{ "cells": [ { "cell_type": "markdown", "id": "8dac1885", "metadata": {}, "source": [ "# Advanced PADR-Net Workflow: Transfer, Uncertainty, and Stress Testing\n", "\n", "> **Goal**: use `PADRNet` as an experiment framework, not only as a\n", "> single forecaster. We run leave-one-region-out transfer, physics-loss\n", "> ablation, threshold calibration, Monte-Carlo dropout uncertainty, and\n", "> rainfall-intensification stress tests.\n", "\n", "This notebook is the advanced companion to\n", "`14_padrnet_flood_forecasting.ipynb`.\n" ] }, { "cell_type": "code", "execution_count": 1, "id": "9f007401", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:47:25.116328Z", "iopub.status.busy": "2026-06-08T17:47:25.116328Z", "iopub.status.idle": "2026-06-08T17:47:25.141167Z", "shell.execute_reply": "2026-06-08T17:47:25.139822Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "BASE_ATTENTIVE_BACKEND = tensorflow\n", "KERAS_BACKEND = tensorflow\n" ] } ], "source": [ "import os\n", "import warnings\n", "\n", "warnings.filterwarnings(\"ignore\")\n", "os.environ.setdefault(\"BASE_ATTENTIVE_BACKEND\", \"tensorflow\")\n", "os.environ.setdefault(\"KERAS_BACKEND\", \"tensorflow\")\n", "print(\"BASE_ATTENTIVE_BACKEND =\", os.environ[\"BASE_ATTENTIVE_BACKEND\"])\n", "print(\"KERAS_BACKEND =\", os.environ[\"KERAS_BACKEND\"])\n" ] }, { "cell_type": "markdown", "id": "dc1e4a07", "metadata": {}, "source": [ "---\n", "\n", "## 1. Imports\n", "\n", "The public API remains small: `PADRNetConfig` validates the model\n", "configuration and `PADRNet` creates the backend-specific model. The\n", "advanced workflow is built around experimental splits and diagnostics.\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "f8a84b24", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:47:25.144389Z", "iopub.status.busy": "2026-06-08T17:47:25.144389Z", "iopub.status.idle": "2026-06-08T17:47:28.827363Z", "shell.execute_reply": "2026-06-08T17:47:28.826346Z" } }, "outputs": [], "source": [ "from dataclasses import dataclass\n", "\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import tensorflow as tf\n", "\n", "from base_attentive import PADRNet, PADRNetConfig\n", "from base_attentive.applications.flood import (\n", " critical_success_index,\n", " delta_mass,\n", " linear_reservoir_response,\n", " mass_balance_residual,\n", " nash_sutcliffe_efficiency,\n", " true_skill_statistic,\n", ")\n", "\n", "np.random.seed(123)\n", "tf.random.set_seed(123)\n", "tf.get_logger().setLevel(\"ERROR\")\n", "plt.rcParams.update({\"figure.dpi\": 120, \"axes.grid\": True, \"grid.alpha\": 0.25})\n" ] }, { "cell_type": "markdown", "id": "92ad5a1a", "metadata": {}, "source": [ "---\n", "\n", "## 2. Regional Synthetic Data with Transfer Shift\n", "\n", "The generator makes WAF, EAF, and SAF hydrologically different. That\n", "regional shift is what makes transfer testing meaningful.\n" ] }, { "cell_type": "code", "execution_count": 3, "id": "fe618ec2", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:47:28.828891Z", "iopub.status.busy": "2026-06-08T17:47:28.828891Z", "iopub.status.idle": "2026-06-08T17:47:29.060954Z", "shell.execute_reply": "2026-06-08T17:47:29.059964Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(540, 48, 8) (540, 3) (540, 24, 1)\n" ] } ], "source": [ "@dataclass(frozen=True)\n", "class RegionSpec:\n", " code: str\n", " name: str\n", " color: str\n", " tau: float\n", " gain: float\n", " area: float\n", " slope: float\n", " impervious: float\n", " storm_scale: float\n", " convective: float\n", "\n", "REGIONS = [\n", " RegionSpec(\"WAF\", \"West Africa\", \"#1f66b1\", 30.0, 0.020, 0.74, 0.34, 0.23, 1.18, 0.70),\n", " RegionSpec(\"EAF\", \"East Africa\", \"#f05a28\", 19.0, 0.018, 0.55, 0.55, 0.18, 1.02, 1.10),\n", " RegionSpec(\"SAF\", \"South Africa\", \"#2f8f3b\", 36.0, 0.015, 0.63, 0.30, 0.15, 0.92, 0.55),\n", "]\n", "LOOKBACK, HORIZON = 48, 24\n", "TOTAL_STEPS = LOOKBACK + HORIZON\n", "INPUT_DIM, STATIC_DIM = 8, 3\n", "FLOOD_THRESHOLD = 0.08\n", "GAIN_PROXY = 0.12\n", "\n", "\n", "def rolling_mean(v, w):\n", " return np.convolve(v, np.ones(w) / w, mode=\"same\")\n", "\n", "\n", "def make_storm(rng, spec, intensify=1.0):\n", " t = np.arange(TOTAL_STEPS)\n", " rain = rng.gamma(1.15, 0.10, TOTAL_STEPS)\n", " for _ in range(rng.integers(1, 4)):\n", " c = rng.uniform(10, LOOKBACK + 10)\n", " width = rng.uniform(2.2, 7.5)\n", " height = rng.uniform(1.1, 4.4) * spec.storm_scale * intensify\n", " rain += height * np.exp(-0.5 * ((t - c) / width) ** 2)\n", " if rng.random() < spec.convective:\n", " c = rng.uniform(LOOKBACK - 5, LOOKBACK + 8)\n", " rain += 1.5 * intensify * np.exp(-0.5 * ((t - c) / 1.8) ** 2)\n", " return np.maximum(rain, 0.0)\n", "\n", "\n", "def make_event(rng, spec, year, intensify=1.0):\n", " rain = make_storm(rng, spec, intensify)\n", " depth = linear_reservoir_response(rain, tau=spec.tau, gain=spec.gain)\n", " depth = 8.0 * depth + 0.014 * np.sin(np.linspace(0, 2 * np.pi, TOTAL_STEPS))\n", " depth += rng.normal(0.0, 0.004, TOTAL_STEPS)\n", " depth = np.maximum(depth, 0.0)\n", " fast = linear_reservoir_response(rain, tau=max(8.0, spec.tau * 0.6), gain=spec.gain * 0.8)\n", " hour = np.arange(TOTAL_STEPS) / 24.0\n", " dyn = np.column_stack([\n", " rain, rolling_mean(rain, 6), rolling_mean(rain, 18), fast,\n", " np.sin(2 * np.pi * hour), np.cos(2 * np.pi * hour),\n", " np.full(TOTAL_STEPS, (year - 2001) / 24.0), np.gradient(rain),\n", " ])\n", " return {\n", " \"region\": spec.code,\n", " \"year\": year,\n", " \"x\": dyn[:LOOKBACK].astype(\"float32\"),\n", " \"static\": np.array([spec.area, spec.slope, spec.impervious], dtype=\"float32\"),\n", " \"y\": depth[LOOKBACK:].astype(\"float32\")[:, None],\n", " \"p\": rain[LOOKBACK:].astype(\"float32\")[:, None],\n", " }\n", "\n", "\n", "def make_dataset(n=540, seed=33, intensify=1.0):\n", " rng = np.random.default_rng(seed)\n", " out = []\n", " for _ in range(n):\n", " spec = REGIONS[int(rng.integers(0, len(REGIONS)))]\n", " out.append(make_event(rng, spec, int(rng.integers(2001, 2025)), intensify))\n", " return out\n", "\n", "\n", "def arrays(events):\n", " return {\n", " \"X\": np.stack([e[\"x\"] for e in events]).astype(\"float32\"),\n", " \"S\": np.stack([e[\"static\"] for e in events]).astype(\"float32\"),\n", " \"Y\": np.stack([e[\"y\"] for e in events]).astype(\"float32\"),\n", " \"P\": np.stack([e[\"p\"] for e in events]).astype(\"float32\"),\n", " \"region\": np.array([e[\"region\"] for e in events]),\n", " \"year\": np.array([e[\"year\"] for e in events]),\n", " }\n", "\n", "data = arrays(make_dataset())\n", "print(data[\"X\"].shape, data[\"S\"].shape, data[\"Y\"].shape)\n" ] }, { "cell_type": "code", "execution_count": 4, "id": "34219a4b", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:47:29.063025Z", "iopub.status.busy": "2026-06-08T17:47:29.063025Z", "iopub.status.idle": "2026-06-08T17:47:29.201342Z", "shell.execute_reply": "2026-06-08T17:47:29.201342Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "peaks = data[\"Y\"].max(axis=(1, 2))\n", "fig, ax = plt.subplots(figsize=(8.2, 3.5))\n", "for i, spec in enumerate(REGIONS):\n", " vals = peaks[data[\"region\"] == spec.code]\n", " parts = ax.violinplot(vals, positions=[i], widths=0.65, showmeans=True)\n", " for body in parts[\"bodies\"]:\n", " body.set_facecolor(spec.color); body.set_alpha(0.35)\n", " ax.scatter(np.full(vals.size, i), vals, s=8, color=spec.color, alpha=0.28)\n", "ax.axhline(FLOOD_THRESHOLD, color=\"#8b1e1e\", ls=\"--\", lw=1.2)\n", "ax.set_xticks(range(3), [r.code for r in REGIONS])\n", "ax.set_ylabel(\"peak depth (m)\")\n", "ax.set_title(\"Regional peak-depth distribution\")\n", "fig.tight_layout(); plt.show()\n" ] }, { "cell_type": "markdown", "id": "769c53e1", "metadata": {}, "source": [ "---\n", "\n", "## 3. Reusable Experiment Helpers\n", "\n", "These helpers keep the workflow compact. The model returns a dictionary,\n", "so the training loop explicitly uses the `depth` output and combines MSE\n", "with hydrological residual, mass-bias, and smoothness penalties.\n" ] }, { "cell_type": "code", "execution_count": 5, "id": "bef93739", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:47:29.203729Z", "iopub.status.busy": "2026-06-08T17:47:29.203729Z", "iopub.status.idle": "2026-06-08T17:47:29.216990Z", "shell.execute_reply": "2026-06-08T17:47:29.216990Z" } }, "outputs": [], "source": [ "def make_config(lambda_physics=0.25, lambda_mass=0.05, dropout=0.08):\n", " return PADRNetConfig(\n", " input_dim=INPUT_DIM, static_dim=STATIC_DIM, hidden_dim=48,\n", " num_heads=4, num_layers=2, forecast_horizon=HORIZON,\n", " dropout=dropout, lambda_physics=lambda_physics,\n", " lambda_mass=lambda_mass, lambda_smooth=0.01,\n", " flood_threshold=FLOOD_THRESHOLD, reservoir_tau=24.0,\n", " )\n", "\n", "\n", "def ds(a, idx, batch=48, shuffle=False):\n", " out = tf.data.Dataset.from_tensor_slices((a[\"X\"][idx], a[\"S\"][idx], a[\"Y\"][idx], a[\"P\"][idx]))\n", " if shuffle:\n", " out = out.shuffle(len(idx), seed=123, reshuffle_each_iteration=True)\n", " return out.batch(batch).prefetch(tf.data.AUTOTUNE)\n", "\n", "\n", "def optimizer():\n", " try:\n", " return tf.keras.optimizers.Adam(3e-3)\n", " except (ImportError, ModuleNotFoundError):\n", " from tensorflow.python.keras.optimizer_v2.adam import Adam\n", " return Adam(3e-3)\n", "\n", "\n", "def loss_terms(y, pred, rain, cfg):\n", " h = tf.squeeze(pred, -1); y = tf.squeeze(y, -1); p = tf.squeeze(rain, -1)\n", " mse = tf.reduce_mean(tf.square(y - h))\n", " dh = h[:, 1:] - h[:, :-1]\n", " residual = dh - (GAIN_PROXY * p[:, 1:] - h[:, :-1] / cfg.reservoir_tau)\n", " physics = tf.reduce_mean(tf.square(residual))\n", " mass = tf.reduce_mean(tf.abs(tf.reduce_sum(h, 1) - tf.reduce_sum(y, 1)) / (tf.reduce_sum(y, 1) + 1e-4))\n", " smooth = tf.reduce_mean(tf.square(dh))\n", " total = mse + cfg.lambda_physics * physics + cfg.lambda_mass * mass + cfg.lambda_smooth * smooth\n", " return total, {\"mse\": mse, \"physics\": physics, \"mass\": mass, \"smooth\": smooth}\n", "\n", "\n", "def train_model(a, train_idx, val_idx, cfg, epochs=12, verbose=False):\n", " model = PADRNet(cfg, backend=\"tensorflow\")\n", " _ = model(tf.zeros((1, LOOKBACK, INPUT_DIM)), tf.zeros((1, STATIC_DIM)))\n", " opt = optimizer()\n", " train_ds, val_ds = ds(a, train_idx, shuffle=True), ds(a, val_idx)\n", " hist = {\"train\": [], \"val\": [], \"mse\": [], \"physics\": [], \"mass\": []}\n", "\n", " @tf.function\n", " def train_step(xb, sb, yb, pb):\n", " with tf.GradientTape() as tape:\n", " out = model(xb, sb, training=True)\n", " loss, parts = loss_terms(yb, out[\"depth\"], pb, cfg)\n", " opt.apply_gradients(zip(tape.gradient(loss, model.trainable_variables), model.trainable_variables))\n", " return loss, parts\n", "\n", " @tf.function\n", " def eval_step(xb, sb, yb, pb):\n", " out = model(xb, sb, training=False)\n", " return loss_terms(yb, out[\"depth\"], pb, cfg)\n", "\n", " def mean_epoch(data_ds, train=False):\n", " losses, parts = [], {\"mse\": [], \"physics\": [], \"mass\": []}\n", " for xb, sb, yb, pb in data_ds:\n", " loss, detail = train_step(xb, sb, yb, pb) if train else eval_step(xb, sb, yb, pb)\n", " losses.append(float(loss.numpy()))\n", " for k in parts: parts[k].append(float(detail[k].numpy()))\n", " return float(np.mean(losses)), {k: float(np.mean(v)) for k, v in parts.items()}\n", "\n", " for epoch in range(1, epochs + 1):\n", " tr, _ = mean_epoch(train_ds, train=True)\n", " va, detail = mean_epoch(val_ds)\n", " hist[\"train\"].append(tr); hist[\"val\"].append(va)\n", " for k in [\"mse\", \"physics\", \"mass\"]: hist[k].append(detail[k])\n", " if verbose and (epoch == 1 or epoch == epochs or epoch % 5 == 0):\n", " print(f\"epoch {epoch:02d} train={tr:.4f} val={va:.4f}\")\n", " return model, hist\n", "\n", "\n", "def predict(model, a, idx, training=False):\n", " out = model(tf.convert_to_tensor(a[\"X\"][idx]), tf.convert_to_tensor(a[\"S\"][idx]), training=training)\n", " return out[\"depth\"].numpy(), out[\"exceedance_probability\"].numpy(), out[\"features\"].numpy()\n", "\n", "\n", "def score(y, pred, threshold=FLOOD_THRESHOLD):\n", " yt, yp = y.reshape(-1), pred.reshape(-1)\n", " return {\n", " \"NSE\": nash_sutcliffe_efficiency(yt, yp),\n", " \"CSI\": critical_success_index(yt, yp, threshold=threshold),\n", " \"TSS\": true_skill_statistic(yt, yp, threshold=threshold),\n", " \"DeltaM\": delta_mass(yt, yp),\n", " \"RMSE\": float(np.sqrt(np.mean((yt - yp) ** 2))),\n", " }\n" ] }, { "cell_type": "markdown", "id": "fd495887", "metadata": {}, "source": [ "---\n", "\n", "## 4. Baseline Temporal Split\n", "\n", "This baseline is the reference for the harder transfer and ablation\n", "experiments.