmjRI7N3hamLGONcqySj50zqt2A9kJqPo/ueKpCzdNzdP66K7Qruhwjk5unvpdTzHp+7m+PfPhz6vn6DIqyz2PbfNUJ5DowTS4QCNw+sP7NHfsc4eO1AAo3tmnEagQVKOoM/qazkjNsc3LM5b3+drjM3eZkuJOg6+DyUo10RmQoX13nUYdwDE0FK5uzvy4jcXSdyvReWWqTj++6YJtNkJuHz8efRSMPqh/YDr7sMwzcPoTj8AajUqkk9ptdlHICRHNZgcs59/qF1rBzbkdjFWK6cZs7Lh721hSYMiM4pzS2/b2NAeK9c4wXw9DL5RK9Xg+9Xg/tdjuNrx2p9D6bzSaF+b3WI2ece7GxKprc56Troeuo16sj42No6Jr30RQEV+q6pjmnh+/7/wENBjJznU4H5+fnURwdCNwyKPurBJNCCYGcoe0svtZBaSSXxrYa3gSNad6P19PodkfFCZUyB2Dbb47t4/lzNxqNQuoVi5kZjdaCcso93c+Hz8frfU+M3Nx1PXmORx9yDoRGd3R99Hn4t9fp5a7RWpecjuZ6uL2g+i5XD8d032aziW63CwChH14jhOPwBqNer2N/fx/dbrcQCnTh6MYo8Fzw+EY5m82m0G3HGQke16KxMlYi1/0od74yKSrQyjpJ6H29BgAopmlp7iqfdbVa4enTp5hOpzg/P0e/30e3271U1KX5/JynMutqtOcK08qYIX02/naB6uydX+/rxvXgnD1VzddYxyhTGGXsFtkkz7/tdruYTqcYj8cIBAK3A51OB6PRKBm+vsGjyho1VkkQUB9QR3jrZiUT1JhkHYGSKmq8AkVCxuu0dG683u/rzgnHUpnIuale0WYaqv/4vOPxGM+ePcNyuUS328VwOExpR5vNptCIhOtDues1BT4nfR7XhzkniZ+Nwsk5Xps7V69R8qlsbq4j1NnwGkn+dv0A4BK51mq10O128fjx4+z8ArcL4Ti8oSDb2+v1kkLwLzkFay6UqewRhQVzQl1wA0XjWBkGHctD4X6vbcXDqjz0WO5vZzwUOWWlim+1WmE+n6fcV+aiKovvXUb4Q1bJlZXOKRd9yDFHOo4rwzLmv2xMv7d/1moMOEtU5vzl5qzvaV3IZrMpjXYFAoFXA27SSGJEW6yqjsgRNHqOvs6lJ5Vdq8jpIJV1OdmWk/852bjtvo6cbtM5rlarFG0gWcS9fnidRvDVadK9G8oItdzzlemH3DN58bNe42Pm6hZyY7ge0M9FdZKOkdNTTvzxh/ohauBeH4Tj8Ibi3r17ODg4wGg0Sqk1/GKyzagWnLmgp5CkItA0ll1GYM4w57geGlaow6HClcqJysUFGI1+Mia5lBxlwvgMquw4Fu/bbrdTmo12UvI6Aab68Pk4tgtlNc4JHUeNbF17dVJcWKuS937mObaNLJ+zSvzbi9uUbco5b/p8PF/T09rtdnKm+DyBQODVo16v40tf+hLu3r2L0WhUaNPN7yt1hHaPo6xQBj7nMFy10JVyhePobtVOfuhvJzSU5HIdoVEDlX/ARRGvRhXY5ILv67OpnhmNRuj1emnXY6bkKnJF5qp79Dz+dtaez6rRINVnml6mHQI1PSwXjcmRTTmCSYkgX2+9Vh1Jhepv/VyZHsfPP1KVXh+E4/CGgqG/wWCQDN5Wq5W+8IvFIoVT1ehTQ083SNMahVw9hLNDetwNfTdc9T2guKmNvk+DPMeoUKiqs+H5tRxTC9n0/MVigdlslnqaUymQNWKKkq6FClh3bAgVwG6IE87uqeFPheTKZrN53l6Wn5MLfmeGVJF4lyi/jvm6/L/Ifd76TPzRGgfOvVarYTKZoFqt4s6dO3jy5ElpyDwQCLx8VCrPW7D2+330er0k15rNZvpuzufztFmoym6m4DA1iTKGexgAuGRk6hjA5fo1Qp2TXAS6LPoBFNNXc119VOZppMQNZL+OkWhugrfZPO+MxG6FXDOmsbquVIM6F1kpq1dwWetGOZ9Tuxh6q3HqtZweyEUOynSzvuZaKkGmTmNOP3O+OT1Sq9VSFOfOnTsYj8exg/QtRzgObxjI9rDNWbvdTl9yOgmVSuVSNEGFqDIaRC49B8h3s8ixGwAKBi6vzQlMVzAcR8/x8KzexxkWD51TeOVY/sViUSjq1eIwsnLuDPn8/fPwtfJIjB9zJenrpNcul8v0WanCzSkjna86CV4X4k6GKjxnjcrg0RS2Yez1enj27Fk4DoHAKwJTMKkf2u12ku9kzKkXNIIIXBh/ynirAZiTi864u/zTOgOV0TnHQsfw15RhuX0j3BHRuecILj8HeK6/uBcN148dgTi+5+5zPI08lLH8Oh/XFUoklRnmeoznck8iXWsn/wj9O6dTdX3K9IuvZe4z0uejvULnbDgcYjabheNwyxGOwxuGXq+Hd999F4eHhxgMBin/kkqBqTUU/tzmnQKPxVzOjKiRDVywHf6afwO4JGh0TBc+fk2OVVIGx1NzeI6z33q9CyyuC/BcwE6nU5ydneH+/ftpYxp9fgCJrS9j+ImyIrOcQvB1o8Ii27fZbFKv8Gq1mjaxozHO9zmm7xJOaKhe+6l7Pq6uD4+zX3nZ5k/6OehrOrFUfBGODgReLY6OjnBwcIC9vT10u91LOoJM8nK5LKQYalqJpuwAlzvBuYzQKKQbzs5WU8aWpe3oPXLIRT3dMM/V4XGeOjfOYTqdYrlc4vT0FP1+H8PhMBFLm82moB9zpJmvD+flDLyvX+6ZVT9rJJo6grJaIw3L5TLpFRKJvmMz10x1LOeohBk/M69TYJcpX2tdz9xnxag+gELzlcDtRTgObyBoSM7nc0yn0yTgWORLgc+8QgoeN+xzIcuyEKbnxBMuHMlkaU5njvXRZ+FvCizPp3WD3Ofmzk4uAqBKgoa3Gv8uOHMCMceqcK15nUddAFwy1v24rjEZNTI0ei8qBjXO3cFR+N8aVfD/A01R0Ot17Xg//TwZvXGWMhAIvDpoauZsNkOv10t99dV4p/GZy2nPGcPbZIxGsd2g1ginvse/9TovolV5o3Ol7FUHZpd+8LQql2eUg2w4ouvgJJLqqJzOoKz2iMRyubykB3RNynQE50m9rh2d+J7XQKh+2vX5qXOlz8PruR5OIurYufXsdDopvSv0w+uBcBzeMCj7sFgsMJ/PC+lKRFlbUv1CO2PiUMORDoFHKhj6JovlgoVz1tcuZNUwVqXgRcO5CIT+LivcUvZJN+dR58YN6RwjpEJSDXm9lsI8x6b5OudC9Uwf4I9HNHKpRK6c3XHxNaJC4XE6Ubpe/uw+D96DEQc6He4MBQKBmwW/w6ojBoNBQUeoPPG0JCDffSinIxSa+qTXu3zh/d2gJrbpCBrHLuevoiOc7OFxrzXTTT45jjsOfl+dr5M9LptXq1VhjyHXDy5r3TnLtcXNrY9GjTwF1+Hr56lk6tDlUqp8zkStVksbEGrKWuB2IxyHNxDKrPd6vVTABVw4DKvVKrUaZboSUGyT5jUOyui4oKUCms/nSRixVR2LtpSdoXGuOaI6NlEWUVBj34UrBZbm5/peBMoKsSi82+1eYl80VKsMEpk5Z9FU8KrwZ5qOMvaqbPjsLA7USAzPpbLXe2rKkd5Lz+Nas+CZ4xH8bHSfD4adGYqn0lQnM/d/p8+1Xq/Tuo5GIzx9+hSnp6ehGAKBVwh1CBqNRtrAjKyvbsrJzRvJgjsJUbYJqButrB+bTCZJhpC1b7fb2Y5vaqSrQ1PWzlTlktZMeJotz+V5HMvlOH8osxuNBgaDQdoMVOer89PjlMG6TkresKC8Uqkkma16ywkmzkVTRjkWx1D9zPE4P01D0s6KJOI0UqKfJ3Uk58L/B/2faTabWCwWSf/kwHG53tVqNe2FMRgMov7tNUE4Dm8YXPiqIUwjkl90ChhtIec5jUB5MZYqIApBZQ2U1dB7k/Gi0GI+vo6be60h0s3mIqTLFn6uHJwNy7FOqqRoWHuhnq8Bn8vv4ywWoa0L9XPxtfTrfM76o5GSsjVTByLHYKnzxOv4/6LzK2PwfD39PXUSmU8bjFIg8GrhEVQ1TGkgKpnh++9sY6hVFlIOMNJYqVQKnf14z1zradc93gWujLhwOcjugdp6nGPmogFlOoKpvszHz0XNdc67WHe/lvqBMjgXkS4jbPQ91Q256LOeq3qOJI/eX6Fj5Wozcs6czknX2XU0SS3t5Be43QjH4Q2DC1kVlmSYVCis1+tU9KZC2jcD8nsAF4qGLDmv4TG2CmVNg6Yx0YhUZaH3y0UdeD7vrwpJWSkX1A4VZFrXoE6OCn5dG66ZsuvunLmyoPG+XC6zaWOeBuBz1Dn5a1emqmT0HGXGNAXL5+wKVpWg/w+UCXlnwehU+v4WgUDg5uGGvxu8/FtZdP3u6vUemSaUlNDIJ3XNer1OG20qoaJ7EqgcUXIoJ3dUXun18/kc6/U6GaZOJpXpCtcRJLY4fydTVB+ozPQUJl1j/Vv3zWBLVx/b6xl03p4FoDqM0QlH7pzNZpMcCL2XElWafqzzUqdMr/M5u34Ix+H1QzgObxgohMigO8OtUQY3Ol0BqHDSvEk13MlQ6KY2NBQZupzP53jy5EkyspvNZqGbB9kbnZM7EfxhKBS4yOccj8fpfkzJcuHkaVe8nt2JOG+NgvBcr/fIGeyubNnzezqd4unTp8npOTw8TMXqvt4eNdFxPUUpp7A1RYgKm0yQRh8qlUra+ZROjP/os6mj6WlhufnzOm0DqNGmUAyBwKsD5YLuOeA5/ZQDjUYjXZf77rqM4jkkkCjbOZYy9Uz5WSwWGI/HmM/nyYis1+sYDocALmrDVBZ7TQRfU+4pE86Oed1ut7B3kc/fowxcCz6XRl/cIfAU17I1ouHN8cbjMSaTCU5PT1GtPi8UPjg4uBQd1nlxTJ2vzlPJIiekqN90nTytTKMHqhM0dUzn4BFqXQuFr6vOTdOjQz/cfoTj8IZBBZnnnDrD5Iaqvva/dZxthrSHOAk1JDVflspDGY2yOapzM5vNMJlMUtcP9iNXIe6KQOeiz+jtVZV1zykBdxxyrB3nNx6PcXJyAuBCUQJFhsif150ld3x0njknwxUZ15br7oyjdynRZ9XPu2w9fV19HnTENCIUyiEQeDVwMskjDW4Q8xw3sB2ua3QsQiPPLtdIerHtM6MM7nBompXLGo7Dwu/xeFyQka1Wq9D+0+WvPw9QjLzw/r5nhRvxfO1z9vmdnJzg7OwMZ2dnhVrEsrXU++nnkNMnnk6k0Plwzp4qpf8HZTrC04fLPnddP31fx9eN8wK3G+E4vIFQwabFUc7WuFHuDACRY5mA5wI111qVgkjDudXqxf4D2l+61+sVDFzOT50INezJiIzHYzx79iztSNztdtHtdpPCUaaMz8p7KLRvOe+nObH6zGr0O8PkDNV4PE5zPDk5KYTK9Tl4vefwukLNsTtcZ50Xj+tnzUjDfD5Px1i0nvts9TN0peCOaS7NSj83KoTcmgYCgZuHfn8BFCKTnnqpclOJG3+/LBLhNVXA5eijyhbqiM1mk+qiSAhxDNUTKo90zPl8jvF4jIcPHwJ4rn9WqxV6vR4ApDHd2HU9CDxPTyLpxXv5ZqBuxPM5Oa6uk+4Z9PjxY0wmE0yn08IeSzkyzdd7GwlFPaafmRv3TB89Pz/HdDpNpB5ltutQfT7OUYu+9f9Lf3SuTtBtNpuCjgj98HogHIc3FBoyVjB0S4HBc9UgBS634wMuws3O/ruw5TXsssTUqcPDwyQgnIHWNCWGhHVMF+7z+RyTyQRnZ2dYr9c4OztLbA036FHBpYa9zlkVDg3dbrebztE18TA158pOUvV6PYWdP/nkE0ynU8xms9RyrtfrFWpM1NHi/fQ3U5PKFIgzdupQEGTs+Hnzs9Ee35rOpOvP59TQv+dG55Sv/x8yh1mfLRAIvDqoseupJdQPavTTWNQORaofKCv1fU87cYJqsVik/YY2m+dR4729vaQbKLcoW3NysiwSslqtMJvNkn7YbDaYzWYYDAZYLpdJF1G+cU2cCKHM4zG2DmWtA6/jb68v5PqwfgEAnjx5gmfPnuH4+Binp6cAnhvx3W43pbE6uefkGl97apbL5lyk2uV2rVZDp9NJ47F2UOW2ptZqVMJTZpWwytkJbo/QkSKc2AvcToTj8AZCjU2FMhnObrvjAJSHFnNQIeEGP5kE5tTSeFaGy/M5VSHo+K40NA2HDgTzZBmS3vZc+nxco11Grs+LjB13Fh2Px2mnUeA5Y9Vut5NSUKWdu5crWD/uzkPZ/PQeur6ubHUdc+M6E+eRj9y4ylDmQveBQODVgDLLDXs1NnMEgBqmLuOVhOE9VM6p7Mjlt5Pdpo6gztCfbc+zTV6q48CINGvsvGDa4ca2RzdyEQeXrWTyGfllXcNsNktOEfUD07NcP3A8/+06SvV7mc7OPW9ZjUJOP/hYfN+jS653ytZG/7cCrwfCcXjDQHaDuwvnGGktDKMS0ff5hS9ruecGvDoqOjaZDL1O709WiUqCzEMuvA3kU3Y83P706dPkRBweHibFoNf4GMqEKEujys8Zf10DRldOTk4wHo9xenqa9kFotVoYDocYDocYjUYF9sqjKDquKlV9dhWy/vm40ixLI2JxG59VPzOyfV6M6Gvj0RJPM9P/C01ZC+UQCLxaMF2UhqzKI2eW9XussoZygex4LrXVjcNc+ipTOP06bZihkQff9BIoGqPqDCkhRQZ9MplgvX7eerTX62E0GmUjuS6j9Rk5D5WruVoEffblcplSkh49epTWvtlsotPpoN/vYzQaFToc6lgcz3WFfmbaZZD6l3P3z8Y/H6JSqRRSlPSzo07QFCiuZW5fCa0N4Y+mOPH/wT+zwO1HOA5vGCj4WHy1WCyS8a6sgQsQvq+ChEY3nQg/x1NpPCxaNjfPadxsir28nc12wUaDXDew4ziLxQKnp6cpParX6xXqKJydopBz5aXMEv/W88kgsbBtOp2m+67Xa3Q6HbTbbfR6PQyHw0JBnq8PBaozVzm2x0PAzvr7etdqNfz5n/85fvd3f7f0nJzizL1frVbxL/7Fv8Dh4eGlFC6fO5DfZbqsyC4QCNwMcjoCKBrsu5wBprFo3RZz9J1M0p+cDPJ58d50GEgq8d4ajXB9xjEYcVa5zvNnsxkeP36cujgNBoNC+1N9TtVJTNP1yIMTUsBFATTTVZ89e4bZbJYcNkYZ9vb20Ol00O12C9GPXVEBd7K4vmX1EWXrrueXfSZ6P10bJeT0mOpv4CLNyeega6zzCXLp9iMchzcQ/CIzl90jD0BxU6/cl1rZJBcUOSZJx3BjX8f08HNOMOkz+Ht8TSaKHTeUPWfLVhZOa9tBN4o5Zi6Vp8yQp4PCAryzszPM53Msl8t0P+ar9nq9tCtr2fP5cb1fTuHmnCllxwAUujn98Ic/xN/8zd9cutd1UalU8IMf/ADHx8eoVqt49913CxElwv8ncso2EAi8Wmi9k8sY/e7mDEslgZzkUTla5jSUGbJKVPjY25Ajg+r1+iUGn3qRaUuTyQStVgsALslozkdlq+rAHLnFZ+Y9Tk9PUyE0dTGdGta98bXrpm1r5PdzXanrUBbBvw58fXmsUqlcir5w7Z2Q8rm5XRL64fVBOA5vGDSFZbN5ntc5n88T+04hMp1OkyBT54LGuKcYaSE1BZUqHd4buLzTcC7cq2FkFxY5Jp0CcrlcpmhCt9stsGer1SoZ8MvlEk+fPk1sWr/fv9QJo4xt4fw1NUfXYTabpTzVzz77LJ0zHA6Tw9DpdC4Vga/XF7tn65i8J1mtMqXtSoLz08+c+MM//EP8zu/8ztX+aa6IzWaDf//v/336+1//63+Nb37zm5fOYUtFbgAIXHT6yinnQCBwc1DShh1+qCNo8FGWUjdQ1gPPI9HtdrvQOhS42NfHo9Ks9VKiJqcjlFhyI9LZ9pyO0Ho3znMwGKDRaCQ9SNk0m80Keqvb7aLf71+KIlDGutPDboJuSAPAdDpNrVafPHmC6XSaotDdbhd7e3uFiLlGT8qi3PxxMi+nK3bpXs41p0/0fY9G67Pr+Zy3prdyrjl9R3KPKdUci/oh0pVuP0KLv0EYjUYp5DkYDNButzGfz1OYVHMTz87OCm3XyHjwi6sGnuYqMtfRHQ4XRC50lIHIhXgJZzMokPR+FNpklFh0zDAwjWkqiOPjY1QqlVSA5sa6wwvyKOjYAeT4+BiTySRFGBhV2NvbS8LSczmpgFwoemRDN9rzVDCez/VR1ovrPpvN8Ju/+Zv45JNPPud/0278+q//empv+HM/93P4yle+UgiPewhb62YCgcDNolarYTQaJZZ7OByiVqthPp/j0aNHKVLLiOpsNkstUZvNZkq39NbKLitdR+T0g+sIdRhyP26ce43VarUq6Aeew4iDyhwaq3zO8XicjF5Gh5WwcXnlOmy9XicjeLlc4vj4OHV0Wq1WSR9z3TUlSWs/NIXX70dovYHqCV1TXSe+LnPWcvD0L3WOytYjFyXy85WI02tUZ4R+eD0QjsMbhG63mwRfu91OIVgWw1ExsJhXO1joDpE5wQ0Uw7Bq4HpIGsAl5sTDlrmwbM6BoGBRQ5rHmVNL5gt4zvbwehr81erzHTmpSPzeuflwDB1nNpul8DMdFKYl9Xq9FAFxFkqVpAt4X4OyHOHc2uhzjsfj5BB+73vfS6zby8T3v//99PprX/saOp0Ozs/PCxsZ6Xyd9QoEAjcHkhyU+5SJm82mUO/AKMFisSi0z/ZOR0ROR9BhUHnmxmuZrqFhvg0uY51o4RisSwBQIJ1UtnN/G0ZdXB/k0mfcmSGxRIeBkW86XYPBILvBmxNlOn+9l1/j6+rj+VpRbzqx4+tZpofLHCnV01yTsnayOb3rY0Sq0uuBcBzeEFQqlZQryVSjbrebwqHs488vKdNpNOSsY3nHHt8DgIyHX6MsVNmmc9qONRed8PQcGum8Xhkqzp2KTQ183rNWqyX2Z7PZFNrCumFPqPKczWY4OTnBZDJJz97pdNBqtTAajQpF3roe/K3sFNfNFbArDH5eObZJFS8APH36FP/23/7bgnK4afzqr/5qmusv/MIv4Kd/+qcv9XznZx+KIRC4eZBRbzabaDabBSeCkQXqCHbE6/f7hc5HOpbKdCeVKLM9h51sPoAkN91g1F2E9Vq9F1CspVIdoXKf9/TN2k5PTy+lefIY22dzfmpsE5vN872EqA+fPn2K2WyWUoCr1Sr29vZS5J9RBJXxZc7Scrm8FIUBLroRcs4cT+fkXatUzzqc3MqlLjFKzvfcidFxKpVKwTHjZ62fMedbr9cL+wlxDN3nKHB7EY7DGwQK+l6vh/39/ZTCQyGsxjiNOG3Nqca/7yqsoVV+0SkYnKHIMQwKFVQ5oaYC3hkVFVw8T5Uac1rr9XpifShwV6sVms1mEmQUXhyLz072aLFYpK4Yp6enSaGyS5IqPq6Nh9s5V11DfUZ9XwWrR2j0M1EF8kd/9Ef44IMPCpvovAro/8Hv/d7v4aOPPsL5+Tneffdd3L9/P7Xe9YhPIBC4GVSr1RQdZStSyjDKUE81pUPB7yzlkHdSy6XGqKOg56nDkYMaqdv0g57rzL3KXMoeylYa3ayFm81myYBV3aB1IHx2NXjZJYnpq9QlTBdut9sFosTZeV2DnBGu68H7ux7U39oW1Z2dnD7Wz6WMbMp9RjpHj55rJEcdQZ07f0jCsQ5RHdjA7UY4Dm8AKNDY/nNvbw/9fh/tdrvAqMzn80vX6O7NKjBpxCr7T+QEWU4o6rl+fS6s6sx/7t4OPp+HOwGkYjgqBAp1FWRkrNQBYC2Dhp2Z71uv11OhtbJurrh2rYEfzwl1Pe6pXyxq/P73v4+/+qu/2rpGN42//uu/xl//9V8DAH7sx34M/X4fQOzhEAi8KtB47nQ6GAwG6Pf7hWLgRqORDDnKMI0aAxeyVY1qz5t3XeA6wg3eMmxjyHOGau4afQ4a/NRxWhSuhd/tdjulF9H45nXUIzR2ef10Ok0pskxdpa7wqKvOK/cc2wz1arVa2HNHoVEbN9x5rUcL/Kds3ctQprM0+sTzVAerc8H/Oc4x8HogHIc3APv7+3jw4AEODw8xHA5xeHiYuvp4GDgnxDWlSFltNdo9d9QN/1wIU++tr52pd0dBC750/Fx0g5EPKjkAqbaDoWd2COEz7e3todfrFWo7NpuL3T1Zw8BNezabDdrtNg4ODlJ6lzJzKtj1OTTErAXnvJeujW6kxLF1PCoCnvfo0SP80i/90o3UMnwe/Omf/im+//3v46d/+qfx7NkzfP/7338lqVSBwNuM9957DwcHBxiNRjg8PES/30/RPyWXfAM4IN9GmzLJjUWgvBe/RyicDXf9oKQWobpBo9EK1xE6HxYws0kGm1ywW96TJ0/SJnFMM9K9ILjjM7s0MZWVEYb9/X202+1CipM+r0cYdO2or8nGKwmma++1hPzMWGAN4BJrv83ZyjkNuUhFLlJS9kz6XP4s/N9hJ0Sm785mM3z/+98vpEAHbifCcXjNwVoF9oRmgbQ6Auog5AQ3Depc8SoFS1m3JKDYLcGv1dcqPAgVJmWMTE5BeC6mMmQ81u/3MZlMMB6PkzBiGpJ21qCgZnHgfD5PP+y7zQiO14rkmB//m8+oDExuHXMMEK//v//3/6Z9KQDg5OQkhXhvM9brNebzOf7qr/4qKeRAIHAzYF0Df9gBjuSKGqQqR1X+qJOQY8VzOiJHLu1iszebTcHgdaPfZS7nq06LG8R6TzWyW60WNpsN+v0+jo+PU6SFhA5rJpQdp3FL3XB2dpbO4bqy5s51Fp/N5b1Gc7S+ZJd+IKjjec/rRHJ2fTZleqrMmciNo/PVaIkXzytpGLj9CMfhNUalUkn7BrAtKV+XpbgQdBT4mr+VXSL0S62CJCd4VOmoolFhr+fnxskpJ4UqCv6tjgNf93o9rNfr1HGIglpD8ry3OwwsdGNx+WAwSEohx4i4YM0pN0YNfH3LojX8TJbLJX7/938fjx8/Ll2T24zNZoMPPvjgVU8jEHjrUKvVCpuMkVjSHZ81iuCySOWQpnS6QZ8rhOZ7hF5f5lS4IcpjOYNS9VoZ261ja9Gukmanp6eF9rG1Wq2wP5ESS+o4MD2p0WikdXViSeea03mqp7W+TZ0M1SE5HZFbL18L/tYffT4fc9trPeb1KjkHJFdU7V0Zc7ZC4PYiHIfXGJVKBXt7e6mmgQqiUqmkTkrajk6/wC7k+ePFuTyfRW7aMUNZqFxqkRrHXgughWdUOs425cZSQaPCn3PlTtKr1Qrtdjv9ns1mabz5fI5arYblcpmKpakUptNpSnGqVqvY399Ht9tFq9W6xCL5Gqnjpe/rPhg8T6MPdEg0MsS1+ZM/+RP85m/+JiaTyVX/LQKBQADAc7m9v7+P4XCIfr+PbrdbKIjWglo33pzhpxzTfRJyTgR1gbZH1YgEoZEO7/6jUQsSPWXREJ1fLjrCe7uTxJa0TD1lDeB6vcZkMkG/30er1UrvLxaLlKrEczudTto/ydOInJnn2nkKlupGHmMK6mazSTqKqa6asqQkljc00c/OnQY/rueXkXZlkYYcCVZ2f93ngz/qlI5Go1RXGLi9CMfhNUalUklhZzLjuZ0X+bcb5t7ek8fdMHfWKcca6HnK+nNMDYnzmM9DFcG2EK07JTnGRSMQ3DnU582fzabYx5z9t8nScb8Iv18uhEsFWJZ/m3su7yDC9fjDP/xD/OAHP8DZ2dnlDz8QCAR2oFarpRQatlXNbbJVxhznurWp7HZ5pi1Sadgyusvx1YBXR0AjxhzP9QOAS/pG76/RZ6IsisHz2MqbOkLnrZEI1xHUve12O6s39V56T5Xz+vx+jRN+GiXQdfDzc5/TVRwIX9NtTkTu2cqQm5f/r3CM2Dn69UA4Dq8xKpVKIT2JnRxc+KuA1C/xcrm8JBxccOhrClTd04H1Ar6JXJlS8FSmMjZK5+1C2UPkypj59XQAGEVQpaD9sjVNabFYoNvtFupFGMLWNXJhqUXmV6mD4HHtfc3r5vM5fvu3fxunp6fb/gUCgUCgFLVaLckxEky674zqCG0UAVw28FT+KpvP651Mopwle6ybyKmBqMZ+7v764ylLXiOnY5HAcbKK4LM0m82kC/ms1A/qMDCFlY4DW543m81CfYLfQ19TR2iajkOjL14Irr91/Bz5p3+XrWduXa7iROScMT9e5jDk/q94re/fEbidCMfhNcXR0RGOjo7SngIa9nXWxUOMfF+7GznzDRSZHf+y6wZw6jDQgVBHwR0Ajk2mn8fLmIZt0QftXsExNFTOcHSr1cJisUjHOX/e/+zsDJPJBPP5