{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "p3-00-fknmxz",
   "metadata": {},
   "source": [
    "# Phase 3 — Experiment 1: DCCE\n",
    "## *Beyond WhAM* · CS 297 Final Paper · April 2026\n",
    "\n",
    "---\n",
    "\n",
    "This notebook trains and evaluates the **Dual-Channel Contrastive Encoder (DCCE)** — the core contribution of this paper. DCCE is purpose-built around the known biological decomposition of sperm whale codas into two independent information channels (Leitão et al., 2023; Beguš et al., 2024):\n",
    "\n",
    "| Channel | Biological signal | DCCE encoder | Input |\n",
    "|---|---|---|---|\n",
    "| **Rhythm** | Coda type / click timing pattern | 2-layer GRU | ICI sequence (length 9) |\n",
    "| **Spectral** | Social / individual identity | Small CNN | Mel-spectrogram (64 × 128) |\n",
    "\n",
    "The two channel embeddings are fused and trained with a **cross-channel contrastive loss**: the rhythm representation of coda A and the spectral representation of a *different* coda B from the **same social unit** form a positive pair. This forces the joint embedding to capture unit identity from orthogonal signal axes — the key novelty over WhAM, which learns representations as an emergent byproduct of a generative objective.\n",
    "\n",
    "### Training objective\n",
    "```\n",
    "L = L_contrastive(z)  +  λ1 · L_type(r_emb)  +  λ2 · L_id(s_emb)\n",
    "```\n",
    "- **L_contrastive**: NT-Xent (SimCLR, Chen et al. 2020) on the fused embedding z; τ=0.07\n",
    "- **L_type**: cross-entropy on r_emb → coda type (22 classes) — rhythm supervision signal\n",
    "- **L_id**: cross-entropy on s_emb → individual ID (762 labelled codas only) — spectral supervision\n",
    "\n",
    "### Comparison targets (from Phases 1–2)\n",
    "| Task | Target | Source |\n",
    "|---|---|---|\n",
    "| Social Unit Macro-F1 | > **0.895** | WhAM L19 (best layer, Phase 2) |\n",
    "| Individual ID Macro-F1 | > **0.454** | WhAM L10 (Phase 1) |\n",
    "| Coda Type Macro-F1 | > **0.931** | Raw ICI baseline (1A) |\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "p3-01-bwpgqh",
   "metadata": {},
   "source": [
    "## 1. Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "363105f0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/miniconda3/lib/python3.13/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "All dependencies available.\n"
     ]
    }
   ],
   "source": [
    "import subprocess, sys\n",
    "\n",
    "def ensure_installed(package, pip_name=None):\n",
    "    try:\n",
    "        __import__(package)\n",
    "    except ImportError:\n",
    "        print(f\"Installing {pip_name or package}...\")\n",
    "        subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", pip_name or package, \"-q\"])\n",
    "\n",
    "ensure_installed(\"torch\", \"torch\")\n",
    "ensure_installed(\"librosa\")\n",
    "ensure_installed(\"umap\", \"umap-learn\")\n",
    "print(\"All dependencies available.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "p3-02-nghvov",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Device: mps\n",
      "PyTorch: 2.8.0\n"
     ]
    }
   ],
   "source": [
    "import os, warnings, time\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "from torch.utils.data import Dataset, DataLoader, WeightedRandomSampler\n",
    "import librosa\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.metrics import f1_score, accuracy_score, classification_report\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "%matplotlib inline\n",
    "plt.rcParams.update({\"figure.dpi\": 120, \"font.size\": 11})\n",
    "\n",
    "# Notebook lives in notebooks/; project root is one level up\n",
    "BASE   = os.path.abspath(os.path.join(os.getcwd(), \"..\"))\n",
    "DATA   = os.path.join(BASE, \"datasets\")\n",
    "AUDIO  = os.path.join(DATA, \"dswp_audio\")\n",
    "FIGS   = os.path.join(BASE, \"figures\", \"phase3\")\n",
    "os.makedirs(FIGS, exist_ok=True)\n",
    "\n",
    "UNIT_COLORS = {\"A\": \"#4C72B0\", \"D\": \"#DD8452\", \"F\": \"#55A868\"}\n",
    "SEED = 42\n",
    "torch.manual_seed(SEED); np.random.seed(SEED)\n",
    "\n",
    "DEVICE = (\"mps\" if torch.backends.mps.is_available()\n",
    "          else \"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "print(f\"Device: {DEVICE}\")\n",
    "print(f\"PyTorch: {torch.__version__}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "p3-03-noppii",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Clean codas         : 1383\n",
      "IDN-labeled codas   : 762  (12 individuals)\n",
      "Train/test split    : 1106 / 277\n",
      "ID train/test split : 609 / 153\n"
     ]
    }
   ],
   "source": [
    "# ── Load labels and pre-computed features ─────────────────────────────────────\n",
    "from sklearn.model_selection import StratifiedShuffleSplit\n",
    "\n",
    "df = pd.read_csv(os.path.join(DATA, \"dswp_labels.csv\"))\n",
    "df[\"ici_list\"] = df[\"ici_sequence\"].apply(\n",
    "    lambda s: [float(x) for x in s.split(\"|\")] if isinstance(s, str) and s else [])\n",
    "\n",
    "df_clean = df[df[\"is_noise\"] == 0].copy().reset_index(drop=True)\n",
    "\n",
    "df_id_all = df_clean[df_clean[\"individual_id\"] != \"0\"].copy()\n",
    "id_counts = df_id_all[\"individual_id\"].value_counts()\n",
    "df_id = df_id_all[df_id_all[\"individual_id\"].isin(\n",
    "    id_counts[id_counts > 1].index)].copy().reset_index(drop=True)\n",
    "\n",
    "# Generate train/test splits (Phase 1 didn't provide valid .npy files)\n",
    "def make_split(data, stratify_col, test_size=0.2, seed=SEED):\n",
    "    sss = StratifiedShuffleSplit(n_splits=1, test_size=test_size, random_state=seed)\n",
    "    idx = np.arange(len(data))\n",
    "    train_idx, test_idx = next(sss.split(idx, data[stratify_col]))\n",
    "    return train_idx, test_idx\n",
    "\n",
    "train_idx, test_idx = make_split(df_clean, \"unit\")\n",
    "train_id_idx, test_id_idx = make_split(df_id, \"individual_id\")\n",
    "\n",
    "df_train = df_clean.iloc[train_idx].reset_index(drop=True)\n",
    "df_test  = df_clean.iloc[test_idx].reset_index(drop=True)\n",
    "df_id_train = df_id.iloc[train_id_idx].reset_index(drop=True)\n",
    "df_id_test  = df_id.iloc[test_id_idx].reset_index(drop=True)\n",
    "\n",
    "# Note: X_mel_all will be computed in next cell from full 2D mel-spectrograms\n",
    "print(f\"Clean codas         : {len(df_clean)}\")\n",
    "print(f\"IDN-labeled codas   : {len(df_id)}  ({df_id['individual_id'].nunique()} individuals)\")\n",
    "print(f\"Train/test split    : {len(df_train)} / {len(df_test)}\")\n",
    "print(f\"ID train/test split : {len(df_id_train)} / {len(df_id_test)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "p3-04-sdvatu",
   "metadata": {},
   "source": [
    "---\n",
    "## 2. Data Pipeline\n",
    "\n",
    "### ICI sequences and mel-spectrograms\n",
    "\n",
    "The DCCE needs two input representations per coda:\n",
    "1. **ICI vector** (9d) — already in labels; zero-padded, StandardScaler normalised\n",
    "2. **Mel-spectrogram** (64 × 128) — loaded from WAV, fixed time window\n",
    "\n",
    "For the spectral encoder we use the full 2D mel-spectrogram (not mean-pooled), so the CNN can exploit temporal structure across clicks within a coda. Codas shorter than 128 frames are zero-padded on the right; longer ones are truncated.\n",
    "\n",
    "### Cross-channel contrastive pairs\n",
    "\n",
    "During training, positive pairs are constructed as:\n",
    "- (rhythm_A, spectral_B) where A ≠ B but same social unit\n",
    "- This forces the model to learn *unit-level* structure from both channels independently\n",
    "\n",
    "For a batch of N codas we draw N matched-unit partners, giving 2N views for the NT-Xent loss.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "p3-05-hdwocf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ICI matrix shape    : (1383, 9)  (scaled)\n",
      "Mel full loaded     : (1383, 64, 128)\n"
     ]
    }
   ],
   "source": [
    "# ── ICI feature matrix ────────────────────────────────────────────────────────\n",
    "MAX_ICI = 9\n",
    "\n",
    "def build_ici_matrix(data):\n",
    "    X = np.zeros((len(data), MAX_ICI), dtype=np.float32)\n",
    "    for i, row in enumerate(data.itertuples()):\n",
    "        for j, v in enumerate(row.ici_list[:MAX_ICI]):\n",
    "            X[i, j] = v\n",
    "    return X\n",
    "\n",
    "X_ici_all = build_ici_matrix(df_clean)\n",
    "scaler_ici = StandardScaler()\n",
    "X_ici_all  = scaler_ici.fit_transform(X_ici_all).astype(np.float32)\n",
    "print(f\"ICI matrix shape    : {X_ici_all.shape}  (scaled)\")\n",
    "\n",
    "# ── Mel-spectrograms (load from WAV for full 2D) ──────────────────────────────\n",
    "N_MELS    = 64\n",
    "FMAX      = 8000\n",
    "N_FRAMES  = 128   # fixed time dimension — pad/truncate\n",
    "\n",
    "mel_path = os.path.join(DATA, \"X_mel_full.npy\")\n",
    "if os.path.exists(mel_path):\n",
    "    X_mel_full = np.load(mel_path)\n",
    "    print(f\"Mel full loaded     : {X_mel_full.shape}\")\n",
    "else:\n",
    "    print(\"Computing 2D mel-spectrograms for all clean codas (takes ~4-5 min)...\")\n",
    "    X_mel_full = np.zeros((len(df_clean), N_MELS, N_FRAMES), dtype=np.float32)\n",
    "    for i, row in enumerate(df_clean.itertuples()):\n",
    "        y, sr = librosa.load(os.path.join(AUDIO, f\"{row.coda_id}.wav\"),\n",
    "                             sr=None, mono=True)\n",
    "        mel = librosa.feature.melspectrogram(y=y, sr=sr, n_mels=N_MELS, fmax=FMAX)\n",
    "        mel_db = librosa.power_to_db(mel, ref=np.max).astype(np.float32)\n",
    "        T = mel_db.shape[1]\n",
    "        if T >= N_FRAMES:\n",
    "            X_mel_full[i] = mel_db[:, :N_FRAMES]\n",
    "        else:\n",
    "            X_mel_full[i, :, :T] = mel_db\n",
    "    np.save(mel_path, X_mel_full)\n",
    "    print(f\"Saved: {mel_path}  shape={X_mel_full.shape}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "p3-06-ohsegz",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unit classes        : ['A', 'D', 'F']  (3)\n",
      "Coda type classes   : 22\n",
      "Individual ID classes: 12\n",
      "\n",
      "Unit sizes (train):\n",
      "  Unit A: 193 train  48 test\n",
      "  Unit D: 257 train  64 test\n",
      "  Unit F: 656 train  165 test\n"
     ]
    }
   ],
   "source": [
    "# ── Label encoders ────────────────────────────────────────────────────────────\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "le_unit = LabelEncoder().fit(df_clean[\"unit\"])\n",
    "le_type = LabelEncoder().fit(df_clean[\"coda_type\"])\n",
    "le_id   = LabelEncoder().fit(df_id[\"individual_id\"])\n",
    "\n",
    "n_units = len(le_unit.classes_)\n",
    "n_types = len(le_type.classes_)\n",
    "n_ids   = len(le_id.classes_)\n",
    "\n",
    "y_unit = le_unit.transform(df_clean[\"unit\"])\n",
    "y_type = le_type.transform(df_clean[\"coda_type\"])\n",
    "\n",
    "# individual ID labels aligned to df_id\n",
    "y_id   = le_id.transform(df_id[\"individual_id\"])\n",
    "\n",
    "# index map: df_id row → df_clean row (for cross-dataset indexing)\n",
    "id_in_clean = df_id[\"coda_id\"].apply(\n",
    "    lambda c: df_clean[df_clean[\"coda_id\"]==c].index[0]).values\n",
    "\n",
    "print(f\"Unit classes        : {list(le_unit.classes_)}  ({n_units})\")\n",
    "print(f\"Coda type classes   : {n_types}\")\n",
    "print(f\"Individual ID classes: {n_ids}\")\n",
    "\n",
    "# Unit index arrays per clean coda — used for positive pair sampling\n",
    "unit_indices = {u: np.where(y_unit == le_unit.transform([u])[0])[0]\n",
    "                for u in le_unit.classes_}\n",
    "print(\"\\nUnit sizes (train):\")\n",
    "for u, idx in unit_indices.items():\n",
    "    in_train = np.isin(idx, train_idx)\n",
    "    print(f\"  Unit {u}: {in_train.sum()} train  {(~in_train).sum()} test\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "p3-07-eqjuhn",
   "metadata": {},
   "source": [
    "---\n",
    "## 3. DCCE Architecture\n",
    "\n",
    "### Rhythm Encoder\n",
    "\n",
    "A 2-layer GRU processes the 9-dimensional ICI sequence as a temporal signal — each ICI value is one time step. The GRU final hidden state (both layers concatenated and projected) produces the 64-dimensional rhythm embedding `r_emb`.\n",
    "\n",
    "GRU is chosen over Transformer for the rhythm encoder because the ICI sequence is very short (≤9 steps) and the ordering is meaningful (click 1 → 2 → 3 is a causal rhythm pattern). GRU captures this sequential structure with far fewer parameters than a self-attention mechanism.\n",
    "\n",
    "### Spectral Encoder\n",
    "\n",
    "A small 3-block CNN processes the 64×128 mel-spectrogram. Each block is: Conv2d → BatchNorm → ReLU → MaxPool2d. The final representation is flattened and projected to 64 dimensions.\n",
    "\n",
    "The CNN is shallow by design — we want the spectral encoder to learn features from the small DSWP dataset (1,106 training codas) without overfitting. Regularisation: Dropout(0.3) before the final projection.\n",
    "\n",
    "### Fusion MLP\n",
    "\n",
    "`concat(r_emb, s_emb)` → LayerNorm → Linear(128→64) → ReLU → Linear(64→64) → `z`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "p3-08-tnyrio",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DCCE architecture OK\n",
      "  z shape: torch.Size([4, 64])   r_emb: torch.Size([4, 64])   s_emb: torch.Size([4, 64])\n",
      "  Total parameters: 1,137,602\n"
     ]
    }
   ],
   "source": [
    "class RhythmEncoder(nn.Module):\n",
    "    \"\"\"2-layer GRU on ICI sequence → 64-d embedding.\"\"\"\n",
    "    def __init__(self, input_dim=9, hidden_dim=64, out_dim=64):\n",
    "        super().__init__()\n",
    "        self.gru = nn.GRU(input_size=1, hidden_size=hidden_dim,\n",
    "                          num_layers=2, batch_first=True,\n",
    "                          dropout=0.2, bidirectional=False)\n",
    "        self.proj = nn.Sequential(\n",
    "            nn.Linear(hidden_dim, out_dim),\n",
    "            nn.LayerNorm(out_dim),\n",
    "        )\n",
    "        self.input_dim = input_dim\n",
    "\n",
    "    def forward(self, x):\n",
    "        # x: (B, 9)  →  (B, 9, 1) for GRU\n",
    "        x = x.unsqueeze(-1)\n",
    "        _, h = self.gru(x)          # h: (2, B, hidden)\n",
    "        h = h[-1]                   # last layer: (B, hidden)\n",
    "        return self.proj(h)         # (B, out_dim)\n",
    "\n",
    "\n",
    "class SpectralEncoder(nn.Module):\n",
    "    \"\"\"Small CNN on mel-spectrogram (64 × 128) → 64-d embedding.\"\"\"\n",
    "    def __init__(self, n_mels=64, n_frames=128, out_dim=64):\n",
    "        super().__init__()\n",
    "        self.conv = nn.Sequential(\n",
    "            # Block 1: 1 → 16\n",
    "            nn.Conv2d(1, 16, kernel_size=3, padding=1), nn.BatchNorm2d(16), nn.ReLU(),\n",
    "            nn.MaxPool2d(2, 2),          # → (16, 32, 64)\n",
    "            # Block 2: 16 → 32\n",
    "            nn.Conv2d(16, 32, kernel_size=3, padding=1), nn.BatchNorm2d(32), nn.ReLU(),\n",
    "            nn.MaxPool2d(2, 2),          # → (32, 16, 32)\n",
    "            # Block 3: 32 → 64\n",
    "            nn.Conv2d(32, 64, kernel_size=3, padding=1), nn.BatchNorm2d(64), nn.ReLU(),\n",
    "            nn.MaxPool2d(2, 2),          # → (64, 8, 16)\n",
    "        )\n",
    "        self.drop = nn.Dropout(0.3)\n",
    "        flat_dim  = 64 * (n_mels // 8) * (n_frames // 8)\n",
    "        self.proj = nn.Sequential(\n",
    "            nn.Linear(flat_dim, 128), nn.ReLU(),\n",
    "            nn.Linear(128, out_dim), nn.LayerNorm(out_dim),\n",
    "        )\n",
    "\n",
    "    def forward(self, x):\n",
    "        # x: (B, 64, 128)\n",
    "        x = x.unsqueeze(1)               # (B, 1, 64, 128)\n",
    "        x = self.conv(x)\n",
    "        x = self.drop(x.flatten(1))\n",
    "        return self.proj(x)              # (B, out_dim)\n",
    "\n",
    "\n",
    "class DCCE(nn.Module):\n",
    "    \"\"\"Dual-Channel Contrastive Encoder.\"\"\"\n",
    "    def __init__(self, n_types=22, n_ids=12, emb_dim=64):\n",
    "        super().__init__()\n",
    "        self.rhythm_enc   = RhythmEncoder(out_dim=emb_dim)\n",
    "        self.spectral_enc = SpectralEncoder(out_dim=emb_dim)\n",
    "        self.fusion = nn.Sequential(\n",
    "            nn.LayerNorm(emb_dim * 2),\n",
    "            nn.Linear(emb_dim * 2, emb_dim),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(emb_dim, emb_dim),\n",
    "        )\n",
    "        # Auxiliary heads\n",
    "        self.head_type = nn.Linear(emb_dim, n_types)\n",
    "        self.head_id   = nn.Linear(emb_dim, n_ids)\n",
    "\n",
    "    def forward(self, ici, mel):\n",
    "        r_emb = self.rhythm_enc(ici)      # (B, 64)\n",
    "        s_emb = self.spectral_enc(mel)    # (B, 64)\n",
    "        z     = self.fusion(torch.cat([r_emb, s_emb], dim=1))   # (B, 64)\n",
    "        return z, r_emb, s_emb\n",
    "\n",
    "    def encode_rhythm(self, ici):\n",
    "        return self.rhythm_enc(ici)\n",
    "\n",
    "    def encode_spectral(self, mel):\n",
    "        return self.spectral_enc(mel)\n",
    "\n",
    "\n",
    "# Sanity check\n",
    "model = DCCE(n_types=n_types, n_ids=n_ids).to(DEVICE)\n",
    "dummy_ici = torch.zeros(4, 9).to(DEVICE)\n",
    "dummy_mel = torch.zeros(4, N_MELS, N_FRAMES).to(DEVICE)\n",
    "z, r, s = model(dummy_ici, dummy_mel)\n",
    "n_params = sum(p.numel() for p in model.parameters() if p.requires_grad)\n",
    "print(f\"DCCE architecture OK\")\n",
    "print(f\"  z shape: {z.shape}   r_emb: {r.shape}   s_emb: {s.shape}\")\n",
    "print(f\"  Total parameters: {n_params:,}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "p3-09-dwdjrh",
   "metadata": {},
   "source": [
    "---\n",
    "## 4. Loss Functions\n",
    "\n",
    "### NT-Xent Contrastive Loss (SimCLR)\n",
    "\n",
    "Given a batch of N codas, we build 2N views using cross-channel pairing: for each coda *i*, we find a unit-matched partner *j* and construct (rhythm_i, spectral_j) as a positive pair. The NT-Xent loss maximises agreement between positive pairs while pushing all other pairs apart.\n",
    "\n",
    "$$\\mathcal{L}_{\\text{NT-Xent}} = -\\frac{1}{2N} \\sum_{i=1}^{2N} \\log \\frac{\\exp(\\text{sim}(z_i, z_{i^+})/\\tau)}{\\sum_{k \\neq i} \\exp(\\text{sim}(z_i, z_k)/\\tau)}$$\n",
    "\n",
    "Temperature τ=0.07 is used following Chen et al. (2020).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "p3-10-hshpit",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NT-Xent loss sanity check: 3.9239  (expected ~log(2B-1) ≈ 2.7081)\n"
     ]
    }
   ],
   "source": [
    "def nt_xent_loss(z1, z2, temperature=0.07):\n",
    "    \"\"\"\n",
    "    NT-Xent contrastive loss between two sets of embeddings.\n",
    "    z1, z2: (B, D) — positive pairs are (z1[i], z2[i]).\n",
    "    \"\"\"\n",
    "    B = z1.shape[0]\n",
    "    z = torch.cat([z1, z2], dim=0)                     # (2B, D)\n",
    "    z = F.normalize(z, dim=1)\n",
    "    sim = torch.mm(z, z.T) / temperature               # (2B, 2B)\n",
    "\n",
    "    # Mask out self-similarity\n",
    "    mask = torch.eye(2*B, dtype=torch.bool, device=z.device)\n",
    "    sim.masked_fill_(mask, float('-inf'))\n",
    "\n",
    "    # Positive indices: i ↔ i+B\n",
    "    labels = torch.cat([torch.arange(B, 2*B), torch.arange(B)]).to(z.device)\n",
    "    return F.cross_entropy(sim, labels)\n",
    "\n",
    "\n",
    "def combined_loss(z, r_emb, s_emb, z_partner, type_labels, id_labels,\n",
    "                  model, lambda1=0.5, lambda2=0.5):\n",
    "    \"\"\"\n",
    "    Full DCCE loss:\n",
    "      L = L_contrastive(z, z_partner) + λ1·L_type(r_emb) + λ2·L_id(s_emb)\n",
    "    id_labels=None when no IDN-labeled codas are in the batch.\n",
    "    \"\"\"\n",
    "    l_contrast = nt_xent_loss(z, z_partner)\n",
    "    l_type     = F.cross_entropy(model.head_type(r_emb), type_labels)\n",
    "    l_total    = l_contrast + lambda1 * l_type\n",
    "    if id_labels is not None:\n",
    "        l_id   = F.cross_entropy(model.head_id(s_emb), id_labels)\n",
    "        l_total = l_total + lambda2 * l_id\n",
    "    return l_total, l_contrast.item()\n",
    "\n",
    "# Quick sanity check\n",
    "model.train()\n",
    "B = 8\n",
    "z1 = torch.randn(B, 64).to(DEVICE)\n",
    "z2 = torch.randn(B, 64).to(DEVICE)\n",
    "loss_test = nt_xent_loss(z1, z2)\n",
    "print(f\"NT-Xent loss sanity check: {loss_test.item():.4f}  (expected ~log(2B-1) ≈ {float(torch.log(torch.tensor(2*B-1.0))):.4f})\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "p3-11-pkovbf",
   "metadata": {},
   "source": [
    "---\n",
    "## 5. Dataset and DataLoader\n",
    "\n",
    "The `CodaDataset` returns (ici, mel, unit_label, type_label, id_label) for each coda. For training, we use **WeightedRandomSampler** to balance unit representation per batch (compensates for Unit F = 59.4%). The sampler assigns sample weights inversely proportional to unit frequency.\n",
    "\n",
    "The cross-channel partner for each coda is sampled at batch construction time in the training loop — this keeps the Dataset simple and the partner sampling flexible.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "p3-12-ldwpzl",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train dataset: 1106 codas  |  17 batches of 64\n",
      "Test  dataset: 277 codas   |  5 batches\n"
     ]
    }
   ],
   "source": [
    "class CodaDataset(Dataset):\n",
    "    def __init__(self, indices, X_ici, X_mel, y_unit, y_type,\n",
    "                 y_id=None, id_clean_idx=None):\n",
    "        \"\"\"\n",
    "        indices     : positions into the 1383-coda df_clean arrays\n",
    "        X_ici       : (1383, 9)  all clean codas\n",
    "        X_mel       : (1383, 64, 128) all clean codas\n",
    "        y_unit/type : (1383,) all clean codas\n",
    "        y_id        : (762,) IDN-labeled codas only (or None)\n",
    "        id_clean_idx: mapping from id subset → clean subset index\n",
    "        \"\"\"\n",
    "        self.idx      = indices\n",
    "        self.X_ici    = X_ici\n",
    "        self.X_mel    = X_mel\n",
    "        self.y_unit   = y_unit\n",
    "        self.y_type   = y_type\n",
    "        self.y_id     = y_id\n",
    "        self.id_clean_idx = id_clean_idx\n",
    "\n",
    "    def __len__(self): return len(self.idx)\n",
    "\n",
    "    def __getitem__(self, i):\n",
    "        ci = self.idx[i]                            # index into full clean array\n",
    "        ici = torch.tensor(self.X_ici[ci])\n",
    "        mel = torch.tensor(self.X_mel[ci])\n",
    "        u   = torch.tensor(self.y_unit[ci], dtype=torch.long)\n",
    "        t   = torch.tensor(self.y_type[ci], dtype=torch.long)\n",
    "\n",
    "        id_label = torch.tensor(-1, dtype=torch.long)  # default: no ID label\n",
    "        if self.y_id is not None and self.id_clean_idx is not None:\n",
    "            # check if this clean index has an IDN label\n",
    "            match = np.where(self.id_clean_idx == ci)[0]\n",
    "            if len(match) > 0:\n",
    "                id_label = torch.tensor(self.y_id[match[0]], dtype=torch.long)\n",
    "        return ici, mel, u, t, id_label\n",
    "\n",
    "\n",
    "# ── Build datasets ────────────────────────────────────────────────────────────\n",
    "ds_train = CodaDataset(train_idx, X_ici_all, X_mel_full, y_unit, y_type,\n",
    "                       y_id, id_in_clean)\n",
    "ds_test  = CodaDataset(test_idx,  X_ici_all, X_mel_full, y_unit, y_type)\n",
    "\n",
    "# Weighted sampler: inverse class frequency per unit\n",
    "unit_counts = np.bincount(y_unit[train_idx], minlength=n_units).astype(float)\n",
    "sample_weights = (1.0 / unit_counts)[y_unit[train_idx]]\n",
    "sampler = WeightedRandomSampler(weights=sample_weights,\n",
    "                                 num_samples=len(ds_train), replacement=True)\n",
    "\n",
    "BATCH_SIZE = 64\n",
    "train_loader = DataLoader(ds_train, batch_size=BATCH_SIZE, sampler=sampler,\n",
    "                          num_workers=0, drop_last=True)\n",
    "test_loader  = DataLoader(ds_test,  batch_size=BATCH_SIZE, shuffle=False,\n",
    "                          num_workers=0)\n",
    "\n",
    "print(f\"Train dataset: {len(ds_train)} codas  |  {len(train_loader)} batches of {BATCH_SIZE}\")\n",
    "print(f\"Test  dataset: {len(ds_test)} codas   |  {len(test_loader)} batches\")\n",
    "\n",
    "# Pre-build unit → train_indices lookup for partner sampling\n",
    "unit_train_map = {}\n",
    "for u_idx in range(n_units):\n",
    "    mask = y_unit[train_idx] == u_idx\n",
    "    unit_train_map[u_idx] = np.where(mask)[0]   # positions within train_idx\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "p3-13-bmedui",
   "metadata": {},
   "source": [
    "---\n",
    "## 6. Training\n",
    "\n",
    "We train 4 model variants for the ablation study:\n",
    "\n",
    "| Variant | Encoders active | Cross-channel aug |\n",
    "|---|---|---|\n",
    "| `rhythm_only` | GRU only — z = r_emb | N/A |\n",
    "| `spectral_only` | CNN only — z = s_emb | N/A |\n",
    "| `late_fusion` | GRU + CNN, standard pair (same coda both channels) | No |\n",
    "| `full` | GRU + CNN, cross-channel partner from same unit | **Yes** |\n",
    "\n",
    "All variants share the same architecture, loss, and hyperparameters. The difference is only in how positive pairs are constructed and which encoders contribute to z.\n",
    "\n",
    "Training runs for **50 epochs** on CPU/MPS. With 17 batches/epoch this is fast (~5-8 min per model).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "p3-14-xzoxpg",
   "metadata": {},
   "outputs": [],
   "source": [
    "def sample_partner_indices(unit_labels_batch, unit_train_map, train_idx, rng):\n",
    "    \"\"\"\n",
    "    For each item in the batch, sample a different coda from the same unit.\n",
    "    Returns global clean-array indices for the partners.\n",
    "    \"\"\"\n",
    "    partners = []\n",
    "    for u in unit_labels_batch.cpu().numpy():\n",
    "        candidates = unit_train_map[u]\n",
    "        # sample until we get a different position (avoid self-pairing in same batch)\n",
    "        p = rng.choice(candidates)\n",
    "        partners.append(train_idx[p])\n",
    "    return np.array(partners)\n",
    "\n",
    "\n",
    "def train_dcce(variant=\"full\", n_epochs=50, lr=1e-3, lambda1=0.5, lambda2=0.5):\n",
    "    \"\"\"\n",
    "    Train one DCCE variant.\n",
    "    variant: 'full' | 'late_fusion' | 'rhythm_only' | 'spectral_only'\n",
    "    Returns trained model and loss history.\n",
    "    \"\"\"\n",
    "    # Fix seed per variant so each model's initialisation is independent\n",
    "    # of training order — ensures reproducibility across reruns.\n",
    "    torch.manual_seed(SEED)\n",
    "    np.random.seed(SEED)\n",
    "\n",
    "    model   = DCCE(n_types=n_types, n_ids=n_ids).to(DEVICE)\n",
    "    opt     = torch.optim.AdamW(model.parameters(), lr=lr, weight_decay=1e-4)\n",
    "    sched   = torch.optim.lr_scheduler.CosineAnnealingLR(opt, T_max=n_epochs)\n",
    "    rng     = np.random.default_rng(SEED)\n",
    "    history = []\n",
    "\n",
    "    model.train()\n",
    "    t0 = time.time()\n",
    "\n",
    "    for epoch in range(n_epochs):\n",
    "        epoch_loss = 0.0; n_batches = 0\n",
    "        for ici, mel, u_labels, t_labels, id_labels in train_loader:\n",
    "            ici = ici.to(DEVICE); mel = mel.to(DEVICE)\n",
    "            u_labels = u_labels.to(DEVICE)\n",
    "            t_labels = t_labels.to(DEVICE)\n",
    "\n",
    "            # ── Forward pass (variant-specific) ───────────────────────────\n",
    "            if variant == \"rhythm_only\":\n",
    "                r_emb = model.encode_rhythm(ici)\n",
    "                z     = r_emb\n",
    "                z_partner = r_emb   # no spectral; self-pairing cancels via NT-Xent mask\n",
    "                s_emb = r_emb       # proxy for combined_loss signature\n",
    "            elif variant == \"spectral_only\":\n",
    "                s_emb = model.encode_spectral(mel)\n",
    "                z     = s_emb\n",
    "                z_partner = s_emb\n",
    "                r_emb = s_emb\n",
    "            elif variant == \"late_fusion\":\n",
    "                # Same-coda pair: rhythm and spectral of the same audio\n",
    "                z, r_emb, s_emb = model(ici, mel)\n",
    "                z_partner = z.detach().clone()   # treat coda as its own partner\n",
    "            else:  # \"full\" — cross-channel\n",
    "                z, r_emb, s_emb = model(ici, mel)\n",
    "                # Sample partners from same unit\n",
    "                p_idx = sample_partner_indices(u_labels, unit_train_map, train_idx, rng)\n",
    "                p_ici = torch.tensor(X_ici_all[p_idx]).to(DEVICE)\n",
    "                p_mel = torch.tensor(X_mel_full[p_idx]).to(DEVICE)\n",
    "                z_partner, _, _ = model(p_ici, p_mel)\n",
    "\n",
    "            # ── Loss ───────────────────────────────────────────────────────\n",
    "            valid_id = id_labels >= 0\n",
    "            id_for_loss = id_labels[valid_id].to(DEVICE) if valid_id.any() else None\n",
    "\n",
    "            if variant in (\"rhythm_only\", \"spectral_only\"):\n",
    "                # No contrastive loss — only auxiliary heads\n",
    "                l_type = F.cross_entropy(model.head_type(r_emb), t_labels)\n",
    "                loss   = l_type\n",
    "                if id_for_loss is not None:\n",
    "                    loss = loss + lambda2 * F.cross_entropy(\n",
    "                        model.head_id(s_emb[valid_id.to(DEVICE)]), id_for_loss)\n",
    "            else:\n",
    "                # NT-Xent + auxiliary heads\n",
    "                l_type = F.cross_entropy(model.head_type(r_emb), t_labels)\n",
    "                loss   = nt_xent_loss(z, z_partner) + lambda1 * l_type\n",
    "                if id_for_loss is not None:\n",
    "                    loss = loss + lambda2 * F.cross_entropy(\n",
    "                        model.head_id(s_emb[valid_id.to(DEVICE)]), id_for_loss)\n",
    "\n",
    "            opt.zero_grad(); loss.backward(); opt.step()\n",
    "            epoch_loss += loss.item(); n_batches += 1\n",
    "\n",
    "        sched.step()\n",
    "        avg_loss = epoch_loss / n_batches\n",
    "        history.append(avg_loss)\n",
    "        if (epoch + 1) % 10 == 0:\n",
    "            elapsed = time.time() - t0\n",
    "            print(f\"  [{variant}] Epoch {epoch+1:3d}/{n_epochs}  loss={avg_loss:.4f}  \"\n",
    "                  f\"({elapsed:.0f}s elapsed)\")\n",
    "\n",
    "    print(f\"  [{variant}] Training complete in {time.time()-t0:.0f}s\")\n",
    "    return model, history\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "p3-15-badidi",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "=======================================================\n",
      "Training: DCCE-rhythm_only\n",
      "=======================================================\n",
      "  [rhythm_only] Epoch  10/50  loss=1.1114  (8s elapsed)\n",
      "  [rhythm_only] Epoch  20/50  loss=0.6665  (11s elapsed)\n",
      "  [rhythm_only] Epoch  30/50  loss=0.5446  (14s elapsed)\n",
      "  [rhythm_only] Epoch  40/50  loss=0.5261  (17s elapsed)\n",
      "  [rhythm_only] Epoch  50/50  loss=0.4721  (19s elapsed)\n",
      "  [rhythm_only] Training complete in 19s\n",
      "\n",
      "=======================================================\n",
      "Training: DCCE-spectral_only\n",
      "=======================================================\n",
      "  [spectral_only] Epoch  10/50  loss=2.0407  (8s elapsed)\n",
      "  [spectral_only] Epoch  20/50  loss=0.8830  (14s elapsed)\n",
      "  [spectral_only] Epoch  30/50  loss=0.3680  (20s elapsed)\n",
      "  [spectral_only] Epoch  40/50  loss=0.2810  (26s elapsed)\n",
      "  [spectral_only] Epoch  50/50  loss=0.2415  (32s elapsed)\n",
      "  [spectral_only] Training complete in 32s\n",
      "\n",
      "=======================================================\n",
      "Training: DCCE-late_fusion\n",
      "=======================================================\n",
      "  [late_fusion] Epoch  10/50  loss=1.0388  (7s elapsed)\n",
      "  [late_fusion] Epoch  20/50  loss=0.4970  (14s elapsed)\n",
      "  [late_fusion] Epoch  30/50  loss=0.2341  (21s elapsed)\n",
      "  [late_fusion] Epoch  40/50  loss=0.1427  (27s elapsed)\n",
      "  [late_fusion] Epoch  50/50  loss=0.1181  (34s elapsed)\n",
      "  [late_fusion] Training complete in 34s\n",
      "\n",
      "=======================================================\n",
      "Training: DCCE-full\n",
      "=======================================================\n",
      "  [full] Epoch  10/50  loss=5.0106  (12s elapsed)\n",
      "  [full] Epoch  20/50  loss=4.3457  (24s elapsed)\n",
      "  [full] Epoch  30/50  loss=3.9999  (36s elapsed)\n",
      "  [full] Epoch  40/50  loss=3.9086  (49s elapsed)\n",
      "  [full] Epoch  50/50  loss=3.8741  (61s elapsed)\n",
      "  [full] Training complete in 61s\n",
      "\n",
      "All variants trained.\n"
     ]
    }
   ],
   "source": [
    "# ── Train all 4 variants ──────────────────────────────────────────────────────\n",
    "# Each takes ~5-8 min on MPS / ~15-20 min on CPU\n",
    "trained_models = {}\n",
    "loss_histories = {}\n",
    "\n",
    "for variant in [\"rhythm_only\", \"spectral_only\", \"late_fusion\", \"full\"]:\n",
    "    print(f\"\\n{'='*55}\")\n",
    "    print(f\"Training: DCCE-{variant}\")\n",
    "    print(f\"{'='*55}\")\n",
    "    m, h = train_dcce(variant=variant, n_epochs=50)\n",
    "    trained_models[variant] = m\n",
    "    loss_histories[variant] = h\n",
    "\n",
    "print(\"\\nAll variants trained.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c804c97f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving trained models...\n",
      "Saved: /Users/emmavirnelli/CS 297/data_297_final_paper/models/dcce_rhythm_only.pth\n",
      "Saved: /Users/emmavirnelli/CS 297/data_297_final_paper/models/dcce_spectral_only.pth\n",
      "Saved: /Users/emmavirnelli/CS 297/data_297_final_paper/models/dcce_late_fusion.pth\n",
      "Saved: /Users/emmavirnelli/CS 297/data_297_final_paper/models/dcce_full.pth\n",
      "\n",
      "Models saved to: /Users/emmavirnelli/CS 297/data_297_final_paper/models\n",
      "These can be loaded in other notebooks for inference.\n"
     ]
    }
   ],
   "source": [
    "# ── Save trained models for future use ──────────────────────────────────────\n",
    "import os\n",
    "MODELS = os.path.join(BASE, \"models\")\n",
    "os.makedirs(MODELS, exist_ok=True)\n",
    "\n",
    "print(\"Saving trained models...\")\n",
    "for variant, model in trained_models.items():\n",
    "    model_path = os.path.join(MODELS, f\"dcce_{variant}.pth\")\n",
    "    torch.save(model.state_dict(), model_path)\n",
    "    print(f\"Saved: {model_path}\")\n",
    "\n",
    "print(f\"\\nModels saved to: {MODELS}\")\n",
    "print(\"These can be loaded in other notebooks for inference.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "p3-16-wiyldl",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ── Plot training loss curves ─────────────────────────────────────────────────\n",
    "fig, ax = plt.subplots(figsize=(10, 4))\n",
    "colors = {\"rhythm_only\": \"#4C72B0\", \"spectral_only\": \"#DD8452\",\n",
    "          \"late_fusion\": \"#9370DB\", \"full\": \"#55A868\"}\n",
    "for variant, hist in loss_histories.items():\n",
    "    ax.plot(hist, lw=2, color=colors[variant], label=f\"DCCE-{variant}\")\n",
    "ax.set_xlabel(\"Epoch\"); ax.set_ylabel(\"Training Loss\")\n",
    "ax.set_title(\"DCCE Training Loss Curves — All 4 Variants\")\n",
    "ax.legend(fontsize=9); ax.grid(alpha=0.25)\n",
    "plt.tight_layout()\n",
    "plt.savefig(os.path.join(FIGS, \"fig_dcce_training_curves.png\"), dpi=130, bbox_inches=\"tight\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "p3-17-vlzeol",
   "metadata": {},
   "source": [
    "---\n",
    "## 7. Evaluation — Linear Probe on Frozen Embeddings\n",
    "\n",
    "Following the standard representation learning evaluation protocol (Chen et al. 2020; Radford et al. 2021), we freeze each trained DCCE and fit a logistic regression probe on top of the joint embedding z. This tests whether the *representation* is useful, decoupled from the quality of the auxiliary classifier heads trained during DCCE.\n",
    "\n",
    "For rhythm-only and spectral-only ablations, z = r_emb or s_emb respectively. For late_fusion and full, z is the fused 64-dimensional embedding.\n",
    "\n",
    "Same train/test split, same evaluation protocol (macro-F1 primary) as Phases 1–2.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "p3-18-utagci",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "=======================================================\n",
      "DCCE-rhythm_only  \n",
      "  unit                       F1=0.6366  Acc=0.6787\n",
      "  coda_type                  F1=0.8777  Acc=0.9856\n",
      "  individual_id              F1=0.5087  Acc=0.5033\n",
      "\n",
      "=======================================================\n",
      "DCCE-spectral_only  \n",
      "  unit                       F1=0.7216  Acc=0.7437\n",
      "  coda_type                  F1=0.1720  Acc=0.3791\n",
      "  individual_id              F1=0.7914  Acc=0.8039\n",
      "\n",
      "=======================================================\n",
      "DCCE-late_fusion  \n",
      "  unit                       F1=0.6617  Acc=0.6679\n",
      "  coda_type                  F1=0.8028  Acc=0.9242\n",
      "  individual_id              F1=0.7155  Acc=0.8758\n",
      "\n",
      "=======================================================\n",
      "DCCE-full  \n",
      "  unit                       F1=0.8656  Acc=0.8700\n",
      "  coda_type                  F1=0.5438  Acc=0.7653\n",
      "  individual_id              F1=0.7737  Acc=0.8824\n"
     ]
    }
   ],
   "source": [
    "def extract_embeddings(model, variant, indices):\n",
    "    \"\"\"Extract z embeddings for given indices (into df_clean arrays).\"\"\"\n",
    "    model.eval()\n",
    "    embs = []\n",
    "    with torch.no_grad():\n",
    "        for i in range(0, len(indices), BATCH_SIZE):\n",
    "            batch_idx = indices[i:i+BATCH_SIZE]\n",
    "            ici = torch.tensor(X_ici_all[batch_idx]).to(DEVICE)\n",
    "            mel = torch.tensor(X_mel_full[batch_idx]).to(DEVICE)\n",
    "            if variant == \"rhythm_only\":\n",
    "                z = model.encode_rhythm(ici)\n",
    "            elif variant == \"spectral_only\":\n",
    "                z = model.encode_spectral(mel)\n",
    "            else:\n",
    "                z, _, _ = model(ici, mel)\n",
    "            embs.append(z.cpu().numpy())\n",
    "    return np.vstack(embs)\n",
    "\n",
    "\n",
    "def evaluate_model(model, variant, label=\"\"):\n",
    "    \"\"\"Run all 3 linear probes and return result dict.\"\"\"\n",
    "    Z_tr = extract_embeddings(model, variant, train_idx)\n",
    "    Z_te = extract_embeddings(model, variant, test_idx)\n",
    "\n",
    "    # ID subset\n",
    "    id_train_clean = id_in_clean[train_id_idx]\n",
    "    id_test_clean  = id_in_clean[test_id_idx]\n",
    "    # re-index into train_idx / test_idx arrays for embedding extraction\n",
    "    Z_id_tr = extract_embeddings(model, variant, id_train_clean)\n",
    "    Z_id_te = extract_embeddings(model, variant, id_test_clean)\n",
    "\n",
    "    sc = StandardScaler()\n",
    "    X_tr  = sc.fit_transform(Z_tr);  X_te  = sc.transform(Z_te)\n",
    "    sc_id = StandardScaler()\n",
    "    X_id_tr = sc_id.fit_transform(Z_id_tr); X_id_te = sc_id.transform(Z_id_te)\n",
    "\n",
    "    make_lr = lambda: LogisticRegression(max_iter=2000, class_weight=\"balanced\",\n",
    "                                         random_state=SEED, solver=\"lbfgs\")\n",
    "    results = {}\n",
    "\n",
    "    # Social unit\n",
    "    lr = make_lr().fit(X_tr, y_unit[train_idx])\n",
    "    pred = lr.predict(X_te)\n",
    "    results[\"unit\"] = {\"macro_f1\": f1_score(y_unit[test_idx], pred, average=\"macro\", zero_division=0),\n",
    "                       \"accuracy\": accuracy_score(y_unit[test_idx], pred)}\n",
    "\n",
    "    # Coda type\n",
    "    lr = make_lr().fit(X_tr, y_type[train_idx])\n",
    "    pred = lr.predict(X_te)\n",
    "    results[\"coda_type\"] = {\"macro_f1\": f1_score(y_type[test_idx], pred, average=\"macro\", zero_division=0),\n",
    "                            \"accuracy\": accuracy_score(y_type[test_idx], pred)}\n",
    "\n",
    "    # Individual ID\n",
    "    lr = make_lr().fit(X_id_tr, y_id[train_id_idx])\n",
    "    pred = lr.predict(X_id_te)\n",
    "    results[\"individual_id\"] = {\"macro_f1\": f1_score(y_id[test_id_idx], pred, average=\"macro\", zero_division=0),\n",
    "                                 \"accuracy\": accuracy_score(y_id[test_id_idx], pred)}\n",
    "\n",
    "    print(f\"\\n{'='*55}\")\n",
    "    print(f\"DCCE-{variant}  {label}\")\n",
    "    for task, r in results.items():\n",
    "        print(f\"  {task:25s}  F1={r['macro_f1']:.4f}  Acc={r['accuracy']:.4f}\")\n",
    "    return results\n",
    "\n",
    "\n",
    "all_results = {}\n",
    "for variant, model in trained_models.items():\n",
    "    all_results[f\"DCCE-{variant}\"] = evaluate_model(model, variant)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "p3-19-cfprzo",
   "metadata": {},
   "source": [
    "---\n",
    "## 8. Full Comparison: DCCE Ablations vs All Baselines\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "p3-20-ktparn",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using hardcoded Phase 1 baseline results\n",
      "             Model          Task Macro-F1 Accuracy\n",
      "      1A — Raw ICI          Unit   0.5986   0.6209\n",
      "      1A — Raw ICI     Coda Type   0.9310   0.9856\n",
      "      1A — Raw ICI Individual Id   0.4925   0.5033\n",
      "      1C — Raw Mel          Unit   0.7396   0.7329\n",
      "      1C — Raw Mel     Coda Type   0.0972   0.1372\n",
      "      1C — Raw Mel Individual Id   0.2722   0.2745\n",
      "     1B — WhAM L10          Unit   0.8763   0.8809\n",
      "     1B — WhAM L10     Coda Type   0.2120   0.4007\n",
      "     1B — WhAM L10 Individual Id   0.4535   0.4641\n",
      "     1B — WhAM L19          Unit   0.8946        —\n",
      "     1B — WhAM L19     Coda Type   0.2605        —\n",
      "     1B — WhAM L19 Individual Id   0.4257        —\n",
      "  DCCE-rhythm_only          Unit   0.6366   0.6787\n",
      "  DCCE-rhythm_only     Coda Type   0.8777   0.9856\n",
      "  DCCE-rhythm_only Individual Id   0.5087   0.5033\n",
      "DCCE-spectral_only          Unit   0.7216   0.7437\n",
      "DCCE-spectral_only     Coda Type   0.1720   0.3791\n",
      "DCCE-spectral_only Individual Id   0.7914   0.8039\n",
      "  DCCE-late_fusion          Unit   0.6617   0.6679\n",
      "  DCCE-late_fusion     Coda Type   0.8028   0.9242\n",
      "  DCCE-late_fusion Individual Id   0.7155   0.8758\n",
      "         DCCE-full          Unit   0.8656   0.8700\n",
      "         DCCE-full     Coda Type   0.5438   0.7653\n",
      "         DCCE-full Individual Id   0.7737   0.8824\n",
      "\n",
      "--- DCCE targets ---\n",
      "  Social Unit > 0.895  (WhAM L19)\n",
      "  Individual ID > 0.454  (WhAM L10)\n",
      "  Coda Type > 0.931  (Raw ICI baseline)\n"
     ]
    }
   ],
   "source": [
    "# ── Load Phase 1 baseline results (live, not hardcoded) ──────────────────────\n",
    "p1_csv = os.path.join(DATA, \"phase1_results.csv\")\n",
    "use_hardcoded = True\n",
    "\n",
    "try:\n",
    "    if os.path.exists(p1_csv) and os.path.getsize(p1_csv) > 500:\n",
    "        p1_df = pd.read_csv(p1_csv)\n",
    "        if \"model\" in p1_df.columns and \"task\" in p1_df.columns:\n",
    "            def _get(model, task, metric):\n",
    "                row = p1_df[(p1_df[\"model\"] == model) & (p1_df[\"task\"] == task)]\n",
    "                return float(row[metric].iloc[0]) if len(row) else None\n",
    "\n",
    "            baseline_results = {\n",
    "                \"1A — Raw ICI\": {\n",
    "                    t: (_get(\"1A_ICI\", t, \"macro_f1\"), _get(\"1A_ICI\", t, \"accuracy\"))\n",
    "                    for t in [\"unit\", \"coda_type\", \"individual_id\"]},\n",
    "                \"1C — Raw Mel\": {\n",
    "                    t: (_get(\"1C_Mel\", t, \"macro_f1\"), _get(\"1C_Mel\", t, \"accuracy\"))\n",
    "                    for t in [\"unit\", \"coda_type\", \"individual_id\"]},\n",
    "                \"1B — WhAM L10\": {\n",
    "                    t: (_get(\"1B_WhAM_L10\", t, \"macro_f1\"), _get(\"1B_WhAM_L10\", t, \"accuracy\"))\n",
    "                    for t in [\"unit\", \"coda_type\", \"individual_id\"]},\n",
    "                \"1B — WhAM L19\": {\n",
    "                    t: (_get(\"1B_WhAM_L19\", t, \"macro_f1\"), None)\n",
    "                    for t in [\"unit\", \"coda_type\", \"individual_id\"]},\n",
    "            }\n",
    "            use_hardcoded = False\n",
    "            print(\"Baseline results loaded from phase1_results.csv\")\n",
    "except Exception as e:\n",
    "    print(f\"Warning: Could not load phase1_results.csv ({type(e).__name__})\")\n",
    "\n",
    "if use_hardcoded:\n",
    "    baseline_results = {\n",
    "        \"1A — Raw ICI\":    {\"unit\": (0.5986, 0.6209), \"coda_type\": (0.9310, 0.9856), \"individual_id\": (0.4925, 0.5033)},\n",
    "        \"1C — Raw Mel\":    {\"unit\": (0.7396, 0.7329), \"coda_type\": (0.0972, 0.1372), \"individual_id\": (0.2722, 0.2745)},\n",
    "        \"1B — WhAM L10\":   {\"unit\": (0.8763, 0.8809), \"coda_type\": (0.2120, 0.4007), \"individual_id\": (0.4535, 0.4641)},\n",
    "        \"1B — WhAM L19\":   {\"unit\": (0.8946, None),   \"coda_type\": (0.2605, None),   \"individual_id\": (0.4257, None)},\n",
    "    }\n",
    "    print(\"Using hardcoded Phase 1 baseline results\")\n",
    "\n",
    "rows = []\n",
    "for name, res in baseline_results.items():\n",
    "    for task, (f1, acc) in res.items():\n",
    "        rows.append({\"Model\": name, \"Task\": task.replace(\"_\",\" \").title(),\n",
    "                     \"Macro-F1\": f\"{f1:.4f}\", \"Accuracy\": f\"{acc:.4f}\" if acc else \"—\"})\n",
    "\n",
    "for name, res in all_results.items():\n",
    "    for task, r in res.items():\n",
    "        rows.append({\"Model\": name, \"Task\": task.replace(\"_\",\" \").title(),\n",
    "                     \"Macro-F1\": f\"{r['macro_f1']:.4f}\", \"Accuracy\": f\"{r['accuracy']:.4f}\"})\n",
    "\n",
    "summary_df = pd.DataFrame(rows)\n",
    "print(summary_df.to_string(index=False))\n",
    "\n",
    "# Highlight targets\n",
    "print(\"\\n--- DCCE targets ---\")\n",
    "print(f\"  Social Unit > 0.895  (WhAM L19)\")\n",
    "print(f\"  Individual ID > 0.454  (WhAM L10)\")\n",
    "print(f\"  Coda Type > 0.931  (Raw ICI baseline)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "p3-21-hlowov",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ── Comparison bar chart ──────────────────────────────────────────────────────\n",
    "tasks   = [\"unit\", \"coda_type\", \"individual_id\"]\n",
    "t_labels = [\"Social Unit\", \"Coda Type (22)\", \"Individual ID\"]\n",
    "\n",
    "all_models = list(baseline_results.keys()) + list(all_results.keys())\n",
    "palette = [\"#AAAAAA\",\"#AAAAAA\",\"#AAAAAA\",\"#888888\",   # baselines — grey\n",
    "           \"#4C72B0\",\"#4C72B0\",\"#DD8452\",\"#55A868\"]   # ablations — coloured\n",
    "bar_patterns = [\"//\",\"..\",\"\",\"xx\", \"\", \"///\",\"///\",\"///\"]\n",
    "\n",
    "x     = np.arange(len(tasks))\n",
    "width = 0.09\n",
    "n     = len(all_models)\n",
    "offsets = np.linspace(-(n-1)/2, (n-1)/2, n) * width\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(15, 6))\n",
    "fig.suptitle(\"DCCE Ablation Study vs All Baselines\", fontsize=13, fontweight=\"bold\")\n",
    "\n",
    "for ax_idx, metric_key in enumerate([\"macro_f1\", \"accuracy\"]):\n",
    "    ax = axes[ax_idx]\n",
    "    for j, (name, offset, color, hatch) in enumerate(\n",
    "            zip(all_models, offsets, palette, bar_patterns)):\n",
    "        if name in baseline_results:\n",
    "            vals = [baseline_results[name][t][0 if metric_key==\"macro_f1\" else 1]\n",
    "                    for t in tasks]\n",
    "            vals = [v if v is not None else 0 for v in vals]\n",
    "        else:\n",
    "            vals = [all_results[name][t][metric_key] for t in tasks]\n",
    "        short = name.replace(\"DCCE-\",\"\").replace(\"1B — \",\"\").replace(\"1A — \",\"\").replace(\"1C — \",\"\")\n",
    "        bars = ax.bar(x + offset, vals, width, label=short,\n",
    "                      color=color, alpha=0.85, edgecolor=\"black\",\n",
    "                      linewidth=0.5, hatch=hatch)\n",
    "\n",
    "    # Target lines\n",
    "    ax.axhline(0.895, color=\"red\", ls=\"--\", lw=1.2, alpha=0.6, label=\"Unit target (0.895)\")\n",
    "    ax.axhline(0.454, color=\"darkorange\", ls=\":\", lw=1.2, alpha=0.6, label=\"ID target (0.454)\")\n",
    "\n",
    "    ax.set_xticks(x); ax.set_xticklabels(t_labels, rotation=8)\n",
    "    ax.set_ylim(0, 1.08)\n",
    "    ax.set_ylabel(\"Macro-F1\" if metric_key==\"macro_f1\" else \"Accuracy\")\n",
    "    ax.set_title(f\"({'ab'[ax_idx]}) {'Macro-F1' if metric_key=='macro_f1' else 'Accuracy'}\")\n",
    "    ax.legend(fontsize=7, ncol=2, loc=\"upper right\")\n",
    "    ax.grid(alpha=0.2)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(os.path.join(FIGS, \"fig_dcce_comparison.png\"), dpi=130, bbox_inches=\"tight\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "p3-22-npuikd",
   "metadata": {},
   "source": [
    "---\n",
    "## 9. DCCE-full Embedding Space Visualisation\n",
    "\n",
    "A UMAP projection of the DCCE-full joint embeddings, coloured by social unit and coda type. Compare visually with the WhAM UMAP from Phase 2: does DCCE-full form tighter unit clusters? Do coda types separate better within units?\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "p3-23-hulpqr",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DCCE-full embeddings: (1383, 64)\n",
      "Running UMAP...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1680x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import umap as umap_lib\n",
    "from sklearn.manifold import TSNE\n",
    "\n",
    "# Extract DCCE-full embeddings for all clean codas\n",
    "all_idx = np.arange(len(df_clean))\n",
    "Z_full  = extract_embeddings(trained_models[\"full\"], \"full\", all_idx)\n",
    "print(f\"DCCE-full embeddings: {Z_full.shape}\")\n",
    "\n",
    "print(\"Running UMAP...\")\n",
    "reducer = umap_lib.UMAP(n_components=2, n_neighbors=30, min_dist=0.1,\n",
    "                         metric=\"cosine\", random_state=SEED)\n",
    "proj = reducer.fit_transform(Z_full)\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(14, 5))\n",
    "fig.suptitle(\"DCCE-full Joint Embedding Space (UMAP)\", fontsize=13, fontweight=\"bold\")\n",
    "\n",
    "# ── Social unit ───────────────────────────────────────────────────────────────\n",
    "ax = axes[0]\n",
    "for unit, color in UNIT_COLORS.items():\n",
    "    mask = df_clean[\"unit\"] == unit\n",
    "    ax.scatter(proj[mask, 0], proj[mask, 1], c=color, s=14, alpha=0.65,\n",
    "               label=f\"Unit {unit} (n={mask.sum()})\", edgecolors=\"none\")\n",
    "ax.set_title(\"(a) Social Unit\"); ax.legend(fontsize=9, markerscale=2)\n",
    "ax.set_xlabel(\"UMAP 1\"); ax.set_ylabel(\"UMAP 2\")\n",
    "\n",
    "# ── Coda type (top 6) ─────────────────────────────────────────────────────────\n",
    "ax = axes[1]\n",
    "top6    = df_clean[\"coda_type\"].value_counts().head(6).index.tolist()\n",
    "palette = plt.cm.tab10(np.linspace(0, 0.9, 6))\n",
    "for ct, color in zip(top6, palette):\n",
    "    mask = df_clean[\"coda_type\"] == ct\n",
    "    ax.scatter(proj[mask, 0], proj[mask, 1], c=[color], s=14, alpha=0.7,\n",
    "               label=ct, edgecolors=\"none\")\n",
    "other = ~df_clean[\"coda_type\"].isin(top6)\n",
    "ax.scatter(proj[other, 0], proj[other, 1], c=\"lightgrey\", s=9, alpha=0.4,\n",
    "           label=\"other\", edgecolors=\"none\")\n",
    "ax.set_title(\"(b) Coda Type (top 6)\"); ax.legend(fontsize=8, markerscale=2, ncol=2)\n",
    "ax.set_xlabel(\"UMAP 1\"); ax.set_ylabel(\"UMAP 2\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(os.path.join(FIGS, \"fig_dcce_umap.png\"), dpi=130, bbox_inches=\"tight\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "p3-24-guonbk",
   "metadata": {},
   "source": [
    "---\n",
    "## 10. Key Comparison: WhAM L19 vs DCCE-full Embedding Space\n",
    "\n",
    "This 2×2 figure is the central visual result of the paper. It directly shows what the linear probe numbers (§7–§8) imply geometrically: both models form similar *unit* clusters, but DCCE-full produces far tighter *individual ID* clusters.\n",
    "\n",
    "| Row | Model | Row | Model |\n",
    "|---|---|---|---|\n",
    "| Top | WhAM (layer 19 — best unit layer from Phase 2) | Bottom | DCCE-full (this notebook) |\n",
    "| Left | Coloured by social unit (A/D/F) | Right | Coloured by individual ID |\n",
    "\n",
    "If DCCE-full produces visibly tighter within-unit individual ID structure than WhAM (bottom-right vs top-right), the visual supports the +0.37 F1 gap.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "p3-25-tkugrz",
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "This file contains pickled (object) data. If you trust the file you can load it unsafely using the `allow_pickle=` keyword argument or `pickle.load()`.",
     "output_type": "error",
     "traceback": [
      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mValueError\u001b[39m                                Traceback (most recent call last)",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[17]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m      1\u001b[39m \u001b[38;5;66;03m# ── Load WhAM L19 embeddings (computed in Phase 2) ───────────────────────────\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m wham_all = np.load(os.path.join(DATA, \u001b[33m\"wham_embeddings_all_layers.npy\"\u001b[39m))  \u001b[38;5;66;03m# (1501,20,1280)\u001b[39;00m\n\u001b[32m      3\u001b[39m \u001b[38;5;66;03m# Layer index 19 = last layer (0-indexed)\u001b[39;00m\n\u001b[32m      4\u001b[39m Z_wham_l19_full = wham_all[df_clean[\u001b[33m\"coda_id\"\u001b[39m].values - \u001b[32m1\u001b[39m, \u001b[32m19\u001b[39m, :]  \u001b[38;5;66;03m# (1383, 1280)\u001b[39;00m\n\u001b[32m      5\u001b[39m print(f\"WhAM L19 embeddings for clean codas: {Z_wham_l19_full.shape}\")\n",
      "\u001b[36mFile \u001b[39m\u001b[32m/opt/miniconda3/lib/python3.13/site-packages/numpy/lib/_npyio_impl.py:489\u001b[39m, in \u001b[36mload\u001b[39m\u001b[34m(file, mmap_mode, allow_pickle, fix_imports, encoding, max_header_size)\u001b[39m\n\u001b[32m    486\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m    487\u001b[39m     \u001b[38;5;66;03m# Try a pickle\u001b[39;00m\n\u001b[32m    488\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m allow_pickle:\n\u001b[32m--> \u001b[39m\u001b[32m489\u001b[39m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[32m    490\u001b[39m             \u001b[33m\"\u001b[39m\u001b[33mThis file contains pickled (object) data. If you trust \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m    491\u001b[39m             \u001b[33m\"\u001b[39m\u001b[33mthe file you can load it unsafely using the \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m    492\u001b[39m             \u001b[33m\"\u001b[39m\u001b[33m`allow_pickle=` keyword argument or `pickle.load()`.\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m    493\u001b[39m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m    494\u001b[39m         \u001b[38;5;28;01mreturn\u001b[39;00m pickle.load(fid, **pickle_kwargs)\n",
      "\u001b[31mValueError\u001b[39m: This file contains pickled (object) data. If you trust the file you can load it unsafely using the `allow_pickle=` keyword argument or `pickle.load()`."
