{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.12.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"nvidiaTeslaT4","dataSources":[{"sourceId":129601,"databundleVersionId":15542776,"sourceType":"competition"},{"sourceId":2542390,"sourceType":"datasetVersion","datasetId":1541666}],"dockerImageVersionId":31260,"isInternetEnabled":false,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# Load Data","metadata":{}},{"cell_type":"code","source":"import os, glob, tarfile\n\nDATASET_DIR = \"/kaggle/input/instant-odc-ai-hackathon\"\nEXTRACT_PATH = \"/kaggle/working/extracted_data\"\nos.makedirs(EXTRACT_PATH, exist_ok=True)\n\ntar_paths = sorted(glob.glob(os.path.join(DATASET_DIR, \"*.tar\")))\nprint(\"Found tar files:\", len(tar_paths))\nfor p in tar_paths[:10]:\n    print(\" -\", os.path.basename(p))\n\n# Check if extraction looks complete\ncase_folders = sorted([d for d in glob.glob(os.path.join(EXTRACT_PATH, \"BraTS2021_*\")) if os.path.isdir(d)])\nprint(\"Existing extracted case folders:\", len(case_folders))\n\n# Heuristic: if too few cases exist, re-extract\nMIN_EXPECTED_CASES = 200  # safe lower bound to detect partial extraction\n\nif len(case_folders) < MIN_EXPECTED_CASES:\n    print(\"Extraction seems incomplete (or not done). Extracting all .tar files...\")\n    for tar_path in tar_paths:\n        print(\"Extracting:\", os.path.basename(tar_path))\n        with tarfile.open(tar_path, \"r\") as tar:\n            tar.extractall(EXTRACT_PATH)\n    print(\"Extraction done.\")\nelse:\n    print(\"Extraction looks OK. Skipping extraction.\")\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:27:56.397147Z","iopub.execute_input":"2026-02-03T13:27:56.39777Z","iopub.status.idle":"2026-02-03T13:27:56.424139Z","shell.execute_reply.started":"2026-02-03T13:27:56.397735Z","shell.execute_reply":"2026-02-03T13:27:56.423335Z"}},"outputs":[{"name":"stdout","text":"Found tar files: 3\n - BraTS2021_00495.tar\n - BraTS2021_00621.tar\n - BraTS2021_Training_Data.tar\nExisting extracted case folders: 1251\nExtraction looks OK. Skipping extraction.\n","output_type":"stream"}],"execution_count":29},{"cell_type":"code","source":"import glob, os\n\ncase_dirs = sorted([d for d in glob.glob(os.path.join(EXTRACT_PATH, \"BraTS2021_*\")) if os.path.isdir(d)])\nprint(\"Total case folders found:\", len(case_dirs))\n\ndef has_all_files(case_dir):\n    pid = os.path.basename(case_dir)\n    required = [\n        f\"{pid}_flair.nii.gz\",\n        f\"{pid}_t1.nii.gz\",\n        f\"{pid}_t1ce.nii.gz\",\n        f\"{pid}_t2.nii.gz\",\n        f\"{pid}_seg.nii.gz\",\n    ]\n    for r in required:\n        if not os.path.exists(os.path.join(case_dir, r)):\n            return False\n    return True\n\nvalid_cases = [c for c in case_dirs if has_all_files(c)]\ninvalid_count = len(case_dirs) - len(valid_cases)\n\nprint(\"Valid cases:\", len(valid_cases))\nprint(\"Invalid cases (missing files):\", invalid_count)\n\n# Pick a default example (we'll improve selection in next cell)\ncase = valid_cases[0]\nprint(\"Example valid case:\", case)\nprint(\"Files:\", [os.path.basename(x) for x in sorted(glob.glob(os.path.join(case, \"*.nii*\")))])\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:27:56.425968Z","iopub.execute_input":"2026-02-03T13:27:56.426375Z","iopub.status.idle":"2026-02-03T13:27:56.471571Z","shell.execute_reply.started":"2026-02-03T13:27:56.426339Z","shell.execute_reply":"2026-02-03T13:27:56.47087Z"}},"outputs":[{"name":"stdout","text":"Total case folders found: 1251\nValid cases: 1251\nInvalid cases (missing files): 0\nExample valid case: /kaggle/working/extracted_data/BraTS2021_00000\nFiles: ['BraTS2021_00000_flair.nii.gz', 'BraTS2021_00000_seg.nii.gz', 'BraTS2021_00000_t1.nii.gz', 'BraTS2021_00000_t1ce.nii.gz', 'BraTS2021_00000_t2.nii.gz']\n","output_type":"stream"}],"execution_count":30},{"cell_type":"code","source":"import nibabel as nib\nimport numpy as np\nimport matplotlib.pyplot as plt\n\ndef load_img(path):\n    return nib.load(path).get_fdata()\n\ndef get_case_paths(case_dir):\n    pid = os.path.basename(case_dir)\n    def p(suf): return os.path.join(case_dir, f\"{pid}_{suf}.nii.gz\")\n    return {\n        \"flair\": p(\"flair\"),\n        \"t1\": p(\"t1\"),\n        \"t1ce\": p(\"t1ce\"),\n        \"t2\": p(\"t2\"),\n        \"seg\": p(\"seg\"),\n    }\n\n# Choose a \"good\" case for visualization: must have tumor voxels\ndef tumor_voxels(seg):\n    return int(np.isin(seg.astype(int), [1,2,4]).sum())\n\nviz_case = None\nviz_tumor = -1\n\n# Try first 50 valid cases to find a clear tumor example (fast)\nfor c in valid_cases[:50]:\n    p = get_case_paths(c)\n    seg = load_img(p[\"seg\"])\n    tv = tumor_voxels(seg)\n    if tv > viz_tumor:\n        viz_tumor = tv\n        viz_case = c\n\ncase = viz_case if viz_case is not None else valid_cases[0]\nprint(\"Chosen visualization case:\", case)\nprint(\"Tumor voxels in chosen case:\", viz_tumor)\n\npaths = get_case_paths(case)\npaths\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:27:56.47251Z","iopub.execute_input":"2026-02-03T13:27:56.473099Z","iopub.status.idle":"2026-02-03T13:28:04.766611Z","shell.execute_reply.started":"2026-02-03T13:27:56.473077Z","shell.execute_reply":"2026-02-03T13:28:04.766007Z"}},"outputs":[{"name":"stdout","text":"Chosen visualization case: /kaggle/working/extracted_data/BraTS2021_00012\nTumor voxels in chosen case: 263809\n","output_type":"stream"},{"execution_count":31,"output_type":"execute_result","data":{"text/plain":"{'flair': '/kaggle/working/extracted_data/BraTS2021_00012/BraTS2021_00012_flair.nii.gz',\n 't1': '/kaggle/working/extracted_data/BraTS2021_00012/BraTS2021_00012_t1.nii.gz',\n 't1ce': '/kaggle/working/extracted_data/BraTS2021_00012/BraTS2021_00012_t1ce.nii.gz',\n 't2': '/kaggle/working/extracted_data/BraTS2021_00012/BraTS2021_00012_t2.nii.gz',\n 'seg': '/kaggle/working/extracted_data/BraTS2021_00012/BraTS2021_00012_seg.nii.gz'}"},"metadata":{}}],"execution_count":31},{"cell_type":"code","source":"imgs = {k: load_img(v) for k,v in paths.items()}\n\nprint({k: imgs[k].shape for k in imgs})\n\nuniq = np.unique(imgs[\"seg\"]).astype(int)\nprint(\"Unique labels:\", uniq)\n\nallowed = set([0,1,2,4])\nbad = [x for x in uniq.tolist() if x not in allowed]\nassert len(bad) == 0, f\"Found unexpected labels: {bad} (expected subset of {sorted(list(allowed))})\"\n\ntv = int(np.isin(imgs[\"seg\"].astype(int), [1,2,4]).sum())\nprint(\"Tumor voxels (non-background):\", tv)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:04.767401Z","iopub.execute_input":"2026-02-03T13:28:04.767636Z","iopub.status.idle":"2026-02-03T13:28:05.361976Z","shell.execute_reply.started":"2026-02-03T13:28:04.767615Z","shell.execute_reply":"2026-02-03T13:28:05.361429Z"}},"outputs":[{"name":"stdout","text":"{'flair': (240, 240, 155), 't1': (240, 240, 155), 't1ce': (240, 240, 155), 't2': (240, 240, 155), 'seg': (240, 240, 155)}\nUnique labels: [0 1 2 4]\nTumor voxels (non-background): 263809\n","output_type":"stream"}],"execution_count":32},{"cell_type":"code","source":"def tumor_max_slice(seg):\n    tumor = np.isin(seg.astype(int), [1,2,4])\n    counts = tumor.sum(axis=(0,1))\n    if counts.max() == 0:\n        return seg.shape[2] // 2\n    return int(np.argmax(counts))\n\ndef show_modalities(imgs, z):\n    fig, axes = plt.subplots(1, 5, figsize=(22,5))\n    for i, key in enumerate([\"flair\",\"t1\",\"t1ce\",\"t2\"]):\n        axes[i].imshow(imgs[key][:,:,z].T, origin=\"lower\", cmap=\"gray\")\n        axes[i].set_title(key.upper())\n        axes[i].axis(\"off\")\n    axes[4].imshow(imgs[\"seg\"][:,:,z].T, origin=\"lower\")\n    axes[4].set_title(\"SEG\")\n    axes[4].axis(\"off\")\n    plt.show()\n\nz_mid = imgs[\"flair\"].shape[2] // 2\nz_tumor = tumor_max_slice(imgs[\"seg\"])\n\nprint(\"z_mid:\", z_mid, \"z_tumor:\", z_tumor)\nshow_modalities(imgs, z_mid)\nshow_modalities(imgs, z_tumor)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:05.363524Z","iopub.execute_input":"2026-02-03T13:28:05.363741Z","iopub.status.idle":"2026-02-03T13:28:06.048096Z","shell.execute_reply.started":"2026-02-03T13:28:05.363721Z","shell.execute_reply":"2026-02-03T13:28:06.047491Z"}},"outputs":[{"name":"stdout","text":"z_mid: 77 z_tumor: 93\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 2200x500 with 5 Axes>","image/png":"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\n"},"metadata":{}}],"execution_count":33},{"cell_type":"markdown","source":"# Preprocessing","metadata":{}},{"cell_type":"markdown","source":"## Preprocessing utilities (normalize + crop + remap)","metadata":{}},{"cell_type":"code","source":"import numpy as np\n\ndef zscore_nonzero(x, eps=1e-8):\n    \"\"\"\n    Z-score normalize using only non-zero voxels, keep zeros as zeros.\n    \"\"\"\n    x = x.astype(np.float32)\n    mask = x != 0\n    if mask.sum() == 0:\n        return x\n    mu = x[mask].mean()\n    sigma = x[mask].std()\n    if sigma < eps:\n        return x\n    x_norm = x.copy()\n    x_norm[mask] = (x[mask] - mu) / (sigma + eps)\n    return x_norm\n\ndef compute_foreground_bbox(modalities, margin=2):\n    \"\"\"\n    modalities: list of 3D arrays (float)\n    Foreground is union of non-zero across modalities.\n    Returns bbox slices for cropping (sx, sy, sz).\n    \"\"\"\n    fg = np.zeros_like(modalities[0], dtype=bool)\n    for m in modalities:\n        fg |= (m != 0)\n\n    if fg.sum() == 0:\n        # fallback: no crop\n        sx = slice(0, fg.shape[0])\n        sy = slice(0, fg.shape[1])\n        sz = slice(0, fg.shape[2])\n        return sx, sy, sz\n\n    coords = np.array(np.where(fg))\n    x0, y0, z0 = coords.min(axis=1)\n    x1, y1, z1 = coords.max(axis=1)\n\n    x0 = max(0, x0 - margin); y0 = max(0, y0 - margin); z0 = max(0, z0 - margin)\n    x1 = min(fg.shape[0]-1, x1 + margin); y1 = min(fg.shape[1]-1, y1 + margin); z1 = min(fg.shape[2]-1, z1 + margin)\n\n    sx = slice(x0, x1+1)\n    sy = slice(y0, y1+1)\n    sz = slice(z0, z1+1)\n    return sx, sy, sz\n\ndef remap_labels(seg):\n    \"\"\"\n    BraTS labels: {0,1,2,4} -> {0,1,2,3} for training.\n    \"\"\"\n    seg = seg.astype(np.int64)\n    seg_remap = seg.copy()\n    seg_remap[seg_remap == 4] = 3\n    return seg_remap\n\ndef preprocess_case(imgs_dict, do_crop=True):\n    \"\"\"\n    imgs_dict keys: flair, t1, t1ce, t2, seg\n    Returns:\n      x: np.float32 array shape (4, D, H, W)  [we'll use (C, X, Y, Z) style soon]\n      y: np.int64 segmentation shape (X, Y, Z) with labels remapped 4->3\n      meta: dict with bbox slices and original shape\n    \"\"\"\n    flair = imgs_dict[\"flair\"]\n    t1 = imgs_dict[\"t1\"]\n    t1ce = imgs_dict[\"t1ce\"]\n    t2 = imgs_dict[\"t2\"]\n    seg = imgs_dict[\"seg\"]\n\n    # normalize each modality (non-zero z-score)\n    flair_n = zscore_nonzero(flair)\n    t1_n = zscore_nonzero(t1)\n    t1ce_n = zscore_nonzero(t1ce)\n    t2_n = zscore_nonzero(t2)\n\n    # crop foreground\n    if do_crop:\n        sx, sy, sz = compute_foreground_bbox([flair, t1, t1ce, t2], margin=2)\n        flair_n = flair_n[sx, sy, sz]\n        t1_n = t1_n[sx, sy, sz]\n        t1ce_n = t1ce_n[sx, sy, sz]\n        t2_n = t2_n[sx, sy, sz]\n        seg_c = seg[sx, sy, sz]\n    else:\n        sx = slice(0, flair.shape[0]); sy = slice(0, flair.shape[1]); sz = slice(0, flair.shape[2])\n        seg_c = seg\n\n    # label remap\n    y = remap_labels(seg_c)\n\n    # stack channels (C, X, Y, Z)\n    x = np.stack([flair_n, t1_n, t1ce_n, t2_n], axis=0).astype(np.float32)\n\n    meta = {\n        \"orig_shape\": seg.shape,\n        \"crop_slices\": (sx, sy, sz),\n        \"cropped_shape\": y.shape\n    }\n    return x, y, meta\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:06.048986Z","iopub.execute_input":"2026-02-03T13:28:06.049301Z","iopub.status.idle":"2026-02-03T13:28:06.062904Z","shell.execute_reply.started":"2026-02-03T13:28:06.049276Z","shell.execute_reply":"2026-02-03T13:28:06.062172Z"}},"outputs":[],"execution_count":34},{"cell_type":"markdown","source":"## Run preprocessing on the chosen visualization case (sanity output)","metadata":{}},{"cell_type":"code","source":"x, y, meta = preprocess_case(imgs, do_crop=True)\n\nprint(\"Original shape:\", meta[\"orig_shape\"])\nprint(\"Cropped shape:\", meta[\"cropped_shape\"])\nprint(\"X (channels-first) shape:\", x.shape, \"dtype:\", x.dtype)\nprint(\"Y shape:\", y.shape, \"dtype:\", y.dtype)\n\nprint(\"Unique labels after remap:\", np.unique(y))\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:06.063864Z","iopub.execute_input":"2026-02-03T13:28:06.064448Z","iopub.status.idle":"2026-02-03T13:28:07.144643Z","shell.execute_reply.started":"2026-02-03T13:28:06.064425Z","shell.execute_reply":"2026-02-03T13:28:07.14399Z"}},"outputs":[{"name":"stdout","text":"Original shape: (240, 240, 155)\nCropped shape: (147, 182, 145)\nX (channels-first) shape: (4, 147, 182, 145) dtype: float32\nY shape: (147, 182, 145) dtype: int64\nUnique labels after remap: [0 1 2 3]\n","output_type":"stream"}],"execution_count":35},{"cell_type":"markdown","source":"## Quick visualization after preprocessing","metadata":{}},{"cell_type":"code","source":"import matplotlib.pyplot as plt\n\ndef show_preprocessed_overlay(x, y, z=None, title=\"\"):\n    # x: (4, X, Y, Z), y: (X, Y, Z)\n    flair = x[0]\n    if z is None:\n        # pick tumor-max slice on remapped labels {1,2,3}\n        tumor = np.isin(y, [1,2,3])\n        counts = tumor.sum(axis=(0,1))\n        z = int(np.argmax(counts)) if counts.max() > 0 else flair.shape[2] // 2\n\n    plt.figure(figsize=(12,4))\n    plt.subplot(1,3,1); plt.title(f\"{title} FLAIR z={z}\")\n    plt.imshow(flair[:,:,z].T, origin=\"lower\", cmap=\"gray\"); plt.axis(\"off\")\n\n    plt.subplot(1,3,2); plt.title(\"SEG (remapped)\")\n    plt.imshow(y[:,:,z].T, origin=\"lower\"); plt.axis(\"off\")\n\n    plt.subplot(1,3,3); plt.title(\"Overlay\")\n    plt.imshow(flair[:,:,z].T, origin=\"lower\", cmap=\"gray\")\n    plt.imshow(y[:,:,z].T, origin=\"lower\", alpha=0.35); plt.axis(\"off\")\n    plt.show()\n\nshow_preprocessed_overlay(x, y, title=\"After preprocessing\")\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:07.145692Z","iopub.execute_input":"2026-02-03T13:28:07.145983Z","iopub.status.idle":"2026-02-03T13:28:07.386824Z","shell.execute_reply.started":"2026-02-03T13:28:07.145957Z","shell.execute_reply":"2026-02-03T13:28:07.386072Z"}},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1200x400 with 3 Axes>","image/png":"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\n"},"metadata":{}}],"execution_count":36},{"cell_type":"markdown","source":"## Save preprocessed sample","metadata":{}},{"cell_type":"code","source":"np.save(\"/kaggle/working/sample_x.npy\", x)\nnp.save(\"/kaggle/working/sample_y.npy\", y)\nprint(\"Saved sample_x.npy and sample_y.npy in /kaggle/working/\")\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:07.388451Z","iopub.execute_input":"2026-02-03T13:28:07.38875Z","iopub.status.idle":"2026-02-03T13:28:07.451251Z","shell.execute_reply.started":"2026-02-03T13:28:07.388725Z","shell.execute_reply":"2026-02-03T13:28:07.450586Z"}},"outputs":[{"name":"stdout","text":"Saved sample_x.npy and sample_y.npy in /kaggle/working/\n","output_type":"stream"}],"execution_count":37},{"cell_type":"markdown","source":"# Data Splitting Strategy","metadata":{}},{"cell_type":"markdown","source":"## Build patient IDs + deterministic split","metadata":{}},{"cell_type":"code","source":"import numpy as np\nimport os\n\nSEED = 42\nrng = np.random.default_rng(SEED)\n\npatient_ids = [os.path.basename(c) for c in valid_cases]\npatient_ids = sorted(patient_ids)\n\nprint(\"Num valid patients:\", len(patient_ids))\nprint(\"Example IDs:\", patient_ids[:5])\n\n# shuffle deterministically\nshuffled = patient_ids.copy()\nrng.shuffle(shuffled)\n\nsplit_ratio = 0.8\nn_train = int(len(shuffled) * split_ratio)\n\ntrain_ids = shuffled[:n_train]\nval_ids = shuffled[n_train:]\n\nprint(\"Train:\", len(train_ids), \"Val:\", len(val_ids))\nprint(\"Train example:\", train_ids[:3])\nprint(\"Val example:\", val_ids[:3])\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:07.452237Z","iopub.execute_input":"2026-02-03T13:28:07.452545Z","iopub.status.idle":"2026-02-03T13:28:07.459895Z","shell.execute_reply.started":"2026-02-03T13:28:07.452513Z","shell.execute_reply":"2026-02-03T13:28:07.45924Z"}},"outputs":[{"name":"stdout","text":"Num valid patients: 1251\nExample IDs: ['BraTS2021_00000', 'BraTS2021_00002', 'BraTS2021_00003', 'BraTS2021_00005', 'BraTS2021_00006']\nTrain: 1000 Val: 251\nTrain example: ['BraTS2021_01347', 'BraTS2021_01045', 'BraTS2021_01156']\nVal example: ['BraTS2021_01605', 'BraTS2021_00651', 'BraTS2021_01125']\n","output_type":"stream"}],"execution_count":38},{"cell_type":"markdown","source":"## Map IDs back to case directories","metadata":{}},{"cell_type":"code","source":"# Build mapping id -> directory\nid2dir = {os.path.basename(c): c for c in valid_cases}\n\ntrain_dirs = [id2dir[i] for i in train_ids]\nval_dirs = [id2dir[i] for i in val_ids]\n\nprint(\"Train dirs example:\", train_dirs[0])\nprint(\"Val dirs example:\", val_dirs[0])\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:07.460792Z","iopub.execute_input":"2026-02-03T13:28:07.461125Z","iopub.status.idle":"2026-02-03T13:28:07.473163Z","shell.execute_reply.started":"2026-02-03T13:28:07.461103Z","shell.execute_reply":"2026-02-03T13:28:07.472535Z"}},"outputs":[{"name":"stdout","text":"Train dirs example: /kaggle/working/extracted_data/BraTS2021_01347\nVal dirs example: /kaggle/working/extracted_data/BraTS2021_01605\n","output_type":"stream"}],"execution_count":39},{"cell_type":"markdown","source":"## Save split lists","metadata":{}},{"cell_type":"code","source":"SPLIT_DIR = \"/kaggle/working/splits\"\nos.makedirs(SPLIT_DIR, exist_ok=True)\n\ntrain_list_path = os.path.join(SPLIT_DIR, \"train_ids.txt\")\nval_list_path = os.path.join(SPLIT_DIR, \"val_ids.txt\")\n\nwith open(train_list_path, \"w\") as f:\n    f.write(\"\\n\".join(train_ids))\n\nwith open(val_list_path, \"w\") as f:\n    f.write(\"\\n\".join(val_ids))\n\nprint(\"Saved splits to:\")\nprint(\" -\", train_list_path)\nprint(\" -\", val_list_path)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:07.474718Z","iopub.execute_input":"2026-02-03T13:28:07.475013Z","iopub.status.idle":"2026-02-03T13:28:07.486811Z","shell.execute_reply.started":"2026-02-03T13:28:07.474993Z","shell.execute_reply":"2026-02-03T13:28:07.486242Z"}},"outputs":[{"name":"stdout","text":"Saved splits to:\n - /kaggle/working/splits/train_ids.txt\n - /kaggle/working/splits/val_ids.txt\n","output_type":"stream"}],"execution_count":40},{"cell_type":"markdown","source":"# Dataset & Patch Sampling","metadata":{}},{"cell_type":"code","source":"import os\nimport numpy as np\nimport nibabel as nib\nimport torch\nfrom torch.utils.data import Dataset, DataLoader\n\ndef load_nii_fdata(path):\n    return nib.load(path).get_fdata()\n\ndef get_case_paths_from_dir(case_dir):\n    pid = os.path.basename(case_dir)\n    def p(suf): \n        return os.path.join(case_dir, f\"{pid}_{suf}.nii.gz\")\n    return {\n        \"flair\": p(\"flair\"),\n        \"t1\": p(\"t1\"),\n        \"t1ce\": p(\"t1ce\"),\n        \"t2\": p(\"t2\"),\n        \"seg\": p(\"seg\"),\n    }\n\ndef clamp_patch_start(center, patch, max_size):\n    \"\"\"\n    Given center index, patch size, and max dimension size,\n    return start index such that patch fits in [0, max_size).\n    \"\"\"\n    half = patch // 2\n    start = int(center - half)\n    start = max(0, start)\n    start = min(start, max_size - patch)\n    return start\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:07.487587Z","iopub.execute_input":"2026-02-03T13:28:07.487857Z","iopub.status.idle":"2026-02-03T13:28:07.499701Z","shell.execute_reply.started":"2026-02-03T13:28:07.487827Z","shell.execute_reply":"2026-02-03T13:28:07.499212Z"}},"outputs":[],"execution_count":41},{"cell_type":"markdown","source":"## Random augmentations (flips + intensity)","metadata":{}},{"cell_type":"code","source":"def random_flip_3d(x, y, rng):\n    \"\"\"\n    x: (C, X, Y, Z), y: (X, Y, Z)\n    Random flips along spatial axes.\n    \"\"\"\n    # axes in x are (1,2,3) correspond to X,Y,Z\n    for axis in [1, 2, 3]:\n        if rng.random() < 0.5:\n            x = np.flip(x, axis=axis).copy()\n            # y axes are (0,1,2) correspond to X,Y,Z\n            y = np.flip(y, axis=axis-1).copy()\n    return x, y\n\ndef random_intensity(x, rng, p=0.5, scale_range=(0.9, 1.1), shift_range=(-0.1, 0.1)):\n    \"\"\"\n    Apply intensity scaling and shifting per channel (only on non-zero voxels).\n    x: (C, X, Y, Z)\n    \"\"\"\n    if rng.random() > p:\n        return x\n    \n    x_aug = x.copy()\n    for c in range(x.shape[0]):\n        scale = rng.uniform(*scale_range)\n        shift = rng.uniform(*shift_range)\n        mask = x_aug[c] != 0\n        x_aug[c][mask] = x_aug[c][mask] * scale + shift\n    return x_aug\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:07.502621Z","iopub.execute_input":"2026-02-03T13:28:07.502873Z","iopub.status.idle":"2026-02-03T13:28:07.511148Z","shell.execute_reply.started":"2026-02-03T13:28:07.502854Z","shell.execute_reply":"2026-02-03T13:28:07.510477Z"}},"outputs":[],"execution_count":42},{"cell_type":"markdown","source":"## Patch extractor (tumor-centered / random)","metadata":{}},{"cell_type":"code","source":"PATCH_SIZE = (96, 96, 96)  # (X, Y, Z)\nTUMOR_CENTER_PROB = 0.7\n\ndef extract_patch(x, y, rng, tumor_center_prob=TUMOR_CENTER_PROB, patch_size=PATCH_SIZE):\n    \"\"\"\n    x: (C, X, Y, Z)\n    y: (X, Y, Z) labels remapped {0,1,2,3}\n    returns patch_x: (C, px, py, pz), patch_y: (px, py, pz)\n    \"\"\"\n    X, Y, Z = y.shape\n    px, py, pz = patch_size\n\n    # tumor voxels are {1,2,3}\n    tumor_mask = np.isin(y, [1,2,3])\n    use_tumor = (tumor_mask.sum() > 0) and (rng.random() < tumor_center_prob)\n\n    if use_tumor:\n        coords = np.array(np.where(tumor_mask))\n        idx = rng.integers(0, coords.shape[1])\n        cx, cy, cz = coords[:, idx]\n    else:\n        cx = rng.integers(0, X)\n        cy = rng.integers(0, Y)\n        cz = rng.integers(0, Z)\n\n    sx = clamp_patch_start(cx, px, X)\n    sy = clamp_patch_start(cy, py, Y)\n    sz = clamp_patch_start(cz, pz, Z)\n\n    patch_x = x[:, sx:sx+px, sy:sy+py, sz:sz+pz]\n    patch_y = y[sx:sx+px, sy:sy+py, sz:sz+pz]\n    return patch_x, patch_y\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:07.511894Z","iopub.execute_input":"2026-02-03T13:28:07.512121Z","iopub.status.idle":"2026-02-03T13:28:07.527657Z","shell.execute_reply.started":"2026-02-03T13:28:07.512101Z","shell.execute_reply":"2026-02-03T13:28:07.527106Z"}},"outputs":[],"execution_count":43},{"cell_type":"markdown","source":"## BraTS Dataset (lazy loading + preprocessing + patch sampling)","metadata":{}},{"cell_type":"code","source":"class Brats3DPatchDataset(Dataset):\n    def __init__(\n        self,\n        case_dirs,\n        do_crop=True,\n        patches_per_case=4,\n        patch_size=PATCH_SIZE,\n        tumor_center_prob=TUMOR_CENTER_PROB,\n        augment=True,\n        seed=42\n    ):\n        self.case_dirs = case_dirs\n        self.do_crop = do_crop\n        self.patches_per_case = patches_per_case\n        self.patch_size = patch_size\n        self.tumor_center_prob = tumor_center_prob\n        self.augment = augment\n        self.seed = seed\n\n        # \"virtual length\": each case yields multiple patches\n        self._length = len(case_dirs) * patches_per_case\n\n    def __len__(self):\n        return self._length\n\n    def __getitem__(self, idx):\n        # map idx -> case index\n        case_idx = idx // self.patches_per_case\n        case_dir = self.case_dirs[case_idx]\n        pid = os.path.basename(case_dir)\n\n        # per-sample RNG: deterministic but different per idx\n        rng = np.random.default_rng(self.seed + idx)\n\n        # load volumes lazily\n        paths = get_case_paths_from_dir(case_dir)\n        imgs_dict = {\n            \"flair\": load_nii_fdata(paths[\"flair\"]),\n            \"t1\": load_nii_fdata(paths[\"t1\"]),\n            \"t1ce\": load_nii_fdata(paths[\"t1ce\"]),\n            \"t2\": load_nii_fdata(paths[\"t2\"]),\n            \"seg\": load_nii_fdata(paths[\"seg\"]),\n        }\n\n        # preprocess (from Section 4)\n        x, y, meta = preprocess_case(imgs_dict, do_crop=self.do_crop)  # x: (4,X,Y,Z), y:(X,Y,Z) remapped\n\n        # sample patch\n        patch_x, patch_y = extract_patch(x, y, rng, tumor_center_prob=self.tumor_center_prob, patch_size=self.patch_size)\n\n        # augmentations\n        if self.augment:\n            patch_x = random_intensity(patch_x, rng, p=0.5)\n            patch_x, patch_y = random_flip_3d(patch_x, patch_y, rng)\n\n        # to torch\n        patch_x = torch.from_numpy(patch_x).float()        # (C, X, Y, Z)\n        patch_y = torch.from_numpy(patch_y).long()         # (X, Y, Z)\n\n        return {\n            \"id\": pid,\n            \"image\": patch_x,\n            \"label\": patch_y\n        }\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:07.528366Z","iopub.execute_input":"2026-02-03T13:28:07.528566Z","iopub.status.idle":"2026-02-03T13:28:07.543464Z","shell.execute_reply.started":"2026-02-03T13:28:07.528547Z","shell.execute_reply":"2026-02-03T13:28:07.542821Z"}},"outputs":[],"execution_count":44},{"cell_type":"markdown","source":"## DataLoaders","metadata":{}},{"cell_type":"code","source":"BATCH_SIZE = 2\nNUM_WORKERS = 2\n\ntrain_ds = Brats3DPatchDataset(\n    train_dirs,\n    do_crop=True,\n    patches_per_case=4,\n    patch_size=PATCH_SIZE,\n    tumor_center_prob=0.7,\n    augment=True,\n    seed=42\n)\n\nval_ds = Brats3DPatchDataset(\n    val_dirs,\n    do_crop=True,\n    patches_per_case=2,          \n    patch_size=PATCH_SIZE,\n    tumor_center_prob=0.7,      \n    augment=False,\n    seed=999\n)\n\ntrain_loader = DataLoader(train_ds, batch_size=BATCH_SIZE, shuffle=True, num_workers=NUM_WORKERS, pin_memory=True)\nval_loader = DataLoader(val_ds, batch_size=1, shuffle=False, num_workers=NUM_WORKERS, pin_memory=True)\n\nprint(\"Train dataset length (patches):\", len(train_ds))\nprint(\"Val dataset length (patches):\", len(val_ds))\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:07.544379Z","iopub.execute_input":"2026-02-03T13:28:07.544608Z","iopub.status.idle":"2026-02-03T13:28:07.561161Z","shell.execute_reply.started":"2026-02-03T13:28:07.544589Z","shell.execute_reply":"2026-02-03T13:28:07.560497Z"}},"outputs":[{"name":"stdout","text":"Train dataset length (patches): 4000\nVal dataset length (patches): 502\n","output_type":"stream"}],"execution_count":45},{"cell_type":"markdown","source":"## Sanity check: one batch shapes + label distribution","metadata":{}},{"cell_type":"code","source":"batch = next(iter(train_loader))\nx_b = batch[\"image\"]\ny_b = batch[\"label\"]\n\nprint(\"Batch image shape:\", tuple(x_b.shape))  # (B, C, X, Y, Z)\nprint(\"Batch label shape:\", tuple(y_b.shape))  # (B, X, Y, Z)\nprint(\"Unique labels in batch:\", torch.unique(y_b))\n\n# Tumor ratio quick check\ntumor_vox = (y_b != 0).sum().item()\ntotal_vox = y_b.numel()\nprint(\"Tumor voxels ratio in batch:\", tumor_vox / total_vox)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:07.56205Z","iopub.execute_input":"2026-02-03T13:28:07.56232Z","iopub.status.idle":"2026-02-03T13:28:13.670932Z","shell.execute_reply.started":"2026-02-03T13:28:07.562299Z","shell.execute_reply":"2026-02-03T13:28:13.670044Z"}},"outputs":[{"name":"stdout","text":"Batch image shape: (2, 4, 96, 96, 96)\nBatch label shape: (2, 96, 96, 96)\nUnique labels in batch: tensor([0, 1, 2, 3])\nTumor voxels ratio in batch: 0.14386947066695602\n","output_type":"stream"}],"execution_count":46},{"cell_type":"markdown","source":"# Baseline 3D U-Net","metadata":{}},{"cell_type":"code","source":"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nclass ConvBlock3D(nn.Module):\n    def __init__(self, in_ch, out_ch, groups=8):\n        super().