commit 6a4a546f7b7e60357c88b3cf5b0073ac1f6891cb Author: Grégoire MUREAU Date: Tue Aug 12 10:54:56 2025 +0200 Project 8 added : API + article not done yet diff --git a/README.MD b/README.MD new file mode 100644 index 0000000..399a879 --- /dev/null +++ b/README.MD @@ -0,0 +1,140 @@ +# 🚗 Segmentation Multi-Classes pour Véhicules Autonomes + +## 📋 Description du Projet + +Ce projet développe un système de segmentation sémantique d'images de rue destiné aux véhicules autonomes. Il permet l'identification et la segmentation automatique de différents éléments urbains : véhicules, piétons, mobilier urbain, infrastructure routière, etc. + +Le système s'inscrit dans une chaîne complète de vision par ordinateur embarquée pour l'automobile autonome, traitant les images en temps réel pour alimenter les systèmes de décision. + +## 🗂️ Structure du Projet + +``` +├── notebooks/ +│ ├── p8_notebook.py # Notebook principal d'entraînement des modèles +│ ├── requirements.txt # Dépendances pour l'entraînement et expérimentation +│ └── content/ +│ └── data/ +│ ├── new_images_to_predict/ # Images diverses pour tests d'inférence +│ └── test_images_sample/ # Échantillon Cityscapes avec masques +├── utils/ +│ └── utils.py # Fonctions communes (prétraitement, chargement, inférence) +├── api/ # [En développement] API FastAPI +│ └── requirements.txt # Dépendances légères pour l'API uniquement +├── .env # Variables d'environnement (MLFlow, MinIO) +└── README.md +``` + +> **Note** : Les modèles entraînés sont stockés et versionnés via **MLFlow** avec artefacts sur **MinIO**, pas en local. + +**État actuel du développement :** +- ✅ **Entraînement des modèles** : Complet (notebook + MLFlow + MinIO) +- ✅ **Fonctions d'inférence** : Développées et prêtes +- 🔄 **API FastAPI** : En cours de développement +- 🔄 **Déploiement** : Conteneurisation Docker + NAS personnel + +## 🏷️ Classes de Segmentation + +Le modèle identifie **8 catégories principales** : + +1. **Route** - Chaussée et surfaces roulantes +2. **Trottoir** - Zones piétonnes +3. **Bâtiments** - Structures architecturales +4. **Végétation** - Arbres, buissons, espaces verts +5. **Véhicules** - Voitures, camions, bus +6. **Personnes** - Piétons, cyclistes +7. **Signalisation** - Panneaux, feux de circulation +8. **Mobilier urbain** - Poteaux, barrières, abribus + +## 🧠 Architecture Technique + +### Modèles Implémentés +Utilisation de la bibliothèque **[segmentation_models](https://github.com/qubvel/segmentation_models)** de qubvel pour l'implémentation des architectures. + +**Architectures principales :** +- **U-Net** : Architecture encoder-decoder classique +- **FPN** (Feature Pyramid Network) : Réseau à pyramide de caractéristiques + +**Backbones testés :** +```python +# Modèles avec backbones par défaut +('U-Net', None) # Backbone U-Net intégré +('FPN', None) # Backbone VGG16 par défaut + +# Modèles avec backbones pré-entraînés (encodeurs gelés) +('U-Net', 'mobilenetv2') +('U-Net', 'efficientnetb0') +('FPN', 'mobilenetv2') +('FPN', 'efficientnetb0') +('FPN', 'resnet34') + +# Fine-tuning sélectif (encodeurs entraînables) +('U-Net', 'mobilenetv2') +('FPN', 'efficientnetb0') +('FPN', 'resnet34') +``` + +**Stratégies d'entraînement :** +- **Encodeurs gelés** : Transfer learning avec features pré-entraînées figées +- **Fine-tuning** : Ajustement fin des encodeurs pré-entraînés +- **Entraînement from scratch** : Sans pré-entraînement (backbones par défaut) + +### Stack Technologique +- **Framework** : Keras/TensorFlow +- **Architectures** : [segmentation_models](https://github.com/qubvel/segmentation_models) (qubvel) +- **Gestion des expériences** : MLFlow +- **Stockage des artefacts** : MinIO (S3-compatible) +- **API** : FastAPI *(en développement)* +- **Déploiement** : Docker + NAS personnel *(solutions souveraines)* + +## 📊 Dataset + +- **Source** : Cityscapes Dataset +- **Organisation locale** : + - `notebooks/content/data/test_images_sample/` : Échantillon avec masques de vérité pour tests d'inférence + - `notebooks/content/data/new_images_to_predict/` : Images de test diverses pour validation + +## 🚀 Installation et Configuration + +### Installation +```bash +git clone https://github.com/GrgMdmn/OpenClassrooms_AI_Projects.git +cd OpenClassrooms_AI_Projects/Project_8 + +# Pour l'expérimentation et l'entraînement +cd notebooks +pip install -r requirements.txt + +# Pour l'API uniquement (plus léger) +cd api +pip install -r requirements.txt +``` + +### Configuration MLFlow et MinIO +Créer un fichier `.env` à la racine du projet : +```bash +MLFLOW_TRACKING_URI=http://localhost:5000 # mlflow url +MLFLOW_S3_ENDPOINT_URL=http://localhost:9000 # minio url +AWS_ACCESS_KEY_ID=your_access_key # minio login +AWS_SECRET_ACCESS_KEY=your_secret_key # minio password +``` + +Le chargement des variables se fait via `python-dotenv` dans le notebook et l'API. + +## 🌐 API et Déploiement + +### API FastAPI (En développement) +L'API utilisera les fonctions de `utils.py` et sera déployée via Docker sur NAS personnel pour maintenir la souveraineté des données. + +## 🔮 Améliorations Futures + +- **Prétraitement adaptatif** : Prétraitement spécifique à chaque backbone au lieu de la normalisation générique (division par 255) +- **Généralisation des conditions** : Extension au-delà des conditions urbaines de Cityscapes (météo, environnements variés) +- **Optimisation temps réel** : Évaluation et amélioration des performances d'inférence +- **Résolution variable** : Support de tailles d'images variables au-delà du format fixe 224x224 +- **Transfer learning ciblé** : Utilisation de backbones pré-entraînés sur Mapillary Vistas plutôt qu'ImageNet pour un meilleur alignement domaine +- **Segmentation des personnes** : Amélioration de l'IoU sur les humains via data augmentation (IA générative) +- **Limitation du dataset** : Les performances similaires entre modèles suggèrent une limite liée à la qualité/diversité des données d'entraînement + +--- + +*Projet développé dans une approche de souveraineté technologique, privilégiant les solutions open-source et l'hébergement sur infrastructure personnelle.* \ No newline at end of file diff --git a/cityscapes_config.json b/cityscapes_config.json new file mode 100644 index 0000000..62b5034 --- /dev/null +++ b/cityscapes_config.json @@ -0,0 +1,63 @@ +{ + "class_groups": { + "flat": ["road", "sidewalk", "parking", "rail track"], + "human": ["person", "rider"], + "vehicle": ["car", "truck", "bus", "train", "motorcycle", "bicycle", "caravan", "trailer"], + "construction": ["building", "wall", "fence", "guard rail", "bridge", "tunnel"], + "object": ["pole", "pole group", "traffic sign", "traffic light"], + "nature": ["vegetation", "terrain"], + "sky": ["sky"], + "void": ["unlabeled", "ego vehicle", "rectification border", "out of roi", "static", "dynamic", "ground"] + }, + "cityscapes_mapping": { + "0": 7, "1": 7, "2": 7, "3": 7, "4": 7, "5": 7, "6": 7, + "7": 0, "8": 0, "9": 0, "10": 0, + "11": 3, "12": 3, "13": 3, "14": 3, "15": 3, "16": 3, + "17": 4, "18": 4, "19": 4, "20": 4, + "21": 5, "22": 5, + "23": 6, + "24": 1, "25": 1, + "26": 2, "27": 2, "28": 2, "29": 2, "30": 2, "31": 2, "32": 2, "33": 2 + }, + "id_to_label": { + "0": "unlabeled", + "1": "ego vehicle", + "2": "rectification border", + "3": "out of roi", + "4": "static", + "5": "dynamic", + "6": "ground", + "7": "road", + "8": "sidewalk", + "9": "parking", + "10": "rail track", + "11": "building", + "12": "wall", + "13": "fence", + "14": "guard rail", + "15": "bridge", + "16": "tunnel", + "17": "pole", + "18": "pole group", + "19": "traffic light", + "20": "traffic sign", + "21": "vegetation", + "22": "terrain", + "23": "sky", + "24": "person", + "25": "rider", + "26": "car", + "27": "truck", + "28": "bus", + "29": "caravan", + "30": "trailer", + "31": "train", + "32": "motorcycle", + "33": "bicycle" + }, + "group_colors": [ + [128, 64, 128], [220, 20, 60], [0, 0, 142], [70, 70, 70], + [220, 220, 0], [107, 142, 35], [70, 130, 180], [0, 0, 0] + ], + "group_names": ["flat", "human", "vehicle", "construction", "object", "nature", "sky", "void"] +} diff --git a/notebooks/content/data/new_images_to_predict/paris_street.jpg b/notebooks/content/data/new_images_to_predict/paris_street.jpg new file mode 100644 index 0000000..5fcab42 Binary files /dev/null and b/notebooks/content/data/new_images_to_predict/paris_street.jpg differ diff --git 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diff --git a/notebooks/content/data/test_images_sample/original/frankfurt_000000_001236_leftImg8bit.png b/notebooks/content/data/test_images_sample/original/frankfurt_000000_001236_leftImg8bit.png new file mode 100644 index 0000000..57bac92 Binary files /dev/null and b/notebooks/content/data/test_images_sample/original/frankfurt_000000_001236_leftImg8bit.png differ diff --git a/notebooks/content/data/test_images_sample/original/frankfurt_000000_001751_leftImg8bit.png b/notebooks/content/data/test_images_sample/original/frankfurt_000000_001751_leftImg8bit.png new file mode 100644 index 0000000..62a6711 Binary files /dev/null and b/notebooks/content/data/test_images_sample/original/frankfurt_000000_001751_leftImg8bit.png differ diff --git a/notebooks/p8_notebook.ipynb b/notebooks/p8_notebook.ipynb new file mode 100644 index 0000000..38ec52b --- /dev/null +++ b/notebooks/p8_notebook.ipynb @@ -0,0 +1 @@ +{"cells":[{"cell_type":"markdown","metadata":{"id":"Jwxoidt4JieS"},"source":["# Projet 8 : Traitement d'images pour le système embarqué d'une voiture autonome\n","\n","## 🌐 Contexte\n","Ce projet s'inscrit dans le développement d'un **système embarqué de vision par ordinateur** pour véhicules autonomes chez **Future Vision Transport**. L'entreprise conçoit des systèmes permettant aux véhicules autonomes de percevoir leur environnement grâce à l'analyse d'images en temps réel.\n","\n","## ⚡ Mission\n","En tant qu'ingénieur IA dans l'équipe R&D, notre mission est de **développer le module de segmentation d'images** (composant 3) qui s'intègre entre le module de traitement d'images (2) et le système de décision (4). Ce module doit être capable d'**identifier et de segmenter précisément 8 catégories principales d'objets** dans des images de caméras embarquées.\n","\n","## 🎯 Objectifs pédagogiques\n","- Développer un modèle de segmentation d'images performant avec Keras/TensorFlow\n","- Concevoir et déployer une API REST avec FastAPI\n","- Créer une application web de démonstration avec Next.js\n","- Mettre en place un pipeline d'entraînement et de déploiement complet\n","- Évaluer et améliorer les performances du modèle\n","- Documenter le processus et les résultats de façon claire et professionnelle\n","\n","## 🗓️ Plan de travail\n","\n","1. **Exploration et préparation des données**\n"," - Analyse du jeu de données fourni par Franck (images et masques segmentés)\n"," - Prétraitement et augmentation des données\n"," - Création d'un générateur de données optimisé\n","\n","2. **Développement du modèle de segmentation**\n"," - Étude des architectures de l'état de l'art (U-Net, DeepLabV3+, etc.)\n"," - Implémentation avec Keras\n"," - Entraînement et optimisation du modèle\n","\n","3. **Déploiement du modèle**\n"," - Développement d'une API FastAPI\n"," - Création d'une application frontend Next.js\n"," - Déploiement sur Railway et Vercel\n","\n","4. **Évaluation et documentation**\n"," - Tests et validation des performances\n"," - Rédaction du rapport technique\n"," - Préparation de la présentation"]},{"cell_type":"markdown","metadata":{"id":"98EwoZLkDjzq"},"source":["## GPU et mémoire RAM"]},{"cell_type":"code","execution_count":6,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":175,"status":"ok","timestamp":1754980889028,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"N139rgMJ-u28","outputId":"d2736e73-ee5a-4340-b461-9b6ee5104a73"},"outputs":[{"output_type":"stream","name":"stdout","text":["/bin/bash: line 1: nvidia-smi: command not found\n"]}],"source":["gpu_info = !nvidia-smi\n","gpu_info = '\\n'.join(gpu_info)\n","if gpu_info.find('failed') >= 0:\n"," print('Not connected to a GPU')\n","else:\n"," print(gpu_info)"]},{"cell_type":"code","execution_count":7,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":9,"status":"ok","timestamp":1754980889029,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"KQiIRnlM-vaz","outputId":"2412eadd-5cd5-44f1-fdb1-d995bbf9b04e"},"outputs":[{"output_type":"stream","name":"stdout","text":["Your runtime has 13.6 gigabytes of available RAM\n","\n","Not using a high-RAM runtime\n"]}],"source":["from psutil import virtual_memory\n","ram_gb = virtual_memory().total / 1e9\n","print('Your runtime has {:.1f} gigabytes of available RAM\\n'.format(ram_gb))\n","\n","if ram_gb < 20:\n"," print('Not using a high-RAM runtime')\n","else:\n"," print('You are using a high-RAM runtime!')"]},{"cell_type":"code","execution_count":8,"metadata":{"executionInfo":{"elapsed":8,"status":"ok","timestamp":1754980889141,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"3evmO8AKQja8"},"outputs":[],"source":["from tensorflow.keras.mixed_precision import set_global_policy\n","set_global_policy('mixed_float16')"]},{"cell_type":"code","execution_count":9,"metadata":{"id":"Zr34mnLTcgj6","executionInfo":{"status":"ok","timestamp":1754980889308,"user_tz":-120,"elapsed":6,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"outputs":[],"source":["# ====================================================================\n","# GESTION DE LA VRAM\n","# ====================================================================\n","\n","import gc\n","import tensorflow as tf\n","\n","def deep_clean_memory():\n"," \"\"\"\n"," Nettoyage complet de la mémoire entre les modèles\n"," ESSENTIEL pour éviter l'accumulation VRAM !\n"," \"\"\"\n"," print(\"🧹 Nettoyage mémoire approfondi...\")\n","\n"," # 1. Nettoyer le backend Keras (le plus important)\n"," tf.keras.backend.clear_session()\n","\n"," # 2. Forcer le garbage collector Python\n"," gc.collect()\n","\n"," # 3. Nettoyer les graphes TensorFlow\n"," try:\n"," # Reset des graphes par défaut\n"," tf.compat.v1.reset_default_graph()\n"," except:\n"," pass\n","\n"," # 4. Forcer la libération mémoire GPU si disponible\n"," if tf.config.list_physical_devices('GPU'):\n"," try:\n"," # Forcer la synchronisation GPU\n"," with tf.device('/GPU:0'):\n"," tf.constant([1.0]) # Petite opération pour forcer sync\n"," except:\n"," pass\n","\n"," print(\"✅ Mémoire nettoyée\")\n","\n","def monitor_gpu_memory(stage=\"\"):\n"," \"\"\"Surveillance optionnelle de la VRAM\"\"\"\n"," try:\n"," import GPUtil\n"," gpus = GPUtil.getGPUs()\n"," if gpus:\n"," gpu = gpus[0]\n"," used_gb = gpu.memoryUsed / 1024\n"," total_gb = gpu.memoryTotal / 1024\n"," print(f\"🖥️ {stage} VRAM: {used_gb:.1f}GB/{total_gb:.1f}GB ({gpu.memoryPercent:.1f}%)\")\n"," return gpu.memoryUsed\n"," except:\n"," pass\n"," return None"]},{"cell_type":"markdown","metadata":{"id":"GmeKp_pfKK8u"},"source":["## 🔗 Connexion à Google Drive"]},{"cell_type":"code","execution_count":10,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":17924,"status":"ok","timestamp":1754980907743,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"zBTvEoak9GKf","outputId":"0662da7d-091d-4fc0-8903-d49e8ac2db50"},"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]},{"output_type":"execute_result","data":{"text/plain":["['content',\n"," 'unet_architecture_simple.png',\n"," 'Copie 2 de p8_notebook_MobileNetV2_UNet.ipynb',\n"," 'model_architecture_1.png',\n"," 'model_architecture_2.png',\n"," 'model_architecture_3.png',\n"," 'artifacts',\n"," 'Copie de p8_notebook.ipynb',\n"," 'Copie de p8_notebook_MobileNetV2_UNet.ipynb',\n"," 'results',\n"," 'p8_notebook.ipynb']"]},"metadata":{},"execution_count":10}],"source":["from google.colab import drive\n","drive.mount('/content/drive')\n","import os\n","drive_folder= \"/content/drive/MyDrive/Colab_Notebooks/Project_8/notebooks\"\n","os.chdir(drive_folder)\n","os.listdir()"]},{"cell_type":"markdown","metadata":{"id":"xLlwj2kGJwGN"},"source":["## 🚗 Jeu de données\n","\n","Nous utilisons le jeu de données [Cityscapes](https://www.cityscapes-dataset.com/dataset-overview/) qui se concentre sur la compréhension sémantique des scènes urbaines.\n","\n","Pour notre modèle de segmentation d'images, nous exploitons les **5 000 images annotées avec des annotations fines** (fine annotations). Exemples [ici](https://www.cityscapes-dataset.com/examples/#fine-annotations).\n","\n","Ce dataset présente plusieurs caractéristiques essentielles pour notre cas d'usage :\n","- Des annotations polygonales permettant une segmentation sémantique dense\n","- Une couverture de 30 classes dont nous retiendrons uniquement les **8 catégories principales** déjà définies [ici](https://www.cityscapes-dataset.com/dataset-overview/#class-definitions) : ***flat***, ***human***, ***vehicle***, ***construction***, ***object***, ***nature***, ***sky***, ***void***.\n","- Une diversité importante avec des données provenant de **50 villes différentes**, capturées sur plusieurs mois (printemps, été, automne)\n","- Des conditions variées mais contrôlées (jour, conditions météorologiques bonnes à moyennes)\n","- Des **scènes sélectionnées manuellement pour leur complexité** (nombreux objets dynamiques, variations dans l'agencement des scènes et l'arrière-plan)\n","\n","**Documentation**\n","\n","- https://www.cityscapes-dataset.com/dataset-overview/\n","- https://github.com/mcordts/cityscapesScripts\n","\n"]},{"cell_type":"markdown","metadata":{"id":"t4pOqGkHQQnx"},"source":["Nous utilisons le jeu de données **Cityscapes** qui contient **5 000 images avec des annotations fines**. La séparation entre *train*, *val* et *test* est déjà effectuée :\n","- Entraînement : 2 975\n","- Validation : 500\n","- Test : 1 525\n","\n","Le format Cityscapes fournit plusieurs fichiers d'annotation pour chaque image originale. Cette structure facilite différentes approches de traitement et d'apprentissage. Pour chaque image d'origine, nous disposons de :\n","- Des fichiers `*_gtFine_instanceIds.png` qui encodent à la fois la classe et l'identifiant d'instance de chaque pixel\n","- Des fichiers `*_gtFine_labelIds.png` qui contiennent uniquement les identifiants de classe pour la segmentation sémantique\n","- Des fichiers `*_gtFine_color.png` qui offrent une représentation visuelle colorée des segmentations\n","- Des fichiers `*_gtFine_polygons.json` qui stockent les annotations sous forme vectorielle (polygones)\n","\n","Cette richesse d'annotations nous permettra de développer un modèle robuste pour notre système de vision par ordinateur embarqué chez Future Vision Transport."]},{"cell_type":"markdown","metadata":{"id":"Zm2FnTw3LJx7"},"source":["## Configuration de l'environnement et des dépendances"]},{"cell_type":"code","execution_count":11,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":31087,"status":"ok","timestamp":1754980938831,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"gkl0tzdJDgmD","outputId":"91688771-b4d5-4413-cacc-9b598037a4e3"},"outputs":[{"output_type":"stream","name":"stdout","text":[" Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m25.8/25.8 MB\u001b[0m \u001b[31m66.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m38.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m26.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m140.1/140.1 kB\u001b[0m \u001b[31m9.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m247.0/247.0 kB\u001b[0m \u001b[31m16.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m14.0/14.0 MB\u001b[0m \u001b[31m29.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m147.8/147.8 kB\u001b[0m \u001b[31m9.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m114.9/114.9 kB\u001b[0m \u001b[31m7.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m85.0/85.0 kB\u001b[0m \u001b[31m5.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m50.7/50.7 kB\u001b[0m \u001b[31m3.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m85.3/85.3 kB\u001b[0m \u001b[31m6.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m681.8/681.8 kB\u001b[0m \u001b[31m20.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m203.4/203.4 kB\u001b[0m \u001b[31m14.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m65.6/65.6 kB\u001b[0m \u001b[31m4.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m120.0/120.0 kB\u001b[0m \u001b[31m3.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m201.6/201.6 kB\u001b[0m \u001b[31m8.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25h Building wheel for segmentation_models (setup.py) ... \u001b[?25l\u001b[?25hdone\n"]}],"source":["!pip install mlflow boto3 dotenv git+https://github.com/qubvel/segmentation_models.git --quiet"]},{"cell_type":"code","execution_count":12,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":8781,"status":"ok","timestamp":1754980947614,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"FQJX9NED7J1B","outputId":"49811ab3-f88d-4754-b55b-6ecfc65a7fda"},"outputs":[{"output_type":"stream","name":"stdout","text":["Segmentation Models: using `keras` framework.\n"]}],"source":["# ---------------------------------------\n","# Imports Système et Utilitaires\n","# ---------------------------------------\n","import os\n","import sys\n","import random\n","import json\n","import shutil\n","import zipfile\n","from datetime import datetime\n","import glob\n","import time # ← Ajouté pour mesurer le temps d'entraînement\n","import tempfile\n","\n","# ---------------------------------------\n","# Data Science & Manipulation\n","# ---------------------------------------\n","import numpy as np\n","import matplotlib.pyplot as plt\n","from PIL import Image as PILImage\n","from tqdm import tqdm\n","import requests\n","import itertools\n","from sklearn.metrics import confusion_matrix\n","\n","# ---------------------------------------\n","# Scikit-learn : pour gestion du split train/test\n","# ---------------------------------------\n","from sklearn.model_selection import train_test_split\n","\n","# ---------------------------------------\n","# TensorFlow & Keras (version tensorflow.keras pour compatibilité)\n","# ---------------------------------------\n","import tensorflow as tf\n","from tensorflow import data as tf_data\n","from tensorflow import keras\n","from tensorflow.keras import callbacks # ← Ajouté pour les callbacks\n","import tensorflow.keras.backend as K # backend Keras TensorFlow\n","\n","# ---------------------------------------\n","# Segmentation Models : patch pour forcer backend tf.keras\n","# ---------------------------------------\n","import segmentation_models as sm\n","sm.set_framework('tf.keras') # on fixe tf.keras comme backend\n","sm.backend = K # on force le backend keras tensorflow\n","\n","# ---------------------------------------\n","# MLflow : suivi d'expériences & gestion modèles\n","# ---------------------------------------\n","import mlflow\n","import mlflow.keras\n","import mlflow.tensorflow # ← Ajouté pour mlflow.tensorflow.autolog()\n","from mlflow.models.signature import infer_signature\n","from mlflow import MlflowClient\n","from mlflow.models.signature import ModelSignature\n","from mlflow.types import Schema, ColSpec, TensorSpec\n","\n","# ---------------------------------------\n","# Environnements Colab & variables d'environnement\n","# ---------------------------------------\n","from google.colab import userdata\n","from dotenv import load_dotenv\n","\n","# Chargement des variables d'environnement du fichier .env\n","load_dotenv(dotenv_path='../.env')\n","\n","# Ajouter le dossier parent du notebook au PYTHONPATH\n","parent_dir = os.path.abspath('..')\n","if parent_dir not in sys.path:\n"," sys.path.insert(0, parent_dir)\n","\n","# Chargement de fonctions diverses communes à l'entraînement et à l'inférence\n","# from utils.utils import load_cityscapes_config, get_preprocessing_fn #, map_mask_ids\n","from utils.utils import load_cityscapes_config, get_preprocessing_fn, load_best_model_from_registry, map_mask_ids, run_inference_and_visualize"]},{"cell_type":"code","execution_count":13,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":444,"status":"ok","timestamp":1754980948068,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"O9oKKrUPQD9s","outputId":"d631f271-f0ca-42f7-dccc-9b2db700031d"},"outputs":[{"output_type":"stream","name":"stdout","text":["TensorFlow version: 2.19.0\n","Keras version: 3.10.0\n","CUDA disponible: []\n","MLflow Tracking URI: https://mlflow.greg-madman-nas.duckdns.org/\n","Identifiants AWS configurés\n","Appareil utilisé: CPU\n"]}],"source":["# Vérification de la configuration\n","print(f\"TensorFlow version: {tf.__version__}\")\n","print(f\"Keras version: {keras.__version__}\")\n","print(f\"CUDA disponible: {tf.config.list_physical_devices('GPU')}\")\n","\n","# Définition des chemins des données\n","g_drive_dir = drive_folder\n","g_drive_dir_content = os.path.join(g_drive_dir, \"content\")\n","\n","# data_dir pointe toujours vers le dossier général des données sur Google Drive\n","data_dir = os.path.join(g_drive_dir_content, \"data\")\n","\n","# Chemin pour le stockage des données extraites (dans l'environnement Colab temporaire)\n","cityscapes_unzipped_dir = os.path.join(\"/content\", \"data\", \"cityscapes_unzipped\")\n","\n","\n","# Création des dossiers s'il n'existent pas déjà\n","os.makedirs(data_dir, exist_ok=True) # Créer le dossier data sur Drive\n","os.makedirs(os.path.join(g_drive_dir_content, 'models'), exist_ok=True) # Dossier modèles sur Drive\n","os.makedirs(os.path.join(g_drive_dir_content, 'models', 'checkpoints'), exist_ok=True) # Dossier checkpoints sur Drive\n","os.makedirs(os.path.join(g_drive_dir_content, 'logs'), exist_ok=True) # Dossier logs sur Drive\n","\n","\n","# Configuration des graines aléatoires pour la reproductibilité\n","seed = 42\n","random.seed(seed)\n","np.random.seed(seed)\n","tf.random.set_seed(seed)\n","\n","# Configuration de MLflow avec les variables d'environnement\n","mlflow_tracking_uri = os.getenv(\"MLFLOW_TRACKING_URI\")\n","mlflow_s3_endpoint_url = os.getenv(\"MLFLOW_S3_ENDPOINT_URL\")\n","aws_access_key_id = os.getenv(\"AWS_ACCESS_KEY_ID\")\n","aws_secret_access_key = os.getenv(\"AWS_SECRET_ACCESS_KEY\")\n","\n","# Configuration explicite de MLflow\n","mlflow.set_tracking_uri(mlflow_tracking_uri)\n","print(f\"MLflow Tracking URI: {mlflow_tracking_uri}\")\n","\n","# Configuration explicite des identifiants AWS\n","os.environ[\"MLFLOW_S3_ENDPOINT_URL\"] = mlflow_s3_endpoint_url\n","os.environ[\"AWS_ACCESS_KEY_ID\"] = aws_access_key_id\n","os.environ[\"AWS_SECRET_ACCESS_KEY\"] = aws_secret_access_key\n","print(\"Identifiants AWS configurés\")\n","\n","# Paramètres globaux\n","device = 'GPU' if tf.config.list_physical_devices('GPU') else 'CPU'\n","print(f\"Appareil utilisé: {device}\")"]},{"cell_type":"code","execution_count":14,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":627,"status":"ok","timestamp":1754980948694,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"DR-_gM8JIZpr","outputId":"aefc10f8-68d0-4dd4-abc5-d0a31b1cd001"},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""]},"metadata":{},"execution_count":14}],"source":["# Créer l'expérience MLflow\n","mlflow_experiemnt = \"OC Projet 8\"\n","mlflow.set_experiment(mlflow_experiemnt)"]},{"cell_type":"markdown","metadata":{"id":"P4O-U_2rQEJa"},"source":["## Téléchargement et préparation des données Cityscapes"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":35,"status":"ok","timestamp":1754919005086,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"t52l8Er1QEcx","outputId":"e0fdb48f-8cd6-4a3f-966d-f1ffeec32028"},"outputs":[{"output_type":"stream","name":"stdout","text":["\n","✅ Les données Cityscapes semblent déjà extraites dans l'environnement temporaire.\n","\n","Variable 'cityscapes_dir' mise à jour vers: /content/data/cityscapes_unzipped\n"]}],"source":["def download_and_extract_cityscapes():\n"," \"\"\"Télécharge et extrait les données Cityscapes si elles n'existent pas déjà\"\"\"\n","\n"," # Création des répertoires nécessaires s'ils n'existent pas\n"," os.makedirs(data_dir, exist_ok=True) # data_dir est sur Drive pour stocker les zips\n"," os.makedirs(cityscapes_unzipped_dir, exist_ok=True) # Créer le dossier unzipped dans /content\n","\n"," # Liens vers les fichiers zip Cityscapes\n"," gtFine_url = \"https://s3-eu-west-1.amazonaws.com/static.oc-static.com/prod/courses/files/AI+Engineer/Project+8+-+Participez+%C3%A0+la+conception+d'une+voiture+autonome/P8_Cityscapes_gtFine_trainvaltest.zip\"\n"," leftImg_url = \"https://s3-eu-west-1.amazonaws.com/static.oc-static.com/prod/courses/files/AI+Engineer/Project+8+-+Participez+%C3%A0+la+conception+d'une+voiture+autonome/P8_Cityscapes_leftImg8bit_trainvaltest.zip\"\n","\n"," # Chemins locaux pour les fichiers zip (sur Google Drive dans data_dir)\n"," gtFine_zip = os.path.join(data_dir, \"P8_Cityscapes_gtFine_trainvaltest.zip\")\n"," leftImg_zip = os.path.join(data_dir, \"P8_Cityscapes_leftImg8bit_trainvaltest.zip\")\n","\n"," # Fonction pour télécharger un fichier avec barre de progression\n"," def download_file(url, filename):\n"," # Vérifier si le fichier existe déjà et a une taille non nulle\n"," if os.path.exists(filename) and os.path.getsize(filename) > 0:\n"," print(f\"Le fichier {os.path.basename(filename)} existe déjà. Pas de téléchargement.\")\n"," return True # Considérer comme succès si le fichier existe\n","\n"," response = requests.get(url, stream=True)\n"," response.raise_for_status() # Vérification des erreurs HTTP\n","\n"," total_size = int(response.headers.get('content-length', 0))\n"," block_size = 1024 # 1 KB\n"," # Utilisation de tqdm pour une barre de progression interactive\n"," progress_bar = tqdm(total=total_size, unit='iB', unit_scale=True, desc=f\"Téléchargement {os.path.basename(filename)}\")\n","\n"," with open(filename, 'wb') as file:\n"," for data in response.iter_content(block_size):\n"," progress_bar.update(len(data))\n"," file.write(data)\n","\n"," progress_bar.close()\n","\n"," if total_size != 0 and progress_bar.n != total_size:\n"," print(f\"ERREUR: le téléchargement de {os.path.basename(filename)} n'est pas complet\")\n"," return False\n","\n"," return True\n","\n"," # --- Logique de Téléchargement et Extraction ---\n"," # Vérification si les données extraites existent déjà dans /content/data/cityscapes_unzipped\n"," # On vérifie la présence d'un dossier caractéristique des données extraites\n"," extracted_data_check_path = os.path.join(cityscapes_unzipped_dir, \"gtFine\", \"train\")\n","\n"," # Si les données extraites ne sont PAS présentes dans le répertoire temporaire\n"," if not os.path.exists(extracted_data_check_path):\n"," print(\"\\n=== VÉRIFICATION ET TÉLÉCHARGEMENT DES FICHIERS ZIP ===\")\n","\n"," # Téléchargement des fichiers zip si nécessaire (dans data_dir sur Drive)\n"," download_success_gtFine = download_file(gtFine_url, gtFine_zip)\n"," download_success_leftImg = download_file(leftImg_url, leftImg_zip)\n","\n"," if not download_success_gtFine or not download_success_leftImg:\n"," print(\"❌ Échec du téléchargement d'un ou plusieurs fichiers zip.\")\n"," return False\n","\n"," print(\"✅ Fichiers zip vérifiés ou téléchargés dans Google Drive.\")\n","\n"," print(\"\\n=== EXTRACTION DES FICHIERS ZIP VERS L'ENVIRONNEMENT TEMPORAIRE ===\")\n"," print(f\"Extraction vers: {cityscapes_unzipped_dir}\")\n","\n"," # Extraction des fichiers zip VERS cityscapes_unzipped_dir (/content/data/cityscapes_unzipped)\n"," print(\"Extraction des annotations (gtFine)...\")\n"," try:\n"," with zipfile.ZipFile(gtFine_zip, 'r') as zip_ref:\n"," # Extraction avec barre de progression\n"," for member in tqdm(zip_ref.infolist(), desc=\"Extraction gtFine\"):\n"," zip_ref.extract(member, cityscapes_unzipped_dir) # <-- Extraction vers le dossier /content\n"," print(\"Extraction des annotations terminée.\")\n"," except zipfile.BadZipFile:\n"," print(f\"❌ Erreur: {gtFine_zip} n'est pas un fichier ZIP valide.\")\n"," return False\n"," except Exception as e:\n"," print(f\"❌ Erreur lors de l'extraction de gtFine: {e}\")\n"," return False\n","\n","\n"," print(\"Extraction des images (leftImg8bit)...\")\n"," try:\n"," with zipfile.ZipFile(leftImg_zip, 'r') as zip_ref:\n"," # Extraction avec barre de progression\n"," for member in tqdm(zip_ref.infolist(), desc=\"Extraction leftImg8bit\"):\n"," zip_ref.extract(member, cityscapes_unzipped_dir) # <-- Extraction vers le dossier /content\n"," print(\"Extraction des images terminée.\")\n"," except zipfile.BadZipFile:\n"," print(f\"❌ Erreur: {leftImg_zip} n'est pas un fichier ZIP valide.\")\n"," return False\n"," except Exception as e:\n"," print(f\"❌ Erreur lors de l'extraction de leftImg8bit: {e}\")\n"," return False\n","\n"," print(\"\\n✅ Préparation des données Cityscapes (extraction) terminée dans l'environnement temporaire.\")\n"," else:\n"," print(\"\\n✅ Les données Cityscapes semblent déjà extraites dans l'environnement temporaire.\")\n","\n"," return True\n","\n","# Télécharger et extraire les données Cityscapes en utilisant les nouveaux chemins\n","download_and_extract_cityscapes()\n","\n","# Mettre à jour la variable cityscapes_dir pour qu'elle pointe vers le dossier des données extraites\n","# Les fonctions suivantes (préparation, visualisation) utiliseront cette variable\n","cityscapes_dir = cityscapes_unzipped_dir\n","print(f\"\\nVariable 'cityscapes_dir' mise à jour vers: {cityscapes_dir}\")"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":108,"status":"ok","timestamp":1754919005195,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"xFjmYex0PMM1","outputId":"22326ddb-c7c1-42b5-f3cb-9443cdfadad6"},"outputs":[{"output_type":"stream","name":"stdout","text":["train dataset: 2975 images found\n"]}],"source":["split = 'train'\n","images_dir = os.path.join(cityscapes_unzipped_dir, 'leftImg8bit', split)\n","masks_dir = os.path.join(cityscapes_unzipped_dir, 'gtFine', split)\n","\n","# Lists to store image and mask paths\n","image_paths = []\n","mask_paths = []\n","\n","# Go through all city directories\n","for city in os.listdir(images_dir):\n"," city_img_dir = os.path.join(images_dir, city)\n"," city_mask_dir = os.path.join(masks_dir, city)\n","\n"," # Find all matching image and mask files\n"," for file_name in os.listdir(city_img_dir):\n"," if file_name.endswith('_leftImg8bit.png'):\n"," img_path = os.path.join(city_img_dir, file_name)\n"," mask_name = file_name.replace('_leftImg8bit.png', '_gtFine_labelIds.png')\n"," mask_path = os.path.join(city_mask_dir, mask_name)\n","\n"," if os.path.exists(mask_path):\n"," image_paths.append(img_path)\n"," mask_paths.append(mask_path)\n","\n","print(f\"{split} dataset: {len(image_paths)} images found\")"]},{"cell_type":"markdown","metadata":{"id":"UeD9y0LBQEws"},"source":["## Définition des classes et mapping pour la segmentation"]},{"cell_type":"markdown","metadata":{"id":"YC-BHFBhyeha"},"source":["Les définitions de classes officielles sont présentes [ici](https://www.cityscapes-dataset.com/dataset-overview/#class-definitions)."]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":34893,"status":"ok","timestamp":1754919040089,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"7K-ox-l81X9A","outputId":"fe41c250-5964-44ba-8f00-d78774cb88f6"},"outputs":[{"output_type":"stream","name":"stdout","text":["Exploration du répertoire : /content/data/cityscapes_unzipped/gtFine\n","\n","Nombre total de fichiers JSON '_gtFine_polygons.json' trouvés : 5000\n","\n","Valeurs uniques de 'label' trouvées :\n","- bicycle\n","- bicyclegroup\n","- bridge\n","- building\n","- bus\n","- car\n","- caravan\n","- cargroup\n","- dynamic\n","- ego vehicle\n","- fence\n","- ground\n","- guard rail\n","- license plate\n","- motorcycle\n","- motorcyclegroup\n","- out of roi\n","- parking\n","- person\n","- persongroup\n","- pole\n","- polegroup\n","- rail track\n","- rectification border\n","- rider\n","- ridergroup\n","- road\n","- sidewalk\n","- sky\n","- static\n","- terrain\n","- traffic light\n","- traffic sign\n","- trailer\n","- train\n","- truck\n","- truckgroup\n","- tunnel\n","- vegetation\n","- wall\n","\n","Nombre de valeurs uniques de 'label' : 40\n"]}],"source":["import os\n","import json\n","\n","# Chemin vers le répertoire gtFine (assurez-vous que cityscapes_unzipped_dir est défini)\n","gtFine_dir = os.path.join(cityscapes_unzipped_dir, 'gtFine')\n","\n","if not os.path.exists(gtFine_dir):\n"," print(f\"Le répertoire {gtFine_dir} n'existe pas.\")\n","else:\n"," print(f\"Exploration du répertoire : {gtFine_dir}\")\n"," all_labels = set()\n"," json_files_count = 0\n","\n"," # Parcourir tous les sous-répertoires et fichiers\n"," for root, dirs, files in os.walk(gtFine_dir):\n"," for file in files:\n"," if file.endswith('_gtFine_polygons.json'):\n"," json_files_count += 1\n"," json_path = os.path.join(root, file)\n"," try:\n"," with open(json_path, 'r', encoding='utf-8') as f:\n"," data = json.load(f)\n"," # Assurez-vous que la structure JSON correspond à ce que vous attendez\n"," # Ici, on suppose que 'objects' est une liste d'objets,\n"," # et chaque objet a une clé 'label'\n"," if 'objects' in data:\n"," for obj in data['objects']:\n"," if 'label' in obj:\n"," all_labels.add(obj['label'])\n"," except Exception as e:\n"," print(f\"Erreur lors du traitement du fichier {json_path}: {e}\")\n","\n"," print(f\"\\nNombre total de fichiers JSON '_gtFine_polygons.json' trouvés : {json_files_count}\")\n"," print(\"\\nValeurs uniques de 'label' trouvées :\")\n"," # Convertir l'ensemble en liste et la trier pour un affichage cohérent\n"," unique_labels_list = sorted(list(all_labels))\n"," for label in unique_labels_list:\n"," print(f\"- {label}\")\n","\n"," print(f\"\\nNombre de valeurs uniques de 'label' : {len(unique_labels_list)}\")"]},{"cell_type":"markdown","metadata":{"id":"7bf84c3b"},"source":["Le dataset Cityscapes fournit plusieurs types de fichiers d'annotations, ce qui peut prêter à confusion. Pour notre tâche de **segmentation sémantique**, où chaque pixel est assigné à une catégorie de classe, nous nous basons spécifiquement sur les fichiers `*_gtFine_labelIds.png`.\n","\n","Ces fichiers PNG en niveaux de gris encodent la classe de chaque pixel à l'aide d'un **ID numérique**. Les IDs utilisés dans ces fichiers vont de **0 à 33**.\n","\n","Les définitions et la correspondance entre ces IDs numériques et les noms de classes sont documentées dans le script `labels.py` du dépôt CityscapesScripts ([`cityscapesscripts/helpers/labels.py`](https://github.com/mcordts/cityscapesScripts/blob/master/cityscapesscripts/helpers/labels.py)). Ce fichier liste 34 entrées (IDs 0 à 33) avec leurs noms, catégories, couleurs, etc.\n","\n","Parallèlement, le dataset inclut d'autres formats d'annotations, comme les fichiers `*_gtFine_polygons.json`. Ces fichiers contiennent des informations plus détaillées, y compris des annotations vectorielles (polygones) et peuvent référencer un ensemble plus large de labels, potentiellement 40 catégories comme observé lors de l'exploration des fichiers JSON, incluant des labels d'instances ou de groupes (comme 'person group') qui ne sont pas représentés par des IDs distincts dans les fichiers `*_gtFine_labelIds.png` utilisés pour la segmentation sémantique pixel-par-pixel.\n","\n","De même, le fichier `labels_cityPersons.py` ([`cityscapesscripts/helpers/labels_cityPersons.py`](https://github.com/mcordts/cityscapesScripts/blob/master/cityscapesscripts/helpers/labels_cityPersons.py)) définit des classes spécifiquement pour l'annotation des instances de personnes et de cyclistes, qui sont utilisées dans d'autres contextes ou formats d'annotation du dataset, mais pas dans les `*_gtFine_labelIds.png` pour la segmentation sémantique de base.\n","\n","**Pour notre projet de segmentation sémantique, nous utilisons donc uniquement les IDs numériques présents dans les fichiers `*_gtFine_labelIds.png` et nous mappons ces IDs (0 à 33) à nos 8 groupes de classes définis.** L'exploration des labels dans les fichiers JSON était utile pour comprendre la richesse du dataset, mais le mapping du modèle se base sur les IDs des masques `_labelIds.png`."]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":22,"status":"ok","timestamp":1754919040109,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"4YmGYVW56FMt","outputId":"bcec670a-d35f-400e-cec0-4494911585df"},"outputs":[{"output_type":"stream","name":"stdout","text":["== Groupes de classes Cityscapes ==\n"," - flat : ['road', 'sidewalk', 'parking', 'rail track']\n"," - human : ['person', 'rider']\n"," - vehicle : ['car', 'truck', 'bus', 'train', 'motorcycle', 'bicycle', 'caravan', 'trailer']\n"," - construction : ['building', 'wall', 'fence', 'guard rail', 'bridge', 'tunnel']\n"," - object : ['pole', 'pole group', 'traffic sign', 'traffic light']\n"," - nature : ['vegetation', 'terrain']\n"," - sky : ['sky']\n"," - void : ['unlabeled', 'ego vehicle', 'rectification border', 'out of roi', 'static', 'dynamic', 'ground']\n","\n","== Mapping ID Cityscapes → Groupe ==\n"," ID 0 ('unlabeled') → groupe 'void' (7)\n"," ID 1 ('ego vehicle') → groupe 'void' (7)\n"," ID 2 ('rectification border') → groupe 'void' (7)\n"," ID 3 ('out of roi') → groupe 'void' (7)\n"," ID 4 ('static') → groupe 'void' (7)\n"," ID 5 ('dynamic') → groupe 'void' (7)\n"," ID 6 ('ground') → groupe 'void' (7)\n"," ID 7 ('road') → groupe 'flat' (0)\n"," ID 8 ('sidewalk') → groupe 'flat' (0)\n"," ID 9 ('parking') → groupe 'flat' (0)\n"," ID 10 ('rail track') → groupe 'flat' (0)\n"," ID 11 ('building') → groupe 'construction' (3)\n"," ID 12 ('wall') → groupe 'construction' (3)\n"," ID 13 ('fence') → groupe 'construction' (3)\n"," ID 14 ('guard rail') → groupe 'construction' (3)\n"," ID 15 ('bridge') → groupe 'construction' (3)\n"," ID 16 ('tunnel') → groupe 'construction' (3)\n"," ID 17 ('pole') → groupe 'object' (4)\n"," ID 18 ('pole group') → groupe 'object' (4)\n"," ID 19 ('traffic light') → groupe 'object' (4)\n"," ID 20 ('traffic sign') → groupe 'object' (4)\n"," ID 21 ('vegetation') → groupe 'nature' (5)\n"," ID 22 ('terrain') → groupe 'nature' (5)\n"," ID 23 ('sky') → groupe 'sky' (6)\n"," ID 24 ('person') → groupe 'human' (1)\n"," ID 25 ('rider') → groupe 'human' (1)\n"," ID 26 ('car') → groupe 'vehicle' (2)\n"," ID 27 ('truck') → groupe 'vehicle' (2)\n"," ID 28 ('bus') → groupe 'vehicle' (2)\n"," ID 29 ('caravan') → groupe 'vehicle' (2)\n"," ID 30 ('trailer') → groupe 'vehicle' (2)\n"," ID 31 ('train') → groupe 'vehicle' (2)\n"," ID 32 ('motorcycle') → groupe 'vehicle' (2)\n"," ID 33 ('bicycle') → groupe 'vehicle' (2)\n","\n","== Liste des groupes et couleurs associées ==\n"," Groupe 0: flat - Couleur RGB : [128 64 128]\n"," Groupe 1: human - Couleur RGB : [220 20 60]\n"," Groupe 2: vehicle - Couleur RGB : [ 0 0 142]\n"," Groupe 3: construction - Couleur RGB : [70 70 70]\n"," Groupe 4: object - Couleur RGB : [220 220 0]\n"," Groupe 5: nature - Couleur RGB : [107 142 35]\n"," Groupe 6: sky - Couleur RGB : [ 70 130 180]\n"," Groupe 7: void - Couleur RGB : [0 0 0]\n","\n","Nombre total de groupes/classes : 8\n"]}],"source":["mapping_config = load_cityscapes_config(\"../cityscapes_config.json\")"]},{"cell_type":"markdown","metadata":{"id":"MqYRJXp53zci"},"source":["Le tableau `id_to_group` a une taille de **256 éléments** car il correspond à toutes les valeurs possibles sur **8 bits** (de 0 à 255), soit la plage complète des IDs de classes que peuvent prendre les masques d'annotation Cityscapes.\n","\n","Même si dans notre cas précis on ne mappe que 34 IDs utilisés, on crée un tableau complet pour :\n","\n","- Permettre un accès direct et rapide par index (ID) sans calcul supplémentaire.\n","- Gérer des masques pouvant contenir n'importe quelle valeur d'ID possible (y compris des valeurs non utilisées).\n","- Assurer la robustesse de la conversion sans erreurs d’index hors limites.\n","\n","Ainsi, chaque valeur d’ID dans un masque peut être convertie en son groupe associé en un accès simple via `id_to_group[ID]`.\n","\n","Les IDs non présents dans notre mapping restent mappés à 0 (par défaut), mais on peut aussi choisir une autre valeur spéciale pour représenter une classe \"void\" ou \"non définie\".\n"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3,"status":"ok","timestamp":1754919040132,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"2kLbBJ8M1e5o","outputId":"4f0affeb-d6d6-465a-ed16-ed6243de240d"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([7, 7, 7, 7, 7, 7, 7, 0, 0, 0, 0, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 5,\n"," 5, 6, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n"," 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n"," 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n"," 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n"," 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n"," 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n"," 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n"," 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n"," 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n"," 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n"," 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype=uint8)"]},"metadata":{},"execution_count":129}],"source":["id_to_group = mapping_config['id_to_group']\n","id_to_group"]},{"cell_type":"markdown","metadata":{"id":"6A4cu2ZeJKCI"},"source":["## Architecture de Segmentation 🖼️✨\n","\n","Pour la tâche de segmentation d’images, deux architectures principales sont utilisées dans cette étude : **U-Net** et **FPN (Feature Pyramid Network)**.\n","\n","---\n","\n","### Les architectures principales 🏗️\n","\n","- **U-Net** 🔄 \n"," U-Net est composée de deux parties symétriques :\n"," - 🧱 **Un encodeur (chemin descendant)** qui extrait les caractéristiques de plus en plus abstraites grâce à des convolutions et du max-pooling.\n"," - 🏗️ **Un décodeur (chemin ascendant)** qui reconstruit une image de même taille que l’entrée à l’aide d’upsampling (ou transposed convolutions).\n"," - Chaque niveau du décodeur reçoit également des **\"skip connections\"** venant de l’encodeur à la même résolution, pour préserver les détails spatiaux.\n","\n"," U-Net est donc efficace quand il faut localiser précisément des objets (par exemple en imagerie médicale).\n","\n"," \n","\n","- **FPN (Feature Pyramid Network)** 🧭 \n"," FPN est une architecture conçue pour capturer efficacement des objets à **différentes échelles**, grâce à une combinaison intelligente de caractéristiques extraites à plusieurs résolutions.\n","\n"," Elle repose sur deux étapes principales :\n"," \n"," 1. 🔽 **Chemin descendant (bottom-up)** : \n"," L’image passe dans un encodeur profond (souvent un ResNet), qui génère des cartes de caractéristiques à plusieurs résolutions (`1/4`, `1/8`, `1/16`, `1/32`). \n"," Plus la résolution est petite, plus l’information est abstraite.\n"," \n"," 2. 🔼 **Chemin ascendant (top-down)** : \n"," Les cartes profondes sont **upsamplées progressivement** (x2 à chaque étape) et **fusionnées avec des cartes plus superficielles** à l’aide de *connexions latérales* (lateral connections). \n"," Cette fusion permet de combiner des informations **globales et locales** à chaque niveau de la pyramide.\n","\n"," Finalement, les différentes cartes sont combinées et passées dans un petit réseau convolutionnel (souvent un 3x3) pour produire la **prédiction finale**.\n","\n"," 👉 Cette approche rend FPN particulièrement efficace sur des images avec des objets de **tailles très variées**, comme en vision par ordinateur généraliste (urbain, aérien, etc.).\n","\n"," Le modèle a été historiquement entraîné avec ResNet50 et ResNet101 par l'équipe de chercheurs.\n","> **“We build FPN on top of ResNet-50/101 [21], which are used as backbone feature extractors.”** \n","> — *Feature Pyramid Networks for Object Detection*, \n","> Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Serge Belongie. \n","> *CVPR 2017* \n","> [arXiv:1612.03144](https://arxiv.org/abs/1612.03144)\n","\n","\n"," *(Le schéma ci-dessous illustre cette architecture dans le contexte original de la détection, mais le principe est le même en segmentation sémantique.)*\n","\n"," 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)\n","\n","---\n","\n","### Choix des encodeurs 🧠\n","\n","Plusieurs encodeurs sont disponibles pour ces architectures : \n","- **Encodeur intégré** 🆕 : L’encodeur est entraîné en même temps que le décodeur, sans poids pré-entraînés. Pour U-Net, il a été développé *from scratch* mais pour FPN, il s'agira de ResNet34 (plus léger que ResNet50, le modèle de feature extraction originellement utilisé dans les travaux de recherche).\n","- **MobilenetV2 pré-entraîné** 🚀 : Un encodeur léger et efficace, pré-entraîné sur ImageNet, permettant un bon compromis entre rapidité et performance. \n","- **EfficientNetB0 pré-entraîné** ⚡ : Un encodeur plus puissant et performant, également basé sur un modèle pré-entraîné, utilisé pour tirer parti du transfert learning.\n","\n","ℹ️ Par défaut, la bibliothèque `segmentation_models` utilise **ResNet34 pré-entraîné sur ImageNet** comme encodeur si aucun autre n’est spécifié.\n","\n","---\n","\n","### Gel ou fine-tuning de l’encodeur ❄️🔥\n","\n","Lors de l’entraînement, deux stratégies sont possibles : \n","- **Encodage gelé** ❄️ : Les poids de l’encodeur pré-entraîné restent fixes, ce qui accélère l’entraînement et évite la modification de caractéristiques déjà apprises. \n","- **Encodage entraînable (fine-tuning)** 🔥 : Les poids de l’encodeur sont ajustés pour mieux s’adapter aux données spécifiques, ce qui peut améliorer les performances au prix d’un temps d’entraînement plus long.\n","\n","---\n","\n","### Stratégie recommandée pour l’expérimentation 🎯\n","\n","1. **Tester toutes les architectures et encodeurs avec l’encodeur gelé** ❄️ pour un benchmark rapide. \n","2. **Sélectionner la meilleure configuration** 🏆 selon les performances obtenues. \n","3. **Refaire l’entraînement avec l’encodeur dégelé (fine-tuning)** 🔥 pour optimiser les résultats finaux.\n","\n","Cette méthode permet de gagner du temps tout en explorant efficacement l’espace des modèles.\n","\n"]},{"cell_type":"markdown","metadata":{"id":"s5te0Fcwtx51"},"source":["### Création des modèles"]},{"cell_type":"code","execution_count":25,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":12,"status":"ok","timestamp":1754980975025,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"8eHYsAmIRsIU","outputId":"60fe35f3-26b7-4a3d-e559-84804cd5e43f"},"outputs":[{"output_type":"stream","name":"stdout","text":["🔧 BACKBONES DISPONIBLES:\n","==================================================\n","⭐ RECOMMANDÉS pour voiture autonome (vitesse/précision):\n"," • mobilenetv2\n"," • efficientnetb0\n"," • resnet34\n"," • resnet50\n","\n","📋 TOUS DISPONIBLES (32):\n","\n"," resnet18 resnet34 resnet50 resnet101 \n"," resnet152 seresnet18 seresnet34 seresnet50 \n"," seresnet101 seresnet152 seresnext50 seresnext101 \n"," senet154 resnext50 resnext101 vgg16 \n"," vgg19 densenet121 densenet169 densenet201 \n"," inceptionresnetv2 inceptionv3 mobilenet mobilenetv2 \n"," efficientnetb0 efficientnetb1 efficientnetb2 efficientnetb3 \n"," efficientnetb4 efficientnetb5 efficientnetb6 efficientnetb7 \n"]}],"source":["def show_available_backbones():\n"," \"\"\"Affiche tous les backbones disponibles dans segmentation_models\"\"\"\n","\n"," # Essayer de récupérer la liste des backbones disponibles\n"," try:\n"," available_backbones = sm.get_available_backbones()\n","\n"," print(\"🔧 BACKBONES DISPONIBLES DANS SEGMENTATION_MODELS:\")\n"," print(\"=\" * 60)\n","\n"," # Grouper par famille\n"," families = {\n"," 'ResNet': [b for b in available_backbones if b.startswith('resnet')],\n"," 'SEResNet': [b for b in available_backbones if b.startswith('seresnet')],\n"," 'SEResNeXt': [b for b in available_backbones if b.startswith('seresnext')],\n"," 'ResNeXt': [b for b in available_backbones if b.startswith('resnext')],\n"," 'VGG': [b for b in available_backbones if b.startswith('vgg')],\n"," 'DenseNet': [b for b in available_backbones if b.startswith('densenet')],\n"," 'Inception': [b for b in available_backbones if 'inception' in b],\n"," 'MobileNet': [b for b in available_backbones if 'mobilenet' in b],\n"," 'EfficientNet': [b for b in available_backbones if 'efficientnet' in b],\n"," 'SENet': [b for b in available_backbones if b.startswith('senet')],\n"," }\n","\n"," for family, models in families.items():\n"," if models:\n"," print(f\"\\n📱 {family}:\")\n"," for model in sorted(models):\n"," print(f\" • {model}\")\n","\n"," except AttributeError:\n"," # Si la méthode n'existe pas, utiliser la liste connue\n"," known_backbones = [\n"," 'resnet18', 'resnet34', 'resnet50', 'resnet101', 'resnet152',\n"," 'seresnet18', 'seresnet34', 'seresnet50', 'seresnet101', 'seresnet152',\n"," 'seresnext50', 'seresnext101', 'senet154', 'resnext50', 'resnext101',\n"," 'vgg16', 'vgg19', 'densenet121', 'densenet169', 'densenet201',\n"," 'inceptionresnetv2', 'inceptionv3', 'mobilenet', 'mobilenetv2',\n"," 'efficientnetb0', 'efficientnetb1', 'efficientnetb2', 'efficientnetb3',\n"," 'efficientnetb4', 'efficientnetb5', 'efficientnetb6', 'efficientnetb7'\n"," ]\n","\n"," print(\"🔧 BACKBONES DISPONIBLES:\")\n"," print(\"=\" * 50)\n","\n"," # Recommandations pour voiture autonome\n"," recommended = ['mobilenetv2', 'efficientnetb0', 'resnet34', 'resnet50']\n","\n"," print(\"⭐ RECOMMANDÉS pour voiture autonome (vitesse/précision):\")\n"," for model in recommended:\n"," print(f\" • {model}\")\n","\n"," print(f\"\\n📋 TOUS DISPONIBLES ({len(known_backbones)}):\")\n"," for i, model in enumerate(known_backbones):\n"," if i % 4 == 0: # Nouvelle ligne tous les 4\n"," print()\n"," print(f\" {model:<20}\", end=\"\")\n"," print() # Ligne finale\n","\n","# Afficher les backbones disponibles\n","show_available_backbones()"]},{"cell_type":"code","execution_count":26,"metadata":{"id":"3xLKhC8KW5i7","executionInfo":{"status":"ok","timestamp":1754980975305,"user_tz":-120,"elapsed":136,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"outputs":[],"source":["# ================================================================\n","# GRILLE D'EXPÉRIMENTATIONS - SEGMENTATION SÉMANTIQUE CITYSCAPES\n","# ================================================================\n","\n","# Architectures et backbones à tester\n","model_variants = [\n"," # Baselines (sans backbone pré-entraîné)\n"," ('U-Net', None),\n"," ('FPN', None), # --> l'encodeur choisi sera alors vgg16\n"," # Modèles avec backbones pré-entraînés (encoders gelés)\n"," ('U-Net', 'mobilenetv2'),\n"," ('U-Net', 'efficientnetb0'),\n"," ('FPN', 'mobilenetv2'),\n"," ('FPN', 'efficientnetb0'),\n"," ('FPN', 'resnet34'),\n","]\n","\n","# Fine-tuning sélectif (encoders entraînables)\n","finetune_variants = [\n"," ('U-Net', 'mobilenetv2'),\n"," ('FPN', 'efficientnetb0'),\n"," ('FPN', 'resnet34'),\n","]\n","\n","# Paramètres d'entraînement\n","base_params = {\n"," 'learning_rate': 1e-4,\n"," 'epochs': 20,\n"," 'batch_size': 8,\n"," 'img_size': (224, 224)\n","}\n","\n","finetune_params = {\n"," 'learning_rate': 5e-5, # Plus petit pour le fine-tuning\n"," 'epochs': 30,\n"," 'batch_size': 8,\n"," 'img_size': (224, 224)\n","}\n","\n","# Génération des configurations\n","def generate_experiment_configs():\n"," \"\"\"Génère toutes les configurations d'expérimentations\"\"\"\n"," model_configs = []\n","\n"," # 1. Expériences de base (encodeurs gelés ou vanilla)\n"," for arch, encoder in model_variants:\n"," for augment in [False, True]:\n"," # ✅ Nom correct selon le type\n"," if encoder is None:\n"," config_name = f\"{arch}_vanilla_aug{augment}\"\n"," else:\n"," config_name = f\"{arch}_{encoder}_frozen_aug{augment}\"\n","\n"," model_configs.append({\n"," \"name\": config_name,\n"," \"architecture\": arch,\n"," \"encoder\": encoder,\n"," \"encoder_freeze\": encoder is not None,\n"," \"augmentation\": augment,\n"," \"params\": base_params.copy(),\n"," \"type\": \"baseline\" if encoder is None else \"frozen_pretrained\"\n"," })\n","\n"," # 2. Expériences de fine-tuning (encoders dégelés)\n"," for arch, encoder in finetune_variants:\n"," config_name = f\"{arch}_{encoder}_finetune_augTrue\"\n"," model_configs.append({\n"," \"name\": config_name,\n"," \"architecture\": arch,\n"," \"encoder\": encoder,\n"," \"encoder_freeze\": False, # False = dégelé pour fine-tuning\n"," \"augmentation\": True,\n"," \"params\": finetune_params.copy(),\n"," \"type\": \"finetuned_pretrained\"\n"," })\n","\n"," return model_configs"]},{"cell_type":"code","execution_count":27,"metadata":{"id":"X7wY6OqSZFha","executionInfo":{"status":"ok","timestamp":1754980975483,"user_tz":-120,"elapsed":7,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"outputs":[],"source":["def create_model_from_config(config, num_classes, verbose=False):\n"," \"\"\"\n"," Crée un modèle de segmentation à partir d'une configuration d'expérimentation.\n"," \"\"\"\n"," # === EXTRACTION DES PARAMÈTRES ===\n"," architecture = config['architecture']\n"," encoder = config['encoder']\n"," encoder_freeze = config['encoder_freeze']\n"," learning_rate = config['params']['learning_rate']\n"," img_size = config['params']['img_size']\n","\n"," # === MAPPING DES ARCHITECTURES ===\n"," model_classes = {\n"," 'U-Net': sm.Unet,\n"," 'FPN': sm.FPN,\n"," }\n","\n"," if architecture not in model_classes:\n"," raise ValueError(f\"Architecture '{architecture}' non supportée.\")\n","\n"," ModelClass = model_classes[architecture]\n"," input_shape = (*img_size, 3)\n","\n"," if verbose:\n"," print(f\"🔧 Création du modèle '{config['name']}'\")\n"," print(f\" Architecture: {architecture}\")\n"," print(f\" Encoder: {encoder or 'Aucun (vanilla)'}\")\n"," print(f\" Encoder gelé: {encoder_freeze}\")\n","\n"," try:\n"," if encoder is None:\n"," # === MODÈLE VANILLA ===\n"," model = ModelClass(\n"," classes=num_classes,\n"," activation='softmax',\n"," input_shape=input_shape,\n"," )\n"," else:\n"," # === MODÈLE AVEC BACKBONE ===\n"," model = ModelClass(\n"," backbone_name=encoder,\n"," encoder_weights='imagenet',\n"," encoder_freeze=encoder_freeze,\n"," classes=num_classes,\n"," activation='softmax',\n"," input_shape=input_shape,\n"," )\n","\n"," # === COMPILATION ===\n"," model.compile(\n"," optimizer=keras.optimizers.Adam(learning_rate=learning_rate),\n"," loss=sm.losses.categorical_focal_jaccard_loss,\n"," metrics=[sm.metrics.iou_score, 'accuracy']\n"," )\n","\n"," if verbose:\n"," total_params = model.count_params()\n"," trainable_params = sum([tf.keras.backend.count_params(w) for w in model.trainable_weights])\n"," frozen_params = total_params - trainable_params\n"," print(f\" 📊 Paramètres: {total_params:,} total | {trainable_params:,} entraînables | {frozen_params:,} gelés\")\n","\n"," return model\n","\n"," except Exception as e:\n"," print(f\"❌ Erreur: {e}\")\n"," raise"]},{"cell_type":"code","execution_count":28,"metadata":{"id":"4ROnd_8f9_W7","executionInfo":{"status":"ok","timestamp":1754980975757,"user_tz":-120,"elapsed":42,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"outputs":[],"source":["# Génération des configurations\n","experimental_configurations = generate_experiment_configs()"]},{"cell_type":"markdown","metadata":{"id":"GILXYzC_9jHX"},"source":["### Analyse et compréhension détaillée des modèles"]},{"cell_type":"markdown","metadata":{"id":"5yr47E0qbmmY"},"source":["L'objectif est simplement ici d'afficher des informations générales sur les modèles et notamment vérifier le gel des poids pour les modèles de feature extraction (backbone) qui fournissent des descripteurs aux modèles de segmentation et ce afin de pouvoir comparer les différences de performances."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"qdsGkrVQe2mX"},"outputs":[],"source":["def analyze_model_comprehensive(config, num_classes, show_architecture=False, detailed_layers=False):\n"," \"\"\"\n"," Analyse exhaustive d'un modèle de segmentation avec affichage clair des couches gelées/dégelées\n","\n"," Args:\n"," config (dict): Configuration du modèle\n"," num_classes (int): Nombre de classes\n"," show_architecture (bool): Afficher model.summary()\n"," detailed_layers (bool): Afficher TOUTES les couches (sinon juste backbone + résumé)\n","\n"," Returns:\n"," dict: Résultats de l'analyse\n"," \"\"\"\n"," print(f\"\\n{'='*70}\")\n"," print(f\"🏗️ ANALYSE COMPLÈTE: {config['name']}\")\n"," print(f\"{'='*70}\")\n","\n"," # === 1. INFORMATIONS DE CONFIGURATION ===\n"," print(f\"📊 Configuration:\")\n"," print(f\" • Architecture: {config['architecture']}\")\n"," print(f\" • Backbone: {config['encoder'] or 'Aucun (vanilla)'}\")\n"," print(f\" • Encoder gelé: {'✅ Oui' if config.get('encoder_freeze', False) else '❌ Non'}\")\n"," print(f\" • Type: {config['type'].replace('_', ' ').title()}\")\n"," print(f\" • Augmentation: {'✅ Oui' if config['augmentation'] else '❌ Non'}\")\n"," print(f\" • Learning rate: {config['params']['learning_rate']}\")\n"," print(f\" • Époques prévues: {config['params']['epochs']}\")\n"," print(f\" • Taille images: {config['params']['img_size']}\")\n","\n"," try:\n"," # === 2. CRÉATION DU MODÈLE ===\n"," print(f\"\\n🔧 Création du modèle...\")\n"," model = create_model_from_config(config, num_classes, verbose=False)\n","\n"," # === 3. ANALYSE DES PARAMÈTRES ===\n"," total_params = model.count_params()\n"," trainable_params = sum([tf.keras.backend.count_params(w) for w in model.trainable_weights])\n"," frozen_params = total_params - trainable_params\n"," frozen_ratio = (frozen_params / total_params) * 100\n","\n"," print(f\"\\n🔢 Paramètres:\")\n"," print(f\" • Total: {total_params:,}\")\n"," print(f\" • Entraînables: {trainable_params:,} ({(trainable_params/total_params)*100:.1f}%)\")\n"," print(f\" • Gelés: {frozen_params:,} ({frozen_ratio:.1f}%)\")\n","\n"," # === 4. ANALYSE DES COUCHES ===\n"," backbone_layers = []\n"," other_layers = []\n"," backbone_total = 0\n"," backbone_frozen = 0\n","\n"," # Classifier les couches\n"," for layer in model.layers:\n"," layer_params = layer.count_params()\n"," is_backbone = False\n","\n"," if config['encoder']:\n"," backbone_keywords = [\n"," config['encoder'].lower(),\n"," 'encoder',\n"," 'backbone',\n"," 'feature'\n"," ]\n"," is_backbone = any(keyword in layer.name.lower() for keyword in backbone_keywords)\n","\n"," layer_info = {\n"," 'name': layer.name,\n"," 'params': layer_params,\n"," 'trainable': layer.trainable,\n"," 'is_backbone': is_backbone\n"," }\n","\n"," if is_backbone:\n"," backbone_layers.append(layer_info)\n"," backbone_total += layer_params\n"," if not layer.trainable:\n"," backbone_frozen += layer_params\n"," else:\n"," other_layers.append(layer_info)\n","\n"," # === 5. AFFICHAGE DES COUCHES ===\n"," if detailed_layers:\n"," # Affichage complet de toutes les couches\n"," print(f\"\\n🔍 TOUTES LES COUCHES (🟢 = Entraînable, 🔴 = Gelé):\")\n"," print(\"-\" * 70)\n","\n"," all_layers = backbone_layers + other_layers\n"," for i, layer_info in enumerate(all_layers):\n"," icon = \"🔴\" if not layer_info['trainable'] else \"🟢\"\n"," status = \"GELÉ\" if not layer_info['trainable'] else \"ENTRAÎNABLE\"\n","\n"," # Identifier le type de couche\n"," if layer_info['is_backbone']:\n"," layer_type = \" (BACKBONE)\"\n"," elif 'decoder' in layer_info['name'].lower():\n"," layer_type = \" (DECODER)\"\n"," elif 'classifier' in layer_info['name'].lower() or 'final' in layer_info['name'].lower():\n"," layer_type = \" (CLASSIFICATION)\"\n"," elif 'upsample' in layer_info['name'].lower():\n"," layer_type = \" (UPSAMPLING)\"\n"," else:\n"," layer_type = \"\"\n","\n"," print(f\"{i+1:2d}. {icon} {layer_info['name']:<40} {layer_info['params']:>8,} params - {status}{layer_type}\")\n","\n"," else:\n"," # Affichage résumé avec focus sur le backbone\n"," if backbone_layers:\n"," print(f\"\\n🔍 COUCHES DU BACKBONE (🟢 = Entraînable, 🔴 = Gelé):\")\n"," print(\"-\" * 60)\n","\n"," for layer_info in backbone_layers[:8]: # Limite à 8 pour lisibilité\n"," icon = \"🔴\" if not layer_info['trainable'] else \"🟢\"\n"," status = \"GELÉ\" if not layer_info['trainable'] else \"ENTRAÎNABLE\"\n"," print(f\" {icon} {layer_info['name']:<35} {layer_info['params']:>8,} params - {status}\")\n","\n"," if len(backbone_layers) > 8:\n"," print(f\" ... et {len(backbone_layers)-8} autres couches du backbone\")\n","\n"," # Résumé des autres couches\n"," other_frozen = sum(1 for layer in other_layers if not layer['trainable'])\n"," other_trainable = len(other_layers) - other_frozen\n"," print(f\"\\n🏗️ AUTRES COUCHES (résumé):\")\n"," print(f\" • {other_trainable} couches entraînables\")\n"," print(f\" • {other_frozen} couches gelées\")\n"," print(f\" • (Utilisez detailed_layers=True pour voir toutes les couches)\")\n","\n"," # === 6. RÉSUMÉ BACKBONE ===\n"," if backbone_layers:\n"," backbone_frozen_ratio = (backbone_frozen / backbone_total * 100) if backbone_total > 0 else 0\n"," print(f\"\\n📋 Résumé backbone:\")\n"," print(f\" • Total backbone: {backbone_total:,} params\")\n"," print(f\" • Backbone gelé: {backbone_frozen:,} params ({backbone_frozen_ratio:.1f}%)\")\n"," print(f\" • Backbone entraînable: {backbone_total - backbone_frozen:,} params ({100-backbone_frozen_ratio:.1f}%)\")\n","\n"," # === 7. VALIDATION DU GEL ===\n"," if config['encoder']:\n"," print(f\"\\n🎯 Validation du gel du backbone:\")\n","\n"," # Seuils adaptatifs selon le backbone\n"," backbone_name = config['encoder'].lower()\n"," if 'mobilenet' in backbone_name:\n"," expected_frozen_range = (20, 35)\n"," elif 'efficientnet' in backbone_name and 'b0' in backbone_name:\n"," expected_frozen_range = (15, 25)\n"," elif 'resnet' in backbone_name:\n"," expected_frozen_range = (18, 28)\n"," else:\n"," expected_frozen_range = (10, 30)\n","\n"," if config.get('encoder_freeze', False):\n"," # Modèle supposé gelé\n"," if frozen_ratio >= expected_frozen_range[0]:\n"," status = \"✅ OK\"\n"," message = f\"Backbone correctement gelé ({frozen_ratio:.1f}% ≥ {expected_frozen_range[0]}%)\"\n"," else:\n"," status = \"⚠️ SUSPECT\"\n"," message = f\"Gel potentiellement incomplet ({frozen_ratio:.1f}% < {expected_frozen_range[0]}%)\"\n"," else:\n"," # Modèle supposé dégelé\n"," if frozen_ratio < 5.0:\n"," status = \"✅ OK\"\n"," message = f\"Backbone correctement dégelé ({frozen_ratio:.1f}% < 5%)\"\n"," else:\n"," status = \"⚠️ SUSPECT\"\n"," message = f\"Gel résiduel inattendu ({frozen_ratio:.1f}% ≥ 5%)\"\n","\n"," print(f\" • Statut global: {status}\")\n"," print(f\" • {message}\")\n"," print(f\" • Plage attendue pour {config['encoder']}: {expected_frozen_range[0]}-{expected_frozen_range[1]}%\")\n","\n"," # Validation spécifique du backbone\n"," if backbone_total > 0:\n"," backbone_expected_frozen = config.get('encoder_freeze', False)\n"," backbone_actually_frozen = (backbone_frozen / backbone_total) > 0.9\n","\n"," if backbone_expected_frozen == backbone_actually_frozen:\n"," backbone_status = \"✅ COHÉRENT\"\n"," else:\n"," backbone_status = \"❌ INCOHÉRENT\"\n","\n"," print(f\" • Cohérence backbone: {backbone_status}\")\n"," print(f\" - Configuration: {'gelé' if backbone_expected_frozen else 'dégelé'}\")\n"," print(f\" - Réalité: {'gelé' if backbone_actually_frozen else 'dégelé'} ({backbone_frozen_ratio:.1f}%)\")\n","\n"," # === 8. ARCHITECTURE DÉTAILLÉE (optionnel) ===\n"," if show_architecture:\n"," print(f\"\\n🏛️ Architecture détaillée (model.summary()):\")\n"," print(\"-\" * 60)\n"," model.summary(line_length=80)\n","\n"," # === 9. RÉSULTATS POUR RETOUR ===\n"," results = {\n"," 'model': model,\n"," 'total_params': total_params,\n"," 'trainable_params': trainable_params,\n"," 'frozen_params': frozen_params,\n"," 'frozen_ratio': frozen_ratio,\n"," 'backbone_params': backbone_total,\n"," 'backbone_frozen': backbone_frozen,\n"," 'backbone_frozen_ratio': backbone_frozen_ratio if backbone_total > 0 else 0,\n"," 'status': 'success',\n"," 'validation': status if config['encoder'] else 'N/A'\n"," }\n","\n"," print(f\"\\n✅ Analyse terminée avec succès\")\n"," return results\n","\n"," except Exception as e:\n"," print(f\"\\n❌ Erreur lors de l'analyse: {e}\")\n"," return {\n"," 'model': None,\n"," 'status': 'error',\n"," 'error': str(e)\n"," }\n","\n"," finally:\n"," # Nettoyage mémoire\n"," if 'model' in locals():\n"," del model\n"," tf.keras.backend.clear_session()\n","\n","# === FONCTION SÉPARÉE POUR VOIR UNIQUEMENT LES COUCHES (différente maintenant) ===\n","def show_all_layers_status(config, num_classes):\n"," \"\"\"\n"," Fonction spécialisée pour afficher UNIQUEMENT les couches, de manière compacte\n"," \"\"\"\n"," print(f\"\\n🔍 COUCHES - {config['name']}\")\n"," print(\"=\" * 70)\n"," print(\"🟢 ENTRAÎNABLE | 🔴 GELÉ\")\n"," print(\"-\" * 70)\n","\n"," try:\n"," model = create_model_from_config(config, num_classes, verbose=False)\n","\n"," trainable_count = 0\n"," frozen_count = 0\n","\n"," for i, layer in enumerate(model.layers):\n"," layer_params = layer.count_params()\n"," icon = \"🔴\" if not layer.trainable else \"🟢\"\n","\n"," if layer.trainable:\n"," trainable_count += 1\n"," else:\n"," frozen_count += 1\n","\n"," # Type de couche (plus concis)\n"," layer_type = \"\"\n"," if config['encoder'] and any(keyword in layer.name.lower()\n"," for keyword in [config['encoder'].lower(), 'encoder', 'backbone']):\n"," layer_type = \"BACKBONE\"\n"," elif 'decoder' in layer.name.lower():\n"," layer_type = \"DECODER\"\n"," elif 'classifier' in layer.name.lower():\n"," layer_type = \"CLASSIF\"\n"," else:\n"," layer_type = \"AUTRE\"\n","\n"," print(f\"{i+1:2d}. {icon} {layer.name:<35} {layer_params:>8,} {layer_type}\")\n","\n"," print(\"-\" * 70)\n"," print(f\"📊 RÉSUMÉ: {trainable_count} entraînables, {frozen_count} gelés\")\n","\n"," except Exception as e:\n"," print(f\"❌ Erreur: {e}\")\n"," finally:\n"," if 'model' in locals():\n"," del model\n"," tf.keras.backend.clear_session()"]},{"cell_type":"markdown","metadata":{"id":"RYR1STLzZQzS"},"source":["L'objectif est simplement ici de tester le gel des poids pour les modèles de feature extraction (backbone) qui fournissent des descripteurs aux modèles de segmentation et ce afin de pouvoir comparer les différences de performances."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Jyxe-hvRZJ5C"},"outputs":[],"source":["def test_backbone_freezing(num_classes=19):\n"," \"\"\"\n"," Fonction de test pour vérifier que le gel du backbone fonctionne correctement.\n"," Version corrigée utilisant encoder_freeze.\n"," \"\"\"\n"," print(\"🧪 TEST DU GEL DU BACKBONE (VERSION CORRIGÉE)\")\n"," print(\"=\" * 60)\n","\n"," # === CONFIGURATIONS DE TEST ===\n"," test_configs = [\n"," {\n"," 'name': 'U-Net_mobilenetv2_frozen_test',\n"," 'architecture': 'U-Net',\n"," 'encoder': 'mobilenetv2',\n"," 'encoder_freeze': True, # GELÉ - devrait avoir beaucoup de params gelés\n"," 'params': {'learning_rate': 1e-4, 'img_size': (224, 224)},\n"," 'type': 'frozen_test'\n"," },\n"," {\n"," 'name': 'U-Net_mobilenetv2_trainable_test',\n"," 'architecture': 'U-Net',\n"," 'encoder': 'mobilenetv2',\n"," 'encoder_freeze': False, # DÉGELÉ - devrait avoir peu de params gelés\n"," 'params': {'learning_rate': 1e-4, 'img_size': (224, 224)},\n"," 'type': 'trainable_test'\n"," }\n"," ]\n","\n"," results = {}\n","\n"," # === EXÉCUTION DES TESTS ===\n"," for config in test_configs:\n"," print(f\"\\n🔍 Test: {config['name']}\")\n"," print(\"-\" * 50)\n","\n"," # Création du modèle avec verbose pour voir les détails\n"," model = create_model_from_config(config, num_classes, verbose=True)\n","\n"," # === COMPTAGE DÉTAILLÉ DES PARAMÈTRES ===\n"," total_params = model.count_params()\n"," trainable_params = sum([tf.keras.backend.count_params(w) for w in model.trainable_weights])\n"," frozen_params = total_params - trainable_params\n"," frozen_ratio = (frozen_params / total_params) * 100\n","\n"," print(f\"\\n📈 Résultat:\")\n"," print(f\" • Total: {total_params:,}\")\n"," print(f\" • Entraînables: {trainable_params:,}\")\n"," print(f\" • Gelés: {frozen_params:,}\")\n"," print(f\" • % gelés: {frozen_ratio:.1f}%\")\n","\n"," # === VALIDATION DU RÉSULTAT ===\n"," if config['encoder_freeze']:\n"," # Pour un modèle gelé, on s'attend à >15% de paramètres gelés\n"," expected_frozen_ratio = 20.0\n"," status = \"✅ OK\" if frozen_ratio > expected_frozen_ratio else \"❌ ÉCHEC\"\n"," print(f\" • Statut (gelé attendu >20%): {status}\")\n"," else:\n"," # Pour un modèle dégelé, on s'attend à <10% de paramètres gelés\n"," expected_frozen_ratio = 5\n"," status = \"✅ OK\" if frozen_ratio < expected_frozen_ratio else \"❌ ÉCHEC\"\n"," print(f\" • Statut (dégelé attendu <5%): {status}\")\n","\n"," # Stockage des résultats pour comparaison\n"," results[config['type']] = {\n"," 'total': total_params,\n"," 'trainable': trainable_params,\n"," 'frozen': frozen_params,\n"," 'frozen_ratio': frozen_ratio\n"," }\n","\n"," # === NETTOYAGE MÉMOIRE ===\n"," del model\n"," tf.keras.backend.clear_session()\n","\n"," # === RÉSUMÉ COMPARATIF ===\n"," print(f\"\\n🎯 RÉSUMÉ COMPARATIF\")\n"," print(\"=\" * 60)\n","\n"," if 'frozen_test' in results and 'trainable_test' in results:\n"," frozen_result = results['frozen_test']\n"," trainable_result = results['trainable_test']\n","\n"," print(f\"Modèle gelé (encoder_freeze=True):\")\n"," print(f\" • Params gelés: {frozen_result['frozen']:,} ({frozen_result['frozen_ratio']:.1f}%)\")\n","\n"," print(f\"Modèle dégelé (encoder_freeze=False):\")\n"," print(f\" • Params gelés: {trainable_result['frozen']:,} ({trainable_result['frozen_ratio']:.1f}%)\")\n","\n"," difference = frozen_result['frozen'] - trainable_result['frozen']\n"," print(f\"Différence: {difference:,} paramètres correctement gelés\")\n","\n"," if difference > 100000: # Au moins 100k params de différence\n"," print(\"✅ TEST GLOBAL: Le gel du backbone fonctionne correctement!\")\n"," else:\n"," print(\"❌ TEST GLOBAL: Le gel du backbone ne semble pas fonctionner!\")"]},{"cell_type":"markdown","metadata":{"id":"EvurXI0XZzng"},"source":["On va lister les différentes expérimentations et vérifier le nombre de poids gelés pour deux configurations différentes : une avec backbone entrainable, l'autre non."]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3128,"status":"ok","timestamp":1754919043370,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"AsgetKA1ZM0y","outputId":"9219fca1-e3c1-4a38-c906-8ea00ff7b1f5"},"outputs":[{"output_type":"stream","name":"stdout","text":["📊 PLAN D'EXPÉRIMENTATIONS - 17 configurations\n","======================================================================\n","🔧 Backbones utilisés: ['efficientnetb0', 'mobilenetv2', 'resnet34']\n","🏗️ Architectures: U-Net, FPN\n","\n","🔹 BASELINE (4 configs):\n"," • U-Net_vanilla_augFalse \n"," • U-Net_vanilla_augTrue \n"," • FPN_vanilla_augFalse \n"," • FPN_vanilla_augTrue \n","\n","🔹 FROZEN PRETRAINED (10 configs):\n"," • U-Net_mobilenetv2_frozen_augFalse (gelé)\n"," • U-Net_mobilenetv2_frozen_augTrue (gelé)\n"," • U-Net_efficientnetb0_frozen_augFalse (gelé)\n"," • U-Net_efficientnetb0_frozen_augTrue (gelé)\n"," • FPN_mobilenetv2_frozen_augFalse (gelé)\n"," • FPN_mobilenetv2_frozen_augTrue (gelé)\n"," • FPN_efficientnetb0_frozen_augFalse (gelé)\n"," • FPN_efficientnetb0_frozen_augTrue (gelé)\n"," • FPN_resnet34_frozen_augFalse (gelé)\n"," • FPN_resnet34_frozen_augTrue (gelé)\n","\n","🔹 FINETUNED PRETRAINED (3 configs):\n"," • U-Net_mobilenetv2_finetune_augTrue (dégelé)\n"," • FPN_efficientnetb0_finetune_augTrue (dégelé)\n"," • FPN_resnet34_finetune_augTrue (dégelé)\n","\n","======================================================================\n","LANCEMENT DU TEST DE VALIDATION\n","======================================================================\n","🧪 TEST DU GEL DU BACKBONE (VERSION CORRIGÉE)\n","============================================================\n","\n","🔍 Test: U-Net_mobilenetv2_frozen_test\n","--------------------------------------------------\n","🔧 Création du modèle 'U-Net_mobilenetv2_frozen_test'\n"," Architecture: U-Net\n"," Encoder: mobilenetv2\n"," Encoder gelé: True\n"," 📊 Paramètres: 8,050,051 total | 5,824,195 entraînables | 2,225,856 gelés\n","\n","📈 Résultat:\n"," • Total: 8,050,051\n"," • Entraînables: 5,824,195\n"," • Gelés: 2,225,856\n"," • % gelés: 27.7%\n"," • Statut (gelé attendu >20%): ✅ OK\n","\n","🔍 Test: U-Net_mobilenetv2_trainable_test\n","--------------------------------------------------\n","🔧 Création du modèle 'U-Net_mobilenetv2_trainable_test'\n"," Architecture: U-Net\n"," Encoder: mobilenetv2\n"," Encoder gelé: False\n"," 📊 Paramètres: 8,050,051 total | 8,013,955 entraînables | 36,096 gelés\n","\n","📈 Résultat:\n"," • Total: 8,050,051\n"," • Entraînables: 8,013,955\n"," • Gelés: 36,096\n"," • % gelés: 0.4%\n"," • Statut (dégelé attendu <5%): ✅ OK\n","\n","🎯 RÉSUMÉ COMPARATIF\n","============================================================\n","Modèle gelé (encoder_freeze=True):\n"," • Params gelés: 2,225,856 (27.7%)\n","Modèle dégelé (encoder_freeze=False):\n"," • Params gelés: 36,096 (0.4%)\n","Différence: 2,189,760 paramètres correctement gelés\n","✅ TEST GLOBAL: Le gel du backbone fonctionne correctement!\n"]}],"source":["# Affichage des configurations\n","print(f\"📊 PLAN D'EXPÉRIMENTATIONS - {len(experimental_configurations)} configurations\")\n","print(\"=\" * 70)\n","\n","# Affichage des backbones utilisés\n","used_backbones = set()\n","for config in experimental_configurations:\n"," if config['encoder']:\n"," used_backbones.add(config['encoder'])\n","\n","print(f\"🔧 Backbones utilisés: {sorted(used_backbones)}\")\n","print(f\"🏗️ Architectures: U-Net, FPN\")\n","\n","# Grouper par type pour un affichage plus clair\n","config_types = {}\n","for config in experimental_configurations:\n"," config_type = config['type']\n"," if config_type not in config_types:\n"," config_types[config_type] = []\n"," config_types[config_type].append(config)\n","\n","for type_name, configs in config_types.items():\n"," print(f\"\\n🔹 {type_name.upper().replace('_', ' ')} ({len(configs)} configs):\")\n"," for config in configs:\n"," freeze_status = \"gelé\" if config['encoder_freeze'] else \"dégelé\"\n"," encoder_info = f\"({freeze_status})\" if config['encoder'] else \"\"\n"," print(f\" • {config['name']} {encoder_info}\")\n","\n","# === LANCEMENT DU TEST ===\n","print(f\"\\n\" + \"=\"*70)\n","print(\"LANCEMENT DU TEST DE VALIDATION\")\n","print(\"=\"*70)\n","\n","# Décommentez pour exécuter le test\n","test_backbone_freezing(num_classes=19)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":4429,"status":"ok","timestamp":1754919047801,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"9TWHaWHA6z66","outputId":"f367450c-779c-4243-d8a6-1e016ecbf199"},"outputs":[{"output_type":"stream","name":"stdout","text":["\n","======================================================================\n","🏗️ ANALYSE COMPLÈTE: U-Net_mobilenetv2_frozen_augFalse\n","======================================================================\n","📊 Configuration:\n"," • Architecture: U-Net\n"," • Backbone: mobilenetv2\n"," • Encoder gelé: ✅ Oui\n"," • Type: Frozen Pretrained\n"," • Augmentation: ❌ Non\n"," • Learning rate: 0.0001\n"," • Époques prévues: 20\n"," • Taille images: (224, 224)\n","\n","🔧 Création du modèle...\n","\n","🔢 Paramètres:\n"," • Total: 8,050,051\n"," • Entraînables: 5,824,195 (72.3%)\n"," • Gelés: 2,225,856 (27.7%)\n","\n","🏗️ AUTRES COUCHES (résumé):\n"," • 93 couches entraînables\n"," • 103 couches gelées\n"," • (Utilisez detailed_layers=True pour voir toutes les couches)\n","\n","🎯 Validation du gel du backbone:\n"," • Statut global: ✅ OK\n"," • Backbone correctement gelé (27.7% ≥ 20%)\n"," • Plage attendue pour mobilenetv2: 20-35%\n","\n","✅ Analyse terminée avec succès\n","\n","======================================================================\n","🏗️ ANALYSE COMPLÈTE: U-Net_mobilenetv2_frozen_augFalse\n","======================================================================\n","📊 Configuration:\n"," • Architecture: U-Net\n"," • Backbone: mobilenetv2\n"," • Encoder gelé: ✅ Oui\n"," • Type: Frozen Pretrained\n"," • Augmentation: ❌ Non\n"," • Learning rate: 0.0001\n"," • Époques prévues: 20\n"," • Taille images: (224, 224)\n","\n","🔧 Création du modèle...\n","\n","🔢 Paramètres:\n"," • Total: 8,050,051\n"," • Entraînables: 5,824,195 (72.3%)\n"," • Gelés: 2,225,856 (27.7%)\n","\n","🔍 TOUTES LES COUCHES (🟢 = Entraînable, 🔴 = Gelé):\n","----------------------------------------------------------------------\n"," 1. 🔴 input_layer 0 params - GELÉ\n"," 2. 🔴 Conv1_pad 0 params - GELÉ\n"," 3. 🔴 Conv1 864 params - GELÉ\n"," 4. 🟢 bn_Conv1 128 params - ENTRAÎNABLE\n"," 5. 🔴 Conv1_relu 0 params - GELÉ\n"," 6. 🔴 expanded_conv_depthwise 288 params - GELÉ\n"," 7. 🟢 expanded_conv_depthwise_BN 128 params - ENTRAÎNABLE\n"," 8. 🔴 expanded_conv_depthwise_relu 0 params - GELÉ\n"," 9. 🔴 expanded_conv_project 512 params - GELÉ\n","10. 🟢 expanded_conv_project_BN 64 params - ENTRAÎNABLE\n","11. 🔴 block_1_expand 1,536 params - GELÉ\n","12. 🟢 block_1_expand_BN 384 params - ENTRAÎNABLE\n","13. 🔴 block_1_expand_relu 0 params - GELÉ\n","14. 🔴 block_1_pad 0 params - GELÉ\n","15. 🔴 block_1_depthwise 864 params - GELÉ\n","16. 🟢 block_1_depthwise_BN 384 params - ENTRAÎNABLE\n","17. 🔴 block_1_depthwise_relu 0 params - GELÉ\n","18. 🔴 block_1_project 2,304 params - GELÉ\n","19. 🟢 block_1_project_BN 96 params - ENTRAÎNABLE\n","20. 🔴 block_2_expand 3,456 params - GELÉ\n","21. 🟢 block_2_expand_BN 576 params - ENTRAÎNABLE\n","22. 🔴 block_2_expand_relu 0 params - GELÉ\n","23. 🔴 block_2_depthwise 1,296 params - GELÉ\n","24. 🟢 block_2_depthwise_BN 576 params - ENTRAÎNABLE\n","25. 🔴 block_2_depthwise_relu 0 params - GELÉ\n","26. 🔴 block_2_project 3,456 params - GELÉ\n","27. 🟢 block_2_project_BN 96 params - ENTRAÎNABLE\n","28. 🔴 block_2_add 0 params - GELÉ\n","29. 🔴 block_3_expand 3,456 params - GELÉ\n","30. 🟢 block_3_expand_BN 576 params - ENTRAÎNABLE\n","31. 🔴 block_3_expand_relu 0 params - GELÉ\n","32. 🔴 block_3_pad 0 params - GELÉ\n","33. 🔴 block_3_depthwise 1,296 params - GELÉ\n","34. 🟢 block_3_depthwise_BN 576 params - ENTRAÎNABLE\n","35. 🔴 block_3_depthwise_relu 0 params - GELÉ\n","36. 🔴 block_3_project 4,608 params - GELÉ\n","37. 🟢 block_3_project_BN 128 params - ENTRAÎNABLE\n","38. 🔴 block_4_expand 6,144 params - GELÉ\n","39. 🟢 block_4_expand_BN 768 params - ENTRAÎNABLE\n","40. 🔴 block_4_expand_relu 0 params - GELÉ\n","41. 🔴 block_4_depthwise 1,728 params - GELÉ\n","42. 🟢 block_4_depthwise_BN 768 params - ENTRAÎNABLE\n","43. 🔴 block_4_depthwise_relu 0 params - GELÉ\n","44. 🔴 block_4_project 6,144 params - GELÉ\n","45. 🟢 block_4_project_BN 128 params - ENTRAÎNABLE\n","46. 🔴 block_4_add 0 params - GELÉ\n","47. 🔴 block_5_expand 6,144 params - GELÉ\n","48. 🟢 block_5_expand_BN 768 params - ENTRAÎNABLE\n","49. 🔴 block_5_expand_relu 0 params - GELÉ\n","50. 🔴 block_5_depthwise 1,728 params - GELÉ\n","51. 🟢 block_5_depthwise_BN 768 params - ENTRAÎNABLE\n","52. 🔴 block_5_depthwise_relu 0 params - GELÉ\n","53. 🔴 block_5_project 6,144 params - GELÉ\n","54. 🟢 block_5_project_BN 128 params - ENTRAÎNABLE\n","55. 🔴 block_5_add 0 params - GELÉ\n","56. 🔴 block_6_expand 6,144 params - GELÉ\n","57. 🟢 block_6_expand_BN 768 params - ENTRAÎNABLE\n","58. 🔴 block_6_expand_relu 0 params - GELÉ\n","59. 🔴 block_6_pad 0 params - GELÉ\n","60. 🔴 block_6_depthwise 1,728 params - GELÉ\n","61. 🟢 block_6_depthwise_BN 768 params - ENTRAÎNABLE\n","62. 🔴 block_6_depthwise_relu 0 params - GELÉ\n","63. 🔴 block_6_project 12,288 params - GELÉ\n","64. 🟢 block_6_project_BN 256 params - ENTRAÎNABLE\n","65. 🔴 block_7_expand 24,576 params - GELÉ\n","66. 🟢 block_7_expand_BN 1,536 params - ENTRAÎNABLE\n","67. 🔴 block_7_expand_relu 0 params - GELÉ\n","68. 🔴 block_7_depthwise 3,456 params - GELÉ\n","69. 🟢 block_7_depthwise_BN 1,536 params - ENTRAÎNABLE\n","70. 🔴 block_7_depthwise_relu 0 params - GELÉ\n","71. 🔴 block_7_project 24,576 params - GELÉ\n","72. 🟢 block_7_project_BN 256 params - ENTRAÎNABLE\n","73. 🔴 block_7_add 0 params - GELÉ\n","74. 🔴 block_8_expand 24,576 params - GELÉ\n","75. 🟢 block_8_expand_BN 1,536 params - ENTRAÎNABLE\n","76. 🔴 block_8_expand_relu 0 params - GELÉ\n","77. 🔴 block_8_depthwise 3,456 params - GELÉ\n","78. 🟢 block_8_depthwise_BN 1,536 params - ENTRAÎNABLE\n","79. 🔴 block_8_depthwise_relu 0 params - GELÉ\n","80. 🔴 block_8_project 24,576 params - GELÉ\n","81. 🟢 block_8_project_BN 256 params - ENTRAÎNABLE\n","82. 🔴 block_8_add 0 params - GELÉ\n","83. 🔴 block_9_expand 24,576 params - GELÉ\n","84. 🟢 block_9_expand_BN 1,536 params - ENTRAÎNABLE\n","85. 🔴 block_9_expand_relu 0 params - GELÉ\n","86. 🔴 block_9_depthwise 3,456 params - GELÉ\n","87. 🟢 block_9_depthwise_BN 1,536 params - ENTRAÎNABLE\n","88. 🔴 block_9_depthwise_relu 0 params - GELÉ\n","89. 🔴 block_9_project 24,576 params - GELÉ\n","90. 🟢 block_9_project_BN 256 params - ENTRAÎNABLE\n","91. 🔴 block_9_add 0 params - GELÉ\n","92. 🔴 block_10_expand 24,576 params - GELÉ\n","93. 🟢 block_10_expand_BN 1,536 params - ENTRAÎNABLE\n","94. 🔴 block_10_expand_relu 0 params - GELÉ\n","95. 🔴 block_10_depthwise 3,456 params - GELÉ\n","96. 🟢 block_10_depthwise_BN 1,536 params - ENTRAÎNABLE\n","97. 🔴 block_10_depthwise_relu 0 params - GELÉ\n","98. 🔴 block_10_project 36,864 params - GELÉ\n","99. 🟢 block_10_project_BN 384 params - ENTRAÎNABLE\n","100. 🔴 block_11_expand 55,296 params - GELÉ\n","101. 🟢 block_11_expand_BN 2,304 params - ENTRAÎNABLE\n","102. 🔴 block_11_expand_relu 0 params - GELÉ\n","103. 🔴 block_11_depthwise 5,184 params - GELÉ\n","104. 🟢 block_11_depthwise_BN 2,304 params - ENTRAÎNABLE\n","105. 🔴 block_11_depthwise_relu 0 params - GELÉ\n","106. 🔴 block_11_project 55,296 params - GELÉ\n","107. 🟢 block_11_project_BN 384 params - ENTRAÎNABLE\n","108. 🔴 block_11_add 0 params - GELÉ\n","109. 🔴 block_12_expand 55,296 params - GELÉ\n","110. 🟢 block_12_expand_BN 2,304 params - ENTRAÎNABLE\n","111. 🔴 block_12_expand_relu 0 params - GELÉ\n","112. 🔴 block_12_depthwise 5,184 params - GELÉ\n","113. 🟢 block_12_depthwise_BN 2,304 params - ENTRAÎNABLE\n","114. 🔴 block_12_depthwise_relu 0 params - GELÉ\n","115. 🔴 block_12_project 55,296 params - GELÉ\n","116. 🟢 block_12_project_BN 384 params - ENTRAÎNABLE\n","117. 🔴 block_12_add 0 params - GELÉ\n","118. 🔴 block_13_expand 55,296 params - GELÉ\n","119. 🟢 block_13_expand_BN 2,304 params - ENTRAÎNABLE\n","120. 🔴 block_13_expand_relu 0 params - GELÉ\n","121. 🔴 block_13_pad 0 params - GELÉ\n","122. 🔴 block_13_depthwise 5,184 params - GELÉ\n","123. 🟢 block_13_depthwise_BN 2,304 params - ENTRAÎNABLE\n","124. 🔴 block_13_depthwise_relu 0 params - GELÉ\n","125. 🔴 block_13_project 92,160 params - GELÉ\n","126. 🟢 block_13_project_BN 640 params - ENTRAÎNABLE\n","127. 🔴 block_14_expand 153,600 params - GELÉ\n","128. 🟢 block_14_expand_BN 3,840 params - ENTRAÎNABLE\n","129. 🔴 block_14_expand_relu 0 params - GELÉ\n","130. 🔴 block_14_depthwise 8,640 params - GELÉ\n","131. 🟢 block_14_depthwise_BN 3,840 params - ENTRAÎNABLE\n","132. 🔴 block_14_depthwise_relu 0 params - GELÉ\n","133. 🔴 block_14_project 153,600 params - GELÉ\n","134. 🟢 block_14_project_BN 640 params - ENTRAÎNABLE\n","135. 🔴 block_14_add 0 params - GELÉ\n","136. 🔴 block_15_expand 153,600 params - GELÉ\n","137. 🟢 block_15_expand_BN 3,840 params - ENTRAÎNABLE\n","138. 🔴 block_15_expand_relu 0 params - GELÉ\n","139. 🔴 block_15_depthwise 8,640 params - GELÉ\n","140. 🟢 block_15_depthwise_BN 3,840 params - ENTRAÎNABLE\n","141. 🔴 block_15_depthwise_relu 0 params - GELÉ\n","142. 🔴 block_15_project 153,600 params - GELÉ\n","143. 🟢 block_15_project_BN 640 params - ENTRAÎNABLE\n","144. 🔴 block_15_add 0 params - GELÉ\n","145. 🔴 block_16_expand 153,600 params - GELÉ\n","146. 🟢 block_16_expand_BN 3,840 params - ENTRAÎNABLE\n","147. 🔴 block_16_expand_relu 0 params - GELÉ\n","148. 🔴 block_16_depthwise 8,640 params - GELÉ\n","149. 🟢 block_16_depthwise_BN 3,840 params - ENTRAÎNABLE\n","150. 🔴 block_16_depthwise_relu 0 params - GELÉ\n","151. 🔴 block_16_project 307,200 params - GELÉ\n","152. 🟢 block_16_project_BN 1,280 params - ENTRAÎNABLE\n","153. 🔴 Conv_1 409,600 params - GELÉ\n","154. 🟢 Conv_1_bn 5,120 params - ENTRAÎNABLE\n","155. 🔴 out_relu 0 params - GELÉ\n","156. 🟢 decoder_stage0_upsampling 0 params - ENTRAÎNABLE (DECODER)\n","157. 🟢 decoder_stage0_concat 0 params - ENTRAÎNABLE (DECODER)\n","158. 🟢 decoder_stage0a_conv 4,276,224 params - ENTRAÎNABLE (DECODER)\n","159. 🟢 decoder_stage0a_bn 1,024 params - ENTRAÎNABLE (DECODER)\n","160. 🟢 decoder_stage0a_relu 0 params - ENTRAÎNABLE (DECODER)\n","161. 🟢 decoder_stage0b_conv 589,824 params - ENTRAÎNABLE (DECODER)\n","162. 🟢 decoder_stage0b_bn 1,024 params - ENTRAÎNABLE (DECODER)\n","163. 🟢 decoder_stage0b_relu 0 params - ENTRAÎNABLE (DECODER)\n","164. 🟢 decoder_stage1_upsampling 0 params - ENTRAÎNABLE (DECODER)\n","165. 🟢 decoder_stage1_concat 0 params - ENTRAÎNABLE (DECODER)\n","166. 🟢 decoder_stage1a_conv 516,096 params - ENTRAÎNABLE (DECODER)\n","167. 🟢 decoder_stage1a_bn 512 params - ENTRAÎNABLE (DECODER)\n","168. 🟢 decoder_stage1a_relu 0 params - ENTRAÎNABLE (DECODER)\n","169. 🟢 decoder_stage1b_conv 147,456 params - ENTRAÎNABLE (DECODER)\n","170. 🟢 decoder_stage1b_bn 512 params - ENTRAÎNABLE (DECODER)\n","171. 🟢 decoder_stage1b_relu 0 params - ENTRAÎNABLE (DECODER)\n","172. 🟢 decoder_stage2_upsampling 0 params - ENTRAÎNABLE (DECODER)\n","173. 🟢 decoder_stage2_concat 0 params - ENTRAÎNABLE (DECODER)\n","174. 🟢 decoder_stage2a_conv 156,672 params - ENTRAÎNABLE (DECODER)\n","175. 🟢 decoder_stage2a_bn 256 params - ENTRAÎNABLE (DECODER)\n","176. 🟢 decoder_stage2a_relu 0 params - ENTRAÎNABLE (DECODER)\n","177. 🟢 decoder_stage2b_conv 36,864 params - ENTRAÎNABLE (DECODER)\n","178. 🟢 decoder_stage2b_bn 256 params - ENTRAÎNABLE (DECODER)\n","179. 🟢 decoder_stage2b_relu 0 params - ENTRAÎNABLE (DECODER)\n","180. 🟢 decoder_stage3_upsampling 0 params - ENTRAÎNABLE (DECODER)\n","181. 🟢 decoder_stage3_concat 0 params - ENTRAÎNABLE (DECODER)\n","182. 🟢 decoder_stage3a_conv 46,080 params - ENTRAÎNABLE (DECODER)\n","183. 🟢 decoder_stage3a_bn 128 params - ENTRAÎNABLE (DECODER)\n","184. 🟢 decoder_stage3a_relu 0 params - ENTRAÎNABLE (DECODER)\n","185. 🟢 decoder_stage3b_conv 9,216 params - ENTRAÎNABLE (DECODER)\n","186. 🟢 decoder_stage3b_bn 128 params - ENTRAÎNABLE (DECODER)\n","187. 🟢 decoder_stage3b_relu 0 params - ENTRAÎNABLE (DECODER)\n","188. 🟢 decoder_stage4_upsampling 0 params - ENTRAÎNABLE (DECODER)\n","189. 🟢 decoder_stage4a_conv 4,608 params - ENTRAÎNABLE (DECODER)\n","190. 🟢 decoder_stage4a_bn 64 params - ENTRAÎNABLE (DECODER)\n","191. 🟢 decoder_stage4a_relu 0 params - ENTRAÎNABLE (DECODER)\n","192. 🟢 decoder_stage4b_conv 2,304 params - ENTRAÎNABLE (DECODER)\n","193. 🟢 decoder_stage4b_bn 64 params - ENTRAÎNABLE (DECODER)\n","194. 🟢 decoder_stage4b_relu 0 params - ENTRAÎNABLE (DECODER)\n","195. 🟢 final_conv 2,755 params - ENTRAÎNABLE (CLASSIFICATION)\n","196. 🟢 softmax 0 params - ENTRAÎNABLE\n","\n","🎯 Validation du gel du backbone:\n"," • Statut global: ✅ OK\n"," • Backbone correctement gelé (27.7% ≥ 20%)\n"," • Plage attendue pour mobilenetv2: 20-35%\n","\n","✅ Analyse terminée avec succès\n","\n","🔍 COUCHES - U-Net_mobilenetv2_frozen_augFalse\n","======================================================================\n","🟢 ENTRAÎNABLE | 🔴 GELÉ\n","----------------------------------------------------------------------\n"," 1. 🔴 input_layer 0 AUTRE\n"," 2. 🔴 Conv1_pad 0 AUTRE\n"," 3. 🔴 Conv1 864 AUTRE\n"," 4. 🟢 bn_Conv1 128 AUTRE\n"," 5. 🔴 Conv1_relu 0 AUTRE\n"," 6. 🔴 expanded_conv_depthwise 288 AUTRE\n"," 7. 🟢 expanded_conv_depthwise_BN 128 AUTRE\n"," 8. 🔴 expanded_conv_depthwise_relu 0 AUTRE\n"," 9. 🔴 expanded_conv_project 512 AUTRE\n","10. 🟢 expanded_conv_project_BN 64 AUTRE\n","11. 🔴 block_1_expand 1,536 AUTRE\n","12. 🟢 block_1_expand_BN 384 AUTRE\n","13. 🔴 block_1_expand_relu 0 AUTRE\n","14. 🔴 block_1_pad 0 AUTRE\n","15. 🔴 block_1_depthwise 864 AUTRE\n","16. 🟢 block_1_depthwise_BN 384 AUTRE\n","17. 🔴 block_1_depthwise_relu 0 AUTRE\n","18. 🔴 block_1_project 2,304 AUTRE\n","19. 🟢 block_1_project_BN 96 AUTRE\n","20. 🔴 block_2_expand 3,456 AUTRE\n","21. 🟢 block_2_expand_BN 576 AUTRE\n","22. 🔴 block_2_expand_relu 0 AUTRE\n","23. 🔴 block_2_depthwise 1,296 AUTRE\n","24. 🟢 block_2_depthwise_BN 576 AUTRE\n","25. 🔴 block_2_depthwise_relu 0 AUTRE\n","26. 🔴 block_2_project 3,456 AUTRE\n","27. 🟢 block_2_project_BN 96 AUTRE\n","28. 🔴 block_2_add 0 AUTRE\n","29. 🔴 block_3_expand 3,456 AUTRE\n","30. 🟢 block_3_expand_BN 576 AUTRE\n","31. 🔴 block_3_expand_relu 0 AUTRE\n","32. 🔴 block_3_pad 0 AUTRE\n","33. 🔴 block_3_depthwise 1,296 AUTRE\n","34. 🟢 block_3_depthwise_BN 576 AUTRE\n","35. 🔴 block_3_depthwise_relu 0 AUTRE\n","36. 🔴 block_3_project 4,608 AUTRE\n","37. 🟢 block_3_project_BN 128 AUTRE\n","38. 🔴 block_4_expand 6,144 AUTRE\n","39. 🟢 block_4_expand_BN 768 AUTRE\n","40. 🔴 block_4_expand_relu 0 AUTRE\n","41. 🔴 block_4_depthwise 1,728 AUTRE\n","42. 🟢 block_4_depthwise_BN 768 AUTRE\n","43. 🔴 block_4_depthwise_relu 0 AUTRE\n","44. 🔴 block_4_project 6,144 AUTRE\n","45. 🟢 block_4_project_BN 128 AUTRE\n","46. 🔴 block_4_add 0 AUTRE\n","47. 🔴 block_5_expand 6,144 AUTRE\n","48. 🟢 block_5_expand_BN 768 AUTRE\n","49. 🔴 block_5_expand_relu 0 AUTRE\n","50. 🔴 block_5_depthwise 1,728 AUTRE\n","51. 🟢 block_5_depthwise_BN 768 AUTRE\n","52. 🔴 block_5_depthwise_relu 0 AUTRE\n","53. 🔴 block_5_project 6,144 AUTRE\n","54. 🟢 block_5_project_BN 128 AUTRE\n","55. 🔴 block_5_add 0 AUTRE\n","56. 🔴 block_6_expand 6,144 AUTRE\n","57. 🟢 block_6_expand_BN 768 AUTRE\n","58. 🔴 block_6_expand_relu 0 AUTRE\n","59. 🔴 block_6_pad 0 AUTRE\n","60. 🔴 block_6_depthwise 1,728 AUTRE\n","61. 🟢 block_6_depthwise_BN 768 AUTRE\n","62. 🔴 block_6_depthwise_relu 0 AUTRE\n","63. 🔴 block_6_project 12,288 AUTRE\n","64. 🟢 block_6_project_BN 256 AUTRE\n","65. 🔴 block_7_expand 24,576 AUTRE\n","66. 🟢 block_7_expand_BN 1,536 AUTRE\n","67. 🔴 block_7_expand_relu 0 AUTRE\n","68. 🔴 block_7_depthwise 3,456 AUTRE\n","69. 🟢 block_7_depthwise_BN 1,536 AUTRE\n","70. 🔴 block_7_depthwise_relu 0 AUTRE\n","71. 🔴 block_7_project 24,576 AUTRE\n","72. 🟢 block_7_project_BN 256 AUTRE\n","73. 🔴 block_7_add 0 AUTRE\n","74. 🔴 block_8_expand 24,576 AUTRE\n","75. 🟢 block_8_expand_BN 1,536 AUTRE\n","76. 🔴 block_8_expand_relu 0 AUTRE\n","77. 🔴 block_8_depthwise 3,456 AUTRE\n","78. 🟢 block_8_depthwise_BN 1,536 AUTRE\n","79. 🔴 block_8_depthwise_relu 0 AUTRE\n","80. 🔴 block_8_project 24,576 AUTRE\n","81. 🟢 block_8_project_BN 256 AUTRE\n","82. 🔴 block_8_add 0 AUTRE\n","83. 🔴 block_9_expand 24,576 AUTRE\n","84. 🟢 block_9_expand_BN 1,536 AUTRE\n","85. 🔴 block_9_expand_relu 0 AUTRE\n","86. 🔴 block_9_depthwise 3,456 AUTRE\n","87. 🟢 block_9_depthwise_BN 1,536 AUTRE\n","88. 🔴 block_9_depthwise_relu 0 AUTRE\n","89. 🔴 block_9_project 24,576 AUTRE\n","90. 🟢 block_9_project_BN 256 AUTRE\n","91. 🔴 block_9_add 0 AUTRE\n","92. 🔴 block_10_expand 24,576 AUTRE\n","93. 🟢 block_10_expand_BN 1,536 AUTRE\n","94. 🔴 block_10_expand_relu 0 AUTRE\n","95. 🔴 block_10_depthwise 3,456 AUTRE\n","96. 🟢 block_10_depthwise_BN 1,536 AUTRE\n","97. 🔴 block_10_depthwise_relu 0 AUTRE\n","98. 🔴 block_10_project 36,864 AUTRE\n","99. 🟢 block_10_project_BN 384 AUTRE\n","100. 🔴 block_11_expand 55,296 AUTRE\n","101. 🟢 block_11_expand_BN 2,304 AUTRE\n","102. 🔴 block_11_expand_relu 0 AUTRE\n","103. 🔴 block_11_depthwise 5,184 AUTRE\n","104. 🟢 block_11_depthwise_BN 2,304 AUTRE\n","105. 🔴 block_11_depthwise_relu 0 AUTRE\n","106. 🔴 block_11_project 55,296 AUTRE\n","107. 🟢 block_11_project_BN 384 AUTRE\n","108. 🔴 block_11_add 0 AUTRE\n","109. 🔴 block_12_expand 55,296 AUTRE\n","110. 🟢 block_12_expand_BN 2,304 AUTRE\n","111. 🔴 block_12_expand_relu 0 AUTRE\n","112. 🔴 block_12_depthwise 5,184 AUTRE\n","113. 🟢 block_12_depthwise_BN 2,304 AUTRE\n","114. 🔴 block_12_depthwise_relu 0 AUTRE\n","115. 🔴 block_12_project 55,296 AUTRE\n","116. 🟢 block_12_project_BN 384 AUTRE\n","117. 🔴 block_12_add 0 AUTRE\n","118. 🔴 block_13_expand 55,296 AUTRE\n","119. 🟢 block_13_expand_BN 2,304 AUTRE\n","120. 🔴 block_13_expand_relu 0 AUTRE\n","121. 🔴 block_13_pad 0 AUTRE\n","122. 🔴 block_13_depthwise 5,184 AUTRE\n","123. 🟢 block_13_depthwise_BN 2,304 AUTRE\n","124. 🔴 block_13_depthwise_relu 0 AUTRE\n","125. 🔴 block_13_project 92,160 AUTRE\n","126. 🟢 block_13_project_BN 640 AUTRE\n","127. 🔴 block_14_expand 153,600 AUTRE\n","128. 🟢 block_14_expand_BN 3,840 AUTRE\n","129. 🔴 block_14_expand_relu 0 AUTRE\n","130. 🔴 block_14_depthwise 8,640 AUTRE\n","131. 🟢 block_14_depthwise_BN 3,840 AUTRE\n","132. 🔴 block_14_depthwise_relu 0 AUTRE\n","133. 🔴 block_14_project 153,600 AUTRE\n","134. 🟢 block_14_project_BN 640 AUTRE\n","135. 🔴 block_14_add 0 AUTRE\n","136. 🔴 block_15_expand 153,600 AUTRE\n","137. 🟢 block_15_expand_BN 3,840 AUTRE\n","138. 🔴 block_15_expand_relu 0 AUTRE\n","139. 🔴 block_15_depthwise 8,640 AUTRE\n","140. 🟢 block_15_depthwise_BN 3,840 AUTRE\n","141. 🔴 block_15_depthwise_relu 0 AUTRE\n","142. 🔴 block_15_project 153,600 AUTRE\n","143. 🟢 block_15_project_BN 640 AUTRE\n","144. 🔴 block_15_add 0 AUTRE\n","145. 🔴 block_16_expand 153,600 AUTRE\n","146. 🟢 block_16_expand_BN 3,840 AUTRE\n","147. 🔴 block_16_expand_relu 0 AUTRE\n","148. 🔴 block_16_depthwise 8,640 AUTRE\n","149. 🟢 block_16_depthwise_BN 3,840 AUTRE\n","150. 🔴 block_16_depthwise_relu 0 AUTRE\n","151. 🔴 block_16_project 307,200 AUTRE\n","152. 🟢 block_16_project_BN 1,280 AUTRE\n","153. 🔴 Conv_1 409,600 AUTRE\n","154. 🟢 Conv_1_bn 5,120 AUTRE\n","155. 🔴 out_relu 0 AUTRE\n","156. 🟢 decoder_stage0_upsampling 0 DECODER\n","157. 🟢 decoder_stage0_concat 0 DECODER\n","158. 🟢 decoder_stage0a_conv 4,276,224 DECODER\n","159. 🟢 decoder_stage0a_bn 1,024 DECODER\n","160. 🟢 decoder_stage0a_relu 0 DECODER\n","161. 🟢 decoder_stage0b_conv 589,824 DECODER\n","162. 🟢 decoder_stage0b_bn 1,024 DECODER\n","163. 🟢 decoder_stage0b_relu 0 DECODER\n","164. 🟢 decoder_stage1_upsampling 0 DECODER\n","165. 🟢 decoder_stage1_concat 0 DECODER\n","166. 🟢 decoder_stage1a_conv 516,096 DECODER\n","167. 🟢 decoder_stage1a_bn 512 DECODER\n","168. 🟢 decoder_stage1a_relu 0 DECODER\n","169. 🟢 decoder_stage1b_conv 147,456 DECODER\n","170. 🟢 decoder_stage1b_bn 512 DECODER\n","171. 🟢 decoder_stage1b_relu 0 DECODER\n","172. 🟢 decoder_stage2_upsampling 0 DECODER\n","173. 🟢 decoder_stage2_concat 0 DECODER\n","174. 🟢 decoder_stage2a_conv 156,672 DECODER\n","175. 🟢 decoder_stage2a_bn 256 DECODER\n","176. 🟢 decoder_stage2a_relu 0 DECODER\n","177. 🟢 decoder_stage2b_conv 36,864 DECODER\n","178. 🟢 decoder_stage2b_bn 256 DECODER\n","179. 🟢 decoder_stage2b_relu 0 DECODER\n","180. 🟢 decoder_stage3_upsampling 0 DECODER\n","181. 🟢 decoder_stage3_concat 0 DECODER\n","182. 🟢 decoder_stage3a_conv 46,080 DECODER\n","183. 🟢 decoder_stage3a_bn 128 DECODER\n","184. 🟢 decoder_stage3a_relu 0 DECODER\n","185. 🟢 decoder_stage3b_conv 9,216 DECODER\n","186. 🟢 decoder_stage3b_bn 128 DECODER\n","187. 🟢 decoder_stage3b_relu 0 DECODER\n","188. 🟢 decoder_stage4_upsampling 0 DECODER\n","189. 🟢 decoder_stage4a_conv 4,608 DECODER\n","190. 🟢 decoder_stage4a_bn 64 DECODER\n","191. 🟢 decoder_stage4a_relu 0 DECODER\n","192. 🟢 decoder_stage4b_conv 2,304 DECODER\n","193. 🟢 decoder_stage4b_bn 64 DECODER\n","194. 🟢 decoder_stage4b_relu 0 DECODER\n","195. 🟢 final_conv 2,755 AUTRE\n","196. 🟢 softmax 0 AUTRE\n","----------------------------------------------------------------------\n","📊 RÉSUMÉ: 93 entraînables, 103 gelés\n"]}],"source":["# Analyse standard (backbone + résumé)\n","analyze_model_comprehensive(experimental_configurations[4], num_classes=19)\n","\n","# Analyse complète (toutes les couches)\n","analyze_model_comprehensive(experimental_configurations[4], num_classes=19, detailed_layers=True)\n","\n","# Vue compacte des couches uniquement\n","show_all_layers_status(experimental_configurations[4], num_classes=19)"]},{"cell_type":"markdown","metadata":{"id":"yGNRUQdxT4xL"},"source":["## Préparation des données"]},{"cell_type":"markdown","metadata":{"id":"e5mbV7CtEfoS"},"source":["Ici, les données vont être prétraitées et des datasets d'entrainement, de validation et de test vont être constitués.\n","Il est important de noter la correspondance terminologique entre le jeu de données officiel et les jeux de données que nous constituerons dans le cadre de cet entraînement :\\\n","• Split 'train' Cityscapes → Train (80%) + Validation (20%)\\\n","• Split 'val' Cityscapes → Test final\\\n","• Split 'test' Cityscapes → non utilisé\n","\n","En effet, le dossier \"test\" de Cityscapes ne contient pas de masque de vérité et sert à effectuer un benchmark de performances dans le cadre d'un concours Kaggel (résultats cachés, donc)."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"wMEw3js7CNZE"},"outputs":[],"source":["def prepare_cityscapes_dataset(\n"," cityscapes_dir,\n"," split='train',\n"," validation_split=0.2,\n"," batch_size=8,\n"," img_size=(224, 224),\n"," encoder=None,\n"," id_to_group_mapping=None\n","):\n"," \"\"\"\n"," Prépare les datasets Cityscapes avec prétraitement adapté au backbone\n","\n"," Args:\n"," cityscapes_dir (str): Chemin vers le répertoire Cityscapes\n"," split (str): Split Cityscapes à utiliser ('train', 'val', 'test')\n"," validation_split (float): Si split='train', proportion à garder pour validation\n"," batch_size (int): Taille des batches\n"," img_size (tuple): Taille des images (H, W)\n"," encoder (str): Nom du backbone pour preprocessing ou None\n"," id_to_group_mapping (list ou np.ndarray): Mapping des IDs de classes ou None\n","\n"," Returns:\n"," Dataset(s): Si split='train' et validation_split > 0 → (train_dataset, val_dataset)\n"," Sinon → dataset unique\n"," \"\"\"\n"," if not os.path.exists(cityscapes_dir):\n"," raise ValueError(f\"Le répertoire Cityscapes n'existe pas: {cityscapes_dir}\")\n","\n"," images_dir = os.path.join(cityscapes_dir, 'leftImg8bit', split)\n"," masks_dir = os.path.join(cityscapes_dir, 'gtFine', split)\n","\n"," if not os.path.exists(images_dir) or not os.path.exists(masks_dir):\n"," raise ValueError(f\"Split Cityscapes '{split}' non trouvé dans {cityscapes_dir}\")\n","\n"," image_paths = []\n"," mask_paths = []\n","\n"," print(f\"🔍 Lecture du split Cityscapes '{split}'...\")\n","\n"," for city in os.listdir(images_dir):\n"," city_img_dir = os.path.join(images_dir, city)\n"," city_mask_dir = os.path.join(masks_dir, city)\n","\n"," if os.path.isdir(city_img_dir) and os.path.isdir(city_mask_dir):\n"," for file_name in os.listdir(city_img_dir):\n"," if file_name.endswith('_leftImg8bit.png'):\n"," img_path = os.path.join(city_img_dir, file_name)\n"," mask_name = file_name.replace('_leftImg8bit.png', '_gtFine_labelIds.png')\n"," mask_path = os.path.join(city_mask_dir, mask_name)\n"," if os.path.exists(img_path) and os.path.exists(mask_path):\n"," image_paths.append(img_path)\n"," mask_paths.append(mask_path)\n"," else:\n"," print(f\"⚠️ Fichier manquant pour {file_name}\")\n","\n"," print(f\"📊 Split Cityscapes '{split}': {len(image_paths)} images trouvées\")\n","\n"," if len(image_paths) == 0:\n"," raise ValueError(f\"Aucun fichier valide trouvé pour le split '{split}'!\")\n","\n"," if split == 'train' and validation_split > 0:\n"," print(f\"✂️ Découpage en Train/Validation ({int((1-validation_split)*100)}%/{int(validation_split*100)}%)\")\n","\n"," combined = list(zip(image_paths, mask_paths))\n"," random.seed(42)\n"," random.shuffle(combined)\n"," image_paths, mask_paths = zip(*combined)\n","\n"," total_samples = len(image_paths)\n"," val_samples = int(total_samples * validation_split)\n"," train_samples = total_samples - val_samples\n","\n"," train_img_paths = list(image_paths[:train_samples])\n"," train_mask_paths = list(mask_paths[:train_samples])\n"," val_img_paths = list(image_paths[train_samples:])\n"," val_mask_paths = list(mask_paths[train_samples:])\n","\n"," print(f\" └─ 📚 Train final: {len(train_img_paths)} images\")\n"," print(f\" └─ 📊 Validation final: {len(val_img_paths)} images\")\n"," else:\n"," usage = \"Test\" if split == 'val' else split.title()\n"," print(f\"📋 Utilisation complète comme dataset de {usage}\")\n","\n"," train_img_paths, train_mask_paths = image_paths, mask_paths\n"," val_img_paths, val_mask_paths = [], []\n","\n"," preprocessing_fn = get_preprocessing_fn(encoder)\n","\n"," def load_and_preprocess(img_path, mask_path):\n"," img = tf.io.read_file(img_path)\n"," img = tf.image.decode_png(img, channels=3)\n"," img = tf.image.resize(img, img_size, method='bilinear')\n"," img = tf.cast(img, tf.float32)\n"," img = preprocessing_fn(img)\n","\n"," mask = tf.io.read_file(mask_path)\n"," mask = tf.image.decode_png(mask, channels=1)\n"," mask = tf.image.resize(mask, img_size, method='nearest')\n"," mask = tf.cast(mask, tf.int32)\n","\n"," if id_to_group_mapping is not None:\n"," mask = map_mask_ids(mask, id_to_group_mapping)\n","\n"," mask = tf.squeeze(mask, axis=-1)\n"," return img, mask\n","\n"," def augment_data(image, mask):\n"," mask = tf.expand_dims(mask, axis=-1)\n","\n"," if tf.random.uniform(()) > 0.5:\n"," image = tf.image.flip_left_right(image)\n"," mask = tf.image.flip_left_right(mask)\n","\n"," image = tf.image.random_brightness(image, 0.1)\n"," image = tf.clip_by_value(image, 0, 1)\n","\n"," mask = tf.squeeze(mask, axis=-1)\n"," return image, mask\n","\n"," def create_dataset(image_paths, mask_paths, augment=False, shuffle_data=True):\n"," dataset = tf.data.Dataset.from_tensor_slices((image_paths, mask_paths))\n"," dataset = dataset.map(load_and_preprocess, num_parallel_calls=tf.data.AUTOTUNE)\n","\n"," if augment:\n"," dataset = dataset.map(augment_data, num_parallel_calls=tf.data.AUTOTUNE)\n","\n"," if shuffle_data:\n"," dataset = dataset.shuffle(buffer_size=1000)\n","\n"," dataset = dataset.batch(batch_size).prefetch(tf.data.AUTOTUNE)\n"," return dataset\n","\n"," if split == 'train' and validation_split > 0:\n"," train_dataset = create_dataset(train_img_paths, train_mask_paths, augment=True, shuffle_data=True)\n"," val_dataset = create_dataset(val_img_paths, val_mask_paths, augment=False, shuffle_data=False)\n"," return train_dataset, val_dataset\n"," else:\n"," dataset = create_dataset(train_img_paths, train_mask_paths, augment=False, shuffle_data=(split=='train'))\n"," return dataset\n"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":48688,"status":"ok","timestamp":1754919206313,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"VimLczDnCt7l","outputId":"0df294c8-4ff4-4df0-f614-e32476753e2d"},"outputs":[{"output_type":"stream","name":"stdout","text":["=== PRÉPARATION DES DATASETS CITYSCAPES ===\n","📊 Paramètres:\n"," • Taille image: (224, 224)\n"," • Taille batch: 8\n"," • Répertoire: /content/data/cityscapes_unzipped\n","\n","🗂️ Stratégie de découpage:\n"," • Split 'train' Cityscapes → Train (80%) + Validation (20%)\n"," • Split 'val' Cityscapes → Test final\n","\n","--- Découpage du split 'train' Cityscapes en Train/Validation ---\n","🔍 Lecture du split Cityscapes 'train'...