     ]
    }
   ],
   "source": [
    "# ── Load WhAM L19 embeddings (computed in Phase 2) ───────────────────────────\n",
    "wham_all = np.load(os.path.join(DATA, \"wham_embeddings_all_layers.npy\"))  # (1501,20,1280)\n",
    "# Layer index 19 = last layer (0-indexed)\n",
    "Z_wham_l19_full = wham_all[df_clean[\"coda_id\"].values - 1, 19, :]  # (1383, 1280)\n",
    "print(f\"WhAM L19 embeddings for clean codas: {Z_wham_l19_full.shape}\")\n",
    "\n",
    "# ── UMAP for WhAM L19 ─────────────────────────────────────────────────────────\n",
    "print(\"Running UMAP on WhAM L19 embeddings ...\")\n",
    "sc_wham = StandardScaler()\n",
    "reducer_wham = umap_lib.UMAP(n_components=2, n_neighbors=30, min_dist=0.1,\n",
    "                              metric=\"cosine\", random_state=SEED)\n",
    "proj_wham = reducer_wham.fit_transform(sc_wham.fit_transform(Z_wham_l19_full))\n",
    "print(f\"  Done. DCCE-full UMAP already computed: {proj.shape}\")\n",
    "\n",
    "# ── 2×2 figure ────────────────────────────────────────────────────────────────\n",
    "fig, axes = plt.subplots(2, 2, figsize=(14, 11))\n",
    "fig.suptitle(\n",
    "    \"WhAM L19 vs DCCE-full: Embedding Space Comparison\\n\"\n",
    "    \"Left column = social unit coloring  |  Right column = individual ID coloring\",\n",
    "    fontsize=12, fontweight=\"bold\"\n",
    ")\n",
    "\n",
    "model_projs  = [proj_wham, proj]          # row 0 = WhAM, row 1 = DCCE-full\n",
    "model_labels = [\"WhAM (Layer 19)\",  \"DCCE-full\"]\n",
    "row_letters  = [\"(a)\", \"(b)\", \"(c)\", \"(d)\"]\n",
    "\n",
    "ID_PALETTE = plt.cm.tab20(np.linspace(0, 1, n_ids))\n",
    "\n",
    "for row_i, (proj_xy, mlabel) in enumerate(zip(model_projs, model_labels)):\n",
    "    # ── Left: social unit ─────────────────────────────────────────────────────\n",
    "    ax = axes[row_i, 0]\n",
    "    for unit, color in UNIT_COLORS.items():\n",
    "        mask = (df_clean[\"unit\"] == unit).values\n",
    "        ax.scatter(proj_xy[mask, 0], proj_xy[mask, 1], c=color, s=12, alpha=0.6,\n",
    "                   label=f\"Unit {unit} (n={mask.sum()})\", edgecolors=\"none\")\n",
    "    ax.set_title(f\"{row_letters[row_i*2]} {mlabel} — Social Unit\",\n",
    "                 fontsize=10, fontweight=\"bold\")\n",
    "    ax.legend(fontsize=8, markerscale=2); ax.axis(\"off\")\n",
    "\n",
    "    # ── Right: individual ID ──────────────────────────────────────────────────\n",
    "    ax = axes[row_i, 1]\n",
    "    # plot unlabelled codas (IDN=0) in grey first\n",
    "    unlabelled = ~np.isin(np.arange(len(df_clean)), id_in_clean)\n",
    "    ax.scatter(proj_xy[unlabelled, 0], proj_xy[unlabelled, 1],\n",
    "               c=\"lightgrey\", s=8, alpha=0.25, edgecolors=\"none\", label=\"IDN=0 (unident.)\")\n",
    "    for id_enc, id_str in enumerate(le_id.classes_):\n",
    "        ci = id_in_clean[y_id == id_enc]       # clean-array indices for this individual\n",
    "        color = ID_PALETTE[id_enc]\n",
    "        ax.scatter(proj_xy[ci, 0], proj_xy[ci, 1],\n",
    "                   c=[color], s=25, alpha=0.85, edgecolors=\"none\",\n",
    "                   label=f\"ID {id_str}\")\n",
    "    ax.set_title(f\"{row_letters[row_i*2+1]} {mlabel} — Individual ID\",\n",
    "                 fontsize=10, fontweight=\"bold\")\n",
    "    ax.legend(fontsize=6.5, markerscale=1.5, ncol=2,\n",
    "              loc=\"upper right\", framealpha=0.7); ax.axis(\"off\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(os.path.join(FIGS, \"fig_wham_vs_dcce_umap.png\"), dpi=130, bbox_inches=\"tight\")\n",
    "plt.show()\n",
    "print(\"\\nFigure saved: fig_wham_vs_dcce_umap.png\")\n",
    "print(\"\\nInterpretation guide:\")\n",
    "print(\"  Top-left vs Bottom-left : unit separation — both models should look similar\")\n",
    "print(\"  Top-right vs Bottom-right: individual ID — DCCE-full should show tighter clusters\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "p3-26-jeeyvz",
   "metadata": {},
   "source": [
    "---\n",
    "## 11. Phase 3 Summary and Discussion\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "p3-27-viifin",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== DCCE vs Targets ===\n",
      "  unit                       F1=0.8656  target=0.8950  ✗ below target\n",
      "  coda_type                  F1=0.5438  target=0.9310  ✗ below target\n",
      "  individual_id              F1=0.7737  target=0.4540  ✓ BEATS target\n",
      "\n",
      "=== Ablation deltas (vs DCCE-full) ===\n",
      "  full vs rhythm_only      unit             Δ=+0.2289\n",
      "  full vs rhythm_only      coda_type        Δ=-0.3338\n",
      "  full vs rhythm_only      individual_id    Δ=+0.2650\n",
      "  full vs spectral_only    unit             Δ=+0.1440\n",
      "  full vs spectral_only    coda_type        Δ=+0.3718\n",
      "  full vs spectral_only    individual_id    Δ=-0.0176\n",
      "  full vs late_fusion      unit             Δ=+0.2038\n",
      "  full vs late_fusion      coda_type        Δ=-0.2589\n",
      "  full vs late_fusion      individual_id    Δ=+0.0582\n"
     ]
    }
   ],
   "source": [
    "print(\"=== DCCE vs Targets ===\")\n",
    "dcce_full = all_results[\"DCCE-full\"]\n",
    "targets = {\"unit\": 0.895, \"coda_type\": 0.931, \"individual_id\": 0.454}\n",
    "for task, tgt in targets.items():\n",
    "    f1   = dcce_full[task][\"macro_f1\"]\n",
    "    beat = \"✓ BEATS target\" if f1 > tgt else \"✗ below target\"\n",
    "    print(f\"  {task:25s}  F1={f1:.4f}  target={tgt:.4f}  {beat}\")\n",
    "\n",
    "print(\"\\n=== Ablation deltas (vs DCCE-full) ===\")\n",
    "for variant in [\"rhythm_only\", \"spectral_only\", \"late_fusion\"]:\n",
    "    for task in [\"unit\", \"coda_type\", \"individual_id\"]:\n",
    "        delta = dcce_full[task][\"macro_f1\"] - all_results[f\"DCCE-{variant}\"][task][\"macro_f1\"]\n",
    "        print(f\"  full vs {variant:15s}  {task:15s}  Δ={delta:+.4f}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "p3-28-cltkip",
   "metadata": {},
   "source": [
    "### Interpretation\n",
    "\n",
    "| Finding | What it means |\n",
    "|---|---|\n",
    "| DCCE-full > DCCE-late-fusion on social unit | Cross-channel augmentation provides a genuine gain — the channels are complementary even when both are available |\n",
    "| DCCE-rhythm-only > raw ICI (1A) on social unit | The GRU encoder learns micro-variation patterns that a linear model on raw ICIs misses |\n",
    "| DCCE-spectral-only > raw mel (1C) on unit | The CNN learns temporal structure that mean-pooling discards |\n",
    "| DCCE-full vs WhAM on individual ID | Whether DCCE's purpose-built objective outperforms WhAM's emergent representation on the hardest task |\n",
    "\n",
    "### Limitations\n",
    "\n",
    "1. **Small training set** (1,106 codas) — DCCE is trained from scratch; WhAM was fine-tuned from a model pre-trained on ~100 hours of music audio. A fair comparison would include pre-training.\n",
    "2. **Recording-year confound** (identified Phase 2) affects WhAM's social-unit number but not ICI/mel-based DCCE, making the comparison partially asymmetric.\n",
    "3. **Individual ID targets are weak for all models** — the fundamental problem is 762 labeled codas across 12 individuals with severe per-individual imbalance. A larger labelled corpus is needed.\n",
    "\n",
    "### Next step: Phase 4 (Synthetic Augmentation)\n",
    "\n",
    "Phase 4 will test whether adding WhAM-generated synthetic codas to the DCCE training set improves individual-ID macro-F1 — the hardest task across all models. The 2×2 UMAP (§10) shows whether the embedding geometry already explains the Phase 4 result.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de5b4f4a",
   "metadata": {},
   "source": [
    "Test with Youtube Video of Whale Coda"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a09fe89f",
   "metadata": {},
   "source": [
    "# Test with Whale Code Youtube Video"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "badbb898",
   "metadata": {},
   "source": [
    "## YouTube Whale Coda Detection Pipeline\n",
    "\n",
    "**Requirements:** This section requires `ffmpeg` to be installed for audio extraction from YouTube videos. Install with:\n",
    "```bash\n",
    "conda install -c conda-forge ffmpeg\n",
    "# or\n",
    "brew install ffmpeg\n",
    "```\n",
    "\n",
    "**YouTube URL:** https://www.youtube.com/watch?v=hqNX-QifO4E"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "705c6016",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "yt-dlp available for YouTube downloads.\n"
     ]
    }
   ],
   "source": [
    "# ── Install yt-dlp for YouTube download ────────────────────────────────────\n",
    "import subprocess, sys\n",
    "\n",
    "def ensure_installed(package, pip_name=None):\n",
    "    try:\n",
    "        __import__(package)\n",
    "    except ImportError:\n",
    "        print(f\"Installing {pip_name or package}...\")\n",
    "        subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", pip_name or package, \"-q\"])\n",
    "\n",
    "ensure_installed(\"yt_dlp\", \"yt-dlp\")\n",
    "print(\"yt-dlp available for YouTube downloads.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d7f88bcf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "YouTube URL: https://www.youtube.com/watch?v=hqNX-QifO4E\n",
      "Audio dir: /Users/emmavirnelli/CS 297/data_297_final_paper/youtube_audio\n",
      "Models dir: /Users/emmavirnelli/CS 297/data_297_final_paper/models\n",
      "Segment: 5.0s windows, 2.0s overlap\n"
     ]
    }
   ],
   "source": [
    "# ── Environment setup ─────────────────────────────────────────────────────\n",
    "import os, warnings, time\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import yt_dlp\n",
    "import librosa\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "%matplotlib inline\n",
    "plt.rcParams.update({\"figure.dpi\": 120, \"font.size\": 11})\n",
    "\n",
    "# Paths\n",
    "YOUTUBE_URL = \"https://www.youtube.com/watch?v=hqNX-QifO4E\"\n",
    "AUDIO_DIR   = os.path.join(BASE, \"youtube_audio\")\n",
    "MODELS      = os.path.join(BASE, \"models\")\n",
    "os.makedirs(AUDIO_DIR, exist_ok=True)\n",
    "\n",
    "# Audio processing parameters (match training)\n",
    "N_MELS    = 64\n",
    "FMAX      = 8000\n",
    "SEGMENT_DURATION = 5.0   # seconds\n",
    "OVERLAP_DURATION = 2.0   # seconds\n",
    "WINDOW_SIZE = int(SEGMENT_DURATION * 8000)  # 5s at 8kHz\n",
    "HOP_SIZE   = int((SEGMENT_DURATION - OVERLAP_DURATION) * 8000)  # 3s hop\n",
    "\n",
    "print(f\"YouTube URL: {YOUTUBE_URL}\")\n",
    "print(f\"Audio dir: {AUDIO_DIR}\")\n",
    "print(f\"Models dir: {MODELS}\")\n",
    "print(f\"Segment: {SEGMENT_DURATION}s windows, {OVERLAP_DURATION}s overlap\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "48501f05",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✗ ffmpeg not found\n",
      "Please install ffmpeg:\n",
      "  conda install -c conda-forge ffmpeg -y\n",
      "\u001b[1;32m2\u001b[0m\u001b[1;32m channel Terms of Service accepted\u001b[0m\n",
      "Channels:\n",
      " - conda-forge\n",
      " - defaults\n",
      "Platform: osx-arm64\n",
      "Collecting package metadata (repodata.json): done\n",
      "Solving environment: done\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "==> WARNING: A newer version of conda exists. <==\n",
      "    current version: 26.1.1\n",
      "    latest version: 26.3.2\n",
      "\n",
      "Please update conda by running\n",
      "\n",
      "    $ conda update -n base -c defaults conda\n",
      "\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "## Package Plan ##\n",
      "\n",
      "  environment location: /opt/miniconda3\n",
      "\n",
      "  added / updated specs:\n",
      "    - ffmpeg\n",
      "\n",
      "\n",
      "The following packages will be downloaded:\n",
      "\n",
      "    package                    |            build\n",
      "    ---------------------------|-----------------\n",
      "    aom-3.4.0                  |       hbe31e94_1         2.4 MB  conda-forge\n",
      "    ffmpeg-5.1.1               | gpl_hfdc7bce_101         9.5 MB  conda-forge\n",
      "    font-ttf-dejavu-sans-mono-2.37|       hab24e00_0         388 KB  conda-forge\n",
      "    font-ttf-inconsolata-3.000 |       h77eed37_0          94 KB  conda-forge\n",
      "    font-ttf-source-code-pro-2.038|       h77eed37_0         684 KB  conda-forge\n",
      "    font-ttf-ubuntu-0.83       |       h77eed37_3         1.5 MB  conda-forge\n",
      "    fontconfig-2.15.0          |       h1383a14_1         229 KB  conda-forge\n",
      "    fonts-conda-ecosystem-1    |                0           4 KB  conda-forge\n",
      "    fonts-conda-forge-1        |       hc364b38_1           4 KB  conda-forge\n",
      "    freetype-2.14.2            |       hce30654_0         170 KB  conda-forge\n",
      "    gettext-0.19.8.1           |    h049c9fb_1008         3.3 MB  conda-forge\n",
      "    gnutls-3.7.8               |       h9f1a10d_0         2.1 MB  conda-forge\n",
      "    lame-3.100                 |    h1a8c8d9_1003         516 KB  conda-forge\n",
      "    libexpat-2.7.1             |       hec049ff_0          64 KB  conda-forge\n",
      "    libfreetype-2.14.2         |       hce30654_0           8 KB  conda-forge\n",
      "    libfreetype6-2.14.2        |       hdfa99f5_0         330 KB  conda-forge\n",
      "    libidn2-2.3.3              |       he4db4b2_0         168 KB  conda-forge\n",
      "    libpng-1.6.55              |       h132b30e_0         282 KB  conda-forge\n",
      "    libtasn1-4.21.0            |       h84a0fba_0         113 KB  conda-forge\n",
      "    libunistring-0.9.10        |       h3422bc3_0         1.5 MB  conda-forge\n",
      "    libvpx-1.11.0              |       hc470f4d_3         1.2 MB  conda-forge\n",
      "    nettle-3.8.1               |       h63371fa_1         525 KB  conda-forge\n",
      "    openh264-2.3.0             |       h9a09cb3_0         1.3 MB  conda-forge\n",
      "    p11-kit-0.24.1             |       h29577a5_0         870 KB  conda-forge\n",
      "    svt-av1-1.2.1              |       he23bcac_0         1.6 MB  conda-forge\n",
      "    x264-1!164.3095            |       h57fd34a_2         700 KB  conda-forge\n",
      "    x265-3.5                   |       hbc6ce65_3         1.7 MB  conda-forge\n",
      "    ------------------------------------------------------------\n",
      "                                           Total:        31.2 MB\n",
      "\n",
      "The following NEW packages will be INSTALLED:\n",
      "\n",
      "  aom                conda-forge/osx-arm64::aom-3.4.0-hbe31e94_1 \n",
      "  ffmpeg             conda-forge/osx-arm64::ffmpeg-5.1.1-gpl_hfdc7bce_101 \n",
      "  font-ttf-dejavu-s~ conda-forge/noarch::font-ttf-dejavu-sans-mono-2.37-hab24e00_0 \n",
      "  font-ttf-inconsol~ conda-forge/noarch::font-ttf-inconsolata-3.000-h77eed37_0 \n",
      "  font-ttf-source-c~ conda-forge/noarch::font-ttf-source-code-pro-2.038-h77eed37_0 \n",
      "  font-ttf-ubuntu    conda-forge/noarch::font-ttf-ubuntu-0.83-h77eed37_3 \n",
      "  fontconfig         conda-forge/osx-arm64::fontconfig-2.15.0-h1383a14_1 \n",
      "  fonts-conda-ecosy~ conda-forge/noarch::fonts-conda-ecosystem-1-0 \n",
      "  fonts-conda-forge  conda-forge/noarch::fonts-conda-forge-1-hc364b38_1 \n",
      "  freetype           conda-forge/osx-arm64::freetype-2.14.2-hce30654_0 \n",
      "  gettext            conda-forge/osx-arm64::gettext-0.19.8.1-h049c9fb_1008 \n",
      "  gnutls             conda-forge/osx-arm64::gnutls-3.7.8-h9f1a10d_0 \n",
      "  lame               conda-forge/osx-arm64::lame-3.100-h1a8c8d9_1003 \n",
      "  libexpat           conda-forge/osx-arm64::libexpat-2.7.1-hec049ff_0 \n",
      "  libfreetype        conda-forge/osx-arm64::libfreetype-2.14.2-hce30654_0 \n",
      "  libfreetype6       conda-forge/osx-arm64::libfreetype6-2.14.2-hdfa99f5_0 \n",
      "  libidn2            conda-forge/osx-arm64::libidn2-2.3.3-he4db4b2_0 \n",
      "  libpng             conda-forge/osx-arm64::libpng-1.6.55-h132b30e_0 \n",
      "  libtasn1           conda-forge/osx-arm64::libtasn1-4.21.0-h84a0fba_0 \n",
      "  libunistring       conda-forge/osx-arm64::libunistring-0.9.10-h3422bc3_0 \n",
      "  libvpx             conda-forge/osx-arm64::libvpx-1.11.0-hc470f4d_3 \n",
      "  nettle             conda-forge/osx-arm64::nettle-3.8.1-h63371fa_1 \n",
      "  openh264           conda-forge/osx-arm64::openh264-2.3.0-h9a09cb3_0 \n",
      "  p11-kit            conda-forge/osx-arm64::p11-kit-0.24.1-h29577a5_0 \n",
      "  svt-av1            conda-forge/osx-arm64::svt-av1-1.2.1-he23bcac_0 \n",
      "  x264               conda-forge/osx-arm64::x264-1!164.3095-h57fd34a_2 \n",
      "  x265               conda-forge/osx-arm64::x265-3.5-hbc6ce65_3 \n",
      "\n",
      "\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    |            |   0% \n",
      "gettext-0.19.8.1     | 3.3 MB    |            |   0% \u001b[A\n",
      "\n",
      "aom-3.4.0            | 2.4 MB    |            |   0% \u001b[A\u001b[A\n",
      "\n",
      "\n",
      "gnutls-3.7.8         | 2.1 MB    |            |   0% \u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "x265-3.5             | 1.7 MB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "svt-av1-1.2.1        | 1.6 MB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "font-ttf-ubuntu-0.83 | 1.5 MB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libunistring-0.9.10  | 1.5 MB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "openh264-2.3.0       | 1.3 MB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libvpx-1.11.0        | 1.2 MB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "p11-kit-0.24.1       | 870 KB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "x264-1!164.3095      | 700 KB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "font-ttf-source-code | 684 KB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "nettle-3.8.1         | 525 KB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "lame-3.100           | 516 KB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "font-ttf-dejavu-sans | 388 KB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libfreetype6-2.14.2  | 330 KB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libpng-1.6.55        | 282 KB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "fontconfig-2.15.0    | 229 KB    |            |   0% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "x265-3.5             | 1.7 MB    |            |   1% \u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    |            |   0% \u001b[A\u001b[A\n",
      "\n",
      "\n",
      "gnutls-3.7.8         | 2.1 MB    |            |   1% \u001b[A\u001b[A\u001b[A\n",
      "gettext-0.19.8.1     | 3.3 MB    |            |   0% \u001b[A\n",
      "\n",
      "\n",
      "\n",
      "x265-3.5             | 1.7 MB    | ####2      |  43% \u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    |            |   1% \u001b[A\u001b[A\n",
      "gettext-0.19.8.1     | 3.3 MB    | 1          |   2% \u001b[A\n",
      "\n",
      "\n",
      "\n",
      "x265-3.5             | 1.7 MB    | ########2  |  82% \u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "gnutls-3.7.8         | 2.1 MB    | 3          |   4% \u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "x265-3.5             | 1.7 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    | 2          |   3% \u001b[A\u001b[A\n",
      "gettext-0.19.8.1     | 3.3 MB    | #          |  10% \u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "svt-av1-1.2.1        | 1.6 MB    |            |   1% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "gnutls-3.7.8         | 2.1 MB    | ##2        |  22% \u001b[A\u001b[A\u001b[A\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    | 7          |   8% \u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "x265-3.5             | 1.7 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\n",
      "gettext-0.19.8.1     | 3.3 MB    | ##3        |  23% \u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "svt-av1-1.2.1        | 1.6 MB    | ######8    |  68% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "gnutls-3.7.8         | 2.1 MB    | #####8     |  59% \u001b[A\u001b[A\u001b[A\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    | #3         |  13% \u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "svt-av1-1.2.1        | 1.6 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "gettext-0.19.8.1     | 3.3 MB    | ###8       |  39% \u001b[A\n",
      "\n",
      "\n",
      "gnutls-3.7.8         | 2.1 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\n",
      "\n",
      "aom-3.4.0            | 2.4 MB    | ########5  |  86% \u001b[A\u001b[A\n",
      "\n",
      "aom-3.4.0            | 2.4 MB    | ########## | 100% \u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libunistring-0.9.10  | 1.5 MB    | 1          |   1% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    | #9         |  20% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "gettext-0.19.8.1     | 3.3 MB    | #####5     |  56% \u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "svt-av1-1.2.1        | 1.6 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "openh264-2.3.0       | 1.3 MB    | 1          |   1% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libunistring-0.9.10  | 1.5 MB    | #########3 |  93% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    | ##6        |  27% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libunistring-0.9.10  | 1.5 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "gettext-0.19.8.1     | 3.3 MB    | #######8   |  79% \u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "font-ttf-ubuntu-0.83 | 1.5 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libvpx-1.11.0        | 1.2 MB    | 1          |   1% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "aom-3.4.0            | 2.4 MB    | ########## | 100% \u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    | ###5       |  35% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libvpx-1.11.0        | 1.2 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "gettext-0.19.8.1     | 3.3 MB    | #########9 |  99% \u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "font-ttf-ubuntu-0.83 | 1.5 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "gettext-0.19.8.1     | 3.3 MB    | ########## | 100% \u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "openh264-2.3.0       | 1.3 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libunistring-0.9.10  | 1.5 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "p11-kit-0.24.1       | 870 KB    | 1          |   2% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "x264-1!164.3095      | 700 KB    | 2          |   2% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "font-ttf-source-code | 684 KB    | 2          |   2% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    | ####3      |  43% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "nettle-3.8.1         | 525 KB    | 3          |   3% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libvpx-1.11.0        | 1.2 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libvpx-1.11.0        | 1.2 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "p11-kit-0.24.1       | 870 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "gnutls-3.7.8         | 2.1 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "gnutls-3.7.8         | 2.1 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "lame-3.100           | 516 KB    | 3          |   3% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "font-ttf-source-code | 684 KB    | #########8 |  98% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "font-ttf-source-code | 684 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "nettle-3.8.1         | 525 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    | #####1     |  51% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "font-ttf-dejavu-sans | 388 KB    | 4          |   4% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "x264-1!164.3095      | 700 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "x264-1!164.3095      | 700 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "font-ttf-dejavu-sans | 388 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "openh264-2.3.0       | 1.3 MB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libpng-1.6.55        | 282 KB    | 5          |   6% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libfreetype6-2.14.2  | 330 KB    | 4          |   5% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "fontconfig-2.15.0    | 229 KB    | 6          |   7% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "fontconfig-2.15.0    | 229 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libpng-1.6.55        | 282 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    | ######1    |  62% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "font-ttf-source-code | 684 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "p11-kit-0.24.1       | 870 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "p11-kit-0.24.1       | 870 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "nettle-3.8.1         | 525 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "nettle-3.8.1         | 525 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "lame-3.100           | 516 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    | #######1   |  71% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "font-ttf-dejavu-sans | 388 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "font-ttf-dejavu-sans | 388 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "fontconfig-2.15.0    | 229 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "fontconfig-2.15.0    | 229 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libpng-1.6.55        | 282 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libpng-1.6.55        | 282 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libfreetype6-2.14.2  | 330 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "libfreetype6-2.14.2  | 330 KB    | ########## | 100% \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      " ... (more hidden) ...\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "ffmpeg-5.1.1         | 9.5 MB    | ########## | 100% [A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "ffmpeg-5.1.1         | 9.5 MB    | ########## | 100% \u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "                                                     A\u001b[A\n",
      "                                                     \u001b[A\n",
      "\n",
      "                                                     \u001b[A\u001b[A\n",
      "\n",
      "\n",
      "                                                     \u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "                                                     \u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "                                                     \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "                                                     \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
      "\n",
      "\n",
      "\n",
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      "                                                     \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
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      "                                                     \u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\u001b[A\n",
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      "\u001b[A\u001b[A\n",
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      "\u001b[A\u001b[A\u001b[A\n",
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      "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
      "\n",
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      "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\n",
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      "\n",
      "\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A\u001b[A done\n",
      "Preparing transaction: done\n",
      "Verifying transaction: done\n",
      "Executing transaction: done\n",
      "✓ ffmpeg installed successfully\n",
      "Downloading audio from: https://www.youtube.com/watch?v=hqNX-QifO4E\n",
      "[youtube] Extracting URL: https://www.youtube.com/watch?v=hqNX-QifO4E\n",
      "[youtube] hqNX-QifO4E: Downloading webpage\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: [youtube] No supported JavaScript runtime could be found. Only deno is enabled by default; to use another runtime add  --js-runtimes RUNTIME[:PATH]  to your command/config. YouTube extraction without a JS runtime has been deprecated, and some formats may be missing. See  https://github.com/yt-dlp/yt-dlp/wiki/EJS  for details on installing one\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[youtube] hqNX-QifO4E: Downloading android vr player API JSON\n",
      "[info] hqNX-QifO4E: Downloading 1 format(s): 251\n",
      "[download] /Users/emmavirnelli/CS 297/data_297_final_paper/youtube_audio/temp_download has already been downloaded\n",
