From 7ef1b3ea30087676dbe361f3d38f4028567d13b9 Mon Sep 17 00:00:00 2001 From: Katydi Date: Mon, 18 Aug 2025 17:00:15 +0100 Subject: [PATCH] Project files added for NLP challenge --- FinalProject_NLP.ipynb | 809 +++++++ NLP-Project-.pptx | Bin 0 -> 198178 bytes predictions_validation.csv | 4492 ++++++++++++++++++++++++++++++++++++ 3 files changed, 5301 insertions(+) create mode 100644 FinalProject_NLP.ipynb create mode 100644 NLP-Project-.pptx create mode 100644 predictions_validation.csv diff --git a/FinalProject_NLP.ipynb b/FinalProject_NLP.ipynb new file mode 100644 index 0000000..e05f919 --- /dev/null +++ b/FinalProject_NLP.ipynb @@ -0,0 +1,809 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 42, + "id": "3f962c96", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[nltk_data] Downloading package stopwords to\n", + "[nltk_data] C:\\Users\\katyd\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package stopwords is already up-to-date!\n", + "[nltk_data] Downloading package wordnet to\n", + "[nltk_data] C:\\Users\\katyd\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package wordnet is already up-to-date!\n", + "[nltk_data] Downloading package punkt to\n", + "[nltk_data] C:\\Users\\katyd\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package punkt is already up-to-date!\n", + "[nltk_data] Downloading package stopwords to\n", + "[nltk_data] C:\\Users\\katyd\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package stopwords is already up-to-date!\n", + "[nltk_data] Downloading package omw-1.4 to\n", + "[nltk_data] C:\\Users\\katyd\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package omw-1.4 is already up-to-date!\n", + "[nltk_data] Downloading package averaged_perceptron_tagger to\n", + "[nltk_data] C:\\Users\\katyd\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package averaged_perceptron_tagger is already up-to-\n", + "[nltk_data] date!\n" + ] + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "import re\n", + "from pandas.api.types import is_string_dtype, is_categorical_dtype\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from tensorflow.keras.preprocessing.text import Tokenizer\n", + "from sklearn.feature_extraction.text import TfidfVectorizer\n", + "from nltk.corpus import stopwords\n", + "from nltk.stem import WordNetLemmatizer, PorterStemmer\n", + "\n", + "import nltk\n", + "\n", + "nltk.download('stopwords')\n", + "nltk.download('wordnet')\n", + "nltk.download('punkt')\n", + "nltk.download('stopwords')\n", + "nltk.download('omw-1.4') # WordNet data\n", + "nltk.download('averaged_perceptron_tagger')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3d1803a2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " label content\n", + "0 0 hillary rodham nixon candidate baggage samsoni...\n", + "1 0 watch dirty harry reid lie romney s taxes didn...\n", + "2 0 hillary rodham nixon candidate baggage samsoni...\n", + "3 0 flashback king obama commutes sentences 22 dru...\n", + "4 0 benghazi panel calls hillary testify oath whit...\n", + "Shape: (40399, 2)\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import re\n", + "\n", + "# Step 1: Load data and inspect\n", + "df = pd.read_csv('dataset/train_data.csv')\n", + "\n", + "import pandas as pd\n", + "import re\n", + "from sklearn.feature_extraction.text import ENGLISH_STOP_WORDS\n", + "\n", + "def cleanup_process(df):\n", + " \"\"\"\n", + " Cleans up a train_data.csv style DataFrame:\n", + " - Drops 'date' and 'subject' if present\n", + " - Merges 'title' and 'text' into 'content'\n", + " - Lowercases the text\n", + " - Removes all non-alphanumeric characters except spaces\n", + " - Removes common English stopwords\n", + " - Collapses multiple spaces into one\n", + " - Removes empty rows\n", + " - Resets index\n", + "\n", + " Returns:\n", + " pd.DataFrame: cleaned_dataset with 'label' and 'content'\n", + " \"\"\"\n", + " # Work on a copy so the original is not modified\n", + " df = df.copy()\n", + "\n", + " # Drop irrelevant columns\n", + " for col in ['date', 'subject']:\n", + " if col in df.columns:\n", + " df = df.drop(columns=col)\n", + "\n", + " # Merge title and text into 'content' and lowercase\n", + " df['content'] = (df['title'].fillna('') + ' ' + df['text'].fillna('')).str.lower()\n", + "\n", + " # Remove punctuation but keep digits\n", + " df['content'] = df['content'].apply(lambda x: re.sub(r'[^a-z0-9\\s]', ' ', x))\n", + "\n", + " # Remove stopwords\n", + " stop_words = set(ENGLISH_STOP_WORDS)\n", + " df['content'] = df['content'].apply(\n", + " lambda x: ' '.join([word for word in x.split() if word not in stop_words])\n", + " )\n", + "\n", + " # Collapse multiple spaces and strip leading/trailing spaces\n", + " df['content'] = df['content'].replace(r'\\s+', ' ', regex=True).str.strip()\n", + "\n", + " # Remove empty rows\n", + " df = df[df['content'].astype(bool)]\n", + "\n", + " # Reset index\n", + " df = df.reset_index(drop=True)\n", + "\n", + " # Return only label + content if label exists\n", + " if 'label' in df.columns:\n", + " return df[['label', 'content']]\n", + " else:\n", + " return df[['content']]\n", + "\n", + "# --- Usage ---\n", + "df = pd.read_csv('dataset/train_data.csv')\n", + "cleaned_dataset = cleanup_process(df)\n", + "\n", + "print(cleaned_dataset.head(5))\n", + "print(\"Shape:\", cleaned_dataset.shape)\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5a2d7af6", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[nltk_data] Downloading package wordnet to\n", + "[nltk_data] C:\\Users\\katyd\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package wordnet is already up-to-date!\n", + "[nltk_data] Downloading package omw-1.4 to\n", + "[nltk_data] C:\\Users\\katyd\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package omw-1.4 is already up-to-date!\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " tokens \\\n", + "0 [hillary, rodham, nixon, candidate, baggage, s... \n", + "1 [watch, dirty, harry, reid, lie, romney, s, ta... \n", + "2 [hillary, rodham, nixon, candidate, baggage, s... \n", + "\n", + " lemm_stem \n", + "0 [hillari, rodham, nixon, candid, baggag, samso... \n", + "1 [watch, dirti, harri, reid, lie, romney, s, ta... \n", + "2 [hillari, rodham, nixon, candid, baggag, samso... \n" + ] + } + ], + "source": [ + "#STEP 2 : Text preprocessing \n", + "#Tokenization\n", + "from nltk.stem import WordNetLemmatizer, PorterStemmer\n", + "import nltk\n", + "nltk.download('wordnet')\n", + "nltk.download('omw-1.4')\n", + "\n", + "lemmatizer = WordNetLemmatizer()\n", + "stemmer = PorterStemmer()\n", + "\n", + "# Create word token list\n", + "cleaned_dataset['tokens'] = cleaned_dataset['content'].apply(lambda x: x.split())\n", + "\n", + "# Lemmatization + stemming\n", + "def lemmatize_and_stem(tokens):\n", + " lemmatized = [lemmatizer.lemmatize(word) for word in tokens]\n", + " stemmed = [stemmer.stem(word) for word in lemmatized]\n", + " return stemmed\n", + "\n", + "cleaned_dataset['lemm_stem'] = cleaned_dataset['tokens'].apply(lemmatize_and_stem)\n", + "\n", + "print(cleaned_dataset[['tokens', 'lemm_stem']].head(3))\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7c8e2aaa", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Top 50 frequent words removed from corpus:\n", + " ['american', 'call', 'campaign', 'clinton', 'countri', 'democrat', 'donald', 'elect', 'govern', 'group', 'hillari', 'hous', 'includ', 'just', 'law', 'like', 'make', 'nation', 'new', 'news', 'obama', 'offic', 'offici', 'parti', 'peopl', 'polit', 'presid', 'report', 'republican', 'reuter', 'right', 's', 'said', 'say', 'senat', 'state', 'support', 't', 'time', 'told', 'trump', 'u', 'unit', 'use', 'video', 'vote', 'want', 'white', 'work', 'year']\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# STEP 3 : VECTORIZATION - BAG OF WORDS & TF-IDF\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer, ENGLISH_STOP_WORDS\n", + "\n", + "# --- Step A: Identify top 50 most frequent words in the corpus ---\n", + "word_freq = pd.Series(' '.join(corpus).split()).value_counts()\n", + "top50_words = set(word_freq.head(50).index)\n", + "\n", + "# Show removed words\n", + "print(\"Top 50 frequent words removed from corpus:\\n\", sorted(top50_words))\n", + "\n", + "# --- Step B: Add to sklearn's stopwords and convert to list ---\n", + "custom_stopwords = list(ENGLISH_STOP_WORDS.union(top50_words))\n", + "\n", + "# --- Step C: Initialize and fit vectorizers ---\n", + "# Bag of Words\n", + "vectorizer = CountVectorizer(stop_words=custom_stopwords, min_df=5, max_df=0.9)\n", + "X_bow = vectorizer.fit_transform(corpus)\n", + "\n", + "# TF-IDF\n", + "tfidf_vectorizer = TfidfVectorizer(stop_words=custom_stopwords, min_df=5, max_df=0.9)\n", + "X_tfidf = tfidf_vectorizer.fit_transform(corpus)\n", + "\n", + "# --- Step D: Extract top tokens for visualization ---\n", + "# BoW\n", + "bow_sum = np.array(X_bow.sum(axis=0)).flatten()\n", + "bow_vocab = vectorizer.get_feature_names_out()\n", + "bow_df = pd.DataFrame({'token': bow_vocab, 'count': bow_sum}).sort_values(by='count', ascending=False).head(20)\n", + "\n", + "# TF-IDF\n", + "tfidf_sum = np.array(X_tfidf.sum(axis=0)).flatten()\n", + "tfidf_vocab = tfidf_vectorizer.get_feature_names_out()\n", + "tfidf_df = pd.DataFrame({'token': tfidf_vocab, 'score': tfidf_sum}).sort_values(by='score', ascending=False).head(20)\n", + "\n", + "# --- Step E: Plotting ---\n", + "fig, axes = plt.subplots(1, 2, figsize=(14, 6))\n", + "\n", + "# BoW plot\n", + "axes[0].barh(bow_df['token'][::-1], bow_df['count'][::-1])\n", + "axes[0].set_title('Top 20 Words (Bag of Words)\\n(after removing top 50 frequent words)')\n", + "axes[0].set_xlabel('Count')\n", + "\n", + "# TF-IDF plot\n", + "axes[1].barh(tfidf_df['token'][::-1], tfidf_df['score'][::-1])\n", + "axes[1].set_title('Top 20 Words (TF-IDF)\\n(after removing top 50 frequent words)')\n", + "axes[1].set_xlabel('TF-IDF Score')\n", + "\n", + "plt.tight_layout()\n", + "plt.show()\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "48e760bb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train size: 32319 | Test size: 8080\n", + "Class balance (train):\n", + "label\n", + "0 0.564\n", + "1 0.436\n", + "Name: proportion, dtype: float64\n", + "Class balance (test):\n", + "label\n", + "0 0.564\n", + "1 0.436\n", + "Name: proportion, dtype: float64\n" + ] + } + ], + "source": [ + "# STEP 4 : PRE PROCESSING & MODELING\n", + "#A_ We keep only label and content\n", + "df_cls = cleaned_dataset[['label', 'content']].dropna().reset_index(drop=True)\n", + "\n", + "# B_Define X (texts) and y (labels)\n", + "X = df_cls['content']\n", + "y = df_cls['label']\n", + "\n", + "# C_3) Train/Test split (80/20), stratified to keep class balance\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "X_train, X_test, y_train, y_test = train_test_split(\n", + " X, y,\n", + " test_size=0.20,\n", + " stratify=y, # keeps the same class proportion in train/test\n", + " random_state=42 # for reproducibility\n", + ")\n", + "\n", + "print(\"Train size:\", X_train.shape[0], \"| Test size:\", X_test.shape[0])\n", + "print(\"Class balance (train):\")\n", + "print(y_train.value_counts(normalize=True).round(3))\n", + "print(\"Class balance (test):\")\n", + "print(y_test.value_counts(normalize=True).round(3))\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "44c8f96e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train TF-IDF shape: (32319, 34794)\n", + "Test TF-IDF shape: (8080, 34794)\n" + ] + } + ], + "source": [ + "# STEP 5 Vectorization (TF-IDF)\n", + "# Train/Test Split \n", + "# convert columns into vectors using TF-IDF, which captures how important a word is in a document compared to the whole corpus.\n", + "from sklearn.feature_extraction.text import TfidfVectorizer\n", + "\n", + "# Initialize TF-IDF vectorizer\n", + "tfidf = TfidfVectorizer(\n", + " lowercase=True,\n", + " strip_accents='unicode',\n", + " stop_words='english', \n", + " min_df=5, # ignore very rare words\n", + " max_df=0.9 # ignore very common words\n", + ")\n", + "\n", + "# Fit on the training data\n", + "X_train_tfidf = tfidf.fit_transform(X_train)\n", + "\n", + "# Transform the test data using the same vocabulary\n", + "X_test_tfidf = tfidf.transform(X_test)\n", + "\n", + "print(\"Train TF-IDF shape:\", X_train_tfidf.shape)\n", + "print(\"Test TF-IDF shape:\", X_test_tfidf.shape)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4b600a00", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 0.9862623762376238\n", + "\n", + "Classification Report:\n", + " precision recall f1-score support\n", + "\n", + " 0 0.99 0.99 0.99 4558\n", + " 1 0.98 0.98 0.98 3522\n", + "\n", + " accuracy 0.99 8080\n", + " macro avg 0.99 0.99 0.99 8080\n", + "weighted avg 0.99 0.99 0.99 8080\n", + "\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "=== Global metrics ===\n", + "Accuracy: 0.9863\n", + "Balanced accuracy: 0.9860\n", + "Precision (macro): 0.9861\n", + "Recall (macro): 0.9860\n", + "F1 (macro): 0.9860\n", + "Precision (weighted): 0.9863\n", + "Recall (weighted): 0.9863\n", + "F1 (weighted): 0.9863\n", + "ROC AUC: 0.9988\n", + "PR AUC (avg precision): 0.9983\n", + "Log loss: 0.0861\n", + "MCC: 0.9721\n", + "Cohen’s kappa: 0.9721\n", + "\n", + "=== Classification report (per class) ===\n", + " precision recall f1-score support\n", + "\n", + " 0 0.9873 0.9884 0.9878 4558\n", + " 1 0.9849 0.9835 0.9842 3522\n", + "\n", + " accuracy 0.9863 8080\n", + " macro avg 0.9861 0.9860 0.9860 8080\n", + "weighted avg 0.9863 0.9863 0.9863 8080\n", + "\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# STEP 6 Train/Test Split (Internal)\n", + "#Logistic Regression \n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix\n", + "\n", + "# 1. Initialize the model\n", + "log_reg = LogisticRegression(max_iter=1000)\n", + "\n", + "# 2. Train the model\n", + "log_reg.fit(X_train_tfidf, y_train)\n", + "\n", + "# 3. Predict on the test set\n", + "y_pred = log_reg.predict(X_test_tfidf)\n", + "\n", + "# 4. Evaluate performance\n", + "print(\"Accuracy:\", accuracy_score(y_test, y_pred))\n", + "print(\"\\nClassification Report:\\n\", classification_report(y_test, y_pred))\n", + "\n", + "# 5. Confusion matrix\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "\n", + "cm = confusion_matrix(y_test, y_pred)\n", + "sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', xticklabels=[0,1], yticklabels=[0,1])\n", + "plt.xlabel('Predicted')\n", + "plt.ylabel('Actual')\n", + "plt.title('Confusion Matrix')\n", + "plt.show()\n", + "\n", + "# 6 Metrics\n", + "from sklearn.metrics import (\n", + " accuracy_score, precision_score, recall_score, f1_score,\n", + " classification_report, confusion_matrix, ConfusionMatrixDisplay,\n", + " roc_auc_score, roc_curve, precision_recall_curve, average_precision_score,\n", + " balanced_accuracy_score, matthews_corrcoef, cohen_kappa_score, log_loss\n", + ")\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "# ------- Prédictions -------\n", + "y_proba = log_reg.predict_proba(X_test_tfidf)[:, 1] # proba classe 1\n", + "y_pred = (y_proba >= 0.5).astype(int) # ou log_reg.predict(X_test_tfidf)\n", + "\n", + "# ------- Métriques globales -------\n", + "metrics = {\n", + " \"Accuracy\": accuracy_score(y_test, y_pred),\n", + " \"Balanced accuracy\": balanced_accuracy_score(y_test, y_pred),\n", + " \"Precision (macro)\": precision_score(y_test, y_pred, average=\"macro\", zero_division=0),\n", + " \"Recall (macro)\": recall_score(y_test, y_pred, average=\"macro\", zero_division=0),\n", + " \"F1 (macro)\": f1_score(y_test, y_pred, average=\"macro\", zero_division=0),\n", + " \"Precision (weighted)\": precision_score(y_test, y_pred, average=\"weighted\", zero_division=0),\n", + " \"Recall (weighted)\": recall_score(y_test, y_pred, average=\"weighted\", zero_division=0),\n", + " \"F1 (weighted)\": f1_score(y_test, y_pred, average=\"weighted\", zero_division=0),\n", + " \"ROC AUC\": roc_auc_score(y_test, y_proba),\n", + " \"PR AUC (avg precision)\": average_precision_score(y_test, y_proba),\n", + " \"Log loss\": log_loss(y_test, y_proba),\n", + " \"MCC\": matthews_corrcoef(y_test, y_pred),\n", + " \"Cohen’s kappa\": cohen_kappa_score(y_test, y_pred),\n", + "}\n", + "print(\"\\n=== Global metrics ===\")\n", + "for k,v in metrics.items():\n", + " print(f\"{k}: {v:.4f}\")\n", + "\n", + "# ------- Per-class classification report -------\n", + "print(\"\\n=== Classification report (per class) ===\")\n", + "print(classification_report(y_test, y_pred, digits=4))\n", + "\n", + "# ------- Courbe ROC -------\n", + "fpr, tpr, _ = roc_curve(y_test, y_proba)\n", + "plt.figure(figsize=(6,5))\n", + "plt.plot(fpr, tpr, label=f\"ROC AUC = {metrics['ROC AUC']:.3f}\")\n", + "plt.plot([0,1], [0,1], linestyle='--', label=\"Chance\")\n", + "plt.xlabel(\"False Positive Rate\")\n", + "plt.ylabel(\"True Positive Rate\")\n", + "plt.title(\"ROC curve\")\n", + "plt.legend()\n", + "plt.tight_layout()\n", + "plt.show()\n", + "\n", + "# ------- Courbe Precision-Recall -------\n", + "prec, rec, _ = precision_recall_curve(y_test, y_proba)\n", + "plt.figure(figsize=(6,5))\n", + "plt.plot(rec, prec, label=f\"AP = {metrics['PR AUC (avg precision)']:.3f}\")\n", + "plt.xlabel(\"Recall\")\n", + "plt.ylabel(\"Precision\")\n", + "plt.title(\"Precision-Recall curve\")\n", + "plt.legend()\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "id": "e76a0036", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Best params: {'C': 4.0, 'class_weight': None, 'max_iter': 1000, 'solver': 'liblinear'}\n", + "Accuracy: 0.9920792079207921\n", + " precision recall f1-score support\n", + "\n", + " 0 0.99 0.99 0.99 4558\n", + " 1 0.99 0.99 0.99 3522\n", + "\n", + " accuracy 0.99 8080\n", + " macro avg 0.99 0.99 0.99 8080\n", + "weighted avg 0.99 0.99 0.99 8080\n", + "\n" + ] + } + ], + "source": [ + "# STEP 7 : Tuning\n", + "from sklearn.model_selection import GridSearchCV\n", + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "param_grid = {\n", + " \"C\": [0.25, 0.5, 1.0, 2.0, 4.0],\n", + " \"class_weight\": [None, \"balanced\"],\n", + " \"max_iter\": [1000],\n", + " \"solver\": [\"liblinear\"] # good for small grids with L2\n", + "}\n", + "\n", + "logreg = LogisticRegression()\n", + "grid = GridSearchCV(logreg, param_grid, cv=5, n_jobs=-1, scoring=\"f1\")\n", + "grid.fit(X_train_tfidf, y_train)\n", + "\n", + "print(\"Best params:\", grid.best_params_)\n", + "best_model = grid.best_estimator_\n", + "\n", + "# Evaluate on test\n", + "from sklearn.metrics import accuracy_score, classification_report\n", + "y_pred = best_model.predict(X_test_tfidf)\n", + "print(\"Accuracy:\", accuracy_score(y_test, y_pred))\n", + "print(classification_report(y_test, y_pred))\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bd2e7b73", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Saved vectorizer_tfidf.joblib and model_logreg.joblib\n", + "Wrote predictions to predictions_validation.csv\n" + ] + } + ], + "source": [ + "# ---- FINAL TRAIN + PREDICT PIPELINE ----\n", + "import re\n", + "import pandas as pd\n", + "from sklearn.feature_extraction.text import TfidfVectorizer\n", + "from sklearn.linear_model import LogisticRegression\n", + "import joblib\n", + "\n", + "# ========= SAME CLEANING AS TRAINING =========\n", + "def cleanup_process(df: pd.DataFrame) -> pd.DataFrame:\n", + " \"\"\"Clean like training: merge title+text -> content, lowercase, keep letters+digits+space,\n", + " collapse spaces, drop empties. Returns df[['label','content']] or [['content']].\"\"\"\n", + " df = df.copy()\n", + " for col in ['subject', 'date']:\n", + " if col in df.columns:\n", + " df = df.drop(columns=col)\n", + "\n", + " # If content not present, build it from title+text\n", + " if 'content' not in df.columns:\n", + " if 'title' not in df.columns or 'text' not in df.columns:\n", + " raise KeyError(\"Expected 'title' and 'text' to build 'content'.