From 7a63c7acd3e3730bcb2ff9d0ee6d6fff9f8d0a4a Mon Sep 17 00:00:00 2001
From: Celina <korzerce84997@th-nuernberg.de>
Date: Tue, 24 Feb 2026 17:54:23 +0100
Subject: [PATCH] CNN test and evaluation

---
 .../CNN/CNN_crossVal_EarlyFusion_Filter.ipynb | 1265 +++++++++--------
 .../CNN_crossVal_HybridFusion_Test_Eval.ipynb |  628 ++++++++
 2 files changed, 1283 insertions(+), 610 deletions(-)
 create mode 100644 model_training/CNN/CNN_crossVal_HybridFusion_Test_Eval.ipynb

diff --git a/model_training/CNN/CNN_crossVal_EarlyFusion_Filter.ipynb b/model_training/CNN/CNN_crossVal_EarlyFusion_Filter.ipynb
index 9a33fc7..9124951 100644
--- a/model_training/CNN/CNN_crossVal_EarlyFusion_Filter.ipynb
+++ b/model_training/CNN/CNN_crossVal_EarlyFusion_Filter.ipynb
@@ -10,10 +10,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 1,
    "id": "99294260",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2026-02-24 17:06:50.836779: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+      "2026-02-24 17:06:50.950163: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+      "2026-02-24 17:06:50.984137: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+      "2026-02-24 17:06:51.218809: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+      "2026-02-24 17:06:52.767385: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
+     ]
+    }
+   ],
    "source": [
     "import pandas as pd \n",
     "import numpy as np \n",
@@ -41,7 +54,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 2,
    "id": "6e49d281",
    "metadata": {},
    "outputs": [],
@@ -62,7 +75,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 3,
    "id": "870f01c3",
    "metadata": {},
    "outputs": [],
@@ -82,7 +95,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 4,
    "id": "38848515",
    "metadata": {},
    "outputs": [],
@@ -110,7 +123,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 5,
    "id": "3e542dfd",
    "metadata": {},
    "outputs": [
@@ -142,7 +155,7 @@
     }
    ],
    "source": [
-    "FILTER_SUBSETS = False\n",
+    "FILTER_SUBSETS = True\n",
     "\n",
     "if(FILTER_SUBSETS):\n",
     "    # Special filter: Keep only specific subsets\n",
@@ -184,7 +197,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 6,
    "id": "5edb00a0",
    "metadata": {},
    "outputs": [
@@ -254,7 +267,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 7,
    "id": "e4a7f496",
    "metadata": {},
    "outputs": [],
@@ -293,7 +306,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 8,
    "id": "90658000",
    "metadata": {},
    "outputs": [
@@ -327,6 +340,199 @@
       " [1.02545725]]\n"
      ]
     },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
+      "I0000 00:00:1771949218.700787      44 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771949218.933970      44 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771949218.935604      44 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771949218.941580      44 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771949218.942914      44 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771949218.944240      44 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771949219.095445      44 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771949219.097769      44 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "2026-02-24 17:06:59.099015: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:47] Overriding orig_value setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\n",
+      "I0000 00:00:1771949219.099113      44 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "2026-02-24 17:06:59.101034: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 38435 MB memory:  -> device: 0, name: NVIDIA A100 80GB PCIe MIG 3g.40gb, pci bus id: 0000:1e:00.0, compute capability: 8.0\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential\"</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1mModel: \"sequential\"\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ conv1d (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv1D</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">33</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)         │           <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span> │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ batch_normalization             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">33</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)         │           <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span> │\n",
+       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pooling1d (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling1D</span>)    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)         │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1d_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv1D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">14</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)         │         <span style=\"color: #00af00; text-decoration-color: #00af00\">6,208</span> │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ batch_normalization_1           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">14</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)         │           <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │\n",
+       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ global_average_pooling1d        │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)             │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
+       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">GlobalAveragePooling1D</span>)        │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)             │         <span style=\"color: #00af00; text-decoration-color: #00af00\">2,080</span> │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dropout (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)             │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>)              │            <span style=\"color: #00af00; text-decoration-color: #00af00\">33</span> │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ conv1d (\u001b[38;5;33mConv1D\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m33\u001b[0m, \u001b[38;5;34m32\u001b[0m)         │           \u001b[38;5;34m128\u001b[0m │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ batch_normalization             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m33\u001b[0m, \u001b[38;5;34m32\u001b[0m)         │           \u001b[38;5;34m128\u001b[0m │\n",
+       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pooling1d (\u001b[38;5;33mMaxPooling1D\u001b[0m)    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m32\u001b[0m)         │             \u001b[38;5;34m0\u001b[0m │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv1d_1 (\u001b[38;5;33mConv1D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m64\u001b[0m)         │         \u001b[38;5;34m6,208\u001b[0m │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ batch_normalization_1           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m64\u001b[0m)         │           \u001b[38;5;34m256\u001b[0m │\n",
+       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ global_average_pooling1d        │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m)             │             \u001b[38;5;34m0\u001b[0m │\n",
+       "│ (\u001b[38;5;33mGlobalAveragePooling1D\u001b[0m)        │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense (\u001b[38;5;33mDense\u001b[0m)                   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m)             │         \u001b[38;5;34m2,080\u001b[0m │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dropout (\u001b[38;5;33mDropout\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m)             │             \u001b[38;5;34m0\u001b[0m │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_1 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m)              │            \u001b[38;5;34m33\u001b[0m │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">8,833</span> (34.50 KB)\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m8,833\u001b[0m (34.50 KB)\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">8,641</span> (33.75 KB)\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m8,641\u001b[0m (33.75 KB)\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">192</span> (768.00 B)\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m192\u001b[0m (768.00 B)\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
+      "I0000 00:00:1771949221.315677     237 service.cc:146] XLA service 0x7f5f54010a60 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:\n",
+      "I0000 00:00:1771949221.315749     237 service.cc:154]   StreamExecutor device (0): NVIDIA A100 80GB PCIe MIG 3g.40gb, Compute Capability 8.0\n",
+      "2026-02-24 17:07:01.372828: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:268] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.\n",
+      "2026-02-24 17:07:01.614024: I external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:531] Loaded cuDNN version 8907\n",
+      "I0000 00:00:1771949224.191377     237 device_compiler.h:188] Compiled cluster using XLA!  This line is logged at most once for the lifetime of the process.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fold 1 - Val Loss: 0.2056, Val Acc: 0.9427, Val AUC: 0.9874\n",
+      "\u001b[1m50/50\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 5ms/step \n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Konfusionsmatrix Fold 1:\n",
+      "[[572  66]\n",
+      " [ 25 925]]\n",
+      "\n",
+      "\n",
+      "--- Fold 2 ---\n",
+      "Train-Subjects: [ 2  3  4  5  7  8  9 12 13 14 18 20 22 26 27 28]\n",
+      "Val-Subjects: [ 0 16 17 21]\n",
+      "Train Mittelwerte (erste 5 Features): [[-1.21896167e-14]\n",
+      " [ 3.99953317e-14]\n",
+      " [ 1.58858053e-14]\n",
+      " [ 1.39544029e-15]\n",
+      " [-1.05876899e-15]]\n",
+      "Train Std (erste 5 Features): [[1.]\n",
+      " [1.]\n",
+      " [1.]\n",
+      " [1.]\n",
+      " [1.]]\n",
+      "Val Mittelwerte (erste 5 Features): [[-0.1614286 ]\n",
+      " [-0.08187427]\n",
+      " [-0.05609159]\n",
+      " [-0.08758144]\n",
+      " [-0.24994359]]\n",
+      "Val Std (erste 5 Features): [[1.06628815]\n",
+      " [1.05958783]\n",
+      " [0.96502939]\n",
+      " [1.01240686]\n",
+      " [0.73864545]]\n"
+     ]
+    },
     {
      "data": {
       "text/html": [
@@ -442,13 +648,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Fold 1 - Val Loss: 0.2047, Val Acc: 0.9458, Val AUC: 0.9874\n",
-      "\u001b[1m50/50\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 6ms/step \n"
+      "Fold 2 - Val Loss: 0.2387, Val Acc: 0.9279, Val AUC: 0.9763\n",
+      "\u001b[1m50/50\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 5ms/step\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 600x500 with 2 Axes>"
       ]
@@ -460,34 +666,34 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Konfusionsmatrix Fold 1:\n",
-      "[[578  60]\n",
-      " [ 26 924]]\n",
+      "Konfusionsmatrix Fold 2:\n",
+      "[[581  87]\n",
+      " [ 28 900]]\n",
       "\n",
       "\n",
-      "--- Fold 2 ---\n",
-      "Train-Subjects: [ 2  3  4  5  7  8  9 12 13 14 18 20 22 26 27 28]\n",
-      "Val-Subjects: [ 0 16 17 21]\n",
-      "Train Mittelwerte (erste 5 Features): [[-1.21896167e-14]\n",
-      " [ 3.99953317e-14]\n",
-      " [ 1.58858053e-14]\n",
-      " [ 1.39544029e-15]\n",
-      " [-1.05876899e-15]]\n",
+      "--- Fold 3 ---\n",
+      "Train-Subjects: [ 0  2  3  4  5  7 12 13 16 17 20 21 22 26 27 28]\n",
+      "Val-Subjects: [ 8  9 14 18]\n",
+      "Train Mittelwerte (erste 5 Features): [[-7.15327970e-16]\n",
+      " [ 3.87293138e-14]\n",
+      " [ 2.45055027e-15]\n",
+      " [-1.17281793e-14]\n",
+      " [ 3.58282615e-17]]\n",
       "Train Std (erste 5 Features): [[1.]\n",
       " [1.]\n",
       " [1.]\n",
       " [1.]\n",
       " [1.]]\n",
-      "Val Mittelwerte (erste 5 Features): [[-0.1614286 ]\n",
-      " [-0.08187427]\n",
-      " [-0.05609159]\n",
-      " [-0.08758144]\n",
-      " [-0.24994359]]\n",
-      "Val Std (erste 5 Features): [[1.06628815]\n",
-      " [1.05958783]\n",
-      " [0.96502939]\n",
-      " [1.01240686]\n",
-      " [0.73864545]]\n"
+      "Val Mittelwerte (erste 5 Features): [[-0.0572603 ]\n",
+      " [-0.05167969]\n",
+      " [ 0.06734314]\n",
+      " [ 0.04175176]\n",
+      " [ 0.14159594]]\n",
+      "Val Std (erste 5 Features): [[1.04792308]\n",
+      " [1.02732376]\n",
+      " [1.06024534]\n",
+      " [1.01980244]\n",
+      " [1.11306852]]\n"
      ]
     },
     {
@@ -605,13 +811,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Fold 2 - Val Loss: 0.2554, Val Acc: 0.9185, Val AUC: 0.9724\n",
-      "\u001b[1m50/50\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 6ms/step\n"
+      "Fold 3 - Val Loss: 0.2040, Val Acc: 0.9450, Val AUC: 0.9878\n",
+      "\u001b[1m51/51\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 600x500 with 2 Axes>"
       ]
@@ -623,34 +829,34 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Konfusionsmatrix Fold 2:\n",
-      "[[566 102]\n",
-      " [ 28 900]]\n",
+      "Konfusionsmatrix Fold 3:\n",
+      "[[598  58]\n",
+      " [ 30 915]]\n",
       "\n",
       "\n",
-      "--- Fold 3 ---\n",
-      "Train-Subjects: [ 0  2  3  4  5  7 12 13 16 17 20 21 22 26 27 28]\n",
-      "Val-Subjects: [ 8  9 14 18]\n",
-      "Train Mittelwerte (erste 5 Features): [[-7.15327970e-16]\n",
-      " [ 3.87293138e-14]\n",
-      " [ 2.45055027e-15]\n",
-      " [-1.17281793e-14]\n",
-      " [ 3.58282615e-17]]\n",
+      "--- Fold 4 ---\n",
+      "Train-Subjects: [ 0  2  3  5  7  8  9 12 13 14 16 17 18 20 21 27]\n",
+      "Val-Subjects: [ 4 22 26 28]\n",
+      "Train Mittelwerte (erste 5 Features): [[ 1.23445813e-14]\n",
+      " [ 1.70513636e-14]\n",
+      " [ 5.98385175e-15]\n",
+      " [-8.32006628e-15]\n",
+      " [-9.28112373e-16]]\n",
       "Train Std (erste 5 Features): [[1.]\n",
       " [1.]\n",
       " [1.]\n",
       " [1.]\n",
       " [1.]]\n",
-      "Val Mittelwerte (erste 5 Features): [[-0.0572603 ]\n",
-      " [-0.05167969]\n",
-      " [ 0.06734314]\n",
-      " [ 0.04175176]\n",
-      " [ 0.14159594]]\n",
-      "Val Std (erste 5 Features): [[1.04792308]\n",
-      " [1.02732376]\n",
-      " [1.06024534]\n",
-      " [1.01980244]\n",
-      " [1.11306852]]\n"
+      "Val Mittelwerte (erste 5 Features): [[ 0.03560763]\n",
+      " [-0.04014632]\n",
+      " [-0.02303064]\n",
+      " [ 0.02336224]\n",
+      " [ 0.13980282]]\n",
+      "Val Std (erste 5 Features): [[1.01651673]\n",
+      " [1.17441107]\n",
+      " [0.92628917]\n",
+      " [1.04731846]\n",
+      " [1.05993683]]\n"
      ]
     },
     {
@@ -768,13 +974,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Fold 3 - Val Loss: 0.2162, Val Acc: 0.9425, Val AUC: 0.9861\n",
-      "\u001b[1m51/51\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 5ms/step\n"
+      "Fold 4 - Val Loss: 0.1392, Val Acc: 0.9691, Val AUC: 0.9947\n",
+      "\u001b[1m50/50\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 6ms/step\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 600x500 with 2 Axes>"
       ]
@@ -786,34 +992,34 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Konfusionsmatrix Fold 3:\n",
-      "[[593  63]\n",
-      " [ 29 916]]\n",
+      "Konfusionsmatrix Fold 4:\n",
+      "[[633  29]\n",
+      " [ 20 904]]\n",
       "\n",
       "\n",
-      "--- Fold 4 ---\n",
-      "Train-Subjects: [ 0  2  3  5  7  8  9 12 13 14 16 17 18 20 21 27]\n",
-      "Val-Subjects: [ 4 22 26 28]\n",
-      "Train Mittelwerte (erste 5 Features): [[ 1.23445813e-14]\n",
-      " [ 1.70513636e-14]\n",
-      " [ 5.98385175e-15]\n",
-      " [-8.32006628e-15]\n",
-      " [-9.28112373e-16]]\n",
+      "--- Fold 5 ---\n",
+      "Train-Subjects: [ 0  2  4  5  8  9 12 13 14 16 17 18 21 22 26 28]\n",
+      "Val-Subjects: [ 3  7 20 27]\n",
+      "Train Mittelwerte (erste 5 Features): [[-5.44187901e-15]\n",
+      " [ 4.35398678e-14]\n",
+      " [ 1.23994364e-15]\n",
+      " [ 7.79327421e-15]\n",
+      " [ 2.17670629e-15]]\n",
       "Train Std (erste 5 Features): [[1.]\n",
       " [1.]\n",
       " [1.]\n",
       " [1.]\n",
       " [1.]]\n",
-      "Val Mittelwerte (erste 5 Features): [[ 0.03560763]\n",
-      " [-0.04014632]\n",
-      " [-0.02303064]\n",
-      " [ 0.02336224]\n",
-      " [ 0.13980282]]\n",
-      "Val Std (erste 5 Features): [[1.01651673]\n",
-      " [1.17441107]\n",
-      " [0.92628917]\n",
-      " [1.04731846]\n",
-      " [1.05993683]]\n"
+      "Val Mittelwerte (erste 5 Features): [[0.09829466]\n",
+      " [0.09221573]\n",
+      " [0.07761458]\n",
+      " [0.03261047]\n",
+      " [0.00553267]]\n",
+      "Val Std (erste 5 Features): [[0.93842973]\n",
+      " [0.89386191]\n",
+      " [1.0290861 ]\n",
+      " [0.9948385 ]\n",
+      " [1.0161051 ]]\n"
      ]
     },
     {
@@ -931,13 +1137,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Fold 4 - Val Loss: 0.1395, Val Acc: 0.9697, Val AUC: 0.9952\n",
-      "\u001b[1m50/50\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 6ms/step \n"
+      "Fold 5 - Val Loss: 0.2563, Val Acc: 0.9282, Val AUC: 0.9764\n",
+      "\u001b[1m51/51\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 600x500 with 2 Axes>"
       ]
@@ -949,36 +1155,197 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Konfusionsmatrix Fold 4:\n",
-      "[[633  29]\n",
-      " [ 19 905]]\n",
+      "Konfusionsmatrix Fold 5:\n",
+      "[[608  55]\n",
+      " [ 60 878]]\n",
       "\n",
-      "\n",
-      "--- Fold 5 ---\n",
-      "Train-Subjects: [ 0  2  4  5  8  9 12 13 14 16 17 18 21 22 26 28]\n",
-      "Val-Subjects: [ 3  7 20 27]\n",
-      "Train Mittelwerte (erste 5 Features): [[-5.44187901e-15]\n",
-      " [ 4.35398678e-14]\n",
-      " [ 1.23994364e-15]\n",
-      " [ 7.79327421e-15]\n",
-      " [ 2.17670629e-15]]\n",
-      "Train Std (erste 5 Features): [[1.]\n",
-      " [1.]\n",
-      " [1.]\n",
-      " [1.]\n",
-      " [1.]]\n",
-      "Val Mittelwerte (erste 5 Features): [[0.09829466]\n",
-      " [0.09221573]\n",
-      " [0.07761458]\n",
-      " [0.03261047]\n",
-      " [0.00553267]]\n",
-      "Val Std (erste 5 Features): [[0.93842973]\n",
-      " [0.89386191]\n",
-      " [1.0290861 ]\n",
-      " [0.9948385 ]\n",
-      " [1.0161051 ]]\n"
+      "Aggregierte Konfusionsmatrix über alle Folds:\n",
+      "[[2992  295]\n",
+      " [ 163 4522]]\n"
      ]
     },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "gkf = GroupKFold(n_splits=5) \n",
+    "cv_histories = [] \n",
+    "cv_results = [] \n",
+    "fold_subjects = []\n",
+    "all_conf_matrices = []\n",
+    "\n",
+    "for fold, (train_idx, val_idx) in enumerate(gkf.split(X, y, groups)):\n",
+    "    train_subjects = np.unique(groups[train_idx]) \n",
+    "    val_subjects = np.unique(groups[val_idx]) \n",
+    "    fold_subjects.append({\"Fold\": fold+1, \n",
+    "                          \"Train_Subjects\": train_subjects, \n",
+    "                          \"Val_Subjects\": val_subjects}) \n",
+    "    \n",
+    "    print(f\"\\n--- Fold {fold+1} ---\") \n",
+    "    print(\"Train-Subjects:\", train_subjects) \n",
+    "    print(\"Val-Subjects:\", val_subjects) \n",
+    "\n",
+    "    #Split\n",
+    "    X_train, X_val = X[train_idx], X[val_idx] \n",
+    "    y_train, y_val = y[train_idx], y[val_idx] # Normalisierung pro Fold \n",
+    "\n",
+    "    #Normalisierung pro Fold\n",
+    "    scaler = StandardScaler() \n",
+    "    X_train = scaler.fit_transform(X_train.reshape(len(X_train), -1)).reshape(X_train.shape) \n",
+    "    X_val = scaler.transform(X_val.reshape(len(X_val), -1)).reshape(X_val.shape) \n",
+    "\n",
+    "    # Plausibilitäts-Check \n",
+    "    print(\"Train Mittelwerte (erste 5 Features):\", X_train.mean(axis=0)[:5]) \n",
+    "    print(\"Train Std (erste 5 Features):\", X_train.std(axis=0)[:5]) \n",
+    "    print(\"Val Mittelwerte (erste 5 Features):\", X_val.mean(axis=0)[:5]) \n",
+    "    print(\"Val Std (erste 5 Features):\", X_val.std(axis=0)[:5]) \n",
+    "\n",
+    "    # Modell \n",
+    "    model = build_model(input_shape=(len(feature_columns),1), lr=1e-4) \n",
+    "    model.summary()  \n",
+    "\n",
+    "    callbacks = [ \n",
+    "        tf.keras.callbacks.EarlyStopping(monitor=\"val_loss\", patience=10, restore_best_weights=True), \n",
+    "        tf.keras.callbacks.ReduceLROnPlateau(monitor=\"val_loss\", factor=0.5, patience=5, min_lr=1e-6) \n",
+    "    ] \n",
+    "\n",
+    "    history = model.fit( \n",
+    "        X_train, y_train, \n",
+    "        validation_data=(X_val, y_val), \n",
+    "        epochs=100, \n",
+    "        batch_size=16, \n",
+    "        callbacks=callbacks, \n",
+    "        verbose=0 \n",
+    "    ) \n",
+    "\n",
+    "    cv_histories.append(history.history) \n",
+    "    scores = model.evaluate(X_val, y_val, verbose=0) \n",
+    "    cv_results.append(scores) \n",
+    "    print(f\"Fold {fold+1} - Val Loss: {scores[0]:.4f}, Val Acc: {scores[1]:.4f}, Val AUC: {scores[2]:.4f}\")\n",
+    "\n",
+    "\n",
+    "    #Konfusionsmatrix \n",
+    "    y_pred = (model.predict(X_val) > 0.5).astype(int) \n",
+    "    cm = confusion_matrix(y_val, y_pred) \n",
+    "    all_conf_matrices.append(cm) \n",
+    "\n",
+    "    #Heatmap \n",
+    "    plt.figure(figsize=(6,5)) \n",
+    "    sns.heatmap(cm, annot=True, fmt=\"d\", cmap=\"Blues\", \n",
+    "                xticklabels=[\"Pred 0\", \"Pred 1\"], \n",
+    "                yticklabels=[\"True 0\", \"True 1\"]) \n",
+    "    plt.title(f\"Konfusionsmatrix – Fold {fold+1}\") \n",
+    "    plt.xlabel(\"Predicted\") \n",
+    "    plt.ylabel(\"True\") \n",
+    "    plt.show()\n",
+    "    \n",
+    "    print(f\"Konfusionsmatrix Fold {fold+1}:\\n{cm}\\n\") \n",
+    "    \n",
+    "# Aggregierte Matrix \n",
+    "agg_cm = sum(all_conf_matrices) \n",
+    "print(\"Aggregierte Konfusionsmatrix über alle Folds:\") \n",
+    "print(agg_cm)\n",
+    "plt.figure(figsize=(6,5))\n",
+    "sns.heatmap(agg_cm, annot=True, fmt=\"d\", cmap=\"Purples\",\n",
+    "            xticklabels=[\"Pred 0\", \"Pred 1\"],\n",
+    "            yticklabels=[\"True 0\", \"True 1\"])\n",
+    "plt.title(\"Aggregierte Konfusionsmatrix – alle Folds\")\n",
+    "plt.xlabel(\"Predicted\")\n",
+    "plt.ylabel(\"True\")\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d10b7e78",
+   "metadata": {},
+   "source": [
+    "Results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "9aeba7f4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "=== Cross-Validation Ergebnisse ===\n",
+      "Durchschnittlicher Val-Loss: 0.2088\n",
+      "Durchschnittliche Val-Accuracy: 0.9426\n",
+      "Durchschnittliche Val-AUC: 0.9845\n",
+      "\n",
+      "=== Ergebnis-Tabelle ===\n",
+      "  Fold  Val Loss  Val Accuracy   Val AUC\n",
+      "0    1  0.205568      0.942695  0.987412\n",
+      "1    2  0.238745      0.927945  0.976282\n",
+      "2    3  0.203980      0.945034  0.987811\n",