__init__()\n        g1 = min(groups, out_ch)\n        self.conv1 = nn.Conv3d(in_ch, out_ch, kernel_size=3, padding=1, bias=False)\n        self.gn1 = nn.GroupNorm(g1, out_ch)\n        self.conv2 = nn.Conv3d(out_ch, out_ch, kernel_size=3, padding=1, bias=False)\n        self.gn2 = nn.GroupNorm(g1, out_ch)\n        self.act = nn.LeakyReLU(0.01, inplace=True)\n\n    def forward(self, x):\n        x = self.act(self.gn1(self.conv1(x)))\n        x = self.act(self.gn2(self.conv2(x)))\n        return x\n\nclass Down3D(nn.Module):\n    def __init__(self, in_ch, out_ch, groups=8):\n        super().__init__()\n        self.pool = nn.MaxPool3d(2)\n        self.block = ConvBlock3D(in_ch, out_ch, groups=groups)\n\n    def forward(self, x):\n        x = self.pool(x)\n        x = self.block(x)\n        return x\n\nclass Up3D(nn.Module):\n    def __init__(self, in_ch, skip_ch, out_ch, groups=8):\n        super().__init__()\n        self.up = nn.ConvTranspose3d(in_ch, out_ch, kernel_size=2, stride=2, bias=False)\n        self.block = ConvBlock3D(out_ch + skip_ch, out_ch, groups=groups)\n\n    def forward(self, x, skip):\n        x = self.up(x)\n\n        # handle odd shapes by padding (rare, but safe)\n        diffX = skip.size(2) - x.size(2)\n        diffY = skip.size(3) - x.size(3)\n        diffZ = skip.size(4) - x.size(4)\n        if diffX != 0 or diffY != 0 or diffZ != 0:\n            x = F.pad(x, [diffZ//2, diffZ - diffZ//2,\n                          diffY//2, diffY - diffY//2,\n                          diffX//2, diffX - diffX//2])\n\n        x = torch.cat([skip, x], dim=1)\n        x = self.block(x)\n        return x\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:13.672522Z","iopub.execute_input":"2026-02-03T13:28:13.672858Z","iopub.status.idle":"2026-02-03T13:28:13.682814Z","shell.execute_reply.started":"2026-02-03T13:28:13.672828Z","shell.execute_reply":"2026-02-03T13:28:13.682256Z"}},"outputs":[],"execution_count":47},{"cell_type":"markdown","source":"## 3D U-Net model","metadata":{}},{"cell_type":"code","source":"class UNet3D(nn.Module):\n    def __init__(self, in_channels=4, num_classes=4, base=32, groups=8):\n        super().__init__()\n        self.inc = ConvBlock3D(in_channels, base, groups=groups)\n        self.down1 = Down3D(base, base*2, groups=groups)\n        self.down2 = Down3D(base*2, base*4, groups=groups)\n        self.down3 = Down3D(base*4, base*8, groups=groups)\n\n        self.bottleneck = ConvBlock3D(base*8, base*16, groups=groups)\n\n        self.up3 = Up3D(base*16, base*8, base*8, groups=groups)\n        self.up2 = Up3D(base*8, base*4, base*4, groups=groups)\n        self.up1 = Up3D(base*4, base*2, base*2, groups=groups)\n        self.up0 = Up3D(base*2, base, base, groups=groups)\n\n        self.outc = nn.Conv3d(base, num_classes, kernel_size=1)\n\n    def forward(self, x):\n        x1 = self.inc(x)       # base\n        x2 = self.down1(x1)    # base*2\n        x3 = self.down2(x2)    # base*4\n        x4 = self.down3(x3)    # base*8\n\n        xb = self.bottleneck(x4)  # base*16\n\n        x = self.up3(xb, x4)\n        x = self.up2(x,  x3)\n        x = self.up1(x,  x2)\n        x = self.up0(x,  x1)\n\n        logits = self.outc(x)  # (B, num_classes, X, Y, Z)\n        return logits\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:13.683983Z","iopub.execute_input":"2026-02-03T13:28:13.684401Z","iopub.status.idle":"2026-02-03T13:28:13.698502Z","shell.execute_reply.started":"2026-02-03T13:28:13.684377Z","shell.execute_reply":"2026-02-03T13:28:13.697835Z"}},"outputs":[],"execution_count":48},{"cell_type":"markdown","source":"## Instantiate + forward sanity check","metadata":{}},{"cell_type":"code","source":"device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\nprint(\"Device:\", device)\n\nmodel = UNet3D(in_channels=4, num_classes=4, base=32, groups=8).to(device)\nprint(\"Model params (M):\", sum(p.numel() for p in model.parameters()) / 1e6)\n\nbatch = next(iter(train_loader))\nx = batch[\"image\"].to(device)  # (B, C, X, Y, Z)\nwith torch.no_grad():\n    logits = model(x)\nprint(\"Input shape:\", tuple(x.shape))\nprint(\"Logits shape:\", tuple(logits.shape))\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:13.699458Z","iopub.execute_input":"2026-02-03T13:28:13.699691Z","iopub.status.idle":"2026-02-03T13:28:19.811492Z","shell.execute_reply.started":"2026-02-03T13:28:13.69967Z","shell.execute_reply":"2026-02-03T13:28:19.810757Z"}},"outputs":[{"name":"stdout","text":"Device: cuda\nModel params (M): 22.580484\nInput shape: (2, 4, 96, 96, 96)\nLogits shape: (2, 4, 96, 96, 96)\n","output_type":"stream"}],"execution_count":49},{"cell_type":"markdown","source":"# Loss & Metrics","metadata":{}},{"cell_type":"code","source":"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\ndef soft_dice_loss_multiclass(logits, target, num_classes=4, eps=1e-6):\n    \"\"\"\n    logits: (B, C, X, Y, Z)\n    target: (B, X, Y, Z) int64 in [0..C-1]\n    Computes average soft dice across classes excluding background (0).\n    \"\"\"\n    probs = F.softmax(logits, dim=1)  # (B,C,...)\n\n    # one-hot target\n    target_oh = F.one_hot(target, num_classes=num_classes)  # (B, X, Y, Z, C)\n    target_oh = target_oh.permute(0, 4, 1, 2, 3).float()    # (B, C, X, Y, Z)\n\n    # exclude background from dice loss\n    probs_fg = probs[:, 1:, ...]\n    target_fg = target_oh[:, 1:, ...]\n\n    dims = (0, 2, 3, 4)\n    inter = torch.sum(probs_fg * target_fg, dims)\n    denom = torch.sum(probs_fg + target_fg, dims)\n\n    dice = (2.0 * inter + eps) / (denom + eps)\n    loss = 1.0 - dice.mean()\n    return loss\n\nce_loss_fn = nn.CrossEntropyLoss()\n\ndef combined_loss(logits, target, ce_w=0.5, dice_w=0.5):\n    ce = ce_loss_fn(logits, target)\n    dice = soft_dice_loss_multiclass(logits, target, num_classes=logits.shape[1])\n    return ce_w * ce + dice_w * dice, ce.detach(), dice.detach()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:19.812821Z","iopub.execute_input":"2026-02-03T13:28:19.813073Z","iopub.status.idle":"2026-02-03T13:28:19.819905Z","shell.execute_reply.started":"2026-02-03T13:28:19.813046Z","shell.execute_reply":"2026-02-03T13:28:19.819325Z"}},"outputs":[],"execution_count":50},{"cell_type":"markdown","source":"## Region metrics (WT/TC/ET) + Mean Dice","metadata":{}},{"cell_type":"code","source":"def dice_binary_torch(pred, gt, eps=1e-8):\n    \"\"\"\n    pred, gt: boolean tensors with same shape\n    \"\"\"\n    pred = pred.bool()\n    gt = gt.bool()\n    inter = (pred & gt).sum().float()\n    return (2.0 * inter + eps) / (pred.sum().float() + gt.sum().float() + eps)\n\n@torch.no_grad()\ndef brats_region_dice_from_logits(logits, target):\n    \"\"\"\n    logits: (B, C, X, Y, Z)\n    target: (B, X, Y, Z) int64 in [0..3] after remap\n    Regions (after remap):\n      WT: {1,2,3}\n      TC: {1,3}\n      ET: {3}\n    \"\"\"\n    pred = torch.argmax(logits, dim=1)  # (B,X,Y,Z)\n\n    wt_pred = (pred != 0)\n    wt_gt   = (target != 0)\n\n    tc_pred = (pred == 1) | (pred == 3)\n    tc_gt   = (target == 1) | (target == 3)\n\n    et_pred = (pred == 3)\n    et_gt   = (target == 3)\n\n    d_wt = dice_binary_torch(wt_pred, wt_gt).item()\n    d_tc = dice_binary_torch(tc_pred, tc_gt).item()\n    d_et = dice_binary_torch(et_pred, et_gt).item()\n    mean = (d_wt + d_tc + d_et) / 3.0\n    return {\"WT\": d_wt, \"TC\": d_tc, \"ET\": d_et, \"Mean\": mean}\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:19.820897Z","iopub.execute_input":"2026-02-03T13:28:19.821129Z","iopub.status.idle":"2026-02-03T13:28:19.838268Z","shell.execute_reply.started":"2026-02-03T13:28:19.821109Z","shell.execute_reply":"2026-02-03T13:28:19.837516Z"}},"outputs":[],"execution_count":51},{"cell_type":"markdown","source":"## Sanity check on one batch (loss + metrics run)","metadata":{}},{"cell_type":"code","source":"batch = next(iter(train_loader))\nx = batch[\"image\"].to(device)\ny = batch[\"label\"].to(device)\n\nmodel.eval()\nwith torch.no_grad():\n    logits = model(x)\n\nloss, ce, dice = combined_loss(logits, y, ce_w=0.5, dice_w=0.5)\nmetrics = brats_region_dice_from_logits(logits, y)\n\nprint(\"Loss:\", float(loss), \"| CE:\", float(ce), \"| DiceLoss:\", float(dice))\nprint(\"Metrics:\", metrics)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:19.838967Z","iopub.execute_input":"2026-02-03T13:28:19.839157Z","iopub.status.idle":"2026-02-03T13:28:26.841751Z","shell.execute_reply.started":"2026-02-03T13:28:19.839138Z","shell.execute_reply":"2026-02-03T13:28:26.840886Z"}},"outputs":[{"name":"stdout","text":"Loss: 1.1703529357910156 | CE: 1.3768141269683838 | DiceLoss: 0.9638916850090027\nMetrics: {'WT': 0.10120207071304321, 'TC': 0.03189205378293991, 'ET': 0.03533950448036194, 'Mean': 0.05614454299211502}\n","output_type":"stream"}],"execution_count":52},{"cell_type":"markdown","source":"# Training Loop + Validation + Checkpoints + Logging","metadata":{}},{"cell_type":"markdown","source":"## Optimizer + AMP + checkpoint paths","metadata":{}},{"cell_type":"code","source":"import os\nimport time\nimport torch\n\nEPOCHS = 10 \nLR = 1e-3\nWEIGHT_DECAY = 1e-4\n\nCHECKPOINT_DIR = \"/kaggle/working/checkpoints\"\nos.makedirs(CHECKPOINT_DIR, exist_ok=True)\n\nbest_ckpt_path = os.path.join(CHECKPOINT_DIR, \"best_model.pt\")\n\noptimizer = torch.optim.AdamW(model.parameters(), lr=LR, weight_decay=WEIGHT_DECAY)\nscaler = torch.cuda.amp.GradScaler(enabled=(device.type == \"cuda\"))\n\nprint(\"Training config:\")\nprint(\"EPOCHS:\", EPOCHS)\nprint(\"LR:\", LR)\nprint(\"Weight decay:\", WEIGHT_DECAY)\nprint(\"AMP enabled:\", scaler.is_enabled())\nprint(\"Checkpoint:\", best_ckpt_path)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:26.843001Z","iopub.execute_input":"2026-02-03T13:28:26.843281Z","iopub.status.idle":"2026-02-03T13:28:26.850409Z","shell.execute_reply.started":"2026-02-03T13:28:26.843254Z","shell.execute_reply":"2026-02-03T13:28:26.849595Z"}},"outputs":[{"name":"stdout","text":"Training config:\nEPOCHS: 10\nLR: 0.001\nWeight decay: 0.0001\nAMP enabled: True\nCheckpoint: /kaggle/working/checkpoints/best_model.pt\n","output_type":"stream"},{"name":"stderr","text":"/tmp/ipykernel_55/562633147.py:15: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.\n  scaler = torch.cuda.amp.GradScaler(enabled=(device.type == \"cuda\"))\n","output_type":"stream"}],"execution_count":53},{"cell_type":"markdown","source":"## Train one epoch","metadata":{}},{"cell_type":"code","source":"def train_one_epoch(model, loader, optimizer, scaler, device):\n    model.train()\n    running_loss = 0.0\n    running_ce = 0.0\n    running_dice = 0.0\n    n = 0\n\n    for batch in loader:\n        x = batch[\"image\"].to(device, non_blocking=True)\n        y = batch[\"label\"].to(device, non_blocking=True)\n\n        optimizer.zero_grad(set_to_none=True)\n\n        with torch.cuda.amp.autocast(enabled=scaler.is_enabled()):\n            logits = model(x)\n            loss, ce, dice = combined_loss(logits, y, ce_w=0.5, dice_w=0.5)\n\n        scaler.scale(loss).backward()\n        scaler.step(optimizer)\n        scaler.update()\n\n        bs = x.size(0)\n        running_loss += loss.item() * bs\n        running_ce += ce.item() * bs\n        running_dice += dice.item() * bs\n        n += bs\n\n    return {\n        \"loss\": running_loss / n,\n        \"ce\": running_ce / n,\n        \"dice_loss\": running_dice / n\n    }\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:26.851284Z","iopub.execute_input":"2026-02-03T13:28:26.851565Z","iopub.status.idle":"2026-02-03T13:28:26.863704Z","shell.execute_reply.started":"2026-02-03T13:28:26.851536Z","shell.execute_reply":"2026-02-03T13:28:26.862982Z"}},"outputs":[],"execution_count":54},{"cell_type":"markdown","source":"## Validate (Dice WT/TC/ET + Mean)","metadata":{}},{"cell_type":"code","source":"@torch.no_grad()\ndef validate(model, loader, device, max_batches=None):\n    model.eval()\n\n    metrics_sum = {\"WT\": 0.0, \"TC\": 0.0, \"ET\": 0.0, \"Mean\": 0.0}\n    count = 0\n\n    for i, batch in enumerate(loader):\n        x = batch[\"image\"].to(device, non_blocking=True)\n        y = batch[\"label\"].to(device, non_blocking=True)\n\n        logits = model(x)\n        m = brats_region_dice_from_logits(logits, y)\n\n        for k in metrics_sum:\n            metrics_sum[k] += m[k]\n        count += 1\n\n        if max_batches is not None and (i + 1) >= max_batches:\n            break\n\n    for k in metrics_sum:\n        metrics_sum[k] /= max(count, 1)\n\n    return metrics_sum\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:26.864645Z","iopub.execute_input":"2026-02-03T13:28:26.864923Z","iopub.status.idle":"2026-02-03T13:28:26.879492Z","shell.execute_reply.started":"2026-02-03T13:28:26.864892Z","shell.execute_reply":"2026-02-03T13:28:26.878895Z"}},"outputs":[],"execution_count":55},{"cell_type":"markdown","source":"## Full training loop (logging + save best)","metadata":{}},{"cell_type":"code","source":"best_mean = -1.0\nhistory = []\n\nfor epoch in range(1, EPOCHS + 1):\n    t0 = time.time()\n\n    train_stats = train_one_epoch(model, train_loader, optimizer, scaler, device)\n    val_metrics = validate(model, val_loader, device, max_batches=50)  \n\n    epoch_time = time.time() - t0\n\n    log = {\n        \"epoch\": epoch,\n        **train_stats,\n        **{f\"val_{k}\": v for k, v in val_metrics.items()},\n        \"time_sec\": epoch_time\n    }\n    history.append(log)\n\n    print(\n        f\"Epoch {epoch:02d} | \"\n        f\"loss={train_stats['loss']:.4f} (ce={train_stats['ce']:.4f}, dice={train_stats['dice_loss']:.4f}) | \"\n        f\"Val WT={val_metrics['WT']:.4f} TC={val_metrics['TC']:.4f} ET={val_metrics['ET']:.4f} Mean={val_metrics['Mean']:.4f} | \"\n        f\"time={epoch_time:.1f}s\"\n    )\n\n    # Save best checkpoint\n    if val_metrics[\"Mean\"] > best_mean:\n        best_mean = val_metrics[\"Mean\"]\n        torch.save({\n            \"model_state_dict\": model.state_dict(),\n            \"optimizer_state_dict\": optimizer.state_dict(),\n            \"epoch\": epoch,\n            \"best_mean\": best_mean\n        }, best_ckpt_path)\n        print(f\"  ✅ Saved best checkpoint (Mean Dice={best_mean:.4f})\")\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T13:28:26.880331Z","iopub.execute_input":"2026-02-03T13:28:26.880642Z","iopub.status.idle":"2026-02-03T22:29:20.051414Z","shell.execute_reply.started":"2026-02-03T13:28:26.880616Z","shell.execute_reply":"2026-02-03T22:29:20.050589Z"}},"outputs":[{"name":"stderr","text":"/tmp/ipykernel_55/1007588580.py:14: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.\n  with torch.cuda.amp.autocast(enabled=scaler.is_enabled()):\n","output_type":"stream"},{"name":"stdout","text":"Epoch 01 | loss=0.2492 (ce=0.1134, dice=0.3851) | Val WT=0.8514 TC=0.7498 ET=0.7610 Mean=0.7874 | time=3244.5s\n  ✅ Saved best checkpoint (Mean Dice=0.7874)\nEpoch 02 | loss=nan (ce=nan, dice=nan) | Val WT=0.0000 TC=0.0000 ET=0.0000 Mean=0.0000 | time=3188.2s\nEpoch 03 | loss=nan (ce=nan, dice=nan) | Val WT=0.0000 TC=0.0000 ET=0.0000 Mean=0.0000 | time=3220.4s\nEpoch 04 | loss=nan (ce=nan, dice=nan) | Val WT=0.0000 TC=0.0000 ET=0.0000 Mean=0.0000 | time=3245.6s\nEpoch 05 | loss=nan (ce=nan, dice=nan) | Val WT=0.0000 TC=0.0000 ET=0.0000 Mean=0.0000 | time=3263.4s\nEpoch 06 | loss=nan (ce=nan, dice=nan) | Val WT=0.0000 TC=0.0000 ET=0.0000 Mean=0.0000 | time=3282.2s\nEpoch 07 | loss=nan (ce=nan, dice=nan) | Val WT=0.0000 TC=0.0000 ET=0.0000 Mean=0.0000 | time=3264.9s\nEpoch 08 | loss=nan (ce=nan, dice=nan) | Val WT=0.0000 TC=0.0000 ET=0.0000 Mean=0.0000 | time=3255.7s\nEpoch 09 | loss=nan (ce=nan, dice=nan) | Val WT=0.0000 TC=0.0000 ET=0.0000 Mean=0.0000 | time=3252.9s\nEpoch 10 | loss=nan (ce=nan, dice=nan) | Val WT=0.0000 TC=0.0000 ET=0.0000 Mean=0.0000 | time=3234.9s\n","output_type":"stream"}],"execution_count":56},{"cell_type":"code","source":"ckpt = torch.load(best_ckpt_path, map_location=device)\nmodel.load_state_dict(ckpt[\"model_state_dict\"])\nprint(\"Loaded best checkpoint from epoch:\", ckpt[\"epoch\"])\nprint(\"Best Val Mean Dice:\", ckpt[\"best_mean\"])","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:29:20.052757Z","iopub.execute_input":"2026-02-03T22:29:20.053024Z","iopub.status.idle":"2026-02-03T22:29:20.272376Z","shell.execute_reply.started":"2026-02-03T22:29:20.052995Z","shell.execute_reply":"2026-02-03T22:29:20.27161Z"}},"outputs":[{"name":"stdout","text":"Loaded best checkpoint from epoch: 1\nBest Val Mean Dice: 0.7874093928125997\n","output_type":"stream"}],"execution_count":57},{"cell_type":"markdown","source":"# Sliding window inference","metadata":{}},{"cell_type":"code","source":"import numpy as np\nimport torch\nimport torch.nn.functional as F\n\ndef sliding_window_inference(\n    model,\n    x,                      # torch tensor (1, C, X, Y, Z) float32\n    patch_size=(96,96,96),\n    overlap=0.5,\n    num_classes=4,\n    device=\"cuda\"\n):\n    \"\"\"\n    Returns:\n      pred: np.int64 array (X, Y, Z) labels in [0..3]\n    \"\"\"\n    model.eval()\n\n    assert x.ndim == 5 and x.shape[0] == 1, \"Expect x shape (1,C,X,Y,Z)\"\n    _, C, X, Y, Z = x.shape\n    px, py, pz = patch_size\n\n    sx = max(1, int(px * (1 - overlap)))\n    sy = max(1, int(py * (1 - overlap)))\n    sz = max(1, int(pz * (1 - overlap)))\n\n    # Accumulators on CPU to save GPU memory\n    prob_sum = torch.zeros((num_classes, X, Y, Z), dtype=torch.float32, device=\"cpu\")\n    count_map = torch.zeros((1, X, Y, Z), dtype=torch.float32, device=\"cpu\")\n\n    # generate window start indices\n    xs = list(range(0, max(X - px + 1, 1), sx))\n    ys = list(range(0, max(Y - py + 1, 1), sy))\n    zs = list(range(0, max(Z - pz + 1, 1), sz))\n\n    # ensure last window covers the end\n    if xs[-1] != max(X - px, 0): xs.append(max(X - px, 0))\n    if ys[-1] != max(Y - py, 0): ys.append(max(Y - py, 0))\n    if zs[-1] != max(Z - pz, 0): zs.append(max(Z - pz, 0))\n\n    x = x.to(device)\n\n    with torch.no_grad():\n        for x0 in xs:\n            for y0 in ys:\n                for z0 in zs:\n                    patch = x[:, :, x0:x0+px, y0:y0+py, z0:z0+pz]  # (1,C,px,py,pz)\n\n                    # if volume smaller than patch (rare), pad\n                    pad_x = px - patch.shape[2]\n                    pad_y = py - patch.shape[3]\n                    pad_z = pz - patch.shape[4]\n                    if pad_x > 0 or pad_y > 0 or pad_z > 0:\n                        patch = F.pad(patch, [0, max(pad_z,0), 0, max(pad_y,0), 0, max(pad_x,0)])\n\n                    logits = model(patch)  # (1,classes,px,py,pz)\n                    probs = F.softmax(logits, dim=1)[0].to(\"cpu\")  # (classes,px,py,pz)\n\n                    # remove padding if applied\n                    probs = probs[:, :patch.shape[2], :patch.shape[3], :patch.shape[4]]\n\n                    prob_sum[:, x0:x0+px, y0:y0+py, z0:z0+pz] += probs[:, :min(px, X-x0), :min(py, Y-y0), :min(pz, Z-z0)]\n                    count_map[:, x0:x0+px, y0:y0+py, z0:z0+pz] += 1.0\n\n    prob_avg = prob_sum / torch.clamp(count_map, min=1e-6)\n    pred = torch.argmax(prob_avg, dim=0).numpy().astype(np.int64)  # (X,Y,Z)\n    return pred\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:29:20.273491Z","iopub.execute_input":"2026-02-03T22:29:20.273819Z","iopub.status.idle":"2026-02-03T22:29:20.284959Z","shell.execute_reply.started":"2026-02-03T22:29:20.273796Z","shell.execute_reply":"2026-02-03T22:29:20.284158Z"}},"outputs":[],"execution_count":58},{"cell_type":"code","source":"import numpy as np\nfrom scipy import ndimage\n\ndef remove_small_components(binary_mask, min_size=50):\n    \"\"\"\n    binary_mask: np.bool array 3D\n    returns cleaned binary mask\n    \"\"\"\n    labeled, num = ndimage.label(binary_mask)\n    if num == 0:\n        return binary_mask\n\n    counts = np.bincount(labeled.ravel())\n    # counts[0] is background\n    keep = np.zeros_like(counts, dtype=bool)\n    keep[counts >= min_size] = True\n    keep[0] = False\n\n    cleaned = keep[labeled]\n    return cleaned\n\ndef postprocess_et(pred, min_et_size=50):\n    \"\"\"\n    pred: (X,Y,Z) labels in [0..3]\n    ET is label 3 (after remap)\n    removes small ET components\n    \"\"\"\n    pred_pp = pred.copy()\n    et = (pred_pp == 3)\n    et_clean = remove_small_components(et, min_size=min_et_size)\n    pred_pp[et & (~et_clean)] = 0  # drop small ET to background\n    return pred_pp\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:29:20.285888Z","iopub.execute_input":"2026-02-03T22:29:20.286139Z","iopub.status.idle":"2026-02-03T22:29:20.706123Z","shell.execute_reply.started":"2026-02-03T22:29:20.286114Z","shell.execute_reply":"2026-02-03T22:29:20.705376Z"}},"outputs":[],"execution_count":59},{"cell_type":"code","source":"import numpy as np\nimport matplotlib.pyplot as plt\n\ndef load_case_arrays(case_dir):\n    paths = get_case_paths_from_dir(case_dir)\n    imgs_dict = {\n        \"flair\": load_nii_fdata(paths[\"flair\"]),\n        \"t1\": load_nii_fdata(paths[\"t1\"]),\n        \"t1ce\": load_nii_fdata(paths[\"t1ce\"]),\n        \"t2\": load_nii_fdata(paths[\"t2\"]),\n        \"seg\": load_nii_fdata(paths[\"seg\"]),\n    }\n    return imgs_dict\n\n# pick one validation case\ntest_case_dir = val_dirs[0]\npid = os.path.basename(test_case_dir)\nprint(\"Running full-volume inference for:\", pid)\n\nimgs_dict = load_case_arrays(test_case_dir)\n\n# preprocess (same as training): normalize + crop + remap\nx_np, y_np, meta = preprocess_case(imgs_dict, do_crop=True)  # x_np (4,X,Y,Z), y_np (X,Y,Z)\nx_t = torch.from_numpy(x_np[None]).float()  # (1,4,X,Y,Z)\n\npred = sliding_window_inference(\n    model, x_t, patch_size=PATCH_SIZE, overlap=0.5, num_classes=4, device=device\n)\n\npred_pp = postprocess_et(pred, min_et_size=50)\n\nprint(\"Shapes:\")\nprint(\"x:\", x_np.shape, \"y:\", y_np.shape, \"pred:\", pred.shape)\n\n# visualize on tumor-max slice\nz = tumor_max_slice(y_np)  # works with remapped y too\nflair = x_np[0]\n\nplt.figure(figsize=(14,4))\nplt.subplot(1,3,1); plt.title(f\"{pid} FLAIR z={z}\")\nplt.imshow(flair[:,:,z].T, origin=\"lower\", cmap=\"gray\"); plt.axis(\"off\")\n\nplt.subplot(1,3,2); plt.title(\"GT (remapped)\")\nplt.imshow(y_np[:,:,z].T, origin=\"lower\"); plt.axis(\"off\")\n\nplt.subplot(1,3,3); plt.title(\"Pred (postprocessed)\")\nplt.imshow(pred_pp[:,:,z].T, origin=\"lower\"); plt.axis(\"off\")\nplt.show()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:29:20.707163Z","iopub.execute_input":"2026-02-03T22:29:20.707725Z","iopub.status.idle":"2026-02-03T22:29:25.535576Z","shell.execute_reply.started":"2026-02-03T22:29:20.707689Z","shell.execute_reply":"2026-02-03T22:29:25.534998Z"}},"outputs":[{"name":"stdout","text":"Running full-volume inference for: BraTS2021_01605\nShapes:\nx: (4, 135, 184, 140) y: (135, 184, 140) pred: (135, 184, 140)\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1400x400 with 3 