HO12G/1+H3t7e9lIiaZG6ZwZqdA+5z7/XEhfe4zP53P8/u//Pn7v934vIg2BQOCF8f7772M0GqUOcto8Yr1eFzbi9E5IlG+6R04u6uq1Zkow5eoiVD5qZDpHKqmsdtJI4Wx7jv3XGg46FJx/u93G+fl5obBZIw3z+RyTyQSnp6eYTCbJGaPupS7lvb1IXNOUuO4AspEfj+5rxIf6kulO/Mk9tx7T9xw54z5HHrqTmJtzLgLv53mqma9ZRBxeD8Qn9Jqi1Wqh3+9f6qiQC1k6yoSAswXqKOTSeyhkXBH4jzo1PvYuwZSLNvicvZBboaFodtTwUDodCAp2jZ6UjZkLP3uerj8LPycPz3pa03Q6xdOnT3d+joFAIFAGRk1prHmxsKKM3MgZ6kqiKAOu+kHZZDoGSlSp/PRjTi75nPzvXfrBj/nzc266u3Mu3Yr5+HQUfBM8XR99pm36wdd+23OXGf5lUYRcRCE3Ts7hyK1T2XtXsTf428m0sjWKqMPtRkQcXlNwoxkanppHqlCBqopAhZMKDi2CVjZpsVgUcj75HpWCFvi6gFDngffmGCogvKiM8yB0TL1WWaScQ1Kv19MGR7PZrBCV8JQrrkGZ08DxdK4q7HQtPX/V5+YK2J2gQCAQeFGwBWulUknGr8ooYLtBqrJXWXT+rQQIi4u9Ww6AJE81DcWNQ61vULms98xFpj0KouOrDqB+UJKGP7qrPQkkfQbqPTYFYWG5OzMEn4MpqKoDeb7qT71e56e6Rus8yozrMkch9zlfxSlwm2Hbebm/FbnPw20D/vD/JVdfE7gdCMfhNUOtVsPdu3dx//593L9/v8CULxaLQi2DFl956NbB97Xbj17L3FPtgtDpdArXc2wKAE/ZUSWjrFIZ3AnRugGmKHn0QgUkoyGtVguNRiMpNjJLAJJS0F2mtSiawsuFHeetDkaZMHaBXiZEfW0CgUDguuBmlQ8ePEC/3y8YvfP5PBVI5yK/vuMwUG58UkcoC08dwnQa7pegRiiv05RWdWhyxr3PJ0dQeeRWCSI11lX20gngfPU8nkv9MJ/Pk06lTgGQHLKcLPe/HWVGvkIj3B6tzjUbySEXgdi2tvo697mX6bJdcIeB/wOM+OhPOA63F+E4vEagcOaeAlQEFCTL5TIxJ0B5GJPvEWUFyi5wecyL5XS8MkZJhZALeL8+N9ZVGJKyNVM2Q//WKIE+u9Zm6Nx9XVxR5ISrCulcjnDuOSJMGwgEXgQ0aofDISqVSoqykqlfLpeFHYpz8l7/1uO5VKec3gCKDohHDHbJN5eVes+cvvm8qS3OeLuOcIeGengXE5+b3zYZ76RXDjk95K+3zWfbsW3IORQ+TlkEpmxuHnHQGkkvMg/cLoTj8BqB6UmHh4dYLpf48MMP8fTpU3Q6HQwGA0ynU9Tr9bTxGXC5VsELzcioOLY5G9wMR8OKOibP1XCsCjwtLlb2Xu/B8bTLhgtNwguvcxvwaGtWOldMX9JwsQovv1bvzbnTyQDKd7jm+5qexRC0PpPmAQcCgcB1wcYOh4eHePbsGZbLJU5OTjAajTAYDDCZTFIzjVzEVgtyPbXUUaYjGP3mNUzrcQZbdYS3YXUdofd35tzlpd7D5SuPq45Q9ptyXtubq35SdlyfSaPYilwKls5doxKaHkU94A6Y3utlEUxlJF4Z8VgWYcmN63pbHQbVy2XrGbgdiE/nNUK/38f+/j4Gg0Ey+A8PD9FoNFJnCLaOy6UK0UBmeo62rMuxF55LqkqlUqlgPp8XhDPH8hCyhrTVkM5FH3IMjQtuzofvqVBTVkiFteat6nvL5TJt6KNCns+q53J+6kR42pWzbLqeHlrOsWiaOxsIBALXwWg0wsHBAQaDQYoucGfjVquVSB/VDdpmmnJa043U0M8Zf+oEsAaOjShYU+aFwSpDvY01xwWKcl7v6dFo73SX01c6Tz2Xc1bDXWWyturWWr6cfuDz5O7nY+ci8kpiec0f19XXMsfoXzeisAvuKDg55jo7p/9y/z9KwNXr9ULLYP4PfdHPEvj8CMfhNUG1WkWn00G/30ez2cRms0lt4ZypdpYi90Wm0NNjOQGkxrcKvmr1+W7LfK0siAuQXKjaWaMcnG3i8+VCvzq+n6OKMCcA3aHQ67SNn16nKGNi9B67oibqUAUCgcB1UavV0Ov10O120Ww2C4QRWVyV5zl5o7JPW247sUTo3kCqQzgOm05QR+2CGsvbdIQTWy5f1aD3KIc+q5NLOn+OpV2icvrBdazqkdy9dU6uH/QZeA+9pzpc26IA246VXZvTazlnwHX4LuQch9zn4O16PZMgcHsQjsNrADoNo9EI+/v7qYtRo9FAv99Pxm+z2by0gY5GFvTLuV6vC52E9F6amqOMANkZnjOfzxNjf3BwkM7LGcmcjxvRvnmbX+PC19kiT8lS4abFbtzxU50QZfcrlYvuS852uYJVhVGv1wvdP3g/fR53ZtQhyhVZBwKBwHXA/WoODg4wHA5RrVYxHA5TeqvuGaNykw6C6wjKJ62hI3SDT6CoIyifa7UalstlajrRbrfTvJRVz0VXcxFmIF8f4ESMymy9V47Q4fjUk7PZLG0Kqiw4r1UHTNlwJc44f9W1Gp3g+2VMun4GGnnwY1ch3sqQM/pzn4OOXxZl8HNzERi+l0vlBYo2BzeyZQH/tuYpgVeHcBxuOZiXPxqNsLe3h729vRR1YPcfZZByDL8KeRrOZJ/Y9szbzfFL7EXC2lUJAGazGVarFVqtFjqdDmq1WmGDGlVCOYGZE4BqgANFRcLXOn/vBKJOhoeh9R4KCn6me6nzlGOMuK4aSldFmruPhtBVcamyDoYlEAhcB/V6Hd1uN+mHwWCATqeDTqeDRqOBVquVHAc1qIELWeZ7ElQqlUSssJXrYrFIDTko37kBGsFz1Ugcj8cpPWowGKTcfUbJaRCrftgVKQAubz7nxI2SZJ7CqnpMdYSe47KbuoZrwVa3qqs4FyWfKpXLKbx8DtWtug45ssnHvAr8M805DNfRN2XnlkUn/JpdUQetd/DayMDtQTgOtxxkOQaDAXq9HjqdDtrtdnIaGo1GijgQuS+tCwjdtVOvpzBVloPjqEHOMQBkDXPOPZfTr/PaxpzovShYNMKgUYeyUKsqhlyxtispVSDbIhp6LFenkfss9DNwBeVKJRAIBK4CdlJSHdHpdNDtdlMhr5I9OTmjkVeOSfmu6ZqUkU6WAOURZU8VdUKLjoTLUS8kzumKnN7QurdcqqnPV+fHeZdFOvRcj4bzdc7hyTk+fO16w52G3GdW9kxl5/jc/JhflxurbJxdcMItR45xzb27UujE24lwHG45KpUKWq0W3nvvPezt7aHdbqPT6RS6D5AxUoGrXzrd8ZLpNTwOII3T6XRS5GE6nWI8Hhfy/6vValJGLLhTpkCVTr1eTxGLMsFYJqDUKfB9IHJ5uWrg828yWgyXMwxNBo5MGSMMyvKo8NLiOjJk7N+dY5pU0OUKtbWNH99nDjCAwvuBQCCwC9VqFYPBAF/60pfQ7XbTxm+5IlM12jTK6Sk6DtU15+fnmE6nWCwWePr0aUHOMdWEP3t7e7h3715hXMp2rbtQHaOyuMwx4Pxz5JTL4Rwpw/kwpWo2m2E2m6Wue+12O+lJ3StJIzQapdbIMdlyjaLk2Hgl7PjcGunh2E54qU7dhhfVI7uIR/289Bp36Jyc89d+T9oN/Ayiw+DtRTgOtxQUwp1OB71eL4WfWcegaUn+BfX0F+9C4UKcgkAFA7/EZFhUqOkceF8dTwubWEPhRXZqTPM6vp+bi7/OjeGsz2KxwGw2w2QySXNklIYKSwuyGJlYLpfJydA1UhaOa+Jrq84bn8VbDeaYuYg4BAKB64DGa7fbRb/fx2AwQLvdLhhduaixG6LOsKu8VTmrclnvo1Fq6ge2fNUx9H40upU8cecmZ+zrNbm9Iqh/yiLEPs5yucRkMkld9UgsaaoM5T5r/Eiu5WpDtAC9rCuf6wB/BteB+h6RS31yXDUicBWURSt2XeN/l0VgfA1Z48B1j1qH24VwHG4pKMToOLCdnhZnaX6oFoGpQausvTIjOaGsuaF0Dmgga3SCTJYKP1U22tJUfwhVRmUCSJ9D2ShlYnLQsRhtmE6naY7KZnCdNX+VOazaVlCFGuer6Uy5Obhj4O9p2kAudSoQCAS2gXVovV4v6QjKN68xyxUJqy7QRhJK/qiBquw3HQaNEGj711arle6TY8z1fq4jfI5l8rDMCXInx8dUcofRaLYwd7ab8+WcGX3QjlMeSeHYjHrznmXkketjTyvLEYS74Pfbda5DHb7cbz3nqth2rpNzuhFcOA63D+E43FKQDRmNRjg6OgJw8eWicKOC8C+ybvKmm9W4MOVxNfKVnWLbVxVwDKMq+87rCW8Zp0XBHh3gOfrceh1/3NGh46IhU0YZqPim0ynOzs4wmUwAXISDc4qL7/NaKkBd18Vike6t89ZQva6VhtH5zFofovPmvf0zCgQCgRxIdNy9exfD4RBAMQ2o1WoVor8AEmtOOcP3WSunP+v1uhB1pnyjDHNDv91uF4w9ld1OpKhcLDP4c/rBx/HoO0EdlKuRY6RgvV4n/TCfzwt60HfX5j3VoNUOfPw8VqtVQa/qnKkXlAjTbkx6nmcEqK7ZFmXQNdXP5kWRi9qUOQ/+2scpm6faE74ZHB26wO1COA63FBSKLIb2vQw0VKvMiAp7juPCj9eXCfKyULFCIwIcw+e/jXkHikKdYxJlSofn54SUF9exXSzHo5KhgFID39fChVWuyM4jB7mIj57LcRz+jOE4BAKBXaAsY90ZU2OUhNBzlRjh+zyeY/tz+kHZetU5OdlYxqir/PYfvq9j+DG+LovU5gxdnSdlNFuw6rPoPgL6nPrsZfrB10+vd/2geie3NjmU6Wx3sFxXvog+KYtYaOSh7Lyye+Z0uDoOGtkh4ZkjDQOvHuE43FIwXYgdlJbLJTabTUEpqFDWLkkuiHJhvpyg1TCrHvc0I48W5JwGPdcLjwEUNmNTNojneFE0x/N8XZ7vHTs2m00KQatg0jQvvZ8LZBeMGtnhcX1f57RNIeoa565l7mwgEAhsA1OVOp1OwXHgD5l1nqu6gjIzJ+OByymTaugq6+xGce7aXWSJRxn4nrZH9VQrjXjnnBTXgX4eI/qz2axwD02T4TW5Wg0n2nTeOcLIyS1fJ3eIynReLjXLjfTc/XN/597TZygj/HIocxpynwPnr+up/5t0GvRzCNwuhONwS9FsNnHv3r20M7R2dVChtVgsLhVp+ZfNHQIAqeMQi4GVSSJozGtnIRdY3nXJQ+Mq6HPKQeEshP7kjHBVCJyn9trWblKsV6AjxjQsLfCjEmZh3/n5eaHIT1PAPNSuz5hbJ6LMCatUKphOp/jlX/5lnJ6eXvG/JBAIvK3o9/u4c+dO2iVaaxBUNnLjSyeZiJxhXqk8T3PlBm5KZvi+OaojCI7n+sNZ5DKd4I4Nz9lsNoX5KxHFuXiqLEH5XavVkt7Uea9Wq9RRqdlspvGYnrvZbDAYDNLO3IzYsEOfpnTp3FyXaRQiV8PhOkLP10j5F4GckX/dsV90Plwf2g387NiRsdPpYDqdol6vY7FYvFDkJPByEI7DLcX5+TnG4zFms1lqvapFZMpgaMGaC9+cEUthlNt/oYxlUMfCnQC/Lmfo5+BMlR/Pne/z0ffUmPdaCTpcmpeqbBc7LvV6vUtdo4iy5/Y6i7IIjB/XXGGyTKenp6mWIhAIBMown89xenqK+XwOoFj35WSFFj2roUcjO9f5jUa/Xr9NVpdFWf18J33KdISP7eMpA79NNxBOaOVIKE2R0bq8SuV5fR/3ydCuS7mIci4S42uw61guwlAWQfg8jsRVdLS+3nWvXXPKOa2apqQ1JJ4hEM7D7UA4DrcU8/kcH330Efb391Gv19Hv9wuGvjsO3v1CBZGyGwz/KuOS+zI6E6HKpEyAqJPCMcoEvjNWXhdQFpb1cfk+hY46OKqkmKbEvSUAFLpjtFot9Pt9DIfDtCOozsMdE507z1NHLReCBpDm6KlVvuaBQCCwDePxGJPJBA8ePMBms0Gn00k6QplvJYdardaluizvIOQtR52s8nQXl+XuHCjKosg5o1mjFl7Px3txTNcRHjlXp8kdAh1TO+7xvsvlEtVqFe12G8PhMEWlda68j0f7/Rl1Hrlndz3tjmCZMf5FRCHKnEL93Ms+021/+3EdR0k9dRqYhudNYEJH3g6E4/AagGzHfD5PgkxzAPmF8hZ8AFLeK7+cFJqqYLaxMByX71ORsAZDoUa7CmUfX50Er3nwIj13GHhM80CBi7AnHSFVdOfn5+j3+2lzJGXZGBrt9Xqps8jJyUmqL/E2hZyHO2Uu/LkGnkbGtDCNCrnSCwQCgeuA0VRGIObzeWLF6/V6Mry14xHle66o2iPSLsOdmGKK6GazSSmw2pmO1xJeXK3HXfZrqoo7PQonk0iiEUyHUceB969UKimaQKdAax64bwWAtFlcv98vFJr7vHR9NMqteiS39uo05Jwif97XTW/4fHMRB9o36sgFbg/iE7nlGI/HaLVaGI1GyWhnGI9MOZEzuv24KgSySrkIhbPryj4oC5LrrOQhxauEWK/CWmxjG3RuhAqkVquV6hsoiFVAcW8KKht9Ph0/N39/1rI567rl1jjYlEAgcB1sNhs8ffoUtVoN/X4fi8WikALp6asq04BiYwrKJTWudddklVee/uqGrTL7rh84NzWOXZ66gZ2rBcjpjrJzcu9TBtNgpdNAB4FOF1PAtH5P578tapIjvfQ919lKUvlPGbbd56rI6Z6rRBuIXZGIMj3PY6qr3ZHw9raBV49wHG45PvjgAxwfH+O9994rMBEM4XlBsrJEfE9D1comzWYzTKdTzOdz1Ov1ZFRTYCpLAhRZHC1G5nvABdueC6+68Od8eU+PKOi9+bosEpFjxOhgrdfrtLNqp9Mp1IRowRwjOLrLNV+74MspYt3fQc93po1r4WxVhGIDgcB1sF6v8b3vfQ+LxQJHR0eX6hJY2KubgBKaFqIyj2OsVitMJhMsFgssl8sUgVX9oEXVKreXy2U2xUijwO7A0EHgPPh8nL8e92i2zp3vu6Pi5/A5uGfAcDhMNW5spgEg7YdBR0yj9FpjyPXQeapjoTLfn1fPJTmoRcP+7GV4EYdB5+pj5e65y4kom4frUB9fHQWPOqgDFTry1SMch9cA6/XzHS47nQ6azSYGg0ESQNpvmkW1NEa9u0ROaNGw5pfVjd4cM54rqFNHg6BBTmh7PRW8wOXCtbJoiUYLdH14jiowph5Vq9VL3ZJ4T1VkVKLsZKXPpKwcr+VvZZ/+5E/+BH/2Z3+WfRYA+Jmf+RkcHR2l8ZyVCVYlEAhcF+fn51gsFuj1emi1Wuh2uwXmliRIWa0CUGR+KaPJtgMXjoYacWVpNMoY82/v5sQ56L5DStS4IZ2bsxq+bsA7saTncj5Mt+Wa6WapSgQpycXnyO0z4I4Lf7Tr0y72XRtzeGcpPc/19FXha5FbVx7LGerXdRp8rn6OOoGaqqTOAx0oJfMCrw7hOLwmoMBhuzh+GT0/1MEvnDM0KuBy7flUMXhYmkJN6ytywnobVCnoMd5fz/H3XJjlwsU6d71XTmi6AFaFUCaUfV7r9RoPHz7Ehx9+iB/+8Ielz/3xxx8XWgBy/L29va3rFQgEAmVQA5u7Rqvs4zku91S+qcPgzLwbyGU6whlkrSHwc3wuLsNz8trTZ3JR2lxU2KHz4znqWGnqll/ndSK56Hju+XL6eZthft0Ig0cFroNt53OOL0JqlRFjZY5Drkg6agBvH8JxeI2gPY5p7J+dnQG4+CIyVYnnNhqNZKiSMdlsNikUzWMurPRLq8yRG/C5jkgKDVUrO6+F2c4E5YSpMvwcN6cEGXbnPdfrNSaTCZ4+fYrFYlEoFPQNhjTti8+qY+m9GIrnfafTKX7lV34l7VRdhv/23/5b9vjP/dzP4Wtf+1qEYQOBwAuDjgNrts7PzzGdTgtylalMWjDNIl2VjdQPXt+gMlN1hKcOUTayQQR1lss4lbFawMw0UnUo3IDUsdTA1BQinY9GkPk3i8k5v1arlfSTOge5Z3VnR+dFXaCGMY3jqxBS+ixXMZpfxLjPOV65+eSeL3d8G3Y5DR5xYGG0tr4N3A6E43DL8Y1vfANHR0eFkN1isSjUNeRCyVrcRrjHT2GYE748B7jo/kDQiVDhS4WgTI2zS8pkkdnXMXQeGrLOKRydpysIdQIohLQrB9dxuVymDY5arVYqjFMnRpFj53KpUy+CP/7jP8bHH3+Mn//5n8f3v/99/MVf/MXnGi8QCLz5qFar+LEf+zHs7e0lp6FSqSR5R1nmxjnlKbv0AcVaNDoLKtv1fUJlcC6KrTLSz8vVKOiP6pkcoeQby5U5EW4cq/FP/XB+fo7JZALgoiXrfD5HtVrFZDJJkX42I1Ed52vH930N+Oy56zTCs81B0nVUJ6gMTghuw7bovq59mcOTi87oOH7Mz83pbU2h3vWsgZtDOA63HAcHB7hz5w6AC8dAhY8KJOByuDm3+6Yb61o47cYycDnkmvtNlOXQ5oS3zkejEXqtztfnURYiVgVJ4aPsmbJxdFCoLFgDkVszBdfOFeOL4rPPPsPp6Sm+853voNvtfq6xAoHA24FqtYp33nkn7V5MWeSGvDLjPIfy0OWdn6uEUA67jNJtMlzvl3s2nucRj7IoRM55UB2npJDm0pNkm0wmqNVqaLfbKVJyfn6e9hRQsi4n8/WY6gVNxSl7/pzO27a+Pofc66tEE1xP+2t3HK8T2ShbIx9L7YCcY5dzpgKvDuE43HLol4cboVSr1STwGGbm/gB8j192hqBVgGluZ6VSSS33/Fx1AnI5/95SDyi2ztNOHfo8rozceXE2pyxUmxOKZLu4N0OlUsF8PsdkMknOw2KxSOf1+/1UdE5lyrE9fYprxvlw3gyrf15Mp1P80i/9UqQrBQKBK4MyXxla1QOMuFK28n2mLLncBy6MdRYuq4xT41edDo/CAsXNPRVa7AoUZbk2/FACTO/JOfLaXP0A38s5K1oYPZvNAACTySQ9z2KxSLp3f38/OQ46D3XMcum+ek5Opns0/rrw+72IUV3mNPixXWO/qEGvTok6C+wa2Ww2U2p2jtQMvBqE43DLwTaprVYrMeXe7YcCXvNRmXKjexKosauslDMdwGVjPcfq87cLwDKBVibEeVydCo+G0NDn3xq+zHVZ4Bq02230+/3kWHEsOmLc36EsRJ6be46J+aKYkDIFGAgEAjlQztHYovNAUHYCF3VuvI4Rh5wBqcQIxymTh27Eq3xWoqosCu16ROcOFHek1no3rZlTh2NXvQN1JoAU4aUDwXtwPX0jUK9R0IiOPpez6mWGua+Dfw5lyOnXF4kK6Fhlev4qY26LwuQiBrnXque5/poNELgdCMfhloKCi0wH8+9p8Ho4GUCBLVfFkRNAFKYqUHd9McuEXFk0oMxJ2IbcmLnivNz9FMpcdDodnJ6eJiXJiITWNficXciVsUMRQg0EAq8CTKmhnqAso3zzSC9w0VRis9kkBp1RZ0JlXJnj4CiT9zn5qIa0y9urECdlqTwknPxcPUevp/PQbrdT7ZvW35HtZjRaIyBeX1DmEOk5vl65efL1LiO8bF049ufRR2XO3LZ5XeeeOQfCncxcnUM4DrcH4TjcUoxGI/ytv/W3Upi03W6j3W4nR4IC3TsTqWArY3E2m01i4FUIMuefXr+yLMr4qNOiCkadGL3XVUOy7pgQ7hjxfrm8W1VAPL/VamE4HGKxWOD8/DyxGLpTKDt4uPDzrlBcO1dcESkIBAI3ia9+9av4xje+kTYta7Va6HQ6ydhitJkRAG9v6pvCqSxl6qrWzvH61WpVSJvlcSV4XF9w/Jzhq/LzKjrCdY3exzfvLOtyx1QtPkun08H+/n5Kx9Iof6vVKugTQiP4WgitacM6713wKEbZ85e9r+v7os7DVeaZw4s6DX49nQYAydbhZ8AU47LoTeDmEI7DLUS/38fe3l4ybFUhUFAD+bCmGtRkVLSgS3NOtR0px2K+qwp+/aKqsMwVLVFgl3VX2vWlVwHix3K5sj6WO0pUMHSE2JFKozJaJM1rlZVyh8Y7KIUQCwQCN4VKpYLhcFioz2q320lHKHOvRI/qCOBCzqmOUP3guoZjsVbMu934PbQrk5NOmh6lzsdVDFCXzXp/vtbfOR3hEQGy2zT61TlRB4yg/svdext5lpuXP/Mu54HX7nIeroOcw3Zd52PX+R5lyEH1rUYctAV94NUjHIdbiMFggMFgUCgOarfb6f2ysGhOKGvkQI1jL04DkNgn7SyUY008vUkFoToOfB8oFtG5knGoUrhKuLYsqqLnemclCiYqQlWQ7jT5vXXju3AavngEoxQIlKNarWI0GqVIwy4docc8Okr57fsn8L2cMUk5SpnuslhlKIBLabM5HQUg6+zkQP1QpgfK3iszjDkeHQHdCE4dB9VHrl8Uqh/0XJ9nGa7qPJVh1/hX0VvXnfO2z2ob/H39n3PHQR21q8wp8PIQjsMtRLfbxWAwQL/fT7mqk8mk4HVrBwsKAoZJgcvdLFgzMZ/PsVgsCkb0fD4vpD7RgdA8WReyPEdD3oTnI25TYu50ABcOTO5azkHD7kwzYsiY5+mzDwaDFHLWwmiNNmjofb1eY7FYpLF8YzhVJKp0Ai8OhqaHwyFOTk7S5oaBQOAClUoF/X4f/X4fvV4vGbfT6RTNZrPgDAAoOAXVajWlbKrcA1CIVvB9LT7W9q38KdMRmjrkJIzOjSjTETyff6tjkrtW761zV92mabwakWbt4HK5LOzboOlOfF62b9XjHl2n8+F7K5U971Vw3WjCVe5zVSdh2/FdkYbrRJL4WtOU6DjUajWMRiMsFgs8ffp055iBl4Owdm4R6vU6ut0uer1eYaMZZYo0h1TZfuCiU4QKJzWEVai5kc58UB3/OgKhjGHJCX0X7mVRhbJIgioFP0efXQvdOKZ3Y1LlyGvLUsE8D5c/OWYu8OKIIrhAII92u41ut4tOp1No6qApqm64KonCCDSvc1Y9J6/VUKbe0fvlUlByEduyKG1uvJyO2EZAOQmlMt3v6e+r0V+r1ZJDRWdDx9Dr9Pm4LnqOfwZcF3eIcs/k71/F8N5m2Jfp0l3nlf0/5HT8Lvg6+HuE/q8y2uDO3nWcp8AXj3AcbgkqlQra7TaOjo4wGAwKLUJVqHoKUI7F0d2PVfg640GlwSKx+XyOTqdTYEc0jM3rOG4uTcmFirL0/FFD3ouKfdxcLiyP63z0WckycQMfXksjH0CKKLiwVOWlCraM4VJWK/D5oP/vgUCgCEYa9vf30e/3U5MMl736/VEji8w6DWU9Jyff1BjebDZJXnY6nfT+NkNOaxx0XDe8d5FLbuCWXUeosa/3VSNfoxDUCx7FZ8qWjq/HNGri9Q+6lrlibh1zlxG86/3c+uTeK3O8rjN27vO4LnLOkztW1L+MOujeVF/EHAKfD+E43AJUKhV885vfTMW7vV4P3W638EWhoUsBR+M7x47nvozKhtCo5pdP93zg+I1GozAmhaSn66hiUMHML78a1hT27pAoK8bn1fSjXFclBeddqTxP1eKGeJ1OJ43JDZC0G4ivGZ9dQ9DKRGkxdRi5Xzy4xtyQMBAIPEez2cSP/MiPpI5uTL10uT6fzy/J5FxUgCSMOhVOutBIZtoIHRU16vi+Ej6qB/R9vuZ7+pqps0p0qa7RsVVHKJHmBcyERhYYZZ7P56mdLcebz+eoVCopJZjRaXVmOIYTVtQpjFjkDFzX1er43DSDnnMItr32iE/u+HWiIrlz/X+x2Wymz7Tf76Pb7aZaxS9iw9XAiyMch1eMfr+P0WiUCts2m03qpKQGrrMlynI7Q+MOB6HHtKOSFiDppis549rhzM+2UOQ254bX5973sZRJ0h91VABcUqB8Vl+PsvvoM+l6e/j54cOHePjwYTgRnxN03NQgCATedhwcHKRmGZRHbM3N74ymcqhh6/IvZ8BrKpDrCOAiZYT3943mcrLe/76KkbxLR+QiCGX6pkxHuE5Ux4vPyvFcH5XpKv7tWQE+79w8y4752GXnqH7KzbtsrmVjubOTewbVtzo31/9XdSRy12vdSavVQr/fTxvxeRfEwM0jHIdXjHfeeQc//uM/jr/8y7/EarVCq9VKEQcKZv5o0S7rEbR/NB0NbbW6XC4vpdxof+tKpVLYXI5fVnVkXBGpUFCWhed7RyQeI8qcAb1HrtWeCkU+i6dfqQLQcVTBaRTEnSMVivr