+      "3    4  0.139174      0.969105  0.994727\n",
+      "4    5  0.256341      0.928170  0.976373\n",
+      "5    Ø  0.208762      0.942590  0.984521\n",
+      "Ergebnisse gespeichert als 'cnn_crossVal_Filter_True.csv'\n"
+     ]
+    }
+   ],
+   "source": [
+    "#results\n",
+    "cv_results = np.array(cv_results) \n",
+    "print(\"\\n=== Cross-Validation Ergebnisse ===\") \n",
+    "print(f\"Durchschnittlicher Val-Loss: {cv_results[:,0].mean():.4f}\") \n",
+    "print(f\"Durchschnittliche Val-Accuracy: {cv_results[:,1].mean():.4f}\") \n",
+    "print(f\"Durchschnittliche Val-AUC: {cv_results[:,2].mean():.4f}\")\n",
+    "\n",
+    "#Ergebnis-Tabelle erstellen\n",
+    "results_table = pd.DataFrame({ \n",
+    "    \"Fold\": np.arange(1, len(cv_results)+1), \n",
+    "    \"Val Loss\": cv_results[:,0], \n",
+    "    \"Val Accuracy\": cv_results[:,1], \n",
+    "    \"Val AUC\": cv_results[:,2] }) \n",
+    "\n",
+    "# Durchschnittszeile hinzufügen \n",
+    "avg_row = pd.DataFrame({ \n",
+    "    \"Fold\": [\"Ø\"], \n",
+    "    \"Val Loss\": [cv_results[:,0].mean()], \n",
+    "    \"Val Accuracy\": [cv_results[:,1].mean()], \n",
+    "    \"Val AUC\": [cv_results[:,2].mean()] \n",
+    "}) \n",
+    "\n",
+    "results_table = pd.concat([results_table, avg_row], ignore_index=True) \n",
+    "\n",
+    "print(\"\\n=== Ergebnis-Tabelle ===\") \n",
+    "print(results_table) \n",
+    "\n",
+    "#Tabelle speichern \n",
+    "results_table.to_csv(\"cnn_crossVal_Filter_True.csv\", index=False) \n",
+    "print(\"Ergebnisse gespeichert als 'cnn_crossVal_Filter_True.csv'\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d2f6de79",
+   "metadata": {},
+   "source": [
+    "Finales Modell auf alle Daten trainieren"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "6e403e5f",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
       "text/html": [
@@ -1090,330 +1457,6 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Fold 5 - Val Loss: 0.2500, Val Acc: 0.9363, Val AUC: 0.9773\n",
-      "\u001b[1m51/51\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step \n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 600x500 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Konfusionsmatrix Fold 5:\n",
-      "[[615  48]\n",
-      " [ 54 884]]\n",
-      "\n",
-      "Aggregierte Konfusionsmatrix über alle Folds:\n",
-      "[[2985  302]\n",
-      " [ 156 4529]]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 600x500 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "gkf = GroupKFold(n_splits=5) \n",
-    "cv_histories = [] \n",
-    "cv_results = [] \n",
-    "fold_subjects = []\n",
-    "all_conf_matrices = []\n",
-    "\n",
-    "for fold, (train_idx, val_idx) in enumerate(gkf.split(X, y, groups)):\n",
-    "    train_subjects = np.unique(groups[train_idx]) \n",
-    "    val_subjects = np.unique(groups[val_idx]) \n",
-    "    fold_subjects.append({\"Fold\": fold+1, \n",
-    "                          \"Train_Subjects\": train_subjects, \n",
-    "                          \"Val_Subjects\": val_subjects}) \n",
-    "    \n",
-    "    print(f\"\\n--- Fold {fold+1} ---\") \n",
-    "    print(\"Train-Subjects:\", train_subjects) \n",
-    "    print(\"Val-Subjects:\", val_subjects) \n",
-    "\n",
-    "    #Split\n",
-    "    X_train, X_val = X[train_idx], X[val_idx] \n",
-    "    y_train, y_val = y[train_idx], y[val_idx] # Normalisierung pro Fold \n",
-    "\n",
-    "    #Normalisierung pro Fold\n",
-    "    scaler = StandardScaler() \n",
-    "    X_train = scaler.fit_transform(X_train.reshape(len(X_train), -1)).reshape(X_train.shape) \n",
-    "    X_val = scaler.transform(X_val.reshape(len(X_val), -1)).reshape(X_val.shape) \n",
-    "\n",
-    "    # Plausibilitäts-Check \n",
-    "    print(\"Train Mittelwerte (erste 5 Features):\", X_train.mean(axis=0)[:5]) \n",
-    "    print(\"Train Std (erste 5 Features):\", X_train.std(axis=0)[:5]) \n",
-    "    print(\"Val Mittelwerte (erste 5 Features):\", X_val.mean(axis=0)[:5]) \n",
-    "    print(\"Val Std (erste 5 Features):\", X_val.std(axis=0)[:5]) \n",
-    "\n",
-    "    # Modell \n",
-    "    model = build_model(input_shape=(len(feature_columns),1), lr=1e-4) \n",
-    "    model.summary()  \n",
-    "\n",
-    "    callbacks = [ \n",
-    "        tf.keras.callbacks.EarlyStopping(monitor=\"val_loss\", patience=10, restore_best_weights=True), \n",
-    "        tf.keras.callbacks.ReduceLROnPlateau(monitor=\"val_loss\", factor=0.5, patience=5, min_lr=1e-6) \n",
-    "    ] \n",
-    "\n",
-    "    history = model.fit( \n",
-    "        X_train, y_train, \n",
-    "        validation_data=(X_val, y_val), \n",
-    "        epochs=100, \n",
-    "        batch_size=16, \n",
-    "        callbacks=callbacks, \n",
-    "        verbose=0 \n",
-    "    ) \n",
-    "\n",
-    "    cv_histories.append(history.history) \n",
-    "    scores = model.evaluate(X_val, y_val, verbose=0) \n",
-    "    cv_results.append(scores) \n",
-    "    print(f\"Fold {fold+1} - Val Loss: {scores[0]:.4f}, Val Acc: {scores[1]:.4f}, Val AUC: {scores[2]:.4f}\")\n",
-    "\n",
-    "\n",
-    "    #Konfusionsmatrix \n",
-    "    y_pred = (model.predict(X_val) > 0.5).astype(int) \n",
-    "    cm = confusion_matrix(y_val, y_pred) \n",
-    "    all_conf_matrices.append(cm) \n",
-    "\n",
-    "    #Heatmap \n",
-    "    plt.figure(figsize=(6,5)) \n",
-    "    sns.heatmap(cm, annot=True, fmt=\"d\", cmap=\"Blues\", \n",
-    "                xticklabels=[\"Pred 0\", \"Pred 1\"], \n",
-    "                yticklabels=[\"True 0\", \"True 1\"]) \n",
-    "    plt.title(f\"Konfusionsmatrix – Fold {fold+1}\") \n",
-    "    plt.xlabel(\"Predicted\") \n",
-    "    plt.ylabel(\"True\") \n",
-    "    plt.show()\n",
-    "    \n",
-    "    print(f\"Konfusionsmatrix Fold {fold+1}:\\n{cm}\\n\") \n",
-    "    \n",
-    "# Aggregierte Matrix \n",
-    "agg_cm = sum(all_conf_matrices) \n",
-    "print(\"Aggregierte Konfusionsmatrix über alle Folds:\") \n",
-    "print(agg_cm)\n",
-    "plt.figure(figsize=(6,5))\n",
-    "sns.heatmap(agg_cm, annot=True, fmt=\"d\", cmap=\"Purples\",\n",
-    "            xticklabels=[\"Pred 0\", \"Pred 1\"],\n",
-    "            yticklabels=[\"True 0\", \"True 1\"])\n",
-    "plt.title(\"Aggregierte Konfusionsmatrix – alle Folds\")\n",
-    "plt.xlabel(\"Predicted\")\n",
-    "plt.ylabel(\"True\")\n",
-    "plt.show()\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d10b7e78",
-   "metadata": {},
-   "source": [
-    "Results"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "id": "9aeba7f4",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "=== Cross-Validation Ergebnisse ===\n",
-      "Durchschnittlicher Val-Loss: 0.2132\n",
-      "Durchschnittliche Val-Accuracy: 0.9426\n",
-      "Durchschnittliche Val-AUC: 0.9837\n",
-      "\n",
-      "=== Ergebnis-Tabelle ===\n",
-      "  Fold  Val Loss  Val Accuracy   Val AUC\n",
-      "0    1  0.204724      0.945844  0.987373\n",
-      "1    2  0.255400      0.918546  0.972358\n",
-      "2    3  0.216190      0.942536  0.986086\n",
-      "3    4  0.139484      0.969735  0.995214\n",
-      "4    5  0.250006      0.936290  0.977334\n",
-      "5    Ø  0.213161      0.942590  0.983673\n",
-      "Ergebnisse gespeichert als 'cnn_crossVal_Filter.csv'\n"
-     ]
-    }
-   ],
-   "source": [
-    "#results\n",
-    "cv_results = np.array(cv_results) \n",
-    "print(\"\\n=== Cross-Validation Ergebnisse ===\") \n",
-    "print(f\"Durchschnittlicher Val-Loss: {cv_results[:,0].mean():.4f}\") \n",
-    "print(f\"Durchschnittliche Val-Accuracy: {cv_results[:,1].mean():.4f}\") \n",
-    "print(f\"Durchschnittliche Val-AUC: {cv_results[:,2].mean():.4f}\")\n",
-    "\n",
-    "#Ergebnis-Tabelle erstellen\n",
-    "results_table = pd.DataFrame({ \n",
-    "    \"Fold\": np.arange(1, len(cv_results)+1), \n",
-    "    \"Val Loss\": cv_results[:,0], \n",
-    "    \"Val Accuracy\": cv_results[:,1], \n",
-    "    \"Val AUC\": cv_results[:,2] }) \n",
-    "\n",
-    "# Durchschnittszeile hinzufügen \n",
-    "avg_row = pd.DataFrame({ \n",
-    "    \"Fold\": [\"Ø\"], \n",
-    "    \"Val Loss\": [cv_results[:,0].mean()], \n",
-    "    \"Val Accuracy\": [cv_results[:,1].mean()], \n",
-    "    \"Val AUC\": [cv_results[:,2].mean()] \n",
-    "}) \n",
-    "\n",
-    "results_table = pd.concat([results_table, avg_row], ignore_index=True) \n",
-    "\n",
-    "print(\"\\n=== Ergebnis-Tabelle ===\") \n",
-    "print(results_table) \n",
-    "\n",
-    "#Tabelle speichern \n",
-    "results_table.to_csv(\"cnn_crossVal_Filter.csv\", index=False) \n",
-    "print(\"Ergebnisse gespeichert als 'cnn_crossVal_Filter.csv'\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d2f6de79",
-   "metadata": {},
-   "source": [
-    "Finales Modell auf alle Daten trainieren"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "id": "6e403e5f",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_6\"</span>\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[1mModel: \"sequential_6\"\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
-       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
-       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
-       "│ conv1d_12 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv1D</span>)              │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">33</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)         │           <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span> │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ batch_normalization_12          │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">33</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)         │           <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span> │\n",
-       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ max_pooling1d_6 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling1D</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">16</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)         │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ conv1d_13 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv1D</span>)              │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">14</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)         │         <span style=\"color: #00af00; text-decoration-color: #00af00\">6,208</span> │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ batch_normalization_13          │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">14</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)         │           <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │\n",
-       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)            │                        │               │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ global_average_pooling1d_6      │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)             │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
-       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">GlobalAveragePooling1D</span>)        │                        │               │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ dense_12 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)             │         <span style=\"color: #00af00; text-decoration-color: #00af00\">2,080</span> │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ dropout_6 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)             │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ dense_13 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1</span>)              │            <span style=\"color: #00af00; text-decoration-color: #00af00\">33</span> │\n",
-       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
-       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
-       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
-       "│ conv1d_12 (\u001b[38;5;33mConv1D\u001b[0m)              │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m33\u001b[0m, \u001b[38;5;34m32\u001b[0m)         │           \u001b[38;5;34m128\u001b[0m │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ batch_normalization_12          │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m33\u001b[0m, \u001b[38;5;34m32\u001b[0m)         │           \u001b[38;5;34m128\u001b[0m │\n",
-       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ max_pooling1d_6 (\u001b[38;5;33mMaxPooling1D\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m16\u001b[0m, \u001b[38;5;34m32\u001b[0m)         │             \u001b[38;5;34m0\u001b[0m │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ conv1d_13 (\u001b[38;5;33mConv1D\u001b[0m)              │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m64\u001b[0m)         │         \u001b[38;5;34m6,208\u001b[0m │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ batch_normalization_13          │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m14\u001b[0m, \u001b[38;5;34m64\u001b[0m)         │           \u001b[38;5;34m256\u001b[0m │\n",
-       "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)            │                        │               │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ global_average_pooling1d_6      │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m)             │             \u001b[38;5;34m0\u001b[0m │\n",
-       "│ (\u001b[38;5;33mGlobalAveragePooling1D\u001b[0m)        │                        │               │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ dense_12 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m)             │         \u001b[38;5;34m2,080\u001b[0m │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ dropout_6 (\u001b[38;5;33mDropout\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m)             │             \u001b[38;5;34m0\u001b[0m │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ dense_13 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m)              │            \u001b[38;5;34m33\u001b[0m │\n",
-       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">8,833</span> (34.50 KB)\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m8,833\u001b[0m (34.50 KB)\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">8,641</span> (33.75 KB)\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m8,641\u001b[0m (33.75 KB)\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">192</span> (768.00 B)\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m192\u001b[0m (768.00 B)\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -1421,312 +1464,312 @@
       "Epoch 1/150\n",
       "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 5ms/step - accuracy: 0.6010 - auc: 0.6312 - loss: 0.7564\n",
       "Epoch 2/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.7887 - auc: 0.8571 - loss: 0.6053\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.7891 - auc: 0.8572 - loss: 0.6054\n",
       "Epoch 3/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.8441 - auc: 0.9050 - loss: 0.5080\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.8434 - auc: 0.9049 - loss: 0.5082\n",
       "Epoch 4/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.8658 - auc: 0.9244 - loss: 0.4486\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.8658 - auc: 0.9244 - loss: 0.4488\n",
       "Epoch 5/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.8762 - auc: 0.9365 - loss: 0.4105\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.8775 - auc: 0.9365 - loss: 0.4105\n",
       "Epoch 6/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.8945 - auc: 0.9477 - loss: 0.3730\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.8939 - auc: 0.9477 - loss: 0.3732\n",
       "Epoch 7/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.8976 - auc: 0.9526 - loss: 0.3565\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.8965 - auc: 0.9525 - loss: 0.3568\n",
       "Epoch 8/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - accuracy: 0.9087 - auc: 0.9591 - loss: 0.3334\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9073 - auc: 0.9591 - loss: 0.3336\n",
       "Epoch 9/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9168 - auc: 0.9665 - loss: 0.3108\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9155 - auc: 0.9664 - loss: 0.3113\n",
       "Epoch 10/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9210 - auc: 0.9692 - loss: 0.2982\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9205 - auc: 0.9689 - loss: 0.2988\n",
       "Epoch 11/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9213 - auc: 0.9721 - loss: 0.2866\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9210 - auc: 0.9721 - loss: 0.2867\n",
       "Epoch 12/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9253 - auc: 0.9736 - loss: 0.2784\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9238 - auc: 0.9736 - loss: 0.2788\n",
       "Epoch 13/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9339 - auc: 0.9768 - loss: 0.2650\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9337 - auc: 0.9769 - loss: 0.2649\n",
       "Epoch 14/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9339 - auc: 0.9788 - loss: 0.2571\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9341 - auc: 0.9788 - loss: 0.2575\n",
       "Epoch 15/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9364 - auc: 0.9791 - loss: 0.2541\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9361 - auc: 0.9794 - loss: 0.2535\n",
       "Epoch 16/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9376 - auc: 0.9808 - loss: 0.2462\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9387 - auc: 0.9811 - loss: 0.2456\n",
       "Epoch 17/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9411 - auc: 0.9836 - loss: 0.2347\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9419 - auc: 0.9837 - loss: 0.2342\n",
       "Epoch 18/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9450 - auc: 0.9828 - loss: 0.2333\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9466 - auc: 0.9831 - loss: 0.2325\n",
       "Epoch 19/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9446 - auc: 0.9844 - loss: 0.2278\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9431 - auc: 0.9846 - loss: 0.2271\n",
       "Epoch 20/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9459 - auc: 0.9857 - loss: 0.2207\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9449 - auc: 0.9858 - loss: 0.2203\n",
       "Epoch 21/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9491 - auc: 0.9881 - loss: 0.2098\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9505 - auc: 0.9882 - loss: 0.2090\n",
       "Epoch 22/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9459 - auc: 0.9883 - loss: 0.2073\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9466 - auc: 0.9883 - loss: 0.2071\n",
       "Epoch 23/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9497 - auc: 0.9888 - loss: 0.2029\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9508 - auc: 0.9888 - loss: 0.2031\n",
       "Epoch 24/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9520 - auc: 0.9889 - loss: 0.2005\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9506 - auc: 0.9890 - loss: 0.2005\n",
       "Epoch 25/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9549 - auc: 0.9904 - loss: 0.1932\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9528 - auc: 0.9901 - loss: 0.1939\n",
       "Epoch 26/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9581 - auc: 0.9903 - loss: 0.1888\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9557 - auc: 0.9903 - loss: 0.1888\n",
       "Epoch 27/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9578 - auc: 0.9911 - loss: 0.1839\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9572 - auc: 0.9911 - loss: 0.1841\n",
       "Epoch 28/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9584 - auc: 0.9908 - loss: 0.1853\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9582 - auc: 0.9906 - loss: 0.1847\n",
       "Epoch 29/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - accuracy: 0.9592 - auc: 0.9929 - loss: 0.1758\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9581 - auc: 0.9931 - loss: 0.1748\n",
       "Epoch 30/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9621 - auc: 0.9925 - loss: 0.1727\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9629 - auc: 0.9926 - loss: 0.1726\n",
       "Epoch 31/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9617 - auc: 0.9926 - loss: 0.1729\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9593 - auc: 0.9922 - loss: 0.1725\n",
       "Epoch 32/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9602 - auc: 0.9929 - loss: 0.1712\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9626 - auc: 0.9923 - loss: 0.1718\n",
       "Epoch 33/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9627 - auc: 0.9939 - loss: 0.1632\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9628 - auc: 0.9937 - loss: 0.1627\n",
       "Epoch 34/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9662 - auc: 0.9937 - loss: 0.1650\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9666 - auc: 0.9938 - loss: 0.1642\n",
       "Epoch 35/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9631 - auc: 0.9933 - loss: 0.1636\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9653 - auc: 0.9933 - loss: 0.1641\n",
       "Epoch 36/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9647 - auc: 0.9939 - loss: 0.1599\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9637 - auc: 0.9936 - loss: 0.1613\n",
       "Epoch 37/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9640 - auc: 0.9935 - loss: 0.1594\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9657 - auc: 0.9934 - loss: 0.1604\n",
       "Epoch 38/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9672 - auc: 0.9948 - loss: 0.1533\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9673 - auc: 0.9946 - loss: 0.1544\n",
       "Epoch 39/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9738 - auc: 0.9944 - loss: 0.1508\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9733 - auc: 0.9944 - loss: 0.1523\n",
       "Epoch 40/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9714 - auc: 0.9945 - loss: 0.1517\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9708 - auc: 0.9942 - loss: 0.1523\n",
       "Epoch 41/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9737 - auc: 0.9948 - loss: 0.1458\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9729 - auc: 0.9946 - loss: 0.1476\n",
       "Epoch 42/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9724 - auc: 0.9954 - loss: 0.1445\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9714 - auc: 0.9948 - loss: 0.1455\n",
       "Epoch 43/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9744 - auc: 0.9955 - loss: 0.1426\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9743 - auc: 0.9955 - loss: 0.1433\n",
       "Epoch 44/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9705 - auc: 0.9948 - loss: 0.1427\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9700 - auc: 0.9946 - loss: 0.1449\n",