\")\n", + " df['content'] = (df['title'].fillna('') + ' ' + df['text'].fillna('')).str.lower()\n", + "\n", + " # remove punctuation (keep digits)\n", + " df['content'] = df['content'].str.replace(r'[^a-z0-9\\s]', ' ', regex=True)\n", + " # collapse spaces\n", + " df['content'] = df['content'].str.replace(r'\\s+', ' ', regex=True).str.strip()\n", + " # drop empty rows\n", + " df = df[df['content'].astype(bool)].reset_index(drop=True)\n", + "\n", + " cols = ['content']\n", + " if 'label' in df.columns:\n", + " cols = ['label', 'content']\n", + " return df[cols]\n", + "\n", + "# ========= Use ALL labeled data to fit TF-IDF + train LR =========\n", + "train_df = cleaned_dataset[['label', 'content']].dropna().reset_index(drop=True)\n", + "\n", + "# Vectorizer\n", + "tfidf = TfidfVectorizer(\n", + " lowercase=True,\n", + " strip_accents='unicode',\n", + " stop_words='english',\n", + " min_df=5,\n", + " max_df=0.9\n", + ")\n", + "\n", + "X_all = tfidf.fit_transform(train_df['content'])\n", + "y_all = train_df['label']\n", + "\n", + "# Best params via tuning\n", + "model = LogisticRegression(C=4.0, solver='liblinear', max_iter=1000)\n", + "model.fit(X_all, y_all)\n", + "\n", + "\n", + "# ========= Predict on test_data_no_labels.csv =========\n", + "val_raw = pd.read_csv(\"dataset/test_data_no_labels.csv\")\n", + "val_clean = cleanup_process(val_raw) # -> has 'content' (no label) or ['label','content'] if provided\n", + "X_val = tfidf.transform(val_clean['content'])\n", + "val_pred = model.predict(X_val).astype(int)\n", + "\n", + "# Build output in original format: replace label column with predictions\n", + "submission = val_raw.copy()\n", + "# If the file has a 'label' column (filled with 2), replace it; else, insert it as first column\n", + "if 'label' in submission.columns:\n", + " submission['label'] = val_pred\n", + "else:\n", + " submission.insert(0, 'label', val_pred)\n", + "\n", + "# Save exactly same columns & separator (CSV)\n", + "submission.to_csv(\"predictions_validation.csv\", index=False)\n", + "print(\"Wrote predictions to predictions_validation.csv\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d6984880", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Final Accuracy: 0.9948763644464246\n", + "\n", + "Classification Report:\n", + " precision recall f1-score support\n", + "\n", + " 0 0.98 0.98 0.98 684\n", + " 1 1.00 1.00 1.00 3805\n", + "\n", + " accuracy 0.99 4489\n", + " macro avg 0.99 0.99 0.99 4489\n", + "weighted avg 0.99 0.99 0.99 4489\n", + "\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# TEST with Test labels\n", + "import pandas as pd\n", + "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix\n", + "\n", + "# 1. Load predictions\n", + "preds = pd.read_csv(\"predictions_validation.csv\")\n", + "\n", + "# 2. Load true labels\n", + "true_labels = pd.read_csv(\"test_labels.csv\")\n", + "\n", + "# 3. Check row correspondence\n", + "if len(preds) != len(true_labels):\n", + " raise ValueError(\"Mismatch in number of rows between predictions and true labels!\")\n", + "\n", + "# 4. Compare\n", + "y_true = true_labels['label']\n", + "y_pred = preds['label']\n", + "\n", + "# 5. Metrics\n", + "print(\"Final Accuracy:\", accuracy_score(y_true, y_pred))\n", + "print(\"\\nClassification Report:\\n\", classification_report(y_true, y_pred))\n", + "\n", + "# 6. Confusion matrix\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "\n", + "cm = confusion_matrix(y_true, y_pred)\n", + "sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', xticklabels=[0,1], yticklabels=[0,1])\n", + "plt.xlabel('Predicted')\n", + "plt.ylabel('Actual')\n", + "plt.title('Final Confusion Matrix on Validation Set')\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c5631c77", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "mon_env", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/NLP-Project-.pptx b/NLP-Project-.pptx new file mode 100644 index 0000000000000000000000000000000000000000..150695c795c96a5995a5c7adeb99df78f27edef2 GIT binary patch literal 198178 zcmeFZRa9KHAYH*wOTcek-7%m@8MnG5vkmW7kS&#{2LWXs_XX2}p2WS?61@@UpgOS}FfgWV2=<4L681%!SI&w6# zVTsS?%o#K+vi;RB)mKGfp8|%3w1d8B7$B-AB)ILoB=sUXG(dezMQWK;3b76$``X9N z`m3m>1JrORt$r=K4eNkCMhH}%C5%0rTB0Zkb(o~QGf>}ZngC;cm4)+ z&@ke^Buc;2QPk;sdAqa zqtMN^8)TnXiB0C6?7|Fxn1w70?4UH{M6BH9+aV}HjIchf!P4n?^7Ko#xy6N18L?fv zi$Pd|Hp~Ty2IVgn$nJtm{!iOi{^Rv8)ukr)re7hV-5O?=yyoeSg5>%*G?uw4Cq<25 zXA7{;7MbB@zqc~M%?|!PEVnZGcn8T~*u@>qBBg2Z)x0S3ltL_s99LnDyl;f21%JOi z@%Oaj)d}#t;Qlz+afJdqIPq2ckM3(H$RjCqd@&16{(9N#Ayb&xex zFw`b=ehB^j9Rx_>pJ;JoH648QaYgY11~4DA&~r4gc4DCaef%Fv{5M9!KYaBHz@!ui z6JqE^;05CTMwSg2l0_p1k|&BLfxd+4`<5*;X+eXX9qMNc%cE{1^3JF0@wl^dM*00L zWqhNWnkq|1+%LCAhjeWXvE@9BnpE!ThWaq#6E#*<)s2(9@yW%!Q2^Pzuhs?%NnU-Y z;Mr8_ikyiV^u=inxXQ7@=SiLevO1fF&*T24-K<`AL}#yXsrQuLP&}^dhmS<9O=&^d z?w_7=ad}^o3TJYhX=hWDl_o8_#UE5gup|qq&AVpBGDf4{veC`dt_#1?lk;EPq;XO- zyiKCfp$M=OM*uiew$-1tAu$N@p8hsM0I9P-$UuOA1V8dA>c<`S_Rb9UjwVhYDb>K) z!p`=0LOo5TF(P)3K^dBXJ~Xrf9{P@wn~C z;Z?;s0ct5IWISRY41Dn1EH16kjLq}{+SAzNizl5{~ z9FW-tS%p}8UB%yfw^vC!j*eCZoV$?+DkOxi%~h`b_)g$}6SHk2Rp>!DFXe1}w*m-c zAp=I7>Y6lO=99>O=3b-n?Zr7G!*Kb={WugKTI?@5V;NIKyzS*eF|Qb{tj-1fi!!>7 zG2H(<<_Wff_pThpxz{+B`scUGDh|ntVK3RP$Fm3e6izHsq{Dl=J!isD3P)tv-9r_4 z2*t=jBE2>wdk)%&10Brd%37`BW(^0(!gROB+dxl)di6lpZEO6Caw%4wsfUcj zYY)ZKRuu8wUSm~~+fc|Hl2auqeqE5(xg~Ix)kIMb2^Zir2L?kojg9BbdGuq!wQEkNtHe>f96wgxRK3)$^vO`bhw zI>VE;Oe}$O2ptnCIw)0iCxnii`Ag=7w>z<$<5agmTJEH*l!^_k{b?8uZGt6aW6rhd zdrZDebr96!ObwDMH*zc#KQiP7R1q(-)bdXABIgHber5dJfiygAbl z)aVKeAT!Prp|=4MV9s1XiG4>;ar_EQO%t;;FZcepVWm6FGkpAUMfD@`5dKG4Iaym6n>aE2 zm4p7AF#nFOKiQ}PAS>O+h!}Da_)avoUU(K5X5EURsc~6&f&e+p3dc@hTo?KJAokhX z01Uw^(~W%c1-EY9=P^8sDIrowcoat;)0vfC1IljjbsdC}ni`X>-yhkObm^{%V-+J) zdlCw zKgjjdZ^;2ObD*SD9$%zIfhe9HKegEs>F0?=_pqY`TKbCNMC%%J7av3 zP^+8fN%dW2o7Qj7O?m_`UGXdpqQ&nslW*&_swz4*Y4yq2Cy0%by?Gou)NK;7GgA(b zLV7@rS?_K^${1xceo*|px))=3B{GPB7N2Ls)mR@p!fZ3@%BL59k`Ztb>cv_hB!cA^ zdLo4qohRoo;&O#wSsYcKw~ly~J}0S|?3e(cBu29s_pcswxhM48zl77jp!!rql)Kfc z)A#Ev9+gMFJq!%Mcq@}^+;G&O{v(JAaqEsjA7QlyMBs?FG} zBuqJ6At@TfcEo130^Pm+>f4F3TI|=+_K8@#CSvj!gqLGI8kzNOGvP3S>`Wx32yW0+6pPV&Ux=N)Yc5y&)&r<{~jZ>^Lj) ztFb$NebeJFegi98qT;W#jH?2m_j~3OVMcAVgj}GDgx?(}LAwDsU(i9V+Cu2CLY>_- zYrbR{`NlF$Q;Ly=@z0|7gh63mW!&6slZ^^gTkF9B?MYd1izzb~yVbRqLJ>%UWs`u5 zC4l&J6`YVs7P&St4!TbR%eCa^i~LyR(YnMK_}+eF^6AG$MUlmL3euz6k$&j2-`m~A z#0lPfJ{TK7zGwT<`QZs?W#|WX5`@RtqVo4V@!mveX!#PWK(5DWr)d{%K8&IK7u*}% zS(t4k0KAw;B8EjcL!1fN4?Ru-cN#8uUySH;crfF_W7ri=U(z` zadrdc+bV-EuQg@DnMR&v+FU%H6Bsk{C8GEQCi=~7{&B;sJ4c%L?`Z@5A>*S)@=`Do z?g}14GFpOi-A4ci&Y|9%))2&l{?Q$LFMV9~Q0)8X_-k!k^3E#6`3q>poUTxy__*s8 z05)fdeA-xIU$~ECWZs(>U}?uUvsvsDT`${U6;sUml!P@!n2kWV_27%hSYw+I^tZgY zg_m)gls&!{gR+Rkg$mtE4hx;{>ZXYnrP3;%RiEsSj>+Yx;jRwovW}iFkuoH|8 zu_lJ_g1afD$iv^o)s1y%xST0H>GrdjGo+A8Ts#L^mBfh;`bea#I03m)Q0)qLP2-mb zk&Y|BbX6!qxwWpf94`)&5)Htr4m@7wxd!2d2d%7}bPqY}fS%!`ooen3fg?+o2f^^t z4RHGcteP7!f^sQPj1oUr{Ul4?%;8L+OxKW_IwxePgGH$w6q`C%hgmtbMM4-C92>+D z5wwVaQU`F=eC3mB22t7I83uWlmqyvC@Us$V|ICv9oY8=Dz#D;M|Q_31c9h!Q$GFbWPgT79wg%?sTQMK8; zvhS%ZnvV-$@aF85cH=CzOb$NTn0?OZMdHbhnZ_NWL)m%ZNtuv0wN#4E8gj8;{acjz>@$R- zetQ|2TTBZSo7z(cl6!ffIS*PXLur}FPJ*>F#S@8%D_w6S4r>lyqq!>D`@B=M{q z8NV9%Qu&E%iIebGgQ`q(a`|N9*K$Az3~9og=1BENNZ zb%6ZTs~4nM5YicFhG--y0wLuS%FKR}m2RkvrdM#TS_Zz?yq~_8ES8Xp*;|st{ZZmo zp8&*er-oMEQI`L-Bk!geVM|#KAii*mB54mY$47GjOg?8ZsORmwDD+F>Co~LMbUMkG zPskIzzcmqz>Lv|9njWae-tst2jOsRNi#nypAD2>E!28SwntT;W8gFGHX{xbIc9qp} zYsHehmgCE5H}z%8B1ht*&leSQszNtlCBvnx-j~#5D^IG{tTb*2G}%2xmm~ zbmK5ddjwaT*69Q>b70{AksrO`fckCVu$C?Tz0JUy6@fkKoE^tmogM89)pmBB5&P+v z@bNwDIxiCO*ioC^{yVxw_0O%zN7!N+G`&5^KRH8)7w7pF@3dJHbcd;Zg(G3Zg*$uA z`*`xR)-qMUz}bX^?YBWDuqI^`wh$}DtKC1Y*Mwb&PJ(s>ENhDiS~x0P!b{2DNR32u zfGwbskD_PCM5v%k;*Y~j=~X>S((vy;P$eZP`BFL*J~c;u&Z91X(app8bYrt>D_4Au zAyW!<3=$?C&M2C0r8l4-f$$2y;IhOihnYe_gFz=K3)WfJW165iGKU@#4zgIrVF6bF zdi4U3lLV#k?kF{P(Ctgy1LH1ns2k!gm2qc9kW4PDi4Xp1z5i7e^=ma&v1Yl}_eE;B z7a68;frw?QXQk=p(1{35r7Ke56ld^#YC`Dn?k}<)LQ>grGoP{dvg@>pE<%M+=`h33 z^>U3z8ZNKPmGTLmvTrK;uYiLG9*Ce`wIjC)=stZVlAf~Y65F16AgxzK~<)s~_O%%((%+VPzxV1aq=L`-kN3FR8IY1cA#t80-krObK zzMNve?0hP6H2)AWfgve5OIl(+W}#WBi95an(=)VJZlXNuqR!Gy#}c23-zS4B-n4$# z{F%dLwFcLOBAe>?VqA{a`uP(Qj?wgSNM*92=ZQgNP2yFrXrI;hh5nosk2=f%G0E@8 zZf`Fa@2n+n`D{PazrHGH9z%k@kkJq$3GcGZd2xktV&Nx3($7;Bk%qns5bA!J<@Jbb z84P7-8o}2^;y$+rpOk#*ic)K%w1Yuc51X#=w;(_)j4K%=DojOU&=|kX8M>~|B~A6E zQ^^pqrhTxhe{UXK1sb;nPDi~W0vfOL*{o@2&*dT?s5+587!tVo#zTX0thn~YJ8e@#Aed0GV@6yI@4Z#`oZ>Nfa~Rzvz-%6z4%-Lwoq6S1ROtM=@VG&+=(NFBLV?|^ z*KvYl(N5Rrp+_tagZ9YH7e>U%9D-;;n9@Rn zz|aO$Uk^rh6h?*vH!b<*N2(2Hdzd2DVJ5v^HRePD28kx|cD~_AY(8;$PBtrpMr*O{ z*7Iuw;T^{yG~fEP$T(AI$bNGHFe$^c0t*D^lnd{5P{4~99b|6HQ}P#Qt73In-EaGv zNIL4241{*WX3kw24m>5KRbOFL$QyAx@bIU0)poaE;WaOXrR;W4P^_O8uq8CW-NT;E z5Js=)PT~-!E#uHBnzH2#kl4I#m|j{5+yg?{ths@4Z?0=KjRtrK>Nnb;v^Y$ea_Gm?J|hXr-hf!rESM`^mjcsO5%$f5lAD+Bv|z*6 zRz6joTeSW}@DU&6=Z9bYk`0~JaUFKD9(>;9$gE2 zx0cokP*~PR3?=kxDhVsB?N+;IQDvo#-S|ld$MdHIP895*L(ori%!({KLYHFhF(d{w z1?-_u%{Y@g+WyRWTghiICD6^_muJ+z>bNk5VDD%%WmlPr&PPBij+tZFBwF-UyO+%u z5vi67jd=rV5MCl!aWFC0dG+1P&)@^np^-$K8rdfWTBolKm z^~5w#0w}iiEl`NXel8C*1}4!6+Y~jE!HE;(sR~AD*Kk1PJ%#5gGVMLKy ztRcY^WlGeInSD!JRDTAy_7j>t#p#S*Hw--q%B96gNx=USeOsaf!b&_aj2Cx&qG0MD z_~Pf%7bmwkNFNk1ztOEyww>(Ya$yV%?dqbg=M+tl+>f}Vp>`}Gmb$yEcx@##en%`_ zx1AFX*f~DI16_mpAb`Qg2bC40>lLm1)(fxq+hRfq_&kJiaj)PUj-qTpMJkYi1J?IiBNB|EG>}&F<92o%F zT>&PjDjD2T2`V6+Rw*VhIv|;zIDQn#Y{-``ONlrpXO#9F7-28=Q$f@LT12!^^F(fT zT1Us+YGeOa>m5k5? zqy%pe=p1_9&Yt+a?WnSSyGa9SkMsnb#-htA%MR>t>l~UWT_h#ZZ>>96Buj$Cn(}9- z?ZS%b>>EYY;xZ&uVBWos`#h%%4r-Q_n0VIBiO#|qI%l&AdbAIfd16+!PMRl8v%${Z z>yjL?*(c-gvv^gPBZygPQ_F3p9@lU)o}K8)Aw(sN3+j@TNF)=YA12G(dfZgmJ_DQ# z>t3e^Ig10r3}Xx_iDE!v0>iv0i^rl%BSc1aDONLvBrTn#Cs&icgtv8%GE2*9rVNhj zYSDY;!PbGXLtc2LBWo+v z01_eA;?KiVL=DP8JrUA&vKYgK%q}-#Dbj=J_u^tDvNT7#s1m2?@Uqq} ziUXS2O-{R_;zr_{Y!(wij;;oqxZQY(?xx80C!Yw-cX#a~Tfc{zQl{qFHrDS^7h5Qarx>}-;8#%qN^Orb!h zbqVn00j>FEx*4}Udr*w=`bhVX7dqhkD9Nfuy;8L+1)AU-T2R;7hk{bb8XIZP z%50fX91xqC^5dc734}@W0tr9I18h+Z^NW{OC+Zp$i!z}WgZs&YVK_$o*T z3L+|{5bnJ%4p0n!{k9fkrvRMWw})ph{?)k_leLxYp!D4bkjk)wKf%m&v9h4a6l7g> zk~&G0Fs@C`{tWL@J?JcWHO#Qp%l9M4r6BaH8|#)a+ol#v7U#HVQEUQg#jhG(rf;tB z3Hh#qda4VBk(`>QTr%BV7&D@VmTKo0f;<_0B&JqF>v_zDm z45yfKFqfh7rZV(?Z1K6P(juFWwF*^2qQTv`^@(?-;P$sBKllcVNfj9XH-eEK*D=$| zv>2QWrBB=MoKLGfLXP8Ek5#P+CqZa0m=0theRNPWIgYy{R3%7}r6rBd?t@^;YwfO{ z4|vTeJ9G8%(_6}=)$X|>cyA7I?Cl8pFDIt_+)zXz79eS_(|UeyZjj&|KMs93Z+|pO zJ1>6QOc>f4@Ywu*bP=(W9pOL9g%4q32{+OgBaD@R+a<${IzkDG97qKKI2Ha<01bqR zRj4JSyh%J+$2#@VQ@CFu{E0PtKF|Qd7(a%uExU5_GDtFthqbNKyjArxa82<`9IVmg z4X82feL~$*!H_boaHiA%<(06&hSC5bXaAQqm!-QXn91hL2Zx{SatXZeQn_1|0f8&? zZK2I0%DjU7k(d$1J>p*=1G_|n<&6k_%xof4HUr#$t%w&-=3c@=%fmu5Il#}(95O({ zsJkVU)1LVdOWU22R(AkAe#q>v5dCOf4s##`b;D8`0W0+v|6C$NG~A|tED9_BAV=lN zM5@MkF>F+4zdoflIpRvv+icCWWej~&PkX=3=PnlCrY|Z&0XxE_9j%R z^tV`BRnTVom1lrxt9>j>3dt)eG9@qQ9`!hset-X<@cFJGiA`p~9Hmh;>3e6@ zkqOEu&+W_Kr}2mp%WDkKj|>m{_i3Ew_Hn)?h=n!1XV5mov*2>vX*G@pv}1 z+!%O!HH}Dh{n);H3*}_|UEk<#gg52e&^gwy9!8r^F*0OD4yEEcioPI(N{rNiPtI2z z%{gm5B+qh7qTw332{;`g$HnugWhlBl0F+3sUcaB7w`yCY_^obA&CPYC1aaC1pf81B z+?EPZ^GTJajL$r2sT$y?sP3u}w#4U%+vAD) zxHk5J&3v-OB71NGV#36KZFGg8wRK+AWqoerv^BO8yF|cCfj6EX_HGZyWtIVyXx6>l zM$j)ORhxSy0AKJFkbensV%R~Ib7%D5WDuOYP9%j7TVgQg$TJP z72o8$8#U;{&7;UygHvUJw070yJUO76P4=RV0Z3tb?ZZTlLp8aZsAH$QBIT%kWJM#R zYMe>QRve=rwsv#5zolBxmxVA{1z&ZKb~oAP#kQ2no0`Cpe7z!M`eF?q8yB<$r_N4t zOFAT}AuwUC25BlfHZ0eLQve|-bHw9gIQQm!&vM!Qs3RVg%k5Z>wqmqIFnE>dw9^XA zWR1zch1V|;G z`Q8_A@c8m+@miZiTgYdbrWtc+-;fP9Fb>EB9g&9yu}s5ZIdlGZuzd*zCa$ak0av&J zi3`e4ZG0dXwS{5$P$saJ3s|iIV8o4WPlj_fA$ntLL2(N49FGAVR<8aDLBh@qOWD-7 zW}9&kuG}J0xoUHXRCD)I1#F@|>PB$5>7>&tSc)??lduH`7wLgs0gaz*JfXONz+?)7 z4v8B4TYjbsE15faH28Zw`EN-AjcHGT^4H`8fhTJXfnxVk#)Q`$Uqx{UT}cu44+`^rEJ2oQUe3`zaedCuPJFcW^^WTemhIRO(nT&+AfM zM(SGbjxH*it%FuS(*UA_*lrD>e{FLnNCB_nnqMnxvlWZi4aE4-+=uDP1heqT7#OS* zU@!kVtmp7xVMhgS6h|4Hbu3fORLcJi^R(uI;cp9q%d$+Cg^w!}ALEFGAAf(3PW)?+ z_fH4&uO4r_(C;2^@PGDrg+8;dM?%76JHG;pFxv##AT!q+zPDcyHq<~M;2(@o#MC42J_f7Y_JUyKQqr!;AIz<>8kcAlec{#ZkVHM$Dp)!|CgX#h9>StwY2Zw-&c>n2h@S4ysVtMUJ9+q zyySTVhzRb~brBd$9xLnFI>_=QJ6Pplp{WhI!{l6ingW93Q>;gIfE5<{FN1}j6BiSY z8@`5E=t*pul3|n?m`kZD49{Sw0YwMui_T94k&?*UW%PfxVR3q^O1dPli$73><{QIjuM{b-qbi5}FK}qjA3MIODcXaqvPZaFS{k`c!NI`;UpU7ARb?{OT zAs{E(KwxWEqa;d&Lx(ycfjfD__&`7>)^wFMwwM-csw(vulQz+4DUf>{>%B)#2ZOJJ z)Gs@3SL$mX>ClA{tj4#hTT1i>-684G_9}12MJt=PKSA2cm1Qz-l~*l;&^bPK40Fcu z@!kJ*Ror0o=ubYb{GX>&{%mOcuj!PJ8M(ivQ`(1JBZ+6M8HiCmXP!Yq#;w_%Z-f95 zFBj2a%>mH(p8sn)WhuN}S!RF-%4!3MWYNncGx^fhTbB<=8Y`=3mZklhJs9knnD`I6)H}oBmn5|^C47c4~j*1!YV)qenGKBwwYavY&I5DXIj>k4DRi@*+ zvo{=q@usJBVr5xW-3l`CmPu1Bs*AV&ni_u0;+*rh3+0Ju99P*9{Wp1LdF(G&93B~zuxHcAD_6%jtH>SUfdX=eutB*9 z3#B}c@jQcc3+%Y0I*su&E7*^qBg>mz1CZOnso^?csfP53M{p7A*V&@kSYrhzDl(wg$tKZv;K z9B#_Ws6x#&$)sq1s?naRYzcI^4O>q-h`ENt#K?GE(Vdmk(m=j`BOV1fE^{L#8bIyX zUFX|!+ub#}mxI}KMcclbOQm@$cA3;J+q|lqG=_TK11da;RKzd=4a~e*_pJTyfeTjO5-4ujDT^LC6xVdc5-cJb zGqBE3)jay45$b!Z^20**+nO@F%VMn&w=33&T7?aI>GsBJl|w7?RV(Uo zt#S%Sz62aG96AhuqEERRg*Fq$LU!=-rwFw8Pb<@>@RMda$gHkGU5Wz^{wSA{TmLyJXGEa(zSfE2!TorA{g0ZNM-eia>G}!1~e{v2x9O2 zz{^9IJ!Q@GRmuCTdbBSYCQWOLybH0RAzQIUwW|LorHao;c!fxdXZtOE3Q zx^l>=Qs$ekk;q;Ns)?X^J$Vg}E2tVJe^?s7(GeFAJ+N|!(Ma)wOpT3tw4ryzWMX4| zFg^_+v6Ntz;O`Xmw=3R1Yfy}W=e0dG!>GG8P^O249CWIPYOj^;QF6;;W{;R{x2Mh{mX(UU%pEi?&cZC2h zG=vfpb0(Yk^kt@sjSMB!k4E=ENo>M;YV=L4`Ot{*pGhsNi1 zp;_%~+SS0ab&N3``kmLy8@uFV=VRH#78F&L^UxSB1GK$Wecv0ITF~zB_zp2bc|+>B z=l|?iHa<$1bzCQF>PQ#4V0c zpv}1xH%&Trr(aDcgjl*NL&N7UsQMvcb+2GkbZJ+^v8kxrjVPYe3&^fhV??6(n=E|% z9YvhVeZ=NrkT|CJ?Z9#aB0ia2^%kzhAy~9oa5}jy1TTT2Mf+Qili1_avaJO!ry<@I zzQH2+KXb?74uhRyV$N=>!A%nqjI0h9K6L+ykUw9ZgL(+uL-NV=J8jCZWoXhXl zo$r5UPlG44gNG|aZkcr4Psr2}hZ9F49gvse-p*n$b#2iyPFWsu)rdC~vQp*u^t5 z=g9DlOjW7+(8c0^S;D>`nGJHA6s{a8r)AC6!IJa5{{&|(FZN*HO9oyK{C3|hyc~*F zI!m^rxAg6zV6bU-k_E8FW#AqGOf!`P+#k5GIV^8fNrO1%6MHYfM+tS^U8}FTw6+_W zcfUAByRo73x9-hXgi-7NW@-Mx$NlrtD2@F8ZD~#$1Fy9|7OnJS{V`>{o{|}*lKlQ#cOu(lgjF{WVAeD?Nh0($V-sWN zpXxm*I4!%E#D-zzDWJp%)2OjEO&;Af1lkRa@shyyq=Z8l^sjjRyi*!A0GRo-o=Ol3|evbWa|M(^7M0niAv>L*P*`-nf4=d1M; z@{137c_ahN)Cgb&!;D{SZ*?zZXdjo)qaI-4V1t8% zWMCWI6K!CJ1U%S6SkI(Ldd{oipWt6%^m?Q|foF+SKrEw~+}(qx%$MU>GourBMgUGU z3Oj!+ad8l+*sU%l`5{4=A`zYWeHQ3tkh;Y5(|G%MZsK3fwJAFy=D$n!KciQ3|4H_t z53*Avp7#AFd$a0qvLF33*%Rg}qbj~_kBQ}4Z*_DkSGMrU#LdH-~xPp=i4 zbbYu~w@cmwShak%J1@$hW1e^CJTPRSEAG(7*m&CH$fKe^J8T|FsgX zwyAr=Xo@q0T*%&DRrIQu>SD@5pexkGDq$P}Nu;Zgcf;uQ5l^8~WOviV6Gb zvZXDn8-9)qYQX`xJA-3b1>fDRsU))hFO>lE#iQ1m0=uyEHYN)bJH~OB2`?1W=X~ZF zay|rI?Ip?+k=QoZYXe%41dVKBJ5=&J5y6c6s^k87B}^?AH8${aI>i>RhGiQ_JqyvX z5ZGdLqs*?Z)bRh!^1JU3j&!# zCaLbVF{m$`ye{y`x>_?8z ziG3x1Y5ig+AFWeLN~{<=aFC_haWS_2|5gcM8X&nNAGH2=+}>Xeh<|3n*?%fw8Hj?Q zOJVMleQ%uNStkPq)r28vhZ=+>=je_X3*q7-57ksx_q`UHyKDS!B)C+sd=d~)J)nuI zC@3oyrqSKvYkF+ueW_*tFne_CC+h!}*(3YQ>?!{-d+!UUs*ZcekoH1Z2X;R;mY~Kn z15N$45m3qnlp>HY+qSXj+cg@|*nT5H?Uqd(<}V>w%sxZzrSE?Tp$y|g2tLb@f*@#M zzlG33o-^Yy$W%%1CSvj@R& zf*c103~=Eobr8I$-aFN<;NtuT5-xb^AD7aW{Wj9d%Gl@UhqJ;vozWy(6BOJ1 zc`Wfmej`ElFC@5qAi=X`#P4sB5Tzw|@$U+O?Qd*AM9D5+l)Uob)cF_8hu9X7;_$PjVIArQ)67_;LUf8wa06j$j1IuTS9qRq&IlAk@7^AlJ>4+22a;*SSnq_tK?guN@`!IQ?i$wAn= z*@SV%Cm#iGKo-BUL6n?%dT6r#8vbQrJ#&bB7I=3&Pe_&cL36?zP=8YTlQOXHQBqR8 z?WTV$xm>hyOf322>DS`13!`#7@QH0pG9@M$xBwyUFK5gHXPGC@)0E}OeorsUQ(-cs za8K5b^RaCoGt+kuv$C=kwG=Zq^0ygP!Xr7cyHCE#P6D69kJM}nMjuni^V%e#FlR?q z|K24Svg)Y+yF%djCn5ah68=9-1nK`F!aw|=#caUMUiOEH*Z%0I{4NlGZ!!MwV$bOx z-v6=j6)LN?+l+`ldKT~9*IwA4ewGP~&eWC76_qv+Y;lKtK3URTRajDe_ZgH^I<#30 z?dZFAr$5LHKe)A4cWf|OK~;)!aGv>ibcniMxMJ|}+!Y;`kvTam%ARTo^CGR=Ea75P zZeBuS6gJS^K+HJG$!eYw7H(Wqax7d$rfXg57@)yA64dfw>->6-ws{s(+;@0&e z*R4_mGdTd*N|9S9eP)rP)#vcYlSz>EA zSwccz1B%$Lu+q&!t}k6S+Hfv|nk~DBCVZ{T(f9$H8Yf#P`DCTG^)3VCQEWD1;Ki65 zF0JKVIo6^S3SGg60@m-=eNA;HHz0#0sFF zQ^Fdy(1puFK(; z4C|-6(&MiaMry0-K*1O5)3_tAH>m-36JILibe@tMuHmg>q{* zAFLFzr5EWE*E;gK=X8vA(1!g|18NOhx%f%zmr22qJNf*orngvs!>Q@H3{=>g=TOe( z=El|o_NR|d_P>^P^V5KPX{wUP>orE2XzKf;=q!!^ozbbdTt_J7V@e~Oy1;-2fS}XQ*kkH&PUm$&U%%)9nJfZ0aVm@X97cDnyp?% zk3BcW?InEi>QS>oovX~#C`APQ6IP&4g**3I7>~ZYcZGOs!+Kw~CmUBAi^0k-ytqr5 z!gBExx!qdqS~3f+r1Kqwir|gfJEbj(tjalbjKqdFVWgtjaCKoie!BH^bnvY~mDn^G zR(=+d?O!i!8n_FRZUTD|2UN-p7TxbAwin zPj2C0+4KFL!s^85DPex2E#N_4Imk-poT)^Azu{;lgqwqJS@EEXgl)aPDz7JC5>;Pe z%MnimG?xIKFx&vTE>|OnbW|VO0cjgk2hv`Q5!r2I>-c3gK<2mr&m@2Z8 z?^)PPeoh3-8Sxi*F56m4%WNF4wpyGW-v`o0)@Vs`N~nTainL#BJccOTi@o)6MHQ1m zfJ8lj^|8cqsi9#3bJYq!v))+;ej^7Dkom{+DFSeT40BAg@TLqq<`l#E36=$N zc;6A$EO}YoKF7JG%ZZN#3qo8P>~PD{%mpP3ov}NO!7vtFAncs^yep#kO7M6WH`I2< z`~rm_9MpuKAsqMDOCy0wpq>{;rsyupnH9*bM95r_(HqN2Irn?`Oi69}NRrSg?6=Bh zG_86HfoK4!pV|kscLGVuSmy65Rn9tLpM8Y>o}3}ZeRwJZc_nhNv}G9_MO(nB?KH{1 zY|(khz%!O|LtFd3SZuhC75bWV)>;8fA$~w#M-)?q^E2fnzy&|KSdsH{ERLwW?gC|| zPkvzi!W%)r+Z+wV3>G?3g#C8Obf2+xm{ViO^{qg`d7r@7PQIm>sSJz!maOe!n8Bh0 zGVt;z!K$~v<+Jcuro=n@=}oE|`8 z`8IigA%NDPZJZl}q~sNOhK-LRs+Um=<%GRyM^3)oX6Ew*7xOnQ{t6xUogeTxmKzPd zzGuF_6axBO<|INxT)p+J9>x-1Om9vYnhe=4F!Lr{b)1=t0wSbk5Wb)=H@ zUBAaW;(F%$jrwy>T~F=|dKZ7Ue2}yx-5BY-)WK7CwRJE>$x%c z%hkHO@{O@eTKS9H16Dw|ZN#aTWld~U6JkPB>byhkbEWW^YJC>X>&56F>RQo=h) zNJyyOW+_A}#x~@wK(X+qwl@(jki|oCsGA4x%*tPap?sr>`rotC8U37cmNFD^Gp}f! zrBxT#?p{28-Y#HcP)BNz^D`(zqf0&9uU;o2coum>PC!O@Ljn>}356t~e`y>jJ~vAs ztB5%`p8;AsvH}f@T240uyjB@N3VJH_NrYTUrgr7zN zW)Lq7BRuq{*=@hyk$Ilhk@~Ln!;fEyi@BvMC-oP_t(y)Dnod7|Am>*ga7kGEY*E4h zMX+0Cts*8UCxD+z=U#CwdP6qQ!eI0}pM=&5WVdxG)iE zv_dwbAYl~{{S2nDDrzA0T&W|#*h2w34>BwV<|8sGP`d?KsNAjIV+H*dM&ezy_O$RR zdBXWS=U`mWsq_5d z7_>ebzyIVM{&S?{ADqKK43_+H4t;Y%R=tF%5SK3>zl5^klU`_}B__*YqOfG)OdvQW zO)RZ4m%O(sPZ5Zpu1Ai)y8yzlPW_p=|n ze|Ni2&#CF|GiRpG%v5#NQ`PvT^J8W*Sdqt1c5lI@$j#$e6MndwZ6};zrY6LyhBe+0i)83Yivc7-7vH}rP4DU7!ZT765an_#NdXaQHU zKFyrvwFuFDJ4|!ZXz^58f7Tr#5I4X5|LPt8b?xh4D9ryp+Sh-b3;$eZ{WsG=|La`% zmjnHO^1JXaU-|!JF8tHR{y+YU_@{ySzZn-48a)LU{>s_^EUe~V5~41t*&dDyJ>nO1 zr{6X)Fq0|`*Caz@EUCN<%hYize>~rjm5%nkiKOBbhTo%(~d}%`T{9^TrCVU@w_n7hOE0co6fUe4Aitrg+ zq&N30{AAbm8Ma^K!S-!2GzCOShL#aNZPZKj%*!3y;cfEw`Tt+rMfO8>!+!-;^Dn7U z_kW^lQU?ElsyhCw4FJrBI(8d4LJHTbry>niO2RAa3noXN4amickuY<4mJj% zbW~8f#f2)u>Fu#ea4t?G(+4$MyIiWBGx|{1VokXX^dpUFWhQANL}L=16L%R#ligrf zpxk98@zuO0zeCNd7tZsG<-bQTWNe;5)i3inMUYhSqy8Db;Qe#))B_=;>uUZ_rK}S4 zi!1>%OKxre@6w-~?B#DSEdLv8Q2)~ZC{%!wJ1eIPQvl!}jqq>JKaBC#e-li*|MSSj zZtd)0Y35<}k71O*4fb#SM=0693Jl;Mx*Y(Zq^1f01pQ5U_a7w{1_1iUNvS4s%R_?!}|GBFI08mX?wg0%4e<$Do8$lY6l~aG{amH3!_c{ zB2~^_c`o(^B6IdW0kHYaKQu-snq5wX8RgKW#dAbkRr7?av;w$7smkx7Rr8AhGFP19rcYm%&=hk)$oaluS`leAtOYjEuht0 zxUwlOpvY*n^T0QTtTAyEQOskmz=!!?a04 z>5gecR{A)WSH$a8(sMGwg2~zYAU{$o>1=a31cXkUZ6)T6QiUT`*w@8@x4GxHGg<-V zxIUG;3c%u$XeV=uE=;Hrejuz#{!2VpA$z8q85}yAPIgUs-OZyx6h7@~qg4&!K zR~id16|TjWUG%O1#RR%Dl|;`JaT;7sok>(mANAulVd8hv7ACe@^OHQWj2!nAt5g)p z`O9M~G4t9n4c%BRt)f!6*XZVqefwdMUT77dgO@0BMCMf547LgTXUVp@xb%5J?NMJc zkHFX*7Nosp+=fTob(tPrd0rJxzwP5VbIbz0)`4evjhiUgApMU`X(+I9=1_R1DV#6* zrwkkU;wxoS;7{BE2WqGucq}V(zZa42@kfu?I;2d73sr;LroFJ1Tp)A-tlc&RN`rqV zHLt;`)P_tBIw7^6G9!+f8ab?>&Z>PwcKc#+;%=v23M{T~8`{R&w%+7dtiQ9@J!N~p zcy3@@P4Ez7vYo=TS#nWsA7UU@^z{P*maobmtfNtthqHn1cSRXL+<%_&ozr?Rm(m-l zX_=ztSb-3PXauGC$hq&Pjs9dC`^!MR)py1q6qb>_uV=9{=Fj?R_VJ+r=BTSi?W(B6 z3)8 z8t*PCT-9}`<^Z*Ievg!{!6G_WntAwwHb9k1Y9`oQX3laCnx%q=o(H2XO>4u&4N234 z372n6G8^k%l9(t-azQr(jqw*rJhU%MTsS88?(zm_lF-ZCa0i$mlPaD-l*dmb73WB` z-obf?!bWz7-I`r!71-U*o1PRSc0&N)NI`5(WJqdi66OhpFgWMeU!qjiMb%qMLW8tY ziYb8vw8o$U2-*-};l_*q%$_ijY>Ss(n~CQD$fRRfZaHxl(FA2$=*O0j!og=Fi?9mfsIjUG_hl|gnXoz7@G!B*wU>I$nyN^=*T+^I!Yp2v=9 zjiTiQs_H+duuG9+s}rqxskJoFC<}DPs|d&V_Qn>xSLB~9IdV=FeYQTDl!BWTHfaD7 zSQM_-PbktY-*2scV`IeYD318KK6WB}W@vFrR(aNPABJbzQdmSf>6h&KX3A>R_FH7b zwVFU(iHP>xSkyoXG~)IlRBM5n9ti;jjXJ??PSh#_jg!FpMfRhBrn%|r$g@I=i%4Nr zT_^&f0GraMa8EYFHVyAgyXj&J;AUV_r|H&}r)vS~d(r;LZTSy24qjD{+ zC2V;~SkIsYAj@xV`zCG#B>~A@-zlv1&XgrLwfrJaGRY0EVoKT7tHAX8Xd7&wnIz9< z(dl5O$6lL@z`xKBE!`v>vj};UY0|QN7|po_!KaEXNDvAE{7a2p+s_WsB63--iG3JG zia~GDeP=cB!HLZAgvXHjfE}i7XY%$>j_H^w#@jlU}CtXcJQ=`}6WQ*C&whySQVl1W@vdtT3f!alsKOHc>>o2!>6> zE(n*4bUW%SNm0Gdp~)r#qrGin6hNeW|eeB+!gwyx(m7+EkaA4?h~MTZ{YR7lwG+&>9O@gQ7pN__*0^hX*Fc*L?M` zi1%VbsoUBFjY$du?tJmoaY$7i^zqi^KXlGI5ouC!qHR^$zEor2buWdVW--lk z_9&|?gA*o2H(1;?uXR-x^93yP;u@z?<&N+iF-VbP+q%oT2RbOS?i@LwKlm5wJT^6) zcsg5TN@Y}d(C(N_fl64&M7ttEHG#Sh;#-AUzq`+KH!fvotOGL0@Pczyz8d6y${q2H zT8}Cvj-Y>_qkAmkg49=SB(+P7PsEqQm#SzUYecAx%LqDN=QhPxDF`S;DP&2W(`nXx z*EuDhkNd9SVJ9qg0kd&H&nL5xiQ9@(pG(RUp>XURw~=11Z3k4ObECah)=Cdi*30f! z?)F^lfOZq^mO&2?1_)e?_J7ADu%33BC&xx(-Pa1EzZSfxg&(XaC2r0Ts(fM91yr`z7_;6dap z)|W4%aM=Tjle3uKxN&4YlKVGd3HYp3ox((*-OJ%)d>^?}PqkNd)sj-ld8ve)zlO2E zDxXuyiqFx~ct=?ISot_~*jrdmxXfTwIv(=HhzRxIx!PGsAV1@WO1{u%x-0)T^ z5`7u2Wd+KLEXFR!JVIacaT*{<6OinZK#VLWwzW=@mfV7O6zuEA3IoV_H^G>} z3aO)j@Fhd~_`FKD6N)ZpIS-l!o+EeAXoywGrb#2u9M1dv{*_~ z1kt*#4>I5q4j`6&Mkc~`1Fgeon8*Qfzk|RM9>L$)OAx|7gKQqMUGh@UWH+wKvK(e^xg91f{Df%3ry;9pZ_y!e5mg>QB(O0~ZjTXIJ8aA;5E* zSF%hh;e;cMcnvI4Ij|$x--me=3m+AyHj==Ztb&zSnXM=UAwvusPYDy9Cj!orbIA4oG zJ&B9Gm*;T_9@x|w=RbSi%t<%lX4OzK7zx#jp8rak<+K!J!R=>@!)}eno=0(MjhRb9 zcjfq-oo6&jNfMxh80RY;rexkkVFs4st|7A05@b3GaNQ6(A-R5SY`A0RKX9EjK4{b& z4Qyn-*{*H8IpKZo6+LH@YAsSr0m?_aQrcg-s#rkl|JY=O{vx;!GoODTu_$ftZ=-BoeF$({F`Hx_i)DmL|pk9DYEmz=q zCofcsS{8a7Z>zHKIS;lNF6UtClxlHz%=3$||2#+2u8mK^tpKni2opt$Qw)`ZsGi=n zuqYm4co8mfTbxTrpMKy_4zE}BbgP&45%O9tFkA%dYy^O_-sr=z7{-cYmIYHI$^h^e zE_Ceiqv=0L6@LB<77j7ue(=_aLVb$p?PPk+fSsX-Vi93J#n-HQMum{9)+wy=0&AO$ zoU{E5ae;-!Kf(JJGpLqzg+yJwHMjzz;qw4s^3tQ$i=){FfgsE<|9*6 z7PpL2R0sww8O64G&N;pq=pERnrdH>GDwb)R7)Ar=5Xgv0%s7jeCyY=UM8?ChLv(J* zx@l-x{hgz#?&e-&=(shM_5RXFt~s$&SLx}NJ*@9d_^SW#932BjR`v;%iI@Y9^P~iz zapXkn8ISmR%8tk17J;%Vh-kYBM$16@oxm=gJtq*}7Q<4B+^;SCP>>RaU1r?4@d}IP zhX<@m8@J?cd!A}WdbDYTn#x7FlwXFQ0nzRcO`yQ7znV2^UqlsH7ti~ecny253bh}P zAc&ALJx8HlDU@28d;PF&=(jn%&6HKyNp5d{t+r6j6OIQ0leXh2%L_jeq{0&3V2J+} z(JfQ(+ty$!ciNCt_Gw3zhp|n-?gy4>ECKQIJF2H0s5q(b)S_bGbHGU?HBs9vJ=vyv zr%gGeioGFFPm%#bJ_ZgbkN-MrdslFBUrj<+i$A)XRSv4ctRPpz?IY;$+-%OxsKj3` z4anD+hZ>0TZbN+qyRq|w>0w+sQIUn+3>)qccx?;f`u%=iU?o#^CSH`0rW48TKr=;z z7RHy8Bc53K(H$xRz7uaUx~1?)k7M~T*eY#-SMquI2)Dw8$yR!p z^Te#h+&1@yAKGn8PI&?