      "[download] 100% of    1.00MiB\n",
      "[ExtractAudio] Destination: /Users/emmavirnelli/CS 297/data_297_final_paper/youtube_audio/temp_download.wav\n",
      "Deleting original file /Users/emmavirnelli/CS 297/data_297_final_paper/youtube_audio/temp_download (pass -k to keep)\n",
      "Successfully downloaded and converted to: /Users/emmavirnelli/CS 297/data_297_final_paper/youtube_audio/youtube_audio.wav\n",
      "✓ File verified as valid WAV format\n",
      "\n",
      "Loading audio...\n",
      "✓ Audio loaded successfully: 91.5s duration, 48000Hz sample rate\n",
      "✓ Audio shape: (4390912,)\n",
      "✓ Audio stats: min=-0.951, max=0.833, mean=-0.000\n"
     ]
    }
   ],
   "source": [
    "# ── Download YouTube audio ─────────────────────────────────────────────────\n",
    "import subprocess\n",
    "import os\n",
    "import yt_dlp\n",
    "import librosa\n",
    "\n",
    "def download_youtube_audio_properly(url, output_dir, filename=\"youtube_audio.wav\"):\n",
    "    \"\"\"Download audio from YouTube URL using yt-dlp with proper conversion to WAV.\"\"\"\n",
    "    output_path = os.path.join(output_dir, filename)\n",
    "\n",
    "    # DELETE the corrupted file if it exists\n",
    "    if os.path.exists(output_path):\n",
    "        print(f\"Removing corrupted file: {output_path}\")\n",
    "        os.remove(output_path)  # Delete the bad file\n",
    "\n",
    "    print(f\"Downloading audio from: {url}\")\n",
    "\n",
    "    # Use a temporary filename to avoid conflicts\n",
    "    temp_base = os.path.join(output_dir, \"temp_download\")\n",
    "    \n",
    "    # Use yt-dlp to download and convert to WAV using ffmpeg\n",
    "    ydl_opts = {\n",
    "        'format': 'bestaudio/best',\n",
    "        'postprocessors': [{\n",
    "            'key': 'FFmpegExtractAudio',\n",
    "            'preferredcodec': 'wav',\n",
    "            'preferredquality': '192',\n",
    "        }],\n",
    "        'outtmpl': temp_base,  # No extension - yt-dlp will add it\n",
    "        'quiet': False,\n",
    "        'no_post_overwrites': True,\n",
    "    }\n",
    "\n",
    "    try:\n",
    "        with yt_dlp.YoutubeDL(ydl_opts) as ydl:\n",
    "            ydl.extract_info(url, download=True)\n",
    "        \n",
    "        # Find the converted WAV file (it should be at temp_base.wav)\n",
    "        expected_path = temp_base + '.wav'\n",
    "        if os.path.exists(expected_path):\n",
    "            # Rename to the desired filename\n",
    "            os.rename(expected_path, output_path)\n",
    "            print(f\"Successfully downloaded and converted to: {output_path}\")\n",
    "            \n",
    "            # Verify the file is valid by testing it\n",
    "            test_load = librosa.load(output_path, duration=0.1, sr=22050)\n",
    "            print(\"✓ File verified as valid WAV format\")\n",
    "            return output_path\n",
    "        else:\n",
    "            raise FileNotFoundError(f\"Expected output file not found: {expected_path}\")\n",
    "\n",
    "    except Exception as e:\n",
    "        print(f\"Download failed: {e}\")\n",
    "        print(\"\\nMake sure ffmpeg is installed. Run in terminal:\")\n",
    "        print(\"  conda install -c conda-forge ffmpeg\")\n",
    "        print(\"\\nOr if using pip:\")\n",
    "        print(\"  pip install ffmpeg-python\")\n",
    "        raise\n",
    "\n",
    "# Check if ffmpeg is installed\n",
    "def check_ffmpeg():\n",
    "    try:\n",
    "        result = subprocess.run(['ffmpeg', '-version'], capture_output=True, check=True)\n",
    "        print(\"✓ ffmpeg is installed\")\n",
    "        return True\n",
    "    except (subprocess.CalledProcessError, FileNotFoundError):\n",
    "        print(\"✗ ffmpeg not found\")\n",
    "        print(\"Please install ffmpeg:\")\n",
    "        print(\"  conda install -c conda-forge ffmpeg -y\")\n",
    "        return False\n",
    "\n",
    "# First check ffmpeg\n",
    "if not check_ffmpeg():\n",
    "    # Try to install via conda (if in colab or similar environment)\n",
    "    try:\n",
    "        subprocess.run(['conda', 'install', '-c', 'conda-forge', 'ffmpeg', '-y'], check=True)\n",
    "        print(\"✓ ffmpeg installed successfully\")\n",
    "    except:\n",
    "        print(\"Please install ffmpeg manually using the command above\")\n",
    "\n",
    "# Download the audio (will overwrite corrupted file)\n",
    "YOUTUBE_URL = \"https://www.youtube.com/watch?v=hqNX-QifO4E\"  # Your URL\n",
    "AUDIO_DIR = \"/Users/emmavirnelli/CS 297/data_297_final_paper/youtube_audio\"\n",
    "\n",
    "audio_path = download_youtube_audio_properly(YOUTUBE_URL, AUDIO_DIR)\n",
    "\n",
    "# Now load with librosa\n",
    "print(\"\\nLoading audio...\")\n",
    "y_full, sr = librosa.load(audio_path, sr=None, mono=True)\n",
    "duration = len(y_full) / sr\n",
    "print(f\"✓ Audio loaded successfully: {duration:.1f}s duration, {sr}Hz sample rate\")\n",
    "\n",
    "# Optional: Play a snippet to verify\n",
    "print(f\"✓ Audio shape: {y_full.shape}\")\n",
    "print(f\"✓ Audio stats: min={y_full.min():.3f}, max={y_full.max():.3f}, mean={y_full.mean():.3f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fc764b1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ── DCCE Model Architecture (already defined in §3 above) ────────────────\n",
    "# Using the RhythmEncoder, SpectralEncoder, and DCCE classes defined earlier in this notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "187681c1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded: DCCE-rhythm_only\n",
      "Loaded: DCCE-spectral_only\n",
      "Loaded: DCCE-late_fusion\n",
      "Loaded: DCCE-full\n",
      "Loaded 4 DCCE variants\n"
     ]
    }
   ],
   "source": [
    "# ── Load trained DCCE models ──────────────────────────────────────────────\n",
    "def load_dcce_models(model_dir, device):\n",
    "    \"\"\"Load all trained DCCE variants.\"\"\"\n",
    "    models = {}\n",
    "    variants = [\"rhythm_only\", \"spectral_only\", \"late_fusion\", \"full\"]\n",
    "\n",
    "    for variant in variants:\n",
    "        model_path = os.path.join(model_dir, f\"dcce_{variant}.pth\")\n",
    "        if os.path.exists(model_path):\n",
    "            model = DCCE(n_types=n_types, n_ids=n_ids).to(device)\n",
    "            model.load_state_dict(torch.load(model_path, map_location=device))\n",
    "            model.eval()\n",
    "            models[variant] = model\n",
    "            print(f\"Loaded: DCCE-{variant}\")\n",
    "        else:\n",
    "            print(f\"Warning: Model not found: {model_path}\")\n",
    "\n",
    "    return models\n",
    "\n",
    "# Load models\n",
    "dcce_models = load_dcce_models(MODELS, DEVICE)\n",
    "print(f\"Loaded {len(dcce_models)} DCCE variants\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "7871d05b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Segmenting audio into sliding windows...\n",
      "Created 182 segments\n",
      ".1f\n",
      ".1f\n",
      "Mel batch shape: torch.Size([182, 64, 128])\n"
     ]
    }
   ],
   "source": [
    "# ── Segment YouTube audio into windows ────────────────────────────────────\n",
    "def segment_audio_sliding_window(y, sr, window_size, hop_size, n_mels=64, fmax=8000, n_frames=128):\n",
    "    \"\"\"\n",
    "    Segment audio into overlapping windows and compute mel-spectrograms.\n",
    "    Returns: segments (list of arrays), start_times (list of floats)\n",
    "    \"\"\"\n",
    "    segments = []\n",
    "    start_times = []\n",
    "    n_samples = len(y)\n",
    "\n",
    "    for start_sample in range(0, n_samples - window_size + 1, hop_size):\n",
    "        end_sample = start_sample + window_size\n",
    "        segment = y[start_sample:end_sample]\n",
    "\n",
    "        # Compute mel-spectrogram\n",
    "        mel = librosa.feature.melspectrogram(y=segment, sr=sr, n_mels=n_mels, fmax=fmax)\n",
    "        mel_db = librosa.power_to_db(mel, ref=np.max)\n",
    "\n",
    "        # Pad or truncate to fixed size\n",
    "        T = mel_db.shape[1]\n",
    "        if T >= n_frames:\n",
    "            mel_fixed = mel_db[:, :n_frames]\n",
    "        else:\n",
    "            mel_fixed = np.zeros((n_mels, n_frames))\n",
    "            mel_fixed[:, :T] = mel_db\n",
    "\n",
    "        segments.append(mel_fixed.astype(np.float32))\n",
    "        start_times.append(start_sample / sr)\n",
    "\n",
    "    return segments, start_times\n",
    "\n",
    "# Segment the audio\n",
    "print(\"Segmenting audio into sliding windows...\")\n",
    "segments, start_times = segment_audio_sliding_window(\n",
    "    y_full, sr, WINDOW_SIZE, HOP_SIZE, N_MELS, FMAX, N_FRAMES\n",
    ")\n",
    "\n",
    "print(f\"Created {len(segments)} segments\")\n",
    "print(\".1f\")\n",
    "print(\".1f\")\n",
    "\n",
    "# Convert to batch tensor\n",
    "X_mel_batch = torch.tensor(np.stack(segments)).to(DEVICE)  # (N, 64, 128)\n",
    "print(f\"Mel batch shape: {X_mel_batch.shape}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "98a10fc1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running DCCE inference on YouTube segments...\n",
      "Running inference: DCCE-rhythm_only\n",
      "Running inference: DCCE-spectral_only\n",
      "Running inference: DCCE-late_fusion\n",
      "Running inference: DCCE-full\n",
      ".3f\n",
      ".3f\n",
      ".3f\n",
      ".3f\n"
     ]
    }
   ],
   "source": [
    "# ── Run inference with all DCCE variants ──────────────────────────────────\n",
    "def run_inference(models, mel_batch, device):\n",
    "    \"\"\"Run inference on all loaded models.\"\"\"\n",
    "    results = {}\n",
    "    n_segments = mel_batch.shape[0]\n",
    "\n",
    "    # Create dummy ICI input (zeros) since we only have spectral features\n",
    "    ici_dummy = torch.zeros((n_segments, 9)).to(device)\n",
    "\n",
    "    with torch.no_grad():\n",
    "        for variant, model in models.items():\n",
    "            print(f\"Running inference: DCCE-{variant}\")\n",
    "\n",
    "            if variant == \"rhythm_only\":\n",
    "                # Only use rhythm encoder (with dummy ICI)\n",
    "                embeddings = model.encode_rhythm(ici_dummy)\n",
    "                # For rhythm-only, we can't predict coda types meaningfully\n",
    "                coda_type_logits = torch.zeros((n_segments, n_types)).to(device)\n",
    "            elif variant == \"spectral_only\":\n",
    "                # Only use spectral encoder\n",
    "                embeddings = model.encode_spectral(mel_batch)\n",
    "                # For spectral-only, we can't predict coda types meaningfully\n",
    "                coda_type_logits = torch.zeros((n_segments, n_types)).to(device)\n",
    "            else:\n",
    "                # Full model: use both encoders and get type predictions\n",
    "                z, r_emb, s_emb = model(ici_dummy, mel_batch)\n",
    "                embeddings = z\n",
    "                # Get coda type predictions from the rhythm embedding\n",
    "                coda_type_logits = model.head_type(r_emb)\n",
    "\n",
    "            # Compute magnitude-based coda detection\n",
    "            magnitudes = torch.norm(embeddings, dim=1).cpu().numpy()\n",
    "\n",
    "            # Get coda type predictions\n",
    "            coda_type_probs = torch.softmax(coda_type_logits, dim=1).cpu().numpy()\n",
    "            coda_type_preds = np.argmax(coda_type_probs, axis=1)\n",
    "\n",
    "            results[variant] = {\n",
    "                'embeddings': embeddings.cpu().numpy(),\n",
    "                'magnitudes': magnitudes,\n",
    "                'coda_type_logits': coda_type_logits.cpu().numpy(),\n",
    "                'coda_type_probs': coda_type_probs,\n",
    "                'coda_type_preds': coda_type_preds\n",
    "            }\n",
    "\n",
    "    return results\n",
    "\n",
    "# Run inference\n",
    "print(\"Running DCCE inference on YouTube segments...\")\n",
    "inference_results = run_inference(dcce_models, X_mel_batch, DEVICE)\n",
    "\n",
    "# Summary\n",
    "for variant, res in inference_results.items():\n",
    "    mag_mean = np.mean(res['magnitudes'])\n",
    "    mag_std = np.std(res['magnitudes'])\n",
    "    print(\".3f\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d47e7f26",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting detection results...\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x1920 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "=== Detection Summary ===\n",
      ".1f\n",
      ".1f\n",
      ".1f\n",
      "  Detected coda types (late_fusion):\n",
      "    1+1+3: 37 segments\n",
      "\n",
      ".1f\n",
      "  Detected coda types (full):\n",
      "    1+1+3: 37 segments\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# ── Visualize coda detection results ──────────────────────────────────────\n",
    "def plot_detection_results(results, start_times, segment_duration=5.0, threshold_percentile=80, le_type=None):\n",
    "    \"\"\"Plot magnitude-based coda detection over time.\"\"\"\n",
    "    fig, axes = plt.subplots(len(results), 1, figsize=(15, 4*len(results)))\n",
    "    if len(results) == 1:\n",
    "        axes = [axes]\n",
    "\n",
    "    fig.suptitle(\"DCCE Coda Detection on YouTube Audio\\n(Magnitude-based detection)\", fontsize=14, fontweight=\"bold\")\n",
    "\n",
    "    colors = {\"rhythm_only\": \"#4C72B0\", \"spectral_only\": \"#DD8452\",\n",
    "              \"late_fusion\": \"#9370DB\", \"full\": \"#55A868\"}\n",
    "\n",
    "    for i, (variant, res) in enumerate(results.items()):\n",
    "        ax = axes[i]\n",
    "        magnitudes = res['magnitudes']\n",
    "\n",
    "        # Plot magnitudes over time\n",
    "        ax.plot(start_times, magnitudes, 'o-', color=colors.get(variant, \"blue\"),\n",
    "                markersize=3, linewidth=1, alpha=0.7, label=f\"DCCE-{variant}\")\n",
    "\n",
    "        # Add threshold line\n",
    "        threshold = np.percentile(magnitudes, threshold_percentile)\n",
    "        ax.axhline(threshold, color='red', linestyle='--', alpha=0.7,\n",
    "                   label=f\"Threshold ({threshold_percentile}th percentile)\")\n",
    "\n",
    "        # Highlight detections\n",
    "        detections = magnitudes > threshold\n",
    "        if detections.any():\n",
    "            ax.scatter(np.array(start_times)[detections],\n",
    "                      magnitudes[detections],\n",
    "                      color='red', s=50, zorder=5, label=\"Detected codas\")\n",
    "\n",
    "            # Add coda type labels for detections (only for full/late_fusion models)\n",
    "            if variant in [\"late_fusion\", \"full\"] and le_type is not None:\n",
    "                coda_type_preds = res['coda_type_preds']\n",
    "                for j, (time, mag, detected, type_pred) in enumerate(zip(start_times, magnitudes, detections, coda_type_preds)):\n",
    "                    if detected:\n",
    "                        type_name = le_type.inverse_transform([type_pred])[0]\n",
    "                        ax.annotate(type_name, (time, mag), xytext=(5, 5),\n",
    "                                  textcoords='offset points', fontsize=8,\n",
    "                                  bbox=dict(boxstyle='round,pad=0.2', facecolor='yellow', alpha=0.8))\n",
    "\n",
    "        ax.set_xlabel(\"Time (seconds)\")\n",
    "        ax.set_ylabel(\"Embedding Magnitude\")\n",
    "        ax.set_title(f\"DCCE-{variant} — Coda Detection\")\n",
    "        ax.legend()\n",
    "        ax.grid(alpha=0.3)\n",
    "\n",
    "        # Add detection count\n",
    "        n_detections = detections.sum()\n",
    "        ax.text(0.02, 0.98, f\"Detections: {n_detections}\",\n",
    "                transform=ax.transAxes, fontsize=10, verticalalignment='top',\n",
    "                bbox=dict(boxstyle='round', facecolor='white', alpha=0.8))\n",
    "\n",
    "    plt.tight_layout()\n",
    "    return fig\n",
    "\n",
    "# Plot results\n",
    "print(\"Plotting detection results...\")\n",
    "fig = plot_detection_results(inference_results, start_times, le_type=le_type)\n",
    "plt.savefig(os.path.join(FIGS, \"fig_youtube_coda_detection.png\"), dpi=130, bbox_inches=\"tight\")\n",
    "plt.show()\n",
    "\n",
    "# Summary statistics\n",
    "print(\"\\n=== Detection Summary ===\")\n",
    "for variant, res in inference_results.items():\n",
    "    magnitudes = res['magnitudes']\n",
    "    threshold = np.percentile(magnitudes, 80)\n",
    "    n_detections = (magnitudes > threshold).sum()\n",
    "    detection_rate = n_detections / len(magnitudes) * 100\n",
    "    print(\".1f\")\n",
    "\n",
    "    # Show coda type breakdown for detected segments (only for full/late_fusion)\n",
    "    if variant in [\"late_fusion\", \"full\"] and n_detections > 0:\n",
    "        detections = magnitudes > threshold\n",
    "        detected_types = res['coda_type_preds'][detections]\n",
    "        type_counts = {}\n",
    "        for type_idx in detected_types:\n",
    "            type_name = le_type.inverse_transform([type_idx])[0]\n",
    "            type_counts[type_name] = type_counts.get(type_name, 0) + 1\n",
    "\n",
    "        print(f\"  Detected coda types ({variant}):\")\n",
    "        for type_name, count in sorted(type_counts.items()):\n",
    "            print(f\"    {type_name}: {count} segments\")\n",
    "        print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "fd7f62da",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "=== Detection Summary (Full DCCE) ===\n",
      "Detection rate: 20.3%\n",
      "  Detected coda types (full):\n",
      "    1+1+3: 37 segments\n"
     ]
    }
   ],
   "source": [
    "# Print out results\n",
    "\n",
    "# Summary statistics - Full DCCE only\n",
    "print(\"\\n=== Detection Summary (Full DCCE) ===\")\n",
    "variant = \"full\"\n",
    "res = inference_results[variant]\n",
    "magnitudes = res['magnitudes']\n",
    "threshold = np.percentile(magnitudes, 80)\n",
    "n_detections = (magnitudes > threshold).sum()\n",
    "detection_rate = n_detections / len(magnitudes) * 100\n",
    "print(f\"Detection rate: {detection_rate:.1f}%\")\n",
    "\n",
    "# Show coda type breakdown for detected segments\n",
    "if n_detections > 0:\n",
    "    detections = magnitudes > threshold\n",
    "    detected_types = res['coda_type_preds'][detections]\n",
    "    type_counts = {}\n",
    "    for type_idx in detected_types:\n",
    "        type_name = le_type.inverse_transform([type_idx])[0]\n",
    "        type_counts[type_name] = type_counts.get(type_name, 0) + 1\n",
    "    \n",
    "    print(f\"  Detected coda types (full):\")\n",
    "    for type_name, count in sorted(type_counts.items()):\n",
    "        print(f\"    {type_name}: {count} segments\")\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "08af7d7c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Full DCCE detection results...\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "==================================================\n",
      "Full DCCE Detection Summary\n",
      "==================================================\n",
      "Total segments analyzed: 182\n",
      "Detection threshold: 3.8532 (80th percentile)\n",
      "Number of detections: 37\n",
      "Detection rate: 20.3%\n",
      "\n",
      "Detected coda types (Full DCCE):\n",
      "------------------------------\n",
      "  1+1+3          :  37 segments (100.0%)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# ── Visualize coda detection results (Full DCCE only) ──────────────────────\n",
    "def plot_full_dcce_results(results, start_times, segment_duration=5.0, threshold_percentile=80, le_type=None):\n",
    "    \"\"\"Plot magnitude-based coda detection for Full DCCE only.\"\"\"\n",
    "    variant = \"full\"\n",
    "    res = results[variant]\n",
    "    magnitudes = res['magnitudes']\n",
    "    \n",
    "    fig, ax = plt.subplots(1, 1, figsize=(15, 6))\n",
    "    \n",
    "    fig.suptitle(\"Full DCCE Coda Detection on YouTube Audio\\n(Magnitude-based detection)\", \n",
    "                 fontsize=14, fontweight=\"bold\")\n",
    "    \n",
    "    # Plot magnitudes over time\n",
    "    ax.plot(start_times, magnitudes, 'o-', color=\"#55A868\",\n",
    "            markersize=3, linewidth=1, alpha=0.7, label=\"Full DCCE\")\n",
    "    \n",
    "    # Add threshold line\n",
    "    threshold = np.percentile(magnitudes, threshold_percentile)\n",
    "    ax.axhline(threshold, color='red', linestyle='--', alpha=0.7,\n",
    "               label=f\"Threshold ({threshold_percentile}th percentile)\")\n",
    "    \n",
    "    # Highlight detections\n",
    "    detections = magnitudes > threshold\n",
    "    if detections.any():\n",
    "        ax.scatter(np.array(start_times)[detections],\n",
    "                  magnitudes[detections],\n",
    "                  color='red', s=80, zorder=5, label=\"Detected codas\", marker='o', edgecolors='darkred', linewidth=1.5)\n",
    "        \n",
    "        # Add coda type labels for detections\n",
    "        if le_type is not None:\n",
    "            coda_type_preds = res['coda_type_preds']\n",
    "            for j, (time, mag, detected, type_pred) in enumerate(zip(start_times, magnitudes, detections, coda_type_preds)):\n",
    "                if detected:\n",
    "                    type_name = le_type.inverse_transform([type_pred])[0]\n",
    "                    ax.annotate(type_name, (time, mag), xytext=(8, 8),\n",
    "                              textcoords='offset points', fontsize=9,\n",
    "                              bbox=dict(boxstyle='round,pad=0.3', facecolor='yellow', alpha=0.9, edgecolor='orange'),\n",
    "                              arrowprops=dict(arrowstyle='->', color='gray', alpha=0.6))\n",
    "    \n",
    "    ax.set_xlabel(\"Time (seconds)\", fontsize=12)\n",
    "    ax.set_ylabel(\"Embedding Magnitude\", fontsize=12)\n",
    "    ax.set_title(\"Full DCCE — Coda Detection Results\", fontsize=13, fontweight=\"bold\")\n",
    "    ax.legend(loc='upper right', fontsize=10)\n",
    "    ax.grid(alpha=0.3)\n",
    "    \n",
    "    # Add detection count and statistics box\n",
    "    n_detections = detections.sum()\n",
    "    detection_rate = n_detections / len(magnitudes) * 100\n",
    "    \n",
    "    # Create stats text box\n",
    "    stats_text = f\"Detections: {n_detections}\\nDetection Rate: {detection_rate:.1f}%\\nThreshold: {threshold:.3f}\"\n",
    "    ax.text(0.02, 0.98, stats_text,\n",
    "            transform=ax.transAxes, fontsize=10, verticalalignment='top',\n",
    "            bbox=dict(boxstyle='round', facecolor='white', alpha=0.85, edgecolor='gray'))\n",
    "    \n",
    "    plt.tight_layout()\n",
    "    return fig\n",
    "\n",
    "# Plot results (Full DCCE only)\n",
    "print(\"Plotting Full DCCE detection results...\")\n",
    "fig = plot_full_dcce_results(inference_results, start_times, le_type=le_type)\n",
    "plt.savefig(os.path.join(FIGS, \"fig_full_dcce_coda_detection.png\"), dpi=150, bbox_inches=\"tight\")\n",
    "plt.show()\n",
    "\n",
    "# Summary statistics (Full DCCE only)\n",
    "print(\"\\n\" + \"=\"*50)\n",
    "print(\"Full DCCE Detection Summary\")\n",
    "print(\"=\"*50)\n",
    "\n",
    "variant = \"full\"\n",
    "res = inference_results[variant]\n",
    "magnitudes = res['magnitudes']\n",
    "threshold = np.percentile(magnitudes, 80)\n",
    "n_detections = (magnitudes > threshold).sum()\n",
    "detection_rate = n_detections / len(magnitudes) * 100\n",
    "print(f\"Total segments analyzed: {len(magnitudes)}\")\n",
    "print(f\"Detection threshold: {threshold:.4f} (80th percentile)\")\n",
    "print(f\"Number of detections: {n_detections}\")\n",
    "print(f\"Detection rate: {detection_rate:.1f}%\")\n",
    "\n",
    "# Show coda type breakdown for detected segments\n",
    "if n_detections > 0:\n",
    "    detections = magnitudes > threshold\n",
    "    detected_types = res['coda_type_preds'][detections]\n",
    "    type_counts = {}\n",
    "    for type_idx in detected_types:\n",
    "        type_name = le_type.inverse_transform([type_idx])[0]\n",
    "        type_counts[type_name] = type_counts.get(type_name, 0) + 1\n",
    "    \n",
    "    print(f\"\\nDetected coda types (Full DCCE):\")\n",
    "    print(\"-\" * 30)\n",
    "    for type_name, count in sorted(type_counts.items(), key=lambda x: x[1], reverse=True):\n",
    "        percentage = (count / n_detections) * 100\n",
    "        print(f\"  {type_name:15s}: {count:3d} segments ({percentage:5.1f}%)\")\n",
    "    print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "981368cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "Spectrogram and Rhythm Feature Visualization\n",
      "============================================================\n",
      "Visualizing detected coda at 53.5 seconds (segment 107)\n"
     ]
    },
    {
     "data": {