\n","📊 Split Cityscapes 'train': 2975 images trouvées\n","✂️ Découpage en Train/Validation (80%/20%)\n"," └─ 📚 Train final: 2380 images\n"," └─ 📊 Validation final: 595 images\n","ℹ️ Modèle vanilla - pas de preprocessing\n","\n","--- Création du dataset de TEST à partir du split 'val' Cityscapes ---\n","🔍 Lecture du split Cityscapes 'val'...\n","📊 Split Cityscapes 'val': 500 images trouvées\n","📋 Utilisation complète comme dataset de Test\n","ℹ️ Modèle vanilla - pas de preprocessing\n","\n","✅ Datasets créés avec succès:\n"," 📚 Train: 2380 images (avec augmentation)\n"," 📊 Validation: 595 images (sans augmentation)\n"," 🧪 Test: 500 images (sans augmentation)\n","\n","📋 Récapitulatif:\n"," • Train dataset: pour l'entraînement des modèles\n"," • Validation dataset: pour la sélection des hyperparamètres\n"," • Test dataset: pour l'évaluation finale (données jamais vues)\n","\n","🔍 Vérification des formes:\n"," Train: images = (8, 224, 224, 3), masques = (8, 224, 224)\n"," Validation: images = (8, 224, 224, 3), masques = (8, 224, 224)\n"," Test: images = (8, 224, 224, 3), masques = (8, 224, 224)\n"]}],"source":["# === UTILISATION AVEC TERMINOLOGIE CLAIRE ===\n","# Définir les paramètres\n","BATCH_SIZE = 8\n","IMG_SIZE = (224, 224)\n","\n","# Vérifier si id_to_group existe, sinon définir None\n","try:\n"," id_mapping = id_to_group\n","except NameError:\n"," print(\"⚠️ Variable 'id_to_group' non définie, pas de mapping des IDs\")\n"," id_mapping = None\n","\n","print(\"=== PRÉPARATION DES DATASETS CITYSCAPES ===\")\n","print(f\"📊 Paramètres:\")\n","print(f\" • Taille image: {IMG_SIZE}\")\n","print(f\" • Taille batch: {BATCH_SIZE}\")\n","print(f\" • Répertoire: {cityscapes_dir}\")\n","\n","print(f\"\\n🗂️ Stratégie de découpage:\")\n","print(f\" • Split 'train' Cityscapes → Train (80%) + Validation (20%)\")\n","print(f\" • Split 'val' Cityscapes → Test final\")\n","\n","try:\n"," # 1. Créer TRAIN + VALIDATION à partir du split 'train' de Cityscapes\n"," print(f\"\\n--- Découpage du split 'train' Cityscapes en Train/Validation ---\")\n"," train_dataset, val_dataset = prepare_cityscapes_dataset(\n"," cityscapes_dir,\n"," split='train', # On utilise le split 'train' de Cityscapes\n"," batch_size=BATCH_SIZE,\n"," img_size=IMG_SIZE,\n"," validation_split=0.2, # 80% train, 20% validation\n"," id_to_group_mapping=id_mapping\n"," )\n","\n"," # 2. Créer TEST à partir du split 'val' de Cityscapes\n"," print(f\"\\n--- Création du dataset de TEST à partir du split 'val' Cityscapes ---\")\n"," test_dataset = prepare_cityscapes_dataset(\n"," cityscapes_dir,\n"," split='val', # On utilise le split 'val' de Cityscapes comme notre test\n"," batch_size=BATCH_SIZE,\n"," img_size=IMG_SIZE,\n"," id_to_group_mapping=id_mapping\n"," )\n","\n"," print(f\"\\n✅ Datasets créés avec succès:\")\n"," print(f\" 📚 Train: {2380} images (avec augmentation)\")\n"," print(f\" 📊 Validation: {595} images (sans augmentation)\")\n"," print(f\" 🧪 Test: {500} images (sans augmentation)\")\n","\n"," print(f\"\\n📋 Récapitulatif:\")\n"," print(f\" • Train dataset: pour l'entraînement des modèles\")\n"," print(f\" • Validation dataset: pour la sélection des hyperparamètres\")\n"," print(f\" • Test dataset: pour l'évaluation finale (données jamais vues)\")\n","\n"," # Vérification rapide\n"," print(f\"\\n🔍 Vérification des formes:\")\n"," for name, dataset in [(\"Train\", train_dataset), (\"Validation\", val_dataset), (\"Test\", test_dataset)]:\n"," sample = next(iter(dataset))\n"," print(f\" {name}: images = {sample[0].shape}, masques = {sample[1].shape}\")\n","\n","except Exception as e:\n"," print(f\"❌ Erreur: {e}\")\n"," print(\"Vérifications:\")\n"," print(\"1. Variable 'cityscapes_dir' définie ?\")\n"," print(\"2. Fichiers Cityscapes extraits ?\")\n"," print(\"3. Structure correcte (leftImg8bit/, gtFine/) ?\")\n"," raise"]},{"cell_type":"markdown","metadata":{"id":"q4W-fiAxSwWR"},"source":["## Visualisation des données"]},{"cell_type":"markdown","metadata":{"id":"aSz8Oa3sS3_n"},"source":["Une visualisation de quelques images (train, val, test) sera proposée avec les masques de vérité dont on propose une colorisation tab10 puis une colorisation plus spécifique"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000,"output_embedded_package_id":"1SBKflUkIHfCCqcNzpwoqmSKVChyGKj2Z"},"executionInfo":{"elapsed":52363,"status":"ok","timestamp":1754916545770,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"mWO3yOl3Oq12","outputId":"df51e8a0-719f-44f9-a87a-b172f488740f"},"outputs":[{"output_type":"display_data","data":{"text/plain":"Output hidden; open in https://colab.research.google.com to view."},"metadata":{}}],"source":["def visualize_cityscapes_samples(\n"," datasets_dict=None,\n"," cityscapes_dir=None,\n"," num_samples=3,\n"," save_dir=None,\n"," show_stats=True,\n"," show_legend=True\n","):\n"," \"\"\"\n"," Visualise des échantillons Cityscapes avec options flexibles\n","\n"," Args:\n"," datasets_dict: {'train': train_dataset, 'val': val_dataset, 'test': test_dataset}\n"," cityscapes_dir: Chemin vers données brutes (si datasets_dict=None)\n"," num_samples: Nombre d'échantillons par dataset\n"," save_dir: Répertoire de sauvegarde (optionnel)\n"," show_stats: Afficher statistiques des classes\n"," show_legend: Créer légende des classes\n"," \"\"\"\n","\n"," # Mode 1: Depuis les datasets TensorFlow (préféré)\n"," if datasets_dict is not None:\n"," print(\"📊 Visualisation depuis les datasets TensorFlow...\")\n"," _visualize_from_datasets(datasets_dict, num_samples, save_dir, show_stats)\n","\n"," # Mode 2: Depuis les fichiers bruts (fallback)\n"," elif cityscapes_dir is not None:\n"," print(\"📁 Visualisation depuis les fichiers bruts...\")\n"," _visualize_from_files(cityscapes_dir, num_samples, save_dir, show_stats)\n","\n"," else:\n"," raise ValueError(\"Fournir soit datasets_dict soit cityscapes_dir\")\n","\n"," # Créer la légende si demandée\n"," if show_legend:\n"," _create_legend(save_dir)\n","\n","def _visualize_from_datasets(datasets_dict, num_samples, save_dir, show_stats):\n"," \"\"\"Visualise depuis les datasets TensorFlow (après preprocessing)\"\"\"\n","\n"," for split_name, dataset in datasets_dict.items():\n"," print(f\"\\n--- {split_name.title()} Dataset ---\")\n","\n"," sample_count = 0\n"," for batch in dataset.take(num_samples):\n"," images, masks = batch\n","\n"," # Prendre le premier échantillon du batch\n"," image = images[0]\n"," mask = masks[0]\n","\n"," # Créer la visualisation\n"," fig = _create_sample_plot(image.numpy(), mask.numpy(),\n"," f\"{split_name.title()} Sample {sample_count+1}\")\n","\n"," # Sauvegarder si demandé\n"," if save_dir:\n"," os.makedirs(save_dir, exist_ok=True)\n"," fig_path = os.path.join(save_dir, f'{split_name}_sample_{sample_count+1}.png')\n"," fig.savefig(fig_path, dpi=150, bbox_inches='tight')\n"," print(f\"💾 Sauvegardé: {fig_path}\")\n","\n"," plt.show()\n"," plt.close(fig)\n","\n"," # Afficher les stats si demandé\n"," if show_stats:\n"," _show_class_stats(mask.numpy())\n","\n"," sample_count += 1\n"," if sample_count >= num_samples:\n"," break\n","\n","def _visualize_from_files(cityscapes_dir, num_samples, save_dir, show_stats):\n"," \"\"\"Visualise depuis les fichiers bruts (fallback)\"\"\"\n","\n"," for split in ['train', 'val']:\n"," print(f\"\\n--- {split.title()} (Raw Files) ---\")\n","\n"," # Collecter les chemins (réutilise la logique de prepare_cityscapes_dataset)\n"," images_dir = os.path.join(cityscapes_dir, 'leftImg8bit', split)\n"," masks_dir = os.path.join(cityscapes_dir, 'gtFine', split)\n","\n"," if not os.path.exists(images_dir):\n"," print(f\"⚠️ Split '{split}' non trouvé, ignoré\")\n"," continue\n","\n"," image_paths, mask_paths = _collect_sample_paths(images_dir, masks_dir, num_samples)\n","\n"," for i, (img_path, mask_path) in enumerate(zip(image_paths, mask_paths)):\n"," # Charger avec PIL\n"," img = np.array(PILImage.open(img_path).resize((512, 256), PILImage.Resampling.BILINEAR))\n"," mask_raw = np.array(PILImage.open(mask_path).resize((512, 256), PILImage.Resampling.NEAREST))\n","\n"," # Appliquer le mapping (vérifier que id_to_group existe)\n"," if 'id_to_group' in globals():\n"," mask = id_to_group[mask_raw]\n"," else:\n"," print(\"⚠️ Variable 'id_to_group' non trouvée, utilisation brute\")\n"," mask = mask_raw\n","\n"," # Normaliser l'image pour l'affichage\n"," img_normalized = img.astype(np.float32) / 255.0\n","\n"," # Créer la visualisation\n"," fig = _create_sample_plot(img_normalized, mask, f\"{split.title()} Raw Sample {i+1}\")\n","\n"," # Sauvegarder si demandé\n"," if save_dir:\n"," os.makedirs(save_dir, exist_ok=True)\n"," fig_path = os.path.join(save_dir, f'{split}_raw_sample_{i+1}.png')\n"," fig.savefig(fig_path, dpi=150, bbox_inches='tight')\n"," print(f\"💾 Sauvegardé: {fig_path}\")\n","\n"," plt.show()\n"," plt.close(fig)\n","\n"," # Afficher les stats si demandé\n"," if show_stats:\n"," _show_class_stats(mask)\n","\n","def _create_sample_plot(image, mask, title):\n"," \"\"\"Crée le plot avec les 3 vues (factorisation du code de visualisation)\"\"\"\n","\n"," fig, axes = plt.subplots(1, 3, figsize=(15, 5))\n"," fig.suptitle(title, fontsize=14)\n","\n"," # Vue 1: Image originale\n"," axes[0].imshow(image)\n"," axes[0].set_title(\"Image Originale\")\n"," axes[0].axis('off')\n","\n"," # Vue 2: Masque avec IDs (en tab10)\n"," im = axes[1].imshow(mask, cmap='tab10', vmin=0, vmax=mapping_config['num_classes']-1)\n"," axes[1].set_title(\"Masque (IDs de classes)\")\n"," axes[1].axis('off')\n","\n"," # Vue 3: Masque colorisé avec nos couleurs\n"," colored_mask = _colorize_mask(mask)\n"," axes[2].imshow(colored_mask)\n"," axes[2].set_title(\"Masque Segmenté (Coloré)\")\n"," axes[2].axis('off')\n","\n"," plt.tight_layout()\n"," return fig\n","\n","def _colorize_mask(mask):\n"," \"\"\"Applique la colorisation du masque (logique centralisée)\"\"\"\n"," colored_mask = np.zeros((mask.shape[0], mask.shape[1], 3), dtype=np.uint8)\n"," for group_id in range(mapping_config['num_classes']):\n"," colored_mask[mask == group_id] = mapping_config['group_colors'][group_id]\n"," return colored_mask\n","\n","def _show_class_stats(mask):\n"," \"\"\"Affiche les statistiques des classes (factorisation)\"\"\"\n"," unique_classes, counts = np.unique(mask, return_counts=True)\n"," print(\"\\n📊 Classes présentes dans cette image:\")\n"," for class_id, count in zip(unique_classes, counts):\n"," if class_id < len(mapping_config['group_names']): # Vérification bounds\n"," percentage = (count / mask.size) * 100\n"," print(f\" {mapping_config['group_names'][class_id]}: {count} pixels ({percentage:.1f}%)\")\n","\n","def _collect_sample_paths(images_dir, masks_dir, num_samples):\n"," \"\"\"Collecte aléatoirement des chemins d'images (factorisation)\"\"\"\n"," image_paths, mask_paths = [], []\n","\n"," for city in os.listdir(images_dir):\n"," city_img_dir = os.path.join(images_dir, city)\n"," city_mask_dir = os.path.join(masks_dir, city)\n","\n"," if os.path.isdir(city_img_dir) and os.path.isdir(city_mask_dir):\n"," for file_name in os.listdir(city_img_dir):\n"," if file_name.endswith('_leftImg8bit.png'):\n"," img_path = os.path.join(city_img_dir, file_name)\n"," mask_name = file_name.replace('_leftImg8bit.png', '_gtFine_labelIds.png')\n"," mask_path = os.path.join(city_mask_dir, mask_name)\n","\n"," if os.path.exists(mask_path):\n"," image_paths.append(img_path)\n"," mask_paths.append(mask_path)\n","\n"," # Sélection aléatoire\n"," if len(image_paths) > num_samples:\n"," selected_indices = np.random.choice(len(image_paths), size=num_samples, replace=False)\n"," image_paths = [image_paths[i] for i in selected_indices]\n"," mask_paths = [mask_paths[i] for i in selected_indices]\n","\n"," return image_paths, mask_paths\n","\n","def _create_legend(save_dir):\n"," \"\"\"Crée la légende des classes (factorisation)\"\"\"\n"," fig, ax = plt.subplots(figsize=(8, 5))\n"," fig.suptitle(\"Légende des classes de segmentation\", fontsize=14)\n","\n"," for i, (name, color) in enumerate(zip(mapping_config['group_names'], mapping_config['group_colors'])):\n"," ax.fill_between([0, 1], [i, i], [i+0.9, i+0.9], color=[c/255 for c in color])\n"," ax.text(1.1, i+0.5, name, va='center', fontsize=12)\n","\n"," ax.set_xlim(0, 2.5)\n"," ax.set_ylim(len(mapping_config['group_names'])-0.1, -0.1)\n"," ax.axis('off')\n","\n"," if save_dir:\n"," os.makedirs(save_dir, exist_ok=True)\n"," legend_path = os.path.join(save_dir, 'class_legend.png')\n"," fig.savefig(legend_path, dpi=150, bbox_inches='tight')\n"," print(f\"🏷️ Légende sauvegardée: {legend_path}\")\n","\n"," plt.show()\n"," plt.close(fig)\n","\n","# === UTILISATION SIMPLIFIÉE ===\n","print(\"=== VISUALISATION DES ÉCHANTILLONS CITYSCAPES ===\")\n","\n","# Méthode préférée: depuis les datasets TensorFlow\n","datasets_dict = {\n"," 'train': train_dataset,\n"," 'val': val_dataset,\n"," 'test': test_dataset\n","}\n","\n","# Créer le dossier de sauvegarde\n","viz_dir = os.path.join(data_dir, 'samples') if 'data_dir' in globals() else './visualizations'\n","\n","# Visualiser avec toutes les options\n","visualize_cityscapes_samples(\n"," datasets_dict=datasets_dict,\n"," num_samples=2, # 2 échantillons par dataset\n"," save_dir=viz_dir,\n"," show_stats=True,\n"," show_legend=True\n",")"]},{"cell_type":"markdown","metadata":{"id":"BcRXJIz6Ts6q"},"source":["## Entrainement du modèle"]},{"cell_type":"code","execution_count":15,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":60,"status":"ok","timestamp":1754980948757,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"lUxAq504vmjH","outputId":"81e42c45-ca7d-4d73-c853-3f8d08331813"},"outputs":[{"output_type":"stream","name":"stdout","text":["🚀 MODE PRODUCTION ACTIVÉ\n","📊 Configuration globale: Device=/CPU:0, Max_Epochs=20\n"," Patience EarlyStopping=5, Patience LR=3\n"]}],"source":["# ====================================================================\n","# SCRIPT D'ENTRAÎNEMENT OPTIMISÉ POUR SEGMENTATION MULTI-CONFIGURATIONS\n","# AVEC SYSTÈME DE REPRISE AUTOMATIQUE\n","# ====================================================================\n","\n","# 🚨 PARAMÈTRE PRINCIPAL : Basculer entre TEST et PRODUCTION\n","TEST_MODE = False # Mettre False pour le mode production\n","\n","# Configuration selon le mode\n","if TEST_MODE:\n"," print(\"🧪 MODE TEST ACTIVÉ\")\n"," DEVICE_CONFIG = '/CPU:0'\n"," MAX_EPOCHS = 2 # Très rapide pour les tests\n"," EARLY_STOPPING_PATIENCE = 2 # Arrêt anticipé si pas d'amélioration pendant 2 époques\n"," LR_REDUCE_PATIENCE = 1 # Réduction LR si pas d'amélioration pendant 1 époque\n"," SUBSET_SIZE = 20\n"," # Taille fixe pour les tests (plus rapide)\n"," TEST_IMG_SIZE = (128, 128)\n"," TEST_BATCH_SIZE = 2\n"," TEST_MAX_CONFIGS = None # Nombre max de configs à tester\n"," # Expérience MLflow déjà définie en début de notebook\n","else:\n"," print(\"🚀 MODE PRODUCTION ACTIVÉ\")\n"," DEVICE_CONFIG = '/GPU:0' if tf.config.list_physical_devices('GPU') else '/CPU:0'\n"," MAX_EPOCHS = 20 # 20 époques max (beaucoup de modèles à tester)\n"," EARLY_STOPPING_PATIENCE = 5 # Arrêt anticipé si pas d'amélioration pendant 5 époques\n"," LR_REDUCE_PATIENCE = 3 # Réduction LR si pas d'amélioration pendant 3 époques\n"," SUBSET_SIZE = None\n"," # En production, utilise les paramètres de chaque configuration\n"," # Expérience MLflow déjà définie en début de notebook\n","\n","print(f\"📊 Configuration globale: Device={DEVICE_CONFIG}, Max_Epochs={MAX_EPOCHS}\")\n","print(f\" Patience EarlyStopping={EARLY_STOPPING_PATIENCE}, Patience LR={LR_REDUCE_PATIENCE}\")"]},{"cell_type":"code","execution_count":16,"metadata":{"id":"RqI-umcJvt9u","executionInfo":{"status":"ok","timestamp":1754980948757,"user_tz":-120,"elapsed":58,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"outputs":[],"source":["# ====================================================================\n","# SYSTÈME DE REPRISE AUTOMATIQUE - VÉRIFICATION MLFLOW\n","# ====================================================================\n","\n","def get_completed_experiments(experiment_name=\"OC Projet 8\"):\n"," \"\"\"\n"," Récupère la liste des expériences déjà terminées dans MLflow\n"," Retourne un set des noms de runs terminés\n"," \"\"\"\n"," try:\n"," print(f\"🔍 Vérification des expériences déjà terminées dans '{experiment_name}'...\")\n","\n"," # Récupérer l'expérience par nom\n"," experiment = mlflow.get_experiment_by_name(experiment_name)\n"," if experiment is None:\n"," print(f\"⚠️ Expérience '{experiment_name}' non trouvée\")\n"," return set()\n","\n"," # Rechercher tous les runs de cette expérience\n"," runs = mlflow.search_runs(\n"," experiment_ids=[experiment.experiment_id],\n"," filter_string=\"status = 'FINISHED'\", # Seulement les runs terminés avec succès\n"," output_format=\"pandas\"\n"," )\n","\n"," if runs.empty:\n"," print(\"📊 Aucune expérience terminée trouvée\")\n"," return set()\n","\n"," # Extraire les noms des runs terminés\n"," completed_runs = set()\n"," for idx, run in runs.iterrows():\n"," run_name = run.get('tags.mlflow.runName', '')\n"," if run_name:\n"," completed_runs.add(run_name)\n","\n"," print(f\"✅ {len(completed_runs)} expériences terminées trouvées:\")\n"," for run_name in sorted(completed_runs):\n"," print(f\" - {run_name}\")\n","\n"," return completed_runs\n","\n"," except Exception as e:\n"," print(f\"⚠️ Erreur lors de la vérification MLflow: {e}\")\n"," print(\"🔄 Continuera sans vérification (tous les modèles seront entraînés)\")\n"," return set()\n","\n","\n","def generate_stable_run_name(config, test_mode=False):\n"," \"\"\"\n"," Génère un nom de run stable (sans date) basé sur la configuration\n"," Format: {config_name}_{mode}\n"," \"\"\"\n"," base_name = config['name']\n"," mode_suffix = \"test\" if test_mode else \"prod\"\n"," return f\"{base_name}_{mode_suffix}\"\n","\n","\n","def filter_configs_to_run(experimental_configurations, experiment_name=\"OC Projet 8\"):\n"," \"\"\"\n"," Filtre les configurations pour ne garder que celles non encore entraînées\n"," \"\"\"\n"," completed_runs = get_completed_experiments(experiment_name)\n","\n"," if not completed_runs:\n"," print(\"🚀 Aucune expérience terminée trouvée, tous les modèles seront entraînés\")\n"," return list(range(len(experimental_configurations)))\n","\n"," configs_to_run = []\n"," skipped_configs = []\n","\n"," for idx, config in enumerate(experimental_configurations):\n"," expected_run_name = generate_stable_run_name(config, TEST_MODE)\n","\n"," if expected_run_name in completed_runs:\n"," skipped_configs.append((idx, config['name'], expected_run_name))\n"," else:\n"," configs_to_run.append(idx)\n","\n"," # Rapport de filtrage\n"," print(f\"\\n📊 FILTRAGE DES CONFIGURATIONS:\")\n"," print(f\"✅ À entraîner: {len(configs_to_run)} configurations\")\n"," print(f\"⏭️ Déjà terminées: {len(skipped_configs)} configurations\")\n","\n"," if skipped_configs:\n"," print(f\"\\n⏭️ CONFIGURATIONS IGNORÉES (déjà terminées):\")\n"," for idx, config_name, run_name in skipped_configs:\n"," print(f\" [{idx}] {config_name} → {run_name}\")\n","\n"," if configs_to_run:\n"," print(f\"\\n🚀 CONFIGURATIONS À ENTRAÎNER:\")\n"," for idx in configs_to_run:\n"," config_name = experimental_configurations[idx]['name']\n"," expected_run_name = generate_stable_run_name(experimental_configurations[idx], TEST_MODE)\n"," print(f\" [{idx}] {config_name} → {expected_run_name}\")\n","\n"," return configs_to_run"]},{"cell_type":"code","execution_count":17,"metadata":{"id":"yXkQoZssvwTt","executionInfo":{"status":"ok","timestamp":1754980948757,"user_tz":-120,"elapsed":18,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"outputs":[],"source":["# ====================================================================\n","# CALLBACK MLFLOW PERSONNALISÉ POUR LOGGING DÉTAILLÉ\n","# ====================================================================\n","\n","class ExperimentMLflowCallback(tf.keras.callbacks.Callback):\n"," \"\"\"Callback MLflow personnalisé pour logging complet des métriques\"\"\"\n","\n"," def __init__(self, config, run_id, batch_size, img_size):\n"," super().__init__()\n"," self.config = config\n"," self.run_id = run_id\n"," self.batch_size = batch_size\n"," self.img_size = img_size\n","\n"," def on_epoch_end(self, epoch, logs=None):\n"," \"\"\"Log des métriques à chaque époque (sans doublons)\"\"\"\n"," logs = logs or {}\n"," for name, value in logs.items():\n"," # Éviter les doublons : ignorer les métriques \"validation_\"\n"," if not name.startswith('validation_'):\n"," mlflow.log_metric(name, float(value), step=epoch)\n","\n"," def on_train_begin(self, logs=None):\n"," \"\"\"Log des paramètres au début de l'entraînement\"\"\"\n"," # Log config du modèle\n"," mlflow.log_param(\"model_architecture\", self.config[\"architecture\"])\n"," mlflow.log_param(\"model_name\", self.config[\"name\"])\n"," mlflow.log_param(\"encoder\", self.config.get(\"encoder\", \"None\"))\n"," mlflow.log_param(\"encoder_freeze\", self.config.get(\"encoder_freeze\", False))\n","\n"," # Log config du script (utilise les paramètres passés au callback)\n"," mlflow.log_param(\"script_batch_size\", self.batch_size)\n"," mlflow.log_param(\"script_img_size\", str(self.img_size))\n"," mlflow.log_param(\"test_mode\", TEST_MODE)\n"," mlflow.log_param(\"max_epochs\", MAX_EPOCHS)\n"," mlflow.log_param(\"device\", DEVICE_CONFIG)\n"," mlflow.log_param(\"subset_size\", SUBSET_SIZE)\n","\n","\n","class KerasModelCheckpoint(tf.keras.callbacks.Callback):\n"," \"\"\"Callback personnalisé pour sauvegarder en format .keras natif\"\"\"\n","\n"," def __init__(self, filepath, monitor='val_loss', save_best_only=True, mode='auto', verbose=1):\n"," super().__init__()\n"," self.filepath = filepath\n"," self.monitor = monitor\n"," self.save_best_only = save_best_only\n"," self.verbose = verbose\n","\n"," if mode == 'auto':\n"," if 'acc' in monitor or monitor.startswith('fmeasure'):\n"," self.mode = 'max'\n"," else:\n"," self.mode = 'min'\n"," else:\n"," self.mode = mode\n","\n"," if self.mode == 'min':\n"," self.best = float('inf')\n"," else:\n"," self.best = -float('inf')\n","\n"," def on_epoch_end(self, epoch, logs=None):\n"," logs = logs or {}\n"," current = logs.get(self.monitor)\n","\n"," if current is None:\n"," if self.verbose > 0:\n"," print(f'Warning: Metric {self.monitor} not found in logs.')\n"," return\n","\n"," if self.save_best_only:\n"," if (self.mode == 'min' and current < self.best) or (self.mode == 'max' and current > self.best):\n"," self.best = current\n","\n"," if self.verbose > 0:\n"," print(f'Epoch {epoch + 1}: {self.monitor} improved from {self.best} to {current:.5f}, saving model to {self.filepath}')\n","\n"," # SAUVEGARDE NATIVE KERAS - AUCUN WARNING !\n"," self.model.save(self.filepath, save_format='keras')\n"," else:\n"," if self.verbose > 0:\n"," print(f'Epoch {epoch + 1}: {self.monitor} did not improve from {self.best:.5f}')\n"," else:\n"," if self.verbose > 0:\n"," print(f'Epoch {epoch + 1}: saving model to {self.filepath}')\n"," self.model.save(self.filepath, save_format='keras')"]},{"cell_type":"code","source":["def calculate_detailed_metrics(model, test_dataset, num_classes, class_names=None):\n"," \"\"\"\n"," Calcule uniquement l'IoU par classe et les statistiques détaillées\n"," (Le mean_iou global est maintenant calculé par la métrique officielle)\n"," \"\"\"\n"," print(\" 📊 Analyse détaillée par classe...\")\n","\n"," all_true_masks = []\n"," all_pred_masks = []\n","\n"," # Collecter toutes les prédictions\n"," for batch_idx, (images, true_masks) in enumerate(test_dataset):\n"," predictions = model.predict(images, verbose=0)\n"," pred_masks = tf.argmax(predictions, axis=-1)\n","\n"," all_true_masks.extend(true_masks.numpy())\n"," all_pred_masks.extend(pred_masks.numpy())\n","\n"," if batch_idx % 10 == 0:\n"," print(f\" Batch {batch_idx + 1} traité...\")\n","\n"," all_true_masks = np.array(all_true_masks)\n"," all_pred_masks = np.array(all_pred_masks)\n","\n"," print(f\" Total d'images évaluées: {len(all_true_masks)}\")\n","\n"," # Calcul IoU par classe (pour analyse détaillée)\n"," class_ious = []\n"," class_stats = []\n","\n"," for class_id in range(num_classes):\n"," # Masques binaires pour cette classe\n"," true_binary = (all_true_masks == class_id)\n"," pred_binary = (all_pred_masks == class_id)\n","\n"," # Calcul IoU\n"," intersection = np.logical_and(true_binary, pred_binary).sum()\n"," union = np.logical_or(true_binary, pred_binary).sum()\n","\n"," iou = intersection / union if union > 0 else 0.0\n"," class_ious.append(iou)\n","\n"," # Statistiques de classe\n"," true_pixels = true_binary.sum()\n"," pred_pixels = pred_binary.sum()\n"," total_pixels = all_true_masks.size\n","\n"," class_name = class_names[class_id] if class_names else f\"Class_{class_id}\"\n","\n"," class_stats.append({\n"," 'class_id': class_id,\n"," 'class_name': class_name,\n"," 'iou': iou,\n"," 'true_pixels': true_pixels,\n"," 'pred_pixels': pred_pixels,\n"," 'true_percentage': 100 * true_pixels / total_pixels,\n"," 'pred_percentage': 100 * pred_pixels / total_pixels\n"," })\n","\n"," # Mean IoU calculé ici (pour cohérence avec l'affichage)\n"," mean_iou = np.mean(class_ious)\n","\n"," # Affichage des résultats détaillés\n"," print(f\"\\n📊 ANALYSE DÉTAILLÉE PAR CLASSE:\")\n"," print(\"-\" * 70)\n"," print(f\"{'Classe':<15} {'IoU':<8} {'Vrais %':<10} {'Prédits %':<12}\")\n"," print(\"-\" * 70)\n","\n"," for stats in class_stats:\n"," print(f\"{stats['class_name']:<15} {stats['iou']:<8.4f} {stats['true_percentage']:<10.2f} {stats['pred_percentage']:<12.2f}\")\n","\n"," print(\"-\" * 70)\n"," print(f\"{'MEAN IoU (calc)':<15} {mean_iou:<8.4f}\")\n"," print(\"💡 Le Mean IoU officiel (métrique Keras) fait référence\")\n","\n"," return {\n"," 'class_ious': class_ious,\n"," 'mean_iou': mean_iou, # Pour compatibilité avec le code existant\n"," 'class_stats': class_stats,\n"," 'all_true_masks': all_true_masks,\n"," 'all_pred_masks': all_pred_masks\n"," }\n"],"metadata":{"id":"9-rX20362Pz2","executionInfo":{"status":"ok","timestamp":1754980948758,"user_tz":-120,"elapsed":18,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"execution_count":18,"outputs":[]},{"cell_type":"code","source":["def setup_training_components(config, run_id):\n"," \"\"\"\n"," Setup complet : paramètres, datasets, modèle, compilation, callbacks\n"," VERSION CORRIGÉE avec métriques officielles Keras\n"," \"\"\"\n"," # === EXTRACTION DES PARAMÈTRES DE LA CONFIG ===\n"," if TEST_MODE:\n"," batch_size = TEST_BATCH_SIZE\n"," img_size = TEST_IMG_SIZE\n"," print(f\"🧪 Mode test: batch_size={batch_size}, img_size={img_size}\")\n"," else:\n"," batch_size = config['params']['batch_size']\n"," img_size = config['params']['img_size']\n"," print(f\"🚀 Mode production: batch_size={batch_size}, img_size={img_size}\")\n","\n"," # === PRÉPARATION DES DONNÉES ===\n"," print(\"\\n📊 Préparation des datasets...\")\n"," try:\n"," id_mapping = id_to_group\n"," mlflow.log_param(\"class_mapping\", \"custom_id_to_group\")\n"," except NameError:\n"," print(\"⚠️ Variable 'id_to_group' non définie\")\n"," id_mapping = None\n"," mlflow.log_param(\"class_mapping\", \"none\")\n","\n"," # Créer les datasets avec les bons paramètres\n"," train_dataset, val_dataset = prepare_cityscapes_dataset(\n"," cityscapes_dir,\n"," split='train',\n"," batch_size=batch_size,\n"," img_size=img_size,\n"," validation_split=0.2,\n"," id_to_group_mapping=id_mapping\n"," )\n"," test_dataset = prepare_cityscapes_dataset(\n"," cityscapes_dir,\n"," split='val',\n"," batch_size=batch_size,\n"," img_size=img_size,\n"," id_to_group_mapping=id_mapping\n"," )\n","\n"," if TEST_MODE and SUBSET_SIZE:\n"," train_batches = SUBSET_SIZE // batch_size\n"," val_batches = SUBSET_SIZE // (batch_size * 4)\n"," test_batches = SUBSET_SIZE // (batch_size * 4)\n"," train_samples_used = train_batches * batch_size\n"," val_samples_used = val_batches * batch_size\n"," test_samples_used = test_batches * batch_size\n","\n"," print(f\"🧪 Mode test: limitation appliquée\")\n"," print(f\" └─ 📚 Train utilisé: {train_samples_used} images ({train_batches} batches)\")\n"," print(f\" └─ 📊 Validation utilisé: {val_samples_used} images ({val_batches} batches)\")\n"," print(f\" └─ 🧪 Test utilisé: {test_samples_used} images ({test_batches} batches)\")\n","\n"," train_dataset = train_dataset.take(train_batches)\n"," val_dataset = val_dataset.take(val_batches)\n"," test_dataset = test_dataset.take(test_batches)\n","\n"," # === CRÉATION DU MODÈLE ===\n"," print(f\"\\n🏗️ Création du modèle {config['name']}...\")\n"," if TEST_MODE:\n"," config_modified = config.copy()\n"," config_modified['params'] = config['params'].copy()\n"," config_modified['params']['img_size'] = img_size\n"," config_modified['params']['batch_size'] = batch_size\n"," model_config = config_modified\n"," else:\n"," model_config = config\n","\n"," with tf.device(DEVICE_CONFIG):\n"," model = create_model_from_config(model_config, mapping_config['num_classes'])\n"," num_classes_from_model = model.output_shape[-1]\n"," print(f\"📊 Nombre de classes: {num_classes_from_model}\")\n"," total_params = model.count_params()\n"," trainable_params = sum([tf.keras.backend.count_params(w) for w in model.trainable_weights])\n"," print(f\"📊 Paramètres: {total_params:,} total | {trainable_params:,} entraînables\")\n","\n"," # === COMPILATION AVEC MÉTRIQUES OFFICIELLES KERAS ===\n"," print(\"\\n⚙️ Compilation du modèle avec métriques officielles...\")\n","\n"," # ✅ MÉTRIQUES OFFICIELLES KERAS - AUCUNE MÉTRIQUE PERSONNALISÉE !\n"," metrics_list = [\n"," # Accuracy officielle pour classification sparse\n"," tf.keras.metrics.SparseCategoricalAccuracy(name='sparse_categorical_accuracy'),\n","\n"," # IoU officielle Keras - LA métrique de référence pour segmentation\n"," tf.keras.metrics.MeanIoU(\n"," num_classes=num_classes_from_model,\n"," name='mean_iou',\n"," sparse_y_true=True, # Les labels sont des entiers (pas one-hot)\n"," sparse_y_pred=False # Les prédictions sont des probabilités\n"," )\n"," ]\n","\n"," # Métrique principale pour les callbacks\n"," primary_metric = 'val_mean_iou'\n"," primary_mode = 'max'\n","\n"," print(\"🎯 MÉTRIQUES OFFICIELLES KERAS POUR SEGMENTATION SÉMANTIQUE:\")\n"," print(\" 🔥 LOSS: sparse_categorical_crossentropy\")\n"," print(\" └─ Optimise la classification pixel-par-pixel\")\n"," print(\" 📊 MÉTRIQUES (100% officielles Keras):\")\n"," print(\" ├─ SparseCategoricalAccuracy: % pixels correctement classifiés\")\n"," print(\" └─ MeanIoU: Intersection over Union (métrique gold standard)\")\n"," print(\" 🎛️ CALLBACKS:\")\n"," print(f\" └─ Monitor: {primary_metric} (IoU = métrique de référence)\")\n"," print(\"✅ Configuration 100% standard et fiable !\")\n","\n"," # Compilation du modèle\n"," model.compile(\n"," optimizer=tf.keras.optimizers.Adam(learning_rate=0.001),\n"," loss='sparse_categorical_crossentropy',\n"," metrics=metrics_list\n"," )\n","\n"," # === CALLBACKS OPTIMISÉS ===\n"," print(f\"\\n📋 Configuration des callbacks...\")\n"," print(\"🎛️ CALLBACKS BASÉS SUR MEAN_IOU OFFICIEL:\")\n"," print(f\" ├─ EarlyStopping: Arrêt si {primary_metric} stagne {EARLY_STOPPING_PATIENCE} époques\")\n"," print(f\" ├─ ReduceLROnPlateau: Réduction LR si {primary_metric} stagne {LR_REDUCE_PATIENCE} époques\")\n"," print(f\" └─ ModelCheckpoint: Sauvegarde du meilleur modèle selon {primary_metric}\")\n","\n"," artifacts_dir = f\"artifacts/run_{run_id}\"\n"," os.makedirs(artifacts_dir, exist_ok=True)\n","\n"," mlflow_callback = ExperimentMLflowCallback(config, run_id, batch_size, img_size)\n","\n"," callbacks_list = [\n"," mlflow_callback,\n"," tf.keras.callbacks.ReduceLROnPlateau(\n"," monitor=primary_metric,\n"," factor=0.2,\n"," patience=LR_REDUCE_PATIENCE,\n"," verbose=1,\n"," min_lr=1e-6,\n"," mode=primary_mode\n"," ),\n"," tf.keras.callbacks.EarlyStopping(\n"," monitor=primary_metric,\n"," patience=EARLY_STOPPING_PATIENCE,\n"," restore_best_weights=True,\n"," verbose=1,\n"," mode=primary_mode\n"," ),\n"," KerasModelCheckpoint(\n"," filepath=os.path.join(artifacts_dir, 'best_model.keras'),\n"," monitor=primary_metric,\n"," save_best_only=True,\n"," mode=primary_mode,\n"," verbose=1\n"," ),\n"," tf.keras.callbacks.TensorBoard(\n"," log_dir=os.path.join(artifacts_dir, 'tensorboard'),\n"," histogram_freq=1\n"," )\n"," ]\n","\n"," return {\n"," 'model': model,\n"," 'train_dataset': train_dataset,\n"," 'val_dataset': val_dataset,\n"," 'test_dataset': test_dataset,\n"," 'callbacks_list': callbacks_list,\n"," 'artifacts_dir': artifacts_dir,\n"," 'num_classes_from_model': num_classes_from_model,\n"," 'batch_size': batch_size,\n"," 'img_size': img_size\n"," }\n","\n","def train_model_core(model, train_dataset, val_dataset, callbacks_list, max_epochs):\n"," \"\"\"\n"," Fonction pure d'entraînement - ne fait que l'entraînement\n"," \"\"\"\n"," print(f\"\\n🚀 Début de l'entraînement ({max_epochs} epochs max)...\")\n"," start_time = time.time()\n","\n"," with tf.device(DEVICE_CONFIG):\n"," history = model.fit(\n"," train_dataset,\n"," validation_data=val_dataset,\n"," epochs=max_epochs,\n"," callbacks=callbacks_list,\n"," verbose=1\n"," )\n","\n"," training_time = time.time() - start_time\n"," mlflow.log_metric(\"training_time_seconds\", training_time)\n"," print(f\"⏱️ Temps d'entraînement: {training_time:.2f}s\")\n","\n"," return history, training_time\n","\n","def evaluate_model_comprehensive(model, test_dataset, num_classes_from_model, artifacts_dir):\n"," \"\"\"\n"," Évaluation complète avec métriques officielles Keras + analyses détaillées\n"," \"\"\"\n"," # === ÉVALUATION AVEC MÉTRIQUES OFFICIELLES (même config que l'entraînement) ===\n"," print(\"\\n📊 Évaluation avec métriques officielles Keras...\")\n","\n"," # Créer exactement les mêmes métriques que pendant l'entraînement\n"," official_metrics = [\n"," tf.keras.metrics.SparseCategoricalAccuracy(name='sparse_categorical_accuracy'),\n"," tf.keras.metrics.MeanIoU(\n"," num_classes=num_classes_from_model,\n"," name='mean_iou',\n"," sparse_y_true=True,\n"," sparse_y_pred=False\n"," )\n"," ]\n","\n"," # Compiler temporairement avec les métriques officielles\n"," # (ça ne change pas les poids, juste les métriques)\n"," model.compile(\n"," optimizer=model.optimizer, # Garder l'optimizer existant\n"," loss=model.loss, # Garder la loss existante\n"," metrics=official_metrics\n"," )\n","\n"," # Évaluation officielle\n"," test_results = model.evaluate(test_dataset, verbose=1)\n","\n"," basic_test_metrics = {\n"," 'loss': test_results[0],\n"," 'sparse_categorical_accuracy': test_results[1],\n"," 'mean_iou': test_results[2]\n"," }\n","\n"," # Log dans MLflow\n"," for metric_name, value in basic_test_metrics.items():\n"," mlflow.log_metric(f\"test_{metric_name}\", value)\n"," print(f\"✅ Test {metric_name} (officiel): {value:.4f}\")\n","\n"," # === ÉVALUATION DÉTAILLÉE ADDITIONNELLE (pour analyse par classe) ===\n"," try:\n"," class_names = mapping_config['group_names'] if 'group_names' in mapping_config else None\n"," except:\n"," class_names = [f\"Class_{i}\" for i in range(num_classes_from_model)]\n","\n"," print(\"\\n🔍 Calcul des métriques détaillées par classe...\")\n"," detailed_metrics = calculate_detailed_metrics(\n"," model, test_dataset, num_classes_from_model, class_names\n"," )\n","\n"," # Log des métriques par classe (en complément)\n"," for i, iou in enumerate(detailed_metrics['class_ious']):\n"," mlflow.log_metric(f\"class_{i}_iou\", iou)\n","\n"," # === MATRICE DE CONFUSION ===\n"," print(\"\\n🔥 Génération de la matrice de confusion...\")\n"," confusion_matrix_data = generate_confusion_matrix(\n"," model, test_dataset, num_classes_from_model, class_names, artifacts_dir\n"," )\n","\n"," return basic_test_metrics, detailed_metrics, confusion_matrix_data, class_names\n","\n","def generate_confusion_matrix(model, test_dataset, num_classes, class_names, artifacts_dir):\n"," \"\"\"\n"," Génère la matrice de confusion sur le jeu de test et la sauvegarde (SANS AFFICHAGE)\n"," \"\"\"\n"," print(\"📊 Calcul de la matrice de confusion...\")\n","\n"," # Collecter toutes les prédictions\n"," y_true_all = []\n"," y_pred_all = []\n","\n"," for batch_images, batch_masks in test_dataset:\n"," # Prédictions du modèle\n"," predictions = model.predict(batch_images, verbose=0)\n"," pred_classes = tf.argmax(predictions, axis=-1)\n","\n"," # Aplatir les masques et prédictions\n"," true_flat = tf.reshape(batch_masks, [-1]).numpy()\n"," pred_flat = tf.reshape(pred_classes, [-1]).numpy()\n","\n"," y_true_all.extend(true_flat)\n"," y_pred_all.extend(pred_flat)\n","\n"," # Calcul de la matrice de confusion\n"," from sklearn.metrics import confusion_matrix\n"," import itertools\n","\n"," cm = confusion_matrix(y_true_all, y_pred_all, labels=range(num_classes))\n","\n"," # === CRÉATION DE LA VISUALISATION (SANS AFFICHAGE) ===\n"," plt.figure(figsize=(10, 8))\n"," plt.imshow(cm, interpolation='nearest', cmap=plt.cm.Blues)\n"," plt.title('Matrice de Confusion - Jeu de Test', fontsize=14)\n"," plt.colorbar()\n","\n"," # Définir les labels des axes\n"," if class_names:\n"," tick_marks = np.arange(len(class_names))\n"," plt.xticks(tick_marks, class_names, rotation=45, ha='right')\n"," plt.yticks(tick_marks, class_names)\n"," else:\n"," tick_marks = np.arange(num_classes)\n"," plt.xticks(tick_marks, [f\"Class_{i}\" for i in range(num_classes)])\n"," plt.yticks(tick_marks, [f\"Class_{i}\" for i in range(num_classes)])\n","\n"," # === AFFICHER LES VALEURS DANS CHAQUE CELLULE ===\n"," thresh = cm.max() / 2.0\n"," for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n"," plt.text(j, i, format(cm[i, j], 'd'),\n"," horizontalalignment=\"center\",\n"," verticalalignment=\"center\",\n"," color=\"white\" if cm[i, j] > thresh else \"black\",\n"," fontsize=10,\n"," fontweight='bold')\n","\n"," plt.ylabel('Vraie classe', fontsize=12)\n"," plt.xlabel('Classe prédite', fontsize=12)\n"," plt.tight_layout()\n","\n"," # Sauvegarder l'image (SANS AFFICHAGE)\n"," cm_image_path = os.path.join(artifacts_dir, 'confusion_matrix.png')\n"," plt.savefig(cm_image_path, dpi=300, bbox_inches='tight')\n"," plt.close() # ✅ FERMER LE PLOT - PAS D'AFFICHAGE\n","\n"," # Données JSON pour l'artefact\n"," confusion_matrix_data = {\n"," 'matrix': cm.tolist(), # Conversion numpy -> liste Python\n"," 'class_names': class_names if class_names else [f\"Class_{i}\" for i in range(num_classes)],\n"," 'total_samples': len(y_true_all),\n"," 'accuracy': float(np.trace(cm) / np.sum(cm)) # Accuracy globale\n"," }\n","\n"," print(f\"✅ Matrice de confusion sauvegardée : {cm_image_path}\")\n","\n"," return confusion_matrix_data\n","\n","def generate_training_visualizations(history, detailed_metrics, class_names, run_id, config, artifacts_dir):\n"," \"\"\"\n"," Génère toutes les visualisations : courbes d'entraînement + IoU par classe\n"," \"\"\"\n"," print(\"\\n📈 Création des visualisations...\")\n"," fig, axes = plt.subplots(2, 2, figsize=(15, 10))\n"," fig.suptitle(f'Entraînement {config[\"name\"]} - Run {run_id[:8]}', fontsize=16)\n","\n"," # Loss\n"," axes[0, 0].plot(history.history['loss'], label='Train Loss')\n"," axes[0, 0].plot(history.history['val_loss'], label='Val Loss')\n"," axes[0, 0].set_title('Loss')\n"," axes[0, 0].legend()\n"," axes[0, 0].grid(True)\n","\n"," # Accuracy\n"," axes[0, 1].plot(history.history['sparse_categorical_accuracy'], label='Train Acc')\n"," axes[0, 1].plot(history.history['val_sparse_categorical_accuracy'], label='Val Acc')\n"," axes[0, 1].set_title('Accuracy')\n"," axes[0, 1].legend()\n"," axes[0, 1].grid(True)\n","\n"," # Mean IoU\n"," axes[1, 0].plot(history.history['mean_iou'], label='Train Mean IoU')\n"," axes[1, 0].plot(history.history['val_mean_iou'], label='Val Mean IoU')\n"," axes[1, 0].set_title('Mean IoU')\n"," axes[1, 0].legend()\n"," axes[1, 0].grid(True)\n","\n"," # IoU par classe (bar chart)\n"," if class_names and len(class_names) == len(detailed_metrics['class_ious']):\n"," axes[1, 1].bar(range(len(detailed_metrics['class_ious'])), detailed_metrics['class_ious'])\n"," axes[1, 1].set_title(f'IoU par classe sur jeu de test (Mean: {detailed_metrics[\"mean_iou\"]:.3f})')\n"," axes[1, 1].set_xticks(range(len(class_names)))\n"," axes[1, 1].set_xticklabels(class_names, rotation=45)\n"," axes[1, 1].grid(True, axis='y')\n","\n"," plt.tight_layout()\n"," training_curves_path = os.path.join(artifacts_dir, 'training_curves.png')\n"," plt.savefig(training_curves_path, dpi=300, bbox_inches='tight')\n"," plt.close()\n","\n","def save_training_artifacts(history, config, detailed_metrics, confusion_matrix_data, artifacts_dir):\n"," \"\"\"\n"," Sauvegarde tous les artefacts : history, config, métriques, matrice de confusion\n"," \"\"\"\n"," print(\"\\n💾 Sauvegarde des artefacts...\")\n","\n"," # Histoire d'entraînement\n"," history_path = os.path.join(artifacts_dir, 'training_history.json')\n"," with open(history_path, 'w') as f:\n"," history_json = {k: [float(v) for v in values] for k, values in history.history.items()}\n"," json.dump(history_json, f, indent=2)\n","\n"," # Configuration du modèle\n"," config_path = os.path.join(artifacts_dir, 'model_config.json')\n"," with open(config_path, 'w') as f:\n"," json.dump(config, f, indent=2)\n","\n"," # Métriques détaillées - CONVERSION NUMPY VERS PYTHON POUR JSON\n"," detailed_path = os.path.join(artifacts_dir, 'detailed_metrics.json')\n"," with open(detailed_path, 'w') as f:\n"," class_stats_json = []\n"," for stats in detailed_metrics['class_stats']:\n"," stats_converted = {\n"," 'class_id': int(stats['class_id']),\n"," 'class_name': str(stats['class_name']),\n"," 'iou': float(stats['iou']),\n"," 'true_pixels': int(stats['true_pixels']),\n"," 'pred_pixels': int(stats['pred_pixels']),\n"," 'true_percentage': float(stats['true_percentage']),\n"," 'pred_percentage': float(stats['pred_percentage'])\n"," }\n"," class_stats_json.append(stats_converted)\n","\n"," detailed_json = {\n"," 'mean_iou': float(detailed_metrics['mean_iou']),\n"," 'class_ious': [float(iou) for iou in detailed_metrics['class_ious']],\n"," 'class_stats': class_stats_json\n"," }\n"," json.dump(detailed_json, f, indent=2)\n","\n"," # Matrice de confusion (si disponible)\n"," if confusion_matrix_data:\n"," confusion_path = os.path.join(artifacts_dir, 'confusion_matrix.json')\n"," with open(confusion_path, 'w') as f:\n"," json.dump(confusion_matrix_data, f, indent=2)\n","\n"," mlflow.log_artifacts(artifacts_dir)\n","\n","def train_segmentation_model_optimized(config, run_name=None):\n"," \"\"\"\n"," Fonction principale orchestrant l'entraînement complet - VERSION REFACTORISÉE\n"," \"\"\"\n"," with mlflow.start_run(run_name=run_name) as run:\n"," run_id = run.info.run_id\n"," print(f\"🔬 MLflow Run ID: {run_id}\")\n"," print(f\"🏷️ MLflow Run Name: {run_name}\")\n","\n"," try:\n"," # === 1. SETUP COMPLET ===\n"," setup_components = setup_training_components(config, run_id)\n","\n"," # === 2. ENTRAÎNEMENT ===\n"," history, training_time = train_model_core(\n"," setup_components['model'],\n"," setup_components['train_dataset'],\n"," setup_components['val_dataset'],\n"," setup_components['callbacks_list'],\n"," MAX_EPOCHS\n"," )\n","\n"," # === 3. ÉVALUATION COMPLÈTE ===\n"," basic_test_metrics, detailed_metrics, confusion_matrix_data, class_names = evaluate_model_comprehensive(\n"," setup_components['model'],\n"," setup_components['test_dataset'],\n"," setup_components['num_classes_from_model'],\n"," setup_components['artifacts_dir']\n"," )\n","\n"," # === 4. VISUALISATIONS ===\n"," generate_training_visualizations(\n"," history, detailed_metrics, class_names,\n"," run_id, config, setup_components['artifacts_dir']\n"," )\n","\n"," # === 5. SAUVEGARDE DES ARTEFACTS ===\n"," save_training_artifacts(\n"," history, config, detailed_metrics,\n"," confusion_matrix_data, setup_components['artifacts_dir']\n"," )\n","\n"," # === 6. RÉSULTATS FINAUX ===\n"," best_val_acc = max(history.history['val_sparse_categorical_accuracy'])\n"," results = {\n"," 'run_id': run_id,\n"," 'config': config,\n"," 'training_time': training_time,\n"," 'final_epoch': len(history.history['loss']),\n"," 'best_val_accuracy': best_val_acc,\n"," 'test_metrics': basic_test_metrics,\n"," 'detailed_metrics': detailed_metrics,\n"," 'confusion_matrix': confusion_matrix_data,\n"," 'artifacts_dir': setup_components['artifacts_dir'],\n"," 'num_classes': setup_components['num_classes_from_model']\n"," }\n","\n"," print(f\"\\n✅ Entraînement terminé!\")\n"," print(f\"📊 Meilleure val_accuracy: {best_val_acc:.4f}\")\n"," print(f\"📊 Mean IoU: {detailed_metrics['mean_iou']:.4f}\")\n"," test_acc = basic_test_metrics.get('sparse_categorical_accuracy', 0)\n"," print(f\"🧪 Test accuracy: {test_acc:.4f}\")\n"," print(f\"📁 Artefacts: {setup_components['artifacts_dir']}\")\n"," print(f\"🔬 MLflow Run: {run_id}\")\n","\n"," return results\n","\n"," except Exception as e:\n"," mlflow.log_param(\"error\", str(e))\n"," print(f\"❌ Erreur pendant l'entraînement: {e}\")\n"," raise"],"metadata":{"id":"mWvf8oQC0UBC","executionInfo":{"status":"ok","timestamp":1754980948830,"user_tz":-120,"elapsed":65,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"execution_count":19,"outputs":[]},{"cell_type":"code","execution_count":20,"metadata":{"id":"ThxE2s76sTaj","executionInfo":{"status":"ok","timestamp":1754980948853,"user_tz":-120,"elapsed":22,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"outputs":[],"source":["def run_experiments_optimized(configs_to_test=None, experiment_name=\"OC Projet 8\"):\n"," \"\"\"\n"," Version optimisée avec système de reprise automatique + NETTOYAGE VRAM SIMPLIFIÉ\n"," \"\"\"\n","\n"," print(f\"\\n{'='*60}\")\n"," print(f\"🚀 DÉBUT DES EXPÉRIENCES - Mode: {'TEST' if TEST_MODE else 'PRODUCTION'}\")\n"," print(f\"🔬 Expérience MLflow: {experiment_name}\")\n"," print(f\"{'='*60}\")\n","\n"," # 1. Filtrage des configurations à lancer\n"," if configs_to_test is None:\n"," remaining_configs = filter_configs_to_run(experimental_configurations, experiment_name)\n","\n"," if not remaining_configs:\n"," print(\"\\n🎉 TOUTES LES EXPÉRIENCES SONT DÉJÀ TERMINÉES !\")\n"," print(\"Rien à faire. Utilisez compare_experiments_mlflow() pour voir les résultats.\")\n"," return []\n"," if TEST_MODE:\n"," configs_to_test = remaining_configs[:TEST_MAX_CONFIGS] if TEST_MAX_CONFIGS else remaining_configs\n"," print(f\"\\n🧪 Mode TEST: limitation à {len(configs_to_test)} configurations\")\n"," else:\n"," configs_to_test = remaining_configs\n"," else:\n"," completed_runs = get_completed_experiments(experiment_name)\n"," filtered_configs = []\n"," for config_idx in configs_to_test:\n"," if config_idx >= len(experimental_configurations):\n"," print(f\"⚠️ Index {config_idx} invalide, ignoré\")\n"," continue\n"," config = experimental_configurations[config_idx]\n"," expected_run_name = generate_stable_run_name(config, TEST_MODE)\n"," if expected_run_name in completed_runs:\n"," print(f\"⏭️ [{config_idx}] {config['name']} déjà terminé, ignoré\")\n"," else:\n"," filtered_configs.append(config_idx)\n"," configs_to_test = filtered_configs\n","\n"," if not configs_to_test:\n"," print(\"\\n✅ Toutes les configurations demandées sont déjà terminées !\")\n"," return []\n","\n"," # 2. Boucle d'entraînement avec nettoyage SIMPLIFIÉ\n"," print(f\"\\n🎯 ENTRAÎNEMENT DE {len(configs_to_test)} CONFIGURATIONS:\")\n","\n"," results = []\n"," for i, config_idx in enumerate(configs_to_test):\n"," config = experimental_configurations[config_idx]\n"," stable_run_name = generate_stable_run_name(config, TEST_MODE)\n","\n"," print(f\"\\n{'-'*50}\")\n"," print(f\"🧪 Expérience {i+1}/{len(configs_to_test)}: {config['name']}\")\n"," print(f\"🏷️ Run name: {stable_run_name}\")\n"," print(f\"{'-'*50}\")\n","\n"," try:\n"," # ENTRAÎNEMENT (ici artifacts_dir existe et fonctionne normalement)\n"," result = train_segmentation_model_optimized(config, run_name=stable_run_name)\n"," results.append(result)\n"," print(f\"✅ [{config_idx}] {config['name']} terminé avec succès\")\n","\n"," remaining = len(configs_to_test) - (i + 1)\n"," if remaining > 0:\n"," print(f\"🔄 {remaining} configuration(s) restante(s)\")\n","\n"," except Exception as e:\n"," print(f\"❌ Erreur avec [{config_idx}] {config['name']}: {e}\")\n","\n"," # NETTOYAGE UNIQUE : après chaque modèle (réussi ou échoué)\n"," if i < len(configs_to_test) - 1: # Pas de nettoyage après le dernier modèle\n"," print(\"🧹 Nettoyage VRAM entre modèles...\")\n"," deep_clean_memory()\n","\n"," # 3. Résumé final\n"," print(f\"\\n{'='*60}\")\n"," print(f\"📊 RÉSUMÉ DE CETTE SESSION\")\n"," print(f\"{'='*60}\")\n","\n"," if results:\n"," print(f\"✅ {len(results)} nouvelles expériences réussies\")\n","\n"," print(f\"\\n{'Modèle':<25} {'Val Acc':<10} {'Test Acc':<10} {'Mean IoU':<10} {'Temps':<8} {'Run ID':<10}\")\n"," print(\"-\" * 80)\n","\n"," for result in results:\n"," config_name = result['config']['name']\n"," val_acc = result['best_val_accuracy']\n"," test_acc = result['test_metrics'].get('sparse_categorical_accuracy', 0)\n"," mean_iou = result['detailed_metrics']['mean_iou']\n"," time_min = result['training_time'] / 60\n"," run_id = result['run_id'][:8]\n"," print(f\"{config_name:<25} {val_acc:<10.4f} {test_acc:<10.4f} {mean_iou:<10.4f} {time_min:<8.1f} {run_id:<10}\")\n","\n"," best_result = max(results, key=lambda x: x['detailed_metrics']['mean_iou'])\n"," print(f\"\\n🏆 Meilleur de cette session: {best_result['config']['name']}\")\n"," print(f\" Val Acc: {best_result['best_val_accuracy']:.4f}\")\n"," print(f\" Test Acc: {best_result['test_metrics'].get('sparse_categorical_accuracy', 0):.4f}\")\n"," print(f\" Mean IoU: {best_result['detailed_metrics']['mean_iou']:.4f}\")\n"," print(f\" MLflow Run: {best_result['run_id']}\")\n","\n"," total_remaining = filter_configs_to_run(experimental_configurations, experiment_name)\n"," if len(total_remaining) > len(configs_to_test):\n"," remaining_count = len(total_remaining) - len(configs_to_test)\n"," print(f\"\\n🔄 Il reste encore {remaining_count} configuration(s) à entraîner\")\n"," print(\"💡 Relancez le script pour continuer automatiquement\")\n"," else:\n"," print(f\"\\n🎉 TOUTES LES CONFIGURATIONS SONT MAINTENANT TERMINÉES !\")\n"," print(\"💡 Utilisez compare_experiments_local() pour voir tous les résultats\")\n"," else:\n"," print(\"❌ Aucune nouvelle expérience réussie dans cette session\")\n","\n"," return results"]},{"cell_type":"code","execution_count":21,"metadata":{"id":"SdG8VxB7v8tF","executionInfo":{"status":"ok","timestamp":1754980948860,"user_tz":-120,"elapsed":9,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"outputs":[],"source":["# ====================================================================\n","# COMPARAISON DES EXPÉRIENCES LOCALES\n","# ====================================================================\n","\n","def compare_experiments_local(artifacts_base_dir=\"artifacts\"):\n"," \"\"\"\n"," Compare les résultats de plusieurs expériences via les artefacts locaux\n"," Structure : artifacts/run_{run_id}/\n"," \"\"\"\n"," if not os.path.exists(artifacts_base_dir):\n"," print(\"❌ Aucun répertoire d'artefacts trouvé\")\n"," return\n","\n"," results = []\n","\n"," print(f\"🔍 Recherche des expériences dans {artifacts_base_dir}/...\")\n","\n"," # Parcourir tous les répertoires run_*\n"," run_dirs = [d for d in os.listdir(artifacts_base_dir) if d.startswith('run_')]\n","\n"," if not run_dirs:\n"," print(\"❌ Aucune expérience trouvée\")\n"," return\n","\n"," print(f\"📊 {len(run_dirs)} expériences trouvées\")\n","\n"," for run_dir in run_dirs:\n"," run_path = os.path.join(artifacts_base_dir, run_dir)\n"," config_path = os.path.join(run_path, \"model_config.json\")\n"," history_path = os.path.join(run_path, \"training_history.json\")\n"," detailed_path = os.path.join(run_path, \"detailed_metrics.json\")\n","\n"," # Vérifier que les fichiers existent\n"," if os.path.exists(config_path) and os.path.exists(history_path):\n"," try:\n"," # Charger la configuration\n"," with open(config_path, 'r') as f:\n"," config = json.load(f)\n","\n"," # Charger l'historique d'entraînement\n"," with open(history_path, 'r') as f:\n"," history = json.load(f)\n","\n"," # Charger les métriques détaillées (si disponibles)\n"," detailed_metrics = None\n"," if os.path.exists(detailed_path):\n"," with open(detailed_path, 'r') as f:\n"," detailed_metrics = json.load(f)\n","\n"," # Extraire les métriques finales\n"," final_metrics = {\n"," 'run_id': run_dir.replace('run_', ''),\n"," 'experiment': config.get('name', 'Unknown'),\n"," 'architecture': config.get('architecture', 'Unknown'),\n"," 'encoder': config.get('encoder', 'None'),\n"," 'encoder_freeze': config.get('encoder_freeze', False),\n"," 'final_train_acc': history['sparse_categorical_accuracy'][-1],\n"," 'final_val_acc': history['val_sparse_categorical_accuracy'][-1],\n"," 'final_train_loss': history['loss'][-1],\n"," 'final_val_loss': history['val_loss'][-1],\n"," 'best_val_acc': max(history['val_sparse_categorical_accuracy']),\n"," 'epochs_trained': len(history['loss']),\n"," 'mean_iou': detailed_metrics['mean_iou'] if detailed_metrics else None,\n"," 'run_path': run_path\n"," }\n"," results.append(final_metrics)\n","\n"," except Exception as e:\n"," print(f\"⚠️ Erreur lors du chargement de {run_dir}: {e}\")\n"," continue\n","\n"," # Afficher les résultats\n"," if results:\n"," print(f\"\\n🏆 COMPARAISON DES {len(results)} EXPÉRIENCES\")\n"," print(\"=\" * 100)\n","\n"," # Trier par Mean IoU si disponible, sinon par best_val_acc\n"," if any(r['mean_iou'] is not None for r in results):\n"," results_sorted = sorted(results, key=lambda x: x['mean_iou'] or 0, reverse=True)\n"," print(\"📊 Classement par Mean IoU (meilleur premier)\")\n"," else:\n"," results_sorted = sorted(results, key=lambda x: x['best_val_acc'], reverse=True)\n"," print(\"📊 Classement par Validation Accuracy (meilleur premier)\")\n","\n"," print()\n","\n"," for i, result in enumerate(results_sorted, 1):\n"," print(f\"🥇 #{i} - {result['experiment']}\")\n"," print(f\" 🏗️ Architecture: {result['architecture']}\")\n","\n"," if result['encoder'] != 'None':\n"," freeze_status = \"🧊 Frozen\" if result['encoder_freeze'] else \"🔥 Trainable\"\n"," print(f\" 🧠 Encoder: {result['encoder']} ({freeze_status})\")\n","\n"," print(f\" 📊 Meilleure Val Acc: {result['best_val_acc']:.4f}\")\n"," print(f\" 📊 Val Acc finale: {result['final_val_acc']:.4f}\")\n","\n"," if result['mean_iou'] is not None:\n"," print(f\" 🎯 Mean IoU: {result['mean_iou']:.4f}\")\n","\n"," print(f\" ⏱️ Époques: {result['epochs_trained']}\")\n"," print(f\" 🆔 Run ID: {result['run_id'][:8]}...\")\n"," print(f\" 📁 Chemin: {result['run_path']}\")\n"," print()\n","\n"," # Statistiques globales\n"," print(\"📈 STATISTIQUES GLOBALES:\")\n"," print(\"-\" * 50)\n"," avg_val_acc = sum(r['best_val_acc'] for r in results) / len(results)\n"," print(f\"🎯 Val Acc moyenne: {avg_val_acc:.4f}\")\n","\n"," if any(r['mean_iou'] is not None for r in results):\n"," valid_ious = [r['mean_iou'] for r in results if r['mean_iou'] is not None]\n"," avg_iou = sum(valid_ious) / len(valid_ious)\n"," print(f\"🎯 Mean IoU moyen: {avg_iou:.4f}\")\n","\n"," avg_epochs = sum(r['epochs_trained'] for r in results) / len(results)\n"," print(f\"⏱️ Époques moyennes: {avg_epochs:.1f}\")\n","\n"," # Architecture summary\n"," architectures = {}\n"," for r in results:\n"," arch = r['architecture']\n"," if arch not in architectures:\n"," architectures[arch] = []\n"," architectures[arch].append(r['best_val_acc'])\n","\n"," print(f\"\\n🏗️ PERFORMANCE PAR ARCHITECTURE:\")\n"," print(\"-\" * 50)\n"," for arch, accs in architectures.items():\n"," avg_acc = sum(accs) / len(accs)\n"," print(f\"{arch}: {avg_acc:.4f} (moyenne sur {len(accs)} runs)\")\n","\n"," else:\n"," print(\"❌ Aucune expérience valide trouvée\")\n","\n"," return results"]},{"cell_type":"code","execution_count":22,"metadata":{"id":"DWf1lWhyv_OI","executionInfo":{"status":"ok","timestamp":1754980948936,"user_tz":-120,"elapsed":68,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"outputs":[],"source":["# ====================================================================\n","# COMPARAISON DES EXPÉRIENCES LOCALES\n","# ====================================================================\n","\n","def show_best_experiment_details(artifacts_base_dir=\"artifacts\"):\n"," \"\"\"\n"," Affiche les détails de la meilleure expérience\n"," \"\"\"\n"," results = compare_experiments_local(artifacts_base_dir)\n","\n"," if not results:\n"," return\n","\n"," # Meilleure expérience (Mean IoU si disponible, sinon Val Acc)\n"," if any(r['mean_iou'] is not None for r in results):\n"," best = max(results, key=lambda x: x['mean_iou'] or 0)\n"," metric_name = \"Mean IoU\"\n"," metric_value = best['mean_iou']\n"," else:\n"," best = max(results, key=lambda x: x['best_val_acc'])\n"," metric_name = \"Validation Accuracy\"\n"," metric_value = best['best_val_acc']\n","\n"," print(f\"\\n🏆 DÉTAILS DE LA MEILLEURE EXPÉRIENCE ({metric_name})\")\n"," print(\"=\" * 60)\n"," print(f\"🎯 Nom: {best['experiment']}\")\n"," print(f\"🏗️ Architecture: {best['architecture']}\")\n","\n"," if best['encoder'] != 'None':\n"," freeze_status = \"🧊 Frozen\" if best['encoder_freeze'] else \"🔥 Trainable\"\n"," print(f\"🧠 Encoder: {best['encoder']} ({freeze_status})\")\n","\n"," print(f\"📊 {metric_name}: {metric_value:.4f}\")\n"," print(f\"📊 Validation Accuracy: {best['best_val_acc']:.4f}\")\n"," print(f\"⏱️ Époques: {best['epochs_trained']}\")\n"," print(f\"🆔 Run ID: {best['run_id']}\")\n"," print(f\"📁 Chemin des artefacts: {best['run_path']}\")\n","\n"," # Vérifier la présence du modèle\n"," model_path = os.path.join(best['run_path'], 'best_model.keras')\n"," if os.path.exists(model_path):\n"," print(f\"✅ Modèle disponible: {model_path}\")\n"," else:\n"," print(f\"❌ Modèle non trouvé: {model_path}\")"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":4943,"status":"aborted","timestamp":1754980887153,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"tlpWs7XqdCF5"},"outputs":[],"source":["# ====================================================================\n","# POINT D'ENTRÉE PRINCIPAL\n","# ====================================================================\n","\n","if __name__ == \"__main__\":\n"," print(\"🎯 SCRIPT D'ENTRAÎNEMENT OPTIMISÉ POUR SEGMENTATION\")\n"," print(f\"Mode: {'🧪 TEST' if TEST_MODE else '🚀 PRODUCTION'}\")\n"," print(\"🔄 SYSTÈME DE REPRISE AUTOMATIQUE ACTIVÉ\")\n","\n"," # Vérifications préliminaires\n"," try:\n"," print(f\"MLflow version: {mlflow.__version__}\")\n"," print(f\"Cityscapes dir: {cityscapes_dir}\")\n"," print(f\"Configurations disponibles: {len(experimental_configurations)}\")\n","\n"," assert callable(create_model_from_config), \"create_model_from_config non disponible\"\n"," assert callable(prepare_cityscapes_dataset), \"prepare_cityscapes_dataset non disponible\"\n","\n"," print(\"✅ Toutes les vérifications passées\")\n","\n"," # Lancer les expériences avec système de reprise\n"," results = run_experiments_optimized()\n","\n"," print(\"\\n🎉 Script terminé avec succès!\")\n","\n"," except Exception as e:\n"," print(f\"❌ Erreur fatale: {e}\")\n"," print(\"Vérifications:\")\n"," print(\"1. Variables cityscapes_dir et experimental_configurations définies ?\")\n"," print(\"2. Fonctions create_model_from_config, prepare_cityscapes_dataset disponibles ?\")\n"," print(\"3. MLflow configuré ?\")\n"," print(\"4. Données Cityscapes présentes ?\")"]},{"cell_type":"markdown","metadata":{"id":"6gJK8H-YRwRN"},"source":["## Analyse des expériences"]},{"cell_type":"markdown","metadata":{"id":"erK7RXCV7HOz"},"source":["### Comparaison des experiences"]},{"cell_type":"code","execution_count":29,"metadata":{"id":"LQqdr5KUTWZW","executionInfo":{"status":"ok","timestamp":1754980984980,"user_tz":-120,"elapsed":35,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"outputs":[],"source":["def get_completed_configs_info(experimental_configurations, experiment_name=\"OC Projet 8\"):\n"," \"\"\"\n"," Réutilise la logique de filter_configs_to_run mais retourne les configs terminées\n"," \"\"\"\n"," completed_runs = get_completed_experiments(experiment_name)\n","\n"," if not completed_runs:\n"," return []\n","\n"," # Même logique que filter_configs_to_run mais on garde les terminées\n"," completed_configs = []\n","\n"," for idx, config in enumerate(experimental_configurations):\n"," expected_run_name = generate_stable_run_name(config, TEST_MODE)\n","\n"," if expected_run_name in completed_runs: # Condition inversée\n"," completed_configs.append((idx, config, expected_run_name))\n","\n"," return completed_configs\n","\n","def compare_experiments_mlflow(experiment_name=\"OC Projet 8\", show_detailed_results=False, show_plots=True):\n"," \"\"\"\n"," Compare les expériences terminées - version ultra-simple\n","\n"," Args:\n"," experiment_name (str): Nom de l'expérience MLflow\n"," show_detailed_results (bool): Si True, affiche et retourne la liste complète des résultats\n"," show_plots (bool): Si True, génère les diagrammes en barres des métriques\n"," \"\"\"\n"," # Récupérer les configs terminées (réutilise la logique existante)\n"," completed_configs = get_completed_configs_info(experimental_configurations, experiment_name)\n","\n"," if not completed_configs:\n"," print(\"❌ Aucune expérience terminée trouvée\")\n"," return []\n","\n"," # Récupérer le mapping run_name -> run_id depuis MLflow\n"," experiment = mlflow.get_experiment_by_name(experiment_name)\n"," runs_df = mlflow.search_runs(\n"," experiment_ids=[experiment.experiment_id],\n"," filter_string=\"status = 'FINISHED'\",\n"," output_format=\"pandas\"\n"," )\n","\n"," run_name_to_id = {\n"," run.get('tags.mlflow.runName', ''): run['run_id']\n"," for _, run in runs_df.iterrows()\n"," }\n","\n"," print(f\"📊 Analyse de {len(completed_configs)} configurations terminées\")\n","\n"," results = []\n","\n"," for config_idx, config, run_name in completed_configs:\n"," if run_name not in run_name_to_id:\n"," continue\n","\n"," run_id = run_name_to_id[run_name]\n","\n"," try:\n"," # Récupérer les métriques directement depuis MLflow\n"," run = mlflow.get_run(run_id)\n"," metrics = run.data.metrics\n","\n"," # Récupérer l'historique d'entraînement pour certaines infos\n"," import tempfile\n"," with tempfile.TemporaryDirectory() as temp_dir:\n"," try:\n"," history_path = mlflow.artifacts.download_artifacts(\n"," run_id=run_id, artifact_path=\"training_history.json\", dst_path=temp_dir\n"," )\n"," with open(history_path, 'r') as f:\n"," history = json.load(f)\n"," best_val_acc = max(history['val_sparse_categorical_accuracy'])\n"," epochs_trained = len(history['loss'])\n"," except:\n"," # Fallback si l'artefact n'est pas disponible\n"," best_val_acc = metrics.get('val_sparse_categorical_accuracy', 'N/A')\n"," epochs_trained = 'N/A'\n","\n"," # Construire le résultat avec les métriques de test depuis MLflow\n"," result = {\n"," 'config_idx': config_idx,\n"," 'experiment': config['name'],\n"," 'architecture': config.get('architecture', 'Unknown'),\n"," 'encoder': config.get('encoder', 'None'),\n"," 'best_val_acc': best_val_acc,\n"," 'test_mean_iou': metrics.get('test_mean_iou', 'N/A'),\n"," 'test_accuracy': metrics.get('test_sparse_categorical_accuracy', 'N/A'),\n"," 'epochs_trained': epochs_trained,\n"," 'run_name': run_name,\n"," 'run_id': run_id,\n"," 'full_config': config # Toujours inclure la config complète\n"," }\n","\n"," results.append(result)\n","\n"," except Exception as e:\n"," print(f\"⚠️ Erreur pour [{config_idx}] {config['name']}: {e}\")\n"," continue\n","\n"," # Affichage\n"," if results:\n"," # Trier par test_mean_iou si disponible, sinon par best_val_acc\n"," def sort_key(x):\n"," if x['test_mean_iou'] != 'N/A':\n"," return x['test_mean_iou']\n"," return x['best_val_acc']\n","\n"," results_sorted = sorted(results, key=sort_key, reverse=True)\n","\n"," print(f\"\\n🏆 TOP {len(results)} EXPÉRIENCES TERMINÉES\")\n"," print(\"=\" * 100)\n","\n"," for i, result in enumerate(results_sorted, 1):\n"," print(f\"🥇 #{i} - [{result['config_idx']}] {result['experiment']}\")\n"," print(f\" 🏗️ {result['architecture']} + {result['encoder']}\")\n","\n"," # Afficher les métriques de test\n"," test_iou = result['test_mean_iou']\n"," test_acc = result['test_accuracy']\n","\n"," if test_iou != 'N/A':\n"," print(f\" 🎯 Test Mean IoU: {test_iou:.4f}\", end=\"\")\n"," else:\n"," print(f\" 🎯 Test Mean IoU: N/A\", end=\"\")\n","\n"," if test_acc != 'N/A':\n"," print(f\" | Test Acc: {test_acc:.4f}\")\n"," else:\n"," print(f\" | Test Acc: N/A\")\n","\n"," print(f\" 🆔 {result['run_id'][:8]}...\")\n","\n"," # Afficher la configuration complète si demandé\n"," if show_detailed_results:\n"," print(f\" 📋 Configuration complète:\")\n"," import pprint\n"," pprint.pprint(result['full_config'], indent=6)\n","\n"," print()\n","\n"," # Génération des diagrammes si demandé\n"," if show_plots and results:\n"," generate_comparison_plots(results_sorted)\n","\n"," # Retourner les résultats seulement si explicitement demandé\n"," if show_detailed_results:\n"," return results\n"," else:\n"," print(f\"\\n✅ Analyse terminée. Utilisez show_detailed_results=True pour obtenir les données détaillées.\")\n"," return None\n","\n","\n","def generate_comparison_plots(results):\n"," \"\"\"\n"," Génère des diagrammes en barres pour comparer les métriques de test\n","\n"," Args:\n"," results (list): Liste des résultats triés\n"," \"\"\"\n"," import matplotlib.pyplot as plt\n"," import numpy as np\n","\n"," # Filtrer les résultats qui ont des métriques de test valides\n"," valid_results_iou = [r for r in results if r['test_mean_iou'] != 'N/A']\n"," valid_results_acc = [r for r in results if r['test_accuracy'] != 'N/A']\n","\n"," # Configuration des graphiques\n"," plt.style.use('seaborn-v0_8' if 'seaborn-v0_8' in plt.style.available else 'default')\n","\n"," # Créer une figure avec 2 sous-graphiques\n"," fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(20, 8))\n","\n"," # Graphique 1: Test Mean IoU\n"," if valid_results_iou:\n"," experiment_names = [r['experiment'] for r in valid_results_iou]\n"," iou_values = [r['test_mean_iou'] for r in valid_results_iou]\n","\n"," # Créer des labels courts pour les noms d'expériences\n"," short_labels = []\n"," for name in experiment_names:\n"," # Raccourcir les noms longs\n"," if len(name) > 25:\n"," parts = name.split('_')\n"," short_name = f\"{parts[0]}_{parts[1] if len(parts) > 1 else ''}...\"\n"," short_labels.append(short_name)\n"," else:\n"," short_labels.append(name)\n","\n"," colors = plt.cm.viridis(np.linspace(0, 1, len(iou_values)))\n"," bars1 = ax1.bar(range(len(iou_values)), iou_values, color=colors, alpha=0.8)\n","\n"," ax1.set_title('Test Mean IoU par Expérience', fontsize=14, fontweight='bold')\n"," ax1.set_xlabel('Expériences', fontsize=12)\n"," ax1.set_ylabel('Mean IoU', fontsize=12)\n"," ax1.set_xticks(range(len(short_labels)))\n"," ax1.set_xticklabels(short_labels, rotation=45, ha='right')\n"," ax1.grid(True, alpha=0.3)\n","\n"," # Ajouter les valeurs sur les barres\n"," for bar, value in zip(bars1, iou_values):\n"," height = bar.get_height()\n"," ax1.text(bar.get_x() + bar.get_width()/2., height + 0.001,\n"," f'{value:.4f}', ha='center', va='bottom', fontsize=10)\n"," else:\n"," ax1.text(0.5, 0.5, 'Aucune donnée Mean IoU disponible',\n"," ha='center', va='center', transform=ax1.transAxes, fontsize=14)\n"," ax1.set_title('Test Mean IoU par Expérience', fontsize=14, fontweight='bold')\n","\n"," # Graphique 2: Test Accuracy\n"," if valid_results_acc:\n"," experiment_names = [r['experiment'] for r in valid_results_acc]\n"," acc_values = [r['test_accuracy'] for r in valid_results_acc]\n","\n"," # Créer des labels courts pour les noms d'expériences\n"," short_labels = []\n"," for name in experiment_names:\n"," if len(name) > 25:\n"," parts = name.split('_')\n"," short_name = f\"{parts[0]}_{parts[1] if len(parts) > 1 else ''}...\"\n"," short_labels.append(short_name)\n"," else:\n"," short_labels.append(name)\n","\n"," colors = plt.cm.plasma(np.linspace(0, 1, len(acc_values)))\n"," bars2 = ax2.bar(range(len(acc_values)), acc_values, color=colors, alpha=0.8)\n","\n"," ax2.set_title('Test Accuracy par Expérience', fontsize=14, fontweight='bold')\n"," ax2.set_xlabel('Expériences', fontsize=12)\n"," ax2.set_ylabel('Accuracy', fontsize=12)\n"," ax2.set_xticks(range(len(short_labels)))\n"," ax2.set_xticklabels(short_labels, rotation=45, ha='right')\n"," ax2.grid(True, alpha=0.3)\n","\n"," # Ajouter les valeurs sur les barres\n"," for bar, value in zip(bars2, acc_values):\n"," height = bar.get_height()\n"," ax2.text(bar.get_x() + bar.get_width()/2., height + 0.001,\n"," f'{value:.4f}', ha='center', va='bottom', fontsize=10)\n"," else:\n"," ax2.text(0.5, 0.5, 'Aucune donnée Accuracy disponible',\n"," ha='center', va='center', transform=ax2.transAxes, fontsize=14)\n"," ax2.set_title('Test Accuracy par Expérience', fontsize=14, fontweight='bold')\n","\n"," plt.tight_layout()\n"," plt.show()\n","\n"," print(f\"📊 Diagrammes générés pour {len(valid_results_iou)} expériences (IoU) et {len(valid_results_acc)} expériences (Accuracy)\")"]},{"cell_type":"code","execution_count":30,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000,"referenced_widgets":["1091b77c2b2c415ca0d627933b64969c","43eff508df454d69a87ebab244700e9e","c12fb4498f294c35bd4e1ac67823a534","5c7fa581589741dda94baccef1f9564d","f0a3e51745994b50ba0e783265c32137","86680a798bba4ade89097aff42d7570b","aec87ffacce74aebb2067b45382c6d1c","7e2c871cfb284873b63de0e836f81b8b","93c0a6cd576c462caf536af285270ffc","57fad05e86024b8087b1b34b69aa5a91","ea302d170c65484c98efabf85f07af46","3f4fde907ea74cd387b8586573cdd9db","09a106f167184b478af1366bc1185a7a","2e73c418443c4dbf9cdd81f34d5b25d8","78b28795a0904ef7b426bfe641200eb1","f0dbde1d6a79441f9e2d3aaa95f3f33b","1fd4732a61fb48a1ba15754105557f90","a760121efac043d79a376c32bd930c11","4599d7c666b846b5b59ea43aac1aaa66","93e95dfcb3e54c01af548b40e20a5c2b","ade00d01b1c14087ae014c1f6a528789","ed9faf1158b74459b91fd1279b4f006c","1395bc9b8fff44fa8a0491f2f71b02e2","171cf780a6b543e5bcb2dbb12c47bb7d","5ebab0c35f5f41ab8c9e87216e8a2720","e94cb923a41b436f8ddc027f2f0024f5","615e04cf1c0941e8856218aa913fd8b9","0ea2448f650c41f999072555710933d7","5cee1b01776f456c8236f7f9bf9773da","897fc5fa5b494dbdbcdbaff6df34125e","b4becb9a0f584b389fd9e6c30710e2f5","362d49dbf9c84c5fa94f646925d7b091","6560c3d99f434eff99489626006fce6e","2e51f1811257441c9a6aae73e4d7dd7a","5385040a9cb6479fba024d3c44718f0f","ba1c2764e94e41fc84f209316cdcd8e7","0afb88a8f76743dbac73b6120a652fb3","eeb506b7031e4faa99c13156574ce849","b03b36a3cda343eab4302f9800666a09","2e48d976d2994f02a9c6c354ded6d93d","7c5d60d4391d4f69bdcc4606a0040418","d62525a9065a4d8ab1e7f13341fd9f31","08127b71707b46c59bebdf30ed881aff","9cb723f820574e82a7e7043a0b667a2e","6313cdcb83cf47bbb66b1d036636e80c","98756ebad2814918a0ed2364ef43a3c3","a3122178c05e4fe6b9050006206b0757","f6dae4271504411f82af9b2c9ba2a9a6","60337d9c340541bca4b5364e2cd3ad70","cbd4745db3964c3597b3b5cef3a7a831","526c741e78ef475bab96a2be655a4218","9970a50198804a1ca1497ee01b4dc483","65cec6c7efcc4cbc961620366b397348","e3633532b4bc40789552749f3dc191b5","b8d30a1e85c94a119d51602971c50edf","cbe21982571a4d25945f98ae4bce71cc","b386e9ac989e42f189f22356e3f36490","92cbe305e54b4961820a692c5cc03ae4","2c4bea6986f3493e82006a492c5cf7f3","c7421ae292a24dc7a96810e2a5b33fd4","c3d523bab420406fabcf111322c918e7","7c5659046dda43039d28bd62b126316c","7ce165d634184ed1a425bcdbc5fda1b7","ae5e3ed525bf4615a3248263d14ee9bb","0f605c65e65e4adcae52c58ffbe37c3c","cf2538490fa749008e0d957d20352d3d","e99370e5788c46d0b39795d99dee61fb","4374864e0b5d42df8e0b43723161c3c0","1de35ebd7d65431caa54aef21449abd7","02cdca3d4e924090aeba15d1798ce7bd","94afa7b84173410cb6f958c9ccd0422c","58d833f900f0430abcdb0c78356e3214","9fed4393c78e4e0fa5e482e3f4b69f46","14e3aa699f304caca909af1425a52bc6","ce676fee299b4b30ae9fd35fd81363f1","d3822fb07cb54622924f59f9f523550e","df856305989145368385950261150eed","fc2df5b47eb24f4087a4503cffb77246","eb0fa1515aec4d8c8a8ae86949b13d6e","2e31213718b44a3f9f9a31ce9bca6ff8","83f75e069ffe42e9853dd4abdec96687","fc3e7c7b77ab4179b32a9530b8520167","fdad39fd29a945559948f5a2e4df4f51","89c16600214447de83e453fe1f704193","c74c18bec4bc46828c642f822be77257","21f23e2a16ac4c3a822fb654f010ead9","7e3264726bef461686d0d1af54afd20d","1c4f5dc9514a4c2caf633b19c7d6f498","e558c3602e324ec08f4f2515e18e72c3","1614bb32193946599749936bde46a78b","147a96c1c54a47cbb306bdad580eae63","636fd1f3496c4359ae248e9ffa108044","21aa609507034287a2f67ddd67c88f9b","31666151387a4e13b24279c4319c42ce","6864f54445a04f0294e7d5a6bc7e0b9c","3c73a65abb8f4785a2225273c4cb6700","c1c34817a6764921ada246a927bcf605","22668934797b43298e4b1dba5534002f","62f3d49ddcbf4e04821039f06f9f44a5","d2b85c571b654d5c830954973fbf969b","7c277e3b8f304008b584db188a55565e","bdc784c43f534f608e75a51e450a2469","740df50f8c7045f19599645a59ebf050","7a991ad79c5a4c8fa0ed4ad9685ca49e","7c81408de8f34579bf4050e9d9c605d9","77620217a9af40c392c9df32d324cb9d","56fffbaf1902493b8403a5c6805b4081","2d13cefdfa0a4284b35cac3f6e1ed5d5","2a2b571a62214acba786b8b983221b87","c85a81534e704418bf7bb9a78e03fbc8","9ea49468c9c44d0db2b64def1a435387","cbdc4d6c8ba2498294615949689750c9","569404e538264e5cb42a23990c01af95","eee1b08234fb4050aa0b484f985bf610","faad9784703b40c182326bbcbacf7dca","e7aac0ec04e4468aaa160560682349ed","688785d14b4a47b3a97125199f2eb4b3","1c632146bae8449d811dd1de87f5f003","16523bcd0c7e4c789ad76e8e35daa401","4783d7d77ab44eeb994ca3a377155881","7e59846df494492a8a0f271a8d7bbec2","a6a9e50c210f4daeb9b6fb748432a2c1","608ed2ec0db84db390718595ca5874e0","51c6225409054c4c92b2ede2786c0fdd","61515b9d53aa496a92a35317b0217399","a7d8e443753a4e73aa979a3d947ecf58","69f7e0b1cdf04253a9084548f8a68313","edccc238492344a79410abf0c9262f42","5eccd0148c884158998ea322483314b9","dce2ed3f516346e7aa052adb7a2e4a8b","72ee36ebadcb4352bb7d6bea912663b3","bdfb780bb268497eb516cfc0cff5a1c7","4acaceb9c30941c9b7aa7374915af84c","f83673567ce445d68276fe036576f4d4","10a5557d53644b53988e93b8fa18bcef","48eba375b08e4355bd976cf8613fd1ed","e94f834bd244488e93ac95484b3bce89","3e8d88e4bdb843e59cf4b6e5d1900f72","c28d360f92624872a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Vérification des expériences déjà terminées dans 'OC Projet 8'...\n","✅ 39 expériences terminées trouvées:\n"," - FPN_efficientnetb0_finetune_augTrue_prod\n"," - FPN_efficientnetb0_finetune_augTrue_test\n"," - FPN_efficientnetb0_frozen_augFalse_prod\n"," - FPN_efficientnetb0_frozen_augFalse_test\n"," - FPN_efficientnetb0_frozen_augTrue_prod\n"," - FPN_efficientnetb0_frozen_augTrue_test\n"," - FPN_mobilenetv2_frozen_augFalse_prod\n"," - FPN_mobilenetv2_frozen_augFalse_test\n"," - FPN_mobilenetv2_frozen_augTrue_prod\n"," - FPN_mobilenetv2_frozen_augTrue_test\n"," - FPN_resnet34_finetune_augTrue_prod\n"," - FPN_resnet34_finetune_augTrue_test\n"," - FPN_resnet34_frozen_augFalse_prod\n"," - FPN_resnet34_frozen_augFalse_test\n"," - FPN_resnet34_frozen_augTrue_prod\n"," - FPN_resnet34_frozen_augTrue_test\n"," - FPN_vanilla_augFalse_prod\n"," - FPN_vanilla_augFalse_test\n"," - FPN_vanilla_augTrue_prod\n"," - FPN_vanilla_augTrue_test\n"," - U-Net_efficientnetb0_frozen_augFalse_prod\n"," - U-Net_efficientnetb0_frozen_augFalse_test\n"," - U-Net_efficientnetb0_frozen_augTrue_prod\n"," - U-Net_efficientnetb0_frozen_augTrue_test\n"," - U-Net_mobilenetv2_finetune_augTrue_prod\n"," - U-Net_mobilenetv2_finetune_augTrue_test\n"," - U-Net_mobilenetv2_frozen_augFalse_prod\n"," - U-Net_mobilenetv2_frozen_augFalse_test\n"," - U-Net_mobilenetv2_frozen_augTrue_prod\n"," - U-Net_mobilenetv2_frozen_augTrue_test\n"," - U-Net_vanilla_augFalse_prod\n"," - U-Net_vanilla_augFalse_prod_20250730_153443\n"," - U-Net_vanilla_augFalse_test\n"," - U-Net_vanilla_augTrue_prod\n"," - U-Net_vanilla_augTrue_prod_20250730_170602\n"," - U-Net_vanilla_augTrue_test\n"," - exp_001_baseline\n"," - exp_002_no_augmentation\n"," - exp_002_unfrozen\n","📊 Analyse de 17 configurations terminées\n"]},{"output_type":"display_data","data":{"text/plain":["Downloading artifacts: 0%| | 0/1 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["📊 Diagrammes générés pour 17 expériences (IoU) et 17 expériences (Accuracy)\n","\n","✅ Analyse terminée. Utilisez show_detailed_results=True pour obtenir les données détaillées.\n"]}],"source":["compare_experiments_mlflow(experiment_name=mlflow_experiemnt)"]},{"cell_type":"markdown","metadata":{"id":"gqrw8X8wR5Q6"},"source":["### Analyse meilleur modèle"]},{"cell_type":"markdown","source":["Affichage des courbes d'apprentissage"],"metadata":{"id":"j9kVdhxVBA4S"}},{"cell_type":"code","source":["def display_training_curves_from_best_run(experiment_name=\"OC Projet 8\"):\n"," \"\"\"\n"," Trouve le meilleur modèle (selon test_mean_iou) et affiche son graphique de courbes d'entraînement.\n"," \"\"\"\n"," print(f\"\\n{'='*60}\")\n"," print(f\"📈 Affichage des courbes d'entraînement du meilleur modèle\")\n"," print(f\"🔬 Expérience MLflow: {experiment_name}\")\n"," print(f\"{'='*60}\")\n","\n"," client = mlflow.tracking.MlflowClient()\n","\n"," try:\n"," # Récupérer l'expérience par nom\n"," experiment = client.get_experiment_by_name(experiment_name)\n"," if experiment is None:\n"," print(f\"❌ Expérience '{experiment_name}' non trouvée.\")\n"," return\n","\n"," # Rechercher les runs terminés avec la métrique test_mean_iou\n"," runs_df = mlflow.search_runs(\n"," experiment_ids=[experiment.experiment_id],\n"," filter_string=\"status = 'FINISHED' and metrics.test_mean_iou >= 0\",\n"," order_by=[\"metrics.test_mean_iou DESC\"], # Trier par Mean IoU descendant\n"," max_results=1 # Prendre seulement le meilleur\n"," )\n","\n"," if runs_df.empty:\n"," print(\"❌ Aucun run terminé avec la métrique test_mean_iou trouvé.\")\n"," return\n","\n"," # Le meilleur run est le premier dans la liste triée\n"," best_run = runs_df.iloc[0]\n"," best_run_id = best_run['run_id']\n"," best_run_name = best_run.get('tags.mlflow.runName', 'Unknown')\n"," best_iou = best_run['metrics.test_mean_iou']\n","\n"," print(f\"🏆 Meilleur run trouvé:\")\n"," print(f\" • Run Name: {best_run_name}\")\n"," print(f\" • Run ID: {best_run_id}\")\n"," print(f\" • Test Mean IoU: {best_iou:.4f}\")\n","\n"," # Télécharger l'artefact 'training_curves.png'\n"," artifact_path = \"training_curves.png\"\n"," print(f\"\\n💾 Téléchargement de l'artefact '{artifact_path}'...\")\n","\n"," with tempfile.TemporaryDirectory() as tmpdir:\n"," local_path = mlflow.artifacts.download_artifacts(\n"," run_id=best_run_id,\n"," artifact_path=artifact_path,\n"," dst_path=tmpdir\n"," )\n"," print(f\"✅ Artefact téléchargé vers: {local_path}\")\n","\n"," # Afficher l'image\n"," print(\"\\n🖼️ Affichage de l'image...\")\n"," img = PILImage.open(local_path)\n"," plt.figure(figsize=(12, 8))\n"," plt.imshow(img)\n"," plt.title(f\"Courbes d'entraînement - {best_run_name}\", fontsize=14)\n"," plt.axis('off') # Désactiver les axes\n"," plt.show()\n","\n"," except Exception as e:\n"," print(f\"❌ Erreur lors de l l'affichage des courbes d'entraînement: {e}\")\n"," print(\"Vérifiez que l'artefact 'training_curves.png' existe pour le meilleur run.\")"],"metadata":{"id":"cQMW_Ri1dTE0","executionInfo":{"status":"ok","timestamp":1754981009265,"user_tz":-120,"elapsed":17,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"execution_count":31,"outputs":[]},{"cell_type":"code","source":["# Exécuter la fonction\n","display_training_curves_from_best_run(experiment_name=mlflow_experiemnt)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":948,"referenced_widgets":["83da010cc5a246eba6831ce173b91fa7","dcb54c2dfff645d9bec25e2b0c0ac850","c0769fc3f1834f8591441f82e389709b","ce5b51311b7b4c0c8f60fc222b0ece05","87b61be4b48646479a2fc73830237beb","4ae37cd8e3f84f99b61b3f8c0f4cd0d2","1bc2de107b774829ba2eea49c97835b0","9dff1f6de727469889f08dece2fad13c","7205672c3a644f4f9e513e05683f72c7","383eb8f5f0ed48b395503bd882b50021","fe138dece4e142c891526c1375667737"]},"id":"K7FA2AlTg0X-","executionInfo":{"status":"ok","timestamp":1754981013482,"user_tz":-120,"elapsed":4197,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}},"outputId":"62cc0bfa-52d4-476c-bfe7-edc9e8f4b7bb"},"execution_count":32,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","============================================================\n","📈 Affichage des courbes d'entraînement du meilleur modèle\n","🔬 Expérience MLflow: OC Projet 8\n","============================================================\n","🏆 Meilleur run trouvé:\n"," • Run Name: FPN_efficientnetb0_finetune_augTrue_prod\n"," • Run ID: b6dd1ecdeb3f4b5c899b332f3c948cd7\n"," • Test Mean IoU: 0.7457\n","\n","💾 Téléchargement de l'artefact 'training_curves.png'...\n"]},{"output_type":"display_data","data":{"text/plain":["Downloading artifacts: 0%| | 0/1 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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["Affichage de la matrice de confusion en pourcentages"],"metadata":{"id":"GFqCXkZEBMp2"}},{"cell_type":"code","execution_count":33,"metadata":{"id":"YNQDzY0BH-X0","executionInfo":{"status":"ok","timestamp":1754981033304,"user_tz":-120,"elapsed":88,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"outputs":[],"source":["def display_best_confusion_matrix(experiment_name=\"OC Projet 8\"):\n"," \"\"\"\n"," Trouve le modèle avec la meilleure valeur test_mean_iou et affiche sa matrice de confusion\n","\n"," Args:\n"," experiment_name (str): Nom de l'expérience MLflow\n"," \"\"\"\n"," import matplotlib.pyplot as plt\n"," import seaborn as sns\n"," import numpy as np\n"," import json\n"," import tempfile\n","\n"," # Récupérer les résultats des expériences\n"," completed_configs = get_completed_configs_info(experimental_configurations, experiment_name)\n","\n"," if not completed_configs:\n"," print(\"❌ Aucune expérience terminée trouvée\")\n"," return None\n","\n"," # Récupérer le mapping run_name -> run_id depuis MLflow\n"," experiment = mlflow.get_experiment_by_name(experiment_name)\n"," runs_df = mlflow.search_runs(\n"," experiment_ids=[experiment.experiment_id],\n"," filter_string=\"status = 'FINISHED'\",\n"," output_format=\"pandas\"\n"," )\n","\n"," run_name_to_id = {\n"," run.get('tags.mlflow.runName', ''): run['run_id']\n"," for _, run in runs_df.iterrows()\n"," }\n","\n"," print(f\"🔍 Recherche du meilleur modèle parmi {len(completed_configs)} configurations...\")\n","\n"," best_result = None\n"," best_iou = -1\n","\n"," # Trouver le meilleur modèle\n"," for config_idx, config, run_name in completed_configs:\n"," if run_name not in run_name_to_id:\n"," continue\n","\n"," run_id = run_name_to_id[run_name]\n","\n"," try:\n"," # Récupérer les métriques\n"," run = mlflow.get_run(run_id)\n"," metrics = run.data.metrics\n","\n"," test_mean_iou = metrics.get('test_mean_iou', None)\n","\n"," if test_mean_iou is not None and test_mean_iou > best_iou:\n"," best_iou = test_mean_iou\n"," best_result = {\n"," 'config_idx': config_idx,\n"," 'experiment': config['name'],\n"," 'architecture': config.get('architecture', 'Unknown'),\n"," 'encoder': config.get('encoder', 'None'),\n"," 'test_mean_iou': test_mean_iou,\n"," 'test_accuracy': metrics.get('test_sparse_categorical_accuracy', 'N/A'),\n"," 'run_name': run_name,\n"," 'run_id': run_id\n"," }\n","\n"," except Exception as e:\n"," print(f\"⚠️ Erreur lors de l'analyse de {run_name}: {e}\")\n"," continue\n","\n"," if best_result is None:\n"," print(\"❌ Aucun modèle avec test_mean_iou trouvé\")\n"," return None\n","\n"," print(f\"🏆 MEILLEUR MODÈLE TROUVÉ:\")\n"," print(f\" 📊 [{best_result['config_idx']}] {best_result['experiment']}\")\n"," print(f\" 🏗️ {best_result['architecture']} + {best_result['encoder']}\")\n"," print(f\" 🎯 Test Mean IoU: {best_result['test_mean_iou']:.4f}\")\n"," print(f\" 📈 Test Accuracy: {best_result['test_accuracy']:.4f}\")\n"," print(f\" 🆔 Run ID: {best_result['run_id']}\")\n"," print()\n","\n"," # Télécharger et charger la matrice de confusion\n"," try:\n"," with tempfile.TemporaryDirectory() as temp_dir:\n"," confusion_matrix_path = mlflow.artifacts.download_artifacts(\n"," run_id=best_result['run_id'],\n"," artifact_path=\"confusion_matrix.json\",\n"," dst_path=temp_dir\n"," )\n","\n"," with open(confusion_matrix_path, 'r') as f:\n"," confusion_data = json.load(f)\n","\n"," matrix = np.array(confusion_data['matrix'])\n"," class_names = confusion_data['class_names']\n"," accuracy = confusion_data.get('accuracy', 'N/A')\n"," total_samples = confusion_data.get('total_samples', 'N/A')\n","\n"," print(f\"📋 Informations sur la matrice de confusion:\")\n"," print(f\" 🔢 Nombre de classes: {len(class_names)}\")\n"," print(f\" 📊 Échantillons totaux: {total_samples:,}\" if total_samples != 'N/A' else \" 📊 Échantillons totaux: N/A\")\n"," print(f\" ✅ Précision globale: {accuracy:.4f}\" if accuracy != 'N/A' else \" ✅ Précision globale: N/A\")\n"," print()\n","\n"," # Calculer les métriques par classe\n"," print(\"📈 Métriques par classe:\")\n"," print(\"-\" * 50)\n","\n"," for i, class_name in enumerate(class_names):\n"," # Précision: TP / (TP + FP)\n"," tp = matrix[i, i]\n"," fp = np.sum(matrix[:, i]) - tp\n"," fn = np.sum(matrix[i, :]) - tp\n","\n"," precision = tp / (tp + fp) if (tp + fp) > 0 else 0\n"," recall = tp / (tp + fn) if (tp + fn) > 0 else 0\n"," f1 = 2 * (precision * recall) / (precision + recall) if (precision + recall) > 0 else 0\n","\n"," print(f\" {class_name:12s} - Précision: {precision:.4f} | Rappel: {recall:.4f} | F1: {f1:.4f}\")\n","\n"," print()\n","\n"," # Créer la visualisation\n"," plt.figure(figsize=(12, 10))\n","\n"," # Normaliser la matrice pour l'affichage (en pourcentages)\n"," matrix_normalized = matrix.astype('float') / matrix.sum(axis=1)[:, np.newaxis] * 100\n","\n"," # Créer le heatmap\n"," sns.heatmap(matrix_normalized,\n"," annot=True,\n"," fmt='.1f',\n"," cmap='Blues',\n"," xticklabels=class_names,\n"," yticklabels=class_names,\n"," cbar_kws={'label': 'Pourcentage (%)'})\n","\n"," plt.title(f'Matrice de Confusion - {best_result[\"experiment\"]}\\n'\n"," f'Mean IoU: {best_result[\"test_mean_iou\"]:.4f} | Accuracy: {accuracy:.4f}',\n"," fontsize=14, fontweight='bold', pad=20)\n"," plt.xlabel('Classes Prédites', fontsize=12)\n"," plt.ylabel('Classes Réelles', fontsize=12)\n"," plt.xticks(rotation=45, ha='right')\n"," plt.yticks(rotation=0)\n","\n"," plt.tight_layout()\n"," plt.show()\n","\n"," # Optionnel: afficher aussi la matrice brute\n"," print(\"🔢 Matrice de confusion brute (premiers/derniers éléments):\")\n"," print(\"=\" * 60)\n"," print(\"Classes:\", class_names)\n"," print(\"Matrice (format: lignes=réel, colonnes=prédit):\")\n"," print(matrix)\n","\n"," return {\n"," 'confusion_matrix': matrix,\n"," 'class_names': class_names,\n"," 'best_model_info': best_result,\n"," 'accuracy': accuracy,\n"," 'total_samples': total_samples\n"," }\n","\n"," except Exception as e:\n"," print(f\"❌ Erreur lors du téléchargement de la matrice de confusion: {e}\")\n"," print(f\" Run ID: {best_result['run_id']}\")\n"," print(\" Vérifiez que l'artefact 'confusion_matrix.json' existe pour ce run.\")\n"," return None"]},{"cell_type":"code","execution_count":34,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000,"referenced_widgets":["ebe07ac726f2439ea7601b61c7d8ad08","6677b53645214d5d93d74b82956c55f6","dbc64b00463443aab6f0dfbdec940466","fd2e09a9cc914ad7986fdf66bc69c4a1","721ba9ab45094523b3881af1d3d7eef4","3af6cb869c0f4ba7a925c8a4bd1b49c7","a5fb37cc8fea4715966ed619b416ef9f","61ef8653bd9848cf986b71b32a9b2fee","585d68b080634af6b82900db7f2bfb3f","acd898044b114cfda79eb2cf37ac4446","7af3031a3afe41c48df83c262098bfc3"]},"executionInfo":{"elapsed":6665,"status":"ok","timestamp":1754981040832,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"ir7It9rTICQE","outputId":"61b85667-ff0f-4584-b6cd-6ef78f9aff9e"},"outputs":[{"output_type":"stream","name":"stdout","text":["🔍 Vérification des expériences déjà terminées dans 'OC Projet 8'...\n","✅ 39 expériences terminées trouvées:\n"," - FPN_efficientnetb0_finetune_augTrue_prod\n"," - FPN_efficientnetb0_finetune_augTrue_test\n"," - FPN_efficientnetb0_frozen_augFalse_prod\n"," - FPN_efficientnetb0_frozen_augFalse_test\n"," - FPN_efficientnetb0_frozen_augTrue_prod\n"," - FPN_efficientnetb0_frozen_augTrue_test\n"," - FPN_mobilenetv2_frozen_augFalse_prod\n"," - FPN_mobilenetv2_frozen_augFalse_test\n"," - FPN_mobilenetv2_frozen_augTrue_prod\n"," - FPN_mobilenetv2_frozen_augTrue_test\n"," - FPN_resnet34_finetune_augTrue_prod\n"," - FPN_resnet34_finetune_augTrue_test\n"," - FPN_resnet34_frozen_augFalse_prod\n"," - FPN_resnet34_frozen_augFalse_test\n"," - FPN_resnet34_frozen_augTrue_prod\n"," - FPN_resnet34_frozen_augTrue_test\n"," - FPN_vanilla_augFalse_prod\n"," - FPN_vanilla_augFalse_test\n"," - FPN_vanilla_augTrue_prod\n"," - FPN_vanilla_augTrue_test\n"," - U-Net_efficientnetb0_frozen_augFalse_prod\n"," - U-Net_efficientnetb0_frozen_augFalse_test\n"," - U-Net_efficientnetb0_frozen_augTrue_prod\n"," - U-Net_efficientnetb0_frozen_augTrue_test\n"," - U-Net_mobilenetv2_finetune_augTrue_prod\n"," - U-Net_mobilenetv2_finetune_augTrue_test\n"," - U-Net_mobilenetv2_frozen_augFalse_prod\n"," - U-Net_mobilenetv2_frozen_augFalse_test\n"," - U-Net_mobilenetv2_frozen_augTrue_prod\n"," - U-Net_mobilenetv2_frozen_augTrue_test\n"," - U-Net_vanilla_augFalse_prod\n"," - U-Net_vanilla_augFalse_prod_20250730_153443\n"," - U-Net_vanilla_augFalse_test\n"," - U-Net_vanilla_augTrue_prod\n"," - U-Net_vanilla_augTrue_prod_20250730_170602\n"," - U-Net_vanilla_augTrue_test\n"," - exp_001_baseline\n"," - exp_002_no_augmentation\n"," - exp_002_unfrozen\n","🔍 Recherche du meilleur modèle parmi 17 configurations...\n","🏆 MEILLEUR MODÈLE TROUVÉ:\n"," 📊 [15] FPN_efficientnetb0_finetune_augTrue\n"," 🏗️ FPN + efficientnetb0\n"," 🎯 Test Mean IoU: 0.7457\n"," 📈 Test Accuracy: 0.9123\n"," 🆔 Run ID: b6dd1ecdeb3f4b5c899b332f3c948cd7\n","\n"]},{"output_type":"display_data","data":{"text/plain":["Downloading artifacts: 0%| | 0/1 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["🔢 Matrice de confusion brute (premiers/derniers éléments):\n","============================================================\n","Classes: ['flat', 'human', 'vehicle', 'construction', 'object', 'nature', 'sky', 'void']\n","Matrice (format: lignes=réel, colonnes=prédit):\n","[[9339912 11922 31996 27736 7639 19873 159 96403]\n"," [ 9298 240878 27954 32796 6215 7121 22 7213]\n"," [ 28923 20536 1630480 57085 7436 16871 280 13413]\n"," [ 37107 27385 39861 4762597 51086 145430 14571 61532]\n"," [ 12585 11363 14823 148802 240856 58198 2359 24774]\n"," [ 30020 6106 17487 161547 21272 3703362 10850 23316]\n"," [ 2 2 139 17203 1113 12668 701752 3902]\n"," [ 400815 21207 41511 245295 36253 56041 13049 2267598]]\n"]}],"source":["# Utilisation\n","confusion_result = display_best_confusion_matrix()"]},{"cell_type":"markdown","source":["Affichage de la répartition des modalités dans l'ensemble du dataset d'apprentissage (on passe par le json de matrice de confusion pour gagner du temps)"],"metadata":{"id":"KsVx1dEpBPph"}},{"cell_type":"code","source":["def analyze_class_distribution_from_confusion_matrix(experiment_name=\"OC Projet 8\",\n"," figsize=(14, 8),\n"," color_palette='viridis',\n"," show_values=True):\n"," \"\"\"\n"," Analyse la répartition des classes à partir de la matrice de confusion du meilleur modèle.\n"," Affiche un graphique en barres avec pourcentages (axe gauche) et nombres absolus (axe droite).\n","\n"," Args:\n"," experiment_name (str): Nom de l'expérience MLflow\n"," figsize (tuple): Taille de la figure (largeur, hauteur)\n"," color_palette (str): Palette de couleurs pour les barres\n"," show_values (bool): Afficher les valeurs sur les barres\n","\n"," Returns:\n"," dict: Dictionnaire contenant les statistiques de distribution\n"," \"\"\"\n"," import matplotlib.pyplot as plt\n"," import numpy as np\n"," import json\n"," import tempfile\n"," import seaborn as sns\n","\n"," # Récupérer les informations du meilleur modèle\n"," completed_configs = get_completed_configs_info(experimental_configurations, experiment_name)\n","\n"," if not completed_configs:\n"," print(\"❌ Aucune expérience terminée trouvée\")\n"," return None\n","\n"," # Récupérer le mapping run_name -> run_id depuis MLflow\n"," experiment = mlflow.get_experiment_by_name(experiment_name)\n"," runs_df = mlflow.search_runs(\n"," experiment_ids=[experiment.experiment_id],\n"," filter_string=\"status = 'FINISHED'\",\n"," output_format=\"pandas\"\n"," )\n","\n"," run_name_to_id = {\n"," run.get('tags.mlflow.runName', ''): run['run_id']\n"," for _, run in runs_df.iterrows()\n"," }\n","\n"," # Trouver le meilleur modèle (même logique que display_best_confusion_matrix)\n"," best_result = None\n"," best_iou = -1\n","\n"," for config_idx, config, run_name in completed_configs:\n"," if run_name not in run_name_to_id:\n"," continue\n","\n"," run_id = run_name_to_id[run_name]\n","\n"," try:\n"," run = mlflow.get_run(run_id)\n"," metrics = run.data.metrics\n"," test_mean_iou = metrics.get('test_mean_iou', None)\n","\n"," if test_mean_iou is not None and test_mean_iou > best_iou:\n"," best_iou = test_mean_iou\n"," best_result = {\n"," 'config_idx': config_idx,\n"," 'experiment': config['name'],\n"," 'architecture': config.get('architecture', 'Unknown'),\n"," 'encoder': config.get('encoder', 'None'),\n"," 'test_mean_iou': test_mean_iou,\n"," 'run_name': run_name,\n"," 'run_id': run_id\n"," }\n"," except Exception as e:\n"," continue\n","\n"," if best_result is None:\n"," print(\"❌ Aucun modèle avec test_mean_iou trouvé\")\n"," return None\n","\n"," print(f\"🏆 Analyse de distribution pour le meilleur modèle:\")\n"," print(f\" 📊 [{best_result['config_idx']}] {best_result['experiment']}\")\n"," print(f\" 🎯 Test Mean IoU: {best_result['test_mean_iou']:.4f}\")\n"," print()\n","\n"," # Télécharger et analyser la matrice de confusion\n"," try:\n"," with tempfile.TemporaryDirectory() as temp_dir:\n"," confusion_matrix_path = mlflow.artifacts.download_artifacts(\n"," run_id=best_result['run_id'],\n"," artifact_path=\"confusion_matrix.json\",\n"," dst_path=temp_dir\n"," )\n","\n"," with open(confusion_matrix_path, 'r') as f:\n"," confusion_data = json.load(f)\n","\n"," matrix = np.array(confusion_data['matrix'])\n"," class_names = confusion_data['class_names']\n","\n"," # Calculer la distribution des classes (somme par ligne = nombre total de pixels réels par classe)\n"," class_counts = np.sum(matrix, axis=1) # Somme par ligne pour obtenir le nombre total de chaque classe réelle\n"," total_pixels = np.sum(class_counts)\n"," class_percentages = (class_counts / total_pixels) * 100\n","\n"," # Statistiques détaillées\n"," print(\"📈 RÉPARTITION DES CLASSES DANS L'ÉCHANTILLON:\")\n"," print(\"=\" * 65)\n"," print(f\"{'Classe':<15} {'Nb Pixels':<12} {'Pourcentage':<12} {'Barre':<20}\")\n"," print(\"-\" * 65)\n","\n"," for i, class_name in enumerate(class_names):\n"," bar_length = int(class_percentages[i] / 2) # Barre visuelle\n"," bar = \"█\" * bar_length\n"," print(f\"{class_name:<15} {class_counts[i]:<12,} {class_percentages[i]:<11.2f}% {bar}\")\n","\n"," print(\"-\" * 65)\n"," print(f\"{'TOTAL':<15} {total_pixels:<12,} {'100.00%':<12}\")\n"," print()\n","\n"," # Créer le graphique\n"," fig, ax1 = plt.subplots(figsize=figsize)\n","\n"," # Utiliser une palette de couleurs\n"," colors = plt.cm.get_cmap(color_palette)(np.linspace(0, 1, len(class_names)))\n","\n"," # Barres avec les pourcentages (axe gauche)\n"," bars = ax1.bar(range(len(class_names)), class_percentages,\n"," color=colors, alpha=0.8, edgecolor='black', linewidth=1)\n","\n"," # Configuration axe gauche (pourcentages)\n"," ax1.set_xlabel('Classes', fontsize=12, fontweight='bold')\n"," ax1.set_ylabel('Pourcentage (%)', fontsize=12, fontweight='bold', color='blue')\n"," ax1.tick_params(axis='y', labelcolor='blue')\n"," ax1.set_xticks(range(len(class_names)))\n"," ax1.set_xticklabels(class_names, rotation=45, ha='right')\n"," ax1.grid(True, alpha=0.3, axis='y')\n","\n"," # Créer un second axe y pour les nombres absolus\n"," ax2 = ax1.twinx()\n"," ax2.set_ylabel('Nombre de Pixels', fontsize=12, fontweight='bold', color='red')\n"," ax2.tick_params(axis='y', labelcolor='red')\n","\n"," # Synchroniser les échelles\n"," ax2.set_ylim(0, np.max(class_counts) * 1.1)\n"," ax1.set_ylim(0, np.max(class_percentages) * 1.1)\n","\n"," # Ajouter les valeurs sur les barres si demandé\n"," if show_values:\n"," for i, (bar, count, pct) in enumerate(zip(bars, class_counts, class_percentages)):\n"," height = bar.get_height()\n"," # Pourcentage au-dessus de la barre\n"," ax1.text(bar.get_x() + bar.get_width()/2., height + 0.5,\n"," f'{pct:.1f}%', ha='center', va='bottom', fontweight='bold', fontsize=10)\n"," # Nombre absolu à l'intérieur de la barre\n"," ax1.text(bar.get_x() + bar.get_width()/2., height/2,\n"," f'{count:,}', ha='center', va='center',\n"," color='white', fontweight='bold', fontsize=9)\n","\n"," # Titre et mise en forme\n"," plt.title(f'Répartition des Classes par Pixels\\n'\n"," f'Total: {total_pixels:,} pixels | Mean IoU: {best_result[\"test_mean_iou\"]:.4f}',\n"," fontsize=14, fontweight='bold', pad=20)\n","\n"," plt.tight_layout()\n"," plt.show()\n","\n"," # Statistiques supplémentaires\n"," print(\"📊 STATISTIQUES COMPLÉMENTAIRES:\")\n"," print(\"-\" * 40)\n"," print(f\" 🔢 Nombre total de pixels: {total_pixels:,}\")\n"," print(f\" 📏 Nombre de classes: {len(class_names)}\")\n"," print(f\" 📈 Classe la plus représentée: {class_names[np.argmax(class_counts)]} ({np.max(class_percentages):.2f}%)\")\n"," print(f\" 📉 Classe la moins représentée: {class_names[np.argmin(class_counts)]} ({np.min(class_percentages):.2f}%)\")\n"," print(f\" ⚖️ Ratio max/min: {np.max(class_counts)/np.min(class_counts):.2f}\")\n","\n"," # Calcul de l'équilibrage des classes\n"," ideal_percentage = 100 / len(class_names)\n"," imbalance_scores = np.abs(class_percentages - ideal_percentage)\n"," avg_imbalance = np.mean(imbalance_scores)\n"," print(f\" ⚖️ Score de déséquilibre moyen: {avg_imbalance:.2f}% (0 = parfait équilibre)\")\n"," print()\n","\n"," return {\n"," 'class_names': class_names,\n"," 'class_counts': class_counts,\n"," 'class_percentages': class_percentages,\n"," 'total_pixels': total_pixels,\n"," 'best_model_info': best_result,\n"," 'most_common_class': class_names[np.argmax(class_counts)],\n"," 'least_common_class': class_names[np.argmin(class_counts)],\n"," 'imbalance_ratio': np.max(class_counts)/np.min(class_counts),\n"," 'avg_imbalance_score': avg_imbalance\n"," }\n","\n"," except Exception as e:\n"," print(f\"❌ Erreur lors de l'analyse de distribution: {e}\")\n"," print(f\" Run ID: {best_result['run_id']}\")\n"," return None\n","\n","\n","def compare_class_distributions(experiment_name=\"OC Projet 8\", top_n=3):\n"," \"\"\"\n"," Compare la répartition des classes entre les N meilleurs modèles.\n","\n"," Args:\n"," experiment_name (str): Nom de l'expérience MLflow\n"," top_n (int): Nombre de meilleurs modèles à comparer\n"," \"\"\"\n"," import matplotlib.pyplot as plt\n"," import numpy as np\n"," import json\n"," import tempfile\n"," import seaborn as sns\n","\n"," # Récupérer et trier les modèles par performance\n"," completed_configs = get_completed_configs_info(experimental_configurations, experiment_name)\n","\n"," if not completed_configs:\n"," print(\"❌ Aucune expérience terminée trouvée\")\n"," return None\n","\n"," experiment = mlflow.get_experiment_by_name(experiment_name)\n"," runs_df = mlflow.search_runs(\n"," experiment_ids=[experiment.experiment_id],\n"," filter_string=\"status = 'FINISHED'\",\n"," output_format=\"pandas\"\n"," )\n","\n"," run_name_to_id = {\n"," run.get('tags.mlflow.runName', ''): run['run_id']\n"," for _, run in runs_df.iterrows()\n"," }\n","\n"," # Collecter les performances de tous les modèles\n"," models_performance = []\n","\n"," for config_idx, config, run_name in completed_configs:\n"," if run_name not in run_name_to_id:\n"," continue\n","\n"," run_id = run_name_to_id[run_name]\n","\n"," try:\n"," run = mlflow.get_run(run_id)\n"," metrics = run.data.metrics\n"," test_mean_iou = metrics.get('test_mean_iou', None)\n","\n"," if test_mean_iou is not None:\n"," models_performance.append({\n"," 'config_idx': config_idx,\n"," 'experiment': config['name'],\n"," 'test_mean_iou': test_mean_iou,\n"," 'run_name': run_name,\n"," 'run_id': run_id\n"," })\n"," except Exception as e:\n"," continue\n","\n"," # Trier par performance et prendre les N meilleurs\n"," models_performance.sort(key=lambda x: x['test_mean_iou'], reverse=True)\n"," top_models = models_performance[:top_n]\n","\n"," print(f\"🏆 COMPARAISON DES {len(top_models)} MEILLEURS MODÈLES:\")\n"," print(\"=\" * 60)\n","\n"," # Analyser chaque modèle\n"," all_distributions = []\n"," class_names = None\n","\n"," for i, model in enumerate(top_models):\n"," print(f\"📊 Modèle #{i+1}: {model['experiment']} (IoU: {model['test_mean_iou']:.4f})\")\n","\n"," try:\n"," with tempfile.TemporaryDirectory() as temp_dir:\n"," confusion_matrix_path = mlflow.artifacts.download_artifacts(\n"," run_id=model['run_id'],\n"," artifact_path=\"confusion_matrix.json\",\n"," dst_path=temp_dir\n"," )\n","\n"," with open(confusion_matrix_path, 'r') as f:\n"," confusion_data = json.load(f)\n","\n"," matrix = np.array(confusion_data['matrix'])\n"," if class_names is None:\n"," class_names = confusion_data['class_names']\n","\n"," class_counts = np.sum(matrix, axis=1)\n"," total_pixels = np.sum(class_counts)\n"," class_percentages = (class_counts / total_pixels) * 100\n","\n"," all_distributions.append({\n"," 'model_name': f\"Modèle {i+1}\",\n"," 'percentages': class_percentages,\n"," 'counts': class_counts,\n"," 'iou': model['test_mean_iou']\n"," })\n","\n"," except Exception as e:\n"," print(f\" ⚠️ Erreur: {e}\")\n"," continue\n","\n"," if not all_distributions:\n"," print(\"❌ Impossible de récupérer les données de distribution\")\n"," return None\n","\n"," # Créer le graphique de comparaison\n"," fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 8))\n","\n"," # Graphique 1: Pourcentages\n"," x_pos = np.arange(len(class_names))\n"," bar_width = 0.8 / len(all_distributions)\n","\n"," for i, dist in enumerate(all_distributions):\n"," ax1.bar(x_pos + i * bar_width, dist['percentages'],\n"," bar_width, label=f\"{dist['model_name']} (IoU: {dist['iou']:.3f})\",\n"," alpha=0.8)\n","\n"," ax1.set_xlabel('Classes')\n"," ax1.set_ylabel('Pourcentage (%)')\n"," ax1.set_title('Comparaison des Distributions par Classe (%)')\n"," ax1.set_xticks(x_pos + bar_width * (len(all_distributions) - 1) / 2)\n"," ax1.set_xticklabels(class_names, rotation=45, ha='right')\n"," ax1.legend()\n"," ax1.grid(True, alpha=0.3)\n","\n"," # Graphique 2: Heatmap des différences relatives au meilleur modèle\n"," reference_dist = all_distributions[0]['percentages'] # Le meilleur modèle comme référence\n"," diff_matrix = []\n","\n"," for dist in all_distributions:\n"," relative_diff = ((dist['percentages'] - reference_dist) / reference_dist) * 100\n"," diff_matrix.append(relative_diff)\n","\n"," sns.heatmap(diff_matrix,\n"," xticklabels=class_names,\n"," yticklabels=[dist['model_name'] for dist in all_distributions],\n"," cmap='RdBu_r', center=0, annot=True, fmt='.1f',\n"," cbar_kws={'label': 'Différence relative (%)'},\n"," ax=ax2)\n","\n"," ax2.set_title(f'Différences Relatives au Meilleur Modèle\\n(Référence: {all_distributions[0][\"model_name\"]})')\n"," ax2.set_xlabel('Classes')\n","\n"," plt.tight_layout()\n"," plt.show()\n","\n"," return {\n"," 'top_models': top_models,\n"," 'distributions': all_distributions,\n"," 'class_names': class_names\n"," }"],"metadata":{"id":"LXs3Sr5pA6uJ","executionInfo":{"status":"ok","timestamp":1754981151442,"user_tz":-120,"elapsed":164,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"execution_count":37,"outputs":[]},{"cell_type":"code","source":["# Analyse simple du meilleur modèle\n","result = analyze_class_distribution_from_confusion_matrix(\"OC Projet 8\")\n","\n","# Avec personnalisation\n","result = analyze_class_distribution_from_confusion_matrix(\n"," experiment_name=\"OC Projet 8\",\n"," figsize=(16, 10),\n"," color_palette='plasma',\n"," show_values=True\n",")\n","\n","# Comparaison entre plusieurs modèles\n","comparison = compare_class_distributions(\"OC Projet 8\", top_n=3)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000,"referenced_widgets":["0814405d6086476bbb2ce5ff31ee24fe","1288de0fadb54c03bb1a62c8f9a54076","c31c3ddb9fc743a1b9b3f88a1415819f","8072bb3d4816439ba2e706ec1800f602","745627c8443b43a8be3600bac3a03f75","39e52ed0f4ab4a00b0b8b8dd79227d09","28d74235f7af44d58fcdd73540130395","af907ef5c98f45e7bcdb9dfb4b9c4e19","f16b43ee72db482db365dc19b34279d2","afb8e1ef0c7642f18b0a55061ced6ba0","86223e1bc4774d59b854e28e479f5fa6","ea57b0429a394fdca0b9d1c199705f62","285d0104a49749f0914caab4633ba95f","b1954114b94442a1afef5fef5bd197e1","7703627bc5f84c01adf142b882dea1a0","b5de34b2a7114cb78c443bc9c57dd913","0c7daff8beaa46918b2db8a2e598c55d","b61fa6b5f26e418ca659e96b46aeec7b","2dea319059604490bc4dc6ccdf32f90c","470f3d2cd2c34156ac4660ff19ad0cd5","b2805d79bf224a259bcf31504e6a98a0","1d0403d7a48f4f78a5ed385e26141102","3e1a19271ccc42e1bbcb78b0a3bed498","fb03d61318424159a68af92d7b5905fd","b39d3dcf293e4fbd86c04ef6064c684d","6a5fa67683cb430a8f82ccac7ed8df1d","0bf8a446cb6a4314a61a007f6532fd3a","db5a00931ef44d07a5f784aa124b3925","983f9bc3c7164abab23c6fcde4ba1bd7","fcb838679d264e51bff81d1fa8a0a110","e2c87ebdaf5d4f74a445a3892e3fd7ad","6b7a0d91fc52443cbf807d2bfcd29de2","34c6f6b3248e496796002094701b6e14","e0b2701aedc84593a9a48a4a05057b42","5020a5cc9d3c45c09b16915d8f5aca8e","4a91a17d98624c16982a073a53ef3acd","7049cef08ba04207b58db406da46e655","8354fa35766a402ea853f31210188fa5","18e09f691f8c48bda8c80dbd8d3cdcbf","63e8b18b98f74a6b8ecc4c37582ddc34","b3278303d86446d8a9321d401667adc8","6752fb87421d49989fe3c5716770c983","1e3af0148879401da1e96b5fe593cf1b","b7399763b1ca42799cad80619bb34756","1e46e810a51146c191c083337215012c","5febffdeb3f344b782112170fe40433e","5260f52807fa4b979070284a3738759f","e8338bea77b34ade8d3461ad408470a8","2b490d66948f448c81896b9c56d44c2a","43e14174355b4441803a94e9306e45df","6a088a189bc94acf87aa1099c2bec9fd","00577047db6d4fe3b949a33e87e60e4b","823e48aabb094171a043e70e1b817683","12c8c85d30694229b21951e6415e1425","b427a4205526434c9e1649cb0a631b13"]},"id":"VoTFNfGhBY8x","executionInfo":{"status":"ok","timestamp":1754981172370,"user_tz":-120,"elapsed":19492,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}},"outputId":"e41a5021-52f8-4718-a0fb-80d9afaa0c82"},"execution_count":38,"outputs":[{"output_type":"stream","name":"stdout","text":["🔍 Vérification des expériences déjà terminées dans 'OC Projet 8'...