$&18Jpm z_-=cPYJ7ro3~Kq7A@cBXhtqReg#m zQU+%A$TdMckj`&!V%#g3vBLhb977}lkaz8bJ`}8&Y!83#&=4$(bK3JHvNG0mQoucS zNG=46$ee2Qv|@6$->I6%$A6DwHOP6z10=%ii@ffVMs6glKYXU0+L5cmJbl&$MRkYn z%S869!*Xsd)!mqOQ}E~MxfRK3=INiD?%6h0Eub3hQmEf$}-98 z(hS@sua_NP?DpA0OfiDmY%1=W2HP^PH6mM6IWaM=65L$^7#j>Rj(o;($}X=p`JTYoH;nPGM+Q;xe_nf)AnQRV#At;c~&hrqF6c8`#A?z zt=I8PZ#WX9D1|CH^aH*gihqrB#APWv1>~+5h=nQhr_X~8>)VeV?-+!^h@3rR1gY^f z^-_}2FdpRS@)%SRJCvl`BKOERSXa^&2*qTQOQ`-wPlo;gc$RSrCbuZLF>K@zl?=l% z_7`Zj%|%@gLV9L(Plh|G^LDd*9PI={UC+c;7At}*t}yUR=n#DxwN~zo%6HMS=ggtH zVV?0e8wI?+C1@Y+IajnQ42}&~e%vUo z8*rG^ls=iyJS5Q?qxl>GHuEg?i$LCc%rNdA1wlOJz)F{y2&1bmWC5M7@A%Wk@yERO zHfaqnV6Zvoh*P3Vb9Nw1A5Czvi9@gqz=gH!v z+h@W^gzU+|VFh{0Ry^ei9Lx%WLKZCUL?W~}7kHCO7s4Rv?n~JFKGAi_R~Iw&V8W0i z1X45=qu+;vPXuAj{d1YewJpxA+G8>Xw=+{?%wd%uCQukE z?frrK+=(}WYpSWJ2=5HbNPRJP>(JP1EvRR0mKrN;C~G24SC7lp908r z!6vk5#1;)NA{F}x-oZ+kO+h$W*7h1DV0F=dJ?bKa=eTkTHQeC9wK@d@=|K zrFvA~CQvM?mpHY@sBmhITZ)j%6Ws*qmsOF=IYSBr<>EtH;Koo+@29)SI_e1Wf~q8# zKEw5RF~`C7wD5a7Q@&+X=u_hImBdXaYNT6q`EbZ#&Xx^Zf&??7A9`nAh7!QV3XwDq zYj$2!e9Q$fGQ;79nN_#%W2l3xiSd>O49)zF7O8}I{p3uUl%yDR>m2!}=S9ELStmVe zj}gH4!<-)dqS26dnGMWg$=8tTl#Lo$)Ede^M_W_K(;Lu}>5%b)_XS33mt`Wr2yMht zli3MLK9nH`;~z>o>dfI^gA{^svcklZQ8keEP)*c0-x}HqLtrT{NdHo2ihkMPd^}_CwX$#sS%^!9HF=2!ITKpZ*VxsZ-$dts_vGC zWN0$?_iNb;&?2u;1C`~Vxa7y(yW?cHKR-PYwEB*Ro2Txm+09{8tO~zQAv<#z3p)Ey z+xFGqXpyLJX*Ydo>b}op!b=azn{}oIyx3;TzjU-$;JxnK*khPT>|6gH*O0hY*F@tV z_h9m9mky8nk-xM#63ezrX1wIw=!?0a7<3^kk>mQ4XnZu&EE1q)n$^!O(lj-^JGZ0z z!35N+O|nKFrfZK8{V899XB4=67uFLE%wmsW%_hEQZ+ObLd6wU+xhe1;Y7X^N;GmO~ zLQr9^4hzum_%eZKSxl>3CxZjKD`%719MhChGSP}>1h6d1YFZpQB4oK|W$x_!xad~T zJtt_bjzRA$@2PB6^Rvzv_VZ&}MdN%pg{Fr-%vv*wpG6Ly$E-AU1FPxA{^8^*5>FdA zEuUy(W6KUoRsXx&?1OX3d!AM_eqeaO?ss4ZsiMu#OL*`3TD+H>$G>g_h{}7jIHu|O z`(j=6SWnG>ck6s>;Ms(7su;me)9g3jhxNu@<96O{G9^Lxrr;9qTnWT*q$@e58$uh6 zAPgU1pD#bmu`?(V>wWthr#8E`WO)P~imOPS*K)E$brvN#?VZF5igXGjhT##YeLFpv z;e<7HVy+0Vh|4ORM^Kf#z>(llF18#-Ly27Zxz5}CK16W~>9k1!`fUr-4V#dJ+fo{M zA7}B<=7xgxFR~|VV-Z7$#!8NRawBu5M6=X{9-5xXs<`w6eB?b$sD+J@p8@^atvpJD z0^4!tNl75EU^|Kr0%As)VkF#8)zjp!t?CL&IN{ORIj+GKCa;I+@D|k@hHAez?yjwxOXGCXVOUsY$3QAJoKE~5Kw4!yAp<7U^kmO@ahP8X7=Y0-3 zA}>d)^I4v4MqBJkP^x12S(bo!vn#r>_j4D4NEHr9wmzXl$s^@(T4IJ=6eoV90^HaX^=d7T-(E)Bv^6=7~^;QcErXgFB@=lq9iCWTgYQT|Fp z5R`Q8K^>8Z(3Gm~XJn!a`vC3)h&fjdVR)?l9UEayRhRn&EKFcXn*cwERc6egJ=8T5 zZV{q7IeRS)x~AV$oh$pDJ(mc=Lqkj)z~#de;FP?!Fbso65Z?Fx(Uc(F0p_3WEQNX} z(O*qlRK9!ym0q64mc=ZdFc?h)v_c#>F~eVh8wDq%#2-?;By7WEJ3BInxJc5t+S=FT z!L>B?U=nINX<3z$WS`oGUosr7e^I+C*!r>Lj}B`?P+H}r3)-oHPsm*=Tr{Dw_KLlY zTvp>XVi0Xa^4yB5%t>v-v_~$Ly)}+Ei4r%3eh&F(Sm0=s!Zzx~OQ%m{t@~#|Q(yhq zROrZecve0?DxJVpb;4ayG_3IjBVi+4E(6g&%p_mC=UR9%)$kj6V_E`4UN2*@g~<}_ z+0jJ$pn5ggRSy!J@ydhH9z$^1X$Xx{kuK_QBWY&BP!G5R$uC(Q6=5UG>Hsc=Cl(yQ zcNxKo_&h0v0}jB!l)j#t;(#T92mBEhzBQQ|&7AS)i+WaqC&=RnL^Cn<)OUlf&-~~d zGtXmQW`H?>Bd9f*#p5n>Ux_S1v>(324=<-a!S&;n_9W9_0Y_N%EgV&OS4H}uUcv2m z(>$3t$=CdJxe$0Tj3tF0n_hy4mGrGOx*&Pn{Mz6=EiFulJ;7O0gTWWs?RU{uazl6X zKUpJ+$LO<$ldB>yr1X8-1YMbQicn;enjH2ciEKP4?^6?AM- zTWDvceVwU-E;vdxwy0D^P<`IO%Cd5b>AN&Ps!}#p{vrEUlW^t_DdLD@EYL>{qBXVo z^6E*6m+P{U$O4L1Rfr=9AHn*#Eo17-$PAx>j^7LWSjr+f;>sCMOJbD}zqTTqQ%)=* zGz`b4;$=a8cx8b+7XAweS%69CX+SqI*21=WKrpeiYYMcCpH#;qz&Bi|JHEAYHrPF4 zfEi;l#nK5T$t`K8b360#menu==V8HPQ0N)t=6ofnK%ciJOyj8GCJ3F2B|5H3EY9g} z%;5E4rV+;og!f0lhAIr<`+&4K@V=@$j(YPzw4$smb~Gi15^%d}B!a?fp?6Xm6j)4i zDGbS&^f?mr7RO1P;@Ec#c057UM{QP%@OcNY2cJt*iai0u^QPYpr|>$aKBHt&c(*ArTr17h!)9 zP0uHyVZT&^bjPbn)ApXDF{>Hll8GKp1ud`nr8LnktBFHLzNn*wvxgUzd^O>2or{Lb zGndOKJ-(;t-I$%RY&^2iV9Q|Bm}lOm25Uk^&jY-Qf0)_DvIY3e7aXPwYdCM0kmrp` zVs9>jdOuDE5d&4+b`Kn1bLqEO6H@C8Krx{FAD&&cj)ZBM0oryw#&30mayKJAW|+|jtPGVuZM|ievh(lnXbDfoKHAav2}iW$ zW>e4=Q(h;VLe`;Rc562pb0!=apS1B<^4@U_;)oI1`TS;!We#2fT``6ITbWctV^jB2 zx_stPJQ6v-{WCI8OELbPcLu4ss zI;7`mrje39B5W!o1945&ht?0$GiB85h`TC}Mi0v_onrHOs@)O=Mj4IH(LoGUwFI-o z(=AMt{yGhBlp0D4v;v~9JxSxV%47qX+4bh9<9%kSfYzPeRPVb}UJ${Z-MCkOeb79) zj8}q;dx6idKPHwPxsH(P?OPP|x;> zCjRKwg@>#>)MO)bU&c0!j!=S$Hf_fCPV3e~qh{euGnu!f+}w(DzrDeJae5&y3U4W1 z9*eb)0p0B`Ln|npx zmIyN%^>{%Gn#^p6hLZkjk)*^K9Xfqb;6u3d;1o|9Q@%dh?;)_NvPJlrW|6JWgez!i zc_n5J&ree>!sZ)%)B59}tHaw6;S@E!PQZ90$-F1pE&HxX&~kA7Va`*mkdHUO zgHuPXgu~}UFfJ#hg@Ob;O$hY*yOJoA!q0Cgw$rR6Tx3x~8T(SJ@mleteP={rMbU%r zIL#b_)9zo1Np7lwR#REqKj!!)o!*kDKNMGr#<|6_3`-}H6xL5%5vM+&+lZnN?KBr( zQgsDZ$t_*&Z&n!nOwkB*j|+i zXDPE=LjvO>w4t~cfSNDaYu^Pc@@+@so)Q}p7tT2H6Dgb`6z=lEo%l9jNgFX+Y3@|$ zWN)Me>77%Mv+BJLEy}_ZSdSTVTY76woR?${uz54;oGz+((9Zx$hJmzeLa&g*P&9<+ z+30{PBsKjKN-j%NoT*L8q}=!l;w=aQzZf#$6*+YNX-}4t*em#uFQ%5%bFP0%%#1%O`5tNa>(91taWXqwG zqd*zX6{KWWSh^KS4X&tCc1Xz(5n`ev*`OLF9!l>*(`;lLihi}f1(>!i4#lEYj8$3b zxJ%#&^}b3CKyv*x`WVKCkfM5nE-2bw#;Ut)lt-;)Y)f}9LX7f!`8n87;z$z61 z?I;|TkvAIPCAm_W(g6}b3!nIF^3i^LYALcEDnLL)DGCiyYoB$zNnno&RRs#h2iztT zDp@#Nx-&e(!~Mj>;cwU&f#GFGy2wnf%}l8HjgiB_NB8ddB6EICrZ|U*Q$;3Ei57 zoZA$XK#QO#IpObZ|4e(q(ZYHt0_{0BCh!sB9!dw-_Tf<_OoKqUFst+9nPCnIn{_F! zlkg!e`{Ud}?|$#GC=&zk2zFJorsO*Cj44z@`a^A+V2G58OFR(N5g_IOW!5BI)(p$o z5;zJ?701v#2`qY%Q1++@iUoPtgSX)nK{#yU3tzDl?8R%IXov_G>n=bTjuj_ z>YU$W4YIRnygdh`Udgi_mfJ77^u3nWaZW;}pD>wG6S8agy%50jZNK*cBmAWJUr{DR z9OM%Df>sp5oTM-d)6+Vq19C#WDr*vtRg^gZhR%F!qE?l(zJv)xggkmmr1sYW267+q6KSEAzEPIJ`@|sRVq0cBmqnQL_%R8V8S73YXa0AmdUGZG!?%nUp;|ub z5v!w@X`RHdL~cO>t#YnG_@T^qE_?2>XT{bl;Su<>^-fEM6*8{BqO9#6u3KGR&x?Hk z)FAw!ho1@tb}}*y-+!RcKN>Jo6rA2NpnatD;ImFfd=@;p-pOiw+N{q|$R6vBU)HEFsq`gXo2F_4IqXX8#YGl{4OnzFpDM@e~ zDGYsCN`GI{T%w)jr87h&-;KloK_7)ymc#3muhC`CC<)NbG;nCFOg+7*LK|G_1Zpt) zB2fn*qc7AmroB~9;&7Od3lh*nvQ`KoA`uMxMez zUSF~=ySLsP%+XKFr*z=kMdUL>CME7f8;M0FH|80ep&%C-c4Ao)EvWz{wj_c*8xp!AI_ndiGNde1q#9uBqWX1c#fPPx z_Myj|{zG!*z6NuDaJ1No8C;qq{}c=^^0Lzywpl%dC8oBRXe+|&t9>9WqoK+DoZ2jgJ`MBqxMDS)5#q%p-;3Irv(v1!_QO!5LNhww$oUK&xPb z?K5_iGAHjSNW7!*6)RiP>CDc%Si`b)uNkkIo*b;zWkgv+R z;N`>`-NaC&L-hrOgQ}P)O}vyHrT=HMWVUEy(+R4%7vzL1chF+iSEE`EmFD|Lkixcq zKwcE4Cc9=&24%HEk6c`@?9JvhyOtI8OK96t@$XNsaJ*`WhPYx8Q2CLD4B31)gwX@& z*``v!+!;rm9vb}m@y$35<+R*P+Tx}Xa{07L2$d+4{pdBxGT-g7Cc7#pvmH?WQ@5ON z6(2bZg94e&d#t)2>T;jZHREQS!9-VIZ7gRE6b2~L-@&9Jw=G>|_N+~?LH=e|WNOOy z8=WWv^?7eh*6__N3VI;{Xht=e=*H*Ei{j|2wMJzE6Q6^Dg9;oSbSJzdo zpxuwlCEh2In=SXMhFPmpI%8N%8{EID2($63M;`4=56CG8zl4~Vq)h;;#uG_=@Lm&~ zxgi$x^sH~A=s9YZgF{n`RY2vx8=nuC^yR zk-}j@^_@S5s4$raU)30L^Juv&oiHI|E0F1CKSdP`@BMo86Bh$4bia`^;tKKI@cKT=D~F3s_0hA=y?=nwWKu(P$txi7b{9yZiubrTD$~rZp&(jCs8+0^ees z!g22(`aDj&I?D&J?L(J;0IM$A4hcF&>zlWt@G8P>shdg@ABUDx*GrmR73fItk1ot* zbGV7eUBw3}qFw^Gy#B~V6GmnyeR0z@!nBth2v?CCaG6aJczhV+BvDp<|4Bv+Omyx! z&%xH5;^?W**l5{m@+tJ5@ z-Ai?#1Yfj@YbYc5>vH;IH$4}9RlWKFcTX!{XZK2yxoH z7%cQA5(2!p33LtKR=6MQaz4qa+MZ#dLIpfD77xR>&RI<{MIeIOs!7xAib`g}aoz1@F>{6E8 zIXNBNe08NdjSBO4pM&-!M{4`ko2_~`ZGAwUjggDcjNr!w;-=2Sc#X&hYjZqB_W*!N znV{z6MGq~&#z=It!j?LZL+E}f(nQ1jH&t77PY@A7(B)vrJ)6ll@$7N{O=;b?-+Bk_ zp@{~}k@%r4wRzml%#^DK6BQ%I)0^R5eN zb7_Nn9gBJ&c#0`P-{EK3=Hu%4Ra1PO%WxDK;LpZ>&azYsv4=-X)REj*ST%`f5$YE`}4;(Az8HDHoWg?sgge;dDmg? z*HY=Jr9I_|M;vVSie3G=)>M>+G)tZ}nEu%L51q_ah}p6x6SC=lm&R1fl;8uIVh%u> zc$TV@c`(2fDimQ*Z6!rS&ElWGQN<$ZKCT$?vi3)4FRoB!?dEZW=ze7)I&24`eEh5- zd1~YHNob&8FZxCD&@P7m+J(2#55l07UW0zs#JG&h89<%KvlKQr#zshEQCf$JUr%|^ zg!~|EKc21KMGS|e^2OalS6Jy1 z5sg7{8m$<1VsgOmy#FQed+2z^Z!zi-$)6<;h3?r_r~pRz5&kaVZIYp8Ni6Gt?Qz3m zHJGe(nCbq4PW<G!Z5BK5sQE<1_({l57OeP+3O7g=4oV6MU1PQyW4)l&H zn{fbjT~pP?sG&Kn-w!`h?f@Olq}4N}nyBG>tPjhCp&@+uv9NjkT%(>)O8;&o=}(h~ zcsm`1s%HjoHqCd)xx(y%3%p`q9M+!hd_``Y(~W#Lt57Rs1@>;x6-~CvE3|AeMeVu%uN&`PXfM}2#T(tg3|`icp+=IMAmLxF4_EL9JeX8S_D zevu=f?!d}TS}30?n5>=vv9)osycho2%=7s~`QoKi&q65ech><2kjX_~kD=;!ex_8Q&SHJ ztiVCTl94laI9dH;S7^B7R8RxgzJQ~haO zDYFm{4IPBiL3_lz_;>Ugx{TA7lr%bVbxk5`8uNk9%o*lozAibE(;=b8S?4MirBZ{x z(gaMFjjJ#(Bl^mHK&BV*r6VTnqBTpZ4-o;!&D@jXHV>x31Aox*7IF09 z_dCf{d9lgc6oR&?Y)dFrf|?8TgW&5JAfC;WJxPkl`4XR&KJA7FVc&Tu-e;A=MLDh1 zz4Ns|8X8HPpQ5){cuS(X@o~GHxB^mnCBV|%DbaMptPk(|jawHmGNOzlTA5~;7@0=R z)0w#!pG+`*QT5ri9HvCpXbNJl(yFAIi)TdvMa|eqOYz#ps~&pwMW`Z(^ol-FXo}7d zHIx?;Um!hiAwOMJ?ujb7tuS5h_-{#(DNCuE1bQu|ah_OGTJ=hQw^Z$YIwZv|7U2JI zg!GLI?U@fz~ee4jvtLuNMDuE@aTG=9XyJ7iTM0_L!Qd#N<)zaL(Q^g0ZM0 zEZc3?h|l>A8<1J3fzD2#FxfVM9YJO*Hfp&)I5Q51ZNL%6IEcjCoaqQlm!@eAVzDOl z=OpN<%Y=Q0^0hm4rCV|EH+NLT+#hP;h-USz`*CRo^dHI(Z10)fHC&w!d9Xxqrio+h zHum0pDe6xjx4*Imtn8g%n%*LG75<_aSlPs(-oFqAAnwW2wF!8h`qi2qMd$6IGgElP zaPQEw3Q$XQ*dH`D)J8knNaSgb({*z?iiEt_AzZ0Tw;c8E$5kGc>SO21Jj@QQApQh%xp4SXURh z{P|s_Vp1*kH$jfrVaYrES2b02I9QZgcM~ZiTT$W>#U>$`L3=nzC^|Y!2XG%Tn!{>Jn&IXcMW8HPTcGbGN%BBRajyq z!%dBijO*lnOLQfbmLj&@=Y8PRyJ5~Ad`a(K41>T`;i~C)Ou{}fPGNIxq2E`}rlkta z%Itz(r;MJ%d4U>fa5`E7ix(l(A5n9c=FaE_qOn*IMOrF(Q%4%ddOrAxnf`P%xaRkd1ei?>Ro0Uc2Jq0b>Ux zr-r!*1~7(brJ6Gd{G@KKskgJi1J;DADw@9DWh{cc3XbW_1k>;mBLtbwBWTfQ(n99| zs{Hwdu91fUYf>Vu(1nH{E^9`Ph_o}#*oI3VW1^3p^I` z3Di|@XFqA*Oa21?{Ua&L@0D!lWVo_Hg8GHxgLcN3Vx>Vl`ky}Avc!w-91~Sw_rNFi z$FN$LYo&JI@%d@^8(02PwMDWC&fiOxbC!l<1Wwo%P>kjkG9=BJiiSMoB%^(eU1;wy z)_Y^gG-EuVRH9^Ic(z(L`jja5H%_Kx$+TnFFpHj$XX)H9L3!CL=6(ju2q$;OZf?@> zB%ZQ3R%Cw+4s4bDS;E}m$P*tLU^UV zab9GZvl{p#JeCuwp!js%SGI^0uV^oWfSK`C=492I1v@xPq3WThnE3)jWD8dbl~ucv z5K^RPp4t4fR2++`+pxq=!&N@KE86%pWR)GWk3H%}lKfB!(iD~Bc73+PD2z|IsjyWp z{_<_JX1fG&l%&zX&YdMYXU842C{d!DulUvtGTqolx3xXwa-7y`83_+46{1cnBNBkk zmG*Y-e%=wBAf2^anafB77FC-S+~k@FLKH{n@?-IG#JxcM^DlO4QKnTVuf&}! zb}9Pt)kkv$i$cRvw?b%x7_Yx+GyK_IN;+vBM=Inn4uS!KCd|YF=*WVV1)9vclxBMS z798F_La57$QpBgcHtUfnOMl59!V82;e*2|#&i9$yA6R4o!|RyD3wmppktZru?a5v_ zh&o`ZHjI@p^rjwR$h$S)w&H!luDuGl&rT#Ph#^_(^>QF^;3Wn zFZ?w$(3pgrT6yg|xsvkv4IKsq1;W&S@JCE*>aVFH-9tM8L z>d!7$BQ}T3fs@xo$(G4aFW=M#-Jg$7r8R0vEgjoI>%*LD8^-y7i5j6U*EWtSO=vEj zG};&UjdHWCSo?wr0T{p!ASf6~uBM^F#PDDC%{vI( zB}4X&No7*v7sxAOHBLE0RqRWl;FQMQ3v&eVNW!pB@$0|VSaHf-GSQ2`*-QJFVejL} zy0}e=#Dj&II2^b!nvs}a(?S^Q0&N9|SLubVuiD=yb+AGn76uU4tB*XDNk|8<31?a6 z*fo5o+~i>1?W~vf&GHK9wxFZu`y1^y+hw+{K z%AT%(g3>Z$cK^~lkua5~MA$OC~B#kXp#lVp;3}_N0El*yKEmmGoMGHjQGf!rwROOcDyUh9>+w`NO zd(a8)kF!0cr=4}*AJ~GD0Y2wF%R2i6!W_del00~B517iQDY@SWZJ4)4Yg5nHTl>lL z^R%+jTChn%`jcD?4fOI+|2Yh=*c{O?yYU7RFTUpZo-RpXC`56_No^vC*$z{u!xyr} zU>>t9b9@-6d@1*EVim|XY$b^|@>kx@4%CcNMzptYU^k)7u+QRHlcUGfjjI1TQ1~$^ z(|)Lcm^Euoqf3qgaHmJgm6M{z zcNUjgC#_nXLbyyCJ1QT;m_d8l`9%H26K z32K`NYBAdaV|Wi0^_21rb1D+D0o8_A7TFNfB})~=0yk6Y+$W;_Nl8=+KMZ8i_m*?$nPE}Ka*kYXJ z!^Tt|Q^=Y^`<-!E=&;|{u7&)?14MDa#G$H3pMGD(#Vnmf{P-TbcXXzQab$7*5eO2B z34TKOpwgmP7u|ZPmL=GZ)EXtbFoWPO-ny1ZBBND_j<<WUGWKHy*9&ls}(3 z?XeF=dGuEEI_dbDqcyfH%h`$`A+$`OcOHMf(+VrZ#AsxX`t}PE;qN79p!s0R#!;)8 zPW!)#caSzyDyBJUpu{fmI)?ql6?s}>Y9Xx9$@N6YAsUf7K5|^Lvi``5)FiRx$={&j z5E+ZFGxosLWBR`N%giPO_w2{@fHF6WY91dEXhJ!y;FEohK#cLrsb5*MO zdFU!t@J1#bB*OaUoYD>y0A%XqwNWBF_w{4s!8P5tMt!p26D0Y8TzPiBq7*(CO%0!- zmaU9`k)}olMPU2-q*xwA_5*M6k?FJlnD?NrDYf#%fcmiiRz` zJ9`=#)hj95_%R!pOxd-ks=rtV1>Jc3fFTlEDzImuQumQ7%E~RoS1-85(h@1~aC&Kg z!gb1pLXNBG+KZi-jyWRxiNbfHb7>hk2)}b;&gkiRfGWFd44hS~z#P9X&`Yk>lEc-% zs8cwKo+)e6Bo9JBVt=o4KU9vCMP=EV#$GkDM1RMxIfi(QoBGiuJS z$w_?bl(U(_r9#+Pr~(=Lkd=2#XK`mF@rW~~><__uZ^wH~ymHvc_~)zGnc9U+ig1i2 zx((F15}T+tnee=FjK-c_NP$+oU9)hIo#+m?4Qv_i!XiJAfjRedrCQ+-IY@NCF3$YB z5S_X=+?D~Crr2KKU>!>IE6PIw{oo;kN=C{^W@lD>Mu4g=R^rQ^5Y?1<^5CssZhNY8 z>K=ny>pUfD>kejBg2BM6FvSLrFiB&K=mo2zP?WTNBETsq-MF$=72o3C|$3(u;w9R@&yJH%Ceamp4)S)iO^r`EFmDb$xz^_j z)M`WcyI@>=8U+h{Z|yLh=^Sy#(BDm1Qr7tEAIdR3&rhhN_!$c3hcv=z_JwxY#K|z( zY{aWHi59$xqY@mA$iO6Wj)?F~l3b!885tb!Bc&&_?Cv!schLmjy_t}gkbUM*AqC~v z5W;Ye&}PgsGl@^=j-K-!3?Brk^;tYUo{H(zu%@Xst+jq}JAcw*)TjB|o`Q|)@GZo? zcR^8+H7QV$cCh>$TNztd7vF*d_ePsuKMiw%5A==<-R}1I4!9y1_w`uv@98qX>(OlU z0yRiE9^IDJz$@ijxGuA{=7=x-ICtF6${R!KXfv_HQsfXf2ia1V^7x`L9SMcZ5h)(N zG)bZ_DgrK*oS3z zb~ka)8NbCAorkiV!(S$Y0X5T!Yh6H!zqH3pgNF1je=+qI73CM&(lFGqnKZ6rjQr0b z{sUUYaQKksXGpPU10vszhiDn+pl%7emS)1j(XhGFU2k}J)@u=skVE;{_kzZ@n(g?jJorq(z;~nd4g;_!WN(kJ zI&`w`c=1xMNC<>diNL)i=l3Q5gy1g3~6aw5SY8Y)B7}MmeSwo(CCD5&@YUQ;bZr~8ViHx8AZmf2|eRD_Xn`O`B7Dd zk!}Yv+=lzOl!lPHZNLxUO8EP|TWJAFbc~TkzlSk`+YUc5(BnBu7Tp~54cqBUF@{d= zO}9!?LE~ZkI!naQNvM)dpE*g2JIiX}V2IXh9`-7AEPshcW_# z%&jUfbi*zm=)!3St6~>UJYm+S$UYry#%1RkFOZ>Bw?El-%pd_KMRDRBj~HqOc!8eO z0ggpjttOirwOkTM2D^Ztv9tv^6AoLAEuQ#L&JjW%U6Xq7xl4fi*mC1HVnllHM|`cU zX7MuchdQyKvjs?WVwd0c#lrPr$v3QWm4qoTqzzWQl$zGgmekO&wC_K#g=^5m_kp2Z zgR9vRTk$Y%y;ku_5{Vd=lkbjCscqm-JO8jFl@9C+1B%3H=b7i@r&=y7IsJrg zRkx+jQ5;r<%mukNYgrQ~@$8Yy)mQ2rYUB5M`?fQ?FL_ru=;^1*wk-8SYPYmh4)OB9 zI?ZwA2odZhSUx_AnsEO}6b*8Tp50<+F&)UK%5TRjel`yitFk(L@#4yp@aTp0E2S27 zD8lItW`6~ZxP09oD~*pQTvm_LEYa#FmX5)ZdfZ=s3z8c>GK~g7M8^T>0Ky<-HCUMN zk104XD$MD@AOB3Kol=ztEE-$x=1GXmKye7kajoKjF2e-@#|dz!GP?OZtu2NZl9L zCP5~A6|h8+R=x)n-LlF|T9N+iwQ6pjB}8*sFTQoq=q++)Oj1G~rYB2dGlb)LfKVi~ zK>gQf#l8J6$@d$@)&g9__+B6(A2vb&wf#$}=B0db8F>p#tGMV)G4sp{jl?r_hQGp} zM0J@{iS(TrgMT9-(9<3Csp2UZ@zNnRh9Cb{AtbPL@9@{mBZ2G7d}l*1aX-g&{7(cB ztbhflW$|}CuzbtG2Xp%_;0m9BYJ3hCHdJ)vWRQ9*mr1~dwknFffL9}7l{GPpmu&3( zbZj86L0!H{^I2d0!$cRtLFWuZ`(0WhuOYm+`vp;c|Eu8ia{));j^L@MUxhLYYw}!Q z;r3!Vey5s=`{#$^-^-}(>gwNCKJEDS!X&sl9*|LcUcOKw)H0^K26AZWoi@;JtE^{g zNvjwyj%GWpA3<2E%lKagNnwtlgdBlyuQ^rT$fG~4n>%76)Xp8WsMzqk2+^QUWpxsZ zMjFcBR1Y)~D#zGl2(QuN9t_EcK0GU-^ejJkbbU_d9`1Z^?>?vgq2ca1*&w5glI5(w z>rAsv@dvZ^UY`rKF%DyjTa^E}FtI=FHwp1*b9s@Atd1PFP3-(nxfoyhakD3-84A!oyOw%w0{(R(i6=38xCENh$N)5*w8NA7%?8b{))qc# zR)U+d>S^?c8(Wq#f%KZyiAuDFOEwv70c<#*?*$sZK$8c>2;Q-KM-j|mDWZgc3myDk zYziW#@(bZ3b}!3??}=D9K(jr8+Rym{<%>0wLT8)m#da|$_Kj=3BE>>vTB zKl!^f;TuK8CkA|6IzMW>$nfam_=5V++Yp+95R-@9m+V>2>T}D+kVX1fbfNF#0_eBU zLAaSjV0RV2hzVv}&7mSiJY{1e5AFlqK>Axo<#^Rw)yVdG~k zLGA)@cwrJ#MrBH+1f0Zc`z&;(_en4LwG=a`G>y`l-)QF^WtX%GOM0h3i4eyf3e!$$eg>G2ya8BizZbGP%x_V)4fenuDYgunA zt}}B;<6gz0C0+k4hjaPuPV$JSu_>PW7^T0;SprQ8HJqa#Mpky zzyfpw8JJt)4_t9xd^^0!t4RquH&twPX@CXu@$bJjVM`&_gH^_~)6p1{XM1_Vg-V4t z`Lc#(sK)Y1coDnLK-#7=&HkirX6zJW?aZNenj+>*j(YInr2HEQ~hgaX;sCVA1oFtFFKWmI4!Q~C`3qvsPT zAPYNaDQwS`s0+{POT49molpUyi%h?Dp{0h~n+T7jGOjlPoawKhB3&=*A&HXv`(zkW zbABEial|rYC3R9Y3Hf0c8-yr9d3w?;Np-*IhoEk*weTe-r$kbQX5ew_2Mh!U%z2Jr zHDH#Ra8ob06xZh!eqlyi20|a`QwoyaJL$;Mzy9Mm z+YwZ98GfiIjZq1dA7H0eXrz@oYf!02SRxqX+>jxR=&;|Rn4xX_hf1ad7w-2SO`l9U z`<+PRU-dXb6@z=H!N;zXiTnWJ2pwlJEg7Ig5;nz7A%h#;PPex`dNm(uvg6u4OF$Ni zZTiJ;3~J_&gr^uVg}E#WlOzBI+#mPNqVjNInV*bpq+|55R6*{33$|lc{Qp`vh=Xw& z?tzH|klpszf`S)qusrAG7R&EQjyRHIxb>y?CiL^H4J@+!43Wud`&zpn;!O<~a67Xn zw+*@2lE>qG6Vpb`?Lu{=+<+?;Zf4kj(1#7v?ys3r`P(UuM-;E`-o*_ zNa@?i|1At;VzzQIzl1Q;f#n#|!$@{aSV z7Pom95NfY9JC5GO@KyLIt5@w;37gGfY1u1<#}JQPU4VWP0FG{zT9U*Fv{SN{ead$B z2z(O^(aA`A{9IPaRHSmwoq&g6h&Ll|-;fz?oRgYaKccaluT|hQ;-g2WhXqn`OTbC zMq?)!^D;K0+e2~DFLymxkMzj9!bp97kqaiT)w&l4AAv^X{fo3rJK3;g3Un@`qQEeK zTqIQ_-zQfwfMP)xeu16RKp%H70P!<$4axrL?3ODiAC%Vs@`~nn@91kS4Z5OlYf;d< zXwRh+2)iI8n*TYBWlvrC2y=Jq`@Xk}sVNZgnz)L_ogm=fwwq_nLpO2Nx-b*#SSNV} z_n59t25~O<^_3M~oYMBjg*XUmm5C`Bf9I_+K4`k^A&@y%@*PI?=_If@+Aa5%k_WMb z!lKp^Y=bYFbi)GNKDy3{nT8vIs2fR+MYyWuZ4@R=VwvnKx&ckn$hSo{ z+Y+Jn95ENsa(kPO?~*Y zWedgl<|8!XCumzOWTmk?u$Um8Rvlyk*fXIgNLqtUK{>YoZqGnWvQEq26mV8fUCM+; z7(@bi6z^|!ZAUSkJxSFHjouu;`2{TL0lRQJsUr`+wGhr z$W0L=70M!SuwWBG6B(j8#5f3j)C?EWnT+>=mv zI}GFE-R#QRlMvsFxQu5|^Z|An9x7VtZcNBhBu@0 zpya>Gf>yyZLdN2l2itt-?5H^HOy${eUVg zy^rE7Lq)vLANfBAl)gm!QtI%wM50wsr&Sx%(FIB<}HSw?c%WZD0vZRz=) zi39Oof6lJDhEI{%G9w@BzNPR$y<|@qJ&0a{rP*TA8?RmaQ9JZBk=Z}hoK+HNv>! z=<_h24zor!X8V|;Z8YzJ9c^>Q=Ubc=zIAlQxS`nzg5a;2!}Nm@>&>dD0wbC5rVMw* zWztf_Q6&+?L-@^=yytryuxdS7pzQ`f+HK4?!ANnt}SpfbPJh7055bP~y4Q400 zHHzcRM?>5{$|_>H$4gf&mnrIL@I{&-A2%FZ9-EzdrLTmEDrRrg&qdUw=^3vP9!WvQ z1!JV`E3&|h<-s!gMHOCpwAw``vt=!vo53>XRrV+b#5qSjxEUZp!#QcSZ6%q{kr`Kj6{pKxFCSSe&IWUg3f?sUrI z%~J^9VW!oSrSYsd>&Tgo%X)P9t~AA1!IM&BmKj)|vK+|hS2lCDuhoPt<*FjRqf(YF zFWy-~Au**?iWJb75k^){wG9m4Q90y~SS4C|@$0-M)(wQm97Pi8bmP<7`yko9{=xik z7zJ$D*CTHCUP6grg}C*K%6m%4flkX|kJJfO5PJPNRSF3n{vCP}`16AzC7ng<4RQG* zs5DetLBCoFSyZp0&hm_m++)lIvRqC5UK8m{m;Beb)CZ5K($Bk9;q4{jlhbY!djiXt zetVPUAo^){_)hKDIyz0VDehQaRA4gn#(=vvD0I9#YDor|jqP&hrohsNjx0y9$`KB^++ZZ@8x%LYL1*N# z6BjB;{3r`0Y9nrDS0{ptM9h#rj)+?&9U1-@XC@9MYO+I8>YL9cNZ2}2oU4%cE@vrQnOopt zRfu97l>bdk-wnFY1%iouZOfXzS`w|1PJx-x^(lMv)WbS5B5Glpw2@*o=F>2>4;~ts z^=a5Mb&Z$=oLoFB^RQ&|>=V<{q*}3RX?MD&2QLE*8FJYOaH6~hTNAFmF3Ye`=$V0m zLWoSodY$`CHcah?x_eykz4k*0=X%6KHI4T?|+V^hS0+VIIvU zc!<>fe+~tHN&t-86-co3>H4x+TC<~(%b0(b1YHU*V z8pY|Z2gFYRNT9g?)tbE3ve-{l3xn^}uXv}hc5m3iq%%~ICiUf1lg3CxSB&K~s-1lA z-F+_h*Quh>QY~z#u6{{v3}rrTk^5}+P%?4WRWf8(S@n!c`yRnKmSO}wKW=Ay&F`x@ zO1}+h?X_HYD#1mg=lF%BGgb`Mm}~4X zxk>lAYzjJDtsrWqTvCOZj3P%igEHNRHX~xH(jrxSh$r-&iltN#N5cHp4@ zwfo3(cZ^Q%W+sOQlci{Qf`w!^=4WIzzVx8+;w0`PgW@E>Nv|KcVH1DxNiIKG|mpB*-D zU%&sJ#`U&?@4prR0EYj|O`!k3d;A~R3ZSQFpoI$1LIddf`X9E!xY?TRguRxx7tD`N zN2r*GKbt?J!pl1nLC`C5%vLotL{^)Y(x6?`*?=cf+ClDaeH?;lU|Mt^2`R;YNC`2) zTfo4hH)1?;fGZ=F`?YOF$54nd*O_iNS*3hU-%8nfYv>Y_jBsl;tnnMoQSvYDHoi#y znFHyO)cIH54K;-Hk4pEH?YRy6iC@c(7nhwC;KI&YrqTCWe3(pLvu}0a>yN*bep0J5 zChdB29OJyEj;;H>PoYtE$V<^yIn)W5`)$%cW08Re$mh^?;*&0WU@yH0ICgvx`@mMX z_C&gk_%b0;B$070x{1=MjFCIHpQ$m|Dk%cw;-UiZt41R7@am24*cRZMZK`ty6ZhsJ zO7F$<+uI4WqAtS6+XuCphoUGKN(>~$N{n$FVVDJre}}xnKSpRy8DrUy#3TEeRh^k< zHE2TON@g~oKROGu8VU_C3x=k$p4Q_^YVLO4ye7B0Lcf}BiHnj&6~oVwGdy?uw|;D;!*%tqynqU#hbHk$)5j3XOj zywsOnPNc3A>S22Ak+%k~4(;n;ek9oJ!}J7%`0u2v@gZbzJcO5nc}Ub$DwdSlHAu$dp1f^rXSq##12^xV!g< z6{w_etOlo3tqzkoNnlx@#1*yg<^ux!T?VM-Gc_3N5W8~})Mu%s`i%o1v7NLdd+?gG zV;HTCFV9f3bARL7r*IM1GQ^kx^l#+9=T-Wru5z|Z`hNo(L_&6g!&s55fHeX)MLog| zCb+3s8~;M(dQdh;dP&t6;b$Vun$TJOEv(H@+3Kvl%By$Bt|*v_hd|YHUSW2%Lxdh$ zS6hnOdjcrHa7Pj@VxAh>$--p^+Dz;6_s}Jty2W4oEt*+Mc-_|B>Lab(L*W*iYH75{ z(O_(CvT#;0+lAtiTBeXWeLUdr^0{_H*m6kb4){eV8Y^$s;@ zfnAotc=uQr{~Ate$|rg0@D{{rBwr|(T=GCmco9Ah4)Tn>NWTsPmsOp7wOD43?@G;J zZ=ZU{UC;tXNabNb3|7T&{5!{hFsNe6Zrd*6zl=uWBVpuy7M)e1=p`~p(_U{tgg6JLAJl%@#0*wMHKtj)NURtwVzD%zBdT=#1T8doo_<{Sv*s-CRIt#N%{-V?TXwxeqhvpmc?WgxHM5L2K6S_1YvMPH-SA2y zG;hP_KeHn+@7@ZkRa}r=?P(fr)oTnHH=LTKmSL`^iDwD0J50;mqg+->$Iq>M#K}%S z1`eTq;;@3l_V>YJ7MDUYOT82id5dC=RRkDVAf|YdHP#C7$V3E6KKiYE<<{=v>Ml2W zs3FsL5LoUjgD17)pcGLXfQMK#gZ8I^bN3)=|I&%ikXRZliNYK?^O0R`CS9R#$H)XU z`=nH6G_X%P`xNB;-jtcy+t~c22&onmLRXHxk3<<-W!rVi3zvGxTf{>e0_&oTk6srhb$*a7{?f)sVg*1H15rPM0t; zrNP&otpsBfR8fRBJzvV1_mZ9>XLRw^pJn_XBkM)HQFM>3Y&~*ujpuXh?MbZHB<{yg zIk@i;A7h1YiKm)kf-n2%R-pSCTS*U1H2QE1>&1cXQr?xllsA*cLs@6q!(m3N<57OO zCxLH}C&coNnLcTwMOh~%IxFgpozE+v=g2e~OZ-m{UXxS54ZXfsR;)JWhO1n;RvQc( zgv=X^Lg>`KrDgdtAm??~9Uh1#CX#4=xucZ9>!E^i|LmP^dwHZlC_>}CZoyBF@)(%M z++?(aE)}H~zYaAbajnXWb@`*EJ-H=SIMSD{g*PE{zLW)LsyFK0B(Vm`7JI)`E*N+T z^d*k10N_xr4H_1D;)ONhkQ2DB;x|gzVf;6o3Ln288*=;^tG00;qAX#HWZfSng8BBk zHM9m9EZUifxlV+)E1nqciV)_0DYTtu!_HViJraMvr`$AfVafrv(z ztNQ=uBL}I5W!j6rPiRADH{1#F|YuZiyWl10O{B~dDJ0?Yyxrje!w-b5vmEjVmJ8&1eKpGS^Hvb`mi_UElwme9_aw@{@O*Fk7p5y2q}c2h-qu^rL5+yBKI&f~^~}^ZwL- zxSNP(9Vc3KH~XPfs5g*s^h(jlSwvovj-fGmedgP1b;I$&5?t2EBc2nyVO$b^IgrBb ze=U_<;CcO3%$nq49$KNQi;MPUdWpJTTbe6Qf8^D5PF5Jyy?S$&g5b}PFk=S)M<$e7 z?nH}Sx$rJLO!qu4*&o~MAQ9%cTSw1~Z$pO~ctJ1w%vf1dhS!pG8updY6d~nL_)VDS zSNTk-DC&h-&*j0fp`V^$X)6aJnJZ*>7%W9reOHyz%ML6lYHuE+ZW)Vmi{H)BT~4aD zzqct_n`5Mi4<*+|nf^ZOmCPM1&IQIRe%QsL`nZTZbDXK#wp&3#&;Z(1K_Vyo_dx=9 zxI^iL4FeTQfc$Ue)cA7}KRJt+ZRbZqoK7T{cf$JI6jC=?rUG*koq?PnQ5dyEHHz)se%P}4nW52`V%?<}6j2tpQq!b^ShjsiKFtufL3K6e;Q zSljmuv!VBuyjKO8_^t&4A>TmpmkA??0(m1EK`y46IOmo>SzaUQ-3)W^)kSBi+n3PL ziu+COWuNtzZ!O$%^~<>1QLKhs?2}ppYcyI{%!29TpTnRuM+N7F$Kt^Vtbz1LAlRel z0?`~CDgpLL9zkTaDGXbW!RlBh7;ZuEm?Wpfru{x8S;UDsKHR;IrktAaHuH;!C4b`O zTq#F;hd>&=4lA`i11{wTSiSF`Pmp(}fvXflc1sO(41eO4ilR`pIf#5}cc3iQdr0tKFv%Mr z-@adAq)5YX)J|Mem6xp$|C(N5|A+nq47Rx%yrKDl528q-P`DmD;6E5g-$|w8RZ2#K z*8CFnvmrm}eUT18vwt(RDJ?u|?19x3(M2I(RB(;}?&na^7!e-Xt;m8RYNEQy8QwHM zgU#g_Txp@`jzu6!SFG(s+JUID{oH{2Kqs}@oJ}+RDXm7|>5qPh{ifuu;J&og=-B*? zJhXH0KL5%K#NU)7S`jaifj+8=)?|wE&|Sj zxbmdX1UI8cLn9P$@fc7qv`W=_=?d?Qcy%IQ5@*$O2Fh z*yOd55eSCZ$8b!ho<`y+iUq=jN2rNCWpk|uk;TRmND1dkPxJMy@h=s3OO)@{YgO=HOpQw-jRZ$>rYtWjkz_Dq;l z_1m2`4l?)gd#^ru@uvK_J3HS`sZNCzfs(6iHy3Ncwfk6yz(I_CvaW}O?1Y7KIU=2$ zy9vdhi?_(JIw4%L$S9(6fH8^~#0a7KtWqKqO$@G)qhGa5aLC2k_#v1HW3R6`wn;dt z0?->~cNyIyK;OX&vb;!5ot~QMQst0a93Yt)IuL?`P6pZ+`15oS%EXRWl0RgkJAtay zcLib_?nI@GixIAQ6zj@Dk{K3UtdtZ19R;rpw*ScJBg6`#XV?$gh4g)-y#+UB6LxY{ z#ve2@FaNmLNv^9f`IoE~lGIgU^Dr705+O*(mY}k(bc~`~ z7?SfoW#;^!fnw?;hVF($SiV->r_%0vq@V{Mg!ut#46d)l(!?Wqy&E&Tg4yv_1QaO^ zC%3p>i4$|bsg~>n_pl{H`vprKRSIBn9|>+9e2nR!&Uz% z!S6Ve0^wIvB6=#08Cm+Y|MJ$({LQ}QU>}K*VQW&vRV29_@$D4y05L_b>72afZAWRT zrZx)t5pG6u-uqs#{JfcJbBr(l6=M{|mBn}{FF=QD!)Mi?K74|DSg~C3%sdsDU(5a_ z*TY7{AYvscY7By)xrlvOLhdc9ZJF(V_hsCKjuMO>7Mp5jZw(-$d4(PRD2*e7fb$2d zm2ACtIXld0$V>Yr?X4usV@<#IUa*u@i+|Hh)TDW2f;f8`!_q|2x6iws*yrNjA^#wk zfJp~yrft|5F!Gm)#G@&(zBA^=L7ma}seejb7=oXXz02pbs&vrWLrkp*sMQesHfeRw zo`@h1AsFxn4=Mmvu^1)zK|DSebfS+gHs|DA>){kES(@3MDCQ*&ni=~ay{Vaj*>H+q zCN&{T7_|()w?2GV_sCFp1#1_Yf%buAiL!e^lwqi8%6o5rtoybK<#{RmP1%&li-?>T z$jJG9!m%_{*Wdv>UE2M805n9|S2KO}Hb&kN`8hedC=!CUv|8K{f}$A}42W?sa}=U) zncLKtz-d^*FWhT^7zpUee`rS^U|1d>!LzvzW%3dQWN&z>H*(tZ(){RWfbV0?%Kx-k zQhZEpU$P%X$!0|{}#a-{Fc80DZE$9l3q;h5*6 zm~<=!W_XkVJ8EUX>uT+X@S* z?!4u|CpA*jl7u~mZB7XCVwIwO8DnYxXUNRyP5SL?Ay2^-8Yk~US^EJS4X6(acz-Vl zFK_B0Q;e+``{m>NVv?>TV|a_P58i9gx7ei=Xy65a#ip!>YiXtOHm>Xy0rq;QLN?+TW>JYrBqkNt^ZVh%*z+*)|oI=A^w) zX5MN06e~W4W~fXV|Clpo4AZ=V%P!Bv)ownD2+3=9E_;RT1-1lZI1-v6r3ef&_s@mQ z$M@-sAV{@|xAt7f@{Yj#0{2);JqS|wYHxTsLFr`Pd5%KRkX`^8DE9{GS_yKTP7 zr7!F9R`#?}=8|dWTu{{fh@kSy`=WDWR_ZUm6CLG$)k6jmLQ+E+ zoIqxqWV(9tp&1`3YDs%6nWIEU+p_jQ4R#{}F zbUtvcJs6Nud+noA<%>J``}?Y5co|>s_AKfude=nwZPh_WR?@5^_71Kje)l!v37WfvG^>YP5pkGJ~XCGR_}xwJAIzEf2r4!{4P-g z(k`#+4R&>nkP3Fx+K^(I$QBUBDg)Nk+71T(ap})Ejt(q2;$4pyjO8XXL`;ql z<#+G_EO#BEZ!