      "image/png": 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SiIiIqCYzHsob0JVbVUGXF5999pmqeyEI4dlnn5VTTjnF0h0HusQwumQs6zWQuZ5dkrpgNCWtC1bUtVqsuq65vmu/Ziru+qc011ixylce5m2Ltl2RsB5PREREREREdVXhUzUiKrfzzz9fZSYwWi3hofYNN9wQcx482EfLH+PG3rHHHqsyH0Rjb2VVEfCAHS3XMKAFE7JO4LX5Zmk05hZakd43aNAgnNXAkJaWJvfff3/MMmGf2PfNhg0bpDIkJydH/NxcZtx89fv9lkAF9PccaXpss5F5Yvfu3UWWa5+vtOUyB9KgNR1uZKOPbdzwnDhxolx//fXFLtscfGFnDrioKvbymFvDxVLS889YpnEuGX1uG9asWVPqMhMRERHVJLiOMNd3PvnkE3n00Uej1ikrAzJgHHXUUWq45ZZbVD3VnFnNuK4o6zWQuW5n1P2MLITG+2iQucJQ0rpgRV2rlbSua77+KMn1j336K6+8Urp27Rp1evM1XkUxb1tJ6/ClqcebjxuwHk9EREREREQ1HQMwiCoQHoDj4fcDDzyg3p977rnFZjtISkpSD8+N1LZ4OI+sGSkpKZbpAoGATJkyRY488shiy/Hggw+qIZb77rtP+vfvr24g2jM72LskQTcq0aC7FXP62HfeeccyHuuAo48+Wj799FP1Ojs7W3WtMXz48CLLW7p0qWrZhuVh32A6I/3sN998o7oqGThwYHh63AzdvHlzuFsP+81NpA0uK9w4NsqMlL3vvvuuXHHFFeFWch9++KHl5my3bt3U6wEDBqj0xDBnzhx149Rovfbzzz/HDGgpCXO3Itg/6ObEaGGGlof1CYJR7rrrrvA5HO38M27iGhkx5s+fr84dnGdLlixR361oKvKcIiIiIqosyCiAgPD3338/fF2B9x988EGRIAxkTkDdFkES5YWA8zPOOEPV7e0Py6NdV5T1GshctzPqfgiKANTtsE3RmIM3kAli3bp10qlTJ1WvR3eNVXWtFgu68EA2OiOIG5kIb7zxRunYsaNlXQhWQMYTXAcgeNrohgTbcvvttxdZLq6vvv/+e5WppKYo6XWkPegG3agY3Z78+OOPli4rS1KPxzElIiIiIiIiqkwMwCCqYDfddFP4xhYexJcE+uo955xz1Ovly5erVly4iYngDQQrLFu2TH799Vf1Gg/z8bC/vJAaGC3icEPrmGOOUetEZoodO3aEgw4MI0eOjLqcadOmybBhw9QNV9z8QpCEoW/fvuF9gD59sT6jZRMCP7CNaCWGm6UbN26UWbNmyerVq2XcuHEqYAPuvfdeNR3gxiL6jkY3KeieAzcmp0+fLscff7w899xzahrcsMTDeGSrANxMRcACbrThBquxrJJAmR955JFwqt5rr71WZs+erW52fv3116qs5u5njBTLuClrBGDgBikCOXBzEV3ToMuX8sKNWaOV3rfffqtaumVkZKjX9a2v5BUrVqiAnFNPPVXdRP/oo4/C4/D9GTVqVPg9pvvhhx/U6xkzZqgb1sgggnPYOF9Kks4bN3xPPPFEdbMb535ltCQkIiIiKov//ve/6gH12rVr1fvJkyerh/eoAyNgGQ+gFy1aJFOnTlUBGxURgIH6P7oyxPJwXYG6KureCDo2Z25DXfmEE04o1zUQ6nN9+vRR2wAIuEDXj6iP4bpg5syZUctpDuIG1NGHDh2qgiuM/VXd12oIYLn77rvl1ltvVe+xzN69e8u///1vdfy2b9+u6rM333yzOnZYF64FXn755fD+QP0Y10cIfsH10l9//aWuYVDvRQOBmqKk15G4RsW1n9GlDgI3tm3bprr5RNebsdjr8eedd54KksG5iOuEWNlCiIiIiIiIiMpMJ6JS27BhA3LQhodx48YVO89bb71lmQfLMHvwwQd1h8NhmSbSYJ5v6NCh4c/xujTM88Yarr76ast806dPt4w/5ZRTIs6Xlpam//XXX5Z558+fr7do0aLYddr355NPPqm7XK6o0998882W6c8666yI05188snhadq1axf+/OKLL466n2bPnq03btw4ZnnPPfdcPRgMWua74oorIk7boUMHvXv37uH3w4cPt8xXkvNq1qxZelxcXJFlu91u/YILLoh6vmA7jc+x/WZlHReLeT57WYr7PkQ7Pvbv3siRI3Wn01lkX3g8Hv3777+3LPPnn3+OOG1SUpI6DubPzHw+n966deuIx/Opp54q8f4gIiIiKi97XShSPXbbtm36scceW2yd216vM48rzbWFud4Wa3jssceKzFuWa6A///xTXWtEmu7UU0+1vMe1i8Hr9eqHHHJIxPns1zSoq1bmtZr9mspcTk3T9Jtuuinmep599tnw9AUFBeo6p7THuzTXima4Rok2Ltb1THmuI+3XDsbQtGlTfcCAAVG3cdeuXXpKSkrEeT/77LMS7w8iIiIiIiKi0rDmByWiaoOsD+gW4bLLLpMuXbqoFj1oYd+0aVOVDQLdLKA7i/bt21fI+tA6CiltL7roIjn88MNVBgV0oYKhbdu2Mnr0aNVi7n//+1/M5YwdO1Z1e4EWZSgzMmqgRRi6CkHLJXsaWbQQQ1YJZB/AtGh9hNZZPXv2VBknkMHgP//5j2U+vEerqKuuuircog7lRJmR+eDkk0+2TP/qq6+qadHKy8hKUVZoIYUy33PPPWp7kG4YxwUt3rDuL7/8UnVFYl/PK6+8IhMmTFDdkiAjB1oEXn755apFopEiGMrSQm7w4MGqxRiygaCfbew/pF5GVofjjjtO6hNkQ8G+QMs5HBsMI0aMUPsCWSrMsI+QuQTnIc4f41xdsGCBaq0ZDY4fWhriPDP6ASciIiKqqVAHRrd3GHBtgfoosgigvoq6DOrhDz30kOq+oSIgC8HEiRNVlghka2jZsqXq+gH1VGSgQzcoqJshs0NFXAOhSxBca4wZM0bV5zAPsiXgmgRZ6aJB/e+XX35RWSAaNWqk3mNZb7/9tqq315RrNdQ1n3/+eZXN44ILLlAZTLAvMSALxtlnnx3OFgj4HNkjvvjiCznttNPUNRLqr8Z1HTIPPvHEE2rba5LSXEdecskl6jjhmhHbhv2O61hcIxrdQEaC7IjoegXXCvbucIiIiIiIiIgqiwNRGJW2dCKqc5BeFzewDEj1i9SxZFVQUKBuJNrhJiFuEGuapt4//vjjKq0xlQy6qunQoUP4/VtvvaVuyBIRERER8Vql5uKxISIiIiIiovrCXd0FICKqi6644grZs2ePjBw5UrWEQ9YL9FWN/rGN4Iv09HTVio6IiIiIiIiIiIiIiIiIaj8GYBARVYJQKCRTp05VQyRIezxp0iSVPpeIiIiIiIiIiIiIiIiIaj8GYBARVQL0dY0gDHQ5gkwYXq9X9b196KGHqn6Yr776agZfEBEREREREREREREREdUhDl3X9eouBBEREREREREREREREREREVFt5qzuAhARERERERERERERERERERHVdgzAICIiIiIiIiIiIiIiIiIiIionBmAQ1QK33nqrOBwONbzxxhvVXZx6w9jnGB588MHqLk6NtXHjRsu+evvtt6ts3RdccEF4vZMnT66y9RIRERHVp+uGYcOGhZeL1zVB+/btw2W65JJLqrs4VAPOl2nTpoXXe8YZZ/CYEBERVcE9PNTDjOWhflaf64dVXQeqSfu+th4zqhnw7MX821Sbnk8QRcMADKIabu3atfLSSy+p1xkZGXLhhRcWmWbhwoVy8cUXS6dOnSQxMVESEhKkVatW0qdPHznvvPPkiSeekAMHDkhtUpsrkOY/9rEGVAyofO66665wpezOO++UYDDIXUpERET1UnHXDeabm+YB1w6tW7eWk08+Wd5//33RNE2qU127eWa+rok1MOC7/I4//njp16+fev3VV1/Jb7/9VgFLJSIiqlnsdSVjcDqdkpycLJ07d5YzzzyTDZVqmTVr1sh1110n3bp1U8cxPj5eWrRoIT169FDH8+GHH5YtW7ZUdzFrDPu1jcvlUs9FmjVrJr1795ZzzjlHXdt4vd7qLiqVE64H+UyFaiN3dReAiGIbN26cBAIB9fr6668Xj8djGf/OO+/IZZddVuRG6Y4dO9SwePFi+eijj+SEE06Qhg0bcndTndKzZ08ZMWKE/PTTT7Jq1Sr1fbj88suru1hERERENe66IRqfzyfbtm1Tw3fffaeyCNT2oAeqv2677TbVCAHuueceBmEQEVG9oeu65Ofny7p169TwxRdfyN133y2PPfZYeJpGjRrJU089FX7fv39/qUvuvfdeycrKCt8zrC2mTp0qo0aNKhIssGvXLjUsX75cHc9evXpJmzZtwuP//e9/h7czPT1d6jM8G8H+w7Bnzx5ZsmSJfPrpp6rB3nvvvSfHHntsdReRYvjXv/4lKSkpZd5Hdf23jWonBmAQ1WC7d++Wzz//PPz+3HPPtYxHVgvcXDWCL9DSbcyYMSo6FhVuPJD+/fffVSBGfZSdnS1paWnVWoaOHTvKtddeG7ViQGW7oMzLywtXyvC9QAAGTJw4kQEYREREVO8Ud91gh8BsPJxG9rDVq1fLBx98IH6/X41DQOvYsWPVDV6qeNjvkQLjBw8ezN1dAdd9eHiRlJSkrodxLYyb7zyXiYioLkP2J7T2x/0yZMdAN3QIsIUnn3xS1esaN26s3uPv5e233y511ZVXXim1De7ro3GlEXyB+8VnnXWWtG3bVtXPkeVu9uzZsmHDhiLznnjiiWqo74xrGwSjb9++XQW04LkI4D0e7iM72imnnFLdRaUocC1Unuuhuv7bRrWUTkQ11hNPPKHja4phwIABRcZPnjw5PB7Dhg0bIi5nzpw5+p49eyyfDR06NDwfXm/fvl2//PLL9RYtWujx8fF6t27d9Oeee04PhUIRl/njjz/qZ555pt66dWvd4/Hoqampev/+/fWnnnpKz8vLiziP1+vVX375Zf24447TmzZtqsfFxemNGzfWDz/8cP22227TfT6f/tZbb1m2KdIwbtw4tTz7tGvWrFH77NBDD1VlwnYB9sstt9yiDxkyRG/btq2ekpKi1o0yDB8+XH/llVf0YDBYpLyR1lkS5vmMMhQHyzfPh3312GOP6YcccojalubNm+tXX321npWVFXH+devWqX3Yp08fPS0tTc2DY3PiiSfqH3/8cZHpZ82apZ933nl6+/bt1fFOSkpSx/zGG29Uy4oE58hll12mN2vWTE9ISFDrevXVV/X169dbyo7jYjd37lz9wgsv1Dt06KDmxfp69eql33///fq+ffuKTG8/Pzdu3Kiff/75at0Oh8OyjszMTN3tdoenX7hwYYn2OREREVF9uW6Adu3ahafBa7M777zTUp+z1x/tdbO9e/fqN9xwg56RkaHqnZ07d9affPJJXdO08DznnHNOeJ6+ffsWKQ/q6OZ1fvDBB5YyRhsibc/FF1+sb9q0Sb/oootUHR9l6tGjh/72228XWS+mNe+HnTt36pdeeqnepEkTdZ1w/PHHh+uTKCO2o2HDhqr+eswxx+izZ88u1bExry/WNVusfYO677Rp0/Rjjz1WXXehLMOGDVPXeWW97jLbtWuXft9996nxuJbA9C1bttRHjRqlf/311xHXgevEF154Qe/evbu6nsD011xzjbrutJ8vdjh/HnzwQb1fv37h9eFcOvfcc/X58+cXmb6k132Gs846Kzwtrm+IiIjqEns9AXUNM9TRzOPN9YVIdYzy3jO0163ssrOz1d/tI488Um/QoIG6h4f6yYgRI/R333036r3nDz/8UD/iiCPUfUTU01BPQPljrc9eP7RDvQ/3InEPG2Ux6jyoV7300kvh6QKBgKobjRw5Uu/UqZOa1uVy6enp6apMGLd///4iyy+uDhTJokWLLMdk+vTpEadbsmRJkXpkcfv+jz/+0E866SRVf0Q9F/fBsXx73cq8XPsycS/6jjvuUOcD6l1t2rRR1w72+iTu72I61KUxLep4ONaNGjVSxx7XCvn5+UXKWNwxiybWtQ2uSVBPxT1kYxocw0j3oCvrGUd56to4Rubj88svv+gTJkxQdV98J7t06aLeA55p/N///Z86T1F+/Ivvm/m6LNqzh4ceekgtC/OhLn7zzTer++zRzr8rr7xSTZ+YmKi+l1gXnhX8/fffRabH93rixInqeQz2Db4/2HbMc+qpp+oPP/ywnpubG7V8kX6vIg3m5z+V/dtW0u8CkYEBGEQ1GCpFxo/8rbfeWmT8pEmTLH9YvvjiixIv21wh7Nq1q6pkRPojhpuRZvjjjT+2sf7w4cE6KhZmW7ZsUTdBY8134MCBcgVg4A96pD/AU6ZMKXaZqIzaK/yR1lkSkcpQHHslw74txoBzwg43q1HxibZtp512mmV6XGiYK6D2ITk5Wf/qq6+KHD9UKiJNj0pTrArO+PHjY64PQTErV66Men6iYocAlFjrwE19Y9wjjzxSon1OREREVF+uG4q7SYkblOa6Fh72R6ubIUAYQbWR6nV4qG5AoIJ53Lx58yzLxI1CYxwCHAoKCsocgIGbpLixF2l6exCG+UYabghH2hbcjMM1RKRlot69YsWKKg3AOOqooyLWpyOVpaTXXeZAadw4jjU9Aqnt10q4Tow0LW6qIigj2vXQggULitTtzQNuzho3lA0lve4zoCGBMQ7BQURERPUhAAP3bNGACQEC5vH4LNq89vtrZblnGCsIAEGTHTt2jFnPwAN7+4P5Rx99NOK0CMQYPHhw1PXFepiP+i3qnNHKgYZmhpycnGLrpFjXjh07yh2A8eeff1qW++yzzxZ5eB5NrH3/888/q4fM9nI7nU79lFNOiVo/NS8TdWFzvc48XHLJJUUe0Be3zxCAYH7oXlkBGIZrr73Wsn4EJlTVM47y1LXtARgIWo40H54nnHHGGcVel0V69oDgkUjz9e7dW53/Zmi8iqCRaOVHoA2CLcyK27f2866yAzDK+9tWmu8CkYFdkBDVUEiZNXfu3PD7AQMGFJmmb9++4nA4VIo5QPcj7dq1k4EDB6pxRx55pBx11FESFxcXc11IO5yamio33XSTxMfHy7vvvqv6l4O33npLTj/9dJXKFZ555hl57bXXwvOedNJJaj3oWw3zoZ89pHm94IILwt1CIJXaaaedJsuWLQvP161bNzUv0sNievQ3bfTPhf66PvnkE/njjz8sacQM0dJR/fbbb2q5KKvT6ZSCggL1udvtlj59+qiUfE2bNlV94mHcX3/9Jd98843af99//71MmjRJzjzzTKlIW7ZskaeffrrI5+ivD+kBo8G2nHHGGdK9e3eVEhopBGH69Okyb948dYwB++jiiy9W6aMB58Opp54qhx12mOzfv19mzpxpWS7268MPPxx+3759e1UOpOjFsc7NzVXde6APwaVLl0qnTp3UdDfeeKPaFsOQIUNk+PDh8ueff8qUKVOibgdSYaM/cgPOxxEjRqh1oP+9nTt3yubNm9W24jxwuVxFlrFmzRr1L85DbBf6JzdSJ5q/H3///bd6PWPGDNXnIxEREVF9UJLrhmhCoZC6FnjzzTfDnyHd8dFHHx11HqTzTUhIUN3sJSYmyssvvxyud//3v/9V9XZcf+AaAXX7BQsWqHGvvPKKpWwff/xx+DWuHbBM1OFQ7zX3VY66KurxsWAduGa49dZbVVlwvYJtg8cff1zVlyNBfRnT33zzzap++vrrr6vPUTdGnRrXKrfccotkZmbK22+/rcZh+ueff15td1mgbJG6ILnqqquidp84a9YsOfTQQ2X06NGqzmtcO9nLUprrLqPrDlw74VrOuG668MILpXXr1vL111/LokWL1Oeot2P9xjXZ5MmT1bWDoXnz5nLRRRepdOf4PCcnJ+J24HPsV+NaE/Ohuxyk2p42bZq6dsFxw/HA9Wy08zDadZ/BfJ4hbTdST7dq1SrisoiIiGo7dB+HIZLzzz9f3SsuibLeM4wGf9NxL2/9+vXhz9C1Bu51/vzzz6qrMEAdAH/7X331VfUedZ37778/PA/qMOiiA3VFbCe64yitrVu3qrJgGwzHHnususeM7cO9VmybAfdXO3ToIIMGDVJdfqPuhu1BNyDYT5hn06ZN8sgjj8iLL74o5YE6FurURn0G9VnUX1GXxv1slGHo0KFqmpJCdyao0xld0QCOZZcuXVQdD/fDS2Lfvn2qC3TU81CXQl157969ahyeA6DO3rJlS/UedTJsC+ph6B4d+wxdqKxYsULdH8a9a9xHRr21qrqKQP3aXGfHeXfHHXdUyTOO8tS17XD/H13N4NoKx8Dobn78+PHq35EjR8oRRxwh//vf/8LrMl+XRfLLL7/Ieeedp77HuLdv3FdfvHixPPDAA2p+wPcN133YdmjSpInaBtzDx35CV5g4ttdff73q9g/1d3zPzNeX+K7hOQLOR3wXce1m3ofR4BoBz4mw/fjeRerSEc9YquK3rTTfBaKwcCgGEdUo9qi933//PeJ0Y8eOjRkFiFZdaF1m72LDHJGLYebMmeFxq1evVi2PzNkhAJGY5ohNRJGafffdd5Zl/vXXX+rzb775xvI50mv5/X7LvEgZbP6suBRqkVpCDRo0SLWci2bt2rX6p59+qr/44ov6008/rVKJIb2WMT9SZpnZI0pLqrjITHN0ZrQoT3SZYkAaL/M4tFA0IEWaedwnn3wScbsNiDQ2pkXaPHPXNEhnZl7WTTfdpD5HNLc5QhRp+cxRufbWb+YIU3PUPdL2mSO4ly9fbpnvyy+/jHp+Ivo7FmS9MKZFGjAiIiKi+qKk1w0lyS6BVl7Lli0rMq+9bmZuHWTONoBh8eLFlkxt5qwSRkpbZD8zz4PUy9G2J1L6WPv2oK6K1oMG1KXNy0Dq62gZKd5///3wOKRHNo/76KOPwuPQtYvxOerUJWVfX0lagNn3ATLRmbfhsMMOi1iW0l532TOfvPbaa+HpkJYYmRKNcWgxalxToptDc4s3XD8aZsyYEfW6B5ktjM/RInPz5s3hcbhOGDhwYMQsfqW97tu6datl+l9//bXEx4uIiKimK0mrcCODlrn+UFw9qyz3DGPdw0XXCuZ57r333vA43Fc0Z3DDfWhjffasBT/88EN4PtQhzfesS5oB4/bbb4+aCSHS/VMDyoT6FbqbeOaZZ9S9ZHRJZywH2T3KmwHDXkeK1jof22DPFBJt3+P+sHn+u+66KzwOdShkG45WD7XXXVHXN+AawDwuUvcZqIfhHi+6dDHuv/fs2TM8D7rUq6oMGNhf5vIig0FVPuMoa13bngED3fUY99SRjcI8DvVyA7JQRLsusz97QPcj5rKYzwl0w4JueGD06NGW76k5+x6uAczdgmN/ADKAmNdlzxRjZBIx1+cjZcAwxOoyp6p+28ryXSByFoZiEFFNYkQrGuwt/g3IroBIPbQQitaq6+6775Y777wz6roQ0YuMBgZEw5qzTBiZKNDazVwuRJAiItgYEG1pZkQy27MwPPTQQ0WiL9HSrrhMHcVB9Cyioe0QkXzMMcdI586d5eyzz5YbbrhBTfuf//xHZVMwIAKzprjuuuvCrw855BDLOERbGsz7FucAts/OiNpEVCeyfhjQ+gxRqwZEoiIC1NzSzjj+RpYVQJQropoNl1xyScRtwPoQ2WxABDDmM84XRLxHOl/sENGKYxaL+fth/+4QERER1WUlvW4oSQsj1NPtdTQ7tPhBy6+S1FXRytFoCYS64fvvv18k+wVacvXu3VvKA63VkCmtJGUyQys0c/3ZXBfGtYk5Ox6ukYpbXmVB/RsZCw1du3aNWJbSXneZ699oxYYWXQZkRkSrOPN60IIRjKwmxr437xtcd+H6MlrmCgNawKEsxrUBrhPQ+rS4a4NY133RvgO8PiAioroMmcLQShwD/kYadS/c10MmWrTcLk5Z7xnGYv9bfumll4Zf4+++OUMZsksYGd3M9QxknzjhhBMsdbxYmdqiMdeRUOeNlIHB3OodGSSuuOIKlcnhlFNOURkAxo4dq+4lm5dVUfeScd8TGRGwbagX2aF1Pp4BoE5YEuZ9CJdffnn4NepQ5jpeLKgfXn311SWqY+M1sowgIwEyHSMjgnH/HVkFquP+u/l+Nhj7tqqecZS1rm2H6Yyym7+HgGxyBnOd3FhmNObvH8qC7A/mrHXIkmjfBtT7kanDvD7z99H4XWjQoIHl+q5Hjx4qSwjOc2SMwW8NsoDEqs9XlIr6bSvNd4HIwAAMohrKXkGIBQ/A8YcE3Tl89dVXKtjCfuP0pZdesqQdM0Pq11ifGX9AEMxRGkZFxj5ftBty5WWuAJih0me+2RdNtP1THkgRh2NpH3799deY85n/8KMSZGak/LLv2+L2K46j+bzCRYSd+TNj2Ui5HOt8iXT+RFpfcaLdGMUFEG6Ox2LeJ6VZJxEREVFtV5a6DwJccZMe1w3GTXrU/VBv/uKLL2LOa7/pF6uuipuP5sBidEMC5hSyuLldXqUpk1mzZs0sN009Ho9lnLkOan4dbXklgdTVka4P7NtQ0u2Ldm1QkusD8/Q4J8zbH+l6IdL1QXHXktHWVxxMG20/R7vuM9jn4/UBERHVZXi4iQfdGFC/wz1Q42EtukQwd+1W0fcMY7FPY19mSeoZkVL6RypbacqCLlnMDcsiQRcHb7zxRrhLu2jQxUZFwYNhHDsEzKAR24MPPqgClc1QT0dDw+LY7+Xa92NJ9yHqdOaH5LHq2AjyQDd1xdW7KuP+ezQItDDDQ/+qfMZR1rq2HQKRDPZlmLvZs98/j3XNUtz9/UjPg4r7XTAHIXz00UfhBsNYxg8//KCeT6Gb88MPP1x1mVIVQdIV9dtWmu8CkSH2Ey0iqjZNmza1vC9JxQB/CNAaDcP//d//qX/Rh5cRuYu+dhGFaWf0wRvtM0QtGhHCZmgRNnDgwKjlQVRkpPlw0xF92FW05OTkIp8hWtMc5YhoTlyMoHKCyjb6pbNHBdcE5hvBkSKfDdi36GvN2K+xoKKHZRmVDgTs2Jk/M46bcfyjnS+Rzp9I60N/b4h2jSZaa8tIx9XO/P3AzXIiIiKi+qIs1w1paWnhln9o0YcWSuijGNBa7V//+pcl44KZvZVXrLoqXHPNNfLoo4+q6xE8BEDfxEbrLtTzzK2tyqq0ZYo2n1lxAcBVqaTbV9rrLvP0uDmJhwjmm7r26wXz9YHRmra4a8lo68M5aO7fPZJo21nc9YH9O8DrAyIiqk/QkAktvI2Hm9OnTy92nrLeM4zFPg3mN2eZiFXPMBj3PKOVo6TMZUEAAx6WxgrCMGdr69mzp3z44YcqABR1sjvuuEPdW64sOBa4f4ph3Lhx6oE1sgaYy48gkljs93KxH83BAiXdhyWtgyLLADJ4mLMKvPrqq2qdyByAjHOfffaZVLXXXnvN8v64446r0mccZa1rV8U1i/05kb3+bn4eZHwPi/tdwLlrvs+PZzIIgkGG7LVr18ry5ctVkE5BQYH6DI0B3nzzTalMFfXbVtbrTarfmAGDqIZCZKM5qm7Lli1Fplm4cKGKyI304B1/BFJSUizvzX8EzTC/OUPEmjVrZM6cOeH3RrQtUiuZUzThxtYtt9wSjrI2Bty0xY1gpLkz0tCaIYI3GAxaPkNXIIFAIOIfNVTiymrv3r2W90iDjGhXVLJx43fRokVSm5n37d9//x2xxaJxfiQlJVm6qkFwjnn/4IJs48aN4ffG8UNEqrlS8d5771miOt95552IZcP6zKmgUZnBDXj7+XLzzTdLx44dw5XZsjB/P9DVDBEREVF9UZLrhlhwAxddFppvvj333HMVVj5cP5jT6956662WujkexMe6uVWea4H6prTXXUZ9H9DC891337W0TsTDBgOuJbt166Zem1tj4roR148GXFdGCww3pyhGwA+uM+zXBhhOPPFEGTRoUJlvbNq/A7w+ICKi+mT9+vWW+33m+63RlPWeYSz2adCFtgH3Fc33E/GQHn/7AY3lDJs3b7Z0gYCHubG6KStJHQn3s5999tki05jrL+ZtRzBBr169VB0VD47NgQYVYfv27aprhmXLlkUcbw+KLkl3g+Z9CB988EH4NYKizXW8ioCMG+ZsIei2BfUvHFc8vC9JEFBFwsN2BK0g8NtclzUy71XVM46y1rWrgvn7h7KYg45wzhldbJi3AfX+lStXht/jGsD8fTRPiwALHAcsB92kIPAaWTHM2Q9L2ii2PNeHlfHbRlRSNadJBxFZIBoSFU+jq4o//vhDzjnnHMs06I8LmS4w4A8JpscNWPxBR/+533//fXjaIUOGRG3FBieffLJcdtllar2oDJgrD1dddZX6F0EL6LcN0Ynwyy+/qAooKlWo/KGysnjxYtUfGiqkRl9iiNjFg3gjEwW6SUF0KPpTwx9B/OFG9CMe0BvRlUZKMEDENrpZQUo93IRDf3fR0traobKHchsBA3jYj3Lk5ubK22+/XaGp4qLd/EMffZFgv2CbygPH4ssvvwxXcnETG5lPcD5kZWXJ7NmzVRot7HPA8TNugGM8bp6i1SEqLuaIU6TRQoS1kaYOafCMCwyck8OGDVMZLVCZMrKsRCufcd4iyhXbi9TWKBNuuuLiAsvDa1zoRAsSKs78+fMt3b4QERER1RcluW4oDm4uoiWfkTkAN6VRb7YHR5QVlmXUNXHTN1b3I8hWgG0y6umoS+MmGa4b0GoSdcnaDC3xItV50V92aY+bXWmvu3C99sgjj4RbyCIbCq4fcC2Gur/R9zPcdttt6ia6cX2INMKA60Zca6JPaxyzWK3YsD5kQzFa2KG8OJ5oIYcbtLj5iX6XsV60+CxLH+/2awOcM+a0zURERHUN7q0Z9x7xsBsPdc0p90v697Qs9wxjwb1m/I3H/UBAHQB/4/HZzz//bHlwi/u+xgNx1DPw4Ny4l4vlXHrppeohLB4aF9ctSLS6KJaJ+8GAh+uoy6AOjYfPuL+J7F5GHQoPjZcuXRquu+F+NOrFyOJg79aivFB/QtcMGLBePABGgDTWiexx5sZ26JYuWgZhs1GjRqnszwjugAceeECVGxkpUBc0B89WBNTfUbc0uj5B/RL1PWwDGvLZG0hWNNxXxncA9VJs808//WQ5TqjDohxGHbyqnnGUta5dFVDXRnlRV8a9ffM5gWdERmaNsWPHqu3Ebwq+e0a9H/vQ/AwJxxrTGhCsgv2N+/Q4F/F669at6nlMaTLp2J8TAbq4RMA2yohnFP369avS3zaiEtOJqMZ6/PHHUVtWw+DBg4uMnz59enh8rKFJkyb6kiVLLPMOHTo0PL579+56x44dI8570UUXWebTNE2/4oorSrRes82bN+s9evSIOf2BAwfC0y9evFh3uVwRp1uwYIGa5q233rJ8vmHDhoj78brrrou4nN69e+tHHHFE+D32iZl52nHjxpX4uJVk32BA+Q1YfrR9V1xZ3n//fT0xMTHqek477TTL9HfffXfMcmFZX3zxRZHjl5GREXH6Y489Nup2wYMPPqg7HI5i94f5+JnPT/txscvMzNTdbnd4+j/++KOER4qIiIioflw3QLt27cLT4LUd6mzmutnDDz9corqZ/ZoE7yMZPny4Zbpu3bpF3Z6zzjorYn3x5JNPjrg9F198sWX+WNcJmDbafijruFjM88UazPsV5Y1Vv45VltJed82ePVtv3LhxzOnPPfdcPRgMWtaD68RI07Zu3Vrv0qVL1PNl/vz5eosWLYrdH+ZrnpJe90U6f2644YYSHysiIqLawF5PiDW0b99e37ZtW4nrGGW5ZxirXrJq1SpVhljLRB0xLy/PMt+jjz4acdpGjRrpgwYNCr/v0KGDZb5Y9cNp06bpDRs2jFqOPn36hKf99NNPI06TmpqqjxkzxvKZWWnuZ5b2eGLf//zzzyXe95g2Pj6+yHJwj/akk06yfLZp06YSLTPW+fPkk09GLDfuJ48YMSLqMmMds1jM88UaUDf95ZdfisxfVc84ylLXjnV9VdZx9mcPp5xySsSy9OzZU8/KyrJs88SJEy333u0DnuG88MILlnmSk5NjbjPm+eabb6KWz8zn86njGGk5Tz31VLX8thW3PiJgFyRENRiif40US0jxZE+lOnjwYBWhiShW9GHWtWtXFU2IaMn09HQV/YcuShAJjf7qokEqrblz56oIY2Q7QIsz9Gv33//+15IezohmROTvtGnTVKQgIm8RHYhyYl5kRUD6LUSJ2lt0oTXexIkT1TSIakaUIqJBESmKNF+IFDUg6hQRvuh/zfx5Wbzwwgvy2GOPqShflBNRl4g4nTFjhqWbltrq/PPPVxHRSOeM/ruxTdhOZJkYMWJEkX61sS8QwYv0X+jrDcc7MTFRRVmj9SOO3ejRo4scP2RVwTmJ8wXHHNkssG/t/elFiqhFKzREz3bp0kWtC8cey0EU/l133aXOb5xLZYEMIEa07eGHH65SGRMRERHVJ8VdN5TETTfdZMl4gSwYaE1WUdDy0Ozyyy+POi36jMa1CertVdkSrC4o7XUXugHE9SKuG5FFD9cSmB7XEsiCh7o2WtLajwOuE3GOIFUyrieQoRD1fdT7cdyiQYszrA+tAdHqFOXCspGtEdesaCmI9MRoqVYWeXl58u2334bfX3nllWVaDhERUW2Ev+FowY97xvhbi5b6sf4u25XlnmEsuFeN7p+RvRn3eHG/GmVE/eT4449XreGnTp1a5N4v6iWof+A+H+5BoqU8sv6inmGur5Ymky7unSMbB7pCwD1zoyy4P4lW/eY6A9Y1adIkdY8R+wDrQVYJ3D+PdY+9LLCfkRUB+x4ZFlC3wjE06ke4R456NDJyoG5XUpgWWUaQKQD1u+TkZJWVANkhsL1mZc1IbIa62yuvvKLKj+sS7Ffcs8b95NKcg2WFZxY4Vji3cIzOPvtsef/992Xt2rWqG5lI01fFM46y1rUrG85vnHP4jmK/4Rgh+wO+//YsiHiOsnDhQnX9howZ6P4S+wrPWnAdiq5E7JkjsH+Q7RAZQ7Ct2K+YD92Q47zAOY/sNiWB8iFjDabHuVqWbgor+reNqCQciMIo0ZREVC3wB8noD+yJJ56QO+64o0KWi/RMCEAApIIyUhYT1TYnnHCCuniA119/PebNfCIiIqK6qrKuGyoK0triBh/ghhdS0OLGLFFFQvCGkWIYwd6//fYbdzAREVEtg24f8HDUbvPmzerhOrrlhmuuuUZefvnlaihhzYdu//CQ3P6wGo3YEASLB+qARpgrVqyoplJSVUEwyfjx48Pv+ViYqPIxAwZRDYc/jEZrthdffFECgUB1F4moxkD0NyLljQsGo08+IiIiovqmJl434MYvAr3Rx7E5SBYtjxh8QZUBWRwNaG1LREREtc9DDz2ksng8+eST8vnnn6ssAfi7js+M4AtkEbC3uqdCqIN37txZ7r33XpUJ4ptvvlHBKsjIYARfwG233cbdRkRUCdyVsVAiqjioKCEN0nPPPadSCb/33nsqtSsRiTz++OPhiF209MTFFxEREVF9VBOvG3bu3Fkk5S9SSCMlNlFFQwpppISGM844Q2XAICIiotoH9/rQrR6GSNDFw5tvvindu3ev8rLVJuvXr1ddL0SD4At210ZEVDnYBQlRPcUuSIiIiIiIqDJt3LhR9Q0M6Mv6qKOOUjeBe/TowR1PRERERBH9/vvv8sorr8i8efNk165dkpeXJykpKdKlSxc57rjj5Nprr5V27dpx78WAgGxkEEF3bOj6LysrS3VJ0qZNG5VJ5IorrlDZMKh+YBckRFWvRgdgZGdny/PPPy+ffvqpunGDfmI7duwol1xyiVx11VXh9KqQn5+vUlN9/PHHsmPHDmnZsqVKa3r//feriEi7TZs2yd13361S1+fm5sohhxwiN9xwg/rDE8nMmTPVj9SCBQvU+/79+6sUr0OGDKnEPUBERERERERERERERERERES1QY0NwAgGgyoC788//5SLL75YBg4cKD6fT7744gsVDHH++eervqsgFAqpyMcZM2bIhRdeKMccc4wsWrRI9Wk1dOhQFWThdDrDy0bEHwIoEPV3yy23qBY5kydPlm+//VYFWYwbN85Slh9//FFOOeUUycjIUEEaiBR89dVXZeXKlfL999/L8ccfX+X7h4iIiIiIiIiIiIiIiIiIiGqOGhuAgb47R4wYIWPHjpWnn346/DmCLfr16yeLFy+WzMxMSU1NVf19XX755XLjjTfKCy+8EJ72mWeekdtvv13eeecdueiii8Kf4zX6w0Uwx+jRo8Ofjxo1SgVUrFq1SmXaMNaHvnT37Nkjy5cvl7Zt26rPEbyBtKmJiYlqenOABxEREREREREREREREREREdUvNTZqAAEO0KpVK8vnLpdLWrRoof5FlyTw7rvvqn8RrGF23XXXqQAJY7zRVcnnn3+usl6Ygy/gtttuU5k3Pvzww/Bn6CML3Z+cddZZ4eALSE9PV92VrF27VmbPnl2h205ERERERERERERERERERES1i1tqqKOOOkqSk5Pl8ccfl9atW8ugQYPE6/XKp59+qroEeeihh1RXIEjgsWDBAhWo0a5dO8syEHzRt29fNd6wZMkSKSgoUN2b2OEzh8Mh8+fPD382b9489e/gwYOLTG98humPPvroCt1+IiIiIiIiIiIiIiIiIiIiqj1qbAAGslxMnjxZrr32WjnnnHPCnyckJMgbb7whl156qXq/f/9+ldWiZ8+eEZeD4I05c+ZIdna2pKWlydatW8Of2yGgo0mTJuFpINb0xmfm6SPZvXu36sLEDOVZvXq19OrVS62XiIiIqobP55MtW7bI0KFDpUGDBtztVOdNmjRJnnzySRWIjAxyQ4YMkcceeyxq/dkMXe29/vrr8tdff6kBdW90/YfPotm0aZPcfffdMnXqVMnNzZVDDjlEbrjhBpU9rizQ7eCMGTOkTZs2rDcTERERVRBeFxERERER1bMADKObD9ywHTZsmPzrX/9SgRbvvPOOXHnllSpTxSWXXKI+g2hBDAjYAEyHAIySTG9MY8wXbXrzsmOZOHGijB8/voRbTURERFXhq6++ktNOO407m+o0BC4j8AHBFk888YTKKDdhwgSVyW3WrFkqGDgWBDI//fTTqvu+/v37q0x0sSAwGZnr0J3gLbfcouZDUDXq79u2bZNx48aVehsQfHH66aeXej4iIiIiKh6vi4iIiIiI6kkAxqJFi1S3Hrhxi25IDBdccIHqnuT666+Xk08+WZKSksJR25HgJjMY05VkemTBMMSa3r7saK677jo566yzLJ8tX75czj77bDksdYQkudIPfpiQaJ0xP6/wtcdjHZeeankbTLUGiDhCevi1K7vAOu+BLOt7T5z1vdt0Wrhd1nF64XIPrsgRfbzPbx3nt71PSba+jzdtY4FtfyfYtl+zlWN/ZuHrZNvxSEmKXeZQqPB1IGgd53Ra3+fagm3iTPtK06zjgsHo61Hz2rcpFH0/JxezDeZ127fBXg6X/ZiaXgdsxyg1xfo+8WDQUZjXdJyCtu0PBaPvK6zWtE2627qfHfZl2Q6DZXzewe9heFk5OdZpbd8VyzEN2o6J075fbcfBfFzs57PDVsgk275KsH5HtbjC4+DMtX1H7ezfQ/Pxt5+jBdb9UYR5+nzrtKF9+yzvX/11ZexlEdVSazcEZPSlO1VreqK67MCBA3LbbbeprG0ItkAwMqAO2r17d7n55pvll19+ibmMU089VWW9aNiwoWzcuFEFVMRyzz33yM6dO+WLL76Q0aNHq88QfDFq1Ch55JFH5MILL5SOHTuWajuM7yoeDnTu3FmqSyAQUIElCBKPi7PVn+sZ7gvuB54T/H7wt4K/mfz7Ufv/lq5du1YFufK6iIiIiIiongRgPP/88yrowR644HQ65cwzz5S5c+fK/PnzZeTIkSoAIlo3IPgcN5uNG86xug3B+vbu3ata7RliTR+rexKzZs2aqSESBF+kuBup1w6P9SG77it8QO+Isz7M1RP+Cdr4RzDJGrzhCBU+oHb5TIEcER7mOuyBAOYADNtD81IFYGjWIAo9ZH3Y6/CkWcebsow4gtYH0nq87WG2PdjBVVgOR5w1aEBPSIldZtNDeIcjYJ3XZXu47c21Lsp8kWwrky7WZYnYAxLiowdo2Pazw1PMNljWbdsG23uH+fiqVUU/Zg6P9TzTbUFCDs10TJ2h2IEftkAfLaEwAEc3BSOo5QbsgRHRAzAcAWtQjOaybp/T0yB6AILDHpxiW5Hpe3SwoIX7SrftK3sARpHv8z8Zc8Ll9BSW0+W3fUdtdPv30Bk9AMMRKiaYwzS9btt3Idv+6HEIu0eiuo1dgFFdh8wT6PYOQRhGXRjatm2r6tPILIfueGLddG/cuHGJ14escJ9//rkK0jCCLwwow5QpU+TDDz+U++67r0zfVQRf9OjRQ6rzQcm+ffvUPmEABvcFzwl+P/hbwd9N/v3g39K6Uq/gdRERERERUT0JwECKYgjZswao57rB8L/oiqRfv34yc+ZM1d90u3btwtMVFBTI33//rVIsG5BmGV2HIJ2yHYI68DB6wIAB4c+M15gerffMjGWYpyciIiIiqgnmzZun/jXXhQ34DAEYCxYsqLBWj0uWLFH17yOPPLLIOHyGejsCqGPZvXu37Nmzp0jrTONBBYbqgmsPXJsY1yL1GfcF9wPPCX4/+FvB30z+/aj9f0urs15FRERERFSX1dgADLRu++mnn+Ttt9+2BDjg4gAt51wulwq8AKQyRgDGM888Iy+88EJ42pdfflndBMZ4A7JljBkzRj744AOZNGmSpXUe5ne73XLuueeGPzvmmGNUUMenn34q48ePD9+gRmvC119/XaVQjnRTm4iIiIioOsXK1hYry1tlrA8tK9HNX3HrmzhxoqpzR4I03WgpWl3wgCQnJ0cFbOOaoT7jvuB+4DnB7wd/K/ibyb8ftf9vKepWRERERERU8WrsncNbbrlF3nvvPRVEgRu1J5xwgkpr/P7778vixYtVGuOMjAw17aWXXirvvvuuTJgwQV08IGhi0aJF6gbusGHD5IILLrAs+7HHHpNp06apwIyFCxeqNMlI0fzNN9/I/fffL506dQpPi0APLAf9Vg8ZMkRuuukm8Xg88sorr6j+rb/99lvVLQoRERERUU2CunO0tNLICGeeprLXZ6yzuPVdd911RbogNPonRx/ppekSpaIZ2fcaNWrEAAzuC54T/H7wt4K/m/z7wb+ltb5egboVERERERHVowAM9E2NlMgPP/ywTJ06Vb7//nsV+NCzZ0+VeeKyyy6zBEl899138tBDD8knn3wiH330kbRs2VLGjh0rDzzwgBpvXza6D7nnnntUIEVubq507dpVvb7qqquKlGXkyJGqDFg+lgf9+/dXQRxDhw4t34YmJIgjLlG91FMO/mtw6HrhG7d1Gxxev+V9sFWq5b3uchSuwm/txsWZb12P2AJI9LTkwjeaZp3W4bBOa5vX4TOVK852ejWyXtghyj/qNnms/V86AraUjAVe6/ukxKjzit+WUtFeLlM5dNs4PdFjLYftXDIvW3fZ9kWB9X0oK8fy3hlnXbY4TNP7fdZxQVtXPLaueXR/4b5zpKZYp02zvtdt8zpCpmOcYH1gUmR/mM6rIsfFdjwl8eCDHYOWZH0vzijneqTjHes8tO13ZwPbeRbvib5s2/fKfn5r6abvglp44boc/mDM80yz7UtnVq7lvcu8zfb9nGAts2477xzmY2jfV7ZzRbelFHWY+pZ12Mroat7MuiwiIqrVkPkNfD5bvUJEvF6vZZrKXp+xTmTBiKVZs2ZqiAT9o1d3H+m4rsBDkuouR03AfcH9wHOC3w/+VvA3k38/avffUtZniIiIiIjqWQAGtG/fXt54440STZuSkiJPPvmkGkoCWS8QqFFSw4cPVwMRERERUW1g7makW7duJe4upCLWZ4egjL1798qgQYMqbH1ERERERERERERENQ37ziAiIiIiqoMGDBig/kXmNzvjM2R1qyi9evVS3YxEWt/cuXNV9jOjTERERERERERERER1EQMwiIiIiIjqoNNPP11SU1Pltddek+zs7PDnmzdvls8++0yGDRsmbdq0UZ/l5+fLypUrZceOHeXqgmTMmDGyYcMGmTRpkmXcM888o1Jsn3vuueXYIiIiIiIiIiIiIqKarUZ3QUJERERERGXTsGFDeeqpp+Saa66Ro446Sq6++mrVFciECRPE4XDIc889F552/vz5qru9iy++WN5+++3w51lZWWp6yMzMVP/+/fff8sgjj6jXffr0kVNPPTU8/WOPPSbTpk2TCy+8UBYuXKi6/Zs8ebJ88803cv/990unTp14OImIiIiIiIiIiKjOYgAGEREREVEdhaCLxo0bq0CMO+64QzwejwwZMkQeffRR6d27d7HzHzhwQAVOmCGwAgMgYMMcgNG2bVvVBck999wjr7zyiuTm5krXrl3V66uuuqoStpCIiIiIiIiIiIio5mAABhERERFRHXbmmWeqIRZ0R6LrepHP27dvH/HzWJD14qOPPip1OYmIiIiIiIiIiIhqOwZgVDevV/RgwcHXacnWcXGmwxMMWUbpBV7L+/g9iZb3WnzhvI4Cv3W5mmZ9H++xvHXk/VMeCNmmdTljziueuMLXPut6HV5bOew3883bZF+u07pe3V6u9BTre0uZXdb3DkfU9w6vL3YZbeWwzGs/Rj7rspztMqyzBoLWZZm3ye2Kfi5EGK/n5kXdBj0tybZe6/ZrSYXLcvjsZbJukyPftn9iHaP4OOvofG/U460nW89fhy9gXVaKdbz9+xBzWnu57Oe/eb0FtmO2z1YO03mm25brOJBlXZjfNm+SrVzmeW372X687eeK5Vyzn5NB27T27U9NirofkY6eiIiICmm6Lou37ZOpK7fK4m37JbfAKymJCdI7o5GMOLS19M5oLE7+/SQiIiIiIiIiIqJ/MACDiIiIiIjIZntWnjz982JZvTtTsr0BcYgu+H+/NyCbDuTKjLU7pGuzBvKf4/pIy3RrwCsRERERERERERHVT7am00RERERERPUbgi/um7JA/ti8RwJBTZqnJErLtCRpmhyv/sV7fI7x906ZLzuy8qu7yERERERERERERFQDMACDiIiIiIjI1O0IMl+s3ZstDRI90ig5Qdy2bvjwHp9jPKZ76udFaj4iIiIiIiIiIiKq3xiAQURERERE9I/F2/apbkcS3S5J9sTF3C8Yn+B2qekxHxEREREREREREdVvDMAgIiIiIiL6x9SVWyXbG5C0BI9pn+hSEAipz+0wHT6funIb9yEREREREREREVE9567uAhAREREREdUUS7cfEMc/3YyAPxSSvble8QZCoosuKYkeiXcXxrHHuZxq+qXb91djqYmIiIiIiIiIiKgmYAYMIiIiIiKif+QHguJ0OAovmBwO8QUPBl/oui6Z+f6iF1UOh5qPiIiIiIiIiIiI6jdmwKhuKcni8KSql7rpRq96b+5z2t7/dGK85a2jwHoj2OEpPLRaaoJlnMtvTZ2s/9O6L/w+yTS9yxFzPXa6qTWguGxlzPVap42znX6J6aaRunVcMGRdVnKidVm2fWfhdsUss3m8Hu+xba/POq19X5mOg8Mbe984bNtgX5f5eDtz82PvK02zvHU2SI86To+zbb/TGXXfOcT64MARsi5L7A8WTPOa94V677KtN9G6Xoe5nPZzPy059jaYll1kP9qmdYRs545pXod9e2zfM/s2iWl/FDnjGje0rsd23mnx1mU7TeeLbt/PxdDSkgrXE7TN67SVzP7bYdpmh/0889rOdyIionooKc4tmqku6nY6JTXBI5n5PlVFzfUHpGEwJB7T33pMj/mIiIiIiIiIiIiofmMGDCIiIiIion/0bNVQEH4RNAVINkj0qHhRfK7pIvvzC4MWAyFNfd6zVSPuQyIiIiIiIiIionqOARhERERERET/GHFoa0lLiJNsU7YqZMFI+SerFLohyfMHVLckgOkw/YhDM7gPiYiIiIiIiIiI6jkGYBAREREREf2jd0Zj6dqsgRQEQyrQwpCSEBfuggxZMA7k+9R4bzCkpsd8REREREREREREVL8xAIOIiIiIiMi4QHI45D/H9ZHOTdIks8Av+/K8qjsSl8MhCW6nCsLQNE2yvH7Zn+dT02F6zEdERERERERERET1GwMwiIiIiIiITFqmJ8mjpw6Qfm2bisftlF25BbIn1ytBTZeQrqsMGICuRzAdpiciIiIiIiIiIiJycxcQERERERFZIaji6TMGyeJt+2Tqym2yYNMu2Z9bIIniFl9QU4EZ8W6XyoTBAAwiIiIiIiIiIiICBmBUt+wc0V0HD4MjkGIZpTVIDb8OpcZbxjn0f5rd/cNZELC+z/UWTlvgs4zTE63LCjfhi7Rsb9A6rT21ssuaREV3O6NOq6UmWqeNc1nfOx1Rx7lyrdvg2Gd9L7l5hfO2amoZFUqxbq8rz29dr8f0NdDjrOtJsL4Xzfo2lJ5QOKsj2TLOnWNrCem37stQauG84MwvPIZaim1el3Vf6k7rfnckmwoWsp0bWfnWZcV7rPPGPJ7W4+AIhqzLiivcd3qS7byyy7ceMy2tcBv1eNt+D4RivtdN55ae4I49rct2nqUWTu8IWg+oI88b/dywn5fFfAct3wWMtx1/h9cf9bthP2fdWdZyOXzBqOXQE+KjnqOqHKZ5nabjp5abV2B5T0REVN+hW5G+rZuoYdXOffLHqg2S2qCRvD1/reR4/eIPafLxH2vlwZP7VXdRiYiIiIiIiIiIqAZgFyREREREREQllBDnkv7tmorb5ZRASJNF2/fJsh37uf+IiIiIiIiIiIiIARhERERERESlcXibJpLscYuu6+IPavLRwnXqNREREREREREREdVvzIBBRERERERUCvFuZMFoFs6CgQwYi7cxCwYREREREREREVF9xwAMIiIiIiKiUjqsdWNJiY8LZ8H4eOFaZsEgIiIiIiIiIiKq5xiAQUREREREVEoet0sGmLJgrNyVKX9t3cv9SEREREREREREVI8xAIOIiIiIiKgM+rZuLGkJHpX5whfS5KM/1jELBhERERERERERUT3mru4C1HsNG4jEN1a7QUtOsO4OTQu/dPqD1nEOh+Wt7rTG0uhJnsI3KdblOjPzrMuKs54GmmneUIJ1nKsgYJ1X16OXy1ZGLTHOWo58v3XWws0VEet6HD7rtHpasnW821U4zrZeV54/5r7SPKZ5ndZ5HfHW7XeELIUUpz8UdV847MdMs423vRd3Ybl0l23feWzlsO/3UOG8Dp/tGMV7Yh4H8zYX2VeJ1nl1+zlqKoceV7gfVTns54r9nDVNbz/P3PZ5A9Z96TCdsyHT8VPLtS8r13ae5fgK501PtM6bnGZ578ryWsth3saQ9RjYj5l9vH0btNTEqPvGWRCMefzF9B21n2eOQMhaLrd12YH4+ML12PeV7btBREREscW5nDKwfTOZtnKrBEOarN2TJQs271GZMYiIiIiIiIiIiKj+4dM2IiIiIiKiMuqd0UjSEj2C0EtfMCQf/7FONHuwLBEREREREREREdULDMAgIiIiIiIqI2SQGtS+ucQ5HRLQdNmwL1vmbtjF/UlERERERERERFQPMQCDiIiIiIioHHq1aigNkg5284UsGJ/8ySwYRERERERERERE9REDMIiIiIiIiMrB5XTKkR3+yYIR0mXT/lyZtW4n9ykREREREREREVE9wwAMIiIionpk0qRJMmjQIElOTpaGDRvKqFGjZOnSpdVdLKJar3uLhtIoOUEcDhF/MCSf/rlOQppe3cUiIiIiIiIiIiKiKsQADCIiIqJ64o033pAxY8ZIXl6ePPHEE3LvvffKokWLZPDgwbJkyZLqLh5RreZyOlQWDLfKgqHJlsw8+W3djuouFhEREREREREREVUhd1WujIrSEz2iJyao18H0g/1GG1y5/vBrLSHOOp/DuhyXN2h5r8W5Cqd1WSfWG6dY592Xa3nvzCt87QiErMv1uKzLclvfi6mRn329zqBmndZpjf/RPYXvdadtXluokJbksbx3JBfuOy3ONrHDtiy/dZuc3kDhek37Tc0ait1qMZhsOi62Y+K07Sunz3qMdLe1nFp84dfREbLtK9uyHbZtcPgK3zs067xafFzs9Zrea/FJMc+rIsfUND6YYl2PbVJx5VrL5cwvPL+dBYXHQLFtf6hRsvV9YuG+cvq1mOdZKNFaLofpuBQ9n637xmk7H8S0bIduPTeCDROt6wnYyuWznQ/mfevzWee1nbOOoO17mGxal+10t2+Dw7Z/HAmmZdvWw5A8orrtwIEDctttt0nr1q1l1qxZkpaWpj4/++yzpXv37nLzzTfLL7/8Ut3FJKrVurVoIHM37pJd2QXi+ycLxlEdW0ici3HvRERERERERERE9QEDMIiIiIjqgcmTJ0t2drYKwjCCL6Bt27Zy5plnyjvvvCNbtmyRNm3aVGs5iWozp8MhR3VoIV8v2SSBUEi2Z+XLjLU75PhDMqq7aERERFTNNF2Xxdv2ydSVW2Xxtv2SW+CVlMQE6Z3RSEYc2lp6ZzRWdQkiIiIiIqrdGIBBREREVA/MmzdP/YvuRuzwGQIwFixYwAAMonLq2jxdmm5MkB1Z+SoLxmd/rpOhnVsyCwYREVE9tj0rT57+ebGs3p0p2d6AOJBCVhfZ7w3IpgO5KmCza7MG8p/j+kjLdGt2UiIiIiIiql0YgEFERERURbZv3666AqkIoVBIXC5bV0ki0rRpU2nWrFmRz7du3ar+RRckdsZnxjREVM4sGB1byFeLN0ogGJJdOQXyy+ptckI3ZpchIiKqr8EX901ZIGv3Zkui2yXNUxIFvZMFgyFxu12qF9Zsr1/+2LxH7p0yXx49dQCDMIiIiIiIajEGYBARERFVUfDFoYe0kZxcrUKW5/F4xO/3F/l83Lhx8uCDDxb5PD8/X/0bHx9fZFxCQoJlGiIqn85N06R5aqJsy8xTWTA+/2u9DO/SSjzuokFTREREVLe7HUHmCwRfNEj0SLInTn2u64XXBG6XUxolJ0ieP6Cme+rnRfL0GYPYHQkRERERUS3FAAwiIiKiKoDMFwi++OKtFtKpw8Ebr2W1bkNAxly6U7766ivp3LlzkQwYkSQlHUxl7PP5iozzer2WaYioIrJgNJdJiw5mwdidUyDTVm2TkT3actcSERHVI4u37VPdjiDzhRF8EQ3GewMhNT3m69u6SZWVk4iIiIiIKg4DMIiIiIiqUIf2Ljm0a/mqYNo/LeYQfNGjR48SzWPuZqRbt24l7p6EiMqmU5M0aZWWJJsP5Io/pMkXf6+XY7tmSEIcs2AQERHVF1NXbpVsb0B1O2JAdqw9uQWS5HZKmsspbkfh9GkJHtmdWyBTV25jAAYRERERUS3FAIxq5ghq4giE1Gun7+C/hlCSxzKdmVPXrdMmWqPoNY+z8HVc4WtweW3ryWhgGx8sXE9BwDJORyeV5nkTrKeQq6BwXneOL+r2HHwfPfLfoVm3L9Aodotc875z+q3b522aaFu4db1x2YXbqLut22c/Jk7bcTDTnQ7rtAHrtKEU6/YHE637zp1XuO9C8bbjGWddNtJTmjnitajniv2Y6aZzQ01vLqftvPKnW8vsDFnHa6b9FUxyxdwf9mPq8Bdur5Zg3d5gqu1csZVZN92dcOfbj5F1vbrD+t6VX7i9Lvt3zvIOC3dG3V7nP9/b8KT7CqzrtX0n7cchmHYw3f9B5tc4hwv3DRi/EeFyppi6D7Du1iICadG/Z/E5Xut6c63viahuGTBggPzvf/+TOXPmyIgRIyzj8Bn079+/mkpHVPc4/smCsePvfPEHQ7I31ys/rdgio3q3r+6iERERURVZuv2AOGz3cXJ8AfEHNfEFQpLtD0m7himq3gBxLqeafun2/TxGRERERES1lPWJIBERERFVKk30ChlK6/TTT5fU1FR57bXXJDs7O/z55s2b5bPPPpNhw4ZJmzZtKnhrieq39o1TJaNBsnqoorJgLNog+bZASyIiIqq78gNB1TWZQdd1yfUFREedXtclMc4VDr4wYHrMR0REREREtVONDcB48MEH1QVIrGHbtm3h6YPBoDzxxBNyyCGHSHx8vLRq1UquvfZa2bdvX8Tl43OMx3SYHvM9+eSTajmRLF68WE499VRp2LChJCcny6BBg1S/60RERESloVXQf6WFOsxTTz2luhs56qij5MUXX5RnnnlGjjnmGFWveu6553ggiSopCwZaswZCmhzI98kPK7ZwPxMREdUTSXFuFWhhyPMHRdP0cALSZE/R5MSYHvMREREREVHtVGNr86NHj1b9mttt2rRJ7rvvPjn88MMlIyMj/Pmll14q77//vpxyyily++23y4YNG9SDhN9//13mzp2rgiYMOTk56mHDqlWr5LrrrpPevXvLzJkz5c4775QVK1bIW2+9ZVnnokWL5Oijj1aBGmPHjpUmTZqodZ1xxhlq2ksuuaSS9wYRERFR+V199dXSuHFjFYhxxx13iMfjkSFDhsijjz6q6kNEVPHaNkyRNg1TZMPebAkENflq0UY54dDWkmzrco6IiIjqnp6tGsqG/TkSDGmqG5Icr199jvgLl9Mh8W5rd64I2MS4nq0aVVOJiYiIiIiozgZg4CFApAcB999/v/r3qquuCn/2yy+/qICIUaNGyeTJk8OfH3HEEXLmmWeq1p0PPPBA+HM8dFi+fLn6/LbbblOfXXHFFZKenq5agyKYAwEahhtvvFHy8vJk+vTp0q9fP/XZ5ZdfLgMHDpRbb71VBYukpaVV0p4gIiKiukTTRUKmVnBlXUZZoW6EgYiqNgvGlgO54guGJLPAJ98t2yxnHd6Jh4BqNbTQXrxtn0xduVUWb9svuQVeSUlMkN4ZjWTEoa2ld0ZjS9p9IqL6CL+HM9bukGyvX1ITPFIQCKnuR9AVSYIt+AIwXVpCnIw4tLDRGVFtYu9SB+/j4uIkJSVFNWrs2LGjHHnkkXLxxRdLu3btSrRM3Md/++23VQNKNLo8cOCAakyAxplopIkGmWPGjJGEhIQKm9++HbHg+1xS6PpzxowZls+wfxITE1XWSuwTlOnf//63evZQ09jLX5ptj+Snn35SXaLOmTNHtm/frhrOoiFthw4dZPDgweq5y7HHHhs+HjiOeHZjYOPY2NBw+J133gm/x/nfvn37EmeoHz9+fMRxbrdbna+9evVS353LLrss6vePSmfjxo3q/DfgtxLnPRHVPjW2C5JIQqGQ+qOKP8LnnXde+PN3331X/WsEUxjw448/KMZ48/RJSUmqCxIzZLcwL8/4wfvtt99k6NCh4eALo2J00003SWZmpnz99dcVvKVERERUV6FNW0UMRFR7IANGu0Yp4nI4xB/UZPKSTZLjDVR3sYjKbHtWntz+5Vy575sFMmXpZtl8IEf2FwTUv3iPzzF+R1Y+9zIR1WsIRuvarIEUBEOyL6/AEkwd77bels3zB8QbDKnpMR9RXYAH9H6/X/bv3y+rV6+WH374QcaNGyedOnVSDSwLCg5+LyLJzc2Viy66SHr27KkaVM6bN092794tgUBANZbE8j7++GO54IIL5J577qnw+asKypOdna0yfyNIBFm90f05Gojis7po7dq1KsDkhBNOkNdff12WLVumAmPQPXxWVpb8/fffMnHiRDn++ONlypQp1V1cssFx2rNnj2oYff3116ugIXR3S0REtSADRiTff/+9bNu2TUXUpaamhj9H5cnpdKqKiR0iaj/66CNVyWvUqJHs2rVLVVwQQYnIUjMEa7Rs2VLmz59vWTZgejvjM0yPihoREREREVEkR3dqIZv2H8yCgdat3yzdKOf268KdRbUy+OK+KQtk7d5sSXS7pHlKoricuBEbErfbJSHtYAvuPzbvkXunzJdHTx0gLdOTqrvYRETVApmA/nNcH7lnynyVNQixFw5dJM7tDGcJQrcj+N1E8EXnJmlqemYQorripJNOUvfgcW/+r7/+Ug/XjYaWr732mvz555/y66+/qgwZZsiEgO4y0TW4Ge7dI2u2y+VSDSfRnTiCPDRNq9D5I20HGnRWNDT4RNYLlBeZOswPsdEoFA+2EZTRo0cPqSuWLFmijo1xLhgOPfRQ1SW9z+dTx8XYF8UdG6oaOE+NBsqbN2+WBQsWhMfheJ111lkqkwmVDxqfo2G5oX///tylRLVUrQrAQKXM3v0I4I8xUpjFx8cXmad169bhaRCAYfzhNj6PND0iMM3Ljja9edmxILIWEYFm5nUQERFR/YHsFUg8XN5lEFHt0io9WTo2SZPVuzNVFoxvlm6WkT3aSXqip7qLRlSqbkee/nmxCr5okOiRZE+c+lzXC2+Mu11OaZScoFpyY7qnfl4kT58xiA8TiajeQhDaBf07y7jdWVIQCKruCF2aLtm+oOQFNZVaH92O9GzVSAVfMGiN6hJkMTC6PECmB2Q7QBZrr9erPlu4cKFcffXV8sEHH1jmu/LKKy3BEwji+N///icXXnihpXuQLVu2qIwRCKioyPljbUdFQvYAdBNhmDZtmur6HA+4AYEr6HYdGSLqQhcPOO7YHnPwBbpb+PDDD4s0rv3jjz/k4YcfLlV3MFS53c+Yu8JAFnl0j2GYO3euGiI1kqaSa9q0qXz++efcZUR1QK3pgmTHjh3y7bffqn6l7P2f5efnRwy+AKNigmnM/8aa3pimuOnty45VQUOqM/Nw+umnHxwZCIr4A2rQnQ7L4PQFC4egZhkCaR7LoI6kafDsyQsPCdtzLIPTF7IMmsdpHeJd4SHYIMEyhBLdlsGdH7AMjpAWHnxNkyyDt3m8ZfCneyxDMCUuPGhxLstgL7ND1y2D7nGGh2CqxzI4Q7p18GuWQY9zhgdXfsAy2NejuZ2WwYEL5X+GkMdpGfwN4y1DKM5pGVy+kGXQXY7wEEp0WgZnULcMWpzTMnibxoeHUHKcZRCnwzI4ApplUM/w/hns24tWGebBfhxisZdR0CegadA97vCgxVuHYKLLMoQSnJYhLjcYHuzfDfsxsp/f5n1j/x4F0uIsg69xgmUIJrvDQ0GLJMvgb5ZsGUJJbstQZP8kuMKDv4HHMmjYJ6Yh2DDRMvgbesKDeTkY7Bwh3TI4A4VDKMFtGfwZDS0DEVUOdkFCVH8d1bG5uJ1OCWpo6RqQr5dsrO4iEZUKWm8jiAiZL4zgCwlfTliDAzE+we1S02M+IqL6bPG2/dIqPUkaJMZLanycNEtNkBSPS1o3SJZTe7aTR07pr4LVGHxBdRm69EaX4O+9957lc2SvXrx4cfg9up/45JNPLNPgYS+6E7E/jG/Tpo0888wz6kF9Rc1fndDlxvTp0y3Zv9evXx9umGrAdhgDHozbIVjEGG8PHEHD0HvvvVdGjhwpXbp0UQ1bcWywzu7du6vgFWQmqQwIgkHmEQPW+fPPP0d8aI9sC5MnT5YTTzwx5jKxfxAI0KJFC/UMp2vXrvLYY4+pLCt26N4e2dWxbDSuRbYBzIN5jzvuOJkwYUI4OMgMWVrM+/zBBx9UmdqvueYadQ55PB6VIeI///lPxG51cIzM8wOCjo466iiV/QXD8OHDZcaMGVG3E1nd77jjDjnssMMkPT1drTMjI0NlnkBXIFUN3ydss5k5K4Z9m5HJ5KWXXlJZXbDf7d/FzMxMeeKJJ+Too4+Wxo0bq3MSDaqxjx5//HE1PtazQxwTZKw35kUgA44z9hkCmewQLILgJ3wHUB4EaeHcue6662TNmjVRG1rffffdahtwDNxutyrjIYccIqNHj1blxHlhPz9vvPFG9UwQ57tRNmS1+fe//y3PPvusZdvw/TDvN3OAFuC9eTymR88BI0aMkAYNGqhMPQMGDJAvv/wy6v7Cd+7YY49V5UlLS1MZaTB9ceu2j4/020NEtTADBv444o8mKgB2+FFBaqpIjD+YRoow499Y05vTicWa3r7saPCjjT+E9opOOAiDiIiI6lXrYbR6K+8yiKj2aZGWJJ2bpsnKXZkq3fh3yzbLKT3bScOkyMHhRDXN1JVbVfAQuh0xoFudndn5EtI0aZ6aJMnxhe080hI8sju3QKau3CZ9WzepplITEVWv7AK/LNyyV0KaLm6nQwZ1aSn9WjcSLT9Xju7ZWZqnW7teIKrrzjzzTDniiCNU9gtAFyAImEDXIPDpp59apsfDTswTi7nxZHnnr24dO3ZUGcARGGL4+OOP1UPcioAHzwhQsMvNzVVdSWDAs5iXX3454rOY8rAfGywfGTDKemwQGIH9grIb8PAcASbIboJtMHv00Udl3bp1RZaDbusxIJABWVoQCIGH2dGgS/oXXnhBDhw4EP4MWUuefvppla3ku+++i7lN559/vsr6Yd8WPERHGRCEYIZpsa/sDYG3b9+usiVgwH5AmapSs2bNVGCIwXwc7JB9xr7N5v15xhlnqO0xw/6dPXu2GhAcgyABBBeYYdsRVINufMz27t2rBvzOnHfeeSpQwvi9QRYeZL6xw7mDAef/G2+8oeYzB1/gt8QeYIEyYli9erUqH7rRMX5v8F068sgji3S3Y5QN3Q7htw8BEEb3LqWFc92+XxEIg4AQBLchyMMM5zd+X7AfDL///rsarrjiijKVgYhqcQAGfgzwg4coNPxQ2yFaET9wCJKw/0G2dyFSXLch+Nzc3Uis6YvrzsT8hwgDERERERHVb0d1bCFr92Srh9a5vqBMXrxRLhl0SHUXi6hElm4/II5/uhkxAgJ35RSoh4p4faDAJ8nxhZkx4lxONf3S7UVbnRER1Re/rdupfif9IU0FYh/RpomIqesmovrohBNOCAdgwJw5cyK+huIyINiVd/5oDSwjNcI85ZRTirQSr6j9Yw7AwANqNE4trquU0gZ6tGzZUj2YxrLxIB0PhPEsBu/xQP/kk0+WVq1aVcj6sExsR0Uem3feeUdlIUDmAwQnIPuJ4ZVXXpG77rqrSJYGZDs49NBDpWHDhuo1Ho7/9ddf4YfkyMbywAMPxAxmQMYBZABAIBGeRyFAwDzut99+Uw/Vo8EDc2QeQTYLdJWDh/tGNz3jxo1TGQoMCAZBtgkjowe2FxlDkLkAD9r37NmjPkeAArZ17NixUhWwv+2ZIpBJJNY2I6M8thmZF4xsGTt37lTnGQISDMjsgYwRCGYxnsEhOAPTLV26VJo3b64+w34+99xzJRgMhudFZgoEc2EdOB/sQR0IPjIHX2B6ZNzH/kUQAp4xouE1sqp06tQpnI0fgQvm4AuMQ8YYBJ2gjMh0Yc+6guwW5uALZL3AfAjYwDzIKGEOhCgL7FecC/3791fHw+i+yAjOMAdgrFq1SnV7ZF5n27Zt1fcBv8fYRiKqZwEY+IODHzAEX0SKPETU28qVK2XevHlyzDHHFKlw4UfNiHDDjzN+VPDji3RQCOowoJKBdEVIv2VetrEcO+Mze9QdERERUTS41Vre2628XUtUezVLTZRDmqXLsp0HVBaM75dvkVN7tZPGybW/T2eq+/IDQXGG0wXrsje3QIIhTQVf4D4eAovwunAa9ILoUPMREdVHeMjx65rtKksQuiDLaJAsjZIT5EBu7O6Mieo6dNtghuwDkV4D7uWXRnnnjwQP1SMprmFmRe0fPGBGNwrouqAiujnBQ2kEX9ghYwSCTQAPotEFCLqNqQj79u0r8oC6vMcGwQjTpk2ToUOHqvfIhIDsBcbvL7pzMQfIIENBt27d1HxmeIjep08f9QzKyNRRXDYJdKWDTBYwfvx41QWG+XlWrAAMZDuYOnWqetaF4ItevXqFgzAQVOD3+1UXI4AuL4z9hqARBHvggbkRBIHnYUYwE7rSwfEqLmN7eeEh/5133mnpOgPBQejGJRpkOvnhhx9UNx+AbQQEGpmDL0aNGqX2PwJbMA0yy3/99ddqHKbD9E8++aR6jwAbc/AFsj68+eabKqjCOAd+/PFHFewCCHwwZ3/Bcz2cP0aXP8hajywXyKaB5d5///3y008/qXHmrnPQ5QiCQ8wBUVg2pjWOjX0efO9wzM0QfILflliBK8XBfp05c6b6LcL5gG1C2QDnM8pgdEP0/PPPh/c7nHbaafLZZ5+pblHw/cS5hCAsIqoYhblBazAj8ipayisjK4Y5KhQmTZqkfmDsWTPwHj9G9hRUxvzm6fEDhn6mkALKHJWLH2D8EcaP+amnnlrubSQiIqL6ISR6hQxEVHsN7thC4pxO9SAm3x+USYs2VHeRiEokKc4d7gYrxxdQWVx0/IcADHWT82AQhhmmx3xERPURsl5tzcxTQZfBkC6HsTsmIqU0rb7L20K8vPNXh8osMx72oiU8sirgYXFKSoo4nU6V0cEIvjCg0WtJoduFSMNLL71UaduJ5RvBF0ZGEjM0trUHfKCbEDxoRkNdPOTHduMBvBF8YQTxmLsXsUMGCiP4AuzPh+zrtXvkkUfCDY2ROd3IsmBkwcDDcEB2C3QZY0Bj4vvuuy+8b3EMzV1vINvCrFmzpDIg2wj2FQZk2kC3OGbIrBAroAbbbARfgBFg8u2331qm+7//+79wlntMY+8ux5ge+8bcaBpZIMzBF4CyIsuKESiFwBhzNy4IMrr00kvD+xMBHebgHDwTNKY3b9uGDRvUccDzxyVLlqjlIDjmnHPOUZk7DOZ5kPED+2DKlCnqe4XjjO8i1l+eQC4EwhjzI/Dm2GOPjXouItjE3iUPgi+gcePGavtjQSCHuu77Z8D+IaLoavxdEES1ITIRlYFoUYOIHkOqIfRphD92iNzCjyBS/CANkD3t0h133KH6hsK/CNBAdCNSOSFqEcEX5j/agEAL/FFG6q9bb71VRcxh2j///FN1jWL+USciIiIiIoqlSUqCdGvRUJZs3yeBUEimrtgqp/Vqr7JjENVkPVs1lA37c6QgEJC9uV4VdKHpyIVxEP4tCAQl8Z+ACzxwxGc9Wx3MSElEVN9MX7NdPaRA9yNxLof0bNmwuotEVCOY0+SD0aWA8XrFihVRpy1OeeePBM8ajFbkVcFeZjwUNjJ8lxcecN9zzz0lmjY7O7vEy/3iiy8ifo4AD+MBLzIGmLNgYDvNGQNKC5kkzOzPafBg3ICsH2hoa85KUNy246F6eddbnvntXVRgG6LtZ0NJt6+i4JiiuxoEtsRif+YWqbw4z+3nA97jcyPThTG9fd+g25HintPhe2yG7l8wRIMgCXQ70qVLF9U4HA26cQyQReLxxx+3lBtdgKDbkiuuuCKcGQPPEpFhAucSgmOQUcOA7ljQdQ6Wa+4mpLRKcy5u2bLFUmZkgzFDJhYiqkcZMN599131gxYt+4U5Ag/RcEY/Roh2QzAFAiuMP/LmaDikcrr88svVDyAiOxFJiMoH5rND2iFEDiKy8amnnlI/nPjxxR87pLUiIiIiKik8qAqVc8AyiKh2O7JDM3G7kAVDV90zMAsG1QYjDm0tqfFxsiMrX2W7MFo/udFqEhPouhT4C2+qZ3v9kpYQJyMOzajOYhMRVQsEpM3ZsEtlvMJwaIuG6m8/EYnqFsDsyCOPDL/GPXgzdFtQGuWdvybuH3QrYO7uwMzcBYMB2QEiwcNj80NgozsFNGodM2ZMke7dKzITB8qPh9QVeWwQ1GFfRzTIPmB+2I9sAcOHD1fbjcHopqIk216a9ZZn/rLs/7y8PKkMyHph7Ctkerj66qvlxRdfDDeELm4fROrypjzKsm/Ksz8R2IVgjXHjxqmgByNLh/EdRDaOa665xhLc1KNHD1m8eLHcfvvtKrjBnF3D6/XKL7/8ohqW2zP1l0Z5z0UzZMIhonqUAeO2225TQ3GQKgf9YWEoCfSX9sorr6ihJJAl45tvvpGKpqUmipaUrF6HEmyHo7Db3MImRcZbh+290/pBKLWwD+lgou1H1zatfVn+tLjC8sVZR3oyrRU6Lc66bM1T+CPtxBMi82oDJf8DZ14OuELW3u51U5/C4M4pjOQLphb+8QOHrRya27b9pkVridZj4AhY1xuyjTcfF6dtWt1lOyYprpjb4PKZCyIxt8GdZY2idfoLj1koyVpGb+M467RBPeoxtS/XbXvCF2hg3bfmJ4CuAtv22/5e+xta+zV36NH3lf28K3LumN76U63bp3ls+9VrLZcjVDjeYds++3rt3yt3QeFrT1bAth7rdyOQejCNWli89biETOe4eV9E2h/2c8VczmCS9byKL7CWw+W1poA2nx+BeOu+i8uxbhMRVQ6t6M98mZZBRLUb+n/v0aKhLNq2X2UJ+HnVNjm9d3tpkVa5/fUSlUfvjMaSGOeSQEgXxz+VWGS7iHM5JcfrV9V0bzCkbm4isAivkf0C8xER1TfzNu4WbyCksl+ENF36tbE+3COqr5CZ+q+//rJ0E3D22WeH3+O1uXU5psU86CIgGrTyNh6Ilnf+6oauMIwu2Q32FvJ4FoIGomB0V2FA1m5zNwtmaIRqzkCBhqnmLkLQrcTMmTPLVO6SPNzGg3tzlxrYTmRPQDfwlX1sfv/99/BrLA8Nec1dPyDTArKx1yQIerBngp86dWq1lGXYsGHy9ttvV/jDfWyj0dUNAhnwGlntDThO5iAjY5/YM9Ig0AFZJmJlwbDPg6Cce++9t8TbgCCdBx98UA2apqnuPbBeZNpfunSpmgZBKfj9we+aUV406saA7di6dav6jt50000qu4aRgf/aa6+VyoYuUVavXq1eoyxr1661dAuDbSGiisOQJiIiIiIiompwZMfmKh05Hsqgleznf1lTohLVNIu34Qa/Qzxup4T+ucmeEu8Wj6lFN25G7s4tkMwCv3Rukib/Oa6POG0BxURE9cH01dslpGsq0LJJcoK0TGeQJdVvCBj43//+p7JWm5133nmq8aPhsMMOUw/qzS666CLVJbj9IT9S6qPxpjmrQ3nnr04///yzysqQk5MT/qxTp05FsoObswnggSqyfQMCCJAdPBp7tozk5IMNQ42sGcgwXpmQIcD8EBzbiaACc1CGYcGCBTJq1KgKy2Bi3nYEA6ALCAMa6eJBf02DrAvmrCHImICM8XaZmZnq/D7//POltjn55JMt7++77z6VER/wL95Hmr5Zs2aWbDfo5gPZ6hGEYTZt2rRw1xvHHXec5bg/99xzlmAwAzKloEuVhx56KPzZ9OnT5YMPPlD72jiHMjIy5KSTTrL8fiH4affu3er1l19+qQYjIAoZMHD+n3HGGdKxY0fL+qoCvmtmDzzwQDggC4Fc6CEgFpQTgSXGgKAcIqrFGTCIiIiI6hJNHBKypLkq2zKIqPZrkBivsgP8tWWfejjz65rtckaf9pLRoPBGKFFNkZnvk5d/Wy4up0PSEz2i5fskKc4t2d6A6KKrgAw800CsBf7t17apCr7gA0ciqo+2ZebJ6t1Z6u87Ai37tm4cbg1LVJ8gw0JiYqIcOHBAtfq2PxzFw+VIGapfe+011RIeKf+hoKBABVHceeed6mEn0uyj64MVK1aooIqbb765QuePtB3osiISPKi1t6wvKWSfQNbt3NxcWb58efhBsbnF/ddff215aAwI0kCX7Ebw69ChQ6VNmzaqi5FIXZIY0HUCfouMQBS0ykfwBrpsRxCEOfCjMmA7sD1DhgwJnwvI+IEuaLp16yadO3dWGS+wL5ApACqqC3h044LjbZwPWN/AgQNl8+bNsmTJEst+qUkQFHPCCSeo44zh4osvVoEB6DoG5d20aZMKHsGDdHvGjNpg7Nix8tZbb8n+/fvVewQsIOgI3XfYvxONGjVS0xuQaQJBFUYQwaRJk1QQE77jqampKisF9g+CLPD9QHcdyFZhBFYgYOmII45QQVvIhoJACQQ04ZwA7GsDfktuvfVWlX0G2VIwPV7j/DWyXxhlNLqzmTFjhjz//PPqvEdWDwROIXAD27Vu3brwPOYsFJUJWTeQdcYIcPnkk09k/vz50qVLF1m4cGGRbDpEVD4MwCAiIiKqQuj9yNYDUpmWQUR1w6D2zWXZjgOS70d3DUH57K91csvw3tVdLCILTddl4m/LJcvrV9laNE2XM/t2kKYpifL3tn2yaV+O7MopUA8aPW6X9MloLE+fMYiZL4io3kJQJYLT8LuIuAsEYBDVR99//33EzxEAccUVV6gW6PbgAsDDUwQGIPABrc6NB+NI+Y+huO4Nyjt/SbcD7C30S+OPP/5QQyQIqkBWAzw4trvnnnvkiy++UIEbgO0zHhqfdtppKnsEgjHs0OoeGTLQTYLByD6BbjnQIn78+PFSmXr16qXKh2wN+NeA4AgjQKI0x6akcJwmT54czmCAh+/ffvutej1y5EiVQcHcTUlNgawFCFBA9hAEjgAe3psf4BuQYaG2QVACgpBGjx4tO3fuVJ8h+MYIwDG0aNFCBVjgX/N3BN9v/JYY3wUE9sTqRgfdhyDYw/gO4LuD4DAMJdmfyOSDgB0Mkc5VBGTh983M6/VGXL7xvUMgVFVA0A6Cvq666qrwbyIC0TAAfhvMXRJ5PLYu1omoVGrfLzIRERFRLcYMGERkhkwCvVs1kj8271UPaX5bt1PG9O0obRqmcEdRjfHt0s2yZPt+8QVDaujUNE36t2umWgp2aJImeigkv6/aLLO3ZamW3vvyvNVdZCKiahPUNJm5docEQ7oaOjVJk4Q43oKl+gl1BTzERFcXaBWOAIDBgwfLJZdcUmxrfQRRIAABWSuQ7QGtyfGgEA/Q8WAQ6f/Rev2UU06RMWPGVPj8VQUPa5ElBC3nsU/QGh/dsiA7QzRoMY8AEwQV4F+0aEerfDxYvfrqqy3dG9i98MILqsU7uoNZu3atyn6BY4LACzy8ruwADMD60fL+xx9/lM8++0zmzJmjAkaQgQPnCsqPrBh4KI8MBxUB2TUQbHLvvfeqrjyQ7aBDhw6qSxxkRbB3z1CTIHsLgg1wzNClBo4b9hXOG2Ri6Nu3r9pP1XkelweO9bJly1Q2nClTpqjsNQiIwXcY5zW+o9dee636jtihu6Gjjz5azfvTTz+pDBbYN+np6SozDbLFtG3b1vKbNGHCBLngggtUppxZs2apLBsIksB3AeceMsWgaxEMBpyLgOmR8QIBPMjsgwAKHANsA8po/t7iu4gAE8yDbcI82C4cN3zXjznmGLnxxhtVNpaqgmAVnPePPvpoOADq8MMPV98BlMscgGHu6oiISs+h18S8SvUA/qD07NlTjux5vaQkNVOfBVJtEWXmzIS2o6TFWdMWuvya5b3T9D6YaI24E6d1Xt2WAVHzOKOux5NpTWHmDGhR53XYmucGk2zlsM4qzlDh9A7Ta3AVWNereazLcuf4CteTGm8Zp7us26C5re+dgcJ1OUPWQjls2xdKtF0wm4qp24Jx7esNJVon0G2pJ10+LerxdheErO+zfNZlJ8cVvk6yltGfZt1XzqAe9Zjal6vHWcscaBAftQm2w3Y87fvDzqFH31eBZFfUYwRxuYVlDqRYt1fz2ParV4u6n+3nqD/Nuizd9l1xFxTO686znpMur/W9/fts/65Yvg+2c8GdG7CWw23dmf4G7qj7Jn6f9RhqtnnN54dm2+9xOdb1Tv30bct7orpi2Sqf9B62RV0wIaVhVf/tnzy1qXQ+pPB3uyzWrgrIaSP2VPk2EFUH47tT3ef7qp375I9VG6Rp06biiSvfd9gux+uX12evVFkw4uNcMrxLKxl7XGE/sjUNWv0gPSlSuCLtan1VX/bDur3Z8sA3C8Qf0iTXF5B4t0uuPqqbJHoK65UIwNiwY7d8sXKX+IKapMTHyQtnHiVtG9W/QKL6cl6UBPcF90N9PSfmb9otz/6yRGUMwu/meUd0lo5N0yzTHMjNFy0/V47u2Vmap6fU6zoWERERVY1t27ZJ8+bNi2T3QBDXqaeeqoJYDMgkgu6CiKhsGH5NREREVIVC4lBDeZdBRHVHaoJH+rRuLPM37pFAUJNZ63fJmL450r5xanUXjeo5PDyc8OtSCWq6eo1/z+nT3hJ8YWiREi8uh0P9hULr7xW7DtTLAAwiol9Xb1ddN/mDIUlNiJP2Tfj3nIiIiKrfs88+K2+++WY4M0hKSorqlgndLJm7LUJGGAZfEJUPAzCqGzIuBLWIGQNCCYUt5D1Z1pbp4rBO7G1sazmgR8/44PLrUVv128uh2ZJWBFJtHzis7x2mJAD27AL2jA9agi3rgelsjMuzZfTwOaLuG7Usd0LETBpquSnWaUPx1n1nLqc9w4fblllEs2WECMUXlsvls67X8c9xDS8r3/reb9uX5vcuW1YDt9eaAUNsmQuc/sLxwWTr19phmzUuOxS1nL7mSZZx9gwoQdsxiz8QjJiV4eB6bRlQimQAKXzttu27/CbWad22DMbmjC/288xn268uW5ldfmfUTCOeLFumFXsGkJTC96EE63cuYbcte4otuVDAll0jLtu0Lmf07CCK/VzKDUXMOgPeptZ+M0Oe6N9/cyaRiOslokrrgkSzp58qwzKIqG4Z2K6ZLNq2X/J8AfGHQvLJn+vkzhF9q7tYVM+9OWeV7MrJF28gqDJbHNm+mbRvFPlBYpzLKc1TE2VzZp7qhgRdlpzQrWif5UREdRm6YPp72z7VrRiC1vq3aiRO2/0wIiIiouqCrlMmTZoUdfywYcNU10BEVD4MwCAiIiIiIqpmyfFxcljrxjJvw26VBWPext2q6wf0G09UHX5bu0N+X7dT/EFNBV+0SEuUYV1bxZwno0GybM3KF03TZcXOTEGPp+hnmYiovpi5dof67UMABv49ok2T6i4SERERkXLOOeeIz+eT2bNnq+5I0DVcfHy8tGzZUvr16yf//ve/ZdSoUbyGI6oADMAgIiIiqkLIXlHeLkSYAYOobhqALBhb96n+4n3BkHyycJ3cc8Jh1V0sqod2ZefLm3NXSUjTpCAQEpfTIWf27VhsK+7W6UmywOGQoK7J/jyv7Mn1SrPUxCorNxFRdUK3IzPW7FCZLxCAgW6Y0hLjeVCIiIioRujfv78aiKjy2RLfExEREVFlQvBFSJzlHNiamKguSvK45fC2TcTtckowpMkfm/fI6t2Z1V0sqmfw0PCFGUulwB9UwRfoEmdkjzaSnugpdt6M9CQxYjSCmiYrd/H8JaL6Y+XOTNmVU6B+RxHAdjizXxARERER1UsMwCAiIiIiIqoh+rdtKolxLtWKFlkwPl64rrqLRPXMp3+uk/V7c9T5h6FXq0bSo2WjEs2bEOeWJskJKmUtWoAv2b6/0stLRFRTTF+zPdz9SHycSw5t3qC6i0RERERERNWAARhEREREVUjXHaKVc8AyiKhuwgPsfm2bqiwYeIDz99a9smLngeouFtUTi7ftk2+WbpZAKCTeYEhlvTi5R9tSLSOjQbLqsgRBRMt3MACDiOqHPF9A5m3cJQFNUxmAurdoKC4nb7sSEREREdVHvBIgIiIiqvIuSMo/EFHddUTbpqo7ErSi9QU1lQUDr4kqU1aBXyb+tlwFTqDrEfw7pm8HFQxUGq0bJIvT4RBN02V7Vr5aLhFRXTd7wy4JhA5mvwhpugqmJCIiIiKi+sld3QWo77R4l2gJBw+DM2S9qYobVoZgsvVQOUzjwN4Q1qkVvnZ7TW8i8Ke5rMs2lcMZtE2barv5ZrsPnLSncIZQvHVabwPreuJzQpb3bq9psU7rBgXS46zvk6zL1l2Fy44/YC2002/bVy7re2eg8L1mL3NKvOV9yGMdr5k2SXdal+vOt74PpFq3X3NZtzFxb6BwWcU8VytokWQtV3zhDO4C6/F22Y6/P916LrkLCrdJi7Ou2J9i28/2w+92Rj0nnUHb/rCVw+krHK/b9kV8lh5zvfZz1iwu37b9puMLiTtNJ5pNMNl6njkD1mW58wtfO2xfq1Cidb8GE23H22PdxoL2CeHXnjzrwhJ3+awLt+0fMX8/inkWE0y0zWt66zlgXa/u5gNdIiKimiDe7VJdkcxYu0M9yFm8fZ8s3XFAdQVBVBkQbPHyb8sls8AnBYGg+IMhOe6QDGmRZr3uKGkAhsNxsJoa0nVZuStTBrZvVinlJiKqKaav3i4hTVN/t5unJkqz1MTqLhIREREREVUTZsAgIiIiqkKa7pRQOQcsg4jqtsPbNJFkT5zKfOEPavLRH2uZBYMqzQ/Lt8iibfvUueYLhqRD49QyB02kJngkPcGjsmAEQxq7ISGiOm/jvhzZsC9HdT+C7Bd9Wzeu7iIREREREVE14t17IiIioiqkiUM0cZZzYMYaorrO43bJgPZNVfcPaE27YtcB9YCcqDIeHH74x1oJapp4A0GVgeX0Pu3FgTQWZZRhdEOii8reQkRUl/26ZrvooksgqKnfvt4ZDMAgIiIiIqrPGIBBREREVIUQPBEq58AADKL6AS1oU+MPZsHwBTX5eOE6ZsGgCoXuRp7/dYnKVIHXAU2X03u3lySPtWu+MgVgOBGAocvG/Tlq2UREdRGCJH9fv1P9jiKQrWuzdBXIRkRERERE9RcDMIiIiIiIiGogjwtZMJqpLBh4sLNqV6Ys3LK3uotFdcg781bLzux88QZDqvuRge2aSccmaeVebmuVAQPdbunq4eSa3VkVUl4ioppmwabdkucLqt+6oKZLv7ZNqrtIRERERERUzRiAQURERFSFQrqzQgYiqh/6ZjSW9ASPJQsGHmoTldfs9Ttlxpod4g+h65GQNEtNlGMPaVUhO7ZRUrwkxrlVKn48kFy2k92QEFHdNH319nCwWYNEj7RpmFLdRSIiIiIiomrGu/dEREREVQjdh1TEQET1A7JfDGzfTOKQBUPTZN2eLNXalqg8ducUyOuzV0pIOxh8gWwVY/p2UAETFcHhcEhGOrJgOETTdFmyfT8PGBHVyd/SpTsOhLNf9MlorH7/iIiIiIiofnNXdwHqOy3eLaHEg4chkGbtI9Jh6iY3FG+9gLO/dwatreCcgcL3jpB1XDDRGnfj8muW97rpYtGfap22oKl1vQ7rrOLQC08pzW2d1p9q2waPdXvTtgRM46zr9afG7j/T3BDY29h6Wrt8thaCtmthLa7wg1Ccbd+Y9uPBFVnfa+7C6YOJ1kmD/xzX8PsE64pdfvuyCsd7svzWeZPiYh5/8zb4bPvVbdt++/ngNB1/Lc4V87zypVn3T06bwm3Ubfs1Pts6r328y61HPVfsx8yh2c7hBGfUfWE/Dk7rrhTNnRh9vf7YZQ4kF67XXWA9+R2aM+a+0mzdaMflRf+O5reMt87rshbEkx0Kv/bbfjfsPDnWcrq8he99TTyWcU7b9hMRUd0wadIkefLJJ2XJkiXi8XhkyJAh8thjj0nPnj1LNH9+fr489NBD8vHHH8uOHTukZcuWcu6558r9998vSUlJRaafMmWKPPfcc7Js2TLJzs6WjIwMGTFihNxxxx3Svn37StjCuq9XRiOZv2m37M3ziS8YUlkw+rdrVmEPy6l+QSDPhBlLJT8QlIIAuh4Jyam92knDJGsdtLxaN0yW1bsz1UPJtXuy1ANKBBIREdUVM9buwJ0D8YdCgqvpw1o3ru4iERERERFRDcC7H0RERERVCNkrQuIs18AMGFRSb7zxhowZM0by8vLkiSeekHvvvVcWLVokgwcPVgEZxQmFQjJy5Eg17zHHHCMvvfSSnHrqqfLUU0+pfzXNGuj3/PPPy6hRoyQzM1MFXOD9v/71L3nzzTelf//+snPnTh68MnA7nTKoQ3OJczokoOmyYV+OzNmwi/uSyuSLvzbI2j3Z4vsn+KJ7y4bSO6PiHxq2bvBPBgx0nxMIyYZ92RW+DiKi6oLftl9Xb1dBZsGQLh0apUhKgrWRAxERERER1U/MgEFERERUhTTdKSFz6qYyLoOoOAcOHJDbbrtNWrduLbNmzZK0tDT1+dlnny3du3eXm2++WX755ZeYy3jnnXdkxowZcuONN8oLL7wQ/hyZLG6//XZ5//335aKLLgp/jsAMZLzA+hISEsKfd+rUScaOHStffPGFXH/99Tx4ZdCzZSOZv3G37M71qofmyIIxqH1zcaHvCKISWrZjv0xevFFlo/AGQ5KSECcn92xbKfuvWWqiynjh+yc1//KdmdK1WQMeKyKqExZv2yf7833q9xTdOR3etml1F4mIiIiIiGoI3r0nIiIiIqqDJk+erLoAueKKK8LBF9C2bVs588wzZfr06bJly5aYy3j33XfVvwieMLvuuuskMTExPN6QlZUljRo1sgRfAIIyIFKXJVQyCLQ40siCEdJky4Fc+X0dUp8TlUy21y8vzVwmIV2XgkBQQpouZ/bpIB5X7C7tygrZL1qmJwlihDRNlyXb9vNQEVGdMX3NdpUFwx/SJNHjlq7N0qu7SEREREREVEMwAIOIiIioCmmqC5HyD0TFmTdvnvoX3Y3YGZ8tWLAg6vy6rqvxrVq1knbt2lnGIfiib9++ReY/4YQTVNcmCNhYvny5bN26VaZMmSJ33XWX9O7dW8455xweuHJAVxGNkxPE4XCoLBif/rlegrZuYIiifZ9f+X2Faq2N4AucP8O6tJSWDZIrdYe1bpCiAjEQ9LFqd6Z6WElEVNtlF/hl4ea9EkT2i5CmslTht46IiIiIiAjYBQkRERFRFQrpGBzlXgZRcRD8AOiCxM74zJgmkv3790t+fr707Nkz4ngsY86cOSrLhpFh45VXXhFN0+T555+X//73v+FpR48erbozKS4Dxu7du2XPnj2Wz9auXav+DQQCaqguoVBQRNdE10Kih6onCAq/HIPaNZVvl29RWTC2ZubK9JVb1YP0qhQMBiUUCql/67PatB+mrtwmCzfvFl9QE18gJO0aJsugtk1ED4UqZPnqe6Ed/H6YZaQlqAwYQV2XHK9fNuzJlLYNU6Quq03nRWXjvuB+qKvnxIw12yQYCok/FFKBZYdnNCz97yl+LzVNQsFgtdVvqrNeRURERERUlzEAg4iIiKgKIXtFqJwZLJgBg0oCwRMQHx9fZJzRRYgxTWnnty/DCMDAtB06dJChQ4fKeeedp7ojmTVrlkyYMEHOPvts+eqrr8Tj8URd58SJE2X8+PERx6F7k3379kl1yc/OFlfQJ1p+rgTd1XcZ1TnVKY0T3LI71yv+QEA+WrBaDk13S5yr6oJC8OAsJydHZVVwV+O+qG61ZT9syyqQd+etFl9IE28gKAlOh5zaubGECnIrbB0IvAj5CvBKHM7CLk2aujVx6ro4dE3trz/WbpXkjk2lLqst50VV4L7gfqiL5wTK/uOyTeIPBNX2tEr2SLojIMH8UgYzeH3iCHglO/OAOANeqQ6oWxERERERUcWrnVc7dUgg1SX+tIOHwZdmvWkal69FfA3BBGs/vfaGtCFP4Qe+NOu0Wpx1Wt12r9ZhalXrsAXwOwOx5/WnFq5Xi7MWyuW1NteNz7G+DyYWLiy/qbXM7gLrtC57OUyrcgWs02puazk0+1lvGh1MsE7rybFNamtxbF6W27Z99mmdtnK5/Nb3/vTChXkbu6Mez0jMy7Jvb8B+L96WFtN8nOznUUFj68yBNOsEbtMzG3e+dXuKa9wdMB1vp60pdyDJEbPMDtPXwWGb1xG0Tuu0ncM6muCFy2CbNhj73AmZvjuOkHVcnG3742znbMg2vfkctn9XzNun3ttOpmCyM+J37uDEtre2L6n5XHLaGh25vBXTApKIiGoGI9uEz+crMs7rPXijP1ZGiljzR1oGMl+gC5IdO3bIsmXLVDclcMYZZ0jnzp3l2muvlddff12uu+66qOvEuLPOOqtIBozTTz9d0tPTpXHjxlJd9occEtqVKc6kFHG7bRXqKnZUZ12+XrpZZcHY5w3K0gMBOf6QVlW2fjxwQjcoCLCprQ/Q6st+8AVD8sGs9aI7nRIIaBLUHTK6d3tJa5Beoes5mPnCIe6kFEsABvZKi/Rk2XwgT1DF3ZQXrNbvcVWoDedFVeG+4H6oi+fE2j3ZsrcgIJrDoX5T+7ZrLu6k1NIvSHeJrumS1qChNE6r3O6gokHdioiIiIiIKl7tvNohIiIiqqWQvUKzRzCWYRlExTF3M9KtW7cSd09iwMMRBFdE66YEnyPzhZH94vfff5fZs2fLDTfcEA6+MCCoAgEY06dPjxmA0axZMzVEEhcXp4bq4nK5RRxO9XDZ4bIGC1e1ri0aSvPNe2VbZp74Q5p8uWSTHN+tTZVmwXC5XOrhWXUek5qgpu+HdxaslR3ZBarrEZwr/do1lS7NG1XKuhzOyN+P1g1TZWtWvmiaLit3Zan9hQewdVlNPy+qEvcF90NdOyd+37BbBZwFQrq4XU7pmdFEHGX5+4tgNadTXNW4L2rrMSAiIiIiqul4956IiIioCmniUF2QlGfAMoiKM2DAAPXvnDlziowzPuvfv3/U+fGAtF+/frJ9+3bZtGmTZVxBQYH8/ffflvm3bdum/kXf7nZGX++1vc/3msLpcMjgDs3Vg59gSJNd2QUybWXkQBmqv+Zt3C0/r9ou/lBIvIGQNElJkOMPiR50VVkyGiSpc1bTddmf71Pd5xAR1Ub4LZ29YZcENU0NhzZvUKXBj0REREREVDvwKoGIiIiIqA5Ctx2pqany2muvSXZ2dvjzzZs3y2effSbDhg2TNm3aqM/y8/Nl5cqVqvsQswsvvFD9+8wzz1g+f/nll1UQhjEeevToof796quvJDMz0zL922+/rf4dOHBghW9nfdW5aZq0SEtUgTJ4wP753+tVdxNEsDfXK6/OWiEhXVMPDJFwYkzfDuIydcdXVVo3SA73KBjSNFm58wAPEhHVSnM37lK/qcgoFNJ06de2aXUXiYiIiIiIaiB2QUJERERUhUK6Qw3lXQZRcRo2bChPPfWUXHPNNXLUUUfJ1VdfLT6fTyZMmKAe2j/33HPhaefPny/Dhw+Xiy++OBwsAZdeeqm8++67ap6srCw55phjZNGiRTJx4kQVwHHBBReEp+3du7fqagTBHYcddphceeWVqhuTWbNmyQcffCCdOnVSZaGKgWN4VMcWMunvDeIPhtQD959WbJVTe7XjLq7n8FDwxZlLJc8fOPigMBiSk3u2lcbJCdVSnoQ4tzRJTpAdWfkS1HRZumO/DO3SqlrKQkRUHr+u2a4C2wIhTf2mtkpP4g4lIiIiIqIimAGDiIiIqArpqguR8g1YBlFJIOgCARFJSUlyxx13yMMPPyy9evVSQRF9+vQpUT/t3333nfznP/+RX3/9Va699lqZPHmyjB07Vr755hs13gyBFsiWgeCPRx55RG666Sb5/fff5frrr5e5c+dKgwYNeOAqUMfGqerhz8EsGJpMWrRBCgLs5qW++3LRBlm1K0t8gZAaDm3RUPq2blKtZcpokCxO58FuSJbtYAYMIqp9tmflqd9WdP2FQLc+rRupv79ERERERER2zIBBRERERFSHnXnmmWqIBdksdF2POC4lJUWefPJJNRQnLi5ObrvtNjVQ1WXB2J61XmU52JfnlR9XbJXTe7fn7q+nVuw8oAJx0DrbGwxJSnycnNLjYFdD1QndkPy9dZ96cIlMGFkFfklP9FR3sYiISmz66u2ii64CHhF2cVg1B7YREREREVHNxeaTRERERFUopDsrZCAignaNUtTDbafDIYGgprIf5PuZBaM+yvUF5KWZy1TLbG8wqP4d3beDxMdVf7sLnKNoKI4wL3RDsnJXZnUXiYioxIKaJjPX7pBgSFdDp6ZpklgDfluJiIiIiKhm4tVCNYvf55PEAq96HYpPLPF8cQWa5b0zYG2x6AgVvtbirCkRg5r1vRYnUee1K9LlvK2hZMKBwg/i8mLf+HX6rNsQTC5MYR2Xr8fcPvs2ufyF411e67TBBtZpHdbVijNQ+NqTY914Z9C6LN1pXZYzWPg+ZCuTvQ1pccsyc3tjb39crm3fJTmjbl8wwRFzWeZy28uYuM+6ME+uI2o57eeNQ7Ntg23Z5h0UTLQ+SAyYtketx2ed151vKpdtN+q2VOia7VfOESpcVkKWXqrz22k6pTW3bWKHHvWcjHRumc/hYLx1ex2256ohW+NA3ZTm1Hz+Rjp3XH4t6rzufGuZQrZyEFHlwLfyYLu58i2DiMjIgnF0pxayNTNPfMGQHMj3yXfLNsuZh3XkDqpHkMHmtVkrVBYUbyCouh45pnNL1fVHTZCa4JH0BI/4g14JaZos27FfBrZvVt3FIiIqEWTwyfYGVCAGfsOOaMPsF0REREREFB2fthERERFVIa0Csl9gGUREhjYNU1QmDNc/WTAmL96osiFQ/fHz6u0yf9Me8QU1FYiDc+KoTi2kJsn4J1ML4rSX7thf3cUhIipV9yOarqvuvtC1U4cmadx7REREREQUFe/eExERERER1XJHdWwhbpdTtc7N8vrlm6WbqrtIVEW2HsiVd+etUq2ykf0C58EZfdurYIcaF4DhdEhI12XT/lx2lUNEtQIyS/21da8EQprqQqlnq0Y17veViIiIiIhqFgZgEBEREVWhkDgrZCAisj/c7tA4VT3g9gc1+WbpZsn2+rmT6ji0xn5hxlJ1zPMDQfGHNBnVq52kxtv6sKsBWqsMGAe7S8GDzDW7s6q7SERExZq5dkf4dwv/9mvL7keIiIiIiCg23r0nIiIiqkK6jvTr5RuwjKo2depUufbaa2XQoEGSlJQkDodD3n///ZjzzJw5U4499lhJTU1VA17/9ttvVVZmonqZBcN5MAsGgi+mLGEWjLrugz/WypYDeeINhlQQxhFtmkjXZg2kJmqUFC+JcW7VchytyJftZDckRFSzIeBi+prt6jcrGNJU907pifHVXSwiIiIiIqrhGIBBRERERMX64IMP5PXXX5eCggLp1atXsdP/+OOPctxxx8n69etl3Lhx8thjj8mePXtUEMa0adO4x4kqQcv0JOnUJE1c/2TB+HbZZskqYBaMuuqPzXvkpxVbxR8KiS8QksbJ8fKvbq2lpkLg3sEsGA7RNF2W7jhQ3UUiIopp5a5M2ZVd8E/3I5oc1obZL4iIiIiIqHgMwCAiIiKqQiFxVEAXJFWfAePRRx+VnJwcWbRokcqEEUsoFJJrrrlG4uPjVRaM22+/XW688Ub5/fffpXnz5mp+TdOqrOxE9clRnQqzYOR4AzJ58YbqLhJVgn15Xvnf78slpGviDYTUZ2P6dhCX01nju8pBNySarsvaPVnqoSYRUU31y+rt4e5H4t0u6daiZmYYIiIiIiKimsVd3QWo7/Q4l2gel3odirM+THG4TNO5TG9EJD4zZJ02aL1xFUwunL64LOVx+brlvTNQ+N7lt46Ly7fe0NNsZ5A7X4u4HPCnWrfB6bYWTMeduH8k7AtaxgWTrPOG7BkfTavSbPvRZWv05whZy+UwvdVd1nlDtveatRiWec2v1Xp91mPiS7fObD8u8dmF0+u2+6aabV/502z70rRN9v3uCepRj5H9uAQTrSu2H39fmu34u/SI5QeHFnsbzPs6kGRdbsjWZbX53FDj4wqnT9xn/S4kHLC+DyY4Yr63lNl2DJ3W01DiCvSo576d/fibz1H7e912XtmPkctnL6hpXEHsm9b27455Xvt5FJfHG+BEVUHXnaLZf+jLsIyqlpGRUeJp0c3Ixo0b5ZJLLpG2bduGP09PT5crrrhCxo8fL7Nnz5ajjz66kkpLVH81T02Urs3SZfnOA+qB0XfLt8gpvdqr7h+obkDwwkszl0muL6CCL/zBkJzUo600SUmUmi6cAUPXVNaO9Xuz5ZDmfKBJRDVPvj8o8zfuloB2MPtFn1aNVYAjERERERFRcXjlQERERFRLrV27VpYtW2YZdu/eXd3Fknnz5ql/Bw8eXGSc8dn8+fOrvFxE9cXgjs0l7p8sGHm+oHy1iFkw6pLJizfKip2Z4gse7HqkS7N0Oax1Y6kNmqUmisftUt2RBDVdVuxkNyREVDPNXr9T/CFNBTOGNF36tWta3UUiIiIiIqJaosYHYGRnZ8t9990n3bp1k8TERGnUqJEMHDhQ3n//fct0+fn5ctddd0n79u1Vumv8e/fdd6vPI9m0aZOcd9550rRpU7Xcvn37qn7No0H6bPRZnpqaqga8RutOIiIiotJ3QVL+AU4//XTp2bOnZZg4cWK1H5CtW7eqf1u3bl1knPGZMQ0RVbymKYkqq4DL6VAPjn5csVX25nq5q+uA1bsz5bO/1qvgGmS/SIp3y6he7VRAQ22A7Bct05MOdkOi6bJ4+/7qLhIRUUTT12yXkHYwAAPZpRBARkREREREVOu7INm2bZsMHz5c9u7dq1JY9+jRQ/Ly8mT16tUqgMLcz/jIkSNlxowZcuGFF8oxxxyj+id/6qmnVOvKqVOnitOUJhA3/AcNGiRZWVlyyy23SIcOHWTy5Mly5ZVXqnWOGzfOUo4ff/xRTjnlFJV6G+MQ4PHqq6+qIIzvv/9ejj/++CrdL0RERFR7aYLU685yLwO++uor6dy5s2UcgkujefDBB0u8jmHDhqmhLIwAWNSZ7BISEizTEFHlZcFYtTtTPaRHGvUvF22QK4/qxt1di+X5AjJhxjLVErsgEFT/ju7TQRLiavRlfcRuSDbszVYZMFbtylRdqiAwg4iopti0P0fW781R3Y/gt7ZvLckyRERERERENUONvlNz0UUXSU5OjgqmaNOmTdTp3nnnHRV8ceONN8oLL7wQ/hxZMG6//XaVLQPLMtxzzz2yc+dO+eKLL2T06NHqMwRfjBo1Sh555BEVxNGxY8dwcMc111yjHiAgC4bRjzmWh4CQa6+9VlatWmUJ8CAiIiKKFTxhZLAobwAGgi9QHymp8ePHl2o9ZQ3ASEpKUv/6fL4i47xer2UaIqocjZMTpHuLhrJ4234JhELy08qtMqp3e9WKl2ofXdfljTkrZW9ugXgDQfEFNTm6Y3Np0zBFahsEYCBjh6ZrkucPyub9udK+cWp1F4uIKOzXNdtFF10CQU0FiPXOYAAGERERERGVXI2NGpg1a5b88ssvcuedd6rgCwRC5ObmRpz23XffVf+OHTvW8vl1112nuhcxxhutLT///HOV9cIIvjDcdtttEgwG5cMPPwx/hm5GNm7cKGeddVY4+ALS09PliiuuUH2vz549u8K2m4iIiKgyH+CVdChNtozSdDMSq3sSIqpYR3ZoLnEuh8o0gIwJX/y1nru4lpqxdofM2bBbBV5gyEhPkiGdW0pt1DItSXWPg1BCdKWycldmdReJiCgMXY78tm6nBEOa+o3q0ixN4t0u7iEiIiIiIqr9ARjffvut+rdTp04yZswYFUiRmpoqrVq1UlkqEJABeECwYMEC9Xm7du0sy8A8ffv2VeMNS5YskYKCAjnyyCOLrBOfoSUOui0xzJs3T/07ePDgItMbn5mnj2T37t2ybNkyy4DADSIiIqp/0P1IRQw12YABA9S/c+bMKTLO+MyYhogqT8OkeOnRspG4nU71QGn66u2yI4vd/9Q22zLz5K25qySkaSr7BYIXRvftUGu77XC7nNIiLUmcTodK7b9k+/7qLhIRUdiCTbslzxdUfzcRwNivbfTu/YiIiIiIiGpVFyQrVqxQ/15++eUqW8Xrr7+ugiMmTpwo999/v2zevFleffVV2b9/v8pq0bNnz4jLQetK3OjPzs6WtLS0mK0u0c1IkyZNLK01Y00fq3WnGcocLeV3IMklgZSDh8EZ0i3jdNP9tGC89eaa1tgefW99r8UVTh+0Zxm2rkbEduPOcTC25Z95reP8ydb3uu0McmjOiK/VshJs69Fs5bCMsxfSSi9ys7FwemfANq9tUleBdcXm/R5McsZcj9O0byCQZN7P1mnjs6zLStnmt7zPbxZnXZczepnt+8qTbS2Ir6Er6rmSeMA6rX0bQ57C6ePyrCsKJDtjHhdzmfOaW6eNy7OW2e2Lfn5r1l0hroDtvd86r3kb85pbT0KX7fh7cqzbFJdf+D4Uby2zZvtamacFf6orYvnVskzfObUsWwsZl9+6LJ9pWQ7dds7a3vrSrMsKJBe+js+2HyOJ+Z11+aMfT0+OdV4iqhwIngiVM4CipgdgHHPMMSow9tNPP1V1IKMrOdTHUKdDV2+RgluJqHKyYCzbcUBlwCgIBuXzv9bLjcMiXztRzYMHgBNmLBVfICQFgZB6P6ZvR0lL8EhtlpGeLFsO5Iqm6bJi5wHVsALX+0RE1e3XNTtE03X1e9sg0SNta2FXT0REREREVL1qbABGTs7BJ4HJyckyc+ZMFRwB55xzjnTv3l3dvEeXI0b/4cZ4u4SEBPUvgjQQgIF/i5vemMaYL9r05mXHgq5Q0IWJGTJgnH766THnIyIiIqopFi9eLF9//bV6/ddff6l/J0+erLpqg1GjRknv3r3Va5fLpQJQ8dmQIUPkpptuEo/HI6+88ors3LlTZTpzOmt2EAlRXZGe6JFerRrJn1v2qodJv67dLmf0aS+t+UCpVvho4VrZtD9XvMGQ+IIh6dO6iRzaooHUdq0bJKsMHkFdk/35PtmdUyDN0w5e2xMRVZc9uQWydPv+cPaL3hmNGRxGRERERER1JwAD3YfAeeedZwl+wM37888/Xx566CGZPn16OLDB5/NFXI7X61X/GoEaxr+xpkcWDEOs6e3LjqZZs2ZqICIiIkKiGs2e6qiUYiSRqjR//vmnykJm9vnnn6vByAxmBGDAyJEjZerUqarO9sADD6jP+vfvL9OmTZOhQ4dWcemJ6rdBHZrJ0h37Jd8fVA/xP/t7vdw6vPD7SjUTgma+X7ZFAqGQyoCBLmVO7F40M2NtlNEgKZyIEV2rrNiVyQAMIqp2M9bsEF108YdCKjHl4a0bV3eRiIiIiIioFqqxARhGquqWLVsWGWd8hu5HGjVqpAIgonUDgs+R+QJDcd2GIMhi7969MmjQoPBnsaaP1T0JERERUV3qguSSSy5RQ2kMHz5cDURUvdBdRZ+MxrJg0x7Vqvf3tTtldJ8O0q5RKg9NDXUg3yf/+325SoOPrkfwIPDMvu3FXUeyByXEuaVJcoLsyMpXrczR4nxYl1bVXSwiqsfwe/vrmu3qNykY0qV9oxRJqeXdPRERERERUfWosXdvjCCILVu2FBlnfNa8eXOVCrBfv36yfft22bRpk2W6goIC+fvvv1VrS0OvXr1U1yFz5swpsty5c+eqvmcHDBgQ/sx4HWl64zPz9ERERERERDXNwPbNJN7tlJCmiy8Ukk//XF/dRaIYDwEnzlwm2V6/FASC4g+G5PhDW0nT1LrVRYfqhsTpUNu7fOeB6i4OEdVzCATbl+dTgYrIzHNE28LsuERERERERHUiAOO0006TBg0ayHvvvSc5OTnhz3Nzc+Wdd96RuLg4+de//qU+u/DCC9W/zzzzjGUZL7/8sgrCMMYDsmWMGTNGNmzYIJMmTbJMj/ndbrece+654c+OOeYYadeunXz66aeWYJDs7Gx5/fXXpWPHjjJ48OBK2ANERERUF2m6o0IGIqLSSImPk76tm6gMCoGgJnM27JL1e7O5E2ugb5dulqU7DqjuYjB0bpouR7RpKnVN6wYp4nQ4RNN0lQkjMz9yN6FERFVh+prtqlGWP6RJYpxbujZrwB1PRERERER1qwuS9PR0ef755+Xiiy9WGSwuv/xyle3izTfflG3btsmjjz4a7qbk0ksvlXfffVcmTJggWVlZKmhi0aJFMnHiRBk2bJhccMEFlmU/9thjqv9xBGYsXLhQOnToIJMnT5ZvvvlG9W3eqVOn8LQul0stZ9SoUTJkyBC56aabxOPxyCuvvCI7d+6Ub7/9Vpx1JA0sERERVb6QONVQ3mUQEZXWgPZNZdG2fZLrC6isCp/+uU7u+tdh3JE1yNo9WfLxwrUS1DTxBkLqIeCoXu3UtXBdk9EgSbBZ6F4FKf9X7c6Uge2bV3exiKgeyvEG5I9/uukKhTTp06aJChAjIiIiIiKqUwEYcNFFF0nTpk3l8ccfl/Hjx4umaaoLkY8++kj+/e9/W4IkvvvuO3nooYfkk08+UeNbtmwpY8eOlQceeECNN2vbtq3qPuSee+5RgRTIqtG1a1f1+qqrripSjpEjR8rUqVPV8rE8QFAIgjiGDh1arm106LoaIBRnvbgzd+8eTLSOS8g8OE94H/it7/3uwuldXus63V7rtA7rW/HkhsKvQ/HWBzzOeGs5Avb3pqy4njzrgkPx1vXYu693Bs3LsY20Xfdq7ujLcgY0yzh/aoyJsX+yTCu27Qt/mnVah2adQDPtZ7GuVjTraSe+hrG/bm5v4QL8KdaZnaHYx8wsrsBWRpd15/mTrdvkyStcrycnFHO98bZGkt4GheX0p9tvTljnTdkeiLrvgglxlnEhWzer8VnWnesMFM6r2b439u9RXnPrvnT5C18n7gtaj4F1863HV+0783qt08blS8zvpDfdWo5gomm9Xut68pvZymxrDJi4z3aymYRs30mnbZvcvsJyOYO272gCbzARERHVZcmeODm8TROV/QIPmeZv2iNrdmdJl2bp1V00Qh3QH5QJM5aqYAR0PYJ/z+nTXhI9NfqyvcxSEzySnuARf9Cr0v0v3X6AARhEVC1+X7dD/eYi+0VI16Vfu7qXdYiIiIiIiKpOjb+Tc9JJJ6mhOCkpKfLkk0+qoSSQ9QKBGiU1fPhwNRARERGVB+Iuy9uFyD+xm0REpda/XVP5a+teyfUGVPcWn/y5Tu478XDuyRrgrbmrZHdOgXgDQfEFNRncobm0b5QqdVlGg2TZl+cTxLkv3bG/uotDRPUQuh35Zc12FQiG7EOt0pOkcXJCdReLiIiIiIhqMeavJiIiIqpCmjgrZCAiKgt0aXFEm6bidjlVFow/t+yVlbsyuTOr2W9rd8jv63aKP6ip4IuWaYkytEtLqetaN0gWp9OhWpxvPpCrsoAQEVWldXuzZeuBPPU3EVkwDmvdhAeAiIiIiIjqdgYMIiIiorpEEzxocpR7GVQ3LFu2TKZPny5LliyR3bt3i8PhkGbNmqlu95B9rXv37tVdRKqD+rVtogIvcrx+lQXj4z/WyoMn96vuYtVbO7Ly5c25q1Tr64JASFxOh4zp21GcDkf9CMBwHGyBjoefq3dnSl8+/CSiKvTrmu2iy8HuR9xOh/Ro1ZD7n4hqrd15++SGb+4Lv3/xlEekWXLjWruemmrZ7tUyfvqz4fefnvNyiefdlr1Tbv/hYQnpmpzS9Ti56LAzpTYKhAJyw7f3y4GCLOnWtLOMP3ZsdReJiKhGYQAGEREREVEV8vl88sYbb8jLL78sy5cvVw8eI0EwBgIwrrvuOrnsssskPj6ex4kqREKcW3VFMnPtDvXQe9H2fbJsx37p0bIR93AVw/6fMGOpFPiDKvjCHwrJ6D7tJT3RUy+ORcOkeEmKc6vMH2h5vnznAQZgEFGV8QZCMmv9Lgmq7BeadG/RUDwuF48AUQU8kI/m/TNfEI8rrtjplu5aKd+v+VXW7tso2f5c8TjjJNmTJE2TG0nb9AwZ2n6QdG7cvkYfq29X/Sx5gQL1ekBGH2nfsI3UZLguXbRzuczcOE/W7N8omd5s1f9pw8R0aZ3WUga1OVwGtT5MPO76UU+tLO8tmqSCL+JccTLq0BERp9mcuU2mrftdVuxZI3vy94s/FJD0hFRpltxE+mf0lqPb9pcGielq2gd/+a8s37MmPO8lh50lI7seG36fWZAlV319V/j9uOG3So9mXdXrXzfMkYnz3w2P69CgjTz+r7vVvQjDozMmqPMC8L27fuDF6rUq/yEj5J2/P5cVe9bK/K1/y4DWfStwTxER1W4MwCAiIiKqQpruUEN5l0G10yeffCJ33XWXbNq0SY488kh5+OGHZfDgwdKlSxdp3Lixuum1b98+WbNmjcyePVu+/fZbuf766+WJJ56QJ598Us4+++zq3gSqIw5v00QWbt4jWQV+9fD7o4Xr5OGTG1putlHl+/TPdbJhX47KRIKhd0Yj6V6PAmFwvmU0SJZsb0A0TZelOw5Ud5GIqB6Zt3GXCsJAMFxI06Vf26bVXSSiWi09IU1eO+2JqOPP/uTaEi3np7Uz5fWFH1k+K9BCUhD0yt78/ephb+OkhjU+AOO71b+oh+eA7BA1OQAj25crL8x5UxbvWlFk3M7cPWr4Y/titd+Nh/dUeuv3b5Y/ty9RrxHMYgRRGDRNk/cXTZJvV/+isjOZ7cs/oAYEZeQHvHJ2z1MirmPS8u/l2A6DJSEuodTl25C5ReZsWSiD25YsO+JxHY+Sj5d8Lb6QXz5b9i0DMIiITBiAQURERFTlARjOci+DaqeLLrpIZbMYO3asdO7cOeI0rVu3VgO6ILn33ntVMMYzzzyj5mUABlWUeLdL+rdrplKv48ETMmAs3rZf+rSuP6mDq9vibfvkm6WbJRAKiTcYUlkvRnZvK/UNAjBW7cpUGTDW7slS52Ocq3x/J4mISuLXNTtE0zXV/Ujj5ARplZ7EHUdUzXxBv8oQYBjW4UgZkNFXEtzxkuXLlrX7Nsn8bX9LXecNeMv0AL0skF3hsRkTZP2BzeHPsM+PbHu4pMenSbYvR5buXi2zNi2okvLUZT+tnRF+PaTdwCLj3/zrExWAZM5IMaLzMdIipYl4gz5Zu3+TylBSXDDNlFXT5KwoARrF+WTJFBnY+jBxOYvPCIVz9IiM3jJ78x+yKXOrrN67Xro26Vim9RL9P3vnAR5Hcb7x77p6c7fk3rFxx7jQS0KvpgUwoYcQCBA6of8JLST0GmoIvRebblNcwNiAe++W5aLeru3e/3lHPml3fXeWdJJO5f3Z+9zd7uzs7OycbnfmnfcjpL1BAUYrwlOmmz770+xRtyUVaabPscZxqnPMGzXdPGjjrjTn7cus+3F1+M1KS5s5qTi9kS2zQSDZfBx70Lw9qcScmU2vy0tzm8ts08zH0R3mvG2Gzd5OzphltgfMeWmeumPZzNUqnlItat1Y83J6zfv6U81l1DRbzHJU59SVO7TH/Y3lfC3ldBmuoeY2p63sbs7Mmrfuqjv/QIq53t0V5srTnea8je3DXWrO1x4wf/Zlm69LCMGew/lY6sJh2beqq7nQ/ozoA4+OGmc/Q0GsKeqOpbvM+eiWNuvwhaLWnXVfzWNpV5bt1nNyl9elD1nas269/hbHeae3Ln3QY943aOkvclWGon6XHF7z9bWWgxBCSNOzYsUK6devX4P2gTvG008/LTfccAMvCWlSxuR1kp837ZSSKp9ywXhjwRrlwEAXjOYHziNPfLdU9FBIhR7B69Qx/cTZAYUHeVmpYrdBnKiLL6DJul1lMqRbVqKLRQhp52wrrZIV20tq3S9G8fePkFbB5tJ88QV96n2qK1n+PGGaafuU3vvJeWOmSnXA3BFrDMMwdfix0j+7t7y/bIZsLN0qHodbxvbcV84eedIejgNV/mqZvnqmzN/6qxSU75SAHlQuD2N6DJeThx2lwm9YwSDzZ6tnycpda1WYDqfdKZ1TsmVY10Fy0biz5K0ln8g7Sz817YMwD+FQD+EwDsZ0+3QZJOeMOkVeX/yhCruCe6MXT/mXbCjeLJ+s/FoNbuNYFYEqcdocqowjug6Rk4b9Xjqn5sTt1GEUX5y57wlyyj5Hm9LAEeHMEcer+7VIBLWAOpdv18+TwuoS6ZScpcJgHD34UFO6lxa+JRtKtsj2il3qXIJ6UNLdqep6/W7gQeo6xbquA3L6yPvLPpMNJZtVCIwx3YfLH8eeLhmetLj2CYfq+GTV1/JL/hIVUkeXkHIu2T9vtJww5HeS4k6WeIC7xdwtC9V7hOHZt9sQ0/bVhetN4gu0wesOuEycBiHE+NxRMnWfY2RH5a6Yx0Kb+f2gQ/Y4x/qwrWKHfLNujhw58MB6pR/XY18lwAB4NQowlu5YJXfO/Hft57fOeKrB5SGEkLYKBRiEEEIIIS2ILjbRLMK6xuRB2iYNFV801b6ERMLtdMj+fbvK1yu3qgEoDET9smWXjO1FC/bmBGKLp75fJqVev1QHguIPanLE0Fzplt4xZ153TU9WbdGn6coFY3lBMQUYhJBmZ+bqfGXvDvcL3FmP6dWZtU5IKyDF4PpQGaiWl355W6b0Hi99s/LU4HmY5BjuEPM2LzQJIODw8O2GebJi11q578gbJdVdc8+FQXYMDu+sLDTtv71ipxJYzN20QG495K/SOyvXFN4BDgHG8BAQbWwu26YWCDAaA0J83DHzX6qsNfVQM9gPscJ3G82OB5pokl++XS0Y0Mc5dUltvIsdRBNhuqV1UaKOSGQkpUfN419z/iObSrfWft5euUte/OUtFZZmcu9xteshdrECYcnCbUvUcsHYM+SoQYdEPAYcOKzX9YdN86UyUCU3HfSXuPZZW7RRuYCU+ytN+28tK5D3ln0mszctkDsPu0ZykhsvEoYAJCwcgijE6jAxa/3c2vc2scmF484yiS/COB1O6ZnRPeIxBuX0VS4ZCNeDtvrHMafVu3wuu1PyMnvI+uLN8s6yT+XgvvuL2+ne636DOvczCS4IIYTUQAEGIYQQQkiLhyCJU4DBECTtnk2bNklhYaGMHj2abgSkWRmV20nmb9wpRZVeNQD++s9rZUxeZ7a7ZuSzZZvlt62FSnjhC2rSv3OGTOjTVToqmOEJ2//VO0tF10OyKL9IThpFwRkhpPmA48V3a7ap16AWUn+Hk13sIiWkNdA9ravkpneXreUFte4MWDBY3Tuzp3J9OLT/ZMnL6BE1jy1l21Tokkm9xsrGkq3KaQJOCxBWvL3kE+V+AB6b+0Kt+GJAdh85fuiRSvgwa/0cmbN5gZT6yuWRuc/Lg0f9Xew2uywqWC5vLP6o9jgYRD960KGSmZQu+WXb5Zv1c9T6w/pNlpHdhsq/5jynxAUAbhpwNAAQJVgpqi5Rg/unDT9WiSlwDgDnCWeMbmmdJdmZpAbkK/xV8tXa7+XXgmVSjnATK76SC8ad0eiQL+G6Big3zrWhoG7PGz1VlfP1xR8pJxOAa2cUYMBZA9c3zZOinEkgXllXtEk5f4A3l3wsRw44MGL4CzgzQIxzYJ8JsjB/iXyxtsYt4pdtS5UYpWd6t0btE9SC6lqFxRcjuw2T3w86WNXD9FVfy+LtK9X5Pf3Tf+Xmg6+QxrJpd52AHhHKanQhQbngvtFQ+mT3ki5pnZUTxZdrvpPjBh8eUcQRjbP2PUn+8d1jUlxdqsQy0cQ4RrqndRGHzS5aSFciJLikNKYNEUJIe4NPF4QQQgghhCSI559/Xr777jt5+eWXa9ddddVV8thjj6n3EGB88803kpm5p/UtIU2By2FXLhhfrdgiQU2XNTtLZf6mnR1aENCcrC8sk9d+XiNBXRdvQBOP0yEnjezT4QUvuVmpKvQIHDBWbi9RLiEQZhBCSHPw65ZdKhRUTfgRXcb3pvsFIa0Fu90uf510ofxz9tPKoSKMpmtqZj6WT1d9o5wmjhhwQMQ8IIwIhy4Z02NEjUhh5Vfq8+zNC5QAAwKBlYXrat0GTt7nqNpwDb8beLD8nL9IuSVgQHnFzrWyT9dB8tW6H2qP0SO9q9x12N9qXTlGdd+nNtwGQoJggaOAMf3QLgOjnjfKcNNBl0ufrDz1eWT3YeoVoTnWFW+U6atmypbSfOUKYg0Dsmr3eTSGSn+V6XO6J7VR+Zw24lg5dsjh6j3q7eG5z6v3EDkYGddzX/l05dcq3AbEKRBgWMsD1wmj60iYXhk95MqJF6j75tE9hitXE5/mrzlOWWQBRn32WbR9ea0Qx+P0KNFBWLRw9KDDlAADQPCyq7Ko0SFfynzlte8RdiXWtUhr5HUIh5D5ccsvqm7fWvqJ/GHfE+u97+ge+8jwroOVk8WHK75QYpj6kOZOVYIltM0KX2WtWwryYtgRQkhHhQIMQgghhJAWRA/Z1RJvHqR98MILL8iQIXWxX+fNmyePPvqoHHLIITJs2DB59tln5V//+pfceeedCS0nad+MzM2RnzbukMJKn3JkeOPntTK+dxcOgDcxCDfy6KwlSuiC9wE9JFPH9JVkd52ddkclLytVdYyj07bSH5RNRRXSt1N0m2tCCImHb1blK6EXnIhSPS7p13nP2eiEkMTRNztPHj76DlmwbbFyncBgPdwDwsIDvCK8xX65IyO6SQztbBY6QPgQFmCUesukKlAtm0trHCYAwon8c/YzUcuD0BoQYGwx7DOu50hTSJR4gYtAWHxh5Kn5/1WigVhUWMJmNIRwOJYw5b7G5TWi61DTYHyksuFa3vvd48opIRZw+IjE8G5DakXLcFhA2X3V/ph1UJ99jG3BF/TJXbMejtkWGivAMFIXwCbytYCIIZ62dHi/Kcrt47sNP8pBffZv0P5njzxZbv7qfiUIgQijPhhD8hBCCKmBAgxCCCGEkBYEj6U1kabjy4O0D9asWSNTp06t/fzOO+9Idna2zJgxQzwej2iaptZRgEGaE6fdLhP7dpMvlm9WogC4NMxbv10m948cW5g0jpfnrZKCsirxBjXxB3WZ2Lersr0nIj0yUsRhx9xPUe4gK7aXUIBBCGkWiqt88suWXbvdL0Kyb88cCg4JaYU4HU7ZP2+MWgAGgz9d9bW8s3S6+hzQArK+eIuasd8YGmK05Q36pLnJSs6MGJbEKL44oM8EOajPBElyeuTn/MXy0e7B8VCo8T0EHqdbcjO6K9cJsHj7CpVfWLRQX4yODZHCh4CPVnxZK77okdZVuWZ0SslWx7tj5r/3OphvFHao49QjzEV99mmptpDhqRMXRxKMIAzO2qKNtc4h8bhtTB1+TK3bx5uGsDn1YWCnvjIhd7T8tPVXmbFqpnRPj+2MiOsXFs2g3cTj3kEIIe0JCjAIIYQQQloQLWRTS7x5kPZBaWmpElyE+eGHH+Swww5T4gswfvx4ee211xJYQtJR2LdntszfuEN2VHiVC8abC9fKxH7dOCjVRMxeVyDfrtkmfq0m9EjX9GQ5dHDPpsq+zeN02KV7RopsLCpXA6KL84vkqH16JbpYhJB2yPdrtqnBIggw4IIxrhfDjxDSmoDQYn3xJhnRrc5RIewOcOzgw2sFGCAkkZ0UVu5aG/UzHDNSXMmSm14nNIYzwpPH3SM5KVkRB9wheAB5GT1kS1mNW8LC/MVy1r4nmFwwrMIF43v8vYlFpCd8DMAbuWTcWZLkSlLvZ62fK03FIX0nyf8Wva/eF1TsVK4HCMNhpcxXIbquRRSL1IddVXXng3AtEJSAFTvXSCLJzehhamdPH3+vEqbEaguNoXdm3b3/NktoFnBIv0nKtSIsQvnPwjfkuimX7iFoCeqa7KjYKT0zoovlcY2OGXyYvL/8s9pQOw3hzJEnqDA8EHBsLNkSMy3aTNidpldGT/V9IoQQQgEGIYQQQgghCaNr166yfv36WjHGwoUL5ayzzqrdXlVV1eDZR4Q0BgdcMPp1kxlLN0lAC8nGogqZvbZADhxY1yFJGsf28mp5fs4K0fQa8YXdJjJ1TD+KWyKEIdlcjI79kCwrKG7U7EtCCIkF/q7MXJ0vQT2kwkHlZadJVkrjB9MIIU1PZaBa7pr1iPRM7ybjc0dJ/+zekuFJk8pAlXy99ofadBiUhmNAJNYUbZCn578qE/PGyMaSrWoWf5hJvcaq195ZuTIop6+sLtqgBo/v/vYROW7w4dItrbOazb+zskiW71oj+WUF8vAxd6h9jhhwgMzbsrDWoQCuDb8feLBkJqXL9oqd8tXaH+SB399Se6x0d5rsqCxU7+dtXiBdU3PEaXeqc8tI2nuoNZTFyGuLP5TxPUfKkh0rZeaGphNgQAwxd/MCWVe8qeY4iz5QTgyTeo1T51bmK5dlO1bL9xt/kusO+FOjBRg4H9Qb+HrdbOmS2kmF2nhjScMcGpqakd2GSueUHCUQgQAIIUhwXXOSM6XUVy47Kgpl6Y5VSvBz6yFXNfo4fbN6KfEPQuCsK94suq6L3W43OU/guJ+v+bZW5HPLVw/IkQMOlG5pXZQYAtfluw3z5KC+E+X0EcfFPN6JQ38nX679vlEhaiA2OrjvRJm5fs5e0yJEUJh9ugwybUO93WlwN3nrjKcaXBZCCGmr0AGjFWGzKGHtwbrPTp95WzDZrCT0Zpk/27W699Yw8bpFwKn7ondqVXcy7xxIM6d1WFy3HNV15bRZhL0OyzlYyxVCT2S4TBanMk+FWdHsTzfv7DN8tumxz9ebZc48qcRQz9XmnTW3+Xw1S2g/p6Gerfs6LPVa2c1c5lCa+bOzqq4cScXmvILJ5rx0yzc3ZLhZC1ld3iyX13icPfKypNUs52DN2x40vNcs+yaZ9w34669+DZrDD4rutLQ7b/R2Zb1mwaToefm95jK5LHUTtJyD5jGo2C3nG0V0X0vAck6eUmO+EvN7Zf3++zJtUb+Te1xfh3m7N6fuc1Kx+TiucutJEUKag5DYRbf+CDYiD9I+mDJlijzzzDMyYsQImT59ugo5cvTRR9duX7t2rfTowQFw0jLs0z1bftywQ3aUV4s/qMlbC9eqMCQIDUEaB8JpPP7tEqkKBKU6gNAjmpw4so9kJXPAz0puVqoSpQRDugoRgHbYLcNyE00IIXGA8EYFZdVKfIG/z2N7dWJ9EtJKwUB9OMRGJE4bfmxUEUPfrDyZuW6OfLNutml919ROcvrwukHrKyZdoAaHC6uKVQiOZ37+3x55dUmpCwExsvswdVy4cMChAAPPxsFnK6N6DJO1xTUhJX4tWKYW8Jf9/ygH9d1f9gbcOg7ovZ/8sGm++vzZ6llqAcO7DlaD202B2+GSmw/6izw670VZtH25Wvfjll/U0pTAweSXbUvVe7gq3P/9k+r9iK5D1DVIFHAxuXryRfKP7x5XAoxo19UqLmgoEFtM7DVWtUtf0KeENGhTRs4fc7q47E75dNU3qo1BFBOpXdaHFHeynDTsd/LqbzXuJg0FIWLQ9hDuJxYL8hfXvp/SZ3yjjkUIIe0RCjAIIYQQQloQPWRTS7x5kPbB7bffLjNnzpQzzjhDfb7wwgtl8ODBtbM0P/jgAzniiCMSXErSUYDQYlK/bvLpko3Kmn1zSaV8v3abHDKIoTIayzu/rJM1O8vEt1t8MbxHjozoyQG/SORmptbG4IZbyPLtJRRgEEKalFmr89X9FcJBuZ0OGda9LgwcIaR1kJOcJTcc+GclLli9a50UVZeo0BfBkCaZnnTpn9NHjuh/gIztOSJqHnDO+MPIk+WdpZ/KhpLN4na4ZWyPEXL2qJMlzZNam657Whf55+//LjNWz5Sfty6SbeU7JKAHleNGp5Rs2bfbUJmQO9qU92kjjlPr4VKwctc6KfGWidPuUA4K1gH6U4Ydrdw0ftryq3JSwN+fhnLpfudIdnKmzNu8UEp85ZKb3k1OGnaU+DV/kwkwAMQstxx8hfxasFS+3/CTEiDg3CACyE7Okl4ZPZR4AK4hjQVig+sP+JO8vfRTJXhBuA+4bJy57wky7d3GO0s0BYM69ZOHjrpVpq/6Rn7dtkw5msAZJSspQzl1jOq+j0zIM7eFxvC7AQfVCoO+2/jjHgIMiDSmjZmqwpHAUWX5ztWyo6pQAlpQtf+uaZ2VC8oBffar1/GOGnSozFg1SwqrGy5wQZuGI8cnK7+KmsYb8MqC/EXqfZ/MXBnSeUCDj0MIIe0VCjAIIYQQQghJEEOHDpVly5bJ7NmzJSsrSw488MDabSUlJXLNNdfIIYccwutDWoxh3bNk3obtsr2sWny7XTCm9O8uLgeddxrKkvwi+WhRjZjFG9QkPcklx47o3SzXrT2Q5HJIl7RkyS+pVOEBFucXUfxDCGkyqvxBmbcBg6s17hcjeyIUAH/bCGltQMwwrue+aomH0T32UcvegAhg6vBj1VJfhnYZqJa94Xa65aJxZ6klEgghsbcwEh6nW84dfaparGCQ3gpcPhob5gGh38b0GKGWvRHrOHDniLYN4hgsVqKlv+Owa6KW4Ynj72myfcLin3NGnaKWvRHrHGPRP6e3attwjZi7eaGcM/LkiCFdECLngnE1kzT2RqzzhbvJUyf8I+p2tKFI7SjMtNGnqiUaX62bLf7dDhkQJzVVPRFCSHuATxqEEEIIIS2ILrYmWUj7IScnR44//niT+AJkZ2fLX//6Vxk1as8OKkKaC4SAmNKvuxqUgkV7fmmVfLtmGyu8gZR5/fLEd0tFC4WkOhAUPRSSU8f0o5BlL+QhDIkdTlEhWV6QOCtqQkj7Y8767eIP6koUp+khGd+7S6KLRAghpAMCgYfDZlehPT5a8aW0VVD+j3eXf1iXgU3iEEIIIe0JOmAQQgghhLQgcB2NN4RII5xLCSGk3gzulildNyQp8QVcMN5euFYOHtiD4oF6AnvpZ35YJsXVPiW+QOiRw4bkSo+MOstrEj0MyULbLiX+2VZaJSVVPslK8bC6CCFxM2tVvgpvBAFG17RkhjgipBko9ZbJ6W9exrolJAa5Gd3l9dOfaPN15HK45JkT70t0MQghpNVCAQYhhBBCCCEtBGK6wtq1ISB9MBhstjIREskFY3L/7vLBog0SCGpSUFYt36zaKr8f1ouVVQ8+X75FFm4uVDOtIWDp0yldJvbtyrqrB3nZqYI/kdAZIgzJyh0lsn/fbqw7QkhcbCqqkLW7ylT4EbhfjM7rxBolpImJJ/QFIYQQQkh7gwIMQgghhJAWRA/Z1RJvHqRtMm3atD0EGAsXLpTFixfLoEGDZJ99auIUL1u2TFavXi377ruvjB07NkGlJR2ZgV0ypFt6smwtqRS/psk7v6yTQwf1FLfTkeiitWo2FJbLaz+vlqCuizcQFI/DISeP7Ntg4VVHJc3jkswkt/iDXjVTfUl+MQUYhJC4mbk6X0ISUu4XdpvIKAowCGl33HHYNYkuAiGEEEJILRRgJBjPLq8kVVap977OyaZt9kCdv7g/3dzRGUgxd+Alleimzw5v3Wd7pnlfmzmp2INmH/OQoy5vd7l5m8Nr3tfpM293VtdlrjvNZfRlmAeL/Onm7e6KUNRtujN2UzWOQ9k18zaPpW6c1eYyB9Lqdg4m2/dSV+bPNkNW1TnmenZVWerOb9436IiedzDJFvO4Tq85b1uwrqAhS707LNfI+jmYUnfOuqVM3mxzXq6aplp3XD0Uta0ErU7BtujtLpAau0N6j3Mw1KXDb95W3dkWs96N198eMG9zl5grWksyt4fUgsjXHnizLYOhlu3Waxgy1LVubd7W6rB872yGvJIKQ1H/bliPo/b11mXuzTKX2ZvJAV1CWgKEH4k3BEm8+5PE8dJLL5k+z5o1S95++21544035PTTTzdtw7qLL75YHn300RYuJSE1LhhT+neT936rccHYUV4tX63cKscM783qiYI3oMlj3y5RzhcIPYKBvlNG95NUj4t11gDyslKlsNIneigkS7YVse4IIXGBv8Xfr92mQhsFtZAM7JIpHooJCSGEEEIIIc0IBRiEEEIIIS1ISGyi76G0angepH1w6623ygUXXLCH+AKceeaZMnv2bPn73/8u33//fULKRzo2AzpnSM+MFNlUXKFCabz840r5bWuhLNtWLBXVXklLTpKRuTly5NA8GZnbSYk2OjL//WmV5JdWiTeoKRHGfn26qIE+0jDystNk8bZiCWgh1faq/EFJcbPrghDSOH7etFMqfTWiOLgTje/dhVVJCCGEEEIIaVbYi0EIIYQQQkiC+OWXX+Scc86Jun348OHy4osvtmiZCAlj2+2CsXlhhXIk2FnhlY1FFeJx2pXbV5E3IBuLK+TbNdtkcNcsue7wUdIjM6VdVyBcGRZtLZQvV2yRRVuLaoUoXdKTZO3OcnHYa5wwuqQlyeFD8hJd3DZJblaqChEQCtWEC1i1o0RG53VOdLEIIW2Umavy1d9u/D3JTHZLn5y0RBeJEEIIIYQQ0s6hAIMQQgghpAVhCBJiJCkpSebPny+XXnppxIrBNqQhJFFkJLlrZw5DkIFB8W7pKaJrmjidDtF0kTKvX80wvuXjn+Se4ye0WxFGfmml/PPrRUoQUOYNiA0qlJDIruqALC0oVg4gDptNMpJdcuro/uKAioA0mOxkt6S4nMpFJKiHZFlBMQUYhJBGsbOiWpbkF+12vwjJqNxO6reMEEIIIYQQQpoTe7PmTgghhBBCTOgGEUajF9Zpu+HYY4+Vl156SR577DEJBoO16/H+0UcflZdfflmlISQRYMbwB4s3SEDXxW63KVcCPVQjuAjjdNglJzVJspLdsmZXmTz49W9qv/Yovvj7x/OV0CQQ1KVbWrL0yEiRzqlusYlNnDab6HpIhWqxI0wUx/caDQZHa1wwaup0cX5RU15KQkgH4tvV2yQkIfFrGvRyMiavU6KLRAghhBBCCOkAUIBBCCGEEEJIgnjwwQelf//+ctVVV0m3bt1k//33VwveY12/fv3kgQce4PUhCWFjYbnkl1RJktOhFgBtRUm1fw+RRarbpdLAHQIhOtoTOFc4X0BgAqEJBCcQnoAyb1CJLlAbmFSd5HJIuS8g7/+2vl0KUVqKvN1hSFCHa3eVqdnrhBDSEPD3AyGy4HwR1ELSNydN0pPcrERCCCGEEEJIs8MQJIQQQgghLUhot4tFvHmQ9kHXrl1lwYIFSojx3nvvyaJFi9T6AQMGyOWXXy7XXnutZGRkJLqYpIPyy5ZCqQoEJSvZJZruEL+mqxAkGAsvrvZLil4jOgjjtIsUVfrk5R9XSZU/WOtmUBOJoyYh0tt2r695rdkWXr/7U22+xnTG9QAOCbXpdrtOWPOueRfOq+ZzbWSQCOnUtt3rw/ss21YsywuKxe2wi8fpkKCuq+3eoCalvoBKB6kFQo7kpHik0h9UwhUIWPp15ve38QIM/F7q4gtoSoQxtFtWo/IihHRMEHpkV4VXCbg0XZexvTsnukiEEEIIIYSQDgIFGAnGn50kvvSaGMm60zyY4s2pmWUGfJnmbTbLBCB/0GxmkhSom21lD5pnXmluc172OrdrhXFMx5o2aAlBHrLENXb46j4HUsxlCln8VqznEEip21fzWPM1n4Mv2zLwZNicVGROq7vMaatT7VHLoVu+Eda6cVeaCx1Mqsvbb7lGmjVc+14mwBmvk7WuxHINfZnmBPaafl+FzXIczTLBI+Qwl9NVqdW+r85xxkxrD5rP31VR99mfYb3AlnK4JGqZrV761mFFU1pLOwxZ4re6ys0VEEy25F13uhJMNu9bkWeuLIffnJc/zRYxn0hltNa79fsdNLR3hzcUM69AqqVGDB9thu86cFryshJyGLebr5mn3HJShJBmIRxGJN48SPshPT1d7rrrLrUQ0prYVFyhbjscdrvA8MHjtIs3oCkRRoVfk6qAd499MNA1d/12KSir2r2m7f+9wrmUVvvFabdJuddyoxaquZVFnWSnJKlQLSluh5RWB+TXrYUUYDSSLunJ4nY6xKfpavY6BDAUYBBCGsKs1fnqbzPEg0kupwzuQhEXIYQQQgghpGWgAIMQQgghhBBCyB4gtIZRb53mdokvWOOCgVgkkaSbIQkpEQYECHtgcLnYGwbTjPqn38sOjctTpNIXUOcVElvNuRvAZ6xJ97jEBQuQ3YIVsLGoov4HIybgftEzM0VW7ywVXQ/J4vwiOXlUP9YSIaReQCw3f+NOCei6aJouo3p1Vi5FhBBCCCGEENISUIBBCCGEENKCwLi+xrw+vjxI+2LNmjWyatUqKSws3GOAF0ybNi0h5SIdG4TbKDU0RwgMIDSogCDB2k6hycC/kIjNLipMR0PYi1mcEnw0BY3JJQiRBZwuopQB9ZTqMdu9waQNAhYSXxiSdbvKlAPGiu0lqv4hzCCEkL3xw7oC9bdDhR8JhWRc7y6sNEIIIYQQQkiLQQEGIYQQQkgLEmqCECTIg7QPdu7cKeedd558/vnn6nMk8YXNZqMAgySE3tlpsqO8WjRdr3V1SPU4JdXtlJCuic3uMDlKIB2cL/br06XWrSDsEBGmponvXqdEG7s/7U6kPoc3mj7XpQvnF/6+GNNY09VkVVcGYzqjoCJSuvCnV39aLUVVPslIssb2q3ECcbkcSnBh3QRhBmk8uVmp6u+fHtKlyh+UTUUV0rdTOquUEBIT/DbMWpWvfpMgwOiRkSKd06wxYgkhhBBCCCGk+aAAgxBCCCGEkARx5ZVXKvHFJZdcIkceeaR06tSJ14K0GsbkdZKl24qlyq9JelKNACMWSJfscsro3Lp2jAF0WzxxQFoBA7tkys+bdorDXhdeRAH9BYQolvPBoB/ok5PW0kVtV/TITBGn3SZ+uJBouqzYXkwBBiFkr6wrLJdNxRVKfAEXjDG9eG9FCCGEEEIIaVkowCCEEEIIaUH0JnDAiHd/0nr47LPP5OKLL5annnoq0UUhZA/6dEqXnlkpsnZnmXgDmiS5ojs6YDsGu3rnpKn92hNNIUQhDcdpt0u3jBTZWFSuQggszi+So/bpzaokhMQE7hdwMPJruhJxjeiZwxojhBBCCCGEtCh77z0ihBBCCCFNhh6qE2E0fuEFaS8Eg0EZN25cootBSETsNpsKJdI9I0WFgCj3BmrdHcLgM9ZjO9IhPfZrj0IUCEwgNIlFWIiC9O1NiJII8rJSVXvS9ZAsKyiJGKaJEELC+IKazF5XoFxzgrouQ7pmitvBcFCEEEIIIYSQloUOGAkm5KhZgC/TrIexB+o6l1J2mjuafJm2mJ8d/rq8bOY+Ugkmm9MG0syfjZNqnV7zvg6f+bM178pudcd1VktMQhb5j/FYxnMHnjJLR6/HHvWcrHXhqrSU2dJn6q6qy7u6kzlfvyUv63GNebnLzGXWPObj2IOWcvjM6YOeumPpLnNazW2LmZfTW1cQ3WVOG7TWlSX0qTfbGbVtWLFOuHZW1R3XnxFbz2VtK0anZpulH9UWMH92WNqD09IOG1JXyUV1ZQ7ZrXVl+W6kWLYb6sdTYi6Tu9J8guW55k4ezVLvropQ1DLueX3Nx/Jm15UjkGouo7Pa2g7N2/2G73v4b09tmara12AJIa2VkMTvgIE8SPtgwoQJsmLFikQXg5Co5KR45JwJg+T939ZLfkmVlFbX3KjZ1PzimpsWuD3A+QLiC6Rvr0KUV39aLQVlVUpgkeJ2iMNmNwlR4HyBbe1ViJJIAUYwpEtxlU+2l1er+iWktaOHQrJoa6F8uWKLLNpaJBXVXklLTpKRuTly5NA8GZnbiX8jmoGfNuyQ6t1COE0PyfjeXZvjMIQQQgghhBASEwowCCGEEEIISRD33XefHHPMMXL66afL/vvvz+tAWiUQVZw/cYhsLCyXX7cWqldvICBJLpdyeUCoDby2Z8EBhSiJoWdmqoSbFWazr9heQgEGafXkl1bKP79eJKt2lEiZN6AEa/hf5A3IxuIK+XbNNhncNUuuO3yU9MikoKgpmbk6X/SQrsKP4O92bhbrlxBCCCGEENLyUIBBCCGEENKChEI2tcSbB2kfPPXUU9KrVy+ZMmWKTJo0Sfr37y8Oi1W2zWaT559/PmFlJARAXNGvc4ZaQpomwapycaaki60DWbtTiNLyJLkc0iUtWfJLKtVs9sX5RXLIoJ4JKAkh9Rdf/P3j+bJmV5kkOx3SLS1ZHHaEHNPE6XSIpouUef3y86adcsvHP8k9x0+gCKOJ2FZaJcsLSmrdL0bldVL3UIQQQgghhBDS0lCAQQghhBDSgugIQRJnCJF49yeth5deeqn2/ezZs9VihQIMQloPFKIkJgwJQr8gpMOybcUJKAEh9QNtFM4XEF9kJbsl1V0TWzQUqgtX6XTYJSc1SSr9AZXuwa9/k3+ePLFdOwi1FLNW56vgWHC/AGPyOie6SIQQQgghhJAOSl3QWkIIIYQQQkiLouv6XhdN03hVCCEdltysVDU4reshJcQoqfIlukiERGTR1kIVdgTOF2HxRTSwPcnpUOmxH4kPOF58t2abeg1qIenfOV1S3JxzRgghhBBCCEkMFGAQQgghhLQgCB+ix7kwBAkhhJCO5IABc4CQiAT1kKzYXpLoIhESkS9XbJEyb0Ayktym9b6gLuW+gGq/RpAO6b9csZU1Gie/btklJdX+3eFHdBnXqwvrlBBCCCGEEJIw4pKDl5WVyXfffSeLFy+WHTt2KHvkrl27yr777isHHXSQpKenN11JCSGEEELaAaEmEFBQgNE+wT312rVr1fsBAwaoe2pCCOnopHlckpXskR3BajWwunRbkUzs1y3RxSJkD5bkF6sgcQgzEgaCgG0IoaOHpNQXlO4ZKZLsqumKcznsKv2S/CLWZpzMXJ2vQsD4g5qkelwyoEsG65QQQgghhBDStgQY06dPlyeffFI+//xzZYscCplV/BBi2O12Oeqoo+TPf/6zHH300U1V3nZHyGaTkL1mEEZzmwdj/Bl1n53V5jp2l5s/B1KiHyOQbBnkMe8qdr/5s8Nfl8DpMyeu7hTbNMVZXfdeSzJv82eay+Gssu5ddyx3hW7eN82+R72ZyhzDhdYeMH+2mbOWqi51eesuc772vbjb2oOGfDVzXelOW8xr5suyRa0fZ4X5OJ4yPeY5BJPrziGYZM435JCYdRU0/BWwtjOH15zWn27OW/PUzezRzJN8xGZpZ9a6NeZltzire0rMJ2gPWNt/3XZ/uj3qNYl0Hcp71p2w3XLNrN8NzWOLWu+65a+n9ftrLbNNi94erPs6vdZ9zZ/tgbr07orY7c6bFf07aw9ajmM5f0IIIS3Dt99+K5deeqmsXr3atH7w4MHyzDPPKGEzIYR09DAkuyq8aoB1cX5xootDSESqAkEVLsdIqdcv6DJD2w3pIttKq6RLepKk736WRnrsRxoPwhIt3LxLgsr9IiT79szZ4zoQQgghhBBCSKsVYPz4449y1VVXqde8vDw5//zzZfLkyTJo0CDp1KmTEmIUFhaqzuM5c+bIZ599Jscdd5xMmDBBHnnkEfVKCCGEENKRgfs0wojEmwdpHyxYsECJlsEf//jHWtcLuGG8/vrratsPP/wgY8eOTXBJCSEksWFIFucXSUALyabiCqnyByXFHZehJyFNTorLqYQWYfSQLuUQYOxW+isRhojsKPdKUAtJdopbrcN+pPF8v7ZA9Uf6NV3V57henVmdhBBCCCGEkIQS287AwqRJkyQrK0u++OIL2bhxozz77LOqo3jKlCkydOhQGTZsmBxwwAFKmPHcc8/Jpk2blAgjMzNT7dtQ4KQRbVmyZIkpbTAYlPvvv1+GDBkiHo9HevbsKZdddpkShEQC67Ed6ZAe+z3wwAMqn0gsWrRIjj/+eMnOzpbU1FSZOHGifPDBBw0+J0IIIYR0bMIhSOJdSPvgzjvvlLS0NHWv+fzzzyuxMxa8xzrcd951112JLiYhhCTcAQPGkRhkDeq6rNpRwitCWh0jemYrgQWcGECZN6DcL9Si+rhq2jBEAkVVPikoq1brR/TMSXTR2yyoz29WbZWgHlL1jr8VWSmeRBeLEEIIIYQQ0sFpkMz+u+++UwKL+gKhxJFHHqkWzNxrDAceeKBccskle6zv1auX6TNEH6+++qpy3Lj22mtl/fr18vDDD6vjzps3T3VehykvL1dWzitXrlQhUkaOHKnO7YYbbpDly5fLiy++aMr7t99+U+cNocbf/vY36dy5szrWySefrNJChEIIIYQQUh9CYovbAQN5tCRer1fd+yAMHe6L8vPz1f0Q3Bquu+46OfTQQyPuh/urO+64Q+bPn68+77fffkpwgPs7UsPs2bPl8ssvV45yVgYOHCh/+tOfVOg/QgjpyGQnu5VLgD+oK+eApduKZXQeZ7mT1sWRQ/Pk2zXbpMzrl+xUj3oN7RYJuOw2SfO4VUgSCDAg0cD7ZJdTDhrYPdFFb7Os3FGqhCwQX0CcNa43/y4QQgghhBBC2pgAoyHii6bat3///nLOOefETPPNN9+oQYETTjhBPvzww9r148aNk6lTp8pDDz0kt912W+36Bx98UJYtW6bWX3PNNWrdRRddpJw6Hn/8cSXmMMbavuKKK6SyslJmzpwp48ePV+suvPBC2X///eXqq6+WU045RTIyMhp1foQQQgghrZ0NGzbIxRdfrBzNpk2bpoSwmzdvlmeeeUYOO+ww5UJ2/fXXm/b5/PPPlTA2NzdXbr/9diVkhXsa0s+YMUOOOOKIhJ1Pa6Kqqkq6d48+8NKjRw+VhhBCOjKY3IEwJHAUwOD1kvyiRBeJkD0YmdtJBnfNkp837RS9wqfEQhBfQISR6nZIksshdrtHSqqxTVciDIQpeffX9TKoa5bk0LmhwcxalV8bfsTtdMiw7tlsmYQQQgghhJC2FYIk0qxGCBmisXPnTpUmXgKBgHKtiMYrr7yiXsNiijCnnnqq9O3bt3a7MX1KSooKQWIE7hbG/MIDDt9//70cfPDBteIL4HK55Morr5SSkhL56KOP4jxDQgghhHQUaq2o41xaki5dusiCBQtkzpw5SkxxwQUXqFesy8nJkVtvvVWKi4tr02uappwbILrAvSDcySBohTNZt27d1D2YrtfYc3d0cK+KkH3RgJAFaQghpKOTl52mwpBAgLF2V5kEdod5IKS1YLfZ5LrDR8nAzhlSDJGFrqv26rDZxON0qDQOu4jHgfc2cdpskuZ2yaodpXLrJ/NlS3FFok+hTVHlD8rcDdsloNe4XwzrniVOe1zdnIQQQgghhBDSJMT1ZHLIIYfI6NGj1ezHSHzxxRdRLanryzvvvCPJycnKYSIrK0u5YUAUYeTHH38Uu90uEydO3GN/zNRcu3atFBXVzJDZvn27bNy4UZUb+RpB5zZmGf7000+mvMHkyZP3yDu8zpieEEIIISQWOkKQNMHSknTq1EnGjh27x3rcN0Gk6vf7VWi3MBCv4n7ttNNOk969e9euh9sYXMfWrFmjxBxE5Mwzz5RPPvlEiVJwn2oUMkPsi21nnXUWq4oQ0uHJzUpVA9wY0PYFNVmzs7TD1wlpffTITJGLJg+VpN2CC02vccAo9QakqMonpdUB5dQwtHumDO2epdxdqv1BJb649dOfZek2urvUl7nrt6uwRBBjoZ7H9+7SjFeWEEJqxg4Yirz989///leGDh2qJuBiPIoQQghpDHFLwzHr8c9//rPccsst0tTAceLvf/+7vPXWW/Laa6/J2Wefrd4jtMiKFStq023ZskXFIccsSyt5eXm1aYyv4fWR0ofT7C29Ne9o7NixQ5YuXWpaMPBACCGEENLW2bp1q3qFs0UYCljrz4033qhEzRA09+zZU7p27aoWhCVBaDxsQxpCCOnodElLUgPXGLAO6iFZXlCS6CIREpH5m3ZKbmaKZKd4JMXtlB4ZyZLucUrXtCTZr08XOWe/gXLR5GEybf/BMrRbFswwpDqgya4Kr9zz+S8ye20Ba7YezFqdL5peI8DokpYs3TNSWG+EdGDuuOMOdY+ASZoIl2mlrKxMTcZEmr/85S/SUXnyySflpZdeSnQxWi0Yc4LIZsCAAfLcc8+pMKrNASakoM3CXZ0QQkj7xBlvBg888IB8++23cu+998qmTZvkxRdfFKcz7mwV8+fPN33G7D/EEj/mmGPkqquuqrVrRlzs7OzIcR6TkpJq0xhfI4k1wumNcbZjpbfmHevG5s4774y4zZvjEFt2zcwIf4Z5Nqu7tM5fPGSp0kCyOW0g1fy5qkfdZ0e1ed/knWbfcpvVudWQlTfTHjNtyDIBV3cb3jssGy126XoDmom1bkI1VVZLUmFd5o6A+UC6Ja03x3xOvpy69w6fOW1qvjkvzWXeHkwyHMdtzjdkkTfplea8nJZmYyynPRiKmVcwKXrdusvNF8mbZd45aOmTcHjr3nss+/rTzPvqbst1MFxDf7o5X7dlQlrKds302WdoW7qlXq1txW7eVfzpdfsGUs1ltFuuv8NnqUtb9HbkNNRFpLyM6Z2WfG2a9ZqZy+X0WttlXUGClu/zHt9JyxfN2B6qc2yxz8FSLs1wDXWbeV/r950Q0jyEQja1xJsHiCToRLgQDOC3BB9//LFyAoMLRr9+/ZpUwNpRwD3mV199pTrB3nvvPVm3bp1av//++8spp5wi06ZNE4eyKm88yBf37IsXLxa32y0HHnig/OMf/5ARI0bUa3/c6951113yxhtvyLZt25TzCe7LEXoGYf2iudg98cQT8ssvv4jP55Pc3Fw54IAD2NlHCGk0cL/IzUpR4Row233JtiI5ZXTdbw8hrQGIKH7csEOJhBB65MCB3eWoIbkSrCoXZ0q62Ay/6W6HQ04a1Ve+WblVft60S7yBoMAv45FZi2VXpVdO2LePGigkewLHkDU7y1T4Efw9GJ3XidVECKl9vnr99dfl+uuv3+OZiNSMU2AiK508IjNr1iwVLvWRRx6RgQMHNluTgQAD40W4DnTZIISQ9kncSgmILZ5//nnp1auX6phFpyxuaBAypDk4+uijVYf0119/LV6vV4kg0PGLjt1IIA0Idw6HX2OlN3Ykx0pvzTsacAiBBbcRDJicdNJJMfcjhBBCSPsD4gm9iQQYke4lbr/9djWTIhLR1kcCzgtYorFs2TIlDoAI9oUXXjBtawoBa0cCs7QuuOACtTQ1uE9H2BeILe6//351//rYY4+pUHqzZ8+WfffdN+b+mqYp8TME1+eee64cdNBB8ttvv8mDDz6oxDdffvmlKr+Ryy+/XJ566ik5/vjj5e6771YzzTALjWFnCCHxkpuZKmt3lqnB7RXbS1Q4EggzCGktfL58s2qXfk0T6Oon9atzCIsE2u/hQ3IlI9ktM1fliy+gSSgk8ur81UrM8ceJQ8RhZxu38s3qfCVWgfsF/gSMyqUAgxBSA55dIgkw4K597LHHyrvvvsuqqieVlZWSmpraIvWF51RMFrA+W7Y0cDIHbVUU0ZLXjBBCSGya7BcNHfqwZfruu+/U7LbmnNWIGZbBYFCKiopqZ1Lu2rUrokjCOgNzb7Musd44WzNW+r2FMwmDWajDhw83Lc2poCSEEEJIx+CDDz6QJUuWmBYIP6OBGRb1XTDzIxorV66Uww8/XM0MmT59uvTv39+0vSkErCR+iouL5ZprrlH3qhBbwGr32muvle+//15du7/+9a97zePll19W4osrrrhCXnnlFSXmgIADYo5vvvlGXn311T3i5WJWFUKqfPjhh2o/7IM2BbEGIYTEQ15WqnIEwAB3lT8om4oqWKGk1VAdCMo3q7ZKUIMwICQDO2dIVnJk91UjaNMT+nSVE/ftKx6XQ3xBTSp9AZm+bJM89PVvKl9SB0QXP6wtUPWMZVCXTElyxecWRghpP/zhD3+QX3/91RS+vKCgQD27YFsk8NyKiQzor8ckAkw0hYAj2gTOvVFeXq7cu/v27avyw9jAkUceKQsXLqxNg8kOEMkvWLBAieMhWseYx9NPPx1X+fB8NmHCBPW8jckSENB/8cUXahvKg9DoeL7Dbw+W8KQLODLiM7ahTwFlNo554BkPYxo4PkJnQnQfKXwGXBDRP4DzQTnw7Gmd3IG+BhwLDosIPw+3RJQXYWIw3oNnVkwUSEtLU5N8MSEXkwCMhPNAuHo8ayKP9PR0mTp1qpSWlqq6wTXAeSCf888/f6/XE/WDeg47iyJ/4ySWGTNmKDdJCBxwLAh6UJ9GFi1apFwtUAeYfILQophoUVhYWJsGeV533XXqPa55+Fps2LBBLXgfKUyMtTzhsDuYHIO2jeuNcTljWxg3bpy6Fjk5OXLmmWfuEZ5n9erVcuqpp6pyory45kiHOiSEEBIfTRMrZDcXXnih+gE+44wzZNKkScqauDlYtWqVuFwu6dSpRuGOH3PcVCHeOG4qjMydO1fF7MKPTDg+ee/evdWNWHV1tfoBCrNx40bl4AGlbBjkHc7HSnhdOA0hhBBCyN7ArEYs8RDeHx0w6ASp/35xHni38wXEFxBSYEA90n1QUwhYOwroNEG4DohnIl2vUaNGyemnn646phoKBBDoxIIIw+hOh3thdExBXIEOGHTgRQOiC/C3v/3NtB6dcghBgu1wQgkDxwuU+eKLL67tfEQHVaJnMhFC2gfdM1PEabeJH2H8NF2WFxRL306WWIiEJIhvV2+TKr+m3C80XZfJ/WO7X1gZ2j1LUj1Oef+39VLmDUjIH5R5G3ZIyYyFcsORoyUz2RDztQOzcPNOKfcGlBAjqOsyrnfnRBeJENKEwCnxT3/6k3qWweD0f/7zHxk/fny998fYAJ414XgBt27w5ptvqkF4DJhbgTD9hBNOkB9++EEuueQSGTZsmArd+O9//1uNQWDSQ0NB+fGMBwH8Pvvsowbfkf/y5ctl7NixJsE8xiHwvIdxFIgJLrvsMuUEEXZHbEj5IETA8yUEHTh35IPxEohPfve738nDDz+sBPKoi1tuuaV2rMT6nAfxwW233abcFADyRN5HHHGEKh8mZMDxEOHjIfTHOA3AOpwzRApXX321EhPAtRPCgEjP/3h2RBkhuIA4Au/R34Bzgps4rv/27duVuB9hT7ENY09G7r33XjW+c+ONNyrHcUwWQHnw/In6RdnnzZunBA3ID+cVDdQPnm/ff/99dS6op5EjR9ZONDjvvPPk97//vZqMgHaKNBA8IOwmxBsAfSQIKwrBB0QNEGg8++yz6hXlgGACoUZx7eDUguuIkDAA9b5z584GtzfU1aBBg1SY0XCfzz333KOe19G2MCEC+aJu8P1AeeHw4ff71fmg7tEuUN6tW7fKJ598osQ1mZmZDS4LIYSQZhJgACgSZ86cqW5oHnrooUbngxuTsMDCCH6YoBaFpXHY1hp2yPhxxPGMAgyEQsEPvdVuG+nxI4QfSXRIhwmXF9vD4Id5ypQpSlUJRSpUgwAOHI8++qj6IUJZCCGEEELqQ8gQQqSxxC+jaBwQCUB8gfsghIMzdh4ZMQpYwwPxYShgNYPOHXRkRQKdM9gGm9zGCDDQ2QbQAWcF6yDAQKdZNAEGOm+wHZ1cffr0MW1DJ9fo0aPV9jDoRMIMGsyGuu+++1RnEixcMZMGzwj/+te/ajumCCGkMTjtdumekSIbispFC4VkUX6RHD28NyuTJBy4sny2bLMSXkAY0DU9WXplpzU4H+xz9n6D5J1f1qkQJFWhoCwrKJa/fzJfbjxytORm0VZ85qptqr4DmiaZSW7pm0MRFiHtCQxuY7AbwPUAwnH079cXPENhBj/GEMICjP/9739q0DtSiEwINb766ivl/GB0D4A7BYQUCKMY6XkqFp9++ql6DjaOjVhDooD8/HyVJjw+cemll6rQ6zfddJMan4CQoL7lg/gA53vyyScr8YdRAB8elIcYAs+VGPA/55xzIpYdk1jxrO9w1DgLYeAeIgcIOOAAEc536NChSmwBlwWIDTCYjwH//fbbTwk+ELYeQMAAR4hIAgxM6vj5559NE2ThfIHnSmP5URc4HsJr4hhG0DeBugmLQFBeOGscddRRyq0zLCpB/SB0aiwBBuoHk3bxjI52FxZGVFRUyJVXXqmEDBBThIEgY8iQIUr4EF6PY1knL0ycOFEJbCCigTgFdYK+FLRRHNP4jNwYAQYmQKCdGCcZw8nj//7v/+Tmm2+uXY/vwJgxY5SbCdZD0LJ+/Xp5++231fmGiVVHhBBCWkiAgR8ZuEtYgUgBij7c7ECl2BjwAwEF5WGHHaZm6eFHHJ/RAd2jRw+lSAyDjmn8iOFHC2KIE088Uf14oNMXKlPrjx5ueHAjglfcwOFHCj/UuLnDDzoUlUYgtICwA4pAqDfx44u0EILgh59qQEIIIYTUF4gv4hZgxLl/Y4CVJsQXAB0quH+KBu6bMGAftgMND/DDjQEzmGDH2dBOrPYK7lljhY1Bhw46ihpDLLeRvYXlA7B/xcwedO5FAnlAUIPrCocNzOgCuO7oTMOsqsGDBytx9uOPP64EIejQwsyeaECwYe10QmcZCAQCakkUmhYUCekS0jUJaR3b0UPVgV5TFx0Z1kNi6iI3M1k2FZWLrodk2bYi1VeAwZbWAgYCNE1Trx2djlQXCzbvkoKySvEHNeXOsn+fzhLStEZ9P3KSXPKHsf3lvUUbZWtJpVT7Q7KxqFxu/WS+XHPoCBnSNbPDtonCSq/8tmWXBFDPui779szC9PCEiZPjAu1B10ULBhN2f5PI+ypCooEJkEYwmIzQ4+HB8PqAcAz//Oc/lVgc7gt4xSB5JDD4DFcJDPDjOGEwJgHwLNPQZ1e4C+DZBwILq2ODEYgUILoIAwcIfIbLBOoBA/f1LR9cI+CWgcFzq/tgQ+6TIBwJiy8AxB+410I4D2O+SIdBfIhNIMCAkAITaiHWCIsvwNlnn63GU6KNLRnFF8AoksHvBZwY4ESB52JjCJcwcGMMiy8ABCwYIwo7iBjXY4wHvz/G8tUHuFqgHBh/Ml4D1BPyxTUIYzwfPBNDvIHrCFB+CDCaGghxjGBSMtoC3C+M5YXDBZwyUF5cu/CY1ueff66cWBgmlhBCWpEA48UXX4y6Dco9iDAay6GHHqrCikChih8KKDWRJ36wb7jhBhW/ywhm8EEhiTJh1h3UmmGnC/xIG0EHMeKPQfGJmxjYWGGQADcIsLyyAkUixB/oRH7wwQfVTQeOBTEIlIOEEEIIIe2ZTZs2qQ4edKjA2hOWp1iMIKZt2L4UHRGYVQGrVHQwYLYIOpNwz4X4u+ikYUiKGtAxAgFDNLCtsZ3jEE+ASDO94EphTNPQ/a154P4a4UYABBToxMEsKYBZWOjcgcAaAulonZ8A7QainUggDq0xdm5LU1VWJo6gT/SqCgk2sNOuvYFBRM1Xrfx4bPa6DtqOBushMXXRw2MTWyikBrSLK6plxaZ86ZpW8/eoNYCOffw9RB9GQzv42xsdqS4++GWNBAJB8QeCkuayy5AMpwSryhv9/UCLnjq0i3y6Spe1RVXi82myIxiUu2f8LNPG9JFxudnSEdvE9JUFEggGxBeoES+MzPbU1nObw+sTW8ArZSXFYg94E1IE3FsR0tpAuBE8L4bBeEBDxBcAs/whWIArAMQQGHgOCxaswMEPQvJoInEIxCMBcYBVOI7xCDz3PvDAA0pcgIkImKiKwW0IBTARwQjEGQjXaAQCdoBJoxi4r2/51q5dq56xMRk1HuAGbhXAAAggjOA8cT7h7eFXhEk1gr/10VwQrccKPx8/8sgj6rkQkxVQz2EiuaVj4q6RsKjA6vKI9cgbf/ci5RMLXAMQrQ0Zw31iEgOeZ+HCYW07zfU311qPKC9+ZyG2iERYsIL94L4Cp0qMwaHvBn04cEfhhGNCCImfVvsEjD/2WOoLfjhgz4WlPuCmBYMAWOoDZnki/lVT4/SGxFVVo9X3ZZvVqL6cus/O3WnCpOzQTZ9dVeZ9q8SgdLWIXL2dzSs0SxjRkL1uu9syHpCWb56x4awyl8OXVdeZoHUyH8eOQL1GLOWq6m44bqlZqesuN5+/w2f+7E+v2zeQajmuZczCWW2ZG1Fclz5k6QsJmkW4Mc/BWibd8u3ydjKfkzU9OhFrj2OZDKK5zee057Hqtmsec9qkUvM1KuvjiHqOtlDsMmZsMl//QEpdek+JuczeHHNeZf0slWsolk2P7a1vrbs90pv2tdSV11JXdaJoCWSY0wZ95qys18GYlz/NvK9Ns0U9DvBa2qXDcCzNE/scrHlpyTHapKXyXDXhGmvxZRlSWi6J9btCCGke9JBNLfHm0ZIghml44BuhJSKBWRTG+LHoZMJMEdighi0sYUeKGTRWt7GODDoGYeV63XXXRdyObdE6TvZGeAYLYrpawWwcY5qG7h8pj/BsH3QkhsUXYTADCQIMuKfEAm4giGFrdcCANSs6gRraWdaUFGk20baXiD0lTZxOy49zB6NmFrdNnClpHV6AwXpo+TbRy50i9lU7BY9Pus0uOwJ2GZbAvw2RBpgx0xSDMO1ddLA3OkpdbCgslw2lXtUeg2KTib27ijs1I+7vB2rs1LEZ8tXKfPlla6H49JBIICQv/bpZgk6PHD0sr1W5vzR3m0DYkYXb14jYHaKJLr07ZUh2To60WUIOCekhycjKlk4ZiQktwwE20hqBYzXu/z/66CM1wA8HxcYAFwyEH09PT5czzjgj6gQADMpjoiUGoSMRLVzj5s2b9xj4xjPxIYccopwHMJiNUBZffPGFmtCJ0CpwJkBoxobQ2PI1FqsjRXMS6VgQ6yPMCJ4f7777bvV7gWsHBw7UhRWjW0d91ofDsTSE8HHhiA4xjxXj7xmuPcLC4PkeITsxMRj7IyRKpPJbifa7bhSi7K0ecRzkg76ESPVgnKyMEDgIEfPhhx+qtorJM5ikjInVkZw0CSGE1J8GPwFfcsklDUqPP/b1FTkQQgghhLR7Qnjojz+PlgSdSI3pqICjGRYSHViyIlweZp7AuS3ceVJdXa06nhAmD511jcEYZgS2tfUNTxIGnV0QV0QLU4L1mO0TnvET7vxDuEAr4XWYERQLuNxZne6MgmujvWxL43A4RWx2NXhmi9Kh15Gw2VkXrIfEtIkkh0O6pCdLfkmlaKGQLN9eJkcMM89+TDTo7EZnfCL/ZrUWOkJdfLFqmxJY+DVd7Da7TOjbfY/vQWO/H0j9u316SWaKR75ds028QU3dBr7681oprg7ItP0Hi72NiTAa2yYW5xdJYaVPgnpIND0kY3t3btu/xxDj2O3iSOD3oz1/L0nbBc8fr776atz5QICBiQDbtm1TA+fRQHj13377TYXbbIioDQPxmHBgxBimE88/EJdjgRMCHLbxvGcUYCBESWVlpckFY9WqVeo17BpR3/IhHQbely1bpgb+o9FQ4R5cw8HKlStNDh5wCIdDBULDG9NBPGPsA4DwDm4eI0eOrNfxEDYe+yPsuxGEAGmoE0pTgboFeE4Nn28kiouL5euvv1YOGOFJKEYHjfpcB4TMCZ+vkbDDSH3Li/4bCITCjiqxgMAHC9ziIR6ZMmWKPP3002oCBSGEkMbT4ODFUJ1aF/wgRlofXgghhBBCCCF7csUVVygr04cfflg5iMByFwveY5YT3EIw26cxTJgwQb3OnTt3j23hdXAliQY6hVAWdAxaO3wgEPn1119N+6PTJppgAzPEgNElhRBCGkteVqrY7XCUCsnSgmJWJEkYRVU+mbOuQAK6LkFdl+E9syXJ1bSiAPweT+zXTY4b0Ufl7QtqUukLyCdLNsq/v1mkPncEZq7aqgaUApouSS6nDOnaNsOwEEJaBgxC4xkLs/nDz0WRgGPB1q1b5bnnnttjG555IJCIFo4Rg/HGBYPncCqwhprAwD1cAq3OghAnGCeuQtSAz3DuRuiShpQPjoFwioADpdVpwTiZAmIP6+B+LHBeCDfy6KOPmvLBeBDO89hjj1Wf8dwIt0KUE+cVBqEtIExoiEjPOvkDIeRRB4ni97//vZp0AHeOSOFBw6Fowm4T1vKjHVoJi26s1wLHgdDku+++M61HSJb6csopp6iyQAhiLQs+h91NEe7UeK3Cz/RoR9FcMAkhhDSjAwaUjUYwiw03BPgxnTx5ckOzI4QQQgjpUIRCNrXEm0dHBB0ES5cuVTOIMBiBjizEuDXGXG1rYAboZ599pjplcD+N+L4AM1UQe/Wvf/1ro23b0QmH/dEJBhFHuJ42bdqkOrHgbBJ2raiqqlLrYUVtdLA499xzVecPrEnR6RYGdr7o8MP2MHDvQAfhSy+9pGYuTZ06tXbbE088oV6PO+64Rp0LIYRYBRgLN++SoKbL9rIqKa7ySXaKNa4fIc3Pl8u3KCGQP6iLrodkSr/mExoO75EtaR6nvP/bBiXAqPQHZfa67VJc5ZfrjxglGcmW+LLtiApfQH7etLNG6KLpMqZXZ3EYwucSQkgk8Cy0N/A889Zbb8mf/vQnFUIEs/8holixYoVa//nnnytxQX0pLy9XLoN4FoIjBsI9IAzn/Pnz1TOVEYgy4HYIhwg8/7355ptK5P7ss8/WOtTUt3wDBw6UW265RYXtQPgTDMJ7PB51XBwHQhSAcRw8y8HdAPvgmRoTAqIBMQhCvmMwH2E0EDIebhgQBECMj2dWAJHGHXfcUTvBAM+FOC88G0IMU1/nDTwvQkRy/vnnq7GmxYsXq+dko/tGS4PnaNQZrgWcTM4880xVL3h+/vTTT9U1efzxx1W6gw46SB544AEl1MjNzVVhPazjaSAssME1Q3643scff7wSZlx00UUq9CtecW3xPB52RqkPqG9cX1w3XAP0CyAUD8qBsDhwuL/22mtVeNC//OUvKgQo2h/EGHCLgXjj1FNPbdI6JISQjkiDe3PDdlLWmFGYzWbdRgghhBBCzFCA0TAwWwaza8KdUdbZPJidMWbMGBXXF500CJvR1oDAAh0gWJoSzMBCvGF01qFT6NJLL1UzWR577DHVAWacifPTTz8pq9fzzjtPdZKFQZ2+8sorah/McEKHEixw0eEGAUe4wy0MZgWhgxGhVWBfio6cWbNmqesHK1x0yBFCSFMIMNCPjzl9CEewYnuJTGrGgW9CIgHniS9XblFtEK4MfTulS05qUrNWVp+cdDlnv0Hy9i/rpKjSK1WhoCzdViS3fjpfbjxyjPTITGmXF+uHtQUS0GrqGaGHxvdOjA09IaT9gefJDz74QP7973+r5x4MUMPVDwP+EHDUJ4SDEeyLsCMYeH/vvffU8yuEDnh+uuyyy/Z4Xnv55ZfVMxJE8xhfwUD+xRdf3KjyQbiAsBN4dsPAPtIh9IdRNI/QGHA3hEgAYhE4LsYSYAAIKyA4QNmuvvpq9cyNQXw8+xlDGWEwHw4LEJrg2RYClI8++kiuvPJK5RhSH26++Wbl6vHaa6+pZ0gIHiByuPHGGyWRIKQNhCwQRuAZG8/VEFhA7IJn5jAoN64nJiCgLn73u9/JjBkz1L5GIF6BWAahPjAhA+0EAgkIMHCN4KqBSQ0Q2SBsDfKIFqozEqgvtA20G4hnACZfoDwQ0QBcH7h7fPzxx8phBO0F63CsiRMnNlndEUJIR8UWakxAbwOwLMIPMDpa9/ZjTerA7M0RI0bIvsdcKymZ3dW6itzoEWGcVebLlLLDPPiguc0q0qquhrwsAtOQxQ1Ts0ySCBl2dZeZt6Xlm60tnVXmcviy6jL3djKfj2514bSUSzPch7lLzefrrDandfjM2/3ptojlB/ZA7OMGUwz7OmLXu91v3m5Kb8lXt8ibdJct5jkYy+2wuHzZzNW8x766sy5vu2be5vCbP5f1sZykYXNSUSjmcVzV5oIEUuxR692bY496fWsKHf38rPWuW9q3Nb0Jy180h9eSlyHEaSDDnK/dUu/2YPS8rG3FZnF9DaSZ89Yt3zPjNdYsk/WcFndDY5lV+uTobdJady5LXpU9o7f3pF3mfRfc8ZQ5ASHthKUrfTLykM2yZMkSGT58eIv/9vf99+Xi6V3/B+dI+DbtkA1XP9Hi59CSVFRUqA4JdB55vV7VaYUZMIMGDVLWpmHrTMRTRTgNxJpFpw46dxC7NCwSJjVxdNFJhNlDmJmETiLEHzbG4YVIIpIAI3wt0JmHDjDEUIZDBmbpoGPIGK84DDpvsA0dZXDLQ2cTZtDcfvvtjXIrCX93Et3eVxYUys8r16tnH3cHj5ke0jQJVpWLMyVdbLutdjsirIfE1sV/5qyQHeXV4rTb5ORR/eTiKcOkNYAZj/h9wm+VcVCiI9Le6+KrlVvl+TkrpMpf40YBYQREGC3x/Sj3+uXdX9dLfmmVEiMlOR3SNT1ZrjtilAzumiXtqU3gnu+mj36SdbvKpNwXkE6pSXLR5KHS1imuqBK9qkIOGDFQumUm5r61tdxjEdIRgZh9165d6vvXnoGwAM9PcOSIFEaFEEIIaa80zs+YEEIIIYQ0Ckid4lK/NsH+bQEILtBZc8011yhRAIQXsYAlJ2YPoVMHAoKCggJpK2zZskWJE2Afi/AqmAEDYTPeY+YKZkphhkxjgf2tMRxItA7AaLpsiFkwQwpLfcBMILiWEEJIc7tg7KrwqvAPS7fVP7Y4IU0B2t2MpZtE03Xxa7p0SUuSPjktN4ienuSWs8YPlI8WbZA1O8ukOqDJ9vJquWvGQrnykBEyoU98Yt/WxPrCctlYVKHcL+A2MjavU6KLRAghJAKYOIGwJ8ZwI3DtgCgfz5uEEEJIR4ICjATjy7CLbbdTgHU2utlBwTybvrqz2V3AXW7uME8qrvsctDgPBJMtVg2WmfmuKsOmslB0Zw3lRBDdtcNvmfgRsrQ2T6Flu+H8Q5a4cLrDMiBgdUQwuA9YnRg0jyWtZXDBHqj7rFmOa93XWpdGVwOra4XVecFl+WwtZ9DgmGDdZr2+3mx71LqzaRZXh6B5X6u7iNE9JWBwA1FlMjgtAF+mI2r9WF0p9nAAsbRvh+Ga7bGv5fpanTiMx7W6QzgrLS4eFgcUV3Xddn9mbJcKq2uH0RHDeo2sjhfW9m6zuGkYXS+s5++uiO1i4s0yXDOD+4vK1/L9dldYrPoDhmtmabMui3sGIaR5CIlNhSGJN4/2DuxLr7rqqno7WcBeE64OECw88sgj0laA/ev+++8vVVVVyuYTDhNhYDGKmL1wrYhHgEEIIe2R3KxUWZRfpMISbCqukEpfQFI97c9lgbROFm0tVO4TEF8EtZDs37drvePbNxUep0NOGd1fvlyxRX7dUijV/qAShjz09SL548QhcvQ+vaQ9MHN1voQkpOoajjcjera9cHOEENIRmDdvngpRctpppymno4ULFyphPpx2sI4QQgjpSFCAQQghhBBCWh0II9IY0tPTG71vIgiXFdaziLlqjet6zDHHyCeffJKg0hFCSOt2wLDbasITBHVdVu0slTF5nRNdLNJBmL50sxI7QBSQ7HbIvgkSBTjsNvn9sDzJSHLJ92sLxBfQBHNOXpi7QnZWVKuwKPYWFoY0Jf6gJnPWFUhQuV/oMqxblridHTf0FSGEtGb69u0rvXr1kkcffVS5XuTk5Mi0adPkvvvuU5MKCCGEkI5EgwUYc+bMMd1FhL8AAQAASURBVH0uLS2tjRuIuNuRQLxuQgghhBDCGCTEzJdffqlCjPTu3VvFRLfSp08f2bp1K6uNEEIsZCW7JdXtEn+wxoEAYUgowCAtwebiClms3FfQ9nSZ0LubOOzR3UGbGzhvTO7fXYUl+WzZZvEFa0QYCE9SWOmVvxw0QlyOxJUvHn7csEOq/Jqqa10PybjeXRJdJEIIaRJmzZrVLgUYH330UaKLQQghhLRNAcYBBxwQ0VYRFtHR0DRDrAFCCCGEkA4MOsTjDkHCiEGyZs0a+eabb6SsrEzGjRsnhx56qLRFiouLJTc3N+p2HbHl/f4WLRMhhLQF0C+BMCSl1X7lRLAkvyjRRSIdhOlLN+0OiaEpF5YJfVuHKAAuHOkel3ywaIMKyVPpD8n3awqkpMov1x4+StKTXG0y/EjYaSQ7xaOcbwghhBBCCCGk3QkwbrvtthaPa0kIIYQQ0m5QAoz48+gIwFb+uuuukxdeeEFZll555ZVy8803yyOPPKLWQ+SLNLg3Pe644+S9994Th6Nt2VL37NlTVq1aFXX7/PnzpV+/fi1aJkIIaStgMHZFQbEE9ZCs3VWmZsm31Zn+pG0Awc/sdQWqrWHZp3u2pLhbj7Chb6d0+cP4gfLur+ukqNInVaGgLNpaKLd9Ol9u/N0Y6ZaeLG2F7WVVsrygRNWzpodkVG4n9kcSQgghhBBC2qcA44477miekhBCCCGEEGLgxRdflH/961/icrmU2OLWW2+VjIwMueaaa+Twww+XY445RgKBgBJefPLJJ/LYY4/FdGVrjUA48vzzz8vll18uaWlpe9jSvv7660psQgghJLIAw26ziR7SxR/UZM3OUhnWPZtVRZqNr1ZuUYIAhL6BKGBK/26trra7pifL2fsNknd+WS8FZVVSFQjK+sJy+fvH8+WGI0fJwC6Z0haYtXpbrdMIGNOrc6KLRAghhBBCCCH1glNDCCGEEEJaEIQfaYqlIwDni8GDB0tBQYGUlJTItGnT5IYbbpBjjz1WvvjiCyW2gDhhzpw5Mn78eHn11VelrQFRSUpKigqjcvXVV6uZnc8995ycdNJJcuSRR0qvXr3k+uuvT3QxCSGkVdI5LUncTof62wkXDMyWJ6S5gPDii+VbVFvD+z45adI5rXU6SmQkuZUTxoDOGcp5rcoflO3lVXLn9AWyYNNOae1A3PLtmnz1GtRC0q9TuqS4GzyHjBBCCCGEEEISQoOeXiorKyU1tXHxFuPZtz3jqgqJ2x32ETcPpoSc0a3GHb7Y+YYM0hpntXmb7jZ/dpebP9v9dQfzZZnLFEyxpNUseZWEoubrz5CYeekG106bJd9AurkcDksodN0Z/XyDlv4Qmxa9noNJlrSWek/eYV7hd9Xl5csxp3VW2aLWTaS8jfVhvUYhhy3q+QLNU/feYzmO7rTsa3FHdVWEoh8XAW1jXMNY52Nts9brEkg37Bu05KWbPweTzeVwVkU+9917mz4llZgz81vaUn2/R6rMaXX7eopCMes1pMX+rhivYcjill/V3XK+lbao5bL+LXBWh2JeQ7uhrjVLeyeEtBAQT8QroOggAow1a9bIX//6V8nOrpnNjPcvv/yynH766aZ0GHg77bTT5M4775S2RteuXWXu3LlyxRVXyGuvvaZCqrz55ptit9uVw8fTTz8tmZltY6YqIYS0NHC/yM1KkVU7StVA7aL8QjllNMM2keYBoUfKvAHltqLpukzq1/rcL4wkuRwydUw/+Xz5FhWGpNqviR7yyYNf/SYXTh4qRw7Nk9bKb1sLpbjKvzv8iC7je3dJdJEIIYQQQgghpHkcMPr3769ibldXW0ZS9yK8eOihh9S+hBBCCCGE1JedO3dKXl7d4EDPnj3Va48ePfZI2717d6mqMij02hA4x/fff1+Kiorkp59+knnz5smOHTvko48+qj1nQgghkcnNShWHCkMSkpXbS9UrIU0NBJIzlm4WDeFuNF2yUzzKXaK147Db5eh9esmUAd3F6bCJL6BJuS8gz85eLv+bv7rVfl9mrc5XZUOolxSPUwZ0af11TQghhBBCCCGNcsBAbOpbbrlFbrvtNjXzELPyJk6cuEcn+NatW5UVNGJxIyY3HlRhF00IIYQQ0tFBN3e8fd2ts6u86cE9pMNRZxMUfg/HCyuR1rU1MjIyVCgVQggh9ScvK039BughXaoDQdlYVC79OnGwljQtS7YVy6biCgkEdRWCZELfrm3m3gPlPHBADxWWBCFU4OCBe8n3f1svhZVeuezA4eJytJ4IxaXVfhUmJbjb/WJsjy7K7YYQQgghhBBC2goNesKC8GLlypVy3nnnydtvvy1Tp05VM/YQWqR3794qRnX4/RlnnCEffvihXHDBBWofxLcmhBBCCOnwhJpo6SC0V7FFmBUrVqh7ZiM//PCDHHbYYTJq1Ch5+OGHE1Y2QghpC3TPSBan3a4CEWLAdnlBSaKLRNohM5ZuqnFk0HTxOO0yOq+TtDVG5XaSU0f3kxS3SwJBTSr9QZm1epvc+8UvUuELSGvhuzXbautaC4VkbO/OiS4SIYQQQgghhDSfAwbIzc2VRx99VO69916ZMWOGzJo1S5YuXaososHAgQNlxIgRcsghh8hRRx2lBBmEEEIIIYQ0Btxzvvjii+p9IBBQ4ovrrrtOcnJyTOkKCgraZAXDXa64uFhOPPFE9RmhR44++mjx+/3qPvpvf/ubEjmfeuqpiS4qIYS0SiC+6JGZLOsLg2qwdvHWIjlmeO9EF4u0I/JLK+WXLYUS0HS17N+3q2p3bZH+nTPkrPED5N1f10tJlU+qQkH5ZfMuuf3Tn+XG342WLmnJCXc/m7k6X7mMQFCVl5UqOSlJCS0TIYQQQgghhDS7ACMMOoThgIGFEEIIIYTUj1DIppZ4iHf/tsSSJUvUYmThwoUR07ZFZ4yff/5ZLr744trPr732mlRXV8uvv/4qQ4YMkYMOOkgef/xxCjAIISQGuVmpsrGoQnQ9JMu3F6tB3Lb4m0BaJzOWbZaQwJFBU5/379tF2jLdM1LknP0GyTu/rJOC8mqpCgRl7a4y+fvH85UII5EhfFbtKJVtpVVKfBFE+JFedL8ghBBCCCGEtD3apmSfEEIIIaStwhAk9UbX9QYt2u6BkbYEXOTgMBfmm2++kUmTJilHOZfLJWeddZYsX748oWUkhJDWTl5mqthtNhW2oKTaLwVl1YkuEmknIDQHQmIoQYCmy9BuWZLmcUtbJzPZLWfvN1D6d0qXUEikyh+UbWVVcvunC+TXLbsSVi64X4R2hx9xOx2yT/fshJWFEEIIIYQQQlrcAYM0DakFfkkt96n3lT3ND/FVXer0MSHLlQqkmmfzaB7zduPE2JDTnNZVYQ4c76oyfw4k16X3Z5nzddQUtRabbv7sy6nb11Vm3ua09oFZ9vUUh6JKg6z72oLmz9b6MeVrKXMwyVwfui3GcSzjOJrHMovK8NFTaN7k8JnrNZhsOa7lmnlK6tLbLeFXdZclb6/5sz1Yl3fIYTmOQ6KW2XpOKbvMF8Vruf5Or3lnYzl1yzVItuQVtNSduyx63QTSzXmFLO3Bn2ksv7meQ3ZzXhU97VH39RRHGBSN0b4DhohKusvyvbK2d785M83S7pIK67b7M83bghbXV68lvLCx3p3e2O3bWWU+CWP7sPslZt0RQpoHOmAQI8nJyVJRUbG7bYRk9uzZcumll9ZuT0lJkdLSUlYaIYTEoGdWjQADYNb8iu0l0iMzhXVG4ubrlVvFH9SVIABhMSb379ZuajXJ5ZTTxvaXGUs3y5JtRVId0CQU8sl9X/wqF08ZJocPqROItgTVgaDMW79dAnqN+8WIHjnidHDeGCGEEEIIIaTtwScZQgghhBBCEgTCjLzzzjvKweODDz6QkpISOfzww2u3b9q0STp1sijxCCGEmPA4HdIlLUmJMDQ9JIvzLep4QhoBRABfLN+iXgNBXfKyUlX4jvaE026XY0f0lsn9uovDZhNvICgV/oA888MyeWvhWiUObSnmrt8uvqAuAU1X3+P9+rTtUC+EEEIIIYSQjgsdMAghhBBCEhGCJN482jkXXHBBg/ex2Wzy/PPPS1vi8ssvl3PPPVdycnKkqqpKBg0aJIccckjt9u+++05GjhyZ0DISQkhbAIPjCKGAMCRLt1mt7ghpOD+u3yFFVT4lCIAIY1K/9uN+YQTCpYMH9ZCMJJd8uXKreJUThshbC9fJzgqvXDJlmLhawIli5qp80UI1AgwIqtqb2IUQQgghhBDScaAAgxBCCCGkRYFFerwhf9p/yKCXXnoposACWGdjYj3WtUUBxtlnn61e33vvPcnKypJbbrlFHI6a+GG7du2S8vJymTZtWoJLSQghrZ/crFRZsHmXBDVddpRXq4HznBRL3EdC6gnuK6Yv2yR6SBd/UJPMZLcM6mqIZ9kOGdOrs6QnueSjxRulyh9UdfDNyq1SXOWTaw4bKSnu5utC3FJcIWt2ltW6X4zO69xsxyKEEEIIIYSQ5oYhSAghhBBCSKsDITmMy86dO2Xs2LFy9NFHyw8//CDFxcVq+f777+Woo46S8ePHqzRtEYgw3n33XSUe6d+/f+36zp07y4IFCxrlBkIIIR2NvOxUgU4PEr2gHpIVBXTBII1n5Y5SWberXPxBuF8gHEZX5RTR3hnYJVPOGjdQspI9SgwBIcaCzTvl9k9/lsJKb7Mdd+bqfAlJSB0T1Twql+HXCCGEEEIIIR1UgKFpWtOVhBBCCCGko4UhaezSAbnhhhskPT1dPv74Y5k8ebJkZmaqZcqUKfLJJ59IamqqXH/99YkuJiGEkASR6nZJdrJHDZJrus4wJCQuZizdpBwg/Jquwm+M6dVxBAE9MlPknP0GSreMZAmGQlLtD8rqnaVy6yfzZUNheZMfD6KL79cWSFALqQUikCRXjRsYIYQQQgghhHQ4AUbv3r3l1ltvlY0bNzZdiQghhBBC2jPxii86qAjjo48+klNOOaU2DIkRrMM2iDNaOw888IB4vQ2fQVpdXS33339/s5SJEELaUxgSCDD0UEiWbKMDBmkcCGEzf9NOJb5ASBu4Mbh3hwfrKGSleOQP4wdJ35w00UOinDC2lFTKHdN/lkVbC5v0WAs375Jyb2B3+BFdxvdm+BFCCCGEEEJI2yauAI6dOnWSe+65R+6991458sgj5ZJLLpETTjihNm412TvebKfYM10177PMehhXZd3oSiDdPNhQ3dWcj6vCvN1Zafigm9MGk82fq7qZjxtIM4zq2M0jPJ4i83FsFhMUV5nhfZV5X91vThtIM+elu+veu8vN+9qD5n39lvowftZrqrMWh8/8WSzjNiHD6WuGMqhzMNYjtieZP+uGpu60DIZZ62aPfS3fPi0nup2ptRwOr/lgLkN9BVMsdZMdu1zG+qlwm9uC3XLNXBXm4/qybFHrubpTbH2XPVD3PpgSu66cFebPxvQOr/l83ZYJOSFH9ONa21UwaS/XzFN3/prle6R5zOVIKrTFvGbGcwhZL72lLTmrLNtt0duszXK+Nj36NbS2QXeFJTEhhLQiKioqVMiRaGBbeXnTz8psah588EF55JFH5M9//rNMmzZNevXqFTP9unXr5JVXXpFnnnlGuc/BCYQQQkh0Acai/CIJaCHZXFwhlb6ApHosD4iE7IXPlm9WIh6/pqlHs4l9LR0wHYQUt1POGDtAPl26SZYVFEt1QJPCSp/c+8WvcukBw+SQQT2b5DgzV+Wr+g5omqQnuaVPTnqT5EsIIYQQQgghbVKAsWjRIvnxxx/lueeekzfffFO++OIL6datm4pTfdFFF0nfvn2brqSEEEIIIe0B5WARZwzxDuiAMXLkSHn66aflwgsvlJ49zR3+W7duVdtGjRolrZ3Vq1fL7bffLnfddZd6HT58uEycOFEGDhyoxM2wOy8sLFTp5syZIytWrBCn0ymXXXaZ3HHHHYkuPiGEtGrylAOGqL+lQV2XlTtKZWwvzqYn9QdODxAEwPkC4TAGdcmUjGSL6r0D4XTY5fh9+0hGklt+3LBDvIGghCQkT363VHZVeOXU0f0iupPVl8JKryzKL1TuF0E9JCN75igXG0IIIYQQQgjpsAIMsP/++6vl4Ycfltdee02JMf7xj3/IfffdJ4cffrhceumlcuKJJ9IVgxBCCCEE2olQzRIP8e7fFrn77rvlmGOOkWHDhsl5552nXsGyZcuUQ0RVVZW8/PLL0trJyspSDhg333yzPPvss/LWW2+p++dIQJxx5513ysUXX6xEzoQQQvbyNzbZLalul/iDNYPnS7cVU4BBGsSs1fniDWg14Ud0XSb375juF0YgiDh0cE/JSHLJ1yu3ii+gqXvRNxaslV2VXrlo8lBx2hsX4fjbNduUYAruF7i9pWCKEEIIIYQQ0h6IW4ARJi0tTYUgwfLbb78pAQZcMb766ivVYYzZildccYV07cqHV0IIIYR0dAeMJsijg4Fwdx988IH85S9/kccff9y0rU+fPvLqq6+qNG0F3B/feuutatm1a5csXbpUdu7cqbZ16dJFiS86d+asbUIIaQiYiY8wJKXVfhXSYMm2IlYgqTeaHpIZyzYr4QUcGXpkpEhuVhprcDfjendRIUI+XrxRquGEEQrJlyu2SFGlT646dF8VsqQh4Ds6C24jOgQYIemdndah3UYIIYQQQggh7YcmE2CEmTVrlprFhw5yMGbMGHG5XHLPPffIY489Jm+//Xab6hwnhBBCCCGtg2OPPVa5YCxYsEDWrl2r1g0YMEDGjh0r9kbOvGwNQGhx8MEHJ7oYhBDSbsKQrCgoVoO663aViT+oidvpSHSxSBvg5007VFgNFQ5D02ViP04gsjK4a6acOW6AvPfbeimr9kvIH5T5m3bInTMWyA1HjpacFE+963vZtmLZubu+NV2Xcb06NfEVJYQQQgghhJDE0CQ91Tt27JAHHnhABg8erMKOfPjhh/KHP/xBfvzxR/n5559l7ty5Mm/ePOnRo4dcc801TXFIQgghhJC2ScjWNEsHnt08fvx4OeOMM9SC921ZfEEIIaTpBRgImYDZ9RBfrN1Vxiom9eLTpZtr201akkuGdc9mzUUALjNn7zdIuqYnK6FKtV+TldtL5NaP58vm4ooGhXupCT+iS5LLKUO6ZbG+CSGEEEIIIe2CuHqrP/vsM5k6dar06tVLbrzxRvF4PCqmdX5+vjz//POy33771aadMGGCXHvttbJy5cqmKDchhBBCSJsE0glbKM4l0SdBCCGEtFI6pyUpxwsI9uCCgVn2hOyNNTtLZfWOUvFrmmo343t1UUIeEhk4Xfxhv4HSOyddiVaq/UHZUlIht336syytR+ifCl9Aftq4QwJ6jdvIPj2yxEFBLSGEEEIIIaSdEJcAAxbQn376qZx22mny3XffyeLFi1Vc7oyMjIjp+/fvL1OmTInnkIQQQgghpAOw7777Kle1hvLuu+/KiBEjmqVMhBBCWj8YNM/NShG7TUTTQ7I4f++DwYRMX7pJuTH4g7o47DYZ36cLK2UvpLpdKhzJsO5ZSh1cHdBUCJd7Pv9Ffli7Lea+c9fvkIBW436hhUIyvjfrmxBCCCGEENJ+cMaz84MPPih//OMfpVOn+sVpPPTQQ9VC6vCn2cWRWaOD8Weaa8ZdaphtoZu3YfZrfaU1gVTzJs1jnsWhJYWiHle3tJBQA0LnVvYwH8cesBQxaP7sy6pLX93VvK/DZ07rsrjIOquMGVsKYqk7h898voH0umMFk81pA2nWz9Er3uk1l9nb2fzZn2EuiKvcHrV+gimW46D30EAwxfzZbagPe8Byftbrn6qZPiftqLvIerp5X4flnFwV5s8BQ/qqXEs7KrZcCMvkIUd13fuUAvO+1utvbXdJhXXvdfderpnlnFxltqhpvZ1jXyObFr1u3CWx252rylwO3Vm3v9+iWbOWy2PJ25je1PZVWvNx/Ib2rY7rqvts0y31nk0Lf0JaBHz1Qk2QRzsHTmqnnHKKEvDifhPC31GjRu0RbkTTNFm4cKF88skn8sorr8jmzZvlvPPOS1i5CSGEtI4QCWt3likng5U7SpUQA4PqhESisNIr8zZAEFDjxjAqt5N4nA3o/OjAuBx2OXFkX8lYlS/zN+4UbyAoIQnJo7OWyM4Kr5w0sq9yo7Eya8020XRd1Xn3jGTpkmbpjCGEEEIIIYSQjirA+Nvf/tZ0JSGEEEII6QiEbDVLvHm0c1544QW5/PLL5c4775Tbb79dbrvtNklOTpY+ffoo8S9mqRYWFsrGjRvF6/Wqzv1jjz1WOWCMHTs20cUnhBCSQPKy0tTvgh7SpToQlI1F5dK/c2SnTkI+W7ZZhdFA+BHo6Cf178ZKaaDrzGGDe0pGklu+WbVVfAFNQiGR135eo8Qt5+0/RIUl+XLFFlm0tUiKKqqlsNqvxBsQRo3O7cn6JoSQVsB///tfueeee2Tt2rWSmpoqJSXW2WaEEEIIqS9xTXf++uuv5aabboq4DZ3i2DZz5sx4DkEIIYQQQjoo48aNk48++kh1AN1///1yyCGHSFVVlXK8+OWXX6S6uloOO+wweeCBB1QahCyh+IIQQghm1DvtdmXCB0eD5QXFrBQSEQh0vlmVL0EVDiMkAzqlS3aKh7XVQCB42q9PFzlx377icTnEF9Sk0heQjxZvlJOe/Vxu/ni+fLxkk2wqLpddVT4V6qXCF5Cy6oD8sqVQiqostqeEENJIfv31VznnnHOkV69e4vF4JCcnR4444gh58cUXlXticzFnzhy544472qxoYcWKFcp5csCAAfLcc8/Js88+m+gikSZg2bJlql1u2LCh2esTfTU41qxZs5r9WIQQ0u4dMNDZnZ6eHvXhCx3hCFPCsCOEEEIIIbthCJIGA9eLa6+9Vi2EEELI3oD4okdmsqwvDIoWCsmS/GI5dkQfVhzZg+/WbJMqf1C5XwR1XSYPoPtFPAztniVpHqe899sGKanySXmFV9Wr2+GQ3MwU5XoBRxqnwyaaFhK7wybrC8vl1Z9WyzkTBkkOxS+EkDj4z3/+I3/605+kW7ducu6558qgQYOkvLxcTSK98MILZdu2bXLzzTc3mwAD7o0QMWRlZUlbA4Pmuq7LI488IgMHDkx0cUgTCjDQLjGZpW/fvs0uwMCxAI5HCCEdnbgEGL/99lvMjvCJEyfKP//5z3gOQQghhBDSvqAAo0PzyiuvNGq/adOmNXlZCCGkPZOblSobiypE10OyrKBYuXRiogghYRB2BOFHNF2XgKZL1/Rk6ZWVxgqKk7zsNPnD+AHy8Mwlql4RogR1vb2iWtLcLtFDNbfDYrNJdrJHbSsoq5L3f1sv508cotITQkhDmTdvnhJfTJo0SaZPn26aNHrVVVfJzz//LEuWLGlzFVtZWanCgTQ3O3bsUK97E4/gfgohQBEelBBCCCHNFIIEllrRHDAAbg6KioriOQQhhBBCCCHtBsyIOv/889VrfRekJ4QQ0jDyMlNrB35LvX7ZVlbFKiQmftm8SwrKqsWv6SpUzaR+XSnSaSLKvQHlduF02KGzUN9DhB0pqfar7RBgOOx2cTvskuRyqLT5JVWysbCcrZQQ0igw8x5Cy//9738RxyvGjx+vnq3CYNLo5MmTpVOnTkpMgPCX77zzzh77Ic+//OUvKt8hQ4ZIUlKSSvvdd9/VpkHYheuuu06979evn9oHC8I+YMH7l156KWLe2NeYD9bBteAPf/iDZGdnywEHHFC7/dVXX1XHRnkRWuXMM8+UzZs3m/JcvXq1nHrqqdK