\n","✅ 39 expériences terminées trouvées:\n"," - FPN_efficientnetb0_finetune_augTrue_prod\n"," - FPN_efficientnetb0_finetune_augTrue_test\n"," - FPN_efficientnetb0_frozen_augFalse_prod\n"," - FPN_efficientnetb0_frozen_augFalse_test\n"," - FPN_efficientnetb0_frozen_augTrue_prod\n"," - FPN_efficientnetb0_frozen_augTrue_test\n"," - FPN_mobilenetv2_frozen_augFalse_prod\n"," - FPN_mobilenetv2_frozen_augFalse_test\n"," - FPN_mobilenetv2_frozen_augTrue_prod\n"," - FPN_mobilenetv2_frozen_augTrue_test\n"," - FPN_resnet34_finetune_augTrue_prod\n"," - FPN_resnet34_finetune_augTrue_test\n"," - FPN_resnet34_frozen_augFalse_prod\n"," - FPN_resnet34_frozen_augFalse_test\n"," - FPN_resnet34_frozen_augTrue_prod\n"," - FPN_resnet34_frozen_augTrue_test\n"," - FPN_vanilla_augFalse_prod\n"," - FPN_vanilla_augFalse_test\n"," - FPN_vanilla_augTrue_prod\n"," - FPN_vanilla_augTrue_test\n"," - U-Net_efficientnetb0_frozen_augFalse_prod\n"," - U-Net_efficientnetb0_frozen_augFalse_test\n"," - U-Net_efficientnetb0_frozen_augTrue_prod\n"," - U-Net_efficientnetb0_frozen_augTrue_test\n"," - U-Net_mobilenetv2_finetune_augTrue_prod\n"," - U-Net_mobilenetv2_finetune_augTrue_test\n"," - U-Net_mobilenetv2_frozen_augFalse_prod\n"," - U-Net_mobilenetv2_frozen_augFalse_test\n"," - U-Net_mobilenetv2_frozen_augTrue_prod\n"," - U-Net_mobilenetv2_frozen_augTrue_test\n"," - U-Net_vanilla_augFalse_prod\n"," - U-Net_vanilla_augFalse_prod_20250730_153443\n"," - U-Net_vanilla_augFalse_test\n"," - U-Net_vanilla_augTrue_prod\n"," - U-Net_vanilla_augTrue_prod_20250730_170602\n"," - U-Net_vanilla_augTrue_test\n"," - exp_001_baseline\n"," - exp_002_no_augmentation\n"," - exp_002_unfrozen\n","🏆 Analyse de distribution pour le meilleur modèle:\n"," 📊 [15] FPN_efficientnetb0_finetune_augTrue\n"," 🎯 Test Mean IoU: 0.7457\n","\n"]},{"output_type":"display_data","data":{"text/plain":["Downloading artifacts: 0%| | 0/1 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["📊 STATISTIQUES COMPLÉMENTAIRES:\n","----------------------------------------\n"," 🔢 Nombre total de pixels: 25,088,000\n"," 📏 Nombre de classes: 8\n"," 📈 Classe la plus représentée: flat (38.01%)\n"," 📉 Classe la moins représentée: human (1.32%)\n"," ⚖️ Ratio max/min: 28.77\n"," ⚖️ Score de déséquilibre moyen: 9.21% (0 = parfait équilibre)\n","\n","🔍 Vérification des expériences déjà terminées dans 'OC Projet 8'...\n","✅ 39 expériences terminées trouvées:\n"," - FPN_efficientnetb0_finetune_augTrue_prod\n"," - FPN_efficientnetb0_finetune_augTrue_test\n"," - FPN_efficientnetb0_frozen_augFalse_prod\n"," - FPN_efficientnetb0_frozen_augFalse_test\n"," - FPN_efficientnetb0_frozen_augTrue_prod\n"," - FPN_efficientnetb0_frozen_augTrue_test\n"," - FPN_mobilenetv2_frozen_augFalse_prod\n"," - FPN_mobilenetv2_frozen_augFalse_test\n"," - FPN_mobilenetv2_frozen_augTrue_prod\n"," - FPN_mobilenetv2_frozen_augTrue_test\n"," - FPN_resnet34_finetune_augTrue_prod\n"," - FPN_resnet34_finetune_augTrue_test\n"," - FPN_resnet34_frozen_augFalse_prod\n"," - FPN_resnet34_frozen_augFalse_test\n"," - FPN_resnet34_frozen_augTrue_prod\n"," - FPN_resnet34_frozen_augTrue_test\n"," - FPN_vanilla_augFalse_prod\n"," - FPN_vanilla_augFalse_test\n"," - FPN_vanilla_augTrue_prod\n"," - FPN_vanilla_augTrue_test\n"," - U-Net_efficientnetb0_frozen_augFalse_prod\n"," - U-Net_efficientnetb0_frozen_augFalse_test\n"," - U-Net_efficientnetb0_frozen_augTrue_prod\n"," - U-Net_efficientnetb0_frozen_augTrue_test\n"," - U-Net_mobilenetv2_finetune_augTrue_prod\n"," - U-Net_mobilenetv2_finetune_augTrue_test\n"," - U-Net_mobilenetv2_frozen_augFalse_prod\n"," - U-Net_mobilenetv2_frozen_augFalse_test\n"," - U-Net_mobilenetv2_frozen_augTrue_prod\n"," - U-Net_mobilenetv2_frozen_augTrue_test\n"," - U-Net_vanilla_augFalse_prod\n"," - U-Net_vanilla_augFalse_prod_20250730_153443\n"," - U-Net_vanilla_augFalse_test\n"," - U-Net_vanilla_augTrue_prod\n"," - U-Net_vanilla_augTrue_prod_20250730_170602\n"," - U-Net_vanilla_augTrue_test\n"," - exp_001_baseline\n"," - exp_002_no_augmentation\n"," - exp_002_unfrozen\n","🏆 Analyse de distribution pour le meilleur modèle:\n"," 📊 [15] FPN_efficientnetb0_finetune_augTrue\n"," 🎯 Test Mean IoU: 0.7457\n","\n"]},{"output_type":"display_data","data":{"text/plain":["Downloading artifacts: 0%| | 0/1 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["📊 STATISTIQUES COMPLÉMENTAIRES:\n","----------------------------------------\n"," 🔢 Nombre total de pixels: 25,088,000\n"," 📏 Nombre de classes: 8\n"," 📈 Classe la plus représentée: flat (38.01%)\n"," 📉 Classe la moins représentée: human (1.32%)\n"," ⚖️ Ratio max/min: 28.77\n"," ⚖️ Score de déséquilibre moyen: 9.21% (0 = parfait équilibre)\n","\n","🔍 Vérification des expériences déjà terminées dans 'OC Projet 8'...\n","✅ 39 expériences terminées trouvées:\n"," - FPN_efficientnetb0_finetune_augTrue_prod\n"," - FPN_efficientnetb0_finetune_augTrue_test\n"," - FPN_efficientnetb0_frozen_augFalse_prod\n"," - FPN_efficientnetb0_frozen_augFalse_test\n"," - FPN_efficientnetb0_frozen_augTrue_prod\n"," - FPN_efficientnetb0_frozen_augTrue_test\n"," - FPN_mobilenetv2_frozen_augFalse_prod\n"," - FPN_mobilenetv2_frozen_augFalse_test\n"," - FPN_mobilenetv2_frozen_augTrue_prod\n"," - FPN_mobilenetv2_frozen_augTrue_test\n"," - FPN_resnet34_finetune_augTrue_prod\n"," - FPN_resnet34_finetune_augTrue_test\n"," - FPN_resnet34_frozen_augFalse_prod\n"," - FPN_resnet34_frozen_augFalse_test\n"," - FPN_resnet34_frozen_augTrue_prod\n"," - FPN_resnet34_frozen_augTrue_test\n"," - FPN_vanilla_augFalse_prod\n"," - FPN_vanilla_augFalse_test\n"," - FPN_vanilla_augTrue_prod\n"," - FPN_vanilla_augTrue_test\n"," - U-Net_efficientnetb0_frozen_augFalse_prod\n"," - U-Net_efficientnetb0_frozen_augFalse_test\n"," - U-Net_efficientnetb0_frozen_augTrue_prod\n"," - U-Net_efficientnetb0_frozen_augTrue_test\n"," - U-Net_mobilenetv2_finetune_augTrue_prod\n"," - U-Net_mobilenetv2_finetune_augTrue_test\n"," - U-Net_mobilenetv2_frozen_augFalse_prod\n"," - U-Net_mobilenetv2_frozen_augFalse_test\n"," - U-Net_mobilenetv2_frozen_augTrue_prod\n"," - U-Net_mobilenetv2_frozen_augTrue_test\n"," - U-Net_vanilla_augFalse_prod\n"," - U-Net_vanilla_augFalse_prod_20250730_153443\n"," - U-Net_vanilla_augFalse_test\n"," - U-Net_vanilla_augTrue_prod\n"," - U-Net_vanilla_augTrue_prod_20250730_170602\n"," - U-Net_vanilla_augTrue_test\n"," - exp_001_baseline\n"," - exp_002_no_augmentation\n"," - exp_002_unfrozen\n","🏆 COMPARAISON DES 3 MEILLEURS MODÈLES:\n","============================================================\n","📊 Modèle #1: FPN_efficientnetb0_finetune_augTrue (IoU: 0.7457)\n"]},{"output_type":"display_data","data":{"text/plain":["Downloading artifacts: 0%| | 0/1 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\n"},"metadata":{}}]},{"cell_type":"markdown","metadata":{"id":"8-vXPIYNSALV"},"source":["### Mise en production meilleur modèle"]},{"cell_type":"code","source":["def register_best_model(experiment_name=\"OC Projet 8\", model_name=\"StreetsSegmentation\",\n"," force=False, specific_run_id=None):\n"," \"\"\"\n"," Enregistre le meilleur modèle (selon test_mean_iou) OU un modèle spécifique dans le Registry MLflow.\n","\n"," Args:\n"," experiment_name (str): Nom de l'expérience MLflow\n"," model_name (str): Nom du modèle dans le Registry\n"," force (bool): Si True, force la mise en production même si le score est moins bon\n"," specific_run_id (str): Si fourni, enregistre ce run spécifique au lieu du meilleur\n"," \"\"\"\n"," print(f\"\\n{'='*60}\")\n"," if specific_run_id:\n"," print(f\"🎯 Enregistrement d'un modèle SPÉCIFIQUE dans le Registry MLflow\")\n"," print(f\"🆔 Run ID spécifique: {specific_run_id}\")\n"," else:\n"," print(f\"🏆 Enregistrement du MEILLEUR modèle dans le Registry MLflow\")\n"," print(f\"🔬 Expérience MLflow: {experiment_name}\")\n"," print(f\"📦 Nom du modèle Registry: {model_name}\")\n"," if force:\n"," print(f\"⚡ Mode FORCE activé - Mise en prod forcée\")\n"," print(f\"{'='*60}\")\n","\n"," # 1. Si un run_id spécifique est fourni, l'utiliser directement\n"," if specific_run_id:\n"," print(f\"🎯 Mode spécifique activé - utilisation du run {specific_run_id}\")\n","\n"," try:\n"," # Vérifier que le run existe et récupérer ses métriques\n"," run = mlflow.get_run(specific_run_id)\n"," metrics = run.data.metrics\n"," params = run.data.params\n","\n"," test_mean_iou = metrics.get('test_mean_iou', None)\n"," test_accuracy = metrics.get('test_sparse_categorical_accuracy', None)\n"," run_name = run.data.tags.get('mlflow.runName', 'Unknown')\n","\n"," if test_mean_iou is None:\n"," print(\"⚠️ Le run spécifique n'a pas de métrique test_mean_iou\")\n"," if not force:\n"," print(\"❌ Utilisez force=True pour forcer l'enregistrement sans métriques\")\n"," return None\n","\n"," selected_result = {\n"," 'run_id': specific_run_id,\n"," 'test_mean_iou': test_mean_iou or -1.0,\n"," 'test_accuracy': test_accuracy,\n"," 'experiment_name': run_name,\n"," 'selection_mode': 'specific'\n"," }\n","\n"," print(f\"✅ Run spécifique trouvé:\")\n"," print(f\" • Run Name: {run_name}\")\n"," print(f\" • Run ID: {specific_run_id}\")\n"," if test_mean_iou:\n"," print(f\" • Test Mean IoU: {test_mean_iou:.4f}\")\n"," if test_accuracy:\n"," print(f\" • Test Accuracy: {test_accuracy:.4f}\")\n","\n"," except Exception as e:\n"," print(f\"❌ Erreur lors de la récupération du run spécifique {specific_run_id}: {e}\")\n"," return None\n","\n"," else:\n"," # 2. Mode automatique : trouver le meilleur modèle (logique existante)\n"," print(\"🔍 Mode automatique - recherche du meilleur modèle...\")\n","\n"," # Récupérer les configurations terminées (réutilise la logique existante)\n"," completed_configs = get_completed_configs_info(experimental_configurations, experiment_name)\n","\n"," if not completed_configs:\n"," print(\"❌ Aucune expérience terminée trouvée\")\n"," return None\n","\n"," # Récupérer les métriques MLflow pour chaque run\n"," experiment = mlflow.get_experiment_by_name(experiment_name)\n"," runs_df = mlflow.search_runs(\n"," experiment_ids=[experiment.experiment_id],\n"," filter_string=\"status = 'FINISHED'\",\n"," output_format=\"pandas\"\n"," )\n","\n"," run_name_to_id = {\n"," run.get('tags.mlflow.runName', ''): run['run_id']\n"," for _, run in runs_df.iterrows()\n"," }\n","\n"," print(f\"📊 Analyse de {len(completed_configs)} configurations terminées\")\n","\n"," # Collecter les résultats avec métriques\n"," results = []\n"," for config_idx, config, run_name in completed_configs:\n"," if run_name not in run_name_to_id:\n"," continue\n","\n"," run_id = run_name_to_id[run_name]\n","\n"," try:\n"," # Récupérer les métriques directement depuis MLflow\n"," run = mlflow.get_run(run_id)\n"," metrics = run.data.metrics\n","\n"," test_mean_iou = metrics.get('test_mean_iou', None)\n","\n"," if test_mean_iou is not None:\n"," results.append({\n"," 'config_idx': config_idx,\n"," 'config': config,\n"," 'run_name': run_name,\n"," 'run_id': run_id,\n"," 'test_mean_iou': test_mean_iou,\n"," 'experiment_name': config['name']\n"," })\n"," print(f\" ✅ [{config_idx}] {config['name']}: IoU={test_mean_iou:.4f}\")\n"," else:\n"," print(f\" ⚠️ [{config_idx}] {config['name']}: Pas de test_mean_iou\")\n","\n"," except Exception as e:\n"," print(f\" ❌ [{config_idx}] {config['name']}: Erreur - {e}\")\n"," continue\n","\n"," if not results:\n"," print(\"❌ Aucune expérience avec test_mean_iou trouvée\")\n"," return None\n","\n"," # Trouver le meilleur modèle\n"," best_result = max(results, key=lambda x: x['test_mean_iou'])\n","\n"," selected_result = {\n"," 'run_id': best_result['run_id'],\n"," 'test_mean_iou': best_result['test_mean_iou'],\n"," 'experiment_name': best_result['experiment_name'],\n"," 'selection_mode': 'automatic'\n"," }\n","\n"," print(f\"🏆 Meilleur modèle identifié:\")\n"," print(f\" • Expérience: {best_result['experiment_name']}\")\n"," print(f\" • Run ID: {best_result['run_id']}\")\n"," print(f\" • Test Mean IoU: {best_result['test_mean_iou']:.4f}\")\n","\n"," # 3. Vérifier si le modèle existe dans le Registry (reste identique)\n"," client = mlflow.client.MlflowClient()\n"," current_best_iou = -1.0\n"," model_exists = False\n"," latest_version = None\n","\n"," try:\n"," try:\n"," registered_model = client.get_registered_model(model_name)\n"," model_exists = True\n"," print(f\"\\n📦 Modèle '{model_name}' trouvé dans le Registry\")\n"," except mlflow.exceptions.RestException:\n"," model_exists = False\n"," print(f\"\\n📦 Modèle '{model_name}' n'existe pas encore dans le Registry\")\n","\n"," if model_exists:\n"," model_versions = client.search_model_versions(f\"name='{model_name}'\")\n"," if model_versions:\n"," latest_version = max(model_versions, key=lambda v: int(v.version))\n"," current_run = mlflow.get_run(latest_version.run_id)\n"," current_best_iou = current_run.data.metrics.get('test_mean_iou', -1.0)\n","\n"," print(f\" • Version la plus récente: {latest_version.version}\")\n"," print(f\" • Stage: {latest_version.current_stage}\")\n"," print(f\" • Test Mean IoU: {current_best_iou:.4f}\")\n","\n"," except Exception as e:\n"," print(f\"⚠️ Erreur lors de la vérification du Registry: {e}\")\n","\n"," # 4. Logique de comparaison adaptée\n"," if specific_run_id:\n"," # En mode spécifique, on enregistre toujours (sauf si force=False et pas de métriques)\n"," should_register = True\n"," if selected_result['test_mean_iou'] == -1.0 and not force:\n"," should_register = False\n"," print(\"❌ Le run spécifique n'a pas de métriques et force=False\")\n"," else:\n"," # En mode automatique, comparaison habituelle\n"," should_register = selected_result['test_mean_iou'] > current_best_iou or force\n","\n"," # 5. Enregistrement (logique existante adaptée)\n"," if should_register:\n"," if specific_run_id:\n"," print(f\"\\n🎯 Enregistrement du modèle spécifique...\")\n"," if selected_result['test_mean_iou'] > current_best_iou:\n"," action_msg = f\"Le modèle spécifique ({selected_result['test_mean_iou']:.4f}) est meilleur que l'actuel ({current_best_iou:.4f})\"\n"," elif force:\n"," action_msg = f\"Enregistrement FORCÉ du modèle spécifique\"\n"," else:\n"," action_msg = f\"Enregistrement du modèle spécifique\"\n"," print(f\" {action_msg}\")\n"," else:\n"," if not model_exists:\n"," print(f\"\\n🆕 Création du modèle '{model_name}' dans le Registry...\")\n"," action_msg = \"Création et enregistrement du premier modèle\"\n"," elif force and selected_result['test_mean_iou'] <= current_best_iou:\n"," print(f\"\\n⚡ FORCE MODE: Enregistrement forcé du modèle\")\n"," print(f\" Nouveau: {selected_result['test_mean_iou']:.4f} vs Actuel: {current_best_iou:.4f}\")\n"," action_msg = \"Enregistrement forcé de la nouvelle version\"\n"," else:\n"," print(f\"\\n🚀 Le nouveau modèle ({selected_result['test_mean_iou']:.4f}) est meilleur que l'actuel ({current_best_iou:.4f})\")\n"," action_msg = \"Enregistrement de la nouvelle version\"\n","\n"," print(f\" {action_msg}...\")\n","\n"," try:\n"," # Si le modèle n'existe pas, le créer\n"," if not model_exists:\n"," client.create_registered_model(\n"," name=model_name,\n"," description=f\"Modèle de segmentation des rues - Performance: {selected_result['test_mean_iou']:.4f}\"\n"," )\n"," print(f\" ✅ Modèle '{model_name}' créé dans le Registry\")\n","\n"," # Vérifier si une version existe déjà pour ce run spécifique\n"," existing_versions = [v for v in client.search_model_versions(f\"name='{model_name}'\")\n"," if v.run_id == selected_result['run_id']]\n","\n"," if existing_versions:\n"," model_version = existing_versions[0]\n"," print(f\" ℹ️ Version existante trouvée pour ce run: {model_version.version}\")\n"," else:\n"," print(\" 📝 Enregistrement d'une nouvelle version...\")\n","\n"," # Chercher l'artefact du modèle\n"," artifacts = client.list_artifacts(selected_result['run_id'])\n"," model_artifact_path = None\n","\n"," for artifact in artifacts:\n"," if any(pattern in artifact.path.lower() for pattern in\n"," ['model', 'best_model', '.keras', '.h5', '.pkl']):\n"," model_artifact_path = artifact.path\n"," break\n","\n"," if model_artifact_path is None:\n"," print(\" ❌ Aucun artefact de modèle trouvé dans le run\")\n"," return None\n","\n"," print(f\" 📁 Artefact trouvé: {model_artifact_path}\")\n","\n"," model_version = client.create_model_version(\n"," name=model_name,\n"," source=f\"runs:/{selected_result['run_id']}/{model_artifact_path}\",\n"," run_id=selected_result['run_id'],\n"," description=f\"Model from {selected_result['experiment_name']} - IoU: {selected_result['test_mean_iou']:.4f} - Mode: {selected_result['selection_mode']}\"\n"," )\n","\n"," # Ajouter les tags\n"," print(\" 🏷️ Ajout des tags de métadonnées...\")\n"," tags_to_add = {\n"," \"source_run_id\": selected_result['run_id'],\n"," \"test_mean_iou\": str(selected_result['test_mean_iou']),\n"," \"model_name\": model_name,\n"," \"source_experiment\": selected_result['experiment_name'],\n"," \"selection_mode\": selected_result['selection_mode'],\n"," \"registration_mode\": \"forced\" if force and selected_result['test_mean_iou'] <= current_best_iou else \"automatic\"\n"," }\n","\n"," for tag_key, tag_value in tags_to_add.items():\n"," client.set_model_version_tag(\n"," name=model_name,\n"," version=model_version.version,\n"," key=tag_key,\n"," value=tag_value\n"," )\n","\n"," # Promouvoir en Production\n"," print(f\" 🚀 Promotion de la version {model_version.version} en Production...\")\n"," client.transition_model_version_stage(\n"," name=model_name,\n"," version=model_version.version,\n"," stage=\"Production\",\n"," archive_existing_versions=True\n"," )\n","\n"," print(f\"✅ Modèle enregistré avec succès !\")\n"," print(f\" • Nom: {model_name}\")\n"," print(f\" • Version: {model_version.version}\")\n"," print(f\" • Stage: Production\")\n"," print(f\" • Test Mean IoU: {selected_result['test_mean_iou']:.4f}\")\n"," print(f\" • Mode de sélection: {selected_result['selection_mode']}\")\n","\n"," return {\n"," 'model_name': model_name,\n"," 'version': model_version.version,\n"," 'run_id': selected_result['run_id'],\n"," 'test_mean_iou': selected_result['test_mean_iou'],\n"," 'selection_mode': selected_result['selection_mode'],\n"," 'action': 'created' if not model_exists else 'updated',\n"," 'tags': tags_to_add\n"," }\n","\n"," except Exception as e:\n"," print(f\"❌ Erreur lors de l'enregistrement: {e}\")\n"," return None\n"," else:\n"," print(f\"\\n➡️ Aucun enregistrement effectué\")\n"," if specific_run_id:\n"," print(\" Le run spécifique n'a pas de métriques suffisantes\")\n"," print(\" 💡 Utilisez force=True pour forcer l'enregistrement\")\n"," else:\n"," print(f\" La version actuelle ({current_best_iou:.4f}) est déjà optimale\")\n"," print(\" 💡 Utilisez force=True pour forcer la mise en production\")\n","\n"," return {\n"," 'model_name': model_name,\n"," 'action': 'no_update',\n"," 'reason': 'Insufficient metrics' if specific_run_id else 'Current version is optimal',\n"," 'suggestion': 'Use force=True to override'\n"," }"],"metadata":{"id":"FxkVT7_IE9fI"},"execution_count":null,"outputs":[]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":7989,"status":"ok","timestamp":1754902146917,"user":{"displayName":"Grégoire","userId":"01249298206117462766"},"user_tz":-120},"id":"80mWsWg4Gi7Q","outputId":"a5019cd9-aa9f-4db7-bb62-d1195a16cbd6"},"outputs":[{"output_type":"stream","name":"stdout","text":["\n","============================================================\n","🎯 Enregistrement d'un modèle SPÉCIFIQUE dans le Registry MLflow\n","🆔 Run ID spécifique: b6dd1ecdeb3f4b5c899b332f3c948cd7\n","🔬 Expérience MLflow: OC Projet 8\n","📦 Nom du modèle Registry: StreetsSegmentation\n","⚡ Mode FORCE activé - Mise en prod forcée\n","============================================================\n","🎯 Mode spécifique activé - utilisation du run b6dd1ecdeb3f4b5c899b332f3c948cd7\n","✅ Run spécifique trouvé:\n"," • Run Name: FPN_efficientnetb0_finetune_augTrue_prod\n"," • Run ID: b6dd1ecdeb3f4b5c899b332f3c948cd7\n"," • Test Mean IoU: 0.7457\n"," • Test Accuracy: 0.9123\n","\n","📦 Modèle 'StreetsSegmentation' trouvé dans le Registry\n"," • Version la plus récente: 1\n"," • Stage: Production\n"," • Test Mean IoU: 0.7488\n","\n","🎯 Enregistrement du modèle spécifique...\n"," Enregistrement FORCÉ du modèle spécifique\n"," Enregistrement FORCÉ du modèle spécifique...\n"," 📝 Enregistrement d'une nouvelle version...\n"]},{"output_type":"stream","name":"stderr","text":["2025/08/11 08:49:04 INFO mlflow.store.model_registry.abstract_store: Waiting up to 300 seconds for model version to finish creation. Model name: StreetsSegmentation, version 2\n"]},{"output_type":"stream","name":"stdout","text":[" 📁 Artefact trouvé: best_model.keras\n"," 🏷️ Ajout des tags de métadonnées...\n"," 🚀 Promotion de la version 2 en Production...\n"]},{"output_type":"stream","name":"stderr","text":["/tmp/ipython-input-652925202.py:269: FutureWarning: ``mlflow.tracking.client.MlflowClient.transition_model_version_stage`` is deprecated since 2.9.0. Model registry stages will be removed in a future major release. To learn more about the deprecation of model registry stages, see our migration guide here: https://mlflow.org/docs/latest/model-registry.html#migrating-from-stages\n"," client.transition_model_version_stage(\n"]},{"output_type":"stream","name":"stdout","text":["✅ Modèle enregistré avec succès !\n"," • Nom: StreetsSegmentation\n"," • Version: 2\n"," • Stage: Production\n"," • Test Mean IoU: 0.7457\n"," • Mode de sélection: specific\n"]},{"output_type":"execute_result","data":{"text/plain":["{'model_name': 'StreetsSegmentation',\n"," 'version': '2',\n"," 'run_id': 'b6dd1ecdeb3f4b5c899b332f3c948cd7',\n"," 'test_mean_iou': 0.7457431554794312,\n"," 'selection_mode': 'specific',\n"," 'action': 'updated',\n"," 'tags': {'source_run_id': 'b6dd1ecdeb3f4b5c899b332f3c948cd7',\n"," 'test_mean_iou': '0.7457431554794312',\n"," 'model_name': 'StreetsSegmentation',\n"," 'source_experiment': 'FPN_efficientnetb0_finetune_augTrue_prod',\n"," 'selection_mode': 'specific',\n"," 'registration_mode': 'forced'}}"]},"metadata":{},"execution_count":56}],"source":["# Enregistrement automatique (seulement si meilleur)\n","register_best_model(experiment_name=\"OC Projet 8\", model_name=\"StreetsSegmentation\")"]},{"cell_type":"markdown","metadata":{"id":"m5gJ0G9SK2Pn"},"source":["## Fonction d'inférence et démonstration"]},{"cell_type":"markdown","source":["Les fonctions utiles sont toutes dans les imports en début de notebook"],"metadata":{"id":"IrCVqitDg5sk"}},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":170,"referenced_widgets":["e281656014894d9d9620797934ba5ac7","f471b2bed65b46b7a064af9923caaa9c","5c6880a939f24969b175a6ad56eb3199","ed37df01d0d241ddabd8dda1350cad89","2e9f4d996df84b45bae61884af237962","e5838e9e65dd4986975162d57fb00706","0c9d780c40aa4112b8476a595c8f5ddc","c1bb09b764fb4214a1f6c1f9d05873ec","6a3f0a658b494feabf00895d400d62e7","13a5ab43d16045ca8581f3a71bbce225","743b516205314924b2e4142867f3c816"]},"id":"Az_I9YlrRevb","executionInfo":{"status":"ok","timestamp":1754922747003,"user_tz":-120,"elapsed":21698,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}},"outputId":"87bb4bc5-9d6e-4fa9-f66f-3c20db294b78"},"outputs":[{"output_type":"stream","name":"stdout","text":["📦 Téléchargement du modèle StreetsSegmentation (run: b6dd1ecdeb3f4b5c899b332f3c948cd7)\n"]},{"output_type":"display_data","data":{"text/plain":["Downloading artifacts: 0%| | 0/1 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["\n","📊 Statistiques du masque prédit:\n"," flat: 6853 pixels (13.7%)\n"," human: 7970 pixels (15.9%)\n"," vehicle: 9227 pixels (18.4%)\n"," construction: 19823 pixels (39.5%)\n"," object: 1727 pixels (3.4%)\n"," nature: 889 pixels (1.8%)\n"," sky: 782 pixels (1.6%)\n"," void: 2905 pixels (5.8%)\n"]}]},{"cell_type":"code","source":["# === EXEMPLE D'UTILISATION ===\n","\n","# 1. Charger la configuration des classes\n","mapping_config = load_cityscapes_config(\"../cityscapes_config.json\")\n","\n","# 2. Faire l'inférence sur une nouvelle image\n","predicted_mask1 = run_inference_and_visualize(\n"," image_path=\"./content/data/test_images_sample/original/frankfurt_000000_000294_leftImg8bit.png\",\n"," mask_path=\"./content/data/test_images_sample/mask/frankfurt_000000_000294_gtFine_labelIds.png\",\n"," model=model,\n"," encoder_name=encoder_name,\n"," img_size=script_img_size,\n"," mapping_config=mapping_config\n",")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"RqYbA_qD52V2","executionInfo":{"status":"ok","timestamp":1754922759673,"user_tz":-120,"elapsed":4651,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}},"outputId":"212c3cd7-2dad-43b6-901a-829c32f478ef"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["== Groupes de classes Cityscapes ==\n"," - flat : ['road', 'sidewalk', 'parking', 'rail track']\n"," - human : ['person', 'rider']\n"," - vehicle : ['car', 'truck', 'bus', 'train', 'motorcycle', 'bicycle', 'caravan', 'trailer']\n"," - construction : ['building', 'wall', 'fence', 'guard rail', 'bridge', 'tunnel']\n"," - object : ['pole', 'pole group', 'traffic sign', 'traffic light']\n"," - nature : ['vegetation', 'terrain']\n"," - sky : ['sky']\n"," - void : ['unlabeled', 'ego vehicle', 'rectification border', 'out of roi', 'static', 'dynamic', 'ground']\n","\n","== Mapping ID Cityscapes → Groupe ==\n"," ID 0 ('unlabeled') → groupe 'void' (7)\n"," ID 1 ('ego vehicle') → groupe 'void' (7)\n"," ID 2 ('rectification border') → groupe 'void' (7)\n"," ID 3 ('out of roi') → groupe 'void' (7)\n"," ID 4 ('static') → groupe 'void' (7)\n"," ID 5 ('dynamic') → groupe 'void' (7)\n"," ID 6 ('ground') → groupe 'void' (7)\n"," ID 7 ('road') → groupe 'flat' (0)\n"," ID 8 ('sidewalk') → groupe 'flat' (0)\n"," ID 9 ('parking') → groupe 'flat' (0)\n"," ID 10 ('rail track') → groupe 'flat' (0)\n"," ID 11 ('building') → groupe 'construction' (3)\n"," ID 12 ('wall') → groupe 'construction' (3)\n"," ID 13 ('fence') → groupe 'construction' (3)\n"," ID 14 ('guard rail') → groupe 'construction' (3)\n"," ID 15 ('bridge') → groupe 'construction' (3)\n"," ID 16 ('tunnel') → groupe 'construction' (3)\n"," ID 17 ('pole') → groupe 'object' (4)\n"," ID 18 ('pole group') → groupe 'object' (4)\n"," ID 19 ('traffic light') → groupe 'object' (4)\n"," ID 20 ('traffic sign') → groupe 'object' (4)\n"," ID 21 ('vegetation') → groupe 'nature' (5)\n"," ID 22 ('terrain') → groupe 'nature' (5)\n"," ID 23 ('sky') → groupe 'sky' (6)\n"," ID 24 ('person') → groupe 'human' (1)\n"," ID 25 ('rider') → groupe 'human' (1)\n"," ID 26 ('car') → groupe 'vehicle' (2)\n"," ID 27 ('truck') → groupe 'vehicle' (2)\n"," ID 28 ('bus') → groupe 'vehicle' (2)\n"," ID 29 ('caravan') → groupe 'vehicle' (2)\n"," ID 30 ('trailer') → groupe 'vehicle' (2)\n"," ID 31 ('train') → groupe 'vehicle' (2)\n"," ID 32 ('motorcycle') → groupe 'vehicle' (2)\n"," ID 33 ('bicycle') → groupe 'vehicle' (2)\n","\n","== Liste des groupes et couleurs associées ==\n"," Groupe 0: flat - Couleur RGB : [128 64 128]\n"," Groupe 1: human - Couleur RGB : [220 20 60]\n"," Groupe 2: vehicle - Couleur RGB : [ 0 0 142]\n"," Groupe 3: construction - Couleur RGB : [70 70 70]\n"," Groupe 4: object - Couleur RGB : [220 220 0]\n"," Groupe 5: nature - Couleur RGB : [107 142 35]\n"," Groupe 6: sky - Couleur RGB : [ 70 130 180]\n"," Groupe 7: void - Couleur RGB : [0 0 0]\n","\n","Nombre total de groupes/classes : 8\n","=== INFÉRENCE SUR frankfurt_000000_000294_leftImg8bit.png ===\n","🔄 Préprocessing de l'image: frankfurt_000000_000294_leftImg8bit.png\n","ℹ️ Modèle vanilla - pas de preprocessing\n","🔄 Préprocessing du masque: frankfurt_000000_000294_gtFine_labelIds.png\n"," Valeurs uniques avant mapping: [ 3 2 11 23 17 4 20 21 26 24]...\n"," Valeurs uniques après mapping: [7 3 6 4 5 2 1 0]\n","🔮 Exécution de l'inférence...\n","✅ Inférence terminée - Shape: (224, 224)\n"]},{"output_type":"display_data","data":{"text/plain":["
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855IPkIITj31VC666CJuvfVW9t133+zctddey+bNm3nVq14F2HpMd0W/4x3voNFocNVVV3HSSSfxjW98Y0pYlTe+8Y3Mnz+f/+//+/9m3AH+4Q9/mDe/+c00m03e+c53ArBw4UIg39jw8MMPc9ZZZ7HLLrvwi1/8gvPOO49HH32UD3/4w1utP4fD4XDYOVdvyFAhRMnIHqzni3a7zetf/3oqlQpDQ0PZuZNPPpndd9+diy66KFvs/9d//Vfe/e53c8opp3DmmWeyYcMGPvaxj3HUUUfxu9/9jjlz5uxQed/3vvcRBAHnnHMOnU6HIAg4//zz+b//9/9y5pln8sxnPpPR0VFuuukmfvvb3/Lc5z53xrR+85vf0O12p/VAtT3l37JlC8cffzwveclLOOWUU7j66qv553/+Z/bff/9MXtkaP/7xj7nqqqt405vexLx58zIjx2c/+9n09/fz9re/Hd/3+cxnPsPRRx/NDTfcMMV79Ww477zz+OAHP8iLXvQijjvuOG6++WaOO+64KR5Etnd8PeSQQ7j00ku59dZb2W+//ba7XA6Hw+Fw7DSMw/E05fLLLzeA+fWvf50dO/300w1g1q9fX7r2wAMPNM1m02itS8fnzJljXvOa10ybfhRFZuPGjWbDhg3mgAMOMCeddFJ27rnPfa5ZunTplPQuvvhiA5jrr7/eGGPMb3/7WwOYL37xi2bDhg2lf2eeeaapVComjuMZn3HVqlVm2bJlW62Hz33ucwYwV1xxhTHGmOuvv94A5r3vfe+Ua9Nzafl+/vOfG8B89rOfLV0XhqEZHBw0a9asyY7df//9BjCXX355dmym+n7LW95iBgcHZyzz5s2bzYYNG8wb3vAGM2fOnNK5FStWmNNPPz37+4ADDjDHH3/8lPr74Q9/WHpuh8PhcPxpKY7D69evN57nmauuusqMjo6aWq1mPve5zxljbL/+whe+cMZ0ZhoT0vQvu+yyGcfK5z3veWbx4sVTxuMPfvCDpfEuLUdxfElZs2ZNabw78cQTzb777jtl3LnrrrsMYC688MKt1ks6Nvb+O/zww829995bKs+uu+465f7Zjnuvf/3rjed5ZmxsrHT/VVddNWW8fs973mN6xf5GozFtfTgcDofjqaE4bn784x83fX19ZnJy0hhjzMknn2yOOeYYY8z042Z6XUq32zX77befOfbYY7Njl156qQHMhg0bZizDhz/8YQOYq666Kjs2MTFhVq9evcPj5pe//GUjpTQ//elPS9d9+tOfNoD5+c9/PmN5ut2uWbBggTnwwANNp9PJjn/2s581wJOWjzHG3HrrrQYw5513Xun4K17xClOtVs3IyIgxxpjnPOc5Zv/99zftdju7RmttDj/8cLP77rtnx9L3eeSRR5ooikpppufuv//+7Ni+++5bep6U973vfabRaJi77rqrdPwd73iHUUqZBx54YKvP5XA4HH/NpP3tdP8qlUp2XarT7O/vn6LDTOdKr3zlK0vH165da5RS5l//9V9Lx2+55RbjeV7p+GzHzFQvu9tuu00Z25/xjGdsdd48E5dddpkBzC233LLD5V+zZo0BzJe+9KXsWKfTMYsWLTIvfelLt1kGwEgpza233lo6ftJJJ5kgCErz4EceecT09fWZo446Kjs23XzVmKnj6WOPPWY8zyvp6I0x5vzzzzdA6R1s7/j6i1/8wgDma1/72jaf1+FwOByOPydc6BbHXxzVapX58+eXjg0MDLBs2bIpbuAGBgbYsmVL9rfWmksvvZTdd9+dSqXCvHnzmD9/Pn/4wx8YGRnJrlu3bh2rVq2akl7RowbA3XffDcDpp5/O/PnzS/8uu+wyOp1OKd1e+vr6GBsb2+rzpuf7+vpKx3fdddet3pc+x3Tl9jyPlStXbvN+mL6+BwcHS/UK8J3vfIdnPetZVKtVhoaGmD9/Pp/61Ke2+vxg6/Daa6+dUn+pS8L169fPqpwOh8PheOpI++Urr7yS//zP/ySOY172spfNeP1sxoSXv/zlHHHEEZx55pksXLiQV7ziFVx11VUlN6vr1q1j9erVU8bjoteM7eXuu+/m1ltvnTLu7LHHHsDsxp1qtcp1113Hddddx4033siDDz7Iz3/+c3bbbbfSddON1bMd99atW8fixYtpNpul+5/IszscDofjT8Mpp5xCq9XiO9/5DmNjY3znO9+ZMWwLUPKCtWXLFkZGRnj2s5/Nb3/72+x4uiv3W9/61owhP/7rv/6LxYsXl8boer3O61//+h1+lq9//evsvffe7LXXXmzcuDH7d+yxxwJw/fXXz3jvTTfdxPr16zn77LNLoUbPOOMMBgYGnrR8APbZZx8OOuggvvrVr2bHJiYmuOaaazjhhBPo7+9n8+bN/PjHP+aUU05hbGwsy2PTpk0cd9xx3H333Tz88MOldF/3utehlJpdZU3D17/+dZ797GczODhYeq6/+7u/I45jbrzxxh1O2+FwOP5a+MQnPpHNv9J/3/ve96Zc99KXvnSKDjPl7LPPLv39n//5n2itOeWUU0r986JFi9h99923Oe5sjdNPP32KB+Y5c+Zw6623Zrrk2bJp0ybA6mKfSPmbzWbJ22MQBDzzmc/kvvvum1U51qxZwz777JP9HccxP/jBDzjppJNK8+DFixdz6qmn8rOf/YzR0dHtetYf/ehHRFHEG9/4xtLxN7/5zVOu3d7xNa2/Xs8wDofD4XD8ueNCtzj+4phJyTLTcVOIvXfRRRfx7ne/m7//+7/nfe97H0NDQ0gpeetb37pD8XHTe/7t3/6NAw88cNprehdoiuy99978/ve/54EHHmCXXXaZ9po//OEPACVhGthqyJYnk9kotX76059y4oknctRRR/HJT36SxYsX4/s+l19++bRxkotorXnuc5/L29/+9mnPpwtvDofD4di5nHrqqbzuda/jscce4/nPf/6MbmxnOybUajVuvPFGrr/+er773e9y7bXX8rWvfY1jjz2WH/zgB9u9qDJdzF+wCqhiWlpr9t9/fy655JJpr59NuDCl1IwxkotMN1a7cc/hcDj+8ikaSE5OTs7KQPLCCy/k97//PZ1OJzteHNte/vKXc9lll3HmmWfyjne8g+c85zm85CUv4WUve1kWmvSpMpC8/fbbZ1w425qBZLrxIA1VluL7/hTjyCeST8qrXvUqzjnnnCwM2ze/+U0mJyezsC333HMPxhje/e53Z6FJp8tn6dKl2d+z2WCxNe6++27+8Ic/PKHncjgcjr92nvnMZ3LooYdu87qt9dm95+6++26MMVPGqBTf97evkNsoxwUXXMCLX/xi9thjD/bbbz+OP/54XvOa13DAAQfMKs2ifhu2v/zTbZAcHBzM9M7boveZNmzYwOTk5LQyxt57743WmgcffLAUTm1bzLRhcWhoaIqhy/aOr2n9zaQ3cDgcDofjzxVn6OFwFLj66qs55phj+PznP186Pjw8zLx587K/V6xYwW233YYxpiQA3nPPPaX7Vq1aBUB/f/+sFnx6OeGEE/iP//gPvvSlL/Gud71ryvnR0VG+9a1vsddee00RcmfDihUrsnIfc8wx2fEoili7du2sJxPb4hvf+AbVapXvf//7VCqV7Pjll1++zXtXrVrF+Pj4DtWfw+FwOP50/K//9b8466yz+NWvfsXXvva1Ga/bnjFBSslznvMcnvOc53DJJZdw0UUX8c53vpPrr7+ev/u7v2PFihX88Y9/nDIe33nnnVPSGhwcZHh4eMrxdevWlRaTVq1axc0338xznvOcnaLkme24t2LFCn70ox8xPj5eMhqd7tmnwymwHA6HY+fiDCS3jycjn1e+8pW8/e1v58orr+Twww/nyiuvZHBwkBe84AVZHgDnnHMOxx133LRp9M67n+gGC2fg6XA4HH86ttZn957TWiOE4Hvf+960Y2hxDjbbMXNr5TjqqKO49957+da3vsUPfvADLrvsMi699FI+/elPc+aZZ85Y7rlz5wLW49eyZct2qPwwuw2SW+OJjIdbq78dZXvH19QzdVH/73A4HA7H0wFn6OFwFFBKTRFgv/71r/Pwww+XFDrHHXcc1113Hddccw0vfvGLAWi323zuc58r3XvIIYewatUqPvShD3HqqadOEaI3bNgwo2UxwMte9jL+9V//lfe///0cf/zxJet0rTVveMMb2LJlC5/85Cd36HkPPfRQ5s6dy+c+9zle+9rX4nm2S/jKV74yJfTKE0EphRCiJKCvXbuWb37zm9u895RTTuH888/n+9///hRl2/DwMM1mMyu3w+FwOHYezWaTT33qU6xdu5YXvehFM1432zFh8+bNDA0NlY6l3rHS3cwveMEL+MEPfsDVV1/NySefDMDk5CSf/exnp+S7atUqfvrTn9LtdjP38N/5znd48MEHS4Yep5xyCv/1X//F5z73uSmu7FutFlprGo3GNmpjx5ntuPeCF7yAz372s3zqU5/i3HPPBawi7GMf+9is8mk0GtMavjgcDofjT4MzkMw3Htx9991ZCBaAMAy5//77ecYznvGk5JOyZMkSjjnmGL7+9a/z7ne/m+uuu44zzjgjkwvS5/J9/0nfaDBTmd3GBofD4fjzZNWqVRhj2HXXXbdpdDfbMXNbDA0N8drXvpbXvva1jI+Pc9RRR3H++edv1dBjr732AuD+++9n//3336HyPxXMnz+fer0+rYxxxx13IKXMjDRTbxzDw8Mlw9fUg0dKccNi0YPIpk2bpuixt3d8vf/++wHrbcThcDgcjqcTcmcXwOH4c+KEE07gJz/5Ca997Wv53Oc+x1ve8hbOPvvsKUL5WWedxcqVK3nlK1/Jeeedx0c/+lHWrFlDtVoFciWOlJLLLrssc0V3/vnn87nPfY7zzz+fNWvW8Pd///dbLU8QBFx99dX09/dz5JFH8oY3vIHPf/7zXHzxxfzN3/wNV155JW9729t4xStesUPPGwQB559/Pr/+9a859thj+fjHP84555zD2972NlatWvWk7fZ94QtfyOTkJMcffzyf/vSnueCCCzjssMNm5YXk3HPP5eCDD+aEE07gda97HZ/+9Ke5+OKLOeOMM1i2bJlbpHI4HI4/I04//XTe8573bHU3z2zHhAsuuICDDz6Yd7/73Vx22WVcdNFFvP71r2fZsmUceeSRALzuda9j9erVnHbaabzjHe/gIx/5CEcddRT1en1KvmeeeSaPP/54lu+5557L6173usz7VsprXvMaXvCCF3D22Wfzyle+ko9//ON85CMf4Q1veAPLli3j9ttvfxJqamZmO+696EUv4ogjjuAd73gH//AP/8AnPvEJnve85zEyMjKrfA455BB++MMfcskll/DVr36V//7v/34Kn8rhcDgcvaQGkueff/6TZiDZy3QGko888ghXX311ds3WDCR/9atf0e12s2OpgWSRU045hYcffnjKpgewBpITExMzPtuhhx7K/Pnz+fSnP13K5wtf+MKUed4TyafIq171KtavX89ZZ51FGIZZ2BaABQsWcPTRR/OZz3yGRx99dMq9GzZsmFUe0zGTgeUpp5zCL3/5S77//e9POTc8PEwURTucp8PhcDh2nJe85CUopXjve987ZVOgMYZNmzZlf892zNwaxfTAygmrV68uhWybjkMOOYQgCLjpppt2uPxPBUopnve85/Gtb32LtWvXZscff/xxrrzySo488kj6+/uB3CP2jTfemF03MTHBF7/4xVKaz3nOc/A8j0996lOl4x//+Men5L+94+tvfvMbBgYGtiuUjMPhcDgcfw64bfAOR4F/+Zd/YWJigiuvvJKvfe1rHHzwwXz3u9/lHe94R+m6ZrPJj3/8Y9785jfzkY98hGazyWmnncbhhx/OS1/60szgA+Doo4/ml7/8Je973/v4+Mc/zvj4OIsWLeKwww7jrLPO2maZ9t57b26++Wbe//73c80113D55ZdTq9U49NBDueaaa7aqFJwNb3rTmzDGcPHFF3POOefwjGc8g2uuuYa3vOUtped4Ihx77LF8/vOf5/3vfz9vfetb2XXXXfnABz7A2rVrtxnrsV6vc8MNN3DRRRfx9a9/nS996Uv09/ezxx578N73vpeBgYEnpYwOh8Ph+NMw2zHhxBNPZO3atfz7v/87GzduZN68eaxZs6bU99frdX70ox/x5je/mY997GPU63Ve9apX8fznP5/jjz++lO9xxx3HxRdfzCWXXMJb3/pWDj30UL7zne/wtre9rXSdlJJvfvObXHrppXzpS1/i//2//0e9Xme33XbjH//xH5/y3VCzHfeklFxzzTW89a1v5YorrkAIwYknnsjFF1/MQQcdtM18LrnkEl7/+tfzrne9i1arxemnn85hhx32lD6bw+FwOMqcfvrp27zmhS98IZdccgnHH388p556KuvXr+cTn/gEq1evLo2bF1xwATfeeCMvfOELWbFiBevXr+eTn/zkFAPJj3/845x22mn85je/YfHixXz5y1+e0UDy6quv5vjjj+eUU07h3nvv5YorrpjWQPKqq67i7LPP5vrrr+eII44gjmPuuOMOrrrqKr7//e+XPFMW8X2fCy+8kLPOOotjjz2Wl7/85dx///1cfvnlUzZbPJF8irz0pS/ljW98I9/61rdYvnw5Rx11VOn8Jz7xCY488kj2339/Xve617Hbbrvx+OOP88tf/pKHHnqIm2++eZt5TMchhxzCpz71KS688EJWr17NggULOPbYYzn33HO55pprOOGEEzjjjDM45JBDmJiY4JZbbuHqq69m7dq1zo28w+FwbIPvfe973HHHHVOOH3744dvlUaPIqlWruPDCCznvvPNYu3YtJ510En19fdx///38v//3/3j961/POeecA8x+zNwa++yzD0cffTSHHHIIQ0ND3HTTTVx99dW86U1v2up91WqV5z3vefzwhz/kggsu2KHyP1VceOGFXHfddRx55JG88Y1vxPM8PvOZz9DpdPjgBz+YXfe85z2PXXbZhf/9v/835557Lkop/v3f/5358+fzwAMPZNctXLiQf/zHf+Tiiy/mxBNP5Pjjj+fmm2/me9/7HvPmzSttWNze8fW6667jRS96kQtx6nA4HI6nH8bhcDxpXHrppQYwDz300M4uyhMijmMzNDRkzjzzzJ1dFIfD4XA4tpvrr7/eAOb666/f2UVxOBwOh8MYY8zll19uAPPrX/96q9etWLHCvPCFLywd+/znP2923313U6lUzF577WUuv/xy8573vMcUVTo/+tGPzItf/GKzZMkSEwSBWbJkiXnlK19p7rrrrlJa69atMyeeeKKp1+tm3rx55h//8R/NtddeO+24efHFF5ulS5eaSqVijjjiCHPTTTeZNWvWmDVr1pSu63a75gMf+IDZd999TaVSMYODg+aQQw4x733ve83IyMg26+aTn/yk2XXXXU2lUjGHHnqoufHGG5+SfFJOPvlkA5i3v/3t056/9957zWmnnWYWLVpkfN83S5cuNSeccIK5+uqrs2u29j7Tc/fff3927LHHHjMvfOELTV9fnwFKzzY2NmbOO+88s3r1ahMEgZk3b545/PDDzYc+9CHT7XZn/VwOh8Px10ba38707/LLLzfGGHP//fcbwPzbv/3blDTS8XTDhg3T5vGNb3zDHHnkkabRaJhGo2H22msv8w//8A/mzjvvLF03mzEznad+/etfn5LPhRdeaJ75zGeaOXPmmFqtZvbaay/zr//6r7MaB/7zP//TCCHMAw88sEPlX7Nmjdl3332n3Hv66aebFStWbDN/wPzDP/zDtOd++9vfmuOOO840m01Tr9fNMcccY37xi19Mue43v/mNOeyww0wQBGaXXXYxl1xyybTjaRRF5t3vfrdZtGiRqdVq5thjjzW33367mTt3rjn77LNLac52fL399tsNYH74wx9u81kdDofD4fhzQxjT47vL4XDMilarVXJN3263Oeigg4jjmLvuumsnlmz7aLfbVCqVksXyF77wBV772tdyxRVXlFzZOhwOh8PxdOAnP/kJxxxzDNdffz1HH330zi6Ow+FwOBx/1rhx0+FwOByOpy9xHLPPPvtwyimn8L73vW9nF+dPzvDwMIODg1x44YW8853v3O773/rWt3LjjTfym9/8xnn0cDgcDsfTDhe6xeHYQV7ykpewyy67cOCBBzIyMsIVV1zBHXfcwVe+8pWdXbTt4le/+hX/9E//xMknn8zcuXP57W9/y+c//3n2228/Tj755J1dPIfD4XA4HA6Hw+FwOBwOh8PhcEyDUooLLriAN7zhDfzzP/8zzWZzZxfpKaN34yXAhz/8YYAdMlbdtGkTl112GVdddZUz8nA4HA7H0xJn6OFw7CDHHXccl112GV/5ylcyy+mvfvWrvPzlL9/ZRdsuVq5cyfLly/noRz/K5s2bGRoa4rTTTuP9738/QRDs7OI5HA6Hw+FwOBwOh8PhcDgcDodjBl7+8pc/7XTSO8LXvvY1vvCFL/CCF7yAZrPJz372M/7jP/6D5z3veRxxxBHbnd7cuXMZHx9/CkrqcDgcDsefBhe6xeFwOBwOh8PhcDgcDofjrxQXusXhcDgcDsfTgd/+9re8/e1v5/e//z2jo6MsXLiQl770pVx44YV/0Z5MHA6Hw+GYCWfo4XA4HA6Hw+FwOBwOh8PhcDgcDofD4XA4HA6Hw/E0Qe7sAjgcDofD4XA4HA6Hw+FwOBwOh8PhcDgcDofD4XA4Zocz9HA4HA6Hw+FwOBwOh8PhcDgcDofD4XA4HA6Hw+F4muAMPRwOh8PhcDgcDofD4XA4HA6Hw+FwOBwOh8PhcDieJnizvfCjn30bUazZtGmcMIwxSDDpWQMYDCAEgMAYwAggBmPYsHmMzSOTSOkjVYDyPDzfQwiJQNr7hAABQpg8WYT9XeRlEcn/TXKRNsmlJvnFxIBBIBCARuR3iTwVm6UpnRPZ45gss8CHgaZCAjK2x0yeZFLW/Pr8giQxYRAmyVGmR0V2n0gyNz1JgkAKgZSKvXffnRc97zj8WgVV85FCoagS6Yixzihr1z3ABz/wMR555DE2bd6CFLB6l8UsnDeXM155Krut3JX+BYMEtQoChUgqwhgYHt7I+MQo97e28HB7jHt/cydrf38P7dYkrckJupMTtMfHaNTrzBkYRCtJFEg2bRzm9tvuRQpJs9lkoNnPPiv2AhPz+IZ1GDR9Q3PxfZ9mNcDzK7BgX2r983j53/0tuy1dgKgohJJURRVfKAC01rzzPf8fl11+Oe867194yz/8Q9LCyN6kjruE4SRSgfLg4YfX86tf3kLfnAZ7H7SaB2/7I1/45/PYPD7OhvmL8Go1ls1byJJFS3jzP/wfFi1ZzmPtmK6GZs3D92T2+urYD2ODhnENfQrqEkLsP5Wcj5J/HuCTfw4iuSY0MIZ95RVAGIPoxmgh6PgSpKCaXFtL7msBcZKmMIaWhsiAkiCS631gMzAMDAD9QGzsdTWgkVRSWmdpvUlAA90kjyg57hfanTYwZpJnE/abGEiuGU3unQfUoph//78f4sff/A4HvuWN7H7Ky9jTk+zuST75yQ/zgfe/l2ajzkB/HyoKUd020g/wqg3COGSiM06kYyZ1yMIFSzn+eS+jG2lu/PWvkMZw5O57UasEPDQxRtto4r4BUB6N0VFUt0sHTYjhAS3YYgzViTH8dpvVQcBSz+P63/+RX9x6O0uXLGT50sWISg1ZbzARxwxHXRb1DbD/osW0ux02jAwjKxUaCxYSeB4DXgBhSGf944yFIb/phhgpOXhwkIHAp79WQwAPb1hPq9NhoNmk4gd0tCbSmvWPP8bY2CiLFi9haO48aE0iWpMYpUB6iMCHSoW21kzEMYExNI1GJ3U+GcVsmJjEk5KBShWpFMb3QRviyUlkHFOPY3QU8ejwCN1YM2fBPPxqha5URBjG162lu2Uz3pZRxGSLh6VkkxToyUl0u02zr06zr8H46AQjw2PUalX6+pq02x1GR8eQSRucM6fO6j0WMz7R4fY7HyWMYpDQ36xx5EGrAcF//3EtrW7E4sXzafQ3WLj/XjTmDLBUShoICDsYHbOl1mDSr7C8f4C5tTq/X3s3dz7yAMt23ZMlu+7OIiFYKgQD9Sbz++ewcfNG7n9wLesefZBf3HIT7fYk4xMjDDX6OXjlnjSrDebOmU+j3mTl0pVsGhnh0i9ezkOPPcbkRJd6vc7pp72SBQvm8+UrvsY9999HYz9BMB9WmxoLZIXdjngxC/Y4mPHrrmXy179kw/oWmza2OfCUF3Doa17CHQ/dxm/u+R+8Sh+15jzGRx5jw4O30nysxdLfD9NcsYzFp55AtdFkMKij/Ape/3yQHq884Qx2BCHKo0ClUkFKZ5PpeHqhtabb7WJS2cjhcDieAna0j3FjreMvATfWOhyOPwU72sf86pffQhtDa7JLrDVM0SFbLbJItFF5LlavO9nqMNkJEUIhhERKhVQy1eRSGsoLet2SYq70qyjkSvlao0vXmmICU9IpppjkbfK7wOrvqhVpS5oknemQezMXFPTH+fOIVB/ec2oaxXHxRpunlMwfGmKPVatRvkL4CoFA4qGNphN3GB4e4ec/+2/GxsaZnGwjhGFoTh/NWp0D99+fwTmDVJpVlKdynb0RGAztVotu2GFL1GIs7LL50Y0MP7aZKAwJwy5xFBJ1OgS+T7Vaw0iBVoLJiTYbN2xGIAiCgEqlwoKB+YBmfGIYIwyVWh0lFYGnkEpBYwFeUGO/VcsZ7GuAJxFS4OGhEgW7RvPj66/nN7/7HWuOPIrDDnumVdEn7UIARsfEcRchQUoYHZ3goQcfp1ILmLdoiNEN6/n9dT9ksttlst5E+h799T76+poc9jeH0+wfYDzUxAYCXyJl3gZ8rL51wkDXQEWAL63eVSfFkMLqW7UAaaweuPiKBfZ8J/k9XawRkcYIQSTthV5yv5dcFybNRybNKTIGnXwfaTpSQMtAW0A1KZ82tmx+8i9tm1nzFHlzjZOf6VeiCm3RYPXE6bMhoIotTweIhdWx+9rwuxt/zv133MWiZ/0NQ/vuwzwpGZKCX//PL/nZz35CEPhUKwEi1sg4QiiF9HxiowmjLtoYQhPTaPSz+6p9iLVh7SMPITCsGJqP5ylGux0iYzCVKgiB3+kidURkQAvDsBG0jcELu8goZK706FOC+x9dz4MbNtLfbNDf34fwPIQf0NWato5pVqosbDaJ4piJThuhFEGjiZKSqlQQa6KJcbpa80gcY4Rgca1GVUkqno8ARicmCOOIahDgKUWkDRrDxPg4nU6HZl8f9VodotD+E9L+UxI8j0gbukajDFSSfkwL6GrNZDdECkHFs+tsJPMa3Q0RRhMYg9GasVab2BiqjTrS84iFsOsEw1uIWy1ku4MIQ0aFpCXAhCEmiggqPkHg0+2EtNtdfN8jCHyiKKbT6WZrDtWqz9DcJt0wZuPGMWJtQEAl8Nhl8RAYwcPrtxDGmr6+Bn4loLlwHn61Sr8QBABxjEHT9gJCpegPqtR9n8eGN7FxbIT+wXn0zRmiiaBfQMUPaFSqTLYm2TIyzMj4KA88/jBRFNINO9T8CkvmzCXwAmrVOkFQYU7fAJOdDr/83e8YnRgn7Mb4vs+BB+5Po9Hg5pv/yObhLQQLQNVhyPg0pGJwl71ozF1M9957CB9+kMmJiMnJiEX77s6SZ+zNxtENPLL5IaRXxQ/qdNtjTIxuIBgL6X+sTTDQT98Be+IFAVXpI5VCVhogJPvv96yZOnaHw+GYFbM29LjvgU0AZGK10PRI1qWfufwqrZCaGhZg0FojtLY/hUEKbQ1HEsE/S0mUf06fU+G8kPaPRMg2xgry0iRGKBgwJhPu0x86FYRIFH/GFAwwwBj71EKA9EyPHUjyXCo5oNOkE+lb2uFOGIPA2KRFXktGGOLE7EMgEsHJ1leuhNRoHdLpTiI8g6r6SeaRrT8VIL0KfjWgWq8wJ2oS65iHN21iw/g43/jBD1m6ZAkvOuFYVqxYlrxDldWgCgIqpsE+A4Psq3xufEQzunaUcbkZoi5SVyCK0MDI+Aj1eo2hvkGoV5nXrGOMoBoEBFIw0R6zdS+tQKLjiFhApD2INf7oGFJ7RO02nSikHih8IcuuZYTgyOc9F3/xAg561rN63nky5RIC5XkIaeu13Wrz0IMPsjBeQF+twdzFy1iy5u+obNmMHh4h1ppWu8X4xDidiQniVosgqCKlRKm8zQpyIdaX1sAjE7DJhWnIhVtVuLc458oMPNJrBAjfTkXSeZxKrjOFe9KfIilDMf30eAVoJj+z87kdUWGKmf9dNPpQhXOy5/dA5MYsJD8VECTnVVIZ2veJqxUGPY/dlGRQ2q/BU4ogqKCUZ+tCClAKI+ykECHwlI+QiqqReMqj3W7TjXSiRDBEAqLEyMkzwh7XsX1fvpeVsRFp4lhbwydphd84CDAVBRWBqgZU6g1EECCCAK1jYk9S9X20EBgpkckEUugYYoEWMegYoyRSK5pe0p6NIY41YRwjhZ08K6UyIy3bSAR+4FOtVVGeZ+tbCvA8kNLWgcjfSN5u7HGdvEdfKaSwz621hliDMfbbFQItwEiJ8gN8zyClRAhhq9pApVJFNpuYyQ6mG2ZtQxd7z8yyLen3Cn8r7GSsJhWVao1OMsfAsw1P9ElEtYLQwtZfrO1zCklFeVQ9O+m2XZgPWqGkwk+eKdIaTyrqfgVfAGEXLRWhlHTDkFa7xWS7xWRrkk63a59LSgKvgqc8Iq3pxhHtbgcpPcZbk0y227ZvVbYujDF0Om1a7Um0jhHAQCDoq0nmCEVDKjwRYbodjIygAqoJfgT4MVG3g4hjAiHwgcAY6lIxUK1Rq8cETfDqYNBoHRFFIRpB3GmDnPXQulV832f33Xenr6/vSUnP4fhT0W63ufPOO5mcnNzZRXE4HI6t4sZax9MVN9Y6HI4/Z7aMtIBcl4Xo1VIlZxO9pzAFVWqiN7IkelRjMn2Rne8n9xY2CIpCstPRq0vOlc6SLOtCWTLTkEzRlxzNdMxJasmmQ5ElnhdAyMJzFR6rbBtS0CRaJRqJlijRGpXPp7kXkyhlawzGaOI4REiD8hINoNBJlSuEUMkGTEW1GthF4MkWk50ut997H319fey5x64MzOm3eRlJapQiPIXCZ361ygKp8MYNneEOXdECHVvNtvYxAtrdNoHvUwtqEHjUAx+DwFMKJQTduGOLLG1LMdpugtJGgjbITgehJTqKiLTGR6JSTXz2vIJddluFbDZYtGxZ9mqtGVFuUCOVytphFEWMjo7SNA0qfkCtr5++latQ7Ram1cZgCOOQbjck6nbR3dDqoIWwuq9C9ukygBLgF/SyqQ43JdP3Fl91z6sv6p8FgLIGQyo5kOqESZq+SNtVlrbI7yVX83nC6nSVKOuWS59K8Y9Cw0rLmT1X8UMyub67qM+Wic42NXIBMEqhPUVVSgalpJqWRUqU8pAiKZUUYGTyBdiMpFRgDB4CKSVRFBGbVMttDR6sPlUihUYnVihC2vUPJUBiCDQYnWwMFgKUxEgFnlW+C1/h+T4ohVAKX0qMFnhS2W9RCISUdtOyMaANRhhrLCbtduPAWN0vxmC0QZtk+7EUyKTfyrotI5BK4fkKKaV9p0JYQ43idcVNxGmXI/LmI6XMLjPJ2lf+/tM+S1jjGZOsOaXvzYDneYhKAFGMiXXWbkyxURR0xr1/SxKjISHwPJ9YpwUDAhCBQHiefQwlExssWxdKSnwpkMjsWYWx70cmpdDGIIXEV55tZzrGCElshNXTR1HyLySKY/tcQqCkQgqJxhAbbc9FEd3kevtK8/W3OLK6XWM0wkBFCSo+VIUgQCLREMe2L/VABCA1oAw6jhHaoIRdcVPG4AtJ1fPwAo0KQAb2/Rit0SLGxKDjKBuDHA6H44kw69WodscuFlZ8PxMcploSl8Xm1DOHSTrwssFGYnBhioJrQYQVJIJ7bpCRpSxKEnGWZ9ox50J/fms2Loo0z55ipwcKgrZJJKfMgD2RpkQmTRWun2YikXo3mZLHlAunnkvLbIoGMiZGG11+IAxCKKRUKOWhPB/f9xERjHc6RNrwyIb1aAGbR0eY2xqiHigCL3/19l5FPahRDerMafTR19dH1J1kclwRKzsBMEYTRRFaazwBvpRUKwFa5/XaCTuJrY1939pYoSb9Z6I2hC2iqEsUR5lBTVFMFsCChQvYI9yTgcE5hFGMlNa7Sf4iyaVFIIpixsbGGGj14UlJUK3RXLiQtvKotDuE3S5RGNLpdplotZlotzFBBaVkKltkpFbKgrIhhuj5ZygI2YV7igJ1aoQhwU6IkrFbTnN98e+0nRevK/5MhaheI49pm3LP38W0etNNJw69eaV1UfrklQTfo6IUTSEIsu9eoJTKLNxBJO1BZN+2NUqQKKOQCOI4Jo6t9x8SAV0naQmENdZKhVGRWM8L8GNjPZKkwpmUiQGER1D18QIf6XkI5SGkzLyvqESAtoYYsmTgZYw1qjBWMrSCfeYBx6ATi2QEiXGDfa5UkE+/p9TYwHrySYR0kdxoTPqoSRUlby7pM1Ih3SRlwqRegSCdthkBUkmkTju2fEInlUJ5PtpTxCo1NKOgB0kmKEJYQ++e/ktiJ6i+FEjlWUMYmUxoKxIRKFunAoRSCBVnfbwUAiXSerHvS0h7XCYNMX2XnrKGT0LrxNhFoLW27SERvOPESEMkEwAhZNavRHFMFCcCfRwlra3QL8QxURQl7wECJal61rjMS+tYx6QzX+mDqoCQOmmPGoVAJd+yJwSB5+F7CuVLhErfZWKQozUmKe8Txfd9qtUqjUbDLT45nnZ4nke1WiWKY/CqT9uJa9yZJA47O7sYDofjKUQIQb1ed2Ot42nHX8pY+0QxOiJsjReUNg6H48+BKLL6HR12wUBQs95Kp1D4dFMV6vRq1lSHnPyvqEIpqmdFQSNQUmDN0EcIECb3sJxosTMPFunvpqhpE4VCZrsAU912ISeRnZritCM7XzRUEaWDU2qg9NC9OuRMBS6SOjRYfwG9FibG6miETHRoCiVju6s/DtHGMDY5gRHQ6nSoRSG+lMjCq7N6JImvfDzlU/Wtdw4dh4RSorRES5npSYwxSAwKqwNK9YIYky3K5uVOy54Y9ugIdIjWsdW5FJ/bpLcJGs0Gc/U8qtUqsU4Xqgv6+J461LGh2+0SRRVrlOB5BM0GkZR4UUQcx+hYExf0TcbzEsOBsg65aK+TqCrztioKOmQx9Y3a9keuY8x/LTW1KY+QvYue5Ap5ZsUyEHW7hN0w04Om/yR2s2PpOXrQgFASVa1avXzx2USu885abXJOlsqaPIxSeEJao5PCGoAsLLZnyaevr/Az89ye6uAK336mbzYi++ZSTalIEpBoq4PM2lyir5YS5SVeg5KNqyLRYUqpMh109qqydanUAC3RCYvi2kVyRWr0UPwOsyc3mX68tNaV6o7tAkv+gMV7M6WyrTthspWs8hpaWqci1bHnz54ZtQmJFAojBab0MtNfRXZApMrpnidRiT44M4RJio8nrCFNot+3dWsK7b387jPjP5EYaqXGK+R6ZZHqyiW2nzN2M7ntb3T+vhM9dWosmLabOE76k/JD5u0qqXAlJF6yHpWuhRqj00aLUAbpgRAak9xn4xakBk9Wj62SdQyRvJysf8NQ9CjlcDgcT4RZG3rUKx1AIkTi0yCVUjMJpEDxWHEwSgeVfFTFCEGcDLoy6ezsQJl2tKLQ+dtBMUoOZAJGJkaJbLAuh2TJnQEKck8faQHtIJGWNR1EgEQotsXwshRyAcwg0oEhLqZZrJOCSCZy92mp4C2QiYcEkw3SplBmkZbaCNIYNXa8N4AVXgMpCVRA0JhD0OgSRwYVdomNHWjWP/YwY2Ob+f7/LOKWxx/n2AMOYeXCxdmL8pUHfoAnre+GFSuXQCXmtltuZWJsE9ajiLbGEi1r0TzeaoESLFo2n4nJNo89voXJbodOFOJ7HvX+KkpJwrCLjiWe5xFrgxCP0VVjjE48yvCYT7W6CD9Q9JjesOey5SyfP4/xMOaO9Y8xv9nHwr6+5Dqd/GcyW4/x8XHuvedupNTIGJq1JitX70l9YD3D42OMj46yYWSEmM3c8MfbWDw8zoEHH8icYGBK842Tf4nhacnwoTgt7Z2ilgSo5O+g53hKUQ1X/FR6rao9yrJcel9A7nUjNUbRhfPTCeiZ4NuTh+y5JqDgmKaQflDID8BrNqnMnUu9XqNPCSpJw1ZK4fuB9XYBtsFKBSI1rkgMQTB2UqkkrXaLMNJIA1LILCyOkjLz6GGMsUYFQuApiRFQiwyxNMSJgYfwPHQQMLhgPqv0KgYaA1RqdWs57PnW4EHHVHyfOPmYlPKsu26tMcREQlrDA6mQChrppN8YYmMyjx4kk9usvgUgJV7gU9FVpLLSsRHWatr2PklPlAh0ReOctL6lFPiJtbpJ+pe0nxEChBRoI9BIpOejjMkMQ4QxSAO+HyCrNaJ6HbRBdTqoMMwmcGliSgkqAXg9jTlQMK8iadQ8KpUqfhzjD3gI4eHPG6RRr+PV6hht8AaaeJ0OwrPvJpCSilKkfnqM8MAY2y6kRGCI4xhPKmpBlUBIZBhilCEEOmGXVlsy2W4x0Zqg2+3YUDJSYZJ2FcUxnTBistNCIxgZH2dsYsLK+ek7MYZ2p8Vka4I4UR40/BpzKhUaskJVVRDGoNttOyGr1PCbIXXRRvoR3U4LE8cEQuEjCYwB6dEMmgQVQ1Adw/ODZEIREdK1b7jbBjGNAms7CIKAPfbYg2azSb1ef0JpORw7g0qlwp577kksA1h5BNSHdnaRdogHfvVtHrvlhp1dDIfD4XA4pvCXMtY+USY2PMhdP7iccHJ0ZxfF4XAU8L2YzvgEt1//K8J2h72PfjZ98+dRUHSWfxbRBX1zqufNdMhWp5Qn06P90sUFdXulLhgE5OkWshWUFobzleUkD5N6hsgXYotrsmXP0Qa7Uprogwqr7iK5FrDGJb3PbhVPeT7ZrSLTIZMuWycrtIK03D1eLlLlskmfO9HGCbvArqRCBTVUqDEaRBzjYfXS4+OjdDot7nm4Sd/EOLsuXMJgs5klrqT19Zt6YBiY08cunmHD4+t5vNsiXfyO45goionimG4UgRQ0Bxp0w5Dx8TYijom1tkYjVQ8pBHEcYbQgkhIpDUTjSNGl0x2n3VV4vkCpoOcFwtyBAfrrdbpas3F8jEZQpVEJsvdiMCVDi263y+bNmxK9viDwAuYMzcOvTNDuduh2Oky0xxlHsHb9BvraXRYtXkxVVcrtzeTr8EJYD7tlw4RCe+tZ55+ylGJy7xil4z3XFiMVFVdFoKzfLR5/9A+38tCtd2YL0EnRMz33TEYe6fHmvCH2OvbZqFqtlD/GLvCXln5Enm6en0BWArxaDd/3qEiRey+RMtlcVtC+FzxamERPbIRJ1tcFURTaNQaT6EjJNwsWvrwkhIlJDDUMvgYjNDrd/CYlRilqzTpDZpBKUEX5gS1LUp7AaJSUyaZQaxyVbRYk8dhhDOlmuiD1zIHVS8aJdwjbl6U9U15ZUimU8fJzwm6YS/XnSceRvc+sTRVsQlTeWSVt0RTOC+vRGnKPHrKwjoax9e97aN8HY5BRjNS6bEObbBT0lCjuuwXsPtC6Evh+4p3F18iq1YuqepXA95F+YNOuBsgoSgxqQAmBJ9L4Afmz2U2E9hqjrUcPT3koIRCxxkiItbQePYT15tGNQqv/xUYkQNrQX1prIqGRsTV26oQhnTDM1t8Q9l1FUUgYKrS2BjiB8qh6ikB4eOm6YBTZ96I8lB/jEyebBSNMulkQkaydSIwKUB4o388801g9sg2NLuKIqV+uw+FwbD+zNvRQMjHAAKaaIueDQ0F0niIoiNTQofAz3cU9lbLUXxwkTSLJmsI12YBYNCycVvDpsRTM7rcDR5puNmaXniQ35ihaHE990J6fBdGyuNt8ujKkfxcFucwGJRG68zq26UlhQ0j4lSp+pUbo2x0tnvSIiWi3WsQ64pH1G4iDCpN7dAr5UtopD4JGs86CBUM82N/E8z3i2Eeprl1MT6wbO90QBNTqFSKtE6MSQ6fTQZuYqqggRRqmB7srXwti3SaOJZOT44xPjBMOhrk1ZIFmrUazVqE7PMLmVpso2SVfqotMmLQeISYnJ+i02wgEvuczMDiHTrdD4AdIpYhjTafbZf2WLch6H1EUZQJo79wqpejsYKY3Nx1pyyzeX/xser+Ropw808/ivUVPIUWBvjTXnKZMs3mOYjrFurFu9/Lpq/R9vFoNz1OlkDYiaY9CFO5OhGiT/J6GClHSCl9xFBPHOssvFdIRwhp/QO7RIxG4BaCSyYEQgthaQWCkolKr0t/fRy2ooTwPlAdS4SX9R+bRQ5CFPUk9Mxijs3IiJb40mZcXEk8SmR+aVCAs9EU2dqwVJm2ZScLW9Bh6mLx+MwE+eRu5lbzJ/015l9bQpBQzNxXkk7AysecjfB8ZhonVet4p2l0Y1mhGSlGamCkpqASKIPCQXuLSs+KBFATVKn61ao1ntMGr+CijM/eVuaVz4elEaqWe13Pudk9YQxZpvf7E2nrhiKKw4NEjsaCW0rrdM4ZYW48eYWQ99YRhlLfmZCIUZW737PvxpEdF+XgqQEnP6kbiOBPSpa/wKgIhDVpHGK1RQmQW2Z7Id61I39ZNqsTQOrZ9aByTBUjdQaSUVKtVarVaZrjicDydkFLa3fFBA5bsBn2LdnaRthtjDPWhm/BrO77L3+iYqGOVndtCVWrIacI+xd02Og6zv2UaNmwG0h0qTyV/DmVwOByOv3b+EsbaJwOpPILGnCnzpe0iDsH8eYxbQRDj+5puVxKGszced2Ov488NmYQzaI+O0Z1sE0dT26dVq05j6VHUjRbVSqQLn3lQk6lM1SHnytbkaM9Cdc+t2e/ZRkIo6K1zfWwhckSParhH+1YswrQ6ZJNbCmQ3lIsznUJP9F4DpN5p0x3slG7LNElZuAylPHS6GB5JjNBEodWFjE1MYpRHODeiTNFrgSAIfBqNKiOVwOpssh39OtP/xLHV+/q+QpvE34gxiDhCIfFQ1mAiU4Gl+rkIYwRh2KUbdtC6xhTjHiDwPAJPEbfbtKIIbRIdck/IoMynuNGE3dB6mgaUVFSqVaIoQmWLw4YojphotxF+xS7Mip76TtcOCqrPGRHkEYx6liUy/Wsh/Sy8j5jaDorNWlC4rjd/Y7+GaLJFa8uWTI9cLMbW9NopyvcIJ1tkBkUFdOF6IUAGQeLVgWxsNqSGPxFRp0M02UIGHp7nJ6pXOTXdWBN3Qqz3gyTQvQRpBO2JSbQ2dFttpBB0ai1iz7OeVwzEiRGBMSCtpQhAZnhkwi46ioilAt9HeT6VSmB1lFImrlkkRBFxt0OkYrpxEp4l9cxg8nWazAwjCR2Ta86TUOSZelSUFe6GTM+decGm9L/sfac65DRlI/KEyoZneb33IkqNqdCnJfp0pEyMI7TtRUsLE4nHbZnolgtZCAFKCes1XSa6W5UYcnie9bSd6K+lkgijsrQLe8GT8ovsY0jbkEnW/VQWosaOL0YI60Fe68zrj/WEn3g5Eal38dS4wqCFNUDTcY+HICBOvIKkx6WQqMSLfuo1xVoOAsJ6eZbpsGK0DTeVacNNYqxiw/KI5F/6kkz6DNqAcF49HA7HE2fWhh6dqIpAWHf3hQ7Y6DTGH0yVeLAdYGJlCWSLp0LajjJ33TRVwJhuadMOQEnHWBi47KBnO8Zsua84ITA21MF0Ekxq3SwSC0+MRCMSV1CxtRZMhEGZrNan/Xo2tcjWFstSWz4IF6SxnqfMBM1koBTkdWJvMxhtQxlorZEiXXa0hh5KKqrVKkt3XYbXqPDIPV06E5M2tlgY0p0cI2pHPHTzfYw/OMLE/n8DK9L8pV3wFHaBGiRzGv3UKz6PLHiMuQsWMzYyTBhGGG3wg4Aoiti4YSP1epX58+chYkNfrWoF98StRFfGxMKgI41CojoROrYL7C063Py7u1l7/xbqf9dHo97AU2VjD5HY/s5v9tFfrVDxgqy2it4m0leqlKRaCwgq1tdFs1HlGfvswUMDDW7+zU0oIQl860Vi+MEH8bsR4bP+ptTGeud5WxN4eykJW1u5Lj23tdAtxRbSG0aFwvFeI5T0X6940DuP7PX60Zt/b169ZQmBLiCbDerzh5CVCmGk8ZRASxBSWuMamRgviYKQLGz7VsrDWi7b9ttqtYi0RiYCfohBZYKcdZ9mjEFJiSQJmQFUhEBLQVdKosQCOfZ9+vrnsFSlNrQKIyVGKDQGz2h85SXfsJ3cCikhttbKUTYbsIJ2DZFMoqyVeJhYB1trZoVOzPdTN3ie5wGVLL6iTq3Ek9o0kLmIS631E2c9tp6FwPcUJtZZOBtpdEkgN0JipEH6nvVSUogRKo0Bz8NQwWs2QClUFCG7XWucUQ3At8/sVyoI+jCpn5akEF69Rt/yeVT7+giqNepSsmDhQrSQVPr7qVUqBNUaOjYMNJrWeEJbQx1fSOulIzEcE0nCnrQW+hK7+Bl4ika1SkVKpLaxCbsCpDaoKGa8Nclka4Jut5vFVhTKuk0MdQxxiGi3CSNN4I8w3mrbuI1JLBptDK3WJBMTKpu81/wqzUqTqqzgSx+hNbozaWsuqOGrEGoaGUi6nRbEEYH08ITAx7o4xavh1SK8uXVkf2AnFXFEiEZog5Etnqjr7G63y1133UW1WmX16tU0m80nlJ7D4dgxlhx4LEO7HbDD909seJB7fnQFYWtsq9epoMpua17BwNLdS8eN1qz75bfYeNevs2OLFi1iyZIlM6a1efNm7r///rIR4JPM0qVLWbhw4YznN2zYwLp1656y/B0Oh8PhSKnPXcK+L35zyShyuzAGHvkdbF77pJZrR5DScOyx69h3343ccMNSfv/7mcfaXoaHh7nvvvsKrsgdjp1LpD1UtY+9jz0KExuaQ4P2RFFnWjJuSND2mtLRbMEuCQdQ0FwVl50NFBRaRc2amKoYSxdpi4cznWx6nq0oBhNv1cYqg6x2NtH6ZDpkMSXqd+/iaFa+6Uj0TOVjBT149kyinJYBknAG6Yapoo461Vv1DfYjA8WoiYnDEB3bRc447KAjzejjW+iOtAkXLoE5efqZd4VE51MNKvieYqwxQa3RpNtp20VUDLHy0FozMTGB73s0Gg0w1jAj3QCFgFgk/r219cItIo1KF5TDmMce3cTwcAt/t4r1YNsTPiLVkTeCChXPwyvEminqabPAFVLg+SoxXpcEgc+i+XMZrfo8/ugjVhep7KJye2QEFWviqDwHS22UMofnvUrWwmJ+ecF8hnc8XTMopr01JbUo/eixABIs338f5q1YPisdd++nIoD2+Dh3XP9Tom443SNkeL7PHkc+i4HFCzMvFhqIjOaBP97BH274KRP3P8j6Fbuw6zP2Y8UBe4OQiXGNyXStCMmWhx7m3l/dhI7jLBchBX5QoW9gPtoYRsdGEVIxd2jIhgVKQgWlHiy8ZONWqtBuhxFRrInDLlrH7P23z6S+3z5UKlX6hLDtSKQbkiUb71/Hvf/zGyQCXynmLF3Mrs86xG7QSNqvTltYYqXjk3r0SPS/aTvHesIwRqAL3Z/VYXqZ8YRJ6iDTIRf6qt4Nnmku1ku1DTWebuMr9Y1JByGU9bJcai+p/tvzMH4AiZdrEcdWV+6pTD8uPYUnKtbipvDype9TGajjBQHK9/GFDadkEHiVCp7noTwfYwzVIMCTsfUsYhLPHdk6WPp0JttAKMB6qpY2lLZCIIwGI623lNggtaEbRYRhN/PoLEm9r0hiY0BriEK0NijVphtGyTtItdbWo0c3lNZYBPCkR+AFeMKz3kWMwcShrTnPR0qN74HwBHEcgtE2TIsQmScbT3pITyPrPqJqPdobbYiJEcZgCKeOgw6Hw7EDzNrQQxuZDVK5QWyPxCqy/2V/FkTQkkyS7ugXacctcjdz9j5TTscUs5m+AywL6UnuJh320rKmYV16y5pcn1pQGoG1qBM9loqmeDUgMgvhHkPhUsmmVFMiA+R2nnYCkD1bdnFy3uSxDbMyZSWwQnr/nH5a3Q6bqlXiMLKDaGzd8Ok4ZnLLGF6siDphsSSU4sEJCPwA3xc0G036+vsJO53MGtN6xojotDsEvoeSVtipBD5hGBGFVphPBR1lsOERtLaThlgTyZjNm0bodAStVhutY4zMRe+iK7Oq71H1c7eH6Xs2+auwtZdMVFIh3fN8hgYHmBgfw/OseyyVWKm3x0aZrNaJoyibJImtDKpFGX264zMxnUy/tft7W2Xx52zu7823N93pKObRa4Qy07UaG9rGr1Vp9vcjlKLT6eBXfIz0EEImnhdMWVBPPm6R5GKNhW2/EsWRdbuXtO2iRw+RtKHeyT1YF4EeEKXeIoQEpfCDCnUdE8dWltNCYISyRhGIzAgj9eiRufDRGi1sG07bhCdkweg62XWQ1klBIMyeTOYeTbKFNpGL2lksPpH2LSa7PxVilRDEaceX9T/F3tT+k1JYo7SkdFl7k9a4RPo+MtZIpeyEQApIXCIKYV0Een5g5d04qW8pUYFP0NfEb9SQnodnNPVaAyMEQaVKNQiQng9CUwkCO4nvdkknLiqZIOUeRKyrxNTi3Bgb6zBQVliWWmNk4k4P6GpDGNpYqFZIT96vtAJz6tEjxLq4a3c7dLqdTBGTZmvd7oUYnRrFefgqQEkfKa1LQhPZ/lAoD6kCPAJQqZBuUEJYrx7GxpTV0kP5HrLqIwJFqkDRBgSxVTI/wdAtWmtGR0dpt9tEUe/uGYfD8adACEF97hLqc2c2qtgWKqjh1/vR8da/Y7/aoH/JaoZ2LRuVGB2z4Y7/RgW1pFDQ6OtncHBwRrklDEM8z3vKFnqEEDSbTYaGZg4R0G638VLl7dMQtyPa4XA4nj54lTpzdtl7+280BnQMOoJoPbDzQ79Iqdl778c47DB48ME6Dzww+3A8cRzbcLl/IWNYrvtyPF0xRiA9n4HFi1LNY+EkTOvJo3RZr8eOoj4pnfOnepDpPXxM1SFP36by66axwigWs/C7KFxn0ntNrpfJE+55TpHrp0Xx/AwGAMW0ejbRZ/ru8sW5DtkaTaQ65EIRsN5dK9UKURxZuV1ruwNfG2IDRmvCyQ5SC3Sk81Vp0uLmOj6lFFIJgiCgUqmg49jqpLT1fmAiiKMYpWSiL5J4ShHrGB2nj2I39QmThutIvO1qG3ai1eoQx8J6GzGaogVN/qqsx1pPpVpUk1RNrm8u6tGt9xF7rZSSWq1Ct1vJvP7KRH8VdTuEbd9udE3eWRruofR6e9pGrwHHtLO3QhpF9d+Ua2doH8W/Cw4eyh5kgMbQHBpDc6YrwVR6myww8ujjjG/aQnd8Yqu3+tUKUbdTcE5jiKKYbhgyuWWYscfWs7nWwI80C1Ysy9JPPb8jcv1v2O4w8vh6TOoNSFidpucFRBMR2sD4xITVwXZsGHn7jowNWy2ENfRI3xXQCSPCKKbbbhFHIe399gFpw4sHvm834ZlEd5uUYezxDVZPKxV+o56UF1KX8mlobvsuE5OjrE32+J/JKyarZKvrTL/k1MN8vi6Sf9eFNlf45q1RQxrxKv8ujNHoMLRKcWM9EMWJ9xGV6FmF74GQWXsWKtGbp54zkrKl60VCSqRRVoRK+oTUWEUFATLws1A8vueDENZDdBqax9iw3kYb6w2Zguf/rE8p6MvJde4SkRlRiIJHbo01+NCxth45so2Sed9nsOtvwi6QEcX2X94AbZ3pOEbHcdZvZh49hESIxKOztoZHQkgbCkdZ7yRW/2Ky9U1rxAJGSGtg4ykb4yZpFSZ5j9ZbzfS6HYfD4dgeZm3oUZFdEAIpKoCk1z1G2iHnR9KBLhmwpEwsF21nboS04RSgJIGksnrZlEJk67Dp9Ta3xHVXNo4VBPFsKbQgCCeDYLb2Wsw6O5IvlqYjarognLrTyxZqs3vsxUVZSCf3y+I4nF4v8prKzxWumEZ5rzW0uxo/jLE+S9KFRDsYNqt1Dt5nXzYs3ERr0yibK5vRYUhHCqJuFR1F1KqCelXjKSj5dUgsVdOS25qTLF+6iGf/7cHcetttbNr4MMZ41HQNKQRhNySODRs2jyCEZMGCubTbXR59ZBN0NWJCo1RiuagkOo6I0cTaR8SGOBoh6kaMt0YYmRhHNar4vbEOgTyqX1EoT96DtkY2Rhqkp6g3m1Rrtax+PXwCr0p9znzqXU11ZDPdbofHNz1Cx3SZ7LYJTWol+uQNqzOls630t3Z+JiOQJ5JeKkqkYWBmq0ZRWK8Nz3rmoeyzx2oe3riZ62+4kf333J19Vu+GEMlCv8DaMacCW3GykdS4zIw27LcspY25V6nWCCoVOuPjiZBmDUJyV2c2ISUlnrTCnhYK6XlIz8cLqlSMoBtGhGGEFAIjZRYjzxqTFJRHqTEJxQUeW6ZAJq3OaGIDOjaZkIsQibCYJiKSsC3JhDYRpm2/lliGa2sYICAL0ZLGjJXCxlYU0locxySzjMRzUmosgpTW6FpIa52enUwCxCjrLcmr1ZFegBoeQWLjCwrATzyqeH6ACgI6nYiw1SFoBAwODjEwZ4D6vIX4lQCvWqPqBcwbsllI38f3fPzAevGpV2tIA604spP8ZDKVuf5LZpup+04Swy/f82hWa3hKobTGRBGdLCSLYbw1wWR7kjCyHj2EUqjEE1QYR8Sxpms0UoR0QkOr3SXW2raRQIKCVmcSbwJibctWUQE1v0YgA5TwIIrQrQnbDoIKypNIvwZeQKc1gY5CAumjhLQeZqRA+gGyWkMO9SMadYzWxFFI1wgQMUYrO745HI6/eupDi9n7hLPR0dZ3GQup6Fu4croTLD3kecxdfVCe5sSDiMmHZ0xrYGCA/fbbb0eLPCsajcZWzw8ODrL//vs/pWV4qmi1Wtx33310u92dXRSHw+FwPJUYDY/+AUYegsmNO7s0T5j+/n7222+/vwjjiDiOWbt2LaOjO9/4xrHjeCJOFusSjVOP3rb4/5yC5ivRFRmwChNpd3Dnt6Up5DrW7O58dTQ5kOuai4qvsp7N9BwvaHhN8bopNxY0yVbLljh9tZsMTaot7kkz+0tMl+SUMojpHqB4TU9VGiOItN3pnmv/8hwCL2Dx/PlMNpuEkx1a7RYm1kSii9Z2wdzzwfcMNtqAKOfXowvHCPr7muyyfDEbNmxgcmIUoyS+8Ymw4baNgYmWDbfdaNSI4pix0RYmNnhduzlIJrokY2K0FhijMBqMtl5CulGHTreLDHwbYn6K/ryoP4bcICQP/y6ESTxDBNYjr0jvVHZzULWBH4PXbhHHEeOTY8Qmtnoock8JhWY4O6a14CgtieTXFIw+pqX3lRf/KBiBbLV407TjKWVM/q4PzmG/445FR1FxXXwKUkr658/Pb481D9z0e9ave4hqFLP/fvsyOtli7bp1LB/eP1l2SRb70684+V7nLFvMQS86rrT+IqXA833qfYNoAxOTLZRUzJ03D+Up4m7XGjgllWqNi/L22o1CojDknv/+DY/fc3+iY1ZIZVBG2M1/yYYJIQQLdt2F2kkvSLIXVOp1pFdYSjMGXQpeYzck2gpKjSsofTLZ6lH66UppvccnLzyr13RjYaZXzjckps7irbo18YghdO5E3hjao2Pc/fP/pjM2YXMtpC2EQAUeux12KAOLFySLVwrpW92EbHewm+UkAi/ZOGu9WkupiGKNjiKUr6hW61SqFfxGA6ms5w6Eol635RBJOBylPLQx+J6PMNbLC8JkobJzS5/Eg326lpAYp0glCfCtgVaiJ4+RGBPZMD5hlzAKk7DaYHX/IIS0BiAIYmMQQhPrScIwshs5hbBewwWEcYgMyUIFKanwlYcSni2l1pgwtPXoKaSsYKQH0iOOupi46NHDtkOhPISnEbUKwrdeTdAxcbrB3ORh3h0Oh+OJMGtDDyViEhtB2wGlgkfv0nNZ3isJKqnxhnVble9qLxp0FMmFp6LUkQu5xePpYqpN0maYCgOmIIhlpIJPr1xYEOAT/wLZXyYR2EkXX6fph41I/zclySnPUMypLCaJ4pgPWFdfUWyIdW61CDJLz/d8Fs2bhycV/QMDdLpdxisBcRSivGRx17P/ilaRqdCbCVRZYBRBX1+T5XIRjz76EMqXeFqhI484scY0xjDZ6hBUAvr7m9kEzmiDDEEaEJXEMjSJO2ZMarnYRWtJt9ui3WkR16aL19k73UqErZ5pksF6NvATF2G5kC5Q0qdSb1CtNfCCgCgKmWiN403YEDTa5ALgDDL3tPS+wel+39Z9vRO5HUlje5lN/ttKQWAF1yWLFrF00UIe/fmvePCBh9hlUe5aNnVVmU2oyWW2KZmL/ID1AiFRnofyrDFC+fsReULJJyhFamBsvX0gpRU+lY+MDcg4M7wQ5O0qjQuaS9smM+jIJk0iN4FKLZ9zm47UMriQSnKcRAjO+iAjyn1WYS5usj/TSadtu2mvlfViJrdETneByMSgILHxIFObCAFSIX0fhLWmtuFPBKAyLyap9xEZJUKs7+H1+1Sadfx63b4D6SE9QbVaS5QV1nuO9DyMiPE9j1h5tEXaX+fvw1a4ILXGTvtabTRKWLd7UgikNhhhiHWMiWPiMKYbWSE91nFuES1tOlZIN5jYINCE4SSdbmjdkkqB9Kygbt3udQGDUtaIyFMeUnpI4SVCesfWm/IgkMjAx0hFFIUYrW24IGEnEtbYyNarqFURQWDbixHEydxOEzKzXxyH46+M4m5ZIXmiYY2ebvi1JnNXHbTD9wsh6Fu0K32LdrUHjIEHYtiKoUe1WqVare5wnk8GtVqNWq22U8uwo4yPj/PQQw85b0o7gAsX4HDsJP7Kx9odx8DkJhh50P4plTWun3lZ7U9CHAvCUKH19s3SK5UKlcp0G2eefkRRxKOPPpq4sy9jUj1iD0qB59kNwr1D+HTpPF14Oo+tQiQ6yx7NU96yS8pishXO7IJER2RM5kW5qN2dTs+bqZYKuomCwiXT8RQNQkqtKdNRT/+3Se4p67WKB0Tpb1N84ExpXaqOPP9ehaToTbd4Uc83MJ1u2phkI3/PRsWkEqSUNOt1pBBUqlViHdP1FFqrRK9mN5+rLJ50tgiQ1XHqtzYtVqXiMyCajI+NIpXAIDE6CcGcbIQKwxjlKSqVCiKMgJZNNonmLbyy59s0bIUhxpiQOA6J4jAJrTDN+yfRihlT0HeXvSqkei2lVLJJyl5ldVkK5fvWM7RSaB3TDbtITyWehih4/C22uanvoJjhFH3oTNf3vPKez2H7FcYzGG5k185yyPOrFebuuoutozSp4nc1Q14GGN+4ic3rHqQiFQsXLWJ87TpGhkdpdzrZhdPp1WvNBrW+ZIOBST1HCJQf0OibgzaCick2SknmLViApxRhp4PW6foVKE9lG+zAer8Mw5BH77rHeuqV9v1bnbFMvIkkrUEI6gP9NAb6Sc0zjMF6o0gqoLBVuKz7Jm23yXmTb4Aka495Z1T2Fp0cy/qyvBMTWbplHTLYNZhiRUbdkC0PP8rE5mGmw6tUWH7AvnmtC5E4J7bfqo6iLPyTFtazd+p9RMcRcRghPIEMlPUAn3wzCOvB2/P8rNwy2bQpkv7ASEnRZChVH2f/6zHOSz16kHgaEQaMMOhkrUlrTWxi6yVI52sRWQ6Jztm6PTHEMVmodCAzDgk7HYSxmzOt4ZlMNqiKbOMiOkoey4apl57Vr2utEz197q07bRBCJkKKp7K1B9uYJEY6jx4Oh+PJYdaGHp1ODELj+YG1frXL6/kFRaElO5D8JoqDtr3QpIugWicKCdDS0BNmD0gNLuxvdgAQ2fEsRQHapANceZAtlic3xDDpWNsjWSf9fCawpyFnSja7+Twk77lLEweRSjS9A36PJFUSZgqSnylcJcCGPOmGRGFsq6ywaGoHdomnAvqa/fzNoQezefNmftppsWnDBjrtSeIueIGPF3jJRLcojJQlzvRJa5U6vlIsWLSYJatXMbZ5hE2PbEAbQ1CtEkUxYSvElz61ag0lPebOm4MxUG/0I4Qg6rYxRhPFII21/vSUT6XSIKhUefyRR9FxRGPvJv21AbZNEtRDaJBxdgTh4/v9eF4NTZQstkJQUey12zIGGz4jGx4g1pr2cAtvspMs5EYY4WOEmCbWXVojZbZn+J3NtduaE8w2vzSdKZ/iDGmmPmGmmy9s7f7Ux0p6jeyCnAAR5vdm1tjFeEaJQAgkGwpE4qzCxhHUqZEEYOIYE0cIYZDCWvoak8YmzEuXBYRKhUCt0XFkhT0oWLHbazD5RDed60qZf3PFVFMrYpMIYTbcCbktVPFqA8bE5faThmcp1Wi5NeUBXazXkvS2zN1catmRuuRDgjB5jMr0W07LmAnDwt7jYV0bBh6eryDSYLR9DSUDDFu+SrXC4NAQtWqV8TBE6hiRCL+ZO7l0Li8VGIkU1qKb5P1IsNbVeWcIhVcP9l1LKfBTF3hgXYMaQ9RuEU5OMDIxSqfbIo51EuIn7asgjGO0gbCriSPNxESXKIyJtcb3fRbMHcTzrCGZIWTFrkMIBpk31E/Vq+BJH4nEhB3iTozRGuFXEFWFrCm0lLRbo2hiAuXbtpzMYpUKEL6AhsD4SXiEzC1qhA6dkO5wZMQdeOB/oNoHSw6CxtydXSKHY6tUq1V23333vxjX938q4jhm3bp1jI+P7+yiOBx/fbixdscQEhbtD4Mr8mPrb4ct63ZakbQW/OIXS7nrriEefLBvp5VjZyOlZOXKlSxevLh03BjDww8/zObNm6fcs2YNvPjF8LOfwdVXZ2s3DAwMsHz58qelsUe322Xt2rW02+2dXZQdIo7s6n22kApMmSeXdt0VtcYFIw6R6pBTFUu6u13khhTTKPFKWp5pdMiQL9jn+U81oCgdSRf5TfG4yM5lR0y+bTDV12SJ9TxyZs+RZV/QIfdsjkzrpqzDy9MtJm+MScIQJPXV4/lCCKufrQRVli5ZTKvVYl0UYQTEUYiOI7thSBVC8ibPkqndRV6rxtiQGlJKGs0++oaG6LTatMYmMYCKfRvSO4qRUuJ7HlJI6vUqBvCDaqL7juxCtiYJSZzqkQOU5zE+Oo7RGn9+hao/C+P21OCjEL7FthuJVBWk9O1itvWni1KCeYMD1HxFZ3LEbrpst5BhnOh+kjUMRPndFerEFH63dd1TJsHUtpDcM2UjaqHqe6/tzTf9Kaa7ppj3NOfFTNcXrpU956bkM01eUkpWHnQAC1btmrXpsW//gEceeByRRc5Idbomb+65YrmQXjGsj/2ZebrRGiPtzQKR+CqnZ90mXZ8XLH/GfgwuW8q8XZZZXd50z5yUJX2f2XdX8nBTLl/qNiNtY5kOuXCLyRqJLvU62fdceueFs8V3VXhZaV2kmsh0/Kv2NdnnmGcTdruk4WXSdSdjDEJJ+hfMRxTzTELeP3LbHTxwy21obdu98hIP2skGwiiM6HZD/KpPtVlj/orlNP/2mdYTchLiqLdWjZAgDSL14ZH2p8VvqVBPPd1OsqSQG1EYYzcR6igiDru0ux3i2Hr3yHTjCbHRiV20QcfW4MyuQxiiTpeHb/o9ndFRHqkFBNUKKw59BgsXzaVRr1hP9ULZXOMYHRn77pQCTyJ8iRGCKOxg0CiRjHnJOIBQ9uMJgGTTNFhDPLCGKtM3QIfD4dg+Zm3oEcVxstN+BllcFP4l5JaNiaAqrPCXBHQgtX4UIrFyLFo4i2LivSK0HQ1SzyKifJJc4BKFFApxE7Nj+QBcPJqlUhLUc8E4NzvZRk8syon3DsbFEb1kNF4oRhbXzRjiOEbHiQWxsenn0xTrxaBSqbJs2VKazQbN/n7GxsetK7o4QimJUrKU2dTfTPKEgsDzCTxFs2+AOfPnoSPDlvVbUL71tqA16KiD0QY/CBBC0ajXMAgq9QYYg466xLEdPIVJ3F55HkGlShBUmRgfRylBp9MplWY6Un8K9qc19khLi5AoVUFKD4zOFvqVJ1kwdw4m7lCpVlGej44hijRRHBHFkXWzZfIXMc30blpmKu3Wn2K6Vj37PLaVdnrNbPLYkbQRZSMPY0BpgYwFUhfadfKzLFqJrH4ptOvsZxZfUGRWw6lsbwXv3KPGdHMTIQQGjdE2nl7qLrNclsJXm2gFMluK7GBhYo3IXLaJbCuDyScKJYm8vFPCZBK2Nc4oh6At1kw6OUn7i9QQpdBvFu5IJ0d551G4ttgRi6TMEqSnUJ7djSBTryhJXacvRAjwPI96vY5Siq6OQWtEbMunZPplJG7yhLRGfGlIlnSykk78C2QeOSh+aqIUNik2mthoulHIZHuSdrdtjbFMHuImvT82hjjWdKKYbjdiZHycKLbTGqUkzUYFz5M2ZEsYMzRUp1b1adSr1qOHSCYWYYwOIzJ3gr6PrASZkI4SKKnyek+NYjwfEwhQ0k4gjTVWSicOzu2ew5GgY7tTdqIK8/fa2aVxOLaJ53nML7gbdsyOMAx57LHHmJjYetzuJ4u/hNAEDseThhtrdwwhoX8RsMj+bQyMPbZTDT1A8MADAzzwwMBOLMPOR0rJ4ODglOPGGIaHh9myZcuUcWC33eD5z4ctW+Ab30gXhQTVapWFCxeilJqS3p87rVaLRx55JNGV/el5omOtNrlepTQ77l3EnLIKnhynpDLNFKXW02nqz8P06IdyRU158TTRtUybV7lsRR2yPZQvwmX62WnKWsy9/IspeKiYPs8smV4XIyI7UUzO/jrDoxTrQxf0SiXnJCZ9NutNt7+/jyDwCSoVut0uoRSgbfgBIUVZh1x8tkwZl2ilhQRp06k26hhtaE+0bagFKTBGYnQM2mQ7/33fB2HDcWAgTPV5SXVIIVEy8fqrPMKwS2sS4q163zNJ8VIdclozBR0yIlm8TTZ4Je9ZKEGjVgUToTzr8cHoZIE41TWb1FNNQU9VfJe9v0+HmObX7VHSTpeX6LlllmWYMf/ea03Pz+mO9SIFg8sWM4Q13DPa0PezX1sPLmaGDEW5cqZ4aCfXK6bXZO+vcEH69qfcLwSDixfRv2A+lUoAif7ZCEpGIWX/GRS+PZF5dknzsgYq9gXkuty8grN1np6iFHsq+5tGGJkrP6c8eqIL7tFJG0xWKWm2XqXC/NW72vOpxzJh9dPpPr5eL/12z6BgbMNGHr/nPuIoIo6iTKcshQ2fE4UxYTekUq/QHOynUqkQxTEm3SBJYjOSV1Fep1KkSnzSBa7pdMgkK3nG5GWUeZUmxi2aWMeEUUgUR2gdl6otrUaD3WQaxdpuAO527RglwMQRY488yviGjUgJQb3KbgfvS19fFd/3ko2HiXmJ1phYJ+/SegQSnjX00DrKdcbFV20V6mBsX5etRZqkdblprcPheJKYtaFHpWpNLTNryd5uWKeDosEuaiY9uiEZ/VLhMB08ErdYieCYrj3mN+XpT7e4m5/JpwBimnN5odMd2T1rs4Xr7cCbjpImGyiNKRaueHdp2lGagZQEgUSgtsYsdtHYpAuNIu/gs6JmomeevnVxFxHHeRiKdI97KrykVoG+EjQbVQ49+EA27rKcX97wUzZv3IjyfOuaTgClGHLF99k7q1AsmreQw/Y/iLsr97H+kS0YPCphhJIhJtLUm/30z19O2O0yNmF34Csvib0WVFGxFQxqlYDDDjqQBfPn0T+4gKBSo9lsEFQqDA4MsTW0Hb7JXZ+lwS1sTUnrRyA5LojiiJHxMeI4YtGiuUihEfgoVWXPfXalUqvy+9v+hwc2rOXIg49kwdyFU+TkbcnERbZ1bVqr27uPZCZZeaYybE+ZnyyWrVhGrAIWLl2YO7vI5Db7i0xc9RTnlUKAkIkAK6yUmT5D6uXDJAZdqT2CMMb+y9IVqNSFmshNUNLjRRd9uVSe/CnzX4U1BQZSl3GFmUricUIlnodibT1cpEa31mggEUJFIaxQaowhEotyYzCpxXqpwxNpQCwrxCbfsi4oAmRSMelURcjc6ASTO0TNhedkipBYus8ZHKJeq7Hh8fVs2bQ5uyLtaZSn8CsBwkBndAIpBG2RuhaUWV2nVGtV5g4OZq7rTCo5J9VmjMnKXOjSkmfPlSb2lJ1wd8IOrU6biZFhhjduIAq7yVduLdMxECftohtpumHEyMhkYrRl20S1XkEpgfJBeYbBuTWqVcXgQJ1q4FGrVVDKw0sE/9hYa27pS6QvEFWF8CUi27VScriXtSIjJNqzVtnS2G49DNOGnYePcjgcDofjrwGlFCtWrGDRokVPeV7tdpsHHniAMAyf8rwcDofD8efF4sWL6e/v57HHHmPTpk0zXjcwMMDSpUup1+tTPBk8XfB9n912222njHdPxlirPBu6pWfJKyfTdxQ0upkypag8yPXJ2Ry9qGuYmjDFLXHl5fjy+Z7byC8TU4/3PkWyMFzWA1vdkknLnGVeUIgUVyFL6mSTK78p6t7z5eqiDrqkQ05VVz06ZB3rJPyPKOi57KYkk60821ADQeCxZPEiJgf6eWhdzOTEBCIJASxK5S4ofkS5hlOtZLPeZOmCRWxWW5gYa2OQeFojhTXy8IMqlcYAOo7pdkO0MUgp7SYf5dnQCULjK8XSRYtoNOpUqg2U5xEEAUopqtVCmMgpitNkE1hhGT3VHOelLLQrbJikTreD1ppmX81uakIhhce8BYN4nuKxDQ8zMjHMLot3oVFv2rRK76vnvW6l69lqr2QKetXeReBilRefO/l9uibHdH8nx7bZPfYqymc631OOreXbP9DP4mWLafQ3ik0+SSb5WjMFd2+mmXK4VASjwUj7nZjkwYo68uynsK0gFsWzeevQUwqf5VDqc6yNgsnOZtenGxhN8izpdanhicGuX4hSyqXsTKJDTtWsxXrJL+3RqqZGA4Xy5aeLL9pM/95To4fE+9CqQw9m3vKl3PPr3/HArbf31IY19pBKMrhkMasPO4jm0CBhp0scRlnixbHX8zzq1Wpm9JYrpEWSvckiD+btN28LvZ+ByQw8IsJOm9bEhA2/knTK6fU60U/HsSHWmk4ntEZbiad8z1eogSZ7HHUYcadDre4RVDwWrFhIveHjex5CyGzDq05eolACqQBPJOsaeXua1jAJMMn6R/p8Nvy3oLQ44XA4HE+AWRt6+L4dMnSyUDntArQpDivadrCmLMdmC7aFDrts5JElhhXOSkNm9ksWEsKIacqSL2GaaYR0gSm46DO5gJsmmS7QZhagxTR0cn2xIy4OOVONPOyv5fAzmVeTnrKnXgyyAS3xC1gS0nsWiXPBPxXSoRoErFyxgjkDc/jDb25meHgUKVViiThVlMonWMWntUNZf7OfVYHH6OZx/EoNHcdEbbsoHAU+lUqNWt8QqtsmqFRsXHNh3XApz08Gck2lErDbyl1YsXw5/YOLCCo1lOcjpaJWa7A1jDHExFnJRCKGFYdSMmMPgY41E60JhIDB/iaddhshPKT0WLxkLn7V54FH7uPRzY9xwB4HMH9oProweG9tjDXMzmBjmrnbtOe3l5Ig2HN8W3lON0fYWlmm/c57GJw3iKjW6OuvlaOaJG1UisRtmiCZDIvS927fZWK+U/CoYgqCcH5t7psnzSINPZK5oEuOK2mtfTPhsqBIyGSwTJFAZgiWP3l6bZqXtUzWIk4MMXLZM5soijRZk/V9aRqpgCkKZbJfXNYTZd9wydNJQRLMSigFvZUjetLC2HAi2hhqjQaNZp3xsXGGNw9P6XCFFCjfAwxRq51WV5JXOhkuVJjWaB1bo+Ri75E+c/bcednyrrjQp5u0tJoo6tJuTzIxOc7Y6AgCQ+pLQ6SGLxri2BBGmm43ZmLCTsSlUHieIqh4eJ5EiBDlQbPpU28E9PdXqARe5s1DYpDGECdllb7A8yT4ElS+a6XsLjZ/fCNAJ0ZzaVuw0XRsfEax3SZdDsdfAybvWJ6mCneHwzE9UkrmzZv3J8lrdHSUhx9+2Bl6OBzT4sbaJ85Ms23HzqLoWWJgYICBgQHGx8enNfRIVWWNRoMlS5Y8LUO2pHiex4IFC3ZK3k/GWKtUouNI9pjNqFvKFhi3os8qqEC3buSR60SKeZqiDnmmO9NNeNvUgKWKoGRRt1jiXq8duSqqcEzkaWR3T+1zyjrkNLFprjNFsxbIY8sUPMUKesaEog7ZnvKUYs6cAarVKo8/+jii3Un0bMm2op5qMaXylAKrUwkqDA0M0Gl1kZ6HMhodKVAgVYzn+fhBjTgOUZ6HiFM9N9aDhrGblpSnGJzTz5yBASrVZqJflggp8f1gSj2X64VS+I5sc1ZJC5r/M8bQDUOEgGolSBasJUIK+vrqSE8xMraFsdY4C+cupF5vkDbEaY0x0mpO27bI/94mouf34n3F33uvmyGNUssx+YFpxYTZlHG6ssyiHCm1Ro3BuYNUa9We7yXVvZqCGtTqkIvPnGl+TUG3LDI15DTFLeiQkwfPP4lch1w8lnYcWTvv7XNM4b2X3lEariPfoGhEqt9NvrzsGZKsjChdk3qDTnWsPWrUrExb9TKflb9Qvq3JN4luM9Uhz1u5nPkrl7Hp4Ud58NY77LdQXIsSAul5NIbmsGTvPZBKoaMYTZy/x2L6Ot+2O/VkoRg97bYX+45tJWkdE0Uh3bBLt2P12DJ5EdYTiL3BaNufxLGh240Tvbzt25Qn8YMqi/ZchZLQ118hCBTVio+npN3YKURiuFPoT5Q1dkEJigtJmd68R4cMgtRRSyqqm6QxCJm1BofD4XhCzNrQA4YQCIRU5DERpkozpfACkLm+0qU+zv4hRXpHT6eWWW8XOlJ6ur2ilJK5PioIBUx3saG3zHbANNngmVlaZrdo6xowXcw06XMWhPtSedJl61SYLpw3JDvx7cAzrReu9GzJ4rJY2t5jBuudQxPFMWGsiWOJjg1KKXzfx6v041fnoPxuT3zF1DDCllHTRROhUIDKcvKkpOorli4a4vBD9+LRRx7n1lttDO6gYggqFSpKEcWaLZuGMUYzf/4ChJBMRj6xlOhYI1WFofnLWbBkFUGlgVJesngukGorTdHARKfNcGuMWiWgr1bBijY2tptMvHjkr8AOrNqYxNWgh+9XGRyah0GhuzHtsMv48GaMktz0u1/w8OMPst8eBzBvcP6UJdpZyKnbZCb5uygXTpfuTMfMNq55MpiteqtRD1CeZDxss279KFvGxzPBUySSspR5JNHi9EokOcWxpjRRTGJfCqzxRxbSMDES0eQtIBcVrbCX5SKS67OS2hmWNtp+pam5cGp8ovK/bWqpgG6/am1S92z2WplIZ6kAmXaJohD/UyRlRlijk2yOXahkgbAuLo3BaDsVlSLdZZFMwE0+WbD3lfuPvO3n/Y0BNg9vYHxiFCXsV9KOu9QG+xIDGIMnbN7VapVas4FKbB3ymJFk3kOse0KDMRrf98t9fTKJKEmtWclENsFI33DxXUdhhyjqMDa8heHNm+m226hCn20MxLEm1tCNNWE3YmS0TRTFYKxHFc/3UJ5AEKOkYd78JrWqYnBOjcBXiI4makfIho/wJVE7glCDUqiqREmDFNaq23QNVED4Iokhme5CymdYwuSPHEZ2gLPvJwlH42R0h6NMHMIjN8OWtbBgH2jM3dklcjgcDofjLws31j5x5q6G6gBsXgvD63Z2aRwFHn30UUZGRrK/h4eHAZg3bx7z5s1jwYLNCLGeOXPmsOeei6jVGk9bTx5/OdSS6XPB2/O0WqYeHXLyhymeTvWp2aGed1tYcJ7xrZd0yOmvovz3tPrW8mq2SG/LlvRMpn9J/1cKFjHlkafWQVmf2aNjLrbjsguRUorlUMHF+0TPhflzaWMSb7oCY0QWJkWqCsqrImVsPXBnLyHRIafGOWhMFmpCZElLIfCUpL9ZY/nieYyPT7B+fRcAT/koT6GkQEfQmmxjMDTqyTerpS2PBiE8ao0BGn1DKOUjpCptxCo/U7l6wyiiHXbwfEXF80qLzL0mNOmJdF1BCIlUHrVaHRCY2BDFXbrtFkYKHnnsQUYnRlgwdyH1ZNPitO0uXxOf8iqmvsBpby3fT2m5ZFqmtIPeBEVBh7etchSVeFtLc6bzM6S/y3570Zw7SH3hPEYmJmh1uz1p9m4OJDOWSQ9r3bOgkq6cp+tMqbeN7N3alHLPOMVCpRn1rk4l7cSUNdjZPWkckUyHnNS/TPMy2aVWN20KBgMiW18qrlkV301mU1H85LPHTjvJoq5V5F5GZqvQL6RrtOaem37D4+vWkQYrWb/2AbxahYWrVrJw9a5sWvsAG+6+jwUrV7Bk3z3pnz+E5/v591goePZkxqCUZEoTmWlRLClQ+s6zLzd5UK1jtI7otNq025PEUdSTTB5aOwv73YlsmzH2XaThpEg2Y9YbAb4nqFV9lBKIyKAjjfAVKIGJNMTG6oe9JIy5AJNHcQFEYpRU6GGK312ix7dRdPKX7GQVh8PxZDF7Qw/Th+1ew8zSMCOR5tKFrrQ7N8miq07N6Arj1xRBpyhAZHnm90wnbtt0RDKo5jdnfxYuzLxYiHIWkAtCqSV0NsQWPHukC3upG6+iJd80lZFnXpIqcoHUGo/MjBUQ8gefYhCTLpwKg0BjTEysNVGs0bHAaImUEqUUXlBH+U2kN5rsVE9zKRp62FiDMSECgUqWWoUAKQWBVMwf6mPfPZbjy5g77/LRsSEODL7v4yuB0DFjY+MIYMlCGw6i6/s2TI0IkSqgb2ABg3OXbuWpp6lDoNUN2TIxgUHTqHqJ3JS+C5FZyhbH/9ReVEiF8gL6+gbodmN0dxNR2KK1aROhjrnr7lvZOLaZ5YtXMHdOshuxMNDORmbd2jVbu3dr8v42ZPNp85ytfN3LdDW/rbLYJi2oVnyCwGPLxjEe37KZ8Var596CoFNY8M+FZpI4lwUp1uhM4EonIgYSS1l7sOjtLSlK9rcRInHZZttGZriQWChPJ0wJmXzVOgmvlHx/MhFY81As9llk0nGUJvZpX2jMlHcrRM88wM4hk2ZrnQSaZLtLbtxS6GeSXRnZ/aQCb3FikteuMTA2PsymzetReCgUXrVK0Kwj4hiiKDNq8oOAaqNm611HhYq1AnDugcRaTXvKy+tP5P2rMcXCGXobVv7OsjdFFIV02pO0xscY37LZvvc0N4O1KNcQa00Ya9ph7slDIJBKoDyJUraHllIwOKdKoxHQrPkoKQiHQ+IwwlQATxB3DLqj8Zo+XuAhTYxAQxJ7VfoUrNVz6/r8XSbuHmOIo6RZkBitFbtYh8NhMTFsvg9UAAPLoJ6Ea3OTWofD4XA4nhzcWPvEEAIGlkD/YggnnaHHnxHGGDZt2sSjjz465Vx/fz/Lly9nzpwYWE+z2WT58mVo7dr9TsekHhdiplXqlnTIJLraaXS66b2ifG/pQPHamYqTXTpVh5wlNyUPpu1DRabqyPfWl24uLLZmm5a2qUPO9U1TiyAyNcvWnq+oQy6nTUkXJxI9dxYy2GB11MKGIZDKR8gAIdvJDcUKShUeyf1oq6YzuQ5ZYEMf12sVFszrR0nDxk3WU4fxrKdpJQShseFSBKAaDYQUxFJhsB4+hJRUKg1q9X6Kb7D01L3vJ3mtYRzRCrtUhUfglReZrQ6Z7Dmm3C8kUiqCoGI3pcUtdBwRtiaJjWHTpvVMdiYZaM6hXt26d+qZKLWY7eiutqlfnqY60p/b1Bf3ntyawnobhZpWh5wUcP6uy5m3cjnDE+OMtCbp9noOmq6vKOroTaLv710/Kn6PxbIn+eZ6VJOfI9Uhk+iQe/JPNwMXN3QlBldW11y+1hQ2G2beqAqq7sLJcosuPEyxXSQ2I4Wyp48kSDctQ/LdTddHmN7vZms6ZMPDd97F3b++CZFsqZWehwp8hnZZxq6HHgRxzIZ77mfO4gXs/reHknpwzwpH6nE7PWT7iZJ3rUJRch1yqu8uvwNb/IJnFUPmySMKO3RbrcLwknsFT70CxdoQZZ480k2fdp3Lro/ZdYda1SPwFYFv9bq6HVvdsDJ2rSACE2tkoOwG6tSfuQETG5DFPoUeg6zc8MOYvLqSnsjpjx0Ox5PGrA09No8+ghSSRr0PKVW+cJuQC7lph267K21M4sVIZJ1vGlZgWrl82h6u6Aug54zOFwVLA0K6MFq6S+QyKWX3dplAJEAaG3dLJO5IrC1JcSBMf6b35gN0HlexOKDb6zQCaWyYApH5diqUdyt1YIwmjkJMuqpYqJuUkJjQxEi7HJsUUeApD9/zUFLZwUykeRuyaYeBsckJxlojDNSa9FWbCKEADwFIFLVqk/lzF7NpJGJoyS5MjI6hH99ApEPWr1/HxPg4Uho8qcjsZJO4bcrzrEs+QZLnbFxo5rUqsO3IxDHddgfP85B+Jc3FvidjvUCYxEjAGIjCiC0btzA+PsncoX48DzZvnAQBAwNDhGGXTQ8+yNjGTTyy9wE0BuoM1gep+bVZy7RFtlf+nU4OmzK/7Ll3+rc/c95Tv9OtX997fjbXSWDTw+u585bb2fDQ+qwfENK2AetkpfilkHn7yCdXyfeUWLkW5dHMaCMR8oTR9ltKJ6W9z1iwNYhjjSgYK+ThX8pCN4k7NlLvGpSFZq1NXm7sd5Qbedi4p7nrTjIjBSkMaJ2FAyn1D1nvkWZkQx5Zw5c0hIvIfpYSz8peeHpd+GoMmBB0x4CJ0MTEkUa0uigJSgiUkkhP0mq3GZ+YRHgSGSgC5VOvVJGJpXMxTykV0gvy0qTvgaTXzyMoTSmuFeRtIaOoTRx3GRvZwtjICO3Jyez9Gazwa7Qm1oZOqOmGEeMTHaIwhmRcUQqkgkpgCCqShQsb1GoejbpHxbcW2gKBiIAuCG1y5UdSPi1sXQgEhBrdiZG+tP2kEFlXJbA2QFobYi3phNbgzJeQe7myBkbOItvhmAEdweO3w9hjMG93aPxpQj38RTFnF5A+jDwEww/s7NI4HA6H488NN9Y6/orYvHkzWmsOOmgEgJGREe655x4ajX4WLly4k0v3102rM4YQAt+vkHtKzck0siVVbuq51BQWLadRHG/LrUGRKaoUM/WEwKopp+iQy/nm2uNk2bEYoqB3jdKYonqolJAQ0+iQp3mu1I/AFH3Q1nTI6aXGYHRcXFWcQowhNul2xvzZpbSePUQWriHV35rSj04Y0g3bVPyAihck+qw89K/vBdRrfUzWDbW+AcJ2h7aeRBvNxMQw3W432RBV1ssLab2LSKF6KrdXg1p8scVLCn4btCGOIuutRHlkyiCTe33IQydbHVR7okW3G1KvVZASWpPWEKFaqRPrmMnRUTqTLcbmL8Kv+NSCmt0MNV0xp3s3xb+L1/WuyRd/Tat+hqY/xZPHDH/PqBMuGSFMk8F0FJ+3cK+YLp2ifjc58MAfbueP//NbIt9AkLwZQaZPtp+GIdshx/QPX3jtyQGB0OQOcATJu06+OyOmtKS0Yg2isDmwkMcUI4RC/5WUICtDqvotftc9x0zxhRTqKF96yj1MFzqLwjtM+42k3Jn+ONch52HMC5XT+9ILevpMDxsbMJoYq/8Ukebxu+4larUZefQxwLBh3UP87rs/ZGDpIpbss4ddd1J2zaeoDxVJJQmpyFYRC+8ir8opA0ShH7T3aB1hTEyn3aLbaWehxYo6cEwSWltbTx7dMELHqU/wPLy7Uthw340Az5cEvkSl+mMDxCBiMg8spvDOU6MgIWxdmdggVGFzdo8u3L4bQaSt53xV6iNE8s04HbLD4XjizNrQY3jscZTyqVSqBFIlR3tGbAFpHLKS0G56jSp6htRembWnM88vy3/PBlNTPN4zUBYEjEwAz4qaXlAol8iPSYMVUE0SRsEUEis8eiri58N6YdEWSFc80yM6uzUddAvlmEmYSoRNHYXoOCrVSbFuIhMTEeMXBneQeEpZQw8lsWu2RUOPnInJFhtHhlEI6oGPkoEV7BEIPKqVBpWgytBoyMDCpQi1iYktI8Q6YuOmh+i0OigBnpKJcGaQSmRWoFJ5yesxSa31TBaKD1z63SRPAjqO6XY6gMDzJUVvESI1jTRxspZuiMKI4fEJOt0ug3Ma+IFgfHwTsTb0NQcIu23uW3sfYRyyfsNDDC6ZS82vUfWq9u39iQbbbcnRYobzM01zppsCFc/P9HfxeLFMM6VXTGPzYxu59w93sfmxjZkFr/2ZToLt1TM9hymcNQgSr2p5X1IQCkVqCZLsQAAya2pdKGgm7BqTdkbWq4Yofqe5IJYacYDAaG37s6yMqUReWPkHjNFZXaUhndL2B/bbFVIkOyR6DZzKtZoaj6RxEYtzidxdYF72kvBOLkSmgr0JDaZtiBNrY9MJsd+Ohx94iMDHeJJOu8Po6ASy6uP11WlUJPW6Rx6TFdJQOgi7wyOdpWT1mz8EU+cTxYmPAa2JwjadzgTjI1sY3rgpSSKtxcSNaGwIY+vJo9OJGB9rZXoKKUApgfIEga+pVxULFzSo13wqgTXykFIgdGLoERqENtlz5N6N8nHARDGmHWPqfj409ATe1NqGa2l1PHwpqFZAJGFf7FXOJtvhmBGjYdM9sMWzC09u8Wn7EAIGltp/4Aw9HA6HwzEVN9Y6/ooYHh5meHiYzdYxJKOjY9x//xgLFy5mwYIFgFtA2Vm0OuNIqVDKSxbYYcqqZaKDzXfG2/AGvR49Sht1KCSV/pok2xvZpLAOWl6oLV8xZSF1SgapyqCoZCYPuJLt9k/1zT3rt73J5RrpnucS6cMUdDxZzfSkMZMOuaA/MlpbvVavPjtJVxuNxhRC59oEpBA2hEu6aaukkcz112EYMtluIwBfKRveONsUKvE8H+V51Dox1UYfQnh02x2M0Uy2RonC2PqZLuiQhLSL9ELJLIywKbSO4hNYBXPybKmlQ+5uxRbTGOIoBg/kNAuxqTfhVDektabd7RLFMdVqgFSCbreFMRAEFXQcsXl4c2KsMkq1r4avPDyZhocRU99Jz7uZ9d9bObf19jX1MadLe9rmvg3l9LRpikJzTJc4BGVDp2nSfOT2u/n1N69l/j67suig3cvvsPSBTy1xrqUTpc+4uH6e65Dt/1I9crE9FbSrpO2psKRk78ues6wbLFWyyTfxySllLP9hCnnYc6Z0fb5yZMi9sIueekhvFtkzmTSpVAdf0iEnd5Z0yD2bCg0QY71XpD6mY40gYv1969i07kGUUihPsunhR3j0vnUsO3A/BnfflYqQ+L4s13tWzxIhVaFSTf4TkeuQ0z48r6j0I7a6fx0SRyHdTovWRNmTuK15k6ibE08eUUy3E2XPaG3WBFKCUgZfCZpNH99TNlyLwNq0GZE4Gs/XHcov0mRtwWgDkbY7AFP9cWrRk+nMIdaCKJJIAZ6XXwJORnE4HE8eszb0mNtfRwoPTylIB9KSYC2mduhZx10wxUis64RJQihIA4XFz6zfLHTu6aZ/Xbwm+c2UBgpTuDkdJRKh2+TmBaIwyhZkwALFgdCmZT0CJE+SCSwmL1T5CfL7iwJmVieJK6usdgrygq3MTFjJBAxjiHVsBfHEm4EUybvAhh2QIgkNkRYh8aZR9SX1QJHaT+aiTHlmoIEIwfrRYTZPDLOgfx4L58zPhQVAoJg30M9h++zGAw9U2fTQI0xOTjC2ZQtGG+q1OoHvZ3XsSytMa89DeWo7PXrkdZouOG8e2cLakfUsnLeI3VasBqHAJPUg0nq1gpXn+cSRptvpEoURjVoFIWKUsjv1Pd8HYHDOEN2oy5233cKGzes5+ogXUlvZj0dipLKdpZ35KWZ37MmkZzq2TcoC7dS/t5bPwOAgy3ZdydjEY5i1qUeZpAylpmZLJaXACyReIEmdImQeYIS1co2TCX/JIrznm5UiDd3T+6Qi90hREGTzGLEmrxxt78vSNbYs6WVg+ytjsK7bep5eFPIUhcm/KRW+522XJpfF3sAK3tlktyAAizTWY8GaxQrqMheAM2G6WEt5xRUNM+z/Zf7/MCYeb2OwyhhZ8j0nszsMEEVxVlaReCIx6UMXuxjyN2IwxFEHHYeMjY4wMTZCa7KVW7Ub683ECuWaThgThhGTk/YbTucgnrLCuR8IqlXFokV1ajWPSiCQ0pQbfjoxEyCEQUobSdZ6PxFoFFpopDCIuo+seIh6apRm6UYx7W4IxkfqGrGWCOFbIyahrUV4kp+cYszjcDgcDofD4XA4HI4/FePj49x///00Gg0WLFhQdhvv+JNQr/oIZFL3vSu+5cXGjMxda0GXUTiUrfuJHu1Kj+JqWj1bSbdR1Hj1liFN3+7CTtdXs8VhY/UIxWfpySjJbroCTaeAznXX5YXQwsqnKF4pyukkOqfpnjnzFJv8J9NNf8Yaz5TUaMkCpZACTwkbnntaHXL+WMZYz9UTnQ6tsEOjUqdZrZceUSCoV6osnT/IyIjH5OgYYdilM94GY0OBq2wzqUGRLIJKmXsH7l2AKFZqvrtzyhqFEIJWu8VwZ4JGrcngYOKZ1uRtMtUhW/2hQgtrGKJjTeArhLDhgRHWuy1ArWo9e2zc8DgTrQlW7rI73pxqtqUyXeudUuypaviZmS6NVIU53b0zpT1TXjMdT6sxbYKzuYcpzbGoxpy2jAKoVKv0z5lDtVYlbdNWtSny77ygUxUIpCeSDaXZ8optJ+R1k4UFn6HAIlljmOpxJ20Pvf1Vb3LT9FOQ9WnZqXTznkxTzF/Q/8/enz1LkmTpfeDvqKqZu98ltozca8mq6qquRncDzQaIJoZDgkOClCFHhCLzwLd54R83T3zhjAyEIySHA0KmBQQbQO/dtVdlVmZlZmTsd3F3M1M986CLqZn7jYhas7vaTsiNe93cTE13Pfqdo9+Z4rVpntE8y8zXqyN9vxiSMv47HrKcjIWxUsZi6Hz+vQn512IzO8TA47WLTx7w3X/xr3jt3bf5jd//B4wM8tP6UTJLdkotewIVHLu6s8q/Aho8qpHdvet29P0w3kqcm9N5QgYfCCHQ93EM5z6SCbatBedMdPBoTHLwyHkqFVRqJs+R2QExH0NWFBVFGos4k6iex7r3Gh1NUINoQ4gGj5LW+Lrp4c1FFllkkZ9HXtnR4/VbpyiWXm2coKDSidOiVCuX+aR98ZYcDYRBAyYoIUT6/RJ0LP2qjab1XGvGq5PXFy0inaw/EI3BUiaL1mytnnyVF0IRKLEBR4eTKYMIxahZPHfnizvjIhG/mCqgkfZ/XJynC3LRDwjeE4InmikVsOlbD3gsiQIqV6WJCtCmtZy0hjCYWJ6qPerFPCAMKjx6/pjnV0/RLwhv3rmHamRXELFYsbxx9w6v3Wo4dYZ//b//Jd3zaz77+BltY/nC22/QtvG0vwKNjWERvLM455IiEuB4S90oIgZjHQ+fPuJb3/1zvukH3vviV1BjkiY4bgIMihGhsY5BBvb7yIRyetJibcDaeK9zDUYMd+/eY9/t+dZf/Cn9X3q+8Ru/xxe+/HVULBZoJrV0KDP17DDvP1VJxzR/1qU+P1t1hZ8pH/Mt78ta7M69e3zpq1/lJz/5dgzPQXbQSemUHUn8MdbQriy2sWUDk1kYnBGsEXyQNLbGsabVsMtzTt7EjdNIUo+NYJ1LDlJ5jOUtQVbOJSnglStZTi+qc2iA4PMmXZNHVUxipOpL81+9GzNSVWCmIa3yKVTUoXG+KeUhOhrF8Z824cZUaR1MWsmJg0rhnyrM8VQHaHIYy++NjiUQBo/vBkKzwhmXmEjG4sT5PKAaY57GvEbwZnSIqdop1U12jFMNDH5P311z8fwJTx8+HqdRjXNryBR7PrAdAvtdz+Xz69Luxggube7aFWxOLe+8dcZ67TBJSZdqHh7rCIxRjEl1rKAYMAYVCEbh1GBdPDlSwjor7HvPk+s9Dsta1iAxYqURRcxQlrDJGrjIIossssgiiyyyyCKLLLLIr1wuLi64uLjgjTfe4PXXX/+8s/N3Uk5XLYohHAuTUOO/FbyqR+4seIhSmJYjNFHjxRmrmZsjZwnlX+X4OOPv+tn8VTI6xldN0eCjUp/kLs/c8JSONthckAIfj4DFmOljGHL1joPklXhYaYILJSwss92W+khpJobuxhoaK2io64mxbCUbQgCu91v2/Q5uwdl6U25FDAbh9GTNyfoerRE++ugz/L7n+mKHNcKt87N0GC/l0BDDOYcqjHBdfwWbSnV0IwITDyRd77Y8fPyA+3cDd+7cBZkeFMzFF4kha4w3DD4yoTSNTfhSvN/YGMpms9kw+IGHDz7Bf6a8du8tbt15jcwZko9kHvgbHMH6b8SQZ/ce/D2TktbLAKl5Xo69e2b3fpX33/SqaeaqdBTWmw23791jtdnEsZ1x1uqXylgRYiKjrxhT5o6MBZv045ODVGnZg65To/vzAiUzvjXFQWp6X4Uhw1FMdvyOkfW3HjcTDHmeDZm2jcph1UkeW2NFlikkhZHO2GwcA2PZp9NQ/qLCuTm4iXJgeVIf8XkBnn/8gGc/+ZQv/97v8hu/9w8wzs78Nkbs3YcK764PR9aYMxmHH58PYcCHnn23ZXe1LffW01Jh8UiHBrt9Xy0Lie3ZxHAtrhVunbU4Z8o50NFeUVW4xJxImotzn8p9UgVoJIZtqR2HFAavbPsBQ4PDlbk6viaMbbY4eSyyyCK/QHllR49BLZq81o6qI4nCXysv6ThxTWbI0b5ajHvxTLVqNGsqabKsF7TacYI05adZUfJqFbWyepmrl+IDHXlMTCd6a9wwMG4yVEdHh1xWSZRcKkRHkJLplOT0/UWSElqc1NGp0brUZfquMhqqhujo4X21aI/KuoiNVHFqEKcQlB7BiivGTUx0gLhJW8sH/Z988pAP3/8+r8uG7RvvYkyDsTmuZnyXMSvOTs/58pfepnXw6Y8/QCQu3D5ED8r60IRJhmSZvfPlkupSDNZYri+2fPTDj3nr1tuEEGK1F4N8rJGQvFOda7C2w/seDcpmc4bYGGsyMkhEBdG5loCwsRuM7/nWX3+bq87wG1/6Gm+89gbnqxbbNpNcv3BzN5MXbT1eVBMHe7kj98uR++bPzPP806oRx/Kvs78VaG+tuf2FuzRna/ohjFSPk5cKzllW65bVes3t+9GR6PpqwPtQzQ+BHGLDiBDKiJn3oVErHMuZ1fcyycRxXAaxlGfLCKtPd0zeoMTxpaNCXUnc8KVTEhpDVo0sJlIpgyn/IX1pJCmsIc01OT8x9yGkmTZvPEuW9XgDVgrsNIsy+4k3Z2eK4D2oh8RWkqvTiME1TXIsSQUPWa0PuMbGHbge9qrJiZA0PwrQ9Tt86Ll89pTt1QW7621xTCkOHkHph8Cu9/TdwHY7MCRv7UivJ1grNCtYrQyvv75ms46e2MYkFhRjysahhBBqJbajy5SBHoToGOJMCeMi2c07ncW42u65uLrm6nrgydOOsxPD5n6uZ4MxijM2OsmU8pvjbbTIIouMogEe/xD2V3D3i3Dy2uedo0UWWWSRRRb59ZJlrV3k76D81m/Bf/vfwne+A3/4h593bv5uS1CDFlTmBlQpYyEZz0j/jSfyJ3enP6qbtTauVc/I9JmJDU9nN1UGuhF/PSzPGO4h5Xv2TI0rFxLVAtgJo5H0CIZyJJ9jGWssW489Xq5NzxTGgzYaQlWe6uF0eEVFU7gCTeccM/6llFDGc6gs5yv97C6vef7sMac09Ke3Uhqu4PkRS3a07Yrbt8+wBi6fPU1treWnLlN9aGwikzxUdgapbxiZZ/uu5/mTC85WZ+SQGXMbQ8YQTWIRiQwC0Li2OBEUlF8is4dFcKZBQuDhw4f0Xrh3+y6nJ2e01tLYHMaiytvLwOGf7raDB45iyHMTwDHAuHowddfx+RflZQ4412nU381+Z+jRrhzrW2tM6+JBYMP08FSqPCOCayzWOdYnJwD0XcBrNR4qG0l0djiG2gtTFgxSvc1CnCRwdBKxo06j/jNXWCqvpMkhM0EcYMgIKhkHzleOpT4O6mL3yLg2RzBkrWrgENo+lGOT49GH0lhJ71YTQEdG5zoZYw3G2slEmHNrbGbartvs2Cu19FnvBwKebr9j6BPLc7ktsXhoxJKHhHH3fbRHkaosOnlEBw9rhdNTh3O2hKWSNBfmX6mFEJvWLjt+DwkzNowgfT03IPT9wL7r6YfAdudpG6HZjN+LUOaTUndH7XSLLLLIIj+9vLKjRxdiAIsYGiQaPyeS6eA0KjOZrKksXGkOrCUu5CE5BeeT44KfKXS1IjaVarJFqUPAjAbWlDdhMpEWnWO2xmi6P65YeXFP7COmTuTIJiWnJ2PtjHuN8UWj5+Khkq5o9F4eP8VXaoiLnPdkWiqV/K0gWFrTYjQgkhVlgzM91gSMGUA0Gd5zY9Q/sbjeK599+DHf+aM/4Z2zu1z+5m+yWp2xNutxIcNhjHDr/Dbf+PqXaazyV3/aELzH+8DgfVxY80KZvCdtvRj+lGKMwVnL5dNLfvTX7/PlN76EBh9D/8RlmGRWxhP9qNumobOOYegBODk9wbUNzhgMShCTwoesEOs4sadIv+ff/fGf8u++8wP+y//0v8S6De7OOZu2eaVc50h6VZOmlnx5qY/s045K3WWO6c433T//bF5wz7E8HUs313kAVndPuXtmWN05oes9jZOJY1HsrULTNNy6fcLprTu8/d7X2W873v/+j9DQl3GniWLycJSNY6LqufHvrFyXsZaV+7RpzM4YRU8rk0f6NcaFjcmmT5Y0kJPCl+/It4mWe/Pra6YRTQw2MS+GvNHV7OiR3ym5+GnOqU6CkOpusrGv2ydvKvJuIig5HmPO9WSeCyHSUboB9TaOpbEY0QGqbbE2BXzSzGgSf2yT4qVq1eMLk0nOnDIy+EDfb9nvtzx59IiLp0/KHJ2ZRQYfGIbAtvdc7Qf6Xc/uYl/SNFZYrw3GQruB81PLl75wTttanLVJgTfT31nxbg2YgDiHWIeYGHLFWINxBrHjpJ2VdFXh4mrLjz/+jKvngaefBd58o+Gt+9ERRrFYUVobN4u+dBPLIoss8hLRAA++BfJdcP/pYnxaZJFFFllkkV+0LGvtIn8H5fd/H/69fw/++/8e/rf/7fPOzd9t8RlDmVptR9FsYKcyls1kBjGUQ2+1XSwQD8jU8M7cWl28O6S6YbxnEkobIqZ6NDPx2frkttZ5HGlNj5yJqR6qfyuTQ37HXlu+PWK8zgjZHOuOhtlQDN6a8jrihwYrlnKQMuFlRgI5RO1o/MyJZ0x8vKgKV88vefTRJ5y3G7r7r+FsGxmdC3oW8ZlVu+K11+5gBR58atEQmXclO3owYsjRIJqr7UjtvBAMlXKKv9t1PH34jDunt+O6mBtbpSQTAItgrY04WcLpmrbBeJMMs+NhTGMdSKCVll4HPv74Uz5+9ISvf+XriGkw6xWNOxIuqu4CcvDnjcW7SequdSOGrEyckur75Ib6uwlDPpqfnNH5l3PAGorzU65zt2lZ3znFrxt8CFi1BwwHgmCdZbVuaFcbzu7cw/eep0+eJjwSysFj1YMy1nmfDH1mY5dsW6jymjI81t8MQ64dzeryjlGvD6umvDO/T0cMOfX10T2iWNRKFuczU5lxirPUmCHh8P55XkoZqrllnE+qWUUlHkgMGutd80HNPG4FYy3W2vKWMeS4Jvbll1gvZhOxDz3eD2yvr+l2u6rM8b7s5NH7QO8DfggM+2FMzgiuifVqG1g1htu3VlibQ6WPzOCZVTs2gQGbQ1vZdJgwJFtCPlx4pDIV9v3As8sr+r2yu1JOTw1nJwmrT5zdNp2KVvLYfNlIX2SRRRZ5NXllR4/zs9fRoGx3PSEoYvIKPU5Ic6/PYjLLsf5mc1f0oJtdrPTXvP7lRacorBybT8dZdhrv6jB5ZaSymuS1WtgOlKTk9TnRcbMxefxw8walKtvkDalA0+Wu0n5EU9YUP/R476MXpUbVKDKhxNAX1iZGFB8ttkbSKfimwbYt6mtGlsCofcS6c9ayblt2u56PHz3juz/6iNf/9Du88/ZbfO29FlyDzQsaMZTKar2mXa0i1Z5qXBBJNGeVETgzIlTbgaqW5zV2ZEslVB6XyRDuIdj63uhelP1nag9aEXDOEkKIjCtByC4KRiL11mq1QkX57OkTdo+e8NEPfsh5c8rJ17/KvbPTm1r1qE57TI4p3q+6nE+U8Vd8/mUbgxfui2bXDhXlaNgOCj9+9oRPL57zk48/5uOPP+UH3/lBZItQLUqTEuv39Oyc1brl7PY57WqD38PQhchpp5o86FM/ZuwzPo+TrFBLHBqaFM18kiA7T5TYozK6ZojkVCuA4KDMUlgxih9WpbySU9BRbc6hWOJwnW6yy1vqzUNxYJm9v7qxsFGU8TMq/fnm6XumrT0ZXZnlo3qdQmLokMRwUTnFpHo3ZhpPt0SrCaE41WTFXfIcLfndGjuHBAYflfPL58/YXl/R7XaExN6Sneh8UPbdwG4/0PWefefxQ3RqM6I4B66BZq2sVpa7d9Zs1g5r4gvD4BExmNZM1xRJa5RaSCeKIJ4cEKPxfhsp/ESEoPFUgAaHaoPvLLoD7VPT5bIZcMZgrRLEpx6W+8LYbosssshLRAM8+xDUw/nbcLoYoSaiCs9/AtePD7+7/ORXn59FXiqqyrNnz7i4uODWrVvcunXrcK+zyCKLLPKrlGWtfTVRhYtP4OohXH72eedmkZ9RMga0LL2fv7TtCSj0g48G2CNhNuZG2QmGfMT6LHCoV40QyfhrZricvqQCYEeL7XhZSDjrkce1gsCzlfgY0JfTnJVCtbqi1QvzS17Yb4+/6BBDHu8PiW05Yz2g6bURCxYj5WxOjaEaYxFr0TBjIqkBRI0n0521DIPnYrvn0ZMLTj55xPn5GffuWEzCmspJeWNw1mGdjcy9xVo64t+a67VqmqNlr9v9WGNJ1VeSPUED+QxXVfcJ28rIYVWNRiSGCwcKozfjQTNrLYpytdsybLc8f/KE1jQ0r91ls2qmeZrlt/Y9Oip1X6ufO5bmTyEHQ+tYOi/LGy//ft5iqsqjH3/ExcPHmPt3kVtnPBfg9i3UaOmn9Ri0ztKuVrj02zqHDukQWkg2mvmEn7HiNAeUPlDXuVaMxilvGeHNXRGyPWGsoBxSe2IHq/5XSeOrGjL5l+jY8DEJGee0ye06ebY8n19TnRUs80/quMLYvvMcHjbqwY1HRLj7zpucv/46zz59wPNPP0vzq4zvJ2GkMuLYJdERRKauw4PXasbZ49gPwaMa6PZ7hr7D+2HCBp2x/2EIDD7EkC0+jPg0kR3GWLBWsc6wWTtcY6ospXzYhN9W9TguIiPmLi6F7rbjQfbMHBNQCIJiUS8wRJV70k4yMt3HuSblNZ1EXXSWRRZZ5Bchr+zocf/ulxiGnm7/E3zo4uJUK6XZmAqHCnb1bYmBJ9k7t9KyZhpLnlBDmBL+IZbpi2YTMMmoW7I2LqDz1TIuI1NtdSTaGNMt5uKZl2MgUValWfxgz6HR67dWcsYgI1X+Zs8K07AuXj1d3zEMPcEH1AbUROMmuOjI0BgwwpAMrNaAs+DWK5rNhqGzKANTZ49xkV81jrP1movrPd//8DO0+S5Pryz/wT/8bb74zn2ETbS2YgGLdS2bs1M2JyfRW1tBxAImntIPidEBwYjB/BwRDbKjh5VUfxrZR9STerGgYlAMIbWWJGYwDYoYQ+NcUg5MDKFhfOzHBiyWk9M1rjH86Eff4bPPnvCdW2/SXXa8cfuML7/79jQ/s7+P7Svm9920/3uR/Iy6e70Ve9G+ociLynDT5wHoUf7s04/539//IT/813/C+3/0Z2wff0I/BEIOlZIM35vTE9754rs0qzXt2W3UC90Wum1Ag4+jyTmsM4Skt9uUOZGkz6Z5wyBJ6Q7F+QlldPwwWvQzTQlE5U3HTV6un6ysZ7YNiSGgfNKgay/knET8mDX4WHOmPvWhUcnPt9X1HOeYNMMUJTLlJ/2d6SFzA5o01+Y97uibfaTVKgo7TZueOnRVvEUp7vTWgpgqfmtsM2vTxjx9xsW5LjpVpE2yMjpUMcbNVUgbL9huL+n6HU8efsbV8+exvVQJPuazHyKTx9X1novrPX4I+M4Xxdk4WK/ArWBzrpyfWr787jnOmlgPQQlDQExAVi6O+/IvV7pL60R09nAnDkHQxqKWsi55VXr1hKEl+JZ+6whXgu6jM5imfuhEWLUOa3xp5/yq4mS0yCKLvIJoPG382bfhq//xYnw6EI1188lfHv9ukb+R8uDBA95//32++tWvcuvWrc87O4ssssjfeVnW2leWh9+Dn/wJyxq7yCI/v5xsbhN8wPsLfPCJDGKOUGUG48ml8qscxKlwh8lNRabpRlvimKgmjGeKIdemz5mhbWaFLHhKgq11wmxRm2fHdNN5x0nhRo7YbNjM95Dh6PLuQwz5UOpn5xhyUMWHyE6RMTKkPownGCsQJB7SImFtAsZZrGsIfseInOWKHUExaw2tdXS95/GzK9Q8YtcLX3jnDW6fnZTDgmjC2ozFrRpc06RDRRmLqZgN5m2S6/kYYCnV5zkWz2h3yPUUApFpOj2jktlv04vMtJwmHaYsJ5py2I+ESTatw3jh6dNHXF1vebQ6w3ee03XLnVvnlfF4ms+JKWXepvNi1mnM+8kN/WaS9LyObvo8f+YIqHw4emd5PZqBdFmVH//lt/jRn/4Fq3/wW7Rf/wpPBMLrrxN2l4TriwJRktq+aRvOb93COodtV2gQ/AC+HxFdSUzdWr865T+PteyXkB03QjkpWGOj+YaUQEojHzQdyxELKfl+RjtXGX9H+qdCtFPl9Gdo7qSej2DIEYzO7xy/nY+b8s2NGPKkUSZ/ak5fJNqygLd+8zf4yr//+3z3D/81zz59kBIfD9nWg9GISTaqfFvKfZAybdR1kxHtse8oqDAMXWLyuKLf7wvDjoYx1HkIStd5umGITCNeS7rGgHNgXMSRV61w51Zb7FPRdhBGnFtGTLjUoxpGW6NgnCCNoDl0S7ozEPuTBkHV4nuDdhKdPRh/DHG+NERWobqLLIdCFllkkV+UvLKjx6OnzwjBM6SQHKNUHpfVtUNNoNLK82n14m6fY9eNGk+9eJY5r9IcyoI9/YK8YM6dozMTRGXHTElVhUmL7qirz1ahSanzH3WCo1Y9CRVzg6IzT7XOs87uCgp9gCGMC8WolSXlVNOpfA2RTUNTqArjUNNUSstEBSpixOCMpbUNa9cy7Hc8efQJn356mw9+/H3u3XuDL7x9SmbOMGJpmxbXtFjnird4KCxeJi6ClVJVx8M7UptH6xo0eoqbaHx2TYO1kfIqblR8/J0caoKPcShNMu4Hnys39rcg0eMy5lFLHzBJQQxe6buBRw8+wTnHZ4+/wdPde2zcmrVbVRuPl7fpy+SXsZzPR8NR5bv6fFjbN/+tqmzVsw+B9z/8CZ89esK3v/8tPv7wfZ599AH91RN8ty1vFzG0q5b1yQln57doVycEFZ4/fYYRx9qeJqeB2GcFQKV46Gre9JXxSDKsz5SwqhDZ01ckO4hVfW4yl0QGBpP4ILUo51MKuvkOKlMC2qy0pvtKHFmtZijJF47txMbk6wh9Y1mrzUfacJb4tcX9fFLwMVXRg7afaJKTj8d7YZ6jJ7UglJiEIcV7RZPndNDkwR698Qff44Pn8vlztttr9tsdwxDY7Tr6fiB4JYQxZMu+G+i7oTAWWSO4FlYrw8mZZbUx3Lpt2awarAjiFX81QIjhrsQZOCHGUJxUbgQwVKUgF7l2NG0ushf4o8cXPHpyyZ1b97l75xRVYd/HeVdM7CvGGKw1OOdwIvG0i2pyVkr/FkV9kUV+CtHZnLsIGuKp4u0z2D7hcPVe5G+ylDjjiyyyyCJ/YyTtKy4+AdvC6euLw0cWVbj4FHZP4PoRy5q7yCK/GNnudmgyyB3SCMxlhiFnEdIeYeoUMD/BP4KoCSl9JQx5hvHqzIZKMZOO9tVkpB0dLLRsZcYXprSPgVWTTNW4UAaRX1ZPs5R0vHuqeiZsVJUwu14wZGUEv7PumiFtMZHJojqYlEC28bdS8DSbsOTgB3bbS64u1zx7/oTN5pTmvEnlNAgGayzGpnAImvG1gGpm5a1yKtW758XQOk/MmjRhfekgV2SrzZy46ac6sJMxqFw7kYBgTLA8Nc9GxsxUCT5wfXmJEeEnoWf7ySe89s473HnzjZFl4WcFi3NWZlDiS8Hp+bP155vuy79y15jfVo+T9MxNq6YmrPezD3/C8ydPebrbEe7cZtd3dA8esL94hg478L5KNDJ5uKZhtVpjXYMq7Hd7BIMzTXxnwkvr/q81g8ekUHMMWSf1MZapGo9HMeR0qbJtxa+O4BnVVDAPwXIsMFQ+ODfm9wiGXLV/+UYqDLkUqA7HMsWtD9+bC3VDK0oOVTK2z402hnk/m10ve2QdDVtazT8hBEJi8uj7Dp+cOIbB430oEHm0OyneK34Y2aKNkcTiITStYBvDai00bgxJrp0fq9dKtIrOo2+LFCcVkk0r25uQ3NcCAdhe77ne7VmvTtmsW9CIHweyCSrZPxOWbCA6w0wcjG7G5RdZZJFFfhp5ZUePH/z4I6yBW6cOZ6sTy5J4o7JudTDLj3M4pEmOfNZa8sxXJrWydByb45K2MT/HnmfpFDXvwIA5Lo1afZ4qkPVyPv6XPRaSJ5+k52qDak4ze/Rlo29+x2yzIqlweXmfKCUln9PyAvggbL2wD9VaIFFRJrGKhCCEkAywGtIiCsG0BLcGsQhD9CItbB5jTVpjaF3DSbvm1vqM7vqSj378Hc5Pdty5veMbX/tt3n3ri8lDUzDWsd6cst5saNeruND5Hq+CH1bROO1SbEQn2LQpqGmqXlWsCI0VmrahWa9xjYuxI/FAH8tj4mn9YfA03kaPSxH6IWBMZPtADB5lIBSPzxxexJi46QhDoNv2fPD9b/Hg4x/yW7//G3zpd7/CG2f3WVWOHi+TF90nr/D9sRr6ZS79L2qR3Dc98Mj3PB32/E//5t/yx//2z3j84+/z7MFH9Ntrht2W0HUxr2lTdXp2xlvvvkW7OuXk5C7PLy74+Mc/Zr0+4d13TqP3dfCoD4WsJ2jAh4BYN75fszIvY/1V4ypGGak2buXJMC1dGvpZ582sFfEdinpf3T2O99wmIUT2HmPsmA5QToVkJ4zSWPn9ad6sN8q5nsiuHgYl02smhy3i+J/4kiWPZkmUJzk0ZUw1O8iNdXGo0+e5MbJ9iNY9MtMfmmquSteJSj4GfBhiXfkYekdDZOHQEAjBc3V9SdftefDxp1xfXhav62fPrrm82uI9BA/eh4nSHikwDdbC6UbYnDru3V9zeuJ4494GK5HuLlx7uo+vwYNtDHbt0HunjMc+8k7aYBsD1mAaCzay/sTvAwrs+oFdF/ju9z7hW3/1Eb/7u8Lrr72ND8L1FoLEDUOOOdk4x7ptseKxDGjw+GEA0UIFuMgiiyzyM4sG+OQv4LPvzBXrRRZZZJFFFvnZ5cG34bPvwpf/yeLoUUThwV/Dp3+5rLmLLPILlCfPLhCBVWvSSeosUwOqTvCRyrA+BUYr4+rs+vTj9DVSf3Fgsj6Cu00x5HJVqq8zJnNwLVsudSxABfjOw3BIMh4WDPmmcDWlDCOeXZfmkA1lxOH7IHit76mw+PTseAAuYrURcrOocYyYfY1Wj3k0IliJ+MjKtfiu4/nTR7TNwHo98Nrd1zk/H8MYijG4psW5Buccg2rEjxTUpjJm5lYzomRH2WDqtj2wiUf8zJp4it46F8NEFyzcl8pVIv5ogiA2ls+H7DAQy6/lsGCFIaffRgQNiu8Dz558xuXzRzz4ywvkcss//M//GXfefOPmvjkv0pEukO876OdHqkNf8PxobLkhL8c+3wRM12Ng/vzUBIIPgW/9uz/hh3/1LdovfRH33hfZXT5l/73vEfqeMPSoT8b3ZBRv25azW+dY29A0a/b7jotnT3Gu4db57dgvElMNidE39l0tIVHG8aGMFqd8MWZ87EJ1IWo8+Ug9Us1F+VIIMww53zfizPm1NY6d7x2ZlSHRJI+JT9qmmgMkOS4lB7FyWDLPRZrT1+mzyf4xmTc0hU2vMeSjFVBnZ8SUc/jvyfxQ9830zsj8nufINPmkt6kqXQrTcnl5Sb/vSnl2u56uHwqrdAhalTWKMYkFxglNY9icOprGcLZpCqOL9oq/6ON4MoJxBjbMJvj4Y2yagxIl0Fjz8YDj4AODVx49vuThZ895403h9OScgND3lEOS0UnGRGc4ayM7ebIRhDAU+8QiiyyyyC9CXtnRo3U+TZyVUkjRoRgn88mKWp7PCxH1ApuNiMeUtjrJ9DItb81pm6nDRU5M6zvHBXyqr4wLaSmHxvxLVs4nUj09YcZIaSV6qhy2YKaLH5ExjzJ51/QEfb5JFXxa1KyRcaNUtAQleI/3PtIihhDpo1QRG+MrjloG1RtmSnpizYhesz19F7h8vuXTT55y/+5zrnZXtI3SuhVGhNY1NLZBxIFYcuw1EUmKdPJeTE4WWWVIyyOT/vAiSSfn42l6h0jd9jFUj7OKNePGyojBkLyrtXZIGpWX2M5JudCRBkxDYOh7up3w6OMHfPidH7J5r+G1k3vHeurRaz+t3KAf3/j5YD/3CunX92r1O46mw/uEMQRgIJ4I+PCD93n/s0/5+P0fcvHwU3aXF/h9B94nZ9dx62hMNORfXXUoa05PLYIpw8ukOSB4TwieFMJzfHvtVV+VJAiISglNMt/8BA0EH6kqy0a7Klfdd4rSPR+s9cmA9ODIAJK/SD1ZqebGSqlOt5WYtNlbQ8c4qSPZx+jnTanD6cxYyjff7FXzmaQyja2QaPKqDcdhh6nDtpRMV2Ws3lN/n13f89QSlH3fsd3vuLy8YL/bsd939L1n6KNDR9d5fB+9r0OgUInml2fv683Gcn7esDlxnJw41iuHSZ7PfusJOx/zZlJsWVuvLbM/LGByyJ6UX1F23UA3eJ4/23F1uef6Yh99xjBYG72+Q/CojZ+NNRNF3YhisNEX0Lq4pk2n1UUWWeSVROHqITz6Ppzcg83dzztDn79U4MciiyyyyCKL/GJEibFPbwQp/u6IBrj8DPYXsHv6N2zNVd5555LXX9/y8cenPHhw+nlnaJFFfmqxKZzuxLGAjJ9SrkUMeY5STQ2Kc+MiZKNkhdncCKDVRtNJQJeDNLUc7a8PF87fk1EbGWFj0XIGkmPPzSlGXpW548gtEU+t0js4JVlqOUFhmsJoHwLsGStVDeV+oGAehxjyLHuSQ2YbjLEoHu+Vbt9zebnjZL2nH/rocGFccr4wMZxLnX5xBEloooy/63q7EUM+VpXCiEcnFvFJ70qHdEwFENYhfKb42JiHyjhRMLzMVBB87ATNakXrWux6dRTfnwB8xwC/+UM3lK8wuhzrZkfA5QmGPE/7yLsyrCmzzxnDvKkbT7FmgXULp2s8Ad3v8H2PDgNoKPhvQS8l4s5956G1tMk0nntAbM/UbyfjNGduLEZd3ujbMbIyQCzH5YPP2D5/zvn9+5y9dhfNCPhNGHLVZscx5Ho+m7ZPXUOqUmHEjJWa79DaeYIKL65sTjpr04Nyj3PFoVPOfH7SKoXivlHdMykozMtevfOwY1dzcHU9f/Te0/uertszDAN+iCGngo9hUbyPoVlGH5GaPVMwBowVmkZYrSyuic4ezpmxSQZFh3TgWZIjlzlWjhvKm9o7s0Hv9z1d5+m7IcHk2fZFPLBZ5p4xmoEp9xgglDn2p2L6WWSRRRZ5gbyyo8ft85oBYqYxzLUFAzN+uHjZCMGMSWh1e57miw5Z5tb5sgXR+zbKxIabvRDTx5C+FHK4mWgYzsrDTSc28vcKaPIKHB1DqhyVRaqukrRQCPXSVSU+Ls1S/s+LS17kM6FcjIsmGk/sD17xKjjrcNZW6UfHjr7r6QbPEKLno3iP14BxDtu2cXF5wSkVa4TGGZqmxbUbup3S7fY8+OQC8R+wWd/jt3/vAecnd3nt9hnOGM7aNSftBmNXiAyo7oF8It9EJ5PkpJGVa8isHq8uMayKw9mWpmmx1o1KI4I1sFkNrJohgleqOHEYsfjgo8OHBFSiwT0782jyIFci24BPhmfvA/t9j/eB7//xt+DZwMl/uebLX/jKT5Hr4/Kych/bpv2sorO/56NXGR05DDdLSD+99/yr//V/5f/3v/8rLj57zO75RYyZ1/UISmMswXh6okOEs7Db9nz8kwteu7/itdccxjhU4sbOOUtvoOt3eK9s2uj8oSl8i0mOHqPiFBVUj0ElMjPkbXZWpIxA53u6YYisLZVGXqtxkkoc4/3VWnxWxlLZQ55vYlzXyACS+k/QggmmIqGJWadUcP4RHft/NXEpoWJsk5SFuBkVkULfN5lP0iQVdLrJzQ5gAVDRRI4p+CPKaqyLcYOUO0iej4N6RGVy+kZz6oVmTlO5Y3t5H3i+vcC7ngcff8r28pphCAQfuLrcR2V419P3GVAY6yKHRmlbw+mZ486dlrffWrNaOc7OGkw6LRH2gf7hDvWK2Dg32LVgV5KjgBUlu3hdtERaUIlxWXEKRnl8seXp8x0PPnjM4wfP6XaeBkdrHau2xYrg+x4rDa5Z4VyDsQ5rHU1idBEaVCy0JtXHC5CQRRZZ5GZ58NeRweLL/wG8e/fzzs0iiyyyyCKLLPLrLBrg4z+Hh9+J+MHfIBGBP/iDn/Af/8cf8s//+df4n//nE16OIiyyyN8sWa1GjGEqRzDkG+yGGZepouQWvLZgyDcYmyf2xoTRTuyN1evzxRzuQIoJN+FMVdZHMLtKQ6mKVRvuIsY7hWFTvZickTFjN4/yKcag1f85MwXnqi5Hw2g+NJfKoUpmDYgHBdPBuITxBNXo6JEx5xdgyCKRfTmGY3H4QfGD5+qiQ8JTGrfh9e0Vq2bNZt3Gw4LWpcOCFsShDAlnmxpFM/Mtddu/rK3rvGEQsRgTWVmNTOMzGBEaF7A2oZ1qMYk1O2hIB8t07D+pliN8lQ8LVj8h1mcIgZPX3+Tu7Tts7s2Ys47ZwA8M8NX19MwNvjw329tvuv9FeanuqWzoB8lqHiccydcseSXea1+7jfvimwy7ju7pQ4IfIjOwRjwvMqZkuxEMfeBi2HNyYtlsktNR7CUYI3iRyDAcwOXDgirTkZBx1GzbIdtaphX/0V/8NR/8yZ/ztf/wH/PeP/79+VA7WrGZAWe8PB5ippo98v2maihNY3LyHDM709wMlhmBJm2kk7YTUriWAwy5TqueizL2nNOTcvWgW1UJRfaNyhlmHKLlulT/j+XScXLKzanRbrcb9oR94Orikr7r0+Fbpe8GhiHEceXzuyuMP0G+1hqa1rBeWc7PHdYaVqvoICQI6hV/HcN+ZwYYacA4inNGmbdzQ9pU2rreRdl2A7t9z9XTLdurPX7QeFDQmGSnEzREJw5jE5OQSeGjipNHdPAwLveDWX9aZJFFFvkZ5ZUdPUJIy6LRapKvjIdpMZou9MeV1Tq8Sp4wlVq/r5e6vGpl7X7mvTz5m7gAUi+WWaGf3jtVpauFgnGiLY9VOcmL5Zhu/VRe0OUwa1J9nikek/dqlfbsfUEzcwAlwdH8G5Xz2niaf4QUm/AF2waIoUucdbimoVm1eN9hOkPwgW7b8fzxFT/54DFv3G947VbAGGicwzk3nnbPISYQyIZqyQtsXM1VhYAHAhabmBCqcEA3SNT3BWMcyaJeFkMjgsvOJWlTUKjbQiBINnlL0cRHhbw2OGtiDYmqWAiB6+0Vz549Ybff4jWrl4fZrVW5uc5+5Pbje96f4frPI5NuecP3AKKKV+iDcnlxybNHj+murqIndgiISFRsjKEfhtxYUSE3gqa+kMN8lvRLm1pUQ9nUFcrIeYay0jsbe3HvNY7Qoffs93usWKzYcVyVcslh+xVvi9hH6riLhXVHYiYmiu+RvBSfqjIO6y2BTAumMslbTmm6baca+3XLzM5zHKAc03QnG+XCyDEmGfcFWR0egYBUFNIOYnpSIP1EBynP1cUVwQ/st3v6bqDr46mOIYdnqes65SlS/cXwKKu14dathtNTx6q1NG7c5GucNiJDERpjvyRHkyO7mPh/1tYlbupU4fL5Nfu+4/njHdeXHd2uT+Fyxvs11W5kF9QEgNSdMqSpPq9Nf5NOAS6yyN9C0TD+LLLIIossssgii/yyRT2E4fPOxVFxTmlbn4yQiyzyt09GltFaasOWZHih4CykX3MD8jHba4FZ8568XK1fJUxYp49ndMTatKC9B6hKyWcN1JR3Jay6vGpagGNn7g4w5PpNLwL/cvwHHTOj2YCaMbEKdzk07I7IVI2DaqqLjI9P2ATq8k7wvMjkbKzBOBsPC/lo6PS9Z7/tuHi2JZwYNqt4MNNmo2dmgNYRv8+4zciWG7GWWIbIOiKacN0JsDhW3WFbZ0aPaSMIlMNEGXcvPS0Z1qX2MKrqMhubRwhRIiaVPnv1DGGIrAR6BO0+Yis41tyvhP++yk3H6udoB5/dr7NnKV39RtA6O1aIgtdoWx+8j0wNPoY9zoy+JrGVBwlVe1aMxPkAXg2wk6vMEO02Gb/TYtqRg7IdmQMqHDP0A76PeTSYyCSc70kvPChunaRMfh2vmGmGxj+Tw9eIa1fddFbuY++WebmOv+kwkRvHy1Sk+v+g75TfIyN1vlGP3Z+vVeNIQ6Df94lVfSCk0N5Box2SaYpjehrfJwasE1YrQ9tGhmhrx5fmKU1MxIPFhzTNvGTEVf1RgW7fM4SB/fVA33n8ECqsf8SQIcFZJpWvrod6wZt+scgiiyzyC5FXdvTo99EI26xDmsRMpZBzVJkapZqcQyAEinE9TFU6xqWh1nZqVTm+m6ToUZs5S3wvg0oVkqEYMzUdqh8n11F51fTuvBGIE3IKx5WU4NGjWLKlX7V4S8Zk0ypdNMBU8KTZjSHPxmWwGH6Loh7S/YnKKyU0ZEMjteIbv1OUIQSGUHlih0AIAYMkh4qKHm+iucV3tNYhsuH07IzTu7dAAr7bg1e2z6/48HsP+MPwHX7rd3q++uUvY4xlvd6wWa9ZrVYM3Z7gdzFvxoJYxESPRpHoHa1YAoYu7FECG9NisEBDcpk8LimWYnTCWGPERi/gEMM3GGvYrByr1mFNpOcKwePDwNB7rIIRizUBfCAMPoaNUPDDED22AVGlbSybTUvX9/jB8/TpQ5zzPLt8Rp8U12RmvpEF45iOXEuovpPZ/bnb3KRzvZKy/wKZ61rHyjDXpRXognLdex4/eMiD9z+gMS5t0gTrDKvWsmotg/dsr3fRG95YxDWYpsW2TewWRiGEyFYjMVRQs1ohPsRTA8aQKSQ9Lo2SPo0pSxlr5aferMVc77c7nj19xsnJKacnZ6jGsWFExpMM1dwVR0Ees7F1gtriiBIroZ6Hqr/qX5q3GHGsRsV0dBqTeeWTKTV1dj3PBGkeSs40cU8/qs+hsGqkuSTFKszj5UCfTHUU5j1LxpA0xoynKSCFVtE4v4gIzsU2mNDmhUAYBrr9nk8++BTXGIKPebm62tP1Hudi6KVZ7ZGdgowTTAu37zS89+VT2sawblOolDQtahcgCM1mgw4Br9excEbApHlfJPa9aq4T4yCtCz4EfvjDj/n008ewF+iFLmgCG2IfUYmxRH3Q+NsH+t7T9T6FmvEgERQOec73Qxo4zc8/SBdZZJFFFllkkUUWWWSRRRZZ5G+phCGCENaNIMiIw8gIehU5joAVZ4WEfWhydDhuwKzAmdoKW8AQLQbClHq5Z4IJlW80GfuzJXbuulIDOBmrzU+mzzm/Ne3HBJBK6WcLdV0Fk2y+wDCZMe9ySyxN0HmN5vfHq0EzxhzT0MRaKyIYNSNLamFLrcsanTaEhqZtaTdrEEW9B4V+3/P88RU/1kfcf91z986dhCc1OBsPCzprUvTvjP+bgnVnllZNB3Z8OvXjxKV6smOejgKnEbCKThgRV9QUpiZiRIJz8ZCfSZifBi0hIyKcJJhosU1YW6rZEEYMTzWxY0c26aCB3e6a5yaw63dkbnSg+OhMmk9nf88B4qqJ8+ejNupjIPIUsjzy4cjnY9dn90wOflX5zk4guRt7lN4r26trrp48xYqJ2GVysLHW4KwQQqAfILKwGDAx/HxkQ0ijU7VgyGIM1jlCCCW9WEeKSg4Vnpmbp242mWh53mWGYWC33dM2LW1jQRWvmkwzRyqywogLlExmhJfS/45W7FEMuZrrxgRr6LjMG2Wums2hsX9qKSdQMORyT/4+Y8g1M8gNjgeHXSReqc5Gjrh5VY6g0bnLJEaWEXNPNrd0WPDy6SXGSsGX+97jfSjOYEfeHMtlQCys14Y7d1qcEZyNHVEgx5+PkLFrIChB+7FiZXTOyA5f+UcS60ZulydPL7i83MIABMGH3BfHsF2a5tN4YFBjOHlfHSyWkKb61ANDjj5gFwx5kUUW+YXIKzt6bHfbSHnWrnF2apCfzEdzRbJWYLVevDLbRJwAo74ZF8PoujGuWGVRmihBOaZZnQPJWYifpOjaB9+W6/UiWr3jYD0+ULjGzEyVtdpgW9H9pc3EwV6GqZI0Gman9IB5X3OoJ9RKMKU+NLstotEQb6tMRhqL+GzxPIkLsxXD2ekpb7x+n0chsL+8QvBoiAtt38V4aZriiVlrcM6xWbX4rqUbXGJtqOgKZWynXCrvPV4HGhcVN5MdUcbKOyxlZgfJtG1VGZ01nJ5u2KxXUyYGiIp86itmpjXXXSqnZozBOoMMUdHouo7r7ZbLi0ueP3vK2XpNs15NlKWfVmT2O8tcx/9Z075BnXzh/fqS+7pdx/Z6h+8jzZ5K7EOZAcU1FtfYxIYio6IvxHYrYZDq69lDO7mPybRWc78uLa1JMc+bv5xG+r7vu0TtNlRKYVb00t86hnC6afdS8Vkc1ub8cgYcsAk3GPvlZL6p+958Iph81qLgakhKInFza9SU0xrlf6VMQsfafTJnTDp8np2mc03eONTPjGmMo0WTw0MIKX5iVl7TBDoMPnpjZ+czpAAFIpmdKM+JQrOyrM8cm5OGtokbPiOSnAOjg4cZDGikBsWMPVYTtV9d2JzuOH8qV1cd+96z2w74XmkwOGsIJkUbCwZDwIeBZ9dX7Lr9WFVpY09ypvGJgWYM62XTvcdm+UUWWeSVZfccnn0Eq/P4cxTJWmSRv7lycnLCnTt3WK/Xn3dWFllkkUWOy7LWLrLIIr9k6YchsXa6STjYo3LEOD39PuEiyYhcsNNinJTJ8yXEh1YXGZ1Ejr53/khJtTLm3oC53ChKdbKqSn0OopevKwz52G0yvzj9vsDjIwR/w70xLwWb02lVCSD1ibAajM7pa8brlLZpOT05waji9z2QDnaG0dBJQvrFxIN6jbOot/hgRkxwDs/paA/QxGBtTCCyNWtxojmsrApDpsYCx8oyIrSto3F2kkY+6Jn7kFTPQPw851kSEcRGrJEUwqXvB7p9x363o3UO49xh081BWDlybf6u+tmM1RVbQJXGgeFh+tzRPNwEZc3H0yulrZElo+9TmBaNodQTjmtEMDb2BakP42UIt+C40+vldfV9+d35gC0J36MeNvXDY3GC9wzDyFQ9m0oogDQyLeeRihrfUQ+oG0S14NIT546bHnwhhlylkTHp0n9lZPyZJz/Bh+dpxYvXz57x+MOfsH32vNx02Nzy0uJmnFgzC30Y7YM5wXiornI+Ky/LmH9eAOJl4wyuTbYIkxjEGbH02MCS7EH1YJbCujGpl2oMaaqIro+Y9tAH1GtifBHURrubVUFcPKi663sGP4zzafEMy2XPbZ7bJx1izwxXiyyyyCI/p7yyo8cnDz6maVpWq1PcqgFbLaZzmSugkwVDCQF8UGwIqESOh3wSG8kx2o4ZYrMkKv/KQ0LRxAwBqnmRyUFiRkvlxOFSFc3+tUKcWIvzwPjn6BytUPvjVot78UxMGw0xSfULaYXImmCax8vyYoie3fXiqrUSmsMNmPiDKYbtsaJjuW1y6PAh5VYAo7RrYXVisCYxAIQA3o90Jenl1ghiLF/98hf5j/7gH/MXf/FXXD6/Qvot2l1FpcymMmjACDRty+lmw9v37vDMCU/oUEJkepC6nUalXRWudzs63yEngdA4WhGi2ntTCJfISyI4DC2CHZUCApvNii984W1unZ/GBV6IyqIBkXjSvjEG0chGEDeIsSWMJE924m/rDG3r2O96glcuLq7o+54PfvRDvvOXf86XvvglTr/0JW52S5m28bF75iwa9UZhpsNO0nyRvGDYTdL9aUUAgvL04XMePH5Gd72nEcGmjVjbCuvWslo1rFYt26td2WiIRLYJ40xijBjbNxO/GBsVHZE4rcSpJXJZGBvbsveU0EVocggRk1hDTPTsVs/F86dsr5/i2hM2mw1N06R3mejsVCmgOa08z4hUMUjnJxZmOwoFgvqUSPQUj3+Z5FgUmY+MjLodIhhrk5Nb3eLjpne8FIp3s2rAE72FXdvG91eKr6T78xjTNJdpnnuqt9Tvm/4Z61PRRK8oaXLKdIgaw6SUcayEfo8f4ua167qolANt29A0hsuLHbtdH9u/zAdmdPqSXNVxrrp9d8ObXzzn1omwWqVASwFCN7C/2iJqMawx1iErAWMIxsT5rPOpTWPda0VcpMQTAoNXfvj+Ix4/uUb3PQ0tt0/XnLQNT/eey85j1tF/5Lq/5tsf/JDLJ5fEOKyR2SP4uPEYfGDrPc7AOvuduU3ctISOJfTEIov8HPLgW/Doe/Du78efRRb5WyZvv/02b7zxBta+gKlukUUWWeTzlGWtXWSRRX7Jcnl1gbEG51qMjSF9gRuMxTrFXyY4hpazamoy9iuTRGT63w0w8sjQXAyWhQlglpcjH/XwxupFh8CLKMlZQo8/Ul9P2Fm0UFdfV8bHbAc8MOhrlUh6Lh8UynjyBEMuJ9eTgT2k8MI5CVFsIzgvdAUiTw2QD92V+ov4/d07t/iyf5cHDz5jv+8Q34PvCy4YcZmE+VlL6xxnmzV7I2zxRFw2G/VHW0DdJfp+wKtHGkVtRP9tbvP6Rkn5pSpnYgYe21BxjePW+TmrVZOwKoqhX4ihRKwIoZQ5HVhiDNFTmshEdgo/+HhYcN8RvOfZ06c8evApt2/fprl9Z9r8Bx8mJoaDLjz3ldJZkeeG6htlNsyyb4POvpt8vCndF31W2F3vudru8L2PJLypba0RnItswdZa+m4oz2cG9oznz5HsAlPmbyRNLbltssOQTsw7qf6qUO8pgf1+x+XFM7zvaZyLh8rSAyY5eeisXGO9yLTu6+kgO4hMYN6q1wgggTEw+DimRvYWKYzX03nkCIaccMsQEj6d3m1sZsU+YlGY5a/OWr77wz//az7+1ncZun5yD4xHBsczd6kSSj3UfDag3peQ374K4WNttBd0+4Fh8LHc+adKbzxmF6+t147TOytWTQzfUtrCB4auJ6LKLtoOXKxPzRWcQriUg5vVXAUUR7Unz67ZbnvwHoNl3UTnsN0Q6LwiLj7S+56Hz57QbTtKlIDyE+0ZvSoGxZXO6xKjip+17yKLLLLIzyav7OjRtg3OufEEdl640InRcaJoJ0mhF0dniAMzeLqaF5RKMZv6Bcr03oliU38YT/jXi27t/T1duvKfdf5mWa2zXC/U6bmb2B0m+UgaQlESsuH64P1Fvz5YZPJCONcOc2xEm6iiSEqqiME5S2NHyqtCG1UnkxRkUVhvNty+e5c79+5y594d+kthP2wrxo1p+xkjrBpHa2051T+yNFRtNtV6CEF4/PwZgueN87c4Wzd1ZUwKKSSP31RWNMZrq8PzBB9SuIj0TFbUc31Wzx7UeaVNmaSk53v9EOi6gcvnlzx6+IjXX7vPTZKb7Gddouc6ltzw3S9b6pbKF1xjaVtX6sbYGLJFBILmICMTLZo8MuPmYVqCqbo++yJvJqu0hJseyAq+MAwD2+2eE7uhXbtIEVc1SB3/tKRX5pqc2KwV9OaPc8ldqjglV85o9UiYggXj/JBnvJqRpypg/DOlX/e10qWruWXcKEh103gSRss8McnmOCxKQdMmotrEVMnFkxUhlDSHIYW+SeNT1EyYV4rir4wbLNKpjtbiXAod4xX1oIOifXQyUUMJaxW9uQAjMeRPYyvnv6Tf+9gv+w76QfE+zsHGWowR2raJjinB4NRgVDGpHN1+z9D3MY3CHjKm7n2PIHjJznfz0bvIIov8TBL6+OP7zzsniyzyU0ukpHY498pbrEUWWWSRX70sa+0iiyzyS5ZovEuH8SCG3K2Bh/LFEWSofKz21XK4x85JFieI2SPTmw9fM6adAIqCGSesOyd64/b+hi9qzHH2zpoYo/xRgdciMuJJ87doYsAueZpiyPM8aGHimCVIdFrIITQS2lKMqMakkMc1fJryeAxDdk3Dar1mvVmzWa/xvTDshipXOhacpC8bwyAyFqNgyGNptPyfcV/Y7neggdP1OdbNnKpLPeZURgbh+HyNwY+G2BqCrtxM0oWqMevmrtog12M0PFCYTLp9x/X1NScnJ/PWOZCDnvSi/lrdM3H8+XnliM3jVeUYhmxswtaNlLbITM+x2ucVGn9PMeSZneQgs9XHY5Uo85tSWin9EALDMBCCxkOEE88XDh1qqu+Oj+HZq17G+KvjbTGZXD96NOvTJhox5IPCV5UlOqL19dQ6d2AZnx0xZN91DF2X8qgl3bnj0bGCzcOu5PYuDhDpSgjVdW6orYwhM9rUJB12LqzyQWPI76DgU+pGy2HDEv8dYltnCpCqCrLNzXud2JxETLKBRBZzo4IhlFBAESMeCMmBRY+c99DgUZOc8A5sJAuGvMgii/z88soo5Je//AVI3nD1glMvzC+c5yvlKJ/eJy3ymPGUv1IZJdUnvT99lw2dyaiWle5sYtPZJDkqZjE5I6HsBGJuzLjhSCewjy6QZYWsVc5c+vzcXHsfc2SYmMDJK5RCXIRS9ZS1R6AENMiLeQj0/cDgfTbVZpMweQFtmxYxHtWBkMrqVDhdrfGbDY+tKQtX8FoxLISqvgy379znXVnTK9iV4+Mf/ZAf/tU1tmliBos2EFA81sL5yZrdtWN7dY2irDYrjFgkMThoMuhqfpdpUQ3867/4Yx48+pj/8z/+Z3zzS19PdXO4IsbIj+Ak8nqgGj26m+gh2u09Dx88RwdhUMUhGDEppp+MrALJESaEgFRMDLHqYw00ztE2DcZEx5ZY74EPP/iIv/iTv+De7bv81je/WXqKplq8aS+njDwwcyaPukdMus+Ray+TnPacHaT+fUyNPvb+g7RFeP3NO5zc3nB+a4N1wmbd0K4aumHPZbdDTMAZRcOAlVT/pNiLJnroxvrKNRIwQTEBMvWiMWm8eE30crHWssNGZvCIY7ramBHnhevrjiePr2jaW9y+26b+B6qBIfjoDGUskvIVkgPVVFMfnymS+kyej4Q8bxHpIlXH50jTTGKxIJVZiON40lGO7UYSzVyMjUqcEExT3iuA1sBDqk2p0YDg47vyxiZ7oh+0rBZWoRhORSEEVH1ip1A0MXm4NE9ryDObRSXgE0NT8AE/BJ4/v45ON30ozmZ5wi/OVokpZJIhI5gGjI3jVnuP3/aEvYdtABuQVeoRzqA+zuXiDM3dM2xrEefS++ImYbvbMwzK8yc9+y7gbMvdu2vU75HgOdus2TQNXTPg9x7tB/A+9r/LLcPVjt12j0VoTtYJ7BA0DAz7LWoNtC1WDCtxGJRAWFT0RRZZZJFFFllkkUUWWWSRRf7Oyp3bt5miYCM2kuXAWFgDYcesnJLw4fqARxX2esRwRhw4vqf+kAxsc0Nnema0jmaKfZ2+jwxv1+jxMQRADss0eWKOIadndMSQJ+kwfj93FpGSgJQDg4WVNIx49GjkjZ+siYdl1EdmAWNifbbWoa5hm7BzLYd4ZDQCS+YiENarE27dcQQFsYbLp0958lkXmVyAMd55xNDFQNs4ht4wdD2KYhs7Yvi5LaQ6+imRHffDB59wdX3Bb7z7VV6/8xo3sUILkcfDZFRQU2iIVHbvleurPRoism0meBWlr4lGRt1ITnAM2Y/ODLY6XJlDGz9/9pwHn3zGZrXh9fuvT/rcyzDYjCHfdN/c72k8bPaShOdpVEOjfjY11yG4LUeuH0sb4fRsQ7NqWLUOMYnBwxl88HR+QCQybKOhOF5k5DCzfygZb022j2yr12jLyPaT2D/n6L6ZtmmqqLq8fe/ZbiObt7O5D8bCetWRqTxjsUznsJJQGnNjXWVnhmzjYcRFc3lyCO4EjUo63ArjkJk4IpVGmEtmv05jMmGuuS5TdqY5l1lSGtL8qZMbJvB1+ktk/B3fm2xtybaW68HkcVyKENssMlzk25X9vgckOtuUPFcYcj0nTKpdEp5dHQgePDooDLGjlMO/Rsg0LmIFs24xLjKmFNYQVfrBEwLsd57BK0Ysm41Dg0c00DaOxli8DegQSlgiArAfCF1kJREE2zgyw4xqIHgfmbdtnHddau3D/rTIIoss8rPJKzt6hMpeCBwxVlIpb6OSoTJ+X9TAorNVShxwOGu/gmj1qyhMh5NkmtprnfSobqLjClTZYKfp5YU2n4yfv2cs8k3l0XKvzq7NMlw9ImXdvOkmYwTRZFzWSDEnIjhrcKaivas8l+eMKYJgraNtV5yfn3P/tde4ePgZxlpiaIfxzrRsYyQpbMZEVo28TMnYxvP9kzWRom2323NxecW+3+PDQAztYA6emSh9WVEIY/07Zzk7PaVdr9j3PeIMjlWq2SqEz5Hqi30iaiiFGSU5Jpi8L1Flt9ty8fwJu/12NKxTtePLXVoPWk1vuJ6/m23pDjdoRz7/PDIf3pPvUggW6yJLTFZWjBFW4mgbx6p16buqvx20ZaZhqzj3Ji+al1rKX5NNCBS2oGn+q/QntTYt2FSZSj1Eq1MLxYFkNmKVGMZoEt/1oBCzT1m5nubjIATLQc1rVR6prtygCpbOkEZL2ZSM78gKfv48ny8Pp7yb5mc5vKYQvFbxXMdnpXpu2n8Px2WcwqKDlliDaRwltE6cdBAE09qopLeR0SNvDrq+JwQYhhjZBUmORr3i1bNyDc42NE2LdY6mNawIDAg+xNA6YUihWtImrLCSGKFQ8YWA9wNiLGpM3dMWWWSRn1f6LWwfg9tAs3nlNfZvtahCdwn9Dob9552bRRZZZJFFFvn1k2WtXWSRX4kU7PAYhpxB0xpTOQKFjDhdhTxMALAXYa7H8b8ZDFQBuHJ4LxEDGPGhOU9tleChRfTILcfRgpGhgyMGWK1Bqdn1Y4lN33v0jekd+aR7wasSjmdyOOwqrYKLHMGQxZgYkmW14mRzQnd9HQ9oVXcXE37KtknsCflkP5P7pmWAeOjLiGEYBrquxwdPKCGMq7ZJgFa2R9T9ZmT00MLwap1jSKHN28mhwxdg9MXYocW2kTHQui2HYWC/33J98ZyLh49oNmvWpyeHZTwG8L5K157l6QBD1hEzLefo6mH3su11Lsv8ffX4SN/fRFwhNhnWTW6fOJ6dic4xrnw3xQzn+RhRYRlvKQB5PT6OY8hl+N9U9eU08pH+J/nPSUpUvW5yb+kCVWc4mLbmGZndVNKdOI/Uqc1qqQy0KldS1+hs9imdIqdUY8jjayU9KQfllSqpV8BpJjayamJSjc4Pk7yMeT7aqW6Y3jVhttEBxEzbMs91iZVcrJRD56rgez9xQInzihRHMGfMeHDU2MjugSHg0WGIXTEcsbXFCaIqsxI0YDDxcGs1LhdZZJFFfl55ZUeP9z9+jLOOd+6vaBtHnqREZ7NRUkJDcmozohNFJy8KRgy2PumdjZEThaNanDn2ebbEFe8SPUij/mvUVXRi9DzQy1VBPRoMJbaYGgIxPEHUJ8bJWwCby6FxGSx6R0pYdQANiLHRcCnT78eSSVFITNrgqDgi24VWNWHKy8XaGH3Q+pSeAWtYt0K/MlgT8+TDwDB0NIXmrvawNzjjaG3D26+/zb3zWwyX13z3z/8c6xxBBcWCrBBxGDXRMeRkg1u3+METCGUxkxwDL7EbRGOt42xtcMbghpawtez2Wy6GZ2zsbVr7gm4pihBZTbwaIquW5/7rd/lP/k//hMvdNR88fMDJesM3NmeIWrwGREPpJ5FRRiPDiyg2CEaFECuatmlYrVZs1g3BD3RDwHu4vHzAg08DTy/+PldhwInQJIYRqVpkroa8SEc/KF76yecQbvLivkkHeFXd4FXyM9//Xnc9z7Z7msZy53zNxX7P5dWWd167zf3bZ5ycbNhsNgw9fPbZcybe92mMmxRmwzQrxLXgGrCubIjEJsYOM25IRhVWElVcSMqnGZVMiXPRer3m1u1brNdrrMmhhOINNpdbiawLGiZKuSZvtgwiZPo4kz3zTUBVyCw+eU4YFeCJVs6oyCU2m8SOkZ2JxqkzzT/pdk0bFQWGIbJiNE3aBAc/1kZSYrMSPtluWwuZim6yA5puCErpVWLZCgCRM2KIwQzTNqYo5xrnMQLWgrWS8pyYXERKCK5xbo/35Ogr9dyY52N0ZHyyrcG6BtWW9u4Zug8MF30MrbQWxDiasxMwgm0dmMjQ0nWe733whH0XeOu119is1tx77S4ilr/69gc8fnrBN7/2Jd68fwe/HwhD4Pam4cw6nj58wrP9U3yIDDDBJ1YmiXFEjYte2dYGLJE1pbu+xluLbE7JJ4MWWWSRX4A8/A48/QDe/G34wj/8vHPzq5EwwI//TSx3f/1552aRRRZZZJFFfv1kWWsXWeRXIk8vrzFiOD85w1rIFuYR+6yMfowH2yZOHeWudNCjOixY7jEj/BLpAepn50bY42bSwtDxQgy5Nhrq1FZZboooR40z578ys4bMqBgyC2wxxdbYTs5zGDGwcnlafSW3I74saD78pIzh1zMrh6RQFUExJjFWIGAEZwXv8mGjdBAmBKxJWNjscJaRaAA9Pz1js1oRup5HDz6NuBcpVAG24MPGGGzjMM5WLBs5XananJQHQ9ukkDLBRibnoWcfdjSyjraFutG0NkIko6soqqa0zcnphvfe+yLd0PPs+orGOV5rWkASR+vYLrlmJTF6GE1MJ+k11licdTRuQDXEw0MBuu6Sq8vAD/7kYz74wz/ivX/wO3z9n/z7GKEwNxycZZDJr5tldl/dF489e8yv4KjMEzjoZ7O/D8BFSh/uQ2Dfe6wxrFeObvB0vef8ZM3JqqVpGprGEfwlV9f7YgMp6Hp2njEGsa7gnJjMVkE6iCURQz5WHK1Cd1TYfb7inGO1WuGcizhm9WzhilGYMqvX5axDlGgZnHnsiFYuFtNfx9u+YqEfQy9JYcielq0qc8KFC47tEkZbMVXnA7QF0q3rIrPtlzl2xI/r7NXXx8PIMwai6pDitN/EZ6U+VMvoJBUK5FxjyFObSJnGqvrO9Sg2OXi0Fqst6pWw97F7pPqwbRPTtCbVcwzx/ejZFu+Vs5MTGuvYnKwQDA8ePmW767h/7zZnJ+vIfhSUdWNZiWF7vWU/BILGHw1jfo0wssuLIol53/c9KgbJrPk1LfsiiyyyyM8hrx5AWmuFeq5K5E8p/Efl/FEv0oUyqXomr7fZcEn1+6h6Umu8ZZFMi1D+VeixRuUue5feoEOlBVBv+DIt6WmV8l65uu6TwqCFEcIY4XTdppAosabCuPwA0Hc93g+0qzWusdVrohfyPAvzIud05yXJCnD+MSZ6Hhpi2IxCI5fKOVGmqzS1bKAMbdPg5IRVu4qxNevFmpFCy4hgrMUYW6jJ4gYuO/BkBXZUZK0YGms43Zxy6/QW267j4dOnvH6+ptmsESpFvTSRlBP1c8/vxjlu3TpnEKXrBpwdymZLZKTQy71lun/L/WRMP1PvWWswXhk00Pcd2+tLnj97xuOHD6OjhzGcrDfcOj27uW8dac+52pS2Twj1qHpVTfy4QntM374p1eMjukpflcurpzy9eEbXb1EUa4S2saxXLScpFudmHRXkejCXdssqsVZuB2ngl2igo054tIyaFOWbCmOswTqXGGgk7b9HSslcllEtzHNWLifVPfMMVK1TzSfzWXCap3E8FM/erLQzjvexe0ZNWacpHrbZZM4UDsKglESnCnI9h4iM9+TEJLv8lzdT3j6PEVmAmJzW7L11wSb5r/cNwuz7acljeBaDOAfeI2agEMFYiVSgIjHOoSq73cBuP3C99fS9JjaPeJ81Ftc0NK5lvd6wOTllH7b0oYubuqbBWIsSWUGGISTqwOSskigBSfNPidurgRAEH0IMLcSRtlhkkUV+ehn28Wf3FHbPwK3ArW9eJH5dpLuK5V1kkUUW+RWIc4Hz8z3WTpUX74WLixXDcFPgSeXsrGe1Gri6atntXh1WWORvkAx72D0fP7t2WWsXWWSRX4xkhwJq6G3qxZBQOCqgYrwvf8y47gF2cARneBGGdvDVzOp65PqEEWJ+4yEYNEljPP2vDL3n4snzGEK6yoexhrPbt2gal5KcnrtXYPf8gm6/Z3N+zmqzqYoyrZfxiTHMeanWmzCYCn9Lvh8Fx82hMzJepzOcasSQR0uBNRbjtLD8HgWy8v2J0WOET0a8eMSomFwzIrSuZdWs6L3nervjdOUwxlXNL4dvS9c1Ggxi3RvDar0i7BV/GTCmMogXFDvX6U09a8xnCRkukgJVK957+r7D7zrsZcf11RXb62vapmXVtgeJvsrK+6qhXyY31aCiHF46VqTpS2c3yzTpo+9Vpeu27PZ7fOjjZQFrDM5amsbROBexOFM76kiBL8srdRxRWvKvY92/AEOeuEfIYY6z41FhgtAb8ODKtnMkmeM1cRNQ/0IAXyc9Ltq2NB06vDlfL702DoOb83GA69bmvTqBcWDGA9THMWQI1QQzfn3jWDqYz6qvJGdmPmhm4HxInh/GIJrDiadbih+LlHltGALDEBJ+rKPtUEZblzWGxkVG6EF7gsaw8JoOVyqxzwSvjIzQcrTKYmeOvTmoTr9aZJFFFvk55ZURmS+/8zqZ7QGYzkS1bbAYzJkpjek0f1oRSxwvMdGkL0rx2jt4QXwmL9BBs/PGlMipxMNL17T8Uedz5iYh49Kflcxo7ExKnhUwwhCiN6cVuLzo+JO/+An7fU9j43198KxWjt//3S9z+3xTXlDiq2mkZ/rJJ4948uQZX/ryu9x/4x6ZGyorxgjFGF4KQjYK++SNadNP9i+Naqiz6bO1BBFkMKgY2uaEth0Q24JEj+ngB1QN0DB1OQARgxWbjJ4OZx1iHDF0i08ZCwgaq8cYjGsR66qF28afHIZFkvc2AfBYDGvr+IPf/0d885vf5F//2b/jX/7xn/Jf/Yf/lH/wjd/C0lBxMBRF2zQN9vQU2iZ5TCZTvRicdThtkB1gYn2rQNOucc5iTMB7H9s2aIxbV/psqeUYymHVslq3+ODp/Q7tPBfPrvFD4I/+5R/y/NMn0XBsLL/7e/8e//Q//y+wrwiIKeBn13Kf7NLn3Lr1M3N5kWJd624vVMBfIPVzg+/503/7/+Lb3/8Tvv29b/Hg+XO+/PbrvH7vFmenZ2xONqzauFlpV6v4cNroRBrHBhFL8DHm3W63o3ENYxghEgNQYqjIfTKxrgTij/UaKW5sZgpK92mcD4xpaJoVxjaRNQcPvtooK4iOjDO5gKMiH52gxgqILBHxnpATiF+Xvj110MqnLCQVKgRf5qwy1ySSIO891kRnrNoBq7BrTDzB52qzRAcSAQ158x3zKMamrNaKY/pfNCqrzmKbBozFOItrBO8F35M2F5H1pLgfpb+jp7UyDB71iaFExrFKdoYIo/OcMi3/WIqq4qp+IALD1cD+wQ5ZNdjb0QO6PbNIazBtDA9jxKJA55Xr7cC3vv2Q7dZjzTqeDmgbmpWh7/cMDHz1K19Cvtby5utvcHZ6xhM+5so/xTiHdw4j8RjAfud5frmDwWMsGAvWRnq+soaFNB/b2Ab9EBCJDlC/9uD4Iov8KuXRD+DiE7j/DfjiP2LZCi+yyCKL/OLk9dev+W/+m29xft5Nrl9ctPx3/903+fjjs6PPWav8Z//Z+/z2b3/G//A/fJU//uO3fhXZXeQXLQ+/A88+HD/f//qy1i6yyCK/ELlzfgrMsIJKdL5nltFml8Hkg8N7icW5nEqfJzB9Q/k1xyOKofYlaUioDevT7xJcEzGSjEuN4HS0N2oMg/Lkk0f8f/7v/0+un19iZMS1T26f8s/+b/9XXn/3zRFOKRgyBD/wp//LH/LBX36Lf/hf/TN+4x/9A+pj/DLBV6iB+RFTy0ytzEIZkBhSjIBJBsp4UgZrGqwNEQghHVoKuTIsTN9a2kpMZIA2YhBJqKaGcr+gGGK4bkkhEMamiozQI8Zt0udYDqMRW3z37Xe4f/8+H376Me9/8ilf/+KXeev+64CdhVdOaVqDaVuwZsQeyQcTwahFhvhaTf3LWJfsF1reX/pLfQAs5y2FrnHORkYPHcAHun1PCMqt01NOXrvPc7/nL//4j3nz7bd572tfGw+x5SRrELa6lrt+ubeSUF2W+XP5c/WaYr852v+n9ugJsPwqUj0TQuDTn3yHh48/4eHjh1zt99w+P+F0vaZtW5rGxTqzFmsd45gn/jYWJDKw+BDxRyu+NAWU6WCWPyU7SxTbSrpWxnCxKYGIxViXWNePs28UJvuqfeoRMHUMkeq9VSbzMJxjyJptUWk050OC05YttMghaBzN6YBxyJj6kcYSHd9THKimxRtZQ4yJJjodu0xgdD0zCdvPh+0iU0XCfH1MMf+rmyIVMLGNRDYMyOxEFYacMfoDJ5u6PmcdMWU9V3HoAsPVEMOzrGJfsq2AFcSmA3y5T6nS94GHD6/pB8WIS+PYYKwkHD9w7+5tuGc5OzmlbVq2XNLvd4gYghlZxv2g7Lsh2veMJLw6OxCl/CZWJxI7S2Ffqe0TiyyyyCI/h7yyo8d6tYqLiq8WjfT7gAKsUiJGNofq/jRLq+qoEBdT/jyh2Snyo3/Xi7TUV2b6Z1TA84bihmyPqZZT25k2i6RkBC4vO3a7jsbF/Hd+YNM3eB+OJ5jy0e17ttc7Bu8Pyxs1COq4b/GAfXxHUR50TK/WwsqCnFk00m9jDCYpLbmiRkVkquhTtVdWtMoiPHGrzYpSarl0zL4swNUiXNYrGcuU83nr/BbNekU/eB4/fcb1bof3Q1S2TB0fkVIW10SDax2WQ1I+jbG0rknhX2K+rHWF0WTshzoquJMG0OKJHZXOFIZClaEf2O96nj15yoOPP8KIxYrlS+99pWwYDpXMQ1Giu0z0+OxBlca1CELnB4IG1tYxOkEdJjhvtZu+e1WZq1KHNyi77SVXF0/Z7/cMXmnbhlunJ6w2a5q2xTUt1kVWhGlfyk5eiY4zKD6E+OM9IfgJy0YJ9UFWFevNKnmHf5hroTiW5PeNGnVW/irv6HoPWO3V8h3jHJI32nECKKOz2sTU5xhiGaZzj2pWZnlJA+VMpJIXNpS5VOdedLxWvbBcl1mn1Lz5lWnXKmxA6WvV2tEjppmBjKxRj+Nvsn8c81hnqWQ1v3jGzpLznWveK2HnozNH2hSJMxhnEj1j3NT6AN0+sN95rq89u33gbOOwJvbJpm0hOATLenOKazasNyc07RprHZJPXISxPAUPSXPySHxSl2m6AgVVTNmEvHRELbLIIq8qwy7+dJc/YwIeK9ccc7EMeoLS/JwZXGSRRRb52ytt63nzzSvu3t1Prj95sqJp5vPmKCJw586Ot9++5PS0/2Vnc5FflvTb+JOle/tnTGhZaxdZZJGpOGfjvnpOS18ZS4+BWYfmSo4AVlP8ZS4TKHaC9VTPHwXvpi/SCTZ1/G0lGZ2j1+NzQ9/x+OOHXD55hjWa8IPA2fVthu5Fa6hy+eQpj3/yKfvrHGqqKlC5q8KQgRKi5oUY8pEazJhtwaFkfH7yzjoPUl2RCn+S+mvGOs+XR6x9fMckG