       "Epoch 45/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9742 - auc: 0.9958 - loss: 0.1374\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9746 - auc: 0.9957 - loss: 0.1388\n",
       "Epoch 46/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9738 - auc: 0.9959 - loss: 0.1370\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9717 - auc: 0.9956 - loss: 0.1388\n",
       "Epoch 47/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9723 - auc: 0.9956 - loss: 0.1383\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9742 - auc: 0.9955 - loss: 0.1391\n",
       "Epoch 48/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9769 - auc: 0.9954 - loss: 0.1353\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9759 - auc: 0.9951 - loss: 0.1385\n",
       "Epoch 49/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9764 - auc: 0.9955 - loss: 0.1345\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9746 - auc: 0.9951 - loss: 0.1367\n",
       "Epoch 50/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - accuracy: 0.9748 - auc: 0.9957 - loss: 0.1341\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9740 - auc: 0.9954 - loss: 0.1356\n",
       "Epoch 51/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - accuracy: 0.9754 - auc: 0.9954 - loss: 0.1326\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9720 - auc: 0.9951 - loss: 0.1354\n",
       "Epoch 52/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9790 - auc: 0.9963 - loss: 0.1287\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9764 - auc: 0.9958 - loss: 0.1301\n",
       "Epoch 53/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9767 - auc: 0.9961 - loss: 0.1299\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9758 - auc: 0.9962 - loss: 0.1301\n",
       "Epoch 54/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9766 - auc: 0.9959 - loss: 0.1264\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9763 - auc: 0.9958 - loss: 0.1285\n",
       "Epoch 55/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9782 - auc: 0.9957 - loss: 0.1269\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9774 - auc: 0.9957 - loss: 0.1274\n",
       "Epoch 56/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9787 - auc: 0.9973 - loss: 0.1215\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9763 - auc: 0.9968 - loss: 0.1240\n",
       "Epoch 57/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9795 - auc: 0.9971 - loss: 0.1221\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9780 - auc: 0.9963 - loss: 0.1225\n",
       "Epoch 58/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9780 - auc: 0.9962 - loss: 0.1238\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9773 - auc: 0.9957 - loss: 0.1249\n",
       "Epoch 59/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9788 - auc: 0.9973 - loss: 0.1191\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9794 - auc: 0.9963 - loss: 0.1199\n",
       "Epoch 60/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9800 - auc: 0.9962 - loss: 0.1193\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9783 - auc: 0.9961 - loss: 0.1214\n",
       "Epoch 61/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9817 - auc: 0.9973 - loss: 0.1153\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9806 - auc: 0.9972 - loss: 0.1162\n",
       "Epoch 62/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9815 - auc: 0.9972 - loss: 0.1148\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9805 - auc: 0.9973 - loss: 0.1147\n",
       "Epoch 63/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9828 - auc: 0.9972 - loss: 0.1138\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9811 - auc: 0.9971 - loss: 0.1147\n",
       "Epoch 64/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9807 - auc: 0.9971 - loss: 0.1146\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9805 - auc: 0.9970 - loss: 0.1163\n",
       "Epoch 65/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9786 - auc: 0.9972 - loss: 0.1134\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9788 - auc: 0.9967 - loss: 0.1142\n",
       "Epoch 66/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9818 - auc: 0.9971 - loss: 0.1094\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9820 - auc: 0.9971 - loss: 0.1095\n",
       "Epoch 67/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9788 - auc: 0.9962 - loss: 0.1164\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9799 - auc: 0.9964 - loss: 0.1160\n",
       "Epoch 68/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9805 - auc: 0.9967 - loss: 0.1119\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9803 - auc: 0.9968 - loss: 0.1128\n",
       "Epoch 69/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - accuracy: 0.9809 - auc: 0.9977 - loss: 0.1090\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9793 - auc: 0.9978 - loss: 0.1092\n",
       "Epoch 70/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - accuracy: 0.9833 - auc: 0.9968 - loss: 0.1087\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9832 - auc: 0.9968 - loss: 0.1096\n",
       "Epoch 71/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - accuracy: 0.9826 - auc: 0.9975 - loss: 0.1075\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9833 - auc: 0.9976 - loss: 0.1077\n",
       "Epoch 72/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9806 - auc: 0.9970 - loss: 0.1083\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9812 - auc: 0.9967 - loss: 0.1097\n",
       "Epoch 73/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9845 - auc: 0.9976 - loss: 0.1041\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9839 - auc: 0.9977 - loss: 0.1051\n",
       "Epoch 74/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9853 - auc: 0.9976 - loss: 0.1021\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9818 - auc: 0.9977 - loss: 0.1042\n",
       "Epoch 75/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9806 - auc: 0.9970 - loss: 0.1071\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9824 - auc: 0.9970 - loss: 0.1073\n",
       "Epoch 76/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9813 - auc: 0.9975 - loss: 0.1050\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9819 - auc: 0.9973 - loss: 0.1050\n",
       "Epoch 77/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9838 - auc: 0.9977 - loss: 0.1019\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9859 - auc: 0.9975 - loss: 0.1025\n",
       "Epoch 78/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9852 - auc: 0.9983 - loss: 0.0994\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9858 - auc: 0.9982 - loss: 0.0989\n",
       "Epoch 79/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9829 - auc: 0.9980 - loss: 0.1001\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9855 - auc: 0.9979 - loss: 0.1001\n",
       "Epoch 80/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9844 - auc: 0.9977 - loss: 0.0994\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9846 - auc: 0.9977 - loss: 0.0992\n",
       "Epoch 81/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9857 - auc: 0.9978 - loss: 0.0999\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9855 - auc: 0.9974 - loss: 0.1013\n",
       "Epoch 82/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9836 - auc: 0.9980 - loss: 0.0964\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9846 - auc: 0.9980 - loss: 0.0965\n",
       "Epoch 83/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9847 - auc: 0.9979 - loss: 0.0980\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9849 - auc: 0.9977 - loss: 0.0988\n",
       "Epoch 84/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9850 - auc: 0.9980 - loss: 0.0970\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9829 - auc: 0.9977 - loss: 0.0987\n",
       "Epoch 85/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9870 - auc: 0.9977 - loss: 0.0939\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9861 - auc: 0.9976 - loss: 0.0958\n",
       "Epoch 86/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9855 - auc: 0.9983 - loss: 0.0936\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9853 - auc: 0.9980 - loss: 0.0937\n",
       "Epoch 87/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9852 - auc: 0.9982 - loss: 0.0930\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9868 - auc: 0.9983 - loss: 0.0924\n",
       "Epoch 88/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9863 - auc: 0.9980 - loss: 0.0934\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9856 - auc: 0.9980 - loss: 0.0943\n",
       "Epoch 89/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9877 - auc: 0.9983 - loss: 0.0896\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9860 - auc: 0.9978 - loss: 0.0910\n",
       "Epoch 90/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9884 - auc: 0.9983 - loss: 0.0914\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9887 - auc: 0.9983 - loss: 0.0903\n",
       "Epoch 91/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9863 - auc: 0.9977 - loss: 0.0925\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9857 - auc: 0.9976 - loss: 0.0928\n",
       "Epoch 92/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9840 - auc: 0.9985 - loss: 0.0917\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9864 - auc: 0.9981 - loss: 0.0910\n",
       "Epoch 93/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9869 - auc: 0.9978 - loss: 0.0886\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9877 - auc: 0.9977 - loss: 0.0899\n",
       "Epoch 94/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9887 - auc: 0.9982 - loss: 0.0865\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9867 - auc: 0.9980 - loss: 0.0900\n",
       "Epoch 95/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9864 - auc: 0.9976 - loss: 0.0914\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9868 - auc: 0.9977 - loss: 0.0906\n",
       "Epoch 96/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9889 - auc: 0.9984 - loss: 0.0877\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9891 - auc: 0.9983 - loss: 0.0890\n",
       "Epoch 97/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9881 - auc: 0.9984 - loss: 0.0859\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9885 - auc: 0.9984 - loss: 0.0866\n",
       "Epoch 98/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9883 - auc: 0.9983 - loss: 0.0855\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9861 - auc: 0.9982 - loss: 0.0866\n",
       "Epoch 99/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9882 - auc: 0.9985 - loss: 0.0857\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9888 - auc: 0.9986 - loss: 0.0836\n",
       "Epoch 100/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9880 - auc: 0.9989 - loss: 0.0827\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9892 - auc: 0.9991 - loss: 0.0826\n",
       "Epoch 101/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9882 - auc: 0.9983 - loss: 0.0870\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9872 - auc: 0.9984 - loss: 0.0851\n",
       "Epoch 102/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9895 - auc: 0.9985 - loss: 0.0826\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9914 - auc: 0.9985 - loss: 0.0824\n",
       "Epoch 103/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9878 - auc: 0.9984 - loss: 0.0841\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9888 - auc: 0.9985 - loss: 0.0826\n",
       "Epoch 104/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9879 - auc: 0.9985 - loss: 0.0839\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9879 - auc: 0.9980 - loss: 0.0836\n",
       "Epoch 105/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9892 - auc: 0.9981 - loss: 0.0821\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9885 - auc: 0.9981 - loss: 0.0825\n",
       "Epoch 106/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9888 - auc: 0.9984 - loss: 0.0823\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9894 - auc: 0.9985 - loss: 0.0813\n",
       "Epoch 107/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9897 - auc: 0.9985 - loss: 0.0825\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9890 - auc: 0.9985 - loss: 0.0819\n",
       "Epoch 108/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9876 - auc: 0.9984 - loss: 0.0823\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9890 - auc: 0.9980 - loss: 0.0807\n",
       "Epoch 109/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9893 - auc: 0.9980 - loss: 0.0818\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9891 - auc: 0.9981 - loss: 0.0807\n",
       "Epoch 110/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9913 - auc: 0.9987 - loss: 0.0772\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9900 - auc: 0.9987 - loss: 0.0778\n",
       "Epoch 111/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9896 - auc: 0.9987 - loss: 0.0787\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9899 - auc: 0.9987 - loss: 0.0776\n",
       "Epoch 112/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9902 - auc: 0.9985 - loss: 0.0786\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9908 - auc: 0.9986 - loss: 0.0778\n",
       "Epoch 113/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9891 - auc: 0.9986 - loss: 0.0782\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9893 - auc: 0.9992 - loss: 0.0770\n",
       "Epoch 114/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9889 - auc: 0.9991 - loss: 0.0773\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9902 - auc: 0.9992 - loss: 0.0759\n",
       "Epoch 115/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9896 - auc: 0.9994 - loss: 0.0756\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9891 - auc: 0.9994 - loss: 0.0754\n",
       "Epoch 116/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9920 - auc: 0.9987 - loss: 0.0740\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9901 - auc: 0.9987 - loss: 0.0757\n",
       "Epoch 117/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9905 - auc: 0.9988 - loss: 0.0766\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9899 - auc: 0.9988 - loss: 0.0749\n",
       "Epoch 118/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9900 - auc: 0.9987 - loss: 0.0764\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9890 - auc: 0.9986 - loss: 0.0763\n",
       "Epoch 119/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9888 - auc: 0.9987 - loss: 0.0775\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9890 - auc: 0.9988 - loss: 0.0770\n",
       "Epoch 120/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9911 - auc: 0.9994 - loss: 0.0723\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9896 - auc: 0.9989 - loss: 0.0721\n",
       "Epoch 121/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9930 - auc: 0.9994 - loss: 0.0696\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9924 - auc: 0.9988 - loss: 0.0714\n",
       "Epoch 122/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9902 - auc: 0.9993 - loss: 0.0731\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9921 - auc: 0.9994 - loss: 0.0709\n",
       "Epoch 123/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9902 - auc: 0.9993 - loss: 0.0732\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9886 - auc: 0.9988 - loss: 0.0738\n",
       "Epoch 124/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9899 - auc: 0.9994 - loss: 0.0723\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9919 - auc: 0.9989 - loss: 0.0703\n",
       "Epoch 125/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9927 - auc: 0.9990 - loss: 0.0686\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9919 - auc: 0.9989 - loss: 0.0698\n",
       "Epoch 126/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9915 - auc: 0.9993 - loss: 0.0714\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9898 - auc: 0.9988 - loss: 0.0720\n",
       "Epoch 127/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9910 - auc: 0.9994 - loss: 0.0702\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9919 - auc: 0.9994 - loss: 0.0691\n",
       "Epoch 128/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9915 - auc: 0.9996 - loss: 0.0667\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9922 - auc: 0.9996 - loss: 0.0666\n",
       "Epoch 129/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9889 - auc: 0.9992 - loss: 0.0741\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9916 - auc: 0.9994 - loss: 0.0699\n",
       "Epoch 130/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9900 - auc: 0.9994 - loss: 0.0715\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9911 - auc: 0.9995 - loss: 0.0677\n",
       "Epoch 131/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9889 - auc: 0.9995 - loss: 0.0691\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9882 - auc: 0.9993 - loss: 0.0735\n",
       "Epoch 132/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9916 - auc: 0.9996 - loss: 0.0673\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9928 - auc: 0.9996 - loss: 0.0657\n",
       "Epoch 133/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9894 - auc: 0.9993 - loss: 0.0723\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9921 - auc: 0.9995 - loss: 0.0676\n",
       "Epoch 134/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9918 - auc: 0.9996 - loss: 0.0665\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9912 - auc: 0.9996 - loss: 0.0669\n",
       "Epoch 135/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9923 - auc: 0.9996 - loss: 0.0672\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9925 - auc: 0.9991 - loss: 0.0647\n",
       "Epoch 136/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9938 - auc: 0.9987 - loss: 0.0664\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9928 - auc: 0.9990 - loss: 0.0650\n",
       "Epoch 137/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9926 - auc: 0.9994 - loss: 0.0670\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9917 - auc: 0.9995 - loss: 0.0651\n",
       "Epoch 138/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9925 - auc: 0.9995 - loss: 0.0655\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9916 - auc: 0.9995 - loss: 0.0658\n",
       "Epoch 139/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9905 - auc: 0.9996 - loss: 0.0652\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9941 - auc: 0.9997 - loss: 0.0624\n",
       "Epoch 140/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9919 - auc: 0.9993 - loss: 0.0672\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9905 - auc: 0.9994 - loss: 0.0660\n",
       "Epoch 141/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9934 - auc: 0.9995 - loss: 0.0640\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9941 - auc: 0.9995 - loss: 0.0624\n",
       "Epoch 142/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9916 - auc: 0.9996 - loss: 0.0646\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9917 - auc: 0.9996 - loss: 0.0637\n",
       "Epoch 143/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9923 - auc: 0.9996 - loss: 0.0632\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9927 - auc: 0.9996 - loss: 0.0635\n",
       "Epoch 144/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9922 - auc: 0.9996 - loss: 0.0648\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9934 - auc: 0.9995 - loss: 0.0635\n",
       "Epoch 145/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9921 - auc: 0.9995 - loss: 0.0648\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9943 - auc: 0.9997 - loss: 0.0608\n",
       "Epoch 146/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9940 - auc: 0.9996 - loss: 0.0614\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9940 - auc: 0.9997 - loss: 0.0595\n",
       "Epoch 147/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9921 - auc: 0.9997 - loss: 0.0633\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9931 - auc: 0.9998 - loss: 0.0610\n",
       "Epoch 148/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step - accuracy: 0.9929 - auc: 0.9991 - loss: 0.0626\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9937 - auc: 0.9995 - loss: 0.0607\n",
       "Epoch 149/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9920 - auc: 0.9996 - loss: 0.0627\n",
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9912 - auc: 0.9997 - loss: 0.0617\n",
       "Epoch 150/150\n",
-      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9908 - auc: 0.9996 - loss: 0.0642\n"
+      "\u001b[1m499/499\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - accuracy: 0.9927 - auc: 0.9996 - loss: 0.0622\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<keras.src.callbacks.history.History at 0x7fabc00cf860>"
+       "<keras.src.callbacks.history.History at 0x7f6008265ac0>"
       ]
      },
-     "execution_count": 38,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1756,7 +1799,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "5a09f80c",
    "metadata": {},
    "outputs": [
@@ -1765,30 +1808,20 @@
      "output_type": "stream",
      "text": [
       "\u001b[1m250/250\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step\n",
-      "Final Loss: 0.0531\n",
-      "Final Accuracy: 0.9944\n",
+      "Final Loss: 0.0514\n",
+      "Final Accuracy: 0.9950\n",
       "Final AUC: 0.9996\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 600x500 with 2 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Precision: 0.9959384352287303\n",
-      "Recall: 0.9944503735325507\n",
-      "F1‑Score: 0.9951938481256007\n",
-      "Balanced Accuracy: 0.9943350133558707\n"
-     ]
     }
    ],
    "source": [
@@ -1831,7 +1864,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 12,
    "id": "2d3af5be",
    "metadata": {},
    "outputs": [
@@ -1839,15 +1872,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Finales Modell und Scaler gespeichert als 'cnn_crossVal_EarlyFusion_Filter.keras' und 'scaler_crossVal_EarlyFusion_V2.joblib'\n"
+      "Finales Modell und Scaler gespeichert als 'cnn_crossVal_EarlyFusion_Filter_True.keras' und 'scaler_crossVal_EarlyFusion_True.joblib'\n"
      ]
     }
    ],
    "source": [
-    "final_model.save(\"cnn_crossVal_EarlyFusion_Filter.keras\") \n",
-    "joblib.dump(scaler_final, \"scaler_crossVal_EarlyFusion_Filter.joblib\") \n",
+    "final_model.save(\"cnn_crossVal_EarlyFusion_Filter_True.keras\") \n",
+    "joblib.dump(scaler_final, \"scaler_crossVal_EarlyFusion_Filter_True.joblib\") \n",
     "\n",
-    "print(\"Finales Modell und Scaler gespeichert als 'cnn_crossVal_EarlyFusion_Filter.keras' und 'scaler_crossVal_EarlyFusion_V2.joblib'\")"
+    "print(\"Finales Modell und Scaler gespeichert als 'cnn_crossVal_EarlyFusion_Filter_True.keras' und 'scaler_crossVal_EarlyFusion_True.joblib'\")"
    ]
   },
   {
@@ -1860,13 +1893,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 13,
    "id": "9f6a8584",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x600 with 1 Axes>"
       ]
@@ -1876,7 +1909,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x600 with 1 Axes>"