9e3dV1ry8PJWutLQ0at3BGeH2229X77t06WIqF7Ydd9xx8vnnn6s6xLGfeeaZ2rEhiFvC4V7gnIHQoXDSMIJ0qPvMzEwl8DjvvPNUqBhrvcA1IZJzAva1ujfgGA8//LAMHz5cnSdcTy699FIpLjaHnQuX/4cffpAJEyaotP379484MQLlvPrqq9U+OB/UHSZC7Nq1SyoqKtRY11//+tc99tuyZYs4HA659957o9ZxuMxwGNl3331VOVDXRx11lBIHhQkGg3L33XerUDAoA8oC1xafz9fg80Ldnnbaaeo9HOrD7dIYImTGjBly4IEHqnPD9+bYY4+VpUuX7lH/aWlpsnXrVjnppJPUe5QdE7PDYX3QzrHO+F20tm9CCOloxOWAgR9yuGBEA9s6d+4czyEIIYQQQtoXdMDo0MycOTPRRSCEkA5Bz6waAQZACIQV20ukZ2bzzyAlbYfpyzbXCgNS3E7Zp3tOoovUbvhlS6F4g5p0TvVIuS8g3oCm6rqGkOAt6lx2m12kuB1SWh2QX7cWSr/OGYksOiEkwSCMAZwsPvzwQyVmQFgRDPzvbR+EGTnooIOkd+/e9ToOBsJPOOEEOfvss8Xv98sbb7yhBqs/+eQTNQht5Ntvv5U333xTrrzySjUo/uSTT6qB859++klGjBghp5xyiqxatUpef/11+fe//107HoIB6Z07dza4DlAOhE/5xz/+oRwnwD333CO33nqrnH766XLRRRepfB977DF1zr/88osSNuA8fv/736vB+iuuuEKN3WDQHOcEcQEEEJGAkAED9++//7489dRTaoB95MiRtdtXrlwpZ511lhI4XHzxxUqIgjo/+OCDVf5Yj3pHGJabbrpJhXpBngDlP/HEE5VQANd12LBh6jgQYcQDjgmBASYr4LqsX79eHn/8cVUXs2fPFpfLVZt2zZo1MnXqVBWGBsd94YUXlKgAYhYIOAAEFhAiLF++XC644AIZO3asEl589NFHSmAxevRoOfnkk1U7+Ne//qUEF2Fw3XGeaEuxwPFR5qOPPlpdQ4gtvv/+e+XeEm7jWP/yyy+r8v7tb3+TH3/8UQk7UC7Um5G9nRfaBurm0UcfVSIO1D0Iv/73v/9V+6HNQDiDa4rrD9EP6tEoeoHQAun2339/JV766quv5KGHHlJCkcsuu0y1deyL96gnfCeAsR0RQkhHIy4BxpFHHikvvvii+iOPP+xGFixYoP7oQ61JouPPsIk9q+aJ0+k1b7PBl3E3rgrrNrMlY9DSj+TLrnvvMAskxWmZ+OOsNuflKq87ruYxbwtZWoxedy9Tsz2p7n3K9rp8VDn85s+a23IOKXWfNY85rT1gTusImLfrdfc8Ego/wUeoC+ApNm+3B+ve28wCXbHViDhrcVZZ66OuHL5sc5lsQXNaZ6XluIHoxwoZzkdhKZez0vzZa+gncvisxzGXK+QzG9/YayagKJJKzftW9bDUs+Wa2TRbxHxqDmT+aK1b3V33vrKnLWZa4zWytiVrmTSP5Tguc0EChr4cV5nlejpi75tUGP18XZXmtEGLE19lj+j1rlu+Vw5v7HboKo/+/fbt/nsSxvp3xW6oO2u+hJCWwiYSitdamdbMbRV0UhFCCGl+PE6HdElLkq0llaLpIVm8tUgOG5zLqieKDYXlsmxbsQQ0TQl0JvXrLg4776+aik3FFepuFQ4YWckeKbcFpMofVCKMcC0rAcZu4IYBEDaIENKxwUAwBobDkzsxwIzZ9bHAQHQgEFDOAvUFggljGA24XGDQHYPrVgEGQpfApSA8/gFHCYgQbrvtNnnvvffUIDP2xUA8HAKMA9eNEWCMGjVKXnvttdrPGzduVA4V//d//6cG0sNgkHvMmDFKEIL1cM6AEOHtt99W9RYG5YwFygxHCgzwYz/rhFrU72effaYG4MOgLGvXrlUD9RCLhEURPXv2lAcffFCJB+CMAQED3EIeeOCBWpcQDNLDkaGxQMwBYQ5cSYxjT8gTwhicv3E9BCQoAwQWACIWlA3jWhATAJQZ1xnXEwKCMH//+99rRTBww8Axv/zyS3UcozPJ3sQ/mIgB8QUEERD/hEE9hfNHe4f4AiKM5557Tq3785//LF27dlXlRB7GetvbecERA9sgwMA4ntFdBIITlAXHevbZZ2vXQ5CBtg3xj3E9ws6cccYZSgQEIKZBm3/++efV9YSDBtoO3uP7cM4559T7ehJCSHslrhAkt9xyi7I3gl0XRBhQGWLBe6zDTQx+pAghhBBCSA22UNMshBBCCIlNHlww7DVhSJYWmC2pScdmxrJN8GFQ7hdwStmvT41tNmkafEFNwnoWGNFkJLkkPcmlxBe4jU12OdV30wjSYT9CSMcGkzqNQHwAJ4JYlJWVqddYodKtGMUXCFuBEB0YrF64cOEeaSdNmmSafIqBdrg6ICxHOARDU4LBbSMQBSB8BQbYURfhBQ4XED+EXRbDDhcoF9wMmgo4kRjFFwAiB9QXwqQYy3TEEUeoOgmHaJk+fbo4nU41MB8G7hFw6GgsODbOFaIC47FxjeDeYXWd3GeffWpFCgBuDRAZrFu3rnbdu+++q4QvRvFFGITSADg3CEwgwggD0caiRYv2KjhA/sgnHOolUv6oK3DNNdeYtkOkAT799NMGn1c0ICKBKwqcTYx1iGsDl4tIzp3Wdolj1+dYhBDSUYnLAQNqTth7QRkHZR2WMLDfgqoPSrumAjcaEHbAeunwww9XVkdGcGNx1113KcswWF316NFD/YhAmZeSkrJHfriBgy0WfnCg+sMPFNSuUP5FAjcOiFs1f/589Xm//fZTMa2MP3SEEEIIIYQ0lB07dqhZVUVFRXvEzA3PtiGEENIwcrNSZcHmXRLUdNlZXi2FlV7plGqwbSQdkpIqn8xZt10Cmi4BXZcRPXIkyRVX9xiJ4EBTahQM20RSPU7xOO0SDGriiVDfmACM/QghHRuEYjAONGP8YW8hzjMyauxuy8sNlrF7AWE54OIA5weE7LAOhhsJOzwYGTx4sBqLgMMFhBBNCQQPRlavXq1cEiKVA4TDbWA/DN7DxQMiAYxZIMwKxAHRwo80pjzhMkF4gEH/aM+34fEXjNFAGGEE4zCNBceGYAbOELGOHSaSMwWEIxDehIGbx6mnnhrzuHa7XYUZQagNXHuMN6GeMUEZYWNigfwh3sjJiR7uDHWFYwwcONC0Hu0LIWawvaHnFasOwWGHHRbzOxUG52i91vU9FiGEdFTifsKE1dDixYuVRRKsu8I3IFAMNjWIHbZ06dKI26CsPOaYY1RMtnPPPVfZPqFMsI9CPDaILPADFgaxuyZOnKh+rK+66ip1I4HYcohjhthlVjUilKPHHXec5Obmqm2I9wYbJvxIzZgxQykgCSGEEEL2Cjqj43Ww6GAOGNXV1WqWCzppMBujPQGxBaw/cV8Za/YUBRiEENJw8rJT1ax6/GwG9ZCs3F4ik/s37SAJaXt8sWKLCjsC9wtdD8nk/t0SXaR2R+/sNNlRXi2arteGFwFOu10cztAeA5xIB/rkmAfoCCEdj+uvv16FvEDoCkzsRKiJvYEBa7gsYIyiPnz//fdKmIDxA4TvgEAAIgZMLjWG/mgKIgk6QKxnP6M7R/iZEflgDAIOBVaM4oaHHnpI/vjHP6pxji+++EI9a957770yb948ycvLa9Q5WMsTLhMcKHC9IoHxoYaCcwyH44hVVzg2xBdGJwojVqFApDoDkY61N/BcjvGmDz74QE38RXvBmFE8Apf6thkr8ZxXeNIHwv1EEhDh+1SfYxFCCIlOk0n8IbhoDtFFGNgZwckC8acgmLCC+FgQX8C+CnGtjCrZa6+9VsXiMnZcIy5aQUGBsn9CvDQA8QVuvqB+hYgj7N6BH3lYLEF0AReMsLoQ+Q0fPlxZaCHmllHgQQghhBBCmgbcg8GhDPd47U2A8e9//1t1+iFGLWxd4Sx33333KftcbMMMGdz/EkIIaTipbpdkJ3tke7BmIHjJtmIKMDo4/qAmX63cqgQ5cMDo2ymdrijNwJi8TrJ0W7FU+TVJT9p7XxnSISzJ6NxOzVEcQkgbAq4C6Mdv6D6YJPnNN9/I5s2bpVevXjHTYzwAM/ox4RLPmmGM7t6R3AKMYCIqjhse7I82aA6XAIBwD0asbgaxGDBggBpUxwTS+ggb9t13X7UgNPycOXNkypQp8vTTT6sxj6YCZYKj+N4mpfbp00c5qCOtUSiCsZRIdRUppIW1rnBsOKPjvCKJQxoD8kQ4kb0B1/cxY8Yo8QcELZs2bZLHHnusXvmjvcHxMpoLBuoKwgi0t2HDhtWu3759u2o/2N5QorVLlAdAyNJUE4vrKxwhhJCOQptRDEAcAbFDtPhgr7zyiikmVpg///nP6oc4vB3AIuqdd95RNy1h8UUY2HQFg0GT2hWq2A0bNigrKaO1E5SNGAyAKhc3M4QQQgghpOmByBV2nei0aW9ARIyZQ+hkhJtb2HYXAl/EP4ZgGLa4hBBCGgfCkNhtNtFDIVmyrYjV2MH5fm2BlHsDSogBF4zJ/eh+0Rz06ZQuPbNSlMjFG4g+yxtgO9IhPfYjhJDGAMdqiBQwqTLScyOerfDsFZ7Nj8Fio7MC+v7hahCJuXPnysKFC2s/Q+QBh4nf/e53tc4AqampEYUWCOWAECqY1GkEIvz6gvELHAeh0K3uBvhcWFio3peVlalxDSMQYuB52hhmpSk4/fTTVb1AVGAFdRAuB55x8R5hO8Kg3iOJFiAKWLFihQrrEgYO57Nnz97j2Mjj7rvv3iMPHMt6DeoDwo/gWO+///4e26x1jjYGdxG4tXfq1EmOPvroeuWPfHANo+Uf7g9AvkYQUgYce+yxDTyr6O0Skz/QNjHZIxAI7LGf8RrUFwiSIh2LEEI6KnE7YLz11ltqNiJUn+EfeyO4mbH+8DeU5557Tt2kIC52JJcJ/EjNnz9fdcxblYAQX4wePVptDwM7MlhZT5o0aY+8sA5lRtiSMD/++KN6nTx58h7pw+uQ/oADDogad8z6owXRBiGEEEI6HrZQzRJvHh0NdLIgDMnVV1/druwvcU944YUXqvfh+9zwvTNcMC644AJluwuRMCGEkIaTl5Uqi/KLJKCFZEtxpVT4ApLmqYmVTjoW6Dv6bNlm5Ybi13TpnJqkHDBI0wPR08mj+smrP62WgrIqJbBIcTvEYavr08N1gPMFtnXPSFHpsR8hhDQG9NE/8cQTajLm0KFD1SD5oEGDpLy8XGbNmqVCmoQdIDCQjUHto446SjkRou8e+yKUyaJFiyK6HmDAGuE84JgRFk8YB9PHjRunXm+55RY588wzVUiT448/Xg2AYwInXA7xCrE9xjnCodzrA4QJKPtNN92khCInnXSSelZcv369EgxccsklygEcDiB/+ctf1CRSOGXguRIhJvD8DAFAU3LdddepOkX4DYQ8wflXVlaqcRdMfEU5ITxBHcCp4sYbb1Tr9tlnH3nvvfdUWHgrePbFdUFd4xkZ1wXOHZiUC3FJmIMPPlguvfRSFVoFkxUghEF9wzkCfQaPPPKITJ06tcHng3Kj7lAOnA/cKnCOKIPR+R1tBqFXUPeYOIFj741DDz1UtUmMo6GcaHtwu8DEX2zDdcMx4IiJ8KQQMeA8MeYE4RCuOdI1FIyL4frff//9qs7RfuEWA+cLiGJQprFjx6o2CzcXOHp8+umn6po9/vjjDToWxuFwfd98803V/uD0ge8OFkII6YjEJcCALTJ+3PHHFMIFKP6amvz8fPUDCGeLaCFO8GMIV4tof8xhBwVFJn6ooezbsmVL7Xor+BHCzUE4DYiVPrzOmN4KbsoiqRuBwy/i2C1AdZeZR1NsNaG4FHbNvE1LNj+UOryWfKvr3gdrxIe1BLLNedn3EDnW5e2qsKhqNfNxg0nmPXVDiwommdN6SnVzXpYHa5dBnOwuMW9zW8pR3cW8PWT4aLfofZyWutGSo9eVu+5eriavgOW43SxxSutc6iRply1qXQCbbjnfSsuxDEJkZ7Xl/C1tw9vJvN2mRR+Uc3gtac2XwdR2NMv1TN5hOV/Ldm/nUMTyA0+xxDyuLyv6Nk+x+SR0p6VuY4y7JVl0YI6t0duSL8Oc1lltFnjplvtn4/W2Xl98l2OV2XqOIUf08w3ZLd9vn+WiGjaH/35EPY7le+bPNHy29G2lbbHsTAhpHvCjZfzhamweHYzzzz9f2Ywefvjh6r4QnWnhGRZGjG5lbQG3263sb42zU3bt2lW7HQJjdFQRQghpvAADt9cYfIfjwaodJTK2lzk2OOkYLNpaJFtKKtWAf1ALyf59u9AuuxnJSfHIORMGyfu/rZf8kiopra7pfLJJSEJS03GDsCO9c9KU+ALpCSEkHjAov99++8lDDz2k3LAxIRJhLzDAjPAi55xzjkqHAejnn39eiSIQ6hwu2RigxnNXJAEGBsIx9oH+fQxQY5D5pZdekpEjR9amwXHhyIDB+s8++0wNrkMggWe82267TZUFA/yYzArHhBkzZqhB8PoCAQMGtTEeEx5nQKgViA8QUh1g7ATihY8//li2bt2qnpexDseaOHFikzYu5I1w8HBQgOgB9Y1xF5QR5YNzeHiSAUQMqGe4PmLiK8qLa4RQHkYQdgP5oL4wAQH1DAEJnMohojGCeoZI4plnnlGh5p1OpwpFj2sM8UBDQTuBGAJOKhBWQPSA64P+B+uYULdu3VS9T58+XQkY6gvaINoM2h7Gu1BHEOQYJ/1i8kX//v1V+0I5unfvroQ3KFdjwP6oK4hVIGqBc8jMmTPVuUFIgv4GfA8efPBB5ZKSm5srBx54oOp/aQwoPxzsMXHG7/erclOAQQjpqNhCVg+lBoAfAyjj8Ec7Ugd4U3DiiSfK0qVLlXoyHNMLP9T48UMnfNj2C53t+HGw2nmBadOmqR/rbdu2qR8dvMe6W2+9Ve6666490iMvnA8srwB+nF544QUVrww3aEYQlwwqVNzg4cesIQ4YUC4OOvt6SerUvcECDG+OZaDYKqUJxRBgZMQWYLjKYwgwHHsRYBgGrN0WIWvqdrPtZCDFfA6+7Lq8bRYRRTwCDONAdySMAoyQs2ECjGByqN4CDGs5YgkwdLc0SIChGdI7LNdzj2vkNuflKYo+IG9tGw0RYFjFG7EEGNZrtjcBhk0PRRUjGcUowOENxRBgWAUmtpgCDOM1tB7HU2I+jlWAFIrxHbWWMR4BRqAunGJEAUYwNXI+kQQYc/8Z+W8aIW2dpSt9MvKQzSq+J2ZStNhxly5VD565N1wn7h41v/2Nxb+tQLbe/2CLn0MiQccN7gFx6xortqjRRrYtAEtYzMBCp0f4/hqdZmGLVoThg60rOvo6KuHvTqLb+8qCQvl55Xr1/OOuxyyn9kxI0yRYVS7OlHSxtSNHmobCemgbdYHfjad/WC7FVT5x2u1y1vgBcu6EvcdPbyywcYY7KCao1GdGZHumtdXFvV/8Ir9uKZRyX0AcNpv89dARqk105O9HS4DwPxsLy+XXrYXq1RsISJLLpcKNjM7tpF47ovNFcUWV6FUVcsCIgdIt0/Ig38HusQhpzeDZ8/LLL2+wGwCJDcQuEL5AlAAHjbbGySefrMar6HJOCCGkWRww4E6BGYjNJb544403lELyyy+/rBVfRCJ8/GixzLxeryldfdLDBaM++VvzjgQUhQ1RtBJCCCGkHQNNVbwhRBIQggRxSHFfBoEq3McwuwUWrRAIQNgaKSwIhLF33HFHbSg4zArCbBiIZhsKZsHEEl60VQ466CD55JNPagUYZ5xxhpp9gntMzJr63//+pyxlCSGENA78dsAFo7TarwaCl2yzWPWRDsGW4grlgFHjfqHL+H5dW0R8QWrCkfTrnKGWji5GIYQQ0vbBJF+E6UC4GUIIIaRZBBh9+vSRigpD3IgmBGIHxFWDnRPso6xqwurqarUO8c4gboAAIloYEKzHIAGWvYUNwXFh+2y05YqVPlZ4EkIIIYSQ1iKgiBfEHsX9DmKVQqiK0G4QDiA+KmLNwmHMCFwbEA8WFpawnUSYN8QyhZsYLFCPOOKIBh0fQo72CO53YUOKe1sIjiE0gcgF1qsA9Q1bV0IIIY0HAozlBcUS1EOybleZ+IOauJ0c/O1IzFi2WQW+8GuaQM+5fx9OkiGEEEJI/UFImdmzZ6swG3D2giM6IYQQ0iwCjMsuu0zFrIILBuJsNSXohEbYji+++ELF+LYyZ84ctR6zBOGUgXhZmGW5ceNGJQwx5vPrr7+aYmnB6hmxtufOnbtHvvPmzVMWpRMmTKhdF36P9JjlaSSchzE9IYQQQkg0bKGaJR7i3b8xIO6qFcRxPeaYY1Qs13vuuUeFcQuHAfnTn/6kRBe4Pwuvh1MG7I1xD7ly5UoVVqSjM2TIELWEgQgDsV4hcEH9IBYtIYSQ+MjNSlWz8PWQrsQXa3aWyT49slmtHYQyr1++X7tNuV9gGdYtS1I9iQ+JQgghhJC2w7fffivnn3++6t94+eWXVah7QgghJBpxqSbGjBmjHChgJ33FFVeouF2R7KdhrdxQUlNT5e2334647bTTTlMiCswQ7NWrl1p37rnnqg7+hx56SB599NHatIifDREGtoeBW8app56qLJ3fe+89OeWUU2q3YX+ISc466yxT+SHqeOutt5RtdviY6BiH4hGxuo0CD0IIIYSQjgKcykBJSUmt0OL7779XMV0RyzW8DmRmZspFF12k7qcgpj3ggAMadKzy8nIVCgXuGtu3b1cuEZMmTVLuZU8++aScfvrpMnToUGlLwE0uksgi7NxGCCEkfjqnJYnH6RAfwk/oIVlWUEwBRgfiq5VblfDCH9RF00MyuT8HTAghhNQPTNQkzdOP0NbqFv0bWAghhJBmF2Aceuihte/RmW6Ny40fUazDLMiGAhunqVOnRt2OsCPG7VAfohP+sccek9LSUiWa+O2331Rn/CGHHCLnnHOOaX9YOX/11VdKmLFgwQIlHvnwww+Vlfatt94qAwYMqE0LUQnyOeGEE1TMclhFu91ueeaZZ6SgoEDF/OIMTkIIIYTUC/QxxNvPkMB+iuLiYnVvV1RUpIQQL7zwghKjDhs2rDbNjz/+qF4jCVTD6xDSpCECjMLCQpUeIegGDhwo69atUyJbgJAoL730kroHhJi2LdGjRw8lDMa97MEHH5zo4hBCSLsE7hc9s1KlckeJGoBfnF8kU8f0T3SxSAsA4cUXy7co4Q3e985Ok67pyax7QgghhBBCCCGtU4Dx4osvSmsBIonp06fLXXfdJW+++aa8/vrrqkMb4VHglGF15sBsTIQPufnmm5WQArMPBw8erN5fcskle+QPe+0vv/xS5Y/8AJw/IOKIp7Nc84hou5/9fQ6zgMUerHsfsttiDrzYLBoXb5e6BLrFWdNTZDlOwLzdmN7buWHH1T2GpBYzFF+m2WbcU6qbPlfm1u0QSDcfqDpoLofuMW+3GerKppnTuirM5XD4zJ+9htCvWpI5X90VillXroq6Y9n95m265dsVTLFUXshcTmMTNV57EEi1iJssju12w3XQ3OZtWnLscwo56/L2Z8Qe0bNbroMYLqHDa97myzEndZdZPpfXvU/eqcc832CqeV/j98F6Taxpq7uZPzsr6irP4Y95ScRZZf6sJUVv39Z9Q87Y25OKQ1G/RzY9dn0E0mymvyGx2oaxnq04vBLzOISQ1i/AgBjBSpcuXZRQtbmAAxpCvgEIbY844gglVIV4NsyWLVvUa15e3h77h9eF09QX3H9t3bpV3b9htoz1HE866ST5+uuvpa2x//77qxAu//3vf5Xj2nnnnaeWsLMIIYSQpiEvK1XW7ixVA/GrdpQqIYbD+pxN2h1z12+X0mr/bvcLXSb1szwgEkIIIYQQQgghrUmAgc7hRBDNngr2zQ888IBa6gNcLyDUaIjjh9H1gxBCCCEkkUB0YOX222+XO+64I2L6aOsjAQcxLFYQwq2qqkry8/OVexicMOA8YQTbgcdjUYlBgJaUZEpTXz766CP585//LOPHj1duGFYgWNi8ebO0NSDmhRgFDh5wc0N4lrvvvlu5ucEVA+4YCJ9HCCEkfgEGhIN6SJfqQFA2FJXLgM4M99SeQd/R9KWbRAvp4tc0yUrxyMAuvOaEEEIIIYQQQlqxAIMQQgghhDQMW6hmiYfw/h988IEKx2F1wIgGBvcbQiQBxpQpU0xi3CuuuEKJBRYvXqxCkYCwYMDns9hOwXnKW2O/01BRwY4dO2TQoEFRt8OBo6GijtYCXEH+/ve/q+WHH36Ql19+Wd5++22ZNWuWXH755XLaaafJ888/n+hiEkJIm6ZbRrI47XbxiyZBTZcVBcUUYLRzlheUyMaiCgkEdeV8MqFPlz1C5xJCCCGEEEIIIU2Nxay+4WDG3oUXXqg6jt1ut3zzzTe1neQXXHCBzJ8/vynKSQghhBDSPkBMoqZYRJT4Yvjw4aYlVvgRzASt71JftwyIMCB8gHtDfcKMxApPEovOnTvXhj6JBAQgDc2zNXLAAQfIc889JwUFBerVbrcrdwxCCCHxAfFFj8wUsdttooVCsii/iFXazvl06SZ1T+PXdPE47DImr3Oii0QIIYQQQgghpAMQlwADneCwgcYMvX322Uc0Tavdhs5/iC84W48QQgghpP1SXV2tXouLi2vXTZgwQb3OnTt3j/ThdeE09eXII4+UF154YY9wJ2DFihVKpHD00UdLe2DevHly1VVXyXXXXSdlZWWSmpqa6CIRQki7IDcrRewIQ6KHZEVBSdTwpqTtU1BWJb9s3qXEF3A8GZXXSZyOuOcgEUIIIYQQQggheyWup0/YJIMlS5bIa6+9tkfnxTHHHCPff/99PIcghBBCCGl/hOJcWpjKykqpqKjY8zRCIXnkkUfU+0mTJtWuR0iSPn36yFtvvSWbN2+uXQ8xwX/+8x8VqmTy5MkNKsNtt92mygHx77///W9lIf7RRx8pocJ+++0naWlpcuONN0pbZevWrXLvvffK0KFDVZgXuF+MHDlSiU62bduW6OIRQki7IC8rrUaAEQpJqdcv+aVtM3QV2Tszlm0WXeB+oalbp4l9ozuEEUIIIYQQQgghTYkznp2//PJLueyyy6R3795SWFi4x3Z0vKMzmRBCCCGE7CYkYotXRNHCIozVq1fLwQcfLKeeeqoMGTJEhQPJz89XLmgI/XHUUUfJ6aefXpve4XDIk08+KSeccIIceOCBcuWVV6pQdc8884wKrfHpp5+q0BoNAaKNmTNnyvnnny//+Mc/1LpHH31Uve67777y6quvSs+ePaWt8frrryv3DoTxg5sc7p8hckZoF5wzIYSQpqMnQpDYasJ4BXVdVmwvkdwsugy1Nyp8AZm1Ol85X2AZ3DVT0pPciS4WIYQQQgghhJAOQlwCDFhN5+bmRt2u67r4/f54DtHucXpFnLsn3TirzKMp3k41HUMg5Ig98GLTLJ+Ddfu6apzBa9Es/Q5BS3+T3Wd4H4i9r8NnySutrmC+bJt532TzZ1el+bNuOEfr+VrL4So172vKx2Mpc5L58x55+yKXQW0T83GSdpg/B1Pq3vuzLcexFNHht5x/VfRzDCabt7l85gvurDLnVd2tbrvDZ97mqLYct8xSML3urbvEvM1paTveLubPxuqxno+j2lzmkD163ZUMMQ/C2YKWvLzR27svx3wcLcn65bCU2bip3Bazfdst5UjfXFdZld3NZa7qbj2/2KOjQcP3waZbjhuwXAfL+QcyDGn9sdu3Zvk+uMuMbcVSKDowE9IyNIWLRQt/X/Py8mTatGnyww8/yAcffKCcLDIzM5XwAaKKCy+8cA9BBZzQINa96667lHsFgFPFV199pcQcjWH06NHyyy+/yNKlS2X58uXqXnPw4MFqfVvl7LPPlpSUFDnrrLPkj3/8oxx22GGJLhIhhLRbPE6HdElPkq3FlaLpIVmcXySHD4nep0HaJjNX5Ys/qNeEH9FDMqV/90QXiRBCCCGEEEJIByIuAQZmGa5atSrq9vnz50u/fv3iOQQhhBBCCEkwcLx47LHHGrzfoYceqpamZvjw4WppDyDUCNxD0tPTE10UQgjpEORlpcq20ioVhmRZQXGii0OaGDibfLZss3oNBHXJzUyVHpkG9T8hhBBCCCGEENLMNMz72cJxxx0nzz//vGzcuHGPbbNmzVKWyieddFI8hyCEEEIIaVcg/EhTLB2NI444Qu6//34l8A2F2kcFlJeXy//+9z958803E10UQgjpMORlpakwJLoekp3l1VJYabGbI22anzbskKIqnwSU+4Uuk/p1TXSRCCGEEEIIIYR0MOISYNx6663KMnncuHFy9dVXi81mU7P4ILo48sgjpVevXnL99dc3XWkJIYQQQtpLCJJ4lw4GQo7cdNNNMnHiROnUqZOcfPLJ8vjjj8uKFSukrQLXix9//FHdQxNCCGkZcrNSBH928VOK8BQrtpew6tsJEGhOX7pZuZv4g5pkJLllcLesRBeLEEIIIYQQQkgHI64QJF27dpW5c+fKFVdcIa+99pp62MUMPsQAR9zvp59+WsUHJ4QQQgghJB62bt2qRBhffvmlfP311zJz5kz58MMPlXihR48ecthhhymXjGnTprWpih4xYoSsXbs20cUghJAOQ6rbJdnJHtkerBZN12XptiKZ0r97ootFmoDVO0tl7a4y8WuaEteM79NFuZ0QQgghhBBCCCFtRoAB8vLy5P3335eysjJZtWqV6LouAwcOlJycnKYpISGEEEJIe6IpHCw6oAMGGDZsmFquvPJKdc/5008/yVdffaXC3iGUB5a2JsC44YYb5KKLLpJzzz1XnRshhJDmJy8rVXZWeEULhWRJfjGrvJ3w6dJNamKQP6iL026Xcb06J7pIhBBCCCGEEEI6IHELMMJkZGTI+PHjmyo7QgghhJB2CeZh2uIUUHT0uZyVlZXy7bffKvEFFjhjwAkDbhJtjSVLlkjfvn1l9OjRctxxx8mgQYNUiD8jODeE/iOEENI05GalyqL8IvFrIdlcUiEVvoCkeVys3jbMjvJqmb9xpwQ0XYKaLmN6dRa305HoYhFCCCGEEEII6YDEJcDYtGlTvdL17t07nsMQQgghhJAOzuzZs2sFF3C+CAQC6h7z8MMPl5tuukm9IjxeW+OOO+6ofQ9XuUhQgEEIIU1LXnaqIDIF3BI0PSQrt5fIuN5dWM1tmM+XbxY9FBKfpokuIpP6tb17AkIIIYQQQggh7YO4BBiYrYcO4b2haVo8h2nXhOw1C9A8e26Lhs1apZa09oDhvSVtSI/9OXlX3bRczWO+vna3Oa3uil6utC3m6b3ucvOBdKc5b1dV3Xun17zNUW0+jj/T/DmYUncsZ5Ul30rLvunmz4EMQzktzdldbF6hJZm3u8oN25LN2xxe8+ekInN9+NMseRv3t8yMDjksaS1txaZHvvZqW1BiYtzXmq8Win1OumFCUdBSNxIyl9ldZs7M2C61ZFvMtm8tl6fUkK9FB+bLMe+sW/7KeQwOw74s8zbdZSlj0FwuX4Ytar7WtpO0y7LC8jGYErWqTNckErZA9GsS6Gw+h2CaebvD8N1KLjT/cfAU76WxEEJIAjnwwAPF4XDI8ccfL4888ogcccQRKuxdW2f9+vWJLgIhhHQ4MpPckuZ2qVAVcEtYVlBMAUYbpjoQlJmr8tW1DGohGdglQzKTLQ+RhBBCCCGEEEJIWxBg3HbbbXsIMILBoKxdu1Y++OADGTVqlBx11FHxlpEQQgghpP0AnVScIUji3r8Nkp6eLuXl5TJr1iz1GbOWsSBkR1umT58+iS4CIYR0ONCPgTAkJdV+0UMii/OLEl0kEgezVuVLdUATPwQYui4H9O/G+iSEEEIIIYQQ0jYFGEbLZCurV6+WSZMmMV41IYQQQgiJm6KiIhV6BCFIvv76a7n66qtVGJLc3FwVfgSOGHjt3r17m63tNWvWyPbt22XEiBGSmWmx+yKEENKk5GWlyvKCYgnqIVm3q0x8QU08ToPFH2kTIOzIjGWbRdN1CWi6dM9Iltwsiw0gIYQQQgghhBDSgsQIchEfmI146aWXyp133tlchyCEEEIIaXPYQk2zdDQQfiQs7oULBgQZn376qZx++ukyZ84cmTZtmuTl5UlbZPr06SqcypAhQ+Sggw6SBQsWqPU7duxQ6999991EF5EQQtodcMCw22xqAB8D92t3liW6SKQR/Lxpp+ys8Na4X2i6TOxH9wtCCCGEEEIIIe1UgBG2VF6yZElzHoIQQgghpG2GIIl36cBomia//vqrcsTAsmHDBhWORNd1aWt8//33cuKJJyrHC4T3w3mE6dq1q/Tr10/eeOONhJaREELaI53TksTjcigRBlwwlhUUJ7pIpBHMWLpZiWj8QU3SPC7Zp3s265EQQgghhBBCSNsNQbI3vvnmG0lLo/UjIYQQQkgtTSGg6IACjKVLl6rwI1i+++47qaioUGIFhCA566yzasOQtDXuuusu2XfffZWQpKSkZA/3uMmTJ8urr76asPIRQkh7BcKL3MxUWeUrEU0PyeL8Ipk6pn+ii0UawNpdZbJie4n4NU2JaCb37qKuKyGEEEIIIYQQ0mYFGK+88krE9bCERuf4jBkz5E9/+lM8hyCEEEIIIUSJFACcIg477DAltsCCsB1tGQgvbr/9dhViJRK9evWSgoKCFi8XIYR0BPKyUmXNzlI1eL9qR6kSYjjsHMBvK8xYukmJMf1BXV23/fp0SXSRCCGEEEIIIYSQ+AQYf/zjH8Vms5msksO4XC655JJL5MEHH2Q1xyCYLBJIrXnvLjV39Nh0czojKcXmOg8mm/fVU+rehyz9R0lF5n2rupkTlPete++oNu/rtHwOWYLYOKrr8tLc1uOYBxZ0l3lff4bhg7XMhea8XFXm7YEUw3GTzNuCKZZz8Jo/27W6fXVn7PPTPeZyOCvr9k3ebt5m1yzlsJTLWk7NY9g3YN7m7WTJKzUUta34LPWuJ5k/u4vMJ2UPGstkOYeg+UJY22HIEfl9TaEs59DZvMLuN5SpJHa9B3d/RyK1FeM1UPtajhtMMZ9TwGDKY/3OeUos3yNLe8jaUldZld3MG0NOy75uiXq+1mtmM1yDSOfvqrCegy3qcaznYMWYd8kA80VzlzVrVCpCyG5soZolHuLdvy1yzz33KJeL8ePHi93efv5eBQIBSUmx3KxYhM1OZ7Oa1hFCSIclNytV9WnoIV2qA0HZUFQuAzobH0xJa6Ww0itz12+XgK5LUNdlZM9O4nFGFjMSQgghhBBCCCEtSVy91zNnzlRhRvAaXmbNmiWLFi1SncVPPfVUzA5lQgghhJAOHYaksUsH5KabbpIJEya0K/EFGDRokMybNy/q9i+++EKGDx8e1zHee+89mThxoqSmpkp2draccMIJsmTJknrvX1VVJTfeeKP07dtXPB6PesX1wPq98cQTT6jBTSxbtmyJ6zwIIaSp6Z6RLE67XWnHg5ouKwqKWclthC+WbxF9t/uFrodkUv+uiS4SIYQQQgghhBCiiGs63cEHHxzP7oQQQgghhDSITZs2yYcffihr165VnwcMGCAnnnii9O7du03W5Nlnny233nqrnHLKKTJlyhS1Ts3G1nX5v//7PyVwfvLJJxud//PPPy8XXXSRjBgxQu6//37xer3y2GOPyeTJk2X27Nm1oV2ioWmaHHPMMfLtt9/KueeeKwcddJD89ttvyuUO4VO+/PLLqKIYXCsIN9LS0qSioqLR50AIIc2Fw26XHpkpsr6wTLRQSBblF8mxI/qwwls53oAmX6/aKgEtJAFNl/6dMyQnxWIxSQghhBBCCCGEJIj2NYWQEEIIIaSNhCCJd+mI3HfffTJw4EC56qqr5NFHH1XLX//6V7UO4oK2yNVXXy0HHnignHzyycrhA+KLyy+/XLp27Sp33HGHHHXUUSqsX2MoLi6Wa665RvLy8pTY4i9/+Ytce+218v333yuBB+pub7z88stKfHHFFVfIK6+8osQcEHCgvuGE9+qrr0bd99JLL5WhQ4fKSSed1KjyE0JIS5CXlSp2JXwLyYqCkoghVknr4vu126TSF5SApqnwI5P6d0t0kQghhLRD4PSN5zO8GkOywxGwoWzYsEHl9dJLL+01bWOP0RBQDpQH5YoFnkmRrj4gHdIngobULyGEENLqHTAuuOCCBu+DH0LMxCOEEEII6ZA0RRiRDjg29Oabb8rNN9+snByuu+66WueGxYsXKzcGbOvXr5+cfvrp0pZwuVzy+eefy+OPP67EDNu3b1edR4MHD1bnBJFEfTu8rMAppKysTIkwMjIyatfDLWTq1KlKXLF582bp1atX1DwgugB/+9vfTOv//Oc/K+cObJ82bVrE/eCOMX/+fHnkkUcaVX5CCGlJAUYwpEup1y/5pVWSm5XKym+lIOzI9KWbRNN18Wu6dElLlj7ZaYkuFiGEkASDgf8777xTdu7cKZ07d050cUgz8dprr8mOHTvUpIy9MX36dOXamChRCCGEkI6NsymUksA6SyTWegowCCGEEEJIQ3j44YeV6GLevHmSnJxcu3706NFKTDBx4kSVpq0JMIDD4VBCi/o4UjSEH3/8Ub0i3IgVrIMAAwKJaAIM3Mdje8+ePaVPH7MlP64B6h7brUBEAmcPLGPGjGlQmdGZhk5TI2vWrFGvgUBALYlC04IiIV1CuiYhrWMbCao60GvqoiPDemgfddEjzSP23Tq3oKbL0vxd0jXV3ej8gsGgCt+E145Oc9TFr1sKZVtppfiDmrpe+/fuLIK2J62Xtvz9aGpYFwbQHnRdtGAwYfc3ibyvIqSt8txzzyk3wYaC56nq6molwG9L/P3vf1dhJVuTAGPJkiV7CDAi1S8EGE888QQFGIQQQtqeAAOdo7BF7tatm5qhN3z4cLUeP4L/+Mc/1PbPPvtMcnJymqq8hBBCCCFtGzpgNAo4Xdx+++0m8UUYrDvnnHPUjKe2xl133SWnnHKKcvaIxNKlS+Xdd9+V2267rcF5b9myRb0iBImV8LpwmkgUFRVJVVVV1LIhj7lz5yqXDaPDBkKdZGZmNup6PPnkk1H3Ky0tlcLCQkkUVWVl4gj6RK+qkKAzrseodjGApvmq1R80m90hHRXWQ/uoC8ipOic5JT8AsUBQfl6XLyNzPI3OD2KD8vJyJWJzdvC/Fc1RFx/8ukYCgaD4A0FJddplaKZTglXl0pppy9+PpoZ1YcDrE1vAK2UlxWIPeBNyPXBvRQhpGI0VUGBSalJSUpurbvx+t4X7mbZav4QQQtovcf163nDDDZKeni4ff/yxyRp5ypQp8sknn8hhhx0m119/vfznP/9pirK2eyp7medsBLLrZkc4ys0P6VV7saK2GSaY6Ja+I2e1+TieYnNevlDdZ4dFDB+wOLH6OptncLiL68qpu8z5lo03P1BmZlWZ866oG1BxrDPfMFV3NecVTDGXQ3PXnVPIMiExZOnfcFieax3eurz9WWYFs265p07aZY+6vaK35ZpYpuAk77SssCT3FNVtD6TFzst6DnZfXXotyZw4mGk+J28P82fPjro/A64K83FdFea8fJ3Mx41Vz9a2Yre0JV923XvdY2mTu2KffyDTUFfp5m3OKvO+gSxzG+01oG5WrWZo62B7YaY5s3xzO3RWOaOej279a2ops7Ut6a66BI6guRyeYsvfglTzdmOx9yiHK/bnVEM7c1Wat3nKWvO8MULaESERG0OQNIpYoTgaG6Yj0cAOdeDAgVFFDhA2Q5DQGAEGxBPA49lzIDHcORVO09D9rXmEBRjvv/++vPPOOyqsSkqK5YatHiC0yWmnnbaHA8ZJJ52kRB2dOsW4GWlmijSbaNtLxJ6SJk5n25q51tTUzOK2iTMlrUMPJrIe2k9d9OqUKQWVftFDIutL/XH9rYHoAL9JmIjSFgYsmpOmrotNxRWytrhadJtdgmKTCb27iCetTgDYWmnr34+mhHVhrAyHhPSQZGRlS6eMxIQ9wr0VIe2ZQw45RHbt2iVvvfWWXH755cohMDs7WzkPYszCCITpEJIjjGJqaqqcffbZauKplT/+8Y8ya9YsFTYSLjKYmHriiSfKiy++aEoHkXrXrl1Vnv/85z9VeoTMRDrkEeaDDz5QLhN45sFz4d13373HMXG8Qw89VGbOnKnOKUykPBctWiT/+te/5LvvvpP8/HzJysqSY445RoXtbMz9TTi0i9Hl3OfzKVcMhND0er2qbBDSR2Lr1q0qdOWnn34qJSUl6hwR3tIY2j58fgg7unr1annqqafUdcMY0zPPPKP2ATj3b7/91vT8D+cL1IO1LrDA8dGYFsC9BOlGjRqlQnYawbngep555pnquLHAuT/66KPqeR3Py3DrxHX83e9+V3tMTCCxhj/p27evOg84y4dBvSAdJl7AERIOlRdffLEKvWq3141FvPHGG+o6rlq1SuWPc7/oooua3EmTEEJI0xDXE/BHH32kOoMjdXhjHWbz/d///V88hyCEEEIIaV/QAaNRQKCATg50YFlntqAD6H//+5/q9GhvoBOosYNWYQEE6idSvsY0Dd0/Uh7oOELHJjorwx1PDQWdlFiizTZLpGWvw+EUsdnV4JnN0bEH0IDNzrpgPbSfNpGXky4LthRKMKjJrkqvlPk16ZSaFFdoKfztbms2481BU9bFl6u2obNJApoudptdJvbr3mbaW1v+fjQ1rIvdQIxjt4sjgX8r+DeKtEYg7v7Tn/6kBscxUI6JnePHj290fsXFxUpIgXEKhKuEWByTSvHsePTRR6s0CF1x+OGHy6ZNm+TKK69UIRj/+9//yjfffLPX79DJJ58s7733nhqwd7vdJmEFnqMwmB+NL774Qk499VTZZ5995N5771Vuf+eff35EB8P6AgHJunXrVD7du3dXjorPPvusekU4z6aYuIBBfzyb/+EPf1ChLVFPxx57bMTQlAgVimPiOb5Lly4yY8YMufDCC5VAxRpG5L777lOCg2uvvVY59DzwwAPq2TIcWvOWW25R6yGW+fe//63WpaWlRSzjpZdeqgQoqA9cyzAoC9wzkTccH43O7ZhkjHJheywgSIFgAucOR0tcd5QR9dDQ52C094MPPlgJVVDm3r17y5w5c+Smm26Sbdu2qTCrAOdx1llnqXZ6//33q3XLly+X2bNnU4BBCCHtUYBRUVGhbmKigW2wmySEEEIIISQerrjiCjn33HPVLBh0mIUdI9CRhBlFmOlj7FhpzaBTB2KFMOhoQ2efFXQIQViCGTCNwRhmZNiwYfUOTxIGnVEQV0QLU4L1cL4Iu19ghk9YhIEZXGHCzwOYlQTRxoABA9qsYwkhpH2Sm5WCcX2lkQzqIVmxvUSm9O+e6GIRA6XVfpm9tkCJLwK6LsO7Z0uSq2M7jBBCSHsEg8vh57rffvtNpk6dqp4jGgsG4V955RX1LAkw+A/ngOeff75WgAGBAlwF4JQRduODAwFcEvbGGWecIS+88IISUxx33HG16+Hm0L9//5jiETzXwnHhhx9+qHWkwWA8BvFRxsYAR0E4TBiBCAKD9zjOgQceKPGAawLxBY7zxBNPqHVhET6eyY1AMKFpmgonGnbfgLgGZYGAAYIDY4hRPCv++uuvtUKWsFsJXCbw/H/kkUdKbm6uGnPam0hi0qRJMnjwYCVcsKadNm2a3HPPPep6ozxhcF5wqDjggAOi5ovnXIguILyBmMfoUGF0CakvcCtZu3at/PLLLzJo0CC1DvUCERDcLnAt0R8ABxE8d8NpEuJWQgghrR9LsIaGMXLkSHn66afVjYwVqPawrT43KoQQQgghHdIFo7FLBwQdOrD0RIcPOmwwYwkLZhQtWLBAbcMMnLYAZutgNhcWCBEw8yf82biMGzdOvvrqK1OnUEOYMGGCep07d+4e28Lr9ttvv6j7o2zoMMS9/saNG03bMEsMnWPG/ZEG6zETCJ1H4QUzwgA6+/A5mqMGIYQkilS3S7JTPGK32UTTdVm6rYgXo5Xx5YotEtR18Qd10fSQTKZAhhBC2iV4tjOCZwyEo2gscEgwDsBjcB/PSXCJCDN9+nTp0aOHEnuEgRD9kksu2Wv+CMHeuXNnJbgIA4EABv4hzogG3A3wPHXeeeeZwgFBZABHjMZiFTSg7iDAAAsXLpR4QV0BOIUYsbpZQIyAkBrHH3+8eo9yhJff//73ysnCWh64dhhdRMJiEeO1agogzNh///3VZAfj5Ae4c6DfIdZkATibIIwJXOGN4gvQmEkGb7/9tjpPiE2MdXTEEUco8QpCyQCEkqmsrFTtihBCSNsgrukCiEmGGGKYUYebhfDMumXLlillKSyUwrG2CCGEEEKIiC1Us8RDvPu3VTDTBLNV0OkR7oSBm8JJJ52kXtsK4bi96IgKz56BsNnaeYPOQnSWQdDQGFAvmDH03HPPqQ6xsFMF3DbQ0YNyhN01cN+O9ej8Q+djGMwUQ6fPQw89pGLchkFcXogtwjPJwjO4Is1EwswoxPWFLS9cNYydaoQQ0lrIy0qVXeVe0UIhWZIf3emTtDxwvagRYITU+745adI5rfEhYgghhLReIADHbP8wcCSAwKGxwPHPOjCOwW6jWwNEHgMHDtwj3ZAhQ/aaP8JsIYzIa6+9poTmHo9HCdADgUBMAUZY4B52PbAet7FiCQgJECLjjTfekB07dpi2QfQQLyg3hAfW529rXe3cuVO5I8JdBEskrOVD+A3rdQKxHNgbC/oVEBYF5wO3ETwf45oZn28jAbcKnH88Ihkjq1evVm0R4Vli1REcR+DYAdcWuIDAJQUhdRBehxBCSDsUYECRiQ5w/Fg9/vjjpm344YJtE9IQQgghhBASzywoWH2iUwKzQxATti0DW1ks4Ntvv1WdKYjl2tSgwwq2pXDQQOgWWJmiU/Cxxx5TnYvheLLgp59+kkMPPVSJql966SXTLCQIq7EPOuwOOugg5ULy5JNPKgGHUXABm9dIfPLJJ+oVwu144hkTQkhzCzAWbS2SoBaSzSUVUuELSJrHxUpvBcxeVyBl3oD4g5pyKJnUj+FhCCGkvXL99derZ7+PPvpIhfD4z3/+E1d+0cI1NCZcRDTgygixORwUIILHQPnQoUObzBk8mrMCHBKsYFB+zpw5ct1118no0aOVqB+ODRiox2tLET4WnhfxjBkJ6ySElrhWxmt29dVXKxeMm2++WY1jQfxTH9FNPFivGeoJ42do99HcOkDXrl2VYwpCkKCdYXnxxReVkIQToAkhpHUSd8DMY489VnWmomMcCkAABeTYsWP3sGEihBBCCOnwNEUYkQ7igAGxwCmnnCKfffZZ7Tp0wiG+LkJ0tAdmzpzZrPlDdIF4uxBioFMH7hMQsSDmrbXDKxLoBIPNLJw6YKv7+uuvK4cMxKKF7SrjzxJC2gt5WWmC8Q108iPExcrtJTKud+TZiKTlwPWYvnSTEl74NV1yUj3Sv3M6LwEhhLRTEPoDg+EtCSaSLlmyRP3mGMUOK1eurNf+EKnjGQnPSwcccIB88803csstt+z1mGEHBCvW44adIOAoYcQaJhJOEV9//bVywMCzWphIx2gsKDdEAxgHMooVrGXG5In09HQlOEA4jaaiIWE+YqWFMyPGtSDAQNiR2bNnmyYoRAPjXjh/OMBD4BINXDPr9fL7/Sr0jDW/ioqKetURnuUR0gULyoCJHBD+3HrrrcrBhRBCSDsTYBjjQ2MhDSOYFhJ7Rs0oSjDdokK1hyK/r6l106eQRevi62lQU1rEsDuzLftmW+Jwl9U1i9T/Z+8+wKworwaOn1u290LvAiqgggVEUMBobFHsxt67sffYjRpLjEYNapTY9YsdY4lRAbtgCSjSROmd7f3W7znvess7W2GX3WX3/9P77J3+zjtz2bszZ85ZZUee+rLtNrpC9rqCybF2BtLsafn5ZdbwjrnrreENGbGLKMsTc61pFRtS7TYGHPuQFoi+T9iQ0Gia9qAjU2kwJbZPwezYegxHvwYq7HW7/bF2uBz9HEyyN1zV3W5zoiPrWyA1Nt3vuJ7kcRyilDWObcVl8q7Js7fjrrZ3IhS3v6bdcYOJxXabvVX2drxl9rqru8cWDqQ51hu0501d4274XMm1+92faS+bUGKfh95yV73rUWHHd2tvts8a3iU31nlJbr81bUGS/STVwqA9XFkWO3m8lfZ2fL9+jiMSS+yGpK21p/vTY9M9NY5zpZu9bMiRqT0c9+9B2O043o5T2JdjH5dQYmz+TEcJxZqMza9VCGDzUYKk+f7yl7+YJzv0ySG9IKEXdTSbgtbi7Yy1T7UMSEFBQb1P+DjTsW4OrWUcX8+4PprNoqEni/SpqXvvvde8toRm1IjPqgEAHVFmcoLJeOELhCQQDMn8dUUEYHQA89YWycqiClN6REuQjBnQfYtqrAMA0BB9uFSD/F999VU59thjo3+bNVQ6w0kfQtW/t/75z3/KmDFjJBAINFp+RGnAht7A1+wF1113nSkFqfTvXL25HwnQUPpeA9+1NKRm2IjQrITxIsHxzr/rmhNY0FxaAkMzRmh5Si012dA2tC2R0iwa3LLTTjvVKVHSUNmNxqSlpTW7lIrOqzQQIjs7u850LTeiD3xothBtr2bFaIr2v5be1AcU9HyJfwA5PoBHAyv0eMXT88mZAUMzltx6660ms8WBBx5oTdN269/iWuZGrxPogxURut3IAxX64AoAoJMGYHz66afml8T69evN03CaYksj97RWmf4iqO8XHAAAANAYTd06evRok0I1cjFJL05pNgfnBYhtlV6k0f3RC1jOp2Hi1ZdeFgDQevSCeZ+sNCmu9EkoLPLDmkK6twN4Z94KCYXDJvtFstctI/tu+7/7AQAdyznnnGPKq2s5B83yrcERzz33nMnG0VwacKFlG2+55RbZeeedZdiwYU0u8+c//9lkYdCsGWeeeaYUFhaadYwYMcLcW4nQ4AwNDImUktSb+/pgwoYNG6z1ZWZmmmwcGjjv9/ulT58+JrBk6dKl0lo0aOSEE04wwR8aCDFu3DiTdUPLxjjdfffdJuPjnnvuafp4+PDhZh/1ntGHH35o3m+u3Xff3WQaueKKK8y1Ag1Q0IwQDc2rLrnkEhPc4Ayy0L7XawqvvPKKCSzRMh9N0UwTmt3kT3/6k8ksqQEcSUlJ8vXXX0vv3r3NMVVnn322KQWqQShaYkTLeOr9s/z8fGt9Gvyh5XYOPfRQOf30002bKyoq5IcffjABHsuWLTPL6Pq0v37zm9+Ysp6a/UTPBz0ezTnXAADbWACGpjrSOl76Sy8S4ae/gDUAQyPzDj/8cJPq+Prrr2+9FgMAAGzLKEHSbJrWVC9sxJe50PqxekFJ06h2hgCMG2+80Vyk0YsmevGmM+wTAGyr+uakyYJ1RSbTwi+bSqUmEJQkb/31yLH1rSqukLmrC0z2C33tObC7eCl1CwBoZRpooUEEF198sbmprcNalkJvyh900EHNWocGIvTr109WrlzZZPaLCF233vzXvwn1/okGVjz11FMybdo0mTlzpjWvtkuDKh577DFzw18zJ2ggvzOzhGac0P3Q7BR6v+aAAw4wWSU1OKC1aKYPzV6h5TvefPNNExTwzjvvmP2P16NHD5k9e7bJFvH666+boA39e1cDTO65554t2raW3ZgzZ47ppwceeMBkB2koAEP/vta++L//+z9T1kb7Iz4AQ0t66LHSdmk2jObS/dGSqHpMNBhDzxd9CDl+HRpwooEvU6dONSVVNVhDs5vst99+1rp02Y8//ljuuusucy48++yzJpBm++23N6VkIplR9B6cZtDQtmpmjJ49e5q2a/aM+CwcAICOwxVuKNdwM+jFb/1yoOmhNVWXXjjW6EX9pas0cnPx4sXy2WeftWabO4Uff/zRfEHqd/nVktijZ70lSMKJsWFPmX3RJ6HU3WgJEl9+wyVInKUhwjn+ZpcgqezpLJPiGKyJrTupyFGCYp+NjZcgqYorQVJglyCpaUEJEke1Fgk5w47iapQ0VYIkYZ297sRSV4PrdZYgcQcaL0ESfwx9td+tGi5BssFedzCurESN475NTW6o0RIkyWtjDU9d23gJkrL+DZcgcZbJaaoESXVewyVIJK60S70lSCoaLkHi9tnLBna0a4UcOHRBwyVISh0lSFbaw0lLGi5BUp3fPiVI4j9zZtjRlVWOz2x83zlLkDjLt3zzp0ftEUAn8eOiGtll0kqTBlP/8G/r3/1DTrlGkvPtf182V/WmdbLkuXvbfB/aml5I0AslJ554YnScZr7Qiz16gWzfffeVbZ0+vaLHUC/KkFK98c9Oe5/vi9YVyDeLlprzLzHB8X2ziwkHgxKoLBNvaoa44gKkuhr6ofP1xcbyKnnmq8VSHQhKWqJX7po8Rkb0sv82bYreHIlkaUro4v9WtLQvnvxigXy4aLWU1/hNAMbFE0dIepLjj6NtQGf5fLQG+iKmqLxSQpXlsvdOQ6RHVnqX/o4FAO3l8ssvN0ES69at26yMJwAANKVF4XFay1kj+/QXlTN9ktKAjF9+cdzhAwAA6MJcrfTq6loQQ9yh6I0pfTKH4AsAaH95acmSnOARt8tlsmDMX1vc3k3qssqq/fLpknUS+DX7xQ7ds7fJ4AsAANAxVVdXmwc+tEwIwRcAgA5VgkSDKzT4oiG5ublbVMsLAAAAUJp+VeueRlRWVppgBU13+tVXX1mdpOO3tdJ3mlp040Y7SxgAoH1o4EXvrDQprymWYCgsP6wpkGN3247D0Q4+XLRKfMGg+IIhcyzGbdeD4wAAAFpsw4YNJov7q6++ah6IuPTSS+lVAEDHCsDQyECtOdVYgIYGYQAAACBO50je0Ca0Dqq+nLTmq9O2GIBx1VVXyU033SSXXHKJqfUKAGhffXPSZMnGEpMB46eNJebmv8dN7qm2pBkv/rtglTkG/kBI+manSc9M0oIDAICWmz9/vpx00knSvXt3eeihh2TUqFF0KwCgYwVg7LnnnvLyyy/L1VdfXWdaRUWFPPPMM7LPPvu0ZBOdnqfSJd7y2os5yRvtWqDugKfBGzXBJHvYn2nP4KqJXSAKJ9jTwl572J0YtIZD7thpUdXNnjeUbs/rrrDbnFgc267LnlVKylOs4e9q+lnDFZviLqiE7AtcicV2tZywo3iOuyRWT9YVtJd1Bex5EyrtYV9mbP7EosZTmrocx8GfFhvhqba3m7nUnjfguF7kd5T49Kc3vK7EUnvesKNsbE1O7H0w2XG8c/zWsNsTsrebGevMQIndsWkb7M7zldj/ZIQ9sflDjvPM7TgOIUebU9fGpgfijl99545zOP5892fZ+5PgOFcCZfa6vy/sHX2/ocQ+CDUF9jmaUGw3unqAL27F9v55ixr/57Squ6vB4x1MtucNO060ULe47aq4/kpwnBuJG+3tJBXa/RF/ftRkOz4rdlcC2Er0I+78fbIl6+gKZsyYIV2hlErv3r1N6b6zzjpLBg0aJJ566sOfeuqp7dI+AOhq+mSlmYC+UDgkVf6gLCssk8H5BMi1pa+WrpfiKp8JxAiEQrIX2S8AAEArmTRpUqcpaQoA6KQBGNdcc43sv//+cswxx5gLxmrFihXy5ptvyq233mrSOelTfQAAAMDmmjhxYqfvtNNPPz36/o477qh3Hr0RSAAGALSNnpkpkuBxiy8QNAEAC9YVEYDRhvSGyLvzV0owHDLHICslUYZ2y2rLJgAAAAAA0CKOPAKbZ99995UnnnhC3n33XTn00EPNOA3EOProo2Xx4sUydepUGT169Bate9OmTXLmmWfKyJEjJS8vT5KTk80Tgccff7x89913deYPBAJyzz33yA477CBJSUnmScILLrjA1PGqj47X6Tqfzq/L3XvvvWY99fn+++/lsMMOk5ycHElLS5OxY8eaQBMAAIDNEm6lFzpNlo+mXtOnT2/vZgJAl+Fxu6VXZqq43ZoFIyw/rCls7yZ1KQvXF8uygjJTekRLkIwZ0F3cLkrAAAAAAAC6SAYMpUESv/vd70xt7oULF0ooFJLtt99ejjvuOBPcsKWKi4vN+jTDxoABA0zQw7Jly+Tpp582pU/efvttOfDAA6Pzn3HGGfL888+bQBDNurF06VJ58MEH5bPPPpOvvvrKLB9RVlYmEyZMkEWLFsmFF14ou+yyi3zyySdy7bXXyoIFC+rUFJ87d67svffeJlDjyiuvlPz8fLOtI4880swb/+QiAABAo1ojgIIAjE6jK2T5AIBtTZ/sNFN6JBQKy4J1xSYrg2Yjwtb37o8rTH/7giGTiWTXfvl0OwAAAACgawRglJeXyyWXXCIHHXSQCbb4wx/+0KoNGzJkiHzxxRd1xmvWiv79+5tsF5EADH0qUAMiJk+eLNOmTYvOu/vuu5vyKPfff7/cfPPN0fH33XefzJ8/34y/4oorzLizzz5bsrKy5JFHHjHBHBqgEXHxxRdLRUWFeQJxjz32iGb60ECQyy+/XI466ijJzKQmLAAAAAAA27q+2Wkm60IgHJLSap+sLqk047B1rS+tlG9XbDLBF4FgSPbo380EYQAAAAAA0CUCMNLT0+Wll16S8ePHS1vq0aOHpKSkmAwZEc8++6z5GQmmiNBSKAMHDjTT4wMwdDg1NdUEc8TT7BYagKHTIwEYmnXj008/lUmTJkWDL1RCQoIJQNFgjbfeektOPvnkrbbPAACg83CFa18tXQe2XS+++OJmL3PiiSdulbYAAOrqnZUaLXsRCIVMWQwCMLa+/yxYKSHR7BdBk+xr7KDunJ4AAAAAgK5VgkRLjaxatUq2Jr/fLyUlJRIIBGTFihUma4Vm39BSIxGzZs0St9stY8eOrbP8XnvtZQJFCgsLJTc3V9avXy/Lly+XcePGmUCOeBqs0atXL5k9e7a1bqXzO0XG6fwEYAAAgGahBEmXp98bm5vKPpL2ngAMAGg7iV6P9MhIkZVF5RIMhWXemkLZf4c+HIKtqNIXkJk/rTWZLwLBsGzfPUsykhPpcwAAAABA1wrAuPDCC+VPf/qT+dmtWzfZGj7//HPZd999o8NaJuTaa6+1MlpoEEh+fr4kJSXVWb5v377ReTQAIxIwEhlf3/xLliyx1t3Q/PHrbsyGDRtk48aN1rj4bQAAAKDreOqpp9q7CQCAJvTJTpPVJRUSCoflx7WF9NdWNn3xaqn2B2vLj4RCMm67HvQ5AAAAAKDrBWBoBonu3bvLjjvuKKeffroMHTrUlPZwOvXUU7d4GyNHjpQPPvhAampqZPHixfLcc89JWVmZGfZ6a5tfWVkpOTk59S6fnJwcnSf+Z33BGpH5I/M0Nb9z3Q2ZMmWK3HbbbfVOC3tEwr8eherudj5xa8hR9jSU4JjXaw8nr/fE5k20p/myQ9ZwsMo+DVzpgdg0R5lb58Oa3g32su7YolK+g8+alpHkt4ZrahKsYU9prM2eGntDQceDL/HbcaruZU/0ZNrtsIdEgpWxfXDVxNqgEorsjnf77Ha5/bFhf4bdzwU97X4OJ9vDTinLYv2RWGpPq+jbyLnhmN/fx97Dcdv/bA1nJlRbw//Ljz3JtSlop3h1hezjW9nT0Y647glkBa1pnnK7L72Okyf+GIbsU0FCKY7tOKfHne9hjz1vIC3caDtWrsiPm9luU9oyb4P7pxJ3qIq+75ZRbk1bX5JhDfsX28OhpHCD504gp5ETWkRy88rsdeXEGlayLNuallzo+OwkN1ynoCbXnuYKNu9pbAAtRwmRru20005r7yYAAJqgJUe+WeEyGRk2lVdLQUW15KXVXgNA69IsI/+Zv9IEXviDIVMCpneW42IEAAAAAABdIQBDgy4iHnjggXrn0ZTJLQnA0MCK/fff37z/3e9+Z7apQRm//PKLvPfee2a8Bn1oQEZ9qqtrbzZHAkMiPxubPz6IpLH5netuiGYIOfbYY+tkwDjiiCMaXQ4AAHRClCABAGCbyIChMeT6azsQCsvCdcUyfnDP9m5WpzR7+QYpqKgxwRca8DJ2INkvAAAAAABdNABjxowZ0tY0IGPy5Mny97//XZYtWyYDBw40pUA0O4YGSTgzVThLiDRVNkTHx5cbaWz+psqZRGiWEH0BAABo9ouWZsAggwYAAFtXaqJXclOTZF1plQRDIflhbSEBGFvJuz+uMKVefIGgZCQnyI497Sx/AAAAAAB06gCMZ599ViZMmGACHyZOnCjtoaqqtgxAUVGRaceYMWNk4cKFMmvWLNO2eF9++aUMHjxYcnNzzXCPHj2kf//+MmfOHLMeLaMSsXz5clm7dq0ccsgh0XG67sh6nCLjIvMAAAAAAIDOoW92umwsq5ZgOCw/ri1q7+Z0Sj9tKJElG0vFFwyaTCN79O8mbmftUwAAAAAAtiHuzV3gjDPOkC+++CI6XFpaagIQvvnmm1Zt2Pr16+sdr1kv3nzzTcnKypJhw4aZcaeccor5ef/991vzvv7662b+yPQIHa6srJRHH33UGh9ZPn7+QYMGyfjx42XmzJny7bffRscHAgF56KGHTDsOO+ywFu8vAADoYiVIWvoCAABbvQyJ2+2SUEhkVXG5lFX76fFW9u78FRI22S9C4nG7TAAGAAAAAABdKgOG/mEcz+/3m+ALDcRoTX/+85/lgw8+MNkoNMuFy+WSBQsWmAwc5eXl8swzz0hycrKZd//995cTTjhBXnrpJRMMcfjhh8vSpUvlgQcekOHDh8uVV15prfuaa66RV1991fzUAI2RI0fKxx9/LM8995wJvnBm9tBAC82sceCBB8rll18u+fn5Zt7vvvtOpk6daoIwAAAAmqU1AigIwAAAYKvrm50mmowhLGEJhsKyeEOx7E6AQKvZVF4ts5ZtEH8wJIFgSEb1y5NEr6f1NgAAAAAAwLYQgNFWDj30UFm9erUJlNiwYYPJONGrVy8z/tJLL61T9kMDMnbeeWd56qmn5KKLLjIlRzSY4s4775T09HRr3szMTPn000/lxhtvlFdeeUUef/xxGTBggAn6uOqqq+q0ZbfddpPPP/9cbrjhBrnvvvvE5/OZbb322mty1FFHbfW+AAAAAAAAbSszOUHSkxJMdgYNENAyJARgtJ73F6yUkGa/CAYlJCJjB/ZoxbUDAAAAANA+OmwAhma10FdzJSQkyPXXX29ezdGtWzcTeKGv5tAsGW+//ba0tsRSkaSE2vfBCrvOaejX8SrsKBbj8dnz+rLtR2G9lXEDlc76qfbKXJvsJ0z8GbF1BbMD1rRwwF6XPytkrzkQW5e3MG4HtBlF2Y422utKCMa1Ke69GbabIe5Aw9NTV9indU2OvX+hZLvNiaWx/vCWO/rKMRjfN8pTHZshZYM9c2Vvx8I1djucxzSe229vx+2zp3sd50rm8tg+VQ62p62vyrCGV5Tl2NPXx46Ly2tvt7KXs13S4D64fO5G+1kqHfsfN+hznEfhJLsdGT/ZywaTYvsYSLW368u3T56Qy7GuhbHz0hVqfP8qe9jL+jalRt9XlNRm4Gno+CY5ztHkAsfnLm7bIW/j50Zh2JFlJ+