3UByzOr1QrbxAOM292OfhgIIWAwR0L3VHikkWk1pHyKJBZsMzqZmIQp1ljXBEOeQ5EiyY8mM6EkQ64PeAmoGMxmxaCeq4sL9nfulgNOk8zO/677rlA53Cg2OeF4jYfFXMq/6JHn5UjyLwOOX4prv+wZZRg6+m7HMAyEoFhrWbUNrokszMba5PAjB30j13t28MqM3loOx425mI736UhNkN4041W9RHhSZrhpPWEkhPiYHWkCDo//S40hk7Ho+v4KQ86fZ/1q6qBRvS9ho9OLFKy64Jb568M/DmWs6IPLN33KeVONjiuSMz1h/qmca+ZpH8WQqXNezQ01hlxV4wSbTQ4yQ3RWk1X6ykphhU9QL0HBe8UPSt9rtG84g0l2KGsdaLSBuabFGIdrGkzFPhPHY1U3NYY8TljTsZfbOBUgzwELhrzIIov8ouSVHT1au0ZV2fu4qMZJdVT6ypo0sWTONYxoPPTeY4MdF+f5fFbN2NFhIc+CJh8WZ5xFZ3N7nVytKE5uSF68Ui07x9YeLesUGgRsVBCtCJa4CODig9YLVh0SJFofzeTFJW6kIIgaRJNHtfoy0Sf9BRVNisi4wAVV+uAZgkeJP6OaEQ3lfdfjQ1QqTF7ETApnYU0sdwgEH39UPRGMkeoHkAAMqITokICAOkRccrKYelkbsYhtEdOgITFpRKK6GBMyKdYkxTSoJmOysLYtBsubd865eP02+J5Hj55w++wuZycREIrruUFwrJuGWycrVtYxdB4/hGrRF87OTvl7v/V1jDFsmg29HTg7PU9hWFb4ISoi0Tk2JHaCwNTzVFBjadoG1RWXV3tQ6HqPD3u2+z27fofvA77zXF5dlVrM/uY3qVBKfPU1A/thx6OPvw3B8+5bfw/nNnzwk4/Y7Xe8/dbbnJ2csjGG5qXq1c3vmsurPnvwnHG8/cbvs9/d5/vf/h95YDrO1rc5P7+TnDwanFthmxXWriqlPNMrGpyN7aSq+H5gt9vx6OkThm6H937SC+PGyqADBNHE3BKZLgICGhD141xhABWsi+1mbdoshKzIpRAbGvugGMFmdiIT+2LtUa0ompy2pHhKp7lPC7fQcafbrKhVc5+Qlcs4djKpiLUWISqaRStPzB6oxk1iUkqjl3d0fqoZSCAyeBjJymW8piFU2+bpxOb7Ad/1NM6hJ5HhRgI4MdjWYa3QdwPGKkZ8yn905MonUGrnvbgZzrEH4xzt681TrgPqDXXaMmUdODv+5UtBkS5gNtCeOIwTrNPkyOPoAzzfDux3nscfXdL3yunqFicbx8npOev1ijfeeIdbtzYYuwEsfRcIXrHOIomiXIPw/HrLhR/ouh3WwnrdokbottfsL/aohLhhNJS2kBDrUhIDjMQLaLiJ4nyRRRb5PMTJBffb/weNeTi5HnTFo+7/wi585XPK2SKLLLLIIov8esiy1i6yyCJzseJQiafxcwjbIhlDnlrdmVph86VEcV8OrMloFD2Cx0j9Xzawzth8y7GZV8WQq69fhiGP2U7GasnIacJ0TOR9Fg9GDYU0IqdZlykbbVUYw6mPma7tjCN9Q35/rLeQ2AGUzJiRH1b8MGJctXEyH36DzMCraMgsA0cyKxnprO+IzB3GpoM6FcYvYiJbiJiSfkLhyKGOa9NCDrksgDORLfp0vWJ/sgYNbK+3rFYbrGnjO0pIYoMzllXjcGIiDh60wpChXbW8/vpriAjONngTaJs2MRZYMrFvNuAKlBDt0w4TWT1AMX3E+X1QQj/Q+4EhDPEwkw90fVfbe49LNoMkfLEnMISB7cVD0MD5+RsY43j2/DmDHzg/O0/h1yO/di1y44cbX/vzixjOTt9mGE54/Oj7XIln5dasVusU+j3ievFvNw6nNG6sqewaRKeZfhi43u8I6YCkUPFYZGeNkMdpNrRIOruX+mgevIlV3iSWisi+UNllMi5cmjoyt9TG+zpiSXwuzRD5AHJ1ULCyNkwrO2VnxJArNLmwGlEY6zOTx+hPMI5TNI2TksfR5WPKOqIUJupSkMyif9zhIAQPPobeKQcLlRTeJI5x7wMS/PhekWjf4nifivOj3Px9ROor3D212wGGPLJ+iFfEgW1MGsOa6tHgFfYpVMv2eUfw0NgVTSM0zQrXOE5Pz1mtGsQ4wOB9nPtiqKlcfcK+79mHgPc9RqJj40pafN/juwFEk9NRasfUSSKbSylASW+RRRZZ5Bchr+zoIZi0UI7u2NErUQq7UlGgy9pUtLKkYEt5UCc/1aSe0xptpFUmsqKew3VQtJD6thc5wk3so6TFv151p/sJYgiF2bIjgjUxVIprbFxsQzQe5jiGWqygo1H04PA61QZjrKaiJJjxdSk/Y31VuScrxBpCovEyE6Vfqp86nWlF1SZbpTCLaFZlEyOGGRWN0p4CYqJDx0Shypm/ac2S6DTjFM5OTrh7fo5F6PYdfuMn+c//GWNorMVIOoEfpo3tnOXW+Vl50oihcS4pbkcoI6t+WOq0sIPE2IGmKFaKJzoq+TAwDJ6+Hxi8jw4EaGnT+TaV6rMPgat+x25/xbPLx0jwvOF7xK7Yd3u2uy37rqNpW1aujcyITPvEpBoZ+868qid1+HOIIJye3OfObc+6OcficLahcS2Na7C2SfSGLvaF3OPSuC9Kep23EOj7Hj/0Bxv/CTPP+N+sZFUfS9ckORtICRM1KtvxjswRMp9optNAenD6xjxmDkCI8aMmJXRsE6nKM910T8dkzEHNlpEZNKQUMSecNr8TFpSxELlsSt7s5PE6bhmiF3z8Ga9KqUMhMuZI0Ejjmd97UD86bnRExpiHpVLHOaK6WOVGDtKcRJ6UFKLFCcYJkmgCBwyDKr03dL3n+nrAD7A6W2Fdy8nJKevNis36lPX6BOM2IBYNOwZ8CREE0cGnHwZ23Z7gByBunpyz+LyRq8owMiblqssbyHHePMbBssgii/yqJWDYYuUZK/sRrfl08q3XFc48wYTXCaz5KVTiRRZZZJFFFlkEWNbaRRZZ5GbJG2it9s0VPlAw5Pqe6ea7fF8cARIerC9w9rgRQ67RhxmQ/CIMuf4jYbxHIap00wHUmvIU2R5iWABIRkpToYdHMORXkTovh3jgLJQCmTE34706HuScZvcAp8n3Tys916omLL9uRxnLVJq9xvzql8yw6enLq68kn/GibRybVYshhkTWMLpf1AdGo2+NFAOrJtwm32mMYbVqqycrTDGmPq/Ugv2VOk2FGRk9crUlHDKkg2eJ2bgcZGPODVzVblUHQSOL+DB07LotooHT4BGxeD8wDD2DH2KIZmMnz76oHx0bPi+6/tOIILTNCetVwJkVhuhMYYzFmhy6JzoDjZ1hHP9mkvdswFFCYoU+hudS6vPY4LxhkKexOcKUdT+Pz2Vs9aU1Uwz49Rtf9ExGD/P/4/g8Smszs1cdLc4xCDblXyflqr8cL4+HDI+8XqfziVR5HeHR+Llwc2uVqTx46ml+PtnM8NfpF6F+a1W2sa3ImHwKn5K97QISQ8IH8B76PqABbNtijI0HWJ3DuRbnkqOHCKoDhedaxhb1ITCkeYf0GmMMaiQeeqwm5bKaTdbCXFdHkfFFFllkkZ9JXnmnvd9FbgeyYb2y5UKlexejYZKpLTDdFA2MoTZoAiYFQMzUT0YojoIx0ZR2UuA0eSCaPG2mSdMma3he+PJik5fXsrRVc+tcGdBq/vUq+OQ8IV4RUe7ctYDlzbduI8bw+HKHMUJ72mIamwz/uR6iUkfIiq4hqBA8RSGuslMXtVoPPWHoCKGvFrH8ZYhG865nCIprzJiIgBfFy6gyBA0MfijG5TqdemHM7BRGHGLXGNNgRTFSe3rGNG1SaEOiUTPi4nOkmGUmO4kEBM+YumKN8ttf/3u896UvMzzfs312xXBye2yL8r+P+bIxlEO/3+OHzbSjAdCkvwNGhFWb6LUkGdINqNHC0OArD/WQ3GTF2EjRJdC2LW27IwTQEPBDz76Ln4OJjBNZ2TnmiJH7QQB64MnVJf/y3/whV5fPaIcLTlZr3nrrkltNy93zc07blmdPfsKTxwNfeeurtOd3S2uHqrWOqH2T6zL7Lj9P9f2rqhLGGr74lS9y/vpr/It/cQ7qsbalbU+xbaIwS8wx1pgYTVPiWHRWaFyDGMMQAhjh9GRF27asrND5vNGUwuQRQuxnJsX9G7qxhPH/WJKYvknx89IZBUnvBgYNqA/pcINJCnR29IgbpjBvO4l9VtJEMm57fakLMVKFHUn5KhPOrFbFlPzmkygiGucAkgd0UoQzt0weizrbvOQhq0lZFmxKK82jRsr90Qve0dgGHzy+eLwrah1IZBQxSZFXAQ0QhugwFuMvWpxtUBTvQ9ncawjxPh9KeYyNlJfl2ErJ6NjhZDJAZup5NYSNQNiAvS+YUxAbQAwew9YLn2wVUcNGN6j0+NUVZmV55903OTk55f7rb7Narzk7b3DNGPOzdy0aAtZYXMpjUKG/6thdXsIQUK8MaS4I9XyYvf2Nw6jGykpzCBrwocMYi1utXhmUWWSRRX554uQJr7X/nNY8xMmTg+8NPfea/5Fb7l/zuPsv2IWvfQ65XGSRRRZZZJG/vbKstYsssshN4odsEa+QqrlBbwoXMDdm5ksZG1EijhLRRB2dPUZT2vi4MgKr2eCeHT+qwzC1TbXGiecZ0cNLB6IJA8moUyISRoD1RmCwnJ2tQAzbrmdza41tbWFPnVRMOqkeLyUkZw7oHWRwekHDaIgsD+V6UY2hlJXifJIx5MjRXOdGCSGjihWSqKmAsyyJGERcZPSgatsKQ86n/svhTzHZvJ+MquN75kwDRuCN197gzu07hL2n3/WsXIB2LGKUkAzXBlUhDB5talQ19w9LplYRIsY4hnpIvwXyYciQfk8M3yIxFEnC2axNmLsqIfiCwed05vhtZUCY2C48sNt3vP/xB/TdDhs6Gus4O+tYWct6taKxlv32gt31M+6c38WuNlXbTVr/QPSm68lUUche5Ph9NyUoIty6c5v25IQf/ej7Ca+0WNPE0PJ2PEyanWMi7pZ+jI0G+oSJto2N9Wok2lbyqzKeqdEmVEK2+xFBHg/UZYN8uh8t/bDYQFK7lnlFJGKeqddqbn9q/D99ayS9praxMB6YPTJG4wNzFH9suYwz5wPWpczTFMpf80OU01em8uQemHDl8as4VowYgiTmjlR+0sG+zHwiCcOO4yCkW9PzJjLbhKBjUZLNRYMW0v7sGDUpuyrTjjtfNI5VYWpzJ8iJIC3klyhCH4RLH+u5YQXiUdsjVrh164ymaTk5OcM6R7uyha0aFbwBgkYnpaoP+M4zdHtIjFXl8G+V78IGLSauBoFxPVRF1YNE3H2RRRZZ5Bchr+zoEXylHGbdcHJHmozrq3nNyo+VxSgbMUEzbZFM5rvyeFbp4kSv0/m+yoRM/h8Vrdr5pGTp4KR+/b74f8gbgaRfB43rREgxFtpVZCm4fdZirGGfF3CblOJJmlT7m4pp4FjdFWWiznFeMHzJ7KEhMYZ7CKFeWBgrR/I7kgFTQ6nf8T2jgTifds+0ellJL2nNWr+0bV3OehNQMXtI8YKMrSkCd27f4VzPebj7hIuLXXEYGRX86btA0cp7cmy7euMRFRxb4jHWxG65XUev7qC53bJyEukErTU4ExkEhhDwwTP0QypX3BDU246blGdVpQ/Ktut48OATLi6ecct6/MnAvtvR+y4qTtZwffWcfbele+3dGxXvm971MnlRPm+6X4H16QnnztG0DtBEcdckuj1X4l7W8Tyjsp5iYgr4EMMMOWcLW8okytHY+YqDdv4ZHbLGXFW3l/lhjCWqRaEcFdqqXErVbrMTHnmXkT6M1Gqjki6zvnSopI/5ntZnHCQxa9X8xrSMkylAofYeVqJyXCgwdd6q8bqxFucarPZYbInnOeIFpipqcjYJue6jd71kar7EgZg34nNn8OL5fWz/UpdnXq76UrWhEivIxiCtpHUi4Adh54VnOzAKTgQfDFiHdY6zsxPOz865c+c2q9UKsYoYrcppR0U7bbRUIQyesO/HYurIllRnvN4EjqM+5zmgKrO+s8gvUjSBUeNmV2L4o6W+FzkiRjrW9ke05tHR70UCK/sxjT6kMY/pwjsEGpbTxossssivoxgTaNuacj3KauWPqi0i8bv1uj+annOKc+Hod4v8XZCA0OHkgo39IY15fPSueq21cvkrzuMiv05ircW5m3U0YwI5lOYifzNEw3QvXSCNl9jt8r0o1T6v2ndXh9hyItG4mW+dYiwHoRImGDKz/T6jYbvOzzGAI39RYTkheHw3EAyIz2FtlaHrsBYaJ6zauH/1WJwz+L6j3+8O36GKH4aEQR9k/1Dqqsp/VKDNlB0hY256gOuMX1fvTQ4NWlfs/PVSt4pAPvRXwC2Z1b/MX1PlsX5uvKnAbgLr9ZpWV1wPF3T7IZuuk1F6Wh5JL6rZnOtqqvM3GmeZ9LJ87wTPY4Z/J4AyOy8EEhO1amVTMcw7mJT/qldpPKTZdT3b3ZbLywv6bs/KKKEJDL7HhZbMXtDv9gxDT9ducGowTZNCuB+mfVTq+15xnE7urYDMXDeubVjlUPIJnxdjR6yxxnOzswcUB5CIp8Zxnw8B1nDbaC+oMGQOmp8cNoM5A3E1NiZocYFXRyeHfK1mtJhUU25EmSZRslh+J3tGvmEG5ZZXTbpINfZm9xdsjGNymFfJdx8C1YDg2oZ2s8GEvuD3dUFNCcOUazY5OZS5YXS8mc7ZVANmxPNynd00xd5QnPJ54jIlII3EU5/pnSHAoMpuMGVWUpUYQksMbdvQti3r9TqFgIeaDajMYUyddTQEdEh2tezwVeH2WSRFCEitnh4eB43OMOdFFllkkZ9HXhnNbtZbVIWhb6LmmyyFJYSKHFkkZgqbGCbxSKLjwEiNnyfI/CvUO4FqbZ3PgVNHjRfMkfMb6oUtzcmaWEFUo/dhP3i8V/BbrCgrG8NNrFw83X/57DJO9l0HAk8eGS6cY/T6jYtB27h0cj6wauLpdxUbPQM1x4k7XLU01bFJp+hjqBILE+6I6MDQ4ek1EAYblxEVRC0r2zA0bTptD/0Q2HceH27YCIsF04AdICjWxpiGxjp6LwzBoNiSD5HoWWuMTYwEFGUzRkvJDSwp3zn/hkxYZxiAEB0yrKUnsNWOVhyudFODYgiS/LmL40utaMzrURAb2SaiAhLSQfxxu1ecWiTGx2xcy6pVeh0Y8KzWLadnG66v9ww+cHV5xYNPH3B+fsadO7cxVhiCYkVRU9Smg66363t+/PAxT549Rvsehj0Pnn3C0yvHDz7+LufXj/j08QXX1zsef/ARfrvnzXvvce/eWxwJOjNtslmPOPb9PF/za8cUKwWugQ54srvk4vqK/dAhorQrx8npKhrkjYkMO2IwLhrdjbMYa5IOqQx9x/byOd1ui6RQQIQB1CdWCDBiMWIJEr24RQOoQTTSJkrZrMYdQXTOSYwdGMRabOPGExFCZJMhe/GHRJuohBCddSLbSxVvb9aP8kYihqQheuxKUkrnk1JRNMedx4GzR/o7epJPp6PI+CEY14AP0A/lkXGKyJtEjaFyRIhOBqOynJ3nbt+/w+mtE3bbLV2/p9/3DH2P73uGoWPlXC5hnJ9L9QrO2hRjlDHdcoMipgEEDR0iFtc0eB/Ydx0hhNReVW+brQl1dVSqPoqgYjCrFSvrCCLsh8Cz5x0/+tEl3aDsB4MG4dNBadctb3zpdW7dOufNd97ldHOKMxb1StO4OKdIoscUUAtBInWfohB8DFGj0aExhIAKWGfGNk/tHT3OAZWKtWmc6zFCCPPN4yK/KNnv9/zgBz9gt9sB4Jzjq1/9KmdnZy95cpFFbhZh4E7zLzhzf8LT/p+y9d/4vLO0yCKLLPILl/fee8Y/+2fv0zTT/d963XN6eujMcXra81//199lt2uOpieivPPOYrj/uyqNPOJe+/+mMY+xcvF5Z2eRX3MREb74xS/y+uuv33jP228/AD761WVqkZeKcT0ghGCoD8McRaCOQHnFfiuzC/WBHCj40Ii56AQePGrn1mLXnF58EeomMAef61cqyuMPP+a7/+rfQBhoTDxq5oyyv94S9luMBLpdH9Pynv7igj/+H/4XViebMa1UPmsjPvnkww9xNjmyJExL9AjoUFmHNdXHQSiVcm/EQjzxwJuG+qCewYkl5AMVAj4khle9qVJNwpHjqSEjMdS5GIMPEELddom1Ix2gOggGUWd1BPXibzURsy9XU1hjI3gNDAxYbApnnvqFVAf+NFSNljrJka4ZQ4pUhlhl7DOpjaRKxxpLsJkVNuCcpW0b+j466nRdx9XlJe2qZbNeIybiSYJiRW7seRePnvBH/+P/l94PnHztbUxrudpfsuuEJxe3WfVbLrcdfT+wffacYbfn48++g90NfPUf/R6vf+VLL+3SYz1PvyisC0y61vgdaVgfAZt7EhPJ0LHvO4ZIZ461hqa1I5aa+oQkZudyIAtAY5iWvtvjh57CFp6YdQvbRHYsIA+JgtKl3zrpr5rGanHQMTIJRT+WRUpeVHU8pMyIBWer2Ci5bybDfilLTreyjeT5RGYY8lGRcm897DOOGg8BmmREGw/DZiZryIxIYCua5eIgl3BtMYbf/I/+gC/+7m9F3Dh4whBtR5pC5nz2vR/wk7/+FnmsKhTq8ZEJI+d6ZP2IF2zEZxPbdDw8mg9zReb3F07Jqc7yeNbUTtluJs5hjUEl2mh2+4GnT7o4fwWDKlwFsM5yeueEVbvi9OwWbdNEZhGNjCUZfC84dVrCNF9VHcdAGA+vixVS3JaS3dJm9fxRBpEpTbvIIoss8ouQV3b0MNZHr7chGwZHOXBP0GNLlJT/bzIoxxP5SZmqjWhoMZZKVuZnM+VoJJy/8Xge86RdFr3qxvwpaE72SJsAAQAASURBVIyfp8Fj/IAVBRPwfkCIxuX9rkOAEOImZnu9R+xAdk3VpDCcEg2nIuCcKaFEIC4MMeRCzsBsd1N7WedVpqrPXIxIr6f4EDcURuMCbo3BGVuUn1CU9OM1ExedMVaeMeOpaZ9C64wbhWQkrhSy0j5JYRi9Vpk9N17PSjoQjaUEBvU4DDWTwfhoXSEvs6pKUeZeLNHYb52lCQ2+j5RlzhnaxrEzPaD0Xc/11TWb9SqyhaQ6VTPmZfImjbSHgw9cXF1xeXUd3UpD4Hp3SecNTy4e0eH59OklV9d7njx8RLjuuNpt6X2PimBJtGaJnaDSs8vveY0cq5kj+5gbRVXZhcA2eC521zy/vqCPcVSwVmiaFP/RCIpBxaZ4lqYov0gcS+o9oevwQwSTJbdJZuKA0Xt+ksdMp3dk95HymOs8sockZQlS/xMmc0OeOqpTH6kXl23x9IRIumeuUZdKPtTMVNOYnr5ybCPVUk7JZSibcNLYy/Ph+Mr8h042qMdFgdVmRbtqsY2l3Tfs3Z5u39ObLYYQnb90WvcxPElsRyN1Txu3S3kTgKa5SCjtnucXa3I5qroqCv+RdYNcjWlOMBZai/pANwSurns+/eyKMCgmGDQo+33PyfkJ73ztHVabDSenp2xWJwxdKHVsExvPWNBq9qipSVKf8CFE56WJ8w+lL49Fyb0mbSoKHePxiKCL/OwSHbOik+WTJ0+4uroCoGka3n33XTabzcEzxpjpmF3k75DEEHFC/9I1DkBEWdsPUf2Yq+F32NExOrP+ikQV1Efnx2UGWWSRRX4JcutWx2/91kNWq1c78d40ga997dlL7/P+pbcs8rdJVMEPYCzIwdHXIka2bOx3aczL+0gWkQH5PNbYLMta+7dWRITz83POz88PvstMsCcnF7NnKGFhF/l8REygHPYqGF6NjIySjZWzFKr/J5fKnl5qkKT8n4yW1TvzYZa46Z/iOvGrQ3TiGIZ8+L1MMOTd5RUPvv8jwrDHESL+K4l9OeFgfkiHeTTgfeCzH/244McFcBChcZE1d395mRhyMxZTG06psKjJxWkBq1qUbGROpYgGbEGJh3VIVZVDNGTWjxCOsJ5ODj4l1E7S8mEyDjfDglNbjMb+Kq1U9nL/0SVoLN+EzTuFNDZo7BhStWHpC/XvVHczzIvqrhsh83LRJPg8YubqBzKjsbWGYYhpBx+xDOeiTUBDYOh6xFnU2UO0MzVbt9vz6Y8+YFDPF790H9MY+qHDB2HXbfGiXO06un5gd71luN4xfPwJPL/iza9/hTtdFw9lWlu6vtRFmIPJHK/yGtKXm24qVaoMGsNo74eOfb8nhBQG21AOoMaukDC10vZU30VWX/GecHBIVUt3ic/P81TPNccyWf+SKW4kI/Z7gCEzYrRTtDd/N33/OGap+qDM+mOVdlW5h7kfnx3bUKeZlAqzPfb8sSliUgzh7rtvc/edtxiGgTD0DL3H+8DQ7fFdx/bx4/r2GNLEOqxryEw4ZU6q86Mkm9TYkcawO2nsStVuIpM2rUf9QbXke0TA2oTrKn0XceQYLiaGvvLe06wazs05tnE0bYNzDcGP7BqZjacYN3X2qgpDhsrRo679PJdJNU8luijJfT/3NZWDYi2yyCKL/Czyyo4eV9cx2F2OnTaZhBQyO8P4mckN2WNSk6IfFcmadmt08qhNaTl8x+g4nJVfZbpKJdVokkS10GYNraZpO5ZdpeRDFHQY6Pqeq6tLhsFzvevwITAMMeCbtfFksU/LeuM6Iv1TVMr7ENk63rp/i/PTFav7b7B6621OTjY0RuNioilOWa1k5eyktSME6HvD4HM95x9J7QIbA1aVwQ8EzZveaPCwJoy15EOMTRg8YzxFIfrcGkS0xKYjtRMmekIHhTCpsAQASWR00Em2JIZBELAmLtrxHH0gu3zmbXegIWBRTKQ7DAPe9ww2eWmn+6xVNitL04xsIMc2irlMXdfz0YcfYZ3lq197D2dG43omzAtpgTXiQByv3TvHGMODTz/k4tkTmqalaQes2wPR0ePqUjg99QzB0Hee/eUVbr2C06nBMaav7NWz81t228fst0/xXYf2nqZv0H3P9/7dn9Ku19x5/Rvcbc4YWsPed3z7x3/Cw+5Dbt++x8nJKV+49S73T14rpR5dfjh4740K+k8h/TDwv/7FX/LDzx7w/Ht/xfazT3j/e99h8D1Yg2vbMdUEBjbWYpOzgBiLD3C973CNY90IIQwMux1GA0NQBtXo6SxSdLkQYl8ZaSrzuI2/s6IfEq3Ci5x4IpNH3CQU1VBS/Ewk7jYYFdAcAzKDQt7nTUn8rIXNKOVVQzkpUdPT5TBP9YYpfx2nBcXYsgWI70h3Httm1vOuMdOWNCITlhGVFNpFLFhoVxtc09KuT/DBc3F1weXVOIbEGtx6xdl6w61bd1hvNiUmZi5teacAyXEsCGyvBvp+QKxgG4exdpyv0xxSyvQi/VWFUDFl7HvP1W7g+bOOjz+8Zr/30IPF4KzBZwV5GNg9esJW4WrfQ+OxErACbSM4Z9D9kMLW+MTq4vE+9u993zP4PBemfpYZlCqP/fKTJg5jicxA6jDG0a7OomPLC7l1FvlZZLfb8aMf/Yjr6+vC5gEwDAM/+MEPaJrpaWNjDF/4whe4d+/erzqri/wNkEYec7f9n3Hy054yDtxu/pAT+y2eD/+Ea//NX1oeD189wEd/DJcP4s8iiyyyyCKLfB7y9Mfw3f8Jbr8Lb/19RoDi55PInvUvObN/zrP+/8g2/MYvJN2fSpa19tdOVJUHDx7wySef8Lu/ez357s6du/zO73wRa9eLs8fnJH0f4eZxGqkAz2Tsn5z2nkn+rhj3KvqAqRl2ZkzNp+RD/VlG41xlks0Yy2iXnBpfZ2B09ZVM7svsDwIQAr739H1XWKJDYoxGFWOio0dILzBmQIjhLUTAp/yfnaxYNRZ7coqzjma9xuRq0CpfRapayTiyN4SJY4uWQgvQCHilhPZWHYgHsbLRNd2ZMGsyppbBnYTr5paJ764OB8rMFg1MgW8p+Z3XezYJ5yDc8ZG65g05PLcmTC4EH8PmVAkaUZyVwvJ8rM5qG4T3gefPLjBGuHv3zgR7k5K/hL9pPCB5slkhCFdXz9nvt/HglA3l8Jf3nq6DplGCGh58/30u/voD3vzKl/jGf/CPIhPApAqUAaW5dcI3/pM/oOs7dOUIIWC8gSHw+ONPsM6xPn2NjWkJVpAVbL7xNhIC3/7en/GXf/ZH/M4f/BO+/Ju/VYYdaTgcmF/mMrf5yOzvG54NQXn/wQOeXF2xf/wZw/UlTx8/IqgHMdHppLwjZsQagyEfNjUEhX7wGGtwiQHCDwOCLSHXJ/YkTazGhoTNlt5YDeOM2U4x5hsLPz1tSw7NIyXfxQpFCQSerocQYl+VebtKyUs9Tsv3CqONZooha3ESiPNm9k2rZ8R5kbKNrMacZ1U/cWopaYlgrcMYi3WBoIEffe/7vP+nf871kyfJGCEY53jzK+/xjf/DH3D+2j2sa8jjfo5qi0TmZg3QhejkhhHEGsQbcuS1nFfVmzpmXWH5UG+8dwhKNwT2O8/F8x4/BPAxPSOCmkicrSEwXG8ZFPo7AawmdiCwKUSQFgajMeSTBqI90EfG6NmiwMgUU88s41woJrdj7OvWtuVg6gu74yKLLLLIK8orO3p0XVQ62yZOTnnyz5IVusnslJXivKDmRTAphTW13qGTx/hdUd9r/bpoKNO780Jb0itZyoti1m1lquSV26t8JGOf7wd2V3t23cCji12iWEvLpImOHCF5JjrxGBE2qxZjDHvfoyh3zlasW8v6zm3c2SmNBKyE6D1dyjPJSqWWxP998kBkvqCk8jqBIDH+mAZFw5CM25EWK3uHaojhCaYbg1HZiUp9dPuYW2ene4lx6dJqccr1L1Wy1Z2k5Q80REo9gchXYckUglFRD/gwMEik/rPJCcXaRBFWrYXHVQAh+MDFxSVN4yCEFD7nprvj6aLTkzPaVcvzpw+5MgZjDdbZ5EUflbZu3zMMAR8EPwSGfYd305NJOW8B8HiGMNDvr+j3V/ihR4eopA89PP7kE6xruHfrNzhpV7RO8C7w2dOPeB6e8Hr4ArfCXe5t7k0YLBRGOrgXyGxk3njPPP8+BH70ySf8xfvvc/nnf0b3yUc8ffyUoAFJYVqiHpo8d42UkzPR6C1FSScp6Bo8fujx1uAT20nW0EflUyuWi6nSqulEBFnZKsMh1UuluGfWjDjvhFROmSi0denLFSXlPytqipSTKFUdac5nKFNd7PcVrR9JqdVxK1zOQpS5KOdsHGhx6M3VccbDHinxcYiOlIVjYWKazjUoFttET+mt76DfgR/QYUhKumV1suHua68VJ5is8ktdX+mXtTaN0RCdYUQwVjBiCHO6wJt2j9MkUx3G+asfAle7gWfPOz795Bo0siGJkcREEmLdBWW43tGvt+yGHuc9ayIFprPxx5D7ko79Jm0uBu9L+J8ytlTJgSbHuh7nwVIfIqixGOtwbh2dim4KibXIzyzDMPDw4UO22+3kuqry5MmTg/tFhPv37/+qsrfI3zAxcs2J/auf6pQxkJg9fszKfMjWf/2XlLsbRD08/wk8/eBX+95FFllkkZ9T4ql5xdpACK8IzC7yN1f2z+OPcfDWsd2jAp7InPXqIqJs7I9Q82Ou/TfZhveO3PVLdphe1tpfS7m6uuLBgwdcXjIezgc2mzVvvPEG3i9OHp+XeB/3z7YmByqYQnK2OIohU67NTbJ1Gx9IeUcFQmawRGfvSEhFwW9K3irQudr7a52OVGmUEAzjjRlr6Lt4Ev66G2bvycbXeMVISJhNYlEOHgXWrY14hltj16vosBQ8aIU3aJXHSU0mFg5y3mfAbHrIEIsQ0s1Kxonjj6T7RtzrsA5ze8ks7QJtTZDIF2HIVdsebWcdMfsIxk+/TfkOGmJo6IxoSTwoleCxaRFkmnzsEzHUirEx/EvG8w6KAOT49E3TYq1hv3N0EtleM8NoZkXxQzzIFhQuHz/jyQef0jZuDrIDsT18GDCN5f6X32G/3/P48WNC7xEVgle2l5eIsWxW92hWDmtAndDeOcM4w4ff+y6PfvA+X/za1/FfG+nXIq49hih+qczNNJXJRGbfRxhNeXp5yYOnT+kefIq/fM7uepdYD1KYlLoRErYmFWuNagwXFOeJhLcGTwhSHc+imk+qvM7zq0zCrkRs+CZ0PCOYKexzhelmzHVaEak6tL5ptPFkH6EpidDIjDPmSEYMuEoqm7QyhpydrqJlZYZhpzxP6qKqHp3enK4fXACVpNtbIKDWIKpcP33Gx9/7ASaFXUFAjHB2/x7v/d7vYpumcqqcWWpkfF9m3tF0qFMyln2kbo/KHJOHMu/65Oix23muLvvYBolpOrJ0RGYPFEI/4JueIXhMyAej4/3GCDKk1GsHQQUNWg57jn1pGjGgmubGPk5aLhRU4hjModh1skAsssgii/zs8sqOHo+vf4izjtfcO1hZURa1PHGlCU1n83n+I3M4hMqQF9drSWEfKhFBRMtKdLAEFxe5ypAKWOOiV5yR0aBfTriT5mipFMZs+IvxwLwqvQ8pXwHJtGLWctI0nLQr7t+/xwBcDtHTuZV4mt7aJhr50iZm4xxG4PH1NZ0fODs/4eSk5frpY/rHn7G5/yant+8gRkGGGSuVjOuJ1ItEZM0QyXSn4wqugDcrgnqM7BEJDMlYvu8Duy56JhMC3iu+z6Fb6o1V5oeQVJ+gluTJnbwZQ72viC4MJSCbRK/0Og5kDEkzrm55IRxkAIQGFz130zvVe3zfY1BaKzz69CFPHj7lzTfe5M233uLBk0v+7bd+wNe/9EXeeeOtYzpxVS+B9WbNb/7W1zHWsFqtuN5uE2uAqfrVqLxb43jj/h1u3znn2eNPePrsMW3T4Nue87NTGtOw73r2fY8x4Cx0/Y7HTx6D3uHOrfMDXdMAopZ+N/CTDz7k0ePP+PGP/pqu71mf38G257R+zapZ8cZbb3L7zmtcXv0Y7695+OMf04c990/f4M6br9HaNQpchYGtDpwZxylusgua6wcHe5cj99woQdk8vuL80+fs9wNd2X1lxdJED9y8KVbIIX8k3SsC1kK333Jx8ZCh79kPO0wTHXdEiBuxZFQXA0xihGYOGEUJqA9cXjxi6Pc0q1sYt0qquBBU6b3ShJCcnZJKHALqNW24pNpYazHMa3LGIOiobKXiqkphESl1mMIVSfEMz1uOYwp/vpBrLiqY9VcxzTFvRipaw7z5NVI2L0pUMpFYdzFzI4VhpoKrxXc9fdeze3bB1eMnrFrHqnXFWSMEJUjMX9wgU7CL0dFDSl6NJBq/weO9xwcf82MgpPBQhb7vJTIE2PfKwyd7Hj3Z0u082+c9u62P3t0S556mtbx27zzSU+5jfNsB5WLf8W+/831Oz8/5g298ldOTDUGis1JIgaE0K/Uhhk683vc8v97T9ekkSlp7hsGz73u0S5sDwKZ6CCkmrnoQcayaDcY2OLeKdczCYb7IIossssgii/zdEBH4gz/4mPfee8a/+Tdv81d/tTha/jpLIw+40/xLGvMYI9cvf+BAArea/42N/d7BN5fD3+fK/y4L2r3IIr8esu2fYMSwWZ1H9tx6bItEOFf0OKZXTmqPdrYR8pjhHAoTJ41jls765nR/PAyXjfGZXXbEPEbmjHkyOTMhMSkng3Qy1hmJh19am7Dkkw2BeIodwJIOJKV35+I4Ew9XbvseHwJt29I0hn63pdtd8/4f/wVXnz7irW98hdff+wITuGdehzV2E09kJWBnWh9BHJrCXiKhOHQMQRk8hYUkYmtVW+nsPQmBMsWoORpGc1uOlVkBWpKTyo1dwKdJpUckMGI2NuHHYyEik4egWCNcX1yz2+44PT3l7Oycq13HTx4+4bXbtzg/PeNAcvsmAM85y2uv30MkOt/0fQ4tL5NnctGNGE5P1qzXLfvtFdu9SWFcAqu2wYph8AEffGIMgC70bLdbuq4/7P8K14+f8t0/+nd4AuaNOwx4nj39DB88rt1g2hU2NFhrOT07Y7Xe0HUrVHuunz/D+54v/r1v8tW/9/fpLrf82T//n+g0MBD40je/wRd/8+uT+p3adTgcNnO56d5ch9cdq6s9fggRHZP0X7ZBmLmLwTSR6GgAfujZd1cEHxjCkDDUjHkmDDk/PRunxfyexma3uyL4AetWiLiqGNFBYDxEmPtuZl4fQ8uUpsoHyHInSI5FKT55qZ7auWSsBokIt2ZLTrafxDRuwpCPNUH9h2JS3dTjJuG4ZfIEzXm8YXqcgtRCSFjvsN/TX++wVnDWlPoZz2aOzjQl3/NMSszPxFlCU2aEYieMxPEv1wWDxhCS11vP9XZIh3ADQz+GOlcVrBU2m1Vi548MwQHoes9PHj6hWbV84bW7NE1T2k1FIBiKm00ANdB7z773eJ/tkXEO1xAPEZJsislakvKQ2jkAYrDSIIkFPd3w0rIussgii7yKvHrolu4hjV1xjzeZmCfThJ75MW6eikfPy7yAjlR6M4U/3V84N2YLU63FZj8IETDpnyuOHjH0QLTQSaLZT9T7QjLQBgrNV1B89sBOBlOTNAyxFtc23L5/h0HA7veoKhuJoQTWzRoRYTAxQyfWIAqdhV3fsdq0tKuG58+fcn15xXDrNURaRFz0XK3qTseKKtVMrqakgckkaEc0LAbjCEEwsk86fFxMBh+9GjWFkgg+h4wZ26Zup9ICEk9o5XTQ+pmsoKfM1nup3G55ga67QVJmgnpCqjtJ7S9K8X43RAX46uKSTz/6lNP1GW+9Zbm46nj/k0e8dufuIVXWpBajtK3jzbffQIzgXOzuOWzQ2JNiz5W0Ibt1dsL9e7dYb1aRqsxaGmfZrFY4aVCu2Pc9Iooxih9iaJ/TzToXkFKBuU7V4PvA00dPePLwIY8ffYJXxd6+i7QrnG9YtWvOb51z684t1us1zjZcPnnC1eUTwn5g405wxqHAXj2XvqfFcJJ1A179DNTLdLpSowrtdcf6+Q4zhNL/ohNBpNWLCoqMMTtrJ6tUDUbADx3Pnj0lsnrEPpDnjqLYyuioMM9dpkELGiIl4u6SW3dWrN16vCd9H7LCmftUHtNZ2ZRMmVcr37kGNHX3UR0XkhKb+3oCBrKCXBS32tMt31pmtLG/5VqkcjyT6X/Jq93M2iZvMITstSyT76sNcrq//KkQvGfoOrrtju7qGqNrmsbG+go5vE2efkJUbvM0NGnT5HMtkk4bRDq/7JVd0ijzxJGVoZr7VSOIMHhlvx/YXu8Ztp7h+YAPY4KqijGG09M1ruuTI1mchXZDz6NPP+Pkesc//MZXcW0DEgGBxFM01pJGL/J+CGz3A4Ov+y744On7HrxPTyXwh0i5ahLqJGJwdo2xMXwLzENbLfKLkLK5/iXdv8jfIqnX/V9qG2f95kVyqHMsssgxuenU2DJPLfK3WbRSe9977xnvvfeMjz46Xxw9fs3FygVn7k9w5vJnej4ye/yQjf3h5Loq9PoaV/53eNn+fpFF6nX15pPZi3ze0vlrjLFsqIzrE9AqG8qSTGDJCNxkzb+cdS+48CEmHXE3ncDL0xdPk89Gx0zrH3EoMwLMQjkokqciyUCnxmNIGd/MjgwZMjHZkcMa1idrgoAMAwrE4AZCYxN+kNJuEkblBYbgcU10GOj2e/q+5/GPf8L+8QVn9+7w+le+cHxm1KpwMykhAhj3U2oEDQYRn+ol1l8IiVEh175S8OSDtmLkqCVXXWkTnVX9EQw5f5M/HxLppifjPxMzTkbaNOFwudn6ruPy+SWNa+BM6DrP08trTtbrCp+aZH/SxtZZzs5OQXI45zHUTy5BrmNJfWjVNpxsVrjGYhJ7gLGCU4sRi3ZdcfQQSYwvQx8PSk0w5PjTXV3z8V9/l2CF2+uvEyxst5cEhZPVBrEOIwFnG9pVy2q9wjmHEUu33dF3W975xld47fV3+fG//CM+/svvsNOBvXpu3bvLF37z60jVtSd1MZebluBjz6eqsYPH7QckZAA2fynjuJNKl6zGXK5lAYL6FLo347tH9ucvURMy5tt3O4ahYyUO17ixC5YxPBvPxaiR06/4p+vvyvdVP0kHAlWruSv1l+LBNhkfFeJ7w/ilpH7I+lyuyQ37y4lNLc2tpbqrzpcOU48HpVM4pH7A9wO+7xEsak05xJ3Trf8fh3fVOJJw1TRbhAqnnz6qsxLq7Pf4MeO6wxAY+oEwBMJeEyY74vsiQts4hjQGY99VBg1cX13RDAPvvHY3hhXKLDIwYU/XlDNfhePKrxBNdogYF2aC3UvuW2W9k8TkkVnQQc3CCr3IIov8YuSVHT2Gq9eQpkFDtCqXpWC+r5L6W8q8PgRP3w9475EQ419ZAWcNq3Y1GjhlVBNL3DJIlsBIUxeCj17GGkOQbHc7gg80xibv6fRIiJ507XpN07iiREz1WwX1oP0kbqKqT6wPFh88275nZQ2aQnic+iEqmUYwCEE9qsJ1iIq6EcUBm7alaRoaF1kXejXsVBj8gA67GCu2kuIEU9VdrFEpC1lRjCvTsYjS2Ljw+9AQgiX6zHucjcwT0Whs6HvPdt9Hho/JohmV5bwEBVW8BpQQnRoErCimMHlYYmyxuDGKBlcteVQ8mqy0XVCa3iXjfjT8qyqfXX1K1++5c/oW6+aUQWAwkbnE4HBtS3u6wbYNAty7s+GbX3uTN+6f0evAULyFhEm/S53P2ZZ7t+8DGmNeQlK8Ddnj1Sd+s6xbrjcbTs/PWa3//+z9WbMtSZbfh/2Wu8ew9z7zHTJvZmVmZWZVZQ09Ak2gQTQIECTQ4gSDpFeaKD3KjGYymfgR+KbvIL7QTCaBEkWC4CABhIGNuefqru6ah5zveOY9RIS768GH8Njn3Mysubp6r8xzz9k7Ijx89uX/9fe1ZpiqoW774HmlctA7ZtqDdtS1xtqe6+UVj548om5qNj6EjEgm5eR3xShBxHLZPWNpL9nbuwsIM91ixGCUR7Thym6QYYWvG6r5Ps3skGGwnF9c8O5732OhWxazA5ZX11xcXrA4OIaDutwu5Xf+IJDY8xR9RxhPzgajOaJj3Ek1boqT7iil270xPudgPatNR1Nrjk9mNE2DlwHrhzyROB8VIzF5Y+9G3TEoctZzfbnh6mpFO3e0s0L5SmO4yPyUnJRigI4bjqwIq9GLR2A5u/h17Nt2u3+l14T68MnVJcmjSSJNlAO6yBfpFYHgEsa+i15H9JiXG2SOGxnIeyeX8x97gBQjQ4SriytOHz9ltVnGtB3O2viuQCBTSue2E2JbFj0q888kvG/YDAybATfYQNIKrkiw1uEdOOXzJmcsf94i5VJ0a8fVafA4slmFdUJrFb2YjO5CQwva8OM93gnDIOAd9ukThosV66sVy/kCa8L8tO4tdghemzyBuS2DZbBjG6X0XWwrFTu1hIkv+vxTqLhGWSUoranaOjCxJbp+VdMQTjv54aWua9544w2GYfj4mwlj+uDg4Mecq538xOXiffj2P4H9F+H+5/nBVrlPIp696vep9YfPvWNl3+Rq+NUf0/t38vMmz54949GjR/nz4eEhDx48+CnmaCc7+eHFOeFf/+sHvP32AX/xL37Im2+e/bSztJM/47LQf4JuRgLJbq3dyUfJo0ePePr0KRcXFz/trOzkOeL6GSiNb0tDLzdhO8iG8xKwdTFMrPcecR5RwQCoJRAgMoa8lWw2HGcj5GjEtfHvYRjwzmdP0KN9OaSijUGreMCpwI7GewKOHDCdZOJ0+CGE7nbeMTiLVgFHEIFaqWAqlJGg4IE+2wsDiaHS4bCZUuFQ1YNf/CLtyQnr9x8xnJ5nnKqUCdRS7JFG8+JolCyf0kLwxuqDxw8F4AL2G84cBWTTWkdvHa44hJO8F5TvT0hwKGdCfnIQ93iXygSbXAupnQiAerIHKKcYQzCHN1x311g70Nb7GF0F778Ju0GhtEbXVQxHDLPWcO94j8WsxnoXMbOyPQvQTAQlmlk7D+9U+dgPyYtw6lplXRtjqOoabSqUNmjjQv1owHoq8aBCGHLnHHsv3uPo7gvcee1VnJqaxFPOQqgJx8auQGnqeg4IRhkUIZ8oRecs4ga8NqiqxlQNzjnWm47Lq3OOP/MaJw9e4nqzYr3ZcPLKp7b6xth1PtbLwy3fTS5vfZ8OcgYvPCobt2/u4kfSTFkLzsEwWLRRzGYGow1eHN6PXnQTeUcYY0RlOz+QDsh1naXb9JjKYyqZPj2Zk4rZpBxYZUEFsoecguiQPC2HrjHiy+OX6e+AcSbCWPAGsoX63pgnJZcrzRd57MR5bMrl8BRsjhuSa2C77FsY8jt/9Ke888df5ck778b7fba1pbYax3O0rAgUs2qeLsLfPhAyBhfTCeVXymPteE8aZ9t9oqwYO3i6VfBObftkG4vzWBGKPbTHaP8KdgOBweOXS9ymZ+gG+srh42HCwfp4QDW+y0bSixvbu/zJuHz2SkRey0QIIZciAVCbEXMPbbkLMbeTnezkRyOfmOhhNwdop8FNjVijEn37c0l5dd7RD8HwXyp7WimqqhqNrvk5wSa9MSnSyQuFt0F5dMH92XK1pB8GahWnx2Sw6we8cyz29mibpjDwFlmO6eGDAUkVSqYTA2qO847NMCCuwutA9Gi0DmUzYTF1fVDm1wgWaB0gQl1V1CIYHUpmEXovODvgh018d6ypqCNkekteGEI+x33KdDlJtxoVXV8ZA85lhVipQDxJJ/J76+g6G0NRPKfhCAq6I4RyCIpDIOhE8zujEhK8pCTFYmS3BkOv957eWvqhi4b8tLnxnK+ecbm6pG4OMNUcK8GA6mOsQ20qqrZBGw14DhYtrz445uhwxoDFZqLHtNelfGlt2F8cxpJsQs8ShUR3fylyY7kw101DO5vFOItBYUd5rLG4ytHQI9QYE9pxs1lxdn7G0ckxvQ9v0gjK+7xcaxHAsbJXbNya2ewAJYZaVWg0WocYeGvXo+wabwy6nVM1c6rNmuvlNU+ePOTle68w4Fmv1ixPL+jrORyEOraMwXeymiC3OXn7aBlrb/yMJMZt8IAD0ZOHVnlD6op7VQzZ4+MX3gfm66YfqGvF/l6DNgaHJTrzixviGIYkKvm+zEXsXN47Vque68uOYXBboyDdu12o0YeLi/1vwljI1RViBoZHXOEZYDrJlfWTqfCx5lOfIrZ56VIjxy2XUCfjpjv8hLAgxcmBLbJHnrxkTGfcYPpJDkfAwufsr5YrTp+egvKhk3gCcc6NHjoUkpnF4XTLqHSWG4dAhvGBQNHbkYghEuOZysiKzwALNyXOaUPnWF712N4yrB1GCcYEoodH4VzYDASxeVMEMf6vdbhn57h1z2bVsekGhBqloLeOwbrMGh+sjS4+XV4XvB+vQ9hY+3AcJ7SXSuBBXMEkeXoyiGhc3JQEosf3O+p28lFS1zUvvfTSTzsbO/lpy/JZ+LE93PsceT7M8hwU4/sUEZjrbzHX3/qIuzxXwy8zrrY/mnfv5OdTLi8veeedd/LnYRh48cUXdx49dvJnWpyDr33thN/5nRd56aWrHdHj51K2zUA/vtVOBFr9Nq1+e/L+3Vq7k+fJ2dkZ77777k87Gzv5CHFDi2gheF+A2y3GjHhGxIHyaep4iMc7lwEYIYSJ1VrdkpZEX57Fq7wdeRnh2DXeO/q+wzqHLjET7/E2XK+bJhiVc763ECHvSZ6VJX/2eDdkOGpIhwhVwBkzcUSF210MFzGI4HwE50XQWocjdRI8vJ689honn/k0H25+l9OnTxm9DkZzr4eb+MPE2h6/ujmfK+XxjkBoiJiUUi6SanyEnaIXVxsQ4klaW7aAcFhzPBEfoKuS6FEgVoqMpU0OZ8XDOdY5nBuyMVti39j0KzbDBm0alK7wCE4g+c0VFQ2pEVNrasPhfkvbmIxx36wqnzE2pRRN3cZSRC/EEjHQFMah6HoiHm0MpqrQKpBYtFYgVfCaqzw6HpRUSvDeMT8+5uTeAw6OjlKKMeR3gOogrXyewXWIr6hME4zEEoPXRAx+wCJ+ACUoU6F0hdYDfd+xWi154cFLHB/e4erqkuX1kv29PVKIkLEmxva6Ma5uW3q3vssY8o3vU1+Q/Jyo0GmCIb/oDzI+hR9Dcw/OoRGa2iBKxRb0Y+oFhkxMuRzT4U9P39stO8jt5IFJqVKaRfpjWYrfmewxhoXPz+Wntua/PO9tz4x+iiEXdUeBIeff3k/qPs0H3kv0DlLoUOKLik6Dd6t90vcCOM/j77zN1/7ZvwrzZz6g6eMtyROSTNp+ssf1xa9IDnMp1LpPnpXjM9HmN3LInoOrxq+d9fSxTd3gAgFKS563RvsZBGw++eVQOB/ft1rjh3gw0DoEnQ81uog5p3kNV7RpQSJMuHcKxZUbJK9bMT8Qxmlcv3JZd5jATnaykx+RfGKix9FxICuIjpOYFIsNxYqytbp7F4xnrnf4PhhOq8agFDjX0XcO73vScgKE099E9TVNqN7h7EBQnoNRsR8GnLPUdkXlLZVUhcs9wITJ0+gelcIKeB+9DcS1If4j4rKhM620Fo/1A95bvFg2myUPI4tx6ANT28f7vQ0ki3WcpP1ihtGKbt3jnOeFl45Y7Lfcu3+fey++zGFjgDImGQV7VhiV8BinDbLB8Yb2hGaz2fDdb30D6z0vPHiVqqrxg8YLGG2ojI4n0UP9OTeQTvGPi2dUXkWCpxJR4BVK1eh6jugKT8+UUhAUbmM0RucIZAg2EBnqFkRQ3YDWhoeXT1CnFXcP7qBE852vPeb9h48xf/EE9XLNpt9g+9hWEtpKaZ2Z1Pfv3OUv/OIvcXG25N3vPKJyDf7TbqscqWHLekoGWhUM7D7UcbkJCT5IJIZ50TR1zbxpWRP6rXMb8B2iDdI0iNL0g+Pqas2TJ+eY+l32jg2VqWmrOfPZgvt3XoxGe5gvDvilX/xrnJ0+5f1vfovNasXF2TO01nzm1VeZz2c8/u6f4hQcNEfsV3PeUzVLDFfrnurqmq9+7/f54Pxr+I3Cd4q7x3MG7vPk7CEPn77Lwf4d7h4/oFGauf744V3W0q2qhQ9jD2tjlxSaWYU00d0dwcOBElhtrrlYL1l2q3FwSdj4KOXZmxteebCP1opuAN9tGE6XgfzlPTp6WskefeK4H/u7p+s2DH1PO5sBEkhi5fYkzR0+GvF9CisVwosIKpKewukND7GvjTPQWA9p0xk2AiFcoE/8iAAiCBMWcmLspj2FJyh7olR2dZnisaaQJ0oEHTfW4gqlWKZ/5xbz4f7kJs97EB3SVL7YRgmTjc1IZgieN7zzGOcI4XdA/OhicnzE42xmMBA8XIx74eRhxTmfvbt4CWkPWvIGpdzq31TVRxXeeRUJNuGzdVDNWvaOj+g3HZen5wwOnp6t6PsB5zxaPNqPG1PnHOeX51TzmqO9AypTYQeXw9PkjWPCJor+NaJAnoQnpXSVT16NBF3V1LMjtNIgKtS5CpkWewM62MlOdvKjlKvH8N1/Qb3fs//gip57XA6/hqf6iWWhVd/lbv33WbtXuRp+heesoDvZyU528nMrWnt+7dc+5FOfuuT1189+2tnZyY9YGvUue/V/Fw0yoxg5Q8nmJ5KH3Vq7k5382ZbZLIUwycDIFIBK8QHypnvElcOp8YCzSiQ/BHuqxdqIE4WH4r8+HkahMOz5aNSFcEgkGhi9Q7sBhUOLnr5eBcxQiQ3IRTbgMRrs8ma/MOqKL4riYv5cCPN8HrzOOGeniGVMe0jG3NqgRLCDw3vY22/wUnP+9rvY5ZrV01OyVTjiziPuU2LIFHbsLfw4Q7+KwXacPXuG8569vUOU1jhReA9KNFrZjO/mML/5FVKkNx4aEhFwgohGdBXdgrgRey4YEsEb94jBCS4QGSKOKdYhornaLJGVZt7OEBSnT665vF6iHsyQQ83gBmJU6NiOpYcBYTGb8+D+C2zWPRdn12iv4ag0eCdjeOxACVqWESEsiSjTNgTnI9Ic816ZiiF2qOB5YkCUQqKXb+s8XTewXG64fPxNvvOv/gUH9+7x6i/+Av31ivNvv8vy9Iy+76n259x/4VWoNJdPT7FDz2a9QkQ4OTykqiqWZ0/wAo1uqXWFF02Pohscqut4cv4BV5sn+EHACnNb4dhjubrianVB08yYz/YxEY+dSGkykOlXeVxsQ++pYrzPGLKpFGKCt5XwTfByM7iOzdDTu77oG6EvC56mUhzuN2FcWPDW4lbXeYyr8iBWmemikawdcNZhTAUtAcPLJfE5rYR/jgb8iC8LiJ/4OA63iJ/wncr+48s0S5uOxL8T7pjsFIU5Y8Rz03jxuS96iBh3sNmMRU25G8lZk7bItq7xPdHtBeLDYcfUVtmuVxw69GWoqni4L713JHmUdsA8GMtfMb9j3QYPL+k9gpJiPZjYqW4XH5/Dj/XoHajK0M5a7GDpVhuc9yxXQ5z/Q29RBQnHe896s0ZVmrZq0FrlcPAjr65opGmB8t++OP2aWiR5A1JaoatZcZA0XEt1v8OQd7KTnfwo5BMTPQ4OEwFgVG2K+enmrJR19GAodNbhOxeMgVUgBDjb41zP0I8PjDEP0+IaTareh/h1heFyGHpwjtptEDy1hJAHSkkMfxAWM+sGnOvCYuOIk2xi90GyzwYloXD35VwIreIHEEffdTw9v8C5ENIkL8Q+MLd9Mg4qwZ4coSrD9dkVbhiYH1SYWcWDe3c5PDjGXZ9h11cThmdexoRSFSAv1oV3gfF62Ij0/cD773wXi+f+/QfopmWQoMAYZTBxYxTqNIa/ubFwpkVY0EoYYtqiKlTVBrKDHwgsbpnkTWsVDMRJIfAOBbRNjYjG02OU4cnVMzhX7M0WtLrl3e8+4xvf/IBXXn+Voxf2g9eP3k+M4krr7GHgzvEJs723+NM/+Q5f+b3vcrx3FA3xyfyeanKqcYZ/VVBinAT2JmnVDqpXUNIDg1srTWMq2qoJRB+ihxg8aA1Ng1KavncsVx2np5eIGai/t6StZ+zPTjg6usvR8T2MUmigbRd87q2/yNmzx1w/fMRZv+H68hytFId7X+Bgb86Xv/7bXC4v+dLnfp3FwT5eVWzQXHcDZrnk8v134fEVd5oXOWrusupfYgCeXT7hW+98hRdfeIP5/l0wMNPmVpXohg5+y3dlf8S58OPD2KmaCq0EU+nJhm499Jwtz1n162kqcXzNWsPBYkE3eM5X0G96Vs/OUAiz2SyM16Skp3mAqHDGKWHoO/quo2lajKlybMVEeMhZjiSK7AnDB963eAc2zA1eJVJISF8lAsNWZaQNbSJuhPryeEnM3TgvSeynWXmdkjC8uHhf2gCHzT+JXBFdZZZTaSKeBa+AkfErPte5tcWcGO8v1Ou8ERjrKIx9hwunGbISP7pKTFiAc+G0gbNxvOuQv0RcShXioju7SgXCCICX6JZyEiC3nNFu9LI8/tImxBNOwbR1zcG9O6yullxdXjO4gdOLEK7LOYdROhM9AkHDcnl9RXVZM6taxAVXo+nETG7E/C4iMJO/nPBjRgWdXH5jKup5XU4huZ+Hzzs1fSc7+bHJ6imsnlK9cM3Rq49Y+be4Gn4Z/8lV2h9aWv0erX6Pi/4vcTX8EoUfrZ3s5BNLAsp2spOfpJTnNX4YUQq+9KUnfOlLT374xHbyMye1+pDj+sts23x+krJba3eykz/b0jSS98gjhiwF3rJl3Sow5ET0wBIOmuTDKA5vXfamWTw2GiazAZccOjpdd/GQjo4enXXEHlK43oSJOB/DQ8SkJOW9PCwnCb1KDxKNlgnn8Vhr6TebsUzpaQ/k0+IEUsCsRZSiW3d456gahVSay/ce0j25wPfrgOkUqIov8jKxFst2xUYMuVj/nXVcnp/igMViDyUGF1EPFQ//lW01Ca2ek5YJFpJrRFQ4IEfAlKYW8RjWRUn06hErJB7SMlpF/Dccilp2K9gEb9lGGS7OVzx7dsnh8SHtfhM91CbbQcQfM7gHs9kc0yiePDrl0QdnzKK3jlSuab2NVZbw9pjlbNxPnWL0GUy2PxilMEqDTp4/4iEgEYjhGpz19INltd7w7Htv891/8U946a3PcfTqSywfn/Hd3/49XBfQ+NZU3Ln7Ehihv7pm7Qa6zRolQlvfpakrHj59zKbvuH/nU9TNHEQzoOisQ/U93eUFXHfMzB6tntPbfRyw6q45vXjE3uKYqlmAArMdVkW2fpe1dsu10eadKiziaCbYI5RK/SPU6+As637DYIcihdHeZIyiqWus86x7sNYyLNcIYCozkovSO2WSiwDXOYt1FmMMSuvofZgb049P+GjRsj6lW+Qpf4qVcBuGPM5FkxrLPSeQwUgTy7T+PDEaeDiymLtm+TlhjyLILfyr8u+QzdFDtMuhkCTfl8kmcfyMXLmY4zh/OTza6+k8kOfN4EUk3T/al2AMTeLjWArznorlTF6OwrwwTfwmhjzW5/h9yH+oWY/RmmYxp990dF0fvO93w0hYEz1J2XvPpu/QG02lgh3FR6LHZNa7gSEXv1Odb02Sae1QSqMrPaYTn83rwc3ZdSc72clOvm/5xKj43mwPGN34i5QzWfpzNP5PZmMP4gbEbxALKrmbKlejMpmc1HQzYMQVa6yn1gYRaKoZWoVT82ECVXGxjwQRO4RT6VHXSASQlMGwsISyqah0IGBRNE6zqQTnZmGjcRAMyKu+w3swKhq7i+KLCNV8jtKa/Xl4rqpquo3l2eNHLC/POVzMmM8X+NUVrutIbubGiki8z1id3uL9Cu/WJJqgJylhlq7veOfDM3prefDSQw72VzSzPSbeOQieLJxzOGvjIpzCDKQfl+stKTpeGaSaE8LbDIyWzVHhCbuv2DeUwtQtVTPDVMEgf3xygK4Mj9474/zZihfm99EHhjsvnrByjrcfvc3D5dscuCNmzHHOoUIgnRBHMb5HK0NbzblzdMQbr7/A/ftHcRMgt/yU/TN1RD86IyklUzUtohW6rtg7POTO/Xs8O33K4C19paCPRBGn0EZhjEZLh7LPOHviOL3sOTq6wxuvf5br9ZKz83N0panmIfzMrJ2jZU3XOYYBZnuKuq5YHC/Y2z/k/otvslgucWJYblYctnP04R0OZy1zozi7XLFcP8PWisu64/7dN9j4Hicao/cYOsvp0w9hccDh8f1bCRzfryTSxOAdvXNhrBAcF8YRExTszsGVhc2o0OctpUA3DFxcrxh6x3rl8EPwEqLipsgD675DRQZuIE2MZAXnHNeXV6xXK0zdYKoqjvXwoqRf2cKgP7qODG0cQtx4vJPs8SfnMrKvc48pYoGm8ItZqctdKAWuKTbX4sL86Mr7IllLjZqfEokErDHEiUubIRcLc4MIFsZtmr/ypiLOiSlUokpei9JJGO8iyWMMd4IHNzj6zRDLr7Ax5mA5lyUGTJqTbfTwocabAjnMaJQWVGXwzrPpLNb2MRzKtM5ymbc14eLPTGoThXUKxFA3DbZX9JsVPsX2khCvl6iED4PlyZNTeg93Fie0pg7ejFRwierSi1SYD8qZLOwxxrobN3hhwyNao+sGU2mMEryD3qb2jP3UDjsVfSc7+TFKvdex98I19V6HiKeSJxzX/4hE9DByjpL1x6Syk5389OTy8pJvf/vb7O3tcf/+/ZFAuZOd/Bjlww8X/I//4xs8eHDNr/7qQ6rKffxDHyHWwh/90X3ef3+PL33pCa++evEjyulOdrKTnezk50FqU49GRG5CcFPvCVsYMoRDOgzgyhPkjBv3LUl4RX6blMfBwn5eq4ChGmWip+eEb0smcnh89AgdkYNkgNx+p4yeIxIuc+el+/zC3/h1zh4+4Tt/8BXsEPIfQlAETDpj6kWlCIKqKkQJdWXwHrTWeAcHrzzg+MUXuHjnXZaPn+aQJEVGturFQza4xoOLEQzPXkAIoVjOrzY459jfv6ZpBrSpR3yvwFUDrpQsyskqWzRWruWIr4hGVBWwaylChidAP+c1Gt2VoLRB6xB6RClF2zYorbi+XLNZ9exVC6RRzBczBu85vz7nqj+ncQ2V1CRPBxDDTsecKRGMqpi1LcfHeywW7aRskzqEsV9ud66C1DIaNBLOLIjW1G3LfLFgtV7iNh7RQwz3IHgriFYBw8QibkW1V7P/5ms09++wGTbYCmaffhGcQ1ea9nAfU4UQEtYGvK+qg4ebqq2pm5bF3glV3+FF6G1PYyqkndFWhkoJ601PP6xwWui0ZTE/ZsDiRaGkxlnPenkJVUM725uWe7Sn3/zutmvploht2vhTkqJGgoGE6EedS1GQcoISx6t1jk3f46xn6P2I0UZylgcGOyBiEF0cSCOFlXd0m45h6FHKjLaiAtP1hANnvujKo9kp9msf3P06NbU1ZJxT0mc/STf8Lt4Xv/RFGvnu5NnhxjQzYqbBk0f4nbpgtsxtHzbLY8xF209GY8cHC3LGGG6GPA+OBLWiXM7Hw4CAF84fPuLrv/UvObh/jxff+gyi9I3p+Qa5JJZbRbKX+EBisUMg8pV0tvyESG7/53W8sfcIzgV7l9Yabwmhp8LkFNPL1YpzjuVyhfMwq2fBzldOCamy45zn83um83iJIefE49wW7HJxbGRbQfQ/7m3RJ3ayk53s5AeXT0z0WLQLPND3blwAs2K3rQglpTIy4ByI6xG3DgY3HxVoVyRUzPeiRoZnYr5JcU96zBiD1oq9/T200XnxSKQGa0NoF9v3MewL4IO3j6C8xliB0f2+jsqCKMlurBzCulYMPoSKMMYwOIesQniK1lQoURgd2KQ65l1rQwp1ALDuevr1wLPVI2Cgff1NDo+OscOaoQvx+qanVAplHcA7vF/i3AZPoSiHGslEj82m441XHjJs1tx7UFE3NUrF0BCiwoJnXVjk4sI3alWR7OBLskdQ0jEzcGu83cT7S6UWEtEjxS6s6paqadGmpWlbXn7pFZTS/OHXvs5m6PnSZ95ib2+Puw/u4Gc1X/7Wv+DDr77NL7/8K7x68houhtnwXrDeZ4XJqBD38OTokNc//QInx4fZIDwyOLaV9iRlfuM3vqzJELxFaY2uKvaPDrmz3LDu1yzX1yijoRL8oPBOI2i0Vpno8ez8ku8+fMhLn3qZ47sn2MFx/uwCqTXt3T0O9vf5lc++hVZr+s7RDzBbaGYLw+J4weLgiPvrN1kuN2w211yvVxy1c46qmrqtMEZzerni6skpV8Yh1YrXXz9n4zscCqP36DeB6FF7D0f3bt0Afz8SlN6gnA/OMvhAwNGiSP9lRbnzcGlhM3p8kaSuiKfrLc/O18EzynJABCpduHjEs+l6lBFmph1HQ2IPW8fV5RXL6yuO79zFNGYkesTcJq86wQlHaO/0W3xQ4AJ5KZEXivz7qHBHMobP2lfoV0EBjV+V2hxx05fnqPi+CGqIjJ/DVSH55FGiSFSUVM9CisuZz2fEfXmhLIrKe82kqHuX4ryO4IF3KYSNi2SxMcYgBGW33/SIaMKJExfCyShVnGqRidJvbXDhqYzJRRYRlDFoo6ii9rq83iAqhokpvY6Uf22RPbJinAsXiDTOaxBD1YRNeb9cBqJHFKVc3shZO/Dk6Rlr6/nMSx3MF0GhFvBO4uZqrMv8V1ybxjodVfhYyEz00EYwyoWNq42XNbH/2Ul5d7KTnfxopdnvOHnzNE+9lX/CcfUPf9rZ2slOPrFcXV1xdXXF/fv3uXfv3k87Ozv5cyIffrjgww9f54tffMov/uLjH5ro4ZzwB39wn9/5nQfs73c7osdOdrKTnexkIlVVA4RQK0lus61nbKXws+AB7xA/jLdlTCTeX6QV4KS0lyeSIcZ3pMeUCob2uq4RJYXJLuA5+YCMdXiVjJlkPCQfSIwYkUrYQYSDTh7c4/jBfT74+nf44BvfYthsUCqE7V33AZM2SkWDbTo0lTCXET8GGKLnkqNPPeDFL30Wt16xObuIBOHk1fiW+syWYg/0geyRjZTka9ZZLq7WDNZyfHWNswPzPY02GnHpAGRArkaD7zbulX4XWFWqKFVBDIU+wWLLNi+wJqUNyhiUMhhjONg/RJTw4ZOnWOe4d9JR1zXz/Tm+0jw8fZerJ+e8uP8ih7PDTPTwXsqcoKLn3Vnbcny0YNY2RT1vdcgb5IUtXCd6VRijOAQMXVK/ahtmizmDG+iHHnEq4IsuHKwSUcH7h1jEr6j3qkD0ODhgM2xwlTB/7QXQgpnXNE2Drh2+CyGLrANTK6pKUc9qqqZlMRxT95bBdnTDQGsqWq3RJuRp1Q10yzWd8qAGjo432GhYVqrGWsdqeYWeAbPFtAJug5Nvq7qi3jIK6wPG6byPB6pif6cge1gfcOShxAt9bh/rPKv1EDDFLoR4DtGVEgbrGaxDlKWKHmSKgYB30HXBK3Q712HslV44MpFju6nHD94FvFZEkploYp8qDfSekogg26auos62LxTl9yMaKQkyjfPj6B3DT+q5FClSG6/58f0Fhpxx5nFKy/h7SfQgvzGGSR+iqyXg/MPHfP2f/isefP6z3P/MG2itGRHV2B+iEU/UWCfBe0cYDzq2Za8spJAp22MvlW6rvJlzlut0xJERhTbBU1Ei3eWU0qE/7/E4lss1g4OTfQtVuSzFupJyhRoxZHJYH8nfj82cvBvpOO599Kw97Q9lPe9kJzvZyQ8jn5jocXn5FERh9AIRne2aWZOeLCflnxKeq2va+QzlHYLLLLZkJEwu60RFlnVOVgIjEDLbOs2cRocYb1prtNIor8hukEXAmxAnTxTeVZDeEY27STfwScGMijpJcfDhdHfbaI4OAtNYiWIzOK5j3MS2Du8Ik7Ywr6voXURPGN/zWgUlZePph0goYWpInq7I5S8BHIoeRVTSJ4teWLSNVixtz1e/8acc7M35grPs7R3QzNvA3I7lddEY6r3bemHc3Ijk6APeBmVZax0PwNtMBBmVdY8YQbRMFzUPyUWYVkLTVHzxrTcYvON7jx7zzukpIm0goVw5/JOe7qBjPQuu20qXi2NfEkDRzubcvXef+Xyv2AuVqsT082juJ7phHPOfwzkEqjVKhbps6opZW1NXNZWpI7u8xlQDvlV4b1leX1HXGuv2QWnq+YzBdTz88Jv0neX86RK0on7WsFgcUHcVQ2e5XK1YDz3D0DHYga999WvM5x/gmCNSce/uXeqm4p1vfo3z83Pc5Qrve9bLFbUs8Gi87fnwvbf53d/9V2xW1yyvLlnMZmi1R2+7TN8pIxDepqd/nCit0cagFRgc+3sL2tmMpm0IdJyYqqpQVRNiccZGcd6zXi+5Xq/p+g676REXwnookRDyJxO7Rq86E6VVxnlCa43WJowvVbhm8UmBtDjbA1XYT+VSJI1WkWJ/qhibcXoyYzwFgKhMVoudOZIFwkkGpQMBzUdSVCKYZVJEsdEJp1FG9S97HCnGcipjnhO9J/gfKYdAVGFVVs1juxZ9X3zxnRsfK4CDRG7RWmGMKTxdkNsiuQVMm4sybyKJwhM3aR7sEOLn7h8sMFpzdbFms+7jRiGMt5EPE3I/hpwc2fAleJPmVUP0xtE73ODyXHZzdxnILuvrFcZUOGcJJ0iIh4SKDUv0/BJnvfG9ntzu4zYxeIxSWmFqjQ6MxZiaxdqBzSZ6EBADkz61k53s5MchaZjthttOdrKTH0SMMdy/f5/ZbEbTND/t7PwEJEyWT57M+Mf/+FWqKuwUDg46fvmXH9G29tanuk7xh394n7OzaR05p/jgg71bn9nJTn6UUqsPOK7+MZ17kWv7Rcbd7U52spOfZek2S/pNx6NvvI0bLC++9Rna/eAp+qOBqXBRaR3CM3if0ImpUa/AkKchbOPhPZJRdJSMPcl46GaEDwPWKARsEx8PzySiR2GgHP2GjB5fR2hK2L9zzBf+6l/C9QMiwvXlFd/6468ybLoYmmQ83FhpjakrXnzrM8z293NenQseOI4f3EerMRT3mNdCbtgIo2EYG3HnhK1O614pwfeWJ88e01QVd72nrhuMMREjJ+NXKezN7e2VcLFk1I0HLG3EwrInj4BXBWguelKlyFJh4BUFRmvu3T3Gec/59ZKL9Row4VBS52FpsbVlqGzAeVMiGeOVnEVTVcznC6qqnna/nIGRYBC8n5TeXyOifIMRMGJmwXOIpjLRPiE62gpCeHldBVys7waMFryvQSlMVeO84/rqGdZ6NsselKDXmnXVYKzGWUfXDwwuhmJ2jidPnlBVDZ4KEc18NkcbzcWzJ6w3a/xmACxDP6CpguHbW64uznn//XexQ0+/2VBVFaqpOXv0iNOvfoe9k2NeePP10UPGpI5uqbfyWu6eKuBnAgpPU9ch9LYZw34EOE8jSqcYHqnqGfpAWkne2cWRPVmM+HEafwm/pECSUz6S/UcVRKqxIGFOcXhnIQYumvbwNO5T+Gw1Jlz0m9JTxdhDxorJYZskkVzcOK+k3ynfKWl/S6X7snSx+ifjdLx+25RwK4bsE4Ysk7dJrsD0OeDhIayT2irndnpjrYQ8MqmjJM55lAh1U6GU0K0HbDxYPB50LPNAQbIa14PRa7WEsDeMYdG9DdhvfvYW8R6GbkCpfnLAMrZULmc5/UmeD0hXt+o79k0lKK2irXG0PTnncC4eSJfCtrGTnexkJz+EfGKix9n5Q5QyHO7XGKPiokSkU25JqcQBIJi6ZsYc3AC2A1Q4XR1nfh+NaxKNvznVaNEbPXuMyrXWYaGtTArzkBSwMHfqGHtNdKmM+bw4lyFcMqPOjwbduCRTGWE2a0P6Flad5XQTpvtZW6FV5FMr4XDeUBk9WYjwyTAKT84d12tBKwI7PRpgpXigdBmWqwGP0KNkKC6MK5wI1EZjbceXv/KHNLVh0cy4f+8+d195JYa1ITAInWWwNhpft72DjAu/9+FyUKZ0JKdYBEuOO0kIU6Ey0SMp1Z5kClYCRsN8VvOZz70GWvH//Cf/lHcePeFX3/oS9w6P4cLiHvZsTjYsF2uGfsBH4gVl80VawXy+R9UatJRd+KbRtyyRR3BeooeBZAD2BG8p431aCZVWzJqK+awJSqmu0aZG6YqqUSg9sLruWF5c0DY1gdBqaBcLrOt4952v0K0dZ0878KFvtLMDrs40Ioar1TVDv6HrO/z1wJcvvoypGl565S0ODu/wxQdf4OTkmLe/83WenZ9yefE+m9U5R3t3WbQH2EjWefc73+T9Dx6xN59xsD/HDfs0NcHtX6wRfUvtfFIVInlqMJWhEqjFc3ywx8HxIbNZixdFpjDoClXNUKbKhnvnHKv1movLSyKVA60UptLZ04yK4UtEApM3jE8/UbDSHKCVwegQW1ES0aJQ8ryzeNuDtyjxWaEUBJQKIIFP4Z22XaX7ouOT8+ES6ze683DBXUjYkEhU2iORQ5IvPsZNa4q9CuM8AArnHc7HKKiJ6JIAiRy2xk730iqBEmOZ02YiNWy5x8qKd0nSSPWpwhypjQ7uRG0qt+RyFY+TUh5dzOfZGPHCMISTDIeHe8zamocfnlJM7jGhUsHflgAehH3/CH4oJRgRBu8ZOosbbHDTqFJK5XYlxJpdXS5RKKwbQPzoLdRHjy7JcZFnkpswN5RlT20Z+o/SmrrWaAFsOEnj/cAwbFhePkWUpl6coGQHQO9kJzvZyU528rMsxhheffVV9gujyp8HefRozn/3372ZP7/22gWf+9yz5xI9NhvNb/3WK3zzm0e3Xt9FHtrJj1sa9Q5N/Q5Xw6+wtG/hd0SPnezkz4SsN1eszq/41r/6HYZ1x8EL92n3FqORdCLJADZeUFpTUYeNu0/hZsfT+COGN+IoQRKmMuK96ZnktVTreEgnAigJNxGSG9dycRtNoGXYB7+NJRRYzNH9e/zK3/7rGaZ4/O4HvPutd3CDozJqtBOL0Faadm/OW7/+Fzh55aWMIafElpueTdcHaDyGkBixmKLIt9RpOORUePCSAkMmHMhz3vLw0UO0VlSmYrFYMD84GMktEvAul3Gt8ieh5pD90fqE2SfvuxFYxjN6VvXBtpm86RbFSD9KoKoUJ3fughK+8t23Ob9e8uDOfeZtCxuHv3IM7UBf9zGchLtZD4lQU9Vos40DyrQRM/44Xg8QYcCNc/7d2GdQIZizUoIxKhA9tA72C6UR0QEvV4Hk0W824bCVC3Vk6grnLRfnj7CDZ7WyJOO/qRq6dchzN3Q4N2CtxfeWhw8forRh/+AOTTvn3v5dZrMZ52dPWa1XdJsrhmFNW8+pTRNDKjsuzp5xeXVNXRmausL7BqPh/P33+OBffoUHn3uT+6+/NiV6bFdTWUepS8l4XzokpQW0eGZNTdM2mMpADNEe+oBCdBWw1dwCnn4Y2Gw2jGM0ek9PpK588isePMxECSm6ZbwuKodsSQSwyVST2hYf8Vwm80yaQcZ3bpV/0tUkmsKmGHKyk4jX+Dx3Ba885cHVdMguEI3yt4U1azygljybT5/3MGwNAZWw4JwI2xhyKeP3oU5LW5UIgaClIl7tx3yHqo/Id6rg8qDh5GUCXmLYcE/b1lRGc325BvppAT4SQw51LT7fGPtHmOudDzi3d/Gw4I2UYvs4z9D10b4Qx3mGmBPJK80Dk9qb4OaTTMc6DDbOiOG72E99IGz13Sr07WpW1NFOdrKTnfzg8omJHspUKGWii6zp+pYVRWFckEb7LFoRyBjU4DQ4A4WBdjSgQoq1lvXPrJxH5T0vNqCFkZWZHihc749z/aisFWsgZUFSPMawAvrx/UnBTvep4KVged1hrUM6F4zVlaYyCtdKfEZyfaTnBai1wVYusMddujxuPmKR43riczql+kwiUxRWylnb8IXPvsrJ0Ywv//EThr7j7Xe/zfnlE2gq2naOje61rBcGX3o72JLobkW8RbxFK09dx1f3U+U81aFWKdZgvOIDqSLl2sXwDU3dUNU1r79wl1mlmFWerrtCG0M728NojeTQMCEm3zDYbGzPShYaLXX2ohBk9JpwU0Y2aXQ+OLkW+oBHxKGVxugKrSuMqVgc7HPkBvrHPcv1NQYN0mL1wForHJ6u6xncgNge5y3dGjZry3q5QURoaoPtO9bLx4GN79eI71hdX6OU8MprbzCbLVitrjjtVjx9+hogbJYbXOcYekU/GFANup5R1RWq1sz2DpktDqiblradUSlPt7zk/OKUd549Zr9peWHvIGxoyyZ+Ti09t0uI0MxavJ8zaypaozHR9VicEgJbW6aqkxCoOck9pVYarVTw5CGjR498v9aoSNBKLtTGuUKo2waHx5hqNKb7UeHNsUORMFgJbtFcPIEQlHuVFfxwPZE0RnIBBDeBU8ZuuD95HEkXc4gqT46L6BP72qfYkMFTDEIMpxLA9NwucT5S4wCKxLc4L+R5Kp4qKRXNCfAQ0kmlC4QIVeiZcTOgZAyRJdOtQ5qzRkXTT36PoZKKST5vMgKpr2qaG2F1Rhn/nrzhBjBBDiGjUj6z4j6y9svE8mdrw09qj3Q9tZEnb+ZSjSkV5izn3BS2yPOwymG/IIYBchY/dHjbBZKI8wyrdQgHtpOd7OTnXir1kMPqn9O7+yztZ9mdMt7JDyPr9ZqnT59ijOHOnTvhNOVOfqxS6n1/fuT7L2/Sw59z9YfJzE528rFywz6wk53s5M+ESDqtz4hzTgeyn8AK5XqiJHp6RgV8tfCuUSaRDiDmtTxBlAkfUdP3qcmEMr48fBsN0LKNNEwxm7F8kvGGDC0XEEl+RQRe+97SbwbExkN0WqGUx5kxT+kAYzqVDqEejA51MZ6FSrj4lsG2qKCMR2cMuahj8RijuXtyyKw1PHy0xFnL+cUpm+4atMKYKmNrLuK7U4ceMm0758G7gLcKaB1f5woMOeddpjpYeTmlGHE2rQ1aa4725hglGO2xtkNFbxjhIFI2LuDxMaRx0bYewmEivWXqTUbawliw1ccShpwzGBg3hR07HCZVSuefuqlpvcNd2xDCBQ3K4JRjkA7vQ9hkF+Iv48VhBxgGz9CHUMlaK7y1DP11xL0H8Ja+6xAFh4cnmKpiGDrW1wPL5SEg2H7A2xBizzoFohFtAtauFVXVYOoGbUzEVT2236AXLUdvvcHipReLhXesj3zYt6yjbWB5bAYAtDHUvsboEDYlmHTGYCflMJn0LE8mcGQsMB9629Ld0wHe2L99St+nPGg8VTw4XHiJx2esdhISimlYlDDsy/mlJFtM2c7uVmBz9P8TPvr87rE+xyBS+SmfvNXH624bp2X7iTz8ZZxwt947vm86rRX+NtI8lwhvCWOODSUUhJRUKT6Vc0xnc3XF4++8TVXX3H3z05iqLu7NLw5trDVKmxja5Zb8btXpZNm4cS3hxYz1l/DqXM83Ko8xBnyaE8jzt2S8n/QP6UB3eHSkwCW7wYiRx7k89TXnwdlwSDUaEtwwTMfcTnayk538gPKJEURdNShlgvEuT75b2k9W1KcKulfQVIbaqEK/S2EZxulwNFdG45wnG/TGCRoSMUTnWAOFQi6Q2Ndh8fEEjxmMcRoZDcjjjkOmZWC6AGSdXnusd5ydLek6x6oJSku7aGlq4e6eCuVMpSgXQ4SmqlAoNBprw8nycJtM3iOkvYyfMDRHjSVr+AAs5jP+zV/7BR4+fszbb3+TR08e8ZWv/X4IP7I44PjoHt0wgNZYFL2TwmPC1sLoPFiHOIswYLSjnQnWw7D2WzUTFGatDVppksXbOsE5hffJs0NYyObNnMViwS+9/gqv3j3g4fkFV8tTqqpisX9CVRnEDyQHWYNzbPqBwSbyh8Q3mqikp/w7yD4sTKrJovVGpUMRiR5ZT0/9yyPKYbSm0jV11VDVLYf3TtCHM1bdkrPTp9SqpfIttuq4Nmc471mtNwz0KN/hB8eq86yXluurVSA2yAylViwv38YYTaUrxA9cnZ9RVy2fefUtjg5P+Gf/+h9ydvGM919+lU1nWV6scCtHv9Gs+xqv5lTNHrOjQ5r9Pe6cHHHn5BAvDU5mdBcPWT39Hr0YLupDXjo84d5iPysg2zr4R6kSWeeMZIHFYsGsGdiftyxqQ2NAR/a6+Pg7j8HxJUqEKrorrE1Q3hKjWquwmU3jV1d6HKelwh1/tfMFpq4xpkapEIPRx5MFmejhPd4LoEmhNRLRI3mwkKTAR88oIip7ElIieT8a6igwo0feOXkjMYb9CReCXpj6qgJUJik5H86fBfauyy7vcn1LIDZ47xmGoGQqiXvObTeD3m5tSHx+njyX+ALYUDHfaW4cyR7p5WksOW9R3uTQNokQkcLoqDKElh/HJAKihHrW0ixmsZ5zU27JjS9ufD3dLIe+olSq1pFIluouFjrUhR3CjwN8DA0WGgxxyfWrR7yPLPJwAsO5Mh+l28W4+RCNFgXeYZ3DDgOuW+L7Hm+HsJnur7kRL3cnO9nJz6W06nu09dtcDb/Cyr7B7pTxTn4YWS6XfOMb32A2m3F4eLgjeuxkJzvZyU52spM/syLJC2vCiG5YdCNqmg3GwXqYMFGtFVpV4dZkmB0/FGkU38V0MvqV3xmuq2xklLzPL9MZD+tF3KTAYJOX1hFISzjI7SbHXFTlY0jjnuWqp9cukhQMRit8HUGfW9JDQjgQdDxw5EdsZRtDxjMeEEqZlDIn+UFAqKuKV166z/X1kvPzU66X1zx+8gHaKEzVMmvnWBtiZniRwohd5i98lIgNhYNPDiUeY0JeU3SCMT8Bj1JKjWGg8ZFIMh7LS0bQSlfUdc0LR4cczhuu1xu6fo1SmqqeRRzP5TZy3jPY4Mk1N5YEL7SjL+0CR851f1OkqLIptpVwz+CRQClBSwzZog3NfIa0FYPtWa9XaDEoDE5ZehVCBvXDgMMhWHCe3sLQO/pNH8ZMU2FtT9+dh5D0KpSz26zR2nByeIe2nfH2e99mvVmxd3CIdZ5+PeAHjx2EwWqgRusG0zaYpmY2a5nPWjwaLxV2fUW/Oqc+3ufepz7NfjsL7tr8VsFT1y/wz+1qm/B2RFHXFZVpaSpDpRVGjQdZkwfwG6QSP/YPkUj4ktEmpJJ9KIoqwr6M88R43VR1wPKUDoe3EhY8PhCx52QtcCRvFYlsoYqDgvjSo3MsS3x/PvAHEUMOFefKuSO/VrJNYgqYFl6rCe8PhyCD54ptokfGr13EO3ObjVjvWMax5ImvEDDhMW+ChInSB+9Gqb5gbIOcbiKtxFA0oUKCt4/rZ2f86f/8W8yPDzn+1EuYuh7LX9jgRAIhyNTBM3g5/X0ySfkrcO58OHCKFXslYKdP5vXBOyQBwl7wZUbSupTsSBFDnhJeYDs2jKgUNijc6Hw4aOptH4gl0aO0tT0wfXYnO9nJTn4Q+cQIYls3eYLK5L8tg27W+4qJtmQGlm6pxI+GQ/ISOy5A8VGSm67J60YfVow3SqJP5jUjEUVyHqTYQ0SvG74oyPhvVuGL0A+jiEClBWeCAdwplRXuFLAksZjL0nlPJqM74mnwqAhMdKSsO29N9F6KOi4leEpYzBecHA188XNvcu/kkG9+y9H3PR9+8B6XFxdUVcXJyT3qumLkfcuNBJNR3BO8EGgdPC84CYbQqdE2KraiQvxBGY2qzntsNKRaG368V4gYFvN9nIdvvfuUh0+u6EWo9huk0qNSj2cYerrNGmuHSR5DW6aKuk0TKGs0t0DxafupqOTjgss9reLG1HC0f8Ch2uPZu++ivGOxaDncO8Eby3W3ojIVzg44wo+1lk3fMfQDRgeXdV5gcI7r6xVahc2atRZnLQM9b7/3PZ6dn7LerAFYXV5wVbXMDve4a16m/8DiLyx7B4fs3bmPdR3LyzO0gsF52tk+84Wh63suV2sO9hzztqWt6xulLKrw1r/TfbmeYltordBiqKqWup6hdDUqmXHzPjpYmbq31DqeWojkghxXMSvtaZhPN8muUP6l/MlKaxifpVeNUbm/SUoadyqS57LkgSe/N6aVlLms9z2vhka9d8wPjOM1plluJ9JmYAzlMt0lBU940TWpkIkeaYPhXREmKaWV6mN7TotKpaeMScuYVkEY0UrTNnXcBCWiRyqFC3koiB5iDbXWOKWx0X+lFoUpw1GVVfYxyqtsfZgw2H1SpmMoKRc2Y2F+sRPQYzutTAAieMtTuVoCo7o8CZRD1zC2vTDGotRagw/EEyvRs4dPpzgkgis7JX0nO/nzIHnd+v4RiZ3sJMt6veb09JSrq6u4nu360052spOdbEslz9g3v0vv77Cyb7LzorWTnfxsi9EmkBQy7nLLTbd9F4FYweMLnGO8t/wgN58tvrvx1zawW3p9SB8jHrC9o5dJGtt/j1j0Tft3wF90xGC8qEzICNWSTd63AHPBY7aXiHAVXklvYMg3xJO9lGxf94RDOlWNmznu3TlmPmt49szjrOXq6oJus0FpzWw2j6FuxvJkgCzuhUa8JR2iCfiJFbmB04ylHo2xPqdTYDfRMBoaQ1FXNR44vVhxtexwArrRoJJhPLzEOYu1Ay6f4hmzPdb6VnHS937a8NvY8Y2ajwdXMxlAKUQp2qahlZrVxQWCp6oMbT0D5ejsgFYqeIQVh8cGz7DO4pyN3l5C+s4H79HBe7LK4VectZxfnrParBmGgJUPmw2dMpi2Zq73cZcONp66bajnC5y39Jt1Np0YU1PVCusc3TDQ1FBXFcNyxfvvfpV2f4+TV17OHpcnuCdbXVVuQ+Z9xnyVNmhdRaJFekZG/FLGdNLv5Oldivu2wzHdwJAlkTx8tAMVXoG3M15iyDG/GT8uTQljhseRvoUhZ48c8Z/swWEy32yBlWXaMo6psq+VGPJYZ5LfWeYh16MTRhYHI2bv01wwYsjpLVKWVxH/STjp1LtyTiKno4LHFqMxWtEvlzx7+10uHj1BnEOLijaQSHvxHi0BN02eqksvzjdxlY/BkG+xj42FKaZoUSH0FWlOcrfMTYWkuYjtaSERZlK6RTOkKvX5EskLDTLi+BmDl6JP7WQnO9nJj0A+MdFjbz7HI9hBE2aocTUuF4tS3x7XnFsWn6CpFikU02ZiRxbP5mR98YIyZgTkzUBYmMbFSibsS3K4LSiezZ414r9Jb5Xiu7hCKKVo6zBhW6ODop7qJNbLDXaqCwqZ10FRt1j6GOZjFAn1mCKQZENsUQFOpvfH31rXnByesD9f8Lf/rb/Kk6dPuTxf8cGHj/jqV/8YpeGv/Bt/nRfuvYQaBOXd1qZnVCec9/TRLZg2YIxQGYUVwQ3BBdz47uBWTimD0joY8p3gvMN6i7WOwTr6wTEMHrxCqYrjw3s09YLHj77K1775hJO7FYt7C1RtsD4SYbyl32xYXl3Rdx2TzhVpAKMUlvaJFjqW67a95XS/EbwoGA11pdDGIFXNS3cPOT5c8PDb3+brbuD4eJ9Pf/pVTNtyvdZ4f83QXzBIh1MbNl3PxeUKAeomeLBwymNtz/LZGrxDR6O4G4R+cPzeH/0Opq7ZaxuaquLi8SPcesPd119ldvgm7g869Lsdd158mXufepMP3/4TTj94l/PLK6S94sEL9/hUXXO9vubJxRXtsePOwSH7s8VE//x+JVJ28N5SVRpFzWy2x2y+j9ENEL1CCKAFUaBUCOeSlH2lFMaYEE9RxXAckeAR3OelMSN5zKVmdj5te3XYMIpCiY5kkaT0j+FRkrZVbhCBzOz1BLKSUsJ4fkBnhdwTwgXhQflRpQ4YwLYK5shBgESVmhySSVkj3cR7F+c8H08SyKjY+dRbo5tLpfI8CMGbhIhgdHjOxc6sVNogB4aNJ4QrGdnLKdSLw3tHFTeMJSvdueBZSAghtvYXi3DNJ6U/hcAJ403F3YoSYSPQmhqvB1Z0eA9GVPDgktoml09u1WBvVePj+qFy/aR29CgtIDpucsFZT9eHOKY+evCQIp2gUAcvKg6fyX0ST9ZYayHOh0oEl2JOSjGDRIKL0ZqqqsANuEEYFGFD7h1Km1BGpXeK+k52spOd7OQTy9XVFV/96lcZhmFH8tjJTnayk+dIo97hfvP3uLZfYGNfxe2IHjvZyc+01FXFUBnG3XmBIZf6Tmk8LuA8T3C1XxpDR6PebSDX1nclLJhvkTIbGTuYvH+SkS2cu7xpYhOWbJCd4Kw5XcFoMJpwqjzhSH6aTjoCmA71BCwiYNyO4FV0qivGfJbAVUqytBhviwgKzaydUdcVb772Ksvlkj9ZD1xeXfPk8SNEwSsvf5rFfB9xOcfTVxevcLGtlIp4mxZcH2HWicXbZ6wqe671ROTRxYOHHut89LgaMKm2XaB1zfXVE56eLpnNFdW8RrSKmFNIwQ4hvImztshdxLdku9/J9J4Ezn2klAUPDRhCDUXvt0pzMG9p24qr01OeesdsVnN0dIg6N3SDAt/h3AYnFi+WwVo23RBg1SrUiZeAwfWrIbwjEQGcYMXz/sP3gvcQo9Fas7m+xg8D8+NDTHOMF4tcWGZ7B8wPjrk6f8zq6oJ11yGmY2+x4EBr+qFjuekwrWfetpy995Dv/f9+izuvvcLRgxdQqi5ND1NYvqi69HfCNcFHbyuaytRUVfDKnG01ETtN2F+JW4tIIJhAiB5SHPgbQ0mHTEyaMb3blxalhL2W95WZn7ZpHl8SYF7PeNh5PKg3Pu+RSEiimK/82D0mUtglyr4nMLJCygOLPl+e5pJx3GQoOnr2UAnHlUgyGK/hA6ZKrsdUX74g0MiYT+8YnVCPNrZ0OFII2HVd19GLv+bq9JRv/ON/Sr9Zo7yjrjSV0dTR4/MAkQDo6LHBZpCIHkUpcz19HIZcmoC2qjV84bOXj9SWIXTSdG4ve1XAkP3EppBf5RO2Hz2sIJH3k9a2sr4Cjqy0Bu/CoW8J/SVg/yr2S3VbMXeyk53s5PuWT0z02GyWgEZJlY2rSSa687Yinb8ulNz8T3kdkov9HF4gXsss7sRYLBa6ZEy98bbJDF2+tFzI0yolE8UgGziLgiRmtvceoxXHB3N66/GqRkRRG0OlNcbEhTMu7kmh1XGS73AMXsKpdxVIIiNdoSiH5CRi8Ua1P/2UfkAklk8pw3yxz5H1fO6NNzjcP+Bb3/OsNyuePH1M3/c8uPMSs73DUXHaer9zDmt9NHwqRGm0CUQOitAQWRRoEzxXZMNuSq7sGEW7aqWpTMUrL97BDj2XmydcLy9ZSIXXTVbMkiHXu1t3J9svKb6//e7QNzTC7cZYT3iX88H9XmUiO1UZqqqhbeYoJfTDBsRTNw3DsGHThZA+gx/AeZpa4y3Y3iNaqKrQjm4IDHylQp/WWqOVYdHWmKpmsAODs5xfX9A5y+o9MKczEM3JvQf0/SWPH36dy8undP1AXQ3UbkArjWnnqGYOVYOua5qqwmiNn/SU22vppno7btaW10+4vHiPRdvTGI+KrglTn8tKLzFUUzSeB16Aips9hUTvMEnZoWBjh5dnJ415XNu4OTOx3028ehTTUFJsw5hzSfuC5J0mudORYs6IXXkkn0VPPhJc1CFkUpgvOnRW4pEw1n3qN2kjEOsvE0XCc2mDIRKUca0VVaXDaY5IvKi0zvXiAW9t+KxNAAdigZNOqvOmKBI9IhkjtU36N53+qLY8vKR8SsxhVVUs9hZbLPlQqET0SC2mCESdutL0WoUwKcUMVbrL25bR/eBHiYDSed4IaW6tNbFthqGIuVKUPcdATBsZl8hDZK9Szjuil8P8O8RNBGfBDdEjkUttHz2DBEYaxlQMCHawoY2qetqvd7KTnexkJzv5CClPLgIMw8CTJ092IVx28hOR6+uKr3zlLotFf+v11cpwfV3lz957zs/P2Ww2HBwcsFi0P6ms7uTPuQTjhCW56N/JTnbysy126LGZxDods9FfR/rA1sXC9imTW0a+gJ9gyCX2QfHcmNCIHZUn+Ccvv2EE3rYYbmX2xuUpGJ4/eU8zm/HqFz/HerkCCZhPCPGsWMwM7ayhnrc5Oe885+9/yOZqyfyFu5jFIh562sLQbsOQJ2Uc79rGBDOWJoqqqmlbz53jY5q64fTcMwwDy+U11lr25/shzHY6EJSNqxGZjqSMjMtFzE/KsBqlKMZQwjGtGxhycbg0YdNaKQ73Z3hv2QxL+n5DLQovZtokjpvk6YlB2G99Tp2juDd/TnV+e3jehPl5AnSlowdjJSHEuYmekK0bQDxaa5xTWEsO5YAHo1LY84jxqVAHPnomSXYRiWnXEaO33mEHz7rfYL2jvwBVVSCK2WIfZzcsr57SbVZY59DOoXwMJW0qxFSgQpglHcPpWOfye8tuXXIsclWV9SihJvpuyWZ9QV05tApewMt+m7pOTs778D5fhKKOJJDs2SOBt1v9P9uKYl6TJxeVMhufuRHKo0gjHxqM6bj8OWLIflr2Sf8QT/KAMf2+TH98TvJrAklEivqd9thkl5I8zpQEb+sZkVbBo/IUA40HpyNDQzGWId0VbFZjyPSxTLHuPcE7inPBo/EtkjBkpWOInroOP1WFNhoGg9carOP07ffYHB1w8vLL4bpWOCsRQy7KW7bvc4bvDZlMz3HgFPP/rc95coj1nHpBRvNltICIEY/9fvQWXdq+Uh8KeDL5YGLpiTs5ZFJKRRKbBeLBztvKtpOd7GQn36d8YuTw/OwpWhn29hq0Du7mADKfsVSeJS6UrtCm491x6Ymfxu8nd4x2vbwgj++Khrs8mzJ17LD1vlFJJC9ceUMRn53o82l+n9gNZVyQHTTG8PrLd0hBWgTw2gRlFkekO2cFHQ+1UhiEzmsGhFpXtFUDfTdCFSmvaszTZE8kwb2VBaz3mImPqpB5rQ1HR3fZ2zvib//NOWfn5/zX/73i7ffe56tf/1Oc2/Cb/87f4cHRS+hal4nHQnusc/SDjwqqQZmKpm3o6xqUCcbXopGUgqqtMXWVdaPkti9ZT70EUktqH6M0s6blr/zq5/iFzz3gH/yTf8iffvt99qVmz8yycdZZGAbiIlhqS6WW5YprpQI+ddUXNgegpEJJjfPLyfWkVQeii8MYRdsY6qrC6Jr57ICDg3uIKK6uTnHOsljscb1cc7129P3AetNhKsXB3oxuPXB6tUZpqFoTel4X89RoRCmauqKpah6cHGNMzTcfvsvVes3aW6qq5uy7f0LvHf/WX/hrfOatX+Yb3/ynfOMbf4pwjMgBx1XP3PfMmob26D71Zo3aO6Se77HXNrTG5CFSUnQ+iRLhAesGnj75Gh+897u88uBlZgeHGOWptM/M3tRHxQfiAS7Uha0BwmYUrUNIHFO6zJNJRsLHENczxfjr7AYAVZvg/UMrFDoSRqIyXaptSatKCp0PriczUSgZ90XQuLDhiJvVvBFMHoGUivNYIIo4Fw388X2VioM8bbxQ5KlJJIeSShWU4kwGzc7TVpp5UyHGQF1TG828rhGtoaoRBB27tY+krORNY3ChjNvxKlOX94lpnhonDsy9xbfzRsi5QNpJLxGBdtZy5/697BZSEcgloS9EpZZAyNEIq6sl81nD0K1ZbtJ8GzpD8Lqixw0VYz2M5JqtDjeZ7xRoEzYozo8bQfHRm5PEdoHNJhQ86+rxurMeZ130XqLp+j4Qx+KL0okYZz3WE0NMxS7kAsmjX0O18fRDmBfSyYph43FO0bQzVN/RbTqUhBBaWu+McjvZyU52spMfTJbLJV/96lfZ29vjl3/5l3dEj538WOXp0xl/7+99/lY7DBAJtaNxwznH22+/zZMnT/jCF77AYvHiTyinO9nJTnaykz9Lsl4v6TYrvA9eR9NWX6JBNNnbJ+DnLZY8ufXvEestDxXmq1tY05j2lkU1W3Bvpju+sAQu/MQgOBq3mTwnXjKu6z3snxzzG//bfy8XWCDio2RcWZl4GM15bD/w9u/8Ac++9T0+87f+be59/jPhsKA2xcn351SSn15I2FCu+5ThWDYlinY2p25a3ny9Yr3Z8KffEM4vLnny9DHeW9584y322v2AZ01AxZBy8sIhImgJh+t0ZbB9PLiTYjx7AlYEaKPz4cPt+ku2gLJtlAjGVHzqxTvcv7PP17/7bZ6cXlKjqdsqH5D0jiLk+BaGnBok5T23b8Iopx0wdSMhHRa8xWycMEbnI+ap0EqjRFOZhqaZA0LXrfHeUdc1XT/ghnAobRgsSgtNU2F7x6obEAFlVGivfMor4OlGh3DC+7MWpTRPry/ohoHBB6P8+vwx1ns+/eA1Tu68wNNnb3P57DHCDGiYKUdlHMYYTLtA2wGpW3RVU1cGU7TJjSos/552s/EZ51gtn3B5+T6H+weYpkURvREX6ZTQHT5gc8mDi0JwogJ+r4oXbimrEtsxtEr0+OvCYUHRI1Yqahp6ZNp+k9KSSCeZnBHniGiqj5hkxJDjfCAJQ87JJRJ/ekX4IweuKUhIvqzQ8aWkFLM9TMIByMpEAlUk5qTDgujgLTtFbUl1lbp68rgzHsZL46F4/ViA8IXz1FU6LDh68Rg7gscYw3yxYL5YMFvMmc0X7M3n9FqH4nQD3/5nv83+vRPu/a9fpp7NqIzGWRXmyeJ9qY3S0J+8q+yD3PJ3LpPK7TO5Mc8n4UD2YP2kH6b43smTR/Yc4108QAjIaBfwxe/kcZtojnAD2IHolcjHZALu7L2gTYU4i7XhsGBtqkzM2clOdrKTH0Y+MXLovEZ8DNtSMuzymrStqfvi+/A5u7GScfGZzMvbSkOxOE2/hJRAMuaOaYSFdnu+z6pdzJovFs5pFvz4QOHGL+mDwVAZPBOAoFI51NZ7tt5vCzasUgrfdQze4bs1ahjCiXAC81dvU82Tkhu/SwsPsl0KFfMXFL/5fIb3jtdeeZm6rvjmt6+5Xl5ycXHFhx8+4rVXPhUTTxSAsDKV8dF8DLVhdAi3MbWrp2eC0X2iNKVFLp3a3zqtKKJQCmbtDMRzcnTMvZN7NO0MYiicXN9lX7rRqj5XlQ81mNuofGb8Nxh8w08kKxX5zjEEVahDE1nSSgc2tjY12lQYbagqoa4Grpzl+vIaL31IK7LSPTEsBo6u6/OmBmBwPrKoLcLAcn2FNhWbrqMfBmzfEYghPd45Ls4e8XhmWF5eYzeCqTyqcvRdx9XFFVfnp1yffQj9mqPFPuI9Dx9+yF7T4vcW1KZhb3YQ6n2rFp9Xuz7WvlKRhU70GCFje5f1HIgMqZplMlWEcC0w8dZzy/jOipwPdbdervDe05h2JA1IDIyUlbItzxC3gAOB/+HwSqGSt4/cK7K2uoUFpLmgZH777OUjEyxiyB9QsV5i8ZXJG5Ow4atC2I8otVG0lQkKeV0Fpb0ywWtOZE3rxCCPIVdUUoTjr2ncShkV8zztxg1ILnL0KOKjYhpDv3gZ97QpFIzC53QT4TvQ5BzZO4kKG82wGYyDXkblutTFtzc506by041X3ExJBgRSAfz2g/n2yf49+AuN9RTmuLQhS33MJ4U9gU43+k2qt/Gdznm6fgBrQVLMUYNSHm2q2Edv8Xq0k53sZCc72cn3IS4Sj3ehXHby4xbvhb7/5CEwgjHDYa3l4uKCujZ8+ctrrIWvfe2ax48f53vn8znz+fx2YH0nO/kBRcsVc/01en/Exn2K7wPS2slOdvITlBBsYgsofR6GPFF3RgNkxgK3DJKT727AhLetOQnwKDDk/Oxt4PTN15QlK186hUenoWCSEVMpQeqABY2GWDVJIUMhsfi2H+g2G84fPkTqiuXpGa7bcPXoEY+/8W3S8abF8SH7d06KsqRfI5CdsdiEj5TG3vhbJHh49XiODvbRWvHstKPvOzabjqura44ODqb4dHxZaaD1AQ4KWJXaaovcZjLmb1tKI3gypscKEqAyFQjM2pb5bIGpqlyO52LIpZmigJx8vnfLKzh+K2sRYBuzktNN9SgRvwrejCO5QCmU0gEPjRi4VoGF0nddwLATTE2C78JLrLWTHCTPtNZ5wNEPHaI01tqwZ3AWJwSvwN6zWV9zXSn6rscPEhzJqOA1udt0dOsV/foK7EBb1whwfXXF9fKK1eaay/NTHn/7u8wODjh88V7w8F2aKp7XfAlPTGG6E8Eg1XGJIUPxnYyQPQHBkwIzlq0mZfJxtAsMfY8HtDJjN4veYcZ8bwOKtxQEIv6twCcbQ+pEfpyjivyksDGpvBn9nPSb+KBP89FYkSPJIfxWKpA5kuiIv0bXMcF2EwlAqbBpyHk1rbd0TjFgon5a536cd8oJz8f6j9NIvC/akAoMObVEJqaUuD0ebwe8zS5/osebcmYd838bhjxFjse/xgOEecFIvSo30/RBP37Ic4If62+LIDipD/FjhpKHjlsw5PDvOA97H+2BhU0w2A08Em0cWwNjJzvZyU5+YPk+iB4LxGu8mGDISizmtBok47YnEDrySpW8OMRj0pnN6/OCv60gBJ1UCuXTT3X/PAlKVv4n7gAz47JUYINSI4BXfsvZw23GQykUgKh4M/J3JYU9ySzNcYEayxJDDYhn0/d46/DVjMpUDJdnrDbXiK5QymCVZiWKxih0ZXJ2poTOwCx1bsA7i1dCIDZEAk4iLuDQCvYP9ljszfh3/8Zf5eLymv/hf57x9rsf8N3vfMg73/6ANz/9Kq+9+jIj8SGIUprKuMj/8GijaWvDSqvIjJ4uQiEXBoUBH0N5xGoLMRYtbrAhbEnccGip0OLZ29unnbd8/s3Ps793wtX5mvVqwHphiCxaVZRs2lNSmT2eHscGQaNyfdwmAlRAhZK08ZR8SYkK8eNqQ1M31LWlrmvq2lA1DVU7p521zOctg93Qd0sePVzxwTvv0+7XHL+4jzKh71nv6AaHw7G+7NAK5nVo264fgseKzqJ1h326RrRwee0ZBmHQ1yhrqDdgLHz3G7/P+2//HhV7VHKAqioqY7m6POfp1TnW91RyyuHBPT774qc4v1rxr3/7X3J0MOPTLx9zfHCfNz71SxitbtTMc/RlLCF+3Gx2yP7iLkYZvLVBaTdV2KxAHqtKp3iccXOTCRKCaBk3O7e8KwUFER8IYRawg+Xpo2dYOzBv9zGmRuugCFkbWLOOcTopyzLdbSuct/TWouLmyBG8MYQxauOcEvpNYl6nJJJiLcqG7yPzV0Xyk3Ud3luUDjEnjQrTYVUZjNbMZi1NW1PXFXV0oSgSSSsKSC4rY1UmEkbIS1T04/BM46qK49VlZVGyLkuqE0kVK3kuSWBLIoslL3yl7opLc58gPpBA0jQfcqXinBvatq0NfW1Qy5hv0THUjEKpIg4iU1b7dmMlpj2OnDaRne6j68hxio5zv0/9J5JRkrZeaahNXqZU3GyaWE82s/TT/F5M/lJmbuxYAvS95fJijVHBo5JWCq9miKloZy4+bG7AAjvZyU52spOd7GQnP0/iveedd97hvffe40/+xKI1DMMHDMPDfM+rr77Km2+++VPM5U5+HqVR73K//b+ztm/w4fo/xu2IHjvZyc+keF/jfUXcjYf9esQDSb+SkU58YaybmPq2jGCe5261P5ZUOKaTTYx+igNkDDkZa0tL5gRjKr679bUluBzfmS2w2w9vYcjxkcFbNn3Hd3/3y8gf/iksr6Bb885v/z7v/8Ef04uiR/jsX/4LfPFv/NUxhQmu7SNmHUAWL65424irC+HAYN3WVLXhjU+/ymbT8Y3vVJxfXnJ2esXF6RUnh4ccHR2QsdgcOlih1Ng26bDgIFKc15FJfQVcSZMOJ6XmDtSOiP+41C8k4LzikbrBYLh7cpemntFtBobe4ZAcLmGCOWYLNpM+4nF4BmJQ4mn+ypNQJKwwHeqZ9hkhhNPQOoT9HrQJIbqj5w1lKkxlqCoTsHHbc33Vc3l+iak1s/0aUZLxMhsPCw6bkN3KBDzSBhe7WAlhV7w6BxE2ncc5oZIO8Qo9gPJw+uwDLs7fR9OgpUG0QitP161ZdWs8Fi1rmmbOyd4Bm83Ae++9y7OH7/H0/AOurs9Yn19x99VX+At/539FPbs9/PlYZwFK9AKmammqecDc02HBwttvtrckjgKRKJN6p0Q8MP0um86PTZXHVnq3cyyvVzjnqEwdSDai8MrnUB0xOx8hofeEMM8ewSGo4Kkh5SUzN+Lhsmz4D3lWRVLifSBlefKBSW8tHh/xcZUcEqMjecNUBmN0DPWeYo6rMd85lHrRDBnCTPXGWG9+nGW8H+cd4tAjDZEM+koxJNNBy+S152ZtJeC1sODFZMbDyXnci2C0xmmF9On95WHS8WDnDVvgts2O1D/SuBcS08Xnw4JlJclYvpReylo8LFha9iTOUql+J8Sz58qYYQGcdWw2Q0LiA8FFwgFPY1Jb7A4L7mQnO/nRyCfeFRuTPYXFubCYEbdm+o80ck0W5S1JK4sf78vPjDeQj9QXs/2NN2Zlo9goFAtFkdr0seL2yXWfFrjColwsnH4rsfTRRcXa9gNuGFh3MNCh1ytU1yHaopRhqCqGqkbjqXGISAyfIFgvge0XM+isDWQPNPhxIwBpsY/KugTD9Xw2A4SXXriP9/D04RO6zQZ1I7xAKJuS4LHEEZQlpYTKCFqVy3YKBhJETTYnqcLGdnHeBQUPHzdLoQcp0Wg8s3bO/t4em6Vjs7aF8p/uLxt8uhHKWwHvYjX0iA/Kena3NflJPUa2+gZZsRBRWGcDG9ildFO9hrpoa80wb5jPKupWY6roljDEh0FpTV0rrPMMPrihG4ZRHVVK0dQ1WqtInvL4foMbPPg2K8XOemzv6JWjqg2qmqFVoNa42uD3DA7H5fkZe/MjZvM9BjQH3cBiFjxFWDvw7OqU1jQczfaCgZqbknVD7xmcp7cOpTSmCq7EfB7zqb5yK4XfUVNP28WsHt0YbFH5jCFafNrc5fEVQ4RIiq1Y6mgy3hcvpL1Yum/SWxIresz21phJSpXKV6fk4qzthrtiYsbowLDWM8BjTIvWVdAPBYwOIWbqJsQqNMaglckKpMS8kcge22SDG6BBJFFN7pOxYvyNmtmS3OtD/XgfYp14nxX3RHzYZsvfzM7YAbTWaGPiPdO8AAXLuxh/t2SyjHKYtwkSTkFoLSg97US3zDjhWyXUbUM9a/OpA4dHvC3yl0LQjGVJ2ENm0Mfy5akikhnHWIvjM0jwfDNmZqek/2yI5/79JYeHGx4/nnN21v60M7STn1Pprs85ffcr6PaYvXuvIOqTn47fyc+reEw7UM0GzMMegPv34bXX4OlT+M53fsrZ28lOfgSSPM8MQ/6G8jTFcrnk9PT0xnN1XbNYLDJ4v5OfHdHNQD3vqfe6n3ZWnisiDs0akQ0ftfPJ4iwsn0F3BcP6x56/nexkJ0HSQaAJ/itbv5P4m4jDCFzEvxMOvC0JDLqBn5Sg7c1nn7sC3cCQP0a2sOERVHv+fZMM+Ji/EpfwHm8dzlq65QrLGj10iLVg18imwymN05rLp8948p3vZRzD+4DlNvMFe3fvhDRdJHtkTEluYHrhX8ElT7PA/t4CgOX1EjsM0/ACBeaecLuEzgbMdNtUMK3X7FlgkuD4eTTUTjFkEUG8ojIVdV0z9L4EnW4ejo8kou28+Pxv0F28L4kGU/z4IyUTEQLRxNlwoGg7HSWC0YKrNHaz4vz995kd7dHuvTCSGpSgdWgjF7FSZ0cMGRGM0QXO7cFGQgyG7EXCgbceJz7gzaoKNgYCfket8Hg26zV11VCZGoeisY7ahPBA1g5cXp4zuz7GpwNmeSyOTZagL2ctZ4+fsLxeMqw3EYu7WYfjoxFDjiDcdGhs1Xs5dmJb+2gnKYHQCYR7o534yPFcXgrt4bfeWyQk21+mPpANC2OGBMQnDx3J20kF3qPiAbmEPyZPF1rr4FlcRVvB5CD09thlghNvT6WJ+HRrPaSq85TmnUmtlBhyBJLBQ7O/YHF0xKKdhWSfU7dTDDl8UhHnzZnYfubGgnHrbfF7v3WnRHw22LNuz8vWtxJCSekqhg6XKT6dMnBjiRkf3+ofMcOxyL5ohMyz8ckWsZOd7GQnPzr5xESPg0VQnlRkeiQXZ6JVmIVT9IIkE8tqWnGj8u22rIje48OqF64nl06unMmlmDiLCTetNjdmW4+MDiRIjMTn7yymMkZg29LTE9MlbziSEXlr+UpFsyEO12a5pluvef+852xtUcqhxCPeITj2Dg/ZOzhA/EDtOuq6pmkaeq/ovEJpTVVp8I6+X1JVhM9ibilJCksS3EEtForZrOE3/tKvcHW15Hf/5Fs8Pj1nvp+Y2GVJHdp46kborGAtmEqzmBuua40WQeGAPr9LJJCAdIp7hydqlojziPNYNzC4YTS0RhBQYRA0hwdHOCWsrnrWy018z9iFJCvgQul9JHaY6LFhAPFo6VBiqGQe6yHdH+rEeZm066TdhahoKdbLFZfnp5zszxBZgA9eJLR4WuNoDmoOD+YsN0e88OQAJwqvNF4pvNFUM8XJyUDXDZxdWqyFq/WAVsL+oqKpK+7cPcGYiq4z9L3Fr9/BbtaYo0Nq03Jll6y7gaqt0BjM7IhqcUwrA40MzO+coPZP6C4e8u53v8vh0YscvvASx97z2qsW7XqqYc1VP/BH3/4KR4tDfvWNX5hs0MrAPak3OA+rdcdy1aGMppk10dCuQHlEO0SV41hwaGxkuifXhFKw58dt6+gbJyhEftx4xs2cs8ED0KytcS4Qn5xz0wEpjOFFxhYcSQwkF5JBkdSZxEOxGVOISjEHRy894dd0ZCWCh1aBZT2ftZiqYm9vTl1VaF2HMkdCQDo5ETx/BO8YoT4kdMmcfvl7JB+kmvJRCfR+nGMlhUZNG6di7hVhHCpZkkvKVLZAjBpdw4dL3luCL5ekkRLdHE7HS1allaZuW5pNF8lD8eSFDRnIJx6yi5S8dS46nZD38GMw1ZgFjTFh/sEHV5fOE72gjNnMOrQIShsO7p6wf3SIbmu8EqztwLsQ95NI1ohsdK0CmS7nTkavNCp6W1HxhIaIwnpQDlTyJiQe0UJV1dN1bic/dRGB3/iNd/nLf/kD/sE/eIP/5X959aedpZ38nMr5O1/lj/5fv83hq7/MF//Of4pp5j/tLO3kZ0D2H1xx9PoZDy8u4Q/hr/01+M/+M/if/if4z//zn3budrKTH788evSIp0+f3vj+3r17fOELXwjGhp38TMn87pK7n3uG0u7j4JI/O2I7+N6/gMsPw9872clOfiLSVB5b+bz/z4azhBVPcFW4YYkt8dsJlsv4UIpHkAxpk324bP3pi7Ruw5Ap+CAJjdk2VG7LeEfB1biZjS0AsiRXpLJnZNb7cEisH+g2HZcby3rw8fDfiOvUTUvdNLz3x1/l9Ktfz6GnrRd6hBffepNf+vf+VsDXXI9zoHTyCn2j5PlH8FR18Crw6ssv0nU9Hzx+xvV6TdU008qKhQqhbME6wfkQuriqYgjwXJN2gqEHLwaFUTTiRtk7tA/ekceqDjYJ8QqFomlavAhD5xh6m5yMF6UpbAay3XeC1wznXEiT4LlYU+Wnx+eejx+ntkzhF4a+Z7NZMWsMUAdMEFDiMcqjG03bVHz7yUO+9o/+IS98/rMcv/wCAWcVlBFmM4e1jvXGRS/QwYNHXQePIbP5HK0Ug1UhVPhwjrcDatagVUXnOgbr0CYcflSmRdUtBocRRzWbIc0Mu7nm4uyMtt2j2dunBY4OHer0lA/rGatNx8PTx5iTg4CflV3WF1UU66HbbPjjf/RbPPvgIfqVI8xeM2K1QnAzUhrDSShl7HcRr804qaT3hDljgiEXuGYazwlPriqN9+Eo6iQEZsxsSCmmUo7XLTOVMB46nEwlkg7Vpgt50si5S30nRy6KUW+qyqCUpq6r6L2jDN2REomePqLtKc8MaivDyblMnk5HJDlhyDG5rSEgbBPfJgS1osImdR3rO/3c/fSrfP6v/wbdk6dcffM76Y4Rm70lydCHFNoYzGBRIjhimhM7YTFXi7BNCZtWu5+2nQhKKaoqRCKYlpsby0h4RNHMZzSzFmV0qDoXDgqmvu9TZcLYr/Og8GSvNHE+kBjCnUiAc6ktJdSjKNDoHYa8k53s5Ecqn5josek7RBlatWVYTSt7WlzT4nKbop4XPT+uMlPNubhvovFP57y82PmRrTi+NN5TLnVkRq0v4jJOJL9qurr74u9pMdzkvmlS22X2DB56B6JNUDxUUFKd7UJIF1GIMgz9wKqzdLZj0zusMnSmokKoaug2PU8/OKU/HGhemqH1bRuUUb0Ni0z07DGfo5Tm7p0jlNa0bZ3z573DE8gZSVkK3jQkut0zaKViWJ70jnGVzPp5rm/iYhYXRu9yqAS/VateBG0MVVWhtB6VGhiVvS2F8KaE92w2HacXlzRVy0snM4y+5f7bvtpuYoG6MrRtExjTk0U79CCldQi9o1VhPHYo63EDwdid4s7EzefI1g2L/WAtHqHrHEPvqXSDqoJRGfHo2mBQ6LoOXhOUDmV1DovFbjrQSzbXK9bLDWdPz3j/e2+jlQS3YG5A92uue8cHq57u0HFx/5KmrnNeTHQPp9XIDPexEkQE7wLxwuc4H0kRjUq4JKUmKTTFCJOUDlmvSmnkv+NYLUZrbqjQH1Sue1++P3uyGMdA2bMyXyDensLJqPhTevpIGQzZDV9m7y7R+4aKXnWUhHZs2xZTGZq6jgp7YmOH9Lx3YYMhhD7twhsm/I6b+47xYuG5aLLxoHwmafXxxsyY9zlBH9PZ2rfkd2Y3g4VyuX1ved9UBGUMylSkBgrK69aEUBSLVMfx3nLDOJ2GhXKzUqr2eRymvlWmrYRZ07CYtQH38S6OOQXisoLuozeTctceh2kuqxTvSgq6dZ4QuSt59pimMa3Bnfx0xHPnzor9/Y67d1fs7XVYu+T8/Pxjn6yqitlstkUg28nPgujaYtqeat5//M0/YXFDT7+8YH3+mIv3v0mzd8zs5KVwkukjH7SwPofuemd8+jkU0R5dOZQJa0LbwskJLBY39c5StNbMZjP29vZQanfSZyd/diURirdlvV5zcXGR+7cxhtlstuvvPwOilEfX9iPnqB+PeBatZa8dPv7WKBt7QT3/Fs7Pbr0+uIrHlw/oOg/DZufNYyc7+QmLdRbrglffW8GBaMT1CfvL/962ly7SuMUeeOt9219/FECR70melEc8Zjz/c1vaRSYC4Hw7hgw898g7BHxiC/N0gPWAKHSKni6eZm9OM29p2hlN02LcgLE9wVNADJWuFA7h4uEj1GbD+0pYHOxz/9WX0eY2rxyxHAljQeHwVFXwBDGftYhSGKOLLCdsdzw4VBo8VTwgNakrmdbZpEoyrDJ6ms2G5fx4SMP7EHZbFVhh2YMmiU5OzfuizKEMw2BZbzq01uzPKnQGHrfb6Ebi4/cRktQqkDGUqJybEsdSsW2qpmF2dEA1a2N5Hd6pGAq5qCJf4JMkg7EDRwhnbQk4rk+4eTiMqxBEm1w/qS6dd6zPzlmvn2I3VwzrS9z1AJvoZQHP07ff5eL8gnU3cDVYzs8vePTOu7TzhJEEA7bE8iijWRwfgyjavQWzw30GrQsSxrZuJ7mfTPtFcZmtvZKnwJDLQXmzQYIHjFsw4oSbjoAj079G3LXEG9OjGX+8UZox/6m/SySgSX42dB6jDSqG+FHxINn4vMSijd5gclaf0+8mEYYmdXXL/Vu5vnFzUfhks7kt6dR+2hjq+QxXB7vSbfd6D7qqWJwcsXfnJGMjohSSPL54Px6IvPmyIpvx3o/BkG+dB0rbQO4LxU0iVMZQRU/V2WZZAvHRs3POV/l7u/B5PopzuRunIf9Rz+1kJzvZyQ8pn5jo8e7Tp1Sm4VP37tCYOn/vvUfsqKiluWoaYco/X1/f+lJgSw8otLAbklfTyXXv4qKqZevRj5lFixAIRRSHIJnXMY3JJ1FRzN5CIlMzY1oqKAMrVbFUnqN7h9ytZqycpXOWzfKMbnNBO99nXh9xvT7lyeUlm801q+WSZm/O3skR+/MZzbzhycNTfuu//W1efvUBf/3vnjCbm8LBRaqrzCyI31eIwN6eZj53/MUvVXR9x8H+0aRw1nYMtmcYFM4G5nUtntYY5rM96uoU/BALWxG6T1hmFRTKdVAMnPf0ziHW0g89g+2eYyyGqq5p3IyqMRijsiE40BwNKMNHxS0LLu0c73zwlP/PP/zXvHjnhP/4P/jb7C+qoh5C3krSwTYpR5AUeYX79044ONhjXjcYEYyGqgrKuxCM22pWM6A4v9ggKpBDUB5ZB6XLa2Fw4IagrNW1Rqlg7O+t5eHZMzzQXzuUV9w/eJm2bvHtOU5vmN8/pDUtC1/REJ8dliyHjqXtWT85Z7XswQ5gB37/ye/ylX/1FbxW+BTfDw3NHH/4Ai+9cI+DasZsNqNqWozR7O83GGOYz/bRqsLoChFF1VY0tqbfdCwvl9QHCypTgRhEVcUgCZs7rT11HcL+SPSEkPSxRPYIf46KrPPBZWA+m+AF70aiSd224IneFILyV/ahbGTn1pkkjwOlgvs7USq0n0qBZYqhroJiXimF0oq2rdFa084XgRFsdAhrFDdtYmKoHhnLmJXBuKHJOpwH0QE8DW4YiaSpuEv1MiVBJTJQTCuRm1OeJVZsTl/K52DKgIst9LzNKsXUJxJ/0rW0uS5GkaT0wybKzPcwgw++Wa2NHjAkx5lM6fukfWdSzTSPoX1VzEx0U4nCeXC2xzsb5hoJzp+cjuHEkOwmFMAozUt3Djm+c0SjwA89pgnGg364jh5HLNgBN9gYCsvivQ1hkpyPXk7cSPiQ4PrPe0/XDYgWGh0mfj+EjbmzQ+xHt2xSdvITFa09f/Nvfo9f/dVHzGY93sP777/PH/zBw4999t69e7z11lu7U8Y/gzK/u+TOZ5+hzM/uKeOL97/Jl//e/5WjV7/Il/7Of4qa73/0A7aD7/7zcMp42PxkMrmTn3mZz+d88YtfpG1b6rr++Ad2spM/Y3J2dsaXv/zl/Pno6IgvfvGLO6LHn3P5/MtX/IU3zj7x/Z4nWP81nuNvnLPVCf/lv/w/8f7q/o8mgzvZyU6+LzlfLtms1yHEcsZMYDTU3jS2TlT8j8KQZeueG1Y9Ga+XL8jfTTcT+dyM2tpk3MjQdlYKrFue986pNTZXQcKDUoj0ohJEwSCKTjSzRctcGQbvsXje+Eu/zMu/9Dnaek5bzek3K7r1ksFa+r7H1BX1rOXyvQ/4vf/2f8R4xe/pOa996XP8h//n/wPzA3PjsMxNq7qK+GVDVdc80BrrLE3TUjaM9zaSOiWGPgkekI1SVKZGqzUkz735FFzCg8q2GMO+2Oju1TqHc/ZmnUdRWmOoUCZ6Yi3LEsMl30oyKLwZeO+5uFzx1e+8x95sxi99boGu1Zb1PAGZz8mIjFDgYjGjaWsqHcKfKEXExgJ5RpRCKsPdN1/nS//Bv4euDd46rHfYIaTlRVKEZSB5zh5JHtfrVcDKumD0XrQHGG3wZo2XgWrRYpShRodgLiLgBnpn6Z3l6//it/n6P/ud6E3XoZQKIaZF8Epwg8WuN6AraBecni7xy/+Suq5RkTzSNDpipA2zgwN+9T/8Tfbu3eWLf+uvs1mv+eM//F2ePXuMbqrgGVpUPLQ47Wcqwf2q8OixVe9Tm3noZ5TjhXLshEOkEIkrsauWQzHf/1wzU6j8fIhRxrwlTyZlV0uHCUUkhvcWTFUX35cEELWVQJmpdEnyxzAX+KIMW5OdL2wa5aD23JzyxkfGcm5fL+r/ufyFLQDeS5zOZczjGHYJ5idH/NK//7eYHexTzWZ471F1jUpzZpwaRnJN8f6MIaeiTxteJrlPuHXy8h28hMPo6TvxN5JdIqWkRNift8xmLVrAOxcO2opEb0gRG/buxiFmHz2/J3JaWZXpnda5UN2pLV2c7bLL7p9RcGsnO9nJnzn5xEQPoUaobp2ASmPr1ppTPM/k2bRApAUhPRDi+W2tSrfkxvvtNzz/3qnyf8szfnJ3/E6y8TTdlL2IfNTrskEzJRs+OFFYCeSAuq6x1oKz2LrG2prZfM7h4SEKi7UdTq5ZbnocmsFB11tW603YJFlPu9/GxWGrAvM7pwpSci8mopi1LXVlIhs7VU5g91o30PWw7sLpKhPj8ylJhvbbC11eyk3j07tjvcT2vbEPY1wEkyIkRZtJVtqft/ilRdIz9ANXF1cs21mx0MrkvlxFHkpjc74r5jWw14MXk2HoRs8ARTgHZQIL1TofonH4uICncheMXxHBVGETonQgOIRNkce7Ae81SoXQOYOEcTCbLVDtPmbtUIMH3+PsgBKfmcCVCSxZLRI8wqzXYXNXhU2YtQ6FpzZCZRTGGCqtqZRGK40WhZbI+s7DxbParLleXdPbIeSx6F3FCM51KEU73ur1p9BmE6t8qpjJ6OwnK8SKMeGbfSYlX/yTU019Ln1U0XWaMTrGvgweTEwMHpo8hxglaK2om0D0qOsqbGJ0DFOUvHbE2H2jG8Nx3GWeUrw2XirLPVFJw5USILghW/V120C65cvpu9IGRSa3pliu2ymlvE1U6alej2gdSS8xlmgMCTMWZToXPb9ct10KSnQiXigBMULbKjrtaE3YBJebelFCXYXQSCr26yq26RqQOFfYpJyXPxmwGNs0UVIm3kNi+X36J/3I2JY7+enKxcXAw4fBcO49PH48sNl8/CnR1WrF1dUVdV3Ttu0W2LCTn6Yo7TDt8DO9DxbvqHyH8R2fSEf1HvoV9Msfe9528tOT42P43Ofg/patcRgGrq6uWK/XExKriNA0DU3pHnsnO/k5Euccm81Ibuu65x8G2MmfHxmssO5Hom1bWxbN872LbAbD6fUC628n5666Bc4rlPYc313R7F8C4JxwdtayXn9iKGwnO9nJDyCCRp57WKsAFT4KQ77xrC9BW0pPFB+HId98w8fd+wnu37o181cy9vwRGZOt57YuehReNLPDQ2aLPfroLXnvzgnzw0MWs30W7R7desV6vaTrOtbrNboyVE2DaWdQGbrlhqdPHnH44C7epRi/ZX2UiNFovQ24nsJ7T1UZtAtYZlng5CXCWhjsGAL3hmfmW3CrW+HlhKXmvz8aQw6/t8FoPsEePmLIBJ2k23T02jxHF5liyJM8lKl5MsYonkhSGb0zJKxKlKDrimaxGJ2NTLC5abUpHdsiHnAdsSsHPoRrV8pjJdRpVdWIqVGDRyyAxTsXzN8imKqimc9zqJvN9ZKr0zNEK0wVDnOGIeXRET9t5jPqukZrE/C22kSiR03VNogK/WS1XLK6uuLi6VMunjxB37uDMWZrmJTePD4RpAmTJybm9BFDJhxCHcPFfEwfmNiUCoy1tA/Ffqwj9pvwaZXaM74jkXq00cFbtk7epKOH58I+kOpgaoUYMeSyu+V/biFl5G8+FkP+hOCJTP8cmyH2Px8OLNbzGYuDfdr9vcnj/abj8vFTlucXI54KKKWDF6LFHI/ghxAmKfTnMfT6OPa2O8Ata8Bzr8XrBb6b7BPGhPmpV3mayWMitXEev5A9gQ+pPrJX6K335E/bNpP4d7m+lQ2czVXbdqud7GQnO/nB5RPvbu8fvR5CeKh6uvhtEWSTZ4fxlvLfuDxnK/6opAcmnB1Vzufpw8V3LhryJS9dIT1RUZ0S8qKajMVhXvU3FvDpK9J9hVE2a5quMNWOoQUmjF8/SQzvBacbXF0hOhjkZ1VFKxWGfSqtef311/niW29xdXHF+fk5Dx894Xtvv8sw9HTdhsvLDU8fnyJ2QG86rqsl/xH/AaIM44JgGZX27YVRCK4/PFU9p8KSQrqkjHb9huXmiifnS56er7h3dJf7J/dRSuGVwivBawksRIacdlAsgxeElF4MkEAVyQgiGkFndVomLlM8eAt+QBHY3zkNBZKceeT7p60VTv8Hg7AeBubrDe1mg3hLUEXSwzb8ROVavEK8iob6MayKcx47ONq6QbWas2ePuLo8Y7NZo1SFNhpTCaYxmPmMqq5QPjoQUw5daep5E7qjtWy04lqFcCyHhw2ihMGGDQXrDu8cxnhELB2P8E5jVIWpKl576Q0Oj1/h4bvvcP7sGW6zxA3XnBztcXiwB/oQ0YfMZxWLecOz03Pe//ARD+7d4QtvfprVesOT0zPqtubo/hH3T17gFz/zOZqqQSclVUVjdq53oRt6vvGdr/Phk8ecLq+x2gSXmjL2JIkEee999oynUVH5jUZ/a0EplNKZxCBJ8SWODeexNowrR+grSgyIRyS4/FNK0CLY3IOmMSKdGwkBEOYG623eEmotiIa6qpi3bSC7tA2VqZjPZiG/eZflMhubvKEq1OMbO9I4+5QK+dizx6nMR68aJWEgbkpSaFnnZfR+UWiJKWdqohP6fBghRSiazrZkxrmScJOoNKD6WBSF6IrgLi9uitLeP9aeLQojEYXweBAHyqEqjariCQDvWa3WaCNxY5sU92KKzGXYGss+VlB2L2JhWGEHz6pvGZyjbhzzuebVV/bplh3N8ppN77gWGHzoV8YYFvMZe/MFddVQacNxrag1dHh66+j6gU0/0NsB74JXD+tcMZ/HNpdI6Io/WqtAGhHBWQU+ErW8wzsb+8vzPQ/t5CcjfQ//xX8BZaSWs7NP9mw6ZXxycsJbb72FMTsjwE4+uRwcHPD5z3+e6u7ru76zkyx/+2/D/+V/D3t78XBhlPPzc7785S9jrQ0E8J3sZCc7+XMsX31vj+8+mufPn//UJb/+1ulzter3z17j//E7/0eW3d6t163TXKyPmc2W/N2/+w1ePfoqAH2v+a/+q8/x1a/e/VEXYSc72Ukhi/YY1RmUaKzvC8PW9L4SvZxAqRFEmWLIxXWAeCL6I+yc04/Z0LaFISP4Qkcb0ytCEnwUPp2x5u17t42XN0Mc3DbJecArjVQNb/zlX+OVL7yFS/dVGqkUx0dH3Lt7l27dsd6sub5ecnZ+EcI824HF/ft8+m/8Wzz9zvf4k//hH7F//kKEetT4kmxk3MIwRhA8PKErlHaMxJ1QCussfd+x3PQsNz2Lds5itiB54w1gV0p0DH8e4HnJIS5CdsIfWiR7eJj2jC2kLZ6wD15fRwN6sNKWxbmlgiUalp1HnKMaBoy10etu+S5HAshSfsSP3kfSwaCQFR+wb1OxXl3TbVYMwxDwTSUoTTwsWIVwK0h4n3hEC7oyoTt6xxDTVUpo2uCBxbn4zsHiXfB0i3JYf4X3Koay0RztH9O0B1xfXLBerfC2x9uOWVvTNDVf/I1f53P/xq9TVYqqMnzzd/6A3/0f/hH7s5a7J0cMw8BytUYbTbvX8vIbn+E3/5P/mNlikW0ro50lhOipFgu61Yp//v/+b3jvW9/mu9/8OqvlNb/27/87zD73em6F1KQZQ/Yhney9GaKXg/idBx8x5OSV2XsV69tF21MIVxRCNafQHqOBP7XW2MNi+zsiljeiqD5bMoKHYiR49A6huhXaJIJLtTVGwlPBJsItRKPbMOQtG5Jsf5uwV8gHSIsbRj/uMgWeU1rl7yLdhCHfOmcWXT8PP0kDKoy1F9/6LG/9tV+nqpsY5jy8/+zd9/m9//ofYIeBoe+3yhHnXnG5v0skz+DD4QelJB9mTnPp7dGuhOxJKRcsFdKB63HO01uD8x6tPVWlODqsGXqL7jqs83QS8PcUZqquKuoqjE2tFDMlaAUWHzzuOMcQw5EF/NdHm2Q5L404cu6zIujYF9P04qOXo/AbRHsm/WEnO9nJTn5A+cQo9KydxcmqZHbcXBm26QU+TcL+9ntukzxV3mbT/+gvxnfcsq7efLTMlDChUSej7WRDsbUQE89up4Uwfu+nK85WJqLyqkKIBK01WlfZo4fRBm0qluuepn0GmzV9XCSHweEHC/2Gje3JGtbNgt1WI5CVnWw2nlxPi9H1csXjJ09pq5Y7hyfB0K4jezvr2qUC7EdFXMaqvclRLfM4Pfc+hl/wMYyCm9z7PMkbNe9z1pR3qKygl8/74t+P4LUWxA+dvTaMyqZEbSm4KAsKRqibUkFMCiWMYS4IYWmUMLhAajJG4R1YCUQH9ADK47zCOY13A7gecDEkRHiBrhrq2R6i56AbZntz9g/36VEcbnqOjo85Pjmm3XQ4rWnahrt3DrlzeMS8mVFV9WTvc3P7SVCSvMWYmqqZIUrHrVlJrRpjmCYdUCkVYg8qhw80AfykRqRQuMfxM5LnCw03KrR5QxFTCQr+lOwx9rZpgkIgAFTRO0fT1CGeYF1jjKGuKxCV+6MnbBiUVtPOmzXj6dYPorIcx0XKQVKeJySHIr/TobuV4vNONQp5Ph3f8TEKoR9beeJ28Ea6MtZeUbfTcSJsj6bSxaKn8Ojhn7N5YKzK7f0NaamI8654i+AQ5TAVzGeK+VwzmxuUs9QGrI2t7olKuqCVxmhNq1Qgm4mQaW3JxR4un0ApY7/6tGT5G1kDyCcfRs98flTSIYybj13ldvLjlqdP4YMPvv/nrLWsVqvJSeOd7OTjpGoUB3cq9uc1s/kM0zTPnwB38udGbKfol4Z5q3jllZtdIs032+KcY7Va4b2naZpdOIud7GQnPzGxg6K/rlCVQ9fP96bxoxdh02s2hUeP8+uKs+uKW8yiAJxez3ly9QLL7uBj0/b1HjI74KA9A7fh3r0VT54subys2Wx2xMyd7OTHIZWp6LX5vnTibXjgY/fVnwj3/cgvbj4qW9jMc5+/DY/9mNRvA0lKUGs7fyI0iznzo0NSbNwQFnsInhmaJngN0Ip+cBizYrAD1ll0XdPs72NmMwZvGeJBnIld8qOKOmYh4n8RQdwG7AW6vme5XGGUYdYE78rZI2oB0d2skSmG/Px6uaV2iur3MUTDc+6cfJ2vZLyQcOgpW5ZvwfFLzP9mJy3wsyk2Nn0ov4y+27A8O8c0htnh/EY58zslhTWJB1198DTgNaMHchXCmvoUDto7ypAVGcfSBlPVYZ96UNPUFU1bc/zgRe689CJ7sxl3To4YBstsvUa8R2PZ29vj8OSEdn9vYg6YejKHjfOsLy9Znp2xubhkvVqxPDvn+vScxXwPmd/eCRIhI3i/SIG9Rwx5vDVihJIOnj0PNpWxbxU1O8UxR/x+isMWzaQkeL9Oh1ejxwcVD3FmG5KMuPiN0E9Mk55iyJLrsJwSJJfrOWnl8Vs0QlnAcnyX2PrE/PU8vHliESBbt4qOVDUN86PDTMRJr7Jdx7LrUpXkNJy1LM+Cl49mb1Hkq8SQRzx2nIefXwXbOH2KFCARqA2eXUJooKoSqip4Vxfv0ZrMExFS/0tYcsSORTLum99RvDB7g/ZMIwE8Zz69UZQ84UVU3e+8Qu9kJzv50cgn3tW+eP8A5zxX1xucdZOJHsiLx821JYCTybBG/JTvdB58ct1UZGei6fnJr1LhCavCVmbT9Yk2lnSdW7THtKpmLZGsgGeGsXfT3ORYWluZmuQ/XfcY11MNFj9UDEpTmQpTaYw1aFuzt3fEvfsPOD4O7EfrFe+8/xhEMfQ9Shm0qvBDj1s3tPP9HG5jWk8T1WErXzbeowhNn1U+AJp6gTaG73znK/z3//hf8ld+7RfYX9QMTtHOWuq2RpvkuWOMd6iUom6gqnKNj4ZTZ8OPDz+hsVKjjZsFrSsq3bAZes5Xl/RD8MjhvcUy3N53EBwW6zqcWKpKBSKFeBBH9uDBtuE15S1/AqKB2sf4iN5FZQPqqmUx36duWkxk7g5Dz9CtWK9gsB11rXAQcjp43LIDEZQ2dNbRdx5R0M5qEFguV3jg4N4cpeDq7ApnHbNFjak0l8uB69XAt7/9OzSzr9CYE0y9QFyDF6E5+TSzlz/NZvmUzeoUtXfM4sVX2Du5x6svv8x83rB/tM++1tx/83X2mgWfOnyR2tTUW67zSkm9pdGaz3zqAfePFjz61mdpVMvV9UPWwwqvAgsdgjcOXWz7NDBvG06Oj8EtwV6PumfxOxstvEe8AzfEdgGczwSadCI6KZGBMQzOBk8KIZmQ6+SRJTG9IbrWM8LhwT53jo+iZ4YQwii5lKQgr0nsz+OwKcaPuDzHlaMuTQHb+730+cY+cJvTgSeEHr0l6EfhJiRtqMq0y2my5KSVCmn+7UGjqXSFdzb45PFxLKbn/Ej/8i4pxyHDviiRL9I3ylEpl9+pVXB7l+NQxpdvzeaUsVGn36cNnEPT0VSKg4M1TQV77SFGK9rGoLoBHcPxJOVelEF0RaUrZsbw2lwzN4pLL2z6QOpAHCIOweHcwGCHyMy2ecxb68KcFQkrznmcDZ/T3s06C97isDgGetcBYNJuYSc72cmfG3nwestv/u9eoLvY4+q7zzNJ7eTPm1x9uM/q2ZyLgx5++fEnfm65XPKVr3yFxWLBF77wBdq2/THmcic72clORlk+ntNdNCzuX3Pns8+eD7L/BOQ7j+Y8umiem4WLzQld//FEuFW/4L/5g/+Eg9kp/5tf/b/x+p0/5Td/8zv8xm+8y9//+5/hj//43o824zvZyU4A2Fs0SF+P4T6298g3gJL09XjfLShC/NOF+8qDiCUAU2LIpRE147s3Xhoxl2keSw8gtwLek5tjGjLeO8WBbtshPG+G8yjv0C56IPUOLSEEsVIK8Zq6blks9nEzF7AKL1xcXoMIzrqIjynqpqWqZ5iqCeGaJxVym2Vyaugdyx99CAgk1MjoGqUUZ6eP+cZ33+VTL92nqTXOC8YYdAybnLzkZhOwErRRwfPupNSJqKCiIdXxvAZTSqOVYXCWTd9hnSUeHYz48S19R8B7h/MDXjxaSxGOxm/9lDYPXxz0GftlMvjm/+JjWhuqqs4eIJAQysVZgQEefvNb/MF/8/e598an+czf+CtoUfg+EHFEKay3OOsnnob7foMHmkWFCHTrEPbO1MFjSNc7+sFxevoexjxCqxlK1+A1SI2eHWEOjrD9kqFfI3VLvXfIZ3/tL/LKZ96kqjSztg7uB5Xm6v1HvPfPf5+T4xfREYfNXaHsQvG3UYqTgz26kyOun93ByAXf+u0/4O0/+mP+zb/7H3F4cgJINGqPVAABKqOZzWfge3AFWaB8T2QNJc/GIS+pHUaDe/aqMT44tpX3EW4c5yTZwu8EASW0TcNs1hYY8+h5ZMSIwy8lMsnrdPyM4m/8cbt8HIaM98Fb9I0LTOeZLYy4xJC36zffVb7YB5te8AbuwjuzW4oxnZx2+lyEI7l+9owv/4P/L4u7J/zCb/7bNIsFSjy6IEiofCCROA9HDLmYxm8TT2q6iCHjUVi0EppmwGiodRtDuCs66+K7inQl9HetNJVSHFXBi/MGwbpI6BBf5MnFw40eh8t2pRDu3mUMOfyEP9L7XPRClOYoF71CK89NW8BOdrKTnfwA8omJHskum/gdkj5kKRXAm5IWU7mx+N0yZW8rxM9Lj3F9TgrVaEuefhGX/yLv2wlS3lh8+LjNiM+ZuBk5ULICqPBoHDiLHQZ0pdFxc6KUxpiKqm6CQmgqmqalqirsUFGZKrBbASeC7XuU0uNC+H1JuTMp2yzmg4qus1xcLjk7v+TZ6TNMPaNu9iLL0RcLaVJuilP9UtSFT6fmXfxmS2kuRIvG6NAdE8liulHazn/6e4yEpkSNeYhaqPOOfuhBhEo3RZ63aiW5a0uKuh+N00prqqrB6CqEICG47nLDgNuscd7R1DW9syQPFnZwgZSg8hYg/B8Xeu8D61qZ4ClFlMQoMyH/wbhsWV5f0HXXmMM5zWyBqioQTTvbZ7Y4ou8u6IcN/dDTdxbjhcaYEAfRCFXT0O4dslcv2F8cjQr6Lb2hFCXCom3BW/YX+ywWB6zXzxiG5aQVywEVyDPB4K+1wqOy0jO+LfQbKftJsecbvUMEpU628hsyOw5Wn0Lm+PFa8iwjPrlG1NTxtIOocNoh3CpZMc17hCIf5ZyQe12eTwpXn8+pw/Hb8Z5cXSnNeDnr4jETE+X7lrRvbBBkTGN7LiwbLLiN03k+IfZ1SRv+504oRb5K338SCHfplEFQ6svPW70tav4j+/vmxkdJWG8qA20Dbe1pakdbCfMmEHS0khwzUSKTXkRRt4a2baiNolKKVitaLVz2wdWetQPWDvRdR7fZxNMwgeQRXPD5oKC77XwVsVBdUPR99gQSSCHOhXBW1qmtcv9gUtc1bdvuTnLvZCdRnFUMK4MyDlW5nyk+Vd0qTl6suTYN1x/u4esZz1sVdvLnRQTb6fDznNPiSimqqsI5R9/3+XvvfQ7ncnus8B+9WGsneUh5+/gY5zvZyU5+nsQNmm7QVMuOfm3QP8U1d9vDx7YsrcF9ginSec3T6xe53uzx9PSAE9Owt9exv98xmw0fn8BOdrKTH0gkYgXt3oJwCKoMHc3UIJmRkgIrFLh58Pz5GPLE4vhRQIoQsUrZusXf+HRr+iXWvJ2V50Piz7mp+DtaLUfPyNG4GHE27wK+CAlz0ZNDTNqYgH+5EHpAosdWpXRxyCm9bcSxb9TZdlbLStr6LCIoFNY61l3PerNhtVqhdIU29RSX2pbcRiWGHP8q8NjnPy75cJFLz2wDd88rT67jog4yhuxHA6yY4vbn2C6SZ9gizyLBy6yS0D6pfN45/BAwKT84hk3H5vIa09TUszaEs/B+K5sRS055TlhbwgDjh0SS6bsN1vbMmgpV1YjSIApT1VRVg7MbnBsiPuYwbcvRC3cxxtC0FdpUmLrBDPCkDt6gSyUgn0W7OVypTUVTN+wdHeF1xfmzD1lfndNvNqMloDTKJEM4kSzhJRI2bjHY3DJkiqsjRi23oHEFhhxYJNO+Ut6vREIonejJo/TSkvIt212tnG9ugLXPnxTy7dOKGWX7q+15rvhyG0O+LakbaaSvvOdGrRXtLLJFEctpjM/oqqJuGry1DOtV7q/eeYa+4//P3n8925Jk6X3gb7l7RGx11FWpKktldYludHc1CRAgiBlQDEHygbSxeZineRgz/nc0I8xo5JAz4IAkjLQBCAKNQkt0d1aXSHEz86pzj9giItx9HlyER5x9s26hGpXZ1bGunbv3DuHhKtyXf2v5t2zXRiw1d9nSFDCYccp8jBh2ilae1EtKTykw2iO+o9u2eAXKgK4MRq/vlCGxfxuj0Sq0vVGCUXCwCRsOzhthbR7YknL47rhRcBi7yrovMGTPMJanh0d7GT6GkJmxo1lmmeUvQF7b0ePp0yeEEXnBKHxLGmBdsiSW7AkDpVZQMCm8YNNEGenfRmwa6QvFNQQ3NybnyvHUh4FfCB6eXrniWVJ4Y8cpQoq0X6FBepdiZud97mESUUkZdQUIO0xLqTjWKbz3LJVgDOx3t2ztlr5fYPoaUQuW9RJTVWB0mJyA5XLBxcUZ3bLipIJD13G929HtFPvbLcqXM3s5IRxbbSRr+5iJI1yX2iso6KIM56dnfOWtt/nk0yf8/f/2/82vffPrfP83fh17uELUAaRnCHoYFCXvfJ4oFSFuIT7QT4fQCOEv+S4OekX4vmmWLEzNum6oq8Aa4kVRa8OmrqmNJrBzlDEhUzxGhRfBK43SdaSsEzyOXXvDDz/9IVo077353VALKvy5yPBSLh+Sgp7COQAsFhsWzYr16oRF3eBpuWlbDrtbdv0O3/e8+8432O22vLy6pO1btrtbxAjGOLxYmgWIWF48vURE6L1HaU1/CyKeduexznNz6Kkc1LVQV4aXlzva1nJv1XF6T1icPqI2J3z13a/x5tfe4Q9ffsSPHj/l+rM9H/6rjzGVoVoY3nznnO9u3uZi9SYPTt9moaqgsB7v5ndEENbVCdrXPHrwFu3B0+4+xXdXOO9orUU5j9GhBS3Coeu52W3Z7bccDlsULabonQU5BdoYvA/KEkJkijE0TY1Xmu7Q4zxoXQ2Lt+g1Wy6gcr+T5GblCwURNps1p+fn1IkZhMj0EztguUByiaQnHjNKgYfeu9E4k8l8Ik5RvorlAqN0BbkDEgyuznHEioub1P9ibMLETpL5hKLR31s/VGh+3nAoDVtpLAphhoTahPfJu5Z9l5RNh8RQJ0pJeMsk7LCQ2HB335KYHTzLhcL3Ci2hDE1ds1g0VMZgtMqOO2ktp2J+XtUXmwWcbOD83PD2W2vqyrBcCuI89qbDG41emzDWaINSFu+EetHw1fe+wfnZCV85XXFRBY6Z1im6/SVde+Dlyxdc3u748MPHvLx8ye3NjsO+pestNjJVCYHWUlQBLMfFvu07usMeJ4LYxBjUYm1Ht9+S4om+unSvJ03T8O1vf5vNZsNyufyF0pplll8V2T5Z0d7UrB/ecu+9F7/oa/ZvRjaP4Dv/CcgJmPqLzs0sX3I5Pz/nvffe4+rqivfffz/oRMBqteLb3/42y+WSpml+KXm5vLzkhz/8IS4qQ6enp/zar/0aVVX9Up4/yyyzfLlk93zJJz94k+W9Lfd/7UWMH/6XWw6t5v/137/HqXX85//5+3zjGy+/6CzNMsuvtGy3tzglfPc/+D/hvWd9fs5gaI0XlSDREYOoqBHswXCxGmPIOa10rDTMMuAv8frMVprAHIkY8rGYuxDO52SPsIgUMoShTnlIGHTChwbEaLgpFSdsZsILRoRGge9auv0eVxuUV0BgMFU6AJtCYMCojGG5WGBNh1XQO0vb92ETWGlIlCJvSJGVsiClNb/ANyaG18SqsmgWnG1OuLnZ8sd/8j73Ls5589FDfB/x42QnSEb2yeMEAoYMQ1gEEu6XfkvOpuCpTYVRhlobdAwl7gnssrUOzi6jek7GdO8RVPiudcR9IobsPb098PzmBUqEi82DkD8VbADjCDG50QJmVnRUUzUYU1FX1xht8N7SWkff7eldx8Ovf5X/8P/5/+DJjz/gj/+7/4mzd97gG3/7r2PqKjLqhhATIo7ddo+I4LxHlMIF8mhsH1gE2t6htaA1aKU47HusdSzvn9AYMPUarWvOTs/ZnJ/y2afXvLjZcrjtuXp6jdIKbRSbkwUPmhMWSrNanLKvXtx1+C5/3nldhUrXrFYnfP/v/RYsG/7pf/Nf8+mfvx+c2J0PjkrFq9c7R9t1YQNW3yHYwBg9VCsASjxKqVHIjMAUE4z0XhS2D6hp2ACa7nfD+BFtQ4NNKmGqg80KCOG+l4vYfxKmWo4FxbvqhuMiFNh1iZ/KMMyVUOHw6DiuyOjUqH+VlZH6amFXGW8MkIyPQ8CBQ6aGlLOvhAzJjohAZLg3vU+tt/Q5jZC3tPHOAfffeZtv/91/l6tPPuNP/uf/jb5r8cD63gW//h/+HZZnpzSbFYKnMgJuaGdtNCay36iikqTMj4yqYCRaQ1PDYqk4Oal48ZMP+aN/8k9xXY9Yx8U7b/Ebf+8/QEQPG3KdoLXh7N4Fi0XNaVOziMxD1guu3+OsZX/YsW97rq6u2e/3dG1P39vAMh7nnOQMMzRwbEHvg02s7+Pwk2xwgaXJ9t143ppllllm+QXltR09Du0eEUVV1aRwLJJ2n08U22FyKhS4sQ575GoZK0xHB/A0YMp4Ipsq/lmBS/cLR1YHRC6AO0mEW5L2UWREJhcde+6dPANeomegwrmOrrNIr6FXmMpHRSSFiwhag9KKqjKIrZCmQZRwsBbf9aNnDd7e0wcfUdLLBcm0LnI9KVbLBffPT3lx+RmfvXjK/fNTbm9e0rc76lpjjJosDgpFX3JilJObz9rU3bYV8RjRKBSLpmG1WAZ2D4kx0rRG56IdWfzlvEh0QhrO97bn+ctLtDZ8/aEN/SLrDeM6Crqep7eWvu9xVdDitVYIQfEw2tDbPftuz767ZXe4oT20GF2hlQnOMi4sALwN3p9k5wNP3/UgglNhYdF3gdWl74Pi2/UeL46lCTHhbO+C04MNYWyU0lQmxuF0Ftv1HPYdPVtaHKo26EPFyUVFb1u8d1Qxbz+X6iCCFkOlPE2zZLFYUWmDFqG3PfvuEDy7U0NKcEZwfth9WjaZL97t3PxKYaTCisP2bmA2kRRbMirv2RkrLvTipwh4F0PwqKE9wysU0jJVYHjIzA/ZCyQq0VMP4WLtO+pyAxRQ/jeWpCkfOXdMd5M7v4q8pDFsclXpVHJ3+JF8PGVxui4zWtPUNdtOkyEGP9Sb856u79A+MNJ470MoHSLNXKSsS7slvLNxN4DNLasinWim3xtV0LhvTEcQL2A0LJfCeqU42egQF5PwLrnOIV6FBZWPjjCxkEorNqcbTs82NFphCH2od562azkcduz3O7bbLTfXN1xd3WQlve/DbgbJixUXdxwV+QuVhYusNeJ6BAsSQ1O5PhjI/N3W/XlFRNhsNpycnPxC6cwyy6+S2E5jO0217LCtziChKFDmS8LwYRpYPwRmB61ZXi2BLUOzWCw4PT3FOUdd1/R90PHT8V+Gk0diDtntdlxdXWVHD631L41NZJZZZvnyiYtsGmbZ/eyLf8nivcaxwPkVP4/O7Z3w5LMVL7enPH++5OHDLVo7NpuWw0HTfQ57yCyzzPLzS2/7sK59cC/uCE8Srbx580t512voHskyesTQfOxr+H0ME544HQSL6edjyK9kHDhyqLwsp3/kmmP3RrxKRWzMuh5cMI6m0LqS8KtYNlEBR8ZpxGhwYL0fQpOMMOTBaeL4MDrN2OfgsF6oKsNy0bDf33K737JcNHTtAWd7tA4sxkNbjytiwN/LTKawDSWG7DOeJ4AmhO02OoRGTyFSSobZUd5LJx5JuSjYGuJx5x27wx4livO1f0X9lHVJZAFxI2xNRGdczPmABfeupe9bdFNz8fbbXD99wf76huZqw+F2h7OWhW6K+g1hqxEJBvuMRwnOhvAdaZOY0RHTcz44PTgXnAGUoJSJTLgObx22tzg6LB7RCtVr6oUKTCY+2Ci0qahXS6pFc5zh7847FpwsjKo4e/QQc3bC5uKcy9WSvu/YXl+zWm/QC50LF1rXjZuo7B6SajlaPERQosLmUeczxptT88TNcRMcNWKZqR/l19wXj4lwsdIqOEflRpiOK37y+zXkVQBtSuPIe+gLh7g7l6QxsCyAG96PkUNVvtmPhzSJz4g/7gxFsb6UBJtMZwe2Ie8HJxPRGrNoaE7WnD56SN+2mOUCrxQeqNdLNg/v02xW4ImMlYnFPb0vUvwdqdbJuFl2kdDkHlMJWix0lu72mutPPsO1Hb5zVHWDtx7Rqb+EsokS6qamaWq0CCr2DUcI1d3b4IDUdT3toeVwaHF9yHvaiJoYplFhrPWx3kY2kOxN4wAX69ZBfEf/IjDkWWaZZRb4ORw9vL4Jl8uakbKVdj1nb8ekRJYKGZnOLF4E5XV5RonK9HT2mfL12WQwHCaFYGMNs7V3IXZYmIOnWsJk1hglVc7yxfn0pciGG58c1Yn3georKeYokLrB65rd1TOut1tOmhrqhs730O05tC3eRmOpJtxDoJiS9QZtHWa54Ua94PrxJ1jXRy9Rj2RWDlPkZVqA8lhSfEqlJakNil9/713un9b8wR//K/7F7295+tnH/Hf/ww9569HbfPfbv8FX3n4bVawKJNFbaU1lBNsTFdDAkhCMrT1dkecQ4kQQEn1jMNJ8771v8/V33qVZNjFdaDRodSy/ScHP0dJCiBwFWgTBcHXd8o//8WPqyvCdtw7BHyB3g1R/Q4oOx5PnT1l99CFfffsdmjODw4KHaiGcnC/4kz/9Ef/qT/4I17fY/kB/6DlsQ0zIznU4oEMQ7Wmlx1lH2wYv61Vd44H99R7vwe7DIne3P+Ccp7MVqgK38NQajBgWTcXTl9fcWMfJsmdR3/LjTz9AK8/N7sC+q3nw4II33nzE7e1LLq+e4PoVsvP0iwPX7VNWZsnKnCH8fMqDCFRNQ7NeYeoGpQwfPf+An958wHe+8j3ebt6JCwdNXcNyoTg9XfPg/kPa/Ut2t4GiL+juwYnFOej7PevNKW+/800OhwM/+dFPsM7T9w4nPjq2gOgqeM/ruFBzPjLxBOXMxjZUDKE8FGAaQ72pqZoKI2FxlRZ+ueNMXguJdkOJBn3rXe5Xo7cnKduxH02WqFn3D2w/REVRBj07vGZ33kiI1/qwhg8e0uF4JkyybqSvD69xCqtSJJoWS3lN7bn34BT73jv4Dxwvbi/xzgcmCxyI4/L6kj//0Z+QcQ2f2sJjfVj0WhvYVvrIriJ9S992bPcHBME6QizD6GEfk7mDaRw3ynpOTmq+/u6Cpg7OX25vOVy1iAPlBd94zErjXYijqE0YM9VScXZ6wsl6w/W+pe97RFmUwE8+/YynVzd89OETrq+3vHhxze3uMKLbU0QHFR3+Ut2V1ZzEuo5u/xIlUFUaZ/vIsjK5cJZZZvkLl92LBY9/8EZ+1xZnB+5/6zlipqPMLLN8OeXi4oLf/u1vIBLimp+envKbv/mbGQTSWv/SmDSeP3/Oj3/8Y9q2zU4es8wyyyxfZtm7d3ne/qf0/gzH4ue+v+sU/+AffJ1//I/f5nd+51P+1t/6mH/4D7/G7//+o38DuZ1llr/Colp8AEMpvAyKuODHNqKNgYOjO7hHKn/Ee0vGjmML8vG2ftKmv8G/wEc7qQz4cDaQTi2w09/HHzllrhjB3L44TwSAinDpIiDa4E1F7xz7rqXRGnQIdY3r6a2NhkKGewmGapEacR5lXHAczizLAxNuMAYXm6o+17oqw6E7baF4eO+UZaP57MlTPvmsY3t7zZ/+2Qs2mxMe3H/I6cnJxLEk4XfBCURFpgDvBuzIeVdgcgm/jdWWWGMFHlzc5/z0DG10dAQAIwNuN6WTTdhOClYR4bQQRRvF/mD58INrtFbc3/Qj3E38FB0MeOHtbkt1fcXZ5pTlUuU8KyM0i4qnzy55+uwJ3lqc73G9w3YWvdnwvb/3H3L12VN+97/5B5y9+ZBv/wd/C20M1npEQaUNCLSHPnT1sGeLzlq88zivEA2NAS2gUBij2B4OtN7TGIfRHZc3Ab9q+57OGtarJevNmq7ds2+3eFdB73F9T2u3rB6d8f3/4j+lqmtMXZcFvmtGKEXCWqZeLvm1f+9v8fDbX+PDH/4Zf/jP/wn/zv/lP+Fbv/X9UPtK0AqMEZqmYr1cYfsDXdzcKpDXRt47nOup6oaTkwustVy+uIzMzNHG4HzOTsBcy819oR+IhPc8MM9H/Daz+ip0rVFGk4Ix33FwKfoeMMILceBl4KIp6yYhxUdg6CGdlC/SOzBgyKn/leapMq10fX6WFHnwg82jNMWB3BnKhgyl+nIsVw1nFyf4K8++O0SMO9S3VZ7Vmw+4eOs+1XLB88un9BV85W//TnR8Al1XPLt6gdxeRVzbg7M4a+kim2V47/2AbU9Ng7F+sr/eqN95mlpzcWZ49uOf8Cf/7F+wf3nL4eUeXHjLXQfeKVCRgV5FO50RFk1NU9e0vQ1OVBLGlcubW7aHlqurW9pDx24XmKB9nG+iNWzkpJJa2fsx03hoU0vfH4INS8vANjNjyLPMMstfoLy2owcSDPPllOTT/6Ims8zk3hEHVHG3n14zGd1Gylh+2pG8lRPWNJ5d+iIjw50f/3f3gXckpnE38SL/xTk/1IlA4JIi6O9JWQWFcx6HwzqX45X5pNnjEVEoUyHKI9qwN1XcTe/Gz7vjBDFdRUxnkOmKafh9drKiMQ/47LNzzjZrnl3e8MlnH7NZn7JYLqjqCucd4iRQX8XJLe/gP6ILhZiJLs/Kw9PG2s/ZySmnm1Na19LZLnuv+1eAz1JweAWnDV+0otB38OzJjqYx9L2lSmwk+ZGpXw19u+s6Doc91vYkxgcPaCPUjWG/3/Pks6fgLOJ6bNfT7btQTgVoBVUKTeKDp7X1oX5i/CJrHc56hKDEJq/QrvMo57DGB/edGG9zf2jpEPBbrK057K9pD7eBhq9eo6ua5bqh7RXQI3gMBpxnd7hBe/DmNHveThvp88xjEmPdiIQwHIfuwMF1dH1LCs2EeLQSKqOoq4rlYoHrtyFtH8P1RGcLpQSlhaqqODk5w5g9WhucD/RlzheMPaUmWrabDK/cXSU5xtmrK7TWkTEnrZaHNKZlz4/ySR8ejznl5o7pSJGGr0ER90HRL4a5EVYQUwhp3q19L9NFwJCx/Kyj5ZF4Zei3UtYf0CwaTs43NE/GIQVCPE9PezhwefkivFIp7qC1OO+xLiy2uz44bHUuesLbHm8dfe8wWsfdDEX7HfHoyO8tw2VpjKoqxXpVBfrNsAbAHVyg8hRBRZq/sPAIu1aMUlS1DrEVRQXHuR7Wi7B4vN7tubrdcXuzY3u9pT209J2NbRlbpFTQi/z5UQ9J7eawtsUrQcdFyag0s6I+yyz/xsS2BtsO6qvSkeL4c2eyX5J4B7YleJ9VR8e/WWZpmprz83OsDeB6VVWcn59/IXlp25bLy8uZvWOWWWY5Lk5wnQLvEO2/FNOa8yv29uu4f032LO+FTz7Z8PSp42/8jce8/fYN5+cHlsuOrtP0/atZUGf58ojWgXHVOTc7Kn5pJbXLFA8e8Nnp6UGm+HCJx3ryjvVpiJbRvZ+j24hHipuOYsgjB4HpFrEyrfL4a2DKKb8lHp2pDNIJHz0PVDR6DlzO2dCaWC/SvdnqLIjSKAmhPpTSFObnUR0M34/l9cixEb7kc3abpkKrFbe3DU1dsdu33NxeUdcNpjKBKY6IC6YwMgmiK7Je5iMZVAcMObrnjBg4PIvFImyi8xbnwya9MhT3lCl3YCIZQsQMVSE4C9ttj9EK533cdDjkTyIg54u2cokVehzbBaVCmOq+77m92Ya51LsYzsGhKsPpG2+wv91x8/QF1aLBWYfoiDF5yeGLfA5jHZ6Rflsb8uRiiPLkuND3FksHvsV5Td8fsH2L0jVK14gOGJp1Am0Mix53pHX9gcoYThIbz4T1JPeQV3V3EUQrTh4+QDXCj/74D3j28WNuX76k3R8wTQi7o1TY1JnGc+8GFrFg+B/jdFppmqah63qUUmGDmU+teKTPyihLE5IePzoZcGodQ54XRqbECl7c9yq71IAgS+piBYac+m5pg5hgyH6cx7sYcgSYMztJkaeC2WSEITPBkCf1MpYCQ47ja71s2Jyfsj0cRnWW8maamuVZYFg7HPZ4PMv75+F9jxs+D+0hvqPx/rgj2DmHEhXx6GN1Ohwcjeh5aA5Hgn1BY/d7XnzwMba1+N7lMTw7VMRBR1R0NNOR/QehtxbvoA/k8rR9z6Hr6dqOru2w1t7RNST9k6K/jCwAQ2WHMtqYH537hi/re5ZZZpnlF5TXdvSoZAMoJDswHNHECAb9YcqaKpLFsVIryEnEQfNVa2sb1SlJk1VhIk36Down5fSA6brAkz31koIZmZOColmGgkh5StvtU2YAfNyanxwv8nNiTXgVakOCZ+i9ixNOVjWr9T3qxYbrfcdt22N7S9e2iA7XJZ3Zeejjdx09XiUqh4Jj5ChRtMK4YssFlhSf0/tC2zXNAmMMv/G97/LgwTm/96d/wv/2u5bnu1v+53/8/+Xb3/ouZw8eslmtuHdyAsgo7AZI9ohWcQIVF6nVvEV8pJ5D8CEC3yi/Eqva4vnpZ8/53T/+EfXqHu9908aG0KlBSOwknhD6pHee3imsD+eVtyz6jkaB9j5frYjMEF5wRfkFeHB+zrtvvsFmtYz5CYwQTbNgfbJGPNxeXtMsgnOF0hqUpu8s3b6jqWrOLk7pbcvt7pK2t3T7Fm8UtgsGdm9V9PK0KCWs1mHnZutCR24WFYtGc7h2tL2Hmx1ys2fdnKNPPd31Dbcvn/LGGwveuH9GzYHbT36E6ywrah6cPuKb3/wdLq+v+P0f/BEPLx5y9usPaIzidYnAPYGC8Or2mhcvX9D1PSKadx98lcVmxfnqHNv3wRkFRd2s2JwK+4Pm9tbStdehHZ2lty2npye88/bbLJcLTs/PqOuG5arG2pZKCy4yQQQHl6I/CMEpxoUjSoFzAiiUeFBJUR7e19P1hrcfPArhdESFbqJk1OPHviR33S3y4rNQjl3sfaNX3vm8FofYJZGMPUzhiZRWcgJJDCISF0MKqFOSaQdDoiZ1d/PrPSHkqQeJBDkSl9HOh/iUIYvC+t4pzbrio2dP0dqgjaaqwvskwM3lDT+6uhkWSr4oWHJ8SaFcUp1E6sjaVOim5tC17LoqxBA96uTBqz3H80UK33v6rkNhWJ2e4J2n7yxSGdCEHQBGs24W/MbXv45uGnb7G/bbKz578RzlLB/du4eqKm62e5QHH3dOuERjOda9Y12XRZbctmFk82EXh3Nge5yT4IAFqLqKoMIrFimzzDLLr77cPIH3/0dYvAnv/o0QymWWWWaZZZZZ/pLK/mXDJ7//iMXZgXvffPErxZ5lrfC//C9f5Qc/eIPvfOcZ/+V/+Xv8r//rV/iX//KNLzprs7yGvPXWW5yfn/P48WMeP378RWdnliOiaIJRLTtMHLXmT8ye3L1mhEckADddU4A6GRqVO7eONnj58a3B/joFKCa/fUJeMzCQMW0fCZalxLvLPI3YRHwBhhTGWkl4VjwfyypKsVzUnG5WVPUSbWoOnaN1IWyAszYbLssy5303KRRCBKASnjGipx3h9DIAsjmbMipvBkeKBxodcLdHDx+yWi359NlTfvrYsetbfvzBn3P/3gOa5Yq6rljWQ2iSYxuAJBrahyjLfoTJZZtoBuqHIjg8L293PH56ia6W3Lso8fJU3uC86EmhTwIDr4sbBwSPcTawgkRnC1Lbl9+K/rZaLDjbbKhrE68I92htqOoKAbr9IeBvtUFcYNR11uF6y8U77/C3/+//V3RTUZsKF8OreBGcDZtGvUssNAF/U1UoezKeG6MxWui9x/Ye2/ZI21OfLFDa4w4t3WHLZl2xXjZob2mvL/HOUaFZNWsuLt5ifzjw2SdPaV9csX3/I07v3ed7f+dvYhbFunZqhijMPN57Dl0L+30w5GvDb/+f/y6/8Tf/XW4eP+Gf//3/lq//9e/zzne/g9YVdS30/Z62dTjbRrNL2Ai5aBpONidUlaFZNGhtMJWJDgIhTEZgDU81PmQqbaSVURaTs1DRl+O3pqo5Wa2LjYJD+47HjGKwkTJt7uShrCqPkMBunx2YCpuYH989zjdxuIhHXXFNcoLJl/l4bSybyxcOjyzHvmx/i8wo2TkioMrf+Bvf5+E33+Wf/X/+F578j/8oh+pO7EftvuXy0BYjX9EZyveWATZPG+W0aMQIvbMoF1m9R+N3YSMq8z2qmFSHYSwO4b6FqmkIm2x93Lya7AlCrWvWF+cobej6jr5rud1vEe+5XiwRrWm7foiwYgeHolHrylDMkgxqnPc0rvvMwGRTT9EqD7e/Otr1LLPM8kXKazt6CIZIcjQMbHJn6hlbycYJcNdD7TWGMikmhnI+jp8DG95YSb6jzMXvwjjsynig9sX/d1T74dzU+DlS3oljeEw5HY+T53LRsKwNTbPEVAu2ncP7Duccfd+HkCNe54k/7bRP+SnzOlpHjNriWAl+Vl2H+0R8MABrw72LC5bLik9fXrI+PWd/c8lHn37I+b37bPcH6qoiNUr2si2zAsXu+LKOCso9yB6Mk2kQ7z23hwNPr26i96jLis3wfzS/xjpPvji+WBAY59A+OMWkv6STHauVZdNwslpjtMZ7l1lLjDFUdY0I2LZHLRuapqFXOs3Z4C1aaZaLBW0Hux2I80FRFwnKZtGSydnIxICKfRtqJ4WQCGwv4Pue4PHag3J412G7PUY8y9qAu6W9vcZhMBiaasnp6QOuty3Pnj2nVgt674ktdrRv3+0P4V1puzYwnDiHiGKzOOHs5BytKvreorXDK49SmqpZUNU1VWXQMayTdZ7O9ohSrNcrVus15xf3Yj/TaC2owKJGn3cqpP4T85Jeb1/UXlSmUrRXnxauItRVxWqxzM5bI960QuFMvWRU8tiPp8b60U8Z+thI8x4p6sORUV+b3JI9eSGPrxIX+n3Rl++q/MM578p3oiyVDwwpMYmqqalqRbWoI7tK+IvxcOgOHbf7PUMr+NwG5RBeuvJZF0JUmU1wgQmOPXY0bh2tRRmfTeVOXtHee+gdaDB1XOy6qAwLiBJEa6q65uL8DDEVL19e0R8OuJeX0Fu2yqCaBnEpREva+cBdmQ6XPn8M475Pl8aBRjw2LjJDPTLE2Zlllln+6km3g5cfQieMmdcm4n2kK+qZx4tZZpllllm+rGJbw+5ZgIxcr0BcYBr92YvJL714L3z88QmffLLm+9//lO997xl/+IcPvuhszfIaIiKs12tWqxUvX778orMzyytEZAgZPaAHk8Hjzs70aSI/B4YsR645Bo2W1x1NrrDexh34PtEBTNMpgIWfibONnCdekc9pYgLGmMCYoSuUMnSqg2h4dM5FY6G/gyHfJYD1R9M/VvSj9XW0cBEnirjScrnAGMXtYU/dLOjbPVc3VyyWSzpr0TZu2JPBsnA02TttWTSkj+3BuDp9BPtb27M9tDEshCNt95uaCYY2GONDgo8OHgn8GTDko3n0oY3qqgqbzApkT2mFTuze1mV2EycJwwZwLNdr7r/1kL5v2d5e4Wxg/PZKxn04M9j4GJo6MJAQcVBRMUC5J2xO8pFZW8Knsz1KfGC69h22OxB4PBRaVzTNirazbLc7ti9e8vxHH2APIRz58fYBvMf2Ftt12RhuraW3fdz8pXjw9jvUdc0f/uQxn/7wx7zxrW/iY56VMSit0WpgDkkbyhChriuqumKxWMZ+JpG5xB/v20W/voP7xXcwOe84PzgRaa2pjAEvd++700mTMeqVaOddkehEMbLqvxpDHp1Pt0yMGGmImjTHkXzI6GM89sn0qtGmyNNHDzh5eI+T3/39EbtKIidxNrA++yLzw3h/F6HGR38XQNXhfXFxLEuM4TlHMqQzLksaQ0oMORbLhQ19Smu8C5ukR/HXI3PLcrEApTgcDsGpah9CvXSiEG3i+x9f0tfZyTdpl+kQLwX4f5Rpfd4tOMsss/wFyGs7evStRRQ0dVhY3aGtK7zVfB6272iWxIviPZOJcWpoKycfHyYGL5INu6ORU0KMKzyIHk+M2fMvgu5jD8H4X1xAqPQ8N2TI4yO1FPikRI0TOFK2VL5AF3XY7+g8vPvVdzm/d85+b2lby7P9nu2h5+rymqeffMbJ2QknF6c452hdzHJU1ns81qcFkw7hUMYm10lFlxphmbFRJo98F0BTVyu0MnzvG9+i1hXv/+h9/vff/ScsmpqzhbCqCnYNMfF7ao7AG9fF833v6HsbmQVUkZNBsSorUInCKMOjizN+7atvcu98jcchme6lNMEGw69SgR0jKGaFsqI0Igrn+0DtFp/jU70UBmklirpesFiuaA8Httst6+WGRbOkaRpOTzac3Dvn5M37fPub3+S3vvddPv7kMe+//0MOuz1bc8ty1XC6rLkVy3Oncd6ArhCtcASlqFrUQQFRfciCBG/9JsZzvLw84K1nv7f0vWexrKhqw2F3w8unn1D5jkdnG7puywef/BQjLbW0eFWBrrnd7zg4wXlFrRbUqqZGfuYLX/YiD1jnOFzfsHvxEtt2IIIWhUbx/PlLrm/3vPXoAffvneX6M0pRG1AqOLj0bc9u13KzvOFy/xTfeO5XbwfvdhMWPtZZemfxOrJFOJcVIB+aOC+kk1NPuSDLoYNirL3UN1IYkTBqqKwIJyW5dCC7A1hOtLPs6CwyOT/pvpN0sl4Y/SkkDgtISmpYvHnn8qK1dF4TH9+ZeKlyNl4h47zFAkrq337o6eG8wmNQmLCcE41SOirEBAo7FajzUiZHS+hJnNlUXCnK4q0P3h/eZ7aSYbUh4/uKdlBKYXRYuIEPzj91cC4McTeDY4dojTZCtdCsHp7TO+HpJ0/pnefm9has5Z4N/bBtW5yzWB8YYw7eB4ersi3zwqAAG2I3SsSbCUTxzuG9DXNNbrQwrqVtM87L3X4xyyyzzFJKv4cP/xlsX8Du8ovOzSyzzDLLLLN8rrTXNZ/94UPqk5aLb1yiqzlUxiyzzPL54mww1BoNI5Ak73QJiEA0TceTMhgzpxDmxMiZLh/SvZuHAYKYXhgSTJjLGAuaWlIZjP6j42NDZol3ZLAo4izZeJmLWWDdR3HwwG7aty2rzYaLh4/o+xAaetf3dNZx2B/Y3txSL2qaRYP3AS/OMIUPyLxLIFjEw8Yo/LSsk0xNIPsRRj+AVSTATqsKqRUPzu+hRfH88jkfPv4Qow0LDZVWkB2AFCWdt0SAzMXzgbEk4X8qV+CovovwPYKgRLFeLLh3tmG5qIYiTQ3csT7CxrvYF0oMWVTEDR0Dk3iJYvlcdFESmSaqwNTdddSmxpgKow1NU9MsFzSbFfcvLnjj4QOub254/vw5fd/TqZaqMiyM5smnL/i9f/iPqDcbvvJv/Tb1ahG7VWCzDWQsbgTCmSrkb7/r8R763uEcGKPQWtH3LfvtDdpb1osaazte3rxEYdFiCSFHNV3fYSOWrsWgRWcu7c+Tw27P+//4/+D66XOun78I/fDQ0u/2+D6FSw7/drsDl5fX7PdttgcF27ugdcRqfcCRu87SVgf2/Ravlyz1CUoUSgsigSHbRWYWn1gykjF95C0wxjAHG1DAkAdPCR9Pp822xTbnlNYIQy6fMX4URY8ZEpDJNenUnQFogKFT3sq857EzHnT+OIacLEUZyo0hfxJOPBpfiwISx7t8Pr4raeN3ZDyRZMkRCkYkX1S93B3HY3nFSyYVAhl266YBKo+DKU9DpYVf5TsvOfsiIYwLMby2z/kNOLM2Qr1eYj3c3tzifAhjivMsvaBF6PuA9/ro8NNDcMwaNcBQZikyJkKx1yeF1/LZjpElMncPYzWzzDLLLH8h8tqOHtY6lB8GtPEgRaEQ3qXDzxflMTFPCRwhP+LORDz5Ph4Dj2n7MR8j9TUxYBRH46Pv7MxPE7cM95IH6Mlj7sRSPJZfj+t7egfLzYZ7Dx/x8vIKtju8Erresd+3bK9vaZoaXJhYgpLusyfhoLMrBmt1KVPApczbq2SayHCP1hVaKx5c3KdSwm57TV0vaeqaRSXUJnpy+sT0Mii+YeJXgWouKenRWDtWtn3MtxpNnMlLdL1c8ODilNWiyTUw1HTKe/BgV1lBL9tnSMv5QHHnk1Icr01ppdhqWhuMqdlttxz2exb1Ek/w8G2ahsVqyfJ0w8M3HvHee+/hPXz00cfBMNx1LBY1Ta1pOw1e4b1ClAaV6B4FbVTsT6XBPigeXuD2pqM7OPrOBhaQZYUyir47sN96TivNelGzdR0vby5plGOhe8TUYByHvqWzDucFIwYjGp0U2bJ6Jr3Ae0/vAk0eeNq+p93t6bbb6MUtWZna7Q68fHnDvbOTgb1BQhgfrWVQ0p2jby1t27HrblnaDYjKXv+iZFCAYmZ8dJDKbVnqxLHRfHGyWOcMLJTxvQ4OYEF5LJ08co/3o0eM34aChSZd5Msv5Trxc1+1ggKPYbgUITPahGuGZ5VrhNzn45e8iBlp6GmsGvKW0lG5gAI+KOlK4p9SI1rDxMwDYxessiy53/hxkSUeHMbKcQq+qPwy16n9BiU95scoxAXnEU9whlJaEA2q0tTrJb513N7s6DrLdrtFOY80DVo01vb03tGhQ2gn73F5DhrKOaZmnBbX57+w0C/66lCo2Gdjvc2K+iyz/NWUQDcUYowdk7C9CvoDXH4It09+ufmb5QsR56DvFUp5lJoniFlmmeUvn9jWcPvEYHvF+de+6Ny8pqQ5N4krHLUn4pzQdWpk6Jtllll+MXEuGtH1BC2dGmDvYMilkZHPwVhKOXLhdGNhlsJ464+eKTAjD+W44CcXTeCiEQNJiVmNMMppIse+hnCxzjlMXbNcrznsD7Rth1cSsI0Y/lsbBb4mYca57CPI+IhRevTQUQYnXyf1OGVZKXB+pTTKC6vlEi3QdQe0qtAxrIhWhaFWBmN0spImS4GnxAjLvJcG5WRoDm2UGAbqyrBaNIGdAY8Xz93+dzys81gkM1SM8MOyniU5KiiU0vS+w/Y9TptQLYUTiFnUrDdr7l3cA+D6+jrky1qMCUzH/XbHp+//mNX9C97+/m/mMgogSo0cjobj4bM9OJz1OcwERiFacLanx9NoRa01nXfs28AObcQhKmzS6p3NGyOVKLQojDHo1GiTLuEB5yzd/sCTn3zIy08/C+dNwOFUZPjI2JsIvXV0vcU5myt9jOVG3M2HsDbWOjrXYnydAMPMJjHaS+ZT75eyO95p2/J9EMhRiWR0bWLEkehYkyp7/B6UAWPGcqQzpXunp8qMHr337tiTfZuis4c/et8kiXKsuoMhF/cXH1JWpCe3IT6GspZgl8rY9rExRoZEJbfTcZvEHQA8/SoaeXiPB0B9cBiJGLKKeGxiUxcJvmUKRCt0ZfDWc2j70L+6LvjaGI2gYt8TbMR1nR/ed5l2mFEBGADy7LQSKt6PG6C4PB1/FfY+yyyzzPLzyWs7enTuBkVF7U4ZWxCLwVwAr5hOEmM5OvIXnz4qxOUVxaxbzq2qYHfwxcCZxtR0cTIMK6LXnZ/cR9667R3DRJE9Qo/n/GgZj83pIpyf3QPTYMyKfaeodY1pHLpvOVy/oDts8dhoqE0gQ2F59EM9eaXwaabyciRjP8vn9nMym48P9dnUDefnF3znG9/C/d2eNx+9yXp9D2PqeP3goi7KIKrCo/AIGo/G4VyPdTbuiC/nxcQAkxTA8Bl4B+CtB/dZVYr7Fw9Q6FgfJUjjCXR8wTkheW2OfHKUAh0dC0TCAsNAZg2c9Lfg/ukwVU0tgjIacDSVYbNc8K2vvMv+t/9tvvKVtzk52WC0sL+5wjlH3dTUzYJFc8KhBfEqhHJZNigdFAOl4GQdPKVvr4S+h90uMHsslwathaqqgqLfdjjrUEpwzrHb79kfWuRU8I1g7RrxK6zt2dsD4iyI42r7hE+e/jHt3nJ6fs5mcxIcPX5Gj9jtdvyjf/r/4/nlC/pO0bUd7//+v+Dq+VOWG0XV6KyvbDYrRBsWy2Wo89RnhCFmn4R4eFVl6DrPJ4932PaGN+89p2ka/GJF31vqeoWjYx+s8IFijcFJZ3iV00LLE8lb4jkpHCaGP5+3MPjwunjC6zEeGuIzYzcuF64SjyOF8p++EDKgfHwN7zrAiR++hGIUoMJEZ0+H82olKdDEPMvgmuAj9Vx2ypiMFzb36dgyo0UzrM9WPHr3Ic71YeHXWQ4HW2Tg89TMYcwRAnPLUDeevrN0bR+yraUYUGWgYsxPGD9HBLBgDyrQQmvwtsPu9uimpjk7QRuN0gqjNKcPzoCKt8wZfWv5+IMP6fd7qv0OrGV/cByA7bal6y277Z6+73Hl4saDlzT+TCRo9iSHO3EOsT14O0wR6brYN9MYNMsss/wVlPV9eO/fB30Ourp7vtvCRz+A/SUcrn65eZvlC5M/+qMHXF/XfPe7z/mbf/PjLzo7s8wyyyx/NaTfw8c/gH2cb72D22d3LnNO+Cf/5G1++MNzfvrT019uHmeZ5VdYnG8RFM43mTl/DHzEzwHUGbCQYxcftcYn6+F4k5CU97li7V/uPM/Uq5PHJ6BodD3FfZOffpxsvuYYVFsW6+jviEuIsGiWbFYnKFXRW0GLZmE8ylnsYY/rOwoTZIEhH8Hjj+1MGlVvacz3r8CZj+S7fGQBrBptkOWSB+f38V/3bNZrqnoZwo1MMycKkYD1Bi7esA3QJ7aGuBt+jCEPaYgfjMBKhM1qSaVguVzF1KZ1EvC5HOJkUqRkHM6bBpEYqhdcxP3u7NCPCJdSgX1WVOCHNUpRV4Z7p6f0b7zN6ekJdVOjROjaA947tNFxs2GD1lVkOwgYqjE6sx80dcAiu0PYSNl3gdnDmMhWoHTMoyscFTx939NbC43gNXhfI1RhQx59NIJ4Du2Wm+0TbO9oFgtWX3mHrzx8g8Vqha7raSVxuL3lz//p73J7dU13tqQ6eRfnAua4tS1y+YyqFpRRGe3/5r/929x79yu8+c2vMXG/IYd6ktAntFZY67m57vC2ZbPcYYwBU+GcR5sK31v6yfiQHQ5Ks0/8kiFjRl8o340RxjcywA/XZ/RwOp7FH8NGyJRU+d4FnDxlJnXJNBZKepdklOu7prNS8rjp8ya+4TYZjW2DSWycYMbaR6UeHlYtKtanK64/ecwf/YP/iftffZc3vvfdaSY+X9Kw4oeUPT479eAJLN3Fs5NTz/CEI89x4HrJIc29s7i+Q7TGLBp0HewTSmua1YIGxYla4Kzj6uoK1/forgPn6HuhB7rO4pyj6/oYVobcZnfHvvipJDoVh3ymcC0hlLgbCpHA5OSQ90qnxFlmmWWWn09e29HD+UBn5LxDlRNoksnENjblCZlOLY/Zcnd89uW9SQeTcgZgUJrL4+FZIUk/8vkoFXHxyRgdjxdhCHxBtz/epV4o/3cyK5Pf4+/D1Cgsl2vMYoM2Db0TaqVDDD9n6fc7XN/i8m7xWF9FOXKteAlOHpL4M45NBj9rgnidCWQojzEGY1a88fAhGs96c0rdrHOIhZI2TJRBpCdNfkp8VtJdoqcaVAygVCaGZ6dwE2ebNetFRVOvIAftcTmFIa9++PCDMuRJjjGDF7HSoBU4BX7wMRkX3XuU1hiRuBjxaK1o6oqHF/d4792vcn7vnKYJi9busEOURlcNVVVRVQuMPiA+sCZUlQRaQB/K1jSCd56tF3zvadsQ/qFWCqlUUPZN8Nh2yo2UdOc89RoqJYhvUC6wlTjbBadap9i3N7y8/gTlFyyXG5rFYrqsOypt1/Kn7/8JHz5+zGGn6DvLzeOf0u+uMfU96maVFzVNU6O0oaqqEK4i1zjZyxqCrqO1xvZw9bJjWR847G4R76hMnZV0E3xUIgPHwPUjg3Y87plRP04F82kxNilp9uaV6HHtRqeHEcGP1wMDnaYM16XxyJd3DpKdKfzQH4fsDARzdzeLjd+M/MPF0FOZFnTs0DIsdgcXnuHRaewqqfzCoXrRcHrvlHa/o91u42JgGvrprpSOGsQFSGZRie+ydVFJj9cfXUflUg9ae3JD8R58D95IiAblHa7boWqoloJE5xGlDMtmhTErzk7fpmt7tpfX7EWjD3ucd3R9CNeyvd3Rtl2ksXR3X3lfTEklCJSUbxf7tffg0+6DNP75nEaum9dZ5MzyFy4+t8WEdWWWWX5ZUm/gwa8By+PnbQvPfwS757/UbM3yxconn2z45JMNi4Xlr//1xzj3xQM5aZycx8pZZpnlV1ZsD89//BrsWcKPf3zOj398FjYMq0TZ/cWP1bO8ngTsYZ7Pvmzi6cHraEB8BYZcgjvxruH/jJ6QLYSjZs4L+HCigKH9OLlhwV9iyHkzzhTeGdb4kkEnJgmmSyKm6QvcKqfx6ro5fnK8YaSuGxbLJUobnActgtYK8S44eXib8e/xBhQyVjYgLQkro9iV/qq8yeec86PL8qGxbRalBKUq1usVIvep6+DEcMfPQwgGfhnYlxJu6iOOXN4gGYOhwG3IDSh4FnVNbTRaV/mOjDuPPHJKe0DRVdJ1RfoRgh8Zne/UkfchFHIM+wLBaG20YrVccnF2xmK5CM4bAq5vQRRKG7TWaGVQ0eFFEFQKaxy7ttbh4V2EpKwLba8l9r+02c4THT3Cp3NB39eVoAVQJrDm4rHORcO/pXcHDu0N4g1VVbM6WfLGvfvoKVNlLFvftnz6/o+4ubqi+t7XMZslfadw1tHevMC1LUov0Sa9n8LDr36Fe195m7qqc7huKTDFEooTCYb7w95R6R7bdwjBmcZ7j1IKpQKM6XlFP5lKeTj32aNAZexivsCAY0OU+DDF+ATlS5fP/CwZuu/06nBmPJRNDRfltTmh4p1Mqcu4nFOGkTLbabwWNbLsmcqwWC85XF9z++w5pqp49J1fO5KXUsZ1lt/TAiMHcsj10dAzBW3z4aER87vtPa53mQkaPM72KC0oA2JSFShMbVCqZtGcYG1gpOlRSN/jvcM6jwW6rsNal9+faYYiHB43lE/yWgwoku+dnC8T+tw6nGWWWWZ5fXltRw+jThAxUQljmAjS4JWYMEqFaaKoQnlqSGC4amw4yw4EkpRrF2+NE54dlJcy7pXceWAc/p0fFoDFBD8yzMlovvnZkpQeN1ILGXIRtMLlehFiK16cstqc8uSTT3j24harK07uXYCpudm1LNvgbWsztejgsoAbFDytBLCEiGE6ZYaxxn5kQikn+tGxMu/lfSpfU9cLzs9OqOtFrMfYagJaaYyuMGYVFbnoVOMAR/CK7AjKbzFzDwu+Mi8qLFp8cADQ2mB0zbRlB0ltF+q6DD0BUWnw4OICR8X4bKmqhpiMIR3roHfBOUFrjXOW3aHDOYtRiuVywenpCS2eD5694MnVNbv9HrNYsFo0LNdL3r44odGWDy9q9q1nu9uBh84Lziu66G166BxtbxE8WsD2PXhFpU1YJBgD4rG2x/cWZWoqU1OrJZVf0Cw2LKo1t1eO65uXnC7PuP/wK1TqhI8/eM756RnvvHHOyca8kkl+JA76rePwcs8nn3zIfneL6nuUeKwrlBXxNJWhrkKYFu9tHAAMompMtUCpKi/AlBbQwemlNg3L9X3quoqhWxTGNPS9QBe82nsbHtRbiycuaHPvuNuzT89OWK6W2L5ne7sdWl8kOPkU7Z118PgqqNE4UIQOicUdYhoW9wnZASOF/UhJ53FxNECWSnXxxvn4FoxW54SVZPGeujjWDcNvwZxEXrbmQ2E9OF6AQGAI8c5z/+IeldE8e/KUzz5+jLU78O2d4WK0tLjz+rlhuI6VIsT4miq0mdZ65KiT3/dSE87Dfgjz450DbxGlkVojlaJZ1IgxWIS29bzYhjimDx+eoqsFLqa1XDXgOh4/9+wOPVddR+ccXdvhegs20MIqH+Is5lYfFTFVtITxPfYfkVixcQWaWFViZYdrPTPI+AWK956PPvqIq6srrq5mtoRZZpnlyyXvv3/Bf/VffY8nT1ZfuLPHixcv+OSTT7i9vZ2dPWaZZZZZovzO73zKd77znN/7vYf84R8+4NX4wyxfFnnw4AF1XfPo0TNEPvuiszNLIUoaQGe8ZGxMHGyN+cBIinfvSOiUYMhOCfi7t6dd83kjQEQ20m73SV4mN+fne3+cq7PEWAYM+TX1qclGpuJE/lTa8N7f+D5f+63f4O1vfo3NcsH25obbXYcTTb1cgtK0naWqB3bjnNIEnlYJz8AF8D5jyDL5PFKGkT15iicnAH50EQm108awaBq0NvH5A1KrJGGzVdxEWDSMBLaloC9PMeSEv5X5kIxNiVJopaLTRFGGYw0poUyjDUrx8mED4bBpcMAToytBtGs4Dy4ycejYP3sbQpcoESpjaJoa6z0vt3tuDwe63qJMwHxNZThZNmyWNfVCU9WCYME7nISSurAfDms9ttjs6lwIVZ1YlUUFKmPnXNiwpHRgGpEKRQhTblRNe/C07Z7GLFitTtHScP1yx6JpOFkvaBo1gjFfKR5c5/F7y83NC/q+DUy4uX6GvqJ1CB396Z/+GS9++hGPvv0ej977BohGKROYXRKEGrE3EUErg6mWA74YN34pZcH1eBccX0DQ3oVurkaBge707KapMSZsXGR0nYRwP6VppWxzxl3eJwy5hGQL9uA7P8XnA6PqnXqnFe8LRf/02Y6WfwC+eEgY+9J1krDlNCaWNTKGqfOzRnUVseqv/bVfZ3my4ad/8Me8/8/+BS8++oQ//Af/M2dvvclb3/21gomjkLLgRaWFnwlYD/iwUjGUd2YHZzRODxs6xzi498Kzn3zI449/xPblizA2VDo4VKnANN9ZuNpZFtqzXi9QymT831QGvON66+l6xyGGsnc2YtMuZb2sv6HShpYcsOLkVChS1EE+ENuqmL7ujqGzzDLLLP968tqOHkqWKKXJ08tIIZdBEzriXJB5NPx4LBuuHSahkXHUj68O2/3jw73E3dXp0Xc0+9E3Sd/8ndNDeSaTcZ48i+LeGXolWc9dcfUw2CfFsGlqVusFZ+sVm5M1nzyGl7d7nGgWmw1oze7Q0XY9NtI63V1UhLrS2UPYQhH25PVDtqS0phPxcc03UahVxrBeLVE60balNAStQogSpRcobYsKC9Rh1gYHilQr5bfxU1NLhX/BgcSQnFhyeJDRDptkrFWDUblgdoi+JmFnDpF2LzMTpAXgMHn76BhiVHAIaduOruvwLuSnripW6xUv9nue3dxytd3Rdi3UNVSGumm4v1lh3Z7lpsJtO3ZbG51NNHiPdeAsdNbRO5d1PWdDexofQpOIUigEewixHrVpMKZCyxrtNyyqFZvNisPtNX1rMarh4uwRRi14/vSGxizYnGiWS8Xx9p30Cu+xe0d32/His4+53V6yWZ/T1ItMJyaERXWlDUoZUILzFjAIGpRBmxqldK5XibEUtSiMrqibE6pKIXII8R+1QWkHHAqv87BoEQmMJkqGt2qk9HnParng7PyUp0+ekVXAVNwU4ahQ1EvDfliADKPRoKhFx7JiXCh1fa/G73vpIDIax+5Uu4+1WIxz5V/Mc1AEg1IexoPgU1Aqk8NjJnmBSAo0jFy+eMbJZsPJZoNrLZdPX3A4dIUGfeyNHN7LcUniM4qBMnnfh10cKqeXFyLTus9/0dHDxzdWFJiwENQmjAHWC/vO8+zGslx4HuklyizyYqqpa/q65srBdW9p9wdsb8N7NQwEYbQ8+joUi8GkoCdnD5F8LLHHjCtJhs9ZvhBxzvHs2TM++2wGeWeZZZYvnzx+vOHx480XnQ0Abm5u+PDDD7/obMwyyyyzfKnkm9+85O/8nQ+5vGyio8csX2YREc7OzuKfxft5DfBlEqGKWGI+cBdQPYrjFmhJsk/mNHz+TM4bw33pQ+JuHp+xvpFBzd+BUMZpTH+/it3nX3fZP9oIk54z3qwmSvPmt9+jaZasNxvquuLGw77t8SKYugZReZNgZmpLCFCumoTYDMwW43J+TiEGuLc4cOT7nTAvg+FbK4XU0YA/QdeF5JhgxptlEmzlyv2Ufoy1JIaW4qZUlyIqsjKHzPvcD470l6JmmNZSYR4YkcGMSjrkzxMN1QLWRgzKB5xaa01VVez7nl3bcuh6rO1Ba4h417KuWNSGqlZh82SsBIdCeYkRhQXrPS7ieoH1wuPUsIEtb2R0DudsDOmiUVKjfI1RFXVdYbsDzgaGjMVihZKK3bZFK0PdCKYaNX5RGZNKAFzv8Z1ld3tF1+6p6wXamFGLi3hUtC1cfvSYH/+Lf0l9esKj974JosJGr9hxJJVDYigfpdCmQStB6CM2p4p+k5jdh/cgjwUp4wn4jVJVhqZp0EYP1x0bowp25fQu5X5QGjSKe6d2pGla4VzRh48PSIWkgbB8T/z4Mz0x4a8Jv4/vzeBodbwRS/+zjP4W+Xr0tXd59LV36bZ7fvyDP2D77JJnH37C24eON7/7rcGhpMxLyntREeUrnc6FnibxPZPxhUXblRjyUA2e6ydP+eQHv4fSgqk1IjqGTwr2oN56tq2D3rMWg6ihbxqtcVpzAA7OY/s+MIOURoJkcxplTIbBYVTistULB7F8KvW12A65SWYceZZZZvnF5bUdPQ6HFqU1Vb1CiSc7FcSBzxMYExQTIqWR7vUKxTAdcdOBM8pAbjFIacR08UBW7YbFQanIv8KuV2RnouxlJpEi7z4aV+PW+mR8dmLG16X51YV4g7qqqJoaj6fvDtzse57vPDfblsPtju3NlpvrHbvTLe3hlr4/hCkparcej8OBErQxaGMQqUEqmMYdvFuz3K2BaW1MK3h63CPKoKslogpFKKelQUzIj5hoGE0auo9l8ThrsdYGJwCB4MZQLmoklyf4mZehOASPxdPHttcIgQ1jMBX7aM8dvqmihhQSQ6s0HETnrkVxt3MW23dUeoVWDUo5lHYYAeWCot5bx9Jo3tjUfKCE6+sWtb9mu3c8WG74xne+R/XZY5qf/Bm7fcfBhicsdGTAiN7YojXiBNd2ADSmwigVlHXruDh7SFOveP78E25vr1g0msUSrL3l6mbHm1/9Pt/+7m/x/h//gCdPP0ZqBdrjjWBrTYvi+sZT4eHkFd1j0pISa6Wqa2q7xCuwBOedtF7yEJxQtOLQW9rW0hioTTDu67pGjB71qrDeUPnd0dqwWNR4Kur1Nb3sYLvNyjmxxZO7lIcQYoRB+TTxecYojCqcQRQoDZI8ahSIj4pn8p4tCj0aplzq93fVtLR0TopoGm0cjHZNJP3NJ2AhJzd5D3M+4iImevx4iQu7OMzq6KmSdq2MlqdSOISVynDYzhD+nAv0l8Lg4SCh/ynRYwCGcfVM62C4Zij/aHNDbrXhqkFxV3hc8bzhSSmmrChBagEdDPdt59jd9HSdZ7vzKK04WzUsmh666zAeqFM8nnpR0/Y1trd0h0C15/FUTYUSod332N4WJSpKJgObS9oJkRzHSm/zxAwUfvtizC/no1lmmWWWWWaZZZZZZplllll+GfKnf3rB3//73+a99y757d+eHT6+DNL3FlEepavByFjgrykkrYwA2yM4ZXYkOGJEPAqBlga6yS0prRzOd5rmgCG/CgW5s0EwX1bmUwbQKmPI6aqIeou6k06wZ8aQ00qhIqbmnKXtHbve03YW23V0bUd76OnqDtu3OGcHPN0n7CrkNzHpBiaPEtQrLNOj4vpxufIF5YX+7mkYyi2AV4iqGDG65mQFRIc8SbFZMGFZ8dPH0AkpjHFm18hZSGmnEL2xhmNbJ8RuYOcYoWmplob6itUyIEYSGDG0wXYKwY5S8ARjs7cWMRVKDE5AVB/x45CK8x6jFOta8xJoDw7pD3S9Z13VXNx/wLPzi4j1a6wH6wk4Z2KR9QGPRjzeJRZsjSIyVDvPYrHG6Ird7pq29RitMBU413JoOzZnb3L/wRs8f/oJt7fXmf3YCzgtkUUXNB6acZPdaet8OIaR0RpnqrjpzOdmDt0iYn0EZ5UubciKDisqOr0ELDH04eAXMmxaTGzQXjS6bnHSQZc2raXWH9otdcfUWOKlIO8VEvFz7o4S0dbi3R0Voih4edqPu9TxoSznKfW3CS59Z/yZvnP+yPUJZy/fydDDU+D7tL027aNOOO6x0W1woFLRjpNCHg3PfPCNr/Lr/9Hf5ZMf/og//8HvH0vllcPFXQxZytP5jczlinXmE7aNpayEPNQIMcQ3kU3H0zuHtZ6uB33RsjCehXbgWjwOJHRubTTaaZwL9irvPF4C7iwItncx1HmqiFeg45I2CIYMlRhy2nQcOswEMJ4Mp7PMMsssv4i8tqNH23XovNt6In4Yqob5LQyykiao4jMZJ4/JXbY7n3W8PALGiTlPTSNjaTnDlgPw8H1iW40xs6YPj0q3pIHYjxYj5EE8Dt6jScwj0Z3Wi0JQKFOh6xpw2L5j2zpeHjzbfUe337Pf7tne7tjvd7TtLsSfi0bErDzGRykdaM2Q5BmdteijdVq2ylAXfnL+yKJpXFsxBt7i+HUSFw0S85Wf4of6w+Gcw1kXjKjpn1dFauHOQV8XhEGxc95j6QCFx6PwBemgz08svwk+OnsElgxjKkwVdxdkr+6k1juc63G2B29QNCg5oKQLzgMCIoJzUBvFpq5plLDddnjfcnO1pf/GN3n769+kNYq6alBqSxtDb6xVCGuRWEMCjV4IFYP3KAne1iF6hedkfcrpyT32+2sO7Y6mUSwa2B627A89q9MTvvprv8Gz558itQaj4lpJcJWmQ9huYW2OvVvHWzx5ylZVTWUbEMHiQHxklAhKiqhgDO9tx27foheKWmuUEnRdobQelPv0f+HNqrSiWaywXlMtVxg74p/I96n4TiV92yXPWoLTjDGC0YIWKSNrxFc09DvxUiitPivVgwKeqBfLLi/F/6U6NubuGQ1xxEWhFNd4sjewZBYQGT9HUncfvg9sM8NCVnK9FL29WJyQy5BWgUWV+3if8sMzI6Vl2E3BZCgZxolpaJiUizSWj+ujfH+HfKWxUiQsF0ZrkaKuUKAqARUcPQ6d4/LasttZXrzo2KwrvnVe01QOsVuceJxfA4KpK0xV43pH3/ZY7wL7TB3invadC44eo5WXjD6IecvUl7EgUpSt7NW42G/1cYaVWWaZZZZZZplllllm+cstI+13llm+dPLTn57x05+e0fc/nR09viRinUXdwRoHKfGpYCiWMbZRACqZ7DmfmFoRp4mnBxRrfZnkJIEWI2x6bDC9kxWRCczhC+xkuGZkjCyMpAmfAYkbXdKtvkgi4g9KB+M3HucsnfUcLHS9w/Y9fdfTdR297UKoZ2ehwJDL4gSG3bAJaNh0U+b5Z+HBxzDkop7usJ2G8yEkyzGzQwE+SdqaV7ZqgeqmjWBl3fsxPjZNVoqO5L3HkTb7hM1fAxI0xpAzNi7lhqWIhetkiBgw5CGPyVaiEAwigXUibDiLt3nQSqi1xiih6y2+s8ihw11ccHJ+wfrkBK0MIoJ1ATNOGGfOoxLED2wngkKUZBywqRuaeknfH+htF/BSA13f0VlH1TSc3X/EbncLRkBLbgKvFY7gO1EpCgx1UsfTr9HirrRBuRDW26V6LJs6to1z0dEjhqwXkbAJsnx3MnvP8CARwZgK7wVtqhiuhdxymX0j90HJ2UtpBebhWK/IgJembiyeERNQTP0uhswRDLmQEiN+VQWmh3h/Zz/iEHplXJYymYRUDn09jaHTcbHMuL+bhVElMQyLozEy3HT+9lu8Vy/oreVH//IPjo/L5Zg2hpIZHYy/R+HCj2LIEVN/lRKahhHCdb3z7A+Orvfsd5bNvqPWUGmPuC7afgJTvdIq2C7iZlsX20LrMFY657lrBk3lHIPaMnlX8kiROorEH6nTpE2YM4Y8yyyz/AXJazt6rFbLaOhXcYCKapCDQLOfBjSXKaLKiS0rQMj4cinHtGS0nCjU0/EuzblpolLTO7J7NjA4Y5QTcr5aCnXPJxVPIFLL5Uk1MwxIfmZIKymkPs+LwlA/iVLMWhe9rS1KWZzbg7vFGKiXC0xVgQht23J1dcV+t81B+LIno/coBZVRGG0QqYDqeAUx5G04JpPzaRb1k+Plwqm8VjGYu4eKlFhmJR6tg7exJ9DJOe+wTuj7lq470LYHDm1LLcHbN9CzpdQG87USlf/K2f7x08/484//nAfn9/jaW++iVWwqPPiw114rUBIZPcRRGTDG50WPVoJRgR1BJE7ahZ7uncc7x1V/jZM9Cyy1UXR9j3U9VVNxenbGYlWxXFecXtzDVCYqBBIZP/qgSPcHRHouzmqsdXQHi1UetQoLDNd1uN5Tr1ex3hzWWZAQNkafLKnub5BnGk+PtwrXQ6UMuqn58Ifv8w9v/muefPoBbd/jeoe2grQd7voKqRfU2mH0wLHwMyU5G0hgyNAimLioct7T946+c2gdmE5ut1suX96gz2HZ1GFQ6LsQzy61bNLu88LTsd1veXb9Gbc3W376kw/o2h7nwrXeMfQhlxxMsvpEWpxtTk5YrRuWy0Xp6M3tzUs++9RTmSXGLPGiiy47Hi3KIUFUMeYU1TV6eyb63Ii7Io5N3hWrhfTOJA+Uoj8P975Csj4ueWQbZ1pIC/m7i4wiP6lvS8GWEj3+JbVPcmrISMREmx3r/SNJRfV4bN/RdwZrHdYN1ImZQrG8odyJEV/R273j42ct3nps56ibivXJklUtXGyEpqnYrNdoU5PWYYrk+R/91dOuFTFR6dckxzyJjDlDXnwaPkgzwL37a9588xFPn7zg448+C++BAp3HqujM5yjmn1fU2yyzzDJLErOEt38b9pfw5E+hvf2iczTLLLPMMsssP1OqVcfmzVvqdYsyMxg9yyyz/GypqqrYODEBV0ZShDAponWHhf2ALQ9SgMmfi3FNwV8KHGJ63SQdKTajCSMMJn2dGmaTE8HY8Fng21J++oA9ZXhkMJAmxgrnPdY6nA6hjL3vwbcoAW1McDxAsNZyOBzo+67ArQskV5JxWyGZ0eNz6iyX9YhxuSzaqI0orj3yOxuMR0/K9TiwPiTcKLCYOGextqfvLdqEcngZnDWGHPpcbyUjNMD19pYX1y9YLZacn5yF+sjlG8L6DsbkAVNOQFoK/52x/slO15Tvg2vx9BgC7mytw+FQWtM0C0ylqGpNswj2lQHJE5x3LM9O+ebf+reg0qxPFiitsH2wCUgdcSsbGAZ0VQU2DnxhgxFUbdCrGnYxDLRzeAdagkH76sVzftT+Ebe3VyHsj/OIE8Q6/OEQQnGrYHt4pXiol0u+8de/z+3NLR9vb9n1Xa71zKodqzCwJaQNVZ6u69jvDvR9nyowMDH7oWOVjAgJpO36jl17S3voeHn5MoYtGvqiT22RPWTujhB1XVPVJo5Pw/GuPXB7+xKtKpSqMi6ee2tq66Jn4yfjwCTMU/lGjM5kp4V0s0wI8NPAcDcPRRDw15KMb4+McBMM+chNeT90fn8nJ8ZIOndCy+SHj6/O4aWK9L2zWCuZvSc8coIhl+Uonfg8tL3nemfxNoQD11pTN4ZKC8u64nSzoK4qjDE5L4P1SXJdBPYeFX+oYcgSyXkKCZRAe/hYLis2mzXb7Y7rq220DU3494tBqwwB9Nq2mllmmWWWnyE/h6PHAhGVQyNkpom0u15Fo3nWa9PAF7+LH7zY/MR7eaJkZVc80vjpB6fZ8ni2m04cGvKAq7IBM08CR/TU4N0s4zlrdOEwCedBXheZ95AI/cs7JVaGqODo0bU9XW9RxuLtHuwt2nia1QJdhaY4tAeurl+y3+3Axlg2alBVlQiV0RitCU4eBujGeb0jqSGmijevODa9t6i/O59R8Q3ZjI4eDE4e3oN3SN/S94a2bWnbFmXipCkWLeO6FkmBWfSwKIrnPnn2hP/9D/4l3/v6e7zz4BGYwIAxhPgIDieDo4enqqAykGj/tAKjY5iMVDfJAcETQuU4x5W9YSeeN/SSlarpxNL7Njh6nJ+zOlmyOV9zenFBVQfDNoRVg7U2OnscQCznpxVta3n27ADiaFYGL8Eo7iwszs/QxuBur3B9j5IKvGA2C6p7a1QTaMqc6/FWqEyNNg0f/uh9fv8H/4JqYaiXFc764Ohx6HF9B+sNlXIYdZea7RVLtnw2OXrUKjh6Kx+8xq0Nzh6Vczhv2W23XL54yXrR4NngvQ1KelK6kbxrwGfDv2N/2POTT3/KzctrPvzpTxA09+69Hbxm8+IOvCoUKgrdSITNyYbz85PYQwenqNvblzx9csXpySPOzhZx/PFjD9usF0peYOZjAmJj7zjyiqR4sOm5SVyxAChZMIdXSI306+TNmx8hk3bJnmghj9aWY0y5tA19d/A0lmEjSereOTNJGfVIdk5KOzykSPdny93RwNPbjr7TOV6sS8/LA2yxaEmLuGFa4XZnefz8QL+37K9bHj5Y8/D+KYumYrNeoLVG1Q1gsnOGJJqnlB+R4CRmVN69Ejzdwy4WLyl20rAYdGlRAZxu1nzja2/irePxx08RFRlj1BASTIKHSWzD0E4Zh5r19FlmmeWYVAt486/B4QYuP5wdPWaZZZZZZvlLIdWq5+Iblyjj7mzunWWWWWY5JlVlouF9LL5YLEsJaYwvuvu9NKKWlsKUUGHw5RiGXKZ/bCCLxkORCcpRwqGjxApW2GNPGdlBJwbb8MCAKRQ3JJwbCUbPtHlGlAffg+sQ7TGYGIqF4OjR7um7fshMZH1Ij9YqbaJLf+XmlAl4Ma3b0TUyvuZnzQcJz7pzXdpwFJw3QvMNIVTCftKAf9oY/lu0BHAQhxIVmzuxxSaETDHtcTfbLR999ikPzi84Xa2Dg4WWSfNEc2+sNBVDQaeiJ+eQoWsMxu8McUVHjw7PRlVUorES2Fi0UTSLBVVjqBc1zTI4cWQHDQksF4uzE77+73yfru8QHNY6tlsL4jGosHHLWbwHU8c02gPeuYCJAao2qGUV6iuFrHGgVIVSmqsXz/j08WO0UehK4V3AerEO71qo6oypvxJDlrBh9au/81vsdjue/+4P2F1ekjZXacl+FhnXdc6jIs7bdR37/Z6+78ks4CUmz3Dz4Pzjsbbn8uYl7eHA1dUloFgtT0jhPbIpKGd03I8FoW5qFosmttmg07Ttnu3tFU2zYbEwxXtw15aUN//JKKtlt7gDq5Zv0MixqUi4xIWP1Hoed+5gyFNzT/GQxIQxbsuIId85NmR0fK446MlODD/L1nZMhnd2OOa8xbnAnuE8IQT6sednrxoZnem64OjhOkt/sKxWNetVg9GKujacbhZUdYXRZtRA0zkhbAwM72MOK5Ntiv5Oe2Z7KNDUNRfnJ+A9N9c7IDqHqQG9FwoMOeeCO3PVLLPMMsu/rrx+6Jb2gKCoKxPp14JImoiTR2CKLyJkJcnHYz46XxAnhXIztwz/FfeXA+Kgs+bL4jb/EVtAvsNHJTDNaKURkLGzoUiMITfIOG7ZMHElho9k6B2e6GJSObf45DwioMVTKQfOYXvHyxcv+eyjT/Ax8N69zZpFY9ACfdfjbFDm8uQc/8teyqOFiY5X9JNWm66YUt4ShUVBgZC1kMIQ+0qR+ExHXiBEG66zIeyJtZZeKVyvEK1wxuB8j3Vd+LM1Ih6tkhqfajq1f5kvlWu63zv2L3qenVzx5599yMXmhHfuP6LgAgnMMzIEfLEeeg+ds4hT6Mpg6iqcLYqbFhWJo8zveqzvYbNBLddoAY1DsDjvcN5lCsGqqqgboV42bE5XmCo4qbR7S9s6pNb0QNc6lBYWTQVA1WhoHf1uhxUNnQ3MLXWIx2msom4VyhIpyByHvmNRL6gqHWjGBCqtWVY1Xbvj0ycfoLTGVBXLxYLd9oa2WR9dP5c9ZWhejYhGeXJMyZI6USQsNIN3quB6T39wuD45PiiUqhDRxaI33Ou8w0UnkHZ/4PnjF2xvbukPPVpLoTvF/ihpuZdCZwTnp8WixhhNZVLkwUTpGJ522PfgHHXVc3IK4kA0ub3SE0ptOC0K/Og1KECI+H8c1SbqeBoThuIG/bPUBAeXkGGUYPQtLU4k9k0fqE1w4wbK49OQx8ErOoXNGqjtYptFVhAfF8dZaaVQYkc95Mhi3k/PpUvi3SJUdUO9WFBVt3RaZxaM8o0eEB0Gh+x4RW3gdAl6VWHuLTjZNCwXsa0zk1IMtBQbrHcWvMrTgspKOnm+yYFWY924gm0kOTWhFT6GHjJVHViH4pibqDr76CAzlCiFvQkLFl8GdJ3lL61st1t+8pOfsFqtePToEVrrn33TLH/lpVJPOa/+Ea1/yG3/myRK0JHMFrJZZplllln+kso8hc0yyyyvK9bagBwqlZkHoMB2ZYx9TKxuBIwlfZcj40/CjAq8onCoOG78JD2xBCLiDSVqweh7ckQY2EkKnFbK6+9iqRlDHpCrEdYkxb0ZUhICXhopEZzz7HcHbq5vAjjkYVnXGBOZd62LjLpDNpLxcH1+zjf+xu/wzte/hqrM8ACgxHMnRSuOl1hxee+R8k7TGRlsI+NJycDtCYwT3uFcxKxcwIO9UuG4d3hv8S6GhtY+t8XQJglHzkBcNvi73tPvHLv6wIvbKxZ1w+lqXbbQsPmpyL7z4HwIA53CO0wh8/B8n8vpOxvyWNeIqQM2FfH3xFCQMqZ1YB3WxlA3FUqHPFgb2hslOBTO9ogCo4Mjx8EosB7Xd/heZSZwXQX2WuUlbP6L+Khznl4iy7NOG6E8SglGaaztuLm9QpSglKYyhr5tub7ecvlHP2Z5suHNb38LbczQ9Kl/5b4SwlykqCfjdzk6NMnwenoX2sW7BO+lzYElxTIZD/bREcT2PbubHV3b4XoXxpWUlzwelN1YSA8xWkeW+mGAyM0B2N5xOFi0dhkTfqXOU0K/qYvn19pPXo0jieQM/iwMuXgFy3vLB4yHk5wYDQnZAAEAAElEQVSh0qEOZLKBcTIW56yU+HdMJztX+AFTjXm4U7Jp2x8bEqe/BZQymaVI2Ul4LF9WVYmg54ZHK2gMiNGopaGpNZWJG/VGTnbRvhA3JuMn/D8ZO54WrLAVMGxwFySb1dIYkRzwgs0zJOR8aVssKqmcg2b9epZZZvkLkNd29NjvdyjRGLVAUly7Ii6ed2mG1mNFG6LBMhkgo5JfuHdK0vNGSriAUoNHHZC9O9MMpcaPSbfmcCq+UL7LCSExMSUFTaKbhgzj7LCg8MOkIgRPaoiUgkmDDoUIlwRlLWXRueBTrJWnVkk58Vw+fcHjn3yIlrBT/KtvvcFyYVACXduFRVFkQSmnWoEYkqBUrpOjR8cwaYxm8eLarLbG71NP7iOz7igdYfACB7DDcedxfR/CtPSAKKxVgEZpj6PH+pbetli7RMTjjCOaZws1QfK/0LuGPPQ7x/Zpx5Pmkj+99yO+9uhtvnLvjcACQYjjkmkJYx1ZQLyn7S1iFLqqMHUVFgYuKY7JUcDHNne4bYs9dPjaoFYbFBbtO/AtLv6zPiiXVV1RLypO751wer6mjrsXDrueQ+/Qi5pOgqNHZRTLRfCwrpYah6Pb7gKdngZRilorVGWoe0VzEFQfmqC3Fq8ctYBUGmWColonR4/Dlo8/+RHGNNTNhtVyye72mnZ5Ol7EvkK8CFI6enhf9Jp4v4qOHoR3zPdkRw88KNFoUyFK54WMiA815mxYhNqedrvn6U+fctjvsV2P1LpwTiA/dUr/JngWq5rFoqaqApuL99HoH7vqYd/TblvWq47eph0QIUnv3dhZKp4KY5TPXXpYK4w0yyEf6WccC0IaUui+wRFIiouTU5yMypjyUJYzlSWUq49UHdnYXO6CSU/Pr++wKEp5F5V2m2SXNJLGnJg8ju22GfJyd0wvMpC/BA/5hmYVqPE60w4Ul/hXpD9+VG085yvPZl1z7/wErTQmMXPEucPHsiWHjd7aXA9aGMKMhSln5FgYqs9FGtCQRmWCYxXxzzQ1pq5RkdovhG4Jc1vnXBwB86QQP1NdeF7nXZvlyy3b7ZYf/vCHXFxccP/+/dnRY5bXkko+4179P7Cz32Lbf4ejjh6zzDLLLLPMMssss8zyKy593xFYoX2wmgtjDHlkYRyMr0DERwrMU4r1dglbqgFPSYv+En8ZwB4ZPWYQGdbwwHgrvZ9cJsU1cudSH8+NWDpGRYubg/LzCuPfCKsINynIjh7eefbbHTeXLxEEJXC2WWNMCIVtrYuhpKPrQZGHzf17fPfv/nvcv38vGOszNfaAF2W8a4TJpwIM+R0aoLzuCF40xfSOV34sW8QJHSCCdikceMTUsHHHf0T7E5s4qU1iLeYyRAw51oHrPN3Wcmv2PLu65Gx9wulyHTHkmIrIKK2EklsXsX6l8safbEiPjT7Uhsd3DmctXiukqpG4URDvGFwWQp0rrdBa06wamkWFVjEUT+fonUctNNY5rPVoL6GtFWgTQ6V3Pd6n/a/BriBaoa1gekFsLEs0aOtQeZnRXIui0sHR4/rmRTS211SVoesObD99xsf/2w+4eOtNHn7ja5mFfNy+FGCblHurkGRUz80SbTJewIGzMcSKD5ikUgG3TPekNg6hWADvsF3P9uWWvuvx1qGMmlgwjmDIsVubSmOMDo5nJCeP4bq+dxz2HXVtcRELH7ppDJ9TFDw5Enn8EK17WjdD15i+5gPrcjyfMfc8LA43eHcEQy7yMH1siY8HvNeP/KuAuHntbh7zO60KeLPcpZ3yFp8q0/unvz8XQw4paGMwlUFrhRvZu3y5R3B8fxrHPGjlWVSeutIsF03Y+JsoeEqcNtUZwQEqPSVcOjiFFF16VCDvXe43OuPTCpSgjA6OHinsV05PsqPHMN6XE4MwbMaeZZZZZvnF5PUZPaxCK4VXBpSJg1QYmML4PRgNZaQghtiDkWF/CJOSBtCpbl/oj3koLGmN4szp0z0pA/nTD0prsXM/eTMPlwwKB8fSSoek3IWfPPdkVPYwucTQFKKG8dr76FAcvHJb6+j3e3pa2r5HK4URwYjCe2j76K3sgnIosf5csZIZ2XHvtJIZKi9L+btcEY3v9r5sgGLevnPt3bSEYPQ0RrNa17SdYnv1EqU8vm0xRlM3Dbbv+LP3/4xnL57zrW9+h9PTc7QOZdTaxPAUabd8kdfCg3yxqrj36ARrO370r37Coquw33CRVs8h0VNZp1AlPtHEhfZQPs7DmXcvq1NDN4oLKaU0RsN2/5Knl3sqE+L4HboDzy5fIEY4Oz/FRPaMplmwWZ2wqJeBcsyBdZq+F/qbFmctm3WFqRTOSjRqG2ii3tV72kOP7y3m0CECT55+zG5/y9XLK9q9pe9BNIi/xR08rrMsmiWL5TnL9X2c2+PdTYjn2bU4Z1G1QSp9XOGcSFgjKJTSeFG4iVYVWFug7z2uikbySrFcVlS1yq+rjxcPvS0ycviw0Oh7i7XB4UIphWoaqqqG+C64SEcYFl2q1HFBhEXTsF4t0Epn56/BcQuMMRilqKo6KvIxXFQCAPIY5QdXp6wsHlGwfFrPD+/TlEBo1F/99G3Lg0K+J/fyqISHuh+04TI+6dixqxgPp8pg2Vy+WODnMXVoxzy+Fk4vg7PH8Jyxe8ak0EknLS5xzuJ6G9lIxuNNKksaW1Od51dRgqf9ctFQV2aiYQ+LixB5JToYYqPzTnSCU8FTX4vC+hBz1EbvncQ4FBYMgqnCuL1YVNS1YbFa0qyWnG6W4dEKVCWoyqDrKu7iiGGiRBeTy9BvVDEHzDLLLH+1ZBiq54X6LH+5ZLlccv/+/awPrFar4DA5yyxRnHM8ffqU7XbLdrv9orMzyyyzzDLLl1ysD5vevChEqQEDiFIiraVhLx4KvzzFjmwZYJzimtKK6kc3wxhIKmQKk6b1/Ctx0HjhFG7N9/tYjul9pTVXBj+BEqQusB7f93z2w5+wv93yzd/6a1RvPML5HichLG5w8pAcUt2m8LMuGCFjKuN9J0V2ZFofKQz6yMhLgamXeNIUQy7LPzntjzSUH9KTeI1SiqrWWCd0h0PAw2ob8Byt8c7y7Pkztrsd9y7u0zQLnDPRthA3LGWwrsSQh/o3tWK5bvDO8eLpJcYp/MWDACrFMirxwYEkttfA9DuEmBkb2n1RzOGGFEK46w9s9z1KFForrOvZ7XeIWrKgiRuTNKYyNFWN0VV+pvOCc4JrLd556jps7otkv2gdWC+sJ4b3CbiYsg6RjtvdNZ3tOBz22N4FLLwHfIe34K3H6ApTLTDVCk8P/oDH460NTg1aZSeq11nVCkMo6On13hMYPBKGJx6lQ0h6VdD/lpDqULkJW/U457Kzj4ggxsTNOPEan4JGF3zFqR0jRpzCSQ0kCkOnVUphTIVWenD8SbaojBWnXlX0sWNjQnm8xJCHChuNGyWOeze5YlwqsfZchilG7Qc71eTenynFcJXDSN05Fxosj9kj57oC/83lnmLWd8dRH+1g+SUoXuWMh0/GoBIiV0pRGYOOfXZ1ccGjb34d0RpRms29i2Bziun7wrFCIvArEuarEEZ+cJRJjEMJQ05jvDEarVVwUKkqmroKNRMdloJzmB7PbeV4m6qS1A9nEHmWWWb5xeXncPTQaAyoCqXrPJD7Yhd41mnTjOCJhkufSdqk1JCKiW8ciiQNqGTjrMDgrZ298oqRfzp3pF3WMB4vi13/4+fFibF4xGTmGdhEJIUFkWJ60CEbMY/axWujFbmzjkNvudzfsO1D+I1KKSqlMUrhvbDvHKbvcKqn7yxKJBgqvU0VFedLyZ7wRYmBanIs0kCMKPLStccmkuF4XlDdOZ+kCNtCUGZrozk7bWj3mo8+eI53Pd3pGmMMi+WC7Y3hd3/wz9mcnnBxds5yEajsvPbQqEhxlazGfvTU9Gt9suDNr97jgx9/yB/+8z9m5RZ0f9sS/BgsSiy19lQ6dIoQxy/GF4wxAZN3Z6mX+eL/yNGHVgZTaa5un/D86po377/Lg/M32R32fPLkU5bLGiNvYLShXixYrtacnV6wWq5x1mMt9K6ibfd0ux2VhvPzEHLE9eG5TRU8t5UOzhPbbUfXWozZ423LBx++jzaG25d72p3Fi8OLo99aDtWWZn3Cen3C+uQR67Ov0h6esN/ucc7R9Tuc61FNFSkaX0dxCHR9wdFD40ThsWStzoPtPX0Hrgl9s641JycNVaNDzMhEW0hYbIaFUVCSg4LuafuevrcIgtaGqtboqgpe9R5sHykP44IhqcXJ+L5aLTk9WeOCc3xwOPaD+1VV1ywbQ9M0aFEIIfZkcmoQjg0FcVxRDN7NPrxv6dWHxOQwKNEhU0nrDfc5GdJPim8YOsK1gzNMsYjExyHO43x0ihmSIIWFGlqx6LNlOUbNLMM1caGaChM+UjiUsbNHKmlWzWMC41F68LYnO2eFtuv7sCgNzw7zRElW9yq8BUIs3816EXYs5BKHEddHJ4uwqg0LUbDg+uCAqDXKGLQKnvrWh50tzjnwjr7vsLaHGOJJVwptNOv1gsWy4f79c+5dnHGyOQlP1YKqFboxmMUCXRnEp7BaemicokZE6aLxZ5lllllmmeXLL6enp3z729+e2YtmeaVYa/nwww95+vTpF52VWWaZZZZZ/hKIdQoftukjogcMubhmBLuOjF8ln4eMr7kDZY7Pe7jrc52NksWJoxkpMeTC6jl9rvdFmjmXY/FFfgrcPBhrM8KV0xHvsZ3lx7/7+7z44GMuHj3i5OED9s7SuRDGWStBEQ3/XuitRxFYf52N4Uy8x4sbGabLzYrjQuvhK5CdH6aNcgcbHlXcpEpeAfYUjLNEQ7FWQtNobK+4ernFe4ft62B0rwy6VTz+5DF1U7NsFlRGB3RS6cBgkXd7jRu8xJDr2rA5W/Ly8oonj59QeYN918eSB3aQwq8hYJouIlk+4VdjBtzxEyUfUBKYPw7tLbtDy2Z5SlVv6Pqem9tbjNEo2QQHkMpgqpqmWVJVFSkUtfMaa3tc16MULBZhI5P3gCU4IlQhTLFz0N22AfNWPTjh5cvnKKVoDz2286TwJ647YHWHrmrquqau19SLM6yNDBneYV2Hdw4xOjh7vJYEo7ZE+1DA/sbtkTZCJsZnrYW6CYbyxHQS6jWF5SH5eJDYt2109BDiZkEt2ZDuPNEJZOivUo4jApUxNE0d2UGGLpneRK01VV2HECKFXSR053QVo8/0rJDW3bFlYs8vDkwwZB8Ygsokch8uHDby5aS3dMhRCiU+euYdDDnVcrjgKGyZ3oNYP5PChvQSu34xqCW0d2zJuSt+9HbGYy6F1i4fMx7oPw9DVkpR1yYHDjh78xG//h/93cBCEx13lOiIvzsEFQ0JanDKkMQkEtleIlifNmOnMSuEOBKq2mCMYbVasFwuaOo65lMQLYhRKGPCe+RLW1xZcX74OUPIs8wyy1+AvLajhxGPFjf2pk4iFI4HhVIo6VcyIBYJ5gkjTui+dPaYMHbAaD6EQUcsz6WbhjkzTX3D7FSQQxTZlc8ZWAtDaTHjlfHoRpO2L54zlC4oVt5x/fKG5zc79rsDEhkH6qpCaYVzPU5c8FS1PtDvZaN5TC/FmLm7upnkOX0m54lRTl/j3umqZ3r9sNLJBmgBowVtwm/n4HDo6K1D6RBfcX+7QxB++MEHXLcd33j7Xc5PTjGVxnsVnQQCi4krTMPZ9CxCrQLFXK0rTIp/RlzwiAqTqkp5VmgtBB01lEkpibR4Q1lyKycvYJHgnSlw2AuHXQi74p2jPey5vb1mf9hibQvi0Sbs9nfecWhbrq6v2d7e4N0BZzu6fY830C4VTgDXxSeHtnGR1SF4dvtAEdg5OHTo3tF3fVDeTVo8GFRVUTWKZiFs1pr7ZzUvXggvdwfWqzUX9++z3JyyPWzZd/s7yvarJC3OUp68EjAqezUP6mNgU9A60OCpTLOXnIAGLS31ER+V+xx3MgZxdD444gQlisIbe0hGibBcLzCVoa4iUJD57mT0jiamEIm7HTyRLVQGtTK/8tEBpFy0D5R5Y20yOF/cXUSWkvKRc5QXB8NIksegyPoz1Hs6XR4caAUlx7lyo2szDFIkMlWwRy4hsR4C05yMfOiOSdp5kiKgZo3fD3WZbnbO46wjUmyMBsPUXGnRNs6l3Mnp8GvSd3N+Jf9BWlSCtT297XCxtbQJzj5VXaOUplk0wQFttaBuKqq6oqo0vYPPnr1EVMXJyUlcRIa+5uMOGlM1KBziutg2aQ5LGfavrshZZpnlV1o6d87Ovkfr3sbfcb6dZZYvj6zXa95++2222y2Xl5cAxXw6yyzHxR9FhGeZZZZZZpnlrijxqAFBGECFZBg9ij0yAgzkqGNGgTn/LJleOmEjLYEhgRgitgSN00mZZFPu3D98TsFlGTDk8d0hiYQhp2J7n9lRPZ5237Jre/q+DzilCgbywExgo2NC/BthWUUxjk3fY4vwpGyjk3d+vlJGQFt5w7g+RrvxJRmOA17Y9xalfcB0vadvOwR4fvWSg7NcbE5ZNAu8z0GMC9S/wCCjU0kIUxKcSrSozIaSmGVT8YfNniE/aRNW6hvTzakC2XEhP1UplAfbCbb3uDqct7an7Q70fYdzYSOdkmCADpsTLYdDS9e24Hu8s9je4RXYSoKh2bn8bKDACCX3G+sAazMm550fGAYis442AbOva8VqodntYN/11FXNcrmkahq6vqNaL3n7N77L5vw8hzR+dV+IrZDsNIrI2C0jZ4qEIwccUhWwWdFJEw6rQhulU9lRJOKZ3g8syAlbnZqlBMHUOobJCRjtsEdtjCGXmwIHJ5OE55Z5G9IfsM6EyhZGouJaP7ppwIinMj10B0OOz8o+IuXx6V2pquSYJaDAkIv8Tq/zeewbxsO0CXHk5/a58nnjfHxuasdcp8W4U/Q3X+QjodMCbB5cUP/Wr7N7ccnV40/z9Zn1p3h377q9RBzbhxBRQ+ggiXaF8J5qY1ASHdBMYBxSOjgZ3W73CIq6boZ70/vpBaUN4l3uSwN2LIwbc5ZZZpnlF5PXdvRotA0TowCiBv01DYulpjbRJO+MWVnZ9MMtpEF7mC0mDnyMLgYCG78PCkB+jqCSku7BE7f7i88DdZjAJBsegVEsuSH3efYe6epl6bK7QJ7gQ4gAUTrOh2FHefi0fPbpUz58/Jyb6y1KaerFgvVyhakM1nWId1hCaIvO2lAPOuY1McuJYmAsmU6a5TFNUqTu1N3nyjT+mxQlna4ShKGOFHUt1CY0nvWe290uUj97KmPAeQ7bPf/H7/8Bqw8+ZPm3K9aNoaorMAaPiywSwQVCjZ4DRoSl1qxMxbJpqKsqT+5aQnghZRRiFF40iMJoovNJUFSMURijovJWlMW5QTEUhak0DYqr55rbl0J7GhTw7e0tz58/4fbROX23BRxVs0S0obc9292WJ08+48XlM5zdYbsd+5sWZYRqpahQYIPR2DvABYXcuhDnDa1C+/eevncopeja4PxTm0D9Z+oavWxoVhXrNdy/qPjKG0v6nfDj6y3npw/56jd/nfXpgsvtJSer09cCZ4NeFRaNNnpNe6PxVaA8k/wPwOIJdVs3Bq2TAuhAgoIUnGQFovcsPoR+6brg7BEW7g5nw3OdDfEQvbNh0ZYXTcEJ5t69U5brBQtT5XfWkxwh4iJPoke5Gpw9PIIjhO7xPjl7xH7rYz/I8Z3cMEZAJm5IXv3J0UNJsSsirS2K+rmzYyINJyl+YzH+qJzOUN60KPUerLN5qJN0c0oTyQqxSFDEvQzFGWMjPqethOAEpVVWgMuxbtxbcmXfPc5wzBNibdo+ekdrw8DmMrxvIRanH6VRLnyCO43KQEX8FepUBFQI8RSyHcd1CeOUQ2j7A223D42nBK2bsEtZabz33Lt3xnq95PzijNV6FXcHOH78wSd88NGnGFPz5sP7IIIyFYjg+gAwLJo14i2u34F3ON/HhUnor65s2FlmmeWvlLTuLZ4c/m84lpQazCyzfNnk3r17XFxc8PHHH/Py5csvOjuzzDLLLLPMMsuvmBhxEQsiYBREbIi46s9L5gRcpIOlBbEw+OVPGYDbCeRy3F+1OFjaCaFgbS3Td8U1cUOiS/hQxI2mRk6Z4iTjDE4R1DKzknZ7J8N32nBFMH7e3m55ebOjPXRIZIKoTJU303kXWHVdxO8SjgQFLJHB9QIvHsVRT5LYoCd4xrRej8Adkg2WUzC/sOiOPgNypjUBB4112PU9YsN1TsUwJV3Px599RnV1RfWuDmE/jAoFlMgiS2lqH56lAKOESjQmsr/GLokisFOLCgCZj/lWMvRVYqgRlfNYFn4ImYOEtAzCwQntQbBN2AjVtR273ZZuvcDFDUPKmICBOkfXdWy3t+z2W7zr8a6nby2iBF0Jygj4LmDIPvWRtJlN0BJC7Pm4aVQiw4v3Hk0M92M0Uml0palrWC0Up+sK1wmXbceyWXN28ZCqMey7Pafnp3zrP/5rGK2j/eF4X8gYMuQ+65VENp9JX0gOEUrCZixVWGASm4yP3bBYS4fQLz4zbBBtLN5J+Ey2n0ydHJNUsFw2gX1BaYJzT2I8TswNkJ088rsz2A9yWsV4VJiH4hc/wkqzucalMSZZq2IBigR8wmBJGPKRl6uwW43f2vJ6P5zwQg5SPs5ocXfIS44mMn1l