       ]
@@ -1886,7 +1919,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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pp3PHHXeULGlFUfnSSy+NyOfgvnTWWWehaRo/+clPjrhsV199NY7j8J3vfId77rmHd7/73SPqfP755/Pyyy8zffr0Uf1m+fLlo8TVoXKo/Wi8tii6Mr4aZ599Nrqus2vXrjHLL8O1SySSiURariQSieQ1sHr1an7yk59wzTXXsGzZMj760Y9y3HHHYVkWL7zwAj/72c+YP38+F1xwwSvm86Uvfak0t+WLX/wilZWV/Pa3v+Xuu+/muuuuo6ysDIALLriA+fPns3z5cmpqati7dy/XX389LS0tzJw5k3g8zqmnnsp73/te5syZQzQa5dlnn+W+++7j4osvPqQ6vfOd76S6uprvfOc7pZDdwzn//PO54YYbmDNnDgsXLuT555/nO9/5zhG5plVUVPCZz3yGr3/963zwgx/k7//+72lra+PLX/7yKLfAYgj7a665hksvvZS2tja+9rWv0dDQwI4dO0akXbBgAY8++ih33nknDQ0NRKNRZs+ePer6qqpy3XXXcfnll3P++efz4Q9/mHw+z3e+8x0GBwf59re/fdh1Goui1erf/u3fWLly5ajPk8kkf/nLX7j55pv553/+Z84991wqKyu5+uqr+epXv4qu69xwww20tbWNOG/KlCl87nOf42tf+xrZbLYUIn7z5s309vaWwvy/EsuXL2fhwoVcf/31CCFGrW311a9+lQcffJA1a9bwiU98gtmzZ5PL5WhtbeWee+7hpz/96RHd+0PtRytWrGD27Nl85jOfwbZtKioquO2228aM5DgWU6ZM4atf/Sr/8R//we7du3nHO95BRUUFXV1dPPPMM4TD4UNqJ4lEIjkkjm48DYlEInlr8OKLL4qrrrpKNDc3C5/PJ8LhsFiyZIn44he/KLq7u0vpWlpaxHnnnTdmHhs3bhQXXHCBKCsrEz6fTyxatGhUdLXvfe97Ys2aNaK6ulr4fD7R3Nwsrr76atHa2iqEECKXy4mPfOQjYuHChSIWi4lgMChmz54tvvSlL4l0On3I9fnUpz4lAHHuueeO+mxgYEBcffXVora2VoRCIXHCCSeIxx9/XJx88skjovsdSrRAIbwohd/61rfE5MmThc/nEwsXLhR33nnnqPyEEOLb3/62mDJlivD7/WLu3Lni5z//+ZiR9V588UWxdu1aEQqFRkQdHCvCnBBC3H777eL4448XgUBAhMNhcfrpp4snnnhiRJqxItGNV6fhmKYpamtrXzHKo23bYtKkSWLBggWlY88884xYs2aNCIfDoqmpSXzpS18Sv/jFL8a81k033SRWrFghAoGAiEQiYsmSJa8Yme9gfvCDHwhAzJs3b8zPe3p6xCc+8QkxdepUYRiGqKysFMuWLRP/8R//IVKplBBi6H5/5zvfGXX+WH3hUPuREEJs375dnHXWWSIWi4mamhrx8Y9/XNx9992HFC2wyO233y5OPfVUEYvFhN/vFy0tLeLSSy8VDz300CG3k0QikbwaihDD/CAkEolEIpFIJBKJRHJEyDlXEolEIpFIJBKJRDIBSHElkUgkEolEIpFIJBOAFFcSiUQikUgkEolEMgFIcSWRSCQSiUQikUgkE4AUVxKJRCKRSCQSiUQyAUhxJZFIJBKJRCKRSCQTgFxEeAxc16Wjo4NoNIqiKEe7OBKJRCKRSCQSieQoIYQgmUzS2NiIqr6ybUqKqzHo6Ohg8uTJR7sYEolEIpFIJBKJ5Bihra2NSZMmvWIaKa7GIBqNAl4DxmKxo1wasCyLBx54gLPOOgvDMI52cSRvY2RflBxLyP4oOZaQ/VFyLCH748SSSCSYPHlySSO8ElJcjUHRFTAWix0z4ioUChGLxeQ/iOSoIvui5FhC9kfJsYTsj5JjCdkfXx8OZbqQDGghkUgkEolEIpFIJBOAFFcSiUQikUgkEolEMgFIcSWRSCQSiUQikUgkE4AUVxKJRCKRSCQSiUQyAUhxJZFIJBKJRCKRSCQTgBRXEolEIpFIJBKJRDIBSHElkUgkEolEIpFIJBOAFFcSiUQikUgkEolEMgFIcSWRSCQSiUQikUgkE4AUVxKJRCKRSCQSiUQyAUhxJZFIJBKJRCKRSCQTgBRXEolEIpFIJBKJRDIBHFVx9de//pULLriAxsZGFEXh9ttvf9VzHnvsMZYtW0YgEGDatGn89Kc/HZXmj3/8I/PmzcPv9zNv3jxuu+2216H0EolEIpFIJBKJRDLEURVX6XSaRYsW8d///d+HlH7Pnj2ce+65nHjiibzwwgt87nOf4xOf+AR//OMfS2nWrVvHu971Lq644go2bNjAFVdcwWWXXcbTTz/9elVDIpFIJBKJRCKRSNCP5sXPOecczjnnnENO/9Of/pTm5mauv/56AObOnctzzz3Hd7/7XS655BIArr/+es4880yuvfZaAK699loee+wxrr/+en73u99NeB0kEolEIpFIJBKJBI6yuDpc1q1bx1lnnTXi2Nlnn80vf/lLLMvCMAzWrVvHpz71qVFpioJsLPL5PPl8vvQ+kUgAYFkWlmVNXAWOkGIZjoWySN7eyL4oOZaQ/VFyLCH7o+RYQvbHieVw2vFNJa46Ozupq6sbcayurg7btunt7aWhoWHcNJ2dnePm+61vfYuvfOUro44/8MADhEKhiSn8BPDggw8e7SJIJIDsi5JjC9kfJccSsj++fVFcUB0FzVFQhHdMKN4GYui1AgJQxPBNKb1GKCgMnV88t/ReAYFAqOCqAlf1jo3FqP7oguqC6nrXcBUQipdXMe9RCO8cxVVQXaV0vuoO1U/gVaj0vvBaKRR6rLp6jcCoc7xyDL12NDFu/d4oMpnMIad9U4krAEUZ2bpCiFHHx0pz8LHhXHvttXz6058uvU8kEkyePJmzzjqLWCw2EcV+TViWxYMPPsiZZ56JYRhHuziStzGyL0qOJWR/lBxLvNn6oxACbIGwHITlIvKu99oVKIZa2LTSazRlxFhKCAGWizBdXNMpvPbyQlW89KoCmoqiFd4X9jjCu+bwzXRwLS8vYbkIR3jpHNcrpyPAccERIASKpqAU8lY0deh6emGvKghFwVU8AeFC6bWDl40j3MIeHFfgCIGDwHFBEQJVgCZAFQLVBQ1QXO81tovIO4i8A3kHTBfhuAgBrhAIAVURH5r6xqgCRVNRdBXFp4KuIjRo3bOHlqZmFAfv/tguwhWvnI9SvFeqJ3xs77yjSdnFM1BDR1eyFL3aDoU3lbiqr68fZYHq7u5G13WqqqpeMc3B1qzh+P1+/H7/qOOGYRxTX5DHWnkkb19kX5QcS8j+6CGEIJ616Enm6Unm6U7m6U15rxVFoTrioypgUK5qRBWFoKugmi7ZlIWdd1A1BVVTUVQFVVUK772BqqIo3mBagGW7ZE2bdN4mm3fI5B3yloOKN/hUUdCUwkBUKKh40bMMQ8MX0DACGv6gji+g4w/o+EPeXg+ohCr8OAJcV2C7whvwugLbEdiui+0KLMctvTftwnHHS1dEUQpb8XF3Yec4hQF0Kf+hcx0hUFDwxuUKSmGvqUOvXTG8PIXzC2XMmTab9ytse2wvjoC87WLaDo7l4lguruWiuC5BRSGgKPgVlUDhtQ/woWAo4Aq8AT5FASCwi8cEKMJFcz0riSYEmusN/kt7ARqKdy+UgjhQCu9F4RzH2xTh9RsBICjtUYYZCgqvXUXBUUGoCroLhitQFK+xFYbaW1EYITCK+Rffu4WH4l53KqQpXve1oIw0bkxInkeAUCCvgq0olFeH8Oua97/jeptwoVRptSA41SFBWHw/ZLqicF7hnEJeQuAJ2WK/d/EEnukJIVe4BLIaImGhKF78Ou/+eBkXryMcMZRHEQdPyELh3hbi36nKMOHtibkR5XNFKT/hFsSwOnb9FKVQTwrnO+7Ic4t5OQLDb6AaR1eyHM5vzJtKXK1evZo777xzxLEHHniA5cuXlyq9evVqHnzwwRHzrh544AHWrFnzhpZVIpFIJK/Mq3kVHA6uK8hYDqmcTSpvkczZpPI26bzjDTALgkErDJaLg2ZNBZ+m4dNVdEVBc1wUS6DYAtd0SKYSKEJFw4ftCCxb4Dgulu2WBvkAmqYUNhVNVdANb69ogrxjks6apPMWmZxJxrTI5S1ylkPetLBsB2GDW3xS71IYZIBwPDcaTfGhq0FUVUFR8cSPUhA/ikLedsiaTnE8NArNFXRagu6DBlGKonh1LwiI4cPT4W+FANtxsRxPUBwORU+jVzvLVRX2zAqO+7kqhDeoF6AL0F0x4rUuPBGnFDyI1FH7ofSGC8aw/IKF8x0FTFXBVCGvKuRVMFUwFe+YQvF8Ly/D9d4HXEFMCCrSIaLxfnRAdz1hc6whALuwgScGinW0VM+yYxTaxSi0i3JQPazCBsU2A6vQbnZBF2glq0/xtSgdcxQvvVW4pqWArSpYCoX3Co5CabMVcIYdEwrDrEpe3upB11Qp7IUYEpYo6HjGM10pfh8UHwh4DwVURUFXCmJSARuBDTgo2MX3hfK4PhXXUBE+FQwV/BqKoWEU/qdCi5uoDPvGvg8T9P0nHIGwHYRZsADanhXQypl0PrWPaSdNxgj6SmJI8WnefphFbUjMuAh7mMXQFV76opjS3vgg40UPtTcTR1VcpVIpdu7cWXq/Z88eXnzxRSorK2lububaa6+lvb2dm266CYCPfOQj/Pd//zef/vSn+dCHPsS6dev45S9/OSIK4D//8z9z0kkn8Z//+Z9ceOGF3HHHHTz00EP87W9/e8PrJ5FIJG9WhBAIURw+FZ56KsVh8vABgYsQDkK4CGEDAsexyZqeiEjk8gxmLOLZPPGMSTxrkshZJLJ5ElkLFw1HqcOva/gNFb+ueq91Fb+hoilKyTJguwLHcXBMgcjZ2Dmb9jadxw+sJycErqLgqt4g3VVAFB+2OqDb3pN63RZo9si96rgojoniWLgUNxMXyxtVepMJUNBQC8MzZdger9bjbq/xTuDJkhgaKk6h/RVGD8p8XjExNK8NfbqKT1fxayoCMG3Hs6aokEGQci3QXVTVRlMVDGFgCAVDCHwu6EKUBtk6oOqg6goqGroCflXFpyn4VBVLZD0FRsFaNXwihlBRULxBvRDkhI2J41mccLGFwBGe9KrpzhNUI/gE+ASowvJeu15rK4rwTCQIFEXgV/0FK5OCJUxc4SLGbB3wKT4UxROltmIhFNdzf8JTX162nqVNV4xSmd2imHSLFprCXvWe/it4A3IQxK0clWVBNFUdZQFTC4NToSm4moKjev3VVguiQVVw8MpRtPYNFwlFoYimeBYDreByp490vROF/u+KIRe4okucLVyEqqD5dVSfhuLTUA3FK29BsCsUDSSexUm4Lq4tCoN3B2G7OKqKoyvYhToULYxFC6CuKuiqilZ8QuDY4NoIxwLHobK6mkgkjKYoWGaebCaNoekYPg1d0/DpBobPh6qOPZgfbvEabiFzh1nKdFVB1zyRoyrg2hbZbJZsNksul6O6uvqIpn7k8/mSi5iu6+i6jmEY6LqOpmmHLJhei7ASQpT6paIo3n30jxzSK5ZFepON0RAuGSCK57mug2u7CCFQVdX7XFVwcEll04U03ufkgJx3nUAgQCQSAcBxHAYGBkr5FvfFLRQKldrXcRx6enpG1Vsp/O8GAgGi0Wgpj3Q67f2vqiqBQGDCHsK9URxVcfXcc89x6qmnlt4X5z1dddVV3HDDDRw4cIB9+/aVPp86dSr33HMPn/rUp/jRj35EY2MjP/zhD0th2AHWrFnD73//ez7/+c/zhS98genTp3Prrbdy/PHHv3EVk0gkkjcYIQS2beO6eRQlj+NkEcLCdiw0VUUIB9d1Gcjm6Evm6UvnyOUzCJEEN4VwEghnEGENgjOI4iYKYslD1X2oRqB0LSeXHubuoyAQRa8XHFSEVnChEKC4JkVBFgACKNTpQBRydgXruz5M3jUxHUHOjhfmNAgU4aI4DprjoDoumqOh29HCIN7FVXuocSy0dB+RUkk9yw5CQVV8CMVBEQouGVBcBK5XqKJJCBdXKLgiWpok7uiDuKqNrTrYqoNQXG8wp4CrCPK6CoogIHQqbQ1deE+0hfCsAS5Drl1WQZj6VBU/niuYoWr4FA2fquEXGrrqDaiDRoCip0xfph/LsXCEJ6cMLUVAG0AI8Gk+ljWuKrm3be/bTN7J4tNUDE1DVdTCoF7FUA0W1x2HqoChKKzveImBbBzTsnAcB1cIXFd4zYHCSWUrSwOZznwvtrDxqz4MRcdWLCxhYmKiqyrzo9NLrf5I7zbSTnbMvulTDc6qGfoNfrz/ReJWaqjvFv8oEELjnOpVpf7y9MDLdJuDFDRs8RaD4lkJz59+SumJ/NPtL9GZ6hlKc5BL4EUr3oFm6CiGyjM7X6Ctt4NigyueQiq5W1144jkYQkPkHZ7b+iJ7uvahCm8gqGoqquoJJVVVOWPFyQTDIRzF5Y4H7qK/Jovh96EbOobPQDd0NMMbhM+dO5dAwPs/SqVS5PN5/H4/Pp8PwzAOeRA5NEj2NsMwSkIkkUgwMDBAPpMhm82SOWh/5plnlqZSbNu2jU3PbUJVVTRNQ1ULdSsMeleuXElFRQUA+/btY/uu7SUX0eLgu7itWLGC6uoaAHbs2MHzzz4/JEwPYtLJJ9NQVg3A7t0dPPPUU2Om03WdVatW0dzcDEBfXx87duxA1/Ux59pPmTKFqspKAA4cOMDGjRtLgurgsqxatao0+O/o6OCpp54iGAwSCAQIBoM4jkM+nyeXy7Fs2bLS9JL29naeGqe8xXynTZsGQFdXF88//3xJKBT3xdezZ8+msbERgP7+fjZu3DgiL8dxsG0b27aZN28eU6ZMKeX78MMPj7p2Md8FCxYwc+bMUr6PPPLIuPdi/vz5LFy4EPDWn73nnnvGrducOXNYunQpALlcjgceeGDctDNmzGDlypUA2LY9ZnmLtLS0sHbtWsB7mPHnP/+59Nmll16Kzze29e9Y5aiKq1NOOeUVzX033HDDqGMnn3wy69evf8V8L730Ui699NLXWjyJRHIM4TgOiUSCVCqFaZqlH3/wfljLyspKgwDLsujp6Sn9iB28+Xy+0gDnlfDEilv6Ys9kMmzatIls1htEFudrFrfy8nIqCz/stm0zODhYWuohl8uN2Dc0NDB79mzA+5F69NFHS4MUEAiRxRE5LCdLrCJCtLaabC5OJhent+1lII+mFDY1j6rk0VQLX8BPOFqGqirYjstgb/eQ6CmFgvLCQrmKilA1LzKTcDDsNKLwFL+EKM638Bxj1EKkKYX0iLZS8Ma/GqALPwgf3nBdxS2lLT4VV0p567bF4ngc27UxHYukswtBYdB20IQJRfGD4bWvY1i4ogvXtVE1DUWow6JSqSj48FONgYomIKX0I7xwV4V5IqJgBREoPgg05YiUh4lVltO72UARAXyqD001QIBrWbiWTVD1sbBqGmLAws3ZPJ/cQV5YnrVGUUtzGhRFIawFOaVqKbqqowCP9b1A0s6U6o5TcNByIaQFOC26uFTXx/MvEndTI+dd2F57hFBoyA5ZxPaaOfJ2BhMwD+rDPtXAb+RK7/PpHFlz6L2qKPh0HaEo+A0ftVMrSi5A2/fsoT8bL3QZpSRqAAJ+P7FTm0tWlLoXe+jp78UVhQG/8DZQCIZDVF0w13M5Mh3Cj+0n319wzURFFSpqYcKMrutEVjSVgin41u/H6DeHiSCl1CaqqlJx4YxSXUJ/20+gw6vb8LFF8XV4eX1JgPiSEYz80HdA8bukKBoCLWWlp/16MoxuDqUVMMwe6eKfXo4/GMSyLNJqHic9iJod2+JSHPAC7Ny5k82bN48ow/B5HWeffXbpaf7GjRvZsmVL6Tvi4IHyOeecU/r+27NnD5s2bRrz+sAIa5BpmuRyuXHT2vbQA5Z0Ok13d/e4aYeHqlZVdUQZfT5faTMMg2BwyP1T0zQikYhnlR62Fa+vaUPKOpFIsHv37nHLUFlZOeI7uLe3d8Tnfr+fYDCI3+8fYbUqWrPGa4t0euj7LhgMEg6HURSlJHyGt9Pw8pqmyeDg4LjlnTx5cul1Pp+nvb193LTF3x3w/k/Gotjmw/u/oijjCqvh54B33/x+/wgBWEQIMULkKIpCKBQa9VtcfD38HgOUlZWN+X8phBiR1nVdNE0r9fPxrJfHMop4Mzozvs4kEgnKysqIx+PHTLTAe+65h3PPPVdO2j4KDH8y57pu6UmS4zgEg8HSl00qlWJgYKDkJqBpWul1cRv+JXGwGR28LxXLstB1fUS+7e3tpXXXDMMYMaCPRqOjlgywbRvTNLEsC9M0S1tlZSVlZWUADAwM8NJLL4343DRNhBD4/X7mzZs3YvBffFq4fv161q5di6/gsqGqKuFwmHA4XLp2IpHAsixs2x61r6mpob6+HvB+eHbv3o2maSM20zRJpVLU1taW0nZ3d/PQQw+Ne5+OO+44Fi1aBHj/w3fddde4aWfNmsXy5csBTzDdcccdpWsX71M+n8c0TebNm8fixYtL9+KOO/5M3naGJs8PjfVoaq5l+qw6HKuLbKafbS+/jBAaAg0hNBBq6XVtYxOVDTWkc32k0j0MtL2AomRR1SyalmX4DBVH9eEYoYKvjovPjCOKEkUoDDnyABgIEcG1/QhHBeKFflYQNUUvNwSu48e2yrHtgLc5ORw7gG2HMN0AthNAczS8M3VUxVc8E5S0Z9ERCt7Q2KufqqjoSpCgXoGqqDiuRcruwKU42BalsgpFoKgGmh5BVQW6KrDMwZKblVpw1XI1F1dzUYPgq9JQAgLVUMn1WiT7k9RFa/G7PnRbQ7NVFFshpoSY62vxrDiqwkupnbgCdEXDUDR0VUNXdHRFI6KHaArWULyTO9P7sYQNGrgaXvQy1xN7AdXP7Ehz6d6/bO4hh43r2IVBoYvjOjiuQ1Dxs7piQSntk4MbSbnZgtVDQSlYPzRNJRwIc8KcFV5wAFWhPz2IoiqEgyF8hh8KFibHsXFdgV83CgY8QTydwHJsXArWDAouPYV2nFTVALqKGtCImykUQ8UX9uMPBfBFAmiGjhACy7JGDJ42btzIwMAA6XQay7IIhUKl//VwOMy0adNe0dIy3LryWn67hltJioO34YO415vid1exDAfvy8rK0DQNy7K4/fbbWbFiBUBp0D3c+rBgwYJSG2/cuJGdO3dimmZJTAzn/PPPL41BNmzY8IqC6eyzzy5Zo1pbW9mxYwehUIhgMDjmvvhblMvlSlYdx3FGuoMB1dXVpYBfRYvY8Psw3MpVWVlZemhV/D05XItckeJvoWmaBAKBUv8ZGBigvb0dx3HGHKi3tLSUxFUmk6Gnp6dU72AwOEL4DKf4m1MUWdlsFk3TCAQC+P1+KioqRomF4RQ9B4q/0cXy5nK5UpsNb9vifrhrYjqd5sCBAyPqM3wsUVZWVvqdHS5Ah49Piq99Ps8F9p577uEd73gHtm2PskoOt6Qdy0zk3NzXwuFogzdVQAuJZCIoDv4TiQTJZLK0TyaTuK7LCSecQFNTE+A9AVy3bt24ea1du5aWlhbAc1d44oknxk27YsWK0lPL9vZ2HnvssXHTHn/88Uyf7rncJJNJnn/++XHTLl68mHnz5gGe+f/BBx8c84caYOnSpSVxZdv2uE/JstnsiB+uZDLJxo0bcV2X7u5u/va3v434Ql64cCHz588HYHBw8BVdBY477riSYMpms69oiZ43b14pbSQSwefzEYlECAQCo8Rp0Q8cvKdnFRUVnvvasAFDcRs+gCz+SHuDnzymmUNVc4CLpkHP4HbWbXNpH8zQ1p+lP5vGFDqGliak9xPS+whpgwSNQfpSgp4NhcijQmD4kpTmxygF3y8UVBR6Exq9Ca2w5ofA8NmldT8UN+BZSxwd1zFwHD+u7cexfdiOStKehOv6cRwfju3HdQIIJ4xwwwg7giKCKBgIxQYli0MGhxxCs0C3EYqNUG1QVVQtjGrrhc1AQ0NTFEJeQ4IusP0mdiiLHUhjBTNYgQxWIIvQLVShojkqmquhOxqao+O4GrbThu7oGK5GzFUxXB3DVTFcjZDrJ0yIoBsg4PrwCx+aoqGrOrqqoxWFj6oXXNzUoVk0mcKGFw2rO9dNbawWVVfH/kUrRLc6oWLF0IRuvTBnRfdEjjBd3LyDyNu4OYcZyqSRUcZ8oBgqWkUAvdKPXhFAqwyglwc4xThu3P4rhCiEjQZ0hXcq46c9mBC1h5w2zPjRcA8mQMWYxxVFGeV6s2DBgkPOd7w8iw8tJiKfo8XhRKP0+Xw0NTUdUvoFCxaU2rj4QKxolQdKA2nw3LGKrmYHu/AVtyJTpkwpuY+9GoFA4JCs+ACxWOyQHzgXrVRHStGCcnAk54qKipKF7tUIhUKl3+dXw+fzlUTZkVC0Oh583wOBAA0NDYeURzgcZsaMGa+eEA7p/6poSSw+AH2zciwIq8NFiivJW5J8Pk8qlSptkydPLv0o7N69m+eee27ccw/FmDvWF1soFKK6unqEm8Bwd4HxzPgHU3Q1KBIOh2lubi5NmLVte4Sr2XCrVS6XGyGsik8Niz90w5+8RaNRVqxYUfL3L26KopDP50f84Pp8PqZPn04mkyGRSJSekBbFyvAfwOJ1ipN8i+Uu7ovnFtukpaVlhCuIbdsYhkEkEqG6unpE+x6qu280GuUd73gH8WyWwVScwXSCRDZBMpsglUvyYt9LbHzkCQwlhUqCYH0cjRQqGYqjatMRZC3BgRRQiLtTBVQ1eB5SuqYODcCFAOFHCHDscvJ2JbYVQnFNVDeHKkxU10LFQhM2iuIFfrDtII4dwrGDhS3kbU4Q2/IPuc8dhALoho6t58lrWdyghWPkcY0UjrEf17BwDdtzndNtXN1GaA5VoSqmxKYwtWwqU6It1OjVaDkg40LWwUlZ2CkTO2FiJ01E3kHTVVSK05zEUJiwJIV5VkMuYI5wRrx3hetZslQNrSCWNN2bEzRmvXxeJCvVp6H4vcn2iqqUQvoKpxje14tkpdgO5qCLUR9Gj/rRwgZqSEcNG6ghAzWse3kc5o+zcIW35k5hDRs1oKNGD//pu6IooL/5BgaSN56id8PBXghFxlsyRiKRHHtIcSV5S9DV1cX27dtLYmq47zd4vr9FcRWLxfD5fKWncNFotLTXdX2EqJg8eTINDQ2lQVVRVI01yKqpqeGss84adbxoPRl+Tn19PRdffDEw9FSmaKo/eKJuLBbjhBNOOKR2qK6u5p3vfOchuWIEAoER/v/DOfgpV1lZGccffzyWZZFIJDjjjDPGfTIbi8W46KKLDqm84XC4NIn1lRBCYJo9ZDKtZLJ7sMx+HNcia+bJ5E0yZo6smSdnmeQsE8sycd0MqmKNm6cDY8Zxc4VK3vV7UdmEQBMuIU0trUujF+a+OBk/Vq6CfK4MMx/DzEfJ58PYLjiug+3ao+YMjbhOUQDpBQHkt3HDNq6RwNX7PUGku5SHy6iNVFMbraE+VkdjeT310Tp8uvdUOGtn6cv20Z/rpzfVSyI+QGYwST6ZIeqGaVDqqKaKSlGOL67jdjsF4ZAl6+wbt3waeJYrZ/xaKCielUnTS9HKilHMlEIUM8XwhJJaFEv+YeKp9LqwWOlhLrZpWRZt92xlwRmTJ9RlWlEVlICOGpA/kRKJRCI5POQvh+RNRS6Xo6enh56eHiZNmkRtrec647oubW1tI9IWJ51GIpERTwPr6uoO2QJSfJr4WigKpuFMhKvMWLxWV4yjQTxj0dqXprUvzd6+DHv7Mtj2IDGjk5jeSdQ4QETrRFezpQUqXSEwD1oxXuDiFlYkEbgoiooQKoZioClhNMLohNAIookgwo2Qt/xkTIV0Hm/LCTJ5B9cRBOwAATuApqgMHEI9hOoitCRCd3E1B1e3cXx5tJBCIKwTDPuIxkJEI2EqA1FiShgtaKAGNHTVQFO1Idc4RcfQDKqCVRjqkGgQlouTMnEP5MmmU7hJEydtEUlZhNJ+GrN1MK6LmIk1KtwBKH7Ns/iEPUtP0eqjhQ2UoO4JHoXSApDFoAZKcUKU+uZ025BIJBKJ5PVAiivJMU0+n6erq4vOzk66urpIJpOlzxRFKYmr6upqli5dSjQaJRKJEA6HxxVFciA48biuYF9/hq2dSfb2pVEVZeSaRZqCzxD4ddAVm55EP50DnXQnurGtQfxqEr+awq8lmRtM4VMzpbwF4LgupgMJu5wBq4KkY2CSxyYLqoVhCXy2TsCM4DcjGGYI1QyjmEFc109x3pOuamiqjoqK6ZrYrj2iHv7C5ukHb5FFRROIoIUedPEbgoChENBUfH4NI2DgC/rxBT1XyKA/SMAfIhQMEVJChPJ+1LQniJykhdtj4uyxClHiCqgKakBDDeqoQd0LsucHX0THzPSRTVm4KRMnZSHyr75mkqIrqBGfJ5KCumcx8o+0HhWPqQHdszRJJBKJRCKZEKS4khyzJJNJ7rzzzlHHy8rKqKmpKa05Ad6E4zlz5ryRxXtb4q2hNEAiuY3u5AD7ers5MNBDX6ofxU1hqGkMJYtQbEzFwcYmo7je0qdKYUFKbAQOOi4NPhfhczFU8CmgKYUlWYUgY4dIWhES+SBxK0LWiuIKtRC+26A8HyGQC6Hnhtw4NUXF0HzoioYjXGxsUGxszcI1LHI+C1f33PGE6iJUl0ggTHmwjIpQOTW+SmqcGOVWEL9Q0F2BYjqIjI0oCqJC9GxsOCga+TC8VRfHXvUHzxLk89bQwRW4GYtcX4JMIkE+nSQYKyNWXVu4nMDKZvEFg4AyZGmKGGhFERUx0CLe/kjmGL0Z6dvfhjLsAYoQgv2bNxKrqSNaVY06QZZh13HIJhNkEnEy8UFvPzhIJjFIWU0dC894RynthgfvQdMNIpVVRCoqCVdWEQhHDmvtIiuXxXVcAsWFOm2LTY89jOHz4QuF8AfD3j4Uwhf0Nu01WtdHlaMQOU4vuFpauRytL63HFwjhCwXxh8L4giH8wRC633/E/U24LoNdB7DyeQBqp0ybsDocNn27INEOxQcuhSURSj6x008FtdCncnFvRWXfmzdIwJjYedj7BAzs9epW2iLevmIqFNa6QxQXc369ymJCphfSPZDq8fbpblj2Pgh4QZnY8zjs+gsEKyBQ7u2Dhb0vAmWToLjeXu9O6N0OdhasnLcvLGyMa8Gi90K0MKbY/Shsvx90v5ePP1rYF143LIZQIfhFLgHZgaGARYo6tAUrQZPD7Lcj8q5LjjrJZJLOzk4OHDhAIBAoLToXiUQIBoMYhkFDQwN1dXXU1NTISb2vI978sDSm2UM+303e7MbM9zCY7iSeOkA6O0BcxLn3qbspRiJXgRrDC/kc9uuE/RpCuJiuienksVwTx/YWLMVxUF0V1/EjrDBYEchHyZkRUnYIxwph20FMM4pwh9zhYkC5opSCIuiqjk/1YWgGvqiPUDhAVXWU8uoI0coAkYoA/pCOL6jj82tYwiJlpUibaZJWkpydo0qvoDpXjtLvYPdmsXuzuOniHK3CWjmMDBqnBvWS+5yiqgjb9dbusV2whfe+sCmqghr1eQIoYqBFh+1DBoqmkOzro/3Fl+jYtBU7mUUT3oKjMcOhesoMtJBBX387W5//G9GmGmacuIbq6a99AJro7WbL44/iOg7hikqilVWeIKisIhCJvi7i7OBwul27d5LPZAiXV1DZ2IRyiOGAe/e1svXJx+nZu5u66bPA8Fx+04MDPHfXbQComka0qoay2jrKauupbp5CWW3dYdfLzGa4/yc/wLZGu1MCOMPmdrquQ+uG9bgHRerUDR+BaJTaKdNZdOY5peN/veUGRGENF9d1yaVS5FJJXMemcfY8jv+7vy/URWf3+mcR7thWy+rmKZz4nqtK77etexxfIEi4opJIRSXBaGzMtrVNk/Ztm8mlkmSTSXLJBLlk3NtSSabMm83ik0+Cci/s/MuPPOiJCsfCEx0uCIGqwKTJ1SxbOQ8WvwfHtnjkhp9D/x6EmYLSUhYutuXQUBth6cImOOXfcV2XR2/6BcTbCJLhHSdN8QbOgTJvkFx8PWnl0CA11QP5BFhZcPLeQLm4dy2Yc/6QCOrcCMkuUAuDXeFCph9S3V4ep3x2qEE2/h90vMIamlNPGsp3w63eoN4XgUgdRGohUocSrKYivXPkeZtuh55tYCYhnwI7NyTcAC788VDdnvk57HtqWPu6pXYG4OKfDQm6F2/xhJDmBz3gCYHivnwyTD/da8PD4en/8fIcj/O+5wkWgJduhS13euJF8w3bF16vugZi3uK47H8O2p4ppDFANbx7ZeXAysCSKyDiLT7Mlrtg05/AHOfJ1exzh8RVfD90bzm08nash5f/OH7aOecPiat8EvrHX0uL0784JK5a/wbrbxw73Tv/n9c3JG87pLiSvOFYlkVXVxcHDhzgwIEDpFKp0md+v58VK1aUgjucd955b7o5RG8GvDVtBsjnD5DLdZDLd5LPdZDNdZDOJcmaDlmrsJkO7rCw52nLh0IFKBFioXLCYR++gIopLHp7LXbvFZhpFdUMomYDKJbfW+vJVUtrPWmqF3pbU7TSXCO/rlJmaJT5dfwxA8Wno/kMNL8fze9H9RneIFFVMHwqkQo/kZBB0FDRbNdznUtauB0p3F2DJeNSBkprUUWACD5wDJxkhqzIjGwYBbQyP3p1EC3mWYVK85FCOop2ZC50wnXJJhP4Y+HSAP+ZO/6P9q1D69YY4QBNc2fRsmAxFQ1NpXTtT+8i68+Q7tpF5//toqZlKnPWnkz15LFDDBetH/lMhkRvD/HuTgY7D9A4aw5TFi31qqmodGwfe1CiGz5mrzmRWatOKOWHEIcsfoQQJHq66dixle49u8ilUli5LOX1DZzw7iu9RMlOnv/DL8ink6Dq+MpqqJ89n/oZs6mdOg3D5x+VZ+++VrY+8Ri9bXsLdVDw6UNrxNmmSVVlmHhvH3beIp6JE9+/C1BA1Zh1/GqOO+OCUn4HCy3Xcejes4vUQD8zlh8PioIvGCJaXU38wH5C0QihsgpC5ZWEyqsIlVcQrhiKfClcl/mnnkV6oJ/UQB+p/j7S8UFsyyTV30e0qmbE9fr27xsaNB+EbQ6JOUVRmLP2JHJdezCzWfKmg2namKZFPpvDHxqynriOw5a/PYrIJT0rhGOiCouQT4BrU18VYMHCaXDKvyNcl/X33AE9270Brhj5KCGXexnEk/B3P0b3+2mev4j8S3diJvvIW2DaAtvxVmNT/F2wYz8sfo93e/t6oPeAN0g9iLw2AAe8hV01XSdcUYlqthO0stC/a8z24F2/HXr93K9eWQTNPm/o9a6HYe+T46c100NipWq6J9I0/zCLjDK0G95fzEK9zBT0p0rlVl2XmT09ID4+lLZ/1yuXdzhW1stzPIb3l+wgpHvHTrdvHUw5ceh9us+zuOjDfktdxxM9ldOGhM20U6BvB0xaAY7ptU9pS4201DlWwepje+U+mOEPAwZaYc/4S48w94KhMiCGhJXuh3AthGsgXO0JleCwcOlTC+I/O+BtucHC60EvD2dYQKOKKdC8GoygJ0KNoGd9LIq90ND/MpNWesLQznuCuCiM80kv3+FpNZ8n9sRBghjhCXrJ2xIpriRvOA8//DB9fX2l94qiUF1dTUNDw6j1IKSwmhhsO0kqtY1kagu5bJsnqKwsWcshZzrkLIes5ZK3bVwc8k6IjBMl44bJOGEybhhfoIxgIEZnci+z5laSdfvZ3ZXG2OcnMBjDl4qAKEQ+BDRVx6/58Ws+An4/0ViIsvIIlRVlhKN+AkENn+WipyzURB63LzfkelfEobCukRf/W9EUlKD3teXuTYArxne9OwTUsIFeE8SoDqJXB9GrAijGaHcy13XIZdLk02ny6RS5dArHthCuS/OCxSUx0LV7J33tbQjXxcxmyMQHSQ8OkEkkEK7DuR//V/yF4CqhWBkoCrVTptMyfxENs2aj6aMj3s06fi2T5y1g+1N/o3XDenr27qFn7x6qJ7cwbelKmuZ4a5zl0ike/tVPMXNZhOuOyscXCJTEVaSikvmnnYWuG6QG+kn195Ea6CM96IkBzRj6v0v29fL4LTdQO2UaddNmUjdtOn4dSHZ6A7PCoFP07Wbzw/fQ3rqfdLIwOBLCG6Q5efLhYSGmt91LVW4bloDBpIs50Mq+thfZ99cwaiBKy/GnsfhcL5pmz75WNj/2F/r37QQzjWpnaalRmVWRwB/I0573LN3ldfWcVL8fEeoga0I87RLPCAbSLr0Jl6q9XYAnrnr3tfLiTd+mNiqoqIjS25ekozOJZVmoOLTsn4xx0Q8BWH3pe/H99Rso/YXlG+KFbZ/mDcyC5XDBD9B0g+nLVsILN4PeDg0+XLWKdF6QtzWMsOMN9qedCorCqovehZtPIRQNRVEJkCHgJAhYPWipDvjb9+GETwEwZ81JcN+9kN0NPrwNEJoP126Hv7XBCZ/CcWymLV1J+qmbSeeSpHMCV0BxuJ5Chbj3/6P7/dTPmIVfbydg5wj68OYT+hQCAR1/sDAAxfuOXnbe30FDEpIHCoNSH45Qydug6AbEvLWHVE3nhHdfidL5EmQHUFStEABFRTcC+EIBCA+tSXfWP37cG3znU95gNjfoWciKezs/0rUqWO4NbvXAaIuN5huyLoHXP21z2IAXz+IQrvE2ZVjaBYcW5AiAE//Fs7qkukZsIt5BMrmNasccuknTT4fGJQXXuojXpoX17goNNpTv4sth/sWFQXkhYIyiDaUfLm4WXgYzz/Tax857wtDOgZnxyjPcYvLcL6HzJahbAE3LvLbd+RfI9nsWm6VXeOnqF8AFPzw0d78Fl3pWJMcctlleORzLE0NF6hd4fca1C6LM8gSNEQA9OFKsTD0JGpdCIOa11yuVpazJ2w6FySu97VCI1g1ZsV6NmWd4m0QyDCmuJK8riUSCbdu2sXTp0lJ0vPr6evL5fElM1dbWShE1gQghSOVS9AxsoX9wM4nUy+Ry+zAdC9OxyDsWecfGcR2Sjp+4YxC3NQYchbitk3bDBLQAYU0lpNqE1Cx+w8KxUqSyHZDIEX86SiAxiSpXRVM0ArqfgD9ItDxIXXM5DXXVlJdHCEYNglEfht+7905/DnNfEqszjdWTBdebh1V8xqkGNPT6MGpAw806uFkbkbO9vVVY5yg17GmkqnhzjYbPQYp4gRxKP8pCeGKjYA0FzzJgGxYWJplsFjM3gNWexdyZxcrlmHfSaeiFPrnhwXvZ/cKz41oZGmbMLomr7r272fnM2ItOq5pGLpUoiavpK1YxbdlKT2S9CsFojEVnnsvM49eybd3j7H3pRXrb9hIqKy+JK8PvJ58ZcqXR/QHC5eWU1zVQXtdAZdPk0meKqjJzxepR13Edh3R8AF+gsB5asovuZ+7F7N7N/o4t7P+r54JVEXSoK9OoOO/fqZ/vDViU/c8wsOEvpBMumgq1ZSoNVRrRgIKhg/8dpw1dqLyZ41fPg3A1brKHvn27OdBv0jkQJz0wiGEM/TTFH/0Z/c9vQVNcptRqzJiiE/J799HN9IE67L7EmlA0g5DrEKp2aRAuuDZuPg3hoYVHu1t3kxoYJNWTA7pKxwOGQlOVipNLU5S5/lDYG9wXB4dFhAO24w2yh9OzzZvbgecyGy1s9ABtPpjutUPDzNnw6Leh44VR96FwA0fOawlWeANWM12yFCiOieb0Q9dmAAyfn4Wnnw2hXZDpRQSryCpR0o4fjBDhsjKo9CwEiqKw+pL3QOoMry6aryBQ/OPPEykOwgtowMGrMimKQk3LVGiZOnYeY1Ex5dDTHv/hQ0879wJvez0wAlDR4m0FXMtiS/oepurDLK+Niw89z3DVq6cppa0eKWDGQwhPEDuWZ0EbbkXzxzwRU+Rw3GaNYEl8vyo1s73tUCi6gkokb2KkuJK8LuTzeV5++WV27NiB67rEYjFmz/a+XOfPn8+iRYuOcgnfGtiOy77+FLs797Ct61l6Us8TVPZTpvUjFC9wRJFB20+XGaLXDpIwK3ByZUSdGDEnTMQO02yFCZohdMdAVdTSpqCMeJ1NZ6gqqyYYCRKNhGhsqaJmUpSqSRFCsZEiWQiB3Zsl83ISc28CJzly7ooa0jHqwhj1IfT6MFrMN+68GGG5uAWhhRBeRLxiqHBg38sb6Ny1g0RPN5nEIKKwwHFRFJ378c/gK7hQbXnwHnavf3bcdp2xYlVJXOk+X2mQ6w+FCYQj+MNhdJ8fVVVRhwUTqGpqRizKQe9WDExCUxYRbl5AqLyCYCQ6wrUuGIm+6v0d1pDg2oQCOktOWsvsBXPZu2kjkfqhgZ2mG5z2/o8Ugh6Ejiigg5qPEy2vGHqavusvTBu4h4pJgq64Q+egS9wUDKRgIKvA7X/inKnzCIQjEG1g5qJ5THWgriaGbqjeU/dghTcvpWKYVXrG6d5GYc6ebVLTv4sF3VtJde5FW3lyKemUSWWYBxSmNkUJ1k2HqhmeC1fldBx/Bdx771C+J//r2PUqtmGBWcevpSLo0t26k8HuHsprqmmaOYvqyS0o/sjoQeOZX/X2JUuc6VlEHHPIIlJk/iWeRcAuWBLsfMHda4w5JMOPGSFvfkh5M8SavNfDxdXJ/zaU1nU8V77hblvD066+BvBsIyFGC6ARlNyxJG9JFAXO+y8Y3FcQVy96Dwqmn+ZZcrTR1nKJRPLakOJKMqG4rsvOnTt56aWXMAvzBhobG6mvry+leT3Wd3o74Lou/clBdnftoL13NwOpvWSyuzC0vQglgYJNbeF30gVSjo9eJ8aAVQbpacRyk6jOVTLFjBBwAwR1A13ThoJEBDS0kF4QUd66RrqhohkqmqGhGyqKCrv37mTVyQuom1JGtDIwSgwJIbB7spitCfJ7E8OCRICiKRiToviaIhj1IdToSDFlmfkR8206d26np621kDGl+TVmJk2ir4eT3vv+kgjq72gfMYdprPYrlUPVMPwBjEAQXzCIL1B4HQhiBAJowxaknbFiNdOXH48/GHrleUe2SaOzg8bUHaAWHLH2bYTeaph3IcwavcD0QQ3nTbYf/vT60f+Ero1eVKth82FCwFyANT8ekUVZ7SG6shRx3cKckBegfT0M7IHTvwR1njWMiimoNbOomtZAVbSeedFGsmqU7t40XfvaSPT2kOrr9cTVtJOpm3byK19vPHQf1M5FqZ1LdP5BHy15F/OWvgdik7zABMM5aLHwV2RYPzMCARpXnknjyjMPr5yKUnBD83sx+8ficCwVZ37VE2CO5c2JOVTLgap56f2HIdAlb18UZcjKdtyhLfAukUiOHCmuJBNGR0cH69evJ5FIAF7I9KVLl46aRyUZH8fJYZq9pLPddA8eoCdxgHiqi3S2G8vqA5HHCzCexiaFqpu4gFA08kqMsvAMqv0LCJlz0ZI1WHGFfNxFLQ7ahs3XMAI64XI/4TKfty/3Ey7zE4wa6IaKqqkIIXAzNk7CxE3kMQeyaF0q1f1ZRH+ehCu8eVKuwDEt7FweJ2OioRfCQysohopvUgRfSwxfUxTFGDlAdmybzl072Pfyi/S07uGsj3zCG6wDvW17x3WzA2/ifEWD53PfNHsu4fJyYtW1hCsq0XS9sFaViqqq6MUok0KwcPUKFp56xsj5DuPgD73ic38P14V7/81zvwGINnjzPdqf88IJO/mhtFbOm3QdrYdEB3Rtgu5NnmuXa8MlvxwSEcU5CiNQPLetqhkjhdjfrvcGUZNXeQN8fZzRf7oXdjzgXbtn6+igAwOtQ+KqZY23DSMItEyGliXHv3q7TASH4zL2ZkNRDs+9SiKRSCTHPFJcSSYEIQRbtmwhkUjg9/tZsGABM2bMQD3ECGNvN4QQmGYP2VwbmUwb+3u30TGwiUy+G9NxsBwXcBEla4WgODspJQRZguTUalw9ytSaJczxn0isp56uHSmsnM3QUF6gKgqhMj8V9SHK60JEKgyiVSH8Qc8645oObsbCTdu4AzmstgS5hImbMHESeYTtRRFzXRfbzBPqdYjn96OqKqGy8tKVuvbsKoWLdnAww3m0phDR6bVUNUeJNg750QshGOzsYN/LG9i/ZRNmdihqX/ee3TTPXwhA9eQWBAKlMLm7aOUy/H6i1TVEhkVrq2mZ6s31GNnQQ/MNAgUXulwcbv+o5xpTNgnKJnuhi8smey5ZoapDsyC47pAIUlVPhOx5DOZfOhS22TY9V5zqWUPntT0NT/3Ym5x+sKuYZniT0WOFBxLHf8RzOyuGMNb8Xr4Hl89Mw/5nPTG290lv/kzjYjDC3to9U04cspxZWdh8x9C5RhAaFnmT7hsWH374ZolEIpFIJCWkuJIcMaKwfomqqiiKwtKlS9mzZw/z58+XASqG4Tg5crl2crn9ZLP7SWX20T24k/5MH8l8ioydwWFoLpLpqqQcHxlhYBLAVgPYmh+heU+4FUVjRvkMTqxcRn18Gj3bM8R7MsTFAPlUB66Twhdy8QVsdN0mXB5kzd+/Czdnk98dZ8dtj5AfSBPQQ/jUILpqoOqepUnTdPzDInnFuzuxzDw5J01eZMgreXoTPcSUKMFYjOUnXQSagqIqbLv7OXLpJHrQz0CqCyEc6AA6oLy+kVOv+hAAg12dPHfnn7xwzQUCkSjN8xcx+biFxKqH5oDUz5hF/YyCMHEdLxywmfYiYmk6BIYWEKb1Cc8K45iegBrY461VYmU90XDqtV66YrSxTJ9npRloHXnDmpYPzd2xTS/SVnH9lmJEMkWBXY/Aiqu9SFjguf4dd9HIOQy6D5pXjcw/1eVFAzPTnsCrmQ2186BuvmeNGh5M4FAnuBshz52v7Wloe8qzTrU9M/R5bFhErWi9F2Us1gTlLZ7wkwtdSiQSiUQyIchfVMkRkcvlePrpp4lGoyxd6oV3rqiooKKi4lXOfOsihEve7CaX3U8u104220Ym204y00XWtBnIJUmaCbJOBhcLVygM2n4G7SBxtwJFb6Q6Oo/aWBVTIyHKAgF0TcdQjNLCuYZqUJ1pYnCXTdezCXY63jonudR+rOxmIIEvqOOakDMBAWq8isSjbZj7kuAKfAMGqhUCCyyyWGRxcLBVE+GDOUtPQYv50WI+Nt/3NH19+8HwLGi+UJgBkaZpwSzKamrxTxuyRq3+0D+UgijYlsXggXb6O/bT375/aC6QmSa06WbSOzeiKQoN9eU0N1dSW6OhaFvhwABUDwuJ/JevekIhn/Qm8A+ncjq845tD7zfcMva6L5oxer2Rd/43pHsg3uZN9I63eQtSJjo88VHEzsHuR8e/6VvuGhJX47nhHczCy2DW2d5iqOXNI9eeOVIUBWpmeduSf/CEZXshKli0ASqHWfQ0A1Z88LVfUyKRSCQSySikuJIcNu3t7Tz11FPk83k0TWPOnDmEDmVeyluUfL6b/v7H6e17gmR2YGgBXtMhY5lYJEk6OfodlbjtZ8CuJiFCRALNzK6axRmNx7Fq0nGUB0eGn7XyDunBPKmBHKnBPKmBPPHuDD2pIQERrQoyeW4FHVs30d2awfBHqGmZStAXJZSJ4BvQ0SwVs9WbB6dXBWhasBRbtTBFjrydIWclyWaSWAkbzecjsrqxlP+s004EIQiVVxAqK0cA99xzD0vPPRfDGBllanh0Ot0wqK6OUe24UFUFM0/1PjBC+Aa3s7olTUVYxdCzkD0A+wonVs0Yud5Mqmu0YDKCnrvbweF6GxZ7IkzzeS53FS2eAIs1jbbMqOrQWiaTlg8dd2zP8lVEM2DRewrR4YpryXjrNlExBWaezRHxeoYbVhRvvlfltNcnf4lEIpFIJOMixZXkkLEsixdeeIGdO3cCXsCKNWvWvC2FletaxOMv0N//V/oGN9ObMulPm1iuRtquZtA2OOAk6LIHiLvVaLqfskCYxQ1LuXjyApbWzyHm99YXcR2XZH+efbv7SPRmSQ3kSQ3myafHjoSm+1TKq3I0z2uipqEKbJcy4wSqgvVMmj4PpyOP1ZHygsv5QImo+KeVE5hZjl51GBPn8ynqmyd5C3QW5vhY40Vn69/jzW3K9EOq0wvOkGj3PvPHYMYZhQUxFVjxIWrzicKK9s7QAp+uM3q+z6qPeXOMfGEvMpoRHt+FbeWHDr1u46HpI/M3gnDc341KlnVcFCCgyTmFb2aE62L39KJXV6G8QVFMhesiLAthmt7eshCWjW/SkOum3deHmx1aP0uLhNHKy9+Q8kkkEonktSHFleSQ6Ovr48knnySZ9CKLzZ49m0WLFqHrb68ulMsdoL//cfr6n2QgPUhvKk8y69BvTWF/diadwiXv24bQ4gT9GhW+Wo6vnMaJk05kae1SDMUgOZAjvifLvu524t0ZEr05XMcd83qBoE5ZQCOqQsAWkEyT7+3H3JcmsyvJYM1Q6O1q6sj195XeG/Vh/DPL8bfEUPRxRIAQMLjXm5/TtwtO+exQsITnb4DWx715QYWwz6oeZvaBVtSHn4Wzvz6Uz0u3jrEYasGCUj/fs/wU3eYmrzj0Bi9GrTtK5ByX/XmT9pzF/pzJ/pxJe95kwPICd/xzSx3Ly7y1s/Zl82xO5ajy6VQbOpWGRkTX0A5nYc5DYNCyac2atOVMco7L2bqD0dmJ1d7Bs/1xds+Yg9rYgCvAZ1mojz9GZUsz1TOmM7+hhvBrEBFpx2Ff1mRfNk9rPEVPKkPYzPFuM0k4EceJx+lPpCi/8goqAn5URWHwtttJP/kkasCP4vOjBPyogSCK348a8FN20UVoUS+keG7LFsw9e0DTUXQNRddR/AHUcBg1EsZoakJ9DfM5hWmSb23F3LWL/I6d5HfvRuRyTPrhD6DQLqnHH8fu60OvqUGvrkGvqUZRVdx8fpQIyrzwAnZvLyKXw83lELk8Ip/DzeVBgZqPfayUtvcnPyG7aZO38PDBKAqTfzIUVn/w//5I9oWh/6fomWdQfsklR1xviUQikbxxvL1GxpIjwrIsHnnkEUzTJBgMsnr16hHrVr3VEUKQTG2iu+se+uKb6Uml6MukSVgae3KV7MyXI3wDVJQ9R3lAR0HBr5Wzsn4la5vW0hRpoq89zcYHO+jZm8TK5wAFdVjgA92vUVYTpKzMT1QFv+mipU3MniRmbxYrlyWTy+IcbDnSFVRDQ/GpKLqKYmjoNUECMyvQYuMMQoWA3h1e8IP9z0Cqe+izgT1D7mRW1tu7thc