Axes>","image/png":"iVBORw0KGgoAAAANSUhEUgAABAEAAAFeCAYAAAD0YwadAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs/XeYXWW5/4+/d++zp2QmlRQIITQJoqiAkgiCQgAVRLHQFFRQ9HMsx/JFwaMiKgqiKIqiIihNjseCiGLBchRRRKohhJA6mb737F7W74/83k/u9cxae+8JyYQj9+u69jWz117raWtNed/tCTiO40BRFEVRFEVRFEVRlH97gnt6AIqiKIqiKIqiKIqizAxqBFAURVEURVEURVGU5whqBFAURVEURVEURVGU5whqBFAURVEURVEURVGU5whqBFAURVEURVEURVGU5whqBFAURVEURVEURVGU5whqBFAURVEURVEURVGU5whqBFAURVEURVEURVGU5whqBFAURVEURVEURVGU5whqBFAURVGUZyEnnHACzjvvvD09jH8rAoEALrnkEvP+a1/7GhYuXIhKpbLnBqUoyv9JFi9ejLPPPrujczds2IB4PI4//OEPu3dQyh7j7LPPxuLFi837kZERpFIp/OxnP9tzg2rBtIwA3/72txEIBFyvgYEBrFq1CnfeeecuHdjZZ589pS+vF3/4ms0mvvvd7+JFL3oRent7kclksGzZMpx55pn43//9X9PuY489hg9+8INYsWIFMpkM5s6dixNPPBF//etfPcexadMmnH766eju7kZXVxdOOeUUPPnkk65zNmzYgEsvvRSHH344enp6MGvWLKxcuRK//OUvp7S3ZcsWfOhDH8KqVauQyWQQCATwm9/8ZqfXaXx8HOeffz76+/uRSqWwatUq/O1vf5ty3s0334w3v/nN2HfffREIBLBy5cqW7f7tb3/DySefjN7eXiSTSRx00EH40pe+NOW8P/7xjzjqqKOQTCYxZ84cXHTRRZicnHSd85vf/Mb3/sl740erZ+HnP/85AOCpp55CIBDA5z//+bbtkQ9+8IMIBAJ4/etf7/m5V5v2XEKhEAYGBnDaaafh0Ucf7bjv3cktt9yCF7/4xeju7kZfXx+OPvpo/PSnP3Wds3nzZrz5zW/Gfvvth0wmg+7ubhx++OH4zne+A8dx9tDIFeXZzbp16/Cud70Ly5YtQzKZRDKZxAEHHIALL7wQDz74IABg5cqVHf3tkkLUiz/84Q/4xS9+gf/8z/+cgZk9dzn77LNRrVZx7bXX7umhKIoyDWxNEo/HsWzZMrzrXe/C4ODgnh7eFD7xiU/gRS96EY488sg9Oo5HHnkEl1xyCZ566qk9Oo7nAn19fXjb296Giy++eE8PxZPwzlz0iU98AkuWLIHjOBgcHMS3v/1tnHDCCfjxj3+M1atX75KBvf3tb8exxx5r3q9btw4f+9jHcP755+OlL32pOb7PPvsAAC666CJ85StfwSmnnII3velNCIfDePzxx3HnnXdi7733xotf/GIAwHXXXYdvfvObOPXUU3HBBRdgYmIC1157LV784hfj5z//uavPyclJrFq1ChMTE/jIRz6CSCSCL37xizj66KPxwAMPoK+vDwDwox/9CJdffjle/epX46yzzkK9Xsd3v/tdvOIVr8C3vvUtnHPOOabNxx9/HJdffjn23XdfHHzwwfjTn/6002vUbDZx4okn4h//+Ac+8IEPYNasWbjmmmuwcuVK3H///dh3333NuV/96ldx//3344UvfCFGRkZatvuLX/wCJ510Eg499FBcfPHFSKfTWLt2LTZu3Og674EHHsAxxxyD/fffH1/4whewceNGfP7zn8eaNWs8jUIXXXQRXvjCF7qOLV26tKO5xmIxXHfddVOOH3LIIR1db+M4Dr7//e9j8eLF+PGPf4x8Po9MJtPx9ZxLrVbDgw8+iK997Wv4zW9+g4ceeghz5szZqTHtCq6++mpcdNFFOPHEE/GZz3wG5XIZ3/72t7F69WrcfvvteO1rXwsAGB4exsaNG3Haaadh4cKFqNVquPvuu3H22Wfj8ccfx6c//ek9NgdFeTbyk5/8BK9//esRDofxpje9CYcccgiCwSAee+wx/PCHP8RXv/pVrFu3Dh/96Efxtre9zVx333334Utf+hI+8pGPYP/99zfHn/e857Xs73Of+xyOOeaYjn9HKjtHPB7HWWedhS984Qt497vfjUAgsKeHpCjKNKAmKZfL+P3vf4+vfvWr+NnPfoaHHnoIyWRyTw8PADA0NITvfOc7+M53vrOnh4JHHnkEl156KVauXOnyWiu7h3e84x340pe+hHvuuQcvf/nL9/Rw3DjT4Prrr3cAOPfdd5/r+OjoqBOJRJw3vvGNLa+v1WpOpVKZTpeG++67zwHgXH/99VM+27p1qxMIBJzzzjtvymfNZtMZHBw07//61786+Xzedc7w8LDT39/vHHnkka7jl19+uQPA+ctf/mKOPfroo04oFHI+/OEPm2MPPfSQMzQ05Lq2XC47y5cvdxYsWOA6nsvlnJGREcdxHOfWW291ADi//vWvW0/eh5tvvtkB4Nx6663m2LZt25zu7m7njDPOcJ379NNPO41Gw3EcxznwwAOdo48+2rPNiYkJZ/bs2c5rXvMac74fr3rVq5y5c+c6ExMT5tg3vvENB4Bz1113mWO//vWvp4xzOpx11llOKpVqec66descAM7nPve5jtq85557HADOPffc40QiEefb3/52R236zeWrX/2qA8C5/PLLO+p/d7Hvvvs6L3zhC51ms2mOTUxMOOl02jn55JPbXr969WonlUo59Xp9dw5TUf5P8cQTTzipVMrZf//9nc2bN0/5vFarOVdddZXz9NNPT/lsZ37PDw4OOuFw2Lnuuuvanjs5Odlxu4rjAHA+/vGPu4799a9/dQA4v/rVr/bMoBRFmTZ+muQ//uM/HADOTTfd5Hvtrvq9uWjRIuess85qe94XvvAFJ5FITNEfe4Jnqj380L9F2/XKokWLphw/6KCDnLe85S0zP6A27JKaAN3d3UgkEgiHdwQWyFDqK6+8Evvssw9isRgeeeQRVKtVfOxjH8Nhhx2GbDaLVCqFl770pfj1r3+9U/2vW7cOjuN4htgwZYEcdthhSKfTrnP6+vrw0pe+dEo492233YYXvvCFLu/18uXLccwxx+CWW24xxw488EDMmjXLdW0sFsMJJ5yAjRs3Ip/Pm+OZTAa9vb07NU+b2267DbNnzzbeXQDo7+/H6aefjh/96EeuHMe99toLwWD7233TTTdhcHAQn/rUpxAMBlEoFNBsNqecl8vlcPfdd+PNb34zurq6zPEzzzwT6XTatT6SfD6Per0+nWnuFm688UYccMABWLVqFY499ljceOONz6g9RqesXbu25Xn8ufB7PVNyuRwGBgZcbXV1dSGdTiORSLS9fvHixSgWi6hWq894LIry78JnP/tZFAoFXH/99Zg7d+6Uz8PhMC666CLstddeu6S/n/70p6jX667INGBH+Otvf/tbXHDBBRgYGMCCBQvM53feeSde+tKXIpVKIZPJ4MQTT8TDDz/sauPss89GOp3G008/jdWrVyOdTmP+/Pn4yle+AgD45z//iZe//OVIpVJYtGgRbrrpJtf1o6OjeP/734+DDz4Y6XQaXV1deNWrXoV//OMfrvOYOnXzzTfjIx/5CObMmYNUKoWTTz4ZGzZscJ27cuVKHHTQQbj//vtxxBFHIJFIYMmSJfja1742ZW0qlQo+/vGPY+nSpYjFYthrr73wwQ9+cEpOf6VSwf/7f/8P/f39yGQyOPnkk6dEs5HDDjsMvb29+NGPfuT5uaIo/3egt3XdunUAdvzOW7t2LU444QRkMhm86U1vArA9ovbKK6/EgQceiHg8jtmzZ+Ptb387xsbGXG06joNPfvKTWLBgAZLJJFatWjXld2sr/vu//xsvetGLpuiP6fzu27ZtG9761rdi9uzZiMfjOOSQQzwjC37wgx/gsMMOQyaTQVdXFw4++GBcddVVALb/DXnd614HAFi1apX535NpyYsXL8bq1avxi1/8AitWrEA8HscBBxyAH/7wh64+2v0tuuaaa3DggQciFoth3rx5uPDCCzE+Pj5lrH/+859xwgknoKenB6lUCs973vPMWMljjz2G0047Db29vYjH43jBC16A//mf/3GdU6vVcOmll2LfffdFPB5HX18fjjrqKNx9993mnK1bt+Kcc87BggULEIvFMHfuXJxyyilT0iI6+TsKbL+nBx10EOLxOA466CDccccdU84hr3jFK/DjH//4WZduu1NGgImJCQwPD2NoaAgPP/ww3vnOd2JychJvfvObp5x7/fXX4+qrr8b555+PK664Ar29vcjlcrjuuuuwcuVKXH755bjkkkswNDSE448/Hg888MC0x7No0SIAwK233opisbgzU8LWrVtdQr7ZbOLBBx/EC17wginnHn744Vi7dq1L3Pu1ybzR3cHf//53PP/5z58i7g8//HAUi0X861//mnabv/zlL9HV1YVNmzZhv/32M//kvfOd70S5XDbn/fOf/0S9Xp+yPtFoFCtWrMDf//73KW2fc8456OrqQjwex6pVq3zrMPgxPDzsek1MTEx7fsD2fw5vv/12nHHGGQCAM844A/fccw+2bt26U+0BML9Eenp6Wp7X39+PG264wfX61re+hWw2i/7+fnNesVicMl+vl/2HauXKlfj5z3+Oq6++Gk899RQee+wxXHjhhZiYmMB73vOeKeMplUoYHh7GU089he985zu4/vrr8ZKXvKQjg4GiPFf4yU9+gqVLl+JFL3rRjPT3xz/+EX19feZvm80FF1yARx55BB/72MfwoQ99CABwww034MQTT0Q6ncbll1+Oiy++GI888giOOuqoKf/kNBoNvOpVr8Jee+2Fz372s1i8eDHe9a534dvf/jZe+cpX4gUveAEuv/xyZDIZnHnmmeafaQB48skn8d///d9YvXo1vvCFL+ADH/gA/vnPf+Loo4/G5s2bp4z1U5/6FH7605/iP//zP3HRRRfh7rvvxrHHHotSqeQ6b2xsDCeccAIOO+wwfPazn8WCBQvwzne+E9/61rfMOc1mEyeffDI+//nP46STTsLVV1+NV7/61fjiF784pbbL2972Nlx55ZU47rjj8JnPfAaRSAQnnnii75o///nP14JdivJvAJ0xTNkFgHq9juOPPx4DAwP4/Oc/j1NPPRXA9tTjD3zgAzjyyCNx1VVX4ZxzzsGNN96I448/HrVazVz/sY99DBdffDEOOeQQfO5zn8Pee++N4447DoVCoe14arUa7rvvPjz/+c/3/LyT332lUgkrV67EDTfcgDe96U343Oc+h2w2i7PPPtslmu+++26cccYZ6OnpweWXX47PfOYzWLlypfnd9rKXvQwXXXQRAOAjH/mI+T9UpqqtWbMGr3/96/GqV70Kl112GcLhMF73ute5BDXx+lt0ySWX4MILL8S8efNwxRVX4NRTT8W1116L4447zrWmd999N172spfhkUcewXve8x5cccUVWLVqFX7yk5+Ycx5++GG8+MUvxqOPPooPfehDuOKKK5BKpfDqV7/aJbovueQSXHrppVi1ahW+/OUv46Mf/SgWLlzoqpF26qmn4o477sA555yDa665BhdddBHy+Tyefvppc06nf0d/8Ytf4NRTT0UgEMBll12GV7/61TjnnHN8dc1hhx2G8fHxaRmOZoTphA0w9MZ+xWKxKeHUDKXu6upytm3b5vqsXq9PSQsYGxtzZs+e7Zx77rmefbdKB3AcxznzzDMdAE5PT4/zmte8xvn85z/vPProox3N63e/+50TCASciy++2BwbGhpyADif+MQnppz/la98xQHgPPbYY75trlmzxonH4y3DP55pSE4qlfJcr5/+9KcOAOfnP/+553Wt0gGe97znOclk0kkmk8673/1u5/bbb3fe/e53OwCcN7zhDVPG/rvf/W5KG6973eucOXPmmPd/+MMfnFNPPdX55je/6fzoRz9yLrvsMqevr8+Jx+PO3/72t7bzPOusszyfOzmH6aQD3HbbbQ4AZ82aNY7jbE/RiMfjzhe/+EXXea3SAb71rW85Q0NDzubNm52f//znztKlS51AIOBKHemUCy64wAmFQs4999xjjn384x/3nLP9ssOOBgcHnWOOOcZ1zqxZs5w//vGPnn1fdtllrnOPOeYYz5BmRXmuMjEx4QBwXv3qV0/5bGxszBkaGjKvYrE45Zyd+T1/1FFHOYcddtiU4/wbfNRRR7lSdvL5vNPd3T0lJW7r1q1ONpt1Hefv009/+tOueSQSCScQCDg/+MEPzPHHHntsSvh8uVyekiq2bt06JxaLuf5e8nfl/PnznVwuZ47fcsstDgDnqquuMseOPvpoB4BzxRVXmGOVSsVZsWKFMzAw4FSrVcdxHOeGG25wgsGgc++997r6/9rXvuYAcP7whz84juM4DzzwgAPAueCCC1znvfGNb/RMB3Acxzn//POdRCIx5biiKM9O+Pvwl7/8pTM0NORs2LDB+cEPfuD09fU5iUTC2bhxo+M4O37nfehDH3Jdf++99zoAnBtvvNF1/Oc//7nr+LZt25xoNOqceOKJrlTLj3zkIw6AtukATzzxhAPAufrqq6d81unvviuvvNIB4Hzve98z51WrVeclL3mJk06nze/Y97znPU5XV1fLlM5Wf5MWLVrkAHBuv/12c2xiYsKZO3euc+ihh5pjfn+LuFbHHXec6+/El7/8ZfO/s+Ns14FLlixxFi1a5IyNjbnGINf4mGOOcQ4++GCnXC67Pj/iiCOcfffd1xw75JBDnBNPPNF3zmNjY201wnT+jq5YscKZO3euMz4+bo794he/8Py/3HEc549//KMDwLn55pt9+98T7FQkwFe+8hXcfffduPvuu/G9730Pq1atwtve9rYp4SLAdsuL9HACQCgUQjQaBbDdsj86Omq8yl6V7Tvh+uuvx5e//GUsWbIEd9xxB97//vdj//33xzHHHINNmzb5Xrdt2za88Y1vxJIlS/DBD37QHKeXIhaLTbkmHo+7zrEpFot43eteh0Qigc985jM7NZ9OKJVKOzW+VkxOTqJYLOLMM8/El770Jbz2ta/Fl770Jbz97W/HD37wA6xZs8bVtl//su8jjjgCt912G84991ycfPLJ+NCHPoT//d//RSAQwIc//OGOxhWPx80zx9cVV1wx7fkB21MBXvCCF5iCWwz3mU5KwLnnnov+/n7MmzcPr3zlKzExMYEbbrhhSuHDdnz3u9/FNddcg89+9rNYtWqVOX7mmWdOma/Xyx5zMpnEfvvth7POOgu33norvvWtb2Hu3Ll47WtfiyeeeGJK/2eccQbuvvtu3HTTTXjjG98IYOeeG0X5dyWXywHAlDBOYHvkTX9/v3kxpP6ZMjIy0jKq6LzzzkMoFDLv7777boyPj+OMM85wRQqFQiG86EUv8ky1k8ULu7u7sd9++yGVSuH00083x/fbbz90d3e7dsSJxWIm+qzRaGBkZATpdBr77bef59/vM88801V09bTTTsPcuXOnbJkUDofx9re/3byPRqN4+9vfjm3btuH+++8HsD3ab//998fy5ctd82T4L+fJtunxIu9973u9lhPA9iiuUqm009GEiqLsGY499lj09/djr732whve8Aak02nccccdmD9/vuu8d77zna73t956K7LZLF7xile4fp8wbZi/T375y1+iWq1OKRza6veJhMW4/X6nd/K772c/+xnmzJljIlgBIBKJmB25fvvb3wLY/ru8UCh4eu07Zd68eXjNa15j3nd1deHMM8/E3//+9ykRs/bfIq7Ve9/7XleU8nnnnYeuri6zU9Xf//53rFu3Du9973vR3d3tapNrPDo6invuuQenn3468vm8uT8jIyM4/vjjsWbNGqPvuru78fDDDxuNYpNIJBCNRvGb3/xmSgQt6fTv6JYtW/DAAw/grLPOQjabNde/4hWvwAEHHODZNu/98PCw5+d7ip3aHeDwww93hYGfccYZOPTQQ/Gud70Lq1evNgIfAJYsWeLZxne+8x1cccUVeOyxx1zhIX7ntyMYDOLCCy/EhRdeiJGREfzhD3/A1772Ndx55514wxvegHvvvXfKNYVCAatXr0Y+n8fvf/971z95DIf22juYYfFeIdONRgNveMMb8Mgjj+DOO+/EvHnzdmo+nZBIJKY9vk7aBOD6RQMAb3zjG3HttdfiT3/6E/bdd9+269Ou76VLl+KUU07BD3/4QzQaDdcvES9CodCU/NidYXx8HD/72c/wrne9yyWKjzzySNx+++3417/+hWXLlrVt52Mf+xhe+tKXYnJyEnfccQd+8IMfdFRzQfLAAw/gHe94B8444wz8x3/8h+uzvffeG3vvvfe02gOA173udQiHw/jxj39sjp1yyinYd9998dGPfhQ333yz6/xFixaZkOMzzjgD559/Po499lg8/vjjmhKgKIARsPbWpwBw7bXXIp/PY3Bw0DMd7pngtMgdtP9O8h8fv8rDsm4LsN2oahvns9ksFixYMKU2STabdf3T1Gw2cdVVV+Gaa67BunXr0Gg0zGcy/JbIXWqA7f/gLV26dEqKwrx585BKpVzH+Lv4qaeewotf/GKsWbMGjz766JSxk23btgEA1q9fj2AwaHYPIvvtt5/ndcCO9dbdARTl/xZf+cpXsGzZMoTDYcyePRv77bfflP/HwuGwK2cd2P57c2JiwlU3TCJ/nwBTf5f19/e3TQGV+P1O7+R33/r167HvvvtOmRfD+DnGCy64ALfccgte9apXYf78+TjuuONw+umn45WvfGXH41y6dOmU34NyPHIHLPtvEcdh/66NRqPYe++9zedM2TjooIN8x/HEE0/AcRxcfPHFvlvsbdu2DfPnz8cnPvEJnHLKKVi2bBkOOuggvPKVr8Rb3vIWswtPLBbD5Zdfjve9732YPXs2XvziF2P16tU488wzzXw6/Tvq9zxw3l7G8Gfr35edMgLYBINBrFq1CldddRXWrFmDAw880HzmJSS+973v4eyzz8arX/1qfOADH8DAwABCoRAuu+yytoXVOqGvrw8nn3wyTj75ZKxcuRK//e1vsX79eld+ZbVaxWtf+1o8+OCDuOuuu6Y8iL29vYjFYtiyZcuU9nnMS+Cfd955+MlPfoIbb7xxt28FMXfu3GmPrx3z5s3Dww8/jNmzZ7uO85ck/xlkcSy//jvpe6+99kK1WkWhUJjyT+ru4tZbb0WlUsEVV1zhGUlw44034tJLL23bzsEHH2yMEq9+9atRLBZx3nnn4aijjuqoONjY2BhOPfVULFu2zHPrw8nJSU/RYRMKhcw/xE8++SR+/vOf4+tf/7rrnN7eXhx11FEd5buedtpp+MY3voHf/e53OP7449ueryj/7mSzWcydOxcPPfTQlM9YI2BX77fc19fn660Apv5dZfHWG264wXOLUlm0F4Cv0dXvuPzn9dOf/jQuvvhinHvuufiv//ov9Pb2IhgM4r3vfa9nEdldSbPZxMEHH4wvfOELnp8/k8KMY2NjSCaTavxUlP9j2I5JL2QEE2k2mxgYGPCNAvUzNk4XGkdb/U7fVQwMDOCBBx7AXXfdhTvvvBN33nknrr/+epx55pm7ZXvC3fn7kn9P3v/+9/v+P8qI3pe97GVYu3YtfvSjH+EXv/gFrrvuOnzxi1/E1772NRP19t73vhcnnXQS/vu//xt33XUXLr74Ylx22WW45557cOihh0777+h04L23i8jvaXaJEQCAqfjeiXC57bbbsPfee+OHP/yhyyry8Y9/fFcNx/CCF7wAv/3tb7FlyxZjBGg2mzjzzDPxq1/9CrfccguOPvroKdcFg0EcfPDBnkUe/vznP2Pvvfeesq/8Bz7wAVx//fW48sorp3jSdwcrVqzAvffei2az6frl9uc//xnJZLIjj7bNYYcdhrvvvtsUBiQs+MRfigcddBDC4TD++te/usJHq9UqHnjgAdcxP5588knE43HPMNvdxY033oiDDjrI81m79tprcdNNN3VkBLD5zGc+gzvuuAOf+tSnPKu6SprNJt70pjdhfHwcv/zlLz0LR37+85/vaByLFi0yAmRwcBAAXJ45UqvVOtqVgakAO1t0UVH+HTnxxBNx3XXX4S9/+QsOP/zw3d7f8uXLcfvtt3d8Pj3eAwMDuyRiqhW33XYbVq1ahW9+85uu4+Pj457/4NjhmY7j4IknnjAeGrJ582YUCgWXR4zFbbmX9T777IN//OMfOOaYY1p6VBYtWoRms4m1a9e6/o49/vjjvtesW7fOVRxLUZR/b/bZZx/88pe/xJFHHtlSzFI7rFmzxhWhOTQ01JGwX7hwIRKJhKvAqqST332LFi3Cgw8+OOX//ccee8w1RmC71/2kk07CSSedhGaziQsuuADXXnstLr74Yk8vvw098PI8ezx+cByPP/64a62q1SrWrVtn/j7xb9ZDDz3k+zeL10cikY7+rvX29uKcc87BOeecg8nJSbzsZS/DJZdc4kp922efffC+970P73vf+7BmzRqsWLECV1xxBb73ve91/HdUPg82fn9jeO+fbX9jdskWgbVaDb/4xS8QjUY7miC9DdK78Oc//xl/+tOfdqr/rVu34pFHHplyvFqt4le/+hWCwaCxFgHAu9/9btx888245pprXNvr2Zx22mm47777XIaAxx9/HPfcc4/ZYoN87nOfw+c//3l85CMf8azCvjs47bTTMDg46KrFMDw8jFtvvRUnnXSSZ75+Oyje7X/wrrvuOoTDYaxcuRLAdu/Ysccei+9973uuXRJuuOEGTE5OutZnaGhoSj//+Mc/8D//8z847rjjph1Gv7Ns2LABv/vd73D66afjtNNOm/I655xz8MQTT+DPf/7ztNveZ599cOqpp+Lb3/52210GLr30Utx11134/ve/75v+sjM1AZYuXYpgMIibb77Z9bO1ceNG3HvvvTj00EPNMa97Amy/74FAwLeKraI8F/ngBz+IZDKJc8891xjbJK1C93eGl7zkJRgbG3Pl4rfi+OOPR1dXFz796U+70uuI38/7zhAKhabM99Zbb/WtvfPd737X9Tfitttuw5YtW/CqV73KdV69Xse1115r3lerVVx77bXo7+/HYYcdBmD736dNmzbhG9/4xpR+SqWSqdTNtr/0pS+5zrnyyit95/W3v/0NRxxxhO/niqL8e3H66aej0Wjgv/7rv6Z8Vq/XzZZ2xx57LCKRCK6++mrX775Wv08kkUgEL3jBC3wrx3fyu++EE07A1q1bXSmd9XodV199NdLptHFmsv4ACQaDxuDK9F0aG7y27AO2GyVk5f1cLofvfve7WLFihaeHXHLsscciGo3iS1/6kmutvvnNb2JiYsLs0PL85z8fS5YswZVXXjllHLxuYGAAK1euxLXXXusZdSz/rtnzTqfTWLp0qZlzsVh07XAGbP+/PZPJmHM6/Ts6d+5crFixAt/5zndcDrO7777bU4sCwP33349sNuuKlH82sFORAHfeeaexPm3btg033XQT1qxZgw996EMdhXWvXr0aP/zhD/Ga17wGJ554ItatW4evfe1rOOCAAzqKJLDZuHEjDj/8cLz85S/HMcccgzlz5mDbtm34/ve/j3/84x9473vfazwUV155Ja655hq85CUvQTKZxPe+9z1XW695zWvMD8gFF1yAb3zjGzjxxBPx/ve/H5FIBF/4whcwe/ZsvO997zPX3HHHHfjgBz+IfffdF/vvv/+UNl/xile4wus/+clPAoDZKuKGG27A73//ewDA//f//X8dz/u0007Di1/8Ypxzzjl45JFHMGvWLFxzzTVoNBpTvMi/+93v8Lvf/Q7A9ge5UCiYcbzsZS/Dy172MgDAoYceinPPPRff+ta3UK/XcfTRR+M3v/kNbr31Vnz4wx92hfl/6lOfwhFHHIGjjz4a559/PjZu3IgrrrgCxx13nCv/6PWvfz0SiQSOOOIIDAwM4JFHHsHXv/51JJPJXV448Ve/+tWUH3Rge8j+T3/6UziOg5NPPtnz2hNOOAHhcBg33njjTm0F9oEPfAC33HILrrzySt95/fOf/8R//dd/4WUvexm2bds25VlhXvHO1ATo7+/Hueeei+uuuw7HHHMMXvva1yKfz+Oaa65BqVRyFWH81Kc+hT/84Q945StfiYULF2J0dBS333477rvvPrz73e92Gc0U5bnOvvvui5tuuglnnHEG9ttvP7zpTW/CIYccAsdxsG7dOtx0000IBoNTck53lhNPPBHhcBi//OUvcf7557c9v6urC1/96lfxlre8Bc9//vPxhje8Af39/Xj66afx05/+FEceeSS+/OUv75KxrV69Gp/4xCdwzjnn4IgjjsA///lP3Hjjjb6/r5iOdM4552BwcBBXXnklli5divPOO8913rx583D55ZfjqaeewrJly3DzzTfjgQcewNe//nVEIhEAwFve8hbccssteMc73oFf//rXOPLII9FoNPDYY4/hlltuwV133YUXvOAFWLFiBc444wxcc801mJiYwBFHHIFf/epXnsVRge3/oI2OjuKUU07ZJWukKMqzn6OPPhpvf/vbcdlll+GBBx7Acccdh0gkgjVr1uDWW2/FVVddhdNOOw39/f14//vfj8suuwyrV6/GCSecgL///e+48847Ow7vPuWUU/DRj34UuVxuik7q5Hff+eefj2uvvRZnn3027r//fixevBi33XYb/vCHP+DKK680kclve9vbMDo6ipe//OVYsGAB1q9fj6uvvhorVqwwTtoVK1YgFArh8ssvx8TEBGKxGF7+8pebtN9ly5bhrW99K+677z7Mnj0b3/rWtzA4OIjrr7++7Tz7+/vx4Q9/GJdeeile+cpX4uSTT8bjjz+Oa665Bi984QvN/7jBYBBf/epXcdJJJ2HFihU455xzMHfuXDz22GN4+OGHcddddwHYXu/hqKOOwsEHH4zzzjsPe++9NwYHB/GnP/0JGzduxD/+8Q8AwAEHHICVK1fisMMOQ29vL/7617/itttuw7ve9S4A2yMZjjnmGJx++uk44IADEA6Hcccdd2BwcBBveMMbAEzv7+hll12GE088EUcddRTOPfdcjI6O4uqrr8aBBx7oqWPvvvtunHTSSc+6mgDPeIvAeDzurFixwvnqV7/q2tah1ZZtzWbT+fSnP+0sWrTIicVizqGHHur85Cc/cc466yzPrRUcp/UWgblczrnqqquc448/3lmwYIETiUScTCbjvOQlL3G+8Y1vuMblt90cX+vWrXO1vWHDBue0005zurq6nHQ67axevdpsLUfabedmb8PR6tzpMjo66rz1rW91+vr6nGQy6Rx99NHOfffdN+W8VmO0t0uqVqvOJZdc4ixatMiJRCLO0qVLp2yfR+69917niCOOcOLxuNPf3+9ceOGFru2gHMdxrrrqKufwww93ent7nXA47MydO9d585vfPGUd/TjrrLOcVCrV8hw+b36vG264wTn44IOdhQsXtmxn5cqVzsDAgFOr1VpuEXjrrbf6Xt/V1eXaNkTC63fV/bep1WrO1Vdf7axYscJJp9NOOp12Vq1a5dp+0HG2b2WyevVqZ968eebn5cgjj3Suv/5618+Loig7eOKJJ5x3vvOdztKlS514PO4kEgln+fLlzjve8Q7ngQce8LxmZ7eCPfnkk51jjjnGdYx/g71+xzvO9t8vxx9/vJPNZp14PO7ss88+ztlnn+389a9/Nef4/T49+uijnQMPPHDK8UWLFrm2XiqXy8773vc+Z+7cuU4ikXCOPPJI509/+pNz9NFHu7Zt5e+673//+86HP/xhZ2BgwEkkEs6JJ57orF+/3rPvv/71r85LXvISJx6PO4sWLXK+/OUvTxlPtVp1Lr/8cufAAw90YrGY09PT4xx22GHOpZde6kxMTJjzSqWSc9FFFzl9fX1OKpVyTjrpJGfDhg2ef/P+8z//01m4cKH+7lOU/0O0+31I2v0P+fWvf9057LDDnEQi4WQyGefggw92PvjBDzqbN2825zQaDefSSy81v/dWrlzpPPTQQ86iRYvabhHoONu3bw6Hw84NN9zgOj6d332Dg4POOeec48yaNcuJRqPOwQcfPEUT3Xbbbc5xxx3nDAwMONFo1Fm4cKHz9re/3dmyZYvrvG984xvO3nvv7YRCIdffJ/6+v+uuu5znPe95TiwWc5YvXz7lf952a//lL3/ZWb58uROJRJzZs2c773znO6dsBeg4jvP73//eecUrXuFkMhknlUo5z3ve86Zspbh27VrnzDPPdObMmeNEIhFn/vz5zurVq53bbrvNnPPJT37SOfzww53u7m7zd/lTn/qU2WJxeHjYufDCC53ly5c7qVTKyWazzote9CLnlltumTKmTv6OOo7j3H777c7+++/vxGIx54ADDnB++MMfeurYRx991Gxl+Wwj4Di7OI5RURRFUZRnxL333ouVK1fiscce86xC/GznN7/5DVatWoVbb70Vp512WstzV65cieHhYc/ii7ubSqWCxYsX40Mf+tCMpfIpivLc461vfSv+9a9/uXYr25O/+7xYvHgxDjroIPzkJz/Z00P5t+G9730vfve73+H+++9/1kUCzEwytqIoiqIoHfPSl74Uxx13HD772c/u6aH8W3P99dcjEongHe94x54eiqIo/8Z8/OMfx3333dfRTk3KvwcjIyO47rrr8MlPfvJZZwAAduHuAMquY2JiwlRp96NdcQ5FURTl/zZ33nnnnh7Cvz3veMc71ACgKMpuZ+HChZ41q5R/X/r6+naq1t1MoUaAZyHvec972u7nqVkciqIoiqIoiqIoynTRmgDPQh555BFs3ry55Tm7ey9oRVEURVEURVEU5d8PNQIoiqIoiqIoiqIoynMELQyoKIqiKIqiKIqiKM8R1AigKIqiKIqiKIqiKM8RdnthwHe9613m+0AgAMdxOtomQZ7ndU27z73a4xh2Rz/2Z37nerUnv9pjbDemTudmnyvPb9WH37ym02er+XuNo5N7IrHX0G/c9nhbtd3J89Runn7teK2B1zy8rvdaM795yc+uvvrqlvNRlF3NK4Kv29NDUJTnPHc3b93TQ1CeY+jvfkXZ83Tyu3+3RwIEAgHzeiZiXX5mf+4l9rzO92rTbsfveq8x+Y2nFV4CT66N3Y49N781bCeUecy+H/aY/ESlV5vtDCZ+/Xu10em85HGvZ8D+KufTqWjv5F62O2e6xhevn49O18O+f9MxtimKoiiKoiiK8txitxsBvDydfgKR5/gd8xNWXm16CVJ5nt8xOUYvAW6Py0sgT8cD7+XZ9ZqLn5HAXpd269hqvK0MILKvdud1Er1gj9HreKvnxB5Pq/H6Xe8lxv3Wx/6+k2fKb6381t4rIqLVuOX3rb76rY2iKIqiKIqiKM89dns6gC1s/ERJO69yKw9oK1HUqg/7mNe1Xp7lTq6ZrlfXS+S3Ev5++I3Na/1bCcZO1sKv704MAPbx6d5feX279WnnFe/0uZDft3ouvMT8rnimdhaNCFAURVEURVEUhcxIJEA7L7n8jNgeeT+Paiee6U4MAq28pX79terXyxPfCtuj3c473em4/SIk/Lztrcbtt7Z+kQudtNnumJ/xwKu/TqIXpnPfOz2nlZHK7r/d+Dphus+BoiiKoiiKoigKmbGaAPK9jV8Iu7y2lXfZFnmtRHOrcdrX2G36eYG9+vULO/eatzzPy3Nsz7fV3GwjQqsxexka7Hnb4/PCnrufd97P4OBl7PBbM79xtYoIaGUs6mSOfoaDVoYKvzb8ns3pRntM53o1ECiKoiiKoiiKQmZ0i8BWAsj25rYSvF6Cr5W3168dHmvlQfa7zu/8dp52v/b9jAat0gTkufa1nXiX/dbM79pWa2X3z/PteXSCn1GnHe0iAbzC9Fu11SrCoNOIFr8omGfi/W9nJJHHp7PuiqIoiqIoiqL8+zOjRgA/zy+P2eLZFqitwu879Rh7ndPOgNDKq+3nkfUT137XtBqb3W+nRg4/77NfqL59bafj9GrHFrxeQrwVnRglWl3jJZr9Ijv82mol2FulFfgZGzqJwuhkbu2eqVZGIkVRFEVRFEVRntvMmBGgnbj28hp3Kqg7iR6w+7C/egk9r/eyv1bi2h6b1zzsObe6vhODiN96etHJcRmh4TffTqIo7EiAVgLY772f4Uie18640cp40qpfL4OB333xmoPXWvid6zWeds+V3X+7nwNFURRFURRFUZ677PbdAfxEnJdX1E8oenlW23k6vcSbfU2rSAG/sXh93sl8W4211RxtAe3VVqv18VqLVuNuNcd26+e3Jvb4OklDsM+dTkSE/LzTZ8przLYxym9N2q2T11xbHfdal1bjk235na8oiqIoiqIoigLMYGHAVh7JVh5d+zxbcLXyrtqiUuLl8fbCy+vt1ZctMNud74eXwO4kHL6VULYNCl4RCNM1EMjjXuvtdZ6XMaDdHLzGJOfj1V4nRiI/5Pq0u9YrwkF+tcfm58G374nfufa47GekXfSMoiiKoiiKoijKbo8EIO1EppcobNUOr+MxP09oq0iBTt63E5Ze17XyUnfi1ZX9Tcdzzc+92m0XTdAqyqLVXFqFpftFM/h51v2iG/zG4rc2rSINWvU5nTVpty5++F3f7nls1W6ruSqKoiiKoiiKokhmrCZAp5EArc7fmTzodh50+zy/a/1Cuf3G0qrfTkTbzoo425hiRyd0cr1f9ISNX/SB3bf9vTyv3TxbGYe8PO6dXNfuXtrndXov2kU2dDKeTubqdb2KfkVRFEVRFEVROmFGjACdCGL7mJ+XuZ3A9xOw0gvsFarv51Vu1Z5XqkAnc/QaS6vwbztEvVW/fukLXvPxihqw18IvhUCeZ8/Ra07t1s9vrdod69TI0wqveXjdE7/77LU+XpEdfnPw+tzr/rT6XFEURVEURVEUpRNmPB2gk+M7G4rvdWxnPOytwsWn01a7NIdOowv80h06WTt5vNN5tRpjuxSA6XikOx3LztznnaWTFIhWx3bVddNZk1bpJ4qiKIqiKIqiKJIZiQSwPcp+Hkw/z7CdH97qayceVy8Pr32e/Zmcg9f8vI7ZHv92tDM4tFq3dmOXX/2iB7y886084Z2kC/gd82vHb4z2GDr11LeLGPCLWGj3nLZ6jlrNs92atGqvk7l4jVNRFEVRFEVRFIXsdiOAlxBtJ2j9QvJtMbsr8+ZbRRt0IlJbiVevOXciNr3asa/3mo+XqPdrx37fao2nu/5+Y7LH1omnn21wrvIlr/GbWzsPvdfX6UZTtForOXZbzHv1aXv3/Y7b17d6LhRFURRFURRFUWasMKBNO++5PMdPyHhFDLQSlO0ElN2un5jeFeHXfmJzV3tvOx1nOy+z3d6uGON017DVPZqJcXgZAHYmraKTazv5+ej0Oo0GUBRFURRFURSFzKgRwEvs+om5dmH9bK+V+G+Vu+6FX8TBdObh1W8rj7fdznS9t17r5yXUOxX3ftEGdp+tojm8rm039+nSiZB+puLXvq+70qve7vnu5PnvFI0GUBRFURRFURSF7HYjgJdYlKK4k9Bqv2Od5pfbx73etzvfL6R/V4Vcy/bb5Y7LsbYSw17eZ7sdv/blNX5iuBNPdiuPfTvjSbvj9uftDA/PJAWj08iDTubpNTa7r1ZpA5302clniqIoiqIoiqI895iR3QE6EfjA9MPsO80ln84YvD5vVS/A/n46Y+pknDvbTqd9eM3NLx/9mfTVybp0subt+mj1DLVqr1WqSLtr/a5pdayTNnYm1UCyK9JWFEVRFEVRFEX592JG0gGm63nu9JrphLt3Mr5OIgqmMzavdIdOPMqdzqVVtMB0PN2tIgBa9burvMytPOWdhsX7ecs7WSNbLO9MqH6r451+7kcnPxetrtNoAEVRFEVRFEVRyIzsDuAVRm+f4/XV6/x2nvhO294ZkW+f4xe6b7ft9d4vp77dGrTL/e90nPK9V9i/lxe5kzSFduPxuraTeg72uOw5+a2nPLfV2NqlLdjPmteaduJ1b5cC4ZWy0Mk1O2uYUBRFURRFURTlucVuTwdoFUbf6iuFzXRz7v1Cur1Czf0E6M6EfLdq0y/M3ev6Tvr2E6WyroDX13Zz6LTvdtftzP1qd9+mWwPBL52gXYh/J7n6Xud1Eno/nZSIdmNu1UarcSqKoiiKoiiK8txmj20R2IqdEf87066fANsZ76mfscGrf/sar7H4te93bidGFi86TYGQx3e1wNwd3upnOrZOjB27sr9dybNpLIqiKIqiKIqiPLt4VhoBOg2r7uSz6YZr2+c9E4H6TDzkO8POGi/88ul39Rj8PtuV/e4qg8KeENI7M/adWW9FURRFURRFUZ67zMjuAF6F13YmnHq6/QDTq5wuj3UajWBfI/vtZJ7t5t0uZ579FItFVCoVAEAkEkE6nZ5WP15t7qp7xHX0egFArVZDs9n0XH+vMbaKhOh0zq1SJTq9R52uaavUk+kc92prOs+3oiiKoiiKoijKjG8R2ErEtRNMfm3axzoR1Z2G1HeCVz5+J+Oezjz96gDw+3Xr1mHDhg0IBAKYNWsWDjvsMHNdu37b5aHba9Zq3F6pCJFIBOFw2LyCwSBisZhpc9u2bSiXyx2teafPR6d1H1o9i/y+3Vz9+m7Xjz2fdutrt+VnrFADgKIoiqIoiqIofux2I0CrPHibTkXOdPv06mNnru2kvWdqSLD737RpE3K5HMLhMEKhEGKxGKLRqBHTANBsNhGNRjEwMIBAIIBkMolcLodgMIhAIIBQKGT6oCCfzty95lipVLBp0yak02lks1kznlAoZL6SSCTi8voHAgE0Gg0zvkgkglAohFAoZM4rFAqo1+ue49uVxoJW18s+2+El/Dvx8rerPdDuWW5ncNCUAEVRFEVRFEVRJDO2O8AzvdYvPFqe5+dR3RXGg07ObVV/wKtiv/1Zo9GY0sbg4CA2b96MaDSKWCyGTCaDVCqFWCyGSCQCAGg0GojH44jH42b+hULBCGuK/maziWAwaK5rZaBpJWAdx0G5XMbGjRsxMDCARCJhBH0wGDQefyL7r9frZo7BYNCcHwqFEI1GzdpUKpUpRoBnYsBpl2rQSYRKK7zO87vWy/vfaiyt3tt9TCclRlEURVEURVGU5x4zFgngJX4Bf+FpC3z7Wi+x34n48TIMtArH9vrenouXIGtlJPD77P7778emTZsQi8WMgC+VSqjVaqhWqyiXyyiXy6jX60ilUujv70cikUA6nTae+GazadpsNptoNpvI5XKoVCoolUoIh8OIx+OeRohO1sJxHDz88MMol8tYsGABenp60NXV5YpUYDQAc/05Jjl/YLvxotFooFarmfHKzyORiPlMHrfX2j7mde+9PvPz3ntdY98ruz0/oe7nlfd6pjqZh9/5XmP0+0xRFEVRFEVRlOcuM1ITAJgaJt/O2+llDGgVFt1J334F1VoZD7y+92rD7xyvudlUKhXkcjmMjY0hl8shkUggEokYb38sFjNtUOzTgx6JRBCPx01IvYwmoAAvlUqu8PtO5uj1vlwuuwoQyqgEjotRBrxfXu0xjYFrwxfH6ziOKzXAHksrgdvpXPi+XbpKp/d4Ote1a8vGy7DU6mdBawIoiqIoiqIoiuLHjKUD2J7R6Xrt/T7bmbG0Y7pttzu/lTc3EAhg06ZNuPfeexGLxZBKpZDNZpFMJpHNZpFOpxGNRo1IrtfrJtw+kUgYQwGNAHK9mJffbDaRTCYRj8cRi8WmRAx0Openn34a//rXv7B06VL09PSgv78fyWQSyWTShPJzjI1Gw1Pwc4zyOMU/IwcYIeA3xlah79Od07NVLLcyPnnRiYFAURRFURRFURRlj0QC7Ow1fkJnOjne7T6TbXfSRrt8bJuRkRE8/fTTiEQixjM/Pj6OdDqN7u5upNNpV5g/owJCoZAxBNBzLsPu6/U6AoHtdQUATMm1D4fDiEajpjAg26FgbzQamJycNFEJlUoF1WoVzWbTRCDUajXMmzcPmUwGwWAQg4ODiMfjSCaT6OnpQSQScRkrWBCQ68SXnwde1jBgRAONATQOSAMH58JrarUaisXiLnkGOmW6z96uGEOryACNAlAURVEURVEUpRUzZgR4JuyMh3M6nvnpnNcqoqFVKDbF8cjICB588EEkk0ljCAiFQujq6sLAwAC6u7sxf/58xGIxJBIJl4Bnu9VqFfV6HaVSCfV63ZV7z/5DoRCazaaJErCL8PH8arVqXsViEfl8Hps2bUI+n8fk5KTx6CcSCcybNw8LFixAIpFAvV43BQsTiQRCoRASiYSJBmARwnA4bNaFnn25dnItZQpAOByG4zio1WqmbgDbkOfH43FTNLFUKrmMAJ2kbfjRqbjfmbafCe08/moMUBRFURRFURSlFc86I4BXrQDAe9szGfruV6zN61op1v2KEbYax3TCy3luqVTCvffei3K5bLz9qVTKCOhQKIS+vj6k02l0dXUZr34+nzdinufJ8HlplKD4Z7g9DQQ0NDBfXyJz+ROJBJrNJnp6eox333EchMNhY6SYPXs2gO31AXK5HAAYYwJFP+fNiABpGJAwEsI2pMjjtgFDRgRwB4FgMIhoNIpgMIienh5TnBDYbjDJ5/PGmOBFp4URvc7f1fgVnZTj6rTonxoCFEVRFEVRFEWxeVYZATrxtE6nkFsnXlop6r2ubfVZu3lUKhUUi0UEg0FUKhUUCgUEAgGk02lTVC+VShmRm0wmjYBlKDzFa6PRMGHvspCeHI/tWWcbMn1AXmtfF4lEXJ59evHD4TAymYzJ/SddXV1GWNv1COT4vN7zmBT8fmvM72VhQ5ka0Wg0UK1WTa0EGkNYdyAWiyEQCJhdFuSc/fpqNY5W972T81q15+fl72QcWhdAURRFURRFUZR2PKuMAFJE8j1pFWbfqeDpdHcAe0zThfPYsmULHnjgAaTTacRiMey1116m2n82m0U8HkcqlTKClEX+5NZ5NAJUq1XjJacYpuC1xbEcA8WyfU61WjVfGWWQSCSMt71YLJotBSORiDFWVCoVJBIJpFIpLF261Hj47eJ+bNsrXUIaIWhsoKdfjhPYsY0gdzeQ0QbAjqKClUoFtVoNlUoFlUoFkUjEbJ3Y39+PcrmMSqWCjRs3wnEcxGKxtvfRKxrENlbY993rul3NTEcnKIqiKIqiKIry78MeNQL4hTx7ndeJh7TVdV5h/+2uny6O42DDhg0oFotIJpOoVCqYP3++Efz08stifSyeB7hz4qVABuCqts8X+6zX6656AMFg0FUbgOfL4nx8sV2G/dMYUSwWXYUBGZbPLQeZQkBRbO8CUK/Xp6yxNPIwKqBer5u+Gakg7wnXxI4AkOkPcp3knJkuwXbi8Thmz55tjAqsrcB2Wz1b0yky6PfM7cyzNp3oGL+ii4qiKIqiKIqiKGSPGQE6LbJmH/fzzrZjd3lppfBqNpt4+umnMTIyglmzZqG7uxuLFy9Gd3c34vG4ycmXYfq24KWYppilWKbwZX4/BTnz7u15SnFO7zrHyDY5Dn7P7QPpJa9UKmg2m8ZYQUNCqVQCABM5YEck0AjQKjzeKy1BboXItjjXUChkjB00XNAAwBfnLHc+4FxZPDCZTKJWq2FychL5fN61dq1o9fz4iXIvo5M8p9W1fm23Y2d/PhRFURRFURRFeW6wx4wAnXpVO7luOuHRnUYOdDomit7Nmzdj7dq1iMViWLJkCZYsWYKuri709PSYc6UHWwpWCluKV3k+89gZWs9t8YLBoGv7POnxt73CFMNML2CxPqYU8Fg8HkcwGDRRCxTOiUQC2WzWrEWpVDJ98xxeG41GzTxlhAJfcrcAvjgeFvmzDSFce3lcRjIwZYIRFjK6gmMul8twHMcYMzKZDMrlMkqlUsdCWdY7kFENXkYBr+iVdkYRv89kn174RcmoAUBRFEVRFEVRFJtnVU0AYPqez06iB2ymK45andtoNFAoFDA5OYlSqYTe3l50d3ejt7cXqVQKyWQS1WrVeNyld5tikZ9JI4Aseie33KMXXG4J6PViX/JcaQRg+L0U1vxK7z63F6ThQVbml3UA2Ge7yAOuvX0v7Ha81l4WEWTaAHc/oBGBY+V1nBujJezUA1mHwI6o6MSItDPRAXKt2vXVqj2vttsdUxRFURRFURRFmTEjQCuh0qkHvp23tNN+d8Zw4EepVML//u//Ip1OY++998bixYuRzWaRzWbhONu3sSuVSsbLza3rZDSAn0FARgfQgw7AFPWTbVBcMg9eCm/ba03xy4J/RG7Hl0gkkE6nzW4BbNuuE8D5yJ0K5Dw5LlnLwEtIyzB/AFMMJQDM9fF43OT1l0olFItFADt2AaDRgtEJAEzBwkKhYPqNRCLo7e1FMplEuVzG1q1bp6xZq9B8O+y/FZ2E+Hf6fNs/N9ONeFEURVEURVEU5bnLbjcCtBNKrYqn2cf9DAJ+4dmd5GK38sra3/O60dFRbNu2DYlEAgAwe/ZsdHd3Y/bs2ejp6UE8HjeCnqJZhq8DMJ59erXZdiAQMOJf7msvx2ELaymkZTSBfQ2wQ0hHo1Hzkp+xHWC7EGdaAD+ThgkaHBzHMaJfeutloT+55SCjEyTSE0/PvPTmy/kxsoJpECy4yPlwDDIKgWNme6xvwB0FACCbzZpdETZt2oRwOIx58+Z5Pmdez3QnHvlWxgX5DLfCL/y/3VgURVEURVEURVF2uxGglRB5Jh56PxE1nevavfcSb81mE8PDw3j44YfR19eHTCaDJUuWoLe3FwMDA8YbXSqVXFv8AXAZApjrziJ8MipAFsCzDRFS2LINWSRQph3Ygpuh/oFAwBQqpBGAQl62wSKBLBgI7BDiFNX8nnn4NDJIIwC/l4URpRiWRgXOi3OTNQEYzi+NKoxGYC0AOR8aFeRayvExlQDYHgXR09ODer2OfD6Pp556CvF4HHPnzp3yfO3sc9rqWCefTScSRg0AiqIoiqIoiqJ48axOB5hue7ubYrGIv//974hEIli2bBmWLFmC7u5uzJo1y+SZyz3tGV7PPeyr1appK5FIuCraBwIBU1TPK9dfes7p7aaotkP/5fe2x5oCOxaLucYsxb30sMdiMUQiESOkKaZpzJDpDBTtFP5ye0OOk2OhJx7YIW7ZB40BMiKA7cgiiJFIxIT881w5RrbNegCNRsPMOZlMmnMrlQrq9ToqlQpisRh6e3uxzz77IJ/P4y9/+QsWLVqEuXPnTnkeWkWx7Mx57ejkOo0AUBRFURRFURSlFTNmBGhnAGhXF+CZiBu/dAH5mR+sIB8KhVAul1Eul5FMJjEwMICBgQF0dXUhnU4bUSxD9SmMWdlfhvd79Suv4Xjli2OX2wTa19vpALIteUzm6NuRCmyLRfOkt16GwkuhLY0V7ULa7etpEOD1XsYFuX5yC0GKesLcfxmpQAMADQiAO4qiUqkYYwGjH3p7exEIBDA8POxan3ZRAK2etVb3vpPnn+11Mg5FURRFURRFURQv9vjuAF4h1l55+n7XSdqFS3sJtXaiau3atXjggQfQ09ODTCaDAw44AHPmzMH8+fORyWQQCoVQLBZN6D/FOb369Xrd7HEvPdT0QnNcFPYUtgxTl1EAUvRKERuNRk2/Ukgz3F0aH+wceXtdZD+MFqAhg6kNcgs+XlOpVFwRBY1Gw3jg2SeLEcqCfzIlgGvCa5kaYRst5BylQJcef7ZhRwZwnWVNhkgkYs7nDgMLFy7EwMAAent7EYlEPJ+RVqH+fmkl9vt29QX82mtVy0JRFEVRFEVRFMWPPWIEaCdYvESTFIydXse+/M5rleNdLpfx9NNPI5fLIZvNYt68eeju7sb8+fPR1dWFaDRqqvRzD3qGw0vPNkPjmbtOYc7UAJlvT+x0AI6RIpjncCu/eDxu5kpxy/6YR0+BTlFN77dMB2AbsiaAFKKcB40AbI+pDlLw22sv19o2Asg5cQ78XBYIlNv6sX8ZFcAUBDsCQEYWyOKCXCN7xwYAxrASCARQLpdNikKndOrtt41R9ji82m3VlxoDFEVRFEVRFEVpxYwYAWxh4id82oU5y/DzVqJHHmv1Wav+yuUyHnzwQWQyGcydOxdLly5Fb28v5s2bZ0RroVAwoj4cDiMajZoQeukVp2ilEaBSqRhvNM+XhgA7tF6mF0gDA8V+IpEwYrdWqyEQCBgvPkU6PeX0iofDYdO/XUVfFh6U3nfm+LP4Ibfoq1arKJfLAGCKHrI2gNe95zzkXO2UAxm9QCja2Ybsg+Ok115GI8hCjGybOwIAcN0zwroL6XQaIyMjGB8f93xObKYrwr2e1Z01kknjgRoDFEVRFEVRFEXxYkaMAF6h9+3CnL3CpDsJtbbbIa3a8yIajWLJkiWYPXs2Fi5ciP7+fsRiMTiOYwrJMWSfItJxHCPCGSVA8Sy93RTlwWAQiUTChMkzpaBcLptt8AAYD7csgMfjwHaDxbZt2zAxMYFcLodYLIa5c+cilUohHo8b73itVnPVDaCItz3qdqE/rifHIIU4Q+ltL74t1AEYI0Wz2TSGBBk9AeyIPqCxQkYWyLZldIUdecGx8DM5DxoHisWi+Z4GExoQbGOTl/GpHa1SBexjXoaSTtv1SydQA4CiKIqiKIqiKF7MaGFAP6+91+ethHy73H+vz6SH1G7fPsYQ+v7+flMAMJlMIhgMolwuu3LR7bZtIdrqHB6XW9ZRnNtb2lHM2uvGsPdyuYzJyUnk83lT6T6RSLhEvX0v7KJ5Ml/f6yXHK1ME7PB+e45Eevq97g2NGrKwny3C7XWz11VCw4KsoUAjBCMkAoHtuzIEAgFXVIRsVxo+ZJSCV1SJ1zPp99x2ck072kXQKIqiKIqiKIqiSGZ0i0D5tRMPqN97L8NAp7SLLACAbdu2IRgM4pBDDkEqlUIikUCpVDLimqIQgMkvp7dZ5q3LlAApJuXWecw1DwQCrsJ2XCcpYHkNP2PxPF4fj8cRCoUQj8eRSqVMSLs9fylm5RhpBJBimKH00Wh0ipfczmHnGOm9l7UFbAOPLPDHczhW5vBzTdmf7FcaQWTb0mgiizQyJSMYDKJWq6FUKpk15FaLMtpCGkni8bhZm2q1itHRUd9nyY5kafWctQrdb/VM28YlNQAoiqIoiqIoitIpu90I4OW1tz22071e0k4AdRI1wPO4HWB3dzcSiQRSqZTx0FMsS688jzUaDddxik32y5B4FtVjeD49+GyH9QU4ZtmmFL92+8FgEF1dXUgkEgC2586n02lX0T8vLzS/SiFO0S0r9NuRADKdQEYt0Jsu10CKYnvsnDP7oND2inpoF2Ug+7TbsI0wcqtBYIcxhcYHu11pSAmHw8hmsyiXy666AvJ8fm1noPKKBPAyIrQ6v1W7iqIoiqIoiqIoNrvdCCDDoOUx+bWVaGmVPtCOTsUQ2ywUChgZGcHzn/989Pb2IpFIoFKpmLx5AK58eCmEJVL8Sg93NBpFrVYznvZarYZisWjqAdhpBFKAy5x7eqz5WSQSQTKZNHnthLUFZM6/vBd2f7JSfqPRQLVadYlpW6zSUCBrHNjedL5ojJD5/+yD/XKnBNvwwHPt7Q1lBIIdASBD9r3myDVlJIf8zJ6zXJNwOIx0Oo3R0VFjBGgl2Ft97vWZX9SA3zG7v1ZGBEVRFEVRFEVRlBmJBPAzBPgJlXaCxj7m932nIqhWq2F4eBhdXV048MAD0dvbi2g0ilKpZLzDzK+3Q/zZT7PZdG27R692JBIx0QLcRk9633mMQpoRApyH3U8kEjHh7dIYwOtYUJBFBpleAMB46fk9BTC39pPh/1Jcs32ew8gIFkh0HMdsqZdIJIyYZgQE+6hWq4jFYmZtZGoDsCMSgUKc/dk7FjClQhYGBOAaGyMv5DMj+wiHw2Z9GI3B9ZWFHOW68/7Ioo1+z7CXsPc6R0ZItKLdz4r8GVMDgKIoiqIoiqIofuyRLQJJp+HOXgaAVp+3G4M0LnCP+2aziXg8jr6+PlMozg7NbyW0KJJZeM4Wp3K7OhnOzlB0O89dzlUKWIrfcDjs2t/eNipQqNr543IrPVtk24X7pKddevT5ovHAHps0AnA+juMYw4Xc2k/O1cuzb0dG2JEC7EeG+Mvwf7tt2Y68Z7wXtqCWhhBCg4E0FtDIQ0OHXYvBfg79ntlOf1a8jqvwVxRFURRFURSlHTOSDiDxEs9+4eadpgi0olU7juPg6aefRjAYxKGHHop0Oo1kMmkEtNyejqHx9CLbhf+kgGbIPt+XSiVUq1WUSiWXx5/eexlG7zVXCs5IJIJYLGa2tAN27A5Ar3ahUHB59O022U4ikTDe8lKpZLzhbNNLtMvwfxYxpNhmvYNIJOISuZynHR1QKBRQLpdRLpdNhIKsXyDD8GkMsNMMWNSP6wPACHoArrF4GZak0caOBJAFHmVKB7Bd8KdSKWSzWXR1daHZbGJ0dBSPPvoo1qxZgwMPPBDpdHrK82cbrziOVu/ls9ouvUCNAIqiKIqiKIqitGOPRgIAnXk4pxMu3S41gMdyuRxyuRyi0ajZAYAeZel5lqHoDHtne15CTHrkWU2+Uqm4igvaefn2nKW3WBoeZL66nBcFMcW5HC8As+WdbE9W3Wd/FM1ea0pjQ7VaNcLZjhiQXno73J8GBYp9GkYYNSGjBrwiGOS4pOGD4p8pDDS+eG11CMBEY8h14lxlgUZGNNhjkPPkdcFgEJlMBl1dXejq6ppynV+Ey3TwioaZbjSBoiiKoiiKoijKjNUEIDsjTjq5xiuaoJVXdXh4GE899RRWrFiB/v5+4xlnkTgAxmtNQ4C9XZ8UgvaLW9BRoPMlhadEitZ2RgAZnk7xWqvVjLGBYwd2hMfTsy5D6KVBgCkQAFxbB0rxTIOGTJOwhbasJ0DDB8V5IpEwtQoKhYKJPLC3IJQpE7bglakVNLQwlSMQ2LFNotx+Ud4zO11C3kcaN5rNpqldwD4ZNREOh81YpcGgu7sb/f39yOfzrloEXKNnIsy9DFut2lIDgKIoiqIoiqIofsx4OkAntAt99jqvU/L5PP75z38ikUhg/vz5mD17Nrq6ukyYfqPRcAliOzdc5o2Hw2HE43FUKhXzkvOmUKSgpniWQs4rZL+VAQBwV8qX3nmKXinG5Rz4vfS22+H8bJ8ec3ra6/U6AHfOvQyVl8X8OE5ptIhGo4hGo+b97NmzzTnxeBzBYBDlchkAzDpznHJdOD47coBRAeFwGLFYzGWQYZuBQMBEEDD9wY4WkYYYroP8jLsY8JjcJjIUCqG3t9cz7J9r38nz6hfuL9dAvf2KoiiKoiiKouwMM5IOYOMlaOT7Vp7TnakhID+v1+sYGhrC/Pnzkc1mkUwmEYvFPCv+UyBL0S6NAHZoPQUrP6c4lIK7VV64bNcOPZdCm/OxjQwcJ3PZ7f7k+V4h9zJFgILea63tscrweLvQn/05jSfpdNrMyb5OzpFjkIYSr8gLmbYh+7KfLQp7aZBhtII0ysgx2+svxyPrQoRCIaRSKZeBwb7H9vPoFe3Q7rludaxTA5qiKIqiKIqiKM9NZtQIYIcydyJSvMSnfe102gmHw+jt7cXAwADmzZuHRCKBYDCISqUypfo8BSi3h2s0GsjlckYQptNps2WfTCOQ/UmRLsfrVRdAimZ+zxD0ZDJpogLoJa9Wq65ruTUhIxQo9hl6zxx8KZYbjYYr4sBxHBSLRRNdkEqlXAX65LaEXoJZriM9/DxeKpVMX9ls1lyfy+VM5AGv47x4TG7RJ40ZMuqh2WyiXC577uTASI9KpWJSAuT6M1ohmUwikUiYebKQoqyXwDQE9sk20uk0stksRkZGUC6XUSgU2j6P7VIFvI53avxSA4CiKIqiKIqiKDYzWhOglWhvJ/Y7qS3QShA1m01s2rQJxWLRFAJk2Lis7C89w1K4SxhSLmsEMAydeeUUtdJLz6gCjtVxHFcOvb39nZyrHSHgNXdpEGARPl7HMciceq6L3JmAQplimQUT5fikUcArIkIe5zpyXTk+esrlmsjoBXtNODY5V3tLQ85HXm8bDeQ2jTJqgoaTeDxu6gFIw4o0BEmjjrx/NKR0dXUhEon4GgE6jVrpFL8ogp1pS1EURVEURVGUf2/2SE0AW7C0EimdCJhO2nEcBw8//DCq1SqWL1+OdDpt0gAoEtmG9BJLT7fMK69UKkZAJxIJs8tAPp83efoyp9323rJfWazP3o/e63sKTq/PpACWHns7vF7mucvCfRTN5XIZxWIRlUoF2WzWtdWe33aGcms9ea7jOEZ4S6+59NizjkA0GnUV9LNTFKTgt7dmlPOTa8Q51Wo1E93A+dN4kUgkEIlEkEwmTXqINHxwpwCmENh1IWgA4fezZs1CsVjE4OBgy/QP+b6VkG/FdCNpFEVRFEVRFEV5brNH0gH83vMY4C2M7PzuTvqQbabTaTiOg4GBAWQyGZdQliHotqgEYIrapdNphEIhl8CnUAwEApicnITjOFNC9YEdee/Ajor1kUjEJZald1l62KWAl95oACYKgaHrLMLnONsr2tfrdVfKgh1VQE+4DKOXxe7scHh+L40Z9J5Ho1Ejzulxl15/GbovvfEyOkAaTjh3+eKaeOXo288H0yC4JSF3LOB9oxEgFoshmUy61kHeN2kASafTrigE1hhgYUjuVLBs2TKMjIxgaGiorYdePt/2POzaAjI6xj7P/rnRSABFURRFURRFUSQzkg4ATN3r3Q8vMSQ/2xnoBaZQ7urqMlvJSXEn8+VtzzO/UlRHIhHjRZfiWRbIs2sgyHbs0HoZBm+H39tF8ewweOmdl4Ken9GAIcW3FLrsz06JoGCmp57Cm0YA6Y1nv+Fw2Ihsinrprfe6jxyHXHsZSeB1vVeEht0ux8adE7gtoFcdBb7siAyZTiCNJnLHBzudBNhuNOru7kahUJgizL3WoJWA91ovv3XkV79rFUVRFEVRFEV5bjNj6QC2h9/+zMub6YWfV9Tv3EAggDVr1uCJJ57Afvvth4GBAcyfP98lrIPBoEkNkNXeKfDk99FoFPF4HNFo1DUOCl96wumxr9frU6r9A9u9xXL7vUql4hLZ9KrTcMFz5fpIcUyhz/nQQMHPIpEIYrGYGRcFLwsNNhoNUxCwWCxidHQUo6OjiEQiyGazmDdvHgKBgBkT58wxsD2/6vuso8CIARY6ZFSFNE7I3RqkIcJL1NI4we0NuS5y60AWJSyXy2ZcvIZrw/sqoxLkuKSRRH7GtBA+B8Fg0GxXyIKTXs+vV0SMfLbbefPbRQN4taMoiqIoiqIoijKj6QC2p9Ir9L9VXrTtLe1U4NBD3tPTg56eHpN7Lvegl4LPyyPP/mu1mmfhO9kPBbGckz03OX9eS1Euc+vt+dtbArYzlsi+pZGAIpXCXa4lPf2NRgOlUskUUJRecjsCwh6bTH2QkQVsQ64xCxfyfsh52Xn/9jrU63VTUFAKYbkVote9lZENtoeeRhQArjFJww7PlTUlGNXBcZdKJVd9A/mVbfo9837Pd7ufE7+fG0VRFEVRFEVRFGAGdwfwC4n2MgT40YlhQB7j98lkEr29vZg/fz76+vpMKD8FPcW9bZiQ3ndW/a9WqyYHnwJWGgZisRgAmGryzPOXVfABuEQvsCOvX4alyznIfHm+bGEsUxcYwi/XzhbgMkdfnsMt8gCgWCwaL3soFDK1Bui1l2Kd+fdsi/3LSACZesBaCnKOPF8e40uuB4U4ayrISAgZRSB3A5DI1AlbVEvjhux/cnLSpBXIKAL5HEuDUT6fnxIJIPES+F7HW6URyGvV468oiqIoiqIoSjtmNBIAwBThKvFKCWh1TLbj5RnN5XJ48MEHkc1msWDBAvT09CCRSKBcLhtRzzbpsZVGC5lvLj2+vJaF8yiYA4GACQ+XxfC8jBP0lMvK8hS0suAfx8H0A6YXNBqNKSkCNFxQXFOs12o1I/BlkUESjUaN+AeAZDJpdjeIx+PIZDJIp9MmQoFCX/bPUHumNUSjUc+0BcIdFGRRRUYlcC1lmD/D+Ak9/KVSyXVNIBAw4p9jqlarCAR2FGEEYNa5Xq+jUCigXC6jVCqZ9ZNGDRnhEAgETCoHDTd8PmhUoSGoVqshEokgnU4jlUqh0Whg8+bNnuvB8UtDjny+5Tle+BkO7DQDRVEURVEURVGe28x4OkAnAt9L6Niixo4u8GqvWq1i48aNSCaTyGazxntP4SgFFz327EOGuduF53g+BaUUlzInvdV85DjplZaeeukV5udy/gBM+DnFKQDXlnVyDHJevIbQ2MGq9qFQCOl02gj/aDQ6JUVBRkrI/PtqtWrqItih9nakAiMEOG9pdOF6ch62mJUGGZ7HvlhHgAJeGlzs9ZfinlEeMqJA1oWQBhavIokct72TAgB0d3ejXq9j27ZtqFQqqFQqU54b+1nxe77t50eurd97RVEURVEURVEUYAYLA0r8IgBaeS29RI19ri0SGZ6fSCSQSqWMeJc53VLkyfB4jkVuRUfRZoenSxHMAnRSJEuhKUPgeQ6jANgv+5TiWwpLjpvGAi8vOyMSpCGDgtMWldLQwLZlgbxarYZiseja3k96wQFgbGwMlUoFhUIBjrN9y0D2Fw6HjVjnulFgc/04XxZd5BqXSiUzJt4riUyTkG0CcHn95TGZwiBTQRhdwcgMPg+8Z+l0GtFoFIlEwoyPnzPCAthhFOJOEhxTOBzGwMAAHnvsMTz88MPYf//9kclkPAV+p558L+OB38+XoiiKoiiKoijKjKcDSE+ll/e+k3Bnv0gB6WnesmULJiYmTCh2PB4HsMNrLgUgxaMsFEcxLj3w0kMN7BCXzHevVCrGCy3Po4GBRgWZl2+3LT3N0svMkHaO2d51wM7Np7DlOO0UAC+vOsPqpdiWglieyzB7iufJyUlXaD7nYkdtyOgEu7CiNMTwXDstQ95v+aIoZ+qDl9HDNiTZwlm+OG9Gj/B7roV8fvms2M+nbRwIBAJIJBJIJpNIpVKu8Xkhr/MyeHXys6KpAIqiKIqiKIqiSGbcCECeSdiyLSzlMWC7d/iBBx5ApVLBkiVL0NPTg0wmY85jznez2US5XHZt5WcbAZjfLb3CdmpApVJBuVzG5OSkac+uBUCBy3a8QvUZFZBIJExfNCxQcDOagfn6PI/90PPMaIRAIGDqCdhV8qVIZV4/AFQqFeO95paAkUjEiH9Z8b5araJcLmNoaAjVahWpVMr0yXWWIpxjoMGFdQCazaYxeoTDYVekhZdxiPeH61ytVl330XEcY8Dh3OWz5tcmDQixWAyxWAyZTMZEZMjnlc+EPRY+f/Yzw3udTqfR39+PBQsWmF0XbEOYHI/Xs8/PvNIBvOajKIqiKIqiKIpC9pgRgOyMSPHyjMpjgUAA2WwWgUAAS5cuxcDAgAnhpufa9pLTI03xSWFH4esVKUBRWywWTZ63TC/geX4CVEYbyF0BgB2iTobgc+xMJ+BXnu9Vi0Cur11vgHPjtSzmxzSKdDqNTCZjPNe1Ws0YAJrNJiqVCnK5HMbHx5HL5QAAPT09iMfjiMfjJiqCayI97XJbRRmVIbf1A2AMGPK4XDcZjUEPPoU8j/GeylQMuWZSqLPifzKZNAYQWRBRFjSUY5DRB3KOXE9GcsRiMXR1dWHRokV44oknUK1WMWfOnCmRDl7PvPwqn3mvdAAV/4qiKIqiKIqieLFHjABexc5aCZdO0waYO16r1ZBMJhGLxTAwMGAK3DH0X4pR21sti+xJMUeByXxvGWJfrVaNQLT3o/cbp/Q6s10KWBopZMi8NATIa23xL79v1S9FNvuyxxyJRBCPx5FIJJBIJMxuA6wHQHEv6w8wrz8SibjWW4p6e005D68oBSn2vcS29PSzDTtFgoaOcDhs2pXjANwFA6PRqBH/jACQaQuyPVnQ0MvoIufHSA6mFfT29qJer6NYLPr9mHj+nCiKoiiKoiiKojwTdrsRQIpRW9C0Cn32Ez5eRgP5/dNPP43NmzdjyZIl6Ovrw6xZs+A4jgkXt/PipcffDvOnQYHCl+kBMoy9Xq+jVCqZdr3Cs23vP/tk2HwsFkM8HjftTU5OIhQKIR6Pm3oGLEhIMQnsKDgoUwWYjlCr1YyAllEI7Jded7kG0lsei8WM2AWAarVqahHw82w2i66uLgwMDKBUKgGACZ+XqQlybXicqQcyEkI+F7JCP8W7l+D28obLNAHbMCDvDw0JNBJxJ4RIJIJMJmOMSpw7x8YtAm2jkBy/jDThPajX68jn84jH4+jq6sKSJUswOTnpmoP86vWz4ZU+4/ezsjOpNoqiKIqiKIqi/Hszo7sDdOLRbOVBb2VAqFarGBsbQ61WQyKRQE9PD7LZrAkLlyHh9LbbbdheYumxtr3zFOWyoJ5dPM9eB7uegPR006jAvoAdIl+Ow/b4Sw87vdS8zq5wb68d+7K35pP1AnguBT1FvRTvNI44jmPC7VnHQBpf5LoyPJ5eeLkLg7wvdoqDLLhIkesnmNmWnYrBz7jurMEg74Vd2JHrad9HO71B9idTS3geDT2RSASpVAoAjAGlk5oAtoFAHmtnTFAURVEURVEURZmRSAAvD6mf59/LaOAl/OXnjuNgcnISDz74IObNm4dFixZhwYIFpg4AhTFFHK+l2AbcW8fJEHkiQ8GlqCMyNBzYkaNuh+/buwvY4fNSUDIPnkX66JW2Ixo4n2azaSIXOCa27+cNp7dfFi4EYDzjPJeiXnrw6RVPpVKmwGC5XEapVEKhUEA+n3dFEEijRbFYNPelXq+brffsNAdez3slnwEvQw7nxfQN+97yfTAYRCKRQDQaRSaTMedyjOxPGlt4n8LhsMsgwrHahgN+Lp8FGj8CgYCJmiiXy1PSUOyomXYRNK2+qiFAURRFURRFURQyY5EAUgz75atL/ASQfU2z2cSGDRtQr9exfPly9Pf3o7e31xWSDuzwNAM7RD5Fsy0Q5TXEFrHs3+slRZzMb5fz4XgoLAGYrz09PcZLzlQFmVsvRS7brVarrvkwCkB6tm3jheM4rjB3RgXIiAK2L3cG4DZ8FO+spM/oiHK5bIwBFPF2vQIaYWgECIfDqFarZk04Po6DY5HRCcDUqv9ynjTY2M8ODQBMtWC9g2q1imKxiHK5jLGxMQSDQZOKQYOIHJN8buxoABZOtHc+oEGm0WiYNbOf/1Zif2fQdABFURRFURRFUciM1gTgez9R0ipqwMsowNz3XC6HSCSCxYsXo7u7G11dXQB2eHHtrdrYhvTyelVnl55deQ3H5Beh4PW57SWmSJf9Mh+fFfFlqLktoGUfcms6O7pBGiD8tuxrNBouY4OdCmGnIEhRT4842wDcqQCMXJBzB9yREjRocF0omCmmpfFFRivY62HfC+mdt59D1jWIxWKmHxpFyuWyMUww2kFuEWgXXrQNK15GE7mbANefbUYiEZdhqh1eP0OdpNooiqIoiqIoiqLMaCSAfC9plQpgtyM/37hxI4aHh7Hffvuhp6cH8+bNM6KWYdfc9k7m8PM9Q9htgUiDgRSg8lpbaNJLzWJ8srK93EZOCml63aW3mgI3FAq5Qv8ZTcBx2sYMnlupVIxnnyH+vFYaG6R4l7n20mhBjzxz/qPRqMsIQIMD+6xUKuZ6e7cEr2dBPg+8Vm69x/HIHQC4TjxGMW175W3jCMW9NOCwCGA8Hke9XkcwGEQqlTJFAfP5PAKBgNllIhKJmGgLGjxkVAL7kFsuyloRHA8jVHhfkskkDjnkEOTzeYyNjWFsbAzVanXKz4jENop5/XxINB1AURRFURRFURQyo1sEeuU6A1PzltsZBKrVKsbHx1Gv15FIJNDV1YV0Om08sLKInxS+XqHj0WjUiHgp3uyIAdvzyzb5uR3u71cEUNYbYCg8P+OYGULP/HspfO1weh6zq/3b6y7HLNMK2L699tLjzv7ppZfrKQstsi96wIGp+fjy/sv0CbnetuHCLvAn8+f5uR1FIo0AsniiRPbPsXJrQB6T2wTK8UmDDvuQxRPlHGVkg1xzPndc10QigcnJySnGE/ZrR8LY33udrxECiqIoiqIoiqJIZtQIYIfP28JNYoe8y/Pz+TweeOAB7L333liyZAn6+/sRiURQKpWMGJZF7ewweQpE5uOzAF2lUjEebOl9l9dyHFJMy+gCKWClZ58V9BkBQC9/uVw24fBsN5fLoVqtolQqGS90PB6fEh4vDQL0yNsCG4BLUMrwfbuYHdecgp/h/RSyUqgz5J8GDB6XYf6yDgPXUYp6GXHBz5kSwLWQxhEi2+GLfUoDANsJBAKmzgPHYr8AmG0Zud72Gss+OF4ZYcBIABpv4vG4ecn155j5vDFdIJPJYHJyEs1m0+wYYP/s+H3vZxhQA4CiKIqiKIqiKJIZMwJ4iREvb7+Xd9r26kejUcyaNQv9/f2YNWsWgB3ilp5Vu0o/AJeo99tGjy8v77GdOiDFuLxehopL0ctc/3g8jmKx6NoSkAJe7mZAIVyv103IvByXfb2cK89lW7yG7xnaTkOALMAXDodRqVSMII1Go0in0656AmzbHpMsNCijCWyjDtMMmPpAsW2Le1ng0M/jbacX2LUQpDeeBgRpwGE7XJNQKIRKpTKlEKTclYFjLpVKUwo2yjoU9PLL+8nx0WBVLpfNuTQi2XO0fx7snxG/7zUSQFEURVEURVEUyYwVBpReSvmex+zQZS9vJkUsAGSzWWQyGaTTaQA7wuS9vMt2OzIvX4p1W7R7FWnzmo80MkjxaofWy636KMSl8Jch5nboO+ctjRAUnxTvdm48hbpMW+A10mPvJYyZjiD7sMPp7bQI2ZbffeRLGl94jl2vQRpVpBHAXh/7Hsj+ecyu/2Cnjci1YkoG10xGlMi1l2sk5+0VCSLTBjgmjqFSqbiiFuSuFPJZs4/ZPy+tzlcURVEURVEURQH2wBaBrc7heX40Gg385S9/QSQSwfLly5FMJo1gDQQCptI7AOORjsVirm3y6GllOLsUxTyfee/lctmkCXCcUpxKDzv7pQGgu7vbpBtwLAw1p1e6VCoZTzJDyAGY61ivQFbkt3Pn7dx06X3n/OT2hrKoHz3kdvV/W1DKe0hPdjgcRiwWM+fIIoTSICCjLbjuNOZwLeVWiMQ2BPiNhW3ZNQhkmgZFtawtUKlUUC6XjXGGc5bRFbZ3XxqPGMZfqVRM/7y3LCaYTCbNvWYUiCwqaNc9CIVCSCaTCIfDyOfzLgOEfM68Qv290mlsY4iiKIqiKIqiKMqMpwP4hXR3IlgozqLRKFKplBGOsrCfFMnSqw/s8BpTGFL8SQELwBynQLa3b7PHKftg+8wFj8ViKBaLU1IG/NaC6yA91vb87TWxQ+0BuMYsPfwyYkB65tmXDHmX46QhgTUNZMqFLcztlAY5NzkPztPPe29HW3Bc0vjCc+VYpIFECn87yoO7EXhFohC5btKQQiOALOInoxxoeGK7XoYIO1LDcRwTERCNRl2pHH7Pi1yHVkYBRVEURVEURVEUYAaNAJ1GArQ6PxAIoKurC6lUCj09PUacUsxRQBEpDu3igPS0UxDKHHC7oj37lt5hKdxsYec4DjKZDDKZDLq6ujA6OopKpeISoHY4uh0C7lUdXgphGzuPXObm83opZilY5XZ8tjc9HA4bsV4ul831jFSQ11Pw0kteLpdNpXuOw96yj/eBaRJyrlJAy7x95u6zb5kqII0c0uAj26Nnnvn8lUoFiUTCPA8U7/I+12o1E0FB4wGNAOxD7p7AHQbk7gSytgFTCWQhSkYkxONxhMNhZLNZFItFTE5O+v48yGdTURRFURRFURSlE2bECNAqxN9L3Hh5ZtevX4+hoSFks1n09vYiFotNKXpHYSlFH4vXATC7BxSLRXMsnU6bMG4KcWkMYGoAsCMP3K6wz1BvGUbO3QC6urpQrVYRCoVcuxcUi0VUKhVjRJAh6TL/n+JZilKZe87xeuXIe3nTpRiVhhA7/D4cDiMej7vWj8I7kUi4rmFUBY0AFLjhcNgYBGQqAQBzDUW3LfrlVwAuA4L9fHBctidcrp9tgOE9lIUgpUGE0QzcdUEWTmQkAFMauCaM/KAxQRql5NaQvL5UKqFarZr1kGkaiUTCpHPI+2j/TKkBQFEURVEURVGU6bBHdwfwO26nDjiOg+HhYTz99NM4/PDDkclkTKg+RSpzw2UbFHNsh4J0YmLC5VGPx+PGc8u8dWBHXjoAV4SAXVneFuNS2DMtoNFooFQquYRlrVYzXmyv6APOQ4bLS/Fnh7LbEQpe60vxHYvFEAqFjAHDjgrgebINztMrCkBGVVAA83u7DoEsmGfnxXvl5vMZkEgDkRyfnLedAiDTHrgtXzAYNEI8Fou51pG5/tIIwOOcj9z5IRaLGU++rHNg1yiQ21HWajVzHl80IIXDYTNeO3VD3tdWUQKKoiiKoiiKoiiSGTECSPEqj9l4RQDw+76+PgDAggULkMlkTBoABRwAV/E8vhguTs92ILC9IF+5XEalUsHw8DAikQhqtRoSiQSSySQAGBFPgcZCgNLTC+wo9MZr7LB3WfFewutlET/OmZ9xazmZcy5D3e36AOyT51KIyuPRaBTxeBypVMpV3I/XyEr6jHIIh8NIp9NTiuTRKy5z2+v1OqLRqNlWMJFIoF6vmyr6dhqCFOS2QcTruQFgvP402EiBzXvGNZRzpxe+Xq+jVCqZSASeyyKN4XAY5XLZlQYgjT9e9SZskS7vLdNNaFTgV25JaI+ZERtdXV0Ih8N49NFHUSgUMG/ePN/aBbzONg5wbIqiKIqiKIqiKMAMbREovdi2uPc7X37vOI7xqlOUSmFne8K9igXK3O10Oo1oNGoEnpdoB9xeeHr3eR7FvxRabD8ajRrxLT3I0sPOfr3C/O31sIW9HKs8j+fINZdecnqso9GoKxTfvk8ATG4/1zKVSrlSE2S/ctcBmetPoU8jiy2YbWSagzTiEJkeIJ8Rmb5BT7q9Fn6CmPcyEAiYXSDkfOw+7RfHyfQBGjS4RhxbuVw2USCMImDkinxm5TPG3QJisZgxdnn93Mh19YqQUBRFURRFURRFITOWDmDTKg3Afk8PbyKRcIkkWzBKj7RXFXZge8h3X1+fEagTExPG4yvFGwW9Haou89cLhYIrhJvbw6VSKZM3XywWTf6/FMWhUMjsM29XmJdpB8wLl558ClTuZW+vFZFCmiHmHBvTHxjCL893HAelUgnj4+OoVCpmNwYaDuzoBI6XHn/er3Q6jWAwaGoLlEol19jk9XJdZZusleA4jjFKSMOIHDPvhVcagIxAYLsyCoOe+Wq16to2UUYi0PjEe8fP6/U6isWiKzpFri3vFddHtknjgzSwyLoN8Xgcs2fPNhEqO/Nz5RVNoSiKoiiKoijKc5MZNQJ4hSrzuFcocyAQwPj4OB5//HEjinK5HACgu7vbiD7psZbbuNEYYBd/k0XpKMoZis6QewAujzKPeXmDJXIPeFagLxaLKJfLAHZ4s4vFojE+2JEAcjs+r0gCO2zfaz1lCgKvi8fjSCQSSCQS5hpZsE4aKfhiiDzD5AGY8fF8WVE/lUqZsdHwIrcLtKMsGAYvC/vJSANbwNvefS+h71UXQUZEyDQIeR7vhV0M0TY4yPx9HpOGGaZ2cH3t4pW8TtZEoAFBPjs8Lx6Po1arYXh42BgGpoNGBCiKoiiKoiiKQna7EcBP4PMzeZ59HQBMTk7i0UcfRV9fH3p6elAqlRCPx43YlvnrfikBFFoUstFodEphP5nfLb3cUgTa47PTHGRfFJONRgPlctl4yCkMWRneq+ibDDG3Q8VtYc+xybx42wDA90wFYHi5XVeA58l97mXbshaBXFtGGQBwhbrb39spB3YUgPTqez0TMgrEvg804gBw1QmwazHwvfT228YjpnqwXXlP7GeMyHQHrqlcAxZOpAFFrgXvrxyHTBOR98wLv9Sadp8piqIoiqIoivLcY8YKA7Z6T7wEC7dfY569LHZH8STDv/megkmG4VMkFwoFV0QARaz0KtvCVAq0er1uvNAUi+yDWxBu27bNiH6KfXrHWR2ennIvD7Y0KEgvOQWwLEjot562YYJRExSjDNvn2CleKZ5pNKBRgwK5XC67jCyBQMB1f+Q2gbVaDZOTk+ZaaQSg6LZD9+Wc5frbRgQvo4FM6bAL+cm1kkX7ZN80WthGISnebQOSvFYakKQRgOucTCZNu7LeAb+nsYdf6fkPhUJYvHgxKpWKqV2wMz9PiqIoiqIoiqI8t5kRI4CfGLGPe6UDBINBU7U/nU4jHo8bL67tUZWiTYpGWSSQ76XI51e2wTx0GcYtvbXMH6f4tIUgDQHSyx2JRBCNRk00QiAQMEX0ZG45++B7Cnjp6ZZrxK/2NoIyzJ/HpBGD2GPnfZBebgAuA4H0hstxMJVArpOsri/nanvC5f2z5ybvJ8dn33PZtv0seJ3rdb79LMo2pPC3jSutoIEoHA6bZ8BOYZBpKtLwIe8Rayww7YKGqHZ9y7VUFEVRFEVRFEWZsd0BpOD3y/+XX0k0GkVfXx/mzp2LWbNmYdasWabafL1eN0IZ2OH5lSHobJ8wxJtebkYMlEolcx4jDyKRyBRxXy6XTd43DQHSU88xjI+Pm634enp6kEwmkc1mjTeeW9DJdpkiUCqVUKlUTCG9QCCATCZjhCSFsbxe5tezCj2919waUVbv5y4LNEzQcOE4jlkXGS5fLpddKQIUr7LwnTSgMHJAFj2UBQ/Zht9OALbhhfeU58koDoms5m9X9ucayXNlbQNGEciIBdvzL6M+bIMIny251SHnnU6nTXFLe+tGe6tH2yjBlIR4PI54PI5wOIyJiQnXjgG8zkYNAIqiKIqiKIqiSGakJoD86nXM6yvFVSQSQV9fH7q7u5HJZFyikYLMax93Gb7fyvggvbLsm6HyhULBiEMKWop3GgCk2JOik+3GYjGk02kTxUCRTyOCHTIeDoeRTCaNKJdi3s5XZ4V7+TnnzrQDhpVLI4sMt6dBolKpoFwum9QI6b0GdhgNWBmf7dtCWvbPcUmxzCgECnjZrp0OIQW3rLYvvfAs7sj1lxEQXjUEvGpH2M+d7UGX6yXvt10jgGOUXn0aBZLJpBmrfNlRDVwfGhK4ZvxZCIfD6OrqQqFQMEYArwgHr587RVEURVEURVGUPbZFYCukJzcUChkDgL1NGgWZFH52O1KceZ0jhZ1sLxAIoFwuuzzEFL4Mc5c7CrA/GTZPIwAr8kciESP+6e2nwKMRgN7iRqOBWCyGyclJkwdOcc38e0YqyGryMjedQtwW2XLMtVrN7GBQr9eN6LfFLAUoUydY3FAaa/iZnQZgr488X4bHS8ONFPnSWMP1lfUSZD699KrLUH0p1qUBQAp56VG3nxUaI+Rc7JQJ9sl14i4E0WgU8Xjc9WzJscvniIYcOQ5Zg4I1Ahgd4IUKf0VRFEVRFEVR/HhWGgHoEX3ssccQj8exdOlSRKNRANsL/VEIUVRRjNGL3Ww2zX72MrS7UqkY4Ser5wOYIo6bzaYJx5f56QBcIo9iToauM6SeudyMHhgcHMTIyAg2bdqEXC5nCudxHDR07LXXXojH40gmk2Y7P0YhjI+Pu4wCwWAQsVjMrAPnGAgEjJedKQiTk5MujzwFO1McOB+53z3TLWzBTIOEvRMDANdnvC/8jOKdQpb3mqKa9zCZTBqjCMdvG2q4dmyX90YaFOxcfymopUHA3vZQpgJIY4LMx6cxg8fZF4U/vf80ZMg5cl3Yn3y+vODzmEgkTFoADTh+2JEviqIoiqIoiqIoe6QwoJc48TpWq9UQjUaNEAa8t8KTQoqfMxRe5nJTvMrt9qQAk3ng0mtsGwHskHo7h5vnkHK5jEajga1bt2JkZASDg4PGwy8FZaFQQDKZNFXkM5mMqU9AYZlOp41BQ4pKuTuB9JxzzhTbFNPSCEABLLc3tOdvC32ZX297xe11I/JeSe+9NBYwBUHuWFCv103khe35l/dERkXIXQLYt7y3XCOugbxvPC6fTTlPposwWsK+37JmAcfMecqUAZkSINMg2JdMR5BRFKyLQAOTl/FADQCKoiiKoiiKongx41sE+okTmY/Nr9wRIJVKmTB8tiHFPQvfcQs+hoTL0HCKPgpKe+s9ea4Ul0RGEMgCeXYoufRIU8ROTExgcnIS//znPzE+Po7R0VETLk+RywiHcDiMJ5980njD+/v70dPTg+XLlyOVSmHBggWYnJw02xBy3PT6AzDtScMAxSvrEXANa7Wa8bizGKLXvWOEAQ0B4XAY6XTa1EdgfQBew0gM+Z658TJtoFQqmf67urqMgKYhZ2Jiwmw3mEgkEIvFkMlkXCJc5r/TwCPvjZ064JUCYN9b3h+5M4C8ZxyzjJ7gMyJ3g5CGJjmGYHD7Fowy8kQaFVgbgFEt4XDYbKfIlJBGo4F8Pj/lZ0sNAIqiKIqiKIqi+DFjuwOQVuKEn23atAljY2PG+y097zyvUqkYIeiVHy09rbJ9hpHLAoJeHljpGQ8Gg0Y4215ke/z07FJMVyoVjI2NYXx8HGNjYyYCQF7Dl8zj53i2bt1qjAbd3d2YN28eYrGY2TKO9QU4J7lLgIwCsCMlOH/p1ZZbJ7LeANdH5sNL44UsrGfPxxa/bNNxHBMd0Wg0TNHEaDRqCiJOTEygVCohl8sZww3Hlk6njZGEOy9EIhFzHsdDwS+R6Qv2mHlPGTFhGxHkOtD4wPWT0Q8cA40EjGyQKQaMxJD9yudQbucoiwTyGA0WPC5/fmyjm6IoiqIoiqIoCpmx3QGmw+DgIJ5++mkcfPDBnkYAKbRsMSSFGw0EHAO90yxcx9B5ClnpSeXY7YgBr7nJ62RBOwCoVqvI5XIYHR01wpZef3tnAlugNptN5HI5OI6DUqmEWbNmAQDmzJlj6gcEg0GUSiUjyCk46TmWuwlQtMraBTQUyAKLsuo+0w6kMUVuwehnCJHnSw8414kiG4ApnBcKhVAul5HL5bBlyxbk83nkcjmXRx4AkskkUqkU+vv7XUUX7edNimveJ64vnx/7JcW3Lfp5T+T5drQJABOxUi6XEYvFTG0IrglrLdCAwG0VOWb2w4gORhdIQ5F8xmwjlv2salSAoiiKoiiKoihkxiIBbIFNvFIFKCQZ/i1D0OnhlrnQ/F4W2aOojEajrjxqAEin00aEsSq+rCFg79vOsdnI4nNehoN6vY5cLoehoSEMDQ0hl8sZYc5wb/lebn/H4od8X6lUsHnzZmzevBkLFixAf38/DjzwQKRSKYRCIYyPj5sicSy8xzky/UGGn3OsFPtcUwBIpVLmnFKpZNafWwdyPWSUgZy3XfFe1iaQRoV4PI50Om1qPjz55JPYtm0bnn76aVM40csAVCgUMD4+jpGREXMPly1bhmg0ilQqhWKxaOYnU0d4b2VtBAp0eZ/lc8i58FliWoA0SgBwGVp4X/P5PIrFormWc+EYpMFI1rrgfDl2mSrAsbNQJo0VXB/7eVUDgKIoiqIoiqIokhnbHcAWn7bHUr6naGLYuxQ0zBeXIkmGYfNcfs7rpbij8GNbvI6ecjtnXIo9KWrZt8QOmy+XyygWiygUCq4ifGxTpiPQC2x7oWXOebVaxcjICIDtxo9UKoVMJmN2GpDCnC/p9ZYCU94Xe04ySoAve0s8rzYpmBn6z3tre/NZ4Z7bIZbLZVM4cXx8HMVi0UQxSK83sMNLXqvVMDo6inA4bIRxLBYznnave2jfL/lefm+nh/B+2OKc50qjh+xTrqf9ObGNT4FAwBgN7MgKuZbyvslxa00ARVEURVEURVH8mLF0ACmC5HH7PGC7J7qnpwc9PT1IpVIuwSO9s0RGAZRKJSO86Uln29L7GolEEIvFEA6HTd51pVJBtVo1RfC8thOUYdkUY/SmS9FOz/rY2BhGRkYwNjZmiudJEcixcCu8ZrOJYrEIx3FQLBZd6Q70sg8PD2N8fBwLFizAXnvthQMPPNDMZ3BwELVazeTYA/AUl+Vy2TU/Gb4vi9LRcFEul41xxq7PIO8d15T3p9lsmr5Y4T8SiWBgYMDMe+3atRgcHMT999/vyumX4flyqz6eEwqFTPTAokWLMGvWLAwMDLiiPLwMOIyKkIYOOQ/pnadhJRgMukL7eT7vvW2kkNsOyvQCAK6dA7iWHCcNUnKnBK65TGfg+ZFIxBWR4vWzpSiKoiiKoiiKQvZIJIAfuVwOGzZsQDgcxuzZs5HJZIxYIxT7UrhRTAE79qGnwKVYlB56Cj9+z3MYFs5wbRoNvLa/k4Jf5vbL7QoZEl4oFIywlzUIuC4yGoECUBoKGo0GSqWSy7sfCASwadMmxONxBINB9PT0IB6PY2JiApVKBcVi0WU44NhZbDEajZrdAqSHmoJfRmVwjb288rZRRkYzsE8Z7RCPx42hoFQqYWhoCOvXr8fQ0JAxkjDX3jb+yDXnujFlYMuWLXAcB11dXUZ8y60PpcCX+fyyXoD9vTSQ2IYgKeDlmnBcdgSJrPcgt0mUKQLyvtsRAH4/Q3w+W9UEUBRFURRFURRFITNmBOiEyclJPP7441i+fDn6+/uRSqVM4TuKVLlNoAxFpyecnzE/HoBL4EshLkWfDJGXHnvpgQamFoaTL/YljQDczo91C+zQbc6rWq26DAnSS91sNo0RIBQKGY/05s2b0dXVhUAggO7ubnR3d+Opp54yFfaZTkFPc6PRMNv0sU8ZNi+3EbRFrjSk0BMudyOQBe1oRJG1AKQRgIaLYrGITZs24emnnzb5/VwX1miwDQBsg/Bebd26FeFwGPPmzTNzkhX4pdFFimRpDOL45X3y2mVCeun5mSweKe+xnUJgFySUbXLtGHkgU0S8nhu2b6fayJ8PRVEURVEURVEUybPKCBCPxzF79mzMmTMHAwMDLlEUjUZNUUDALYrK5bIJ12ZxOLlfvF1J3c7XJjyPuwjIon9SjNlh17ZAk1XwKYblPu80OkiPtu35t6MKgB258Dw+NDSEZDKJhx56CPvttx9mz56NvfbaCyMjI3jqqaeMJ5w0Gg2T7iD3sGelfzkfe996RhRIowDFMKMEHMdBPp83KQSysj4NEiw6SPH/6KOPmiKA0vgiDQfsk3NhagLrPdTrdQwNDSEWi2F0dNSIZKZD8Ktca3kvvdIP+PzwWmlUoNde1hlguL7dHu8fjVC2t99Gevbl9fLZlddzDfyKWaohQFEURVEURVEUybPCCNBsNpHP51Eul5HNZpFKpcyuAHb+vAzzB+ASjFI0ShEuBT2FHq9l214eZ57Dr16ef9sLa3t4edzLo2v36/W5RBovWCQwn89j48aN6O3tNVvlsR6AHVIP7DAEcB3kmGXoO9dBzl/mo8s1l+OSBQC5ZjQSxGIxBAIB1Go1jIyMmG0TWW2fbUrDhbw/MjpCPg+BQACVSsW8otGoa0tCGeXhZUSy75G83/bc7XvAcfB8mSriZySyI0Jk/6xFIO8Z2/AyAkhDkZeBSlEURVEURVEURfKsMALUajX8+c9/RiqVwkEHHYRsNotIJIKJiQmXFx5wpwHwPUPHpXdWin8KRXubNlkwj8X3pEeVgk3mXDNM3vb2SuEnhaztKZcvYqcrcD4yZ13WPZAe/uHhYfz617/G8PAwlixZgiVLliASiaC/v99sUSe3nvOKBOD4ONZkMukS9Xxxezp67LmOrNQv1zQUCpk6BwydTyaTmJycxPj4OB555BGMj4+bbQntSvoyBJ/f27sUVCoVszacV6VSMVEHsVjMtOVVgd828Mg+q9WqST9hZAPnJdMdZIQJ25XCXG4HyXvH9ZLpLHJ3ARoViG0UsZ8vmfagKIqiKIqiKIrSij1qBJDCiaItnU6b/dClCKbooviROdjAjtxrGgLs3GivsPparWauYaE828vrl/vPPu1K+RSy0gstDQRe3nWOSYaqUzj7ecdlDnu1WsXGjRtNMcBUKmUK8MndBjg+CmEKftuoYacnyOr28p4B20VurVZDpVJxpTnwOvZDrz13S8jlcsYAII0adv69TA+QayDb5/h4T+2wfHlP7doA8l7YBiCZumE/Y1wnpmcwfYCf2UYiO9rCTvVg33YUgByjF7bxSX5VFEVRFEVRFEWx2WNGADt0OR6PI5lMIpVKIRAITDECUNwRWfVdhlLzM9sIIN9TMMq8de5CIPPCbcFoCyvpxaVQl55seoptI4Aci3xxvrFYzGWYaDQaZttCOUYp6jdt2oStW7cimUxi9uzZ2HvvvY0nvFQquQSzFNRyuzqusSyWxxdFPgBTEA+AiQ6goGfRQXkf6OWmEWBoaAiTk5OunR5kHQS5XaIdISBFu1wLGgCYWsD7IyMZ7JQOuz0amngtv0pjTqv7zWgOIr36jATxMhRI45N8tuxnxS8FRa61bQBQg4CiKIqiKIqiKJI9ZgSwhUxPTw+6urqQSqWMQKd4YxX7cDhswtgBt5efYpBCsFgsolarIRqNmvB3O6c8HA6b7eoo6ijI7DQEuRUcxZmsDk+RKSv48yW35KPXXObj22vC8HE/4SpFOsUzx/XII4+YInmsrRCNRlGr1VCtVs1ceG2hUEAikXCNo9lsIhqNIhKJGMNAoVAwxhoaavL5vLlH8XjciGUaGhKJBGKxGPr7+1GpVDA5OYnBwUFs2bLFhNjLKAPuGsAxNJtN44W34XW2R99Ox+AxRiKwPTus3hb1sq4A77NXdIdtmLJrLng982yX94D30H6+ZLtyHnLLRwCYmJjA448/jgULFiCTyZjr1ACgKIqiKIqiKIrNHq8JUCgUUC6XEY1GEY/HTWV+WYBN7jkvRZAs+MbPGZ5OkSlTC4AdKQh2SDavkdEHPJ/iXgpNuYWbXdGdL+llp/Czix16GQHkXOR5fukEnKfjbK/OH41GMTIyYrzTLDZnh5jLiAu5LR3FsqxDQEOMjMCQ0Rp2eDuwvSo/oxpqtRpyuRxyuRwmJyc9CwxKYS2PeeG11nzJ+ybX1Suaw15LaRyQ6yTXQ/Ynn1U7wkPWH5DPB/uUNQ5keovtyedX2bdsp16vo1AouGoPqAFAURRFURRFURQvZswI4CVKHMfBQw89hE2bNuHwww9HJpMxRd4opOr1OsrlMqrVqtnOjuKa3mp6n2u1GsrlsnnRw8qCcfF4HJFIxOXB52elUmlKNX2Za04h71UAkB5cGgooAIPBIJLJJBKJBEqlEqrVqgmBl4YEQnFHYVkul6cIXRkFQS99pVIxnzmOg4mJCTz88MPYd999AcAYV6TnnP1wu71gMIju7m4Eg0HUajVjPGA/uVzORDiwqF2hUDBzoShmikUoFEI6nUYsFkOxWMTmzZvx6KOPYuPGjcjlcmbt7GgHYGrKgl/4vuw7k8kgk8kgkUgAgKs2gPS6y+dQGprsdmWIPiMt+KzxvYwg4fMp50HjED/nWCj+y+WyS9xzjrJGgh1RIO+zjIawa2SoAUBRFEVRFEVRFC92uxHAFnheUFTZFeClpx2AS2zxvFqt5grBDwaDiMVi6OnpQbPZNFXpY7GYK9ycXuxSqYRarYZSqWTGI73Udki3FK80AHAOUsBzvizQx+3xvF4y8sBrbaSQtQWhFLL0PFO0j46OIh6PY/78+VNy2WWxOwpPriXD85lWUalUXMKZRgDZhhwXizwyAmBwcBCbN2/Gtm3bXNEZMq9finyvGgAUwzzfjuhIp9NIJpOuegVe2y6yL7kVoh3F4XWujASQYfxyjLxGGou4O4CsU0Di8TgAuGpZ0BjFKI5IJOL5rEgjkpdBSSMBFEVRFEVRFEXxYrcbAdqJf4orije51ZwUXxTd9KjK6v40IgQCAZN/Lwux8RiFOD3ypVLJ1A4ol8uuVAOKNzscX4Z9SygobS9uPB43ufFSePqti59gZbSDbJvHpGEiEAigVqthYmICIyMjiEQimDt3rhGU9JDL0HJZS4H3gGMpFotmbYDtQrVSqbjy16VRhhEa6XTaRDOsX7/eGAHYJ0PXZQi8XwFAO0XAXh9GAqRSKTMm3hOO2WtN7Z0IbPHO8+WuADQacL04PhYF5LPIaBUaTBjdItNIWN8iGo2iXC6jWCwil8uhVquZ5yYajU5ZJ6/nzk6bUAOAoiiKoiiKoihe7PF0AClepUCjmKOgohHA3hNdeu0p/O0Qa4b0l8tl421lyoAU0dLDzzYY9k0jhZ3TDcAYI+gplvUGAoEA0uk0KpUKxsbGjPil0KanVxbAo6GBAp1RC9LbL9eUHn65NuFwGBMTEyZsP51OI5VKoVgsuowJLFhYqVSwdetWI0pJoVBArVZDd3e3aUOma0jvOFMKGHUxODiI4eFhrF27FpOTky4hLz3mXG8ZMm9HOchUCBn6zmKRyWQS0WjUFZ0ha0bwGi8DjD0ePjPyfGmAkFsCyjoVnAPTR/jsclysncC2otGoMX5MTk5iy5YtGBkZQaPRQH9/v/kZkNENMrJAjpvnaASAoiiKoiiKoiitmDEjgJ/wssO/eS4FGM+VYtEOi5fGBHpeZZi+NDTQCFCpVIzolO1IT7OMRLBzru3+5TW2QSMWixmvLkUzhZysBu/l6Zbzsz3kFJVetQiA7cX8CoUCCoWCCdGXuezADkHL822hzHEypYI1AexCi1wn1h8AgMnJSYyPjyOfz5udCbzC/OUcpTGEayK94HZ0BOfFudni2A6f9xqDVzqGfM7sFBVpUODLq6ClnbIg+5Fj4BaLhULBGGkYrWLXReB7OU+/XQUURVEURVEURVFs9vjuAPRsStFjC2GGWtv5+BQ8sqBesVg03msaD+z8fbl3vNxykOexABzTCvwq1FMsy+r/HIvMee/q6kIoFMLExAQAuIoQSjFo547LNAgZLSHrGrB/uZMCjQPVahWNRgPr169HsVhEJpNBPB5HNBpFoVBwedgjkYiJUrDXGwBSqRS6urqQyWRQrVaNEYXjZFG+3t5eFAoFjI+PY+3atdi6dSuKxaKZk9fuCFK8ymgH+zy5e0EwGEQikTAFARmBUCqVjDi2d0Tgmtm1B9gf0xwCge3FJAGYXSYY/RCNRpFIJKaksXAbRr74DMh0FfbJcwqFgnlmx8bGMDk5iUqlAsdxMDk5iUgkYrZepAHJXiMWx+SYFEVRFEVRFEVRWrFHjADSuztv3jyzT73crs7OfydSNMqUANu7a2+XBuzwntpF6aT3nt55uxK/7bmWY6CQlG1StMuw797eXpNnz9x62aaXp5/jk4USKSzt0Hk5Lvn98PAwms0menp60NXV5RKMrOZPwQnsKFQH7Cj6x5QKrg/vDQ0m/FqpVDAxMYHBwUGMjo5iYmLCJbrt4n5SjMv1lP3bIfmBQACxWAx9fX2YM2eOSVUAYIoYypB+mR5i9ylfrIkgz+PzAsCVBsFx0eAijQ5y/bxqSNhjCIVCSKVScBwHiUTCfI3H4660CN4Du2CljATQdABFURRFURRFUVoxI0YAW5hIsbJo0SIsXLgQQ0NDLpFDUQ24K6rb3nBghxFA5stThNu1Aey8elnwjWKL0QEyzN5LZMuweaYiUCDy/EajgWQyiXg8jv7+fgDbw+QpvmkI8NqFwGsOst4Av0pjhVwbXjc4OIhSqYRMJmMq6UciETiOg1KpZEL4k8nkFMHMugTMdW80Gq56DTIsPxgMolgsYmRkBBs2bMDQ0JAxAsh1b2U8sbHz9GlUSSaTmD17NvbZZx/09fUhHA6bkPpWRgCuk516QbFvp4fI54nREoyAoECn6JeRIbIfr/akQYTe/Ewmg0ql4jrOCAIZvcL7wLWkEcCeoxoDFEVRFEVRFEWxmREjgBT90uPLz2TxOylqZY41kfnYMh+d5zLnnYKI4pSCu16vm/B0AK6Qf46LHlgpqhhaX61WXYUDpeiSaQcM5a/VaqhWqwiFQshms2g2myiXywCAfD6PfD6PWq1mwsCliJdh8ZwvCwpSgHJM7JuivVQquSIaCoUC1qxZg3g8jq6uLvT29hqjiwx355rRs59MJs1nlUoFhULBdV9lmH21WsWWLVuwYcMGPPnkkyblwI7KkJEZMv3DjvCwUx8ovOfMmYMFCxbg4IMPRn9/P5LJJEZHR11rb2+JKI0oMvWCwl+mI0gBzagObicpa02wtoMsAsgaEByHfMal8UF+Lq+VUQKM9CDSQEYDEbCj5oBtaFMURVEURVEURbGZ0cKAXt5JWxB20o40AADureCYpy295XzxXIpavpeeVLsWgBSm0gPbyoMtj8kIBeaTZzIZFAoFOI5jxiIL58lwdM7ZDmX3C22XIlcK2Xq9jomJCeTzeRSLRcyePRvhcBixWAzlctnUY5DiNBQKmW0VKeRl4UH7ftRqNYyPj2NiYsJsdcf7KoW2nfJgY6+pXOdIJIJ0Oo2uri5ks1nE43FX0Ui7kKNteJLpBrYBQvbnBQ0Rsr1IJGK883x+ALi2T5R9yeeOfcpnj0hPv0ylsFMq5POrwl9RFEVRFEVRlHbM6BaB8qsdHVCpVMz+8baHWELBJz+nUKUAtAURhRI9tDK0nWOIRqNmazuKYBZ2C4VCSCQSaDabiMfjKJfLKJVKpkq+9DxLcUehyPOi0SjS6bSpZp/L5RAKhZDL5cwWhrLooT0HAFOEoBT/HANhCD5D/4vFIgYHBxGLxbBgwQIkk0kMDAxgdHQUjUbDhNLLrekymYyrFkAkEjHjdBzHFKVj0b+RkRFMTEyYc+TYJbLegy3E/YwrsVgMyWQSPT09SCaTaDQaGBsbAwATXZFMJn3Xzn6epIGG19hi3Rbm0lAVCARQLpen3PNqtYpoNIpUKoVIJGIiEqQBgM+KvKeyWKRMBeFYGfEhIwmYGpHNZl1pLoqiKIqiKIqiKF7sdiNAp55WP++rjR0yDuzwpMqwahneza9eL15H8R8IBDA5OYlarYbJyUmT755MJhGJREyUQDQaNefRCywL+EkRSUFL73wkEkFPT48xLESjUZTL5SlRAF4RD3IbPHtNuI4U8naBRWB7PYJt27Zh/fr1yGazpk5APB43UQlyxwZbrEshTGNGNBpFsVhEsVjE5OQkyuWyKwWA47IFNL/a4tU2olAM0wiQTqdNMUmZmsE1ks+TV5i/NBgBO3YM4PVMqbDH42VEkPUBeC7XkcYXCnz5TMhIBbvwojROsB/7mCwYyGdKRoVoVICiKIqiKIqiKF7sdiOAFMTymPwKuEWbl4CxP6fgBnbk9cuK/rINuX2eFMbMoafIZz/c235wcNDsQz8wMIB0Oo2BgQHTT7PZRLFYNF5ou4gdPedst1armWP9/f1GKEajUeRyOSPyyuXylLWR4pVzssPc5bmRSMQIbJn3ns/nUa1WkUwm0d/fj/33399Up+c2jY1GwxSoY5tSYDIlIJFImCr2o6OjyOVymJiYQKFQMIYRKcKl193ezk4aPuzcdnmPUqkUstksksmkEeu8jwBcz4V8/uRLro9sg9f7PY/Smy+FuQzH57mNRsNEtkQiEVeEgV23grUjZFFA+ZxKAwK9/zRg0dgSi8Vc6SpqCFAURVEURVEUxYsZiQTwMwRIoSJzuumlZbE8L693NBqdIkwpjGRIOz2mzJOnaKK4TyaTiEajqFQqRsRu3rzZhHnXajUUi0WMjo4iEolg7ty56Ovrw8DAALLZLNLptNkaj+MlFGVyCzl62IHtxos5c+YgHA6jVCq5vO+2iOP30sghj8m6BYxK4IueaUYWNBoNrF+/HqOjo3AcB/39/ejt7UVXVxdqtRry+bwpYEgjhvSWR6NRU9+A+90/8cQTGBoawujo6BThy+fA6/57pQLYHn5GKvT09KC3txe9vb1IJpMIh8Pmfsp5895L449XLr4XUsxLowHb41htI4zcXUIaU/g8yzQXOSe2RSOARBoAAoGAqX9gf0YjzhNPPIGxsTHsvfferrQQRVEURVEURVEUske2CCTymAyHljsA2MUCpfiVe7DLYm8yLF+KOZlvL+sH0KNaLBYxPj5utvDLZrOmTYa5c7eBRCKB7u5uxGIxs7d7tVqdEoEgx0yRKLeZS6fTSKVSJs89n8+7zrU9015h6rIPilP7Wgpqisd8Po9Go4Ft27YhHo8jk8kgFoshFAqZQoGsiQC4C9UxmoGh7xMTExgZGcHIyIhrm0QZSeCFbQiy7xePyUiATCaDRCKBaDQ6xUMvRbtMpfAyItk1FWxBLyMEZLSFV6oCkUYpvqdhQhoBOCcaLmzjkG1UkGvltZZsr1AomC0ZFUVRFEVRFEVRvJiRdACJbRCg0BkaGkKpVMK8efOM0JPh/USKYOlhtz29rExP4c+t9GQ4ONMIHMdBoVBALpfD2NgYotEostksli5danLeN2/ejPHxceNB37BhA573vOeht7cXPT09pko8+5VzozdY7jOfy+UwOTkJYLv3eeHChcYAQK+wLDonPcYy7UCGpMv1YEoBw815vFqtGgNEs9nEk08+acTpsmXLTK795OSk2eKP4pNr1t3dbYwFmzdvxrp168yWgNIDTeErUxlk7r68F3xWbOHLwoPZbBbz5s3D7NmzkclkAMB426UxCMCUlA/2J8V9rVYzhg5ZbI/9svYCIw1kdAnXlOvKcdOQZRszvCr685mUKRu1Ws0VJWDvckCDFYs0cj3r9ToqlYqZjxoBFEVRFEVRFEXxY49GAgA7jAQUVfQkSyFme2yBHcXVWJVe9gXsCMWv1WrmuL3HuwynpzecAjkWiyGVSiEejyMej6PZbCKVSqFSqaBYLCKfz2NoaAjNZhPz5s0DAGMIkEYJO0/cTl8ol8smtL6vrw+NRsNs5WenF3DeFLQyxYBrIw0Bcj1sLzXXllEBQ0NDmDNnDtLptKmPEAwGTZ46iwBSnNZqNQwNDWF4eBhjY2NG0Nr3SXr7vbzp9lzs47L6fTabRVdXl0tE+62x7Jvzl+OSRgG7er8cu9yNwmuXA7m2MoXBLhQpX7IwIMcsq/1zVwaOza7FwPFLY83o6ChGRkaQz+fVCKAoiqIoiqIoii8zVhOAeBkDKKKkaJeV8KVHXwpKuTWf9LrK6vYU9cFg0ITy80VCoZARXclk0hRvYxX6RCKBTCaDSqWCYDCI9evXY3Bw0NQO6O3theM4iEajJhJAepA5ZxkSTqFaLBYRDAaRzWYxZ84cJBIJDA8Pw3Eck5svhSvD8GVRObmGnKPdD+A2QshzxsfHUa1WMWfOHAQCAfT395uaCRMTE2g2t2+NyLWoVCqYnJw06zA8PGwiHmjMsb3kci1kGL+MYJBbCtKgkUgkkE6nMWvWLMyaNQu9vb1mqzyuscyTp4efa8G14uccByMWbGMKx8XzuE5cX7s+gJe3Xz5j0tAk+5bGGlknIJ1OIx6Po6+vz5xHDz8jR2R74+PjGBoawrp167B582ZjRFMURVEURVEURfFixtMBvAiFQli4cCGSySRmzZplCqDZueUyJFqKM4Zz0wAgBWIkEjGGglgs5hL/UrAx51x6XovFIkqlEgKBAFKpFILBIHp6ely514wKYGoBQ9s5DhmOLrfNo1hnGHm5XDYCcOHChQiHwxgdHTWC12tNZa6/nZ8uj8m0AemFB2CiEWq1GtatW4dqtYp99tkHAwMDSCQSyOVycBzHGEcajQYeeughbNmyBRs2bECxWDRGk2az6SrmKLfNs4vcyTlwjSiypYEiENheBDKdTpuoj2KxaCI9pIFFRonI54PrQaHNtZHPGM+Rot6OQLFrPNCrb4f+8xyv6AJ5H+SzzPaSyaTZcUH2Q0MXnyvWRGC6Co02ftEKiqIoiqIoiqIowAylA9hITysrqWezWaRSKVMLQHpaZcE2W9hKjze9uTJMnBEFLGYni+XZhQVpDGBbFOCNRsNcz/D0rq4uFAoFs50e+7FFnS0qAbjEKMVxpVIx6Qc9PT2YnJw0aQi2uLTXkcftiAs7B92+BzItodFoYHx8HJlMBs1m06QnxONxAEAymUSpVDLh5yygKAsBynvi5f33K2zndxzYkfZBESw9/bYxgWtLMS9TQWT7MjrFLzLFy/BipznYdQ7s59GrX66V3Q6fiUgkYp4jwrVlZIM0XkWjUZOmEYlEXHNrlYajKIqiKIqiKMpzkxk1Anh5gdeuXYuRkRE8//nPRzabRSwWQ7lcNpXpKbTo+ZSh2/a+6DJtgIKfX+lRlmkGFHsUlhRpLAAXi8WMIYBF7xgWP2fOHIyMjBgBb3uWGYEg87+lIOMxFgAsFotoNptIJpOYN28eAoEAxsfHsXXrVuRyOVM5XlaNl6kPFJH8jKkH0iPPdaJAllvMBYNBjI2NIRaLYevWrRgYGMDs2bNdXvMNGzZg69atWL9+PTZs2GDqBQBTUx0cZ8duCVLQ2qLd/p7GFxpcWIOgXq9jfHzcGFwikYgxUMg5RKNRc4w7IPCeynWQa2dvRSkNCHxeGJbP9eV95TMl175cLps+5LMpDS9S/LMPPjM0jvFaud2ljJpgZAqfieHhYeRyuSlrrSiKoiiKoiiKQma0JoCXh1KKWL7nS+ZUy/akZ9z+jO3IegFEelzZl5fXVoaZy374Pau3x+NxUw1eCkGeYxfBk+MgDHFnKH0gsH0/+FQqhVmzZiGfz6NUKrlEIdvw8jRT9Mp+vKICuLYMow+Hw8agsXXrVixatAjVahXd3d0IBAIol8vI5/MYHBzE2NiYqVdg12zgnOwIDum95hrL9ZC1A3j/YrEYuru70dXVZQR/vV53GYQ4R2ngkUKdRiO7LoDs266dYKdb2PhFpsjQfTvdgessRbzclUAaS2SUirzPMtqBbTCShi8+J/KZUGOAoiiKoiiKoihkj9QE8DIK8Gu1WjVefubXy3P4vS2GCcU4RaHMDZd54TJ9QFaal0Ka3ldpSKBgjsfjSCaTqNVqrnQDAOZ6vtiHvR5sC9gubovFImq1GlKpFNLpNBYsWGAqvk9OTrpEoJy3HYYvj9tClVAsc9tEjqdUKuHJJ5/E4sWLMTk5idmzZyMUCmF8fBzbtm3D2rVrsXXrVoyPj5txM6qAfXp5/zkuGmBkfQSKZplGwLSLOXPmoKurC5lMxjwX9PbLOUrhzbVmaoe8t3YxQfYrixLK+yTvI1/S6GOvrcz1lzswyH7kc8Hz2Lc0ctlbYEojFK8vl8uYnJxEPp9HoVBAqVSakiaiKIqiKIqiKIpC9kg6gHwvc/bpvWcIPwudSUEpvfTAdpEjPfoyBN+rSBrFU7VaRaVSMR5amTfPnHMZqi37onhPJpOmcj6NDrYHmOkG0vtO7z8AU9gtGo2a1AOZGpBMJk2+d61WQ6VScRU7tAvRya3n5DjketnrwnNqtRrK5TImJiYwOTmJUqlk1mXTpk146qmnsHbtWuNttqv0yxx5KWg5XztKQYbDy+eDQppb5XF7wHK5bCJE6vU68vm8aYPFJNmOFNMyNUIag+xChDJMX64h006kYchrBwAij/E+24YhPg9S4NtjYFtEGknk/eQ69fX1eRa/VEOAoiiKoiiKoihkRtIBgKmF64gdSi2Fspcgkx5Xe+cAr+spgmzPvBR2Ehnaboez83MAxkjhOI4R5facGFUg25P9EBotaCyo1Wom750GAubFSzErq+9zreXcZU46x2wbCOT3FPTlctmEmfP42NgYxsbGMDo6asYpUymkaJUiW45Pzts2AEik8SUWi5mXFMg0rkijgW2E4Vc5Vq/+vJ5NO6pAGii8zrfvr3z27GtkuD/f2y+7uKI8z14r1kdIpVKu593vZ05RFEVRFEVRlOcuM5YO4BW+HwgEjPeZaQAUj5VKBZVKxYT2UyhL4c7IAYpxmWdui3gZji1FOUP4+Rm93OFwGIlEwnwuBRpFajKZdInSSqUCYIeBgPOzvd522LcdccAUg0Qige7ubpRKJeRyuSnCXm6Lx/blDggytYKfATvqLgA7tioMBoNmrMwtr1arKBQKKBaLePLJJ7F582ZMTEygUCiYc20jj1xbL885xS3D92VNBBkZwgKMjLBg2gIFPwBXmkWtVnPtIiDTOuSa23n3jB7hutjPkZwbq/PLnHzeg1bbH9rPnVcNCnlP5PMmf4bk9pd89lOplNkhYMuWLa7z2Y4aAhRFURRFURRFITOaDiC9+FIEy5BtYIcgp9CsVqsuQwCwI/efAlN6QAG3l5t92kXs7OiAWq3mylXnWOTY7DB3r7B2AK4+eJ2XV1gKRHke0yLS6TS6u7tNEUJuAyfFqt0e25Fr7nWeLdA5T0ZJsPBcqVTC+Pg4isWiSQGQnmyv6IJW3nX7Psk14vwpbGX+uy2epaCXa8Gvdli+l6HITkGQ7dvPkJwjr6URgLsJcE3lOtspGbJ/Ox1BplbI9xy7bC8QCJjUlmKxiGKxOKUmQKt5KIqiKIqiKIry3GPGdgeQnmEiQ+bldn8UooVCwVwTi8UQiUSQTCan1BCQopwiyfbmAjuEufTI8iXFrawwz/B8joPedCkc5TaAvK5arZrrbfEvUwykuJX1Ebg9Xl9fH0KhENavX+9aJ7u6PLGLzUkDhVx7htbTuCK92zSGNBoNlMtlFAoFs/2cbQSQc/EyAMjoBXkuc/vldXI7x1gshkQiYe4voyzYDrBjBwbbsMP5cA1CoRDK5bKrAKD9fMq2vM7jufIr11tGkHDsdl4+X1wbaYCQffK5kYYytiEjP/ic8f6MjIxgeHgYk5OTngYHRVEURVEURVEUYIYjAYCpeehLlizBnDlzEIvFzDF6gNPptMlRt73v9IBKocRwcIo/v9xrev0Z8m57oqVX3+taeZwinpEJzKXnFnoATL66nLc0FvAzGjqkII3FYkilUkgmk0bIyj5piJBefCnAGTkgxyqRYpSpF6lUyhTkYwG+jRs3Ip/Pu0Lr2YfM/5ftchxy7jyXgpaC3Ra9jASQXneuo1w/GbEgIyhYT0A+BzJaIBQKuXaGkFERwI7ikDIyxMswwHnLVAE7BUbeczvEX0YqMC2GW1DyebajN+S6R6NR17NAvKIuFEVRFEVRFEVRZjwdQIbtBwIBdHd3I5vNGk+q7cmlV5oeaG5HR491o9Ew5zN/XHpL6XGWwoztVCoV4+W3t3uTIkp6+KUQoyeeOdoMqefOAxToUijbYfDS60tDghwrax7QQCAFrQzlt4Vio9GY0rcMp5fz4phoQInFYojH44jH46jVaigWi8jlcqhUKlNy+71SAjh2v1x0GR0g152fyaKIci3kmOUaSuOMLB5oG4Bk/3ZtAJmuIe+7/Tz5hdrLwoR2wUS/Mcj1sVNHuDZ2wUP5fDJqhefKZ8E2NiiKoiiKoiiKogAzWBhQ4uWZZBg7PboUMvV6HZOTkyYnnccKhYIRzQsXLkQqlUI4HDbCnv1ILz3FP3PbWXiQ4fe2OKQwj0QiRvCzToHtpWUBPnpzKeDlXvE0SNDbTwFMD3w8HjeGD4Z6RyIRJBIJ9PX1oVqtYuvWrQB2eKDttAYpLv0K0QFw7WbA+bLKfFdXF9LpNOLxONavX4/169cjn8+bXQtssSuFaSQSMfP18or7jZNGnEgkglgshr6+PgwMDCCVShkvOZ8nrql8tpg2wPZ4rry/NF5IgS+jPuQ62TUgvCJKZAQFUwACgQAKhYKJNuFWhzzPy3AiDUwcY6lUMuNkZIxtpOI9pIGou7vb82dODQGKoiiKoiiKopAZTwewhZQU+xRJUnBXKhUTBUARz+MU05FIxLVNH8UU+6F3nkKdIpvijW1IcUXDAYUdvfB2yDXPk/OxhaVdzE1eC2CKWJYilNsDplIpUwmec7Hzw2W6hPTye+WycwzSK08DRTKZNLUPcrkcJiYmTD0C9muP2RbVMqLBFq8yEsT+XBpEuDsA7x/7osi3UxLk/GSYP+dGA4u8ThoP7LWX7+1oAVnnQN4DO7pCYh9jezJ6gc+ETEOQER3ymZNrLI/Z41IURVEURVEURSEzbgQgtkhhbrzjOEb4M7++UqkYocT0AIZCJxIJpNNpJJNJIxgZVUADQKlUMh56mV8ejUaRTqdNcT+Oh1EBUkBJT7Lsg6KVIpDGAvYvaw5IA4It5CgGpQhtNBpmXr29vSiVSkilUmZ97PQC9i/bk4JWfrXD0Rm5EI1G0dXVhWg0ikajgeHhYQwPDxvjSalUMuOX601xyrW00x+AHQYR3ksZ/s6xhMNhJJNJZDIZZDIZJJNJs10k10TOw2su/JwRBuwjGAwaIwAFO8PtmV4iowHYhr3VoG0IkBEifC/blmOSBhcZ6s814fNTqVTMWPjsATAGK1nQUc5HGr+81kVRFEVRFEVRlOc2e8wIQCimuLWZDJmPx+NGLFFAsho7RWEgEHBVkQfcW8fJIoAUSvF43BSeSyaTLk8+w+IBmAgEemXtHQlkJALFsMwFt/Pv5U4CUiDKQnm2Z7lSqcBxHGPsyGazKJVKJp2ByNx4GhgIRaxEjotCNJlMore3F8uXL0d/fz9CoRBGR0cxPDxsIjDsWgR2WgHvTzAYNIKdBf7oeec95xy5LnJXBKZW8LmQ9RAokOVcvLYI5Loy7UN+JqMX5Plsi/eSL7nG7cLtZYFBeQ9kKoR83jgvGlP4rJB4PG6MO/IZlOtPg5hMp1EURVEURVEURbHZI0YAKZL5lVXRKeYYqh+NRpFMJqcUcqOwZ5464C6uJr3OdgV8tstcagpWWQeAMAWBAo3iTHryZdSBV0E4KbZ5jfSWy3nJ0HYKQ2kUSaVSiMViCIfDU3ZH4Ly5fnK9bc+5jAzguGKxGNLpNObNm4dMJgMAyOfzyOfzLhErayFII4JsX36VURZyPLzX0qBAYwDXU1but730dnuyT7kWtrFD3h8eZ3oIxySfG69+Wj3X8mXXbLDvifzMNrDwxXQXroNfEUuZDqAoiqIoiqIoiuLFbjcCeIlPWyQCMNsAFgoFUyCO+fDADq88r6PgYeg0xSzDt7mdHgAkEglkMhkjAqWIYhFBu+o/z2MUAvPwWXWf29ABQKFQQKFQwMTEhBkfC+RxTBR5FPMM52auu9x6UBoWGKKeTCbR1dWFBQsWoFwum7HQ8MD5sLYCjRtSiEqRKj3xFP/d3d2YM2cODjnkENRqNYyOjuKpp57Cxo0bXekCHG+pVDKeaaYtcJ0ZwSEjG6TwZSRDsVg095XGHT4LoVAIqVQKjuOYwoAAkEwmXR57acCRfdked8AtlO3PeL5d+8CrWCThfbN3dbCNBbIWAl+ck4w4YdQDfwZYGFIWGJRpMVy3ZrOJyclJFAoFz9QPRVEURVEURVEUYIZ3B/AKpeZxiiBGBMiq+pVKxQgzthkOh40AlN50eu7pJWfoNEW3PR4vsSajBmRkAa+xr5f1C6RotNu1c8ple+xXeovtAnThcNjkyTNEHMCUVAKvfmVbEtuLD2wPLS8UCsjlcigUCiiVSiaXXo6f2wnGYjH09PQgkUigv7/fHGMuuyxyx3uaz+dduz7wHNZj4Ljj8birIKTcdUBufeh1T2XIvNd62wYRGpBk+oRfRIWXqOf9tQ1fzPmX/Uu8IhvkHGUUiWxXpoCUSiUTtWEbQRRFURRFURRFUciMRALYudj8XkLRLr3L9JJLjzexQ6Ep5lhIsFKpuHKouf2ezBWXBgQp0gmvBbZHKthCjmNi4cFarWa8tdJ4YNcEkOH+XmHnjESQUQSO45it87LZLHK5HPL5vGv+FLD2ujO83is9wl4T1lCYmJjAli1bkM/nUSgUUCwWXTsxyB0LMpkM5s+fj+7ubixZsgTZbBa9vb0mjaNcLrtEc7VaxYYNGzAyMoLNmzdjy5YtZvtHjo3rlE6njQGgUCigUqmYe8mtG2VUg0yr4DhlPQEZ5UHjAJ8FRifwWWQ0g7xWPn80QtBoINM8pICn5172L1MT2I589ryeR68UEz6bw8PDGBwcRD6fn7ILhRoCFEVRFEVRFEUhMxYJIEPRbVHCkP5arYZ8Pm+2h6OgZoi77fGXX2U0Aavky/3b7boAMvdeenHpuaYxQXqSKZhZ1I+eWSn8CMdBwwAFJQBTvA2AS0RKDzTHwnHLCAlWzx8aGnKFhMvrbcEoowwYISFFbq1Ww+TkJCYmJjAyMoLx8XHkcjmzM0MkEkEsFkM8HkdPTw/S6TTmz5+Pvr4+zJo1C/vssw96e3uxePFixONxU9Sx0WhgfHzcrCnn1NXVhcnJSey9996YmJhAsVjEyMiIiQ5oNpsYHx/Htm3bTEQG11xW0peedrlNooy6oLecQp/3jPeNofUyosI2zMg15E4A8pmQOwvIoo/SWCV3KqBBRY6F9R/4/MiaEcRO7YhGoyZ1wKsgofwZVBRFURRFURRFmdGaAHzvJUooZpnvDsDlpZYiSgpeGcbN/H7mVdMLLMU+PbZEhv/L8HAaFCiS5V7tUmDa4f3s324DgEvg2f3zGlk93g75BmDyxZknLsWpV7i/9Fh7hcpLYwQ94YVCweSXU3Czz3Q6jYGBAfT09GDZsmXo7+/H7NmzsXTpUvT09GD+/Pmu9AOmEVQqFRPlwXubyWTQ3d2NcrmMcrmMLVu2YGxsDLFYzOyAkMvlTHqBbbjh/Lxy8aUY5r2Qof5cLxp9eFw+B36pKxTo0lNPA4Id2i/vg20QsNNTJFLs2/3bBi15L1XwK4qyu3BSQTgzUHs04ACYbG7/qiiKojxrcGIBOLFn9r9moNhEoN7+PGX3MqORAPK9DT25FH8Un/b1wA7BKoUSXxT+8Xh8yjZ5MsSeYorbzQWDQeNRZX+s1m6HZksPOwBX5ACwI4+cY2NNA5mjbld453H5VRpB2AaLBDLcvl6vu0Lp7bByzsWOeOA8OcdoNIru7m5kMhk0Gg0MDw/jySefNHn+oVAIc+fOxfz583HYYYdh/vz5OPTQQ40Hmm09+eSTKBaLmJycNOK7UCigXC6jWCyadZPF9rjjwSGHHIJKpYLJyUmsX7/eFY2QSqWM9196zBkNwLb5Gb3zNELY68F0Efk8ci7RaNRc5xe5Ygt9P8OWFOdya0hpzJDpCzLyg99zjvKZ5r1m/QtZuNJG0wEURXmmOCGg+L7ZaOwT2+19BUfqSH1sMzA51bCtKIqi7Dmqr+hC5XU9O9+AAyS/MIjwg6VdNyhlp5jRLQKlqJKiKRAIoL+/3why2yvuVQtAfs82Zc66FLns2y4iKPuRufu2V1h6zO3cfbuSvH2OHZZOZN62PF+KQs7R9uSzYjy3CvQTqfK9XfvAFrDBYBCJRALRaBTlctmkBiSTSaRSKWSzWSxatAiLFy/GPvvsg1mzZiGRSJiidFyLXC6HUqmEUqnkimTgWsh1lYUfeX8ikYiJDojH42aM9hrIyAe5RvJ58fPssw3bmEOhbhtNZJoBx2JHYNgFC+Xn9rNuGx/siAwZ6cJimTIiRj7zjIBhBI09d7/IG0VRlHY46SDqByWAAIBQAM29onD6d/+/Dc1oALUXpRBaX0Xoicpu709RFEXxxgkAjYMScNLb/wduLI8/s78DDlA/JAEnNTV9lQSH6vq7fwaYUSOALbooUMLhMA4++GCMjY1hzZo1RgRR/NCjKrcF5O4B0tvP7e5isZipIcAUAX4O7IgK4DEp5uUOBOyTIex2uDc9zSwkx8r2sg+5VZ80Kkixx/5khAL7Y8QA89ABmND4ZDLp2hJOClZGHngJceafy8iAUCiE7u5upFIpTExMYGhoCIODg9hrr73Q19eHAw44AMuWLcN+++2HWbNmIRAIYHR0FOPj4xgbGzNrKcPiWReARgv5GaMbisUicrmcmW93dzf6+/uRSqVMBADTE1ic0d4WkevEdbN3kZA7Q/BeEbuWA4W+vTOEXa+Bc2DUCutQyGKScr62gYDjo+GB94EpC3w+qtUqCoUCarWaqZPBaAIaAUqlEkZHR1EsFl0RDPJnTVEUZbo05kZQ/PAcIDKzv0ecbAil981G5Jc5JL+wbUb7VhRFUQQhoHxOHxrL4+3P7YQAUDmjt+Up+rt/ZpgxI4CXGJFChWKJYc0UdlLsVKtV817mVEsvOkO6pcCyBb8UgnJ7ONujGwqFXNv+ScEWCoVMyDbFpty2sFarGaOFHd4vw71lcTteK3PqpXjk9/T+M32B45Lrahsc5BpJwwO/Mh0CALZs2QIAmDNnDpYvX4758+fj8MMPRzabRTqdRj6fR7lcxtatW001/XQ6bYS4TM2g8JYpEADMunI+MiqgUCiY4pADAwPI5/NGlEtDTrlcNqKdfQEwKSVca85Lro9XMUfpuZfpKDzf3oWA19jtynvqt6uANGrJFAE+h3z25NaI+Xze1IRg+/J5P+CAA1wpLRyfGgIURZkOTgionN6Dxr5xILTnfn80Dkig+N4BxH4yoV4hRVGUGaI5O4zK6T1wQgEgADTnRtpftAvR3/0zw4wVBpTef/mexyiYKIRlDj8rwstwflmYTQoxaTiQRgDpBaaRwQ7Jl2kHXjnbRHqgZdFC6eGXIefyc17D+VC8SsFoe7a9wsdpdJDzk/O28Uo9sEVuNBpFMBjE5OQkIpEIZs2ahYULF2LhwoXYd999AWz3bk9MTJgq/myHtRjk3OW9kUYUKaQpWLlu9XrdpAJEIhFkMhkA2wtGcotAns+52vUTpKHDfj7seUsjklwf24Nv33OvtqS4l8arVmvOsdvPs3yeuHtBsVhENBpFo9Ew0S4y9WDevHnIZDIq+hVFmTZOCEAiCAQAJxJA7cg0mnvv/vz/VjTnRdCcF0H4oRKCW2pAUYsFKoqi7A6caAD4/xf8a86NoPqKLiC8Z/6f1N/9M8OMbxHY6pxms4lisYjR0VEAQDabNXvR02MqxR2xQ/TpBQ6FQiav3HEc5PN5E4JOLyw9qdx7nqHchOKWY2QoerVaNeKM285RhAKYkhogvfrSQMHzpPCXW8xRdMqtADnWZDJp8vgZWWCvB9dKCm8eD4fDSKfTZo1nzZqF7u5usxNAMpnEC1/4QvT09MBxnCmh/9ls1qxjNBqF4zhmRwFZoJBjl+MoFoumoCLD9fm1Wq26QtsZpRCNRhGLxUyRRLnLAu8br3ccx2xvWCgUXFEZFOy8hzItxTaWyOKQHHutVjMGmEQiYY7zGI0p4XDYPBsckyzeKA1c8l6xPkOlUkEoFDLbZ+ZyORMJkM1mEYvFTD2AyclJ1Ov1KT9vahBQFKUTmktiKH5oznZjQCAAp2cGtgHokPK5s1A9IYvkJZsRyGmxQEVRlF1NdXUWlZOy299EAns0Cozo7/7dy4ynA3iJEjsSgCJ9bGzM1AOQ3lHpOZeeWQp0hlPbHnZZLT4UCpn6AXIrQYZkc1yyaCAAVyg9Raz0StseX6+5AlONGOyDYf0UoNKjbF8vxy+3RwTchQel8KXg5Jyj0SiSySSy2SwymQy6urqQSqWQTqeRyWSQyWQQjUZNiL0dFWHPwV43jkXeZ47fvp+yXVss0wjA1AI7LF/2QQFOUey3Fn6RADKqwo7GsD3/9nNhe//lS85Jjl22yeP08rMGgIxekeOl0atUKk2JUFAURekUJxJAcyC8xzw/rXC6Q2gGgfphKYSeriK0VsNDFUVRdgVOOoj6/nE0lsXhzJ7ZsP926O/+3cuMGQE6iQSgJ39kZAQTExNwnO2F4iqV/197fxokWZZeh4Hn+fLe8zW23KKysiqra+1uoBegsXQP2AQaA4CAARgKBAYak8gZksMhRRGkYKS4aKghQUoDmUDRCI5JxtGYiRrMaAYjcWgQCUAkIECECIIAp4EmutF7V1V3ZVVlZmVmbO7+Nl/e/Ig6N4/feO7hkUvk9h2zsIhwf+++e+974Znn+853vhy9Xs9lp5XYMxvMn5mdj6JDGSMzt+Px2BmsMfO/traGdrvtSJm2+vPJsrbBIxlL09SNretgVtknuXyPBJLz41q0Pp7GeSSNqm4ADtvZdbtddLtdlx1X4s2xfT8Dvs/uAq1WC2fOnMH29ja2t7exubmJzc1NrK2tYW1tDa1WC7PZDLdu3XL7wXtFjwbtUKDu+lXt+Zgt73Q6mEwmTt7PMXXuzK5HUeT2ezabYTQaueNVKcHfGeCpIuG8BzpvLf0gqGzQLD0DCAwyqVEl50yjPt5nPpc6B15TSyJ4fJZlc6UIvEcA3H6rz8RoNMJgMMDe3p5THRgMBsPjhrJfR/oXzqP5awO0/9PrD3o6BoPB8FhgeilE8h9uP5QBYMA+++8nTiUI4BNB/z2fPPf7fdearl6vYzQaOULFjCuJmF+Dzbp0kuXhcOhk3yRPURQ5szgSpzzPkWWZa3enygNmZHkuSxNI7ljXTnXAbDZDlmVOGk6VgS/R55r811TRwHlQFcCfGehotVpotVpIkmQuuKDjcZ/VT6HZbKLdbuPcuXN45pln8Oyzz7p9595rwIW16DSoo1kd99+/x2VZzrWs4/6QSGvXBP89zYCrZ0K73XY+Cr5jPwMOVUoM/xnRoEuz2XRk3+8M4WfntYyD+6zPowY/OI5/b7WrAb8YGKnVai4AVRSFK3/odDpoNBru70DH9r0yDAaD4SQoG0D+IxuYvhADtYfzP4EOD/n0DAaD4VHBo/bZP30pRvpjZ9H8pwdofMkUAfcCD7Q7gP86CVG328X6+jparZZzSWcWlMeRBIdh6LLTYRjOkTH2sGcQgKSSrdYAzJH2JElcyz0SRGIymaDZbCKKormgAJUCPIeBgaIo3DHM9PqyeH1NiadPVDW7znPYWSAMQ+cR4JvgKRHWkgKurdVqYXNzE+fPn8dTTz2FTqfjSgz4RXLNrDk9EFjjznnrvqv0Xa+pxFq7GahSQWX7voohjmMUReG8IXhd3/PAX7sGATSQpIEBXwnAMVQBoq/5AQKFlgb4ShB9hnVf1K+A+6x+FVSD+NfyjSgNBoNhVZRhgLJTw/jjPcyeDY8/4SFA2TicM/IZgsnxxxsMBoOhArWHwwB2VcyeaqJ4ag31L+Uo3xwDqZkF3i1OJQjg113ztarjGo0GLly4gEuXLmF9fR0AXB14EASuhSAzt6wX9938syxDURQYDoeOrLbbbZdd1VaBQRA4eXy/33fEjaoCVQYwMFGv19Fut13dOY3qSNhVOq4t4oB54z4GMJT8k/yypIFQI7k8z102f2NjA4PBwGWK/Wty/gycRFGEtbU1XLhwAd/wDd+Aixcv4vz58y6gsLGxMUc8adQ3Go0wGo3cOre2tgAcEtHBYODui2bzSWR1T4MgcEqCyWTi7kscx0eCFZp9b7fbKMsS/X4fSZI4nwdm1zWjzvWyvEONCvXZ8+vzSaqTJHH7rQENPgO8R1qG4QdCfGKuAQpeazweO9d/VY3wuabixDcn9L0KqgIA/vUMBoNBUfzgGorvXcPszKnlA+4ak29sY/jTlxD/lzfQ/FfJg56OwWAwGE4R2R/ZQvE9fbT/xlUEe9PjTzAsxKm0CFSioplpn5yQ7DHjzky8SvNJ+NT8j3JokkJmqxkk4Nh+Vha4bVDHbL7KtZn9VuM/JbRK+DkHX/6tY1aRUK5P5dw81yeohJoINptN106PMnmfFGqNeaPRQBiG6PV6WFtbw/r6OtrttttzftVqNbePLJXI89xl4qmAoJJClQrcU72nuiaVxWsWnPP31QzagWA6naLVamE6nbp7phl3DQLU6/UjgQk1XvT3XZ9NKk/oDeCXcmjpgr/P+sxUPec8lqA6QX0huGaFr/TwVRd8TVUGBoPB4KPs1jB9McL0xfjU+z/fNVo1zFo1TN/XQpCWqH8hQzC2dJDBYDCsiovvyXH2uTF+uzvD8C7GKScByt0msOQjOFifIAjvXclquVHHrBlg8sHWoVng6+aHdad4YOH/KoJC0kXyk2UZADjpO7OwZVkijmNH/JmNJWFlnT+P5/WYZR6Pxy4rrW3dOJ5m0UmcWZuuxItEkPNldlsz/JrZ1hZ0SoaZESeBZdtAZsy1PaBm+UnYaZpI93wSRSWlHLfVaqHb7eLpp5/GxYsXsbm56faIPgCdTsf5IxwcHCDLMqcAmE6nzoyQQQoSZu6nf2+rDBI1+KIZcN0bEmJt0xiGIUajkcuQM2PvBxUAuCCFEmxm8f3gDOfCY/M8r5yPH0zS8ga9P0rKlbj7wRA+A7zH6j0BYC64xHVyXDW9ZDDmuICDwWAwTC+HGP3EUw9FC6g7Rf4jGyj+l310/+wbCHYsG2QwGAyr4nv+zVv4wT91C3/iK8/hK1nrzgdK6pj+Vh+YLv63pP7RfQTn7i1RL7s1pH/xApq/PkT7J6/d07GfJJxqEEAJip/tJckhkWT9NgkSs9JaK661/6oC0N7ufjZVs7lK7NM0nes9r4Q1CAJnCAjcJuMkcErEtN5cSalmjHVsnbtv5EdCqnulNfBchy8l1wAFAEeAaTK3traGra0trK+vO4IdRRHa7bYLsrBcgn4KGsjgmHTrJ5FfdI91TSSx3HveB2a+qWzQLgzcT5ZsrK2tuVIF7gGfFc2KV+297q2OrfdaAwP6xSw7fRI0IKMO/746QJUkeh/pH8E56nOl5oKcHwMvXJsGpZYRfVMEGAwG4F0jqD+0gekL0WEA4FH+aAiAslND9ke20PhchvCXDh70jAwGg+GhxvblHP+rP3YTX/fNI9RquKN/A2bvhCivveshU9SAWbBYCRAAs9dbt49XhCVqLyYI6neYqHqU//16SHDfgwB+GQBQXausmV8SHJJgJf+UjWu9PDPpJNQ6vk++eX11taeHAIm871rP70rWSKxJ5tSlXUsH/KCFvze++sDPDvvnaAZbM/wMAmhmmj+rE3673Uav18P6+jp6vd5cEIBqAlVM6J7qfnLPmKn3fRn8II8GNJT46h6p0SIDD1SDMEAEAL1eD2VZIkkSR8hZ/uEHAar2XvdQ99xXKWjWXp8j7g3vGQMZOpYqPbhfen0Gr6gaUfNH3nu9l7p+DfIcZwq4qBzBYDA8gWgEGH/7w2MCGAVT1D1np7ysY1qu+JkVBRh/dx9o1SwIYDAYDAtRImqVuHg5xw/+0ZuYBgFGsyZmK37WltPbRL/caWL22orqgRIor4aVMYJaZ4r2iwMEtcP/H5/os5/D1wOUrQAoSgQmCDsxTs0YcNnvBLPLJHQ8Tom1SrtVuk0TOCWbJOUqsSYhZIabJDxJEkciNeMK3A5aaF94HT9NU5e5JflTcs11sAxBiS+JO8dnLT7JrGapdZ9msxnyPEdZluh2u+h2u+h0Otjf33dzI4lkkKDf7+Py5ct4z3veg+eeew7r6+vY2NhwqgCqAJIkQZZlThXhk2YSc/6uBJhBHK2bZ4cH+gqwnEON93ifOZ4a7XFfqcZYX193pnycY57n7pnwCbu2N6zq0KDrZFCFQSatudd7oYEFJfvqbUDVBoMCOhbLKDSbTw8DzpvKCPU70GfLf46rAkYWADAYDA8rfvzp38WHOzfc7yWAv/Xmh/HJ4bkHNymDwWB4zBDGJf6Pf++reO59GWq1Ej9740X897feg6tF+9hzyxkw+50eyoN3y5yL2jFnrIazzRQ/9fyvoRsXd/zZP/lQ69Ao9r+6heZvju7JvJ4knEoQYJk5mi+RVvd/kkt1QifR4TFaLuBngtVQUE32lCDz/CzLHElTh3bCN7vT7/x5UWaZc6kyCNRMs85JSarWgnMsroOklU78mqnnmJTY9/t9bG5u4uzZs+j3+84DII7jOQVAnudzmW7NbPtz57WUyPpr9+vpmf1mEECVBnq/SajVWJAkmP4GcRxjMpm4+auKQ5UG2rbPX5Mv2dfMPpUGmm3XDD1f8w0Gq6T6i35XY0DOgUEwfV51jnxuR6MRarUaLly4gDiO5/6+VPliMBiebEyfamJ2sYkyvjf/gbsbnG2meDYa4MV4D8/Gg7n3vr5zC3lZx+eTDUzK1eY6W69j8sEWam8UqO1aOshgMBgUtVqJC88UaF0o8TvDc/h8soE38u6x55VJHeWwjvKggXJQP/b4VfHShVt4/uwOLrcG6ESHpb138tmPdg2zdojpKzGCwRT1L+VmFHsCnFp3ACV5VeUBzOImSYI0TZHn+VxvehIkdU0n4VcpP6GknWSwKAp3vBLV6XSKwWDgzmm1WgiCwGWrSaSV2JFk+zJtXZPfNo7mfzxWgwYku34gwZd9c74cg33k4zieUzComVyn08HGxgYuX76M5557Ds899xzOnj2LdruNzc1N1x1gNBohz3McHBy4EgsAzjhRybzOk8dyHVw3lQ9cuwZBWD6gZFqNHllm0O12XUZc943KBnYJoJEflQZ6fxqNxlwrQT4P6qGgvgzcU66Dsn1VJXA+XBfP1fIDDSBwrxT8nQEs7pf+TTQaDed9QAPGer2ONE2RpinefPNNbG1t4bu+67sW/v0ZDAZD8X1rKP7g+kNRR/n7+lfxF57+FIIKkeifuPA5/OD4q/jfffE7sT9drWxh+nUtjP7ji2j97esIf3Vw/AkGg8HwBOLVdA1/7rVvWz3AeiXC7Audpe7/J0UQAP/uJ34LH3vxDdRk4Dv57CfyH9lA8V19dP/cFQQ3J8efYABwSp4A+r3qNT8goPJ7Elk1fiNp8gkmx1IiRYKmGds8z+eCCZqBZd18FEWI43iOjAOYUxxwTtpKUOfC12iCp0aEWh+vQQKuVQMjKjfnuLpXSvR0n0h4W60W+v0+nnrqKfT7/blsPcsPWALAQInvccC99RURSqr92nuuV++j31qP69N1aQBDa+tZcsH34jhGp9NBEARI09TJ6VnKwCAJPQZUHaFyfF5T58LnS7P9ek/VGJL7pMEuX+Wg5+pa+fNkMnGBDN1XDQzoNRi08EtnOF7V35bBYHiCEQB48CIAAEAQlKgF1f+rrAUl+vUCf3L7s/jU8Ax+ee/SCgMefo2/vYfZxSaif7iHYHTvWlIZDAbDo4qPfs8+vu7bRvj58j14+2Yf0xUCAGVax+y1Fspby9v/3Smq/g24o89+NyAemn/fHiU8sBaBVfAl2koulfATaiCo5Esz9ioD1/IBX1oNYM6dnpl1vRbHUSNAqhPUtV/LDjRDrj3qq8ggyaVvEqhlEFWoGkOz1nEco9fr4dy5cy6zroSe+8Eae83K+872usf65fe155q17t83SlQyrWvU9aiyge9pwIbtDbvdQ1kT20Xq+qkq0ECKBmH0vnHvWWrB+esc/HF8cz71hdB7rfP3lTFVBph+1whVOKh6QVtacu8NBoMBAMoagGbwSLUD7NTH+KEzryKqTU70H8HJR9qYvhSh+asD1IrSZKEGg+GJx9d/6xDf90d38ce+9CG8vtc/9vhyGqBMapi92gJOOZZ6p5/9AA47xkQBymZgn/0r4qEKAmxtbeHbv/3bMZlMMBgM0G6350iUkjFm97VmXkm/b5TmE2kSMZoG9no9xHHsHPKDIECSJI6otlotR2aLosBwOHQBiSiKKt39OQdeo9lsuiAEySl702srPma8uV6taQdwhBSWZYkoitDr9RCG4Vw2fzab4dy5c3jqqaecEqDb7aLf76PVajkpPTPOJKDMnCu01p57rgaISvYbjYbbM1VtUB3gqzVUNaFeAHoMofeapQXr6+tuDlEUObn8eDx24wRBgKIoXHBGgzi+UkWJul8CwTmoYiEMwzkCz+eC7SO5Bl7fXw/nxGdFAwNcl16fz5Pukw+/7MZgMDx5mL4UI/2z51Bu3rt6zocZZaeO5K8/hcYnR2j9X28+6OkYDAbDI4NyFhyaAO417osC4H7CPvtPjgdiDFhFTkiWm80m9vb25ur21ZFfa+Q1g8yMttbsL8qea+aXxDeKIoRh6DLGWmbgZ4hJ2DQzXNUiUMmk/+VL9tXQTlGlBlA5PUEFgxLDZrOJMAzR6XTQ6XQQRZH7Ypae81BSq6UVWq+vRnsaECBpZylDFWlWfwPeb+BogEPXp4aIvqRe948tI8uyRKvVcjX0fF/bPup9Utm9PhtV98Hfb79MgkEA37NCyw/0edGfGbShZ4Q/J1854AdRqp5zCwAYDAYAQBxg9kz4UEglo2CKl9p7eDoc3r+L1IHZxSamuxEmXxej9tbYzAINBsMTh05/gufem+HM9hg1lHhvaxf1oMRX0rXFJ5VAOaqjHN2foPHZXoJntvbQb+X3fvB3P/tnbzTv/diPKU69ReAicqL11JPJBEVROGJVlqVz7+e5zCgDcHXRKvlXguYrAnQuzOL2ej1H2NI0de/xHGZ02epOjeD4Ok3pAMy1/lMfAz8jrFlqzXzzd+4Bx2YgxJfet9ttrK+vo91uOyLe6/XQ6/Vw9uxZrK+vO/l8t9t17vdciwY38jx3a+D+k6CS8JNQM3BDkz0NGmRZNlc6EIahuxbXoe37fDWFEnfgtvSeSglgvoOAthukmoMtJ7kGvbfsqqB19iwdUJLN54B75jv508CQ+8A94DNBNQQVG7qu8XiMnZ0dl/VngEpVBRok4nq5j3z29bmxAIDBYHgYcTZM8Z899y/QrY+PP/guMX1/C6OffBqtv3sd4S+bWaDBYHiy8OIHUvzH/81rqNdLBDXgrz7zSXxqeAY/9urHMXtADrG//+XX8Re/79cXesIYThen1h2AWEZO+F6WZRiNRo5os/WZ1uVrNlihmVet+V4k6yap0vptkmgSOiW2vB7l/CSrJKpqQqiSbZ0D1zCdTpFlmfu9SoKudem6Ht+cT7PxjUYDnU4H6+vrWF9fR6/Xc7XzXMfe3p77mXPU4AnJJ8/ROereAbeVEHxNlRSqANCyDR4bhuGckoLkmMRWSS3no2Z9qi6gGoJlBbxXw+HwyHOnpQ9qaKjPju6tmlOqOaTeW1VK8P5q0ETXwcAAgxGqwCC5Z9CB82JHBQAYjUZI0xQvvvgier3e3N+PH+gyGAxPHspmgOIH1zB9Mb7dEWBSIvzH+0AUoPgDa2j8doL651MU37+GcvPk/x0IUOLf2Hod2+Fq/Zn7jQKt2qTyP4CffescfuVzz+P7P/hFvOfczonnUjE5oI5DK2qDwWB4whAAqNWB4F0VWC0oUVvycTh7J0T5Tghkq8vGznQT/K+/+ffQqK9mHvDyhZuo144/ttxrYvrZDmqXcgT9k7n9z54Jkf2xLTT++RCNL98HxcFjhFPrDnAS5HmO4XDoWsXFcezIr0rWWdfty6SpJiAR86XoCs1uq1ScbeBY86613RxPTQv5XeekMnENALDtmwYVfOWBrknN9Tg3lcoDt2X5nFsURej3+9jc3ES323WdDoBD0n5wcODm2u12ncu+ElUGRlSur4EKX2LPwAmAI5l9Em0/0EGfBFU76Lm+4sFXG2hwgGUB3HeSdb/1ou4ZM/m+RF/vs3YyIEFXPwBfucDjNYDD9WuggMdpEIDPH0saVCnCvS3L0gUBLl++fKR0oCrgYTAYnjA0gOJ71jB7WqSREyD8pwcouzUU39FD418nCH9hH+Nv6544CFAPSkTBFN+7+TV8fefWXU/3y9e38H//jQ/hfU+9g4ubBwjr1ubJYDAYTo4SzahEI1oxCVQeegGUN5qYfaV17OGNWon6u6T//NoQ/9ZHfxdx8x5/Xh/UMftyG8HaFOhMEdRXT2jNLjaR//AGam+OAQsCLMWpKQH0u6KqVGBnZwdf/epXUavVsLm5iWeeeQbtdtsR2el0ijRNXU95SutVRg3ME1FgXiVAgkYVAAk/jfWUlHGe2j6w1WrNZbxJQNM0dW3qgiBw8m+SeBJGqhtIVNmujgSWZFmNDjmfqnpxyvgpE4+iCOvr69je3sb6+rozBOx0Omi1WhgMBnPr4/7oXHX/WHPPa6pLPcmztqpTMup7NVDST8UHM+U0J/Qz8DxHWy1yvVqCwXvUbDYd4W40GkiSBMPhEFmWufIDyvXLsnTZfC1N4Jz13mRZ5t7nc7NIRcJgADtN8H3OV1sYbmxsYDKZYDwe4+DgAEVRuDaHVCCwbCFNUxwcHODVV19FmqbY3t6uNAbUPTEYDAZF/bUc3b/wJoKdO6+V/76Nr+JHz34FF6PVVAAroQR++pc/ip/71Hvxk3/ol+/duAaDwfCEIG7P8Jf/8zdw+ZUMwQqy+/KggemnekC6mgLg+z/0BfzoN38GABA1pggb989zZfa5DvBGjPpHDhCE1vb1XuPUugP4JQF+xlJ/j+MY3W4XaZpiNBo5h3SFbwBYVfevhJSkla/7Znya3SYJ13N9wzYGI6hI8OX7fE+VCzoHHlc1B79sYJn5mwYBmNkHDjPIcRy7oEUYhq4GnkEPjkmiXVWuoHXvOo+qEg+VtGvQR/dAPRF4LmXunIPK/XWtPF7nqYEMrZvnc5TnuTNMrDIm9MflmjW4wXN8V3//OfTNKPXeahmJPo9lWTqCr8oI36BQ58sghbbL1HthngAGg6ESNWD6nhBl+91Sr+3aYfvAeHX5Z1yb4Pn4AO9t7+KF1v5dT6mY1PHl61t4c/ewdVXYmCJqTHCvSlZn201MXoxQ/2phbaMMBsNjj6AGXHohQ+/pGT6bbM2Z/L+WSYvA8jAAUO42Ue4f3w2gFU7w/LkdvPepG3jpwt2rv1ZBmdQQlLijTgX22X88Tq0cQAmuvu4fBwDvf//78fLLL+Mzn/mMI4zj8dhlZJUEae24kjUdV2XWarancvc0TRGGocvyA5jL/BIkqiSV0+kUSZI48hjHMer1umsvSLJbq9Wc8Vuj0UC73XYZaJWMa+kCv5Rca+BAgwB5nmM0GrlMdBzH6PV62NjYQLvdRrvdRqfTcZnp9fV1t6eUuGsGfjweu5Z1VED4PgxKaLVunvd7EemeTqcYDofu+twzBhvYwYCvKdHWQAuvx3aG/J3nxnGMyWSCfr+POI6dgkC7BfhlIlpq4itBfBk/cFi6wtp/DUDoPfKfP70er8WfKfnXPdPzATjPh6oAUtXflsFgMAAAwgDpnz9/9D9U9dU/My5FQ/xfnv+fEdfuTfbn5qCDf+//9X3YTw+9C/7d7/wtfPylrx7WjSZ3P37+IxsovqeP7o9fQXDdSgwMBsOTgS8kG/jx175t7uO+LANnCljOAkw/1UN5sFo7wGc29/Bf/OF/jFbz/hu73gvYZ//xeCBKgONAUtzr9RwBpVwcwJxcW7PzwLwRGkkZCbqCxIoEjJlo30OAYzPLq5J1ddNXLwFKxElKSTo5JyXPWk9PkFRqOz7NdvOrqsackvlWq+UUAPzOvciyzMnN6XXA2nmOoV0W1JHfz5xr2YJ2O+CezWYzJEnixqFrP7P/6mXA/SiKwhnjKanmmHo/tBZfs+4MKPD56XQ6aLfbcyS7KnCh6ge/zp8Ze98kUJUY3EfeGz+Aw/UDcMELDeZQoaHtKVVFwQBAr9eb62JQFQwwGAxPJsbf3Mbk61oo+xUZ/hMQ/ioEABpBudDduSwD/ON//TKSook/9I2fQ3OBVLQsgV/89Mv47FvnMCpCvHThJr79ldfx/NmdlU2mVkINd71mg8FgeNRQApiUAcplsqoSwKoftwHQqE9Rq51uVr0cB4f+ABtj1C6eoMbfPvuPxakFAU6KIAjQ6XQQhqFzfFdipGTNJ4hq2MbflRwpMdN6dZK4Kkd/vz1dEASORLOlnpJGbffHIIC+R8Kp3QQIBgVUIaDX1S+SdjU41Fp0ZtVJunlNBgE0EMBx/DILrtsnxrq36l2ghoGTyQQHBwduPAZ2GJTQrgcqb6dKgGUgOi9eR+X6GghiEACAU10wEEC5PZ8R7om/Zr+8g50efIm/+gtQacCAknoFqEeAzpOKCYJBAPpS6B4zCNBsNtHr9SrNLi0YYDAYJt/YQfEDS3pB30eUJfALn34ZNwdtfO/XfxmLbKZKBPgfPvMifvPVS2jUZ3jfUzfwv//4b5/qXA0Gg+FxQr1eohmWmKCGSbm4zKsk+S8fgf8nTgLMvtJC7ekacJIggOFYPHRBAJKX2WyG/f19hGGI9fX1I5lnzeTr70qWeI7vqg/cJnB8n99JRElUCTrCc44qaWcrQ22z52f+Sf6ZHVYnfM3g832fwGktuioLgNvKCRLeKIpw7tw5nDlzBltbW04OP5vNkGUZiqJwJQw6BveApoZUX2gJBImuT259DwU/4KDlBQzwsFyC41Gyz8APfQw4Zp7n7v5oIEMz6P6cgiBAt9vF9vY2oijCwcEBDg4OsLe354IbqgZh+UOz2XTz515okMIvC+G9z/McWZahVqshiiKnCiFhpxniwcEBBoPD3tVbW1sIwxCtVss9Dywj0WdOg0mrkHwLBBgMhgeFq3s9/Dv/jx9Y2g/6ys4aznRH+Js/9Ct4euPgFGdnMBgMjx9+6E/ewLf+4AB/d/xhXHmrv1AFUL7ewuyNGOXoqLG04cnBQxUE8EkLiRCzrH6bOc0GaybXH5Pw6+z9sfi6yrQ5HwYBtM6bmXSfAPvn+lBVg2ad/VZyDBL4dfj+Xunam80moiia6wSgKgASW60xr8rqM7BQtSZVYzB44TvUax27jqVz988jaa5qq6jz05/1XnDuqqLgF80m2+028jyvLCHhd50TiX/Vs1KliqA5o6o4dOyiKDAajbC/v4+DgwMEQeDKXag0UL8K//nW++XDfAEMBsM9QQnUrrwbiLwU3pFJXz6p44tXzyw95pmtfbzn7C7e99QNdKLiyPvr9QLvbe/izbyDwTSsGGE1lHVg+lyEsh6g/vajUc9qMBgMJ8W5iwWee3+GN7/Uw5W8u/C4Mq2h3HuoKOCxKIsA5W4D6MxW7hRgn/3L8VA9ASTYwCGh0XZ7URTN9UlXEg7My8P5O4AjhN4nbzoWCWOWZQDgvjODS0JL6Gu8Hs0EgduZZa5J58igAjPjKpHneOPx2O2B1rgTqipIkgSj0QhRFKHf7zslwMbGhlM0MCOvBnWqntCSBw0cKLluNBpuDGb22XWAygHW9PPe9PviRip7x3tABUC73XavkUyrWoH3giSd7zMDT2UIM+/aujEMQ/T7fWxsbDiVCZ8lEm6Oz+dDAxkaBFDPBt4Pv60g7z3H5nqGwyFu3bqFmzdv4uDgduZrbW0N6+vr7v63Wi2nIuA94DPKeSss628wGO4ZJiVaf+cdIABG/8nFww4C9xhBAPz4d/8GPvrCFTQWmAx+tH8N39y7jr/6tW/Br+1fvPOLtWpI/oMLaPz/EnT+5tU7H8dgMBgMDwTljRCTmyHq33iAYNWyAPvsX4oHGgRQ4sXfNZNJcqmZYUIJPXDbME9rxv1r+LXjfF/l61V+A7VazZE4v1YeQKXDPK/r940nyaV8XMsTqA7Qdnzal57ncWwlzEVRIM9zR3rb7TbCMHTX8deltf4+SG7VvE/LJZSI83XK5lW5wOupZ4EfVOB1SHj1/pP4+veO146iyKkm9Dg/k05SzkAAOxKwM4Lvg8D7wHtepSbRe60dCrQcgetWdUccx9ja2kKn08FgMJjrLFAUhVMDqBEhfSO0mwS9HNTDwP9uMBieLMy2myi+vYvpS9HxBy9DCQTT8k66MjmstzP8wW/4PJr1aoIfALh8Znfh+wBQe9eAcPUGhgtw6Gb4kKU9DAaD4XRRJnXMrkQod5rHH/yw4d1WgeVbEWZpHcHlFEHjmH+l7LN/KR7YtlQRFf93SttJRvU8JdV8XcsF/CCAklm/HIBEliA5BODIKQkhM/jMpqt03CeH6jtAAs8xdW4AHNn02/8xCEByqJlhrl2DADQEZE092/1VBQFIXjl3DVA0m805EzsNGpBoq5rAb6OopJqENooip5RgiYcGAfy99EsT/HvI9ddqNaRpirIsXQCA94xknkqStbU15HmOKIpc9l7NCXlvVQVAaC2+X4qhzwXJu3Zt4DpYltBoNDAajZDnOXZ3dwHAeUvo86rPtAZJ2JXCh/93ZQEBg+HJwfSpJvJ/e+uO5PtzCICyHlSOUwIYlzU0ytnCev96bYazvQR//OO/jXb4EEkwgwBlA8AUWGJVYDAYDI8UgqBEvVGiDIKlHQHKpIbZFzortQQ8enKAybSORm2G+n3qEFCWwHRWw3S2OPQ7eztCsNNE/ekMOC4IQNhnfyUeWBBglbpmlXZXmbNpezn+TkJKMkXCTXLLc0jYtJxA56A/k1wSSoZ9d37OW8319DydF0kuv2v9OWvjGaBgdr5q7sBhdpxeAL1ez7nwA5jLzpPcUj6vgQetpff3TxUWGpTRjDSPVyKuaolGo+HM77QGnvvJYAeNAVXFofc2yzL3nmbrteyC8+L+sWXi5uYmJpMJOp0OkiRBlmVz7SD9AAb3mwoBvZecG7+4tyxFGI1GLruvzx5VCQzQaLtLEn0NZOm949r29vYwGo2W+gBYAMBgMNwRGgHSP3vO/ay4kvfwY6/+Pnz/5tfwQ2dePXJqEJT49//Ar2M8rSFuPFy9maevxBj9p08j+ge7aP7G6EFPx2AwGO4JXv5wgj/1E2/jV+LL+Pde+wCuF4v6stw53thZw7/zMz+AH/zQF/DD3/TZez4+AOyM2vhrP/cJXNm5t91t7LO/Gg+dQMI3WWM2V+Xn/K5fVQoBJVX6nsrtgduZa5908me/NEB/VgKpZFrXU/WaD7/GW+fhr5VQgzpm7lutllMBqEpCAwD65c/BN8DT4Igew9cZvPD3jPvCa2pWG7hdyqBjcjz/Xui61QSQx6shpBJoJdH0L6AiIY5j90z5Xg8K34wSwJGAkF9mwuvneT5nqsiAgj4rfhBG1RV+Rt9fC5UaVWTfAgAGw5ODsgbMng4x275HEs8AmF2uNuLLZnV8LtnEN3XfqT41AJ47u3tXlx/Pavha3sP03fZVg+m9WVfZrWH6SozZujliGwyGxwfd/hSvfHiEX3g7xOdvbhw9oATKYR24i24AadHAZ986hxfO7eCLV6/jma19tO6x0ms8rePzb5/FXhIff/AJYJ/91Ti1IMAyorKIsKRpitlshjRNHbFdRKiZTQduG/LRbE7l4QCcXDsIAgyHQ9cyj1DlgU9ISSTLsnTZXM3eUppfFIXL/vK7zpc/K/mnBwLnB9w2v9NsM88lAa3X69jY2EC320Wr1cL6+jqiKJqrdSdZL4rCtdej4kCz6hpkIWHluql2oPSdvexnsxk6nc5cOzzuC8f1PRt8OT2Jr/oOBEFwxCxRVQ3cb73vhAY8WPJQFIVrO7i+vo6DgwOkaeq6UPgBJYWWNrDdIok+7x3vNdecpql7DrvdLmq1mpP8U9lBdYt6X+j1dL/4DOd5jpdeesk9V1V/OxYAMBieILxrfjR7qnn3pQAPAXYmMX78tW/D/uQwELGs37XBYDAYlqOcBpj+dh/lQePOSgEEP/+7L+OXP/s8/vM//PP4wKVr92aChgeC+x4E8GuoF73v/wzMy6CZbdUe9VVZaxJROs5HUTRnpkbipmSVRE3d5oF5M0GSPB2PBEyz1zpnkkYtFVCjOCXAvopBCS4l5moeqH4G6s4fhiE6nU6lkaI/b/UdIBlVsq2EmJlsVReoqaBm3qvWxtd9+b6fCa8qjaC8Xo38dB7qj6DPlbYlZDCAJQhUTbRarSMZfi3T0L3jddVDoErBwXP0HhRFgSAIXBCApRIa2Kl6vgG47g5hGLquCxx/EUwJYDA8GRh/YxvT98YoN+pHpPv3E59OtvAz11/GH9h4A+fC9J6N+6t7T+NzyQYG0xBFaVkbg8FgWIRmNMN3/+gOeu8L8DPvvIIvJBUqAGIWAKt11luK6SxANm7g53/3Zbx2YwPf/8EvolG/y4FL4H/8/PP43FvnkI2Pp6blJMDstRaCjQlq2yt2CjAcwX0PAiwjIv57vvxZCbW+75N/v4Y7DMM5BYCvFiAZZHabmW7gduadJIoEnj3sGTygGoBt37SzgDr6kzQyQ6wu+Rrg8IMAGpBgRl59AJSghmHojO9Yd+877auzvl5TSwL8doEk7SSqGszQ99T4Ts/ntZXcays9n2RzHGa7lRxrZwEt8dBgixJyZs55HzWAUqsdtuBrt9vodDpun/3Agl7fN+zTIIqv6NDraxCAe8Z74Ev+/fvBa1EhEEURkiRxRo/LYAEAg+HJwORjHRTfu6R+sgQwKw91+vcwof6p4Vl8enQGX9/ZwWbz9n/CAgA1lAhO6L40KwPMEOAXd57Frx9s37uJVqEWoKwDweLGBAaDwfDQI4xK/PCfuoE3Njfw46993d0m+VfGrAzw//3k+/C75y/gu97/KoDV/F9qQYlaja3ggVlZA//7/Au/+xL+5y9eXm0CkwCzL7VRu5gDJwkC2Gf/HB7qcoAsywDczqo2m01H5Hi+GqqxNV4cx+j1ei6zmmUZ8jx3ZJ1jkqQzq80v4HZJQRRFiKLIGe1pRpjGcwwmTKdThGHoCLNK4H2pPTPimiknwVciyCywnqe/U52gLQFJcNUXgGsiMWU5gK8q0Llolr0qO67lGVyjZvU5V16XZFbLLZTI63vazYDvV2XnaQCo5nr6vl5XAy28r9wjjusrOjQYwJ9ZDgHMl44wgMH73mq13Hlpms51euA8Se71mdIyjel0iiRJ3Ng7Ozu4du2a6wCxyt+ZwWB4clH/So74v7yB4gfWMf54956OPS0D/K03P4ROXQx7UeLHL/4uXm6fzBfgNw4u4GfeeQVfzXr3dI5VKP6NdUy+pYPWT19H7ab9b9BgMBjuBG/t9vFn/p/fv7BTjI/veOU1/Nsf+10AwM1hB3/jH307kvyQ57x+Y4mK4R7BPvvncWpBgOMCAD55CYIAnU7HkWq+pl96LBUAmq3Xa6m8WmXxhGbxScioFqDcngTaNwFUwq9t4TRjrJlbBgZ0XSrDV/NBJcpci45Dost2e+rMr9dm9t+H7g33wy/D0Ey3jqP3ws+eMwhAck+SzJ+rJPX+HvnPBI/VYINP1PVY9WTwnxfukQaCdH99pYmu199/vuevp2qf+Gzoc6SBD1/ZMJvNkGUZsizDaDRCmqYnUtcYDIYnG8FoivrnMgQfuz9O/a9m8yqEACW+lK6hEZxMHvqFdAOfHm3dy6ktxGy7iVm/jjKsAbD/CBoMhkcPWxfGOHexQLO5nICXWQ1I6/floy4tGvj0lfMrH3+uP8RX3tkEALxz0MWn37iAYV5tQns/YJ/983jg3QGUKBEkcN/2bd/m+qh3u905bwAlUyTrnU7HkbI0Td1YwKEZYK/XcwSQpD7Pc6cAyPMceZ6j2+2i2Wyi3++7jLG2/+McSNba7ba7VpZlc4EEn6CS6DHjS+LO8gLKxalsUOLrB0GoVGi3265cQQMRDCpkWebk7uy4oLX5Wr5A0k6JvBoHco3qF6D3ws+aa1mFdhFgkEYDL1yjPhd+5wUek+e5e0/LD3gOibT6PlBCz9d7vR46nQ5GoxHCMHQtCpWM83i/XEMz+X7ZggaWeC9rtRq63e7cMVouQLNF3qd6vY5Wq4XxeIw0TXHjxg3s7OzgrbfewqVLl/DhD3+40gPBAgAGg+FBo0SAn3rzG1bODBGT0j6/DAaDYVX86J+5jj/wv9lBGM3w6nDxcbNXW5i91jr0BHjA+NXPPe8k/yUCFBPzfXmQeCBBgOMIC99rNBooisIRdd+AD4BTAJDUa/Z2WdaWRJju8OowrxlfjqckUH/meJwXAxLq3K7jVa1bs+k6tpoZqkcB58nr+F/qOu97CzDgoQaIuk7gdjmCn+nna1W189wjzaQr2fXNEHWsqiCAr6TQIAPn52feVVHALw2wzGYz5/0QBIEzBoyiCEFwaNpHqb+qRnjPdJ6+WkOvX6WaYNkB742uic94mqZzngsM9HQ6HRRFMfdcKfRZt2CAwfBkofE7KTABiu/oAd2jRf+zs00UP7SO6QvRqc2pKGt37UBtMBgMhqOYXWhg/LEuai+9g6i1guKqDIDpw/H/wskswGT2wPPPhndxKneiSurvG6pVlQQAcJlsuqJXZX7jOHbkW4MFwLz0X2vbSYZ9ozV1dFfSqTXm/lr0eA0CaN23EreqEggdp2q+XI8GAdjuTsm/dgqYTqdu37g+ti9Uou/L8VmSoF9UEmgQQNejwQCOy3XTFFGP9SX2JMOEkl1VDuj9ULKua2GAg/vL689mM+dj0Gw2nXcCa+s5dz9I4ZdJjMfjI7J+vq/z8U3+wjBEHMdzezWdTl0AIEkSxHHs7h3n2e/3AQCtVmtOheCv238WLRhgMDz+aPzGEI1PJ5h8pI1ZVRDgYhPZHz/zAGb2CCA4/P/xCUULBoPB8EBQBsD02QjZHz+D8aUrmL2roLoHpv+PHu7mv7j22Q/glIIAPulflBmvOo410ZRxNxoNJ93XmurZbIbRaOQIr5rQAYekKM9zR7oYBKB8n8RXnfaB29lfdcfnnKu8CrTfu2af+TsDED7R9DPsNDQkkWy1Wkf8Bvr9vnudY7M0IAxDZFk2FxRRwk/4ZJzkXb0V/EAF56t1/Xmeu/F5HkseOG+t0Q/DcG4/gNsBDn8vVGngmwfy+twXBkZ4v5jhV5NCXocBFJ0Hx+JaaHioZQu6d36Aw+8soe8p8eeYXFer1UIcx24dRVG4PYvj2LUW9Im9//ekf0sGg+HxR/EH1zH+aAezTcuunAhxDemfP4/676Vo/f1bplwwGAwPNcp2DemPncX0mQgIgJ+98QL+x72nAQAHk/DJ+ggLS9Q/NEDQvYO6fvvsdzhVY8Cq7OQiJYBK7LV+XbOzSuhmsxnyPK/MMpN8sQSgKApHDP2sscrQq9zhdR5q4qbzIdn1TeVUxVCljtA94XF8jxlgDRj47vas6ycJ97PimsGvCgjonnEdVaUKPE4l+n45gDrdq8rCv/d+/b3/XOh+EH7tvc7HD/zw2VCpvpYqVCk0dG2qclgUQPHn6ZcF6Fq1haTeF38uup88jh0f/HVb1t9geHJRtmso1xuAlVaeDHVg+kqMIJmhxN0llQwGg+F+o6wDk1dilOcPk5Rv5D28kd//bioPI4JaiWBzjCC+Aw2EffY7nGqLQP1eRV6qsplUAiRJguFwiHa7PZdFBw7N2SaTCUaj0ZwzPjDv+s/M+Gg0mpuHOtazRp3nkVQyGFFVDx7Hsav3ZhaaigUdi1JyZs2DIEAURW4e/hez5vQ9KMvSSdGD4Hb3BBrLqXEiAGeip20P1cROCbreG5Y0NJvNSgLvtztU8qylCSw7YCkB56/En8oMZsc5D66bmXoGFDTrr+UZGqihSSKDIFmWuWPUVJDzUj8FroOlJ/7a9bnTdXPfGWzS96mKUHNE7QqggQYGfjj/yWSCd955B0VR4IMf/KB7FnUuFgAwGJ5cRP/tLsJ/so/RTz2N2YXmg56OwWAwGAyGRwD3PQigZNt/bRVozXSaps7ETQkbyXi73Z6TzPN8XwHgS/H5M79IxCaTiSOHwG3irJloPZ+EUgk0yZ8eU0XkfOm4v2dqisigQBzHrsZdAw0ksOx2oJ4GJN8q6Sc0k67k1D9O561lEKoaUPm9KjZUWq9r433y117li6B75Gf5NbjA19RHwd9fDbRoVwTfKFK7Dmi23/dKqNfrriSFJSY811dZaDBCzRs5Jz77e3t7yPMcTz311BEFRBVMGWAwPDmYvi/G9KUYZfv4zwaDwWAwPBko0zrKqyHKPSsVM1Tjvj8ZVbJzzSIDy0nLbDZzpmnD4RC9Xm8u4w7AkaZWq3WkBIC13mzBRhLqk1PN6mr5AJ3l/Vp4DUJwLVQDlGWJMAwdqSWBbTabrm5dM9sMahDM3OseqXN+GIZotVrodDpzzvcMcNDrgIET7pESWS17IJSccu8J/1ifSGvgRbPhSrKZYffvG+9TURRz94EE3lcsaEDDJ+VVwQRtYaj3Wss3/BIKBgF4z3TuKuXX8gdVlXAfVInC49nakfPQto2cUxzHKIoCSZLg5s2brtRlETiW/91gMDzeGH+8i+J71x70NAwGg8HwEKEc1jH9TPeJrnk3LMepKAEWBQIWERU9Z319HR/96Eexv7+P/f19XL58Ga1WCwCQJAmyLHOSeGbfSfxJLLMsc1lxEksSPyWuSgr5mma7OTbf19Z3vBbJno5PEquBAiWSwLw8vygK97uScr7PIEAcxy5j3Ol0nAnhdDrFYDDAYDDAcDh0Y2hAQwMQJK/0F1Dyqq0OtXZfpf/alpCBCD1XlQhacqFBoCpCTYJMkGDrvVDjRo6v2Xy/vl8NI3l9dkzI8/yI2aMGE7Q8QoMB/rOswQDuvc6TQQp9tniemhUOh0NcvXoVt27dqvQk0L8VnasFAAwGg8FgMBgMBsMiPJAWgYT/mhIaIooinDt3DoPBwLn/kxjmeY4sy+ay1L77umZZlbz6RFBJKrO/Wmeu5M83/NPrKpH1pf8+UeR5PjFXgs5xuBZ6CrD1H9dOZQIJJ7sfjMfjOWl9FfHWsgqta+f4nCf31M/Ecz1cg5+h96+j+6nH677pPHV8zehXmQpqwKXK0LGq/EPr8X2/CV/xoIEJX4FQpQypku/761VViSoqxuMxhsOhCxxVQf9WjPgbDE8OyjjAbLOBsm2OgAaDwfC4I5gBtesTzBoByi2T+BvuHqdSDqDwAwJVxLjquN3dXVy5cgWbm5sIw9D5BEwmE1y8eBHtdnuutpyEldl5AOh0OqjX606KrcSUWWvK9TV7DOCIsRuAOdNAyvBJ4JgdD8PQXV+VBRxbiSzl5jy32+06grizs4ODgwNcv34d7XYb3W4X9Xod6+vrWF9fn2sNSP8Djqfye5XGq+mfZvvpI6CqB3W118AGyS7BcbQWn8fpsbpmkm9VLOg4/vNBtYHOIc9z9x6NAbWFYZqmyPN8zkuB9zqO47nOElVBGVUCFEVx5Pkuy9LttyorqoICDNLwOCpbNNPP6yRJgm/5lm/BxsaGuxdVQTXL/hsMTxYm728h+csXgMj+7g0Gg+FxRzCaofMTb2Pykc7hZ7999BvuEg9UCQAszl76AYGzZ88iCAL0+33keY7r168fyQzruUqySeAon6fcWrPwej1fEq7XIZHzM9Zas85zqzLvfhBAJeIkhSTBk8kEw+HQrXc0GmFnZ8dJ/QeDwZwPAkm8HwTQLPmye1JV565fDEjoaxxLs+56D3RvSZSZmdd5qNHicfOidwDLJTi3Kok9cDuAoQEXNeCLoghRFDnPBF8NUOWH4N/fZfeeYwBw5RsMUOjcVYmgQSgGhXR8//4tC6AZDIbHEHUA7Zr9R9BgMBieEARpCeSrtcUL4ilqz6UobzVR7ptywHAUp+YJQNwJOQmCAM8++yyeffZZAMDVq1fx5ptvotfrodfrzZEu3wBOSRSVAL4E3CfHmpn2x2X2X9vUaUDBJ7NVQQI/SMHMcBiGaDabaLVamE6nSJIE165dw+7uLq5everKH4LgsLXgwcEB+v3+HOGkCWKapnOdEHQ/9Hd/3X4pgpoF8nefaJPcL4K64Ptz0gCABkh0j6jA4F7T7JAKDs2Q+2oLvcf6Rfk+95sqAfUS0PmrLwOvrf4RupcaKOEc+DvvLdUqQRA49YYGKxbJ/6uCVj4sAGAwPIHgR1BwzGsGg8FgeLRxnNlfAAS9KeofGGL6e93HKwhg/57dM5x6OcAq0MBBVVaTEup+v++k8ErgSOK0XV8YhgDgCLeSeSXAmokFbkv41fRP51lVdw5gTubOjLwGBtRQkHX+lLHXajUMBgO88cYbePPNN7G7u4uDgwOUZenWw8w1x2HmfzgcYn9/H1evXnVz6fV6c+UOPrSFIUmp/q6BEV2j7rHvr+D/zGBM1TPhB0TYlYHr4x5q1r+qrZ4GJ8qyRJZl7hiWc2RZBgCufEBLD1Q14ZdKKKnXMgOuR58l3RtdX61WQxRFbvwsy+YCVqpA0ECBf61FfxcGg+EJRTZD6+/dxGyzjvwPbx3+Jykv0fp7NzBbqyP/327Zf5wMBoPhMUD9iznaf/3txQdEAdI/eRblmceI+AtqLyQIzo2BprU9uFs8kCekitDo71Vy56pzKfGn47vW2KthXrPZRKPRcG35VHqvMnofPsFX8zfNVOs69Bxf8q8EnIEArdvXNn55nmN3dxf7+/sYDAZI03ROgaCKBm27NxgMcHBwgNFo5AIGPF73WPdTSWoVmebYmqledL/8c/mzqgH8a+veab28jq3Bl0XtCnk855gkiZsDr0vfBgYV1A+hqlxCgzb+z3qcH1zxj6sKAvFeV0Hvi3/fqv42VD1hgQKD4QnDBGh8JsVsq47xtTFma4ef9/XfS1E720BeAsFgCiSzw/8YNuxzgSjDALMLTdT2pwiS1WS2BoPB8KBQ25+i9slk4ftlK0CQlY9tZ8BgbYLa2eL4Aw3H4lSDAFU14seRFP99krw0TZ1knzJ6mrvNZjO02233nsr1gdut/TieZr+B26Z1zCRrJr/Vas21fWPLPhJdrSkntB6c61YXeP4chiGiKMKtW7dw8+ZNvPXWWxgOhxiPx3N7qH3msyzDzs6OI7pXr17FcDjEYDDA2bNn0e/3EUURgiCYC36wDt0PQjDbXRUI8NvU8V6wxr3qnvmKDF9ZMJvNjmTbVVWgJJ1frVbLHUfFBZUSVEUURYFbt24hDENsbGw4ZcHBwQEmkwniOMba2poLIHH/1H9ACbvOq16vO+UF172oXIDnFkXhAhMcV4NKVb4GGrxZ9Dex7G/IAgAGw5OF+uczdP/cFaR/7AzGH+/OvRf+3B7CXz7A6P98EbNL4YIRnjxMX4kx+juXEP/9mwj/ycGDno7BYDAYDKeCU/UEWEb+F/2+KMM5mUxchwC62FMNoJnZLMtQFIUj0my3phlavk7yR2KsPe+ZhVdZfVUdOMEyAo7tlwBopldJYL1eR5ZlyLJszgVfSWEURWi1Wq6MYDQauWsPBgMkSeLmHEWRC2YURYFer+eCFlyrr1hQIss1aJ28ElO/DKIqY8/MO9/3r8P1+YSa90Cvw7kwqKDt9TgO1QTD4RBRFKHdbrsgANecpql7nXtPEq7PH4MDvpGhD12LrxTQwIKqKKr2TJUTfhvLRaj6G6t6z2AwPN4IpgCGMwRj+Uy5NUHzlw7Q+GKGYDQDLNk9j0aAshegbNrnpMFgeAwwBZq/PsDmKyU+8okDfCZ+Bl9G60HPyvAQ4oF4AviEZRlJWUS4xuMxkiTBwcEB8jx3WX9m6Jklpot+kiTodruI4xjtdntOfg7czv4z88/vnANd+zWA4GeMeSxJr0+aG42GG1vP53tUNCRJ4oz9tL89j+l0Ouh0OiiKAqPRaE6NsLu7izzPnUoijmNcu3bNBRaazaYzE+Q++ntbtfc6B1UxaKkAf+e6eKz6LmgbPe4r50AiTn8HqjF4LFsX1ut1tNttp/bwDQs5n8FggDzP0W630el0nNneeDzGwcGB85LgvY3j2I3B4AjHUrO+qmdykdmhdiPwgx/A7eCTGkuqWoOtDBfhpEoag8HwmKFcXu5fvzJG++++c3hobJ8HBoPB8DgjKGaIf+YWXv59Q/yVP/Ia/s7nY3wZFx70tAwPIR5IOcCi3/kacNQXQDOnm5ub+M7v/E68/vrruHLlClqtFtbX13H+/HlHUMfjMSaTicuCa0aXLeY0COC/rwaC6tROl3qtn/dr1peBBE8JJiXzJLKDwcCR+8lk4joHUMXQbrfR6/WQ5/mcUd5sNsM777yDoijQaDSwu7uLRqOBr33ta65Uotvtot/vu9aCSjBVdcEv7o9mppVw+74ItVrNkWbdF/7OwAoz85ToZ1mGJEmcTD+KIncfuW9pmrr2h3EcoygKZ5CY5zmCIHD7w/s2Ho/xzjvvoCxLdDodXL9+3QVIWq2WO5/mkVRfqAqDXwwAca1UIfjPBV/X/dOAkCoCdG8YBOAzvLm56YI+VX8XvmrBfAEMhicH9S/laP/Nq4e/TEoEO4s7tABA8d19jD/Wwezs42kWZTAYDAYgjEv8H/7a23j+fSmCoETtmRT1yQFmn+2iTBYnlR52BFtj1F5IEayPjz/YsBJOpRwAmJeWL4OSm6r3AKDVauHZZ5/F22+/jeFwiJ2dHZRl6erfm82mq1Vn/T1l38B8dtaXsmuHAWbzfbm8L/PnuSRxi9bj70VV/Tgz3qwh55dfDhBF0VxmnQGD0WiEoijQbrddS8HRaIQ8z13WncSUayC09ED3Cbjd5k8l/rpnWrOv974qEKB7wKDBeDzGYDDAdDqdC3jo/eF6syxzRJ51+UmSzLn3U1Uxm82QpimS5NBEZTAYOB+CLMvc+VQh+GvXrhFK0vV59Mn+KsEtfU33SJ+pKIrmvCr0mdLvVa/7ChWDwfB4obY3Re03R3OvlWGAcq2OslXRBebZEJNv7pzW9AwGg8HwAFBrAJe+ZYLN95S4Pm4j6QYILhTAV6cIpkCZP2KBgAAI4tmhIeD2YWcvlECZ1YA6EIRLatxmQLA7AaZH3wr2pk9805xTKweoIkFV2Uo/y+nDl1I3Gg3s7+8DALa2tgDcNpNj7bxKxP3WctrGz5f0a9CAnQX0upTgM2usJJfkkTXqKr1XckZDwF6v59rH0ceA1yb5bDabrhSg0+nMSccHg4EzBAyCAJubm4jjGHEcY2try62v3W4fGdevV1e/A5JbEmTK75nVp1KBe85suSoldN/1Nf7cbrdRq9VcuUKVEiEIAkfsef0kSVz5w9tvv41arYZ2u41Lly6h3+/j7NmzLghCc769vT3XIeDixYtOZRHHMVqtFvI8d6UmWr+vpo9+YIJ7xz2gukMDO77p4LJnLggOW1LytUVBheP+lqp+NxgMjy+m742R/OULh0GAyePqDW0wGAyGRchmdfyl1z8KjA9VzOmsjqBeov7N+yhvNTH9rTU8Sq0DgmiG+sf2gJZ0FytqmP7LdQQbY9Q/PFh8cjJD5yeuInjnqHogmOCR2of7gVPVBfqZyiqJ8zKfAF/uTJLEzLhm+6sM3pR8aSDALwvQa/nzUKd6nqPmdX6G3Cd9vIZmfEkYVTJO4qgKAA0WsASA16JBIADniL+xsYGtra05GX6/35/rmKC16jyGknU9Rkkq18iSCyonqswS/ay3/zqDIJw3gyok7lmWubVz3Vq6QQNFrn08HuPMmTPodDqukwO7E2hQZjweu/mHYTjnyeArAvyWhFwPgxQatKjVam6/1D9BDRj12fMDXnxNAytVfwPHqQH8cwwGw+OPshGg7NedScDkY11Mdw8/12fPWEcAg8FgeJwxeTnC9PkIeRyjnM53lwqaJcrGI/j/wQBAWCKQuQeTGcIv7CBojlG7lWL6/hZm28250+qfy1B/LUdwY4zagTniVuHUugNUyaT9TOZxWcsqQl6v19Hr9dDv951RnBJPNeGjFJ4Gc/oes7dK+PzWdfo+x5vNZnO1+ZynSvRJ+qgm8DPqPIeEj6SUpDIIbte6b21todPpoNFoOG+D6XTqTBLr9Tq63S62t7dx6dIlXLhwAWfOnJkz5APgvBL0i0RVM9icP/eOxnxlWbqSBZ7DDLYGCmjU6Lf+UyVCq9VCs9lEq9VCURTI8xyDwcB1gIjjGOvr64jj2Kk7dN2U/E8mEyRJgu3tbYzHY3Q6nblgymQycftKo0TtmMDx6S+g5L6q1EFLTviaHs+AgraTBDD37PmBE46XZZkLSvh/M8v+zgwGgwEAEAbI/ujWg56FwWAwGE4J40/0UfzA2oOexn1HUEzR+Y03UNs5/L908ufPHwkChL90gPCXrO3rMpy6Q5ASHj9DWVUSsOy1559/HmfOnHHGb9oCjoRWjer4ncZ/JKe8tmb3eQ2Sdc3WcwyOM5lMHFljIMB3hfcDE7wuie5gMHAO9sxKsyY8CAKsra1hfX0dW1tbrtadGe5Wq4UwDBGGIdbW1rCxsYHNzU1XXqAgyWSfewZEtB2fdkIIw9AFAbi3qh7QAAn3RvdP761mtbVE4+bNm9jf38eXvvSlI9nx2WyGXq+Her3uggU0DWw2m1hbW0MQBOj1ekiSBFmWYTgcYn9/36kAVDXBAAfXy+4D2v7RD1xp1t5/dpXE+0EABooYLFJ5P58tBgkIPsNUAvh/J4uI/iJFwLLSGoPBYDAcoviePqYvx4j//k3UblUUkBoMBsNDiul7QuT/5iamzx/9f78i6E1R/6YDzK7EKK8+/Oqw2gspgrMFcIyCIfxHe2j+5hAAMHk5RvHDG6cxvUcep14OsArBryI6PqkJggAbGxvo9/u4deuWI1magde6bZVg+xJ2XwFAKGlVoksiry38lBjrPPyWcFyvklwl4wwCkOzy2myJxyx4WZbuOJWdR1Hk6tvViV6DIJw7gyW6NxybBJTf/RaAWo7BwIdPVqvq3f19mM1mGAwG2NnZwbVr11CWpescwDHo8q9dB7jH6s9AH4WiKJzSQdUHPrmnnwHnqGUAOn8/sOErWHR8P+Cj5or+HminBR7PAAXvS9Xfi+6fnqtz9H83GAyPL8oAh4aA/frxBxsqMXtPhNl2E9HP7qDSRcpgMBgeUsw2Ghj/L7rL+8UCQLNEsDFGcCN8JMrhg80xaueLY49rfDkHvvyuaWBWYvztPSCzEoDjcGrGgIpFCoBlWcsqUkPClaapk6Izu+oTxip5t5I+VQAwI8xsOEkpVQVa/023fhI8BhcoNdd5c15K7IDbgQDgMDu8ubnp5sQyhXPnzqHX67nXy7LEmTNnHOGnuz4N7MIwdDJ5muGR9LLNnk9k1QiRrRJJVBmQUELPsoVGozHXWk8z8Nw3Ztr92vjJZOLc+7V148bGBuI4Rr1eR7vdngvU0P/g1q1bSJIEeZ47qX+73XZy+vF47NbGTgkk10VRYDAYYHd3F9vb2853gHNWgq5EXp9TDZb4z7OWCzAYAdwm/gCceoQlFLxeWZYYjUZzvy/ColIFfz4Gg+ExRquG5K9tY3oxPP4/gQaDwWB4MrHXwPRf9VFOHt9/KBqfTtH9s1cQJBYEOA6nXg7gZ02rsrTLzvN/BoA8P4z+JEnier+TcJNc8zwlu3ptJXmazV12XJVPgJ9d96XiHI/rVRk6ieDGxobLCJMYd7tdRFE0505PopmmKbIsQ57nTr7PedCUTmv7GQjgGjRD7Wex/fnyd85VSS3nVdUmUffeV0e0221XxsDs/vr6uuvsQHKuAZssy7Czs4P9/X3X/rBer6Pf77vyCF0HAyD8nXvBsghd+6K5axBJA0H+86iKCr3H6rWg0OM4r9FohCiKjgSM/HOqsCwgYDAYHkMEOFQBdB+x1k8Gg8FgODWUs3dbBD7i/zUswwDjj3URDG+rtoJxicYnEwR5iWDP1Fyr4NSDAMTdyJb97H6SJJhOp7h16xa2trZcLb1K8oF5SX+V3Ns/nvNSgsxray28Enwl2VoioE7+Ctbyh2HoyOLTTz+NjY0NV+c+Ho9dJp7jA3AElpL60WjkMst01WeggHNhFpwKA3oOaCDA91DwSbyWAWjmnATeLy3Q80iEVYZ/5swZdLvduW4DZ86cQavVcveFhJtrGI1GuHbtGq5du4Y0TfHMM89gbW0NZ8+edUEAbWVIwq8lIVQHqMGif/85RyXiagaoXgEamFEPAu6TZvupMOA4VCJkWeZaH8ZxXBkw4JyqygGq5m0wGAwGg8FgMDwW6NSQ/emzcy8F+1N0f+wKgnyy4CSDjwcWBCDuhKQoIavX6/iGb/gGHBwc4MqVK45w9vt9RzpJzihF9zPcWtPP4/ieBgjUNE6z3T4p9L0AqoIAPIdu9ePxGMPhoakFTQG73e7cef5XkiSIogjtdhuXLl3C5uYmwjBEv993qoE8z51cnnJ93/yQpLVKDaDkVdUKQRDM7acvi/dJqRrj6Xf6IARBgLNnzzqy3m63EYahy9LTxG82myGKInQ6HVy4cMEFBDqdjvNMAA4DJLz/9AtgGQFLCHRvNTiipR40YeReaukG95D7oioDfU4YKOF+c2x9hunlMBwOUZYl3vve97q16L3yFTGLygGM/BsMjzemz0fIf3gdQABMS13Gmn8AAEKYSURBVET/n13Mnmoi/5ENKwkwGAwGwyOL4MwYtedSBBvjBz2VxxoPJAhQZXa2jLgsKxsIggAXL15EGIb4/Oc/j9FohG63i263e4S4aktAQsl/lRSeJE5l7Hr9sixdOQLnUzVv/7p6DZLQLMucFwG/+14Eej67EoRhiK2tLVdGEMcxms2mKwNQI0Sf8HMPFt0DVQD4cnZfMbGMeHKNVf4DzJRTDVAUhcvk6z4zOEOlx9raGobDoVsz1RQMdATB7TZ9LJFgUIQeBnov/OCNH+zxVR26B1UBJRJ/3TeV/msQgO8zEHH27NmV/jYMBsOTidlWHeOP9w4JfzJD+PP7QG41kAaDwfAkoGzXUEbv/j/xUS4FqwNB01Pgrk1Qu5gvOMFwr3DfgwB+bb1fW67v+edVEZ8qYqTkPcsy7O/vO2+AZrOJOI5Rq9WQpinG4zGSJDki4VbZexiGc1ndNE1dJwFfJu+vkbXrzIwziKDBBo4BwJFTGtWxSwCvOxqN5kz8OCa7B3Q6Hayvr6Pb7SKOYzc3NQFUGb2SXWbidd2a6VfiT4JNks1rqJv9otp1LUdggIMKCAYpACCO4zkFAwMCQRC4ezibzVxbv7Nnz6JWqyFJEkeiR6ORu1/r6+vu9fF4jDRNsb+/j4ODA4xGozmFhF/WofeJc9R7wz3zfRA0COB3l9CSiHq97so5WM4ym81w9epVAMDm5mbl30lV+cyiv5U7KbUxGAyPIFo1JP+nbaAGUwEYDAbDE4D8RzdQfOLQMBzN4JH97K9t56h93XD+xfojblrwiOBUuwOsktGskjdXnV8VQFASR/KmPgBsZddsNufOJdnzvQKAeSk/x1ISr/PRIIdPwJYpGfRa0+nUkU1+98mpthDkmqpaAPJcBiSYddfxdM0kp/QJqJq7BjN0DxcRVv+cKgNGf3+rghDNZnOuXIPvad08163zYDAlSRKMRiMXwPANEf35qHKCXxyXWXwNHPh7ouNpaUBV6QC9CegFoOP7qAq0+M9d1XNoMBgeD5QNYPLhNqbvu10uhAAo1609oMFgMDzumG3WMX1fC9MXIpRbK9K4KdD43QRl2kD5VAvlQQPl4AH/m9EoEZwdI9gaI4jvTsVW/1KG2lcLoDA13ElwKkoAJYiLspPLapurCKa+rwSMWWYSwtls5lrN0WWe5zJL7fdkVx8BNfpjRpznq/mbSsf5XlUXAs7XzwrruWmaYjKZIMuyuf3S+nuqAFjvPpvNkCQJgPnABYA58z5fmaDkNgxDNJtNV4vO9asUX++hkloNJvjkX+Fn3TkH7gm/eJ8472az6aTyeZ7PqSGo3KB6QNv7sXXizZs3sbe351QV2t5QyxvUOJBKBC2h0DIGv5yg6tnXAJN6DGjAhp0Orl+/jt3dXbRarbngQdXfEeG/VvXdAgEGw+ODslVD+qfPojzfPP5gg8FgMDxWmL4QIfkrF06W+R+XiP9vN1H2apj+ZIjpFzooB+37NsdVEEQl6h8eIAjvnriH/3gf4a8M7sGsniycmhJACX0VKVlWDnBcVjQIAvT7fXzTN32TI+xRFLlaerbQY4ZbSSxBzwCV+SuxZc95P5urJFbnpcf6poDMzOt+aLaZJDRNU0ewtcxAvQ789n4k3jTt0/npPKmGULk+z1kUtPHLJvx2d0rstVZ+0b3VjLsGOLg/Gqygi7/uU1EU7ngGOlhuMJ1Osbe3h+FwiGvXriFJEmRZhjRN3djsysC9XaQO8O+3v1ZVmXC9es/H47FTdTB4MJ1OXRCCxohpmuLy5cvodDpzRoIc905h5QAGg8FgMBgMTx6a/2yAxr8aoXZzgmnvMJFZu5gj6E4x+2IHZXJ6fgLB2TFqz2SHv9RLoHGPklSW67ojnKonAH9fREqOI6BVGXV+j+MYzz77LG7cuIHd3V1n5ufLuf02bSR3avynAQsldSTMSmx9aT2/+9luoopAa8aY16ACgevwz1Wi6s9FiaZ+VwLvk0zf1b7qOCXqPvnXn31zPX1f90+VGH7wQM3ymJXXEgfOlyoAVTlwbkmSYG9vD9euXZvbCzWLZNBA99dfm98KsupZ1GdK74Gukc8f58IARBzHGAwGiKIITz/9NPr9fuXfR9XfybLXDAbD44WyFaDs14Ga/a0bDAaDYQkmJYLRDPXfSxH+syHKbg1lpw4EQLA+AXpT4EoMTN/992SC2z/fawQAmiWC9Qlql7L7cw3DiXGqSgD9XbGsFMAfp+p9DQiwlRzl7VEUObm/EkyFksdF5QhqrkeSRxm+Zuo5H63D91vGKTHWFoRUG2irOs6PYzKDrTXyvCbPVRO7Kid7jknirEED4HZ7vSAI0G63XSDCvxb3SPeFZRMcH8BcEIJzoDcB58X75asaqgIO3PvRaOSUAL1ezx3H67OUIY5jd38ODg4AwHVVqNfrLgjBIIMaAupeqD9Ds9l0X9rJQRUlRVEcCV7oOoiiKJAkCfb39+faDy6CHxTja4tg5QAGw+OB7N/awvj3d1GuP/DuvgaDwWB4iFH/Yo72T11DMJiijAIk/8EFTC9HrowgqJWof+TAZdFnX25j9lpr8YB3gaA9Q/1b94Foel/GN9wZTvV/En4Gn/CzxScNCOgYlLWTcJKckcSRiHNcJdrMKPuZ9EVBiqr5+NnkKuLnZ5P5GgkySWnVXpBca927jumrDzQ7rfusGXs/c69fOi/ui6oQeI5P8jVoUEVC/fd8tYGOoeUSfjkCz9HuBAyaMAjUarVcQKLdbiMIDrsNtFotF0zR8X1FBeem2X0179Ogh5pHVilL9Bze68FggOFwiNFo5AIxVfvlqw/8n6uON4WAwfD4oOzVVjeCMhgMBsNjg7IBTD7QxvSVeLXj2wGmL0RACZTNANOL4byBbIA5Q75gc4IgLVDebALje/f/xmBrjKA/BdpTBPfY9T+4NUH9SzlqN49PoBmO4lT/N6GZcmCx2Rnf4+urkB8eP51OURSFqxdnFlvN5oD5DD1JHa/FDDKNBZVY6vnMzqs83yft/tqWZWVJQsfj8ZGyBQ1WqCGeKg58Au2XHPgkV1UNqlJQMqt7quvR9WophZJmP9OvY5JE++UVut/8YlaeGfU4jucMGhkE4PWpKOj1ei4zrxL8ZrOJfr+Pzc1NdDodFzhSxYhfnqDBEn+ffY8G7gvnob4QPIdKiPF4jKtXr+LatWu4ceOG627gY1EQ7Li/DQsAGAwGg8FgMDzaKFs1pD+2uins7LkIyV/dXnn82tMZgu0c03++jnLvHtHDAKi9nKB2rjj+2DtA43MZ2j957b6M/STg1IIAi7L3hJ+pXiTL98/1M/IkaVpPrtl8nqN15fqzttejzB+oJtkk6Up21T2e8I/z56BEVlsb1mo1N38qGjSooeRT11hV3qAu9UrifZ8Av65eAwZ+eztfrq/X81vqLQpKMIOv92E2m7l1DodDpGmKvb09NxaN9LSkgPea8nudpxrzra2todfrYXt7G1tbW+h2u0fm7j8PfleAKsWJHwAhGLSpCrjwnmdZhvPnz+PSpUtYX1+vVEdUBZKOCwxUnWswGAyGo2j+swEan0xQ2zW5qsFgePgQZCVa/9UtTN4Xo/jB9ZN1B1gVtRK1lxOgeJc7XItQXg1PNs94djhG7d3/q/ZPnqWvfy5D+EsHx0/3enXizLAaTs0Y0CftiwIAy7KZVcdVKQiU2Go9uh5TRcJJSknutPUdgCNjMAuv8nt/3Zyjth1Ueb2SVQYBSKA1W89r+V0BfNM6wu9iwNf0Z15DzRF9sq6mff698EsPdFw/8801+i32GJjga6pYCIIAo9EIo9EIe3t7zs1/Op26wIKvGOE+6p5oYCeOY3S7XWxtbaHX6yGOY+R5XvkMaZmEXoNz5f3i/dUyCv/e65pVPUGVxblz53D58mV3/UWkXl/z/16WHW8wGAyGxah/PkP4q9ZiymAwPJwIxiWa/3wI5LPDIMD9uEYABNvyf+KihumtE7ajbc8QXMoQ3Inz/wwIkhnqr+UrBQEMd4dTbxG47Bget2ysRVlRvj8ej11rPRq35XnuTNr8MgASM5JEzWBXlQ9ogEFJq2bpKUGvWrca8AGYI48cX2v+NVDB47kuHU+DF8B8EIAZc2aklYzrHvCrKIojBoYsPeCceA3OQck491bX5Zsd6v5rBwSOkSQJiqLAO++8gzzPkWUZer0eADhDQF1nFEVuvDRNMZlMUK/XHcFne8itrS1sbGyg3++j2WzOBYGYmadygM+LH6QA4NaSJIlrZchr+M+8Bqw0uMTrjEYjV25xEkXMskBBlXrGYDAYDAaDwWBYBcHlFI2L+fEHzp1U3nHtf7A7QeevX0VwwzL8p4FTLweoIiUnISyLZNH8ud1uY2try5FzEjMep1lYAHPk1894azbbLwfQa+p5fmZ8UcBimcRbpf7+eFXk0B/bH1fn7KsbuE4Njuhe6ZhV98hXN2hwwT/ez6zzeC0hUAWCr8rgGAxS+MqFoiiQpqnr2hDHsQsGMdBAPwHeP107SwnUC4LX9Pde1RsAXGcHVQUs2ztVnjAApViU/a/CceUBBoPBYDAYDIZHH8HeFI1/NTosB6gHmLy/BcT35/98QbMEmqdTIlX/Uo7a13LUrhYIEutqdRo4tSDAqkqAZcdXyaR9AnTx4kU89dRTeOedd5AkicsQ81xm7DWDvkjuTpM2DRL42WzgdstBJYf8nV8++dWABMci6Sdp9WveAcypGJTIq6Rf5+erG5R0q1SdWXCdO68H4Mh5/K6181X3teqLoLKAe5xlmbsWAwBBEMy14ptOpxgOh6jX63PGe1QL7O3tub1pt9sIw9ApCGq1mntNgz7MyCdJgtFohCRJ3F5okERJvrYB5LEk9FEUzSlDqoIyDDoURYEsy1wwYRnRP8nfj8FgMBgMBoPh8ULjSzkaP3EVAFB2axj+9CXMtk8o2X/YUALRz+6g+ZujBz2TJwqnEgRYJvFfRvYXkf6qOmgfSZIAAPr9vjuHhKzRaDgJP+X3DAzMZjNnIucTYv+azPgyaw/AEVfgNnEmOffH8RUEqgLQcgN6AihxZIcAZrqpbiiKYi5YoePoXHldzleVD34LQP/e6PeqPapSfXCemmHnWjmGT4QbjQY2NjbcvuR5jslk4koLaJjo73MURYiiCJubmwCALMucykCDCUSWZUiSBPv7+xgOh0iS5EiJg95Pwi+rYMkJn604jtFoNOYCLRoMmU6naDab+MAHPoB+v1+5z4sUNIsUIQaDwWBYHbU3CoT/aA+Nz2YPeioGg8FwMmQzRD9zC2gf/l+0+P09TD/QesCTMjwqeKDdARa97hMfP+t93LllWbpacL8zgMq1ScJYN09lgBJpzdb71yEpVAO+Ksk/r00yyPf0ZxJYEmOdO9/TbDMl636XArY31Ow/1Q4Kv5tAVdBF93NRAMNf87J74/sQ8NpamqF7Vq/X0Wq13BoPDg6QZRmyLJvLzjPjXpYlGo0GWq0WWq2Wc/5vNBouwMDOB7y3JO9ZlmE0GiFNU+R5fkTNoYGcqjVraQGvo/4J+vypyqJWq+GZZ5458owdR+79+2HBAIPBYDg5ajcnCP+HAwSmPjUYDI8YggkQ/trQ/T59qonp8xHQqgGL83kGA4BTCgIsksP7qFIAVP287DuPS5LEnceMOTP8JMrMsJOI+r4AWj/vk2Y19ANut9oj/Gwz5eucJzP1Wgfvt/zTmngGKWq1mhuHwYswDB255fxVxk/wWjpX3VsGC3zVhJoLatmAT4b9e6o+ClXKAX88v/whCAJEUeRUDzR5DILbpnq8b41GA3EcI4oi9Ho9FzzgWlut1tw94DWn0yn29/cxGAwwGAycpwCvzyAR76c+P7o/foBjMpk45cJ4PEYcxy6owWPSND3SccK/J77qZVGwxj++ajyDwWAwGAwGw+OJ6B/sIfyfBhj91W2UFx7xEgHDfceptAjUbGoVwak6Xn/2M+qLJNKKLMtQliWGwyFarRbiOHbkVjPjPsn3X9evqix/VUa46thFGXN/bQDmMsqqNNBMNB33NYuumWeOrevidTS4oeqEqpZ7Ojdet6obgE9Wdd3aKUEDLOon4AdRCAY+NPDAEgISdADOLLDZbDqvAZYNZFnmTAJ1biToRVE4wu4He9R3gJ4FvlpB742vrND7w+MY3FlUdqDXIDRoUqXWqLoXRv4NBoNhAaYl6l/IUP9yfl/abRsMBsNpo7Y/RZnN0Ph0itlghukLEewDzrAIp1YO4GNZGYD/+yIys0wxsLe3hyzL0Gg0cO7cOWxtbbmsrRJsEkqSUa1LXzQfzXD7Mm8lwVpDrk7yVWsiAWddP8E5M9sfRRGAw/p5tkLM8xxhGM6RYq5TCWaj0XCmg6okUHLp162r18F4PJ7bH7ZQVIKqvgJqplh17/i+GhLyPc6big4NBACH6o52u+3q8Hd3d9FsNrG+vu6CKPv7+8jzHGmaYn19HZ1OB+12280tyzKkaYrhcIg0TV2JBXCoyqCqgIES1vszEEEVhrZOVDWKdh5Q74LJZILRaISbN2+eqJxiFVK/KLBmMBgMBkFWovV33kH97TFgH5EGg+ExQZCXaP/0O5h8qIXR37xoQQDDQpxqEKBKqszXq6TMPqFZlB2tItTvf//7sbu7i6997Wvutc3NzSNZWn5RHaD1/UryNUvur8cPBGiGnSoDAC6TDGCO9AJwhJqkkCUHSv7r9TqazebcnEhAeR0Sbt+wj+cyU04Czg4IvlJAyxEYcODP7XbbjaOBFy1vUPWDrw4Abmf4Sab1fup9IfGeTqeunINBkU6ng8lkgizLXJkAyT1l/lp24Wfc6f+QJAmSJHE+Es1mE+12G1EUubICAE5NMplMXM0/gyrNZnNuD1Q1oSUfNJ4cDod45pln5gI3xyllFqlnjoMpAgwGg6ECJSwAYDAYHj88zJ9tJRD+4j5qbxRzL9e/mj+gCT25uO9BgEUEn+/pcf55VWMpNOuq5KlWq+Hy5ctotVr41Kc+hTiO0el0sLa2NlffTcJJBUCVGZz+XqUO8OfnZ9CVCKtZn8ri/QADfybJDMPQydl5rJYJkESrr4HOhz9Tus4ggBJUvq/lEST/RVHg4OBgrna/as7+eLoWzsH3CQiC4IjDv7Yc5Jhs4TeZTOYCITT1K4rCrYtBgeFwiCAIEIbhkblwbJ6f5znG47ELlNBfgB4CAFx3Ay05YBAgDEO3LvUiUJ8FzmE8HiNNUzzzzDNot9tHnm9flVFVMqJYFhy408CBwWB4eFDWAYQBULe/ZYPBYDCsgCmAdAZEAdBY8m/HDEA+W/w+AER3YTSYl8BM/v9dAs3fGKLxqfQOBzTcK5yaMeCy34mTEpZVAgW1Wg3j8RiDwcBli0k0WQ+u5JV15b67u2bolSj7xFd7w/M6GhAgGIRgdhu4bQzIeTBLzrmoWR9b0KmRoCoBdBzOnTXyk8lkLjPOYzkGSXFRFCiKwmXbfTWBmutpoIME2W9HqPeXARcl/KpaIPmO49gpApIkmSPtX/va13D9+nUMh0PEcYzxeIwwDDEajVAUhZPznzlzBu12G3Ecu2tz3jToYzlAHMdotVrOTJIlF3pP/OCVr2DQZ4TBFSo5WAqws7ODp556aulzverfggUADIbHG9MPtJD+qbOYbT6wCj6DwWAwPEKofylD98evIP+RDYy/q7/wuNrrOdp/6zowXSAdqAdI/v3zmL0nOvkkSqD1X9xA/fPzhL92c7LgBMNp4lT+R7GIjFTJ+09yznHy6TAMsb29PddjXuXqVd0AlPgrgfbr1pettYr0+n4Bem1fMu4b9KkxIDP/2kZQCb0/D7/tnt/K0N8HGumR/KsZHwMADALo3H3Z/zKVhx8M0Fp7v8RBvQV0fJLp0WiEJEmcEeBoNMJgMMB4PEYURa5lIGv3dc4MiGhQhNfU+WlGXstE/KCO7pXeS1VZ0NCRbQ5XwSp/F8vOM08Ag+HRRNkApi/FmLy3hdmlQ0UTJiXqX86B4t2OK083UW5ZcOAkqL1ZoPbWGMFx2S+DwWB4RBHkJepvjlH/Uo7ZhRTTFyNgAtRfnZfd17+Wo3alQLDg47CsA43PZpgOTv55GZQl6q/nqL85vpMlGO4zTq07wDLCXiV/rhoDWEwuq8ZeX1/Hd3/3d+Pzn/88vvKVryDLMiev1/E0666SeF8WD8yTQiWOvPZkMpkjkirDJ/wxtO2cZvyVFKsagFnlJEkwHo+RZZkzBmRpAIA5I0KOo7/7AQ4GSkajkTuOSgRK48MwdHXyVFGo5J0BAl2vXksVFSTUw+HQEXJK8TkWpfMk9tzzLMuwv7/vavlbrZZTCiRJgrIssb29jU6ng/X1dXePuN8k4lmWHTE81PupKg/OsSiKOQ8HVTPoGFQFqGdAlmVIkgSDweDI8+P/LXAsv3xmlfIa/z2DwfDooezUkfzFCyjP3v5cD5IZ2j91DcH1w8+s7M+cQ/G9i7M8hqMI//t9hL+4j8A+Hg0Gw2OO6Bf3Ef7qAYZ/+xKCwRSd//Ctw1IBwbLPwmAKxH/vxh1f3z5nH16ciieAfq96reo7yeKyWuhl19OfSbJJIkmqlUxpqzdCs+U+SGT913is3+JPyZ3W7bO+3S8hYD25OuzrNYMgcMQ4z3N0Oh1X/65KAmatdW3qHUAST2LM8gVVHfA8BhEY6PDN9kjclTQzsLFImcBxdW9ooMhAQ5qm2Nvbc+NFUYSyLBHHMc6cOYPZbObKAbgnCpXoUwXAzgBpms6RcT4rDGZoecdkMjnSDlDX7u85FQ2NRsONu7+/j263i/e///1ot9tHnu1Vg11V5+hzeNKSAoPB8JCihqPuzqX+x8r+h3VilKX9x9RgMDwZKAEUJaJ/sIugKIHpyYm5fV4+nngoNYT3o5ZZM7Yq+Sf8DLwS7+Nk7prV1nMJzc77x6nsXd+vCgL4MnTWsbNFoPa051hKuKvWBtwOkvB6WnKgQQCOwSCABjO4DwwU+NfQ+fgklfvONTIYAcB5ARwcHMzJ9QE4w0dedzAYYGdn50hLQi214LyKokCe586TgQEWLU/QoIoqOqoCU1q2oHvIL96ng4MDnDlzBtvb29UP6j2AEX+D4fFHWQMQBijNLNBgMBgMSxBMgfBXBg96GoaHDA9lEGAVErMsUOBL9F988UU8/fTTePPNN7G/v49+v49arYY4jufa5VUR+clk4kjhbDabUwz4gQNtKUhyyd7zQRA49QHr0MuydM74SpBJYrXO3A9E1Go1dLvdOUf7KmKqhJUZfyW9bEGomXvfiFDVDByH4wOHARQ12eO++6Rd99cPIPhKCZLwer2OXq+HTqdzpJ1jq9VCv99HFEVOAcDACgMYmsHX/U+SxHkKqGqDnQgo32fAiOtga0LuFe8vr8V9qdfraLVabn23bt3C3t4e3njjDTQajcogwJ0Ev1b9OzAYDI8Xpu9vIf3TZ1GaWaDBYDAYDIYT4oEYA1aRk3tBWKrGCIJDh/lms4ksyxwBjKIIzWZz7lwl3BoU8E3j1LxOW+75wQetYVc3el+Or3MAcOQYEnY/e84sNYC5tn1axuDXlletT6+hJNpvA+iXa1S9xgCGXy5Rde2q++cfz3WFYTjXvQCAc92nxwMDLTzev8fcW9b1q/pBgxD+/vEe8XUGBtQLwPeS4FgMIu3t7WE0GqHX67kuBYue2UWv6xyPk/tbAMBgeDxRNgJMX4oxu9DE7JnwaKmAYSGCwRS1rxWo7UyPP9hgMBgMhscYp94icBE5UXKzCoFZVhu96Nzr168jTVM0Gg2sra05RQCAI9J/n7gr8fZ9BLRHPOXwYRgiz/O5zD8z8Uo8qzL9fF1d69nrnlJzEuDZbIYoiubO5fjqVq91/sx4A5gLVHBNau7HrDv3dRFh1TkTvJ6+zy89hlB1AK/DPeX6+T5bOTJjn6YpZrMZer2eUw5sbW2h3W7PqTVYBpCmqWuD6Lv0q/TfDwxxPvzdLx1Qw0CWMezt7eHVV19Fs9nEd3zHd8wZNOrzrgGkVZ7vRcE1CwAYDI8x2jUkf+nC4c/2Z34i1L+Qo/033l7ogm0wGAwGw5OCU+sOQCwjJ6uSnJNek2O+8sorODg4wI0bNxzx63a7Rwz+OAYDAMBtl/w4jh0BVNm5knqV0KsUXqEZ/EXkmhlruvaTlLJ9H4MPOrbOQwMBVYZ2ukaVxOuYvhrAP0avpWRWa/39OdJPwC810Oy6r4rQNfBeMDBAEh5FETY3N9Hr9dBqtVyLQB5DQ8Asy1y5RtWaqzLwOg8eo+ULegy9GkajEfb393FwcIBLly6h1+tVmkn6WPWZX6QK8M83GAyPGY7+k2VYCSUCEwEYDAaDwXB63QHu9txF8mg9blFGlQTyhRdewK1bt/D666+7jHccx45M+lAyyjZvKkvXIIBmzBkgWETulSgzCOArAQA4kzoa5fnydH+PeE5VEEAd633SXSWH55eSXZ8o++UNfF39EqrW7o+txopUE6gSgNehVwHJfRiGc54LbF/Y7XbRarUQhqG7D1pK4AcBlsEPduie631T5UiSJEjTFDdu3MBgMMBoNMLXf/3XY2tra27cZcqKZc++T/z190UBMIPB8CiiRFCUKMcl0LS/4ztGCWBcHn4ZDAaDwWA4PSWAflcsIjc+wffPrSL7q5CftbU1fOd3fid2dnawt7eHOI4RRZHLrquUXg3wmH3mtVgGQGk3M/R6XX88JcUaCOAaNPtO0Mmevemrugj4BFr3E5jvTqDvE+o3AMAR69ls5gwHfbJb5XEA3G4j6N9X/4vzKIrCjT8ajVzGniUJulcMuNBMUf0aWq2WC/ZQrs9AQRRFGA6HSJIEt27dcqaAen/9dXEPWG7AsXU9DEzw+WD2/+rVqxgMBrh16xbe85734Fu/9VvR7XaPPL8cq+rZXqZKqDrex6LzDQbDo4NgOEP7J97G5CMdZH/izIOezqOLdIb2f3IN9SvFg56JwWAwGAwPBU7NVtgvCTgu21kVDFgmi17l2iSG6+vrGA6Hc4TYJ+OarVaS7NeP+xn1Krm3BgF0vKpr+mslKWV2nFltfy5V3gJ63Elk6Epylfwf96XH6TUWqRP02Cq5/SL4e67rW1SOUBQF0jRFmqbOINLvUOCP76+7KoijXRQmkwnSNEWSJMiyzHVuWF9fX7iWKgl/1XwWSf+rxltWQmAwGB4dBFOgfmWM2aXxg57KI4va1TFqV8eov5abIaDBYDAYDO/i1MoB/Gz9Kln7ReoBfe9O5gIctvDb399HkiRHAgy8nhrqkXyPx+M5klmr1VzmWDPRlKEz6z2dTuf6zXMM35DQB8dNkgRhGM45y5P8anCBRNXvPkAjPWbXVb7OvVHFAOErB/zgANej73FdOoYSdj94oN4LzPb7Mn49T+dEMs+5qGKAioA0TbG3t4fd3V3s7u66rgCLAiF+AIHXpipCFQAsJSmKAqPRCLdu3cJwOESe524Nd4KqgNgqgYLjjjMYDIYnCdF/t4vmLx+YF4DBYDAYDIIHogS403MWEZ2qgMCyIEFZlsjzHAcHB9jZ2cF4PMba2pojygAcafcN9VSi7tfbk3gyMKAdAUiKtV+9zqcqg67vMfigzv1KUDXAwOv4En5tdUhiXRXU0MCNknlfxaDH+Vn1RT/rvDlmVfZaX+N8tf2gH0BQvwD6AbA933A4xN7enlN/qILCl9UziKOlF/rM8f6plwJbAO7t7WF/fx95niMMQ7z00ks4f/585TPIa9/J38UyZYCpAAyGxw+1NwpEP3ML4491MXshOv4EA2pvFGj+2gD1L2UWADAYDAaDwcOpBQHuBneS4Vx2bBAELnO7s7OD6XTqnNubzeacIaBm10kC+bNPfElEgdvZb82Cczx2EwBwhKjzZ1/Wz9r56XQ6F2jQY0mw/Rp/HlcVBGCZgZoFVpUpqIJBZfH+OVXz94m2T2A5Xr1eX1gWoISf6/C9CGq1GuI4dkGALMucDwBVH1RW+HuvzxiVHLon+izwPtNosCgK7O/vu04AfJ7e9773zbUDvBc4LuNvwQCD4fFD/c0x6j+7i9l204IAK6L21hjx/3v3QU/DYDAYDIaHEg9dEKCKUALVbc+0VMAvHfB/9sd/6aWX8NRTT+FTn/oUrl+/7trKxXHsyCWz+2EYHmn1p5J3Je/MNOd57hzoq0gwze2oPADgatXzPAdw27CvVqs58qrEmS0C1dCO11DyqT/73gGLiL2/h6qKWNTCT6HX0eM5f52T+h/ozz5ZH4/Hc+dqTX673UYcx+h0Om6Ou7u7GA6HuHXrliPriwIM/nPid2Bgxp9jF0WB8XiMnZ0dJEmCnZ0dZFmGRqOBj3zkI9jY2KjsjnAcqp5jfX3Rc71sLIPBYDAYDAaDwWAgHqogQBVpOU7mv+z4ZZlS9pGfTqdI0xSj0WiOlKtEnrXlJLR+plznRuk/gwEqnVcpvWaVOZ5m6v01k+BTaq4u+UC1MaBPzP33AczNSUsbFsn0q8bjMb4CgfuopQlaRlAVnOHx2rbQn7tej10bwjB0+8H9T5IESZIgz/M5D4Cq/dX5ct0+Idfyj6IokGUZRqORMwHk8Wtra1hbW6vcM39vFr120uda92XZMQaD4dFF7doEtVdzzJ4JrWXgIkxL1L5WoPa2dQIwGAwGg2ERHqoggBIu/k4sIqMnyXZWkSSWBVy7dg3T6dS1/WO22Zf3q5GgtocjafTl/2oOp54B/M4ggCoEdBx+cV+yLHPv61yriLhPnDULTnWDkn8/Y895VqkwAMwpD2iax/EYLFGVge8FwNdI0NUwEZhXA6jiQBUa7Xbb+QBQnUHp//Xr151b/6KgC7+0DICBIO5fVTeDwWCAg4MD7O/vHympuN9YFCgy4m8wPN6I/tsdhP90H8O/fQnluYfqn++HBsFwhs5/dBXBjaPtcA0Gg8FgMBzigf4vYpHkueq4VTKky87zf+a5L7/8MnZ3d/HWW28hTVOMx2NEUeRqvklS6ShPZ3qVtdNV369fJ6lW0z7faJCZdz0mjmPXcYCKAiXcRVGgXq+jKAo0m03nMaDX00CG7wlAws3xqkz9mI3nd/oHaGDAL5HQ7Ln6I/A6mmHn8drGUAk3Axt6XNX6NLDCDH2SJM6hnwRdCT7nnuc5xuOxM0f0OztwXpwTAwicH40I6/U6JpMJNjc30ev1XAeHRc/fSXASdYz/3WAwPF4IpgBGM0Q/t4fpyxHGH+8B9qfu0PiXIzQ+nyE4mJkZoMFgMBgMS/DAggCrkJuq1/3zViU8VWQsCAK8973vxa1bt/Daa68hz3NHsJvN5lw2noScdek6HtvE+dltEkg6+ivB9IMARK1WQ6vVcgaAaZo6eTuvwdr0orgtd1S3ekLbFKp3AOfE8bQMgPPnXPg7jQkBoN1uzykQ/Gw5SxV4fc20E+pjoIEIv2SB73EP/FIA3VN6MWgQgIEMBgziOHa/+8+DHqeKBl0Xs/3ajaDRaKAoCpw/fx6XLl2qDG75WFaasIr0fxHu9O/DYDA8GgjyEtHP7WH8TW2MP9YF6gFwcvuRxwszALMSzV8fIvyfBg96NgaDwWAwPPR4YEGAVeqaVz3vJPLoqtf6/T6+53u+B9euXcPbb7+NZrOJbreLKIrmzN0YCCBIClX6zmtrDbpPOpdJ5cvysB99s9l0kn2WG6gyAQCGwyGiKEKn03FjqaSfRJV7EUXRHIkmGOioMrIjuaapHgC3L8y+M1gCYC7IkaYp8jzHzZs3Hbnu9/vO04B7UWUsqERcSToJuWbtGRBJ0xS7u7vY39/HcDh0+8z9rCq9AOCCKT55ZuBBlRplWTqTQQZqOp0Otre3EUWRG6dKvbKI+B/3Ht8/LkhmJQIGw5ODxucydP7im8h/ZBOTj3Ue9HQeKOqfSRH/1zdRuzp+0FMxGAwGg+GRwENXVHhS0rKKesCHT46azSbOnj2LW7duYTAYOJNAv4Z/Npsdqb9f1AJO69cX1epXmd/p/EmcZ7MZGo2GI9s8l4qA8Xjs5qr17pyHtif0zfuqstRKlAm/HaEf9OBrOj6VE3meO9NFzpmEXufnk1mSaZ2XtkFUYj4ej11LQJJ0vU9Va9f3/H2oui73kyoPDfL0er2lGXyV6t9Jtv4kz/OqYxoMhkcXwWiGxhdzTL6SYbbdwOzpJ9AscFqidmWM+pczNL6YP+jZGAwGg8HwyODUggDLiMoqXgD8HThZoOAkZQdJkuDGjRsuY/3UU0+h3W6j3W67LDLLAQA4N3qtHyfJIwlnoIDZaD/7raSYc1NpPv0GWq0WxuMx0jR112ILwtlshk6ngyiKXHZ7Mpk4j4OiKNBoNNDr9ebUCyTTSqq15l9LBZSo+z4IJPi6DvonzGYzhGHozvPLErSLgrZL1GN4jvomaH3/bDbD/v4+Dg4OcOPGDaRp6vwS1DuAc9bx/VIGPjOqpqCKgMqALMtcQChJEqdqWFXBsizbv+x9PU7/blZVvBgMhscP0X+3i/CfHGD0nz2N2Xbz+BMeIwSDGTo/8TaCW2YCaDAYDAbDSXDfgwDLiIq+7/8MVPdI1/N4jJIi/7yq61WNDQDnz5/HBz/4QbzzzjvY29tDGIbodDrIsswRTs0u+9lwJbg+oVyUaabcHMCccWBVIMFvT6iGf1QGdLvdubkpmVfZPksKtMMAAwR+xprrImFP09T5Cmg7xKo9r9fraLfbR4g/ibN/L5SUA/OBFZ6j82SJxnA4RJIkrmxBlRr65e+/X4qgJozce77OwIY+h2fPnnWdCVbJyFcdt0j5sAiL5P/LrmswGB5PBFMAyQzhL+yj7FUr0wBg8qEWpi/Hpzex00AJYFwisBiAwWAwGAwnwn0PAqyaHV127HGZzkWkaJUMqf5+8eJFbG9v4xd/8Rexu7uLIAiQJAnSNEW323UZYV9WDmAuAKCE2M+k++eozJ6EXOvlOUcGCHgecJuwkpwy+61+AnreeDx2c6ECAQDiOEa9XncZe47LoAPnQuPEdruN6XSKTqfjrs01UClRq9WcaR6N8+jWT98Drs1XHHCeVcETv66fZQCDwQBJkiDPczduVUtGwlcBEL4PANULfF0DMbVaDRcuXHDdAKpw0iz9ccT+uGNWGcdgMDxeCIoS0T/cW3pM2tjC9IXofs0A8OMPJQ4N+1AuP+6kKAHM3h1zev9bshoMBoPB8DjioS4HOOl49wJBEOBjH/sYdnZ28MlPfnKOELMvvZJsZp21DICGcT4xJonTTDOvye8qe/cVECSlJMlKaouicBn5ZrPpCDjJPcfnmCTTwG1VAAm6dkBgu8I8zzEYDDAcDjGbzdBqtdDv9wHME+rJZOICEdyDnZ0dpGmK0WiEOI4RhiG2trYWdhhQc0Ou2yfwVCQcHBwgSRIcHBw4FQADDwyqcG3+nnGNqhBgJ4gwDOfmQvl/EASuHWCr1XJ7u+x5XKZ2OQlWOc8UAAaDoQrRz++j+S9H92Xs2XYT6Y+dA0IJzr8zQfvvXgdyUVqdbSD9c+eB+M4/oxr/OkH03+wc/jIpERxYL0CDwWAwGE6KUwsCHBcAOM4X4G7IzaJyAX1P57m5uYl6ve5q6EmEWVvvE8kqyb+/Ni0TqAoCqBeA3zZQ560BAl9xUJaHzvUkvPQI0FIGfyzgtqJAgxa8DjP9aZoiyzKkaYp2u+0MCf3rcywaKdK7gCoClfHrnvi1+ZwnSyM0+89AC9sBsgyAwQz1NvC7LxxXUlL17PjlHdwflgHoM7XsWVv0zC16bdF4y/4WLABgMBiqULs+Qe36/dHNT/enqH+1QClBgNq1MeqfyxBoEOBcA/Wv5ijj1Xoalt0ayjMNBO9MECTvGty+mqPxuezeLsBgMBgMhicMD7w7QJWU3yc5VXXSiwjTovf09VUCEGwbSPzO7/wO9vf3UZaHJnokwiTKem0Sef/aVA4At7PuPF5r/n0FAEGJPUlwURRzmeyyLFEUhXPkj6IIYRgijuMjHgEazKBfgBrv8bgkSTAajfDWW285or2xsXFkbzkHnQ+JfhActies1+vuO4MLvH5ZlnNjcD9pzBfHsTP2Ozg4QJZlODg4wGg0Qp7nc+oFnqP3W2X8/O5L/IMgOKJiGI/HcwGToihw7do1hGFYuQ9Vz/OyEpRF99p/3R+v6m/EAgAGg+FBoPb2GJ2/9Ob8i+VhmYIiuDFB56+8tfK44+/oIf2z5xD/1zdvqxhmVgJgMBgMBsPd4oEEAY4jLFWkSY3qVj2P11p0XBXBUpB0lmWJCxcuoN1u4+rVq67VHeXsSvg1A805+2Z7fmZbv3TOqjjwzwHgCLb/pW74i1oY6hi8Hsk/gxVlWSJNU2cEyDmp4Z5vhAjAGRXynDAMXZcAXkMz63pflXBrsGI2myHLMkynUwyHQ+R57roAaIcBBmD89ou+kaNeS6/nPw+6T/RO2N7eRrfbrdxX/34d95ofjOJri57Jquf5XpUbGAwGw50gKDEn+7/b44j6qznCf7iH+leLOUWBwWAwGAyGu8OpBAGqJPd3InNW4riM9PikctF7JyFMzzzzDA4ODvD666+j2WyiKApEUXSkDICmfuoXoOTUDwzwS80GNQjgk3U9xw8o1Go1R/5ZCuAb6fnBBjUzZNAgCG5L7mmMqF4CPM6v5+eY+lqtVnOGgzpnNRP077O2KWQghq35iqJw9f9pmrp56rPBkgTtElC1x9oW0YfeA5ZvxHGMZrOJ9fX1hc/JSUl41bN6p0Ey/95aMMBgMDzKqH85R+vL+YOehsFgMBgMjx1OJQjgk/5VZM5VMulVpNb+OMSy8RbN2Ue73cZHP/pR7Ozs4MaNG4iiyGWHSdJrtZoz5lOHfeC2od10OnXkM4qiOdKrZNUvb9CsdqPRWNjejuOFYegMDLkHSsJZrz8ej10dvz+XOI4RRRF6vZ6r7WeAg+eRcOsceQ1/L/U4n4D7awHgWgDmee78DvI8r7yu7jPf88f3gxQA5tQSfJ2O/0VRoNPpzJkMroJFz2XVa1VBslXHXVROYAEAg8FgMBgMBoPBUIVTNQZclLWven8ZkT+u9r/qPT/LvkiN4M9NX2s0Gjhz5gxGoxGSJHEu8prp14x81VqUhAK3ywdIvPmaP1+dj2awSVp5nDr189pV62KdPGvimZnnmByf5LfVas21R/TLADQIQvgu/zyOe+nfn6p5jsdj1wbQJ/9+4MGHrzTwAwCqytA56H2jv0AURUeeiaqfq+ay6Dlb5ZzjcJyCxmAwGAwGg8FgMBgUp9oiUL+vkgFd9HtVYGBVHKcsOO4cAMiyDDdv3sTa2hqCIEC3250jdmVZOiUADf+UWFNGr3X2JMVBcLRlnU/0GWDQ9oVKxsfjMdI0BQDXss9fg9bRaytBBiQIvtZsNt08fCk/76UfGOA1/Oy/7jvXUZblnAKBwYk8zzGZTOaM/zQIUaXuqOoMoEScbQD5uq6fpoB5nqPRaKDf7y98Rqt+9pUs+t6ywNRJMvka2FgURDAYDAaDwWAwGAyGKtz3IEBVlt3PDp/0fMVxBGgV1QCPW5VMra+v48UXX8RkMsHBwcGcpF/b/6kiwJemkxhXmdipYkBJNN9TortIXcE2dlqbryoCkmQ9V40B/bIBkn8l335mXdsMqiSfe6KZdgYaWHPPIAmvz2tpK0E/eODL+NUTwZfu8xzuF4MdGoApyxJ5nqMsS7TbbRc8OUnQaZmSxUeVEqAqiLDs+GXjGgwGg8FgMBgMBoOP+x4EUBm0vqbfl5GWZeUDx+EkZKjquEXnnj9/HufOncNv/dZvYXd3F2tra64dHzPNwG2pP4MAHLNWq7lMtGbzNRPOcaoy3hoEADBXG+8T8slkMpfhJ7FlcILlDDxXFQUk4bwm2/otCgJooEBl+xoY4ViqClD1QFUnBb/d4qLjFgUBNPjA67DtYLPZdIGIJEmQJAmKosDGxsaREoBFwatlhH3Z+1XvLVOnrBJQWBZEMBgMBoPBYDAYDIZTUQIsCgQsIirHERr/tUU/3w0JWkbc+Porr7yCJElw5coV9Ho9tFotxHGM6XTq2uoxC6+KAFUBKGlXUkzJOqFO/Poaj6d8Xgm1GvcxaMC6fpJfDTxU1dprJwCuhWPS+E/XwGtqzb0fBKi6Z4QGB/i+30nBfxY0KLLIo4HzGAwG7vVWq4UwDF2ngZs3b+Lpp5/G008/jWazeWSexz1vikVlA/4xWqqwDMf9rejfmAUADAaDwWAwGAwGwyI8kBaBxKpy56oAwLL3j5vDnWZN/fPX19cRRRHefvttR7ABuJryqsyxnwWvInDats8nvr6hncro/fVqDT8d/ak4IKHXsoCq7gXqVaBjcy7+/dB16Hp9/wANaOj5XJOeq3vm3wu+p8EKvUc8j4ELdhhQlYS+32w20el0jlyn6jmoev84pUrVM+7v7UlUAKs8+waDwWAwGAwGg8FAnEo5gMInOYsy9ycpEViGVQj+IrXBovP1+DiO8aEPfWiO2DETPh6PF7azo0RfzetIxFkHP51OXeae5N+vr/cDDep0z3F9wz6//p7feS1VHfhyfyoASJz98zm+7r+WFPC1oiiOKCA4jrYO9OegzwqvyQCMf/+0DIItBnd3d5EkCYbDIYDDsoBPfOIT6Ha7mM1mR7wEVq3rX3TsIsWDznPZ73dyHYPBYDAYDAaDwWBYhAeqBABWy3CeRC59XGnAoqDDqvOrUiH47e4AoNVquYw7SXVRFHNjaL27EnrfDLBKHcDXfSm9n2lmYMG/hg+ep8EAP2Ot8/Wz+PyumXh+qZpAx9PAhK7B747AYwnfO4HBBJ6r+8NAzGAwQJZlOHfunOs6ABwGTaIoOtIVwd9T/uzvV5VKZdFrd0PSV7mOPzeDwWAwGAwGg8Fg8HFqngDEnZCTk0j1j7vW3ZKjVc6v1Wro9XrOF8DPZmutPLPyjUZjLgjAa/nE2yfdPpGu2gclt77JnioHtK7eVwr4igKV9evcVA3glzRo2YLK/v3yAv89bYHIczmO+iqQyPN6VFWMRiPs7u6iKAp8y7d8C9rt9rH3UHGn8nx97W6IeVVga9lYFgAwGAwGg8FgMBgMi3Dq5QCr4Djpc9Vxd4p7La3Wc8MwRL/fx61bt5BlGeI4nmslSCM9El8SWpJgvq7jNhoNV1pAJ34l4xpA8BUBVfX2NAhUfwC9pmI6naIoCiRJ4swFKcdfpAzQ8fi6ElnfH8Afg4Sfcn9fScDfqV4AgKIoMB6PsbOzgyRJsLe3hxdffBHb29vO8X/ZfVv0O/et6rWTqFWOw6JnUq9v2X6DwWAwGAwGg8FwJziVcgAfVYRGf19Gqu7EQ6Dq/WUZ1arjjgtG8Dw/A6+Z9PF47IgzSbkvu1dpu2bp/fmqqmDR/KuCAPq61tTrXHRNujYGHvI8RxAEcwEMfy/0PL7vqxAWlSb4Enw/oOEHEvT1yWSCNE2R57nrmDCdTtHtdrG1teWOO+5Z8Y+7W1XJokBT1fN13HO97LVVA2gGg8FgMBgMBoPhycSpBgGqiOxxJMV/v+rcuxln0RyrggSLrnNcsOL8+fNIkgT/4l/8C9TrdfR6PXS7XURRhF6v566zv7+PNE2RpqlTEZCYqyRe6+9V+s4AAufk7w+z/Sqb9+vg/Zp/XR/r6w8ODlwWvt/vY21trdILwN87lfbzuwYGNDiiAQ7/PnDeagaYJImr/d/Z2cF0OsUnPvEJtFqtuTKFRffLH9/fg3uNVQJe/ryqXjvpuQaDwWAwGAwGg+HJxql6Aiwj7ceR/VW8BU4it+YYi0j/qkGDRfDHCcMQ29vbqNVqaLVaiOMYQRDg1q1bAA4J/cHBAbIsw3g8RqvVQrvdnpPp+9L/ReZ9PnnVzL/fmlDPqSK9+h6z6sywJ0mCZrOJMAwRRdFcGYGWJfjjqIpBJf/80rksC9ZMJhNMJhOMx2Ps7+8jDEOcO3cOnU4Hs9kMcRwjDEN3vH6/E9WIfucYfmnDqs/fSa5/kvFWUQ0YDAaDwWAwGAyGJxcPxBPAJyzLSMoqBGaVcfzjVy1BWPW1464XhiE+8IEPzL2epik+85nPYDqdIooiDIdDJ7GfTCbodrvOpI8EezKZuDGVyFe11PPr8v1zgHljvUV7wgAASTeJ92AwmAtSNJtNd462RPTd/PV6GpygZ4GqA/ysPH+n6uHg4ABJkuD69eu4ePEiPvKRj6z0zB13v1b5vuznVcbX348rPVh1rJO+bzAYDAaDwWAwGJ4sPJBygEW/8zWgmhjdSRZ30WtVqoRVpf7+3O40cxuGIT784Q+7bPhkMnFr3N/fxxtvvIH19XW0221nKqiy9qryAJXl+8TeDxT466uqtef7RVE4wz0el2WZI/hRFLk1cVx/bBJ3/lx1n/w18RwGH2azGfI8x/r6Op555hmnSnjxxRfRarUW7rX/+7Ka/EXP4CJVin+dZWMvmpc+3/qazsefk38PF63FAgEGg8FgMBgMBoOBOJVyAOAoKVyEKjKk791r3OmYvhTcx7KABV+r1+s4d+5c5blBEOCrX/2qI8FFUbhsu7bv86+jJn30CdA2ff78tBOBEm8GE/i6qgB0/MlkgqIoXOZ/0b0j8a8KTGh2X4+hooDzVGJbr9fR7XYr93hZYKcqq7+MNJ8kMLTqNZbNuWoux62h6vVlz6bBYDAYDAaDwWB4cnFq5QB+dtV/ryqbWYVFWdFFx6oMfVFGWOeyaD6LsEzdsEy9cBzxPHfuHD7xiU+gVquhKAr8+q//OqbTKVqtFjqdDuI4RrfbRaPRQLPZnBtbAwQk8L7sX/eGfgN6jhL02WyGJEncV61Wcxn/MAzn1AfMzE8mk7k1aftDPR84NBycTCbODyHLMhRF4QIMFy9exAc+8IE5lYAGO/jaovvoPzM+fNK86N5UBVGOewZ9rDrP457B49QAVeMYDAaDwWAwGAwGw6mWA/jkuIpILcpyAqvJrKvgBxSOy8oelwn2CeOqgYBF1/DXBsxL+wFge3sb0+kUYRgijmM0m020Wi1Xkz8cDpGmKcbjsRs/DEM0Go05PwDO18/MVxFlknoA2NraQrvdxvr6+tyxLBPQdojqYUAwwKDeBtPpFOPxGGmaAgDOnDmDsjxspTgej53SYHNzc64MgnNbtp+691V7XXXecQGbRc/NsmDWomP1mKr3ls192d/JoufVYDAYDAaDwWAwGIBT7A6wiESdJKO6SmBAX1tlnONUBIvOXybVPo6gVpHNZcSz0Wi4TPiiNe7s7ODGjRsYDAZO/r+2toZOp4N+v+9IOsk/ZfZVcyVRn81mKIoCURTh8uXLlcTzrbfewptvvolmszkXcOD5Oqa+zlaIw+EQw+EQzWYTH/zgB+fMBf39XPT8LAsKVZH8qv32r1V13HEkfZXnatHYOr+TBqV4rmX8DQaDwWAwGAwGw3E4VSUAME/EFhGuZcR+WXZUx+DPi8jRMlXBsuzxcUqFqnVUjbkKoVz2mn/98+fPY21tzSkBAODKlSt4++23kec5oihCp9NBvV5Ho9FwX/1+381vd3cXQRBgY2NjjrArgfevu7m5iTiOcfPmTYxGI9fNQIMJwO3MPzsKPP/88+71yWTiTA+r7kXVPlcpLZbdG//1ZddYtXTkuKDTSQJT/loW/Z2ssjZ/jqYEMBgMBoPBYDAYDMSplwOsQvAXZWn9MVYdb9k1VgkeHEfu/TlWraPq2ouCF/54VWP6pLLT6aDT6cy9d+PGDUeyG42Gk+Mz2x6GITqdDoLgsO5/OBwiCAL32jJyy/m1Wi3EcYzd3V3X3rAsDw39NFPP46lAoDrB35sqEnwcoV1E7qt+919bpk7xX/OVB8ddf1kGf9EzteiZWWUd/nhV1zUYDAaDwWAwGAxPNk7NGFCxSAGwLGtZRWqqMrj68ypke1nWfxUsIupVa/SzycvmtyhosUr5BN975ZVX8OKLL855AiwipkEQzHUqOK4cQucCAJcvX3bnXLlyBV/5ylfmzr948SJefPFFVyKgAQD/+3HBh0Wvrxpc0WNWyfAvuj/+fhx3PcVxgYpVM/lVwYNl1zIYDAaDwWAwGAxPNk69HEBJVBVRP454+j/rayeR41eNtYhQLSJox63Tz26vciyvuexaq2SEAVR2DtDjfXKrRoQnQRAEc8Z93W4X586dm5vn2traEXM/ne8qRHqVoMSye3Pc/a0KBixTFhz3nBw39+OeeT/gU3XucdeyUgCDwWAwGAwGg8GgOPUgAHE3suWqLO5JJd6Ljqu6xrI5LMs6r5Ldrrr2SY5btoZVxiCWyc6rjlt2rbNnz+LMmTOVwY3jAirLlBl+YGVV8rxsvlV7t8o1VhnbX9Nxe7HKvVy0tkVlEqYCMBgMBoPBYDAYDIra8YfcX9wJUSEB8jPmvrqgSh0AHFUh6Gs63nFzWOW4quOXkbvjXls07t1mfJfJ3auOO8l4/t5WYVnWW/dsFULvH++XiZxk7oveW/T+quOtovBYNMai57tqnwwGg8FgMBgMBoNB8UCCAJq9919bdrz+7JMefU1xHKn0X1927ZPguPr1Zddepo5YRKjvhPQdl0VeBauSan/PV/FvuFusWmqgz+PDJJ+v+jsxGAwGg8FgMBgMhrtBUBrDMBgMBoPBYDAYDAaD4YnAAy8HMBgMBoPBYDAYDAaDwXA6sCCAwWAwGAwGg8FgMBgMTwgsCGAwGAwGg8FgMBgMBsMTAgsCGAwGg8FgMBgMBoPB8ITAggAGg8FgMBgMBoPBYDA8IbAggMFgMBgMBoPBYDAYDE8ILAhgMBgMBoPBYDAYDAbDEwILAhgMBoPBYDAYDAaDwfCEwIIABoPBYDAYDAaDwWAwPCH4/wODteXvoZ1vrwAAAABJRU5ErkJggg==\n"},"metadata":{}}],"execution_count":60},{"cell_type":"code","source":"import