8zmZp6PSP//iP8ad/+qcv+i8Q+P/B//PpdBqKIRD4//EjP/IjuHPnDv7yL/8S1Wo1GVKMnuoPjSqyst4SlefRQef3zCPJ1BGUg61WK+kEbprGiMO2egfeE0Ah6uyptq4f/P2c0+C1UK4fVEe4HPc0Kkbxeb23KldiTu/H5+dxdRp0o1ad31UjDLscBn/m67L/28bddp/cZ1GG686fv5Xkq1arODg4wNOnT1Gv1zGdTkv35wjcDMJxeEWoVqv4yle+gqOjoySk6/U6Dg8PMRgM0Ov1EstD45wOAwX+crlEq9VKfbjpJDBaoZ0kAGA+nyeBSKXCe/AcKiNncsoYBAphNfR2OQUACmwWx6YwyLH7PpaOl3OevAsS4cqLY2l+a47t1vM57rNnz/Bf/+t/xfHx8a6PO7AFd+7cwT/4B/8Af/EXf4GHDx/i008/LRg1gcDbiHa7jffeew/dbjfJ+9FolFqxkuyhjqhWq5jNZqmImYY/88QrlQoWi0XSGdqmu1KppBRPGtfsmkQ9oa9VR/DewOUIsv5oKpI3lMgZ2EoCUS77Bm9uiFcqlQLRxfnpb30W1128b85ZUF3Dc4lcZEcdihfBixjk1xn388zti4I6IapjOUf+rx0eHuL4+BhHR0cpuh/Ow6tDOA6vAPSmDw4O0G63U9FZo9FIuatUChRwFFrM1XShDBTZcq0LUPYlFzlQ9iXXVs6jDP4sxHVDokC+ePoqYeey+/N5NMriPx7izq1l2fy5Vo8ePcInn3yCTz/99FYI4NcZjIzx5/MoxUDgTUC1WkWz2cTh4WGh7kqjDSR5VGZrAbQbxPqb+qSsaxDP0TGdnHEGPhcBcOzSEc5sqy5So77suVwf5s51B0Cv88Jyf3+bnuI13gHoqhGGq+KLjDBc5R76t77v99w1B12PXe+7nuYmuP1+H48ePQod8YoRjsMrQL1eR6fTwb1793B+fo7xeIxqtYput4s7d+6kMLAbv2SP6vU6FotF2mdAvW8atrrBm6bZULAxP9ZD3fpldRYoF4bWHFsNC+u123I+NXysfbZVCeU6ZDg4jj6DjqssVC40qmukXTBUcfFYo9HA7/7u7+L73//+dT/6QAaPHj3Cf/gP/wHA88+i1+u94hkFAq8WzWYT/X4f77zzDsbjMSaTCer1OobDIY6OjlKnGU8x0nRTZdNXq9UlmU1ZyWYE2mGoVqulImGO6WlPvG8ZkaP34rjupBBlDgUjC55m5Aa6jqv313G4Bp62ql2WnDhS+a9r5CSd6gymcOl65p7RcRuN4ZyTUuaYXXW8bc6D123yM6nVauh2u9jf38cHH3wQZN0rRjgOrwDtdhuDwQDNZhOnp6cYj8fodrupAMjbwhGa5kMBxULS1WqFbrebFAaAlLbEc/gl1HxOOh0UhBrdUIFXFnVQY5vncS8JzkvH1WvcwcgpJf+tgozrw7QWVU58Jndm9Hk0VUnH9M2JOGc/P/DFY7PZYDqdppzq8Xj8qqcUCNw4qA+4aedkMkkprOymVKYjKKNoILPmoVKpoNPpFBwOvtYuNZvNJkW7td6Bf6vT4bVoZTpCHQXqCBrr7tQ4UeTyWUmlXLRYDVo6T7pPRaVSSc+b0w+6li7zc7qB99Tx9P4aKSlzsl4GXjTSsSsi8HmR0+uErpfaH7R5Op0OOp0O1us1ms0mzs7OIqX1FSAch1eARqOBXq+XhPpyucTe3l6KNHj6DlAsBlNmXs/zNqN+jToL6nR4LUQuX3VbmlIuMpELY/r5fp2eV+Y05EKzfsy7hFwVOndXRPxZLBZ48uQJ5vP5lccNXA9UBFqAHgi8TWi326kYmcRIt9stFCUD23WEOxVAcYdjAJcMcR2TrS85no7vJM82bJPzim06Ihfx9nNcZ7iO0DHKnJMyaNQ5p/c8UrHt+qsix/bnnqns7xe517b3XS+X2QRl983dw/83cnoXuCAbWa/D9O7bGKV5GxCOwyvAYDDAnTt3sFgsEttycHCA/f39pCzcoG+326noOZfew7oIKgtllXhM92sAUCi25hfUlZK+pnOiUKaIf/umbf6aHT/IKmgdh99PX3sBtp6jz06GiayYFztr5EadhW0OAz+TTz75BP/5P//nMGZfMjQKFgi8baA+YEOLWq2WNgdttVoAkCIJJIWYB07ZqpucaUtVAEkfUBYyvYl6hTJ5Op0mmc3zcqQNX29zBpTB1wg1i7RVBmu9E1NrOYbez+Wz6hqeQyKJY2iUQ9Ns3TjntT73nF7kDyMcqhN9TMcXZQB/3jFc9+mcc2O7Y/d57se/9bhmM/DzYnvW6XSK2WwWbbtfEcJxuGE0m030ej0Mh8PUdrLdbmM4HKYWrPzisMtFpVJBt9stbELGL9O2dCIKMj2uIVs3spVVcEPeuw6psFDj3BkPFyjOMHiXCnVEOD+9T24c3Qk1x8z4/f0eZY4F19nvH8bsywf/TwOBtwk0jgaDATqdDk5PT1P9G6PSGjlme27KNMpxAAVZD1xm3fWevJaF2Cof6YiokehRadUxajwrtsnZsggy06JU5ioh5jnxCjXmPTrv6U5+jdfKucz3qIPrXX2v7JnLPo9tuKqRvksPXuXaXCTAX191Xu6I6O/cfN0hc32vxGjg5hGOww2iUqkkZqjVamE8HmOz2aDdbqcwtDoG2nqOUGPfHQf/8rkjQSFIgUwhsFgs0heRAl+L0HJwgXgVY1rP4bhe4OYFyb5+hDoqVCy5NShjNXhOTrirgPR7R2j0ZsDPN+pKAm8TGIHlBm/j8TjVqnW73VSwDODSRokqR6kfPG3TjdWcjvBj6/U67UjNOWqNg5JNhBNLyiKXRSwUZURY7rg+v16v0QcSXrvgMj+nh3R+OZ2769ly873KnD6PE3Ddc8ru6VGJMuya61XnpQ4yr/GGLsBlpzTwchGOww1D/+HZU7vf76fCt3a7nb4wzWYT3W43fWFOTk6wWq0wmUxSipGmAtEh6XQ6SahrERqFO3eJns/nWK/XODk5SeFv7ZldJvBzkQKmQfFLrl2KAKQCPN1Yx41CZf+9F7cLGi108w3qVHmqctOx9JxchIVjec1IOA43h2q1isPDQ0ynU5yenr7q6QQCLx2UrZSvi8UCg8EAe3t7GAwGqcaB+mG9XicdsV6v8fTpUywWC8xmMywWi0JTBzogjFpolIHpquxMx7mMx2Msl8u0Vw33gFD5q80u9F7+Pufrspf3qlQuOjwBRVIppyNykQBCiSiSbXov/u1kles83kejLAq/luNfB1eJIrxsvZNj9nmc9y+bZ9nx6845R/a5PUFbg3YO29k/ffr0WvcKfD6E43CDYMRBw5+1Wg29Xg/NZjO12ANw6cui6USaq8mWrAwxq2MAlDMHZI1YAMfrtbsGW7a6kc5nUMPfDXYXynwGZ8E4F5+f5ud6KpIrGx73cXOMkTNpeqyMYdrmwAReHvg/E2xS4G0BdYT+72u0ge24nY3lD+V/q9VKcpjRAkaXadQ3m82C/AZwqbUoZS9rDrQDE6PUOaNTHQcdP0cs0SBnNzztTKTjuRwmEUUHSN/L6RZNa9L15jX8u+zYrgiER3Ouyqrr+WXG9lXOcz3nUZHcfNUhy0US/J56zjZnwnFVx8jno//nusa0XxaLRXRVegUIx+GGQceABnS9Xk9Kgf2ygYv8TWVAKMiBC6NqOp2mv1erFWq1GpbLZaEITpkQZfzJbNGgV8dhs9lkDfZthnUurKgKw/dT0OtzjoMXOTv7VOY4qBL0OeaEuiuG3DNqe7jAzcHTMQKBNxl0HNS4bjab6HQ6yWnQ9AxnuzWFiEa4Ot9sTKEFxy5/VdYzIsHuf7VaLUUnSGK5sec1cHwvd46+73NV5HSGtpl1x0HXk/A6vDInwQ3onH7w+1yFmd+F3Fz0PXdMfD084uHn5SIKZc9R9l5ufa6C66yJ39Pn7fWWoR9uHuE43CAqlUrqQTyZTLBardBoNLC/v19ow5pj8ulh07ums0FGaTabFe6l4V7eW41itjNjp43z83Ocnp4WWCiyU97Cj+HknEGvQlxDvewgpaHwXGRAmTN1blQxcn2uKoh0fmxTWK1WC84V18qVnXacCtwsNptNqgMKBN4GcKMrdhVjG9a9vb0CkeMkBvWDGvn9fh+tVguVSgWTyaRQM0fZpo4IjTHggv0nWdVoNDCbzXB+fl7QEfP5vJBrzvEXi0WSs27sUq7r95oODeWzM93ayELTS9kZalcHo5xh7fpHx9ZN7/Q8J6P4GX1eZ+GLPDfnBH1R8IjDVXGdc3XO6kyqk8Dx5vN5tEZ/BQjH4QbB7hiVSiXVF3CHThes7tkrQ8O6BQCpJoKClztGk41SQaxCWAV6t9vFfD7HYrFIX0LuTk0Br3tEUMjmCpn177LOGwpnEvisKrC3sSB+b6C4CU+uMG6XovHIRi6PNXAz4P9evV4PBRF440HHQevS2LueoBxyosnrGYh2u52iyYxGa60Bx1C5rjqiXq+j1+thOp1ivV5jNpuh0+mgWq1iPp+nLje8J3VGrhGH6oIc+52LfDgpxTmr81GmI8oi5GqAaoMRXd8cc6/PoPNXEs1R9oxKDOb0mI9xHaLsZeIqzkhZ9P6qjoxHqHStPfqj3cAi+nAzCMfhBlGpVNDr9ZLApXGtjoMKHxX+ynzrcRbGabG0svbaFk+FL79s1WoV/X4fAJLjwMiI7vHQaDTSdblQrj5jLqSpyo4KSpUdcDnSwms9vcnXyoUFWQpN+1LkaipyykXnzRQxLTgPJvxm0Gg0UhFcrHngTUatVkO/3y+k7JDxV3nkP14voOh2u6kWjtFiJVd4HeUxZTx1R71eR7/fT3UO3NmdEQdNqcoZij4n1xGuHxQ5g9H1Dufq9/BzFDxfowq5yILrMZ2rOzRXYfhdV+Z+77pu21i5Z/2iZeYux8Tfz9kH/lqRI0z9s1Eyj3uQRD3czSEchxtEtVrF/v4+JpMJzs7O0j98q9W6ZMzyCwGgINCBi51Eaby2223s7e3h8ePHWK1WODk5wcHBQaEeguCXkPcGgOFwiEqlksZlH/HpdIrlcomTk5NCYR6hm+jw+XhcFQ9w4ey4wnLB7o6DjutOAteFfcep5JSVyrFD7sDonHTdCaZaVSoVHB4e4hd/8Rfx27/92/jggw+u+MkHAoHAbjSbTRwcHODJkyeppoARB2fGvePbZrNJBr02ouBx3fV+tVqlzUZ1TOoBAKnJhhaiMurAFuLT6RTz+RyTySR1uul0OoU50TjnnCm3NeWI98ixy5xfztkgck4UUKytU9KszPjNrS3nqXNVgk91EHB5k7zbgm0OxHWjGR6R8SjNVeawbT76f+DOg0bEdBPDwM0hHIcbRKXyvJOFbvyW2zV5W2tQ4MIIp5Ck0GVuLFml5XJZCHHzGgpQ/eIul0v0ej2cn58nR0bnQWdA93wAUBCoil2sAt9TpqasvV4uxK330LQmHYO/VfCrMFKHpKzVHpWQRnsGg0HBgQq8XJyfnyfGNBB4k8EINGUU9/bZpiOcEPFIL39Xq1X0er2U0sE6Ck0z4ti8hoZZpfI8pZVRbNbkaRoSU1vp7LjRn2tWofCIAuei15Q5FHpMsSs6wXX2ItscuZVzYjjHXEG4P+dVDNzrsvk5XDXCkHu+svFf5Hju8yxDbu14XH/72LyG/8uBm0FYPzcIFcQ00CmA9Yvg7DyFrn8RtTVerVbDaDTCfD7HdDpNbJMWzXEO/lodEi965vVMW5pMJuh2u2nfB4+G5ELLDv2Ce2tBXqdj87WHY5Xh4VppO1muIVDcF0LbxeraqGOhSjE6N7xa0BkOBN50UEdQ7uueC3yfkVXVDyqzKOd4DuvcarVainhzrwcWTyvB5M0rWGM0HA5Tcw+mJakOYVQWQIpme2qKjqvPo8dz7DKf01OS9Nwy49PluBuY1JWqaxih8Ai06gEtJN/2jDl8Xpbcjf7PM86LOhq7zsvdY9v9rrJmucjGer1OkbDAzSAchxsEWRmy9/1+H51OJxmv3p1ChZbm7DuTpIY3N0WZz+cpXM3rctu0M9zXbDZToTWVDTcbajabKYqxWq1SXmuv10vzUVaLhrwLeQ1Ju7D1ELM7IJvNptAqVs+nYqDjw/dzConn0enyczX87IIox3IFAoHAFwWmRZL0GQwGadM1rU1TeatGcU6+a3rQZrPBYDBIRc4kW6gnlEgitOhZDXjKd+aXs6f+arXCdDpFs9lMqVMeFVEHh8dVNgMo6A+vQwAu6wh1olRWq4OT0zv8W1NvVYe5U+D6SJ+B9/R769/XRc4Q/zzIRarcIM+Rf3qOpgvtah5yFV3pDoU7hHqeR7pCF988wnG4YVB41Ov1ZJiXQb+E+sX02gFlzzVlRxUKN1LjWN7xQo13bUmnc9DCa29T6kJRIxv6LCpMOW8XOB5ZyK2Fryl/K2tUVhx9Vegz+e+7d+9iNpvh448/fqGxA4FAIAeNHjBVyaHEEf/ORaQpB714moQR69rUaFaDTGWnRkJ0rnqvSqVScET8uXS+OechB3eIclEMffacAc/fbmj6PHL6xte97Hn0tzow7kDk4Odum0PZvK7C6u+6rmwOuf+zbXo799rndJV55t4vc3ICN4dwHG4YFNgsLtO9BDzvXoWZF2T5l1ZZpfV6nVKgNptNihZo/20a7LmNc1Rx0VlgVyV1GrQlq7M/nJO2zsvVGijTVeYoqXLiOb45nrYv1OuVQdNn53g6f527rquvDwD81E/9FL7yla/gl3/5l0NwBQKBLwyVyvPUIdateXvTMoNS5TXHycli6gimKQFINURMb1LHgfKRKaza9pUpTsvlsjCetgbPpbFyTvpcrJ/Q8yjXNfVJny0XTeYzEhpF17H5bB4B0Wi5Fm3r5+PrntOBHv3IXevHtzkmOcM7d66fV+ZQqJPA/w8n/HierlPOFlG75SqOTxn5tws6D1/zwM0hHIcbRqVSScXH3MTNGf9cCDfHqhOaAkSoQKBhzc4XXtjrX3ZNjwKed/qgAG82m0mwMqeVkQnOjSFcfx5VDpyzbi6nUQxXJrynp3K5UlOnRBUgw+g8j46MRyh0zbTbkioWd0gCgUDgiwBlC3eK7na7KcXUCRC9xmWfRqUBFNKQ6BDQ8Gd76dVqhbOzs7TXkMIdEt1sjjKcRdOVSiWRVYvFohBVp/HO1uE85s9Ph0Ojxl7ToRERj5TrePpb9YLO5/z8PG1mx30p9D1C9RWPq3Ok93ID+7rw63YZ4u6k5K7Lfa7q4HgUiNe445BLVVJi77rPvCv6oHPg61wkLnAzCMfhhtBqtdIeDowGkFXyMKkyOvplvIpnrYJUv2AUgGq0c8yccFUWQb+gqjByYWsVQrvYlbLX2tHCx94GF57OILmCugrKhHEgEAh8kWArU+qGVquVWHxNRdX6KyeWgN1tN9UJ0PowlZNlxIjrCl6rBI7KzNx+N9tSVnIG8DZjdJfBmTsnp1s8ylA2di4KUMbo+72u6gi4Drsqc7/tvG2Rj6vo66v+6Ni5e+jv60LH/bxOWeDzIRyHG8L9+/dx7969FNqtVp+3xuMOzfplcCZcv3DuabvToe/zWLvdTmwSW/Gx17YyKv6FVkaB0MiAsj/KzJOVUSdDC8mUPcpBBYI6Ilo4506L/p1LO+IclO1SgadOhiMXfo4QaSAQ+CLxta99DYeHh2nDNaazAs9TgVRmKQmi8l7JHiViFJTpmrrT7XYxn8/TD5ti5IgglXtarK06gJEHl5eqn6gnWBPhztC2TTaV2NLn0utVRmukPjcm9aBGIvQ+HsneZaTrfV+Efc+9zv19FWyLRDhJyGdzB0kjDm64u9Owy9F5UaeB99VmMuE4vBqE43BDaDab6HQ6SXBSMFNwajh3V969h6GdAeEYKuRqtVpyILjHgzJF6pTwdS7NqFJ5vqs0lUouXJjLP/QcW2fIch2MlAXS+/t4bvy7Q0AWjWF1jsOCQBd2Za85bxWigUAg8EWg3W6nCAM3X6OcXa1W6TWAS2QOcVXjlmNQpqmxr92RtGZAoxO8V64eolqtot/vF5wFh9ciuM5xYibXRlVJLF2THCFER0nXSx2U9Xqd9j1Sx0plPp9Zx84RT2rkln0GuxyPL9IgLnM+dP5aX5nLQihzGrY5EH7P6zgMvr76Q6dBbZXAzSIchxsCnQUKWOZRak6hCx9nA3iOG8g55L647IqhBrmmSukXM3cvKhruIM2Qtt4jp8TK/i6DszuqEPyZykLJKvz4vO6cePh6WzjX75tTToFAIPCiYMtVEjKUs17oy9+uL3hcW7PmSJEyQorOA6PSSqx45EGJG46l47EWLmcE61xdx5TpCNcjem7O0PVn9XGcbCvTD7n5+XOUvVf23Lm/c3qrDNc1lK8ybo6Q0+PbHIVtToN+1leZJ+FRLr6fq60I5+HmEY7DDYH/2Ow+0Wq1UgRCDXBl3z1dyZkCdyhy9wMu8kzppbOHd6PRSN2SKDz1Ph4K1GLhMqGhz6AOCq93FsFzbZ3l4QZxHNd/9Nn9evYXn8/naWdJZcl0B26du+b46nssuvNxAoFA4POCBt5yuUSv10s6QptNAMW0GpenbryW6Qg38pgKRVJruVxiNpsBuEhH8paulcpFhHq9XqNer6cIgBZilxmSlNWq59QJ0qi53pOOTa5gXJ0pj1gwisD78lmZnsVoPPUWn0/nzbE4PzeYXY9f1ah9mYZvmY7S/xn9fHNdpNxp8ELobY7biz6bj6+OA4vYt0V1Ai8P4Ti8ZDQaDbz77rvo9/sAkIxSGuyEh4T5hfN0If3t4egcM6XGN8fWftw0qN0B0C+8K4HcnDS/VcdSIaQbCOXYfg1b6zPwdVn9gf9wDmTN2GpQ2SV2ANH55ITiNmUbAisQCHxe9Ho9HB0dpfo3dn9TUge4kJ/ARSonz88ZWbmIby7PnzqB56teYu2BpoU4C88xVO7mGlF4WpLKW52j/6hDpGO4QbytPs2JHpJAq9UKy+UyRVd4rnaLUufGmW5fyzKd4Me3nVdmbOcYeL/u89xbazl8bP+8djkQfi+3K3YRbroO7jSo8xCOw6tBOA4vGfV6HXfv3kW73QZwYWCzsxJRVtiVE9LeuQIoTwOi8e7h61qtlhgW3t8NZmcS6IRoIRvfy6Ut6XUcE7goPNsl+F1xeEQkpxj5LLVaLbFIy+WyMCd3Qvi3CqJtSiGiDIFA4ItCp9PB3bt3E8FDx4GGqzP8KvudiFHCBricL+/yUs+nwa8kFtl9OhSqnwCU6jCfk0cOdK46P627cDmrLL5Hm/nadaWeo+fq87J1rD6b1n7o2Lm8+jLHIfd8eo6Psctp0Ne559yFnNOxKyKgjqE7EDn7oGxO/r9wVech95NLVwrcLMJxeMmoVqtpEx8tVG61WgAuwps5AaMMvQuLnDDSdn25sK1ew9xZsi31ej3l1AKXjWv9grKQ2zslEdtCxnQ+6MjwPppjWjYW/+Y4Oh7P0zSjZ8+epTQlLaZSx4V5xVe537ac3kAgEHgRcKM3NVqZRqpyO2dkA/lIcw7UNS6f+dujzOz4R+Oaez6oU6I6QPdcaLVahToJn9s2HZErTtbfOfJInRU3SrULD8eo1+uYzWY4OzvDYrHAZrNJ7dErlUoh0sJIUC4K4rotVx/gn0Huvevqks+je3IOxLax1WDf5TS8yDx2/c+600Bdrs4Dzw1S72YQjsMNQLv5aEG0bkjmHjlQbHUH5GsEeA1wNeZDnQo6CfP5PAn5XK2FCoxcONjv592HeL+cE0FWh4rCQ6XOcBE6ngstRlJms1likwgN969WK3Q6nUKbV1cOej99rZ9LIBAIvCioCxiF9g01XQYqa6tppAAKzHlOR+TYatcpmvrUbDZT1Faj0yrT9VqPCpQZqdvaneYIMk239ZQnH1vv67tF8/d8PsdsNktRab6ntXbsLMVOSzqGpwnr2K6//PmvwvB/XpQZ5WVGfs4R8mtyXZX8/+wq8/G5bbvW/zf1f97TpAI3h3AcXiL4j75ardBqtVLeKg1wZcc1jchbugH5QumyL0uZENVCNmWHtItGLuKggqIshOyKx9cgl1vrwkAFtr+fg0Yr9Dw6DYvFIhXrqbNEJotKgc/ozk3OackpuEAgEHgRUL4vl8tEYjCiS9mmufYqJzWVKWd0a+TWUWY8qr4hC08dxmMe4dUUz13yMZdH7/oqR4BptIB1eXzfnSI1TJUoU3JoNpslHaF6jtFw6iF30nLkV5mOyBWHb1t/Xvt5kXMOr3r/3LU5J8Htk12Gu38uOcdy23y2OQ7hNNw8wnF4iXjw4AEGg0HqWMFuSuv1GpPJBI1GA+12G51Op1BcrF8s7WykkQjCFYUKXhdyFPS60Q3TphaLRUrr4b35WjtL8G/OSTtR6BwUuSgDj2sxuIbAnV3iNRqxoSB3R0znul4/7yDFnOFarZYcE0ZYzs/PUw2KMypUWOxpzjHLIi+BQCBwFVQqFXzlK19Bp9PBcrlEo9FIOmKxWODs7Ay1Wg29Xi81cnADnQ6Ej+s6Qo1AyrSccU9CRVn9er2OdruNyWRSMNw3mw0Wi0Xae0INO72/Guecj/7m6xwb7VENym/VET4eU7w4f9VVOZac89MIv67BeDxOaVo5w7VaraaohacL59Z/1//EyyCk3MEqc2ZyUSIn93Jr6M7ftnnwHLdXts3b113TlcJxuHmE4/ASMZlMUKlU0Gq1UucKbp5GZkO7/jhDoULTvyDbBAzP8/H8C88vLb+EqlC0OCzHFJSxBTml4H/T4Nf3mHeqc3NHStdBayJciKnTwR9eo7t0a5ShbP45xaRrHAgEAi+CzWaD09NTAEgdlJrNJtrtdvpbDXVnX1VW54w4J2n0mOoITbtxJln1jzbZ2BXd8FSenL7K6S99Po1cuw7wtF0lnvg3HQzXD5yf1k1wvt7qVesMfc6uI8p04zZDvez5/V5XuT53nd/f53WVMXf9bBsv90y512Xwz88dCX++wM0gHIeXiCdPnmAymWA0GiWl0O12L+0IClzUM1BY+ZfdQ4KuCJxh4d9u+KuAp2D1EK0LZXda1GD3e7pg1XvrnFTh+fPsEnS6bvqMfF9ZM1UKnAPXuNvtbp2nOxWez7stFSAQCAR24eHDh1gul+j3+6jX62i1Wuj1emi324nIYX2BNnhQI1lr5a7C/Kps1SgGr/F6L96P++IoG68ssN4vV4egY+r8ynSYpqzm3uf9fd68vzbBUBKKToWTSwAKxBIduNw8fT6u+1Rv5nRZGVR3u5O3bQx3zHLXlBn92+Z1Hcchh5xzcB3nQdfA7RG9/8uI0gTKEY7DDWCz2aDT6WAwGKS/1+s12u12+sfX8C/TarrdbiFVR4t4iTIjXu/tQsRrKvjlrFarqcMElQUZFyoHz29V9ikn2D1dSucFoBDlYGqURiT0+Z0ZU/A6hqM1L3g2m6HVaqVUAKZXTafTpDT6/X6h3mQbq5FzmAKBQOBFsdls0O/30ev1AFzs58OaOOC5jpjP5wAuUkyZJqSESM5Q12NqbPO3v+/EE2vh6DhQ9jFNyjfNdDY/5yx4ypT+qMGoEQbqiBzRk4vMuDGtOpbrwOYgXE+2KtcUKxauq15TIzanJ8rW9zp40et2jZnTZUD+f8GdtF1OwzadmLvPLv2Zc1a8ODpwswjH4QZAQUWhVPYFoJDVHHzNq+dY+mXxMDXPIcqcCP3tNQ8q3P05FGo4u0DNXZ8TqPztoW1XInostw58L+eo6Ho7m6N1Dv6sroDKnicQCAReFJRdJDZyOfROxmjXHyVzOJ4iF1Ugcka4G47eyUhrKsqYX5e1/qz+PLm58HeZIbpNR+Sehe97fZqTRB45YctybR7iz+jPybXT96+iQ3J6ze+Ve71tHnrMScSy4/q+f8Zl110F14k2lK3XLscl8PIRjsNLBpn5er2OTqeDTqeThBBZF6YtURGwRdx8Pke73S4Ib2WXOL4bxnyfwrAsjMpjmgvKuZQJc1VCHv3w0LCuAVDsO64RBUYuVCirE6AFgRrl0AiBRkG0AJysHYuqWajO+bHr0nw+L5ync+Xc1blxZi8QCAReBJRbTGVtt9uYz+dJjupmoRot5caWumEb5TN/8ziAghwFigZzzplQA1zlabvdLpBNfj7npPrBdZA7DxwnV1zM1FN1WpQo0mcjEcbjujY8Xxt6ABetXll47UXo8/k86Qfey9Oi3Plwosp1ohvfZU5WmY55ERJrl0OQO4evd0XedzlIejy3Fu4YusNY5izo/2jg5hCOw0sGBX+z2SwUvDEdqdVqod1uY7FYFELNdCJ08zLgcn4/cGHUMh9ToxYq0PXLx/d5Xb1eR7PZvJT7yXvqfXhMlYfvQM2xnf3hdTqXXLqTh7z1GMfIdXfi3g10ENi5inOmcqpUKknxauTBBX6ujoH3HwwG+Of//J/jf//v/42//Mu//Bz/JYFA4G1FtVpNdW8kLmhAM1Jdr9eTTKMM5sZsObIjZ4hRHrrRz2v4WskmnseOdCp7XUf4deoA8LU7K7n31QHSOaqjwLVx/aYR+s1mU3A0qBfYipWEHjsd8l5cJ63lUF3M83jP3DzdkCZyhNtVUWaM547tYupzUQS/jxvq/px+bi4iUvYc7hjsQtnc/X8ocDMIx+Elg4JC24dpqzp9XxkX1hs48+9fNgpJ4CJy4NfklAh/O/OTY5H4t/4uE4w6bpkgKWMtfN1y1+r7+hzq7DDiwHWlsgRwyTnj82vuLBkojl3GzNTrdbzzzjt48OABptMpPvnkkxBegUDgWsjpCI0C8H2N9NLIJmFSJrd5TKO026IFqk+Ay9Fi1xmcZ06OuxOh2MUUu74rM1Bz+ih3XAk1jVqTwON7+ln4tVxr1dP+zDoHX/+cwZ3728fd5hzsurevx1UchNzxXWPkoJ9b7nVZBMI/y9zzlT174GYQjsMNgIKoXq8XekFryNSdBwoobmLGKIV3FOCXRzdOI3gf9cz1eC4MqEpDoxz+xVYhoH8zJ1TnwPvp374+wEXIWHcuVYWlTBoNfypBjZTo/Hk9n5epYcq+rdfr1KN8s9mkTeH0Xh5613l95zvfwTe+8Q38u3/37wrPHggEAlcBiQhGfwFkjVyVlYvFIu2/w8YV1CEub5VcUpRFKjytyfUInRAgn4fPv3Pva0Rcz3OZ7/NU3chxcym3qo9IvlFH+DmM9mhxN3UE986gnp5MJpd0lc5Z153HdjHhZYbxLgLqqteVkXRXcRpyxdDbjHV36oDtNRr+e9fz5uYRkYZXg3AcbgD+JVLGW48TFEKdTicxRMzFp4JRQ12/SF7IltsIyIWDCoOyYmwdn19WVRyaGqXz0BxTCm7m7242G7RarcJ1hDoAORZL76EKj2lJwEX6Ehklrq3uF6GMnT5PrkCR7+uGd5xfr9fDP/kn/wR/8id/gj/7sz9DIBAIXAVK5FxHRzSbzYK8zpFQfE8NWo04eL6+GnL6nuuIXDqU1ptpjYHOz8kuXqcOBYuRNaWX15VFunPjaiSaa1ur1VKt4WazSSlIXDvOl/fcbDZpbwfFZrMpzEudDnVOdG1c15a9vqoxnUOZYb/ruL6v/w85Y71sLJ/3tvNy87iK8+DE6a7IVeDlIByHlwgV4A4XFPqF4PsUuFQgHvpVj10VDwWlvp8TTDkGwb+Uu4RFjlng3+p8qDJQQexKQZmtMqZqm2DlmlNQay0HHSkXhjzPGTT/TDR07fev1Wr48pe/jOPjYzx+/BiPHz++pGwCgUBAkWux7TLXiRpnuTUfn3LSZRmvU/2g+kLHVjmn9yOU5fdo9FXgegxAahjCHxry2gZVdYRfT13p0QwHxyKZRGJLaw9zcl8dJdW/Od3q6+fY5jz4Nbkxcsx9GXz83L13Hb+q48C56br567K5X8fw9/uH43DzCMfhJaLX66HX6yVh58Vcyoi4Qcv3dat7hl2duQEuF8RpaDqXN+sRAqAokLQIT6FC2zeL4zF1chhKPz4+Tgqq2+2mgj7NL9W6BGeLGDJm5IUhfRaEa3tCzpPdP/hsZOk8aqLhbzppntPLNSsTivz94z/+4/jWt76Ff/Nv/g3Ozs5e/J8nEAi88RgMBmkjSmX4c5FVdTJoKAPPo6xs7sB9eDTqzDEcGp2mPCaUPPH78bjeh6BeoiHu7LtGiSmHF4sFxuMxZrMZ1uvn+ylosTj3VeA12n1PuyPR4WAb82q1ilarle7P973+TcdhO1zvEKhRGuob1XtcC2fu3RHbRSJeN9JwVafNDX9n7svO0eNlDs+2CIM/S5kjsev5yuYaTsOrQTgOLxE59kFTd/iPr/2hcwwRBTG7P+S6YgBFQeXC2hkSDZ3m0oJyRnHuC6pfYK0z4GZF0+k0GftUAro+TFvS6AQdDDoLvA+7U3nkwIva+MwUfFQ8ztzpczsLRwXEDZhya+rz2MU0BQKBgCLHviuZAlykeTLnXqEsvG56mashAC5HC5QU2Ww2lxh3/pSljuYMSIdGSOgAaAe86XSa7s/6M8LrPAAUNqDTFF7Kf90viXqE8pprq2uuThCPKXmVe586gp+Xr6fq7lydodbe6fk5g3qb8b3rM3GDW9OlypyGXC1fmeOwLarg6/AiDpGP5fMIx+HVIByHlwj/8qvRClx8qZzN4Hv6JaFAVwbev1Q5IeQCT3P2c19EvT7n1W/7kmpkYLFYYDqdpqJjbylLQe4FeXw/V2/gnan02fhMOgd3rso+AxWmum50HHRNHLp++v5wOMR6vcZ0Oi1dr0Ag8HYjJ1tJSFCuaWTAjVM1/Lw+raxZhjsOriOcXNLr/XWZI1Jm7GodA/dHYNGx3kuJNZ0XdSCdAB2fuoHRE66F67nNZpN2mc7paD4Xr82lRlFv+5rkDH6/t+uhnA72dXSHxD8PX+fcZ+XO4C4HIndd2f103mo/5I7n1srHLPv/8TmG4/BqEI7DS4QL5JyxTwNVBSXf8zxVFoqRuVHjmNfwxzcFAlAQqKoYvMhZBTXH5Vg5pcNnYITh+PgYy+Uy7U2x2WwwmUySsOx2uyl3VZVbp9NJ82JkodVqJdZf5+DsiIbmtS5E817LhJwyURyTRdxcN86nzLFTxV2r1fCLv/iL+IM/+AP8xm/8xjX/awKBwNsCN0ZzhiKJkLJIM1GpVFLqZq1WK3QUUmhev7LnSsq40eg6QuWtEye535TBk8kEs9kMJycnKa2qUnmehnt+fo7xeIxWq5XSlXgt58tUIu18BCD95vyc0dc1U12SS53yz0afXyP1s9kspWRRP/jnoaSUOgpeeK4kXa4QW1/nPvvc8/mx3OtcBGLb+2XQeX3e12XPts3BCtwswnF4iVgsFqjX65eEPqGMigo7FSC5bgzaQ9rDp7ye8MI7FYTbPHt9TwWqX6MCb7lcYjKZ4OzsrKBcNptNYYM7VVJUdA51gFywcm1ywj5X+Kdrr/UknJuvD9dNQ9DuAGoURNeVc6/VavjSl76En/3Zn8V3v/tdTCaTS88YCATebsxmM7Tb7dQwIiePt5EfPCdHYpAMyUUs3Bj0+oYccVX2nuuenI4AkCKwk8kEk8mkQBqRPCPTr53udG8jvQdJqZzhzbXM6d2cjvAfT6nVz0LX2KMR7ugoiefrkfscFL62PG+b8+D3yP1v+Dl6Xu5aP5abZ25eVzXqnZDL/e/4/5feI1e/E3i5CMfhJYIsvLZ70y+CptZ47qPCjWYVRmTWy9iqMi99mwDQv7cpBT13vV5jsVhgMplgOp1eCjWzjsMFLfN2XQGoc5N7DioXZ75UKfhz8Dq9V+5cjlfmOLD4ToWWC+HNZoO7d+/i6OgIf/EXf5HStwKBQIBgZDZHLlEGanqqp1UCuHTMySGVczlDVB0BH7eM1NFzfczcuZTNs9kM0+k0pXBybnx2r0GoVCppv52cIVtW5KvOFsHn8XVWOa66WHWKPy+AS/pBn0XvqZ9BzmnIwXW5Hr+q80DknIjcT+5cf82/y5wZ/e3nbnMQyua87RzVy4GbRTgOLxmbzQaz2SwpB+CCrWi1WsmxWC6XhU5DKrC8HkCFlxdu8Z6EKoWcoNj15dUx/Z5qjE+nU5ydnRW6Y6zXa7Tb7RRZIDSNarFYZB2GbawDx+Ca6Hw0fYvHNZ1JN0tSRo7F0GT+2NWDa7tcLlPhXrPZTAzZZDJJc+71eoVaDs7hX/7Lf4nvfe97+LVf+7Wd/y+BQODtwvn5OabTaWpZrbKw3W5jMpkk2eTd5PRnm45w5wHYzkrr6zIdkSNcdFw6PcBzEm0ymeD09BRnZ2eYzWZpzixmJhhl0MiDkmVlBb7+zK733KjX85ieSrnO9FhmDHBdqT8ajUZKraXe4XE6FHQKOQemX6ku1PXyKPougzhH4Pm4uxyB3OttBdQ6dplTWeYgXef1VZ5dP5fAzSIch5cMCivdrp5fDE1DoqAoSwty1j+nIHiefvn0S8l0KBcAfm1OCejf+r4Wu2nnIp+vP6/udK2F33pPNfp5L10PZeJ4TOfrhdcuYJQNYvSC3Ut0XILKgc6BOh5cX95fU6zq9TqOjo7wne98B3/+538ebVoDgUCC6giNSgOXowmenrlNR5RFA8oMPo5bpiNyJJKz/HoNz6Gs15oL1U2a9qQtZ0niUNbq8+eMS3ek9FhOHwLF2jhPFfZ0VM0a4Fx8LG0FS+KJny9/qx5U4o8F277Gro/9uXMGeBnKdL87j3pMz72K4X9dXCcSwXuo/g/H4eYRjsMNQPcYyCkFZRx0989cjimvU7Z/m2JgPQFfUzgDl50GFf67hBXBObO4Lcd2kc3RwjsqBRWgvpOoztGVggoPF2A5xyqXi+rOhAsjVwz6+bVaraTMmIqm8ydDVqk8bxm4t7eHv/t3/y4ePXqE2Wy2dZOiQCDw9iBHLqn8VEfAdUROPlKe5urAnNHNna/39Xnmfrt+8PFJLOWKtSkn+dzqOLBGEEAhhUl1I8fgvbyWoyyVVM/Xtdb5qzOh0X895hEPjtdoNAp7SLDtuD6nRs3ZZQq4IJ3K/lfKPpddToM+v0cUyhwHP1/fu46xf124beKvc0504OYQjsNLBv/B5/M5ZrNZwfh0paDGp3byoXBxxsORy5ElKGy5l0JOEPA89+h5HEBBMPMYe3LP5/PEuDAky3sxhFupVC6FezkenQkVrJwb586ohitYChHv8c0N6DQflU5OjlFRhaGdOlRxsP+4p2CpA6XdP1Sh//2///fx8ccf47/8l/9ytX+gQCDwRoPygTJU5bhHpelcACjIVI6jhESOjVUdA1wYhdQ1qiMcOcJKDXONClDesbvTarVKcnO9Xqd0K43e6hiLxSLt20MDnDpQU01VhlPGUwe4ka1RZT4L95HYbDbp3lw7TVlSYo2vddM8JZwWi0VylNQR4r0nk0nafI73VCM8V2/i/y/bnDX/e1s0Iec0XLWT0hcB/5xy0Qt3IuhkU9dGcfTNIxyHGwANWv6jUzBoKFT/+XUXY36JNRdfhYK2HKXRrcb/ri++nlN2be5LXa1WkxJjmlKOCVNl5JEERhlUGVFp8XwPR7picoGpLBCv03vQsfEcVb8Px8gpBhXcGprW65QR0ed9+PAhPv300yv/7wQCgTcblBWsddO8ftURmgqpOxtrzVhuR2PVESR8trHEOYZZ33PDNneu3p/PpQXgHm2nDFWZr8+qslfXxGUy10HPzekPnsffvEaj8rpPhF7na+F6yKMtHM8ZfK4N4VEeZ9r9PTW63cjepvu32QRlEQc/ljPwrwMf56q2Cn8rkRoRh5tHOA4vGRQeZL6ZJw9c7KtQr9cLRVSa2sT9DjwiwbG1Y5NukJYLOeeES5njwL/VQfHrNcTKIm8a/6o4yGi5QK9UKqmXt85V2SQa57xOBQWfVZWoOl0Ei9LX6+dF3Awj7+/vF67LKQYqD8/fVfZKFTxZNo0S8dmq1Sq++93v4qOPPrry/08gEHizQRlHOUp5RT2hhcIEjfDVaoVms1kYx4kUdUZ0Lx+gvLhYr9e5UL55vV4ZocP9cPijjgPvSTmrjoA6EbrfAx2GRqOBRqORdI7qANURrFfjfXMGJ9cRQCrabjQa6Ha7BcejrOuVd4LiNbpLtu5krWuujkOr1bpkPLvz4HCnIcfS+/ll2OUwflHYNk+3G/yZ9TP0//XAzSEchxsADWSGRF2A+K7QZJD4xeCXiyHQ5XJZMFaZMsOuP+44UGipx57L7+f5ylDpfdQw19QgdXo4FpUBU5ba7falcZ3tJ8vD8LDeW9kyZ3+YLuTzrVQqBQW7WCxwfHyMxWKBVquFg4ODdM5nn31WWDMqCSoSFWb8vDh/PiefXZUnj33wwQf4nd/5HTx79uwL/u8KBAKvOyqVSkpVAoopSirDASSZQ/mrcnw6naYosBqrJJWoI0h+OHvvaVI5VtkjqqqH3HBXx8WNRMp7piPREWD6jjoXWiPHFCfOkeeo/PaUWo/Y8B5KTq1WK5ycnKQuiFqUfXJygvF4DODCaeO4fE4ntLge1WoVrVYrPbfqP+2Opc9KbDOMc0Rg2XsO1U/uMPh7N4GySIbbLeo0qEMcuFmE43ADoGDSrgk8roIduBAqhLIWfA2goAw0T9QZDS0k04hEWRSCr12YqPGsPxrmVeFJx0EdAM5Hx+SaqIDXHFsVsirMVJjommpdhM5/sVikHuIcdzKZJCfh5OQksUeM8qhyyYWZc2uYE7h8zkePHpX8hwQCgbcZdAJ0IzRCmW1NRSJYdKwsrBIcriNUnuZ+cjoiJ9dyRqXrBjX29D2gqJu0Bk/BKLtew4g0IzE5feU6Qo9r/QavYR3idDpNLcK5L1GlUkmtxmnoV6vVS2llvkZlujVXY6gOwzYHIOfA+TEfV1HmMJStYRly0YDrYNvYOd2qUNLSnz9wMwjH4SWDRuNisUg1Dh4BqFaraffQ2WyWrq1Wq5hOp5jP5zg9PU3szGg0utQPWhmq3ByAi05AHm3QL6myJgr9svJcVVZa40Dh6O1KtQCOCmEymaT3u90ums0mOp1OSm3SvS90szhllBiuBoBms3kpjFmpVNKO1mdnZzg6OkK328WjR4+SInj06FG6t0Y8uLbsNc7jGnLns3jhOefpAjkQCAQIjdxSllFuqDztdDqpwBi4cChOT08xm80wm83QbDbRbrcxGAwK+yMogVNmXCpxo0Ypr3MW38ehHPTaAWeIOR/dS4f3YTSBNXR8Xt6zXq+j3W6nCIXej8+q0Q4lt3gOjX59PpJHp6enAIB79+5hPp/j0aNHaLVaePLkCZ49e4Z+v58cu/l8ntaAzTA00qBpyVoLp7rVC9Vzzo7/nXMe9PUuXbMt2lB2/heBMueHyEUbcgQmvy9OxAZuDuE43BA0pYcCUAWds0o8v1arodvtotfrodlsFtJiCA03e+FbGRvi1wNFQavMlV6j4WgyNGdnZ5jP56m+QfNINdrA16o8VHj3+310Op2CYPeNgbwzhjMfytSt12u0Wi3s7e1hs9mg2WxiMplgb28PvV4Pjx8/TtfevXs31WlUKpXkxFGRnp+fpy4Y2oFE11yfR5+5bN0DgUCAoOMAoBB5VcOQpAqN9MVikTar3NvbQ7vdTga5Qo1Wl1VAUW66rFIZzmu0TsD1C50MGv5nZ2eJydeUKE2V4tiM8moTEeqber2OwWBQ6LxEB0SfQaMb2nhE69GU1On3+8lZYsTnzp07ODk5SZGGer2OO3fu4PT0NMn3k5OTtLYkjpgyrPpB1xwoj6Lr+qqTpnAHQnUNHRrVqf45ljkM13UmduEqBn1ufvr/pPaDnhs1Dq8e4TjcACgIfVdjQtkgoLgpjabN0HClMFSHQ5WCs0OqKHxevE9OIClU0PE9Rho8ZMsxKOz1XlwLCgYa6sy/9RQljY64UNwm6HRNWWOxXC5T1AUoFsWRnaPwpeJz50YFGeft6WE+B74OBAKBHMhQ6yZwOeNOGy/wGFl6khpeM6dyyg11/vYotL5fNt9taTA8R7vuefQ1Z+Cq4cxIAJn7arWajHKgaIB7pPcqspfncN263S5arVZB7lO/MRKt6cDa+junj+m4qOPgc1E7gM/EuZV9Hrs+p13pO643/X9s2+ur/E+UzXPXPcrOUztF7xP1Da8O4TjcALyrkoZSVcgQFEDcot6NU68dyAlJjWbsalmW6ybkAs29fjJGqhQ4b+0trvegoNV83vF4jHa7jX6/nxSghym1v7Y+t8+b89LQNJ+/2Wyi1+vh4OCgUOvA98fjMTqdDnq9Xlq7er2eHI16vZ7YPu0QpbUl6ti40nAGMBAIBIALA3s+n6d0VsJTW9Uoq9VqKW1H9YBHFtRZAPJ58GUMN4/5cdcPAAqkj6brqI7gtZ4KyzXQ+axWK5yenuLk5ASj0ehStF31lDPSatDzfa6hdidU56XVamE0GmE2m+HJkycp+rPZbFLK1HA4TM4L5TvTptT5YKqVO2yut5gWC1x0WNL12xV54DNq9N0dqG140ejCLqLxRaEOk0cg9H60PcJxeDUIa+Ylg19+1jloKNpDp8oOkUnyYjZlXZy9AfL1Cio09SfHIqgw9lAgn4VGszoMzDelomu1WikErCFkOlFUJkwlomIALgS/zlOZKA/PqhLS/F93mKrVKnq9XsG5YESn3W4nIa8OQafTSccZ7dHzypiYsihEIBAIKCjXWAenUVjXEZRrlENA0fikcUq5BpS3v9ymI9TgBi63o1Yd4c+iekJTXhuNRjq/Xq8nI1tr9agX2J72/PwcnU4Hh4eH6Pf7l3SlM/QarajVaomsosGutWnUD7oGavSrQ8H2rxpBZ1oYo9U8R/W3r6uuoesGXdeyyEOO1ec5rjd97NxPbj5X1Vufx2jPPbs7DMBFhywlLvk5RsTh1SEchxvCtpCtCxdnKNxx8ELoXeFDIvdlLTsn954KK3UggGILPF6vjDtZAi0C3Gw26HQ6qYZDheY21kQVaS70XsY20emiYtJuI+12uzBPKl8qYH+eHGtXppwDgUBgF6gjcvsFqI6gLPPoAnC53o3IRWeBy2yx3mMbuaTzyY2nOoLX0JDn3zpPjTLozsskb3q9XkFG73oWlfn6WnWL/wZQcGLUAWH0X59N04dzOrtsjtt0rBv1uxwHPb7tfR3f7+P383OvipytsG0OZa9zURMnSdW5Ddw8wnF4yahULroIMUWG4Wg3NJ2l9sJgVRDbBJMKEQ1754zeHDPPL2Vul0+Oz8iB7oyp3TTm8zmOj48TU899HFarFSaTSao7uH//fmKe9FnJMmifaxagASjkoTK9iSlNVFhcMz9GZ4CdoM7Pzwvhfi1q4721naHvKHoV5yAciEAgkAN1BFtGTyaTtJ+BngNc1glKoHAc4Or1CW7ce+qsRot9jLIGGJVKpUASaYqSkjNnZ2epAQVZe90wrt1uY29vD/v7+4VogzLPZPWVjKP+oHGvMp3RHGXnNdKtepaZAtwTQ/WvpqhyTqofnDzaJf/decgVOZc5B2o/uP7fRhzq51X2/nVxVX14Fei83AbRaFbg5hGOw0tGpfK8E8b5+Tmm0ynG4zFGo1F6zz1rZdDV01aF4SG9MkXgyH3Jciy53nOb4FJGS9N/fOdTsmjKpnU6HfT7fXS73YKCVLZGlRgFvTs5ysiok8brNSrBcDK7W2no2ZWnFmvr5+JCNqdkuXYq8DynNxAIBAAkYoX7BozH4ywzrnIuV8PgdQcaOVCZqY0syphr3seNV33PySwe1781Gqy6iQXPNM4Z5V0sFokUGg6HSUfomNppyiPvufQjfU4SWTQ6nSzSrk7qQHjKTKVSuVR/6Lpbf2s9Y04v0NniGuVqMzyao8+kzlnOeC+LNOTevymU3Ss3L127XVGVwMtHOA4vGRQSy+US8/k8sUl8L3e+b1CjBrR/YXICxQuqVHg5E+JQYaRGcc7B0Gu8fzcdBV6jDAF7kvf7/UKkwY1xFZrKNORYFJ2fhqRd8GjReK7jk34G2jLXWQ8eyylKTzHztIFAIBAgKCPm83mKOGjLaj/XmXeVOW44537njGu+lyOKHDmSy8/fFsHme1owTXm9XC6TcU+ngSlCbvSWsem+N0Ju/XJ6gvpBo9Pq+Oj6aFSa5+TIpZzh66SSGsS+frnIBddTzyuzD3QMXz/XXzmDPfd5Oq5ixOc+h9zxbdfrXHO2QODmEI7DS8ZqtcLDhw/RarVQqVRwfHycnAd2iGBIlT8aPQDygteFP8/jj7d+pYAiaDS7YHLm3Y+R7WEYWgv6VOkwVM1xyOAwPWk0GqHT6RQEt4cg6XCoUPVN5jSUztoFn6v+7WFpXQOteeAxMmMa8nZngeuT2+BH5xwIBAKO6XSK2WyGTqeD+XyOZ8+eYTabodfrFVI1dcdk6gmPNnvXvjIdoZFh4HIaa4495/WanuQMN+UjiSOtV1DZDKCwrxF/6vU6Dg4OMBqNcOfOnST7lfDRzducYNLnqlQqhcJxptaqU8b0Jf2bjkOOJGKaK9fGU6JUR/iac66uH7w2UJ0av94jEnq9Ox8K11m3HWXOjJKQ0VXp1SEchxuAfuEpQDXsScGYY434Wr1rjyzoffhbBZU7IsDFZjgqyPRcV0qqUNQ5UEGWY/8pBOv1Onq9HrrdLgaDQaHjhAoEOki8lwpPzlk7iqhT5YKWa6aKxXca9QiLs0B6P30+nTeViEYpXBlExCEQCJTBdYTWl/F9TYvhMco0l9d63O/j+kGP5/72yEKOhQcupwVxDjo/vVaNQ6aRDofDlKLkxI8TaHpP4MKI99Qt1Sv+/OogUAdp3Z5Gd1Qn+N/aPdCdKF036sKcblUdn2PYcz/bPg8f5yrRhptwLq4bZdD/FaC4UW3g1SAchxvEZrNJuxM7054L+6rgze2kuS31qExhABepQ2oYK+uujos6HypsXCkQqjhU6TQaDQwGAwwGA3S73Wwdhwp4dRoAFJ6XSkb3kuD7qhA0l1edHWV+lM1z50hDy+qouMLT13QclPnj8VarhcViESxJIBDIgsXBSi45uUEZqzpC5SZQdBxyOqJMZrsx6zLRjVw37N3Y9X11HEoscR8F6gifh8p1PeZEEcdjNIEM9TbyTZ9LiSvqQ40kq86i7tTot665rps6Dn4f1ck5eLRB19OdBV9fdxCu6zRcV185gbgN/n+Ym7OfH07Dq0c4DjcECpWnT5/i+PgYp6en6PV6BcfBHQs1ytVw9i9NLkcSQOFaBRkSgp0mnKFxx4Fz4ry0HZ0zN5reQybp4OAgtV1VNkbH5U+Z8NlsLtKw2BWJoWZCFQjnyjVot9vpWmd+uJaNRgOtVit1gtJ7qkPBteSPb2Ckc/7a176Gf/Wv/hX+43/8j/jwww+3/KcEAoG3Eewq9PTpU5ycnGAwGKDX6xUICN0Lx+V0jo0mcjqCKT1lLLUawqw9cHZfjWQ9RvlHHaFjELoLc6/XQ6/Xw+HhYaG9KcHnVoNb9Y6CjgLTWTQ9Sc9x3bbZbApdmjQDQNeGKWPtdjuNpTrL07x07Zn6qmvu2QdlUKM5p9N9HfTvXZGGbdg1L9XVu869CvxZ9Jn5f+SfZ+BmEY7DDYGs9Ww2w2w2w3w+LzA0/FKocNRcTmUsHLkv7FXYIIULmbJj+joXLvX3ySQNBoO0C7Mb2x7OBi6EaU5A6vx3/db1UfbOx/QQt0dE+Iz+2rtd5ZiQzeZ52Jvh98BukMnzDaYCgTcV/J9nzQNrAAjWcVFH6Gs3AD3SwGPbotIu969iAJYZoT6Gy0o9t9FopGYZuY3rNGKg6agekfFoiT5zTi/4M5fpWI1saB2b6gL+1vXQ9GO9d87oLYsA6Xvq4Fz1s1GSriz6kFsPv/dV/id83v45XAVl/7NOXG6LzgRePsJxuCHQcZhOp0kxKNNARpvOwnq9LnjWNLjLvjAeduWXzZkPPX+XI7FNKXAuFGSa4kSQwel0OhiNRml3Zp2XFzV7lMSNfWdmck6MHleFUPYs7gB5q0NdP1USueJAdR6UidP55xyiwAWU1QvHIfC2gFHgyWSSyCWV05STTi5pA4dcQbPKS4+EljHRfN/H0jFdp9AxoF7ja60pU6OZ4zebTQwGAwyHw0JzkGq1WogcuBOQk6EeKck5Ebl18fnnIt3UW2XEkqa0ch66ASrH0fpCQnWG/uh1akAroVgWMXLd506Enp97ret3HQfCUeZM5P7W+XNd1Gng/0M4Dq8W4TjcEE5PTzGZTNBut3F6eoqTkxPM53NUqxe7GfMLtlqtUncN77bkxm+uvWgZa6JGriokjQKoANOe1oTOJyeMdA+HdruNu3fvptoGVQhUKFSELhCbzWYhKuHKwnM9eS4dEy0u5N4OPFc7Y2haGNOuWq1W2jVa82lzQlWdAC9cdAFfqVTwC7/wC/jggw/wK7/yK5/n3+mNRaPRwFe+8hU8evQIz549e9XTCQRuDJT3zWYTJycnGI/HWCwWaXNKNZ7Pz88xmUxwdnaGZrOZZJfrCDektZbLIwBqrCqjT7mq+kNlv8phGsusMVC9oxEE4LnD0Ol08O6772J/fx+dTqcgK91RUuOZKaUc09NEywpo+RyqU3I1B9ylGkBy4Lh+zWYz/QBItSVeo8h15f3UiHc9rLpDn4Ov9bk8NarMiFfdXJZeW+Y07MJ1HIirjlt23mbzPMVrNpthPB5jPB7j9PQUZ2dn13JgAl8cwnG4IfALv1wu0yY/ZUJxMpmk3TObzWYSwtpVg1+ynIMAFDsG+fsUXC44+L4zNc7w+xxUsBFsvdrpdFIuqLI06jDkrvc55I7ptapQnB3xyIGyQVx/3Rla27LyPno/F/K+9g79HPb29vDuu+/iR3/0R/Hhhx9iPB5nr3kbsb+/j16vd2ndA4G3ASRSKpVKMoxWqxUajUZBR5yfn+P09BTT6RSLxQKdTqcgt3KRgG3RA8JJKf9d9trZ8Rxr7tEC4MJx6PV6l1JYgYt9HnI6Qh0Y3lPltJ5TVgfic/WUHsohX0vf48c/w5x+zOlaj1LnokU+Z3WKdP76meSeJecs5D5fhc9f56znqFPo121D2f+Sg//z3AtL278HXg3CcbhhzOdzHB8f47PPPsNsNisUiFEwPHnyBPP5HMBzBpa7K1+l5ZsKRWfpgYsvpheeaViVDAnPL3MmeDyXTsKCaG7ydn5+nnbaBJBC7CoQlZVRBisHXS9lvLQndy73VJkaFu3pnDWioulhvn8Ex8itrY6pnwfX+M6dO/in//Sf4j/9p/+E733ve9nnexvx9a9/HUdHR/jzP//zKH4LvJVYr9eYz+d4+vQphsMhFotFMvwp85bLJR4+fJiOtdvtRDDlosdl+wZoBCHnWKiu8ahqzlEo0xF0iBSVSiXVNXBn6PPz87TfEfWKEmuUw5yDp4TmCCPVD8rw81moa3LRExJ12hhDG4LoXkg8hySU62l9bj/uxFfOISlzHMqcNa/X2+Y87CK89LPOwT/76zipuWM+J/7PcwNdOsyBV4dwHF4BPvnkE5ydneHb3/522iGTYWnu81Cv1zEcDtHtdgupNb5Rj8NZHQpKP64CRNN/XCGo0ctz+DdTerRD02ZzUddAh8cN7eVymVKEKKxdcKoQ0jko60bkWsIyRQlAUkAE15LsNkPVXGdVwnq+KizmFZc5NorcutbrdfzMz/wMvvGNb+DXf/3X/7/2vqQ5ziy77mQCiZwBAgRAgmSxijV0tbot26GOUG3a4bG90MKhsLT1xuqFlt75Jyj0DxSSdw57YSscoQjbYbvtthWS1bItd1dXVTdnFokZCeQ8D8j0gj4P57t4SbB6qALJeyIQQH7De+97X+Led88d3hvNnly9ehV//+//fXS7XbTbbfR6Pc9tcLzRePLkCQaDAT788ENsbW0hm80mdMRsNgsylrljSmpQxsTwIkY7tvjmdQASC2+ej+kIyl8WxNCFbiqVCoRYPp8/tz8Fc/vofdHy1rPZLLEwZ3/K6tswJasvOFadIw1V4vFcLodMJhPO8z6WAyfxZBfk2q8SWDFW3uo+guPSioFqBNFAsf2/yFCY53H4ReIib8M8g+FFXg8aZqPRKOSIuuHw1cINh68Ao9EI7XYbjUYD5XIZKysr4Z9hNBqFxSsVghoNVihYgwB4OZYjJkgsi/Gi9rjg1vwLjV3lj60soRUy2PY81iQ2BssgxQwl6/K1bfE8cxhUcMfYGo2fVU+HjivGyljvjzJFCwsLuHr1avCAvKmGw82bN7G1tYWNjY1QSWYwGLjh4Hij0e/30Wq1UK/XceXKFSwuLgYdwfAlloy2sezzQkmJmLx5kY4gYjIqpoOUALIbYp6enmJhYSGhIywpox6Kecy6jpnnVTbHwpN0rLHkZvvcqt/UcLDkls6d/s1njenqmLHGsWsfGrapXofYO52nv17G0xDTt/a59Le++3lzEMPLGA6xd8IEeeoHW4Ld8eXCDYevCNPpFE+fPkU6nUahUEC9Xg+syvr6emCTKHjI7PMfyjIuupCNJQ1f5Bq0rI26Wq2rmoKfLnJNIj49PQ1xqyw/SgHGZDcqBVUUAM4xSSpwNRTJGhE6bgsKcF5H9oqKgYySfXYVunSVkgXSClJ0nVtWyxoKPDaZTBKKk/2/qfhH/+gfYWtrC8+ePQvJns1m8401pBwOYjgc4smTJygWi5hMJmg0GoHx39zcDPljlFnq/bWGgw1voex8GbZX79HjL2L9M5lMQkcACHKY3t5isYh8Pp9Y9DJ+nR5degLYtnpR5j0jF5U8pp4EHlcoGaXyn56FpaWlxLPrebZPnabhr+xfPRHWcLB5fTzPkC1uGspxal8xI8EaHUo4xoylF717ayDob3vsZQ3RWD92TPZ8KpXCYDBI6AeGcju+Grjh8BXh9PQUd+/exeLiIra2toLRwBAgCo5YiJIKSbsjJpAU4vNiLXlMhY0VauzPLuh5HxWV5kZQ2GqsLZCMl1U22QrQmILiuNi+TShXKNNln5t96zVktzOZTELY2vwIrdJkw5Nihoz2G3OH04hZXV3Fb/zGb+CTTz7B9vZ2/MvyGuL27dv4zne+g2vXruH09BT9fj/ErzocjudlWT/99FNsbm4il8slZBfDaGJEB5CUqxrmo+cs4RLzmCr7HmuD/Ws4EoBwjLpAKw/xuOo0q9tUTmp/ekzHrknJGv6qC3PeQ9kfCzPVMCDdfVqTom3ZW63kN51OQxUsO0+WxNK5ol6jjmLYrJKFavCpkaPzYb8L1uOg35EXGY0xxLwJ9pj+bY0MPa/3zfsO6N4dg8EghCk5qfTVww2Hrwiz2QyNRgOVSgX7+/uJyhKxetD6D6dCVZXCPOv/onFYAWTZc80tsMpCq0uoULZKge3yOhXsVhhagcd7XuQ90bFqdRHtl39z7LlcLixU1ZiwXg8gqVB03rRt3ZwmFlLG+3Qes9ks7ty5g6dPn770O3vVce3aNbzzzjv4+te/jslkgk6nE6qIcWNEh+NNx2QyQb1ex+HhIXK5HIrFYiI2X8kN9Y7qgtmG/VD2vix08adyTPWDLtZ5jw1VIjtPb0Rsd+iYJ0Cfh59VtsZk9Tz9oLrLJjBb/cmyqyTwVOepbmF/qsPoYVFZrwYRPd52/DpO/miFPx3vPJLqRUZDTJ/Omy9d2F9kMMTOs915Hgrbt86H5gTy+zsajTAcDjEYDFw/XAK44fAV4/79+3j8+DF++7d/G6urq+cEidbP5qJU3XT6j2nj9XmfKpWYa1SvV+GpLIkKKHobisViYIl7vV4QrHSh0xCigcO+c7lciGfnQnE6naLX6wWlyKQ5y2AASWHD+WHbVEp0GSu7w/uWlpZQKpVw/fr1IID5TOruV8FsE7A5HjJpwPPQAiZ+Ly8vn/PkKCM0nU6D4VUul9+YkKV0Oo1/+k//Ka5fvx7eP5Oim82ml6d1OAz+/M//HJ999hl++7d/O8qU6yZjLAShMeCU78BZuBCAcwtwJYj0XvW2xoigeQvYpaWlEI4EPJePTJjO5/PB62Db4OK82+2GsKXpdBoq61BG53K5cwtYILkopjdA9RzDj5TAUqTTaeTzeVy9ehXFYhHNZjPxTByftqshRHb+NMyWCb65XC6R1K7viPPB5ygUCkin0+H5+Z7T6eR+FGoUxcrzvqzRwOPabsxQiHkUbJuxRb5tj8cYraDhzKPRKJSvbzabaDQaXnHvEsANh0sAZSt0V1DL8FAp6M94PI66J1VQqLFgDQOCwi/mtVDXL9sAkKguMW+35ZgQVWZ+NpuFxXar1QqMlCoQ2zaNC7apz6ysjAoj3WQul8uhUCiEih9WEVOBqmJ5kedDlR4NGS0rqFBvDsedzWajJfheFywuLuI3f/M3QxWr1dVVAGc7ww6Hw+B18KRoh+M8lGWm/LRED/WB1RXMq7K6wYbBWC+qLgyB5O7GMeND7+E5MveU8ZYN5z1ETBeSLBsMBuh0OiE/jOSL1X/WELLHVO/RkOBccQFfKpVCOJgmd/P5NbTIzpPVD0r6AQihyEtLS+f0o14PIBgBvIfPy/ca0832J+Z5ULzIeLBjs+O071zvtd+nWFvaj/Uu8dlILnnRjMsDNxwuEXRhbd20yiZpkjGFsYbZWCFhDQH2BSRDcfg5xuzHwEW9MkdqNCj0c8wI4fNxzLpLKtu1wlDHwTlgW7onhO6oOpvNQkWSmCJhXzFvxTzmRmNyORYaNjZhWg1BvTbmsn6VkUqlcOXKFaRSKSwtLeHXfu3XsLq6ioWFBQyHw7DwOT09DawSS/Q6HI44VEdo+IqSMDw/Go0ShoOGwGp4qdURL6Mz7OLRLjLZruYFxJJ0X/SMKnP1ublgpldFZbwNQ2I/Nl9AyRv1erBPGg3WMNL2rOGgz2V1p3oGSLaRXY8ZTrxXw2PVcND5sO8uZixYvIyxMO94zMjkNbHvA++JfY5dZ9ufTCZhU9yYh8jx5cMNh0sAsj8URtxKfWVlJSEYWHFiMBiEfyC6O2OMP9ueZ+GrMKPAVUWi1wLJf3a6bcmc0G2szJZdEJMl4vNSQJLtKZVKCaPJxpRahsOGMmn5O7sQZyLh0tJSqH3O0oax+VEBxvO6gR2PU4ExgU7L0HJelUXROaTgV4X2uqBUKuGf/bN/FiqDZbNZAEgYxul0GqPRCJ1OJ2yI6HA4ziOVSoVwRuYFMS9OqwjRa0ejgR5NLVZhF+8xHcH2lPiw5cB1bNbYoD5hWBBJLy1cwfNW9vFaleHFYhHj8Rhra2sJHaFFLThmOwbCVk2K6TMaWcViEcDzUBnrdeY9SuyxPxobHAsxGAwSobx8H+o5t2QZ559zxrAv6n8lX2KelXnhSfZ7dRFBGDtudaO91s5NDHwf+o74zHw2Gg0nJydot9tuNFwSuOFwCTCdTvGjH/0IN27cwAcffIBOp4PpdIpSqZRgXCyzAZyx/hQUFDKWEWI/FHianHwRI6GKxrps6YpmzKc1QKyw1d/6THyOmMvVCnzbrgooy1KpYKJhw4Qrxotq/zrXVgnpj3qBqOh0oz7LxNj5UAYulUrhm9/8JorFIv70T//0lYrhXFtbw9/6W3/rHBtJA80qUjWiTk9P0el00Ol00O/3Q46Iw+FIot/v4wc/+AHee+89XL9+Hc1mE+l0OuzjAJwvKQ2cLZ4pZ2KJtvN0hGWy54HntEw1wQU5iRXVUzF9YOUkx8C2qSPsc6q3QL0pbIPXWCaeOkufgQtWlkFVBt+Gh+kcWKafi2DqG92zQselbVB32PdGw5GGkspRNWx0jmO68iJcZDyoTp43B3w2LeKixU/s9dqGhqex2l673Ua/3w95kW48fPVww+ESYDab4e7du5hMJviVX/kV9Hq9IGzsQh84c6+qoODfdAtrTL/2o3/H2ADLrBBW2KlHgAJRhXDMYODf+pnCXAXzbDZLMDFWEVnvg/3RPmwsrZbO092r9cf2axWHIlZJSeeRY+W91ghie++//z6uXbuGv/qrv0K32/3SjYdU6nkS3ssqGc7NtWvX8Pf+3t9LeIms8afvSpUCmVPuiMtESIfDkcRwOMQnn3yC1dVV3LhxA61WC7lcDqVSKUF2AGf/dxrCqTqCxjy9rdQDlu2OhZTynJUTKrv1GrLwSqrY8NBYWypHaTDYRb8STbzGyugYCWRZbr2efVA+6XPo2K2+UUNNx68eVvts/KxtxAwA3qM5f5aEsbpqXqjSy/wd+6xj17Hqc+k1MQPUrj/s98AaQ+PxGL1eD61WK1F4xPHVww2HS4RCoYAbN27gk08+QbfbxfLyMq5cuRJcqPwnY3iLVgFSll+hVn7MUp+nBDQ8SP+ZeZ7Cg/XFa7VaQoiT0WdFCF1Y07A5PT3FcDgM7eXz+SAcWNLO5npwHlRpqNDk9cxxsMwV22QMMBer6vJWYc++6FXRd8DzthIT2SUruHUXUt23g4ZSqVTCP/7H/xg//OEP8cknn/zM36OfBZubm/jn//yfnzPYLKOkCoOMXAzWiKQyput/PB6j3W5jf38flUrlnEHmcDjOY2VlBRsbG9jZ2QlE0fr6OgAEmUf5xQpAWv7UkhnKVtv/dyCuMwAk9I3VD0Ayr4Ab2GmblB80LNSzS9m+uLgYPLq6GGZVwUwmc04/ULbEmH3VBZpPZ5/VEkt2XwXOtc4dw8jUA8I+qCdprDAcyu51pKSW7s9EWcoNQ3XTUrt4n1cKfR6ZFjuviBGG2ve870ksV9O+A+2Xx6kfptMp2u02jo6OsLu7O5fQdHw1cMPhEqFSqeDP/uzPMJs9j93c398PC0oKL+tZUCYGOM8aUegSll2KuUuJGKtCA4BQr4PmTFAAqguZ0OuUPbGhQMoMWWZMcz/0R6tsWFaJ4+aCV3MurBdEY0gpkJVF0vFzTFYx2/nUObbvjMfL5TKuXbuG27dvI51Oo91uo1qtnmvj58Wv//qvY21tLfS7vLyM5eXlxKIiZjhwvNPpNKG4VQG8zOJjMpmg3W6j1Wqh0+nMXaA4HI4zPH78OCxom80mptNpqFbG/0ngTC7P0xEEZan1tL7o/zEmIyj/NN5fF8TMdVCyxLLlbDvmXdd2eT/j/wm9T/UPP6t32RbU0DFPp883HNMS2THZFkuwttfofaqDOF7LuutYYot0DQ223hU+jzUcYgbEvGO2P5XtOo+x+Yjdr98VOz8XEZr0RrdaLU+KvmRww+ES4eDgAAcHB/joo4+wvLyMnZ0drK6uhgUalYE1HGL/2PybhoOy9PP+CfWYskcqKOwim2PKZrMh1p/CwVZ80DERCwsLCfadP1QKtkwplQ2T/zhOejDoOdDYegpY/vBeFYKqNNgPFQOfMcbwqBJUVoyfY4YJn1uficI1m81iY2MjPP/e3h4ajcZcRuhlYe/9O3/n7+CDDz6IutatIaBzFKskwnce6yv2PaP3odVqBcMhtk+Gw+FI4ic/+QkePnyIb3/722g0Gmg2m7h582aihDWJjnk6QuW/MsMquyxpFIMloVTHqD6iPKZ3GkgWh7D6QWWvyhjgLAeBrLwW4FASSsvSsl2tQMhiDSr/VPf0er3EAl1lPdtT/UAjwxpDSoTZMK15Bpo1CPRdcB6th4P3UP/ZsCpeY0mrmAGhRp2OSb8/6r1QfWjXFzZ01balRqcln2g0tNvtaBETx1cHNxwuIW7evIlcLod79+6FBF56G1Kps1h0CuqYl8D+4wNJplsFnLpXgWQ1CsseWJaBQjifz2M4HGI0GkWrXFDQWi+ELkB1nP1+P7h7raBTAalhPzQoUqkURqMRyuVyIhGQ9+ruxNZwUOPBzonCftZ3QcXN51fvyTxWh8+Zz+dRKBRQKBTQ7/dx69YtvPfee7h9+zaKxSJKpVLojyFf1pBRo8QqBv5mbLSORZXBPFbKelhUOet1dh611Goq9Tzc4OjoCN1u13cEdTi+ABYXF3Hnzh1UKhUcHR0lwpKAM5msi2Erdyzjr4tKvc4uCm0lPiBJNui1BMtf5/N59Pv9YExYxpmynOOyBBXBZGstNWvlseYA6t5I/E2SiVXfVPYBQLfbxXQ6TYQTqc5Sj0tsvCrvrRGhclr1tBY10XlRY4hVmQqFQqigtbCwEPJd1NihrFayRxfyCvvOrPzXc1Y/8F7OnfUo2UU/n1/1g+Zz8rtQqVTQbDYxHA7DesBxOeCGwyXE2tpa2H2Zm5+sr68n3KyqACxi7LRdyPEf1xoGer0KPMtWKUvA+EsVgjHmQVl4vUZ/rNeDO4Xqc7M9HbOOj9B8CFWMtgpSzLVLlkznU5WnFahW0PKcKuV5Xh5ti96NTCaD4XCIXC6HK1euYGNjI5TjU8Gt3hq2E1OEOkcU7LZvVVT2u2DnWduZl29i50INt8FggFarFQwKNxocjpdDOp3GxsYGhsMhGo0G2u02FhYWErvVa3gPgLn/24QugvnZ/v/qcbtg1IW0kiX8n2eIDWUv21SjQ8OQrFzidVZWsD31rHCc9jPzy1R3aiivylDmX1C+WQNMvdA6L7poVmIsJo+t7p2nH3hen4t7QEyn07A5HPMo1NPAsahBqJ/1On7Wc/P0g35vYmsNfdbYeiV2H79L3GG71WqF0rNuNFwuuOFwCbG5uYlSqYTV1VV0Oh0sLCzg1q1biUWzjfFXqPBVQcBYVrvoVje1FZBWIGqIEDdRAxDiV6fTaWITIq1DbY0IZSSYjKb9M8GasbvKliibQ0XJPnTHVApazX2gYCLDrxU/1HCwicIcN5/PCnudV2ukcZ4JvVcVMb0prFS1tLSEYrGIYrEYSi9SEKsStqFP+t61b32vlqWzIQz6nYgtOHS+tOxgTEnqmGgM12o1L6/ncHxBLCws4MaNGxiNRmg0GqhWq1haWsLm5iam07MKRCpjFfyftd5Wyu+YF1uPxxbRSmTwR+UuvSDctJQeA45T5bv1iFDmUq7rhp79fh8Awn5CtlyrstvaPgkXsvgq6wCEPWWm02nwzqruVIad1/Hd0AOrC3SdJ3uPylhrKFhSSOeSeqhQKAQdoeOkYaG5eux3nsFnvyMxIsw+V4xUUv1GUtF6p+fNX7/fR7/fR71eDxUmHZcLbjhcQvyLf/EvsLW1hW9961v4/PPPUavV8NZbb6FUKiVc0KlUKhG3qbAMvgointPYVl6jSoRQpkf7UvdiJpMJQt1WPrroH59sESsp2ba50zBZIyqkWGylPhufmQoHSLLtmrQ3D1YYWqGsSkrHozkR1sCjcaAsWsxYowt6ZWUlbOKk8xljw6ywV4YtxipyfqzS0Hdnx6bXqaGmu7rGFh4cW7VaRaVSwcnJybmNnhwOx4vRbrfx+7//+/jggw/wzjvv4N69ezg9PcXq6ipWVlZCeA29DrqHgkJr5ls2XmUTcJ7cAM6H0vB/XkNVtXoRw0tVFquBE/OEsG+tJsR2uQg9PT0NC33d68CSM6oTbZUnu3mohpfqhp7zxqc6VIkdqx+sJ8Z63/V5gSSZQ92lRs7i4iJWVlZQLBZDnov+sC2rI/TZbd+ah6Lzo9D51e+G3kM9qHPOtnU+rdHSarWCfhgMBufepeOrhxsOlxCVSgVLS0vI5/NhE5RqtRoSo9S1y39KyypY5say4LzGLgT1J+bNsB4IIF7BQ/uwblD9HVuIzmazIHBoiPA5tWqEVYT2+S0ros/L89atq89umSBVjKp0rRCNPU9sDuy7sJ+ptFjS1s6nZaNiSj2WoM5reZ01JOx1MVd9DFZh2efiO2y32+h0OsFj4oySw/HymE6n2Nvbw82bN5HNZjEcDtFut1Gr1VAulwEkZYPKTyszY+y+9YwqYgtESzrwt8o8LegRY8C1bdUtdsGon9WY0Dh6zUuw98a88fPmBUhW47M6QsdsvQdWDtvPOlcXMf0xcMzMeWD5b47RlhO342UbsRBhQtcX1svAtnh8Hrn0sot9Xjcej9HtdtFsNkOpdC+ccfnghsMlRTqdDqFAw+EQjx49QqFQwPLyMsbjMbLZbGCtyfRqJSFC/+moQIAzll/LyGnfGg5lWRJNuuK19DhkMpkQfqJCSRegwHmmg2PgMQ0h4lbzDN2h8mE7+oyqjHQvBWV3dMHP8VsFaF3XygzlcrlEojfbiSk462nQOVAlrYKZx3O5HAqFAsrl8jmlYJVkzDiYTqehLrY9ZxPnyA6pwcExc2waepBKnYUnqZGlUKXKBUy/38fR0RHq9ToAhNA3h8PxxcBqdgDQaDTw6NEjXL9+PTDP+XwewFlFId5jCRaVE1Ye2IpMxItkAGWFlbPA2d4LWtDCemq1Pyu7dLHK64bDIVqtVtAx2Ww2cV9sAzZ9Rh7XBbZ6uFUuq2dhHgHGMFPOKVn/mKHAz2qQcA74PhQcO0PBstksyuVyCAfinKr8nsfWs53xeHzuvHrWVX+zLVuKlnpCvzNqwLBN+yz2vZIkrVQqYXwv2i/I8dXADYdLiqOjI/ybf/Nv8I1vfANvv/02njx5go2NDeTzeVy9ejUIeApoyzAwvEdjznnO1nq2ycHqUuViUQUYBYAVCqyewcWgVrF40Y6PMc+DuofZNwUyx6V9U/jajXO0/dlsFioqkc1XxRBjnahA1DBQbwWfi8rBGkxqeKnhoAttZWx0nkulEorFYnhu4CzRjH9b746GDelGQvMYsdizWsaIbTEemN8JvgddNDDXhePjs89mM/T7/eCCZvyqGw0Ox8+Gzz77DHt7e/jWt76FTqeDnZ0dVCoVTKdTrKysYDweh/9RZW8pa1iVR8OEKMdUJsXCXHThSFlgy2wDSXKEMpeGjBJTNnRIWXzgfJEHEms8d3p6Gsg0lddqZKhHxXpH+cOFNPUZ52KeF8Auiq2XxRJn9FarbuDfKlPZl74D3kt5ms1mUSgUQhir9SZYT4O+D8656gr77mJ6IEYQaXsMiyNpZ+dAw6nUIwY8JzYrlQqOj49RrVbR7XYT3wvH5YEHF19SDIdD7O7uIpfLYW1tDbPZDN1uF41GIywIyRTwZzQahR9lgoBkqU4besK/VUBad65d2OsPcLb41ZAlAFFhbe+3bemYFhcXkcvlEsLRGgRWwMXcwTynwi8WyqSeBdueZWWUFbILYOtt0Ptjc66eD15TKBRCpYzYM1sBzj7UC6XfA/ss9icWMmTPx8KL7JisguW9/X4ftVoNnU4Hg8HAjQaH4+dAq9XCwcEB1tbWUCqVMJ1OQ5Wl6XQajAUlM1gyWxfu6hGdpyP0c2wRP09HAMlwHQ1Zsh5WXWC+SD9ov8xT494GKit1HHrvi0IjOQ77rPosVo7Oa091yrz9Kubpl5jBpsYJybVisZjQi1YWx0KkVD9Yoi2mH2Kf9TlUPyhhOE9nWY8Xf08mE9RqNbTbbfR6Pd+74RLDPQ6XHFevXsXNmzdxcHCAbreLp0+fYnNzMyzMNWym0+kAQIJJp2DVBapd2Km7ln/bpNWYEFG2GTjbITSfzye8DsBzF7UaFEQsMZd9sE3G7fJ6Zbv4TDY+V70qVrjxnAo73RMhxt6owaLjZGULrc4BJGNu+czKgLF/rSZFFnA2m4UqKdyLgp6NmHfICmjgrCY6PU7q7VBlop4InXf9O+bViLFwlpFUj9NwOES1WsXDhw+Dt8HhcPx8SKVSuH79OgqFAnq9Hg4ODkKiNHAW8sqFYrvdTmySSVmnTL39v9bwVJI5usgHkuE2qisse81+KHdYYYlyjUw1+6K8UaiHWT3dhMpeK7vUMFA9YD0A9PJq//Qw894XGSOcQ8p36jkWN9F2rVFA3cp2teQsQ3cymQxWVlawubkZwoQZvsSxqtdFx6XzpAVSqB9i3iJLwOnvmGGmY7Fzou+B8zAajdDpdPDw4UOcnJyg2+3CcXnhhsMlx/e//31sbm7igw8+wPHxcWCUisViKMmm7DLrZTM/wjLTeswKV2sE8J9cqyzYRbD2y/PqOaAQ58ZwhAp+ChBd5Cp7ovewDx2rurztwlf74TVWyFF5caFNQ8sme1tBubi4iEKhkFCCZNPsmF/kxbGGQCaTQalUQqFQCErBtmcFPH9zHm3FLJ1fG4OqiwUbG6tKngqN712fS+dTE8d57e7uLg4ODlCv19FqtTAcDud/6R0Ox0thPB7jj//4j3H9+nXcuHEDu7u7CR2RTqeDh4FygR7cXC6XWKQTygrPk7kqozVM1rLJzJ+g7Ih5J+g9T6VSCQNASaCXKUbBPq1uexn9YD9bual6jPNh9xfSMVH20lPOsY/H40Tunc5bjJiybD2vYRgrC6hYw8V6sPlcGsKqsh5Ikj1WH+g6wu59oe3z3Vqdpe9U3wX1Q6VSQaVSQa1WQ7PZDHmNjssJNxwuOZ49e4ZGo4Hbt29jOBxiPB6j1WoFwaWsLnAWR6peBsK6YO2iWmGZehVk/G0FhLoildnWxaRtW+NPLZOh/RHaprZjlULsObRtZT54nMJUhaS9n2Og8lhaWooKbsvE65ypQWQ/AwiVMuzeFbZ/vf9FBhOPqUKwz2+ZQ02iVCHPueE7jTF62j/34jg5OUG1WkW73fYwJYfjF4TpdIp79+5hPB7j6tWrGAwG6Pf7aLVagd3m4oz/vySXYp5VLvD1/9zKJyKmI2KyTWH1gxIYmpjN4zEdZtu1MlB1m95nj8WeSfUDP2shDi6a1aCyRowaV/TuaK6hHfdF+sGGpKZSKeTz+WCU2PcRM854fl5+xzydofqQ80DjTXUx8NzwoBfHvifOq/ZPHTIajVCv13F8fIxOp4N+v//CnEjHVw83HF4BNJtN/Lt/9+/wzjvvYHNzEw8ePMBbb72F69evhzrHZKlZiUcXhMpMx0qzqReBv9UYscJMhasKLrIvFDaafMVN11Kp57H7vIbtqOdB24sJUyuEYnsqqDt5nsdAQ4R08yAVuhojTCVAbwSQ3BXTLv51Ic15tonpnENVfLlcLuwera5nnrdC27KCNsZUXc5UZvpeVIHr94bPMxqNAutWKBTC2LRv9qkCP5VKodvt4vj4GA8fPsTR0RGOj48v/L47HI4vhsePH+Pp06f4xje+gUwmg3v37oUF5nA4DGQSa/6zCo+SPSpfiFh4I5DMS4gtbq2O4GcSEjRmKK/I5g+HwyD/rC6gvNGCFCqrVY+p7NUiEWxL5bGOVxfPlGca1pTP58/pI93MjuFfnDPVA6of2KYupLXSYex9qGG0srKCfD6f0HF63m5eqrqex5iozGfgnNpqjRyDEkg0PGkUMYRqaWkpEW6m3wd95xzPZDLB4eEhPv/8c+zu7oZqSo7LDTccXhHMZjOUy2Wsra2h0+mg2+2i1+slmG9WlQDOmHnL/r+ofV2E6wIyJoR4jlAmhkIxk8mEkBS2aRe1bIcCU0Of2Kdep8JL4yRVaLJ/bYOCW0N4GG+rAhVIVgzR+dOKSKqsVHBTiNqQMFU+9p2ooZZOp8+FmnH+OPeqGHVudF74LPo+VRnqrqK8Xw09KgFVIlagq7Jle2SmJpMJOp0OKpUK9vf3cXBwgHa7/cLvoMPh+NkxnU6xtraGbDaLbreLbrcbZBXzALLZbIKMsCRLDFYGWRmu98a8D+r1IGy1PpW9ZK4VNicMwDnjQuWj6odYjL/dSFQZd5XFagTooluNEJ3HmDcYQKgmNZs9r+xn58fqiBipp1EFTAZXAok6zoYD2Xdo8wv4vHwG5u3xXegin/qDocckKWN92feqXpfxeIxer4dWq4W9vT3s7+/j+PjYjYZXBG44vEJg/Px4PMZwOMRgMAgMMI0Gy2arO1VduFbgKiNgmaTYP7M1RGKMv92IZ17Ikho5PBYTPjp2+8P2VBFeFAZFI8sKcL1W27Fzy3t5jTWM9NpYCJdVrOyPoQR2Duw8zAszUkWo71N3s55nCFDAs1QjDRhrqMTGwj4mkwkGgwGazSZOTk5weHiIer3u9bgdjl8yuJgcj8cYDAZhI9FMJhOIAKsfrGyLhX3GdISVcYp5jDMX5NQPXEzaRbsy9NQRNvxG71OP7TwdwXstiaPjUzlL8ov3WDnLv1W+x/Svel10UW91QSyES5+Xc0KiMJYzqLD6wc4Nr9EyvQAS1Rpf9P5tRMBF3xsSgtPpNGxaWK/XcXBwgGq1ilarBcerATccXiF8/PHHuH//Pr71rW+FKkobGxsol8sol8uJxbwueLmAJywzbRecBN2KaqDYKhTsS0OWVHgOh8PwQ8aJCWJayYhCjsLQJv5aL4cVqDxmhS+PU1GwdN/S0hLK5XKCZeczxZSEGgA6v+xbFakaTKqk1LAjq6NzSCYp5sZWZavKRt8X2xgOh+EZuIDodDrB8GQ4m3WBZ7PZkKjYaDTQ6XTQbDZRKpXCO9YEa96nbu5+vx8UQbfbxYMHD3Dv3r2E0eFwOH7xmM1m+O///b9jc3MTX//61zEYDJDNZrG5uYmVlZVAAhCUUxraAiTZaSUYLHtPYmI0GiGdTodkbA0rUiZdF8ILCwshB4P6QUMnKQtjxgTHqkSYjonPoOOIeQjUkOB99MwUi0UsLy8jl8thOByeY9W1DdUZljiLkTlWP/BeeoPotbX6WMOAaAAqEWfL3Nr54X0qw/l+m81mOFYoFILBqfPK58hms6HARafTCfqU+pwVldRTQVKMm/Vtb2+j1+vh5OQE//f//l/XD68Y3HB4hRCz2pVdV+GlXoZYyIsVthrTaBkVhq7M8wTM82ZQeOr91mCJsTjKpMxj3ect7PVaFexkUaiwrMteGSE1RNSlaxfwdgGtyX06fvsOYt4C/k3FaCsf0ehQg0IXATHGjGMaj8fo9/vBANCN9KiM7U+xWMRgMMBgMEiwS/pd1PdMD9jR0RE6nU6IV6aB5HA4fvnQktKsFqfhNrHwJCVELEtP6OJddxqmDNEyoQq9jrKLxzWkVEMnrQxWz4KVe7xmHux9SrbomChnKX81FEhzAZRgYlt23NQrqpN04T1vbmLyNaYfeD3ngaFdnE/eD5yvemQ94jzW7/dD1IImzltDifeRSGT4qeoR9qeV91iS++joCN1u99yeU45XC244vKJgOIk1GGJxkvpPHxNgajTY/Qd4H70FymioYiG7YxeUVAp6/kXGi1Vi8/Aiw8EKO+03nU4Hw0EFsB0f+7C7YCs7pwZTLMbTCnk7vnlKQV3YFOya82A9LECyJK1VTsrkMQxKlW/M2OSx2KJf+0mlnieWDwYDNBoN7OzsBKUzGAy8OobD8RVgNpuFogaxOPyY3qActYt3tkc5qASJyj+GIsZkOD+r3FBm3uooe13MAND2dZwcgx6zi3BCPROaQ5DP5xN7IbFPu/BWvRkzeF6GLFIjzj6TXmuJQYJhRuoFpwHD9q1+UGKQ+p3hT1qUQ3WrGkTFYjHkMKpBQaiOX1paCnuI7O/vh/w5epocrx7ccHjFMBgM8Od//uf42te+hg8++CAct4w7cLZwpwAhM8RwFGVaVHACZ4wB257Hxqvw17bJ3GSzWcxmM/T7/SCsbKwrj2tIVYz5sqy3CmMy6frc2g7ZN/ZjXb0qfFlLfDabnaseZGNZda6tguOY7Fh0/IR6ExQqsPmudNGvoQQcH0vEnp6eYnl5GcViEevr66H/wWAQlKKW7VUjhwqkXC6H3cpHoxGKxWLol0qq0Wjg448/RqVSQT6fx9bWFnK5HP7Lf/kv6Pf7cDgcXx6Oj4/xZ3/2Z/joo4+wtrYGYH5ZT8odyqjpdIrBYJAgkSgfVdZYAkoNCOoFftaQWcpbeie4SNf9iCzRQ6inl2PVsVj9ACTlo+aNxRKLR6NRggyxxBNwpmfUw67n1SizOQicA12453K5ubKf9+mz6zPzWZTMU+OH1yl5ozJ/PB4jn88jn8+jWCwmdCXDjXitzi11BMO6Op1OMAJUr1KntNtt7Ozs4LPPPkMul8PKygpu3LiBv/qrv8Le3t65Z3Zcfrjh8AqCTNJsNgu5A8pwKEtgGQ9dvPNHFQQFEAWmLnZ5TN2khHoptHqG9XgASDBa1v1qF9ccK9uyBhIVhmXjeZ9lrHRMvJ/KRb00hBXq1oujCiRmOOh8qsLT+YgpPB2nKgbrEuZ1Oh/2nBqOfN98Hn3n1oOkbBgXDzQ4+dzD4RA7Ozuo1+sYDoe4efMmarUaGo0G+v2+u6Edji8ZDGPl/+xgMEC5XAZwnsGOMf2EJZVi4UN2sauLeNuf9VLoZ6untD+7aI31GSsd/qI+tC973Oosazjoc9nn0Xm1nls1rtifjmuep12v0d/WcFAy72X1A88zHIuGA+d0nieEz8Lys7qBKolDjml/fz+EsG5sbAAAPvvsMzQaDfdIv6Jww+EVBReAvV4vsAUKDXdRzwLxIibJKgYVqDyvC2or5F+0yNU+lZWx7I8dpxomeo7HrKBXBaYGSUwpcDwAEkmC2h/Zdc6DzgHbie3doAYW58u6dq1i0DkjGxhT1PbaGGOlY+b4UqnUuTAGPp8qO/6QKWQ1L45pYWEBnU4HDx48QLPZxOLiIq5du4Y//dM/xSeffHJuLA6H48sD/2e73W7wPChUdmgoC6Gy3ZZS5b0q+1X2UY6QSNLjvJa/5xkOdq8flXPW80H5rfKe59WTynsp65gzaOW7JZY4P/Rq65js2HWeLKGlxJI++2w2O7fng+riWGgpYasXWsPNeqgV88g0GgFaplWv1etVD9IQUI/O48ePUa/XwyaFJycn+P73vw/Hqws3HF5RPH36FMfHx9jc3ESpVAob51j2A0CCNdLkLvU+AOeTuZStVuYkJkxUOKkCoWu3WCyi3W6HhKhMJhPcmhyDKgRVWIPBIAhDdRMryzSdTs8xHSrIR6NRlN2gomFlEOu9iTFCF8WkslpFzDCwMbK6cKf7V6+xitDmS1hDwhoCHJ9lxBiCxRCuVCqV2BRKjT6Gb/G5JpMJ+v1+2A16Z2cHd+7cwdLSEv7Vv/pX6Ha7L/MVdjgcv0T86Ec/Cjqi3+9jaWkpUalIoV5gqz90MWtlnpI/KpNIDNkFMK/TMSwuLoYKPqyuxHbs9dZIoTwaDAZB7jE81splyrmYjmByNz3qCsq9mHfehiSpDNa50jlQQ4L32LHofGs/1Duai8iEdPWaqxFg54FtqTFo9QONKRoQABLhW1opiR6LYrEYjFVW8qvX69je3kaxWMTXv/51fO9730O9Xj//ZXW8UnDD4RUFE9G4EB+Px8jlcuG8FVZ6zAoTew//1oXjvOtiUOHG+7mDqfUI2Ha1/VhoDRlwFf5WKVnlxja0+oQujjWUR8sBUphru7ZfPR+Dehb0mW176qmx8x/rZ9782/bnwXp4yDLZsDJew/HQYBsOh6hWq6jX68jlcmi32zg9PUW9Xn/hd8PhcHw5GAwG6PV6QT/M0xGxRa4u0q0siS1ElVRRHWOZcKtTdPFLRt96FGKwngkubrno5dhshaOYPtQwTF14a3gSvRMM47GLffWwxEJPXySLY+dj+iFG7MX03UXzpgbCPP2lHgs1aDgW1a12T6DZ7HkIa7PZRKVSCR7ro6MjVKtV9Hq9F86F4/LDDYdXHCyZ2e/3sby8nIijtDkEQDJUCEiWpFNvAnDGJsVqfFsXpyZSaxIc8FzwlkqlkHD1Moy0skmMn9SxMbZSDQYdoyoeGgSTySSR7EV2icqCikENE86hrUZkGSMdN+fOntd4Wg2BsqX1dN7s8ylTZ5kl67WZpxjUY6ShVtwN1LZJZcl+T09P0ev1sL+/j8FggBs3buDTTz9FpVK58L06HI4vD8xx6Pf7ITFVvbo2r4vEgDUcuHC2C1KGLFrWXa+jHFUvKg0F9pHL5ZDNZkNZZy35GoP1OLD6HWW1llK1ho9dJKvHIZ/PBxnIRTb3PmCoJpl2DS2iLLVedNtnjNCzc2bJKSWybKdpFzcAADaJSURBVOiwnXedG71GyTo1GG0ImY7b6nItekJw/jXUbTabBY/07u4ubty4gUqlgo8//nju+3S8WnDD4RXGeDzG97//ffzqr/4qPvroo1AhIZvNhioVVA7AWVK1hitNp1P0er0gjCg4NeFKBdm8UBjNI6AgYtIUr+HimyXYKJCU9VdlQUFMz4WGXKnb1N5jjSXgjNHSY7owp5uV7RNqLNhQqJgngYixeLEEQxvzy/mIeSD0Pu2D7Wscr2XEdJM2Psu80AQN7+J+DDpnnU4HOzs7mEwmyOVy2NzcDJWoHA7H5UGtVsN/+k//Cd/5zneQSj2vv5/NZrG4uBgW25T3JE5sRSWGAgHPZU4ulwsGgw3lVD0BJPMRNOSSn1OpVMJIyGazCcNFQ15V9umCWnerp5zVfXaAZGiVsum6yLfhp+pB0FDN2WyWWERrDhpDXmOEnULniNfoc1v9S1hZHwtNtjpbj+umdDzGcat+VC+9vZ4kIdcOXGuwz9lshr29PbTbbSwuLmJ9fT18fxyvB9xweIUxm81Qq9VQrVbRaDSwtrYWFtvA2T8/YV3AunAHklV8tEwngKgwVNhjdpEOIJSTmxcGxPvUfZ5KPY+9p/vTMjYxF2vsuBWmlsnXXbG5yFYjIuZpUeFv5yHWR+z8vDbm5THY57HzHfvRa2LjiY2Zc8lx0AhlsmW73Q7KtFarhdA5h8NxeTAej3FycoJ6vY5WqxV0hF3Yk81WHUH5Z/OdtDiCMt4voyNU/8SuoyfZbkRqSRYuUCmzl5aWwgLWkjOqi+bJRkuK2XPUWbo7MnUoj7NNJX94v52HF82R/YmFPsXCZWN9cb7UcLL96z30nsR0c+x6zZWg3uSeDbPZDOVyGa1Wy/PeXjO44fAaoNVq4dmzZ1hfXw9CjBucMQSF7BEFkW5ao7WkqRBYY1sNB+B8lSPgfLk3vU5jTLnQ7Pf7QUnpolnZEwrkhYUFFIvFwJABSLSrY2M/lonXDYvsvgUEnzedTocSt6PRCL1eDwsLC2EnUc4p+3qRELZjs0mEVFLqtle3N+fRKj/7HviMGmdrDT4gWdOcxmXMmCLy+Twmkwk6nQ56vR7a7TZarRYajQZarRbef/99DAYD/Of//J/hcDguL46OjpDP57GxsRFkEhOlScqo/NGNzVKp554K6gjVD5pPoDJ3XpiOXaTSE83j+Xw+kBQqZ/U376U+434zzL3SCkv6m22o10E9GwASHgS7QOZza4U5/qZ+UEafnoOXMSJ0nHZOteqTem8sbNs6jnkhThqyZMNk1csTM15msxlyuRz6/T4GgwFqtRp6vR46nQ4ajQbW19dx7do1/Pt//+/dcHjN4IbDa4BKpYLBYIB3330XS0tLIWzExkXqIpP5BktLS8jn80EocPFsS5wqCxUzGqgUlK0AkhsDEYVC4RyTBZyVilPjg2OiQaM5BFQwXNDHwnvUQ7G4uJgQ8DakR+eAc9NutwODwg2EqOysgqGAty5kuuLV5a73aoUMnXN6WlTwK0Ooz8oygWog0rVOL5LG5PLdxdz2vIb3pdPPq1llMhlUq1XMZjNcuXIFn332GVqt1hf8tjocji8bjx8/RrfbxQcffHCOPKFHEUjmNVG2cqMvIOmV1lwAIha2OY8FJ+yimBV6NFlZZXQsvJLyTSsSpdPpUOxC5a3KOR0z5Vw2m01s/GnDSSm/WY2v1+uFxbMSMpS3mnCt+Qp8FkYGaHiUzbNTzzfnXA0KjlXfo/YT21xVw421pKrqaptcrvezD1bdA55XxRqNRlhZWcHx8THu37/vYUqvIdxweA0wGAwwGo2wv78fjnFL+FwulxCAyuaol0EXkLH4fCL29zyXqQo53UmSW9BrmBTbi8XdK+M0T/hbWKWgz6bPZ9sDcG4ubDUNRYxR0vZiz2LHoCVg7dj097znjc2/9qV923dh2biYUah5JvTEjEYjHB8fo91uR+ff4XBcHrRaLSwsLGBvbw+np6dYWVnBZDIJhIDKhJiO0AWxyg2Vbbqg5GfeQ6iMUabdesTZX0wXqYfAhiHpGLUvXhfTG1bmxUKV7G8N4Uyn0wlvOMcN4Bxrr23GdKxeq30oWTRvbHbe9bljxg/HSc8IoTl+L0q+1rlXo476odls4uDgAI7XD244vCaYTqf4kz/5E9y4cQN/82/+TVy/fh1ra2t4++23E0JI2SQVFplMJrDWZEBsnWcgKZTJStvFtF0EW/e15hOQTeHiXPcwYFsURBwzx60eldjCWZ9ZFY32SYNKPSyqBDS/gsyJunlpdPFvZX5UIfAdqFfCKlGeJzRZ2z6bZYa0P31HsVK6llGynhmOi5VExuMx2u02Dg8P0el0UKlUcPfu3fNfQofDcWlRr9fxr//1v8Zf/+t/HW+//TZu3LiB69ev4+rVq4kFrm7+pXKHIa2Ub5pDF1t8A/FNQHmNhlTymCW0lJFXPWHJEBIas9kssfmYhoEq0857eb8lrHTTOuDME6/kG9vKZrOh8Ag3yOSzafU8vd9GAfBavc56z9VbQdj5UCgxZ9+lNWS0H9VbHL/OhRp6+txHR0doNBpot9v40Y9+lFg/OF4vuOHwmqFer+PHP/4x9vf3sbq6imq1irW1NRQKhRCPOJlMUCgUwkKVwkfZDRWO8wS/Ch5duM7zWKigtq5qKg2ORcG4VW5gxDGruzTmOVChSSGmBoru68CFvxo1HBvvA54bPYz3jbnptV8KV3VRq8GgrI0du1V2sR/Na9B+7bhUgcW8E3qMf2vVpdFohH6/j06ng+XlZY9XdTheUcxmM2xvb6Ner2N/fx9bW1vY3NwMldEWFxfR7XaRTqeDocCQH4Y+KplBTyQQz++KsdQ8x+P6W9vQkEqtXKSx+LxuOBwilXqeR5fP5xMLdMvgUz7ybz4PjRMSJhoeSoMmm80m7qe+05wLhsPGKgVSX/G5qJdobMTyL2I62BJA9hjnSefaemQsgWT1s9XROg4aVjTqhsMhOp0OFhcXsba2du674Hi94IbDa4Z+v4+9vT10u100Gg2kUikMBgOUSiWUy+XAynAjIBoL6qZWVt4yNMCZW9JWklD2hLAL1BjswtkKQN25cmlpKVEWb14bPKZGEHDmTdH4TmV8bDv8TXcu8yT03Lx+CcsiqeHA83bOrKK1rJg+h3p3rMGmyjE2//q+9H5NGqS3hbuzOhyOVxf1eh3NZhO9Xg/D4RD9fh+np6cJcollvfn/ronSKhtUd1gZRmJK5ZnKIZVVxEU6QtlubZd79DAfY96iOybrNBE85tWIjcXKW/bFwiS6n4Ml2ayMtvpB8+PUqz9PR/Cz9U6TgFNjRNvSd2Hlun038wwXEkvUD443A244vKZoNBqYTCZYWVnB4eEhFhYWsL6+jitXrqBcLqNcLifiW3WDNSuEVGDYWtzWHamGiGW5rcBUoaeKJpvNBmU2mUyCIKYiI7NEz4H2bRXFZDJBt9tFr9cLTDpwtvGajkFDhdRlzWekMtU9JFSJEJqgZpUH22dyeir1POdDa3hbz4KGjikTpkwaFTSQ3AtC514NmliImbJ09PJMJhPs7u6i0+lgPB7jL//yL9HpdF76e+hwOC4fptMpTk5Ogizb3d1FqVTC8vIyNjY2sLKyglwuh+FwGEKGgLNFqN3zxso5XdxbDzKvtXszxEJzNMyU91L2s6pRKpVCsVgMVfs0R4JEmfZrwR22+/0+RqNRIm+NY+DYKGdVxtPIWFxcRKlUCl5xqyMIq7MI6iQtccrS6GT5VW+qrqCsHo1GCQONepi62FZOst4H1aHzjInT09MQOjyZTHB8fIxqtYrxeIwHDx7g6dOn57whjtcLbji8xhgOh9jf30epVMLS0hKq1SqGwyG63S5WVlYCg09Bbzf+UcEzb+EfY4vUS6FJYoQubC3zTiFJoZROp4OXgX1YV7Oy8upqBRD2HRgMBsFTsbS0dE6wq8GkikaTuFlxI1amLsYG6fxpohuh8ao6Bv6tIVUacxszxJRpUqVr21eGTPvjfWpADodDtNttDIdDZLNZ3Lp1K+GpcTgcrzaazSYmkwmWl5cTm3mNx2Pk83mUy2UAySp2GqOvC2wlI1R/zNMRlm2f5y0FkCCjWN1O5ZtWitK8LR2DDYvi736/j16vF3asZlhSjHixOk894izbrbrFPpvtX8NYOU5bYcnqKB0LcxattyH2LnRu+S7m6QfeZ69lf9Q5jUYDvV4P0+kUN2/exN7enuuHNwBuOLzGGI/HOD4+DsJnPB4Ht+KNGzeQy+WQy+USu3XqJmtat9suVC07rgLICtdYeIuyTLzWJugpS29drcqQqGLQflnXu9frYTQahUQ5W39cx2iFnsbJqqHFe+3eDFYpWaWgbE+M9bfzqDkZdp7Zj3Xdq7LWz/Y92LECSBgO/X4/LCwKhQLK5XK0frjD4Xg10e120e/3USgUMJ1Ow+I5lUphdXUVg8EAqVQqMPiz2dlGnLqwtSBLb+WSymorywiVnWqA2Osop4CzfWnYnhom7Etlu8rNfr8fcv94rZYvtYaDHSt1leZAqF6xct7meqhHgOdsCKqdJ2X/NR8tNlfWSxEz0OZ5GayOoPebOrrRaGA4HAJAiGJwvP5ww+ENwNHREQqFAj788EO0223U63U8ffo0uBtLpVJwiWo1CFtLWoVmLIGLAkpdvPzMBXtMAehCl4JSN1uLsTW2nZigbDabYdfK1dVVlMtlbGxsBHZKGaXY2FQ5MkzJKihtQ4Ws1u5WI2fe9Zb5Pz09xWAwSMQWa3hVzP3OdrQyk51n/dsaXBp2dnR0hJOTE9RqNayuruLzzz/H//pf/ysoCYfD8XpgOp1ie3sb165dw9bWFqrVKo6Pj4MHuFwuo1AoBM+vJvJqnluM8aYs04UrkKygpMnHaohY40LbXlxcDBXvlPjQ++glYRtKetAAarfbaLfbmE6nIVG8WCwGrwZ/1DPC+4lU6nn4VC6XO7dwtgSRPhPPc45iusgSYupFIAnIUDAaPGoo6D3Wy2MR08s6BhpW6XQatVoNzWYT+/v7wSv1R3/0R64f3hC44fAGYDabYTQaoVKpBMFUq9VQKBRQLBaxvLycUATWRWvbsgte4DxTTracxggFpC6m9bP1VFiWhePWWE01VAhlerSMqwr2mCdF+9GKTZrzELs2JoBtErRea5WXBefBhibxeiqYef1adk/nhH9b5cV5pGIYj8c4OTlBt9vFZDLBvXv3cHh46MlvDsdriul0GkotU3bWajW0Wi0sLi5ieXk5yLXYBnLAmewCcE5uWQNAizyovNLypbYqUMxIUCjppe3HSCbKSpIz6XQ6kcNmN/PkffqMbFs92bYvazRo/zbMVr0MhH1e9TTEwqbmJavrvS/yYFj9oISg6qRGo4FGo4HZbIadnZ0QsvSi9+N4feCGwxuC8XiM3d1drK+vo1QqoV6vo1gsolwu4/bt26EMqa0GQViBr+ctgx5b9JJRsu3qYte6Ra1S0j0TNJlYFYsqBe5BMJvNQilXGjKaT6GwYT8xz4cu/m0iIMdMZaLJg+r+jilYVUx6nxpV0+k0jMkaJjqPL6M4OA7+0LvBmtwc38cff+xGg8PxmqPdbqPT6eDmzZuBza7X68jn8+fkJmFlDHA+Np6/1UutIaDAGTOvC2jrvVC5yDatLmE7Ki+1PV1Uk1CjbuJzZjKZxM7YsWfUioNLS0sJ/WZDlSwppuFJWvEvlqwcm0ey/6pzVAepR4jzHQtBmpf8HCOVOPfUEdVqFY1GA4uLi3jy5Al2d3fPzZHj9YUbDm8YarVaYAqYaLa1tYWVlRWUy+UoO8RNXiiAKFR1saqxpECyxB2AUDmI7SrjYjdL0/PA+VAeQkv9AcmKH6PRKCiDVCoVXO3K/FtPhVVUvEb3fLDGlFWM/EyDZTqdBoNHmTDtXyuU6Dyybw0hUiXE8zr/bE/nNzbOWKzudDpFrVZDtVrFzs5OOKfK2uFwvL6YzWZht99UKoX19XUsLCxgbW0Nq6uryGazievT6XSQ86PRKMgaDfVRua4ylDJyPB4HGamFMtTba8ujWq+uhkDxtxI4vIfHWTUuk8lgZWUlVO2zFZViOkLPU4fqfhYKlb1KnOlinMaY5jloqKvqB5vbl06nz82NFr6gfrVzpd50fTfWULLt9vt9HB4eYnt7G81mE5lMxvf1eQPhhsMbBs1VKBaL2NzcDAKbApywrmEVpjFG296njAiF14uS3WKsUGyhTvZeBaN1r1L4MhbWVsnQsbLt2OeYyzpmxMTujwljnRu9z/6tbcTm1/YVc+PrfNn3powcFX+n00G9Xke1Wg0VVpgs7XA43gwowXP16lWsrq4ilUqFEtL0OFCuW2+ryhrCyiwrB0nMUD9obhz7ioU/xfSD3hfLzwPOPL58HiXDrMy1/bIvtj9PTs+T7drevMW6ze2zbejzxmD1No/N8+bb98Yx6A7hvV4PrVYLx8fH6HQ66HQ6wUPteLPghsMbjGvXruFXfuVXwsJ7MBgkEqR1cUuDQhfR82IhtWQfMR6PE25bFe7sIxajb92pygipIFRXsDL9luG3xgX71mewAp/sl92fIaYY1ANjd5e2SeTWiFJBzt8x1o5QN7wmJuoOpMpcWQWitb8HgwGq1SoODw9xdHSEXq8XQhccDsebiffeew+bm5th8QiclT4FksnOGkIZk41KVtgf5hlQZqv3QVl+62G2OoK6Su/XctZsj38zzEgJIiVirI6Y59lgDp/KeFuZiX3r81Cv6n0csz4j/7ZjmBduZL08nGcNBbPElvalZcCpI+iN3t3dRbPZRKfTQbVavfA75Hj94IbDG4z//b//Nx4/fozvfve7YVOdVqsVBBprUsfCeoAz4aIJu7pYBc7Ke3IfBVUAbFMrSxCagMfyf+PxOJHYHFvoa3UODefhOVU6xIuY+nmLdhW8VimwfZ0DXqsKZh67xfv1Ws7zcDiMehK4cV4sZ4Tt0rjg+6Bx12g00Gw28eDBA1SrVTSbTZycnLinweF4gzGbzfDHf/zH+PDDD/Fbv/VbIWS1Xq8Hlj6Xy52rhgQkw3F0AzjqEvUu6MZl6s2wMlgX8qqjeD/1kFbNYx8MA1K5yIU9jRZd+M/zmOgx6hAdnx7jNfYZeJ0NVVX9yOtjuQkq++lV51yPRqPE+NRA4Q/bmeeF4Uaj3Dyv3++j0Wjg0aNHqNVqOD4+Rq1W87y3NxhuOLzB6HQ6GI1GePDgAa5fv46rV68GIcSwJTI4dhENJF2csUWwHtN4TltlSa9XUOCx2o91tb7od8zLwOP62x7nWGNsTsx44r2cG+spscJf+38Zo0TZNzXYeB3n07J91qiiwcD3wGoi0+nzsrUswcjytXa3V4fD8eaBDPP9+/extbUV8gCoI9RDbUOLVBaqbIxdA5zpiJjsJVTOUvYBCN6Qi7zY/DuTySQ8toqYjoiRQ/M8KzFdqLCeDWtsaB8x/cA21MOs12rRECWs7H3WqNG8C3qhT09P0e12UavVcHJygnq9HtYNTiy9uXDD4Q3HaDTCv/yX/xLf/va38Zu/+ZvI5/MYDodoNpuB6c9ms1EBqQYAkKyWQUGtuQi6w+a8hbmy8cpMaQI129Zks5gwjC3GbbyrXse+R6NRSFiz7cXcxtqe9c6ocqPXQJktvS+maO21uiEckNz4yCo1Zd2sl4HCfzQaYXd3F5VKBXt7e4m64A6Hw7G9vY0//MM/xO/+7u/igw8+QKlUQqPRwGg0Qr/fT4TcKHThquGRNgSIi3gAgTGPyVyVvZSPLLqhclgXzapTCOolW3RCDQsta2rP04vOzUB14a86SfWNynpbuVBDtGJJ0Nq21T+8V4+rl4d6jPtL2HKtnCd6bdTLQB3BfZ92d3fRbrfR7/e/wLfH8TrCDQcHAODTTz/F0dERvvvd72JzcxNvvfUWTk5OMBwO0el0gktaBbJNtqXQs5uUATh3LRe+MYWjiobsUDqdDq7y2WwWYlNVsFrDgots5m7MY5pSqVRwlavyoddCN8OLeVXmeSKA83Ww7RgV2o7doVnd2doeDRNVCOqO1udiIht3hOa5wWCAwWCAfr/vLJLD4YjiT/7kT/D+++/jn/yTf4I7d+4AAI6PjzGZTNDtdpHL5c7pBc2H46Jb5Zhl7zUPTsN3CJXzwJmRsLS0FHZQHo1GgVCx4URAMjmZ7PpsNgthudawUT2huWTcYZv9x4yceV4WhdUPqjtj7fG5OK98VupejlGT2akfVIfr+9B8hk6ng16vh263i9PTU/R6vWAkeiK0A3DDwfH/wWSnzz//HAsLC3jvvfdQKBSQTqcDw6CLXstsK2sPJF2idnFtYyuJmHtX72WbZO6V7bHQ6zREJ7apkIUy9YQtXfeisVolpW5gazhY93RMUcS8HhT6tv1YArTGvw6HQ3S73WAsNBoN1Ov1sNmbw+FwxHBwcIB0Oo3PP/8c77//PpaXl1EsFoOX0uoHK8NUPlkDIKZDYrBEEX/rglnLj8bktI5RdYLN2Zs3Fj6Pls+OhTXFSCYr83U8lrjivOi4Y21bY43QYh7z3o3qxfF4jOFwiF6vF4yEer2OVquFdrsdiCaHww0HR8Dp6Sn+4A/+AN/61rfwO7/zO7h27RoWFhbQ7XYDQ63Ch9UorIKIVXogi8SYznmLfqsYNIk4k8lgOByGBTMT9KwS4t+DwSAwJOqSjVXbIBuzuLiIfD6fUCp8TrZjvQHW9cu2CVUK1jNjBb4u/LXMrDJMvJblUrVqhu7rwHHwOZvNZqiWdHp6ipOTE/yP//E/fpavisPheAOxt7eH3/u938N3v/td/Pqv/zpu3LgRSIharZbwjNqQISAZzqPQ0M+YMaGIGQ/AWbJzv98P8pMFI4DzuQPj8Ri9Xi/IYnoblIXXsB+GRjH0Rxf6SiypTtQxW687MU8/aFv2fuDMCx2b41QqFTwwSh5Rd1rv/3g8RrfbRbvdRr1eD3rjf/7P/+mV9Rzn4IaD4xweP36MP/qjP8Lf/tt/G9euXcPy8jIWFhaQy+XCYnU6nSKXywVhpDuLWjcr/57H/lgmRhl75kgACH1pmA6QzA9gm+PxOITe5HI5lEqlsHO0KicqMa06YfeyoEERM3ZstQ41dKzHhSVd6fJWtotzNy8kioqYCi6TySCfz2NpaSmM2XoigOcxw9xBmwlt6XQan376KY6Pj7/At8LhcDie47/+1/+K+/fv4x/8g38QZGsul0tUf9MwGQAJGUXEFtgKNSJ4XokiJVT4N3PzJpNJ0B/2fsbz9/v9sPnb8vJyyD+gXiJpRMKIewJpbh9JrFjJb/s55nWhfrA7R1ujhffG9BDv5zkSYPybYVhAMpGc4UnD4RCDwSDk9x0cHODhw4deOckRhRsOjnNoNBr40Y9+hI2NDXS7Xbzzzju4cuVKYPhtTWzrQo0ZDkDS7ar3xwwK3q9Cl2yVJghbpoXX8prZbIZcLodsNotsNhvu1xwGClct9arjVEYnZhTYZ9Lx69itccQxqCeGY7LhXep1oNLi89g4Yk0kZ2k9up3psTk8PEStVrvgm+BwOBzn8fTpU1SrVdy4cQO3bt3C+vo6rl69mtj9OMb0q2ch5nFWo0J1hEUsZEe9tkowxcgYZdqpG5ijQWKHbVEnMJdhnjGgOoLnrKFjw5rsMynxpu0TqgOsPtFz3Pg0prdU76jh0Ol00Gg0MB6PUa1Wsb+/Hx2nw+GGg2Muvve972Frawvf+c53cPv2bayurmJjYwPpdDqxoRthP9sQIsIKULL0XDyrq9cuxll9otfrBcFXKpXOjV1jXfP5PLLZbGCFmExGpaJudds/E+AUVriri5nPbY0PG8NqjSJd7HM+NMnZKj+64dke94rgOd7H3IZWq4Xvfe97qNfr4ZzD4XD8rGi32/i3//bf4qOPPsI3v/lNpFIprKysoFQqnTMUgPP5ampEWNgFs4Z+0gNg9Qvbz2azgTAhcWTLf1PmTiYTLC0tBW+0JmNTbi8tLSWeRz0L1EEKa6So7FdPiQ0X0vN8FtULGpqk+op9ci8fPoOGU6ne0QRv9t3pdPDjH/8YP/zhD7/Yl8DxRsINB8dczGYzNBoN/OAHP8B4PMbNmzcxm81QKBSQz+eRy+USlY5UGCliTIwyHzymglCVgWXSdXwxj4e6Z7UtCn26o7nYtu5z3qNeghjDo8rNntPxqUvauqd1Hujytm2pd4LPoedingYqxU6ng52dHfz0pz9Ft9t1g8HhcPzCMJ1O8fjx41BVqd/vY2VlBeVyGZlMBplMJlFcQ70IlkmPyUe9xnptrY7QxbfCLtYBBFZedYR6FxhWSg/wRZ6C2J5B6gWO6QfOnz6b7UM95Nxbif1o+KzVRfMMJdU1rDjYbrfxF3/xFzg4OHD94HgpuOHgeCF6vR4ePHiAjY2NIKyuX7+OYrGIYrGIdPqs6hKZcltOLhZ2owtiexyIV2d6mcQ5tqMhPXYcKnwJVQwxQ2ReQrRuxqa/tS17PnYtE9l0brRaRmxOVaEpa5VKpUIFpWq1ip2dHdy7d2/uO3Y4HI6fFZVKBa1WC3fu3AkhpMvLy8hmsygUCmHfA5WJLzIIYqQJYT0NMWaf99qKRAo1EhS8T/eH0Pvtb70nVhTEXmeJr9gcxOaCnmMaMuxr3k7Q2oZ6vNUbzbLcJycnuHv3rlfVc7w03HBwvBT+8i//Enfv3sW3v/1tDIdDTKdT3LlzB/1+H91uF/V6PcFmaOUgMjgq1JX1sMyRbqIDnCmL09PTICjVfWxLrGq5Vm2HoEJggrUaEZpvYFkdHT9Dh+hOVqEMJPdhUAWoykWrNg2Hw5C8vLS0hGw2O/ddqMLR+tt8hn6/j0ajgZOTE/y3//bf0Ov1Lnq9DofD8TNjMBjgP/yH/4Cvfe1r+PrXv45sNou3334b6+vrWFhYCNXcdCFuNwSNLawp36gXXmRkaKEKhqOyPyVlACS8CTESicYOC1JYLzLDR9UAURlPgop6wRbDUE8Bx2/JNc1B4F4ZrOpUKBSixJn1jPBZONepVCrs5XNwcIAf//jHePLkiRsNji8ENxwcLwXGQd69exej0Qjtdhtra2tYWVlBoVAIDDeTbxlXqcx8LKlsHpRZ0rZ4Tr0JVqHwPl1Mq9Ig1Fjgb96XTqdDMrjGtSrjZN3Quks2r9F+tH81LBiepMl82oeOzbJ2+pm1t09OTnB4eIj9/X3f1M3hcHwpmEwmODo6wmz2PC9gMBggnU7j6tWrKBQKITdNK/MByYpBMaZ8XviMGgrq0bAJxEoO2fa1PKnVTxybjkFLm9JYUcPBeshjHhCrQ3hef6sRoZUA7R4TStTpfOkxXjuZTNDr9dBsNtFsNnH//n1UKhU3GhxfGG44OF4ao9EIDx8+xHA4RKvVwvr6Or72ta9heXkZhUIhXMOwGyC5mZp15c5TCOp1AM4LYA3TYR9WKdCbYZPxYgt79kFhy70RaDzY3AsroDku3TE7FvaksC5yjs1WrLLhX9aYICaTCdrtNprNJnZ3d7G9vY2dnZ3o/DocDscvA9VqFfV6HYuLi6Ek60cffYSlpSUUCgUMh8NQGhpIys3p9Gy/HOB8jpiVt3rchnKq4aAhSXofd41WXaX98m89Rv2g+/DM81qr3gLOSm7bsC01GlSn8bzmW6jhwL742yZX69+np6cYDAY4OTlBpVLByckJ7t27N1cHOxwvghsOji+Mvb09nJycoNfr4dGjR3j//ffxzW9+M+z1cHR0lAi54SJfWSUr4IBkoph6K6gAtPyqGg5kZHgP3brtdhuZTAZra2vBezAajTAYDILbmJU0VAlo9SWtf60KRRUFDSU7ZqvULIulrutMJoNcLhc2rAOQSDq3LvKlpSVcuXIF7XYbjUYDn3zyCarVKhqNBp49exbqfzscDseXiel0irt37+L4+Bjb29uoVqu4desW3n333eDBbTQayGazwaCweVxAnFhST7XmgunO0Rq2RE8wy4gT/X4fnU4HrVYLa2trSKVSyGazgfjqdDqhH5Zg1VKnVj/EPBWqp7i3hPVu2PDeWJgRgFAdUHPh1EDRuWG/q6urgVD66U9/iqOjIxwdHeHg4ADtdtuNBsfPDDccHF8YZC8ODg6CQF5cXAwbAZHp15res9nZPgWayMtzsVCjGCwrE4t5ZSgVN7NhDgHHrrGrurmbupPnhTXpcXUrv8ilbsOaeEyfh4qIRo1ucAfgHGM2nU5Rr9dxeHiIarWKw8ND1Ov18NyuFBwOx1eFyWSCVquFVCqFhw8fotvtYjweo1QqJUgW1QnWs2BLiQLxAhoq66zcjuUwAEC320Wv10vsEk3Za8enle6UBLN9ztMR1H2xik8cv/WY2L9TqRQymUzwdmhFQF6npcRTqRRarRa63S4ODg6wv7+Pk5MTHB8fh+d2OH5WuOHg+JkwnU5xdHSE0WiERqOBwWCAjY0NbG5uhs10MplMYNYBJDwHFH7qhYi5fBUqRLnYVraHvzmm8XgcxsBYfwpwMkzceTkWUmQVkv7YCk8cr3Wpx5SCPgf71DjWyWSC0WiEbDabUAjKrPV6Pezt7eHhw4eoVCrY399Hq9UKFa4cDofjq0Sv10Ov18Pi4iIqlQqq1SrefvttFAqFsAMzw3AAhMUxF+70uGqC8rz9H2KkzGw2S+zNoPK21Wqh0+kkNorrdDqJECGWk9VCFVYHWbmu+kufiwRbjGCKeVH4t+ZMZLNZDAaDQIRpDp56Q6hDjo6OUKlU8ODBg+Bl4D4+DsfPAzccHD8Xms0mOp0ODg4OsLW1hXfffRe3b9/G2toaSqVScNFysU5BTmE3Go0SjL8KXVUaChoNGkZEgd9qtcICemNjA8vLy1hfX0epVApsTGwsGmakHgQKbTVQbLIxr9McB5u4bK8lC8X2FhYWsLS0hKWlpbDT89raWtjVNJ/P4/T0FN1uFz/5yU9weHiIR48eoVKpoNvtJnIjHA6H47Lg4OAAlUoFjx49wq/+6q9iY2MDN2/eRC6Xw+LiYqisxwW2LoSZSB2rvKS5AqojtC3KfMrn4XCIbreLbreLdDqNW7duYXNzE6VSKZQXZ9sasmq95pT1wNku2PzRMq46Jq0OGAth5XX8zXs0nJVlYlutForFIgqFQjDEMpkM2u02jo6O8OjRIzx8+BC1Wg1HR0euHxy/ULjh4Pi5QHaI29SToZnNZigWi8jn80Fw071qq2FoeJCyRjaGk/2pENYx0D1+enqKUqkU8gaoQKiUVLGoMrKVnOYJd46V49RxayL4vPAk3m/vtQwW52kymaBWq6Hb7eL4+BiPHj3C8fExKpUK2u225zM4HI5LC5YDHQ6H2N/fx2g0QiaTQbFYxGw2Qz6fD3KPYa8aEmQrJgGI6gbCsveUqwxHarVayOVyyGazCd2gIUkcg3rDtcCH9q0kkQ291bEQqhuUsIrpmJiO0Hbogab3ZH9/HwcHB3j06BEODg7Q7XYxGAx+zjfocCThhoPjF4Z6vY5Go4HZbIZut4vFxUW89dZbyOVySKVSIa4yk8mEcKXxeJzwGsyLc7XhS2p80HAZDoeoVCrI5XK4detWqHvN62PKwHoAlHGy+RiEDVlSxWLHRm+CzXNQZontaOjW4uIistlsUApPnjwJXoadnR0PSXI4HK8cnj17hmq1GgyE0WiE27dvB/k+HA6DPGU463g8DgSUDUu1C3Ag6QFQHcJqgEdHR9ja2gKAUDKWRE2shKsSXLESsDYPg+NTI0dzHOxePjHiSK/ned1bgt7pTCaDbreLk5MTHBwc4LPPPsPx8TEODw9/8S/P4fj/cMPB8QvFbDbD06dPUa/XUavV0Ol0sLm5iVu3bgXGnyX5qDxsfWvgjG3RKhKsbsG/VbCyPrW6bw8PD8NmObxuXsiRusj7/X4Q0rlcLlF1ieNUJfWiDed0YyCtvqRGCV31mUwGN27cQL/fR6/Xw8cff4x6vY7j42M8ffoUvV4Pg8EglDJ0OByOVw29Xg8PHz5Er9fDxsYGBoMBtra2sLKykiCVWCo1tq8NobtSa+lskkS6MK/VahiNRlheXkaxWESv10OtVkM+nw95DNY40FKtPEdjhiFUdi8HXfzz79FodC7PgtfwGPWA1RFKKK2trQF4HpK7v7+ParWKnZ0dHB8fe+Kz40uDGw6OXzjoGk2lUkFAZzIZlEqlkBRna2cDZ8yMClcKTi76tT63YjweBw/DbDZDr9cLwtq6utV1rQlt2qfGztrKHHRlA2eKazweh2fTZ2KIFpkmrR7CvjUhkK70Wq2GJ0+eBAPMN+pxOByvA6bT5xvBnZycYDweh83huKjnIt3qCOtZ0LBS6ggloqyO6PV6mM3ONqfr9/sYj8eJstgaNkSZbGW/hrCqXrIFNHTn6PF4fM7jzWfT57SGEY0g6ivugXF8fIzd3V0cHBzg4OAgbOrmcHwZcMPB8UvBYDDA4eEhDg8PUS6XsbOzg1u3buHKlStYXV0NLA83jlNhbEOJdG+DTCYD4HzFpX6/j1arha2tLXQ6HVSrVQAIyWQ2WZkCXetp21hTJizbpOrFxcVQe3wwGGA4HKLf7wfDQWNlgTOFpUYCk8IXFhZQLBbR7XbRarXwk5/8BHt7e9jb28OjR4/cWHA4HK8l6vU66vU6nj59ijt37mBrawt37txBuVxGsVgMRBNz5mxOgIYCDQaDcJ5JzUrSTKdTtFqtoHO2t7cxHo8DsWTDUblQj5WJ1dBWhpRq6XHmS5RKJTQaDQyHQ3Q6HRSLxaBT7D5AGjLFoiEAgsc8lUqh2Wzi2bNn2NnZwb1793BwcBD0nMPxZcINB8cvHXRN7+zsBKH6/vvv4+bNm3j33XeDgmA+AGGrTajS4IKa7BV/arVaWMwXCoVEMnSsapIeI6NDg0J3MWVfFPz8fHp6GpLsmIhNF7m63On1oDeGbYzHY3z66afY2dnB0dERnj17hkajEZK8HQ6H43UH96F5+vRp2Ej0137t13Dt2jVsbm4il8sBeB5eauWyzYcji08dQWKHXujT01P0+32kUqnQLhDfF4jHeY4bxHGDU7s5KMNb6W2gMVIulxMJ2byepbcZxsrPNC6As7yQ+/fv4+joCPV6HUdHR5707PjK4IaD45eO09PTc65Ueg64a6eWaFUwNClWSYlMUL/fDwqh1+sl8iI08U2rKgE4pyCYh6DeARu3yvtYKYTGxLyNhvgMQDIRmqFV7XYbjx8/xrNnz3B4eIharYZ+v5/wsjgcDsfrjH6/j36/j0ajAeB5ztn6+noILeKiW+WrhnvacCHgLPR1MpmEfXxIxpCk0kRoLQvO9tRLDSAYDRyjDU3VsQ2HwxCmSiPDVnqy4U7s5/T0NHgqnj59isPDQ9y/fx+tVgu9Xg/tdvuX8yIcjpeAGw6OrwQPHz7E9vY2BoMB3nrrLdy4cQPvvvtuwuNA5kkZJl3I8+96vR5cva1WK3gFKJRzuRyWl5fDXgg2z4GKYDQahY3XcrlcKOnKhT77sztTU+j3+/2waRDHms1mUSqVADxXZN1uF81mE48fP8b/+T//B9vb2zg4OAjGj8PhcLzpmEwm+MEPfoDd3V0cHx/jG9/4BjY2NrC1tZUoTsFQ0qWlpXMeZeA5QTUcDlGv10MC8mAwCAt5JlUXCgWsrKwk8g14/WQyCcbBcDgMpFK5XA7GA8kqbmjHCk4cE5O+J5MJ8vl8eE6GIVGnjUYj9Ho9PHr0CNvb2/jBD36Ao6MjdLtddDqdL/ktOBxxuOHg+MowHo/x4MED7O7uolwu4+/+3b+LtbU1rKysoFQqJbwEtuQdWX4mQgNAPp9HPp9PxMVyLwkaE8ViMZRu7XQ66Ha7GI/HKBaLwcgoFAphV2kaF6PRKBgO4/EYnU4nKBHWAc/n8yiXy7hy5QqKxSKA58zR/v4+Tk5O8PTpU3z++ec4Pj7G559/jpOTE3S73cCGORwOh+MM1WoVo9EI+/v7ePvtt/E3/sbfwMbGBvL5PAqFQsLbq3lsuiEbPQ6U6alUKizYAQR5n06nUS6Xw0ZxNBqazWYof5rNZsNGbGyLC/7ZbIbFxUUMh0OMRiO0Wq0wBu5vlM1mQ+iVbuZ2cnKCBw8e4Pj4GDs7O3j8+HGoqDcYDDzXzXGp4IaD4yvDdDpFpVIB8Nzt+/bbb6PdbuPq1au4detWENIaw2prYI/H4xBeRPaHCXBUEExey2QyWFtbQ7fbTZR7HQ6HweDgpnEMU9LYU601zrKo2Ww2uKNpoNCQYNsHBwfY3d3FT3/6U9y7dy9UxHA4HA7HfDB3jTH9y8vLGA6HWFlZwfXr10MJVlvpSPc+oI7Q0CQmKqdSqSD7aTgsLS2h3W6j0+kE7wE94WpAMFeB4UsMcaV+GA6HQY8ACEUzqB8WFhZCeNbe3h7u3r2L/f19PH78GDs7O57D4Li0cMPBcSkwmUzwH//jfwzxnr/1W7+F9fX1INRZvYKLc1bJ6Ha74X4K8HK5jEKhgA8//BCZTCYoDR6r1Wo4OTnB9vZ2UARra2uJXUSpeJg7wWS3wWCAo6MjpNNpZLNZ3LhxIxgR7XYb9Xodw+EQDx48wMHBAba3t3H37l0MBoPoRkEOh8PhuBjb29vY3d1FKpXC7du38Q//4T9EsVhMeAB0357T09Pg1WUoKY2LYrGI1dVV3LlzJ1S4A4Bbt25hZWUFx8fHaLfbaDQaKBaLKJfLiXLiDGViMjONl8lkguPj42BsrK2tIZ/Ph52da7UaDg4OcHR0hP39/WAs7OzshLHF9qtwOC4T3HBwXBpwUT2dTvHDH/4Q+Xw+kYBmE5zpTh4Oh7hy5QquXLkSdlsej8c4ODjA+vo63nnnHSwvL4fyePRErKyshL7pdgbONoazApx7NnBM0+kUT548QbVaRavVwng8xsnJCY6Pj8Pmd+12G71ez0ORHA6H4+cAjQEAOD4+xl/8xV8Ej4OGLKmXmns1TKdT3LhxI4QrTSYTdDod7O7u4oMPPsDKygqWl5cxmUzQ7XaRy+VQLpdD9SXqHh2Hbj4HnO05pIU1aETs7e0FI+PJkyfBo1GtVkO4rMPxqsANB8elw2w2w/3797/QPW+//TZmsxlWVlZCydfBYICFhQX8tb/210IOw/7+PorFYqLeNncD1RhZegeUBRoOhxgOh6G+92g0wvb2Nvb29lCr1XB6eort7W3s7Oz8MqbF4XA4HADa7TY++eSTl76eIazcI6LT6YQ8hA8//DDkwpFYKpfLABBCV6kLlFRSo4HeBu7cTH3CvRYePnwYwp5++MMfOpHkeKWRmr2kTyxWZtLhuCzQWtuMY33rrbdw7do1vPfeeygUChiNRtjZ2Qnxrf1+H9evX8fVq1dx8+ZNFAqFsDGdtjscDtFut3H37l1UKhU8e/YM/X4f3W4Xz549S4QgeTiS47LjlxUG4TrCcZnBEFT+lEolXLt2Dd/4xjewsrKCfD6Pvb09DAYDlMtlDIdDpFIp3LlzB1evXsWVK1ewvLyMTCYTvA9sq9FohATnnZ2dUDZ1f38f7XY7YSh4orPjMuNl9IN7HByvBWIL9uPj47CjtLq0mRcxHA7RbDaRz+exu7uLYrEYfsgoDYdDdLtdnJyc4OjoKOQxsHSrJ7A5HA7H5YddsKt3mQUxSEDRIzGbzdBqtUKo69raWqiORM/CeDzG4eEhms0mKpUKGo1GyHtrtVpeZtvx2sE9Do43BqVSCV/72tdCmb3BYBA2jCsUCiiVSigWi1heXg6hSI1GA41GAwcHB1/18B2OXwjc4+BwxPH++++jXC4HYoiLf1ZSunr1KvL5PHK5HAaDAQaDATqdDp49e+abdjpeC7yMfnDDwfHGgBvxaFyq7t7JUCfdQMjGtjocrzrccHA44tDiG7bCEZOk7e7PTIp2OF4HuOHgcDgcjgTccHA4HA5HDC+jH9IXXuFwOBwOh8PhcDjeeLjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC6EGw4Oh8PhcDgcDofjQrjh4HA4HA6Hw+FwOC5Eajabzb7qQTgcDofD4XA4HI7LDfc4OBwOh8PhcDgcjgvhhoPD4XA4HA6Hw+G4EG44OBwOh8PhcDgcjgvhhoPD4XA4HA6Hw+G4EG44OBwOh8PhcDgcjgvhhoPD4XA4HA6Hw+G4EG44OBwOh8PhcDgcjgvhhoPD4XA4HA6Hw+G4EG44OBwOh8PhcDgcjgvx/wDSt9/6PZWCzAAAAABJRU5ErkJggg==",
       "text/plain": [
        ""
       ]
@@ -618,35 +981,120 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2024-08-30 15:29:59.806\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m46\u001b[0m - \u001b[1mInstantiated Inpainter with algorithm: BraTS23_1 by Juexin Zhang, et al.\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:29:59.808\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m163\u001b[0m - \u001b[1mFound 1 subjects: BraTS-GLI-00001-000 \u001b[0m\n",
-      "\u001b[32m2024-08-30 15:29:59.813\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m172\u001b[0m - \u001b[1mStandardized input names to match algorithm requirements.\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:29:59.814\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m276\u001b[0m - \u001b[1mRunning algorithm: \u001b[92mBraTS23 Inpainting [1st place]\u001b[0m\u001b[1m\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:29:59.815\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m279\u001b[0m - \u001b[1m\u001b[34m(Paper)\u001b[0m\u001b[1m Consider citing the corresponding paper: N/A by Juexin Zhang, et al.\u001b[0m\n"
+      "\u001b[32m2025-03-06 14:15:34.599\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m48\u001b[0m - \u001b[1mInstantiated Inpainter with algorithm: BraTS23_1 by Juexin Zhang, et al.\u001b[0m\n",
+      "\u001b[32m2025-03-06 14:15:34.600\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m198\u001b[0m - \u001b[1mFound 1 subjects: BraTS-GLI-00001-000 \u001b[0m\n",
+      "\u001b[32m2025-03-06 14:15:34.610\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m207\u001b[0m - \u001b[1mStandardized input names to match algorithm requirements.\u001b[0m\n"
      ]
     },