\n" ] }, { "cell_type": "code", "execution_count": 6, "id": "ff54d76d", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:47:29.219625Z", "iopub.status.busy": "2026-06-08T17:47:29.219625Z", "iopub.status.idle": "2026-06-08T17:47:36.457163Z", "shell.execute_reply": "2026-06-08T17:47:36.457163Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "epoch 01 train=0.4231 val=0.1593\n", "epoch 05 train=0.0568 val=0.0496\n", "epoch 10 train=0.0407 val=0.0301\n", "epoch 15 train=0.0333 val=0.0259\n", "epoch 16 train=0.0305 val=0.0293\n" ] }, { "data": { "text/plain": [ "{'NSE': 0.5295109002287013,\n", " 'CSI': 0.7997227997227997,\n", " 'TSS': 0.6785502958579881,\n", " 'DeltaM': -16.995160313730974,\n", " 'RMSE': 0.06130300089716911}" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "years = data[\"year\"]\n", "train_idx = np.where(years <= 2018)[0]\n", "val_idx = np.where((years >= 2019) & (years <= 2020))[0]\n", "test_idx = np.where(years >= 2021)[0]\n", "\n", "base_cfg = make_config()\n", "base_model, base_hist = train_model(data, train_idx, val_idx, base_cfg, epochs=16, verbose=True)\n", "base_pred, base_prob, base_feat = predict(base_model, data, test_idx)\n", "base_score = score(data[\"Y\"][test_idx], base_pred)\n", "base_score\n" ] }, { "cell_type": "code", "execution_count": 7, "id": "82e99e62", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:47:36.459470Z", "iopub.status.busy": "2026-06-08T17:47:36.459470Z", "iopub.status.idle": "2026-06-08T17:47:36.643605Z", "shell.execute_reply": "2026-06-08T17:47:36.643605Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, axes = plt.subplots(1, 2, figsize=(10.5, 3.5))\n", "e = np.arange(1, len(base_hist[\"train\"]) + 1)\n", "axes[0].plot(e, base_hist[\"train\"], label=\"train\", lw=2)\n", "axes[0].plot(e, base_hist[\"val\"], label=\"validation\", lw=2)\n", "axes[0].set_title(\"Baseline training\")\n", "axes[0].set_xlabel(\"epoch\"); axes[0].set_ylabel(\"loss\"); axes[0].legend()\n", "axes[1].plot(e, base_hist[\"mse\"], label=\"MSE\", lw=2)\n", "axes[1].plot(e, base_hist[\"physics\"], label=\"physics\", lw=2)\n", "axes[1].plot(e, base_hist[\"mass\"], label=\"mass\", lw=2)\n", "axes[1].set_title(\"Validation components\"); axes[1].legend()\n", "fig.tight_layout(); plt.show()\n" ] }, { "cell_type": "markdown", "id": "62acc8de", "metadata": {}, "source": [ "---\n", "\n", "## 5. Leave-One-Region-Out Transfer\n", "\n", "Train on two regions and test on the held-out target region. This is a\n", "stronger diagnostic than a random split because it tests regional\n", "transfer.\n" ] }, { "cell_type": "code", "execution_count": 8, "id": "30aaa72c", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:47:36.646133Z", "iopub.status.busy": "2026-06-08T17:47:36.646133Z", "iopub.status.idle": "2026-06-08T17:47:53.750029Z", "shell.execute_reply": "2026-06-08T17:47:53.750029Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "hold out WAF: NSE=-0.254 CSI=0.701 TSS=0.459 DeltaM=-41.6%\n", "hold out EAF: NSE=-0.564 CSI=0.632 TSS=0.012 DeltaM=-49.1%\n", "hold out SAF: NSE=0.215 CSI=0.636 TSS=0.309 DeltaM=0.4%\n" ] } ], "source": [ "transfer = []\n", "for target in [r.code for r in REGIONS]:\n", " source = data[\"region\"] != target\n", " target_mask = data[\"region\"] == target\n", " tr = np.where(source & (years <= 2019))[0]\n", " va = np.where(source & (years == 2020))[0]\n", " te = np.where(target_mask & (years >= 2021))[0]\n", " m, _ = train_model(data, tr, va, make_config(), epochs=10)\n", " p, _, _ = predict(m, data, te)\n", " row = score(data[\"Y\"][te], p); row.update({\"target\": target, \"n\": len(te)})\n", " transfer.append(row)\n", "\n", "for r in transfer:\n", " print(f\"hold out {r['target']}: NSE={r['NSE']:.3f} CSI={r['CSI']:.3f} TSS={r['TSS']:.3f} DeltaM={r['DeltaM']:.1f}%\")\n" ] }, { "cell_type": "code", "execution_count": 9, "id": "00680fb5", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:47:53.755451Z", "iopub.status.busy": "2026-06-08T17:47:53.754441Z", "iopub.status.idle": "2026-06-08T17:47:53.906641Z", "shell.execute_reply": "2026-06-08T17:47:53.905463Z" } }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "labels = [r[\"target\"] for r in transfer]\n", "x = np.arange(len(labels))\n", "fig, axes = plt.subplots(1, 2, figsize=(10.5, 3.5))\n", "axes[0].bar(x - 0.18, [r[\"NSE\"] for r in transfer], 0.36, label=\"NSE\")\n", "axes[0].bar(x + 0.18, [r[\"CSI\"] for r in transfer], 0.36, label=\"CSI\")\n", "axes[0].set_xticks(x, labels); axes[0].set_ylim(-0.2, 1.05)\n", "axes[0].set_title(\"Leave-one-region-out skill\"); axes[0].legend()\n", "axes[1].bar(labels, [r[\"DeltaM\"] for r in transfer], color=\"#7c6bb0\")\n", "axes[1].axhline(0, color=\"#222\", lw=1); axes[1].set_ylabel(\"DeltaM (%)\")\n", "axes[1].set_title(\"Transfer mass bias\")\n", "fig.tight_layout(); plt.show()\n" ] }, { "cell_type": "markdown", "id": "82abe0be", "metadata": {}, "source": [ "---\n", "\n", "## 6. Physics-Loss Ablation\n", "\n", "A reviewer may ask whether the physics term helps. We compare the\n", "physics-aware model against the same architecture with physics and mass\n", "terms set to zero.\n" ] }, { "cell_type": "code", "execution_count": 10, "id": "542d0f82", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:47:53.908776Z", "iopub.status.busy": "2026-06-08T17:47:53.908776Z", "iopub.status.idle": "2026-06-08T17:48:06.910303Z", "shell.execute_reply": "2026-06-08T17:48:06.910303Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "PADR-Net NSE=0.217 CSI=0.651 DeltaM=-25.5% residual=0.1755\n", "No physics NSE=0.475 CSI=0.747 DeltaM=0.9% residual=0.1758\n" ] } ], "source": [ "ablation = []\n", "for name, cfg in [(\"PADR-Net\", make_config(0.25, 0.05)), (\"No physics\", make_config(0.0, 0.0))]:\n", " m, _ = train_model(data, train_idx, val_idx, cfg, epochs=12)\n", " p, _, _ = predict(m, data, test_idx)\n", " row = score(data[\"Y\"][test_idx], p)\n", " resid = mass_balance_residual(data[\"P\"][test_idx, :, 0], p[:, :, 0], tau=cfg.reservoir_tau, gain=GAIN_PROXY)\n", " row.update({\"model\": name, \"ResidualRMSE\": float(np.sqrt(np.mean(resid**2)))})\n", " ablation.append(row)\n", "\n", "for r in ablation:\n", " print(f\"{r['model']:10s} NSE={r['NSE']:.3f} CSI={r['CSI']:.3f} DeltaM={r['DeltaM']:.1f}% residual={r['ResidualRMSE']:.4f}\")\n" ] }, { "cell_type": "code", "execution_count": 11, "id": "f36432e7", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:48:06.913669Z", "iopub.status.busy": "2026-06-08T17:48:06.913669Z", "iopub.status.idle": "2026-06-08T17:48:07.111135Z", "shell.execute_reply": "2026-06-08T17:48:07.111135Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "labels = [r[\"model\"] for r in ablation]\n", "fig, axes = plt.subplots(1, 3, figsize=(12, 3.4))\n", "for ax, key, title in zip(axes, [\"NSE\", \"DeltaM\", \"ResidualRMSE\"], [\"Depth skill\", \"Mass bias\", \"Physics residual\"]):\n", " ax.bar(labels, [r[key] for r in ablation], color=[\"#2c7fb8\", \"#999999\"])\n", " ax.set_title(title); ax.set_ylabel(key)\n", " if key == \"DeltaM\": ax.axhline(0, color=\"#222\", lw=1)\n", "fig.tight_layout(); plt.show()\n" ] }, { "cell_type": "markdown", "id": "13e32a14", "metadata": {}, "source": [ "---\n", "\n", "## 7. Threshold Calibration\n", "\n", "Warning performance depends on the flood threshold. We scan thresholds\n", "and compare CSI/TSS.\n" ] }, { "cell_type": "code", "execution_count": 12, "id": "5d6dd7ba", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:48:07.113594Z", "iopub.status.busy": "2026-06-08T17:48:07.113594Z", "iopub.status.idle": "2026-06-08T17:48:07.219023Z", "shell.execute_reply": "2026-06-08T17:48:07.219023Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "best CSI threshold: 0.03\n", "best TSS threshold: 0.088\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "thresholds = np.linspace(0.03, 0.18, 32)\n", "csi = [critical_success_index(data[\"Y\"][test_idx], base_pred, threshold=t) for t in thresholds]\n", "tss = [true_skill_statistic(data[\"Y\"][test_idx], base_pred, threshold=t) for t in thresholds]\n", "print(\"best CSI threshold:\", round(float(thresholds[int(np.argmax(csi))]), 3))\n", "print(\"best TSS threshold:\", round(float(thresholds[int(np.argmax(tss))]), 3))\n", "fig, ax = plt.subplots(figsize=(7.5, 3.7))\n", "ax.plot(thresholds, csi, lw=2, label=\"CSI\")\n", "ax.plot(thresholds, tss, lw=2, label=\"TSS\")\n", "ax.axvline(FLOOD_THRESHOLD, color=\"#8b1e1e\", ls=\"--\", lw=1.2, label=\"configured\")\n", "ax.set_xlabel(\"flood threshold (m)\"); ax.set_ylabel(\"skill\")\n", "ax.set_title(\"Threshold calibration curve\"); ax.legend()\n", "fig.tight_layout(); plt.show()\n" ] }, { "cell_type": "markdown", "id": "47346c34", "metadata": {}, "source": [ "---\n", "\n", "## 8. Monte-Carlo Dropout Uncertainty\n", "\n", "Calling PADR-Net with `training=True` at inference activates dropout and\n", "creates a lightweight epistemic uncertainty diagnostic.\n" ] }, { "cell_type": "code", "execution_count": 13, "id": "9386f938", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:48:07.221314Z", "iopub.status.busy": "2026-06-08T17:48:07.221314Z", "iopub.status.idle": "2026-06-08T17:48:08.747802Z", "shell.execute_reply": "2026-06-08T17:48:08.747802Z" } }, "outputs": [ { "data": { "image/png": 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ll1+2yvJPRER2oqLXqiMiouoHd63z/iCFrfN+t9zcXPHzzz8XO3fuLPr6+ooymUx0c3MTW7ZsKc6cOVO8evVqidqWnJwsjh8/XvTx8RGVSqXYvHlzcdWqVWJMTMx913m/n+PHj4sDBw4UfXx8RLlcLtapU0ecMmWKmJSUZFPXvJb3lStXxAULFogNGzYUFQqF6O/vL77yyitidnZ2qc8hiqJ49uxZsXfv3qKLi4vo7OwsdurUSTxw4ECRa5bn5eWJU6ZMEWvXri1KpdJC1yEvSknPdb+1yc3rj8fExNhsO3LkiDh48GDR19dXlMvlYq1atcSePXuKGzdutKn7999/i2PHjhUDAwNFBwcH0dPTUwwLCxMnTZok7t+/36pucX7Hu3btEtu1ayc6OzuLAEQA4rVr10RRNK3D/tlnn4mNGzcWlUqlWKNGDXHUqFFifHy85fdtriuKD17n/e66ZkVdn8X9ven1etHHx0cEIJ49e/a+r5WIiCqGIIqi+KgfGBAREVHhxo0bhzVr1uDatWsIDg6u6OZQNXH16lWEhoYiPDy8TPMBEBFR2eGcdyIiIqJqbsGCBRBFES+99FJFN4WIiIrAOe9ERERE1VBCQgJ++OEHXLp0CatWrULz5s0RGRlZ0c0iIqIiMHgnIiIiqoauXr2KWbNmwcnJCd27d8fSpUshkXBQJhGRveKcdyIiIiIiIiI7x8erRERERERERHaOwTsRERERERGRnWPwTkRERERERGTnGLwTERERERER2Tlmmy+mrKwsHDx4EHXq1IFCoajo5hAREREREVEloNFokJiYiE6dOsHDw+Ohj8PgvZgOHjyIgQMHVnQziIiIiIiIqBLasmULBgwY8ND7M3gvpjp16gAw/cBDQ0MBAHq9Hrm5uXB1dYVMxh8lVX68pqmq4TVNVQ2vaapqeE1TVVPYNX358mUMHDjQElM+LP6FFJN5qHxoaCjCwsIAmH4xWVlZ8PDw4M2GqgRe01TV8JqmqobXNFU1vKapqrnfNV3a6ddMWEdERERERERk5xi8ExEREREREdk5Bu9EREREREREds6ug3eNRoMZM2bA398fjo6OaNu2Lfbu3fvA/WbPng1BEGw+lErlI2g1ERERERERUdmy66wQ48aNw6ZNm/Dqq6+ifv36WL16Nfr06YOYmBi0b9/+gfsvXboULi4ulu+lUml5NpeIiIiIqFoQRRH5+fnIycmBRqOBKIoPdRyj0QidToesrCxIJHbdr0hkRRAEKBQKuLm5wdnZGYIglPs57TZ4P378OH788UfMnz8fr7/+OgBgzJgxaNKkCaZPn44jR4488BgRERHw8fEp76YSEREREVUboigiJSUFGRkZAAC5XP7QgbcgCJDL5Y8k8CEqSwaDAdnZ2cjOzoaXlxf8/PzK/Tq22+B906ZNkEqlmDRpkqVMqVRiwoQJePPNN5GYmPjAdfJEUUROTg5cXV15QyAiIiIiKgP5+fnIyMiAk5MTatWqBQcHh4c+liiK0Ov1kMlkfL9OlY5Wq0VycjIyMjLg7OxsNeq7PNjt2JTTp0+jQYMGcHNzsypv06YNACA2NvaBx6hXrx7c3d3h6uqKUaNG4fbt2+XRVCIiIiKiaiMnJwcASh24E1V2Dg4OqFWrFoD//i7Kk932vCcnJ1t+EHczl928ebPIfT09PfHSSy/hySefhEKhwKFDh/D111/j+PHjOHnypM0DgXulpKQgNTXVquzy5csAAL1eD71eb/naYDBYvieq7HhNU1XDa5qqGl7TZA9UKhVkMhnkcvlDz3U3M+9f2uMQVRS5XA6ZTAaVSmWJFe+9T5fVPdtug3eVSgWFQmFTbs4Yr1Kpitz3lVdesfp+yJAhaNOmDZ599lksWbIEM2fOvO+5lyxZgvfff7/Qbbm5ucjKygJgmueQl5cHgMnwqGrgNU1VDa9pqmp4TZM90Gq1kMvlZRaQGAyGMjkOUUURBAFarRZZWVmF3qdzc3PL5Dx2G7w7OjpCo9HYlKvVasv2khg5ciSmTZuGffv2PTB4f/HFFxEZGWlVdvnyZQwcOBCurq7w8PAA8N8TFHd3d8hkdvujJDtkzseQnp4OZ2fnR5Lgojh4TVNVw2uaqhpe02QPsrKyIAhCmVyD5h53qVRqF++FiB6GOfGih4dHofdpV1fXMjmP3d71a9WqhaSkJJvy5ORkAIC/v3+Jj1mnTh1LVsz78fPzg5+fX6HbZDKZ1Y1KKpXalFH1pVarkZqaavlIS0sr8mutVmvZz8XFBfXr10doaChCQkIQGhqK0NBQ1K5d+5Evm8JrmqoaXtNU1fCapopmfm9SlsG2IAgM3qnSMl+/5vvyvffpsrpf2+1dv0WLFoiJiUFOTo7VHPVjx45ZtpeEKIqIj4/H448/XpbNpGpAr9cjIyOj0CD83u/NQ2RKKi8vD6dPn8bp06etyh0dHVGvXj1LMB8SEoL69esjMDCQb9qIiIiIqEKsXr0a48ePx7Vr1xAcHFzRzSlX48aNw4EDBxAfH1/RTbHf4D0iIgILFizA8uXLLeu8azQarFq1Cm3btrUsE5eQkICCggI0atTIsm9qaip8fX2tjrd06VKkpqaiV69ej+5FkN0SRRHZ2dlWwXdRveQZGRkVlkRFpVIhLi4OcXFxVuVyuRzBwcFWvfX169dHcHBwobkiiIiIiB6FxCwVtIYSvG8SRegNBsikUqAMe94dpALqeJRsmu3dLl26hHfeeQeHDx9GRkYGAgMDMXLkSLz++utwcnKyqnvkyBFMnz4dp06dgpubG4YOHYo5c+ZYLRuWlJSESZMm4dChQwgICMC8efPQr18/q+NER0djypQpuHTpEtzd3R/YxtmzZ+P999+HIAi4fv26zTLaOTk5qFGjBtRqNf7v//4PX331lc32L774AtHR0bhy5QoMBgNCQkLwzDPP4JVXXnmokc7F8e+//2LDhg0YN25clQ/8y5rdBu9t27ZFZGQkZs2ahZSUFISGhmLNmjWIj4/HihUrLPXGjBmDgwcPWgVXQUFBGDZsGJo2bQqlUonDhw/jxx9/RIsWLTB58uSKeDlUzkRRRG5uLtLT05GRkYHMzExkZGRYfZjLUlNTkZ6ebjVsvby4uLjA19cXvr6+8PHxsXxt/t7b2xtZWVm4fPkyLl26hCtXruDSpUvIzs6+73F1Oh0uXbqES5cuWZVLJBIEBgZaeurNgX1ISAicnZ3L86USERERQWsQcTmtADJJMQNxUYTRaDQNxS+j4F1vFBHq4/TgikVITExEmzZt4O7ujpdeegleXl44evQo3nvvPfz111/YunWrpW5sbCy6du2Kxo0b4/PPP8eNGzewYMECXLp0Cbt27bLUGzt2LJKSkjBv3jz88ccfiIyMxPnz5y3Bq1qtxuuvv46PPvqoWIH73RQKBdavX4/p06dblUdHRxe5z9WrV9GtWzckJCQgMjISkyZNgoODA/7++2+sWLECmzdvxsWLF4vcf/To0Rg+fPhDdRr9+++/eP/999G5c2cG7yVkt8E7AKxduxbvvPMOoqKikJmZiWbNmmHHjh3o2LHjffd79tlnceTIEfz8889Qq9UICgrC9OnT8dZbb9k8KSP7pNPpbALwwgJyc3lmZuYjWzbHwcHhvgH53V+bV0d4kA4dOli+FkUR6enpuHz5ss3HvUsY3stoNCI+Ph7x8fHYt2+f1bbatWtbeujvnltf0n8QRERERPcjkwio5VbMoE4UYTAYTFm5yyh4T86xTXpdElFRUcjKysLhw4cRFhYGAJg0aRKMRiPWrl2LzMxMeHp6AgDefPNNeHp64sCBA5apvsHBwZg4cSL27NmDHj16QKVS4bfffsOBAwfQsWNHTJkyBUeOHMHu3bstHYsLFiyAu7s7nn/++RK3t0+fPoUG7z/88AOeeeYZ/Pzzz1bler0egwcPxu3bt3HgwAG0b9/eavvHH3+MefPm3fecUqnU7la8yM/Pr/KdVXYdvCuVSsyfPx/z588vss6BAwdsyr799ttybBWVlCiKyM/Pv2/wfW9ZWS2nUFyCIMDb2/uBAbmvry9cXV3LNaGKIAjw8fGBj48P2rVrZ7UtOzvbEsibe+mvXLlSaHLHeyUlJSEpKQm///67Vbmvr6+ll75u3bqoWbMmHn/88SKTNhIRERFVZTk5OQCAGjVqWJXXqlULEokEDg4Olnp79+7Fa6+9ZpWja8yYMXjttdewYcMG9OjRA2q1GqIoWgJ+QRDg4eGBgoICAKb3aHPnzsUvv/zyUImKR44ciYiICJw/f94ylfjWrVv47bffsGHDBpvg/eeff8aZM2fw8ccf2wTuAODm5oaPP/74vucsbM57cHAwmjRpgpkzZ+J///sf/v77b/j7+2P27NkYM2aM1X4A0KVLF8vxYmJi0LlzZwDArl27MGfOHJw6dQoSiQQdO3bEp59+anmQApjmoW/atAlnzpzByy+/jEOHDqFr164ICAjA6tWrkZKSYtNpO2LECMTExCApKQlSqRRbt27F8uXLcfr0aaSnpyMgIADjxo3Dm2++aXcPJszsOninysloNOLYsWOIjo7Gn3/+aZNZ/VFRKpXw8vKCl5cXPD094e3tDU9PT6uA3PzZ09OzUiSAc3d3R6tWrdCqVSur8vz8fFy5cgVXrlyx6qlPSEiA0Wi87zHNc/uPHj1qVe7l5YX69evbfHh5eZX56yIiIiKyF507d8a8efMwYcIEvP/++/D29saRI0ewdOlSTJ061dK7+88//0Cv16N169ZW+zs4OKBFixaWRMSenp4ICQnBnDlzMGfOHBw5cgSxsbH48ssvAQDTp09H7969Hzi6uCgdO3ZEQEAAfvjhB3zwwQcAgJ9++gkuLi545plnbOpv27YNgGnoe1m7fPkyIiIiMGHCBIwdOxYrV67EuHHj0KpVK4SFhaFjx46YOnUqFi9ejDfffBONGzcGAMvnqKgojB07Fj179sS8efNQUFCApUuXon379jh9+rTVMHu9Xo+ePXuiffv2WLBgAZycnBAcHIyvv/4aO3futFr6u6CgANu3b8e4ceMsgfnq1avh4uKC//3vf3BxccFvv/2Gd999Fzk5OfftPK5I9h+tUKURHx+P6OhobNmypVg9wSXl4eEBT09Pm4Dc/PW9ZY6OD5+kpLJxdnZGs2bN0KxZM6tyjUaD+Ph4XLp0yaq3Pj4+Hjqd7r7HzMjIwLFjxywrPJiZg/oGDRpYBfXmp8lERERElVmvXr3w4YcfYs6cOZZAFwDeeustfPTRR5bvzUtY16pVy+YYtWrVwqFDhyzfL1++HBEREfjxxx8BAK+++irCw8Nx5MgRbN68GefOnXvo9gqCgOHDh2P9+vWW4H3dunUYPHhwoXPSz507B3d3d5sEd2XhwoUL+P333y1TQocOHYo6depg1apVWLBgAerVq4cOHTpg8eLF6N69u6W3HTCtvjR16lQ8//zzWL58uaV87NixaNiwIebMmWNVrtFoEBkZiU8++cRSJooiateujZ9++skqeN+5cyfy8/MxbNgwS9kPP/xgFS9MmTIFU6ZMwZIlS/DRRx/ZZRJoBu9UKrm5udi5cyeio6Px119/FXs/uVxuFYSbv7774+5yDw+PStEzbm8UCgUaNmyIhg0bWpXrdDokJiZaht3fPRRfrVbf95hFBfXe3t6WQN4c2IeGhjKoJyIiokonODgYHTt2xJAhQ+Dt7Y2dO3dizpw5qFmzJl566SUAplWBABQa5CmVSst2AHj66aeRkJCAuLg4+Pv7o06dOjAajZg6dSqmTZuGoKAgLF26FIsWLYIoinjttdcwZcqUYrd35MiRWLBgAU6cOAFPT0+cOHECc+bMKbRuTk4OXF1dS/LjKLbHHnvMKpeTr68vGjZsiKtXrz5w37179yIrKwsjRoxAWlqapVwqlaJt27aIiYmx2eeFF16w+l4QBERGRmLZsmXIy8uzZPz/6aefULt2batpAncH7rm5udBoNOjQoQOWLVuG8+fPo3nz5sV/4Y8IoyEqMYPBgMOHDyM6Ohp79+6FRlN4UhAvLy/07dsXYWFhNgG5i4tLuc4bp/uTy+WoV68e6tWrZ1Wu1Wpx7tw53L59G1evXrVktC9OUJ+eno709HT8+eefVuU+Pj6FDr/38PAo65dFREREVGo//vgjJk2ahIsXLyIgIAAAMHjwYBiNRsyYMQMjRoyAt7e3Jfgr7L2wWq22GQXq4uKCtm3bWr5ftWoVbt26hZkzZ2Lfvn1444038P3330MQBIwcORINGza0mhd+P48//jgaNWqEH374AR4eHqhZsyaefvrpQuu6ubkVK5h+GIGBgTZlnp6eyMzMfOC+5lWU7tfuu8lkMsvv527Dhg3DwoULsW3bNowcORJ5eXn45ZdfMHnyZKv4Iy4uDm+//TZ+++03S54Dswet/FRRGLxTsV26dMkyLD4lJaXQOnK5HF26dMHgwYPRqVMnS0IPqhwkEglq166NsLAw9OjRw1JuMBhw48YNSzBvHoZ/+fLlIh/emKWlpSEtLc1mTr2vr68lkA8NDbX01jP7PREREVWkJUuW4PHHH7cJDPv374/Vq1fj9OnT6Natm2W4vHn4/N2Sk5Pvu056Tk4O3nrrLSxYsADOzs5Yv349IiIiMHDgQABAREQE1q1bV+zgHTD1vi9duhSurq4YNmxYkcnvGjVqhNOnTyMxMbHMh84Xlejt7mW9i2LO0xQVFYWaNWvabL93FK5CoSj0NbZr1w7BwcHYsGEDRo4cie3bt0OlUlkNmc/KykKnTp3g5uaGDz74ACEhIVAqlTh16hRmzJjxwJxRFYXBO91XZmYmtm/fjujoaPzzzz9F1mvatCkGDx6Mvn37MqFZFSSVShEUFISgoCB069bNUm4wGCzD7+8N6h+UpNCcKO/IkSNW5X5+fpaA/u7gnj31RERE9Cjcvn270Gl/5nxB5uWJmzRpAplMhpMnT2Lo0KGWelqtFrGxsVZl9/rggw9Qt25dPPvsswCAmzdv4vHHH7ds9/f3R2xsbInaPXLkSLz77rtITk5GVFRUkfX69euH9evX4/vvv8esWbNKdI6yUNTo25CQEACm94J3v998GEOHDsWiRYuQk5ODn376CcHBwVarOB04cADp6emIjo62ShR47dq1Up23vDF4Jxs6nQ4HDx7Ezz//jJiYmCITm/n5+WHAgAEYPHgwGjRo8IhbSfZAKpUiODgYwcHB6N69u6XcYDAgISHBJqi/cuXKA4P6lJQUpKSk4I8//rAq9/b2RkhIiM2HedkWIiIiorLQoEED7NmzBxcvXrR6j7t+/XpIJBJLgmB3d3d069YN33//Pd555x3LPPKoqCjk5eVZJUy728WLF/HVV1/h999/twSyNWrUwPnz5y11zp07V2jv8/2EhIRg4cKFUKlUaNOmTZH1IiIi8Mknn+Djjz9G586d8eSTT1ptz83Nxdy5cx+4XNzDMmfrz8rKsirv2bMn3NzcMGfOHHTp0gVyudxqe2pqKnx9fYt1jmHDhuHTTz/FmjVr8Ouvv+KVV16x2m4eIXD3iACtVoslS5aU9OU8UgzeCYDpwv33338RHR2Nbdu2ISMjo9B6CoUC3bt3x+DBgxEeHs4kclQoqVSKunXrom7dulbD7/V6PRITE3Hx4kWroP7q1asPDOrNc+qPHz9uVe7o6Ih69erZBPVBQUF2mSWUiIiI7Nsbb7yBXbt2oUOHDnjppZfg7e2NHTt2YNeuXXj++eethsN//PHHeOqpp9CpUydMmjQJN27cwGeffYYePXqgV69ehR7/tddew7Bhw6wC7IiICAwYMABvvvkmAGD79u3YsWNHidt+b5BaGLlcjujoaHTr1g0dO3bE0KFDER4eDrlcjri4OPzwww/w9PQst+C9RYsWkEqlmDdvHrKzs6FQKPD000/Dz88PS5cuxejRo9GyZUsMHz4cvr6+SEhIwM6dOxEeHo6vvvqqWOdo2bIlQkND8dZbb0Gj0VgNmQeAp556Cp6enhg7diymTp0KQRAQFRVVrOH9FYmRVzWXmpqKrVu3Ijo6GhcuXCiyXqtWrTB48GD06dPHJlkEUXHJZDJLUN+zZ09LuV6vt/TUmwP7y5cv49q1aw8M6lUqFeLi4hAXF2dVLpVKUadOHYSGhloF96GhoeWWYZWIiIgAvVFEcs79c+JYiCKMRqNpFF0ZJTPWG0sXgHXs2BFHjhzB7NmzsWTJEqSnp6Nu3br4+OOPMX36dKu6LVu2xL59+zBjxgy89tprcHV1xYQJE6yWL7vbL7/8gt9//x0XL160Ku/bty8+/vhjfPnllxBFEZ988gl69+5dqtdxP6GhoYiNjcUXX3yBzZs3Y8uWLTAajQgNDcXzzz+PqVOnltu5a9asiW+++QaffPIJJkyYAIPBgJiYGPj5+WHkyJHw9/fH3LlzMX/+fGg0GtSuXRsdOnTA+PHjS3SeYcOG4eOPP0ZoaChatmxptc38QGbatGl4++234enpiVGjRqFr165W71HtjSDa++MFOxEXF4cmTZrg7NmzCAsLA2AKOLKysirdMmYajQb79+9HdHQ0fv/9dxgMhkLr+fv7Y9CgQRg0aBDq1q37iFtJFcHermnzknZXrlyx+cjLy3vo4/r5+aFevXqWwN78uWbNmlwFoYqxt2uaqLR4TZM9MGcqv3fVGgBIzFJBayhBeCGK0BsMkEmlZRa8A4CDVEAdD8cHVyQqA3f/TRR2ny4slnwYvOtXE6IoIjY2FtHR0dixY4fNcghmTk5O6NWrFwYPHoy2bdtyLjFVqLuXtLt7Tr0oikhJSbEMub87qL99+/YDj2ueV3/vsnYuLi6W890d2AcGBtrMuyIiIiJbJQ2YRVGEXq+HTCbjA3SiB2DwXsUlJydjy5YtiI6Ovu96ju3atcPgwYPRq1cvSxIJInslCAJq1KiBGjVqIDw83Gpbbm4url69agnszZ+vX79e5CgTs7y8PPz999/4+++/rcplMhmCgoIsw+47d+6Mli1b8k0GERERET0yDN6rIJVKhd27dyM6OhpHjhwpMvFCUFAQBg8ejEGDBqF27dqPuJVE5cPV1RXNmzdH8+bNrcq1Wi2uX79eaGBfUFBw32Pq9XpLz/6ePXuwZMkSBAYGon///hgwYEChwwaJiIiIiMoSg/cqwmg04uTJk4iOjsauXbuKnA/s4uKCZ555BkOGDGHPIVUrDg4OlnXj705EIooikpOTC51Xn5aWVuTxEhIS8NVXX+Grr75Cs2bNMGDAAPTt2xc+Pj6P4uUQERERUTXD4L2KeOONN7Bly5ZCt0kkErRv3x6DBw9G9+7doVQqH23jiOyYIAjw9/eHv78/OnToYLUtOzvbJqA/efKkTc4I81D7OXPmoH379hg4cCC6desGJyenR/lSiIiIiKgKY/BeRYSHh9sE7/Xr18fgwYMxYMAA1KhRo2IaRlSJubu7o2XLllbLi2g0Ghw4cABbt25FTEyM1VJ2BoMBBw8exMGDB+Hk5IQePXpg4MCBePLJJ5kVmoiIiIhKhe8mq4iePXvivffeg0KhQN++fTF48GA0bdqUw+KJyphCoUDPnj3Rs2dPZGdnY9euXdi6dSuOHz9uVa+goABbtmzBli1b4Ovri379+mHAgAEICwvj3yURERERlRiD9yrC2dkZP/zwAxo2bAgHB4eKbg5RteDu7o7hw4dj+PDhSEpKwrZt27BlyxZcvnzZql5qaipWrlyJlStXIjQ0FAMGDED//v0REBBQQS0nIiIiosqGi3hXIU2bNmXgTlRBateujRdeeAG//vortm3bhgkTJsDX19em3uXLl/HZZ5+hU6dOGD58ONavX4/s7OwKaDERERERVSYM3omIypAgCAgLC8Obb76JP/74A2vWrMGgQYMKTV534sQJvP3222jXrh1eeOEF7N69GxqNpgJaTURERET2jsPmiYjKiVQqRfv27dG+fXt88MEH2LdvH7Zu3YpDhw7BYDBY6mm1WuzZswd79uyBm5sbevfujYEDB6J169aQSPiMlYiIiIgYvBMRPRJOTk7o378/+vfvj7S0NOzcuRNbt27FmTNnrOrl5OTgp59+wk8//QR/f38MGDAAAwYMQP369Suo5URERERkD9ilQ0T0iPn4+GDs2LGIjo7Gvn378PLLLyMwMNCm3s2bN7F06VL06tUL/fv3x4oVK5CSklIBLSYiIqo+Vq9eDUEQLB9KpRINGjTASy+9hNu3b9vU/+WXXyAIAvz9/WE0Ggs9ZnBwsOV4EokEHh4eaNq0KSZNmoRjx44Vus/dbRAEAW5ubujUqRN27txZrNcRHx9v2ffnn3+22T579mwIgoC0tLRiHe9uR44cwezZs5GVlVXifenhMXgnIqpAdevWxauvvorffvsNGzduxKhRo+Dh4WFTLy4uDnPmzEF4eLgl8M/Ly3v0DSYiIqomPvjgA0RFReGrr77CU089haVLl+LJJ59EQUGBVb1169YhODgYycnJ+O2334o8XosWLRAVFYW1a9fik08+QZcuXbB9+3a0a9cO//vf/wrdp3v37pZ9pk+fjsuXL6Nfv37YvXt3iV+LKIol2ud+jhw5gvfff5/B+yPGYfNERHZAEAS0bNkSLVu2xFtvvYVDhw5hy5Yt2LdvH7RaraWe0WjE4cOHcfjwYbzzzjvo3r07RowYgbZt21Zg64mIiKqe3r17o3Xr1gCA559/Ht7e3vj888+xdetWjBgxAgCQn5+PrVu34pNPPsGqVauwbt06dOvWrdDj1a5dG6NGjbIqmzdvHkaOHIkvvvgC9evXxwsvvGC1vUGDBlb7DBkyBI899hgWLVqEnj17Fut1tGjRArGxsdi8eTMGDx5c7NdP9oc970REdsbBwQFdu3bFl19+iePHj2PevHl48sknIQiCVT21Wo3t27dj5MiRGDNmDGJjYyumwURERNXA008/DQC4du2apWzz5s1QqVSIjIzE8OHDER0dDbVaXexjOjo6IioqCl5eXvj4448f2DveuHFj+Pj44MqVK8U+x/Dhw9GgQYNi974fO3YMvXr1gru7O5ycnNCpUyf88ccflu2zZ8/GG2+8AcA0gtA8ND8+Pr7IY3bu3BlNmjTB33//jU6dOsHJyQmhoaHYtGkTAODgwYNo27YtHB0d0bBhQ+zbt8/mGElJSXjuuedQo0YNKBQKhIWFYeXKlVZ1tFot3n33XbRq1Qru7u5wdnZGhw4dEBMTY1XPPKVgwYIFWL58OUJCQqBQKPDEE0/gxIkTD/wZVRQG70REdszV1RURERH4/vvvcejQIcyYMQMNGza0qffHH39gyJAhmDRpEs6fP18BLSUiIqrazAGzt7e3pWzdunXo0qULatasieHDhyM3Nxfbt28v0XFdXFwwaNAgJCUl4d9//71v3ezsbGRmZsLT07PYx5dKpXj77bdx5swZbN68+b51f/vtN3Ts2BE5OTl47733MGfOHGRlZeHpp5/G8ePHAQCDBw+2jDz44osvEBUVhaioKPj6+t732JmZmejbty/atm2LTz/9FAqFAsOHD8dPP/2E4cOHo0+fPpg7dy7y8/MRERGB3Nxcy763b99Gu3btsG/fPrz00ktYtGgRQkNDMWHCBCxcuNBSLycnB9999x06d+6MefPmYfbs2UhNTUXPnj0L7eT44YcfMH/+fEyePBkfffQR4uPjMXjwYOh0umL+dB8tDpsnIqokatWqhUmTJlkC9C1btmDDhg3Izs621Nm/fz/279+Pvn374tVXX0XdunUrsMVERFSdPP/1MVxPLXhwRSsiRBEwDS4THlS5RIJ8nfDd/z38tLLs7GykpaVBrVbjjz/+wAcffABHR0f07dsXAJCSkoJ9+/Zh6dKlAIDAwEA8+eSTWLduHSIjI0t0riZNmgAwPSAICwuzlKvVaqSlpUEURSQkJODtt9+GwWBAREREiY4/cuRIfPjhh/jggw8waNAgm9F8ACCKIqZMmYIuXbpg165dljqTJ09GWFgY3n77bezZswfNmjVDy5YtsX79egwcOBDBwcHFasPNmzfxww8/WAL/7t27o1GjRhg5ciSOHDlimQLYuHFj9OzZEz///DPGjRsHAHjrrbdgMBjwzz//WB6eTJkyBSNGjMDs2bMxefJkODo6wtPTE/Hx8XBwcLCcd+LEiWjUqBG+/PJLrFixwqpNCQkJuHTpkuVhSMOGDTFgwADs3r3b8nu2JwzeiYgqoUaNGmHmzJl48cUX8d1332H16tXIz8+3bN+xYwd27dqFwYMH4+WXX0bt2rUrsLVERFQdXE8twKXk3AdXrCTunbseFBSEdevWWf6n/vjjj5BIJBgyZIilzogRIzBt2rQS9467uLgAgFVvMwCsWLHCKuCUy+WYPn16kQnuimLufR87diy2bNmCQYMG2dSJjY3FpUuX8PbbbyM9Pd1qW9euXREVFQWj0QiJ5OEGb7u4uGD48OGW7xs2bAgPDw/Url3bKneP+eurV68CMD1U+PnnnzF06FCIomiVHb9nz5748ccfcerUKYSHh0MqlUIqlQIw5QnKysqC0WhE69atcerUKZs2DRs2zOr31KFDB6tz2xsG70RElZibmxv+97//YezYsVi2bBmioqIsCe4MBgM2btyILVu2YPjw4XjxxRfh5+dXwS0mIiKqHL7++ms0aNAAMpkMNWrUQMOGDa0C1++//x5t2rRBenq6Jdh9/PHHodVqsXHjRkyaNKnY5zKvIOPq6mpVPmDAALz00kvQarU4ceIE5syZg4KCAqt2pKamwmAwWL53cXGxPAy427PPPmvpfR84cKDN9kuXLgEAxo4dW2Q7s7OzS/RQ4m4BAQE2Pf7u7u6oU6eOTRlgGmYPmF5fVlYWli9fjuXLlxd67LuX0l2zZg0+++wznD9/3mr4e2GjEe9dqtf82szntjcM3omIqgBvb2+8+eabeO655/D1119jw4YN0Ov1AACdToeoqChs3LgRY8aMwaRJkx76Hy8REVFRgnydHmKv8h02Xxpt2rSxZJu/16VLlyyJzerXr2+zfd26dSUK3s+ePQsACA0NtSoPCAiwjADo06cPfHx88NJLL6FLly6WzPFPPPEErl+/btnnvffew+zZs23OYe59HzduHLZu3Wqz3bxG/fz589GiRYtC21nYQ4HiMveIF7fcnFzP3K5Ro0YV+WChWbNmAEwPVMaNG4eBAwfijTfegJ+fH6RSKT755JNCk/w96Nz2hsE7EVEVUrNmTXz44YeYOHEiFi9ejK1bt1r+6anVaixfvhw//PADJkyYgPHjx9s84SciInpYDzO/XBRF6PV6yGSyQudh26t169ZBLpcjKirKJgA8fPgwFi9ejISEBJue3cLk5eVh8+bNqFOnDho3bnzfupMnT8YXX3yBt99+2zJ3fd26dVCpVJY69erVK3L/UaNG4aOPPsL777+P/v37W20LCQkBYBrVV9Ryd2aP8nfl6+sLV1dXGAyGB7Zr06ZNqFevHqKjo63a+N5775V3Mx8JZpsnIqqCAgMDsWDBAuzatQu9e/e22paXl4dFixahS5cuWL58udU/fCIiInqwdevWoUOHDhg2bBgiIiKsPszLqK1fv/6Bx1GpVBg9ejQyMjLw1ltvPTAolslkmDZtGs6dO2fpPQ8PD0e3bt0sH/cL3s2977Gxsdi2bZvVtlatWiEkJAQLFiywDOO/W2pqquVrZ2dnAEBWVtYDX2NpSaVSDBkyBD///LNlhEJR7TI/SLm75/zYsWM4evRoubfzUWDwTkRUhYWGhuKrr77Ctm3b0LlzZ6ttmZmZmDdvHrp06WI1V56IiIiKduzYMVy+fNmm59qsdu3aaNmyJdatW2dVnpSUhO+//x7ff/89vvnmG0ydOhX16tXDli1bMG3aNEyePLlY5x83bhx8fHwwb968h2r/s88+i5CQEJul0yQSCb777jskJiYiLCwMs2fPxrfffovZs2ejU6dOeO655yx1W7VqBcCUBT4qKgo//vijVeLcsjZ37lzUqlULbdu2xauvvorly5dj7ty5GDp0qNUSun379sXVq1cxaNAgLF++HLNmzUKvXr3w2GOPlVvbHiUG70RE1UBYWBhWrFiBDRs2WGV0BUxPrGfPno1u3bph06ZNlrnyREREZMsclPfr16/IOv369cM///yDv//+21IWGxuL0aNHY8yYMZgxYwZ+++039OvXD8eOHcOCBQuKfX5HR0e89NJL+PPPP3HgwIESt18mk+Htt98udFvnzp1x9OhRtG7dGl999RVefvllrF69GjVr1sRrr71mqffEE0/gww8/xJkzZzBu3DiMGDHCqge8rNWoUQPHjx/H+PHjER0dbVnrPSMjw+ohxrhx4zBnzhycOXMGU6dOxe7du/H9998XmbugshFEe52Nb2fi4uLQpEkTnD171rL2ol6vR1ZWFjw8PCCTMX0AVX68pqsHURRx5MgRfPbZZzhz5ozN9nr16uGVV15Bnz59Hno5GHvBa5qqGl7TZA/My2jdb3h2cVXWOe9Ed7v7b6Kw+3RhseTDqNzvyoiIqMQEQUB4eDh+/vlnLFu2DI0aNbLafvXqVbzyyivo378/9u/fb7cZV4mIiIiqEwbvRETVlCAI6NatG7Zv346FCxciODjYavu5c+cwadIkREZG4o8//qiYRhIRERERAAbvRETVnkQiQb9+/bB7927MnTsX/v7+VttPnz6NMWPG4Nlnn8WpU6cqqJVERERE1RuDdyIiAmBKYBMZGYl9+/bhvffeg6+vr9X2P//8E5GRkXj++efx77//VlAriYiIiKonBu9ERGRFoVBgzJgxiImJwfTp0+Hh4WG1PSYmBv369cPLL7+MK1euVEwjiYiIiKoZBu9ERFQoR0dHTJ48GQcOHMDUqVPh4uJitf2XX35Br1698MYbbyAxMbGCWklERERUPTB4JyKi+3J1dcUrr7yCmJgYTJw4EUql0rLNaDQiOjoa3bt3x7vvvovbt29XYEuJiIiIqi4G70REVCxeXl6YOXMmYmJiMHr0aMjlcss2nU6HdevWoUuXLvjoo49w48aNCmwpERERUdXD4J2IiErEz88Ps2fPxr59+xAREQGJ5L9/JRqNBqtWrUKXLl0wZcoUHD16lOvEExEREZUBBu9ERPRQAgICMG/ePOzevRvPPPOM1Taj0Yi9e/di1KhR6NOnD3788UeoVKoKaikRERFR5cfgnYiISqVevXpYvHgxduzYgWeeeQZSqdRq+8WLF/HWW28hPDwcc+fORVJSUgW1lIiIiKjyYvBORERlonHjxli8eDEOHjyIF198EV5eXlbbs7Oz8e2336Jz58544YUXcOzYMQ6pJyIiIiomBu9ERFSmatWqhWnTpuHw4cOYN28ewsLCrLYbjUbs2bMHI0eORN++fbFhwwao1eoKai0REVHZi4qKQqNGjSCXy+Hh4VHRzaEqgsE7ERGVC4VCgYiICGzduhU//fQT+vTpYzOk/vz585g1axbCw8Mxf/583Lx5s4JaS0REVDbOnz+PcePGISQkBN9++y2WL19e0U2iKkJW0Q0gIqKqTRAEtG7dGq1bt8bNmzfxww8/4Mcff0RmZqalTlZWFr755ht8++236NGjB8aMGYMnnngCgiBUYMuJiIhK7sCBAzAajVi0aBFCQ0MrujlUhbDnnYiIHhl/f3+8/vrrOHz4MObOnYvGjRtbbTcYDNi1axdGjBiB/v37Y9OmTdBoNBXUWiIiIpP8/Pxi101JSQGAMh0uX5LzU9XF4J2IiB45pVKJyMhIbN++HevXr0evXr2s1osHgH///RczZsxA+/btsWDBAiQnJ1dQa4mIqDqZPXs2BEHAv//+i5EjR8LT0xPt27cHAHz//fdo1aoVHB0d4eXlheHDhyMxMdGyb3BwMN577z0AgK+vLwRBwOzZsy3bd+3ahQ4dOsDZ2Rmurq545plnEBcXZ3X+cePGwcXFBVeuXEGfPn3g6uqKZ599FoApb8zChQsRFhYGpVKJGjVqYPLkyVaj2czt6Nu3Lw4fPow2bdpAqVSiXr16WLt2rc3rzcrKwmuvvYbg4GAoFAoEBARgzJgxSEtLs9TRaDR47733EBoaCoVCgTp16mD69Ol8wP6IMXgnIqIKIwgC2rRpg6+//hoHDx7E5MmTbXoqMjIysHTpUnTq1Akvv/wyTp48ySz1RERU7iIjI1FQUIA5c+Zg4sSJ+PjjjzFmzBjUr18fn3/+OV599VXs378fHTt2RFZWFgBg4cKFGDRoEABg6dKliIqKwuDBgwGYktg988wzcHFxwbx58/DOO+/g33//Rfv27REfH291br1ej549e8LPzw8LFizAkCFDAACTJ0/GG2+8gfDwcCxatAjjx4/HunXr0LNnT+h0OqtjXL58GREREejevTs+++wzeHp6Yty4cVYPC/Ly8tChQwd8+eWX6NGjBxYtWoQpU6bg/PnzuHHjBgDTA4P+/ftjwYIF6NevH7788ksMHDgQX3zxBYYNG1YeP3oqAue8ExGRXfD398f06dPx8ssvY9u2bVizZg0uXLhg2W4wGPDLL7/gl19+QVhYGMaOHYu+fftCoVBUYKuJiMhMo9Hg+vXrJdpHFEUYDAZIpdJyyXMSFBT00P8nmjdvjh9++AEAcP36dYSEhOCjjz7Cm2++aakzePBgPP7441iyZAnefPNNDBw4ELGxsdi8eTMiIiLg4+MDwBQkT506Fc8//7xVAruxY8eiYcOGmDNnjlW5RqNBZGQkPvnkE0vZ4cOH8d1332HdunUYOXKkpbxLly7o1asXNm7caFV+4cIF/P777+jQoQMAYOjQoahTpw5WrVqFBQsWAADmz5+Ps2fPIjo62vLQAQDefvtty4PyH374Afv27cPBgwctIxAAoEmTJpgyZQqOHDmCp5566qF+xlQyDN6JiMiuODo6YtiwYRg6dCiOHTuGNWvWYN++fTAajZY6cXFxmD59OubOnYsRI0Zg5MiRqFmzZgW2moiIrl+/jt69e1d0M6zs2rULDRo0eKh9p0yZYvk6OjoaRqMRQ4cOtRpOXrNmTdSvXx8xMTFWQf299u7di6ysLIwYMcJqf6lUirZt2yImJsZmnxdeeMHq+40bN8Ld3R3du3e3OkarVq3g4uKCmJgYq+D9scceswTugGkYf8OGDXH16lVL2c8//4zmzZtbBe5m5ocpGzduROPGjdGoUSOr8z799NMAgJiYGAbvjwiDdyIiskuCIKBdu3Zo164dbty4ge+//x4//fQTcnJyLHUyMjLw9ddfY9myZejVqxfGjh2Lxx9/nFnqiYio1OrWrWv5+tKlSxBFEfXr1y+0rlwuv++xLl26BOC/gPdebm5uVt/LZDIEBATYHCM7Oxt+fn6FHsOcKM8sMDDQpo6np6fV/PgrV65YhuTfr+3nzp2Dr69vsc5L5YfBOxER2b2AgADMnDkTU6dOxdatW7FmzRrLGyHANDdwx44d2LFjB5o2bYqxY8cWuq48ERFRcTk6Olq+NhqNEAQBu3btKvR/i4uLy32PZR49FhUVVehIMZnMOixTKBQ2iVyNRiP8/Pywbt26Qs9xb3Bd1P/AkuaNMRqNaNq0KT7//PNCt9epU6dEx6OHx+CdiIgqDScnJ4wYMQLDhw/H0aNHsWbNGuzfv9/qjcg///yD119/HZ988gmGDx+Obt26wd3dvQJbTURUPQQFBWHXrl0l2udRzHkvCyEhIRBFEXXr1n2oYfghISEAAD8/P3Tr1u2h27Bv3z6Eh4dbPVgojZCQEJw9e/aBdc6cOYOuXbtyZFsFY/BORESVjiAIeOqpp/DUU08hMTERUVFR2LBhA3Jzcy110tPT8fXXX+Prr7+Gk5MTgoKCEBwcbPPh7e3NNyNERGVAoVCUOLAVRRF6vR4ymcyu78WDBw/GrFmz8P777+P777+3aqsoisjIyIC3t3eR+/fs2RNubm6YM2cOunTpYjPMPjU1tchh6WZDhw7FkiVL8OGHH2LOnDlW2/R6PfLy8kq8tvyQIUPwwQcfYPPmzTbz3kVRhCAIGDp0KH755Rd8++23mDRpklUdlUoFo9EIZ2fnEp2XHg6DdyIiqtTq1KmDN998E6+++iq2bNmCNWvW4PLly1Z1CgoKcO7cOZw7d85mfxcXlyIDe09PT7t+M0lERI+GOdP8rFmzEB8fj4EDB8LV1RXXrl3D5s2bMWnSJLz++utF7u/m5oalS5di9OjRaNmyJYYPHw5fX18kJCRg586dCA8Px1dffXXfNnTq1AmTJ0/GJ598gtjYWPTo0QNyuRyXLl3Cxo0bsWjRIkRERJTodb3xxhvYtGkTIiMj8dxzz6FVq1bIyMjAtm3b8M0336B58+YYPXo0NmzYgClTpiAmJgbh4eEwGAw4f/48NmzYgN27d6N169YlOi89HLsO3jUaDd59911ERUUhMzMTzZo1w0cffYTu3buX6Djdu3fHvn378H//938P/KMgIqLKycnJCSNHjsSIESNw5MgRrFmzBr/99tsD5/bl5eUhLi7Oat1bMzc3tyID+5L2bhARUeU2c+ZMNGjQAF988QXef/99AKYHyD169ED//v0fuP/IkSPh7++PuXPnYv78+dBoNKhduzY6dOiA8ePHF6sN33zzDVq1aoVly5bhzTffhEwmQ3BwMEaNGoXw8PASvyYXFxccOnQI7733HjZv3ow1a9bAz88PXbt2tSTMk0gk2LJlC7744gusXbsWmzdvhpOTE+rVq4dXXnnlobP5U8kJYkkzFjxCI0aMwKZNm/Dqq6+ifv36WL16NU6cOIGYmBirNQbvJzo6GmPGjEF+fn6pgve4uDg0adIEZ8+eRVhYGADT8JSsrCx4eHjYJJkgqox4TVNVk5ycjL/++gvp6elISEhAfHw84uPjcePGDej1+lId28PDwyqYNwf5devWhauraxm9AiJrvE+TPTAvNVavXr1SH6uyDJsnup+7/yYKu08XFks+DLu96x8/fhw//vgj5s+fbxmCMmbMGDRp0gTTp0/HkSNHHngMtVqNadOmYcaMGXj33XfLu8lERGRnfH190a5dO5tAR6/XIykpyRLM3/2RlJQEg8HwwGNnZWUhNjYWsbGxNtu8vLwK7a0PCgp6YEZiIiIiosLYbfC+adMmSKVSq6QISqUSEyZMwJtvvonExMQHLkvw6aefwmg04vXXX2fwTkREFjKZDEFBQQgKCkKnTp2stmm12vsG9sUZsJaRkYGMjAycOnXKZltAQACGDRuGZ599llnwiYiIqNjsNng/ffo0GjRoADc3N6vyNm3aAABiY2PvG7wnJCRg7ty5WLlyZZktpUBERFWfg4MD6tati7p169ps02g0SExMtATz169ft3ydnJxcrMD+xo0b+Oyzz7B06VIMGzYM48ePR+3atcvjpRAREVEVYrfBe3JyMmrVqmVTbi67efPmffefNm0aHn/8cQwfPrzE505JSUFqaqpVmTlzsV6vt8yT1Ov1MBgMpZ43SWQveE1TVVPW17RUKrUMgb+XWq1GYmKiJaC/+/Pt27dt6hcUFGDVqlVYu3Ytevfujeeffx6NGzcuk3ZS1cX7NNkDo9EIQRCK9cDyQczHsOM0XEQPJIqiJX9DYffpsrpn223wrlKpoFAobMqVSqVle1FiYmLw888/49ixYw917iVLllgySN4rNzcXWVlZAACDwYC8vDwApjd0RJUdr2mqah71Ne3r6wtfX1+bJXNUKhVu3LiBa9euYfv27Th+/LhVG3fs2IEdO3agTZs2GD16NJ544gkmbqJC8T5N9kCn00Eul5dZQFKcPCNE9kwUReh0OmRlZRV6n87NzS2T89ht8O7o6AiNRmNTrlarLdsLo9frMXXqVMubn4fx4osvIjIy0qrs8uXLlvUczcsDmW9Y7u7uzPhKVQKvaapq7OWa9vDwQK1atfDEE09g6NCh+Pfff7FixQrs2rXL6k3r8ePHcfz4cTRu3BjPP/88evXqxb9FsmIv1zRVb1lZWRAEoUyuQXOPu1Qq5UNLqrQEQYBcLoeHh0eh9+myWoXGbu/6tWrVQlJSkk15cnIyAMDf37/Q/dauXYsLFy5g2bJliI+Pt9qWm5uL+Ph4+Pn5wcnJqchz+/n5wc/Pr9BtMpnM6kYllUptyogqM17TVNXY4zXdrFkzLFq0CG+88QZWrlyJDRs2WI0oO3fuHKZNm4bPP/8czz33HCIjI+Hs7FyBLSZ7Yo/XNFUvUqkUOp0OAMos4BYEgcE7VUqiKMJgMEAul1vuy/fep8vqfi0pk6OUgxYtWuDixYvIycmxKjcPhW/RokWh+yUkJECn0yE8PNyScMicdGjt2rWoW7cu9uzZU65tJyIiKo6AgAC8++67OHToEF577TV4e3tbbU9KSsKHH36IDh064LPPPkNaWloFtZSI6D8uLi4wGAxITk5m/gWq1vR6PZKTk2EwGB7JUrCCaKfZIY4dO4Z27dpZrfOu0WjQpEkTeHt7488//wRgCtYLCgrQqFEjAMD58+dx/vx5m+MNGjQIffr0wcSJE9G2bdtCk+HdT1xcHJo0aYKzZ88iLCwMgOmXlZWVZbN+MFFlxWuaqprKdk2r1WpER0djxYoVNqPHAFMm/MGDB+P5558vNBs+VX2V7Zqmqkmv1yMpKQkFBQUATL2KEonkoXrOzYm+2PNOlYkoijAajZaHV05OTqhduzZkMlmh9+nCYsmHYbd3/bZt2yIyMhKzZs1CSkoKQkNDsWbNGsTHx2PFihWWemPGjMHBgwct82UaNWpkCeTvVbduXQwcOPBRNJ+IiKjElEolRo4ciWHDhmHfvn1Yvnw5YmNjLdu1Wi1+/PFH/PTTT+jRowcmTpyIxx9/vOIaTETVkkwmQ2BgIHJzc5GTkwOdTvfQ2eLNib7kcjmDd6o0zDkfHB0d4ebmBldX10dy/dpt8A6Yhrm/8847iIqKQmZmJpo1a4YdO3agY8eOFd00IiKiciOVStGzZ0/06NEDJ0+exLfffov9+/dbtouiiN27d2P37t144oknMHHiRHTp0gUSid3OhiOiKkYQBLi5ucHNza1Ux+FoEqLis+u/EKVSifnz52P+/PlF1jlw4ECxjmWnswOIiIiKJAgCnnjiCTzxxBO4dOkSVqxYgS1btlgSRQHAiRMncOLECYSGhuL5559H//79C11qlYiIiCo3PqInIiKqBOrXr4+5c+fi4MGDmDx5ss2yM5cvX8bMmTPRuXNnLFu2zCbhKxEREVVuDN6JiIgqkRo1amD69Ok4dOgQZs2ahZo1a1ptT0lJwaeffooOHTpgzpw5liVWiYiIqHJj8E5ERFQJubq64vnnn0dMTAzmz5+PBg0aWG3Py8vDihUr0LlzZ7z++uu4cOFCBbWUiIiIygKDdyIiokrMvHzcL7/8ghUrVqBt27ZW2/V6PTZv3ow+ffrgueeew9GjR5kHhoiIqBJi8E5ERFQFCIKAzp0744cffrAE6/dmnz948CBGjRqFgQMHYufOnZb1aYmIiMj+MXgnIiKqYpo1a4Yvv/wS+/btw+jRo6FUKq22nz17FlOnTkW3bt0QFRWF/Pz8CmopERERFReDdyIioioqKCgIs2fPxqFDh/DKK6/A09PTantiYiJmz56Ndu3aYebMmTh58iSH1BMREdkpBu9ERERVnJeXF6ZOnYpDhw7h/fffR2BgoNX2goICbNy4EcOGDUOPHj2wbNkypKamVlBriYiIqDAM3omIiKoJR0dHjBo1Cnv37sXixYvRrFkzmzpXr17Fp59+ivDwcEyePBl79+6FTqergNYSERHR3WQV3QAiIiJ6tGQyGZ555hk888wziIuLw8aNG7Ft2zZkZ2db6hgMBuzbtw/79u2Dj48PBg0ahMjISISEhFRgy4mIiKov9rwTERFVY2FhYZg9ezaOHj2KhQsXon379hAEwapOWloavv32W/To0QORkZHYsGED8vLyKqjFRERE1RODdyIiIoJCoUC/fv2wZs0aHDhwAK+88gpq165tU+/UqVOYNWsWnnzyScyYMYNJ7oiIiB4RBu9ERERkJSAgAFOnTsWBAwewdu1a9O3bFw4ODlZ1CgoKsGnTJia5IyIiekQYvBMREVGhJBIJwsPDsWjRIhw9ehSzZ89GWFiYTb27k9xNmjSJSe6IiIjKAYN3IiIieiAPDw+MHj0a27Ztw7Zt2zB69Gi4u7tb1TEYDNi/fz+mTJmC9u3bY+7cubhy5UoFtZiIiKhqYfBOREREJXJ3krtFixY9MMldREQEk9wRERGVEoN3IiIieigKhQJ9+/bFmjVrcPDgwSKT3J0+fZpJ7oiIiEqJwTsRERGVWu3ata2S3PXr1+++Se66d++OZcuWISUlpYJaTEREVLkweCciIqIyY05yt3Dhwvsmubt27Ro+/fRTtG/fnknuiIiIikFW0Q0gIiKiqsmc5G706NH4999/sXHjRmzduhXZ2dmWOuYkd/v374e3tzcGDRqE8PBwNGjQADVq1LCZS09ERFRdMXgnIiKicvfYY4/hvffew8yZM7F3715s2rQJhw8ftpr7np6eju+++w7fffcdAMDNzQ3169dHgwYNLJ8bNGgAb2/vinoZREREFYbBOxERET0y5iR3ffv2RVJSEqKjo7Fp0ybcuHHDpm5OTg7++usv/PXXX1blXl5eNgF9/fr1bZauIyIiqkoYvBMREVGFqF27Nl5++WX83//9H44ePYqNGzfiwIEDyM3Nve9+GRkZ+PPPP/Hnn39aldesWdOmpz40NBTOzs7l+TKIiIgeCQbvREREVKHMSe7Cw8MhiiJu3bqFixcv4tKlS5bPly5dgkqluu9xbt26hVu3buHQoUNW5QEBAVYBff369RESEgKlUlmeL4uIiKhMMXgnIiIiuyEIAmrVqoVatWqhU6dOlnKj0YgbN25YBfQXL17ElStXoNVq73vMGzdu4MaNG/jtt98sZRKJBEFBQTY99XXr1oVcLi+310dERPSwGLwTERGR3ZNIJAgMDERgYCC6du1qKdfr9UhISLDpqb969SoMBkORxzMajbh27RquXbuGPXv2WMrlcjmCg4OtAvqWLVvC19e3XF8fERHRgzB4JyIiokpLJpOhXr16qFevHnr16mUp12q1uHbtGi5evGgV2CckJFhluL+XTqezDNM3EwQBTzzxBHr16oWePXuiZs2a5fqaiIiICsPgnYiIiKocBwcHNGzYEA0bNrQqV6lUuHLlis3w+6SkpCKPJYoijh8/juPHj+ODDz5Ay5Yt0bt3b/Tq1Qv+/v7l/VKIiIgAMHgnIiKiasTR0RFNmjRBkyZNrMrz8vJw+fJlq4D+4sWLSElJsTnGqVOncOrUKXz88cdo0aIFevXqhV69eqFOnTqP6mUQEVE1xOCdiIiIqj0XFxe0aNECLVq0sCpPTk7Gnj178Ouvv+LEiRM2Q+5jY2MRGxuLuXPnokmTJpYe+eDg4EfXeCIiqhYYvBMREREVoVatWhg7dizGjh2LlJQU7NmzB7t27cLx48dhNBqt6p49exZnz57F/Pnz0bhxY/Tq1Qu9e/dGSEhIBbWeiIiqEgbvRERERMXg5+eHUaNGYdSoUUhLS8PevXvx66+/4ujRozaZ7c+dO4dz587hiy++QP369S098g0aNIAgCBX0CoiIqDJj8E5ERERUQj4+PhgxYgRGjBiBzMxM7Nu3D7t27cIff/wBvV5vVdecvX7x4sUICQmx9Mg3atSIgTwRERUbg3ciIiKiUvD09ERkZCQiIyORnZ2N/fv349dff8WhQ4eg1Wqt6l65cgVff/01vv76awQFBVl65Js0acJAnoiI7ovBOxEREVEZcXd3x+DBgzF48GDk5ubit99+w65du3Dw4EGbQP769ev45ptv8M033yAgIMDSI9+8eXMG8kREZIPBOxEREVE5cHV1xYABAzBgwADk5eXhwIED+PXXXxETEwO1Wm1V98aNG/juu+/w3XffoVatWpbl51q2bAmJRFJBr4CIiOxJmQTvaWlpSEtLgyAI8PHxgbe3d1kcloiIiKhKcHFxQd++fdG3b18UFBTg999/x65duxATE4P8/HyrusnJyVi1ahVWrVqFGjVqoGfPnujduzdatWpVQa0nIiJ78FDBe35+PjZu3IitW7fiyJEjSEtLs9ru4+ODJ598EgMHDkRkZCScnZ3LpLFERERElZ2Tk5OlZ12tVuPQoUP49ddfsW/fPuTl5VnVvX37NtauXYu1a9fCx8cH3bt3x1NPPYXOnTtDJuMASiKi6qREd/309HR88sknWLZsGdRqNZo1a4YBAwagXr168PT0hCiKyMzMxLVr1/DXX39h4sSJePnllzF58mTMnDkTPj4+5fU6iIiIiCodpVKJ7t27o3v37tBoNDhy5Ah27dqFvXv3Iicnx6puWloa1q9fj/Xr18PJyQkdOnRAly5d0LlzZ/j6+lbQKyAiokelRMF7cHAwQkNDMX/+fAwZMuSB/yhSU1Px888/Y/ny5Vi+fLnNPyEiIiIiMlEoFOjSpQu6dOkCrVaLo0eP4tdff8WePXuQlZVlVbegoAC7d+/G7t27AQBNmjRBly5d8PTTT6NJkyacJ09EVAUJoiiKxa28e/du9OzZ86FOVJp97UFcXByaNGmCs2fPIiwsDACg1+uRlZUFDw8PDl2jKoHXNFU1vKapKtDpdDh+/Dh27dqFPXv2ID09/b71fXx80KlTJ3Tp0gXt27eHq6vrI2opUcnxPk1VTWHXdGGx5MMoUfBenTF4p+qA1zRVNbymqaox98j/9ddfOHDgAOLi4u5bXyaT4YknnrD06NetW5fL0JFd4X2aqpryDN75F0JERERUSUgkEoSFhSE8PBz/+9//cPv2bRw8eBAxMTH4448/bDLX6/V6HD16FEePHsWcOXMQGBhoGV7/xBNPQKFQVNArISKikip18H79+nWsWbMGV69eRWZmJu7tyBcEAVu3bi3taYiIiIjoHjVq1MDQoUMxdOhQaDQanDhxAjExMYiJicH169dt6ickJGDNmjVYs2YNnJycEB4ebkl6V6NGjQp4BUREVFylCt7Xr1+PsWPHQq/Xw8PDA+7u7jZ1ODSLiIiIqPwpFAq0b98e7du3xzvvvINr167ht99+Q0xMDE6cOAG9Xm9Vv6CgAHv37sXevXsBAGFhYZbh9c2aNWPSOyIiO1Oq4H3WrFlo1KgRNm3ahAYNGpRVm4iIiIiolOrWrYsJEyZgwoQJyM3NxR9//GHplS8s6V1cXBzi4uLw1VdfwcvLC507d0aXLl3QoUMHJr0jIrIDpQre09LSMH36dAbuRERERHbM1dUVvXr1Qq9evWA0GnH27FlLIP/PP//Y1M/IyEB0dDSio6Mhk8nQqlUrS698SEgIR1YSEVWAUgXvbdu2RUJCQlm1hYiIiIjKmUQiQbNmzdCsWTO88sorSElJsSS9O3z4cKFJ744dO4Zjx45h7ty5CAwMtPTKt23blknviIgekVIF7wsXLkTv3r3RunVrRERElFWbiIiIiOgR8fPzQ2RkJCIjI6HVanHixAkcOHAAv/32G+Lj423qJyQkYO3atVi7di0cHR3RsWNHjBkzBm3btmWPPBFROSpV8N60aVN8/PHHGD58OJydnREQEACpVGpVRxAEnDlzplSNJCIiIqLy5+DggPDwcISHh+Ott97CtWvXcODAAcTExOD48ePQ6XRW9VUqFXbv3o3du3ejWbNmmDRpEnr06GHzfpCIiEqvVMH7kiVL8PLLL0OpVCIkJKTQbPNEREREVDnVrVsXdevWxfjx45GXl2dJenfgwAGkpqZa1f3777/x0ksvITAwEBMnTsTgwYOhVCorqOVERFVPqYL3OXPm4KmnnsKOHTsYuBMRERFVYS4uLujZsyd69uwJo9GIuLg47N69Gz/++CMyMzMt9RISEvDOO+/giy++wNixYzFq1Ch4eHhUXMOJiKqIUi3gmZ2djWeffZaBOxEREVE1IpFI0LRpU7z++us4dOgQZs+ejYCAAKs6GRkZ+OKLL9ChQwd8+OGHSEpKqqDWEhFVDaUK3jt16lTo8iJEREREVD04Ojpi9OjR2L9/PxYuXIiwsDCr7QUFBVi9ejW6dOmC//3vfzh37lwFtZSIqHIrVfC+dOlSHDx4EJ9++inS09PLqk1EREREVMnIZDL069cPW7duxdq1a9G+fXur7QaDAVu3bkXfvn0xbtw4HDlyBKIoVlBriYgqn1IF74899hiuXbuGWbNmwc/PD87OznBzc7P64JB6IiIioupDEASEh4djzZo12LZtG/r162eTff7QoUMYPXo0Bg4ciJ07d0Kv11dQa4mIKo9SJawbMmQI1/MkIiIiokKFhYVh4cKFmDZtGlauXIkNGzZArVZbtp89exZTp05FYGAgJkyYgCFDhsDR0bECW0xEZL8EkeOViiUuLg5NmjTB2bNnLXO59Ho9srKy4OHhAZmsVM9BiOwCr2mqanhNU1VT2a/pjIwMrFu3DmvXrkVGRobNdi8vL4wZMwajRo2Cp6dnBbSQHrXKfk0T3auwa7qwWPJhlGrYPBERERFRcXl5eeHll1/G77//jvfffx+BgYFW2zMyMrBw4UJ06NAB77//Pm7cuFFBLSUisj8lCt7Xr1//UIlFRFHE+vXrS7wfEREREVU9jo6OGDVqFPbu3YvFixejSZMmVttVKhXWrl2Lp59+Gq+++iri4uIqqKVERPajRMH7q6++igYNGuDTTz/FtWvXHlj/8uXLmDNnDkJDQ/Haa6+VuHEajQYzZsyAv78/HB0d0bZtW+zdu/eB+23evBk9e/aEv78/FAoFAgICEBERgbNnz5a4DURERERUPmQyGZ555hls2bIFUVFR6NChg9V2g8GA7du3o3///hg7diz++OMPZqgnomqrRBNLrl69ioULF+Kzzz7DrFmzEBwcjJYtW6Ju3brw9PSEKIrIzMzEtWvXcPLkSSQmJsLb2xtTp059qOB93Lhx2LRpE1599VXUr18fq1evRp8+fRATE2Oz/Mjd/vnnH3h6euKVV16Bj48Pbt26hZUrV6JNmzY4evQomjdvXuK2EBEREVH5EAQBTz31FJ566imcO3cO3377LXbs2AGDwWCpc/jwYRw+fBhhYWGYNGkSevXqxTnSRFStPFTCOr1ej+3bt2Pr1q04cuQIrly5YnkKKggCQkJC8OSTT2LAgAHo168f5HJ5iRt2/PhxtG3bFvPnz8frr78OAFCr1WjSpAn8/Pxw5MiREh3v9u3bCAgIwIQJE/DNN9+UuD1MWEfVAa9pqmp4TVNVU52u6aSkJKxcuRI//fQTVCqVzfY6depgwoQJiIiIYIb6Sqw6XdNUPdhdwjqZTIZBgwZh9erVuHjxIrRaLW7fvo3bt29Dq9Xi4sWLWLNmDQYPHvxQgTsAbNq0CVKpFJMmTbKUKZVKTJgwAUePHkViYmKJjufn5wcnJydkZWU9VHuIiIiIyEQURegMRhRoDcjV6GEsh6HstWvXxjvvvINDhw7htddeg5eXl9X2xMREzJ49Gx06dMDixYsLzV5PRFSVlEm2ealUCl9fX/j6+kIqlZbFIXH69Gk0aNAAbm5uVuVt2rQBAMTGxj7wGFlZWUhNTcU///yD559/Hjk5OejatWuZtI+IiIioKtMbRah0BuSo9UjL1yI5R4OETBUup+Xj7K08/JOci7O3cnHudh6SstXlEsADgKenJ1566SUcOnQIH374oU2G+szMTCxatAgdOnTA7NmzS9zBQ0RUWdjt2JTk5GTUqlXLptxcdvPmzQceo127drhw4QIAwMXFBW+//TYmTJjwwP1SUlKQmppqVXb58mUApmEQer3e8rXBYLB8T1TZ8ZqmqobXNFU1ZXlNG4ym3nO9UYTOKEJrMEJnEKHTG6HSm77WG4wwGAEDjNAbTfsAgEwiQCoRIBMEaI1GJKTrYTQY4O+mgCAIpW5bYWQyGYYOHYohQ4Zg7969+Pbbb62SEavVakRFRSEqKgo+Pj4IDAxEUFAQAgMDERwcbPne1dW1XNpHD4f3aapqCrumy+r6ttvgXaVSQaFQ2JQrlUrL9gdZtWoVcnJycPXqVaxatQoqlQoGgwESyf0HHCxZsgTvv/9+odtyc3MtQ+8NBgPy8vIAoMxGHBBVJF7TVNXwmqaqpiTXtFEUoTeKMBjEOwG6KRDXGYzQmgNzUTQF56IIg1GE4U7vuVQwBecSQYBUAsgEAYo73wMARAB3csnJICJHrUe8Kg8FuQ7wcZaXWwBv1q5dO7Rt2xanTp1CVFQUjh49arU9LS0NaWlpOHXqlM2+Hh4eCAgIQEBAAOrUqYM6depYvnd3dy/XdpMt3qepqinsms7NzS2TY9tt8O7o6AiNRmNTrlarLdsf5Mknn7R8PXz4cDRu3BgAsGDBgvvu9+KLLyIyMtKq7PLlyxg4cCBcXV3h4eEB4L8nKO7u7kywQVUCr2mqanhNVz75GtPvzFnB31dh7r6mpVIpdEYReoOpB/3u3nON3giNzgi9OYA3mj7r7/ScSwRAJjf1nDtIBMjufEglwkMF3kpnEekFOmSJErjKlKjpatsBUx66du2Krl274vz581i5ciV27tz5wB6urKwsZGVlFbqEsLu7u1WPfVBQkOXD09Oz3B9KVEe8T1NVU9g1XVYjfuz2L6RWrVpISkqyKU9OTgYA+Pv7l+h4np6eePrpp7Fu3boHBu9+fn7w8/MrdJtMJrO6sUilUpsyosqM1zRVNbymKweN3ohbuRqk5mkgCAL83QTUcHX4r6eXAAB5Gj1SC/TIFLXQGgXojUZLUK6/08MuAhAE/BeQSyVQyO8Mc3/I4Lw4fF2lSM3X4WauDnKZDDUeUQAPAE2aNMHnn3+OmTNn4vTp04iPj8f169ctH+b3jw+SnZ2Nf/75B//884/NNhcXF6tgPjg4GMHBwQgKCoKPjw8D+1LgfZqqmnuv6bK6tu32L6RFixaIiYlBTk6OVdK6Y8eOWbaXlEqlQnZ2dlk1kYiIiErJYBSRmqfFrTwNMgv0kEkAgwhcTS9AnlaPAHclHOUcSmswikjJ0yIpswDp2WpItXLIZTJLgK6QSeDkYPq6oh54CIIAH2c5UvO0SMxSQSII8HVxeKRt8PPzQ8+ePW3K1Wo1EhMTbYL669evIykpCcVZOTkvLw9xcXGIi4uz2ebk5GQT2Ju/9vPze+CUTSKi4rDb4D0iIgILFizA8uXLLeu8azQarFq1Cm3btkWdOnUAAAkJCSgoKECjRo0s+6akpNj0nMfHx2P//v1o3br1o3sRREREVChRFJGp0uNWrgYZBVroDCI8HeVwkEkgiiJyNQYkZqlRoDWgtrsS3k7lP4/aXhVoDbiRrUZKnhY6vQEejnI4uyogscP5weaAPTVPi4QsFSQC4O38aAP4wiiVStSvXx/169e32abRaHDjxg2rgN4c5CclJcFgMDzw+AUFBTh37hzOnTtns83Z2RnPPPMMXnzxRcv7VyKih1Hq4H337t1YsWIFrl69iszMTJsnl4Ig4MqVKyU+btu2bREZGYlZs2YhJSUFoaGhWLNmDeLj47FixQpLvTFjxuDgwYNW523atCm6du2KFi1awNPTE5cuXcKKFSug0+kwd+7ch3+xRER2wiiKluWbVDojHOUSKGQSyKUSOEglkEsFy2cOOyZ7k6cxBe1p+ToUaA1wVcrg5fRfICoIAtyUMijlEqQX6KDWGZHvpoC/mwJyafXpwTSKplEJN3M0yCzQwVkhhbuDHJp8dUU37b4kggAfZwek5mtxPdPUA+/pJK/oZhVJoVAgJCQEISEhNtt0Oh2SkpIK7bFPTEwsVgbp/Px8bNiwAdHR0Rg8eDD+7//+DwEBAeXxUoioiitV8D5//nzMnDkTNWrUQJs2bdC0adOyahcAYO3atXjnnXcQFRWFzMxMNGvWDDt27EDHjh3vu98LL7yAnTt34tdff0Vubi78/PzQo0cPvPnmm2XeRiKiR8lgFJGp0iEtX4sslR75WgOkEsFq+SbLh1SATCKBUi6BUmYb1DtIJZBKGNjTo6PVG3E7T4uUPA2yVHo4ySXwu8+8dgepBH4uDshS6XEtQ4U8jR51PBzhprTbgYNlRq0zIClbjdt5Omj0Bng7yyGXSmAsRi+wPZBKBPg6m3rg4zNVEATAw9F+A/iiyOVyy9z2e+n1eiQnJxca2CckJECr1drUNwfxERERePHFF1G7du1H9EqIqCoQxOJM8ilCQEAAGjdujF9++QVyeeW7IZdEXFwcmjRpgrNnzyIsLAyA6SaclZUFDw8PJtigKoHXtP3SGYzIKDAF7dlqPdQ6I5wcpHBRSC2BjyiKMIiA3nBXAqs7H6Jo6g2TSwGpIIFcCsgkpt56pVwKh3uCerlUqBI9nLym7YPBKCItX4vbuVpkqHSQCICHUgZZCa4xlc6ALJUeHo4y1HRVoKaroko+fBJFU9b2m9kapOVr4egghZtCapkyYDQYoM7LgdLFzS6Hzd9LbzAiLV8HL2c56nk5VYsHL4Bpqajbt2/j2rVr2LZtGzZv3mwz/F4ul1uC+JImYq5KeJ+mqqawa7qwWPJhlOovJDMzExEREVU+cCcqD+Y3aJkFOng4yuHlJK+Sb0SpdNQ6A9LvBO05aj10BhGuShnclTKb+b+CIEAmADJJ4W/o714qSmcUodLpkakSYRQBAbD01MskgEwqgYNUgKNcCoc7X98b3FfX+cdUfKIoIlutx60cDdILdNAajHB3lEMpK/mDIfO1mFGgwzWdCvlaAwLclXBysP8Atri0euOd3nYt8nUGeDuZcgBUZjKpBN7OcqTl6yCgACHeTnCpBssASqVS+Pv7w9/fH+Hh4XjhhRfw9ddfY8uWLTAajQBMQ/LXr1+PTZs2YejQoXjhhRdQq1atCm45EdmzUt0927RpgwsXLpRVW4iqDYNRxM0cNW7maJCj1sMpXwt3pQw+zg7wcpLDoQr0eFLp5Gn0pp72Ah1y1XoYRRFuSlmpsm5L76zhXNjiTUbReqmpAq0BOUYRBqMGAu4sMSX9b0i+/M5wfMWd4fgOUgEOMgnkEtNnzrOnAq3BtPRbvhZ5GgNcFVJ4ODqU6qGPVGJKhpar0eNGlhoFOgNquynh41z5k9llqnRIylYjNU8HB6mAGi5VZ5k8uVQCH3MAL6gQ4u0E5yr00KU4goODMX/+fLz44ov4+uuvsXXrVqsgft26ddi4cSOGDRuGKVOmoGbNmhXcYiKyR6UK3pcsWYLevXujdevWGDlyZFm1iahKU+tMGZRv5WoAALXcFFDpjEjJ1SKzQAe3O0G8t5McSi6PVK2IoogcjR7p+TpkFGiRozZAJhXgrpSVe++bRBDu9K4X3q67h+Cr9UbkGQww5JvWk5bePc9eIsBRLkGAhxLuSo7KupcoilDpjFVmWkJhdAYjUvK0uJ1rmteukEvKfL12V4UMSpkE6fmmZHZ5GgfU9lBWygefOoMRyTka3MrVIE9jgIejrEre++VSCbydTMvISQQgxNupWi4BWLduXSxYsAD/93//h6+++grbtm2zBPFarRZRUVH46aefMHz4cEyZMgU1atSo4BYTkT0p0Zz3Zs2a2ZRlZGQgOTkZLi4uCAgIgPSe+VeCIODMmTOlb2kF45x3KgtZKh1uZJmW+3FWSOF6z9BBtc6AHI1pTpybQmoK4p0dHlkPBa/pimEURWSpTJnjM1U65GsMcJBJ4KaQlmhOcEUx3BmGb55rr9IZ4eEog7+bssyDtpKyp2tabxSRnKPG7VwtpBIBHo5yuCqkcFOU/8OZR8EoikjP1+F2ngbp+ToAgIejrFwfUoiiiCy1Hlq9CD8XOWq7KytVUrQctR43stWWgNbTSf7Av5fKNuf9Xmq9EVkFOtRwdUCIt1OVfFBREleuXMFXX32F7du326zY5ODggBEjRmDKlCk2SyBXJfZ0nyYqC3Yz593Ly8tmWJq3t3eha2YS0X+MooiUXC2SctTIVunh6SSHopA360q5FEq5FFq9ETkaPbJUBUjJ08LLSQ4fZwe43pW0iCo/ncGIzDtBe5ZKD5XOACcHKXxdHCpV/gPzcHzcuaZdFabkZBp9AVQ6AwIqaY9oWSrQmkbc3M7VmBIMAMgo0EEpk8DRQQp3hRRuSjnclLJC7w32LketR3KuBun5Wqj0RniUcopHcQmCAE9HOdQ6A27lmpZNrOmmQC07T2ZnMIq4latBco4G2Wo93JWyKjV3/36UMgk8HGW4nauFRBBQz9upUl7zZSUkJARffPEF/u///g9ffvkldu7caQnitVot1qxZgx9//BEjR47E5MmT4evrW8EtJqKKVKLg/cCBA+XUDKKqS2cw4kaWGsm5Wmj0hmIFZg4yCXxkDtAbjMjRGBCfoUJqvhaejqYg3sNRVmXmQlZHGr0pc3zqnSR0Gr0RrgpphfdSlxWpRICfiwNy1Hpcz1RDpTMg0NPRZqRJdSCKItLydUjKUSMjXwdXpcwykkYUTVMQ8jV6ZBbooJBp4SSXwE0pg7vS1Ctv772SKp0Bt3O1SM3TIEdjgIuDFDVdSjev/WEo5VL4SSXIVOlwLb0A+RrTQyN7nFedp9EjKVuDlDwNjCLgV8ke1pUFpVwKdwDJORoIAlDP26naP+ALDQ3FokWLLEH8rl27LEG8RqPBqlWrsH79ejz77LOYNGkSfHx8KrjFRFQRSnWnXLt2LeLj44vcfv36daxdu7Y0pyCq1PK1BlxJK8D1LDUAscRv0mRSCbyc5PB1cYDRKCIxS40LKfm4mJKP1DytZW1vqhzMva//3s7DxdR8pOdroZRJUNPVAS6KqvVARhAEuDvK4aaU4lauFpdS83E7V2MzLLQq0xmMSMhS42p6ATLydfB2llsFk4Jgyubv7eyAmq4OcJJLUKAz4nqGGudT8hB3O8/yc1Pp7Gttb9MUAA3Op+TjWoYKGoPp/uZayCoIj4pUIsDH2QEKmQRJ2WpcvPOzM9rJNWcURdzK0eBiWgFuZKuhkEkq3SibsuQol8JNKUNyjhbxGSroDMaKbpJdaNCggaUHvnfv3lbb1Go1VqxYgU6dOuGTTz5BWlpaBbWSiCpKqYL38ePH48iRI0Vu//PPPzF+/PjSnIKo0krL1+JSWj6ScjRwcZDCw/HhsyFLJaZAqIarAyQSIClHg4up+TiXkodbORpo+abHbomiiBy1HtfSC3AuJQ+X0wqQo9bDTSlDDVcFnByq9lQIR7lpGkC2Wo+r6apq8yY9T6PH5bQC0+s1ivBzdbjv3G9BEKCUS+HlJEdNN1OeC5XOFPxfSM1H3K08XEjNx61cDQq0hgp7CGKa167FhZQ8XE7LR5ZKB08nmV0tdemikMHbWY4slc5yzWn0FXvNqXQGXEkvwJWMAmSrdPB1lleL5dIexMlBCmcHCW7maBCfqYKeD6QtGjZsiK+++go7d+5Er169rLap1Wp899136Ny5M+bNm4f09PQKaiURPWql+s/xoDcP+fn5TDxB1Y7hTo/UzRw18rQG+DjLyyxhk0QQ4KqQwcVBigKdEal5pgz1rnky+N5ZZq46Zu+1R0ZRRPZdSejy7iSh83Iq3wRe9kh2Zxh9llqP61lqqPRGBHooq2TwIooiUvK0uJmjQUaB7qHmMpsDeaVcClEUoTWIKNAZkJ2lxm2JACcHCVwUMngo5XBVyuAklzySB0C5GtN67Wn5OhToDHY9T1sulcDvzkOj65l3lpRzV8LzESezu3fahJODFH4VMK3AnrkoZBBFPW5mayABEOzlZDcPguxBo0aN8PXXX+PcuXNYvHgx9uzZY9mmUqmwfPlyfP/99xg9ejSef/55eHl5VWBriai8lfid099//43Y2FjL94cOHYJer7epl5WVhW+++QYNGjQoVQOJKhON3oiELNWdoZqmuYzlMRRaEAQ4O0jh7CCFWmdAlkqPLJUebgrTEFxvJ/bqVBSDUURGgQ7p+VpkqvQo0BngKK/ew2OB/xKLFWgNSM7RQKM3IsC9aqzPbaY1GJGUpcatXC3UegN8neWlXi1AEAQoZIIpoZcjoNUbUaAzIClHg9u5pjnyrgoZ3O9krndykJb5PUejN+J2rgYpeaYcDY4OUtR0tf8AVBBMGf3VetNSnCqtATXdlKjlpoDsEfwtavRGJGWbVhdQ6QzwLsMHuVWNq1IGo9qUC0AQBAR5Olbr+2VhGjdujKVLlyIuLg6LFy/Gvn37LNsKCgqwbNkyfP/99xgzZgwmTJgAT0/PCmwtEZWXEr+737x5M95//30Apn+My5Ytw7Jlywqt6+HhwTnvVG1kq3VIzFIjJVcLZwcpXJWPJnguLEN9qlIKLycHZqh/hLQGIzLydUgr0CJbrYdaZ4SLQ9VJQldWnBykcJAKSC/QQaM3okCngL+botIHNTlqPRKzVEjN10EuFcqtd9VBJoGDTAIPmObUF+iMuJmjwa08UyDvopDBXSmD253EeKW59gxGEan5pvXaMwr0kElQKR9CKWUS+Lk6IKNAh2sZBcjX6hHgXn4jP0RRRKbKtARcer4OCpmAGpXgYUdFc1fKkKXSISlbDYkgINBTyXtnIcLCwrBs2TKcPXsWixcvxv79+y3b8vPzsXTpUkRFRVmCeA8Pj4prLBGVuRKt8w4AycnJuHnzJkRRRJs2bfDBBx/YJNQQBAHOzs4ICQmpMsPmuc47FUUURdzO0+JmthqZd5aBU1bgsjfmDPVavRHOCmmJMtTbwzUtiiL0RtNQYa3eaJnPL5UIkAgCJMJ/X0sFQCIRIL1TXhFvjlU6A9ILdEjL1yJXrYfeKMJF8eiGMldW5gDHYBRRw9UBdTwcyyUzeHlf0+ZlIG/mmP7+PRwfzRJp9zIH8mqdAYBpaL3znVwbbgoZXBTFD+RFUUSWyrT0W0aBDjqDER6OhS9vWdnkaw3IUZvu0/5uijIfHaU1GJGco8GtXA3yNYYilwUtjcq+zvuDZBboAAB1PJQI8GAA/yB///03Fi9ejJiYGJttLi4uGDduHJ577jm4u7tXQOuKxx7ee9xNazAiS6WHl5P8kYzSoarHbtZ5B4BatWqhVq1aAICYmBg0btwYfn5+D90AosrMvAyceZisPSz5Y8pQL4HBKCLvTnbz9Hwd3B1N8+I97eSfkd74X3B+d6BeoDM9eNAZTUG83mB6vigRTHP+hTuBuvnD9L0ACQCpVIBMYvqQSiSWQF9q2Ue4E/hbfy0VBEjuKi+OXI3eMjw+R2PKBO5WCZb2sheCIMDLSY58rQE3szVQ3xlG7+1UeYbRa/RG3MhS4XaeFhq9Eb4uDhX2tyWXSuAulcBdKYP+TiCfmqdFap4OTnIJnBxMD/JclVK4OMiKvE/law24laNGWr4OeVoD3JQyeDpWXAb5subsIIXizsgPtc6AfI0eAR6OZRJgm3uNU/N1pjwPHHXzUDwcZZaRCxJBQG13RZW5/spDs2bN8N133+HMmTNYvHix1bLOeXl5+Oqrr7B69Wo899xzGD9+PNzc3CqusZWA1mDEtXQV0gu0qOHiwBwMZHdK9XirU6dOAACDwYC//vrLsmxccHAwWrVqBWkVfCJMZFagNSAh0/TGXVaOw2QfllQiwF0pg6tCivw784wzC0xBvI+TA7yc5eW+rq5RFKHRG6EzmD6bA3WVzgCN3gi94U6QbhChu5NlWHon+JZLBChlEsgcTD9TUTQdzygCIgCjUYROBIyi0Xrbnc93k9wV8At3BfKCYFpyQyIxPRSQ3vlaLjEF9pYPQYBEYj6OgFy1DhkFOuRqDJBLBXg4yqr9GsUPy/neYfRaBWq7K+3+zVKWSocb2Wqk5umglNnX379MKoGb1LRevN5o+ntLy9ciNU8LJwfpnUBeBleF6UMqEaA1mOaF387TIFulh1IuqbJTPmR3ktnlaAy4nqlGvs704MjL6eGS2ZmXzbudq0a22lBhoy+qClN+DBnSC0xT0QQB8HdjAP8gzZs3x4oVKxAbG4tFixbh999/t2zLy8vD4sWLsWrVKksQ7+rqWoGttU/mwP1mjgbSOyv7SAQBQV6OVfJeSJVTqcemrF69GrNmzUJKSool+7wgCPD19cWcOXPw3HPPlbqRRPYmPV+LxGxT9mA3O864DFhnqFfd6Y3LKNDBrYwy1BtFETqDCK3BaAnUtQYjVDoD1Doj9EYjdAbc+SxChCmIlkslkEkEOEglcHYwBezl8eZMvDuoB6wCfKMoQi8Cot5o+f7uBwF3swT7AqAziFDKJfCpwJ7WqsScGTyzQIf4TBVUOiPqeCjt8u/KKIq4lavBzWwNstV6eDrK7Hq0hUwiWIJ0w51APqNAh7Q8LRzlUjg5SOCulCNHo0dmgQ6CAPiUQaI9eycIpoebSpkEqXlaqHUG1HRVwN9dWaK/6VyNHklZaqTkawHALkZfVQWCIMDbSY60fB1uZJl64Gu5KSq6WZVCixYtsGrVKpw6dQqLFy/GoUOHLNtyc3OxaNEirFq1Cr169ULjxo3RqFEjNGrUqNr3yN8duLsoTAmBM1U6JOVoIJUInMJBdqNUwfuyZcvwwgsvoEWLFpg9e7Yls/yFCxewbNkyTJw4EVqtFlOmTCmTxhJVNINRRHKuBsnZauSU8TJw5U0QBEuvW1EZ6pVFxCCiaOoZNw1t/2+Iu1pvhFpn+lpvFC2BulEUIQimwEEulUAmFeAol0EmFR75Pz/hztx44OHPK4qmhw7mwN88557KjkQQ4O3sgDyNHknZaqj1BtTxcHzo3tDyoNYZkJhtSkqpM4qVLlCTSgS4KGRwUcASyGep9EjL10GAabiyPT+IKA8KmWmEQWaBDtcyVMjXGhDgoYTrA5LZGYwibudpkJyjMd1H7yQIpLIjCAJ8nOVIzdchMUsFiQDUcGUAX1wtW7bE6tWrcfLkSSxevBh//PGHZVtOTg42bNhgVd/f398SyDdq1AiNGzdGUFBQtRhFW1jgDgCejnJkFOhwI1sDiURAbY4AITtQ4oR1d6tXrx7q1KmDffv2QS63foOl0+nw9NNPIykpCVevXi11QysaE9bRf8vAaWEURXg5ySt9AKc1GJGj1kNvEOGmlMLdQQK5vgAubu4wQHInUDegQGeE7p4h7gajCAGA7K555ube9MoU0JD90RqMSC/QwdVBCv87S3s97DVVVvfpzALzMHnT0POqtIqDKIpV5rWURoHWYBlN4e+mLHLOer7WgKRsNVLytNAbxUee1KqqJ6y7l1EUkZZnWsUl2MsJvi4OFd2kSunkyZNYuHAhjh49Wux9lEolGjRogEaNGqFhw4aWnvqyTn5Xke+niwrczURRRHqBDgqpBIGejhwBQsViVwnr7nbr1i1MmzbNJnAHALlcjuHDh2P69OmlOQWRXchR65GQpUJKrumNu5vSfnoDS8NBKoGPswP0BiNyNQYkFKgh06khU8ughynpnQhYgnNTD7oErlIJpBWU3Z2qPgepBDVc/lvaq0BnQB0PZYXMI7YabaMxwKscsodXNP4dmzg5SOEgkyA9XwuVvgC5Wj3quCstoxGMoojUPC1u3skf4qyQ2tXIkKpKIgjwcXFAap4W1zNVd6Z2MIAvqdatW+P777/H8ePHsWXLFpw/fx4XLlyAWq0uch+1Wo2///4bf//9t1V5rVq1rHrpGzVqhODg4ErXkfWgwB34bwpHar4ON7JUkEpMOU6IKkqp/soef/xxXLx4scjtFy9eRIsWLUpzCqIKJYoiUvK0SDIvA1dFh5XKpBJ4OkmgkwvIyS6Ag0wCF7ms3OahEz2IRBDg4+yAXI0p67Rab0QddyU8H2GwpNKZVmtIydPAKHI+c3Ugu/PGPFdjQGKmGiqtEbXdFXBykFp62zV6I7wr0ZSpqsB8P0jN1yIhUwXJndUqqOTatGmDNm3aADAlnE5ISMC5c+cswfy5c+eQlJR032MkJycjOTnZank6hUKB+vXro3HjxmjYsKFl6L29rjNfnMDdzDKFI890/UkFwJsPkKiClCp4//LLL/HMM8+gXr16mDRpEhwdHQEAKpUK33zzDTZs2IBffvmlTBpK9KjpDEbczNHcWcbKPpaBK29SiQBHuWm5MwnfmJIdcFXIoJCakopp9QbU0pmG0Zf3lJX0fC1uZJuWWXRWSB84B5qqDkEQ4GZOZleghUpvgFIqQXqBDo4OUrtaWaA6kUoE+DqbeuDjM01z4D0cGcCXhlQqRd26dVG3bl306dPHUp6Tk4MLFy7g/Pnzlo8LFy5ApVIVeSyNRoOzZ8/i7NmzVuU1a9a06aWvW7duhfbSlyRwN7v7AdL1TFMPPK8/qgilmvPerFkzZGRkIDk5GTKZDP7+/gCAmzdvQq/Xw9/fH56entYnFAScOXOmdK2uAJzzXr0UaA2W+e0yiWkpsOrwZq26zaWkysNgFJFRoINUIqCGqwMCi7k2d0nv06Zlv9RIztEgV2uAt1P5L6lI9ssoishS6aEzGOHpKIeDHUyZqO73ab3RNH3B21mOel5OcFPy/dejYDQacf36dUtQf+7cOVy4cAGJiYklPpaDgwPq169v6Z0PDQ1F7dq1ERgYWO7vpx8mcL+bwWgakcnrj+7Hbue8e3l5wdvbG/Xr17cqDw4OLs1hiSpURoEps216vg6uzCBMZBekEgG+Lg7IUeuRmKmGRmdEgIeyTHs+CrSmYfK38zQQANRwqZrrnFPxcXi2/ZFJTEOYTaskFKCetxNHxjwCEonE0kvfq1cvS3lubi4uXLhgGXJv7qUvKCgo8lharRZxcXGIi4uzKg8ODkaLFi3QokULNG/eHI0aNYKDQ9kNTy9t4A6Y/heZrz+JoEI9L0e48PqjR6hUV9uBAwfKqBlEFc8oikjO0eBmthq5GgPnNBLZITelDAqZBCl5Wqj1RtR2V6JGEVnBi0sURaTl65CUo0YGH9oR2T25VPJfAC+oEOLtxL/ZCuLq6orWrVujdevWljKj0YjExESrYffnz59HQkLCfY8VHx+P+Ph4bNmyBYCphz4sLMwSzLdo0QIBAQEPNRKyLAJ3M7lUAu87c+AlAhDi7VQhCVWpeuKjIiKYloFLzFLhVq4WBqNY5BJBRFTxFDIJfF0ckF6gw9WMAhRo9Qgo5jD6e5lzW9zK0SBfy4d2RJWFXCoxZQG/E0DV83KCk50G8AajCOOdJRkFAOa3F+Z3GVVtWp5EIkFQUBCCgoLQs2dPS3leXp6ll/7uoff5+fmFHker1eL06dM4ffq0pczb29sqmG/WrBlcXV3v256yDNzNHKQSeDnJkZKrhQRAiI9zlVuJhOxTqYP3nJwcLFmyBDExMUhJScGyZcvQpk0bZGRkYPXq1ejfvz9CQ0PLoq1E5SJHrUdilgopeTo4yiUcIklUCZiSV8mRozEgIUtjykbv4Vii+Yd5Gj1uZKlxO09rWv6HD+2IKhUH2X8BlACg3iPuATWKIvQGEXqjCJ3RaPlabxShM4jQGYzQGIzQGUzLrlqC9bs/37nnSAAIkv/KJYIAQQAEmD+bqpofAJh2vfvr//Y1fX1nmwCrOuY9FDIJPB9xPh8XFxe0atUKrVq1spQZjUbEx8fj6NGjuHz5Mv7++2/8+++/0Gq1hR4jPT0d+/fvx/79+wGYfgYhISGWYL558+Zo2LChZZ5xeQTuZgqZBO6OMtzK1UIiEVDP24k5UqjclSp4v3HjBjp16oTExETUr18f58+fR15eHgDTfPhly5bh+vXrWLRoUZk0lqgsVZdl4IiqKkEQ4K6UQSE14FbunWH0bsoHBuHmv/2bORpkFOjgrpTZbY8dEd2fQiaBh6MMt3O1kAimAKq0PaCiaB2E//e10fS1wQi13hSUG0QRBqMIgxF3fW0K1gHTg0apYN27bs4VLVqdE1Zld+eTFu+p81/pgwPvu2uY2yAIgFImga+zHP7uygod8i2RSBAYGAg3NzcMGzYMMpkMGo0G58+fR2xsLM6cOYPY2Fhcv3690P1FUcTly5dx+fJl/PzzzwAApVKJJk2aoGmz5qgV0hgegQ1RJ8C/XKZWOMqlEEUgOUcLqSAg2MuRo7eoXJUqeH/jjTeQm5uL2NhY+Pn5wc/Pz2r7wIEDsWPHjlI1kKg86I0ikrJNGaVVOgN8XRwgq+LLwFHVk6/W49qtPLg4ylDb2wnyajpkTymXwk8qQVq+Fhp9AQp0BgR4KAvtAdEajEjKUt8J9g3wdZZDxjdaRJWaUi6FO4DkHA2EO0PoC1sZQBRFGERAbzBCdycg/6+33BSMa/VGaAwiDEajKRAXTcPe9UYRRtHU2w4AEsEUmMskAqSCALlUgFIigfROub0Mhb/3QYH5AUCeRo/rmWrkag2o6aqAnx0l6FQoFGjevDmaN29uKcvMzMSZM2cswfyZM2eQnZ1d6P5qtRonT57EyZMnLWVePr5o8FgTNHisKRqGNUVoozA4OTuXSXudHKQwiCJu5mggEYBgL6cqv7QwVZxSBe979uzBa6+9hsceewzp6ek22+vVq/dQS0gQlSdzRulbuRrTUFmu2UuViE5vxMlL6Yj5+xaOXUiHTm8EYHqzGODjhOAazgjyc0GQnzOCazijhocjJNXgTYT5bzlbrUdClhoqnQGBno5wvKujxTxFJjVfB7mUf/tEVcndPaDmVQLuHsauMRih1RmhE0UYjUYYjID+rl7ze4NyqSCYPksEOEj/+9peAtzisvS2WwpMn9wd5XByMCKjQId8rQE5aj383RR2mznd09MTnTt3RufOnQGYHkrEx8db9c6fO3cOer2+0P0z0lLx5+8x+PP3GACmHv86wfXQIKwpGj7WFA2bNEOd4HqQPuTyi64KGURRj6QcDSSCgCAvx0p3rVDlUKq/UJVKBV9f3yK35+bmlubwRGUuo0CHG1lqpOVrmVGaKg2jUcS/CdmI+fsWDsWlIE9l++bEYBRxPSUf11PyAaRYyhVyCYL87g7oXRBcwxmeVTBwFQQBHo5yqHSmYfQag4iazlLIRBG3czW4na9HpkoPD0cZMwMTVUFODlIYRRFJ2RrcztXAIJrunyJMQ8XvDsilAqCUSqwC9epGLpXAz8UBeXc6NXI1etR0VaCGq8LuRyMKgmBZum7QoEEAAI1Gg9h/zuLAkROIPXMG186fReqtm4XubzQacf3qZVy/ehl7t28GADg6OSG00WNo8FhThDZ6DAFBdeEfEAgHhaJYbXJTypCp0iEpx9Q5FOChZABPZa5Uwftjjz2G33//HZMnTy50+5YtW/D444+X5hREZcK8DFxyjho5agO8nOVMKkJ273pKHmLO3EbM37eQmq15qGNodEZcTMrFxSTrh6mujjIE1zAF9EE1XBDs54wgP2e4lOG66RXFUS6FXCpBer4WarUOCoMaaqkArShwigxRFeeikEEhM8IoFj7fnKwJggBXhemBZmaBDle1Bci+0wvvUcn+HwgyOTwCG/1/e3ceJlV15w38e++tfe99X4AGMSIiCigCAhohLhH3GJNoxknedzLJOybPTGYyGZOYzCSTmJl5ZybLjPPm0bgmSqKT0Rg1CipugCIgoKy90PQGvdVedznvH7eq6KUaeu+q6u/neXi6+9bCre5Tt+73nnN+B8sDc7D+htvhtino7T6Fg/v34qN9H+Dg/r04uP8DRMKhjI+PRiLY+95O7H3v9HB7SZJQWlGJqtp6VNfNQXVtHarr5qCqth4FRcXD2laB02p2FPXFIcsSqnx2tj+aVBMK7/fccw/uvPNOLF68GLfccgsA80rW4cOHcd999+Gtt95KF48gmilcBo5yycn+OF7dYwb2o+2ZTzBSygscWH1eKXRDoLEjjKbOEE4FM1foHSoY1bC3sRd7G3sHbS/22Qf10NeVelBT4oI9x3qqLclh9D3hOLrCCfh8Tg6TJ5olWDBs7CyyeXEzktDR1h9HOK6h1GtHhc+eE50dI1WVDxQWYfmqtVi+ai0AM6e0Njfio317k6F+LxqPHIKh6xmfVwiBjhOt6DjRivfefmPQbS63B1UDwnwq3JdX1SCoy2jtjUGRJFT4RtdzTzQaEwrvn/nMZ9DU1IS/+7u/wze/+U0AwMaNGyGEgCzL+P73v49NmzZNxn4SjUt/TENzbxSdwQRcNoXLwFFWCsc0vLG/E1t2d2BPY8+QisKD+VxWrF5UinWLy3FujW9YGA1GVDR2hswh9B1h8/uOMEKxzPMAhzrZH8fJ/jjePdyd3iZLQEWhC3Vl7mQPvRnsKwudULL4pC41jN6uW+F0Whncc4CmGwjHNPhc/HsRzQSXTYHdIqM3quJYdxTBuIYKrx2FWfyeTAX3tlEsB5ea615TPxdXXnM9ACAWi+LIhwfw0f69OLjP7J3v6mg76/8bCYdw6MA+HDqwb9j/UVpeiZKqWtTUzcGihfOx5GMLMHfuXBQXD++tJxoLSYgznSaOTnNzM37zm9/g8OHDMAwD8+bNw4033oi5c+dOxj5mhX379mHRokX44IMPcN555wEANE1Db28vAoFAej1Jyg5GaimoLF4GTgiBYx0h9IVVs1qtIsOSLIpjfpUHfC/BosjJ+5nVbeUpqGZr6DpioX44PD7I4yzaQqMzUuG5TGwWGZcsLMa6C8qxdF7hmKvKCyFwKphAU4cZ6hs7QmjsDKOlK4y4OvL/ezYWRUJtiTsZ6lND8N0o9Tuy5uSEbTp7JVQdjZ1hHD4RxJG2IA6fCKKxMwxVM1AacOCaZVW4amkF/G7bTO9qVmGbpukSU3X0RjW4bApKPTZU+uxTci41kfPpgcHdPYnruEfCYZxoacLxpmM43tyI402NaG1uxInmJiQS45vGBgBerxdz585N/5s3bx7mzJmDuro62Ec5t56yX6Y2nSlLjsekhPfZgOE9d6i6geMDloIqdtuyqhCNEALbPzqFR7ccxZG2Mw+LPpuBwT5VhGfottSFAEsy9JvhX4Yy5EKBRZEgS4BTMTC/phANVX5UFs6OSuXTZTSF51JkCbhgbgHWLS7HynNL4HJM/jFGNwQ6eqJoTPXQJ3vrj5+KwDDG/9FQFnDgxstqcdXSihkfbs+gkx2icQ1H20NmSG8L4siJEJq6wmdtZ1aLjMsXleLaFdVYUOWbpr3NbmzTNJ0MIdAf0xBTDRS6rajw2lEyycvKjfd8eqqC+5kYhoGujja0NpmB/nhzI1qTAb/7ZNe4n1eWZVRXV2PevHmDwv3cuXNRVFSUNRfEaXQY3rMAw3tuCMU1tPTG0BFKwKZI8DssWXPAE0Jg56FuPPrKURw6kRsrMThtCuaUezCvwot5FebX2hL3rF1PfLzGUniuodKLdYvLcPn5ZSj0zsxVeFUzcPxkJD3kvjHZY9/RGxvT8xR4bLhhZQ2uXlYF1wwtP8SgM/2CURVHkgH9cJvZq956KnLG6SCjcU61D9cur8KaRWWz+hjENk0zIaEZ6ImqsFtklLhtqPQ7Ji0sj+d8eiaC+9lEwiG0Npu99a0DeutbW5qgJkZXjyYTn8+HhoYGXHzxxVi+fDkuuugi+Hy8mJnNsia8y7I8riCkj1AEIpcwvGc3IQROhlUc74uhO6LC77DAlQUHcsDct11HevDoK0fx4fH+md6dCUsNlR4Y6OeUe2YsnGWrsRSeKws4sO6CcqxbXIaaEvc07eHYReIamjvDaOwMp4fgN3WG0RM680mJx2nB9ZfU4JMrquGd5roTDDpTqzeUSPakB9NBvb1nbBd5Ulx2BfMqvHDYFLx7uHvEXnm/24qNF1Xi6mVVKPE7JrL7OYltmmaKEALBuI5IQkfAaUG5z44yj33CoxvHej6d0Awc686u4H4muq6j7cQJ7D94GOGu4wh2HEdz4zEcO3YMnZ2dZ3+CISRJwsKFC7Fs2TIsX74cy5YtQ3Fx8RTsOY3XVIb3MZ1tf+tb3xoW3p9++mns27cPGzZswDnnnAMA+PDDD/Hiiy9i0aJFLFhHU043BFr7YmgLxhGO6yh2W7Om0uzuo2Zo39fcl/H2hgovrriwHBIATRfQDQFNN5JfzZ+HbtMMA7ouoBnC/Drs/saA5xr6s3H6cYYY19BoTRc42h7C0fYQXtplbpMkoKLQaQb6cg8aKr2YV+GddXNVx1x47rxSrLsgc+G5bOSyW7Cwxo+FNf5B2/vCiXS1+11HevDORycH3R6KanhsyzH89o1mXLO8CjesrEWBZ3a1jVwnhMCp/jgOJ+emH2kze9VP9Y9v7qfPZcW8Cg8aKryYV+lFQ4UX5QWnp+mc7Ivh9ztP4A87W9EbVgc9ti+s4tevNeGp15twycISXLuiChfMKciJ9xBRLpMkCT6HBS6rjO6ohsipCPqjGir9DvimYGpXJrkW3AFAURRU19SgtLIKp8Iqyrw2zCtywWlVEAwGcezYMRw5cgRHjx5N/2tsbERihN56IQQOHDiAAwcO4OGHHwYAzJkzJx3mly9fjqqqqul8iTSNJjRs/oEHHsB3vvMdbNmyJR3cUw4cOID169fju9/9Lr7whS9MeEdnGnves1NU1dHcG0NHMA4JQIHLmhXLwO1t7MGjrxwbtgxXytxyD+5YNweXLJzZqqNCiEHBP5FQ0XziFI73CRztCONIWwiNHSEkzlBM7UyKfHbMSw+7N3vqSwPZU8xsMqiagR2HTmHrWArPLS7H0oaxF57LFcc6QnjytSa8/kEHMl0fsllkbLyoEjetqp3ynlP2Uo6dEALtPVEcTg17PxHEkfYg+oaE6NEq8towr8KbvqjXUOlF8SjXPlY1A9v2deJ/3jl+xpFLNSUuXLu8GlcsKc/7UUBs05Qtwgkd/TENfoeCMq8d5V77uDpPRns+nYvBfai4ZqAnoqLca8O8YjfsI5wH6LqO1tZWHD16FEeOHMGePXuwffv2UffUV1ZWYtmyZelAP3fu3Lw698p2WTNsfqj58+fj85//PP72b/824+3/8A//gIceegiHDh0a9w5mC4b37NMTUdHSF8PJUAIeuwJPFpyw7WvqxWNbjuH9oz0Zb68rdeMz6+fg0oUlWVkILtNJoa4bOH4qgiNtZrGpI21BHG0LjXrpsaE8TgvmDgn01UWurF5ybKhsKzyXrVpPRfDU6014+f126BlSvEWRsP6Ccty6ug6VRa4p2QcGnTNTNQNtPdHTw95PBHGkPYTwON/fZQFHuic99f6erNoNh07049l3WrF1b8eIF8mcdgVXLqnAtcursnoKykSwTVM20Q2BnqgKIYAitxWVPgcKnGOrNzSa8+l8CO4pUVVHX1RDpd+OuUUu2EZ5/iOEQHNzM3bs2IEdO3Zg+/btaG5uHtVjCwsLB4X5hQsXQuHxY8pkzbD5oY4fPw6rdeT5i1arFcePH5/If0E0jCEE2vrjaOuPoS+mo8hlhW2GezA/bOnDo68cw3tHujPeXlPiwh3r5mDVx0qzMrSfiaLIqCv1oK7Ug/UXlAMwP0A6e2ODAv2R9tCohtCGohr2HOvFnmO96W02i4z6Mk96Dv28Ci/qy9yTVqlcCJFxWoKWmlKQ4fvU1AJNHzztoLkrgq2jKTxX4cW6C2a28NxMqypy4Z5N5+LTa+fgN28044V3TwwaxaHpAi++14Y/7mrD6kVluG1NHerLPDO4x/klGtdwsj+OU/3xwV+DcZzsM7+erV7BSCTJ/PumAnoqrE9lTYP5lT589QYf7t7QgBfePYHf72gdVkQxGtfxP+8cx/+8cxxL5hbg2hXVWLGgKKcuDhLlEkWWUOy2Iarq6AgmEE7oKE0WtBupV3ms8im4A4DTqkAIoK0/AUWSUF/oHNWIBUmSUFdXh7q6Otx8880AgPb2duzYsQM7d+7E9u3bcfDgwYyP7e7uxgsvvIAXXngBAODxeHDRRRel58yff/75sNk4nS0XTKjnfdmyZTh58iS2bds2bG7F8ePHsWrVKpSWlmL79u0T3tGZxp737BDXDLT0RtERTEAzBIrcMztM/mBrPx575Rh2HDqV8faqIhfuWFeP1YvKsmq5upFMtEenL5xIhvlQ+uuJ7vFVmZZlCTXFLlQVu06H7wxz/tV0GB889z/1s6qPb27/eJQFHFi7uAzrLihHbZ72+k1EdzCOp99swe93tCKayFzI9JKFxfjU5fWTtixYPvZSCiHQH1Fxcmgo74/jZH8Mp/oTONkfQyQ+OcViZVlCbYlr0Pz0bChSqRsCOw+ewv+8c3zEC6cAUOK345plVdhwUWVe1OHIxzZN+cEQAn1RDQldoMhlRYXPPqrztDOdT+dbcB8oGDeX4Kv221Ff6JqU88Senh7s3Lkz3Tu/b9++URUOt9vtWLJkSTrMX3jhhXC5pmZE3GyQtcPmt23bhg0bNgAAbrjhBjQ0NAAADh06hGeeeQZCCLz44otYtWrVuHcwWzC8z7z+mIbm3ii6QiqcVhleuzJj83eOtAXx6CvHhhXmSqkodOLTa+ux9vyynOrxmYqTwtT6zqk1no+0BdHUGYam58cqlblYeG6mBSMq/vvtFvzuneMjTjlYOq8Qt11eh/PrCyb0f+Va0NF1A92hRLpnPP21P5YO6KeCiTPWVpgIiyKhvmxwIbnJHAUzVY6fjOC57cfx0q62ES9aWC0y1iwqxXU5vmZ8rrVpmn1S87qdVgXFHiuqfI4zrgA00vl0Pgf3lP6YhoRuoMbvQF2hc9I7pEKhEHbt2oXt27dj586deP/990cshDeQxWLB+eefP2h5Or/ff9bHkSlrwzsAfPDBB7j33nvx4osvIhqNAgCcTic2bNiA++67D+eff/5Enj5rMLzPHEMIdIYSONEXQ09UQ4HTAscMnUgeaw/hsS3H8OaBroy3lxc4cPvaOVi/OLdCe8p0nRSqmoHmrnB6/vyRtiCOtodG7I3NNrOl8NxUi8Q1PLe9FU+/2TysonjKebV+3HZ5PS5qKBzXhZFsCzon++NoPRlJ9pBnHsY+0fXQz0aWgAKvHcU+O4p8dpT47JiTrENRW+LO6fYcjWt4ZU8Hnn3nOJo6wyPeb0GVD9etqMLq80phy/ILEylCCPSGVXT2RBCPhFBQ4IfPbYfHYcnJzxvKb0II9Md1RBM6ClxWlHvtKPXYMvYuZzqfng3BPSVVM6A24EB1wDGlI0rj8Xi6+N2OHTvw3nvvIRwe+ViZklqeLhXmly5dipKSEs6bH0FWh/cUwzDQ1WUGmpKSEshyfn2QMLzPDFU3cLw3hvZgAnFNR5E784F/qjV1hvDYlkZs25e5ymeJ347b187BlUvKYcnhk6iZDDqGIczCWcnh9keTvfS9YRWSBFgUGRZZgqJIya+nf7YqMhRZgkWRoMhy8qtkPkYZYXvq/kOe16LIg74f+BhFluCwKTinyjerCs9Ntbiq44V3T2DztmacHKFuQkOlF59aU49LFhaPqW7ETLbpYFTFodZ+HGwN4mBrPw629qM7OL455qNls8go8pnBPBXOT391oMhnR4HbmvdhTwiBDxp78T/bj+PNAydHnDrjc51eM740MLNrxquagZP9MXT0xtDVF0dnbwxdfTF09sbQ2WduG7FQn02Bx2mBx2GFx2mB22E5/XPqe6fV3O6wwJv63mnJ+lEVlNtU3UB3RIVVkVHitqHSb4d3yJSboefTsym4p3RHVMiShLoCBypHuRrHZNA0Dfv3708XwNu5cyd6e3tH9VhJkuDz+VBQUICCggIEAgEEAoH09yNtczhm9lg7HXIivOc7hvfpF4praOmNoSOUgFWREHCMrXrpZGjpCuPxrY147YOOjL1hxT47bru8HlddWJHTvVUp2dZLCZihPteK/NH4qJqBV3a346nXm3CiO5rxPnWlbty6ug5rFpWOKoBOV5uOqzqOtIVw8Hg/Dp7ox8Hj/SO+hvHyOCxDwvjwYO4dY5Xn2eBkXwzP7zyB5zOsGZ8iS8CKhcW4bnk1Lpg7NWvGh6KqGcJ74+gcGMqTX6dj1EUmVotsBvwBgd/tTP1sHbw9fSHAAq/DCucMTl+j3CGEQDihIxjX4XdYUO61o8xrSxdpG3g+bUCedcEdMH9HpyIq7IqM2gInKnwzU+jWMAwcPnw4HeZ37NiBjo6OSf0/HA5HOsgPDfojBX6v15tTHcMM71mA4X36pA5gLb0xdEdU+B2WM86VmgqtpyJ4fOsxvLon8zrVhV4bbltTjw1LK3JmyOVoZGN4p9lH1w28vq8Tv36tacShzxWFTtyyqhZXLDnzhbOpaNO6bqCpK2z2qB83e9QbO8PjLowoSUCBx4Yirx3Ffrv5dUgoL/bZ4ZglJ7FTRdUMbNvfiWffacWBlr4R71dT7MK1K6pxxQXlox5hoxsCPcE4Ovvi6OyNpnvOUyG9q2/yCghmE1kC3A4LKgqd2HhxFa64oDwvLmTT1EgtK4fUsnJ+Bwqc1vT5tMvjQ0u/OuuCe4oQAl1hFW6rjLpCF0o9M19gUwiBlpaWdJAfy/J0k0lRFPj9/kHBPlPwv/jii1FUVDTt+zcUw3sWYHifHrohcKI/hhP9cYTjOorc1lEtnzFZ2rqjeOLVY3hld0fGE/ECjw23rK7DJy6uzMuhhgzvlE0MQ+Dtj07i16824tCJYMb7FPvsuGlVLTYsrcwYbifapoUQaO+J4qPjp4e/H2kLIq6OvWBcVZELC6q9mFfuRWnAkQ7rBR5bTk+3yUWHTwTx7Pbj2LqnY9DyhQM5bQquWFKOa1dUo9TvwMn+VG/54CHtXckh7foUrWpht8oo9TtQ4negNOBAsc8GocYRMywIx3WEYipCUQ2hmIZQVEU4piEc0zJeeJ5qRT47brqsFhsvyvx+JAKASEJHX0yD166gzGtHiVNBX18veg0HOsLarAzuKYYQ6Aol4LVbMKfQiaIsXCGjo6MDhw4dQk9PD3p7e9Hb25v+fui2YDDzZ/dUeeKJJ7B8+fJp/T8zYXjPAgzvUy+q6mjpjaE9GIcEoMA1fcvAdfRE8cSrjfjj++0ZQ7vfbcUtq+pw9bKqvD4hYXinbCSEwK4j3fjVq034oKk34338bituuLQG1y6vHtRbOtY23R2M41BrEB+19ifnq/cjOEJF/DMp8tmxoMqLBVU+LKjyYX6lFx7n1K2BTuPTH1Hx0ntteG7HcbT3xM7+gCngd1vTwbzUn/wXcKAkYEep3wGfyzpoaPpo2rRhCEQTA4J91Az0Q4O++VVDeMD2YFSd8GogPpcVmy6twbXLq9juKSNDCPRGNai6QIFDhhEJog8OeJy2WRvcU3RDoCucQMBhwdwiFwI5/B5SVRV9fX3Dwn2m4D/we00b++cuADz//PNYsGDBJL+KsZvK8M7ESVmhJ6KipS+Gk6EEPHYFnmlaP7irL4ZfvdqIF99ry9hr4nNZcdNltbhuRXVeh3aibCZJEpY2FGFpQxE+aOzFr19rxLuHB6/r3RdW8dAfj2LztmZct6Ia119aA5/rzCc8kZiGgyf6B4X1rr7MBfPOxOOwYP6AoL6gyoeiGZqvSGPjc1lx06pabFpZg3cPmWvGD21bE6HIEkr89nQ4Px3S7cledMeUfLbIsgS3wyxcVxYY++Pjqp4O/MFkyA+nAn8q/CcDf3cwjoOtg3vX+iMqHn75KDZva8K1y6ux6dIaBLJgCDBlD1mSUOiyIqYZOBmOwYgk4A+4Z31wB5LHDbcNnaEEGnuimCtJ8OVokVyr1Yri4mIUFxeP+jFCCIRCoVEF/oHbwuEwCgomtrxsLsjNlkB5wxACbf1xtPXH0BfTUeSywjYN8+VO9sfx5GuN+MO7JzL2MHicFty0shbXXVIN1zRdSCCis1tUH8Ci+iU42NqPJ19rGrZsYyim4YlXG/H0Wy24ZlkVrl9RCZdkzndubAunq74fPN6P46ciYy4QZrPImFfhOR3Uq32oKHCyqGKOU2QJy88pxvJzitF6KoLntrfipV1tCMfO3PvjtCvpnvJ0j7nfjtKAE6V+Owq89hlZIWWi7FYFdqsy6otQh07049evNeHN/YPfj5G4jidfb8Izb7Vg40WVuPGy2hmv6j+dYgkd73x0EidORVBZ5ML59QEUenlhbyCHRUaZ24aIsDK4D6DIEordVpwMq5ClKOYWOqetY2umSZIEr9cLr9eL2traUT8uHo/DZsv/i4QcNj9KHDY/+eKagZbeKDqCCWiGQKHLOuUnOd3BOJ58vQnP7zyRcckdt8OCG1bW4PpLauDO0aucE8Fh85RrmjpDePK1Jry6N3NxSasioarQgeOnYtDGOAlYloC6Ug/mV3lxTrUZ1utK3ZyfPkvEEjpe2d2OXUe6IctSxpA+E0PCs/k43dwZxlPbmrBlT+a6MYos4Yol5bh5VR2qi10zsIdTTzcEdh/twZY97XhzfxeiicGFCquLzRBv/ivgKB1kd5ueaQndwKmwijKvDZU+B7x2ZVprQdH4cM57FmB4n1z9MQ0tvVF0hlQ4rDJ8U7jcjGEI7G3sxSu72/Hq3szFiZx2BTdcWoNNl9bM6vl5/AClXHXiVARPbWvCy++3j3u+bnmBA+dU+zC/0odzqn2YV+HldBnKOrlwnO7oiWLztma8uKst44VySQJWnVeK29bUYW65dwb2cHIJIXCkLYRXdrfjtQ860B1MjPqxVcke+fPnmGG+eBaG+Vxo0zMprhnojpjnyy6rAr/DAp/DAq/dAjtXd8hKnPNOeUMIgY5QAif6YuiJaihwWuCYoqrtTZ0hvPJ+O7bs6cDJ/szzWB02BddfUo0bV9bCe5b5sUSUvSqLXPiL68/Fp9fOwW/eaMYfdp4YsYo4AATc1vSw91RBOX8WVvUlykVlBU78+XXn4Pa19Xj6zRY8t6MVsQE90EIAr3/Qidc/6MSyBUW4bU09Plbrn8E9Hp+Onii27OnAlj3taOmKjOs5Wk9F0Hoqgj+8ewIAUFnkxPn1ASyuL8D5c2ZnmKfB7BYZZV4bYqqBUFxDd0SF3SLDaZXhc1jgs5th3pmHqyDRcAzvNG1U3cDx3hjagwnENB0lHhsskzxMvjsYx9Y9HXhldzuOtodGvJ/dKuOTK6px42W1PGEnyiMlfgf+99UL8Kk19Xj6rRZs3d2OcFxDQ4U3HdQXVPlQ4rdP2WgfIjIVeu24e0MDbl1dh9+9cxz//XYLQkNWb9hx8BR2HDyFxfUB3LqmHhfOK8jq92YwouL1fZ3Ysrsd+5r7znjfAo8Nl59fhovnF6G5K4y9jT3Y29g77Hcw0IlTUZw4FcUL77YBACoLnVhUH8DiOQVYXB9AsX/21Ayg02RJgsumwGVTIIRAXDMQUQ30RmOwKRKcVgVehwV+uwVehwUuq5zV76PJYAiBmGogouqIqgZcVjkrl9abbBw2P0ocNj8x4YSOlp4oOkIJWBQJAYdl0g4qsYSONw90YUtybuKZprUG3FZcsaQCN11Wy8q3GXDoGuUbtmnKN7ncpiNxDc/vOIHfvtmMnlDmoeULqry4dU09LjmnOGsKQSZUHdsPnsIru9ux89CpM07NcdoUrPxYCdYtLscFcwuG1fIxDIHGzhD2HOvFB4292NvYM6blKCsKnek584vnFKAkD8J8LrfpmSaEQEIXiKg6YqoBiyzBZZXhsVvgd5pD6902ZdqWXp5KhhCIJMygHlF1BOMaogkdcd28mFFX4EBDsXumdxMAh81TDhNC4FRExfG+GE6FVfgdFrgmYQ5pqiDMK7vb8eaBrkHD8YayW2VcsrAE6y8ox9J5BVBmcaEPIQQMYR4AdcP8Xh/wvaZpUKMJOBQVdquAzSLDKkt5f/WWiIimnstuwU2ranHdiiq89H47Nr/ehI7e2KD7HGwN4u+f2IvaEjduXVOHyxeVzsjndqpezpY97di2rxOR+MjnGYosYWlDIdZfUI4V5xSfsVaGLEuYW+7F3HIvNl1aA8MQaOoMY0+yV/6Dxl70R9QRH9/WHUVbdxQvvmf2zJcXOHB+fQEWJ+fMz6Zq/mRWZrdbJHPuu9MscBdVDbT1x9ERSsBpleG2KQg4rPA6FHhslpxZAUMzBKKqjkhCR0Q1EIxpiGk64pqBhC6gyObrdlllxM8wTS7fMLzTlBBCIBjX0R1R0RGKI5zQUey2TrhC5tH2IF55vx1b9565IIwkARfMKcC6C8px2bklcOVx5XhDCBiGgD4glOsCyW3JgJ4cjiDBPNArknkCoUgSFBmwKTIUWYJkkaAKKySrAk2YhQVVXUCSzPvYFPNAaWGgn1FG8kp7QjMQ1wwImHPi7IoEm0XOiyvsRJS/bFYF1yyrwoalFXh1bweefL1p2Jzx5q4wfvyb/Xj0laO4eVUdrlxSDts0zOk91h5KF7gdqV5OysJqH9ZdUI41i0rHPQVPliXMKfdgTrkH11+SDPNdYew9Zob5vWcJ8+09MbT3tOGlXafD/KL0nPkAygLOce0X5SbzXE2G32GBpptD67tCCXQGE+awe6uCgNMcWu+1WyZ9+upEJHQj3bMeTmgIxc2gHtMMqIaANRnWPXYLbMqQ89AxjF7JdfmbaGhGJHQDvVEN3eEE+uIawnEdNouMUo9t3IHiZF8sXRCmsSN8xvvWlbqx/oJyrFtclrPzwob2jmcK4roQMGe8SJBgXvWXJfOrIkmwSIBiNUOcVZFgU2RYFTN0K7KU8atFlmDoGvr6NLi9bmiQEVONAVc9dSR0gb6oBtUQkFOB3mKGegb6qaMZp4N6XDcAAdgs5t+1wGmFJAEx1bwy3RPVIEvJMJ/8xzBPRNnIosi4YkkF1i0ux1sfduHXrzXh8IngoPu098Twk//5CI9vPYYbV9biExdXwjnJ61139cWwdZTnGZVFTqxfXI61i8tQWTT5y93JsoQ5ZR7MKfPgk8kwb86X78WeZKA/e5hvxx93tQMAygKOdCX7xfUBlBUwzM8WFkWGTzGL2unJXuzuqIqT4QQcVgUuq4yA0wqv3Zwvb5vGES7p4f7J88tQQkc4riGuCcR1A7ohYE12GAWcFp5jDsDwThMmhEAooaM3quJUWEUoYb753DYFJR7buIbnROIa3thvzmPffawHZ6rMUOi1Ye35ZVi/pBxzyjw58+YWQiCSDMepYesp6TAuSZBTveOy2TtukSRYk8FtYPDOFMbN5xn970MY5n2tigynxQLvgCK3Cd1Ih/mYZiCc0BFVdSQ08+CrpQK9RYZdkWFVJK5FOg5CCKi6+eEV1wyoyaFhNkWGwyqj0GWFx67AaTWvoDus5u84VbQlkkjOA1PNv1dfVAMkwK6cDvO5MmSOiGYHWZZw2cdKsfLcEuw60o1fvdqED5p6B92nO5jA/3vhMH79WiOuv6QG162ontAqMaGoim37u7B1dzv2NvWe8TzD77bi8vPLsG5xORZUeaf1PEOWJdSXeVBf5sF1K6phGAItJ8PYc6w3XQCvLzxymO/ojaFj1+kwXxpwYHF9ABfMLcDF84tYtHeWUGQJHrsFHrvZORRVDfTHNZyKqHBYZDhtCvx2BT6HGeYneyUoIQRimpEeAh+Ka4ioZs96XDM7pGzJcxS33ZpVIwKyDcM7jZua6mWPquiLqgjF9eTBQUGBc+xVLnXdwHtHuvHK7g68/WEX4urI81ccNgUrzy3B+gvKcMHcwpwKI6qeCr6GucyH3XLW3vGB38sSZuQCRWoolm/AFISEZiCqmUVSYpqBYFwz5yJpAuFkoDeDp5Qedm9hoB9ENwQSyaAe1wwYAubvy2K2Da9dgctmgdMqw2lVRlzTNVWFFu7TH5JR1fygDMU1hJMfksG4PuhDMjUNgohopkmShKUNRVjaUIR9Tb148rUm7Dh0atB9glENj245ht+80Yyrl1XhhpU1KPSObjk1VTOw4+ApbNnTju0HT2Vcgz7FbpWx8twSrF1cjgvnFWTNZ5csS6gr9aCu1AzzQgi0dEWwp7EnWQSvB71nCPOdvTH88f12/PH9dkgSML/Si4vnF+Hi+UWYX+XLqfMpGh9ZkuC2KXDblHTF9nBcQ09Ehd0Sh9OqpJef89rN84+xnndmKi4XU3XENHMkIVIjBBUZXjs7FcaC4Z3GRAgzlPVGNZyKJBCM60hoBpw2BcXjWPpNCIFDJ4LYkpxfdqYPHFkClswtxPol5bh0YfGkD5ubSiJ5lTOU0CEE4LHJKAk4UOiywu/M3SuMNos5bD41QyE1DCrVOx9TDYQSGmKqgYRuIJQwpwIosgR7smfeNovCoxACmiHSQT2hC8iSBJtFgj15YcRrt8BlVdJhfTwfaJJkLhvjtCooTPZMmcvKmD3zA4enhRMqdMOAbUDPPEdM0EwwhIBIThkyRxzNjuMCZXZeXQD3fTaAI21B/Pq1Jryxv3NQ73g0oeM3bzTjd+8cx1VLK3DzZbUZh4QbhsD+5j5s2dOO1z/oRCg28txYWQIunFeIdRfkznmGJEmoLXWjttSNa5cnw/zJCPYe68GeZAG8kSr7C2EWCDzYGsTjWxvhc1lxUUMhLp5fhKUNheyVnwXOtASdVRlQuT7ZI++2KRmDvG6I9DlGpuJysgQ4ksXlAk4Lp/NNQFYfleLxOL71rW/hkUceQU9PDxYvXoy///u/x8c//vEzPu63v/0tfv3rX2PHjh1ob29HTU0Nrr32Wtx7770IBALTs/N5RjMEeqMquiPJXvaEAUkCPDYFBc6xL/vW0RvF1t3meuwtJyNnvO/ccg/WX2DOLxvt1fVsoRkC4biGiGrAbpFR4LSgyGVDwGkZ8QCYywZVPU0aFOhVA1HNHC5lHtDNCxq6IWCRpfT8+dSUgFxniORc9eQyJqnXmSq4krry7UzOPbNbpm5d1lQwL3CaYX5gYZjQgMIwvVEN2oC5ZnauOEBnkKrRIYSAAZz+PsNXQwiIIfdJSbUuWTbreKTun4/HBRqbeRVe/O1ti3D8ZBhPvt6ELbs70kVYAbM3/bntrXh+5wmsW1yGW1fXoabEjebOMF7Z3Y4te9rR1XfmwnPzK73pwnO5dp4xlCRJqC1xo7bEjWuSYf74yQj2NPami+CNFOb7I2qyxlAHJAlYUOXDsvlFuHhBERoqvFmzdB9NDUmS4LCaQ+YHnru19sfRETQr15tB3uxoEBCIJAxEEhqCYykuRxOS1eu833777di8eTPuuecezJ8/Hw899BB27NiBLVu2YNWqVSM+rri4GJWVldi0aRNqa2uxd+9e/Md//Afmzp2L9957D07n2It1zNZ13sMD5rIHkz2oTqsMj00Z8xCy1PyyLbvbsbex94z3LfbZsW5xGdZdUI76Ms8EXsH0Sw1ZDsXNUOqxK/A7rSh0WhFwWrK6V3O62nTqd5TqnY+qOkJxHQndXK8zoQkYQqTnzSuSeXVYGvgV5gfNTE0jyETTTwd1VTcgRKoGgPmBmBp+5kz2rGdTW1D108Psw6kP4mSdA23ARQd7Mkhly+/8bLh+8JkZydEghjEgYAvAwJDQPSB8iyGhO/U+TL0XZckspSnLw9+nqRoep6cDyen6HlKqzocsmb04CQ3hhIG4ZhbLTOgChjDMETvJaTizcXWF2d6mO3qj+O0bLXjh3RPm8NshJAmoKHDiRHf0jM9TXuDAusXlWHdBGaqzZG3o6SCEuTTdzkOnsPPQKexr6ht0MWQkfrcVFzUU4eL5hVjaUATfBOoNDDXb23QuUJOV62OqDsDskTcEhhWXc8zQikRt/fFZs8571ob37du3Y8WKFbj//vvxl3/5lwCAWCyGRYsWobS0FG+++eaIj926dSvWrl07aNvDDz+MO++8E//1X/+FP/3TPx3z/sym8K4bAn0xc1h8qpddCDGueS+qZuDdw6fwyu4OvPPRyTPOL3PaFaz6WCnWXVCGxfUFOXeFVzfMKQXhhA67RYLHZkGR24qA0wpPjvSyz2SbNpLDtczeeR3RhJ4+cdcFkoFiQIgQp3vwhh7EBoeIIeEBGHwRYJwXA1JXpVMjCFKF5czCcBJcVgWeAWHdYc2tkHG2IXDKgDBvz+Iwz5NCs63qwry4pBpmQUTNMKewSACsihmYZaTeE6ffQ6n3zNA6HKkQLicDuZx8L6WKbZ5p21jaSmo+plnDQUcseaEvrhvp5RJF8jXYFRnW5MWlXHqvjRXbtKknlMAzbzbj2R2tiJ5hDfaBfC4rVi8qxfrF5VhY48va49Z0isQ0vH+0BzsPncKOQ6dw6izL4wHm8eGcap85V35BEeaVT6xXnm06t2i6OYpSlswpkNlQD2I2hfesTZybN2+Goij44he/mN7mcDhw991342//9m/R0tKCmpqajI8dGtwB4IYbbsCdd96JAwcOTNUu57yoqqMn1cuerFbtSA71HmsPoRACm7c14zdvNJ9xSRNZlnDRPHMe+4pziuGw5d5BO5Zc4kLTBdx2BVU+Owrd5tD46Vx2I9fJA+ZpF8C8op8K9Jph9sQbyRCvD/h54NfUdt0ANMOAbiRvRzLkD3gO1RAQGDK8F+b8yKEXA9IhH+ZJi5bspUyte+93WOCxKXDbLHDazLCe6397RZbgtZtD44DhxWf6Y2bxmUhCQ48muDxdFjCEgKYLqIYYFNQB8+9plSVYknMYbRYZrmQBRJsiw6IMCNup4C0PDuYzYeB8TCSPC3qybkSqtkYkedE0rpvDN3s18zVbldSQ+9waLUKjU+Cx4fNXNeDm1XX4n3eO47/fakEww1rPNouMSxYWY93icixtKIR1hKKfs5XLYcHKj5Vg5cdKIIRAY2cYOw+avfL7mzP3yhsCONDSjwMt/XjklWMo8NhwUUMhLkrOlfc6J69XnrKPRZHhzfFznFyWteF9165dWLBgAXw+36Dty5cvBwC8//77I4b3TNrbzSUyiouLJ28n84BuCPTHNHRHEuiJasmCagKeZJXJ8ZywCSHws+cO4rntrSPeZ36lF+uXlOPyRWUIeHKvIIo5pFNHSNVhTS6/UeSyosBpLuPF4DI5UoF+ItLh3hDQkz32w76OcDEg9TjNEIMuBtgs5tQR5wQLy+USWTq9zAxwukd0pOXppGSYd1imdi7/bDOaXnSLbC7V6LQqcNoU82+QLA6ZuuCUy2vmKvLAQG9KrWGcmooTUc1An9DNGhuqLgAJp4fbJ5ezzNXfAZ3mdVrx6bVzcMOlNfjDuyfw9Jst6A7GsXhOAdZdUI7Lzi2By5G1p7tZRZJOrzF/y+o6hGMadh3pTg+x7w5mnivfE0qkK9jLErCwxp+eKz+3PHeW8CXKBVl7NGtra0NFRcWw7altJ06cGNPz/fCHP4SiKLj55pvPet/Ozk50dXUN2nb48GEA5jAITdPS3+u6nv45l8RUHb0xDd0RFaGYjoimw26R4bMpsKWGLBkGRh7knpkhBP7j94fx+53D/z6lfnMe+9rFZagpdp1+jD664W7ZIK4ZCCfME0GXVUGZy4IClwUBhzVdpM3Q9TH/3rJFLrfps5Fh9ppj0DmENOTr2RlCpIfipwhDxxlmhOQtmwzY7DICdhnCY0nXMQgnzKHNkYSGcFxHd9hIVppVpn3OvKHrMAw9p44zwOBedF03oIrhveiKLMEhS7DZzF50m0UaFE5HnA8uDOTYr2NUHArgUGTALgOwmCs7qDqiyXaZmgKiajr6EipUXUBKBnprsjBeLhRnzNU2PdXsFgnXr6jCJ5dXQtPFoB52/q7Gx2mVsHJhEVYuLIIQAsc6wnj3cDd2HurGgZY+ZOiUhyGA/c192N/ch1++fDTdK39xQyGWzCuAJ8OFFLZpmiiRbD/Zcv6a6Xx6svYta8N7NBqF3T684qfD4UjfPlqPP/44fvGLX+DrX/865s+ff9b7/+xnP8N9992X8bZgMIje3l4AgK7rCIVCAAAlB+bopIa99sc0hBIaIgkDAgIOiwK/VYakSzCiQGwCz/9ff2zBS3sGr8m6vMGPay8qxcIqd/JEUkMs1D/h1zNdBFJzLnVIkOCyySiwpZb0MiBrKqKhKEbfIrNXrrVpyj4SAA8At1UgISdrGMjmEOd41EBfssdYkVIB0wyh0hguoIyFMHSo0Yh5wUXOrjadmrahGwY0w+w91pMjRCQgXdDNIgN2SYLXmhwCLptzDK2yBKuS/P1JmlllzgAM1TyOj/dYnm8sMNukxwposoGERSChm8s1xlUDsYSOhA6EdQOaMKeApEYvpOb5T1X7HI9sbtPZhDFw8lV6gMolAVy3JIBwTMPupiB2HevHrsZ+9IYzB5OhvfLnVLqxdI4PF87xoa7ECUmS2KZpwvRoAlFLHL1K5tEh0y3T+XQwGJyU587a8O50OhGPDy+aEYvF0rePxuuvv467774bGzZswD/8wz+M6jFf+tKXcMsttwzadvjwYWzatAlerze93FzqCorf78/qgnVxzUBvTEVPREMwriGiybBa7ShwWwYt6TURhhD42bOHhgX3jUsr8KVr5+fkMPKEbvYgxjUDLoeCMoe5ZnbAYYFjgkO5s1WutGnKPQOH2YcTOoIxHVHNHOacWprOppjD7CezCr+h6xAA7O6ZK4QkkhXdU0PcVcMY3ItuMXvSXcne36G96FaFdQSmUkI3Q3yqPUYS5sUmVROIGWb7HPirP9NfIVOvfab7n+1POfTmQSN9JB2aokOxuuFyWNkuaEY4PMD64kKsv8g8vh9rD2HnoW68e7gbHx7vH7FX/kBrGAdaw3hsWxsKvTZc3FCIpXMDmFtkhcflhcJzDxoHRcTh9DgQCLjOfudpkOl82uv1TspzZ+07pKKiAq2tw+dMt7W1AQAqKyvP+hy7d+/GJz/5SSxatAibN28edRgpLS1FaWlpxtssFsug51EUZdi2bGAIgWBcQ09EQ3dURSiupQuqlblsk/phbxgCP332Q7zwXtug7Vcvq8KXrlmQU1XjhRCIqOYcSUmS4LFZUem3oNBlg89hyft5zUD2tmnKfTYrkKpikpqjnFqhoT+mIaYZ6EsY0A0NtuTyeg7LxNf2lmUFsqJMeXgfGNLN+egGNN0sgGiRzRButQAuxZqXc9FzlcUCuOxAQfJnkZyiENX05FKWBuK6gVQlS3H6m3RxS2E+cPDP6ecbvFEMuX3wnTLcNmSboeuIaQp0SDgZ0QEJcA4oFsn2Q9NNBjC/OoD51QHcvm4ughEV7x3pxruHTuHdw90jrivfHUzgxV3teHGXWZfKbpFRWuBAWcCJsoADZanvCxwoCzjgc1nZvikjKfk5n03nrkPPpydr37LnFQ6xZMkSbNmyBf39/YOK1r3zzjvp28/kyJEj2LhxI0pLS/H73/8eHk9urRU+XgndQE9ERU9ERV9MQzihw6KYhaYcU1Bh1TAE/u13H+LFIcH9mmVV+LMcCu6qbiCUrKTtssoodttQmCxA58rBCvhE2U6RUwXwzI+hgUsthhIaQnEzOJ2MqzCEGFT8bqYvog0K6clpAENDuk0BXBYLnDazqKFNkVmNP0dIkmSOfLDI8Dum/v8TZwvuQzaqmobuHhVWlxsxXTJH1CU0RFQdPVENFlmCwyLDYZ3cUSxEo+V1WXH5+WW4/PwyGIbAkfZguoL9RyP0ygPmSNGWrghauiIZb3faFJQGHCgvyBzuPaxyT7NA1ob3m2++GT/+8Y/xwAMPpNd5j8fjePDBB7FixYp0pfnm5mZEIhEsXLgw/dj29nZcddVVkGUZL7zwAkpKSmbkNUw3IQQOn4zgVDiBhC7gtiko8dim7ER3xOC+3Oxxz/aro0IIRFUjWWEf8NjMK75FLhv8s6SXnShbKLIEn8Nc5QKwQ01OWzHDvI5w3OyZ74+ZlextA8L8VAXhTCFd1U/PR7cmK5a7klXdGdJpPAZ+VmZsLUM2CtmcUhFwWmGxWNKfZQNHsUQ1Hb1RDZohJnUUC9FYybKE+ZU+zK/04fa1c9AfUfHe4VPJIfan0BceeTnhoaIJHU2dYTR1hjPe7nFY0uHe/GqG+9ICB8oDDjjtWRt7iEYta1vxihUrcMstt+Ab3/gGOjs70dDQgF/+8pdobGzEL37xi/T9Pve5z+HVV18ddOV648aNOHr0KL7+9a9j27Zt2LZtW/q2srIyfPzjH5/W1zKdVM2AIYByr21Kw7NuCPzrfx/AH5NDnVKuW1GN/331/KwO7pohEI5riCTXsS90WlHoNnvZ3exlJ8oKVkVGwGkGFABIJKvYh1UdweSoooHL0jkmMGxYCHF62bURQ7oMl9VcosxhVdLD3BnSaaZJ0uml80pgTptLBflwXEP/gFEsIjWKxcp2SzPD57Ji7eJyrF1cDsMQONwWxPuHT+F4Zz9OhnV09sbR2ReDpo/QPX8GoZiGUHsIR9tDI/7fw3vsT/fc2/O0ntFs0BdO4GhcQ0Oxe6Z3ZcplbXgHgIcffhj33nsvHnnkEfT09GDx4sV49tlnsWbNmjM+bvfu3QCAH/3oR8Nuu/zyy/M6vANmIZwpD+7PHMAf3x8c3D+5ohr/K0uDu6ab8xajmgHDEPDYFVQHHChyWeF3WDi0kCjL2Szm3PACWCF8AnHNQEQ1l27si2mIqXp62LCSHDZst8iwDBiIPDCkq7qR7lUfGtLdNhlOqwyHVUmGcyk9N51hh7KdLEnw2s0VUeAdPIolGM9w4SvZKz+dSzgSAWav/IIqHxrK3YiF+uHwmIVFdUOgJxhHe08MHb1RdPTE0NEbQ0dPFB29MXT1x2GMNPb+DPojKvojKg6dyFz1u8BjS4f7Ao8ddqsMu1WBzSLDblPgsMqwWZT09qFfbcnPDQvfS9OmP6Ji87Ym/O7t46gvdePj55Xm/e8+q8O7w+HA/fffj/vvv3/E+2zdunXYNjF0ghhNGt0Q+L/PHMDLQ4L79ZdU44ufyJ7gLoRAQjcLYsVUA7IswWmVUeSyIuC0IuC0wGNTsmZ/iWj0JCk5DNhqrgBRnRw2nKpk3x/TEFXNoJJQNYhYApKIQ5bNkyqrbA5v99hkuGwyHJbkyRlDOuWhoaNY4qlRLMkLX9GEjlBcQ0IX5nx56+Sv+kA0FoosodjvQLHfgUUIDLtd0w2c6h853J8KxofVihiNnlACPaEEPjw+seWMZQnpMD8o5FuSX22nLwI4krfbMlwMGHjxoMhnR3nB6Fbamg3CMQ1Pv9mMp99qQTRuLgx58EQQL7zfjo0XVszw3k2trA7vlF10Q+Bfnj6AV3YPDu6bLq3BFzY2zHgQTi1FFUuu3Wu1SHBZZRQ67fA5zV4It03hSTlRnhk4bLjYbR4LIgkdEdVAMBpHd3cM/oADLrsNdou5tjxDOs1WqakehS4rqpKfm6me+b6YiphqpOfLp+7L+fITk9DNUX+yLEGWJMgSeOyZAIsio6zAibICJ06vE3Gaqhno6ouhvSeGzt5oMuSfDvcjVb+fLIYw5+dHEzqA0c/pP5vzav24dU0dLp5fNOPn3DMlltDxP+8cx+ZtTQhGtWG3/8cLhxneiQAzuP/zb/djy56OQdtnOrinlpuKquYQWIdVhssqo8Jrgyc5bNBp5dI5RLOJLKUq2QOFDhl+KY5AwJVVS8gQZQN5yHx53XCYI1jiOoIJDcHkfPlQXAVwetUHXvg6O003EFYNRBI6LLIERZZgCAFDmAV/B3YMp8K8LJlDyZUBAT+1jaF/9KwWGZVFLlQWZV7zO67q6OwdOdz3RyYvcE+mfc19+PajezC33INbVtdh1Xmls+aiWkLV8fy7J/Dka00ZL75YFAnXX1KNb2z62Azs3fTimQydla4b+KenD2DrkOB+w8oa/OmG6Q/uidT8dVWHBHM4fMBpQcBphdduDoe3TcGyeERERPlMkU/Ply+HHYnkfPlIwiwUGUqOaBlYW8IcYs85voDZoRBRzd8XIMFtk1HlsyPgtMJmkaEbAroQ0A0BQwjoBqAZRrIOh3mbIQQMQ8AAoOrJn4WAPorQn/p+pPBPJrtVQU2JGzUlmYubReMawjENMdVAXNWRSH6NqwZiqo6Elvw5kfya+jl9X/Pn2JCf0/dN6CMulzcaR9tD+OFT+/Dwy0dx86paXLmkAtY8Pe/VdAN/3NWGJ15tRFdffNjtiixhw0WVWLe0AhfW+lHss8/AXk4vhnc6I1038OPfHsCrewcH95suq8WfXDVvWj6shThdnCquGbAk56+Xe+3wOyzw2BV4bFzajYiIaDLZFBk2p4wCp1koMqYNWZJO1dGfnC9vUyQ4Z+GSdEaq5kZCh24IcxSDx4YCpxU+x+jr64hkr3wq3J8O+hgx9Gu6Wd/nTKHfEEj+O50WZcks0umymX8vXngZzGm3TOmyckII8283IPTHVGPARQJ9QOA3EI5p2LKnHY0dg5fIa+uO4t9/9xEe23IMN1xai08sq4QrT5bD0w2BV/d24LEtx9DWHR12uywB6y8ox+1r56Ci0Im2/uHBPl/lx1+YpoQZ3Pfj1b2dg7ZPR3DXDfMkIarqUHVzqJ7TKqPUY0t/GLo4f52IiGhaSJIZzp3WwbUlTs+XN3squ2KJdBV7Z572ygthnqNEEjoSukiPAEwFdp/DMubzE0mSoEiAAgkY44plA8O9GfCHbBt4ESDZ0x/RDEQTOnqjGmwKg/x0kiQJVosEq0WG2zG6KHbzqlpsP3gKT77WhAMtfYNu6w4m8IsXD+PXrzfiuuXV+OQl1fC7bVOx61POMATePNCFR185huaucMb7rF5UijvWzUHtCCMn8h3DO2Wk6wZ+9Jv9eP2DwcH9llW1uOvjUxPc1QHD4YUAnFYFPrs5HN5jV+C1W2DP02FBREREueR0bQnzVDK1JF0obha+iyR751VjQK+8NbfnyseTgT2mGrBbZbjtFlQ5zPMUn8MCywyNOFBkacyhP6Eb6I9p6I9p6E2uOsAgn70kScKKc4qxfEERPmjqxZOvNeHdw92D7hOKanji1Ub89s1mbLyoEjdeVosSv2OG9nhshBDYeegUHn75KI60hTLeZ/mCInz2irmYV+Gd5r3LLgzvNIymG/jR5v3Ytm9IcF9dh7uunDtpB3MhBOK6QEzVEdUMKJI5HL7EY4PfYU0Oh1e4XA0REVGWG7gkXZWwI6IaCMU1hOIa+uLm/N/+mLm2vNmDnxvL0am6kV69wpocal7qsSHgtMLvsORsjR2bIqPYbUOx28Ygn0MkScL59QU4v74AR9qCePL1Jmzb1zloaby4auC/3z6O53a0Yt3ictyyuhbVxdnbS737aA8efvnosBEFKUvmFuBzV8zFwhr/NO9ZdmJ4p0HM4L4P2/Z1Ddp+25o6fO6KiQf31HJuUVUfNEeu0GVNB3Yu50ZERJS7JEmC22Z+npd5k4Xv4jpCybXlI8lwmFqOzmGRs6pXXjdSy03q5lKU1mThOZcZ2J3WMY5rz3IM8rlpXoUX37h1EVpPRbB5WxNefr8dmn46xWu6wEu72vDH99uw8twS3LqmDvMrfTO4x4N92NKHh18+iveP9mS8/dwaP+68ci4Wzxm+HOBsxvBOaZpu4IdP7cMb+yc3uGsDlnPTDXNumNtuQaVdgS8Z2PlhQERElJ9sigybS0ZBcm35SEJHKFnBPhjXENUM9MXMCvbOZJCf7l75VOG5cEKHYQi4BxSe8zsscI+y8FyuO1OQjzDIZ6WqIhf+4vpzcce6uXj6zWY8v/MEYgk9fbsQwBv7u/DG/i5cOK8At66ux+I5gRn72x1pC+KRl49i+8FTGW9vqPDis1fMxcXzC9m+MmB4JwBmcP/Hp/bhzSHB/fbL6/GZ9XPG9eYRQuBURIVuAE6rjEKnFX6nuQSNx67AlgPD5YiIiGjyDJwrX+61I6EZZpCPmyExop7ulU/1yE9VSEwVngsndGi6gMOqoNBpRYHLkh4NmC2jAWbCoCCvGeiPM8hns2KfHV/YOB+3ranH795uwe/eOY5QVBt0n11HerDrSA/Oqfbh1tV1WHFOMeRpqtXQ3BXGo68cGzYtN6W2xI3PXjEHK88tYVs6A4Z3gqqZPe5vHhgc3D+9th53rJtYcLcrMioKzDVO3TZlVi0fQ0RERGdms8gotMgodFlhCJEuetefnC8fVQ30pdaVt8pwWmRYJnjxP54M7DHNgMMiw2u3pHvYvTNYeC6b2Swyii0M8rnA57LiM+vn4qbLavH8zhN4+s1mnAomBt3no+P9+N4Te1FX6sbNq2px+fllE35fjaStO4rHtx7Dlt3tGde3ryh04jPr5mDN+WXMCaPA8D7LqZqBHzz5Ad7+8OSg7Z9eW4/PrJ87rucUQqA7osIiy6gKOFDls/MgTkRERGckSxK8dnOEXgXsiGsGgnHNXIouavbKd0c1GIaAPRnk7aMMiqlq+FHVgFUx5+RXeG3wJyvFczTg6DHI5wan3YIbL6vFdSuq8fLudmx+vQknhqyZ3tQZxj/99gAefeUYblpVi49fWAH7JNV0ONkXwxOvNuLF99qgZ0jtJX47bl87B1cuKZ+yCwf5iOF9FhspuN+xbg7uWDdn3M/bG9UgSxKq/XZUMrgTERHRONgtMuwWG4rdgO5P9sonzKAYipsF5XqiGqyKBIdFhtM6eISfliw8F00WnnNbZRT5HQg4LfA7LHDkWeG5mZApyPdFVfTFdQb5LGG1yNh4USU+fmEF3tjfiSdfa8LR9sHLsXX0xvCzZw/i8S3HsOnSGlyzvHrUa9AP1RNK4KnXm/DcjlaomjHs9gKPDbetqcPGiyph43twzBjeZylVM/D9X3+Adz4aHNw/s34OPr12/MG9L6bBEAI1ASeqA45ZPVeMiIiIJociS/A5LPA5LKjwmnPVQ3Ed4YSO3qiKqGrgZFgFIGCzyEhoBgAJLpuMUo8NhS4bfA4LXFYGyKnCIJ/dFFnCmkVlWH1eKd493I0nX2vCB029g+7TG1bx0B+P4snXm3Dt8mpsurQGAY9tVM8fjKj4zRvN+O+3WxBXh4d2j9OCW1bV4boV1XDYGNrHi+F9FlI1A//wq73Dqjx+dv0c3D6B4B6Ma0hoBmoCDtQwuBMREdEUkCQpuVa8ghIAmuFAOGH2xvfHzGH2XrsFhckh8bO98NxMGDHIxzREVGNQkLdJGSZC05SRJAkXzy/CxfOLsL+5D0++1jgsE0TiOp58vQnPvNWCq5ZW4KbLalFW4Mz4fJG4hmfeasFv32hGJK4Pu91pV3DDpTW4YWXtuHvz6TT+BmcZVTPw97/aix1D3qR3XjEXt11eP+7nTc0jq/LbUVvgZMEJIiIimhYWWYLfYYXfYUWlTyCuGbAqMs9FssTAIJ+qYzAwyPckVMhxFapFg9UKWBQJFlniBZdp8LFaP77zmQtwrCOEp15vwmt7OwYVlUtoBp7d3orf7zyBteeX4ZbVtagr9QAAYgkdz21vxVPbmtAfUYc9t90q47oV1bh5VR18Lut0vaS8x/A+iyRUHf/wqw+w49CQ4H7lXNy2pn7czxtJrtVa5XegvsDJKq1EREQ0IyRJ4lz2LHa6jsHpIN8TiuFkdxSyBCR0s06BZggImEO9LbIEqyylQ71FljjkfpLNKfPg6zefh8+un4vfvNGMl3a1DZqvbhgCr+xuxyu723HJwmKcW+PHf7/dgu4hVewB8+LL1RdX4dY1dSj02qfzZcwKDO+zRELV8b0n9uLdw92Dtn/+4/Nwy+q6cT9vTDWHqFX47KgvdMLKapFEREREdBapIB+wy/BJcbi8HuiQoeoCcd1AQjMQUXUkdAFNNxDXDIR0AT0Z7C0DAr0Z7mUoEhjsJ6Ci0IkvX3cOPr22Hs+81YLndrQiOmQo/NsfnhxW7BoAZFnCxy8sx+2Xz0FpwDFduzzrMLzPAlMV3OOaOWepzGtDfaETdguDOxERERGNjSKbdQwsluHRRNUNJHSBRDLQJ3SBuKYjmjCQMAxzVQHVgBbX00uSWVOhXpHTvfWcRjF6hV47/uSqBtyyug7PbW/FM2+1ZBwaDwCSBKw9vwx3rJuDyiLXNO/p7MPwnufiqo7vPb4X7x0ZHNzvvqoBN62qHffzqrqB7oiKMo8NcwpdcHKIGhERERFNMqsiw6oAbgw+1xRCQDVEOtAnNAPxZA99NKFDNQQ0wwz6qg4YQkCSkO6ltyZDvUXh/PqReJ1WfOryemy6tAYvvHcCv32jGV198fTtKz9Wgs+sm4P6Ms+M7aOmGzDE7Cl6yPCex+Kqju8+vge7jvQM2v6nGxpw42XjD+6abi7HUuy2or7QCReXeyAiIiKiaSRJEmyKBFuGKZuGEFCTvfVxzTCH4msGYpqOmGpAM8xtUVWHqpvD8GUJg3rqU733HIYPOGwKrr+kBtcsq8K2fZ04fjKCSxaWoKHSO2P7pOoG+mMaVF2gwGmdNR2JDO95KpYwg/v7RwcH9y9sbMANK8cf3HVDoCusotBlxZxCFzx2NiEiIiIiyh6yJMFukWC3yBhaM003kkPwdQMJLfW9GeTNoG/eFk6cnl+vDCial+q5n40Fmi2KjLWLy2d0H+KaGdoNAfgdCorcZgFE9yzpTGTyykNxVcc/P7VvWHD/4sb52LSyZtzPawb3BAqcFtQXOuHjWo1ERERElEMUWYJTVjL21GrpYfgDe+x1RFQz1KuGQFQ1oA6ZXz8w0Fs5DH9KxFQd/XEdEgCfw4Jitw3F7tnT457C9JVn4qqOf/nNfuxv6hu0/YufmI9Nl44/uBtC4GQ4AZ/dgtoCJwqcXK+RiIiIiPKHRZZgsSlwjWN+vaoLxFQdmmEurSbLHIY/GaLJla0USULAaUFJsqd9thbKZnjPI5G4hu89sXdYcP/fV8/HJy8Zf3AXQuBkWIXbpqAm4ECx2zbRXSUiIiIiyglnm1+fDvUDeuwjyWH4Gofhj5kQ5goCwZgGqyKhyG1DiduGIpcVtlka2lMY3vNEJK7h7p9ux97G3kHb/+yaBbhuRfW4n1cIgVMRFU6LjJqAE2VDJw4REREREc1SsiTBYVXgyDAoVTfMQnmpefUJzeAw/DMQQiCc0BGM63BYZJR6zdBe6LLCmuHCyWzE8J4HInENn//JO3jn4KlB2ycjuHdHVFhkGdUBB8q97HEnIiIiIhoNRZbgGucwfM0YPAzfapHgsMhwWpW8W7PeEALhuI5wQofDKqPCZ0+H9nx7rRPF8J4HZGn4MJ4/v3YBrlk+/uAOAL1RDbIkoSZgR6XPzjk6REREREQTNJpl7k732BuIqWaF9ahqLtcshIDDKsNhVWBXcncevW4IhBI6IgkdLquCSp8dxR4bCpwM7SNheM8DDpuC//rSctz903fwxocncddV8yYc3PtiGgwhUBNwosrvyNmDAhERERFRrhi4zN1AmiEQTmgIxXUEYxpCCQ3huIYeXcCq5FavvG4IBOPmxQiP3aypVeK2we+0zJopAuPF8J4nzAC/DI++0YKF9YEJPVcwpiGhGagJOFATcPBNREREREQ0gyyyBL/DCr/DCuETiGkGQnEdoYSOvqia7pUHBBwWs1felmW98ppuoD9uFvLz2hXUFiRDu8OSVfuZzRje84jTZsGKc4rRF9fG/RzhhI6oZqDKb0dtgTMnrt4REREREc0WkiTBaTXXqi8BoBkOhOIawgkdfTENkYSGUFxDXBewKeZ9HRZ5xs7rVd0c9q/qAj6HgkqfE8VuG7x2haF9jBjeKS2SMIfhVPkdqC9wcskKIiIiIqIsZ5ElBJxWBJxWVPrMCvZm1Xbt9Fz5uAoBAec09sonNAP9cQ26AfgcCoqTy7157Iyg48XfHAEAYqqO/piGSp8d9YVOLsdARERERJRjJClZ4d6moMRjg2YIhOIaQgnzXD8cn/pe+Zhm9rQDgM9hQYnbiiKXDS6bcpZH0tkwvBPimoHeqIYyrw31hc5hBTKIiIiIiCj3DOyVF8le+VBCRyiuoS+mIaYa6IolAAnpID/eXvlosjNQkSQEnBaUJHvaHVaG9snC8D7LqbqB7oiKMo8NcwpdfHMREREREeWhgb3ypR4bVN0cXh+K6+iPm73ywbgGVROwWSQ4RtErL4R5QaA/psGqSChy2VDiMUO7jR2Ck47hfRbTdLMqZbHbivpCJ4eyEBERERHNElZFRsApm73yyRAeTA6r74/r5s+xBCQJcFgVOC0yrMleeSGEOa8+ocOuyCj12tJz2jn9duowvM9SuiHQFVZR6LJiTqGLhSOIiIiIiGapgb3yZV47VN0cXh+O6+iLqYgk58yruoDVIkHVBZxWGeUeG0o8dhS6rCx2PQ2Y2GYhM7gnUOC0oL7QCZ+DzYCIiIiIiExWRUaBU0aB04pKYTfnyg/olXdaZBR7bChwWrm09DRiaptlDCFwMpyAz25BbYETBU7rTO8SERERERFlKVmS4LYpcCd75TVDQJbM7TS9GN5nESEEToZVeGwKagucKHbbZnqXiIiIiIgoh3B4/MxhNYFZIhXcnRYZ1QEnSj0M7kRERERERLmC4X0WEEKgO6LCpsioDjhQ7mVwJyIiIiIiyiUM77NAb1SDLEmoDthR6bND4vwUIiIiIiKinMLwnuf6YhoMIVDld6DK72BwJyIiIiIiykEM73ksGNOQ0AxU+R2oCThYEZKIiIiIiChHMbznqXBCR1QzUOm3o7bAyfUXiYiIiIiIchiXistDCc2AbgCVPjvqC5xczoGIiIiIiCjHsec9D0mShAqvDXMKnbAq/BMTERERERHlOia7PCPLEsq9NtQXOmGz8M9LRERERESUDzhsPo9IkoS6AifsFhl2BnciIiIiIqK8wfCeZ3wO/kmJiIiIiIjyDbtniYiIiIiIiLIcwzsRERERERFRlmN4JyIiIiIiIspyDO9EREREREREWY7hnYiIiIiIiCjLMbwTERERERERZTmGdyIiIiIiIqIsx/BORERERERElOUY3omIiIiIiIiyXFaH93g8jr/+679GZWUlnE4nVqxYgZdeeumsj/voo4/w1a9+FStXroTD4YAkSWhsbJz6HSYiIiIiIiKaAlkd3u+66y788z//M+644w7867/+KxRFwdVXX41t27ad8XFvvfUW/u3f/g3BYBDnnnvuNO0tERERERER0dTI2vC+fft2/OpXv8IPfvAD3H///fjiF7+IV155BXV1dfj6179+xsd+8pOfRG9vL/bu3Ys77rhjmvaYiIiIiIiIaGpkbXjfvHkzFEXBF7/4xfQ2h8OBu+++G2+99RZaWlpGfGxhYSG8Xu907CYRERERERHRlMva8L5r1y4sWLAAPp9v0Pbly5cDAN5///0Z2CsiIiIiIiKi6WeZ6R0YSVtbGyoqKoZtT207ceLElP3fnZ2d6OrqGrTt8OHDAABN06BpWvp7XdfTPxPlOrZpyjds05Rv2KYp37BNU77J1KYnq31nbXiPRqOw2+3DtjscjvTtU+VnP/sZ7rvvvoy3BYNB9Pb2AgB0XUcoFAIAKIoyZftDNF3YpinfsE1TvmGbpnzDNk35JlObDgaDk/LcWRvenU4n4vH4sO2xWCx9+1T50pe+hFtuuWXQtsOHD2PTpk3wer0IBAIATl9B8fv9sFiy9ldJNGps05Rv2KYp37BNU75hm6Z8k6lNT1Y9tqx9h1RUVKC1tXXY9ra2NgBAZWXllP3fpaWlKC0tzXibxWIZdGBRFGXYNqJcxjZN+YZtmvIN2zTlG7ZpyjdD2/Rkte2sLVi3ZMkSHDx4EP39/YO2v/POO+nbiYiIiIiIiGaDrA3vN998M3RdxwMPPJDeFo/H8eCDD2LFihWoqakBADQ3N+PDDz+cqd0kIiIiIiIimnJZOzZlxYoVuOWWW/CNb3wDnZ2daGhowC9/+Us0NjbiF7/4Rfp+n/vc5/Dqq69CCJHe1tfXh3//938HALzxxhsAgJ/85CcIBAIIBAL48pe/PL0vhoiIiIiIiGgCsja8A8DDDz+Me++9F4888gh6enqwePFiPPvss1izZs0ZH9fT04N777130LZ/+qd/AgDU1dUxvBMREREREVFOyerw7nA4cP/99+P+++8f8T5bt24dtq2+vn5QTzwRERERERFRLsvaOe9EREREREREZGJ4JyIiIiIiIspyDO9EREREREREWY7hnYiIiIiIiCjLMbwTERERERERZTmGdyIiIiIiIqIsl9VLxWWjB6+8EuU227DtH//BD3DBpz8NANj9+ON46RvfGPE5/rKpKf39I9dcg44PPsh4v8W3346r/vEfAQDte/fi0WuvHfE5P/Pssyg//3wAwIt/8zfY88QTGe9XtmgRPvvcc+mff1xXN+Jz8jXN3te06LbbsPFHPwKQP68pH/9OfE2je01FCxfm3WvKx78TX9PoX9Nd776b/j5fXlM+/p34mkb3mm5/5hnYa2oA5M9ryse/E1/T6F/TebfeCgDY+8QTePnv/s7cl0RixMeMBXveiYiIiIiIiLKcJIQQM70TuWDfvn1YtGgRPvjgA5x33nkAAE3T0Nvbi0AgAIuFgxgo97FNU75hm6Z8wzZN+YZtmvJNpjadKUuOB3veiYiIiIiIiLIcwzsRERERERFRlmN4JyIiIiIiIspyDO9EREREREREWY7hnYiIiIiIiCjLMbwTERERERERZTmGdyIiIiIiIqIsx/BORERERERElOUY3omIiIiIiIiyHMM7ERERERERUZZjeCciIiIiIiLKcgzvRERERERERFmO4Z2IiIiIiIgoy1lmegdyRTweBwAcPnw4vU3TNASDQXi9Xlgs/FVS7mObpnzDNk35hm2a8g3bNOWbTG06lSFTmXK8+A4ZpZaWFgDApk2bZnZHiIiIiIiIKOe0tLRg6dKl4368JIQQk7g/eau3txevvvoqampqYLfbAZhXUDZt2oRnnnkGDQ0NM7yHRBPHNk35hm2a8g3bNOUbtmnKN5nadDweR0tLCy6//HIEAoFxPzd73kcpEAjg+uuvz3hbQ0MDzjvvvGneI6KpwzZN+YZtmvIN2zTlG7ZpyjdD2/REetxTWLCOiIiIiIiIKMsxvBMRERERERFlOYZ3IiIiIiIioizH8D4BJSUl+Pa3v42SkpKZ3hWiScE2TfmGbZryDds05Ru2aco3U9mmWW2eiIiIiIiIKMux552IiIiIiIgoyzG8ExEREREREWU5hnciIiIiIiKiLMfwTkRERERERJTlGN7HIR6P46//+q9RWVkJp9OJFStW4KWXXprp3SIal61bt0KSpIz/3n777ZnePaIzCoVC+Pa3v42NGzeisLAQkiThoYceynjfAwcOYOPGjfB4PCgsLMRnP/tZdHV1Te8OE53FaNv0XXfdlfG4vXDhwunfaaIR7NixA1/+8pdx3nnnwe12o7a2FrfeeisOHjw47L48RlMuGG2bnqpjtGVCj56l7rrrLmzevBn33HMP5s+fj4ceeghXX301tmzZglWrVs307hGNy//5P/8Hy5YtG7StoaFhhvaGaHROnjyJ7373u6itrcUFF1yArVu3Zrzf8ePHsWbNGvj9fnz/+99HKBTCj3/8Y+zduxfbt2+HzWab3h0nGsFo2zQA2O12/L//9/8GbfP7/VO8h0Sj98Mf/hBvvPEGbrnlFixevBjt7e34yU9+gqVLl+Ltt9/GokWLAPAYTbljtG0amKJjtKAxeeeddwQAcf/996e3RaNRMW/ePHHppZfO4J4Rjc+WLVsEAPHUU0/N9K4QjVksFhNtbW1CCCF27NghAIgHH3xw2P3+7M/+TDidTtHU1JTe9tJLLwkA4j//8z+na3eJzmq0bfrOO+8Ubrd7mveOaGzeeOMNEY/HB207ePCgsNvt4o477khv4zGacsVo2/RUHaM5bH6MNm/eDEVR8MUvfjG9zeFw4O6778Zbb72FlpaWGdw7ookJBoPQNG2md4No1Ox2O8rLy896v9/85je49tprUVtbm9525ZVXYsGCBXjyySencheJxmS0bTpF13X09/dP4R4Rjd/KlSuH9ZrPnz8f5513Hg4cOJDexmM05YrRtumUyT5GM7yP0a5du7BgwQL4fL5B25cvXw4AeP/992dgr4gm7vOf/zx8Ph8cDgfWrVuHnTt3zvQuEU2K1tZWdHZ24uKLLx522/Lly7Fr164Z2CuiiYtEIvD5fPD7/SgsLMSf//mfIxQKzfRuEZ2REAIdHR0oLi4GwGM05b6hbTplKo7RnPM+Rm1tbaioqBi2PbXtxIkT071LRBNis9lw00034eqrr0ZxcTH279+PH//4x1i9ejXefPNNXHjhhTO9i0QT0tbWBgAjHru7u7sRj8dht9une9eIxq2iogJf//rXsXTpUhiGgT/84Q/42c9+ht27d2Pr1q2wWHiKR9npscceQ2trK7773e8C4DGact/QNg1M3TGaR/YxikajGQ8eDocjfTtRLlm5ciVWrlyZ/vmTn/wkbr75ZixevBjf+MY38Ic//GEG945o4lLH5bMdu3liSLnkBz/4waCfP/WpT2HBggX45je/ic2bN+NTn/rUDO0Z0cg+/PBD/Pmf/zkuvfRS3HnnnQB4jKbclqlNA1N3jOaw+TFyOp2Ix+PDtsdisfTtRLmuoaEB119/PbZs2QJd12d6d4gmJHVc5rGb8t1Xv/pVyLKMP/7xjzO9K0TDtLe345prroHf70/XkAJ4jKbcNVKbHslkHKPZ8z5GFRUVaG1tHbY9NeSnsrJyuneJaErU1NQgkUggHA4Pq/FAlEtSQzFTx+mB2traUFhYyB4dygtOpxNFRUXo7u6e6V0hGqSvrw+f+MQn0Nvbi9dff33Q+TKP0ZSLztSmRzIZx2j2vI/RkiVLcPDgwWFVA99555307UT54OjRo3A4HPB4PDO9K0QTUlVVhZKSkoxFGLdv387jNuWNYDCIkydPoqSkZKZ3hSgtFovhuuuuw8GDB/Hss8/iYx/72KDbeYymXHO2Nj2SyThGM7yP0c033wxd1/HAAw+kt8XjcTz44INYsWIFampqZnDviMauq6tr2Lbdu3fjd7/7Ha666irIMg8TlPtuuukmPPvss4OW83z55Zdx8OBB3HLLLTO4Z0RjF4vFEAwGh23/3ve+ByEENm7cOAN7RTScruu47bbb8NZbb+Gpp57CpZdemvF+PEZTrhhNm57KY7QkhBDjfvQsdeutt+Lpp5/GV7/6VTQ0NOCXv/wltm/fjpdffhlr1qyZ6d0jGpP169fD6XRi5cqVKC0txf79+/HAAw/AarXirbfewrnnnjvTu0h0Rj/5yU/Q29uLEydO4Oc//zluvPHG9CoJX/nKV+D3+9HS0oILL7wQgUAAf/EXf4FQKIT7778f1dXV2LFjB4dkUlY5W5vu6enBhRdeiNtvvx0LFy4EALzwwgv4/e9/j40bN+K5557jhVfKCvfccw/+9V//Fddddx1uvfXWYbd/5jOfAQAeoylnjKZNNzY2TtkxmuF9HGKxGO699148+uij6OnpweLFi/G9730PGzZsmOldIxqzf/u3f8Njjz2Gw4cPo7+/HyUlJbjiiivw7W9/Gw0NDTO9e0RnVV9fj6ampoy3HTt2DPX19QCAffv24Wtf+xq2bdsGm82Ga665Bv/0T/+EsrKyadxborM7W5sOBAL4yle+grfffhsnTpyArutoaGjAHXfcgb/8y7+E1Wqd5j0mymzt2rV49dVXR7x9YAzhMZpywWjadG9v75QdoxneiYiIiIiIiLIcx1QRERERERERZTmGdyIiIiIiIqIsx/BORERERERElOUY3omIiIiIiIiyHMM7ERERERERUZZjeCciIiIiIiLKcgzvRERERERERFmO4Z2IiIiIiIgoyzG8ExEREREREWU5hnciIiIiIiKiLMfwTkRElEMeeughSJKExsbGaf+/v/Od70CSpHE/vrGxEZIk4aGHHpq8nSIiIpolGN6JiIhoUj3++OP4v//3/870bhAREeUVy0zvABEREeWXxx9/HB988AHuueeeQdvr6uoQjUZhtVpnZseIiIhyGMM7ERERTQtJkuBwOGZ6N4iIiHISh80TERHlgeeffx6rV6+G2+2G1+vFNddcg3379g26z549e3DXXXdh7ty5cDgcKC8vx5/8yZ/g1KlTw55v27ZtWLZsGRwOB+bNm4f//M//HNV+rF27Fs899xyampogSRIkSUJ9fT2AzHPe77rrLng8HjQ3N+Paa6+Fx+NBVVUVfvrTnwIA9u7di/Xr18PtdqOurg6PP/74sP+zt7cX99xzD2pqamC329HQ0IAf/vCHMAxjlL89IiKi7MeedyIiohz3yCOP4M4778SGDRvwwx/+EJFIBD//+c+xatUq7Nq1Kx2eX3rpJRw9ehSf//znUV5ejn379uGBBx7Avn378Pbbb6eL0e3duxdXXXUVSkpK8J3vfAeapuHb3/42ysrKzrov3/zmN9HX14fjx4/jX/7lXwAAHo/njI/RdR2f+MQnsGbNGvzoRz/CY489hi9/+ctwu9345je/iTvuuAM33ngj/uM//gOf+9zncOmll2LOnDkAgEgkgssvvxytra34X//rf6G2thZvvvkmvvGNb6CtrY1z74mIKH8IIiIiyhkPPvigACCOHTsmhBAiGAyKQCAgvvCFLwy6X3t7u/D7/YO2RyKRYc/3xBNPCADitddeS2/btGmTcDgcoqmpKb1t//79QlEUMZpTh2uuuUbU1dUN237s2DEBQDz44IPpbXfeeacAIL7//e+nt/X09Ain0ykkSRK/+tWv0ts//PBDAUB8+9vfTm/73ve+J9xutzh48OCg/+tv/uZvhKIoorm5+az7S0RElAs4bJ6IiCiHvfTSS+jt7cXtt9+OkydPpv8pioIVK1Zgy5Yt6fs6nc7097FYDCdPnsQll1wCAHjvvfcAmL3gL7zwAjZt2oTa2tr0/c8991xs2LBhyl7Hn/7pn6a/DwQCOOecc+B2u3Hrrbemt59zzjkIBAI4evRoettTTz2F1atXo6CgYNDrv/LKK6HrOl577bUp22ciIqLpxGHzREREOezQoUMAgPXr12e83efzpb/v7u7Gfffdh1/96lfo7OwcdL++vj4AQFdXF6LRKObPnz/suc455xz8/ve/n6xdT3M4HCgpKRm0ze/3o7q6eti68n6/Hz09PemfDx06hD179gx7fMrQ10lERJSrGN6JiIhyWKoo2yOPPILy8vJht1sspz/qb731Vrz55pv4q7/6KyxZsgQejweGYWDjxo0zWtxNUZQxbRdCpL83DAMf//jH8fWvfz3jfRcsWDDxHSQiIsoCDO9EREQ5bN68eQCA0tJSXHnllSPer6enBy+//DLuu+8+fOtb30pvT/Xcp5SUlMDpdA7bDgAfffTRqPZpaG/5VJo3bx5CodAZXzsREVE+4Jx3IiKiHLZhwwb4fD58//vfh6qqw27v6uoCcLoXe2CvNYBh1dgVRcGGDRvwzDPPoLm5Ob39wIEDeOGFF0a1T263Oz0Mf6rdeuuteOuttzLuW29vLzRNm5b9ICIimmrseSciIsphPp8PP//5z/HZz34WS5cuxac+9SmUlJSgubkZzz33HC677DL85Cc/gc/nSy/Fpqoqqqqq8OKLL+LYsWPDnvO+++7DH/7wB6xevRpf+tKXoGka/v3f/x3nnXce9uzZc9Z9uuiii/DrX/8aX/va17Bs2TJ4PB5cd911U/Hy8Vd/9Vf43e9+h2uvvRZ33XUXLrroIoTDYezduxebN29GY2MjiouLp+T/JiIimk4M70RERDnu05/+NCorK/GP//iPuP/++xGPx1FVVYXVq1fj85//fPp+jz/+OL7yla/gpz/9KYQQuOqqq/D888+jsrJy0PMtXrwYL7zwAr72ta/hW9/6Fqqrq3Hfffehra1tVOH9S1/6Et5//308+OCD+Jd/+RfU1dVNWXh3uVx49dVX8f3vfx9PPfUUHn74Yfh8PixYsAD33Xcf/H7/lPy/RERE000SQ8fPEREREREREVFW4Zx3IiIiIiIioizH8E5ERERERESU5RjeiYiIiIiIiLIcwzsRERERERFRlmN4JyIiIiIiIspyDO9EREREREREWY7hnYiIiIiIiCjLMbwTERERERERZTmGdyIiIiIiIqIsx/BORERERERElOUY3omIiIiIiIiyHMM7ERERERERUZZjeCciIiIiIiLKcgzvRERERERERFmO4Z2IiIiIiIgoy/1/dSvBDsDa1p0AAAAASUVORK5CYII=\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def mc_predict(model, a, idx, n=30):\n", " samples = [predict(model, a, idx, training=True)[0] for _ in range(n)]\n", " samples = np.stack(samples)\n", " return samples.mean(0), np.quantile(samples, [0.1, 0.9], axis=0)\n", "\n", "sample_idx = test_idx[:40]\n", "mc_mean, mc_q = mc_predict(base_model, data, sample_idx, n=30)\n", "local = int(np.argmax(data[\"Y\"][sample_idx].max(axis=(1, 2))))\n", "t = np.arange(1, HORIZON + 1)\n", "ref = data[\"Y\"][sample_idx[local], :, 0]\n", "fig, ax = plt.subplots(figsize=(8.5, 3.8))\n", "ax.fill_between(t, mc_q[0, local, :, 0], mc_q[1, local, :, 0], color=\"#6baed6\", alpha=0.28, label=\"80% MC interval\")\n", "ax.plot(t, mc_mean[local, :, 0], color=\"#1f66b1\", lw=2.2, label=\"PADR-Net mean\")\n", "ax.plot(t, ref, color=\"#222\", lw=2.0, label=\"reference\")\n", "ax.axhline(FLOOD_THRESHOLD, color=\"#8b1e1e\", ls=\"--\", lw=1.2)\n", "ax.set_xlabel(\"lead time\"); ax.set_ylabel(\"depth (m)\")\n", "ax.set_title(\"MC-dropout uncertainty\"); ax.legend()\n", "fig.tight_layout(); plt.show()\n" ] }, { "cell_type": "markdown", "id": "6b113059", "metadata": {}, "source": [ "---\n", "\n", "## 9. Rainfall-Intensification Stress Test\n", "\n", "We perturb rainfall intensity and check whether predicted peak depth and\n", "exceedance probability respond monotonically.\n" ] }, { "cell_type": "code", "execution_count": 14, "id": "e274aff9", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:48:08.750035Z", "iopub.status.busy": "2026-06-08T17:48:08.750035Z", "iopub.status.idle": "2026-06-08T17:48:08.953209Z", "shell.execute_reply": "2026-06-08T17:48:08.953209Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "x1.00: ref=0.193 pred=0.138 P(exceed)=0.632\n", "x1.25: ref=0.271 pred=0.190 P(exceed)=0.845\n", "x1.50: ref=0.301 pred=0.204 P(exceed)=0.889\n" ] } ], "source": [ "scenario_events, factors = [], []\n", "for factor in [1.0, 1.25, 1.50]:\n", " ev = make_dataset(n=100, seed=int(100 * factor), intensify=factor)\n", " scenario_events.extend(ev); factors.extend([factor] * len(ev))\n", "scenario = arrays(scenario_events)\n", "factors = np.array(factors)\n", "spred, sprob, _ = predict(base_model, scenario, np.arange(len(factors)))\n", "rows = []\n", "for factor in [1.0, 1.25, 1.50]:\n", " mask = factors == factor\n", " rows.append({\n", " \"factor\": factor,\n", " \"reference\": float(scenario[\"Y\"][mask].max(axis=(1, 2)).mean()),\n", " \"pred\": float(spred[mask].max(axis=(1, 2)).mean()),\n", " \"exceed\": float((sprob[mask] > 0.5).mean()),\n", " })\n", "for r in rows:\n", " print(f\"x{r['factor']:.2f}: ref={r['reference']:.3f} pred={r['pred']:.3f} P(exceed)={r['exceed']:.3f}\")\n" ] }, { "cell_type": "code", "execution_count": 15, "id": "7ca416ac", "metadata": { "execution": { "iopub.execute_input": "2026-06-08T17:48:08.955483Z", "iopub.status.busy": "2026-06-08T17:48:08.955483Z", "iopub.status.idle": "2026-06-08T17:48:09.123163Z", "shell.execute_reply": "2026-06-08T17:48:09.123163Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, axes = plt.subplots(1, 2, figsize=(10.5, 3.6))\n", "f = [r[\"factor\"] for r in rows]\n", "axes[0].plot(f, [r[\"reference\"] for r in rows], \"o-\", lw=2, label=\"reference\")\n", "axes[0].plot(f, [r[\"pred\"] for r in rows], \"o-\", lw=2, label=\"PADR-Net\")\n", "axes[0].set_xlabel(\"rainfall multiplier\"); axes[0].set_ylabel(\"mean peak depth (m)\")\n", "axes[0].set_title(\"Stress-test peak response\"); axes[0].legend()\n", "axes[1].plot(f, [r[\"exceed\"] for r in rows], \"o-\", lw=2, color=\"#8b1e1e\")\n", "axes[1].set_xlabel(\"rainfall multiplier\"); axes[1].set_ylabel(\"fraction prob. > 0.5\")\n", "axes[1].set_title(\"Exceedance response\")\n", "fig.tight_layout(); plt.show()\n" ] }, { "cell_type": "markdown", "id": "8c1c69a4", "metadata": {}, "source": [ "---\n", "\n", "## Exercises\n", "\n", "### Exercise 1: Harder transfer\n", "\n", "Hold out one region and one later period simultaneously. Which target\n", "region has the largest performance drop relative to the baseline?\n", "\n", "### Exercise 2: Warning threshold operations\n", "\n", "Use the threshold curve to choose a threshold maximizing `TSS`, then\n", "recompute CSI and mass bias at that threshold.\n", "\n", "### Exercise 3: Uncertainty screening\n", "\n", "Flag events whose MC-dropout interval width is above the 90th\n", "percentile. Are those events concentrated in one region?\n", "\n", "### Exercise 4: Real scenario forcing\n", "\n", "Replace the synthetic storm multipliers with real rainfall ensemble or\n", "climate perturbation members. The stress-test code remains unchanged if\n", "`X`, `S`, and `Y` keep the PADR-Net shapes.\n" ] }, { "cell_type": "markdown", "id": "5ba3ff31", "metadata": {}, "source": [ "---\n", "\n", "## Summary\n", "\n", "This advanced workflow turns PADR-Net into a compact experiment suite:\n", "\n", "1. baseline temporal evaluation;\n", "2. leave-one-region-out transfer;\n", "3. physics-loss ablation;\n", "4. threshold calibration;\n", "5. MC-dropout uncertainty;\n", "6. rainfall-intensification stress testing.\n", "\n", "These diagnostics make PADR-Net results easier to defend in papers and\n", "operational reports.\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.9.13" } }, "nbformat": 4, "nbformat_minor": 5 }