numpy as np\n\ndef region_dice_numpy(pred, gt):\n    \"\"\"\n    pred, gt: (X,Y,Z) int labels in [0..3] after remap\n    Regions:\n      WT: {1,2,3}\n      TC: {1,3}\n      ET: {3}\n    \"\"\"\n    def dice(a, b, eps=1e-8):\n        a = a.astype(bool); b = b.astype(bool)\n        inter = np.logical_and(a, b).sum()\n        return (2*inter + eps) / (a.sum() + b.sum() + eps)\n\n    wt_p = pred != 0\n    wt_g = gt != 0\n\n    tc_p = np.logical_or(pred == 1, pred == 3)\n    tc_g = np.logical_or(gt == 1, gt == 3)\n\n    et_p = pred == 3\n    et_g = gt == 3\n\n    d_wt = dice(wt_p, wt_g)\n    d_tc = dice(tc_p, tc_g)\n    d_et = dice(et_p, et_g)\n    mean = (d_wt + d_tc + d_et) / 3.0\n    return {\"WT\": d_wt, \"TC\": d_tc, \"ET\": d_et, \"Mean\": mean}\n\ndef eval_full_volume(model, case_dirs, max_cases=10, min_et_size=50):\n    results = []\n    for i, case_dir in enumerate(case_dirs[:max_cases]):\n        pid = os.path.basename(case_dir)\n\n        imgs_dict = load_case_arrays(case_dir)\n        x_np, y_np, meta = preprocess_case(imgs_dict, do_crop=True)\n        x_t = torch.from_numpy(x_np[None]).float()\n\n        pred = sliding_window_inference(\n            model, x_t, patch_size=PATCH_SIZE, overlap=0.5, num_classes=4, device=device\n        )\n        pred_pp = postprocess_et(pred, min_et_size=min_et_size)\n\n        m = region_dice_numpy(pred_pp, y_np)\n        results.append((pid, m))\n        print(f\"[{i+1}/{max_cases}] {pid} | WT={m['WT']:.4f} TC={m['TC']:.4f} ET={m['ET']:.4f} Mean={m['Mean']:.4f}\")\n\n    # aggregate\n    if len(results) == 0:\n        return None\n\n    avg = {\"WT\":0.0,\"TC\":0.0,\"ET\":0.0,\"Mean\":0.0}\n    for _, m in results:\n        for k in avg:\n            avg[k] += m[k]\n    for k in avg:\n        avg[k] /= len(results)\n\n    print(\"----\")\n    print(f\"AVG on {len(results)} cases | WT={avg['WT']:.4f} TC={avg['TC']:.4f} ET={avg['ET']:.4f} Mean={avg['Mean']:.4f}\")\n    return results, avg\n\n# run on a subset first (speed)\n_ = eval_full_volume(model, val_dirs, max_cases=5, min_et_size=50)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:29:25.536411Z","iopub.execute_input":"2026-02-03T22:29:25.53667Z","iopub.status.idle":"2026-02-03T22:29:52.436149Z","shell.execute_reply.started":"2026-02-03T22:29:25.536637Z","shell.execute_reply":"2026-02-03T22:29:52.435491Z"}},"outputs":[{"name":"stdout","text":"[1/5] BraTS2021_01605 | WT=0.7032 TC=0.2042 ET=0.3382 Mean=0.4152\n[2/5] BraTS2021_00651 | WT=0.8636 TC=0.8727 ET=0.8017 Mean=0.8460\n[3/5] BraTS2021_01125 | WT=0.9425 TC=0.9315 ET=0.9154 Mean=0.9298\n[4/5] BraTS2021_00026 | WT=0.8924 TC=0.9159 ET=0.9009 Mean=0.9031\n[5/5] BraTS2021_00231 | WT=0.9250 TC=0.8708 ET=0.8128 Mean=0.8696\n----\nAVG on 5 cases | WT=0.8653 TC=0.7590 ET=0.7538 Mean=0.7927\n","output_type":"stream"}],"execution_count":61},{"cell_type":"markdown","source":"# Detailed Evaluation Report","metadata":{}},{"cell_type":"markdown","source":"## Convert history to DataFrame + plots (Loss + Val Mean)","metadata":{}},{"cell_type":"code","source":"import pandas as pd\nimport matplotlib.pyplot as plt\n\ndf_hist = pd.DataFrame(history)\ndf_hist.head()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:29:52.437062Z","iopub.execute_input":"2026-02-03T22:29:52.437325Z","iopub.status.idle":"2026-02-03T22:29:53.458476Z","shell.execute_reply.started":"2026-02-03T22:29:52.437302Z","shell.execute_reply":"2026-02-03T22:29:53.457835Z"}},"outputs":[{"execution_count":62,"output_type":"execute_result","data":{"text/plain":"   epoch      loss        ce  dice_loss        val_WT        val_TC  \\\n0      1  0.249222  0.113368   0.385077  8.514432e-01  7.498026e-01   \n1      2       NaN       NaN        NaN  2.510962e-13  7.453402e-12   \n2      3       NaN       NaN        NaN  2.510962e-13  7.453402e-12   \n3      4       NaN       NaN        NaN  2.510962e-13  7.453402e-12   \n4      5       NaN       NaN        NaN  2.510962e-13  7.453402e-12   \n\n         val_ET      val_Mean     time_sec  \n0  7.609824e-01  7.874094e-01  3244.516654  \n1  8.054322e-12  5.252940e-12  3188.249862  \n2  8.054322e-12  5.252940e-12  3220.397334  \n3  8.054322e-12  5.252940e-12  3245.566804  \n4  8.054322e-12  5.252940e-12  3263.380235  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>epoch</th>\n      <th>loss</th>\n      <th>ce</th>\n      <th>dice_loss</th>\n      <th>val_WT</th>\n      <th>val_TC</th>\n      <th>val_ET</th>\n      <th>val_Mean</th>\n      <th>time_sec</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>0.249222</td>\n      <td>0.113368</td>\n      <td>0.385077</td>\n      <td>8.514432e-01</td>\n      <td>7.498026e-01</td>\n      <td>7.609824e-01</td>\n      <td>7.874094e-01</td>\n      <td>3244.516654</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>2.510962e-13</td>\n      <td>7.453402e-12</td>\n      <td>8.054322e-12</td>\n      <td>5.252940e-12</td>\n      <td>3188.249862</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>3</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>2.510962e-13</td>\n      <td>7.453402e-12</td>\n      <td>8.054322e-12</td>\n      <td>5.252940e-12</td>\n      <td>3220.397334</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>2.510962e-13</td>\n      <td>7.453402e-12</td>\n      <td>8.054322e-12</td>\n      <td>5.252940e-12</td>\n      <td>3245.566804</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>2.510962e-13</td>\n      <td>7.453402e-12</td>\n      <td>8.054322e-12</td>\n      <td>5.252940e-12</td>\n      <td>3263.380235</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}],"execution_count":62},{"cell_type":"code","source":"plt.figure(figsize=(8,5))\nplt.plot(df_hist[\"epoch\"], df_hist[\"loss\"])\nplt.title(\"Training Loss\")\nplt.xlabel(\"Epoch\")\nplt.ylabel(\"Loss\")\nplt.grid(True)\nplt.show()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:29:53.459413Z","iopub.execute_input":"2026-02-03T22:29:53.459815Z","iopub.status.idle":"2026-02-03T22:29:53.567653Z","shell.execute_reply.started":"2026-02-03T22:29:53.45979Z","shell.execute_reply":"2026-02-03T22:29:53.567076Z"}},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 800x500 with 1 Axes>","image/png":"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\n"},"metadata":{}}],"execution_count":63},{"cell_type":"code","source":"plt.figure(figsize=(8,5))\nplt.plot(df_hist[\"epoch\"], df_hist[\"val_Mean\"])\nplt.title(\"Validation Mean Dice (patch-based val)\")\nplt.xlabel(\"Epoch\")\nplt.ylabel(\"Mean Dice\")\nplt.grid(True)\nplt.show()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:29:53.568665Z","iopub.execute_input":"2026-02-03T22:29:53.569289Z","iopub.status.idle":"2026-02-03T22:29:53.697778Z","shell.execute_reply.started":"2026-02-03T22:29:53.56926Z","shell.execute_reply":"2026-02-03T22:29:53.697023Z"}},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 800x500 with 1 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\n"},"metadata":{}}],"execution_count":64},{"cell_type":"markdown","source":"## Full-volume evaluation on validation set","metadata":{}},{"cell_type":"code","source":"FULLVOL_CASES = 30  # عدلها لو عايز كل الـ val\n\nresults_pp, avg_pp = eval_full_volume(model, val_dirs, max_cases=FULLVOL_CASES, min_et_size=50)\n\nrows = []\nfor pid, m in results_pp:\n    rows.append({\n        \"patient_id\": pid,\n        \"WT\": m[\"WT\"],\n        \"TC\": m[\"TC\"],\n        \"ET\": m[\"ET\"],\n        \"Mean\": m[\"Mean\"],\n    })\n\ndf_pp = pd.DataFrame(rows).sort_values(\"Mean\", ascending=False).reset_index(drop=True)\ndf_pp.head(10)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:29:53.69874Z","iopub.execute_input":"2026-02-03T22:29:53.69904Z","iopub.status.idle":"2026-02-03T22:32:20.145214Z","shell.execute_reply.started":"2026-02-03T22:29:53.69901Z","shell.execute_reply":"2026-02-03T22:32:20.144608Z"}},"outputs":[{"name":"stdout","text":"[1/30] BraTS2021_01605 | WT=0.7032 TC=0.2042 ET=0.3382 Mean=0.4152\n[2/30] BraTS2021_00651 | WT=0.8636 TC=0.8727 ET=0.8017 Mean=0.8460\n[3/30] BraTS2021_01125 | WT=0.9425 TC=0.9315 ET=0.9154 Mean=0.9298\n[4/30] BraTS2021_00026 | WT=0.8924 TC=0.9159 ET=0.9009 Mean=0.9031\n[5/30] BraTS2021_00231 | WT=0.9250 TC=0.8708 ET=0.8128 Mean=0.8696\n[6/30] BraTS2021_00022 | WT=0.8866 TC=0.9114 ET=0.8653 Mean=0.8878\n[7/30] BraTS2021_01596 | WT=0.8784 TC=0.7773 ET=0.8891 Mean=0.8483\n[8/30] BraTS2021_00436 | WT=0.9720 TC=0.9696 ET=0.9186 Mean=0.9534\n[9/30] BraTS2021_01649 | WT=0.8484 TC=0.9320 ET=0.8770 Mean=0.8858\n[10/30] BraTS2021_01636 | WT=0.5832 TC=0.2378 ET=0.1629 Mean=0.3279\n[11/30] BraTS2021_00705 | WT=0.5190 TC=0.7566 ET=0.7684 Mean=0.6813\n[12/30] BraTS2021_00459 | WT=0.9200 TC=0.7469 ET=0.8024 Mean=0.8231\n[13/30] BraTS2021_00107 | WT=0.9563 TC=0.7833 ET=0.9296 Mean=0.8897\n[14/30] BraTS2021_00109 | WT=0.7680 TC=0.4942 ET=0.7005 Mean=0.6542\n[15/30] BraTS2021_00735 | WT=0.7963 TC=0.8872 ET=0.8872 Mean=0.8569\n[16/30] BraTS2021_00078 | WT=0.9279 TC=0.9559 ET=0.9323 Mean=0.9387\n[17/30] BraTS2021_01642 | WT=0.9330 TC=0.8953 ET=0.9351 Mean=0.9211\n[18/30] BraTS2021_00831 | WT=0.9011 TC=0.9045 ET=0.8918 Mean=0.8992\n[19/30] BraTS2021_01604 | WT=0.4243 TC=0.2633 ET=0.2601 Mean=0.3159\n[20/30] BraTS2021_01425 | WT=0.9243 TC=0.9364 ET=0.9371 Mean=0.9326\n[21/30] BraTS2021_01469 | WT=0.8079 TC=0.4453 ET=0.4076 Mean=0.5536\n[22/30] BraTS2021_01149 | WT=0.6095 TC=0.0375 ET=0.0462 Mean=0.2310\n[23/30] BraTS2021_00401 | WT=0.9247 TC=0.8888 ET=0.8149 Mean=0.8761\n[24/30] BraTS2021_01466 | WT=0.9549 TC=0.9340 ET=0.8922 Mean=0.9271\n[25/30] BraTS2021_01302 | WT=0.9318 TC=0.9155 ET=0.9330 Mean=0.9267\n[26/30] BraTS2021_01485 | WT=0.5871 TC=0.0417 ET=0.0467 Mean=0.2252\n[27/30] BraTS2021_01231 | WT=0.8718 TC=0.7853 ET=0.7386 Mean=0.7986\n[28/30] BraTS2021_00824 | WT=0.9528 TC=0.9300 ET=0.9268 Mean=0.9366\n[29/30] BraTS2021_00645 | WT=0.7255 TC=0.9407 ET=0.9330 Mean=0.8664\n[30/30] BraTS2021_01465 | WT=0.9450 TC=0.8979 ET=0.9358 Mean=0.9262\n----\nAVG on 30 cases | WT=0.8292 TC=0.7355 ET=0.7400 Mean=0.7682\n","output_type":"stream"},{"execution_count":65,"output_type":"execute_result","data":{"text/plain":"        patient_id        WT        TC        ET      Mean\n0  BraTS2021_00436  0.971979  0.969641  0.918602  0.953407\n1  BraTS2021_00078  0.927866  0.955929  0.932300  0.938698\n2  BraTS2021_00824  0.952849  0.930011  0.926804  0.936554\n3  BraTS2021_01425  0.924293  0.936396  0.937089  0.932592\n4  BraTS2021_01125  0.942511  0.931470  0.915355  0.929779\n5  BraTS2021_01466  0.954902  0.934026  0.892249  0.927059\n6  BraTS2021_01302  0.931752  0.915537  0.932957  0.926749\n7  BraTS2021_01465  0.945010  0.897869  0.935842  0.926240\n8  BraTS2021_01642  0.932990  0.895280  0.935058  0.921109\n9  BraTS2021_00026  0.892367  0.915865  0.900935  0.903056","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>patient_id</th>\n      <th>WT</th>\n      <th>TC</th>\n      <th>ET</th>\n      <th>Mean</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>BraTS2021_00436</td>\n      <td>0.971979</td>\n      <td>0.969641</td>\n      <td>0.918602</td>\n      <td>0.953407</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>BraTS2021_00078</td>\n      <td>0.927866</td>\n      <td>0.955929</td>\n      <td>0.932300</td>\n      <td>0.938698</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>BraTS2021_00824</td>\n      <td>0.952849</td>\n      <td>0.930011</td>\n      <td>0.926804</td>\n      <td>0.936554</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>BraTS2021_01425</td>\n      <td>0.924293</td>\n      <td>0.936396</td>\n      <td>0.937089</td>\n      <td>0.932592</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>BraTS2021_01125</td>\n      <td>0.942511</td>\n      <td>0.931470</td>\n      <td>0.915355</td>\n      <td>0.929779</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>BraTS2021_01466</td>\n      <td>0.954902</td>\n      <td>0.934026</td>\n      <td>0.892249</td>\n      <td>0.927059</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>BraTS2021_01302</td>\n      <td>0.931752</td>\n      <td>0.915537</td>\n      <td>0.932957</td>\n      <td>0.926749</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>BraTS2021_01465</td>\n      <td>0.945010</td>\n      <td>0.897869</td>\n      <td>0.935842</td>\n      <td>0.926240</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>BraTS2021_01642</td>\n      <td>0.932990</td>\n      <td>0.895280</td>\n      <td>0.935058</td>\n      <td>0.921109</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>BraTS2021_00026</td>\n      <td>0.892367</td>\n      <td>0.915865</td>\n      <td>0.900935</td>\n      <td>0.903056</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}],"execution_count":65},{"cell_type":"markdown","source":"## Summary stats","metadata":{}},{"cell_type":"code","source":"summary = df_pp[[\"WT\",\"TC\",\"ET\",\"Mean\"]].agg([\"mean\",\"std\",\"min\",\"max\"])\nsummary\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:32:20.146306Z","iopub.execute_input":"2026-02-03T22:32:20.146599Z","iopub.status.idle":"2026-02-03T22:32:20.165798Z","shell.execute_reply.started":"2026-02-03T22:32:20.146571Z","shell.execute_reply":"2026-02-03T22:32:20.16516Z"}},"outputs":[{"execution_count":66,"output_type":"execute_result","data":{"text/plain":"            WT        TC        ET      Mean\nmean  0.829218  0.735458  0.740042  0.768239\nstd   0.148349  0.291913  0.283391  0.231235\nmin   0.424322  0.037485  0.046173  0.225188\nmax   0.971979  0.969641  0.937089  0.953407","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>WT</th>\n      <th>TC</th>\n      <th>ET</th>\n      <th>Mean</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>mean</th>\n      <td>0.829218</td>\n      <td>0.735458</td>\n      <td>0.740042</td>\n      <td>0.768239</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>0.148349</td>\n      <td>0.291913</td>\n      <td>0.283391</td>\n      <td>0.231235</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>0.424322</td>\n      <td>0.037485</td>\n      <td>0.046173</td>\n      <td>0.225188</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>0.971979</td>\n      <td>0.969641</td>\n      <td>0.937089</td>\n      <td>0.953407</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}],"execution_count":66},{"cell_type":"markdown","source":"## Best/Worst cases","metadata":{}},{"cell_type":"code","source":"print(\"Top 5 best cases:\")\ndisplay(df_pp.head(5))\n\nprint(\"\\nTop 5 worst cases:\")\ndisplay(df_pp.tail(5))\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:32:20.166807Z","iopub.execute_input":"2026-02-03T22:32:20.167074Z","iopub.status.idle":"2026-02-03T22:32:20.188172Z","shell.execute_reply.started":"2026-02-03T22:32:20.167047Z","shell.execute_reply":"2026-02-03T22:32:20.187569Z"}},"outputs":[{"name":"stdout","text":"Top 5 best cases:\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"        patient_id        WT        TC        ET      Mean\n0  BraTS2021_00436  0.971979  0.969641  0.918602  0.953407\n1  BraTS2021_00078  0.927866  0.955929  0.932300  0.938698\n2  BraTS2021_00824  0.952849  0.930011  0.926804  0.936554\n3  BraTS2021_01425  0.924293  0.936396  0.937089  0.932592\n4  BraTS2021_01125  0.942511  0.931470  0.915355  0.929779","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>patient_id</th>\n      <th>WT</th>\n      <th>TC</th>\n      <th>ET</th>\n      <th>Mean</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>BraTS2021_00436</td>\n      <td>0.971979</td>\n      <td>0.969641</td>\n      <td>0.918602</td>\n      <td>0.953407</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>BraTS2021_00078</td>\n      <td>0.927866</td>\n      <td>0.955929</td>\n      <td>0.932300</td>\n      <td>0.938698</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>BraTS2021_00824</td>\n      <td>0.952849</td>\n      <td>0.930011</td>\n      <td>0.926804</td>\n      <td>0.936554</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>BraTS2021_01425</td>\n      <td>0.924293</td>\n      <td>0.936396</td>\n      <td>0.937089</td>\n      <td>0.932592</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>BraTS2021_01125</td>\n      <td>0.942511</td>\n      <td>0.931470</td>\n      <td>0.915355</td>\n      <td>0.929779</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}},{"name":"stdout","text":"\nTop 5 worst cases:\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"         patient_id        WT        TC        ET      Mean\n25  BraTS2021_01605  0.703242  0.204178  0.338191  0.415204\n26  BraTS2021_01636  0.583177  0.237784  0.162888  0.327950\n27  BraTS2021_01604  0.424322  0.263279  0.260123  0.315908\n28  BraTS2021_01149  0.609464  0.037485  0.046173  0.231041\n29  BraTS2021_01485  0.587109  0.041746  0.046710  0.225188","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>patient_id</th>\n      <th>WT</th>\n      <th>TC</th>\n      <th>ET</th>\n      <th>Mean</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>25</th>\n      <td>BraTS2021_01605</td>\n      <td>0.703242</td>\n      <td>0.204178</td>\n      <td>0.338191</td>\n      <td>0.415204</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>BraTS2021_01636</td>\n      <td>0.583177</td>\n      <td>0.237784</td>\n      <td>0.162888</td>\n      <td>0.327950</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>BraTS2021_01604</td>\n      <td>0.424322</td>\n      <td>0.263279</td>\n      <td>0.260123</td>\n      <td>0.315908</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>BraTS2021_01149</td>\n      <td>0.609464</td>\n      <td>0.037485</td>\n      <td>0.046173</td>\n      <td>0.231041</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>BraTS2021_01485</td>\n      <td>0.587109</td>\n      <td>0.041746</td>\n      <td>0.046710</td>\n      <td>0.225188</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}],"execution_count":67},{"cell_type":"markdown","source":"## Compare BEFORE vs AFTER post-processing (ET cleaning)","metadata":{}},{"cell_type":"code","source":"def eval_full_volume_no_post(model, case_dirs, max_cases=10):\n    results = []\n    for i, case_dir in enumerate(case_dirs[:max_cases]):\n        pid = os.path.basename(case_dir)\n\n        imgs_dict = load_case_arrays(case_dir)\n        x_np, y_np, meta = preprocess_case(imgs_dict, do_crop=True)\n        x_t = torch.from_numpy(x_np[None]).float()\n\n        pred = sliding_window_inference(\n            model, x_t, patch_size=PATCH_SIZE, overlap=0.5, num_classes=4, device=device\n        )\n\n        m = region_dice_numpy(pred, y_np)\n        results.append((pid, m))\n        print(f\"[{i+1}/{max_cases}] {pid} | WT={m['WT']:.4f} TC={m['TC']:.4f} ET={m['ET']:.4f} Mean={m['Mean']:.4f}\")\n\n    # aggregate\n    avg = {\"WT\":0.0,\"TC\":0.0,\"ET\":0.0,\"Mean\":0.0}\n    for _, m in results:\n        for k in avg:\n            avg[k] += m[k]\n    for k in avg:\n        avg[k] /= max(len(results), 1)\n\n    print(\"----\")\n    print(f\"AVG (no post) on {len(results)} cases | WT={avg['WT']:.4f} TC={avg['TC']:.4f} ET={avg['ET']:.4f} Mean={avg['Mean']:.4f}\")\n    return results, avg\n\nresults_raw, avg_raw = eval_full_volume_no_post(model, val_dirs, max_cases=FULLVOL_CASES)\n\n# Build compare table\nrows = []\nraw_map = {pid: m for pid, m in results_raw}\npp_map = {pid: m for pid, m in results_pp}\n\nfor pid in pp_map.keys():\n    r = raw_map[pid]\n    p = pp_map[pid]\n    rows.append({\n        \"patient_id\": pid,\n        \"Mean_raw\": r[\"Mean\"],\n        \"Mean_pp\": p[\"Mean\"],\n        \"ET_raw\": r[\"ET\"],\n        \"ET_pp\": p[\"ET\"],\n        \"delta_Mean\": p[\"Mean\"] - r[\"Mean\"],\n        \"delta_ET\": p[\"ET\"] - r[\"ET\"],\n    })\n\ndf_compare = pd.DataFrame(rows).sort_values(\"delta_ET\", ascending=False).reset_index(drop=True)\ndf_compare.head(10)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:32:20.189048Z","iopub.execute_input":"2026-02-03T22:32:20.189419Z","iopub.status.idle":"2026-02-03T22:34:46.586267Z","shell.execute_reply.started":"2026-02-03T22:32:20.189383Z","shell.execute_reply":"2026-02-03T22:34:46.585587Z"}},"outputs":[{"name":"stdout","text":"[1/30] BraTS2021_01605 | WT=0.7032 TC=0.2040 ET=0.3375 Mean=0.4149\n[2/30] BraTS2021_00651 | WT=0.8635 TC=0.8726 ET=0.8017 Mean=0.8459\n[3/30] BraTS2021_01125 | WT=0.9422 TC=0.9307 ET=0.9144 Mean=0.9291\n[4/30] BraTS2021_00026 | WT=0.8925 TC=0.9157 ET=0.9008 Mean=0.9030\n[5/30] BraTS2021_00231 | WT=0.9248 TC=0.8677 ET=0.8064 Mean=0.8663\n[6/30] BraTS2021_00022 | WT=0.8867 TC=0.9106 ET=0.8642 Mean=0.8872\n[7/30] BraTS2021_01596 | WT=0.8788 TC=0.7702 ET=0.8788 Mean=0.8426\n[8/30] BraTS2021_00436 | WT=0.9721 TC=0.9697 ET=0.9188 Mean=0.9535\n[9/30] BraTS2021_01649 | WT=0.8484 TC=0.9318 ET=0.8767 Mean=0.8856\n[10/30] BraTS2021_01636 | WT=0.5838 TC=0.2389 ET=0.1647 Mean=0.3291\n[11/30] BraTS2021_00705 | WT=0.5182 TC=0.7505 ET=0.7612 Mean=0.6766\n[12/30] BraTS2021_00459 | WT=0.9199 TC=0.7438 ET=0.7980 Mean=0.8205\n[13/30] BraTS2021_00107 | WT=0.9563 TC=0.7832 ET=0.9295 Mean=0.8896\n[14/30] BraTS2021_00109 | WT=0.7682 TC=0.4948 ET=0.7009 Mean=0.6546\n[15/30] BraTS2021_00735 | WT=0.7956 TC=0.8787 ET=0.8787 Mean=0.8510\n[16/30] BraTS2021_00078 | WT=0.9278 TC=0.9549 ET=0.9308 Mean=0.9378\n[17/30] BraTS2021_01642 | WT=0.9331 TC=0.8948 ET=0.9344 Mean=0.9208\n[18/30] BraTS2021_00831 | WT=0.9011 TC=0.9045 ET=0.8918 Mean=0.8992\n[19/30] BraTS2021_01604 | WT=0.4249 TC=0.2786 ET=0.2766 Mean=0.3267\n[20/30] BraTS2021_01425 | WT=0.9244 TC=0.9366 ET=0.9373 Mean=0.9327\n[21/30] BraTS2021_01469 | WT=0.8079 TC=0.4436 ET=0.4055 Mean=0.5524\n[22/30] BraTS2021_01149 | WT=0.6089 TC=0.0373 ET=0.0458 Mean=0.2307\n[23/30] BraTS2021_00401 | WT=0.9247 TC=0.8888 ET=0.8149 Mean=0.8761\n[24/30] BraTS2021_01466 | WT=0.9549 TC=0.9339 ET=0.8921 Mean=0.9270\n[25/30] BraTS2021_01302 | WT=0.9320 TC=0.9157 ET=0.9331 Mean=0.9269\n[26/30] BraTS2021_01485 | WT=0.5886 TC=0.0415 ET=0.0464 Mean=0.2255\n[27/30] BraTS2021_01231 | WT=0.8710 TC=0.7788 ET=0.7305 Mean=0.7934\n[28/30] BraTS2021_00824 | WT=0.9526 TC=0.9295 ET=0.9262 Mean=0.9361\n[29/30] BraTS2021_00645 | WT=0.7240 TC=0.9376 ET=0.9292 Mean=0.8636\n[30/30] BraTS2021_01465 | WT=0.9450 TC=0.8977 ET=0.9357 Mean=0.9261\n----\nAVG (no post) on 30 cases | WT=0.8292 TC=0.7346 ET=0.7387 Mean=0.7675\n","output_type":"stream"},{"execution_count":68,"output_type":"execute_result","data":{"text/plain":"        patient_id  Mean_raw   Mean_pp    ET_raw     ET_pp  delta_Mean  \\\n0  BraTS2021_01596  0.842590  0.848290  0.878797  0.889084    0.005699   \n1  BraTS2021_00735  0.851001  0.856916  0.878689  0.887221    0.005915   \n2  BraTS2021_01231  0.793420  0.798574  0.730468  0.738575    0.005154   \n3  BraTS2021_00705  