@<|*`-Pcek)|`dTT{#d zwowxb2r0kG=e|W&J!1(&rpg6Oo1EISaenku?iXJp74hX+x{>$Oyqo8Fu#bB`V91R( zc9M%;@WNnp9b0S_d$2GPx@F---?X^+Odp()fZnI<(6F+3)_{<%4kryRNJ}=-k|EaO zRn1rP;C~fnU*4Sx*V2$O=&-IYK2GYHKN;52pc=Cf2}r^WgHbrU6;KrYRi@42L4=7fYKDq{<;Nn6u3*c0SJL$1p@k`I4r^|Ct-qTF>o zc6XZmbnT}_MTC?6Hq`d%B=2;Q8||kc`}M!50L$(-g-vLpp(3kWyU+Z28E;e(;b1XJ ztdNi*8ty!eyuMC^pg#QSgT8KB_UUt3h?yl$pi~2QxCJLwgG`j%`;P!KiTlt>6H6ax zyDU>6Qx4W&+WbfoZDG4Wff^Leo+PosMpCsN9;+uBl+*sqwB0}JsLG_ifc|AN4_Usc z;IDqzOqq^d{jmdmW)`6w?kos|RHO1k9xe|^Mpm^maZQR1VYErxhlQ7iYscwv*i=pZ zYn#3ueqKtDec?@cGEkU({Hsx>??JK?VPLpaVMem~mUiNN*I$}B&8FQg?Ns4DHqIY0 ze4{?x2zSJmp>Ff``n?sZ{#XwMsE}YT=zZ>W327N*=q$`xDG+= z%?L$INfd&nHBh^W=~}X>5gztv2R}+-Df(RXafaF(eDD^rUJP~KmY%{dK`YJti}**2 zCM(GdCx{baZ^#j}rklnG-#97{o}>u#L^Y%(9mAKWnqze$LhCCP-$ym5*6s%_si*S6 z*ZFH5fu?@Y+`(tw(M&&a{?hp(GEOhIE++9{v(ERgNrW0^IOeSiq*1fr7*LY5LsmAI zL#WmV2Uonel0+_fqLjcTEVVTY3g}-U0?%Nq?$Cff!%GkW^RAFg zv}?ia(w7oY$wJ+dnln4%m!OF$=2Cg-!nMB$?>pGwABbz&%*r)w#Www*Q*1oW#j3Mk zB@Tst@Kt+vYJWWMq^faZ8=o+uSB@14K^r9+MzeHmB?s}4>O{56>6=zwUK`#BoIY@1C6JT5J{3{t`JF*diLJ%V^^tdQu#m^QD~7j zbfx;Ew$11O*X*2gf0)rs=ab6AA7VWxXY)77S1Dx?BmH{98$w#_P~&&jWBH59$SUPe z3poqoqlu|$lml&JiAfzw9N?yJo1=+g&B`B;C@faWV;ziw@vtraNf5oa$6X+Pu$CYYM-b|J!dK1B$u$%v=h#t zU{hC3d^@ffVx_KJpJ>LA%w_2z3*@S`OY35KEy{{i$1q4ryW_(BOI;%bG^jj^xOv$%gvzn)(Q`Lp@ll80@U_88udQalyH~Y zcsV+M>drNOpO#!rR82qhvjc3GCB#T8_R}mZXz@$yqasiLD0No3RT z5aRiS?Ercp>Qpgy$DF9V#hpK?svOS_LN}HcBU2x>+o<1^|9=2-K#jkL;;tlV55!lB zL-IURK5q+(qu4P=)uNBbqM$J$`4vIB0Cg1@^G2ALA^5tS1H!1H!&su(G?W-12^?N7 zRTNqQ7l<0D%TZe1?uetf%GxMKE4m60y`w0#i^xW!7`jzbhcau;6h|Ed ziUXCrvoZmwPz9+lpc+LBNT3EyeozgPnkCbwq;RM3T@oscTAj@Nrq+@MTTXUMUHL?0lRPI0AJ@qfG>99 zfG-1LfNViaC;*3vWdIKS&7Jrxpbp$>r4#@$2apAExp78?97F3Vk?CWuJzU=WaXA0S2| zdOXQPDr~TaUXTydpEEHr12aZuR6M~$Z@^^C%8*)WQ=l;~L~$-c7ak`w;t+8EkeG6w zAq8fw2M9nU55yoa9pok*=M0E2Y3ptwFl2I&m@-*NOc^@FCJZ4H13jZE#3s3Lz`|$? zArgawkcmtZh3Ia;q#{%KOWqO#!Vwvvz^gO?kdc}k3aXuhkz3h=z^D&kp3C+X2? z=(y;F@le4KiBkpgJ<%w|Z$z7-5g8x|gpPJ7J?vLRB**=)VgQUD!~g^GLQN;(N{J`g z4;uL){6qW&AXuwf_A4*F4p0Fe$LvBQ5NtvsKExt1KExs+IM{?lDO(VTg_F?<9L6q1 z>`9fLh?^=7Jj5b2NJlBfWFFLtgsk--6#^3g3s6r~&t;I909t}#s84i42NDX9gA_7P zXhIJ}Aax{?5FY&?gatf?LIdC65P-H$2tYt>$UtRrJ@~JJdy4P?1}IDdmMBdYhe9|L z=1rLPB<@F)-MJsN%n1B~gpLbw2^t>~5;Qeuh|rN8BSIg!8y>VHcaUsHOHX1DG53(1 z(!7M@)`TK2TbQm?3{mqTARjUk0DGZD1r-kz1_k6IQsaappzR?N`XB(NLO}62LPKOs zgo4b80R%H3A#@3l5V;+xkPw4GIM@ha&RK{dNCUD2<}erObSE*;AIA(QF-AwfhcW>Y z1Ar|c8uKDRVr~{dW1vicR;ADyDUcIiX#roaA_82pASJ{yASJ@cKv#W&171PIGHk|B z<6-%4e1;#*6*_R@0oR~1fGr{Lut4BakpqtK89)ikNP)suL{7;VhY&Ka0|*%wV1x{v zFGLKCe?$zl;5k&A?E@+)Iz$M=T!@Smm=0H3L<5!394Hf_ZvD#Spe7O%a2K3Sfrp}M zQOHf+=AIg&{#HV7_X!EmX)}q@21N-K>1py4q3NJGQw9nVqV)zsZ`nD-*c7G{qNI-~ zy-Sdrs8@-oM@EY|z16B91H4J@$t$TA)Gh;sB}wL7RIH$I&kR6O17uHZaUlYsHkTY&M*MPPX4h(gt50{=zJ3%M6Es{_RZs1F>Ws1Fnbsjun3PWK<-aaF2*C#jN2t;&MTag4K=76!X1~ z9F3+q?borxGQEx+yQVaxtud%~9BY1KjZEe7u&SJBDyJF?`uN!yY;2gZ#;V1!u&SJB zDy@xy-MH2^h^{qJ7MYm^gi-}}IXWkE2QPQT@B0-^G;U&K{CZ~ zSrVE}7*~0MXSJl!gl{=gKJ%4jxTRHh5p8baoo(DAMVp2(_W-FMa0;i~0;;=+zN>J} zckW}ygX{N}9~Td7bZE5iFv$mCw%Ne4D4Gn?2zgXdfdGChPP2*^AWZ4a)KH+oC346z z{`F&h<9DmWBYzRBO3}pu)gmQ7f7r1TFAqfuYpyY3DTP zV7y0J%$$kSls1#f?2cqPu{I*Gco}rbGbBuf*nu4ORHhN^k1%4kyp^@s+x2-#?oHYM z3e^@18qVd41$UPxjt{C0IJFQ}sLTi1fR)IKTve8v^cSZPc3$vhAl><^cx6KIc)gUD zr-A@1jXl!*>qS*2$II3@%1WfgL;|^X*9YWhxP~x+f=Bx(D1*5l(G?0IK}26{n@=~D z(9)K)zv)&5@QnFUq46vTg=6h05~8nAZ@lXfv*a17=JR0Y}uSO*dZAM3Buo7|_;i`_q=e{r7V zJEj@THH9Ay=9?IrY*Ept6NN)R@SZdt`@E~nO4p=la=^wsxsY-hu??BPiQ3G} zO|V59@s%S9p;9EF%!diPBR}I;(&8EcVITpr(u@*lHCwm7>Kf_8 z8W4o>+8cABE!>ldq4aYE|H-G`;Ocsnj*h&=u>ubh4@YwTqM4F(qcHA;J;mr#89B%o zqOuxgcaYJ-4^i_{|7Fno7xGe6_eJDm<`2#!m<7~7ucIFvVpAVN0RnyDdWjcp-gDA?BmB7+r{F3>|?DuQqt5%RC2 znt&~o@;q+u?--;Rqb`#DZYOg-EUcoB_}M|-&n_n8J#0`KhteluPc8Zxe5E%97Dk&U z#4{kGFoYSiVNDAf@r-UO5u!M5M~*)St|4sM#R%ca-iY9HilMj}x!{}%vk&t@l9<;_ z%beYIQjCH&Zf?W18|AsJ@NBV>A!3wesj>#oSp_c>TU)Kv{BW3i?Z(1>YiViGT~aH7@EmL5p?)~TI(Z;{ML0`D0(PI=EL<9J;x+ZA(s@^byz`e zfsTMfAvkyClo0bkAf2=W+T~^B9K=8uZj&ph7#DB&5sAU_<13A%7edltNLX-qanId^@fQq=9d!DL(_}G+LQ1GU2?zT4A z#k#GQozBzmQSfE?TNQeAM2hE^`o1QX!t~<8*d4YDy9k5|@)Hb}5Y2iqc#A~Iy6B)Z z0(TKZro|xqjKB@LAy2Ns=47pK4sK-V&(P14_NXeyFIOpBlL{`Dx@v=#eG{%B>}|Bs z+ba)7F)T}RA$m&pM@9X8nQRPsB)%mi^FaGL%i@I zKn^&J)kRL542W;z7C?-KW`1YV>LCzAZ`hb)Rv30u9B9rkWN>Dx186oAh;6hLs{+Q2 zB!Hy)L|^^k>J)N&vJ)0tCA~j7R4F?>?m+KnO-}RI$!;*HS^1FW8#(}UK%~<04_5aU77GsF26we4+ zM{ofF2wdQ}n%u}pZ2f>oVhbk4SiWljjG5@*U6>R|0{p--qEe8N0P(;UGGP0^FQ1Dr zlH?~#2Pd`AmE*4u*pqO-rbg)sP{IG{%Ji0XQm4#E05Ep7EXF(TSr?XGJp&9e4mAC` zK!Mk}ayMC0fRnc%qYirk|8n(gO>DH2lZ7ivJ+dh9{%oZoY>5JaWSDm2|6%yk9G2M! zY>3Sr+}-yzFjIZ8Lh@jw9nDqad$2wXgNh~Vwr?Mk(Ye@qG@#S^%{nIx^I%}hG9`ev z0=D2!P-m;M7Z_qqflfezU_|IL>$C)_K1wf=)zXza99UZ=#e#n^)m{Yz_~|ark*ew- z0(!jawFLhdVmk-y=DrHC#l3%BfkcD79TUsPY#z(d3p?3-stkaBV?#vjJOVzc;TEEH z2e=w1QBl^3))wiCVBrvfPvMuC@orL;SPDQS=l;;AAgBN3Se z4HFS_!U&kGSOik;jxr?^87V@MF<79tuMjeo2}H$WUG?fm*h-UfAW!m<3z?%?O(aZY49p^9F8Uc08E#(DF_0+siHwDAXh8u68eyVu z*7bxMJI&dv`xLCru#xY2BB;z-?$AEWvmK8QkyOs`b67JUixBDaFJ%21Dm1g5vMeA zQY$5T>WJMX?=uw>Cr+PbZKqkEjD4Z=c|u!q7%DEz7aIIuU#K$D7lduP%Sc2-*S_la z5~w|xWhcSvf$6*9zIxPj`$Bz?m#2`_@`r?_%2Ef9%|l#9=Ma6x@p19E_MB129t)15 zx`|mrEV%!Ex}}Kv=J`lB!!foXzj1s$YUJaGP@DnCCrM97c#a)Unt%FXDUkBOC$~7r z!S8Ej2%U^EoVfd6U|@A=uwoz)(8pVrmjg=oIohi`d!Mh=ck;G`rZ@gNszj zNt5cEKKhbT$y`Gxp;T4<_2^m#z8{*HybGQ0lD_oc8wyl*=s}I@P%ZVB_Q4NE!s1P>T4S$q3 zUA3*DZ$xHgz?OOjgGdmb%mc)!HWS&(3rpQH6<#K(Z%#go4F~fy&jlktrV} z+H9ARiXD(M1f+|QoFR-EHl8fvT?1BwFii{L^2o>Pe#fksMJ<{&|{VH`{%k`ATd3jV0yH%jw zQJ+t7fwPT=z%m+$JEg+9eM_P~ra*UMrSKG8SaR)R`3iQiual6!;nS(s zTyW^jD7!#;lxKfTx$q%*fq$w(MXZ)u!2;|jaLHs?67Ys%NSiRJ@hE{fXd`*+%=M)` z3=e82AnD9ei{@$CJyQx>`j0s@n90DrDq%N_UW|A}qoF==L`ooA^6lc0q=oVP3GxZ6 z9uNExBXmWo z5rkw5BO$2+P$`Jvp$wjY22g;XJPYuGTFT!J1fd}^v1F4$a#Ku`~)htU7& zE%byUPKTG9>1 z$a6F^#X0$y$P?^4AWiBTQ!n6TWn^^0)cwV?;v?}P5_|^(Y@eKEjy-t;|KU0sDz->W zT41b$Q|nCB$#ioXnIajf^ace? z5-bLoDZaG+VNzc-oQZjhOHh~La6Sf@V?(dQkX$nSIb1-~^$895S28Xx{5d+Mr)Zxf z(4#SFN625>V*yTpq!svGB(211+je5pw=oD&+{0stX-@OJ1v)oB)1eXlIvYMyp#ljp z89GuiRJ4#IhWsmb-kkwv^yrA~PJ&x%bVdtK)w8r&2rY$!Kr+*|dD@);4z%cuUrvvS zY4Tc%;BwL=1kpz|Z^BQ&0~ks80e!li9%ygCRVm-K0Q7M>O3II(cpwIQx&7Q8NZl=0slz}JU1k{ww79`+{)>~_9rer<# z{5%n{aF4@)+T`Q;t2|Ro%hd4v2dRiFIQVDNd+;8D2FKt%9oz4~dQ_mat&~Cl>02lD z^Gb~};`8txW<}@VIIn%z;5^1}1x`=>MfeXlQj72&Zv6@7(=v4jyvtiufRm!r_AIhC zvq;LQo$^TS2jDzYQeS}at5KvhjJh6nXn-%1yT!|d{0E54-jsYohws36JB{fl;Ostr z1Hb~MKu>{|<@gT+qnGeB5$+wtI60~`)NMwZbtM!#Ge2@zx1UqYBBLJu>hwCjyuhPV zC~8GD!-$>+#BjH?YI}I^hd#0Wi^YIe`DIH)p0=4GPn07VL!}R38PbNx1azUTJ33I5 z`Z`dKH6E@>VF&3($+<}6M2>D!ARiYg5T}GLQmJ*J3CELNdG>ekDU=7+Ua1@6&jt)^ zs>OWb+{GNF2=EJu>`Cx+w=;FpIjOD)oyKN=9T*vslfdYkrObrXaGQ5_tbW=+`)Lwo zNZ8K9@EzS8?q1>5$dRp%=|VdyBq422C%SwyY#QI@wo@sycZ32rlGxobrkKR3Mst&g zFq@u8j}B$Q?sWbErg|ito&ds-=5!m)$Vlor6De90oJLVCcW0MjcT9_?OR;MqTQbWl zIATCcLOlm7{8GMz9kyeuFl#RRB8P*uNy#NbeGFtBGeXL2QqPxfd9l&+V2vP2-6Z)6 z#YX$+#Lq(n?6!cG76YD#6PjXNsALLtBq_{6W*?pQ5KD=R@pnVm7Dmce^UwW|~CqSS6QEZXI{r6<#MhzR~MXsA7k zwzt&~n3eEVK{D`|0qz8yRO$tk%;^#3C$g^#CmiIhL^{gl{<7B*i_O7fh+N zk%V-E1ABx7upt<49D%USU%ZiR1jGk$%nHhbp}3*06-Mh2q6*il7~qU8dbJgnZ)jY@ z2b7Hi2biL)$;<3oATZ)s8evg&NOe3o;v>^=rxv$}sUvSfA#g_cc_#qac?>x3Od+6w zWaSZs29Wt@#0RLSg{?&lI3xgzNLOFg9702*@AD)g!O@PG@f*O0NS|AF{2zW@^!dzf; z3$t>@mF6hQ1<;xm+vJ?NQnTBG4d2q@K>!I;pwtgEt8I-S()9dgc5&pn)PFuYZnZki2jbJK!AO;U2V~i%OY(4(=sPZXNTO zp>8z|ba9(h<=~ayxVrFX_!<_#02&?;$76@yBK-g z87%9wLZ`cBN2{_ZCo8o=g`L)^42pMBl2&(G031r{gQ9)fDscwvQZur;#+ov_Q2qq2 zr8^m2N@uLDr7A@$sY_8SsYsxe){2aZb%^d3yA;PLU1G@x&~ZJ$R2&>m$_^Qu z>I|53tVM%a9hOv@8oX|{MTddxqk^U`!RLqt4s1>@f)d%R;K+|>AZ;SjC;6H^vP5c& zElw_XK66qAEM!>KGL5Iz0|zLvm=Y#=D##{qKMOKbnnDfxqoF(=JpzcamX;&LZz{1v z$SzP;%7|mxRAqWGxE}?~dls9wAqpt|wIhZEsP z1y99V2FHr%SDp&&aQ3sEl|atRSmkBu;AJRoveq{laCVtgD@?YUtgeczvxZO=!O>-2 zQDwEsWhf-Fn4~g;Q5i#*ETG$#P*KY*V9}Mfy_KU>zaX6WYF@4Ra-;&~Pihr0sCY1_ zcn^=f9K2Mss#Vm*O-YKx@s(5KD-y<33yi2K8Cugmp(hzpA|jyM#Yt}!L^f1085w8~>mBq)kVuRA4p!Sn;!aO`nqK5n%_$T8f0VBd8 z43`4o=djQ$P&5jPjRJw8pip!J#<*o#z2uKtLkPHM(1m`pf$c_ojgbR^?2nk(&1eOJDz>jbMBCr4w>rfE0 zP!Z=q9hQJGzJMUBJ?93JA!cz27I6oLaRGjD7A4Oy7U3c*VPZ02V@Sfp?S+WRbIek( zFEseTyx8W_^KteUnkZOaYGp<#KhD$C7|i5_vS8tAW?7w?(C+cI?9 z0Iyq`Cbu>rZfY}bY<5u?nGEZ2a3H>-QmfOZRbmumwUl4Q#*llo@gS?vj%t%z)TYN~ zO*y8}g_9;$nT}ip*im9R#>OeZ+9}4qEG^ZW0FP$CNExsL3pN0-oq*b}G~7Yt~@3{4Ml z?GJXu$EUJm)UNjvAn>IbuD((#6sLtIZ*XmwxFJ;ZBjG(9B|Q;kEfeV{k<@%II}8M= zwDyH489^#^_DO(aNrLW^092GT_eL8iBMp)0YqnN_2U$r6Q{e|wIQLsfN&9osr~}fY zIq6oJ=~%hsSAoJJN}e+|pNtE~B~X)+y7Q8x>BLrUMj{3RF%V+Wh=Lf5L>dHQA-qN+ z86zDghUUNA|RKc5e>o-5Zs>;3K{VbKNA@KI>atE#4R$!QefhT zFzV14b$t?bV#zw4%t|UwYCUjOF8C%$p}Zi?!8%|~R>?J3$f_0*R4*d03e+|Tsv8hd z3&^QpNR4cb8gv>o_!^|1F0Bj;t9M1!r}FC5*>!0SRa$YCR-Xk`sgkPDz?!#YOAzLk=SgNjCmI*+{d|v{l`xh{1Zh-a9TFy#YD9-%QAAi&0-4Da>5fw1S!Y(1H8ctd&jaUlHp_@I5+#G+zJLf1 z;$*hANtY`OIFLPA=McfFpgs^IKKIRhj{kYPHPW69(11W#_XS}~H)gC;N)~R-c_;c2 zX6)69VnWT?s+8yzLJwhM)fL784mDQ~HBz09Lvup28Yw^JUIH>V)kRGi3>7HC0i5i?5+(kIows&GD$GluM}@loiyvlRe_^PrHf z;Bvnr(P0L4V`~tiWE1d*sxe(0q3o%%AbB!a7f6{*o)^V;Sz*dOfG4(wZb{pgrpkm( zpds}UAirQpk<&N2&84Zp;BW{rBPoi!VSuJ_F5I9kOxc0p<0%LPG{OPW@2`7l2|LW$ zwj|V=;g$gqX|9by5=0g4d@sojFbM=lhO$qDks7i*u{ITwkDwCECn*A$1BXDB9@qSR z3a{ckAcNvqg+Z!;EJZmPRKS#^pN*{nHHsyOlS(vlo2c2H z1)vGGDKwOEI&`=1gc&BBmf)bFq2fo_Vo16788RCzlf)#LGy{u%ns|kpD3Q6812`7+PYT?OI zZmENGW@79@ZfSgk=SgaUe8B|@UdJ%Vwd9&U-HfQtcEKV+K~gklSepvtD@ha;$U$}4 z5^l(2_)(;mUU@~(N^tr_QYaOw?o8qgl%ank%9Nr!s-*CZ8=a&;3o%;NB2mkW<=(~&zOg3&}Yq~#-$Ne{6k z6qO`@$zE_7Cn`$MC2^oYEg4V`*17|tKoViKC`)f8(1W3>jp#g*C`&yO8U~V}kTQ~t z0P<844U+Ag%5y!i%^XS;6f2y&wi8hhZHN^R+~X86EP7I>%HjwPxru_!N&8hW)K(q1 zJDOz;?h3gbDBu}dD&w72j*n_t6;s+saCnNI+j)CSZe+kanK4V_CJ7;}iFI?|IT8(^ zJR=K&bv|x%OKw5)Q*;frIXDx&j@C+xP5^e6oDAiiZQW;UT-xZkN806Mv7ilcd0`y9 zwVN`)@~%~v=3g?!s+(q9$_}duzilE;A|pfg_)i)d8a>p&vtx<;l2z_r@1=BHOkxyv`A=OCgczTJhKBJ_AA+qf@I zRH9g!qsuPaM9KD|>py!+f6qp`&-}a-RH|)*qgm?hDG>mIL}c+uj)U5gL}`^(4hOp; z#v9C5utQ_Z!wrBwkSKYe4w_V94H_--K}_>BOb>YrI)8?6jA?-QT#PwUP3OkYfGH<} zG&&td0kAU}WE!t9`DBd@-7$h_plphjn(E5WQoM}{8!O?3DR&x&4}Iv`8Lx6D8Ro*- zGZ}rZLl~)Y_R$n*bI=@Rcy!+6Q4f2UJja?M7!oMMMwK;+m$NaQsRw{!fSpyuRsp!Q z^>7t$UlJ6c6GQ&=C1-o$L`S|^Ex|}I2$o(EX(Yl%B$pQEjKIN=0fPzx<+4~9QK`FY z!G$|R4+auL(fu|gw&VzXQrc1j(F8wF4k;q`a_rnMm-gJIKZ zyZ)OZYDs^fv>^;Y@WLFFxW7U5n>~tFoQ58W2Q83p{ZXnBA*;}WNJ@;JsG^NmR7RUY zet@wXVf~nTII;=cA5V7NEH_`dWb?5H zQEY`IliZ-R2~V0+`)hV#f)2wK4t*vnCO!Gif?mS@89tI*mEEM4LkvYMo%7K(7N;6HIVde(VY3KLX2%P1*zn)B92oM$BUal~!m9`@H#QxICWJAil+EPH zloHh&loHnz9R#uQ<_|qAc@mzMF7QuF7QBKa$tWvmD(5wQC zD~MUr!M~G zv6g=p3M*b3+||fl`s38lyk+<)rG6_H zTVni|w4#Dq6XujeqNfs23`pX|3`pjz!csBVsRIH-Tv-VoH+(`zSmd7c zWXU41g0v5&-7yF~BfgJB-JtZFWCKv~Ok!Hnh?ZoGBKatubOJP+gk6x4otLrFGdFrV zMpcLok&(yXWQ&DDGDXT|QeAe+OTrT=_=CjDCFKE>aFN=XbOw_!pQI;}T zxk&O8=@LxJE`~_17cr6`L4Gs%-jo^tAn+OgKz|wj7t4(QFqL*cD1N01a3onWX-7rH zIUaWj88V5{r!hX=caxfrgeRi`H4#QL`S#i~|FN1g|2XajkrjU9g7)$O zdsSb1a2@T}iPz^%H)G}r|7G@dZ?mQF&Zr#eAJ8z1caD$L7*LFlWL=p$oEX?SMlx<= z84qNGPQo?Ao_*g9T1z$epK_t=&I~a97-9W;59`=;zKtA1^8*Qy>^@h1a|ApdjwBbe(oBQV&)N?BNoEPnntkihb$HS7YFl8KEBOh&Lp$j87}Bi zI-)WV7zUm6lF#3HU>EdRKcq@+>}_C`{!mDc&(!#!i5Rtk_yU4n;ce;(LQz7&9DgXG zU3j?ee_1`x7k5x>I3Q%_87!Z@EX8Rdy`1DUb(Ds&g$1o9(X6D_a!EIjTR|k5Qd{#W z2U!RR`j>PV9wKn}KoSWRMnVLYK_mf++})&-QcQwLF7=D`AY!5*{>i?KQ1@o>3uQ3ACt4<#Zo}dnLS;<3S`s3ecCfq8C{0Ce8E zCPE$F(!lAHWq{?iWl}|=10{<@4y@T^8DIHw7+DF3wJ{aLivzg9vSi5a7!DcE8RguO zhXfXy#2^R6Flo99T?bvJYmqP;p(TMRCbE=V0;Jh-@+c$Lvf?$Oz00Hh*_D|UmI}_U z&F;(k$zIL|t@ThqLgr>3#tzuA+ZT~mXrXK9%@k&V<(+8A^I`)Kyn$d%AB-=)tH!E= zuB;-8TZGsMwSZO7Js^T9!4DZ>N9Ukg%L1?K*Wjqu=)CBaCdp>pO=^=vrJxHh(_RyG z(_ZpsGFozGK^-FU1(^vgc`#Wu*)wS{IJMy(TLA8kgX0~vcsx-9f`T<3ksn0_VAg43 z3KyO&Gm6ZL_=`7-2a3yz3yS%RIS1e&Oe{28s|O1N*9L45%PoBfUq%nngY;n4HG@U1 zx~sHBDl7qUolAO>5;D#bfcqZ0(aYdDSHSQoz6RKUV;>i9xtQ zjXiTcTD^xkd~HPt!7drE1lNLV!K4{GQiBEc$RZy0Jon2V0B3oO?krd;5Z|z%#3sOr zZQL_)yD_1n+=n33l6#fHG}Kve<>2QA<{}Xe3_CHJi#HsD&SDN(+l&IsDLrh-Y{_ie zcPj*Dc?{1EWcbT)_l~)1Iex-QFtx^03%cinK&pw z30vG4w$2qWI`MN#asaj4H77NLHF7mMHDR^6wPJh-!NHQg$Q&61DNq514?<5I$r7n7-dj zYUvO(v4U9t%O9&By^q4g?*b2*U(ByG z*fULep=xp6{GBECf#5_Ha1tB9NN)ily99>9<#P*_TrN+LxiZ4%Vxg|4GUhIu9Ge!) z5L*{p5FLwIiGhiQjJ=BVn6QkAEZO`fW$+lM`{b+7x_Jmer#Z6JX{@P0p;?!#Gm+YU$HVJv2cn7C%vx%~y50zKT?M zEgo>rrokZFLn$NM0rM)0e&Qwjf`?`oJYS+;!EtSN+RZ{Ca}=Oj4&Dqos@Mzuzx{gd zqTIH!qE9p{?dV*D%zcjHtfHuHy}nghz-zn|EZ)3t;cC1f*%7Q&P+T^^uPQ{u@M(mg zD))vOECpIBupzlaiC45v-k$_4+3jTuLf1H8*HFq;Uyy8kM=Gx@HPIjydny~73&qzU zux)@9qN=(fv7tdzCQ#Q*KvZ5>Z^#5xSo}7|{3>>88~OAqWp#GwE$5bT$9KS~(-6=f zXsE8h+3QrOw8?o|7HYW$kT^wFBB(Z+6bxe9vrr2_36Krv1gF=4R;`&$V*z8kGMdW* z{AtQ+(E^`oiB#g%OO;W4z_A%}o=za4gmFz}=q(;JrlGhixe`-d&?vn2Q&o^J-sn?Y zkS!I+t2MC#uIP7%80C zr!DXo?=&f`fERQImzs;fzoSB(z93c%%&UH;g8Yg~c|n4)L?u?ba8eY2rEG8)?iML# zWCe8u%1ihPd0|DDp?b#l zT68OT#Rx6MCC+@l>nSd_EpN0rE|cYhK}lJUhz??s$9f6*A!M%}n0%!rj`RrfSjlsJ zCYcILNa<<1RW-o$c-<*v80nkN?3W?Y^j#{2FZ4eyl(LPcLLyz6==ZWwR3||ZWTL2F zM~=ZkZ2pfn3JXcUO2QOV%M)?aAO-*qi&H2?lj!eAxqEXnNTFt1q~y})`OEy$g^zbf zEYjuC$?|DJ%cns4S#!V3jwwRKqov*zth7CLrfQ@nGj@38}s6BY3Yai7F|c6jfh`|=QErUU#-%um4m_9q!9A-+A1D9CR6DH%Nhz9p<_ zklprZ?skHES*vqFJM2WRPeJ=pTUmg8_EEPmVEwvlQ9wQRBG)mXJ-A>%;B6UZ+`0e{ zNVMy>-w(DU?|xG&f|b7Za3E)vf{ZBz7PsHrv{v`N!u7yD-#q5lH=XuJw;IcQ;ASYfg-12rwr({AYrAaK)W6-^WJO4&-Bv{E1}Uejadd6!u+31(rk<@!s@|(TH5|0l z)u~)lPgR9;Z&q{_G<4I|VOv|(WMfg-rk-jb0$bH$Jy9K|-?^uoZ%q|-S@2aTsTH%S ze6;|3I+brwT9@Fe!BencD=caTl+(pTh0^s{vZ>Fen~j2@qbF6DMN4%w@q8kkH1T`@ z){d-!d7Bw%;9RO?d|vxABP@SMDW*QDG;+3%e}mtlFPlE z>tgE2Ze_Apbt+_-BgODmi3$_t9MblD!v&ZU=9B=Vl=v-L1~mR(5W&wHlFE@ie?e>PIX zzXfRvILUQHpIf~)a&JnN-Wtn&cc#Z2!S&uae;sdzQMf-Fd)(j>N7-f2-W0b!3aWE8 z61nfP^w;SHS1@6fe@x0~<(EQnAJ^&6u4AfI|CA_fWpDJ(q8N0ym(u+jj} ztZz!9(FfCb1%S*$!kqe|3nui~KEyyx>0Qi9P~M!{|>m&MWAh7>5JSKt-XhBwZERVz5+@j3h8Qro!xHG%5 zHxAkN#_PK`I-M`srn8Dz0=(BOjp6K~jL#};1{Ozat2EoX&8ZQVZh_{N(A?{|H(+jc z2ijL7bFCSmC^tIptqEay*FtC}i_X0ZPkokYz3mZ3L1U^c(tyhHb;2~$vmG5{)quLK z@z$2J&|Y=eEUv}pQ88ygUUd*w4Px^z)n`CnWk(iR#O7G~!|j^?*DbTUE6BTsJI^trf#;}$X6;jCul{8IF+OU{RRkv6wCMv}iQwfT{Yb%1qSQ5)1 zu~ZycEEX!r)mtEos|K?O7Al;}H$h^nfnoeCRs5_KfyG)< z%~&|AVp#lxioNBZKrvVJvBv`yLM4yL7>l-9oK*frlPoCJwGnA61&}coNU&K05ol`> zWpiXuwPXASBGeW?>WYY^Qoz6rMcphf)w4*Ua?RZngo;um;{k}a6qL|07ygj$MB*ZZ zNdh1-6uG2VK*U~=CKvdMbtLkC5l)1Gav*sZwvmhcMX{s@BEcfWBCkjIYL9gv?foAz zKh#uQlz)cwWuMDj?vgo3{}z#`qB`f)5_&&~xOAH@;)*%Z{(XuF7Kk7A4jmDB6C`HF z$N`9sZro&>uVN{ZkRSFIKiB`FI_8StX$pS9!uchl2nt^f;Z^KK?nvaLrGmSpjt{XG zjU}_#I7W_gBFJ!v{XK&OR?3gIQ4mEO@d9NX}dFdrGs;Wd8kI9jpjm)Esf@I&3l{7R~!B}m>4%;Z#5QZGH);@ZfxFeaibx- z+4Dx`?_iC0jn?rS**98%Y^AKy3H_U_SDIVvH1%N3*1;NCYc%@R4gZ>08jRLy{bP;R zs2hPdJGg5IZg+s*0lD52YNqE%%>a$g5)H%~oLHK|8=UzxXwGRo;f>A^%|^4DO@7VJ zsv7U-G?-6B=YL5>^O{e&(s94UjJV9FAjF(xWR^D>l*t-N#t{jh6Ma-C$eZusB2hQe z(m({?9^{Q;Z<$`A^4;?uyK00xgp*b~DDK}GTV*(e+6GWyqfkrEWd@X;-x*j%I@iWj zEThy-tjc?ok`uCJUl^c0d}Uh-J;~oTp&ThaCw-L?X+!q-%hf6RzB1@aG;fTcAw{y- z$~F|J+Zl6ZJXXe2a*ca!i4jtcyJIUvp*F#{p-m03mrPLMwi>!O zPwlqVXNO_{Q=>dPB}EL$;n)t8 z^iK}XQAf&nb{l0cbHlTsu#-GHJ>>?O;aCHdMyG{i*rzIZR&~l!Q^K&+C>EX-h7m;y zcvg0b0CU2z#8DNV6_=!@GFVmvWer(jS=1=|OA5_!rHd>pA99U^Fs!f?Kp}--3R80o zD+bbyj4-S*3T`2VVVI?=7*+t~9}vQ^dMIkc3d97Z@)%ZnN*Zv&u?$mj3@ZmBfLt)F zzLajm3e9++KMWfIQjwTo+2Sclh7E(EP2=!v>l8O%gJObH2K*a0g%l^?*l8)Dehr(+ zLvi>v4h22$!LamF5`GPo;(%lDY(PqT-GgQ{rJdL|UKYP!LVQ`_I3@C@`k5i*-t13b`6#V4UWOH#GF2S*OF-YtiFyl0h!LbGzwQdc7Sj7#vHhhL)S%YTK zXIYpw5aT<{!Lbl95M~XK=*$x^Yb!lwerxWX|w7AYeOiNLei zF;q?kn&F)k;92Py?56_4^k>yL78_$7q~KX-8Q)F?fxyFcI2IwJ2;|^c7>vZzfn~&E zkemxF;|P@CSj8FkP6e7H4kX}N+4spf7C%OG6M`5biiU3bQu)m`nosSSQx2B`xsrb z=-*}dW@#JjU|+B!eTCS=f;ZTvjB%rVhEagBH?2_0dNS!7`ZB(a{eFxlQNF;eVU-)~ z48|ph-)7KZevS4%25e8h&iKO-_t}3KmY;owP{7pt?9Ys$pM8y3%vtx?p&3Lz`x4^- zC*NaIFf~5=H^Vch-)DGXlzsLS0|Q6jVv{j4KKm1qh7tGJpd9%=`yDYTB#Myh`&eNJ zuYX)%#$db=NOjoFdK_as#Y#DI=GqFZa;HXbg{?VX!wEu|yt^@t@UcfIATfm%SmjT4-wRvi0fs+?CAo6L z8v=v;sjK3mnEasF#aOAIDmY{OQa6?&F$O;6^U@T}KINheZjZT9A%G$GF7Rb+RZl5+ zVvJhjq^7S8{=46yl-0v=NwP{~Vx5&+wtIE>vakP}h}08KxD4P8r#|Ha1}kUWq$t1)`N{;KQ{Py~h5!i1_DYTkk?O|?Y9G3MI2z?pzf%~6~n zj13D{j1r`6tH=mKn`(~%4uJkEQi>3W2k}>wK!-zZRk$K12+gWA2?{pVytqtlt6K;z zn`((+F=pDQz(JX|sxlLMHpNqfB7uD3lL8As?|7uJNcpxZ-V=K^#TbG$=GecrPBp;> zrx=wO!PVl|1e^j1{T;})sM#Y0vusn?BFYNG78(&}HpLx+3_yc5I0+&fXJY|1VDs^P zK?s9vQ!paVU5dU0M}kY@kpUBh*rK3^(0$)(*9pJ`_|BO^S&OkxaEW*zugL;%fsFD< zNJ20wE-Wk}eqD+ugnw{F$Y&1hW@sQK1F0>{&oX`F1Fz z5MnOHRDwf+1pNgu$*f(SA_N$Vu|*(+Kzum7fP-0fD6|t;4zm_G5N|HU(S+xhVu>Lk zCD^KvL9`hQ7sL?uF2(VL7mKk>P@aP9QG6!6yBEq49tY@U#~_x4*UVHvCNR2JUJ^qF z>lfq*V;5Sw?)qYjt!IKJMb1@X!xYQE0-*$fORu{Si6ZOjA`sABc0hqN#nz%&N%?pA z$sk1xy5v^~tuDUv0wln_Ek!{kK=G|-K@9*!`%}~+_+4rv1myzjyq6>h^aPT%l!O$) zk?m!|LyN6qAq7BowygkzsdcNEree!y+Pnf0ms;Y2FBe*h0VIpRN)90fV(aSO5i>5e zzyf;9t$hI%V(V1QCoH;^85{m2F&?OyaU{`s~6klUm5ZA!OIm_)KXv^l%7}1wy?@2ww-O zYA^`Y1M*o0m`0?U*Y%4ML=l>m0|~PP{l0eSPKh-rh7&>x30-PJbHP??uuz=;Fp!u6YOuZ%2u(}g3DYK} z!30)GsZAh~(rR9)LmZlx91<)|N`nLulYA=hBCt(e+=P`ARi83tjqqwP#n?oUnv{AF z)#^Xe~Z^} zvZJ?+@@Z3d!sDU6&Ja9t6Hj3;BfWSXihFw5NQB4sAL}~9y*;YsIaW2ZfcZ4ovv`3MO^-hd0${I)mx9SO_N4P{O)6t}Sd&bK4~@Q!<#RqV$)}|U zjDl(Db>%RcY&LvdlTC^rhW9|(uoduSCYuW{G33)?P2%L5Y)E`q6HSbtfQdBO5%3-+ zn-VV);%T!nce6*mB0~2Rd6^^vJ?t=V4v%`&Y>%)2-@jCR zy1^oKRcq>i2{a7Ng=_0@2z}V|sb+-pi{XiR)EJAcY(N)XyUwFPYSXtJeoQm@I35of zE~#9-z!QR?3b|aMjSOPVdT_IR`h^1pU;zl0G>lbZLX*I8p1~38aK)s!b_GYr{ zvI<^$%BwEzL$a#qw*;Oyq%Y+NmRz#tfdOT}gfWjamz%uNzvOel;tMtg)TFZo~ z?`|srE{I~%g$)KRC5EL-N+^Y;diI$LS}$maB$D=s#F}2w6rStaBa*#q zM2RBSv`D5^9~2_ctx7E@G(}e0tks^PcA52Kr4Yizto0;lho~(jbbe7UM@?g@B|=pI zG%414gb9kuVI{2J=K(nxN~Fz_(>ntugs75$lML8p*Cmv(=N}?Ws1jR2H4cPJ<0}I6 z{qXq`uo%Y53K%G08G_Oh=pG?m3OF5$E3oN{1OpM6hZG?ucoi2YFJgNV2s7ee2Xs$a zrOXa6>W55Rp~DQ=cZB1Kehulq*ZZEOBuDRt@L+@D5LY7EE|3MQ#B!PaOb?=LXb(=K_i>3~(8_ z+^kKUcEBv1;8`>s0(GLb_p5nja%OciGn?#SxlG+Y2)7~mlETmhGH z#L@!Hi=l3n1cwZ36%DtS`PValmydK9|7?@wiYQ{kUm zt2NP6vto`(*|aTG?EtK~J3uj1Bn}8HK2`5eh<$UR-b&{e*Sm4=?_hCLk0Rg#mD)+# z2CIi3qTmUk+Hr6I#O#MJMZg&7xBv-p_AUSlqTmCy@$NaK4hRQhhX^xXX5b7Q0dIMO zg>Y~HUNyi=hPVk+2LNiE?lr)35O4&=+2J{8*8xGfUB`Gh0Sx$e!8jiW00EG20Im)I zVL`wFbDZNG1aS7jK)!Vf4gk@?z!H+GOv7|R!6s}C3~(7!6-|R@LpxyL11>SZL@;my zs%gXoxCwF;$L7+*V} zkSfg(J~+9Lf5N480dx&%6}!k@Z8HuED~d%Rd?Kz zjTCB8pQud2*wiEg)vR&d2K3%3S+~KeK+g*TsBRqC!C}h|&0uLYr01bRO%z8MAwgSM zxy1@|VZ>J}DFx0m{KwhYBLmn5kch{WI5Q}9ivvnxZD2z(_QqRC zI6?+d!B8EwS6hj25ba=N2Vyc?SDlATuXKi6u+@@X&6X2nl8k~_7S_PUZvsS?(27?usiSF7?}*NGKIx33>Cl48N=wDl*o#%Nyx|X*birB{$MR_Glu>`i_XV zHrg5J;FmOox7sS&tt7xfhM$wvSg%jUjr1h4GtfhAHdKqgZ8`;IUwuC(0&RI2w- zQPptzhNV*{nc?KWriWkVc|{h~TSnTHzK58kk1mGR_?iF{otZNHDi)Lk9=QiX<<9uH zE%s|-w}^nO36}xAnPOxEA@rs3pg&k0SFZW$<$eV2!aXw0_RLCm#2X1%6ip3>g$*(3 zB~3V#ul+MNG>c9sd{YfmysMm`Y0fJvOqjMtW7((dg z3=))u7#9Jt4~#)ve%y>v>e4Yql(CBeiws%ejxl9TQK(3mLYK!a52EoDCCbnzBEd*b zMKM7*?0bK7UoGJ<`E4_Ql>lFStUJGzp!oS*P9H9SDEzpS@Il9);Uw<=s!f3p6WZ4CTo&WU9#?no%6iMxP=9u580#RRa-d7$3Sb7}Gy^|D!gS^D; z2&%3Wlul6nc<}C5PXq;4oa98txyO)5cxcA6$`(E@7nLF5diuFRlS|48Qk?zJR@v01 zR?f^a_d_m|d>S7e(GI1%JCuWCTXY7R_RYl2njqP1aU0`7JqZobY?#WsD|-vLOX2WY{_3;ZL2Q-Q_BAitpNL4RWH2LR$KXb5oT!02P>FZC~5i36!Sk6*G# z9^iZ{&tI|0=r$Hq!oEY~DhIFhk_Wlq;UljQVR-_R@_|Y!w50X?fb7M~^G8$H<$Rvt zWGD|`v>YH>2uuc)t$|COc zxT#(yD@HgmTi%u{SUh5=F??00{83|G9;Agrh!j0R$>&#xp>#g{ zk=~RTcR zwGyaGr$q^JP0f!UF)tc$Z46TaDx???+| zLK6$wYm+YI9C&u1DFXX3o@bje`1KqH0YnRU1qA4XZ2Co6h=gD^V?MovliUcX2n}Yv zkfysaNg$aCnexneb_UE&{g8^Nv?Zi~fShVF5m3L#MXK@wbh5E(-G(fWb%t-AC5XF6 zSfXuo5>svj_we5S+wo%uO*$ z&gYDw;)wEO+~t-*Oy%7tiOVc!5eN}F%t<-N)d)?LKhP<2Pa*3*a1H`+lAq>XiB!?vziJC;o;pLF@45G@~HvoBLIRuDJWC(Gj zI`0tnrL9P;2Ow^1R)ICt%NSn^O$rtuBW>Dm20fk}QF1>a%yBc0@OW0ex{qA7Ddccv z)NU^5YxUT985Fk-+gX%%$}m4Jb;;R5#m5rNN#*z#NQ}J?-ksoE?({PatrvH-I&-&qI$*^e>I$1v?$=N%{{fEnnH&|At?{KeDyCn0D79U zvj%r~Tt`g*68gEhXPo5s433$>@cvd51id!^Ue2qrq+KK2Na_dIxbdg3hq~cgTh!#x zrW@QeYJqww0rPK-?Vp-Ha0(1vIbAe#*;?jndx!$2`lK(&I3wg@;DDl6qFFh1B~ta? z!L(jy<;yLI7kYcmsUUBfe=>H5a%^<=DCkl&#f2CN)dB?|ECEi^hf6~KOoo(HFieta zjt!F$x-zg4ze-;H2=-f325A9q{H)Oi~vDtX8w9Z5O zSzk@#%b$P4eM&$V1VijCANyu(J;s;JiFf_F2U$R$rOknINw$rI*3ay}0$j4BpxSF` zZ{8tX>!(&MMa?TnQl?%9WQcH8(E<#WPH(5#ZfS_oy@kJ*na)Aeez0@UtH76H*V3Sa z{PIDPdvLg-FV#Ov-Z({~TJcYzcL;X$4CzPuc+hRXy9s5IEpLfaUR*9b1?JTDq8WGu z!JG&WzSL>CBn=05*FQLyAfH+#9F6=*aT!;oSF7_nrfF=c_b>0q?R^=a`4vS;2>@|= zWgpk#zV(<~+?*Dm@tOW&3bu6l8p%ZhyWCthv&D<#DmmYb(};#YngpQr)qP)2-)FY81Se`eOqy5s8;CIf z<|H6XK)B|!fWE!B6fN=IkKHbiTgZfZIZ-mu6Rf3BDT1sk(0d?z+98ri)9b}hG>U)_ znaQV6vp^#?o#u|cq6?J|G325a9xRhZQjj)VGHC!x9FeR$?zQ6gJ1M#H{?O|a!l{oa z-;(3aKySzaajW>K+@B+*C0H}JgV{5VzSzp-Q&Q;a4Z+AU_(X@YevwKC5=Bu^w7{Po z`X`x6T{wy%n7Qz~|H~3i%c3$p0t*wZ&t3ABCU`nR{GalUrBn|lX81zW&B)>lbI~WZ9HV8vn#DSfcBa?V26TrlZJwB|27U0O>9z8S4zi069SyP!lO%w{Tm)U2Q2g z#M53lK>6!#v6_cK4x0H^PJqY(8>e6$0`sZsU_DK)9_3nzmPMbjYeWvb15{Z_}3XKmZ>#2Ol=)jrEN1 zaGR2|wp7N3*re^prjUg-=Bt%*>=^Vi2D#6TdI&IzO;IVp&+N=r*#Ty{x`z~Hs9Gbb zo3qZ2X(0O{P7}PIHEUJ4+5J|23ZS?HT~d3nsL~z3Wze_7Ol_DPob1m$!kPf(=82v= zl5X&3WZw)?`#}h>+E`~*=z=VHQEj;XqE_up&-#xDxvRI#wO7x)d+`*(mB!CR3>hsg zg+Mb8sbz2A0p3JoD}2iWBfhKf&!(Lgxvo!u z>vvQ7oSL=YxDY)&ARX}q7YAMv%dzQwY4dzO_Suj6W$A3J2eW83G@y&Z?z{Faoo<;o z&?f)qZ4-+6ZRh76Pb^l1hyPnsv;1O*^aCbC(c z)Iz-FIGO$EyhSvDXk1MQ>})p}WMHs-9i%97r|`QPKu_msv{j*eQFCkwDZgv#fr(T@lH zH`0B`^+^E~mUa8Awm=fnECIcs^mkE7!(`-qzWN(Czul9kE&LFSutR*=UWIFZ&ha{m zBo4g2(8H)X1*Lmsm!HB$T-y_+(VG)JL9Ye3jE7S6$DR&Qp$<@EPo;+(^Pt$Dl9D+! z)lC4$`^utg*F$JY^}hEGtV)heLGK3J-6>PTN05d?8=2eFzyraB0JJRBjD0k3Im&UZwLaYJQPMjJd3s%nl3-&xvK*>f=28`av27tsh)H%!oHCBviT9bw( zZjv0!!Zosf6FT)G2$~WYrZ`D6o1&j$37)r(3`_1g{lql13*omsdFIY92NBGR#Ij6j zxJZMTF)Z9B;e!