6PDuA4rqUZ7pRetLe58UQ0hVTvDlRoSoIVnpBEurmjVqHp9e02Z8zEYCqgK4oqICmKOiKQp1fLw3+LVfgCIFfVcZdWPi1YLoug5bDoO0waNne3nZYEw1Qn8uiaBqP5Bxu6Y6Pm0eF4ZXVzWR4ae8Bfp+xUQruksKycLq6CCkQU+AKkWOmoaL4fLTrfnbX1BGrriKsaQSSCZyH/0IgnSKQTKJm0ohMFlSVPZEYe1aspmvmbFpzeQYyOczWVu8apsmspx6mMu9ZObZOnc3jVZMwAt5DEGdgAFMLwf5e2N/L57pbmTF3FsFFi3hAD/FAX4KorhLVNGK6J+LDlkU4n2OxnSOcSuEMDvLnnMvzs+bSa3sPAaz9bdj9g6V2uODJB7ELkSJvm3kcL25uRfP5KNd1hB7DnbkITbhoQvDRjc8QcLy0L1fWcqZtl/LJvvwyqb88PG57133+8yVxk3z4ERKPPUp1Vxf9bfsxohGUYBA1FEYNhQitWF4SbanHHiP9zDOYe/eOEjdaVSXKMMGWeeZZ8jt2jHl9NRKh6bvfKb1PPfzIuGnRR4pY4bqjhZWueWLxoIdUajCIVhYrvVf8ASQSiUTy5kCKK8mrYhgGy5Yto729nRUrVuD3H+LE/Tc5GSvDrq6/0NF5B4nkHhL5NHnHpj0fYWeunG47QkXYoK4W/LofRVGYHJ3M2sa1LCw7jnjbAXbe8SyPbvk9sdqT0AqWm0x8B+n+DQRjUcpqq6mqradKryKQyKEeAF/AEywuEO/qJJtPktXSZNU0qXCO+hlTmXPiiURra8YWHa4D+QQMdHhR88omQ6jSC//euZnE079gwMwzqAQYVGMMhBsZLJvGxZMaqYl4onljMsOjU66kcvoVlAuLcpGj0skQMeNse/ZJTjjhVAKq9/XRnjPZ03wemaZzyDguGcclbjvE21MM2nH+qbmWSQFv8LpuMMUfOvvHbfN/m1rPgmiolPbn+3tQAJ+qEFBVb9M8IfbuhkrmhL22ejmZ4Z7eOCoKaqFJLFdgC4ElBJfVVzIv4qV9ZjDFz/d1kcNLKPJ5rK6ukquWb9N6lnV3AGCUVxE6+SymzZ5JU8BHg3CIPHA/TT4Nkcuh3t1De28PbjqNXlnD4lPPJDV1Gr2mzWA2i9U/QByIA+kN6xhMekLt2cYW7l59MnrWLZUhp0QgEoFIPR/e9Bxz4l7al2PVPCIMjKQX0EMRgpr+XppSCcKWhU8Bo6kJo7GBZU3NVDdW4a+tQFUUMiGdXivDQGcXg6k0wT27iW/fSvyOP9O6aAV9q0+k3yqI2fZ27L6he/Ov6/9GY8ZbDDk5ZRY9k6ai+HxU+3Rqcalq20ktAjNWRtncOWhlZWgV5RixGlRVwxXQb9mIpklQV++JC8ehesUCfKZn6clanpAo4p82DWGaYNsI20bYDiKfw0mlcFNptOhQJEu7rxe7sxNfdzc5ITAPCloSmDO7JK6s7m7MXbsB0Mpi+GbMwD99Bv6ZMzCamkacFzr+eIzGBuyeHuyeXuz+fnBd1GBgRFkBAvPmolVWelY5f8DbBwIFq1wAIUTpf7Ty8su994YxtI2zVEXllVeMeVwikUgkxz5SXEkOiSlTpjBlypTXxYJwrNCV7mJXfBetg3voGXgaI70Rn5vGclxsobAzW87WbCWGUcPcuslc0NBMY6SO2lAt1YFq7AMD9OzeReez67lt711kUxbC9aLshSt6mbZ4IZPnVdL6Qjt71keI2FGiPSFCnS45esnhTZNqXDIPf2MUvSZEb2sP+7v7ONA4g12RSvZrfq6d0USsIBSei6d5sGeAcLaHUGIfoXgrTj5DWjVIKz7em9lAw8orYNop3N0T59Y2E/xrIKB5ARWC5d6cKFXjhPoGanxevnuzJs/Eh6/BpAFRhBumq/YkmiuPY1bB8rYhmeF3B8YXTP2WXRJXdT6dlqAPDQUHgSPAEQJXgIPAP2ywmXMLwgPIu4K86xBn6Ml/1hGl1wOWw8Zkdvwy9PWTemEPua1b6O3qI3X8yeh1dfhUhZiuoe9rJWbmiZl5qrJpz+rguMwa7OM6J0nZNG/dKevAATqffrK0+thwZ84FVo41dorYDG+wbg4M0N3fRsKySVg2zYsW4jfzCDNPveZnqQ52JEjacUipCon6OrK6jqJpNC6ZRV3EE5nH5ywEOtOqKpgS9DNJAyXogAC9qhK9pgalYPmoAkYEfq8thxnNADiJBNmXZpDd8CL5rVs5bfMGzrzwXDKRGEnboXPvDnr37ybl85OJRKiqrsIfakIrL+e08ipOmlTFlOpKwrqGO7UO5awTS9cdzj8DrhDEbYcBy8EULq4AW3j3uywaLC1qvTJnogaGrEahZcsILVs27n0cTvS00zDmzmPrQw8xc9FC1LyJm83iZtK4mQxqdMhqGl65Et+kSfimT/fa6xW+xyInrAXWlt4L4d3tsc6JnXPOIZUVkHOmJBKJ5G2CFFeSMRFCsH79embMmEFZWdlbVlQJIdjYu5GH9j3E7sFdxJw+ap0OAiKDKyArfOzLzqDbWsWSpkV8dM48ZteWj2qPbU8+wfr77iObMjGznpuT4Y8RrWqkZeFsjjtxEeFYFKszzbTAQhobm7GzeWzLxLEsclqWhNZPnD4mr11NoqySZxNpnmueQWtNc+k6ChDWVM+1T1E4kLfY3NflrecEoDRCoJBS1TjHSNKgeiIopKlghDCqZ1AeqaDc8FFhaFQYOmW6Ro0x9HWwIBpEV6oYsO2S69yAZdNvem6JmWFzxOp9BvMjQUKaSkhTCWoq5brnZlaua0wJDlk6V5ZHWFk+ZH14Jc6sinFSRZS865JzBTnXLYgsF9MVTA0ODcpnhQN8eHINrigsvWw7uK2tuHtbYU8rZfv3MmB6SyvP1HS+2N1K82krCakq2DbJ3r3oVVXolZVoVVWoEa+MIpsdsWCvGolQ/q7LvMG7349eU4NWVY1eU416kEXXV1HBpHPeMWbdzihsI5g/FVcIso6LX1XRCya4xYVtBMcdd0htOBwtFiNywloiJ6zFzefJbdqMPxpGK1gK3dNOQJx6Amo4NKp/H7za1sF1PRhVUagwdCqMV/6JmRQ48vlTelUV/liM3K6dhE84YVT0yuH4WlrwtbQc0XXeqt99EolEInl9kOJKMiZbt25l27Zt7NmzhwsvvPAVBy5vNoRwyeR6eP7Aw7zQ8RjpbCfCyjDNzRBWQMWPcCfRm19FbfW5XL6omfmNMfSDIsOl4xl692fp2h2nq9UgPaAQi84hWFlHtLmRxoYy6g0dN23R99ABblb3kVcEmgA9pOCrDBKoriAQSjLV7GVltBxmv4f18TTf374f+nYCAkXRmW1YrPA7LDFMqp64yVtbaf4lLC8LUTV9Kunev5CumE6mfCpGpIZwIExYN6iPXgCFAe4JFRFWl88kcAhzmFqCflqCowfQlmVx1+6NHBcZco9aWhZmaSGow0SiKAoBTSGgqQwPWu6k0tjdHTiJBMl4AjeZwIgnWFAWo+zCCwFvLlL7b36NKM5R0zT8M6bjnzOX2rlz8LW0DEWHMwxiZ545dhkOioSpRaNETz11oqtaQlUUwvrrH7VO9fsJLV0y8lh44u+hRCKRSCRvN6S4koyit7eXF198EYBFixa9JYRVIvESvX2PksrupzOxg75MNznbJui4+FwFnSiGUoMrwhA4idkt53DllEYCxtBAVwhBoifD3md2se/ZZ1EyAl/tIjoDgg6/wv7j38lgSCXvU1EUhdPiKS5JeYLMUgWPVLkomoLiB01LozgJGEzCgMvJ+T0sMbph9jnMiQTxqwqzUztYkW9jqdVBTORHVsjKwvxLaPD7aPBXwrn/OsLCMha+ceZ3HC5HK/i4cBx6fvBDL4CAEKM+NxobS+JK8fkIrToexTAIzJ2Lf+ZM1IAMCiCRSCQSieT1RYoryQjy+TxPPPEEQgiam5uZMWPG0S7Sa8K2k7S330JX3xP0ZHvpzfRj2g55R5B1wjhuM64zk4pIE1PrW1g2cyUV4aH1pwa7Mwy2p0ht7sdu7SGbSeDLZWggRr9f48fTFDRdR9UK1iBVQdUUNF2FsgDh8jLUqI9IWOfCTJrgtj/hDnRhKyoOCg4qli/MrOoGaFrtLdirqfx4bjO+8lVgHgf5FJiFzcpB1XRoWj6yose465KTSpHbuJHsSxvJbd1C1Qc/SLDg2mZ1dWH39GLU1aJVVaGoKsK2ye/cidVxgOhpnqVI0TSEY4MQaFWV6BUVqLEytFgMrSyGXl094pqVl1/+htdTIpFIJBLJ2xspriQlhBA89dRTpNNpIpEIK1eufNPONxBCMDCwju17f0V7vJX+XIKXU+W05xswnSYC7vHMLFvI6uk1rJxaSW00gJm16T+QZvOB/cS78yQPJEkn+uhUTfZGDFpbfExJ+Lm0NYWvIsL8eVOpr9KI+XVmRYPMrQzTHA1QbuiENXVU272XELQ70LcNauZAwwJoWATlLaPEkU/TYNKhTew/VrG6ushu2EDupZfI79o9wtqk19SUXmeee47EnXcBoBg6ek0N9sAAIpsDVSW0ciVaxHNZq7jsMtRIBL3q4FlAEolEIpFIJEcfKa4kJbZv3057ezuqqnLCCSfgew2LdR5Ncvkentn6Hdp6niZlpum1/DydbMa059ISPJ6TJ09jOgOU6XHMnk62b47z+J5e4j2D2PkEg7NPYTBWTXsFxGtiuK6JwMVSTfa36My45GTK67yQ5T9w3fHd7QbbYP2NsPi9Q2tHLX4PLP8AGG9tF7XMs8/S98tfjThmTJ5McOECAscdN0JcqcEgRmMjdk83wrKxOg54x6NRggvmIywT8MTVkQYlkEgkEolEInkjkOJKAniWnvb2dgCWLFlCZWXlUS7R4ZO3cty14f/R3/tnLCeLKxReTtfSN7CMkyafxrlLljG3IUpf214e/93/0ppzSMfz5LM2ChBTy2gMzOD/KmJ0lmmoqkLYp9HsM1gwuYJltdVMD4dKUdxgnHlMZho2/i9svx+ECy/cDKd/0fssWPHGNMYbgHBdrH37yG3dSm7LVoKLFpVc+PyzZ6MYOv6ZMwksXEhw4UL0cfpU9LTTiJ52GsJ1cfr6sLq6UcMhfG/x0P8SiUQikUjeekhxJQG8yGynnHIKe/fuZcqUKUe7OIeM7dg8sXcDT+25D5H+CzEtAUCPGaXLOpu15mRC8V1MbuhjXmMMIQTJAQUzX03K0tk2pZbdleV8plvQoAXxB/2cZugkoyEWTa9k3qTyQw8EIQTsfgRe/J23iC/A5JWw5MrXqfZvLEIIrLb9hLdupb+9HXvnTtzM0NpSiqaWxJUWi9H4ve+hHob1U1FV9JqaEVYtiUQikUgkkjcTUlxJSqiqytSpU492MV6VeHaAh7fdzc7Ov2GZ24ipSaIKoIEj/Nj+d3BW1dnEX1hHNrETANe22buph9YN/fTEs7w8dS0bYgpqWMNnu7QbCjNyKoE5lVw4rwotOoYoyA5Cusfb5wahaRmECtaY3Y/Cht9DdsB7H2uEZe+HhoWvf4O8DgjXxe7qwk2l8M+cWTgo6P3+9ynb30authZVUVFDQfyzZuOfM5vA3Lkj8jgcYSWRSCQSiUTyVkCKq7c5/f39dHR0MGvWrGN6jlVb32Ye334rPYMvoLsHUBDeLBwNFFR0rYaqsqWsmXoVe9etp2P9vQAEY2VMX3YaB3YHeOqv7bwQg02TFPSYQVhTqRkwOTutsELzUXbOZIzaYesaORb0bIMDL8KBDTC4b2ShwjVD4go8YaUHYMGlMOsc0I6Nfy8hBCKfx0kkcJNJhG0TmD279Hnqb09gd3cj8jncXB6nvx9z3z5EPo9eV0fDV74MeJYl/6xZ5B2b6DnnEp5/HL7m5qH1oiQSiUQikUje5hwboz/JUWPTpk20tbWRSqVYtWrV0S7OmDy05Ta27/424FBccctyw2j+2UyrXcPamWcSCzXS17aXdbf8DtsyUVSNqUtWomiz2P5cAiEy/H6yglLhIxY2aIrbnNFhsTivEpgUJXJiE6pf91z7ivN8dj8Gz/58WEkUCFVBsBwC5WAME2INi+Gsr3sWK98bsxirEAKRyWAPDCLyOfzTp5c+G/jd7zD3teEk4riJ5NBiuoBWFqPxP/+z9D7z1DryO3eNyl/x+dBiUYTjlARU5Uc+TN899xB9x9lvifXPJBKJRCKRSCYSKa7exsTjcdra2gCYM2fOUS7N2PzmmZsY7P5vNMUl4VQTipzAyinvYEXLUlRVIRMfJBz2gkQYNXW0ldfSW17FYN1M/tTn8K62OACTZleyvFnDMm1O35VlzoCNoqiEl9cRmBlA2X0f7HwIZp8Ds872Lt6wyBNRDYsK20LwR8cuaLDc215HUo8/jrlnD3Z/P87AIM7gICLvLS6slZfT+O1vldJaHR2Ye/aMOF/x+9FiUbTykUE1gkuXYrS0oAYCXppoFF9zM3pDA8oELTwskUgkEolE8nZAiqu3MZs3bwagqamJ8vLyo1uYg3Bdl/989L8Jpm/Gp7pY6lSuOe2XRANR+vbvY9MjD9C+bTNbQuUYp51HW86kM29hzl9LJmGT7/MsNW6Zj1UnTaZ6UoSmbX3wwiCKA2rYR3RFEKPvbrjjYbBz3oUPbBgSV5EauOinb+gCvXZfH1ZbG2ZbG04iMWIh3MzTT49pYVLDYdRYFCFEKbpe7NxzEfk8aiyGFo2ixmKofv+Y14yedtrrUxmJRCKRSCSStxlSXL1NSaVStLa2AnDccccd3cIcRCqf53P3X8cU5S58qkvQP5t5kz7Pj598gZ19A5zd+hJ6YUHa/bF6DvQOoOkGubiJrzfP3JRLS0awNBZkVmUAnjlA36M2iuud46vME4k+gPrk00BhYdtYE8w5F5pXjyzMGySsrO5uBn9/K7mC4C1eu/zSS0uiKLR6Nf45c9Grq9EqytEqKtDLy1HGmCt3cHAJiUQikUgkEsnrjxRXb1O2bt2KEIK6ujqqq6uPdnFKtMfj/Pv9X2dx4HECqkNZdDlb3fdyy+a9XgI9QCJSweKWyTTNnsfkaC0bdg5SvqGPSX0mEQcMv0a0KoBhCtzuYaHCDZXQohoCB36EcqAgYuoXwpzzPLe/o7CmkrAskg8+SOLe+7x5UZqG0diIb1ITxuTJ4LqltJG1a9/w8kkkEolEIpFIDh0prt6GZLNZdu3y3MuOFauVEIInXlzPjX/5ASfXbAW/S7bifP4a+wcG0zk0LcfxAY2lTY2c8I5TsLtN9m/tJ75tDyvieTRXoKgK4aYw5c1RtIiBGvWhBjW05CbUqQtRy2IoqgIVF8D+eph9LpRPPqr1zjz/PPE/3wmAf+4cKt79Hoy62qNaJolEIpFIJBLJkSHF1dsQ13WZPHkyqVSKurq6o10cMok4v/3pD9jd8QKrj2vHZwieDP4D8dA7UF2V6RVlfHD+dOpslbYt/bzwh93kUyaxnE192sLwaQTqQ9ReMJ1AddDLVAhoewY2/gHi+0G/BCou8z5rWuptE4ibyYAQqOGhSIHCdccMCDF8blTo+OPJvvACwWXLCK1YUToukUgkEolEInnzIcXV25BwOMyaNWtwXfeoD+bjqQz/7/qvk+zdzoz5nfgrBJOrZ7O39myyjp8La8s5uzzKpof3s2W3F/lPEYK6nE2VqhBsCBOeXUlkTSOKoXqiquMFeOkPMFCIlmeEwBd5XcovbJvUXx8ncffdhFasoOLd7wLATafpuPZzGE1N+Fqa8TU3YzS3YLa2kvrrY9R+5jOoPh+KolD90Y++LmWTSCQSiUQikbyxSHH1NkY9ymG2H96xjd/f+l0q+zupXpBHmxzluKY5zJ5xLcdpdWRdlxpX4Znbd5PozYKiUFcXpCFt4Qvrnhvg8noC8yo9kdj5Mrx0K/Ru9y6g+2HO+d6cqglee0oIQXb9euK3347d0wtAfscOhG2j6Drm/v0I08Tcs2dUSHSA9F//SvSMMya0TBKJRCKRSCSSo4sUV28jbNvmhRdeYNasWZSVlR21ciRyOb7x6P/y4p77OMHqxlzdwKM1Z7IikuLd099BMNhEEEjH8zz5511kEia+oM7S5bXwci/CFahBnegpkzHqh4mm1sc9YaUZMOsdMPedEIhNePlz27cT/+OfMPd6QTbUWJSyCy4gvGZNabFd/6xZ1H/ly5h792Lt24e5dx9mWxuKqhA77zwip5wy4eWSSCQSiUQikRxdpLh6G7Fr1y527NjBgQMHuOCCC46KS+BD2zfz/Wd+Sc7pYFFdP63TTuSAMRt/oAylbAV6oAWAwa4Mz969BzNrEwnrLJhehvtCNwjQa4JET6hD614H/hlQMcXLfP6lnrVq3t9BqPJ1KX/qr39l4JbfAd6ivNGzziR6xhmj1pBSFAWjrg6jrg5WrgQ8a1fxM4lEIpFIJBLJWw8prt4mOI7Dli1bAJg7d+4bPsBPZHN87dGbearrMSb5EiypMNgaeQ+WVk7MX8N7m2dzfm0VqqLQsy/J8/e1omVsJmnQIATuLm++VWBakHDZepSH7od8AlrWwNp/9i4SqYHlH5iQ8grTxNy7l/yu3WjlZYRXrQIguGQJ8Tv+TGj5MmLnnYcWO3TLmBRVEolEIpFIJG9tpLh6m9Da2komkyEQCDB16tQ39NovHWjjsw9/l7zdzfHRbkRwIRsia9H1MNPKWvj41OlMC3mWn/1b+tl5Xyu1GYuorlBWE0JVFPQyl2BwA/4D98F+y8s4VA3VsyakjHZ/P+auXeR378HcvRtz/35wHAB806eVxJUWjdLw9a+hBoMTcl2JRCKRSCQSyVuHoxvRAPjxj3/M1KlTCQQCLFu2jMcff/wV0//oRz9i7ty5BINBZs+ezU033TTi8xtuuAFFUUZtuVzu9azGMY3rumze7C2aO3fuXHT9jdPU+wcTfPYv3yemtHJh1X5WhSPsVo/DSmmc3biQb82Zw7SQHzdn0/rnXfT/73Zq4nnKfCrl9WGCM8opm7md8vy38fffCY4FFVNhzSfgnT+E2eccdpmE42D39Q29F4Kub32bvl/+itQjj3hzqRwHrayM4JIlhJYvH3G+FFYSiUQikUgkkrE4qparW2+9lU9+8pP8+Mc/Zu3atfzP//wP55xzDps3b6a5uXlU+p/85Cdce+21/PznP2fFihU888wzfOhDH6KiooILLriglC4Wi7Ft27YR5wYCgde9Pscq+/fvJ5lM4vP5mDFjxht23YF0nk/d+2Pq9W2sivUyr6yFZFuS0+KdTF62hL+b0gSA2ZWm/dZtZPrzaECwKkDdCY0EZ1eihgzYvB722lC/EI77O6idB4fpYmf39ZF+ch35XTsx97SiBgI0fPtbJfHtnzEDp78P37Tp+KdNxTdtGlplpXTlk0gkEolEIpEcMkdVXP3Xf/0XV199NR/84AcBuP7667n//vv5yU9+wre+9a1R6X/zm9/w4Q9/mHe9y1tLaNq0aTz11FP853/+5whxpSgK9fX1b0wljnGEEGzatAmAWbNmYRjGG3LdVN7m3+/9A8J9Fqd6AW44T2pPnFzHHNYct4Cly7xFfLMdKfbfshUzZWHpCrHl9UxZbKJqcQgVFjiefa4XtKJh4WGXw83nST7wAMkHHkRY1tBxVcFNpdCiUQCq/vFDUkhJJBKJRCKRSF4TR01cmabJ888/z2c/+9kRx8866yyefPLJMc/J5/OjLFDBYJBnnnkGy7JKwiGVStHS0oLjOCxevJivfe1rLFmyZNyy5PN58vl86X0ikQDAsiysYQPyo0WxDEdSFsuyqKqqQlEUpk2b9rrXRwhBzrT42kNP0Jp/FKPmBJJaHfendC7r2EpNVQ3HnXYmtm2T2BOn6/92IUyHnE+j+qwaJuXvhIf+ihNrwj37W6AWumj1XDjMsue3bGHw5t/ixAcB8M2YSXDZUnzTpqE3NOCqKu4xcH/fTLyWviiRTDSyP0qOJWR/lBxLyP44sRxOOyqiGB/6Daajo4OmpiaeeOIJ1qxZUzr+zW9+kxtvvHGUWx/A5z73OX79619z1113sXTpUp5//nnOO+88uru76ejooKGhgaeeeoqdO3eyYMECEokEP/jBD7jnnnvYsGEDM2fOHLMsX/7yl/nKV74y6vgtt9xCKBSauEq/RckP9JHcswMnn8OxLHbr1Tw6L0OgYTa66iOSNlm2fhcNmRTVy1ajB0OIbo2mPWE0oZDRHUTjM0zLP4zmmgD0ROext+pUHM3/KlcfH6O3l5q77sYJh4mvWEGupfmw3QklEolEIpFIJG9vMpkM733ve4nH48ReJVL0URdXTz75JKtXry4d/8Y3vsFvfvMbtm7dOuqcbDbLxz72MX7zm98ghKCuro5/+Id/4LrrrqOrq4va2tpR57iuy9KlSznppJP44Q9/OGZZxrJcTZ48md7e3ldtwDcCy7J48MEHOfPMM98wt75DJdnbw+O33IBtmSBgT3+Gv0ytZWBGHSEdFoRUzm4zqdTDTFu2kvK6RnY+3oH95AE0V6DEdKbMfoTAwHMAiKrpuEuuhKqxhfAr4cTjmDt3Ely2rHQs9/LL+GfPRjnG2u3NyrHcFyVvP2R/lBxLyP4oOZaQ/XFiSSQSVFdXH5K4OmpugdXV1WiaRmdn54jj3d3d1NXVjXlOMBjkV7/6Ff/zP/9DV1cXDQ0N/OxnPyMajVJdXT3mOaqqsmLFCnbs2DFuWfx+P37/aAuJYRjHVIc83PIIIeju7qaqqup1iRCYz2R49o7/w7UtapqnsLlsHr/LtaNEMkQ1h7PCPXx80XsJr2oAwMzZvHTXHnyb+tBcCNb6aa67CT3eCYYflr0Ppp+OdpjWJau7m/QTT5J69FGEYxOcOg2jzhPaxiu4g0qOnGPtf0Py9kb2R8mxhOyPkmMJ2R8nhsNpw6Mmrnw+H8uWLePBBx/koosuKh1/8MEHufDCC1/xXMMwmDRpEgC///3vOf/881HVsaPKCyF48cUXWbBgwcQV/k1CIpHgL3/5C4ZhcMkll4zbRkeC6zg8c/sfyMQHCJVX0N6yhkd2rKemchOu3sy7wpu47LiPEA54wirRm+WFO3dTvj+JLgSxKTEa3zUL9ekGSLhw4r94QSsOEWGaZDdsIPW3J8gPcyH1TZsGjj1h9ZRIJBKJRCKRSA6Voxot8NOf/jRXXHEFy5cvZ/Xq1fzsZz9j3759fOQjHwHg2muvpb29vbSW1fbt23nmmWc4/vjjGRgY4L/+6794+eWXufHGG0t5fuUrX2HVqlXMnDmTRCLBD3/4Q1588UV+9KMfHZU6Hk16enoAqKiomFBhVSRSWcVgdxfm/NO5Z0crPv8fuDRwgGhgMmfM/DjRyBwA+g+kee62ndT2ZfErUDE9Rs3Fs1CDBqz+Jy8zf+SQr5vfvZveH/0YN532DigKgXnziJx4AoFFi2TUP4lEIpFIJBLJUeGoiqt3vetd9PX18dWvfpUDBw4wf/587rnnHlpaWgA4cOAA+/btK6V3HIfvfe97bNu2DcMwOPXUU3nyySeZMmVKKc3g4CD/+I//SGdnJ2VlZSxZsoS//vWvrFy58o2u3lGnu7sbgJqamgnPW9U0Fp99PpsmH8fPtvdRo/8f51R2UBkIs2LKxVRVnQh4roAv3ttKbX+WsA4V/lYqJsVRg/O8jMYQVcK2cZJJ3HgcJ5nESSRQdIPw8d49NBobEbaNVlFBeO1awmtWo1dWTngdJRKJRCKRSCSSw+GoiiuAa665hmuuuWbMz2644YYR7+fOncsLL7zwivl9//vf5/vf//5EFe9NTdFyNVagjyMl0dtNpLIKVdX4W2+C69sSpP09LAkKIj6duY3nMqnxMsBzydzw0D5inSmCrkWFbxcVVY+h9SqI9CW4BNAiQ+Kq+3v/hdXRMWSRGobeUF8SV2ogQN2//xt6fT3K62CRk0gkEolEIpFIjoSjLq4krw/pdJp0Oo2iKOMG+zhcEr09PHbzr6lqmkTk9PP4j5fayDhxFqjrWG5sZGr1GmZN/ScUxRM8ezb0Ym7upyKbJaq14cs/QGK3wAoeh/n5b6BXVVH/hc+X8nczmSFhpWlo0ShqLIoWK0OvHWl9MxobJ6ROEolEIpFIJBLJRCHF1VuUoktgRUXFhESJMbMZnvrT77HzOdpchd9s6aA/l6aRpznXeJD6SDNLZv8HWmFdqsGuDHsfbaM2niCQ78Rpu4c4g1DeDEo7AHZvL8K2UQqRDCvfdxWKpqHGylDDITl3SiKRSCQSiUTypkKKq7coE+kS6DoOT9/+v6QH+slV1XLn1KXs600TcTbwrsBtlPsjrJj9WXy+KgCsvMOGu/ZQ3TuIkRtA73kK9Cz+xadjNDfja56MMbkZo76uJKwAfJMnv+aySiQSiUQikUgkRwsprt6izJo1i1gsNiEugS8/+iC9+1pRDR9PLD2Vrd05dHs37zZ+S9TQWdB8OeXlSwFvntVLf9lH2YEkhmFQGWrH1h0qPvx9/NOmvuaySCQSiUQikUgkxypSXL1FKS8vp7y8/DXn09/Rzq7nnwFg+fkX8WyrQMl1cY76c6p9JlOrVzN18uWAJ6y23fIo5mZBmS9IeUsllRe8G6WyRrr4SSQSiUQikUje8khxJRkXIQQvPXQPCMHk4xbyfDZGa8dGVob+H7Mq49SFJ7No1r+jqj6szk72/c9N7O9ooC5cS7gyTNU7pqBWhY92NSQSiUQikUgkkjcEKa7egrS2tuI4Dg0NDYRCoSPOR1EUFp15Ht9+bgOBmQu4/alWLP33rCjvIeaPsmTmJ/EbtSTuu5++P/2R3fZ86mIV+P0m1WdNxaiXwkoikUgkEolE8vZBLhL0FmTLli08/fTTpYiBr4XnfRH2TZrJl3f30suDnFC5jZDhY96kiyhnLj3f/z6Df7iZfekqasqm4gtp1Jw4g9D8iV+4WCKRSCQSiUQiOZaRlqu3GKZpMjAwALy2SIHZZIJBX4BbOvrY258hnNjD4vLHqPC7TKlcyrSGK+n+8jdxuvfTm1EITToewxegfG495WfOknOsJBKJRCKRSCRvO6Tl6i1Gb28vAJFI5IhdArtbd3Pf//yQb65bT3sih5tMMJVfMyOcpi7cwMKZ/4oeiFJ20mJcpZ/8lPMI+SJEGqqofucsFEObyCpJJBKJRCKRSCRvCqS4eotRXN+qpubI3PIc2+LFB+7m2bJ6dlmCnsEs9ek/sqa8i0rbx7zA3xEKtYAQBI2t9LacT0ytwheNUnf+dPQy/0RWRyKRSCQSiUQiedMgxdVbjOI8qyN1Cdz+9JPsyeRZX9tCjxugIdHBybFnqEmYNGzzw++34KTSoCjsDb8PnzkbxR+manUjgallE1kViUQikUgkEonkTYUUV28hbNumr68PODJxlervY/u6x9lSVkMuUEY47bJcuYnZg3HK+hWqdkwlNH8Oqs8g2Zdj8NEuVD1IpCVGxYmTJro6EolEIpFIJBLJmwoZ0OItxODgIK7rEggEiEQih3WuEIIND96D6zic5NjsGlCYE/8rq/yb0F1BzYEF1L/nYgLtv0PsqmHXY5PwmQ5G2KDx4hkomgxgIZFIJBKJRCJ5eyPF1VuI6upqLr74YtLp9GFH62vfuonu1t24iso6fRYL27ZzUvQmFFegDtYz690fRX/px2Dn2f1YD0ZnJaqqUH/BVPSYnGclkUgkEolEIpFIcfUWIxAIEAgEDvu8ZN7k6dopVFtBBghwXuCPKL48OeFn/tmfKgmrQf8qst2zUYDIohpic6omvhISiUQikUgkEsmbECmuJAA8WjmJDTMMUj15TjI3o0/Jku4L0F17Gu/cchvYeZzqBbRvPAHFtdGqAjT9f/buPT6q+s7/+OucmcnknnBPwEACKImCgCAgeMGuUKDiWlYFd8uWNuAirRbZreJPqiIqQitFoGC1QJBlK6y22iKsUlEUEClUbC23Ksg1EEFgcpvMzDnn90fIaEwCBJLMDLyfj8c82jnne875nOQbH+fD93s+3+/kRDpsEREREZGooYIWF4kvv/ySt99+mx07dtT72A9PlvBO0UlOHv2S7PJibrjsXUrsU+xKy+LG4ychUAotOvP5l/8CxSFwm7Qf2QXTre4jIiIiIlJFI1cXiaNHj3L06FFcLhd5eXnnfFzhwQM8f+AEX+49xLf+soU+V+/GdPnwOQlgtyW39DgktuB4ej4Vm44CkP6ty0hsfX4LFIuIiIiIXKyUXF0kznd9q99u+Yg9vgDNTvroZ2+mVXsve/wn+JQruLv7WIwSHwGzLUXLj+E4YGSn0va6to1xCyIiIiIiMU3zui4CjuPwxRdfAPVLrkrKylhbXIETsuh9aBepw1MoS7D5zM4gOeEyerTqAZ1u5uA7QWy/RSjBTac7r6h3JUIRERERkUuBkquLwKlTpwgEArhcLpo1a3bOx73y/geUWg4p5aV07HWU1OaJ7C0p5+ixk3wrox8u00XZoWL8B4oBaDUsB2+Sp7FuQ0REREQkpmla4EWgatSqZcuWuFyuczrGLi0ledXv6dS8LRnNv6RlpoXP7+eTI8UkW3DdsX3QEY6sPYjjgNUigcyuKrsuIiIiIlIXJVcXgfN536pkx3aCx4/S68RBkrobpCeksWn/IYKWxbeTO+Hp+X0qviyn4vNTALQc0FbTAUVEREREzkDJ1UXA5XLh8Xho1arVOR9zKjGe0swsaHmYhESwT33B7pJy4sw4bvzW0+CJp3DtP7AtBysljswe535uEREREZFLkZKri0C/fv3o06fPObdf92Uxqw4dxxOfwhXZZbQxKvjrMR8YBtfn3UVienuC5UHKdn0JQLM+GRimRq1ERERERM5EBS0uEqZpYppn/nU6lkXR0v/m93sP8XmLy9jf9XISvX48/mP8rcLBlZ7NzVf9KwCF7x7ECdrY8S4yr8toilsQEREREYlpGrmKcY7jnPO7UMVvvsn7//icQ55mhC7LYUD8Zjzxyewtq8BJSqd3p6E0i2+GHbQp+biySEZyj9a43edWJENERERE5FKm5CrGbdiwgWPHjnHNNdfQvn37OttV7N3LiZVv8HbPAbgzM0gvOUq6u5DE5FTedbUEPNzS/hYAjnxwGMdv4XhMLhvYronuREREREQktmlaYIzz+XyUlZWdsQS7XVHBl4sWs61FG45lZFJ8vIheB18Ax8GbdjlBI46Wia3ITM7Etm1O/PkIAPF5zfHEa10rEREREZFzoeQqhtm2TXFx5QK/qampdbY7ueJ/CX7xBX+6/Ers9DRy931I+/i/08pVwhdmZRXA3Oa5AHyx7QsoDoJpcNk/1T0SJiIiIiIi1Sm5imFlZWVYloVpmiQlJdXaJnjoEKUbNvDXlhl82fkKjBOF9Ayuw+OG1OQu7PBVrpHVpXkXAI5vOAyAp1Ma8WneprkREREREZGLgJKrGObz+QBISUmps1Jg2V/+AkDPy9rwr80CXLX9HVJbnaDU25zMy+/gSOkRDAyuaHYFx3d9iXPcj2FAu1s0aiUiIiIiUh8qaBHDqpKrM00JTP32t/Fcdhkuyujx7i/xBw5hx7kJplzFMadyZKpdSjuSPEnsW7cHANdlKSS1qX0kTEREREREaqeRqxh2LskVHg8JeZ3wHljOwaJSzIxyyrzNaZvxT+w+sRuALs26cOpgMU5hCQBtbrqs0WMXEREREbnYKLmKYcnJybRs2ZJmzZrV2ebTsgr+38cfs8nvotAJEEoyCXpS6d7pFnad2AXAFc2voHDtAXDA1SqB9M7pTXQHIiIiIiIXD00LjGFXXnklV155Za37HMfh2Pz5vNMxjwNtLmNr+1tpZ36JZZXjTr2RcqeCE/4TuAwXbe0sDn2+HQNodb3WtRIREREROR8aubpIBQ8dovSTv/NB0ZdgGlzb+XLKkv1UJLWiS4ch4VGrnLQcit49gmE7uFLjaH51ywhHLiIiIiISm5RcxahQKIRlWXXuL9+6lc9Sm1HWvDkpHg9G0duELBuf1YmrO3Rm55c7AbgirQuB3ScAaNY3A8MwmiR+EREREZGLjaYFxqj9+/ezadMmsrOz6d+/f7V9juNQtmUrf0lPwxU6zpVfFFNYsRoch/Rm38JtGuFiFu3LOmAET2G4DFr1yYjErYiIiIiIXBQ0chWjqioFejyeGvuCBw/iP3acv7ZsjemFlkc3UHH8IKFT0KPjtRwsOUhZsIw4VxyJh+MBMJt5MT2uJr0HEREREZGLiZKrGHWmMuxlW7eyMy2dQKKHdKecROtjHAeOOv25sm0au7+sHLW6vNnl+A+WAhCXmdx0wYuIiIiIXIQ0LTBG1ZVcOY5D+da/kFT8BT2tIzSzTRyzFCvkoV3HW3GZxlcl2NO7YH1RjgmkdExr6lsQEREREbmoaOQqBtm2TUlJ5YK/KSkp1fY5gQDezp3pfGoPD7KJfsZRgrZNSUVr+nbMJGSH+PTkpwBk2zmYFRaGAelXpDf1bYiIiIiIXFQ0chWDSkpKsG0bl8tFUlJStX2m10vz4TfguFdiuDwUhfw4DvjNTK5ok8ynJz8lYAVIjksmbr8bP2CkxOFJiovMzYiIiIiIXCQiPnI1f/58cnJyiI+Pp1evXrz//vtnbP+rX/2KvLw8EhIS6NKlCy+99FKNNq+++ipXXnklXq+XK6+8kt///veNFX5EFBcXA5VTAmsrnf7hp1s55kqCdr0oKz8MgCuxE4bxtSmBza6gdF/leeLaJDZR5CIiIiIiF6+IJlfLly9n4sSJPPLII3z00UfccMMNDB06lP3799fafsGCBTz88MM8/vjj/P3vf2fq1Kn86Ec/4o9//GO4zQcffMDIkSMZPXo0H3/8MaNHj+auu+7iww8/bKrbanRer5fs7Gzatm1bbXvo+HG+3LOXBe48JrX7AYfa3YTtfAFAUosrAcLFLLo060KwqAyAxGy9byUiIiIicqEimlzNmjWL/Px8xo4dS15eHrNnzyYrK4sFCxbU2n7p0qX8x3/8ByNHjqRjx46MGjWK/Px8ZsyYEW4ze/ZsBg0axMMPP0xubi4PP/ww//RP/8Ts2bOb6K4aX8uWLenfvz/du3evtr3kvfd5e8n/4D/6JVltOtLqshzMVi0JJDanZasrqLAq+Nz3OQDZno6YpUEAmnVp1tS3ICIiIiJy0YnYO1eBQICtW7cyefLkatsHDx7Mxo0baz2moqKC+Pj4atsSEhLYvHkzwWAQj8fDBx98wAMPPFCtzbe//e0zJlcVFRVUVFSEv1dV4gsGgwSDwfrcVqOoiuFMsTiOQ+mfN7O1bSeMpCT6pMRTUvI5AceFz2zH5cmJ7PxiJyErRIuEFjh7bXAcjHg3ZqorKu5Tot+59EWRpqL+KNFE/VGiifpjw6rPzzFiydWxY8ewLIs2bdpU296mTRuOHDlS6zHf/va3+c1vfsPtt9/ONddcw9atW1m0aBHBYJBjx46RmZnJkSNH6nVOgOnTpzN16tQa29966y0SE6PnfaQ1a9YAlb9gt9td7X0rz7FjJHy2h10d86go+ZLizQfZ6NrGqUAZR4sz2b51I3vYQlGwiFRPKjs+/4QWFV6K40r5x+rVkboliVFVfVEkGqg/SjRRf5Roov7YMMrKys65bcSrBX6zIIPjOLUWaQD42c9+xpEjR+jXrx+O49CmTRvGjBnDzJkzcblc53VOgIcffphJkyaFv/t8PrKyshg8eHCti/Q2tWAwyJo1axg0aBC2bfPaa69hmiYjRowI37fv96+xulNH4hIMrjYLGTV0JJveXcepigCG5zLuGj6EX277G61LWnP7lbeTdNiD6a2gRa8OtP3WZRG+Q4kVX++LHo8n0uHIJU79UaKJ+qNEE/XHhlU1q+1cRCy5atmyJS6Xq8aIUlFRUY2RpyoJCQksWrSIX//61xw9epTMzExeeOEFUlJSaNmyJQAZGRn1OidUFojwer01tns8nqjqkB6Ph5MnT2KaJomJieEpko7jUPHxNj5q2RpXgpsBrdIxTYOTx7bjcXy43G2wXQGOlB3BNE26pOZyyLcDMGie1yKq7lFiQ7T9bcilTf1Roon6o0QT9ceGUZ+fYcQKWsTFxdGrV68aw5Vr1qyhf//+ZzzW4/Fw2WWX4XK5ePnll7n11lsxzcpbue6662qc86233jrrOWNFVeb89RG14L59+L48zpHkFFzxJn069eTE0UPgLsUxTJLSOrP7RGWVwLbJbQkdsDBsMDwmSe2SI3IfIiIiIiIXm4hOC5w0aRKjR4+md+/eXHfddbzwwgvs37+f8ePHA5XT9Q4dOhRey2r37t1s3ryZvn37cuLECWbNmsUnn3zCkiVLwuf8yU9+wo033siMGTP453/+Z15//XX+9Kc/sX79+ojcY0OrLbkq//hjknxH+fnfXuZEx6Gkp7dh16d/xHZsgiTRKrUNu778AKgswe7beRIAV4t4TFfElzoTEREREbkoRDS5GjlyJMePH+eJJ56gsLCQrl27smrVKjp06ABAYWFhtTWvLMvi2WefZdeuXXg8Hm6++WY2btxIdnZ2uE3//v15+eWXmTJlCj/72c/o1KkTy5cvp2/fvk19e42ituQq9TvfwXv0j5gBh7Y5PQA4eWwXtgOloVZkpyXwwemRqy7Nu1BxqAQAb7uUpg1eREREROQiFvGCFhMmTGDChAm17isoKKj2PS8vj48++uis57zjjju44447GiK8qFNbcmWd2kd8cjG4kiGrMoksKd6D7TgUO+2Ijy/j2JFjmIZJx5SO7PnybxhAamctHiwiIiIi0lAinlzJubNtm5KSylGnrydXv/+ihL+0/C4j4ku5Ni4JKxSiIlCIbTicMttTbFeO/mWnZhM4EsII2himQVqn9EjchoiIiIjIRUnJVQyxbZuuXbtSXFxMQkICAGUff8y6g1/yZWoXQnmV0ylLvjwOHh9OyKTYyOJo+R4Armh+Bad2nwDASPfiinPVfiEREREREak3JVcxxO12061bt2rbdu/dz5ESm0SXm57N0gFIbOYltcNlHDvqIz7Qln+c2ghUFrMoO1AMQFxm9CyOLCIiIiJyMVCpuBi3tyIIOOSaEH+68l95+QEClkOp04ak5CAlgRI8poectBxCX5QDkJKj961ERERERBqSkqsYcvLkSYqLi7FtO7zt6IlD4PeRcXJ3eFu5/yAVIZvSUCvi4ytHqtoktaHiywBmeQiA9C7NmjZ4EREREZGLnJKrGLJlyxb++Mc/cuDAgfC2LzABhzYeAwArFGL7ht/hP3GM0kALXJ7K5Kp1YmtO7jr9vlWyh7gUb5PHLyIiIiJyMVNyFSMcx6G4uDJR+nqlwCIzDoA2ifEA+I4V4fcfwiovpcRug2OeAqBVQitKP68s4+5po/etREREREQampKrGGFZFoFAAICUlK8W/8368iiXnfqCzNTKbScKD2DElRIy3ZRarQkYJ4HKkavA0TIAkjqkIiIiIiIiDUvVAmNEMBgEIDk5Gbe78tfmOA53/3kNBMrJuHU2AF8W7cDBIeAkESKV4uBxAJrTgkDxF4DetxIRERERaQxKrmJEMBjEMIxqo1YAbf+lI7bvFGbLTAB8J/6B5XIosTNolmziC1ROC4w76CXggBHvIqG1pgWKiIiIiDQ0TQuMEVVTAr/+vlXQsjApx5PqwUhMx7YsyssPYDvg4zJSEivLrid6Egnur/z/rpYJGIbR9DcgIiIiInKRU3IVI6qmBX49uXr96HHy2+bz+zaDIS4F37EvMDw+HAyKuYz4hBIAWie0puJwKQAJl6XUPLmIiIiIiFwwJVcxIjU1lSuvvJJWrVqFtx0+foqy8nhw54HLTUVZKZ7kCiyXh1KrNYansjpgS28rnJMVAKRdkR6J8EVERERELnpKrmJEUlIS3bp1Iz09PbztyEkfoeNfkrJrJwDNL2tB65zLCCS1pDTUCtuofN+qzZcZGJYDbpMUVQoUEREREWkUSq5ilOM4FAVDgEMbrweA8vIDODicDDTDxk2AykWD04sqpwKazb2YLv3KRUREREQag560Y0BxcTFlZWWUl5eHt5VaNmVlJ8Hvo/XhD3Ech/LyAwRCNiXBVnhcJsXBLwGI/6KyKGR82+RIhC8iIiIicklQchUDDhw4QGFhIX/729/C244GgjihEGn+EuITvfi+OMpHf1rGiSOFlFqtaJ7iUBIsARvcJ20AUjqlR+gOREREREQufkquYoDPV1mY4utrXBUFQjihIC1KT2GmpnPiSCGOeYJQKERJqDVJiWUAZFRkYgYdMCBdxSxERERERBqNkqsYUFxcDFQvw57qdtG9aB9XfHEQV1oLThw5iBFXWlkpMNQKb3xlGfZ2Fe0qD0j04PZqzWgRERERkcaip+0o5zhOrSNXVyUn0OLjtwkWHsUcdiMnj+yCeAiQTIWdgun+AoLQ0t8MACPJE5H4RUREREQuFUquolx5eTmhUAjDMEhOrl6QotWgDtjHPRgdL6f0H+/jjodTVgZgEDpdhj2tvDIhc6cquRIRERERaUyaFhjlqkat3G43pvnVr+tEMIRplOFJ9VBqmeA+iWEYFAUyAahwKsuwJ/i9AHiaxTdx5CIiIiIilxaNXEW5quQqLi4uvM1v2dy/Yz9xLe9mrrWZk6fKMb0lmB4vJRWtiXMb+ILHAfD6XYBDXIuESIQvIiIiInLJ0MhVlMvMzKRPnz7VilkUnS7D7pTFEfT3wJPcjITmQJyX0lBlGfbyUDmGY+D2Vx6T0ErJlYiIiIhIY1JyFeVSUlLIyckhMTExvK0oEMIJBEjfv4/S99fTKieD5u1aQWI6paFWJCaWAtDGbI0TcgBIzEiKSPwiIiIiIpcKJVcxqGrkqmV5KWZSEuXlBwAos5pj48brrSzdftnpMuy228SbqBmgIiIiIiKNSU/cMehoIARlJ2lRuAMncISS4qsBOBVoAYDh9kEQWpVXfifRjWEYkQpXREREROSSoOQqBhVVBHFCQVqUnuJLr4fP//TfJGWUUuTvCUDIOAlAannle1pmSlxdpxIRERERkQaiaYEx6GggCKEgLUtPYnkTMONKcByHo6XNAfDblWXYk8ory6+7U5VciYiIiIg0NiVXMahvWjLdTxykdclJQvFxGHFl2JiUhlqREOfiROAYAN7yyoHJuOZa40pEREREpLFpWmAMGpnZnOO73qesopziJAcMh5DjpcJOoW1ygBN2CMMwcJWDBXhbqgy7iIiIiEhjU3IVo5pd147UDqUcTq0ssR4INQcMEhPLOAFkeFpDhQVAQuvEuk8kIiIiIiINQslVjDkZDAGQ5pThSfEQcldWASy3Kqf+ebzFEIB2dlssy8E2DZI0LVBEREREpNHpnasY88YXp7hvx36Wt7gJ2nTFwgagLFRZtMJw+QBo428FQMhj4ol3RSZYEREREZFLiJKrGHM0EAQgviieUyVXk9i8Gd7EJIpPj1wFTpdhTy9PA8BI8miNKxERERGRJqDkKsYcrQiCbZP84Qf4Vv8fGZ06kNamLafMZgD47S8BSCqtLGLh0hpXIiIiIiJNQslVDHEch2PBEE4oRAt/Kbhc2C6LCsvCcuJI9pqcrKhMruLKKl+n86R7IxmyiIiIiMglQ8lVDDkRsgjYDmb5SZrt+QDj1KdYoTIqgjaWE0daSgDLsXCbblyllcdojSsRERERkaah5CqGFAUqKwW2CJThcmxI8LBj/Rp8B/YQstzEJ5QA0NrbCsdf2Ta+lda4EhERERFpCkquYkhVctWyohgAOzEJTAvLAYt4PHGV27OMtthBG8eABI1ciYiIiIg0CSVXMaSd18PQVmn0OHUYADsxGcMMYQOWEwdVZditlliWQ9BlkpSmd65ERERERJqCFhGOIZ0SveSmJXPq6G58gJWQeHrkyiTkeAkZlUlXelll5UArTmtciYiIiIg0FSVXMSjlqpYkJlzG0XZX45T9HRsDy4mj1KqsFJhcmoBDAFNrXImIiIiINBlNC4wRDvBZWQW+kIVhleJJ8WAlpuIYIcAg0RvPqYoTAHhLPAC4NCVQRERERKTJaOQqRvgxeHLvEQzT5Dctc/HGJRIw4nCwcQw3CYkOpTjEueIwSh1Aa1yJiIiIiDQlJVcx4pRZ+e5UusdFxeE2+CvS8LRJxvQmYgdNLLNyYavWCa1xSoIAxLdQGXYRERERkaYS8WmB8+fPJycnh/j4eHr16sX7779/xvbLli2je/fuJCYmkpmZyQ9+8AOOHz8e3l9QUIBhGDU+fr+/sW+lUfmMyuQqI85Dyfr38a3+P1q0SCeueRsC3nQCRmWlwMtcmVhBGwytcSUiIiIi0pQimlwtX76ciRMn8sgjj/DRRx9xww03MHToUPbv319r+/Xr1/Pv//7v5Ofn8/e//53//d//5c9//jNjx46t1i41NZXCwsJqn/j42F7v6dTp5Kq1x41dXLlYsBNvYjkOlhNHBScByLBbYodsgqZBYmpcpMIVEREREbnkRDS5mjVrFvn5+YwdO5a8vDxmz55NVlYWCxYsqLX9pk2byM7O5v777ycnJ4frr7+e//iP/2DLli3V2hmGQUZGRrVPrKuaFtja/wXOno1QtAM7zsA+nVz57cpKgS2CzbEsh5DLVHIlIiIiItKEIvbOVSAQYOvWrUyePLna9sGDB7Nx48Zaj+nfvz+PPPIIq1atYujQoRQVFfHKK6/wne98p1q7kpISOnTogGVZ9OjRg2nTptGzZ886Y6moqKCioiL83eernGIXDAYJBoPne4sNJhgMcspwYTsOzUuO4wAY8NE7K6kw9gEdKYk/Tqptk+iLJ0Q5IY8Jph0V8cvFo6o/qV9JNFB/lGii/ijRRP2xYdXn5xix5OrYsWNYlkWbNm2qbW/Tpg1Hjhyp9Zj+/fuzbNkyRo4cid/vJxQKcdtttzF37txwm9zcXAoKCujWrRs+n4/nnnuOAQMG8PHHH3P55ZfXet7p06czderUGtvfeustEhMTL+AuG44vvgWlX3zBF5+/T2ZFBUHTw8GDe4jPCFIcClFUfhB/CRw9coTkigSOGaWsXr060mHLRWrNmjWRDkEkTP1Roon6o0QT9ceGUVZWds5tI14t8JuL3DqOU+fCt9u3b+f+++/n0Ucf5dvf/jaFhYX89Kc/Zfz48SxcuBCAfv360a9fv/AxAwYM4JprrmHu3LnMmTOn1vM+/PDDTJo0Kfzd5/ORlZXF4MGDSU1NvdBbvGCBQIC/vbuBdld144bAXyn3eknMyKBVy1TK3C5MdwLN4hNon96MDhWXUVJcTGbn1lw9rPZkUuR8BYNB1qxZw6BBg/B4PJEORy5x6o8STdQfJZqoPzasqllt5yJiyVXLli1xuVw1RqmKiopqjGZVmT59OgMGDOCnP/0pAFdffTVJSUnccMMNPPnkk2RmZtY4xjRNrr32Wv7xj3/UGYvX68XrrbkmlMfjiZoO2S1UzrB2LQlu+hI/4EpJxbb84ECFCS7TpE1im9Nl2A3iWyZFTexy8Ymmvw0R9UeJJuqPEk3UHxtGfX6GEStoERcXR69evWoMV65Zs4b+/fvXekxZWRmmWT1kl6uy0IPjOLUe4zgO27ZtqzXxikUJbZPIuPUy0ocPxLIry8v7sTFNgwxPa6wKq7JdS5VhFxERERFpShGdFjhp0iRGjx5N7969ue6663jhhRfYv38/48ePByqn6x06dIiXXnoJgOHDhzNu3DgWLFgQnhY4ceJE+vTpQ9u2bQGYOnUq/fr14/LLL8fn8zFnzhy2bdvGr371q4jd54U6XBHkiOmmzLJJs0rxpHgItM7E+DSE44DfCOEyPLRz2mCFHCyXQUJ6zZE4ERERERFpPBFNrkaOHMnx48d54oknKCwspGvXrqxatYoOHToAUFhYWG3NqzFjxlBcXMy8efP4z//8T9LT0/nWt77FjBkzwm1OnjzJPffcw5EjR0hLS6Nnz56899579OnTp8nvr6G8ddzHK95mpB/3MbJ5R3BsAu50MC0cw6CcAKaRSAu7WXiNq4QUDQGLiIiIiDSliBe0mDBhAhMmTKh1X0FBQY1t9913H/fdd1+d5/vlL3/JL3/5y4YKLyp8EQwB0DrOTWlZB0LFCTgVCaS2akZZeRF+249pGqRXpFBsnSTkcWmNKxERERGRJhbRRYTl3BwNfJVclf3lL/hW/x/uUz4uuyqPiqR0KpwQpmEQV1w5WmXFmXi8rkiGLCIiIiJyyVFyFeVCtsPxYGWRilZuN3ZxMQCupCRsq5yQEyTkmKTHp+GcqEzCXKlxdZazFxERERGRxhHxaYFyZseCIXAcPDik+4s4/tc/QpmBkZhIIFSOQ5Cg7aV1YkuCvgAAnvT4CEctIiIiInLpUXIV5Y4GggCkOhZGoAQ7YIPh5vO9/+Dzk5uIc5UQIoF0MwW7rLJtXAslVyIiIiIiTU3TAqPc0YrKhCnNtqD8JHbAAtNNyDBwCODgEMJFWjAZK2RjmwaJGrkSEREREWlySq6i3JXJCfxrRnNyLT/2yS/AoTK5sm0wLBzAxiQlkIAVcgi6DBJUKVBEREREpMlpWmCUuyw+jjYtUghaAZxTxwEwExIJBP1g2jgmWLhIrkjADtmE3CaJqVrjSkRERESkqSm5iiEur0XGrZfhZP8Tn/t8ODjYhoNtuIgv92BZDkGvSUKKRq5ERERERJqapgXGEDNUgifFQ1z7DgSDpQBYGBiGK7zGle11aY0rEREREZEI0MhVDHHSO0CoDFLbEqr4BMcNQcfENMBTbOIA7jSv1rgSEREREYkAJVcxxM/lhHwuvCe8pLZpRkXAS8AO4jZMXOUmIcDTzBvpMEVERERELkmaFhhDKnbtpvj/3sS/Yzt5N1yPp2Um5S4XaaFEsMAxIEHJlYiIiIhIRCi5ihWOg13sA8CVnIxl+7Edh6ADzUKJOJZB0GWSkKrkSkREREQkEpRcxQi37YcPl0Dhx5gJ8diWH9uGgOOQHkoAC0IuQ5UCRUREREQiRMlVjHBb5dgBG3Aow+GDV5cS+OIgQRvSQ4nYIQiahta4EhERERGJECVXMcJjlWFV2GC6sTwebKcCx3EIOSZpgSQc2yHk0hpXIiIiIiKRouQqRnisMuyABaYHy3RhmBY2laXYm1ekAobWuBIRERERiSAlVzHCHSrDCdjgcmO5TDBDOIZxeuQqubJNerzWuBIRERERiRCtcxUjPFYZbYa1xcnsz0HTCI9cuULxeGw3GOBtpimBIiIiIiKRopGrGOFx/LiTPXizOxAKBsAMYRsQH0rA5bgri1mkqQy7iIiIiEikaOQqRpR7muFktIS0ywh+WRYeuYqzEnDZLiyPQaqKWYiIiIiIRIySqxhx3OrAyVOpxB/1kJCaRkJxIsetU5hWHIZjYhta40pEREREJJI0LTBGeL78kpK33qLsw0106tWHjCs6EojzYFpeTNvENtAaVyIiIiIiEaTkKka4/OUAmElJAIQsPw427pAXw9bIlYiIiIhIpCm5igWOTecDf8Qo/CtmfOXoVChUhoONN5CMYRgYHq1xJSIiIiISSfVOru644w6eeeaZGtt//vOfc+eddzZIUPINFSU4QRscCzO1GW8vWkDR3p2YoRAJwSQMwJ3o1hpXIiIiIiIRVO/kat26dXznO9+psX3IkCG89957DRKUfEPFKZyAA6YbMyUFf+lJrFAIx7CJCyVhGAbuRNUmERERERGJpHonVyUlJcTF1Xy3x+Px4PP5GiQo+Qa/D4Knk6vERILBEhyoXOfKjgcMDI9meIqIiIiIRFK9n8i7du3K8uXLa2x/+eWXufLKKxskKKnOqPCFR66c+HggCDgEHBOv48HAwIjT+1YiIiIiIpFU77lkP/vZz/iXf/kXPvvsM771rW8B8Pbbb/Pb3/6W//3f/23wAAXwnyK+VxLNLr8eu01rDNPCwSAAeG0XhgFGnEauREREREQiqd7J1W233cZrr73G008/zSuvvEJCQgJXX301f/rTn7jpppsaI0YJFGMmmMS1b0eJYYBpgWESdBziHDcGBmac3rkSEREREYmk83oi/853vlNrUQtpJEmtOZmYTcv0DgT95RhmqDK5si3iHDdg4NK0QBERERGRiNJcshgQankNhYc7UHLAhel2k9qmBYYnjpADLsfEMMD06lcpIiIiIhJJ9X4iN00Tl8tV50canvXllyT/7W+UrPkTzdteRtebB2Kmt8C2PRiAgYFLCwiLiIiIiERUvacF/v73v6/2PRgM8tFHH7FkyRKmTp3aYIHJV+ySyhL3ZlISAJbtx7IssN0YmNiGgelRciUiIiIiEkn1Tq7++Z//uca2O+64g6uuuorly5eTn5/fIIHJV4w3nyS97HNMT08AbMuP5Vg4tgfTMXAMA7db0wJFRERERCKpwZ7I+/bty5/+9KeGOp1UsULYpaUYjo2Zms7f173NX9euxCr1YVgeTExsA1weI9KRioiIiIhc0hokuSovL2fu3LlcdtllDXE6+boKH3aFjQOYqc3wl5QQCpZg2TbYcZXTAk0D06WRKxERERGRSKr3tMBmzZphGF+NkjiOQ3FxMQkJCSxbtqxBgxPAfwo7YOMYLszkZIL+cjAtbBwMy3P6nStwaVqgiIiIiEhE1Tu5mj17drXvpmnSqlUr+vbty759+xoqLqlSUYxVYeEYLoykJILHT2GYocqEyo7DpPKdK9OtaYEiIiIiIpFU7+Tq+9//frXvp06dYtmyZTzyyCNs27atsoqdNBz/KdJ7NuP4Za1I6HUNgT/sgXgLCwfT8mrkSkREREQkSpz3E/natWv53ve+R2ZmJnPnzmXo0KFs2bKlIWMTgAofrgQ3VstmuNLSCFb4K0eucDBPj1zZhqHkSkREREQkwuo1cnXw4EEKCgpYtGgRpaWl3HXXXQSDQV599VWuvPLKxorx0pbYAiezO6UHKwAI+v24DQvLcHCFvKDkSkREREQkKpzzE/mwYcO48sor2b59O3PnzuXw4cPMnTu3MWMTgPb9OHXqKooPxmP5/aS1ycCT4MbCwW15T49cgcuj5EpEREREJJLOeeTqrbfe4v777+fee+/l8ssvb8yY5GvsQIDiN/+P1KIiDMfhhru/z8d/3cCeg7uJC8VjYGCbBi6XClqIiIiIXAjLsggGg5EO44IFg0Hcbjd+v1/1EM5RXFwcpnnhgxXnnFy9//77LFq0iN69e5Obm8vo0aMZOXLkBQcwf/58fv7zn1NYWMhVV13F7NmzueGGG+psv2zZMmbOnMk//vEP0tLSGDJkCL/4xS9o0aJFuM2rr77Kz372Mz777DM6derEU089xXe/+90LjjUS7NLSyv9jmBjx8ThOANtxcLDxhBIxDAPHAFPTAkVERETOi+M4HDlyhJMnT0Y6lAbhOA4ZGRkcOHCg2hJKUjfTNMnJySEuLu6CznPOydV1113Hddddx3PPPcfLL7/MokWLmDRpErZts2bNGrKyskhJSanXxZcvX87EiROZP38+AwYM4Ne//jVDhw5l+/bttG/fvkb79evX8+///u/88pe/ZPjw4Rw6dIjx48czduxYfv/73wPwwQcfMHLkSKZNm8Z3v/tdfv/733PXXXexfv16+vbtW6/4ooFdUlL5v14vhmFgWX5s2wFs4qzKkSvHNDFN/eGIiIiInI+qxKp169YkJibGfEJi2zYlJSUkJyc3yGjMxc62bQ4fPkxhYSHt27e/oN9/vUuxJyYm8sMf/pAf/vCH7Nq1i4ULF/LMM88wefJkBg0axB/+8IdzPtesWbPIz89n7NixQOUaWm+++SYLFixg+vTpNdpv2rSJ7Oxs7r//fgBycnL4j//4D2bOnBluM3v2bAYNGsTDDz8MwMMPP8y6deuYPXs2v/3tb+t7uxEXTq7ivRw/sI+P1vwWT9Zhgo5Bqu3FMIA4/dGIiIiInA/LssKJ1ddnQsUy27YJBALEx8cruTpHrVq14vDhw4RCITwez3mfp97J1dd16dKFmTNnMn36dP74xz+yaNGicz42EAiwdetWJk+eXG374MGD2bhxY63H9O/fn0ceeYRVq1YxdOhQioqKeOWVV/jOd74TbvPBBx/wwAMPVDvu29/+do3Fj7+uoqKCioqK8HefzwdUzleN9LzbwKlTOLaD7Y2nrLgYf9lJTMsi4IDXcYNj4LiMiMcpl4aqfqb+JtFA/VGiifpj7KqoqMBxHOLj47FtO9LhNAjHccL/e7HcU2Nzu904jlMtJ6hSn7/rC0quqrhcLm6//XZuv/32cz7m2LFjWJZFmzZtqm1v06YNR44cqfWY/v37s2zZMkaOHInf7ycUCnHbbbdVq1p45MiRep0TYPr06UydOrXG9rfeeovExMRzvqfGkLRzJ2nHvsDq0IEPP9hI2YkiDL8fv8vCHTIJBgMUFh1m1aq9EY1TLi1r1qyJdAgiYeqPEk3UH2OP2+0mIyOD0tLSiy45Li4ujnQIMSMQCFBeXs66desIhULV9pWVlZ3zeRokuboQ35zT6DhOnfMct2/fzv3338+jjz7Kt7/9bQoLC/npT3/K+PHjWbhw4XmdEyqnDk6aNCn83efzkZWVxeDBg0lNTT2f22owxYaB79PP2Of10u2qq/g0uIOExCScYAlxhhtvnJd22RkMGKYKjtL4gsEga9asYdCgQRc0ZC7SENQfJZqoP8Yuv9/PgQMHSE5OJj4+PtLhNAjHcSguLiYlJSXm3x9rKn6/n4SEBG688cYa/aBqVtu5iFhy1bJlS1wuV40RpaKiohojT1WmT5/OgAED+OlPfwrA1VdfTVJSEjfccANPPvkkmZmZZGRk1OucAF6vF6/XW2O7x+OJ+H8g0771LbxXXsnfN26kWSiI6bJwTBPHdmNigmHg9rojHqdcWqLhb0OkivqjRBP1x9hjWRaGYWCa5kXzflLVVMCq+6rLwIED6dGjxxlfn8nOzmbixIlMnDixgaNsWAUFBUycOPG8Kz6apolhGLX+DdfnbzpiPSguLo5evXrVGD5fs2YN/fv3r/WYsrKyGh3E5XIBX80tve6662qc86233qrznNHOlZxMXIcOhNLSCPr9YFg4gGO5MQDHMHB5XJEOU0RERESa2JgxYzAMo8bn008/bbIY/v73v/Mv//IvZGdnYxjGGRM1qDvmr3/Ox8iRI9m9e/d5HduQIpqeT5o0id/85jcsWrSIHTt28MADD7B//37Gjx8PVE7X+/d///dw++HDh/O73/2OBQsWsGfPHjZs2MD9999Pnz59aNu2LQA/+clPeOutt5gxYwY7d+5kxowZ/OlPf4r6bPtchCr8GKaFbYDjeDBxVSZXbg33ioiIiFyKhgwZQmFhYbVPTk5Ok12/rKyMjh078swzz5CRkXHW9s8991y1WAEWL15cY1uVQCBwTnEkJCTQunXr+t9AA4tocjVy5Ehmz57NE088QY8ePXjvvfdYtWoVHTp0AKCwsJD9+/eH248ZM4ZZs2Yxb948unbtyp133kmXLl343e9+F27Tv39/Xn75ZRYvXszVV19NQUEBy5cvj8k1rr7Jm5xMQloitmFgWJXJlW2Ay3NxDGGLiIiISP14vV4yMjKqfapmdq1bt44+ffrg9XrJzMxk8uTJNYo1fF1RURHDhw8nISGBnJwcli1bdtbrX3vttfz85z9n1KhRtb5m801paWnVYgVIT08Pfx81ahQ//vGPmTRpEi1btmTQoEFA5RJO3bp1IykpiaysLCZMmEDJ6SWLoHJaYHp6evj7448/To8ePVi6dCnZ2dmkpaUxatSoRi/yEfGCFhMmTGDChAm17isoKKix7b777uO+++474znvuOMO7rjjjoYIL6pcddMtFH3hY8vuQ2CbmJjYpoHLreRKREREpKE4jkNFKDIlzL1us0GKUBw+fJhbb72VMWPG8NJLL7Fz507GjRtHfHw8jz/+eK3HjBkzhgMHDrB27Vri4uK4//77KSoquuBY6mvJkiXce++9bNiwIfzqj2mazJkzh+zsbPbu3cuECRN48MEHmT9/fp3n+eyzz3jttddYuXIlJ06c4K677uKZZ57hqaeearTYI55cSf3YVjmWbWFY8ZiGiW2A26XkSkRERKShVIRsfrTsLxG59q/+7Rri6/E+/cqVK0lOTg5/Hzp0KMuXL2fhwoVkZWUxb948DMMgNzeXw4cP89BDD/Hoo4/WqGOwe/duVq9ezaZNm8IzvhYuXEheXl7D3Fg9dO7cmZkzZ1bb9vVXfHJycpg2bRr33nvvGZMr27YpKCggJSUFgNGjR/P2228ruZKvWHYFlmNj2J7KkSu9cyUiIiJyybr55ptZsGBB+HtSUhJQmSz169ev2ijYgAEDKCkp4eDBg7Rv377aeXbs2IHb7aZ3797hbbm5udWm2jWVr8dQ5Z133uHpp59m+/bt+Hw+QqEQfr+f0tLS8D1/U3Z2djixAsjMzGz0kTglVzHk7d/8CnfrLVjJQUzLi4mJo3euRERERBqU123yq3+7JmLXro+kpCQ6d+5cbZtt27Wu81o1xa62aYdn2tfUvpks7du3j2HDhjF+/HimTZtG8+bNWb9+Pfn5+Wdc+PmbJdQNwwiXqW8sSq5ihGNZlJ46SUKqDyvZxrTivhq50rRAERERkQZjGEa9puZFoy5duvDGG29US7I2btxISkoK7dq1q9E+Ly+PUCjEli1b6NOnDwC7du0673WjGtKWLVsIhUI8++yz4emMK1asiHBUtdNTeYywrcrKLoZpYeHgtr+WXKmghYiIiIh8TX5+PgcOHOC+++5j586dvP766zz22GNMmjSp1oWFu3TpwpAhQxg3bhwffvghW7duZezYsSQkJJzxOoFAgG3btrFt2zYCgQCHDh1i27ZtDbrWVqdOnQiFQsydO5c9e/awdOlSnn/++QY7f0PSU3mMcEKVQ56mx8F2bFwhLwYGtgmm3rkSERERka9p27YtK1euZPPmzXTv3p3x48eTn5/PlClT6jxm8eLFZGVlcdNNNzFixAjuueees64ddfjwYXr27EnPnj0pLCzkF7/4BT179mTs2LENdi89evRg1qxZzJgxg65du7Js2TKmT5/eYOdvSIZTNcFSwnw+H2lpaZw6dYrU1NRIh0MwGOS1l/8H89BeUnM/5IC3nLLdN9P/1E0UJ6XQ8Ts5ZOU2j3SYcgkIBoOsWrWKYcOG1ZjHLNLU1B8lmqg/xi6/38/evXvJyckhPj4+0uE0CNu28fl8pKam1jpKJTWdqR/UJzfQTztG2FUjV+7KkSu3VTly5RhoWqCIiIiISBTQU3mMcEIhMGxMl4Ht2HiseEwMFbQQEREREYkSeiqPFYZJSos0XG4PNjaeUHxlOUkDXB69cyUiIiIiEmlKrmJEQqs2DLj7X0lp1ZqQ4+B14jCdymqBpkauREREREQiTk/lMcS2/dgOBG2DONuNAZUjV3rnSkREREQk4vRUHkMsy49l24QcAxcmOIbWuRIRERERiRLuSAcg5+bU7u1sPrkFb3Yxtu2i6i0rR+9ciYiIiIhEBSVXMSJUXkZZ8XFcVgjHdgMGNgZo5EpEREREJCroqTxG2KEghhnCBrDdmIaJY1SOWKkUu4iIiIhI5OmpPEY4oRCYFrbh4NgeXLiwT//2TLemBYqIiIhI/QwcOJCJEyeesU12djazZ89uknjqo6CggPT09EiHUYOSqxhRNXJlAdgeTFyVZdjdJoah5EpERETkUjNmzBgMw6jx+fTTT5sshr///e/8y7/8C9nZ2RiGcdZE7NVXX8XlcrF///5a9+fm5nL//fc3QqRNQ8lVDHAcBycUwjAtLBwMKw4TU2XYRURERC5xQ4YMobCwsNonJyenya5fVlZGx44deeaZZ8jIyDhr+9tuu40WLVqwZMmSGvs2bNjArl27yM/Pb4xQm4SezGOAFQzgOA58LblynR65cmlKoIiIiMgly+v1kpGRUe3jcrkAWLduHX369MHr9ZKZmcnkyZMJhUJ1nquoqIjhw4eTkJBATk4Oy5YtO+v1r732Wn7+858zatQovF7vWdt7PB5Gjx5NQUFB5fPt1yxatIhevXrRvXt3Zs2aRbdu3UhKSiIrK4sJEyZQUlJy1vNHmpKrGGCFQniSkolLdGM5NqbtCRe0MDVyJSIiItI4gv66P6FAw7dtQIcPH+bWW2/l2muv5eOPP2bBggUsXLiQJ598ss5jxowZw+eff87atWt55ZVXmD9/PkVFRQ0aF0B+fj579uxh3bp14W2lpaWsWLEiPGplmiZz5szhk08+YcmSJaxdu5YHH3ywwWNpaCrFHgO8iUm0unYAna7ay1/2vYkZHrnStEARERGRRvO/3697X9ueMHDyV99/Nw6sQO1tW+fBLY9/9f0PP4aK4prt/nV5vUNcuXIlycnJ4e9Dhw5l+fLlLFy4kKysLObNm4dhGOTm5nL48GEeeughHn30UUyz+jPk7t27Wb16NZs2baJv374ALFy4kLy8vHrHdDZXXnklffv2ZfHixQwcOBCAFStWYFkWd999N0C1Qhs5OTlMmzaNe++9l/nz5zd4PA1JT+YxxLb92I6Ny/aefufKwOXStEARERGRS9XNN9/Mtm3bwp85c+YAlclSv379qhU+GzBgACUlJRw8eLDGeXbs2IHb7aZ3797hbbm5uY1WkS8/P59XXnmF4uLKJHPRokWMGDEifL133nmHQYMG0a5dO1JSUvj3f/93jh8/TmlpaaPE01A0chVDLNuP5di4QvG4DJOACR6NXImIiIg0jjtrFl0IM77xDDbixXNve9u884/pG5KSkujcuXO1bbZt4zhOjYrSVe841VZp+kz7GsOoUaN44IEHWL58OQMHDmT9+vU88cQTAOzbt49hw4Yxfvx4pk2bRvPmzVm/fj35+fkEg8Emie98KbmKAYW7d1L05/W0SDqC5Vi47LivRq48Sq5EREREGoUnPvJtz1OXLl144403qiVZGzduJCUlhXbt2tVon5eXRygUYsuWLfTp0weAXbt2cfLkyUaJLyUlhTvvvJPFixezZ88eOnbsGJ4iuGXLFkKhEM8++2x4+uKKFSsaJY6GpifzGFBeUkyotJRQqAzbtnGHvJiG3rkSERERkdrl5+dz4MAB7rvvPnbu3Mnrr7/OY489xqRJk2q8bwWVydiQIUMYN24cH374IVu3bmXs2LEkJCSc8TqBQCA8JTEQCHDo0CG2bdt2Tmtt5efns3HjRhYsWMAPf/jDcBLYqVMnQqEQc+fOZc+ePSxdupTnn3/+/H4QTUxP5jEg6K+sHmO4LGws3FY8JpXVApVciYiIiMg3tW3blpUrV7J582a6d+/O+PHjyc/PZ8qUKXUes3jxYrKysrjpppsYMWIE99xzD61btz7jdQ4fPkzPnj3p2bMnhYWF/OIXv6Bnz56MHTv2rDFef/31dOnSBZ/Px/e//1XxkB49ejBr1ixmzJhB165dWbZsGdOnTz/3m48gTQuMAcEKP+Bgmg52yCbeSsCFgW2AqYIWIiIiIpekgoKCM+6/6aab2Lx5c53733333WrfMzIyWLlyZbVto0ePPuM1srOza6xXVR87d+6sdfsDDzzAAw88UGcsY8aMYcyYMed93caiYY8YEKzwY7gsDJcL27HxWF5MQ+9ciYiIiIhEEz2Zx4Cg34/psjFMk5DjEGdVlWLXO1ciIiIiItFCT+YxoGrkyjRdBG0wHRMTA9swNC1QRERERCRKKLmKAXEJibjj3RimgW27ADAwcDRyJSIiIiISNVTQIgZce9u/cDzuOEbcZmy78ldmuFygd65ERERERKKGnsxjRpCQbYHtxjAqR61AI1ciIiIiItFCT+YxwjCCBO0Qju05XcyiMrtSciUiIiIiEh00LTDKBf1+3nnpN/j8nxDf3ALbg2G4sE/vd7lV0EJEREREJBoouYpyAX85xV8ew3aXYtkOWB5Mw8Q6vV8jVyIiIiIi0UFP5lEu6PcD4IpzCDkWhhWHyVfJlUqxi4iIiMj5GDhwIBMnTjxjm+zsbGbPnt0k8VyIgoIC0tPTIx2GkqtoF/CXA2B6wLJtDNuDabiwnMr9GrkSERERuTSNGTMGwzBqfD799NMmi+HFF1/khhtuoFmzZjRr1oxbbrmFzZs31zvmr3/Ox8iRI9m9e/f53kaD0ZN5lAtWVABgusFyLEzLWzkt0KnMrlSKXUREROTSNWTIEAoLC6t9cnJymuz67777LnfffTfvvPMOH3zwAe3bt2fw4MEcOnSo1vbPPfdctVgBFi9eXGNblUAgcE5xJCQk0Lp16wu7mQagJ/MoFwyPXDmEbAvTjsNlmIQ0ciUiIiJyyfN6vWRkZFT7uFwuANatW0efPn3wer1kZmYyefJkQqFQnecqKipi+PDhJCQkkJOTw7Jly856/WXLljFhwgR69OhBbm4uL774IrZt8/bbb9faPi0trVqsAOnp6eHvo0aN4sc//jGTJk2iZcuWDBo0CIBZs2bRrVs3kpKSyMrKYsKECZSUlITP+81pgY8//jg9evRg6dKlZGdnk5aWxqhRoyguLj7rPV0IFbSIcsGKyneuTLdDyLFxWV5chgtb61yJiIiINArHcQjY5zZi0tDizLjznhr3dYcPH+bWW29lzJgxvPTSS+zcuZNx48YRHx/P448/XusxY8aM4cCBA6xdu5a4uDjuv/9+ioqK6nXdsrIygsEgzZs3P+/YlyxZwr333suGDRtwTs/WMk2TOXPmkJ2dzd69e5kwYQIPPvgg8+fPr/M8n332Ga+99horV67kxIkT3HXXXTzzzDM89dRT5x3b2Si5inKG6SI+KZmQ28FyLFxW5chV8PQfnalS7CIiIiINKmAH+M93/zMi13524LN4Xd5zbr9y5UqSk5PD34cOHcry5ctZuHAhWVlZzJs3D8MwyM3N5fDhwzz00EM8+uijmGb1f6DfvXs3q1evZtOmTfTt2xeAhQsXkpeXV6/4J0+eTLt27bjlllvqddzXde7cmZkzZ1bb9vXCGzk5OUybNo177733jMmVbdsUFBSQkpICwOjRo3n77beVXF3KOvfuS4fu1/D229vwOadwh+IxOT1yZRiYppIrERERkUvVzTffzIIFC8Lfk5KSgMpkqV+/ftVGwQYMGEBJSQkHDx6kffv21c6zY8cO3G43vXv3Dm/Lzc2tVwW+mTNn8tvf/pZ3332X+Pj487wjqsVQ5Z133uHpp59m+/bt+Hw+QqEQfr+f0tLS8D1/U3Z2djixAsjMzKz3SFx9KbmKFUYQ27bwWPG4DBeOYeByn39FFRERERGpXZwZx7MDn43YtesjKSmJzp07V9tm2zaO49R4TqyaYlfb8+OZ9p2LX/ziFzz99NP86U9/4uqrrz6vc1T5ZrK0b98+hg0bxvjx45k2bRrNmzdn/fr15OfnEwwG6zyPx+Op9t0wDGzbvqDYzkbJVcwIYjs2cZYXFya2ofetRERERBqDYRj1mpoXjbp06cIbb7xRLcnauHEjKSkptGvXrkb7vLw8QqEQW7ZsoU+fPgDs2rWLkydPnvVaP//5z3nyySd58803ax11ulBbtmwhFArx7LPPhqczrlixosGv0xAi/nQ+f/58cnJyiI+Pp1evXrz//vt1tq2rLv5VV10VblNQUFBrG//pxXhjUeUfRRAb+/TIlYltGEquRERERKRW+fn5HDhwgPvuu4+dO3fy+uuv89hjjzFp0qQa71tBZTI2ZMgQxo0bx4cffsjWrVsZO3YsCQkJZ7zOzJkzmTJlCosWLSI7O5sjR45w5MiRapX8LlSnTp0IhULMnTuXPXv2sHTpUp5//vkGO39DiujT+fLly5k4cSKPPPIIH330ETfccANDhw5l//79tbb/Zl38AwcO0Lx5c+68885q7VJTU2vU+7+QeZ+RZtuVa13ZjkVcKCFcLdBUciUiIiIitWjbti0rV65k8+bNdO/enfHjx5Ofn8+UKVPqPGbx4sVkZWVx0003MWLECO65556zrh01f/58AoEAd9xxB5mZmeHPL37xiwa7lx49ejBr1ixmzJhB165dWbZsGdOnT2+w8zckw6maYBkBffv25Zprrqn2El5eXh633377Of3AXnvtNUaMGMHevXvp0KEDUDlyNXHixHMawqyLz+cjLS2NU6dOkZqaet7naShlZV/w/vofsi90lDZb7+OK5CvY6/aS0iaRG+66ItLhySUkGAyyatUqhg0bVmMes0hTU3+UaKL+GLv8fj979+4Nz6S6GNi2jc/nIzU1tdZRKqnpTP2gPrlBxN65CgQCbN26lcmTJ1fbPnjwYDZu3HhO51i4cCG33HJLOLGqUlJSQocOHbAsix49ejBt2jR69uxZ53kqKiqoqKgIf/f5fEDlfyjP9JJcU6moKMZxHEJW5R+HiYGFAwZREZ9cOqr6m/qdRAP1R4km6o+xKxgM4jgOtm03erGDplI1dlJ1X3J2VUVAgsFgeBHmKvX5u45YcnXs2DEsy6JNmzbVtrdp04YjR46c9fjCwkJWr17N//zP/1TbnpubS0FBAd26dcPn8/Hcc88xYMAAPv74Yy6//PJazzV9+nSmTp1aY/tbb71FYmJiPe6qcRjGF3i8DsGQiW07nCoupihoccJ/hC9X7Yh0eHIJWrNmTaRDEAlTf5Roov4Ye9xuNxkZGZSUlBAIRGbh4MZSXFwc6RBiRiAQoLy8nPfee49QKFRtX1lZ2TmfJ+LVAmsrEXkuJSALCgpIT0/n9ttvr7a9X79+9OvXL/x9wIABXHPNNcydO5c5c+bUeq6HH36YSZMmhb/7fD6ysrIYPHhwVEwLPHnyEzb/5VUM4nCZLpo1b05rx6B1hxSuGdL+7CcQaSDBYJA1a9YwaNAgTXuRiFN/lGii/hi7/H4/Bw4cIDk5+aKZFug4DsXFxaSkpGjZnnPk9/tJSEjgxhtvrHVa4LmKWHLVsmVLXC5XjVGqoqKiGqNZ3+Q4DosWLWL06NHExZ15LQDTNLn22mv5xz/+UWcbr9eL11uz3KbH44mK/0CapoWDg225ARPT48IMOni87qiITy490fK3IQLqjxJd1B9jj2VZGIaBaZoXzftJVVMBq+5Lzs40TQzDqPVvuD5/0xH7acfFxdGrV68aw+dr1qyhf//+Zzx23bp1fPrpp+Tn55/1Oo7jsG3bNjIzMy8o3kiy7XIsxwbbg4GJ4ar8takUu4iIiIhI9IjotMBJkyYxevRoevfuzXXXXccLL7zA/v37GT9+PFA5Xe/QoUO89NJL1Y5buHAhffv2pWvXrjXOOXXqVPr168fll1+Oz+djzpw5bNu2jV/96ldNck+NwbYrsHHCyVVVSqzkSkREREQkekQ0uRo5ciTHjx/niSeeoLCwkK5du7Jq1apw9b/CwsIaa16dOnWKV199leeee67Wc548eZJ77rmHI0eOkJaWRs+ePXnvvffCK03HIss6PXJleTAMA9usnDvrcmsOrYiIiIhItIh4QYsJEyYwYcKEWvcVFBTU2JaWlnbGih2//OUv+eUvf9lQ4UWFqpEr047DNFxUFdTUyJWIiIiISPTQ03kMsG0/lmNjWHGYhol9uuqL6dKvT0REREQkWujpPAZYth8bu3LkChPr9HaXR78+ERERETk/AwcOZOLEiWdsk52dzezZs5sknvqoWpYp2ujpPAbYth/bcTCtOEzT9VVypXeuRERERC5ZY8aMwTCMGp9PP/20yWJ48cUXueGGG2jWrBnNmjXjlltuYfPmzXW2f/XVV3G5XDXqKlTJzc3l/vvvb6xwG52SqxhgW35sHFyWF5dhYjkOoHeuRERERC51Q4YMobCwsNonJyenya7/7rvvcvfdd/POO+/wwQcf0L59ewYPHsyhQ4dqbX/bbbfRokULlixZUmPfhg0b2LVr1zkttxSt9HQeA+zT0wLdlheX4cJyqqoF6tcnIiIicinzer1kZGRU+7hcLqBybdg+ffrg9XrJzMxk8uTJhEKhOs9VVFTE8OHDSUhIICcnh2XLlp31+suWLWPChAn06NGD3NxcXnzxRWzb5u233661vcfjYfTo0RQUFOCcHjCosmjRInr16kX37t2ZNWsW3bp1IykpiaysLCZMmEBJSUk9fjKRoafzGGDZFTiOgzukkSsRERGRpmJXVNT5cQKBBm/bkA4fPsytt97Ktddey8cff8yCBQtYuHAhTz75ZJ3HjBkzhs8//5y1a9fyyiuvMH/+fIqKiup13bKyMoLBIM2bN6+zTX5+Pnv27GHdunXhbaWlpaxYsSI8amWaJnPmzOGTTz5hyZIlrF27lgcffLBesURCxEuxy9nZdvnpkat4XKaL0OnkytQ7VyIiIiKN5tBPJta5L75rV1r9+Efh74d/+mCNJKqK9/LLaf2fk8LfCx+Zgl3LKEzW8wvqHePKlStJTk4Ofx86dCjLly9n4cKFZGVlMW/ePAzDIDc3l8OHD/PQQw/x6KOPYprV/5F+9+7drF69mk2bNtG3b18AFi5cSF5eXr3imTx5Mu3ateOWW26ps82VV15J3759Wbx4MQMHDgRgxYoVWJbF3XffDVCt0EZOTg7Tpk3j3nvvZf78+fWKp6kpuYoBtlWBjY3HisflcuG3T49cqRS7iIiIyCXt5ptvZsGCr5KypKQkoDJZ6tevH4bx1T/GDxgwgJKSEg4ePEj79u2rnWfHjh243W569+4d3pabm1uvinwzZ87kt7/9Le+++y7x8fFnbJufn8/EiROZN28eKSkpLFq0iBEjRoSv98477/D000+zfft2fD4foVAIv99PaWlp+B6jkZKrKOc4Drbtx8GpTK48JsHTqwirFLuIiIhI42n33Ow69309aQFo+/OZ59w286m6p+bVV1JSEp07d662zbZtHMepcd2qd5y+uf1s+87FL37xC55++mn+9Kc/cfXVV5+1/ahRo3jggQdYvnw5AwcOZP369TzxxBMA7Nu3j2HDhjF+/HimTZtG8+bNWb9+Pfn5+QSDwfOKr6kouYpyjhPAwQbHwbA8ldMCLb1zJSIiItLYTK834m3PV5cuXXjjjTeqJVkbN24kJSWFdu3a1Wifl5dHKBRiy5Yt9OnTB4Bdu3Zx8uTJs17r5z//OU8++SRvvvlmtZGvM0lJSeHOO+9k8eLF7Nmzh44dO4anCG7ZsoVQKMSzzz4bnr64YsWKczpvpOnpPMpZVmUxCwPA9uA2XFhW5dCV1rkSERERkdrk5+dz4MAB7rvvPnbu3Mnrr7/OY489xqRJk2q8bwWVydiQIUMYN24cH374IVu3bmXs2LEkJCSc8TozZ85kypQpLFq0iOzsbI4cOcKRI0fOqbJffn4+GzduZMGCBfzwhz8MJ4GdOnUiFAoxd+5c9uzZw9KlS3n++efP7wfRxJRcRbnKBYRtbNsNGJhxbjBUil1ERERE6ta2bVtWrlzJ5s2b6d69O+PHjyc/P58pU6bUeczixYvJysripptuYsSIEdxzzz20bt36jNeZP38+gUCAO+64g8zMzPDnF7/4xVljvP766+nSpQs+n4/vf//74e09evRg1qxZzJgxg65du7Js2TKmT59+7jcfQZoWGOVqJFduF4SqqgUquRIRERG5VBUUFJxx/0033cTmzZvr3P/uu+9W+56RkcHKlSurbRs9evQZr/H555+fcf/Z7Ny5s9btDzzwAA888ECdsYwZM4YxY8Zc0LUbg57Oo5xllWM5FrblxsDEPF3EwjANTFPTAkVEREREooWSqyhn2xXYjo1jVyZXxunRKk0JFBERERGJLnpCj3KW5cdybBzbA5jhqYBKrkREREREooue0KOcbZdjOxZYnm+MXGlKoIiIiIhINFFyFeUsu3LkCiuOr49cqZiFiIiIiEh00RN6lLMtPyHbwrTjMDA0LVBEREREJErpCT3KWbYfy7Yw7NPTAk2tcSUiIiIiEo20zlWUa9nyn/ji0AFKT57ENFzY4eRK71yJiIiIiEQTJVdRzhvXki/tNMwAmIaJzenkyqORKxERERGRaKIn9BhQFizH67hxGSb26d+Y6dKvTkRERETO38CBA5k4ceIZ22RnZzN79uwmiedCFBQUkJ6eHukwlFzFgrKgnzjHjWm4sE5v0ztXIiIiIpe2MWPGYBhGjc+nn37aZDH87ne/o3fv3qSnp5OUlESPHj1YunRpvWP++ud8jBw5kt27d5/vbTQYPaHHgPKQH6/txmWaX0uu9M6ViIiIyKVuyJAhFBYWVvvk5OQ02fWbN2/OI488wgcffMBf//pXfvCDH/CDH/yAN998s9b2zz33XLVYARYvXlxjW5VAIHBOcSQkJNC6desLu5kGoOQqBpSH/HgdT2VBC0fVAkVERESkktfrJSMjo9rH5XIBsG7dOvr06YPX6yUzM5PJkycTCoXqPFdRURHDhw8nISGBnJwcli1bdtbrDxw4kO9+97vk5eXRqVMnfvKTn3D11Vezfv36WtunpaVVixUgPT09/H3UqFH8+Mc/ZtKkSbRs2ZJBgwYBMGvWLLp160ZSUhJZWVlMmDCBkpKS8Hm/OS3w8ccfD4+iZWdnk5aWxqhRoyguLj7rPV0IPaHHgPLT71y5DRPLcQAlVyIiIiKNxXEcQkErIh/n9LPehTp8+DC33nor1157LR9//DELFixg4cKFPPnkk3UeM2bMGD7//HPWrl3LK6+8wvz58ykqKjrnazqOw9tvv82uXbu48cYbzzv2JUuW4Ha72bBhA7/+9a8BME2TOXPm8Mknn7BkyRLWrl3Lgw8+eMbzfPbZZ7z22musXLmSlStXsm7dOp555pnzjutcqFpgDLBCAQzHwGW6CJ3+e1NyJSIiItI4rJDNmy98EpFrf/uerrg9rnNuv3LlSpKTk8Pfhw4dyvLly1m4cCFZWVnMmzcPwzDIzc3l8OHDPPTQQzz66KOYZvVnyd27d7N69Wo2bdpE3759AVi4cCF5eXlnjeHUqVO0a9eOiooKXC4X8+fPD484nY/OnTszc+bMatu+XngjJyeHadOmce+99zJ//vw6z2PbNgUFBaSkpAAwevRo3n77bZ566qnzju1slFxFOduxcYKVb1q5TBeWbQNg6p0rERERkUvezTffzIIFC8Lfk5KSgMpkqV+/ftUKRAwYMICSkhIOHjxI+/btq51nx44duN1uevfuHd6Wm5t7ThX4UlJS2LZtGyUlJbz99ttMmjSJjh07MnDgwPO6p6/HUOWdd97h6aefZvv27fh8PkKhEH6/n9LS0vA9f1N2dnY4sQLIzMys10jc+VByFeX8IT9uq/LXZHhchE5XtNDIlYiIiEjjcLlNvn1P14hduz6SkpLo3LlztW22beM4To3Ke1VTDmuryHemfWdjmmY4hh49erBjxw6mT59+3snVN5Olffv2MWzYMMaPH8+0adNo3rw569evJz8/n2AwWOd5PB5Pte+GYWCfHqhoLEquolyFVYErVDk0bLhdWKHKDqHkSkRERKRxGIZRr6l50ahLly688cYb1ZKsjRs3kpKSQrt27Wq0z8vLIxQKsWXLFvr06QPArl27OHnyZL2v7TgOFRUVFxT/123ZsoVQKMSzzz4bns64YsWKBjt/Q9ITepSrHLlyYWBgxCm5EhEREZGzy8/P58CBA9x3333s3LmT119/nccee4xJkybVeN8KKpOxIUOGMG7cOD788EO2bt3K2LFjSUhIOON1pk+fzpo1a9izZw87d+5k1qxZvPTSS3zve99rsHvp1KkToVCIuXPnsmfPHpYuXcrzzz/fYOdvSHpCj3LlVjke2wWYmHEu7NMVLfTOlYiIiIjUpW3btqxcuZLNmzfTvXt3xo8fT35+PlOmTKnzmMWLF5OVlcVNN93EiBEjuOeee866dlRpaSkTJkzgqquuon///rzyyiv893//N2PHjm2we+nRowezZs1ixowZdO3alWXLljF9+vQGO39DMpyGqvd4EfH5fKSlpXHq1ClSU1MjGsv249t54ZWlDCy8mivyunM0aFJ2qoLrRnSmeWbtL++JNJZgMMiqVasYNmxYjXnMIk1N/VGiifpj7PL7/ezdu5ecnBzi4+MjHU6DsG0bn89HampqraNUUtOZ+kF9cgP9tKOcP+THY1dOCzQ1LVBEREREJGrpCT3K+S0/HssNmLi8Sq5ERERERKKVntCjXOXIlRswcHtdWMHTyZVH71yJiIiIiEQTJVdRzh/y47FcGI6Jx+vCsStfkXO59KsTEREREYkmekKPcuWh8vDIletr6y1oWqCIiIiISHTRIsJRrlfrPpyw4zBtD+6vlV9XKXYRERERkeii4Y8o1zw+gyS7OSZxuDyVvy7TbYZX2hYRERERkeig5CrKVQRtPA4YgH16nQKXS4mViIiIiEi0UXIV5fxBC49dmVw5p0er9L6ViIiIiEj00VN6lKsI2cQ5YBpgnx6wMj36tYmIiIjIhRk4cCATJ048Y5vs7Gxmz57dJPHUR0FBAenp6ZEOowY9pUe5imAIj+1gGGCdTq5Uhl1ERERExowZg2EYNT6ffvppk8Xwu9/9jt69e5Oenk5SUhI9evRg6dKldbZ/9dVXcblc7N+/v9b9ubm53H///Y0VbqPTU3qU8/stoPIXZZ/e5lKlQBEREREBhgwZQmFhYbVPTk5Ok12/efPmPPLII3zwwQf89a9/5Qc/+AE/+MEPePPNN2ttf9ttt9GiRQuWLFlSY9+GDRvYtWsX+fn5jR12o4l4cjV//nxycnKIj4+nV69evP/++3W2rSs7v+qqq6q1e/XVV7nyyivxer1ceeWV/P73v2/s22g0QX8IAMOA0+sH650rEREREQHA6/WSkZFR7eNyVa6Num7dOvr06YPX6yUzM5PJkycTCoXqPFdRURHDhw8nISGBnJwcli1bdtbrDxw4kO9+97vk5eXRqVMnfvKTn3D11Vezfv36Wtt7PB5Gjx5NQUEBjuNU27do0SJ69epF9+7dmTVrFt26dSMpKYmsrCwmTJhASUlJPX4ykRHRp/Tly5czceJEHnnkET766CNuuOEGhg4dWucw4XPPPVctKz9w4ADNmzfnzjvvDLf54IMPGDlyJKNHj+bjjz9m9OjR3HXXXXz44YdNdVsNqiq5CpkOllXZAV1650pERESk0YUCgTo/VijY4G0b0uHDh7n11lu59tpr+fjjj1mwYAELFy7kySefrPOYMWPG8Pnnn7N27VpeeeUV5s+fT1FR0Tlf03Ec3n77bXbt2sWNN95YZ7v8/Hz27NnDunXrwttKS0tZsWJFeNTKNE3mzJnDJ598wpIlS1i7di0PPvjgOccSKRFdRHjWrFnk5+czduxYAGbPns2bb77JggULmD59eo32aWlppKWlhb+/9tprnDhxgh/84AfhbbNnz2bQoEE8/PDDADz88MOsW7eO2bNn89vf/rbWOCoqKqioqAh/9/l8AASDQYLBYK3HNBV/WQADsAyHgD+I7ThgOBGPSy5NVf1O/U+igfqjRBP1x9gVDAZxHAfbtrFtu9q+P/yy5vNolTY5nbnujrvD39+Y+4saSVSVlpe15/q7vx/+/ubzz1FRXlaj3e0//Vm9Yncch5UrV5KcnBzeNmTIEJYvX87ChQvJyspizpw5GIbBFVdcwaFDh5g8eTJTpkzBPL3ET9W97969m9WrV7Nx40b69u0LwIsvvshVV10VblOXU6dOkZWVRUVFBS6Xi3nz5vFP//RPdR6Tm5tL3759WbRoUTgJe/nll7Esi5EjR2LbdrX3rjp06MDUqVP50Y9+xLx58wDC5z5TXPVh2zaOU/mMXTXyV6U+f9cRS64CgQBbt25l8uTJ1bYPHjyYjRs3ntM5Fi5cyC233EKHDh3C2z744AMeeOCBau2+/e1vn7HKyfTp05k6dWqN7W+99RaJiYnnFEtj2XvQzRWBBOwEh4/+so3Sox5OhQ5zOPi3iMYll7Y1a9ZEOgSRMPVHiSbqj7HH7XaTkZFBSUkJgW+MHoWCdU+hq6ioCP+DPEAoFMSqo31FIFCtbTAYrPXcX29zLoLBIDfccAPPPvtseFtiYiLFxcXs3r2bXr16UVxcHN539dVXU1JSwo4dO8jKyiIUChE4Hdtf/vIX3G43V1xxRTiOtm3bkpaWht/vP2NsjuPw3nvvUVpayrp16/jP//xPMjIyuP766+s85u677+b//b//x1NPPUVKSgq/+c1vuPXWWzFNE5/Px/vvv8+sWbPYtWsXxcXFhEIh/H4/hYWFJCUl4ff7cRyn3j+zugQCAcrLy3nvvfdqTJ0sK6uZCNclYsnVsWPHsCyLNm3aVNvepk0bjhw5ctbjCwsLWb16Nf/zP/9TbfuRI0fqfc6HH36YSZMmhb/7fD6ysrIYPHgwqamp53I7jebNt/YQ9+UXlJvldL2qG3uDX5KV14yrbmwb0bjk0hQMBlmzZg2DBg3C4/FEOhy5xKk/SjRRf4xdfr+fAwcOkJycTHx8fLV9t//XI3UeZ5gGLvdXv+vhP3nonNsO+9GkWtu54+LONWyg8v2l1NRUevToUW274zg4jkNcXFy1Z9mkpCQAUlNTSU1Nxe12h9tU3XtaWlp4VAvAMAzi4+PP+kxcFcOAAQPYu3cvc+bMYdiwYXW2HzNmDI888girV69m4MCBbNq0iSeffJLU1FT27dvHXXfdxX/8x3/w1FNP0bx5c9avX8+4ceNISEgIx2sYRoM9q/v9fhISErjxxhtr9IP6JHARnRYIlb+wr3Mcp8a22lTVtr/99tsv+Jxerxev11tju8fjifh/IHu0S6d8XymHA2XgmJiGQZw38nHJpS0a/jZEqqg/SjRRf4w9lmVhGAamaVZLKgDivvGQfSaN1fZMqoq7fTNu27bp0qULb7zxRrgNwKZNm0hJSSErKyt8TNXxV111FaFQiL/85S/06dMHgF27dnHy5Mlar3E2gUDgjMekpaVx5513smTJEj7//HM6duzIt771LQzD4C9/+QuhUIhZs2aFz/HKK68AhH9PVdvrG1ddTNPEMIxa/4br8zcdscoILVu2xOVy1RhRKioqqjHy9E2O47Bo0SJGjx5N3Dcy/IyMjPM6Z7RqEecmLcGDN87BtirnlKoUu4iIiIicSX5+PgcOHOC+++5j586dvP766zz22GNMmjSp1oSkS5cuDBkyhHHjxvHhhx+ydetWxo4dS0JCwhmvM336dNasWcOePXvYuXMns2bN4qWXXuJ73/veOcW4ceNGFixYwA9/+MNwEtipUydCoRBz585lz549LF26lOeff/78fhBNLGLJVVxcHL169aoxN3nNmjX079//jMeuW7eOTz/9tNYa+Nddd12Nc7711ltnPWe0coKV61zZLgcrWJlcmSrFLiIiIiJn0LZtW1auXMnmzZvp3r0748ePJz8/nylTptR5zOLFi8nKyuKmm25ixIgR3HPPPbRu3fqM1yktLWXChAlcddVV9O/fn1deeYX//u//DhesO5Prr7+eLl264PP5+P73vyr40aNHD2bNmsWMGTPo2rUry5Ytq7XYXTQynG8WmG9Cy5cvZ/To0Tz//PNcd911vPDCC7z44ov8/e9/p0OHDjz88MMcOnSIl156qdpxo0eP5h//+AebNm2qcc6NGzdy44038tRTT/HP//zPvP7660yZMoX169eHK5+cjc/nIy0tjVOnTkX8navSPx+h9JMv2B06SHxWLkc/85E3oC0de7SKaFxyaQoGg6xatYphw4Zp2otEnPqjRBP1x9jl9/vZu3dveN3Vi4Ft2/h8PlJTUxts2tzF7kz9oD65QUTfuRo5ciTHjx/niSeeoLCwkK5du7Jq1apw9b/CwsIaa16dOnWKV199leeee67Wc/bv35+XX36ZKVOm8LOf/YxOnTqxfPnyc06sok1c+xTsOIPSv+/DEzo9LVDrXImIiIiIRJ2IF7SYMGECEyZMqHVfQUFBjW1paWlnLYd4xx13cMcddzREeBHnaZMEzePwf25hh04vIuzSO1ciIiIiItFGQyAxxKoaudI7VyIiIiIiUUdP6THE0rRAEREREZGopaf0GFI1LdB06dcmIiIiIhJt9JQeQ76aFqh3rkREREREoo2SqxhiWacLWuidKxERERGRqKOn9Bhi650rEREREZGopaf0GKJqgSIiIiIi0UtP6THCscGpnBWIqXWuREREROQCDRw4kIkTJ56xTXZ2NrNnz26SeC5EQUEB6enpkQ5DyVWscOyv/r+mBYqIiIjImDFjMAyjxufTTz+NSDwvv/wyhmFw++2319mmrpi//jkfI0eOZPfu3ecZecPRU3qsOD1qhWFgmhq5EhEREREYMmQIhYWF1T45OTlNHse+ffv4r//6L2644YYztnvuueeqxQqwePHiGtuqBAKBc7p+QkICrVu3Pr/gG5CSqxjh2JUJlct9/hm9iIiIiFxcvF4vGRkZ1T4ulwuAdevW0adPH7xeL5mZmUyePJlQKFTnuYqKihg+fDgJCQnk5OSwbNmyc4rBsiz+7d/+jalTp9KxY8cztk1LS6sWK0B6enr4+6hRo/jxj3/MpEmTaNmyJYMGDQJg1qxZdOvWjaSkJLKyspgwYQIlJSXh835zWuDjjz9Ojx49WLp0KdnZ2aSlpTFq1CiKi4vP6Z7Ol5KrGFE1LVALCIuIiIg0LsdxcIJ2ZD5VL9lfoMOHD3Prrbdy7bXX8vHHH7NgwQIWLlzIk08+WecxY8aM4fPPP2ft2rW88sorzJ8/n6