0.676641  0.681345  0.761240  0.768400    0.004703   \n4  BraTS2021_00231  0.866285  0.869558  0.806377  0.812798    0.003273   \n5  BraTS2021_00459  0.820533  0.823122  0.797954  0.802424    0.002589   \n6  BraTS2021_00645  0.863604  0.866402  0.929213  0.932978    0.002798   \n7  BraTS2021_01469  0.552358  0.553620  0.405534  0.407623    0.001263   \n8  BraTS2021_00078  0.937821  0.938698  0.930809  0.932300    0.000878   \n9  BraTS2021_00022  0.887153  0.887783  0.864215  0.865349    0.000629   \n\n   delta_ET  \n0  0.010286  \n1  0.008533  \n2  0.008107  \n3  0.007161  \n4  0.006421  \n5  0.004469  \n6  0.003764  \n7  0.002089  \n8  0.001491  \n9  0.001134  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>patient_id</th>\n      <th>Mean_raw</th>\n      <th>Mean_pp</th>\n      <th>ET_raw</th>\n      <th>ET_pp</th>\n      <th>delta_Mean</th>\n      <th>delta_ET</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>BraTS2021_01596</td>\n      <td>0.842590</td>\n      <td>0.848290</td>\n      <td>0.878797</td>\n      <td>0.889084</td>\n      <td>0.005699</td>\n      <td>0.010286</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>BraTS2021_00735</td>\n      <td>0.851001</td>\n      <td>0.856916</td>\n      <td>0.878689</td>\n      <td>0.887221</td>\n      <td>0.005915</td>\n      <td>0.008533</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>BraTS2021_01231</td>\n      <td>0.793420</td>\n      <td>0.798574</td>\n      <td>0.730468</td>\n      <td>0.738575</td>\n      <td>0.005154</td>\n      <td>0.008107</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>BraTS2021_00705</td>\n      <td>0.676641</td>\n      <td>0.681345</td>\n      <td>0.761240</td>\n      <td>0.768400</td>\n      <td>0.004703</td>\n      <td>0.007161</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>BraTS2021_00231</td>\n      <td>0.866285</td>\n      <td>0.869558</td>\n      <td>0.806377</td>\n      <td>0.812798</td>\n      <td>0.003273</td>\n      <td>0.006421</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>BraTS2021_00459</td>\n      <td>0.820533</td>\n      <td>0.823122</td>\n      <td>0.797954</td>\n      <td>0.802424</td>\n      <td>0.002589</td>\n      <td>0.004469</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>BraTS2021_00645</td>\n      <td>0.863604</td>\n      <td>0.866402</td>\n      <td>0.929213</td>\n      <td>0.932978</td>\n      <td>0.002798</td>\n      <td>0.003764</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>BraTS2021_01469</td>\n      <td>0.552358</td>\n      <td>0.553620</td>\n      <td>0.405534</td>\n      <td>0.407623</td>\n      <td>0.001263</td>\n      <td>0.002089</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>BraTS2021_00078</td>\n      <td>0.937821</td>\n      <td>0.938698</td>\n      <td>0.930809</td>\n      <td>0.932300</td>\n      <td>0.000878</td>\n      <td>0.001491</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>BraTS2021_00022</td>\n      <td>0.887153</td>\n      <td>0.887783</td>\n      <td>0.864215</td>\n      <td>0.865349</td>\n      <td>0.000629</td>\n      <td>0.001134</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}],"execution_count":68},{"cell_type":"markdown","source":"## Plot improvement distributions","metadata":{}},{"cell_type":"code","source":"plt.figure(figsize=(8,5))\nplt.hist(df_compare[\"delta_ET\"], bins=20)\nplt.title(\"ET Dice Improvement after Post-processing\")\nplt.xlabel(\"Δ ET Dice\")\nplt.ylabel(\"Count\")\nplt.grid(True)\nplt.show()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:34:46.589931Z","iopub.execute_input":"2026-02-03T22:34:46.590334Z","iopub.status.idle":"2026-02-03T22:34:46.762288Z","shell.execute_reply.started":"2026-02-03T22:34:46.590311Z","shell.execute_reply":"2026-02-03T22:34:46.761591Z"}},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 800x500 with 1 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VatmuTy/HwLLmF97tbCwMJUvX97tB1VG+7VzHiVlGlNISIjKlSuX6fZEWd314ciRI67AeLWMt3aPHDmi2rVrKyIiQu3atdPHH3+siRMnSroyZcDPz8/1Frt05Xn64YcfMh1ThhMnTrg9rlChQqZjlOR2d4ir2zOO/8CBA5Kktm3bZrmf0NBQt8dZPc8lSpTI8vnMrYx50m+//bYOHTrkFqpuZFrMgQMHdPbsWZUpUybL5dc+h1nVNSeBgYH6z3/+I+lKAI+JiVH58uVdy48cOaKqVatm+sT71a8J6coHvT7++GPFxcXptttuU8eOHdWrVy916tTpumM4e/as/vzzT9fjgIAAt/Mvq/OsWrVqSk1N1cmTJxUZGelqv/b4jxw5Ih8fH1WpUsWtPTIyUuHh4a7xZ0yVuHYawtUyXmfx8fE5HkuJEiU0ZcoUxcfHKzo6WvXr19c999yjhx9+WLfffrtrnKNHj9bUqVM1d+5ctWjRQl27dtVDDz103SkDUuZzpUSJEpL+75zIOK5rj7tkyZKuvkBeEV4BD9izZ4+kzN/Q88rpdMpms2nZsmXy9fXNtDzjCm9eZbWtnNrN/5/Tlx83emeBBx98UAMGDNDOnTtVr149ffzxx2rXrp3bXR6cTqc6dOigp59+OsttVKtWze1xfo8/42rXhx9+6BZkMlx91Tan7d2Il156SWPHjtUjjzyiiRMnqmTJkvLx8dGoUaNu6FZsTqdTZcqU0dy5c7Ncfm0Iz2tdfX193W5Rl19lypTRzp07tWLFCi1btkzLli3T+++/r4cffjjLD3ddbeTIkW59WrVqle/762Z3/Nf+8pcfGXV85ZVXVK9evSz7ZJz7vXr1UosWLbR48WJ9/fXXeuWVVzR58mR99tlniouLkyS99tpr6t+/vz7//HN9/fXXGjFihCZNmqTNmze7/QKRlcL4ngBcD+EV8ICMD8Pk9LZq5cqVtWLFCp05cybbq6+VK1eWMUYxMTGZApinHThwQG3atHE9Pn/+vH7//Xfdc8891123YsWK2r9/f6b2H3/80bU8Q/fu3TV48GDX1IGffvpJY8aMcVuvcuXKOn/+fIGEo5xk3Pu3TJkyBbavvIadTz75RG3atNF7773n1p6cnOwW6PO6v8qVK2vlypVq1qyZR25lVrFiRf3www9yOp1uV1+zek0EBASoS5cu6tKli5xOpx5//HG98847Gjt2rKpUqZLtMT799NNut+u69spgxhXPq/30008KDg7O9qr+1eN3Op06cOCA24fDjh8/ruTkZNf4M15De/bsyfaX24w+oaGhuXqdlStXTo8//rgef/xxnThxQnfffbdefPFFV3iVpDp16qhOnTr6xz/+oY0bN6pZs2aaOXOmXnjhhetuPycZx3Xw4EG3q9GnT5++oXcYcGtjzitQxObNm6d//etfatKkidq1a5dtvwceeEDGmCxvBZVxVeP++++Xr6+vxo8fn+lKhzFGp0+fLtjB58GsWbPkcDhcj2fMmKHLly+7/cDMzj333KPvvvtOmzZtcrVduHBBs2bNUqVKlVSzZk1Xe3h4uGJjY/Xxxx9rwYIFCggIUPfu3d2216tXL23atEkrVqzItK/k5GRdvnw5H0eYWWxsrEJDQ/XSSy+5HXuGa28hlBvBwcGSrowzN3x9fTO9FhYtWuSal3s9GfcjvXZ/vXr1Unp6umt6xtUuX76c6/Hl1z333KOkpCS3+c2XL1/Wm2++qZCQELVq1UqSMr3mfXx8XHdnyLglVXbHWLNmTbVv3971dfX8VknatGmT27zh3377TZ9//rk6dux43avoGb+0XXtni6lTp0qSOnfuLEnq2LGjihcvrkmTJmX6NH5GXevXr6/KlSvr1VdfdU1BulrG6yw9Pd3tdlfSlV+soqKiXM9FSkpKptd/nTp15OPjUyB/3axdu3by8/PTjBkz3Nqvvo0dkFdcecUtadmyZa4rNldr2rSpay5YQfjkk08UEhLi+lDPihUrtGHDBtWtW1eLFi3Kcd02bdqoX79++uc//6kDBw6oU6dOcjqd+vbbb9WmTRsNGzZMlStX1gsvvKAxY8bo8OHD6t69u4oXL65Dhw5p8eLFGjRokNtfTypKly5dUrt27dSrVy/t379fb7/9tpo3b66uXbted91nnnlG8+fPV1xcnEaMGKGSJUvqgw8+0KFDh/Tpp59mmvf4l7/8RQ899JDefvttxcbGZro92FNPPaUvvvhC9957r/r376/69evrwoUL2r17tz755BMdPnw4V1clryc0NFQzZsxQv379dPfdd+vBBx9U6dKl9euvv+qrr75Ss2bN8vxDOygoSDVr1tTChQtVrVo1lSxZUrVr1852TuS9996rCRMmaMCAAWratKl2796tuXPn5vp1nRHYRowYodjYWPn6+urBBx9Uq1atNHjwYE2aNEk7d+5Ux44d5e/vrwMHDmjRokV644031KNHjzwdW14MGjRI77zzjvr376/t27erUqVK+uSTT7RhwwZNmzbNNX984MCBOnPmjNq2bavy5cvryJEjevPNN1WvXj3XFc969erJ19dXkydP1tmzZ2W329W2bdts5/NmqF27tmJjY91ulSUpy18wr1W3bl3Fx8dr1qxZSk5OVqtWrfTdd9/pgw8+UPfu3V3vUoSGhur111/XwIED1bBhQ9e9Ynft2qXU1FR98MEH8vHx0b/+9S/FxcWpVq1aGjBggG677TYdPXpUa9asUWhoqP7zn//o3LlzKl++vHr06KG6desqJCREK1eu1NatW/Xaa69JunLLrWHDhqlnz56qVq2aLl++rA8//FC+vr564IEH8l2vDGXLltXIkSP12muvqWvXrurUqZN27dqlZcuWKSIiokCmUeAW5KG7HAAekdOtspTN7bBu5FZZGV+BgYGmfPny5t577zWzZ8923VrpatfeKssYYy5fvmxeeeUVU6NGDRMQEGBKly5t4uLizPbt2936ffrpp6Z58+amWLFiplixYqZGjRpm6NChZv/+/bl6Pq69VVaxYsUy9W3VqpWpVatWpvaKFSuazp07Z9rmN998YwYNGmRKlChhQkJCTN++fc3p06dzXPdqP//8s+nRo4cJDw83gYGBplGjRubLL7/Msm9KSooJCgrKdCulq507d86MGTPGVKlSxQQEBJiIiAjTtGlT8+qrr7pu6ZVxq6xXXnnFbd01a9ZkeTuhrJ6/jP6xsbEmLCzMBAYGmsqVK5v+/fu73WYpu+c547VztY0bN5r69eubgICA69426+LFi+aJJ54w5cqVM0FBQaZZs2Zm06ZNplWrVqZVq1ZufZXFrbIuX75shg8fbkqXLm1sNlumscyaNcvUr1/fBAUFmeLFi5s6deqYp59+2hw7dszVJ6e6ZiW75+Jax48fNwMGDDAREREmICDA1KlTJ9N5+cknn5iOHTuaMmXKmICAAFOhQgUzePBg8/vvv7v1e/fdd83tt99ufH19c3XbrIzn6qOPPjJVq1Y1drvd3HXXXZnWy+k2eQ6Hw4wfP97ExMQYf39/Ex0dbcaMGZPl94MvvvjCNG3a1AQFBZnQ0FDTqFEjM3/+fLc+O3bsMPfff78pVaqUsdvtpmLFiqZXr15m1apVxhhj0tLSzFNPPWXq1q1rihcvbooVK2bq1q1r3n77bdc2fvnlF/PII4+YypUrm8DAQFOyZEnTpk0bs3LlSrd9ZXerrKxe+9c+n5cvXzZjx441kZGRJigoyLRt29bs27fPlCpVygwZMiTH5x3Iis0YZlUDKDgZN7HfunWrR+/oABQkm82moUOH8nZ3AUlOTlaJEiX0wgsv6LnnnvP0cGAxzHkFAACF5urbj2XImPub8SeAgbxgzisAACg0Cxcu1Jw5c3TPPfcoJCRE69ev1/z589WxY0c1a9bM08ODBRFeAQBAobnzzjvl5+enKVOmKCUlxfUhrhu9DRduXcx5BQAAgGUw5xUAAACWQXgFAACAZdz0c16dTqeOHTum4sWLczNkAAAAL2SM0blz5xQVFZXpD9Fc66YPr8eOHVN0dLSnhwEAAIDr+O2331S+fPkc+9z04TXjTwb+9ttvCg0N9fBoCpfD4dDXX3/t+rON8D7UyBqok/ejRt6PGlmDt9QpJSVF0dHRrtyWk5s+vGZMFQgNDb0lwmtwcLBCQ0P5RuGlqJE1UCfvR428HzWyBm+rU26mePKBLQAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZXg0vK5bt05dunRRVFSUbDablixZkqnPvn371LVrV4WFhalYsWJq2LChfv3116IfLAAAADzOo+H1woULqlu3rqZPn57l8p9//lnNmzdXjRo1tHbtWv3www8aO3asAgMDi3ikAAAA8AZ+ntx5XFyc4uLisl3+3HPP6Z577tGUKVNcbZUrVy6KoQEAAMALeTS85sTpdOqrr77S008/rdjYWO3YsUMxMTEaM2aMunfvnu16aWlpSktLcz1OSUmRJDkcDjkcjsIetkdlHN/NfpxWRo2sgTp5P2rk/aiRNXhLnfKyf5sxxhTiWHLNZrNp8eLFrmCalJSkcuXKKTg4WC+88ILatGmj5cuX69lnn9WaNWvUqlWrLLeTkJCg8ePHZ2qfN2+egoODC/MQAAAAkA+pqanq06ePzp49q9DQ0Bz7em14PXbsmG677Tb17t1b8+bNc/Xr2rWrihUrpvnz52e5nayuvEZHR+vUqVPXfTKszuFwKDExUR06dJC/v7+nh4MsUCNroE6eVzthRY7L7T5GExs4NXabj9KctgLZ556E2ALZDq7gPLIGb6lTSkqKIiIichVevXbaQEREhPz8/FSzZk239jvuuEPr16/Pdj273S673Z6p3d/f/5Y5eW6lY7UqamQN1Mlz0tJzF0jTnLZc970eal04OI+swdN1ysu+vfY+rwEBAWrYsKH279/v1v7TTz+pYsWKHhoVAAAAPMmjV17Pnz+vgwcPuh4fOnRIO3fuVMmSJVWhQgU99dRT+stf/qKWLVu65rz+5z//0dq1az03aAAAAHiMR8Prtm3b1KZNG9fj0aNHS5Li4+M1Z84c3XfffZo5c6YmTZqkESNGqHr16vr000/VvHlzTw0ZAAAAHuTR8Nq6dWtd7/NijzzyiB555JEiGhEAAAC8mdfOeQUAAACuRXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBkeDa/r1q1Tly5dFBUVJZvNpiVLlmTbd8iQIbLZbJo2bVqRjQ8AAADexaPh9cKFC6pbt66mT5+eY7/Fixdr8+bNioqKKqKRAQAAwBv5eXLncXFxiouLy7HP0aNHNXz4cK1YsUKdO3cuopEBAADAG3k0vF6P0+lUv3799NRTT6lWrVq5WictLU1paWmuxykpKZIkh8Mhh8NRKOP0FhnHd7Mfp5VRI2ugTp5n9zU5L/cxbv8WBOpdsDiPrMFb6pSX/Xt1eJ08ebL8/Pw0YsSIXK8zadIkjR8/PlP7119/reDg4IIcntdKTEz09BBwHdTIGqiT50xplLt+Exs4C2yfS5cuLbBt4f9wHlmDp+uUmpqa675eG163b9+uN954Q99//71sNluu1xszZoxGjx7tepySkqLo6Gh17NhRoaGhhTFUr+FwOJSYmKgOHTrI39/f08NBFqiRNVAnz6udsCLH5XYfo4kNnBq7zUdpztz/jMjJnoTYAtkOruA8sgZvqVPGO+W54bXh9dtvv9WJEydUoUIFV1t6erqeeOIJTZs2TYcPH85yPbvdLrvdnqnd39//ljl5bqVjtSpqZA3UyXPS0nMXSNOctlz3vR5qXTg4j6zB03XKy769Nrz269dP7du3d2uLjY1Vv379NGDAAA+NCgAAAJ7k0fB6/vx5HTx40PX40KFD2rlzp0qWLKkKFSqoVKlSbv39/f0VGRmp6tWrF/VQAQAA4AU8Gl63bdumNm3auB5nzFWNj4/XnDlzPDQqAAAAeCuPhtfWrVvLmNzf5iS7ea4AAAC4NXj0L2wBAAAAeUF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZHg2v69atU5cuXRQVFSWbzaYlS5a4ljkcDv39739XnTp1VKxYMUVFRenhhx/WsWPHPDdgAAAAeJRHw+uFCxdUt25dTZ8+PdOy1NRUff/99xo7dqy+//57ffbZZ9q/f7+6du3qgZECAADAG/h5cudxcXGKi4vLcllYWJgSExPd2t566y01atRIv/76qypUqFAUQwQAAIAX8Wh4zauzZ8/KZrMpPDw82z5paWlKS0tzPU5JSZF0ZRqCw+Eo7CF6VMbx3ezHaWXUyBqok+fZfU3Oy32M278FgXoXLM4ja/CWOuVl/zZjTMGd+TfAZrNp8eLF6t69e5bLL168qGbNmqlGjRqaO3dutttJSEjQ+PHjM7XPmzdPwcHBBTVcAAAAFJDU1FT16dNHZ8+eVWhoaI59LRFeHQ6HHnjgAf3v//6v1q5dm+NBZXXlNTo6WqdOnbruk2F1DodDiYmJ6tChg/z9/T09HGSBGlkDdfK82gkrclxu9zGa2MCpsdt8lOa0Fcg+9yTEFsh2cAXnkTV4S51SUlIUERGRq/Dq9dMGHA6HevXqpSNHjmj16tXXPSC73S673Z6p3d/f/5Y5eW6lY7UqamQN1Mlz0tJzF0jTnLZc970eal04OI+swdN1ysu+vTq8ZgTXAwcOaM2aNSpVqpSnhwQAAAAP8mh4PX/+vA4ePOh6fOjQIe3cuVMlS5ZUuXLl1KNHD33//ff68ssvlZ6erqSkJElSyZIlFRAQ4KlhAwAAwEM8Gl63bdumNm3auB6PHj1akhQfH6+EhAR98cUXkqR69eq5rbdmzRq1bt26qIYJAAAAL+HR8Nq6dWvl9HkxL/ksGQAAALyER//CFgAAAJAXhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAluHR8Lpu3Tp16dJFUVFRstlsWrJkidtyY4yef/55lStXTkFBQWrfvr0OHDjgmcECAADA4zwaXi9cuKC6detq+vTpWS6fMmWK/vnPf2rmzJnasmWLihUrptjYWF28eLGIRwoAAABv4OfJncfFxSkuLi7LZcYYTZs2Tf/4xz/UrVs3SdK///1vlS1bVkuWLNGDDz5YlEMFAACAF/BoeM3JoUOHlJSUpPbt27vawsLC1LhxY23atCnb8JqWlqa0tDTX45SUFEmSw+GQw+Eo3EF7WMbx3ezHaWXUyBqok+fZfU3Oy32M278FgXoXLM4ja/CWOuVl/14bXpOSkiRJZcuWdWsvW7asa1lWJk2apPHjx2dq//rrrxUcHFywg/RSiYmJnh4CroMaWQN18pwpjXLXb2IDZ4Htc+nSpQW2LfwfziNr8HSdUlNTc93Xa8Nrfo0ZM0ajR492PU5JSVF0dLQ6duyo0NBQD46s8DkcDiUmJqpDhw7y9/f39HCQBWpkDdTJ82onrMhxud3HaGIDp8Zu81Ga01Yg+9yTEFsg28EVnEfW4C11yninPDe8NrxGRkZKko4fP65y5cq52o8fP6569eplu57dbpfdbs/U7u/vf8ucPLfSsVoVNbIG6uQ5aem5C6RpTluu+14PtS4cnEfW4Ok65WXfXnuf15iYGEVGRmrVqlWutpSUFG3ZskVNmjTx4MgAAADgKR698nr+/HkdPHjQ9fjQoUPauXOnSpYsqQoVKmjUqFF64YUXVLVqVcXExGjs2LGKiopS9+7dPTdoAAAAeIxHw+u2bdvUpk0b1+OMuarx8fGaM2eOnn76aV24cEGDBg1ScnKymjdvruXLlyswMNBTQwYAAIAHeTS8tm7dWsZkf5sTm82mCRMmaMKECUU4KgAAAHgrr53zCgAAAFyL8AoAAADLILwCAADAMgivAAAAsAzCKwAAACyD8AoAAADLILwCAADAMgivAAAAsAzCKwAAACyD8AoAAADLILwCAADAMvIVXm+//XadPn06U3tycrJuv/32Gx4UAAAAkJV8hdfDhw8rPT09U3taWpqOHj16w4MCAAAAsuKXl85ffPGF6/8rVqxQWFiY63F6erpWrVqlSpUqFdjgAAAAgKvlKbx2795dkmSz2RQfH++2zN/fX5UqVdJrr71WYIMDAAAArpan8Op0OiVJMTEx2rp1qyIiIgplUAAAAEBW8hReMxw6dKigxwEAAABcV77CqyStWrVKq1at0okTJ1xXZDPMnj37hgcGAAAAXCtf4XX8+PGaMGGCGjRooHLlyslmsxX0uAAAAIBM8hVeZ86cqTlz5qhfv34FPR4AAAAgW/m6z+ulS5fUtGnTgh4LAAAAkKN8hdeBAwdq3rx5BT0WAAAAIEf5mjZw8eJFzZo1SytXrtSdd94pf39/t+VTp04tkMEBAAAAV8tXeP3hhx9Ur149SdKePXvclvHhLQAAABSWfIXXNWvWFPQ4AAAAgOvK15xXAAAAwBPydeW1TZs2OU4PWL16db4HBAAAAGQnX+E1Y75rBofDoZ07d2rPnj2Kj48viHEBAAAAmeQrvL7++utZtickJOj8+fM3NCAAAAAgOwU65/Whhx7S7NmzC3KTAAAAgEuBhtdNmzYpMDCwIDcJAAAAuORr2sD999/v9tgYo99//13btm3T2LFjC2RgAAAAwLXyFV7DwsLcHvv4+Kh69eqaMGGCOnbsWCADAwAAAK6Vr/D6/vvvF/Q4AAAAgOu6oTmv27dv10cffaSPPvpIO3bsKKgxuaSnp2vs2LGKiYlRUFCQKleurIkTJ8oYU+D7AgAAgPfL15XXEydO6MEHH9TatWsVHh4uSUpOTlabNm20YMEClS5dukAGN3nyZM2YMUMffPCBatWqpW3btmnAgAEKCwvTiBEjCmQfAAAAsI58XXkdPny4zp07p//+9786c+aMzpw5oz179iglJaVAQ+XGjRvVrVs3de7cWZUqVVKPHj3UsWNHfffddwW2DwAAAFhHvq68Ll++XCtXrtQdd9zhaqtZs6amT59eoB/Yatq0qWbNmqWffvpJ1apV065du7R+/XpNnTo123XS0tKUlpbmepySkiLpyl8BczgcBTY2b5RxfDf7cVoZNbIG6uR5dt+cp4fZfYzbvwWBehcsziNr8JY65WX/NpOPCaTFixfXt99+m+nPxO7YsUOtWrVyBcYb5XQ69eyzz2rKlCny9fVVenq6XnzxRY0ZMybbdRISEjR+/PhM7fPmzVNwcHCBjAsAAAAFJzU1VX369NHZs2cVGhqaY998hddu3bopOTlZ8+fPV1RUlCTp6NGj6tu3r0qUKKHFixfnb+TXWLBggZ566im98sorqlWrlnbu3KlRo0Zp6tSpio+Pz3KdrK68RkdH69SpU9d9MqzO4XAoMTFRHTp0kL+/v6eHgyxQI2ugTp5XO2FFjsvtPkYTGzg1dpuP0py2AtnnnoTYAtkOruA8sgZvqVNKSooiIiJyFV7zNW3grbfeUteuXVWpUiVFR0dLkn777TfVrl1bH330UX42maWnnnpKzzzzjB588EFJUp06dXTkyBFNmjQp2/Bqt9tlt9sztfv7+98yJ8+tdKxWRY2sgTp5Tlp67gJpmtOW677XQ60LB+eRNXi6TnnZd77Ca3R0tL7//nutXLlSP/74oyTpjjvuUPv27fOzuWylpqbKx8f9M2W+vr5yOp0Fuh8AAABYQ57C6+rVqzVs2DBt3rxZoaGh6tChgzp06CBJOnv2rGrVqqWZM2eqRYsWBTK4Ll266MUXX1SFChVUq1Yt7dixQ1OnTtUjjzxSINsHAACAteQpvE6bNk2PPvpolnMRwsLCNHjwYE2dOrXAwuubb76psWPH6vHHH9eJEycUFRWlwYMH6/nnny+Q7QMAAMBa8nSf1127dqlTp07ZLu/YsaO2b99+w4PKULx4cU2bNk1HjhzRn3/+qZ9//lkvvPCCAgICCmwfAAAAsI48hdfjx4/nOKHWz89PJ0+evOFBAQAAAFnJU3i97bbbtGfPnmyX//DDDypXrtwNDwoAAADISp7C6z333KOxY8fq4sWLmZb9+eefGjdunO69994CGxwAAABwtTx9YOsf//iHPvvsM1WrVk3Dhg1T9erVJUk//vijpk+frvT0dD333HOFMlAAAAAgT+G1bNmy2rhxox577DGNGTNGGX+cy2azKTY2VtOnT1fZsmULZaAAAABAnv9IQcWKFbV06VL98ccfOnjwoIwxqlq1qkqUKFEY4wMAAABc8vUXtiSpRIkSatiwYUGOBQAAAMhRnj6wBQAAAHgS4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBleH16PHj2qhx56SKVKlVJQUJDq1Kmjbdu2eXpYAAAA8AA/Tw8gJ3/88YeaNWumNm3aaNmyZSpdurQOHDigEiVKeHpoAAAA8ACvDq+TJ09WdHS03n//fVdbTEyMB0cEAAAAT/Lq8PrFF18oNjZWPXv21DfffKPbbrtNjz/+uB599NFs10lLS1NaWprrcUpKiiTJ4XDI4XAU+pg9KeP4bvbjtDJqZA3UyfPsvibn5T7G7d+CQL0LFueRNXhLnfKyf5sxpuDO/AIWGBgoSRo9erR69uyprVu3auTIkZo5c6bi4+OzXCchIUHjx4/P1D5v3jwFBwcX6ngBAACQd6mpqerTp4/Onj2r0NDQHPt6dXgNCAhQgwYNtHHjRlfbiBEjtHXrVm3atCnLdbK68hodHa1Tp05d98mwOofDocTERHXo0EH+/v6eHg6yQI2sgTp5Xu2EFTkut/sYTWzg1NhtPkpz2gpkn3sSYgtkO7iC88gavKVOKSkpioiIyFV49eppA+XKlVPNmjXd2u644w59+umn2a5jt9tlt9sztfv7+98yJ8+tdKxWRY2sgTp5Tlp67gJpmtOW677XQ60LB+eRNXi6TnnZt1ffKqtZs2bav3+/W9tPP/2kihUremhEAAAA8CSvDq9/+9vftHnzZr300ks6ePCg5s2bp1mzZmno0KGeHhoAAAA8wKvDa8OGDbV48WLNnz9ftWvX1sSJEzVt2jT17dvX00MDAACAB3j1nFdJuvfee3Xvvfd6ehgAAADwAl595RUAAAC4GuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGUQXgEAAGAZhFcAAABYBuEVAAAAlkF4BQAAgGVYKry+/PLLstlsGjVqlKeHAgAAAA+wTHjdunWr3nnnHd15552eHgoAAAA8xBLh9fz58+rbt6/effddlShRwtPDAQAAgIf4eXoAuTF06FB17txZ7du31wsvvJBj37S0NKWlpbkep6SkSJIcDoccDkehjtPTMo7vZj9OK6NG1kCdPM/ua3Je7mPc/i0I1LtgcR5Zg7fUKS/7txljCu7MLwQLFizQiy++qK1btyowMFCtW7dWvXr1NG3atCz7JyQkaPz48Zna582bp+Dg4EIeLQAAAPIqNTVVffr00dmzZxUaGppjX68Or7/99psaNGigxMRE11zX64XXrK68RkdH69SpU9d9MqzO4XAoMTFRHTp0kL+/v6eHgyxQI2ugTp5XO2FFjsvtPkYTGzg1dpuP0py2IhpVwdqTEOvpIRQqziNr8JY6paSkKCIiIlfh1aunDWzfvl0nTpzQ3Xff7WpLT0/XunXr9NZbbyktLU2+vr5u69jtdtnt9kzb8vf3v2VOnlvpWK2KGlkDdfKctPTcBdI0py3Xfb3NrfLa4jyyBk/XKS/79urw2q5dO+3evdutbcCAAapRo4b+/ve/ZwquAAAAuLl5dXgtXry4ateu7dZWrFgxlSpVKlM7AAAAbn6WuFUWAAAAIHn5ldesrF271tNDAAAAgIdw5RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBleH14nTZqkhg0bqnjx4ipTpoy6d++u/fv3e3pYAAAA8ACvD6/ffPONhg4dqs2bNysxMVEOh0MdO3bUhQsXPD00AAAAFDE/Tw/gepYvX+72eM6cOSpTpoy2b9+uli1bemhUAAAA8ASvD6/XOnv2rCSpZMmSWS5PS0tTWlqa63FKSookyeFwyOFwFP4APSjj+G7247QyamQN1Mnz7L4m5+U+xu1fK7rZX1+cR9bgLXXKy/5txhjLnPlOp1Ndu3ZVcnKy1q9fn2WfhIQEjR8/PlP7vHnzFBwcXNhDBAAAQB6lpqaqT58+Onv2rEJDQ3Psa6nw+thjj2nZsmVav369ypcvn2WfrK68RkdH69SpU9d9MqzO4XAoMTFRHTp0kL+/v6eHgyxQI2ugTp5XO2FFjsvtPkYTGzg1dpuP0py2IhpVwdqTEFuk+7vec1rQdjzXtkjPo6I+Pk8ojNeMt3y/S0lJUURERK7Cq2WmDQwbNkxffvml1q1bl21wlSS73S673Z6p3d/f/5b5IXQrHatVUSNroE6ek5aeu0Ca5rTluq+3KerXVlE/TxnHV1TnkVVfB3lRmM+jp7/f5WXfXh9ejTEaPny4Fi9erLVr1yomJsbTQwIAAICHeH14HTp0qObNm6fPP/9cxYsXV1JSkiQpLCxMQUFBHh4dAAAAipLX3+d1xowZOnv2rFq3bq1y5cq5vhYuXOjpoQEAAKCIef2VVwt9ngwAAACFzOuvvAIAAAAZCK8AAACwDMIrAAAALIPwCgAAAMsgvAIAAMAyCK8AAACwDMIrAAAALIPwCgAAAMsgvAIAAMAyCK8AAACwDMIrAAAALIPwCgAAAMsgvAIAAMAyCK8AAACwDMIrAAAALIPwCgAAAMvw8/QAbkaVnvmqSPd3+OXORbo/AJ5X1N9nAHheYZz3dl+jKY2k2gkrlJZuc1vmrfmCK68AAACwDMIrAAAALIPwCgAAAMsgvAIAAMAyCK8AAACwDMIrAAAALIPwCgAAAMsgvAIAAMAyCK8AAACwDMIrAAAALIPwCgAAAMsgvAIAAMAyCK8AAACwDMIrAAAALIPwCgAAAMsgvAIAAMAyCK8AAACwDMIrAAAALMMS4XX69OmqVKmSAgMD1bhxY3333XeeHhIAAAA8wOvD68KFCzV69GiNGzdO33//verWravY2FidOHHC00MDAABAEfP68Dp16lQ9+uijGjBggGrWrKmZM2cqODhYs2fP9vTQAAAAUMT8PD2AnFy6dEnbt2/XmDFjXG0+Pj5q3769Nm3alOU6aWlpSktLcz0+e/asJOnMmTNyOByFO+D/z+/yhSLZT4bTp09LkhwOh1JTU3X69Gn5+/sX6RiQO9TIGqxQp6L+PuNt/JxGqalO+Tl8lO60eXo4+ZLxvbuoeOJnU1GeR7f6OZFfOZ1LRfkaPXfunCTJGHPdvl4dXk+dOqX09HSVLVvWrb1s2bL68ccfs1xn0qRJGj9+fKb2mJiYQhmjN4h4zdMjAICi18fTA7hBN/v37nI3+fHdTLI7lzzxGj137pzCwsJy7OPV4TU/xowZo9GjR7seO51OnTlzRqVKlZLNZs3fznMrJSVF0dHR+u233xQaGurp4SAL1MgaqJP3o0bejxpZg7fUyRijc+fOKSoq6rp9vTq8RkREyNfXV8ePH3drP378uCIjI7Ncx263y263u7WFh4cX1hC9UmhoKN8ovBw1sgbq5P2okfejRtbgDXW63hXXDF79ga2AgADVr19fq1atcrU5nU6tWrVKTZo08eDIAAAA4AlefeVVkkaPHq34+Hg1aNBAjRo10rRp03ThwgUNGDDA00MDAABAEfP68PqXv/xFJ0+e1PPPP6+kpCTVq1dPy5cvz/QhLlyZMjFu3LhM0ybgPaiRNVAn70eNvB81sgYr1slmcnNPAgAAAMALePWcVwAAAOBqhFcAAABYBuEVAAAAlkF4BQAAgGUQXr3YmTNn1LdvX4WGhio8PFx//etfdf78+RzXuXjxooYOHapSpUopJCREDzzwQKY/8jBixAjVr19fdrtd9erVy7SNw4cPy2azZfravHlzQR7eTcFTNZKkH374QS1atFBgYKCio6M1ZcqUgjqsm05h1enXX39V586dFRwcrDJlyuipp57S5cuXXcvXrl2b5bmUlJRUKMdpJdOnT1elSpUUGBioxo0b67vvvsux/6JFi1SjRg0FBgaqTp06Wrp0qdtyY4yef/55lStXTkFBQWrfvr0OHDjg1ic/r4NbnSfqVKlSpUznzMsvv1zgx3azKOgaffbZZ+rYsaPrL5Pu3Lkz0zZy8/2xUBl4rU6dOpm6deuazZs3m2+//dZUqVLF9O7dO8d1hgwZYqKjo82qVavMtm3bzP/8z/+Ypk2buvUZPny4eeutt0y/fv1M3bp1M23j0KFDRpJZuXKl+f33311fly5dKsjDuyl4qkZnz541ZcuWNX379jV79uwx8+fPN0FBQeadd94pyMO7aRRGnS5fvmxq165t2rdvb3bs2GGWLl1qIiIizJgxY1x91qxZYySZ/fv3u51L6enphXasVrBgwQITEBBgZs+ebf773/+aRx991ISHh5vjx49n2X/Dhg3G19fXTJkyxezdu9f84x//MP7+/mb37t2uPi+//LIJCwszS5YsMbt27TJdu3Y1MTEx5s8//3T1yc/r4FbmqTpVrFjRTJgwwe2cOX/+fKEfrxUVRo3+/e9/m/Hjx5t3333XSDI7duzItJ3c/BwrTIRXL7V3714jyWzdutXVtmzZMmOz2czRo0ezXCc5Odn4+/ubRYsWudr27dtnJJlNmzZl6j9u3Lgcw2tWL1j8H0/W6O233zYlSpQwaWlprra///3vpnr16jdwRDenwqrT0qVLjY+Pj0lKSnL1mTFjhgkNDXXVJSO8/vHHH4VwZNbVqFEjM3ToUNfj9PR0ExUVZSZNmpRl/169epnOnTu7tTVu3NgMHjzYGGOM0+k0kZGR5pVXXnEtT05ONna73cyfP98Yk7/Xwa3OE3Uy5kp4ff311wvwSG5eBV2jq2WXBfL6c6wwMG3AS23atEnh4eFq0KCBq619+/by8fHRli1bslxn+/btcjgcat++vautRo0aqlChgjZt2pTnMXTt2lVlypRR8+bN9cUXX+T9IG5ynqzRpk2b1LJlSwUEBLjaYmNjtX//fv3xxx/5OJqbV2HVadOmTapTp47bH0yJjY1VSkqK/vvf/7ptr169eipXrpw6dOigDRs2FOThWc6lS5e0fft2t+fWx8dH7du3z/Yc2LRpk1t/6cpzndH/0KFDSkpKcusTFhamxo0bu9Urr6+DW5mn6pTh5ZdfVqlSpXTXXXfplVdecZuOgysKo0a5UdBZIz+8/i9s3aqSkpJUpkwZtzY/Pz+VLFky2/lySUlJCggIUHh4uFt72bJl8zTHLiQkRK+99pqaNWsmHx8fffrpp+revbuWLFmirl275vlYblaerFFSUpJiYmIybSNjWYkSJXK9rZtdYdUpKSkp01/6u7oGklSuXDnNnDlTDRo0UFpamv71r3+pdevW2rJli+6+++6CODzLOXXqlNLT07N87n788ccs18nuub66FhltOfXJ6+vgVuapOklX5vzffffdKlmypDZu3KgxY8bo999/19SpU2/4uG4mhVGj3Cion2M3gvBaxJ555hlNnjw5xz779u0rotFkLSIiQqNHj3Y9btiwoY4dO6ZXXnnllgivVqgRrFGn6tWrq3r16q7HTZs21c8//6zXX39dH374oQdHBnivq3/+3HnnnQoICNDgwYM1adIkS/0JUxQewmsRe+KJJ9S/f/8c+9x+++2KjIzUiRMn3NovX76sM2fOKDIyMsv1IiMjdenSJSUnJ7v9RnT8+PFs18mtxo0bKzEx8Ya2YRVWqFFkZGSmT3ZmPL7RWluFp+sUGRmZ6VO9ualBo0aNtH79+hzHfTOLiIiQr69vlq/fnOqRU/+Mf48fP65y5cq59cm4W0d+Xge3Mk/VKSuNGzfW5cuXdfjwYbdfBm91hVGj3CjMrJFbzHktYqVLl1aNGjVy/AoICFCTJk2UnJys7du3u9ZdvXq1nE6nGjdunOW269evL39/f61atcrVtn//fv36669q0qTJDY17586dbt9sbmZWqFGTJk20bt06ORwOV1tiYqKqV69+y0wZ8HSdmjRpot27d7sFosTERIWGhqpmzZrZjvtWOpeyEhAQoPr167s9t06nU6tWrcr2HGjSpIlbf+nKc53RPyYmRpGRkW59UlJStGXLFrd65fV1cCvzVJ2ysnPnTvn4+GSa9nGrK4wa5UZhZo1cK5KPhSFfOnXqZO666y6zZcsWs379elO1alW327r87//+r6levbrZsmWLq23IkCGmQoUKZvXq1Wbbtm2mSZMmpkmTJm7bPXDggNmxY4cZPHiwqVatmtmxY4fZsWOH6xPSc+bMMfPmzTP79u0z+/btMy+++KLx8fExs2fPLpoDtxBP1Sg5OdmULVvW9OvXz+zZs8csWLDABAcHc6usbBRGnTJuldWxY0ezc+dOs3z5clO6dGm3W2W9/vrrZsmSJebAgQNm9+7dZuTIkcbHx8esXLmyaA7cSy1YsMDY7XYzZ84cs3fvXjNo0CATHh7uunNDv379zDPPPOPqv2HDBuPn52deffVVs2/fPjNu3Lgsb8EUHh5uPv/8c/PDDz+Ybt26ZXmrrJxeB3DniTpt3LjRvP7662bnzp3m559/Nh999JEpXbq0efjhh4v24C2iMGp0+vRps2PHDvPVV18ZSWbBggVmx44d5vfff3f1yc3PscJEePVip0+fNr179zYhISEmNDTUDBgwwJw7d861POM2FmvWrHG1/fnnn+bxxx83JUqUMMHBwea+++5ze8EZY0yrVq2MpExfhw4dMsZcCa933HGHCQ4ONqGhoaZRo0Zut8TA//FUjYwxZteuXaZ58+bGbreb2267zbz88suFfbiWVVh1Onz4sImLizNBQUEmIiLCPPHEE8bhcLiWT5482VSuXNkEBgaakiVLmtatW5vVq1cX+vFawZtvvmkqVKhgAgICTKNGjczmzZtdy1q1amXi4+Pd+n/88cemWrVqJiAgwNSqVct89dVXbsudTqcZO3asKVu2rLHb7aZdu3Zm//79bn2u9zpAZkVdp+3bt5vGjRubsLAwExgYaO644w7z0ksvmYsXLxbqcVpZQdfo/fffz/Lnz7hx41x9cvP9sTDZjDGmaK7xAgAAADeGOa8AAACwDMIrAAAALIPwCgAAAMsgvAIAAMAyCK8AAACwDMIrAAAALIPwCgAAAMsgvAIAAMAyCK8AcAtJSEhQvXr1PD0MAMg3wisA3IBNmzbJZrOpc+fOuerfunVr2Wy2TF9DhgzRnDlzslx29dfhw4czbfPw4cNufYoXL65atWpp6NChOnDggFvfJ598UqtWrSqIQwcAj+DPwwLADRg4cKBSU1P12Wef6ZdfflFUVFSO/Vu3bq1q1appwoQJbu3BwcHy9/fX2bNnXW3333+/ateu7da3dOnS8vX1dVv38OHDiomJ0cqVK1WrVi2lpqZq9+7deuONN7R582b95z//Ubt27QrgaAHA87jyCgD5dP78eS1cuFCjRo1SmzZtNGfOnFytFxwcrMjISLev0NBQBQUFubUFBARk6nttcL1aqVKlFBkZqdtvv13dunXTypUr1bhxY/31r39Venq6pKynDcyePVu1atWS3W5XuXLlNGzYMNey5ORkDRw4UKVLl1ZoaKjatm2rXbt25fm5AoCCQngFgHz6+OOPFRkZqUaNGqlv376aPXu2vOnNLB8fH40cOVJHjhzR9u3bs+wzY8YMDR06VIMGDdLu3bv1xRdfqEqVKq7lPXv21IkTJ7Rs2TJt375dd999t9q1a6czZ84U1WEAgBvCKwDk03vvvae+fftKkrp3767ff/9d33zzzXXXe/vttxUSEuL2NXfu3EIZY40aNSQpy7mykvTCCy/oiSee0MiRI1WtWjU1bNhQo0aNkiStX79e3333nRYtWqQGDRqoatWqevXVVxUeHq5PPvmkUMYLANfj5+kBAIAV7d+/Xxs3bnRNFQgJCVG3bt303nvvqXXr1jmu27dvXz333HNubWXLli2UcWZcCbbZbJmWnThxQseOHct2PuyuXbt0/vx5lSpVyq39zz//1M8//1zwgwWAXCC8AkA+vPfee2rYsKGqVq3qauvbt6969uypt956S2FhYdmuGxYW5vbWfGHat2+fJCkmJibTsqCgoBzXPX/+vMqVK6e1a9dmWhYeHl4QwwOAPGPaAADk0eXLl/Xvf/9bffr0cWvv2LGjgoODNX/+fA+NzJ3T6dQ///lPxcTE6K677sq0vHjx4qpUqVK2t866++67lZSUJD8/P1WpUsXtKyIiorCHDwBZ4sorAOTRl19+qePHj6t27dras2eP27KWLVvqvffe05AhQ7JdPzU1VUlJSW5tdrtdJUqUuKFxnT59WklJSUpNTdWePXs0bdo0fffdd/rqq6+yvUtBQkKChgwZojJlyiguLk7nzp3Thg0bNHz4cLVv315NmjRR9+7dNWXKFFWrVk3Hjh3TV199pfvuu08NGjS4ofECQH4QXgEgj9577z1JUocOHbLt88MPP+jOO+/Mctm7776rd999160tNjZWy5cvv6FxtW/fXtKVW3FVrFhRbdq00axZs3KcohAfH6+LFy/q9ddf15NPPqmIiAj16NFD0pV5skuXLtVzzz2nAQMG6OTJk4qMjFTLli0LbY4uAFwPf6QAAAAAlsGcVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZRBeAQAAYBmEVwAAAFgG4RUAAACWQXgFAACAZfw/G5hJ8wz/gUIAAAAASUVORK5CYII=\n"},"metadata":{}}],"execution_count":69},{"cell_type":"code","source":"plt.figure(figsize=(8,5))\nplt.hist(df_compare[\"delta_Mean\"], bins=20)\nplt.title(\"Mean Dice Improvement after Post-processing\")\nplt.xlabel(\"Δ Mean Dice\")\nplt.ylabel(\"Count\")\nplt.grid(True)\nplt.show()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-03T22:34:46.763285Z","iopub.execute_input":"2026-02-03T22:34:46.763557Z","iopub.status.idle":"2026-02-03T22:34:46.903975Z","shell.execute_reply.started":"2026-02-03T22:34:46.763532Z","shell.execute_reply":"2026-02-03T22:34:46.903249Z"}},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 800x500 with 1 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\n"},"metadata":{}}],"execution_count":70},{"cell_type":"markdown","source":"## Visualize Best vs Worst prediction overlays","metadata":{}},{"cell_type":"code","source":"def visualize_case_prediction(case_dir, min_et_size=50):\n    pid = os.path.basename(case_dir)\n    imgs_dict = load_case_arrays(case_dir)\n    x_np, y_np, meta = preprocess_case(imgs_dict, do_crop=True)\n    x_t = torch.from_numpy(x_np[None]).float()\n\n    pred = sliding_window_inference(\n        model, x_t, patch_size=PATCH_SIZE, overlap=0.5, num_classes=4, device=device\n    )\n    pred_pp = postprocess_et(pred, min_et_size=min_et_size)\n\n    z = tumor_max_slice(y_np)\n    flair = x_np[0]\n\n    plt.figure(figsize=(16,4))\n    plt.subplot(1,4,1); plt.title(f\"{pid} FLAIR z={z}\")\n    plt.imshow(flair[:,:,z].T, origin=\"lower\", cmap=\"gray\"); plt.axis(\"off\")\n\n    plt.subplot(1,4,2); plt.title(\"GT\")\n    plt.imshow(y_np[:,:,z].T, origin=\"lower\"); plt.axis(\"off\")\n\n    plt.subplot(1,4,3); plt.title(\"Pred raw\")\n    plt.imshow(pred[:,:,z].T, origin=\"lower\"); plt.axis(\"off\")\n\n    plt.subplot(1,4,4); plt.title(\"Pred postproc\")\n    plt.imshow(pred_pp[:,:,z].T, origin=\"lower\"); plt.axis(\"off\")\n    plt.show()\n\nbest_pid = df_pp.iloc[0][\"patient_id\"]\nworst_pid = df_pp.iloc[-1][\"patient_id\"]\n\nbest_dir = id2dir[best_pid]\nworst_dir = id2dir[worst_pid]\n\nprint(\"Best case:\", best_pid)\nvisualize_case_prediction(best_dir)\n\nprint(\"Worst case:\", worst_pid)\nvisualize_case_prediction(worst_dir)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-02-04T00:01:19.062458Z","iopub.execute_input":"2026-02-04T00:01:19.063264Z","iopub.status.idle":"2026-02-04T00:01:19.073248Z","shell.execute_reply.started":"2026-02-04T00:01:19.063228Z","shell.execute_reply":"2026-02-04T00:01:19.072375Z"}},"outputs":[{"traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)","\u001b[0;32m/tmp/ipykernel_55/1718211873.py\u001b[0m in \u001b[0;36m<cell line: 0>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     27\u001b[0m     \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     28\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 29\u001b[0;31m \u001b[0mbest_pid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf_pp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"patient_id\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     30\u001b[0m \u001b[0mworst_pid\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf_pp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"patient_id\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     31\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mNameError\u001b[0m: name 'df_pp' is not defined"],"ename":"NameError","evalue":"name 'df_pp' is not defined","output_type":"error"}],"execution_count":2}]}