_dqGwyOcPY^>t0vgqdpvCjS0&$S`;^$0iQ}f7uN()ait>JWh1%Le zuFXM-uq37~*@@+h@5>U0@>h7B@`Q5l=%K^nWUTaCjs<Erli2 zCDqu~|DuH0Iq*bu-Na<|T7pQ~?zYQRnnr8xTV2P<^BS6PLMFh^w7+k}f7)&r-pdvU zY&xRHglmLuPyq&SSFdLm?*NpMK$i#~OV^Ex8Sa8`{d9(TtWBP~3ofMs31SawkGaSg zc<^ihVQ!ia6R6uU2c}llLK-#s>}a^XVc&BlAJPpP*&OoZeUzD-LCndKfeGFX+iU^% z|3RQ>#xVL}*8LkGKSf*`5uzhh;^7!-DP`|FW*F*bX(Y@aMQce8#!w{=VFX{c(>?#f zO%`4^hNP#t^JpL`>xX|CF{bta2cpV#Z{M513lDEmx{!@-qo;4Urr3=oB*TP{q{;|s zpsYpbXQ7nBVqP?c7*t(;`!zuH;^SLpQg8uuaBV;|nZLPcT)T%t+T%LzgT+kGAOEZ3qlnDp2#q1<95)>09M2wNJ5wsv zTEp3{6|=B{)@uadl-8N%jiV*qO3+nYzZ+cs;@=t$QXioyMPx4s<_s=gFE`tqqab+Z zD!lPsZN$$WW9iKC_!{U+r<>}FUE;+m)aPio7pA<3-mD0!FdSU2&O6epI^C&fO(TeO zrp>1ZjcWUZ1S`?pgO6aGVj%EB+&kh`@c+t&UL?x_NY**K%4-F$t6+J*%DU+{Z@Cs4 zAlXz?s;@LoueB8<_ZXU)>zG_|{%!pXY3J@}% zR&5^idQigkEW&_v4GRsnjvJLf*G=XXV{OUed?-^yf!T!jrz|m4UgpVx%}PU{D_ip# zR)(l3$N{(`YoqeqY{hO{kNS>f-B4_S--|+M9uG>2v&0aj(+79!^jTF4IxIt1pEP>l z1?sdsju%6|LdZ3V%=g>wcD7S9-<1?lsQ^8>6wZjEf&2jWr`9Vm70;LyyFikLnz3QZ zk&+Tn2!u5rvy?j5OqUf0F1^i2wy_@89KZ#8E|l@%r13~59HCavtX{p8V-n(9DW?#} zQBX~O4qzp~k|#F1tXPnNv3L_E^>xx9^ln@ql02Df$lq9DBcCRzuZm6h~aua31G;YNpEnVOxE8RAq zL?-kd(uJIf2P1?yWx9*Gsi~4Y>%1T_tI_-c8@tOpO{balxzkeJZW8uLXd`4y zvr7!ot2DVPPv6c)4P&!F*)z*;@p_<`-N5 zsOwQtXGK{|iF|~>{ggY1;W5h|sWU(oxAJp^oD8fB6!W5Et@W`4u#hsISuQE?l(}iJ zs-4Xjx#e=gn74ho-pw`Wqjv*EZ7X^}K$c$Bt828!0@}{8W@}BzaD{0L{B%5841k9e zMj;MifyJUymQ-LrA==|F;l>l}2ZV;uNrLk}#9&l_shlH0Q*IGmIx>eA)RM_GL$yi3 zsSwRumQ-PH8z&|47f~UFwMgg0lym1h?0l!JPQcfzn~Jjt%qPOL3EMXA>niJ;^uoJP zgw6U_!jukf)B=lnA!XEk91-96D_Ybh{2p%^4IhjOPz=J9fN4?E{fyz$B7bCY>`q}c z$u1On!k!Fz<&kb{i>Zda24zDBh8l9xE^sq0qzn%~06Z=)34@3f2sl7-)L{T}FEVPC zbVZ0_4edlBLM;TcHvAF!1)&NJM}>_ChsEvB0|A~84g4Ea<7^KA*Mn--Y*-ZcTMaF9 z_eQ`}(Y&<;a?KB#c3J;)uvI;(m@P&LxGkK)y0u`RMT21u2e`pE9YBD|;v8Ll$PRJ!}vZ`b{vMtTRyz&X>M)%A(*zi&W+dt5jbg zvnNalGK4p)Dd0aTfZCJ2B$bI~8Hr&<@kRq{q*qyvdQpIyg+OJ)Rzx#0$E6rn7fL6Y zsYHO71P(FxX`y!v8Qm>S+{)TUvZw?2-u8^JNd>D4akBeI^X0CI!xsbVj+WUx08+~4 zE*pbLUu_6KI8&#U*Qx*@8aKrdvJz0QF+$ZWE`W(cWle&pG3M}S!Rl#LN#O+!Q?9fG zap&lXH668Ag7_HJFHdUeA5_&Q!%u*sY31yoBl=&J_On0(V21<1;f2*hmO^-qvzFTE zrwe!iYr@+EOR|Il)u^ob0aSbysDyq-FcN^$Qcx{&07?)W7%prg1*@j^Pav*HnkCJI zqM;_VS+lu`t$c)#veeWW)EymQ+O7J}Oad28xhUW!ydA8oN|RpO)OCdf5a2Y- z)Dj%uqPSgwAbb3je@Tw--EOFm*zVoQo7Q#INa~&sf2kqd$*^j-U}eF=&iQU8S|RWv zgZ9Ry3`y;UiRyQ-PqQ>L5q@*9%^Ji$G=Ubd{U|0=%6dI0MN^~GP?(P;)JT|fq;>JE za`5GK&nZPHflLU*M0aeDRT7^`JsCj=;|c{~ip*CRl*!r&0*Lzmipah!DPr^-V300i ztPWGqZ`;YJ=3kK)@*rSkAmjsg_u+)s(%X`&a43KK{eT9xyp0eg155BhUH+V zvdd$JgzZ8f*=MZ*?YnN$y63P7oyrJu#sWSyX7UXB>xcrie=;t~s+RJnk_omDxE^?E zdlka5@)Ryf^A%uugv+=QtGy)XT@pg_KtMnqNHoS9j*+WIdy%5*@75U;a=(fygrMnr zLA6+D)iOp}li(rWh9jmD{~yfU?Q8c=tc2kOX*Pc+vJcb%Dua^h{rl=f{oWR~ouF64PvLP(lTbNbZZ| z0+>DLsZ#Xv==*mv;rO~2pmC}N(4ljaUvf%72ugw&B29$9y!3UX?>XnS@gw}nU=|d= zFChnlgNF$TNieDu6NkAJRAXudl6v$Le5qOHzc2slDr3cb`b;};Gf{*86tMkbeV!!> zZ(yc4jw)cHDpw1az(Rhva_7`#Y9Ei9+1lA^idPS5)Zji>o#E=-Wcx-eIJui}Q}HI! zqYzg9D=dG7UBg1{gv&%S#aLwUPSAhV)1ysk_v#;~7-aG>qiQQ6L0?GOE83yum>0xy z!=I5mn>u@bDQ&4u+Nd(90p?##Lv#tD9oOOG8(I$AV)mHhgu5t!JM6npRDW|Bz{Z@G zy#2p1&s+$94~QR@oVfzh2d0xEA`G`VB6^2^%qh$#L9?_}_P0jxh_008>ZVGFEK_h$ zfN?GswY?t)55Ymshd&2)Fc;ixVJSx;NehTE9WbF_s;>RAUBxP(l0Ev6l#f}vS;Bkq z>Ye*qkE?v8_-v)WauvGvwnmC%dl!=<1mpMa5sID=BOJ?Akp%_#5i%5{!Zd<1x3;cc zbera@SrOH^6*zW3AD$a;sAo+fWx5kZo&0 zO^P8T3%=QVexD+}_Ld7sHrLh#YXy`x=C+k;EQxrn!#=A(ag+=lQSTV?;tq)94CReQ z#kC3CNYlFbqyCcqY%E6b67(96eiOHAd}(29Y4I#9d0T8yL>FWpIp_JhFDEr$M}sFlNHw-Q}QPQapeRW#!k z34MYBVRqdW&ip%EB}e()D3frAm=@7AxzQ58(zC@RF8d=8YY^{~C#|DmgTIRz7Ii&4 zH4u2n@fDY01(zpN!>e5IdFMN+L+PnOTg8k~kS2##S2>;?5lBx$Qc_T82%@`X4)Nn1 z4S_{;{tYp*-X;HK3-sYu#=YW^_ku_QlG&y(0z4#7BkFP{dQX8Z_5nRF6Ckrp8abW_7bSh`234q@0Q|4+Fh115;F0TNDJads%4?#QFob8eRgA< z0sLfQaX_(xGA6x2LC#qqLQT7yJHI0&0-?JK1Zm;FgUe_Pr2$CAdh%Y%R7V!Hjewv7 zF%qh2ZEF&(7di<@sR;AYl@ebuN({obDiXIAOZI_c`<>`w3Ip*zay|Ar@gcq{j{-d_ z&D}0a${tF;a#1oVa61-!uySXm{6g*ggR2z3G1@uAl9cBha6t)6TLPul9?`g&No9Da zzXlZIor=OhPcXM5GSSM}D-T>mh|W0lHb!%iOmfX>Ye1rvlBJXAKyTCCvm*jm({u}g?#!AUed z%}1f7P@y}VW)dGmp<_Y+NFIeUMBy;;mZC7KBWuq*WAkZWnN0$t(dLlmO<_^nORbfA zV8+ww=M_e8*Lm2p11{P$BXY$;Va7*_+OBnN))0p{6fv-i4dnt+L5|zV>i7~*5-FBy zP-f~WPNOY~TI3c7wJ0gzLNrz}hLirmP8t(hh<(H7+_|H5d0x(Rv}fG?fJ#EhhzIvsrVi?@6dwmeuMvc zYOT_ROl%%hf5#l4>D4R9MXOseex!kvBVF=IU6yGaiJ(`X`_5GW5i+#LX(%=eAJZ;Z zI(2-BkjoZ|PVb-vQ|qnohy{-%nDPKvZ_ZptuINP|QUf!`C2iz z2+$rQLO2t%`e+dR&mta3d?mA=-!zthC9U2)|A#)-rb3kQ-aJ@7W!j|fQ)0-VY{XSW zor+GF6gPcVF!-#WdxaJ2wSGv@0YHl%H}p%v?be^3j|I823Y*h#tsSmaeazc{v<0sQ zTfD-?xsqru9GR+J4Nn1l{g4i&r=P;jid0I(^dNjsN!eLJo7ASCSwr3^LhJ4TCPFEE;6lxYBwVE07YaahCK%EG6lqnS%Qks(gd;k6oM)!G&!UjNhVp-1zC9Tt#CY%8+!C zS@)f)pJ_`-m|#+RPbri+T+-wv7Z^M*Ngh39W0-I);52YiSw_5>ftJSkzrj(dvrzpP zrD93gmI=4iP-~1lHSESQgj0+%C`eioOOD82Oa`w810B=Ij-Y}pW0|>fw=I~@Ac9hP z_?NJG1}fQ5Wi%oVegOcX5GXxQlO8hjBq9(GV6_{CpA`^cOQ8qUqH5VWJ^sTbr|xpE z@Q%2rHl^dn;1Y|h5{(CJAp560&$n%L$H@M*j80Y)>(PWh)D(6ph8JXKZXV%u!TCgZ z%ZaJ62M!5hAuTIw0C6^FFz0)`zcKq0%c}tZ+BJ`1D?&;jDB6;9_TKzDtD@my zF!0aqvZRDS-Gk;IbjTmmHNq51_;K+}$zc@D71EPO=`aIHN2*LEY_$r_=%!S$Y&Eeg z11wSZC?lQ=tnhkP{dZ17BMb1r&5B7xjb}Q!;{oeC8=n4H`$67!VviYi*#Xo_=IN#n z7f_nkwUIAat8SEJEQ!1uXV~U8#$o+ya*6Tns@R!~V?KWwjbc6JA>-aYb_w#IV};|) zFbs_KhnWG}#FZihmKaib9K#?H@F*;>MJj^b#!-_FgBcvxn^*?s!@m%)0uo7u4mSdo z>h<6*vR>0QC_RQV1eNDO%VX84SjLniD>%B?P&O}N`AHAO92gUbuhQ&TF{=g`ecgVE zoeVMHaXO0g{u{gv;t!6B@kK*WAWZgm1v-$#^Crfabo{XAS*;lT#Ws+CQ3c zaOmk&Q0;-E3Ydm#5nq627(UV9!PC+NC-W+5@yMS$1(agNiH2IIvD0U9dPZi)c*gNB znL_De&Lb6^@30=zC~5{OK-H?qgCqdI8{{qytCHT(SYIlD4o#p!_^eVlsUqA^8$U4G z?VO@=c}uv;rZCTje=V#Q@6kKm*&J<#`rd*IWiXIQ7>Il38pmo6m;}RMAC092?e|IX zy*j77-U30OPN|ODR7R1(wX?Fzs>~mexGC;wZZ(Q3bs<2|`4BacgI*>hIbMqZ`yYR- zJLSt|zE#miQfC{!1@@H4voHPpP$^$ehtQeQGp?OCAfi5Z0{+$69~Ym2Nw<3DQU8@X z@rIn*SY`7Dy`!bVGlX(P+*PyVA+nh7$MA=yu0*EJ6d5vnjR-;po9xB6gJmK?6VMT+ z&e8pI4s&4=4qGWCNKwOHNw*vknY?U=2pu_JYi`E(ze0qY%0?C z9tE5Yd(hwi^eM(*F#wyE2;OK(RN#N@FLsH8c+uNN_Hs7sYwVBQ8Fw+VbHw_54u|m~7x&ca+Duc?=wGnKK0{6W z1EL}4#nGS?AVo6S>}jipmMCYoAQJBE5=CqSuUAW4aTf2#91)fXEVm}2y%A-}(_&v; zP*El(QHi=bO&KfU=m{pEKr`5bonBtjne%5_KaS8xpTYoV-@PgopV;QmXk$O+lht9iAF6D1sdKEvWW2*a{#_lbgl z@~7&-YlPbOW?O88v|UpKxz4M566n;?DVpvaHqy}aJKQ#ncRA!7a}Df~1@>Ks5Og~o z7a!a}2ysbOi_JL%5511*yRle&l3Zj!=?7cmx9b@Cw&W-^PP3eFK-kCfZ7eA%7J+bJ_tue`Hr!x`v z8%D!gEk>wUOdZ{aXW|%jux=bbK>ueE_imJ!lL8WN`GH6R$|w_^2WJpLwBf{ZnX85o zrT({mrUV-iBLWYdv5*f+a_PieEr3NXlT!iIKIz0;qd7>>P?Gg$ zUC1el3LjpweYId6wedKDL!hC!=>X%j#RUzu1p)__u?Y`Y9c@vRDbuon1L#Z#7kMy& z*b{L;L!Yr{p(-6{Yq;(f=>JK;qe25U5$m1Cz&ZpEXktx>KdJXSWG28F&p@E(XootS zc$Adm^E>nSahy=Hk4bK&Zs#A=#=&3@Yw$xm+$RuvOg*o02iPHYJx|i~@G0QP4C(?W zznSD|lNoh}#&e@3GDA)ODFh9(@=O0nJLz3c8znHNGaO7e4vx2j<=f{WN)4dr*-Xg~ zya7VYEbP2zbGe*gr~_-U5FK*u337qsym zN${GZ*~yV<%AXxB`uX2^h*@A$Y9juRXMdHDzHopfqGbUJra0+<1txb1GmfNjKli9k zyzDQTBF{OI6nF}7O+E!;pfJ2pPoAfOB7QbXGgQH_webl>mlJ@Jo#8-~H5TCsab}`( z#TtjpS~mg+_rNtSyOCu9*-FpWZJ;60MFysZw8xCrhOFExD4;h<;LB>b_*{A zxTlv2rDWj({2w{!wA2ppW~Q4!IAvUsUt3-p1WKglI}qApd%zPsAek%)=!UxmGfNOY zXMGdkl1e?j{tgF%aDx{PdX;yRiS9{IkD)#%UmeVw=Qu)JWoJE=f>YzLdP@nyH3GMU=JsjQ#8b!P1>R-TGy*}6FC&-*2k%Eo^> zyoeHwI=AMNg{|g@3lq;Xp*B$)>Pt)?n0@pux(kJAp{o?EM_`>yf*9eMRVI)yle3O+ z3nkKkH3K^LdsC7eI~hPI6@k*!`yBQk{y+O;+H>X$iqL>ng01q1bLbp?u6T;LPo1ny zk`n|YoY3MUa$}}z@#h1|O8|OLfF~w>Gh8(%%zKkQnXWEradn46kO2snp4O;B+{a9d zOqmy`c6p0BMhHQ~BwR~@oHcn5!zhkmxtD4h9fAc(bRUq4MW=YJlsqBnff5>$(Ug`q zY?C!X(O4ljY?C#7(Hzs}2t{b<=a4s!(P>Z|nURD%92ez&8#lqhzisWMB!~(}SnvtS zCn;;cx&`%x~h;xoxxV5|eC- zeHCLE{(>@N)h9}*y3upT!%tDPb|O5Hy6vRsu;e3Zt<95BVzS__ zNHer%B3*}J5&!Jb(0)E*Cxn|GxZ=MhUQ|=(TH*+}85|xT;yU@Wexi_{iSaGLK~)Ce zfR3NO4e~x3waoAUp@J1QLDmsad`4c`BA>{C)$Te_LC=Cp32jjPO=ZD9h7MTsllK)E zY2G~jxZ=Z2B&)1ZIK(Qe;@&1@tzV^XWkwHpDx;*StG+seiE0aR?1ru6%ED!W#@=GK z^3rj2`h_e@@aQM z#v_!b653{XyIme$XHY&F`516vRAMXWT^<;JSPoPr>{wJ2D|sRcx8#OEN0VY`38ftP zAjBaaF3#%`kQspK5vquLjEM;eAa?~^-hq2!f}m{g!O?7i;@I3JdLsNLtM5duRg$y` zvd}^BSJPBCz!$WgWsd(cJ}Uu#g=3qI(Q=?Gj(z8J=}w6NAj<1{nEIlj3QwM6v#fQm5ZGy#EoPZ!L ziV~=StF+3*lU72#@#STxIE0kiM0&1`gm$q=fi=L0p>#;tiQseqLU3H9AA{~;$?%P> zNKvSD%!bTtNUjkd9xqgYl%w!2Nqq|-FdXB}&Kv_!5;B`25S7ABBG7~VLkNuOVD({J zk~ph5BCMxF1Yhk3MIye{EfMmNvI-BijKo>*8_AFMgQAkY)#br#AMkFUphBeA+NF3# z_>YS9JmLJqLJ*Xofv@ye*N{>88z4`tg{nuInw8C=DFFlJx=~<(59?qz=(VoB&tbsu z)RI|94N2q-Vd!g$H&iV{r559nKB3Y&5MS;8iq-bCinM6)7JtQR`(LQ7Uu#3FLplpV zt3bZhk6I z1u~ecAHu5CV?p_!SjsB00Pddxgb^9XTovQzH1YrVIQ(4F8T# z;t}51v{D6Szuqgg(eDHI+l63thJ$kub-6l~mJwbKu;A25VIC|pj2NSXKbn-xA>oQ2M}cl1g-Ub}PJ_d@)arb* zf(!s@sLhCz+2O)hK^+e&z@ubh9-bG+2g5(diqay8955D~?+;{Ogovf)#UuM&xTWUs z*P38{fXn7y!EhN@{gq`C)nv1k-!Cl+gj9j_CeUdT3$hz8W)@~L-7dXn%)viB!mCFC&>ybM+qVgdkJP@)HK5z%407-$9M;r?rH z1HmtAaX$OE8Xii_A?)0JL7NZF){KqplNiekV*RuTqfPd=9 zDwP0*g3p5X)DjjPHPlGCob-8b*O3Lt_Q`y8s9_ze00(1bOs#@j%EB57h^X#}xB zMuH0inCnvOs|sx}(9={w#?2IB2?k}x%{4(Gu{LQ1VUt7|Nlh`(0|GqBqdl_sb}$xP zShB>*#Bs{akc51(A9y-whB}DZC#mV2V`!3o%>pG|Za*SZ(+GLKeYjmB2|F`DMmPc= zK>zkk>6}FZ{`F*1e5a5Ulh+Q0_ezo7PpRtQ|PE7Q8)5f1xm$*)9Bz(C8->WqubInU85-p z4)8`;7LFcQeG$P*_5&?cw1^aH5j}`-u>S@!h&EBcDVD}m{)0iZG4(x7?6Q8R_zX4o zr=HQ&2RIRJh~vwBpg~!a*v+ zQwxM7O2TZ5gc0aF!openOExP@p)dv9^E%HE{0cRi$pS+F?%W28VinbB(9!na1kE*J zEoFiTbzvx#f)RzgTfTgzBK=Ufm+DPrz6x_bik3o>w`v(sO_6DFhDA#uM6KHsRURw~ zt=kh+A-^+5ABw%GM%NS+{8CEGjGimY0Jjg7LwRCU-p?w80r+nrDKhw|K&d7_&Co8aPBF=WJpOzZps zqD0$fSfG?Q`qAo6VA=+PL=Tp>Ye?&?2sD4Gfd)gt(G+x=fa+l}A2vc385iWvnMvhD zi4!W3zJ@<*x>&}mV~6shz-uP8#H5zW z1WcXZQ5t1O8p&k9I2{8NyNpq!VJ@^F8{KzXk5Z*TBT5Mdr9*(9F$@(#s!t@%;Ed+> z+>9c0sNkc+v4j!WPo!}+omtr|S+;bWU@(meVk(Ye3u-K*Xdl+;ZF0nE>i{u_YD|jx zActXMMoLc8MGcPV(*%qVrWrGP#R9Yl0)*0-dIf4?+Mm{*B52H-gyxtSttpHMF@S-9 zNvBKR z{Rm8Uv)1Lg;s{>*{)%5U1NmuS3br+amqJh?R27Tp_4eJ-B^+FiDFF$XrR&HIJLLF@ zLR2q0*$dJva_0MZOaKpznQikbbqN(q=~7VgGdHdk7R|l~69&Q%KI?3{w|Krw&jP(W zX+WouBSsYuFew@R7TGg+ej6vf2W=+{Qj*}I6pfMbIk~hImr_MX4Isfg=60M{0&Fi6 zw%au(IRgb#;)20v>2dq66?rm#?QY-w0*w-RX#;gO1kc_J3?1bqB|Bu3Me;^g;b536 zwSMR1fW?Y zif7WC>hL~lT!JIsDJO${s6q1O0l@?m0_jWRpDcjFb;Uqw2TGkQ*41!uIeAhrC^S~kS?9oBhn#==XsjTd5Wnw)FUK0oLhb~@@&Y_a{J60y{8Zvz)V z!K_bCNX;)a>qw-r3Mv*4*(?SnC7xh23^PX_k?Dyo%6t@>QaclYlXc^llx3tnO~hO} zr%O(d^Cnc0*EmiasvNa0Ytx}&=*-|E6P$8{V)EpggLIfpFJuNyAYM$GjbQG8L}WrB zZzA6==JB~#)66Tc)i_rZ3WfkE^& z8rfSqq*xdw+k%qC*UaZQ-EnZV1{nzu!Y4xZZ+>Zp(1H{10zmh#zXOm(>M2I0U_*A}i0}@A+nBMT%_FQNh%^@z&>CNVUMvNU1^{j<2_p!|Kq$Ig z&>3b2Ap(Y36$2ADkqFdWjlp9DBm)9TJYx;ZEYV69|JSY=7mgux%;>r=-wOP_H@{YE zEDE9c*=c>mIPMn*SPXp?1Z$8r008HPXuz0mVoFyi&M-+)(E;Ak^GZxAW2S`{kX(~; zDa^|lkGomu7y^cMRnl{8EnMT09596&F&5!{MomlG&1mZ0M2&+(^Rz|+_6T%RvxoR=n8a&AsZJHu=$o-Ywkg~}pYT}Kb$cb6B<4Sdg&RU;wrwXdtS;pNRd&3+H2gn=XhFx&@1har9 z&p#*3u)`qBQ3QuV4#XhIUMHmpG6}jVC!$N40$5=s2y&ft2|Q;;`MPU}lP#PI;$`VJ>PidCt*hNr+x*mJU*=M1)EuX<2J76O6*Y z36`ZPB{fJ+$)E=m#;s&`BjA%}&<$1Dg=Kt4j~ASQMajzUZ~{QPrIxZuHX#H2%HVic z&atP{^QAr=Mv9e0ohFaV{Jd0pFux-EzuR zl?jy#G0KRB8an@Eq6rxLkBPbpF~M<0U;o$g3MYolS{g^dW|BIJcpN2VS)-3~na7Bh zLWU(%_IDhFkSi!df@Z*{uYjX)i3_>#n}%X^>KX>vGUc5+Zel~Gy0tJH_Z0tX)I(ne z8N^&wkcS#liUFf-a(~Mxd=}YZaB6uGC9vYcVX8Mg@e)$9h$4ota6mH%?L$c+?c&H~ zs6dm6X9c{2syIW-0)!7{12w4Dp@@gn8Hh@{2qD~$g=Llkg=`8_`RvFNmfI6hg$o& zWKUsFi1j;eClOfU;WiXb&$Gm52Ymo)3e^%y{UOLwb_onj_ekOJ>KhULJRyktm`}GQ z(*+p!vzg0`OJ+-_aztrdbrTf#P(UvHp|{&Y@5=9J;<`Vtr% zOmr=*#V9>jfzNTef8lDHCtdxruu#K4el`&c?LWSR(fv&8-C^_zKNvg-iI$Ww{!T3@ z6iVI3h^VmRm$?zRsO!B4s zD1Ej6TR~h{6)b>l7mB#gnw!Luuy+Z4NCB(=P+aLLrwOlAO}G0-N6FoOV*EN2cC)7- z3y!oVY7D-RsHj>7P?{;Dk3qia96~`0otqwdC*>Nay1;?bJ?@Eu5SVN|uRN zxx)=aFS6-UAru#$D!*oIp9v^Iw24o7;-zh~QN0jmP#Pt2pjQiMA4DzI`{t~zdlmd~ zD4+UgT7xM(+6zU=sYXOdTNH+)$mwPn%eRe9uDLM>q6?#tYh~7kMNb)8wk9=%zw~Uj z{)J!Hlqij50b+Jk0nGFuz-TVH1NgeJRSiW*CA^^8Sc8f>qJ)`-Q@JNkLJ|% z&vCW{Xv7YmD5`U91~`~PrWqHkN0q|1*RLXJIuJL-dBd-xgV%vkP3lBJUxLqZfpm-K z%(9yv2js;jdta6kZ~7WLJOy zid}R3py?kdKrA8`fkVn^eDZ(d?sSl_h47GgOClx-jo%^hNv z7S`OJ6+~X>Ou~M?e|&ej2#(K~K8da`3yfb_(vsVXrVHND*tHgT+y)eI6bTh)Z%Nh8U2J-eNoVDA% zn_`j|NMC}P)v(3!xI#syaep9iB{<rpvf^;^xwtYcRYxJJQWIjx zNPt%7IM_Bo=c&y325~q|qQ)dp8>R%J9+j0tRs|^j|1ALnhKd>X`5oFDb3wa24*PX? ze@$A=Q_$Vj@P>A(K+iEn=-*-i4#unEV@makk*Uigq6_YI8+?=Kc6HP$S2mPXijl`A z_*-YNwKS^9KZj6I=NA;J1M?#FwR};w%W=`@X~usMq(Ih6S~MwyYE}eo;T-o6OpGe* zhS7kU@{+y>K``)&g9irR(ee%lOUSybk|{>1i-0Bq?)z`2qqmKr%aILQc?Y8DS}qWT zwqV6FKq`g@SaWbdD?tM4gvAPE71%g{A^jAFuBs&~nJnOQ0xRrbHu$!cMK%~Xu7>bf zJ|}iQCvlYR+(@-dGovQ_jN&8EF|8BFVZpej+wv%8Wwe2@p7^93VhPW&kMBfnvy5GC zU=8l}hbYe1;paX2HuSP8~pfzk&_RkCLw4e;eXHjL%OX7q+2v z0YV4w;s6W6)-!Kz4FGvQq!0R2ZdpRV0Ef}+9oznvI9I&8YM%Wot}i=&wZePC&a?*b z847_cf|16=q`|bhyVxZwH27^pMhQg*qKF|3b%8B+OQ&09qIeX$TX{;}Fy%#;WguXx zF$P9Ti;_iX?>d@8b@8+QsUA+IR{y@UpKAmFEg7MB)!+*3mV-lm&=R#{sz5(#8j9Z` z+BYXaLstkd55bHWj0NGdEreb?S}s7!64)P7lSlxv%FDp85rip%1ZKJV5X7`!QNQit znSgFn&VDMouHyo4Xbr$Jn)D^(pbM9Gwh#)cQhu*M_LsEzM~>k=2KUzhfGIo2XSJTg zpnx*>S=<8y4IY(v{ma$YK>AKnK}tfn&Sr zWsG1Ei|q-gxI-M@dQ1J{Z$^71F4@@9K%jifN9Dd6O(FQOajl2!lAx!NX+!~=z3<{Y zsseo8Xb}_|r?fiH)i2TWsC@|Q*r<>wQv~r-R;jq4VvR99`)8Zz^MvPQkWD;7h?lfR z2ANt0BtZvalEy=*jp9Et_AW+(uSmS4UJ2qiS=7l;Il8{1AN)UyH;-Yky5P}V1^Q#? z{fTgZ_s4y-UrIHiA&rHETEwNXBfuA;C@gaOhCoXr&xEcJx7?w~M^q$d%M_Z&H6%rN zzYs!qt}g_DR}UjC#|hk+Yee`*azGpPR{6i_z(n>G44 zxNpHR;qfwfIRSO==k)X^%2@x8Z5tT3Tv>oCm zAA{e)jYLo`y2>o?l(GzFz)alLfyXZ<^y3<~QN;_&e}vM8Gk^Ooy!ZLJAOJO4pvW8! zO^>I37OZ#7iov=iNtC{tCydOkM?|Y)0`MJ|qbx*`jQBwXb|#B&R!2EqkKVo9#6Ic9!a?_-~-7fYGA2>i&0x9>#`3fhnT)r zoSXPI_KxfT>|q3lglSz`#*Rnw42+!P2D6opqp;WxFnbN)h0{G2{uprZ85sEgdyW>R z`7N1uVTRs$K&Ja#-C-(q<)yj_CAtHaJeF7(eymDW2kA8ehSDbF2n!-^df5#d4u2ax z+%g>SA#R`94oksp2%K&}f60|XKNpFGu>yMy7A7w*obZ{q{#wpQd6LUUpu`y#$PX4{ zfWf{r`xfcbf@J8S(=dga;;#`B(&$t`D%EAH~@T=yAbAkpN5Dnj!tblWnBj9=Aq- zhhA}ElA&~PS#gkQ4F*W~j7}tm^ckbC{`Qg>A%P@Bf(vtSB#7mg$m<=LS=+DU!d#fx z$tjZYWBLN5=EdOh4hbhSn^~}iXn3jL7MEi#&?@g#$GXLT1N(RP6*0j zW(^s7Kam;=G9=!z9F_w0+VU4Oxk7T;P;}77c#DE*3-`c(|BqMv>`DNa#G&;#Dofdr zAh@A4t@xFUKrMi1W$cDf$>hwOD_{+N#8WmMl4lTR&2%M6c*6U{!l!{KXak$CA*A&L zPoo_A2*LS28GzCC{1kuwDGeB5wxeqIIC`nU+HvJcJ=#8UB;Jh}(WYiM<6>O}{JaW)@xHtPi!20@AL zMd)-g%wmu?mveM8X}@ypzRQL%S^$vQ7GZG%BF<$v2KCQYr0&2RVT%#b$0fL8VES_*y@xJo1dh-uL=*`ZVX?DHDU=Z# zOgsSEVdGB`->OPF%Q$r#&uPTYyW9vs6wNbo3<;%?VWrI4j-jOGi(zsw6Tp?i7G}e5 z@4S0On%VbgD>exi;V=9OjDtY!(q~wL8D|S4kHNc-*YC5TH;%IcuahpY`An-CYWMTx z397&V3ZZ0NAD|0=T4C236Q9{wK*=D}sM_oX3)cZ+;(dm_$vM9`%xs{@M?krCG_)cz zJDbMPyBhk^b_i4bxv%Lgw1GYl0q7He#~FY6+t^$Sg!RJqrX!@TVN|^}(fxV!D;f-2 zSP_^ah7XNgr>9UQ+6En-4O`57ON%2C1S7l+>f` zTo#&u5UtfAKq*-nL{!pHQ6r{Xc>%Ce=$&lfrH>N2`TH4onjy=I#DzpQO-NzlKha0j z*)ss3N192au@iGMV}cS}8f;<>fV3bOG6HsCN&S1^+GJuH{q^wy2m<4Al3OhWC6xIr z6XTIe)sHuRfJ8oNBMYF_Hs6HAhhn!?X>l-&xY5kvNrJqw$;p_=IN$=f1~TVZaSZ{Y zeckD_{H(5-3S{qx0t_#u1;=gi&@hM+UM^>L?rN z^39mCycbF7gNMOFkXg-F(-pNJC=bJh%o_lByGiPHVkF!o70*FPOSVtGnUaZRi{6KzJDOgj;%*>P`Yn#f4ifo|$Za^CD zL5m%vIrxAK*>e6pgElhFqaj3>_DqU+09k%=Un%GgI9a`t#XPfBZGHzPm?wK*Oc}Fe zqEw1q&_VHjf_S^aWF`{G2{FY25i~Wj4}eS}W9p4i4)7cT9wbF~2uesXSS1Aumd2YT z7{}zU3Iw5t-gG5cl$0`%36Q@Az(zl%lwRoS*zo?ly&ttj1m~h>TL(tNCND2;Eil5? zc;?8%y&-+&^6kBrW8)o@_z<7yiWnQ{GEajK!OE#dP?bEO6q9HH2SbmF3>~OqjJCsM zW?~+D#x}Wth_g1-9A=&MrO~2;a0pJ63jhHKJE$8pK%>$la@8F?K@KPNxT7Y+h6USCxPAf(r)kMf)2=0* zprw@Jm|Fd>Q`-9Up932?kwzV{K;(%3T{hSH)W z5+)%Qg&h`{3GQ&L$Z3_QAW)x+VSm=4Cu@t@9FFJ2sTaWs#fI&X{21RpC5N}A!q5fA z>6QEp0dxY&V=(piFevoD?tf7u@TBM~5*yAb&4fyEDpi+>|BluZwc0Z@nm{{5Y)XC) zcv*M`L%BQFi#C~P{b ze6V{}r22l_p^Ni1;6`1;nM#tf>22W0!%089n1D&nCNbI*9pND}E=ieARDIxAXR~I3 z6dVT44W?}05gDJp%=bzYG7Z_MNIM@&>0Qxvu@Q`AL2(%gK+;7{!>NpMjHEHgSm5Nj zsbD?_=kycMnMMqfTL6I)DFB4$b+m{05r#KFrYF}}_SLeGb1rFS1FGS0vw0iV0rX*o zPm0lBBcV410a~@$16Y;{$A;aG)HEoqg{VmqA$>4Vhnqmr#u*lxNgarHAIT*M7Row| zr4l2i&M1sn^78_Ci*@&dPQo|=XNJTYWOcWQeH8|UJSi!0OCUU}2@eT~lQ!B!+J}X- zX^dQEg;G^O2}sFjB@o2QG+>V=pqNc2jO9%vs|e(#Q5O9ztf_zu^+*sI9>zR+#0@2e z1V1n!VXtaS+;2?+Cn%X)AYxYvTohp{X&FRfA!tGYzTKfjrc8wnmx17Lry-Ut3Ms{6 zEuj!ueQnG1f-vWm$=652%7RxuaZ=1daH9;NNe#IGLnxitVmLYp=*s3|+sccaW7aCA zoDtpX$C{=GX0h+m@JB;Sf*Y4lVpOQ%g1#BiX_m1zQ1#%6a*O0Y8`m!uu6cI9EDfS) zh5{{H31%As(;U?o+&Q%oa1F2jbGc+S3lyR2SUK~)f#s)#afthiR|6%8H6_6 zP$RHqAea;u#0QzQ+V4R2Ero>zrRT zdf4WwdDw_zYNHO9bf`K|-Ln^}M&c$vQ)=%2ePt7Q4Iu~olh`}EgfOhj1dn%(Wa*2Q z=m)GY4G1=!gZLa+j2bS+$AzCJNR%+tUx( z0|H0F<0#^M!Xk*jd4Sh`4p#j{rfe|$?iCCx9bYlr^ll=vaA?01Yr&`B*edtUKvGlD zT8nYsJRj9CrZIPJY;;g)2i#g3vwJzAN!F5vlI4gcq+Tx!LF9a^hs>AQnB*Oh0X#y5 zzY>N+c%?u9ibw}PYqth}i;i=?*0qNyMg(y{6$uTW;wZ>mj4t-A2`z2>Av?JZoriqf zd)4Uj<*j-#w9pHmjpOhaS6!}DO^?&@S-=e?BrhEqb9MTK33v@Ho3?du(6!GDz6pL`-~qj4I^`|7u62SgRv?R#&uWDC6ou{D%FkHuhA7X%7ks;~#8fY7^*b$2 zKbyF@6+%G)+YL-3@X#4bwM>lx?p$-n#fcu3Iwg?JV4j#NfGTzf+w&!y;E{U7fW?C$brur1w4l!wQbBGqZk?$qp0LT-XogKLh52gymWX0|j#f!sL7pG!H2U z7rD4Z*#+?6H3h}09h433s@JETzdDgfwdhX*yR`4)$%PP~#rl1=k#MyIObO=!zWKB= z02NKNMta_wdNA!Fif!G_&>4Xum52_rQgZjpb8QeDzAA8*1;LubKoTd^Y=qV>eN+>l z?EUwubS%D{cC38_tFCAApux$BZ>LlZ{k3<;%xzs7-5P{G6>&D4(XP=|5` z#|Aw@93!gKhBCsJ@~bGs=+X~~G|q(G7A%rIk?c9dQ*~w^7N-2C^oS|Y9S)jdryabY zV?GFlah|X-3{4N$5F?gNZ4eSiCGwz7hfZW1u83md`SlEi0h@N!P2u&ariZpr4=}kz zwxTmGL+VeD*!|_I-TGEhm(-0MXS7RT)>Aj}9x1<3A-x#UrD_?8;ovtpUx=83-eeqV zYm}qi*F2q}Qy;~sDpIW;C0#B`{xQ)KD6QR#r&gB!&ur7uD-TC=?-(-JWJa5!dP!Rf ze3Yh{N(2~ai7)2_Vyz0VF+EOzBEo0}!ZDss2dHcoPpU z6)J`j`R0iI$dg{>9EiBwfZXNN z1;m}>|7euZ59tg^xg4L1X?3MC8j4CbVd;&I@u!tewJwZ(QUda5=t#GLkhqk1;-@2J zb^sn4@w1PxVL-;TAjJu!S%{HcPKrys$N??W2?fes@1$|8RVO6MZ@pF+kg`?6aQU$(s)II?4OR1n1YI|nkOVQcjgz!RN4`yc-s0*A zmf)$=wh=a8ex_I*#~PZnz()tZR5>UpW-KOuI{wYkvwnZP#OKG;Um4V&=|2im&+Z*Vo|}YFy9<@Z;P=)~Rq--@ESW5j5j@%22l)pjYPi-+ck zE453htAx(MxMv0^+q`?-BvR1Uo+m&9nTAX~uo_AOAxEVmCONJSM*`z0b62lxmmYxe zb0GChOAw{NNjig)5>=o}zl2=- z#}Jfi|0(PP_+k30nHAs~A3pH{X;cluM_*lUd$mB$ct)H7`?I_v^OOf2&=ykikOBAy zG?|vdBOIA1ONjeFz?+QDa^ZwOqXCib7wSsYQH7Ir2&A|rP{#)dKDqsZrySSlkcGUv z6HEwdEfER@x#!6Hk<<4urXsQ6r=Ke~$9=gVs{U2}Xey%7Gglac>;qPXyftWA%u=PX z!slohA*a_jG~_n`q$<43xm6!LLg6(ByCxi0_%H>%^AHP?t1j75O)JLmJE1}lR0 zXj~pr^e;M_6^BJ4!U6BT43fg)2?i-pqh}>Ff)qHEsZ$-LIi5L7N1QdCQZ8rcTD%2G zL?D9L*rGz>3;LSJcWhsBOIbdb(GyU>{Vb<#{_ZI9{(Mb9Q}poRj&eUu{kA_r(VdDT zI$?tngc$v4*Gfh`!etT>E7s+v*q2g~G9a15LyhoTmtf!b2YWZmUY$7vw8$}-J}>DKL}Eb+Mo z{BorD_fetsdJ={@J;Xn2FtP}fVnfIVuaJX~MU5LF2mf{rKuI2CkU!0(atE)JTUx=y zh_nK!&%^`~YGm(+v{@KrcWLMjN0QLBBtUXLPZ#W#L2zN;;|0W6vPWisc4pGOfyBfh zxukp)MS}EY3sFmX=DoyNp?bjA+`MjEVk+Yx()rTtIO93FG5-jh{7jIUCl2QLp>TxO zK;vcbns%!VRX2rAnC+1;+&2HNVC@Vhoa@`cE6@o8P{L{d@GPk9AY{{%Rx)7d0f1j5 z8E^~=oJ_W%1^N^lX#f(A76d-fD``sL?)3oX#;pf-FO&+5a3HXCoqSq?eQzvK-@H2a zfOBjXLE1H8AlwKovpNQ%hj<4z%;*~TK&D$6^kP?6ZrXOf2>dspn>-RPTJSXttpK37 zHK1f-EJY-IdEmnfSblD8hiSxttW5V(g~ua$|2s~+{B#ir4Y5uCrI_G|fj2%7H$K%x zuMSXZQ0XAn)5w3id$OAI{oN!Qp@d_AqiG}Ju8u3L3&G8>nEz-OgPUMM_PqoZwsE}G zAx1H_QBo9R9%_xfACS;}IfU^8)$%Ti0gCAwPOy|&0wC1^{qEBXYwD)>;WK@N1`Kwb z_nN4orMcjOOnCFKxeii2d8sh;nbx+kLP!mrt z<5*exuhApwDSU*ZavEQ)Vusd&grH@7&`vQI+6o3+SybF=J+u@9=P9Cbt~$_A0UV}{ z#<+I}0h!8XTx-d2a1flQEyk)F0YQt5(j9TA3UIA7Fq1w5H}W7F@G$}l@G>3)2Mi<} za3Ci)HNA!sMmP}e8=8jZhNOv!tFjb+XqhmS`pgFuO{hMgmt3Kbh6ph{wkAnt3nfyD$tGuJ}kiC zL0S>l#oX&fS`pX8M~De?wUA7GR0cEAH^dm4rBKlr9Y2Id5JVrx^l)^XOw`?643miP zGgJHqrD}6#rq#g8c#2%^>J_UiV+PGgZs6rE%}E~MV2PTSQ-P3Ji7t0BiHId5frupO znZ*VhA(Tba;aZO1S%^6#7%=imRCfT&F-C?u$%rE@fkV;wv$GMLqXRyMX)#5wOa7=x z3u}n@Vzb&NaIg_B>@pCnkX136G(W8N>f0m9F)$ipgnk&TAXuy;*sOH3+GHFju!e^7 zHH`#%B(tkR6r>It@|2$}v857O+anc_m`YNik%owvyG27H=g4m*DNx8qK~TuIM_{u> zLn6%=;>{Hdi!^-+*9$FIWJaX&wSa1NUdvP}wSba!49ivKxlc@?S!zpGusnyj>LE1~ zl`Nc=ShL$F4j?#ToPoezI3mDPB#x~rkAiZ~XpDr`u~d8!EOzGy&1N4p8OF_ADdXUr zvD&p7H766m@IWi}p$A7G?Uxr`2M0&csz&Zt2oe42dqjsJ4rD6O(*%MGgaji-w26X9 z1;QCYqhDajsLC*E;Y}V#_g$*IOw@@=u(1#;wLq@db|#HTQwZg73;X=KS#ZccL%?)B zV+x{AMSj>mL%>pdN>ZgtvWYDI15jKO4_Kn8q3msdL+)Lul#%g@kz(B=;bZE%RUnzE z0F7Z|>bq1)=-xKSqqm_9R!W_oQRu<(%Sm=22-`159{{!0C&SX`WI2OLHR`K*=BUqb5P+Ej|?Pe$4M06?LJaMN=fh6ZKZ+tP;!om zVGTSbW5{qBPWfx(>yQC>5!=EOwHkJsFBBMidX@0QwJpjBiZiA#;oPb`>T zs?D;(gG}zFPymOEFfu~q#2Fj9c3DU&t7S9(QgHbQdurtbuKd8X76*1gZw1}dj11?o z64YN-u=`YeB%!Vi`&Xh2;11Ie)uw#~D~oXO!|*+(00biGegK6e&B4ka8pyH8?W%={2YZInxkA0z(viKKiS90!0vH z4Qr(W;nE<$;t39ACoaLj2y~jlCR;+bcG(jt9xo_383}9WwTwghl!+a)i6Ws*dGrHQy#k3n`amlr>4UL;4fBjdXiJQBg`#%S<=PF-<)SXIg|$QhTX)8+ zNW>LvRl(1~tUKhEs$#L>WbzC$Z(4@wdf)*OZYkTSOXh>i8WeV(AUav1sz*?l?Hp3o z3o1T`0y<42ej2#14 zg8_58rywEyKt^P2xj*&YhY=>x-W&g7vtY8+yvSnIrC4mD@yrd7UrePCMG`GDlZT=k z5Nd`C7v+8=+i?(ryi`5}yK5YV)SX2EMzZrbvlH7x<81)hSA-1&Xz5}lU9rS9QR6r- zO4L@uHc;a1jp?K0-Lx2Rpv3Omfi%+cQ2*Os!n3bY*Tgb z9{?3cYw=zaX{eQBGTFMEQpn7oCkvCIV1xtN6VU8D1l)z;lE#{4ut^m9O+Se8XoA2tq|3HED$n92wOQJl7lP+Me#Yek~l5imuk!11@RZaxdI z957ij<_i>H5|D$GOJuXdBD7#!{<7h}2aa8hLm*y%00A*-7cgV!Ja|>XnsAHnnB9>Q z6EXiJN%x?7%Zp+>TXVHKfRc=GU@V_(jH1ZK5sA__JiK#yNuba%RMJ74!eZq~2pC`r z`DpR%lQ)E%$oPmzA9J^s&pSQiz=RSHAt)W@PwzqG${%kGvcc6CCoB|AUVQ;{9G{KeHGxXVpVzpLmrM># zt5&}ZVT|J*+{3b^k}G(Ne(yW^xH}X9U4;%D;{u%<(IDedHtqG;l94`^&I!M98+~FWQ5Flv{2FuL%J9fEW!*Tylq$0KgD_2GWbA z5iR`1=_zCmc@l#njKVNKpMPP!@3qq z62RQI&xT23gS@aUg&D7eJkedtU5cu&)J6>A15VHr=h!GSfe?7A@q!{5afgH5mzA$M zP+2XgP?RDpMMg-~_|ailOFMvI?T8W+xdlh01l(4fVzi;#i=7X-LyF?$$SVYsI7JEy z+=vIpl%0;mL$rx#nHt97zNaOomR5K?$mBbysDVbO_gB3{41QR+@>}xn+oZZrq_q;! zZEY~>f#mR6L5I0@yvGSZ8c0|-g`qWYeyLe!5zn{qrBNWMWXp>Zk(!UN0=Kc1e#_== z34SY>D!3&5F!q0hL=&30V`_ZiWEPU-Dav|qLpt3=ZRa3z<@7a6jm~sNABivr>2OfD zX!WQ+4Z1Qhxj2G~!dFI8t(?n8gSUbwzVq)U*YekduLxC0ZEH#S5p zr_PodS;bBfYC9G@E&!yQeFL{qh7Z(jk5Xu9ClaXn8g}3R2?-8)0@$&akqx*qv6fk# z0N26C2!kWojPLbwlkD%MH%v0q@W_OL4Q^a-xO$};hQn1k%bnX)jLn>a;eg9 z?lDL2_wG+ZyjzoND|L)d+EZjyP!)