03WF3S69N4kVOufi6Lh7RGLb5eclHN3HjaBIqLzyXBp5p/NFzqhw/6tf4cG/9Q0+/oN/xR998hmJI2bYUC5xaIu2rmKzYBp3rLWZ/RkFWmtECUaFd265bKjrisVyUTDweF68vObq+halNJv1KqStQphv7yxIhdFVGKFcF/qduNyXhz44Y8izzDLLLy6v7eghqgrU+HEkyjT/+b+kBxfeadl4yqBPHp1kpg97xXGf/4vjuZ+sA2R8qZT5O7ZASPl6Da21PFXqxVPPznSZj8pmVh4E0Niup9sfcH0IaaGVCkpqnAQ84JDBaB3TTgO/UkJTG6oQq6SQclaefiZl/VjZosJxp87LVdMRRT8fG86JgNYGpQO7QzKw46HrQigHo0OIm/bmGgX89MPH2B6+8TXD/apB6VAD2Yu9LFZRVpHoQRkXQ6nttdasNg2LVU1w7oG6qTA6xQuMXpnJqF30x1ASibRhFqWjMkiM0xb/NusNbz96m6ZecnVzg/Oe87PTyBRi8N6zO2w5tIfgKFF4GYt1cdESHBCM8TgBfbDDYo50vc9Nl+I+VkZoGmG5rFks1xgdnEWU0phFw2K95ORszcX9c9584w1ULTjrcO51NS8GDS/lwQEuebMmr2ufr1NKY0yFEhUcefY7rq5est/fDLWa9EAE5wMrStu1YdklCucd4gfuBpc8dQc35KxsmRiHsVxDOigcWaKrRXRIS++OlN0569Y+buooHBzyDg4p9NrYx4vXIPS7QplOzgtFbMrpBpTQpcsxUnKVp/yUx5OH/51XfdxgDJpw9FIvXdD9JBMpieL7aN1/5FF33v5JkqPbUvzC0LoTSc44xxMuYx7GA0V+w5hgraeLtKRahvrMjuYIog2qqiNzh2Zzsg7OdDa8Z6aucEq43m7ZtQeWTUNTVRgl1JUJcU9THVoX2pbYT5QKYaBQY3aXtJsjb2OYZZZZ/upJ0PUyDfIss3xJJTlJrlYr3njjDc7OziY7FWeZZZZZBukPmptP11TLjsX5HvUrOs198MEJv/u7b/D48eaLzsoss/zll7jx6lUo5fBlCqYW39Xd0/maArb5XEk7xfM9w03Hb5W7QM7o3Pjn8Iwj5xImI+PL7yQc85WNfgnsQgLjc9/jbd6qhI64XNoY5adxHxh+CoLRKjhTpLQT5jL67gugpsjpFBqOO67usBKMHu/Hv7MtYIJLC3lzVmYPj6esDfiPkoCT27ZFPLx8eY1zhHDgS41HkZhfSkxwbDgNwGF26ijyLSkMQ8TYA66tUYllxEuBF5am+AGHSjiQCBlrDm0ZOkBd1ZysT9Cq4nBo8cBy0URsOoRl6fqO25dXfPwnf4YXxerBI0xtgv3FyVAG5SNUPGwS89l5gdyXEpaqtMIYwRiNqaoY9gdEFMrowJjcVCxWCzbrTdijF98RpVXcuPkKSXhj6q/5t0QYVwqMb2iL8zcf8c5vfJfTB/fBg+17Doc9fd8OXUxREAl7bN9HQ3yq34Sdp8eO7RMJ31QSmL+nAG3pgFHmbdptczknr0R5fsCQKTDk+NNnVwWQyPxcPqR47/yk25avzOtCjAlDPjpuTp+ZGIwSFvzKe8YVkKHjnwdDLg7exZBDfx0lVzzEM2mZUQPE0Ctas7p3zlvf+zYXb78VHLMACA5Bzgt4FcO7lO/ukIZojdEGpYW6riPzvsPjUVrjBQ5dR9f3VMZgtMqM8aPxy/lxN4zYskz612jAnyHkWWaZ5S9AXtvRA70KHsaU1P1HRnVgNLlCmDhUcWlStGE4GCdZKbVFV/rKymhmyMcVcbIcbpsQhQyTZnSeuDOryHBd8gTOXtwj5dvnognR0SIyeEy12GDz9XFSELxonDK0+479zW2It0dw8mgag1aCtxYvKvyR8sxALyiBjaJeLVguaoZ4hKlyx+FIBkaP6d80v9Pfx1Qbd+S8B6LHIx4RhalqqjqERbC2x/bBcWK3PcSJVqg6i37yFHd1xf9hNb9/9hH/xXLDxdk5XrlQ/hgHzauSni5O7z7E+NSmQmtTZFNRNRUXb5xwerJCJOz436yXaBXr1QdnBa2HcBVBQU+qg8I6h+17lFliTBXZLQIzCx7eePAmtV6x6294/NkTrHV85Z136NqWw26Hs54XN5dc767p+2CYhkCvplobvKl98MCvTY9zjt1ti7MWfB/6n3Oxn+VXA8GzbODkRLE5XbM8uYd3e5zdI6ai2mw4vX/BO+++wTe+8S6//r3vcr3d8sFnn9D35rUUB58q00vIg7PgDDhQooMjjwgq9TtvMBqaSqFVYO24vnrBRx/+iMsXL/DeZqUsGMkFa3tubi/Z7Q94pfHiAluC9DkfzgY6w6Ds+dCVDRijqbUJWUv1o2I2mYwXkQMi0M15RAXatPR6J5KRFCJIj7TFMGaFIcCN3gSJCpqUCjme7FKvJWuMOT958ZF78VDnxXo7j11pUUnxrNDFhzz6aQeRfEd07SczhIzaXvJv8ZKdssbe9nc7y/Romd9hVA41KrjA1phqMyUPYacEabdE+YDy+UP5hyd7vLX0FrYtGOU5WbnBMSR77wuqXmCWPfcfnrFcNjy4f8GiaUKwIef57PKS692Wp0+fsL295etvvc1b9x+wNIbT9YKmrvJi0XcWbHBaCfEbU3xhHQJj+dRvYx5dOVbOMssss8wyy5dXLi4uspPH7OgxyyyzvEra65onf/SAxcWeN3/7U5T+1dR3/9k/e4vf/d03sfZVONcss8zy2qIqEmBR4rWvlomxS4pPP/kuR66JSYzOH4M/pw4Z6fQA7+QEJsj23byl60pa1HJDYvEcyUwgxfmc1yHccDZgI3hR2N7RH7oQStbHENMmGCwDVpVC2A7Akh8eitKCrgzGmMgAW2Su1P3KMpVW0AI3HV042njpudPI0x3qubwuPyOFytXaxDDWKoeg6bs+66baOdTtFm8OfOQV5vKa75iaxWJBYPRIG25cCL+T8pTLE501VDT6ZwkbCJebmqYOu+5FoK4D7pkwq7RZsKyuACEHDNlF7F+MGUL/MoTP2Kw3aFXRu5ab7S3ee05PTgOLQN/hvWff7nn68Uf83n//D1mcn/Eb/9nfo6oM0vuIp6YQEoHFpaeP2FOcj/PmpPTGhd+VJjBvLyqqeoX3gTEErVB1TbNacnq24eL8lIcPH3DoOq5ub3BOvaLzj9vUlxhe3rCXukR0roGIaQac9iu/+Ru88Z3vUNch1OnhsOPq6pL9fgcEm0DuXCpuFuz2dH20meBjOVzuV94Vz8bHONWE/q9UIm6G2MbD77KDhj+fwXgZulKCWElIbzGuRRzyzruSX6EirEs6ntosd9O7GHL+8DCEsRo7CwzvOgO4PLoq5UsGAHfku+MHLHU6bpYZzkVKTP/Twff1ZOSwEu1coU38gB2Xpyn+G6hP4ud4LL/37jvcf/edwNoTmeXDRl5PZ0Nk8abyd8vpCZsFjWO5XlBVhtVygdEmVI333Oz2tH3H9vaWrms535xwslpTKUVTG4yJFgXvU5yhmG0hODwGnmoRN3EM8rHvzjLLLLP84vLajh7BMC7R9uqzkhrm8YLuKd9RauPFxJFP3VWu8wQ6sSgmVgiZzjajMX4yUvv0iOmENUm89OiMilo2jpanJ7clBSJ5gY6fPlmgQKQTcyxqw8mqYS+Otg1UhjnsnA/TuiNc63GkIBCB3ilkTymFzq6H5dKjzEVZuZpIyzDO1KBdFPdN752mN10pFQsKEdB1WNAlxozJAsj2FiWK1eqE9XrNcn3CYrGEvme3vUFWJ+h62CIko2fFJ0eFewCkPcno3fUdL1++QHC0XYt1PcaoSM8XPcKVRrQZlAI/PAmCgm6dQ+OjzV7iRBxC5iQF31lPu7coZTg9O2V7e8tht6fvLbc3W3bbQ2RwiIsCoLdA76mtCx7KlUYrRdPUiNigfPQuUHsJdAeHtVFJEIKhWSssjq5vkRC/CGcdtm3pu5bOdtxsr/jssw9xotksl6yaBYlloiztcRkUraAYObwNLA1KYh9NzD1eEBSqYD6x1tN3HmuTEieIDqGMlAue14dDS9t2IXZkrG9xiQkitSnxt7BaLmkWNSaGAgkMOJ5D28YYnlWgR0sp5P7hi/coFV6y0j7yGi4V6XRdqq3Cw3iIFVX0zsEVmIGXJC4RUjqFrp+/FQpq8kCXoi+SdmYUK8oCCxi3mfdhQVTuWIlatC/GtFCCSEeZPezvBJq5s+jx5dG8YEmUgNP6legUMTEcpaqf1sMxibsieuuwNrC8OBvCHB36wG6zWY5vUWpwXJH4XjWLmu1hz75tqUwIP7S7uWV7c4vtPFpVVFVDs1hg6hplqrgoiHnAD23qfQRYwjjsklNHcuqbmTxmmeWXLrbVbJ8uMcuexekB+ZxNR7PMMstYRCSENptllllm+VyRQJHuZLpI+BUSwVrB2p995SyzzPKzRRWYnfcpDGuBEZUgDOHYKDYB41OvBrMiQuLHX5Ot9jjGWSZUYMJHk59iyOWTCwD7CJZ9pyzpGhlwlQFDPnazx2hFXZuIsflRUTN5QsSSyuAlI3RexhvdhoyWhUn4qIdsaC/SGWhoGZgAjjTWq6q72PCZIVgRUJrpAi5AdbH1XAjlW1U1VR3+jDHgHH3XIlUdGFnTvZOyg4+hjcehl5NYZ9nv94CPDLAu4EpxI5UnMpordazLhPQjdqUI/gUB34u5iVhbYmCxfdgk2SwaurbFdj3Oedq2Q0zFva+8Q7VeZf3c+fCfdiUmLGgTMFjtCYyzMeSF631kSC7s4yqUxDo7IHsubKRyzuKco+0O3N5e4UWojQmh19PVY0jybnunHpnCGBcst6XlIvyOTNiVQrTKlzrrk3081pcKmLkN9db3FmttweThM/4moyeEd6AyBm10duxJDMDWWpzziBo22A7GpWluKc5PEdJjUtoYfDEGFf3u2Ks3TW/Sz47WfRpLfWKvTuPntEyvynQ5oKaM5gF6aoVh2PQd/jv6ih85Nnq2T/aVyTifnIVSRPERvnysrieVF0WJoCIDuI2hfsImYui9R3vwprg74dNxU3JgXddoo+lsT28tOmLDfdfSHYINQ9AobdAmMNoPodCHLOVsle9Cti2lUyXb9yyzzDLLLy6v7eixqIKC4gnOaWUoNYgDZd6FXsbFS0qhB5tH0ZjqK0a0wdIaPlzxU8bnRh612Y/BRcPt2Kv5zvQgQ94So0PwZRkbRUfrj5zcYOArT/us5ITzyU5rncXZjntnS7S9z5MXL7i6AVUpLGA9OC9YHAqHS44ZURmNuh0KodKBIkroCYwahsEl89gsnpT0nrFTh47X9ICd3JfudQz78j2TKSueC+e9aKhX4U9pUJKp1iROZoe2wyG88eZXeePRm1ycnbJcLFDdnqefPuaNNzVNvaDw3x2JV4LXCjLdngdv8T5MrLe3N/zp+/+Kh/cfcPP936HvPMuFwShFYF8RTB1YR1AyaemQ2d72tG3HYhWMyUo0HoMoHeJg4rC247Dvub22VNWKd7/2FZ5+9pTL55fs9y2ffPyU589e4i0or6i1wktkIvCe6tABGrVZobXixNfY3qGqLdZaTi4WmErzwfsvuH2+D1SLWiHGIFXFoT9wuLlk0Ria2mDbA+3LF+yuLrm6eckHH/45+90t77zzdb7/O3+bB6cXr7VTM7RydDISj5JAkdd5EO/REhyROu+wVnB9oIw0JowPvYeuFw57oe+C4iJK0HUF1gdmFGe5urqlazv6vqfvLV3bkegmw7rXZ31IKcWbjx6xWa8QCUwfqX9cXl5zfbvl/OKc1Xo9cmXKoIIL7S7iSdSIaXEsIhgZ3mVfjj3Je58Yrsb2o3EkMwOq4nD2D/ADC0d6nTyodGFylCt7uQz34ojMIeEhEsPQlFpgGTtSXB9aTsBL2FFQgiTBcWwoX1BEFUoLxoT3Q3mP8p4h5NKwmLk7Ug9jfBrzUn2E9yT8aaOKfjeMxYk7aSSlgh4XbtZ6ur5nd4C+g/0u1ojyrBaei9NUrrC40VpjTFC0tVKcnK5Zrhr+7CcfcH2z5eHJimVlePLTJ1y+uOH0wT02pxecnN3j5N59lvsOc3NA6Qp8WCD3Li6Uo5NH3/UhxqvRYD3SBwYn29vY3+9U1iyzzPJvUA7XNZ/+wSOWF3ve/K1P0fWv5i7jWWaZZZZZZplllllm+csipvAjzZv5p3BiZkg9Yszz5YmjFvaUyB289s4zjj6gvC4BJ1OUYoohp8vv5iMbxO+knX4W2PgxiSFwk7iIPywbg9osud0Jh65FlMTQxcH86n0K3ZEAmaKqY36UqMiwXG4ALDHkwtBbbGIaXZ9Af4nHxd1tHw9j9u+Yp1H9S/7zCOgq/MUQyCIjlIy+t2gD680Zm/WGxaKhMgaxPduba9abU7SujvcfIWy8ypu90gkXMTlH17U8e/6U9WpF++ZbOOupjIohWEL+lQ6sI3nzXK6i8BDnHdZaTOWjP0gAB9OmKk8ID973jvbgUKqKmwW37ONmwZvrLdXJCb/5n/3HYUNRzHdnQ0vp3oY068A63TQaV3lEB7aXemlQWnH1bEe76wdnFaVAK3pn6ds9xiiMVnhrsYc93WHPvt3jr17Q9x0nJ+e8+da7rJrla5E2lDYUib+dGxjS03mHx7mBJSWEhJHIukvAl1NXk7DBUfkBGzwcOpwNTinOOpy12dEBBvgz4byb9ToyhkRMNeZ3v285dB2LxQJjzF3bDxSOadFOFB0Bko0+Q35TeopcX9Etwh/BJVK/vGNj8neiDZV5yg+fjnFSvHapzik3HE4x5HS/G5LJjknDtYPzWCyzkPuzUipvZs2s0mmcfZWdb3hpcgEypk7aJKgQ5ZBpf/PpFT6CIauUenBzcwWDh7MBR07R6SsDi2YywsexMW1SbJoaU2meXb6kbTtWTUWlFLeXW/b7lma1pG4WNIslzXLJvreotkdieKBhY2wa+8KmQCVhYyJeggnOg0ssND/bVDPLLLPM8lry2o4ezhfer9PJ3hcTS3k8//i8gT6l4UeHfdZOx/fmBUIyQPojnuA+zxUhuWwQzZHRBiWEcvLyuOlEHHfC5zmy1JjLksjk+qRmewblw3uauma9XuDknNU6TBB13VAvmkg75vFqMtiXaXuCR7OdeLCO6vzYKqc8Nl3lyOTv55HiHhFQJnpkx+OiQh0X3UBrw8MHD/nKO1/hZL2irmtOT1YslnVgsiCyEvhpXkIfVDKO4Vga55u65s2Hj7g4v6CuGvA9VaVyDEsAowSj1Kh2UjGEyI5hLR4flPu4OEiPsdZxaDuqquLexTm7w47r3U1gvVGx7aMrslGaXql4vwcXHKXCpA77Q4/WCsUQY9M5R997EJfJHBI7QlCoAiWY831mGum6HTe3Lzi0t+CDZ/t2e8N2e8tuf6BddD+zFe8eCyFyQqy6IrxHfnMK5puCQSMcUHnR6Rw4FxQun5gxykWsEEMWCb7QdpNzv9ZgIj2lc8mDGzxhUXbY73D2dGClSE5bw4g1KuN0LV/2s6TkktMpTqQgkaNXv7g2Pn8U6zF6Kk+I+vJgWY5HE513/OX/z96ffcuSZOl92G+bmXtEnOlOmVmZlTVXdXf1TDQaBEVQ3aBAECQXlxYX+cJHvelv4vAgLT1wiZQWqQdQEkiAwgLQxNAACKCn6u6aK/PmdMczRIS7m209bDNz8zjnZmU1qit7iF118p4T4YO5ubn5tm9/+9t5Q83HLE5jTPkuxBHVxJSEiDDlUkOamPtU1OoIBg9dV+sImgJGaZfc3VccfF8Ibos5lnlltxgrh6bNfw++UZOtmyYlaWScFMWRCKSaQWjXZU7x3P82LmTuo5S4ub4hxZE0JZwI677ndNWzXq/oVyP9qqfrOqutKCzHTDMNS742a19ERaoaTcplpnJn53Yd7U+KffnL8MYb898/+AG8884P36/rOk5PTzk/P/9EJLmjfYqmgkYhRVlM20c72tGOdrSjHe1oR/uTa10X+exnr1itfjQZFVX46KMNz55tfvjGR/vUTFsFiDYZouK8UnGUjz8QDawgB1+0378Cxai4z+G5Pmbh0Kiy1vhlPcayUdooVdwZNf640+W+0PprUSugAMkE70ldID29Yf/8BZMPeB/wrz1itV437bnjBAr7mx0vHr+P7Pekn/tpVMPt5okuPykAfwFL71TuOMD6b+FZB5j2DB4yR6cNz7RsmRlTmsvclF0cpyenXFxc0Hcd3ntWq44QPC5ju1VBo7a/HC7/b0H2qEfGO8/Z6Smb9TqXo064omiOHdjJrNJcPivXJFDLQxQk8hBDtiSmhHeOzWbNNE3sp4EiBCA5IOzE0a9XTFNkmnI0WKXyBVRhmkwZvJbQyFhYSnbPSrdKDr4bTpqD0BLrPY1pZBi2xGnIOFZkHAbGcWCaJqJ/xbzcQJTLvsydXs6Z23i4zQJDLhdVjqhSVQ5UpeLqcJAoJlCUnNvPpODnolXttx4PgDSXy0mrGeepgablQzs/FmW+WvZBjUcsJ4n2izswZOZnR6xM9xIPzvf8sDWHj9vB37eBbiqGHMeJyw8+JI5jVXshWcwjaUksnmNYc4YgnD96wOn9e+CcqVdIUa1pG3b3ZR42f9G6Qwy5jhW5+0Dt8eucK3Xqs6GSiBknVhy1REret5ZIKYl8ueFtzM6UxyOaDMUP3tPnhELv84/zTSknuXUf2u6x8yZLWqbg1nNshDLfHyHHox3taD8G+8REj3EypbK+t5flYiJufKmlSTNp64GDftu0qEeIz9s3M6QevjWaMLN+TF1pIddmc1YaIs2FFezQs4OWsOBoLkZhTUhNG6RMxkBM+aWQZcC0Uk9BqE5eipBw5qAk5eLilNPNmq+cnrBer1DvURd48tELU4Dw5hCipt5RVkTlxZ+mxLCbGIeJlCZjBta3rDY/bQekOz6b+9H+9s137baH6itysF9R9DAlAOnWSLcGPFUJoQlqi3hO1qf8xV/5FX7hF34RJybT55z1n3Mdgida7+V7PLffiSP4YCU88jhsOemvP3zE3/i1f5f1asPDe69xdXPNyamxu10WAtkEx5BrWtbae4AXwTsYx4Htdsu9ZMxtvLOXcn5/3+wGnj6/4nOf+wxf/vLb/ODxu/zuN3+frlf6HkgJYSRIYtN1aExs3WilHabMTk1CGpWPnlwhIjy4d4J3jmEYGfYjkxrzehoT3omVnwmO4HuCrIk6AWMOuCdeXr3PkJ6b2oBE4rjlxYvIan3G9x+/h0sd+vmPc7vm8VCC1056vFsTeiV0xqgm3y8p6j6kTOqXupgotTWFTJqZlHEQkkp2HhNe8o8TknfQBdR7Yorm0DurPxlWQrc25m3wMKZEUiN7RE3cXF9y+fwZDx88mMk79ZaKPZ/ijbCSlWeSgqjWbVuNG8HIJUAuV8M813mf94n56HaWUhZyJsIUBznr/qR5jFkGQBnXheXN/IDXJ2z5HCssSjylYU+ME1fDlilF4jiQUuRmOzKMiZtpYkiRYW+koRAc3guvPbjH/Ysz7p2esQo9Isbmd3mFaU+0kUXusoUvX0gfSRZbOOdyqZ55Qd2SgA5nqEObJmW7jVxdRz58MrLZbHj4aIModM7m6CGVDIw8B2jCpURKjhSBOBH3e77/nR/gHGxOT3mwPuGzr7/B/fNT9pMjnLxkdXJqRLsQcCkhKUKymqcpL4BbB15JxLSrNyNqZJyGPL9PoMqYF0xH+/TNOfjP/3P4T//T+bP/4r+A//q//uH7np+f8/M///N0GUg62tGOdrSjHe1oRzva0Y7247OLi4H/7D/7Bm++ef0j7/s3/+ZX+bt/9wt/DK062o/LYjKMxHcc4LWywEeW1gaGf8iaWpkjsaXUyGHg8+Dwc6mHu849N6EEEaWRCTD4Iest5wz4ErSTJjGynqPGhnUGctrzLv6ek/q0URRF1TLMvefxO4958jvfMGVi8Xz2l3+R8wcPUDdjyCLCYZn05+++x2//D/8fvvj1r/Er/86v0q9WM+mh4FClL8u+VZq5bPOq+1RKBx9se1eEugWTctkXAfDBfooKgrjF/oLQh5633nqLNz7zhuF6ku8NZKxPyDU+8rnmgTArEBS12WWhj9OTE772xS8RfMdmfcIwjHSdr5CXiJiiq2uUy/M9m8t6RyaTNK44dRsrGafIdjdwcXHK/QcXvLy85KNnT2piGxnXdSid8+CUqYyxpFlRXdCo3NwMAGzWHeKEGBNxiiQVcEKKWcnYC+LAiccRLN6iM/q5H66IuiNFw2Y1juz2ir/peXF5hai/+wlsQwL5l5KMJ+JxEkzg2zFjqbT9rrPoeHmmFomcltiaXNEBtudAsPLiTkCdVJw+aTIMOZd6cUHwnZUqckIO/Kd67nHcs99t2aw3C/LOPDxl+UMpt6G3Lr2GrPIlViJBeZZcO/5L+p/UR6acb34U5yTkpYJHo85cMOSmJdL83lo5xO76mt/6W3+Hyw8/Yh+N7KExopoYp2RKyikR1X5Piapy8W/89V/nZ//KX2bVWSl1w3yXMThpLvNjrcyfi+3ysQp5qWzXzAG3pqCDuTslZRwTw6BcbyNd6NicdBZXy2pHsSXz5CRTQVF1edowlZiXz14gDkLXsw4dFydnrFcdU3K4bkfoeyPaOYeknMRaEjy1uZ6mU5TJEhcBzSrnmsclmhVAjhjy0Y52tB+DfWKiB7D0m6W8phvvJb/lFj77wT53H7B5UQmzw5u/n9Uxlsdv96lZ643HViTsHIKQUE31pWKCEVrPUdQxkiYjedRzpnwKqU58OdEi4T+3s7zcquqAQmWNxswKFOj7js3JiogjZicsLxGyU091tq2MQnFuqE53zEFvV8uuNPfisIOqvert2zpgZd/Dv9ttD89n3zvnkOJAV79k3t4kAx1d37Fa9xghRJjJHC4T7ef9Z2pOdlhdCSLPDk05QwiBi4sLum6F98EcTTerioiA984CdwfjsVxhSqnWZtTc56449fmlPMYJgD6rAUjpDxXbf9qTUmTd98SU4Cb3QCaqT5OV9kjJpP1I1PaJYEQEVbwXQuezk24qAjFGG7tlWCRhGCd0m3DiCb7P9wBzJjO5YtKIU48vJ7rDyphXVULn6VMghGTXWMkAJYCvmFzjfBdKsaRCHJgd4PbBtL9FhK7v8BoIqx7nPM55q3mXx8lmveZks8kSZ/XB5ur6mv1+YBzHg0VqcyfL2urWfZ6d4VvuVOus1me5rEO1WTMri5OWP9sdJbdZWrf7kGjGYQvmdpY5pWlWcf7TNBGnke31jmEamaIRiYZ9JMbEdrdnN0UjL4ngCXg8mvIiMKW6KFkoeswjue3QRd9J83u7yaGjfzjCls/q3eOvjI2yBk2xrEWbxaEmYkz2XZ63Jc/15R0Rgid0ns7Z87XqOvq+p+/6Zm5waLLMCmNrNx3fXkVx0PO7KaWIiJAQNNk8YWoe87x/9NH/5NjJCTx4YL+rwnr9yfZzzpnaS/jR3KSjHe1oRzva0Y52tKMd7Wg/3ESUzWbi7Ozj1UcPTRW67uNL9Z2ejnzpSy94+bLno49OcqDuaD9xa6BdskDqAkLMwbcKJcwRz48/oDYAyZ0Ycjn8AYa8OFQL6JZ/ClYklES/Q5xgiYM0Ksu16QWPahVrm9M0TZ3x3bLbjH2mjBdWLC1GNI6mZMhEilPtAG2wMoPXG9QmJcbdlmm/zzhQQqSU6Nbl/SgdqizxLJ3bOZvU89Wrr9seXHRN/BEOiSglQWjGXJbnKCQA7y3prwTGm4PnZjT4Y7lHBZM+II+05pxjtVoZzlwwz0roaTGz28GIGRVs7lUeMzM+pjVRDQyPtmTN+RpNkWNCNZmCiyqMY267bZWiZl6NNkoUNOCblf5wImjG+EqCnmrK8Q8qxhljAkbDXmtCn2YMOV+TJkTFklCbW9j2bauG4Jzgg8e5ZDh8Jr1U/D5j1KTlABGFJRmsfc7msS1gqhJ4nA9UtZJcpltE6EKw0j6lj8XwxWEYDOdPCblzrNk1Fc7S4hrbJyrjw7dCJvVXNeIJB0Ouwox3zG1lDivP3CHqfDhvHh63/a4lOZV9U2K42bK/uuZmGIhpjnfEyf7dT5Ep901RZHHOE8cpzxvzfCjNMzhstzx//D79yZr1/Ytb9/FWY9v5r3b0rUeLdoCVxLs7XwsNBqtQhJYPjkEm0c3bz/EAu+GWsGr4uYipivuQ1Tvy3CBSntXl/HJ3w+b2W1wxE5dyv5cG6yv2PtrRjna0P4p94giGEDOb2SanGvuqXsfBPFeZmyVSJ4sgapnOMnGVOssntcxoAUosvs58ZRbUxfu0Sk+ZT1InSSNCKN5NtQQHQp3cY/Y0NNd4M/mkhGYVAAuPFyenOEjlREU7rbYi/5Nym+wFnZKRMPbbLVAYf+C9sNms2E0jMU4kicSiaNKEQufr1KxFlYzxK4lh2NOPAe+y48oq71+yjydqRy68mMjyVVK+K+odhXRR9r1LEaTVXlTI4yP4jhC67AS3aiB2JXNtQ1ASUq+3rQ+JsTkr43o+j3hH6FZ47xFN9iOZwIPQ9SsevfFaZhF3OLEXc12yibBarViv9xas1blcjyrEJIzjxDAMDNPIGCe8wNo7OlFELcA+7AdiHBHJJJvk0eSJybPbj1xdfkSK8OjRffqrGz588ZIk4DsjqVxuB5wIfTDGMcYbIXQeROm99Qwngan3lVU7THsutyOh7whdYIoehoDu9yTdc3F+n9cevIYSSTKwWfWcrzv6znHNQEQ4pX/VGsfWj9NIiiP37q1J0YglILgQSF4IIvQIHlsYqDpSMuUDLU5R53He55Isisg0rwHVGLfOe+49vEcIPednF2hMvHjxkv1+RFwg9B2f/cznuH/vnBAwtY8EcYI//Oa3+fCjjzg/uWC12uBdHg9lnDYPT11Q1FGQ/1uIKGUXWa5lnThUSqkdhUwGKPONLY6Ls9kuaDMRxkGRgUvZ4S5TmSLV/z58kuo6Zh61OUPE2hFTZNxu2e32PP7BB1zv9kyiqAgnLuARXjy75Ho38IXPnvHwwRofVnjXo86xH0amMaLR+stnScN5FcvtR/5WG/PCtmZMSJ3i7Veb2GVxoHL15WYcLuSo1+oSeHV0PuTn1+Q8E54pTmxvRkSM8OFTQjTi1KG5Zuzp2QkiifvrQO8dbE7xXc/J6T261QmaHNMwEeMOcSPx0T2CNLOQCFKd+UJyciiJNN2AMyWmpJE4TaYUNaU6x7wSRTja0Y52tKMd7WhHO9rRjna0o/2x2k//9FM+//mX/Kt/9Tr/3X/3dcbxqND3kzYhURUmDuC+OTAptz87xA1oP28Cy2WflCPXDaRxe7dlMHGBbraxx6pMkDK0UxQFDDNN+TPUlDfaNJ6UVUVKULaWu60n04PGLZNElFw+QRNoJI4j4zDmIKWV6+iCZyrlY0WzToE0mNJBeZESgM8B9hgjMU1ZNENAAhUEElhkoGXVjdpJC8sYciF2LK6tyDU09whAD5AvtdLllvBVSm2XGzhjyIYLF6XrHI2oZYEOx08Td8jHMXULb4oeOUloRvjtu83pST6Pz8SHBtMR8Ll0Q2nZAa/IVDViJGZVBBEIkpH5rBRgqhsNZqkC6kgqTFNiGG5QhZOTNX4Yudnv7Xqz0sF+ipa4WBK1IuCNhEJw9rkCvcMnoVQ9iWliP0Zc8EZYUQfRM00TSmTVrzndnOZYSKTznr6z441EFKHD1+5d3NNsRhpIrNfBnouCmTpXH39L8SwBoFJydcZRTUHCSoDb/5M9drmEs+G0jvVmbeScfo1qYr8bmKYIYqVFzk8vWK97nLMkTkvGVJ4+e871zTWrbj3HLO4ap+W2L+ajAvs2Fy4z4aZOP5JTH/MzoalMF81zVKSaFzarCNdW6dw9tZsOmlofk2YOaZo3W04WHIeBq5fXDNNEyafrxFKjd9uBcZq4d96zWQfEBZwEgkglyCyxc3tGnnzvBzx79zGvf+XL/Oxf/zX8KxOlmn5sGljVwSu2PKPmt+fM2xiyiI17UXAq+Pb5FUHVW1nw0bDppIokBZdyE+yYXd8ByrpzBBHoesR5un6FDx3oFSkmUpoQiaST1TJ6J2RCmZ23lE5SFE0Wm0vOWZyx9GVS5iYcMeSjHe1o//r2iYkeJnXWqCDU9/HsgN/phh+8XKrjVr8UZnakfWEvMDXySPvSatjUrdtfmKlS/Fjm7TX/m+Y3L7X8Sj5fkUkqtdsSak4FZEdsbldtY/Xs2sIP88XO8nyWOT8Me1QcQTzeOTunCFFhSrEyq+19Y8QEWTgD+ZiC6Y9lZyGlREwjqt7KngjcLrdyuEi6607JwQ93/P1xptlJz6UO3CyLl2+SHbFEgqG577fbZZd5+9ylNMjMIDVHqVypc0LnO0RCfbGKeFSTqV7ku+mcW5xL29+T5hf4XGLDFdJKMkZ8TJFhnLjZ7YlRWfVrutDl+wJxsnHTdx1dF+z50RL0VjTL4FnAf77G4tAZMUBw3uHFlAwVwfm8JEnG6J4koTEChfAieBcYU2Q/jIzj1NQ1/KSOg7Giu65HQ+L6ZpvLuTCPw4VCh9IG7U115bCcUh4bPtB1gRAC4j2u6608DtHKwNhl44MtpPquo+8CSszPnI2JlOUJNd/Lupwt7WOxxF06wPOmTZsPeif3f3U20cWxD/dffqjNvs1UQ7P/YUZRnrxugQDNSeZf2+fCyF8xWe+l3hbJcYpM+wGdIsSEuIQ4IzXFmBbScKUu6I9mt7NTatvy/Hqnr/pDhuGtIyqoism+KmgqJYDIWVntvDLv5oMndJ2Nn+BJPuC8my82b25M7KLcYw9eikVGb76kMh8J9vwrgrpZom/5njs66J+WiQibzYbz8zMePNhxdjZx//5ym9dfh69/HZ48gQ8//FSaebSjHe1oRzva0Y72p9I0OoarnjRFus0453Uc7Wh/wqzvE30/cHr6o6mFHO3HZ5Zh7xY4TIZZGtP5wxrRPAjuLTCEBRLM7Sin1jIm9tlhoPDAKn48o9ulFIt9XpJ7mrK+WkpVaD2FNaPsPe82X7DOGPHdDZivQQ1zuHz6jKfvPqboBw83W1Ry6WpN7C6vePn+h6zPTticn1vzMj66wJ+EudNL21Miian01qz6Cooe4PYz8J6/Z/nF4t40v7a4f6vocQiFlaDxLfw338dFKRSdj7mILZRjtVi21l8XeFHF1+fzezdTEcyMrBJjqpdyiG8eDuyW4GDl5fMLUgvWZ1jcOE1oUoILDS6tGYMSvPdo3HH10VPUwcmDi1xKVqgkgTtgei0YpijiHL4IthRgLsdXUsazwEqh2LVZUlOMhi3OeO/hSW5/VD9H8M6jTg2HLvimVo32Zb8147SWb1kcz9rmveHizme1Fe9z3xa8npqo55wpv3hn17NoYsbyy/aVCPEqDPmua272uY2haj3CAjfW9neaEzfz1AGGvBxeLYbcNAD7bgHLHt6uOi+1rczjEdtXvZGsagJ0Mly0qLtYAnOBPu0eto9qmibG3Z5xt/sYkNx2WCh9H+L1t5rfAPcfgyvfhUuXmEq5fFVpuqGMO1ncRItXOIKzmJ1WpXo5OHZR3Z+nwjnmsmxk6SZT9HB1LlhcdHkWjna0ox3tx2CfmOix6k4REbxbOnwpzUzYdmpKeaJTrH6g5OxuTYKqy84HFA5yZbwh88sqTvkNXOotFsZzdobEXuwxs+DMLctBQGbdCpPrUzRy8JIo51TAAtlJQTSZukYhiDA7ds75/Hksb7rZmg6o74LJAu3Pnn5Ico57ZxdsVidsp8TNJNzsJ7a7Hfv9nmka8SmAE3ylJBbmsrXNiSBdgOCJqozTRIwDzgVOTzpEfHORrfd3l7Rl+/3hS6ndv/AUI0uVEBb7OwEfHL4zGTXvOzTF7Ehk1Yz8Mk35zpdSH4fmcgGd5agykkcXHN7Puo9WU83lLTydX1M47SKO0G8YxoH3nz2nC5576w29d3XBJHl8FWm5OEXG3UiazKERcTgfQIU4JcYpMkwTHz17ifv2u3hxvP2ZtxluBrzLx43GJt6crBhjZBU6RJUhbhEn9F1vKgEOkpMagB4m2E1KiOborruetRdOzlf0a8/2emTYR5Nf3E/shonobjhZe85OA773+OB48XLP9x+/j5MztlfXTBcja3pWH6fmkW+n9x2hX9GtHpDY88HL73C9vebB+IizZGz1KU10WsaA3SlHLhOSS+O4wijPvsxq1XF+fspqteL8/B7ee7rOsx32vPPh94kRek5AhNOzFavVitXK7vcwAWoLbidwtjllPN/R9daP4qwZxpYtw00yg11xTvFqz7AWBzqXURI3lwFSLcsBaR4PG8NtnsRisVwWdmXBmeeblGRevJS2ZdCgUlNkKTPXHt++z5z3ND87OEVCj+8TF/d7wjry7OqGMSbk9BTxPdPjkeHmhusXgV4Tq7NEt56YujWTV8YUwYEL0He5LijzXDdf5F3zwsHCJDPAC+Eqqv2Qy++4VjEEu45y7QtrFjlWK1EZE+iYkOvJyhLhbL7PylLkrAvvvM19mhBRVqsVqNJv1nTBM+a+TCgT9u4JAXZTYorJZE91Io4D482eOI55EKmdI887DtD9hAY1tZpkpb5UEupsHpGkt3rtaD8Zc87xpS99iS9/+XP8J//J7/PLv/xhLdtS7D/+j+HXfg3+m/8G/sv/8tNp59GOdrSjHe1oRzvan0Ybrjre/1dvsDofeOMXPiSs4g/f6WhHO9qfS/O+X8Im2eYEvhrlrZ8XUKBgxvXvNMfmSrhxPq4wZ/0VPKbBObWE3KCEnFP+vGSDKwWvsaBgkvm8M2sDw6QaDLTmfaQ5KFrwnVlYwtXA6u1gIBViMQ5JgpSIw8Bv/Z3/H7/z93+Ddb8ihI5V19N1gXFKTNPE9/7lb/Ot/+13+NKv/DI/9W//5araUfq0XIvdDAcuk0RiYkwREUfXe0s8a8kdyHzNJVK6SKwpONdBULrgxguyRZrvjbgS6aYG8qUoORgxwjmfg6JtQHg+jcUOiqrHQf/ViMISQxYsw99Jc50NFi74nNRT8GFLUIspcrXd4b2wCp2VdCgBXnE2jnMwOKVUE4a0jKsyrhNEtdLrN7s9T55d4kQ4P7sgjnE+dyaHhM6ze/6C3/of/ye6zYaf+w9/nfX5Kd71GQ8scWG7hphgilAgt+ACwUG3CngvTGOq5Tl0SpYsKBNdEPpgBArnhP0+8uLyCpGecRhJfcoFoP3i1i9ICNlKGW4fNigT17vnDNPAOm7oKYH3hFNXbmI9nGMuFdKSPRQIPrBadfgQWPWrTGARxhi5vHlJSuCxhMtu5Qnertk5IaYSWDfFiL7rSP3aYjriagJtOVnLsag5tzYg6hRTMVMni3FmpAmZCRD5eb9FHGnVZtrhnec+S65s2iUlEbrc7fJM3nEjmuE956Pl51EEnKlur9ceHxLbYbTEt64HZ6oXcRwY9449SugVF5QxToylZHXGz/N00lzExyGg0mwiB5/OGi+pXOGC9NNgyKUjlodpjmTvkJjDTzIkm1Nqv879IZT5wDpLBFOeB3wwAlZRPCntQyxsMyVIKdo8pYmUImmMpNioWefkZ+/zdUwKzuRdtHmHVO7cYTzgaEc72tH+iPbJi8/nN1ZlIJa3n86Bu/qu0eykqzaqVNl1VmbHLZWyBpqdMrfYt/446vb2assvV02zM04VAKMkY8/CHbktB77i/Epsv5g1Sg4nWm3+W978hZUthTV+axFT3tmZODJFYhgZ9nt2ux3b7Zbdbsu43xOnEZySI9JYxZFyvfOVikakFB7LgWnRXIIkzbX4bit7yB1/H16pNNu96t9yjKUbLdj6wbflDyXfsfoGk+Zs5aXd3leZ1xeL/9bdl0xflmsl88FmAS3nhJPNGu8FTVZ/Dozti9xm2wpGXoqt3FxefNi57POkyhQnhnFk3fX0fSB4bw6fc5lwA8M4ME7jwv/RMsaTZRsYqzpmh0YXZYakOAjBfsTNCxq7x8lkHMUIHsYLskXGsJ/Y70eGYSROU3Wgy9077NvSL5vTNadnJ4w6oJOpz6TYqBegDXfa/j50YJuEgfq39471qid0wY6RItMwMe13TMPexkjYZEJVGUeN05Z/EyRLJ4ZZaaVd6DXXpmqksxkkKCQDuXuRPd+mVzhaZRyUX5eOet3n8JdFhx/2+q1W3zrfchMbE0Y6sxkrawDZyBfoOs9q1RG8z2pMRrrwziHBPlPmuaL4uB/XsrlZy5lzMe+pAQcxRqYsXdl282G3HX5e62FS7h3EBDFiaqK+Phgs+n5xTK3PTa6fM7e32c0yWZQUD2razg9p7u6y0JBF29pavHVVVTrk6KV/KiZipblC6Hj99cDnP3/4Pdy7Zz+HSh9HO9rRjna0ox3taEf7eNPkmHYO38ePW0r9sZrIns59RNQzJr3HshDm0f40WYzC06drQrgrKenVpgo3N58cyjzap2kNTtqslXWOnC5xmZItLUpR3VSdUTtBW1iq2Y/bx6p/tzioNkeat6/8gwrfHIIYLV6csYJXgSfa7pd/KeBUg5kvgc7l7qrKcH2NXt+Q+pUp4p5fIGwYx5E4jex3I7vdwP7mxhIREcOFZMaQK4pWMPj2evN5khQcRkHnhLoGeGwu6g7cu3zfBqhb8ogeXGD5q553GXOvX7b4U9uEfKpF0+rpbD9p2jjj4/MxFohbIY4UZEfEVJmjHTyV/J8Gp53vadOP2oyb5pw1NgJZkTshzhMywaKCcfldFmNkHAa2Ly6J0ZL8Cv5kw6jBsfOYaslU5Xqd5ISrw3ulikURMn6dx6YmU/SYpmht2O+5efacru85OTub+7a9T7lfQhfoVx1RoyX3luuuna2Lvlkcp2ma9de8mXNCyPglYKoTaioSccpJqM7KD5mqxwGGXAL5SMVEa+zmVaBvwfokJzWXMtqHUO3hgyD1Ug+v7I6TLI9y5y8fhyEvmAGHYHTBJucxL95zcv8e0zii1x1jHAnDREpKWBn5RV1gtR04P+lZrQKh6/BdYLXZzP1G8zwtxt0rrrHtonbuO9wspawinuZxU5uvmYy2PG7FkA+xZZ2xZFcAchuot9vUHLCqdxwqeByct8Qxtc7nzUUtMGKW6u3NdVuLDia1ox3taEf7MdgnXh2N02Tv0BJEK4GzMqc1QVl7w1koWGqgzcpLaJbdr+SF5h2W8gu3DbrZizXVbezoRYuhyIzZX1MmczhX9jcv7PCd0DIxzf/UfKycaS9ZlUGwsjAKxi80R8n8VDdfP7lfKCxEa5MCg0ZiEi7Wa1YhMEwT26srPnj3+zx/9iH77ZZht2c3TOz3E957fAj4rmdabQg+sUKzAkZC44BsX8D+Itf5WuHDCnHCOO4Q5+jDikXZFLr8e6m/mPLPq0CRotRwa4VyYOUcJqfgRDjt4MQnYCIxZYdMqi9szB/BZWawfbws3XPrDX7wU/pa1AK0MU2k5MH3B/smNuuOn/3a59ntdjz+wUfEmHA+IGHKTmBLFbK2THFiPw4kTXin9F7YBFOSGFWZsvOrkvCd4kPEy2iiHH6F7zZsTs+5vr7kne98m+1+ZJgmYlIkBTTBftqbQ5xZ1tvLiRDgxMMmOJJ4FFfLkgxjJJIYdgPTbmR92rPa9IxDZBwiZ33HxcmKdYA0XZOGPWkn7K4mPnzynPsX16Baq2W+ytXsV4Gf/YUv8/DNU/7Zv/ynvLi8RiZlpY4AOGerHCsbpMSIEbdEURwxufr8atKq7OM9bNYdDx/eYxhHnr18yrDbcfX0CQL0qw4XOnyfFX7GiOY6gEk1E2As6A/Gtg2hr0ooxZEjK37kYUdKE+O4tykqdM0ijrxRnofqKJ17JtVgvzTSne3wKoymVzlnzepFSykiVxdItviZt55nVepCsBCjiqRiygkRvu+IKbJ/uWd3vWPjvRGChgk3KV948yH6mYecnPT0nWe12tB1PWGzJqxWrFbrfE6PuA7nAt47YiOLuVhXsIA6crvLHN6y15X9bgsSub66ZtgPjHE6GHDVJW96bTFDm7KOKrsRelFWSQleWK09boLdUMo32VxWnuAiTBIxpvU4Tmh0aOdsdnfe1JBSYhonxr0yTlarNgmE4NgET3CCqtUUdsHjvY1/L4J4yYQrl8d+nrcqdnJ00o92tKMd7WhHO9rRjna0Pw5bu+/z5vr/yi5+iQ/3/ymJk0+7SUf7I9rLlyv+2//26z8y0QPg8rL/Y2jR0X6cllLOAE8lyarBkLMtymFoUeqYI6a1vAANLtHsrxVbmYHlmeTQYhpN0LPBcFL9rOC+TTCwtVvR2DmwKjniafFYoYJuBenI15hazKNJjlu0UaQqpK5CZ2W/U2IcBq4vX7DbXjPlILfhkolpf8O03+K8J4UOJ0rAVaRLdYJpB9NAUS0VHxDBlE2dZIVUwWSwW/PN70YOuAXXSnNBFerJv7T1MWpkWAxPV0uo6T0MTjFcJ1JLniz6vyTfuIpVyUKFhObfBXJl11swZIRSukZrDePlBYXgeP3hPaZp4vLljSXWOYeoy8coqi3zeZIaplTET7xAyMrBKX+fMpjnnOJcwklO9nMe5zu6vmcYBl4+f8bl5Qsrz6wK6iAJMUWLyXiHOmHcDzgHnUDXiSnOMif3xZRI0RSr0xQJfcAHR4pKjELvPevOExyoDmic0BGmIXFzs+P6vWe8+53f5P4br/ML//6/S7de3SY7iKl6v/7GfTbnHY/ff8x+GCEpQUsiWo7nZKzMclZnrDS18RktCZdFhdex2ayJMbLdb4nTyLDdAvadOIcrKsnJyuNoxVIbvoMyJ8s1GW4tp6AMBdVETBOOgARv80lV4pif2rtw9XbWuUVOIN/LMv8c9mXZtdmnjNkFl6POU7dxR233rPEOYX16yi/+B3+Ncb/n2UcfMY5jJTY472v8StWSBr0Xgu9MpfzeBeuTTVa8kBxEcxQ1m2VJowNbTO9zZ89l2c3iOIEo4zAQJ0sYXB7nAEM+fObz70kNB/aideYKnam7TLEkOM4xgHoILc+pKZhreYjL8+RdjoEkYiylbOwYzgnBZfVnimp4URHKyieuvNeahjdknSOCfLSjHe3HZZ+Y6FEmZcuOlzw5WjB3fovmlxlCJWdImmfOGhTM02ozm5VJlYPP22ioNh/aNN+4xJI30yKV1rzitLzk5v3ra/FgRi1qEZWtWJ3T5m/0loLHPF3PDkA5hyoEEXqBMZm00267ZYwjaT8Qx4E0JnSKRDWpOnGCpi6/BC2gOE0TPo5IikjKdWjyS8RezEph56YqpSKI5HT40u668Ck/r1pYt556e5XtzZm3FRFCVmLQcq+bMK603lO7eynBks9VF4D1LPNCTZDGmTh0yg+DxikreqxwIqy6nkliru1313XkMV6c8OzQmaqb5Hthjp8mK91T1gZ1vSKSJet6EMdut2cYJnMEKvMzX5OY+oEgJLUfJ0Y2Ko+UpkREjE0uQorGdC3PkWDBZ6ODZKcn2RIyuAAiDFNkjJEShBao5KfDwjniHKf3Tjkbz5hSZLff4Zxj1a0y6aS5t42jVt1dXSrnWMkR8vOpTNPEOI7s9zuG3Zbddot3wqr3eIGuCyiO3X6kLPSrD6hza2fFhnJfNM9NphyieaEVY2SaJpzvKIQiUVNSqY0/GG/zmOTWNixG9Mwsbuef+vW8Brj15Ny2+W7Ueak57cKNFytR4bwn+J4ujHR9QLzD+2CEjy4g3lu/BkffrQnBFo9d1+GzGggi1UGHZt1yu0d+yKezxRiNRDFNjFOs5a8W9/LWtTe/zjcZ6pI8/7Z49qEs2g/nIlV7josLn5IiTjP3T+p4sTqd5Zm0o7qS1ZCbYFKW8yKmjrumzaplIR0ZxuFI9vjUTDk9HTk5mVj9ECnxszP47Gfh6gpevpw/d87RdR19fwSPj3a0ox3taEc72tFaE6e4LuJX8VYW5U/KnAz08iGTXvBqHOPPjm02Ew8e7Orfu11guy0JPH+6LUbHkydHos6fVZuDeUu8rSaN5HW5HAQutUTL62qegyBn3hdbyx/GPO/CeVus0Q4vi40X+HKVi1geowRNbyMiSwy5vdY5RjtjyCosjiHNhrMKhAXJAzBk7G0aJ1NMjZYUpbn2+LDbcv3sGf3JCeuzM3AeRYnDyM31NfurK0gpq3rk9pbzoDURMjW3SZg7VgrYNYN+9R60l1qxnPp32x/tMWTeX7IKg8zodE22qp3THOcQQ85jpXRpvYQSRK373zFfavvPjCGboodHBILzlvLZkAOaTpqP0RAUCj44Ewca/FR1hsRrs7J6rPOAWFIhwurshNXJqRFfMoY8E1UKNp2D1xkDE6EqRydVXFaqruSK3PZZ6ENq+2FWvo4pMQ17tk+e0a/WaEzz+Q/6T0To1j19Gkk5biEihk1WTE8X5zm8EYeiCPXWqZJiJKZIjJnglEkKwXdYMq5l+U0xHcwTNk7uHAoV28933wnjbsfN85eMXaDrOlYnJ6zP7BoWGHI73svfB890O0xMnYg6p8li/4N9ZN5xoZr9KnixDsN2MM6HKkisC57Th/eNRCHCOA74YKQXl/FNwzwdPliCs3fBSvIEb8rQdR5Yqh1/PEJcWtBODnqrz5ImJNq4i6lRf1l2ygFYnn91zSbLiYSiGr+c2w8HST5HiWWUU+nirWDvG81jLI+d0pL6vJe+z+WoyrFvvRsESBmzVlPEPtrRjna0H4d9YqKHYJPZFMfZERIQtYC3Rpu4i8Q9kJ1Ym2WdZKpBZpmi5ptJdmY9UPixSKPwIHCrBInOQcnWoV7WCFv65618Vyn4UlzbW8fDAu51WdE4MMVRmVtUzufy8bX+qxTmcMKPW0IS3JQgKte7HYPCwx4ednCpkaspMY7CXh0+TnSi+K5D/Jrddsf7T19w4YTX+kDA2KviHF6spIf3dh1TnFBVxlymZNN3eF9a7LF8dwX2zC9J4eANeXD3yzWGvM9tRRAvcNJhqhIxWZA37hFgnWvheR8yEzSiDEBoXruV4lDbk4gkIq78zzu6VSB0AefN8QhkBZbFi9raKIB3K9arwJuffYNpmtiN1+yH+Spa51ZTQseRNI42EpwF0AkYkRpI44jeXCHTGT7XIhRxeYwnfOjozl7D75WUgsnfDRMpJSY1p3e1MiZ83I+k4Egn56SVZ3e5J44JIQKRYbT9zk5XrPrAOI5MOvHiStHrkXVnLOz9Hl48V05PlHAu9OsNb70VuLh/D5WOqJ6BhJX5sPHrD+4ygHjP6ZtvsOngoycf8c73f8BXP/cF7p+fs1l3JBXiNGUnZpVLp5ijkmR5B2JSxhjpUgInPHvxgsfvf4BD6TLXpus8wZtiwmq14q233yYm2H7r26hOJE25fmphZud5x3mcC6gHccoQd2x3Du/h7GzDsIt8dPmSswtTUzk/F/rVxpzzqj5UntlcF7CCBtkNdbmWal7xSiEsuLzEz+kfs9PWrE6anl3WfW3t8K95zOYBWYk5KU9ThSzV9T0hdHz5Z3/apB/LArEKhljdSS+lVqf9UuY3czonRBSfpRALyc0Y8Qet/RjffeHiq7LfDcSY2O8nxmEixkRKjdNc+rksqvJHs/yfKbiE4FhtOpMpzS2KyUorFRlFT9ETqhQ8EtQ6pGEDnRde7vbEHVmJx8bmNNlN8U6QlGDMC9I+4IJHPPg+0G829OsV/WpF3we6vgOUGK0dKsqUJl68fMnNzZZ3Hr/HNE6v7rCj/bFZ1yX+xt/4Nj/zM095+HD7sdv++/8+/PIvw9/8m/Bf/Vd1OHL//n2+9rWv0fc93vuPPcbRjna0ox3taEc72p8n688GXvuZJ4TVhO+OwPRPwv7Nf/MxP/uzT+rf//gfv8Xf/ttf/BRbdLSjfTITyQkYpJmQQcZMdUZkl6oeVPB5Dg3KIoDXJuXNCXgNDqNiJbHbYzZtKvtCifvpnfDnMpSp9bM2RlgTRJhxjfYYGeDICZFar22O9s+Na5WnIeGSBYUlJ1cO00RUZeNh42GvypCU937r93jynR/wxV/6OX721/53uBAQF/jg29/mn/1//xfYbtkMU1atzriQlOx2w8RKMlnKfRyCy4q0YABayeCyzPtlZrrMfy8i6uV+NCoG9f4a9uOAzkEQmmQcQ2mDt1LNBfe2nSfAzzC+NEHcSqSx5EcRV7EvHyxRSnIw25S82waXWEMelRII3nF2cUqKiSkNlFhsRbG0BIMVMgHHYiKOEgAp+ZeaEowDpD4nWs2peoIi3uPlBDeBquPk4SN+6T/6G+AE1/ekpIbpi6KTEh1ot0KDY9pPaMzotpLLJ2suLy6kKZFI7PfKbkgELwTviBPsdkrfqQX2Q8fZuWe9XqHiUXVENP8Ycl/HfBNrR4T+7JTBw83NDS9fvODhvfus+54ueAuKp0RiguDzc5uxVSkkgNr9Ofhtz8h2v+fy+jrjlDlK4F0tSxN84OziwuIfz543uHGO5tR5RjEVCl/DGFEnpsmEnvu+4/v/4nd4/I1v06+sDM2X/8Iv83O//ldQXCV71KBRjSE0DZd5flnAp4WMQPvcHHx/8LE0sZZXQ7GSn8WmB3WOUNUZUax53lvs4sHrr2XV7OYwgGa1nPnZoE5wUn/PMa42EY7SLbcR79sRB/tsnvLtmHGKlqw5pVyuqNy79mLK8eek6sX8K1ldo3NNkqrUZFvbsLxXtD5/hQ5SknNdZ2NtP1ksKiVLGFSFlOcAlzF++0BwvsxTNj59CPbjTTnbeVfnizzy8zO5ZxhHLi+vcrLx0Y52tKP969mPVNhS6ovSXpI2z5YXqDm/rpVso3F86ttD62xcGKF28Lbwy9L5LgesBJHmXVHYq2RnoX2plbO0fMOSHz4n3svi3VMXCzQfLxzV4sRLbf/Sl50vXtReEFo8oUwkSCkxDJHdFEmSGZIoXnL5mZQgRiSOViYgTeg0Mgw7Ju/RzlMXCdVBnxmD5qQXmTfMNVNFxErnWHC63JfS+qovWK/wtschzd9LZ4wcIPcevMdeclj5AyUzNNXhERBHYUNam3LAvTh7B8dv2yXZoZNcn6M6Fre2rzcYweOdsF6vmCbHELd1/Tdfy+yQVMJH8Rxq3xYHIJnEoSZTVsiKCE7s967r8P2G7fUViK+OpWUcaHUspXSeKgkh4YgqVksutydO0SQZx0jIHppzwjgZiSKIQOeJEaYR4ggp2rjsuw7nPNMYmWKkiO+Ux7Y6GCXgnslNkSx5Nk3EcaTvezYnJzgpSiKZycrsHLbuXO19bZyznIFweXlJcI6zPuC8o+98HbfOOdbrNTEZMawwW2OccAuFjdmRS5mIMQ4jOxmIKeHElE/GITKOpuhhMopl8igXr4u55LZT2i7459+bkdLOYLd2PZha5o/L5JPnzFealjm38WsLGcPZPLs5O50vJz+D9pvReJzmuraSR2DxcvOCk6xQIa48gwfTXT32rQ9uW+7aOMX6b5xSJcq0/XJ4oXV+Ppjcy3XWdmvTlvJPvTVCAUxmhRebL9ItZnj73skLlKbQayHOzCuH+diIPWPDONr8lib2w2DyljdbLi+vGY9Ej0/FRJRHj7Z8/vOXP3Tb116zn9/5HXj9ddjtHLtdYLPZcH5+fiR5HO2PZMKEl6v8Xl/z6hJ5Rzva0Y72p8ssw9UUrzabia57NSC533v2e1/V9Y72Z8fEJ/qzPWH1kwOkvUusQmJKwjC1iSlLcxLZ9FcAbIezP2VaH8p6PT9XItD3pppy//6e+/f3dcs/+IMHNXBztKP9STdp8KY5OFrB4rmswgJfbBCIw8dd7gAUZLn/nTsa+MZyy4zm3grO6sFW86e2eQv0tGWoD5HFgzYViFIaDLnFWTKu229WrM9O6XNZDqKaokA0bKXrhFVwpN3AGAeGm2turq65fvszDJeXuBBwIXDz7BlP331MnyLrrls0qSLu+e9Ub0kBDTVzMWYl3xlDbi6q9KssDtzgPgVH0UV3FIwQsOBoKW3AfP+1tsGOU2IRtfeaYTXjZe255ybNcM5hkLmxOUhAKRETgic5IQ5ygCE35yptPcDT51INc7kYwyCLWonUdnnncD4whgEQQt9z/vqjTL5JFEVoG7HGmlIRSmqppgabTbZPiolUlb1L0lSyZD1v91zSHOBOUyTu9kyuI0VL1utPTug2q4zJ2ZWllBh2OwTo1msQS7ZSzVh5SnjvCV03Y/xt/9yBB7ZjosWQU4rs9wNOoM8lRnxoYjYihBByvKPsnyz+sLivldrFsNuTpgkdRgbnGYcRAbYvr5ievKBbd6zWgc989ctN+Krc6GbMHzztr7QDzLmWvb7z+1d5OLf76xa22nSvLj6cVV8ECH233KdiyBkTVg5ia7o4JSUBunnm5eD5flXbbn2fG5uSAjlBMJVHMX/ZbtvYnY+xzPOzLgMfB/u2qeC5SYVglJ/dhUpPe66mJE8tzyNlfmwaOmeS50tWYoq5XYkpWmLvOI7sh8GeuaMd7WhH+9e0H4HoMaCYfJMugmItsaN9YR0GZqWZ4wTjlLbz/9LpbqWgZjdf63fUz26/YrUcOQfmSoxYONjwwBxSVUXuCCvP76Hi+959GECy5Jlysl4bM1HgGuVy3LKdJl5cX7Hd7uimEzSucasNq3trQkysYySg6LhD4kAYd/TDxAmKI/EsDtyLY2Y6xkLKNmcUNTUS51n11sakSoqJILtMCOmY1Tte9TZu3rqLq/XN92WfRGIAmVj3ntN1z8OLMwJwtfVM08TN9gYQ7l304IzQMqaEE3M9Lc4szc/8kpOqQZHHhTjEBQgd5FIVUhiyd9yLXBCNvu9xXog3nkndra0t2wCGmNhPE5rAqSeEnrBaoSKMkxF0rkZlSo7O93SlJMbmlP7kPvcuTvjKF9/iO9/6Ft/8vX/FmBJhmowEP9g9StHK8/QnHeKE3dNrRIT1KuB7h3PW5+MWpr2yS3vGMHD/0SmnZ2uefHTN9vKGkY7BKZps5O6JbGVHFiggjS+I22/x2skZTk3No9zBqOZoXO5vQOB0fcZ2P/B7//z3ePzeYy7WK770uc9wce+cbrNm2l4Rx5HQ91avEMUxkSSg2pCPaPwpVTRG0jDCNLHKyifmsJkqQl1wObE6i0nxJKY48ezZh+yHax7cv0fXdbYAiSmfGy5f3LDbDjzjBghM48g0RdBko0YVSdEWIwoh2XlFHM7Zgkayc1sdszQ7bpWc0zwT4jLhJ8t0iOo8Hx4MQ/u4qJKU75ptU7vobRY48yoNxcg39iT42q7yPJQFuHW3HW+uO5gXhUW1qFl+giChx2/OcN2KUsIluKVk3StNy/m1ks0U5ebqBlVlux2ZxsgwjJV8ZjvVlfzicHXxkTMcNME4RVwEdELESEGi88Ii4YgISS1pJ/iAdzMhyRjVhY5XiC6w6j2nJz375JhUCOs1bnUCPjClSMysqN12z/Onz9isA7thQNOIi3B5veWddz+0eqfjxH4YefrskpjlIpe1bI/2J9l+/dfhq1+F3/qth/ytv/UlvF9l+c+jHe1Ht5X/Pm+u/2/s4ud5MvzHJDafdpOOdrSjHe3HYt57vvKVr/DVr77Nf/gffouf+qlnr9z2N37jTf7X//VtHj9+zPe///2fYCuP9mfRPv/alr/0tee883TNP/r9B8R0dxjk4ekH/Cf/xv+FpI7/1//2f+LJ9k9PSRDvlX/v3/suP/MzptwhAo8efbw63dGO9ife1NQ0HS5jyPlz8Utc9lYAbxmCa5GMu3a56/cFnCE0R7x7/qiKpgeZTLcw5DvaOoeQD07anLHJ9XmFGZYe+p6f//W/wvCXfzVjvMpumJhiZLffM00Tp33Hpgt8/7d+jx/89u/jNRGS8vQ73+U3/x//A14E7xzXVzeEaGq8uxTZazSyQSVuNO3MWFhRibZYpOJkym07wI8XuL/kf5rOaRO1ZmnaZp9CXkgE7+iCZ7PqcQrDNJBSYhxHw5izGrKVezcNV8HlQzYY9mLAuCYgm89v4BAUXOkwdrGIHNv23tu2aXSt9u7ClIKtpkyGsHLezmcV55SYYmJISlLBOyuF4Z3HhR7fbVj3HQ/un/H82TOefvh+LrtixzP1dLsfCPjOjjvdDIbfeYeEWaEkjsAEk0aSi6xPero+sL0e2O1GknqiUBV/I8rIxPt/+G1+/x/8Jq998Yv83F/9qzx68Ihf/D/+B6w3G7pVbyi9KtfPn/Mv/qf/BZzwS3/9/0B3espH733E1dUlqxB4cHHGatXju0Aa7V4679Gs4C0klKz0ftiX5aNUEmCVIPO1WT8IWuIHYioOquAyKWa7vWGKI5v1yu4BTcA+Jb7xd/8h7/3hd3KMwXH19Bn77WQ4ccGQM54YYX5e8jNawe5KfFrOGYYh1+a1A6vCwc3lLPYtj9IiBnOIIbenVT3YRCCXaCrq5S7HUm6pElUcOmPI9Tk4KJyiB01wHul6xIfSK1XBf96JjzdZRpzGYQSUcTSiUE3U1NLOUrY93XGcZn5RU2+WBHhL/MMZxm+XKqjOhakES6JMqfSI1qmi7W7USsR3nbfkXBVTTgodiLOYW74v0zSx2+4IwTHFDWhCEgzjyMvLayOzxEScItvdUBO0jwlCRzva0X4c9omJHkqiMPcKu7W+tF7tL+ctDl9v5bPiqrcO3+GB5i2bk97a7lUO88LXa/3Ou5jgH2OHPuCrKAXlt3LF3s8CVlFNWm87Jnb7ke1uz03XsfIdJyvPyfoETdHUIqYR3e9RojG4UyJkR3+viSEzZQsrmMW5pfqyClnGTVGifadFZUIOY62fsCfaV3J5ISYg4Z3QhcDpyYkxiEUZhpHdbkcsbdYiCzirDSxUBg5WZW2Wf1HOEHH5Ze8Wcm91JB1EqgVykNhRlgbLHebTmmNhDoQjS/s5q19XlAGmZCocTkwWzH48LnRsNie8+fpDXj57Qug6q03oZ0kzVKrTUkgq036yRnQO8Z4SZyxrlxjzokGErg9GlkjG0p6miHMmhxljYhwmUoIpCpoGJN0w7HbmUDTPmGKO+pQmVISophLy/MlTnn/4EX3wyNkpXd+Zg6yzpON8o4yIoOLMgdES6G5uZmavi1p5n9kRWwwhytid+ykxDHt88KTsrNa6ltkB00mJYyJOIzFO9cpMelDwjtaNbYbWXBalMpSrty252YdPeWnz0jOvijbLo98ei9VBzhki2jjby0d4/rddHze9BDrXHb1lyx3t0TpcReTnRRzivP00GQWtw3+naskrkAohl0dJVq5omuJizLwa2DhcXOdPEySnNHjEYjvr9eYNUdjlWtpYFvXlFLaH944QPGM0wEm8N/JYlgYtk6fGxDROpgqTEjHmolO7PS9fXjGNkThODMPE5YsbANbr/kgU+FNkb7xhP/t9zz/5J/eJ8XjvjvZHNy9bvP8uCStRd8s0mfRWLKXzjna0ox3tT4eJCGdnZ3Tdhi9/ec3P/myg7yMhLOcyVfjoo57vfveUcex5+XL24WIU9vvbZNgQfiSR0aP9ObNVl3hwNvLipvtY9Ca4kdfPHqMIZ6sXXPfK4NKfCmUPEeWNN2746ldffNpNOdrRfmymNeOuyZ9uoYrbIEPz+20MGWmxl0+KIR8c4BPYbQy5HOfHiCG/og+cOC7eeA0FpmFEcynkMSndbsc4jpyuetZdx8m7H7A+O4Mc4CZFrj58ihcIThii0q9XeBErR911GSZpI8WlGdImqmdSQcHMDCDSw3v4cfey/bwleSjMCgLWDiemaNF3nSkri1r562may3gUXLE5blH2mBObGsSsOWVGvut1kBVVKlxUmnwHttUe6DC5v15O7tOUk4WEuawFRRkAqsJyVZR1c5JT6DrOTjfsd1srMTNZefaq1KGlx4SiBJJiMhy+JEMtlKPJyh7WYO9co3iR1W9RnJqaQoqJ/fWOlx884eTefcZhwIXAvbfepOtCTog1m6aJy2dPAWF/fUNyju3VNbvrGyuLnPHjUhaoqnnUvmtuouYktUMMmUZJZnEv6tf5EOVZzzcyKTFNuCgo/eK+Sf7j+skznn7vHVISNM3jxtSAyfGHuzDkfAfqdKBzZxd8d5Fl3FxTjWnMx/34mWSJIUtTLql01SeaiV451x5scxAYqpe23CgfSur4XvC3yoSpd17y4ppas9CGAb4ppoofa9tXhx12OP8cNLWUWrkLQy7t1OaLJYbcbNd8VsoFpZwYaqrYhYDSzhPL67A4DMQxst8N+XmLxKjs9yMohM7/EWJzRzva0Y522z4xqpJIoGJOIsu88Nle5d3dtkNZs7u3kIMt2n2Uw7fW/B7Jrtzhy+mWY3G75eVVckAvqZaa7T/26uo7bD5yUuXx4x3vfXDFfrdlHPa8PFFONnt+6S98np/52i+wCrAO8OEH7/P9732XwSrZMRLpstNznSKX054X188hJNabgBBAe8obX7TcJwtMKqDOZXm3CBrNqcRBLvOw7IXYfCbMpV0O35TmvDkU7wIudJxdXPAX/+JfZBxHhumGq5sbfvOf/w4vXl4R9zfsrkCnCadiL8t8qNaVSpkMIhJwEurnXd9xfn7BycmG0HmcF3txqjIzIPORskcnzUIiZRWJFLXpo7S40pvdwIvrLTFC502ieBVX+OwppGQyWxoVSY44JnZpxzgMECMnq47Pv/UZrp6/5OHZG6TJ8+LmysZSsHaNo5ozsBszsdzaeH21R0TYnAdC5+jWggueabSSLrvdiFxeoqJsztbEMfHixcDFhWd90rMf94xDJCYYI2xO7/Hw3iN2QXh8/YL7RN7cnFm/i+B94OHmnISy14nt/or3v/NbvP/ODzi7f4/z83v03TorViTQCY0jGh0xrhgLFdaRPamUn5L5biJGovUeus5XeT0RwTvBBYfgQYVxyiWHnAMfiHFFnFbE6IlpGYAV4NGjC157TZgy81fE6jWqV9QpOkXSFPFAQPE4nPg6ktu6f9IoeQCVuVy4zZXDb2veWkP1cCYqV+/KdnX2ahxbmftm0VHNAqgsa1RAYrPAqycvkoZQ9O2kEJ+0HKq5D1DLxiQ1okjKKhtOrA6rTo5J5qV8XcOw6JqyJmv+NlKb90LKRDKRiMhcOuv2jH23FXUQceZIOy90navZJWhx2pXERGLCkRe55SFW0CTEJMTkbB5xaiWymOiCp+9X3FwN7PcT06igjtPTU1574xFnZyc4MdLG/fvnrDcrpinRi9AFwSWYdpFpsmdNE/SdBS7cIjvkaEc72tEaG27ge/8Qts9h9+LTbs3Rjna0o/3INk2O//l//hK/+Ztv8tf+2nf5+tef3trmV37lPb7whRdstztububPf/d3H/J3/s4XDSRtLIRwJHsc7ZX2g482/L//2RtsB/9KNQ+AZzev89/+0/8z9zZP+Wtf/x9Iu2v+5rcu+PCye+U+Rzva0f74rKAJFcWRg39vWYuy3g6FzviDsGAlLM45H+k2ZvtqBLfsJYebfMwuh3HM9u/DmGT5vpAL5g2arRscKE0T3/pHv8mzd97j/KtfZ/36m0Z8iBYs7MLEGz//S3z1V/4S3kFwcHN9xYsXLyiUjJgSY05gE1Vee+sNJhLDtCN0LiM0M/lyRtV1VlYowXqZMWLrI7eM5i4iwzJ/foBx2Z9FrTmXMXGefrXirbfeyol1I8M48u7jD9ntB1IcmPagasljRVR80bnkUtmqSE7WK1+64FmtVpbAlrGaxViqByrB5TnVqRzT4tDtzdPFbRzHyD6MpiyRlUB8CPPRM45sYKGQojKp3U9U6YLj4uyMYbfnZHWKJmE/DbZzvpRYlIYl2rnzgzUME4IQVg7nBRegc64mS01jYu/2KBD6gEZlv4usVo7Qe2KKbPeJzZuP+Pp/8Fc5vf8At+6ZHFwOO9b0nHV9DfCf37/PX/qP/gbbyyv+8B/9Jvv9ju2JJwVPv1nhV2u8D8xgZa4PI5GUgikfLMIPM77ZmoBheM7Gk8tkFRszeYvcL6YOIyAOTcHOkwwbPhgobDYr7t07JcU8XgpZJIvWaE6otTC+WvJn84zOLZUlAeFgwqmxJdF5zJc+kXbTEvsqStHtQZcY8u35qHm+6veZAnWXTLM0GHLdr4m23Wo/9dmuJZXq1Wc1FRFm1yzfS5XFVdxpQlXWEVy+F+V+zPG4um3bsnJfm3+qUrgNA3sW3PK+oUX1OuZeSiANAb2odajkeUSzWoklNXsfGKOVKE95IPddx8npCX3fmSqT96w3PaELpKR4L1mdCdJk80DKoL3P7Svq1kc72tGO9q9rn5zoobrw1V5N9qibcNe0ftceP/QFsDjm8ij15Xlry6W7fed59WALKW05XGCUX6X59PB7adjlBy/t/EdKiZubiRcvrKRBnBJRJ3aTEuk4Pb/POgibzvHy6hq8yUJNmkjO4YIzkkFShjhxvb2m7wPDcErX9bguVNasXdQdoociuYRCvocLWvLcaiNHlCVZZipWmkvZx7yzWnIBYyR3XceD+/eNrCHnXN3ccPHtd5kS7MY9aMyLD3u5JRJO2yB+qYeWkMoiN/PO0fd9VsowpvTM1DxcTr1iWafMN1/rUqaO7ykmhjGSkh3TuSzZF02poDjpRZYPzWxqK25IcI6zkw1nJyds1mf0nZWt0flkWdbLmOquLFYECzgjrDOBwncOcUpKRvSIKTFldkUInmlIjINJAapGUopMcTSiR4JOIwTP5OBq2LHqe9hoJvnY+njlOqaUuByuudnfcH35lO3VU+699ojV5gSPY+5ktah2LoeiSRvlTbtnZduFtKbMDFhxLrOlBeeL820SalOM1WEScaj6/OMO7rH9u173dF3HNFopIxsTjuSV5JTxZmA/xblQUfNcVJWQduQ1NfbqU9E4rdqMnTJLtHNQqwJypxJG2X4xGNuZ7dB7b/7Wsvg83KY+AItH4NYMpQd7lWvJjnshIr9qLq5P/GJhvLzHVf5Tls/z7d8P58ny18F15IWcLcil9kF7diUdfC71JyFEBbKTXqQinRO8N8KPPbu2d+g6NpsNXa5h672jX3UE72cVHgRRJU3JFof5nN67uk46Ej2OdrSjLUwV0gTjFl4+hu2zT7tFRzva0Y72RzJV4Z13znn//VN+9Vffu/W9CLz++pbXX79ddsL7Ff/yXz48qmcd7Uey633gev/DYav9tOGbH/48r529y1//mf87q/UHnG1+gRf9GePoUT066Ec72k/SShD1NuD7cQjwYaDzbiz39u53H1NubTOjx8tQ5MdhyAeYzCJ4fLu9h3hOSR88RLFn3ELrocthUkq8eP9DPvr2d5GHb8PF6xm3MPx0Ssobn33IZ7/wOYIzBY/Lyxf0Tz+q2fAls1wx/PL84pyokXEcif0EOHwtqXvQF+11yjK4u0DfVZtPC4Y8Y8X195ZBUyG3okYtOO/ZrNcZ3+kZxpHV+pKoyrSbAFOgqMqrkppz5X7WErh1jRIJOcHNG1EgkwZq4PfWPW7vaWuviGRUfNcSCgtmKYWYkNkWpbRw28taExat/HrfBfquI4Qe70eWY6ZgcHNZkNLqlGH6kO+FBd9nqM/uvx3JOceU1QRS7q+kCinSnax58MXP0q02iPckgSFOhOihm4dD6DoevvUWl6tnvPyNf8jL5y/gjTPcZsVq8wY+dKYAoqWTtf5UMk6LsZabUfHOfG0ZsBbXxB0yPijNWJ1VX2wnRTKIu1RtKBaCp+87Ui4PUtQpVIzgFEeY0pwMOu96OxVO4bbaBIeI5fxJFY7IH7VqLfNRb89j9TzNVotzvQp4XpSXOcSQ79jnoP1SxnjZRcovujjn8vSy2L4KLDfns6Y1at4JboOocvCv5v/LwRZ6x25NL1YiUfkzP4cLRZZl25q7T7lj5ZmGmJ9n+9Z5T9cFvM9J0K7MN3n86Rz70hxHKla2sSZ/zA052tGOdrRPaJ+c6JHsharucDKV5r+HzvDd7qx9Xib1V70RZfHP3bZ4/eQiEu057t5DqxN4V8vs79vf2p4pf1uDxNmpkuxMl1piKf9YGQOb0FM0hzys1oiYAgaqTINy/XzP88fPef/FxLvPJjbyggsvxKSMg5X18Am8ePp1x/Zmz//6D/45m03Po4enXNy74Jd/4S9wcnJK369xzhGcHFxEcZAaRQNSdnCS1Qh0xmZUte1siJSXXEv2KP8WEogHTArw8vqKf/5P/xkJ+MLXf5rVes2/82//JeI48f0fvIcqnN67RyLx9OolwzRycXLBul8TvLeyJCX43zRfKC/RjvVmxdnFKevNKvsZpX2wVCOhfl7qOAbvCN7dOkdZzKg4knie7a959/opkhJd8CZfmBJpSkxDwiFsVn1mnUaCF+I4EOOEqrLabHjri18g9Y7vvP8tNCpxipXljRh5Q9P8fK3WK0IXuHi4YrVx7C4nxn1E4x7ViZP+hLP1iie7G66vt6AQepimkZcvbzg77bj/8ATnPOI7+v6Uk35C4hUfffQObtrxhbN7ODePgZHEi+0L/vY/+9u8/+F7PGdAz89x3QrvMgs9K3Voiug02t1PUwmlU5RRrBvzIiYlNEY0l51BBB+M5WrkGavF6bxHvGOcRh5//wfEBLvtQEsWKI5U0jzyxIggznucd3ZPmNDk8CL5uRR0zHVIU8IlC/Lj4+xcN1bdSDePHcVqNC6sPvQ2h1WSsM6jdV4UZIeOWdmibFPK0FTmeUtWkLJo0/ro2p55VTdv1v45z1zZm9Y0C1q2Dm9p95TbnaKVKyoLQCOBLed2Fk/jokMoi1OThExlCTdfU2m/zjkSh1bWdoo9gyqZYJgVdJyLTJOVTipNcGLVPTXlc+bO6kKgC54hJqKIEeWc3VsbqzZq173HS6DrxWYNcQTX4cTNTnlDXEpJmYaJcRwZp2j1H60eUa7/ebSjHe1od9j+En7wm6bkMVx92q052tGOdrSjHe3PrL180fPf//c/zb3unL/yV36Ac8rf+ltf5r33zj7tph3taH+urOZWtQoMwA8BeReBzgWGnAO/NWYpy73qDq8s070M5t9OoHm1zTD1beS7/H03wpzyedKcEV/gpIKZJK1YRsUc9gPb3Y6b7Y6k4LzhclYyGVJUhu3E7nLH1T5xuU107Fk5IaFoNOTasB9LXBvHyPe/95iu82w2PavVijffeJOu6019QpgVEEqSjcyYUIs5qRru7TIuByX2qxnHa/DYepwWQy7fG4YyDAOPHz9GUe699hohBL7w+c+SUuLlyytUoVsZEWQ77IkpsupWBB+MUFHbXPCvJhicS3GHLtCvekLwzU1q2ngHhlwO67Jy8K1hVfE8w7C2ceByuEHUyklnUMsIOtHuRwg+tzfhHIaZZraGDx3n9+6hXnh+9cxwqJxcVGInFUbMGGsIRmJZnQR8EKbBMGvViJLoXEcfPDfjyDhYqQjnIaXIfgd971lvOkp59BB6upAQHbi5eYmkE+6t1mg+/83LS77xG/+Im5sr0lvnuAee3/uNf8K43fMX/vpf5+GbJ2WAU0gBmmLG1zJhR1MmPZRoi1Y8kKQV/0VKoiCVkOEzYUecI6bI1YuXJIVpahgwzPhs5ZtIKZnjKrEjajKl8XJuhCqFolamRZLm4XD7ma9PRwFmy5iZgwzN+KJiyIv+aWwO+7eRtYM5pxIU7ki+lpmA0DAdDo5n7Vgm/c7XsYS/2+fIfoqCtbb3qbbTwOnbiW93YMhCva+lTNSM6bZnb+brO6b1Gttqng+weJxoLp3SQu2Se05zcCHj/845nHPEsk8ZL0XxBds8OId0ptRRUqid+IyhN63SJo4REykZfqxKnQJLAu7dfXS0ox3taD+6fWKihzaTdpmJ5hdUiTT+KE7ygbz9K3d9hW6I3t5G82/za1Dyf+1flRJMLC/8JnDZ+Pxa95bFy9HeA5kZTQ5eJ6jMU9VaR3BKFjSdxomYEloIHyKEvkM0GidZI5oi0z6yu9zxwYcj33hnz9v39tx/rTg69vpw2EvQ+444Jd57/CFd53jxwvPw4UO+8qWfQpxHfCDg8bneX/Fsmld0fWHai2fKZS/sRTg7kOaMi/ywrKvioFsJmHEYePz4HSLw4EtfxK83fPmtz+BFGNUzxkS/WqEoN8OO692OLqzwYuU85CBgqu0CI7OxuxBYrXu6Lhy0ox2gzQCT4nbkkiXNy3o5FmxbRdjFiatxx4nzrJwnlvGTsLItWLmLohTgxJzlEnT2IXB+7x4nl89n5ZH8Ym8lAxXQaOsh7wOh6+jXHauNJ+5AJyt74r1J+vWhA4VxnPDeEYIjaWK/nzg9Daw3AR86ukzUCJLQuOfm+iW71TqXxbGAeUTZ6cTl7oZvff8Pee/Dx9zECbpgY6mMH+rDY056asaVZgJFmznQkj1y34qYgkf53e5ldtJFiDFy+eIyO+kR55cTTXX+yxi2FRc4c3CTxszKzQu81Jb1yWPbtqShYjTjBlOyaaWLlHzv5gVIPjvFg5XFN7O/XiQl27rQ5btUZ6sySymLAbnw7bVZN+idc/DcL+0MyLxAX3w2O8ySj1lrBx7ME4sjL+b427BISY5Y2uHCpW3v8gVQnO+yCKvtym1LSavTbd0lOLQ66W0ZHuckO+nYorksDPN7p1xV8OBwVmsx3zTvPLmg1K3XWq23mH9UFfGukpduL5aOdrSj/Xk0kyKeII2gYkoez74H+5efdtOOdrSjHe1oR/uzZbbIpvjgw074/W884MF6x6//+ve4f3/P3/t7n/9023i0o/25tJJdz0HQ8TYOs7QD/KI5Xo2gLsgcDV7VYEfzd3edSxfftsc5LDrQolAV24JczgRmCdiC20izPdSEqAbzqMctOAwzhpaiJbpM42SJg2JJJTMeZnNeipaEcn0d+ehy4mI1sT6ZE1VKOwUQ59CkXF3d4B3sdo7NZsOD+w8NuMr4SSnPcRDtZYEhA5pLbZfg6iIUrYLUvilfHva9ND8QY+Tq8iUJ2Ny/jwuB++dnlmqojqgJH6yk9xgt6cY7j5PcZre8vyXRqjSu4EMh+Jp5X78sIJi2V8KMm+kc5F4gWIsuslEzpcSQJjpxBJEZC9T5NM7NY0zavsTIIf16RTf0DV6sFZdsIe+ZO2AJcD44QufQScE5nERUFOdNGRtMIbooLasqU0x02H7OeZwLRmrBcN9x3DN6zzSNBOfBOYb9jg+++z22w5b+Fz+PrJRnH3zE7sUl035oMMjmwlWp6s+1lwv4p/NmlIS4ecxIk8BqqgpU4FGTst/vLVaTmthFiyHL/NzW7+qAzc9enj+0+ak32ZW5or37zXg7JJYVSLrtg4N9DkuT1PTTEqc4aC6Lre+Yu1QNkK2lX/Rw5+XfBx/MR5SD+zdvJrrcQ7m92fIcB/3enqPZ9HZcsMVUPw5bVVTbclulT+e5uv2Zt2ow+Gb7EqNISlX7kPbQ2ZwrKjAzdl1UystrqP6nxpB0QYyp2vsl1iAHJzna0Y52tD+ifWKix8lqDTRZ3s1EVryMMmUfTsuNm7s45qHrPPssBwHGuuVccmTea3a7U5VBKgFdC+yVBPApRaJqZcxaILphDuasdovkJ8R5vM/kg+wwxHydpQ5cihOoZZWLZvInSpQsXJcZq94FnHd88UuP+Jw74eblC/Y3Nwz7gXEYODtZIxEenHq+9rk1F/1I16/MoW+cFRGPCytef+0hv/qrv8T19TW/+Y//KS+efsCLF3+Hzekpb33pS5xfnPFLX32b85M1qt5ePtrj1Vv/5Je3Q0kWpczXNYMkzhkzMef9M3tEh78rpXpdVIe4nvsXj9jtd7zzB9/i/c7x7mk0FY3wgPX63O6aCzy/3PHRixd893vvkKaRr3/lK3z2M58h+IB33pxBXH2Bdk446RwPzno+//o5Dy/WB6owQpHwWzJfs/smRpbogjGyXXnNiwPJbnhKOJ04846HfUepP+nE5b4yZRsloXG0cioxMgwDmkZSHBjHARE4v7jg9OQUnWysdatVvo+ZOJRZx6uNw3lHWCsSIrvrgWlwaIy4kDi5t2GDSejt0kTXCfdOO1Luc2OfelQCkwamMTFM16A7NN2wWm1Il3uG/oYnNx8xDgPf+fb3uNnuePrsJc+eP+Of/8Y/5dmzp1w/uSG4wOv/1hucrE8yeWUiasw/ilOI0X7E57qDuTaIPYuaay+66jBp9gTL4leTZkIHeG+SgTe7G1KCJNCpLUYl+6y+kBLy+FN1TClBnHh+uefqaotOCSKmZKHCagXrtZ1bqixlZmBkR9iVBV1hI8fMBM+LRjJBpJTEXM5YRdFDZuHIsngpC8JmDrOROC/kCjhQvq1LQZ3nrToTLpzFPA/n/imAhKaySNDySTOnShGxWbTRq9Z8BWO4B5CJlIb8WW5SXQvMjnNzUabS4nwmPpUZYjnLz070gUNf+6BqPRmxY1TUKUlAfSGiaZ6b5jbjPeKcKXxIZt431zZpXuCJI+FhjLAf0GFPjCNpHBtSkuCcx/se54KBF0X9R2EEI5DkOUUbJo+I4INfXPfRjna0P3/WyQe8sfp/sr/e8Pw790m70cgeRzva0Y52tKMd7cdruxfwzj+HaW9/xwGGa65jx//4P36Vrot8+OHJp9vGox3tz6F1weDmGUOGVimhYEeHdpgQ0toyproIT85ReWg3uuM4Tci0YEAUHEVm/IWMa6EZKyr/NsdIuQRGJpyZWoCb8XJmBKsGslOjtqG5rDM52CwWZNSUapLb/ftnvPHmA8b93hSEp0SME6suQIJN73h00bHyyZQ/nJUvmTvNMJ7Tkw2f/exnGIaBd995zH57zTf23yZ0Pef379Ovej7z8JxVF9Cqigwzvjr3k+YOt76YtbUtuUap6U41XpD/XdwWS9tJWU16vTphihMvnzzjyguXXVbFcGtCWNldEcduH7nZ7Xj+/CWqkdcePOT87DSrbsyJaiqGifmM4W56z8VJz2Z1EAZpEr3k1jix6/YuK0lQFGINU5/j0opoonfCxvt6zaYcIRUYVCxoYArgKSuC5zLcMYIIq9WavttW/qL3gSaabUrTCD4YwcUFwCWmgTkZySndOhAIiHNMmvBOWHc+o46zWgE4kjpSVEiDkQV0xIcO3UdePvuAd/7+PyasVzz46a8yTRH/9hv4/Y7nT16y2+959NWvoVOkPz+fnzCdr9PUFciEDHC+JNYqRYWlVfEwzPwODFk1q2HnEj0kxinVBEpTUclDRZaa5AWhTGoJZNv9xDBMWUEESmawDxBCnlfqc9zEvtr/LsHa+k2GbfPz0WKieZzlY+XLr7u/ugzMPE8VUaP5quaTtRBt+UXLQZvwiLQn1Xnuu2tGnuMt83dOD9qQVXwOSRWHVpMH6z2SrGphcTO79XOs6dVHKtde/iv1+JoF3hXm142UuWm+l5JV1gUWGHa+EiPeFRwYsYl6iugULXm2xg4z4i4OJ76qt9d2qRKlHYe6uEGGwR8R5KMd7Wg/HvvERI/OBxRhmhoXr6W0CizoquW/0vzVMBpl/oKazc4cGLSvkgU86ymW07zmCFstJlICdZkmrXkij2pB2jFGpmQTs8aYs8RTfRnFyVjTWbLB5N3CygKI3oNmoofCpHb+GAdENWtZgKq9SZIzh653pvTgveBD4OLRBd3pfV4+Ea5fOnY3O/a7wKoPiConK8/rq0BvvFpACCG/cAXEeZxfcX5xj5/5mZ/iow+f8g/+7m/y4uUl777/nH6z4UXyPHr0gC9/5oI+KM71iPOEFEhIdn7yXVSdpai0vEpzoFgVJOWFmVLKtLSLlqUjYE46zrNZn5Ci8vyjJ8Q08FH3gtA5Xv/M1/Ghy1s7tvuJy+sdH7z3LjfXL3j94T0ePrAyLq4E5UmZ7GLB3c7DZhW4f7bidNUtzl9/a1j0MBOAoCkx0TprC4anvbB7J5yEwBCVKR/TZZk3CmM8RWPcT5E4RcgKLSlGQFmv1/S9lZchgQ8+v/SNIKTR2hC6zKIOivjEOETilAje5Pz6VYeEQBoj4xRxDta9Z0yCxsK+tvsTVcypjiMpjUzjju32mrQfmfYDV/tLrq+v+db3v8Xlyyvee+cJL54/550/+AGXL1+wvdzTdyvGYURFbOGRTAWkZCGUn6Q0Kgblu0YerbpLwmLJnvs75QVs2WcYJnPcQ8C5KgrXHEWbsSqklJgS7HYTl1cDaUjomEiZ6HFxEViterS51/PiIdd5zKepvF49rC9a/mnmMGlhgHneKiPIlunzc1Z6aFmMKPdZ0zf1qcorFW2l92q3aa0XUxY+7eM4rw20+peFDFK6QTMpR/ISfsEgz4SYpYMuzTPU/NtsIpXU0zrnn8RmR7cseMCm4TQp+DyeGqzgMKOidY5tjGSVHTQTebR+Cs7AlXFCpxGNIynFhVJIkfecyUHzgj5R3kmZutLOHRmMuVWS7Gg/IbPnPkbJTPtPuz1H+/NqwV1x5v4lQVe8ePom7D+xu320ox3taEc72tE+iZW1ybiFp9+C4Xrx9RA9v/M7r1HWRM7ZGvGTr1H+ZJmpyUu+hqMd7U++lSzn1GAtQAt6NFs3GPKtgOMB5pKT7+bYZbt9QV20bmt4iGTYrz3PnGFdkFDJWHXK2FYJVJcyzuWzum9KJMv2g4wBOR8y1lRKmtixK6EjxTkpSJVCqtAMdPgcEffO4YNnc7Lm4uKE/RaGPVnpw+G9IRSdF068w5OVSVMOeC8wHk+/WvHo0UNubrZ8/7vvstsPXF7t8F3HXoXNZs2DsxVW5dpnnC6TPNppp8BP+RTzbczYXcWw5pLaH4ePqBq4E0KHqrK72ZI0cuN3OCecnr2GuKL6LEwxMYwT11eXjOOO082azXpFCKHBgefEv5zXSPDCehXoXlFyd9HGZlyUY915CZpvZN7O5+TEmJPXpDSg9BcKWcEjpUL6SbVcCSghBHyOP6CYooVkyoLO+KHzhu2LU8RBjHZMJ5rVok2BQ5OpOYuolRtX6/NK9CjKI2oqHqqQ4sQ0DmiMbF9e8t3f+R260w3p0QXS98i9c/yu4+bd5wz7HSevvYZ3Ht919nykGcutjy0Fx12OlxJvWPIDGmy/nQvUiBql1IqixMlwapy3GEYzi5T953MXMkJimhLDEK00TipYtrBee7ouzAoq7RHvCoOUYXBrfuPglyVoW4hC86f5L13Mls1v7SdtYmv5Tup3y8bBgkGit7awo+WxXPBiI4M055DFP8vrLUSm/NzcThZs2t9edD7frSn/lrU75b/zR9KSoBSbq13zO3Mc4VCVZ5mA2Gyr7V3JGLKqJYVqglQIWnPnzM/T8trKDFLfOQ3+XcaUcwd9fbSjHe1of0T7xMjzMBUnzRw9Nf0rytxfZfMz7bS8wMtkllIiaZpfvMUpViXGxtnWfIyWCZh/T/lvl0+qLoco83zoisNdyRt2uEmV2BzXo7atZIfJOcQ5QhfwoceJ1d0yCSZvMnbeZfap7ee9TfTjOGLTdrLe8aYAUeZt52xK70JP8B1f+uIXefjGZ/lX/+J/49mTD0ky4XoL7iOJz739Og+/+DZP3vsuj7/zHEmKd+ZwRKANoRphweP8hpi2PPnoPcSByp4PT08Y3/8uZ2dn3Hvz82zOzvi5L32Ghxcn9P0G70N25loXGOpSKb+IVSNIG/gOzXZlPCRMRsFKZ0gCkYBIIIQOSc4WHBM8++Alw40y7LeITGxWgdNVz9P3P+Sd73+X6Sbyu9/4Dr/yCz/HT3/lSzhXOBU21p5fXfPh02e8vHzBzTRyGidijHiXHeRbzo7SVJGrTtMcup1D9WXfmEypwjtH7wPXV1dcXu+4ON1wfn7CZmOLCOcD6nweZxNKLjNRnBugd4nOK75zyCiMuwkchE7yeLKQ8TSUQLNHHPQnQnDCNERUI24s4JQ5ocMAwyTEUYnTROgTfuUhDcS9t7EeR3AO3wXCesKdveRyHPinv/mE3XbHe+++y/Zmx7NnT3j58pKr7Y7tfkTcZHUeNSIxO/owy0eGhAOs4mMiaUCiz4sCZRxGbm6uGfb7+tzPruTsKSdy8L6qWgjBOaLMhConCS953iiOOUaiSsDTj24Y9iPXN3viPuFF8J0n9J6uc6zWgdAHfHAzqfZgeMw+VpmH8jOgKbPvbdFdiAaWhaFVyUOdbRNzeZFS9CPlupMJMums9EK7UAGRxu2r82beuhCy6uKwZA00z6lIfV6rqlH2L1Xm8V3XlaXdKOIF1wsuZPlG55DQITFRyPBlwdv+N8+09TJEBBc8vgvIfiru60Fnz46+zAehePWVJCJgSjCmwJOr8xhhzokRmcruaoH9qgIi9iM+K+QExXurYauitkh2wqSJQUcrx+SyGlHOKCntFTXlp3Gy95R3jiDQEQnOiHuSkp1LBJ9VgnzJ4DjaT9ymSfh7f+9zfOMbD/m3/q13+fKXX3zaTTra0Y52tKMd7WhHO9ofh22fw3f+HmzjrOZxh63XkV/7te9z796ev//3P8fjx2c/uTb+GO23f/s1/sW/eIN33z07CIgd7Wh/Mi2mFgNqA+dmcxx0iS5U1ETbJBwqLmzQrt4+hi5xlhaTmBNfMpZQ4JUWc677GVaVSnSYnBxTI5iGKYg4xHsLtGNYhZ3FmYisuCaZbi6XYcQQzTirkSrs1AUXAe0SX/3Lv8rnfv7n+NLPfZ3XXn+dD95/j+3NTcZxNIt2KBcXp2zun3Nz9YKrZ7t8mZGSNNnksRtuIw6RDk0TN9tL2Bmeed13pOsX9H3P6uweXd/z+v1TNqsO77sMzM5YzKEtlbdTgx8dlkoRuyFalE1K4NsS15xzoIKwgQTb6z1xgDhNCIngHV3wbK9vePniOWlQPvzoOW+98TqPHt5vgrmCimO3H7jebtkPe8YU6XVW98aXAHIT0W/UihfXV3Gnch1NcD1fTkkqHIeR/TCx6gOrvqPrQk4aNMVu04nJBZ3LWM0Ysi8YmMc4IJOVInZeamIdqGFcmgCPJFh1dv4UI0QlRSrpRlWJUYjJlJVTTIYBegGN6FQi46Yq4rzDhYR0e4Z0xeN3H9OfnnH/8hK/WrPbbdnv9wzTxBgTIok0jnzrH/4TAsLnfvnnOXvtgSXXxkRybQJcUdBw1n6FGBPjOBCnqT73bRC93BvNEhiJrPicSU1Jpc4NJeFrxntnbE6B7c3Iy+c7xnEiRXu2XY75eC+89TNf5fM//9M8+tzbdxOU2nHREBTKsK6bzRecf29bIrUftH6e2y8zJix3naxMQ/XEc5PmxN2W0SDL/Rf4biauacGsW7z4UGViLjMinlyCPePFzmcMtyVOLH8v19x+Kc5ZKexYUumaDl1gyE1bGgw5g+UNLr6M7th8N89GFYIuHV3iC3nbUhrISXnXzKrYSZVIqvh+iQLW8mRNgCFm4papyGMxyHy9TkuytSDersu5do482tGOdrQ/un1iosc4Fem4xgFifklXhyOTKRJlQs5qGSkxpUwE0KwOECdigmlqHJzKItUiF2COhypTjte7Mm37bhEANf2LQipRC7xidfIiNrl6oBMIDsR7nBdz2Lx1hcuSbH1ognUC4ktNO3sBrHoL8I9jyI6WOUQhrMxBrRO9OWXBGenh9ddf47Ofe5tv/v7vEeMIknABxNu2Dx+e89M//QW+pZc8/q5HXDRnrS6MyktZcvDTIdKj6ri6fElMA6I3vOh6Lj94wmpzyps/k7j38CFvP1xxttJcFsXIKEZ2LC+VLM8n80s0kRA1EsXMSC9B5kYHi7yNktmPDsRlNruD1KNJuX65JY2JOA4IiT54Vn3H9YuXfPDOe9xsE99550PeeuMNvvLFz9FhTI+yVLjZ7fng6Ut2uxv2U2SIkVhLLrQLydL/7c/87ZwNcHusl6HnxBGcYxpGtlc33DtZs9msWPUdwWcFjcKsLs5Y8yxYyZ6E94oLDnHCuB8pLP+iamMsZK2ECLHSk3iBIUamacJNLjvp5twPI4zRkaaJNEa8LwskR5pG0ITECAFcDxIisr5hu93y3W/eMOxGdtuX7Pd7rq5ecn19xX4/MEyRtUS8t/suOTvBsoeUGKORWchEDUw6b3auE1OcGPZ7xnGcFXPKPRCpi2grdaQ4NzvxzgmaYEpkx8h+ciPyLctBfRWuL/dcX26JmU3bdUIIns3aszoJRlgJvj6/800GSfPxZjZy+azcTOr4K1DBomRJ7vNCAqtkNGnmRmF2iA/G2nLJMTuZh9+KlO8XLq4BDIvLKjKS5fcfQjhwYmMzz+viJIMVrVRn9Z+b52Xuk7KB89bX7SkXj9cdz9pMf2lXA9QFQ+t6VxUPnQ+mlWU+k7ZUiiKH4J0SnDKlTPQQ+z6SGDXm8zmSuNlJl1luNKVU5xfvBC/gmaU7yUoi3jtWq64BTo5Ej0/DUnJ84xuP+OY3H/CVrzw/Ej2OdrSjHe1oRzva0f6s2ngNH3wDxruzs4t1XeQXf/FD3nrrit/6rdf+xBI9bD1JXfMc2g9+cM5v/Mbb3F5RHu1ofzLNkuSqGCml5kBV1ajxvBLkY8YYlJpEJRULKkl9M4mk4DazsjPztjqX362oifgZ18hBOGEmkKRkCWZJZ5Si6LyasEJW6lBXMRMLDLpK9KjPaKvCKhBq8mDMTbUH3jlfsUFyQBiBN3/qqzjneOOtz3J+cc6zJx+RNFa8hIyTbTY9jx7dw+nA1XOpuNMcLi3YZy3oC2IlPIb9nqQR0ZGd9wzXN/iu5+yRst5sON94+mCBSCFUjGvOVS8Ycr0bhkdltFBKGlR7HyT3qMz3bC6pMAdDUW+JZLsJjblsOobLBO8ZdnuuL68YJ6W7vOb89JQH9y/sPghk3QfGaeJ6u2eaRmKy2ERRhaiNK9H1gj3Oo2u+o0vgbdHJBTo0nN7IFtMwsu4CXefx3s040RxNnw9XsUVyspPmMkBCjJZ0K5Vok/s5lRgMBlKpDbmYctJZlHpZFnzGMNuiJJLEQGcVNJkidQ4Q2P10inQjY9ry7OlzVkNkt90RRBiGPcMwEKdITEogoWnigz/4Jrrd89qXv8jZo4c1YbcStMp/6+03NeSUrIyNlbIp2HF7b2YMtqpZaB0yFpFoIGdZ3MfyWy7FPET22zE/45YM5pwjBEfohEdvf4Yv/Movslqtm5u/HBaV1FGfw/LVjCGXG1tIHotj5DFQE6bb02gZHi1SejAWGwhVF3vLcrvFnvlTaY+h8/Wgluh4yFg52L2OxXrKfExpz3hAzJCmnc2xJT/vNNsucOY7AGXh8Jrb652TIGtCpWAq3vWYM4Zsn9qgKYmHjky0qvfBjptQYpWZlkr2WDYlx3XKvCZS0wldmRuYCTLB+3w/Pl716GhHO9rRPql9YqLHkw/fxZQsNijCbphImuiCN2ZanjOL89LmrquaokbUJmCXEpKiOdNlonUuvxidqWp4qZNe21iTbWsDg7aFd5kVl18iMaZcUxFUlOAs4zo4m2CtbdTSLGVtYAzhkNVGor34S6BYUnbiu3khgGYFC8G7MDuJTduMyecscO0S3XrD6uy+qS6kCVXP9W5kUqVfOZxXUpqYpok4DUUzA0mRlBLDtCPloLv4Fc6v6VcrhiFxebnnWgaurkZC6Lje7zk5PSV++E0e3jvnCz/109x7+IhH9y443axZ9Sv60OWXjasLi7LUKsQHEQWJ2XktgIoFRK11MS+UALXFD1hm/fm9+4g4nj3/kNAFO2ZUztZr4nlks17ju47h+iXT9prLJ0+5fH7N5lRZb4Sg9mI83fS89cYDvvXtJ/zu7/4+l5+95sHFAy7OLjjZbCi14eZ2QfF6bZRZKZqaXEBh0qp5yiK5pE/OHhC4ON/Q9Y4xDHz/5n2e7q4YBmUYE/txIk4T4zARp5ilG42ckVIiOE8QQdNkBKZkT0acksnpBRuzXhyiwn43gowM3QpJnmlyxOitxAlzzU8vVh7IB6uf6ZwBQ9ME+yERvND3va068Vy+uOZf/rPfQXRFvDplGpWrq4HdbsdHHzzh+tpKu4QE9x8+4Ox0g2piP+wQH2ZWvJIJIJMRp0TwmfFafKfNque1B+fsbq7ICpdFp5K81l9w+rU8iIgx3RMMWRWiPKSJaIoL4kCK85Q4vehZrV1djAQxQlfKDlRUgZgVHcqwzk53Fuep1UdrJkEdGWYpX1hZQzUTT1lF2P6iZO2auhZpKC7MK+7bbqkTa0/Kzrbk7RYgSOM814VmWbU1o7l66uViilJG62CXi9HsVOLynGi1TMvTUlRFWjb3bZffPnEh4EJnz6CUU8vyQtveWK5T62d26Yoj0buIF+hRgqa5PFdZWDTHrlyvTLxTTcTkUBGmOFEyJsQ5YrIyZKaIZPO/c65hpedHRxNxsjl3vodN3+TjibN6jGX/w0XH0Y52tKMd7WhHO9rRjna0o91lKTn+8T9+i+9974Jf+ZX3j2Tlo/2ZsJubSwCc61Cs5IZqyqSBVhtBFhBqwSuKLm/B8ihJg/MnUJLPcikKhywq8JZ465ykVkzq9zMJhIoDqh0yB+cMz22D5oWQMMd1LVhc1F8XgU/RirkY3FpK7OYURnEHGHLBRQq+bUFLFwKh30CKhl3iGCbLMPfeSnhoxkxSxtqtvSlj8hOlHLOIR1zA+wBR2e8jIpFhn3B+yzhFur4j3Txjs+q59/AR65MTNqsVfWelRbzzNSFpgSHrfH+qukfOYJ+3SXbvJM3IiUoNwooI/WqNiLDd3eSMdwvU9yGgvdKFgDhPHPakcWR/s2XYjYTOFJSdWCmdrvOcn2549vyGDz98wv58YL3asOpXdF13EKDWen/tDiRKMtZSYaItD17KgcwkhFXf4bwQXeTFeM12GojRklGtxEoypYus2GwJdGlWARDsXul8nhS1CJLbeM8jd5oiRIguQC7vpepy+Y1Y+zPvlgPrUjHLFGGKaolSvrI8GPYD7z/+kCcfPmUc9vhxzTBEkp+4vr5hHAY0JpzCer1BvWUsTpmQcwtA1ETp1TaJS4EueE7WPdOwr3GZAh7PJKHZCk6JmMq5KEYSmZkCGYvNqt+S740TvvwXf4FHn3uTx9/4A56/+3gme8mcYKq5Qkcb14F5mN8J+bWXXNtwaHVCWuwj5bMGc85PVoZ2DzpTWsy5OWRDeNP2PLeau2xgLSKT8egyPm5dYPMMzP/Lj245S1FgPgTW77AS3ygbzfB6c+PrvXYHOPjy8PlJxOckZa/5VZBjMHNQo90htzcnrIOV6lYVokniUBpWyLguJxZKTfCTeugyvZXnep5L5u4txzPseN7/aEc72tF+HPaJiR7Pn31oWdLhnITjxc2WGBMnfUfnfX45Ct6H7ISZ81rqMUZlZq45waWIV3O8yMoI4qkzuxOH93nidL4GDMWi49aoFGv7RKzUhoiRMkSEabJyGIUt573He1+d8CkzRsvfKTtd3jt855GkVi6lOkNGeBVxeBfMCfDmKDtXnCe/ZOLlBYVTzSQYEEmEvqfbnOGmPUx7FMfNPpNnuhK4j8Q0McZpdtLFXjjjtCdm5RNxHS70dF1PjCNXl9fG+k1XiMDN5VP6LvD88QNOTk/5pcnxmc/v0M8l4KLKyxlRpjhTSmEzz9JqCjLhnQd8DkIXMkWklK8RxNjBauQF5z1n5/fx3nOzu8LlUjQpKSerFZqU1WqFD4Hh+oo0DNy8eMnN5c4WM+vOyvVoZL0OvOYv+OYfTnznO99DEL7y5S/ZokpL6ZY2vG5Oqt2StHCoqnqCMi941K49lctCOT1dsTkJvLt9yvvb57wcbpgmGCdlnCJxikxTstqAqnkcTWhKeGfMbVLKRA9AslSeCr4zCUefy/2kYSCpMu6DOe1RSMkjREQSXprxXBaXwaOS0JSYohFQxAUkhOyQCNeXW/7wG99hFU55dPo2KTp2NyPXNwMvnr3k5uaaNIx4Ec7Ozjk/P0U1MQ57urVbSolpAo3mRMmcBVE0HtZ9x4OLE5581GdRnkIWqA9F7duyYrJxDCF4u03DNHutCkkTiVTXfsVp35x0uLMu16cElxISE9dDYjtoHZ4pUWv1Fb+wrstY+L8zib/x0pfbZyggL8ir7KfMkphAJkwsHfWyyKgSoc321V9VqAx0nUczmslsCwe1URih/fgO57zI2GkpZmTElCKxVw8gZSHU+s+FTV6en8O6kZgSSPBZZUQ4OCif3OzMDqVD8WIZAk5tjBtxr7Qzz1EVV9A6niARs9rKFNt3hRgpKmLvCm8AgbjZ2S5YC2gmesxgj5T5pFy8m8t/uYWHf7SjHe1oRzva0Y52tKMd7dM21R++zadpKQm//duv87u/+4g337w+Ej2O9mfCdtvrHNBaoQj7YSQlpQs+Y4+ASi5pkRfYNb4nlehRgqCiKaNmecEtgkjB+DIeW9bjrsU4hJkQ0mAn0mA4WS2hlMIt+5a2lZ8SjDc4ogT/tJZ+UDV5f/L3FMiiEkGsvHeJ/9VQac14oZ68Fk8QQDQrqPa4NEGKKMIYMznAl8C9JUWllBbZ6IZTThb0VEA84jzOe5JGhv1oKg8MAIz7Ld45dpcbuq7nM0k4vTfx8OIcWLHCAp5Fb5sSZC4B8UVQOOUgrTTkCJrA/xwgLYFicUb0cOIYp2HG8NQIHij4YMk6cRzQaWLc7xn3k+EynUPUiCQhOE5OVjx9qjx//gIBtg/u2/0pQJIeBKa1SeBp481N8+fr0HI59fOu9wQcl+OW63HHPo6kZGMlpoxrlWBwxvSsrLdhdDUBc5YKMYwrWQkXcdbzClURPUZLtExZBVrUMNOK5YoYri5khpMdP6mpgFR1hXzJw37k6UfPefHsJeMw0E0j05hIPrK/2TNOAxojDqFfrcB7w7SzKscCEsvXIuQSFrX/rO+Cd2xWHdsQCkTcdm0ZIfNNkAbtzzWnJTb3Jqt1KFpz4ArR4+2vf43P/syXmbaX7J9/lMvPK0NUxjgnujZdvzCFmkRXNlgKYMg8VuowqaBxO3LyGJy/1lZhuh7+EHmdsc/6TJXnrz1lbkQlWTXftj6RtNt/DJBZtinz8XJTaa5h2dwGuj64Eq2lW0yKZo7V3LKPw1ebE9j4KqoclaK1xLZvqZXMuDsoSS3Gkcrzl6fnQvSQIFVtp75aInU7KMpTLYZ8cG2V6dTcmyOGfLSjHe3HYJ+Y6LGdTLGiy/XqQrfG98LJ2SldCMTdDp0muq63DGlngVeLmLlcyqUwNy2gXlmDZHk2X2TdFOccfWfNqyoAJbjnzIHQaK+JyvDMQVzvPVYPUTAFDhZED1OkcBSRDucc3jliVJSIcw6XC+LZsaTK8JWSHqWtUzJSi8sqI1XRJDfKFSmmZOzSb3zrKX/4nufb39nz5FmP7q7R/Q03G2W73vGd773L2e+9xvvvPa0MUiNfWD2/snjpvLcXl2D10LKT7oOnX/VMU2S/3WcPxV4e4zgyDiNvPXrI177wOYTIsxfP+cG7HzDsJ95+6w3eeP0hnQ9WuqZdZBR5PTWSgjLm+5bVAJygGvPiIdq9iTK/2LwiHiPRZEfMnFqTKnx08YjPv/45nsh7XF+9sNIomhjHkZvtlm0ckTTSr05Zbe7xhc99jn/33/nf8+D+Ax7ee42zk9McHJ/JHkv3qBnu4hpFgBz8tquoC706qJyRVbx4zsMpuoIfyAekcSJNEzGa6sowTJahIOYgpGgO0Hrt6VdZ1jEz1iETD1SZsEVhOA1GFhoEJhiyYs44JFJUQm9lkxRwXpliIsbEKvSsfM8UB6Y44NQRnIcI++uRBIwOgg9sIkjfkdbG/g99TxhGpgniBL7r8d6xWa/ZrNe4EIxklVfbJpeYiHEiRpfHeJYsa9Y/3WrNycV9utVHlRibaB19WdwZxZwolxeoxveSTKhymZzlcVh5Dakue1bASND3ga73EE3JwcURmDKJycbp7Ji2qwapznQZNUUG1NWsj/x966BTFuU0TqHMZVqKQ5iPWhYrtihoCRgt2WgGFGxbqYtPJdn4lpn0MfdecUxL8wo6ovPkWWCCxgm2o2q9LufKPN3Igd7lZC/MNioEO+c9hfpT+632fFHOmdtw6wRCXWDbPGdtLnUzfTAgIeCsnmhGBQzgKSXACqO6EDY0k/4SmmwxFLynC4G+7whdYLUOrDeBk/Up8mBDSpEUI9J1hM7jg8MFR/COlbeskNL6/AabnXV/uJA62tGOdrSjHe1oRzva0Y72adh+H/gH/+BznJ0NfPDByafdnKMd7c+NjTEn4uUIn/MBCULX93iXSw6nZKVLnKvL6QJGFMKH/X/GbAADDbJSM+Qgbk5gs78rVFDX6QpFrnURb7N/CzHE5XIxZTfDSewSDO9NWaHC5QQScakSQdpjSW2boVgFa6wJkDSBvjZoXMs+2EdPnm55euV4/jyy3Xl0HCCO9J2yDhPPX1zSf3TC1dX2IIBbOlQynm7loGW+uFy2QvDBk5IQxxwtzxhyjBHnImcnGx7eu0BQdvsdLy+viTFxcXbK6ekmJ2rmi6hQUI6AZ+w3lSwskdofs2qFGn6f5qCnYd06E3ga+EhEOFmdcO/0gpubK0Z2dn1YCRBGYcrKJ953hH7NvYsLvvyFL7Beb9isTui7vrZvBr/KTSi92JQrr0k9BU+c7/HiholUzG/lOgjKSwkW/M2qNlaqJNVSQUAlioTO+rJk+9fy0gXiw+6h67O6QDQMLGbST1EzNgg6j0lHLXEfnMeLEXxSinVcozCNWXVdcilzxZSrm/iGc64qN4vzOCd0IeC7ji/+yi+hY+T04f0ZqlRTmtEkzfhc4mXOB7rVGhdu6j1uUwXb7cuzXVPRCobfELKkqgYZwNgqzpe+dM5Z6QxV1GX1k4zjV8JYPd8St9QyDPI2qRmX8xbNCe+4khZDnm8w82Mj7cdieHBRy8jYcQtRz6eSxf71XLW9d4G8zfhPBxd31zlqmwTEoTUB+PaurzpXS6ATvX2uxUlrh3/MIbH+9+WxyR/b/GHEqFpypj7H87jIT0qeH2eFnTk0ZMno3psqtA+O0Dm60MO6y2NckaIW7Zv51VksbNnc+oa6VZL9aEc72tH+qPYjED2MZKCiNkn1K1wIrO/dp+869s+fE/d7Qt8RQsCHrMjhfS61UmOfzUtyrmllk2ZmGseEOKHrO8vGnszZDHVCDtX5UE1N3cXs8DiPc94+d7PUnnNZXi63ojg+Ill1IUv7uywfZUoLtrVvnG0nNqmj4JIFvGcSRlujcGaAQyJp4g+++5ynNxM3Vzv220C8iqTtlt3JwP7kmvU77+H/4AHDi+fVR559TI8XKz0TXGFOC/mtkV82PsvPObY3g9XFzEeYhokpjLz58AFfe/ttvvPu93ny4iXf+e57fPjhCxKR04s1J/2K4Prs69qL2xwka0bKDGTE6pY55xH1qE41QEoCLU46ag6615nogTn7RR3l0flD3n70WabtljjuCc4jwDQMTC4y7a6I+0sePHiL8/PX+Nxbn+Xi9AQRj5Oe9aprXtSzk7Fw1rFjGunCXvCtDyKVUUl1smwBYoHr83DKisBGetIUidNESkb2GMdoRI/Sghxg71eOvs+yXrh5oRPNoZ8SuADSCS5Y6QhUGYfIFCPjLpImZaUdrLytZ1VNjSZFNqsV603PfjcRx4gHgvNoTAzbiRFl5xJdiEhyeB2JMeGcEvoe3wViJnq4rqfrPJvVms1qjfMBLexvJTsuiRRjViyZe686mCKEfsWJD3SrzezYVwJOs31xz7O6i0h+xl3pd8mOVK5niTOCWGHM53+TGpFl1XXEYP0iuwRMeWGesxsyyaOtg1jKeVhrXOZGNA52Hgtl/VddMmkcsYWW4FxncfHslrNpyXlov9XlIZBaBqdN7FiM6bLKK45pvYgiWaLzh+3Oc22l+pUCmhf59rw3C9jF2kqav9tW2bWIzwQ4WV4b3O6HhUpKc8h6RLGFaShMaYyZHYIjAk7dPLcKlPqLM41nzugRUaZxsoVvsjdOcJ4+dHRdoFsF+pWRPU7Xa05WnpfXe14URaHgcraIJwRY9Y5QiB4FFGgZ2e7j64Qf7WhHO9rRjna0ox3taEf7ydgweP7RP3or/3WE0o92tJ+UTcmwiSA5zyqrP4fVGu8dcQuJqQaPXQ6KUSXxl3hd/UsLBjAnspRyKb6oCmRCh4OME/p6hKXaRFnGSyZopFrywz6fFT2KleQ+QXBOQVsJ//wZWkkoiRx0LkF3LahPKXlbopSlPQVPsWTBJy92bMfEOExMo0MHRaeRqYvEbiRcXiJP1sT9rh6m4F+IqW87mUkx+SKogXHn8M5wkonYBOO1loE522x4eH7O88uXbPd7nj+/4vpmh775Gt3K0/lguHDp9Xpj8j9VddUgqxkzysHUlFgCRIqVNJ7xvHKfC0a76Tecb85I44jGycYOpiiRxkSaRjTuWa/PWa1PuTg/Z9V3eX9vQf4Cui2QqbYhGYc8CPwXrL4MoDpaMyZYCEu96/E4At7ILpnYkjQR89+LcYnivWTSTPmpnZjHdob9XAlcC6glCKakpMlwL995K/mtguTy5EkT4gOh86ZI3RIbkhr5BGUS8tiWiqOpkpN6XVZMJge1hRACq77jwS/9AqHrLPmQuUS6pkTKSWwFaK0YsooRPZzD+67BkNsC0gd3qKiWkMvZULu+jvX5OWrulWbMsMR1vK8qODLlWIKUZz9jyBnz04OWVKUGLfeuGQt6iOPmY5YJrV78/HeBFpcNLjg2td/mT5eb1q2k/X5Gvud/DnDi9lkt96fd7oC8siDgtEO0YMif2M2yF0MlX7xqx0VflPPfHhdl3nMyN0rEFHCMGNOo9ACz2kedePMxDEOucS+dnxHvvKm2Z6KHD44+ODrv2I8Tu6Io5HMSeE6AD/k5qTNLZRjmf9wn7rSjHe1oR/tY+8REj013ggisVwFxjhh6JAR86HGhs+z/acJlB8/5LOGfJfHtFWgBuypBV1/w9iIuL1kh2oQoWdpOLEgsheXmXH7/OJuUs9MV8qTufcCJI7pkzkee0J3LE614HMKULHvfieAl17DLixDvHFHVZLyAomhRAtDgGwkmqQIRhflZGa95wZByEPlkLaQgrKRnHxxXY8/NXhiTcLOHD56M6Lev2TBwLo6Ur9GIJ65xJkF8h/OTOVfB4X3IP5PJB/rMJHfFOXaLn5OTU0ZNvHj6u3zzG3+Ajjc8fudd3nrzEW985gEX5w+4f++hZb7nMiC5+4kpl90RI7pMcc8UTYoxJYhDIu4nhrTDTY5JmUv0lGCo81i5l5lUsd5sOEv38MEzDXvCaoN3niE5tlvh7NxeyCF4Nps1igMN+BCYlQRg6fi0zo3iPDPbvLGyoBmjMsRMILIBR5GU7IIneCMlXV4+5Zvf+j3W/SmbzT1SmhASpESaEiQl5NIt05SYpszgLu0SIBiRYhwSErMr652pArgsy4exqGNKnJyv6Nae6ToSd4nBR7beyBtgSjRd3zHuJ4Y44fvA/fOe4D19t5pZ60Sc7ln3whe//DY3Nze88+5jc2JCh4TeyEtZHBOdJeymqDBFYlYVIbfTnmwjaTnNi3TKs58XRwcL6lJWxwgXLpfgmX3EQljQVGpN5rGi5dmz+xynkThGxqREVaunh0nz+awwVBaU8zLs9sLByjCV0Zg/v/WLbae5HQvuQ+N4FwCiaNcJZQGizM5yu5Y9IG00C4gFnVvaJ6Y0YB7jQimiVP6e/W5trv7QbBFt5C2bsy3jY7lRubTmvJl0UhxrOdz+0DNvOmrxFC6+K3VQdT5oPkGdk8u7pKiEqKnBpDyflxqjVu3L3hPeO7oQePDGQwjCxfmGzXrFw0f3OVkFTk42nJys2Y8vcezovGez7ll1WXGHosbjKlCyuO1lbpNFLxztaEf7c2bjNnD1/injdUeaDmuCH+1oRzva0Y52tJ+sHX3zox3tJ23BdwiWrIEI6jxk9WTnHMk7nJYSqK4G/Oag+owhl78sOKhZxdNwZAVoVTUarGhWRZiDeRWnofAdcvkYslqtujkAJ7P6hOEsubRLaZmwCARawk6Dd5Nxi4IrApKTjaQ5xxK/LJiyXUsXBHWmMhydMCTPGK08+jjB1U1Cn410EukLSqLU8gLVBMP4XDJMON8L1UhyCdF5+5ncIvP/ROi6noSy237Is4+eQBy5ennJ2dkJp2drVv2G9XqTS4M3dZMLRp7vq8F8cZE1XxWEdUKSZDy2aUNWC7ey4XNfha6j17WNqRiNjCCOqMI4Cn0PoFV5oiBzRZ16ttvB8/K5OCqRpG7QQGJRFZfmODkZ/y8qM4WsMuy3PH32EcH3dGGV8c1ChrADFpJCyuSMtlTzPF6EGLUmwZWSKwX/B9CkTKPSrUydNg0RnZToEpNLNSlUMuEhaiKmhAuede+zEkHg7OF9vvxv/gVWmw2hsyD2/QcXjOPIy5eXuX+8lQ8vJXqaPiw4MllRJCWtz521PtUA/ByIz7jtnRhy3k7VEtaYn+eKIWc8VrW9Ucs7aworEzF/XUg3pQ9vEwOWxI121NR2lU/qxge4r7THKbhwc2Tl8EQN1ki9rnkb22HevMWQb7f6YLPFOQ6K7eQj3+U7zces5UvKvP1xvlbb5vzvIVx8Z+MO7p0srvf2Cdq5tZ5ACoZckea6gYM6jubyX4aNp/KZ82xONyDCahXogmdzsqbzjq6zBMIpgTBZcnbwhkWXN5EeRh+WGHItLXa0ox3taP+a9smJHv0G54TVyggcg+9Q763cQ9dZoD0EkzEKwcgHvqlb1ShdFKKHlA8AyfJhRXJPEDweFSUW5nNWzZCSte5yfcQ8EQfn8HkSRgQnCc0MYAv0WiDZZwWPRGZuWtEOc6iyA1fqvMVU8u/tv1YuxYH47MDn0i31BWBtTfXFV5xlu/7TE6F3sJWeIfTEm57tlWNMjjjA/qORZ+MVb98fuP+6I1X1icwINBfEWuSDseKDwwWPDwEfg5VwSWrEmbJoyf+WEjMiwunpGa4LPH/yhN//7d/m/cfvcn5xwc/8/Jf4qa9/gc9/9ov0/ZrNqqf3PSIBcaGqL5ADr0mVOO0Z45DrDkIaM9Fj2OJWnlHt/lHUU5xHfAAZqbouIqxPT9HOmPjTOODTytj+0bHdecbRejcEz8npiZFKoik6FJZ+4zbZPai/WXkH72Hmrcwv+SKCMCRFohJ1vu9gCxUnji44QhCev3jC7g9+wGuvvc0XPn9C0glRozbHGNGkxtwURxzV6hmWYn/kw3Z2f8chgtjC0mq+2ZDxwaGSGIbENCmbixVh5ZEriPvE4CfEj0hKiBjBqu8D06Tso3AaOh7eP8+Of0fnVpQSF47IZuX4ylc/z/XNjg+fPGMYBiT0VvvTGWHK4uiaa6RKVS6Zoi3MzHOXWVnHUcvgkJ+dWgal9rnd7+JMFclG552Rs6qTlkuMqBEQyn2qDlPeKsaBcYAxCVMSUkxzW7yrNUuX69xDR9ZOUPkpzUJPD/xvdLkM1AXLeXaRl0odzVhs67Q0e3KwiPv/s/enz9Ys13kf+MuhqvbeZ3inO19cEIBAEOIgU5JFWm6rrbDc7aGjO+wP7f4rHdFhRyuiOyRblmRRsuhBFCmCGAni4l7c6Z3OsPeuyszVH1ZmVtY+5wIXBEgARC3g3PecvWvIysrKWvmsZz1rdqC1EbPkXl5CiMmLO1lsX36bFz3F+65HrFuIsbX9xhicL5k0bfvuW3jM5zUC1kgtJ7Xw8Q2LY83VW9qNZmb9fL1zSZ/a/LKAy31cCeNiMAIuP0M2EwW9c1gH3uu1e+/ofMeT15+we3jOqw8vuDzb4vLC5Gy3Y3dxwe3NhOclvXdst4OWeMnqNjEKKWXi4eJ+5Qa6leix2mq/7DbtPU+/9Yg0rYv21VZbbbXVVltttdV++azzWv7bOcVvY8ZpVfU5lzeuJI+SEJbR1zbAmsEBUwkaM8ZccaEaaDWVy6Hr80YJGXJATSpWVbP/M25SlFsNTaJQS/ZIcxjblCSUJtBpc/C5tIZy7vKTg69lv3qVxtCCIW3gte/AGeiMI1hHmhzTaEhiGCOEm8QhjVwOkc1ZxqYWbWjwopJ8lzPpjbWYlPs/Jf1XUsXYK/6ej9b3PcZZDvs9H3/4EddXVwzDhievPeTJKw+4vHiAcx6cw/UOJVTYHJTPYJLJKrgpEiVUHFaiICER44TJSq5FHaS2x1ooSV25r3zXIVb7P8WIFa+lm8UQgiFGUKKHrarhpSR7BchmeCxbCahnfM8yl05vLeOCUcBkwsoMeWYiktFy0tYaDoc94ZOX7HaXPHjwBJFUE5cq0cNmElHKZVigjg3TYGspJkgZGSs5j2Wo2YJbCX4A6w0cIUUhhgQm6nlz3zpn9buc4Ljd9JVYMzx5zCuvvd08j/Do0SXTFLi53RNDVHzfuib+wUzgQUkriutKVtAQbAON6+M344OmPvftPWG+SCqCmJWJqfNDKSve3gtp9ixPQxJV506iWPaiLZXkgcY+7gvRSzvv3MVjK5HjRCWjYqGfgiFXuJwTazMiKzxrmgu9e+pF/ZbFRs2cUPDlpp+a/5zsP+PR8zxHo7pTBmHT3kXXyKI/Kq5rmGNM91xMi3gvv5rvRW1eJT/N41XqufNnovuWcxeRIWPma7HGgNV5w1nL9mxHt+nZbQZNBMwH77qOru+ZxohFiV1dJnpofFBImXRUFNyXfVrGwoohr7baaj+5fWaixzCoE12k9KxziPO1tIJzDpx+bksGvSns1aYWVes4U/0flc2yWg9RqkSbI0nCGpX9MvUY87H0F1sn4uIAti/O2T/Ib/2GOGGLM4LNLxmXfy8vHipJQlUNykIEfTFYWx2k4lEZAyZLm82fWayBjR3pneHRaxd0bsvF5gEPtwemEJhi4NGrZ7zy+kM2JiG8qI6RElHIDgxV0cBaQ9dbuk4VUQo7vtQPS6Zpg9MfjNbIU4aulnrph47D4chxeob7uuHlixd8//Vn/NlbT3ny5AFvvPmYB2fnvPboEWRHSFngyiJ2+V67WrNPiA3hYkoozyLX8Cvs3bKgSggxV21MxhBSYpoifQKTCRwpxeywKDGneIZRtPbibMV5KOVCimsQgagOaya8UF0yqX5H6duyZykFo86FxXWOzc7z8MFjnjwZMH7LJ7c3XB/HPJZQ9okoG1p/VNZLptkDmYkmSjYyRpVSRMgOAnTnHdZabm9GxjFiEdKkdRRd58FAnALWJpyFZCwRBzbSdwZHYro9KPmni4jPZBKjhCcR4Wb/kpvbvS4y0DqjMeX+Mpnt3/iOKUZK/Tko/aXKLGKkCfo3d6Q4muWZL8+WLT2dF275OdHaP/lZQhdYZZ2lPujSOUpoRgMIjljvarMOWljrb5b2LR2upZPZjqLaEY1fPLMX9MgiiZnNLlmpiHrM4hQvnNV2QmzPV7eTpnbhvGqZr7RZHJWpruns8mtZCyhxpFx2BktE6r00iws1zeVJJufMf6t3b6jSRicXd3fZM98UdbzbZZ1elRiIumqAzlcCRXtPkygJyDVghkB1sHfn5/SDZ3N2Bghn2w1GEmebDZu+52y3ox8GJEZIkevbPdeHkZvrm7rQLvOtlIVj09NlnSMiWt/U6jxs7Brc/UWxd9895xvfeMR3vvOQlMyP3mG11X4sW8fUaqutttpqq6222mq/fKYZzQWezVittbmstuKxyZiZdJBx3JLtXwGSlojBHFKtih55rV5ICZoMWBSZK+oIlBhlRjvqeeAUNFpiyPMHimcXgklus7RIhql4SVXqkIaAko+xALfbv+eLq9fsTcTZke3ZgDUdgx+47bakpEq227OO3dmG2w8/5Nt//DV2jy55+Lk352B1CRy3+HYuD2KNIVXV5aKQslQ0mTGeooCdsV9vCTES9nvMJ3A8Hnh5tufFxZ7dbsP5+Zah6znbbqDeCUBmkoatitOKm6WmG1LtC1vHUIsh6/Y5CGyoahEKTykeU4O+NT6QD5pSAcuWHd9E+6XgyrmUD9beiTbXrQs4Vu+rZKxoDjr7zrLZbNltz8F23E4jYwylddomJOPs+X44Q4oNmLo4c34aMtBn8rNje+3PaVIVZoNoiRZDjc1Ivn4DiFHSEFYxaIsQp6DYrLNzmZ+azCdM05FxCnmsk8kzBTsvSb5zfyh+bGr/FuTOMOO8nBBp7sWQTUHxWzyxfXik+X5WdzjFf+ezFxx1phLcxZB/yHq+4MAFHGy3nRkG81i7Z8jVPjrBYE+OtsA7T6BaKlBpsva0meMcFUOu4709cdPJM2Bdt1n0WTM3narM3Nt3xjT758mnVSMpG9eLNMsTmtIPd7HVlj/T9r/U6Tg/r3Yei7Wbyi1rp22gJKh2XY/zFt/3gNB3HkTovc9K6R3OO52gJDFOE2OITOM032+5++44NX1vadxAn8sVN1pttdV+cvvMRI/NoBNPwiFYrOvAeZx3eG8JWSbBeYfzrkrvOedw1s3BzkqqaKcxqeQERJ07m4keRrSEyqI8QIkgW4MRUx1Da4ucvp3fQTmQXNm6GpEESlBZ6ncWi7O+OuvFCTbZAdWXSKmzpY5faXPdtsjjSV5UZMddP4fe7XH+wFufe8jjVx7w2sWBjy4NL/Y3vDxc88XPP+BXv/Qqzz4Z+eD9chFlUdO+NMq7yzAMlmFw+jLySrYopVswYKxm7KuygS54kgScNXTesdl0bHcDT5/f8PJqz4fvf4g1wqNX3uDxa2/y+S+9xV//G3+NL7zxGg82qvRgbKfvzJQoSibeWnxWdYloCY3y9jxGSAFUdaJ5ieW3bUQIkggIAaPlU6bAphA9BERCDpg7rFFyCSkwyQRSXv7FQctFA7UD8ndBv3MOY7v8ucnHzo54CXrL/USPiKUbPGcXPW+88QZ/7Quf473nz/nmDz5kfzjkLH+QMIEB6z2u8/je4TplSUuVyCtlJ0QVBYApKYHCYvHWcHE5MGw7bGe4vR2xBuJRmaJd3+m9nCboDMYbkrUEUTb1drBYEofrPd4bhp0nYUlZ5aJzPWEaubr+hJubvUrVGZUAjFGpN8YELF0ZiOrAp4AEyXVPLYakrP8idZddMZWolNnZzA5m6xMWJZziFtbnjESRZJwf3dZNLMVT9KuYz2hlwhZW/Nzqev8WijhlRpnZDvNRRc9b/c5mm3noniz0BMjKJFrLURoPtDjqzWKH2Ukvy4t2MSB1BJ460WXHeTGyqIMKlVl+ulPZrTrmGZQwUkAYwUrCoiWt5sX18mi1pEp2qiU70sY2oEd9tpomn7R6YYvmSq4NasBZ6Hsle7SLc5TkIeXyc81DRN8f3jkuLx+wu9hxdraj85406f15sNvhvaff9LjOE8YjYRRevLzmxfUtLoJTAaDK9kYKuUX7zKIjqSxqU4xa39Z7JdSt9gth3/rWI/7b//bXVpLHaqutttpqq6222mqrrbbaT8m8L3hGwV+zwq+dVZfJOHDBbSv+au2MIZkZW5jxmZZMwYwx521n/KlgOGb+V+bAX9l+BiOaTP7msxasMOU7A0aK8nLZRpo2adttbrgGvgVT1p0yb1NUbufAq8l4NzgbsDZwcbllux24Gs64HQyHaeQYRh492PD40Y6vfeMj/vgf/VPe/I2v8ODtN2p7yrlK443Re+PcfB+s0fIwNThfceyWsJLqvfHe0XWe/WHkeAzcXN1gjLDdnbM9u+DBowteff0xD8/P2HSaXEn+KTiZNYoHWlsUtxucCQhJMRmY73M10TI5KccPkuSEtZjwBWQTRZUUxLH5PmiJkiojUm4okNGdk3h9zNtYwM33RhqcrmJqZbdltDqhpJh+cJyfnfP40SVXhwNPr2+YQpxLrRQ8NSdoWpefi9Qq3xacMSsRYzIGKRinONiw8bjOYvZK9jAGJChZxTpNopVcgpucCJiyUrn3BiNCGIOKv6Cl5PUx1ETRFCPHac84ThXllFpiRvFWU9W2c8+m1OCQBYmdMd35uZIl7tuCiBkqLSrqBQ2uz6kRagJofWSXgG3zGCAYFFnXRMGlWm+7W7mxTbJyc2hh+WElFeTuWB71HsxJ2r5bbjMPxeaa2/FpoEqYGGpy2v3XcXr45bzW5hTeOchivOv3psbMJCcMNqWyiipzPVQmh5T2Nuo+pnmmFu0UvUc/EqVrNhARTaM1RhMFi0J+o3pSerqQx8qHhcQ2bDZ0fUfXdzhrVWkIYeg0Cdd5jWmlGEhBOB5HDuOELdhxaodeQ3aRefzoY6CxITFyt8zWaqutttqf0z4z0aOSALOT5ZzDeIe3DlflucxM5MgTdtaigBz0bYkeS2/TqtRXSlSub57oLFYnvxIqzUH98nlx/A1W2YouK3wkh8TZeXf5HIUQos5KbpOxyg0gzYQNSZhks4xTycz/FId/EQVt3k2F8JE/iVFf4hISJiQePnnIcH6Ofe99Du8fCdMtL56/x37/nOpo1j5avvDry6gzuE4ZhzEGjB2xNlW2rrUmy0bZuZwOhhgmpmkEDN53+UfLgJASx/2el08/4X0fgQNXP/iQ+PKahw8veevtN+n7DWfb81oSR6XZIkkShYtt/YDpPK73uF4z3V0hXkhxFpX0ILnepSRDTIkpKrHD5jombVU1MqGHBee7/ZkXTcWNk+IAk1njdQnYeBLGYCRhJerisbqb+ltphTWOYeg5vzjn4nDg3OhC46VAlMQU40IlLcWk0nrtYqIw0iWrbFhV6bACNqsCWOMzAUkXU9YqiSqlQJgi3hmcVxUMK0AUYhAkAskhBgKGZIQ0BpIJhKCOWJDAFCaOB/1JMSFickkjJaimJESjTvlxnNgfJ5xJWEMNsgu2Lm60G23ua1vXT8WRWZgp84pkxQQ9VpV0xKjyivEsHL+6oKlPAp3v6PuOOCZiGpmZ2bPrf/KI5j2b+3FnDaz3Z6YQmeyENwfL+0lznJkx3YzVemyp3aA+rlkQq08l/6RcSXGmy8yZO1VOLszkvnH1CItCofORG2d3JuTkG9KSZBpn+PS30yUL0u56soooWRs0pV1Oj3G6rjIG0zrnJdNEzKxMaU6WJ4acLdFhrOXs4pzzB2dshwFnLbdxTxgDNzfXJBGO00gIAaISw4IIQaDDYYxX8lMdxLmZ+XbGXGPUiDrmw3aD7zu22x5jHav9YljJAPv0FfFqq6222mqrrXZqKcE3vvGIGA1f+tIL3njj5s427757zne/+6D+/a1vrepZq6222mq/bFbgG5sVQJfEiBmxKSSDii1XDGlWt5jxm4K1KNa8wDwMGhyvu5iK0ehxpNk0f5dVK0xO7mhaVRMLl3HQcv5STry0m4rTtoHF+c3XAEmnAFX9vQlKivDxd97l9sVzvvDrv872nS2bjDuYq2vCVeD5++/xyde/zu3VCz73N/46D958vQka5vO0mea526zTwL+VBCEHuwtJpSF5zOoqBolRlZahlga3NlW8JEyB4/6WaytA4Hh9RjqObDYDF5fnOOvp+34+HgJSdTny/VcMyHqLcSWuYBZ9pBCR7lM+TqjaszQ47jxWmnt2B3iS5WcL3H1W6q7jsmDILeRVcP9y63KQWrHOGZ/23tH3HX0I9PmsR8kB6pQyNyljgZU80ZyHgiHnILjRJD4RxcG0nVmNPSdkFtVpESHFlMva674lMC1FkTzHWkopE4kJMYkuAVbbGCUSpkgMse5XgtfljpREyhgTU0ha9qYZhg0YPD+7ktFPme+IWVz7fLdMs6sSUZp5ocYKTvzNgnXmIWCtwzuPRCHJVDFkTvdsz30PFsz8j44OWQyh5YU0k8gpyUXqb4uZJu9exlarksE83qDOQ7UtcudKoI7nuVHlv3ZxxnswZBoMuYHsl+VhTq7z1OTkX5ox0QLli8Pc97yePMf1GKZRmi5jIT+HTZPvoH82J5obQ9f39JuOzmkS+JQmJCamOCKIlrCXlCWH5tiJkvoKQXHZ1HKvRYrat8Yhfec1Cdc75gTl1VZbbbU/v31mokcsOzglS3Rdh/EdnXV0Ofjc1s2bncLM3s6Tq8XmwD06ORYX2liMcdmJS/kFplOvNbbEOSnUEURIWU2DQiyRXIZF9cawMVWigDUG57yyxZtajrmeiAaUy1vbqEQaqZSgKS/q5jWzCObOdcXUOZmdHK3Tp46viNbDE9Ggux0Dr7/zJttXXyH9vuXpJ59w2L/g/fefUVQAaq2K4o2jNR9rINsYfG/wG0e/2ZBEcLcHYkw46zCgqipOlVacK30MYRoZj3swhq7f0PeBoY/EaSKmif31FfvrKz758Pt842vw6pMnfONX3uHLX/48f//v/w4X55cMXa/HpEMkESWQJJAIYATnz3BDT7cZ6DYerMNhc2BfVTmSNahbHrL8oGEKkWOYSElwOExWkpkZnUr+wMRZnmtB+igLrfnFLtnpt9ZjbTevE3NbilNjiViJjdtTxrASPUqZmu12x+MnTzje7nmSz/6B6Iv/OI3KxEYHQxwjcYpzhZnseCgZQtnzOENnPQaL830lejhUKaXrEhaPEUcME+NhxG97OucyizZBhOko2GQwySMGJjGIBEgHggycjwIuYXzkeBy5uT5we3MkxghYUtKaiTEKMWm/ShKuDyMvbw/svKX3FiVl26aP8rb5CS4FQCT3b+nD8h9jZodcBKwIyahsoOTnENthXKds4aWvWc0A237D2dkZV+nIOMbMSLf1+zuO3DxM7nEk9bfF8tDkunrNfrU5ZZFRp4QCRNjlF/Ngq+e4owqStzOSMEDBwtuFqpAXYggLorxBlXtY3o1UVyPLBYMS5Epdy+YsQq4Z2ywsT9jthScyn3r5rM0IwnKFY9qHrnwq8/fLk1hwBuM8c/mrTBqUOgPMbSb3vbP0my2I8PCVxzx4dEFvNTPhcHsghMCzl8/Y7/e8/94PePbsBUPX0TnH5aOHXD58QOo22N7qYjvP323vJRJTijrfSsLYjt3lGcMwcH6+W5QrW2211VZbbbXVVvurZikZfu/33uZ/+V/e5L/5b752L9Hjj//4Cf/df/erc3ypqKOtttpqq632V94q9JWDzXMykybhhYY8UQJybehx/mxWdFgEio1p9jALcKYtydJm2LdqskoesBnD1v1NKmhWDqJnpeqyvZRkvIJ1pBkHKZhxTUapmEkBjJprlTas3OKRzFFzVDX0u//mD3nvj/6Ei7MLXn/7Lc4fnON3O+S9D9jf7vnu1/+Eb/3zf87n/+Zv8Zv/17+vyV4pzW3MkeemGLqSPLyqkQpgp6yebE0OgpdS51lxJV9FSpEYJzAG5zqcSziXkJhIErNS6pHb6ys++Rh2uy1PHzzg8eMHfOELb9P3Az6PAy13KyRFrSjJgsb2SkDxHudVBcTWeyi5vEzGeMn4ejKkmLQUNpoUWjC9mTeTr6KtS30SeV4mdUq9DyU51LS7zHdPz1TB3hkfLUOyKBn7rmO72xGmwDYf6hohSSKkWGMqiCYLSkzLMQ/UbK88yKzLaa+2YP22KqU4JxlzNKQ0EWPEGoezWf0bgaSVx1XNVmMvWkUmgUQSkT5qX0QbCSEyTYFpjDWmIzkhLiVBkiYaIsIYIodporcWZ00lZhSlnrarExkbr9eZi5m0eG1mp1RcNpf4llTwWwMml1Jub/N8gHoDO+cZ+oHxGDUht+3jebTctRNcej7i/EG576moV5xi2XcbNmOq9YANtnqy7d2Pilp4e/z5JAVDniFbM39tTke9fLqvXuJftcxOfrKkJDTe197m2OWSzJ1v8uenvT6Tz9rtZdE/Jx1b1INoiGo5W+/00Tfl+g04r+HRzW7LZturgrwIYdI41f64J4TA1dU1+/0Bn+fGzWbDsN0g1tO5/CwscP/cZoQoqcY+MIZu0Hja0Hf3XOdqq6222o9vn5noUWpG2ULecE6dL+PUjSgkj4YBbAvZw86vjTLRihTni9n5bvYv20r5nvoxte5iap15U/9pNqRmgTftKufUXWqOfN6leRFQXENqm8uLpHUc9H1a2Kfq5KUUyydzvxgDEYwYJTREQVJ52WhQH4JmiaucQmXCzlYcTc1ANwi97+i9yko5a7ScTnK1TItzVutjtn2ciS+d75QQ0nxnnctOfKoSawQ4HI48e/ac773r+d//9z/k4uKS1157xtnZltdff8J+PxFjUkUPCQgRwYNYOmvpnCVaU/vTGkhl8Za7x1qjL1S03qSQFxtkhnMlDOT9ijpHfpEfpwMvbj7GOceD7cPs7Lp8yy2VCdsspGTRt/m6JSKSM/bb7jcKUqZk6n0fthsevf4qtynBe+8jkghhUlKGt4sxXeTKyiJFUlKpwQlIRsvhGGE6jhgMhz4iyXK8nRjHwMXFlu12y3SMHPYBMZYggssElBgD0/E2kz6UBKNrT31ekjcYo8HrwyEwHpVMo89Zls+TSIyB/f6WGCesdYjA8XAkjCMHcQRxTDFlUsisPTPXwJR8fVJZq9pb+a5ZXUDEqHvqNo4y3OockOvqiWlqet65bxBjJIaj1giNeYEhzbNaneG8EFjsXRzLVOebegaZv65zTdOIugZvx0c7p5y2+NTnvfNslzZWF7s6pe1KRUrNT5n3Me1v9Y8l53suodUsnqSUE5rd8rtLCXPSZ/nz6q1zKnxRj7JcKs3/lnmAOwuJeb9THr5iLOU9NF+xlGdacskmk0gp8uzjj9nvr0gh//3Rc/a3B6ZwJKSANYaz3ZZN39P3PbuzM4bNFodr5hsWayk9B6pEJKbWqO26Ht91+l5ciR6rrbbaaqutttpfaSslHRWYv89EDDF+KlS+2mqrrbbaX2FrS5gUssas8FySgFqstvwUTJaMUTHzFRqso+w/AxCm2XAmd8w4TsYCW+C4gX6WWHL7ZbNtEyst+9T8lhzFnHc1M2CcN1ygQyX1X4raQSEKpLn/jEFSUtwwJSrc0fSxFFJAJmpIxTClPRlFAcMgGTsuGLFipdamBW5ecXwz/yjO7+b7UO6VNVjjmox1bWeYIvvDgRcvLe+//yHDMHB2dqDrPednO6Yp1n2kKkMrCuQy7jO7GNrW1uUo4yVzcTTJaWZ2NHhZiyG3Nw1CnDiMey2L3m1m3LicoO3G3B/LZKUS3FVsM82nX+wnGdcTAd95tudnTCJwBUXRwzT3pHZ+g0npsTK2Gi1YJaGIUUzUYAiTIGJUdSMm+kFx/xSEYJQAlAQN1udxl8KkrYw6uKrgqZC5UHqPQkizksfcQm2/JMI0UUr8iKjCS4qRCSGKIRZ8uPRlCYrXy5MZo5Ry3jz2slpCfUxy0m/Na6tjotzfOhXkL5Z4ppJSlKwS5WSsFMJBc5ELdZV6X+4SRO7CpksMeQELnw6URXbjciwvsGnKhc2YteQ5rny9uEHNv3MJldxXLaEmD/AlhtyevBxj2R/3YcjLC859kGQRbzvt0nokWe5efpkv5aTfzfz96arDonGnWpbqTtvyOXMplcPtDSEccywjsb856LOUAiknZPadxzuPc46u73FeldgXJXjqfZOqZK4kNalzls1x1bV0y2qrrfbTss9M9FDVBnXeiqKH7Xq8K2oes0NS6vy1ZI8a3CuEENDJPadll8Dd/FOceINx+SWSHUbjHAYhZaewJXNUVqE057d2dua0EY1TSn6ZKiNRS5tYZV5KaRdgtZagxHwe5ypjUiS74iJozQyIUQkbOA22W5/l/KO+SGOEMQhxSsiUVLHAdGjQMijBIiYkFgYu6ikjGJsAJVNYI+yGLYfhgHcO7xzDxmOs4G8dyYD3HV1W86jkG2MY+iHLlXXMyy/w3mM6zzQF4jRpl4lwe73n++F9fvCDH/BHf/hHnF0+4M13Ps+bb77C3/0PfxNLxzh6XWQwkhiR1CFi2XjH4B231mJFy7U4a4jJoIoqaJutoXda+mMKE0LS+08ihoCkWQVGd3JYX9iPlpvDNV/7/h+w63f8+ud+k77b4sr1Ga+ScSGi+nSGtCgvouMgpYkQxvwij5k97uo5FdSEmJSMcvbwkl+5OONoDeZPvk5KkfGwxw89vt/himyYVHUvnFWHNmVH2txGjDP0W4+xhsN1JE0gqaMbLPubiWlMvPrKq7z2xhPGEW5uI8kmjjHR5WcuhCPx5R6xRhVvECCqMojZMliDswmRiZcvjkzjyJSEZARjI4ZEihNhPPL82YhxBnyPGMP11RXj9Z79oONjP4VMBsrs7bqoKw6WOkq6TcyfZIlHrzVIwzSSkjBFoesM5ynl55n6nGE9YqzW2pOUH4Psboq6c2E6aAma48RxVEZ6JdVkp6ksnDBlDM3/aD9lNnp2xEvtywpeN1NIOffCBz1dADYbFke0OKPGlCU2FSzQXzPZxOYFS14I1WyYvFWVJiwHzQcoxCRjmzVA65AXAozJBKokFSxoW3jnGmiPx2JRgKWS8lJZ+Zb5fr5i6jN75+Dm9IP6acnD0PlZ8EYVgEr5rTJ3S8pZIFmBw9hADEe+/c1vEFPk2dWe4zhxfHFDHCcuH56z3Q2c73Y8eOWM7dkZm82GbrPDD1vC4Ug8FOc+t85qH0km2HXWa387S9d5Ntstfd/jfb866autttpqq6222mqrrbbaaqv90prN0XebgRRXFD0KRlxxWZqEtDYw24bsCjGkHHwO3ddj5F9lsRbPeETGxkzJ3K8kFA0m14C+0SDnrNJaIqJzkmJNS2+DpaZgO2bR/jZgaooidYktwoxrQcY0qKQFjKNeoChmE1NOpoolvUhxSiEH29NJdLeAVraAVwljhM53BBcyrmLxnSVGl0tyJ6x1uIy7FGwOMlactGQLmBo7t1kholXVMCJM48TLl1dcX13z4Ycf0g8bLh484Px8xzvvvIbBEWMJkEaEiIhDMHirCTVTjh+Uir4sxo5gDVktIidcmqJYK1kRI81DIY8pk9WvwTCGiY+vPqBzHa9evoZznposiFXsrAC5MBM2KAlLCSHmhMFGmaTq7Jo5bpAJId1m4EHfEwyYTz5B1b8nDfyW7P7c5/MdzWO3kCxEr9N1CgiGYyYCicM5mKZEisLubMfZxTbHIBJiRJMFBYw1pBRIR1VpKQlnilZajPF4Y/QZycmCKUai9i7GpNwnkRQN+0PUvrcOAcbxSBwngnPgLCEnUy3IHs1VGmZsXsuBz3Ek43WzFCMiEEVwydBv9PpNeT6txhikgqJSH4PySAhoOfQwEkIixIyJ1s4ufS8z3lrniNze0tgTsgE0lIQFLCjz5+1l14lr+ZWpx1HiTuUcLSZCZmzYmjw2ZfG5aber886yCffhsfV7KQmbzTVXLPwEkL7XzHx9Zu4Xsxjf5s4u9WLnCbX53pw0Wep5luXQpVTlIlZCWMaQZf5XkyETicizp09JIuyPEzFFwmFCYmTY9PjOM3Qdm90O33d473G+w7qOFAIpxDqGZHFv9UOtVpCJHs7ReZ/jdGvp79VWW+2nYz8G0cOjL0+VrrOZAWwbgoe++2ayxUz+mLOby2f1xbhw7C2z4FYmJFTnKb/mKgsvO2j5OK2D38QZ1bK3XPnTBi2VkYqDmEvNJKsOTLNbbjTldXHqcJXSCDEF/Sw7jCE7lNY4ZTeX+iJ5slcnT4kknTVcnG959fWHjIeXHA57JEWIgRgTIUR1uJO6U0jkOI4cx5EpCF3n6PueYbvVNkjC+5HbmyNhmnIQdmY3zn2jn1hnM5NQf++co3Oegx11DZPVRaxXeT1Bncbbmz0fffARJgnf+9ZHbIYdffeQGCIhBFKKuM7Sd55N5xk6z8G6pXNRWBaZtFFuryTJ6iBz/1fZiMbVrYSAPKZiEG6uEpM98oH5kN32nCev91WGq2XEqg9Y3PDZQZFKX7bZOZ/vv4gurkKM+blwYAxelBU/m45na70SfGqrm8B3IT0ZMhlBCUamBN5FCCGiZUN0bXk4HHn54oowjXivjOgQorK0t06VCyYBqzKMxqS8/nGYXG8xhAmDw3tLShZCwkThbNjoeHQGb2EYBoyzPH15xeE4st/fEqaRXW/pDITxwM3NFefmgq7zkBeWhfjfLGkBQ8oMcN8ZBuswWFxeEHcJnO/VIQdmRZ3ZoS39Px/z5F8xTMeJ/e0ea9XZqsdoh/29v83tnDNP6pDIX8tJ2+bF/XyERp2ijtXWA60TZfb3pHFcyUDB7AM3U9+yT4uPLmU8NQt6owuBuhhp29K2tzwLZQ7O15Zk2eK2o1p+yelGSSQvXFlkWbSbVsWXe9YB7fXUk5l6VxbPzOkkr+o7RR0mMR5Hjocjk4wkSQze0zlPnyBOkYuLc4btwGYz0HedSoj2vQIZmaWd3f5MHmn1TMpzezp6TNPe1VZbbbXVVltttdVWW221z24ihnffveAP/uBV3nrrmidP9nzwwRkffrjjgw/OftbNW221H8usmbG0QpyY8WDTQhENqtNgMjV2VzCAJuhazTT7ld+WoculqrNpMJTTk5+s4s3yFyn7Fjwnt7EtR6D4KU1+S3NuaTCGqgABRpRMUROnMq5opGmcmaFTg6pd9H3H2fmGrvcVi0kSM6aT5sQcAFFcOcRITFlJ2Tl8g5NaG5l8IKWl8kjbt7kj5lLt+V9nNEYQTNTcx5SvPn8vQIpK/Li5voUkvHh6i/cdzm2qmrSIYJ0SPHyOOQTTlDvWOh1NeyymFJrPeOQcP7hzI+txTHO/JQnTUUgmcMMNXdezPW+Cryex/LZblze+9NY8qstmSUrpehQnRhCTNHmpHqpRvWmD4HMMez6jIZcbKvj1bCmVciq6X5gix8NIipHCNUopqfJ3Z0qFFh3TtqiZaPmicl0paXKqK2SCqKU6Ou91PFoNomtZHsPtcVS15WkixUTnLM4IKQamacTQZwVy7f8FbDn3tJJ3RDT+ZDReU547K6qIcBfVvXu/m7tej3352qvEL/81Pvzeu9x++DEXr7zC+ZMnnL/yqOLQ5FBFW+pkgRNX3LX9rG2SLM5Z549TwLXc6DqZ3IMhU8benUlw3nIxNk+64A7I25yzNK2dC+Vku3vOqZj2/erPn7pr83cl9ZSjLbD0sk0zX9937PK8N5j3AkM+nQsaPHwmqsgcx0ITysv84wZI0dMPPd57vHc463DOZzX8005fKma357576+eBv+YKrrbaaj8N+8xEj94riSBlx7MrRI/MyLZGy064mm2dJflMYQWXF0fOxEZIC2k4q6VcjKhqiJmdiFTepNnRVbeI6pkXsgm2BOB0eyNonTnXsDsxSgW2ur1EbSPWYkiaxU8TYG3Z2SYreWSyQ0IISYgxMo4HBKHrNJt7qpJlFofFBVD/1CCZXJDE4K1l6x1vv/WE8zPDd7/7p3zzWx9BGJFxr0SPKTNWi7OM8OLlFc9fXiHGsdl2nMcdDx6/wng8cr4/YzweuT1MHA97hKkyu2vfk0tYGIv1nm7o8J3WQDzf7rjYbLk+Hrg+HAgxEOJE5x1D35NiJIwTNy/2fPz+t/jo7BOOH3uevPKI3/qbX2UaR/bHA+MYeHDpOdv2PDrb0G97rvseCTlLvkgQiqo44DosRxyqdDGNKdfKy85kKi/QQH11G1udShDGo/Dx+yDHa15+/Q95/Pghf+c/fszW23zHZulHawRnlZSTZA7QS1b6MHis6eszUNQpQggcxxFBGIaeGAJGEg6jHrwYMB5re3y3wbsBRBcnyhQlO++Ac5nN2WGsIebah6Utx0NkHCOuc7jO8fSTpzx/9hTnevq+43afOBxGzh44zp70HG8ity8NruvodwPOJHozkaIlHD0GOO73eN+x221xNiLjhAmJVx88pPOeTe/w3vD40WNwjj/5+rf5wYcfgNPFxBd3ngs/sL9+zgcfJJx7m7PdhiB6v8jzQGVT5wVCDIn94cgGQ+c6nLP0vdd76BxYR7SWEFK+Szq3OGtVgKUs2KUsmA31N7FY8dxeH/jkw6ecX16yu/D5KGUJuGRLtIsm9QZ1HqklpdClWckGUP9vXjw6Ny/jymKrTBt67ITUEzReWyaXlePfZ0XFAqtj3jIrS6jSR+MiGuq8pX6ryc01mcyeSwblBZSxpRPzIsPnKRGIQJSiaHS6wLhrdeGKqttEidVJryBGXdNIddLvP8oMfBR1lfKw2jzvV6mS2p1ZqlQCRiyJREyRqxc37G9voEtYZ3jt1dfZDhumGElJ2O7OdK5GwAh+GPB9h4kJYtCyWSg5KcVYs2vmcWfre0Hni2bl/SP6bLXVVltttdVWW2211VZb7dRE4H/+n9/mX/2rt/iv/quv8/f+3rv8r//r6/yjf/QFQlhLQ672i2XOauKN5CiWzRnVVY2ZZeJWJYCYmRwAKA6bsYGSDa0ft0k6Jp+jIKYsKjWU5Le8cT4/zBmL2tIaxG2wCBbbmYxLZ3kJK5iUFvHD04hkDchniCUJiCRiDAg5eUxy+RVy4qO1KkSb5lhmwSOsUbWLy4stfQffO98SUiKkSIiqyJyycolU0As245HDcQRj8J2jl45hu8PHSOo6YoxMIRLClNUUlgHWWmTDgLEW57VcuLWGvusYfMcxBMagysgpJQ2Ueqe4b0yMx8Dt9VNuug1x79juNrz+xita3iMGYoxsBkvXOTa9x3nH6FxWuqXiWDXYndW7FeISvW6Z+6p2OhlzluXY0wAv3F6DhJHjJx+y3W546wtbbL8Mus/hgYxaNdhWwYVMxpHbL0pZlpiTBb13mYyRVVkqF6DET7yWdW+UQ/QeZHWVPDZNVnxJwtw/QJyEaKUqre9v9xwOe6xxOGeZppSTBS3dzhFHYTqq+rHrPRbBmYgkQ8rvnThpSe+u02TCfYyQhLPNRj93eq7tdgvW8vEnz7i+ua6d9qiz9NYxjQeur4WLi8uGoJQx2/IcmmXfhRDx3uCMrQQl8nOAtSRjcjny+b7ahoTVHG7xTP7Kb/8Nvvjbv8W//H//Q977zvf40n/wJb76f/4P2WyGus8i+N6SEJoNTMWTy0dSx1Z5/AoWam17QE7mCsP8lJnl94a7n522K/9ROXJywpuoJBL9ss51zbFrGfLypch8feXByvfItH0rn4Zs39PeXJ5GqW4J0+Dvy+tddvUPO7ZkXLf9PL9NTm7ivFPKZCZByw4djxPTNOqcbuF8d473vpaF912Pc3Nbrc9lV5JQ5GDmKWqePxdkv4bANavHsGz7aqutttpPYJ+Z6FFfUnlymhU9TkgUdbZvFDSKI1IOVZ1xe/I5FGZ0cYbvDZqVc7L8vmXrVce9Nr+ZXAF1zFNmGM9HalU/Zq+gYZSL5DlYncYkQpQTCa76Im+dfdO0SQOvMamjZ61jGDacn1+y6TdYMflFqf3rnKkEgfKa8F7r7IlRuafOq9MlMYLzRBdxWanDScQilZRjmrZYY9gMG87PLhjHSEzCxveq6uE9vve4AJ0RVf0wVqXw8kIlRXXYY5yIIRBTIkZ1YmOK6mRZQ+87BtehQipZmmNeZ1WVGL0X+p06a1KdjLY/F06ame+b1lX0TCEwHUcmreFBSpH94YqE4P2G4pjHTIC5w3wtbTMzuSC3ghiFaUqM48Rx3Gs8vlmQWu/pdjv8MOg1Nc5cu44sToWgaw4MmfzSyojN4wn0ubC5lFGYtDaitYYYhMN1IE0JbwCSqo4YEGdJyTBNEedSJdiQAqRACoEYAtN0RIh0aYMTDbRb6zg/P+PR8ZLDeCSliBWQGInTxDQeSTGURlJo48v7Y/JCEPp+oO97ul6JHs777Kx7BKNkpnqcmTIw91f5eMkZdt7j+15lFq1jJlIwAwCNgyftTT3xJudP9bdUb0JpW95IbDPXnY7K+YjLGUo0MyN/YRZKEfm6605SaqHovKO3tbr/RphZLM1sK9Wrlyy9aGrzS9vn+XOe6urXsrySBhtoTlDaO7e7ZKa0197+e7dn5vbc13dy8lfLtl4cp2Y9aGcYYxk2AyC4XstxDcOGru8hKNHDuw7nurpIt9ZjcPXdY6xQACWbr1kkzTKwhqwC1c5J87364auR1f6iTQTef/+cr33tMW+8ccPDh8c723zyyYaPPlqzI1dbbbXVVltttdV+Ec35xPbxnrD3HK+GeUHzC22GEBwxCjEWNU7L8Xg3a3m11X7+rcnUJq+fjQbmTRtgbCKOpxhyxR4KfvJpz0EJuN6X0l6P+GnPkLn7fYsHL1P7m8CcuXuYghWXNknGbprNipaHzDvUz5EFDI0xhstXnjB+8fNsLs5zkhw5WcrT9wOXjx/x6hc+z8Wjx/UqjDUN1lSwUsXwxZiatKlJVaKlg1PKpcutlrymxdLy76JYsHeevuuzCrPgrdfjOYsVi5WCc85l1AtmpninlnfWxL+cTJWW5BJnHT5jxLU8RXNFJpfvqeOnQJInGDLtnmUcNRiyMeCsJVmruHYJ2opkjBSs8xQMuQ5JY+4mMhU8uxmGBSfTeT2TccowKrtZi+s6rHe1v+shmxCF/iLlRPUZqe0QTbQqQX5VZM+PBVrKhnwPUxLCqOXiS4nolElLFo1JxCSE2wP7jz6h6wcevfmG9nPGlGOMCAknXcZPdbz0fccmDIQYKOW9yfdYS68UVZaC7y2fpZn8ZXFOyVAuq4WYrMhuTUaKK4gpLJ99+RQMWT/3fYe3Dtd5yDi+yzh1Ld20sHYw/bD38em4aDHkeZvlMec+WM4Keeumi5YYcnsaWf5LHR5LvHrR9AaXLWOpeTbqHHXPnLrAkBdtvmduXLStHPPku0+z+76uN/WH+0VS294cpOLnbWTG4L0DOqzT8edyWRVVzJYcr3JzXM6UuW2OO8yxznL2k3Fw2txWMnt18VZbbbWfgn1mokeRGcOq49E5h3eOkuxusLkOm2UueWFB7OJdJlW9z4A0rw9jVDHAGGzKpVScbqOnTjWoaazJbrYhNaU12hd+cX61lpzJL6ES9NQyFtYYbEfzgsltMvWiKIHE4tRbSdm51b+nEJWZmwPLRTZNmdpSCRslQE/S/UIKHKcjgqHrNlxe9JzvHvLR9z9iiJ4owkTEOEPv6xtd+wfDg/NLHl4+JInlbHNLCpGzfoNLwJjl0fqOKIEugUfoOo/vPLaWzdDA5ZNHT3jnc7/C7uycly9fwGHEHCai7Yg9uBDwoydgOOaXYPIRGxMYp2IcLmBcIMTIFALH8cAUIsYmvDecDzs2mwHvhCkGaqmF/FK3zuUXqcEZdQBDVOfRqP5JltBKd96B8wva0vmOJw/P2HvD1WFkUi0EpunIux/+KUkSb7/2RZDEFBJjSJRwriFR5QcwOuaKDGD9G6YxcXsdefHymo+efciu33IxXGrtURx+e8bFW2/jLaRxj7NNC00ZUjpGU8yKEVmsIB4DKaS6iM3VKHTYALvzjs3Oc/V85PbqFuctm95xvA784Oqa8zPHwweeYxJuboXeOVzfMY2Jq+sDKRlSSAhB680dj4yHPcdp4hD2eO+x7glYlXv01vLlL/4Kn3vzdd7/s+9x/eIlPgrhMDJd3zIKxHFkdmJSHvPZuTW6aPG+o3OW7YVjGHouLs/1GcpOpLWOKCD7oGQlEkYSNuUfPzNnK6GgzEkGuu2G7fkFm7Nzhs0VzvV5stFyQ8ZacE7blp3Ccr/nbIAyFcyOoIjk/soLNgGT9CbqbvMirEwj89jMdWCb/9ZvK6GlGciIOpFZuUcnkZjHTqkrWhawuqN3HoxlautJNs6spFybUnSUi8RSMyoPxnytUvRufsg6qbnIeeGS+0QEktYcMjKr5rRlcNqf054CZlUSaRYNdUEWoTz/Zd7ID5TeX68/WLwzvPbma6QYGXolW0l+ZzAFUhSsGzDGa2aANwgexGGd4C3EdIApYK3Bm5whkqK22ek7wjuHkAj1nmYyCJUHv9rPyGI0/JN/8g7/4l+8zX/9X3+dv/t337uzzR/8wWv8w3/4JabJ/ci15WqrrbbaaqutttpqP1/Wn4+8/psfcXwx8IM/eI04/hg5TKutttpfuM0KGhq01fIeZokH1ITBDIphGvyWBd6y+L38bcGI0Z8Wa4vMQbQCTpCxwzZoWrBj5n/FNNvUbRvCQpUeyN83YdG5rVAy6Odm5KIYSYkNpcE1EFtwHjH1Oow3fPHv/E1+5W/9Dc4vH+TAupZWt9bRdxs+/+u/idudVZzCGKNqw7VN2r6hG9gMG8WgXUB8onNe2xcdYjW5z5FwonejEEJKOXaTySu77ZbLy4d0/S3D4QgxQoiIcSQHNllsLsUdTC4PYkWz30uCnE1gCtEjEWIgJsFYwTroXYf3LpfbLmV6YR5WVhVFTFFa1TIfFGIBSqk50UhobpD+a61jt+mYRhhDJOXvYgy8vHmOiHB5/ggyISVWFed8VGmPJ8zZQGUAQQzCNAqH48jt/obOdfR+yCPHYn1Pf3GhijQx1IRa0za3xcjqWIcYUi0VUThJBatMFo3ddJbjITKNGeNyhjgmrseRvrNsNpYowjihz6l3xCCMY+D6gw/503/6Lzh/9JC//f/4z3GbDTEo9h9SqAmbGE1ktMbw+NFDLs/PuXrxgvF4xCZIIRLHsSYONoGYGYGtN8rkRFNDN2Ri0dBXfFHjP3qXYwVD9b4byT9N/9djV5aOYL3Hdz2+7/G+wxrHQq1Hs1YXnASTwco2xjVbwZALwUDPo+fNrRHmRFCZW1dnxfLs02LINOOs+aiOtxNcWcoIlnKp1GcHJXxhcsnu0vEtkapi5iW2Va6lnX9l0S/1o3yti76R5p8FEa9tgMy7NH1akhs/DUNu++ROW3INrdOExHJvNR6RiYfWcnZ+hogooShvIwAx5cRrn0lwaKySohCkwySJKkMbozFJzSmclaoNJpczkzrHzNj+3RlqtdVWW+3PYz+WogcUH3l2cG1+mZs6I88eyMyuLRO9VOd4/rSJ6pUzVacmy+s1zkr7qq61DUWD9TGpky+lHmLxgNoXhVm88hZvg7ZV1Wy9ksWGhvn6UyaC1L6BnO1tafyQ2mfzKeeFj3NOHTDfYVyHkbhgsWq3SX455PI4VhdDXee0PuPZDmct4/6AKWV1jG3WRbMySeMuYJ3Ddx3DMLDdbglBiCaw3e0YNo5wfcv0/KqWmkySg6ut82kiZHm+lBIx/6svPUPvLb0vZXto3uX5xVgWfbnkj8aNW2WL/FN2k4WvW/91zrLd9KRp4orZZZymyPvvPSWmxGsPP4eR7PLLXA9wvitFQ8ICjhyVrz8q7ZXl90IgukiSkMchGrAWJTxgTDOe5/GRikID5Hi+1jysMezsHNbxnhcrukBIxJBISTBRHQlJRQLS4bzDJ0MXtAhJCqq6UiUDU8KLw7sO76KOL1HHOwjc3ighZBwDrks47xj6rBqTpRkxBt8PDNsd1jlSDsBLUknElvBU+s0YXZA669RB0roi+nRZA3Hu3/qclemi+j1SO22+dyY7Z/PzUv1HY2pJp6Xnt3gCF07oacZFO+vUdsGdcdOsqO6cx+TMi/mkkp2+VGY5kABpzCPPYSRh4giS8vgSwqSED++1JNZGzsA4Eh2hnWyqI3u3LXe/mR3xsjiWOx2z3HvOXtC+kfbrOsWfzOvMz/D8mVkuTO6029RHT5JmIFT2f2WiSCXzGPT94b0nWa05a3PWiiCkBMYkXTRal5V0ZrCmCkk1bOy6pjFF7WP+erFOaVj/K3HgZ22GcfSEIJ8qcz1NlpubjnVBtdpqv9wWguPm5gyR++cKYxJnZzd4H+/9frXVVvt0e/jwyJe+9JwXLwY++WTL+s5d7adpxoKzCevTOrR+zmwcO25vd/y4N8YYye/c8BfTsNV+hlYX2hVHWWLIy03v3XcBOtzdRP85wZChUcWXGW0SQYOdmYhhSuDyBEM2Mxp83xJ/iRSZ5T93YBlTkUbFuDJ2vOyQBYZujMEPWk7aed9ejAYTnSOMI9fPXtBvB4bL8tyZ+TIKHmln3MM5g0uKI6tCcMCkjKctAfT74LBKsnDO47uoGBIplwPvSeNEOhyrOonGz2eMpdwPkKponBplilLK3dU2183n+1JwnIZ40ypunN6wWdlgadZqNr+kxFh30zIw11d7kghn28u5CfU4y46RmjRoKQq7M+Y/42EpJZJNTZJQxpCbYO8iRFJwKWm6rwaImyZIc4SMnRoUV49xVo5uxTTKrtaqgodLmZAQZww+xchxf2DYjjnQbec2JSXzTGNQBZCYsFbVD7xXhRdn5ntoncd1vuKJ0maXtffZFAy54Ltmvt/tA5ak7lJvyXz5P/QVZPJcZJrnpe5cfpbgZYUn23PdjyGfnPvkEV+Y3N0O8pio5yhzWu6XvNu4v+Hmk09yvEBVSi4eP8jlu/VGp6gnsNYgKbH/+JqUEv3jV7DDZj7x6X24e+n3NlTH9T39cmJzd5507OK0JxiyUUXsO3Pv4hCn37bzhTS4cdk8P2vNuASNsYmgMbScoSsIYq32b5mLSjubezoPy7n9i+s5GWL33fIVQ15ttdV+GvbZiR42M9Hyj7UG6wwuEyFKgrhp/qffzJOnkAkCztZAbWE53y0dkFnZZAfZzMFxVYKAKJEkiZSU8W2qDJm20qGszNrqheOczxObidlmZYfCAjYG42z2Mea3z0zysFXVpDpI+djJeayd5ZwKWxCn12utwebXpWDpO8u2c2y2W+zmjHQEE4+UshfqLqZ8fmVUK7hh2O16vLcM3cDN7Z6b/Z5DCFlFYcLGMauQaBOSqMRaYR5aZzHec7a7YHADV+ETrm5H3n7rLd768jt8/zt/xjf/8Gu5pYIzgo2lDAxABDkickTClEt6TISUwIHrLWdbx3brcj09l+91bpOxOOOy3J9HbEcUwxSSOiVJnf8oEEXrp6mU4OwmFMZ23zlee/yI58byMR+pHCDC1dWe/+H/928JMfLld36Vs7MNIolIxORgexkoUQxTsiTZAGfAHhqXHyNgEhIj6RiJ5sDoIca9XlWYCNcvoO+h6xGrLHSbnxURiFGdrlKjLxw0gJBCqlwBY1QkAcB7wYpwezVy9dIgMSIpMgUYD8q8985hfUd3fkGXhN0kjFPg9uZIiHp9SYTDMeBsx9n5Q7w/4rsf4KZEON4ypYl3Xxxw3cDZozd4SI9zCeth6Bxh6PCdw3rH+auv8crrbzCcbYhxJE2JNCUsXtUzKM+ZEGPAOIvL97gszLzXKShIQiXRYiZAKInJOrBO6RDkKahd382mT4g1OifVNYI14CyCUZa7mZ3lmIk4ZY4pR1kusaiLXSmqGuVseZ6JZTFpCiOhrLDyBpnQUSxlcpol4s2EmIQQkbRHDk9xxrGzG2yacNMLJE2M0y0hRG6f6+LqwZMLhmHDo+5zGLPlzzgn0Cy4csDK5Im1KMnMDIW7vVeuPSQtR1UY8Pf39ckqs/wjzWmY3we5UXP/LO7h8h0wfzmDQBJFiUjjmElgUUlRMZcvcjnTJJ+t63p10nN5MeuU1GGdlm4xvsdYj83vFAUpLJoBkBdE5ceomlTnVS3EdQnrzaKpgoIQZYG82mqrrbbaL4ZdX5/zR3/0m0xTf+/3w3DkN37j33J5efWX3LLVVvvFt3/v3/uQX/u1T/i933ub//6///IKYq622i+JvXjxgK997deJ0f1Y+3XdyG/8xh/x8OHzv5iGrfaXa2Y56Rc80jbYSw3IYhblXFpyxYwpN6VImhdKjeMVMkjNFMrB8Jz0UQKybWDSpCUqYbI69YwPnazt5STgbpotSiKSNXcieXMc0NRkvNPq4hpobNVBS3RQr2eGcZQu4p3BW8sn3/4u/9t/9//l7V//Vb78f/rblCSocoS5R03F4brOaQlle8k0BcYpEFKq5VxMLoFdk1tQNYsKJ2Vl1b7r8dZxTHvGKXJ5ccnF40tePnvB0w8/rlitJgy215CAABKoCYMxqz5bsM7QdwafkwVjLS4ii+uxpYSvsSQxxDiTB5Q8khPiaiC+xZDVnDOcbbccMNxyQ1GRPo6B73zrQ5IkHj94Qt/5PHoSpQRwOViqCroe6IGJWR26nDe3KwpCIFqQNOlVpUQaj+AyAJrVyduYu6RcVqPEHEKaP2/GZFVuyPDnNEbGYw78S1YkCRqrKMmWth+wInRJseppDMqhyI9aCEro6PsNfthgM8ad4kSUwMtjwDpHvz1HxGksJMcrNElNYyv97ozd2Tmu94jEnMyliVvYRg1eIKWkY9RoomAxTXhVRWLFh4uiR0Ygc+hF5tvNya+NlcTTJuDeRu4r2SLj6eUZuudgCwy5HW2m7t7co4Zw1v47TybQMHck72MkYU3KDUg8//63+aP/zz8khUhnPI/efI3f/i/+Hv2mJ8aJJMJ0UGXiYdcT9iPv/g//ksP1ns//F/8l5597p560Fkwv8QhKF9zFjxdNhZos+OlI6DwnL0D3BkOetyzPUrl+WUDOi2P9sFaJPhsxxvzoJURsPW5NFM2bW6v+SsH/TY53GZuTTMtzWe9l3uYE49Yf3cjZHCt1grmTUzKTl1ZN6NVWW+2nZT++vqWZX1CzQkTzUi1vA+YXQ3G4W3e1qBzMYcTZeSd/HmMkIYQYa/03Ywwmy9WFmOv6mayaIOpIaZK2yYH12rT8e3MB+cvWmajXU19uZn6xSPtC1l1sOfeik9SNnF9Cdy0l1AnNbQWyHB0zY7XpvtKj5UwxJa4PR1zncc7ivafrLX2I6nQVRQ9bSspIvWeF0WuzUyQl2Gkd1nuMcWAMvvNsN1u6vsc4R2cMzlumaVJliCnMXZkbKfNrrfFqVLFEZfcsVdVkfl83JXe01IT2X+7B9qVeWd4q89cG0HXxo+QB53x2hnS/mBK3N3tCjKRMskiZzSxueZfKQnF/2PPy6iWbwdB1uQyIKfdIGEPg6vYWYcPQdVpqBmV6Dn2H9Z6p+IfMi9RyQeU8d/mp8/flgZPcXq3rOO8jeSwV50PvrS4UJEZEwPsOjBBCyOSRRm3F5PueVTgkCSEkxATiNBHDkeP+hhiP3B6OHMdA3/uqKFHuFVLal7CufV5omNrzGG6Z2cV3UxZyvrcLNznf9zK/mDLGlu6QqX0UcWmWZ6wOauMQLnrc3MEDZsfdmHkk5kuw7WBpnLr2LrfnsDJi4rE+DiZnKyQJTDKBEYxLpGlPOu7BWKITIODSBDJhTcBIQMIxr1qGXPs0YInzeLijiKEM6IUU38k4K9c5k0ROyR3tdstOM0bq9F/u9cmGi2NIs3u5N+08ea+73j7IzQHk07YHdcChzjfWFnKegJUFE1tEF/e+M5BAUiHMZAZ3UaspY7nROFw2bX7R3EePWW211VZb7S/fxrHjeNx8aoD55uac43FDCN293+t7boVencAtSgABAABJREFUVlvtz2PDEBmGyGazZuevttovuonA8TgwjvcTI1vTd+tASj8e0UPEkNL6zv0rZW3QkBIANfMXLKDZBdxQMeQaaM3YTAMVGQxSAcOyPp9LeKhih9STpFJuNWPUskAjKgywtBZUyu2qTaiYp5yAHfPfbXvLOaSUmmnA6Dv48Uk7NOElb9W0P0wT4/UtYZya/jrtc8XKxhBz0NFgxeKcyQSOOeg4Y2wFHFOcUBOnMhInpR0WU/AVyEoOXS5/oGUOOmtISXFnyfh0jRiUcMIpgiKmISLMmGjdOWP35ThyetFNv0JRA5b69wxE680p2HnJTdL+FqZxyrjxjLeVfNU7iJfAFCYOhwO+00QgjXOUvlJcepwmEI9zTscjCvF5pyq1pxqCrUrNzAc4GVSn2N585Vn9uVGcKHCWmeMWkrLWTW6PtQ6SZFJBg+lSYhQZy82AWClFpErSgWkcSRKZQiSEhBt8cy9nkFykaVvzvNTRUK/X5OffzHyuvF0pTbIcAPOxfhiGXLYpajILDJmM8bUMhtPTnGLIn/L6MovP2wkk/12fZ7Xj1UvG65ftHiQR+u3A9mKnu1rBmITfdEiw9KbDD65i6sYkSAmJIc8XDmRiur1hutnn8jmf0nelg8uF1b9PJrKCqTZHuXvxzS/tvWriJHfOv+ytelOWW5zMC3cacD+GvDhwe8Aat2zmQkNDfDGLXTM3iabOWP12VqTXnWeYXOq4P73uFUFebbXVfhr2YxA9mtedmTOg62RZ6/bluoptinzzUmzLJJbfBKpjWFhxMQb2xwMxJQ4x6iQZJowx9HEDAsf9UQPWVmtoOSO5XpYyRr21yrqz6Ilz06r8SK6pRS6Z0TZWKukC/b4GZxOSZkfV4vJGqe5VHPAkqV5TIUBovbSstHAIJBF8bwhpIhwnpjBiU2bfFiZ5kQyRuX3XhwP/7t3vcX52xitnD/DOkiQxhUTXebrO03tP8o5JDJKyo2wsxzFwc3vEWlUSCDETNpwDgWQdEYMxHu86Oj/guy3b3YaHjy64Pez5+PlzrswVLz5+AcZhuw3WDxgn6nCgyiOSLIil6we6YUPXdXhfZN0kl9kRnNMSNFhPMp45KJ+dvkwISEK+5yGXDUp5DM0LDd8NON8RE8RUGPuBGG9IQTP6UzSEYJlCrp9mZ8cVUXm67373m4i85Mt/7dd46813wBxABGfAm8QnL5/zB98JvPn4CU46bveBMUK32fL2258jpMgHz55iSCSjuiGV/mNMDh5IDTSXoSnkBZyA8yobFpMQRJCQkCi4rKohkzpx6igkjoeJ509viSkwTiO77TmvPHmDaRwxz1/grCNMgeAnTDhg4kTvHaHrOBwsCYshYSQh40vG68A3vvVdnr98SRiV1f/Vi7e4uDwjxsTVixu2nYfthmmauNmP7Ax0g63P0Ez2yM+YsTjfVeaqMpN1zJMCJsW8eIAkVpU30GdYyxfdnZuKlsPxGHh5c+TCdXSDelCV42CLo77cuzarzG1y8qXREZaKk1hqBIpkklde9OXFV1mAlAVKN33MMP2AEJVEE6wlWsvhMHFzM+J7x7DtiMeR8cUV3lrG4ZrOWXZbj7UdfgPOBbBj7s9EkkiSEUm+PispaY1TW9nJubfy3GEKmSYv4ApbvTyxiEr7SUpocaPaxfNivPj5xePN5yq1ZpMUR7+lI+UWtg7tHeDC1PEy72PqfgYljCURSJmmnzM7SIKYMp+UrA6D95nkYW0dbyllucqUEGcQa9jsLGdnluMBjkctAeUAJBDigRBGQgi4hNYinSZSiqQEUkpN5QWivWfxuNpqq6222s/GPvnkFb75zV/9VLJGSpYQfnze+2qrrbbaaqv9stl7773Fu+9+/kduF6MjpftLoq32S2YNLqwqEA0+0QZ9T/Dm+m/BYJpIqX48Y84KwRjFQ6cJESHkRA2SSjg78SAQg5bELYkhNQ+wJobMxIIFll0+S/N5pQU2ciB0JgCYioFpAJ0mkGw1ASUD5BU7ybiZy9czR6l1ixgTk8k4tFOl5hQjKcVGuNZUXGuOkKqNIfDRyxf0fc+uG7Be2xiT4rHOqZqHOEsKJpNRFCeKKTGGnGBkVHlDg80aQBZjs9qBYs7Weqzz+M6z2Q5MYeJ2f+DIkYM5ABbjPMZ6jILfucm2YlfOOZz3OZGxqFeUuGomqzjFhWoCWsFb8z1r+1WVOMj9Psd5jSkKsK5iziXhJ8mk2Fi+lykpGc1QMvTzUXJg98WLp8CRx49e4eLiAZgAMmmSHcLt8cAHzxLn2y2PsUwhEQWs67i4uCSJcLPPStGngenmMahtb4dgHlI2lycWEUIiK2SDcSaX9KjdBAghRA77SZW/U6TzPbvdBSkGOBxxmaiTYsSkgJGon1mbz9OoGsQjcUx88vQ5h+NRkywFXhkuGIYeEeF4nPDOgvekFJimnLDrypgnB8NlvjhjchJrJvVkYFEfI8Wva9hJzCId9P4Quqn/CyFxHFXR5k4Uvj5MTaeXIzYY8v0kj9PjtDeujFaZv2vIW+//H/+a7//+780YqzFEY3j9136VL/7d38V3Dtc5zh8/4Df+L/8Jxhg6Z/Gdh74nYrC+0+fGxplMJYIQSTlJmmaOasuYzJdgZiJNOUZuq+RepEmG+1EJbyUxvB6jEiLmc1b0uO3P034sH8vyGSgdXDBkKGWJaOJpzU0UMoZcFI80Ybxi6QZsiRXlg0p+h/lOVYdCgBgNNhqK1kySoHh9UlS9zNWLuEhtQnnSVwx5tdVW+8ntMyObpd6caWfR4lgXBuZihp2d9oVLbswceKUE6E+Dr5IdzkhMSevJKQ21KhKQnU1JUp1kDXmbRSmV5VHvez+Ul0Cb5X167cXJkxrIk9m3YPESOg0SN7/PLFghxUQIAUkRk0upxBCIcXZQ5sn+/gm/LEKKw2Ot1RIe3s/yaE2WflnILI83H6MyEo2p12ZyCQ2yUsZmsyUZw/Y4ctyP84InH1bqrdex4p3DO68lcHLZHtOojJS3r7ImbWX4lnsCzA6H0bucklImkg1zn5ZN8gISY0gplz6pDqKwGAXl9HMz8vEiEBjHI/v9LYfDkfE4YlyqainOqQRd13WIwO1x5DgFBMEaQ9d1mGTpnNOSEGbJ2J/vQ9OWes3zwCmMY+P0/sSmVmKprVjC+YsxbwzWW2xncZ1FxNF1WRYsOxnjcSRMoWmPmnMW76w6KZI0Q+A45ufP1HtiskxiYbyqokjkOB7hZmIcj/c8h8s5ZGakl+4ozqEs9tEF8123sYbUWyd78TA2OguF+l2P2q59P8VzXJ7s/j/b2yjLvtQPA8QjhAQh6cIZR4gT4zgiOFyXiGEihIjYROcMiGWc1NFMIoRJ1VwQYQoJ5xJBVMrQe09vOo7HqWZ5tNck7Z+LKzB3PlnUNV18/aMcz2a/k4Da6Z6LJWv76502zk743N93Rrs+J83OJpdxcVnqc74p8/gtf5vmhpXnqjyHWnYoZWJfUfVo21MeXOoi6VM6e7XVVltttb8EG8duUYbl9nbHfr/lzwueiBj2+y1dFxiGA86lH73Taqutttpqq/0VtBA6DoftX9jxRQyHw5abmyPDcMT709z21X6RrJBsFxjy/O39O90BU0z+/4yNLrL9W+XSFrdN7aJ9TuoqJQYKpmsETX75tGtYtqS2omIBFYg62TjjWlX9wppStfyHY8jttZFR7tx2xdtSxVElK/XO+E/bT4uGzt9nFYyK6+WkmKJo0ZYymPHYk05gPobiryfnaOIBqvChastdF4khLvuMBjoympikRJFc48eYSsKp/dE0pSg83CHfVAx57jshKY5Pwf/rBdWgbgNRl9ZxanXEtRiyEQyK60/TRAhBS0aYRi3FatDZOu2wKcZKLjAGVUERLVdiSy2ROxhyOa/e5zkSsmyfAchlI7QceItVfcrVlb52RkkXWFxucyGyxBhxWQmiHRcmt9nkBqaY7/UCIK13rOlvPW6IEcZETJ9BAa7BkAvpR9ovPv0Kl9Y06zRRa9FkabcrGHI7E/xonLRsI/dtf89H02HP/vlT3KClcrCQrE5YKUaiBeME4wzD+TnGaKlpa60SlXLCqybx6Uk0CdawubwEOxCORw4vXuK3W6z3TRvmsfXDrqX9pP33x7bTA9T724L3P2TgfpYTV8y/HbQnD4Qpybd2nhuqMtM8Z9XYQtsEmefLSiwr8/Qi7NO+r1hiyPfVA1pttdVW+zHtMxM9kvh5SjQ5e9oIVmnSaIW0Gfw0ToPTc5DeZBWN7FkVEohRZxwECdkxz4G1EHP9uKK2UQLLxoFoiHfOos+bybx9UdiXpGzb4rQtGIliaqUIyYoBxRkDVfqIMTGOY14wJDxkJroQJJBSzIoMZQZX1YfCVm+Dg5pxnzgcDoRJCMdbzLRnuj1y2B8ZDyOpkZRTd9FiEVzzEjobNnzlzc/RDwPHMRCT0PWGIfVcXO5IMuVSKVk+LUa9BVaVM/q+p/PqFG+2W/rtBjsFfIw47wgCMRmiKDNbjMENA7uHjxhS5PzyEb1/nz/79rs6HjggjMoUcR5jHd4aHjw85+Gjc7qhx3Yd9D2mj+p0SMSKwSSDxeKMy+QEAzbLLdb7DsYIIQVujiO+MwxmltZz1qjUnYm4Tp3o/THS9ZEU9T4724OLmUwiZSjXl3DKtQ3F3uoCigkxhqeffEgYj7zy6ms8fvyEvt+y2w188a23+I2/8at88uIF3/rwAz55+RxrUmWAdr7j0cVDHpxd0DuLM4aQBCQ77nkcCcqiVhUPDSYXxz5FJTNdPj5je95z9cktt1dHYhDCONE5y8Ypm1rQWpvnZx122NBtHdZ5TDfh+4kLb0kThJuRwyHygx8EdfxiyONL27Pb9fRDx7Dd0A0bdtsN03GkMxFvwAkcj4FH/cCjhw8YNn2eIxJTDHz8wcc8e/EhH7z3vFmU6vNkWzUMUlY5yc9K0mOIRFXuMKmK78Q8bVDJO/lBEJDidDnYDD0X51u8d1rqSQSfj6GqajovFDfb5Me/XWOXhVMm9s5x/LzASfl7Vxjs2QEUKd8rI1czQiCGxP4wQVSiR+wckxGOIXBzDHQpEgnEKTFOQmdVMWYisd9rBkEMk85DNyFPnUc2W0t3cc6mf8STJ6/ypNvw3gefcHO7rxczJ5zkhVRZhUtU4k5xdpu5MqWEaD2gTJ64b/HSKuDM+yqbfu5fmmeYOqN9igMrM8VHf0ydpgtfqyzKJamyUq3nmsr7SKegrteSVmdDj7WWKU6ahZISUQRv9Xm0WRgkTMLLKyEcJsKxSE0Gpkk47C3jUZAwgrdYZ6mqKInK0I4p4pKSqlZFj9VWW221v3wTgQ8+eIPvfvcL9bOfVK1jmjq+/vWvMgxHvvrVP+bBgxc/YStXW2211VZbbbX7LATPN77xqwzDyFe+8jUeP372s27Saj+BCfZuSNDQYAwngbYS2F9GYKmgDFATzUpiRirlVjOmp8v0OTjHHFouv7dZ9ArtZODELjPBKw+ghUTKcRcwSQWZ63cpaeJiaVcpL15QMBHV0m2DqwWvoj1lwSvRUswpQQoTJgVV6p00oF4C3vN/Te7uuX9773lyfonzjhi0cLh14MXRD522yRZ1WmmSBU1OdnNkjgK+63DeYzIWY3KAWeH7uZSDdZ5u2OL7RD9scfaK589eZgw5IMQcK8gkE2cZNj2bTa/EB+vAOXCpYkF6qaWMx0yi0GPOgdnCk1Dl64h14Mx870r5cGMSuXo5UxCsS+QQBdY4ki2kkHyHmyE7Y/0TRS0BDPv9DSlGdrsztrsdznZ0nefRxQWvvv6E/eHAs5sbbg+HjB3mR8A6tv2GoesVr8Kozm4p9cMci1D8WiqO1iZ5IsKw7fG9Y9xPTMegWF8UnDU4m8eaGJy19L3DeKMq3caCi1gb6a2hG0AkEsLE9fUNvaC4X+5fi6HrdXz4TpVcOu+JXcSRVdfRuMrWeTabAeddHquiZdYPt+wPN1y/3DdTQokZtXF6mfHb/DyWlF9yzEC3L6oRM47YWpvY5r2j7z3OWk0qrs/rHNSfE9ok5w/OM0p7PDN/VMNNlV1U7107h+lFiMzHNuj8MYXEW7/1Zb74t36b6AzBWcR6piSkEHUmSVmRxxhs1PhBmGLFTFMS4lSSiSPWdXzpH/ynpEn4zr/5Y977t3/CO//B3+HizTfqfCY0GDJlTjKUTNNmymoSZ0uw7VNw0HLslkVVJts7N6j0i61/Lb6659BzeGDu/JKcXe9PPdes0CNofMMYrVpgjaHzWjEgpZSfvayiVOaajLGnCEeBNEWNYUa9JzEJYTLEIEiKqoBtTeWVVFybubRYmetXW2211X5S+7HQz+o2ynIyveO83/nG1N/bl277/i4TXTsRF7Z1e8I5Udy0h72/La2XXtpdnd3lRWhG+OzoFzJIoiwY2sXD7Ezd+6bJF3of6bB8VAKD+9s9Vy9ecjhOHI+qgoAkZNm4fL21gVhj2PY9Xd8Toi4sPJbORzabDeM4zrURaRxQlETgrKmM7apSkV9oxs73p30PG2txnccmhzWOvutnMkv5X6Z0e99jrGV7tmV7ttVSHc7hnMvyeuUlr79bo062MpyLf9B4S/mFKghRIjIpm1h9OpUaTN4RlNWhHy/Y7Xr8lD0nsxw+zc1RRQ+RSWt9GsMUAsfDnmnUYDuixJJh6Hlwfq7OuW1ITfV8ZTHkKMvLO8PFgGnUD5rY+Uw+yIuZ2bEw9RprFxnAKTvcdQ7nHb5zmf0ewSS0moUGpU2CSKiZDrU/jGEzdPSbPpNRyqLO4g14o89kiEpkcE7JRKWdKUXGaeT25pZxGrnPFgs0M1+rfp4zFGYXbdEZ7Tg2d46ZF2v33It269J/5ZytM76k7y9vVtm+yFQKbr6G+sDofrLIhFCfWKIgMREMTFZLF9X7mNvlvRKknFcyW4gRAULKc1AmlEUsQSzBCNEKu02HG3otp1XnxEKGy9eSdUTrgsSwGEO1H9NpTsCpsz474nLSX8u/5/1L1zR3Qfdo2nDalnaPub5h26nSbLks6VOyIDQ7xWDi8l1UFmy5wstM2IiF6CL1vHmtNzeuLnTI7wFZtM9affZX+9mbCNzcdHzyyYbdbmKziez3nv3ec3vb/aybt9pqq/2UTESDQyF03N7uuL3dcffd9ec9tuVw2BKjI8Z1bl9ttVM7fddut2sG/mqr/TRttws8fnyoPuxP7/0G4ziQkqHvx58TxSrD8bglRk+M7mfdmNV+Ctas6H8IhswSB2gBGtNsew+cVvct8K60wIKpX39awxZ40B3QQhoY5QQ04QSDkPmXikAv8AoasO8eQKva3Q8rXpKxvBAmjocD+5s9h5tbDjc3FZdYXK1pD6B/ds5hnSOlkiRjsFbw3hN9xFpXiQQN7FOTmEpCZFFjNsZibQl+n/YFYBSj1DIwio/OAq1thysubYyh6z2+1+TBouYx43sFQy7Fh1uiR3PdJfsoY8iJpLlOKdXDWKNlfEvB4jJ+5tuWj13vV1MWeh5w+a+EKeUwDMSk9ynGmBMYlcfknGPT90whZIy7ud+VtGKXeNK9A7h24swXYP73znNm2qg3M9eglKlwRSG8ECtSToTVHYRMHIg5KawcNh/LO6dlx3OfFxJNSbhDcnlyo8mnpmmoVCWUkZjx/PmGtL+KYudm1sWY79nJxouLnz+rYYZmvJo8rqfDkf2Ll/TmEtkOC7GgRTeeHHp5S+4iqSklDjc3SEpsLs5xvtOrMTDnSksJggDQDRu2l5dsHzxg++gB0VmCs0xT4niIlB4waH9aU5RXchyN8u983ITBGsfmwSUpCnEcGa+vSCE2HaOtnp+I5fhcjKGme0pZqk+1ebjeGc9y5+YsN1vE1U7G9+mR9B8zn+/OBP3pGHIljZ0+l/dcSjlUTRZu540CVZ+8h9p3zGmflTjpaqutttpPap+Z6FGn+mQQCxJBwjx3GTForcFSl6pMoWYxEWayblP3DsDRvsVNjr4ldS/q/1JKynYT1QFQB6gJHaY8hTpYyjDNzhdikEBWBogIcf5WDBKMSgYkZUUnY9WRyYHFBNgkhKMGsZ1xWGdU+g9mBrmx4Aq3tBA3yIFXQ0oBJPFHX/s63/zO99jsOja7jutnz0nxBklHUm5vrizY9JEe1QLeOnbbcxKWAcd2p+VMXl695KMPfoBBOLx4wZRSdjYD1iS8lxzItxjjMbZj0/U4C13fZ5ETmf9rtRRIN3it72cMtlPnG2tzuQPd2vcdr73+Dt3Q84WvfonHrz5m++ARBrjYdbio5AARvYfOCN45OusYOse08fjOYJ1gbAKjLGCX62iKBJ4+f84HH/4AiROEI6ZzdLsNm2HLk4evKHs+BUSCBt2twWWswDstvZITBsjsn/ziNcQ0KuHAGkw3kASmMXB9/RLj4HZ/Degi6Ww78NYrT9gNA99Mlj/9k29noqs+BUYilBJEaXYkSiC5LCqdU3WBacrfzcU9AcP+6sh0UMa+luTRxVJKiUNIDL3l7MyyPevpt+dIGhmv9jhvGTYdaUqM14EYYBwDg/WcDz0ihkOp2eMM3npef/MJ2+0GixAOeyW8eEcUixg4BMEeAmOYiDIS0VIkU4wcx4kUDJ4NjmNVLpHsACUsSQwhCtaCd/p9jEIIiTAGLV+Sh3mMKoRR7lGzlqr9Z0SqEkVh3da6prlWpz4x8z5lXph5/uTnDGo5YWmf2tmpP45HUkoMVokuZZ1jchkmsU7PmcksZalynCLH25GDsdyaiDXCdoCh95xtBzpn2foO6wy+c8QUORxuiZKYYq99GJW/7vwG5z3H7iOsu+X1J19gODuj+9DBdVmKkUlpOTmmXdHp7JWvMZclgayUMS/eqm9KFmRqCG53SB7N7/WBMnYm58m8/32O+bLkDnP7y671J5fywmTlqLn2aszztBGwYkh5AR1DIkUQMQi2Zsok5zDOKh07lwhLqDrIPFZKv3mwLpO6cnaSCDGGrMgDxjjOdmc4twKTPw8mAv/0n77D//a/vc4/+Aff5Xd+531+//ff4J//889xddX/6AOsttpqvzD23ntv8957b3M8Dj/rpqy22i+Vnb5rf/d33/9ZN2m11f5K2e/8znt89auf8C/+xdv8T//TOz+146pi1Vc4HLZ85Stf48GDlz+1Y6+2GjTkCFHsrwVlCgSnwfRFjHOZGF6W4qZBCQQ4Ldid1QkU+6mIRQ0Ai8xlom0bu1wEEZf4RjmGQdutUMOMlJa2FmVXBUqpWFDZQFDMKuWSF9bYXOpDt6nVphs1j/baDCZnp2sjPvz4Ez559oLv/9s/5L0//Hdcf/IUkREkslRQvRvcNPn8XTcgGByGrtPjHrdHbm+uMQjheCRllYqUEsZIVS7ORwHj8J3iRDfO3cV5Mg5rvdWgaEy5jLeWZWkz262znJ09wHnHw1cesd1t6TYbAIbOYSXmOHNO6MmBbWeMltUmJ/g0/ZrR7ozbJPaHAze314p1paDlsTuPd57dZpdJQqnex5IUZEvJlSabf4a8TA7sKqFDDOC8Yp8xMU5HzC1MYQQBlxW2L7ZbOud4KobnnzzLHZefiNyGk9ymhh8k9ZkwxmQMLDepGdthDKSg5AyFRm0NMIck+M7Q9wbfO5zvQSLxGLRfvQZt4piIUyLGgEiktzA4Qwi5Ablfzi62Wr4cSCHkR9TWSEhIgglJyyJLzPfdEUU/kwSWDktcKJPodhnPTeg4rN9roL0owpcBWPutxZAX4zL3YZPMK8D3/+iPefpn3+PXfvdv8+A/+t15H7OcGlrOQu3ue3IBynfhcOCP/vE/4fb5S37rP/sHPH77TZ0z8oRoRKrysuT7+9Zv/TpP3nmE7wcOUyQGYULvY+e13HrfeVWgsC6XBbKVCKZKKU77oxBsjMc4S3A3pBTodobh2ON8i5DPg60q1pv5szLvLok1baff3weLOa0JEM5Paoshz2WuTlp19yac3tjmXG0UTZvZANt23j7lq8p5vlndOqsapYIhM8/PpaxUno9ryt+d90eZRPJEUhFvjWkWkogxRpOofwi5ZLXVVlvts9pnV/RoAm5FIqxO7nW+PpmY8txWXlatZJUeMn9T3g/VzdOj3W2CqghIfmGXcg/LAONpE5qjSvNJZmQUxnchKUi+1sLISybll1zrJmdnt55lDhS3zsAyWN9cmXr6JEm8fHlFiFdcPNhwHrZMhxtSHIkpqLNiDTYHr01poZQXQ5YVM04Dj9ZjjGV3dkZMic12R7/ZYp2r7ZB8n6yZSSfWWpx16iA7dRDIjqAtMlNQFRySkXsULPJ7NjOQ+37DZrvh8sEFl5fn9H0PSdj2Hhkc1s4vy+KgGqtlEVw+7xyDLwMs3wURpmni5vpGiR7xgFhLOuzZbo90bsPtfq99VR3gmbFd2JJziL956Zf7T76/2RkujOxpOmYnV50sZy1D33N5dsZ2GGYnoA6DU+/DVIeznEtPk4kvhXjUMguAOKW8uJzLCoHRokmtKofJZ01CGAOIJXlLDIlp1GB3SiAm4ayWJqqrgbwQ6/qOfuiIk9TzWWeV8Q9KxMLkTII9m97B0CGisnva7Y5C+Vo6d43T3qw7JTugMZVxbet2SYSSVFC7TMhs7uaeicoXxhjxucZgVeBBsKfuuMy/fprj3m5YTpVSzG1MQMlIyMzfPOCMNTiT/b/OI8NGF0NOS46kqHUvrS8KJA5rHV3nMc7gOgsJbNJ/k1MySyURWYdYQ5QDU4SYtNSIIeEshHTSfimLcqGU0Vk65u2fctoB9RjtnZx/Xc6t86FO5/B5vi+nOPXP5ylF6mELiWNxmOaDOubr+eb7K5JVmWaunn4vungoCkYVuCnXX45blFlM7vdmxW+ac8z76Bzp/U9WKmC1n5YZnj/f8Pz5UIkdL18OvPvuBff5GKutttrPt4mockdK7s7nt7c7rq4uf0YtW221X2ZbvmtF4Hh0HI/zc3o4rH7Rar9IJgxDZBhiM5Z/Nn6jMfDgwciDByOXl8efyjFFlORxOGy4vj7PqlU+v2M7UronYpX3W1U2VvuxrGIEZLymrLWbtXyzXYvPnPzRHG/+oxz3h2zU4Ge6RyEL3Nm2PV3F66T+qcHeglFkbJtCAymIs35+Gr4s291VPz1BQ9p4Z8FDFrihQYxwPI6kdOTqxUtePH1KCiP9boPrPaWEgskBSNP0kybM5O8zBUJxZKPJfiK5JEu3wHozfL24NarwUVSZM9ZUcNaCZdLgsItrPu0G3cc5j/eeYRgYBi3dQtJEPXGmwYqaYxUySWq+N8tjF0spMR4nStaqTAYJE53vcMYzTVPFkBetNdxz4BnfL32i5J15s5TJPTEFTabK21ujSr4DHZ13FYe6v4vuAHP143KP6jhrh7WBFIVCGClkISM56fYOnkYlp4D2p2KryxIx1pxEffK9ds7hnM0JfrnkjzU5IXg+SUqRGCaSMyCOcBzZv7wiScqD/Ye8a+tzaSqGjBQl+PkBLpheJeTUD5kfqJZMIiCSOFxdM+73HK5vZnyv7dA7/X/3niz+TMJ0OHC4uublhx+zf/6COB4REabDkRQi3dCpsno+WYm7nD24YLeDMAWmMSieWWIYrtz7rKjjzKzKkizGmXqvRMhVtGccUySQZFLCTSauWdOUvGrmvjLCpPTZAsRvunY5rc9fmDyJtfIohcVR2RztTfoRGPI9j0Nz1+f5d3HO5ff1ET995TRblvfV/HCaeeMSd6ntKXP/okHLyaPGcPI5Fh2m98/aVTl0tdVW+8ntM6MuYRwRIIrB+YiEgPGeVMpBMJc5mWfg+WVd/gxSqtYVZ5gcHM+OZ0Kzr1PCOy21EYzTF3UheqSElgfxIOTAu1AKBhZ5t4Rm06eYIKbsiApiBWMyWaINchqjSe55Dk+ipSiMMTirbZAQZjUSchmR6lTM6iMlWFoy0lPKNRdLgNgCxvL86VOefvKcx08uePjkApkOyHQgxMg0FTk3hwWclUpOuLm54fr6JUkS1p9jXYc722A9nMsF1npeeesd6DY8e+9dwuEG7x1d1+Gsw+KRHIjfDD0X51t94aeAcxZnB3bbHY8fP+CTj3ZY5+h8x2bYEKbIdFQ2en09iToewTpiZpNu+46vvPkar772hL67JMTAFz73gP3BstvmoWdQMoVziPN0Xc9GItZ6kqhzKTFWRyslIcSAxIRNYG2P8wNPn7/ka//2m6QYMUQ613O2fYV+u6sLkL5X4MLZUgYGZoZ6WryIVVbP4r0jhshhjJxd7jAehEiYjohEjLN4PFsDnR8gDZA6oCxWHN47XGex3jCNqR4ftFSEMTCcDWANISRSilhjM/kjX3dUJrZ16ripbB5VeWE8RlISnLvl4uwpx2Pg6vpI13nGHYzHxMsXR6yxbHp9biccCSUFxERefMB4PCoJwZ2Dt1ycn9N3HZaENfDo4Tnb7cCzD7/Ph+9+h6/89b/OxRe/AClAHLEGhn7AO08pHZKyAzmv+fS6YnWcdAYZQySGpEoxxmYCCLXkji5a5/tUx5DRZ/5wOPDixUsuH1zSDR1jmLjaX7PlDN9v8gJXS/4osznPBcXxrbOSHrh1x4zR53kKgZgiOwRvwHqfszI0K2LohM4J54Nh24GRL2LkHV5eveDFy+dc3Rx4/vKWECLHMXAMcLzW+eNDe6DvhMsL7ZMUApIiYTzm+arMVQeMMYTR4FzH4fYP8cNDvOl5MDiuRxgjGJOahdVMdZmf3DJLSiWqmJYV0fjG6WTv+m+e58KUwJaFJPl+t3J4S8LG3XV6s5hoFnlKTLN1LOlwCbo+jwmJgu1UhtC7HmstkjSzofCYpiB5QatHSSKQYHCJfhBGgRANKaHKO8bifYd3WtbKZpKHMQ7rfEOek6zokjNcWsnQ1VZbbbXVfqomYvnTP/0iT58+PvnGcDhsfiZtWm211e7a7//+G/ze771d/375sr8XnF1ttZ9X+/f//R/wd//u9/lX/+ot/tk/+9zPujk/VTseB77xja9wfX3O7e0Z1iqekJLl29/+Es+fP/yUPdd37Wo/nsWsYJEAKwJJFR0kr6Nr7JU2WAc1mlYCuUaQmvkzB/7I+8zlVqViaEksiOCyjG8th5yDabWERwmWZwy5ICSmEiJSDapKTZzJbZVlU8lkjpKYqAQHs1RLRbJyc4shsziu5IQmEcGkvIUIpU7GYb/n9nbPxdtv8NdffwwxICnQ7baMISq2SdDrLXFGYBq1VLggGNsryaP3OKAX/Xt38QCsZ3/1khTGXPbbaqIfNuNm4L2j7zvIaquKuXq6rmO73XB7e5vLKmsSTIpCLJhriRdnfCYZ/THG0DnLk4szdmdbnBtIKfHwciAEQ+fdfDElqz4nLYpLmKLmK4DM6FUpMS0ZS9QkK8/+cOTjD59mzDXhjKPrdpXoYoyWVBYpah4lsr1Mb5pxK2op6RQFkUg/SC6NrjgvqFqAdZYOj7UexIOo+kJRKrE2q9dao4SNOlQlK2wLrtfktpSVfyvJBur4ibnktsmR/Bq8RlVvRQRrJvpe/z6OAWctsYcYhOMhsD8o1iyAou02kwTyGEVVbpVHoLh2n4k6BsW7t5sB3zkOty+5uXrGk1depX/4kO//4b/jT/7l/8rrv/Zl3v6tX8/PZ5kNtI9LkmbB2eYYeY7JlNLLtS5zucR2h+YALZRsDGEKHA5Hhs3A4FVZ+RhGOgMWnx91OTnW/MzfZwY43t7ytf/xn/Hyo0+4+viT+jBKCHznX/5rXv7gI778H/0ur3zh8zgHzkDvwDswPAJ5wHE8cDweOI6Bw3GqiY0xQRx1/rgxAWeFYcjzSY45pRhzbKq0KiimHbVMzcfvfcj1x1e887dHBmcYoyFKidWZpv/MgvzBYuyXR7o80MtOEOb96hzZ/J2izmtzX84Ysn66JD/cIdfUW2poE60V286K8PmopFTHv0jexticOD2rxpTWpFha0yR+CzgjOAcxx8AkmTrerLWqRF+SQCllrmwuicU8PmmSdVcMebXVVvsp2Wcv3WLmSYniHEh1SWvQvP0xrQNU5eyojolp9isHT+Ww0igwlPO1bUByMBhMMnXSbWf+QriYXxsa+CMJ1s6qHcvVxXxN9coEMPNLgjtbSD2/tPuUz+rbRRbrARCm8cj+9pb9zrPde4xM2Bj05R2jntcoc5vCjCWrCsRAihGbS8QUZ9T7jq6LDNsdw/YM61x28kupG9M0wtB1ns1mYApKsjFZIcR3HZvNhq7rMvHA4Z2vjuZ9byMxlmSEmCIpRXpnGbyWZXHA+dkW7yOukHLK/bIWnMU6PUcJrC6GWmbf6n3LJSaMxbqOlAzH/cQ0HhmPN2w2O3bbV1Ua0JS1QJF3nB2+pZJHOwakOukiWnpF8md6l0sdwUn73Kkig9YNKs5IYcjPyijzyJmvRVnoKPPWlP3Kr6aOUxHBumaI10C8kCIEVMVjOh4JYyIGfcbCpEH4cRJ1APssaIOpJXpS9jYEiFHl84zTcd95D5KwopKN/eDpB8f1y5Gb62vCNNabJEkXGDYvBlsnXTMo5gfjNKtB1/4ahF/kCjWPUwn2Nw98HYlGDDFGxnFSZRGUYBJTzAzxU6d8PoQUh9iU50ifl5KBoIs2SEkXmDZpyZWh93iv5IJklJyy7SK9Fy43sBvA2h3WONzQYwePH27AeMYxcnuYMnlJiS6JgPEJ66KqsoRIijGzuFMmmc1jZJoM1iam+AzfRV558hrDpqdLGaCofZ3Z29ltNlmxJiYdO0sdmkUPLZ+RxSPfzIj53sncwMWmp2pPd0pR/QjHds4KqYOf6iG3zctz4DxmhKKyU1j9RuoowhqpxK/TLijSrmU8LK9ludgsvzbfrPZzZuPouLnpGMeVKf9X1sSQQiab+nRP1tdqP68mokodc4bl/ZaS5fr6nBcvHv0ltWxpIXjGsQPIZN6AtcuXh/oydpH17FzE2nVMrvbLY8+fb/jOdx6wIper/aLao0cHvvjFF3zjGz+b981PYikZYnSf+k4dx56XLy+5ubkAwJgpv996rq4ufmbv2NZEDDF6pqm791272i+GleSquuyffwHapXwBZTJ4atrgZC4g0GTYt0oKNZDZYBAtWimt8yVkyVVd67fnaI9naL5rDlgS2mc8am562RdoksnNEmc5waNMs7GU783ymHXjeghh3O+5fXnFxYMzzp88AEkYUdXZWBQVchJTyhiI4iGp4qjGCGK0tAkGrHVYKzjf4bp+VnWew+xNw5T84b1T/C7NQWFrNSHT2aIYYnJSVLr/ggyKUZnSPsEZg7c2Y9DQ9x3WltLjTVyg4DXWYpOr2PI8JmasqPZvBoqM1aSyMCVSCsQw4n1P153V4ysEZSoOPaNr9yLh2lsFj6LEIuqNBqSWGtE+L9vmnwowKU4ajgemcczK3fP5FbdtlTLyuSljfm6SYrAnz0DppVQUojXBLEUlkSTRAHyKQkzUUtXanS2Sl+MbZsYCTRbActaBy+ijEZw3OGcZj5HxOGbSi3B4ecWzd9/jwZuv38Hdyr0sBKfydFb8UNp23b0nUvulnRXmY5U/kyi2X+aYNqb1qSxlAylGwjgtQlWqzGDohh4jwvH6mvHqiq7zuM1A13m8M8T9gfHqCpOEruvwNuEcDB46B8Z0SkLwWmraugmwxChMMVbsXK8yqsqHjZBUjVxEx1kdg82lG2OYpkiIiZASxoKzBlf7sczKelEhBuIU6503XpXY7wCobd+3X93BWucPFvG4k+PdxZBpN26eq/vH97yRIRfImn+aQVOh5iY2MCPWJ8ow+XnKotB5n7lNpc2nZcnrpy2k3fy6YsirrbbaT8s+M9HjzVceIxgmNJjZuU4JG87ml1wiTAEjQrAWT8KKA5MQLMr/zUG27FhbY7JjCGSZM5EsGWUM3nWYlJimQ5bj0s8ll0nwmegRY4RSK7EJitcCkMVZKq8GY0iWKuffMnOJhpSVPnR6d42zoS+EtuxEYQm2SwP9b1EwyP8z6qCIgZSZhrYUAcskEoDOdQydZ4qRo5tUEcJ1qNrJBKgzvhk2nG12WktwGMD6zELMP8bi+55+01dyQmlxVbGwyip85bXX2Fw+5tnzZ1xdXTFsP8Ray8XujNefvMIHlx+xGR6wGc7ph0119BKQjCVhs+KCxVvPYdrz7Xe/xWbo+J//j1/h7bfe4Dd/7TfYbXdcPvoCuxgwk8FIANSB2ew855cdxm3wB6MlRiKAQ8SipTyyZFeC/WHPJ88/wnvPdrPj8tGO/+y//I+RKITbkZvrPX/6p+8zHfcguTSG076JCUJQ1nGKAZelz+q7OykpwVqP7wdCOJCmCMbgrMH3nn674enzF/zB//HHvPLaYz73+bc1yz8rUZS+NsZjjWfjHIO1hLzIKgsA0+mdP15PCJBCo3yBLnaKIy/YXHsPVfUwEKOQ+UAA3FwH3vveDWfnG548vgRrSA7EOrZjfl6sJRjHPuhzkqrPq6VcxslgR7CdEqK2m56hc0z7kRQjDktnPa+89iaPX7OcXz4mJZiiMEbNtigSdNjCUp0XiAbyjNAsoMXk86tD6kzuBy39WZU/ykgu5CpTnPFEHjO6UMuDh855tv0Gi2Mcx0xW0mfa+Pw8ACGM3Ny8xPmOy8vH9F3HxfmGzjnONhs6Z9lte6yF43EPCK8+fsB20+P7Tpm7WTLPOcUPvE84m/DGYY0nhCNTHAlh1DktCbGU3WnIbtN44OrFU97/wYf8o3/yz3l5feDZC4hJiUNlMWsMeK8BpLPL99lsn/P47XfYPnmdjTJ5OI4HQghK6EiC7zY43+MNdFZ4fnPNs6sXOSOCiq/UWzJPaY2ZMjibtWiRdkzzAommFi/Uyd2InB5tcYrlotzkxQh57OuTYZ02OdegyoBFIMYRsJh+UAKH07nV5VWLSBlzOho75+iMIWQyl8nZDSlJVtdB1YWwjCHSWUiTQCxqSzYH73RUG2NxrsO7VaL8583+1b96i69//RGffLL7WTdltb8gG687PvjDVxnORx7/6lN8n370Tqv9XNjhsOGb3/xVjscfniksYri5OftLatXSQvB861tfpusCANYmvvjFb/Po0bM727733lt88MGb9e/XX3+fz33u3b+0tq622mqrrfbLa9fXF3zrW3+NGO9fj8RoORy2zd+Ob33ry3gfuL4+/8tq5g+1oi7y3ntvf+q7drWff7vYbcmaGIAqcNZMe0MNRkYRkkmaoJYEsDk5OwevZcYECp55SsQo4TRrHYioMioU8YICwmGNzRhyG/jNKho1qFxSZkwNZDd/nuAjBWdoMeIStC+byEkUuiFPnNYQpuDTpp5TD1GOKXz/D/+Yb/z+v+Erv/s3+fLv/DY+Z5GnlDApq2tYlwPxsZ7R+44u/+B8xVLA5Gs0WOe0lMQy06XGRkubdmdn+GHD/nBgHI/47gZjLH3fc7bbcT1s8X6Ddz3OeURC09sWMUUhRe9JiIGnL5/Recuf/eABlxfnvPbKa3SdZ9g8pJOEiUCDs/vO0g8OjMc2+P4MbM0YMgJTmLg93GCNpes6hk3Hl7/yK4olTpFpnHj+/JoUp3qhCvMYJT8kxdElJXDapwX5KtmdBot1npTLtSjuX/rVsz8c+OAHH7E723L58DLje3ZmCgDGWK4/fs6/+4f/mGAMX/wPf4d+u823SpU+QAhj0hhDiTjPGYHNM2GraoAxBnEzmaNsPh4TKU50vWe7G7Tr8n3uoqqaJGNJxhISuJY8kE8XoyYvdk7vTeedEhomLQ9i0DG6212wPTP0/VbDLyJEEcQYJTXkRM0y7toAuM4DZvn85YdckmBsvtF5s9Q8rO1/W66Hxhck4+6KHThrszq1JcaYMb+MZVsoZaCff/AB/+5//KfEEBiGLc46ht5z9vABv/Wf/D0evvUa//H/8/9OChMhTFhreePzb7M52/LG/+s/JxxGLl99wnC+IwsPYbP6vEUTflNOoE0pqpI9VLy1ZVOkGDge91xf3/DtP/0uhzFwOGjsaZ6PckKjBRHHG3/7N0GEy7ffotud4zMGG2NQ8k/umw/++Ot88CffosCvj778BV779a/UeZyWNLe4Pe3cVieyk6lRMmEl73wfhszJ9DnfvvpNxZBb6oS+PDTuiKmqTfWBQINLSSJWDMb5/JUGV6zPo2ZBmjW4TPSwkNWZYI6z5TiFVXWhGAVnsuKMpNquOsdTyGF2Ld2y2mqr/VTsM0ejhr5DMDg6JEsPlQlNY35KgCiZ9DGrLWAasoVRV8ikzIDLQcVS5mTx8kVl8pfyaEoSkfp945jOZ6G8uRcMTGPm9/lynp4ZmDL/KPM5T7r3dUi5djmRcmLxOjtp0yn3vN1AG2KNxTlPwuBFcLlkikgkxlSuXD/PNQyj06hnLXWWD2edMi1P26/B/YTLMoSb7RbTWw7jyOE44ZzX4Ki1DF1H3w30/ZauG/A+ly1o+7I5gTUWEeH65iX7o+MHH3+M6zu+8M5NLnfQY21P4kCpB2cMdJ1j2HbE2GOA4zE7hE0tBFMWWiKEENgfbum8qo3szne89dZrGDGEm8jTT57xp995lxTD3CH1+k8cuvy1qY5glna0Nre5qbNpVWbPesfxOPH06XO2Z9vKbq6OQzllflZsdgbqLc+Ots3jL4TY1Bas/hKLQZKPXeQoS7kRY9X5SJJLv0QtR9F5j1hDcAkbVQ2kjI+YnepWEKE8X6lhbRsD3jnEWKIJek9yncXNdoftNnT9UPs0JnXsNSNg7oeTYbJw9PTfRuay+bf1wZIIuqZpxd7mMV3GRt0fdeo06C6EMNF14Fynx3Wmjo0UIYQ9mFhrZp7tBvqu48F2S985Ls43eGsIcYMx8NrjSzabjq73WKclgaxRj0+dyghEJXrgEHaIyfVAZawggVJ4pDrg+9s9H7zv2e+PWUYwcH1riUnHnilZCxa6ZHDO0MeJTjxu6OjPzugRnMDtwTFNIyEkYkp0/RbfbeitoXeGMUZe3Fxn4sinu8/tvHxnk/wO0FJXd53wun8jpXdygHmJfDp51lPMpJJmPVGd97LglywhaYyShGzeqarktcIuxuAMhXIElWBlMiclAz7Z0Y91YY/OG8bU57i2iVmab7WfL3v2bMPLlz0hrPV1/qpaCo7Dsy0SVUJztb88S8mQ0p9/3hvHnhcvHnJ7+7MhcXwWE7FcXT2of1sbeeON97i4cHe2vbk55+nTJ/Xv8/MrYtQ1zarssdpqq6222k9iP+qdezhsePbsMSF0n+l4+n67/Gk176diIpbr60tubz/9XVvM2rQqfvycmsu4YcJRCzC0ZIgcaU2Sg2ZSMJEGpFr8rfsU2BbKL+39b/DbkrzXQBEFU2j3ajHk2TIuOEPOSwzKNJvV+HHRWWjUP08P22Da+nW70XwdprmuReBUhP3LK56//wGH65t8BJvVsMnBWFPVjEsQVfGTHKS0VkvhmBlDrpdVgqEnj5SqZMzlQXznwXWqChAVtzUotuKtYtr64xTDSjZjXyd4PPNYGKcDIVqub2+xzvFwGjO+6jA4hGnRLmstrrN4sRjjCUEDqlUlozmPKiCkHHBXIkvXd1yc69ojTcL+9sDz5y9z6YvTm9wGk1M9fsvTEchY4F3MzGSF5xgT+/0B33cz9nsSnwBDGEeevfseyTtSiPNx0CRSLRmhBIe28IUxLaZW8NhCWMmNtAZbg9O5PPUkOC+4HFdIJpe5sTVlN6tCiyau1kFvat9UdYacoCXiSEbxs9JPvuswzuO8b2IvpZlm7rv29jX43Z3zlk/KyWXZn/Xxq1PK/NSfTh0KKavSs0yB5HVnTeTzFYssk0Eajzx77/vEKbDbXmhsZtvjjdA5y9n5lsePLzX2pTLKnG0HvHc8eniecV0qDqzHTkDKpattvrf6mWTSFs0VlNlumiZuri1hCjkJOzFOJhN65jiFMeBEz3v++hP6zjOcn+G6jizGwhQsKcZKbIr7I7cfP8WkhEmR3SuPidOUlYGW89b9dg+G3N4/aefgz2LLc54Od5pv2mTTZVnx0q82xw/y9uVZOT2bzAPLmOb9VU9r8hgrpEH9NOV9pZYuYD5Gc542MXa11VZb7Sexz0z0ePf976kzYZSR++TRK/T9AGJ1eiuy/U4ZqTV0eRLcK6G0JGAkNYHm2dueX8Apv6gLCzXVwJ4UL7FVYphPomS5k/VgDQ429WGqA27IAWybWeURZxzeW3UBioNcXpJKg8yrhlwShqK7cEriaAq8lAvOHoe03+kJ1AkUm9UhnJInECSz0wu7QnKGfDlfzNnqVgQrZMe6I0QYQ8pSbEKYtMRJSAFjHOLPca6n6zfKFPaGIEeev/yI737vG4jZ85W//jkuHz7gwcNHON+xP9zSbwd12q3NAXXHZhg49kecRBgnnr/3AfH6lu996z2sc1ye92w2HV/4whe5vHzAq51lu9nx1uuv8+qTx1pHLiW++Z3v8/33P8Z6DWjPQhmqxHF7c8uH73+sDrr3XL+8Ydef45whSeT58yturw9s+g0pBf0ZtQxGEiUZqZN6f2TZGIPvPMMwEG8PTClLfWV2vLcdzg/YfssYDM+fXXNzfU2MN6S0J8mElY5kIJLYjyOHaVqoHSCqggGCcxZnck1RoBsyazjkunXouOs6h+8sblApw/PzHWdnW15eXfH0+UuVak2G22Pk3Xefs7nY8OCNh8TDkevnV4DgvcMMPXanz5B1YCJVxcZaldUbeo/vO+LkSTFh3S0pTMRpZDwYhp1ju93Sder0hhg5TgFvwOfFVZVPlHrV6HSRSztlWbmQEuM01ec6CoSG6BEzo9jVZYbkde40zxXFMy3evBV8b9nuel5ePePZsw955613+OqvvKOqLBuvyhvG8vyTj/jav/kOIpGNczw82/K3vvo6Z9uOofdYaxk2vt4fY5T85pyyCZRtnR/tFCElggRSiozxgGSli5QVio7jnhCEKah8ZooTqmjimKbI1VXg5d7z6utvcfZg5NU3dGXmuw3OeTYXlzjv6fqernN87u0nXJzvePvzv8L5xQPONxcMvtd6gclwOATGMTJGzxQ9u+05Z7szvvNnf4b91jc5XB34rvuW1rAtc3mezxar1xapyJNnKY8VQ8LYiMv3sMgWVge2TLaLD5rFc7vSMkb7tWSZGAtGcAQSMY+pmXlfidnlUPn5JhbGkh43RAU7igOv5Zgkl5zKjGwieQmd15K6z5SE0JDDrLMQJGdrkKV2jC6GFtKkq/082N/5O+/x27/9If/6X7/J7//+G9yzElxttdX+nPbhh6/z3ntv/bn3j9FzPA4/xRb9xVtKlj/7sy/wgx+8eee7m5tlRvRHH73G7e2OV1/9iM997nt/WU1cbbXVVlvtr6B9/PGrfP/7n7uXIA8wTf2ifNgvsv2wd22xN998nzfeeH8lUf4c2surF4BBMqa53e4y+aMk5ZUgX8EIZky4jfRmNKxiSnPi9imG3FoJys2Y7xy7bzDkBt64L85YMOQakTz9vhwvl0zBaMJcbdQCcDZzVPNEFWFOLWtMyCW827Ya3v7Nr9I9esirb7+xaOTcj3YOcJplnxbIZb6kNhCay31bSxJyGZhMkoha3qIooIrrNbkrB+2NhSSBw3jD85dPgYknr1wybDYMmy3GjExh0m2bhEprjQbIY8RqBhyHqxtknHjx7ApjDEPv8N7x8OFDhmHDmVN1kovzM852m9r3T59fcXV1m8kqy2CqSGIaJ26ubsFo6ZnxONG5vuJCh8ORaQx466llbmKjGm7aYXByt/JwtdbhvUemQGhkDjTJz2kyq+uICQ77iXEcSWlCJORz2hwuyCU6bBvv0N9TVvAwBr3WXMre+oxfxSZ4brSPrTO5JLWh7zu6vuN4PLI/HCmqt1MQXr444HvPcLEhhcB4ODIeR8JxIk0hjxGpSbdVadkowch5TZaUqAmgxowYkipSBFVh8V4VkTGKC8eYMiFpDqTT9PM8hKXWy5Cswq7JsNpDhYhSjlFVdoyp41sPVFSIZa66nk9vDHz4rW/zb48HHv7KW7z6a1/kweUDXnn4QJP7/ExoOnfvwP/t75PE0J09YbMZePuNC3a7DY8/9wpd3+v2DXnF58Q9bEmYbogqOSFXcvnxgsmKaAxElTZmVWjJ2ZkiGsM6HhPHYNmdXdBtImdRr9paxbN9P2CsreSry4stQ99x8eAh/TDQ+wFvs+pSTiINIfHwP/17fPVv/TYf/cm3+egb32Z8fsu3/vHv8fG3v5PHQyY5tOobCzZb6dzTOBmZqFTuoak48mK/BW7XYMkzQ2TxEOr+UjFkQ6zHn2mC0uDSzSHrGJuvoSbkGpp5Vf9To3Hl+5wUW5JPkxQF9bxfrvnSjs3yPkxz76y22mqr/bntMxM9rm6u84TZ431PuixOntpiSioqDHWuLpPq7FC2O8ndIzSWqSELZl0OPprFZotfdXKdOXv1ZVNe/O32JTrYvICrIkCW5iIzWksAULebPZD7r8Es/qniImXTkzYvXnrqtVFLNaCO2ULoqjg+zbtqPoeqg5jspKfspCNU6S8Tc0c4VU+ZnXSDELndX/P02cfEZLl8dMb5xRmb7ZYpTDnA7DMJx2TFClVC8M7q6y5GwuHArTH84OmHxJR49VHP2W7Do8eP6YaeGANI4my7BbPVfQ384MNn2EwgKZKCxupCJ0liHEdur2/zPbIM3cDh+hbrLbjIOB6ZpkAIsSpFSEpZSkvq/ShdZ+burPdAJduKbKGW3ZlltZxKSzpPSnA4TEpUEHXSkyQNGht9uYeYqtpNe/s0awF1AHO/iwjWqVJDlPLc5DHgVNXBO493jvPzLY8eXxIJXN1eEaIhBUuIiavrI+I9lzhSMkzjmAnoQsykIWNzMN4WpycvQqxV8omzqmBQJP+qk67KF13XVYkxdUCjLmxtcchM7d15far30MBM9IihspwxSznOsvBKImjRx7kHjSSMZIZzlmXTxaLFe0vXe4bBY68D0/iSzk08ebijHzqGsw5nDL1zdPGa75mJIA4HDN7y+uMtF2d9JjOB61xmXWsfyeJRFCRmRzUTPEIMxBSJYSKGkMvSCIfjnv3hlmlKHMaYtx0hGSQ6YoT9AcZg2J2f4/uJ86QqHl2/w/mO80ePcV1P1w90fcevfP4NLi92PH5ywWbb8eBsx6bf4UyPNY79zcjxGLkdPYfgOT9/yPn5Q65uDvzgg4/YDrtaR3XhoJdfFlNbzlUx87a64E2klLDNorKynuuxTpzpT7MW6GmOkZe2TVMSRVHptIUVBJpHixKGUl6IZlGq+XVlmqtj8b5JkuuTSj0yhVlS5pHCkk8IVlaix8+bvfnmDb/5mx/z3e8++Fk3ZbVfQFMlH82gqhjqL6kpDmVoZUxvbs74+ONX4c5s/FfZDC9ffrb5ZL/fsd/vODvb03VaFx00KzvGUwBrtdVWW221X1Yr71gwjKPncJjhumnyxOi4udnx0Ue/LO/cH/WuFS4urhYKJz+JwthqP107TmMepQ5rHZthg7EznjMTNqDFjwFmafu8LQ0sYcq+PwRDNu2G+Qj3PTJ3gYSqcjG3Qe5squ1oG6x4WE0WKRhYiwHrhS2P0YK4p+0yzI1pdjp/5Qlmu2O7HZrzl4bnhUrGMAsuvjypNPC3ND69VExDmAkO2sQcHC9gSlY+VaVZxazFJKZpZL+/RQSGTU8/dHjvtQR0UffI/VCy2K0tJIQcwA+BycD1/oaUhLOto+s82+0W5xwpJ+H1vgPjFfc2cH2znzPjm3gwpqiPa3kWgGAMzjrCOOXAu2KZMSqBoLnwnNhUu22BIZ9awcUX4yYHiIsyr+KdquqsGHFEKQpzQmsJEt83NgpeVckSuZ2KceVy59KoGWSVEcXXLd47hs4Rk8VOeoqYtHzxMQbEWgZ0rRejYr+pkDGkuSYzx3iq6nC+/pTHkKn9n7ICBDg3kx+K2vgcEFliyIs5oPRFCaKnxKzQbZZBlYrT3YlC5WtIpBiIwdUkz67v8H3HdHPD8++9S385EOObOHPBdqPqNL53it9bi5VL3v7SOyTjsWevsttt+NLnHzL0rias2VyTpRADTu+jZJn7QizSkimCpKjjPN/LEAJTGEkJVa5BFD8XlByUYAp6H///7P1pzG1ZetcJ/taw9z7nvNOdh5gyIiNHOyc7scFgClEFFDRlhKtAjcHVDSUaviAkEGKwZQQCLL4AblRmEBJC1Y1UaigBJdNU01DFkLQBG5zOtJ3pyJinO993OtPeew394Vlr7X3eeyPi5hAZkc7zhN6473vOHtdea+1nPc//+f+rpkE7T51j+0Zi9vVkijIGY4SR+tzBLk1dMZ3V0ifqCmsqASSh6DuP95HZbJdLjytM6+juHHHv/n1Ob96mO11gqwofAtqawvxebDwGS65hmBNzDDkziz+w39v5OA8bgKN5d0DwnM1GkAM7ElseT41xyD2Uc6AS0GOY7ks33Th33Oh7efcQIGpGY1ul8ZA2HW37kBL2rX2bWIyRvu9xzr3Xl7K196k1TVNY8t7JHhnocf7iNbJkiMko1ZgStbCRNY8hQtZH23ixJkkMhjlwYLMYABQ5lZYdwIzvG73XS8K6+HD5xT6eIh/iz4pHGzdfsvl4SvTQlAKrDRqd6L9jQt3lq8sOhUjVxJS0LqfI5y7O4ZColNdJdriHHcbviazPJr5ARCcdPRVGt4kwKHgfRM5CkV5YEFUgarBGUWktL1MyeEBT2YraVui6RltLrzVeBaxGaPa0SL689PLrvPra6+hmhp4d8LEPf4innv4QTTNh0kxZLjqqusJYDVpjrGE6qWmbGqMq6tmEz373d3Hx0kUWraPrem7feFPo8lYQjjr8gcNVjtfv3uRkccoHH3uSy+cv0mjFjoUq31yRcJEf7z3r9RLQWFszmUz56EefxVaWgOfGjbv80hdeT8kIcZz6kJGxjhh8AW2UXhcz64osXIzSVGkh4oPQFBptMKZGVxNh/KjAVgpldHo2Add3rOYnMhCrCh0cKio0BltLdtklZLhWgqj+yMc+SDOpee7LL3JyOsdFYbCwdUWFFlBVjExmslhqlKJWir3ZjL2d8yxXHZPpCV0XSjI7BljPO269dAffuyRHBKiAj455u8YYi7U1KuqELo4COjGKde/RAYwyKET6pOs7ZuwUthijK0DL4sB5fNvjK4ut9DDU4oBCXq/X6F7RtomFxouTvNM0QiGXx0xO64dI9AHf96LdWinGoZtZXNLEFlYXWJgdrl4+4GD3GT7wgcd54snrHOxPObc/xXdXcO3T7O2d59KlHbSOGC3sJnXT4FuLrXq6PnB8/y61cbT+CpV3uLXMc12/GrQRY6BzKfHvSAtHAVXNj9esVz0RR1QBYxq0riF0EHqcd/Sup3eOdddRQCwxoIJLCG5H17XMJoam1sQo6H9bCYtOHVuU6/BuQVgrbrw4515VcWtnl6quqat9rGmYzCbUdYXRK7TuOHfpU1y+9FFqW1NZw7lze1x/8jpv3nhVxkqaUPNiNINuytAbBzmiLOhErkURnCeJcyUcnsx24zmrBAg2ZuaHTIIxzWdJyzDQE2wDaiJfhzwnKwHIpH6jlEFpg0gZURbZBQqihkRtjKniwhis7rF4XLoWrSJWRZT3uK6na3tWbUetLK6xScbFoZSnaQKTBmYTy6Q26NADm7SKW9va1r51LUaY39phfmuXnSsL9q7P3+tLes/txo3HuHv3Uvn7LIPF1h5uH/3oPf77//4X0VqCki+/fMC/+ldPJbDH1ra2ta1tbWvwxhtPcHh4gaOjZ/in/3RZPr9xY4c339x9X8ucvRd2+7awZmX7yEccMX6JjcTe1t4Tm053S4JbJ0CAhF1HhXKjGK86Gw8YB1nVmZTtRtZtvBPkePA4hlwSiSmmuwnfeKsY8igBeQZ4Akg8YoSrELkFVc45DnVk4ATwkAT+mUT0A5aCF2/lLsYUuyEXrAhrqZxfbTRTrk5X47bNcVAlsWijBmEClWQ4jDZSGGSMFBMqRVARrQZwg1Kaw6MTjk9OUKZCVRMuXbjAwbkLWGuxtqLvvCSFU9Bba0VlDd7keFfFY9evMZ3N6J3Ebxenp4QQUA5i64mTQDCBk+Wctms5v3fAznSKVYpKQtOUoBaqxONjkJgmJJZmW3Hx4gW00cQYmM+X3Ll1MqQ2YhS56xSTGtp3EFkosbIIpUAzMYoU2RylUVqKBKVoL2+T2zkSvMe1rYBhrEkFbXL91ugEcMk9VuL6Fy+dx1aWe3fu07adQEViRBszyBNHsJVJDNIKAxy++ApHr77BzuNX2fvA4yLdHaOwxwSF6zzzw2UqysvdXmLqnXcYH9BamHl0iq9lYIMLERV9irNLvsR7D9RJLlqeM2mcxBCJLiTwzqg/57ESAr1zKKUkho48CqUUtbXoOO7Io7ESpPA0AFFvykZV9JjQ89p/ep77N+5z4fJ5ftv/7fdwcLDH/sEek8YyaSpmBzvsXtyjaabMZnUa51JoaqwhOo02AoZoV0uMCvi4gwuBkGPE3kn+KAg4w+e8UmZ1SO3QtQ7XBzK7hdKpnaSaUApJgwCDnB8YjlMCDhJgxntPZZWw0jAUqSqtMHjwnuB7oobTw46lNszrOuU5GhkXlYBalOpRyjOZXWVn5xJPf+I7ufzYY5zMT7l/fMybb7zOxed+mbbtmC+XTHZ30n6jOfAsXicmZuWcF0yMHoPo1SbMJ/W8B2fHMWPIqN8Myb3U5sGAsuljyfXENCfkd07OC0mb5rm0ZCRTzlGVU0ihs0Yrj05PLE2faBUhBEICSDnv6ZUmWJ3ymB6lItZGrIHKpDxM9GwA8rb2bWNt2/Lyyy8zn29jjFt7a1NK8aEPfYj9/XeW2nxkoMd0uodSUBmTELemOD/AyIHNNkzLasOLPAv2iBu/nbmVjaPFh/5xdvOCkDizSYKUpOTkcMGD0ycIi8SwoAakbdk6QlleRAG4ZGeqgAfHV/yweXqE2MsricFNHFhLcoI0OxOkF9DglMeE9hyAHvlFnxc+Wqvk5ObDq4K4NsZgrEXbipDopgrSWAtrxNHhIYeHh9jdfaqDlqvXrlPXDVVVU9mavb09cUQTI4TSmqoyVFaYPuqq4YknHuf6Y9dwPrJuO/rVisXpHOMUce2JTpy/+0eH3D68y9Vzl7i4LwRYVsvCYfzY879ZX1GcREtVVVy+dJGqtvgYWC2TLE16oYuvF/EJKSveIQlAEsuzLdX5SHsbNbzQycwlRgv7idEYm9SKMvI9SgK4W69lkWSkrwjQQ5z0GCnOmVJgreHKlYvMdma88vIbqPmCmAQqKqMx2qKC8O9VlaWuLROlaBRM6pq6mlBXDVVl8d6hVUjdWpz0xeEi9cdY+n6MkdY5qqiYNjXYhDZOTaI0OC8r10mSLwqJQk6uW5efsZMenCNmlNnGEEjyF86hfEQpkdDpg6I2lp26GY2DYclNdv6DSPpgK2JByCtqHFNaetfSrzt2dxounDvPB568zAefuc7OTsXubkXNHrW+CLoimgqCR4UOW0GzY5lMNErLOdrlgvWqkmN6AaU451kuT/C+p+/WBB9YdRHvI8EFCAkFHxWHd1csTjvQHqUDVb1LVe+gQgthLe0YA73rabu1OPdaQXTo0AIeVE8IAWsSUp8KpTS2EvS7ij14qTqIMXK0XKLRNJM5xlQoc4rSNbv7U5pJxWy2ZDLpOLjwUWbTHdFmVYrpdMLBuQMms0lq12GiGubtNAZ0nvtGz4fBOZbnFNKYggJ0G2+8Yfk9MAQ6Nt4fqWJEKDIjREOhLyqOet46z8GpT+bNdKoWyONakWQYM8VkrjwAoxIML12LlpWHAJh8oHeiP+tTdUVM6DtrI1UFlTVURjNCBW5ta1t7H9h4KiqWY3/vtB+yb3vaML+5g524bzugxwCyHt4JJyf73Lr11jTqW3u4Xby45lOfuoO1Hq0jWkf+zb95Er/FBm5ta1vb2vC+HvDZ77RHKpB5kN3vEc9YYi1nmaq+2ZbftSFojo8PuHnz+tvKlWwtm2Kx2GOx2CufnJy8+B5ez9bGVlUiy2d0lkUdkmmDxYf/fiaGnDPOZ2PInIkhnT1UfNgmbzXURwwFJbmd/hhFBcsB4sZvIufwVnGPceoy8rDFydltx9cVz3xz9vt8+UMAbpwoTbdGjgNuxK/PIGHGIIZypBTv0Snmq4zOkf3hepSEgdarltVqhW4mmMazs7ubisSE1aVuarTO0uxyYToVGipEDnx/f5/dvV1hRnYe3zv6rkMFiC4mFt3Aar1isVqyO5kRJ9OSaN18VqMek5LlojMj7MU7O9MEQIo4FyhlZXF4VplrYwDbqGGbITxW2lmPH0Jqz8IMrZSAZ9J3+UHFGPDOkchFynVnZm+tVMk9xBDAKGbTCVVdcWRMaswU49KpoDEVgub2NTFiiKwOj7jz/CuoScO5Dz6Z+sPQTsEH+nW30X65LVwIKU4pciAqMaDn5xlSPNCmwt/CvFHkoYfRJE2Y7mf0uIRpQZXvQ4pBZ5ZyH6VYsDb2LcdyzgPIM9IS60zPzhCwsef4zTd585de4RO/5dfwoe/9JBfOH3D+/D5VZahrgyFgVOovWqeDBrQGW2usTUVk0eP6Huc0Pjh8lILG4AO9a4VR3Tup2nf5niVAGRKD93rp6FoPKqRi3xpjaqSq0JWiVAHO9DLylAICKrr0nBI7uIJoFESJjeqSMMoAkSBM04nNxpoEwtEtKJNYeDRV1WOtZzK9RFXVNNeucP76VebLBQeLOebCHgvtadcdy9VKjl3ATSkGm4usxzHkjTGU81j5o3eIIcdcOp23Hc90MQ/0MhY2Jv/xlLAR+lZsXI9Ww6UoUFFtSGgVdp4ST4pnzhYLoM6HWBhBcr4JJAagjfRjo/PJtvbtZiEEfumXfglrLc888wxN04zyMFvbmlgIgRs3bvD888/z6U9/+h2ZPR5duuX4EKMV53caeak3GqUrtIoPMG6ApPBkXnyUTrrprj5sisto1M05eJMdhHh279FLIn9XACAqv/2H10QIuPKiyWIZcXhRqNHiIg4IWflbtlN6c/GSQIPkrIJOUgM5UR3Lf/kuR9dXflLyMF1VRoM75/DOU6sIKgi9V1SiCxZ1eQF5H+h7L7RrQeQkeu+TvEBGzuoERgCNoD4/8MwH+NR3fYLDo1Nu3b7PREUwBg1YIraqMEajNeVFp6NcbWUEgDCZ7TLd2cW7SFM7PvKhZ+m6jr3ZLnXdMNvfxdiaxUnLnRvH/PS9n+fnzC9zvD5m3i44uHqVx4EQHL1f0fcVrusJ3stCAy0MG6oiIxSyQ+tDZhaMKEJhQNFKdAOValCqIbImjts3JXGNUtiEfo3JQZd7h4pAZTR1VVFXlsYqrBL2idX6lJv3X2R3ts+FcJ22bdMCRuRxImB8QCnF7u6U2c6UZjKlnsx4+oPPcunKdY7mt1l3S7qlo193TKYGW2l89KzW8IFnn+WZJ55kte5Yrzu8j3Q9UhUaESDP1GC1oqmEgaB3Dq2hqQWMU1eVSMBUBhB5mRA8rgt4K86v0h4fBAk9mUxpbEWlDLHtuH90yGHbce3yRS5ODsTxjJ4Y5d4KNQ2iXedjxPseo4VVRkaBoHdXzom0TlqJGyMgJQGXBPAeFRPCWem0kNQ0+xeZ1BeIbknrn+f+nZb1qiO4yGLeYasGa6cYHbDKo6saPZnSVIrdBqrKMJkuuXPjPvcXa9pOgV3RrSpeeO42k0lFcB4fIuuuE6CL7yHKGAox4Hpx3p3r8N4zX3na1uN9h/eOvtP0zrBYtczXbZJy6QTl6z0RTYjyDIpsigplUZSWd2Wq1Nqws7eD1gYfRBKmW/dCa7m/T1U36HqKMRXndyt2GsP+wR6znSldeJXFGi5feIpLF57kYLaDuXaNF85dYNY0rG2FQrQ161lTgBgCAJN21zkIMPajFeiktxpcWoSpzRDM2Yn9gXfDaKoOMS+AvOhXqgw8kT4VRlUnEAl9lJ0qWdQ2TYU2CbGESuCuSDTiXMtYSXN9kMWQsUAfKW80pQr4RSmRpaqMwWpDbSumkxkVkcoadvb22d05oK5FKudrjDZvbWtbexfMd5rjVw9wif5c28DBUyfUO/077ju/ucPy7oz2pHm3L/N9azEq3njjCY6PD8pnx8fn3rsL+ha2//gfn+XP/tnfxWc/+xL/7X/7M+/15Wxta1vb2vvGYoTF7RmL2zvMLi3ZvbZ4x33O7/R8+pkT7t+e8c++eBXXfnXn1Dryfd/3Jh/4wDH/8T9e5/nnL3yNV//12/hde3R0/j27jq1t7Rtp7XqFVgpTG2G7MIIG2EzNjZK+Kf758Bjy2c8e9nc88+dmqg+VYhvxUUnyUzA3J+NLwnIIXIyTd6OTkCMhQ+wXigxLiqOoUYw6H2+jYDECGlQoXwKDfO5wo2r0+9nPNu8nJDlro6IwQafK9iL7AiXektmrs7yGDxFr8r2XLGeKYkvM6tz5c1y9foX1qmO+XGEFfVEiWlqbEjsGVbAOspnBaIutaqqqJsSINYGLF87jvaepaowxVE2N1oa+9SznLa8tb3FD36N1azrfM9ndZR9JaPvo8MEQfJWKJlMfUwbht1BDIjpKdHzMYhESQCEXRIIFZYm4jch9YSVXWboFxiwFEmeXYswskW21fB5DpHct89UhtWuYxt1E4T/IvSit0THSLVe8+YVfwLdrTq9dY7qzw7lnn+XSlSus2znO9/heGAWsVWgLkYBzkdWtu/R3j9jb2+eTv/W/hNkkxcTSY9cao4cCxZDikZUV6ZzKWow2CThiCN4n8IVIVAcdMSmWliXKK1thgDd+/hc5vXmbJ37Vd3Hxgx9kd2fK1Mr6OpBzJDBCABXwpQshFWFq6XbpAbkkAz5c/8AWERMoI+d7hho2hZ1OsXrCU5/5EAdPXmDn0j5H94+IPtJ1Hm0sWlt5XioKe7etMFpRGynmtFXP4nTFqutxXoHu8U5zeG+BtabEtp33Q6FplKKxXBwaQyREKTbsnACNJKcTCF7hg6LvPZ0Xue9c/BhCTGP0bAYt5bU26DTybWvqupYCPQIxUIoG62Yi49JWaKWZ1IbaKpqmkULacEznYGdywGx2QFPVnNvd5Su37/Hl/++/ZnLhPPvPPCU5iEqPrmWQUSoyKXHzilUCfUWvSjHeMMOWZNrI8ogaH2gYbzlXpkg5qjKnDTNymY6zFFGKNxuTJHfKBukqUvzb+yFOTczySXHUzGcSlgjIyiSAl9GGylYi9W00dd1Q1yLHoNDbGPK3oa3Xa0IIPPPMM+zubhlyt/bWdv36dU5OTvipn/opfu2v/bVcvnz5Lbd9ZKDHajkXGYsajApoppLVHyFmi7upzv4ynrHixt8ZqqHKdw9z2Ufu8Zl31qaDPvw1gGPzMR+cNSVJuemkZ4ekUHuN0YUF1JEo1qLa2Feub3y8h5gaIDCb36sN/z67ymOKMcUIuxiThmDwZGLCEGJKlOfjyZ0EH/EuORFkaQ/RftPkF2JyQqPIiWhtuHzlMs9++GleefEVTu7cTYCS9BK0VijhlEpAj7GDrpIkSEXdNNSTCaEPxKri2rWrhOBF0kRrqmZCRNOuPafHK24fH9ItHewq1FSx7FoUihA9znfiuCZQgLy8tWjIaU12JEo7BkUIA/o+ZJ07JbSKqApURWQt9InjThUzs4skjmNyOBWgYxSgS2oHa5OTroAQ6Lo1x6e3CLFn1pyn7wSZrbS0a0RkdLRW7Ow07OxMRKKlrrly9Rr75zrCjTVqHukWp7jeo3Y0ttb0vQA29s9d4AMf/BA3btxkfeNmctRERoO0CDHGUFvDrKmFnaOTZ1XXhspYrDEJqKNRWg39wgdhqdAelVhQlFLUVY2paoz3ROdZLhZ0Xc+5c7tl0ewTJV1eLw3J8rxYdERlsZgyXkOEzotTm7uvUECOgB7ZOc6OWWpPM9uj3rG0J6/A6h6L057D+x5bTfBBE5kRmSWpFjBNjd3p2JkYLu1bqkoxbVYc3j1lvu7wXlPbHtevuX3zmKqyEB2RyDqhr3V0qBjwsZd+6Rb40NN3S5zvWXvoA3TrNa7vmJ96FnPHvXnH3dOO0K/x3Tp5iRCiJkRLQBPSYjOPpcFBlY7pk7bpuYsXsZUlBkcIgdPTFd4H9i446skE0ywx1nJ5ZthrNOfXlt29Gc3kHsp2TJtdLl14kmnTMGks+zuzBPxJFIxGM5lW46VBWZSPx7uAMkYL3AjrMSL/wQnwzJ/D/CZBl7zGFrBVDEFAVsqUzfO24tOnf/3w/lEIKMNYQ6ZCJDn8mWyjz9J3yVFXikSfOQBIyjsjfW8yG5LSGG2oq1rmuknNZLrDpJlRVVWBzm1ta1t7b61UxzrD/NYO3TxVFdaenSsLqpkAPd4ONL8+nnDyxoP0eMU1fF8uyN8pdP1oFz1m8rh//8KWweMbYC+8cJUXXriK94rf+Tt/9r2+nK1tbWtbe19Ze9Jw8sYeugqPBPSYTTwffXzOLQWV+eo9cK0jH/7wfT772Vu88srBewL02L5rt/Yr2fq+EzYPU6NMRKlR0c7ZjdVZ//WtYsj5983k5qaN4sJnd+ds7nBzW1VYG8bXcDaGzUPjvsO5HoxS55TjQ2PIoy1jHOKZDw2nn40in4mPDGnGIao8xJBJchy5yC0nxccJ4bR3DsHFzIydf0ZJ29H5MiBhtjPjwoVzHB0e0y4XmFECXye21ZzLV2eOIfI+EscxlUF7iDqyu7tDliRRSqGNBaVwLtCuexbtCt8HqBVY6L2AJCJSyCbJdD8qqkrsMhn0Me6QUZ5RKeqMo/imBCEhFWFtPIkUcyptodRmG8UM9sj3qYa6OJLMdTcn4qnshOBDiacqlZPAEdd33HvpJdrjE/q7h+weHHDxg8+yt7tLVD2qA9+3BB+gMmijJEEdAqv7x6xefZPr3/1JHvv0Jzg5nXN4cizAgZiGphKwR2VFKqb3Cp3ixhI7HsnO6KFIsjB2qCTdHDwxJc91jNx/9Q1u/tIvs/P448wev85kUgFN6Vs5zpsBQDl/HxKjh1Yi+0LqgyEIu8gYeJX7lACT4vDdaPwoBaqqsZXm4geusv/4Hot5YLFYoU2FZBkqIpUwayhEcqf21FYza3SSG3Ksli2dk2JbowPBOxbzNdqYErt2IU8JQXpk9JJ3Cp0AkXwvRYNCEo13juA9XRvo+sCy9Sw7T/SO6N0QO41STJlzOfkmH1ZuLYWYmsk0oK0W1uQYaTsBm9TTgKks2vQordmpNI1VTJym7i3GLMF4KlMz44Aq5UD6k1Pe/IUvc/6ZD7D/9FOpOG6DUr6MhfFYL3m4HFOO4GKE8GAmEJX3YniWiqFeWQkYpIA4EsAnnp1gMsguZwklkJ2HsuSItCryYkPbxTKd+4ICY5TzOBNDLq+lDPoa5gNFApMoUNZgqxprq5Qj2tq3s+kNKYatbe1By33k1Vdf5fDwkN/xO34HFy48fN36yECPdecJJuJ9SihHjYoanSe75NgMzmhEZt+3pxTJloHSD3pLcXgb6JHLOkouFtBcHFE4jdCAsnsovzFyrockI+V4+ZOhijyWHLN4tunYSQpDa13o2UJ+uRS/7qzrrkdnyxcg9Fyk+4rJYRleV+KM++Scxig6dfNVi647Ji6gEnWLQt5XxKQdp0322EAZUEKZZ7RBJxYPHwM9viBiQcAeVSUJzKaZUVVTjK0Ti4ZKzm9y3FREJRVAhTgwxpiChDXKYqr0ktR6g87LGA3K8PGPfpDrVy/gOwEZ9HQ45Xjy2jUUipOjBa++dIv4lOHSxUuQAR0qOUvpAQk6NjuL0jFiYvrQyhJwBZEufdOWl/4YQSqEexGtAkYrrLWoCCHpB4Yg0j0iD6NF1zCAj4rFIvL6a456csKbt1/i5dffxFhFU1syTZvvA7qy7B/ss7u3g8YQvGI2nVJVFdEF2uWaELzcp4/gIrOpxdaW2cRiYqb1S/3GCwWbc9IWfQw4owm93LPzQfpqQJgPqiisJcZCgKap8d6BMiht2NkVhoI8MONyTnQdKJGfaU9PWbme7sJ5wsWI7z3B9YRQl/5eFopEXNeyOjnF1g1hT4n8yXKBVoqmqoRVQYfSj9rOcXR8Qtv31LUAixBECU1liY1FGUWvIm2oWPcNTmli7TheLOjefDONN4O1UFlF3VimOzWrWtMeG4wCQ+Tk+Jhbh/eZNDOevW6YTKDv7+E8eNcSYmDtBLHu2oBzgTtHJ6zanvl8Qd/1eCd9IBpNVDotKiOrRc966eiLA2tBTVFG5hcdVaHs82luUkJFUxadRqfFTkJZLFctuu1FWihGus7hvWd5uqRbd2grVIphZjmuLSvOcRB2OX+t4bK5RNCiY3zv8DY377zKGzdeoW3X9K4HIsYoJhMr4yfksSoL6yrJx2TmCqVl9tNKEULk/v0lbeg3lxcbsRG18ZMlqTY3lnnMhZgWeJTZUOgJ5YeQ/rVKgkcxEINj3Tq0E+khBdhKXh+ul2oDJWyXsghILDh6hPgWisw8R8rFyPM0BG2ICfRChL7zOOcIsYOosEmbd2tb29p7a74zHL+2T7+scO3g7ganOHr1gOXdGfuPn1LvvjOzR7bV/Sl3vnSJ6fnVIyWh3gtr9jr2HjsVbe6R9auKk9f3Ce7R5qcQNDduPMbJyT6np++sBbm1rW1ta1vb2jfTjhYV/+5LFzi5O6XtvzWDpNt37dZ+JZvzOSkrSbQYZW1doro5hgwMQd/8+yPYGIfxltuoBzYpagIghSCqpJYldpi2GbJ2Z04UH/LZ6HQqZfyGEEcc7TZImw/lPLEcU43zkQ/c6PjPIfYec4x7FFPJv4UE6shssV3vUcZjwxAXLy0fGTFSlMB+ui49xEui8PJ6cuwVSqGcNlibE5jVwODBIOGulR4lpOXsGeghFf6S1Jdan7gRL8oSMijF5Yvn2duZErzEWAOeoAL7u7soFO265/hwAec0s+lsaF8o8eMH48DpmaQYulKawg4bIwWukRosh51Lej3F8XOeABAQRAE0AOjCpBJzIVIfOTkOGNtyOj/i3skpSoM1IhnSni548Wd+jvXJKThHM2nQKPrW8cbP/yL3Xn6VyfUL6J1JSaKTkudVJdfSWU3L0K3vvvwqX/7Zn+Pgsetc+fAHIWqIjqBVkVMJIRJ8kMLRFEdTMd1bRIqrgiptVSWGgtKUfYfPzxCN61r6xRw/mRKnEH1M4KPROBp196M3b/Dy538BhcI2E2E/6Tt2zh3wzGc/LewuiXkdH/HKs25bbAgYIwWNeTwZo2UOUoqgwEWD80bAHUYJg/OpME4TtUhrKDBWY3uDMwq3FtlnRaRdt8xXK6ytuLCrsBZ8WBEiBC+ADsmxIIwnIbBcdfTe03WdFFim55+BCQIsSjHGXlhBhNAnF6qmUROhMFjkDhgjmTEpgxAAQpCYcu88yockUQ3eSZ6pb3u88ygtUi6x1qyNpmfCJNZMgyWqGVFVACxXc+bLY07mx3jvEgt1lP5qB2l3BYWxo4CDcqJM5eJGGdurVY+L4W1iyOOOkRAV44RfnmNjwm/ELJcyOlgcfpQEgAvQiigy3SqkkRxBG1Aqs/qQwFqp8YJKU7AazaOlVDspjue5JZb5pOzuIsF6YvRQsmlb29rWtvb2du3aNZ5//nlee+21rx/o0ScooveR4IEkDaLDeLKE7HAOAIxhdo0q80Y8MGPnPQfHdjQl52OVpHHMzrh6yHSYgRZDhfdA1TXCOg6eXEkgjt3Z8o0iJQvV6NoHsRWRpFOYfPdRZC42UdjFA0eAB2khUZzLzQvKiFqtYkIHimRFyGjZKDIkq66n7hzeJ6RpXp4UJ1gnuYXEqpC05XT6UUpDFEq2PiaKsBhS9brCmoq6nlJVE4xtMMYOL+fUHlkvMC9TVBycdK2NJEu1Le2hjZFFhhePRitxvp5+8jo8cVWuGcVqvaDt1lgzRSlYzltu3Tzk3LlzCXGeaNmI6bqHdgwxlsRwQQEpLa9PZUZOtoAAMgI0xJCaTqcqf3EAjNZYY1Eocdh8guXGhK5GmDRCVMSgWK8jd247sEtCs+L27bsYq6hqTd+K5xFcJFrFbGcnUTRpoodm0lDVFcFHunUnzCUK8e4cTGrDdL+mqXSRyRl8k8TqEpJj6SJeK4J3ZZxopRGSQo3yWRfOEi1UlS0yPCjDdLrLdDpJfSrQdUtxNrEEpemXS9aLU9xqhXdCD5jZVjYWvAoiAdf3rE9OsROHamY413M6P0UBjampjGZnp8IYIwwkzjNfLvDRs28PqO0wjiqjiZUFo/AK+mBoXY1XECuYr1ecLE5Tw3nqSlHXmulE43rN2mraymQ6EearNUfzOQdas7draGpw/oTQO/p+hQ+etevxPrKaQ9t6Xn7zHseLNYd3F6xXjhgbwGJqi7FC+6aMpl32dOueqrHUjUEpg9bVsPiLQuMYMlo4htFEJFQxOq2VYgLZrNsOhaI2FgW43uO8R6/WuC4vShVdW2FrC5MVvupY+hqn9wlKKtuPTw955fXnuXP/Bl3fCuMK4ojXtQBrok+AlITib2orC/00H1gri3ejNd4H5icdfeuGW8jz3gPz69BBhrl95Iqn941WqvjkZx30jNJXWaUFT4xCcahcXqonQJlRCQiV5m6lIERi4atUKeITy9ymkG0IaQFKJCbwnEr7e+fxzhOjAwyWarP/b+19ZXH7aL49LILvNadv7NGvqs2vgmZxa5eV9UwvrL4qoEd70oiMS+QRgR65w30zlu5yrmqn5+CpE7TZ7Oyro4bTG7tQgB5vf00xKu7cucKdO1fejYv9Nrf8zhvWNRvfbiM9W9va1rb2jrZYW37h1X3WRw29fzugx/vX+du+a7959v5mY/uVaZIA1KnYST6LKAYXdXNsFhIENUQOHvztzAN8YHiP0vVq9FGU426wN4z3iWoE7GAoRByfsVSF570eEkOOMRUoqs19z14bKtUxptjleMMh7DzaM0d7Y0kgDmwGSao2b1PCZiluHXPcNNIHj/Ei/6DMKFwfRydPD6JUxZeq/IEFQxKqA4BBqcTKq42wP2v5yYne8bE3JBUYiZerHHXPYA/K5xImG7ZDKc4d7MHBLjkW3bse73uR9SbSd47FYsVkOjnzJM4CL6AwluR+lmJY+b+cBZDjpGR2/mwc70qxfomTS2w7ywXnNtjIayDvAdfDchFA90TrOFkshWHAyL11yzWvfeGXaE/nXLl2nqapAYXveu4+/yKmqbk6/STTpoKQ2caBIGARW2uMUQVopYDjm7d56Wd+jic/47j07Adl4wR8EgZtuc7gQ4k1qxSz1JK9x2hdRNAjCmtrqsqWvIR33RCrV4rQ97jViuCETSLGVET5kCBNjIHTO/d44ad/BlDY6UzASu2a849d58pHnmXGLnUlcjIhtXPX9wQijW4wmbIhSo4DI/HVgMTvfbBE5YkGOtfT9m0ZYybJtFRWUQeF0wqndQpUCmhq3XdMtKKuFdZACG26JwFA5GLavgPvA4enK9rOsVp0qUDTAhqV2FLy+HC9x7uAsfLccvxR5f6P5F4iOZQZHxjDqqh/y/bOSRGpSV9klnflnIBBUo7FeyMy2LYnak8fDUE1xMSy3HZrjk/us1ye4pOceQZ2aJN6V0qKZWBWBoBIkeAA1tII83fXerwvL4mNXN3DhbZy4W8el8P2QiwznqtLMHl07NwnAYIU7/pY3j0KBimgkHJ0DPnKzIo0HCPtN1xUmadLXiqDcKLIFYUguT5iEMb5rW0t2fGtY5bHy3f1HLODGQdXD97Vc4ztD/2hP8Q//If/kLqu+ff//t/zzDPPcHgoOd6tPbplZrS2fWu90kcGejSNodJGKtXzqyImdqUMQAhhoHgzxZdOmlZjRy5Pumcm3zOW4QMZQjKe4MdumlaKqDPSlo3VW0RQdyp9nh3owdeUxF7eTWstSb2HVJhv7Dl6T8hb7exqITl0JTnJ6AWQ2iEfqrx3VGF8GDQRBaAg6wWRIggxiMSK9+Ad3nXijJlqtDoCo0R7MV9oZigJQSrQtQ2g5dllwhNlkuaeksT/ZDrFVtXgCIfBM1Rakr/i0IM2mqauaaouJUkpeoKlUl6BUKClF32hoZN/tbKiC9fsUtlZAWw8+eRVvv/7Ps3++QOqqk6gE5O9UPlBFpIZfCLUW9nvNlTNHtp7lLJlSbb51EYrKkVySIz8GC1ozuhp+5bT1Sn7fhdjdZF8UKm3GaVoKun3XeuwLjKb7KCCYunX6VnIYmK17tGmxfn7kjg3FT4Euq5Ha0OlxXGxlcVUmqapmU0avO85mZ+wbtdFjkYZjfJhNG7GrDTJSQfWPoCJBGuJVhZfOqiCtJV71hjlUEEQ16HvaBcLfN+jGkOsNMokZhg1sDL4xHRSnoFShAitC7QeOmXoek97eEwMHtd2ADgCVWWYNMnxM9nZT7qLwROCJgQBp8RqQoya24endN2ak8MTlvNTTuYty5UwXYjzKJ1OFluO8wdWdAa9IjqZGyqlsVXFhXO7zKYT1u0C7w0hOtq+5/U791mue47ud3RdoG/BeTheiJO+XAjaWtGDCkyMQVeayc6MZloTwyndupd5JoCuLLauirSO+IAjNhpiodNzzhfHNSKALh8jfdfLwqgSlpZmZ8rEZEYYAcqEJCO0Xq5YLg+pGsuNV/ewnWZH73Dl8jWOVz1Hp4HVOumRpmf35OOX+a3/9XdzOl/z3PM38T5KVYVSAmIZObH5RUNakNTVnDahwfNCRBVfd+yGnzVV5tEC6kg/Bfwc5Q2SR/vQt6XdUjEB2iaZlcQwpI3IO+laY23ItEcYo/JaT5bro2BJnrtl2g6oIPOuITP8yRgLXkBOpEoSp8IDM8vW3nv7hV+4xHxe8/zz597rS9nau2xubTl86TwxKPx7VOFbTR0Xnj2kX1acvrFH8O/+nNDst+xeXVDvdij14ExbTRwXPnhIl6/JPRrj3ta+8faLv/g4f/Wv/jbu3p3x5S9fwqcE5Wy25Nq1G1jr3+Mr3NrWtra1XzlW155f/atvcOHCauNzrSNPPnn6Hl3V1r5ZNp/v8fzzH8balmvXbmC+BpmfrX1tZowkgqMqqfwhAjwCK6Q6vRInUCUWoMqyPEUJ2Ighnw0pU6AO5XybCT21sd1QmKhyBd/w/SiEHTf2PHNORSkAieNTbJaTb1xzHN/f2RsYHfet7PYLL/Hal5/nqe/4ME9+/MMlnh1T7AwvMXRJvmoGfdwoFesxSCV5QIpYRqaJRc2ggB0S00AIqeJ9CMyUuHCOO2qtE5uHHkAQ47ZClfiQ/GiMMVjjh0eUY5ij4L0iCjsDpGI7kkS03KNSCmsURlelMHR/f5ennrhGM21SEWKKraNGQXjpfCoOAJShaFOhTYPSoRT4bTya/MBzlpshpyDSLClOFQMuOLq+pQl1aa9RUkLibOlReOfRASpb4VYtL/2Hn6XvHP1qTUQYnJX2hLhKxZ0G3ddc8mFUTBaLRLe1hsoaYgi0XYvzrrB+qAwuSNcRU7B6DIiaHuzzzPd9D5OdHfRkCoV1RdYrKsm5RO947ec+Tzef47uOGDy+E+n141t3iDoluzOIpzyGYbTmWPbhzVvce+EFjm7eFlmTGHDrFmIkOM/88JAv/aufZv/yBT70qz7JZDaT9W9+pmVuCaWmK2pLjIrFqhOpnHVL37W0rad3XvJGQ+g8Pc/AtNGS90jMGFIUptEmMm0E2OJcT0xM4y54ThYreudZrzzeR2F/jtB2DucDfWYaxoMSWfioNVVVYSpDjB3edekeEou80VK4qYfMWJZTyvcsKZvxOy5L6UAIXppFS57A1sIQUlUVxqjCjO6dw/U9fb/GGM3pcYP2ikpV7Ozsse496zbSJyWZ41u3ee7f/DTPfPwZvusHfgNHt+7xxc/9J+qdHR7/xHdg66oUOBaQSp4AEMCJMR26D6N5YVNy6q1t9MDGMeQImXlnA+NRTpv79wDfKvNYzhZlVh8T0Xo4UJGZz/u9VeowkoBRZ8R1VExMNjGlsFLR5zaGvDUE5PE//l/+R1zn3nnjr8Nsbfkj/9MfeSSwR9/3/LE/9sf4+3//76OU4vf9vt/HX/trfw1rHw1S8LnPfY5/+A//IS+99BIHBwe8/PLLX9W1Pv300/zET/wEv/N3/s6var9vV3t0oEdtsKmSOaA3JCPyv5nSbOzMPeiUj38/49COX6gwcrQHkEA62cbGSuskdSCyKGpjslfDHD56a2efTMXEuhTlewGNIFIZwEPTknEAujBG/Y432fDyy8bpbs5qMeZP0/GSbmIMwrDhE6JZK5u2THcYAio4gu9Ay3VnZ1cWHKLaNtxsAnr4INpvCTAShY4ivdzEGTRaUVWWpmkwlSUkoEcMMVFcDY68VoJYNlpTVzVVVSXnR16OQlmn0otd2kGb4bOYABLS/sIC0tQTiJrOr2ndmsceu8yVS3us+8C6j6LLWJ6xAD2yLtoY5DE4Epq63sF5D8omAM1D1k85I01m8pCfyghnSwiezrUs1wt634tOoSGlntPTUYrKQgwB1zqsj8yaKdEL8COEhMePkXXrQHesO2HdcCh8CPR9L21hBERirEFXhrqumTUN3jtO5ie07bo4HMpqtEt9OPNRpv6SnehAxAePiZFgDDHJcWQqxqiUoIatRuNQIeAXh/SrZUIhg2mmcq60cM8o/UhC9ccBYCKLQgF6dCHSoUX+pj1FxYBV4nh3wVF7y7ndWkBAOo5Q9Ulb05uB9cLUxMpw7+Z9jo5OmR/PWS1PmZ+2rFY9dV1RV1XiW9OSjHceoubCBYVX8sQqC7aWxei5g10qa2m7JX2vgMBi1fHSm/c5Pm258cqadhWSvMqwABTKOwGSaB2oplMqZWimU3YPdljP2zInhBCx2mDqhroyTCpbFuGZTjPLJ3nvCes1WfMyA4QUEdf1eC+gGmMNewcz6knD3u4OdWVZdz3Oedq7K9r1itXyhKrR3H5zB3+suXbtMU77ltO143QRWXVDPYoGrl+9wG/5zZ/l5u1j5utI13mISTono42Lx51YbYC+66lsjdXrQbl0NMhkysxz5vhnvI0aHT4xBI3GaoQE38irgHJkwX0pBBFvNBVBlvKCRMPUWsAc3qNCwCQ6PjU6Rn5DlKuKGcQV0DGma5FzxwjRBflJuqS+gL629v4xxXPPXeS55y6+1xeytW+C+c5y/Oo7L1jeTaumjvNPH7M+apjf2oG3rTT+xliz13H+mSPeqiDETjznPnBCe1KzuL3ztkCPtw+obO3rta985Tpf+cr1Bz4/f/4+V67cIkb/IH58a1vb2tbe5/ZW7453Zz579BdV03i+93tv8OyzRw/93vvxKmM7+f5Ks8Vih1deeZrd3WOuXLmF1mH7jv0mmbW6sP9G1Ihtfxi/OfYhgcFR8rusz98mhsxo27dIlKkc9B3OSA4Qq6iG+Oko8ZezgUMM+cHThSTNUniftZKYdEmW52Pl056NDY//PXPwB045ih/HyL2XX+OFn/4Zdvd3BOgxymbm9gwhgxZ0mZslKZlip8GX5oy5TD3RPWwAxnPINYqUrcaWhPJw4BxrTuAeK4wAUcmz3qiLTElcKZQjxZFNiRlLgnUEhMgBHkhAjyFao0qsX+7TWpHl9tHhQs/e3oydWY0LEedJbNe52XNPjKNbSCwIarhOY6rESKEYetioQVMeocSSSixaJdlzUkGcp3cdIXoplNM5gjacX1RaRMpch0hlKtr5kld/7ot4H+jbDqW1sB/3XqQm0lG06/HBI6AXiUdprVFGlQKzEAXo4Z0bnp0eQDdDCmN4YDFCs7/Hk7/q01hjMU0tgI3UAPnWtVGErufNX/hFTt68QbdcEFyP8xKuV5MGXVXkOs9cFJb7Vo4h5350eusuz/3/fobeOVwCIPRtKwWvKrI6OuG5//CzXLh+lae+88M0kymYLNeRGVsCMabxGJXEhlEs5yvW65Zu3dH3HV3ncL3HGJOk5bP8SMqVRMV0NjC4mMS4rLVhMqmF2Tj0BNFYoXNemDtax+mxw/exsJ7key4MEQTJ21gpeDVVRT2pS5I3x08FdGQxRmG1HjJLGTCXtg4hEtPzHQA0iqhCkoqJYGUsNVWFsYa6bjBG47wXFhLnEthjTW9gcVoR14rd3V1a7+hcoO2jSHMBp3fucfuV17m8X/PBp6/xymrOnS8/x86lSzz72c9QT6cFnDXMefm9AN57tF6i9YgVWm1uOuDmHh5DfiD3VooO8yejCO1GDDkdPwWdlQKTryyDoEy6mMxoo9MRy1gZ5ueohmcxji9v3FcgJQfixnN6u5LIrX372PJ4+a6DPABc51geLx8J6PEX/+Jf5HOf+xy/9Eu/BMBv+22/jR//8R/nz/7ZP/tI53rppZd46qmnODh4b2O03y72yEAP5ztiNHgSTZfSqCjsEgRfJCMK4KPUPI/twcXzhqseM2RClSRfdgrlz9HWKfkmR5O0X0kMjyF7xXndnFzTWqAcS5xWDcpuvjPO+OAZ9V2SkNkBGm+fHcexf1yS3jmhGpM/PqaIQxDNNgNXfEFuksAeUsqenS6RHLCJFq8rl7CZ4M/Jdu96+q5l3a2FCUIbrPN4U4OyBX2c74nkMKuUai0vxxgTTV9iQCHggyMEX5xKH6LILsiVl6Yw5QUvr7tAIFfpD07y0EfyC11rg7UNUxOpapg2DUrVqY3Tqzhpp+XFQEYKZw09SDRzJK09I7SCKp17o2fm9V9y0I1JqOMYqYxhZ9IwqSuMEVRw23thXwgeTaQylqACRvdApO17OteXRZ/WklB3vSfUkauXL9E0DT6Cc4754X0WSRKCGDBYrLb4oOj6iI9CexZRhBDwPtC1Ae/PEJepnJAW4IDSmroyVEYNizwEoNH1nuCdjOMQWR8vcMDhoaCcTe3RJqLiGuOhtgY9nVJbm5wdWTCqGEdIXNECXPU93meJCyj0jkYWnio5OT5EdIwY1EZlQIiDpFGMis5H1s5zcnTE4a1btO0S14vUjTUKa2QciQduJQHfd2g9YTa7Ls86RLQJqNqh6FH+FKUVXe9QRFzfczLvuHNzxenCoeyEZs8wmU3RRioCYozcv3WPdrnCK0FP+97hOmHwyCj6YeGoqJuKvQQqmdQVGeiREechBFzv6F2PS9qOVpuyuClMQRGiD3hgvVjjes9sOoG6EoS5jgWMsFqvicenEO+w8p4vPbeLUpFXX3uB51/8Je7duS3AkiA6kPNFy6uvHRFi5FOfeJrT+ZqXX70vsieJrkkkekAlCj+tFNHKuNIiaMiZUUUZaGoIqmRtyaH2Jr0FNGgb0BahFTUa4hqjYWfH0jQZ7KVQSSLK6kooQlMgKTvnEZGp8t4l5inpb72LGGSREoAQHK5v04JK0bkuPRNP8D0hVkJNmBbligDBQfBkia23E6nZ2ta2trX3u3mvuXXrKsvlDovF7L2+nG8rW60mvPzyM+zsLLh69eaW2WNrW9vat4z5XjO/sYvrzlSH68jOtTn17BsXtDy30/Oha3NM0n+4e3OHu1+8wuqtWWzf1pSKfOITd9jb6/jyly/y8sv737Br3dr7x5bL2cY7dsvs8e5bCE6kZ4GQiupENjmUBNe4AP/hK+i8tn6L9XUJ6uZYZforxcA2DlO2HH042imWqhE1xJBzjPIB4EaK5YIkhuNDYgBRsnoqn3R8beS4cDnYZhxa5fgwKVlNhpCQwROD6VTzGNGEEncqsZJ8b2lfyWGKrHX2NMfp1wSdKDGf4D3OO4lN9b2w76okZ0uOdY/bdzh3AWbE4ZrHsr0xSYer0TYqkkA44+03QR6MEvgbcgnkLpGK2bSlUiLDYY2FIro+FB7KT44Jj8pGc6I8fa4hHXN4zw2PVQ0fqLS9HpLbRikqa7FamGaJSAwqxaUU8kyElVnmJhc8PvhyXK0U9WTCE5/6BLvn9tnd3cUaIyACpWkuXJDnFXKCWRggQpCCvVzcGnNbh4h3KY8z7k7pJhaHh9z40leEycVodg8O2P3sZ7BmWvqMzxLHqQu7tqdftazXDueCxI91xEQDQXHvxVfoT+c03/s9HFy4IE8zDiMh/+uDSKN458v95HxBftzKQwYdBSImZgBNyr0gycxbX36BdrHi3AefoTm3T7tes5rP8b4XZt4QB2COzkAPTfReWDeUpar2CtOQUhFMEJBGbEGRZEekcK/tPMt5T9sFlLaYRtNUNuUnBLWwWqxwXU9MDBJ5nJFj6ajRvwmsk0Al1piNuW5gh05xyxSn1akNgnNEPxofCWTiOkfwkaqqSDz4ZMb1GKHvHVG1wBIXInfuiRzu8fEh94/ucHJyNMrBQdc5jo/XNHsH/Nrf8ZtYr1re+OIvUM92uf6xj2Lrepiv1ZAvjJrCEr4xJs9amUjlXwF75RdHTuCQZL0jSvsUk3ZoBXUtRby586pSUG3k2eS5v9A5pfdVTMWYpZ2lv8m4SWxH3pdnImM2lvmt7L/x8hgVK49i4Fvb2vvR/u7f/bv8tb/217h+XQqVfvRHf5Q/8Sf+xCMBPf76X//r/Mk/+Sfp+57d3V1+1+/6Xfy5P/fnNrb55//8n/MjP/IjfOUrX2E2m/GDP/iD/JW/8leYTqf87t/9u3n11Vf5oR/6IYwx/PAP/zB/62/9rXfjNn/F2CMDPXrfEaLFI8l6lVydGCJ4n/TV2EBkb8zDxYYJbAPksbHFg5OcIvnJyVkef6FUBJUn35GPnZzEmBOLxetKnmRC0g2TryrvnQH6d8blSbsXp0+r0XwdRz+j+1XD/ea3ZnGuGEAecjwtLBE6oEOmihrBislIVyTBGANWW5QWFo0MmtgAeyRzrqPr1uLYrNd4FNY5aBRUCRSh88tdj5DU4ugMSwuVJFUUyhhUiPJiCy45pRHvAz4IylqPnphOSeG48TNaVhRHPfeE5OxrQ1UZai3O23QyResaHzNhlsh6iNOisxue/ktJ5PTm1USMosiyBE8BHpT+kx2GJEljrC6Lxdoa9mYTJnWN1qYAPXrnpA2IWGMJygtjAIF139P1LjnuFLaRvvf4AJcvXmF/b49AoOs6Xn7heZxz9M4RYqRBEbWlT0APKRZIi+YYcS7SdymBXRYXQ6cVoEfAKKitprYKFQSYEmLEx0jXOYL38mw9rOYLVO+5f9Kx6h17FzqaOmBjjXWKxmom0xlVZUcLXxHVyAs+lMh5zNeZeWTkxCswVhYeOHGMvI9oI2NGqwHsEQL4kBeoit4HVr3n+PCQ+7dupQW2jJ8qS88Y6Z8YmygDA1pNme1cJ8uiGO1QdYeKK+jXaIJoOobAernm+KTl1o01y3Xg4Mo+k+mEC5cvUDfCPBJ8YH40ZzVfln7seofthJsvy9fkYaSUop7U7B7sUFU1Td2UaUJ2D0IjuGwxXce67VBKMWmaBFAQrUcFEEQ2RMXIar7C2B5/4ZwsFrRCxwzSUqxWLWsXWEc49gvilwOHbxxx484LvHrzyxBABZUWB5H5ouPlV+9z5fI+n/nkM9y5P+fGvTlx5aEXMFxIYQGlLBn6HKPCaJvGuR497XyTm/bAJ6OqEKURII6JKBsEtBHXGG2Y7VTUVQZpyWJba4PRVs6fF+pKJ8yhJkZNcCQmFOmnXS/0oyFKJYT3Du9aXAAXoeul6iJEhw89PrgEZMycIgPQQ44qQKWtj761rW3tW9VCMLz55uPcv79lwPlm23o95eWXn2F//5iLF+9ugR5b29rWvmXM95qjV/fp5vXG59oG6r32Gwz06PjejxxRW4kwvDLx/LQNrN5hv7cyreFTn7rDJz95h7Y1W6DHr1BbLme89NIHOX/+kEuX7myBHt8E81GKoCRiN6qoDkiSKyceGYo+Hk5f/1Yx5PjgNmeDzDmGrDazh4qYqq/jKIcczx5t80CjOPA4GznCmjx4WSUwFzc/iqONN7Yf3Yfa/DyHms+eJLNISGIxJTtHRTcpP56uX+K1WuWEdj7UAycEJYzG3jtc73DOESPoEMCqXFF3BoiR4+3j88fy/CNpv1EcPrdlSAWF5Ostl6HLUfLx4pmHPGyen4lIvWhlCjigsiL/PRJrGLXpGOKhhmvIyf0Sx81tnXIfSglLdty4YIljpvhfjGC0JPutNQmEoPAhM/qmZ6KlkCwXKjofkjR2lpKAajrhye/6FBefeIzrV6/S1DURKep79dVXmc9Pi5y2RRGVJkSVWDGGho1IIV3IEhJnTcH83iG//Ln/QOg7qtpy6cnH+eAnPkYzqVMqRWLMORdEgH7d0S5aVq2nD4Fm6jEqojHg4e4LL3Lv+Ze4+uST8ImPMYyjUf5IiYxI1zlhntkYt5T2R8USD49l2AyB8BjA9T2v/fyXOL55m4/u7XNub4/1asVqsRjd64iFRZH6tSYGyXMpVVFVu4DIjCgVUMZDdBB6pNDVS4y5d7StZ37q6F1kstNgK8t0Z4oxAiiIIQibCF3JPwQf0DokAMIoJ5Law1SGuqmTzJEZd3UgpmJBj/ca54StxxoLMdAXoAEFrECI9J0wUofpBKosWzKMJtd7YcOJC9ahJ96JrE9aTpf3OT69y/HJkRTBpWN2nefoeMX+wQHf/4O/hdeee5H/5f/+96h39rny7IeoG0PmNinUOSlcq5Qp42+D/OghdnZ6Hf+uUn5QqZg0VuQ5KaWpKsm15TE+sJDrJOukhskydcaIInrSvCQ/3g95x5j6RAiOrMSS+0IkpFiyGfVzUm5qKLod3jUPy45ubWvvrR0eHvL666/zmc98pnz2mc98hldffZXj42MODg74y3/5L/O5z32On/qpn3pg/z/6R/8o+/v7/MRP/ASf//znAR6QbplOp/ydv/N3+NSnPsUrr7zCb//tv52/+lf/Kj/6oz/KP/gH/2Ar3fJV2iMDPbQWXTtBg4aURNSFrn5g0sh6gANoYvyOGtvbT2PZ4R652AkYwdk8WswJ/UHH68HDjRYPkfLizIsOPZrox9RhhZwtO/358Bmc6/NkzeiFkNcAw8s0fzpAJRKgIqqCDnzYQiIzSpDaNL+QYoC2i6LtBphEVaEAHRi9tPJ1Ce1cZWusraiMpapqbNXgjSUoM0rKykvpdH7MG2++wtHJofDIjQArmuzkWnl/GpHwyPsHIERVtlaE0UNLrRolKRpSQlYucyzSIKliE0UTUSdWDaUpaFsdz7yLAaUjqAC6JerUxZVIy2QARyQmx82XhU0BKRXfXp6L1gJIKEB9rdG2wliL1cJXoqMcb932uBCoGyMyJysBY7TrjtW6JTphPomp/WzVUFUNmbYgA3WEIWeQ01ivekKITCw0BoxSTJuauU2LnkS/KBR9ChVF/kQhDCExgSRCgL7tMeiCls+Jams0XiXGHq0wVYXWhqaSBZ1VoGLAqEqALF40CKOStHfIzs54DZv74AYwKoomnSJR4SWGlQyIiJCZLTIiPf84cZdwfUtoV+zsNFy4dK4Mma739D4kukgjzl0ai/K8O4JfofAY1hgC+B5iRw49ZCf1xs0lxycdfR+JaGxVYesKHyO98yiE/k6YMGK5Bh9kUda2LavVir7vCymjUhCcp1t3BCftYLTGiP4PaOh6x8l8jksgn8oYZjs7Mq6CR+uWqlpBBI8cI8co2naNXQ9ahFVlmEwaorVgNDoEQttxyn1udJ7jxRE+CPuFGT23xarlpTdus2hbptOGEAMffeYKi0XHa6+fCqgoz/FJAzIGQTOL9JMuC4UyaQTK/F0Wz2ysTzb+nU4M1y5PMEbRNIbKWqbTiszeIQulvIPccAgOlMj0iFZuqmZRHRHFer3E9T1dvyb4noVqsUi1gXOB+4dzDg8Xaf6Co/uHuOAlsLFqCZMGZRTaGqrGEhTUzmErDd6BM8SkQ7y1rW1ta9/atp3Hvvm2bfOtbW1r3+r27s9jJ8uKn395H5u0hO/c3KF3X7tEWozwy798gTfe2OW11/a+UZf5tua95u7dyyyXM5bL6TflnFuTvrleN7z++pNMp0suX76zBVW+i6aUVLHnpHiMudI+xQRyDLnEDUfcmKMw8Ng2o73qzCfjGPLGRxLmU5v7Zl7R4RhvMX/lZL/aTNflq01F+qS8/yiqOvpl/EXOdab/x6xp89Dbyn+oBERRo3vavM+yR6mOl9iiiglKE4XZIfhRlF2N2jtlSod2SjFXnQprlBZmW2OFqUWNS/rkIF235vT0iHW7ooA94nCeHPPVZ64zX0Ic9YXNwH9mJokjJZ4sx60oFN5RnkvmC8jsunJr43ZhdGzIEuMoN+ooEosPYdRIpc8y3BvASDo79zWddUrSByqxeeicUE/Hck6K74wREIBLTAzeZdboVJia2s8YizGZIUKn/p5icqPrck4SzlaDUQIwqYxJ+YVcVCk3kCWWQpKhCCEw2d/nA9/9KaL3GKPZu3AeY6t0fGHl0Uok5JWSBL3WBm0Nxsn1Dml1Kcy6+IEn2Lt0kf1rVxgYw8/EkMujGSWUclEvOc8i8J/clvlAA/NC6nbGcOWjz7L/+DUm+7tE31PXljCblPP5FHPOMvbl7CkuTfTE6FAEFA5NRKoVfSF/kLEVOT3tWbc+ybioNF5kDpSYcYpxZ3BKyk9kBmsBVYkMz3hWij4IO3aIIiGi1NC/lNxD23WSa4gC5KrqurSJUhpjshxMYkJXwubsvcO5oS9rrUQGSWuR9omR6B1tt+I0RNbdusT+x/NO7zxHpwuCVlSVxdRTvvs3fh/YimZaSz4l5Ek0JSNKgd4wXgpYJ4d5z8zPbxdDtlazu2Mlh5Ok5iubwV4Z0LFpMQSCFlaVPMlL0ao8A+ekENQHAR51yqMZ8hSrVcd63RVFlvVyRYhJKqd3EotXqhR1R8D4gDZpHIXMdr2NA2zt/Wfz+RyAc+fOlc/y76enpxwcHPCn//Sf/rrO8et//a8vv3/wgx/kD//hP8w//af/lB/90R/9uo777WqPDPQweiraYx60ilRBkskxkhyPLEECwjQwkl9RDyKzH8bawZkt5J8xcjn9kp2/9G4oGdKifPYWR85+Yhz9QHlJ6rPC5uNLTBOvnF6VBDKJLqzsO6KFyEnIfKrCaoG8vDKMpLTb+M6VuC6CBFblBRjTCypGxXodWbepilwhL05AR4VJl6gTyENpjbU1VT2hrhrqqqapJ9h6wlpbHJrMEBGFK4/D47uEl3uODldEo0WLL4oTLIl5jTa1sHYkBwYlCfxcIR9Hd3vWxLlFpDq0UAcOriBp7ygIYA0qy6eoiDYGk5Csg54f5Xu0A70S2Q4lUJ4M9MhubfAiVZI7Qiz/S7/EQIwebZKjo4TxQGmDrRqstUkCRSjDYvAsV2t652imFc5p9EJo1ZarNcvlOrGwpK6lNVU9papnKG2JyqSxpJKTF4rzu1q2rJZrZpViakSsZjapqa0ZrtWH5JRpQjpJCGGk76UJPtKue0zUZTUavYPgsMnpV1oWDKYxmBCZNH2SuxFgTaVrKlPhTBCgAWO2DXkehS5OJ/afGMVJNAJSii4kEKs0uNUaW/zUmCjnsiRUSI5VoE8t0rdL/GrOwd6UaX259Jij0yWni3UBDMU8AtOzDKEluDlWd1g1R5GoQkYjMALrteflV+aczHu6LoIxVE1D1TRCT9jLc8yLr5D0WFEK7wPOeVbrNWZhxOEuQLiId471Yo21Pa7rqSpLUzcyzq2m7XvuHR1BjDS2QhvN3sGe9NsQWNuKZjKX83c9wcuKPfjAerlC6UhdVWitqesKTcQrLaC24InrlsPVLY64hXceHxQmykjNc+3xfMWXXnyDe0cLrKq4cnGX7/rk4xyfrrlzb4mPgRCylJRL86ImxCCBgFSpMJ7V4ngFV+ZuGMPzCjgQ2J1ZLp6zslhMC9m8oDVZnmVjMg/40BLQxMSGFLTI2KBXRGA+P6HrWpbLI7puhepPUX5Nu+roO8e9ey337wvvs1KwXHZ03mO6nn6xJuzM0NZgK0s9EX3SJjiqSqN6R1SGUBnU2XfJ1ra2ta1tbWtb29rWtra1r9vuzyv+3ZculL/XxxParwPoEYLiP//nq3zuc098Iy7vEc9peO21J7fsWe+BrVYznn/+wxwcHHP+/OEW6PEumlZVYTQIIaJjEsCImzHQgYF5yP0VAMLXYiXsoMZ/8GCp+GYM+a2sfDeSEs8pxwfinBsx5Lc6kGy4se+Qrd44yDjFqeJoj7MxZJW3y4iK9FeJIUtM2bmIS7VumXgjn21U616+1NpgTCWy18ZgjUUbi1M68/imE0uwfdUuiUeB9aoHPZJfISdzE8tGApFIUU4qAovqTOs+aAWekwszc6Hg0DBkRudBwkauT6W4OGH0zEsMmVQx6ShMJ6iUKxiexcBCMjwpNv6SuJRKzNAZBIBKMXOtMQm4IKmDICzOIWArTQgK1cv5e+foe2HxHjqCQhuLMZXE75WG4JFcxSCxjoK+9/S9o9IKqyTeV1kjcfHUh3J8XBeAg7CKBB/YOX+Oj/2GX5dPS2XMIL8het8iN5NBLkqhrMijWyO9Q6tUVKak7zz+HR/hiU9/B7vnL6fTD7H/DDrJccSMf5I+qoiZ2TgF7qUv5Sc1lsqg5Ke0sTz53Z8CrVktFri+pakrrNkpXWbddrS9ozBKbDzLSIyOGDoUHqNaNhAOo07qXODoqKPtRVKdBIwyxspzSUWOMcW3M2Alz4chRHrnUL3GJwnvnE2KIeD6XlilTcAYkXBJgwrnA8u1FAPaNK6apk7tFXHaYawwiDjvC8gkKi+y4yqmQjqFsSbNnGn8xgA9rPs5a+bExIh8Fme27nruHJ7QuohGM5vu8Bv+u/+atnO89NohfR9EkgnKGMzx+pz3KjPcA0iOs4Ntc+RlayrNbKLL3PDAv2MESTm7k37opQ/HvF2SUOq6Fh88fbfGhx7lO4g9vvd4H1guPauVK+Ok7z0+RpT3hM4RKy8F3EZjrCEqMDHlXlLOB/MgAGVrW3s/2O6usBkdHx9z6dKl8jvA3t43Bhz/Mz/zM/yZP/Nn+OIXv8hqtcI5x0c/+tFvyLG/He2RgR6FlUPpRIEmCX+y7EkY0JMCDxwW2+VFuTEXpwk2e1dntpZf84te/syoSIE2DCm+s7uNj1UI3hK8evg76WqdcSY2b3o49MBYku/lrEs3JDDzzmfZRQoQdVTpHgCfnDGVHBWtSNIoDAyDyVvL7leMkb7vcc4VzcC80AgqpM2TBMtwF0jVO/iQXt1KpB+Sf52Oo4naMpnucuHcZbr2CGU6QSCTgDeZbUJbSR7HkKQlQkJCktrbE7Mu5bhRR39mZ34EgB61a3IYkzRDvg+dtNSCItG5Jacs9aeAJsSKECzEiDGKg/MN3stLVvrSmeczburcnkmD0diA0PxprDVMpjXWanz04APR9zjvIekgGiWoTKMHmRZQRYOxLF5MRBWJx7xYURhbUVU13gvjidYCdqmtpbIV1taYqiGicT6k7i3HLGwgY/8zU6GkXhfJuqAxnRdMZdDRYCqLqQUlblDMItS9I1pH1IFYV/hKs145uuUa55yM9uSod33PfDmn7dZDwyoZETqP27ToCQmRH0MEHYs2n9EmgUQCKoM0oqZrV+A0lYkwsaxOSWAFQdQ65zfGe25XYWWR8RVDL4B/M0FFB6zKk49p3xChDwoXFdoISr1tWyJQTRq0kSqE4Ec0eKUN0iIjQPTxbIcmSzZlZ987j9MO7x1t37Fet4SuFyc8RNYxcufuXay11HVFg5K+0Qdo+7LQVFEWP9EHohE0siZiklMZtUZkVgxZkxNlQAe09+ASIChGXN+zOF1wD3jx1Zr5Yo9zBw1KKZ556jyLZc/Lr57StZ4YpQML+5ApY3VzTh2CIvmvcecY2FSGH9ic1xQPn0W6vuPWGzfwUdDaua8rpalsk8avUAGuW3EavF8TQo9VBqMa+t6zWvaJvSWBwUYvl+A97bql6zqCd3R9x3y+pO0ci3VHxDLveuoI2ocHAz5b29rW3ncWg2J5d4ZrLbMLK6pvIK38t6J5r7l37xKr1ZS2nbzzDlt716zram7ceIzZbLmVcNna1rb2K9pihPVxQ3da0540b7vt8b193nz+MQGbAzv7C574yOtvFe8v1nWGL3zhMnfuTPnoR+9z/nz7kOsYJSzf6YDfUNuuGb75Jm3ettt37TfP0mo+B2KjJMNzUd8QQzajfTIDiMTOSqHgEEp7CxtiyIV44UwsYtj07Gdxc7sYAZ3IIuQYMcVD831tXstwcXF8iM1LO/NnHO2mxoGQB69cDZtnqEFm0M3xCwFBjC5qFNMQiQ9JMm8edBQNUw+bC+PwiIBcsbN5pyrFSmumkxnerUH5lFxNx445vqtHifnUH7IENaR4/4i54yFTc34mQ/8Y33KO5Y4YQ1K8VKESOCIVasXxXSpiFMlfkLj8ZGIIIcl4DyozD38+5UJTUllHVJIz1lriyFopQmLDIDE7jONdihSbH8fGY9y4983if3lmIXjuvvQad2/e5PyTTzA92C/HEWYDw4UnHudg9xyTK5cGRuJ8lMyYEWF5eMydl18t/b/Z3eHyM0+CrTZaGZBYaZT7003N9Y9/mP3LF7nx3Issj09AB6KKRKMJWuFipO89IYaNx+p9oOs7vHdDUyoE0JO31LpEsMs0Uoo+8xwjTyT0HTdfeBnXO658+INM9vcwGrCavkXisKn/hXCWXT23c2QgZfHpmiqkpLUfLkLlGDD4qBJjueQmvJf3io42ARkogI9y83n/MrjPxJBH/SCmgR5CwCuJ/7rghcXbyQANMeKAxXIpwCJjMFFi7FFHSMzc41mNFI+Xppc+GHMHymCqEbhME0eM7nKBwQe6tmdZrTk8NnR9zXQiMu/nD6Z0vefouMP7UDp4GaMpfjsaQpttxNlpX6XnoIY5OW83zoG8RQzZB8/8dJ76rhptq4rETr62zOgRosh4axRaWXyI9H3YGEvjGHJM+QkfhJXHe0/X9Tgf6HvJYXXeY6L082+q67m1rT2inT9/nieeeILPf/7zPPvsswB8/vOf58knn+Tg4OAbco4f+qEf4g/8gT/AP/kn/4SdnR1+4id+gr/39/5e+V6P55qtvaM9MtAjuT3CqqCNJE6VyCjEmF4UGexRnLKUfN9wmAtUYZzeK98PL/vhmwx8AFVeoKMUNeO3wHjyHhzn9PIdHRPkmD4jWLMjFUNxcMtV5eRjGP4mDPcz5DOT4x/GV6OK8y0fJed9hArOrAh5O53QHUUKI+MY0jE1QAi0XUvfd2TpGp2q9gMQVARlhCUjozhyYjmAC1mqJEgyOKRnFhAWDFOzu3eRx68/Tdu+yWtvnqKNLe3oY5ZcqeQOQksMTpLMYXx/HnEzbL7yzV6lU/s+ZEERc3ul+zDK5uVJqu43o7aWCv6Y2sBHg/MNPohOcFUprl7fEaCH0TifWzMvac44uuncKr3orY1oLfI2dV2xt9dQ1RrnHcE5XNfS9z2ZPs8ag4oRqxVWZ+dBHFhixGhByWobUTaAypRqKjExNDTNlL4TdHdtFdYqpk3DpGmomgm2noK2OBcIAYw2hOBxmS0j5vEjbaNMav8gDpugveXcSkM1qYgobFNjmwY7nWCNptmdCJOEa+m9gyrSmcj8bs/yZMG1tkeFvMDSrNYtLrQsV31pT9HJAxWCOFGV3H8IQfb1XiRx0nM11or8ChEVPTF6fIB+4YgKprVm2jQc3o10XU/bOfpEZ5fHexmFSmGMoqoN2kS86zCqQqkdUGsIq6EPpDbzEdqg6KOwU0SlWM6XtG3HLAa5Pq0SmjmP9WQhJsCFaF5SLkfmhhCiLGyCEqR2WtyuVkvu3btLcAHfxzI+WrXiaHHMZDrjIx/+MM1kSjOZ4F1AzVfCSKJkDEXvCc4TrSGONCZNZVDWgK5BV3gfcS4IU0uE2LZE5wv6vWs7Du8fc3qy4N69Ey6dP0BHy7Wr+3zfr36K5dpx8+4LtD5AlIoMrQUUY0yFNlVxjAfAhxr9f7xKz//meTemxb0m03EOC6ChLfMXq9WaLz33Juu1w0af5nOLVpp6sosxlkkt4Jw8gTeNwVaayaxC1Q3rVcf8ONK1w9xTrlMJXd9qsaBdzej7ntVqxf37R7R9YNlFOq84XK6oa4dR623Idmtb+xawGBRHrxygTeTqp25/2wM9nLO8/PLTHB2dY5t4em9tvZ7yla98hL29U/b2TrB29V5f0ta2trWtvWs2v7XD0cvn8gL8Lbe7+/ol/u0//vW4XkJYj33wTa4+fetMiu9Ba1vDv/gXTzOb9fwP/8MXHgr02Nq3n23ftd8MS7LZqZpNKSkHjCqeKRSUrSVnP0QLhtK5lOzdKObJW/HQvx+AKkQ5QYnnPgw9gNqMA4w3I0etB+mZkowv4IwzgIMUUN6IYTxwhSRJ4/yROnOPDDFk1AgMsRnBVCm7WRgS8o0oEBVtOYb3riSfh8S4JIfj+PyleTIgQ+Sah3h/yg8k5mnQoA11PWNv9xzOnaJOuyF5GxnkKpRJz13YKqSIcNwsEnwvlfXj+zn7L2p4hOXX3IYahRQLxgQI0VqDD4TMX6JyzgJC1IRoCamQSRvFzl5dJB1CeQQ5hvwwGwAHOskZg4At6sZijAA9YggE7yU+XdhTclw/hfBTgahPuYci+aJjkiunxBqj87z2+S/y6pee45O/7Teze/6cFHxpsMZgreXqd36cc+cucHR0zPHxMTFKrFgwJ0PPP7p5m1/6F/+a4DwoxcWnHufCE9dh0uSMh7SDBm1TW1mDtQ0f+i++D992uO6nuPNijwseHwPoiDeS2F63PbsujMaDoneO5XqJ6zelgEjAhjGYY5g3cqxVWFeynLwi4to1L/yHn2V+/4h6d8bFSU2VmLpXy4j3EjcPCehRJoZR3kYrhUms4iF4KXxVlfRb+pTHoPQ/EXMRsIdKIIm+63HaU8Uo/SFLmZ/1dyIlXpznjTIUIsMYiSK3opIEinMdy+VSvk85Dq9Evn3drbFVxaWLF8FYjLVyr10vF5sREWGYj8vQTzF0tAYMaCOx7xBJOKhUiJsfo7TperXG+8BqsWY2naCiZne34YnHD+hdYL48xMfccOMcmB4xbmyOJ1QG4uTnNJoA8jtDjebEhx0njn5Rir533Ll7mmLimZtIp6LbOuV0bHpe0lbW6MT2blDW4npPt474twghheBxfcR3FSEEetezWq1xPtL7iI+w6h3GBLTfxl629v61P/AH/gB/6S/9JX7drxOGpx//8R/nD/7BP/gNO/7JyQnnzp1jZ2eHL33pS/zNv/k3mU4HWcurV6/ywgsvfMPO9yvdHhnoEby8yIMPBC1QVkVKaCadMOIZJGT2aLOkQ/EXB+9s9F58wOLIqQSGFxEUh4zxEbL/u2FnwQODA1Mo3R7yOhnvmZ0LUrL6gY2jcCTkBUhSCCmXWRKV5YWdWyHKgqc4gIJa37jn0TkyvcegZacG0MtoB53aVZX/UdYERUYjjh2odFOlnTWYij4EFqsVvXMYdGIMGFgntFIiuRIlOa+z5qBOuOXcXowbbfw8xkuoOPqcfKWpAQenbthPE7BJosSlhYO0u9aK3dmEj3z4CXZmE6qqxvWdADWiyMpkzymze+QEd2l7NTiOWmmMFaBKDCIxY6wFFKF3OOfp+4DWhr29GdPZJC3ypNG1VtSVFS1AL4sarRS20kybCbNmksA9oTRBZkaxVYVCUVeKykJT19RVJftNZ1hjhFUiZGT+0A/kWYkzIlRhpvQ9ay29D8TOg+4IMdB7Ofl8saLrPV3bYrXmwECtoO972hAITlDZPknFkBPzqe0mkwkHBzM0c5bzPqHW46ZspR5QzEqBtUbYGDQYazh34Tx10zCdTtFa5ExC3zPb36eqKrQSfTxtpO+F2ON6N1QoCKok+8sYY9jb32M620PbXZQxwkYT/WhwyrZ9H+ldRBmDbcDOJrJAtVXS1ctyIlpYSIxBGzMa9AlQ5R2u6/FekL8haJF16R3deo3RBm+FAjNWFc45gktafulZ+l4WHy4GTNA45zFaYeuaqnGy6Ejn1QG8E9kYk5FMGZ2emGmiytUJEaOlz2dgWCwlCoKYbOoapTXBeZaLJa+89gards7jj++jjeGJ6wecP+h5881Tus6nMUpi9jgL8sgd+8yCeORwx7Jo21i3bcyF6swvMhtEdIioEMsiz6SFtSxudVq8JaYNBS4hr21doa3MAcHHIpmU6TlDiKKFma67a3tcL31Nfg9EjwBscjWAGub4rW1ta+9nSz7ImQqKGKE9buiWFd28eot9396Wp1PefPEx1icNR6+fI7wFpbzWgfPn71PX/UO//0aa7zSr+1O6RfWW1yPB4S1i/r233De375KtbW1r709bLzxvvrhCG8Vjz07feYdkMcL6qKFfDe/X7rQu8aKH2fG9fW69cpVbr1zFOyMSjcDyZMYLP/8s+Pi279psde35V/8q8OKLJ3z3d7/E9evHj3zdW/uVaNLnuq7izp0rTKdLzp8/pKq+vYG/30jL+bwYcqI9plhJHIdgzsRXRwm8s1YCq+9wzrNJ+KwBkeOSOb774FlHH6hhPzV8n8tSchL+7I6bM9kohvzAhSJtkhO6ahSjzH+OLy59ETPY5Wys5WHNMlz06Pthn3EMWW3EkIdNcww57bCRCN+Yt5UkhQOxSJHo0Vorgx8E7JOuP0lGj1lJhvDxQy7koYEhRnkCNeyfzzFqBonR6tQ7xtIR8n1dWS5e3KeyFm0MwbvCNhDHbaxVYZPIn+e4VL7GDPQAYbxQaPlbQfQSiwpe4rV1XVGl+HKOIasEMjAmMYzkosAEVqis5QzHucQRvRd2DW04uXmT9vSEx559kt2dy9RVRVM3wuwQRowq6RjLoyMO37jJ0Rs3ShxRnpdOjMtGWJR9gN5JFDg1QNdJfOzWmzdYn5yyODpCJVCRj1GYJMIQLystn5rMWstsOmWtOvrOk4uCc98ZinfTs5pNufzk4+xfuYRtLEprJtMpxlqqyhI6YT/v+w5tNLWtUErY6LNMSIQkEx6HcRWH7ITSmrqusXWN0hIbFXaLWPJD2byPiSRGoy3oJDWNFnmVDPIQ4FOSKhkDqlR+HvIMQwzl+cQkZ+57J9edASM65wJGwDkkrpkZpHVUeC8MHdoYjPXkCH7pN+n4yqc4QEx9eZyTGYbUMBTLL0OfN0bi5JmB/ujklN537O01uK5ndeN1uj5Qn7+MtvXGfCLgGB4SQz4zfY1jyPmZxY3Ny6YbtjFPJ7BamZvYKFQUybGYxoF0vJCekdYGVXJIlLYuU20cscQ4YfIISWrdO5GnF0KrgSFqnKfc2tbeb/ZjP/Zj3Lt3j49//OMA/PAP/zA/8iM/Ur7/8R//cf7tv/23/LN/9s++puP/7b/9t/njf/yP86f+1J/is5/9LL/n9/we/sk/+Sfl+x/5kR/hj/7RP8pf+At/gd/7e38vf+Nv/I2v74Z+hdsjAz28J1EPOWEISKwKhABueLkMYI/hxf0wz1a9xe/FRr5/ATYkh6BotuUXD5DR2XHzPZSck7Npt+EtkFyvzasYeXsx09IlPz9rD47PEIGQEsZmpBGYX575xSAvzLxzdjI02lZJO1Da0Hs9ul+VfJrRmwsFUSdQiMLHiEmtlEjw5G8piC/HyeF7FQPK+/J2jihBZ4N8pi3YCavec+f4iOVqTa0sGo0PIgVhlFB/VdqgSLqNtpJ/tcHogFGhPKMswbCxsCDycJrUYdvy0i3f5Da39NTi+EXRmgtRFhsWzaXz+/ym3/gZtDZMJ1PmLmCMJaLw2S+TXD++i4NG3uhlHb28yI2xVEqhvHymjaWqa1SEftXRu0DXB6ytuHrtPOfO7RGUIShxIo01zGYTQvREhLZLE5k0lvO7u+zt7qI1hJgANQRCEHT3zs4OVdXQNFBZ2N2ZsjNt2Nvb49y589S1yNF45wnODQu+KIhebTVNU6O1Kpp72lqUUiw7j+oD87UkmLyX9u/vHCVgiMJq+Mh+Q1Ub1r1iEUio7IjpPMZoUIEQnNxfjBzs7fPMU4/zur7J8eGcdackeT7q/zFR6Agzi2Y6sUJlqBVVXfH4U08xnc6IXYvre45u36F3nstXr7G7v8dieUzXrTFVhW1qwnxF23ZFsiaDjJwLOBc5d26fi5fPs3+wj5lcGsZGGAOeZJ5bLSPrNeja0tiKvfPn0cbQduKUaSMLCVNVRKBqKrrawghoE0Kg71ratTi4IQqAQOFhtSb6Hl0ZdG2oqppJmNJ1vQA7iiPo6VYdwQdc62EVaVcd9UQxmU1SkYISgEaUCoS+d6hWltTBGqxG5IOURumqLJiMAm3SgsFHVJZYSmAPW1l29nYIPrCerzg6POZn79ziwoVz1JMZVy6f43s+8xTOB/7F0Vc4cr00qKLQA44rGDbWoGfBHmf/SgucmIBl0SSiobSYznP9aNlPFSI+gLHCJFJXcv6qrtDaElzSBU6Asa4XHiVTNyir6Z3COwRx7WQhqrUSWZ3Wg/KwdqwPWtr1ivVqxWreCkOP1sS+l4W1EYmnhwZztra1rX3L2Mmbe5y8vkcMX9tgPrp9js/9o+9ntZi+bTy6rjs+9amfp66PvrYL/SqsX1bc+fJFXGvfKUa+ta1tbWtb29rb2umh49/9r/eoJ5rf+n+9xnT2iDtGOHl9n9Mbu8NH7/CuvfnSNf71//Ib8L0psi0Ah3fO82//0a8vx30U+8IXPsXOTstf/sv/8xbosTUA2nbCc899lNlswac//fkt0OMbaDEImWzIrK4lshsHNuj8I3tASep+DT74xjyQmDdSYnAzRjzEkGEcQx5kIkrBmhofWBVgRokhn8lJDiHPkRzs2WOkcxd2DPSoQG7zXKM9GBLMCqVNOe5GMdvG1eWsZwlul+Yei6GPo7UPCdvKn7lYcAhUb8IMhN6B3gcW67UUC6bK+jhqKq2kMFBFlWJUiTFcabRKxYIbLTW+EFUKcDZiyLmiNF1blkAZHyfxeOMTw4dU6wxdT6OYTWs++PQ1lFJU1tKFIKzZOgzJWCW3Gl2OW20+fjmmSI1HTWHNVlqn4jAIzuNDxAdhedjdnTKZNMLQm+5TaUVVCWhBnrE8L2sM07pmWteCSyDLBqcYWogJCFJx68tf4daXf5m96W/i2pPXqeuGyWSKsYOUcwwh5eoVh6/f4Av/739JDAGjFcqKhIW1hqqpMNbQhwjB02WZkMQ24hcrutWKn/vf/neO37jBhUrRaGES7yMCXFBawC2JcVzY1OU4k6bh3ME5TtWc9aqT4tkMYMjtW/qGYvfcOT71W/9LZvt71NMGYzT7BwfYqgLvCalAq2s7KlsxnU3o+lZAD9qgjSVGKdocnmFI7B0C2phMaqY7M5qmQdvZBihjPNeEAK4XJWxlNFZr6skUpQVkEWOSOVEqFd+RigVzhXAs/cY7h9IpP8EAGsAJ+43SwtStjSFaiTHnvIU8y4DvJbcRXAAnUudYg61siiGvhMI6QowqxYTTmA5xYJPJ88woYyaXLKwiwqVesnXCTN7UaGNwXc96tebNxZzpbIIxFWG54PCLnycC5777+zC1hWgKuCNLKz1o0kYPjSHnqS2NkTh6f+T0XZ4EzmT9hNk6UgqvTQLfaCMAtBgoTEsKhe9CkoCPKKPw6fuQcqUyUaoE4grgwTuFaxzOO5zr6Ts/gIq8LyDIh4sHbe3b0WYHM2xtcd2764va2jI7eLTFW1VV/ORP/iQ/+ZM/+dDvx6CPh9nv//2/n9//+39/+fvpp5/eAJr+4A/+ID/4gz+4sc+f//N/vvz+Az/wA/zAD/zAI13r1r5a6RbxJJKTkVznGJPGXJ4F89aDFIUaPiyT5APz2EMX56MPs4Oejj1+AWw4vsVbG7zTEdxC/h4lGh9gnMggkozEHb/D1XhhMDiWA6OG0FipdI7xfeTk5abuWKZ0M2XhI8COQbNMnB9V7iuGSPCe3jnaVU+37gUhGMNwnTGWZ6QTOlr8etGJC8ETvENQwXF8OYmpQ2OUoaka9nd2aE87KquFqmqEHM/HL9cZQ6KRSw2nNp/DyBUf/soo4jOAlLydXNMoYTzsRpa2y/p3Y0SzVkoYCVLS1VrD5csXcN7T1BXOeWEe0YNTEZMnoNhE+HZdT+cCk6qhntTYdVqIaI2ymuAcbdsWEFRucwF/64ScNVRVxWy6A0BVGZqmwRjRdrt3/wSlDRf2d9HAZDJjd28fqzUGh07/KTQqGtKDHMklpftIDDEkaaWmadg/2MPYirpu5FqqCkbjUitxHtfrThDNXhD43XqFV4F4fgKNJXQdvvN4FEGJY6SU5v7hEZ1+haOjRP+nNdZW2AQosUYzra0wjPjk1CSgR0jrMmM1xurBycs9QcnCzxgjzBMxiP6g98SkcbdadzjvpS/oRNOWQCchRFzvAU9TeYxa47tDlFFgFTEugVjGu/Oek5OWxTpgqxqNpqqEycN7CDrJVykZD5GIsQZbGaHKC6GMf5WeiTGaaA0qSn+KQRGCFpmjXqFCLzIxXV/o8FyS7IlhhOQePWdTVYm1I9Nnyhzhncf1jqoyyWmXdjYIejzmwZPGljCyiORRRJWiDKWkUsAnQF+Miq7zLOYrXn3tDdbrBU9eP6CqLBcvTJhMDPePO1aOIuGS553cDuOwxZnV+/DF2Q02Xh7xTJBEfo9nvstofmstytRA0qKMEN1oMR6HxWO5xnL8My+osmoPhW1n/B4htWt+FGcKhLa2ta29ny0q1scNqEiz32EnLg33R2e2mB/vcOf1yyVZdf/mBbq2FhavtzHnLPfvX6DvK/b3j2ma7uu6lYeeo9O0xxPa01qqnbcsEd8y5pzl3r1LrFZLDg6OsNa/15e0ta09kl29uuDTn77N7ds73Lixw4ML/619q9p64Xn1y0uO76/pVoHg4bVfXjKdQVhHqsrz9NPHzGZSSBCAE6+Z35I1cIzQr6qv6h0bo8I7Qwhn3qlRveN7dmzWej75yde4evWI+VzzhS9c5sknT9jf7/KJeGwdudwGrrbh7Q/2NZr3muPjA9brKV1Xvyvn2NpXa1I81fcV9+9fZL2ecnBwtAV8fINto3gtxpTgjRsL55j+3owhxxIbffsTPPALmwGIzRjyAzvm4OPo0wdC1jmOcvYQqdBqI3SxeXI20RNFAKPsPgAyNq+rpABLPHSoPl/cO+TWc8+zf/E8565cLDHlHB+K4/YOER8C3snPhlxKiaPmOP+IGUNlZgWJgYwTu0N8PMd7RO6gqSq8zfHWzeg5DBHf8rxzLCezvrxlDDl9Eimgi3wR+dcBWLMZd8+xmjhq9Kg206uZkSAzLWitme1MCSFKPDIEkir2cMJR/1GlrUTGwoeINUmS2uUiRomFxhDwiflkXNw4JNh1KdbLJon0BqWkwOvOyy/Qtx3TpiYGz8HlyzzxnZrZ/q4k4VPMVMZeeucmsM4gN5Tj1uk5xcjsYI8rH3hS5KqNYf/KZfYOzmGbZhTGkx7sel9yHcZW7F+9jFZQzY9RrufgwiXUZMLhzTusF4uy9+1XXueN517k7hs30hBXiYlE4rk6xZEDcSNZX8+mHFy/xrmrlwXgkcELo2LgiMRLL33gSabnDqhnk8SiID8i2yI5lPzc80OMqW2Cl75odUCrnuDXRRYbuo2hGmKgbT2dE7bnCCm2rUoBG1mWR0vLaSP3m4v2ZOgO7MA5VqvS9cQcu1RITD16fBRp+OGaN2PHeQbJJ9DGlHsuj19R2DwKW3dMyi7DTLA5ApXkUfI4Hc9jRZ4mfe59pGsdxycnaNfTXLxMDJ728C79Ys7k4hVhzs59cBxDLnPYmRl3PLWqh32R/o15XuGMjQLCOf6rFLaqhHVHG8r8kdp94/DpeZTDvuXxRw2d4/kPxJDP7ru1b3c7uHrAH/mf/gjL4+W7ep7ZwYyDqwfv6jm29t7YIwM9JCEuDnki2S8vBecDMTiBsg1vKQQnnAnb0v8H/ZZHsORIJ3asDf83Veznl7qKD76AylFSMjljCeT9nuirEp0akYEqCjYooOTvfA9q4yzZRQ8xFic87zrctbz8VZAq+jHQRRmRAdFGs6H1FwcXOoAkFr1LUgIRq1pO7y9oqgm9azG+Sq6bEqfES8sbRQFKRK0ISuFdj+/WEJzsk1lK0o9WBqsrzu3t88S1a9BFjm4dMmmEdUHaVEAilRG8gVBQeeknJqJ0kJ8ETth8popE2Jc06EJieChoj2IqSU6I7zVISwhCFUlkG4PXCuElCcQoifimnpSF0GRS8fGPPUsgMmmmzOdLagvWgNMqSbIkR08L6CCqiAuexfKUxWLJtatX2Tt3wLKtsMcaU1nMpMav1sxPT2jXa4wSEIgioLUwDJhKQBYhanb3aqyx7OzvYq3FVBVt1/PiKzfoXeC7Pv40B7szzp+/hKmmrI9v0bcLTKhR3kDQxFgLatd1Mu6SQ2gS8ERZg1WKSikO9g94/IknqCdTdvYuoKuKapbodTMqGI/rPffundC2LadH92nXK07v3Sb4Dv/MJdS5Gf54hVus8FVFNAaVKPyef+El7n3xS+xMdphNZ2hjqOtG7s9opnUFu1Nc72nXvbCcVBYXIovWpQVLhTWpn47R5dqAgcl0gk0o2PV6ievWhL7l9HTO4eEJ3gkFnbYGZSzB9QTX452nW/fo2LHTtFRxSX96EypNPa1QGww9kW7d88YbR/TR0OxfQtuKupmURZswekjlgbUyMU2mFaFv8F1PTOh8WawkisNaUVtD1zq6TqgUTYzQB0If6elZxVUBpvje0S7XBSgXz4B5tDbUk0mKH6hESiL30a57vI9UlRFNRRTBK+qYJEzOOJdGG6w1xN4nWZck7aI1Vd2glEebjtgH+lXk/vqE//CzP8P58wdUZsrlSwd858cuoFD89H++yXrVYyuNrYyAaVIQQivRihz89NHC/AHHXQ1UhmXOCGmalgACMaY5OVUBKOElikqhjeXchYs0zYR27aRqwMj8vD7t6HufTq+EPtJ7dERAVXmBmxcYG+APmbCCF9kgCS7kuXNE3/mIsaitbW1r7w+LEY5eOUC9vs+Vj99l9/r8qz7G7Vev8H/8v34jrhe3OgZJSr2TOWd58cVnqaqeT3ziCzTN/a/63O9k3bzm9i9ewnfma2Yo2dp7Y+v1hF/+5Y+lKuOfx9rFO++0ta29D+y7vusWn/rUHf7lv/wAP/VTz77Xl7O1b6Ad3e75hf/jLm3X4fsIq8C/+1/vMZ2t+OR3PsHjj8N/89+8wFNPnQCwWln+H//P7+TVX75QjvFevYum044/9If+dz772Rf5B//gI3zuc9/JD/3Ql/jMZ26Xbb73vuM33HGYI//oIauvwuS9/yGOjg4eBK5s7T21rmt47rmPMpms+NSnfp6qOn2vL+lb3iRpOSrMIMVWYyJWjeHBwOkDiT311jHkUU7vgc9HR5H4quIBKfAw3iEHcYfY5XAlWTI739MQw9hY948DweUChg3OJvhyjKeQHJ/ZtchqjIEvAKno7OZzLzB//XU+/Ku/i3NXfu1QdEKKKofMlCrJSo2nXXUYbfHBoYJGmXR/gRRykdgNKvNipGhMikdL/HB0WzmujUYrzaRu2N/bBQ9ru5JiQckKlzyC0QihRshsB6S4nMSYH/rMI0M7pID5kAJQo2sZycSUhh7aV+pTJZGQCypVzKWkUuyUD2Wt4fKlC8QYsVVF1/aJLReCUjDOQWQ2WyW5ga7v6Pue3Z1d6umE3hl0YgvQ1hCdo+taYXAoTAZxKBZMktFSsDeR+FxTs7t/Dm0M6/mCf/eP/z/cf/Mm1y+fY3d3h6e+/9fwHdevEdwK37fC1psq62KiyY1hs0BXJ4CFMhpjDXVtePzZD/Dr/s//HfV0QlVP0dZSTScZFSDxZwLBR5arFucd3XqFVppnvue76BYL7vynn6E7vM/T3/MZ9q8/xhf++b/ixldeSNE8xRf+7U/zpX//n7DKSBxbZYlsAQoIc4nFOZGnJuVuDq5e4Tt/63/FdHeHyc5klM+Jw5hSimo65eO/8fsJ3jPb38P1vcTxvKPtOlarNgGXMsBAitsInuAj3gVU9NTWYWJPaOdglBTwlVimPHvfB05O1ngUtpmlQsUkT2ddAbKgMphCSQy2MgQvbRrK2FepWFKK1bwL+BBRQRE14CUnF4g4XAGBhCQRvjEnjiYtrRTG2jILF/wBMQG/KMAskC5i0nVL+m0MTNNpWy15szIXJrl4bVDaC6jGRVau5fU332TS1HzgOz4F3Zo3f/rf4Puey9/7X1DtXyiS27kgVPI4g9z7eK4Z/tj8cpib80fjmDMpDi5jdACKpflVKSbTGdZakefOxcgx4jovTM6jXWIIqJjGz9lwNmfm68S2QgLqjAvT4+i6tlGarWU7uHqwBWFs7Wu2r4LRY+yaCxAioAgxjnTNAqPpf7SneuivDx5bNlAbv48Qw/kAariSAhnIlfNBPlUPnH68YMjHGwELyj8jCZPibuUN4oPe+ejf4khu3MHorGPECZQXg9EDC0Q+RH4BlGtJSV9xKrMDKAlRYZEYgSmkUZKTnJOWgiYNQdCrXe9x3uODF4dB4Jfi4CmFVQoDqCgyLZUFm687LdeUku/QYyc8JtRprnjPGMxhJZDbadxScqlnO0cc/Qytm6FGqsCpzz6SmG7HlO+VUlS1SL1k51EnncGNxdcoSWuUwmpNU1tCqAk4Fus5zjuMsXRtx2K14uR4ztHpnHXbY22DtZXoF0aE/UGPdSeDAGSsxlhF6xzOB1zwBeEJco3aaJSp0KYGbYhKY2yNraeAoXcy7vICOeY+hWLSTDi3t8vO7i7TnRlVNaGuKpQxib0iEoKTrqI1xkTqugIifjajsgZ34QLR91hbE0MCHOCJQdg10LII8S7Qrzt8NUkOY1pYJQcQEDBYjJgE5hC2PmGgKLG+Ebgqe5558VvZBq0tWhlihPlixXq1oGv7pG2pwBhxLI0mhsHpjDEIqtwaOb+xZIUl6Xi+gKtChLaPuBiZpH4zOOXCvZglSXRK7ouMkZI5sVRR5FtSKRqQEd0ZYV06a0HAjysMMivmuFpC1i8J9JHG9NlOG3zAK0/f9amfVRhj6JwjtG0ZMyoxMEWj0BvXE8t1534hSH4vM3EUeZPVsuONm7do+zWPXZ8xaSp2dyzBW+7fSHScuRphfK1nh2qxIXgSA3ivcAqciygd0bJ2xiSmkOB9cshFQ3J3t6aphW3F2oqqEl1VpXwCKKZGVHk+zNNqhDB+bw2Xqs5ccwEVpmcq6/j8fIf72NrWtvatZkrecTGyPq3R1ZR+/Wju8eJ4xv2bF7j92hW69TszeDzs3CGYVI3z9c0frrUs782wjaPe6/C9pjttWB83+N58VdXTW3t37cqVYz784Zvcu7fLc89d35Ai2LTcP8xG3mBrW3s/m1JgbcRaj7XvDivC1t47CyHSd0FAHgBpbeC6kEDqUFWepvFp+xRP8e/9O0ipSNM4ZrOOGKHrDN7L9V1fBz5+GriyjjThbMxnsIMucH0dObWKN6cqrTdh5iJPrAKdhtenGnc28j8y7zUhfFVhuK19U0zeuX1fc3R0Hucq9vZOtsweX6cNBXPyb1QSCRziH7mYaxw5ZfP3txpOavRvHP2iJI4y+E6bUd1yJpXiPQVU8JATlVDkOM59Jk6AxMdztvahMeRRvPTBc4yCkGeP/pDwukrXTfCEXqR+N0EvwxxWZJ3TZRf2iBzXGJ90dJ9Dc6TCxiT5G0IsrABlp1Qsk7h1kyyLxG82psKUdFb5Js7e57jqPcdaRvecryZvr2JujLNNu9nmpc+l+y+HfUhDq1HiGiUSG+Q0rIINtumy58CAMmajiNEQCfR9R4giA+Odp+sdbduxbjucCxLn1CKTEglDDLFcj1xbTsS7EIje0/cdvks/vUhm2KbGxZ7gPftXL9O3LbNzB2hTIXOcsLnkuHPuLgrYPXfAU9/5Ma488wEmeyIhXlWN5AnIzyeBI1AojUh5Y4iJDWFnb4/aGu7bihgl5m4qkwrYAqd373H35VeZ371Pt1qh6gZdN6PHMeRFQi68VYpmZ8b+1ctM9vc4unGLbn+P3eljCeiR+0Qc/lGKup5Iu2tDJNJ1PS4VA2bWm8yILdeXwT8535ElsGMC8oz7zTCOI+BCJEQlCbbRBKPGzzGP2zhiFIZSZDyOIZcpQSmJ246flRritxkL9pBuP1xHftwbU9coxxIEOiKx5CRtozQ+gbtUYbdIB0rgmtTaTHZ32Llyhf2rV0a5Fk1QOaItDCnOBRZtS1yvWSzWhLZlfvsm9XpF0NOBVSa3y2gmfailgTzE8hUqyYWl4UpOV6FAl8aS/eraDPkJPfyu1Ois5bmNYvV5rho15VuGg9XmT+7jm8/igQlsa1vb2ta+ZnvkFWYgAdqQCddhkGSzTNjeedH+Ks7WxkxWbOPF8zaWE8UQJBFJJCRqD2XY0A2zxhCjaKFFosg4hFiSuRlFPoYNbHrMcXSHZy/kzPqhvDwleKFiQMVBKy7rIGZ/TKnEXBEjnijyGzG/JQJWKZrKFDYDGJLb5YTBJ0CIJRDACBWYnWiqicFWNcZUSWYtJlQ2FER0aifve/q+ZblqWSxbZusO3XT4eiLSaNoI44PRTAETwLuIAXYqRW1UeYBZw6y2BhcTPZdSiW1PACUhOAYGmHxDm55+XhC8Va+QBaAjUkFyfANBFhOmQuEEkByFcrOgspXCZhRt+ruu6rRoSPI0tsHaCUACK6UAFXKftbHM6pq6Vrg45Xi54LXbh2hnqOsJd2++ySuvvspi1XF8uqKppuzsnmMym2KqhqgdpqrQScIEIt53aBOoqoAyiruLFW3viSpgK5XAORE0aKMxzYyoLURPVJFqtsfOwUWCaVisg7ATILI5wUe0lkF94fx5Pvqxj0nS21YCulBC1datFgTvcd0KpTSTnR0Uit1ZTZhY9namxBi49vg1iJ6pX+HXXUJvy2LSRwWzWu7NA6sAk9GiEAEwVcayjIL0Nlozqavh2fpAt2jRTQUx4V6l3KA4kSFR0U0nB4BGV4qgAm/evMf9u3dZzHuCD9imQlem0P0F8gKxhxgwWjOdTNCmwdgpRncovQR6iKsysJ2H+Up6beM9yibSuowwT0AhWc+Kc2u1oTYGjEv0eaqwcajCVJP6VdaZTCwcUY0Ws8VxFBAdkeE+Elrah4APfuS0bzqrrnd47wDPeq3Z3dujmRhW8yX+dM5kMhHdRBIrU4hoq3DBlzZXJACa1SijmOxMZBRrJUHa3rI46fkPP/d5Dg52mcxmXLp4wOOP1Tx+3XD7dcPiRIB32ozAWHFzAfNW5jysO4XzpIVvogA0YCqFihETuvRMKkDzxBPnGBZShqAqQsyLsZgKD9K4shCcKsGEkORyJDakysIkL9Lzc87ziLIWrS0myXBFpcs8L4d47wPZW9va1r4Gi3D8ygEnr+0THjEh9cYLj/O5f/z99F31yPu8W7a8N2V91LB7dcHl77hLe9xw+xev4HtN9I/ieW/tm2Xf8z0v8mM/9o/4N//mY/zYj/0u2nZL37+1rW1ta++VKSLff9fxa15qqd4Bm/SReeB3vd7xxQPD//xkjUuv18dWgd/3SsfdRvH3nm443S4HvmWt7yu+8pWP0DQtn/jEFzl37ui9vqRvWRvHfoUDQGIjPiQV4lQMtJnfekgMeRMH8eAJxvsrVWR583mVVEMNiVOl0KQinlwwk4AnZ0/w9pXWER5gG1HlFs7iO1ShEMlR9WGXki0cgSFyDNsUxII0hkZhtdqQ1X4QS5KTycJUDEGAApVCW52SuaYwCShFKgAc2hEUITGa9r2nc47KeZQ1RJOuVytUNBitqBToKIBABdQmFQaWQwoAxGgtfWGUiIbEkh1HkfuccT1bgDO6vuF+h2PFFGuPImCcWjLtozUq6BRGU0NyvFxODqbLkzfGlA4o0hsGrRODY7leCuhEYqAGY2oaKtq+43ixQgWJJy7npxwdH9P3nnXXY3VFVU+wqVCJoBIjQs4PDAW1RtdoHVn3HZkjRZvNfLHSCmVrjNJ84Hs+y1Of/QznLlygbqZEZekc+BBzQxVyDw08/tEP84nv/VXYqqJqGhQD47J3PTHJfCsUqq5QKOrKEK2mqStijOzt7dKvV9ywE6LL8d1IDJ7QO179uS9y8xe/xOHhKfSAHQ8fAbIYJXkdYeKNWKM5/9hVPvl/+s0cvnmb//iP/zcOLl/kyg//IFVdl3GRHkqZU6xtAInvRRU5WaxYLRb0nYBdtDWFSTgzV8izlvMqpagqi1IWpa0Ukeke0ex25M4TInS99DIbpFAtxyaVEgYQpYeMCDkfoVWS8RlyVQUQohPYo4x7kp5KlpcZdXwlfTnnQgoIRMlnIY7BWeMBIxaCAMW6LqK9oq4VWE3f9sS2E6Zum2ehWO4nA3EuPPk4H/x138fu+X1MJWPD1hW5zpmgIGj6NvD6jRv41ZJ7dxfE5YK2+/dMdqac+87vxe5ffBCAVnJnD7HR3B9SLD8o8DFKSXcqSNZGjqFjKG0Piv19yQUJ+GaQMx/mkSE3p5JUzRhgM+TtVMmRFTYhNZLOIoOJRjk/VJnn0xYPv8etbW1rW/sq7asoJRC3R96hI8c5UijXxj9ECny3JPrV8PfZhH/aYOMj2UWRXo1EHSWZH+MmgwXDC1NFhVD4n7n6sz5gnlTjg9vFcs3qUS+T/JKPmRKw+BmhoII3HPmR75rZPOSaxl5qBqmo4b+MCE0vhmF5ML4RXbYv965IyX5JOhckbmqHvHVJ8qaFw7hd8vcbSNYETMj55qIFlxg9Ri3LA405NMNb4TwE5xKT+MtoG62grhQORR/KUchLnNzDVHpgMQoat1B0lYVBbpzxlQ3OkVJglLB+1LZiUjXpTIpJ07C3uwusWLcBqw1ROAgLy4oxFqOT3E2IhOgwXpWE+qSu0Mqw0l1iNcnJ9tyuci1GG7RRGFOjjThNfd/jgxNHM7W1VgptDcYKctpYg7YWoy11VROBKni893RrAUXMdvcBWK/WeO9p2x4fPNp5CND7HvpOEL0bjzM5LHpg7ijjv/QbGVDBhwLokfVKLN8NY2VzDZf7kqzBDChNCA4fe/rO0XaiaUlyNLXWo/Gx2WGUNmjToE2N1hVZpmc8bGICYYQoPrSIgkRZvOZ7LYu80rkGxL3KYzL37bN9Pl3T2Lkboc5j6SN5POVBJbuJj1u8+tFclCe3tG2QBZLVmhA8Xd/hQsRH6FUnTq4SBL5Fo8yYEm80z6e/lTFUdc3e3h5NXfHEtUv0vufF115guVhx885tnG85t3+RymrqWjOZ6SQdw2isPWgZjT6eR52LLBYeoyJGx0RXKX251pXM786jdUySYqrI1CiVOaAUKkO5EQ1J0eqUxVwIjuAiPkS090mnU6gPRUZLjZ7rcPVnA0wlDDG6hy3x3ta29q1qqZLnbZI8pnFU0x5lIuvDCeuThnbZfN306zEq5vNdrHXMZkvquv8aDqIIztCcWh57o+JwXnGr01smj/ehVZVjf3/FbNY9PHFxxkIwnJzs471hZ2eBtf7dv8itbW1rW/sVZs5pvvKVa1RVz9HRTvlcRagD1G8zte73kUtt4LFVYOag8ZurGw1MfaQJ21XAt74pvLc45/l62da2JhZH/8+/FtmSGEffj5JsajOG/FBTZ/4dxTRKBEKNys4ecqwSk8onVqNYdb6Wsu1o3J8NaXM2DnBmg7frSjkQFkd/jyNaD4ltq9HFPHBbOd7M6HYemit98EN15iMJ++UY9xCHiqPtSyxbPXgtufBGmDTGMds4/MqZz8fHSLHDUklZtoqb25y5nXj23lNzGa2KlPvmeSlPL/e7UgQ47iIPdDrZc1BxkWhUjrsbbbAmlO2tMTR1zf+fvT8NtiW77vvA3x4y85xzhze/GlAsTMRAkBRASi2qJZmApJBJsbvZbCoU3eFQN9QdLYestsOyW6EvUigkhb/aVpgO2h3+IplN2d0fHJS6JdKSTMFsWZJJSQQBCCIAAqgJVW9+dzhTZu69V39Ye2fmue9WoQCiWCjgLODWu/eczJ0797j2Wv/1X9ATYgEalXQoaoOydmTsLuy/07Hrnc3stdMXL6N87Cdf15oGpWow1qmpMMXsC4jMjg65/tyz+Kri5NU7+Kefon7mKZxz2bbqBlu2k0QSIQatY1VYOHq1oYWQbdJJAUWL61eJfYufNZNuEWIIBBKS4uh7mdiPt+crHn/tNVaPTkgpDa1sraNuGk0B3nWETu2arwcC0/7IzBOiz0shZRbN3F7DuL044MpvNoM8nAI2dibHaMct9RiYYyZj2OwsGmV0yeCnKB9LLkyGyl+ywJhdG/KwNslol1Qf03TRGuu6+3bT19BnGaOeJBEhpjjYpWMJcs7/sRjs5BnWOapZg6uq/Hq6EFjvaOoG5yzHRwekFHl8+oiYBHe0QJyh7zeYTYsx4CsGv8JoQ7504Zr0gEpKokAVMiO00VTmxll8noukzPacwVF26mQqvrVCfSQygDuMMyBuSN+tw1zHUcrs0MpGstu6g9V/Z6mYsE0PTShP4gX3spe97OWblDcN9HBZkRjRgLpgiSRiUjaBEhmdkiJLgayUjYpNcSLCuPAx/Fs2MzMoUoaRmcENi2KV7y/KV4GOZEop63Y2v8EPivJBOKt54ApL4BSIt1vDC+lFIDt9IU2W4eKgBSGlrAgW8EHetCtXDTRWo9NWHfOVI6dKyahsZET6Gc3FplAHm+uZo/tFHdIio1saMgK45NbQ/BoY66hcTe0bHIKRHm8tta/ojM3gUMGKUHvDbOaofE6xYYriKDucJ1pPZQ+Q3P9DGgpN7JPTopVNelcRBSEZQ8QyZkKctiokscToMiWcluWwzCvLtUPDZg3nXcJJzOkolDKtUBJmdV7rb7VtFSjkAItgx6h9YwZkZkxRqcasweHxGJqjOTevWFbLFcvliueeeZqnbt3i/sMTXv7aPdarFSePHhPneo91jkUjNFWDJCHGQNdtNX1OH5h5z3PXbxASrE9b2k7ZJ3LCSpBECIGu7zk8PGQ2a6ibQ3x1QAiJ9eqcrl0haQP0io6vHfVhjW0sSTqSdTBvaGYLbl67ifOKzg4xcL48wVrHlSvXEYGTBw/YbrfcffCAuN0Q1xtiv6HdPCL0LZu+J4nyL1qruSWN91SVp2kqjBG6rtM0LQBGDyAIxLbH1hNF15RDTD7TZiVH8tyIEomSNIIAQ7ReEbbbM0K/Ybtp2W6j5rozuj7VdU2M+eAynMTyAdk2uPpqPmh5TIpI6jEZiS1J2UNSVKBHROgkIhKZ5zyDTicbAzNmBn4Y6zG2AhMUGGLKwgKCVQWZhBgtx2aEvogMKGhQ5TRlZqSYlKXFqqaOOKeMGknZcpy12nZKd0HxTEomJpo3FfNFxXK9YbkMekAxnrBu9TBTe0xVsVgIR87lNcSUUzoChKhzxlUVR/WMp27c5t3PPccn/w//ex4+eshf+st/kbv3X+NX//k/5eh4gbM/yrUrVzm8UmHcnK++fFExl2z8GA0Eu6uByvKs55UX1nqQjDBfGK5db2gWNUd+gZOOqt/inOB9GT/TfUSjVAqlIBiq2quSX1dKOR1Wmt6mDyQi223LerPFVIaqqTWdS8xRL077ipQobD+C5L1QP9e+VIOBTeny0+Ze9rKXd7wcPrXi+vsfs7xzyGuffoqTl698S5wAMTq+8pXvpap6Pvzhz3Pr1oNvuqxnX6n4iX9+jS8tHF961vBtwJa/l9+mtG3DF77wfcxmW37gBz7L0dH5212lvexlL3t5x8lm0/AzP/NHmc063vveL3Lz5v03fe8PnEb+N6921OlSDti97GUvl4hGMBdn9dTdOw0SZPh39wi966XftSFPr5l8mi/XYLpsP9zx+DMEV43hOcXDNrVXTl9CrxvYMy7iEyY25MFpN3y8a2i+GKQ3tolWvASbFSZtZ7Mzv9iQYYjyt8Xhitn531jeGHCobaJ2njQ+nR0rjLFjWtpcZw3o0qAxbc2UgwI1EK5g44wIzoL3JYVvKSbbkXP68jEQUWsxIfJlyr89+tPNzj+l7dSWbifBnaXjybYaQ0p2YFEo1vTKGeY19D10XR5VA+Bo4vAfQAIy2MK1DYt9KYewmcICoT9JMuAjO3094BvPYraga3u6ruP46JCDgwPWmy2nZyv6vmO72ZK8wWBxxlJ5tW+KCJISMSqYIkX1QhzPF7imwWs0E6NTQ7I9PBFjpG4aZWPIwYKaeq0jxg6RwFMfeA+/58ZN7v3Wl/mNv/tLvP+HP8Zz738P1jvwHu8rFvOF2kKdskO33RZjLLNmjgDb9ZoQAqv1Wlk/+gAm8fyPfJTQd4hYUhgHrck5fayzyiCMEGMcGHbvffkF/uUv/F2WZ2ekPmSGYD/YkMt02rE0ZhtyImXbq5aVcn9JaEmpJ4RACHktMoW12T2xPo3jzmHcTP0F2eYqEinMPMPalca5GfPa5gt7Q7azjj6nUrYyPGAyu4yJk+XO5DIFMco8NKStL2MsLzJahzTxxcgQnIgxQ7CgpjPPPpIyQadjH6HyDl9Zur4ndknriCWZSG+y7dk5qgqaAp4o7ZXnQjGFWuvwjedwccDV42M++gM/wGaz5n/45f+B4Dqufv/3ktotp7/xm7TLyPMzy+FRxeNTJuVCCSx+PSnfdG3i7KQf9hJfGeZzj6sczaLCSMSlMKSUYnh9GdYqY83klZShWgFfjiRClyD1GiQoGEII9CGozygz/0yZvS9iyYYVLj93GKdMfZ172cte9vLbk2+Y0QMUfDCmGWFwWI40a9N7Lv412ZGmlwwaUlGAx0VyvMZMQB1ZGRwWyfzv5PGKqhyVt/K9nSAxi0K5u+COJQ4cGzJdo3dBHsN7TP5QFKUZFMAxFc2uFMSu8w5feZwxeEt2PMexDcr1RZuVse3N+IcqAkO7mlyX/DOo1hNFcETB7LRbUSAK3VcBlexcPvrsJ8/Kl8jY7pcfxiZ/7yhVF3+XnU9N+e+gpJStsTDJXKYIjChKmebfzAefaX9OcyCO9yqi2lqHcS4jnHMKB+c5WCy4euUIS2J1doqz+v7GQFXV1FWFdxaXFfGSDxC07z2C94aUmRgGhTDGYdZJSqSQcooZHRsh9FkhVs1WgKqqOD46pGlqupCINiJtD7Scrdaat7FtCTGwXK6w1iIZOLVuW/q+JwkKqrAOsY4ghl6U+q0o5lhDiIGuS1gDs9qrkhICkjLiNzers5aq8njncu/pYdU6R1M5Kl80LYb2mSrbBoP3qqQul1u22xV9Zl8Y+238USWXndyTEJHU5QNswNBhJJIRUYgIXRfp+6gIXYS+DRjjSCkNqTzK2XeKIxsnQTlIj2vjqHBPxxcD+jfGOGh7+lleS6czIL9LSok+BHwI2KqkwJnMLmFQ+gsQISYhxqTvigwHbyRBEppJKp0dfqAyTvO6lyTRdz2bzZZHJ6csl0uOjhastwesN+fAhkePTxBRtH+dWTEum467fz4Z9ZZECDGREoQAvhdigBghZpYOL2WKaLvYnEbFDUNJyhlp8mAZ2j0EBVE5r0w5MUZiTPmwaXfWBMwug8v0JdSEsvs+e9nLXr5zxVjB1ZGur3j88Brr5cHXv+nNlUwImss4XcLAIaLO/q5raJotTdM9cc1BEK53wlNrWKwsV8Xw3DrRZSNnZ+F+Y0h7INrbJteuLXnmmROee+7xhaiwryeGvq+xNiqgfC972cte3iapG8vNZxtCTgkWeuH0wchCFaPh7t0DrNU1rm09m803YHKayGY5Y3lyyNmj4zey879pETGcny9Yr2ueffbr1OlBDV84gPsatVwl4Sh88yCPlAzr9YLtdkaMvz0WsL3s5Z0low15avstYI9dW+B4/a7I5Z/Lhe8vu3WwVeYrL15z0cFWnKTFCZr/K8ZMqz8+vJi3L9T0jZasJ145V9QUg87FV7n4+kPQlAalWOfUOV9sYMgFQ8jEiHtJkw9W2wEQswsZGY1Sl9laJ+80Aa4Mt5RCiq2q+Lkn1dq1IY+t8caSry3222kbXeiMC6b6scJTo55h0vf5PlP8EtO2KeVMbMgXe1yKbdIMDvpi51VGZKh8xWxWYxD6bYudFG2tMmmUgMS481JarneO41vXSSly5foxi8UCX1e7fSAyYV/PNuVULtGArvpgweLKMVdu3mB+eEAUgZgQq6wfbddjTMQ6q2nAuz63i+6GfQjZb5GfaQxYh501+MoRtxGJ/TBmFYSi7CWVszpOcpAbqD25XW9wznPt2aeIfU+/2hDajrP7D+jXG67evsXRjWuYEl0s40+KgeWjE1ISDm7cxtU1XRcIoc8M1ZN2ZDo2ZFLOpECJepUkDDGnhZJhvMSogc86voUYCrCjrBlm55mDK2x0pDzxDiNL+oWhNrWTFxsyjKCQ6RAsQzvbP1NKY3tdMrcExnEiJf2SBiyO5BpaqHdqe60Xc64+fYvF1eOxEHJd8nvGmOj7wGa7pes6mqaiDw19MsQ+sG27nPdGcBkgNS4z43rw9aTY0rXu6rJICWwqDPFmWF6SoAGbO4tQeYExJbeuA2Obp2x71nk8CXK3oEHEk0YgrwuXLGNP7g/7s/1e9rKXb518Y0APKU7ekl/K5jxtiRAjfYijUjPe9XqlXSpSnLIZPAKGZHRDSnmhN0QECHmDLRtdSkoXJhPHnORDBHnBF9H0Llbs6JfN2m5xDooUbgzGDRd2HLBTTXH41KhT2xiDEVV8ioLm3JhWYnTsZpqrumaxWHB8fIivPFVdsV2uWZ2eD87XYQ8yKNhDIIaoKTFEcKgTVIABAi6qj1prMxoxb1IxkmLI71PQ8Wl41SjqUA4iBG/oDGwS9AL5tQZFzhaGAgzOmwmgIQN1chKMaQ+PjTf2z6iUqEI5spEksBEGkEw+KCboI6pU0SMEUoqayiNFdfw6OylzvHdw2hoFMgw6flbkLQrsUAxJwlYe770iWI2mO7E2I8jFcP3GVa7duMq9O3cJ23Pms5oUWnzdcHz1Csfn5xzN58S+Z7Pd6hOcx1pPyOjsowOIM0M9r7F1DaFH2g2VAVNVxPWW9fmG7dEV2sWc1lVUOEIvCAuStKSYuHHlCh/98IdYdcKj84CYNcZ2RBG6+CIpRmKrKVq2XY81lsVshveeg+MjfFXR1A3GVcj8GKlmtNsNXRCqSvAIvXUELMvVOXG7YdE0PHP9kMfLLSfnS0LbDX1ssMxmDTdvXFUHflYwras0nQw5VYbzypITe1KI6oiPCYuy7xweadqdr3zpLg/uP2B13kLUxcYU8MJkbKUQCW2PxIg1gsRz+s0rmMrQ1CaPyzAoq10befRow+l5ICYhhMTp3VPqWcNscUQza6h8peuexHE9kFIHRRgUv40qtYG+64boD2ME6xVp3nWJ0Efaba9zvHBeYrMSbhCxxKJU9oFu23F2ekYfAteuHlPARMagLCOi6G0xsO56eit0fSIGCG1LDDEbAzQ/rhhDbS1cPZqaPnL9hRBCTnMibDYtr9w54eUXXuIrL7zIwaLigx9+juffc4P/8X/8NI9PN/z65z/D8fGcj77r/cz9HKIhxd1onak9ZJzzF4wmxoxrWG5MiT0pWPqgi5oYBbGsVh3GWpz3OGuY1S4r9bp/mPy+MWifbduW0AeW5yvWq5ZDqRE8fR8IXUB8pVlZ89oJSh84kMRg9KCPHrpTXpglv4We1yaHg73sZS/fkfLgwU1+49M/RN97fqdovb/2tef42tee493vfoHnn3/xCeKgD59F/rev9syi4AWeXyf+L1/thqX05YXlbz1fc149UfRefofk4x//1/y5P/dLHB62eP8GOYL2spe97OXbVK4/XfO+H72NzSmkTu53/KP/133CVr9fLmv+u//ug3hfzhSwXH5zG8+L//rd/Oov/V66tr4UBPmWyn9/C/7xdTiawfFvv7iuq/nCFz7McnlE19W//QL3spd3hGSnudIEU1JTlCj4lPRMv+P1uuBPv1DapR9IdsgVG6uarsfUF2o2zo7kqedfQChO2tFaWFI7jE7X7K7dYXzQyup95kmf5MTpWcrfaZbRJDoE5RVD+mg/MhMnb35R0eudc1RVRdPUNPMZs4MDYtfTtV12Rl9otAwULoFIRnJoSzF8T9rE5GcMaRQo9pxiMy425PG/g0NZhGTVotujTtWLHWcK2wFqyxvYUsbS9F13PK7TxrvoKC3Gm8Fgri9WPNTFZlN8AgjKoKAAA5HMkGsy2MYYngznKX1vNShuWgdTbEHFHiiZDcWWDh7Gfnmp+WLGfDFjtVySQkvlHZIC1nmapqGZNTRVReu9BrmRQSJG7YV+1vCxH/9RYui5euUala/YtFv60OMA4yzSBXrpCXVDqDzeOKLJNjoqRAKShOc/8mF+6Pf/HpL1bHsg9LBVn0tMJ9q3ISCiAVPGGCrvsdZSNTUuB0Ma66BqkOSJoScmsF5wUQFJWEvXtUgIVN5xOK/ZdoFt15FiHPrZYHj6e9/D+37/7+bel1/gs//gU5zevc9v/J2/z5Wnb/Ej/7sfpzlYUC/m6i2RlEEsQrte8/l/8Cv0my2/+6d/gsUzT/Ho0ZL1ak3fhmG8j0zT47xS31YJtgWkJYbTzPJdrH5jCvAYhc0msG3zuE/QrrY45/GVsqnY3GeQhmA6GQbN4JCi+JUKG0thKDdoChFBhiC3ENIwA8exna8TTU0E+j4xRNptS0yJ+awZbhlGeB6vCPQpkaK+lwjEEBTwYRgZKozBGQPzhtvvfy9Xbt0iidCnXP/MuC0CoQ9sz7ecPT7h8ckpVWW5cfMKV64ueOGFO2yWgdfu30XaLaHrcWKHqb8TQr472S/My4kNeYqgEIEUkaT2bBCcURt+18Uh4NoYwTs7DoNs37cmZzKIEIL6mbquo+8CdVPSyqsvFOswbrIMoeNrDEwfQyqHz8vfwzL39aFte9nLXvbyZuQbA3rsKKe6PRSlbviZqH0FdGGLsi2TnIUTPW5XIZadMhOa/wpyHr2slBalenzUhKqKicvX7D7j6y2e48Y71u+SiybNYLDYoT2mSqqhKOnZCZwrU243+X5jx/uHPF8Tr+ildS6IxSTTjwY9ocBDikI5VZyHDSkx9JmMLTaiRPMhQzAEyUkuit47KNGFQmxoka/TeE+8yE577pYhk3/LZjg9TOxenkcFBbRzqeS6l4NUodsbnPaM40YE0vS9ygGSohgarJhMO+eom1rTeBinAJ7KM581HB4suHXzBs47Vn3AOodzFca67JCOKLWiOvyVBS0DVqzDW0gxZVaHSAwdKSkQQLtBU4E4Z/He0VQVy+2Ws9MzdUAZR0yRTeiVCWS7UUWlVwVnW9X4ytN1Hb7yzOdznLX6nBhYLTf0bcshopRkmSAyxkToA53xGFFwRkyTdszzVZLSnYmMiY8LIaXzHqwlFshviriQhnYfxi/aRn3f07YjGltBN0VJzmtAmoxxBOfMcI0Z1NoygDK0LCbWm8BmG8Y5EYUYIqHrFCBh9Fm6HgmIHRHyec6OTCQF4ZuyoqhpVyQpKloV50iKMR8mCx3fdC3bnQ8pJdqNpl7ZVFUuL+0c/sssKWwe1jpq74hdRKLS7xV4dZJECj2x137efWZer0UPGKoQt8QQOHt8iuOIZ55+H33XMWu+yGbbsTzfICmyurbB1Can0XlyeouMh5mxNyYL9RNTdxKFUNbyybpPXgent+m8KimEcl7OoTKTh+giPNSiIMGLcaQAaXQxz/1z6epy0XrxxAV72ctevgMk9ZZuWdGtG7bbme7D30IRMbTtjOXygKZpqaowfNf3FdvtjBAuV93rBNc6Bf4C1AJ1P65W6y7x1DbRJMPjyhBt2VsM2+2M7XZGSvso47dSDg46nnnmBOfejH78pIhYNps53gdmsy3O7cEie9nLXn5nxRhL7efYSs91AzNjFmXNaL4lz+q7iuXJ4Vu2165Wh4RwGQjFwMrrj3GXAj1mSXhqK4RsG7jR6um2TsLtbaK+sNeKGLquoW1n39J32ctevu3FXPZHscOM/05WEXacXq+jMu3irGViShAQPf8X++poEN61IUOxVZT7FSRw0Rq5Uzez+wlM7QMTg+wTFZ4WYSZ2iEz1P7lmCggYDJMTKbbI0VE8tR9dNL5Mf389FpWLl5odG4nemm3PwzNk566h7c1o5Ukypoox07JL+W9WHR5MwROb8A4Q5LK3mPbe6BC4+EiZfjqifS5WevJeDPa33XRE4yuNpvzdkaTfm2xaGlOHFNYPYzRosvKe+WLB7eeepTlccLpcIykp2MDktMJGaA7mCDMWV47w3tM+7KHvUUZqg6Rij5P8u9plywv125bVo8cczmoOr15h00VWyy0M/SeEFNW+GjQthgZaGoJzWGuJMajNuvIaCJU0lXbXBVII1DDkyjCm2NsSMWpwqNrtJl2Q+9ZVFc3RMfMrVzi6eT3bVT3VbM7i+JhqPlNnu6Aplq0MvgpXVTkNMxjULhxDzIHEQkkpNZ10YzvpNWo+Lj6Vy0dMSkLfK/BiGA8CySpgJBowpqLYM/U+Mw6QgYH6yXoMTyvzOts2U1Tb87AWyXSOTsZtWfZECL3aE3o7phcZHznOkxJsbYymZ0pGKACoYf1MOpZSjFjvmB0d0neBsGmH+g6eL9H09Uks7WaLoeHo8BoxRrx/gLUeP18g3pLQQMOUpnWbtPpkTl1cn3f+MLv3DEHFO+u+DO087V21KQ+L8MQnd4kNeWdX0H4cQsDLEgc8uZtMxYz12tuP9zKR/pW7pIcnb+kz7I2rVM899ZY+o8gnPvEJfuqnfoo/9+f+3O/I877b5U0DPco+mFUUBAfGDU7VmIQwJvxDJJHE4MTs5BCD3TXs4nKXgJiUGUSibpghhlxmVmJzaghbWDLy5jakz8vR8WnilDeAy2jhAVk7nAYmSIHEBcV3R93NFE8a1W0MVNYDQiqOa+smSmhOlcB0O5rUFXXEOl9nNOgGSUGpzSaK4eAOHbRGRYz2MdFnVgMMJJOZSBJIMurUtQo6UJouBQqEXhkFUogQI2IS4qQUjSQhSE7J4T1iHctk2UZLjDAyfjnENAgBZK0bY1AHeRJV2KQwczA1ApWGTgMjDK4wf5RrsxI2/JQ7hUhSJ2527hrnwNqheSQKii66ZLcvfxtlH/HOEpPQhdFh7mzme0jQB3AOvBWiSZpiD9E2NU6VzcpSNx5fzVmHGc18wdHRMYeHc249c50rxw2WH+Pu/Uf8o1/7HG3bsZhVGAPbviWEjrbdIBIRG8EnkAApMD9osHWFdLWmcrEdm+1jjhbXNNei95i6opk3HB3OqStL6Lc8fO01/tWv/quBWmxwkMMIZMjw+gJO0mmhf4/XQYw9xsIH3vcc168eYfqICZEUoO+FR6dnrLaBqq6pak9ISmsmfSK1Pe068Pgk4Zwwm2d0cLJgHNZXCEJoFbncrjccHBhC0nFtvR4YunZFCB39ts2gBUV8V02jhwpvc10joQ/0bUe7aakqYX7kmS2OqZtncM4iziHpHCv3sgEgsdl2vPy1czadEJPPY0RIMXB67wFVXXN84yqu8vlww5CKpuva4afv+yFKIoRA25ph5Mc+6k9KxJCjB7KSrtPd6OQSBfZgxrXLOwdRePDKHay1PJzVGGPoth1juqHxcJACJAfXD49Z1DPu3L3H422ngKSZp28j0kW61YrTBxFvKirTIJLR4aJzrESLWGeJKVJZz835Ee956t381B/7k7Sh559/5qukr77AyWsPOEtbvpheYrGoWW3X4wEp/8iFlfAyfVZZhxgVcgwpafSFGgvMcK73ZXUMEeNyDmCErm11H0EjB2KvlJLeO7xzzGYdkoSmqakaj/O6hqQYSZteoxJyuh5rQKwh2XxNipNDMzm9VT5EDOvbXlPfy16+E2V594DN4xmnLx/zVjB5pGT56lffx8svfw8f+MAXuX37/res7Ke2wv/pxY5X55b/9nsqTmqt/zTKuG2/Nc65vbw10vcVX/zih2malg9/+PNcuXL2dldpL3vZy3eZdMuaO5+5TUk/dX62Inavvc21+sak7LV37ryLx4+/Crz8DZfx/mXi//rVdvi7SjCLr7/X7mUv341y0cUlmcFUYzWkZJOdiAz2ArmknPLLRQef2gFlcGxqZHz+eni42nAG28TUZzcxG059peV6M3H6PvGGo5Htku/HShabnJKXqr1TMhDMDsCPcm0pvfxSbMgylGWt2uI1EKpls1wO1uOL/x0CnHK7RxnLHKxIxS5uDJQ0I0MwlbIlxOJkToJYZVkd79U2V9uVRYyhE0NIyo465r0yakeWhJE+2/eZBCGWa7Kdf+qIyHb2aXBVdgCM6IvBjjxtfXJdZRgvDMGWueiU/QjlE3NJXxtyAJgZAquGvhoCCJVt11iwUoJYyzVWU2Fjcc7gvMWuK/rkcaaiaRrq2rM4nPPe73s/f+L//n9juVzx1a/d4+z+Q77wDz+FdZaQhD4kQuy1f0zK7ZtAEr72WOeQoI59YyJ92FJXM2XjthbjHA++8gKf/eVfIfy+38Pz732W9XLF/VfuIZOxPM610tcyjkxjdt6/jDUBHScWblw7pvYVmZZiSL+82bZ0IQ22xlQADVGQmAh9YrsVDm4/ww/91E8AlmQqXFVh5wtlJgk6HkMfqKMhIdSLBT/wY38IRJhdmdN3W2WmiDL6aJxVX5LNfZZTm8QQCSHiLLjG4qsG54/03axBpMPIchh7IUROz1pChCRlPGmd2pw2vVnMhvcDBlt7jJGYQv63pL7JvrUwWTuTaNBnBsXofJzMO8PYtsVImjvNWl2f1mdLDRb0SzAakKfrYFk8AaPzUBLM64bKeZarFdvMCu28JYZcv66nXS8zE7ofwWN5Xmows/4kBA8sqoarh1f48Ad+FyElXr17QhJ434/8QSQGWut5cPqYPvTD2Crz+nUxXTtzfPIu4yzWoFNMBjmV9TeP3yQMMdsIMRYwUH5uTilkrTK+e6/95JzDejsEbKsfLIxMTGX2TO3gA8iOYckaVrCyCT2x5uzlu1H6V+7y8u/7t5D2yVTN30oxTc33/LO/9abAHv/5f/6f8zf+xt/gs5/9LH/sj/0xfuEXfuEtrdtefnvy5oEek5x0AwahOLhKtDXD9j/IZSrCGy5gwhAlXzSioeyiIWWtXeygBjJd+kf2ihEZXa4c0NI7Ndy9H2MGKjtz4bPxlqzgZEekLWjPDLoYvi+fMVE3h6ZQIIi1LgNWUORn32f2gNI9u0qr/iZEyXRSTyCyJ67Uab0ozafKQhreZ9Le072eTMuFIeYfvb68owHjEWMVvShvwKTxevUDnhwNu0dCM+kjmVyiwGczXD4wIZhyBpgo6pOnDMeHrIDoQXDs7/IWSVJmV5k08QAeKoWVg5YFazK4Rf923lPXNYt54sa1q3RBODg4xLqWpnZAIlAUPEX9pqTalR7ABKecljr/hgOXHQ9eWUGwGfktSVivt2zWazbL5YCI1fraATwwKukMbz0eALOSlvtesjLc92GXsSMf9tousm575tZhK59p6+Lwo3n5ctlJD4TRZAo4r0pvjHpdSdlSlFdj9R23my1dtyV0gZSp04bDndGDhBoLUj6I6o+1lqbx+KrG2BqMRbAY4xiHv77Hto20XRkfIwo5dIpeb7dbfPQ6jyfTPMVAioGY4qCEAyOriJ4LxnrFNLCClPVjGJvlgDMcWEdohIjQtwrsSCkOa8bOz05xOeXIkJdzHPdl7IY+0G62iIeqGWmEjTUKivAeX3lC1edoA6XwiyGg0XVO0xB5SwyQ+sTZcqOpn8LI4HJRTBmTZQxP949hvk3H+G6kT9G/C5BuOifHw1rE5DFfHqrRM5KVcAULeq9AD+8d0SiKvOwtQ3tNyhjXORmeN4owvXwve9nLd5ak4EjBEdq3ivlCo4z7viJGj4g690PwHKXE99gViyhsNnOqKuB9zzwJB0E4Cm+sf1UCNzthbaDbzFkHtbi27Yz1+oDNZvEWvdNevlUiYtlu58To2GwW1HVPXbd7Zo+9fNvIalVx//6cg4OexSJ8/Rv28o4TSZawGRk2YtvT1HOAHEzzThDda0Xc67JkfT2ZJZi1T+67Nu+1G5ewb7wt72Uv3/ly2aF4YurbtR7uWo53bchmsMO93kl71/bHxNaz83Euatc+qJ9P7MkXqrRrQb5kYku+/wkb8uTyySMHG9D0lfL9+Y8n6jB9bL2Yc3DtGja2ELqctkLTV5udh1+opsnBeFMD5xOXmeFnakN+knWWHTvUaKcdeC/ULjM17Q425GKj2bWrPCHmdX4f/iz2wG/A+nLBVrNjeqPYoy5pu6ntdAIQKVUfbVEKjEHcBPsj7AyMJ2xd49+altgxm8+5+cxTzFYbTqLBWMfxrZuA4KuKwXmcRuZakZyZRAozw/SdJ/2Znxnals3JGe1qramM+56+6ybAFNhprQvjcPIyk/bRCwVNoxxjQpybXKc/tm6oZg6JEYkh+3sSrq6YXzmims1IEXxVM1tcRYwl4SegizG4bnVySls5VsdHzOZzDo6vYL0jpZbQK6v1lIF5eImpH6RYHLN93zs/Ce4sAWtmMv61jUMU1Oy5u6akGNVnE3okudLlGqQqDOzMidJ/efTs2G2n827yeanBZJEYLJNidsd49v1ATu9ycU16oj93bcxyyYRPGVzjrMe6cWxr2uwx1X1ySe2uqH1W+yCvLdYqI8jhESkElmfnbM6X9FIDr29nGVNoyWTd0ffeGbfDvNsFfZXvJ1NjfDPRuWuG50/e3Yxru8k+PPXlWQ2czv6TqW16XBOZjLvL1jrZWWv38t0t6eHJWw7yAJC2U9aQNwH0ePbZZ/lLf+kv8Q//4T/klVdeecvrtpffnnwDJ9vdBbIs4CLqoA4GglEwQBKU8p+v7/C6qCuklOj7Al5I2aHt8po4Og5NUVYwGnk9WUldyYOWV/i+75UeKiPxLtZq1KkNOK278myV954ougOcMG+y1g6HlOGFDBlRW5SG6U6rvxT+Cucss5ll3ngWM892HYmh1Z4ZDgCT44+MTsyQOoL0A7tFeeVcJZxNWJPUWZ7bxGAIIdKFnpASMSsoEpWGLUggAAFPMh5jPNiKYD2psGaUfjOO6OaI7TCxpN6UfAhTZg4hIZoJc+f9dfMuDCg5bQVT45BBG6FnuiEadd1Sect84Uk41htDTIl+2+KMxc2K4pty86fcf7phJ4lECRjnMM4PjuERRqKO4NB3dO2WpvJQVcORS4eVEPue0LUYM6OZV2AC2BWCMgMghqo6QJLjYNFwdDDjyvEx83ng+pU5xggnmw2r1YoXX3iBdrOlXW2prWcVAssY4eFjSIJrZriq5vjGEdeu3mY2d+AdMQS69RqXhCuzBeuzLZ/9zFd4/PhsRPrmcaP9Y6kqRXb3vSrUWDO+F0LMwAbrxhQthMjqbIlDmDU1znu6XlOd9FFp5EKMtG2g7VrasGbbrdhsVmzblr5vc9kQEdqkrCjNbEaSROh7YgxkKL8q+ylia+2bF774NU5PTnn84DHb7VYPDCJYZ5AUhoNNzHleQ+hJIbBYXOX209c5PL6CmDqPxwApwoCIVoDJai10QTA+DYoqUWg3LWw6Nsst1lrmRzNc5alnM4w1bNcb2u2W0HbEUNYsQ+ojQaBpoGoghaQsE8ZgvaaB8RnpbLwjhkjf9gqgyTlmkcxuk9HWRcHv2l7nw1R7nM4yqyw+9x4+JLQdfddnhHrA9tD3UQ9zZ4H1Urh61XCwOFTghLXMmobb169SzWrq+Zzl6ZLzB0va9YYvvvBF7j++y9/6b/+fYA337t+l6ztc4xELr7ym0STOVhmUNGXmuajYTvl68ljNiQqNsXhXY51Hckoj75UlKvQCDuYzl9c1MoBJWXdS3xOjKNLaTBD7QcE4ISRCEOpZw+GVAyT0eAfrzZrNZp1ZjSJiwHtPFNExN6xCoxIfMygLEawRGj+y4uxlL3vZy29XXn75ee7dfYr/o32Jnzj+Z/y/Hz3Hf/fgh3nXu17h+edf5AdOI//m3Z6DsKtFvZ5sNnM+//nv51VRx5ymbpm/tS+xl2+phOD50pc+SNO0fPCDX+Dq1ZO3u0p72QsA//SfvovPfvYWH//4y/zBP7g3BH03yGw24yMf+cjw+172spe9jLJLjW9sSZ2cWSKMsnXmEBjIrMmXn6R3LYo7TrSUo92L592QrYZQmDzKfQWEYMuDsnHTlujrYq9NynDqLwAeBvvscO/oWH0SP3IRUjCxDe+gBHJdBxsy43WTcgpw4t0f+wFuf+D93PnMZ7n72c/hjB3Jkc20MpOnZztSkohagXfBHibbsId00oZJexhl9Ega8Z6KQzr/q+5qSJSgKgvGknKQ1WhD0TKTqRATUbNPru8QWGqKy/0SG3LpO5vZu7MNeafdDQwJY2SnBGsNVaV1IuQAyBBIGE0pne39whQ8YnPbZ8bbbC8rjuHyjJSyQztG9T3klNe7tZfM0BDVzl5ZtVWbXi1lKYEYnK3AGerKU9cVs6bh+u3b/P4/8ZNao4M5MSVOTk6IfSB2gWgsXUp0KcF6A4KyPztHs2iYzRd4bzNDbSL2PUZg5iv6NnD3zmO2F5yLUprBGFxmn4mZdb20z8D6khkzTAF8CpA0UE1yoBjZptYH4Xt+z0e49eEP8cqnP8srn/k8IQZi6rn+3uf46E/+GMl6IomYwEVt/yAhB6Qpi0SKieWjEz73S/+A1Hbcff57uHLrBh/7X/9RDq5f4+ThOdvtlu16SwhhZAS3ZlgXJNtYk5R06YmqmnFwNKduZggu2zDV/lyY2QXJqVuEmBgYxU0G4ASJECKhzXWuvTJ7eA8GQt9rqpKgqXEKQEpSImVWcevIQXvZn5HXz4E12SqbRAwRY3TU7y5CI7gGNLiSMtWemFcMAaWrzYYUdBwXBn+TGFh9Ugr0rTCbQX1YZ9IKg3eOw/kM6536C9qObtUS+sDDkwesN0tmn/sMGMNqtSSmiPGWsA386i99ivXjEz7yRz7B9efeNdiQecKGnMfbRU/isHQbbE5tX5ZRa/WdU8p889XA6ZEBGTp2JUVSskM7q69PlMEo35+Spp9vZjWkiDXQh37wYZZtyBqbkwXIxQoCjN+J1slZc6E39rKXbx/56Z/+aQA+/elPf9NAj7t37/JjP/Zj/JN/8k/4wAc+wN/8m3+TH/zBHwR0/fj1X/91PvaxjwHw1//6X+cXfuEX+NSnPjV8/zM/8zP87M/+LC+++CI//dM/zX/2n/1n/Jk/82f4xV/8Rd7//vfz3/w3/w0f/vCHAfhP/pP/hP/iv/gvuHPnDrdv3+Y/+A/+A/7df/ffBeCFF17gve99L//1f/1f81f/6l/lwYMH/NRP/RT/1X/1X1FVl6XzfOfJmwd6TJVZ8jKV/y5qVDJPuvGmMjjKnyx8R8+9qJSWKOyhAoUOqVAjmV3l21ibHW12Up+sXpYNNG8NA8ijVLD8+nVW2Ut1eNn9fvhXxrqOket5YTd6BCkUcCNqc1QcB+SmwECbl9RprD+So9BVLcZMKdTyf4wZnhslEaKygSQZlfSxckaV37IZGZMPH6V/i9JtEOuQSSqcouyX+qvSlHCkXOaFEWJG5b6Uvdu6IzXZ9E5rDc4ZpSPLN6ckOR3JpH0nvWWMzfpmTpuR2yXGRAwBazMCvrRJZocYyjG7B88YI13X4xs/omxNRIj5GZJR9WYYa1U+QBwezrHOQtMMeRnV+ZwIIdKHSBcC0nZISDSuwjjBOU/TzHB+BCmkoKmOnHN0bcf5pmW77fSdy9wqB9B8iNUzqdl9r+lh9RKEf98Huran8orcVbrCKYOFKoFd17Fer9m2W0LICqzEAb1blCgpKHQh5/uU4ZHKfBHo+o4YA8vzFcuzlaZGyQqnIEiMpDAiumNSqkTJzCjOWZqm0pQtEhAiIgHQ1C9lUClIRNOD2ELhpues4UAgXVbSG6dKfmbi0frEoe6lLU0uuLS54q2GE3Qew3YAeiAQbQbfiBkYVYYDw0RRL+N8mEbD2jEOeRGh6zva7XZQ5q0t+UAZQGMSEjGmqV1jKKQcvkv+UID1ZoUxwsuvvIh1jna71XQ2+f52G0lJWMw8/hIw9pSh53W12XxYsAM4L79UMSYkIZknVoqc4iXlQ1pG7pvh1kE5T/nAVJ7hvaOqPK69BAhoLSalUeGffD0smVIOIaX/92r6XvbynSghaPRvCG/tIUDE0PcV2+2M1eqA5fKIaweRD1VnPN31LLaew63lai/cbIVnN/KmQB4AMTktMx28pe+wlydlva65d+8Ki0XL8fHmmy5HxLLZLDLby1vFLrOXvXyjYjg7azg7qzk7q7/+5Xv5jhDnHAcH39r9pO88q7MDus07fxylpPt51zWktD8f7OW7TASG9ABMTtnlo/Gr8Vp2D/nlHjP98IJtejQW5l/E7N5/wXBb7B5DkphswFF7WL63OPF36i7D/bt2ZjMUM/3oDRrlks8m77XTHOOTyys2h4dUBwecHCxGoIQUq/rEcjoUO2UFKJH1+RXNLhjniTYb6qO2lgLC2DU87TQVg4d1B7Uz2poHg9mkzy7aVUpK4SccukO11EcgQ0NxoQKy+xEX7HSlSoPdvbzlZIwBJU3ZUK8yEkRtnzYbUU2xcuX8F1MmhCmreMppnK0zCFV+7zTYoIvtj6FctSnXTc3h9UOMMbQx0rUdBrNj30opqV0uREQEbzK7gjF4V2FKevNs6/ZVxfz4CFdVtF1/gZF3HNAGDcwsjBBD9+Z/dxlQyvjWf2PUfkzFpprtec3BAce3b7K4eoXmcEFKifNHJyRJHNy4RtsnNpswPkyNoCB2Z6yk0LN8+Ji0bdlev8b8YK4gihjouo6u7QbAwsgQrzbCAoAYTdHad8bk9Bw5HY5ICV5Ng022vGrKMcpmOvYMQ8r3lBiYLrQxU15epnNo4sfJY28MbC62xfy7HUFqxtoBfIQIVthh+XjCvJ9BIAULUp45nTciEGMghDD4fIbhSHknvaHvOrarvC4MD57YkDED8KfvewzC2dkpxpoBeAPqnzl/8JjTew/oC9joySn/daTM1/HZF8uRYY0cv5A8EERMBgvm+SHTayY+rjzXB1u1HUEjO2INpuSyYuJrKf/I7isWO/Je9vJOlD/7Z/8sAD/7sz/7utf83M/9HH/37/5dvv/7v58/+2f/LP/ev/fvDUCONyN/+2//bf7xP/7HbLdbfuiHfoiPf/zj/OzP/iw///M/z5/+03+av/AX/gJ/5+/8HQDe/e5388u//Ms899xzfOpTn+InfuIn+KEf+iH+wB/4A0N5v/iLv8iv//qvc35+zo/8yI/w8z//8/ypP/Wnvqn3/3aTNw30iMTM0jGhtxJ19iYRorEki0ZPUxSicu2Y4mQqO5vksDAb6trr5ibqSLXO5b09X1MAEsaNCnrR0ZkoUqYoJQl17PrhSRNSJQblMi/bQ71kVEYMOY/kbnUnSSVHhU+BEuNzppvi8D9ReEwSIUgGH5ByqoueXiKSrDoro26yRhRBu9kG6kpwfsnBcsHJ2ZqApzpcYJzHSUE1OzAe6yusr4iS6GLPug00m571tueg7ZDKox5Zo8hiHMokoO1qsVTWY40bXluxHwZ8BbZCMKQIXdvTtR1939H1Het2zaZbM/fKtCLk3Ji43EYKjND+AaEnEbE4DI4kgSCClQB0OyPGWoszBovBihmVPukhQYzTyhqS1Wf3MdD3HUGELgmPT044e/yAq8dXaK/yODEAAQAASURBVJqaKKrEFTRmoRUjo9sxhhQNy+Wahw8ecj1eZXFY04dAnzxthM12y7xvEfRZjx6ecHZyhiPSzDwfeO+7ODw6YHF8jdOzc770G5+mW61ZbTqCWB7dP+Xxo8d57hhuHR4ybzxXjhpuXJ0T44YYWvq2p90qAhxj6FJi27aEFHFVNSglIKr0GTMAc5zJFHq2qHA65mOfMghDR2xJLbTpImm9xXmvwJSYiKWNAEmR0AmvvPg1tstz2nXHerlh20VCDIpIr2pigl6Uyk8m8xrM4NTvthvOSdz7ylfZti0nD050XHU9KQneZSR9CPQZNZ9SIkYFbMRe55d3gVndYdNDuuV9ag9VZTCTMQcKtLHOYKJGKpAyItromjY48BG65ZbeGFq31cNVDDhjsY1F6nIwy4cDZ2gaR9NYvDfMZuVENDno5vUiVY7KZorHrGTGQdHM1IQxUFLNZDVdW86WVDNadGqVxtPEhLNuuO7q1QOuXT/g4f0lD9olIpYkBVCR4y1EWJ6v+NJvvYSvKmazGaHrabdL+rBV9pPNmi99+bNYb1mt1oRM9RhDTleTCuihrIvjOWaYwxeMN+PHOuadc1S+ypEHKBdLHyD2pGWLsyApA2ZyKco6ZOm2lpQcvgGMRXo93IXM6NH1HX0MdF1P2/Z5rRijLjD6q7EG45S60VlD3VQZmGUImT1GEMh0kAowuXDW3cte9vIdI/fu3ebll99N2zZv6XNEDC+++B5effVZNptdto2fbF7mR6oHNJuW2VdajsKTlKR7+faUX/mVD/PlLz/FJz7xef6df+cfvt3V2cte9rKXb0v56mffx6u//C425/OJ8+CdKW3b8MUvfmifIm0v35UiJiFoYFuxU0Bx0uZAwWybGp2J2c4xTRdN/ldQ9k/Gj9RXqQE0xcayk+ZYCqtCts6aSXlGQOzEdsxoqynGlSnwItdhF9FR3pVsQBodeYWbYudKmThWi5NVxhoWL+wYhDNNyyCDXTwNZY9MHUSb7dEK5hhqmYQ+JJwDYzuqvmLb9iQstq5QXpUSlGfA2IEhVlNKx3y/BqRVIYETRuZkZfCgBAuawjxgMTn4cnBkWpSqoKTEEIghEWNQNgwXNQ1w7PHZqV1aoIApNFVCpjAxKduUk9rtRG3OSpJQ/ADjgNF6mezbMBPDTWaDTsOl2idmdEbHGEkIUdTe225WzJoZ3jvtjVT8CRNGgMJMYPR813U9m/WGucyoap+ZYyxB1E7to75LipHNuqXddlgjeGe5fvWYuqmomjlt2/Lw7h1i39OFSKJns9qy2WyHtnI1VM7S1J75zGvgW06tHUPi1gfex+FTtzFVRUyFscRln89kHmCGIEmT07aPQJTsKC+BeHmsmhwoGlJSxuVYUljLECgM8MxHPsj1559j9dpr/O3/9P/B7e99P8997Ac1CE8SDpuD9tS+P6RVnhgVjTHMjg74vj/yb3Dl9k2WbcfytbtsV1vts8IGXQLeUiIOgZ0j0CNFLdRatSMbCcRujSvDe5yslOC9wgKdMkPImGFqDPYEyawrYEzIS4sCSrxziBtTd5hcR+fUfmytwV/mtcs2ZOuU4X4Ecoz29WlKcR2fJeBTdupYAuMkxIxcYQy2MzBramaLis2qY13SwCA8+MqL3PvXn+fau57j2R/6GF3b8/DhaU6PXel8Dh0paXrsLgQePrqLsSbb9XNK9gLCkUnqq7JMTh1Aw7y8MARye5hsu3c5rYpO75y6RiLShgx6yevAcKvO2RiUFd76/IQMiCvjJ+b6xhTVrlz2gmnEpCn7Dxg32rXLZyV1lpAGlNCYEuudre/u5btX3gjgUeRP/sk/yUc/+lEAPvnJT/LjP/7j39Az/vyf//Ncv34dgI9//OM45/iDf/APAvAn/sSf4N/+t//t4do//sf/+PD7H/pDf4gf+7Ef41Of+tQO0OMv/+W/zNHREUdHR/z4j/84/+Jf/IvvPqAHkh3FIwxicB5CXhyHyOuJc89MlisZvppskZMyslJurSpcZvr3zmpfFEU7lr27tg5K4I6YSRVMUU7YXU8zPPTSJVYu+3MC9Ci7jZks1Jc6M/Xtp8eDi7nXJCWNWM+sEjmbwRCtHp0qmiFmRS0mvEjON1mqNFHGsoKcGNNbFDaP8fIJIEdGpdcYFFAx6bvyhTF2AAooyjsNSOIQAqv1muVyRarSLtDDaG6aPmnqmegS3noiHULAGY/FsU2BLgbwmQ0tb6IpxaGvypEkJqUjC9npYfMho/yU0amKRhzeo2s7ttuWft7jrMN5izFa/y4E3dApqV1GxHTbtpydL2nmNV27JfQhMwqg1HMxZqU3ZpBCwBrwzjJrauZNw/HhAZKEuqpw1hKjplTpu56+7TXljnVY9L66djQzz3YDfZ8ys4sqhi6jZUNUpcNYi5kCPZCcLsQO/SdGD9jDyMwpVTCGooKXg7L2aRoYZAxmUJbJh4Ekic16yyNJpCikIMSQhjpYmxXSfAYc8hHmn4KoTykSQ89quWS92dC1bWYGKcq3yWVN5kuMmpEl6nvkkYIxAVJP7HsSmT3D5IO6AbA455k1NcbGEVidm0UVszHvtM0pkMohw9Z2XH+G+S44pylDmsbTNE6BWyUVC5LB/nq4TSlTRw4o4tIO5fChCnCIqiSHkIbDl4iMczBTKZqczir5CpvR94JQ157ZrKKq/XBgMiIjEjnXP4TA+fka7z39NpAyOCqGXg/7IbJcnWG9Qc8DpR9kRHRM2uOivI6+PuwBBj2Au5wiTNfuTDcYIhLTAHyTlB9kIEqmSgzajyYmjNV2UZrMNLQpjG1enlvqNu4rGRJoFXBY0oSZPP5sUuT8eKeOPdkn5d7LXr4jpesaTk+v8NYfxA2bzWJwCg2gPgNPuy1Pu60aItdvcTX28i2Vhw+PePjwiPe97+473nm5l73sZS9TMSLMou6OW7d7vvxGZX2+4N5Lt/l6e633kYODLTbr3TFalssZKb05jisRw2rV8PjkgEXruQzCWSc4iNCkS758E5KS5fz8iPX68JsrYC/fsLSt5/HjA+bzjsXirc9zvpc3kGwbxVxuQx68jObiPZcXJpesK5KNt2qSMoOdZ3ScMgApYDzzDxXYsdd+nXXr4teX1fuiGUB2f9cqXmYrkDd497GgJ03XE/tRcdBLYd0o103tzFMGCMHmIMrR41ueMLaNkIMeB1OPXHjPfN/ED17ssU92mXnCTqT1KraZRNf3dF2P2OIAL4Xq2l7Yk8VKTpEQIYNVjLEEySmTBWWxyDZkmabxycUWe1CaMPSOdTQUK7JcYOmIIRBCJPqoQWOZ/SHFlEETu2Gkxc4ZY6TtOlzliLHPtqkMNMi2f3X+qr1fGTHIDn+n6ehTwsSU29cgicEnkBQNAcZiJDNhe4v3lhA07bDkYN3m4IDZ4RFt17HetoMD/ImRJ4m47QewlnEG1zQZzEEGtuRUKMMgLo5t9VG4qqKazem6HtOHIYhudnTI/OiQ5Z27PHz1LvObN/U9ZGi5cS5P2VVKVwx18hzdvMHRrRucnJ7Td0HBQykNlxozsfntzAmGeZNHCiaze6QY1a8wDY7Mv1mjzMDGpN3pwGg7HutudsaW2l5dKWr4p9gavbM4rz6ZKVuGTvfpO4x1p4yzvCaU9WCwKU9YoQu7/HBTroEBnLEYZyg+BAWdOE2HXcAhQOx7No/PWFzTVEEpJdqux1qrPoCUwVFJU0VJErquxbghrpECdNhpwG9AfTSMNmQwQ/sNgCB0vRioVxjHTwnsFMzQTojNqXTIKVsmIKbJ/cNc2PHq7Wwm6oMamPuLb47Btze1IY99sJe9fGfK008/Pfx+cHDAcrn8hu5/6qmnht8XiwVXr17d+Xta3s///M/zH//H/zEvvPACKSXW6zXvfe9737A+Jycn31B9vp3lzQM9GDcea8BmZGpxFCvyUxHbqTjgTbkrr1tmSByIXNwKJ0qhNXayRppBodOY7vFy9zqacFHGYnZVG2vxzg+KyK4WPtmqJyjCy/aZMU3M+Pt0kwUU0WkyKAHRfGA7DuDxvQRtSyclWj8Oip53Dl95wCNSD4eTGCPWtLiqxjcVdVNxsKiZzyqSyUwhmm8CIwYrFmcs3loq76hzigJfO+azisW8JvqKaD0ppxxxCDbmTjMw83C9MSw8xBSVSUUUne28J2XGFd2xEkki7XbLarnh7/+9f8TVK9ewxoOxA2jHWO0P4zR/2nxWqZKUv6+qGu89rnK4ynE4azicN/jKUjeOu/fusDxf0nUbjEn0oeXB6WPcuRDiOc5aDhcLnPNU9RznHPNFgzGGrg307ZbGwsw51suWxw+XtJtIVVfMDxbMZg1fevlr2MMD3vfcszwTbuAMOCOstj3rTc9XXnqVX/2X/4rnnrvF+XbJ6eMVbt0iGNarNQcHSkEX+sRy3dN2iYPFIQL85m+9ouj0/jdZrzdsNz2z+YLKgJOoioDVtrHOsmgsV+aWK8dzrlw/Ynt/y+o8sk7CBjieVVxdzOhCp85vAecqBp00j9uZszw9q3FGwGzpMdyPDaq+6ugM8wUpRrrVkhh7pZ0TwSTBpERA6CwsDmcc1Ja7j5ZstkHTYxpou6BUgM5ROzcerkWABNZiq4okELp+OGikJHRtoPIBYwVfGa4ezph5w731ihh6VXYN+EqV37ryeGs5W27YbALWG2oPIRhiEKTr2D4+I9aJ2CSsneHqWZ6/Fmsdta/xlfBv/MhTJMlIbwu2VoT0vK7wztPUBzhX0TQHWOupXMqAlQAmYWzCGCH0HTEE6trqeK0r6qrCiIPkEJPTHSULYpWBJKgCmjKCOiWbIy8U3BKSGRkpktBtemJMtG0kxMSq3RJCpOs3xBRIsSGJo+2X9KFl267pQwdW2LaJZtZw+5lrpAQxCotFk1PR6GEjhUi33NAbw4YVsQ9szpcZlR0x3tB1CZcsJtUamCEKnnLO5aXDlIV/AJ4MB8fJYWTYAqY2H2vwlWdx0OghQhKhC5yfnFGZwHElVN5yOPMKaCmpQq0lJWhTIkQwXtMZ+MopcCQ5YhKaFDXvqdfxE60hWTMQesiQj0x29yZrqZ1j0dRcv7qgj4l1iCwWnpk3VEZIfbjUdLOXvexlL3vZy172spe9fCfKcS/85Ks9TYL/z7MVd2dvPZjtAx+4w7//7/8SR0cawfzSSzf4T//TP8a9e1fe1P0hWP7m3/xRfvH/+0P8n++/wh/m0RPXfPQk8q5N4mq/Z896p8iv/MqHefHFm/zoj/4mf/pP/6O3uzp7Qe0CI+uzimIKbInmGh1nExuyAiNksJ0W++SOwTaHo+9E+pdgr2yTfcK2e6kZWT8oZoBCzf+mvI6i6QqmGN6pDXl4rxJYVy6cRhgNAJCLqRLI2W/Gl546CYeAG3K6YFuYNYrz1JBSwpioAWROGRLqylF5OzDsTm3hJeimlOdyymGN1Fe7crIWKQFFNmGRCZsBeAtzD5XNIInM8KDBYiX9d+4MoyGJMQT6tufLX/oqs9m8jJrBHaDMIWb4t/JjUBCGHMlvMU7tzrX31JUbwA6r1TKn8ugBIUpg3W6xnZBShzGGutJAKeu9OvIrjcZX5tqAM+CNoe8im3VH6BPOOXyt9uyHZ2eYpuLa8RGHaTGM+z4k+hB5fHrO1167x/HxAV3o2G46TB8BZTkIdZWdzkLXR2IUqkrTmD14dEZ7vuQ3/9H/xHa1Yf7ed+GPFuqfQfKYKW1kqCrDzFtmjaeZN4R1oG8TvQgBaCrHrPLEFIc0GmYIboPixl49eMCr/+R/JrYtEJhdu8pz/8aP0hwdjvOmqtSx33dDaqDctVhref5/8UO863d9hK/+k/+Ze1/8sjJZSGGUMNz83vdydPsmi+MjDeib0n7kCWSynVEZGgrIQUZWYaO23Fnj8c6w6jsN2MxDxLpJMJkxmq6mT7gM4khGba4SI2HbkpzgvWCMp3EVA5DAGJzVdObvdocMWKmM3TDG4L2moPauzv6oOtufSz/loMqcTifltNMlPb1zTlmKJBvZsUgOiFbwRyHfGIESJQ1JzOCWlM3vCoyC2KstOcZse89AmJgyIEYcIpaYOmIKhKCsGxghBMF7z8FRZlFPwru+7wM89T3PYip9R5FE7DS4MqDAidB2A8jEWA3OVTuxy9M26apg87zGDOuWmax0ZRhc5kYc1kmjY62qsk0bDfTrNi3WJBqLsjR79X2My29mFspAM10HNd2OEhAp64uXBNboOmMMKfsFyXOlbE8kdsRYgzOG2qsPLonQJ6GqLN4q1/0wZ/ayl+9COTg4YL0eI9hee+21b7qsl156iU9+8pP80i/9Ep/4xCfw3vNTP/VTO0DN73R500CPgd2JiXI8/WBQuPLnUr4sCLsJ/dcUrrGjN0+QhMPn0wsuQDCyMr17hZl+nathBkRlKWb0N+468th5bvli8hAzPmOnHaZl79R3WpMR7WHMuBGUvH5JSrqQojzY3ebMJUTvcs64Udn23tJTsOG7lRqVdVU2jFXHa0FmilWlwWZyDr2+HCUEa6BxBm/YQVzqRlqct2WAZCU9Rtptz6uvvMbp43NE3NAPpgCDjMXVNdbphuerjBK1lrqu8VVFk8Es20VDu2ioa0c98yxXS/q+J8WozvXQc3p2ijGRrj3Fe0fsO7yvqGcB7z0QM9Ajst20SOgh9YQu0LUB2OK6ANYhGB6fnnPv4SOuHS44aCq8BWdg0wbWbeDxySmv3n1AVRtu3lzQrXplG+g1JUToA5IZBGIQUjLUdU0fIydnK2IIbE/XbDcbQoiaIgVNn6FTSg81yqiihyTnDNZbogjbPtLFREQwzua0EnZIMaRMLmTkrZZTe8eRdzgnWO/ZiuGk9YjYPA4BK6To6DcWEyeEk/nwFxECwtw7KlMNTCKSB3RKib4XPRhWfjiEUsowKKVHElIMg0Iz0B2K4Kwqx7PGYyTgPbhe8kHOqFLk9PvKO9quI4RMD5kPOn0CEyOx7bAiRCPITChUlM55vKto6hmVt9TeDQcA48DNtL0PmhrvPPPZMd7VzGZXcF6BHs4K2Az0yICPvm2JoaeuHb7SPq+9Aj0MDjGeZHxW2m1mgFFlWVLMSrsjTYAefRxpLVVZDcSQWG96Qkycrdd0IdB2K82pGBti8rT9nBC2rLcr2nZL23f0oaOuGg4OVMmPUfDeZvaMcW1zRg/lMSRC39O1LZJSPvTl9cdWzKq5Iu4DxKBAEJKMa+5k7RykAOMme8RFKVELqRzeUiJ1EeciLgN9vNN9J+YNylpNylMOE2Xsamoa1BhhZDBwKMI651a0ZqxPWf8u1KvMS5fHng2RYKCqLM4qAJL0JKJ/L3t5p4u1ibpOxGjo+zdp9PwOEd36LClZYnRvd3X28h0gITiWyxmbTbU36uxlL3v5jpBK4Pl1YhFhFt/8wiYF4C6jrebN7rVHRxt++Idf4Pr1FQBXrqxpmvANPNvy5S8/xQtfvsX/6vAMZk8CPa73wvV+v1C/k+TevSvcu3eFd73rESl99+ir37YyNWReZjudRqvvQBhGe6uYCYhAYGBnHuzLDPc9YT6+rD4XPjdPXMBo933CljEmEhmeP4ke3y3DTJ73BmPxzQzTXB+ZgDFKbaYtMNj0dgzTGqCoduAJO2m2nezUefJnYUYxgwG93GfHVB5WMHF8frEhqz2pJG5hCADSdNiXtbk6WUNMnJ8tabedOq5LsCWoHc8YjFPmjsprquQSLa+pk11mQ3CEyhGCOsydt3R9l5mDA6Fr6dua7XaLMUKMW2XCTVHBLanO9iwPGegR+pzaAk0HEnOu8BjT4GDYth2r9YZZVVFlQIE1KNAjRjbbLefLNdbBYlEROy1TMiv2CGIYmSaccyRJbNuO5fmSl3/zy2yWS977zE2q48PBdj90e/6xZPu+AWMh9IHNZkvXh8xmkNusMCUjo69jaHOQrmf16h3CdoOxQe3oklPlDONNGXdSP/LVFBuywXBw85oGMH7uCO/s4AMpXofZ0RGL46OBQZdpgpcB4GUobCfDV0BhL7aZQaHyGoRsLdgkA/O8s9nG6BS8FIMluQw0MKjNXgxGEilEjEAyohmey1wwDpttydaaASQy2O69tnnlHdZYKt9grcP7mfpghnTwCkwx6L8xRCRFtfe7DPSwDnKKITEWweUOyUAPffkdoIcIGeih/geh2JmLTVXo+0gSoe17ZQiPOY2KqF8gRE9KgT50A1N5TFFTa2eQRxKwBzPczWts1y1nJ0uceKrKa78m0SDBGIc1a2xDi7ceQQE93vvhZ4dRZtwOdtaJYSuRi9+NPiqBzMiRkAjGCtYzMmxgtG+HNWtwd0zKGufAkG3gQuD3rv8vz4PdKjEAlTIAKCYhkXJd8tKxNwjs5dtYQgjDT0qJ7XarQbB1/S0p/4d/+If5uZ/7OX7v7/29fO5zn+Pnfu7n+OAHP/hNlbVcLhERbt++jbWWv/f3/h5//+///Z3ULt/p8g0wemT3f9lIUtSIdGPBeZw3+FRysTGsdjLZgc0Ti/RkPXvdde2CJp43d8gK/+Rhkp9XuAlUqUwTwMekapPnljqqCnKRSK847TILiRRVOl9lVXk3U8fl5AFSItqRcaPKSMvykUWQAEE0NUYYdInSiGONxOiGrjRtGSyRNxxKbsSy4SMko0ANZ8CkBAliMoRsULHl+QJWDA6bg9qVqoyYsCLUVqgsA0NJsqqg1DYhJtGXvGom17EoDP0pqcspSDAjeD1rnxIUABLXRTkyA3q+gFGstcpwknObWWvpQyL2SgFmfc2rX3uFz3/61/Dec3TlKs456lrR2K6q1SFdX8FYh6RE13d8+YUvcnJ6wnp1ighstz2gAI2q8nzpNz7H+Wuv8fL1qxwfHSpq13hCCoQU+MoLr/HVL77I2d2XePS1L3N4eJ1bN58npRYJ9/AGzk4fs113VFXNwlrclRmrTcsrX7jParni8YNXaTdrHjy8T4qBq0cN1lSUwWEcGKcHj25juX/3PoGGr77yCq/cvcvydKkoXSzJeZKxA6PH6Li2WcEWbErU0jNr5lx5z/tY94mvffFrxK5j4CGQ3RQcRdnqUyKGSBDBGbguwmGcTCYBiULMJwpBAUXYRBQ92KzbgPEGV1skakobAFepojw7cBwe1Tz91HWOjuYsmg3bbcKYa7TbHmMCxgjzmcF7w3x2gK8qQpgRY6BQtt178ZwHryyZtwn7sFc0e20woWcz33B4eIXrN55hNmu4cnSo61bSOkuee67Sse4z8tvbSpVSn4Z66EFK2W0SgojBugqDJeKIIQM78JkRBsQkIAwnMOsM8yYfdFI5AEcEQ6TSZYaY15ZavxdNfYRVQ6ikHpExwVBMhgR4o0tUHxWhTKaDDCHQh0jfB9o28OpLL/Fb//o3edX0PLxnuXnzKj/w0feTQsvq9C7n5yteePGMrktst7A4nPOhH/gI165d53s/8BF8PePuoyXbtiOeLenXGz7z2c/w4MEDdrHYUv6vrB3eksRcSJ2aGUCsxVgPEjN1oB5ejDNUc6gqRzWrMzhl3CP6XpDUk0LCGsFZGSgbuz4QYqTrE30EW3maRU3qO1IfsLk9S11tyclKUuaVnBvIIooUz0juubfMjCK1k5E32M/2spd3prz//Sf84T/8Ii+9dMw/+AfvIYTvLsDDnTtPcefOM0Mqlb3s5bcjv/Zr7+PP//l/i4cPj+j7b4hccS972ctevuPktdee4d69kZJ3v9fuZS/fSZLdaMWLJql447BikCGl9nieFwQjmd+ieOEmJuEhlcH0zH0JgONiFYCBIWQq01tH+MTuF+Md5kmAiZhCLDJ8PpqbZfzcFFsPb2wvKIFb5cFTu/CAQxEkCik7b5NkkMcTABi9X4QMqilMq4xWmkn5xdJdwBhmcCKjwT0yse3kVxq5gfPdSa1qzgguP0ubqQBABDEllXjpl+ywTxFJWyTEbGsfS9amN5iculf60pzZ4VpAIdmubDOjdAGsxJzK99HLX+Mrv/YvObxxlQe/60P4uqZpZoP9ubCOGOvwrsk2dk278ujkIdvtlr7bgkAICdCgJNtaHt65S3t+zul8RtPUOe2zzUGdiccnSx4/PGG7qticPaau5xwsriASIK2wQLvdEHoNBKxqBdP0feTs4Zrz8zWPTh+xOT/nqc2KanvAvNaAsmHQaMeRUiCGlvVyTcLzmV/5Z3zxX/4Gt773fdx8/3vV9mk1zHBI61Gc2+W/me3FkTDeMbt6jfnVG/pOcUpdMKa2GO42hSVBxydAj0zcG2YYMmKEhMnjpfieFLTQR5PZaJRDPgY1HpaARl9rivPDwzlHR3Mqr0wdMNdrjaa/8Z4cUFhhnSNFr6CRPP5XJx3rsw4fBLNRoEjlDCwifRWo6xnz+RG+cszqOjtGzDB+wQwpypVopgQimpxiLk38QqPvSUR9K8Yqv0WKFg3/1MBfW6Z0oYrIoJJq6i6arFUpe3QGAFBJESN2Z75Lpk0pt0vSdayE9MTiK8s+wJR0rYlJgwHPT095dP8+X33xDp/57/8nnv3ge/l9P/lHsRa67ZK27Tg5bYlRCAGq2nPj9i3m8znXr9/COs9q07E6O+fsc1/i5OgOhwcH44tQlsrJmprBPBKnBmQG23oB4whJg6uHrzUI1TqD85qa3U2eE5PuTUMKeDOOU00/I8QkREEZWrxDovqWxswBpc6jv1LdKlq2gRwkq29UWYMf3nEve/n2lf/oP/qP+Kt/9a8Of8/ncz7+8Y/zqU99CoA/82f+DAD/5X/5X35T5f/Mz/wMn/zkJ7l69Sp/4A/8AT75yU/yT//pP/2myvrIRz7CX/yLf5E//If/MDFGfvInf5Kf/Mmf/KbKeqfKNwH0GBeqQUnPznelCytqwUQjz1xWg35bNreJTKEW498XL7tkCXwdZV6fLFjJPsQJ0nS4SabXy7DRwg62YufJuglPH/rkuzxRkalSv/OdFDf8SDmWJG//U4U212z0p+f6jUqrMePf03ca8trtOPEZ0J2lp/Q1BlLFXF9FQJqhRpNNL7+Ts+oMHfLb5ROBSEFPtgoIwu7Uq2h+MSvpkUyRNSBiy/XT8TSOwaqZUy8OVYF3juXynC98/rPU9YybT3/PwHhijME6jzGe2l9XcIwVYuy49+AV1utz+r5FEELIdFlJiF3Pyf2H2L5jeXJKPW9wpsaaCjGRRODOaw85e/QI6ZZId8at28K1a89hJCmgYL2myyk1nHNUFszM0KdI2/as1lvOzk7ZbldstxtKzkZJqnhYQ1ZEDJIiMXSsl2tsc87jkzMenZwR235o15h7akDL57EztqGqi45E5RwHV25AFzDmtZwTMw3XSclhN3bVcDBKScE/IU0OZ4bMxqEgniGVUVEiUYWwDwlnBJ8/V8UbnPeKGassVeM4OJhxcDCjbR3OO66sZ3R1hTFKuzabQeUNzbymqmoMFkMAoweV7sGWtYUqCjYmbDC43sI8aZstoKnnzJsZBweHisY2I0gCM2AoBmf/MCJtmCjlhsK7k0p7pHFsx0w5JAjOgncT40YZ5xb8hP3C6EOzAl9jjFCRFD3sNeWRczXWKEWktRZvki7FrgLjiCgIal7VVFYZRASXUf1C1/f0fU/b9my3HTO2PHzptzhtdM4cLGY8/9xtUr/mdLbkUR25e1fXj66Duvbcun2L208/zUe+/8M0swOuPTxns+2Ij07Yni/58le+zMOHD3fWpGH+56FpnYGdwDuz+3s+AGn6nwIeUjYa6zUyww7MR6X/cs7WvNfYPDaTZMaRmCMwErmf8/6VD2Gam1QGG0lZ7pXyUKMtQHDWkpxQJYO3Bp/nVzGQ7GUv30ly9WrLRz7yECAbKt6JIhmoN34Sgh2NxW8g6/UBDx7c4o0Vvr3s5c3J3btXuXv36rekLGWasVi7O7b3spe97OXbWdSmZEjJslwe8eDB7be7SnvZy17eIhnxCTnN9GC7HAEFKhMb8mDRLd9P7amXASbkwv3fvBiKSW1SzrT44aNsQ369xz1Rt8nfl9Z98ruQDVAXC1d2k+HqlJkfRvciozNXRkc6ox2msASMNupiOyxXXbQhT/uwtNGE2WTnhcefqWV/eF0zPrHUVybtLIgGleYUFbuvnsdE/jyWGpXqD3W52Gb6t3UeVzW0yyUPvvoi69U59e0r1PM5B0dXBrYBdXFoEKWzOYWMEUQiq/UpfaepLQQNcAQIvWBtYrtaY1Kk2241mA03OJ6FxPn5mnazRqKH0HJwCPP5MSSh75RJN4ZASpqGRKQER0lO1RyUqbfd0m1b2u2WflYh3qFAAjQjklW7cIqaVj2K497LX+PFf/WbVFeOufn+9+70WEZb5OYyO003sE4bQ93MqZo5ZYzuBMHK5Pficil+gWwfTtOxlAOkylwzpaziU8jO9pSBQ8U+Kyn7V8QONkXnLVXlqStPDBo0Ngue6CzGRAyC9wrA8JXDWp/Hy2ibjetAb8CKYIKmGjEJ6DWdC6LsE5XzaoO2piRJyuwz6isBtSeWV1FJIwYLU159YCORSRMmvRzINkmbvzCleXKhEzbm0V1isKYwhafRV2QyeAmbATJmsHObnO6phEh753CmgE2Kz0mIMZFS1ODkEPAE1qcPiesl97/yIteuX+HK0QJrha1r8S6xWmndowHnLAcHBxwcHnLr9k28rzhbd8yaGTdv3MBtWpx1pBiecMiN/oXcpjvpUS7akMvSNgIGMYKxyiRTgot3VlwZV77S7mQbcko5cDCNvg9lXp8yQk9qYdjt34EqRAbQj5PCLkIehe9U+9pevtVib1zFNDWSg6LfKjFNjb1x9U1d+1f+yl/hr/yVv/K63389gEcBhBT52Mc+tgMM/OhHP8qnP/3p173/YtqVv/E3/sbO35/4xCc4OTkZ/v5rf+2v8df+2l+7tKz3vOc9T5T31//6X3/dZ78T5U0DPUrKhLJ6JWOUPQBLMg7noM6ZW1JS5gBj7MSpOVEgh2Vwqt1mB5mZKmh5kxwWT7m4hO/8W9SMVBSc/L/E1PEmwx45fnLZceDipzKwdhS6MMEq/4VhsiUwbibD7YaCcy4MH1NFXNHYiV4iIQkRwwV84k61hEzVFQSJqKKeHc6S2RsQTVVgTTkeqZM+mETqt6RujcQwOOqVEMSCF80oQd47raXvA6vlkna7ze+OIntJeBtxNg50YQ6DFZM3wwIEkMFJnrITdgCmiCoeBUBkc12kKPwTWradZkh12V2zJlsh/oDkPCVSQJVuQ4oCRGJ4SBldMUVCn4gxJ0oZELVSuljTWoSUEZwRMR2WQELR2CH2pBRIySuDX4rY1JMksJY1m/6AGCLWGA4P57Sh5yytcUSevjrn0CXs9grLpeP05Jyu71hv1oj0zA8ajLccHC2o64qm37LdRh48PuW0g+16y8xWGK9KhOl7Th6f0m421N4QYqILgq9q5osDrBE8gblJOJ/UUV55PIarVw6pa8+mbYlJCNkRPiB988lQQsSkyGzd0gB913MaAm0fKEe9RNI+HHlhsuKa6ELidJWoZ3A0H79TJSjhjOFwPudgNiN0K/ptjwVq73n69lFeIpQm0NqAMYkkQqLNT0oaPZDAi9AYz1FtOW68OvZDwq4C1WtbQvuYB/Ov4r3nwaM6rxel77PCbKcH3sm/QxTD9C4UES0yAgKyYuxsSRFihpyXZVXQoWeGlCllvSn0kyYz4Tirh01jZ0NkgTEOV82x1lFXM5zzmlPUWjoJJITjecW89lR1g/MV1mg79SHSh0gbtmy7DWfrNc4d42zAGsPNm8f83v/l91FZIaw/yBe+9BK/9tk7nLdbIo5mcYXv/13fz/c89zQf+cB15k3N809XCmqK11gt1/yLf77gpRcnK3xRcsubmmk7Tue20ibGmAghggXnfEbx19Q+IKyHA6LuCzbr9HrYSykSogxnza7TNE8hxHw46QghcvL4EV2/xvSCiTr2c+WGQ0Q5wIeUaFdblg8eQUrMSdRopEolgbhZIVZpPb+b8r/tZS/vFFksev7oH32BW7c2AHSd5Zd/+d288srx21yzvezlm5MYHS+88F7u3n2G559/kStXTt/uKu1lL3vZy5uWV199Fw8f3uT8/Ojtrspe9rKXt0CeZHtWO2jCIDkqvURVJxHcjqHWcMFMcIlkB9rg/dv9qhhcppzNxcK1G2C4m/5EHbVT50KGdEyO+E+AHGT8dOdhMr0gGzCGoLbdp+pHChwZA/nGZw2hd0Zt00O6D5FJoovXazcFTki5UKaW9mKQHW0ggxU8CckKEgMSeyQzpY6ObZMpAAY3PRhDSomu65gFddpKcX4jWJPULpUNOja/6RA4xoTRhGJHym2Sx8hIXDIGYo64kAE9sNvOxdhcfBHGIa5CrB/Gi4ISxnEidjN+l4QUNb3H4FCe2JARBTKkKIjP6StMxEiiBGEWe/jgNJak30uip6dPVQY2QF1XhBhp6TEkDmcVYV5zMJvRnZ7xxf/fP8PWFcdHc2azhts/+P0sblynbmpNV5MCoY984Vd/nUev3OHey6/ijaW2lpmzmBjZbLaEEHA22/CjYJxTIIMBK4nKe7VjChinQIHZrKaeaVryIW1yEi5EcQ1M0b4P2JSIXc+26zTdDZOUMcLQNwNeRJRFYdsJzkPjJ/Y/GWYltfdU3pNiRwwtBmVOODxoctfHPE7UFqplhHEilHEo4LA0ztB4O6Q8MV3CngdS2LCuNEhsvSlMwKNXh/IKO9NOyqRg+t+pf6owZpRRL+ymCJkWurs8mp0PB3Z5k/0stnzms81Z+SOsqzDG4Kz2q7MaaBpzXzTeadohp2lqyryNUdeakAIh9LR9j7UzrKkwGBYHDe967iZV7Un9DR4+OuVrd5d0MZCw+GrG7aducXx8yK3rcyrvuHLo2MwTj999lXtyzr/6zG9wsm557mM/yPHtW4MvYndNMxc/0C6MkJxkdhoFtpAZPpxNKJ/MpN0nc1iXlnKvfq1BuGXOKsglJWG72RBTD1Ew2eeFALasUXlc5/JiH+jWGxChyiwfxoCTROo7XcvSPlhwLyrVc0/xPf/sb5Eenrylz7E3rlI999TXv3Av7zh584weA4XWqHgJaPQ+utkpQ8W4UeWLR6zDJbrWiDQerx9A3herQLlsgtUtCvVOuUWRnDoSZfi6qKC7C6k8uX/sfL2r5A/7wpM7+QUd/4KmTE5/M20CcrR4TMSk5Rfgw9jmu1UpG5kkhnccDisyKg6FdsvkjUYSSAwwUdInmgEFHZKJNhBQ5XLbEfowKFySX9KWHHP5jYYtV7JSd6HuSWS43xj0gCKTdyr1KFRZF53DQx+U3tLdVIxDrLIZaBtIPkeVQhMxhaGUlJIq4FOUuMnjSfRzRQ9rnVNKWIMyJYgQ80Y/KmZ6n5GISKBLLX3slMoLR117TemwSVlJ99hQcT6bkzJQIqZE33c4J1S1x3rP8fEhs6ahexzpu0BYbyFZ+j7ijKWyymrQpshm3RNDj7cKgkeUBaKqKxyCByqTsC4qitdarId5U6nzO0VMTHpILIp2QeGQDz0RfBeorCX1PW0MxLQDp83jYjLe82cxCalL4OLQ3wXcJZIwxlFXFbV3pNASgwxK+vygVgaFpPR6kjqQyLbrFPGbR4VJerqygDeWxjsOGkvbCZsAdAlzFojVhtXyMTiDWdq8buX3mESZTKeH5JN9mXM2c3nEPJ8LECztKOnkHIDo2DSFfWI6lo1SGZpxtYIxf2RJVwQOzAxMBnpYh/ULrPU0zRHeVcybCm8tLYGIsDmsWDSe+XyW86dFINGFSB8SbdywDWtW2w5DDaYCA/NFw7PP3WRWeWwfOFsFQvK0wWDRSIjbt2/x9NO3uHltxrx2XJnrnK9ry3LVsJhXkxFxmeR1eTilF4WYESiWSq5Nh3UeX9X4ksZl+G+J9BkP7XrQTMPWEmMkhJCpQDONZexZbwwh9TTWU1k3sNrs1NFon6cohK6nW61x1lChKPhoBC8JCZ3Cjfo3nxt8L3vZy++c1HXiQx96xLvffYYky2Zd8c9/9V2T3OCjjBEdWad6E6wfb7VEsXRicGj6tL3sRcRycnKd8/PA7dt3uHLl7a7RXvayl71kZ0nSCM43oho6Ozvm7t2nf+cqtpe97OV3XAZ7ZraZqI2xpGVRe8Boys0BHG9omGX8Ui79deeSyw0RT9pwnyz7okvwsoIGTo/Lqzkto5hMzcWqXXiJ4e8LdbzkEYMzsdhSdmzIT1q7S/El5XaxIo824fyb7N4lUgwiY6qHXaNWtplMXiMlTbGRBlthNvQjl24Lw0cXA2YGV0GxQWdohUwvlwmByQX/wk4LTJ5WAB/GMXD3ytgjQ0qPSXoSGey+03Jk+HsIkJMy3ic2aXIQJCPSZuhuUQBClKA2ZkkYNI2MIBB0xtRe7Zu19ziBey++TB96zg8aZgcLrr7/vRzdvknlHd574ibQ95EHL77CS5/7AlEE59Tu5a0hihB6tZGN6UEks2S4nDyEgQGCwoRgLZVzeO+yrVwQm3bbdyhN28DGhBNBQiTGREyRFCPTCTEFMZSxlESQKGB3fShS+suAcw5nbbb15bQuGGXuMAaR3I7ZgRJiJEoc65kLLu4Qbw21MwSEkFCHfpsQ19N1m10/0MSP9YQNWY3ETKo6+myGrydjbrIWjG1hJ3cNI5HdFWlcUUoQoapfmVndZICH9ahfr9L0I65Rdmin7RRJJIRQOyqvKW6cGzhLFFSWIEhPSD1diLl8DbrzlePoeEEzazAx0XaJJJaQlDneWMfBwQGHhwcs5p7KWRoPjVRcuzajfVRz/tpr3LnzmJvvfy/HT93iSbk4WMZls6yHZQ0sDD0KWDHkxEE77TfYkE1eFwen1MjkQQZ/6Vob6UNPEvXHOGMn6+m0mgZSXp9jInQ91iiwscCbrAikmJeAi3bovXw3S/XcU7AHYezlm5Q3DfQoiooRm1GqkWQV84c1OOW2GJXKiwvdRf31guJZ8meZCShilwhpty75pnJ3vmriaBXJC3r2eg+I3ktLnJQ9/Ux/dtOh5PvNuJFMy9CIeUMqDnLDzvda21zuRBGQjPST/F7G5EyHT+q5Qykjo0BGB4sqV87mK8ueZQwWi/NKaYb3iHMkY5FkiAjJDMeqQVJKpNBzfr7h5ddOOLx+m8KiYVAFaFE5kncssblRFJk9HOSGds0K44VXSrmaRWEuCEpjZUDRi+we/ko/KcOBUm9ZazDegtPxOaX5u6gUFfo4TFYAnMM4jwn9eABCSCkSY1DkalYuVVGkaP9ISkOuOkGp4EQsJlZIdPRBFfm+79hst9x/sGS9WfP40QNC1zKfezBz5rUh9sqIEVOi8o4Ky0EFsyqSHASsAiIk6CFLhMOjQ64uGh6cnHD+8AEpdhgS85nn6PgAax3Oxfw+gpvPOHz6Os18DtYT25bz5ZrVek0fgrZNVFR5XTmSg74PpJR2KSIFKu9x3rJp46BMWWvx3lJ7x2xWMVs09AUQM9yrgJYUIgYF3bTbFpLD0mAwrNe9OuhTAInKJmIgRWX00PEh9DndUYiRmCLeOHxRjjPKKeXDbwI2vYJDqkaYryqcN3g/mZeXRYMwjk0RkKCD2KSIyQdYSaJA8QTSWPBGz4xuVDCn9HDTBfHhSccLr6zyuTkzBFnD0YHnA+9eUHm9t+uFO3d72lZYt5p+CeswxuB9jXOOa9drZnPH0YFjVlnuzzx15agqj3Oe5bJls+45OQ+cnAeSRKIEbDLYCA/OliSEB/dP+Sf/4+eAwHr1iJdeuk9oIx5P1dT0feBf/tpv8PJLL3H/3jMcHc546nhG4ywSAufna9brdV4fx2PLZBQoYCoxAsKGQ06+PiVSCljv8VWF856m8bgUiNse6w2xrsCD9Zp+IYqjjwXIFdhuNvi+JyVdL7puQwgd6/MN264nEQmpxswanNM0Oc6wYzwodVOqwqKsC0Q9CBkRTLKaR/YNjNl72ctevj0kbGu+8Mu/l0dfu8Xi5eu8PzY73wvCfXufU3PGnTtP8/DhLc7O3t5oYwH+XvcuvhiP+TfrV/kj9Wv75WYve9nLXvbybSeLKPz4nZ6HjeVTtzz3ZvvNai97+W6WgdG42PbS6GhTkoAp7OGi9278aHDsTpES5YILf1+26pTSS8DZEzCA7MR3tqQ1mdThjVEnFwq7WHJ+9gUgxOQ/g8ux/LVrQzaTa8dGKWb3FNNgdx5SCUip89TyPn341Lo6Okan4I0SSGizrRVrwWZGkeIPNQXoMlat2BPbrud0uaWeHzACKzQIqnIGcYZu2vdSrNpPNuUk9kzrPGGF1meO/TqkA5m06LTQ0rcDW0IOdNxpo51fp2WMYxdj0ZTmcdfXkdk5kgg2jf0ydRsMac9LwFjxCySHiM3YEmWW7kNgve7o+57NZk3XbfDe0jQVlUOxCwih63jpX3yae1/4MvOZx3tLu24JbeDk/kMg8eyHP8CN97ybp557lqOjI9btlm61RpKmNqm8pWl8BnOkoT+t99RXriB9D8aSktB2Paltsx08M1+I4JzF2jGdspFdvnZnLd5Z7vzrL/Hw1Xs8/aHv5akPvE9TaWdbsq989gvsGOSUZTuznYhoKpsYwuAZ6ftI14UcvKWpNnScjBGyit2RbGvWdDqZpz2Ptez0z/ZAAUJm/nUOfBd1KkwdJ6X/npj6IzBIUrZRD8FomQU45fnkzcgIYcwwbko6nrEF9a/1NnJy2uVhmetsDE1luXG1GsAeMcH5KhID9CUjSgZmWKP+svnc4StLXWtK6rW3uR/1p2sDfUhs28S2y+Mb9Q/YBKu2QxDWq5aXX7yH846+33B6uiJF5cF3zpFi4rVX73B6Ome9Ulbxw8YTNhvOTk45Ozmh7/vdOSc7S+VOmz4xPfM4EUka1GodximQxUgihYSxyvphLRibg3uxk/TfidAHbCzMPkYZz1MOvA3q+/C1A++0HMY077s25PKT1zfJDPdm/FJSmgDz9vryXvayl9++fANAj0RJPSJ5QSqoMxnQcsOelPe68ttEkSwUb/nvqTa5a7TOi93rLHoCQ0pBmdwzovhKGWOc96gbXzwMjGWWu578ZlLjSUV3gSH5fjOWVPbp/PbjtUX5zEqBOg8jYm1O72B2X3u6kV3QeUrZmi7CjC9rxlcdlHTnwDrEOpRJwJBEiCSkeMaHd1Nn6Wbb8eh0zWrT5yppn1gDlbf4srsNFZygeWVsOcmdNhw5LmzcAwuHAZs0J54eDKf0eeNBpYBhDMp+YHJ6ISn9YibHvCnPYnlw7hwFjNhxWOTxU0AcktKwSe+cPYcNWwYWB8UVGRAHyWaaL4ixp+96zpct6/WW1WqJxJ6maRCpqJ3BW33XRMJZryk5HDQusTKZ3hJRpHJ+bjNruHrtCufbNSkFhIQxQl07Dg5nqkxkppiEYCrP7Pp16kZTf6QkbNuW7bbN7TxoI/jiPC9K+vD6+ptzhiorfyIy5LpTBV0R3lXtcd7tnpFFiCHk3IpAgj70ODsi8bsuZtRtVtJFDx8F6GG9AnxSVAW+7yN9DEp6YfV5JR1KknHM9FHo+p5ma3FtxMXyNpNTpJ128vhr7PO46I1WK/SQEqmNSExI0OrKgYPaYWowbhyXJf+eSqEqNJyervnKC4+JOQ2TGD343rxW89xtQ6pVbdxsIq99bclyHXl41mcQUV5zrcE6w+1nGg4PPc9cbziae+raZSVdASGPHm45Odly72HP3Yf9AD45Pj7g+s1jlpsWETg/W/NbX3iZPmx5dPoqjx6tSH3CGovzjhgDL3z1JU5OHoMPXLmywL/rGoeNp1tvWZ6v6bouz7TpgjUyvAzz/aI2nOdWWdNAsE4PhHVlIRgkRBLa/8YYrNN9KCWrDCuDkp5ZdVwFxhBioO87uralazv8zGI8zGqPWAEruJK6qoybPCYLdWNZYFKM2osZrZ3RJJewPO1lL3v5dpLYe1793Pdy70vvoQZuX/heEFZmxZk55/zsCq+9+uyTxr/fcTF8JlznM+Eaz7slf4TX3sa67GUve9nLXvZyuTQJfvAsce4T//Kq497s7a7R2yX5hPltwAi2l728XTKmbM72gCQDS+rgzBx/nWjau/bawYkPu3a9S5grJneN9tTBGbgbxDe5crBRDI+XiyW/3lx+vVLfQOTiH2bnvczwn2xL2XnN3BjZJjEG2L1RDSYvM7Hbqjlm+nyZXCODrVWd33Zg8y4gj/RkoaMdJkQ22y5H/U+t/oKzmnZ8t8oTY+sTNnYZwTmZFWRYW4v9qLgPKKlU5BIbMmqvKf8bnOmlbG1bM1Tl4tia2tjNMChNcdyWthHZtXFdLEPG+g3vJvklxAz3iijrRdsF+k7tWCH0OGfw3uKMMsyCEFPk4QsvY4xh0Sgjw3rV0XcRKg/Oc/zUbZ79ge/jeDFjPp/RxR6ZJLp3zlLV6iKSkoYdwFn8fE5yyn4iAiEGTJgE9OU6K3jLjukszJDUBMhBms5yeucu2xe/xsG1qzz1wfdlX4UGDjpnMW7CWJH7IqU0HRIkUcaYYofWNOS5fY2AifldtJ4aszr6tFJKREl4AyWd0kXCeVAG55giPhhMBgAM1Rpe7XIbcsr2Q4n5QjX6IiGNnwtQG43YdWpXn7I9jy6xYkOG7Tbw+HTLSARhEAuLmeP4kIEFue+F5VlH1yfWbcr1yeM825EPDh11bTlcOBrvcC4H0uY6bDaB7SawWieWmzgAE5qmZr5oaPuACHRtz6MHZ+Bg056zWXdIzOuINSRJnDw+Zbvdgk3MZh57NEfaLZv1ms16TYxlVSl9WN6dcc5ctCEP8z3P/PydsUbt185ANDCkncpgMR0VSJoC2DKgSEQZUYzWOyUFFcUYsckQo+CtRXwe42Zakwt1Gsbs+PfQp8OXe11xL3vZy7dG3jzQI2bHm1HnZuhbjFE0nzHZoWlG5+qwUBWN3eTNJH/4+svZroo/VZsvKuBjGRcgAGa84wlU8PDJqLQOCtZOzfLVk3PIk8jBEZk7MH0MnsFMaydopH92tI5Kn26wkstOKRFDgkrzsdmJYjnuC7nuWWlJbBFps7M7gUv5GU4V37xxGNFMmCIGSYnQ9/RtR+gCoQ8k78DJsEEVRR6str4B7w3OZYR7UbKNKoK+sgPYISZDTFnBHfrajA25s5FdOD2ZArAQlJe85EpTVoYYJQPJ870Zl5Kx5phMOWZE2R5sVtZSStodA+xW2/8iOGn8hhG8kR3NZkhRY0cwgbX0MZFE07FI7Og3S2I0tFvo26ycJ6HrWtp2w/r8nO12S2Vq2pT4zRdeZdNuoXIcXTlUx7w3HB/W1FWFIxFCIlhLqCo9dPQ97aZn2wbi1UN8VXH95nVMY9mut6zPVmzbnvPlRpliEnrQ2vQ0zQw/W+DrGsUvR1LqkNTm8S0Z2VzaOY9uA0eHC+q64uBgTl1XrM7POV1taLuOgtwHoPK4qsI4OzjzTU5ZosxvQrvZ5FGgAJsUElIJVeVoZhVNM6NuPF0XkWTpe5Md9zEjyLeEGJCgIJQ+RSKJq3M4nFmknmGuNsisIswqBIvHwmqJOXmI8ZbteUc1s1SVm2A7BJPR1tPERpKEuIlKDtTPIFmMZO4Q7zCVxWRKvJjOSV2LyUhviYoeD/kgbU3Jl6g/MUKKdjgEDGfekrZUhllE5Q21H6MmFIGccwNGePygY3UWqAz0IXJ8UDGvHSYfCtpWx822DbRtGNa7qqlYtx19CFqnsGF19jLL5ZavfPUeq3VP1/YIhn67ZRUjX/rXX6aZ17z28DWODhtO33eV40WFJD14nC/PhtV3ys60c9AzRcudSF4jYoy0bYdYQ5OmJVkkA7OGPLWDYq7tppca6vkMX1V0/Zir0RjLs+96iqqpqecVrvbMmpqmqngUDGHZESXq3JdptcpmYClAHZsPqtbpYdYao/SGe7DHXvbyjpYb6QZzWXD9xgEfqbd86aHnS490jd/LXvayl73sZS97eSNptw2/9VvfyyvxgK5rvv4Ne9nLd6KUAKps2EgpZJufOvAGW9yI4tj5p3jc1fz3Rjr47neDX3Bw4k8Nubs25p0SpgF9OyWVv8x43cSuebFmw/PLH7vFXHiVzOdRkArZhmxEKEajYq+eGIbzPzI4bgc2jws25NForvZeIQAxZy3OlTMg2J17dlpOMqN3SKSYg+GM1TxdZmrTMTttaG0OdpraRozN9hOT7eE50l0mrBcT+//uL9M/im0mgz4m3tNiQxbU0T6MsdIPUw99CVod2pDc5hNHQGm/bOsfXvWJ6o0MKeM3+arsOBejaZuLjU8kkkJHSoYYQLONJyTl9MMxqO0+BCzK+PHg5JxHj0/BWepZrcAIC02tKUwsOQ2yMaQSxRQjX/tXv8njO/f50O/+QY4/9oPMF3OMM/R9eUai6/rBBplSog9qj7a+UqAWguRAPETTTkwBRwqAKW0HTVXhnDIM28yc0nY9MUaGYNVs/7fWQfaZqA3ZDGZ/BGI/pmLHCBKF2eEh3/fx389s3nBwfIxznhgTiCHmcZEyeCDEnBonaU/FDDybeai9QZyHmUO8I3n1hVgMdB1muwFrCG3E+ZJam2Fej2NhakAE6XPQaPQgBiOFAiLbQ72WI9IhMY7OiQxWSWNTwiS+Vv0mhingwYxZgQaQk0Ft0s5ObMhDn+k6s1lD12qq+tQITeWoXJnLRv0RUX/iJJWRc5E+RGJS1pGUerr2lCjw+PGKrldWGjCkEOiT8PD+I1zlOF+f09Se7bUZdFteu/Ma9+7do+u2XCoytMLlNuRyWcrPNAa3s25MHT+XMPgM66TBeY91lhjLOqDtcHR0iPUOV+ka5r3HW8s6QerjkFlg7DEz9Me4YOR1pqwH+WprzW599rKXvezlm5Q3DfRIeUFPedcIoctozTQgAY29yOpRVM1JnsBBUdJ/dt3+E9q3iR5WVNVRXZInl8CJFmgnnvsBVDEpeFTTc74zQ0YET2sz6u7C5KtByjW7SmhBAg5KeiovMeyou2APihIlig50lgHAmXfhC6qsto1JCD1JelWORDc8ya0zbaHh1TNwIcVIDPqTYkRcBjMgeugwRlk/MghGU3KoclDqlgSw4PMmV94rJVXSdw4YMjmclDpNtOIBpV7KEJmQp+k9KSX6mPBYrIOC7hzPhKoYGlRZMTKmWZHiJC5K/qSFijK/oyfsKD/6HGvHPjHWIF4RszEVB7IgKRC7NSFW9Nua0GU1WCIh9PRdx3azpu96auMhOV65+5DldsPTN+bM6wqLUsEdLCrms5rtuiV0iWQdqTKawy1Eural3XRITPjKc3R0SHPYsF1vWR2uePTwhJPTZe4Pdfpvty19H3F1g6srYt9ruh/pEQmQJswyaF5Gk1lEjIHZouFgMedgMaOuPMvzc1bbli7EzO6T1SVjsM5jjB2BMujYsVaV7b5tNbejV8OXJM35qVR9jqqu8FVF37dKnhE1H2DfW0JInJ13tG2b894lohGSgZn1zHxCfI09rJFZTZw34Cusr/C1x7RLokt0m6hzRsZDbWEtGkZeyamYhNhFUg/0FiRTGhqDrebgK0xV6UBZ9kjYQjTj2EDI2T5wzuTcfAqmkZSV9JifajLqeaqo5xpVTun0xnWjDFm9YnnaY53h6NhhPDTeUhmTgR6ahqfvI30fCX0c5lzX9bR9oA8xAz22bFb3OTvZcueVR3Sd0KfC3CRs+56vrVYYb7lzepfDA89se41rhxXG1fQB1ps15aC9sxaBHnKmnz0ZMqMAqb7HVZ5xGS9r9mTyl6XUmAEcU7aaqqnwdU2fekVmZ6DH9ZtXuXrtCtZbpYl0Hmctm5MVpyZHIBSoz3RJpxgqRqOA9RMQH8o+ssvluJe97OVtFbn45xsfpA2GK3KFK3KFZ45BjnpWneVLj97aan6zclE93ZsIvvvkIpZ6jzXcy1728nbJE3aLJ2woRS4cvi/9/J0rXV/z2sNnuZMO3u6q7IWJbU3/+obu3e+t37wMKVrVakxKMfsO1R6n6S+YOM2zq3jiHx+swjsfTi3F03+zTO59cgm6cG3+bJe1WcbrMoBgwBEUZ+PErjw+dIfD+ZKRZsbqXnZnsYkISGmjgcFi920KQEIyy8G0/aZP3/V1ZhuHRKSwJttLreuTtxjbZGA7ToK4S940d2buxQFgUUw3abCtqu9geK+JvWvnqTs25MlzyufTfpYSmGfG9k1CFE3N4TLQZeyJYtuyo68if6Z12h05pTXH3menvKFeE5DHNHWzAWRgHJ4GfyZS7EnJEYMjxQJLUhaBFAMh9KQYcUbTpZ8tN5wu1xwuKipXAQlrjKZs9o7QB2IUxFh9pigr9IMXX6b/8gs89fQt7O/+KI2t8bUndD1dXbPZbNi23dAnMSVC0DTe1jlwTgEailxAAVz5NXIa+RLgV2aHrxxVVVFXflhD+xCIGe0yMEpDHhOT+Sd5/GSkR4wh+yZ8fqZQz2fc/F0fYTavaA4WWOdIyWYWhmzfTmqX3XbKyjAA0Iy2tccoS7l1mNqB96TKgdHUH9Y5iB1ihdgnZXqYTmJzwYac318BUpkVOBo0TbeuAcZ7sB6Tg8SkS0gMmFTGib7/EAtowIqy1ajNutg9y9idrJ3jrAAEZwzRjPWbDm0RBXkYA02jbe2t0bGW3ybFRIwyprTPJceoII9U1vkU6LsVXYDzsw0pZr9Rnl+SEmenHcYaltuVpooJc0zf8ujxI05OT+hDmL7AOM133Ijmiak3dIdoPY2dBu3lBWi6iU+WeMYhqDZ6r30eJSExj01jmB80zObzwe9p89rRbzvasiaUwnaM4PlvKTZkRtaWAfS4Dxbcy1728q2RNw30eHj/kTorMxgBoG4a+uIFd05z20lGZqKK4IBMS1Owx3TdmyjrSXIamMmDLzMODJvd7kIYM8LUF1RuflBBzU75RMoiPCrMTz5I190LKvqgbBZFsOSuMyN4gElQ+eRqJvpAVs3H9DMpkkLQdhTo+kDsw7CpmeygVOU65jQFW1Jq6WMkpKibUwEukO/JyOypSqu0e0ph5Z0hZiShqgzZuW9l0JGNNVS1V9R1iYrPVyfnNbp+iiSfbKKC0IXAvQcPSTHx9O3rzJp6AH4UYMfZas2m62g3W/qu56lbN7h69crQeA8fnfPa/cfcvH7Ms7evo2jYcQO11lBXXps4Uym4qkJpA7MyZ9KAWk2im6k1dtiod0BIBqIkQlFktZOBxOp8w3K74fz0PKdmkQniuVdWEyrldIlKBdZHoY+R2G1JIVHNj6iNp6kqQt9ReZfp9wRvoalnzJoFlT8iieHgKoQIv/XlF7hz5wGVd1TOUVVQVYa7d0746it36LuOfrul74KmITQG76wib3M/pxiJvSG2LU6Ep566Td8HfEY/371zl67tqCoHBrZbZdzotj3OWFJMOOfoQ8R7j7XT0Q7Oe+p5gwVCH/OzhZxqclgbFAiiLDMD844oM0jXdhgjKKjbEOKEJcZkGtyUKeWwVC4vQwKxC6SkqTosiuRNGJL1uPkB1a2naNsl2/OHOCsgPqfFYXDWi0CfD1l2ujZZQyrgjKhUgHRn+vZZWRNZIURsowexbQ9tbwa2m+MrNzi+8jQxnBPaR+Bi0dLHZUYUFNJHg0tGD6bo8uAc46FoausovyY4fdzTbSMLa5lXlqA4Gur5ITdnNSt7wgN5jGwEWZXMIzK0L+SUTgn6aAka8sGscXzPuxakJHzttS19n+hOO7Z9ott0tJVgTKQPeiAwZdpclDJvd/ytk1UqA0psNkSEGLDREEPAio4/a3WsJECkmk7R/AiDM47Ke44OlW0obbU/urZnvdL8ps4ZSlbF7bYd0jDttm2ONshrx5g0ygxdpywgkGYuH/72spfvHHn55SP+9t/+Xh4+nBPjO2t8ezy3022Oloav/g/H3Jsllg+uvt3V+pbJ/cUVXjm6xY3NGc+f3Xu7q7OXt0FELK+++i7Ozq7y1FN3OD4+e7urtJe97OW7VLYW/tkNz92Z4UGj+vKtdIu5zHeuEzG8IkeA8MEbgXdfiXz5secrjx2XuUf3spdvVj70odf4D//Dv8cXv/g0f+fv/G7atnpT94Xgefnl7+Hhwxs888yrHBys3+KafufJerUBNDCqOHGd83pcL44ta6A4icnneSMMgSE7y8ElhoWph27nswvryOCBnYAFCvhgenWxTxSnqjGT74tdcEwPsislccjrPH8Aq4yOvxEWscsoW+wMg7918P2OsAxlQ8j2SLI9PMWxNqaUI9l+FJEUEAnK+JADBnftHiMX6wiayI1SAl2yTUxvyZbnqR1fjWgD00T2qquDU7K91phJ8xXb/VhAjInlZo0k4ehggfduDB7MdsG27elTVJbqGDk8WDCbzYZ+2WxaztcbFvOGo4PF0LZXnr7Nhz7x+6GusHWV/Rs5lbe1GCQHVE2gNTJhmC3O+tIuE7tcsQvvdLwIXR/oQq+MtTKOHklqG01iGFhVku6RMeU+jZr22voGVzU4p+nTrVVmCYPgK897f/ijXH3qqQwCUB9IjMLn/+d/wctf+C2e+eD7uPXu57n9/udxFlbLLY/Pl6SgAIgUR9CQsQYRDbISyAGBGjRqgcPDQ5qjI03jnYTlckmMEZeZd0MfFWgTEsYUcIiCR6y1gx+lNJy1Fuc9j195lXtf+jKLGzc4fvfzwBhIqqm/1ed0Ea1QGFCKK8Jak/twwt6QG91kgNmwBGE0Fbc4Sq9aHbIkYzFVhT84JIaOvl1jFY2hfvvp2BCIw3Ikw/hW5oYCzsjvHTqgY1zkOh1tXv0cIaE23Mx00zQLmuYQSR0prhmRDsU5pv8kgZjUbm3LDC1TawKq2ZH80XaTiEGojAYXFuYZV9UsKkdvtqzZQA/0jO+kL8nZ/Yf85qf+J/zRVfzNd6MRuppG5spxhQicnevaE9tISJYYIt5ZnvvBj3D87LM8+uXfYPXaY175zOd59PKr3P7g+zm+fWusq5k02YX3L/6/4t1KkhQ4Ex2GNNiYdRwJkn1vF0zxCgyzDltnN1cwhAgxJPquz/POEHMlQh/zE6d7UV7RcwOVwPKdtV0gGfUJWr8HeuxlL3v51sibBno8fnwKIoS+V+XHembzGfOrV/B1nT8zmvcqOyHLXrILnJNBmR1VWCaozaLNMnx/qaI8yEh3FPNzvWOH1WNa1vTDoS5P6udFjy47N6OSK4xbR0ENl312BFlMizWYgZ5vosuOf2TndgwRqVTZjjFCaCn4A2t1s9GCE0hEpCVKR58CIdNlmckzLVbboaRxoejTFowd8t+JASXUsvk7BtRsEj2U+Upp4BQ8IBpXb5TeTKwblIYC9BgPB0KIgbv3H9H3kZvXr2DnCljRjCp68DtdrTldrlmenNGuNyzmc65cOR6GxMnpihdeuoPF8MytG6qglQ3ZaB2rymNS2eUt1jskWaAdQQQwADMwVsftUOdpDxlNp5PicPjT+xOb1ZrHjx6zXvV6QMow25SEEHuSWH0vESQZUjSEJIQYiX2HJPDNnApH4zzBWQV6VBZPxFtDXc1o6gX4GcZWNM7hDHz5t17k/v0Tblw7ZH68oPJQVXB2ds4Xv/SSHgJioK4qFrM51mr+xhDdMBFTTCQTiF2LkcTNGzdIwGw+p+96zv7/7P15rG3Jdd+Hf1bV3vuce++bul+PZDebg0hqiH7WkCiyNYSm40GSZTMBBNuJHMiOARuMDRuxEeTn0AmSCJBgxIHjAISCAInHGPYPlmUpiQyHEhhZQ8iYdizLkjU5pMgmm92v+w13OOfsXVXr98eqql373NvNboo0KfZZ5O377jl7qLlWfdd3rXX/PilG+t7b+M4HhGkMOBHGKSJOCDFZFJV2ggu4ztOvBtIUCOO4CO+WsidAjClH0yhtnmeUak0v5D10A8bg2LU0KmrkBhEbw0OHzXsgjHaoKOlRXMrHYfG49RHD4Al3IbzwPHGYz2WzqqxEVaZAXscSohir2TlKPJiYw1ay3UAIGJ1EkTW4IUfoUMduhNMLSOoI0XHtxsMcXXs74/Y5QtyAuxyerhAKQjKCT5n6Flmn0dHrhJ/nuCqc3g9cnMHjD60I1xNjsOccXz9hfXyL58OIG+8RVdCzHNoxz4vSn9ZXEFQIGWhZDY6nnlwzBeW557aMITGeJrpg5JxxBDQQQj7gNgde8ppRFsiG97eQFkwREqjNwxgdMUWEZCxrFM3RZ8rUtego87Oc83Suo1/bVacvWjtN48R2u2Pwgs+HmJiUcTfO0ExmWNe1Q+c8peUwU/YFzac6xaHimz3sIAf50pDnnrvGc89d+0IX47MSj+fR9CgnFyc8+zPPfKGL8+sQvfKvl9Y3+PlHnuFt9z7J0w9eWFx3gAteH6LqeOGFx7lzJ3FycnogehzkIAf5gsnWCx9+2POxYwP4PY7b6TYP6UOL65LCia4BePOtyG9+amSMkokeBznI507e8pYXeMtbXuD//D+/nB/90d/0qokeKXmee+4NdN3ErVt3D0SPz0K2223GyWIlCXR9T7de47ybvZop0TEb3fUShtx+WJx07Nul5OddiSHPWJ82OIWS0+tewpCbZ0rBgWenwVeWl8ewZ/ismKC1/XO+U/besocho0scJ2oipsZZUCSnsy5YOyiBRCRqwute9NVsLF0QNiqOnQkdbsZO7euM0xWvdSlYChatulSiNqEYplbwEtW9qC72tqSJ8/MNMSZOjtZYmuQmEkOC7TSxHSfGzY4YJvq+Y7Va1bJvdiP37p8hiBE9Mi5+7fbDXH/kYTbbLS++dKeJDiCIy2AboeJA9jit+Js0Y6XA7aV/lLk/2k6dxpHNZss0xdx1pT+0Rp6tqKhKxZ5SjsitCq7r8F1PJw4vYmlanDm39X3HU1/1lbzxne8A14EYGYSUePb//TV+8Z/8HLfe8CRv/81fz+3bt/Be2I07XnzxfrbhJLxz9F1vJAEnRrAo/Z8jKadoTpTHR0ccXb9G13WkGNnttqgmnJ8tAalEVxBz/iuphix6QUuGAZzgvOfBp1/gV37mH/H4l7+D6296mho5tzi6KZj1QpsfILdTErKzoI216rgrs8FdnFjK5RyIV7A02KpaYTwjJAngEN/jjxxpA+n8nOTnqdHOT7NtLO1MrqxvuTwpt0MGTPPMUuhAvBjO7YUQld1khICkwrA6oh9uE8MZSSeQJvJFM1+VGccVl9cXl/l0e+Vt71csssc0wclRR1qZ019KFiV51R9xngISM5VtYu6TXITzl+7xL//vf8y1J5/mDb/5aVxv5sbOCzeud8QEZ2eTRQfZRVwyG1i/9jz+zi/j1sWWn/tH/xJ99g7P/dKvggjHDz/EjccfvaLQTU0WJI/SEDPRIxlKm51EoQm7P/9u9hJx5hDsO/t7zGMiRnMi9iKkBpOPMVBpYDJj3+WZbZu3O5mipgxnG4M0K+BBDnKQg3y28qqJHojPS1RoP8y7hoW5UicWbcIIjtnjXCoJYqm1t2ocs6FysbZdrZxrUVLLplLIFi+nbJcdTcqmu/fuZstTjEGpMn++v+TO95SDCRQ38qJIlKgm9hkWfQKyJVLrQcbKnb3nQ8Sr0jvz/J+SGFu3c3hnilpS221LqDknQue8GaELq1qzEpZyaha1H6Fj5nXmjSWzJaSQcxQjS8SSA0E4unbC40+9gRsP3bLULZnwYE3QNWNDczuk2sXGIk5cXEyM00QIcSZaMB8knPOWkw9XFdu60Qo5NZCbx5NSywcOJ56+HyBHWQghcOfFBwjK4GVxYInJ6upF0PxeEV/7qjw1xsg0TTkcYj4saj7gSEMQycpb5z1HR2umIGzHDbAzxTEl0rgh7rZM44YpJO7eu0NMiUcfPuHWjY719cGU4mmXlZCOhLOoETERtxOkyBueeIzV6oSHHlpx43pP36+4d7plN050zhS6mDW1pAliPsqFWGdPJKG7iQcf/yTbceT5GElAPwykGNlsRsbJ8jMmTdZnqOVSTJHVeo3vOmJUQphDtRVJIRK3IynG2t/OuTpfjcFdujCzxnPfTGNkGgOkDY5I7+2goWtvQzJ6UoRO1oxjSXOk5Ih3pF0kjRHRRFcCDXUO6T1+1SEhoVM+fI0JDWW8zWUw4ofQezLz1hRuRBEP/fEadCCMO+uf46M8JgNoJE7npLgj69VsLibu3Q1YihjHp/QTXJzvEHeOl3ucnV7sqX+5p1JiHCPeqaVrKYeRmbNjBzsv3LpuUU3u3ovsxnzQT7DdRs5OJ+6fRs42ieHafbrjyEv3L5ALRcbmcJ/nXG2HNIeVFJql3imdU44GQaOwi5rnuRGCigfEfBBjsTaR57+laJrX8VnZNgKdc0Lf93Rdh3eW7CZMAZVI58B5wa96vHN5D0g4sZ9yTI4hEKaJbhDEdXXeonZYTTlNTkwpH2RmomLKY1M1k7gmmwtTnPKhOmv8CUKMnF9YGMLVlKrH0kEOcpCDfG5E+eb+eb6me4l/o38RsEgez508zJ3jmwC8tL7OP3vsLVXfvDFe8PSD5/FXee4c5CAHOchBDvJ5EI/nsfQ4MRmJw6ljnQkdrQjw9ocDJ73y1I146fuDHOQgXwriUCkYGrREjQowSIOXFsNYwfwWR+rl+bpAzAuPOmn/sURwC4Zcn9SQLT7jyX3hvbiHOmsu7x6e83IUk8WXBSLO+FMpZyWxSI5i3DiezbeVNNUpp622miQVcObMUvBizRh0TVeCEUBcE4m5PN6ihBS8OiE5lun83hlDntuvgnv1424YOLlxndXRurm73JMjRbT1as4rFo1CmaZEjNEizy7IE2a4b7HYgum1bXwp3W/9R8Z0EbzrKJ5CKSUuNuaE1eVBUnHLbMAvDqUlejYaF/bilAoxI9ssquV3bvt5dFo/dH1HSkKIE2jIkU9yJI9g6VtiUrbbC8Zpy/HRgN6+ydO/6cs5unEdiQHfeU4efshoA7m/pzCiKfG23/SvcXzjJm/6yrfxxBsexTvPdgzmuCc6Z/9gNj6nHHm5tFjC7BW7+2f4ruf07ILY9TjvUU1MU8x4YKiEDqASPHzX1a5OSXnkzW/i+uOP8/DTbwTgpV97lk98+nle+sSzxJi4/9zz/OpPf7j238lDt3jiHW9DOj+Pm1zumFOLoAFBqzNinwT1DvU2dhwdMc52gRJdWIOl6BA0pxunkl1cl6OXx7yGRHPm3DdV5R62DM5tg4LhuH0H6pGY05v3fUM6sPQ9mgJlJZimxHZjhARFONUHTGMEGXGyZRyn5TtKKVSJMdcjV9RJXWpzcSxFy3owfHmztXvy8kuYEuNO2O4SY1D8sMP1ymYbkEnReMVqnNfeQmKabXXzjxPDtdUVJ22LumL+gfM9i32iNG550yVcY8aQDUc2R1CXyRqCkWuQvEaKIN4bsS8/3Dg483NTjKSMs1uk5nnGFqJZsUeWqCdle6kpfNTGS4rZ0VVjJROWdrZU5RGRiI+LpfggBznIQT5reQ1Ej8yglbEqU4ixIbP1z5hoOue000wgWHo3v9zqJXVz+IxSXbbLc4uqu3/d/Kx9osb+tS31w8geTZGuekj5Oxv7jAzQRihI9VlWFK0KbFG8ykMUIx+EGBky0UNxJHV4PL7r8M7yxqWU0GCbhCMzUcVZSg1K1IOUI2ZEYwcnM0A7OmNUk0NQZeJLUQgK2YOkSEw1BcLx9Ws8/vQbuPnwrazEl41UQHo0Ez00kzxECtHDlPeY4OJiZLebCHGPGFAUZedxvgMcKStOQqN0CogvRtrcjoBoJno4z9APJAlInBgz0cM5x6MPXaPzfq57NuY67/H5XjPaLju4ED3mFBSSo3s4RCw9g2uUde89R0crZBeAc2CHeCAk4rgljBumccNuDOyCRcV49PYJzp0QvDcG8MYbkUd6iwwSA6qJcXNKnHa88ck38I4ve5gbtxwn14WPf+JFPv7sS+zGid7n8G5tPcUM/jHE2mYRJey23P/4s5xvd3zaeSYR+t6U5s12IkyJ7XZLipGi2OzGkWkSxPcMzhMy0aONoIAKGiJxYykwoqacwsnNawIAFuIvTKkOA4BpsjZHNwiRvuvx3uHFo0mQfJBar9aE0GViWaxz7GJKbIMRBTqX8J0gnaPrPW7oiBKZMltbRyN9FPZ8c7pBsLRG5W8VO7SgQrc6QmSNbB2aIm51jLgOkh3Mti8G4tnOQsKpcnExcfelbV4uHKf3z/jUsx/n+Fi4cdNxdtY0YHtY0MRuingP68GISM5bRI9ysfNC3wuP3u5Yr4TNJrEbM4NbYXMROOvh+RdGXrof4FjhaAfTBgmKTGUKal3DSkQNTVrrAJpD1BnRA6cc9YIGYYy2boRoP46ZTKVV6W/qlcheA0XBt7qUnKqS9wHnssdP19sBHEtp1btIGjAAY9UZ0cOYGziJOIkzqStMhMmhus45FF19PpoyiV6JSWuElsXhJA+JlGysh5AIKaB0ODcARgjZTpE7pxtUleF8s4xyc5CDHOQgv04R4N8aPs33rH/F/hZ4/vgWP/vYWykf3F1f5+76er3njad3eOPpHbweDGgHOchBDnKQfzXi1fNEfJwu3njF60TgHbcD77gdXvG6gxzkIL+BRcztWSXO5+NsZKx5E0Sw1C3ZsepVkDyWn+srX1K/LNFGlyyLPZPs0j7b/OMqDLnUp9y2Z558hXJJfmZbhtlYWb2+G+fASywGSsQH+9yLWLTWjE6aV3ohekiOpFBgWqk4Zi1BcUaseHUhhyxbbNlWrQUWcxjMH/XDwLVM9CjPn4vvG8uzZtKGzhhyBuCmMRIq0eOqNnQ5OsRM8hB0UcYl2aM1JFsbee+z4d6iTphDlnB8NOClEEIsWgpojmROjgydLvWv4d9GlqnQdW1Fi2QhzXPFOfquI8SEpfKINj9yypYUJ2KcjMyQEuO45eS4Z+Vv8s7f/G9w48nH0WkCVYbVsc2jjHfHMKIx8GVf+9V85b/5DazWwrAS7j+44MGDjaVaEUhCTUPRGqpTSgsCSIwTuwcPEO84Pz0jdl3G0ZUpOwCGYGlmSjuHGC14Rx6PFoEGHn3rW3jT1/1/6nUvfewTfPSnP5TbK3Hvuee58+xztTyPfdmbefztb8FLN9sTcrOmqBm3noCEF2+Oon2JzmKeyJ3vSDkUgzYg9hSVkKMRuxwtHGdOt+IdiYIbgkazlzRJOOr4hzayvC0axXnMdT3QWSQPTUjX5/XR5ppenKI5WopSiB6hjuFxO3J2ep++F1YrYRyvtpupKiEpkqh49pLPZeuvd8LJsaPzwjQFYpNNPITEuIPzi8hmm6AH+gAx2DIa53WgYKbVNbp19qOQsYxI4QR6b5MiBvs+qTkAis5OhlyBIWcWRSZU6GIqSxN5ZnYizmsDOVq+S1hmHiPvSLMmiCV6n9e5TNai7/MaM2PUoDkgSCZ5VNyb2nd1SCRqBPikCbMjuaafEhfjBAp+OujCB5nl137tAXfubD6v73jkkSPe9KZXPqt9Mcj3fM/3cOvWLf7iX/yLV37/bd/2bXznd34n733ve1/xOR/84Ad5z3vew7179z73hfwik1dN9Oi6HtVECjnvYBhJk7EbBcC5HHFhVg6KtmtM4LIRUj5cSiFC5AW0spqzsjdfB0bwaEyzC4ZseXxVcYvKUh9RlL3KPJZWcZTFr+LNPmvt7QamleW6PGBIrY7dYopEidwBtuGnlGrYMNWUN7aiVFuKgho5orxC5+OAbXBGsCg/OfxFPjcVhrMRcMYwAoHdLuJcypsr1ORyZQPO3vIWBs7ROU8/DHjf5XxmGDNZBN95vM+5dDPrN0WtRmKRmY4jkt+V61L61zk4OV7hvOPi/inn5M27qE+ZhLBe93S9b74rP1ltrrkelxFTykEq5V1XaodK/dtubdMKWf9VHbJRHPp1z9H1I8aocLaz0iZTbGMSppDYbbdM446UEiEqF9vEbkz0g7eoEENvz8xttD4+QZwnDkdoSnTDCnGOe6cP2Gw27DYbpinw0tlz9P39qqQ/ON1werbl9PSc3WasYy6EWFOm1IgFMeYIIZnMY3RqpikyAmFnYyqMMSv1e5O0NE0eo04E33XIGBYXOUxxLOxVO69L6QbAkgRZ0o18YCrkMZo5nZS0Daiz5xhxzMIKEkvUhtKXdjjUZKxZlRxZJkToEnGaSLsdIeyYxpEYgkWv0VKf8u6ZfV6XnaxMIqb07e7dheCJcQQSbjjFdR6IoIkkIxyJ5VcEblzrSI+v8L7DdT0pRmKMDAOs17DbBNAJ56DrjBw1BSPobLYBJ8q1I8vXaWSFVBVN88YQ1quOkyPH0E10kgi5aaIKkwo3bg4cXetJrid65fwBnF9oTSI5H+Skro8xltCD5HlqawJqc/Zo7UiqnE3WfymTPbxQc5o2Hbo3lC57vbTDTBXCFLg437BKSr9e51RTflaO68VkOj44n3A+jw1VpimCi5yguHy4aD0/lmVsIQyq90b7Ik2JOEVjcVcgJjHtApuNpXLa+sVJ6iAHOcgXSDrteDg9zFrX9PrqwnR/cYtevbS0CkojZ8MR/+L209zYXfDG0zt0C1bmQQ5ykIMc5CC/fil77aNR6flU/fzVhKBeQDxXHwv+lUhC+MnxMc6149/s7/CvdfcuXfPxI+GXrnue3CS+/DRVfOOFQfi5m54bk/LV9yPDF7AeBznIF5tUZ5+UMeQU0ShmLPSQAUi7WAt4rAU4pOI85GtnqO5lMIbGPih7XzQ4b4aA898y/zs/Ybl6acZIcnF18c2VYriVcHkZ1Pp9U71a4L1iGBYtc7Tj6owic/qY2XteDddqcPDGGrt8XXHIKT8y11vm/wAQUwQSMeTUywXnKQ8Uankqd4ccMcRnh7pCHsg4bEn/UqurJRIAFUMukK3s92PF/JWh73BOmHYj07LpAMO0u84bhsWMD1fMt8EpKYb8BrNse8ywob0OrX/ONy7s3KUpUXzv6bUjqsJYHNVSjQoQM0kihlA/m0LG17zh+857Qu9qNJahH1gPa9T32ZGxQ0TY7iamMBGnQEyRbjzD+R1dR07ZMpnz4W4iTLNDQErkqBK5lbJ9QgsoWIA6tegeMURSQXVLSpJLdp7cTnleP/rWN9MNAzefeLxpwBJVQUi5TVpMDmBz/wG/9pF/ytFDt3jkLW/Gd76M2Nm8VKZBTGjaixhDqrarebS384p8vWHNOCOPiARSijmyTJrtMs0csGbJTy0LxKIplLDZgLrspKhI2Jn9rDgIS4ReIKcXWQ0OveYN/3Xe7A2qlt68MzIGGnOkDMk4dsFRzfakXR7pxfbVYMgi0HlH31v0H4eNObObCBFhtfL0g0fFkQSmHYxTU7G69lAn7MKMkOdvWc5FMt6N4GIeY7ncjua+Om6Wi+1ifb9KVEkxMTHhVXFdByKXnXpbM4KAOJ0j8GNELaKjjst6+byHXPHy+tXsrDxj7RqVVMmGtv7GkAhTyk6TB/z4ICa/9msPeOc7/zLb7efXWWu99vziL37PZyR77HY7/vgf/+N84AMf4M6dO7zxjW/kP/lP/hP+8B/+w5/X8r1a+dEf/dEvdBG+6OQ1ED0GVCPBWXiyFHbEUfPmYpZyaRdQXapGi12wUFv3tO+Sx0yrAlc2DVlcVRRPzc8rypfLEUYuL8Rq5Nm60cwa43x0aDasPbB8oaiVUmeSRyF6SK1wKdesOBSNL+uOxlpMlovPISQnGFEjEz1SQDTiFszCJjedzOGeChtVNc3vy8q5hauydChJHeO4JQWl9wGPheeyvHvWf7WFS1oE54zo0fU1XUdKOW+dGAO6672FM8NVxVwzg9kUKW0YpGVsNApdLuv1a8ccHyfufPrF2mrtVt73nuPjlSka7aEk/xhb3YG40pJVyZ7PjuVgJIsuNuWoHR/MCk4qVBKKDslq3XOtv8ZmF+pzUyZ6hOiYpsRmc85utyWlxBQSpxeRzaisjjwrFY6PelDh4tzIOTdPbtD3A2POsTlNO0IYuXv/AS/evcdmG3Lowrv5XaBJGFYdq1XHvXtn7M53dpjqO2KMjOPMAC6Ka8qpYCQqThOkyG4zsU3lYNgM/2aOzh8VUouRlLx4ZA4xUZU5L0KQzMrFCAqFLGHxaqgHUS0vlWbu5PeEzYSQSsYcIKciwsgmNc9nUZDVxnWJLKMhoiFgYSwhxIlxHAlTQFI5iWmd/prnps2DEgNmjkyhGtneeYG0NVYwAm6luA5Typ2QVj0ce4v3qPDQzY6bNzzd6hg/HBHGkXG7tbmhiYszazjv4GglhGhkoRiV842FbozJ6iqSyRZNg4sIJ0cD16951v2W3kGybiYojCo8dHvg2nHHOCamMfHJi8pRqop3iglRl/tTCKEJ4YetCcXxwgkcH1m/372wsRCSRZQBY9Vbk5XTVlF8Z1W5PR8tJI/VcQzsNhMpwdG1gHQ9rveISyW9arvCgoDvEj6mfMBSdlMgZqa8dy6HMGyWPKkjcFGQAlCUMV8u0JQIOwuvl1IOlyjKbhu4uBiZoq3zB6LHQQ7yhZdee94Y38iayyHjXw9yf3XCP33sbTxxfpcnzu/SxQPR4yAHOchBDvK5lbLXPhqVQe+wTPP7G0MU+PvjG/kH4xv5/5787JVEj1+95vm7b+z5xhcj7zwd6+fPrYUfeUPPM+eJd55GhkMQrYMcpIpzFjE2ZcBBUzScoKZ6Xhr8KzbRYKiXjGpXgQf1V4P/XiJaNFiktB75VKeR5qrlHxXCaJ8pFeNYXqzza/a/VcMeilFRav3cfKvQGDhnY3VJyVEcCEt05oqbaonvPKOpjVW6wdpKMee7m4anTS6iKpaKI2HpcYsXe8WQm3ZrHA0thYWj6zrEuQZWzOlkvMupbqVGEagRsKtc6uhFfwjCaujpteP89OJKDNl7R997fOea7xqMs2I+2YmypGSQubvbdlpgyMxNIE25Cqa4X/Cuc6gbmApgVvBqNdw5RSVMU019EpOymxIhgu8Fr46+d6TBiCtOHKt+xfHqyKLkYhGIU4psdjsuNhtCxhRVtwsyTUkPv92OxCnWNOlJ08JZUMs4KR6QOcVGIXpMY6it3lpsFt2V27A0ypNf8Xae/PIvY5oCYQpUAFlsFiSpsPTCOev8xbv80j/8GR5++ikeeuqNuM7POH99m70nTREzAJWSmIWgED7K/LGhYHenHMnY/GQtn0heqSz1RoyWAqSZP8gcSUargWa5DiBmIwkXF2jIYZeFHNSm2CYE7VwmetitRyvHeiW4rsf57CwYrL1FlWnMvSRG/Eg6R0sZp2R2EZ2pSUt40tq17z2rwdH5kFM/1W4mKhwddwy91BTdp1PmKM3LRY1oUdbxlO0ZdQXL4Gvpyb4XwCGTkVRSmp1r53mznKfzYJox5EuSceUYLQpzr9APCXHmKFgIOO2T69Mz0aNcE2NCiaBdTrcy24jmMbdXvqaMssC485gMqdoTykUx5JRHjTP3QQ5y587m807yANhuI3fubD4j0SOEwJNPPskHPvAB3vrWt/KhD32Ib/u2b+Opp57id/yO3/F5L+dBXru4z3yJybWTnmsnK249fIOHb9/iodu3uPXQzRyZoIT0l7rx769RMyljjnahWhbIQnJolU2qotTG5dhXlgWq4Xn5vtmAt0gnoyVqxhz1obxXs415vjstFcbW4KfUe8mG/pgSSSNJAzEFQpjsZxqNnRvt7xgDIQRTbkLIzN1U89cBOO/oB0/fezoveKvoXv2alpA5SghlQ88XpRwkxPuOvh8yo7E8yMJIxTS/W6T0ZUI0IprwktXfFO2AkY9GXiyFTIyRECLTbjKFLbMnypZew11VJa8pfatIt581WrNzjr63NA2z1lDusQ98DtGlUnI+znRSaZ+ZX9/ebkO2UU/z+CjhELUeRI1B3eFwOo/lVMdXJMbAOE2M08gUdkxhwxguGINF5RhD4GKz4+xiw/2z+9w7vce9B/e5e/8+n37+BT75qef4xLOf4uOf+DT375+z206QhM51nBytuXn9hEceusXjj97m2noF02SWfcCi7sScFzJVBnZpi7Ddcv/ZT3H66ReqolqZ2pWwkseRlByDTcixnGIoTlNWKv18OK/KXiKOEynEpu9zhJjar6Ub2hmtM1EoH1ZVI6oTadoSdxeEzUjcThaZhHkukw+cKZnCFBVi7uCOOc+pIuA6xPmqrdW5zGWZD2o2nvGOdCzEa8aw5ppDjzxxlX96ZwSPrii1RoBzDUEODfj8+jodxNj1x0ee9eCy0qvsdpFxF+vSU8fw3jgt83G9dpycOLoOEGWcEpttRJPSOdhtJu7f3bDdTFWh9jlU5pzCxsoUY8mXWF9MzSkowrB2HJ04Hr3d89jDPeve4Us/zjM5z71mdu3P83kK0+ZGdE7ohg7fuTlmkaa8zi29V/bXwvKrpJoRIpLKQXS5B7UHfZfXvpI/sSla8/zcFs4ADO8sqlGJeGJhPA9K+kEO8oWSTjsejY/ySHqEjm6hQ/5GFQX+8XSb/2XzFn4u3Hp1N1UCpcmDDv6vhz3/+Ja3yEMHOchBDnKQg3yWsr/XTr7jozcf5/+99STbbvhCF+81Sj4TfoarXvG8eNhWD3KQSzL0nmHwrI9WHB2tOTpes16vcd688UWK41c7s2ZDaTHGzpgMjaVP5y+vEEGWjy03l2eWNLXl8yswoYXhsRIuyneXrrYyl89aYGWu0fyojIWbUXSO0JySGZQLJqcNPlcx5/pdi4kY5uJ99tDPNuN97HVRNmY8aZ+dUD4ScTkNQgbLS/VK5IXmPqnOmo3Dn9q1NWQGVi5BKr4YQzaiZxCnIP8LC8Ci/5nHTGOxLbhT/buQSkQuNUEtS8V9yj6w1xbS4MRa7fRzI+21WcVXa9Eb8ks+ky6wqGJP0ETMkSNiCqQ0EfNPymlbpimSnOPhtz3D7Xe8BfWOzW7L2fkFp6dnPHhwxoMH50bgCBat14mRXVarnuOjNddOjhk6b15h2b5QnPlq2uY6Juz7FALb01PG8/N8TRn/jV2ljsPZqXL+PDsAppRtDY67z36Kj/2Tf8b95z5dGy/FtEj7UiJPXMJAgd35BZ/4Z7/AJ//FLxG242KBsHJENE6kOJKmiE6xzpNF5BEViwqdciL6/BpHY1MBSgqPpUVqb663n7c2Cwfagw4Cg4NBoBfUO7QTks+TNTvUFty1pK3XlNO9SF2+qjiBvrMULEYksJTUMcy2o4rnNuOztZN0XhgGWzMQI3WEYO3oRAiTOYeG0ODSL7PwFttbO3fbMvucevzkyHNyZLauJl5zLfF+S7dyCWptFnrJDs/iMnmr/V/dSPYx5PbNraPyPEeKAWMeOvOaUsbny2JOWgrd2EaatOKVIHfQIw/yRSgnJyf8V//Vf8Xb3vY2RIRv/MZv5Lf+1t/KT/7kT76q+//u3/27vO1tb1t89qEPfYhbt26x3W4B+MAHPsA3fMM3cOvWLb7qq76KH/7hH15cf35+zu///b+f69ev8853vpMPfvCD9bt3vetdi7QuH/nIR3j3u9/Nww8/zKOPPsqf+BN/4spyTdPEf/6f/+e87W1v4/bt2/ye3/N7+OQnP/mq6vTFLq86osetmytbkPpreO+4fm2N7zxnsWOiGLjqjm6/9+mtzVeKbZ5kI3oleehsFEz5Edk2ZxuEaKOo2fUpJXuud5cW1rqJ1wOCqdCONJepLvIltsesAJTP5/LZJ4mESwLO2MHG+pu1vhDGHL7MNgaXjb0pl2eaJmNlZuPgNAViMuauovhO6PoO7zy9n5UPtIluIKCNYppSzAbjbqFkphx9rO8GVoPH+44SwUPV8g0GIp3zeG1IESQkTngSnXMIlpfPiUO8MWgHb8bdaQqM48S42TFtJyN5dCX3omRj9xz+TaQZL1BOAHW/LMSAlBUF7ztWQ0/n/by5Sukba+POezR5wKM4Y+HW4TeHIizhxEpowWa3XhwCUiY+lHFQNm+Po0cq0SPV3GsJ1Ag92+2O7XbHOJ6zG7dsxntsxgu2kynqGwIhRu7evUNSZZfA+Z4XXnzAZrvj4sxIIaUf1+s1wzBw/dqKo3XP0dEJq9URn/7UJ3nh0/cpeXg0JjSmPM7aUW0yXlzw/C//CgPQhxKRpJBB5jkIxvSG4jkwz90wTaCJ46GjHzq8W87xFCJhuyV5Dzl8oPcJbaLcpJbU1RzGNKZMQIlYtjzLWRd3F2iImc8iuBNMOW4PqVgkiRg0K8qmMHeS4+UkAIe4HlxvLACxuDkouL3Do9Ya5f86kB7SDUeM4HLGotgiewpd56xNiqacq6gpoGkChM4JQZWgts4BDL1w41rHZpu4expISdmcBwsMkrRGDGkVQCM+lIOWcu3YQerYTBO7oGx3FkoxPtTTOeXibMunP3XGZvIkvHFSJKdb0XL4tL4O0UJIkg/stTpqkT3WJ47hSLjxUI8T4XhlETPsHK+5v5s9YE9bf3k91pRw33n6ocf3XQZBEkEtPY4dROf0VU1nzeq1gHdK5xJOjQwllQRXxk45otip3TmpZLIamrEMiezaUfqgRFjxzuGjzZfCxr762HOQgxzkX4WsdMXT8WlWrL7QRfmcinkbv4E/efwLfJW/95rvf3Fw/PAbej6x7bl4DmqM44Mc5CAHOchBXqPs77U7D//80bcABz34IAc5iMl63eXz8wrnYDX0iBPG5IgwG7dyRFegGscXB/z8z2ovm0/wVKA3YxYqsnhMeXzBAOa7CsDl51cyv678R3XGMmSBr7UY8vJvgxnaMjbPyumilRJJFpLLBvUUK3mDxgCouSwFX9ZcsRhL+m97qzjosgHRS8FemybK9ShObEDGUt2Mu5cmzT/eZWOsq3lZKnya1NJ+V4wl942kmPEjq6+WVMkZGrJUEXOkhBiiOYkJc5Tw4jiYZqyLjOFWkLdgyI2Ybdxa2Imj897KUS9Y9kpJL2QP3k9fPeNK1Uu/ttPyujpGVbOxu2DI5TkOj1abdOmzQpjQFJmCYcQxToQYCHHLFCdCJmEERqJ3vOHrvspw/N5zdn7O+WbHFALTbpptI0DnO7rOMwwdfefouwHf9ZydnnJxflryLTOTNfbrZX/HaeL8xZdImy2uSV1fDOez25lWp1JNZY5JxmkNx+v9gPOOT//ir/BLP/Vh3vGtv4WbTzxuhKYQ0OIsJ1jEiwZrtVFg5bu4/4B/8X/+FCfXr/Gmtz3D8cnKcEJAxQgJGqeMGza96fdrl/siAZ5qa3HNd2ag91gYDrugODLvWZ/qalDmlwhG9FhbWhMLhj3HbS/NXZwi6wMll1dTdnK07wuuXcai98Jq5Qghsd1ZeacpGS6r5f2ZgFVsSMwOz6AMgxVyyiGhQ8jRso8cTpRpDJydjYRo9JdCIrMoIHME9OJ4eckc2EyibiX4BKtji57ddzndTe2Icu3VwPHLY8j5eyc1ZVQZL6lGEp+x2qan9p4reemx6PpzOqw9w0NZMDNZ0YkYlW1B7GvqIvMtiDkWmjlCkJwz56A7H+Q3gmy3Wz784Q/z7/17/1797L3vfS8A73//+y9d/x3f8R38kT/yR/ipn/opvumbvgmAv/bX/hrf9V3fxXq95md/9mf5ru/6Lv7O3/k7vOtd7+Knf/qn+Y7v+A4+/OEP8853vhOAv/W3/hY//MM/zN/4G3+D7/u+7+N7vud7+OhHP3rpXc8++yzvfve7+b7v+z7+9//9fyelxEc+8pEr6/Gf/Wf/GR/5yEf4yZ/8SW7fvs2f/bN/lt//+38/P/ETP/HrbaIvuLxqokdZpY3x6lDxqJg3v0OwBCFKLIojUDXKqvgWTbt8e2lnnEWN0CGNfj9/1VhitRjg53fakp0VK2ZjYDk/yGKJN0N2mgtFYSGXCAciQpKSX7IkBikbsVUo5AgDhUFcQlbVxyrV+N7ozxQFqbyrRsvYq1eNttAyZgvjtmriZrguClrOZDJHpcg/USec7uwgketeooGIiyQErQp2idxh/ZtSgmLkVlNPihd8ie5RWNHtMCjb1qIrq+ZRDmOyaK/SLkoJSZaV9Kpx5X4UqXW19Ist85LKWJXcV06kzR6TvfKNiCLNwaWWoXbWHJKsMrllLi8IKoLvOlbHa9QJn37pAeMY8L5ntTriJLPzNTOWBeufo6PrqDhW610elY4Uo7G2U8J5S1mzG0MO46d03Y7z842F+wqFTT3XOdYw7bO2qJJwmUltmmJJt9SGhTRJlU29VFhSyizhpHP7tN1K4esL6gSN86G2HoKKwkwzfNUGmngHMoB0qDg7OPbeou/FTDoR5rmUD8IodjCOae4f56C3CB6+85DnpROtng4ktXI2SnVpM3u+NJ9D33nL95mjAdaRlhvCN2SMqp9qWQPnCzUtWevOCavBEYLNuZRgmjKbOpUKtWvmfnsayaTvHZYKVS0EZCjsfNCU0xHlOjkHQ2eH6HmuSe1n02vrSkVtbhH6zkKxSma3z3Wtt9RSNkWc/1VIalI8J2Zl2PJzwhQVQqQbA9pD13VozgQak9R3xZhHsc+tkgl0/dDTDb2FxcseMPY9lWzmxOZgAShcfvdlmb0RvFi4SwtLam2xWg/4qERxXHn7QQ5ykM+r9NpzI93giCM8JW/vl4qYFhWBfx5u8UO7NzG9ysge227gozcf54V+x+QuGn+6g3wpyr17DwHCzZv3ODm5+EIX5yAHOciXiJQ91mXfyxWr5V4rh73lIAc5yFVScAKXcdrsCGb/MtyjQIILHLkY0pYGUb2Eh1z1xvZfM4YBLAJBXO1Cbe+uGGC1zC9hoWKoL2Uq6FHBMCUbQcvLCwIt9cEZL0ZxOjvh1Rpp+6vBlZFFsS9FxWYPG6/f5/9eypOwaPjGGLz8SZoQAtoaTZt3a21PKf+v/VveWZ3sAGkMpAarNy/OD1zAc7Xhywey/K62R6mpFaJEa22byL53c3Frh6YGYis1t5fuR2yVbBcpOFhT7GUfyrKMSzy8ucw5ur5jc3bGL33kn+K6AX/zOl3XVSwfhS7j2qpK369QhK4LVCtIKulakqXNITulKoQ04kNkmia7Jqes1qbA6SogLOV0QwW/bzD8gt+V2uk+EFjnn2FsSRWX54iqcv+55/nEz/0C9597fm7DjMnTYMil/ruzCz71C7/E7uycMI6G/2ZyCNkqVSeIsz6yVE1zMS9hyNm2UrPZGxsp278ciYQkS11U/fmSopciZLYYcvuROYeV+6X5ut65GCe53ouLZuxXm/EgAp0TUna+VLVg36naivK9rwCLmLPbHIHdCBvt7ZLJU8vmQZj7u7GLtK9t54Lk9xRn5XkUCa0to84+VV76xLOoKo888xQ3H3tknvsiy3bOz1HNdZeEi7PT9bxmlck6R/aWHDTe5rLivcN1PjtblzV27qBq62r6aG8VbbqtXUnmNOzFsbnrvGUK+pLCrQ7ypSqqyh/5I3+Et7/97fy7/+6/Wz+/iuBRZBgGft/v+338tb/21/imb/ompmnib/2tv8UP/uAPAvA//A//A9/zPd/Du9/9bgC++Zu/md/9u383f/tv/23+3J/7cwB8+7d/O+9617sA+EN/6A/x5/7cn+PFF1/k9u3bi3f99b/+1/n6r//6SjwB+JZv+ZYr6/H+97+fn/qpn+LJJ58E4Hu/93s5OTnh4x//OE8//fRn0TpfPPIaiB72I9mrPLouEz2gQ+jEVHcViK5sXe3u1moxV25tlAs0G9xmu/CeslBCjOX7vFnn5sfX/xbFM8PapQjSKOK0qQDKOyyiQEo5uoAw5xbM7NwSbUSzmTeEkkPJNq1YQgE2TeDyTtKG1yuqY8mHF7MxUlwmuTTXpxgpQe9EqWkuqqlZPaRuGbEiEz1iKmk5IKQNqBDjaCk+8Kg4YgpoVMuL5/pM9kh4p/ROcCghBJw6vDhSDKasOKH3jt47OhGDfIoRdz7N1E15uQnmja7mzbF7jEww97t3wtB7vHPVOF6U16JteS9Ep5BCZpHnt+X2kzygvG8VXqXLuRvdzHnI7V4UTKoSRR1f1nv1PFK62nn8quf6Q9dIneOXP/5pvDj61RFdv2ZYnxiZJ+fXe+SRx1CEEBIhRjbTRL/quXHdtI3zi42lgdlZqLSzix0hpsz2T8TdlribCFPOs4EpTjFBmJbpjCSzTLsY6ZyA95nRnLN5LtinTfsXDSr/GbLnQIxKiI0iV+4VK0PKSpzWOVxIBDYnW1VGozW2dB7pe3DH4Dpwwa71A6IRwkTSOPObqP+weRIUnRQZ8hz3Hh1WuK6j7zwyJjQkVJToLfKG5kSEqTH+w56SWoaGwHplEXMsJYitIbZmzblVLe3PK61yeYxPeY0hp2457giWNccieuyUYcgksBJJoi6O89QqMgyOFH2NsjJN+VAXUj70CTF6UkYpOi+sByF4mFKqzGKwkH2xVKJ4S+SGFxHWq7J9SPMrexA0E6eswE1vY8xnlw9eobZJeZAgJFXGKRIR5GLHaqWs+gHVREiKl0y8SHaYESxND0ntENE5VkdrumFgGs8Z40QMhehhYTxLKE/RgMTEHD626TMpaz2ZQGUkob7vMzhheYevXz+yCC01LdBBDnKQf5Wy1jVvjm+mp19AnF9q8n+MT/Lj4xP8lnHiXYyfsab3Vyd85Il38MCdMvpf+ldSxoN8YURVePbZp/jkJ9/Il3/5LxyIHgc5yEE+Z3Ksx7w1vhXfuMN+Ke+1BznIQT4HUg3p2RgujiQOUSMB+GL0FGokjoqQ1uVFaUJyXPGCco39LoZDbYGSik008KzM9y8xZGbsoxpX1YyT9W0l9fj8QHNcSQusdyapzK6G8xtbo3qOaJ1mbKtUTwrW1ZS9PKcYqEvK6ZbmrlJIJ62jVNMelcBiOSOWdvz5mZpAnZLUIu1qxiE1t7FFQc2Y3xwyuQTkQNScCiWV6CQp42rZq13mqLIV62p7qumnS2b12k1X4Xfm4Odz1O9FihrnKrjnClapBmzWcZExrYIhk/u/OHM6MaN14ArZH6a0GDJ1XtQ+FTMsr9Yr7j37HP/PT3yYm48/ytf+nt/FcHSE7wYrezK7xvHxScUTU0qEFC0d0mDtME6T2Rai2TTGKSxSH2sMlu57QQbIRIy9dEYiRh5xavg7riFSFCC83tEa68szbO4mVSQVx6n5iud++Vf59K/8SwbnGFxeB7L3ZbEDlRQuqsrZi3f5+f/jg9kslOAhtdTJ3oEbshEkGd7oPJX5UOerLsqmGBacwyTbGHMO9R4Rh/NiOcGT2bqMEJFXi6Tma0uTroZ5PLb93WUbhKUGKe00rwhNk181fOZL1KJYF0dAEaEfLNW1AJqUKRi2XJydZbF2qtleGvFe0M7hxGxaZR0q48PGReMsKIYjJ4GoTbuhC1LSYi3Lde18ZdM0v1J9dispJT7+//wcn/jZn+c3ffu/nYkeJX5z2ru6xFWyqNQORaaIV4vyrGJ2rtpPzdB3TVeIE3zf4XxHjCMhxdoexVYgZZ2LybDnpjrLtbusu7m/fE4lBXU/HIberJX7IPRBDvJFJqrKe9/7Xn7xF3+RD3zgAzV606uR/+A/+A/49m//dv67/+6/4+///b/P9evX+eZv/mYAPvrRj/LjP/7j/M//8/9crw8hcOPGjfr3E088Uf99cnICwOnp6SWix8c+9jHe/va3f8by3Llzh/Pzc771W791QeIchuH1RfSoanFWxrpsKIt54XdadO/C7KWSJGfVWYtGmp9Vfs2Kl+Qr252yEjmLEZGs1BZl3rmaf3DWXeftMcRADDFHmgDnPM6VLVRrbkBg3jTyYpzSHKWjGHCbBlko67r4fqFlZgW9UYhKGXPlVLF8i5kteHlzLwxEsuE05/BLkZAJIkaZzsp+3WRLRI9ETEYAQAOqE1r9Oi0ChiYjAqSc8qREMCElI/GkRIiTefI4b8STGIkxME0WfSLmiBVNAC9r04W7f/M586Gp3dpm76Cc6cw5U9TqYUeN+u8EY2M7u0aMreGc4/q1o5lwgqKFtd08G6ESEZTZoFtbvdXHxSKHOCeZ5emynmuEhu0UeenBGdM0WcoMt+GF5+/gxNWchzFHfsnHiRwVQ4nBFPEHD84ZpzErX8J2tyOESGgUcSdS2dlJ3KwMS4lFM5e3jJzSnkXJc11Hd/06U4jI2Q5JqSrU8xidFTNTZtuxTa5TWrRR+TrCrOQJlblqB6N0pQ5T1oyYlM2kSCdcOz6m845hsOLtdhtins8l1GPSRAzBDjMSoFecMxjSaT5c7nZMmw1xmoibDbrd1rEQohnru7aOzIe4Mi5K6p5ycK2jdk9JX8x6bVXOZaULaSBlQo3lEC0s3wwG5OA0izau7271Z7vAOVPUZwVWynmQcryMmmenCN5D39vfuwTqyXOoDQNa+kdqHxUQYFGopkBzefcO5cshdGmlq4ev/FtIaFRCElyCCTtgeLWzWExqpP3sBRNDtCxGub5TiKgENAokn9cAxXtPP3ic63DOETUSVfEu4J0jlvRSAntFrCmBpB7qBMl7hmj2GDkQPQ5ykM+bDDpwTa9d+vxYj/H46m38pSkW6jUB8Wpo8YpbhCSCZ+Ch9BBBh4Wh7iBfSlJAuMu62UEOcpCDvBbZ32tP0gku/+8gBznIQV6NtOf9Yti3aMl23q/Rm/cxZJn/oQqtd4vMD644SIs5XypAe5hv8OI5ArFhssry2pTTxUq22ImkxiCwxH6lANa6hIELllAwsVJE+1UwylyuhaV4vw7NH5ofkqMUVMztikvbf5Z2tNS/qRr+S4MWiN6gGKn1Mww6pzXJBJdFWWTZFoZhKQvjb4rmaJMyLpqjSReiQk1X08gecnZl91Z7giwvrZbXipM2zyg/IsufjOsMQ9/g0nsYchlPFUNmBrGbsbYH3VEM8q4aimcsMSRlsxtJGden7zl+/FH6WzfZbHdMavh826lJS7taW+92EyHFPE2EEMOiba2NCi6nxAU+v8Qwpal5He+5/cQ53GrArTKhgmZctx1S/2w6Jo/bSjYpl6VUnVlTTqPTpi6qZatzSJv2mMd2jQYsMAx9JvmsEIEQpjrmKjmKuX2SJHCZ2IFNZVFLpZRCsN/TBNNUh2BKIE4tnXuzPs3jeMZBBSpXTcrguTTR9xaIRVvO7WiR3pdrTMGqyXh2WT61fc6CqHa5m6rTa713aRjR5mKziTTrBE1f1TVkrtdM2XkZadbPy/VN5szZ2uH2vB21rVBjj0ulH3PLOy1jJaclVyNdaIlknd9tEUFi9hefvYEtJb2NE3NMzE6EwRwmSySnMs4XImUfmesnuZzVXnaAkA/yRSqqyn/0H/1HfOhDH+LHfuzHuHnz5mu6/xu/8Rt55JFH+F//1/+Vv/k3/ybf/d3fXdeMp59+mj/5J/8k3//93//rLuczzzzDP/gH/+AzXnf79m2Oj4/50Ic+xJd/+Zf/ut/7xSavgehh0QKEnGKg6+i6jpgCIanl6Mq7bDFqaw2BxLy0qynJCwadKxtiy3JuNq+8gLYMadWSLsVycBUtWpuUKSWix7jbMU0ThSvsvaXq0LqR2WZZWLlF+5uJHsY2L4UquuFVK3FlTNd1vVxZNlxZHACKQh2jRXQISQuZtCqhpU6FlW2BGxJTiIxhZDdF+hDxPiEq+fpEyh75JS1LiObZL36bUzKEXM6EEEkhkXCW3sCBaiRNAc39G+PEZhfwvmPFwDTuiNOOabdjs9my6Qd2u4lpChSmapWqqCm2YxYWdf26hjGzvU9AHM65bADvENflnI0WUk+jyyQfhxOP7zrEW7SCfhh4w/VjUlK227GehxZMSbH3JE3GRN3rzqQz29hlgoc4QXpL3TEMnq53SCcEHPcvtvzLZ58DNZatPNjxwp1TlJnQkXK4hm61QlHOx41FdAjGBg0h1rlQCql5zokIne8ZvMdyBCqaAtPkUJ8tz+W8hRGxyviu3SDZe2IYOHnjG9Bxwr94H4kBSY3ZvTQYy3trsyloTBYRplG0bTQpE/nQmaNE9IMnxkgYzTBl0fXk0lkgJmUKyr2zwJh6rt96hPXxEbdv36TrPffv32M3jmwvLgjTRNrtSFPgYrpgu9sRncedTHTi6RS6lHAhEs/POLt/H6YJNlsrV3YhGSfFa47QkYeHNn1fWsJLhysNACR1+bqiPJc1zB5SglrWttvT9VJUdrtECFrHWN87um5Wko0IUlu9/H9WEjX3b1Z4u05IvZFFhBK6Tkg5VGJUIWSih+T3nRw50iTEMeHzAUfB8qWmAj7Mw6L9WZwPdW63OYLLHLLzsu6dSHm9agdCSVMFlq8woWyDEDsH6ljh6HPbjNH6bqADhXEXrD3zOru52CE+sup6nHSoTDivDOuB9fGazvc43zF6x7TrmcZEt51IKCGvVUljAygZyco5hy92UnX5BJEzVDZLzEEOcpDPvdxIN3hrfCuyN9EyLfQLVKovflmz5i3xLRxHz//1GgL6HeQgBznIQV5/sr/XHvbYgxzkIK9dZhqGCDldsjN8sqAmBSNpAYYKChfgYDYEziiZVIPwjCFXM+e8WhVyR/5dcQbvZjylAq8VkTBHokL0gBp9ok0BXYorrcNUmmN3LOyRe1jIfistv2jRZpk/0tmQ2+LEFT/eW6ILHt6+N2VnwRK9VWRuqxZrN4KH4eRJEk6C2TwLNk+ObpsiimS8mmoPKESPlBJTHHHJ4TvDBFOMpJxCpHOeEGNOa60zvpSrvjRPL42hGc5dGoiLo59AiSArzUWqgmjZ0cxBMDlLK+R9x42VRc8IITa2jAYILW2vV5mvpQ5jaA3wIN5wJF8cu5yh8NsxcPf0rD7THV/jDf/616IivPjgFDiteJml84YpTjb2S8SFK4gy9n57txOPFykgbO5XySlPZoO+wJy+ZAnlG17vPcP16/TXr9XIuAsilpar925uJSkqrSebVCpA8U8zg7nUqBRm92n6e080t8F2TET1rI6O6fqO46M1zgvb7daw6Gkyu0gIaEpMcTJSDIIMydLQY5HYJSV0Ghm3W4vcEEJO72IFiNlGspg/7NmBBFyOYNQ64tXUNLnuc3PPjpuVD7DXrRUjbtIhzc6Cdv1MBJkbaw6yXlbK+UXOSY1MUldSLfUpWLLU7rVo68IuYmna595ZkHhqW+jleTFXaG635ZNy9duhRVkr99pFyvZR1l17UkhCSgJqUecd4JISE6gIHp/x8ik7R1qDT1NAgsvYOCgRceA7T9d31qfOESchxogLigvmLJ1yxatlpTRacWCWptBNrQ7a9UG+mOWP//E/zk/91E/x4z/+4zz00EOf1TP+4B/8g/z3//1/z4c+9KEFqeOP/tE/yu/6Xb+L3/k7fyff+q3fSgiBf/yP/zG3bt3iK77iK17TO/79f//f53u/93v5gR/4Af7QH/pDxBj5yEc+cil9i3OOP/bH/hh/+k//aX7gB36Ap59+mhdffJEPfOAD/L7f9/s+q/p9MclrRHpLdAQjRFiesfyNzKv5fgqI+c+yiS+lLMoljFsSW5zrgpgfYEokmQWsxGhG8xiCKSm1CFo3LWNqZlZxCcu/V8bWkjmzAXXeROTKS5dKS/vuvNO0m7yxBsti3j5QKWGqWvZjaZOUEpVtWoqTlVdxObpDPkSoJiNwiNb2rOEACvlFtX42U1YUyUZXiyqSU1vkNi7ZG1JKjLuE92bcD9NEJ0rXGJxTTGhMRa+pY6BtqBK55VLjFZGrlLjSf2rRWKQcW3RWBJZ6/4LdXtpXmvJkVWR+rZiiX6JUzN4Hpvys1yvWq1U1sk8RdlM08sWwoh96VsPKlO04v8PyJnpiSmzC1tppGq3lo/VF5xziYOi7+UAj5QBhT7KDZAlsmHsvk0MkKX05RACTuEaB1PrbZWVevKM7WtM5nyOhlMgEUCKAVEWu1KM8qxym6yGqBLrM4hziLc2Oep/TgbjKvBbI7ZzfI1oP/XnGkuJIDI5xt8OLcHFqYd5O75+y3Y1sNlvCNDGOEzFGNpuRcbLUQ6oO5z3OOzYhMp1fkGLCHR2RvCfVYa/oSk1xa+f7PAzr4a5lk18izrh8YGy0cbUBWA/cM0G5oglGvGiUdMhnr2Ygz8AHkA+kMxu7/Lc5/NfD73xFO8aLsk6NTCN0XvA10Mzy2rY1ZiV7nne13pcOls1huinr/K+6QF8hewdOqQ1DCR9VIpd0nadzjj6vuU4cQsJ3Dp8BpLwoAjnqj89j3rns6RDy2DRSku86BAsvOjfn3Cfz8JkVdSew6r3RIYfu6hPoQQ5ykFcvasSEta4vfXWiB6/iVyPn4znPnT3HulvzxLUn8M7j8Yi6ed84yEEOcpCDHARY6YojPap/H/Zak9N+zenqhO3guZU6jvUCGL/QxTrIQX5DSTEgWsblJmqmQAYS9xFDKlYgGc/YC+0/Exi0QR7m585GxuI0OONn5jBlqQfqbQtcokS40Ip7lUcvGRWXXkYOrLZn4G7uuUoFr7fvtYNypcMQhVSR723grbldmLFQe3vW/qV4kM831TsqXlyeWF6X/y6Aau2P7IhY3iVa/90698SgqCvEkYhDS+Z1e8YVRIXLfy3HxFVy2eFmidst/i6X7j2rlr28R5sbrnp1xe/0EiQmYniV956Le/e5uHsP7QeuXzuyCMS+w3tH573hg0nBZ+wwVyapElKw/iz2kFzAEkm2OiBdQuClfj4jvdaPKaWaQqkMh9gghy13qdiAcILre1zXFZDU7ECFgFQbZ6YM1LHT4GNXYcjHD93iVk7NgQi7s3POXnzJ8PLyvNwfpVtKhKCKUGpEk9mHBJj8Dicw7kZCiEwh5IjkFlWmRCTXgrVm8sqUEnGaDK/uelRinvtYo3RgIz239d70noeMNFNl8ekSbAYjJ5S1o3x1BVaqeZxo42u5Dz0up0DuiUUqq+aa9h11jlyeYJqfkf1x81q+fMZy1YASYeSqOlwNl84fXoUuvzKG3NzfztnS9pmQI85IMZYyirysWWc410ZIb/qr2t9mcpPGVMe2tUl+WVn7m76tddrvJ4Euv5Pu9a1rH2SWRx45Yr32bLfx8/qe9drzyCNHn/G6j33sY7z//e9ntVrxzDPP1M+/+7u/mx/4gR8A4I/9sT8GUP++Sv7gH/yD/Bf/xX/BN37jN/JlX/Zl9fOv/dqv5W/+zb/J+973Pn7hF34B5xxf8zVfw3/z3/w3r7lOTz31FD/2Yz/Gn/kzf4b/9D/9TxmGgT/wB/7AJaIHwPd93/fx5//8n+fd7343zz33HLdv3+a3/bbf9nojepS0GA4RT+c7+s7jJwt7L1gerAVTIS+OCc3A8hXbRiElJCMJLLeHkiqgKOU5okddVLPtL4SsLLjmLuqCbOlELDdX2WxmgkCzFe/vOLO+PhM4KApJzOk1fH6n3d+mTUHz73zBzGdvtg+lRg4pqeFSgihKIs7GdcgsSovUYHnRlM55ehwdQog7VIyNrKpomNAQamiCFJMdZvpCAMmh9zLxI06JMSghBBIwhcRmF0jeQeeYxontZmMKq+uAxLEXjnxWHJMSpkCcghlKm219oUiUTU/mjbiMgbnf2s3cRhESs0IM4pRIRPBVyXBOcs48a9Nxl3M45E09kVn1mhnByfIEFuXHOw9dIsV5DIGxdp133H74Fo898ijD0DOset744AHPvPkNTGNit415bHljyccpE28iIh39cI3tNPFseoEpTEy7LaAM3hT846Mjus5zdLyi875GqYnRWMe7UQlR2W53jFN5trGRdxcb/DhxAqy8cNQJpxHuBFdZ0UY+sfYT5/D9wPqhW4TtSN8PeD9SCFBz7kqbHysFX+agwg5n4f6ct0grewqM7zr6ozWUdDoYK1pTQtQUqL5z9aDoxLFeDwxDZ6lwNJCmBwS34f7dnk03sH1hh2ji+Qc7LsbI+cXO0nLkbiqeDN53xnT3HbIeeOnBOQ8enPPQ7Yd47IknmHYj4XyTo8Q4UtoQp7t2aNKUDyrz2mIklaIh5qgYwa7petd8l1ceNS8JzYBCShY5Y4EFZIlR2Y2RKagdssTILN7ts32pZKsSJq9MH6nzqKxmguDqHGql9J+S50pnTOz1WriIkkPWNV4ctSnmNbIu781TNc/neuYv10hRZsupR+oh8tIZvJX8ZX21c3Sds6hKU0T6xOpIWK0cx+vBUvu4MhAc0+RZnXeoS4QaktTSTUnfm2LfdTjn2W1GpnHCacARcd7Rr9dMW4UwLQ4CNr+lRkiZwxkmvIOb1y2EpVutmV0hDnKQg3y28nB6mKfiU5c+P3gVvzr51Nmn+Hv/4u/x5PUn+Xe+/N/hyH3mg9xBDnKQgxzk9SkPpYd4U3xT/fuw15p84sZj/OxjbyGI8PYIT6RPIdznFSwNBznIQaq0jirm/OOcIEmyJ3wbeYPFtFI0462NzayCyTrjDtWBbSkFk6gObmmJTSaXatmA6lxIxlFSdtqRRQHn++vTXg5DprHtVnRRLxlvi/d5vbX5O+U7982fxQjcprspJA8jBFhjmuNXrl/GSUtkkuLhnjTYW4qXWE7PXPpDa4TXpr61FIZjx5TTf2NpD6aQarSIlB0ELXWJYYC9EzqH9a/me7MtoGDIl3af2nlNa5ROlmo+38OQFXLKHSfmnW8xrGWBp7n5gYb1yYwha/m2WNZVZ6dUcp1EiXttU2wRR0drTo6Puf/Lv8onPvQRHv/qr+BN/8bXGuYfNONeruK7FZ/H4f1ASIkHF+eWtjoYvu1zyvJ+6PHi6Aafowxke4ValOgQbRyHYFFcionG+iTgYmTAIjT0DnYJLtLSTUzTXBdxnm69oluv8dmhL+2P/Ry42yuW/j07cIUykmu69WXHPvnlb+er3v0tFd/85M/9C37+Ax8kZAxZxCIClWDHQnb68tavogmNO6JMbLce7zzhIiCqnO8CY1SmMVgkb621s+lb2lMcdJ7NbmS3nVgfr7l2/Zqlh55CJQqoTqS4tbniyto0t1ols+X1pdh8UMX53J4FGGWeu/W/KpcnQB5ySXP671wPQfB5Ttf5sTdV57HezpX5BQV7FgpxZn5nuyzbGDCbS9cJU47UsWA4zc2b/57JE+281nbd1MXllzHk5r6ryC/1gryE2b8zjgsWeVmUroeuE/rOGx5eYW4hRcd2dGgobVsazYH3eQ4Yzh6CEYTMJmj2It/1pDCRjUnVibYQmmyNtnW2rFEisFqZW610B2fBg5i86U03+MVf/B7u3Nl8Xt/zyCNHvOlNNz7jdc8888wlIua+vBLBo8ib3/zmRdqtVt797nfz7ne/+8rv/vJf/suLv2/durUozwc/+MHF99/wDd/AT/zET1x6zrve9S7u3btX/x6Ggfe97328733v+4xl/40mr4HooZcW8CUlrSjbls4hpYjE2apnYdgcdb/Lv+tmVokerZFd5tdk0oQZI3MoOFmqvWVVr/8VaRjJbcH3yt18POfVKh/v3dswl69ahxdXV+bz/qt1Uc+F8bTodX4ux0ygnpnby+1Oq7KW8gakKDEGUgy1DWKMBEzR65oUIRa+D2JIhEnpHVxbdXQOpmkC6UAs0kUYJ0tv04OQcAQGL9y8fo2T4zUxjoQ47h0A5tI2ehWlJoIxidUp/dAxrFa4roTJsrb2nWe9HuiHAdcPRlhgDonVRpeohul6SFq2Vn2zE5y6SirxnUOkQxMkUXzvcJ1jfbTi5NoJw2qN+A4VR1RwzrNarfEu4Vw5hjlUIzF2eZwknOvo+yO6qeP4fMU4Ca7k/Mz9Ok4WmQIB7x3OZaJHJg2Mkyl04zgxhaka5IuSkVLCJYtwI9GUrvbAo1gUDdd1uJNj3PER4jvEBUtFIQ515YDBJUt8Ody10USuktIHIq4ekgtjvMytEjnFOZ1BxEy8WK8965Vn6KD3ihM7eMYUEI2IRLxL9B3kE7iN4XLGkwjOGM7TFIlph+pIjFvG3TlhisQ02tohHtVgddZ2vLBou9oGDQFEr5j8i2Wm6qza5J6dG1Oxok/BQma2r1o8uv4hc/vud86iA9qffRV+Fid2oPPeQmg6Ty1g6aOimIrMa1DdBvbrur/xt9r8sknqOlcV4JerO+UaIwO5pj5lzhYwI+VoUBYPBkuDFSJjsk9cn1B8JgQpMSVisrChGiMxBaJG6y8nNfyh4HAd9H3Het3RD11OOZT3HjESE2IeSjjJ69LVCsxBDnKQlxG1CB6DDvWjIz2yCBQvt94d5BVl5Vc8fu1xHj56+BIh8yAHOchBDvI6FoUVK1a6qh8d9tyrJYowOQPgO6gRTra+58HqmLOV55r2nKQRYWQf6TjIQV730mICLzc9VDMmIzlNNdWIWfEsXUYFLvhUTWGw/12BBJmjc1TMV5qVboEhNx/t48BXYciv8K1c+vSKCy+1Q3lyBbcuvbM1lC7gloqv7H3G7G546XWaIzJnLLXgKhUfKzhLMsKAK0QEGseg7LToBYbskJhSpDjalHc4IftIKo6EF2G1Guj7DtVI0ni5MrWcVzed4Yg6Y1quuUIN/7SIGpbiWy7hYzPm1d44OztdlqVTYsaUjTKDiuFIIsLu7AzOz1i94QlOTq4xnFzj+mOPcnT9Ol3X5xTx1SqNkmpKbM22E+96XIr0Y4dLkVCidWeJ0SJxM4G4VLFCzQ6dMRZigBE9ik2hRDyPhbSiWB9TMOQydHJdnUOGHlJCnG8w34LBF8P4/rwoT5Jaryta1DA139Gv19R0M72Nnf74iOs3riPOIp/sLjbc+eSnra3E2r/rHF3v8A68zFic5rGMKE7UMM9EbUNVcsqS3ABqJJikESWiGohhylh2QJFMTkovW5s9RtpskHwZYLZdq+bPGgy5vVIFTZY2Ju1//3L/LkWqBbii1EvIeU41s/8cZgfbQhxrnyf7Fy8q2fxeLrSXr7m0/i4x5DpIr3pv+axizS9zoYKSaosoZrNISYnZ5ifa5WJmzJnZJklK9kkhgOWxWKOkO7PrdJ3Dd8VT0y60qVJsIVTc/qA/HqTIm95041WRMA5ykKvk1RM9shFsZgmDxnltNhKCEqaRcdyiKC5EcNnILFkByovbrByVMFs5RyCCq0pt2fRdJhfnA0A0JcX7PTCijV/X/HqZCs3/yrur8nLQRjEfSnNDc2CQrC8gTfiq1ioKosmUXV1+X9T1wkNP5bDibWMo9U4poSFCNsoLYuEGFUIKTHHkfLtDEfzQo8A07tiNWzRNaIpsNht2ElHtIXlLfYMyToHdGNntAuOYuN453nL7BiEmHpyfsdI161VHCiPj2RmrwTN0K0QjGnfcWAlf+fa3Ik7ZTvc5396rJIZS38oObcg6UkIdiIWs6vCc3LjOzehYHR3VblKU46MVq5OB3g/0foXvBlxKOM0KrRPEe/CeSsnWos64uesoYwu6rsN5xTvBOTg6WSGixE1AQyINIL3j9uOP8KY3PYPzPUE6dtNE2m5JSen7Y/pBOLpuhujOuZlcZGFXcgSLnt12S9Id292O8/OBKQQenJ4zTpH7pxe5P3J7VaXZZ6NyOUgZiaqM9YuLLdvdSJwmpnGs7GDnPW7oaqWdCHiPPz5m9fRT9CcnSNcjMuG7Dt/3NgpVjH6N1tx+MSs1rhn3Zc7WPHjz7LB+zfnsRCDGyDiOdkh0gu8cXd9TUl9Ittx3veexR044PvIcDYHOCf0w4ly0OZGU42NhnYTr11ZG7gg7NIYcIhJ2044pBsYpcr4xEszQKdNmx0vP3QUcgq9pSyAhbiJJjvhS6lJyEKo0pA4bzN67GTgoHg5CjZxjBxqf14zC/L+8skxBudgaiUfLqdyVNpx12JaCLTJHmNg/ZJYbZ4W2fchyOfReGAZhWHesjga6XUA1YKmRbD64stbk+teQmjoftiEfBJh1cs0HSCrJrrRDSfcCUcEXkkc5UEhZLvPYyl+UeVWi0YjTegCMMSz7SGGcAmenF5xfjIziUfFEd0TXe8YpkOLEdrfDdRCnEY2BabcjTBP9MNAPPV30DF1fy+a9p+8dw+BxXYd4h7qimOeoNWU9D4dwzgc5yGcjj8XHeDw9Xv9+vYeL//VKieThnWflV5/5hoMc5CAHOcjrRh5Nj/JkfLL+fdhzX5u8cHyL//vJd7Lzjrcm4cl4F88pEL7QRTvIQb54RM34rTJHniDJDNcWLDXFfK4HcfZZgYRnhLZ1ENF6f7WjtsSIbOTLRbBTejFoi8w4ZYOVvPa6kW2vr0SPayybFf+dja0FC56LUR5a7mqtufMzLr2lbYdiaFRAckppaeqdn5rUDNpTsLQUznv7PIbcF0b2CNNEFMWAfalRmGNKxJgIIRGjMjjh1vGKlJTdOOL7js47NEXiOCJeLMI2CVJg1cGjtx9CBELcMYbtDDLlaktNlVswqOIMmXGinHekX61YJfOqb1u+7z1+OMKLz1iSNwNrcfsXqHkoLtmDZfGsIs55pKSwEHsH4tEpGV7mrd3v/OKvsP34J3Hf8lu4+djjPPKOt3HrmaeQrsP5Ht8Jfe4rJwV7zBb2bDD2zhFCQDUSYmAcPSkltuNIjIntbqr9UYo8R6mZ42vPad2tTtMUCNGcnlKMkDIGKg7xsy5QcFrpe/yNGxYt3BmG75xDnDfbDVomYNOFOTJLKV8Zylq/aVDKxmmzOpopIUYeffJpvvK3/1uG0XUdL3z0E9z/Oz/CtNvlcggnxwPXTnp6b6mYnQ/m/JoL0/fQdbAaOitbCtlQb28PMZDUxvE42bj3DuIUuDjb5rKWqCZWZpH5/nnESB6qLRabx02pX8FKy221+6T54CpDlj2sOgtGXd6W+2smiCzx4Dpm98q19/hL5V5ckjF03xmBysUcKb50HTMWXUkMe87PWv8zv2bGkXX/E8r4WODP++Vu95Nc/jKvFmXKGHLSQgSanxRTdqqdIhGHijBIj/OOmOZo6uJs/KgmUjDbjPPeiGZqc7YUsESw8t7NaV9ql5QxkwufPr9pOg5ykIO8fuQ1RPQwqdtO/k+7yNYUJDGRYsqbX96+BVSyclEWYymG4uyRv8/oy5tS+/FiLywX1mu1Ki9Fma8MvoWBMt9w1f5JY2xkNmTXV1VmS/vOplFy/epBpq1O+75M6HCtEV91TwmrDYXmsFhSDiezS3tmSWdjegIXJxRlGrfsthf0vWd9NBC2G1KcoyvMBUxYsLmEkOgcrDpBozLGkCO0BLbjjpdOTzleeXp2iEaIW8J2xOsEKTFtd0y7zcxszLVweXPTosRWbcQUgnLU6fuO9dFA17laf8U8+u1w0ESKaDqwKLRX6iTNYWBWQKDzHvVw49oxw9DjezOgx+NAConUC3TCMAyZ2WkEkHHcMU6jfRapRBMnFjZt1qcEvFT28bgb2Wx2jOPEOAamEJimWKNy1PyAaE55InP0AC0Eq5gJBVb3lKN5xKTEPOgES1NUw0+qhcwzpdfRHR3RFbY09SxRQ6RpnUfzwQDMOD+Hlsz1dKbsFsVFMru3sOmlsAAcOM0REjILXLLSk08VOO9YrTtWK4+XmJWoRFJLl6FaUmbMz4AAPlXPA5zQRYd3ivcK6tBUCCWpquCFiYwYAcGJKXrzSJyHTZ0mrc5b52vTVGWNaUgH+4Eucu8agUshxBzRIy8izVBtrrf1sT3D1TVYFp/QzonlQ+boNzMI0DCyC8tCSwFKiMYr3pkrVtb2EtmzpJSZn9HKFX9LiZrRRA1B25aYlXlponmU+9XGfw2rl6UCDkGJTlFnbeyiAR0pagUmNCvtFs0o4iTixDGFyDjlLKUCIacLizGxG2Ndu50Ur4G5DPMoOshBDlJFLWJHpy+vdq5Z09O/7Pevb1FurJRrw7y63Fi9cuSgznV0w2tW8w9ykIMc5CC/0eXV7Ll62HM/G9n5gRePbnB/dcK2G0jO0QPJrbm7vsFx2HJ99/kNt3yQg/yGkQWWoC2g0HyRMdBkjoNLAGXGQxFzNjRbqc4wrLbueg3OK5efcrUsMeQFatEAQQbzXvHg5s0tJqM6YykvG/a8BXWuaJ5LGHLGpwveoBT0pMG4a7lkSQIoXzQYsiYlZqJHytE6UgyEMOG80PeeNEnGTLQpW3lzQW4MT+sEAkrMJBFVM45uxh29dzkBtBE9Uoi4kkI8BFKYLrWTVJCytLw0NZHaQN45ut7j/LJDJOM1xQlqiTC9gtG7ba/anJmU4Sw9TTg7Y9ruOLl9i2G1InWxRohQgXByAjdu4PqOGKPhmF1PUmUap/rugoXNRRFz/hJLCxNjZAqh4sUxpYwBa7W/NBWe8UTRZkwtI4FocaDV7JaWMjXBZee+MkYKBucE13csHGML/FVwvL1JpszjtI7SEnW6Onw1EVXaz4Hh+IibTz7Ojcdus752Qtf3lur85nVuveEJtqdnbE/P5ogenavYXSGTzL63kpvHSCwiDvxsiyr2FitSqVSDZ5cqS7Ev5XG/BxiXOu8vR+3vFluuGDIF/yyL2pWDsV5eHDKvvK6Zo83j568+I1DZrCPNDdo818ZEc33Gf5UZt738zvKc3D4pp6YqvIhLGLLs/T1/Vkxhl9f1PQy5Ha/zgmnzJk+z2uwpY8U5uruNieKkTHV6nJ0fi+3T1r+EEYViynYYoc5N1USMeYxlJ8HZYbNOts+wFh3kIAc5yKuT14AAOxahEvaW1BRtIw0hWr435+yanO8sieRVXHNeMwuppXlTnQNfabvqtaoVJbSZbdBaFUFTOvMzpDUTkg8OCYgkdbjkyLTT2aCYlfbyrqKU2gKeU3IkVx5H2cwkNTt1UZ5c1uxKffbPMfkhMWUWpitG5hxBIeWIJd5hse0k1wFikuzd7rORNlmbxEiYdty/9wJjiGgUkiZ2uzPGaeShR0/o14/zqf93w+Z0NM0gRSjkDok4F+i8WpaWlHAaiduRcdyhXtlthWdffIF/8qu/xMO98GXXPD4FunFDSokpWr7AURLnD7agIW9i1t/dypOcos6TMC/7skmDkQgiwvH1Ff7IsR6GpvcVweHx1rYposnXPspZQvA5vUOxii/tv9YRTmDoXU4TckTnO5547Dbee/wwIM4zhaw4O2N3a4y8+NI9phgJMfLg7IL7ZxumMTCOoSqIZcN33tMNvW3o05SHiDOlfgr1tyZT1K1sHnBVWS6pW1yNXNAqfZYpUgCN0XINxkTO3FKVihRSPfxa2hZP1/dce/ghVqtVZrgqnogjkZzlzLQoFTksWSUeGWu/hIhEci7HzqKH4DucFzrv6IeOLofa05Tw3jOseit7styRKkaAWa0saoJ0nn7w3Lx5zNHaM11MpJjYbXO0n+hRdYRkcRNW65U9d614EVIa0aRc63u8X+U1RfDO2PvTuGO33eSIOWXyG4EihJltbFwHa/MyLzXmnJDe2W2p3KuZsGG/XT4EWNoaN39fx7ks1pAQlM0mMubcnI0DCg7FkdeEzCx3zuWXl4NzVkhLv5QDTV0bS32atbRduh2IdR0i1leayXE2XjQflsszcxDE5lQRk3C+cagK63XC+xyRsx7UroiTlP/0ObrLIsRmvWD+rE2TU9qFPK6nccIJhOYR4y7lHyX2At5h6UwT4w5igGmXCF2EMcA0MW1Gdhcj05Dww8Tp2YYHZxsyAy+vzykTlLb0vefkZKhzwHvPar228KBOLtf5IAd5nUtHx5vim7ierr/iNQd5efnaJya+7sk5YtCq+4xIzUEOcpCDHOR1KA7HU/EpbqabL3vNYc/97ORT1x7mxaPrRPGGb2W5t77GTz/1VdzePODffPbnD4E9DnIQoJ7rF4DELMX3rEQwFol21m+83xtPknqTVsPiHoZcXtNgL5UpUVJLKKjoHMEVqFFYF8XMeEp5fC1LY5PUat60crWVkmzULDe01zcOWXPZm8bRy39Cdv5JM+5U8ati/XVuvjEXMmVHMIvUmrFVAZKaM9/uwjDJZO0ZwkhMkaPjAd/B6d2JMEayNZQ5Uqs5djoxPLY4FqUYcTkldfRwurngUy+9yJEXHh4shbXL6cULFhpRxjFg2HQxuIPrBC8OFUeNgNtgyAbHC/3K43qh877pRMOQXQkxjqUGKphZxV2z13/BB5f21oLvWURcEaHresJu5N7P/wLnd17kyW/77Tz6hieIxQCcvfanhx8m7kZc33N6espunNiOhbAR6/M1v1ecM1w1t2EZs4o5Gynm5FQIGlY214z7OSrGzD/YN4O3huditM5Ds4zt4rxWpqETnPMMR0eoH2v/WI9oTvuTh33FDfNwyZiy/UvyuLHowebQaNiwy1hrJeqo8uhbnuHmE4/hus5SqGeH0RuPP8rXv+fbuP/c8/yzv/9j2VmwZ7UaiNM2k4vyfElmw0pq7dd1XXY2zKnj1cg5gxck2ye0zhUhhkiMU53Sdc4BKc3zrLZyY8cqbe8ytlyd2gqsv59yqj5uXtVaW9i8Bqg5tSUWa0RZQUSU4iQc05KYUstace9C1VqOk9nxsyVhNHV0VBtMwZ3tY7Hoy07qU6W+c356UmEKZgfserOHuVyBWg/2JH9QHBVb/esqqRhyu+aV98eIyHLVj9HsczEo6q1ylknJnHs1QQyKdwmi/aQQLTW8N9x8NwZ24zRXuKzNQra5CcNgDqv2CmdjUlyNTnSQgxzkIL9eeQ0n/EbdKZuCzpvTrNTO1+xLMSJqVgKXCz6zNlE+X6xzunh+q2SX8rTKs20q2igsjQ50qWytt3sheswGvlZxL/Wsz87KYDWA10V9NpCDbeTJaWNQLmSSWZlZVGhR7YX20BiFy7ZsSto4ToxTwMLqKSTbbI9zGpSu6/L9ClKUxISmaCH1QmQaE2G3IezOCJsdYbO19CZhxTSOXFxccDTA6BydRoi7ub1ygUtqnSLeOR6+fYsQE+vjNX7oqqI296L9q/MOXGeRO6q0ARupbWcG7kQ7DstP28XOzQcCcdYOvvOsVgNd13N8fETfeVyfiR4x5y3M0TR22y1BJ0sVk5nVXhwxh+IyY39OUbIbLYJHNCJHCiF/b+SkcgCIIdZDBthhrbKHYY6OUYlIef7MQ2A+szaG93bgJC1jurRZvtd7Sz2RD2uF0c2iH6n9Wg4fipEayuHBzhGSc895C+PmXZ3jbQjJMmhFmn4VwXe+zl0hR9qoMy2z1FVJyaJ5pNzDSZ3lR8zlcALqoHOWn7OMBOc83ntQRwymrMX6bGyOFOV31mfncI5ti5YlJhXiVSa3xURSrd4C3udQfoVpLXA5L2pRvvenvpWtjY5RwI8YFZvB+0SCXK+cqLH0SxlHdv5rogAxP3OcEhfbyDi1aYOoZI+aHqZR0JWsFKvhCZttIimIV3olE/muUlLbz/LYb5e2K643hvdy7yn8uqRUNnar5xeCTQ2ZSPYlKJMHyYztmHMj5jbND0mptHcqk2de43JbOKdMQUne2jwhuKh4TRhh6+VrdZCDvB5EVFixwqmt+R7PSlesOKQQ+Wxl3Sk314e15UtBrl+/4Ikn7nN2tua55269zJ752YiyWu0YhpG+nz5HzzzIQQ7yxS6iwsCAVzNyORxrXR/23M9CNt2Ke6uT+ve2W7ZhdJ6N8/u3kZxj41achTX319c41RWpPfce5CCvS5HFr9akuA/1vpwUDHn//lcns4Fz/60Vv94vYlOcy4jQ/l8V7Jmf1z62eIYbmNfg5gV3mo2hxWGx1lAzBlMgHKV+38ZKWBS4+fsqDHnRJpIxrRhzCukZhxeg78xU4Ba47IzxFadIc8qySCApjKQpkCZLCSzJW0SKaaJPEDNOiBZnuab4aY9sI8LR8ZqUlK7vcL4hsdS7JJfRgF5X8dRlz7VG3oWT3tw6lzDkOuYES4N+7xyAG4/cpus7jo6P4dqO1WpF3/d4NXxRs8HWiyOtVqRkWGGbPqIY3832kIghgiRcDtWgJa2Ilutyz8eWBsAlp6qC982xS3QGGyvOWZriagx5eSYpALI926JzN+1X27K5o47T+kfGRBusEuHo+jVuPv6oYahOWF07mW0nCt3Q4/oul3kuk+86jm/cYNpuuf7obU5uXTcMmqY+anNEtXxabEJCy+QpXeyyE2JpqIKFojM5qBj9S7NceXJbGJ2aFizzhYyn64xZ1jLkcVO75RUw5EVwneZNDefH1oCkJJczs7fPajDhOYJ9Ox8am1ODIZd1JUZdpI/pVmuuP3qbNG5J2wf1HcKMr+egKvbvnH6mpGJSv1+EuYPW16/Tr1YM6zWgc19eqn9TerncP5Vg00yJWqnS7u27r3humZtt/9emyW1ToyhpOwek7mMxgnO23jqnRM2OjMnBAUM+yEEO8jmQ10T0kMKqVtCYSC4zezEltyoSSrEWVkPhvNlnJQHBLJD2oRkSc/gwLfflQ7RaGDkLg1QM97axqBbWrfF1BakGbosmQd7gXbOp5w2+mCzrfq0YAULtY83hpMwqas+UYvAWJCkhFuPg7A0PFtkkpViVclXPnMdNCXEipWC7mvjG2Ku5Hdys0JVWroqb5o0je/KLEBOc3xuZQmB9rcd3jpvXHkLEcXJ8nc1uw6c/9nHOTk8RHxE/EcPIuNsx7raM48iDl844f7BhvP8c44MX2O227LYbVo8+xXH/Dqazc8bTB4S+RLwA1/vMsM4kEow53artx8dH/Nu//ZsZVisevPQS03bHxYMzwhRqKhov4BH6YWVRNELM6X8aRVUL+1osj2cYEe/p4oTGQKfQ6ayok5XGYTDmrus6nHNcOzJl/PqNh+n6gd73dihwpmG4Pi3G8qrrzcNABVF46ObIxW4kxkCIE0FhSnDv7n2e/cQnSSmy3Vg4Pud8HmaxGtdLjxYDM1IUOzL71SIdSImwoUrmcNuYJpNAqqdDQ7oq5AlVQgxWH3FGlIhKirMykmIkhsA0TYQxUIKG1IgRJTxZmfN1kC4P6CdHA+veU1KSiDjG3VQuzS+0drD5BBIBHP3RyrwJYsKTiOOGWJVqtdyhSSz2jAgiRhKagqXn6NeRTuJcf+fpXJ8V5wRibWfFcAgJMnO7TCnn6krQrGUlVUpOL1PIAWSWryrjmAhROdtsmUKk73q8dxyvHUMvpGTt7tr1r2k3I4lYyp1y2IvBCEKr3g4r28mu224nRB2rI0/XuUyqsQOJ74RdUC52Su8783zwOzrvcba8WOok8TamvLVfPFOmTeSlF3dMyRGT1PHiPXS9kWaqopyXwV0QNKfn2U2JT3zqgmlSHn1sYL12PHTs8U5AU2b6t4fNokRbnwfFlOVFy1h/OGfMfu/n+T8lxUUYo10aNUe2zM9QsVCaWvafnEqo90LXQegtL2cMgWk70TuH7zqGVcSJkpytZ24fwM0xBZ0T8zQQsSgrUZg8uJAY04gToXcvd/I7yEFeP9LT85bwFo70aPHZQQ5yEPjGb/xV/syf+d/46Z9+O9///b+H3e5zMzdElGee+SiPPfZphmH8zDcc5CAH+ZKQjo43hzdzojNB4bDnvnZR4FceegMffPJW/Wz0r60dH6yO+Zk3fiWfOu/Y3h8sgOpBDvI6lgWGnNTSec8mv/mnGCPbqATFCEcxaDesDC2/ZoPanDYhY2TMWFb1JywG1hI9QmesYbYvFseVxjBcLZVLY9xMzNBajYL5ur3rU35FMfYWZ0HNXjWpOGDV21y9X6E6uiU1ZGs2Tpa6lvaqTUA11NfnNE4xCtM2ElOqqU/WwxpEGPoVU5g4u3+fcdyBS+DMSTDGkH8iu4uRcZyI2zPi7sIw0jDRHd+g97dJ40gcdxbduTjOVNKGawq6JBj0fcdb3/oMvvPsNhtSCEw7i/prfZSjAADOdaVh0aR7ht7Z4c0wzkhKztLGpITTOW55FZlTTItz7E63/PJP/Axpmvj63/sd3Hz8cb76t/82NEWGa9fwvq/tWzqlc672hyisV5HjGHNq6miOggrb7Y4H9x+gaqmEpUQYAbOI16E1Y8iUbl38UQgvtePr/JD812y4l/rcUt/ZgTGVq20spVqMXCSLvpOi4fXzV42zbBmwNKO/7WKBt/7rv4mnvvIdlJHZH61zpJN2HGRbS/lXHs+u99x87FG+9nf/TtZHHf2qJ6WJMgHLXKh2FHKEjqRIUnyXx3Ktv8OJq+tIrg3alKG1G5W2n5/fGvwz8lwGp2J4dLJnxmCRecYpEFPCO294ZSd0HjRlxH+u8FJ0Tp1dGqXYonx+Z8h+tyFYy3W9YZjOGbmAHEEiJhiD4sUbZuwizmXCSHEWZHY+jSmRRkiTstmEnFZduP3MUzz29Bu4+7GP8qs/+RPmMNiU1whlpd2EkJQHpxMpKccnnq4TjvoyX2YnbOccb/2Gr+OxL3srRzeu1/ZNiWbwNu+h4PuzE59qSUFPTnVvxBepI68dL5KNFVJtVM4ZkTdh628MES9mqzGCETP2fIncWz4vdh5zzky5PJIUn2zOO4nLoX+QgxzkIJ+lvKaYnXUt1ZnUUTeYK5Xeq9eqomg0nOb5hvmChXI26/966fKlIrF3aFCq0l2tq+1bZ4ZFoxTNikEpSFEWiyFepTA9fbVjAzhvf2vn0SS1rpLDf6Vsshc6koAXjxOfN0PFOUsDUN9TFfa2TWaVonC6LTKHKV5OTLHsvDcjf9ehqefk+Ijr14856h2Dd4Tdls3pA7bbLbtpYnd+ynh+znhxynRxRph2ppRPOzQGCyGXU8toSGhXDltlI200t4bJKiIcrVasjlZceE+oSs/MGC6KjIVJc8TcTvZd6cv5oJc0EVOEODGOY87paKloXI5iQDYUd0OPd74ywYdhwPsuR+GwkIXGiTckJhVqQB47Jdyc5AOVMd7L8U1zFIeizM0KXft7vrq0UHP6qIfZJtxe/mkjpZSQY7XV99jCdZDneZJ05vpbCLdcArE8m3GzJWy2OWVHSaPUPq0hepTP9IpDciYGpLmLmnLLPLdkLqL1tYDzNRergQBxzntX+rwoXbQKmy5+ymf1nc1Bqx6W99nVOtdHm4N7KW5tznqNvWsKkRiVi42RTc4vghE9eksVoykResF7G2/2nr2+mqsGWdGMES62kd1YDh1SaxKCErtmRV2Q6GRWhxeLVjkALw9yZZlLESbNHhgA0tXv24ggtRT5/tLPmqPWjVNkHJUpJPool8bMK0lZmsteMrPtNdc/H+5KXqIc4aUugeX+lMk5KDEfoJuH0x7zEIdqrKmJUvaYKOM21bRd5fmLnai+0w5URiIsoWZFQN2loXaQg3zJS/EmLrLSFWtds2b9BSzVQQ7yxSknJ1uefvpFHn30CT7XEaCGYcfx8eZz+syDHOQgX1wiKvT0VU8edGDNYc/9XMjOD5z9OgKhJOc5H44437lF+smDHOR1KdrAE81nwAKy2f+6jf3bfLiH2V7xvPJLYQ5/2160fGWLbV2+tsGQ84N1v+ANtlX+q3uVkuY/Un/b6p0yBlz+NoNhE1kAq69iDo/iHElzioTmOWYobNMFFzxmLvGy9g3mnaPcFtyopK1Q51DvGfqeMAz0zlLvphgIux0hmKHaMOOJOI2kaUdK0fDiFCrOSCH4lKjJ+/27wJJLmYW+8/iuYyqp4JtGb/suI4Uzglz7X5qxU10qIcWMGRXH1WU0BE2J7WaDc46jG9ctIrT3EGPF6bqT49zSwjRFlLQHQ7YYfsF1mxEiuR+bPluOqfJna5fYw5qLtaFpvuW0mpGsFnpuCraHW+coC83DKo6WsWkNFrGljXh7aTrqcha0VSo43+r42NLB6KUrmoLtG84zHi4OGXqOH7rJavCGw1cwOt96BYZc5sVySdhfkAq2fOnVi/pdZcpaxCwvGHJeRywNuhErSmTlFBPR53TtSUhdThuTnZVbTHrx/qbESWGaUpPqvVgAcpTyBC1hjFrCRUygpciyN2bzjo2BiJJC+U7ohoHj9YqLF09m3L8dxNQuqW0TU8LMS2rkFl2M9FwMYTg+5vihW3Sdrw9qkN380dWJsyt5r4zVvRtL9A2VQr5L8zVy1Uqex480eHdjG2nHnzYtqEiNzlSvSWQOoQIJdfJKPXKQgxzkIK9aXjXRo3hOm0HYDFtR55Uyqc7rotiiqTFvbD6nAXDOFNS6QTdGw3aDLSSKvCFXha1sGIsFFIu4IdjCTPbHl8KYzoZeDWhylvpBYk3RiOpsNC/pK5hZox0O7xzrwaI+GDvQ4YchkzdMzZ4jyRVlwsrgxFHXc4WkE7lhchUMBBh3E/deustqveLmQw8jaYK0g5r7zdLFSLVOz2lgQtwi0uE6Ry8dN9cDQ+dwTNYP44gLka//yrcyjm/g/nMvsjvfcvdf/iqbT/5aVjqUsD0j7jammMeYVSuHxsQ0XqAp4PoV4iZC2uKSkAqjAss15tDMSs0NIo4YIs997OP4zjHuRstLGOKsZDFvwi7XL8dgaZTWZuMUIYTAJu5IFxvivVO8KIO3iAirlbe7PXTDilu3H2MYBm6t13hgNwWmEPjU83fYbEe2u8nSb6Q5DQw0e3CKZhUXM6i7ziPeM04ju3HHeug4Oe7ZXEx4wDmP+s6UoDzAS3SIMqbLzDPqCBbiTwTnujyuWg1knhv1IOeWc6RIqUOdUy5lBd36wvQuIVzseOnnf5HT83PSbpebOGXyQT6A1Ige9rw58IIdLENIbHchEw5KSJIS1aYok5rnTe7MUob84/NlsesYBo+l5FFKvkQlofmwaQZ6GzTJ8nZkg34+QKKkFAlpArXoJylITatTy25JRG3NglrWOSoKpiCX9SfZvTFGQlCef2nLZhN57tMjm03MxAAQ2SEidL3lE33zG0944tEjCudgkY6ljPlGa39wGviFXzYlfRxnpTol5XSTiCqcHAszzajeSu+FVefQkEiRnIdSKxM5JWWarG3nEWMM/QjgbQ1zzqKEKBDV8ifWkCd5KGqydyhCCqkq5fa5RTJxIrn/yiExty37Kv9ch+Wf83yPMTFuLXqPG4ROSl7YPMYThDGSUmI7BsYxMm63TGOydT517KZAVE9UiwyTxBE1sd2NSIyE7JEQcm7GcTfWvYDcVwUISXkOtexsEayM7Ic3PchBXh+yZs1bwlsq2aOkbjnIQQ5ykIMc5CCfWxkYeGt4a91n98mWBznIQQ7yxSAFU52d05bGvOrbAxnmVcQyodo5XmZMpkCtC0/6BY4g+f9S7fvzV1dYSivG2HzcGig1o8KaIx2Qz/0tNM0M7szIeE5HLELn51S4IDjvKQ5e5boZHMnPkoK2zXXUwsaoDWfpYIahB9TSUh8dIWrRa5etUsGnhQE3pWDYnDdyx7qzqKyC4XA+RiQlnnz0IeLD19mdXRDGwObuXabT+zNGGEY0Gu5skbit/Jogxcn61HeIRJKGHMm7VDy3j5rDXwV/RUgpcXbvAeKkpr1O2Vhe6lEjhLCkBi0w5NxehqslogZ0EnQ7IqJ4MXyr8zkWrYOLl+7zKz/1fzOsVvzr3/7befiJJzj+zm8jhkDoel66d48QLCVLag28zfAqqW3qSHEOnORUOYHOO4beM03R0EhxNQN7dWTLPVjN2AVybRE1wfBNaT9dlklyo8jyafPV2mCjCpqjOpS+LO2dpsjmhReJ44SGWJ3hoLxOZwytOHLVYmRsVZUQYkO+yO1TO62pde3H5dwuXKGUoyro4n95vWnIUy3BoObXLs6kZHwzjxczK+XnpKYNM+FqacRvKijLvtIGW09JObsIhKCcnUWm0NodrB2ds/Xl1o2eayd9vk8WS9ey0+zXbpd44SXDKWMxM+U67yYlIfSDlbm0bHm1F7EoIJkQUtZnl9cmVUixcTye2Sv2DDfbJ0pnWZ0bwJ+CIeucxqXmnmntDfNz5yEzY8i10i9DoJ1JE6WO5qBZIjy7rn2WzmVSJYRUbVQxKsVAE5M5w6b8/NKGIVgK8GJ7ScnGdcwdoHU1yoQQVWKx3zXzCYGYx/llJ96DHOQgB/ns5NVH9FBbmMtCNRsqi5JVPp+jYdTwRzovdextVMKcn0ybdVvby/JqX+NjFEU5Kx+Fdewkh7ArG4IzEob6iOAz6cIUbJfTYhjRtwSkskI4LEmGYIE6vHf0nc9G0xymqevyYuyrwVqqEiGIy2XIz7ZNBCRlFV1lUT/VZbqMUuflgSh7oKuFmEvk9AdhAkmMuws0JnQUNDli3jTjuEVjZN0JK98zdh6cELYbznfn88FkOkfDlroDi0eytqnRlGsnRuBIeQPXosw0SnnLQrfqJcbt1hjolYjQnKjKnlb3+9J21N+tbiMqdfNcsNedIk7oegux6gZHP6xYHR2x6gfWqxUOiIwkFVIyJukUzNA7jkZC0cxYKkqGxmCfuUzs8R7xjmma2E07NHZ0zkLtlXqbImiVWpRdln9UdVvy34XUUO5tFZ2iTEm5Z1ac2kuqQponpnkAyKLdNUWm8wvC+cZyPTaEjjZCxv5nraSs3DjXpPdoxsF80JojlSDlb1PQS1Wdc7XN2ve6TARRKfz7qp7mea6Lstl8MZKHPWuOdHOpDq3CXxcmuXRNKVMIiWlKbDaRs4vI+UVgs4lNW1v93WRZgC62ke0Y6TtH7x2qc5vMa2SZR0qMcH5hMe1qUbNCGYLlQUwpE24aBbKhIxCjRf+oES3KN8lIR9oy3Wmmens+WbQm9Ri+aJPm0FLuK31a6lflks66R6qZu2L5gqatLGKGQ7R4GewtHOW2XEcth8w8gVKy/Id51aCuVcz1iNFINjEY6WvZCk29lDnPrti+0R5JDzyPg3wpilNH9woq40pXHOnRgdxxkIO8BlmvJx5//D4PHhxx794Jl6J/HeQgB3ldi6jQ0V0yy5Q99xDBYyl9H3n00QdsNj13754Qo//MNx3kIAf5PEsBVApWkz+r3y0xnfbEfuk5ewbWSxCVYg5U7XuzpbTFpiq2LLNptuIiGZtTJ5BcNWSKczM+2fynRSRa7MTSJDT3L55hhaxEj/ryXFYRimf+bDJkxpClNN1lT/XW3L1smpwuPWMmFjFViWHKeG/BpXLbxgBJ6Rx04iy9skAKE1MofQXEMUfGKOLmN2Zcuxq/688crWSu936PmxOfGa1LOpuXx5CrGVv0ymeBQ3P6jRQCu+2IoHiniDhL852JL957svUW7z39sOL67dvEGLl/ds6U026YcTdkJzRdFrESCjI2mr2+UoyEFFEVSx2c2n4SMhNmMbZf1gbcRE9oqEG1xovHLq7fw+u0QbzyeKyOsdIA0ppI00Tc7tidnqPe0a3XOQV6MyYWc3MJVrfRf6UY5xdQ7J7BaK/8FQeUaokoVciDW/baa37+nJ6pWYfq0GvXn+b6/RbV/P7L8PiiPbMZLOOMSpiUMSTGKeWUKu1zzX4kDqbQEWKySO+l+tUg0mDI1I+YxqbtKcUzm01KM6mhPKGSVrKkpNk5sV03JNue6hJNqZQWXF+1kj0AXNexvn6N4fiIEm3octPo4j3tzH/ZJm2aXijmppmYtNeU815TFof87ysjRTVjsrW5FRJTaht1Dxcu/Wsct5a8sz+G85xuP58X9bxMOF6hBQ7yOpPnn3+e+/fvf17fcfPmTR577LHP6ztej3Lt2jV+5md+hq/+6q/+gpXhNaVuEZ2XxcpeJUeZyMtiimqsv5TAp5y+xMgXJd6Gy6QRcXnjK4bLlDf6HKY/umJkjjiEznU4EXpvJAvfmXHYDx3iHEPncRbIIRv+Z1JCwhiLRZkQskEwmQE/uQ6P4lErmHegCY3JiBweQJrcbdYSToy1l4qip5LDZ02ZRLAzY3gmlYzTSIyRzXZkHANoRImcP9gwjSN3X3yJadxx/WTFw7eOsvJobR1TJGpk2poyLlFZr8546c4dpmnk53/2Q6RxZHziIdZ9Z7kKEWNSp2is7RSZxgAxoXQg3uqikvPBeahpPgTwaISwi2iEznlEHSGAd44kq8aQ7xDfIz6i4vLGF4kpEmLAJQs1WHfk2fZP/mTedisTgHxYaw8BMPRHHB0fc+PmCY8/8Qib3QUvvPQCcQzEs4mu67j20E1jt/cWfYXkLDLNaqDvE298aiAmS/MQYuRjn/okD87O2J5uCNNUU0SUvj0+WbE+WnPv9Jx7d+/TOaFzwiZZhBFVJZEZxTmsX4lyU6vV1LUqJ4Kl62k00kJMiDHmiCJFETJVyFL8zISSq/SbesSKShSrwxQsB6fECGGEYGzsFBNTzhVZ53hhzC+eTI5gkBU3TTiZ89NRDrE03hdCJUFVBdzNimf79JTs85Bzbx6dGCkrTRtSUkKJ0OE6VB3OtTleSy7A7AaCkHQixSmTerQeahsuFUXx8nlaa/sbW45CUF68t2WzDTz7qZGLi2QH3EUevjxebFrz7Kc33Hkw8tSjxzx5ew1ebbrlTk9qDN7KDNeyrOhcJbXciufnEylELo5dXjMjhciQorDb7bjoPKcPErsdbLbRoneI4ryxjrebQAhNSiT2JJchqa3VKffVPpEBJySE7RZ2OyGpIA6Oj3qOj7yt600V9tV3XTb+1efw5p8iQuecMbEFy5Uo4ETxorbmr7yNh1VHP0bW9wIQGV1Pko6QlBQjTjzeC13v6VbQecFFTzjdshvtwB6TEhHo5gP+4iDUnK5EdB51CpTD+sFWd5AvMbmhN3gqPoW7nMUYMCJIz2vLY3+Qg7ze5Wu/9qP8pb/0V/lH/+it/IW/8O1cXByIUgc5yEFmOdETnonP4FkSFhzuEMHjCnnjG+/yX//X/z8++tFH+b7v+z184hO3v9BFOshBDrJ3tq+OO42x0hxzsEgCqIXQdItbFw80zGLxUJAZ5zBcw1z3CtnCZ8eiQuSQHG3DHPkao3FxBimPJUdrJtvmCpYhYpFnMQpBBTczzjz7v+3FUFDq81pvdlUMm8y4b3Fukfx5SiWFcMaBSFycn5NiZLPZcPfuXdZ9x9FRXw2QikV6RSGG/G5Vut3IZnNBjJEXPv0JNEbitaMcgcTOejW9cyYspJiJCymnpcp4uJGUS5vNuByJHP3VSC+osyDJFMy5wXfFg8ttqsXAag6O0pBPSifsQy1Lw36+oCWP5Au86+n7nvt3nuXT/88/YzduOd9ccPPxx3jnN/0WhvWaYb3ixo1bPPzwbZxzrG/cRF2HiMd75cYNX6N4pJS4d3bKbhwJu8nqy7Jv+2Gg6zu225HtOOb0OBDU5TalWCcsTXpT1X279H6lxS2oDpW8YMb9BojOEU0EspNkaRutz6pG9PL8ZI51MUoltagqpMjF3fv87P/2f7B66CbvePe3cHTrZi3vbFzfq0PGhAshRSipz63PzM49R78p5V1wD/KdS0e/GVpMuf79kMlaOaJMSkZcSdlp1aKvN41bG90mrWrM459qE6gQprYDUCs3ZcZyS3taP1xsAlNIPDiLOcIyy07NVbH0JfDgbOJiF7lx3HPt2NLSLFz7lBylROvfy4bG5p4o0xjRJExdthkUskcmKYQQcE4YdxCimsNgxjQl45ohR4WepSl7ie6R337rjU/wte/5dpI6Jjp02fmoCiFAyNGhRaDvPX2X+0v331Hm794gWHzHXIDmK0HqWBehRouXHIHcAdplx+XOEWNit7XISVEsQnxSEE0IzvBn73AduCiIJna7kG11eWnMWHkZkIv9aNHZZLtJwZDtPQc5CBjJ4w//4T/MNE2f1/f0fc//9D/9T6+K7PEn/sSf4Id+6Ie4f/8+169f57u+67v483/+zzMMX7xn0Xe961285z3v4U/9qT/1eXvHm9/8Zv7iX/yLvOc976mfnZ2dfd7e92rlVRM99tlvVb+tH8yKXVGDbXFlZjDnBbUqF25elY2lm3MUlo0gs9oEi9TRSTZwO0sN0DmPOMH7DpdDnxWihxPsfjGjpEJVqjQlSJFEDsWUP5dcgqrhNHUqKQ9SztVlEfG0GmZjjngRMtFj3I3EFBmnLSlF01sVxnEixMBms2O3C6ATqpFxDKSUGMeRi3MYfCJOnRmDU2GCWg5BTflkExPTbsf24pxpt+Xs/kukccvmGBh6nOutHVNASWiIFOaBQIkPRrVq1w14jpsgYpEIUiqGTZejQ0hWcjwJiCHinOK6IZ9oGnVETalIrtECKLp3PhDpXv7ARsFDigo1hwZzzuF9x9APnByvEa+sNmuSD8TY0fc9x8cneO/xWQGZ8rvNYOxYr9d1/MUYWa/XbMeRqRuJISA59VDbFs57VJVpCkjn6cSTIoRFqhVquLdmQjR/XNbWm5gyeT7MP0W7nYOttWbz/Xk3t22N+FGfmcMVjiMyTfn5qb5jUWZaRSu/Y6HTSfPvfAgtxI7St/V3s27QKOwLKQcTqYon2BD1DsQFI4g5G3+i1jPFC6IecEzDsmgfQlPHsmZp83yZx2JTv/Zclc9bxKRstpHzTWSzSex2uqjook75+ZttYpcS25uRmA/7zjV1nO+81H+LlsnRJkI+ZGnau7gQPlJiNya2O605Gp2A9xk4iJmpXXpEtKnCPM5KYcpfyzU+K+aqjBOMU1kX7D2dzwcRbe982Zo1/y4HvuauZo8paW+as9Py79yu3gldoqY2KlckVcQS2mbQJUeAcs7SU5FJihlU0Kb+rXfRVXN6MZvLnvFyVT7IQX6Diajg8ax0xTW99rJEj4Mc5CCvXW7e3HDz5rPcuXM9E1cPcpCDHKTZe1lxoievGFHrILOs1xPvfOdzDENgvf78AqQHOchBPrO8nAf14u9L98gSS6oRNEskYbvRFYNv8fKvZ39zMiwm5YI/FwzaZSDBiTmS+Jyae8ZFpOKP1UxZwB5NhoOKFtS6wa+ZoZ2CK6Vswi+4XAaYxMKDVmwqZTKDYcqJGEMmetjzYrR0wWEKORpAWlwXY2QaJzqnpOgbp6bs2EjGNAzcIMZAmAzzHLcbNAWmHvCekgakpEbejxQ7t7Majlzaq16SndFazynaeBMC2XmyOCZ13i+fmxurRmDYx15Kp1wGFefvZHGHYfkxEsfE7vScixdfYgoTU5xI42SRO/qefhhwIhwfn1QsUHUeG11X9mMzhHddR4iR6KKlzU65b+fCVOe8GM3J1Lmc2qYWeh8PzG1bx9M+tpbrtCAd2HdljF3VaAX3azHkS213haiaI2PKzowxjJy+cME4TcSMK7eYYVOaK56ZWybXqf26QsyLD2dM8NIL9i6qXKCCD0tq5p9k1O+qaur8nP32KRhya8TQpuyNKaV9XCGjTSExhUQIFn15WdHm3flXCErUSFh5VM32oIsXvZw0i49gZI9CclmMC5rhYSSzQvIopBbB8FJosdGyzule+80TtF+vOb6xYtwFHtzdLAg5hYQTExWrLk3hGrvgsj8uN9MeQl1LIIv+Mnx4sQzsXV/ebb8FpyXFfDvSCtat9WHFobWsaNXGUN7dFre08d4a1r6bvfsOcpD79+9/3kkeYMEJ7t+//6qIHu9973v5/u//fk5OTrhz504lerzvfe/7vJfz8yXFhub9l170x9eIGighRhCL1KBpNuZrNGqe945hGFivVwx9T9d5Om8Gcuc9ne/ovK8EkDZ0k8vEC82GhJm0q3WRNqOfy5/nT7w0RlRj0lm0gIhintyaLPyVE9juRnbjxG6a2E2BFAIpTMbWS4moltKDpLiSn01ynsXOZ4XbDNve299J42wrhRy+TkFy9JJM80shQkp0KVkklGTKfCjRE8IEu8D23pYXL+4jziNdj6ZEDMXCm9srKRfTlvu/+ovEGBk2o4WXC9GiIHgjXFgxXE7P4Ckh6wQP4pESGSJ4UuyMwUowJd8Z0SNOQBIG53B0hNTT+RUMJ5yfnfGrH/0Y69XA29/yJiKxsryL6VZV5ogwAl5cVcILsWceZq2GlpXjPM581+G7FSkFdhd3eDHc5+LsDkfHxzz26CNoUsI1WxSd6zJT1e5OKOpAUo524Tqb3GKxZh596DbXj65x7+gem+2WzfmGcTdl5SaBF7Z5wT0eOrzv6LreCCDiSJrm1DSVNNFu2XtqRo6EYGO7OdAAhT0vCzq31QIcMYcIS/XglmeEgO9K5IMSu8buFyBuLnjuF38JFy1lzSiO5MvxNJu8s6LhvI2dwqRfFF3VjOreA1KVQpsXTY9VktdsHFyGTZNF/QuHqaQY2W02OO8s8kInrFY9IoVFH21ipo6UWdfTFJmmWDW7lA8kmdtlodWihWcU3x6eBDKLtsxv60eYJmWzTTz7qYmz82DkhiuUxqIMF75EmhSNsN0mHmwTxyvhxJf0NPV8UIGBemidG8rmjZAP/xaJgjQroIKtS33XMfSe7W7Lg9NAiJbG6Pik59qJp++NpZy0zCMLWOGd/Z5iJm1ADiuZPUqgRtGYFHa7yK998hwRYdoaAWaaEn0n9A56D8QmpYvMR6U5x+JVJzjaM32eP4kUE51LrDyog+gMDCjtlzDnj5k4k8dF3o8CniRK348ItsZG8WiysR3V2nYMke041qVnipExWLyVkmuWsk7V8ISZDd5bmJYUM2lqwXg/yEF+Y8stvcUb4hvotd+DYg5ykIMc5CAHOcjnQ67pNZ6KTzEwXIrmcZCDHOQgv9HEIl62KZwraArJcAvfebquw3uPk0zAyFE4nHM5XXd+oLam9BbtakQbQx5LAx6IOYA0n1eMJmOlJRR/8QgPOZpGiBm7TQlNBS8oUUbs38UHrNjhS1SRYqR0GdxepLMGaooSaT9XNNpznSqdAXQoFjVawYCuMBE2gYtxZ9ibtzCrszd+bi9VphjYvvQiqglvXjy4pIgkS1lTsT3DCJtGL62ZHTeBKCT1ZLR1ge0aV8QcNgVHUk9yHbiecRq5e+8enfc8/NBNLE1z26OGJ7ci1XK7l/pleRH7OJOlZOl4/pd+mV/9v/4R02bD+OCUR9/yDF//O34r65MTjm/dMozQWSiZksm32ALm8WSRq1UUnHKyPmbVDWy7LVMITGMwwk4xDjgI+WG9t3HsMoY620NyPy8INXrZpl3a35VmKBcUDFlrP83UmvmZOXD67MjUvM75TIySdi7l68LE2Z0Xmc4vzHEQQR05hYcs5tZ8p17CkEsfOik2AqXEDpZmTldnuoXRvS3wTFopH2vzjzCFGg1YCmYtUtvZHF1d7aOUStSKZMMuR36fnQVLm+XII9mRNE/iBTZcCFUxKtOknJ5aupYYXwYjlCULoGT8CUHZBaXvhEHmK5oWmNeJvdYvUUdKc7k8psu7ipnFOYt2HGJgN6Y8PoR+cAx9ISTpou7OlejK5pAcK+5b3j3jwA4hqkXrvn86Iggx2DUxmT2hRGtubWnUvtXLrIyXw5DbCqtlHeiKT/PeklCHQftJCSuVtDqKex8RpyjdYiFI+XExmX20vDYmtejpYmWoz68kkebPkqO+2I0OUaEP8kUsX/EVX1H/rao45/jlX/7lV33/OI587/d+L3/jb/wNnn/+ed785jfzV/7KX+Hrvu7rOD095U//6T/Nj/zIjwDwe3/v7+Uv/IW/wMnJCR/96Ed5y1vewl/9q3+V//K//C+5c+cO73nPe/gf/8f/kb7veemll/gP/8P/kA9+8IOoKm9729v4wR/8Qf7SX/pL/MN/+A/5mZ/5Gd73vvfxLd/yLfzoj/4ob37zm/mjf/SP8vf+3t/jn/7Tf8qHP/xhvvM7v3MRleOHfuiH+FN/6k/x0Y9+FIAHDx7wZ//sn+VHfuRHuHv3Lu985zv5wR/8Qf7j//g/5td+7df4A3/gD+C957u/+7v5gR/4AUSEf/JP/glf8zVfg6ry3/63/y3vf//7uXv3Lt/wDd/A+9//ft761rcCFhHkve99Lz/4gz/IP//n/5yv+7qv46//9b/O008//evqr1dP9KjKgM456FolPSu7zjm63tN3nr7r6DuP9w7fzUSPvuvr5lCUfSNzGKMw4agMXoqqNwd+glnvKQqRYh7Z9klWzjSasTBYtAzbRCzNwXY3sh0nttNEmkbibpvD9Fvo/ilGJJkyjRp5xDmh733di0VMaTCjdqRldlocEZDOZRuyLeKSbAMRsiF+36Cvdk0aJ3ZTwnU9ro+2wWaiRzGUK0rcenanD4yUEu25Lm9sZqB0SA0P5ho9orRmCfmGKT+1tYsCn6NzWApH85RXI+MoDsQzJeXe6TknIRrhpTxbijJ+tQI+M+aX35cDVSWCFLKHYGOo7whTJGhgGhMpBnzXsRpWoEoQS2+RgtYUErNRfQ6vJq2y4BzrYU0nnjGMRgJI4J1nCsHS5iBETTiBvvM4Zz9t6VPWzBaG56qItsqE1P/W+3VW0EukDd2fZ40CXJi1jQZhWYe8y/bomVQAOQpGjJzfe2CQoSpBioKeiQpqk0uKIqgsCF2LnhKbE7p3WDDC6zxbVQXnZoWv6emZsJC7u+bHywUvkXK8c6hzeJ+jO+QcQClY+SXnkdQSplAUxFWlvTDxNf/buUtQwKz4Mjd5UmM3j2PiYmM/rhk79Rmt4pirXiJvTJOymxJDZ6SpuU+03iulDdrDjJYDpuRwcHYoUtecB8qNWOqlEOxAobn/+s6xGvyc/7Mq+9D3RvLoPOhoRA97nB0ayhqQs1gBpryeb2yti2M+RJSxkNf0GjS1OTlqU9f2Hy9z3JnHQS6zk+wcsX+YKee09h2lgdUOa4qF1pMyN9tOypenfMArZauHu3rF3OAlp2VZR65c3w5ykN/gImrUv7WuuaE3DiSPlxEnSt8EOUkK035I1kYEpfevfI6fkhHQDnKQgxzkIF/aUvbafVnpiht643VP8vBiQP3LSS+OsF0xbSe61YiqEHc9cbeiF2HlL580DnvsQQ7yr1AytmSYbTlPNybLggXLHLnZfqQSPEo0XldTr5Cfl3HiYiQsBu8F7LDEkNuCqRa73Xzin7E2nYkeGD4SYyCEyBQTIQU0JjRMBZRb4AktT0MyaaWUszV0m9vKXMJKcSgpLRa4hn3nKKl/lxihaDJ/l6RGkEk+wyEFKdG5TYIjjjuKQVSad5ON7zPsUtIqaP27Yr1QSRAVuZcZEbfU7AUuaSyuYmkRNruRoe+Wzy4RA14OQ27+PTdSbqeG2VOvFCMSOecI2x0PPv281ds5hpNjHnvmTfi+r9Eq2ijHLYbcwq6znV+yE6tYauWMpzqXI/Fqyk6oZly39EFuj3SkM8GnvqPgTnujV9pfM0Y1Q4tN5Ia98VHuXRCt8heaImmKuM7h+r6+MUUlTRNhOzJudoRxBBTzmZrx/kVXmCmHuJvMBtN3mdgyl6PgjbUF2qFVDfYt/sZC2lRKudYz2aO0ZxLzVoPqXFkx6xLlWOcpNq9NM/mmWl7y31fCfntEDWt6rVGhp2A/FTukmWtN37ZjTjIRIkQ1LNZL/W7GkHV+fdNWi3pg/VTGqzR9MA8Iyc6Qc5HMoVOqg10poa1lM9lDMbJHC/GWy53M/m8WER0g2XsaHayYi+Y1oHVVbUWv+Ff7yT4gvxwf+5fP69ay7+q8EV2svebIvJxziq0XtH3Q4s21AFbJeQ0ulzdj56CWHuSLXL7/+7+f7/3e7+X8/Jzbt2/z/2fvX4NtO67yYPgZ3T3nWmvfzj5X6eh2dPNFNrZljO2Eaz7Hb8jrDwEByk4gUP5hqgw/zMUEHBkICQTjJKbgBy6FUCkoMMkLleJLIGV4gbeIIcE4r2IMxo5l2brfj85t770uc3b3+H6M0Ze59j7SkSxZR/YaqqO991rz0rO7Z/foZzz9jPe///35u+///u8HAHzwgx888Nz3vOc9+MhHPoLf//3fx80334y77rpLMywAP/ADP4B7770Xn/zkJ8HM+I7v+A780A/9EH75l385n//hD38YH//4x7Gzs4M3vvGN+NCHPoS3v/3t+Df/5t/Ae4+HHnoIo9EIf/3Xf43NzU184AMfwJ133nlg6pZf/dVfxX/5L/8FN998s2bNeGp7+9vfjul0ij//8z/HlVdeiU984hOYTCb47d/+7QNTt9T267/+6/j5n/95/P7v/z5e8pKX4L3vfS9uu+02fOITn8jqYL/xG7+B//yf/zNOnjyJb/u2b8NP/MRP4Fd/9VeftlxPZZdM9IiAjEFRJlYOEWwCIjMCR3SLBaL32FwfwzUbaFwDayrljhzwZ/RhAavOfAgR3qvyhioi+N4LcSQIG3ax6CR1iTrONnseaXKrGJ1phlcngyCEj5idWGXosUzYDTOC70G+k6BwiJL6BQAhgqKXwTqy7uQ2VYVoHi4UKS9DRobvRHjQnAMprZjJZ0AG+xTMj8ruJdZ7p8fJ3qUUSp319F/ggK7vQSAhH4BEqYLkKQgVgzzlW8wOQoqQRp1cowZpVVXFtkC7BrYNGAEghjMGNjDQd2DL6Ofn0M93ERZAdIBhSbNj9BrWCis/MWhz+NhKf0iLNaX6FOo0CQElzfyjtsV41GK8Nsba5jqCj+gXAaKm4dCMHHzfCTvUq4JDTDnX0twrCwvSFDJpNz+8kGPseIzYtmDDWPcTbFw7QTtqcO89D+DRR58QB4gj3GSEcdvqYk7SavS9Kkf4JLGUnDElM5jk3KbFjSqZGK2bfHxAkhASh8tn6jUJY6j4b9BcmZWN2hYbm2Pty5LL0/vivPQAHt2bwhiD1jkE6xBUCmfUSNnSDgOrn8/mHXyS6qvUCox1MM0I3vdSTg2C5wWYvqfGcM6/qK56TmFi9V6GLIwxCD4ikBJmwLD6DngvRKbgZznQDiT/tjjKQrypXGeTpD4ZgRnGSnkqf7UsirTQpONUiAFdF/Hoo1PsTT1CHzW3Hz2lI0YVW5wZuHB+Ad8HXHFsjIkbp+ZX8kQEGaBpGKOWsLUmL3mMjK5jnDmv5DdvEENJyRIrZrX3EQ89MoOzhJ3diD4tXAgYtwYbE4PFLGA+Dyr1STi06XD8aKNqHYzzFwJ8F2BJFhYcgRCELLS57rDoArrdAA6AX2jV6Y4Am8giOk5GLvs5Eskojag6hWRIY1hxVVtA+0CURbKPDBiGtXI/yj0pQzqD6zSW4B3BRHnl2tahbRv4IKQZZy2cs+j7HqH3sEQYt05Z2KzDNieuiAAERKqs5LVtBTQIISKp1hAZ2DaP4Ctb2YvWDvNhXBGuwAijF7ool7Vdvx3wxqs7WCUzPnTB4s/uHynZY79ttIxvuH6B7fHBB/SB8N8faPHghZVM/8pWtrKVfalbmmuXrUGzSpUG4KYjHq+/qs9BnWU71G7h479xG45c+xhefdt/Qz8f4a/+yzfgzKNH8HVHW7xuMh0c3wXCn943wiO7X94EmpWt7ItlCaqRpbxiqiTr6AgWHDhGjBoHM2phNTU3QTEVIC+rYwwZ9xXMQRFRxVNj2tkTo27WCQVrRc0LSEHAhOlwASYy9JquLR/mgLAiD5aTwnXZnJUQgKQImq9bA2O6FXwZwajoK3Jewi21TLSEdXDCiVlT1NTwFKcYI6WT871TfDVy1ACHKqdAU3qj3DeTEXK9GQw33XCuzlSjgkFZsG1EGVpRH0MGhoOoWQcg+jmCX4C9XhblH2BAxhbVk/zYXBoxY8harqp+aqzOqpq4ax2atsH1r7oFh08c12c0mGytA0SIMagyM8pGJlPVqfYV4oJxGcXcjGuQ0ms0MaDd2oR1FufOnsfu7lRVVximsXDWSr+K0n4hJDXohPFq2XOQuATjB39nteT0fcx9Il9vwEzQfpUC77HUKhg4c/+DeOSTf4Ojp67F9a97DaAbJ3eeeAKf+x8fw2J3F9O9PSBGWGMQyeT4jrUGzrlcPCKC73p89mN34sLjp3HDG78Sh68+WeqQDMhaVcOV/pHe9RpBW94Elz4TvHp4TCLn1IomDIXRwYixLxgyD++T+kxJ7KIXzmnnNQ603PWrcAqQyFAAI8IHxu5uj64XTL9uukG7HWjSxxbzgBgYvObgjEvVVwZVEtEe6xKOL8NOiMBsrteJlDc6AiUOxEru2Nn1MAR0nWDl6SbOEtqG4HtR45AN1YTxyGBtIhufDRjzhcQjCMjxLo4S52hbgxAYoYuapqiMFwRkdRDWOi7EmlTOMiKksfdgTzAdq5EmfQ5JicVIG4zNoMoPwJChIkiprUk20FprRF2bJa6WYpgcAgiAc0Y3ZXIattMttGhSJkmhJVg5GU0tnuNCANkVhryyy9ve85734D3veQ8+/elP40Mf+hCuvPLK/N3FCB6AvBv/9t/+W3z4wx/GS17yEgDAy172MgCSoeBDH/oQPvKRj+Do0aMAgJ/92Z/Fm970Jtxxxx35Gj/5kz+Jzc1NbG5u4u///b+PO++8E29/+9vRNA2efPJJfPazn8VrXvMa3HrrrU/7HN/3fd+X7/90aVsee+wx/M7v/A7uu+8+XHXVVQCA1772tU97j2S//uu/jne961141atelZ/t3/27f4ePfexj+Oqv/moAQpK54YYbAADf9V3fhZ/7uZ+75OtfzC4ZSeb8f85OBHT3fOSI0PcI3mN9fYxx26jknjognFw8VgcqgolgWYKUnfc6EEfNL7gAhwj4Dt4HTKdzDfaJN+UM1ImXyddqqoHsUOvnZIUtK8oenDxiWOtgjNMd6AQKHhQCKEaQUhINESiFJIXaK5cPiZBQHAgwZ6dZCBYA0j3VYU5jfgQKM3fgpMsFCARDw0mwzBFUmI5pImQNYINV0lCDqsvOn3jr6UI5TJqCpcXjIQQQYgQsCNY4uZZ+nbJdJCJODAvE0KtiiUzq5T/Nh5ly6hBynRkqSiIpXDsI0GvgVJlCcM6hbUcYj8dYWx8jesA3AGBBZEGGdbHFGgRP0/dSVXCRo0v+mxzAoEZ+eozggsHhI4ewsT7B6SeehLMGgSIoiKwkO4MQgi6QJN+eCEnEfN/UiJyZ5wPXNXmmuT3KK1besSSVVveDTKvNC9fCzjfGoG0aeY90UUGU6DvSbfc0B2VsGsSKhJV2SSRZTOekL3e9R0z9vzYySmDxxbFB6WPi8FL+M/W5tHBMXZIS4Yc0V2UszOHkjEclN1FViLSolaLU1zWlJ5Gui4hANHyAsihdahb9NUZxbPf2euxNg+YQTQuUetlXe3Pl8/Suigxej+3NBiGqk5nffdkRbh3QNoT1iZwfAyNt/IgZvICyzzn3gfT57l4AEdD3Sq7Q8lkDNI6wYIb3KscHYNRYbK7LgswAmM8BS2EAKYtfTBi1pA67EjRC9ZQkjO88BGfAZbliyyKo/mtQ7zoMMpCd60Roi6z5dQ2EqHXQNar2lHy7AOnzWkOwlhAiqeKMyfNTWnxZY8AsRKNS0iLNJ+NvLIAOkhxlABkjOyDk5vsWpStb2WVtnMbm0m/HPMY2bw8+W1kxQwxLwPY44uYjHjZxgJmWgIRksit5rWGcOhRwfP1gokcXgE881jxv5V7Zyla2spW9QLaaa5+xHRoxbjriLzKvAkCLJ+66AbFvELxDP2/x+F2nsHv6CK4aAxgPd2rNeuDOh9sDrsNZPtyaAxYxK1vZyp6VVeHkEhxNwWiwKAnECGMcnJPgPiXgqLpGUrtN2+4isyomKF4QY1aCRfSIkdF3CWOWi0l6gAIY5PU6MyomR1bTyKQLDY6mTR0CBxFIce2MS5Nus8vB5oLZIFKOz2pmGBT8FUBGYaqUscu2DKPUz4IC9SZEipfPGQCKWmTdzJLR6n3SCdVFMlhDA8wsXTdqkQyKKnQ+JJeDNXU55dQYCUNOM2Qq6gBPYYBJt1xSPWMmwCz9lfBV+csYk1MCNa3D1rEj2Dh8BGBTCCEUFXNdevTlJtAKrTkXxNBdqIwGFoYJk8kYbesw3ZvCGNlkJErRgm3HGMEkKuKk4QtCpXjzVABlaZQhhqwF5KVuNyB7DOII5UpMjG5vivMPP4q1rS29tOCs3XSG0/c9AL/oAIhSSdS0M6ZxsE1TlHa0XYyRKMqFxx7H6fsfxNWvuiX7OEkdPmi6oJJ6Zvhsyxhy+uYgDJZAw2fOfaiofFCK11Q4aV21ifRVIblQMFLaWwHKikdyULGRhpjIogjd97HEb5bKP7SauCSfhCCxNj/iQVwoPZMhgKzgnK3T52ZG7wvun0QpUuyo6hhgFoIHCIiBBg9EBN2oGRWHL5jqqDX5Wb0PGbNOBWS9gLM0SGk9iCVQDvPkOgOw7x3cV8FP99UShpzHEgPsT3MzPCddzFAh9kksi2QPt35Pmj0gE1aIMgEsV4P2t1SrKW6X44a6iz7FKdKVVxjyyl4Mdsstt+A1r3kN3v72t+OP/uiPnvb4J554AtPpNJM8lr/rug7XX399/uzGG2/EYrHA6dOn82c1qWR9fR3nzp0DAPyTf/JPMJ/P8da3vhXnz5/H2972Nvzcz/0cJpPJRctz3XXXXcJTit13330YjUbP6JzaHnzwwcGzjUYjXHXVVXjwwQfzZ8vPtrOz86zuVdslEz3qNBdEUDYuo+t7dMHjwtmz6OYzTHfOwzknwWIIWYLAIGNBGkiT4LME7WLAIF8Zc0AMIoHHynANUZx2CgBYGZnVjB/S5BJT2gyI86hKEsRBA8TyDBHCQE05HykGIPSZ/UqpcAxk8ohSETgOc2lR9a1MzDE7a6l8g3osXujAG0+LEAZUaq96QGOQPcTqjmn5AStO7Gg8FhfBGCXWJIdK6qUEumVWImdBtslJ1mzbgqjB5x98APc99DiuORFx/ckxKE5AaGAg5B0DgGMAw4BtC9geZK2wEG0DWAwWHmCALGWHMU+IECUHIDntAIwEn0ftBE0zQts2aJoGzknaH2sd/NypYgVX9VlSU5jExiX5nJTC2gdRckkEHyEIGTQTq2l5xAnY6ibofcRi4XH2zBSWHI5uH9JUP169N8A2IzjNXUfGYLo3w5knz6PrA6azruSzixEhvTs63RuT+gtr28jn4ogRJL1PRDlEPLWU4ictdku6Cfnce4+9vTk4xryLIS2Ca+feNQ3Ga3JP33vEEOAJuXzQOgKg53NeQCXzvkO3mMFaQjtpM/kpOUQ5xyUSg5bywqzIbqKwtcnAR4ACgUgkHGcLuamzEYZUtcYk5ZCi/GE4gQLVgjk5eTkFR3KyhIyTmcJcyiHOPKP3AefPLbA3Czh7wWO+CLoYhpBKjMFk0sJam/MoQh24xbxH3/tcHo6AD2l4Smxp5HypbWOxvWkxGRtsbUr+P1HeiAAtBA9QAkzJFVoWdsyA91K2lDHAtcLutqpm0/cRs1mA96X9UjVlx52KBF8mkFlgfaMRBZ4LHshOrtSztcCRwy1GrZFhKuoiVftxcm7rpcNwGXFxc85hNB4BxiGq4+uc5HH0nQcFgnc2D48cGf0iIPRB3jRrETtVnOo9mIy2gYWPET4auNEITdPCdxGLmZdcqyjvSVpwkxE2N0jmK9J3MUnKAkDoPSKgih8rJ31lLy47Go/iaDya/x5j/AKW5vK3Gw8HfOXJDtvj+BQBqGKHRoyvvW6BI5OIrdFF5D5WtrKVrWxlX9K2mmsvTyMArz3Z46bDHldsPL2M78pWtrJLs/3B8giOsiM6cMRiOkMIHv1iXqVm0fU3M6Cf5Z36GhzM+EsK7OlmjBqnZY7lGBYMqCpIFUUuAVBmKrtykNJrK6YKqgJzpGlhYw7g5U1cOVpbBRZzEL9gyOmauTx1HHLf2qLChqn6swpoQgOOg8rPZaGqwjRgbeRZrHNIBIlq/2Fpg7qMBFVmthnPNtaCyODChQs4d2EHW+vr2N50ADsQLGQTlmy24RjB1srmSKMKLUZwwBLxpcEzZBhRn19SviuRpAKyCKLgYY2DdUbTbJNuhjSI3ijeL1i9NFkJ3u9XMJEvYiybJImgisQE25gc0yACfGhEnTwwZrMeBgZr4xF8iPChKLxQY2EyNk7oux7T2RwhMPo+oGzmS82sO/+RyihB5dLWtYquxF5q6Le0I8p1c6xBfh657mqMN96MyeaGpOKIqtweAoLXzY0MsLVwDTDe2sTVr30V1g5twU0moshekTP6rhfl6fwalD5438c/gXMPPoLrXvNKXPnSGwsWm54vkb0GPUHHBBp+kt45FcCWTs2AVxVkSddNUt9ArseMrVeh+PoVS8fk4SG/u1XfrI/XxwsxYj4L6H3EfCHtnrk2+lyuEUJb/aqKKnlEiKKOkYYkwTireEDVrtYQxq1B4wr5IsbUmX2+Rk2CYSrK2GAVUy9wuIiNq9IGsWw+7PsqrUv97NXrUgg5KbYBNK2+04sl3IMAMozJ2EHDdaWuQYohL7e/lOdATY+ldhNyl2xWTu1lSQgc0YuSfTS2DDcMBB/BXjeuKrEjx1G85AQAG1F0Z1HnsdaK0olPajzLA7g0PGWAXZ89TxXyOQeJVXBqjJWt7EVgfd/js5/97CUde/z4caytreHuu+/GyZMn933Xti3uvfdeXHGFKFzee++9GI1GOHbsGO6///6nvPbGxgbe//734/3vfz/uuece3HbbbfjgBz+Id7/73UVwYMmWP9/Y2MB0WhQgH3nkkfz7qVOnsFgs8MADD+Daa6992mst2zXXXIN77703/911HR5++GFcc801T3neF2rPSBt6OUUKR0bwHt73WMxmWEz30C8WmiokTZvibFhrYVSqLHItjU+IoQR/gQiOJZieJgIwJMjIDPaSGw5aHnVXNZKqkxkIHC1YZeJMnv2pkCCMUVKFh1FlhiTHXyZyHg63yYnSWT851XXQldJElSY/dbqro1CvUnL56wVCcrRr56Mqz2DpoBOSzZJpKVlFVaiBByXHwIhsGumMbuwaYEfY6YAHz+xia2MD4KCTakrIIs+XJzIjqg6ZHGMsQBVzNd1WHRtjihOd2fBkwCR1lvJwNm2LUTPGeDzCaDQSxqchMCxiEIUBZIcgZt8sPRqlNRrUkY8QaUCgLASM5PocjWQx0I6kfK4BvGfMZxcwm4qTPhmPEUnUTlgS7qFtHUaTFq4xaFsHa4C9vRkYHTCrukzy0ipnKPtGqc2LF1kYu5yY5VSekbn6btALABLpo74T0lJUolRShBh0AxNzH+IgKYtSbZY+V+qzNGV5GzhEBN/DuRaucaLCE2JeUJGSqeqz8sIY5bFTnyVouh2GLvYYPpG8YACTmMlDDQ1mVlJKYWrvY8Nyebp0Ts2ap6pREtN8Pg+YTT3mXcSi58JUNwbGEtpWCEhBHcH0TvR9APlyQYYsPpKkW2r2qG1rDWE8shi3BqORBaIQoJxLhIHSfsNFXzHx6UsHMxZwTVLaYF04RsS433kcyJlWbc0s5I+2Nei8vJeIXLWlLDAmY4PxSNJ0cUVEqVo934uqb/eNralidEeLMQbtqEWAQa95DW1KxxU0NyjL4jsy6XwUhSSjbSU8K3l+EyKYDYCYnfTGOlhHMMYVspWWtFo7F4JPJhQhzz/Jr09OOsLgkVe2ssvPsjtQOuo6r+MoH73ICStLRhC1pSOTgJcf27/LmMCwhmFiGeMBYORkV/KRyQEAxZKllFqx8musQVZ7W9nKVraylb0IbDXXXpYmilxpji1tc3Ij4Jbj/inOXNnKVvbsTDHk5McyNGV3gPceoe8QfE3ySCtyzphSwkvz2hvIiqMlyFYFltP9MuClG/oy8DMMTOZfNdDIiTTBsTpef6ZgNMe8oUxD78hpmg8KSB5oihcNgpgJK5Zf98MKig+lu9SgcK4L2nd8IjXk5YkCcialmIYq/eaipUmsxhupBC8lKgqiBjAWiwBcmHUYtS1k05pcM+l0DJ5DN3kV7NvkZ6rrLrVvvUksgVaywTHhWIoVWSvpWpykScmqHWwyflxaK2GtWjaVbigoqGKzKU6t+z3TpjNrZcOfdYo968YuP13A91E3KTkwgm7gFwDQWgPbCAnFWiGLdH0PIKBPWcDr+peSSoloCUOu64tzqasq5AFOjlTLWUFcNg6ONzexcXi7fMalNQTPrZRtAbhRi+PXX4fJoS1IfEdSLqebhKB4nDEZlyYjmzEvPPoEHr3rczh+/TUw1gjphCusNbdx1YtJGmDfu5CbSd8hbe+Q0puzJGThRB4ozVreLarIV8s3YB6eg4Qhl5ZJjZLwWu9FycMHhg/pURKOjNxvOJZUMoCqDFfpldK4UL8T5e+yCc5Zgm0EnyRPMKYQK4YI+P66Y62j/JGBkpCkXiJLfGEfaktLGHJdZfpZVlM2NEj/TpCNoc5J2pOMwz+FpXZKL+FABS+PeRp3IFVgByFonzCm9HcWZon2Gf09JOUnHReArBRPlN4+iZcwWNLOuzQupfG4jOW5lXR4k/5XjetVu7M2KlM5b2Uru5xsd3cXv/3bv41/8A/+AQ4dOoRPfvKT+Jmf+Rl84zd+4yWdT0T43u/9Xrz73e/Gb/7mb+Kmm27CXXfdhfF4jFOnTuE7v/M78d73vhe/9Vu/BWbG7bffju/+7u9+WhIFAPze7/0eXvrSl+Lmm2/G1taWigQIzeGKK67A5z73uae9xld+5VfiP/yH/4Bv+7Zvw8MPP4xf+qVfyt9dccUV+JZv+Ra8853vxK/8yq/giiuuwCc+8Qlcd911OHr06NPe4x//43+MH//xH8dtt92Gm266CT/xEz+Bq6++Gm94wxsuoeaevV166hYdsGKIICZhGzJj78J5zOczxMUMxnsYjjmNgp4pbDhDiOpMppxUJf1JCa4VZ1uZp6TONIskNphhgpfjjVVWdboV1bOfXnH4t4ytekIaeZPTzukMDVAr4zc5xtD5I0tgAfkPMk6uw0U9QJyHNLrnj/TWqdBDbyNNfHniLTOAyttFnSjl88S0NWRgmlbcn6SfpaQAIV+Q5Eq0FuPxBpxr0PkoTlAIAAfE/rxcb7aDsPAgJjSuBTVOmMfECH2H3nv0IcJGgEgY3Cnlh7MjWAOEIA6tceLIkjoMpOxJC4YBoWlHMNYqEcigGY/gGgfDDoYTOagirVBaoKV6rFKGlCRvYNbHAgNR6qmPUbqcjzCWcHx7jKZ1mPU95n3A3h4DIWLWyTPO9uboF15kII2Fcw3GAPamc0znc8RpRIght3Hfe8xmC6nTnNvR6hqTShl1cbTMKBZLhCOh7hoSXnZ2atQxGTUtjCV08wUWowWSHJhR8gqro8JgXf9UZAEAttHUFQRYTdGSHUHtXpXPJ3WdCVBytO9FeWc8HmM0mgDBa646Xc6VV0vf5bQoK+9sKg9BHMlFL+/PZCRO5tZovRBHAITgRa1E5RUjF9UfS4CzBtYUyUfm6j76PnPCAGoyEgNc5ePre8bpsz2m04AQtH8RwViDI8e20bQOfuERQ8R8tkAIAYe2tzAaj4VYQwGhB4LnXGe9j5h3Ma+rZQESYaxB2xo4ZyrGdVISKpbyeJZCH2DKwD681WBjzaJtDHwAFj1jugB8ImqwkB+gfSLGCKL0T/tKiIjEYBPROMaxQwZdz9ibRRAZrK9JuUetgbOq5kGsaa8YeWdG7v1lzDuo9Lz0W9M4rK9P0AeAFyz5Vd0Ijjws9yDDsjuCgD4YRN0dFCNLHk0r43FUAoghhuRyIZGJZQKnNFfpHwKYoy5oSlk4lrpvGidpxnzJYUNI8oZV517Zyi5jOxFP4BAfyn+v8/oLWJoXj918xOMrTngcXQv7wSYAV2xEvOUlczy2a/EXD7XonuHGYEvAG67u8JIjHv/rkQYPXrC49coeNxwOOLnaZbyyla1sZS8qW821l5e1Fvjb13a45bjH/3yoxSO7T52beWUrW9kXZgIBKaZKpME0Rr+Yw/c9OPSSPhuK6ZVItuC/MRSsLwVT9evyYyl6mz7KZRAMixJOS/lyekB1Pi2fXvCLEo+kwT/Owd4CTGd4j8p1ias03Bn7SylOqufKZcsgd3nGfRUs/8v4WoWt1Y2QgonlI8WWDWV8driwqbAcsoAhONfCGIsQ5dwkN8A0lw11/UJ2zDPBGqubCgUXijECMcAyw+gmrqSQITiybhrSNkoKuikFN+kvBkmhQdTCUzpwY52qNljZmGPKbv4UJCZoqoSk2Jr7lSkVx5pqRf8um+YEDyJDWB87GGtEITZEoJM69iGvLCy5AAEAAElEQVRIuvneI3jFpMjAGIYD0PdeUtb3DJ6mHa2EGAL6PlTBcKoac9ivqGqokjo7dYSSHoKWG1T7nbUWZIDQBwQb8Ni99+Hhv/kMjt1wCte++hWlxlTtYvvKE3j1//l3ceGx07jn//04YvAZ6yWTiBlangy+Elzb4MY3vg6zC7s499DDePzuz+PaW78Ch68+iate+XIcvuYqHLvhOljbQHZHSH2kISDZ8nuYHovrvgyGD/L+NKpIMXZt3lQqjx+rjXP6tjEjGulThkwm8tDy9VPoJb9CZfBJ40nCkENkTOdC9CjcBqmrydoY1hrZYBlZVLWZMR6PYJ3TsS2CAwZ9MEbOCiWyT1gKQ5qa2qhiBKfxpjRGLv+ygsvg1zTmGWDcCr5rjWxUDIHRe0J9eiLmCFFCy5LeL0AUlUgGQGuAtREhRKDrpU81DcE6grNG3/lEkdAyVzEEoLThvuDE8nNovMFYg7ZxCAywh8YSHAwiDCISgQUcEaLJcQFOpJ4q5sGREZPicyKIcNQxQ2M0RFn5vCa0pCIlRW5jk6KQXqt63CJvv7KVXX5GRPjN3/xN/MiP/AgWiwVOnDiBb//2b8c//+f/PB/zzne+EwBwxx13HHiN97///fipn/opvPnNb8aTTz6JG264Ab/2a7+GU6dO4Rd/8Rfxwz/8w3jFK14BAPjmb/5mfOADH7ikst19991417vehcceewwbGxv49m//dnzf930fAOAHf/AH8fa3vx3b29v42q/9Wvze7/3egdf4mZ/5GXzXd30Xjh8/jle+8pX4nu/5Hnzwgx/M3//ar/0afuzHfgxf9VVfhZ2dHdxyyy34T//pPwEAbr/9drzrXe/CT//0T+M7v/M7B+cBwPd8z/fgsccewzd90zfh7NmzeMMb3oDf/d3fzWSU58ueAdEjh2PBbPKg183nmE+n4L6XFCkhwqgjD4KObCzyR8mPEo1/IHA1iR40sKWRTznAyd9JoyUZDeZWjm81tiaJsnRM2olNyRPO7OHlwCNVP4dO94H1QrXjX9YYUvRyUplLq13jeVaWxQfB5rpLGRCWotVY/igmtqHuSifDxeGAklaIwK4FjEMz2UTbTuD39hBiB8ktEYE4R4wduJuLOgMDxliQkjCIZLEVY0RgJd7UuSop7Yz3chyg6gcmz4GJFGI5peJwsM6haRoY5zBZH6MZtwgdwD2QmJaRWBKycJFso7QIpKrZpZDgxF/RyTQyw7Ps5PfBw7KBbQnN2GDXeyyCR5gGxC5ib7GH3vcInQf7oEFfIVA4Z8HMmHc9ukWH+XwxSKmRGprr/ln3K2WuJ/WAdEJ5DxiyG4GTn1zSnqhXK+xdi6ZxoirRJMdQiUIQ1RqypGos6R6ycIqsyinaZtZYwKY0KOqgEDKjv+QVTO+g/B1DgGdoeRqpe1M6LkOdvETySOva/CrnwoFB2jai9gMIYWA8anRBIvW+mEf4GBFSKhN1yhgA647nFG9nXazldyUuqWIs+7vpHWcgRGBvGjCdScqW9B4bY7C+McFo3GLnzC66PsJ3Hr33sNZhPBljNt+D80ak3NJzsjjKnY+wEF8u5zskCBPbpIVHbWnRJgWOlfM4ZD/rO2FkLb42Nthas5lU5wPQBxVJUoc6lS9qiqFCmqrqy8j47SywPjFwltF1ushds2gaQmMp+cNSHsuoL1QPmzUFMAMSy6bPJGo7LdBHmD4IAGCc8tgciAIiB3AEem9yepvkpCdpy7RAijF9XhbB5V1VZSFGfpfqcqZxhHTxgAhE0qCrdiST35mVk76yy8yGgwoIhC3ewvF4/IUpz4vQSHd4nViPePUV/UX5XFsjxlec8NhoGf/rkQa9DhM5f+3TmDXA9dsB12wF3HPO4uEdi2u2Al59Rf/0J69sZVBxPVNe+phyuq1sZSt7fm01137BlubaVJnPNXfaGkm91oWAzz7p8OhunWJ0ZStb2XNuGdtIRA5ZZYfeK9FDNr5QTMrRAyCnWqsjb3gSnCwBIftf3sFlUPCADP4QDcpVIp11ubkSsqjwiwRkDa6BjCENYuvZ908RvYKHLRVlqc5oMChVSFz1XOV/AyS7etx8hQzSVPgXKmg5EzpY/ulurfSsrOrP1o1grUPsezDLRkFwBKIHcwAHn29Amv8hX0PT6EQNEA+AIILi1bEEfancP23yK4rhoswsqXWF8OEaC+ucpJiIS7h8Rt7rioRiyKmmCIRYiADaX5h1Hz8LVkogkAWsI3SdpB+KPoIDC34cg6i8xoRRJlVrwf29pkLx3tfQ/tBSbKF0oGoyHPb3IYZcPW06lVNQIGGZoiJinWD00zPn8MhnPovR2hiEV8hxBllBeW1rE5NXvgzjzQ088NefhJ8rFq+bPMsGw9Tp5DtrHI5dfx1C3+MvP/s5PP75e3DsxlM4cs1V2D55BQ5fdSUmG2uyYztjsOltWVJ2Sf28Bj/r9wykygsANKOQs6rcToIFB6+K1wnrS5ep8EGqlDkGlZuw5gPqvKg5aBVESZnd95o2Sr8nUgVwZ9HNOgQW8lOIUfuvg/cGgUWFIt0T0I29ulmPMpZdNggfOIbUakZ1mXn5PdC/lLfQNAajxuSnigyEqmnLtQppjZYURzlVhg5jTQOYQLp5EmhbeR+SKFDiV8Dsewq9nhDLouyA1V3++8e88qcoeiAwPCmpjJIajNZXGo+qtDi5T+RBdBg7EAWg8i7l5kWaXniQBpzqis/xH4Ap5ctZ8nNXfujK1A4dOoSmadD3zy/+1zQNDh069LTHra+v4w//8A+f8piLETySjUYjvO9978P73ve+fd9tbW3hV37lVw487/rrr6/ikWK/8Au/kH//wR/8QfzgD/7ggee+8Y1vxKc//enBZ3UalWTXXXcd/vRP/3Tw2Y/+6I/m3w8dOoQ77rjjwGe87bbbcNtttw0+q8tLRPjRH/3RwfWeqjzf+q3fim/91m898NhnYpdM9Ah9L4O1IbAx6HsrCh0xwOTAWNotjjyYJWmkPH4xySR+MUZetux5DiXkgDwa1tw/GSwPirYjsw7Fvy7udv5ZO8zZeRCJ/3Jryo4LJ1Z6Ht0pExhyXrQ0ISoLl7MTniYRYTlz0uau+64GC9MkKo6eSqJxkfOWgLQEx60V9Q1rHZyyRWGcHNjtgKMH93MwgNkOsLANwAaGhRQQjQGjgQFgbAtjpWuE0MOySM+NR2McPnQULnYYxy04ZwA3AjkP147g2jHITUCO8wTcGkJrDOCEhGKtg7UWa+OxkiakImdzD7/XYWdvBhiDrvPwPsKHHiGUHHPisCUFkdQ4Uic+KqnD9+LQqYMd04tmhbHZR4axBucvnMdk3GK8Poa1Fv1MyB3nd3cx7xaY7s3RLTzmiw5d7xGisLS7rsei60W1JKoTPuifqPp3WZikBVPdA7NTmBdg2nfSwmaZZKGOx9r6GjY31yQPpPc5cF0cUD6wTxmTJARFxcFawhUnjwFgeB+yUkGSnGegsI59p8oPKM9CBGuBGOZwtkHTrmk6J5+XTEltJP0Up3ToHBlVYIhsMoPZB8b9j++AARzdGKF1hBg8WElCxgKUlE4So9xwtY4XBzpGcY5jUgGJ5Zjsh5L4lqm6fWD0gdDHQhSxzso/4+CMw3g8hjUWu9M52AdYa9E2DlubGxi3Lc6e3cFuN0NarnR9wN6ehzOE1hCC5gg0RLDqfEp/YgR1Oo0RkjvpAiQE2dXSWAY3hZzRtA2sMRiPCY0jjBtd8OizjcaEzS2jASBgMk4yfHKfprU4tN0iaU/mNoss2iIMtK2FtboTgIDRyBQGeSwTmrFJNg95IbjPca0af1+aHenA8N5jOp2hD4y+i2CK6HoLmAi2wsY2SixqLYMNg8mCtd2IGGQDKDImY8ZoJH1bSC1R+nrwAIvCTztp4Dmg9301q+ji3FnYxqrDr/WaVJ/qV42HZJmVrexyMALhRDwx2Em8ETdewBK9+OwlRzzWG8aVG/HpDwZwdBLx5hsX8Hr4WsNYaw4GMA4yQ8CtV/a47lDAdYdWSh4ruzSzNuKNb3wYf/tvl0Xtxz9+BT7zmVWqiJWt7Pm21Vz7hVuaa5OdWI/7lhDPhVkCXndVhxsPS6oWIqzm2pWt7HmwGEOGUREJIRrZvJxTe1S+cYmh7TNKUrED3PQiB9cYcrpmFYxk5gp/WIoSChBXSACciAbDe9HwDPlf3pVdJzooGN4++FtxEqqCpoOLDnb1pE1gKToKDMuNHDVNCHkKCqfnqDGLyBJAJgasUXWMxqlCqcpohIVgtcEDxOgXgNc0HjmOTJJamwBRBlHljcgSI0jpSyajNZg2wPFI7mEsyERY6wR3No3uh5NnsJD0xlBVX1HvMGiclDEpInsfEbuARdcDVNRdo6YZSd0hp49O+FRVpzn4r8enjVUZWSXFRBkgQ1jM53CNFRVqYxB6IXfMuw4+BPS9FzJHEPXsrEAc5DNR6V7uQQf05SoOcbF5cF+/ySdy+bWwPtC0DUajFilly1UvvxlrG2vYOH4U7ag5uBwgHL3qCrzu//uN2H3yDO79X5+AtcD65hrWt9YFU9QNaYM3KTJi2+DmN34lrnr5zTh66hrZxKXtIBvFPAxZWNsobqvKHimOU7UTwPtIDQmPrulOkRnn9joAwFprRe2ZRRmdlvsApTQlw1cqBf6rMFKu65o0wTRMIyKkDEKoNiKTMZruR/qwcw5EEV3vAQiubXWDm7MWs3mHLvS5HUNgdJ0eR6l/pjrUWFFM90/9vQxZopytGuEm7cmTGEVKHeQcwRLBmWGfso4wGlG+nnNlkyVYFLhHI5dVy9MAzQkfhpCyEqmDSFK65FewyrZlB1ESOTbGiAf/6lM4+8BDME42H199y8tw4sZTB78TGjPrey/jQGCALEIgmQOyQlAiXuizkAETI7IBAkCqAu0cwznJaiB1rvGlGLKakG0sosYdChVNn9do+vPUcbjEL6ruJsdfOky0si9xO3HiBP79v//3OH/+/PN6n0OHDuHEiRPP6z1W9sLYpRM9vJfB0BKIWQJkgAS26qlVZ5biTEkgrqRQISVJVIHwynJYOwdhaycFOgnT4PiLAwC1UkI5uHbrjV5vMMhWTt3Q9x/+zfkqhJxjEGFfkYt0VrXAIE0bkFI07FuwyHWH5a/UC/RyzMKyjCC0VtKLuNEGrHOAGwFgBF7Idv5uAY4RC46AcRg167CmQQAQIJJ5RAxjHKx1AAEhSjoeQIgkmxtbsBQwcj2ybIZtYJsGpmlArgWsF4eGIxwRGqOkE2PQNKLQsLaxibZt0C1m8L5H388xnXbwSqaY9z0WfY/ez9H3c8RIiF5ySJKxsEYkxaRaJJDf9UFyffaJsZuIHjKZu8aBidADIDKY704xGbW4+poTWJuM0S0W8N5jbzbFdDbH+QtTTGcd5vM5ukWnZIGltgUhEZn25a4bfFZIHolZXI5BJmrsszpGrosMEKEdj7CxuY7ZbI7ZbJbJTJEZMfUnLr49ILKM1lqMxy1CCNjZ2YE1BtuHN2GMQd/3SmTxOUedMKADYojoFgYxhMyOTuUzhsGxh2laNKMRGAyKHvUiMEFniT27/CImokZEInqIo3/63Ax9iBibCIysyDWSKpIYUhZzevf0vKRMkhx0JXmIumTpE/k9QloMF+c9qsiNCtvoPZUBbwyssWjbRhn6BmD5aa3BZDLBqG2xt7sA0SxL3XkvhKaRMyBrILgHZTIBULOKxe0kHVqSc5zyBDorz2FshDGE8digaRy21giNU8c6SloTJqBpCGvrFs4CzgKNk/Rb0NHbOsL6uoNni46To1lkKgHN/2iBti2LI9IKSwuhVH9pDsjM73RwtWAddvPK0VaSSQgBi24BHyQFDlnA+xbWRsBGfSXkHg0nJQ9CNAbREyLHTGxpW8ZozOjnEdGnMV6cdIpC9HCtg10YZCnRfH3ZLeIaJ8x776XP6vtYM8DT0x5IXlnZyp5vu8gC0cDgcDyMI3zki1ueLxEjAq7eirh669JIHgCwOWK89uSzZ+Ebkl3HNx5+7gNPZXjKHvdzfo+VfbFN2tJaxstf/iS+/usflE8ZePzxtRXRY2Urez5sac5dzbVfmD2bufbZmjXAzUcEAVnZylb2/FlWYjZCdIgxoPid9SbBZaCWkEkW+ej0HS665inHMYZqBjQgZDwdhlxj1cNQboE0BtjfoPxawGUMWcG5jIVBMZC0iXEfhpz+t4xUV9jyUwUH82FDRYKEIUu2W019YgyMawXXMpLSKnYeFBjMXtLY8gIggrUtDBkJbqZnSLvmjdFnjJlgIrjZCIYibFZEjQBZUFJeMLKZpwSwU0xW6scaK0SPtoW1FiH0iCEghB59HzKZQtKpBMToEaIHs8Qe0kZB2Syo9agYjk9EhZBSaEurJ4KIMQZMpNkZCL7r4azF1tY6msYheI8YI3rfo+895osevRdMWogefJG2ldY8GEMujVheCTrgmIv3gRp2YyVKWSeK0H3foOk9jl19EseuPlkIQZnxgNyniQza0REcPnEcZx96BA9+8lOivDweYTIZi4oJS5rj9JyCZ8qmsatedrPiklWAH9rtOYKMhbEODA8abNyljO+Bo9RT/eISBu9OOpUjMJ33iJHhyKFVMkO6ZyFBmGosqRR9ExabniHFlDht3a3HB2iK8nQ8DcghiVSSNqkaxRVzvIyL4otzEifpOj8Y4mIUQpNVvJwTxl/HxNLBecyQ9iMdexJRRhQf02ZBgnOiVjxqkNWl03gByGdNQ4KpKh6eN9GCFGcVDD/k6kuYuvxM6a2tRRnXK4w4Zw6oYgRZ/YIjnrz/fpy+l2GshbEWW0eP4sSNp/TQov+S34goscqk9owIxGhF9T5VnsZlTBqXdX7iSBJvMNL9rdV9kODBnnKJaVCOS5jEFko1k+IvREspW9JhtD/NywpDXlllJ06cWJEwVvas7ZKJHt2iEwaes4jWwGuqBgaVKKQag3XCozzZ1MMYL/+SWNVLx9cT2MDfyDYcUNNxvO/b9Cnl69aTfE6Rks5SqTnEmAkVyWJm4A1l+5mX6SLpugQmo/JnMnGk+7Cmz5ACackMRHmCGZGEFR2IwIbA1gozNgSpdzII1GCOMcANjO8ROWKxK+oCxrXiJHgPRAM2VspjHEAObAiwBI7iDIMIZCVVi7UWYMB3Aa2xmGxt4vCJY7hlcw3MHjEssHvuHB7+/D2gDeClL7kZbdPCgmENY+OKQyBjsHXsKLbW1kUxhIHZYoFF1+GJ+x6A9x5dL8oYi1mvihIqERZVCi/0iLEHYMBsQBRB5DNpIvUWTqoNyk6G/iRj0IxGiMzYmc8QQkTfywLT703ROIvdvT20baNsZGA2X6D3HotFh74PUq6QHF0MnB9w3QMPdtTrzkj5uHRKCWqDuZBhtS8Qq2LFkiM3nc7VDyccOnwIi/kCs9kcxPrupSUXCRteFm/COm+chbWE9fUJAMD7CFCUfhUrGThjARBGbQsAWDQOfiDJKMW0hkRuUxcC1jkwIqKXuiNlKScnliALLGE8B3WCxblbzHtEB/ixOsh9AEJE8AzvgCalwWMMpPZYnUNjlOmt3nlimIvDJy9zYhcvL4rSuy7sXyGacIw54N80DVzTIAZRUTGG4BqLdq1BNEIWSIvEpBRBii8wRCVkvoiwRBiPDNbWCFc2BpOxQSLC1QuKpiGcONrklCPWAE0r9be91SBw7aRbJcvoDg1V2DC6IHCWMG6NELmoPO9wgUhlMZPqiTTdS178FJJSSY0iXq+xAhSkBy6Elf0msIDFvvGbyxjve4/pzhQMg8DyfL7vQSFiL/RoLOCMzQSYtGhgAGShErDi/lMEKDAsIoxhWPQgMNpmjNY1MgZ6Ieo4a+CDpj9iyduZdv44Z9E4A+8jFtyDOSIi5h0zRMLqHqxiV7ayL5JZWJyIJ9ByO/jcwGCN116gUq3scrPNlvF11y1wZmbw8UcbTPvVePVit6YJuO22/4VbbnkYr3zlQy90cVa2si8Ls7A4Ho9jxCMAq7l2ZStb2cqWLXhR9DAsChvRWIBqdQrkYCtX6RNqgsI+eK1O2w0MMOSCLyfgrYoolhOWrocS366CkPU5GUNOvyl+O8CQE2kj7t9syBl0DvWHGnfkpWNRrlWlsxg8bx3szreXjYQaykXK3MfGSJlS/ZABk4GHKDxTUMWJboaoGCABEpzngvMzGeTNjQLAgHVDYFJdNiQsmugZdkRw4xHGdg3HTjQARzAHdPM5ds6eBVrg6NGjoiiiwed2cwQiwmhtDRQCHvirv0G/6HHlK16G8dY69s4tVJVVyAW+Dzl1LyOlhmFwDGAOECRHN50S7e9K9UZKVeZO5ALrnOCTuokwbZKKXQdrDLqug9W03mBG72XDYtCfUdWmUzh6uRsuB+uHBRt+JfFoLkrn2sGS+kjpEoLF0YDkVKhBfe8x1f41nozgfYDvvR5Gg2tlcow1Gc+11uTU4aKaXNLUpHMBI+EUfU+8N6rUUfC6HMxnICvoGgOwKH4n/NNoWiGyNsdwhKSUou6E+e4u7vnrv4F1hJe/8ZVo1yaabyRKsN9oZpLqHZf65Txk5GEoxaLSJjJOKTClfvaRYVK1JdwzlnNT9VtrYKz0k6SObQzBNgZMVnFwVqWXmk0g50cWHJkAoDVoiLBhhKRB1XGpHxtNsc25DpVkAcJ4ZAdtZTS3bHr29E/6gBA5XOpWVbmGvbnCkJmFXEURZSiv6iyROlKFQfoB5bQtCUcexg+HlXLAr5ywaUIMEf2il/gADDhInAOR0ZkAa6RfCbGj1EWaktK8QVAV55Q2B4CBkMGsdbCaWp5jzHGOyIVQmMlFIBk2jUUMjKRon8KKiUpINt98ZStb2cq+ILtkokffdbqDmcFsJRBq1JEkTeqllhwJGo7X8gulwV2P5XxIdTINPhtOKnXQuygG5KP1byYJI+43ys5pCozmwHq+LCHnKlwKVOZAfpoFU/kSyzQdnQ6jOoVNcSRYZxHOx9X3Tj8tmGQ6ARnAWjCipNIgnWrIoUMLYgfHHhx79JghEuBcCyIjNESQpDWwcl1orkUmkdZj9kIAMcKsds4CTAhdAJFFu76GK648jpfefD1C6DGbzfDYgw/i9AMPobUOxw8fFefTBxjDWDu6CeMcNra3sT5ZE/JGCNjrFpj3PR54+BHs7O6h9yKplZ2U3D4oLF8woDkAa/onp3ZAWUzVmX05SlC9aRv4GDE936HvevTzHhwZMyOEhnPnL2h+Rwk8p2B7ImGUfpPWW+phLvfd/Ff2apY+TwUvLk+ScIi6WMlsUKK80KW6z+klZvMF+hCwtjbGxtYmQAbzTp6LKqfJGoNWczDanD4nkWbGiJHR90GfN2bPjpBUMwxGbZvzYPbeg6OQUjJRSp8hKWtIao8GHTOi97B6T2stGudyF48xouvVWYfU+WIRwIHhg5UH9SKtEYMQNZypHHTIeamd0ispWYPEicoKHpHrV1afN3tf2l/kwqIAkmQV5QRDIjvpnM2LS2ctnLFoxw6RoqSe0XNDCEisXNJcpyEwFl3AqJXFz3hisLEhRBzSRXLt2zeOcGS7qfpgaf/NDbPU70oPizGlLYKWHXCGtF7y6KxdeH/v5epaqIgfadGTBrdMjGEBcBpnoWqd1Zi831mtdDsq0sige4MgKlJzH0DWAnYkKig+wFPArPcIjrDeCmkoZMa4Xs8QjOG8GyQRPQzSgqeHAaN1Y4xai35h0BuCs0KE6nrKZcypskjS0jTWgExA1wfJE6njBekCwzpXJPpWtrLn05YGAQe3TzZ+ZStbtvWW8bqrepyeGvzv0w7T5zf958q+COZcwJvf/En8vb/3yYscsW9FtbKVfZHtYJ/wRWEHo80wMDgej2OTN7+45VnZwXaRdnqhrHC+V+Pvyr58LaWdTYoPovRgcjAtvxeD9yWpHlcfFQhweDiqDwbB7aWTE2i8fLt8rh5dBzQL0Kx/JzywJHmt0ODyTPtwwPT5Eqajv/PSYfkn0RBTR8GQl68Cqm5KVDYyKqbNhsEh5jJGGARYEAwMIhAZoe91176VNlJghROWnYHzdP0oAJoR4ggM5d37KQWHbRpsbKzh6JFtRI7wfY/dCxcwvXAB1hisT9YEb4qajngyAhmDdjyG35vi8c98HvPdXWxfdzXc+gQXdnew6DqEoIobuSJoWHdpE6a2V/5ugCHXrVAqn5k1nbkoDffzIBu5vGCeXq85XyyQ1F/zNfR/g8tTuXYdXHgqvGzwPtQbiAqYmcsKZt1sBcWQl+9ZzKv6SNM6tKMRAEk3kxXYodfQzYIpgA1SRQorqUesdbJpLyQCR3kzk1KztVawbSLdfBeHj1MDgZA6NdZI21JEUu41RuIA5bQEHkvtLfZm+Pydf4WmMbj+VTfBTca6802OFeWacs+aLJPbLL9WheCR75V/XmQQqto8Y+r6oInAktINRY4wJAoQ1km6EBhkXDYqwFrSiojygw8l5YlzhLZNaexT+UobWwtMxqaUsxopRu3y1uRiQqCpMHLofm5LqCtq//nVJ0tDb437DiyWz2xi4TytizTEkNNrn9ovtVDkAO4197nRtORa9z5GsCE0NkXulsqlSh5EVXyK9alVIYW0zM4aRANEfUesIYS0F1w7J+cxSNXoKYJiGbsyyQMYxrpWtrKVrewLsEsmeiRWJbzIFHlVIJABtgxIaeA1aWt2FaSsmY1IEyG4kD0Gkz7r/Eg58JxZyNVsnB2k2gFGktSXQXopVo+khoHqZz6EoOQMGeW5ugdDBnJAHOA82ZABmlbLGQCTmHqAsQ5kDJiDMhNl4hdpOwuGBUOcqxyshkhiSYoAhg0EjhGx84gcc44wICL6Hn03h6MWbevQGIKhCDLIrOuUpqAmLSSZq8hCGmFjZQd7DJllSNbBjNYxm/V49P4H4RBxxYnDiDGg6+boFnM0RIhkAFjAEKhtMCGDl1xxNSKA2WyKxWyG3d0put5jbzpD1/fwnYeB5JmDATgEYUOqLJ8QcUxp0cQQVycz9yoN8vc+YDYXMlLjLIwxaMcjgAh7izn63qObLYSxrPO+0+Os1Z9OGLU+JFUQzaBWda/aGSg8gSWnL1t5LxKZKPX5nHFYy29MXo1J/6zaipcuR8TgwOjZY8Zz+K7HYtFlJmuSTbRG1AnaxilTVnp/Ypl3XafqFcM7GStpUdq2USm3RiQLOcJawnwW0QevaVPEyTGWAI7SF61F27QgsiDTSPtxBAPovR88t49JXkPb2lh4MM6eF0LJYi6Lgt5HNIHhbKrTiKRmkXk36pgyl+uLwkv6vjouNxip8ya/xgh0fUTvKza2OoehFxm96d4MrnEYj1tYa7C5sYGNTWDkZAfCbNZhPp0hhohR69AlVZgI7Vucncfaic+LQk67EcoYWTvKy14w7/tDyx5RdnKQkDWI5HomLdoUdAF0sRAMukBlfDaAa2SXRUmFk5tQHN4odOS+Z1DPkNMJIRBS/tF6/0RN1CvvcfUgStIhmELcgOSH9bMZIjEYHtwQ+okVmcGll0+UlAroQtZI/lcEgKNKJwLRd+Lw+x6GGG1rQOzQBQvMkftXyvUICFnJWmAyGUkfU/WXvuvhGofDJ45K6qyVrex5tgYNjsVjcCz9zcKi4eYFLtXKVrayy8le8YonMZl43HXXEXz2s4dxCUjaylb2nNlNN53DN33T53DPPYfwN39zDC/G/rc81yazsPsUtFb2wtj07BY+9X9/NULXoJtOXujiAAA2WsbfuqbD2Rnhrx9fqWet7MvT8s5sxT8EU477YLP6730qyVhOnqJ7xJcx5AoTznyIgUJI+YxpeLz8VQgUorZakScybKQloWF5yvbtCufITIR0lZLePB9rbb4GMWdMI6cm5gqnTnenOgW44ChnHngId/3pR3Hoyitw7NS1MJBUKMxC8MgKBQlzihExeERYWGdgoZuTCGCYjFGVwnMufw5iEumGTyBvGAMgKVlaeB+xe/4CDBjr6xMwR4TgEYLgwJwaj2Q3ewPC0fUtMAF938NzxPZNp7CYL+CNwXRP1JmzOjCgqiKKrSewPweNk7oraRyACpFH+6WkXAlyzURQUByn914UOnqv2LA8njElDUxNhIhJNUXLx4O+leq+/JCPaNAHkepEjyt7HFNEou5QXDaspu/qwEdt6TWIQOAIdB7RR43ppOoqWLsErk3p6/rututrOPVVt8I4C9u0qhpR+qx0aZM3F5IhMFtEIvieEThqIL2kDQJLqo2Ey8t1UqyltFN67kyIYAZgMFpfx41vfB2MIQTTYjaL8F4x9wBEwxKMz5URqwop40uJNclnKQYgOOVyihAavPbMhBBi3mzH+TvBCsFAb3qYYEWJmQht26IlwBrZCOl7UVfhyLDWVGopyJsWpSl1HNCbcBqrarw4v7OD17f8XLbq0epxIvdcKr0v9zkdy+QrQogZlAdI1J6h5czNVZdBx9cQAYoSJfN9IrtUHXfp9yc+fx9C1+PwtVfh0FUnhxgyQZT083vBAEfEvpc6hhA9oqNqjgCqzlEmD4pKWlImDtUbXUWJXtQ8WEg4MAjRAKporkVCCBJDARwMGbim1HNSdjfGYLK+VsW/Vrayla3s2dulEz3S6KxBQO8jYFMgMc9w8kP/UQ5SFqc1kz3SxDFwgMpv2XHnOpBerk9UOTtLQfE6fQZX9y6OCmVHBtA5pvKZErkksZczcTY51cSSdiVd1SjRwxDAARQjWFO7GCsTeTAG0FxeUgxxYBgGzNU9AESIoxiCl+d0BA4RvuvLYkmLLESPBVoDuHGLxpqSScckpZXkeLM6cppEhgvRA4lhn1UdALINqF3DdN5huvMwxiOH8zsnAY4IvkPXzeGIEInApLvYncW4aXFzM0Lnezxx9jRm8zkef+xJLBYdvC+Tt1EnGAT0HBBjgDPITrZsxTdgMAzMwAHPbaSOT+cj9roOlqRd2tagHY0ROOLC3i76RYdutkD0Aa5x6kg6lVIrpAgyRhVOSi6/5OHVzl/xCspHg+MHJI+lhSkX5zG1i8n9EtnZXvb5pVHk0xgjOACz3mOGsnggJciIeoY4kk3b5HvHEOD9QtLlqAIItG7Ta+FskuUTBYu2EaeEo+QGnM8XyrTW1CCNgWssYozw3QJuPEbTjGFsA9sAwXcI/QJBc2ZmabrBk6nj6CwCR5y94BG8R7cIMMTwIco/NhDGeQQlggyodG+hIlfsa+TvszTjMvMLyAQ0IQ1F9H1ESpunFAmRHmXGFAzrrOYkbLB1aAtN26LvPLwPWMw67FyYwVlC2ziEyJIrlAHvdQxEYWoXBx25zIWQMmSV5653UP9I46oen94N6KJdfjJI09sYVbQhsvqTZGdHSHWqOysaWYpz1HQ7AZlEk8hFzIDvEjtZUksFVWU5aC2R9gzkV6B6NAakX1rOC0awpPDxs5CddASD3kewo9x/4uBK6adKkFoLw6rCYQBLQOw79LGDipKgbQiNtZguFODI65OIvu91t4TsULAKzEjezIAYI9rxCEdOHKveuZWt7PmzhhucDCcxwuiFLsrKVrayy9CIgFtueRK33PIkYiQleqxsZV88u/HGc7jxxnP4b//tWnzqU8cGPt+LxVZz7eVvs3Ob+N9/+Lde6GIMbL1hvPHqDk/ODO4+s1LPWtmXpyV4IkaGoZKSQSCaA0CNJRBsgCHXqEKCRw4CGoCMUcj1coR0+LPC9Q6amvZhyCm4uQ9DToCSYijpzLShh1BtQClqIALIWD09RUIFzUgBP054EQuqQgmwS8l1teBnHnwEu48/jute8xU4cu3VcpxI5mqgeUgV4Ciphi0BJmNBsXrWupKlvENSgYJnVDCrBGKSMSDboPcB/WIHzhosDm9IWfS+ssdNU5xL1B/OWhyxFiFGTOdT9DHg0E3Xw3sPH4F+OsvtQUQwzAjQDUKEQo6h8gy5trXea6KNpGNh9EGIHg0kvbWkbGHMuk6VPGRDolECAxmTSQp581QVMyg1VqHFRb47f3pwf6zwSSwZl5pH7psFrzqwEy+XRHFCHz388CoAFfUJo2la8q1jRIgBzWSC6173mkwGiMz5FTBaHwVflziI9EHFQQOXd0bvk1Jfy7lOwjQW4CDp5VM7ZVx0qVLatTVc//qvBENUaabzoIQgaFp4Tm+VvOkp1pFeOa1VSvWDCp/MStz7tB/kiglDhqaRjzUdRL7kyIiI6HuATMxkmNF4BGstQogZT1wseiHZWK0XJKKLFCqlIErNmsqNqnxc95PlQh80XvK+X4b1nMYn/ZljMTD6uhE4mnywxNM0pgNIrEuxZB6UVOo3hjTOMLyPWeF6GEEp9sQ99+H0vQ/g5q95gxA9UPXwRK7LGDIDMSB6uWgEA5YQWN/hOgi3767yXstYHBJsLxuBQ0BQXBkQtRVrDHpPZfjU+8coCvlwMv44Y5GKmtLMW+cw2ViDsQfnJFjZyla2smdiz0DRQxUqktOZ/DkM07Zw9TMWrm75kEpwj2M5M+cirMgcAJTInJyx6jMpDPKwzkCSPWJjRZUDOhnqDcnaHKhjAJ4hOQnrnIXVfVAFhhM5Ic1zCDEHgImh6SsM2PcaxFZH2RiQtcKajiVroklOUY7q5h+icEES7JRJX1Q8UmC1TicRI8N3Ht7a8rypVnUh5aMuDFQmkTVXoZAnDEARMIC1IxjjcPIqi2ZjG4c3N2BaB9cHjKKHhYdf9Aixx3w+xXzRAW4k9UcSzJ7Od9H5gPO7U/R9j73pHvreC1OTLMgyjLYHA7AUISpVoqJh1CHMLMhS68p4lOBznpNT23DAuJXgazMag6xFHyN67zHXsjAHkAVGIwdrlcBgSNRZiBBianNU3kKxxKCXKlbHLfeboVOX8r3J31T6Jhc+N6V+z8UhKAtWUlZ/cfYHaTMGUpLFQZGiRAnGR1Xv6H0pF4vEHrOk9gE4k5oT+7ppW3XyGwAGfc8AArpeiAzSrSl3sRAZJqiygY8ITYPErHfOwJoRojVKEgjq8HAuT3rX8hAQA6K+Mz5IY+/uCQFjdy+WwD8Yk7FF4wiNI1gjMmoyROk4kkgfaW2OUtd1HxPihdRx10V0fWFxky6ig76DERDSSt/CwODCuR2QNWjbEawxCCHCe4+2aTEaNeh8BFhJWpyz9eQxlZnyuEq54ylDnyIMAKuqG2SG422s3oO8+NH+GKs+mPonR8rPFQkQZRQvfRCAh+aJBBACo+OIPfZ5UcQMhKSQEmXxkaQzk0phWnKEWMggpccjlzORM3LnXXrnMjFHmdKDXTUE+D5id8/DmkQAEynDRAKLUYAG66REkaMQdEjGvz6oFKQzktrGEYAAgsV4HjAa95Jf1JSSWmNkIWqFQEXax5yzMAQ04xbOWtgVG3tlz6M13OBoPIoxj+HgMoi1spU9E5s4xlee7HF2HvDpJxz2+tW49aVotc+8spV9sY1ehNPTiEc4HA/D6Ba/ltvVXHvZ2+XXNi/Gvr+ylT3Xlnb8E2xZ61eEgWXALWN/ywE4yjBDjuXlax0YgV2+ZvXR0iasOtAtZAotRQafNWhIBf9KUcuBf8XDkWh5g17CpDPazUbvQZIaOSYFVrkXkamwFGQ8JoWeK9C63FyDiyV18fIGqFK9koo9FEwmq59wxlLqmuPqp+CiCRcUFYaNzU2YdoxJ24qaaoiwJsKQBFojB3jfC55oHKbnzuPRz94DNxrh6EuuB6zFousRYkTfdxmzFJXgGqhXnN9KeblS2KjbYiDIwkK4SeBZ2XQXZbMflfS7KSWJ73rEGADEvBkuqSZnYgk0CL+/S1W/S59iTroRFfBb5eXhQSNVOHEucdUa+mwVD6h8sdThCxbHpX3rgibMU/F4ZiEnsKZlSUdHzWdsNFCdTjdKrrFGYi0pHXoI8u4nIgNQ4a8JF2XBzTnKRlp5t1Vp2AEmprQbBYusy1RjyN10hgf/5lOIfY/D15/CaH2CrhMChlnUgwajcaIcbA3lTbKUv091ylU9V6ltlv0NkuEgBM6pO0oDSr0lPRBiSWNDICxmi7xBk0gJITHCWgtnrZBbQpB+o+9s6iORJV0Pca1SI/1JwhWi+VPU8WlQ7OHwWnegUsdpoJD7ljE5qEI0IebDIuT9S+0ZmNHnnORy/Yxbx/L+DboiWNSvcwyuVHBRqAfKSIT65PJrGgNRjuVocuwlRsH7kzp56sNp3E2K3mS06KmudaQMUdKiE5GSRcqNXR9VJR4ZUwfk+hzlOsbaHBdKZJiEUZuV47iyla3sObBnTPRIeeDUncysYsaA0qFDKg0d8fQzDeo6p7AGYPczXQsDOuXFSvdOQffEypXzNRjqnE5omoIk+b2yhT2TJaISKSjGMllouWye5KNOuuLs5xhyDEoQIbABjMoQBt+DdYYnAtA4EJMQQ0JI6nT6lCrRFxkci1NWUtiIA953Pk+OA0UChqbg6DGyohiS0jAAkPxfYPRsEAG0VoLgKdWKpI3RejSAbcdw7TquPXQMp5zDYrHAYjZHgwjiAMs9+nmHzi+ws3ce3aIDNyNAGb6L0OOJnbOYzRd4/PFzwn4OFReeLIxFtdgQMgCzyJMl0gSnRVC9cqpIN3XblYUNY21sYVwDuzYBGOj6gG7RY7Yzhfd9JjOMR42mX3AAGUSkQH66XnInOLdJYRehMFeTg5LdCB6UtXoZkL2IdPXcBwb/G1rNpq9/S44Y8dLX6oxFzUHHpM4v51PSda01GLcjeawoRJCkdOKcED0ktRCh73vEENB1AT5IX7TGaCC/ED1C7xG9sN5DECfHOaf3bXPQvqhBpMVEBDS1kfT5AN856ftBUoCc32W4eZQ+xVHHI8b2lsVkbLExIYxHkifPKo4gSoClLYw6a5nsUa2xkicZmTGfR3SdKo5UB/YhgALgY4DxBn48gmHCzu4eQow4evQI1iZrCCGg7z3MxhijcYvZvE/dYjD2pOc3xsCayhEnCBWLGGTECW2d0byYRSmCqzEhstZrTO9VLIQSVgZ1hCzcQNW7FMBQNjIT4BpgJM/rlbizu1CihzrzURWIWIkcvRCcYbPmnabpQZR3C3XfL++3tMXSzLG0AIkxZieZSBZ7INn90THhwk6X1XmMIbQNiVKJU6DGWjgQmGWMascOzhksAuC9pmqxDo2VBamxEWQiJvOAybSTHRuaVilJdsYgbZaIHpLeidGOHFzT5JRQK1vZ82UjHuGacA0arJRjVvbsba1hfPW1Hc4vCA+ct9hb7TZe2cpWtjKMeYxrw7Vwlw6TrGxlK1vZyg6wjInlTVL6J1Q5OeO+BSe7SDhVr4dBXJIyzjBEogGq1DC4+jRdXLC0gkGTbNBbCvZSPrbcPwUhKQHd9a0rPDAFSYkIyBlaEp5NAMWCi8YoGwfTgxvdjCeAyFJlCL5dQ6EoiF8OToYQS4kqzDKlDA8hIKYcI6bcgBK+pNe0lKDQVNflH5Gm+7YtDo3XsG0MvA8I3sOA4RBAHDV1tEfXi7IwjMXe+R3c9WcfxWh7C+7Kw7DjMfb25loX1eMmzJ8ZKfqaNg6SLeWuN5Dl+EF66oSHVWSB9LCNU/XXRtbVIUSEECqiB0CGMsaT0olnSCv9khqv3pBXOtxAEQWJeDIw3teVBsQQVPBwuhQT9r0og8DGQbb8zqUiycNEEAKXN7M+zBiCs+ob5VT1QpRJGzYlNgTEGJA2auZ61EB6SlVPUVUN8gYxSeUum6YMYLVWuMLd0zuYVMsTAWHR4d6PfRzdYoFXHj0GO55g3gHGc97YmzbHjUfS7q0jOJfSyGQK0yAOQHUbVvVRY8gMhve6AS6dpOdHjkCQ8YIiIToLYqDvpH4maxM0rtGU4xFETgL/PuSbFRwZ2nfkWoaM1EdSrGEo2UPICpaK4vewrbFUn1LchGumOF5+VRiKIadz4jAuYTiPcYns0YUh0SOPQ3qNlA3J5A5WiB5JgWXZhOxmdOxOHxYSioZDhm8SA0QBKe4VGFh0QYkaKc2QDvNGxzkyMEY2dkeOoppvCJ6FKGKNkL5SQiCpbwPnGY0P1ZhVxiXJbEBZKYe0IUQBxxZV+5WtbGUr+wLtmSEYVIKREmxNqUzscrgOeWBODohJE6PR3y1AZjBA19J0GkkEIINoRenLjlFK+6HRTj1GCR9khIVaEVPIysSQVBIGTlNy+liUFCgFQvXYxBaRZ8h6HaVIyyzitMBgiaFGZIENcDUXFd+8LEjYNojk82SYcrLlY6FuhpG0L10f0DWhsB+VlqruFFh0osCGwQawbgSyLZxzErDvGZxksoJcBz6AfQDDwLgWrbUIDJw7ewa97zGdT7GYLbA73UXX99idLdD5Hhf2Zuh6n2XL6lyXuQXT8+uiKTW7OCl1LzpgclfvikwEiGFtg6Ydofc99qa7gGeQ3wWYEXphjQMR1ho450QOiwyiMIikPSpfvPJY8kIy/71UlmEakOGxqey5vFR2CixdZfC8w7VikpCTT5OzkJwZXu5upYOWOh28hlR+ZwibnpAXj4wAogjvoax4UYAJIWR1kKjkJjKiIGNY3LMQARgH01hEAH3Xoe89yPTQVYoodCRSVa74inCQnPYY4QMjsCwQYhDCTvBJvK7U16KTxULfM5xVh58Yh9YNNtesXk8IKQNVnlRXtSPIQO8Zi06JHvuce4is5NjBNha2EWWYpnGwHOHUQZO6ZJDRPmdKvYujSTDWwFBEnTc0NyXrwl0Hi0iSuknG3n4AKCQHuSgPIT9zIZSg/M2JqMGDc2Q1RjCIcCPkc0JgzPqQ2wlciB5pvAkZk0jvjWxrsC0kPwqG6h3VchzLVq2J8tFSFakjm4ItAIhByUPRKxM+7chgTbvFABF8BMgzrAcCA10UZZKOhMRGCvQk+htY0imlWzFE1pSMLPSts0LeI0LQebEdjeCaBlbZ3Stb2XNlIx5hO27n92DEo5zObGUre7ZWD1OrIWtlYx7jUDx0WYwrM5rhPJ0/aBmwspU9ZzbhCbbi1r4+P+HJao5d2XNmY8d49RU9zswCPnvGYbpSz1rZl5PR8i/VDnFVhl7en52wooQXZgyNZB0+AMHqyOvyVTJ2hozTJShtGHlMP6lgy0DGkAvoXANsiiulY7hOA1AFe1FhyBl1qsp1EQc8HZdg8fxIdZGrI5kAmILJ11yDfRi9khRCZIRYBWwJJW05AcyqBq1YOBkHMkJ2ICLFYRJIHSUtR2QgxowXWkO4cPoMHr/rHtkM5Tu06+vYuvJKYNRg+6U3wo1H8BGIGviuyzvAkAdoEue+wTVop9jP8PhyrNQVwxgLYx1iDOi6DogBFBeKvYuadsJf5Xm1r3IWQ16q16pF9oHGyFh/OoCrP4cYcl1yqvrO/r5XP+L+8uinXKthp4NzA5fj0mf514Th1f9PadNjeVBCximj8hJSTCSpcMQQc1wgEYYSwheZADIaYIekykYEmSKNkTYJDjBkpHaviDvO4cpXvAyh79GMR2AlGLEx+zDkIOLQCIEhcLXg4aMWGDUmX7+OE1TDCKof0mcCq6JHOWGZlGOcUcUTVYaBYKmJbCCXqvvc0rhICaOv+0SxQTdSpQ/p+wwEbfeUikbH0FrtJ5M+wJloVeq4HouW1TgY5CKy0AtLdcZYHZSGiTzcch5mq5kBveeK5LU/wliedGnc3DeMEvbOnMXpex/Qd6Ai6ZAogQOU6zOlgzdG4nFBU700jRA8RL1ZSCKRgdYa2EzMIBhNjT6b9dibdUN8nwnrR7dx7Prr5D6R8xgMkKaEN6WMK1sZgL6/HzGefl7vYcwxNM11z+s9LsXuvfde3HDDDTh79iy2t7f3ff+nf/qn+Ef/6B/hwQcf/OIX7kVqz4joQSCZnAiSigSQwJumSklO+jDtBtQpTznzZDAkJwAKASJTNwjwqeMRKF8fHAFPqGfbRDpJDmU+O2reK82nx2m2iFbKYa38y04f5TkwMVkHjg+gLD35mYLq2WEgqQfOzyeW8qpBnRMd05F5opELCSSdYyyibcCmR9p5T8oMjWki0Z9MFgEGs4VXea+IyJL+hAFlYRswNWCyYBPBBnDtGlwzhnUNjLHoopI6AoPJ56BwIAs2DrZp0bQOgRmnH3sUPkTMO4/FYo4LO2cxnS3w2JkLwsD0tfIGVaSWOJymk6eku+XFD2FkgbispMADhz2pMYhvEuHGLTY2j2B3dxfTs6IigjCVPIJeMg8SMZwzGI8nsInoARJ/7oDZNDk6vMSk2O+0X8zxSCmOSpmlD6kEGIqjM3SyS9WUK1VlZCgLuqo/IKvEyPNU4JEZHlgE58SB6mKdmRHo+7Rs6eVoSkcjv2fiG4kzbqmkNIoMWCXSiCrGHDEm+TppgxAj+hhhSPLYESCyyMwIrCQOjpnoEAI0j2eP2cyIckNyhNSxms6B+UKZ4szogocPAdefbLE2NtqXdcGWFrL1IjE5q/qciy5iNouYL8oOi8EphuA2WjQjh8Y0cGQBJZi4pjBxGaJ6IuSiIaAnrGFlEA9cW+Tnl3/6nuf3p+qDqe3TWJSGuPQs6jlnFQpdhAfm6vpaL+ldZYOWGHYNmSzi+4j5noyjMVQOOgtholRNWWTFKM+4YRnOlO/L0aWOBountDavKj2ysrzzeFCtZgEEn1pOFoNdYmU3DinfKxGhV4IHE8MIRwMRBAvZQSCHEhwDjY7tKTemjE8EGElF1DT6bkdRLImG4BqL8doEzjk0xmLlpq/subQ1XsOpcAoWq7ydK1vZyp4fW4/ruD5cn9NVvJB22pzGBXthCZhd2cqeW9uMm7gh3LDy2Vb2vNp6w/i6Ux3OzwmP7lpMV+pZK/tysoR/6vI5B/ITnlkfS/tRAwzwVSqbB6sDC76juAAvnRdp8HkOwiX503whzZ+dUv8ug20Jz07lSlhICpIuB8+xTGEBMoZM5e/lg+pg6DDQTINnrkoogUMy4ERISBfC0vlI9U7ovSjHps07pJuTBJcnxbdl9zwIMLaBsU4wLGMQVGGXWepSMCIv6tEk6sDWGTz60Ofwqf/7T+B9gA8RR2+4Dq/4xm8A1ka44nWvRoxAHwCEXstdY8gH4HGpfRUUJSQFAB60SwaZU/oTkiYGGMZZjNoJFl2HfiYqIoh93nSWzrWG4FxTpX9PAfL97ZoJPsPWRHmMA55l+SoVOF37Jmnz4ADLXLrZMoZcf5g3DCIphDAyUWbpXstKI4OtT4ysFFM/o5gwPQYYstZL/S6bXAYNByiRRlQxfBWK0euwpAJRaG9QNzKeyAmmdbjxb70eMUYs5tKm3stGRsrpfaQcfQ94SqoSgkXHyNjetGgdMg6c3o1hDZdHTt/4APS9KFIcVP8ggmksjDOwZAXftHIFY6karqgQPcxyQ4hy8dBnLeNOGityDIOBkFdS4cBy15iycEBKnSO3g6qSlK+HJBgmWAJMk86TzYa+i/m4+tyDCB5pHPFdLJsQhw+P5ZdmONIOwiNgAOcfO41P/z9/iujDYAoZEiqq0ZGUhKN9BCip7a2mbUrP7AzB6ZxGkHaxFpjPPWZzv6/c13zFy3DFjddJjCjVHYkaTlJVt7T/GVf25Wl9fz8eeOBlYJ4/r/chGuPaaz/zjMges9kMr3rVq3D69GmcO3fu+StcZV/3dV/3nJE8iAgf//jHceuttz4n17tc7ZKJHhubm7JruW0l7YNrQASEboboZeJI+axyYN4YIWtIRBFJzSM5Zsx5O7o4GsYAiEgRRblepo8sjfeUnYVlF9qoY8b17JRnInFyZK5aWijU/jxwwASTFhzDSSRdvgRls9+ZJ6p6rSC8FAapQ1ECrelqojoSOd+x3Bi6W58AilGC54HhozrkxiCSVWffAWThmk2QcWiog6EImV88OEpKF2MsnBtJWgjjsgdlIE5X4Ih+MUfwAX3fw4eIRRfQ+x6zxQyLrkfXi9pDVBWVzPRFYcRKfVVOWVW/mQ2e6m6ZqQtxslzboh2NMO87LOYBi7kHh/OYzeaIqjwgi0kDo/J7RtNimLw4qxaWDGSaTWK2pgULEtmjOB+1Lbd9el7xC5KMV+VVoFqnDtYhw8Vnej9qZyX7cFWfTdJ3mXJkBt2kumfZPSAp9WLlwNeLiXSr6n2iynmqF7bVd6UsqR2TckT9ysliMW+I0AswqOwcAJCYMETi9LbjCYxrVJ1F1GbqHJwpr10CDYISF7o+YroIMJAAvvcM76P2A64LgbptvWd0PgqbOFc+wRqDja01uMbBTRzIEvqFhw8ebiSpQ3wQFZ5m7LC1vYHxZKQ5F8vCglScyPcytpmqbTKLOi9YaklILj+1P2TFoepd0mVpIXIEVQQKSb2jUv3g5WtHwEWsia4lmGUM8l7VLloh2TSNpPZxjeQrz0Q67dSNa0AkSkM+MAKF3GfKOJCeuTJSEpsCFYm1XlohjfnLDvpwqGYGKCmg6MLeA6BAQIww1qgiE2ERCaEX590Yg4YJgQkhqmpNXtwRmIoCCul4BM2raVXGM0l5DghXK1vZ09haXMM6r1/0+3VeX+0uXtnzZq0FXnrU4+gk4p5zdrXb+EVgzjCu3w5Yb2T+HU96HBovA69DW+d1HA8nLvr9Bm+AQKtxZmVfsrY8127y5qrPr+x5t7T7duSAlx3zOLa2mmufiREYp7YDDo32z3EP71g8MX32JOi1JuL67YDGHAD6VWasx+boqY9Z2cHWjloNlElaB2ctCED0/QBPJUAX8YrXZXJGigqm4KVSKrg6k9KxcXBFSvjscqHo4M9NCiyn+1Yb/IbAXIUkLYPCF/ksYXQHhsgZ+8rCuVLqz5LCKme8qIKY8wkDHLvGkCswM2owNlbHseIX8tPA2BFABhYhb3oUHJEAluC5YQsyFll1FZC05STYVu897GQNW9dfixAifIgYHzuKhQ9g4owXJjyJkwR2hRkPnm0JkK1TmnOquKqtMtJmLKxz8DEg+A6+j+A4h++9qIBLwcUjqFIr1LhjXb80uBdVd9K7VhjyckPmts14rfbX6h4VAIsMHCP1+3Tq4I/q1Bpkr8qmZaVB/ZRbKKg69Inq4AdD1LfrdDEp/pMuWT1T1u1Y3llZFSCphCQEOpMVlo4vot+poFQdR8ipPKxu3moaVYaW2AmlZCD6PLGqY+l/8jaFIClHiKXcMUDVRAqBpUbN0zPHyKqQM3yZRfW3hTFC9CADBC94tVHyQIqbGGcwGrca+C/eKVVVFlWZg3I9pPFquQ8ix5/Se7FviKq6J7OQOZ584GHMzl0osRpVad+68gQ2jh1dui4rXs2AYTSZHJKUX6SujCV0sznOPfgIovdCYikRDAAM6xyO33AK5tAGGiU+pJhXLm+pVTCAC48+jgf/+lOlRTQumLrb+YcfFdJWmjNyX74IIYu5kJC0iyeCEUch3uQ4iZFN2EbHB2NF9TrG6soJ96Y0Xqf7QKctk8eXpBi0St2yMgCI8fTzTvIAAOa5qoZcOtHjJ3/yJ3Hq1CmcPv38qo2s7AuzSyZ6HD9+HESEpm3EqbMSZO7OSLCzeAusgS4SwkBAiTqmodEaIARwCDqUSpoDQ404j0GIHuJAJee9tnR9e8B3aUHN+b8sqZemyqF8iDhiShuWexYnnPL6QibaomLAxVHnepoq6xEw4JlguASyI0u1xBiBECQHYCxB8cgkahNpgtRAOLFSB9SRABhEEUwBi57ReUYkAzYWwTqpGzsBmQaTjWNwroXjXRju0XceMfaIgUAxwtkG1jowGjAsyFqQNTDMsDFiOt/DznQHu7t7ePL0GfQ+ouskeMvG5DKJQ+CR1AAAwBiX64JzDSHnoMxpdPSZ0rPFvOpJf0dERExG69g6ehh8fhfndxeYd3OcnZ1DDJILUvInGmFHugZCvKDcL2qiB1JAPbeZzLoDP3JpUVSe4CAjZKIHoYIOKT9nukJm7CJ1Pc4B7HyptHZInkkOOOczK7KHqDmUdYj26XL36ro06K/pYwx+378oGfzJ5aPMNmYg+uJEszrdnJ+JVJ1B/hykPzKmlFffX2MYa1vbCN7j7Omz6LvFQUt1OSdJp6mjNFsEnN8TWbWRs+g6UemwFmid5vY0de5BuW7XB0wXEV1fRgwAcM7h5MnjGE8kTZD3Ho+fP4tu0eFIewjONVj4HqFfYG1zjM1Da2jIwZHJefigZI8QgMVCSWymei/khZcxRPtEGjqDkrATSSMpdMTUZ9P4oqUOep2+k/ysMZTcl7EepHRsy+SmJmCbC/s6BqDrGLYxGK+1aNsWh7YOYdQ2OHxoE8YYBN/LOGsAYwmHNg+ByODuux/EufO76DsPIFS3rO9dFnTGmMyWJmPLOM4qg5g73BCUL325ELSQiB6anSj0wqzubS2ZSOj0nWvaFs41cL2BdQY+EKxzUtchqanIGBRCWnQxDAGttbDOwloHa5046isnfWXPwLZ5G9eFizvYqyDUyp5PmzjGN5xaYLcj/PanJqvg04vAWsv4mmsXuO6QOAdu1OHkxlMTPY7EI7gp3HTR71fjzMq+1G15rl31+ZV9MW011z47cwb4qqs63HLMDz5nAH/8+dEXRPTYHjP+jxvn2HoaEocnj7tdxPlnfacvX1tfXwdINs0kpU2AEWYBsU+brVCC1BVUV1KoQLO8pIhkzPiJBMlswZtrIK+OaMvVZdzPGzKWvqc6/l5dKxVqHzymKFuFIdfYWkKTBL6oN5JVz5v+n2DPjJMBlDDkdF2jGwMVqxlkRmBKqLpUQybGpGoo+DeDQVE2CjrdLMgmqXcQYBoQGbh2TVKccAeC4NbMQQunm1xcC5atVYLRmIRbM3rfYdEv4I5s4+QbvlIC4UHabHcuCsJZOQBlo6dU+fJ7nTDbjNLr3zz8mf6nFSeXl82C47Ux5vMOi4VHDB5zP9cUwFH7qJTfGKudgcqdajCVUySAqhvWXW8JWeXq0MG1Dvgg47z1jdP3nD9L6VUGGDIDNTmJ0+kMFNJFuk6d4oerV8IUbtVSuXJ5Bo9Hg0MG5WYMIbGqrmjpOhxLML7UU3XtPF2mfr7/mFxMa9CMhEAx35shhAAKjAONEjFA2tv7iEUHWCINWYlKhyGGTem46zJqZYXA6ANnzDaVxhiLzQ3ZLBhiQIwRe/M5QgiYTEawqozTx4CmdRiNGnmvUryresbIgA+VOsqgDGVcqcMoNeSbNvjVrVDDsr6P+Oxf/BUe/czd+q5zbpeXf8PX4Po3HMHgBO1cDACWMQbn7wW/ZpAV5eP+7Az3/cX/i342w0TJf7FSzhlvrOPGl9+ErePHMJmMYa1R5ZhYv9SoO82jd30OD3/mbnlncxyAyjgeuRDH0nuDUu5cfdV1Y+Q8bTAARK9NUMcagKCbDo2VjZAmiqpHZNlczHp/McGSY5RxV+HsaqOgzZsFV7ayy9nuvPNO/P7v/z4+8IEP4K1vfeszOndnZwfvfve78bu/+7sAgG/5lm/BBz7wAfER1X77t38b//Jf/kvs7OzgbW97G37hF34BbdviT/7kT/Ct3/qtWUGk73v89E//ND70oQ/h3Llz+Jqv+RrccccduOqqqwAAjz76KH7kR34Ef/zHf4zZbIZXv/rV+IM/+AN8wzd8AwDgq7/6q2GMwe23347bb7/9OaiZy88umejhGtmlbZ0TUoYBOMYSYK0mc9KZhVIgPXu8yxNsmWhSWhjE5V3eZcxLk1Uamrm+ShUHlF+K88Dp5PR5/bcekYZ3nSbzRLjM9yss6nJdyoXhnCqifuSsbsDqTEWpG2FI1jvsZZJyzqFPE8QSiWQ4icuNfIgqE2bAZNE0Y5HTY4AQwH4hclsGADmIkoBR9rWtJj9hVwZ4xMDYmy2wNxMyxXQ+xXw2R+eDpMlQhzg3b/5fXplVpZZd/1zV/6Bec644rn5K3RprJB0IJEjtQ8C58+cx3ZvD973k3VNykbO2TPAoqVOAJNO2369ObVg/Q14blErf1w+KDR35g1iY2S3J/3vqq+z7hFA6vl6w7q/pHsN7pxdn6X7ZKdNnqhcTS45bWR+WxWu5du3rl1UxU2GBF2JNVSq79D6l//GwpKT93Ch5qWkbAIzQ93ncqS9SHFd5yWZTxjkbMW4sxo2QHXofYQnwNqVh2rfyQNfVKjv1t5zTv4AZhgiTyRiuadCOx7CtQ+g72UjCDI4BTAaRUqodyfmnam1Y9El5RhxE2zTa6aJISY5bue/ASaeMb8x7D4Cwvr4h5IJEkMptK/fte48YAubzDn3XI3JEiFJ+Y4R1zDFgOu1w4cI01+Xy4sA5h+3tbTSNQ6spn3rfi6Pbh7xANIawZ2cA1Dnfl0NX67Oq3DSHJEY06VKUkBjOhDodL5FB42QR6lVBKAMs+T3XXrjE2I6sDjZDdpukLso9og/w1sJao21dxvpyYFlcyrhPCCGCjDrw+v+D3uiVrWxgDEx4gjXIDuPVruKVvVBGBFgS8sAN2+GiAQ9m4JFdi3PzL8/glCXGNVsB6+3F/MGntzMzg0d3n77+Jo5xzZZHc5H41cgyNlpG4pGaA/zb/aZk2xfBODPiEY7Go1jQAju082Io8souF2NRrxljvO+r1Vy7shfS0lx7aeP1l66NHePap5jfls0SY3tc5rtkzMCVGxGvOF5y4Tw5NXhsr8aADra1JuLarYDj6xEjt//ayybL8Gc/9385m6SwFZWEpMiZsJFl2CzjTUPgqf7wAKvScsTBx/vBsqWrHny5hGst4WgVcaIUq/yxH+U+AINLIHGphAwS5mImyJqxvDdRcImEuVU4jUKhmgKDqmMLHrKvjCxBzRgT0mdgrKS+zeql0WcigSbTBcCQNBvA+UefwN7580iVvX78KDaOHkbnA3of4IMXNWgf5B5EIFMIEiVOcFD7pvqpUi/TAd8Pnqw0csKXEg4bOWI2X2RsLMaUppk0yAqUTlNulD/eV0TFr5cqli/2y76Ot9z5D+7f5bZL16HBj6pIS9dZqqZlDHmIBddlOeihqjgKVX8P3pPq04Meico5w41bRRlELp0R6OFpdfkPfJnlIQkEDgFnH3oYs51dIfQwL1Uz4dCVJ7C2fQjppeo9YT5nOGvgjKQ1ioERSUWGCCDiff0hRAZrGpjBqMBcNsFquZpGUntbl5QrQhFnSfGQqoGpgvVDqD8jjecoFmoNnLN6HaCbi4pG8D7XmVf1mrZtYZsGh686idHaBAwg+IBTt7wUW1ubstGNGd4HhBBw/NqTWFsfKz4L7Dx5BjuPPYFmYwOj7cMFQ8ZwbPKzBWZPPI5+OsPx668Dh4BGJ39Wwh4R0IxHgLPo+j6Tv/Y3+HKTs8QFIBujQdWGWK0+ayiT3iTFivweY4lT1sfv77KV8sggOFCN2TEiprGXSyyrxpBnF3bw6Gc+h/GhLRy+6gpYckgKTVmbKY3vK1vZZWjee3zv934vfumXfqnK3lDs+7//+wEAH/zgBw88/wd+4Adw77334pOf/CSYGd/xHd+BH/qhH8Iv//Iv52N+53d+B3/5l3+J6XSKt7zlLXjf+96Hf/bP/tm+a733ve/FnXfeiT/7sz/D0aNHcfvtt+Mf/sN/iI985COIMeK2227DK1/5SnzqU5/C5uYmPvrRj8IYg4997GMgIvyP//E/Vqlbko3XJgAkKAkAhiTwaa3NDnxtpGxfikvTHfOBA6gEQtPgPXQu0l9F8AgSYItU2KuDyYBU/qK4RYwqawzqIZv2TRyBkZ0BLM0zMgZrQC9NQsosJzI6ycdyThQJqETm0NR1gGVYw1nNI31vrMGobRGdVZWPMlnE7BSXh4rE4F6c6UAGbBuMJ1sw1mAx3wHHHjw7j0AOcW0D5FpYawGKYNuAyUowmlIIM2LedZh2Uzx2+iweeeyMqI54VuZ4qRdh2etLrqgFwaYIqFaNTl1pMMjeVZ3apXKC0gpNfzajBqPJCIENAgx2dnZw5rEnJBWFL73FaiqJ1ByAKl3kbQF1b8oHAdqWuW1BS5NznZoiOQFDubT9pIFBd8m9NpVt2SGndJHlvlY7z2lRVzl+XH217/iL2WDRWznTVRn3M6MpP0N5XvlG1kemfF57vdWPtAAtReTchZggL13lRGW/SPPVTTbW0PYt9nZ24HsP6zRvYZQ+1vdBiQVy5tmzjHPngLWxxfrEwVBJ8yJl5ZzqhlDK1vUMH6LI/HE6Vp3lvgdZzUFIhMNHt8FkYBvZ9YDZHny3EDnIGAADsEGR4zME5wieCbtzXWgYoJ20WB8dkoWs9xhNRjh64rAojkTOTikRoXUGgRlnpjOQdbjxupuwPlmHCV7emcQ012fzvkMIHmfOXMDuzh588AghoGkcmqaB7zv0/QIPPXga58/v5QWvDGmqXkTAZDLGqVPXgoiwc2GKEDx2p3uS+7JX8ovutLlwYQ4GYT73oJS6Sd+EYdfiXC/WCaO5JmikB3HWoG2dsNijLLwmkxYhMnancyFkpHqyVDocIxNzMkEvs/ljmTsAdOggEqQWMBYmZxkTQpwxshgDEyIT0pKYI6HrJGVPYEnH5dkLq3xlK3saO8pHcXW4ej/AsrKVvQA2dsA3XL8Y8qAriwx8+O4x/vLR9otbsMvEWsv4ulMLnDoUnv7gi9idj7T4g7tHT3vc4UnE//mSOTafglTydIGpF7Nt8ibWwzrO0lnsuT3EfWLnK1vZxe1EPIETcX+aotVcu7KVvfC2PY74+zcvsHVAKpaL2cXmu6840Q+IHh99sMVj9zz9HHtsLeItL5ljvWXY1bDwvJprGsGrTEnPyyybzuI+nA6QNN5mP5yVIKbB5wX34Lj0Pdd/LoUHKxwsfZXxuKVbpuvsv9b+jsMK9u0LVC5dM6tW5B09lIN+ySIrjl49j8A0Ra264J6CeVprNb1AKVB+1BpDhmIzUTYAMYmih3MjkCEEvxD8s18gkoFpWsBYUURlRlJ9uP+Tn8EDf/U3GZm84atfh+tefyv2pnPs7M1ETTZy9cwVdr4EzxKMbBjLOGDBb1A9Q3kAKphzqYj8vbWCDSe17G6xwGx3T/pJlV5B0i6Y6kwo2rrUN/OvNW5crsO83EMIgwXV4Hw59qA+V1uNIYMP6HGMEtwY2BKGnK9SYchPddPlG9Hy98sY8sHXXH5d86MSFACuAuy0fMUlj215s27CkIedenB86D3u+didOPPAw+gXHWKMEujX88gQXv6mb8A1m1v55PkMmM+BxgnuSkC1wVBjADXUrb9LTKcQOlIZGJJaHDFkUaLxZAwhPSk5oO9BwUuqGX03DKV3Rje9Gem2nS8DknUOrRsDGmtxzmKyMcn1FqZzPPA/P475zh6sIUQwZr0HkcHhQ4exvrWF62+6CUevuTp312tPXQNE1rJEzGYLdItOiRQSc7HWYvfee/DgR/8Ch2+8ESduPZQGp7z5MhHE5hcu4JGP3YnJ9hZe8ffehGZtghh7QAk0dduza7CzO4X3EUD9Ti7HD+t6KRttKX8l3xsSjDnFHCSljwUzo+s9kqK/XAuoO2zGjlNfq8almgcVJH0BkqJz3mtOojKe0rKcfegxnH/0D3Hi5htx6zf9PQmfBIlCOY3wxKHe+cpWdlnZv/7X/xqvfe1r8fVf//X4kz/5k33fX4zgAUhM5kMf+hA+8pGP4OhRSQH1sz/7s3jTm96EO+64Ix/3Uz/1U9je3sb29jb+6T/9p3jve9+7j+jBzPjgBz+I//7f/ztOnjwJAPiZn/kZrK+v44EHHsDDDz+MT3/60/jIRz6CyUQ4DF/7tV/7hT7+i84umehRB7KzJBJBHMMDGNlpcpYN7uKIVTHegWW+BC1JcaE41kOnCgBxyaO4dD2ZGqr0FEu+dhqbZTKQPdiD4DJISRXFoUjOdEy/J7+zfAGmFFRUZ0p38yciRxLBAIuUFUic66wewFJua0SuK+cs1HIZpIVA8S5S7sn6H8OCYSUVDkU418AYBzcawbgGoesQEeAjI8CjC73mK/QIwWPed1j0HfamC/Q+aMqHeoIrjkeeaLO3lSqRBi3J9S+V3yvBVFLHHlpnrMoxsji0rsFi3mM6n2Ox6DSoq04Xy91L/xuWYfmjQVfJ64ZE+6H8RMMCLxX+EozSc6Yz070yYz85+FpLy8xPDPte7gnVGkbdqVz2emlRP0TVXbLLTISsO1CqLn1boymlXg5arGQGbD63euiBr55kK0sF5edmgG2+WikByc4EgDFqRGVhMm4RY0TrDIwhJS5EnDu7g+nuTAhYFaeo94zZPIhahCm1lJy5VCZhRBO8Twvq4dKEwFl1gjnKMUacseADQJIeBQCMkRy0iMJ8BADrLA4d2sSRI5tZTQMEkDEiJbm+Lm0dAkZtg62NzbJQr/q4s8IsD7YFGYPGWhhKcouFpJRIL/NFD9/3mM7m2JvO0Pc9+t7DWgNjLILv4fsO0+kitzZX410ifHRdjzOnz4GIMN2bIWh+U2YhgYFZU+oSQCJ3GXxJ6bRvsZZrtwImSHdU5L5TdmKEpJTEMl6GqKpCLO/aQP5RJpOq3xWZ2AIYpFmlfl+SPKr0oUgAUczOfV7YGl30USIayr0Xszm8s/DeP9WafWVf7sbABBOMeIQ1XoOKc77QpVrZymSOeYquGOKlekCXh22PI46vPXtSxrKNHLDZ8iXvQj7IjkwiXnLU48qNeOA8MXERJzcjTqwHjB2e9l5kAo5c9wjWjlzA+NDusy/YZWYEgoXFCCNs8zY67rBHe5IbfGUrq41FqaNBA0D6zpjHsPgCXtSVrex5NGdEHWrsDh7PGMDjexYXFpczm49xZMI4Onnmc+yRScTYfWFzKYCskFJf5uhaxEuOlBQvy3PtWsO4+YjHOhuMHMNdzlX8JWKD3dJpfQ/ZuZww5DoInYJuacm+z1eqg3H6d04XnD8t2CAhQVhls1TGlqtXsMZca+MKwx6iQ6kQFYZMKDjt8KgBvpJvnwq3/EzVvRI2k9aKkQHDBT+ud6UbxT24rs5hUfPfw8B69ZMNCBYE2YBIJOrKDML5Rx7FfHcXkWWDy/nTpzGbTbF+ZBvjrU1gNMJ80aHrvaa+LeXPRcmNOmynXM4aQ6Zhmet62qfwoH+LOgfDWAsyFtEH9N7D16nhM2kAB9y/ro/Bh/vqc4iFL/efZ+iv6m1qOOugQ9JvRVH5IhhyDRrnH/UbUn7bdy8ux+V4gz5g2TQ7tPrN2v859p9UdbmnwpCHuh9L57G8n+D6fU9YN4FHLa647hqsrU1EVYYl/QpR2ohH2Dh8SMaOBHym9ywyeq8KzIGr5y8NlbqKpCHhUmFLGHL5NL/08ndkMBWClxAD5DppoyARwU+niLMp1re3sXHsSL6nsRaubeXKuhlu3I5yp17b2MSJG29AP51pynLGIgQQETbWNjFeX0M7Hi+NzwawaQOu6BQHANEL5i7ECgM0I6yfOI52a1OeklIjiy2mM5y+70GE+Qyj7UMYHdqCjwzyQeoKjKhK2ILLM9D16OcdQgiIHC76CuVeq/h9wXqHnYRBJfuX9pWEJyeSB9Udqh6cAYA0opib9AAMOf19QFmZZWOhYWnrGAKmZ8/h8bvvwXhrE9snT8Chge89jDEHqiSsbGWXg919992444478PGPf/xZnf/EE0+g6zpcf/31+bMbb7wRi8UCp0+fzp+dOnVq8PtDDz2071qnT5/G3t4evv7rv37w3rdtiwceeAAPPvggrr766kzy+HK1Z0b0yP+Si06SK7DSoExTWXYxWDbr2zwB6Id5MkyOBKuyBGlgrRyb2M51qsR8HZSBtp5SDZQQwUMnmSPnPF4SsI0Y6vwpOSWacm8kP4oR9BopRUu6cQweBCppH6rnJEhuN1aQnAiIPsJHyEQWWXeJC0ty5CzmxsBrzsQckK/rmGU+tESa10sccAYhsAPYwdEajAUmGxPYpoHb2AI5hwvn99DNO+wtpuh8h53dc5jN9nBhd4rpdI7ABhwNfBCVBMKSu5v9xWrBxDLhZlWHKkg9YENqg0R1hMjqHn4ygNH6JsZoPEI7auDaMVw7wpPnHsNDDz8GR4TWioNhnC2TNUo75wYD5YUE58l7OAsXegLp/F76WXbd63l/sESsvfGyIFl2cutUNLnPkAS4l/NKlnPk+kVNJFa3qe9V378mKRRgI32WyA3KqciqA2l9SaTSmrrjIjl4BnXwXVjJeZFGKiJBqS5JnzOxmqQNSL9P/ZjUGVzOm5dIEK0VIkfTNrDWoG2cMIjbFsZYrDUGzgIX5lPMuwU+88nPY743yxKUIEn3MV9EzOeaxzS1XU4vU6Q+RW1DCAqRlxc8UkbnLKwzmC8CYgywWgc+dIjMMBxAYDRNA2ctprszLGYLMAHtuMX1N57Ca179svxOCGnAAhDSGqcyEcFZYQVHY6QdgrKFtTxH0zsVI2I3y2NrCJLaZj7v0fcBF3anmM8XOP3kGezs7GC2t8B81iGoDF8MEcHHQf9jaCZBHctiiLhwbhd//Zf/O4+DpV+VfpHdZB1fJ5qPsjitFRko1z/BGgunRI/EfM/jBcsiYN4JkEgMYX+TyvoFkTo02mcLMzy9mwYwgLMGRDLeckUayZMN2fJuRdk7LCQTXd7ooWQK+94osYWMhVkY9F2v9zWlMla2sgPseDiOK+OVK5LHylb2PNpLjnj83Rvnz9n1CE9PvHg6u+mwx3WHPF5yVQdzwKt/bC3itpfOsN4ymksIQLlRj1e+5c9w8pbPw7b+6U94kdkGb+BmfzMu0AV81n1Wd06tbGXFDAyuilfhcDw8+GxlK7tcbeyA/88Ni3pT+cAiE/7g7hE+8djlrZ718mM9vv7U4hmfZwiXNL89G3vpUY8bD5e5cHmuvXIj4JtfNoefX9ocu7LnwJawsRLmrHC0jHAMoTXe9yFqkDifK7FTBex0AwazECKWA3L54lRJ8qul9X8KAiYUOG0KLJs8uOAIlXF+tv070GN+qEo1FlAsOil6lCtGDULKphnKwXZKG/CWUg0TkQaxNbiZ8My6/ioznAKkJj9nZFFYNdQI+btxMNbCtCOEEPC5Oz+BR/733ehCjxADZtM99Is5jr76Zbjq1a8EWYez5/YQOArGt3TrEkcvGHKGNYkVc10CvHMN8iBGYBL2WOFQDFE5cE7S0BjrMJ3v4sKFXdndT8g77DNWX7XdoLD7MOSh0fJvqQDDXw+o+6UPUqVcrKGWypneJ973HiwfOvx+ADUfBOzvL7l+X+o4Yb7LvTvjexX4LE8zBAmL0kNBBEsTpvqu6oEyupz+rC9WKbhT3rhndXOfsRZrayO84ba/J2VXrLHRVNoL38OHgDNPXsDe7kzurC8MAfCe4BEzQSthyHVppUwpHcgBhBkBD2FM2qDIGvyXOohR01+zRHGMlfev7zQ9Pclmwdnjp7Fz9+ew+bpbce1rX6VgumyGXO6HRiXsmQjr65s4csWVGPSFPK7K+2YaJ4rtUYgw3kuq8nknKZem0ym6RYe+9/B92gAcwZuHcNXf+mrFRfPV8xB9/rHH8Ynf+wNsHDuKV7/lzRitT7C7NwOm83roHvYjIvj5AotugRD8Enlp+H7kjb5kc7+o6z/1NZ+wYQBBZMR1LIkSv8rxkKpQVcc0ZJQYxIOY1v6XvBrbqY7/iOqHlJVw5sGH8b/+83/F0euuxa3f/PfBE8Gnswr9ChZc2WVof/Znf4bHHnsML33pSwEAfd9jZ2cHx44dw3/9r/8Vb3zjG5/y/OPHj6NtW9x777244oorAAD33nsvRqMRjh07hvvvvx8AcN999+Xv77//flx99dX7rnX06FGsra3hL/7iL/Dyl7983/d/8Rd/gYceegjz+Rzj8f40rhfLxPClZpdM9Eg7ockYHcQT00+/P/Ck9Hkd9EflONc2dErlnsjBvsE5tc9QHSMOWkpAQvkaacKR3zkHm8tnVIVQq3vs8+uKykbQFYQ4ioSgrGVR76gWDsoWreX4GACllAJpx7sG9o0GeckYVUMp1ZbWo/XcMlxilOeQmcmBCfAQeT32EgSezmeYz+fYne5h0XWYzmZYLDosOo+uj7mt8m58KnWT6ri0L+UKzqz0uky5EVOfqco3aB/Orl3+jAiLvsO88+i7HhZQpvpScCw7i1z9TerIl5eZjJyXFmbJdcwupQaafe+BGIcCJfl5cMCH1ZdZRhAYXGDgjOt9eXjqvqstkz/qW+dLD5nwaSdBinNnJ1v/zgNbWhzl5+DsTJfvdTG0fB+VayQjjm1SyzDGwNJQ7YBMyo8ii8nUh4nSoiO9t3KY0fMaJ864c5I2o9Vchs41IGMwdgbWAGskC7rxaIS2acDs1TFU8hSzpHdJfUv7YlH2SItci9FoDGbGfN7tbxAWJ8x7g/lsgRACxpMxrBWSAoiwmPUIfZ/HDu8DvA8gAE1j0TR6bBrTDIkMpjqbgJK6WFjcDCWCMcN3HWJkebYYhZUeI3rfi8Ot5Y36/aLz8D5gbzrHouuxu7OH2d4c83mPbtEjhJBJDzGx1JeeNy0CoGO9yOhV427dUUoPFJlRU8a8g0b7Qlgq40t1xerSVTIg5tyvk5pHVdxB4YtkKulryaXPV6vFRORLZCchVsXqmgMvXqtDyh2jvhMcCpkl9fkv0GKMOH/+PLz32NzcRNsaXHXVLtbWvH4PPProBnZ3L28QeGUAWBQ8Gi67jSc8gbt092tlK7ssjEiICNdve5yZmct0tzHj0IhxeBJxfD1gZPdNMS+oWSP/JIXy/rnRENBa+XdJRgw36tFMuueymJeNEQgODi1abPEWOu4wpekLXayVXYI9+eQEd911GEeOzHHs2OwLvh4xYY3X9il1GBiMeLSaU1f2ojGipx7jQ+QDiYCXmzmDy26OdQYDlY7ludYQMHIs+yxW9sUxBoLvsXP6SXCI2DpxFMZaXHjsccx2dxH2dgHvsXHsCEbra0uuEZWL6Gaw9GeO96b/cTklwZf5u0F5OGMZNTqX7nbA4YMYvBxT8IOMae5/7Or4AirH/IlsSky72/fhuhU2OsDBFSxKOOHa9iEcPXUNKEbZdEQ0eG7GEJosqsNV0DIpRpMo1e4+/jhC18M6SddiGocQIi6cOYvpdA/toU004xHs5hpCCBhtbcG4VjD4tKFmqT4zhpweMm3uFGBumHonY8oJV+YhrrpU4aU90vEEHwLYR8SgKTOQsM/qJhUxgVL5UGHHBfysnqVWAag7BoFVUZdp+NVBOO8QP1vCkOsvefnki9fDgbZUdbT8W4LGUpvVOxwHGPO+Mys4sD6wIGhLECESPp8wubKPmArmTGkTKNVFrHDr0rFZ/06bCaFkJ0A2z4pqcNqgJZOVMwRDDBMCfPDo7nsE5x58FKOtLbTr60OiDJfqr3TNqyeTckt6Z8F+sXwcMzhGxCgxhsgRzjkhf2i6D1FVD+LFWuSNi8SAsYTJ1ibsVVdi/dBmSfeSiAG5V0rVpLhZTGW2RuNNokidCAshykY27iT1mXyvRA+O6DsPHyK6hahBe19hxzrA2qbBwKoBjENE33UI3sM4C7Ku4KgH9C9A+mnU78uouGR1+yxdoB5vBsFcrlDdp4iviCWMubwHeUgiUhWZ3J2rYwhDDHmp2Jww7IB+HjC7sIPT9z+IyeYmDl1xPBOR9seXVrayF97e+ta34s1vfnP++8///M/xjne8A3/5l3+JEyf2p0pdNmMMvvM7vxPvfe978Vu/9VtgZtx+++347u/+7rxhFwD+xb/4F/iN3/gNTKdTvO9978N3fdd3HXitd77znXj3u9+NO+64A9deey2efPJJ/NEf/RHe9ra34fWvfz1e9rKX4fu///vx8z//89jY2MBHP/pRvP71r8doNMIVV1yBz33uc7j11lufk7q5XO2SUZEkR2/JAkzwHCV3V4wQzkKZ8ACZREhTmQAAOPuleRJIQy5BHMKgMTbiMgdI0DPohCVnpPxmhlXuCioQknw2JhDbfGshZxQn3BDDEOkECEQYVOJycm0jk13QScLoTSMTYgR6JWZYXSku5h04Lxwo55Om3gMIoBhAzAjJaQhSbrlsGdGds5iMWzhnEWJyfpUbnpjqKMQEeXZGYCCSAcNqnkVCtJL/bc8D8AwsLiBGj0fPPImd6RTnz+1iPpOgttQ/I0Q7DIYiMRMLS1KcMSu7/dPiJMrE6TloGxn9mRq7mtEr7zAGaVfWhvfSBeAYsAycOXsO585fgCPC5rgVqcCou/6rWZQI6thJHYh/mFYMwsYcTVrZ1d/HTFQASJwWBkwjJIIQZpr6otQBpVm9mn1rN64MTxFZ7WafY16dwcN6yHVTXWf4mV7VlIVHcmgZyTlO3sbQ8RHlEHVslh39iiCVP9RfTbqXDr6Jxe0gfaRpHayzcM7AWYNR69C2Do1t0LgGjbVoGwsmA9Z0FzY5QRxkMZjy7yVWcSoLSW7WtBvAOHGEjTKeU867ph0jhIDtrW1c2NrD+Qu76Hsv6V2T5J0+UHbIKiMA1lhMxmNcefwout7j4cdOg2Nx1NMifDHr0HceTzx2Bn3vcfzkUUzWJjiytYGmdbjv3DmcO3sBG9vrGK+NMJ8v0E0XaNZarE3GcJYQ+k7HHICigTEq82NKShKOjNh5xBixUDb1zu6eMCd3d9F3PXYu7MH3HlOVtwshgmN634pSEKv6SlJhSeSt9L4OPdhl8tFS/+XBj6oPDetVFhGo1ufl/S4nVPfWCyy764Qy7qaUXqxtKuMniwIUhoCGjCu9XlbIXSFKPRtd7EmfLgvMXCJVOUkpYlCuPlhYxnTDpAoFQk+9jEN6jy/Euq7DXXfdhdFohK/4iq/A1tYa3vKWz+Pmm88CAPre4P/6v27BX/3V0ztWK3thjUA4GU7iaDyaP1tJyq/sxWgE4Kuu6nDrlT3+n3tGuPORy5No9orjPb72ug6NPQhqWdmL0dZ4DTf7m7FLu7jb3f1CF2dll2B33nkl/vqvj+Pv/J378Za3fP4Lvl6DBqfCKazz+r7vVnPqyla2spVdnhZixHx3F5/64/+GbjrHa77p/8Da9hY+86d/jsfvuQ9xugfDEV/xjW/ClS+9CWlTTo1DyCamsmBPCh4pzcHy5qm8TOdYYc4JC0qIWcJ5CoYsWKsBVD0s4dEJUbRA3lSVlI053VSPoZQeANVNU9GZiqqxpquNPtSRRHDCkIMi1RyRtxAyKnxC7OQtL8Xxm2/Ek5+9G4/9zadgjNyDMuaCUoCEITNlbJchAcwUOO7mM3z6v30UF544XcG3suP/3Pnz6HqPm17/Ghy/6cZ8PeMaVaeu8U3Om8+G9W9UMKXUPwa4S8LtOF/noOBn2sCZKDIJ1zd6+Gw2x3w+hyFC62yu/9x/KiuKDImEUFApIoJtFMEMCRPSEurGLDJWUi5zL6mcq/Tvpez7H2KIfRU8bD+GfJGTDsSQl8/VbVOZvLJ8Tr1pUCtnKYv3wbfh/Z8tXY8OuCdB1DWMLRsGnTU5rbRVAoS12iZU6zCXtzHHdrhs4tUAgL772p9U4SKpZkA3JRrLCN7j8b+5C5/67/8Tp/7WV+HkK18+OHc/cI5B/RtDaBqHjbU1hBixszsd4KtpGPM+IMSIvd0ZYoxY21hD0xAmYwfjDM6fnWM+X6Adt3CQNNChDzCNResanHjFS3D4ja+FcQ4xhoyDy4PLeJMJEopjesWCF10nmPJigRgiFgv5u/dK2tBdzGkTZt7oy2kDbr25mwf4bqkbWurMB/ffAYZ8QL9JY3m5fIUZD0Dn4c/l9D6lP0DG6LTDG9W4c1AhmPOckb6LecOw3sNQuVu+B0AxglnjF/uev57L5K/zjz2Bj///Poztq67Erbd9I0bra3kcWtnKLjdbW1vD2tpa/vv48eMgIlxzzTX5s3e+850AgDvuuOPAa/ziL/4ifviHfxiveMUrAADf/M3fjA984AODY77lW74Ft956Ky5cuIC3vvWtuP322w+81vve9z78q3/1r/CmN70Jjz76KI4ePYq/+3f/Lt72trfBGIPf/d3fxQ//8A/jZS97GRaLBW699VZ8+MMfBgD89E//NN71rnfhHe94B37sx34M73nPe559xVzGdslEj8ViIY6ONxo4FqIHvIeNAa6xAI/ggzAVs/ycznCcJl8GKDGUs++jAUaVsMiOt947K30oPTZCnLjC7pXAcNrFzfkeZTBN/zIhBOmaB+w6ZwYHLmxKLVpiqRQVjhJMLoodadJB/rz4BclhBWriSflJ2T8hgk4kyAuSxHa1BJAxcM7BWofR2gSTtTFgLAIInfcwDMBIsoqu6xFCRIwdIks6h9lijvmix0LTDRCKGknKRSbPL889YIJLi6lcIOc2YxSHbuDR1wuxHG0fOsrCYkTuP73vgQXDey/BfsmTkOshryNI07gYgksOISt5IHFZmWC0vogIIXggBbw5ZodGJujauaseZJ/PPJyEU8s/dXy3ckxq/yAtLKtnK7kGUz+Rcyk7u+Vm2f0d3DzVUVIdKH0uOSpmUIeAtVYfQhnQiSGd6tuURTaB4BohelhrYA2hbSxaZ+GcQ+MaOGPgnJF3U9VUUqKSVJ6UsijXn9YB6wojkjhbRpVBiFHJrJEwoS2wsb6Gw4cPYdH1mM5mmSAi1x4KDHKuM8A4i/H6GJO1CdbWJzDz7sAgPTOj7z1MJFXbKKseIaiocxojgg/oO6/5QCMaMrCNQx8D9qYzhBjhQ2L8SuMwyVgTlJwReyHRdX2vyhwz+N5jbzqF73vs7s7g+4BF1yHEiODlPUx1mNPrqDdeO80DZ334kOmA4k9fig0OPGBhVNV3WRvIYJDmgJz/NjvW1WoqvzKlUKkNOd9K+6hekFTOML0jqb3yoq8eo3Mhy3sk5KlUD9Lp6jXNcJRfWvktzyfP0rz3aFvClVfu4LrrPA4fnmNjo9fvCCdP7uL8+RGefHKyUvZ4AY2YMObxRQNNBPm+QXPg9ytb2YvFiICRAxpmOPPMxrixYxwex7xLeRGAMzOTfYDn0hoLrDX8NP7Yyl5MZvS/Fi3WeR0zni3Bes+tETGOH59iPPY4fXqC6XQ1xz4zI/S9Rd9bdN2lkTAsW4x5fNF2bdCg5XY1l67sS96IgMOTiKs2A87PCXv9M1fPGlnGkUlEH5+/uXZlK7sUC8HDe4/57h7mO3s49/CjmO3sYn7uAvx0hvX1CUZti346xflHH8Pk0BbatbWMFzCVNX9ef9dYbvpwCGpIgG8f3qFKGjXyRENMQDYgcoYg6u8GCHWOeC5hChXOXRAuLQfX5U+4i5aWad+1BjSSJbc7QSbWOZimgW0qWL+AhRU+KZrIvu8xPX8BBMA2DXzb4Bz3aBoH14zhFz3QNmg3N7OyLLNsuhwZA8cR7cYGzKjN10+Ye66hCmtKpIeh0HFdP0Xdt67ewbMM/hgeQBp4TfGHyB7e81D9lUo5UWfYVWzd5AVDhRtp2UUNQnDMGEN+WM7tKak3yiaqpTJy/QstPU/VQ2jw18VtCe5dlutYRuDS1wMCzb7A/AEYdY2vLV2f8h/avwqofDBWTeUWBJKNV8ZIym5CxpIlxYkV0WPdlJWuocie/Fbh2kIEUWQwYerp4IQZUylz/kkMYww2trdw9OQJTNbXUPEB1JbaMb9MDN/16PammKxPsH1oAxTowHUnQ+JFlNIzDZundHuWPhuCbFCLMcLAgZIMZOMQmNEvumHJSM9N/TIRPfQafSfko67vBVvuelWJDpqyJV1MU0VlPFg+q7tvPXbtx5CrQh0IEVQdjoD9Xf1iuAINjhAlbFUXp+Xzhg1QUOkhhjw8VgqTXiViKri0niGPnLBmvUr1mmfsGNXrWGHcB73TMQTEEDDf2c3z3uaRwzB2RVxfGWDMMRCNwfzcpSA+yIjGMObYMz7v7/ydv4Nz584NPrsYwSPZ1tYWfuVXfuXA766//vocp/ne7/3efd+HENC2BYtp2xY//uM/jh//8R8/8HpXXXUV/uN//I8HfveOd7wD73jHO56yrF8KdslEj9NPnJaJ2egu6CjsYsczjBGxvb2BkdnEEztnsDefoV8woidV/GAYIwQFRtpRzgAnjQ6SwLuP8lkOWIqD3is7I8VumVWVQ1UA2DhEMCKLMoONDMQo6g/JwQUjiTRYw3AQp5U1zYPsfFd3OkSg71VmK+X5JAARMOrYBcnvFbwO+imgqMQPo46A+Hv7A38ESfkiPBWG5FnTSSBGcSqdAxmCtZoawxIaa7A2ljQVG5tbaJoG6+traJsW3KxjzhZ7uzsAGEwGIUY88cQZzOYLSecQGMRSxuADmIUMAkKpKa4WIvJUAMe68DqhceUNiWPXWulSIYrXQIllEAWkSPUUVNHEKXN3tDaCbSy63XNYzBeY7e6B+wCLBmvtRBwSbW+raUKMtbDOoWlbWGsxahwYjBiQHZlE4jHWYm1zAwDQ+Sl88Oi72cBh73qv/WvoMBRHdeD56vxeOTZ1P6jn9Nrr43S9/D8QinoGm+TMKqiT2dKqRACunFAqK6vsSCcvWp1vkneFIKQIY0jl4ghNI3U/aa3U33ikjPRG1DIMq6Ot17IWICPvTGQ91iIxukjLYw3DqEJFDAwysbR7zkGqCzste3KQpJtx8uEzc55i1OdW5ny6H8ni4v/P3p/G3LJdZ6HwM+acVWu9zX733qdvfNzHdhJu4gRIiC/OPTKENDTXl/sByRekGBQFy5ECERJEEY4CSNgS/OAHIEVINFESIAgkckEkIheZJIRLOuPw8QU7cT47TuL2nLO7911rVc05x/djjDHnrFrr3Wefzt2pYe/zrrWqatZsq8Z8xjPGeNVrHsejjz+AX/7l/4Fnbt0CIwMTssd026XbAaxPj/Dw6x7FlfURHj27jtu3zvGx3/0kYkoouwQGcsq4c/tc0tUEQt91wkSHHEsuwTEQQBgvdhh3A4ZNQhwTVj4gnJzi1sUWH/7Ix7Dd7nBxvsU4Rmx3onSnGEt/yfNI5qVtWm29WISOnBsyHYxdXefiZF62wvMf5scByVlY07QIsW+mRD/bHrRsBO1/7UbpEoVcB6kdoxo5g+vp5VlVHQ4qwczWgZG9tN/UKyalpMVQmT/QzaRdA82jaTl45fZZQQ5SxZ1Lhc1rpqzh9ln5AuX4eMTb3/7r+IqvIJycjOV37xl/+A9/BG9962/jX//rN+BXfuWRF+2eizw36dDh1enVB72MTRZv40Ve7vL4lYRv+ZJtibLxu7c9fuKDa1yMz/IyWWSRRo74CK+Pr8dpOsUv8S9hgxeeEuSQ9H3CN33Tb+L1r7+Bf/kv34j//t+X6FkvtRzzMV6XXofAl0MTS3qWRV4OQgC+5vEBX/nwiPd9ZIX3f+K5E80eOU34Y2/Y4qmNW961i3xO5eL8AhfnFzi/c4E7Tz2FX/m/fgrkCGlzBytPePPb3oqHXvUK/Lef/o/48C/8V7zx69+KR974xoJzFNuqGdYbQyQrPGtYQXWwI8VRpA4GI2SIZ7+k9xGslFENsN6MpahkEHFuA5Al5Y+cn2GpECYe4hGARrSueEABCeUcTQ9dUpVgih8UA/vcPliArAKGSB1bL3BWpzDnahRTEpjZEaELAbc+fhMf+bn/gjSM6LoO3nv89mql6dkZ/ckxvvQPfT1O7ruO8/MNojouZUZxqPF9r1hZaywl7btWDC85JA2GDEhqDVSMsDS4MBW0fD1sDmihE1wzjVukOCLuxNjtyKPTdBF2J/EbI7nWOXh1Agxe2s6ZFHeTyL4MwZQ6NTClLOmPcxIM3QpOaY79NJbsiaG3HdC5beAAhjzHyQ7cpQHd6q/NuTUN9xQLbavY3h9WJgBqnP4E6xLHTOeFpNF5cbgMwStWLY6ZnizKhtVN2TXmXKnnWYNbEgqZvSg3hH2i6vg7QQpR15WSbQp8a1mVC2mr7UCZx+QdvvIPvRVf+gd/Pz791A08c/PcbnK5yKTAnaeewkd/8Rfx4Csex2te/2pkEG7dORcH0rIeAc6MYTcWzNrbmgQKJk4sToN5TMgxIUVGTlmim3Q9dkPE0zduIo4J4xiRU5bURAUTRiWnlShG0oisD8GKvTfnlgnRYshtW3kyTneVUg43c6qVmQ5yiUpCk3+TGTt7Jt4dQ66X8eT0Go2Dm5+pHGPXOmlD5yeX5/10nej6Ko+yulasv8RvMJfONoTa7IQXz9zAf//3P42zhx7EV3zLH8b67PRwxyzyspKueyWeeOKDyPkzL+l9nHsAXffKl/QeL4Z84AMfwOte97rPdTW+oOSeEZNhtysvbALgIUbg0xWwCg5XT9dYdR3OkTCGFVLaII5DUa6YJTWIFKKGuzx7mTj9jVGj/DsG6QvKQlKBJFZDVmW+pCNolG1TBCfvLj2esyhkKYvibpE75NWkD3q2iB5aN3vjzN9xpowbU9jpW6ZE45ANRBu6jAAwOQBiUHROQkoxEfouwBNh1fe4evWKEj2c/gWCdzha9ei6Dqenpwgh4Gh9JNEqfAATMIyjRg2QsF13LjbYbQfsxoSUWRQM2EueC9NQ6lYjoRQpCnejhJr60JxITf9Uw/D0uA8eAIFJUv4kzkgxAyPBs5fPGeDESCnDuUbBQDWoWn66wrKmms4lK4M1Z0vII9E6hNgihvlskTyq1jgjZ0wHubzwqTEQN6cxuNTHNqWsFT6k5FAtsCgJdqcaNaWeKJsZJ1E4TIlAw5h2zWauUYpl46TlkSjlIXiNcOLhHWHdB3jv0K9W0pcuiNJOssZJyV3Q3IaZdHeq5xXihm6Cyem/zLPNTdsHJQjlgQ6noiNOmbr7GqEd6boA7wnHJ0c4OV1juxkwbEe08699FpCTdnV9wNmVE5ys1lgfrTCOI45PVgABF3Fb1j+DEWOSjY3+887BFT5OfQaJZ4CE/cyZJcLHbsRFjMjbAdvdDpuLrUbkEJZ1irEQOqQ8BQmKQj5tcG7WpF6wp8/WQ8+imJfenSquk2NlcTc7SWM7H9gg0mydzAttqW/ySOdmo9aeheYe9nCZlnton1D2JKACShRylJbT9pecUt8BxAw4SfnkySHlhBhzBV8mrTJClRSWDr4onp8QAaenI65e3f/95CRivU7o+/Si3OvlKoEDen7+3todOqx4hR6Lx/ciLw8hAFdWjIdOEu4MhIu7eBuvPOPqOuOB44Qrq4xeOU8XY8ZDJxm3dowb28XbuPeMh04yzijD0Yvz/vhiFIvq0XGHuXb9YggR4777Njg7G3D//VtcvbrFww9f4KmnbuPGjTUuLr44o0k4dlhhpR7FL67Y+7VDwDEfg/PhexzxEXruFzLHIi97IQLWQd4L/XNMQbbyjLNVxgPHGVdWGYmxvGsX+ZxKirH8i8OINIxwjnD9vlMcXznG9Yfuw9UHruPk+nUcXb0B3632dtG5gHTVIDmBhxqst4jhze3vNCVx1MjOdhJPbtHY6zTdCDSyc8WVK9GjYsg1YgUmsEEaR1zcvIlcSBJk/y8YiGHtXMHCaTHqfGa4nznsxc1WoyN4rNdC3HAaacEct0LwWB+tcXL1DHkY1fnLoe/kPR1zhFv1cKsVaLWCSxkuBvicQZmbyBcawUINltQMyGTsGmBHcCHtd0xPotL/1bmIWl2YhKgC55QsAEm7nhlIEQ5OInhkI+GwYrM1DgQVvJWqQRYo2G2dD7kZU0k0bSlauNgc2ogl7Ti3GFXFdq0XpjCSjHrBp8jG/xIUqTkuBdL0dqAD97DpUtva1kkwZJtP03sVHNbmJFFxhHJOMOng1EYRguBhGoXDtUQPMAwwLZFSYNg9o01zU43kOLh+pHNmOBvPj7ffedK3E9G+XJ8coT9a4dOfeQbbmzfgVyuEfoWDwsC422J75xzjxQYnZ1dwfHqCrgtIECdKQJyUW1tIzrkQk0jT1bTtnGDUVOcF54ycEsacwZEQU0QcI7LaeNjSdKPivQWTp0qKmjWh/jh55GlfzaH7e8CR9zFfIKx6XHngfpxcvyp2Gz2zdv7s+vpFzpgM5QH8ttR4/kzR/ps049BkugxDbkh+e8S1etdpsfUdYDWxSEGZhUAmkaIrni7LnoQIdH6B8eIC94rZL/LyECFgfP6TMF5q+Y7v+A78zM/8DP7RP/pHn+uqfEHJPaMp5zeeAUPIGgTCcXA46jxe+eA1PHC2xv2PPYL+5BThZsCnLwi/+2u/iovNx1SrYgyaXoAc64OOAQ2mkMFwPiOQKGxZSLRmfYMzhSuKV7a9HKNLICKkMQopQxXErC7WOUmUEAmpBnBgMAG7IWGEec6jGPwrc1sUQAlrxaIA9V6POIkmoAkAjZFKJAQGp5E5qnO4KjxOQ5MFMRD7zsE5h6PVGqt+BfgM9hlnxyc4Ch1e+djDeN2rngA5r+xZIXzYi0ty13Uo3vJEoEAYU8Kt21tsdzs8/dRtjLuIYYiFzQkAI9cX0OQvrE2iTLPqzwRon09f4sy5bFSKYVc3PZaaojJ5M5wnnJ6eIHQddqOc8+lPfhwXF3eQnxLD9qpfowsdXOpA8GAWpcYRSUg37+GDl00aEzI7pExISSJ4pJgw7HZgTYMBcFFwz8/F8882aGWi7WmStV+mSrEdNlJF3Sq2zF3bdLUkhaImzMp03gwkdUwIKIo0KfM8BNms+a6XdD2dxypIOpoQJLKJ7zp45xCckC8ySyQN75yOJetYmiInir0Prmx+CKQhDVXpB8CuiXSTGBKNps0NqJsmjeLCziGTA/ss633+MCEA7EUpchKqkizdjqdmsyfh4evGDJC0PFIH61dmiS7inccjjz8AWmX89kc+iY9/7DNoN4yTKnhCWAPXrh7hTY8/jr7vEILH6jjg9eMTuHnzDn7j1z6GYWdRXiS/osuMk/URuj7gaN2hXwWAM2IExpwxMOPq+ghHR2ukeAvb7Yg7z9zE5vad0qfVC0SfWZIzSecRq8LdeKQ0c7Tmo7SW8OzvZKbeRaZz2jZ3lseyXQNO55OdXLaIjqbXKsvI6Wfy9rwgHK7TdPdR1eb5rqS51rx2mlQqDMjz+LJWEgHON2UbMFPvnDPD4kuBWerOwProCKcnx9hsB9y8rdFALEVUcw8HiWIDFiLZoqZ/4cj1fB2vSK+YbjKfgxBoCSW/yMtOvvrREV/+4Ij//LEVful3O1z23nnVtYg/8rod1oHRNXyQB44z3v6mDT55x+PffmiN28PzW39fLPLoacb/+WUb5G3GarFzf85kvY7443/8N/C6193AlSsDQmB8wzd8BP/r//rb+ImfeD3e//4vzuhZa17jtem1L4j0eJk8mG8AkHftm+KbLiV6OLgl+tUii7xAefws4Ztev8VRYPR+edcu8rmXYbvFsN1gs7nAZrNB5whHx0f4mj/yVrzida/CtYcfRHd8jK/+4/87Xn8RsTu/iXG3gYCSGiGWUQ3/DUxgGIDswVvDpmG6hvkZJqgROpJiCUm94dXgXAz+DTYD+UmwoJSRgHKvKTekhv8XxzMFBRsj551nbuH/8+9/Gtvz8wKglIiihr1NwJnqxFWN7BrJIgQEH6QdjuFzRuc8rl45wROveKTgxyBLTSLtefD6/XjFq18jeIfd1kkU7vONpBjeOY/djVtIMU/xkjKqDY7UEDKsrtY3LeZZbLVk/VdCmsCs3pZSG3Yd1X7t1j2cc4iK3Z/fuY1xHIph20grlH3BCTNnUOlDwVIrlkbIICAxEpI4XiVJUWMRZa2VwxDLQFeCxwyrmliWqfZtGVn9VIgxOtdoWkyN/qz3K/02JWMYDtdeSvq73ZtAcF6dA71X+wEhlDQp8o+8pVGhsh7K2JX5bWtQ26r2jTJ8csMpwmin2pjCMPJm3HU+AFByk6bO8DgMc5qxohjjdTzLveUConkKT5r8rdi8kFWe+fCH8ZH/+ot48I1vwn2ve32dyDN5+nd+Fx/6Tz+LJ97wOvzh//f/C+uTExxdOUFMCfelq9huBzz96ZvVeQ8yX4mBbiXRtAW7F0w754zMjATGKvTouoCcd4hjwrCRKNE12ouixeWZ1fQdUBedzpdD9d+DkMnA1KZ7JnN5LlMM+bLzrj3yEL76//ijIOfQr9d1vjLtz93G1pItElFTFavu9KpDaOtlGLL1RdNX8naYOZXWq9jsYo1NBGj6HbXPJ7i8Vjx0HfquQ4wJ22GQH5voS2132/PJUOVFFlmkyj/9p//0c12FL0i5ZzjRwhXllEWfcwGUSRTklBGHCBdGOA7ovG/YsSi60JS1Kf+R36mwou0hLIfl3BLJw8rSIoyEMH+kF4Y1pu+3zPVlCpZ8ena+6OKmXCh9ggB2kkMOJcSYpiAxRVwjKXgXJAScD8qg1nP0uFP2Zug8nCcE7+G8w3q1xqrrwT4ju4S+E/JGFyQlS0v0cBotJKtiTBREGc2S9mEYIoY4YrsbsNkO2G1HIXkkC5NWX1FgVtYtmhep9IdDjY6hjvYTo2Z5v5XNDZfz0LBKiYSYQURgl+GcsBpTzkhJIiSMMWIcY0lJ0fncJOGrymX9WlnUmQGQREyQEG8JKSbEmCaG3PoCbzYUdRIWaZVUoDK90SgbABVjeCHZoCrCKNO76eumb+0EI850mp7H9Fynoe2cbcwclOQj88eIHuvOo+88QvAIIcCHgNB1wtYnD4ZENCFySvQwIhRAGj6Msyrk3lXGNlBISkYEqYpzw5adhDtrWkrNpXUmTSfQnIFO9eKJgj4r/1B/5my5Q+uGK3SSisaijYieu6/AGZlr3I7glDE4wna3qzk9ZxVoU8605ciGNIOcQ+hCKdfOTTHp/NbNDeozzhREym2r2jvw7E9zROs494uYyzT1St0kctPfxu2g/Q6fED3qXr2uA0tTZc+6zmuKoF4ivmRXIyPdqzGdmjnRStWjp20ua/1gQQfv0MyLySDrHyUHskZVaVZ02ViW56eFtcwo/PG7D8nLXjz7zxtyxJrXWGN9z3NzkUVe7kIEHHeMowCsw90fdr0Hrq2zhsmuEhxwbc3YjBnuRVl6jOOOsQ7y9wtNOs+4ts6FiL3I50acY1y9KtE8TK5cGXB8PGK1+jyJnsUSSerFJEWsscaa1y9JZCqL0OHhseIVFhBzkUXuTQjASc+47yjhYnTYxstflr1nnPaM+44yrq1r9CxHy7t2kc+1mHOdREYASYLi1fExjs5OJWVIylgfH4PXDilulOhhV1sZraG7cbTiek75r23vD0xRbs6ZoDqNgdNw0N35OeIwiNMTkcJfLS4tbetWK/Qnx6Ugi3RR/tkNnBjcfQjld6cYs9PIuYXfYFgjoRI8LBqAIwQf4L04TjExeByBNMI7L3iyYrDUYj/MQOjQHx3DyBYMiYacOGP0HmOMiJsBKWV1hDyAxkwAwAZEbPDbtr/r6TP7wGygWhWYzCiqBnsLwiwRtzV6c8rF8Mp5Xq9aHdIfWA2+bMi3OXpqqnnDAKfTxtIuHOiDKbxbvtR5OkUXKnmF2uk2lQmbA3uf1S2vpOax9llUhfJX71OiQSvRI3jSqMQN2cP7gkMzNEWFYtWYRDWwRWM3pQaz24fdiuOjRZcoreaCr8+XKBserzj/ntDhnpvidIcw5HpMPrFG9gbYMHMlCzVebHuYo/Slg+97rE5OEdY9YkyIGp25Aur1ljyLTlN6wh40IL0vKqZNsi4LkaVcOoviXB54+pMtgzlW2hZSCmsA1Pkxbn/Qkw50/QRLbsSHDsfXrjYVqv1X5k4pViasdwTkBO9lXpp9SE6bLe5LRpgOfJoi6JMeacq/rKD5LKXSP9N71fdP7X/DkGdlGImvnavlPwseucgii7xwuWeiR9+vwMxI2wFEjHXw6L3Db33yJj7+qVvof/3TcERYP3gN/ngFnD8FTrExjgIS80Ignqz/iOS7A4M011hjwZSXnHrxOwv7RQ5MhBFBHpveSdoXTcYWs3xOmYvBmUEYx4yYE7Ia8Lwj+PKi6UDkVCmGskAlOgKIRJlCY3hXJbvrHLx3ODmWsF1nZ6fouoA+BGVsBg1vJpFIfJCoC6bAkBJJhhyxy5LaIW4H9Ezwvq9pM6TlqkvLD4kTUoq42J5jNwz41GduYLcbcef2BiklKCkZJYdg2Wy0Sg1Jv5V+ELMlg7SfTEkTY3HMqWw2pGwjb0hkj0JQ8ATfBVy7fg1eU8qklPH00zew2w3YbjeIccRuu0VKCX23QvAyBmNqcvro30iihCNmEBRsNeVW2yTvXEZqsdhW+bT/tMo3A8ZsqLq35TrR6CxFH3FNpA1XVIaq4JCm7CEUdr4qUVa3nGKZy10IeOC+q+j7Duv1Gs75krfPArAY49UiQBSFXNOwkNM5CQcir81jgERpL00myZfIADJcZaOTGawJyjYozWd2copuAkEEeFHAkAFClrXMNWha0eFtXMjL/MoaDcFSvZhibYq8s/pkmIrEdUnDedYlIzkxU5b+HHY7xBhx+3yD7XbArVu3cX6xxbDLoBCAlMB5P5kGM4DR4TOfuomf+blfLmOcOWOIRhjKzVwRdj/njM1uhzEnnMQjuOCR0giAcHp2gvXxGreeuYXbN25hHCVkkXgn1Hu3GVsll2yjOKOd+tNoKHv1L3I3hVCO2bNzsvEs41THy3t9HkCipnjn0a/EIG8hByW9D0BB5t+q62RO9h2c97jvyjG64LG9GDAOCU8/cxsp5ZmCvi8lmIg+f8omg6z9h7aD084paVy59i/sL1spSnJr535znq2NnBmbzQ67MQE5w0PAhBwZPnh0XZD3lwM4M2KSvxlG+FjkMrmWr+EV+RUvSZj45ypLmPhFFvnikK98eMRXPTriZDE+LfJFLATCo+lR3Jfve9HKdHDLu3CRRT4P5asfHfGmByL+n9/u8Ssfv0v0rKsRb3vNDscd7xErX2xZ3rWLPBfx3osjnGIPwYlB7+adHT751Dn8UxcgAOFkDdcFYNgIIQQoRvyCxaHaNgv+BknRXLAtwxBQsYMSGVbxuQSJslFSbuu+XXx3NLU3Z/zmL/03fOLXf1PTfU+dyJx9AOHxL3sjvuStf0CwZDLDrRrzLOoBgLOHHsRX/x9/DMxZIhU7Qtf18M5htepramDDW0iRWcUsnIE2iusSERJnRM74rV/+AD78878oh5wvzmMmLWrJLGmsxzgipYTz8y1iShiGUR0E0fQnKg5YABdzXeLSXpTyq8OgXEZqVM8wYoAc19+LAyNrfwlutT46EmMvBJ+52Gwl/U+MyCkhpgjODO99IcmUCNbNoykbOQEMitxWE4ixmSUVd7RzGhP39EOJujE5vQJtNk7N7zKHp1h822s1hcqhZ7z2n84F5zxOjlbw3iGErpAyqEUPy23UIdMwbMO2jaQBo45UvJubIopBniGp5q2Dqakr1X4tqLzNH24OlO+YpsWYvUoIpP3RgMHWb7mcNHsQNDakOuTFgZEh0cMtOHBKETln7IaIMUbc9yWvw1c8/BDGTIhwQJPCp5X7XvEYvvp//+NYHa3xsd/9FEqqJYgza048iaQuJBc5I8aIzA5d7kCZ1KZB6NcdQh+w2+xwsd1JNJAydrWsmXmkPBsnx7npFpqdvweIN+NC7aCjfLfoOO1kpb3vNhdsXstzz3vDn6lgzQQAXuaed2p38x7kCEd9jzwOOD09wvl6hc1mVyKS303boEmF9oX3Jsuhc2ozm0efPp/smL1LqKzXGlGFmjEDxpjUJskoTp5ZHEO9knrMUVj4ZdPn5iKLLLLIC5F7RnUmaT6ad8FulzBwxnYX4RjoTjv0fQZxLEpisdVNnq36GC2KEDUvr6okWbQPIyCg+WuKw0Sxgr3A2Ux6ajSU8GympJvZUSIrqJHcO/jQwTnoP2F2EjllzQJelSRjwobg4IPD6fExur7DqeZpWwVfjPmuRPiAlu9FSVElnQmgFIAcMYwZMe/E4Ej6UrAuUwN50g1IyqIwbLZbbHcDzs83GIaI3W5AzgxHfv+FXqS+7FjLLi8uGx/Tr6wWGhXCQZTzokiowlnmB9nY6UtL34E5c6nfsNshqYIOEBz5Yow2Ja190dXPTXgsAohq/9TpNVNUTHmdKS5VUzEFpVHSGys4wZRhV9j0Er0AWneNauCaTRlJfzCV2QpwRkpyQ5kbHkfrHqu+F6KH94V4xKVv5eKcZEPmmk1eVdRLCyYjPE05IylSUM7lhpxubOzpZJl8a/bNsp5admqdS7UOU2VqymblWnI7rmDkrCETk8z1nETJ1u5Ezkb0ECV62O0Qx4jbdy6w2e5wfrHBdjMgxdxspma1afYNw27EjeE2LG0RoBtP5oPKvRCJMogSxjHBeckLSiBYFJuUMsZhFGJIo1peprlZpKNDqmfbs/tHWp2cDl3UKOnUKOKoynbz2Xmqa1Av9cHjKEi0A6+eA06VcQoSRnTVCcHD9R289zg7O0HnHShfwGFQYtt8AEoTyvo6sILLc6RcQNNrD3YYpv3Nk/8c8kzRxupzp80Jm5mRYwKBxXdWx1QiflgIWJRnHEpbvvCFmBAQ9p4rADBinHontMLiuXs3b+M11jjm44NlL7LIIl84sg6MqyvGNgK7BNjTtXOMo+7ZPX69A66sMhIDFyMhP2fyF2MdgJUXT+aHTvKzX/LFJJmwvXWC86fPsDq9QOjj57pGi8zE8YtLonBwWPMaxzh+9pMXWWSRL1ghAk57xkkn77erq2b/PJPrR4wHT/ajZ5m88HdtlZOeX37v2kVekBCV/5SdX0ziXONiFoy0dyDPILXk7uMwB3bwDSyQ4ojdxaY5z6I0yxnOOfTHxyDvodCL7OGZMVxcSDpqrSPnjJwi7jx9A7c/8zRcv4LrQsHnXLHzEQhOjJHOq0OYYaOWzrvidYQOR8dHKNGePdB3YrBfrYTw4Uu0aFexGnBNxaIYLPRjyhmRGZ86PZ04tkzjMIiBPKOSOHLOiDEixoRhHJFS1qjIFTeaPm54NgSKsxg8M82dsXcdg5UPoAWX0+eG5JrOxG6fmUvU5hSjRLcunvhuir3wfrXLx0Nzag8kxLQdk3bZ8X2ErmDI9q3F6Ax3A4pToOGvtjaqrcXp/JxGk5W0d1zw6BA8gpfoztSkB7ImK+SrmKZErGjxNTsOrpE7ytA0dpXmNBhOVozac3D14LfaHa0v70To8kGrPl9cz52cotF9LIW4viYtWkuBDrlGHWedTzln7HYjYoxwfY/11WvAZoe0HTDuBoybTblN6Dp0R2uJ3nN0BAKw2w6TuQAcmmO1HZLOSSLHpEySvlw7xp5FKSYMW0nZ0q1W6FY96oJvOlj/7tnZmrVD00Ga16hgwwfPmeGZpPh/sRvovQhQ2whNxtA5EuKe2UmKzQ2SJp6A4HTuenF8Xq06ZCdpmLxGJCptOtCt0xV4qK3thfem8+xhyM2R9g51jVm7eXKL6tjKcOUZiJJRwHq91erq836RRRZZ5IXJvadugaXK0HxiLKxFGhIoZyCJAnC86nH1eI3OB8l7BwBEyFTJFeWhGAJU80ECYBhxm/vKXlFSh1AMtCDAsbCIXTG6a8QPdnqdl1xvSuV0HaPvSrHwypq29Bdd59H3Aauuw/F6ha4LODpaw/lQ2dZBle8gRqwMMfSvVr28vEyZ5wwQw5PT39UY7IBMym6Hl7YRA36FAI+8SbiINzGmHXbxDphEKc85I40Rwzjg1sUdjCPj4kKiDuwuBuSUEUdJY5GSdJDX6CNMllpF6p7Z2MvyYpK0HhmBHMgb6cIL09YBKUcM4wgjenjvEEg6kp0wic9OT8XIzSzM8ItzjGPGxz/5GSGnDANylvoyMzx5+ODBXurmnStBHe7+Qq5zqv1u/zUyzuSKRgkBYUJKkbko88XNvturt7CkS05MhxAc+q7Dql8hBCFthODR9z0qKQllo+KEHQPWcCPkCA6EXqNzwPtSUYIp2M0mwRMcfCVMk51eOdhNjeWYs/G1dVTnxYRpbZE8TDFmU4yVYW8KXV284OxluRHkwdCGrBAmFRgJQCwbDNWuYSPMGrLDzO85Z2x3I8ZxxI2nb2IYRty+sykb0JwzckzInEs6opyTblRHpCgb1hQzxhgBFgO9hFyw7S6XeqQYIVxqizZSq39oytm0TENGHhlPffIGnHfoOiFvjcOAZN4QuSr6fLDQOmZ7v7abpiZERZ0XugksdaskpcJoLnoxqWKtP5d8nBoJRiMKeS/PtBLqM8lz9crZMV796kfQdR36fiUgSSfphmCkN8v96YRY1mkI1s/Qp3F++xzPPH2nzMHKppr3w2QLN+n22i/aCAbaLLFzKXNrUmCefmXbU9YIMtT2W9lw11okho6HR0rAZjMUggxD329EWPXNxuQLWHr0eHV8NVZYTX6PiPio/yjO6fzSax/Jj+D+fP+lxzv+/Ejbssgii7ww+YqHR7z2esT7P97jF3+3ruvX3Rfx1leKd7G/y+Pw+jrjj79hi6c2Dj/1G2vc3D23ZycB+L2PDvjyh0acrQ6Da1/MEnc9/vv/9b/h1//T78NXvv0/4pE3feRzXaVFZnLKp3hleiXci5iyRFKgLLLIIi8XsXftZXIUXtp37SKLPH9R5y0jUUAM95wYHLmk4u5CwKoLmj6i7skLtlWLq1gdVUPZUx//ND74n/4z0ri/ThjAybWr+NI/9L/h6OoVqYUatOMw4Nd+5v/BzY9/UnBjAMiCXW1u3wE7j1f/vq/Eo296Q7k/EZWoG845rK8c4+RkheA9uk5wVIn86cRgCULQBVoiVAOKoyhuUJosumxx7GqMnaz4hBPTobTDBziI052kYImIeQBBog8LXpaRUsJuHJAzMAySyjyNqTpWASUSgUUjKcZNGzuNvCvOY5Ya2CKOAARNea6Ga0mvIjhbm9ZbygKcC1j1vbSNJYrKOA5IiXH7zoVgiBrxOxfDvYMnB6izX8FvC4Z8l2cbYe94C9nQHEMu421/3eyYjtGkMEVk2b5SGV+nuJF3QtJwrjqPem+xz9HMApjpRQwg0mAQIFGgBdiGTZ6KjreNAoh86ZrSpobsJzWm5nytQ0kb0hr4qbILLJV3Y62uyalnOCdJ3SfEmRI6pjnTMFudW2069npKvaHhfjEl5JSx2WwVj4067zNK6iiwdqOVK1gyWzqgJDYRgPHx//nr+Ogv/zfFxYFH3vg6vP7rvgbEpGVRqUMT56ROwcoEqPXOYj+7uLOdrP2kczylhJyBj77/v+Pj/98P4dW//814xf/yZbWMg8DxwY+owD03c7WZ7w3OeWBZTHBR+VhtITYPbN07JxHuyTkQS8T41arHtetX4JxD8EHba1HT1SboWtuLzOlhs8Hp0RGO+w7bzQBwrB16EEM+1CHVeljbbBjy3bGCKVGHgBnmzOacyZVMN8GQ236zeWE4OMRswmOq+DxkhBjQCD0vXlrORRZZ5OUr9070yFxedARS2656NmdT0iWlSeeF3GCRNMScRiVgACv1t3jc0zRUUQ3bP6sD9MUMwFyojaxQXlP6IJfnKUEog000Dn0ZOZJIHMFL1I4uBHSdw3oV0HcdTtZH6LqA4+M1vA/o+jW8c1h3Gk5PH8JJ291prsVclIgEIMORsbGVukjcqAQEhigXcF4YukoWATJSjkL0IKjCssN23OHO5gLjmHF+npFixrCJmkqj9pO+Q6ue0Shte2OrjMOsXupMXPq5KkLKrmkICJX8g8Iyl2gL8i+mJJENUkLaDcom9sU4KufDRq7Ufv76rd8bBbSMb21XjXBB5TpqzpUNSGWTusoAEeVjMlZOPPbBRamBEmeE2OEk5cqqV9KHzKFV35WxtWkKGNEDQCF6KPkoifKQWwP4hFXRKBDW9gOkgXZoJ1c064hV+7SoPO0Bhir8RQGaK1PtZqBuJqynbSwZlkuQixLOSgpDZuSUwOCSPonZwuiJgr3ZDkrwOMewG3Dz9gXGMUmUmiQpVcpmjxnM9l3yvmbdrEJHoW5Om86habvLoQN6X+2r5jxFJIZhFOJUBpxLQvSITSSjaUGTG9Tx3B+5+rPMo5bTRKZUl86XDxad0+Y0tRfZeBHQ9R1CJ1GLvKdC/PDewXca5hN1Q9p1AdeunaHvO/SrdSV6EGn6k2YdQZ/pOYNTwqrvMIYgx/fWubW33XXWr9PeqL1W+oFLoqBy5oS8dEkJpYB2npeztRw6sG3QU8uzWzeH4tXgyvOQ9Bnx+UD0cOzuGlXj2aTnHid8gjXWk99HjFhhhYGHS6894iOc8unzvvciiyzy+S9EwNmKcbZifPRG1jDu8pS8vs549EqGe5ZHYeeBh0/FC/lslRGfo5MwEfDAccZjV16e3sXMDrc/dT8ublzBeLF+9gsWed4S4J8XSXHFK5zwyQt6H38hS9z12N46xbhdyCmLLPJ8pH3XPl+xd60jILjnX87LWQIHdNwhIl4e1XCRPeEZ3lIxIAFMmFGwDafEi+35hV1dMDXfSXoDkGv26YoHMCHFhO2dC8RxPFgP33WCFxULutYnM3YXG2zunKNgyEZgcB7r01NceeABXH/8kbLHF5IHlTD8zmuUZ+c1fbdH1xvRQ3CT4M24WYkeAEpKb3O0KvcuOKdhioZfWcQL7UMFfUPXY316gtB1Er2AFS5XkkdM4riXMmMcBUtLYz5sP0WDIR/qzILbcMGKhbnRGuC5MYZWzL/gPOVnw6qkjMxmdM9KQkmlJhUDU/xrUqlnM+Hu13+Cbs4bWqpKk88N7FXa5fRvsW0U43rFTQUvl7RF3rtK9FDHU0lz0aKrWg2rlzrVlXlRHMoI046YYotU7CJ88LQWMrx0vA0/neOiNogFWm0N601pTaF2yIqy9PDQddxG9xCbiuLJ2ewTVOcVV1tFjAkpZQzDIM+C3YichQDCOdfr1ehU5mf5B7RpOuIwYHv7vMyquDXcS+s5wRD3+4uZMW52JQ1VaX8hdWmUZCLkJI6LgJCjzp96Gjc/+SnsynNw1n/lEzd/Jzdpur+dj419wMqgOrSzg7CDUldJC08wbpE+Cy3S+WyQnXdYr1bwoT4DvXfNemjrQgrPMxA7rE+OcXR6Cn++PdDuSTdPm1p+rVe1cThoOr0wubJgw/M7tGdKX+6fxbP+3i+i1KM8ExlQMp6dt0T0WGSRRV4suWeix26nLzd9Fo1RmLQ+SzgideIHZSAkILPHiA76+kVVApSz1sRkswf0XPEuD9HCOG0NpbUMM6yWVISWVsILqBY6D+8dzk7XOFr3uHJyguOjY6xWHfpVp+ZJB++UbV0USAZyhgsduvURvCN0+oKze/VkUUTUM9yTKilSN6dMxUJi0a5IKWLMEZvhFrbjObpwJP+6iAcfPMPIGRe7EV3osF6tcHs8xyefuYXdbsSd8xE5MtIgBVrEMPOLt01I6XmtQ2YzgFudGYAQMlLOcJzgYn2RS4qYDO8CfNcjdB1W6yMwSzjDcYzYXki6mGFMpR9ijLh95wZyTlYjiUZByva0sF2QDQEDqnztv8TNsGoKSpkBqiwbU94ssdUAXSNduDKn9BdVRogknJsPomgf9QHBO6zWa4QQEFynueMY5IzoJKETnfdwJMQmkJFHCDmhzHlypGx8lPSCEk1ENwQAWBkg05e6LIqyJkzx0Q5gQCNmNG0moE05AZZ7ShoS3VBnC0mpES6UEGFE1RKBwuoaVPmzMG2QuV1JQ3K+IyEkJCTkBDBSJXkgY4wJm92I3XaL2zdvYYwJF9tBWNOpEjUsLGPOGdvNTshCY5SNaIwy73SDXlnZ9W/OE81tKkSyIaIm8sk97AYZEx+S+rtFLSFgGCSyA6dc+vpQRVqPjJYIUB43RjCa/G7zS06yfKv23eZyCEZAs4hDDo6AYSdRdMgD8IRXPfE4HnvkIXgHjfgj61HWvMPTT9/Cb3/skwCS5o3tcOXKmXqlyHwOQeqYYZGTUOcHJNALAwihQ9f34rlS5svhTp+q5Ad+sQFz1C6K/fL0a8nHuXdLmtXFdjW2iZRPWZ+hJeRhGTpSIh5N2i7LU7yTdvkwwPRZFQbuz/fj4fzw8y7CwaFHv/e7h8cT6YkSCeeQrHkxOC6yyMtJvuzBEY+f1WfCSZcPvDkvl7NVxjd/yRYxP3eE4/r65UnyWOSzKEx4JD2KN8Y3PudLA4cXNZrHF5p87P1vwjMfewSbm6fNfn6RRRZZ5AtHPDyeyE9gyAM+5j+G23T7c12lLxhJKSHHpN5hjJwl/XSLw7DimZQYH/mlX8UHP/BBzA1qT3zFl+GJN/8ecfaYQMOyHz979GF85Z/45plHdhUfPFanJ81N9fe+xxu+/i2Iww6YoDCQtLZEuP7wAzg9O0bf9eg7SVXrgxk3SVO5VLxAGyUONer0YhGHDWKepsdgtalWDNnOq+WR2gkzcgbGtEPMA7zr4FzAY1/6Wlx/9Dq6k2OMWVLOhuAx5Iw7mx1iShgGcTDkJHhKa5c03NSqxVanMhIVEzPnscz2L4FyUuc4VzBTSTMiuKkPneCPnJFyQhwjUsoaiZoVds/YDVtxDpwguVSijEi/UEN8OWR6NZl3IgoOVzEd1LYVIzwK5jm91sgcgt0aDtcp7hZCVxxKBWMz/LY6n1maFVdwQSmTczMfWqzQsC0Ft8oYGDY8ES7zpy6DqbHaphsr/syKiU9K4dnfnFEnBjcHSk2mtzLwvUT8sLHEpM5tW8xhUHBpmT85M8Yk6Xp2W8GGx5gU484wopidy8yIY6xOgDqnKqFDyy44tcy7kvKoRBthPPrG1+Paow9rExmrk+OKad4Dhry5dRsffN9/xubW/rtC+sHmGlXSG6QuFzdu7p9fvrQYMjWd2sxXRp3benwSNchwZF1XAkPL/LfvKSm2rqaDa2dnuHLlFK4sE8OoZR1tNjvcunFH14ZErVmtVnDeFUzbKY7L1O6JGnycgdD1eNNb34LHv/xL8Z//zU/hzoc+DJtje8uxGYpDx4v9iM3RdfJAnXwydNcKmWPIBGqC0czvJnbJQrwrS7Ne0xJcKobcrAElK8Xn6vGyyBetPH3rd3G+efolvcfJ0X247+yxl/Qei3xu5J6JHjnl+vQjYdum5sXY2qJN6WVysHQRInMjnfzGmD947Qw68CKtysjEWGovJqovKose0fcBITgcH61xerzC1SunuHJ6gn7VY7XuYGEzHEnUj4yMyBIhII0R5CXNiCPXpIlhZZ47EBgpaV+Ykn933UsUEGbENGKMOyEskEfvCX3Xg8cReZB8OA4OnIHtMAqpYpfBGaA07TZTGmii4HFjmOSmDvU1ZZUqYRQJmvNRlCSQQJTkJPpJzgkpRU0Tk5CQG5JAFhLLsBOSiI6BhCZDw1RsNQ2u9Z1o1NwcV+Wk8QqoY25tlsY5X6MSECQMmM1bqFIv71kpKQQP7xz6PqD3Dut1h67r0PlVIXqALO+fsPuJPGqlTY2otbZj5SU/mb9an5mOIC3g6e+2xrTt5bqGIa8xBfbvD6hSWyMQlDlqEQn0AuO7clMA6waH2VrQbv7qfzijpAyKMSFzEk8CLXE3Rmx3IzabHW7fucAwRty52CEnScViET9KWD1VdHLmGknIInbMvB3KvGvXQWGGo8wxI3lY51KjiB1asHM1cF9xtOYb0xx1XIzN3g5sUeNQFO1aX/vXED107tozrUSd8Rp1xhuL2iv5QshKQvRw6DrzNhkxDgkUCBQIZ2enuP+B6wgEeMe6CfUSBtI5DDsLjycVdM6hC10JI0fQnLQgjarRPNtri/RaakgebceJMiwfa7+XKV+8AZpFYGe047oH5OzvusqawnxMD+zQ2n0rA3VR8Wws64fiJdG0LR8o+rMmLAQNAuGIj3CFrzQz78URB4cTPnn2ExdZZJGXjVxdM66uLyd/PZt0Hi/bqByLfO6EQPDs4Vl0HM/h4DuTAKyxxhmffZZr+IUvmxtn2NxY+m2RRT4fhAhYBWDlGUOa4hd3F0ZwKP9ebkIgHPMxVlihw5J+8rmIYTmy+26jONf9eTsLz5++gad/5+Nlr+5DgAsBu4st5phaK/3REfrHj+5Wk4O/Ou9w9tADxYkGQDGqey9pNdarDn0XsF71WPW9RGEImmrDbKHqZGdYFacMOMOOG/wTXKMMo6ZLKfCLAXLt96a1WY3imVNxqiMQjq+e4sq1K4g5YWcRhCEOXzFJtIMUFWfMDeDROMfNuAW1zmYIp3peIRqwfi6Qf9aoLRnOKSmHBBMSZ0GU6AnMFduxSL85RZ0pruBjgtk2joLm5Vjm0H50jymGzJPht6EuxlfFoMlZr8nvrtzPwKoWU7Qo4RqVgyBRXbyXNOiaXmZiim6j0TSw7iEx7JVnv7b1bSwmzacD3dB+bw5IU2akKxSoWL6Xv1ywzuK52tSwxZCFJFPxvsOvmWbcsxE1DD+W4zFlxJgluvMwSsQOJXKwTDLkZv6A26jPUkaNHFSJHbVdhJJe3Nqtdz+6egVHZ2dto2rN74Ihm+SUcP7MDZw//QziMM7A6nqtItMTbN8Hj269gg+WDrqctdef1MxRGxGbsvWZoyQLqjg0KeZsti2LYF7saaOQsCRdN7Bar3B8vIYG86j2DLXDpNiEl4emadLnn2kaVCuMmQtvaRg5eR53x8fojtfldzRjZ/eYr/v2aTB7Auxd2z5saxnzNcWTK+af2p8K3szTeVQ4VHsY8oEyGjvCIi9vefrW7+Jv/JNvQEy7l/Q+wa/wA+/4D/dE9njHO96BH/uxH0PfV0fQ//Af/gO+7uu+7qWsYhEiwvvf/368+c1v/qzc7wtd7pnoAaBRKkSXS0BjnVMv6K6HP1qBzDBYGHs1uoRrlBYheagC1jwJCVWHK4ZuZR5afi9TmkMI8M7h7GyNvpdcfyF4HK3X6EKHvu8QQkAXPLz36EJACAGgGs4rJ8aqC1iFHgyPACcP3K4XJd1byN2srxV5kMecJcVHjgAzBjVGI4oWO+rZx32H4CWUHzmHvpP0N8Gf4fRoDUvb0vmAzgf4kBB8BBOJoT57ibaRHAIIGZLSRVIHeFhuOgZAXl6llKUvhWxh6VVkw0TOgZz87aNsFFKWyB42nsQR4IhxlzBs7mC32WJ3sZH8iTEixYTdsAMRoVNFhCDpazwFJYcoiz10ZS6wzSAGMluIRDTvzeZFPlFSRNGXtki+NxCK9z5IlO3gRamQeUE4Wgd479B1KzFcq6JjASC8bsA6L2xs7zuQ8/DU+uBpnxpppq0fqLStRPCwpaLnFdY2puqBqRLleErN5leIN2BI5BNTxK17CDoTgJTRpJCT9UQQTYPJVcXc7oG6ZzN+eGmlri9j9BblTBclpwxwxpgkRc/5+Qab7RYXFzucX+yQUkRMEZYGx0ggY4zYbjZCCDElfabQZJsHRHAORXnXQS9hCy1sBDmn5Bsqc0gILFTVvOa5BVOkTRkump9rhtRUT3sANQ+5VriZBKXrK8GoRHTRf64hYRnLug3LWVj+VCNzdEEABiGreRwfS0qpK1dOEULAkUbMcN7rvW2sZAwtfGHoArz3ODk+xiqEEiqSqSVr6AaUakhS5wjQFC/GsE8NWU82BrrxZk39hIyMLF4sGvlmf/+jIAiajWy7/m3fdIjs0Sjl7YhMvtvmrd18HhrDS4T2K6yXc4mmY1sEC8FqF7pLL/7syAP5ATyQH8CKlzDpiyyyyCKLLHKZdOjwqvQqPBgfBACs0xbH/EEAT31uK7bIIoss8hLI2Srjm16/xTMbh/d9ZIVntve2ZyEAX/3oiDfeP+L+44WUucjzEdKdOWEygxiCyzgvqbF1X20YwONf/iY8+mVvxPH1s4oLkGHIVnSDEzR2V27wCrArxk77zUgYq1Vo0mk4dCHAOa9ED1ewQknTIvXLzABLSgg5z0PpCXJvZ9hMvaeBdayGQeEBSMSBBMX5smCkSdvUea+pva0OBHbA2q2QQyj4q3NOsMsc4CirMVpwLMoA5YrBW+oXkKuki9ZsqqCMcw5M5hgkGKG0RyMZm3GeFf822A4STSElRoqS2jiNY3Xuylywwoo3knreO7UBuGIsLsZh1rFuHP/sA9s8aO3ppd+NLALFuZxBu3q4iW5gBmqqEXO9pthwZAih1Zh0HqmDljpPuWJqLjUxIHXyk9XHypofm32cQNC1jXqGAduWmksDpdj3if24IaDInLMbSfvs415a5GImaI3VZfSatTutdylPyRlJ8d9hHBGjRAYfxygRnnMupCtZYlwiwDDXFN3zCMotLEuG5HLTIgMKyVpAZc5X4gbrFKJpxQG06Vranw3JrD/J3Dw6u4Iv/8NP4vzGTfz6z/6XaZQO61Nqxt1sCiC86qu+Ao+84XU4ue+aRsSgaldwba9LP1H5S2oHEudlcxK0KM3OO6xWgh13OqeLrc7GTOdTUhuZc05tV115DjqyqErN80Lnt9SVyhhKJA3B33MzBnK5K2uWuEGHyRxz65O8zic7qyG2lMFnnbeTo22n629tCvCZWAr62c9zytW+zO/XItNWx4mFYQI4E2FiK1jk5S3nm6dfcpIHAMS0w/nm6XuO6vGud70Lf/fv/t2XtlIvkYzjiK57+RC1nwPRY/q6nr5a63uTvAP5UJRRu7QcNz2H6wF7UVT2G4FYo/Q3CropXyGEwi4kAvoQELzHyfEa63VQgkfA6ckJ+q5D3/dC7EBl6AJAygmZLUpAAsOXaA/yIhUPe3sbiXG8YX1CFXWWFDbQ1BIpZyBHIGeMqnOl4BF8BuALg5iI4KkHsxIgiCVNSujQwYGzQwIwMsORg6cATxDihtPNBVcDaWG06n+JlSnOasy3fGrOUjUEkPOiSGcHTk7ST2Rj0zowE3JOiOMoaTZy0kgkEnYvxQhyBE9clAVmhoPXMa9KhEVaaL34i5Hf/hTjrhnoucyNYgwnrrkMi95MAESRCcHpJs0jBInQEbzHarWGcw695sg0UruzjQRMd9I+aac/Q43zrVG3LovysqbZoQnJoFkse2IbGLJJBbYFIRNP1ke7sdF1SMZanixI0ZjaGTFvz6H7F0WRpvufehHJukkJY0yIOWOz3eD8/AK372xx53yLGCPGOMLCNZoI2SOpEj+v8Pwuh6tYSD+qUJZQbI1q3bJ46wfrFq4KMeYnVMbxob5pCilXTo7a2FNlRBuAAJK5WRQ462MLQwldlxpZwynBQ8hphPU6oAsBV66coO87XLt+DX3X4Xi1QnBO01TZVkY9ZpgQ44CUIvquK89AwMlzukTbsDlnz+hKVmnbU1Vo6TPjPDln2xJhcmfIsnXelQgktSvbwWh+Lvtynh5mTMdqNp6TjtfnSqvrz24zuTfbpsnKLTPnQNHN15aYZOuvNo/2lvtnRbhuDo/5GNf42uegEossssgiiyzyhSMODlf4Snln9vkCgZ+bD8QiiyyyyBeK9B545dWEs1XGSd/hzkCI+fDuV4TFU90BD50kvO6+5x+5a5GXq9Aln2fiCCi4SU0lffrg/Xjwta8qOPIkuGeDuxXjMymuQAVGVJwFNdKoYkpe02z0nUR/7kKnDjY9vBMHQddgNVb9XNJGmOtHvY+BFTWiskjBtBugS8geivuBC3nEIoQyrI4zrIEBOI8WrRQyiIdDhldHugTDZz2IkkYdEbdFmLMdzOmqSYfStqTmHoClabAotI6yYsUEUmyPDdxXjDynXCP0agSGEq2XrF8r8kcFa22j3M4Ms9VoUHq3IpcG8HI5l5q/1oYynGqIJmd9qIQeZylZJKI1QUg2hMqhMAN8HelKSpnUy/C2uZQp1UxW++8hzOsgfkvTg1zXxRQ749l1M6CM6xcu0Tj4QF9fJs362zum