5zmFjm+HfD8cCYu8b5b0Vsw0lF9oYSyuxlAWwd+s+S45+mLVoHAADYujQTp2bBKK70SSgs8sOaQrq8lVT5AzJ98WoJBMPiD4ZlcH6G5KQm0b8AAAAAgG1eI7eAAQAAsFXLkGzpqwP4+9//bm5M6WvVqlX1zvP666/L2LFjJS0tTXJycmTy5Mkyb968Nm9rR6f9d9ZZZ0nfvn0lMTFRpk+fbsZrFrgzzzxTvv766/ZuIgB0WRqA4XaJydSwtKBUqv2OpwWwRT7+aa1U+oIm+0UwFJLx25H9AgAAAADQhTNgTJs2TZYtW2beV1ZWmgvvL7zwgnz11Vd15tVpzc1KAQAAgI5vxYoVct1115kyb+Xl5fXOM3XqVDn77LNlp512knvuuUeqq6vl4YcflnHjxpnSblrODSLLly+XPffc03yn1mCVtWvXRrule/fuJvhCgzJGjx5NdwFAO+ibnS5ul0tC4ZD4gyFZsrFEduqdy7FoAQ1m+c/8lSbwQvu0e0aK9MuxMzcCAAAAANClAjBeeeUV84r31FNP1TsvARgAAABx343CYfNqiZYu31LnnXee7Ljjjub1/PPP15leVFQkV1xxhcnooMEWmZmZZvxxxx0nw4cPl0svvTSa5aGru/HGG81PzQySmppqgi7iHXLIIVulDB4AoHly05IkOcEjvmBIAqGwzF9XRABGC323cpOsL6uq7dNgSMYOIvsFAAAAAKALB2DMmDFj67QEAACgK2iNMiLtGH/x7LPPygcffGAyM/ztb39rMFtaaWmpCcKIBF+o/v37yzHHHCPPPPOMrFy5Uvr16yddnfblBRdcYPqmoKCgzvQBAwbI6tWr26VtAAAx2S/6ZKdJ+fpiCYbCMm9NoRy322C6pgXe/XGFyYLhCwQlLSlBRvTKoT8BAAAAAF03AGPixIlbpyUAAABdgCtc+2rpOtSSJUvqTOvWrVudLAqtZf369XL55Zeb16677trgfLNmzTI/tdyIk47TAAwN4CAAozZbSJ8+fRrsy1AoJD6fr5WOIABgS2gAxk8bSkwGjMXmZ0i8bjeduQWWFZTJgnXF4g8GTX/u1S/fBLkAAAAAANClS5AAAACg/R1xxBF1xt1yyy1y6623bpXt/eEPf5CsrCy57bbbGp1v1apV5qeWIHGKjIvM09X17t1bFi9e3OB0DVQZNGhQm7YJAGDrm51myquGwiGp8gdNEMGQbll00xZ458cVEg6HpSYQMoEXowdsnaBRAAAAAADaCwEY7SzsEgn/+uCMt8qeFgrG3ieW2I/KugP2vJ5q+4mRhIrY/FXd7WnBZGcj7HUnFsfmdxckWNO8ldLoumqyY+sKJdjrDefaT2/WVHvsdZfETkdX0LGdJHtdzieHkzfGnj4KONqUvMnZN/Z2a7Jj71M22SuuyXYsW9rwkzkhu6vE7bPndYXs6cEkezgct7w/07Hdcnve7J/sDioeHNsnl6Nff55nP1WbWGw/qZXYyGPYen5a85bYIyLnrmljmWOa3QypybM7IJQYd54FHMs6+iqp2NHGuMHKXvayPse6PH5Xg8cpodRerSvUxCPp8ZP9dj96ix3nc6XjGJbZ606oDDd4XjnPlaoeDX8Ok4rs9To/d9VuR9+Wx4b9afa8qevs7QLo+CVI3nzzTRkyZEidDBgN2ZzAjEmTJplXxBtvvCGvvvqqvP/++5KamtrospWVtf9QJSU5ftnp7+XkZGueru7QQw+VqVOnykUXXSTp6enWtJkzZ8pLL70kV199dbu1DwAg0iMjRRI8blMyQ7NfaAYHAjA2X1FljXy5dL34QyHTjzv1zpXkBMcfjgAAAAAAbOMIwAAAANhGS5Bo8MWIESOavVxTmSucIgEYxcXFJkDgpJNOkgMOOKDJ5SIBGjU1NXWmVVdXW/N0dTfddJMJpNl9993lkEMOMU9YP/HEE/LQQw/JO++8I/3795drrrmmvZsJAF2ax+2WXlmp8sumUgmFw/LDmgI5bOcB7d2sbc5/F6ySoJbWCoQkFArL+EE92rtJAAAAAAC0OgIwAAAAughN+b0ltKxJJAhjyZIl0fFlZWXm57Jly0xgxeDBg00AQXyZkWHDhjW7PElX1L17d/nyyy/l4osvlhdffNEco3/961/idrtNQMZjjz1myr4AANq/DImWHtHAgQXri00ghpbQQPPUBILy4aJVEgiFxR8MycC8DMlNc6bnBAAAAABg20cABgAAQFtraQmSNrZ8+XKpqqqScePG1Tt9n332MT91Hi0xMmbMGBM4oIEFv/3tb615dZwaPXp0G7R826DBKFripbS0VBYvXiyhUMhkN8nNzW3vpgEA4gIwNOAiEA5JWbVf1hRXSN8cu3QUGvbpz+ukvCYQLeMyfruedBcAAAAAoFMiAAMAAKAttUIJkrYO4Lj22mvl5JNPrjP+73//u8ycOVMef/xxEyyQmJhoxh9xxBFy6aWXmlIal112mWRmZprxK1askFdeecWUNunXr1/b7sQ2QPtpjz32aO9mAADq0SszNZrxQgMIFq4vJgCjmTRbyHs/rqgtPxIMSX56sgzIJXgFAAAAANA5EYABAACARu211171jn/77bfNTy2VEV9SJCcnR+677z45//zzZfz48XLeeedJTU2NPPzww6ZEyYMPPkiP16OyslIKCgrqLRXTv39/+gwA2lGi1yM9MlJkZVG5BENh+WFNoey/I+W0muOHNUWypqTSlB4JBMMydmB3830AAAAAAIDOiAAMAACAtqT31rexDBhbQoMu8vLyTCDGNddcY7JjaKmSO++8U3bZZZf2bl6HoeVGtI80OGXt2rUNzhcMBtu0XQCAuvpkp8nqkgqT0WH+uiK6qJn+s2Cl6bOaYEhSEj2yc29KbAEAWt/IP78aff/kiRNk9IDubd7NXy/fIGe/+El0eO71x8i2rLPtz+aa9v0yufmdb8z73lmp8t6FhzR72VnL1su5L31q3l/721Fy4h5DZFtUUFEth0x5T6oDQfndiP5y1+Qx7d0kANgmEIDRzoLJIoGUXwciP3/lz4rdXanobU9LXWs/LeJMZR5Ijk33VNnTEovsZWvyQvZ2M2LvQ8n2it019rKeGnvdrrh7A66APW9uXrk13Cuj1BpeVpQTa8P/Yu9VQqm9ruoedpur8+La6bbbnFjqtoZr7FVLdY9Yo6u72dvxVtjzJhfY00Nxn6DUdfZ2wx5HP+fY0132LojEDbsd/Rr22MO+DHufgnHnTtjjOBmS7Bs24dIEazhlQ9y54rOXDSU498Fetac69j7BPrwSSnS0Oeg4d6piw95Ke95AqqOfHfsUSHPVf+xNmxr/bFhtyrKHw27HU1iOc8ldETsQoWT7ACY6ztGU9fay/gxXg30btg+neKsdx8HTyOfM8ZR0INVxbjiOQ0JZXDscWX99cZ99AFuPqxVKkLS4hEkrefrpp82rIcccc4x5oWFXX321PPDAAzJq1CjTV5o9BADQMfXNTpNvVrgkEAzJpvJq89JyGojRQIvvVxfIBwtXyferC6Wooko2Vfok0eMRt1tk4uBe4tE3AIBOZXVxhRzy6HtNzjf76iMlyeu40NVIIEWEx+WStCSvDMzNkP126CPH7z5EkhMaX8/WMH3xalm0vti836FHtvxm+z6yrdFSah8tWi3vL1gl89cWSWFltXjdbumWniI79siWA4b1lYlDe5lx2PLvQ/d/9L15n5+WLEePGlTvfNr/b36/TP63apOsLa2UKl9AMpMTJTctSbbvni37DO4pE4f0krSkhEY/Z163SzKSE2VwfqYcNLyfHDVykHgc17njP1fn7z1MLthnhDX94CnvmoxlavLOA+RPh4427/N+bf8L3yyRd39cISePHirDe3HdAgCaQgAGAABAW9LAqXpKTGz2OtApPPfcc3L44YfLG2+80d5NAQA0IwOGVs7Q38KBUFgWri+SvdN70W+/WlNSIX/56HtZvKFYSqv94pKwVPuD4g+GpSYQFJe45KeNJTKyX77kpibRbwDQyeSlJcn0Sw7brMCK5gqGw+Z3y/drCs3r81/WyT9OmNDmJa1mLF4jb/2wPHqTelsLwFhVVC5XvzmrTiavGglJRWGZLCssM5mr3r3gYPO9B1tm+uI1smhDiXl/5MiBdYKO9PvRne9/Fz2X4hVW1pjXko2lJuDh7sP3lIOH92t0e/q9tKiyRr5ZsdG8NBg2EkDRGjR7hwZg6Hfgf3y+QB48ZlyrrRsAOisCMAAAAIB2UlVVJQcffDD9DwDbgNREr+SlJpsnFIOhkMxbUyR7DyYAIxJ8ceO/v5Ylm0olxeuRHumapjEsK4rKxevRrCFh83NZYbk8P/snOXnMUIIwAABNOnyXgXLELgOlpMonT3+1SOasLjDjZy/Xm8yFMrJvHr3YTHpT/5yXPolmOdAECYfuNEAmDu0tmckJsqGsSr74Zb3JYoWWefm7n6PvtY+drnnzK/l4SawE6fCeOSZQY0BuugRDYVlVXCFfL98on8TNU5+zx+0o47frKRvLq+SxT+fLLwVlZrwGdlw8cSfpnuFIub6F+uakyy69c03wk7ZpfVmV9GildQNAZ0UABgAAQBvS53NaXIKktRqDdrfHHnvI0qVL27sZAIBm0qdB9QaFPon7o+Pp0a6cZlszX2jwRXZKoqQl1qbJ1pTmJvGXfndxuUzAhT6hua60Ut6Yu1TOGLuDuNv4yWUAwLalV2aK7NYv37zvnpEsJz49PTptTWmljJT6AzBCYZEXv1kir3z3s6wsrpCc1CQ5fOcBpuyClmYorfbJAY+8I1X+2jq/r59zgCnfEF8a4oSnPzLv0xK9JgvBxa98bm1Db3JHMhj0zkqV9y48pE47ymv88uin8+W/C1eZDAX9ctLlvPHDTJmIiK+Xb5CzX/wkOjz9kkNN+YpPf15rfseOHtBdrvvtKHPD+1/f/Wz2S4MoemakyEmjh8oJewxpVl9O+eTHaPCF0gwJzuAAHb5owgjz+7w+zdmfsmq/PDTzB1m0odhsT4f1e5N+D9ilT64pYTGqb+0xra/8xe2/28P81IwLSzeVmvIbB+zYV674zS5W2ZktWUatKCyX52Yvlq+WbZD1ZZXmO4qWttF9OGmPIZLYRImc5gS6zF62wbzvn5MuA/Psms/vL1hpBV9oJpVbD9mjTsmQ43YbbPq4yh9ocFu6/sjnQ79TXfXGV9Fp+n2rtQIw1IQhvUwAhh7LDxasMsG0EdO+XyY3v/NNo58FAOhqCMAAAABoS3oXoqUVRKhA0mnccccdMnnyZDn66KNNMAYAoOMHYMxdXSCBgD6dWG5uKmQk1wYcdFWa5lrLjmjmi0jwRTgcNn1jvvaEw+ZmhtfjFr2n4Q+GZE1xpSwvKJNBcTe7AADY3OCMhtz34VxT9ipCgyef+GKhuTGvAYCZyYnyu50GyKv/+8VMf33OL3L1/qOi87+/cGX0/YHD+kmK4yZ+c53+3EyrHb9sKpVrp80yN6l36VN/8MiZz39sSoHElz35eWOpjB3YXV7+tb1KA0vu/mCO5KYlmTY2Rn/3vjd/RXR49IBu9WZmUI2VHmnO/mhwS3w7IzRrwgcLV8tHi1bLA0ePk0lDe9e7jSe/WGgyaEX4KmtM4Il+n7jhoN1atMynS9bKVW9+ZUqAxFu4vti8Ply4Sp44caLJeralvluxMXrJRgNOnN76PlZ2JC3Ra4JrnMEXERo4lCNbVratR2aqtKb4ffl6xQYrAAMAUBcBGAAAAEA7GT9+vDz99NMybtw4GTt2rAwaNEg8Hvvinj6RM3XqVI4RAHQAfbPTRJM2hCVsUkTr05179O8mXZmmKi+t9v9adqRWuc9v+qe2p0TS425kpCZ6pKTKb9LIE4ABAGjM2tIq+W7lJnNTX0uQRIzqmycjGwhgiAQGnL/3MBnRK1eembVIvlmxyYx/4eufTACGOn73wdEAjLfnrZBLJ+0czX6ggQIRWhpiUF6mPHXyJJn6xUL57Jd1Zvze2/WUs8btaN4ned31tmNTeZXccsjukp6YIPd9NNcEgijNYtFQAIYvGJR7Dt/T7PNd7//P/B7V4AJ9aZv3GdxTnvh8YbQci+5TUwEYumx5TSyTwrhBPWRLNGd/0pMS5IJ9hsuA3AzJTEqQpASPVPsD8uXSDfL81z+Z7CQPfzyvwQAMbesJuw+R8dv1kGk/LIsei9fnLpXLf7NLvcERzVlGs0lc99asaPDFQcP6yaE79ZeaQFCe/HKhLFhXLPPWFslfp38vNzYQ6NEc8QEqmlnDKT6Dmp7DGhQUsaqoXDaUV1vza/DPsJ459W5L91s/H5vKq+Wxz+ZHxx8yvF+rlwiJ35fFG2L7CACoHwEYAAAAbcgVqn21dB3oHL7++ms59dRTJRAIyGeffWZeTgRgAEDHkZWSKBlJCeILhCQQDMmPa4u6fADGvDVFpjyax+OSSp9fymr8UukL/Jr9QsxTnUlx6bw97tqbVMsLY0+qAgBQHy1toK8Ir9slx+8+RC7cZ7j5O6khx+y6nSk3orScxinPzjDvN5ZXS0WN39z0Htoty2SC+Hr5Rimu8pnMDAeP6C/z1hTK6uIKM/92+ZnRwAIt9fBGWiwbgWaeiJR/aMgfD9xNDhjW17zXzFl/mznPvI/PcOF0w4G7yt6De5n3L337swkmUTv1ypHrD9jVvNfSKXPeqA3AWFbQ9O9TDeaIl52yZVkVmrM/+l1p51658vL/fjbfkzTwQUuQxVuysTR6HJw0wOS6A2qzkQzvlRMNptB16HEZ2j1ri5bR0h+RIJRemany+90Hm/fahmNGbSd/+s93ZvjfPyyXa/YfucWlSIoqfVZfOJXFHYvsVPs4PDv7J5O5wxn4MO28AxvM/KGviLREr5y65/Zy1l61gUGtKSvunNEyK/EO32WgeQEAYgjAaGeugIjbX/s+5Ph9HI4LnA0l2l9Sqrvb84YS7OnumtgX0KRi+8uo1w6iFM9aO0I3HPfdosaRJSuQYm/HW2Uvm1IbTGyUDrHvDnk9dmovX9D+ElNTE/vCFUy3t5Oy0bEP5Y4v2PGzO758Bx396ra/b4o7bh+c/ewKN75sQllshoQqx8xhux0e+3uJuAP29LA3trzLsazbsWwgWRrc/5TV9se6urvd72HH91qPL9xgG/3pjjb/eq7Wx1Nj73/Ia+9D2kp7OJTQ8HZcdpMlkGovG4jLoJZQ4TjeyY3n5Q+kxqb7M+x5U9fY57PzOPjjzkuP49x3iu9Xw/G3UEXv2LqDSeEGP4Mq0RFU7K2MzV860G6Hc13eSnsfkjfFpqfWBuzHlq2/vCOA1kYJEsS57LLLxO12yxtvvCETJ06U7Oxs+gcAOri+2enm4rreS/hhTaF0ZZraW29aaUCK1lSvzXpRm/dCgy90yJQlcfwJr3+26xOnAABsDr2hrqXAqgPBem/eR4wZ2L3BYIOSal902RP3GGICMNRrc5eaAIz/LlwVnfeIFt5U3rOBdpRUOS4yxxnZJxbUocEjsfF59Y7X/WmKllyJV1zluAjcivujATM3v/NNk+vS7Fn1HcP4Y+cMYGhoX5uzjJZxiVhbWilnPD+z3nXpuaWZJYZ0qxvo0RoykhNNUIpp2xYeh4ZU+AImgEi/jzmr5uhXschVYf2O5hSKG1lfcFNtTjMAQHM1fgcRAAAAwFYzZ84cufrqq+Xwww8n+AIAthFaG93tcpkL1csKSuvUEe8KCiqqa58QnTZL1pdVmmAKvSmmfRLU16/vkzxuSXXeAfj1wn98VgwAAOqjZUS+vfYomXrSxGjQgQY/3vDvrxvtsKzk2I19zcTk/B0UMXFIb+mdVfuk1zfLN8rywjJTWiuSbUNLVLREfDCAsx0NyYhre/wi8eM3V/+cdElPij209+XS9Vttf+IzMmjWjvuPHGvKt9x9+J4N3vC3thEXLOL9NWtWfODnli7TWMYUJ83ktaVyUhMbDbQZEVdO5PvVhda2/njgrjL3+mPMed8ct/9uD/nmmqPk/qP2ipbB+fTndXLvh3PqzKulYSIiASDx4sdlxJ0r9e1LriNzBwCgLjJgAAAAtCHNruTMsLQl60DnkJOTI2lpae3dDADAZuhrAjBqbxz4giFT63vn3o70kZ2QBpp8vXyDubCvT1fqk5AadJHgcZsAjGBQ66zpzSKXpCYmmJrlXle4zg2PYKg2W+aAXEcqRAAA6qE31Pfo302u2m+k3Pj219EAgk+WrJUJQ2pLdWwpDSI4brfB8uCMH8zz/Xf85ztZU1Jppum689LsNMTxv9MaCiDoiPR39SHD+8vL//vFDM9evlHem79SDh7er868a0oqTEBDYxlGGrOutLb/1Lnjh8nEob3N+7fnLZf2NCgvI/peS8u8dvZvzXcWJw2ISE3c8ttmWtomor5SM5N3GSCf/VKblljLtv11+vdy40G7tejY7r9DH/l5rx1lyqfzzbg35i6VE3YfYpVrGdwtU+asKoh+fgKhUDRYRYdrArFs5oPryf6xtKCs3n0EANSPAAwAAIA2pfm4W3qhZtu50IPGHX/88fLaa6/JxRdfTFcBwDZCa74nJ3hM8IVmeliwrqjTBmDozaX5a4vk05/XyqxlG8zFeR3nD4bMKxAMicflEv3P7XFJdnKiqZlu7mfoV55Q3ewglb6gpCR4ZVRcKnUAAJryu536m+wKkZvaUz79scUBGOqokYPksU/nm9ITGpgQceTIQXXmjS/98d3KTSYIRDML5KclS/8OHlh4wYQR5sZ/JMDkj2/Nkq+Wrjd9qNk1NpVXmxvx7y9YKW+cc+AWB2BooOovv96sf/7rn8Trccuqogp55JN50p4OGNZXHv54ninT8cumUvnDy5/J4bsMNMd0U3mNrCwqly+XrTfZQv506Ogt3s5u/btFy33MW1NUtx079pW3h6ww54565X+/yNKCUpm880CTjaXKHzSZMTbXyaOHygtfLzElV7QinH4+Hjh6XHT65J0HRAMwVhZXyIlPT5d9BveUsmq/FRyTluiV/bbvU2f98WX3du/fzZoWX3ZG9+G9Cw/Z7PYDQGdDAAYAAADQTs4++2z59NNP5bDDDpPLL79cBg0aJB5P3ZTs/fu3LPUtAKD16NOSWoakfH2JCcDQC9L69Gxnsqq4Qj77ea189vM6KaioMem7/aHaoAt96X7ruL456bJL71z5ZuVGWbqpzNxsaCzDt2bR0OX1JtWAuCdRAQBozu/fs8ftGM2CsWBdsUxfvFp+U8/N4s0tq3HIiP7y+tyl0XHd0pNl/HY968w7blAPeWbWYvNeAxkufuVz8/7IkQPl1kP26NAHUctGPHHCBLnqza9M3+lN+je/X2ZerenkMUPl9ve+M+81oCUS1DJmQDcrwKWtaTaTuyaPkWvfnGWCbT7/Zb15OWkARkv7ec+B3eWrZRtMsJCWtRmQm2FlUbn3iD1NH7374woz7psVm8yroQwXzaEBMyeNHhLNgjFj8RpZuL5YduyRHQ0o0gCbDxauNsOL1hebl3NbWtYkvtRMxMc/rTE/NfD2wGF9m9kbANB1EYABAADQhihBgnjDhw83F2D0Jta7777bYOcEg3WfIAYAtB99uvOnDSWmBEftz1ga521VabUvmtL9FxNMETaBFtFsF6HawAu9saAZP0b2yZPMXy/QazDF87N/MmnHdd7URI94XG6r7IhmvtBpPTNTzU2A+tJ+AwDQGA2U+MfnC2RFUbkZ1swV+w7tXafc1eY6YY/BVgCGZgvQ8iROYwf1kGv2Hyn/+u5nWV1cYb4HbEs0cPL5034jHy5cLf9duEp+XFsoRZU14nG7TdCJ3qw/YFg/6ZGZssXbOHrUdiYzlma/WFVcbgIfjthloBw8vL8c9vh/pD1NGtpbXj5rf/OdZdbyDeZ7i547msGkX0667L1dT9lvh5YF9KhjdxtsAjDUO/NWyIUTRljTNRPYnyePkeN3GyxvfL/UZKZYX1YlNf6gKX/SKytVduieLWMHdd+sAKMT9xgqz339k8lqoWfmlE9+lIeOHW+m6feu+44YK/+Zv1L+PW+5Cc4oqfKZ7696vLXMz4l7DJEh9ZQX0ewg89bWZvPYZ0hP810OANA4AjAAAADakv4VTAUS/Ormm29u8cVCAEDb0wwY+u93KBwyqaK1Lva2WA9bAyIiKdTnrNpknobVYIlItotAUIMwQpKc4DUBF7v1y5ceGSl1fndpUIY+8ao1x9cUV0pJld+Md5kwjkD0ZoNmvtDgC50fAID6zL3+mAY7RoMi/n3+QZu1nP7Obmydavvu2Sa4UjNAqSN2qVt+JOKk0UPNqz6jB3RvcFta7kJfm7PM1JMmbfZ2mqI33A8a3s+8mrIl+6OOGjXIvJwaWldjJStacxml2ShuOGg3aY7G9rExv9m+t+zQPUsWbSiR1+YslbPG7ShJ3rqZLkf2zTOv5mrqXNZSMp9dfniD0/X728Ej+pvX5njxmyW1y4vIeeOHt1o/AUBnRgBGO0sqDkuyPgorIoFU+wKGtzI2HHZE3Nbk2HduXI7pgYxQ/ERrWsp6e96sX+wnKsv6xr4MpKy15w0l2MO+bLsdNVmx6Ukb7e2uy8q2h2vsLx0JxbFh53ND3trSdA32RyA11o5Ait2mkKNcXeoae9nshfHrsbcccmTbCibbw77s2Lr8GY7jV2XP6/E5+9Ke7o/LvlrjKB+c6CgX5zwOrrhDGHZ0XjjNPr6BjIA9vD524cvvyLDmijuN6mtz/DW3QIrdpvS19sLlvdwNnsPO9SaU2+sKO/6l8lTH3vvT7OPtifvcqOre9v66kmP9EfbZbXIef/OtsgFux/FMXWu3w5fZ+M20xJL6zyNVk2P3XbjMnu7xxZ3vjmMWSHcs60hTV5LVcF95fI02GUBrCddmwWjpOtA53Hrrre3dBADAFuiRkWrSNPt+zQyxYF3RNhOAoVmXftpYIp8uWWdqnVfUBCQUrpvpQv/e2y4vU3btmyeDu2XV+yRwPA2qOGPsDrK8oEzmrC4wP6v9fklOSDAZMkb1yTM/yXwBAOgofIGgKUehgYiR4IuxA7ubgEFgS+l3nSv320XOfelT2VRRbYIwNLvEtqigolpen7M0moFmeK+c9m4SAGwTCMAAAAAAAADYDBqM0DsrVX7eVCqhUFh+WF0ok3fu2E/+bSirks9+Xief/LxW1pdWmUAMDbaIBF5o0EUwHJZemamyS59c2bl3niQn1H1as6kbDoPyM80rHAxKoLJMvKkZ4vJs3noAANuegooaGfnnV2Vb8qf/fCdv/bA8Oux1u+SSSTu1a5vQOew5sMcWZynpSLSEzKyrj2zvZgDANocADAAAgLYUDte+WroObJNWrFhhfvbv398abkpkfgBAx6GpyrX0iAZgaB1tzSLR0VT6AvLVsvUm8GLBumKTRkvr1QeCoWj2Dg28yExOlJ165ciovnmSm+ZI/QgAQBOaU+ajI0v2emRIt0y5aMIIGdHLkZoYAABgMxGAAQAA0IZcrVCCpMUlTNBuBg4caOquVlVVSWJiYnS4KcGgXVIMANAxbjZpxgd/OCRlNX5ZU1whPdJjJR7biwZUfL+mQD5dsla+WbFR/EHNbBGKBV3ocCgkiV6PDO+ZY0qM9MtJb9bvIwAAOpM/HTravAAAAFoTARgAAABAG7n55pvNDS6v12sNAwC2Pb2yUsXjcon+K66ZJDTDRI8hPdqlLVpOZHlhuSkv8vnP66S02m8ycjhLjKgBuekm08UOPbLF63a3S3sBAAAAAOisCMAAAABoa2Sw6LJuvfVWefbZZ03pEc1+ocMAgG1Toscj3TNTZGVhuQlu+GFtoUxq4wCMwsoaE3Dx6c9rZWVRhYS1xEiwNvDCF9Cgi5AEw2Hplp4iO/fJkZF98iQtMaFN2wgAAAAAQFdCAAYAAEAbogQJzjjjDHnuuedMAAYAYNvWJytNVhdXSCgUlvlri9pkmzWBoHyzfKPJdvHDmkKT/UIDQCKZLgKh2hIjqUleGdkjX3btly/dM1LapG0AAAAAAHR1BGAAAAAAbUhvlAEAOoe+2WnyzQqXBMIhKaiolk3l1aYkSWvTciIL1hXJp0vWyazlG6TaHzTjokEX+gqHTUmUId0yZbd++TIwL0PclLkCAAAAAKBNEYDRzmpyXOLKr7084w7Y00JxWUHDjrKsnhr7ko4r5Jhe5YmbaF/k92Xa81b0tFceSIu9Tyiz5w06HprxZ9obDibF1pW8yXHZqSauTdqsoD095I21M5Rst7mit91Gf3bQXlc4ti5PuT1vMMVuY3W+PT3safjyWE2u3Y5Aqj0c9sSGkwrs/QumNH5zJW2Vvd2Esthw6WBHm7vbw4mF9rYSi2PLVvS3+6ZbjxJruMpnp5sNu5Oi7wOpdhv9GeEG26i81Q2fg+V97H6u6u7oy7hzx1tqz+tcl3PZ+OnOYxLK9Nvzeu2VhYOxbXmLvI1uN3mTve6anLjtptszF+xuL+vNq3ZcMHV8ZlfEPkwJ5fa05E2N12GuijuHU9bb0wKl9rnh2KyEEuPmTXPsXw9HBwDYOrT++q812Fu0DgAA0O76ZKeJxjjob2bNPLFwQ4kMy2q9Sy2aXeOzX0uMFFTUmCA+f6g24CKS7ULHaTtG9c2X4T2zJdFr/00AAAAAAADaDgEYAAAAbUnv0LQ0foL4CwAAOoTURK/kpSbL2tJKCYRCMn9dsQzLym/ROkurffLl0vUm28XPm0olLM4SIyEznJOaJDv3zpVRffIkMyUu0hoAAAAAALQbAjAAAADakCamciSn2qJ1YNv2j3/8Qz788MNmzetyuWTq1KlbvU0AgC2j2Sc2lFWZkiDz1xXJ0TtsfgCGBlb8b9Um+XTJWvnfqgITYBEMhUy2i9oSI7XDSQke2aV3rikx0jMz1fyOAAAAAAAAHQcBGAAAAEAb++STT8yrOQjAAICOrXdWqsxeHpLyGr98vWKjnPtGmWSlJssufXLltzv2lV365Im7nkAJLR2yZGOpKS/yxdL1UlETMEEcWl7EF5fpQpcclJ9hSowM7ZYlHjdBFwAAAAAAdFQEYAAAALS1MCksurobbrhB9t9///ZuBgCghQorquWzX9ZJUWVNbbCES6SgskZKavyyvKhcPl6yVrbvni1X7zdSemWlmmU0W4Yuo9ku1pVWmRIjGnQRKTFisl+EwybDxcg+uabMSHICl28AAAAAANgW8Bc8AABAG6IECdSwYcNk4sSJdAYAbOPBF89/vUTWllaaYU1M4Xa7JdnrkW4ZKRIMiZRW++SbFRvlurdmyeG7DJR5awplwbpijcaUQKhutovM5AQZ0StXRvXNk7y05PbeRQAAAAAAsJkIwAAAAAAAANgMWirkje+XybrSSklL9IrX7ZIqX9BkuaoOBM08Ho9LkhM8UuUPyg+rC+XnjaXSK6s2MMMXDEogGJZgKCQJHrcM65kju/XNk3456ab0FAAAAAAA2DYRgNHOAqki/vTa9zW9/PbEuOzk7iqPNclVez2n3nlVMD0UG0gI2ctWO9dlDwfSYiur6m6v2GWvSlwBV52neiMSS+xlK+In6rw1bnsX4s7GcLK9g6Eax3aC9nA4MdawsNteb2KRvX9WI5vgz7R3OJzk6IBQrB2+oVX2vM42Vtoft5IUu50JZa4G+1nsWcWfZc/g6xYbTsj0WdOGZG+yhguq06zhxTulxAZqnOeGvQ8Bx3bDaxJi7x1trOkRsNflt9flrooNB1PCjZ7f3gp72eoecTM0cW3SvSnRGg5mxJYNZDk/SPb+V/ew99ebVx1976+M7btphsfeh9ysCmu4rCrJGq5Kjw0nVNjbTSpynKOOwaqesZ2uyXXsg6M/wl5n37oa/Jw5zzMAW4l+LFtagYQKJgAAtKvlBWWyprjSBE9okIUGZFS5gqbKmC8YloKKGqnwBUxWC8MlUuUPSGFFjXjcbvOrfEBOuozsmyfDemSL18OXcQAAAAAAOoMO+xf+Tz/9JLfeequMHz9eevbsKWlpaTJ8+HC55JJLZO3atXXmDwQCcs8998gOO+wgSUlJ0rt3b7ngggukoKCg3vXreJ2u8+n8uty9995r1lOf77//Xg477DDJyckxbRk7dqy8+eabrb7fAACgc3OFw63yAgAA7ed/qwqk0h+Q1MTaYOpET3xQdVhKq/2mxIgGZgT197b+NMMik4b2ksv23UlOHjNUdu6dS/AFAAAAAACdSIfNgDF16lR55JFHTNDDcccdJykpKfLVV1/JlClT5Pnnn5cvvvhCdtxxx+j8Z5xxhhl/6KGHylVXXSVLly6VBx98UD777DOznAZNRJSVlcmECRNk0aJFcuGFF8ouu+win3zyiVx77bWyYMECeeqpp6y2zJ07V/bee28TqHHllVdKfn6+2daRRx5p5j399NPbtG8AAACw7QqFnKmuAADbmhVF5Sb5nGazUB63S9wukWBtrIUENceF+T8sbpdL0pISxB8MSVZKoozbrmd7Nx8AAAAAAHS1AIxjjjlGrrvuOsnOzo6OO/fcc03mifPOO09uvvlmefnll8346dOnm4CIyZMny7Rp06Lz77777mY9999/v5k/4r777pP58+eb8VdccYUZd/bZZ0tWVpYJ+tBgDg3QiLj44ouloqJCZsyYIXvssYcZd9ZZZ8mee+4pl19+uRx11FGSmZnZJv0CAAC2cXrvvaX337l/DwBAu6oJBE3ARYTLJZLs9Uqlz2/Ki2i2qqQEj6QmeCXR6zHTiyprzHIAAAAAAKDz6rAlSDTQIT74IuL444+PlgSJePbZZ83PSDBFxNFHHy0DBw6MTo+fPzU11ZQgiafZLeLXp5YtWyaffvqpTJw4MRp8oRISEkw5lOLiYnnrrbdauLcAAKDraI3yI5QgAQCgPSV5PaacSLyM5AST4SI72SvdM1IkJzXJBGFo8IXSX+G6HAAAAAAA6Lw6bABGQ1avXm1+9ujRIzpu1qxZ4na7TXYMp7322kt+/vlnKSwsNMPr16+X5cuXy6hRo0xZk3garNGrVy+ZPXu2tW41bty4OuuOjIufHwAAoFHhVnoBAIB20z8n3fwMxpWV0kCLlASvJHs9puxIvMh8A3JrlwMAAAAAAJ1Thy1B0pCbbrrJ/NQyIRGrVq2S/Px8SUpKqjN/3759o/Pk5uaan/Hj65t/yZIl1robmj9+3Y3ZsGGDbNy40RoXvw0AAAAAALDt2LVvnvy4tkgqfUHJSG762RadT4MzRvXJa5P2AQAAAACA9rFNBWDcdddd8tprr8kRRxwhp512WnR8ZWWl5OTk1LtMcnJydJ74n/UFa0Tmj8zT1PzOdTdkypQpctttt9U7LTygUkL9Ksz7ntnl1rT1G7Ki71O62dsY3n2dNVzut9tXUlPbNtUnvcSa9lNBN3vetDS7UeWx0yKcZBeZd6cErOGd+62xhisCidH3y/vlWtNG9Npgr8tlP767tiwz+j49qcaa5gvaaVqLylOt4ZQkX6zNvewnjTxuezvZKVXW8Iay2BNI5WWxfqtdmb2uhER7//0Vsf3Nzqo9jhEZcW2qbYfdl+tKMqzhyuJYRpbsfPtcSPDadYJ7ppdZwwPTCqLvq4KxNqlMr72/wzPWWsMpXn/0fZnjPPK67DaHxO6PnBGVDR7PourUBs9JVVgam94nzz5HCyrsZcsKHedoXLPccedrbaPtNgcz7b5LzY21uarC3t9Agr1sfo/SBs+dKn+C3cZqe13BkH0RtmaZfbzDabFteXcvspe1hkRCjvMwWBPb57H9VlrT0rz2ebei3P63cW1ZrB0exzErq3Cc/wC2Ds0/bsqItHAdAACg3QzIy5De2any88ZSqfYHJTmh4dIiOt0fDEn/3HSzHAAAAAAA6Ly2mQCMv/3tb3LDDTfIpEmT5IUXXhBXXDrP1NRUqamxb9hHVFdXR+eJ/9nY/JF5mprfue6GXHjhhXLsscfWyYChgSQAAKBr0dgnR/zTFq0DAAC0Hy0xcuTIQfL87J9kXWmlCbBITfSIx+W2yo5o5gud1jMz1czvLE0CAAAAAAA6l6bzZHYAf/3rX+Wyyy6T/fbbT9555506AQ9aCmTTpk31Bkk4S4g0VTZEx8eXG2ls/qbKmUR0795dRowYYb2GDBnS5H4DAAAALfX666/L2LFjJS0tzWSNmzx5ssybN6/Zy2u2t+uuu04GDhxossLpz+uvv75OFjgNTn7yySflqKOOksGDB0tKSor069dPDjnkEJkxYwYHEkCnk5uaJCePGSqDu2WK1+2Wkiq/FFbWSHF17U8d1vE6XefT+QEAAAAAQOfW4QMw7rnnHrnyyivloIMOkrfffrvebBNjxoyRUCgks2bNqjPtyy+/NBeAc3Nry2H06NFD+vfvL3PmzJGqKrs0w/Lly2Xt2rVmffHrjqynvnXHzwMAANDsEiQtfQHNMHXqVDn66KOloqLCfK/WjHJz586VcePGyQ8//NDk8sFg0ARQ6LITJkyQv//973LYYYfJfffdZ37qd/CIZcuWyTnnnCPr1q2TU0891cx79tlnm+/dv/nNb+Tee+/lmAHodDSo4oyxO8jJo4fI6AHdpHt6smQkec1PHdbxOp3gCwAAAAAAuoYOXYLkrrvuMheJDz30UHn11VfNE3f1OeWUU+TZZ5+V+++/31wYjn/aTy8E33rrrXXmv/POO+XRRx+VK664Ijpel49Mjxg0aJCMHz9eZs6cKd9++63svvvuZnwgEJCHHnpIsrKyzMVnAACAZpcgid2z3iKUIEFzFBUVme+6mq3t888/l8zMTDP+uOOOk+HDh8ull14q06dPb3QdzzzzjHz88cdy8cUXm+++EZoF46qrrpLnn3/eBFuobt26me/Lu+22m7WOc889V3baaSe56aabTICGZuEAgM5Ey4oMys80r3AwKIHKMvGmZojL42nvpgEAAAAAgDbWYQMw9Ik5Db7QjBWaxviVV16xpqenp8sRRxxh3u+///5ywgknyEsvvWSCIQ4//HBZunSpPPDAA+bismbQiHfNNdeYgA79qQEaI0eONBeWn3vuORN8MXHiRGt+vdisgR0HHnigXH755ZKfn2/m/e6778xThRqEAQAAAHQk06ZNk9LSUhOEEQm+UJoN7phjjjHBFStXrjRlQhqiQc7K+X36wgsvNAEVOj0SgJGXl2deTr169TLfr9944w1ZtGiRKYcCAAAAAAAAAJ1Rhw3A+Prrr83P9evXy5lnnlln+oABA6IBGEovIO+8887y1FNPyUUXXWRKjkQyXWiwRjy9AP3pp5/KjTfeaAI7Hn/8cbO+P//5z+ZJPid9ik+fGtSAEE237PP5zLZee+01ExwCAADQbK1RQoQSJGiGSHk+LTfipOP0+7N+524oACMcDpvpvXv3Nt+V46WkpMioUaOi39mbsnr1avNTg6sbs2HDBtm4caM1bsmSJean3+83r/YSDAZEwiEJh4ISDnb4So5blemDUG1fdGX0A33BecFnhH8r+Hdzi+nv0FBIgoFAu32/ac/vVQAAAEBn1mEDMJ5++mnzaq6EhAS5/vrrzas5NEWyBl7oqzk0S8bbb78trW1w902S0bv2JkxmYpU1rcYfOzzD89db04anr7WGvyuxL5yPyIpN755Yak1L8/qs4Yw+1dbwL+X50febKtOsaacMrL2QH3F4+gJrONHlir6f2a+3Ne3Hqr7W8K6py63hRdW9ou/TPXabQmH7Ivd7G0ZYwzXBWF+lJdj7NzZnqTWc6qmxhmd6d4i+r8pIsKZtKLeDdwZkF1nDiZ5A9H3PZLufa0L2x2u7lE32uvrZwyv9udH335bYNzl2z7L7anhy7U2MiIJArJ3rA3ZGlgGJ9nbW+7Ot4YpAYvR9dcBuc2qC/cf4+jK7P/bttjj6vm9igTXtu4qBju3YJYRKMpOj73fPWmFNCzqO96o+dqryBcWxmzcr1sf6TXm99o2Afn3s/e+TVhx9v6na3p9Kf6wv1MQeP1nDOd6K6PvyYKz9ak6JfX47JY2InSuqsDw1+r5HRrk1zS32jdneaSXW8Ma4du+Xa38GC4P2Z3ZlhX28UxNjxzQt0f6sdE+32wFgK9GPeAvjL1q8PLqEVatWmZ9agsQpMi4yT30KCwulsrLSlA+pj67jyy+/NFk24jNsOP373/+W2bNnmywYWt6vMVOmTJHbbrut3mklJSVSUGB/32hLlaWl4gnUSKiyXALeDvtnVJsFHgRr9G+XsLjcXbfEAv1AX3Be8Bnh3wr+3dxi1TXi8ldLaXGRuP32NbC2ot+tAAAAALS+rn3lEAAAAOikNHhCJSXZQZAqOTnZmmdzl3euo6EAjPnz55sSJTk5OfLPf/6zyTZraZNjjz22TgYMzXynZf/qK3HSVgqDLgmuLxZ3arp4vXbQbldTm/nCJd7U9C4fgEE/cE7w+eDfCv7N5PfHlv0y9Ug4FJbM7BzJy7QfpGgrlFQGAAAAtg4CMAAAANqQK6yvcIvXATQlNbU221JNjZ39S1VXV1vzbO7yzVnHokWLZL/99pNQKCTvv/++bLfddk22uXv37ubVUMY7fbUXj8cr4nKbgAOXp+tmfYhwuekL+oFzgs8H/1bwbya/P7aYZpByu8Xj9bbb95v2/F4FdEa33nqryeanpRxby+mnny4zZ86UZcuWtdo6AQDA1te1ixcDAAC0Nb0Y0xovoAmNlRlprDxJRG5urgmuaKhMiY7XzBf1Zb/QzBeTJk0yQRoffPCBjB07luMFAAAAYKsFP7hcLtm0yS5FrDSA4aijjpKePXtKYmKiCfg+7LDD5PXXX4/OowEOuvxf/vKXRrej2f90W7pObJ41a9aYvpszZ06daS+++KI8+OCDdCkAoNMgAAMAAKAtaexEqIUv4i/QDGPGjDE/v/zyyzrTIuNGjx7d4PJ6AXKPPfYwF8qWL19uTauqqjIXzupbft68ebLvvvuKz+eTjz76KNoOAAAAAGhLt9xyi/nbRP9GOe+88+Sxxx6Tq6++WsrLy+Xoo482N/43hwZgaJaL+gIwbrzxRvN3Umt64oknTGbBzkD/rtS+IwADANAVEIABAAAAdEJHHHGEZGRkmIt2paWl0fErVqyQV155xWSo6NevX/RC4sKFC2Xt2rXWOk455RTz8/7777fGP/roo+biYmR6xPfff28ucGrZkenTp8tuu+22FfcQAAAAAOr36quvyu233y7HHHOM/Pjjj+bm/5lnnmkCMGbMmCH/+c9/6s3mt6W8Xq8kJye3eqmgpKSkVl1nV6F/k0bKZgIA0NYIwAAAAGhDrnC4VV5AU3JycuS+++4zpULGjx8vjzzyiAmkmDBhgsluEZ/idfbs2TJs2DC5/vrrrXWcccYZss8++8jDDz8sp512mkydOlUuueQSueaaa0wAx8knn2wFdvzmN78xaX/PPvts+eGHH+T555+3XuvXr+fAAQAAANjqbrrpJlNW8Z///KcJZHA68MAD5dBDD232+rRMSbdu3cx7DebQv6n0pWU14sugxNPhP/zhDyYAfvjw4ZKSkiJ77bWX+VtJPf744zJkyBATuKF/X+k24p1++ukycODAekul/OMf/5DBgwebAA3NTPj111/XaXNku7r+nXbaSd54440662yIzqP989///ldGjRpl1qHrii/dogoLC+Wqq66SnXfeWdLT001Qy8EHHyxz586NzqMZQyLZE/VvzEjfPf3002a/33nnHZN1MTI+vn01NTUmk4n2k+6rPkSgf4/q+Pr6+oUXXpARI0aYeTXIRreh0z7//HO54oorzDFMS0uTI488UjZu3Git45tvvjHnRX5+vjlWgwYNMkE7AABsLu9mL4FWler1S3pC7ZeFBJfmFI8Z2yuW6nn3dPvL13p/ljW8tDjXGq4Oxr5UDuxu174bmrrBGt7gz7CGE92B6HuP225TT2+JNdzDk2INJ7g80fejktZY00JhO94n1WV/SSoLxiKE0z12dGplKNEargrYX5rzkiui73MS7VRvy6vtvhmQXGi3w+uLvve6g9a0AwfPb7Qd88t6Rd8PTC6wpq312cdop5SV1vB2Xkc73LH+WOiJrVcV+dOs4ZXuPGu4MJAefe8Px45Bvf0etx21W26sXWur7ajvDVX2ueHz2f9kzCmNqxvvCBj3hex5i3z2uZLsiZ1nhQF7/3okxJ7SVSnu2DFSO+fEzq1gyN6/7OSqBs9n5XHFblpmO84V57o2+uz9z/eWR99XBu1zodxvR6O747ajJvRYYg0vy4gdw43VseNXn7WVduf2SyuOvu/mtfuqLGRH2hdU2n0b/5l2thFAG9HgiZYGULRDAIZepHnmmWfqnXbllVfWWyv3k08+MRehIheC9IKLXqjSG/poG5pmNy8vzwRi6EUqrXms/X/nnXfKLrvs0uTyHo9H3n33XfPk2L/+9S956aWXpFevXuaY33zzzWZ6xC+//CIFBbXfh+6+++5616dPmvXo0aMV9xAAAABAZ6GZ+c4//3yZNm2aufn95JNPmrKIm+unn34yGf705rlmBWwNeuNeMwFecMEF5ub9UUcdZcY39XfVp59+Km+99ZZcdNFFZvjPf/6zCWzQv8+mTJkiF154oRQVFcm9995r2quZBJuipVPKysrM33saXKDLanv0b7JIsIkGNfz+9783gRG6Td3GWWedJX369NmsftR16DHRgPynnnpKjj32WBPY8Nvf/tbMo9t88803zXg9Zhp0r4ElEydOlPnz50vv3r1NsL/+Tal/Q5577rnRawLjxo0z7SkpKTEPDjzwwANmvAZyRLJYTJ48WT777DOznK5Hg1d0vsWLF5vtxtO+e/nll00ghgZRaCBHpOTJxRdfbB5S0GAODWTRBxJ0Pv07V23YsEEOOOAAc5yvu+46yc7ONvM5A04AAGgOAjAAAADQbM8991ydcfoUjNP7779vLirpxRS9wKFPn+gTOpoh4b333pP999+fXm8jmnJXX43Rp47CDQT26MUvvaCnry1dBwAAAAA05Z577on+zakZFPTvGGdWiOZYsGCB+anBB61FsyZoezQAQ4Mu4rMBNmbRokUmGCSS1UGDADRw4o477jBBBJEAkWAwaAIldH+bylCh2Qc1OELXpXbYYQc5/PDDo3+HK81uqH+Pa+aHSEDDfvvtZ/5uGzBgQLParu177bXXosEmGsCx4447yrXXXhsNwNA+1vnc7tiDbVqqUufTDIqaiUSD8DUrhgZgaAaQ+L7bbrvtTDs1QMTZpxpo8uGHH8rHH38se++9d3S8ZvPQoJAvvvjCBHHE97UGaMRfo4gEYOiDCZrNI5KlRIM7HnroIRP8kZWVZdalbdB54oN+9DgBALC5CMAAAABoS9toBoyI5lxk0gtHejFEgy40C0b//v3N+FNPPdWkAtULVnphJP4CDQAAAACga/v222+tYS1LoSUONZvB5igtrc0Y21rZL1pCgx7iAyr23HNP8/Poo4+22hcZrxklmgrA0KwUkeALFckoocuqNWvWmECEP/7xj9HgC6VZKTRgItI/TdHsFZrtI0LLi+jf9Roos27dOunZs6f5uz/+WkBxcbHZpgaFfPfdd9ISWkJFs15oMIeeBxH6YEckw2J8AIbuX30PiCjNoBFfIkb7TDNp6DmmATWa8UK9/fbbMnLkyHrL1gAA0Fxc9QYAAGhLoVZ6tRPNcKAXa/TCSmMpVvWpHU1BGgm+UPpUydlnny1LliwxT5cAAAAAABDhLDeigQibG3wRCRRQWqajvcX/TRz5u1j169ev3vGahWFz1xkJxogsq0EFasiQIXWWrW9cQ3Te+KAFtf3225ufkcwkmklCAxmGDh1qgjH0eGkZj++//95kl2gJzfLx448/mvXFvyJt0LIh8bQEypb2mQZvaFCMlk3VfdCMIlpypabGLucNAEBzkAEDAAAAzaZPhWgAhsfjMRfHNPVo/BMxatasWeZn/JMoEZFxs2fPtlKIAgAAAAC6tmuuucYE7L/11lumNMWTTz65RevRjAlKs0C0N/3beXPGN6esY0uWbW133XWXKTNy5plnyp/+9CfJzc012S4vu+wyE5zRErq8Zuz461//Wu90ZxBLSkrKFveZBpq8+uqr8tVXX8m///1vU85F9+n+++834+IziQAA0BQCMAAAANqQS8LiauFFEV2H0gtTTvo0SPfu3aW1ac3Wiy++2ARdaBCG1nh9+OGHTS3Ye++9V66++urovKtWrTI/+/btW2c9kXGReQAAAAAAUKmpqfL888+3uDM0Q4KWwJg2bZr87W9/a7Wb585sEB3VgAEDGrxmUN+4hui8GqAQv996LUBFyqRo0MK+++4rU6dOtZbVUiTx2Usa67uGpg0ePFjmzp1ryri0Vd+PHTvWvO6880558cUX5aSTTpL/+7//M9k8AQBoLgIwAAAA2pLGTrT0qZRfFz/iiCPqTLrlllvk1ltvrXexhsbXZ9KkSeYVoTVenc4//3zZdddd5YYbbpDjjz8++vRJZWWl+RlfCzYiOTnZmgcAAAAAgNampST071S9ca5BHV6vfSvkv//9r/h8Pjn00EM3K0AkElzQkfXu3Vt22mknefbZZ+X666+PBqB8/PHHJitIJECjKWvWrJE33njDPHihNBumrnPUqFHSs2fPaGYJZ+aNV155RVavXm2VO0lLS2uw73RafeVKjjvuOHn33XfliSeekHPPPdeaVlVVZTJkRNbbUlqKRB82iQ/00P1UlCEBAGwuAjAAAADakl6YaHEARu3yb775Zp36rZoBo7ELUJsjPgCjPnoR58orr5QLLrjApOeMPBESuShV30WK6upqax4AAAAAAFrb73//exNsoJkM/ve//8kJJ5xgAg8KCgrkP//5j3z00Ucmw8Hm0BIXw4cPl3/9618my4aW29BAB311NFoa5PDDD5fx48fLGWecYQIMHnnkEdPW8vLyZq1D9/Gss86Sr7/+2mTF/Oc//ynr16+Xp556KjqPBrDcfvvtZhtaclT7/IUXXjAlZJzZLDTA4bHHHpOMjAwTOLHnnnvKoEGDZPfddzd9esUVV8jo0aPNtYbDDjtMTjnlFHn55ZfNwx8zZsww+xIMBmXhwoVmvF6H0CydreGZZ56RKVOmmBKr2taysjIT+JGZmSmHHHJIq2wDANB1EIDRztZXpUt5RZZ53yu11J5WnRF97w/ZNcqqggnWcFqi3xr+eWMsvdfnCfaNmUDYbQ3PWWmnB09J8UXfpybF3qt/rJxgDc/L/8UaLvDHIk4zvbU3WCI2+uxUbz2T7P1dXB5Ll16VYu9fedB+gjYctlOOVcf1x+rKRGtaTdA+zRcV97CGS6tj6x6ev96aluA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      "text/plain": [
       "<Figure size 2160x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Mel-spectrogram shape: (64, 128) (64 frequency bins × 128 time frames)\n",
      "Mel-spectrogram range: -57.6 to 0.0 dB\n",
      "Dynamic range: 57.6 dB\n",
      "\n",
      "ICI sequence (simulated): ['.3f', '.3f', '.3f', '.3f', '.3f', '.3f', '.3f', '.3f', '.3f']\n",
      "ICI range: 0.023 to 0.096 seconds\n",
      "ICI mean: 0.063 seconds\n",
      "\n",
      "Model Prediction for this segment:\n",
      "  Coda Type: 1+1+3\n",
      "  Embedding Magnitude: 3.900\n",
      "  Detection Threshold: 3.853\n",
      "  Detection Confidence: 0.046 above threshold\n",
      "  Status: ✓ DETECTED\n",
      "\n",
      "============================================================\n"
     ]
    }
   ],
   "source": [
    "# ── Visualize Spectrogram and Rhythm Features for Detected Codas ──────────\n",
    "print(\"\\n\" + \"=\"*60)\n",
    "print(\"Spectrogram and Rhythm Feature Visualization\")\n",
    "print(\"=\"*60)\n",
    "\n",
    "# Find detected coda segments\n",
    "magnitudes = inference_results['full']['magnitudes']\n",
    "threshold = np.percentile(magnitudes, 80)\n",
    "detections = magnitudes > threshold\n",
    "detected_indices = np.where(detections)[0]\n",
    "\n",
    "if len(detected_indices) > 0:\n",
    "    # Take a middle detected segment as example (not the first one at 0.0s)\n",
    "    segment_idx = detected_indices[len(detected_indices)//2]  # Middle detection\n",
    "    segment_time = start_times[segment_idx]\n",
    "\n",
    "    print(f\"Visualizing detected coda at {segment_time:.1f} seconds (segment {segment_idx})\")\n",
    "\n",
    "    # Get the mel-spectrogram for this segment\n",
    "    mel_spec = X_mel_batch[segment_idx].cpu().numpy()  # Shape: (64, 128)\n",
    "\n",
    "    # Create ICI sequence (dummy for visualization since we don't have real ICI from YouTube)\n",
    "    # In real application, this would be extracted from click detections\n",
    "    ici_sequence = np.random.normal(0.08, 0.03, 9)  # Mock ICI sequence with realistic timing\n",
    "\n",
    "    # Create visualization\n",
    "    fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(18, 5))\n",
    "\n",
    "    # 1. Mel-Spectrogram (input to spectral encoder)\n",
    "    img = ax1.imshow(mel_spec, aspect='auto', origin='lower',\n",
    "                     extent=[0, 5, 0, 8000], cmap='viridis')\n",
    "    ax1.set_title('Mel-Spectrogram Input\\n(Spectral Encoder)', fontsize=12, fontweight='bold')\n",
    "    ax1.set_xlabel('Time (seconds)')\n",
    "    ax1.set_ylabel('Frequency (Hz)')\n",
    "    plt.colorbar(img, ax=ax1, label='Power (dB)', shrink=0.8)\n",
    "\n",
    "    # 2. ICI Sequence (input to rhythm encoder)\n",
    "    ax2.plot(np.arange(1, 10), ici_sequence, 'o-', color='#2E86AB', linewidth=2, markersize=8, alpha=0.8)\n",
    "    ax2.fill_between(np.arange(1, 10), ici_sequence, alpha=0.3, color='#2E86AB')\n",
    "    ax2.set_title('ICI Sequence Input\\n(Rhythm Encoder)', fontsize=12, fontweight='bold')\n",
    "    ax2.set_xlabel('ICI Position')\n",
    "    ax2.set_ylabel('Time Interval (seconds)')\n",
    "    ax2.grid(alpha=0.3)\n",
    "    ax2.set_xlim(0.5, 9.5)\n",
    "\n",
    "    # 3. Combined DCCE Processing\n",
    "    ax3.text(0.05, 0.85, 'DCCE Dual-Channel Processing:', fontsize=13, fontweight='bold', transform=ax3.transAxes)\n",
    "    ax3.text(0.05, 0.70, '🐋 Spectral Channel (CNN):', fontsize=11, fontweight='bold', transform=ax3.transAxes, color='#55A868')\n",
    "    ax3.text(0.05, 0.60, '   • Mel-spectrogram features', fontsize=10, transform=ax3.transAxes)\n",
    "    ax3.text(0.05, 0.50, '   • Captures frequency content', fontsize=10, transform=ax3.transAxes)\n",
    "    ax3.text(0.05, 0.40, '   • Individual identity cues', fontsize=10, transform=ax3.transAxes)\n",
    "\n",
    "    ax3.text(0.05, 0.30, '🎵 Rhythm Channel (GRU):', fontsize=11, fontweight='bold', transform=ax3.transAxes, color='#2E86AB')\n",
    "    ax3.text(0.05, 0.20, '   • ICI timing patterns', fontsize=10, transform=ax3.transAxes)\n",
    "    ax3.text(0.05, 0.10, '   • Coda type structure', fontsize=10, transform=ax3.transAxes)\n",
    "    ax3.text(0.05, 0.00, '   • Click rhythm sequences', fontsize=10, transform=ax3.transAxes)\n",
    "\n",
    "    ax3.set_title('Biological Signal Decomposition', fontsize=12, fontweight='bold')\n",
    "    ax3.set_xlim(0, 1)\n",
    "    ax3.set_ylim(0, 1)\n",
    "    ax3.axis('off')\n",
    "\n",
    "    plt.tight_layout()\n",
    "    # Skip saving to avoid disk space issues\n",
    "    plt.show()\n",
    "\n",
    "    # Show the feature values\n",
    "    print(f\"\\nMel-spectrogram shape: {mel_spec.shape} (64 frequency bins × 128 time frames)\")\n",
    "    print(f\"Mel-spectrogram range: {mel_spec.min():.1f} to {mel_spec.max():.1f} dB\")\n",
    "    print(f\"Dynamic range: {mel_spec.max() - mel_spec.min():.1f} dB\")\n",
    "    print(f\"\\nICI sequence (simulated): {['.3f' for x in ici_sequence]}\")\n",
    "    print(f\"ICI range: {ici_sequence.min():.3f} to {ici_sequence.max():.3f} seconds\")\n",
    "    print(f\"ICI mean: {ici_sequence.mean():.3f} seconds\")\n",
    "\n",
    "    # Show what the model predicted\n",
    "    coda_type_pred = inference_results['full']['coda_type_preds'][segment_idx]\n",
    "    type_name = le_type.inverse_transform([coda_type_pred])[0]\n",
    "    magnitude = magnitudes[segment_idx]\n",
    "\n",
    "    print(f\"\\nModel Prediction for this segment:\")\n",
    "    print(f\"  Coda Type: {type_name}\")\n",
    "    print(f\"  Embedding Magnitude: {magnitude:.3f}\")\n",
    "    print(f\"  Detection Threshold: {threshold:.3f}\")\n",
    "    print(f\"  Detection Confidence: {(magnitude - threshold):.3f} above threshold\")\n",
    "    print(f\"  Status: {'✓ DETECTED' if magnitude > threshold else '✗ Not detected'}\")\n",
    "\n",
    "else:\n",
    "    print(\"No codas detected to visualize\")\n",
    "\n",
    "print(\"\\n\" + \"=\"*60)"
   ]
  }
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