*2484k;H1`mKNL)Erw?V>T5e6)r^3r{Q-1;03 zMLUxK30ZHL0fPXnv>o;_1{1Ex$d)w$V@&e%&>@;W7J=_g>XOXD8fiS9-dTD8-?ETxE&?^EY z-@u;8N&2SB@YK2^IWWc57>p6Ur@G082$k4@bF(%&WO>^QexnpAad=VH?Z=3<)hoau z;rBOL76zlV;u8SQ$U5jkdmY6Cv#5O?PZJ_@8;w21T@Q|^@hCx2pnk{Yls9>5E`Z7b zT0%{diBLDlp;Mq&lLHSxLbUY?EK*9vn-n|B5K~ErAxSAUbmLUH4P<>FZ4f#%0HI2W z5wVR_Zp<~}RA}ZJ?AU4&agUoRg6gF!wmAn>WG~o&p^40#Z2%ig>-}?egG|_VZj#(0 z@aGM{Xc{atkm*KLQ{|Mx_W+9wOPhx8mYB4#@777hutf@h{5XWj8xgt5 zXwbwi&}SW*B-X!RNNJm%a+EY}R41&h0a4OUvOrPco!3>_M@68IKpsoM4Kx5LfdHyl zBAQCJQ0bZHt7{o90eHaS|J?}+4|AxENzT#CaA37x!+Rge`tb9olb0(wO(0l|ZY<^!BO=%W6t;*2xoQ0og3FT1Z#UNqot*?9w+Net(wF}BuX5kq z^G@O$NwSn6q6z<-A+s`*@{WxVG=hk{vvzmZOs$F%m2bIKm$$bk+e!ll@IWMH)}yQ4DYQ2%Ckmq{Og30*0sz$-HF2!;7hL z$E6PPV{1uyM-diOw-Z`ZQW|39c|Mm^C~-oI39xM$C!!*SxHE2#|{N7hwPHWUf+4?Vc++genX zXkQOJHP@-GNZNGbmV1GDbUx8cN7NdYuxn3x(1)#>8Uxq81>{mZ-jeBcmdm^o-1Yo~ z)#xg#9c!yz5}o(TQ)OkT95AoFrPDJ%5rc-PkbvIz!`RLg6W_sH*czEPMSGo7h7#fh~M2@vbVp-lB_I8>5G?H~3;d;)h=DJko;gZS= z99??U=_1Dj3vvT;r*9rUwb|9-aumFMPoSDGH3|Q$jEt*I< z^udjc$3{2=xX4{-*hr=67<>%9ALcdbM6*(aKBgy%v~@64qW@mtP=w~#tkI8ZjTk)) z;nbv=B@sQ-!L^0-LF}pXd<^*D@r=!X-sa-F^f~Zp z+T%v@z}FfOnI=vc-wfa^eN=1{Y`imZ_WUw~r%`%X>X&JZ4OfjTfMx$u$3#xD4z)CW z^w82hO=C0(rFyr)c(=jN3(L!m-aJRCV<`AN#U5#Kt?~;%=C~#5gd3q=Vjd#*{%l_f zO3|=Xgy8Zlz#?YEI&I;a1Kcd~m9C(RLJc89DS|Bd$Q#!7CJ1!Fzm`1V_=pO0QDT2Y z(Iq8;+Gw0t2$9%oui=8R9K}=TLCTT%0w5Y84>4aVI#A=wWi0a|E;?BY=76 zqGD<*dMmqWHAOqNLwBOq7LjDwN)}AN+|hrt9_t~9j7O39X6x+UW$Cv_$VVMC7d&=PA1oKMs=`*URRs zvw<_t9_n|((sNV!*-#tDHj3Rj=|vMD2;H-{1#IdGAti5((n6JQ=p>S^f5*e$(6nT* zE621~o+v>h$x)_pPZ#ST1f2oN1V~F510)HojBG8}HznhVl)<*u^DfzvU-3zCxm7Z< z@=+M~yf)#ufJTa(}(fV9hiBK+3Yr`vv8kZ5JET9&E93J$NTzNO8N`Pc{Y8a`Fd?EJQR( zJv6Tq5Z`W*yTRB6!LbyO1w;+DG9uv>evase3EXiy_B$P`0R%GR7UE<%rGYv`d#T_3 zbVD2>osnI`FY&;Z!W7+o!FW3Fmy4X? zo^qL3*o9FReY>F3gj*N54Gz++&dw0h?lZR|! zt#=xJhf3ZQ)4%Yy2b}B=3>c&5S}cZYxwjQjnk;9Q5MB@R0oDmzj6bM{NFJ>Z0yi z(!;ts0~*!jfygm^aqZ{7t^!Aj*!{uRLbix-2nvYJhc}>kC<_G!Z}Ak9_0gon_Ehpm zYh>uhvvLm}F;66r23@ilEl{Y-tk0lcBoP0boh`tIyuTF&5$Ch{Y%JH3KO8|hxH+A) zrNk-%TKte-koK6k*h}$DCfC~&!5r#kiaAS?lV7O>4E2Qwtz8A&76gsmhs)wrxz}T* z=tZvbO8Pn+<4TJtS=bA?356}}|A<5YC!V3;-gTQnI-vjp<=1RRTR_h91aF7aP=69E zgRq~%C8%`F%p1kZk194jvcx*b-OzNg*fZaw;r1SQTG_7Ov0(img5TP!1(iN_6hFch z1MQcQ7$1w@@KBXZAp!^>9x?fp=xkC40-jIbam12j;<#x)J5PB=Up$uT>=!*HLg)m) z4@EnS$f;D%oC5o0srn}k)qCm0feWW>O^0UDFvhE;I z9N?cDhJcoco73!Ep+tK z=xls~)&b;6H*qThujRT>SyaC<*ew0PJ8x_X%QK_bhJj@EkLKA2@Om&+FvC*i!Q;Wh ze}b)f(+G%@69|VBikJ^bHYNAQIb4`YhvJk#K-;_T>;_Av>lL< z39R>*P!I?bcSKS)Udj$dFok5%RpYaS&ZGfkZx(^}%x%qTk0m0iC6b%$g;DWY)g_;q z=uT7eZhvE`C|@Qo9{D?UlsQF+VO*XsS!9~g0s;^m1Sh91`qqPcxeqUb?lmH$Fxm|- z2h`NjqE@akHGDkYjqB=sM=wQQ0wh)-xO8*;<{`-a2WcEHLJJ**1$Gw?I58u)gqZiQ zH@C$2cCF530|w)o;kXb+5T95@sLDc#70lV^Drt+D2X=%ozP`SXKCq17G5@*v9-dFgQ}g7+;*V=lW?&Wq2~Kkk6GXd@OZk-K-`3R;#&mv`(u`GEn+(9Mj8a4D&-yO z&aBS3l^T>oVLG5>wW%3ZSxIQd|9^%STGYsYejxx7Wc5^6X4qPmgq_+@lnjhQG|sibioIYIo&j;4cEkr3WewhQG>n{8-k^$kAO^G9 zWO7Ka-hdl1+pB!?gez&A92;3WBUTvUhQCEfii?<@q8AY*r|wn&SE+cHPq>?2udx(M z!_Jb0xYjjs!P-pFtBs&h7XG7igcDHF%?Ij=xj-5vaqFOuGsCX+aPsB=#5^}vN2k{q z^XW3{uTm0W=}8TzHSJ&YN96-OLilpu;h%Vz*o{Rg*%->wcWSn8k9|*H?!>_-pW+cQ zz(TOjs8YB`6d6@uI*2x&q5ej5f|766ooco>^}`GkMe3Im5kPWS{O3bzF}=lS3KB!r zQS+~Q4S`LJOZQ@cF@O+2tc==9z*jX^WIVmT@Dt(JdJgH8KC8wypN2$R?deB+$Dx~_ z2LHp4dWU0`wunASzFf}xakR`{@FaZ&r=CxQW8kw$>(cAQ)5zTdrKI4t9Q{`oxJb@c zxyhe3ZRchNs&I+-1%GM=V=!feSM3v-g4XvoW6ra|kp1$ONe?cHM1@B-*E-6rV4>p&hiG1!@y*g zKmk)n=mv3(#@*;6(`GYKWmNtTdYC8lc|kb9%p|*?MWZUo#CVd;y&0c&sv-Cee)1-5 z@I+7v@`=6W$94)FNKPTv4IY8BLX?q*RSsYkzEH*)A6Q~fM|5>$f~1bnZCx1|C)oBn zZ8Ov`M6f714H81q7^V5Eyr=8E!Oc(|vfxFm%r4j>nQXvXr>kWw#z&wrvB!;s)_7|@ zaqv=tat0;QsrZyHIhb2l&uZF)N}o@+U9qk6fZ5n zD5|E#dsVwCIu1{2*oMHRqH~-I>(k0aTR@_Q5hG289HB;{M@ePlV}|Bmhp>|hWOH!9 zDh{V|G^lg$R6W{t$OaSl3Rf7i%+&M-zrpm#UkmsqP6%;q6DqiLtbXs74s?wmn>hd7 z)$V0p_PwG@2(2pa@XdiN?&ur95zivoqyQThz5nZAgPikhNZgh~pfJ+PRPn)pgAxw7 zTC+|4Fd|mXUh?8#F^B@6L<%k(oMf)^tJ$MY!#0}-8N|yqPhA|gc-@}&P6as84VJF< z96&O=vkWtqI&24C-bVA|`x&4$bUv8Ez&IBbE33=%d!yB_-yo@BbVvKn`eg$%Z_T9j zo3Dl9#K@DV1xjZRVMh&ooPflBM+3xeQn62sy?f{XGtai)!*#J3hBd8nsUzwE627#} zUGU3v3dFsu`?w2xh+tsIVjmHFPOaJLynGd0HwNW1wZ}l2T(9S9E5r z=+8gw)7s!8{=s;%ptp;|yL>ZfU@*uGVVqstkvb!`Z4E|moCPNStTuyLr=bB?TlMQLK+J=%gS(-wX-6os)vnGoU8Wc{rquj*5-ir)c zYfYd$+P@cO4lc}Ei?pdB@)FCf%K%<-gexB{^9#a{$wC2;)ai&QL7Etufeah;!N7EJ zEFosxxfMh}#KD`G7EgsFBmFek-)(YPkSGdQ(%j=G#{=Ml}fA zHlu`zAMau7-Q~xMJj0+L-^fW8-3#MXwAQ{ zfR~IjJ9&FCDyH5poaL0|M+@4@X;e9n7;h{`E?Bhkh}Lb_GD6&j)eBcH*v}ZtU7sKU z`gSS|q??i7ra9(>0%%ejGUi-aQ&Dq4YMA0|$Vk80rNc=-mXdvN-(mG#0rh`!tbhy= zcqxmLNXWxtQx?(U+Kmbrh9}KQ=r3}{1LZb>1yu-4%%Xi44RSQy5O1R0%$8X8S0KPl z2eItHl7ZlcY?gMRgj!xG!3WM;nGS|2{@w~Zyq&>1UL>@;d{?c@Trlkqagu99JAGkH z)MF08Jg9cODky5Dv@-9VgAWUiE%EW2B!Q)xDZjrJWz^($AU^OV0PBGS z=75!iJJc_NxQXxP;i4ya&Ctm1>nIP7VB(8GFDBt_B#o85SsK7H1oZh^aEXa)V(kRS zqPw+?$RIq|0@A(cKDXetJSaSqMm?82iEP({CD$#?=tSjc#k4Dl?R$@F)+^e-2 z%s`#hkR0P*yCGKEce=p`4M?wluB8b985*(UhcIix%kGyi)nX=xh7J}7jTGEkPK4T!mo0d-iJlP zK)7=)$8b>iC~?dn^NcThSMCIH8Ak&E{sak@>l(Zy*>UcUIo80SH$J)xv{Q6QYsuBC zC3pda?;3hlJ@jfsS{CoRlK0F9-cyup_0DHFwPpp_H!iwEaPPeqdvUAY>ob;!$yC|6 zQSQ?TT@~y_l)LqFJ8lBYXr&bm1?}Tx&RUtS#g&!eYX_QStwTEu2h#`HzHIj(ILkwQD8OJk$-ZoYv_8~r$4L- zRfK8>MEKj37g3NLgnVl9>ZDo?`$H4wkU+QTLujUj_3oh9sG-)ZhUK_uh|U!p_+wzs z5vjN=;(F*#&;M>;SJ&e}Bp+08tpaVx3C}a@l!)pa5 z?fM#sya59kp~Fj5VH8}Oc)PI7SQpOf05h;Bdf-zU@t5zQO~#xgX`KOdric3ntrc)_ z1?R0LMoJubYmv7r=oQ+BgIG&-xlx7rAX3DH##aQ@+be(w!*p6Wza?M(k2W4i{xh|I zB1m`0w8G13D#4SRI~H;{AvR57+I~Wqf3AC+lhg8&2FC+%M6HI`6u3K}Fztfl!JKzt zJSlq!@PoMb_r1-oPy;vKVVY=Gl?3O^l+#9;9j>ao?XW#qd1aM4Wu%PxOx|vF=I)k@d4)5F|$_) zF=#F9Q_$~r(I7Y5C7@x-Y_Rwd8XbaL6f%h?I65n^Tnodh0mcJ89XM^B!ggYC0yB#FQbAN&VS5!kc-5d5KGrD2GX|Uw z^xy*%P$wsBe@To_;~Ay-`2{LgWpQf#tn?;m66PfPoqbffK)zNaXx9zz>k8Mk5WY7YkmJg?noRh;sRxxqogBeb-C~zXe5J-ifRqM zU%p3?Mi5mFq)9%a0_vKg=TO=Efq%fNy6tvp$9B0k{sDAkXE`HbFxN675E4Krl5RpG zIar=>Q-2ak7cNZC$Y#<9jsg^=RI2Q0Ke$BX{>3Tgh%>GBE_MK1gjLylz@OLM@|h~O z1q78rDx+QRwGgY{-ueIED zpUQ^ooOiYf0=|-xE6|hZ;50VG3#B@@O-Q)}VlSXjaA|{Pi2eSow zqYYo~^eV$wM0y#HcVHNk(9dp*CsI_XyLenn!%k~8SzgeciNKV|X(u3vX9*h5X*0RY z$#%dq;^z|a4TaUC9Ec3GVM)@wM%MEg3f}M;$MWI)xQ6XzF&CI_olB&(jEkGas>cIH zq!MXeC7OtmMFjeV(peQ_4_bFQ9tRpwCy20zCU01v^u6JKS=$OKbIregMcWc=RLWnf zt!)NY6#CWxH@Ipvgc@33YTVYf0SPO6(|aw59m$of3?L5CrHBfMUv?#S^u%_Vr4EoZ zd);V)i(-R&ObYRALnXsPlb-=gzbN11fY1#o?V&^iVjeVt3D9}DlsrKEkOksLA}BB< zgM`4SV{JDfF49~b6yd$aWMH63L|*{_2^JH}(a>wsWAl4WeHu$-6_a6dL*N6Jug;){ zP2dzxje?@IWT_Vvw;j&D)RE91-W)Q*gfuuk?9rh(mDP~Mk9H3^;2TY9f{@9BnA8h2 zcLI1)tZK>xosIKZz}B$d#|SSF*{h2>Ydh19){Ld#)C2Qds90 zr^bnmQUxM5Zo$gO7RQ?` zJ?&Eq62eNFMOb^uXkr@yj(4@Rww=<5^4}Zq8Jt(8G+W=h+ptc)K!~#Lh7;w5^ZWYp zo(#-&Gta5A+==P_Jq0A#6LGoE^t*~TS5d5&(T|)-NfkEB1CA{cWwv;L z2(B2^^C#3wu9ic;@FB5#{dz=3$Mj{gwUgLle?z%HY~(kg#G$v91l@noNfo^gJUj{|({7}xmra^AsJr>ox72x+#;?DobOQ!#19})kbo%glx$O71&B?)#nhw(BJe-3i6A)Zg9fX=VFK(ReS?wVk}OPma$tKzhW(a^#Cw5g zF~d$$2Ms0zy?`9lfvwhH3E5K_7-h^r;1A{y^qOu#Z*m9+1z*0DHW;kpGsMTjAm^}F z;W(RJxde9i(}e)Of^^gqLdB=*H#SagZ?o=7<;tWUS%9fsVcc^+K$@0%At~Hi-q*-1 zWNVgyNK24wBVRXhn%dTSmW?r3mO&;6_>oJ)62#_MyFX!IGWQ|aUG<4V_$Jh&A0P#BZC^=eY_$Htj z5K>g)Ol5Xk3Bn*?=FTq~_Dc&CFIlPku=;h4F zvM9egi#;5oY4*uP2AsvOOE0by06TP&~_KMO^^Epf}GrTkMk2p1V+t;-Y}p>k*eOt6tH56>ZjKNPVVy*wS| zijM+-d;i}T??Y^(A6Z-sn9@+qk`&Ao z5kz3V?CNx!tkMPMT2lH~`+9F=Txgx9W2db<{DOKdfSOkmN~8vOgOhapix7SfZ?g!t z97=m%D(Xb^7p6J6!?G3{?>^K(wUbV-r{yC5BCbiu$5j#fEKx zkBxL>EJA7aJd}V8RzTO-*f?Oa9g1U368~oRKSQ` zL(IlSj=;H!IE1g~;KrNA3c`yMXIp)yULMo+w{#8zlg;ltp8I8-i7Z<2Eb&w2*V5a#|VXV#9hkRv*C;OTm}pY*e+IK^FN?O)xfdG zE`^}ZUT?5ZFEysZZ8v95sewDx6Ji^{;LRbZv)Wvn{3-_<&2_9I=NlEgSQnW1DLE5i z?n?6;yU0aAdB9+sJoYm`MBZOb?_CeHXO5182MjX6nviXuI+W&iexUk#7mObE=U}q& zIX*K|SU3eUUCd2Ae6B(R8bc7+2GU8rkZ!;Xp#$?PBPGLKOB7*b%GT0xPlpI(bP?h` ze!{|U8j$5ZXYoPL(*gz<_n>;wT?S!++kXj`gL2I*R9pz4XNEqSBMrV19eYl8%w=1) z_h7;r9Hn{nt+1UxEB6%oxIk!Dagr6KBhG&g*N-*W5?J_FeF?sV8W z;7hF_NVehH!3cW`^vqj-!P<54vXYj}n4VuKLUh@H>tOfDn=X{Ah9RB5Xd(6)f^8<4 z$-Rk37X!y`p2uAZ0n&ZI)6AH%#!zu3VmCYv?;_x|J$J8MN;|Z)F?zk60c`T@=KdwT zm|vk?m)V6T#)$XnK4LZ%K*Mz{(m5*u4$Qe-TIl|AY+>F>#BSf>^UVxFOTmvuOoRc= z*_VW{yGBf#I@y?i827Zm)iAvrY%VRS+*-CaaD40b`A&cyeI>=b^j5V<9T-%A#~;8} z-fjQY*K*pq#mtV5Vht8vd8+u5((vJryph<_@j?)gWIYT#2Qg{0?2{EGhCyKt+(Yy) zrH{a45RK>L-ks(WpmXt_hfF5>ZkRdc=Q&Kd(U!ig<&l}A4P1&{1n>a$L6bC0tLhkA z`h1x4N#%<<-e_IM1&QH%bV6ebeYl|ltEPQ^-HOlG%DEOnBS)lGYuMxL-pDpPp}b2@ zUKQ7Tw~rtJ&*;rA#P$$}%yXDEa~_8p z96DKi5aIIxTjD{|cJvgN;sL&%=N-fBw36#A39T7fnw%LJRo~fki5V8#I0FHp1RilO z_!@e^|Fs#K7>|<;OJX~a5X(fnasG;%*-t1+HlEl7^d>UpXc1YMj|FM8XYnC3;Y98D z-ulIyQqolOh6!jGJ(^%gnry;7tzH$!+010@{OI_Lc7m?p9vhE)Kx{&sgzO_QVo=6H ziYJE~=SbNBAy1TZPwjghQs&$A30s-4$2{R-S%Ce4H#;wjvn-3(r!E)GWdc;eJd;>2 zYv*k29Mb@(GL^@+}K*nD3p7lg#1vtL25`mTQy%|pp@z0{beot#% zJE9f77FEYU<5+tn*_NuAQ$6(6+`&ED*iQsNC1|H{?clz1zEY(SCa)UPQ+_u^BPvDU z<{KBC4y1opCa|ONKbi}y&y;XlQZ!VyZRjGXv10`bNfu?3v!?bVJxa>)P0K!}0v{a= zO=Juahz$loMst{K#rksHajKSx%a4_zAD=rW67T@)T4*+;hG#Px_h-4s4*Cj@p zGjwAyjR)=_stNevTn&q)#0vKU?;lgO!k8V1IS*+@LxfT>^@7k}hVS?M1}&Y>$g z!k&E(MHthF(C03KuGIP+)X5j&^o)H=n5cJrSe^Xtu;uW^WE)OK)KJ;$lsC9V@-?RJ z8qz6WFr^spD>< zRTT=Rtx3{1m}n{MH-=Y)QiH33>qK19a#ISkjyKE%HO)4DSSI~MeB|k&<9QIt-udjB zt3gA^hC(2$O3^X#gkq?`74~>!`Ft>7WSTh$w?>V^ZLn5-C9B8(IVix`*Q% zg}4z5S(KWx09Nu8A@rO>c8xwfpH1ggzmX2M%-OVwgt^kQf3QC~C{j zG|>0%*zH0DWCyZNN(;RMKwE?)93LPxki(u>3?Iq^k8qPT*I?)ryY6r-Iu1T4Hw$(`aG}@%ciL4+n)hF|ANe>l*InU3_3M<)mW9SGf3G0cu zu5fTj9@6#Ike}rbXc|r@bllLEc4vv?538WOcqO5(cfd;OZ9Sd^FWHYIz*PN4vJ26T z{NWp{7jGV*$OHuFAjku)AU zlXK?phfxlAvz~k_ZH$ca7)uOLZW{r?5b#YvMZp3pTY?jlOycspk2UeH1IAyt4^x-c zGbhBrWxUHns&ojKw*}ORGY!L));OCC5DvzdHY2|@n0_1j^(0-e25S=C5kaFF*~5$? zXagoL#Ca5ble$n4`h}ILt&^Yr*aiX6-!~gy^>E9ZpulY6X7^i_>*?f>5>`PO{gOO;V6L)tP5-XEx%S7>tHbux=2k0F|?jD+vO)`OQ6^H@Z;*O zV00L2WHG9?;J|Q6mfxI|!H_`-Z?>~Jtz z=gb<5#~9n6(jy@Uf8_NK>KexA|0E59i0@h{i!KdVWw3Cj=7GoDGyu4!4O6mZJ~a=K z!E{)E;`5X=E0A7{+nNUr;B^7hue=jg$Bh8yk%5W0sFdJ1$YO=xk5i&W8LXGtS%yEb zw1j9}AW$gH3X(%+-^8W+czA(LIXE2&mD6Zh9o+mD@Zt!cwRT}>fvoNLO|&RioPn@k z%(L*^8btnY(ErEzQ?sgDx%3X964Zu%qq@TxYJt9c|70`2hD77%o4s&U>g9@^LvC6a zyg_1Ur1$VB@%+oDC}?|Co3-Bq+RA(MCoG4%lr$eORAi8{>rm33KpEu_LLYOJ+2eo2 z#IRDBB1{!37_gF3ASk`a24Qh(u-*i+ZAt*cCTF2@n~D4QoCGXFw9Ny22ZHH)bcv*L zF0sI(NGIq3x430I;usI(R|nyQ0&op}!Y&gm07E8m7=s{p9sO%W}h zf=U&9S`S=0>K2F@I6vbkaPfSv>1}Ca)9O}^^qMxN_Q`rgL7y}TBoHUAPUryMZ z6i*-FqWukzM50@A?ae=GqKV5bwv%^A`ing8Uah1Tus%S1FjOw9^=r#`Sn0;waOc@j z2A+(Fj#1*=Bae*!`uzaG&BMCL+5pj;bE2fAtNX%jqscOjVEzcT#>^3<0IOn@yuAi& zj`UChm^?w4WUK&NK5jY8Oe@ja9A>)QrzTy1wWHobnk`ajwsAMFLcpWpNa7wg(_F*Ri;%*)S1{YaRn7P99T&m?YVDV_uxCh$Fvj`JbnBMLC59(4pTY)(KFR(mvY+LW zER)|WRZ1-ZXA@PVoB*f#r~%O2jSM(EOzA+vX>1Y##~|Q`3;^^K`y--|#)LR%^9K(< zd^3n3hqSviqU!f_UBO)n1tHZa$vt-(ft*n*#7v z7kYO{10h4%UywmQbS{%xJ}z~G`@-u}PnwDH7)cq*gdOMcGRp=KXK{&ZFViFpI?Un+ z^ur6#jL%yjbyCv+>woB&cinuJ@!dVbSMt$xfAsoIdb;Gn)@40;-IJ6T1^}0%%YrYL z;0cn+$i1a4=tW$WVx*8~#Fg%>KABa(PdVaI^$P;{YQFGtSGs_f=TedGk6_`&<8=<`YA)QL7gNI1|S=o;SC`!+jyNoj#03y@}a75sJ9JcFyJ$H>6mf6K_M}eVC=r>As4=3YGz-N#2zv&|sm~2y^-9q~irpQ$lCC z=%}Qz(x8uJ2HlX@sD?~KD8WNLF)b-0jBL-6+zhC1o9-$ zy9bwtz8Hd^cAj>=z41C%wjig14+m-KI3q>ihIX@jv%P%|kQiZt8Dj-00H*RJp2(8p z=p2O3xF!SKyevlq0)i+)Fu_){hZs6+07vXjRs$^(24FoPRgIXAU_d)8RH7&We5v#v z`G8{aJQrCQGa0EXfG*9F!@AUtNzxV&Az`E|z=vJL>&0b&a{X zfWr*LR1o`x4V`(kzYgx)0HXTr)U$Tcnj|0PtHhVagXL|AxVsmqh6ZHo+pt@1-}rCI zlAY|0;LLU;+y_~Bsx|<#GGuAY)Ft!e^A~a0cRr|O#gpOQ9oL<=*M9uFpO5()TcrU~ ztoC)&DnpPWLoe@qk!<6Hr`3?|)ND6O%ryH>iZad>PRAl@(}YB?m@O6W4HXpL$p^np zslHRLa)o4-&0a?kn*3-dlBJ;NIaW7T#U}{@1w-Llk<3P*PFalQdyIS*_*=b!*tVti zS_r4H*(}vbC=5`pUe_oiOWnRrO&Cu8<*xri=C@(WVX~5ZV!sZGnN+_@pyOe$8d}j) z+}?eg!AYgF33RHxB3ag;m8^oS zDd0r9tr`*dC=$nREAGz@9rPfY_SZW-80&+Uc%=A{uPPqTpz?e6*x@@WF9l!SfBJFs z1fqSXnOs5lp?H)RN0k*!Rj&iB=Up*qUn>V=U<6Hgr8>Jq1tbRNFSoiuN<;uhqaIpL z*c&hmo`lE6VzvCeP3_P_$2S~IFEJhFRVHy4m1Hbyd_e#Hrzze`ZMd!gcbUz;eoY`3 z`$2eN{!#z5B5Lt?PbC0H9_u- zc+y!u07PTr%h101xLB$VMj;`g_$xM#EI{Du_^bLZKy?t6oWEd!regR;^#vx>!Oxgi zox=D#Di?j?^+6Se#T`@xvA+6T_;2bJQFig%R56PF}{lCK%3(4RuLx#CGG$XoTfJv)dK~pq#j`PK| z7UjdCC$*N%M;aq>$p7}l9nIX|A&6=qr)}ORAJu~|EEz8Ufef%Hes(EqO%CFt{306} z_C)v&dF@0R!tX6yN5F!{^Mny%x0$0I6vzkOd}YvqmO+MNG~^Itcml1Mfo(R^ZiIfI z2NHBd@fnYilZ9{;K#IW_INZe6BgK&9S@-W8C+N^~PT2orXcwE34gccA9mQ(G=fKdj zD1qSa`43P=e2%c4co+g8*O;@aBo@jj+A zFw+Mu;uxUcuD;TUCZ{k!TY>|{;>eg5_h}PJ-)KRPHlA<1O9rS84>cGw`nz=?f?W@H zy_n=}G{Bu_x(rU8DDOY7cl2 zF@Xd0xR!SsZo5LR2+%YXmj#temnSI77^?K zs{7?DfJNhv9`_KBPqT8s7fukd*Pin&q(jXNz`KyI1qSa}M}Qtc3i3MxEO}_o${Z{! z3YJtqtz}WQ z7Ah(SBe^EfX|F601hxpEhomR)orx+wm;L2>SS$#3`IG|qA@n)}4HBF17#`NIv9x-m z*Bz*xLQr@0p%?j#V{pPFLzjS&y*wkE8a;i40Sc?roCW~Ka<~<|hyvg21{JeScCY|y z38Z}k{dHZwYY@bhcOXW)(|M#F{2BA?6F=sUFFU9{f+B+;8Z^arg5cYvKQ`k<%gxu! zj;XCHs$=r_??shC7k?H~ zs@+a*b-qd=Jv?U%3io))K<>1*@1@T7c%8~59kEQGf2@g)hm7z{f9Xm$_)mRgY&(YE zvWtNaQDv=kmJt%qRzfB=A-mK$HA9O69uiMs1aKYZSpvGYISP^{35}9oPeiP+w29QT z3!{8WAgeLc00WfiMF>Q?VEPav9yy!Jrdj_+|MG|!=mQITxm1SgNSG8xc_;5g)At!A zq@YEH-?c;9y55+o$E74p7)Q-7i9!h^WS~VQ3dSHjpl$JqeYkn_JKs1KDU(Gt)Nld) zA=woU`FyO3MK2PG5y(>@8e|DnT7;Pa>^VEJq=*3S?%-qK+DnB18e}G8-lg-|s_NG} zg!CC@H1)COKo`86XaEp&l^@}@fd<%8qo28%PLz_=WZ41!orm6pfRp;+dlBZ{!hnQ{ z4Whu@f{tEgkq8#WN z3bth=a12F^>|CiRr#oG>{sXMhPUC2FH2QqEv9aM_{HK}rN}0dwXf4?W z!f)`_NOuwUN}tT10qU+EvMo!qeallbQ)TwSxa!z(pLg9#2O6dEcB?FK9Hh&gPR5~c znNsURei{s=A!ult@qUWBaoH0|{uGN-ivgoTv=8t^m;Rbr?bdZG-A#R#wZ zk3Wh*N-Q9QghikD%8?b-9=VPq-|;W|5&(c#O8z^C+K!{vvWFV{jxI$3{?o!6yd#!I z0`z$GBP#Kr64dO)2oya@8L&i30NBvLF<&C8U_P}D@(@?6GZDTBBbmIk7OiOLF_?6~ zshBo~ScI3*BW+-!DgyakuAB+WVXEGZ#p9Ceg@|S~0uNyKS3_XIR2Ze;2I}Ec{K6ypOk(5}9>>FYKeGwI^InBM>4D{|VG>=o2#q0_ zexlpKNNRf}bkzTU4Jq*PP>(hd_DfbhreDd+LZFW{qA7`aXJGPeAY`O0+(q>l%sEhL zZ2<%@vL)5Y3b_UW#)o?Vtph4mm$^ZE?RE8GXEZBH1V@0IzSJ%FT0cV$T zWsPqWZ3R(_jw^yFe8?43oo#ABqggR28MTDA%EXypkS2Er1`yzIqbm@+EapBN|U4*HoQlQyg6YrH8?N2KT_=K4@@v_u#=HSa5#{&fxAoxFxtlaCf)h z5IjJD00FYB)z(%$zo4r>^u2w~a}XMT&5~?jDI;7pQa|S+^3)K0L?+SnU4{2RSqk`l zkYzZ*>m=_Mz}GT0PwKs)^gc4Dq*)#^EhzX2DX_@qb>SLwWwVYzva@(9uE^W$cTwIi zrgOBpeyLg`oU14G2JBB{r z+9mOju~^kLwRCsWfHd^1%(oe%Ople)?xx8}WpoI3=ov=_=KDiV zUt@IkqT4xkvH{~{I?**!a!SyV+23y}$s&IVR9=S(z1jsDBBeEVEMN)KYd0D_?^>JC zLt#WH_BE?|2_XnWN{50Pp^kt!|JuXolDkZb4eikZi3P=C9^}?J4x2(_mn;6S1A+TU zlxyGl8K4Nt@+B%EAbJh+3%=oQOA?Ny5kvqdRuoqABkZ9~6+^v#f zzC%z)MOST+mi3>I$FA;Zm3~t??zKW7v0<)KF;~?eL(f~(8XQt(Vxn^|w0Dz!;G_Na z9;Tu3uIuxF07u_D=@eA1ev0dtq)65l{wP1{(bG3^*azr>DPrsxu`S2v*Zxgd%Q!qt z?$h92X>VkMJW`8Jo&cXs6gjVmj?+}xGRB>VP@m?)k1nAv`?A37rN!7BmFRzZ)6&v& z`hU4QO;D}X)f2Du1gSl}y$mW9FADN;LZ0>ca`uvymolN4SWWWzOY&4+e{JehVDE3P z`(F=szi>CZ$WK+w&5{s1-XLW}&oD`R|Q{3q83eol%8C;)q7~l2>$MpVM zTB4YZ;`Wp54I+IeXFLdBABJMPZGbB#`4X;wrm#8)V$?6SYq^gEc*G?3@OA0B%$<32 z)jX%`diu7J)>0)7m>UsA*C;nP238JnBmZYxGHUCeqixA%(=qHSp*5+q$l{5m59|Xj z&>R20wfTHP*!1gWYS@|{Lo$`RZWtizlw>Qvqt5hYjXue@V8<#W+C^|MEa{&2xeTY| zG=i_|nJ&()MRfr#^4?dDnuN7lt`}w~DI@BcO0fN$ zwam3HLF2tN_u9m#M0^PcVaFWfbA3Q;3f%E3`pVS5{{tjcKkN)gPC z2??}t3OrGczUw&J2;L}33D=ay#VIp1(vBwXNCdL*r2QA*;mJOvT4ogc0X0Dl&@V`< z0we;LzfkKv;*X5g=(K)2ci}Y-j>rU~{T)43tmX9}5XLHMi``#PWtf&rrWN$~gKDm_ ze1%DibNzEYck?Nn$uy3R7K3da1rC|4aW5AafR){QTDS+Jx^Zv1Ggm6sst|D&Tms() zgUn2m&9V|l+7R~f7K)<(`T^9Byx~(=&U>GGjt4Vtxd5_&7R>Zsc8%d1OOv(U7`x9O zqDkswX=P0=`nFJZot3JWj!xmeQUlyC=UTYv4<_AI@(Mh()6=(&aq(yup#4H9<RXhV*| zy&4cx&ql7}LJ`r7Sfr!WoohFhMv2hIOv#kPLc1;&XLA&Wj3W4(Sl5Xlbzxea?cdl5 z;`(JrOY|@neJV(O-gMV>AT`oxwzxlWhdN$9P zp!y62p<>7xZG=JvCC1rFU@+OB4)td)t9mKGIhEB{rQ~z98P8A`^kj0b>0;;GTLP*q zsZdSd^{9ldqzpsF8u^_k-D*AHmO9&WIT<@~p#tK!58wGpN= zV#jcI@(i61bM4_Ng3b4y5x~jm{AFPJ&IM^AH72^9LQJ^QQf~pkICVGr3<;*?*c87( z&jMcr-#C*prG0VG2>AEIZmFq=Ab(Cx4_)jrm;DmWc}Gk|57R})P#Jv2mjw7jWTyvX z_qPqRj61Fz6i3u1Jj@PSZQ11K@P{dEh-apjvtNW3nUQe%j86kXy*@&=a z_QcR4vfMAqh=3=Y1T5*Uu7XX6vxZ4NaI~n@@nwc>=CuU|bT&AbI$D1Gj@-X(EO3#E z1mCwogMy;~8CTh%E+A>MN)TcemZ+EmqQpsN#D0fnL|R2gs5Ufv5{jkjb%UykmE%Ix zghI-VW`JrQ3Lz2wT9eU)5WkLA%T!>irDt93W2Jh*9oajb`BsR+ZyL|mtNZxv;H6ppiaf>TMjKx$Zy#YJH=N-dDNjGL!Q!WR%urb zZ+zQX;OvlIXzrj6{RQ!NNwBM=t=8C^`7d~2FNcyrFYAES63-pn9*kKpLT!S$JPD86 z_u-{uLv=Ncu`Xi{=3AUb9@hHVmoGAUQoJq2<1I?jCLz_|@l8a;S3<^j%KT#pW^5U8 zCI$_6`KA+0+cr|mAzMRSgdW~A8YaXZTQfm%)GD9h$3JhlV)ap5Wh>FL#7mM6Sy@4G zLCI7s!cK_2j4x;<)~!@*b>+*4=ATJJUi=4J4~pCcF|n|3>ogJD@bBY=wig{En7e|?&u&k#%xjr;Y%$*05;81oMpFfbA;CGO@7}sT68*5Z< zU$n77wUMX%i4N6jrnHdsiPP_1a)&PKa63n}oo*>P3+jz%Ts&$E2Zx~lKI@f&8W4qgZ}(=y#XUS3Cv2HPk*3Zc zDvMFduxt^22^!VJlr1;v=h`~T@G}2VqpD^XQN}64#{#ebj|@rix~ZA^7t9jb)({YO z+%Qm%( zK@gP0TCVA?WKSjUmzdQ=pX|U0{v~^oC^Os6x};F6z3Z+$hkaQ>$WwQ{k7(}i$9I&x zEl7ADSweM+DDpKZ&~ZNXwr=}y<{~n*yG^qVI`95^`E0{gW)LAm`9S5x=8$tx_B?Y! z4i!?*5xL5%lpP_%e$fjL(h2MS@S$imzR=EGc~dOYX1?-dg`(RRXA}Q6odmGg6prHU zgf>);Ts&)|RD&6XTk#_Ky&(eB6TDS9~hU+ zZjiYDx|l#%8TE*6c7)`5TM0I1y~rm_kkO78R7&*ck4dLAb#2N8xjqwMhlNn+DE)S? zC)Sk)jM^KqJzCp&1UZ}I4(i&^<>Z%ooE5;8*QT6|>aB>F}qR!!_llMoz$te?Qz z2bm$lO5`MP`;;K!;!!;7iXsuVPTsaM=Wye?G#H&kuWTdT*Xm_Wxb3s{kHz8e;Q^6Y zYK@+Cxy+V$X;CB_PJ-JelDCesQV-o%Ho@g$2_|O~NfOW^9*cBxj)|i3o`8~-rI!O@ zh}B3zlw4L7Vk_*N zp!c|;wfseJGM3*p2|EaYQCIyHqiXFNu47s-0*e`xe!@x$-y|g{@}lhsK!KQrjRO+$ zA$Df`=z(q4a#x8mXW=v`)~aB6}Yc5xgf6RpbpNMXq)AX=H85h$Z}ZThs#-$Ur1}t?PyPqK z{cN@@3x9zY3_|vVvz6Wts_5q1e3n{)C1*0da&71a2P=kWOv(dAS~99J`o!D%j<;&F z8(NdcgVsb^Inb0r(E>lO%<+y>U8WOanK>fV*~%(;rm=7D`lDH`Bld{w`WJNUB+B_o zsWvs!^&?$xN~mOYtM{fRat}s0>t>4?G|G?jbiIU*bj#vmi@SWxA9M|ZuMSz|R1B|6 ze~_BY)$@TAQa}4l^mfJvyGKekTPOF&3pIVLRFpAsU*lu~C-Y_Ef7Mb8_WCsdyeW91 zeBV&6aX6?77bf5Ak8unV&}Q@e{)2Lh(Wz;R@Jzt_nh?mg!!QZjLZBs-ZY=N08>%DC zfMbqHwi9?uri)=*)}A*k{V^kZ*n$`` zs+@xzaHRQ0J0A=7ewUke`j;}Sh$3QR)DHy-WDMC*lF&S;k0PkWFeQSOViJWNlLDX3 zN&ln8Cmi!NdUsielcN?xDeR8=-Fp&&`p~;AV#u$>Zff*ZwtO=oHLUnU^Fk`>@8q8L zu%DSH-f^OK(od+Sf`uCv$x$yqby>sdus&)TJP%c2g+MG0y$|p_Yr1BY2=0ow+>dJn zbd9>I5ud#pL79o!L;gyc+BPzpiGP86A{~7ma6lW~9l3Gih@@R+cSty-6=nkXfW#oW zllPCYrW!w_!rR@!eLTj0bUciRN4U2X0(<)^xz>##11@xbtzr2XzGa+{P5G3WiGd>2 zcGvh$2+J4sF32k4KVWwfra=_~adwEMclWRlxD$Fm+H|MuwxcU`TG3S!XnOt<#u4O0@8Ed zBHptbWK+hKNtknL$ws$@IGACK3k8J)YBeDT(4<_zf@Ssh)+g&8u6U6{k_9!f0J`|P zXl}cauXRZuUy;6@QlHq$5CSazndA%*@DYyqppz&PwDQA&bV~g}btZHO_3&pR3`aVw zbO+g!U*A0pufE~jLWOd9p&^OMkNPsf0g~s$0au-=sqPIxg%@r!^UeFDVA|=Q-$3W` zxO(X6UZ|wQbupwJ%RZ3VIx;Z1KRLr*CV5`yRv8BKv&7x1uP%uD?fVn77# zj}D_5B=zOUQi$&}J~4xuUooxDkLu$Q(`9~mph|;B6hCmE$=4$m!CI*uVv{2-)$%Yo zj@%K8gx)W8Oydbi_poQ$ss)*8dC*DJ-KKsPi3aq!SoETb>D3<9W0)KtIa6fm&ewGn9F#3+32yj~qa&aEoU@OT=iHSyuZtC*G9cAZMqO)?i=Gk-=!t&w~x$Jt~$`G|n} zp;>z3UY{65)hSzl=BuE(Voidn3UK+%7Z#JhKy&wm3@)rAdBD5S?~AW)l4_%_0~(Tk ztGqN{XNCWQZjk-KQ3fcX$9+cJ4IWsjAWkbs#$C|K94tc9WJ2gehj-!U%>eI+Nz?JH zZ}bXP5;gyGK(oZ9mvk>V@vD;~l7{|A8U8^DxBKmK*Tm;N`Sm3V%z3a=@GCA8=Kfio z6{iFeD=OT(Z&{A5kXJWuFhn$m|E@*daB6N;w?q>mJI?Y&d3;Uv_c_93;_nPL>sK$g z(6V{B#txdvq~O09o`XU~8d|6tb{-_O=rCF#lC{P%$z8$MqW%`yn59M(ZysGhsG(R7 z8)X*)nkJy&Bu|GnW`xX*A7GL*V~9M(wu;9M5d^T%Xizj-jpq}!;9DJrB~Y}O!dYo= zJxYQwepsy;*oK8zZMEr{a@S-grlad_{S=zjp)Q2_JsrB}!d%n26H$m5>~<5zVE{H75Ve0SNzKGl>R& zg39UvC_Nb?TNF$OH@*$bdmt8a`=POARpfa7^&2%mYtTYd=xi(Yj=(m|aB030vHZLT zLy+D}A2^JGS&3<08(%#-IwiqFDrQF;q`+X+&A%`iF+Q1Ei+p3wNG!bZhX-JbBTU}eW4tzNVXD*{Qx+l# zpKS*E6~0U0uOozwO%5x0#mhP7bREq(J&M%Dk3!s>k|w5ye^6&A*{4tQ-iw8;)A%lB z1k)e1qGfISPEZ|^ag(aAdN+7C81A4DW=b;A2>vdZdF&s5v#AaM%yWix%?{2CZr-X{;yj*@}pOt-!=)6BQ%C+BY%KEOf7;_AWEu8ic z3Fu3R;UqaMeMPNg3~R+gNolgv34ypm6K=fkifZPM>m%FW@g=Fl5Ild+4o#En5G6P@ z_Q*^M0;HcXZA6A5s7(F&H`ZQupI!mA#pENo^0=JhT4;U#qT5_*RK`P-U;BwEe^6zb z6HY`ZS2d2Cw74fZPIwx}`$z90+)JqcUHBW>SxdV3M-DfHN`Dxa(W0~3h`5CVDl%X6 z@=b2|VAVz|F3s>v7UHR0{{Y8a#wmh2gYL#^aalzp#I-o^@L7%epZdzyHOq#X$>hgyjeVS0h9>ZzgKXS3onS|O>va` z+I+u4S7$}66?7ZUGT5p}O3Mk56LfFr#yyIxbPEs4OC$Hmrg7DfU5ImVn|+|Bw3dzwi5&}N{yr-Et^?D9CQwV;sLXkMS)4+HpH%)s zQH9FTv%`Cqf?CLPty4_!M5<*6*_UTX1Bw*m>_cMi(b4i*7Up1Itxwx(CW|F2nPLKb zO8-w;Zz2bsIhLmSpGGH@h}_aii^gKD{M$bAyuHOQ+*ISOWusO69bb-AERO&2P&lK5 zW|QrDK{j0d_jP_%U@t9h{n&1$hR4L49u>C^!kvFqS*7Ii?WzSwZq!6W-Ccz2F0&nd zZh(zyd7dA{h>GLG1S}V_O2fYR)kqIriPh&?+P=-vaA0DhI(x1}rGqnEsjVtiO4nn4 zxW3fJ=Qu)FzAiZMbmZ9KP-QVVVB0V>V66cX?tl`v=#X4im46 zwKm3Vygs`&hs)FpeVcph=5Xd$qX<(dqF*GlM@*x*Ogdkq)2fptgM>imb_~`GG!_dj z!o*?PG6je$rJ`xpoQB88ra}+{{DOu|Rm4Y1-rA6djKwO9IY#r9lXhn4CsPu9jiZOY zt+4T4<|TvaCE-&ja3App3Z|%lt{E8G=i;&Jx4ou&W+h zFLn?z>8)!UsOA6OlHwU7AD05zT|K%!N)0LE_U;@b)kN9p$XZ4lA4J!{P8NFNW4}t{ ze+P+v`)RZDkdhvGEyh+~MKR>DI1)Dz6zEc=;KZ?W;6CsthHPGfeRe<3UcHp*G?hl_ zSGLMm$_jzUpTBW^vn#0gM+#zlGC~umTw16Joo1*+TqEuh$(n{|J#7lV#O1rxR}68N zMPlU}iFsHP9(b?ZrxiJrW9)hm>XBxqPBztj$`}DZut9==(Af6Od zQ2Ng2u2HK+qhM2;@@7K4^Z$5$eBvo}vU!9fu*9*TDTVsq)CM7V->Jm;Vs>%0NxnEB8)m#{Ag@6VoXB#YM+W zTL(BK{)vEXN#$VsZGG>mXK4{uNf8AQFB`KsgCi4Ag?e1UvfdHdkjzgjEYO7{Ch`9$ za*U4mz&0u$%GYAGH_aX-DSN4W&n0@Zhx=7Gwj!+!mmTHp5H{&W+G;`WEiTS`V0vd~ z752fjYkqtNaV}~anHHI2@iPQUQy(KJOGu}Mp_jZ@XNfpV&`raPr)5fwZW>O+GW&fB zLp*hx+D}VUMd{>9N5*%DZXCkQ^hI?6NG2jh|UUW_70EX@=A_xcEpgJ zPe@LeZx-%#QU@NFEq6?;Ho*)z{7{2DE}^N#;l{woEVm8KvuEWGTXlV1({JL;FbJEm zZk_h*u(*Ic?05ZB218y#GQ$7CTmnLH1ESgC&SjO3e^|%(&AF2;4DFg$!as68$UrUq zW)HwC&ReTyQq2kx^7SDEDAgW@L>jYMFTu0>xdt2r9Sx0Kuj%}6y{&C%HJ&O{a^}f6 zErXCNgIf}NB$7wzn>FqO;_Q&rU)NCW+wt~bGRmWLw8f?O3k`9q62;T!z?!mC$}pS= zG6A+4RQS0Q>oG-o3TqhwL$XckmJW9-S$kUmUO7HL!=kDLd8o#nFmbshP``qFBDrO* zp8vfJ-lM)!a!LfZ7nU>J~EMecVwpAoFhy zJhk{lBi7ruI^8hP`w_C)qr@ltu}s75Q(D;Yfu=kJW~^onMsKq`wPQlWrL<}b{<7(S zU#OIq<61&@*=R0(DZ-}qRhUO<>ZGNC#=%{Aaf^U}M8gI`q9NJ?E!@K+(fYS&E|vX( zjzG0q^(se@XW-?Z`*2lSxsOgf*Spax)_+skA@AVhkdKnBv1wz-&sr=RPnkz5&f?q8 zXx_&>5@wsM--ExnGXfrSKWk~DvnB_sSY#{mB;fJwee6_N*1&N3fK2Y9`zJzUPu`gD z>+3<*f)u`ES=&yb(PzUi$g#dpAAU^cvvUPiK~$S#lR&s!XYil#sE`rar-KTo6gyun zx^4!0!Y6hh=Qy=XQAutzK^`H7)#R32Vp3g%mTT1#fpJ-0RCZ$yK6fJve^)Eh`WecT zlah=wO4C{+s~M*2$$ywC%36MVu!