KiorNe64knnqBVq1bk5+c3SOxLlizB7XazYcMGfv3rXwNgmiZz5szhk08+YcmSJaxdu5YHH3zwjOf57LPPeO2111i5ciUrV65k3bp1PPPMMw0SY13cjXp2aTBVyZXetxIRERFpZCGH48t2ROTSLf4tDzznPktp5cqVJCcnh78PHTqU5cuXs3DhQrKyspg3bx6GYZCbm8vhw4d56KGHePTRRzHN6s+Uu3fvZvXq1WzatIm+ffsCsHDhQvLy8s54/Q0bNrBw4UK2bdt27jd5Fp07d2bmzJnVtn298EZOTg7Tpk3j3nvvZf78+XWex7ZtCgoKSElJAWD06NG8/fbbPPXUUw0W6zcpuYoV4WmBSq5EREREpNLNN9/MggULwt+TkpKAymSpX79+1V4nGTBgACUlJRw8eJD27dtXO8+OHTtwu9307t07vC03N/eMFfiKi4v53ve+x4svvkjLli0b6I6oFkOVd955h6effprt27fj8/kIhUL4/X5KS0vD9/xN2dnZ4cQKIDMz85xG4i6EkqsYER65Uhl2ERERkcblNipHkCJ07fpISkqic+fO1bbZduX0wm++p1815bC29/fPtK8un332GZ9//jnDhw+vdm0At9vNrl276NSp0zmfr8o3k6V9+/YxbNgwxo8fz7Rp02jevDnr168nPz+fYDBY53k8Hk+174ZhhONrLEquYkQ4udLIlYiIiEijMgyjXlPzolGXLl144403qiVZGzduJCUlhXbt2tVon5eXRygUYsuWLfTp0weAXbt2cfLkyTqvkZuby9/+9rdq26ZMmUJxcTHPPfccWVlZDXIvW7ZsIRQK8eyzz4anM65YsaJBzt3QlFzFiHC1QL1zJSIiIiJnkZ+fz/PPP899993Hj3/8Y3bt2sVjjz3GpEmTarxvBZXJ2JAhQxg3bhwvvPACbrebiRMnkpCQUOc14uPj6dq1a7VtVdMIv7n9QnTq1IlQKMTcuXMZPnw4GzZs4Pnnn2+w8zckPanHivDIVWz/K4qIiIiINL62bduycuVKNm/eTPfu3Rk/fjz5+flMmTKlzmMWL15MVlYWN910EyNGjOCee+6JirWjevTowaxZs5gxYwZdu3Zl2bJlTJ8+PdJh1cpwGqre40XE5/ORlpbGqVOnSE1NjXQ4BINBXl38JkmBy2h3RTOuGdwh0iHJJSoYDLJq1SqGDRtWYx6zSFNTf5Roov4Yu/x+P3v37iUnJ4f4+PhIh9MgbNvG5/ORmppa6yiV1HSmflCf3EA/7RgRnhaoda5ERERERKKSntRjhda5EhERERGJanpSjxFV1QJNlWIXEREREYlKSq5ihKNFhEVEREREopqe1GOE1rkSEREREYluelKPFY7WuRIRERERiWZ6Uo8Rjta5EhERERGJakquYkQ4uVIpdhERERGRqKQn9RgRLmihaYEiIiIiIlFJT+qxQgUtRERERKQBDRw4kIkTJ56xTXZ2NrNnz26SeOqjoKCA9PT0SIdRg57UY4TWuRIRERGRrxszZgyGYdT4fPrppxGJ5+WXX8YwDG6//fY627z66qu4XC72799f6/7c3Fzuv//+Roqw8Sm5ihFa50pEREREvmnIkCEUFhZW++Tk5DR5HPv27eO//uu/uOGGG87Y7rbbbqNFixYsWbKkxr4NGzawa9cu8vPzGyvMRqcn9RgRLmihd65EREREmkQwGKzzEwqFGrzt+fB6vWRkZFT7uFwuANatW0efPn3wer1kZmYyefLkGrF8XVFREcOHDychIYGcnByWLVt2TjFYlsW//du/MXXqVDp27HjGth6Ph9GjR1NQUIDjONX2LVq0iF69etG9e3dmzZpFt27dSEpKIisriwkTJlBSUnJO8USSO9IByDnSO1ciIiIiTep///d/69zXtm1bBg4cGP7+u9/9Dsuyam3bunVrbrnllvD3P/zhD1RUVNRo96//+q/nH+w3HD58mFtvvZUxY8bw0ksvsXPnTsaNG0d8fDyPP/54rceMGTOGAwcOsHbtWuLi4rj//vspKio667WeeOIJWrVqRX5+Pu+///5Z2+fn5zNr1izWrVsX/hmWlpayYsUKZs6cCYBpmsyZM4fs7Gz27t3LhAkTePDBB5k/f/45/wwiQclVDHAc52vTAvXOlYiIiIhUWrlyJcnJyeHvQ4cOZfny5SxcuJCsrCzmzZuHYRjk5uZy+PBhHnroIR599FFMs/o/2O/evZvVq1ezadMm+vbtC8DChQvJy8s74/U3bNjAwoUL2bZt2znHfOWVV9K3b18WL14cTq5WrFiBZVncfffdANUKbeTk5DBt2jTuvfdeJVdy4WzrqyFTUyNXIiIiIk3izjvvrHOfYVT/B+8RI0acc9vbbrvtwgL7mptvvpkFCxaEvyclJQGVyVK/fv2qXXvAgAGUlJRw8OBB2rdvX+08O3bswO1207t37/C23NzcM1bkKy4u5nvf+x4vvvgiLVu2rFfc+fn5TJw4kXnz5pGSksKiRYsYMWJE+HrvvPMOTz/9NNu3b8fn8xEKhfD7/ZSWlobvMRopuYoBVsgO/3+XqgWKiIiINAmPxxPxtmeTlJRE586dq22zbRvHcWokdVXvOH1z+9n21eWzzz7j888/Z/jw4dWuDeB2u9m1axedOnWq9dhRo0bxwAMPsHz5cgYOHMj69et54okngMriGMOGDWP8+PFMmzaN5s2bs379evLz88/73bSmouQqBlSNXBmGgenSyJWIiIiInFmXLl144403qiVZGzduJCUlhXbt2tVon5eXRygUYsuWLfTp0weAXbt2cfLkyTqvkZuby9/+9rdq26ZMmUJxcTHPPfccWVlZdR6bkpLCnXfeyeLFi9mzZw8dO3YMTxHcsmULoVCIZ599Njx9ccWKFfW5/YhRchUDqkau9L6ViIiIiJyL/Px8nn/+ee677z5+/OMfs2vXLh577DEmTZpU430rqEzGhgwZwrhx43jhhRdwu91MnDiRhISEOq8RHx9P165dq22rmtb3ze11xXjDDTewfft2/uu//iucBHbq1IlQKMTcuXMZPnw4GzZs4Pnnn6/H3UeOhkFigBWsHLnS+1YiIiIici7atm3LypUr2bx5M927d2f8+PHk5+czZcqUOo9ZvHgxWVlZ3HTTTYwYMYJ77rmH1q1bN1qM119/PV26dMHn8/H9738/vL1Hjx7MmjWLGTNm0LVrV5YtW8b06dMbLY6GZDjfLDAv+Hw+0tLSOHXqFKmpqZEOhy8OnuIPv/6QDp3bccv3r4p0OHIJCwaDrFq1imHDhjXofHGR86H+KNFE/TF2+f1+9u7dS05ODvHx8ZEOp0HYto3P5yM1NbXWUSqp6Uz9oD65gX7aMcAKVea/WuNKRERERCR66Wk9Bnz1zpV+XSIiIiIi0UpP6zHAVkELEREREZGop+QqBlSNXKkMu4iIiIhI9NLTegz46p0rjVyJiIiIiESriCdX8+fPD1fl6NWrF++///4Z21dUVPDII4/QoUMHvF4vnTp1YtGiReH9BQUFGIZR4+P3+xv7VhqNrXeuRERERESiXkQXEV6+fDkTJ05k/vz5DBgwgF//+tcMHTqU7du30759+1qPueuuuzh69CgLFy6kc+fOFBUVEQqFqrVJTU1l165d1bbFcmlNy6pa50ojVyIiIiIi0SqiydWsWbPIz89n7NixAMyePZs333yTBQsW1LpQ2P/93/+xbt069uzZQ/PmzQHIzs6u0c4wDDIyMho19qakaoEiIiIiItEvYslVIBBg69atTJ48udr2wYMHs3HjxlqP+cMf/kDv3r2ZOXMmS5cuJSkpidtuu41p06aRkJAQbldSUkKHDh2wLIsePXowbdo0evbsWWcsFRUVVFRUhL/7fD6gckHAYDB4IbfZIIIVlSNzjuFERTxy6arqf+qHEg3UHyWaqD/GrmAwiOM42LaNbduRDqdBOI4T/t+L5Z4am23bOE7ls7bL5aq2rz5/1xFLro4dO4ZlWbRp06ba9jZt2nDkyJFaj9mzZw/r168nPj6e3//+9xw7dowJEybw5Zdfht+7ys3NpaCggG7duuHz+XjuuecYMGAAH3/8MZdffnmt550+fTpTp06tsf2tt94iMTHxAu/0wpXs8wButm//hM9Pbot0OCKsWbMm0iGIhKk/SjRRf4w9brebjIwMSkpKCAQCkQ6nQRUXF59x/6233kq3bt1qnTFW5eqrr+bee+/l3nvvbejwGtT//M//8PDDD7Nv377zOj4QCFBeXs57771X45WjsrKycz5PRKcFQuUUvq9zHKfGtiq2bWMYBsuWLSMtLQ2onFp4xx138Ktf/YqEhAT69etHv379wscMGDCAa665hrlz5zJnzpxaz/vwww8zadKk8Hefz0dWVhaDBw8mNTX1Qm/xgn20Zj9/++IzevTsTudebc5+gEgjCQaDrFmzhkGDBuHxeCIdjlzi1B8lmqg/xi6/38+BAwdITk6OuXf0f/CDH/DSSy/V2L5z507atGlDSkpKnc/VUJlYxsXFnfF51zRN4uPj62xTUFBAfn5+je2lpaW1/jzrivnrLMs64/7afP/732fEiBHn/ezu9/tJSEjgxhtvrBF31ay2cxGx5Kply5a4XK4ao1RFRUU1RrOqZGZm0q5du3BiBZCXl4fjOBw8eLDWkSnTNLn22mv5xz/+UWcsXq8Xr9dbY7vH44mK/0AaTuUfRZw3OuIRiZa/DRFQf5Toov4YeyzLwjAMTNPENGPr/XbDMBgyZAiLFy+utr1FixaUlpaG7+ts57iQNqZp1lpMrq7ZX3PmzGHGjBnh75mZmSxevJghQ4ZUO2eVQCBAXFzcGeMDSEpKIikp6azt6mKaJoZh1Po3XJ+/6Yj1oLi4OHr16lVj+HzNmjX079+/1mMGDBjA4cOHKSkpCW/bvXs3pmly2WWX1XqM4zhs27aNzMzMhgu+iYUXEVa1QBEREZFG5zgOllURkU/V+1Lnyuv1kpGRUe1T9c7QunXr6NOnD16vl8zMTCZPnlxjytvXFRUVMXz4cBISEsjJyWHZsmXnFENVMbmvf+qSlpZWo116enr4+6hRo/jxj3/MpEmTaNmyJYMGDQIqZ6t169aNpKQksrKymDBhQrWcoKCggPT09PD3xx9/nB49erB06VKys7NJS0tj1KhRZ50qeaEiOi1w0qRJjB49mt69e3PdddfxwgsvsH//fsaPHw9UTtc7dOhQeOjwX//1X5k2bRo/+MEPmDp1KseOHeOnP/0pP/zhD8MFLaZOnUq/fv24/PLL8fl8zJkzh23btvGrX/0qYvd5ob5aRDi2/jVFREREJBbZdoBPPvlxRK7dtes8XK6aM6rq6/Dhw9x6662MGTOGl156iZ07dzJu3Dji4+N5/PHHaz1mzJgxHDhwgLVr1xIXF8f9999PUVHRWa9V32JyZ7NkyRLuvfdeNmzYEE42TdNkzpw5ZGdns3fvXiZMmMCDDz7I/Pnz6zzPZ599xmuvvcbKlSs5ceIEd911F8888wxPPfXUecd2NhFNrkaOHMnx48d54oknKCwspGvXrqxatYoOHToAUFhYyP79+8Ptk5OTWbNmDffddx+9e/emRYsW3HXXXTz55JPhNidPnuSee+7hyJEjpKWl0bNnT9577z369OnT5PfXUGyrqhS7Rq5ERERE5CsrV64kOTk5/H3o0KEsX76chQsXkpWVxbx58zAMg9zcXA4fPsxDDz3Eo48+WmOa3+7du1m9ejWbNm2ib9++ACxcuJC8vLwzXv98ismdTefOnZk5c2a1bRMnTgz//5ycHKZNm8a99957xuTKtm0KCgpISUkBYPTo0bz99tsXb3IFMGHCBCZMmFDrvoKCghrbcnNzz1iJ55e//CW//OUvGyq8qPDVtECNXImIiIg0NtOMo2vXeRG7dn3cfPPNLFiwIPy96r2j3bt3069fv2oFLQYMGEBJSQkHDx6kffv21c6zY8cO3G43vXv3Dm/Lzc2tNtWuNudTTO5svh5DlXfeeYenn36a7du34/P5CIVC+P1+SktL63zXKjs7O5xYQeX7XecyEnchIp5cydlpWqCIiIhI0zEMo0Gm5jWFpKQkOnfuXG1b1ZpNtVXlhprVus+2rz7OpZjc2XwzWdq3bx/Dhg1j/PjxTJs2jebNm7N+/Xry8/PPuAbVNwtRGIbR6Ot+6Wk9BlSNXGlaoIiIiIiciy5duvDBBx9UK5CxceNGUlJSaNeuXY32eXl5hEIhtmzZEt62a9cuTp48Wa/rNkYxuS1bthAKhXj22Wfp168fV1xxBYcPH26w8zckJVcxwD49cmW69OsSERERkbPLz8/nwIED3HfffezcuZPXX3+dxx57jEmTJtVaVr1Lly4MGTKEcePG8eGHH7J161bGjh0bLhpXl6lTp/Lmm2+yZ88etm3bRn5+Ptu2bQsXqGsInTp1IhQKMXfuXPbs2cPSpUt5/vnnG+z8DUlP6zFAI1ciIiIiUh9t27Zl5cqVbN68me7duzN+/Hjy8/OZMmVKnccsXryYrKwsbrrpJkaMGME999xD69atz3idqmJyeXl5DB48mEOHDjV4MbkePXowa9YsZsyYQdeuXVm2bBnTp09vsPM3JMOpbzH9S4DP5yMtLY1Tp06d9yrPDcWxHVbO/5iio0WM+ukNJKWe+V8PRBpTMBhk1apVDBs2TItkSsSpP0o0UX+MXX6/n71795KTk0N8fHykw2kQtm3j8/lITU2NuYWRI+VM/aA+uYF+2lHOsr566U7VAkVEREREopee1qNcVaVA0LRAEREREZFopuQqytmn37fCrFlOU0REREREooeSqyhXVczC0G9KRERERCSq6ZE9yim5EhERERGJDXpkj3JV71wZpoo6ioiIiIhEMyVXUc4Kv3MV2ThEREREROTM9Mge5TQtUEREREQkNuiRPcrZ4eRK0wJFRERERKKZkqsoZwVPv3OlKuwiIiIi0oAGDhzIxIkTz9gmOzub2bNnN0k89VFQUEB6enqkw6hByVWUsyy9cyUiIiIiNY0ZMwbDMGp8Pv300yaLoaCgoNYY/H5/re1fffVVXC4X+/fvr3V/bm4u999/f2OG3Kj0yB7lLE0LFBEREZE6DBkyhMLCwmqfnJycJo0hNTW1Rgzx8fG1tr3tttto0aIFS5YsqbFvw4YN7Nq1i/z8/MYOudEouYpydrgUe4QDEREREbnE+C27zk/Athu87fnwer1kZGRU+7hcLgDWrVtHnz598Hq9ZGZmMnnyZEKhUJ3nKioqYvjw4SQkJJCTk8OyZcvOKQbDMGrEUBePx8Po0aMpKCjAcaoPHixatIhevXrRvXt3Zs2aRbdu3UhKSiIrK4sJEyZQUlJyTvFEkjvSAciZqVqgiIiISGSM+/vnde7rnpLIf+V8lUT8aMc+AnbtM41yk+J5pFPb8PdJuw5QHLJqtFt6dcfzD/YbDh8+zK233sqYMWN46aWX2LlzJ+PGjSM+Pp7HH3+81mPGjBnDgQMHWLt2LXFxcdx///0UFRWd9VolJSV06NABy7Lo0aMH06ZNo2fPnnW2z8/PZ9asWaxbt46BAwcCUFpayooVK5g5cyYApmkyZ84csrOz2bt3LxMmTODBBx9k/vz59f5ZNCU9ske5+GQPzTISMb3n968ZIiIiInLxWrlyJcnJyeHPnXfeCcDChQvJyspi3rx55ObmcvvttzN16lSeffZZbLvmc+Xu3btZvXo1v/nNb7juuuvo1asXCxcupLy8/IzXz83NpaCggD/84Q/89re/JT4+ngEDBvCPf/yjzmOuvPJK+vbty+LFi8PbVqxYgWVZ3H333QBMnDiRm2++mZycHL71rW8xbdo0VqxYcT4/oialkasol92tJe1y0zi+akekQxERERG5pLx4VXad+8xvVHL+VV6Hc247q0vWBURV3c0338yCBQvC35OSkoDKZKlfv34YXys5PWDAAEpKSjh48CDt27evdp4dO3bgdrvp3bt3eFtubu5ZK/L169ePfv36VbvGNddcw9y5c5kzZ06dx+Xn5zNx4kTmzZtHSkoKixYtYsSIEeHrvfPOOzz99NNs374dn89HKBTC7/dTWloavsdopJErEREREZFaxLvMOj9xptngbc9HUlISnTt3Dn8yMzMBcBynWmJVtQ2osf1s++rDNE2uvfbaM45cAYwaNQrDMFi+fDmffvop69evDxey2LdvH8OGDaNr1668+uqrbN26lV/96lcABIPBC4qvsWnkSkRERETkItOlSxfeeOONaknWxo0bSUlJoV27djXa5+XlEQqF2LJlC3369AFg165dnDx5sl7XdRyHbdu20a1btzO2S0lJ4c4772Tx4sXs2bOHjh07ht+/2rJlC6FQiGeffRbzdGIaC1MCQSNXIiIiIiIXnfz8fA4cOMB9993Hzp07ef3113nssceYNGlSOGH5ui5dujBkyBDGjRvHhx9+yNatWxk7diwJCQlnvM7UqVN588032bNnD9u2bSM/P59t27Yxfvz4c4px48aNLFiwgB/+8IfhJLBTp06EQiHmzp3Lnj17WLp0Kc8///z5/SCamJIrEREREZGLTNu2bVm5ciWbN2+me/fujB8/nvz8fKZMmVLnMYsXLyYrK4ubbrqJESNGcM8999C6deszXufkyZPcc8895OXlMXjwYA4dOsR7770XHv06k+uvv54uXbrg8/n4/ve/H97eo0cPZs2axYwZM+jatSvLli1j+vTp537zEWQ43ywwL/h8PtLS0jh16hSpqamRDodgMMiqVasYNmwYHo8n0uHIJUx9UaKJ+qNEE/XH2OX3+9m7dy85OTl1Lnwba2zbxufzkZqaWusoldR0pn5Qn9xAP20REREREZEGoORKRERERESkASi5EhERERERaQBKrkRERERERBqAkisRERERueSpxtulraF+/0quREREROSSVVXdsaysLMKRSCQFAgEAXC7XBZ3H3RDBiIiIiIjEIpfLRXp6OkVFRQAkJiaGF7ONVbZtEwgE8Pv9KsV+Dmzb5osvviAxMRG3+8LSIyVXIiIiInJJy8jIAAgnWLHOcRzKy8tJSEiI+USxqZimSfv27S/456XkSkREREQuaYZhkJmZSevWrQkGg5EO54IFg0Hee+89brzxRi1qfY7i4uIaZJRPyZWIiIiICJVTBC/0nZto4HK5CIVCxMfHK7lqYpqEKSIiIiIi0gCUXImIiIiIiDQAJVciIiIiIiINQO9c1aJqETGfzxfhSCoFg0HKysrw+XyaNysRpb4o0UT9UaKJ+qNEE/XHhlWVE5zLQsNKrmpRXFwMQFZWVoQjERERERGRaFBcXExaWtoZ2xjOuaRglxjbtjl8+DApKSlRsTaAz+cjKyuLAwcOkJqaGulw5BKmvijRRP1Roon6o0QT9ceG5TgOxcXFtG3b9qzl2jVyVQvTNLnssssiHUYNqamp+gORqKC+KNFE/VGiifqjRBP1x4ZzthGrKipoISIiIiIi0gCUXImIiIiIiDQAJVcxwOv18thjj+H1eiMdilzi1Bclmqg/SjRRf5Roov4YOSpoISIiIiIi0gA0ciUiIiIiItIAlFyJiIiIiIg0ACVXIiIiIiIiDUDJlYiIiIiISANQchXl5s+fT05ODvHx8fTq1Yv3338/0iHJRW769Olce+21pKSk0Lp1a26//XZ27dpVrY3jODz++OO0bduWhIQEBg4cyN///vcIRSyXkunTp2MYBhMnTgxvU3+UpnTo0CG+973v0aJFCxITE+nRowdbt24N71d/lKYSCoWYMmUKOTk5JCQk0LFjR5544gls2w63UX9sekquotjy5cuZOHEijzzyCB999BE33HADQ4cOZf/+/ZEOTS5i69at40c/+hGbNm1izZo1hEIhBg8eTGlpabjNzJkzmTVrFvPmzePPf/4zGRkZDBo0iOLi4ghGLhe7P//5z7zwwgtcffXV1barP0pTOXHiBAMGDMDj8bB69Wq2b9/Os88+S3p6eriN+qM0lRkzZvD8888zb948duzYwcyZM/n5z3/O3Llzw23UHyPAkajVp08fZ/z48dW25ebmOpMnT45QRHIpKioqcgBn3bp1juM4jm3bTkZGhvPMM8+E2/j9fictLc15/vnnIxWmXOSKi4udyy+/3FmzZo1z0003OT/5yU8cx1F/lKb10EMPOddff32d+9UfpSl95zvfcX74wx9W2zZixAjne9/7nuM46o+RopGrKBUIBNi6dSuDBw+utn3w4MFs3LgxQlHJpejUqVMANG/eHIC9e/dy5MiRan3T6/Vy0003qW9Ko/nRj37Ed77zHW655ZZq29UfpSn94Q9/oHfv3tx55520bt36/7d3byFRtXscx38rJ8dRhrAsx4rKyDLtQGmQh4ISQoPCMKQys7oIS82Sws4Zld1ERVADE+VNhSF0sLKjRWAQSjUlZXURHSDCouhIBrrei5e92IPtvdtv04za9wMLZp5nzczf4c/gb9Zaz2jChAk6dOiQNU8/IpDS09NVX1+vJ0+eSJLu3bunhoYGzZw5UxL9GCy2YBeAH3v79q3a29sVHR3tMx4dHa3Xr18HqSr8aUzTVFlZmdLT0zVmzBhJsvrvR735/PnzgNeInq+6ulp37txRU1NTpzn6EYH09OlTud1ulZWVacOGDWpsbNTKlStlt9u1aNEi+hEBVV5erg8fPig+Pl4hISFqb2/Xzp07NX/+fEl8PgYL4aqLMwzD575pmp3GgN+luLhY9+/fV0NDQ6c5ehOB8PLlS5WWlury5csKCwv7j/vRjwiEjo4OJScnq7KyUpI0YcIEPXjwQG63W4sWLbL2ox8RCCdOnNDRo0d1/PhxJSYmyuv1atWqVRo4cKAKCgqs/ejHwOK0wC4qKipKISEhnY5Stba2dvoGAvgdSkpKVFtbq+vXr2vw4MHWuMvlkiR6EwFx+/Zttba2KikpSTabTTabTTdu3ND+/ftls9msnqMfEQgxMTFKSEjwGRs9erS10BSfjwiktWvXat26dZo3b57Gjh2r/Px8rV69Wrt27ZJEPwYL4aqLCg0NVVJSkq5cueIzfuXKFaWmpgapKvwJTNNUcXGxTp48qWvXrik2NtZnPjY2Vi6Xy6c3v3//rhs3btCb8LuMjAw1NzfL6/VaW3JysvLy8uT1ejV8+HD6EQGTlpbW6acpnjx5oqFDh0ri8xGB9fXrV/Xq5fuvfEhIiLUUO/0YHJwW2IWVlZUpPz9fycnJSklJkcfj0YsXL1RYWBjs0tCDFRUV6fjx4zpz5oycTqf1jVefPn3kcDis3xiqrKxUXFyc4uLiVFlZqfDwcC1YsCDI1aOncTqd1vV+/xIREaF+/fpZ4/QjAmX16tVKTU1VZWWlcnNz1djYKI/HI4/HI0l8PiKgZs2apZ07d2rIkCFKTEzU3bt3tWfPHi1dulQS/Rg0QVypED/hwIED5tChQ83Q0FBz4sSJ1nLYwO8i6YdbVVWVtU9HR4e5detW0+VymXa73Zw6darZ3NwcvKLxR/n3pdhNk35EYJ09e9YcM2aMabfbzfj4eNPj8fjM048IlI8fP5qlpaXmkCFDzLCwMHP48OHmxo0bzba2Nmsf+jHwDNM0zWCGOwAAAADoCbjmCgAAAAD8gHAFAAAAAH5AuAIAAAAAPyBcAQAAAIAfEK4AAAAAwA8IVwAAAADgB4QrAAAAAPADwhUAAAAA+AHhCgCAX2QYhk6fPh3sMgAAQUa4AgB0a4sXL5ZhGJ22zMzMYJcGAPjD2IJdAAAAvyozM1NVVVU+Y3a7PUjVAAD+VBy5AgB0e3a7XS6Xy2eLjIyU9Pcpe263W1lZWXI4HIqNjVVNTY3P45ubmzV9+nQ5HA7169dPy5Yt0+fPn332OXLkiBITE2W32xUTE6Pi4mKf+bdv32rOnDkKDw9XXFycamtrrbn3798rLy9P/fv3l8PhUFxcXKcwCADo/ghXAIAeb/PmzcrJydG9e/e0cOFCzZ8/Xy0tLZKkr1+/KjMzU5GRkWpqalJNTY2uXr3qE57cbreKioq0bNkyNTc3q7a2ViNGjPB5jW3btik3N1f379/XzJkzlZeXp3fv3lmv//DhQ124cEEtLS1yu92KiooK3BsAAAgIwzRNM9hFAADwTy1evFhHjx5VWFiYz3h5ebk2b94swzBUWFgot9ttzU2ePFkTJ07UwYMHdejQIZWXl+vly5eKiIiQJNXV1WnWrFl69eqVoqOjNWjQIC1ZskQ7duz4YQ2GYWjTpk3avn27JOnLly9yOp2qq6tTZmamZs+eraioKB05cuQ3vQsAgK6Aa64AAN3etGnTfMKTJPXt29e6nZKS4jOXkpIir9crSWppadH48eOtYCVJaWlp6ujo0OPHj2UYhl69eqWMjIz/WsO4ceOs2xEREXI6nWptbZUkLV++XDk5Obpz545mzJih7Oxspaam/qO/FQDQdRGuAADdXkRERKfT9P4XwzAkSaZpWrd/tI/D4fip5+vdu3enx3Z0dEiSsrKy9Pz5c50/f15Xr15VRkaGioqKtHv37v+rZgBA18Y1VwCAHu/WrVud7sfHx0uSEhIS5PV69eXLF2v+5s2b6tWrl0aOHCmn06lhw4apvr7+l2ro37+/dQrjvn375PF4fun5AABdD0euAADdXltbm16/fu0zZrPZrEUjampqlJycrPT0dB07dkyNjY06fPiwJCkvL09bt25VQUGBKioq9ObNG5WUlCg/P1/R0dGSpIqKChUWFmrAgAHKysrSp0+fdPPmTZWUlPxUfVu2bFFSUpISExPV1tamc+fOafTo0X58BwAAXQHhCgDQ7V28eFExMTE+Y6NGjdKjR48k/b2SX3V1tVasWCGXy6Vjx44pISFBkhQeHq5Lly6ptLRUkyZNUnh4uHJycrRnzx7ruQoKCvTt2zft3btXa9asUVRUlObOnfvT9YWGhmr9+vV69uyZHA6HpkyZourqaj/85QCAroTVAgEAPaQw4VgAAABySURBVJphGDp16pSys7ODXQoAoIfjmisAAAAA8APCFQAAAAD4AddcAQB6NM5+BwAECkeuAAAAAMAPCFcAAAAA4AeEKwAAAADwA8IVAAAAAPgB4QoAAAAA/IBwBQAAAAB+QLgCAAAAAD8gXAEAAACAH/wFS/lhQyLiwR0AAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 1000x600 with 1 Axes>"
       ]
@@ -1921,6 +1954,18 @@
    "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.10"
   }
  },
  "nbformat": 4,
diff --git a/model_training/CNN/CNN_crossVal_HybridFusion_Test_Eval.ipynb b/model_training/CNN/CNN_crossVal_HybridFusion_Test_Eval.ipynb
new file mode 100644
index 0000000..75dd894
--- /dev/null
+++ b/model_training/CNN/CNN_crossVal_HybridFusion_Test_Eval.ipynb
@@ -0,0 +1,628 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "b65b6b7d",
+   "metadata": {},
+   "source": [
+    "Imports"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "530e70af",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2026-02-24 16:57:49.034186: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+      "2026-02-24 16:57:49.047136: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+      "2026-02-24 16:57:49.050974: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+      "2026-02-24 16:57:49.062835: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+      "2026-02-24 16:57:49.832762: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd \n",
+    "import numpy as np \n",
+    "import matplotlib.pyplot as plt \n",
+    "import seaborn as sns \n",
+    "import random \n",
+    "import joblib \n",
+    "from pathlib import Path \n",
+    "\n",
+    "from sklearn.model_selection import GroupKFold, train_test_split \n",
+    "from sklearn.preprocessing import StandardScaler \n",
+    "from sklearn.metrics import ( \n",
+    "    precision_score, recall_score,\n",
+    "    confusion_matrix, roc_curve, auc, \n",
+    "    precision_recall_curve, f1_score, \n",
+    "    balanced_accuracy_score \n",
+    ") \n",
+    "\n",
+    "import tensorflow as tf \n",
+    "from tensorflow.keras import Input, layers, models"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0d01127c",
+   "metadata": {},
+   "source": [
+    "Seed"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "67aaf56e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "SEED = 42 \n",
+    "np.random.seed(SEED) \n",
+    "tf.random.set_seed(SEED) \n",
+    "random.seed(SEED)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "844e250c",
+   "metadata": {},
+   "source": [
+    "Daten laden "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "73a34b69",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_path = Path(r\"~/data-paulusjafahrsimulator-gpu/new_datasets/50s_25Hz_dataset.parquet\") \n",
+    "data = pd.read_parquet(path=data_path)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "325179d3",
+   "metadata": {},
+   "source": [
+    "Daten vorbereiten"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "a5ad3126",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "low_all = data[ \n",
+    "    ((data[\"PHASE\"] == \"baseline\") | \n",
+    "    ((data[\"STUDY\"] == \"n-back\") & \n",
+    "    (data[\"PHASE\"] != \"baseline\") & \n",
+    "    (data[\"LEVEL\"].isin([1, 4])))) \n",
+    "].copy() \n",
+    "\n",
+    "high_all = pd.concat([ \n",
+    "    data[(data[\"STUDY\"] == \"n-back\") & \n",
+    "         (data[\"LEVEL\"].isin([2, 3, 5, 6])) & \n",
+    "         (data[\"PHASE\"].isin([\"train\", \"test\"]))], \n",
+    "    data[(data[\"STUDY\"] == \"k-drive\") & (data[\"PHASE\"] != \"baseline\")] \n",
+    "]).copy() \n",
+    "\n",
+    "low_all[\"label\"] = 0 \n",
+    "high_all[\"label\"] = 1 \n",
+    "\n",
+    "data = pd.concat([low_all, high_all], ignore_index=True).drop_duplicates()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fd843b62",
+   "metadata": {},
+   "source": [
+    "Features"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "5f10e6ca",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "au_columns = [col for col in data.columns if \"face\" in col.lower()] \n",
+    "\n",
+    "eye_columns = [ \n",
+    "    'Fix_count_short_66_150','Fix_count_medium_300_500','Fix_count_long_gt_1000', \n",
+    "    'Fix_count_100','Fix_mean_duration','Fix_median_duration', \n",
+    "    'Sac_count','Sac_mean_amp','Sac_mean_dur','Sac_median_dur', \n",
+    "    'Blink_count','Blink_mean_dur','Blink_median_dur', \n",
+    "    'Pupil_mean','Pupil_IPA' \n",
+    "] \n",
+    "\n",
+    "# NaNs entfernen \n",
+    "data = data.dropna(subset=au_columns + eye_columns + [\"label\"]) \n",
+    "\n",
+    "# Arrays \n",
+    "X_au = data[au_columns].values[..., np.newaxis] \n",
+    "X_eye = data[eye_columns].values \n",
+    "y = data[\"label\"].values \n",
+    "groups = data[\"subjectID\"].values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cabe09af",
+   "metadata": {},
+   "source": [
+    "Train/Test Split"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "52d3b7cf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Train: 6377  | Test: 1595\n"
+     ]
+    }
+   ],
+   "source": [
+    "X_au_train, X_au_test, X_eye_train, X_eye_test, y_train, y_test, groups_train, groups_test = train_test_split( \n",
+    "    X_au, X_eye, y, \n",
+    "    groups, test_size=0.2, \n",
+    "    random_state=42, \n",
+    "    stratify=y \n",
+    ") \n",
+    "\n",
+    "print(\"Train:\", len(y_train), \" | Test:\", len(y_test))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6dedded5",
+   "metadata": {},
+   "source": [
+    "Hybrid CNN-Modell"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "41cc1b30",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def build_hybrid_model(n_aus, n_eye, lr=1e-4): \n",
+    "    input_au = Input(shape=(n_aus, 1), name=\"au_input\") \n",
+    "    x = layers.Conv1D(32, 3, activation=\"relu\")(input_au) \n",
+    "    x = layers.BatchNormalization()(x) \n",
+    "    x = layers.MaxPooling1D(2)(x) \n",
+    "    x = layers.Conv1D(64, 3, activation=\"relu\")(x) \n",
+    "    x = layers.BatchNormalization()(x) \n",
+    "    x = layers.GlobalAveragePooling1D()(x) \n",
+    "\n",
+    "    input_eye = Input(shape=(n_eye,), name=\"eye_input\") \n",
+    "    e = layers.Dense(32, activation=\"relu\")(input_eye) \n",
+    "    e = layers.Dropout(0.3)(e) \n",
+    "    e = layers.Dense(16, activation=\"relu\")(e) \n",
+    "\n",
+    "    fused = layers.concatenate([x, e]) \n",
+    "    z = layers.Dense(32, activation=\"relu\")(fused) \n",
+    "    z = layers.Dropout(0.4)(z) \n",
+    "    output = layers.Dense(1, activation=\"sigmoid\")(z) \n",
+    "\n",
+    "    model = models.Model(inputs=[input_au, input_eye], outputs=output) \n",
+    "    model.compile( \n",
+    "        optimizer=tf.keras.optimizers.Adam(learning_rate=lr), \n",
+    "        loss=\"binary_crossentropy\", \n",
+    "        metrics=[\"accuracy\", tf.keras.metrics.AUC(name=\"auc\")] \n",
+    "        ) \n",
+    "        \n",
+    "    return model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cea6d0d0",
+   "metadata": {},
+   "source": [
+    "Cross Validation (nur Trainingsdaten)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "9c390b46",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "===== FOLD 1 =====\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
+      "I0000 00:00:1771948671.077495  347703 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771948671.117462  347703 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771948671.119081  347703 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771948671.125047  347703 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771948671.126507  347703 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771948671.127885  347703 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771948671.321528  347703 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "I0000 00:00:1771948671.323000  347703 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "2026-02-24 16:57:51.324225: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:47] Overriding orig_value setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\n",
+      "I0000 00:00:1771948671.324317  347703 cuda_executor.cc:1015] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+      "2026-02-24 16:57:51.325558: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 35614 MB memory:  -> device: 0, name: NVIDIA A100 80GB PCIe MIG 3g.40gb, pci bus id: 0000:1e:00.0, compute capability: 8.0\n",
+      "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
+      "I0000 00:00:1771948673.622665  347894 service.cc:146] XLA service 0x7fcbc40111e0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:\n",
+      "I0000 00:00:1771948673.622720  347894 service.cc:154]   StreamExecutor device (0): NVIDIA A100 80GB PCIe MIG 3g.40gb, Compute Capability 8.0\n",
+      "2026-02-24 16:57:53.667316: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:268] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.\n",
+      "2026-02-24 16:57:53.897373: I external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:531] Loaded cuDNN version 8907\n",
+      "I0000 00:00:1771948676.141382  347894 device_compiler.h:188] Compiled cluster using XLA!  This line is logged at most once for the lifetime of the process.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Val Loss=0.0339 | Val Acc=0.9836 | Val AUC=0.9994\n",
+      "\u001b[1m41/41\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 7ms/step \n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "===== FOLD 2 =====\n",
+      "Val Loss=0.1241 | Val Acc=0.9591 | Val AUC=0.9861\n",