+    {
+     "data": {
+      "text/html": [
+       "──────────────────────────────────────────────── Citation Reminder ────────────────────────────────────────────────\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[92m──────────────────────────────────────────────── \u001b[0m\u001b[1;31mCitation Reminder\u001b[0m\u001b[92m ────────────────────────────────────────────────\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Please support our development by citing the relevant manuscripts for the used algorithm:\n",
+       "\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "Please support our development by citing the relevant manuscripts for the used algorithm:\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "                    BraTS Package | N/A                                          \n",
+       "----------------------------------+----------------------------------------------\n",
+       "      Challenge (Inpainting 2023) | https://arxiv.org/abs/2305.08992             \n",
+       "----------------------------------+----------------------------------------------\n",
+       " Algorithm (Juexin Zhang, et al.) | https://doi.org/10.1007/978-3-031-76163-8_21 \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[36m \u001b[0m\u001b[36m                   BraTS Package\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mN/A                                         \u001b[0m\u001b[37m \u001b[0m\n",
+       "----------------------------------+----------------------------------------------\n",
+       "\u001b[36m \u001b[0m\u001b[36m     Challenge (Inpainting 2023)\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mhttps://arxiv.org/abs/2305.08992            \u001b[0m\u001b[37m \u001b[0m\n",
+       "----------------------------------+----------------------------------------------\n",
+       "\u001b[36m \u001b[0m\u001b[36mAlgorithm (Juexin Zhang, et al.)\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mhttps://doi.org/10.1007/978-3-031-76163-8_21\u001b[0m\u001b[37m \u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "───────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[92m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[32m2024-08-30 15:30:00.250\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.utils.zenodo\u001b[0m:\u001b[36mcheck_additional_files_path\u001b[0m:\u001b[36m56\u001b[0m - \u001b[1mFound downloaded local weights: 13382922_v1.0.1\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:30:00.251\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.utils.zenodo\u001b[0m:\u001b[36mcheck_additional_files_path\u001b[0m:\u001b[36m66\u001b[0m - \u001b[1mLatest model weights (13382922_v1.0.1) are already present.\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:30:00.645\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m329\u001b[0m - \u001b[1mStarting inference\u001b[0m\n"
+      "\u001b[32m2025-03-06 14:15:34.617\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m329\u001b[0m - \u001b[1mRunning algorithm: \u001b[92m BraTS 2023 Inpainting [1st place]\u001b[0m\u001b[1m\u001b[0m\n",
+      "\u001b[32m2025-03-06 14:15:34.925\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.utils.zenodo\u001b[0m:\u001b[36mcheck_additional_files_path\u001b[0m:\u001b[36m60\u001b[0m - \u001b[1mFound downloaded local additional_files: 13382922_v1.0.1\u001b[0m\n",
+      "\u001b[32m2025-03-06 14:15:34.926\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.utils.zenodo\u001b[0m:\u001b[36mcheck_additional_files_path\u001b[0m:\u001b[36m72\u001b[0m - \u001b[1mLatest additional files (13382922_v1.0.1) are already present.\u001b[0m\n",
+      "\u001b[32m2025-03-06 14:15:35.557\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m381\u001b[0m - \u001b[1mStarting inference\u001b[0m\n"
      ]
     },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a26f635627474438bc69eaca35968079",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
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      "output_type": "stream",
      "text": [
-      "\u001b[32m2024-08-30 15:30:15.967\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m349\u001b[0m - \u001b[1mFinished inference in 15.32 seconds\u001b[0m\n",
-      "\u001b[32m2024-08-30 15:30:15.969\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m189\u001b[0m - \u001b[1mSaved outputs to: /home/ivan_marcel/tutorials/BraTS/inpainting_batch_out\u001b[0m\n"
+      "\u001b[32m2025-03-06 14:15:48.308\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m404\u001b[0m - \u001b[1mFinished inference in 12.75 seconds\u001b[0m\n",
+      "\u001b[32m2025-03-06 14:15:48.309\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_batch\u001b[0m:\u001b[36m225\u001b[0m - \u001b[1mSaved outputs to: /home/marcelrosier/tutorials/BraTS/inpainting_batch_out\u001b[0m\n"
      ]
     },
     {
@@ -668,11 +1116,175 @@
     "\n",
     "print([path.name for path in output_path.iterdir()])"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Missing MRI Synthesis (BraSyn)\n",
+    "\n",
+    "MissingMRI algorithms allow to synthesize a missing modality image from the three others (any combination is possible).  \n",
+    "Below we demonstrate how to generate a `t2w` image from `t1c`, `t1n` and `t2f`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m2025-03-06 13:39:02.261\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m__init__\u001b[0m:\u001b[36m48\u001b[0m - \u001b[1mInstantiated MissingMRI with algorithm: BraTS24_1 by Jihoon Cho, Seunghyuck Park, Jinah Park\u001b[0m\n",
+      "\u001b[32m2025-03-06 13:39:02.263\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_single\u001b[0m:\u001b[36m155\u001b[0m - \u001b[1mPerforming single inference\u001b[0m\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "──────────────────────────────────────────────── Citation Reminder ────────────────────────────────────────────────\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[92m──────────────────────────────────────────────── \u001b[0m\u001b[1;31mCitation Reminder\u001b[0m\u001b[92m ────────────────────────────────────────────────\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Please support our development by citing the relevant manuscripts for the used algorithm:\n",
+       "\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "Please support our development by citing the relevant manuscripts for the used algorithm:\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "                                           BraTS Package | N/A                              \n",
+       "---------------------------------------------------------+----------------------------------\n",
+       " Challenge (BraTS MRI Synthesis Challenge (BraSyn) 2024) | https://arxiv.org/abs/2305.09011 \n",
+       "---------------------------------------------------------+----------------------------------\n",
+       "     Algorithm (Jihoon Cho, Seunghyuck Park, Jinah Park) | N/A                              \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[36m \u001b[0m\u001b[36m                                          BraTS Package\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mN/A                             \u001b[0m\u001b[37m \u001b[0m\n",
+       "---------------------------------------------------------+----------------------------------\n",
+       "\u001b[36m \u001b[0m\u001b[36mChallenge (BraTS MRI Synthesis Challenge (BraSyn) 2024)\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mhttps://arxiv.org/abs/2305.09011\u001b[0m\u001b[37m \u001b[0m\n",
+       "---------------------------------------------------------+----------------------------------\n",
+       "\u001b[36m \u001b[0m\u001b[36m    Algorithm (Jihoon Cho, Seunghyuck Park, Jinah Park)\u001b[0m\u001b[36m \u001b[0m|\u001b[37m \u001b[0m\u001b[37mN/A                             \u001b[0m\u001b[37m \u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "───────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[92m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m2025-03-06 13:39:02.287\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36m_log_algorithm_info\u001b[0m:\u001b[36m329\u001b[0m - \u001b[1mRunning algorithm: \u001b[92m BraTS 2024 BraTS MRI Synthesis Challenge (BraSyn) [1st place]\u001b[0m\u001b[1m\u001b[0m\n",
+      "\u001b[32m2025-03-06 13:39:02.964\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.utils.zenodo\u001b[0m:\u001b[36mcheck_additional_files_path\u001b[0m:\u001b[36m60\u001b[0m - \u001b[1mFound downloaded local additional_files: 14287969_v1.0.0\u001b[0m\n",
+      "\u001b[32m2025-03-06 13:39:02.965\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.utils.zenodo\u001b[0m:\u001b[36mcheck_additional_files_path\u001b[0m:\u001b[36m72\u001b[0m - \u001b[1mLatest additional files (14287969_v1.0.0) are already present.\u001b[0m\n",
+      "\u001b[32m2025-03-06 13:39:03.861\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m381\u001b[0m - \u001b[1mStarting inference\u001b[0m\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0e130a2c88ca4215bafadf292ede1d35",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n"
+      ],
+      "text/plain": []
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m2025-03-06 13:39:41.185\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.docker\u001b[0m:\u001b[36mrun_container\u001b[0m:\u001b[36m404\u001b[0m - \u001b[1mFinished inference in 37.32 seconds\u001b[0m\n",
+      "\u001b[32m2025-03-06 13:39:41.187\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mbrats.core.brats_algorithm\u001b[0m:\u001b[36m_infer_single\u001b[0m:\u001b[36m179\u001b[0m - \u001b[1mSaved output to: /home/marcelrosier/tutorials/BraTS/synthesized_t2w.nii.gz\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "from brats import MissingMRI\n",
+    "from brats.constants import MissingMRIAlgorithms\n",
+    "\n",
+    "missing_mri = MissingMRI()\n",
+    "missing_mri.infer_single(\n",
+    "    t1c=segmentation_subject_path / f\"{subject}-t1c.nii.gz\",\n",
+    "    t1n=segmentation_subject_path / f\"{subject}-t1n.nii.gz\",\n",
+    "    t2f=segmentation_subject_path / f\"{subject}-t2f.nii.gz\",\n",
+    "    output_file=\"synthesized_t2w.nii.gz\",\n",
+    ")\n",
+    "# .infer_batch() works identical to the segmentation/ inpainting batch infer methods"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       ""
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "utils.visualize_missing_mri_t2w(\n",
+    "    synthesized_t2w=\"synthesized_t2w.nii.gz\", data_folder=missing_mri_path\n",
+    ")"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "brats312",
    "language": "python",
    "name": "python3"
   },
@@ -686,7 +1298,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.14"
+   "version": "3.12.9"
   }
  },
  "nbformat": 4,
diff --git a/BraTS/utils.py b/BraTS/utils.py
index c46ebb4..70df1e5 100644
--- a/BraTS/utils.py
+++ b/BraTS/utils.py
@@ -88,3 +88,33 @@ def visualize_inpainting(t1n_voided: str, prediction: str):
     for ax in ax:
         ax.axis("off")
     plt.tight_layout()
+
+
+def visualize_missing_mri_t2w(
+    synthesized_t2w: str,
+    data_folder: str = DATA_FOLDER,
+    subject_id: str = "BraTS-GLI-00001-000",
+    slice_index: int = 75,
+):
+    """Visualize the MRI modalities for a given slice index
+
+    Args:
+        data_folder (str, optional): Path to the folder containing the t1, t1c, t2 & flair file. Defaults to DATA_FOLDER.
+        slice_index (int, optional): Slice to be visualized (first index in data of shape (155, 240, 240)). Defaults to 75.
+    """
+    _, axes = plt.subplots(1, 5, figsize=(12, 10))
+
+    subject_path = Path(data_folder) / subject_id
+    modalities = ["t1n", "t1c", "t2f", "t2w"]
+    for i, mod in enumerate(modalities):
+        modality_file = subject_path / f"{subject_id}-{mod}.nii.gz"
+        modality_np = nib.load(modality_file).get_fdata().transpose(2, 1, 0)
+        axes[i].set_title(mod)
+        axes[i].imshow(modality_np[slice_index, :, :], cmap="gray")
+        axes[i].axis("off")
+
+    # show synthetic T2w
+    synthetic_t2w_np = nib.load(synthesized_t2w).get_fdata().transpose(2, 1, 0)
+    axes[4].set_title("Synthesized t2w")
+    axes[4].imshow(synthetic_t2w_np[slice_index, :, :], cmap="gray")
+    axes[4].axis("off")