^vp!{K$)o)0dqq-X~}m|IQ+n=qFgh#G_(fsaD| zR_47j<=Y2A%?AoNrT$33PG`HeFuc{WLq4th;n(J0Ke6gI_Ks8tD58r%|5dIZ=eO!u z^D6hgo>3CBj?DK1sUUiP#^T^yn`yJbFyow`CFn+E42!z{4lNeQhkyP)ho?--G72*osZ(pkF}NX&zc{P6hhZfR5bFh=}d$`g_XhMUDX^(e;KW=5G|NzH2FFSQIipl z2Je*-iQ-kVO0d_=W{r*$;7Ou{Aj55C{zS>f|G^VGAGgcDN^bDFh1Wz0!LbYyRgmP^ zz<2mtv$AP(Bz%57uv3{6`0mBH#Z--G8=O%JcFG6iXl|v` zl5!hCG$Emq5rde(N8zvV8n`~>0&X&=d|-)>lIWI1xNaJ!V`h~%hXf}4)C%};++O(~ z3tXn4p$dMx5u?eFf{a16$2c#0(B)X$k`gEUsZWsoNxqjy(b;C01yaE%lEW#cW1pdC z$mF4-&`uY_%PVWhHqUXxU}V0u^XP zFLKh!imu$@jp2E>)5L$1&wZKKJffYGFHS(C+Hv_0EbzWO`slJiUD~-#zSuV8_bShf z-}MpgY|6A~<OT9Dud;^^rrlG)cjr79hd8$)c&F)fNlwOn;F(ITpy{$Y9t~Q%%caJO8^Q2 z(FLuvr9P^p;*tiYMo8XrnK!0Xn6?lxZh;h%wAaQi0L8vdh*S_vZR|_&JL`1MOxN{5 zD6e2xJ27(PqmGAQ!G((S1RWQn7m3T~&EGm{rW6bj`f(?P2}Jdt3UPD>YskGKPH3`1 z>I|vDU1YTKtBGW7yRmPtBj17@?0 zknU;&2EIp{mrd^Aq2M5XGTW@l}Pg< zVTg8TB0+E*RO+#u43b_aflivG1KqK3uw`0T>w4RhDj=C={FdqpV)i^sNq=!)k0a20 z75++a4Phat&et3na!Dq=hf+bMgDmgwNw7&*73i6vUuhugbcOt(AH~YWXrOIA6j;IY zvSaUdG!Z;n`YMPy{;|I1k9LPLx&tklM;Hj1i42&7m!*`(;^=fnhBc_dz^T;ya7Q7j z2prFyksh+{VyU+=Rj|E{lGppyx+=*cO{d51i~P;w;3w%qq) zlUPZ4NJ%SdcRpE$Nbb^1lfKD6ulg7o1S0T=WTFPq`x(r4-DC#tVJV8gXOhHM^#>g? z`x(?NnAiyrq*$9zT@X?gUmk$+>Wo8C{f>k(Qc1dfl2Snf3w;{2WyphtvdEeQxRWPg z+O29)`2T59^6s(pA((*aj+MG;a0fu~z@i@>N<}vz3?d#@RFEulI-OrdMP%h`kB>b`4!RQNZcqCS`Nst??D<}hW?yF;wh8R zpf}p-WO`XI`4!Q*JaGt_Ownc{v9FN zIw!P*YSEALDkxAOnVBIWv?AcisBOI-kMc}Ky82i((0D3+VMCyf1pRxiB~)*FYqJjg zT;UPT*qn!cN0LOVl0LN4)3B-w0q5#@jE*9ZSJeA!QiEeq9Yei?=}i)G1Ws?I)+=mP0Z1FdK zq?+>1pg1%uJWoaPL|)|lIptM7oSICJ{lwy(Mt&K!oF@#5ky;N-=Ua%VXrVU8JxnN> z0P!t)dlbf4AjdQ439;1!cj|x4FKUD6953r6bub3eEqHRaaM==>0rRW}(rx`u8w#H@ z4#)fw1u;75hp7+F6?l{E_dy)l3Y;!Gs#pQ%k|!J)9g?Ye#Aw{}KWSQIVZQ`5k;Ej{ zT$QJ$=8KSmljxkD<<4+Y4QV|S2YwCD^GQ3mkn-=`DUZi+)D*eJ^nM5k@-0d_{5&vM!mNgeW$UATmT!mcyp8FV`l$xx{G z1C8Xj@l8FVBFVVF7@KNkS^V^E@yq)Eta){ABPlRKq=TBr1*m!Veo6sx7{pn{fSZzQ z^TBBIuU0aMQAIe_1Zc!MiXGN~8=EL4y0$H!2yZ04*m(BLhIQeqvg@D2sHAM4FTfb= zNAb5-n!`E_xbBdWNve}wc;6}YKCRB?f7xcAE!NHavKK;T%zl@HCz+wX(GfWp#hsz_ zBp$ZlJ6ouahA5ScJ=UeTL7B&fc!bBs_sXANygW7p+xNeNT^k#uN&^z+X;K4RR|d|< zHZ$2GaEN8@iE$>7swvSX*jPRuqo^dR4-#2okaIWd z0`e2;`dzW93=W{NAx9+YG<>%iwNl%+5b#xM2wvT5HE=CVpDlA zoQS767>H`laxX<&V@q;e66$J*H*immfEsRO9N(g}k~stv_!bH2MRO$1+70b!{UdWFJsVLmaZ*`%l*6 z6Y3J(IM;q&C0^b1B8s)z0$n>ZHIj{ANm6AH;{`C8crVnG~QYCAm`h zZwbwpT9G0=xEO>ZcM%c5oAAu!k(TZ6x#t#X8$$QgI7*L`NFd!Py^u^qn&vM<5nxbR(ZeHZ8;?|Y&nVgZ8=$mtn#$1 z#)O#QR(TL>ZnYpjm6W_`mBXp$RzY`{S{&m7KdW5L{H%$y*DS_QSt^G&Y!-`$qusiG zEU%|loEqB0@(l^3rUr3VY+Iv|XxAuqsyno;*s3}V`9XamE0NY#S`;i8*eq_Vqi3G) z`=3V_^&eq$Ez!6(F55gr>Cy_&dr90+fTL0zN6-;3jt%t4$8m~7imM&1;{bB1`x|8r zOV<Y-_%B2RDzPY1RA`0gl=J<+x(X2cEi!cq;L2m+fm)R-GssPM8E{gC zw_JCQB!X&B(X!%>YAd;19R^%Jqp3l*?q0F=7gk&KDLz9m=sr-u46l2PWcwD3kNY{8 z7!~UCOCQkY;(#Ea=yc_Pz$?+f3ZS$$L%*p&HP8XpT%px>9q6A)4XM|cu9`FLjutgo zgq$|wyyu4wXj^1+&mv16dl>W(6C^A5vIwC=xW%sst{eawsEM0;Vb~76%g|=p^X0J( zLkuC#NW;jdUdl*Kh2m@iyDFA&Bn&dyMQDY_CBYl zPQ!N3s@LQyh9x_M8nrR+{Mv7;?%iXOG`r@ibl46zffo;d*Opv86h~Xn^@82*lj!*n zJ-%E@Kg)xe#JvbXEiYuBA3wJSTp9(+Ocg*|W|C9)0P&qBx!T%Aib=Ve7nic23r#Ql z7Cw<6$G_Ol?)bz9Yvo6HGr!R-9~X@NCt;Jy9sgeJ{>2K%wvHCF-<)b6JZUdJXt*746dR=?=|<*fX>>fyO>BzUnW6>n`r+&Hh|lQ6!{~U=XcE5U9zr)_U3Zu?7Ts;Nk|B(-XCgszf;8xM8J12uD&%|zdfb^ zD(SXil>YdmgMCJ=<={iLeJp;&1ULMysaXw)w&6IYdCI2KPOD=fuSrbiKxY6Y@2;K> zby3Gj{`}AF4tT?$KB3}ipOmAIXT^XqCeaT2kCTyCm=->-nn#R}_IO-nWF zB+zIiFBTEi`QlNZxpr1`DZhRA;@E~C%JAo3+*I))hP#MV;i6+jTFQz&e=d^si-CB0 z+Q_p~(n!ou?j}Sw32s(I1_1Z9jbu&@T2&n+yEp1w&wU=A84660%9js|kSV1`=uD2K zt44eu{9TWllS-DC1EIe_fpE{O_xOPMQqIVmmi@WKc~YV)2SmT7=_g|fl)Cy_B5ZcB zhL9|$`}khwnH(O7cE}DpXo7ObBC^M#pP(tPeiqwoIo1q8#{El=G2bVl=8_U#)SI;S zT8V9APzo*%!lGLr6q2walmP1yHsc-?NyH!_wcuhtlAByo4W`f!ehpp2w_*>rwLqS6figRM*}tvG6xmG%fO4$l>|ij*AAH zJ=-cC9G1%*ZQ`X{Sp&rB+$+@vWNEv_v)X9Z{mv$SF(PBGK;rZPvf zIKZuiB}udDzUU?;{phIb%S@FO{F0|9GZ4Uw1-3vYfNGsP*MK{Zgz3|vGVAA^^o^py#t#BU5=4MC|(2}4Eb z?iH5$Cs<4U)HO45V7Ez+{mg(j_Nw~Zi5^)&CZ9Pdd#2RbF1-355lKM10)jq zscU~D>JAEUa_fj$RXE1-HDgzh9+$wnc1f&tz~)S&M0+ViG%!+T09zZsH?FAo%3ju& z1QN+WmV&{LxA668d>AlA&mj95SeNra+oX|fHB_2_-ylRCQNI;Lcu4ed zr=c|+ry-cdJCE#}+dV^4Mo&PBt%V@SY|G`XcoR!zJ-(03_JM#l$%H%--Zdwdg-X1J zk95*Bipw!N=^I`jy{|POI{xWY@dfQLq=pMut0ZkW4R7vV+HXAMSU(nQZCNT=60T7k z=Zc^7Z_a|5+hXT1XY`9N{Uu8r1%A-3HMwI7?AEclI`WhiT)nE|kC5F7^hmb&L8!A* zQ^DOc-D=k()2~?LMwMsO>_3rCh=j7-!=E`Tx zFS3#q(Vj#|1TDbW7R13h_|La6D-yxlbaHR1T@h&)+R*#Nq4#y!awZ^j;eH02hxk48 zAN2koO(|^tbAu`+w)bBWlyNw9sH$1eY4()~VhA3IiDw0YSeRl_} zi00L9ZzS&lvNTnrV(?(!@iY(Ti_OgMj`Qg>@qC%^!Z2Vz%T^Kz*q^M`WfUv3ihi#$ z`VNlO`bI;#elUNdrz3fP>x>h$W3W^&7!FCKelj<4q@@Y{itzBLWlM$sL&9L0)os_Y zp^*@ix z{gtO^Q&&q1XrMSH-TLq3ViY;(y(9{#@)BpsxVZTS#O4QNZW-%Qr-ST#YwnDZ6yVs( zal6~c#>Z|P9%%dsRJWNiud^2dL;~+)kFIvX7`Z5%IN-zjQJ2vwEeNd#6@^l?kh}ha zw?l{fe?<^=k0TD*3H7vab4<&$LK?wH5LTFIVQP~a35?PGH|bbQ(4^p)q%DEg`YVA? zI=-B*#lBkE-XA^%rem6bP#47N3lZcu+ajEzw@T&=)@j=N>Unr~fPI%3;EfEqy=!OA%{B zQLrKLBtIQ@oXk1dV+!en40E2B7=GwKYZ_hHjVtMMud%R5TwcMcHfx$&*e%Gq6>__T zd}5C|<`%(N*rhJ%lOA%*#9XBGr?5*|(8t;BW_^oWeMBG&0~T8>@)3!a!sJ$j<)Y<6#YnkEl4aNgfn(P%KsIRrbqxskb(qj3mZg(q$c;-U6PY+D*4RS7QL2EX zqRDbK6B*_^{kw;Y_15BBncPf(+7>MzNxH?G@LH0CgeXCwbL4m>{g~#8Xg!(iw)7PeJ%UqstByq# zma1fY1uY?xVP?(({mE!3|bt~HIN(ygkv|!Mh^a!l;8ZD*^;n}b{ST= z8d%7zo6pS8eob5M$2pdk5r$#!ZF6v?rSm;HUOG}K8y=k_M$%WRBo00r<0Km6dTQgO z{|&jZB$;uN{+njRSW@%96Wq3s3BVKB{N5aqV24CQ#sbPOj)R7<)Jz`-mW zQ4J}mH~O~}xGuTRykAacB*`?yA< zMx&gXmCfRjmcvvE>UevU<#=d`iJbGug3a^+{V-+<_2Ou+-jb3@J}E3V)ua8Nyb1Jk z2QMag39P{S12vJX;dDDa(jt9v@4%_hZ?oW)W3TDIcT|n0o~xAz-O3Pz+hw(o?)W} zYtDj-y@<-VHVKY2HO)HpeKqMAm{dU-G~&`M5y3bOq)0SYqD=0y8$}n=YGKeYV3;*l zGBE)s?6bx#4X6l(=9iR*l%(|6FqVkKu+uQTu=p^IF#9lAxK_ATcyt7szk(&q8qHO~ z?rtv9zg%jHQkX8y!N<_bEARy*$EVsafMwikE5jc5fjU7(ky~)^n~YeTHk>bqYEXNy z&2S!ttkNwsv$R+RRh9l%)SOt~@)LK%54HsNHY~CZS!t(321iB` zbxZUbbGJaqWC(q1^!>965tz48w^iY}x#E(?-P1T7O8#x>lTRp)RjY26RT;Bt2{oLh zhhzkPb8AcmYwR-@9PBzR6T)7#Y+wr~uNbkK5$f+mPSo!t*z?n#cXu+|VN&Kh#oo!N zLBRFQV$5GarA7*)BvII*=!GR#Ti)UVQJbP$c$J&9({o#GCa_i3ghLxGWot+Ifl-p6 zAFTcTYMu_s7__{5Qm0>Kp+iAy-eC7u`yx{*k|=G>(g`&hj|>Zx?p4clSv(TjKd%#oOzyIS%MiNqpj3Tl(kr|Q9%AO%x$jm0BLW=BJD%phW5k)p-W@lx~ z-hS7?k?v3T_y76+f4?5x=Z5l^Lk#_S?!q{zQtDc&Q;vYlfdfycvBC-F&r8> z5zoyq?2a3@kx%G1?s1c1C3ow}-Q14B@A8*rSPU2XX%%75MMz}M5a9DGyqU!Dxpdc2 z&~fOBK~-|?uf#O04eKm#oU~YvR(<#Et+@E7VCEI8$a55wA>h703+BY?Z_J`_e~7HGkLT0B+o{f8*Y6x?D8|= zeUXl%H;G1P}=eUa|=EzU7g8DM9)*hbEm&kPk-H1KMU;b!=x* zMr~TNuitqT#oF3f@7!G07|6e>g8id~O`U=9>WJ~%3+6uW9*4-SP+WW*nrI()HCA5v zaYQT$yZY6Pl(!dNwRtRMT7A@=M3X0RpdxX=%A^smKk_J*syv+S#gZpo>IF7UsR!eV zDktNkfZEJJ+q z_WN5S-f>Ld@5eyKdk7<*xEh0U#iL+4s*`l`Co>nX#(X&%Q=@Jx9^7%YqA^vx?NLw` zm-2<$Pid-gj7cRUKc6YnC3}}ByuoQXQLg60a6(+_rT5AB;j2Me$pqZzjbC3s_2ddw z{mCciemuulpi4e_?&mA97SRi6&)&Tf6w58$t;Zx<1bU_J`2zsYDG<}Fb6P=ay2}IYm4LXf#pJWh&YR+%m84gn3O+jPEaUs0 zZ86;J=i`jmpIOBfOK92G&VL?ctNuuMG(_fe9rm-L_sO^1(a@G6q(7c!Jz;k}JK`Fu zGtJXmN4w4^sX9L=PHjZ1(3?9~n4Kr#T8Ufqh|Esx919_fF0ICM8D6Yo-v`-mh+I=* zV!bk^L`R-RXv~yscU(E0lYhO&yHT7?;hH%P?(-Cn=7G79!U+5e*;eFXj3 z{=d(mD2vbK3u&OBApScAzqPWmWxZ=~$3&Oa>rMKLSDhIWp9;^KwTW`Im$ZpV{(jU!-T2=N07BI+Z17NGyGejqxNSmuvuf@mr5} z;|Gsaj-#C(Nv??hvL05{-erWLtLj2#WLUPLCf^j9+u^p7=dM3{+03wsirt(F1r6~x zo�N!1aq43YG`ruUO{*CF<@!Jtolcd6KECutiYN;V(YVD)0Ui{HWdm6OZnp;iI6! zUvJ!P$QDC9@=gv#H-TR-diV1pD7s$mNA@~NCKTy>_mqTg_w)E7odf+IO6YFeYh%@v z?!`t;vFYjQp-23wE9QkGY7c}EB4t*x3PWl@cq&P^9 z2Q=XK=9zbKjL&~?Trhki;p(~-z}t6G>gKg;kF1NIZ&&!>gfVNhe?fQb7;T7h59YqC z6)dTXhSf<6AD(Wk7X4TBMS{Q90Co9(R|&eZu{=FF zHkPMb`Ox3rpO8*2N1T(IIw3PN^TII|e&rKn4h}0{zFZqQ%XhM;w>J$h3R=?OEO`H( z13vZs{Y^*yMbUCOY%24q#m8nP?;U1(x<1_PZf;fxu6ZqBcK7adB)8cM>WVG<>FsqO9Uy*ShB+>x&3g^6cx zV>1cU>nX5d)hhf%GBhh&Gpn$*OxtN`#7=VD+Bfb-Y-n5@YvAj|L|<=j+lf}G#BX+! z?bDX-8{KOQV@RR&b2;`8#e|=M?c)DIhnnAf2mCc^EipsbZ$psQPIj| zhvoR!H%m)P^XCMe76*tKrEUgN2$JYqv&XrukJ~f}I&3X<H02)ldK(wfme$W>(Bt1rcLXN{U&3=@vXh#%l5PwNwzz z=TDzrzkbc6p7Z6~w``3(i$wXj(7EWC4M-sWh{+Uib}@QCr_+xY`XI- zAOE6*h<3SjTn zu4Pw@!alOFupGfSzB(K%|CB9zYtdEC6G!1!lEh#0%m;@&Tw#Oq;9%ht0W;4 za>>ug$j~g=j0l*&{_54M;UWo?QGgm@aVWMosN4J7q`>xdr_s3KEfATSf1+ADztTk4c^?^8mSCf zdma+f1|n*((lvA^JjZnKcAq^nA>E+EVI_qODs|3-E zG+0`eEQNkeHRviVEUd4ufAk1TDo8n1^&B2U<>+W@oV*sHpVc< zsYFmV32mgxC8i`LJ$GQQN%MWxc!Zdjq<``RRLs)-^QOjd2(NOrQf}*%ZTT?d!Cy?C5iK|&&1XKXKra~ zGWju9juwo?7L7)lt=`pdYisK*a!_e^@4lP&OXK)(X#oKe%{ycCy#6gANMYJXdDG z9;(Y}Gb%$zmza~owbnW~IEc^^PsuMEDq~YT@VI*tW;wc`XQKoXf|r3I8Dt&YyZNTJ z`bh4S*RRD{6t`mo%F4>Jvu(y2W2mXALoAE9dCf`mVY><^(~H177#JGTXCr}oQ`^8# zO+EAxlX9vh!8au(#n)F7RDW@K5aW%9xcW?&FJBfA(9Gy4%FjnXdX!!`Fl*5vIaAmF z0u4=%?KfF4Hh6oiDnStr4GlSN`DYDP2L_UI*Y@`IPC4@gq?*HIe-017-nXPj)uvPEz@+SLf;I z=+-)TLC{{1s;#eo5g6p2U-DeI>72Y+r|Oj|EQINIiOTcWP_=v%&vf1_PLxl8cE-x$ z;^M+W6q{~E(yhc{#;~#|O=aaOQFIK9#z<~Ib|Om3jE>2*OZqYy9dtA_7bTfCK2Y!! zmfmU>@dy=ZxcU$S%^RI5KiNwD_Hx9rsr7Djp93k($ z+k}-v+oYkS6q44tzA{UB=1fFP%w79|2u>p~yGDe&So*0ltw*jq%H6w{)rE_;X*p|X zXt=$+;xfIBfhy@F8eo=1fW{_?AAjMtVHdOGyCT;}5wn>yYu(0RY{v+>t~bV9URYS* zwd^~4_UzQq&@CmU3pf&zk`B|~xtW<8jJZyb@zhVXkCm5~``2m23AvsfY&RmyqI)rT zZEu{-@P(ImN=3f@wAk6g$TqwyV4j?kA{jtBGCn>&HPr(<@$TKb2M^F#ly2Q3BqaQn zbc+tmmds4Hk#x9IAo5r0G{nWdsa=x3Jr_99p+}8=`zfrON0Ck4<-+ZzV>zL5d8bcV zd5K61qht~sxq7CZFrJ(AohQo6Taz>4EX`Or3i8Kvy)s+QqJ~prHJ_y7GWLAk(#sx` ziL&$>pC>X~eNqMGDSvRgaXg$Oj5M-2R!<3452u@0WZnUzSmkF$Jwj1licVsbQth{u zz?Wjzy7XkJoKkhwASD&oyLu(X*#HvCS=qTJV~+e zNpo0M4gS^-4ov{ObMOqgU5Vb7T?;90tB6N)yq!Y>zOnbwcXU3PqMgQ1QR)fMjj^FE zi{`SUq`IgRQs>OMjB?vEP|n)XrnQLRqGREz^RAx$mwqhf828$O6Ujf}^m%>q)!xF1 zPR{UP?T?$voJ$gA6bmh9x2<7rWLphtX-kYKk}*<;*5Fyk-_}4d1LyY|{9`_1M#%U6 z=!eS0R?LWyC_eU7g@lc=+19c08%AG|Yfw4*_p!O8i%>I(2-3r@rMBPbU~JbRMy>(0 zS2=caw>=Eq1iroVE@IqVNN^7=;NQ-{+S~p1aA6SphYq$Nq3`7W7W~Ju!QNT4YW!_~ z7Q6qoADkH0e>tN*jdcGqABR~qtlDfM&dUgZ|~vZVJq(7np1>?LxY1YrLG&`|5Q|5DNQ+~a^4pg zN6!}C#Dujyd^J27yHd*YS$ zFXN~pA@Pt#3XJ!FFi(W2Rxd-dYK_Q|IKqu@+;b-?SA}@{r3hz)OvsalI~?5izwW8B z0QRcN(Vr~|K{RIqB!qT6F)2ud-30WR1O>H%UW2P&%E-oM)t;*6pS8MrzeKyK`i#C) ziO{)oqI`N?l80uqtHoBz&wCoOk-5GQ=^ z$EO4nmUr^W7#LB~?yxRjvpF=mV{Hv;u zq^&*?P7bXK&(Wht!MyJ(g70l4(dqi43#Mv4PAuqRm=4+TC<1B;nOFg}6J+l0?rvE6 z^&K66P|$9to~ZbJlj3uFiI(Aj@fzL>rqe2M%B7LIyVFA>W%}(c!qEsk%l9C!Wjo$z zt4^sN9hDKg8F7{4r84r|9?WD&qpJt6gYVk)B+Y$i8{mwtuC94pG=vv?8XSfO3w+fA z>o>(I`T3nw7@lzG990YrX)W-Zd(7+^dzFX2?W%+Q);_*LYjARPq;)3?U?(CbPVAUe zNmCDri4nBuxs5u1|I z=WA$E3C>m~)DLiHZaxgyd?Uxo%BrH$aZc>v9V4R!F;i1hFv0lkCWc2xiHL}l6%@)H zLPA3&#KrS<`p%y}Kli2)!(U>Eb>iL{7%F=jOT((}vW2@Ju`#o-CF8{b3{>=>QLNpy z@Muoz7JhL^zkL3Ift0yaCf|iyKjqP5*O@&&wYTVdr}6R8DDv*@L3B?;TD>Sd0)!?@ zHQ(#0x##j`KgVGavENPn(V(}LJIn`il8BLPUn%}H+unYBSm5m%86YEP^uv%c8ctEx zdr!UxD9oVrW>&u>B83_jSp&ho(iO#_k*$^#x`32ihkAHABy{?)_CiYMou5X?h7QjG z#wr1C9THjl53I8iKrZ}&iu^sKQXY;Q`|@x1aPF?tuD≠dp)^=MPpX{<7e*&)?=8 zQ{{f{x3d3SduTKG19l$lwRCvW&f;lE#SAh-&)|p+I;uKY6TNG{X#Tbhf;(9^e@kk= z5L~1t7x{XBTmQnIDhK0)T4Z0nF1zTx`K{g#Eh@{-CbFe}%z1pii4}X-_yMW>dk*V` z*gDvUlsjO-yN1s+_b)T#P#e^km3elJLO1|uQbX|8-f|=4?!g0s^lE>d!^-d-WJ3t; z^!w;lIa^x?A9Vqk$#s44URiOk<5&#BmBf4eqQiwl3Su%O}) z4i**`4$hDyqL<(E4Y*`(7sI$sORhP^;TZm;G~;b5i+!O*|Xhw8GsdnXVEr^fEL5({^lA5 z%I>;GH=g*P<+BDf)IW>QW^{FJjox8xZS8Ya6@w({6g9%sRPEZek43!t7C+CJQZ_3E&FB7-0^Pa4U4nf z!L$6@wi1r58rb~{TBK9Wqyb0XHR#O6mg(V~D3vaKw}#V4#_eQ#TcLS+YeSevh+#6Z z^yUEGdmHnPRoq?0Ct{w@#JCAvIS6Y*&rzgP9;IIv}8%bhCi3T>-?JO-e zVd8}72G5Jh1rD;-G&p}*5MU;9FPQEKHdv8!vmEFwh{~Q{9zFe`j9H@3x%g*&3QpOG zq$9d;UEtT-lDI`#W(_chqLtDO96#w{W!q%M(&*tfGhWN?d#kFV%bsGar2<1Ax-Eu^ zrq-Qm{4Bptro}Z6MOYpMoh~o%OB|qiO-)S!K|x={pc1!PWB*1TCVqyR{ zq&R(A33TV1f9TV1w5+xttW;D|8gDYl zg~ctctn|NkH5&SsQxHaGTXz{v>KhDN!>teW_zH$6#7p2}_dqZK0e>^+^;kCvuGELK zi$y$>)qcs-t57=8)NWY1qE?tbdn!AVK7-#qIcEaK_NzwNmTdi%faBsPhco)x4m*B? z8*8@*r>;(p_*VNho(fZprWelR&9G|UFzekAu1qw^Opp~bA5I=)z0b;a(YQHYbmcht z`eLhzZ{X>0*>rxLqMt)=^7`GJ@6}NHQDkG2x_7<~R1G=`mD5fC>g%ug_{!bJZJs1 z!#!HrO%b`3XC(AJN+sMT|J@LIS<_=DlZd3{2Pah~8hbA2+zpeAb)TFh*l|hR*=cy} zHoXw^KG|F8@(a$~_Kti`b#1qax6J+N@?CktmJ1)q10}>UF#GL(*hUC2U$DESpwJ&> zQE1XU@UbXBScAgvd8D6mWQ5W;Cpite=G36l@4<@4qqes;01axGM@y8AYA2{L(qrie6tEVUtQKS~UYr*c^WAoum!YmU zweJY&k-4o&Wr7%y)vI=4@z0qpflw;Lg@Vawke!qPU?Ep<1eNbHu-MV+Y~S&e#< zqWf8L7XDe%VJuq3s@1}CV=^aptW8HBw1KHd3Z`dM$5M=S<(D&My^`(@!%?-OvP;~P zkCnAoSKn0|m2%Ws&p#rd7GAY_K5|JSeb^9fs3ca4wHaNmb=~(J2~UaBlIa|#&B>D| zot7r--bjD0mFRG|K2{W4H2t!xcq`mS;8%AlY};KT><-^z1^vRgPi0|~>vGR6@gLoH zOA<&NdlVMJi**stWo|ssZR264&d;(CugHnYvt;KK982xzdL7CZW;Q}?9^z55yMJ^J z9U>_Rio*8qpX!m_yYo)0KWs?Ygqe&9zan_*TtfKwQQ4G z^bFgq&AVKI14jL7u|yo(!rLpQ9P@EF9Lp42OLx>@(7||`nXN-mNA)!?#|SQ56T@^WZ2UB2sR-A`(UJ=bIDP)pNB@)fp)X!=Sq+p!SSz=n7)%3;fpX7Hjih$XVxr=V8na>Dg)q-=JTqSemDH8sNU?r? z6PI2yN50i>X)%Gh33xi^$XKIFM|$`Bz}dou=LKrQl#ChtI$F1)9Hu^zQKpqGH=4-C zwtCW)Q#N1;2-mwANC$OI3 zQ*r&&(B9TQY^d)K6$^JAGNccg_Dbq3ozIz8uxv##cRaPdrZY)E1$j8UWMFotsJ9q9>*J;43qa$B`+chXlk3eZeP~%jwCRLDFJGR~&;t{~PbbN1&xU_oCW4NBX%|9Ujk%|BG;%kxK^r`NJuy8c zMI%ek2jnxTPB5_;q=H(Ehl45a4f}njfLW3&8_#|I z;;hr!NLb$8ZlK4ML8uw5$V+^DcYE@m|1Z&~0^Nj`c}6GABAI=eDiW-1x#j(Fr;DXI zveo^^V>+kBpMyVs{1_kS0}=tB35ouE7=KA|F$8^p`w$cp)9_D|`Vd6*MTa2Z(WCM( zegdA~6G5G+V4lUIX&Bfsw_J175Jlz1;+m3FMZd&`ykXvQt}ETbe+Yb}28s8r-x2*S z5hu%~i5OV}4%C5fakkiDd4E`XotvGaLV`u@wP8Ca1b#o)pMBf+uqe$x5GOy2E+eH7 zxS=PC?_|w?JuGOCyE@SQMp4T5PB;j+%D!&;-^fnx{7BgmdFlhvN8Q(igmHG`D~C1D zqZQ5rnP@j~!7n6C;z0CCx;;bUMY|&DK+00&vfcWbR;=4o=yYLWMk1*MZQ()PAq(XmVh4z$_@PuRi`;f4*T`H2*_? zJD-rF`E%Eau0@u)>(Lyni)R>TMX znfdv@S69<CCA>2iH!q@<+y_?ZjyMELmlL_}4A`|+JW?u^w1=hGy_ z*CHiDXHD84U%!5xM(TT^U5X0;Zmr?$`b?)m+eOF31P28TYhAs1RZdQho}S)6tEWd( zDu{z~XVs>4morDNA{}b#&knJ6h_vlras+(!QBt^*>An^TUa&A|d0m9)2wqOrmcyTK{Wd z;noZ={`>+0l%A?Cli@`11X#d~L#>CYRq6t*v@vOsa_FZsniS!$E^V)m@vHtiz*ALW z7*9%!odAx?e1h9Z{VtDS3}`=9;Rc)pg-?iCm zF$-5Xl82)pWe%lK=xVlz*?W)m^>zANZ#CVwmH-?zy)(bZBnV^GX(S1@+>ONul>Hft z8No#ZrL9rswj~LUVY;5#YvW|C6XuTjIVo3>EY=#TUuhGQ54Tz;QurO;g2>WbA&KGlyb26gp9}D z^@tyls6LGzL_6UZw>GFUaZ$MC`9@tRv%bHQiVA|)^X=QWuC4;OEjMo5fVi0E>$h)d zX=&dAm||gJ0cK#W7F-wt0)m;aJRl~#XSI9i?JX01DJwmFCekdO&uP(ERP^Jsb7I4I z&+n@-*q!a1w=z-jLqXpB6=#>vLVFTXxtA)wV{(Lb>gUor+=ePuL&H&7-rm>RYMN`N zYXpsx<;Z)GuajH65O{h6UA?ZU``9sMA6ZyzJPHB8KUY@5%0!(8%29zZq5Q6C-%mt( zH?~(iU$0d^aYd*R1Eo%Yayi)9pR@Bg&JUv=!EgZ@7g$ylY_~m}4DOAjj7VO}I6}BD zY6slf<{O2B-ycQx*#Mp^@7?d8NEqqq3xK5wxYEYbWS+xp-(UKzz-G+e6YpxLc_v~? zrT)>n@z?6qII3q{gv#5$7>(NFMw08rJB??IE|OomdPwi|3I3`(yT4jKvH*rUbLS+f z5UG6lD#V71o=UfWnaa14M`EOOMzHpXAgRZqjy{=A%jozTx zsuc1#KJKVFk0!-Ao^lou*Lcrh&LqDBBryc3G<0Z~TKPNXTThQA9T#{13UW+hdK=76~ zY$gGl4+~QPB$$|0I~7hsmlNhk8T`y3EygZRhTQo6m;L-EZbhnfJM0L^R++}Tt-DC-vT>M%SL3^f>I>Z{kAaQ z{#G^$7|S(Va2(b*HsI1SaB|)%d7sY_QU>tICDdJdja8Ycqa>9{tk#f-WkN6DxCRCW z%wreh%W+{)@#j%?qjPAD_HV>uHKOR6(_b6j8j?*lPj^Z?JZzDl!8_|b^1Hpm$}KdD z;YDmsjYa_uHdl$40!MKa0}u@bg1xZA{_d2OHkcvo=a0#m<2?lnrLH>*M(GGQ3VcK5 zcY(D!FuiD$y-;S%+?t&u@)VH8$c2Ti2oE~Kh3;9eZ@?kn*dM7k#@3H@FXZPCcxl=4 zceC2_$1y7J=Jmckdn3tGhvlK^^n?9oduK>u{V?uNch71y4P-iTJ3rn~c2=H^Iv%sboDG*+g% zz8zcY3iErZUPQGYprnh=8jRmF63r?fswik{Z^M0Bob13W3osRpwThXcGf-Cw3t@}T~OhB4!%v*=8Fy?I2KfbhyFD%!}uHv}_LQBkP|zg{(xSYpa=fAO}y&uyLC6Fair2>L>t>v9+1#YHk= zotuhgXv=tHnr-RBVEwN1Qp3IbQ)tb!ss%XYhbW427^=FJD0SzN6Coy2>G66{_x zGCbg1-~iVKhPwlx{Sf$XhV>*PVT+Uhfr6O+HzB;c|`ABI}4J>HeM3zq>50&!0v#|m(bwgY!Kow+%nL5pjd(fpZNLN zI5^15$w5ey;<9~eULJ4W%Fmz1l$3F;t%?aPmq5G5$5X9ULWmQ-gB!rt#ySlksHm!{ z26Mxi(Y(OQI=eO&w=zHfb=(%v8yC%zr&{5}PjXoIcauxR^R=Vkl2!Jxi}du*X-p>D z)BLl*?C9SV_^-J-G~09y92^|Le@_o3O-*#vrIv1OYfIBEA=TB_IpJr@w@3CfZr1pW zVU$QtbYR^{G`g+M=}HB?&(1!h5Be{JMrutk6qDlq?akF+{#lEQwo*Ya+-sQr;Ok@v z_-JRyU%RFNcHPyAs+(6!2rTeHf}Te1>_Bu5H6r$T?FqbSCcTE)08Q$n7iJydZ@lDx z$=P9J!0~!ovLDlw);~=V5#=TxuU7URLB$96|D*6kSmoRN{BU9c-3srP1W8^J9%>2y zZ~@2nXL+`_w>R;t!XYW3t6$*OOvuI_n{hW5zf1o?4>Gh^Ct#E(2FfMi;(&<#TDwmc zkkA~B_r2~%dHSR`B9`j8L#piOyud?FU@RN^p|sQu@c#}S_mX+(;7trq$A!_FW4XDx zfR3bU7ToMp($qA!_YzT74lQN`shmcJ9$Cy*fo*@+^kN^+9_z=W`Bz_$i{c+ z-|wJ4DZZ@3G-Vtd9L9?m2k01> znE?{9Dl5J!F8<6lDL5{E>GGfBCfUgzdABFwdZ;`CeSXs-*Qe7Y54p1+3cedRBqQlF zAS0IB-}XyTrz)r(rlI05>(m|T@3NPPSDWY@zyildxjWJft6N~7v>3D1J6(;wPwGSf zt@~5N0Kj+FVrMpt3!Cv=*ei z!KW^VJ#{4M6%d08^0fmT;`^v+0(T0MB7po(x|8)tav)u>|!z91CGE5EYK1f>6_jXOO&d~zoy8kNr>qCq0waSnP z7QnfGEFBPz47*s010;SO&v}bEs7ZQmZ_Q6BulQEc72)jdhOU8E$RSos*enYYG6Lq0 z>7BK&UkobtIm7PD`Y#V}1#)a~Cb|NB4wjW?K1heU=wP3AvK03B=`f+^=cl-1hgOJG zt(40;;x|Pnc$KhEBH=y;Y1Z*6G*tFINgJP8D9lyLw#~4IVK9=V9wPJd*Q}=O4-N>k z%I4ey*CdfVSete%4t2gI>DRx2*gR)(;YYIIV$u>FbSMyC6TP9M{ycGjf;!3 z4vUM^fgBTn684f3(lE}BU);5yRY_CkzD&f)V{siI6alAh6Y=3hqo+;TYv-EUwtTU&^yR|7|hYsM*demO(TPal-E4JC<$E*Fgphq&<}a5ed>e z8lreHF)=q*R~3PI>?{61Bs5q}+8mM4r)EvRQKdw)XYQI6_to{HECbG}GlPh7_cyU;+AVo*VSoEQQ--n8? zAFJd=5BT|!OMLDwV{w_sxgqTV5%Sw}TdtUGvm}cD)(mDtbx)Nq2JW*0W8Rk`-}^(z z_m71h5~CWr%@-u%^Tb8w#sSm-nzYHW9Ur7F52U$m>Lm)Vk|JvaA=J(*f zE35K%uF@j~wgz4(GEDrNc@DW1R3;xNnD(izTWZsrM`zaZ(Hmw4N=rV;6F9;YjIL9a$FpmN`(v9(oR=oe zM^?jk%r^#a*EoLr{A7XHo`QdRV=Awjx_(&AXpF4&NU%dMpL3rn-l-w=zOs zcF#NJ8v4vHZR_6{UB%;kSRBeToSU<9^F+ILF_+6S?b9D|ltv?`l%p?ZC_ij~fu*FD zvN<$t4`%cBZmEACep6%-y)3LtShi;D)Hv%-ds0_yq@^1#1e+^4J0;mGGpjBW8_&J` zYr|~G?Do-F*YfJ>&83fdeQv(O;=Y6fCsIb_)(XD6yOv7QHoK3md^TvSG_qv4WTSnC zN0^*ZYfh^#?e;XDyV!_iLF^9$j#9=G|nx5VTwoV9U0H%5{>%E z8TpL0!P}1qQ(SxX+AmhVot5rquhL$#?w?6`b0OrdzgXf9kNaiG*4dF4Ki*GljNQeK z%_YzkLl9&aDqnISfTTixU7$S81-fr0d`#g$BnhPbh<*&%BZp_JtVXF;+ir3F#9Pdh_VgaRmxZ$oCHcRbg3&% znrlB{aGn5yd6rG?{Edl+4UvrIv&9RIAr%;mWYRX~E_Ym7hd6a2l-xdywre=M$9;&9 zcl$MRCU9p6dmEoz&Z8(X^m6yYb)o*)or#XFFqSr*)FK+*D%IXM>kl}`iaw_n)ID48 zt{sKPe!OVkUYtzU@`3Gry{W0WQYNXDTC}KSh#Hrad*Y=T5Z9{)tr6RJlNXWyIy5}o z`u64YbzOb?B*4B*o{5aCegEjtztvbY8^hh_b(1F3HLExzM-8~EJ{@re?|M}aTfz>;o%lMdyXnv z<}SPHvNFp#adi?do3v1Y`b#%in$@kVlrJmyW)^I(PpV{S-*senUY-)|w3;=uFtRuA zS&mWjUBG$o_WiQ%k72j1b@Hu|j!3_$mPcQlXN%mspVn8d9hK6dT^av|sgrB+ERATY zX`ZxyXL~?w)*LT3_ui*yS@`0@)FQ>5pBtAO-qH(a17miyEhC#Tg;hqo&}=Tn1gEqv zB`J+;(=@s3+-m*9WzML2>eFZqU-j==iTA>##&aJDQDI_rp6x5S`#mS?Y~ERuW+pD7 zRUj}TF62^sACR8h=99vskN6r;`Fy^x<23k2)C&{FWYqez1(F(g}Y zqX5lvUFn_WRfxO`_(k`71HZ1@UU+0&IL9A|NMl(gi0_i7eroA?sYx=TM|KvduU)jO zd^gv1eOqe%|up0~RNBU8(_(7ygOVWME zk-xitPlX<^W)_Q{DjiaYd#Qd0@zp-p)IUi22eHTX>dot(hO($oUji2gXJL6c6yS(} z7whXzULOahr_;WTU%7Gx=py;R{`mjk#rG`|OYbIuNNQ!Mx@+wRKYJc%^buT(q+DQ3 z*qJ336e#~&mWTG#ehE9$#fqv?%R~5khrl*(cQ&Lof^sg5|K@}u*4GkeQ^ne%ig*<-_=}i#M z88QGhi%ewPi%^LS(RQbn2$N@=GBy;ZH{pmN>e zkv@}RZatLes(Xaa< zB81xiWqwsbEkT{oUarsnQ9&ez-DzS~0tX`TR=W8d&v*A0wH@ozoTBB|(f0RxhdY&M z1#q1vR`(tO!;zX0UFv=+Hp@PNwa)L~)wB0(=vhEnc#1@+7#XGeLLwp_lc961MD||K zYgmPua8XpNZ;;fsFmD4lOA+c4;U;+XPU+Cws9> zLs9XRzRY2a2E3O7by-gv#XUevH#2e2wRRYtvDqqv~EaKkz(4WcTUa6GMhg z+gDD<{*j)9jEssJ5g)v?BAZTaTBE5H%|Y9H4v@S zbdbIYNkPcCp;w=dt=wTu;DFf>qjB&C07!=)0S-dX`CTld{EVnaG&0WX)3){UxrWPr zYsx&TU64k6(2tOU3zC-!%}JLkWL_3M5Mt2ckFwbSAIpFsI({@#n`)~UtDW`M@v})7l?JO1gy(~9x zGXL9_QC|Sm6b88!R`afT25UbOxQo0z4Q<_12^F;xHW`!CEM#ABMi00w`iW+T;l1C> z0)R>9IO$%#6+l!q#K-LEz8nyk*8c6Wg{J-9b}_+ei*r}B*$!5dQdl498ScVv2UCMh z9Ws(RfTDs}Pff`^+Y6QhrPH0B8yn&kY$V5n^opP)$$v}M3{(A+o2fV2J#gdb8(Poy z_!rjAx7nc7)W)Yc4JoO|#k?#mjlI2sKvDtFcd9e1udff1LFd!|irc&~v;iO+7)rg& z;sq?;!V=g7<&S{e2Q~C7a^B`5`K6yjpDc>Tm@| zu!x!FLS6}m*GmXY!mtFLm(O0dhdLsX`+9FoS`P0TqSn z>g$i=;6NNo*lqKYKGXjk7&x9M#M^B=S4e@r&j92aUuu`XnEvjxvFt=$|I2&!_N8D# z?=0t)A)!U7@z@f=dLOwuv1BJIE3 zq``wb1lL)7MVBCnYJU^7vNc_PhtQe>*&yV){OaGudV~$}-^DsixSnrU^E@j{ z_Mt+meg)NDO42uD6G#+2p`c?4i|l}8sAXUJcNGWm4ui4D1M21H+J^_UQh)++^0oT9R%I&KMWH0vGH(aHDtB3zoa8D+r|F#n8sRf65fJHu7 zjvo(nu$GbyvdvwH?7+AOcqrL)j)(L!r^t3P(E}=^b)akKZmbx=vX_LrryB@(4xU<1 zO+xD6-R2JZfrT)VT{;lehfhUQTRT#F{dxGBIu73W^Sm~Xv9|vG5!k-Xqb`PGzm5+W zT*7)rh;(swN3C;v4|V~i+cW88J^SIXeXvn>h(w8e%(xkg>`M5vS9G^IB7m=8x$`FM z;VWhA0m=~NILF-d?sgR(Q>{Gxae(`;2PvwljjM+Fq!dJ=&jn7Hes%a{Lv4O`P|b(+ zQbo40eusyQqd#|4@;=esDbl&X+NxOmB3AI)R^-oBR1w5p=`O`4``rzFl05aG{J>-L&&={0tJ8iW z-q~5lY4@2QDk9>OlQ%d(eqsZ#=1;mmI)Q}+bHGZd^bCd4cA+v;Ca*tyK#T(n^&eM- z7wS319v&aWYk_LpQY0n&Qil^Mv9+~V%^xW}AG~%Gf zmW_=KA_)*O4xrLjcfUcrUeq}&C_pC|#w!&x+7wr2)I`xEW63H1l$;pY6+?7^VWn1s z6~M8|&(H6%@4gF;^vDpDN<;AkfM0s22uP>cKL_yf6`-itMU!~Ey*j4HppG7c>bYZk zKfw%dd=;TYR4x?}ISq4B%Di%F?JOcW`dVHbG=X#kq=U9In z#w@*H^f6uReJE&0=0b)@e+LMGx9@&}pPzJ|MXzB~Yy-)yZ5mZ5uf`Pq?3vX<18-4b zVINdcgPSpIR8w0!0sJ<&9@BaKrKW8R#Q{|{K!w^ntZddH*x^16-{gg-2M2Z8NPxo0 z25icNmeqwO;f{_DJW{TU0s=0OA_An;NFi6K^eAa!La%Q=QX2xb;iN;EYU=8ufIL)G zWt5lg znfUk$AP@%+VCy58Jh8E{z=&w5saad@wzSM2#PDuV+IH~z*3E;c3o9%fnJRaN2Qrc< zC@9=_Hu@o728z*vIqOd&C|Ckd(gr^!Ec{hP21LGk5}Xq!luM@(oNg%Zmz)g6@IsC} zWMr#i>c<7@OE0cgRCGo3QbKz2h zn1DP?VCLZotqwrdG)UHg5@Q)t4ZQuf*47j8oj~BzzCU=hs#9lsJ`93r3lUI^CHr_3 z6i|^0f?9i3i8bVqx{M&;)HE~%#8tPoiRKUzZtNksidL@*QbefG+wb#|(* zb%MgMoot5#`nZ2RIy}4+Mgo;1%rZ*sp%5}i{2(L4J9oenD#*`YobKl3<2$39P~)DK zZ)^r*Nxk6XxL0kt0z_KHPb;cDk(LWTwFgxQ>`AeGHG#h?3Cq<%RGCTXQtW+_4Xyzj z|5>bE0eYJme#(8#hPNj(_Z0^^LN4NGhJvtCzZs6X`$;Mp6kTfn6POQnOB||7!&zXa zuRpT;Nqkz5OacktBM1eIf}VN-)K2KBQP15^ViB&oo61j|;JKG#1_iNEq^`<|r(e1K z;Lm#7LiO@R=XFp}5dZz9-ZsboUA=8=O+}@hs*H+IhyteZ_guakO6Zrd}sP4Iwm<0a{S)`ZLVk#X&)RnE4U!-->OY z*(;W<5Cba7?$f2ckD*jx2>)A6ZKM4z>|j&d2!_!24g*$HnHxqZliK-+yWnvOxUT2W zNP%QMwHsZ*Ok_)e4|+XzA8+HSx^A78|fB!y-gk-h}O+wNjrEEf(4ecaKQ$u?o5)B$ssSric zLVJp)3TbKYz4yMK@9NXIzSsA@f4{%(>$ncbL4C&i{eF$}b)L`j@wCLE3+(Q`O3D7G zQv}zRf?(tNtc`E~qP5^=K@gjmON#P&C+R;)X8l1a%3%Sg?xpCRiQMKR#Ov$r-P+bB zj1ITne2_aza&mU<-1)=8L;u(WJ<6(|h1I+5a?D)NodIB39mNSrb?o=hc7Ys*l^OET zILJK-&TU6=_)*h@jr|{!IyY`tmS-a?7!wNkEm^XIYx4E(D-o<0!hH^!7pn6??cdPQ z@OOty$5@v2WOi1TujRlMF_&dj41L(PIT`?K^kw)WV?