+      "\u001b[1m40/40\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 7ms/step\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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SmfGnCwAAJkLFDQAwD1rlJG4AgInQKqdVDgCAmVBxAwDMg1Y5iRsAYCK0ymmVAwBgJlTcAADzoFVO4gYAmAitclrlAACYCRU3AMA8aJWTuAEAJkKrnFY5AABmQsUNADAPWuUkbgCAidAqp1UOAICZUHEDAMyDVjmJGwBgIiRuWuUAAJgJFTcAwDx8WJxG4gYAmAetclrlAACYCRU3AMA8+B43iRsAYCK0ymmVAwBwJq1atZLFYqmxjR8/XpJkGIYyMjIUExOjwMBAJSUladeuXS5zOBwOTZgwQREREQoODtaAAQNUWFjocSwkbgCAeVgs3ts8kJeXp6KiIue2bt06SdKtt94qSZo5c6ZmzZqlOXPmKC8vTzabTb1799ahQ4ecc6SmpmrlypVavny5cnNzdfjwYfXr109VVVUexULiBgCYh8XHe5sHIiMjZbPZnNvbb7+tSy65RImJiTIMQ9nZ2ZoyZYoGDRqk9u3ba9GiRTp69KiWLl0qSSotLdX8+fP1zDPPKCUlRZ06ddKSJUu0Y8cOrV+/3qNYSNwAgN8kh8OhgwcPumwOh+OM55WXl2vJkiUaNWqULBaLCgoKZLfb1adPH+cYq9WqxMREbdq0SZKUn5+viooKlzExMTFq3769c4y7SNwAAPPwYqs8KytLoaGhLltWVtYZQ1i1apV++eUXjRw5UpJkt9slSVFRUS7joqKinMfsdrsCAgLUrFmzU45xF6vKAQDm4cVV5enp6Zo4caLLPqvVesbz5s+frxtuuEExMTGuoZ103dwwjBr7TubOmJNRcQMAfpOsVquaNGnisp0pce/bt0/r16/XmDFjnPtsNpsk1aici4uLnVW4zWZTeXm5SkpKTjnGXSRuAIB5NNCq8hMWLlyo5s2b66abbnLui4uLk81mc640l45fB9+4caN69OghSerSpYv8/f1dxhQVFWnnzp3OMe6iVQ4AMI8GvAFLdXW1Fi5cqBEjRsjP73/p02KxKDU1VZmZmYqPj1d8fLwyMzMVFBSkoUOHSpJCQ0M1evRoTZo0SeHh4QoLC1NaWpo6dOiglJQUj+IgcQMA4Ib169fr22+/1ahRo2ocmzx5ssrKyjRu3DiVlJQoISFBa9euVUhIiHPM7Nmz5efnp8GDB6usrEzJycnKycmRr6+vR3FYDMMwzvrVeMGAl/IaOgSg3i0d0bWhQwDqXWNr/d1PPPCm57w2V9k7D3htrnOJihsAYB7cq5zFaQAAmAkVNwDAPKi4SdwAABPh97hplQMAYCZU3AAA86BVTuIGAJgIrXJa5QAAmAkVNwDAPGiVk7gBACZCq5xWOQAAZkLFDQAwDQsVN4kbAGAeJG5a5QAAmAoVNwDAPCi4SdwAAPOgVU6rHAAAU6HiBgCYBhU3iRsAYCIkblrlAACYChU3AMA0qLhJ3AAAMyFv0yoHAMBMqLgBAKZBq5zEDQAwERI3rXIAAEyFihsAYBpU3CRuAICJkLhplQMAYCpU3AAA86DgJnEDAMyDVjmtcgAATIWKGwBgGlTcJG4AgImQuGmVAwBgKlTcAADzoOAmcQMAzINWOa1yAABMxaOKu7CwUHPnztWmTZtkt9tlsVgUFRWlHj16aOzYsWrZsmV9xQkAABW3PEjcubm5uuGGG9SyZUv16dNHffr0kWEYKi4u1qpVq/T888/rvffe09VXX12f8QIAfsNI3B4k7oceekhjxozR7NmzT3k8NTVVeXl5XgsOAAC4cvsa986dOzV27NhTHr/33nu1c+dOrwQFAEBtLBaL1zZPff/99xo2bJjCw8MVFBSkK664Qvn5+c7jhmEoIyNDMTExCgwMVFJSknbt2uUyh8Ph0IQJExQREaHg4GANGDBAhYWFHsXhduKOjo7Wpk2bTnl88+bNio6O9ujJAQDwiMWLmwdKSkp09dVXy9/fX++9956+/PJLPfPMM2ratKlzzMyZMzVr1izNmTNHeXl5stls6t27tw4dOuQck5qaqpUrV2r58uXKzc3V4cOH1a9fP1VVVbkdi9ut8rS0NI0dO1b5+fnq3bu3oqKiZLFYZLfbtW7dOs2bN0/Z2dluPzEAAGbx1FNPqWXLllq4cKFzX6tWrZz/3zAMZWdna8qUKRo0aJAkadGiRYqKitLSpUt17733qrS0VPPnz9fixYuVkpIiSVqyZIlatmyp9evXq2/fvm7F4nbFPW7cOL3yyivaunWrbrnlFvXo0UPdu3fXLbfcoq1bt+qVV145bSsdAICz5c1WucPh0MGDB102h8NR6/OuXr1aXbt21a233qrmzZurU6dOevnll53HCwoKZLfb1adPH+c+q9WqxMREZ7c6Pz9fFRUVLmNiYmLUvn3703a0T+bR97iHDBmiLVu26OjRo/r+++/1/fff6+jRo9qyZYsGDx7syVQAAHjMm4k7KytLoaGhLltWVlatz7t3717NnTtX8fHxev/99zV27Fg98MADeuWVVyRJdrtdkhQVFeVyXlRUlPOY3W5XQECAmjVrdsox7qjTndP8/f25ng0AMLX09HRNnDjRZZ/Vaq11bHV1tbp27arMzExJUqdOnbRr1y7NnTtXd955p3PcyYveDMM440I4d8b8GndOAwCYhjcrbqvVqiZNmrhsp0rc0dHRuvzyy132XXbZZfr2228lSTabTZJqVM7FxcXOKtxms6m8vFwlJSWnHOMOEjcAAGdw9dVXa8+ePS77/v3vfys2NlaSFBcXJ5vNpnXr1jmPl5eXa+PGjerRo4ckqUuXLvL393cZU1RUpJ07dzrHuIMfGQEAmEcD3TjtoYceUo8ePZSZmanBgwfr008/1UsvvaSXXnrpeFgWi1JTU5WZman4+HjFx8crMzNTQUFBGjp0qCQpNDRUo0eP1qRJkxQeHq6wsDClpaWpQ4cOzlXm7iBxAwBMo6FuedqtWzetXLlS6enp+stf/qK4uDhlZ2frjjvucI6ZPHmyysrKNG7cOJWUlCghIUFr165VSEiIc8zs2bPl5+enwYMHq6ysTMnJycrJyZGvr6/bsVgMwzA8fQGLFy/Wiy++qIKCAm3evFmxsbHKzs5WXFycbr75Zk+nkyQNeIlbpeLCt3RE14YOAah3ja31l1wvnrDaa3N9+/wAr811Lnlccc+dO1ePP/64UlNT9eSTTzrv9tK0aVNlZ2fXOXHDu265Ilp3XtlCq3fYNW/zd5KkBxPjlNwuwmXcnh8P6+E3dzsfNw30011XtdQVF4Uq0N9H35ce0+vbirSpwHUxBXC+eP3VZXrjtWUq+uF7SVLrS9ro7nvH6+prr6sx9sm/PK5/vPGaJj2crqHDR5zrUOEF/MhIHRL3888/r5dfflkDBw7UjBkznPu7du2qtLQ0rwaHumkTGay+l0aq4OejNY7lf/uLnt1Y4HxcWe3acJnYs7WCAnw1/f2vdfBYpRLbhOnh5Es0aeWX2lvLfEBDi4qK0oTUSWrZ8mJJ0turV2nig+O19LV/6JI28c5xH/5zvXbu+EKRzZs3VKjwAhJ3HVaVFxQUqFOnTjX2W61WHTlyxCtBoe4a+floUs/WmvPxNzrsqKxxvKLa0C9llc7tsMP1/rjtohrr7V3F+nr/Ef14yKHXthXpSHmVLokIOlcvAfDIdUm9dM21iYptFafYVnEa/8BDCgoK0o4vPneOKf7xR83MfELTs/4qPz+W9sDcPE7ccXFx2r59e4397733Xo3vuOHcG3tNrLZ+94s+//5grcfbR4foleFXaO7gDhp/bSuFNnL9R2y3/bCubR2mxlZfWSRde0mY/H0t2vHDoVrnA84nVVVVev+9d1RWdlQdf3+FpOM3znjsT5M1fORolwoc5tSQvw52vvD4T8+HH35Y48eP17Fjx2QYhj799FMtW7ZMWVlZmjdvXn3ECDdde0mYWkcEadLKL2s9nv9dqf6194CKD5crKiRAd3Rtoen92umhf3zpbJnPXP9fTU65REtHdFZldbUcldXKWvsf2Q/Vfv9e4Hzw9b/36K7ht6u83KHAoCA9nT1HrS9pI0nKWfCyfP18dfsdwxs4SniFefOt13icuO+66y5VVlZq8uTJOnr0qIYOHaqLLrpIzz77rG677Ta35nA4HDVu5F5VUS5f/wBPw8H/FxEcoLu7X6zH392jiqravyiQu/eA8/9/W1Km/+w/qnlDO6rbxU21+Zvji8+GdbtIwVZf/fntr3TwWKWuatVMk1MuUfrqr7SvpOycvBbAU63i4rTs9ZU6dOigPli/VlP//KheXrBYDscxLf/7Yv391RWmrrCAX6vT18FO+Omnn1RdXa3mHi72yMjI0LRp01z2te03Ru3631PXUH7zEmKbakrfeFX9arGZr49F1YYhw5D+OH+rqmv5L/3ikA5a+9V+/eNzu2whVr10e0eNf32Hvis55hzzlxvbquigQ3Nz952Ll3JB4+tg58Z9d9+lFi1bKi7uEs16eoZ8fP53VbCqqko+Pj6Kstn09pp/NmCUF676/DpY64nvem2uvbNu9Npc59JZrdKIiIg486Ba1HZj99sX7zibUH7zvvjhoO5/fafLvgcT41RYWqYV2+21Ju0Qq68iggNUcrRCkmT1O/6P28l/ylUbkg/FCkzEMAyVl5frxv4DdOVV3V2O3X/fGN3Y72YNuPkPDRQdzgadkzok7ri4uNO+cXv37j3jHFartcaN3GmTn52yimp9e1Ir+1hllQ4dq9S3JWVq5Oej27tcpE0FB1RytELNQ6wa3q2FDh6r1Jb/3yYv/OWYfig9pvHXttKCLd/p0LFKXdWqqa5o0URPrPm6IV4WcEZznp2lq6+5TlE2m44cOaK1a95V/tZP9fzcl9W0aTM1ber6E4p+fn6KCI9Qq7jWDRQxcHY8TtypqakujysqKrRt2zatWbNGDz/8sLfigpdVG4ZiwwLVs228ggN8VXK0Qjt+OKS/fvBflVVUS5KqDEPT3vu3RiS00GN949XI30dFBx3K3lCg/O9KG/gVALU7cOBnPTZlsn7av1+NG4covm07PT/3ZV3V/eqGDg31gIL7LK9x/9rf/vY3bd26VQsXLqzT+dzyFL8FXOPGb0F9XuOOf3iN1+b6+q/Xe22uc8lrP+t5ww03aMWKFd6aDgAA1MJrtxB64403FBYW5q3pAACogVZ5HRJ3p06dXBanGYYhu92u/fv364UXXvBqcAAA/BqryuuQuAcOHOjy2MfHR5GRkUpKStKll17qrbgAAEAtPErclZWVatWqlfr27SubzVZfMQEAUCsKbg8Xp/n5+em+++6rcbtSAADOBR8fi9c2s/J4VXlCQoK2bdtWH7EAAIAz8Pga97hx4zRp0iQVFhaqS5cuCg4OdjnesWNHrwUHAMCv0Sr3IHGPGjVK2dnZGjJkiCTpgQcecB6zWCwyDEMWi0VVVVXejxIAALGqXPIgcS9atEgzZsxQQUFBfcYDAABOw+3EfeLOqLGxsfUWDAAAp0PB7eE1bloUAICGRB7yMHG3bdv2jG/agQMHziogAABwah4l7mnTpik0NLS+YgEA4LSouD1M3LfddpuaN29eX7EAAHBa5G0PbsDCXzkAADQ8j1eVAwDQUCgiPUjc1dXV9RkHAABnRN6uw73KAQBAw/H4XuUAADQUWuUkbgCAiZC3aZUDAGAqVNwAANOgVU7iBgCYCHmbVjkAAKZCxQ0AMA1a5SRuAICJkLdplQMAYCpU3AAA06BVTsUNADARi8V7mycyMjJksVhcNpvN5jxuGIYyMjIUExOjwMBAJSUladeuXS5zOBwOTZgwQREREQoODtaAAQNUWFjo8XtA4gYAwA2/+93vVFRU5Nx27NjhPDZz5kzNmjVLc+bMUV5enmw2m3r37q1Dhw45x6SmpmrlypVavny5cnNzdfjwYfXr109VVVUexUGrHABgGg3ZKvfz83Opsk8wDEPZ2dmaMmWKBg0aJElatGiRoqKitHTpUt17770qLS3V/PnztXjxYqWkpEiSlixZopYtW2r9+vXq27ev23FQcQMATKOhWuWS9PXXXysmJkZxcXG67bbbtHfvXklSQUGB7Ha7+vTp4xxrtVqVmJioTZs2SZLy8/NVUVHhMiYmJkbt27d3jnEXFTcA4DfJ4XDI4XC47LNarbJarTXGJiQk6JVXXlHbtm31448/avr06erRo4d27dolu90uSYqKinI5JyoqSvv27ZMk2e12BQQEqFmzZjXGnDjfXVTcAADTOHmB2NlsWVlZCg0NddmysrJqfd4bbrhBf/zjH9WhQwelpKTonXfekXS8Jf7r2H7NMIwztvbdGXMyEjcAwDS8mbjT09NVWlrqsqWnp7sVR3BwsDp06KCvv/7aed375Mq5uLjYWYXbbDaVl5erpKTklGPcReIGAPwmWa1WNWnSxGWrrU1eG4fDod27dys6OlpxcXGy2Wxat26d83h5ebk2btyoHj16SJK6dOkif39/lzFFRUXauXOnc4y7uMYNADCNhlpUnpaWpv79++viiy9WcXGxpk+froMHD2rEiBGyWCxKTU1VZmam4uPjFR8fr8zMTAUFBWno0KGSpNDQUI0ePVqTJk1SeHi4wsLClJaW5my9e4LEDQAwjYb6OlhhYaFuv/12/fTTT4qMjNRVV12lLVu2KDY2VpI0efJklZWVady4cSopKVFCQoLWrl2rkJAQ5xyzZ8+Wn5+fBg8erLKyMiUnJysnJ0e+vr4exWIxDMPw6qurowEv5TV0CEC9Wzqia0OHANS7xtb6S65J2Z59dep0NqR61qI+X1BxAwBMg1uVk7gBACbCj4ywqhwAAFOh4gYAmAYFN4kbAGAiPmRuWuUAAJgJFTcAwDQouEncAAATYVU5rXIAAEyFihsAYBo+FNwkbgCAedAqp1UOAICpUHEDAEyDgpvEDQAwEYvI3LTKAQAwESpuAIBpsKqcxA0AMBFWldMqBwDAVKi4AQCmQcFN4gYAmAg/60mrHAAAU6HiBgCYBgU3iRsAYCKsKqdVDgCAqVBxAwBMg4KbxA0AMBFWldMqBwDAVKi4AQCmQb1N4gYAmAirymmVAwBgKlTcAADT4Gc9SdwAABOhVU6rHAAAU6HiBgCYBgU3iRsAYCK0ymmVAwBgKlTcAADTYFU5iRsAYCK0ymmVAwBgKlTcAADToN4mcQMATISf9aRVDgCAx7KysmSxWJSamurcZxiGMjIyFBMTo8DAQCUlJWnXrl0u5zkcDk2YMEEREREKDg7WgAEDVFhY6NFzk7gBAKZhsXhvq6u8vDy99NJL6tixo8v+mTNnatasWZozZ47y8vJks9nUu3dvHTp0yDkmNTVVK1eu1PLly5Wbm6vDhw+rX79+qqqqcvv5SdwAANOwWCxe2+ri8OHDuuOOO/Tyyy+rWbNmzv2GYSg7O1tTpkzRoEGD1L59ey1atEhHjx7V0qVLJUmlpaWaP3++nnnmGaWkpKhTp05asmSJduzYofXr17sdA4kbAAA3jR8/XjfddJNSUlJc9hcUFMhut6tPnz7OfVarVYmJidq0aZMkKT8/XxUVFS5jYmJi1L59e+cYd7A4DQBgGt5cm+ZwOORwOFz2Wa1WWa3WWscvX75cn332mfLy8mocs9vtkqSoqCiX/VFRUdq3b59zTEBAgEulfmLMifPdQcUNADANH4vFa1tWVpZCQ0NdtqysrFqf97vvvtODDz6oJUuWqFGjRqeM7+QWvGEYZ2zLuzPG5T1weyQAABeQ9PR0lZaWumzp6em1js3Pz1dxcbG6dOkiPz8/+fn5aePGjXruuefk5+fnrLRPrpyLi4udx2w2m8rLy1VSUnLKMe4gcQMATMObq8qtVquaNGnisp2qTZ6cnKwdO3Zo+/btzq1r16664447tH37drVu3Vo2m03r1q1znlNeXq6NGzeqR48ekqQuXbrI39/fZUxRUZF27tzpHOMOrnEDAEyjoe5VHhISovbt27vsCw4OVnh4uHN/amqqMjMzFR8fr/j4eGVmZiooKEhDhw6VJIWGhmr06NGaNGmSwsPDFRYWprS0NHXo0KHGYrfTIXEDAOAFkydPVllZmcaNG6eSkhIlJCRo7dq1CgkJcY6ZPXu2/Pz8NHjwYJWVlSk5OVk5OTny9fV1+3kshmEY9fECPHWssqEjAOpfs273N3QIQL0r2zan3uaesHK31+Z6/g+XeW2uc4mKGwBgGvysJ4vTAAAwFSpuAIBp+FBwk7gBAOZB4qZVDgCAqVBxAwBMg8VpJG4AgInQKqdVDgCAqVBxAwBMg045iRsAYCI+ZG5a5QAAmAkVNwDANKg2SdwAABOhU84fLwAAmAoVNwDANFicRuIGAJgIeZtWOQAApkLFDQAwDW55SuIGAJgI17hplQMAYCpU3AAA06DgJnEDAEyEa9y0ygEAMBUqbgCAaVhEyU3iBgCYBq1yWuUAAJgKFTcAwDSouEncAAATsfB9MFrlAACYCRU3AMA0aJWTuAEAJkKnnFY5AACmQsUNADANfh2MxA0AMBGucdMqBwDAVKi4AQCmQaecxA0AMBEffmSEVjkAAGZCxQ0AMA1a5SRuAICJsKqcVjkAAKZC4gYAmIaPxeK1zRNz585Vx44d1aRJEzVp0kTdu3fXe++95zxuGIYyMjIUExOjwMBAJSUladeuXS5zOBwOTZgwQREREQoODtaAAQNUWFjo+Xvg8RkAADQQi8V7mydatGihGTNmaOvWrdq6dat69eqlm2++2ZmcZ86cqVmzZmnOnDnKy8uTzWZT7969dejQIeccqampWrlypZYvX67c3FwdPnxY/fr1U1VVlWfvgWEYhmfh149jlQ0dAVD/mnW7v6FDAOpd2bY59Tb3y5/s89pcdyfEntX5YWFh+utf/6pRo0YpJiZGqampeuSRRyQdr66joqL01FNP6d5771VpaakiIyO1ePFiDRkyRJL0ww8/qGXLlnr33XfVt29ft5+XihsAYBrebJU7HA4dPHjQZXM4HGeMoaqqSsuXL9eRI0fUvXt3FRQUyG63q0+fPs4xVqtViYmJ2rRpkyQpPz9fFRUVLmNiYmLUvn175xi33wOPRgMA0IC82SrPyspSaGioy5aVlXXK596xY4caN24sq9WqsWPHauXKlbr88stlt9slSVFRUS7jo6KinMfsdrsCAgLUrFmzU45xF18HAwD8JqWnp2vixIku+6xW6ynHt2vXTtu3b9cvv/yiFStWaMSIEdq4caPzuOWkC+eGYdTYdzJ3xpyMxA0AMA1vtomtVutpE/XJAgIC1KZNG0lS165dlZeXp2effdZ5Xdtutys6Oto5vri42FmF22w2lZeXq6SkxKXqLi4uVo8ePTyKm1Y5AMA0LBaL17azZRiGHA6H4uLiZLPZtG7dOuex8vJybdy40ZmUu3TpIn9/f5cxRUVF2rlzp8eJm4obAIAz+NOf/qQbbrhBLVu21KFDh7R8+XJt2LBBa9askcViUWpqqjIzMxUfH6/4+HhlZmYqKChIQ4cOlSSFhoZq9OjRmjRpksLDwxUWFqa0tDR16NBBKSkpHsVC4gYAmEZD3fH0xx9/1PDhw1VUVKTQ0FB17NhRa9asUe/evSVJkydPVllZmcaNG6eSkhIlJCRo7dq1CgkJcc4xe/Zs+fn5afDgwSorK1NycrJycnLk6+vrUSx8jxs4h/geN34L6vN73EvyPb/T2KkM69LCa3OdS1zjBgDARGiVAwBMgx8HI3EDAEyE3+OmVQ4AgKlQcQMATMMb3782OxI3AMA0aBPzHgAAYCpU3AAA06BVTuIGAJgIaZtWOQAApkLFDQAwDVrlJG4AgInQJuY9AADAVKi4AQCmQaucxA0AMBHSNq1yAABMhYobAGAadMpJ3AAAE/GhWU6rHAAAM6HiBgCYBq1yEjcAwEQstMpplQMAYCZU3AAA06BVTuIGAJgIq8q92Cr/7rvvNGrUKG9NBwAAauG1xH3gwAEtWrTIW9MBAFCDxeK9zazcbpWvXr36tMf37t171sEAAHA6Zk643uJ24h44cKAsFosMwzjlGH61BQCA+uV2qzw6OlorVqxQdXV1rdtnn31Wn3ECACCLF/9nVm4n7i5dupw2OZ+pGgcA4Gz5WLy3mZXbrfKHH35YR44cOeXxNm3a6MMPP/RKUAAAoHZuJ+5rr732tMeDg4OVmJh41gEBAHAqZm5xewu3PAUAwES4cxoAwDT48hKJGwBgIrTKaZUDAGAqVNwAANMw89e4vKVOiXvx4sV68cUXVVBQoM2bNys2NlbZ2dmKi4vTzTff7O0YUUf5W/OUs2C+dn+5U/v379fs5/6mXskpzuNHjxxR9uxn9OE/16v0l18Uc9FFGnrHcA2+bWgDRg2c3lfvTFNsTHiN/S+++pEemvGaJKldXJSmPzhQ13ZuIx8fi3b/t0jDHlmg7+wlatYkSI/dd5OSr7pULaKa6edfDuutDV9o2gtv6+DhY+f65cBDtMrrkLjnzp2rxx9/XKmpqXryySdVVVUlSWratKmys7NJ3OeRsrKjateunW7+wyBNSp1Q4/hfn8pS3qefKHPGXxVz0UXa/K9/KXP6NEU2b66evVJqmRFoeNcM+6t8f1V2Xd4mRu++OEH/WLdNkhTXIkIfLJioRas2afrcd1R6uEyXxtl0zFEhSYqODFV0ZKjSZ6/U7r12XRwdpuen3KboyFANfXh+g7wmwBMeJ+7nn39eL7/8sgYOHKgZM2Y493ft2lVpaWleDQ5n55prE3XNtaf+bv3nn29X/5sHqtuVCZKkWwYP0Ruvv6pdO3eSuHHe+qnksMvjtLva67/f7tfH+V9Lkqbd31/v5+7SlGffdI755vufnf//y/8W6fa0ec7HBYU/KWPOW1rw5J3y9fVRVVV1Pb8CnA1WlddhcVpBQYE6depUY7/Vaj3tndVw/unUubM2fvhP/fjjjzIMQ59+skX7vilQj6uvaejQALf4+/nqthu7adGbmyUdv/Xy9df8Tl9/W6zVfxuvfR9k6aNX0tQ/qeNp52kS0kgHjxwjaZuAxYubWXmcuOPi4rR9+/Ya+9977z1dfvnl3ogJ58ij6X9W60vaqE+v69T1ivYad+8Y/emxqercpWtDhwa4ZUDPjmoaEqglb30iSWoe1lghwY2Udldvrdv0pfrfN0erP/xcy58Zo2u6tKl1jrDQYKXffYPmv/Gvcxk6TCYrK0vdunVTSEiImjdvroEDB2rPnj0uYwzDUEZGhmJiYhQYGKikpCTt2rXLZYzD4dCECRMUERGh4OBgDRgwQIWFhR7F4nGr/OGHH9b48eN17Nix41Xap59q2bJlysrK0rx58848wf8P3OFwuOwzfK2yWq2ehoOzsPTvi/XFF9v17Jy5iomJUf7Wrcp8YpoiI5vrqu49Gjo84IxGDOyh9//1pYr2l0qSfHyO1yJvb9ih5/9+/LcTvvj390r4fWvdfcs1ys3/j8v5IcGNtPK5sdq9t0hPvvTuuQ0edeLTQL3yjRs3avz48erWrZsqKys1ZcoU9enTR19++aWCg4MlSTNnztSsWbOUk5Ojtm3bavr06erdu7f27NmjkJAQSVJqaqreeustLV++XOHh4Zo0aZL69eun/Px8+fr6uhWLx4n7rrvuUmVlpSZPnqyjR49q6NChuuiii/Tss8/qtttuc2uOrKwsTZs2zWXflMem6s+PZ3gaDuro2LFjei57tmY/N0fXJSZJktq2u1R79uzWooXzSdw4710c3Uy9EtrptrSXnft+Kjmsiooq7d5b5DJ2z167enRq7bKvcZBVq/82TofLHBoy8WVVVtImN4OGanGvWbPG5fHChQvVvHlz5efn67rrrpNhGMrOztaUKVM0aNAgSdKiRYsUFRWlpUuX6t5771Vpaanmz5+vxYsXKyXl+DqiJUuWqGXLllq/fr369u3rVix1ugHL3XffrX379qm4uFh2u13fffedRo8e7fb56enpKi0tddkefiS9LqGgjiorK1VZWSGfk74U6ePjq2p+nhUmMHxAdxUfOKT3Pv5fK7Kiskr5X+5T29gol7Hxsc31bVGJ83FIcCO9Pfd+lVdU6ZbU/5OjvPKcxY3zh8Ph0MGDB122k7vBp1JaerzLExYWJun4+i+73a4+ffo4x1itViUmJmrTpk2SpPz8fFVUVLiMiYmJUfv27Z1j3HFWd06LiIhQ8+bNPT7ParWqSZMmLhttcu87euSIvtq9W1/t3i1J+r6wUF/t3q2iH35Q48aN1bXblZr19F+V9+knKiz8Tm+u/IfeXr1KycmsKMf5zWKx6M6br9Lf3/6kxoKy2YvW65a+nXXXH3qodcsIjR1ynW68rr1eeu0jSccr7bdfGK+gRgEaO+3vahLcSFHhIYoKD6nxhyzOQ15cnZaVlaXQ0FCXLSsr64whGIahiRMn6pprrlH79u0lSXa7XZIUFeX6R2NUVJTzmN1uV0BAgJo1a3bKMe7wuFUeFxcny2muMezdu9fTKVFPdu3aqTF33el8/PTM4x/IATf/QU9kztBTf52lZ7NnKf2RNB0sLVV0TIzuf+Ah3Trk9oYKGXBLr4R2ujg6TItWbalxbPWHX2jCk8v18Kg+embyLfr3vmLd/vA8bdp+/N+mTpddrCs7xkmSvnwrw+Xcdjc+rm+LDtR7/Kg7b96AJT09XRMnTnTZ504Ref/99+uLL75Qbm5uzfhOyo+GYZw2Z7o75tc8TtypqakujysqKrRt2zatWbNGDz/8sKfToR51uzJBn+/ac8rjEZGReuLJM/91CZxvPtjylQI73X/K46+8uUWvvFkzqUvSx/lfn/Zc/HZYrZ4vip4wYYJWr16tjz76SC1atHDut9lsko5X1dHR0c79xcXFzircZrOpvLxcJSUlLlV3cXGxevRwf12Rx4n7wQcfrHX/3/72N23dutXT6QAAcFtD3YDFMAxNmDBBK1eu1IYNGxQXF+dyPC4uTjabTevWrXPe66S8vFwbN27UU089JUnq0qWL/P39tW7dOg0ePFiSVFRUpJ07d2rmzJlux+K1Xwe74YYbtGLFCm9NBwBADQ11A5bx48dryZIlWrp0qUJCQmS322W321VWVnY8LotFqampyszM1MqVK7Vz506NHDlSQUFBGjr0+O8/hIaGavTo0Zo0aZI++OADbdu2TcOGDVOHDh2cq8zd4bVfB3vjjTecq+sAALiQzJ07V5KUlJTksn/hwoUaOXKkJGny5MkqKyvTuHHjVFJSooSEBK1du9b5HW5Jmj17tvz8/DR48GCVlZUpOTlZOTk5bn+HW5IshuHZd386derkchHdMAzZ7Xbt379fL7zwgu655x5PpnM6xrcx8BvQrBvXVnHhK9s2p97mziso9dpc3eJCvTbXueRxxT1w4ECXxz4+PoqMjFRSUpIuvfRSb8UFAEAN/Kynh4m7srJSrVq1Ut++fZ0r6AAAwLnj0eI0Pz8/3XfffW7fWQYAAG+yWLy3mZXHq8oTEhK0bdu2+ogFAIDT4mc963CNe9y4cZo0aZIKCwvVpUsX56+inNCx4+l/9xYAANSd24l71KhRys7O1pAhQyRJDzzwgPOYxWJx3rKtqqrK+1ECACCZu1T2ErcT96JFizRjxgwVFBTUZzwAAJwSq8o9SNwnvu4dGxtbb8EAAIDT8+gatye/XgIAgLeRhjxM3G3btj1j8j5wgJ/EAwDUD/K2h4l72rRpCg015y3iAAC4EHiUuG+77TY1b968vmIBAOD0KLndT9xc3wYANDRWlXtw5zQPf0QMAADUA7cr7urq6vqMAwCAM6L5W4dbngIA0FDI23X4kREAANBwqLgBAOZByU3iBgCYB6vKaZUDAGAqVNwAANNgVTmJGwBgIuRtWuUAAJgKFTcAwDwouUncAADzYFU5rXIAAEyFihsAYBqsKidxAwBMhLxNqxwAAFOh4gYAmAclN4kbAGAerCqnVQ4AgKlQcQMATINV5SRuAICJkLdplQMAYCpU3AAA86DkJnEDAMyDVeW0ygEAMBUqbgCAabCqnMQNADAR8jatcgAA3PLRRx+pf//+iomJkcVi0apVq1yOG4ahjIwMxcTEKDAwUElJSdq1a5fLGIfDoQkTJigiIkLBwcEaMGCACgsLPYqDxA0AMA+LFzcPHTlyRL///e81Z86cWo/PnDlTs2bN0pw5c5SXlyebzabevXvr0KFDzjGpqalauXKlli9frtzcXB0+fFj9+vVTVVWV23FYDMMwPA/f+45VNnQEQP1r1u3+hg4BqHdl22pPbN6w72eH1+aKDbfW+VyLxaKVK1dq4MCBko5X2zExMUpNTdUjjzwi6Xh1HRUVpaeeekr33nuvSktLFRkZqcWLF2vIkCGSpB9++EEtW7bUu+++q759+7r13FTcAACcpYKCAtntdvXp08e5z2q1KjExUZs2bZIk5efnq6KiwmVMTEyM2rdv7xzjDhanAQBMw5uryh0OhxwO1wrearXKavW8Erfb7ZKkqKgol/1RUVHat2+fc0xAQICaNWtWY8yJ891BxQ0AMA1vXuLOyspSaGioy5aVlXV28Z30l4VhGDX2ncydMb9G4gYA/Calp6ertLTUZUtPT6/TXDabTZJqVM7FxcXOKtxms6m8vFwlJSWnHOMOEjcAwDQsFu9tVqtVTZo0cdnq0iaXpLi4ONlsNq1bt865r7y8XBs3blSPHj0kSV26dJG/v7/LmKKiIu3cudM5xh1c4wYAmEjD3YLl8OHD+s9//uN8XFBQoO3btyssLEwXX3yxUlNTlZmZqfj4eMXHxyszM1NBQUEaOnSoJCk0NFSjR4/WpEmTFB4errCwMKWlpalDhw5KSUlxOw4SNwAAbti6dat69uzpfDxx4kRJ0ogRI5STk6PJkyerrKxM48aNU0lJiRISErR27VqFhIQ4z5k9e7b8/Pw0ePBglZWVKTk5WTk5OfL19XU7Dr7HDZxDfI8bvwX1+T3u738p99pcFzUN8Npc5xIVNwDANLhXOYvTAAAwFSpuAIBp8LOeJG4AgIlYaJbTKgcAwEyouAEA5kHBTeIGAJgHeZtWOQAApkLFDQAwDVaVk7gBACbCqnJa5QAAmAoVNwDAPCi4SdwAAPMgb9MqBwDAVKi4AQCmwapyEjcAwERYVU6rHAAAU6HiBgCYBq1yKm4AAEyFxA0AgInQKgcAmAatchI3AMBEWFVOqxwAAFOh4gYAmAatchI3AMBEyNu0ygEAMBUqbgCAeVByk7gBAObBqnJa5QAAmAoVNwDANFhVTuIGAJgIeZtWOQAApkLFDQAwD0puEjcAwDxYVU6rHAAAU6HiBgCYBqvKJYthGEZDB4Fzz+FwKCsrS+np6bJarQ0dDlAv+JzjQkTi/o06ePCgQkNDVVpaqiZNmjR0OEC94HOOCxHXuAEAMBESNwAAJkLiBgDAREjcv1FWq1VTp05lwQ4uaHzOcSFicRoAACZCxQ0AgImQuAEAMBESNwAAJkLiRg0ZGRm64oorGjoMoF7xOYdZkbhNYuTIkbJYLLJYLPL391fr1q2VlpamI0eONEg83377rfr376/g4GBFRETogQceUHl5eYPEggvH+fY5f/DBB9WlSxdZrVaSPM4b/MiIiVx//fVauHChKioq9PHHH2vMmDE6cuSI5s6dW2NsRUWF/P396yWOqqoq3XTTTYqMjFRubq5+/vlnjRgxQoZh6Pnnn6+X58Rvx/nyOZckwzA0atQoffLJJ/riiy/q7XkAT1Bxm4jVapXNZlPLli01dOhQ3XHHHVq1apWk/7X9FixYoNatW8tqtcowDJWWluqee+5R8+bN1aRJE/Xq1Uuff/65y7wzZsxQVFSUQkJCNHr0aB07duy0caxdu1ZffvmllixZok6dOiklJUXPPPOMXn75ZR08eLC+Xj5+I86Xz7kkPffccxo/frxat25dHy8VqBMSt4kFBgaqoqLC+fg///mPXnvtNa1YsULbt2+XJN10002y2+169913lZ+fr86dOys5OVkHDhyQJL322muaOnWqnnzySW3dulXR0dF64YUXTvu8mzdvVvv27RUTE+Pc17dvXzkcDuXn53v/heI3raE+58D5ila5SX366adaunSpkpOTnfvKy8u1ePFiRUZGSpL++c9/aseOHSouLnbeOerpp5/WqlWr9MYbb+iee+5Rdna2Ro0apTFjxkiSpk+frvXr15+2GrHb7YqKinLZ16xZMwUEBMhut3v7peI3rCE/58D5iorbRN5++201btxYjRo1Uvfu3XXddde5XFOOjY11/mMmSfn5+Tp8+LDCw8PVuHFj51ZQUKD//ve/kqTdu3ere/fuLs9z8uPaWGr5NXvDMGrdD3jifPqcA+cjKm4T6dmzp+bOnSt/f3/FxMTUWJQTHBzs8ri6ulrR0dHasGFDjbmaNm1a5zhsNps++eQTl30lJSWqqKioUYkDnjpfPufA+YrEbSLBwcFq06aN2+M7d+4su90uPz8/tWrVqtYxl112mbZs2aI777zTuW/Lli2nnbd79+568sknVVRUpOjoaEnHF6xZrVZ16dLF7fiA2pwvn3PgfEWr/AKWkpKi7t27a+DAgXr//ff1zTffaNOmTfrzn/+srVu3Sjr+PdUFCxZowYIF+ve//62pU6dq165dp523T58+uvzyyzV8+HBt27ZNH3zwgdLS0nT33XerSZMm5+KlAU719TmXji+E2759u+x2u8rKyrR9+3Zt376dexagQVFxX8AsFoveffddTZkyRaNGjdL+/ftls9l03XXXOVvaQ4YM0X//+1898sgjOnbsmP74xz/qvvvu0/vvv3/KeX19ffXOO+9o3LhxuvrqqxUYGKihQ4fq6aefPlcvDXCqr8+5JI0ZM0YbN250Pu7UqZMkqaCg4JTVPVDf+FlPAABMhFY5AAAmQuIGAMBESNwAAJgIiRsAABMhcQMAYCIkbgAATITEDQCAiZC4AQAwERI3AAAmQuIGAMBESNwAAJgIiRsAABP5f7oquqjwSPrYAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "===== FOLD 3 =====\n",
+      "Val Loss=0.1050 | Val Acc=0.9772 | Val AUC=0.9900\n",
+      "\u001b[1m40/40\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 8ms/step \n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "===== FOLD 4 =====\n",
+      "Val Loss=0.1166 | Val Acc=0.9489 | Val AUC=0.9913\n",
+      "\u001b[1m40/40\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 7ms/step\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "===== FOLD 5 =====\n",
+      "Val Loss=0.1385 | Val Acc=0.9571 | Val AUC=0.9910\n",
+      "\u001b[1m41/41\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 6ms/step\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "gkf = GroupKFold(n_splits=5) \n",
+    "cv_histories = [] \n",
+    "cv_results = [] \n",
+    "all_conf_matrices = [] \n",
+    "\n",
+    "for fold, (tr_idx, va_idx) in enumerate(gkf.split(X_au_train, y_train, groups_train)): \n",
+    "    print(f\"\\n===== FOLD {fold+1} =====\") \n",
+    "    \n",
+    "    X_tr_au, X_va_au = X_au_train[tr_idx], X_au_train[va_idx] \n",
+    "    X_tr_eye, X_va_eye = X_eye_train[tr_idx], X_eye_train[va_idx] \n",
+    "    y_tr, y_va = y_train[tr_idx], y_train[va_idx] \n",
+    "    \n",
+    "    # Scaler pro Fold \n",
+    "    scaler_au = StandardScaler() \n",
+    "    scaler_eye = StandardScaler() \n",
+    "    \n",
+    "    X_tr_au = scaler_au.fit_transform(X_tr_au.reshape(len(X_tr_au), -1)).reshape(X_tr_au.shape) \n",
+    "    X_va_au = scaler_au.transform(X_va_au.reshape(len(X_va_au), -1)).reshape(X_va_au.shape) \n",
+    "    \n",
+    "    X_tr_eye = scaler_eye.fit_transform(X_tr_eye) \n",
+    "    X_va_eye = scaler_eye.transform(X_va_eye) \n",
+    "    \n",
+    "    # Modell \n",
+    "    model_cv = build_hybrid_model(len(au_columns), len(eye_columns)) \n",
+    "    \n",
+    "    callbacks = [ \n",
+    "        tf.keras.callbacks.EarlyStopping(monitor=\"val_loss\", patience=10, restore_best_weights=True), \n",
+    "        tf.keras.callbacks.ReduceLROnPlateau(monitor=\"val_loss\", factor=0.5, patience=5, min_lr=1e-6) \n",
+    "    ] \n",
+    "    \n",
+    "    history = model_cv.fit( \n",
+    "        [X_tr_au, X_tr_eye], y_tr, \n",
+    "        validation_data=([X_va_au, X_va_eye], y_va), \n",
+    "        epochs=100, \n",
+    "        batch_size=16, \n",
+    "        verbose=0 \n",
+    "    ) \n",
+    "    \n",
+    "    cv_histories.append(history.history) \n",
+    "    \n",
+    "    # Evaluation \n",
+    "    scores = model_cv.evaluate([X_va_au, X_va_eye], y_va, verbose=0) \n",
+    "    cv_results.append(scores) \n",
+    "    print(f\"Val Loss={scores[0]:.4f} | Val Acc={scores[1]:.4f} | Val AUC={scores[2]:.4f}\") \n",
+    "        \n",
+    "    # Konfusionsmatrix pro Fold \n",
+    "    y_pred_va = (model_cv.predict([X_va_au, X_va_eye]) > 0.5).astype(int) \n",
+    "    cm = confusion_matrix(y_va, y_pred_va) \n",
+    "    all_conf_matrices.append(cm) \n",
+    "        \n",
+    "    plt.figure(figsize=(6,5)) \n",
+    "    sns.heatmap(cm, annot=True, fmt=\"d\", cmap=\"Blues\", \n",
+    "                xticklabels=[\"Pred 0\", \"Pred 1\"], \n",
+    "                yticklabels=[\"True 0\", \"True 1\"]) \n",
+    "    plt.title(f\"Konfusionsmatrix - Fold {fold+1}\") \n",
+    "    plt.show() \n",
+    "    \n",
+    "# Aggregierte Konfusionsmatrix \n",
+    "agg_cm = sum(all_conf_matrices) \n",
+    "\n",
+    "plt.figure(figsize=(6,5)) \n",
+    "sns.heatmap(agg_cm, annot=True, fmt=\"d\", cmap=\"Purples\", \n",
+    "            xticklabels=[\"Pred 0\", \"Pred 1\"], \n",
+    "            yticklabels=[\"True 0\", \"True 1\"]) \n",
+    "plt.title(\"Aggregierte Konfusionsmatrix - alle Folds\") \n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7e564308",
+   "metadata": {},
+   "source": [
+    "Speichern des Modells"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "9afc926b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Finales Modell gespeichert.\n"
+     ]
+    }
+   ],
+   "source": [
+    "model_cv.save(\"hybrid_fusion_model_Test.keras\") \n",
+    "joblib.dump(scaler_au, \"scaler_au_Test.joblib\") \n",
+    "joblib.dump(scaler_eye, \"scaler_eye_Test.joblib\") \n",
+    "\n",
+    "print(\"Finales Modell gespeichert.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "391af5d5",
+   "metadata": {},
+   "source": [
+    "Test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "0bb8c14c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m50/50\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 8ms/step\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "F1-Score: 0.9851222104144527\n",
+      "Balanced Accuracy: 0.9809860091542237\n",
+      "Precision: 0.9809523809523809\n",
+      "Recall: 0.9893276414087513\n",
+      "AUC: 0.997147009306686\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Preprocessing Testdaten \n",
+    "X_au_test_scaled = scaler_au.transform( \n",
+    "    X_au_test.reshape(len(X_au_test), -1) \n",
+    ").reshape(X_au_test.shape) \n",
+    "\n",
+    "X_eye_test_scaled = scaler_eye.transform(X_eye_test) \n",
+    "\n",
+    "# Vorhersagen \n",
+    "y_prob_test = model_cv.predict([X_au_test_scaled, X_eye_test_scaled]).flatten() \n",
+    "y_pred_test = (y_prob_test > 0.5).astype(int) \n",
+    "\n",
+    "# Konfusionsmatrix \n",
+    "cm_test = confusion_matrix(y_test, y_pred_test) \n",
+    "\n",
+    "plt.figure(figsize=(6,5)) \n",
+    "sns.heatmap(cm_test, annot=True, fmt=\"d\", cmap=\"Greens\", \n",
+    "            xticklabels=[\"Pred 0\", \"Pred 1\"], \n",
+    "            yticklabels=[\"True 0\", \"True 1\"]) \n",
+    "plt.title(\"Konfusionsmatrix - Testdaten\") \n",
+    "plt.show() \n",
+    "\n",
+    "# ROC \n",
+    "fpr, tpr, _ = roc_curve(y_test, y_prob_test) \n",
+    "roc_auc = auc(fpr, tpr) \n",
+    "\n",
+    "plt.figure(figsize=(7,6)) \n",
+    "plt.plot(fpr, tpr, label=f\"AUC = {roc_auc:.3f}\") \n",
+    "plt.plot([0,1], [0,1], \"k--\") \n",
+    "plt.title(\"ROC - Testdaten\") \n",
+    "plt.legend() \n",
+    "plt.grid(True) \n",
+    "plt.show() \n",
+    "\n",
+    "# Precision-Recall \n",
+    "precision, recall, _ = precision_recall_curve(y_test, y_prob_test) \n",
+    "plt.figure(figsize=(7,6)) \n",
+    "plt.plot(recall, precision) \n",
+    "plt.title(\"Precision-Recall - Testdaten\") \n",
+    "plt.grid(True) \n",
+    "plt.show() \n",
+    "\n",
+    "# Metriken \n",
+    "print(\"F1-Score:\", f1_score(y_test, y_pred_test)) \n",
+    "print(\"Balanced Accuracy:\", balanced_accuracy_score(y_test, y_pred_test)) \n",
+    "print(\"Precision:\", precision_score(y_test, y_pred_test)) \n",
+    "print(\"Recall:\", recall_score(y_test, y_pred_test)) \n",
+    "print(\"AUC:\", roc_auc)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}