^ zHU20o4($W-g2Ny}<8Nr1kXn7QpJm%N^uPcFjcwW83;6^TYYOG+5HWsu@dBcc=g;2> zOMmGDld7Sm#mmo6SAPH$ZA6RLa~NE2xq7gx7}R{T2UEsXFv~;gE9j&g9NtOw7pY~j zw53vuwpCYmSD1HxudD!eHydwG^!j9taJ9%;S8`oUjy{cPZGFex`hu>K{pQ*;1PY zK!XJ;z1+Bx|9v$s3XMSm^czfuv$>N_xqJpL@{Vd}-BzN}p`+v6!Tvw^kRN$+Qc~cM z?7R7gvvt>RhWz)ZYkK~^JAi%*7uIIHkZ)}pVgj^U>QuyQ?A7V{&8l^Fz$@vq@3j~e z)!nD~BeY8e#9U~&6}7g>$jaW_d$Hq;W`}tU#ntoLWEgqNr8fw$Gy7*UZvu<73C%D; zN=a6=X^wv89WkIoTDgKE91M;7pX}^l2*5!*!8KgAB9js;hEy;WjBexqicjx{eM-3~{NCvI(Fd^jzz8{slbnD1_iKF)`rhh5{W%#7Ge|uev?; zPpp~x=rf-|X3l#xAqXQBsBr24PdklsQSg8?ZFB{yV4 z7NHiq(w&)^_v^hx?DOe*&ct}9HJ2{EUnU*bu3g$-&S7M_-g&5pSNbEAZc%t;m-FyEf2SIZ0r?V`9GG zfuuRmZ@ixly6_gU-(WF+qu$r~LdaOBujyA}BEe?{DLYT7GoHon*73n|`Nb^8zKgy# za5waD--N(P{QK=}i)<=yJQV~MMtGjMYHaA19WjkV+UBT8B4TA^W==wwgg5^TOkP$3 zd(z|>XWDZue*zP(|MQI!fXs4}gr@**2LLN^ID4UFS(DEy7Tf4+e!#e6Y<#d%_wVQT zXiY*F2?82c)wXZ;>rn)G#;P&W*Npj%Fes8vfJ^EF*xKJ|mCEp55S2IPcn|(Q!=2f< zm(m-7*BO^Tp-M^oP~pqR^Z*Q~2jpxpPl@}EJ87*RLJ^0v&v+6Ev&~G?Ezsf>pRsd0 zY!VUx$OVrMd@Pgd`?Lt>>bNx=PN;(U#45%e-*tB^v&nuvhmKh0cYv7^5KPELYCRS8 z-rJq?{5hSN3xTnw6EbW%j|J{P6aK>I<#{ zdU|>YJci;tPk#+SlnH`*L4gtK=-&Hu1?W~0x_i{r(0+)nac1kWTZnWpfvnoX(=kQr z-XvKJM|>D7l+(>*t>3_NM*z{km`1MW zy#V`70n)R$FO}c|KO+u@BppxG+tt;-jBPN_N2my|6ctUvnyOnK+mFX;jKMNca)VxV zW4W=xT8A=IVgY)dog|SJ1;to7>QZH4M2p9;B?HP^5`nx*PHxYhA)jf0c1nn)8~naX zuM-Fl4~M+Wd!I9xw=vN(F7_Mf?>ys7zxeV9YSUvbZ`j4XHqg*yaZir*on!z); z>uo_lV;-t@57olOb;h>t7P(S#;ej{=VFWBON;j|aog#RLw`$YIj_xUO|8R%h@5pLz zIm@YfuqCL7@$te~05FXIvTC`pxx2Yx*by3jgvZgsiXGQtp5r*M!)%S1dS<+~Nlw)9eb8 z4)q-yZK|#1)vr61cwNoGk)Ag|F~JP8vHqmxSa-S$Yo_k2tb|Sr_5%f{7OC{oS_o=k zeR}qxc!z9BSKe(nLM$4?x9Zt-R!oc%we`Nf%MDT&FS^7>JyPifz#nE3T=&{>&T?Vx z?*I8Q&&SuSWqUofYgCjmcwxdzX%vM%0+0W`vg^9~iO>@vF{NU;8x<07_D}kvl z8<#i1t1FDC#fOa<_QY{c$XDV+i9}0)I3s}7A;QYZi%b*0han)#{YW8)#X7H_UKNrK z5c3}k|MovgJ-q&mNHuol8skUQJA}|1Sqag_8SaEXF$Om4DHIdNVl(pYFQM1WF% zE@UV_%H7tHpV_}3Wg-aZc!v*TEJ|Fv_C}b~`iB3Ds>VhRYw269M|tHy_=z;>uED_` z>s=fME&)qB!&#qo9lNg!t0j^US-pt}hg?|4ao&$wrp6Vz+^dH(CQlm8O$Z^0T@>aB zbo@8nVw{mK;Ba9@2#LKIjlbIk1x=B;8msQn7eBc>t*-k>Z&-{`2sXnrF5im88jSX) z0gl8d<}yU_pyvh7Yp<}0G!$)fb~E4oHhRqSP5dHaqzNACi|+3j{Qz9} zxw*ZO_u;hOAf9M-=^3jZ_@*+ZZ5TY@$@ifXDlI)7tUhkk#rE%)nYbGII`Eep?Y2st zdJjH_aHzM?K6_EbXUxa3XD`>V!g&eTQB3llfdK^OiH6PVR6pRm2(NYb!Md9_X7^2= zie=^zxP%Rl_2#jO9WZEEmE^IKX6N~dgQwY&lnaHobYWT)221BzsP(2X>So;d%&!He z_$0!e?wh(LSyd_bVy^UdBO@j5EpTwC>K;MmFW8=%mgVj!Q*1FW;RSTyc9 z@`RbK*BlU)ITq>ez2eI*_a@@GT#;_f(VGm0>hH5OPr${KWYudnW*Vy zQF!^C*`7fMY%dNNDPTg@pDa*9Cd2e=XVRoqt56JIqbSs`hWBAoT-3y7Bvd+;soJ(^O~h_zRq4gH zeagjF<|_lMwO`;9+DNobB<)EXc|mhi8K^Qc{Z6Dk`twr?Ga)m6UkgHTK0%zyw6o z+LI?wTwGibzoBm!bHa1O_9VBYPxO1QEwA);cdu`0Vc5KRw=-wx@y$Gfw4&!r=tZq8 zz{24`94Yo2J(G0`z$?43ev}Enn`Z%MosX*+A6J%`n3*}z^FH9xEe@+L^k&^G(DS~Y z`uz}7{e8f8PPu$bx_Q-s=vXU^^1T#r_Gx431_5NY+(eJpHC}a~qT5qdSi8BWW;+}R zumy|-pReajlZhEDzqVRYYUN_v9HnA0l6wkLpJj+Lf+T}SV4Kw0saucxoi_Q-psOk+ z+k?9jyDMUH$kgAUJ6g2G&F@5SSJ!jg){i!@9ztlCr5mUXLKe5KuStzP5=_IeOlkf3 z>Rx5L_{3pw$}qubaSR2dI7Yud3p|6SezV~vSP>rZuv_==Vtd0!SixDPhvA`h^tF!8 zLOaLIP+PI$3~FP9ll)t^s-XCa{SL#Knc7<}svs{fR5Dmf6#gjs`VnI}F{V6G60iDl z@EEXp@nMO!%7 zM92H`ZEbB4IRC^k2z>&=S|N%FEe#C_JEPE}iIJ1Na=GhD`h#YMA7#H_0(2pNn&&5) zgm?l=eq-gjk_`f)V_ioPY~Usn^$19Jh&c%14$enlNbh|IWGccXyk(vzF9+@iPGQ*a zH^aVok|}R2(R)o=_DvWk4X+du!z?QdRbpmh`jFpjVQGoCWKHt_tgpsWIf2`}db4mb zz9&{9Dh9sgl$4(PbT=EvBAxy29VhCH&CdUlmmI=N5R#lhe+Jm7<)4>X9wqup|}Y8{=I zRSa-GmsYYYKuR0dRBgq#a=iGnM(9m^47|g>`Cju5`^_$x+X%_%*+gk+JnNv41DTc zdDauWyuA5YVKMzYko>3Mu3Mw%UVz7f_j#?4`sWfhU1A(X#I8$=jV3+C6V- z9&O~3MQk7{az3-NgdEH#At4;H)!`peHd1fbR{BLVuTNmhACMMt0BbkyIuYDJ^@-qLKO1^Cpc>1E*P(08ajHfVbF*9p#(qjxR+ThUN8{( zrO!uD+HeUsMdu>X2<6% ztw;#z@_Xw^)o#3GAe!dYNBTKJw;{E}H0@=<=fviQlDY;^eASSq9C){k^wnB>7BJ%G zeYMt}IVXpOpELNgm2{~@`v$4qqBS;g9@6No0$Z^^!(5A8Q*5HxoSOxS#cV`hgTy1D*h$RpwBt{yVXGmNa*Ecpg)A78X zXxGL}#41x0x1)K>v`&b)BX>?S6&5PQD&~`WegE_U>k3xMle)UFd_e>zV%W4sb?3Hi zR}nroPQ=0Q?bds&d5Di;0tZ()tl{Jo6drDF8RkSGmyRxaaDax6j*fvL%Q@%`#`lYY z-y!STE>KMku^qQ$S=DN*HNBpu%q3u0n0^tT3S{dWRpYoxK zw~;-?Qh)j>s2I@qdhwt($p`m=`rY_W*bcc)X0@}-dl34dy`3)_JW6;bY*6YwgH-TX z8yMgS5l!^F&ScbGa~xYail}?j>L{jK+49gr$76a(8CytC2s8k~TMnV=a42#U zzZ~nLsYQZ4M8Vx7cEWEt-{TuN9qmIav=P!yD2l->4lVu&qKC0VB2!<6^eyfScA5&f zJYtZ+p5w|c7-u0sz`zt26KgIA_Q>?lLt5NEDhlV1+Fv(psg}E)n{FthNvIg1j9vVR z-0S#wqn~v}US1yB{IGE&tAOOqbq9n9ACZm4`2`ybGKR*;7QutT15#oqC#M0lyP=Vq zib}F0D?587HMPg&F+O2oChI>}5`W29ls=|heQw%8Ci<{+0t;@=;!i{2FB$t{{>xI%*e5u3?KA zKx&W1I=1j~h(+#I?>s3jX*cT#UrJiyv70^C9ou9@Mq0}|y6=;IHh=lYSH@3fWkCzC zCvIGo)Udl?YcjIiHSZoQydGFYbcB7MCxe>lwu|jp|Cn??3FcmsUbx8}(rVr@DZg#L zM3!_xhki#-8c_cG18OomXSG0AOL|dy*IUw+;x5=JMa#q=BDLv_oZGd2elz&YmxI=- zMf8gUsTq9Xtuq`C^!V3DG+DIozkLv45;fV%_@8^4rSwqLycaEaMuzv+W|MBw{2>RG z?J|~Uvt5h}2SfYt4`b3B&VR7xPGclR90rhPw_{T3xtW$t!f`6^Y2~z5d`cxoYNLFx zmW#AQ{>L+N^mSYyaG$w#e_LbRNuU28gARTa2cul(*m$I%!~9?psiWmTMtAwp{m%b# z7t**bbi-|c{XxpFqIO^asRd-2#6;eF`0zt{4+thrhOszRp#=2s483DoQ&STZP&kR~ zLx~OOyUwh5eJc(^)d_IHdxh>_}RL3EAllk@9YTyDhobz z9SI3bmo0nn;DPK;8=eRAOcp+b%W^fEIFDR-d1ZTUAiw%gWklg9L*W34I%H4uFZDmI z{m7WAI&AzOZq-#a8;z!P!}G@dy9~vpX@E4F|8Xw#d-vweHCRz%i$wiFWJ+j(uRPX; zqyQLSEQ8Mm3{0iXD6-V^nXZ)FbeS z6UJ)_yifH0xmv~9PYMEF#{^XBJ7E}@!coTLcJRK zLpyN^iPe5gaQ;ZLp43kb!22P$`81V%%N85vuXLIv5%t)=-B{`um_-op&iRB-M70KF zSE`irp)?pWE{RSSn%Rsd(mw?ayw>=$ z2YU+>zIm0Cx_5CLcK)WYm&Dt4r64Er*UZSg+ftx;<^lQvBYk|IPKCUYW|nNdmgylh z>h8<4;wrFjWAB8E-T{7oBUB-w*O}T-!F5Fb1_=Np1`py)&+aU;PqR=9(I=iH`0sm7 z`vf^TIlBi66D`e!r&?%wW{5_|;hJ>h(=E+^+pP6}?@6l@ZRtZ6(8#DANkVui{Bx7e z`SGJJ4qhZ*Q&a0j*HTear!yNp)8)H8a-B(S{krMtZCo8>Ozsj;63s6u+PUd`@)EKP z*4cLPKpg=q$9V?Z=9RH%}pgv9H!|kG!OHXSRJBpiA zk_QftFMAMD8mXixN&Z}$*)LxxW(lY_%%j#)1^L~DUO|dsFjlR#;3ad@%?PMFE`zvyx7_~Vp#FJb6Z!)SDYpVdTt&&Em? ztsTP`w(_YbdCUrLiw_sa>pT}REOw>Qw)|$`Z%0MVZTvS)VLQ;$!mqP@{C!eR%P)yL z`}M>!{hG5hUjtnHsHQvx@gBsM;TEfcN-96FeaPQM;`C2sU(E+zfb-L1s{NQYU=ziM zy3^+U?V`7Ogx30}8MTzXoqQQ~u92J9FP@`a3l;jt-Qy`1MY4~YD1PHq;i zA4>m3OR;n*o{w!`vz;0h2TK+EUqNye7QN7qhP;{q<-98R@DnkA8)1QfvaZ)2mAk_m zC7$njg*0bFZO_BZ$qOCH?!9^&`3x~ZTQ|oLTT;)+pP%Uux;^wc-WVrQh9+t6 zjh<|Z*){q*sq!=LSV_j>dv?!{JH5!JwMgGvWx5XKwiUY zNJAQh#s@w)45&?3d7f#%cei2J=mo)dC5blP>Wyn`9g`D6GIGe%wa!^+iMQS+-h%m4?39W7^X{5cL=(@f8kGDa(rb~}gT+F9_6M*MBcB9&5$@}KO z-0QTJ*Q^zz4Y%-H8hmxKv9T#=71(@AJTEKL$b=zM@uj=Y^_^kez3pu4nr)(N% z7#RtTDKdh8ViO8*#zbCgtnyS?Lk+*?Lw4GUerNBIKIT6m3d*Patk}=_TOQEWP#%3b zell-6b;bD*zjN6Kz$LK&$Ub&@4LFSZqmi=qG!319U9a^Fri4nEB@D4Y z9v8{IW>I)UNqzA{@gj8sO$bzAhj(=5>FySv0G;BDqT4vjzbGw5m0T-9c9;3K5Ct|e zf#K!s_iT=nMgEm#>y=9!aXl1#EUcj|cD>3a_h89Poh`v?WHbp&)*nh{CzA}{@2Wb^ z0e0}&V>cVl*g9?+V+&=lnZyt!^am5|VEz0W&zXFq8 zq!s`KSHWqrDT#dAJ!{V{Tl^R({n&!mZc@BP#EW4~z_^kLterAC)95!7o{hE#zO1<5 zFY9eV?s_EET`t2q z(NxYMRPrH1!QVQT=c~wQ2rGy%6%yCzA72$` zgu7I7vzBO*svnh=yhzU#U#QxLd_GM?rf)S=)86oE?Hli8CpGsVlh>}f@%4!>b1%g1 zHkjmnXfDe(_e#U`!AR1{1FtNQ;VSkBn7ccoT@wQT{*myC5XKK@+lK!6ndQy*+DUhB z;UH+D2-K#X%kBO1QFaJhEJg9>3HboSbwZSArxU_3KxprH4X5)PYmvpQHrziPb<|U?F{c(-Z_L5x!iPHD{jd z`KJIj8GD8weR)Or0@&9cJFn;?k3|S|HwzD;2(o*}4j1P~4|ZM&9KOT+K}-kX(eZH3F@{L1zaCVe5%_VP8^U?tyk@uLDLqRJGtpYL?&&#YCSO z;nnWW(m)ta1A-i4)-|x0SHnE6Hn)qf!o3*!T^*( z)1g!avYZk398?<#FKnfLt~1aXqlwOmFkADqBf9iZ{baEdN2#hO8KMj5fQ|}Yt(Z14 zO@3{xOt!rESaKOmM&WQ-O>KO|G!`eh>p5Q7*MnS!k!o|Ww^wnfR^`hP^k>j*=MN!G z{PXt4rLn=KC*z2$DlXHJSu_zPMM#u_ul3;Mf~^dx*ep6%=4leOCYd^gyvS3=VJC`&hcF{<5A;3YU zCIJl?kf7o2MkoW`g#8l%mzRsn?_go?Y~Ji7+CpHV1ZPJ=w2*W{Zxct-^3OqjgR42KAfx!PTz7Jlx6SN& za>>}Q|MC1Z8EF(@nNANhpO+YLO1K%`(4sZFr(o`zS;X4So%825l_p=m_W8N5-ipfb z#^SlEe$vyPsJE#4-n|sx^&1LE4eWqp7X_BP^5_Ja#g1&nNf0}(|lhr3z(p@0( zGxJ`!q=9wbLjBRSv$NP>!TnkGLu}gVV8Q%^vrSc*C21wb2AHn+MaIBrZgV)OUNM9G zo^I5g+Z(XNuksok6wNy;^MCo{V((2YF-NA)>8Io}Hkwg3b z>k#T&f5wV*!28Fy6&*I3XIxeI&&x!YV`k{3e~rF2Pb_%lKX0w*mp+?+pJSLrzOrUE zvpGo3icz5frnx9;q9|g?^mXo7>HX!IKz~+EmQ%Y~bnMO91q(3q7N0KN)hnha`DGe` zFFVSi{p>hoS#b5l{`acu!$^afU?NjaHf$lLfg}w$>jh?N>9-HcD|}f)n!I5ZKX>Lb zb+;eBbNxaj``JUqRYF9(NP36QJvW|B?w-opX8jG@zGKH}ksynxAIV4hoPBJi?F~_`wn+(uI@CaQ0@f_J1>(TZoXgp!^`YDEK z_@Qdt=8zEC<+Gc~NX5!<4IS$NyI;!ii6S;f%lVKD*!P-ukG z>EseEVqn7oMrQwiOFv$%h}xm$;_3=ZrZfUHv=AdhM*&k}X1!t<^0- z_vd1SQOAkuCx<@CB*PX2sa6^RKpf_M z!@S=Iew}0c zt>`I7w)LOp_V)Ic7DDPYyq(`v8XcvEhMxli1JRuULMv*FMOY(HQXGsS{IP+o6gB+-1vJ)N36uP>du;7KbN(uG@ z`v17>Xe^c}b=FFa_b06h9`=@0F=)-ZR5{!^0MUI8WWf-088`gZimk`7wQ$W(BRc10 zWVYnXbM}}?#!hc9!Cy}#{D+*2Xl)CQ- zX&}Vy?vjdVSA;TI@b$$?_VvVu{$SDAT5@&DHL-q&e#b|TthUU({5>1)4$yV0trNgx zI^YxXs4=oZPcwdr0g<_w%HxKmWqo+j+v5eIIgt{%zE!Kvddc6+Oby5;#wzdmLXD^D ze2{3;7CIj*&Q2sWsHSo2TMWNS7jB-87S*59_e?Ao}NflFG**=JzwHp(J)(0Z$^4!$0eJP(XMd zw2U}RMb*=b=4o+pNhuhFV?R`_e|Xw*;U^d-i81b-jw0c2a=>RdORe?SUOZ2ez7qC( zsdZjQr>os?v+Q>~IUV=l7jgD6gGSK(INhoTm~}f&UT!I3vOB`I`smCZ=ooBB^Pe8N zaQ1+FuJHY(8xZ6vRaW?#Hh5yJLG&$)u@;d^$F%!R!wea|Lt2usZS!VymKu*YJ_Oqd z6$j{-tI=iubM>9Lv<5?-kLA$nxmv`GPiJG2r9OFyyi*%Y?<#SzWvhm!p5OHfZw z`w%{C$BlT^blK(J5W}09mhduAO`lK5;&mPgWFz&sbS(+(f;c(&>MaP?kaQ3LQz&MHN!`s&^a6{*$an^~mpk#t^&XVnMdiVM{*`7$H z<)gVHFR8R`-JQLiU@~G%Ae8Ix?uJDL9>drZqIosksQLH(&b-uuGe4@yI93@mi0$; z!!9^MgLmT#!~RAgsoS5}Jd-P=Pz z3c_dAVekK|I*gPWnqKG{(sl^%HSW}y)@#L`LPM+z+1an`=y$_ng+?eWC_pCY6ovS_ zken_tUuZ!S`@a{MiT6fkmCH0c^r^yB{a;zMws%NbZDT7WCVIm>nl(~cqcrRCDC<>|< zFJ@i8+-+vj7cjM~cctwR;`+Ix$ZZgfU-ilD;x2C>+(M*Ug|>g`5P8r2w`x$!Mfp1c zc`mfMz+8j|ePwn)L0~KXuT^7tr(b26#y|H<=gcU|3QZE+4Zw%2PW%LHd1a!)@R~cU zVn{|ok%x-6A6zm%ed@&tXw%xYPdz;|3xMwg4;219 zA)C37GN0gzE1xGn910#W?X)4=yoNK~;bz0=t;@%c&+LXiW|CPpYzijOkw|wS>AGyVI=jD3-c0RHV z(kID;bggn00Pp5xLW#rularqGUr%SeoswAu_1_t9nK8WJwjR|a8E8(Wc}Tk4Z0l^& z+nKM@)n2q{^EZOGjWo!Dk43)X$^@gx3IFIN3yh?|PSUjS=$T2p&p@e2U$xjxl$4Xg z6da>Uye>3TPRHBXix1zMTcSt{rK0H;xjCs^aLH1tB)u8&RNo*)1S!`-3~ACTjv_@R zbH;QD2W#Q8q?95pJJNcbnlfXwHl3p)*?**O`Y|u_ck}k)RPGluFG*+_G?@P|N#6|H zt7MWN3(5L&!N(+w{QGMZUCrhRofcdTa%3OGzNf2iFt%YN%*tm56X%BxT}Pw$*3;?3 ze=Pc;=SJswuFe}wQw6dsegpH2VM+SFiYK?{Ropa_xYh+_sW?q3&tLA_e1L?hT%bHZ z^jk~V(04Z5Gk+W%o;2i~c3j&qO>rgZBZg9EOy8!4-l)RU^OCD)B#z?-W+C(QN~EEO zeb2yb_iRn?a_f@Of;%(8OvMW;lI!jQ71+maKV3t85*|@8@vakAkhq#nL^^xoZjpu!AvN^|(+Oypbj9xBMva7TW`<4q^=%!P0@+5((;6gD%v=!lQ*wRD28{RkkCo# z=^vHt^Z8+{5vH1Z-sD=*FN-_K_Hc6v`2Ug-TbwmR?STZzV&cixqbHo0GU?8oIt62L zQBl9n|7*>PxTI&=LLwt3g(KpkT&e8)lJu^9`=nW@E3DsEm#9R&%Dl$U`QSu!&@=6% z8V19oILA(!XmtE+D!FsCf{Lj}=f~Zl)_pn^lg@)io6<)6t?or#xRkUV1cQSnK_RIo zd3K6|o}O{nTklZ#J|9S4pI@jg^!&x`zwHz1o)vGLt=cAjoLs!5vW33;R!xelJ;k}3 zu0a+BM5qxlDwBAKmmrwp5BCi(S9wD`bBZvN&1r;vAc2{12uGiOTy%8Ttuz@3vf&Dr zLkHoDS5i`vzDH8hWM6asRAmlVNo8!RR@`+s#`Q&yIiB46PbKWNCRZ$6HA-lPzcg;# z;Aq+?H*vA!L+Ncjxr-0Vn3?*~oAX{e%D(4J=Sd|s2P&rC`c`PjRLJRC3AQhaFI+j`rZ1w%eT@r;bqrfk4hcQuAk(1!k%$g zDO9ymsN;smoN0A;#|{)3FA+=fyZN`4UnC?&B1Vc`AbN0!?auZ57&jG`X|djwYUBdh zsizId++AH&du)=?I8dh`CML!|xcClg%LfDn-B)JRrKWG!Wz6bdxr(OpTKxm@>Mx9{ zuhUl3kI+5i-#Gq6{U=rZnSrLhi=}%~QzyNKt6%#W^sW?_5}*&v&AAeOl=6n&9}f;* zgEME&;DW9sT2<=W<>ku7xSs23AC|3pVoc#UtbZ=cUOeviQ1mjPdRfn6<(lp@SON_c z{xhs|2uEvnf?^U9F&G4aepY|$el?;%s$Cw-kLLm56(oU>OR-f{`~})++*u^_qw;89 z{yDA{Fmc)uajN%LZ`d%GMw%0J_d>>7D=kD$TqDE0>OCWI>cDIHfIcf78r8NGjzI6c zK72pdlZpjKbk-eT)h1qg>HoDH4*=`LVN6Ew-TOp-McsO)J8#5T=$5}kd6Ua` z>rgP`+O;Wku9NTbOG`@u2LtB>D{A~7n9hUEd+yvhn9jmP`p1v6iSz50isR7zqYywe zh1Y9uyib)x7qi6rgRKoZEX8>Bepa>hnz}RHSMcgdd9?es+{LtrFZLFl_#(y4&I31W(cj^?irV@T@Itxikh{=fZc&ST?l zyrKjC-$g4&n%YJjz0-4FShv^i7n#6P8QGZ~ZSwwIu}N(oGi`%)Qmf+Fg}@k7O2_4_ z;=k?5UR{Ei1V#!(BPd2#LlFw!pg}58N6C~;IT#llxAA62@O32lweuBGmC8)AJJ%De z_;WAs(+aXuDVTN+p5c9-H}bDtF?x<>IiHn@cn2t&L(T^_?Wew+z(+!K6DA7d9Njz& z-#48vFx(O%PBw!+oeJv416NE3!!tH(v!3yWJ@2zgF$l`6+9B87q{T_>_LtTNEf>g) z=0j7Hd=t-3YjaRx?KzkzFgnLtjmr0!A1o)&Vz!ffVs_5-GoS)p&~WpFX~FEvQ0TJ~ zy660hv%}^$%TJ2M>qrECIK@Ss$nrcgoy3qSQC9O8BwZfTfypH^KOu^}yE5Ujcznj} ze9B8`^^0Bex(H`j#!w%ne41_iz?H`-x;@#DH~U2?cvsH9f(00HW%j9~2y5rHtz=}g zHUY$!OzZTNCf#TMn8E(jr3KghX1Th7*A+-{{}e5J79$?0Hv0n{eQp}?`^VoTv2_WN zuf`SWc_mfS6Tc@hT05^6D>b}X$=h=FWtL6O+ek?tf@D4W#1Z>5jrc#D4Y2?5$f3I+ z73>!>Z}UGro_C(g8XWrD<~p?U*dd$sQwIRCyforGamZWeVX&0@JTCsnr@ohFD8K&% zC^Kiq%u}368vRnHt(iZ>PU?qDi<_sS@Y!*4pteksbZHoS3OhwE?{b+1Lp%G%k=}Ib zTrqb?`tpM34RuLcs@q$0XCF8i_I>9pZXCTu(e^d|{2R+z8++oA$u!zK(^vW*V0^0y zQpYKde}z-BtTVIo2j%dgVa++c0O_{8I_$UKTKwgeogkS){)Hy&o_`78<+J{!QcE!4 zXH`=(x8&Q8s4{q(s^{2N}P%S%(!V}6*gagPR5-cVrCf~k)N7a#vS)?pIJuocn ze8t9%8|zzJO4+p+ zeVpi&PXG2TqxOXVh0vlrz6 zHcjW^jtm88Y)mT#rAt9xerUfc;mL&Bx0F-y->E#KI+2IYf)|f&k)lh;Lr@Xe`fA3Zv5EvB%k)t zQrY7-H#)+$hhxW%70h73Gmn~OI}nc3(;szbvin0&!hXwe8Hnv9{C~jqo+A{>E-E5%cR-2ZnXkLE=MbKLU%cT6DYiFbz8& zNJvP4t_*^A-)GO#oOdm3YMknq_;z3@H|=_GP_=I91>fVO)&6ROT*rkQy$)m_<==b3 zPh@JXB+=95@_z7=)J@1wPWLCxUo$*SpNYc0v329H6_zBZTyZ_@~#^`Q0hGrQvS7{&{eXLwiqzy3p2JyPYXy^%q*F+t6Sd2vUv#mzp<i@oOA1U_5ba4i86+y z^wh%L0^f2s&D5Pf-`;umf=w-HrGS}85`WL5)AKiMC)&-Cifc)O?Otw@?1J{o`QLIZ zc*cv7$W|_V4h$+sm*)#?Pd7Lqf8h(slp!qV&ki5UW?B0~!IvWf+P+PfRAz@u5i=}3jp7aDD< zGU*i?Te@vaG9e)U)xVdtYcB{$`U+arNTZfe`pLa7Hak8yrdu5U{bh(_`W_sGZr~Q0*^0w!QTf=(Y(u~0JkK3azR-&~GBgC(5)d|zIIdDJ2RBzmb;$=W zL4E;&!jckGAey1PLZ4DZT-+$EUp244f0wm;IpOR#U3G(pK(x}pMb@uriXE5l8zE6C zxMRnoPH4^g!3;=IdcA~f29Nww5Y!XF_2vvQR^w(6^Gbh|{r=dh`K?E+acAzo{a$8n zE+CPxosDmTdU+|*HXdNo&p?yaCGbUazxkf1BMQ*m+#~m>Mbry|Hd@=yA^aPFY;8E( zra{i^Uy@%wP1L`geiKA}Zw5>A58Fdf&j&E7p11U~26of^RE9y|xm?<4w!hF8z-97> z;|XremWrR%FPNE)*ix=9D=*J`A*gEYap#fdsykfLAxzN;VlI5>6oM+CN@aw>z@RM} zElZm!g%w9ob{ZdpL8APD+ilSXjS?bG_+o2{0rKrjl7p_@X7%dDi)R@31o>qVSrBOc z@9u7VJ^i=S0Ku?P^-Y7EFM||xVJX+K>A$(*x=u4R-J7C1zatPdE2JJy)1Wy4rgr1Q zX^P;?oF@=88$YaBI{mk4cz>r2IpptpdSMnSC|aR0L9%ums$#puenTGcXN?{E^8JhO zpq7*!I~iw-V(l<>F))_-XnqAK69|4vr8j%Ekj6yc@MU{9z3a=FWyE-jmy$UhTclEZ z$~gaU2-^&@Bi9E8H1d#_d3$^J_-#{jC_~!^c>eqz0CS=1rlxjA^oneh{t9Tv)S)dypQkVQ zRYgkH31!Z|fTagc0x^>aI+Hg##ZASr9EsfkcdxeJ)q_DcbX$=w(QLK6mL0Xa(qW)#4QHk2bV zy&S?JhXbY<><$da%$o#g8GLpmh#>FWNK4z;+&tW0q{N#B6C*&M9#At|LG1}NdZl?M z2J+2`n3QHs0QJRl5~qRssF7+yx#D_GL}L#f0yVfnsIj8HjF;?VaD4F-()oSX6BcPQ zC|J5P$DtJeU04h93q)`AHq|Q}czVyJdhOGlKnb&3kdT_-_vlr@Fd6LYiwBS~UK3QX z<%|-Po7U{%fbYbOyH9Vj6MV(E+uFv)plwMbYXv6k7z*2{O5@BCA3?CT5GyN$gT$9G z@K@6z97b50(8*XdU|#)5y^e&j3oFDukIuOYv8%x0nM=&Y+nZ6;IXGAoIahks_3UTC zzJeS_*kp}Lss`e!>Dj&KVh;JXZQCFwG(giH$ctS!7N1RQbhfwe?(aW1kyJ_mqE~tU z`EyzGYeSysB!JBz%}e^8bb1F&6}`%(98u2w2?}drTvE{f`$Tw_^RJ6OIf-gETtbD4~-%2DGa~IrZ@2Ltrp-EP&Jp778VlT31?RHf|iB)Yt^QA@{)R=% z7A?m=Ze6reO8gxs1$g?~=9v11>T23*+*5z<-EE?+)h3(cTq;15#2q%dIj+((6ONc~v(oe$@Bp%pEfAU)f~lrAuiZQ-v*!EY99MaE|il zOJ?h1VyB-S_rB?MJ%Z{d{SsA|k%V;SN^=Vf7mL<}?B_NH-}VQHRd(w{uRfG{ciDc* z(cILM&xJ;dX!lTVc}3YG#Q4o;P-n86I;u*1?JK&)+x@z{!#a;0d9$z8DDg?^lggLd zPuG26Q{&kXk^R*yx$6EOM%UQR*mkp3w`y$2(=N8}9I32)6G4&9rnseXKx))B!`i;; zrt;xp&)<&vPuB^^n6^CD9eTJ&Z?#zE)AdXHu0Gg(f64MX`1lHiOc=C8=@zWqx^2g` zGy0dtJ+kY`QnHHlcfO##+wrYaAmK>TvNg9JdK(r5{tR5K7yg7RC)zDsF}VHqIFlTi zn)u@m#dOW*LoO3(uO<}DoAyz~FH_5DsAdRE$c$F2;^)+iT-~*#h!XV* zU#vPX@hw^N{4u?V1IMC-%5{WJ(mr8hGyc$}7}tI~P0+$F$m2Da>$zi+AHH`{s$HV| znR}m%IWN` zlWA84zV0k@m-Sg!SE`$6+TGSln>R6DQ|qiGJj${Es|xE*ePiWy&+4s)T5pI>46}5N zCr$LEHYyc&$2(XLJD*dWXiO3fRHXZyXfe^#+E{7T-)w9>Sw_aZXFqr9jr}K>%1+W& zxuxmfc}Ds3MS}0Qop+;m@|-%ddi}d=JDcnuuId}7V*PoSaa+EV^YgQ`0#&1}9LuUd zJ^Z*da#82;@WsLbZmYI`3TgKB3f8)BwC*p*jn=@?KpmiZs#K3DkO!CdQ-;G-vp zdu>m7q^@B*waCaZWKG1wgK5QKtvrf*vYId2q|>e18tHZILE{O&cH53BnGrQr7S3_) z;)bEMbQiB)55JU@m+!MpauBOQX%gW8qH|z>7b2aHa1_XvsW{M_$rk=xAJ=O#?WhbpQhnralaZM@X_bnlFf{*!GFxw9cKA(*{`(L zD0S83xXVFyHQ%un^nHK#?hT*3TKZ!P4}0;_AFHnFT{{zX@tfYH#4&A-U6GMlyK=b*sUY>q*HfrR9dlF(a0dZX?+4D<mw|Fr%IK_4#}pc^JVze zzCUnAwA794d|O(%6wmH6{7)Sth2kh)-8U;=*`HdtYcbpC0oK#5o~#Ts>wMa)xK1^> zD^Nc6y?L!}&}HhmZr#Kws@5adsTdO&?4Yr`G-_vPV6>uR zAl16Jdc0z8U-!7!rB8Hi9F2`Kcz^huXU&rnfujNzA6+sOb+*`-ETMgL>16Yjn&Zi(%xUrkPN!ZdUhoDNZqpu{`YKZ@(x>__dZW_qu-K7#&bw-=e>kB3KzGG{<;8D z>CE9Q%1#Esamj(bvb%pBx$Mvu+anwB&8(j)CFp38OW&0Z@-~83K3(FZDrhmuid)?9 zTF=Pl%Jx`esj_V8VMRX0#q9%}tQzFKEN@@r@J8#<8lG?r zPYNy{HN2Od(tq@95rxNIwZ9IoNg}&liZul89Ee|WI9O6Vg(>Nb@O?d+Dp4-^Q(Bq> zM`S$e1(w!CJQqy8v6?I5gwA$%&D9?`JICpmw3RxpH(z$vxzzV|k>-QZTss}jpG?Ca zFXXgGvVXbm-&`2`@vy&u`WJ?ZH}x^KuO=`5UVowO%U%iz6^BgrNlM$zqC@n@;uBP2 z!e8F*JV+AV@*liv>j{$fU_^n8u%&@U&~6&X@|{Ht6{SMawy^QWJgYeTVnRoPk()781! z;f`6QqKg+Tnw(s+h;XZ!+gZOoH9S^NwrCN}YGR*Vv`A0SkXuLBP|ZMG#lTQa-(db< zc&4^lk8+*TEgRB1Iodbv)Cv64edEPDiGnvd0`JR%0?ZfP4Od;Nx>DUs>u+4=p)F!@ zihYYMR99QCrWg~VxTd7o&d{L!{)thx!3OzNPfrSJJob_n9O?f|cP+zpMK9T>XZcL+ z?~h66=lSi9qtxB#J}9$ehw#I%_2iA}A209gwiGM;oYM2UozpHnVk4E*&yDU%%g4xm zF*ewxsDb|Ra`iUB_t(aIHz`FVTBes8uN=DZc%(6Osb-m&+OEzke*{N(y&d!Qd~=q4+M>9s z#=BcxFX5DH$~OBN6OrtY#$WA9;s+jb96Rr7+j;+t(wa$+zqBs!jfB|KsO$Wdi&mCz3Dqizx>xn# z==bNf(U;9n7%`MQTl$1GG^Hl@&ALx3R_{NmcsQFQUUnk)*ZzmKTUSwjcUbw|*n(Xk zfTrKHCUWIb%^zI*KU3$u;5-=OVROhi?5^#p!|!Uf-u*Ow7@1R|ennyD&9n+Z&P7Gf z3b?pG1qBXl+QoC{Q`g(-B>`G%YxgbLQ2NMSciF?w;nYHW0re`sY&rOD?cM9$Ijqk4 z?3`gu?Up_Zz75$NBHfg)FFYBrVcNKoQ*epf{VRn_^e^vx*+DpA>k6Nts~2Jjdc z?dmikCDGG<>^Ot zs7Q{rAT@OkhG^G1#Yl-SeyR&4zZC&RK%;&NW@-<%c7h9+E1&J{vW7`<>)!OL(YgLC z%&X69Ywj#;&U67K<rdnsQa)n2L zff=-08!JEGjHUqhq1hhGYpW=ma8o6ooG|{i(jg{x^V{~X;Rkutw``k2MRq1QZoJz5 z(zUD3fv-O*>iKh}C3K;7XLhQI%p)!%Lu5OmL06#v$31xT+kEjh^o`)!#|^MRIpg%i zKvV{~7Ts<%a`Nd}T&YNm{x{F49N}_6%{lSYC}2^dVJb@3uRnbN^qot_JItUTq15rP ztX>3XK6=@c+MOiLbogUkP#o4Wd4p&{CLXO__s8d-T}a2#ugi*>YJ{I#@No0x8K{_+m(jJ+k%m#3_!Xg$ zHo7f43Mr;!J;7-DR@1y-=0GNwwfN#F=p=!f&mx+_nGv5v=$nze(cv;0{6RD+(Rlc9 z?CbWA4{(Jf2A);7nbN&=6D*LCb)=?9dlkwh&1e-?0G|!P@3IK$;CZJ**UTb3V3C;B z9H#YNCErh9{v1D96EQ4s4uwDuCFRvynQ^^TdYNju<<(4bZZv@z6Wi){J$-Ud1GAKD z8J#5?8aL0Be3xy;W_=G{^DuIHbIY-?Nqq9VaP#M~*xL;|jirK8eUE5xA4#HX1+k6z z2aoM2?p2(8Wvxo>N{JO|)oLpZ^q%$@#cEp{7oM;Eglctt>lc=0HZN*ruDAcdhw{aA z>02D153kA^SJEZRhaGz6%eS)aLe`e`MB&<9N$+_s7!yRuCYmw?lx4m{Cw>`Vt7o^SHcWIm`1Ls@t!BpBvXjAGYp3* zWhGy$jJ<@UrfxCYWqk#oi@3jvR?eJPCQt`|sfpwEcM6E0W)*w7#JZ4N`8*UT zIjb!6j18PcsZ=QGUB)b;n(x5S?>0>?GH+EruINjBu2`UyF}O)sqb+Yn$KTyBC&-vT zHFNa^d756+rgDlZi8SUo~~j5MU!G~#Xx!yS~RRe)`(Rqi~JYo}5$30|$H zw2E@h`jB7~p2Ae&Hql#@w9_I?u5!tP9#^K2UF7;h-IN+eUDtv0au=k&kW2-4{!~H_ zT1wP1f6YbYV&B0vR`IzryF4;C)}Y5@Hp*U2%92Pwndzrla=oj!5@Q)b2Li5TajW7{ zhN|GVS1Kd@xc2lN{%BH<6V|qWj1l}ipLKbGGW%WMtN7WWEJGcHLiO(Lh>Tbz3ss;4 z^@Via*SL)B(wie$G#w@|-wWljd5==?lGW95c9l=K5;t=6u8phmQ#p?2?-D<$vW*p= z#fv}4Eo>A0)-L$1e4W*|AJ@iL^=0w4L`#p;rKBrd*U+MpfZZ1M3$s?A)i+>)Fu(nmjQv1vnRmE))hDXh zYTrC98?12S%u(!wUof#ngZVMEe!&mWJcF~NabA6k`W`7R&rD-?k&vn;naCX7!{0pA69C$qfZD~(1 z2#Z@+8*K>Izk3Ow+>;+NR_>&|i$TY0Qk&%{&=Mo*%zHH|d!QMn*pfmXYSW-6Gb1uo zO>X$eyw$$D{rYMIg`O6vELjacA!T&2=-uu$h6slr8xQ7#>X@npR+D<3U0~F0)oV}1 zqaeXj=x@2#=gfG~c0Z#K zS6&%;f`$3OJHS-@gY$^9bul#m46bMC=u;7A6;F5;sm^ToGpj@=%nUgETClxrTDj;W zz3KT?3$>5-6?jh!HoSWu(%+t^9wj{l`UO?vU`=WP?g)^ccuUc8OYnjhX* zWd35g>?>X<28jNras>|6KVJa8)k6b;h<+>QW^L}S>f-3MuUc4iox?CEUeE&CCV~I= zoX6SM$>@{|Oa|C7_-HG(bv-ZAoek@g!?qx6W^U}IiA_OHCOD;qLdUd zq>M}?-F~QSZ4kGuvifC>)e>??t6l(?K@7BXx1-~E3C9|R@hvPFOfp=xrAsn5%*b0Y z^>4d(20Sf$jGGfo8YHA4Q61%MTj-h0QK)Uz_Iz_O(yMIP8fWzJoPNGDFAh|S-oviA zDLQdCIPt8XS@g@i$gtNNanD!FpmC?WWSL4iT7e#^$qCgLX}m)?^FN#pxw8F?oBW zbaZOfI7##m6()D&*rmlutem zhsNcDGk2pW?=ADT4hrXN8_gz^R<2%qhr%QOwhhAw&vMCWQ?N2@H>3l(TdnAOnyG*b zIy8(!w>r6)!~f&f?3fXoVNOU;7gp8X&+xZVmvF3)R>0{_yv__885MW0bk;X&LY&5ZLO^)e6~*~2qA zH*B4q&^9}p2xWXZhUyY$SG{MndW#=k)+|||dYySMc0|g=ZQiPLq;VbLo%7|4^%p7N z_nQQqn--ahlcSPUdIt@sRXmN9svPtyaXg>%+l~>3xwgG6n&wt%8-h>m)CO`r+CQ z21Ql2rkL>5gBhCD7eg%~=v^+-HY;mQcgioPZ7Fx>1u0RSU%0}@jvGV=K_g{EC+sAL z{$N4jvV;*!C4q57O)rdW)6Qyt)pnm`Ut~1l6&C4vJpMKB)=nh9(u0hoJZuaiJQs1o zI=`Hxz!%~Ycq61C9MAf5G6QqPR!vwvM~1HHI?Li0jX6@Wqe{U7nVm}2#ZjwKS3Fc8 z8S)TmND#I$#GG#J@ncA6!7DoIMt+nw+OG^xG5kcP`~p$1vgpPAr0}r9st6-UppUeL z)8?be-m9z=-i*eF$7R((gLVV%IaYf3kmQc$blgCiB5reAO2U8?Q3%8n5eOT_%+Yi| zj5tgkUCj5gA5A(s3R5Zw_{jh5M_81aNA~|+3TZaxo8OM(nzK;X?ev4tD9N# zD8L<9hUy1u%P8%{zt)vieR98%+kdIoC(>KETPBu8njSk6Dz&jUCgT)(Ie@dgy<))h26MnMNS!{2A2`P-4QHCT!F7hW67emSz|2 zHR`mAIS5uhHKSzD3cZk}nwezWF#WMTWb{7n<;Xd#7zTe0R(k?Hf0eY*_O)5ca?$f= z?}b)iT3mlD$~El4(^70f)tgdA*%e=ayDq?rGoDr~JTu@z z;FN>h*{x~Tg^Z>_m-~fGVV8U%TVH+UO@t_VnRe`CtER0&X5 zp~wGYf}_nB2(3Sdt{a+~&xL`Qd;{b-!lQ8sb8`CsusrOF?V9@|_^Y!6Vvrhs<;u%U zsBfhs)0<(&_zm-&3DQmVW<3$4d4u4b(Z~ywY>W=o7-)sPcn}Zz6y{Ae`YNAH&2GN} z;#JzDutpe2NcQ5Y1<_UWvpW1RC{@2dYhOOLJM_))#xLPmitIW89KKZ2A@=%r6<*ZR zd>m=xZc;F%NK~b_RPh!hFtz6M-?>J$Q;iU!)Lpb5&Z!u|S(PdfH}a|Qt^Oyd%cWPh zlICq%!9{pfI`P>w$scc;^(3~`0ADexNmkbFlW^1NSD5@5N$X4t4{z-qmocUkBSl$rmgsfW=}dCunsGg}6Xh(u|uhN~H~ z=c%Bq%;?jSi1zf`9Z_bPX7gyW%^w7H^6AaT{aJBiD&6zXEtbwQ#|1qKPvnmf=Dqz; z?8QP6=SC}Au@`%N5M@gVuCTtPN4CwZViIl3wRMx(C%dlsmuCW~lYQYK6TCa0anN@Z z=3LAtb}TW#^eKi>hC(*FG($Q|6gh~(ifNr^Q!2|r{jrOxu0k5OeJ)Q^m-8r<3)=hV zrP)g8bW)TBIZP+mQX*KWTjzSHv{E}|qH-`4RsDJ(^fX^fh1!G_C1iR9x_{-YTkH;v zF4YxpyML9q;H%+#Ppf0~KC0*@{VM;Krlm(0)%hvQX|vfVO2XpM&7U(=cG5;XFDE#z z=kn9sPZC3$KjZb?%|#?Wym4j29==ji^|k!+m&1Vo1(glBfB8Qvu%`Y9xmBPuVw^oF zg%5*l@1239qXWX+0dYgq)5#oewATk!uOA02+xFb~0en;q=(o7XTC<~rKnK?n`_~R9 z8%90qtzrObRB_tY9EPxVbU=1$;}+qT8K9XKaB7;v=D@q> zXATH(J8Ls@ILCn$`#bwf%1GsjV}F6o1)Le39t1jfjMfF{wI|PS+WyP_cs$3EC9a{%uWw3iAQ&0CUpc zNMS|Jb+7@XqHzFMvq!W$BHF%=NNMi4H`r$Z+MgjL&2}1X-{?qbUXZyPlz`=n0WB{c zQ`7;7i2um;&l1djARX)=4X3Sn*`hYUZXjSdJdSGyqT@d}MVP0fD*}EHo(DU8$eaom znYZZ$Xte;6<(PEucn@&<3q%@6`^@2y)3x@MPr8FHa-`UNry~Uydh)o@)oV!?^oB6SW_e zNc~Db{K*YDEL-|-Fr;36-xKwt8t?)?;EKJ;vBSq*IV6f6$uUPd9@5<4gF<%A2pH~a zf$`zE&f)TZ6BDU>r(6a3ki!_2{su!DdS)55Mw@`5`aqgFu5+F05uN|ZT1Rv~lDm-V ze7ZF;)Q^z=Nnl6F2Zv4{Qcfr1YWy4W>1Dv_WFpOfLq0uEo=yg9{TuS>neucpmG-|O z@Avutr3dMB{tbD*`y(YQYGpXb-ZK}wg#*G2hJYPZcZU#3VS+1g zQxwqNb{yhYbrQmT8bn)avHYq52(-5yFPxb!pzfCi_U2~RFb->bn58)vyOV?ENinXr zt5nh60D<