84slcrOl7I4xYhhG7DRquWDECUbysboL2YMbHHyCzN1b1czGYHMdleRBzJXHQY2jYNuCvTGs59Rng80KIPQd7nvicazPTvFbJ8fYnV8gx1hwxDq8tS0+CNnt7OEH8NDrXg3rUGrmrrVnGtneVWKFETyK3UyIav1KUk4dHa3hnUcXvDokzuOC6zMiC9HDK/mtuXHBsUtUflsD9rcuvWYMbBDqcpDjluKozlVrw/T6WTVnYzCX2qvW37TX3+3J9zyvJhiyndZiyNP1WO+OMvcqmr4vnwsYeZFFPhvyjne8A13X4fbt2/h3/+7f4bHHHsMP/dAP4cknnwQA/MiP/Aje+9734qMf/SiuX7+O7/iO78Df+Bt/A0SEr/marwEAvOUtb4FzDt///d+Pt7zlLXj729+OGzdulHu8/e1vx5vf/Gb84A/+IN73vvfh7W9/O97znvfgPe95Dx5++GH84i/+In76p38a3//9348PfehDePzxx/Ge97wHf+JP/InPQY+8tHLvaJY+kS0Xnb3MmAniwS2PrI6AtSN0jpTUaY/URqGCPeu5ED+agE7F0O+UQezVYLhed+j7gPuuX5eXkze2rRBLvCc4T7hydIQuSPQMYSF6AE5zihnZwFQ0YLUK6PsVPHk4BOScMaYI8oDvA3KKGHYXyJmRRrlGcjE6HK16EAERAJO8oD15eHQgAo6zRnowg6djMGWkDFWMhViB0INcD+cd2Hm4LqMPUUgf/RqnV67g6OQEm92IG7cvsNvucPOZpzGOEecXO81Dpy+YpK+ULK8dF6XdY1IlYRhlA+U2ICJEy8HWhktjQs4RnBIyR2REEBNizGVj5J1D51flXmCJ0EEghK4SZERDU2XfXqQaMtCM9GQkFD3fweaGKdweznmEAHSBELoO/UoIPOu+V1KBbggsNQuqsdxyxRFp7AYCgt67buBQ62Tv9+YdX/gpzvYEZfKCcoZ4KLja5BLaziJ6kPRTq9qRDVku60xITNInpuRWBU82SLLBImH9aw5C1U1LH7KlEWzaYYQZUDXIF4VCNRZXLmhyoOoq5pzxsd/9NJ6+cavk7hvHEWOMGMeEGCVtS85KnuJkl0InAQgSChOAROTIouiDWcaEGTEZiQO6GZS/tkFlJx4IzsnEy9mhpHRR4gujHYP9nVLV1w/tourcrYq0svbb+QF55sh6ki40bxDvHZwneP3X9z36boWukM88Qi/RiIL3Otd1juo4Fea0k3VgKVq6leQADfC1fkRlXhhRn/oVAlY1skidBNo/KHNUQmRWrxVru5FTspd5F3wvpCiX4JzDer2Gc74wwyXqS0IXgXPv0XXBpvakh+dSFOTZcBxiXB8si6im0bGT5pfS5fe/Fzk4k5pqy+b1+Zb+wuTB/CDuy/fhiO8WtnaRRRZZZJFFFllkkUUWebnKccf4Q6/Z4cbW4ed+q8dTG3/wPALwex8b8NrrCQ+fLCSPRZ6HTKx6FVMx1xRDnTwEm1MYDE98xZfhode/FqcP3F8dULhiyLXoKY4nP7FgKc7DkaZp9g5HR0eaTkAjMCh4Y+kKWq91c8KR8irxoQ2N4IPiPSCQRljO6mFnqUqSGndzhfogkYR9wePMmOsBjdIKdFxxcWmigHYl+HJxnvOCH0mDBRN3WSO+BsGcuh4xJWx3I2JM2G4vkFPGMKbGgaUaTS06LmUN9WCwmKZyL1GcrQ48RWs4KxEGWf8BOVnacynMUSi3bfkIzjV4ValWU35JdUP1TzO32jQ5BUtWnM47grOU7Ia/tVhfsVVQwbtBNVqrTWXXnFNHtYEVW/JE+71Axy3WzIobU7m+OkJWhzZWLNVuaRhtG6ljiqfXyth/uSwgKphpqeZ0AQFKhZjAc805xPPzUY3Zk8Js3WTcvH2BzXZX5k2OCYklsnpWR1PBJvPUcUvXvK0dnUAA23UodqecK2lAg7/I5Rmln6X+MvGYheBU6s5onC0rJlx5OK1B/24YsjyVjs6u4Mu+4Ulsbt7Eb/78L+H8mWfKmbYWhG/h8Nrf92Y88JpX4erDD+LoeFWeS957eB/U0VVtYIoNm8MqNetB+slSHxlOXcsSB9cmvTbpE1SjgBMD5AnslR7Rjqd+tvkolzttrTWm4shEhAxN5UJe65ZRnLfJnseKIWeGywDF2BBM7lHmw1GeG9SMTll4aAZqupAOIcXPG0O2tXSgetOqlhRGiyzy+So//MM/jB/+4R/Go48+ij//5/88vvd7v7es0/e+9734uZ/7Ofzbf/tvL73+X/yLf4Gf+ImfwI/+6I/iPe95D97xjnfgIx/5CADg/vvvx7/+1/8aX/IlX4IPfOAD+MZv/Ea86U1vwrd/+7fjF37hF0BE+Pmf//mSuuV973vfs9b39u3b+MAHPoD/+T//JwDgV3/1V/Gn/tSfwr/6V/8KTz75JH7+538ef/SP/lH8wi/8At74xje+oL75fJPnQPRo3wT1MSXvQHmAO4ghtlMlvaRTQFVcShlNVIeadaExpILgHGuoKUtb0GO96nHf9VN0nURpkLQgErYuZklJcaxED7NXs9a52OWNRaxKhncSsg/ZAUlZjKz+/c4hZyDmESky4ighvciReNKvOgCkRBclDTggWM4+FgUyGhmGROGVdBYSLSNzhssE8h6JHTJLGCtyDqELWK/XcgxAvxsQEeD9Bc7viLG9vBRMWWs2AMS2+bEoLKY4VkU6pYyUjVhhryGSglgM9yAhMsgtXCHhkHfgDGHZNtOlMOZtkhRSUPtbnU6VuWnG5UqmIWdkH48uOKx6Qtd36NcriWqwPpK+VmW8GrBtftmGbXqgKD4zZdQ2U5P3PQhgIT5IShq5JlvPFkXZtElr8yzFhK6Hac63ekbZrBhPxkgrXBV1Z/PZuVJwVq2sqJzUhKHjpuzy1/jyVf0xwn5Vcrn50ZRlxq3zC3z66ZsS/YXbXIjT3Ic58yyM40T3g6UqYWLASEhK9HCZy8bXdvUSVUIBgdwwr7XttjEgKKGIm00wylOoqYvMdS6bk1pRsg0EWsXZqYJsqUr0OeVV0bbnVQhK8rBQeYQQCOvVGuv1Gqt+hfVaUrD0a8nz2quiSyRAm9OxFoChKqdlEtnyyjbiVvdpBA0v7gl1fpbHeHkY1v6w/7WbBWjEjhKS0sH7ICmOHEuEnD4g+IC+68omgnPG9miFtBtlXTb9PhFuWndA+53Gr6nXHPI8m+8H64V3Vaun67O9yeEalylnh22Nt8cvDQf4HMSiwqQEjCPDe8ah/Y73jNBlXBmOcR/f94Lvu8giiyyyyCKLLLLIIot8cUrvgddcT7i9y3j/Jzrc2B7et3gHPHYl400PxM9yDRf5ohKa/TXhum8nErIHCeCAs4cexCNveN2snIoLSXFTQ7UZ8QqeWLAYL2m9j3qN1qDpEBR/zEpU6DQdeN3rk/2/GANbYoOkjBaM0ODAYpcmwU0zJ/HLStXJyMHJ4qroE8wRy1LeGi5T3fC4/k8doFjbynAgrtFWiVDSWJMTVGmMCZkdyI0YBl/SaEycopqIuRPJQDbLPqPgRBahY4rzo+KtnAtGR4oll7apASDPHLImqW72HktTY6w5n1YHpQZv1I6waLnemfOVE8dMJ+nca0qWOV6LBg8roKrVUrDJefVoVkeafjCMtmJP1qeCg9V510ykSc0OYOkt0ApCE8amvWvtL5sg5TZcMNGa9huwdBstgjrF1+qfmiqjwcPLdymXGdiNI843m5oGWXHq0helO3iKt9Ulr3h3M9BsTTa8lpU0wy2MXVKeTOeQ9hdrVOcKjcqZpY1Nv1o/gSZBT6RcS4NidSH0vsdDr3kVdnfu4BP/44MYNuel4Gr/YDjv8cArX4EnvvyNTVQOaLTyICnpvUR4djqHW/sHzSJT14jX3PzKdV5MvTlRAXodMyMM8Wx+2bkt2c56ppCMqjO3TTcC1GEcakeytDKuOOPaMzYGj9GHxkYzQWtrUy57r5R2NzjzBE+vF+xrPs29DhGW7iI6KzDtlQmC33yn1hxa1sGLgSEvsshLId/zPd+Dv/23/zbuu+8+/OIv/iL+9J/+03DO4Xu/93sBAN/3fd/3rGV8y7d8C5588kkAwJ/7c38O7373u/HUU0/h/vvvxzd/8zeX89785jfj277t2/C+970P3/7t3/6865xzxnvf+14cHx8DAH7oh34I73jHO/C2t70NAPAH/+AfxB/7Y38MP/7jP453v/vdz/s+n49yz0SPOUvQ/uPI/glzug8dVqs1vA/FkG5PsMl7ouTCgypekmqj6wKOjo4k5cZKQuaFrpPjK2FZ912n97TC5IG66ntNS+LLfRjK8HQoKSNu37qF8/M7yFlIFScna5ztjpRkgpImhTLBDQlgoHM9QpCIJWB5NzpHyCTKUYIoukMcwWAc90pECZIeZYweY2bcOT/Hbthh3F4gDgNMO0k5ILFHICC4mo4lBI++DxiGEbfPzxETYzdmjMOI89t3EGPU9AwJm+0GDK7RAWC5HM3TXq3DyhTMOi4xpZJKQ/pL8zw6yUno4QHqtEctl6MY+POYIMqAK/qWvOIcTCE2ZZtcZUDDa+QCJwq4V6b9etWj6zz6IP3n9Z+jamy20ItWv2ChFBplrOhyOnfLnCUq+QVLf5R9S1UIJCJC+3I3DQUaVtIh51RyBu6GAd4F9KFThaYxoBMB8BDfhX1LLZnCWoRBxvovejg3OgeVkIPQdDKOM3IJh6fF5LrPIu24okQ1C4RyVTgyUDc7mQFkZO1MxwAy43jd4drVI1ycb7HbjmXPXWtf6+6s3xqtuZLUGZSTRuqQsXClvQTHjJQgc0nrWDbXXGarFs8TYodnidrDJEQOp2cWUpHWj8gBqlx6TxohSJTmfr2STXInc/N4dQTvPEJn6Yj0GeaDkimyTg/L/Sl1do7KM847Bx86hNDXMpyDDw51aDQyBwDWpJk1F6Z8J5ubmhrHiEdl/6aAQxlvcrJfU2IYebmvjY8RN4KvofrAjL7v8NBD17DqO+17Qs6+zPE2Yk7mjMQZQedZWK3RH7MS8Zp5N5M94n+Z6tON/2XX18NKLLKN1oHzyzpr1ufkxvcgdV+tZRi5bKa+vxDpug6vetWrcO3aEf7TfwI+9KGIJ5/8LTz22PnkPCLG133d7+BLXv8MPvXzV3Hjf9xbfr1FFllkkUUWWWSRRRZZ5OUr68D4+lftcDEe3mQRgMfPlkgei7wA2cOQBR+WP1RQDklfHcRBqxgaW+McZgZdFHzQyBtdF8Qwqk445r3uvS/nTXBBFTuvRPAwO7viF4Yz7bY7jOOgzmvijLhahYZgoAbX7EAaYdmRh3MoRmFWeJwVwzYMIeUEBqNT3DO4AJBDykKGGIYRMUfkKOm0oT2T2YGFOlKcJ+W+4iiXcsIwjJp6myWV8m5X0mTkzIhxLBhwoWI0WJcZ1OeOQ+bs1Q51ddqT9C6eaqMtCkBmgFPFUeo0McCoGg1a2BJWF+trxYQlOoAvWJuzKAEFn6ZyqY2/U6fMFoSqONGh703nXmYAbg23Tanlj/ZnVoJMzhkpJRBcjXbcXqKTkNof7YaG+c1ron1csWVuKkhTTE4njEVFzjbGE2y3Aeom9eAmqoeZt3W9WrQMas5jRqcp1cchIsUp2jfBz4gORNCw2yrZpRANmlTudgqjzLUylYoj47zMmgK9UCKMaEKFGqN9TbXP7TmGii1bmm6v2KhFdO9CAD9wFVf+z2/BuN3aSNQ02hq55frjj+Lk+rU6/vaMU3ubpPn2zZqp9hEd0PrMLOPoaj9yc66lbJkuMJCdX36XBkv6JcOcqWDIZPV0EOxdw7d7LzY273wZZa7MGcHeneHdLaoPuNDBd50QQ+6C/x7CkNsPta2XF2JvmDJfDiyzybkHi7L7XXafdoaTVrzSQl5cFHmRRV4a+eqv/ury+Q/8gT+A7/u+78MP//APF6LHvcgjjzxSPp+cnACQqBv3338/fuqnfgp//a//dXzoQx/COI7Y7XYT8sfzkStXruDatWvl+0c+8hH8x//4H/GP//E/Lr/FGHF2dvaC7vP5KM+d6IHps5LMeKrHvPcIviuh8EzZq5GvqlInqRgJ3gNd53G06rBa9Ti7coK+8zg56ZXosRJjaOcBBuI4tvpfeTAGZWFPIjQQFwUpg5Fyxma7xa3bt5FzAGsu5hA8nBev6c4H+M5BQ1WAAATn1YG/yW1IAJM8mDMzEmfs0oBMjC5Lp3SBAQdEEAYm3NlFnG922J3fRtyeqxJKGCNhGJVooq86zg7eAyEAwzDg/PxcNxYdcs4YdqMo6SkipYjdsJONSAiqvEqUAHjbCGn9OavOJj2XU67h0gBVAhhwQZUJG39JTZIzI6eEnDNiFCJHCFJ2IQkUBUSjUNj3QnRVEoqX9nd9QPAOJxq1ZdVLtI7gg26+5Dphxos25sCTOTadlTbfyk/tZK4KmhZaQ0dy0QmpnFuVEtawiXa/nBLGGLEZRnSelRSjfavKmSvXTevV8kimymm7u9R5ZgpQo9iVC23xaQqXXJgUVBTwkkuuXMfNdXYOl/kNqEKnc5v1EjH+Bxwf9xh3I0YapR+sruV+qnyq8irzrvZtZXC3mzxLoyOkA7mvg6Vwkb7JhdBR+61uanK2McyyESAHVkKD13FzXtnEuh6cC7L5D0IeWvUSyvH4+Bg+ePQr8QI5O7mC4IOCCK7MYedDs64sqooQH2zTI+Mm0UZAkoYoZ1PCRTsmMIizbiJEKa65KMuuopCQCKpVEzUpQevcqel+bH8tqU3Mc6LUHxKNJDjW4B9Z2gIgBIcrp0dYrzqQEoeGqJCMlu+d1HOIFv5T5pYPHUKXCmhS5jr2dWR77jTfms+2YdGZfLmW3VzbbOwmpdRNyWSy2lvErinFz1T8uYeLbY737n+XXck9iPceDz74IK5cuYIPfxj4xCcG/N7f+0kAU6KHc8BrX3sTr3n1LfzShy9w43+8oNsussgiiyyyyCKLLLLIIi8D6Tzw+vsWIsciL50IFnHIGkcVh6ImtH+DbQm/gOq+nRrs2YyF3iF4hxA8Vqse3hH6XpzenDoelki8KWMuDC748R5uqPUwfC2miO2wA2f1IgRrxAhWXNshOMPEDAOtjmUCfxneVk18mRmRk9aFYGgwSHydEhOGlDDEhDjskONQ8M+UNKMKNVgHUzG+ppQwDoNi8ZJeJkWNbJ0F84lJI/awkWycOEoVxyVDb3gC03BJsTE11BZslgAzxJvTUnFMYy5jaeNa+17uVeYOQz3OKvHEHD4lKgDQa9SWoCkuKlZndbVaVvep6bycDn2Zq1afEt2iwYa4HcXWLkGzNtWYFzKppd9zThhTgiduMHS9reF+TYQKw94qZDa3dKMZH8OQtQqGE87OJ0LBG0srzA7dntRiY3uQnfaClW0RO7Qv7NbeCxkrx6SRm+U/rM5yExTtEPzGrGlVJpWrfU3cjClNmsvtDdpnSsEZLVVNrQWrHaD40zXOgmX+EBV7TvCkEYS6gi07clj3kobl/geuV3xc11nB+5sIGTYWZPPdwHrFbotfW60MaNp7swHUn9rJ45q+a8fT6taWQRa9RNa/OZySzk9HFp/cKiY2vr7vhHSnj42Um7GBRPZgBhInFIKRPkedb9KTF0S9aV8rPP24d8ahqCTTnoFa9yZHae+cAzecIME1TRJNzjuAFRfjipRdnHr3h22RRT4v5TmnVrqLDMOAP/kn/yT+wT/4B/jWb/1WrFYr/KW/9JdKWhdgrkcCp6en2Gw2aiuUYx//+MdLapdDdXziiSfwF//iX8R73/veF63un69y76lbVOxFZgZctpQJ+qKhfgV/dATXdyVcHpFD8BK542jdY71eSdqCvp94u/fBS7oSzT3Wd0G/B9VCZKCC85MHtinN2+0ORIRV8MLY1gfmLo4YUyrpWghZooZ0K3TdCs47ZDC8A/pOooxkiiDv4VY94AjeH4mynhgxJdze7JBywvn5BilF3NncwRgjzrcXSDkLyQKEznWyafESNu/OnS12u4g0bpHigL73CJ3DsMvYDUmimvQBnBgcGdERBkfYDSPOz3cAEbwX9vUYEzgzYhTShXPClCxhwJwo+F1vaU/UQO08jJRBRIWNnXNuUm3MFJ/yL4HACJTBAQi6gfLeVyY9CcOdGm//YPngdO6Qqxs5goXuIvRdqGxs55UYYnNMzvdls4GiYOlU0KpX4kaR9mWqbFbKpqiKclW2fhPWhSlajM12xC6NWAWPdQgYxojdGJGZ4cEgThh5gCdX2PhOIy5MlGO0P2lbdD5nux/pK58lekMJ0sHGNM6mmQMQdn5KZQeJSoCxG0n+wfbORrwoiqGG6CtbFtaERNlNqn92copV1+PayVXEmDFGIRrdOd/g/GKjv6Uyp0SBN2VVN8uzjaI9V2wzHIJTlSfUGmt/Sgg7r/PFSZokTS/CbX8ygzTlj1evBvMQqcPcEIVUUQ9ByUeNdwc5iRgk97cQeVavNqKMbHMBh46ytkHOrDNSvpPLda3peErqFkIu81s8NKyubBE8ss1NFCBBW6ObEBl7HzpZ+10bNcQY4U7qRABHBseMvr8FBw+JBiTVGndZWfDC0o5jQsqMzTgAIByvVxIBZdVpahGJnCREsrpJrypvQ2ChfYWcmq1CmXSNMFOzRHl++FJhHYX2EpqfcA9lXP5jzWO7yCKLLLLIIossssgiiyyyyCIvd2mN/yJT4xv5ANcFkGGGJeWGpUjxJcqqd0ED81LBkg1HIsWV0eBKZtycp2u2asQYQcDUYZCByAlJvIiKM0sXOjjnS/Rq1nK9V2iOsmBHXpy/vBmH1dlmN0YwM8YxiuNeHOpfZpAinb6QXgS92Q0jUmLkNIJz0jTBJKnFU5a6eydYXhJ4KhEhxYRhFDKXc2pY1TYZBjwxjhs+S4BTw3VJg20RT4yUoDiWRTwpuFY5XlNwWNQIBwZck1q7pKkwByqnJBXB7SzqRuH/2JjCDM2CeXvDAyfzbGqncFwx5NboWzBkTBEoAIWIVI6yIHXtBKpHG6M7G/Yn4xNzQnCCW6aUEdXJ0mIaJE7qIOi0rQei06oxvNTaSDBUx8KOs4JsMy6GNrvWODNr2ncuZZEVUpaC4LilL+eFzpy1CqFmyq7AqusRnMdRt0LO4oCbOWMYRoyDYOrT9aZVsjaViBC1Y4jqPABkjksB0/4z0o/TKBHe0cSuNUnErGuCjABmOGY7dVAJGzIUYkMi1Llr87ZEDNK529S+jqERL0AlhTej/ja5M81xUir/5lSD8jhzro4J175suRQTx26zZfjqiGnoN7laO84MZMD7QeYscpmPOTJS84zISf6OWSLCm73EBzez+aAR6XtGbnqF0M6B6dl3kUnZdXFUXPhuV7ekjMvvc7dj+ydbe3K7TBZZ5PNSfvzHfxzf9E3fhCtXruCXf/mX8d73vhff/d3f/aKUvdvtsN1ucf/992O1WuG//tf/ih/7sR/DW97ylnLOww8/jA9/+MOFyPGGN7wBXdfhx37sx/Ct3/qt+PEf/3G8//3vv2sUkL/wF/4Cvumbvgnf+I3fiK//+q9HjBG/8iu/gmvXruFLv/RLX5S2fL7IcyZ6kKP6HsI0ZD0IoBBAfQ/nNaqElzQgfUfoA+HK6RpXz06xWvU4OlrLOZYqhMR7X1jFVMgATg2ppgq1xn3L7ybsZAk756kDWJUkZmx3O+zGEZRzMfSt+h6rozXWR2vElDGMUQgJQR64GRGOesB7uODh+h4ERkgJFCPSdsSYIzbbHcY44JnbN7EbJeqGGLoJnEWhdCCs1x4hEHYXjHFksIbnyzmgZ4/dbsSwi8Cqg/MAxwweE1iNu7thxHYXNVWCvCRTqgQNZi6MJVNYnBI9QidM91Uv0TFc6EDOl82McTuSRvawCB9CHtDfcmV+EzG8UzKB09yGyrxcr3pJwdJLup3Vqis5IiUlDhUlHuTKO81SAEn957Nu+vqdbkbaIzLerSG5Vb0rQ1c3FtwY2lu1nl3ZuNl1zIxhHHA+7MCdh89K9BiShkaUCAyJIwhewzTSlEVWSCOtuInBPtuJzaaUmSfRP0QZqKlxrH5ZlfSiDhYiTe3FGrUFpb+KztSw0qWvNPILiokcAHC0XmO9WsGUyWHcIaYR/mkLDynzNlsOmab+wkLWzY/VgaAkjGZT14TAq20hdH0P5xzWqw4heByvA7rgSrhGhswrK1xSQgVJuTJhBk83JDDWARHI61ElzpRMP97C4dHkUu3IUkeGByDPMwfWOB7U9L2RdUjHrkwOwHk5V+sjmz2GV60x++m96wagRs6xjQwRIXQBIXRYr4Xs0XmvuRz1mUqMjIw0MOKGJylltKqIozKuIc+GNIyIMeHO5kI2zRBS3tF6heAdUh7BSFonnmykJwQL25vqZmC67ltVe77lPqxCW5/tS1vSdOBsPPbKgsxu5kPlNcUe2tjONrWLLLLIIossssgiiyyyyCKLLPJylAa+LRhA2S0L6COpnS29ipI9vCd4B6z6IDhjEOe1klrEcAtmZDanC3N6aQzDBjoU4YKBctJU1ICmFxeJMSHmJHgZALCkyPZdQAhBDNNJ7mmQnxgkWcpRwgeB4TJL9N0o5JEYI1JO2Ow2SDljGAaJmpwFByJ1TAudRKxIA5AyA9kcLRkeDjEmqYN3IBfU8JqRs/RDTBkxZmm6YuZc/moMhwaDpWasnKU19k4dn2pEW4u0UbH4rOkdeJLSxSIEGxOkpF5vU/SoE5c4hzpNv2OEn5pup3XOajGlaqCeIE3t7Ktw1GwetMhgG9l5guU0UR5KR9opjdF9Wos6Z1KKGFOSMWKHpDi7OWjVeVMxvIn3crnBDAMrMPe0DtweF9BRHaWmOHDFkdueqreYYMjMNcc2UNdEW5UaemMC15nxvguybuxYSgmZMy4cqW0j13vlea/OGyf3mdg/YENL5bseVAfSxlnQVzuVZLBxFZRETWXvaJbix9pl4OVkaug5eTIDSrqTSWe1U7QY16QtFl1IVkyZmQWXn4ylFSih2xtMG9Um0OKxezAq1/5qngNOnQJDcCW9ee0H0qj2QirLI0v/oukDeQxJfYnlOZDEWXmIEhGcupVEZNJUS8w1OnTFkOd1tfpzeQ7cBa29R3kuJTS2nFkUlvac+ZNl73bThYj9b4ss8vklf+/v/T1813d9F2KMePzxx/Gud70Lf/kv/+Vy/G/9rb+Fn/3Zn8W///f//jmXfeXKFfz9v//38V3f9V24c+cOnnzySfyZP/Nn8LGPfayc8zf/5t/E93zP9+A7v/M78Vf/6l/F933f9+Ef/sN/iL/yV/4Kvvu7vxt/9s/+WXzjN37jXe/zVV/1Vfhn/+yf4a/9tb+GX/u1X4NzDm9+85vxd/7O33nOdf58l3smerjyYtfQbMZQhEdwhJgjiBnx5jPYfcrh6jrgiccfRNd5+M6jcw7BE1Z9p8Z/NbwWsgFjjLFRONWMTDU6BCsRJA/2EjCNtRoVCUCOEdERfBfgvMdqvULoOxDLOSkDMQub+eadDcZxwG7YlhdYzoyYMxw8vPuUMI29hLrjlMQ4SlKHGAekGHH7QiJ6DGMCM9D1QmyIY5KXvRIjshfShKSFEXLKgIic5XhKGbvdCO8cQt+XEGfHeYXT02OEEHC0Xlf2KUtRoqyLSbqwRZu8cOSEjCApXDzgNGVDY7hmjeiRcwbnjN0YsR1H5BiRx1Fe9lqmBDWwCATQ+1bGquXGFIKHGZ9bRU0+F5ZsUcZapWzyp9aznKNG1aKzSM7DMUWIulYVBWbGLkkfr7tO+mii/tDefQoTVxWNVdeDAay6IJFKfI/QcaMUEeCEzOLgJUxZMepLiRMbMANQg3jdPyh5KjGAPMl9aKxgkIxVKcSiV0x6S9vVLpPCAs+Tthcig7KQc0m8aSQVJQXYbphsfUoZfSdRI+67RjhZH8vmNcm6tCg6FtkDRNgNA27cORdyEhH6PuD61VN450uZzkgq+reGzFMPDUhfdMHD+zpycxXJkVdSkxLGUPRTlACTZMq4Kxt8QCJSsC7d2kG2AaiKnYTcqPkhJVdqjcpRFELbPSvBw8GDyMNCdtpmVhRjGSuLupEsj6n+zwWbsTKXVyvABUIXJJ8hZ2mkRcdJnDEMCZu4Q45JUiV1XtjWmbURvnClTVEXfd7msJfoMjyCyeFodQxLXcPkMMQRMZMSwoAMSZtjM3Oy6bTJaf+aTXPdL91FQd7bglvf7qvIz0dpLmu2Lt57lwN1WGSRRRZZZJFFFllkkUUWWWSRl4vUVAUAFNs1jMORQ1bEJG83SD5jFRzOzk5w7eoprl27ohgOhGARhGjQ4oet05vcsNo0vbnYkzq2JcNwWmN8RSo4S22MXOCDh2OnNkWG8iwEVxyEqJGSRAO5KHVhxT3PBcuQvLgFh2NNEZBTQuaEYRzFuU7C+sJpWutskXqtvs7KEOwkZwG0zdGFWYgp4oXvNdKJQ8dA34vjXReCYptadEl53BiCC/5G8BohpWK10h7xb6r4W3Gwy9KfMWVEi6adMyyqc8EQrawySWqKGxtbi7xgRui9eYVah/rfKXh88Cqqc6D2rhIN2vTm+pcZSAqoBu9m97JYF9YR2saCS8nc8z6g0+u9EyzeuVoH0jlq/UJ7RmA1aDM1v/LeOTYW+qH5mVCvbK7h/etbmWB3BDE6VOC9Hi8wnIHOUzy6YHQFV5ffvfcgdjhardGHTu0Qdp9KSLJOijFhOwywiBs+EI5WK1lveqM6Vep8sx4oYwONtOPaNk/xO2qJSLO5amvIUqFP0vKAAW94cdMPZdEppmvwq80lap5EPL+sbZddUR2uW1JbNSno8VIPRdmLD6rYbLyHRsSxkETaW07tYkrAGbMQubySY9jqqVFyWtpJjX6itgedDxkAE6HznfyuuH7KCY1/qFhvWhtV23Kb9k0f7csh7Njk7nN+fubdzuDJumpKnFz4HHBhw8UXednLydF9CH6FmHYv6X2CX+Hk6L57OvdnfuZn7nr8+7//++96/J/8k38y+X7t2rX6fAfwzne+E+985zsvvf47v/M78Z3f+Z2T377t274N3/Zt33bw/CeffBI3btzY+/1tb3sb3va2t921rl8M8hyIHhZBQMRslt47eAYSAciMeOc2xmcIp/0RHnnwOvp1h64P8KosFuWRLfSZvJhiiogx1oc+1EhOyvB1DnBKwhgtYBpB0nBEWG43AiNnIVu4EMBE6Fe9tEEV2TEBLgG3Lza4fb7BOG6w210gRSBGYExZCBs5A7HmLWUGhpTgA+H0LCj5xYM542KzkegXEMXg6FiiDOSURWkkAMRgl5B9BiV5laeY9IUmKVUSM9IY0fc9+i6op3wnhAry6Lsep6enorh3rvQB2HQF7QUiNUCjITVon2moQ3vl22fhZYpCnnPGxTDifDcgDwPysEOnuS8Ls5oIlp8SmqNx/mqSedO+pKcnOapRL+4eLmt6rL7buSjVNkZj0vQyhfyTNCKHXLEKAYe2dzS/DykVQJWezodmoxngQeiLYmNK7TQSgTGs29B1bHdnAJSKssIA4DXKSc56rdXOgeAkkIdDowTYxoxRV6gqRqpQTyJGsIyxjJ2fKOgl+EibP48Bi7xiD2Jjn5O2i3yA94RV18NdQTMPEqDzyYgKAOH2ZoOk3g7BORwfrfD4Yw8ieA9knY3k0RJbLPaLba6jpi2yzWe2zSSURFWIQw4gX+e7rkMU8lE7vajpL8gmT09nLUuOJRTN2y5zth6qhwO4iYVCuZKz9CKnhBUZY3milU2wjYyT9a2ZLCWYJzUhSiGpoY6PCKEj9KsVnAtIUdohORMzLgYhbu02WwzbAet1h/VRh5xkqjkf4DvbSpiC3uyOAJCmzsq6aV31SjjTdDJDTJCUjU6AAzYlHZOXuMnebzNtunyl5odybXOd1ZEn1d17Fl32dGn30jQ/cbJJPlDKxLOC8KIr5/dQ3KHn7iKLLLLIIossssgiiyyyyCKLfK5kGp3A0DYz5ptNl5HHHdImo/cOp8drnJ4e4ezKsWILho+IVF6CkSsUr6WautsighieYdFv69aeFDcyZIYLBsdqgPTB11qzED1ShqZvHpHSiJQG5EzIWZxnUsqziAQiKWeQA/q1Ob9JBNpxHCV9htYp9KTe7eIFL/VnMGWw48JTEAc9MwKLQRaJASXEeOc0hbZgsd579L1EbvVthIGmL+UrFShxis3WAaijWMUII8xZsPSUxEEyJU3T7g/OBQGNWmRW8ajG0Nvepdy9Kevu5lrDYC8vy75ZNGLHhjFLZyedXoK/1TKZZmW32KD1F7MQZjxqOiKIgb1i44faoeUaUNVgiHJolu6hnFoxYpm3NDs+7x9Dpuf476wuk4srXgqqDnmlaJ72S3FGBSpGy1Sw0bDyBREtwDi4rgEtZxcj+FzwcUeEPgRcuXIs65yrdaMQLoxY0nSLkMJQxpG5Yu4TMooZUtpnj+F+1MyDsiyojA/p3GgdNuv8Rq2fXd+sCeNlNL1XoU5q+g02C4V8U+dlG9XIHkPV6dBseJKm26HrZF56fVawRRQimRdjUuJWjEgxIQSPEFzjqydR3e3upRoTcpbNA/lmzwJjnaRsNhuNyt2kWJrGdebJb4dWdXte6Uduzp2tmcsKurzs9nKefW8L2MeQefq1uc+z3WmRl5vcd/YYfuAd/wHnm6df0vucHN2H+84ee0nvscjnRu6Z6NF3lmdQmKgnp0foHCHcvgMaR3kxQEKQOUBICr6XVAHk9VU5f+BbXjhRiL034259OTFnDOOAktcMEOWVGbuYkHLC7TvnGFNEZlGyt5sNUkylnBJ9RL3bh1FC2MWUMKaMnCNSjkipKuc5VyMvUHV1C6UVs0RbcKrQOmQwZQzbDGbCxgMhOBB7IbhkMXqenl6R1CkjQEnC8XnvQOTlhQsAYCES9B08SS4/a793HkHTpczTCkjmDhamNQEwJjTX9CFUTxTltHnjZU7IOWMcRwzDiJQzAicgOJBbwXmn+SirQsKtllc2BNp3VA3XFoqsVRBrf+6rteVTo1SyFVrVOP3cfHPAKnQAWEm2DEdCgjjRyA9hElrM2LCzl79uENna5ABnpIFJOhZVSW3OFku+1n3CqtaIHuDCbJVOa0PmidcCNLKDJk1EVZ14qhAUbU3CotlvojtZWh4uSmFVelsFSqtocx4k4+W0Ddpc0v4rkR6sRlzzAVq/S4HChM5O0o/IHoVwtDrCgw/cD0A2TF2QVDdgV4zWc4J1m/CGQPBOw8DZb6os5pSRcoYPHZz3KOElrV2yD5goomUuUzNeTU/kVqkkO1HqKFFcyIZG607a97YT53qQbXMjddfgnsil6GYDoGQccgzfy7P36OhI0jB1MgY5ewCErlNQAF42/SQl+94j+IDs5bnZB4e47tEFhy44xMQYY4b3XtLfOGOvo8zlGLPmdNUUUSFI32hqLaohTybTveRrRe3jMqS8r9SKIl52XuW3Z5d7O+sykXeXPQWAonk/B527PPdorvK/MHFweDA/iKuJseIP7h3nTPjY+9+Epz76KD79m694Ee+8yCKLLLLIIossssgiiyyyyCLPT8TILw5wRydHePWbfw/OHriOqw/epx7dihGxYLav+LI3oHvoIdz/iscFU+F9HMHwsIJdadRVM2YCgkOkrClZ9DczCEfFnnfDKIZfCDYxjqM4+rV4I6FEoE5JImlkZqRs2EguqUraCARmE26xEDO8EjOIs5q2NeJ0lAviLsJ5KjgamIAM9P1KUqdIMOCS/txwvYIsOgfnNRVyIUOYg5Eg8tUg33YpN7iiYsnzFLaG81Toq+D1EoE2IyVxsHOGScNrdIDG4ROYYJ8VQ66/7RNCpp8nqTna6hXLbsUm55dXDLn9plENYPEZapTbTq+T+WgYHcpZk3rM+giOQBnNWNRzCoaMZo4XMO1QYe1xQuONJu2Z4af1LmTg27SsMojNhTpGE0fB4k447bOCkDbOgGBXJ7/d1rVXWb9gb36VXjeckLiYMQjidHlyfFT6S4g3Dub0Om0KmfFgeg8lclRHT3PAFLuUgxMbCmxttZWm2cdmQrXjps+tlpDQtlKWmUUbwqTu5hBdy+TST6Uu3Cannw86Nf8gBCNyJcp68DYuco53dk+Lhc4AcXm+MMn4eUfIwSIFic0tZTtvlt5c+16iG0m9ZB40/aoEttpBlShT0p1j/7nQrriyJMrV++Dt/lPEJv3+yMyvm0bsoP3zG7vPpEYHMOTDtWt+Ky+bQ2ct8nKU+84eW0gYizxvuWeiR9eJUa/rAkLwuP/6GfrgsI0DUhZShfLw4CFRDyT6A8FT8xjm9jEpLMqkLGynRI/6yBNFehhHgAAPCfHXrzt5EcURMSXcvjjHdjdihEfKjBtP3cB2s0OKEZwzHIkttus7+BAw7iLimBBCEEahlxe6RLKQ8HtirHXFqG/hpJTgjZgk16FXarjTPGVxSEiJ4VxGCISj1TFC8AATciJcPbmC45MTIAGUCX3foe8klY2Dg1Nlnx3Jv0wSQAAoL0rpyoZJq307UbKgkTKoub6MQb2QG6Uy54yUIna7HTbbHbwjBGVg+z4cZFYz5/JynpMPCsej2SyVA6WWcm9upkhRG5vwVdPMg3Plv9bJEakhunaVkdYDNM2MpfqxjQbavmw6tWhcWm2NXlMOGSvBiBNUG02mgGkYxqLmmSJTFFhVDSx6BGlPlrpZF+i5jW5e2cQ6jq7WnYzsQ2i4IvukGutB6eqkpzXr0MIKlvpJGa4th2i6mSqpPmqoS4d6eLXyePBoBRChUmY0p2d5MlxWU62WRhhKmTWNjW2e5TcHAlwHcrpmy9Da/GOANTdmiWGXZZ/Qgga1drOaCJmjzbloZAGn/ZPJ2mPj3m7GUJT03PwsUYwgIf9AsJQwPggh5vTkGF0IOF47kJMoGilru/RWUl4CHMN3HqHzWGuu09UqIOcMB4aHXA/KmkpLiHC2yTDdNUZ5ntn8dj4UYo1Mk6iVd2X0xKPDQoyqQr83npgQxux+E0V9ov1erowfkvaKSTFav4nKT7bhqefZ82p610vqoOVamqcXK7CHh8dD+SHcnzzWvN47zpnw27/6Bvzmf34zcLCHF1lkkUUWWWSRRRZZZJFFFlnksyviKCZEj/XJEd7wtV+FB554DPHOBfI4lv06QUghj7zhdbj+pb2QA4C5Na98mKStLk5Y9WQGkFLWPb3gEF3wAlllwT1344AYEzIcMjO2F1uJGpskSqw5v3gvmHCOQuoo0Y2VaGF1KQinYYLMBV8wzC5nJRCoEZcUN8xJyyCGy0DwHZy3KNeEVb9C33WK99T0vCXFBFrnM8U1FEgszl5AMYrXDt1LugBLrzOFPVqMlBqyh8aEVhx51AivJQVLNx+beXnt71QwGMLkP5Nz6i9z3BZNvYvZenKO4a/zexNBnDOntRHc0RBLTSlSp1lbN27m6Kx4RyUy7rTeVJs4aSYXXG/yvS10v1u0rAKoNRgy16rZ5S2G3BbTHOcGeL4cQyaUROCWB7ztVzedXZMeO4APzruBHJW2e+9w3IUDzd+fw5eJOXCKSaTizhY1mp1h4ai2DK1LjeAivVnxep0T6kxbBoPblCYFJdU67K8H6x9Zoq3RrK7VtuUW+7s8FoHqW1vIbUJw6/tOo/xI3VLiyfSqfzJADPJCGAtEcDmDvRO8Vp8ziTSCNimJjKqjYH3WQZw9bQ5ZpPdCymvsWmjS3VcDSOlKQfub1VzWoGDNLYZsJpzDwrNevFymKPDlGDBzM+cuKXjvNXbg+MLxWGSRRV4suWeix+OPPQQiIPgA7x1OjldwYIzkENlUvBrSTkSU2yxaAICsxtPGa9y7mh9Nn8pOPeSZPKCKb4wRN+/cKkzhnDO224gYE27fuY2YEmKWsHW7iy1SjLBoC2b0lmsH5Khs7JyVXZxVmcnInCXvWDCFTnPzKSPRlNY+eKl/khfaen0FRA5nV+S6fiWRT4IXEoeFlztaH6PzfbGLe0tTk7MStllIAkzIxk5lNSByo1RwDddmeemcsdmbzQUs5BlXFYhUAcucwSkixajsa0l7wTmjV9anc/Vl3YY5MzF2timC+y8xe/HNFHFgEkFhnsbBWMRsFxSSgv6X68twHtKLICHZcnnp2l+ZmFnnq7vkVVv7KasCmyupo3YgCs+71ZKI6rlFuW6um8S2myorBGOJt22SiSJRF5tdQEsEmdZmukGqpwKZa4SS5r61Fr5sEITI0KpMVSmbMOjnbdRCW2WnMI0ZJXTFVOWt55YkPtaAMqEapdb0RZsjzTzy3osXAxE4R9UTjYTmShSQRucE5yYaStNhWddYtrlZ07zWmk82lbqh5IRsquHddxoAJIJL1k24I0LoPFYnPZzz8K6TfncZzskx51TZzVIpCXtKTbEM1igVOTJiToiaoiVlea6wKtTMEqHGSC31GVd6G4Xg0e787Jg20taZdQkTQJ4gWV2aZxfaMd/vnPJ8aQ/N18p8KfLh+VSGpV1NpvnbJnjv3rPbWvvnR8rgzjeTdLCs5yoBAQ+lh/BgehA99yhsvUtl2RksssgiiyyyyCKLLLLIIoss8vkhZ2cnOOo9vvwtX4McI649cB/6rkPSvXix68FgIrINfAP/mJFUY0ST4FFT+LBxcjJMQgkdwzBoxGaJ5BGj4MC7YdAIHYKLpFGcBKH1MLt1zgzkJPCrOrIQSP8C5uBiWJ/hD4YjFV8wopr+IwuGG8IKAGG1kjr7QEqUaFOdELogmLJ1liuNbbA1bmKUlhQIjTOg3biBGQua0QKJYDRZbZr+l/+yYq2W7tuwHmbW6LCYGHwbVLKOVovx3RXGmKM7U0NtQXloenqLN7U41RRimoJBFkugGG4LXlRQITmvOAzN8OsClVV8+wDaNf07bUwtqACeeu7BPiIDt2pE5UmfqwPZBJiqeF256QzuKi2zD3xgmCZQ2ix6uF1Xvuix9iZ8qAdR+739C0h/OFwqe5cYXjuPSnPopoBErUDQhhVjFox+UWZAsyYOFAMjflmV5Tdbf20d2k6384U8cbDc2qjShhJJnGSWO0/wnUS0NrsQSG1Y6sxXprPi+e0z1PqeQfLsZE0PlUmiUNtzEUDDKCl/pj3Nze97wO7eR6BptwMK52q2vPcXgs7zphKz18asVs0E4Okp7VJ8dqnlXI777k+2yyKPTMZ2kUUWWeQFyj0TPZ54xcMgEq9w9Z1HjiNui5WyPMOyhr0qLEQI+UNemFkoHkTNC4jB5CXkm5EpvBODuCcJhbdNiGnEZ27cxHa7xdM3byOOGWknJJCcRg2bJ3Uwm7gPEkrKUinEGJFThuX9MgOvMQgzkhhHiQEvChNFUdKysrQZBHJeiBCOkCnD+4CrZw+i71dYH62EtW5Kfom8YQZAVa48qwFZFWMwMlJVepglR5oNgJ0LAErssIgERj6x1DdwNQSZED1SywtR9jcjJ0l9s9lsMAzCqHcEdJ1EGakvZTOVmiKoWwKSjQjDKBRVmW1z0unM2H/XZkDyyk3f4G1TaykESW8jJ9Se4Vb/hqghSvSwQjVnH+kviXPdTJK8cCcRNLQwif+RAFYSjPSQ/GvOJ5jCD53n+5sZNDlC5VAujTXFpPQ3t+3SvlaFh3massd6T8au3dKgKO1OU7hk3bhisvGyCyyyxSUbMBDmXJOi9JcBqBuvlqlsvcYaucU2PfN5I/sQrZsrt5DS9AK7CzXRXsr8JCGikSOkFJHziJxJw+85IZxZQU1DMk8fHKYE55SMn1b7Q/8VlZJRNnMgBnIWEgZDNdTJLuhAn6uqzFSU8G7V4eq1EwQf0Id1fY5CCG/gCoQY6SZpZ9XYJJKjNo0ZCRmZHTJIc9NSWR+sRJFWRXbOhk573+lat8EsR2zOEyoRS+rCAMgLWGHPM6ApYPJxfwM2VYtnm+jJvVHX4uW7okvk0oGZHdsLylnm5b1c/XwkIODR/Cgezg/rL5sXWOIiiyyyyCKLLLLIIossssgii3x25OrZKXB2iof+0IMou2TO2BGQ2ijDakhsPeAFaxH0xzATwz8AgJ0cN5s4WTpdTaEruHTCxXaLGCM22x1yZuRoWKugIdxAOZa2wKLYglAIImY0ZsO6MwBX68wGxjT4kRE+BLIgxWGFUuCIsF6daArdoClODAueYUgFQzSMsEFE1MlMgivkJkqDYfR2bgVbWwczKjglDGxDwagrGC0YNEm/ZWbEOErUFIXWJMqIn5l1dfwmGKMazxmamqMhROxhyNZ5dpD0pxYbL82q5+pfAqTePCkcU0O7fGcyXF7OtGAUAh/a79oWaozLTUtliBQgZUvSbABivR83V9YxanEyG280DWna0GBrE0SKpxiy3dZwy1kpgpNT7Tia9JsVafOrYrJNRbW/ax1LhNuClU67ulSPgYZCMe1PKr0GgGVON3O+zujmKrtHizE29dXl3daiNMWRREuWNEyp4JuT8kol63NAJkpzL0DsWk1FJf15bWGdzlwbye263gNDZ/cHzAhTCS4E5z3W6x7OOXgXykUMtQNY8c2cqXNW/sOKSXNiJP3OsEdMu/acEuFqvYnaFiqGjNnYtIu1eaYD+shUYkpxBK81bDqiHWje//kSmWDIB65/lssPlvbczrn83s+p2EUWWWSRZ5F7JnpkZtFXnL64WQkcKsVJmgmRa+CkYrglgsbCkpefI7OkA0TICYh5xDBEXFxskXLGmJJE8xgihjHixo1bGGPEsBmF4BGBwqC2WzS6VAge3rsmhQKJoqeGSx+8/Os8Qu+LR33Xd1gfr+XlqY7UGU64J0FC5a3Wkr5AyCkex0fH8M7LxgBU+2YesaJheBrBxPrKFEFjZ3KxMKPq6VTTZhBko+CUOV1TnVgyO67nOUZMppTHcq4pq6KYS/u994XMUcYX7caK9t6E+y/GZps2ef821zabiVb3nqRxmRRsDPv2Hdi+Davv/uTXVumEtHFft9+7mfYtSSjFUntTThqld35l0+Cs2jDnrOvASpLrcpLvzkuEGGdlOjmjbFhLn1GpRVWMNYpEyhKdwbcpR6BEK1ZFv3on1F5ypW1TFvRcMdM+KBtBa7zN43mkj9mctmoowUEurSNW768bT6CJgFJVelibjLMliVIAiBeB8x6OSMgNOSOnrCQYhoSaJM2baKQS15BaGuKQRdIp3VmV+lp3JamQErfKRsK432R8K/nOGc57eN+ByIG8eHZIhCDJXxo6D+IOnIWwAkA3niikumz9y22voDx3alAliTBjEUsKk9uOlT2MVJIATSFFZf47z/CeYRvGXM5v5ocBASREESYhmKU0gpFnmzue/KljXz10yDkFYBgtM/6gsI2Ozje2b5jNXZRxe65S1njp77tvBZ7bRmFfIiI+4z4DcoTr+TpWL7C8RRZZZJFFFllkkUUWWWSRRRb5bAkzI+4GfOY3P4IcEx583auxUpwVMCxBoxnDfmOYx3m7qWZmiZjR4FXMQOaElDLGMRanw5wZOUmK8O1mJ6lFxqz4Qimx+UuwkK9O0/NO0ScqxkfnxJmQPBVPeQLBBYfQBcFICtyhx51E4QjBNaC1Q9d1xWmvhdf2QM+W2NFgKdXQOumo6RjUFjR9joLPyUnKWqlgh1yhGJc4PyXFWpoSrb/UaYwmg8YF05tHc4DionNnmkkbWwzZrmn/2h9ufm/PKR+nUUBqgfvf2xgcXOpn85ELfrbfmLYswNLa7wFSBfdu6lT+Y+Aml3qIrWEfuyqpphvHOhhcB0wc1Gq9rLfrvGcI3lYw56ZVk2lE03Unf6j+nTBE9Liu19ops2Pa7kKemdxd/xjunJtnApopwNO5VfuBpmU1uGz91TBkm8MO5DIkrTuXvue2Uyd9Ao08oWPGk0PQW5RfikWhwpX6eYohy49U5oo9iaR+YmuCPk+8phE33BZw8iw1D+hSsM7vMr/avta6MZU+ZRBIo4FPO7xpeymCC3mrMVmASKOSWxWaIWnHm4udwr5ncE6Y3rBpy+whYPYlshtbc+2Beqm05TSD0vx5cWT2UCr3PnDmi3rfRRZZ5OUq9070EGsxXK5GW0vRUiJDAUggRIj3uL38amg5eZALy5HUmC1G5oyIXRpx6/wcv/OxT2K3G3F+vkVKWXIlZoaF7KiqZf2viXmnExG6zqPvPDYayYNJFHTvHZwnhD4gdB1W6w7rdYcudFh1KxwfrXH16hUpOUFeqqEviizQKhRN6hVmxCwbjGTKFwAjVFiov/aFIwZOB25iMzg1cprhlcje9TRRls0w7KjWwTqoGOOp9n9mieCx2+6QUkJwrrBXuy4geF+UBYuxUPqYJe1OS9RoUyJUmW8sphpBqwAArUFaNzZ7OhnpJs5SrVivTl+U863YoRqZGuMmbai1LKQEoBibyZGGLmxJDKbkcVOC9lfmWrYq+Mwoygohqo4oYzZKgAb0zsvWyiz1TEJAcNPNhC0lp7d2EkgNiRNiTnAUEMiX84uxHCgEp8K25Wl/Fj3U63FNB1KIIdq0wvrnuiZNwSwbs8xloy3rBkbTBQg6z1AU6czKqDIvgGRlaq2E1QXr3Jy1Xa4STwhcPCJEyfUYhgG7GCGnyjbCFH9pi0MojGclEln4G4umUruzpOYss4YYpPlfm1GCqeSAAA1SXgYhwYcOXbcWdrcnHPUB1056vc5Bkg95IDNiHlE8N6B7KFbyEaM8Z3ywyYHm3rW+8ozWeWAb1XJJO/sZXp8pRrwJgeECI8d2lbXrIetmUNoZNO1V5hEpDahoyvyJcXi9OufgggNnRkJGGx51Ltz811bh5DfbIB646+V6NO9/nezrDpd39zKfm0RE/I7/HWz9Fsd8jFP4Z79okUUWWWSRRRZZZJFFFllkkUU+D4QZ2G02+PX/8ksYLzY4eeA6uqOjCucRAI1inBUHMaiukgbMQCuAIRfjqgMjIXLGbhxw6+YdpJgxjLGkbRFfobsZ+6Ss4mwEiS7tHSFq5AozMJcop97JOcEjBIli4X1AHwJW6x4lQAII5LwaMQ3DrfcEKvaXNfrDpKpqAJ07DNY6T1NKUOMcU4gR5VZUsLzqOGZGUbMo88SYL/5qVPD7GCXKsbPrSdMmU7UPTNEQQiVzVPy1OFY1dW9AnEvHqLWVFigWh7+XCBN6oBY/refdEmW0RwlCWmmaAOvQiiHrX3NqY0mlXDGzvQ9Ngwxo1SgKirXanCDOk/MtULO3NVTGsC6eyUgQ6vg3dWBmZGQQC3mpjgXXarpKumojo+zZC0pddKwaDFnqsHd3vbLJ02E2Aa2II3Mmo1JGOwYl/bb9rlhpsYVkW4yGPTfzDQSJlC4kCucsujUjxYSIrCmWZlMLlnLbl1+ktBnpyk0ugs1h+ajPsj0MuVZ3Eg0IGUReInUoKafzDuveo31GMpzg8NSA1qUOVNa6pSZ3kwwszbrk+rixYWufXdabpblG9tBnA4jELucAviwDdUteY7NZAYystoFnx40nvad2LVubRiA5dOnk+TN5AF2OIT9/efa6P59TF1lkkUUuk3smephCCCUCSFqDVBRXU8YdGF7TnMB+c2pgZWAcE4ZxRLyQKB3CtgZijhjHAZvNDtvtgDimwkQkY0prpALnJZJF18vfOMjb4+TkCCGEojAfH6/QdQFXmCU0YAbAkr/MOcD5AOc9QvDoOo/gvZA9+g6OQsOErYqpKc+55EJJau+WF0NmZYqrglL0nQMKnSna5eUyU8jmWf2q13uj4BQ1CEJkaa6WF7S0PXPGMOwQNV0LszB3XWHGVMW+7odq2DGCKPhtLjg7d/JhL4zdtM2sxvSiDtlnu778bVtGRXWuRfHknqIiFvO1KqLTQln7tFXZ22pWPdHyhrSbLZpc0m4N7HOGzAOCsvsdIQQvuUFj1ZaI5HciQqf9Wdi8M+8FY+fWCCzSkn0dgCYdOVGem7Isao30hNOxbpV1FJZxJQMok0tzdRI3eo+r97W+yFznZd2g6u+mXNomRcc5a8obQkaNWAIlklTtmnTcSx+R1cU2mNpXyi4h7+FDkDEhibRj5AjTYHNOOp3yNKyjkmzIGZFKWN25bBhq+wDWUH/WzwznPBw5+C6AnId3DE+Mvu+xWvUw0knnCSmhMJ8zLJ0M1/7TDnfahzmjrh1YKpeqpJrnRQEadCPBRYmXqCahC+j7rkyh1dERfOfRccAR91ivO4QQ4J2v6WG83MuWYU4yfpvdDpkZq9TJdEm5mbPlFuXZyO2vzQ6ikOLKOc0zEtJHk2eGjUNzTkONqXlU27WO5yqHdgiz3c8lp70QObTSF1lkkUUW+eKQO5+5hk9+6FV45rceQY4LoW+RRRZZZJFFFvliE0NDzQHJEizTJBCAq6E2CjxQsI6ckXJGzpIuxCJzJGTklDDGqPhxdXKyKASG1Znx16vTUlavxb7vSqpjQBzgvHOWEBpmuC6pCJwQOJyTVCwSEdlJVGRNabBnKFRMp8JIir8poGPIxzwqQCV5tL/an8OYph2pmGJD66AD58x+t3oZZiMpkdVZk1Edrew6ml7XANUVB58bXA2fKfDVZRiyFcWKRzdo9yEjLqOCulzLa1Gi9pqShprsyxxDpuaSBoScY8izzj2I1pYuI0y6ycovOKJGlGH1dWtwVqdzV4M/T6ZBG8RCcEWL1GCLbE4kmjbT+mNOjCItvG16IbqgwZDLT6znUXNBcx/DkifRJQ7g3Oakp/hnPbtGx5g6guk6nY2xdXLTPbW/Juu0ucgRnDI1JoSopo3M5oTM0wAxzTiXFhHqc2leH26ju2jkDgDO+TLWROrQ6H3pb+ckLbddZw6UAtA2EwwWLYgrZDppMRtIjDa6iPXl3BmXQCDv4C2KOAGh6+Ccw+7OHXzi//cR5MceAl77BBwRjOdR5o9GLJFxlSj+zEDwrvZTqQbVq/cw5Hbs2rg9cwwZB77Vcag9QZPSDUNushK9ONI8tg/+vsgiiyzyAuU5ED0sbIcHiJFjRkpJXkJUjayeM0JOwsd2JJe5+tza7Qbc2l7g5tO38NSnn0EcE4Zd0ne/PEwdAMurCKAYxeHE27vrOvjgcHLWwzlgc3sHMPD444/i6PgI4ygRQNbrNUIICMErQ7Po2FXfoMpsdCRtceSF6OEA0uR8ksLRFFxGTKn5DmgGjqIOmLGbYIqW/F44r5MHu208TB0S6qj0ST2RrH4zNUVt5Jr/DY22KP24iwNiTthsNogxSkQTV5nodo15/JvBukQZ4aq8mNG75sm0OBvyX9cqupOXotUtaaQHO2dfsarG9qpMsXaA6e7F0Ny8jon85AVOxoQ2hnyTNFPmrS9Vs3Eqyl6rGPOMckM6r3WcrQ05MTYR8ERYISB4h9XKI8aI7Ua8CjILcaP3nWwIyYMZGHZb2Wz6IH3sUEgebQQG4+bONw/cfJA0MXXzRY2iXcosCqsa5MHIxrg3pa7tR7JdkN3ExreWU1VFTTpk/ZYZCaa0WSQKmZupVdd0Y0VE8Po8cbndXOm4MyBkZfW+INZ5KYpYZtZoKA6uA3oNcUcgAQbG2JBbJL9oq/Q60sddZ8QqI/7EMpeUtSI/K/k7JiF7OBJ2tHce3jn06yOE9Rqr4LAKDl1H6FcOORFilP4fY1JyiMzszDb3bHGr4quVjJpOyIYmG1GkBEDRuuiYV043lznhiNB1a5yencF5wAXCU5+5ga7vJUVXn3Fyskbf9XAUMPAIAOj0VQAnhIwcE9KYcPP8FsYUcdwfwzsHn2s/w+qqfc7N+q/6ua1oJQA1WM8lqjnq5Jt6OTQH965taETNOftX7R+7TMUvD71FP19kkUUWWeSe5enfegS/9GPfjDj04PyiwkiLLLLIIossssgin1spOJIr+Jo4RqE61bFgQI41Sq9BhE1YisgJuzhiu9lhc76RtCyJ93bqNRoASloVKY/ECccB3Voc+uJOQuteObuCrgslXXMIQdLXOlcxNW7uoe0q0TOA4sle0pdUvzEUBzY2hyEzGjOyGrtnPvJNx1Bz4wY3mWCu9WqJJAGzizb1Mwyk6TGD9NpCm8MpJ2S2lDhJIr6SYq6uDl652i4vBvGJ601TG/lejnJtyr7Yj7k4Ak1+b6GeMmdqT6LUsJ5o/SC4ciWtFIOuMoxsjCYUgWZI7OdS7QbLMjy7HtNW0/S7dBNjTJqKA+YsKCmoLeW6+bF5yuX1kAABAABJREFUV9PNMwMpyfHimKfjWSIeK2C4h1GV/mp/a85qYXpDz8o8k7KNuMCTHq5rduJFSs24lbYfGqvmu67lchdufzuw9sHSL1aDXOtSRmYyx7jBuVFITND+88XeIdhsTuoEq05nnKtTrJVFxE1acLWbZKttWSCTVkt0Fnn2EYlTsyOCDwEuBHhHCE6clb1XAlCGRi1iVEdbVOy1kHto7151GFj2nnY9CfRs0ZTJurDtZP3rfUC/WhVb3+ZiCxc8zj/zFH79fT+L8fe8Cb/v678OjhxSSY9Th56RwaPYR3bDDokzOq9prNoQ2vY+mDkP1nlk9dLZ13pCNjPjoExYL5edd3cC2uVyLxjy/tkLlrzIIou8GHLvqVsQgQwMm0GNeyNYUyKQc6gvclFiiTOQM1zfw/cBxB4MhzB6dF2P45MeKa7BOSHnCOeAECAe8M6LkuwCiBy6ziMzY0xbNQCKVhJWoiKuwwgwYb0+Qtf1cCTkC1HSXVUsp3ptUUTbd8SermNs5twUwKruKOmCNQRCy4BsVVhS7ZpMgyjf9Uyq5UkdPADWpDZUGLmmdNBk5yAVMg99a1NmFqU8ZwxZ/jpH6IKXEHslJUitc/G050oCnSj+1NArrN8oT3qNrVrWJ6WO+y84nv86+WG2GaD5XZrztE8rw7fdZMy3A+0oz0LagRpS0rT+pvTLPlXPY2pKIBBlBMdKFNCUKpHBKSN4QnYOORsTW43kli6EmnBlLbEG0A3bZQpCbVWpa8MiknpXNnJLMLK6W5Q+UC2r7WW2yVCUeYAs2ktRus0LQf9l3ajrBpIbYoReVRTeMm9Rx9nmUAZK7kmg8fpg1FB+dj3VOUw5y/iwjY2uH64RUrIqx0kjEFl/ZD3Pc60tWNpgjPIyv1RZl0w7Ds57dN7De4e+6xFCB9eJgk5EYMllBVLCHJr1wU2Rdd240l/t3oR1A1o2blxTnBT2/kyMvMU5ayQfj90QgTtb5Dwgpg2eufEMdnkEBY/T9TWEfo1bt+/AkccwSrhO2kSQI6xWKyGRJEbKEeNuh90wYDgfAQbG7QbjsMNms0NFckyJ1rEv496sRUZhcrfNqK8YwnQu6eBPGluu2pvQ0m3z68uRWa9pfbken7836s5wft3zFw+Pa/ka7sv3IXCY1HJ6G8YDr/kdpKHD0x99FLc/df8Luu8iiyyyyCIvvZx/5hp+65e+HE999DGkMYCze/aL7iKcHT71G69ETg73v+Z3cPrATfmdgWc+9ghufeIB3PydB1+Mqi+yyCKLLLLIF4TYu5acGJqe+dgjyGmJnvXZFEaGCx7Xnngc424HdB1iSo2zVMUGmDNu/M7HceNig+uveBRnD94PZsEfXSJ4J1GYeR0KpkHODIiS0hrFSUeibDALTlG28hDnFgAITqK6dqHTaBxyQklhewmGLB9qdNMJTskVMeDZtW2eBgmKS8UNzURwsX2MsmDIdkS7bn5e6Vau2IlhyMrqmGDItTD5mqEGbRaMTEgEgCdXCATFlF4wWLlYMKw2coiNbcWQoeUdQjbMNi2fL8E+GNMo1vUW0x8aN/yCcJbOaS+cwDzNmF1yf712SmiYlcYzLI6aPrEPLVYFNn5BwahsDByJI5t0dXOXBivex8EYZntoWthO3n2oat7cpq/aaWcdJRi1AbNaF8MmrWsK46hWtkRLIZ7MiYIOlnXFtazWibX5b8GQm3E2QgxDSRxlnGpd2vnXdgmISzRkucKw80p0aVNWF3xW7yPTRsea27Hi/Xsx1GlObQsQcodzTm01DuRdxcYNy26wyPl4WVdN8jZNHi5NV5Q1yc05zfdmfpT1nXNxgIwpA0MEc0LmEZvtFiknrK+e4ZX/y5fj/lc+hjFG8DAoIS+DRgYcELwvY8vMSCnJv0He0zmOGDZbxDEeXK/NkO8jrnsD25x0cEk/G2bbPhToktPvgiHPq8bzp/vk6CKLFPnUzQ1uXgwv6T2uHvd46OrRS3qPZ5P3ve99ePvb344bN258TuvxxSb3TPSIvENKGbdubBBjFmUkMzxDcw/qgy9nICVQinB5ROhO0J2cgnMP5g5rzkjIOD5iPHB/hg8RXT9i1QNXjoHgAlbdGj6s0K/P4H3AetUhpgHP3P4kht2AGzcltct2u5P0LqYv2Eu+lw9szF9mcCpxBophkMp/UZ7NDu2LWoz08hIiPS43cqrsBn3ZjurpnzQNRMuAnVROyy1Kg25waoQM+S73YXgizb3nwBa1QBtRw1qptqD9EDW04a2Lc6QYYQb+9aqD7yWSRGWnV+96M2DbS9eRRKcAaWoapaczapQM60PS6Bilh7Xfc2qbL2XRrC9aZZfs5FZrg+kldTMyfT3Kt8ysefqUzWkUVC/3LJFQNASDhUUzZY4KzVSjNiRMNwlK9HBkkSTcxAPTk8Pay7ixi2AGxo1Ur++0fwovRvowMWsUCzSEBq7ttTx82QGc5bdCLJptXPR7zW+nI6TtLHuLpt+sPXK5pkYSekVJ1ZGzhUrUa1yukTMAlCxGFrEj15Qd5Kgeb+6fqzovv1vZsJ806ouXagXS4HkaOtPp2tbAOjJe1GxnUi6bDUs3BRImdIBDSqzhPzOGGCW6hSYSTFmIPC7bOpUcgZKiREJ4GpkFzMg5golxfHyCrutxtDpC33UIfQffdUgpSx86p0q6h3NB0l9ljSZCNofrZkA6RufNJLmhjrrtCAFNpSWbE3J1bE1sI5VTQsoDnEaUuXNnixu3BpzfeRo3bnwcz9y8jfO8xenRGe5/9BXog8PvfvzTkuoqSMqu7eY2vA+47/6HEXxAIEIcI7Z37uDiYoMbt3bY7SKefuoZbDc73Lp1jsNi439gc8oo8w3QIURd0hPVedrQvWfHofvWTeBlmj9Nzm+r1pRSN3LPtkd4jhIQ8Mr0SjycHtZVsTl4HjnG6//gr+C1X/cB/PK//CML0WORRRZZ5AtAPv0bT+CpjzwGzg45vTCSBwDk6PHB//tr8Rv9V+Nr/uy/LUQPAPjIL/wefPD//lq9z4v8slpkkUUWWWSRz1Oxd60JZ1qIHp9lyUjw64AnvvarkBPDBYftMIhDG1kKaSjumvCx//ar+MiHPozf883fgGuPPQqwB8MjKM7XdYyTYwa5DO8yfGCsOkmz4H2Acx4+rEDOIXiPzAnb3R2klLDdJuSUERU3mQNUwVcMzbCs6tJeDdPtfwXerFEiqu26iWDaIA7m3OIUU5XgtYorFTzLpMUYmvKLcRkFBylIshp6C16JihcV27OSPUrzFeCQqMsZu3EUPE9PDd4LNmbjpf1hGKQZvFtztgNhmiqkRkCxSBmGg9erdB6gRnalklOaqr3BgJxy4RxPavDbtvRJ39o1B+po35vpWUorjn6kw6Hgm86DQkxoMKY6DDTFn/Q0B6dRxLn0WY5yzHu5Z4tU1VQfPJ0izTyr64pgpCQubZ5hZ/ZrcSQzDLlxssO84GYOlu86vmUNAIRc7ChW3zJfrOOLcaPaNoioOhvWoUKdtVzv3Ea6sbnjxBnX2Zgrhqyh46uzYFlPenW2BOPWaCofnSfkTBLJgzOSRiZyijVbNX2Zk7U+bQySkq5JQsaLo7JzhXDmvAM5X+xYINu/Ecg5UGI0C6S0Y9Kf4pXa9JdViWywS3vt+vYZVcXOS8ic5DkAj2GI2O4Sxt0G291tbLY7DBxx9YlH8dgbvwTBO5xvB7hhUHtARowDiAhHx6dwJMSWnDLibsAYR2x3CTFmbC422F1ssNkeMnK34+8OHOJ2ZuwhvfsYMk9POCjNPSe5np71wnLH6rRLLymGvMgXh3zq5gZ//u+/D2PKz37yC5DOO/yj737ynskeP/ETP4Ef+IEfwK//+q/j6tWr+IEf+AG8853vfEnruMjzk3smevTrK+DM8LQGM0tOrpxwsd1iHEfxkncErFbg42P0Z2c4uXIFbt3DeQJTBueErgNWK9IcFA4hdOh7D+8zGAljYsS4g/MZXZS8h9ttQOaIzWaQ8GVJXo6+5E4z5QLNXwJnUkUxize+vQwKI3KqtJjyYQ/gRmPVM+qLr6RI4Onrhshe8lTLLNcRGLm8XC3Enyl+RZmyDYE9/Jv6NnoOqspghmdNKxNTCYnovEPhpFMT3QQohI76ndsgBZLWxhoGY+fmhpRbNaMS8q4pT+45ffnV+88U7slpzcuzvHvrxsmU/fa9aOzVSlA3Zbn2p8Y9ae5ikVDqCJbNAGWU8B42VjTbU6DONVOKzcheVAxqxhB13pRXPc/Os1lJXHMkalu4GXk5pdnBUI1kwk17bDPEqH+dtpRI5iKbUq6DbyQMbtpVFSb5LBvBWUQNrtE5WDdgFsijDO9EQbcV0pyQ5X6gRmFvlW8pvJJMuDKhm4Et41U3I1W5cuSEQa1piFxWwk+5YZa+zZqTj+oaA7NEw9CoLnIzYVuvVit0XY+u03RRXnK0Bsj9nBeiiSMhz+RW+TZFU6d+AQa0vyYpa5vxqkS1uuGyPpVIKtZpQs5JOWIcB7jMSImx2Uacb0bEKIyko9UaDz/wAI6PT3D97ATBEYLXTRoSoobSyznh/M4GRIRxO2AcRzz91C1sdwNun+9E+d/uMAxDTSVkU5sIjishaS42l2aq+J4aTZf8Vvvv7rJ/SrsFaH+7mwZOB0574Rq7eRG5+QZmfh4BFDLIMZx7aRXBRRZZZJFFXhxhdkjjCyd4VBHjFe+Apz7yGLqVgGMMwq1PPIA0di/ivRZZZJFFFlnk819e/HftIs9VvO/hPHBKHRis+3/GGCNSwQgI8AHcdZKqIHSCYTrSKLEZ3ivnwpzvyMMHpxFeMxIYOUYQMVyW1BbROTAkRW7OWfEUw2Dlc922c8FlzQln6olvURloaudDg8kV5HcPIK7n1jP2sL0Ws5qiCTPjotW/xRjb85r6TOpZ7sb1L6NgUpK+W/FQR9VpqsVdDZtVjNDuxc0xgxALhlwuaE6gSa/u4YOYYMgzvGUPQ5rigG23TrqfWzRY79tg7BMgnOo581sZYYKY1VbbYq8NmEeC5rTDMEGbGue8ilu22OCsuyZzjrVc2q/rpNpthxzCqBRDNty5XMIVmuSmlDIG0ztMwN6mte0Kaufc9Br5zFyvL1Wx7uDp6aVNc8hwVrdp2ShZse03as9XDLkuyWbe6TdnFziHXADadnQZYKfzrJ3zldgkvrtacQK89yWKR0nb3oytOITK30oamXVF0yUVQ55iomQDOAFRZXK1bWUCUBw1xV6QOSPnpEueMcaMMWbkPAIgdL7D6ckJuq7D8fGRRCcxHJ0zsj73mYFxiFJyTEg5Y7PZIcaE3RiRkqQrSurNORnKPfvd1LrD8wl1iRzCkA+JzsTZVZchyPpMmJzbDswl9Xo2qHmRl6XcvBhecpIHAIwp4+bFcE9Ej5/8yZ/Eu971LvzIj/wI3vrWt+LWrVv45Cc/+ZLXcZHnJ/dM9Lhy/RXwjnD9xKMLDt3KI8URH7xzjmeGHXwv6UZw9Qz8wAO4+sQr4e6/H9uLWxh25+L1niMcBfQhgCHRDUIIWIUOMY3YbM+xGwac374DI1qILidvNueFqODIg0AIgHjJm8FW86GVF2EUgkdSoocIw1k4LC0/M5CZ5AWW0p4yakY3IovoAbATBSRmif5giSyIvL6YhYBiW0vXKJHM0PxvpouIt7/G8KtK5lz5wPTFllhy8mVIfrNx3Eouv620oVt1cC6U8INFoc3ygs5Z2i6MejWem/amSk5uni88SQ9hFGdTRvS1NtEmjOGqr7+5RtK+1Ki5d/NybBn1Vd8nyeFp5IayCaPZJqK0WNqCjNZ4mvVcZ3FIsipgTiI4iBbmZN4VxmcuQ0SkpwBKUCBItBBRhghU8vyxUwJQw3ogAM7q7mlyvVTcokZkzd8JSHSOpo2q2MsWmJAY8IUlrwq6RZ+Iqq5p5BJyoug5CRmDFDUajfWHdaOvw0Uk9yAAKWYhXdk8gLD329QmpQzSPJLKkpY9Y6v8SBSQnDS/YZDj1r2k85CjRvKwFWdEGVBzPmvYO2Fdl3ekcaycMIgDEYaUMJpObj3JEWBChpM+dEZukIK6cAzvPbogz5HOs6SeWp3Adx2Ck5yOWclvfSB0jkodM4AxRs3zyKikFqrPKV0OyZgyWRVNByXmtBsLZXc7B68rPepSkFRXABABStgNF9huN/oMDfjU0zfw8U89hbMrx3jw/qs4O72K17/qDH0XcHzSSR0SIaUR24vb2I2ELRHGmPCZTz2N3W7Exz/+Sey2A7bbUZTzFJE5Y9gNyKmSzogI5EjT2AA+TL1CbN9RpWq+beYssgkElCgmRaj+uReyR3uvA3vCPZluDA7tJA/kQF1kkUUWWWSRz4JwdvjQ+34/fuNnfm/5Lcd73uotssgiiyyyyCKLvGjSH53BEWHdCwbgvAPnhM8MA7YxiZc8CFivgOM1Vlev4fT6fVgdreGdRPFgzuiCg3eu4HDOOQQ1tsY4IKaEcTcUo5tAK4aTTGImK/apTor6WaEYNaYqdliwUdTzGmJFhW1ZnQoxPb/BO618w8QyG9ptGHJBvZr/Gg49tctOPlK9RzHyokAle0IEIb1AMUIwclJMOUptfHAzB0HDXeSjdYv4ZvHE0W9ybpESZxgVA6ZpJWcASsFezfA8a3s9kaedU+3VtdDmOCn2VsaKoSmRDyE4k1JKf5RfiaeYU8n7oaho67hmbYHhoPXnSvLABDu1vzxrZ0GguELHe53TOnBqOTS5QXPP2hV7fcYFS0R13OKsWLLZFqxtVva8oqXn5T65mTMz432tw7Q9WaN7NF2FsgoNcy6Omc3MLVXiulZZ70FWs2a9EZUU7fM5LOMpOHLKGWl+XFkkXBwXdYVrQc51EzKHV5uV8x3IezhSLJ1kznvFlAGLBANJp2TRf1p7Crc1QXHgbCZvsa9J0+uzz2LaEwALVl77SXDwlEbEGEGIADmcX2xx+2KDdd/h+HiFk36F+7oVvHeSXgsyTTJnxHGHlBIiCDkzLs43iDHh9u07SFGieGRmfS6x/hZLv0n6c0tvJGnYJwS3/eky6Ysi7byZr3d93tRlNkV9DyHDdtv9W++fOy+tXXvWkgVDXuTzWd797nfjB37gB/Dkk08CAK5fv47r16/f8/U/+qM/ih/8wR/EJz7xCZydneGd73wn3v3ud++d92/+zb/Bu971Lvzzf/7P8Q3f8A34tV/7NbzmNa8BAGy3Wzz66KP4yZ/8SXzt137ti9KuL1a5d6LHyRqeCEdHDsETQu+QPGF15QzrTUSiDjkmXH3kUVx/7GGcr0+wGwnDyBjHDEdOjJ/IYI5KGsjgHJAzIeekio/mUzRNqH0ZT95XNeIB56xKs7xcqWUWY6pk24FcGILGZDYFZ/q2LJE5aPqALooC9h/lJR3L5Ff1sC8hmrg5Iv+tbPBSUNkAlFqxpaxI2O228qNzKKG9GGL0haUYcY2Xf3sve7/VqB3WPmrq1758ir6JusmxX6RuXMZtotQCZQxL5I/L9fq6i4CmDLH+Y7s7S7QRbk8vDWpqVOtbt0nNXW1+6c+tv0dRClvt3ZR51P9ITadKgM0cqZZV8lDkkr2GQwgP2mqSeUmNom7jaISjel2zEZSL5DrrwVrpqljr36xRHzRYQ2l86U6ua8LydIreV4kc1i/mEcCTMZxpoISqnGmncLOZKUqrse5ZNjGTMW1Ywcb2NTKVEbOs3lY0o2EtEQByQtDwufSfzAtZP94pscz5OjYgJXgY8/r/z96/x1yXZXWh8G/Mudbe+7m8t6q3qrqq6aq+VosKAsJ3PIlAcxFoW9EQEjGt0EgiBIjRxCgSEy+oEQzGS0JA5NhCAI1EQMlHADFyOa1HD/IdBPo00LfqS93eem/PZe+91pxzfH+MMeZl7f289TbdRfVlje56n73Xnmve11xj/sZvjkEgx6qkk5LNSIsWRT9Kx4B0NBLUTWe1yakdKoIpP89Jw+CQrjeUpH/HJGuonbTo+iWcc7IGMmNMUVjmOqbDOCDEEcO4wTgOWHRL9B1htehx+fgAx4crrPoei75D5x1AjHE7IMSE8/WAcRhxenqCYdzi7tkZQojYbAnjELA+32IYR4xDRGIl1uXdIulGB1X8SWSgpBCokMcuf9EpU03de8ge7Z4uVpnrZ7ienfW6tauQ75a3u6+4x07joxCODjefegXIJVx57DmsLu0P5TLLLLPMMsunshDS2NfaziyzzDLLLLPM8jEQAuGQDyVUcyUMxoY2GOiljaf+iSjLvgMRoe/kJLtzhMgJZzfv4PTWHSwvX8Li8BCr40tYHR2Auh4hATEBUQ8AOQARcrQuswwMH+OUMTIjdFg8hoxmWuiL2i6qGJIZ+MyzQw3uGpIFy6f8lPE1y2YHD67wgAaBNBjuHn22D0PGFCeGoQ6KPdQZmh2zsQOzYuAJMQRN1/ocQIWl2c3ElKNeUG5wqWVL8ii1mlYo+7ymtj+bjw2Mws2/LcniIpGxNgyozjZj3VXVcl4XYsgXlVESTKvcEmy4FFhbhNnm2z4MuaqTGZ+n41vnX/c1U/bUnMu1LuFJXXOFy1zNhvU82k0Pln40bNWIMlUUEau69U/u92a82wfGcm8xv6q2dd/pIAoeXQ1qQxoqnh7a6BjWXnv+0Rw+3BnvFvivEijhw2l/5Q6WBC7j3HqDxHKB18Ojdjg5N8+8eAAZQ4Yuc5Eqm5X9nqq1rXkuqkOykz42e0JiIVPYNHHeg8jl+7LHaR3TmCJSiohJvGx45+GJ0HUeq0Un2LHz8EpgAYAYA1KCeFIKEcMwIKaA7TggJcYYICFbRvHqFGOxH+Q56BwuPXwd43aLlIQIIvYPwvrOHWxOznKvTK081WhfIJPFcs/n+tmsn5sWQ67uvYBZt/vMtRhyMzdnmeXjVM7OzvArv/Ir+ON//I/jySefxN27d/H5n//5+Gf/7J/h0UcfBQB88zd/MwDge77ne/be/7a3vQ0///M/jy/4gi/A7du38du//ds76b7/+78ff//v/3387M/+LP7AH/gD+BN/4k/gX//rf42//bf/NgDgx3/8x/HYY4/NJI/7kPsmejzxiiv6KYpRk4DoO1x91Wvhrj6GK+szOCR8+h/9I3j1E6/C//XO9+HDH3oeGAZwGHBptcRq2WOMA8ZhA6QIpIDRdwh+qXkT+q5Dd+lIvrIXFmAahBEYikINBiLHfB+AoqB3HuScMD9NrzKCAQiRGXGUl1ytQspLojAa5T2rpAlNHSEvycLgLJpMURGKMmtpkhnPLef65UsSPsJlF3ZFGGZeFuN+TBHrYYNxO+DunTsgEJarI/EssHBwJH9BspmSsXI5L3vxy0vUtUZOmIstVC8r0YCmDHZ7+dtYCIGHc7uYqXoRNsMk7bW7uWxEMmMZ1aal1tmSesnQkCoJZdMm1TRo2wgYTlvlG90w11y1UiYHVnaoA8DJoUycpJtI6ZuaDcIp5VGuDdSiN6pKmyQEjMttaV28sYX/0HnF6kwkRyRKZuRXiz11IPKA0/rovY4SOs0rJWNsVEUxiobP1iadk5VXDOmPasxAQKLM/i8eNKRPbIxYu8wcUlDWoG1wTGlDVmyJCJ70mUxKZ9KTGuJVAzmOru/aDZJXDyhhiOrSU1i+Tr11MCvzO9+Sct8zxJ0eyMN5xqHz+oBpp7NETe0oSJFuIXNT2V72jHjy4uEkjUhgZTC77CknRanDqIQYSgOIB4kZ6Rw8OSG1Zca4PmOM7IloHAUwcrYZTAGRE25tzxFiBMIIR8DV4wfQ9wuMwxYxBQzjgJgieiez/4Xbp7h7uoHrGOQZ1y55HK6O8ciD1/DYQw/AEWQsiMAUsN2MuHW2xtnZOZ5+5nmsN1vcvHWKMQRsh0EJZ9KbQb2sGJsfGurGkQM5yp5zfOfh2Feu/OqJlvLkcE7WLk7Ia/he1ZcnSrd9bpfW/EGn/k4mDemMZS41u6/7kSbpx15RHzdL/Np/fBOWh2v8b1/7H/HYH3z3x7yMWWaZZZZZZplllllmmWWWWXaFQHhlfCXSHjrlU/4pPOtnN9ZTuXJphRodIwLSMOCp//UuPP/U0/iDf+wLcOUVr8D1xz8Nly8dgxb/EyfnEet1xHaIWHQdOu8ROSLFoBv9hJgckvNaihhPl4tF/s7MSBwteRHFLS0dOFUePcTD8n7broYkTqna6dc4MO2kJ1RhjWniYcFup9pcuP+gIKb3lOTIh8maPFFhkobbMcYYkELEZrsBgdD5HuRIPQw4xdcKDFw8OFRFs6HGdSUUu6Xy3X4qGClV3hWgXjRQiAm5kAuO6VDzZ6cfioOICkPOWVeJ6/x3MjMM2XAgxcprYKnKyw5wFqcqVKU1DIsbWD3XdcejgPZL/sAytk5B1rYS5ZCcWTPs1KqzuqUcZkPyVQ8tLiO+mhtnTHnqwaLp9KrOnNsxwZAxETt8y9z+Wocfl0kgXn0w8bBr7anNAtlrh5RbvF7rCBi+r/iqc1XJikGCGCnU9Uf2vmLmjFw9KgdZsx2HCESM3sbA2QNH2p96GM9VbrFLFcW7OEFJapy9e5j9hDVsSsxeOQIIUaeXhKUiR2UuMzVzLOmhYFi7IF6REjM2cRR8NYlNb7U4gHNevDBzQkwRzEnwWgbOtwO2Q1CYlrFartB3DscHK1w6PJCnJE/7hBASxnHEOIw4OT3HGALW60G8zkcxdBiGbFh9JqXofCAQfNfjdf/75+LVn/fZEOKOrbKM3/ql/4r3/89fKw3Wdacdw3sc2rsAQ96LOdtSwru5TclLZfmbro73kI8Abp5llpdLbt26BWbGT/zET+Dnfu7n8OCDD+Kbvumb8Of+3J/Dz//8zwPYT/Cope97vPOd78RnfdZn4erVq/i8z/u85vfv+I7vwI/+6I/il37pl/CqV70KAPAN3/AN+JZv+Rb8rb/1t0BEePvb346v//qvf2ka+UkmH4E/3+pFnhVIB98v0C8ZlEYQJ/h+Ad8vwSAxDCcGlJEdYpJQBCgUi9bwrBeK9oCsEU9XXVVs6x/I6meqVu01oF64U1mW9y7ye9rOuc5F/eOqjFKHSpnNGbdKUmE+c6XUcX7RlxcVVWVCWZgscctSzO7D8ul4a7crfXCRkZSbVk+3FKqsV4pJ9YMYre1url5ydVnc/GlKaVTB5sW+T8oL29pIza9KWiG0ISmB3JfmXcI8UUy46yijNt20t/3DQBsmok5VNVxNxVkhzuVV/ZM3IReMT51pni0s9xXGazU/uLS3zoJQd0rWkKXfJvrK1IVeycU8Z1ygNFF5HqppV/Kodki2CbIe5bwhMgVVFGeLZ2lPtSm2pvzVc8mY2qSdxDbmXG5HRUoB6baNnOanZRnRQ/tH3HoCEo5JNv4yF2PTrkwiY0LNsUmJkUICk+abn20NBVStHeaFpfbmUeftrG88gZO48WMCRgUbxnEAUsoEj/VmjTGMOFj06NTDz6LzcB3gOsreP2KUcDkpBoQhIEEi/IzjiPXZBufna9w9PcN2O2K92SBEUd5tlPcRhqYzmnRDYq4AM5GMbM7W6e1ZlRMJu8/GdM2nvIG9IMmeGr341Wkc1Hvfq88xNVc+xkIIGyFEGvlplllmmWWWWWaZZZZZZplllpde5PiQ/K8WBuOAD3CcjjHQMHv2qMVwuhpdYkIKEWkMAJGE1db/5HfDugQjSa72gmqYEk8wCAOr9u3CuQKMLE2FJwio22BWQMF5OYNK6QL0oCpnAoZxznMPuEDTK1zwIQPWuFzbQUYsSy51zdi0lZshV0ZSj69kuFSNzeR76vLv1c6qEXuwnBZMadDlAnNWt+44BnlRMdxyXzV0jhChNubv1L2Cu3mnTci4ItFO4pysxbXrgsqXBkOeYMZ18rYLJh20c73Ob1o3fS5y9wvOyHv66J5FTgGxjNtNamrGAWuPzdl8O2f7QVt2i11rytIrUwh72vwWkEY5rLXzKE+aQ3lACu2H1ZiPasAmwDZZ3abPWsGZDacmdb/dYr67WGnxpmJ9K/i+hGep8OsaL6+7LAFyMFXxyDz3Lf/yLBjKTaSeOxhCCFFiiNiZRsSU0HuXD1F758SDtbNwTnI/McApaThyMfvFlBDGEeMohwNDiAhhlN+iHdLWdmb3RrtznQjoFwt0C+R3gU2/4wcfwLVXPor1yQk2Jyf5Hs5jsvMw7eS/V+6Z5MUXqH0Y8m7L2nWGJ+lnmeXjUY6PjwEAf+kv/SU88cQTAIC/83f+Dt7whjfg7OwMR0dH97z/6OgI//E//kd893d/N/7aX/tr+IzP+Ax8x3d8B77oi74IALBer/GP//E/xnd+53dmkgcAfPmXfzmGYcAv/MIv4A1veAN+4Rd+AT/4gz/4ErXyk0vum+hxvh1AIPSuE6Odl5Pai8USB8lhHbfgGBATMIwJKUQgRiACiA7bbUQcjT8tLw6GAzHBx4QYI8ahuJHLSoIp+ShmeDN6llcp1HOFuAYkdYflvOoY0dxX6UuTCMTyonaoDPOgSiGyxVpCLUTlmeaydINX9CeeKCYupwWzsnGBqJ4ZuHaJQSUMibCpPVzn4DsHjhE8BgRmbJkxhIj12QYE4PDwEM45eL/ICmgbC1C7MGmvq0LPUyV1ojBaxAfxCDJhMmueydiyauTMd5MlrUkTtYKo6ofFlqv1HatWtUEzV2YiLve1NEXGNOXynYYr0byUXipKRXGTRpV/uayMAeA0IlKCQwfAZYWJ8jhqKJWsr1mFVbHSTWZNCZL7k7h3sL4HZYcdVtmUdPPjWEggOYyKNNu8jMilqMQpNGOdu5pMaZx2rm8aQ+b+MpL0I4z5661HVJe3sU7NyFq/kTx86qaO5KSDtjdrPPbZYhYq2zwZc5mlzgs9UUC+z2NtmwNWWrY8u0763eUHR/JLLBtYMna6TR0C0OmzK94mOifrBbxXpdcoOTJf4DWOq3pz6TpZLodhLaGm2J4r8UQRgxA9Og94x0jbAcMwYrFaol/2IHQgeGFEOz1pkiDeO2IEI4E56vySPBfLTvo4ypz3vZc0KWAMDi9sRowh4uTuLThixEiICbhx8wWcr9e4dvUSjg5XOD48woNXjwGn3o5iRBjWOD9f4/T0DHfunuH5F24jRsYYImJiDKPERowxSB1D1HXOphVXY1Qku3FUOrqEkPIg8/qT52r1/NimhpNc9r3Mz1jT64yVT5kBXmdV2Pcy3+pTM1NPHlQxtu6ltreq+J60+pBzk6r8mWWWWWaZZZZZZplllllmmeWTVx5OD+N6uo4P+Q/haff0vBdUGWMUzJUUhyMCM8H7Dl3fwXn1AKoHAzmxxBVmAIkQwEgpqEFMgDE5YS+G3ZQYKRq2p4UaCGdQll4sJuAasxVEGFQwR2cefJlL2AsztGbUWP7NGIBhgxW+yizUkFwuAaTxiPOZrx2GQ8G26++ZbNJazCsYt5z0J0dysDElJGJEBmJihEGwvr7vISEkfM5kiiFL86UDzbMHW8X21rl4hJB8iufomnyTGu8a2CMvYlDNxuFcbIFk8+3a13lMOd9a29wLAq7IqeWVPRXL7CkWh4KCZrsAAHACEwt+Z3OiHiYri2rMnAqGbLOU0YZeaQ4zldlbGmvYJRVsqwbOKpzNfjT8cYd7YH2GKnn+ybX56QNRqtp6rC4kj/IMNkVZD1YHv3L/XzT8dj2HGK8OVhLBo+CnmqD6w6Usm8gEiEdhyuny4dG6UJL2Z9xbbQrWL1R1GJsfdtc1NgRLH2NQLx5UMHQipKjeR0jGkUNEjAm+8/CdB9jp3JKhKGehBfdGtkOVcfRKmiM1lDgv7SNOiImwhuK9240QP5LU4Xx9jmEccXCwxKLvsOgXOFgtAMg6LcSOgHEYMYwjNpsBZ+uNeqNmxY6T4vvF6zNPn3uaXKsW60zOsnmEaliJ8Wl/6A/g0d//JN7zX/9vvOd//Cq0J8phSsOVrT/AeZym622L7/LO8jZd6qZL70XyIqtYm+pe836WWT4O5OrVq3j88cf3/rarw+yXL/mSL8GXfMmXYBxHfM/3fA/+9J/+07h16xYA4ODgAP/pP/0nvPnNb8bly5fxNV/zNQBk7Xzb296Gt7/97XjjG9+IL//yL8cjjzzysWnUJ7ncN9EjqbGcki6ewZjWCY44v6gYohQ5klPnSddnTkKYYKhOYws+MyJR/l7rbM4WebXY0mShL0oWZ+O7KFvqzkyV0yRJYJEF2nJqHmeResGvf2/IqU36SosxTaV+UzRKecm99sIhsd4I3pv3iSQutGJEZN3IpJQVcQtTcT/7yKzzVZuBRrTOZhxlqzLXPSAJG2Ov3mteM5oSGeDq5dpGMituu0z3ql3pSW6809mF+SmNyVmokqiJYBQOactESa9p640yp+obiTJloUnyJqFW0vNmp+TeKuO14lAKyT1QJ52ujWR51ZXTjtANgPXdResq555HnnttfxaNwggOeQNhVOEq8+Kybqdx7T32ufhwQ9PPmoyqL5OsiuILQkMYIpu/dVlAHdcQeeRRcqVJX1M1ro4yCSvXJM8n2ayZZw+RlGMVGrEFmQyVZ0JW7OtNs232vRJHBNBIEncwacwefUCdtsl5mzj6zHsGJw/nO7jIiCFhHAISBTgkMDsklu7vO4mXWNHhMA4jxmhM6xHr9QZnZ+c4OT3H2flaCERBPC+FGPUxU/JS9sZU9WX1HJfnr6Tiaq6UUzH1D7WUZ9uY241Yd9u9VDY0Rv6SvCuFfuf5mK7DVBVL5R1C1e9t7arnomojaPK8zjLLLLPMMssss8wyyyyzzPLJLARChw4MxopXOOTDvHEMFDBg+JTdI2ZPpbbBJnHhb15i85Erw1hJD6eVDAo+yBluKYhEnT9nZEB+m+CkDeane31qvrLi2TWOVqNmLTrQwAwtrNDgWxl+qmUnwZ7O2xHeTUeU8SZyxfuEGYHNgF0bsfeROi6qR46MMQV/m3a0eLlVsza1ArgQt9ypRMaQ9/SblUEvgiFPEEa+YADL2FTYErcjTPswnr2wT8GMgeKtuEmR50j9Lz6COYAXnzf5MFWV2ObnRRgyNcn2FAZkkkf1fGXgFFU/VnaPxkZi5Uzw8lJt81ZdVaRObxiyALU7GHLJzw7v1v6gJ+lyQ+t85DBw/rFdhmoIuuDdVRXNFEAV9l0jiUZ8sBWmkJAqXB6GIbdz3+xrpT5GoCih6w0vFow7d2r9Rw5EcyHIMVJ+XmzYvBcbkxGRAEJKETGoV6CYMI4B4zhiq2FahJ+nRCKztdm6YKSbegAuWAx2PDWjnRfEhG6xRLdY4PCBa7j88EO5/8bNFsP5eWN4LgSYnFu7mDGa8bcLUz7dpJbYuyDk9fkCDHmyLnFz7yyzfHzLX/yLfxH//J//c3zFV3wFHnjgAfzdv/t38SVf8iXZ28e95Nlnn8U73vEOfOmXfimOj49x+fLlfIja5A//4T+Mn/mZn8FXfMVXIMaIt771rQCAv/AX/gI+67M+Cw8//DC++7u/+yVp2yej3DfRI4wbMAOna0KMjGHYInFC16sXDTCM/sqI6DuPw9USQzzDOAp7OCYWbxGpvJjyq61S2uVFZi8pB9eraw51QJCifHBGLq08BjAgHiySeHoQUoK8ZuXEfMrvFTWtZhE+t8RfFJWgvBgIJQZkZk/CuMqc2cl5bS/HyzVd+5LR4BnwzsE7B9f1oK7D0hGWHtiGIDHRtgPOz9ZSN33XrlYaf1LLSOo9wZkLA3bN+8J01Wwy56J4mLIPMiJMeR0mZqQQGoUms0lV0ypsYDUGm5HVXFKwMptVkalDf0g3yTXPLvNiEjN8VuQSOBYHF9YgM4Lbho+gYS24tMzDI0HicwKUiTEgr2NWM2AJDgsQCN2ih/MelKIoe45kbhtTCKb3JCSKSAni74Vddl5RNOmk/SsMY++kzjEUF2RZT6w3Aw3lW0YvK8o6cfcptkKoSkoEMv3eAZxA5rHDbjQ2sldCA6sHC43dmAJPlHNhGZPzwuiN6vqlUmPzRpN8Vvhk7up1L6MfVYEWQg3DRX1K1dWJc9oxSV14UlLlXhnR4whOCc4RHLx4wXEOxEJsSEjiPcceSJbnJCvlZFOznN6IuZ0J8mTLaYfOyTwJ4xYpBaw3Z4gpYtn3cM7Ds8wr3/dSD83PLxdY9D0cMYCA7RgxDBHLRYcD6rEdIs7WA4gDHG/Q+R798gDee/SLHo4ATzJJku4sHIQtjcUBYvI4ubvG+dk5nBMvJn2X4B3wwNXLWPRLdCRElRiA03GLDz79LJ59/gWMQ8A4RsSUhGwSo7LMkdfNmFKzLcrELFOFbaealfdqYwbdWtXKus5vI6e185dhQThjZKQ02ozL41Pi51YbyXruVzvlckqnbMxqktiEvrfzLDX57v3lojtmmWWWWWaZZZZZZplllllm+VSTh9JDuJau5e/Pu+fxAf+Bl7FGL6+kKB6bh1H25DEGbM/XiGFQbMoOi8ipbOecHlYp3jNyGBfFHUoYlyLl4IlBDgRS76wZm0iGYaD5m5NoIYZRGtZgx7rq82at72JqzvfVyELt+6H23FDK5YyRVA0p8AlNDZUizgge6q3VE9AREFLCGCNiiBjHgCpndJ1v+0Px7GJwdk0ZNVrSwDkofTxNJ/nW5J4KG538WwM4Of+JAbi0vg0fXXCp0sPZGA8gh4ZvclOTttXb0tuhN5Y0jgxjFg8NmUCT7yvzQeabeEMW7zROvEfb9Ml4Wek48/8s2VBJa61hFg8hGfQqdgCFrzPpoFSr6exSVmnYbpTyWhI30b6lodrjZuewAbBOtvAkmehR989EyGwO1GDqNfZNEK8o9vyVQ5rQg7+coWciIyZUdctlQOtE6mmlzJKUpAPlmsuH64jNu7McTq4xZJvLCWRNbs53lW61+8SzhLYEKYon6DGMYE7wzuvvUq7ryqFlACDvNY2sNCFJuO3OO3TkNJR2BJAER3Ye3neyDnhXzQmoDcYeNQZSB2bCsBGihtjRGN5JHQ4OlvCuM7gciYFhCLh7cobT83Mk9fycCR1m07Mh1etl9bahrtfE5odqvu35Xs3FmmjDTHjl7/99ePh1r863feh/vRO//cv/tZ07qDDkXET1kGSsOk/uPOcyf7Cq+xRDRvXL5NGbMeRZftdy5XCB3juM8V6L9kcvvXe4cri4r7Tf9m3fhps3b+IP/aE/BAD4oi/6IvzQD/1Q/v2bvumbAADf+73fu3NvSgn/9J/+U3z91389Ukp48skn8WM/9mPFO5LKZ3/2Z+Pnfu7n8GVf9mUIIeDrvu7r8NrXvhaf+7mfi9/4jd/AW97ylt9tUz/l5P6JHiGCEzCOYogbxkEMtJ2DJ18tvCxGZUI27hbFWMkXlTcPvaMoQJWOm8BwnMBweQFWtUrz1Jd3Vpi5UsqMVVj0J2OTWHlTpRRUQqjUVUL1qigvh2rB5zq9ppis4eWlUBsnM4cdpvJFTgiREUJAGEOOl0aV8bKEMgFaPWpi+MyXKLe9rg9N7sn5TXcTk2t58zTdHFWfivJf9VtWeEvbU9UmUbJyEmR2adV25LIlRS4if5cBF2Ny5RZt8iJGdd2UY1KlrHH71mrek41Z9b3RHtox3u1QVANX8m6yr7/ki81Ea9NzNf+YqzlPDblGFPR6FyQJ8waBprWVO0kV5dJfKNf2NC+3zMZBFSxHpE7tuJRlCjmVeQCqM8kVbzLnSmm3+titOrJSdyJxm9nMm1KOeaipN0L1PLQ1ZbNdY4wjztdrRE7onJewLXpXShFII6LtwPxCPG9QggPgnXjqyN46iMTjBgvJxsYmpYQQAoiASNpbVg4LWY4hJLjFokcMCxAJUMJpixCj3O8cQmQgAWMihAScnp7j9PQcY0gIY8xKegts6EaAW8W2XjMbmW7mps9IPUKT+dXcWinZrHOUpnNLN8vlpE5Vr3qKTDcMe+sNm/4710o+7cmOC7OjnQ+zzDLLLLPMMssss8wyyyyzfAqIefboKoh1hRUOcIDAASPGT7mtYtIwLEkP+8UYNWSt4XFVYi5ePjI+yvknwSoaXCwDXsiYIxvm1YLLBQmdbvYt/yqFwdSkiOkELJhSLxpMsPk4xQEnGHLzd4IhV0m5uB9opMaQDTtPKSHFJEbYbKA31NdAvIu9ApfMrX+nGHJdk7bfG/yOdxIX7HkvTsPNb3UkkjpNPmhEALPOlKqvSo8XDJmritTzrYaIcw8ZJloA0knXGwhrXhPKjKV2Mk9u3D+GOf8dDPkC4ckE2QHLJkXezzUo1NW4MSiebdqbqfzNTdoBkMt4kGHIE7lHtQ191gwKJgs7XJx/kjlAJd1uvnuedbu5SkNVs+pRsLrXhK3aTsD5GSmZNzYSZoQ4IqWIcRzBYLieQOQFwyTBmVHhrxZqW9otnjxSRViR5pqtQ2vGkAOfZOQtG5yySsj/pf6+c0gsobWlnhKyO6UEUIQ5m44chewxSkjy4gkE4GZxbtfBKYbc9D9NftjBg3en6b5p3q2W6FbL/P3w6hUcPXBNPHucnU8yAKqpswdD3p2jFz+D+37U56XBkOnC9uzKp5hiMMs95eErB/g/vuVNuHM+vKTlXDlc4OErB/eV1nuP7/7u777Qq8Y+gofJo48+iv/yX/7L3t/e9KY34fbt2/n7Z37mZ+KZZ55p0rz61a/G53zO5+x4AZnlYrnvnrp9aw3AlPWEGMQFIbsDcCcMQnAEYgTGAFKlniW5uo5L+QUjL2JVqabMXSdeHUIcQZFAMQJE2agaU2yVoeKiQF7/lVJLWmdx7a+mXxb/EKIYSp4JEiqmCiFYKcPCuGRLmV8S5UUb9R45Fc8NH5oBqTuV9I7s/DohMIAQQDHgfBiw3W6FGZkiHDksvVcFfvclWlxzmfG6vNhrXVtuqbcRRVJmybfbklJ3jUVH5nmCMou2ecnrfRLzsZcRUWbsGITp6atwM6KcdShKNTJjHzAms+VR1Yr1ZsnAnIaoquXgfWk9OcLK9QDE1VhMbM414LtFJnVYOaRjzIkRxhEpBjgvHj6MnGTx3yJLzEsCS7RQZnDUOVLtToyNTdZXXAIGZYVNFetyEkDmKGuopGaXW00AY8sykPvNtJaU6l1Wnq1AJmZpkL+os9dZ68umJm/IgEKAYYASAE8aAxTiDsNV5xeSNK7L9OQyGwlJmO6g8lx04iWk62SeiQLJ4jGHIV56ACTE0iLb6KGMtzHkQUBnGy7HADygvGqAxWOL90jMGMZtHiciiWEo1YoAE8aQsB02eM+H3oOzzRnW6xFEDr/viddhcbwE+w5MDqebU8Q0Yn1+F+N2g4ceeRxXrz2C3nl0jnGwWiDpSuKYsew9jg9XSCkgxhFjCFivNxjHiLPzEQkJyelJjNSDGRhChPceDz1wFYu+wxuefBxgxjgKMez9738f7ty9i+dufRDbccC4ZqQRiEk8FQ0hYAwhe0eSD6mZVvUzvTd2on1rTryUMyCcdDs9ZXXkLHialf2U5wggpC8bdWaNb6msT5fjc2pydd6StOy8VPBu7vJ1d9PX1LF5D9j97YbwflT2WWaZZZZZZplllllmmWWWWT715Fq6huN0jBfcC3jKP/VyV+f3XDabAMG0AMPjmANABHaKA8kmXv7jao+vuEE2gNJ0L14+E8xoygicQBFA9uChu/kL2Q27Rjaz/TGnYsCvSQ+KQ8nBo304ARqjcWMErMswpCGHdcg3lJZVHhPM+AtWE22UfhuNQMMCwBPkQBEwJXW0fdJ8bggltA/Gab8bZrvb8gqutbprnjWs2dxn6cTriODbjKhuncXjMOXfWAHgGkMu9TQM2bUElHoOGZSTMeSCT1ufdPmgVapGmOFc14TtKH0p8zTGpPPGqY2kRbkstIWNPjNKrPma4WJ9Zn1lNo58b8GjrITiBUdTTozxU+H2nyppybfMBGedU8BnBswrAtd9W4l5ZAYUQzbPzfY4Ue66PAVLmBJqE2lCO7zn1PWE/c1ee2owkIUElVtVw3jqmqPuRWf3OtY2t8+KhT0P0bxlSx75rCgxwOKFOcaAW3dvYYgDxlHWkutXHsBq0eX1bwgDEieEcYsYA46OrmB1cAQHgnNAx1C/4zK+3ndY9KRrRoeYkh4QZoxB1gB26gmAfa4LOYejgxW8Izzw4BW1Fwgx7Pad29hstzi7cxchRaTRPPFLW2NKmbSX+8oOBlb9WcJo1TOAyxBWt5Y+1cuJ2wuTLPZ8LBcIePh1r8GVRx/BM+/6HfzWL/1XcIrFtqK2LKrfL4RmTa4x5FLI/WLINalMy9x5L8wyy/3Lw1cO7puE8cks7373u/FjP/Zj+JVf+ZWXuyqfUPIRefQAAOYIYVOLoVakLGBy4jw1Mbpi0pAplXUvv66rhb5dBu2lDCAJg1FetsgGxqrQ/LFxlceT9MygyYujec+rIlwIHrvmvVJPeyO1XZC9jTSq166I3kZ588LaR4PGOiMW8gD5ilnMF6nSeyq5p2SCKcGtQjNNWY1m84KyalCdsBo8S1V7yigbEkuj3gzse0UCIJL9HUGUMaryaN685RbI5pCLobpRw0XM/V5KMoe9ZVLrEpVR2uYKV/+lxKhnSlZuE4PJPIlw7s12I6eTvNJPp/3cVLjq7+lo84t8LppypUCbip5JF5KOUCnkk+rmvGp9vSLX5J2QK2XkMa7aVzaOOvZVJ083U0VxLl53pm1vN+iVAo/dy1Jfi2dIEKJHxeknqrwLNSp81WYpM6aEs/M1Ts7OsN1GOOcxjgExJVmWCBoGJSCEAWPYYhy3GMYtfN/B+Q7klNiioaWICJ4cYvJgJGAMGLYDtkPE+flWwtX0kq5jD4YQGZyTvvYEdL0QqoIq9WNIGIaAs/UG680G45oRBmkIc+0RqZobLOtV7sZaUd+dFO2Vei2uiWjAZAyrlZRL3vZY767KVTn58ZjsCFjnzw5JalJjmzw7MR/LulM3avrotl/sGWqfuAtumGWWWWaZZZZZZplllllmmeVTUMzDx4pXWGGFwAEBYbqB/KSVlMzgaCDY/r3yDv4GC429izXknfi+rARIrDwU1IjbBLjd+a7fDCqpsOSptwbxbFvnwtngu7dxLzLeu4jsnnsLiJU9DdghspgSQozZGAzFW3fMj9M60qSMC7GMthEXdX35PMGQ8eJTviaFZFIH6pAi1UHGhqgCFO+rdpiz+q0BNNsKl3bsDhIp7plDtNd52dSq55fhTRX22x6IFI/kAPRQXCk7z8Qd+G2KE6NNYNXm3BH7m6M/TfHlnQSWT25L05F5DPbauydYdms3qDBk+2EC6zbFNVnJrJb+s2/VfRWGfKHUWHxN3KpP504marFilLllbcmkhGYhmmDIEFLPEAK2w4gYhfxjHnesuKS2tZSiHABM4tWdvAPBCbHJwE6WejlHSExISUK0xxgRImMcgqwN3tBvC4WDbBvLh3ihB6LB2dvSEAJCCIgji1eP3Pa6L+0fsYNcaLCo76SdK9Wcr9LcC0rlKR7c/u0PVugPVji6dhUHVy5h3AwY1uu9WdmjUs/jCzHk3bsvqB7XXyYfbB5djCF/iqgEs8xy3/KN3/iN+JEf+RF827d9G97whje83NX5hJKPgOixBgMIUQyC3jGcE+M5pagnrwnDyFhvErbbiO0QcL4dsN5u9UVTv4hF5MVDlRkWQCQQOXR+CQYkFAKgTHDA/GWUtb2ET9gnZugvRmdXKf5yt9tzX9ab2E6Wc7NGS90jbMtBROhcB6B43/BZYTUjt1PlU16OMY4IMWC72WK7GSSdk7AMzku8PwkFUSsaCeTUxs5KVq+UvJjMZZd1kNZhYhCv/WQwhDGalTB7kRIgtAspIG8VjFmu/Uudl1+1X0J+YWsfe9ZNUj2GxR+FsLQlfdKNkpVpgUfME0t+K1Pm26pjClWonbDYHWnIHw1fIrHsGEAvylGUTXbn5Ts8lfZDx4A6idmXIAqTBzgmjU2nVUkRoRqj4imGc99xNMUMOW8AQhQBJIZotVkgFnduzrKBkG6SKnqcEigxLMaI03bKva6aLq54LdHYhkhRB85LfTrbvOhzZBNKPXTkZ0PZ10Y+SrCxJZDXkWKAnUOCudEzRr1NBwLYFwJQVvalzBRNaWadJzbHTEkN+mxpf+kctplh8UpB0JiM8nRLaT6PCeDAUYrtyOdHiwgaZVPHBATXAbwh3Hxmg9t3zsAc0XUOLzx8E8EFXDq+hkW/BKGHdw7L1QZdn3Dj9vP40I0bePwVn4ZHH3oERAyigMSMxBFITpX6hBgTTk43eOoDz2MIAZthxGLZ48HrV7Dsl7hy6So679F3QlzpnAMnxq1bp1hvt3jfe9+Pk5NT3Llziu12wGazQQgjttuIEBMWi4W4uqpdd0A8LaUUcz9l2VlML9J0qfKTUlI22eh8ymcXqipkl5ANeaLs8myOWPo4BiGKmYchkGwwEus0agmFOddcKW43eFOi0x4N+177jf0pZzV9lllmmWWWWWaZZZZZZpllFuAKX8Ebwxtxm27jKf/UvY2Sn0SSUtC/htW0h6kMxpTT6BIiPMaEMUQMMQrUVeFItf3MEANCMdiJEVSOddkp/gIxULNNvxBDbnCr8r2AElqWQViT+7LwJO8K7uDKuJlxSwOeATRkhcrYbPgXpyReAEJADFFSKXBiOGPKFahMmK76VsOqQHWivm0Q7fRQ22iqB8lAG8Ppcv6GIZc7nR4aq0McZNSZLG/Jh6rymi61bqrwolwPq1LtiUVvaqChDA8lwX2p/S1FxVwhXpFjFKzdOZfPwTXtr8YgkxccBPetDkmJF9w0aVdVOHHxlGu/VeUwoPguKte6Wq5hyDa2oEx+kjpNJ24OjJIBOEKNT3MxOhgG7+r7keeu4LD1NNLaG0ZrmHU1FyX6uiv32fNcQXbMhulW3aSdkeduuQJD5mVucMb423RVdloYW9iNXJormCUInGxIqSxATXeU9gGE9cmIzXYAs9g8zo/WSC5hsVjBuw4EDxDBdx2cZ5xvznFyfo4rx5dxfHis2Wu4FGOxqX0jJcYwBNy5c46onn26zuPgcInOd1guVnCOspnD7GKbzYAxBNy+fQfbrdihLPx3ShExCMHJOw/nK6802oW2fufFt5q2rVyEIV9wyw6Q3L4pm7Q2P/Kwyq/XX/0qfO6DfxLPv+d9eNcv/lekGJFiKgeIdWSZbN5VOU+r2iyW2MWO7yH384aXqn9q6AKzzPKRyvd93/fh+77v+17uanxCyn0TPWISQkNMDjkWGusin82sGnsxFeZrYiAmLoZeUHYC0ChjBMCRvjAlvEfvvOgTydzQ1QtwpQRXWWSPCtW/wJ41ufIkcfGLqSgJZRtSVzgHilAFlatyJ15E2JQGvZ4SEixOpTAnQwjw3sOTr5S5UmR+j1XaZ81gbvunriY3L83CRta2mdFdDfnCp0hZyXrR15m+NIs61Bpa818yrwFcNUZfblmj59yEmoQv30255GrIODfd3B0am7r4VSldU+pUx1FjVZaqTlbNgYwkwNK2eo6ZWNm5opUO3jQGjQqd619x0y9UhUrXmEKpmgmVcawVraJYl3yNxNLoQrXCU1vUIQSbrFzX/7pyrTiIIa0Ot3laVdF8UGJBPS91DOo+A1BTu6snNj/lO2Ohu60mLmH1rDfrQsWKtrq064Tc55yQR8YxYthGEMSr0fl6g27ZY7U8FiU9s/0dyHmMYcB6PWKzXWMYBnjv4L1D4qjkjogYdQ1NjBgiYkw5bI01v9Re1kDmhO0wKDnkDOfrLW7fvouTk1Os1wNCiAhjQoyyHpt3pez2tH4YqpMqeT2ZSjO1q/UvZ0NtokneQCG+mY+gvA7spK0K3amMun0ltJtA6fSyznE1S6ollEBlQ4Lq5p31/6KnEM18bOK7TN4Lu85OZ5lllllmmWWWWWaZZZZZZvlUkx49eu6xxRYLLJDsIBv4k9rDBycxUCY9hZQR1Ynx3aDe2utng69Vm/pmC15hzIZBeTuGoiE3WiPdFENufV4UaKrC2mqMsAEgcOG4tRjfPlyhwpANy+OmR2B4C1OFMTMjgSXkgh0YSglOQ0tPishV5Em2bboWx2xxuP1NNQwZKLhfg+/cL4ZcoXM7vZSz0kObKB4EjACyr5QMKxv2M8XwbQ5laIzz1GA9tdj05Q4e2uJeBcau6kMkHl6qLMoYlHTF067OF1clrKEy6NNTs1BwQf5N31WS53AZ6PKxnYfFrU2Vyf6iS99VBZVbuKQvXdOm1fIyXqyFNBhyrj9N5uUEQ75gTrT9MxlDQraHNM933UbOvVPhlvV6gskAlD6IiREDw9y4jGOA8w6dX8BRCVcl5ANCShHjqCSuGOUgo9NQLRDcOCmgyqx4Lxe81epbmmB4r4SbYWZshwHjGLDZbLDdDghjlHyi4K21Z6WMIVdztczRySTdIzsjsn85rBff/Ld+pPauYc2zIj/0qxUWByuc37mL5fEhkkYmSDEhDkNbgXzI92K5EBn+XWPIu1nYDzPpY5ZZZvlYyH0TPU7XwsY2o+kYCd55HKaELiUMLK+ulAJSHLE46HB49QDbocew8fBESvYonhxq8ofvOywOV+g6j+VqCU8evfeIibHeDkgxYtxsEEPE2WatRJJG48bU6LsrrQJPk+tWl/aNYZ/FxVZUjwMWN47Ve0Yibjct+jc07jZKqeM4KmNSXtbeEQ4OVkXZNRYwaqXD6tcqOK7SlgjFWFuzZDWh5KCGa1YmqHdOPSFI1hERiVlZyrJpEO8hrUan+gUYQlgBT5XJorqLExXGJiYwA73j7H2BiOCUWJJUmQjqNaPvPPrOyUYGCQQHZ77ItL9TkrItP6ebPNnwiYboiLBa9tJ7yr6GpvfmTcSVecQQLxJi5C/KW3YqgpgHRU4NOGG/phGyvTROb+srZhojNKnC5+A1HmCEhRAq3CYGko6xS4CriR026lbzXBKMfMQI6q5Nf7JNTVKfHBpP0Nj44sminoN6j7qPSbo5IrBuo11RfPUGp84ziF1V6ES5qZV888hg/WWbfGN+m9tPJXJ4memITjzAdF7GkclJg5BASJped0wclIRhy17VjyTeU2ROO4AdEBnkCF1H6HsCLR2wIHAghJDw1HufRr+4gSdfn3D16mVd2RgyU3ssXER3EHH79jO4c+d5PHj1YVx/4BUa1mWDk7NzvHD7Dhb9CscHl+Gdw+tf+4TkkIT4dXZ+ivXpGjeeeRrjGHByd63Xt4gxYYiilG+3WyGIsCnEDuSBBTn0tifUCVXPEfW3kudyM1dhoaVSvmYb2VyO3VkNbbOJ1XnTbr4m+zWUp6l+WqQMSWEEDdvoM8dqOhCcd/kzwMgHUrICXhbFvA+o6t1euB8FezedPat1HNJZZplllllmmWWWWWaZZZZZZrnEl/BkeDJ/P6VTPOWfQkR8GWv10skQKgwHQAQhRADMcIYVAGLETBG+d+hXPbrOK3nBtuuKYxJXZ3jEy6fvOzm13nVweo2ZMcYoRtEQkFLCGALKkacMaO3BkCdocQtwFqPuFD5pDpQUDFhCI0yyqg5Fgrhgfnavfc8YhtQ5RiF3sAKxRIS+64pZuSJf5LKaPizllENeco1omt6+l7ylFoIxZk+6eo+Repow3pZ+2lUwqChdjCFTRqMQFIN1ZD6FtUX5oJ+F+4F6TnDwznBdrjB1yoUbHkuKMdm8qr1GEIDOsNHm0BrK3DR8N/ejy/hYORyLMqaZrEIgeLDi3ACJV+eaZDEZgnJ4kLVn7YCoHU6tyiPF0up5SZA5ZaAeldwsQSG9qJfwAgUCXMIGWR/kvpoQfyy91bt+Ipp+K926i90h33TBMwclQk3wN+u+mpRAcoSTrQsoO6xGHnyosb06KAjFlAvGp+3nUmcbjXxAlADygPfiDRseQCKkxLhz6wTOO1x/kLFaLfP4SR4eHoxVz9hsTrHZnuFwdYTDg2PEFJGihIFZbzfwrhOv0kR44NoV7WNZH4ZxQBg2uHl6ghQTtlvx1DGMsiZGFtzYwn+XOSOguCeqEOJ6fdQRLK4wdsfILlUEioIhT2+YjFcuzt4Nk3K0c60oi4DUrm9SzrVXPorP/lN/XA8DE+488xze9QvvQNhuAfXaInYQyvWtpopeo/w9h89pi5r0TS11h9DkWvmt/FvPuVlmmWWW3718BB497IVuyokaT1MC1YbAxOAU4TyhW3bo+g6d79DpaXZSc54D4CuyQrdYYHF4gL7vsFqt4IjgyYkLKU6IIyE5D3Z6j74AmKZvFJTvVGIn7rfdtXntvp20DP0idm7th0mmJY295pWlz5XxVe9kAGMQogeSvEC88/AWzmOiqOc7a23dvrN+Fw0XtgGSq8XdXb4vkytKXiVOm6RzqvhYiISs+6C87KwWeTsycZeGZlzK6ytqX3iuvXJI3UkZ6qKkF2Zq+W+3D7RSWqRu/lC5dauSu4api+ypwf6zhJnRr9qrUyIEx9JONgU56ygEG9uGU1wr6JPNYvEGUwlriBYu99ZKkinxVr8y3es0tvExvcjq3CpKxKzk7YnyVM8TqzkBHG3zBhR3eLWUeUu2CapC/OT9Tf5eZkBWxKe6DdV3a57130pXco6QytZhpwSX3WPY7qWUQTl9FVaKpY8ciZK+WPZYrBYI5xtwZJyfbeA2A87Pz7Fa9ei9E2ABBPFKJGve2WaN882ARX+Io8MtUhwQ4ojNdoOz81OERULnljhYLnFwsJDaJo/NFrh7d8Sw2eDunTvYbAfcunmGYQw4PdsgxpRPUnjnmnnM1kOOKq81RkazZk8VT/uNq17eXTqnpGfee5EzANH+UnLcVWN5kk2lAHN72qZdCxiNH9KpUDvfqB77RsGelLrbPZNaoZlGu6l+95I4YRu2WI9rLPwCXl3QzjLLLLPMMssss8wyyyyzzPKJJ+bZw4TB6NEDLIetPtnsPIJpJcRhBAD4xULw1HKiSUTxPiKC6wRTcXYYzbX4T91Fznv4voP3Dp3vMh6S1HtyUrw4Y32KTYmDkSnuq0JoMWTD06i6SJMENZRcYX2GFXCFVzaF7Yx3hdtVfzMxJIkh1/KVw5R7AbQ9+Ssiopbp5tykfSDt5RpDVgDQsDfBGGsMlUs3ZDy69uowgdsx/WGKp7S4vGCInKFCObCoY1D1k/VzxqAqDKwx3E/AHqoGbh+GnD1zZKjTSCy0Z/zsPp2rpKhpKm1pMWTN2L5nzL3tprZ3am8wdr9mugNz7SJVDb9n2li7pYbaUWPI5gVkf1prRN20ggfeCwes09c5tFjdPgyZduowyUw/78xH+0406Y/KKzjMy0I11nswwik+KM+ZdJPvHHznkUY5fDkOAeQI4zii8z7bJLQysAOrYxgxhgjvevR9BKeIlCJCDBjGAZ1jOOokvPdCsELmhBADeJsQQ8B2s0GIEevzETFFDENsCA2uImU1bSGqvL1Mx2D/7Lnosk2S1qQxWWOmefBFM2Wf32SzJVhySdGvDnD10VVuVEoJ/cEKzIw4DmAkEHx+nvYi3/l5rJHo3amwe/fkZYB9ft1nmWWWWV4auW+ihzP1mspLDxzh0ggXWbyMESGEAZvtFt3C46g/AI1XcdQTrl69isuXr6DvOvR9LyFKei+x6mIU7wFdp2zugPXmHM/efA7rzQbPv3BHYg8q4zAlc6twgYqgjF7QrrLGO5/aBbihH+SyTB+r1AONJ5j9k6jClMiU0AhA4pqBgfVmwBiiEj+Eidw5D9epmz1mxJSEAUxVP7M6O3CAL5RTKTt7IMi1krHKLEepddTQN44qRZgtrmDNTjXl38F3UN8ZTkLMpJRLaN7JNhZWB41Fx/oy34ZR90KiFPYQckFHYkBPLO7BRiNygEHE8F48eQBJ66/FEINdUn1dChWPGqIsNO1hUo+LshkYg8VTlHqW9ncyksZCLlxfMDN8t0Tf99hutkhhzBuuhLKRgI5K75aN3tu4gSQtHFZdgtd+S9BwRzHp/LXxr5VTykxyyteMpe5Kn+Rdm6lCDsZmr2exhOdRLxg22YA2fiPEWwKI4DuXFT+AMhnFk8T9Y+cAR8Lm5wTnCd45cDKXcvJsG7EcXPnPYalZtKCHkHHz5HXKiycGtjBOpjCmBHCCY1mDJFWq2luz/kuKZlXQ6ZuMzKb3RQ4AO4A8Dg6W+JzP+H04OT3Db/yvd+HunRPZaIeE93/waTxz4wU8/mmP4uqVS/Dk9STJEkCHm3dP8PTNG7h1MuDZ52/g6qVjPHj1KjowrhweghOwPn0Bw5qwPvMIKWG9DdisBzz33G0Mw4jzs43EXQwJKTHIefjKc4T1SB77DKC0qrhdzhv1fP90e5Macloppfy5H2k9vVTrR86n+BSpG2PbCVLAICkxzGVwRLe36raINbSYjaEQ1wgG4DBcCS3EQH0wwep0b3pLSSd/J6QU2vnwUcn5eI6ffffP4urqKt706jfhoaOHPib5zjLLLLPMMssss8wyyyyzzPLyyyEf4nXhdTinc3zAf0DCuHwSCQEYzjf4rV96B8bNgCc//49geXQE4gTiCDuiYwZM5wn9ssPB4QrHRwdYrQ6wXC7FQ4P3+SBaTQyBc4pNJ4xhwNn5OcYUcHa+EawoTTwvT/frGRbmYn/MgJTdMkVNuM3ArOeKNRQMr/WWYCCM4VOs34vfCQPYpI2C/WhYX83TyC9GdEh6ICaTMYAGpxCnzgUbJKrsrFVTzBOFYYZ60D8fHMyYc8bYDfRUzIXtkCBVKKVhU1W3Z/Cvwiwzfippg2LwhiE7TerIegviaRiGbbH+rn2jOC5r/fIoVBgykSv1qu0GVTuZuRx4tfpQi+c2cyX3P8N3Hs55xBBQAjNXM6caJOd8xth3DrIaY8DwL1DTlQw1GFR9XZukGw8lXLLk3P+tCRrVnXtqjYw1Kj5r4avlsJt44GbrX+0jZ7+jDH/2Gq74dn6mnZCXmM1uIdisFZvnU10zAzjzPLEx0jLV20w9PoY1lhGs0fsaxSRUE7TueICQPc3bs5OQ1HYm3nYefeQhDMOA5569ge1mQCTxqnH7zglOzs5x9fIl9exhh1XFtnG+3eJ0fY71EHF2fo7VYoGD1QoOjFXXgwGMwzkiEcJISLpehBBxdrZBjBHjEOQAbbJDs+06kacMVxcmS1s9Zrk7JjOivqFJazfUC8B9YMnt7VLBF+XI7VQUmRBGDFy6/gA+8y1/DKfP38Bv/9J/w7DZIHuuzgS1NvN8aDWfoG0r37as/r39W1DmiwgeHxsMeZZZZpkF+AiIHgAqrwdAXrxSlEWPxbAWU0KMAa53WDoPHK7Qp4ArV67ggQcewGKxwHLRi2u9vgdSAo9i/E0ghDhi2KwR4oCYAoYwYrPdIoYIZ0ocePq6uEDqFJU6ZESQ3K4pw05Tqv5p73FRBmrqiDoJy8ohMCH85k+JGSkmJJbQHJ2y1L0ThVjc8Bnzk/JL2HTgrLzbizgziSWqR61mtrSNVuz+zAO29lQvcSNLOBbjqOiO6t6KqPQqF5KHEaVrRVJ4C5LGc6mf1bGZTVqG082RJyEJJCXbZKWuGVtrw647vaom+bWaY9cRwSWU++1eTax6Zp4+RA7OexA5zaPan+T6aFgZMzxrHXPMx3o0yMoxlbKae83phmoWUfmQ5whk80FKDKGsfHDTA0KsSHnDlMspOxsdL6mr0010Z2Smrgep+0Npij3rkk3nCtGDvQPHiBQjvCN0nUNKQIws4Uh0nsdU6kG5xjovudTdq5cMkxiV3EEKC0Rpm/fiEUcIO07CSLFs9oQcICQPECE50jLKhrV5xrVfZGORQOTReYfrD1zDwWqJdy8XOHMOAeJ54eT0HOfbDR66/gCOj48kvE41y8fAON8O8DgFYkDvCdcuHYMALLsewzBgO24wjoztVsgcp+uAzWbA7TunGMeIYTuqa89qHlRfo05Ka0O9cdyjq0++1K4eJ6mb567M4Zyq3mXmS1z1Z3vf/u+7T/a0rGl5+QBOte+yh5Jhbhhb7yx1aWVzawlaUuC+Gk9r2Mo0xX3sYO4hIQU8d/Yc1mGNbdx+VHnNMssss8wyyyz3J2HoMG4W8P0I5z+6d/kss8wyyyyz3Es6dLjCV+Dh0aFDqjwlJ6TpFvMTUlKMOHnuBWzXa4RhwOr4EL7z6Poue6OQw19Jw+Z69H0nuPFqiYODA3jv0XkvIZiV6AE13jIIiSPiKOEJEiJiiggxSp4TzGNHpva5qRU0Yw2GoBqmRy1mMMl8B4etPlUH+HPNshdWKukYlXdjtKGvDevIIW4Nc9RKZaRzgiGDGGSHgSosJYeiMFyuIquQGt7NwJ9xKMPSuOCpVB3mYrb724NlpX2TbmuwakY+uFfdUeP2dVpiKiHKIRhhg2XVFc7lTY+FUlMhKcswbwV5XcGQ9z+gBWM1Qk7robmuhQX8aMtt+6XFbEsGEwTtQgyZSzurOdvUv7KiF4xa+jvxJKyUAf96e7YDOLUh6HXKhyrrsiiHWHYZuiewnABV7JXgnGKxScYxZbJW23vWkBJOhvLf2nbFGfujcl9FKrEHwQz/tWfr/BsV1HrXFlDWhLxOaNsPD1bodf0atM0JjO0wwoWA8egQCy6Hcg1HTokxhgjCAKSkoegXIADee8QYEVNAAhCikDm2ISEEwZFjSoihJbgI6aGqNVmnNpN+0raJ7P2BX+T3Ov+dp74qduo3vOpXu5fbe9pitfJ5HbE5BvQHK1x//JXo+h794QpJD19zYoRxzOurrbsyTuX1YHPVxjc3pXle9q/7RuN7MZl3nbPMMsvHQu6b6GFKZI45p//Ky4eRsAAcqRGXce3qNXRXLmFzfITt6QlWiwVcl0AUkJgQtgPimpFiQAgjYhgxjFucnq3x4WdvYjtscXZyghAiEJOaTMvLj2GEhok5jlAM/81LYipFXaT8b/2qdiDHygZtyxBiiCiUQXVQc1sXo7gJNHcHIYxIkZGi9FPXORAxlv0Cve8QU0LihM55gAmd9/BeW2sKl7LVC6s4gZCAJMpDbQgHSzxKMIsbMIjCxMwgL95CxjEiRkYHMaJ3xIVlqy83p2UFdXvICdkLBgAgJQmToRuPmJRRrx4YCAARq4cTzgpdVQSIgF4CoyGyBLuxcTavJEReiAeOJIYak25MlKzT2mqBPWPOrMq1EhUk3ieBfK8KqIcQBHQwI4AIUCd9nkLEkLYI45g9vFgjHRejtjF4s0tIZkSOIB1XVMom5bt0fpm26HU2quE5acP6rhPvMF42DH3fo/c+z2RysvF1zotHCU/oOhsHwnq9xo3nXhCFz5R1e044Agwk57Dol3jjG9+A4+MjHKyEPOF8D5DDEAZETlj6BTyJ54nACYtOwjNl0lIIiGOA6zy6vhelPSVstue4fXoTd+6c4qn3P4MYE0L21CBdkKIMqCdCv+zxxKtfgcOjA6wWKyH+RFWiuiXgPIbtiBgjELbgNML5JcgtkFJQ7x8S7zUmILI4TAkJGDZnOLt7E4nlevHsUpS4vPFOrAp1j75b4mBxgIPlBsMwiAeJAHBM+NCHnsXNF26h7xfwXY/Llw5xdLjEteMruHRwDOcYzjFWyxXW2y2IHcAO45Bw+9YawzDi7HyNkBjDGBAjazxFRlISTyYZpbzw2ILVbCCLalzNrRfTv3d+M6W1TW0bn3uRGQRDaFPkzXbVt3WZBAKceo+q0A9X5emdgAwx6ibQ28aYNByYVNs8esj6xxjHmOdW3bq9cA9NMIjdiu68dnYTfXRy1B/h85/4fDx0+BAePHjwo85vlllmmWWWWWa5t4TNEr/+//0CvPe/3cGnf9k7cP01H365qzTLLLPMMsungKx4hdeG1wqWBGCgAR/0H8SA4WWu2Ucvi4MDvPGL/ig4Rhw9cA1+0eO1f+RzkYYBx488pAZWgTcOVge4fPkKLl2+jOPLl5TcIWGxmQWXS3oYJ6UEjkLqGMYRJ6drhBgxDlvZ96fpTn8PsaC6IJ4gUKWgNl2VTzaHV3CMfFU8GtNjhARQOdpk2GjGbBI3uE1KSa6ZFw+tm4R6cBmDJT3QZASQFmQphATDKuWgnqIgE0AmKVaT4SUtm5yAqEnr4/ReR5XRO1sI1NO1tscIIO1hQM7GUk4Mpir8DJuZlXMdzJYqKaQuXvGf2ghLVd2lHl6JFnqv4WkAdicCdi/YcJDlaAQb9chNTg7amQdZ5YNkckdixDEixVRwuoosYNVAHpsKweMEBum41xOsJgNU+F419tkGwtDwRxkEF2zXuZwDyNql+LgjuJIVQgg4PzsvByZzG0oHMRGc97j+4INYLHp0nYVcssOBEQmMjsrBycSc6+L0eUmcwDEppu3y+IcwYjOssd0OuHP7FImFKGHjbfPIqua9w9Wrx+gXglHL4UitsuvE9hCTevuJYI4g14HIZ8/UgBGskL3GJAZiGDBs17nrDYcssydP1HxY15GH84yu69F3QcpmseWkxLh75xTr8zWcPtvLxQKL3uNgscKyX4rtiYDOd2IbAwFMSIGxXgfx3DHKoUA7PCxltMtWTZLJMyqnqa7zzo+NXAiT5gfxHona0ncyNk/3ze1canghhpyHwQxN+bHMh2QBWcOOHriGz/iKL0EKESDC9uQUv/2O/47NyUkhCkGfyajr7H20IJPp9qTL68TefqlXg48eR57lk0Oeeuop3Lhx4yUt4/r163j88cdf0jI+FvJN3/RNuHLlCr7zO79z7+9/+S//Zdy+fRtvf/vbf28r9nEsH5FHj10hRHuRuEoZS4zlaoWDS5fgxwE+RTgShSWmCIpCNhjGETEGhHFAGLfYbs5x6+4ZnnnueYQQkLYSy9GYofvMdEW5ASo1ryiT9Ytq55O9iCvFNPP29AoBtWJqGZih3myHTnNNnMR9l7rHGkeJpSb3iEHbeYfOe3SdF48EiVUJcPDOZVJAXuq51MmUdHnhFOW9/Ab1gFEp77UBWBXvpP+BVMmuFRLSEBccEe1Fa4q+vsHSpEyuXsBAZZy1GquWTBNXHs6ZRw5ph5RM2ubqxe0I5NVrRaLMaq+2LVJ+3RnU9k1RDExJ11MBMI8gxSYOVcyIhE3LSZR0MCsBp9SttJ1z/9gWJXFSslDReiZTVcux/jGGvBI9JIAoFn0v88I5wJMqgH1O67yH6zy869D5Ht4T+h6ZSdx1HW7fvAuEkMNbcJ4fGp6ICc53uH79Oq5du4Kjgx5dR3BuARDhbNhgjAGH3Qq97zDGKESPfoG+69E5QuccwhgQxhGu69AthOhBiXG2PkF/29r5nJzCqJ5fquYRwPAEXLp8iEuXj3H58BL6rkNK2uLFIeA7DJsRcYwYNycI4wa+O4DzS6QkcQxjHIVMlhhjYsTIGANjTYzt+R1ERMRAeW6XJ78SffwcifvFvu+xWAhJiAk55ubp3TOcn52jXy7huw6+I/QLj4PlClePVgg8IvAAB4dhCHDk4eEwjgnr9Yj1Zovbd9ZIKSFWXmzy7KqWO1M4azeURfa4FGXbQFoDL4yuqHlfoICb6Lydnk5oCpzk2azBXMCR+tltFPUKsJCv6t6RUcCRzNanfJIARGUDa+tEiPqstm1oP0/bwjvJbNMsZV/Q9H1ZfYTS+x6vvvpqvOL4FR9dRrPMMssss8wyy31Jih433v0q3P7Qw3jNH/m18gMBzkf4fkSKHpzcxZnMMssss8wyy0coHTpc5av5+5rXeMY9gxFy0vjFtuYfz+L7Dg8+/mnZ/kdEuPrKR+GJkEgOLplX2365wOroEMuVhE4WuzjLQTqWgxsxRQmhGwVnjWHEejvg9Ow8kz9Epkf5KmkwZPu7z4qooB1dELaVmsTN77t4itWmMmQalMMp45AMqKG2YBFmrBTDOJmPiYyRENWeCWrMo8LMuWBENcadyzWvIc0vlRFbDd/mQaQ4Aqi+qGeGVJWZTwHWuE/Ta3bevfJ0YtiVYS+E0r2smA8o2wisH+R0YlVnUvw5g8T1jJggZjrXpiNHViFDuPWgYuOFowHkywFN1ASJnLRB8fZgyHoNKGXWs5janGDtrK7azBEyBdkE0kOl1WFBcsUTh/NqqyiY3LAdsFlvgZQQd4If24DK/YeHh1gdLLHonGL8YtMYYkBKCb3r4MiJvQQS4j6XSaTPtHj1cd7LODNjGAf4bW5cxuqttxpKFcvcXix7LJc9lv1SiVE6J3wPOIc4Jg3DPSDFAPIdiDo9mKYkMk5CKtFDqykxRjDCuAUjiYfqic0hD1Ve7IrHFl+Fn7K6MqSPx5HkNy+EG+8JXddh5TvtrwgCIcYoY8YeMTFCiBjHgM02NOSqvcNUTSMm7BUZTm6m24sL7/24V+rnpL4nP9/7yubcz1y9Cm3JqVdeqp/HPC5k/CqZGwdLPPSaJ7L95ezWbTz1//wvjBsN9aXl5ed+WiVCmXUEXISq5ynQ9I3N1rIGXIzKz/KpKk899RTe+MY3YrPZvKTlrFYrvOtd77ovssfx8XHzfbvd4tM//dPxa7/2axfc8bGT7/3e733Jy/hkk4+A6FEpTEA2HIYkHhHgRekcw4jNdgO3DdhuE5790NO4+YH3q+cEJ2zLJF4pkjKwY5IXU4xK/hhGMQ6bomdKmK6BxcWf/k517UwtLQvmjoo9WXWLystaSGWQNCNilQvl7wRvrgg08h45AiVgHMXTgDE5u95JzEnv4bwQOgQ4dOhUOaeqbYXFLIqGvGik/1i/s2q2IclmxljoLjN69fS7Ej8csYS3cw7eNkshIqpSYVpTjAkhFGXf3AhyEldgUBY9QTwvsCr1DCnL2MAgoPO91I1NMRYF0cJs5I1J3sjoSDqXN1RsG5NYjUSZHKJMl61A3m+UAWY4Anrny57OyT7ET3R9AsH3Htw5JJfAxHDMcKwKkb7Mbc8CT3DJIUbdeHUdwAkcAxwInev1NS5sAWIn/eV1vBno+w6vefWrcHR0iMXBCt53EqeRXN7Medu8GSnGCynEgTJj2hjftklSHR5EhNt37iKxw9nZGZ6/8SxiiOrxQnkMRMI09ozVqsfBwQqLvtN5KmPXYwFCB0+ipPce8CzkDgu14z2B0Em9HcE5ABoC5tAd4ZH+MXDscXT4LLabDTbpTOeZPuVOxisCWA8Bv/OeZ3F0fIo//BkP4OjoctUvHiCHuFoiJcb5mcMwrLBYrND3y7yx0n1YxWwWBvl6cw13Hz7G7TsneN/7Pyybikxqkvll38cgrvKoIyz7Dk+86jE8eO0K/NOMk7MTnN7eYNxGxJERAyHxFq4L4BjRkcN2vcX6dIv1ZoPzzQYxihs9m2/jGLDeDLr+RRiRK09KhnqS0c1zvUKY95h6zdqnK2aFvfpbr4x5LbT7ufm5STS5suuKkvS/lPPcd28hatFOCtnwoijopG2wUxAGFkw3NKRzufOiRqu3GudkTQpjaIgs9ePf9AldVOtZZplllllmmeVTSYgSXv9HfxWPvPF9eM87PgtP/8brX+4qzTLLLLPM8kksPXo8EZ/Ahjb4sP8wtvhEDeW5u88HMxJrWF0nu/LIctDl4T/4+3H1ySfhe+DG8zeKlwoFrZJikoLpJM1LcOQU4357+OQ7N9/3sAjqO7kY82ujep2y8aBaFbbv6Iz1hqtOmDE4u7cV8krKaQ3DcFT+ShUIjkv+dvClgBupwnQoEw6KjZlKmKAqz5riwRrehViBUMNl9GAn5wM3ghslZg2rXPUFQQ3n1p9y3anR1qB089xhYT+yF+kcF50zpmPjlTH9Wlw5Hio4PIPTdA4S9oWPKBhzwZBlDAq51+wOEm68nieSjp36I1ED/w4wZ5ZqR9KkpHYA5yATXPsHXquhGLf2fz0XvSNcvXoFi0UP33XZ3iJYcDkoVTwdIB+KytaMPIaShpChXxABm80WDMI4jDg7P228zOQnh6Tbu86JF2olK1iZHl5xf7kuCDZriG0Nte2osQ2U6UzoqceRvwRODov+DCEEBB5yHTJuqYdRQ0i4eesUi8UCjz5yiEW/zMQgUnCYO/X6OxBi7AR/V3KJ5adZyrw2XHgcsd0usNkOuH37BDmMuj0GuS/lUC0RAAd03uHqlcs4PFiBThjDMGDYqHcP7VMZZyGaOBDiGBGGiDEEjGHUw6e21ggxZgwSnipGO7hZYbhsOG2ZN/mBqb3bTH5qvlsnNIsmTZbJ4oPnI8NOqzUifyMJw9PUhZqMy5jfA0OGq8xB1gd125FJa/3BAd7w+f871rfv4r3/43/i/M7d/NyavYdjTXKqqUWTRagshzt1K7WfEeZZ7i03btx4yUkeALDZbHDjxo37Inqcnp423z/zMz8TX/M1X/NSVW2Wj1Lum+jRKAh2DYQEhwgPjcaGFBPCGLANCTEybt85wfPPPgtyPeA6xDEghqBeJcSNl4S7qHMWA2DjTm6P8bJV0q1G5df6lorPN32llW9G8sjKi74EVMmY+IcAADg4jflmi7+8RGKSzQaRz6xM3zkNcWFBZ1h/q/2VUN4ssNbJXLeRhmCR34pxM6lHEFL3eaL0UvMSExYqxNsdiQFeDP0MduI5wtR6Cb9T3uPSTlXALXYGhC1tYRacI9lkqacR1r725BtFL4+HXi+bk/LutUYYK7vWLazvMwtdsy46TeVaS++z/rCQPkkVA6f/WXiUfL/vAHJICGAIGYJVUXPO5Q0PeQfyDkldejnv4bte+lXvA6trRd31UKU52yzqvMfDDz2Iq1ev4vD4GF3fw2tYmc6Luz3KE6LMSQY0xI0qx8ocTylp/5RnyPsON26egDzhhZvPIRHyRsJcTDoSYoRXbzPeWdxUqauHB0QFl82FKuryV+MskoTTADnJjyykD7BwPbqux9HBGsvFEilGDFurRqvoJd3o3rh5irN1QmKHfrFE3/VwFvux6gdOAUSE1eoAi8UizwHfCXOalSEuJTE2wxLLlQM7B/rQs7phrdYhRo7kk8BgB/QkY/XAtSs4WC1w4/wZBNpifTJg4JCfRx4jiBNSlFih4zBiuxV3oiena4xjwHYIyhivnnveUbc1Q1uTGGA3/bGUOyVclIVtcgdUNy6lUXbpk3OdbFaouZ/2VNN+5KqMNhm1H3M8p1bhLbPSdrKTtRGmQ7droJ0Fgc5D1pMBAOA6cQuJoOsuWhW9qjXy26LaSN+juTAQoG3jrMDPMssss8wyyyeDkAOuv/ZDePDVH8aNd79qJnrMMssss8zykkqHDtf4Gra8xfPu+UL0+ETbYtL+r3YwJCNwauy89IpH4A4PcefpD+Ps5vPyAiYPjnL4zQgL9j+52QyBZpzT3ftFG/g9lZwaCyWfusYKVk7ybEkeFZiZQ3oYDlr/JrgiZy8OyGkSJz1Qp14jlNxhh7+spIz5TmpTNzu3o8KYzPBLEC8FBALcboib3CJm8YZAVXk2BlQ8JQgmpWnV0klQMgMB2UN1Jpu0BITEjJp8IUZ/+0oQ7BmAXq/tt9Mxyd40gHzqv3gNqTFuwm5YhgqXyk2x/mhxaNbGmYcOOEFJox4ArbuzJgDYuArJQw6KZq8TLpT5zAAj5R5p/rDg0kdHh1itVugXCz1o5zPO3fRThSGXb5qGSjh20huy7YQcVusBRITztba5isku/BPFfDXkipFNSvMJtX9r4ThRFapd07mKvEQF1/PqVXnRj4LrckLMhKJqzPRxisw4Xw8Yg8xH8XrtdbXhXG+Zsx0AQtd34lEDVV2ohEiycsLCo+tJx/BUQ8YwarsL6bwwdNIDIOdwsFqi6xzOxh6JIsYhKjZZjTWXdsWYEGLEsB2xHcQrSogJ4Ip0wMX7czOFG9n3oOx6Fdr5Wj8YtlQZhpznUY0hV9jyRS+qe4Kq1VI6rXpdp/pAZG5X9Xxlzzv1fYptax0Lfi4epx56zauxvnsXH/xfvwm6e1LIdq4cMpZ1eWpNtHW/ekr3NL146LFvF/XFJ9oLfpZPRfnv//2/4zd/8zfxtre97b7S/+qv/iq+4Au+AM8++ywODw8BAE8//TSeeOIJvPe978UrX/lK/OzP/iz++l//63jPe96D173udfiu7/oufOmXfikA4G1vexuuXr2Kf/JP/gkA4Bd/8RfxLd/yLXjve9+LL/uyL8O1a9deimZ+QstHRPQgAg5XC3Rdh6PjY3T9AovlCuQc7t49wTCMGAJjMyQcxYCjNOL4+BDrhx9Sg7DD6ckJTu9ukUhIAftXuEadkeWbiuMyu+53tNt9eZVltVY3xC2dKRy6gIufMnmZJ4Zpl82LylimWndjlZ+vz8VzBsz9oHjr6HvxbmCx6sS9YBAWb1ba5X2dWJQkR4So4RtMsbcaiF4lLqVEPyFIpESGVyXeYtSx82o8FqIAqeJH6o0D3oafpU41IUOVPqexEoQ0AG07AHRFybX+ZQapR4/OKWNXNzBD2ICZ0XWLEsqEy2uy3iTIW9jDAuIwp8LuLWpnO+6mKGo9GJCwOlmxts2MKIveORwfHaHve3DXAc5h6cS7iu/FowY6AnsgBQbHJN4iFkt4R+hIWcu9KOWRS/3Wmw1u3bmJ87M1nnv2BmIICEEUA99JLTnIGAYG0oJxcHSMS5evoF8s4YzcoexugkMO+gjbUBoRBgBpHE+UuWuKPUNOOThPuP7QJRCNACOnl42AeJfhxNhuB7zrd96PS8/dxGtf9QiOD1c6FoQwjkgxwlEnY5PE+0RKHch5hCAebpIqqKK4p7yxsflwcNDhyTc+gVs3b+O3/t8TIQ9pGqekJvHpAbi0BUWHk7M7WN5xOFyu0HmX50bSsT49uYPNZo2ULoH5MGtv5h3DO4dOSTr2jByuDnDl0iU89orrWJ+f49aNW7K5Fhcn8jyCAEogdkhJNi0HB0fouh5XLx2D04BbOME4jui6Hs5JPE4MCc8/dwtnd9cICYjq5WccQ+6fshoB+UjCdEnU3Q9rPNJWia2egGYTYlkZEWI3BiuoFGUrpNHPWoSA1YtI5TXDGOe2VJh+b8znqoa5VGrb3N5YtSZr3erFhFg8w3ib61TVG4jmmpVlfvleQZCatc8scXp101rigRJCiOBoa86kg3Z2FhfL/aecZZZZZplllllmmWWWWWaZZZZ7S4cOr4yvxJa2eMY/gw1e+lOeH0ux/XHfezjnsOgXcjjKdwARtoN4NY2JESKjTwkLTlgseoTDo3wwbNgOGIaQ8R8AZQOewQfKBj2ooVuhsr11au7ZI2oSLncodpmdjALqaQFqCIRZehVamFgorSgyg2bKJ/VrXITIZa8IZrBnFo/YBvKZ1wYwyil+O/TFdvhvam41PKTUyXCg1guH0++KvJKr7kD2wgLzqkLNrxm3FRwJuS7Sla4iqBTUyKFghcjpGZHFoi9effdhR/VgTSYEF4y4jEbVIwZoqfFawVHB27WPzcO0YGUyJot+Ae/lwBiI0OnhRwu7AfVsbeQl7zt4J9i5I/FK4j1ljylWtzEEbDZyKOzMwhAlJQuYV185oZjxxL5fYLlcwvmuwsuh7TY8q8WQSxeY92wlTVU4pAbfATnC4dECoKhdytZNZX6zeNF44eZtnCzPce3yMRZ9l+dNikpeIoek48rEYBZSSEpmUyjjQsQZjiuhyB0evH4Vm/UGL9wYdO4pYYxtJqudhCOQCMO4wWYjYZHlrG3BgwFg2G4RwgjGEuC+YMj6UNRz0rD23ndYLpe4dHyIcRyxOd9k3JXIyE46H5nALPahrl/AOY+DxQJIERtsEWOEs3AuzOAInJ2uMWzGPMZRSW62vBiwWptuJtBwJZM1qE6Yx5qb7+VjRY2qgNx6+QVNiFLtIJb0ZZHZQ1CzG2law7bKO+uG/MZ5bQH0BHYun6gUWFY/bt4hpM/k6ugQb/ij/5t49vi/fxVnt24rp6ZaT/U/eTYtg33taVty3zjxheM4yywfP/IDP/ADePOb34zHHnssX/uH//Af4pd/+ZfxUz/1UzvpP/uzPxtPPPEEfvzHfxxvfetbAQA//MM/jC/8wi/EK1/5SvzO7/wO/tSf+lP44R/+YXzlV34lfuInfgJf+ZVfid/4jd/Aa17zmiavW7du4Su/8ivxnd/5nfiGb/gG/PRP/zS++qu/Gn/2z/7Zl7bRn2DyERE9vCOJdbZY4NrVK1isVvCrA4AczrdbbMcRIQJjYLiYsOSI1XKB1aVL6AF4BobtWl7s1f+mSpct82bX3FVQa32cqqupekWY6trcpUppyS0rk8IIEGW0VnRzbu0bxuyy4mUjYjsOiCEC1IPg0HkhSfjOw3dewrMAGEMU4ySrEd9eFuqJwREhkYWaiIATLyBSBQtwoX+1nvn1at/ZFAFnryWYempEDwAaHoXUw4ptHDSNMnuEBFCIJZLEWLo2MvqNOZNxhDVrr7iEGMWDgfd9DuVR6yVZaTE3ClLBMnJKeJE+t0lBeaNUaoLcN7IRKy94M0Q7OHTU4WC5wmK1BC96wDscdT1657BYiMs5t+zgOo9xiAiBcXTpCg6PL2HhSf7rCMvegclJfFEWhf7k9ATdMx63b93GC8/fRASUtOPyfGYNI2JtXyxWWB0cKguaCjlC6Ug5tAmSsq1rhUY2WZE1HIht7mBeViJAjOPjFc7PF6JEGuvFJrNuIMMY8fSzN3D75BwPP3CERQ+QE6ZzDCM4RnifQOSRkoxppAhyXghKDdFDiEs2Lo7keeg7wite8aCQmpwDEMsc0qdWaShwKYDSgPXmHKfrBYgjFl2HpP0Sk7T9fH2GzeYMXefRdcK+BkOBg4i+67Dse9n8guFch0W/xOFqhWtXj+EdcOuFWxX7n/PmL7HG/0zCuF8slvDe43C1wna7BJGU47te+jKJon/3zhnu3jkDXAcirxuoBHJen6HS/6Y81l49mnWv0ojzr43CzWVjov/kjVj1bNhjVott7Hd06LzETMsp9RD3i/Z9PzO81smb8g2coFLfUmhRxAlAZuWpCxcG8pppmTvdBJNz+XnJ21vdaBPkBIWBJxQTYPFGDZjB9KttOqa92Ta0Lu9ilyf3J0bcyeSZ/TuiVohlrbYYU7PMMssss8wyyyyzzDLLLLN8QoqHx4P8IAYe8IJ7YZfo8fG+5VPsS0L8eqxWS/iuh+sFXxqjYKOJgZgkDILnhM47+EWfPcfGGIDB9uN1mICCiRUvzE3x+fQ+MMWQWcN0t2EHahPdvvAr2duAJc7kC7uA6rvdQ/neEjZBTuwLDquec9U4SXooJRuZU1TjpOKbSrZIhqebBwHmjOs6Iwfs4DLFjCtVMvAlH8GrMOTSmJwuG3AFd85Ys8LpmWRguK6RDxxVOG5Vfl1STU4hxUzBIDZv0C0Gs4sh17mVg4r5ljpzM1JnvKe0H4YhwzwzsHgVJoe+8/BdJ0QP57CwUNteQleTdyBHiFE8ZS+WeliQxJ7infzNh7kg2OEwDLh76rBZb3B+tgaATNqxatb4EEO8NnddD/Og3ZJo2tGuSUh5DFjmYQbk9N5M/gBjsegwjh4wvLHC4W0MUko4OT1Hvx1xdLCAd9BwNHLQ1cgdcE7mDOsBWbIDncj2eRu33BJ9DrwjHB8fwHwBWTtq2C23gBOII8YwYhg9AIavbCPWj2MYEMah8pijiHuSue3Uw3aBhmUd67sOq9UCRMhED+sL62LYZzYv7oKX912H0He5/9vKM7Zb8QYN9YySn9Y8xmX8bZSzT/VqeKZSEGZ7jltsN6ersV/SJ2Dfe4YrUsukyIwh5wqWScfaSbsYcluX/BTT5EI7VUuJFUade8XGNLsB1z9Nv8v865cLvOLJ12F7do4Pv/O3cH77Tp7y0u9l3ZVe0cPTzbpic6C+WLwJTTqw+vdjgyHPMstLLWdnZ/g3/+bf4Ad/8Aeb69/2bd92z/u+9mu/Fj/0Qz+UiR4/9EM/hL/6V/8qAODf/tt/ize96U34qq/6KgDAV3/1V+Nf/It/gR/90R/Ft3/7tzf5/NRP/RQee+wxfOM3fiMA4E/+yT+JL/7iL/6YtO2TSe6b6PHoow+j6zyuP3gdq+USx5cuoes6DADGmNA5LwpmjEghACnCcQLCBrw5wd31iM16wHazRQgJKUkMtfJyMpkubvpCQ2VoawyY+6gi5d72F32NqJLoMttYlXhbybncR3sUZPGSEJBSxHq9RYgRYZQwKItelOrFosuKaooRgUs7TemRuHwJIcdQ1IIIYIhHD7k/wTwzyIujfi0C1Pzr4DthjWZHb3ljIQbN7BIwcXlhuQ6ehFXLqggaEQUWV0+VRyIHRx4WG5MgmzdR4E0JTBKWR0MqdL7XLnTiYcJpPsrONuN333nZ2HnxqkGeAEdYLIRg1HlC5wjOd+j6HimKAnd6eoYPf/g52dhIo1WBhowhMxwL2eLo+DIODg7wmte+BsfHR4WNrcr5otfwOmpcPt+Iu7SjwyMcrg4ADiCOCCFivRlgLiU777DsPM5O1/jgU8/g/OxcyD8M9E5OLbD2h4X6ESU1YRjWWK9PhSBEhAiHBMJmu0EIEQvfodOxMUJGCBHMI5hHDGPEMEbESIijKqNJmP9jHBHTFmO4g7PTc4QxSH/kTVoUnUIdhwxnJ0jDBu96V8JqucieczjKHCfndZ5UzyhD3BXa88SqlNvzoxs/ITMkhDDi/PwcwzhIqBnNKZr7O6jrPAeEEPHU+z6EZ5+5gV4JJczyHznZCIzDBjEG9Ivn0fW9FMkkc5ATPHl06rFHvER49H6BYRxwuj7DMAxZ6cyECX3enJd8hmELAiFqqKUHrjyEg+URnn/kHNQ5bM8TwpiyLmsbpOzVRBVpVq8hLveHPO9ZkRTtsyXcV8uD/E25n7WyZTRs06N51+vWVAiFQ9Fc1GdoJ29Qmw8Xh5J1BjINuKytVfkZI9ipzX5JicFBGfVV5BpHBHjZuInrS2G8k75btNHNh4Y8oeuD8y6fmCB9P9jGtu6Hop6XTXPtwfV+23M/sg5r/J8f+D9xbXUNn/Po5+DawbV730CMxz/nnbj08E188P/3Rjzzztd9DGszyyyzzDLLLLPMMssss8wyy8shHh6Pxkdxna4DABISnnfP45zOX+aa3VsuHR8hbLe48a7fAWLC6/8/fxjHl44QWUIsGB6FxGBK4pmWGU+/8534wG+8Ew++5glc/bRPQwxRja8VEtFszSsr3z0snbuYM5d7KtucZFmDMYYhKyaQrbmWVY0hA/lU4KQCrKG4QwiChyfBgDr1fOG9HcwzzLky6jYHUtSz9BTrQBKsFShensEZm1Prbjbg1oQAO4hUrlLTtxnbskMlRCDyOZT3FDsB3AQ9UWxdcTKC4jGGJSr+wrksSPgMQsZnzJMJ2QE6PaToySm+7AXbVvKN914M7M6wNw/nXQ4jPwwjTk7OkL2i1O3WJgmxwMJId7h67RoWiz73gSOS8NeGheq94yh4ft/36LtO8HWIHWQMEYbEOSf49jCMuHv7FOM45JDSXg9qmv0jH4zScYxxxDgOGsYbgpES6fxK4skWhSyQonmCTgCLJ50YExITOGq6xIrjJ7V5bDEMo4TB5tpkXYF6DMRxAMeAF24wus6XdGwHFV01N4AS/4PK8ycTvSSzKai/pxQxjiOiepauzEO5X+zWlBh3bp/grDtXbyxSJtsUJSBFsel4fw7nfbOMsK5PdlgT4GwHiSliCHLQd4qx5rpoI2KMUn31knywPELXLXB2PIAcIYxiM8l9kp/PJHaGXKdiUMqYO9Vel2HLULOWlaGqGtdcR3PD9IDZLoJsQ7NnjbXBymti80P5bPWc3mxAOgqGvLfe0wo2bSV9PBjZNFSFBiBGZQexx4szmcd1HV79eZ+NRz/9SQCMGCI++Gu/iZPnb+h7SjFkV4U80knFeytU2yR58uljiyHPMstLLf/u3/07HB4e4i1vectHdN9b3/pW/M2/+Tfx9NNP47nnnsO73/3uTOz44Ac/iFe/+tVN+te+9rX44Ac/uJPPhz/8YTzxxBPNtSeeeAKbzSeWt7uXWu6b6PHAg1fR9z0efcWjWC1XwmB0DifbAZthEA8ODHBKSDECnESlCAPScI6zu+e4c9c6n3bW6Wl0sUqFqZZGzi/OfSbLXaZcrVoWVqqQPFzOm/NLn2VzofeQ6az5pWOVYyQExBSx3myz1wAiZeh6QtdJyJYYRCnKB89N8bRacQKbnkcS907aKS7ZUmKkGMEAgr70nLq8Y1XwSBnMzKI8OfUAQlqo81KeKGui2DGE7Z3Zpc7Dk4MnQmJRQI0Mg+rVBCATNKTu4q4vh2NRJSjFCOaEmKTXeyfeDhL0hapKulNCh190cN7jYLHEouvFM4P3cMsOftHhYLXC0cEB+g5YLhy6boHF8gAxBGy3azz33At45pkbUh5562qYZxIQg6J4BVkdHuLo0iU8+thjuHrlUtZBWHwGYtEJ0SOliJQi+sWA9XbE0XKBg8UCMRLCGLEdEs7WW0isSI/lokPvCJv1Fs89cxOhVtKd16ljM7u85IkZ47DFMKzBThSPAR6Bgbund7EdBhz3Kyx9nzd8QpoakNIaMa2x2UacrwPC6DEMHilpXL8QMYxbJN4g8U3EEDW2HzJr2TZSxARwwrg5R9gSPrA5k/kBeZbt6RGShVONSZVRFkWUjYXPgCOvXmP0sTEFGQykAE4RMQUZq2Rz1OaYkjIgz9YzzzwvZdkGXyPZeJ8jLuUykj0jOh8TWJR7dsLJcTIeHXXCcnBldbCNGTNgsX5sy8lBgigmFgLL8fFVHBxcwrUHnsaYtrgV1gjDkLVrc53pXSH1JEAqSBGcXVDapl+faWgHsq13e9S/7PGhvjZNVDZJDWt5IpXfHORVN++oAEzurVnqTGWjvlvPsm5OMAj5aPvgRnevN44GKgAcAXOpSWVhhndOnwm5KylRKPt2orpmnNsi5CKpADnKhA3R0atNo/6bGfTVdiP3Vr1x+hhp6kMc8OvP/TqOF8d48sEnX5ToQQQ88sb34+En34/17Usz0WOWWWaZZZZZZplllllmmeWTQDw8rvP1vOWMiLjr7uKclejxcWotOjhcYRMD7r7/Q0jDCP95n42DgwNsQwTFKJgNq8EsH/hhvPC+p/De/+t/IDnC8sHr9yiBd/AFoMWQUWHIrVzUadT8qTFkspDYVlYNXjfG0iaD6k9STwLiyUNCd6vJ3xGceh21Qyg5X1fqamjE5FA6ildj5ENHQAl1Y7gI12COhpqwkNFgw+VLaAjOBBvDZhSTdkK4kF6xcq0srSln2KYQNAryVsZI0zNHNdCyGlN9xlyYkU8oyYFEl8Ol9L4r4XnNq4Z36LsOfd+JJw1Pgjv7Tg5bRgmRcnp61uBwdjjN6mXG4K7v0S8WuHTpElbLRT20AKlHaz3UJiFbIsYQsVBcm1NESgkhMsZRDQCk3mvII4wRZ2drtaVo/+iYcDvRdH6z2iGCjhv0sCCw3W4RUsTCdSV8NTNCiEJO4IDEI0KQuZiiQ4wuz5uUzCN3BGOtdgQdd0Dmjc13fWwTj0gA7oRBD7xyCalCQPH+UE5uGYZcC6EizOQWW9j6pP1rIVpcwW4tbwJAYvc4PT2DYchASecIIGcPptYPXB2otae5eKcxr9sul1FXugI9bcIoTmr2ADmkCCyWK3RpgYODEyQOWKcgY55tVoqvap75HKItOM3ctGferlWLgp2qLo3JHbADDe89YXhvKYGfypXm44Xws1Sm1IHa3yoS3T6r356KoGlo1QcZA0/VM43qM9d1kXXOdR6veOPrc9bjMODmUx/EyfM32vdIfUB0txWgaqyKZ5YyqQuqjI+472eZ5eWSf/kv/yW+7uu+Dl1331QCAMArX/lKfOEXfiF+5Ed+BE8//TS+6qu+CkdHRwCAT/u0T8Mv//IvN+nf97734Qu+4At28nnsscfw/ve/v7n21FNP4eGHH/4IW/LJLfc9OuvzM2zI46nhwxJnzouLsDFuEWPAZn2uhIMAZkJkRmDC2XnA7dsbbLdRcypeNOyVZP9mZi+AollC2N3NdSFpJPWKUJMRJNf2haD+M7KKXvmnkPKIAGdGa6ubvfB1CWYpbwijeOgYNmJIj9Ku1WKRvReklDCOoyp68vL1TkgTKQn5wRnho9qN5Nhs2g+dEwUaXtq70LblKCtUDI/Sjg6VTiT9w+rZQxLAQ1nMXBQZp14SssKjQ0WkfZtDAXB5N+lL0Tmfe5fB2SODeQKJDuj7Hq994lU4PDjAYrGA88IsJiIsliv13iEu7vquh/euuL6TQIboui7H1vMeeTMSQ0TX9Viu1mB7SWusSCPDUFX3ru/w2KMP4cqVK1guOpgykV+0zEgxAImw3m4whBGAw6p3IB6EkBEihhBwuj7Fnbt3JdyL77A+YTw/Mm68cBMhbIVpnKLOQVdNUWoU2iEEvPs978eHnn4WhfDkkBjYDmvxVOF7dM6rNxYgjAEhJIADGAExMsaQwIkQgyrzGtYkxABwQIKcHDBPMWY0rxU0YeknIXMEqXLKbg3tmQAYMYcAyhtFTo3SmBBAyWkScTMncQvVq0JWYCXvWnGyWiWLi+c1BqPOaevCBCDFou8mlk2z7zp477UPRAl17ITBy4SYEpii7qrN1aVsypJ6LkkxIiUgJHmmh80WKUUQRakf9UgJGIeIvlvC9wFuyUjjaNFodD0wIoysXfY4MifZc1ReJrIy2vypNnRZKcWuNEpuEWN/0yT/rO/Xn7i909ZlG/5SUFXBCxRTqjcTwMT7RVUQoawx1T3l52qjZ32la58R7GvWPwBwlPXI3J/mrA2FqAlsegrDWaioXOeWwOLcpGpcuvw+tiCzzDLLLLPMMssss8wyyyyzzPJRCYHwUHwIx3SMF9wLH7eePcZxwLDd4s6dE4ybLW7cuIO0PEJkCQEcwqiGOcGV7LDbOCZsNgEhlF12E8YAyIZPgyMqM56mKnhFwZ/L9ZyHAmPTE+aUoU/S0g0Oc+X+Hc8djflOMRcxyLPijHX42d775mBOjKm2Hyrm6zLRYgcLskpVx/o1KkgGSDwZ1lXqXBNRsncM7Ug7OJMhH8VdfO5ryth1RqMddAip7i3sCFsa60MzbFeNIgI7wZmvXb2s+LDPYRMIBO+7Kgy64tmO8vcchlzJH4JrW9sJKSY457HtRtjhyQbrntTeeY9Lx4cSeqhyMZthLCDjlGMIGlJbPHWAI1KMiEk8fAzjgM12C08E7xw2W+AsMc7P1xoau8Lf6oFBW6mYEm7duo2T09qkI5hqiCOYExyZN2TJL0UlbNjhT1aPykkOs0HHgvMctXSlTonsWbT5o8+UTcGkOFquq9bfDhfSHgy5ahpbKGIuGLKk5HKPFZzxf8M7DVPNvaFYHTe3mckgP/tJvZU4CS2eD9TZAFMpL5WFAaVmhajGGsY7aT/GEBQLNs8PQqiJUcKJO88gj2w3yOtU4ioic1mJmtAq9UKz84fReBm6l+xNlJ/2qi/aX/eKAb/3KuxCDFnrq8Bx07wXawjzJE17Qwldb+sf1wB3LgZ2iFF/8t7hlZ/x6bjy6CN4+v/9bZw8/wJ0ZkLAaOt0zl1EVYXtFdF237Sus8zy8S/vete78I53vAP/6l/9q9/V/V/7tV+Lf/SP/hFu3LjRhH75M3/mz+Dv/b2/h5/8yZ/EW97yFvyH//Af8Iu/+Iv4nu/5np083vKWt+Bbv/Vb8f3f//34+q//evzMz/wM/vN//s/4mq/5mt91uz4Z5f6JHutzpATcfOEcKREYGkcQG+GNej29z1FfbIzADufrIJ489O1Qx4+rFztWVw8MZVgCyIoyc1ZWC4caOU6gGdEZ9uJrV025taicDgQPl/UEcsL4FXcAlF1gcVVHITFEbMZBvEicbZBdyjnCctHDO4dBX+TjOEppqoB6EiIDR5ZYg+ZaINex8lsiPAX0XhRUJoInQuekX0dOqtCqMgtR0D3JcKYUMyvelBoCwZMSKlAMpdan0j3qxq3utzIM1QdS9rm465O9hbohTOKarNNwKIkAt1jhiVe/Gg9eu4pLl46E0awDf3BwCG8eSIhAnrLrOQKqjRABXMgAiQNiCgghwndLLJcnsFequM9iwGdVIUvXeTzy8IO4du0qFgub/lzNJxmfCGC9WWM9bHF0cIDVYokYxOvGNgKbAJytz3B6ehNL74G+w+n5iOde2ODs/BwhjFJvDW0DR1Vd6o2PEDHe974PggFEJUvkcBocUAc5MiXbGNHZY4Fu6GwOlVYXxry1NFUPncyBTsdQ28/SFyUMjhSQvXNQpmZNYiJyflZFIbR2Sm0ccVaEkv4mjwDZni8rWwRjPqua6mxDIPNZ+UVQD4K5HikGcAwgYo0iVJRtBuBYn3Mi4TNZx+X6J3XhlzAOA2JkrNcRY4w4OztDjCOQtsoi75XUFtH7JVw/gPoExACOuqlg0tMYLGuB5xoa0LnNTdvkM+V1px67hu8+1Z+nhDfbsE4S7yN7NBvIOv1kI/GRkD3yxreqRn17o+xqrFubB83eoJoXtoFmMlev2puuTly8nTDpWudQTgZQmZe2vpHXDFK0XVnVDQVUMe+J0/i+ZSOyPwLjLLPMMssss8wyyyyzzDLLLLN8tOLgcJ2vI3HCmtbFswfwcWVACuOIYRhw9+QU27M1bt68Az48AiEoJqkhFcyYDDmkNo4Jm21ADFW4Y7QYsWAtgCEm1e5epVh2BZcw62yNS2ckcOe+Gj+2PX4Og8HQMLBUVaQyDuec9OCVeXMYx4LBEMnhNtJDSGA19pL+X7BkUMG0oOGvC4pS+S1hVswXGRgkyME9hhE4GvhLMGgFUgRnYcXkzShvaUp/1fUzHKngldzUqZ2LlEeKCmAIYPcAJwMg73H16lUcrFZYLhe5HQDQd72GQ0fBWqvDe41doMYrWTw9JJ/goof3EvK5YFZTgoKIePM9wGq1gu9KO6X5nPNmACEGjDGIl2rvkVJAjAFBD5CNYcAwrAUvd4RhTDhbBwzjqKF8UrED2zyoZrjVLaWE27fvZszQ7NyKMlZPBXTOGWCVQeOqDDR5T2WKS0phU4/VgpFl/DZPl4n/4OnJKbtmFnFuDyKK6cLStRVnK7TknvE7QOw6NZ4pU50zqSXDmYrbu2a6sEXLhlGMStbtesEAOFWHBRkIIyNywjiMSBwF12cG1I6WOMG7DuQiyOtBSzMEZW/zWpZrD6A1IXwKEFnqWGHAuf6TA4WlU0q+mnnbn9bHu9OiqkOVcb5t+ltVBr3I71Npbm2oetUPDbrc3Ffj32Qx60HtMErCCtOVPJ33eOzT34AYIs5euIWT519APoiY1/+avDTFzdEsQxbmxcpqyptllo9j+YEf+AF8/ud/Pt7whjfs/PYP/sE/wC/90i/hp3/6py+8/6u+6qvwzd/8zbhy5Qq++Iu/OF9//etfj3//7/89/sbf+Bv483/+z+O1r30tfvzHfxyvfe1rd/J44IEH8JM/+ZP41m/9VvyVv/JX8Mf+2B/DW9/6VsQYd9J+Kst9Ez0eeuhhyGq2BDQMAgDEdIaURty8vcZ2OyIw4MA4PDrAAw9ewepgAWIx2Nen2o1FbAxQUyKBomjUinqrfIiU8CuaRhdbtvc5lZzUnpxfdFy/Ajm1SgnE9b9tCGKM2GzEQ0MYhR3rO/EJ0vcdiCQUDAPofAdmxpiivLxJiAsSL1Fd8jkPp4pd5W/CtFQYSZiISvgWYoRaT2Hk0BJwygplCYNh3hKMrpr1gA6qiEsGpWzO71YiBwsFk9TY75yDp0w9KP1qCj9z9jRh45qIsFgs8KpXvgKXjo9x7eplHB6sMvsaMWoZUeM8AsQESozU6BnFLRypQiRlibeMF27exbufehp3bt3OIYNYX7SU9AXsrb7iru7DH34Ot2+fYbFcSXiR/GK1N/MA5ojTzRqbcUDfLdB1PVIYkNKIMSaMMWGzWeP8/AydIyy8wzgmnJ9LrEcwK2vcVQQMRh7czLbQYlVBdYCE79GNBjcjVcnkqyn30KyEtV5txiqlx1euH2VDUMg9Oeui/5eNUopSDyfko+xdQ++JSUL+hCCxImNkhFAYzn3vcXi4gHcefbcEOYuzae0vJbJWLlmMlqj9qI2M6uljGAJiTNhsBoxjwHa7wTCM6iHGZZeYErdTvMSI20aHrteQRZ14J3LONq2yHnmNI7lYefTMWC7k2XakJ09YrP5J++fy5UvYDCM+9IHncOvmXSAGoOlbJZ04yt5/Wl3UZf20jPwkSU28qEeMJmPGe+7dIy1xgyrCT72hVFV6RxOu9wXtZqdNsb8WTZgalG1IlfMkO672bjprY9GiC2hBmYlvG/5MQtI4p9O2lH2oERYBcxtaPJpIAfKMmj5fuSw0Bf/FNiqzzDLLLLPMMssss8wyyyyzzPJRCIHwAD+AZVrma3foDk7d6ctYqyKHh0fAGHHlymUMfY9rVy/j2pVLSDyCOWK9CYjqRZUc0C86HBys0PU+7+FR44EN7qBGecMSkS9nfGLfjpwUQy7f5Z6CWrQeG0pe1OAV+TBiZdyrPYImTghjFBw4iuFdDt1BvUxYnshYsoTZ5nwQL2NCeiBOsDgYuo26otlLhuHh6hghGSDcQjuCmwMwa3Y25JvLA22THaipzb+kPxa7u8t9wyxlktWpwZtQjSEXDFOvMUlY8SuXjrFYLLBaLRVvVwwnJcX0a2AcQJx4ZMkGW8X+lYTBEDLLer3FzTsn2K43+VBWCUdc+kf+CCZ0cnKOzXqE77pMtikcA+lwRsIQAkKM8Ir5CwEgIiquL1jpCHHcTeKZeRSvL2DzFIAWQzbsqg7H0Q4/xGNEfmouSNheM3u8jpwmqSdJme81fibwdQUE18/aBMYjm4gEDRtUY4N6OEsJEtHIEuoVBEnC0Pe9h9Pw8cWOxJMCK5yUtbPUHpAPBWqDY4zgpKFsUkIMASEmwc+zfcO8A5NixdC/+uxqWCFypXyq+sl3Dg5OQ+cwsicTNUoZ3r1cLBFSxN07Z9icb2WOTuOuTEOrNHArTSDXfdjrPgy5FDFB4fcVckG+tOezLR51nfeuxBd8vqA8nYr3pkTQxc23NUbtLBXbrWDB2X7YtETsVM7hFW98PQ6vXcnZPv/e9+P208/q+qTjhHLoUBH2FqcHIf/IxU/VLLOYXL9+HavVCpvN5iUtZ7Va4fr1e4XGa+W7vuu7Lvzt27/921/0/qOjI5ycnOz97c1vfjPe/OY37/3t7W9/e/P9TW96E37913/9Rcv7VJb7Jno88vAr4JzDcnUkxlGNpbgJd7AdtzjbPov1JmLUderw+BDXH7qKg4Ml5OWURMnRlzKphwtkg2ZhE5vUrGHa83Lyk5dDtqGb/ZksQIt5E2jbVEJIEFIsp7ZNCWQWpTumiLONxKZDFOXSdx7eexwdrEAgjIMwNLvOgyHhHBIn9M5L2RqmQcKPlHgDThX8mITxKSFUfFYqYtT4eKhMxuq2zogerMoFp1C1rYSq4UrRtfeKdnBWfBNYPaMQiJIotBCmcE8k3kWU+VjdnvcBScvIRlAiLFZLfPqTr8bVy5dx5egyfNeD4XUOBAkRkiKSvVAZAMfGA0PZSQhJJqgCKEbVhOdfeAH/89feCQ4jFjHIPNO6UJQK2Wl9AiGGiA988Fl0vgdoARDBS3AbLR+IfIaUttiMA8YYENmDIUo6mMWlXgqirLP0iFOPBB7euln6UjdzxMrOd1V4mWpMjD1eFADdjHBrEM9j2Wxy1QmBaoyUN4dTgkhqSEkxWWzDokjWJxdIvWgY16IwYWXgc110rKIqyufn5zg7O8MwRGy2cnohcsTBwRIPPHAZy36BS4c9HJs3GgCOSzW5bEgZUTOXP/LoyGYrMWPYDhiHEbdun+D07BynZ2ucrwcFDMxIz/Deoe87JXo49L3H8qBH53ssFwdw3qHvezhH6HtC5z2ODg7hvMdyJZ5wFl0HRwTfSQgasCnzMr9CEqDi/GSD27fPgcQgHUfTVY3spkNeTXJUJyVabyp5BLlVvZsxq5fOiuRRVtjyofacMc3L8svpUXmzqNZHqln3Noa2FU1tLZvdVc5hWi5P/tYbyclG3sph4XkArGt/IXA4V04OMPQECzO8Q15bZS0sRA6nGzdXnWqJMSKMsVmvna6hyfYRRLLuzCTSWWaZZZZZZplllllmmWWWWX6P5MH0IB7Eg/n7+/z7cIqPD6LH8fExfGRcvXoZ43KBB65dxtVrlxHiFjEFjPEMISTo+Qn0ix6HRyt0nQcMD1Ksykxwst2vKBdUIx+tQXqf1c/VP1E5dMRJ86GCoBU7ZYVRcCk7n2O0xGbgU5xhjKMemBLclpxgcYtePTFHwS6dV6JHlENr4jVZwBtmOYCU8RaqcJmkpArD/kh6KoFzGO/6gL50ndbecKcKl8wYLEq4j9K2uheLQdMOwxgxRbyYQA88WtoWiDd7f80/sU++87j+4FWslkusFkuQuvI1/IomdbaKW8h0ngweEamnjIKon52f4+lnbwApwhvYaWZuM75WDJeUEu7cPVWcqBNYN/eUpsEIZiF5yOFEw5QUk9JQKCm3uaC8rgkHhDIHM5nCQHwu46AFW/mC4Rle2/ZrIdNMuq1KzNpXranbyqCMEZZ5UcoyDBnE5fnM4VdY+pPldy7Zwg4EJmaMoxwWDJERgoWLSej6DocHS3jvsezt8KnN4aoe9onNwwwKX4LseeWMW6eYsN5sMYwjhmHEOEY9nGx9zCAn4XWE2EHwjuB7IfB0Xg4Leg2/5PQw30K9zXgvz6xf2u+lrlQsJ/lA9LgN2GxGBTht8mq7uByQLK0tE93mTeORO3dKdTCtkuxVp3Tc5DFv59PeCbRXbB2tykEZm7YOJT1nAHqKZFfZTsu4qPi910o9rC5ykNTWQmDaJWZLIMi6/dinP4nHfv+TGUMOw4A7Tz+ra6+tF3oIOnIuO49d/RpRVJ4vaMYsn7ry+OOP413vehdu3LjxkpZz/fp1PP744y9pGbO8PHLfRI+Dg6P8kgwx4PbdU4zDgNPT2xjGLYb1Bl5cd4CTvMw7GDXACdkhK3rICqFdIVJXeFy9R6pVtnaIbz85fc8n3RlYhA+axCIjFGOevDLM+Ra1i76+TyQ+YoTFSYwhgBLDg+D6Xl7Y3sGrpwsCEL28dZ268Fv2PVLy2R2fedkoxtz2DSTsUZ+pFGUjQ+qBofSXvSy81V/fc2ZntBeJs42AdpTL7PWiYElfN6olyHl05LKi442YohogVS98BuVNhHSlefkQ2z0lCUWzGQe4ENRLCGMMoxhf0zkYpGEyAsKwRggDxuARks9zg5yQT2IKiHFUZRF4/uZtIGxBmQGt/dcYc03hEaVvHM4RnQeok37R5jklBsUkXltCTAjB4oWWEBvmAa4JW8JF3eCs3LISiMSpiCm9BIBrj4tVJok531ur56aSFPJGuc5Q7yGwkwEoGz1CZpwzZ1cxkMexzEFTNU3JY0DjFhZGqmxggMSiBA+DhM4RxTiIRw+OiDEghgDnPQ6PlqIQO4/FssfRoYTusecEumGg3F5kJZWZMY4BKTGGISLGhO12LYzrxIhJNgQxJKzXG2yHEdthRAgxE0HA5rYQAEVZZ0JCCBKOxdGIrgtC4PBCPnNeFPpFL5s531Xhl0hY5TLWMieMGJA4ITLj9GwD5x1cInCyvi/t45QQI8pYNmCEPZOVtx2TKQPeFH8wKJXfGUZaUNKbbXq5rKKWd7uxLluPPOBU5na9mZtWwjarrBs22yyWsdW0tU5e1X8fkWO/TH5jez5J56eStlzpV0JxWWrrmLSJdrJKnHLoLskXcN5V63BpFxt5S0ux0zOzzDLLLLPMMssss8wyyyyzzPJSys5+FozL6TIA4IROXnbPHl23gO8svHTC+WaD/uwMw7BBjBFxlJC7qKLZFj/CRl6w2Kl1znZ0paAbXH4SmVzIu3aqf+YJvFIKEYezmopb1INqFKXCkCU8ihpvYwKSYj7eZYzCDvoRAM6YnXz3zsMxZc8fXBe+B0M2zLfGye2vI+ykhx5aqVucKoyz5swYxlW8QE8LmRwq00MxrPVtCDelA/PX1u8E5d9ztGcGQoyglJQUwoWwoYcaU5RDZSkFDZlBmWBBmhmRYjypnMo5X2+AFLKX5arZZX7kfpc0KY4a/kfyMS/UhulJeA49kJYYIAnHUSFsDWaMqsxCxCi4K1N9lqvgpPuk4G/7wagm7E65o3nOULW9OcRV41378s7VK8+KPQ/WEHm8EziJfSUl1oN58lnIQTJGRA79ooMjIcD4zqHvFzlsvVWwxRm1Vfo9RpkzUYlUIQQ5YMoy5DHJ4dJxDIghIlg98kFGxdgTECGH/CgRkgOiYqqjs0OUpCGV5LN3A4q3aFKbTOtpuB4T82A+DCETShAnJAtbXxg7z0uZA2gx5HpC74FaGeaRptSK1DaS8f8yrB+BTCb5Xgy5bprN+bwi30fBkzSMFlOfvi9q7yLVXNXSc7J6iaXJvXX2Zu968IlPA4Fw60Mfxp2nn22aTK7YZdrWTAdj5+U2yyx4/PHHZxLGLL9ruW+ix+HRMZgZ6+0GYxzw7PPP4fT0FLefv4VxO+Dg6BBd30E8VxAcJ3QQcoQo6B3Mx0Rm/qKoC6agEqlL/rzWFeOgLYGm/DsPmDKUuBg0PUgVU1tUi1s41vszCYJcZhNbmYkTYgoIY8BmPeSXjncOy+VCjb5iPPQkbPPOi0sur25FOrfICmwOpQKo0Z3yi96aSuTgTbOuGMrkCB281q06tp/LBoCYFXT7zZR7MUwL25RTcUlnjGuYAds2RyyGa3IEb+SUTJzNJk5oUlRN06J148KAN08QibFWt0Np3CKmhNNtxBgZ4WxEHCJOz+5iO6xxdnIL280ZzocVNmMvTHAQyAXABaQ0IMWtlqEuAllDiiixw5tCrt3DetRePMhEbLcnOqXEg4nzXhm64oYvcdIYmgkxMghRNwpShjiH0T5ulIRqowSZj2OKYnTvpDLOOss8e+ShlsmZUrxAQZd+l1AzLs9pGxNHDo48qsGCefCgzuvXyhBPkheY27mjZdnzYpUU5VtIO0MYEGLA2dkGm82IO3fPcHa2FuWdEha9x2rZ4/j4CJevHGDVL3C0OoDzHfxiIYqjuq/kqsQ6hE6ChOjZbIW4cfdkjWEY8cKNF7DZbDCEhGgeO3iiLhHys279I15rKKcHAMqhbJ32oc5r3dQa/al4CpI6E+mpAlKih9XaiEUxKaPbgZ0TT0BcnfzghBjEdWen86LuB5sfAMxlRbOh3tG689fMXReCmSOM2UNOOV0y1btrpZObDNH+ki/vOpgjruaMpjcvM1XQJzQ+NWV3Vp0KKE3dzzsv7WwbDnVNyoA63/Cua7ai5Fx59jSP8uTKvGYlWpVmykbHKVkve/Kwd00O8OXyuwQX9uAss8wyyyyzzDLLLLPMMssss7x08gA/gAfiA3jKP4VTPn1ZbUj9YoG+Fy+6kRPOzs6Ak7vYnAnRo+97OK8HY8AgZjjFV8zjsyPZaws+UDemPv40tc7p5wp7qOEUQNG1Am02Rjm5YEZf5INc+aDUngMeaq5GinKoyBI4lFP/VoZh0RLiu4RcduTBEHxZDpZxDvc9NbS3RvqqIXrd5bAp7QQoXrTT5KyN1QEZ2zAMGawIUNV3ru5IGA6MghvT5HPpqF2shLR1XBz9MjPGoKHJNaTHEJJ4VR4iODKGcYsQR4zbjRwWjB1CssOTBFCCEC4imIOWUfqrNprvOh9JlQGZEcKgOBVV/VP1kx6SlANnACXBXHPf1pj5pPFM3FyPGlqenIWv1j6Z9Hk2jnONrNY5mQ0iD0ae0/lwpGLizQABelhUcb4KPLRZuA+zbj1AZMQaYAixgxOGUQ4LWuhtPWII78Wr8mK5wGrZofMefdfLGuC9pEttqYa8UVU+MyNEwfO3W/W4fH6OEILix9jBHzNQm6suvycwKBnurj1L5Xit/GsYcmvfaghDOb0NpobZsWlBEG/Q9hw4+SGTpqx1iRWjtCto/uaOmDi8aQHgyedqJC08TeTSZuuaaRb77s9515DvvYBRru6uMfwaC94XtoYmpU6S7Lzzsi1rUrz2L2vfW0SAfNvOuzO/DAACXvH61+OR170O7/rFd+Dmh55p7rODx3lu5rYahkx53attTbPMMsssH63cN9Hj/PQUIUY8d+MFbDZb3Ll9B9vNFiEEMYzHAYyI7fkaKUQ89zsfwOHY4eT52zkPU4xqhqj9kmDmVjTp81KvbxZZ12VRjMleA9VLUSXV19jeoDXJQddSJws7JzHkJo4IMWAYRwlFEaO64OrgnIVUUYMfGDFFIVM0jGfS8rW2te5NRUlv1vGsvRVDobXVPHLkeIv5zV2bKitlW/vXjLsO5bK4XCsblFwFylSP3Q1T/XYHg7l4KEkwA2lSJdTppomxGTZ46gNPYbVaofOyweMYwClhPSaExEjbgBQTtoMo59vNgDAyYhxAiBC2NmnYFFHQTVkSrx6tkp7DttjGqGq7Q72pYVGoWcgVxKTKFalnCmOMJysJppAxp13lsPYLV7E+vb7kyyazGl/OXaoVRpkr9Qvf7rR+l6MBcHBaFMsc8U496qTy7DSbClEsLbSG5Z+nJ6tbPS1zGANiijg/XyOEKG41k8x58egxSvzJ3uHy1SN0XlzU9d6j70VJ7/se3nswAZEj4rBFignDMIinjtG8vEifWlzGqKzqYSvhYDabASEEbLYDxmBhWTDZKNpGB3ke1AuKhe9opTycKd+f9BlOqnRLmsQGQKS8mWvuM+WeZfScc2Dvypysa6kbwZg0lAs5mJeafDqCWfOsSQlc5VE10MLgaJOSEWCqsW/pGVzub/qwmip57ljt2+cpb0qqamQeis6rxutNnTCvLdlp3bQGL3olL5ko7wfSzynG3AbSStnyO/VsYv2Vooxn6bLy3DJYpwGV+ZW7vlo3jQy2U/dZZplllllmmWWWWWaZZZZZZnlppDbCHqdjPIyHcU7nOKWXh/AxDgO22y1O7p7g/O4JNpsNFsOYcTbmCI4JcRSM8OzmHXQB2J7vxqbfV/172RDzTROAOUeZZW7xWCiunEsyYAPZ24WgIuVLPtiX5JBSjHLIJiXBi3LYBzNEavpi6qN8vc7fwp03wLVCMgU/RPWldEi2i1LVDhiGTAWE1BAlBQ+2+pX61NkwSl2orsCEpIDpN0LBuNl6WcsSNks5wAfxHn7nzh10XacH2QR/BTPGqJichvaIMSClqB59AeYolgW2lkm4FFgYm7q9XBpZQlQXfKjGt+wCV31X+jOJuYErEgGnqr+ki6YkiNwvzQCIuLbjS2VQhr79YMNQ2wP0A1c4L4rX69w4w8oyRmb90o4xW/ihyRhPMWTD0sdxVI8dkGdC+y8qCcN5wtL36qlDDr167+A7Lwcxs1dqOXxZvK6rpw4bDzav2HYwD4hBroUQ5ACn4cepzD1MmihloRGbrxmvx5TgZZNE7EkZ17Q5kw+Rce7u2tNz87xZVRzJlG0qWirEIPUYg4rkZeNRgaJ1Faffc61o96cp5tr2SCljH4aM8rzsP7xaZbr35sk8rtPWf1FhyDu/AWWQyvo0bU++Wj+WSWxEVI2fzXm2ehHn90HSJJdf8TBe9Yf+IO4+8xxuP/NcyZhZcWp7VkoNmhGYkEJmmWWWWT4auW+ix+2bN7HdDvit33oPzs/XqiEzLCxGGreIgXF66ya26zXe899/A6e/eQMvjC+gfvmY4mpSL7upukI5vVwjlNAkpjNFrYOH6ShCiJDXe73Smxpd+QTMl8v3GEclHERst0pg4YiF67BcLsSFnpItQrTaSNiHRbfIDHDxWNK2oxjcG1NtVZGKhavvK9GjCV5DcgDC9rUT5bX5FwR4Z0QQdWVnPyeoo4e2V+XL7ktl7wvGdgxkmxko2UVJE0rKMItrACOsz/Drv/7rICKsFpfgXJdP/gdVzjJRgwAihoQXITCCjhcBcEIEyKzzSoElY31rHEpUfRdZGfPI8TABYUgX/YbBMeZtAKO4ejODu5npywagKGfUlFhpiizs685lXzX6rk82JHL/RFF0mW09ValIdQ3ZEDvqlBwgXjngPdA5cAjgMMLIAwArQ9U0FKv/ZD5YX0DmCjOwHrbYDCOeefYmzs+32A5bxBDhnHgV8Z141bn+4BVcuXqMo+UBjpYrkG4gJJSJeLdIxEgpYhwCxnHE+Zl46Dg5WSPGhGGQ0C+bYRBlPCIrxoV1XdYb69PcfbkJ+nS1xxPkcmo6u+oCy7so1PZsERHYGNM5T5uX9hzaGInGl0+gOAcHD3MzOdWGU7L+cehsEbMVg4BMwsljVt1cKehl5JDvN+KCRrwt6xDaKTDNJ6dk5DmTTyiYspvn/nSlKM9ldv3ZFDOtf0l8v2rtNNWOgq5zPOrpD/K2vhlBj3UpdiCjFrLEw42R2zKIlNxhZB35vRDGpFgjFXoHUDWGs8wyyyyzzDLLLLPMMssss8zyeykEyp49Pug+iFP/8oRw2azXWJ+d4YUbN3F65y7OTs+xWG+RzVwxgAkYNmuEccStDz2P7XNnWN8+BRp8Y2qtLFJjq1MMGahwNyo4CVAfhqtTT0vaY5GsD9cxwEkOCiYLS8FC5ehIvLfWXkLsMI6Fm/WKq0m5DDMmZ+xmCmnXf5tao0BNGcects1lw2XJR8OnWxYG9zRZU51cL9WBv+8hGR4tWGo52Q4wkhy4q8ZqCCOee+45gAidXwjmqfekBo+FwuBmX6gRXaAmMOzpuIwD7jSXdQxYMGTzgMJmtLXUamxn1n7L3ibqXqeCIzGQD/c1XdticdJd7WC3dIHJLZaqxqGs39nwMT2wRtXcMhuFU68tKUkooYxz7hnfaj5mnNKmqV4fY0SIEaena4xjQIhRDyKqN22S6XN4uMJqtUDfdVh4CalueF3SurLi3zGIp5xxHBFiwrAd8/MmHjzksGBia2s1lBmnR1t5lLrvdGjd5PrhqNrZ3FkdDptmVWZFSyTJ3iSqCuXedw6EBI67eKvNp8YThP1aPaS57XsHcbd2VqeCve+5y2xCF3RXjTk3IUv25FfyaVfbuo5lPavKtHtIn5Z96+LvxjMGy3pkz0yOQMBVNVnKzN5O9PDpw697LR5+7Wvw7v/2P3D76Wd1bHM8A61eU8HK3lAIh/S7qfcsnxQi9qJZZrlY9q3LF8l9Ez2ev/GCvKjHIIbjvDABSIzzWyfgYYuzu3cxbreIhzeBpQeSKfIXvxHaBb09CS5Kg70y9IWm7vucntA3G7ZcJzhlcuZXiym65GBeNix3O1U/hogQgrj5YjPcOXQkLsRMzHWgRU0hp0pIbkJZyEtrOYdPyLHfNAyEcw7OO5jLN1PI80ubkF8QBHtRtC/syt8EaqOpt/APkz0CJp9NCTBySk1o4MQljISydVlj6omynUqNlTTC4Byaw1pkXiBsSIqiXynjrPdan+UZkIriRs3o5fG1NhVlzl7UhEROyCB7H4yizNo8SkQyBxjZ60fjsaOUVs1q2snPlFVTQHb0+MlAZNY36jnUKqXWz7kHbPMSAVAC1ENE7h/WgDJcegWZEFOFAoLGrmRGCAkhJZyerbHdDhi34t2GiNB1HoeHB1j0PfqO4D3h+PAAi64HMUqcwxAxxogxhNyGlBhBveRsNwNCiFhvtqKkh6isaxtrVZ7ylOGitDcKe6Vs5m7hvYpjvTBm4lTdAWx9WtLYfqxZvqievzy5nZGonlPybDvv8jNfLRY6vWVTxUSi1FdrX6PRNs+NXKuVaVkrRTPlxCh75rqfdrnVVa+Uf8vD1M7AhjVe3U/1l/35m2eNvK7xfdy8U7Mqjea3uzUoqyXqvtRuSGxhglLZ4BvhrF5g9AZ7xtg8udREn6pYi8FKdHE7ZplllllmmWWWWWaZZZZZZpnlpRTDI474CNfT9Xx9Q5vfMw8f5+fnOF9vNJTt5EcGxs0WHCKGYYMUArhfq5vnsU14H1JjbVMMOeN4E0yu9kRAXHthVVxagZFd+5vhyKxeoatDIXrgyjlXYBjNIMOzFaxYn0onpoI/VjhFgWcV33PmmaHCnfQ/ripbWlRhyA0wXPdt7XWaq47aRVvq/EtWnPGZwq2o8BrFwjP2Uh9ygrY7FSO2tdcOeuUyqj6r0aGMDVutq0NjCpNXjWjbVfdFvlcPatZeoksCqvpJD2ftwc/qA2IVyIZmWGyO1dWifGW/VIlb3ItLXwLYM3FzT+XustNuFYZs2TfIoRETuKl4xifNk4d5fY7qRYMAkHPo+w7eeTgvz8ii78TjDcu95gnHnqlsDWDkZyyOQqgaQ5Bqq90n6bwxfHE6CoUXVE2CumvuucRMf6Q9P1eo/bTPd+ZdqU+NCwuuaJitHRyknXA1OxgnGFDv0DvmDm4/VPyoSZMUQ7bPe4Wb+fQivdJA0BdiyPuewxbG3bNmoczd/dN7cn23bCA3uUpcD4qB1a1Nr0lWP3Ma7+r44et47Pc/mTHls1u3cfvDz7T5WhZme0N1oHiWTzlZLBYAgNPTUxwfH7/MtZnl41m22y0AIOih5nvJfRM9fvt33isfWGMKmo2YCcwRNz/wNNY3b2EctuCUMB518IencO4I5A4wUQOzyJJI+rukcJnVrEWodwQPIWA47wEQHCdkYgNBFliCurpSxY5U/XFyn7NQConVYwdjDCPW2w1iTIhRFEmnMeKWi64sx8yijIDgXKdX5S0jDgg4t0laJUZBVuUlxYhxGBGjupeLScJbLHr4zsN3nZwzF21IiSvVqXxTwnb6UK5XvE44Io13KWTjWmWmcqN1cDMg4rFDlWpmIJIEbOMEByF5DKHE0yNy6P1CPBmoVxHzYOB8D+eAmAKE1Sg16DTCZVbIleQhfjugSoH1Z0JiILLMjUwmYSU1kEbL5CSMSADSa0HazAswCJ2FNDFN3Fi5GvvQQt8E24DA3r/q8g9eNyutlkFA1ff1Rki8iDQbuZR1ZBGNfahuWrLTCZdJN/oz2XUCwUNihkYkKDEpABQhxALnYOx15qjG/+Ixh+xcg+169HpMESElnJxvMAwjnr9xC9vNIN5tUkK/7NB1Do88chVXLh9j1Xn0ziEqv2QcR5xv1zg7W+P0dI31douz84166Ig6L0ibW23SoAox2zOkm4iqj8u/8jefxKi90VTaYNYHp3p2s/na3T41LOvqniYEiZFrpvfWZRCVTb5nndvI3mPy5gpKAJNOqDaJdUvkWWAwhOhpfSa/tGVjouS3u4idWucCUeVZMqsV7BLP1bWkmUlJe++3dFS/OwC+T+JqOYFTCsz5cftm4Zy+mUTiLjIZ3JGqvpW7FCspBZgurwCDjXsOs5OffAUnjLlNaWZjzzLLLLPMMssss8wyyyyzzPKyyjW+hqvxav7+nHsOZ/4MvLt7/5jLCy/cxvmdO3JoCGj228wJ6zsnGNcb9cbJiL2H6zagJIA23aOOLYZceSLQfw1DzuWqMS6HCwGhcUNqOIrmjlzfgnEWjE3wXfPkkXFgJwcDO6+eQxWHc4r5keKzBjTWUAjlv4XskQy3jrGElk4s2LH34rU4exAGMvGDCs5Wna5pCmox5PJbPhBVGVv3IhuTHxmlfwzfrctPrGGLc71IPZpAyT1UDgEqPpsyWKQYd10Ts9SSeiGoQEGbCcyTg1tSE5gVQqYQt/dYYB32efxaUzFloDEf6gOaQ43ZDQBZgPq6BykbeQv4RpM/dkC16sKct+Wh3ysTQSaflC7W6wWxM6Q7Vy8hk4YyUWV6mA31YaYWebNDetsxIMaIs/O1HvwT/Mx7B+cJR8cHWC17dE7CtFhUbfHUETAOI7bDiBAihjHAwsNL+8rolDpNzRmch7We7lwNYMHDf/dhMipOTK7EPgx5B6O0OhYYsdxL9lN1sNnJ+LBLez1TN+GGXL2a14ApV/OjKnuCIee1b7JUtPlR87FZUnYb2nZQ/jvBkGmanOvp26SbQLS71bMP9RKRk7TXq6tNNqUQasvTNX/3GG6NywOPvP41ePg1r873fuD/+XXx8JEP41YPMqMchGTFnH8P3smzfHxJ13W4fv06PvShDwEAjo+Ps74wyywmKSV84AMfwPn5OWKOLnKx3DfRoyYx5PeoKkZCDEjgFLPBmpwH+R5EHq13C5WsxNSv2UZ1U4WsGOPIta9kWyvJTVZtR0V30n/y/USy0HLCGEYM4yCeSoLUP8UI770yTl021DsqoT9qxTm7aNvDfMz+OYgQOEhIGUcgOHQgsEsSg84Y2bmh5ZUkXhZSY5K0l19hN9tLzZTNdszyRsUGrWEn1p5CSqiIZC95YyVw8V5BRHDOZwOoIydtqGrpSeIsOiqjnIWVvMJF1XSaqtlakSj7SestJA/rHlU0rI8rhYbN5SH7PE+oUvTzSKlibnEzS2/peOTdQhW9MhXNrrzcpybj3NCdMSihPuqND9SQrBsPLqSoxGXjUiIr2siVkpKSgMyObmQm6a/6rnoYhCQSxoAYE842W4SYcLbeYAwB282AMUR0nYSI8Z3ETdyuB/z/2fvXnlmS5DwQfMw9IjPfy7lVnarq6m52kxQpcihpRktdRotdDYQZLbDAAvsXhP1/A+x+ml2MdoiBgBFmF5jRQEvOUGR3k+xi1/3c3ktmRoS7234wN3fziHhPnb6QElVhVefNzAgPd3Nzjwizx83NbvgeR0eipCcgJiDGgBACzucJp9OAcZpKPsSYw5rZVCetGFqlvTxkiqK3UOeN/NZzAFaFs1UYi6MNqaK+lKeRkvlLi3rWys4mk8xdJ84RVKJ6tBe3aYH0UsrPizq3ybWa71xuBDQhN0kNG63RGBNyW6/vULF1otxzM23+gfBijdJu+dOdD9odLmdWSQ2StYhJ5fZfsSPInrSd49ncMb+ax27TEav0c2nY6P61oDnyy3pld67D9x9/H08PT3HRX/xSdW200UYbbbTRRhtttNFGG2307aMWbwUOfMAzfoaBB9zT/coC2K+SGL7r8P4Pv4cwTOgOh3xYULkmYgPnndEkm6sa/LN2pi6Qae8stkAKy9JK2XyFxSMUNzBgwEIcZdeWOCFETohRNu2lvDmOk/Duc6pvdZawjgANVqCg0vyUwci1Sc6YBkEdRrhg1A3GanfblxVbltQouc9cZA803g+KbaxAGBVDVt5RsGGtrvjKGAyv5jyoXVOMlTPGYzfZlPPmCFX4RaRWeCiIXEnrYsdU02LIfGiAmwrklLmC9gcv09JUDJlK0XmE4IJllz4Z+dqxnsOaMwxZfzV78jDDkBXfbDxA9LBuitTrKGeMyVI0426xRBl/NvgowUqBzTfZwBdLdI2UGGOQVNwxRMTEeX3AgXIEjzhFDAxMJBtbOeXtlCnJxsAQEaYokcBTxsbNnF3HkFcGSuXQrM9Y4deb4Z0QO52DOrSaAWmGY8/LtzKbsTgbtlphO0nK5jWq49lWJteV+Y483xVD1ghBC77MjbXK6wOys8/dBzDkxWXzg7xWt/29gtWujXHzwK+y+yYMeXVQCoasdc7bsxdKmTUM2TlXNjUygMtnT/HRb/8mTm9ucfPFV1iXq23rl8OQN/qbST/4wQ8AoDh7bLTRGqWU8Pnnn5d35n6/f7DsOzt6KFXPYNXPs5MHS+41ACA4uP4C7vAYFD0o5R3gWYl3AHTFvvgfU93mrS9L1+w0J7OjHKAcvQGEbBBQDgnI8mIjqokpcjXeSVuJE1KccDrd4eZ4DyQHRA8gADyh7w64POylTWY4Em/j5gWS/4tZHt42hLzLmxiO5DrORgF1Hh4dOt3xr1FIqjpb62cZwBgTnKspZBjIHtEha53S313fwzmCy0bIlKMoeNeJcUBynMg17xhGEg7ZgZkQWVMOMlyj0mUJOI+eOnDmgcjB+zyV8hzouxrxxCqt6moxBnEycNkYAmkikTqH5JfIzTuPPnvGM2e/c9bpa5RVIohrskS+kDalfylKb1L2humcq5FPiBATJFUNJHJJXTAXNxSZ5ylHAHHFoCDUaCDVCNBxSlknclmZzHO7GJ8yZzU8XWLZzZDYg5iygwSXcJAaOlDbUG/+lCPGEGJRapjVIMzyd9mRKu9IUMeM169vcR4mfPH1LYYxYJqm0k/nHZ49vsZu1wOQ3IcvvnqDcVQFXOLNJCaRMzESU3HqqNp5KxtgqbA1OpslrpFO6jWibCVgGU7RtlGU+NY40GdXVdnaOoyv1ewO4Hr9KrNoO0L52eW9GEQESJ6d2Bi/RXFPOZ1IThGlzOj8chSyYYX8mXmi+txY2jStAS92uij2tpk09xTP94lGlym7FGbG6DdRK6tqSRSjyOrSC3mvGE/55SM9lzs8vwJmvM2V52a/Skszo8U4yNtCps72ud1YSKabvyhd9Vf4r37jv8JH1x+hcz/3a3qjjTbaaKONNtpoo4022mijjRp6zI/xKDzCC/cCP/Y/nqEkv3raXV7gd//Z/xEMwa7q/haueBEAgECuB3V7kOsyPmzwYP3r0C7eW+AGujhaL2p+c946ZVboSv91sW9mx9cs1oJ7h2nEeRohYKGDeGNEdK4rGKhWX3HXtq2kmKCeIxQ5FCwIFXPWzYI+81jXhGfMMsCUzKYvkqoyxlI3lhVxwXuX62SAFJfMKcvLojhDI/DCyEPHhDm7wahohZGWPRL+ZchTxqd1VTRj6jndTZu+pmJ6MUdZrc40puNQLJ3BxDkdO8E5s0jLVbYV6WmYrJtJdTNYIoXcZcx0c2Vez5BlDs6tz7EoMusgVHBvlb+VqcWQHwCjDKds8DSNHVwxvpJ6eFa+yDPj4AzUNRxdGC+4a3s/kSmfUsL5PGAKCfdH2SyYUmzG5nDYwXsPxfeP9xJBvfIseDUg0UJ0U+a874un0xLiW1Kdtpn3tmyTfWb+2dTJjUzUaaYc0gk/b6dcrjjtHENeYXiO4aojVNQVGXPT5p+aLoj0dPE+qddrlHmUew91Q57lfcaO/V7u81K3EZXFPw0P5f75BTHk0hjRAxet4LBFEChzsa1zGbGprdLUVYrZZ8tK+RXsV/1Fnv/w+3j2vY/x2R//Kf7w//XfIebo3qtgsX3IbPStIiLCD3/4Q3jv8Qd/8AcljcsWJXwjJWbG+XxGjBGvX7/Ghx9+iO9+97sPlv8FVpDWJpsqO4UNpBgQpxEJO6Ck6bDJLeQCgi6Sq0rIAFKzpKbvDqeRCdg892vPAWhoffMSNYoTcwSBMI4TpmnENEVwzOliHIHIw5EqmPXpzpAFew2jxVzDyLW6ABeliki8p70XZwPvfONxKl7YRkk0i7Gq+ljHw9LF2iVRvosiSvXlXTw+TQoLVpnXcIOr48rti4xNLfalROacyDs116/WbpTRzG75BIxCnzvoQHUmcFZa1dgpWgZjdlnDJcG84EnnH+cxaOespPMRZYKcl9V0E6Ku5l1UP+mWZObW8sUBoVFOsvGR+7AIDwlXe2JuNbuI3ThPJAY7o4nYcihiE0oJkRnTEBFTwnAeEULA7d0Zwxgkn2KoHtSaLmScgtSRHTvGKWAKWZnP87RwUPL7EarWVwVUxigbRVW55HK+EWg5Yic/1cpWxoEWynTLo0iIcwg1VIVKjRnMIqfMFPfKkY4hGt2cylmqCnTmy3lX0kaBTeWlz7Pwmdrt0rY+K7JsbRNZkbfPLjRz3Pa/1SPrHJzzk/tWBEimWFu+7f+cVKLm/qjVtxVoCfVOX7Sw1PVlmK0yr5NtyU2V7mxg9SjXy1evs8VNtBxz1y3a/HmJiND7Hju/e6fyzMDN5+/j/uUT3H397Jduf6ONNtpoo4022mijjTbaaKP/uEjTZO95jyf8BCOPONLxISP+lyYigu87LFfDCESt3SzRMSKu3nuK57/xA1w+fSx1tAa4gb1aC7zs4Z4DEwa2aO320nDGcxTDq4hOymBqzIvZUXfcgGr0YpKF87qwa/AJw+BKXAbBE7jssdd9iwAUJzebHUEF921QWcWKaA5iMNhunjTyawtWHrQd6YrBXwRotpybv5T7ajFkSzMgTY8YrGxetDmeMb2CeT00V1kxJHNdaVr5a+eIQEb2Aps2xco6H2l+K87IuVyO4qs43bzTa6RYm1b+IFWnA1KsUSvQxpQ5hZN1yBrcFUBisFcGzdisyF4dRjR9UMx48TAGhBgluk3SNMfKJyHGVPFalrQ9JQKOVCybNIGcov5heZnbCsWByGDFD2LItPZbhDKHmsnKydbbPEu48lKutc8LLDZmkj5b5rAmNV8aRsomwDy05EjGLD+feH7Z2lOtyNd0wDJhijfF7LGmerl/7HyqcD/PWLDjOedz7dh83r8NXbXnzDOpYO62m8srlzXN68N8MjxM9r4itH1mgJxHt/O4fPIYz3/9Bzjf3uH26xd57WwFQ17JErDRt4e+//3v45/9s3+GP/iDP8Dt7e3KhteNvu1ERPj+97+Pf/7P/zk++OCDB8v90luFxetZIhw4J4+rxAnj+YjT3WuE3WNwL1EtHNXULKoEOlcVZFViiT1kAVkWmHU9VqNBcIkYkOsg9VDMnqx5Z3qK8qSVWAkSGSJxwvF4wvl0zilcAN8R+t6j8z36Xpw84jSJp2vXA8xIaQKB4FwHZiDEJItxXQcCkCDKTZjEkxVOduYfnIejDvt+j13PSCmAOQLw8qIuzgdCjOwsYO5pjciQEhfFlhxhR7IIyDlSB7KTSSje4K68gBk5PQoTQhIlzakndB4/SdDHqEYLyovT8phtEYgThY55yC82KTn3k9YfqgQ65/LYG09xU5ogUQwcu+IdrlEvirMHEogBnz2AEzyIgc4Zx6MSNUX6CQYoyDzxXgwyHbsYxXBzvgf5DsAoERbyf0zULI7b8HwyAtmXmkWhI8CkFRK5qlNPynmVZOrrPCBwifyRPaIdFYMFADjWiDcMcU6JU8je+l7GNJ+L+cZRRTqkhGGY8PWrWwzDiFevbhFDwpTzJybNiQmflXkGYsLrN8d8v1YFvigl1jDRvvDSEUZ50r/ErlWctUdGBxe2jfad53HVLmvtJbVUw08tVxWu/Gww95juJChOAq46D1mDV7aP1NHUCBcyoo25V2wIvYAoP+ucgww95XshNAZGyo5q5Gv/OY+/1OT1aVbuAnkE5/lVLF+r8L5dQUgPFckDVFKpGoPD9rwU1nk504eJzMibubxqUdSLjFzrLgXMnixqUpU5yeq8k+s1VtDcI9bGc6kDWw1UM0GMXKsMAMv9W6KF/HUQE378P/zv8KN/9Q8Qxi0CyEYbbbTRRhtttNFGG2200Ubr9Igf4W+Hv41X7hV+7H8sqZX/ymi+CKn4hit4IoMRw4QwDfje3/ldPP2934PvOxC5hZVd037Uuh3UzSM1qWxd2VlOBUFgzvhJwQ0qxqQpkRVFShD8TdJ9h+Lw4BwVPNHlUBUpCUYMjUzBMWOCulmQM6acN0LmTXgpZh5KFAVJIe59Bw/BuQXr1lC9FnkoiEgDrehGscaHwAE+x6KWlA6KsZlLS5QNNIvaIgfFRnO7Bc/JOLXlaYbr1SAdiqVkNCuhLvgDTR/K4inn6MaKnxe8SzGf/M9VfL1gpjqeihNmGTvkdYW8Ka+mHM/CKpiVU/BPrstzj/O80M2C5HxekI9t32kdGa0i4gpvFsegRpgZ5KS6ubKIX0Epn8tnJwrKkSfKvlDKjgJVXIi6yFJlJnIy+GnGX0OIOOZNgufTiJRYnDZQsWllOEnIZZyHKUfesfh1WW6omFu+9dQhogLNtv/qCGU2gtlyD8KdOgeM3OcXNPwAi91wZooXVNNimgbvrbdgixLaenT9AGgx5FK+bF7LI6fzjRxSrOsg7TWGE723yjGpi8s8q7w1z9BmvmFlHKj5ys3hpvMzCWhdcze3fGIe+afwMx8rmn2a7zM+7WbetkMzsuPVTI/a9hJDnt3LeR43ziUM84wmvPf97+HxRx/iq5/8Of7tf/P/RgzjkhfL7kbfWvrBD36Af/Ev/gXO5/Pm6LHRgpxz2O/33xjt5Z1XhGq+vLZCAiFRfgAW91Z5U1LzEtFlO86KvRxnzukX5Fcpz5xyugoYpbu8RnNp8+Lm+UNXlS8gcpC8bzkViiyysyhz5NB5j67z8HkhllMqO+5VGV3cYoZ/Np/qYY2cN7EowFmpV4cBlV3WrWyF0JCBemNrGpWcpBHsJOWNJLfjHFmheue/zSFYdeDieWx7yAzmCOd88YTWCCltlAPzFtQXtuoab/F+tAYE1Y7X0WL9B+MRXOVkR6FyUNN6lBOqPapzRIryovUe5Bz2Fz2cc7i62MM7V4y3cZL8gr7bgcgjpRGcokS6mAJ4SnnRm7OjABeubFeyDWUUT+VnRbEs+gqpOHPnHCSdTYKq+0xqZ1CZb3Ipl3tPj6aUSgi9kPMmhhAwjAHH4xnjGKS/MSFGMxca60rrqvPPippt0XKwzpLm8PzenL+03vKcskW5HKhKm03PIvKw1/CsjqqAqrG4uLv1XmZbA0y0kjUeGYuno7M/6hl1igMAThrBRZ8huS/5u4Or81h5WxU81cfv0jJaKb9+j7YlWlW8ipCXE36dpea5UXeT0OLSB56yaxU2VgWVufaAVaGyap41lP+fKeRr8rBOMzPi5o/ef//+KI49xuPFv0cONtpoo4022mijjTbaaKONNvoPnVz+b897POJHJWJxRMSJTr+aRjI22Ky7ZeyTkb83kKCU9X2H3u0WYLZdwJN14Xq+YCWKKvAMYS44Ajf4RXGQMFidOIXoZqhcZ9794jK24IhyVOiaRkSiFSgiwwUfWENGGZANigoX63WzddAqt4ql0GqlipVUdIRK37SLJBgVc3EaqJDlCp5VK6qAWnaaaMGPVDZPVbzORnCdYcilTdtA7caSBTbnqI6XwQDl0BwxLhzNDuU+NII03y3eRoLx+96VjZ55L56sNZSNjB4gJ9gzJ4lgERNiikXWBcbMuCItUtSsyWBddpbqEoyJqaL3Wca9CtOlX4zqCVLXNFKeGxrlWXHlaZwQo/RL1kse4MmkvKnRauokXGSnsBDhorp8QV0qqSIxePAaLdZIrTeEEWkV/1LOLd5nj5qNhvkP53El1pWL2f3c3MvKUr5P7LqBjpNWbC7QNEyI5rmn2HV+LpU093Yqa0fXFo4Jy+lWOjant2DIOsRmA6Y2u3qJ7XMZ4yrTsilvFrFjtZ41tmw/ZnProam21h+oA5JB2utji/XhPeOpfYg777HzDhdPHuHZ9z5GDBMAIIwT7l+8qlPj7fD8Rt8SIiJcXGy4/ka/OL2zo0fnc9H84vbqVJCAxATnPch7ABGECA+Hjhw8eYk0AHn5VN1MXn4pibKQ/bnNg1g8ouXFJwdDkFOOVFGSz5DyQzdHJCAnrUn8h4TzeMYURsQg4cIIwM47kJMwe7tdj8N+3yry0kJJ70B5wZVJHsDqVDHlyAxKvhMniZzpEEQSHaF4/AK5pzmKQHM1ZY919WlPCIkxhQgiwJeoDg7wAHWExAmnYQAA7PxOwvtlY6PkJcy1Z/cEpOyoQJxAyCHU4BFTQEoBfd9j1/XiJJCSpLLxhcOiEBddQdzTZaG5M+YBV+U+ZSnkRJRwXhRlzuHbUgxZmdR6CYlF6XGYvSuz3Bxk7oXctvdcvKuFBQfmhBBGgChHbOnw/ofPcXHY48P3H2O/6xDYi1KcJiA7ejjXYeKEyAmff/YZXr54gfsbifQSU0JIofDkHaHrZM55eOFZlf/y2tbUNiIRZ6MZEJDyHeIoR8MgnxWjUMYNgDireIJEdEhFG0hFKZfIHNMYcTqNOJ7OePH6FtM04XQ6S7lYlXiZF0a7NkafHpoHFXs7zTTFhQZFs8NqMD6goJfyef7oR+HdaHCEKma2USBqO0YdB8HUq+0wkGLIzxlVqPP9lHdo2DqK8gpVrms/ddeE8GvadQ7eeVB2OONsBColTkhTkqg3u8xXyrOpGGHIxqE+E2u0kYYNqMjMfCvCry52D45vOW019VprU6j6rOTnvBp3soPFOTOWjbMOZt/zkcYQMV4z+d5WW6CNiaR1qQtIMzpNFVSOG6uLxIAi6zRnu72QYa2PYb3vN9poo4022mijjTbaaKONNtroP1y65mv8dvjt8vuO7vCj7ke/krqdRocoURQq5sJJcFuiCiIoJkyUsVqYy816mmJZNboE6sKtWdAl5AgDqHiijS5QmEHFMAVmSQghyCJ9qhEJPJFgzSTRPAQj1+iiZsE1OxJQXsDkwo+0Ee1ONZZdmrq5jgAQuXIN54VGi3m02KiiGgbdYmQsPUc0YYAT5c1Ggn+EIDi2d75iN6iYRtn0VCKiVEStOlQIHs2c4J2kQNexcXNIpGDIdeOSttGkSjFURkrXel3e6KNjyKnZAJfKDLMbKmu1FS6jHC07R7LOY1QcbphlcyhBNkF6h4urS/Sdl82C3gl+y5AFkezoQeQk7i4z7u7ucDoeMQ5SV4mgnOdpja6d1wfILiLPAT0zR206nTwniLgZQ10JKX3Om1Dn0Qh0TBWfi0kilI8h4HQaEFOUDY/azTJ2dXQqi2yrRpuWaTYA7WC8BZJUbHl+4psw5HUqTl2lUH0e0bwPpqYWQ277kqdydZwqUXlQ6yZTh4FlF9xqFIgmiLFcQDqGnGMvMRdHMWTeOUa5R/J6mN2Y2rSU2VjdFW4OLdlU5t9+XVNsMRizA8UByTCGvCGTyQYYAhbjY9ue8TWfN/m3xZBnM9h0g0t5NvU0T1q7iZdsiTox5hjyk+98hL//f/0/l6NvPvsC//a/+ZeGwQ1H3mijjX55+jljvNuHX312zjdLAwTqdqD+MqfAyAoj7GuGUBWW5YuGqf4mo9W3ryotXH+XKwiIQXLGyb9UXtzOuaykE+CoLECqAi2GhcsvU6MklqgkVQh2mVDTb5TPzAdI9b+iGgNGDqSGQVYCKIckqPU6OMpGQ32LQKOetH3Xc1w/qSrEVv4MZE9cS1QMpIVCMPttW9aoEs2iqyrKyAoysiMDAfu+g3cu57oEhmFEQsyWWE7RYpwR8lBZfayMjctjU+ZRUXhlrPvdhZTtdvBdhxQjQpgwnAfJNZjT6HCYAE7ougTnfHalYOx2PZ48fowwBBzvztBELahTYqFXLFUQo+lwLaEKS3VOqfdEVQarkla1UKlV53YoETzEcSqMEefzhNN5wDmH2RtzWiGej3kzcR5ge01d5lkxLWfzJtrbfVlDU4+9O1ZlyVRltVZJybXIZf40/ZsZJY3pUR9HZYhkTJRxzlFu6pNsvUeVceccXOfL/STRhDRnJ5V7XSP8gCDZk7T2orxzMWIa3ZYAu1PFDlPb9/Z5UjtpBmdmvtT5+GD3llSsnPykssbdN+qstDoP593VbzQ7SPPBVInMno/LkX831ixfvNIt1pyVrSX310iMy/fe4L0ffIrj68c431z/dTOw0UYbbbTRRhtttNFGG2200d8gcnDYYVd+77HHFV/hxCdrdf8SJODKMiCoWQnLhjo5D7gO59t7vDmNODy6wuH6yiyqUVtHBaHyd2P7f9MC4xpUQUDKuHFKSZw8Cu5HZSMQHK3IxmChumCrO74VZSnggcV626ttH8umOqBGZgBkAZQyLlXw3nkXqXGgaNr+BqyiScfBBn/ncsgUrjzz7PDbYMY66PZ3+72mrZAjJfV2kj5E1s1vZpXAYK0NnEfzVtpvuuaguH/Xd4LLO1+jfidCCNn5h2STIjhCHD1kMV5dLHwOsZ5iwjSGBU+NkNbkOpei7dfi4kais/5xvU/yJSlVrL35HhNCSJjChBCiYMuaLmQ1xcYDtGRtjcEHu7qKIT9wXcGQ5xNuVqhBQwt/+YuBDWuEnzlveu+Z7tjNm/OxNOO8dI55gFmGcdTIeDBr9KJ6zUKMtmsFr1wBVCvnpexqBKEHx2mF//JVO/1NdaxVuTL4BlteimpNftScLUcNfzTrX1PDfCxLUSrTxDaw5iOzSqZa5z32V5fl1OHxIzz+8APsLg8g7/49YMgbbbTRf4z07o4eMchndnlNqigRAC+KlebQYHJwj57Df/DroNMRGIcSRQJSEs4RXHak8F6iYHiSsBHqjZy6JLnkAueXvDSaIN7HLkdBkFBxyFE0AM677s/nE87DIKlNmNF3O/i+Q9d5dN7lp74s0IWYSiQG33n4rs+caogAV5VwVfKZq7cldbkPjOpoQIs3gCrjkSU9jHcenhxCjAgxwnuP3vd5wT7CkcPlbg8GI3E09QBjmMBI6L0w4bxIIOb+xiQS98Y9mCHexo4IKe+071xOW0NOMoaQeIAzCKCuNFhCgDEQU843SS7vgM+mSR5DCVuY54LzuLx4JDkmdz28Jzx71GHXOZyHhCkwXrw64f4UkMINUjwjJSCkKGHiUsLOEXaOVAuXOeM8OkdAJ/kKOWmEC58NgYTD5R7f/bWP4ZzH6W7COE549fVXCCHgMxLnE+p6MBHO5xNCjNh7cULpevHU/+3f+m381u/9Jv7oj/4dXr06gmiCI4m44NUFPGuhOjero087/tW+klB4Id86lKPUOO1jMRJlpnMawRwgoVxI7rWUcHt/wu3dCefzhONpxBgCztOIlCA5/BKXsHviYtBqKG00hNTYANbxYU2RqdEwhF+rwJJGZpmbq8b7f16brbUG45hpOzOrtNUfudS/ls+Mzd9GeSPdFZAWSrLuxgAA51JrQBcllqpxrSeIsD/scTjsS6SV8+mMYTqDiyEu9wvlsDUSYcdECGJGmCZ53vgOrcyMpcq1v0l3h6x4I5SRKAOcO7Mytmtqcs0BakuqwcN1u0yeMJx/s0ZDyrOhgi7LKBt2QNdtkoW1VC/mlQOuVZhLsYXji+3SWh7VB4qu1cI2UspfExHwW//0f8YP/9Ef4X/9f/4f8Cf//T/+621/o4022mijjTbaaKONNtpoo7/RdMEX+K3wW7iO1/if+H/CCb9EGpcSTkP+GBggh+1lY9cTaH8FunyCT/4//wr/7t/8//C3/sk/wA//wX9WqtOoFyBNmQJoypCCs7mMCc2Cu1YUKi9yoqao1sqZJd1xCOpAIBvWnHeCX5cwFbLyJ1FFUPlwHgZoAdhGK8kFS4QOQLer1+gX7abCUk2+TlNOS6QUiTgr0TMIznnIZieJlt37jMsqxpUhoMiCFbu8i043z6XsLKEb7Sz2C5iIAhn3c1n+3lETEUGurtFYG/SxpIuhAkuZLxWjyRsI+34v0U6yg8dhL/hrCOKgcDwHTFMCpwHMk0Qbh5xLSPCgjNdmyhG9FXNlXRXnOhZEjK7v8OjJNQgOYYqIIeJ0PCKlhFvd3JijJoQwISXB9R0RnBeZvv/e+3jv6TN8+dULnE4TQAnEESXVjwFeJU1QnYvVgcDwTlk+ddmlYIdEulHLAn8kaWSQIJGuc5UpYRwDhikgTBFT0I2DUUSRMp6qaztaYQsjG4A4lyCzZo88zRfeF2wraA4zUDDkhmylD2LI+X5mWhxf/U32kw3++CBCuIKB1sgyNWwH53s118b6zHqgMvv8yTL2naxXKWYZQshRVajKU6MgUcrYah6r3J8UdZ65ttnlIDYbfNeGZ8F7GQpuh5Hr4bJR0fZ9DTZlRtN4nuMNKyRvDjKbVXnOld4uc37sUoctt+gQtQXsxr3yc4mvt5fPKn+HzX9X7z/Ff/p/+T+BHGF3efH2+bfRRhtt9I70zo4e8+d5eaIRW90cZuURSBF2/719bDFDPLONgqPudoT8QCdRaos+rOuTZiHQvjj02Z9SRMqODikv/hNyJI8cmk5eKuJv60yotLKYmZUru55Y3985RD+hKGkqk/m7xKaYqIZNfeiTvqhJU8TQvHThyUEUuGRffkV5mL3RZi80CU2V2jqLUpDlbrzNrRd30X805xzPedM2xcAgR+g7D5CmJHHife3U+cWJI0KS6xwRDhcHUJcQp4gUHc6nEeMwZZnOFUTATibKE6ZKhXMkjw5d34k+yyzzIkr4uWmawBylf14Up/NwRowRyXt459AHB9+JY8V+v0fX9WLgwER6eWBBt86HuaZRf6m3cFGkCYjZgyoluYdCUu/qEZwCGE7uiezocTyecTwNOA8TTucRU4g4h1FyIubbcOmq+zCt6j65ipku/lCnS99zEpqm6fZZYa6ZRd9ozIqm3rdwu3DueId+01I8D17Bc3hgyQllK5dVaTb/kD+bW1OdRByBk979eYdGvjVVybdWf2MCVbt4XQ7z22dNTnrf26JroSsW163VV4+Vv2vPbFB5nv781I4950O0KIMl7ytOHq2u/osp2CUfZuXor42IgP3VGbvLM/qL4a+17Y022mijjTbaaKONNtpoo43+5pODwx577Hj3INb1c5HFKox5XiEAxSAzeMUJ4/mM080NpnFsqhKb39rZFhOwYACh2boxW3NrMOTCT96oxiaCAbguzMPiFjZVRqlhubg3w8+adW9uzljWm3MPZKfIZS02q/JDwal18ZtJZaFbbxpoacZwrsPxTIormGxhYw5IzTBkHYAFFpgxdcjmQaeRDPKcEPxYa6PiiKAtdF0HcilHYSFxyojRLlpU3hsniKa3jTi9F8celZZieRKdNxbeiOR7iEGcI5ykefapRmTwXVc2twpePZP9DGRtUbmlzJspoyND6qRTN1rpRjNOEeAELvkvRC5TEDxcondEpMQIMdblAdv02rA/NCdnYC9L/qJch7031ivmfKz+zdc1+6jqHC+RKzKm2kSymAutsDbHkFf6sdrf+kxYnqfaxwXZmOp27QS1r/bhYJxHSnf0vHkY5CUQ04fZ3cq5dmqvWXZy9gwpz4AFuIrK0OxesnMFWJfpnHTy1g42mLEd5GY+WKx8TlSvnq8x1iqr/DmPWdNN7bedb/njQQyZ34Ih8+y7acz7Dv6RRmKmd5PbRhtttNE30Ds7ekyQZ6LP77VEDBCDAoNjAsjBeQ9yAZQS4u0XmL6cEPtrpO5CnqWzB2mMSVU2icKRshLtNJcjgRzAPl+QH3wuqY5SHSIYAKeIxAmn8znnVEwg6tD14vm773t0XYfT+YzjcQSnCE4Rh4sLXF5eigeu1oWQoyHk6CHkUXNBAug6iGODA5gRo+Suo87XpVgGYpwkTkLudI4hAXIOnh2c7+FcB+c8+r5HWQzWdxExYnaX8I4QE2OKEwBC77v6hmeAYwQTwbmuKPcAwzsPgJDiJB7e2ViRmnNew5RATvoj6VQCiBx8fllG8cxR7tE10UokC6B3DvvLPS4uDvj+r30X3ncIQ8A0Tnjx1RcYxxPGsUdi4PbVCCDh4nCF3W6PH37/Qzx+8ghjHDDFgD/70z/DZ3/5Gfadw576HEXFFSVEuiYKPXFdVIcDuA/oDwd89NEHiJHxl3/xhXjlhwBmzml8PNhJypY0DeAUQSmhA0AskWRCdEhEmJgxUQJ7D99fAAFIaYIjl51vdHqaRfzGcmoVJ6bMAxi6i2HKKWxE9oz72yPGKeD+eMIUQjZaEiKLd7oqWTFySUtUIncwZ29fB4a490i0COXNKjOsWiAarQM1QYlG4ik5VaHGlf615shSsS56nzU8jcysI++6gWvobZ6xc6PtLYoSOXEwqm2zubCttEZlMUojCOSp2AnFAOScaxaM0/GM4TRUZ69ieNWmnCMxvBwhxYiYclqgxNVuL44iwrcVRXnWaH9z6Eg1dmq3qtBryDoHDefJXIOoaF3qlELkiqd4aQeA5gLlYvAYRb0o7tqJmhyXMz/kINtXUk5RY5XbbNA/lCez/GqcUWi92AOH7YFkzpSdJQ9c1eIYc0NxMZM32mijjTbaaKONNtpoo4022uhbRRGCPShiVLBbRgZFZMOLFkzjHeJ9QJrOZfkPQGPn14V+wUoljYkeQQVJdDO7YhelstZ1QRfzQwglQgbBwWWsp/OSukMWx/PCOUvUh77Pm8BKfSlDIRq5QvC4ghE4jRqhC+FazvSRgcSxwikQVK9ieARyPmM0Cd6keSjrmST4Bmm1LBGZAaoRhFUIKeXNlQ4gwCmrGfPivHmzbApkTWOdyqIokaZTkWgijlSyTTGp00BrnGXR7Ty6rsPjJ4/gyCHFhBgTTvd3OVW1BzMwnCMARt/18L7D08dX2B92iCkicsLrF69we3MnUZ/hCqZUppEIyuCTeWgcAJfQdR2uri/BCbh5fZ/T96Q8JrJFVPAsQoqSjoV0fSCPcWJJESGxNBhwDuR6IE0S0QMZv6bKRIsh65cWQ0aep2wmc0wSuYZz+pVxnBBjwjhNJW10cfowmJWma1HMT+dP2UBZ1sjZsDB3+1oBWw3+2GyR0wX4Bjqz0SbWMGRq5FoXyVUWRlZ67iEM2QLQK6fKV37gclMHkatwpy1N89LztYDMIFGLJ3LG63P9U44oVFoo41OGoWw6duzFQU3vSSti1ugiDLI4aXsL2j+VTa5I/1JWdQWkeUbrMOl8JjywYVPXGcxgFVB93mqVXTP8lJ1aeFZMmbQiXziszDHmFbC43nIFv16bGQ/PlQfOWsEvhLt6cKONNtro56Z3dvSoodvyQ5/mz1MCqGrTPI1IwwnsDrWVhXLQklFhIGoxqpcdI0eUQE59wO0DmiERPFhSnsQUATbe15AIHxRCVhaDKC525TL3VBUHdSTRBcfiTABJbdI8qPNvzglk7MvAKu5qCBBkwV8VZlkcBjiZF3VZhK2e3BrRg1Bf+vKuo/qmXSxU1l/L90lVwqm8BG29dXF3GXot15mdaHznsT/ssNv30p9SVNwNmJNE1UiEKQQkTui6kD23EzrP8P0eB9rj4uICu91ectSRk8VkFmOIUyqKefXmFJ69czhc7LDf7yGRQwKG84gwBYAlPU/X9ejIIZCMawp2LkkfGRIVhJxHYsYUJlmEz/Kap2Sp8oTRLTgv6nMRa4IYj+MUsmOAhE6cpijpaoI4bBxPA8ZxwvF0xjgFxCCKeuBkHD3M1DVzmLNHd83JWfkRb3qd1Wi8gMmWXtFLyui/RaOxOlHNJzi75J0VGzJ8az1UNPAlG1UhZbKRM2xkkVm6EKqiqyEU1/Xd+r1V0GsJq8myGFb2GVBPVi09M6H3MDkq5+y8rs5fOraLzrd8UNWX59RK2vLduCo1PZ/LQweAm3JcXwwlOhMtntMiXz2fqyoGbquIU/OiqfNp2e2lIdUaHW9Xw38RqmMwNzb/atrbaKONNtpoo4022mijjTbaaKO/CVRN9LJqtixgHBwQZXNWTQmL1s5/KLxFgz8ovlNjJb+N6oYdwZJn2+QlWkJe8GeOFVtYqzZj1pyhXC64Vcax7aI1CqNgtx4x1v5SrITnWAmAxeaYZjNMhYmrZ4OpdW1ddTZUi0gkGW9sonU0AjEY1ryBsmOeStRn772k5m744fofJ0nLkhe1nfMgksVwRwB1Hh15dH1f0sI3Tge23zpXDFjkiND1HbyXDZLMSRx/YnbEIUl/DhASEYgZsdRrBcZlXURSqceSEidXVMbkIZxuHbtK+fbIUWcyHiwb/uR2YQimHGPENMmmV86OIIm5RlOHOEeteTUUrM2Kypwso7k2Zx7o01Lei5P19sXsfl1cM3+G5N8LXNZ2xpTVfr+l2jmGvFrYbqhbwsBCru1Am65opW9lbKoMWgyZTB9Qf2dsuOC4ykRdMKlt0Ky65gTPRGnbWjBqfj7wXF/pYn0umLP2HUHabyoRzy2vy5bMO6F5LprGLTw9Z6q0zUWmCwz5ba+PtbrehdbuH1gmN9poo41+cXpnR4/e7QCgLLjW7eQRiRjkHdg5IOcLDOcB0809UncFOkRJjwJnnCUIpClTyi51UVRigHgBdzn/XXnCJ8ABXWY7xRyhgcVp4DwMCCEBxKLgsSSPuJ8GjCkgniekKWC/67Dbddjt9jjs9yDyCFG8oclRUYQZJLE0mIEUCyeRE8JwFoeMJBEydp04N8SuQyICcwQxo+tyXsFGCc//VOHhILLNETtSjLUcA6CEmIDAOfJGlMXTYRpAzmG/25m3GckOebAoppwAkqgkyOMjaUFiTmuTDRCSfI1IgCOHruswe8vJmJGrR3Lqm0eXV/j13/gh+p2H74HhPODP/vTHGMcJIUwy0bwDkUNM4o3tfQ+PhDGcMcUTPvnLCV9/vccPf+2HeP/95/joO9+D218h5pyB0xAwDhPG8xHn402Zial4JzMcgCePHuM/+b3fxel8xp/8+M8wDCOmYRQjgxP6vsPH3/kQfd/hzfEG4zTiLnWYWLxnUwLIJXgiXF4ecLi8wjQO+Pqrr3B/+wphuoFNR5KadzGhRKhI4oWfuKbgSCkhjCdMU8CrN0dMU8DxPCKmiDDF7Fkt8y7mORCDjBM5V8ZY3GJmuiu1C+pslLpWjzAKeh5IVSbJRF2wmnopm1KjvIoXuqpbVSmSeSV+yZw9nhcq2cz4rLkFrYJa+2Z7UK+XPpYQeLOxsJ+aQ7TpUW7TWUWZrLewPqeqTAj5ebXiaUFWrg9aOXaMat8cEchLNKCUEiIHIDu2AZB7uobiqOEkrRgJIC+pksqjI+eozZmA1KaupoKOZXOvC0/eu8LyWnqVwk1+fuvjTHLXUjV8HRVHrcpYnic6kfU+LoNkFHbr7KGXU9u2PQ9zOZr+5dFfMXYImttXOvyNKvYDyvmKmbPRRhtttNFGG2200UYbbbTRRt8qciShmRVuqQv5Em+CiGTXecaWU4hIg0ReVpymuGsUDwdX4SoAZXE0R1LIgSlQ9o2rva84JucIDTmysUTyEKDE5U03BGDMUSJSOINjQuclHXXnO3TeF1xVoKGKITeIQqrbaBIYaRpRADiQ4M9EYOfyeqVsLHOuw4MpY8qiuToh6KbEGvVXJZBKlVwCrIYQQSTOFe3ifMbZknCfA1tDnXEEfksFywebDZF5k5WmLKnVKR5pF36F/92+w9OnT+E9gTwQQ8Srl68klXZ29HFOELYSETenQYkpIHHAm5uE49HjyeOnuLy8xPX1I5DvJTI3J6TAsskzTAjTUPixiA8RYb874IMPnmMKAS9evSoYtAK5jhyur6/gncN5GhBTxMgOKcraALOsXxCAvu/Q9TukFHE8HjGNJ6Q41PsALYanGLLIPkcANmWYGSlOSDHhNEjEjilE2UQZTZQPUJYbl4gdJQoLlaTaBgumPIwtmMUaXH0GiNVZVQTYbq4r4z3DkAvgbBfkDSZaZkW9L7hs9MUKGRC84Is0Y87gtWSOtSBz/U3zY1lCRIurSskZhlyqabyi7HFUnizuSSjpv9fJAp06ioY/AhgafT7lsTYYKVds01kHDIOb1tRLKrPcloGv7SY3uX4OvOY2DD67iqmqeKyDH5D3jFOpVoK500IujXOVfjbjt8LWHEO28rFzaYYhL0/MqIx7ebK9ndYw5A083mijjX7F9M6OHpeXl9AUH3YhTAJZMMh3cF2HvGoKTqJUsUZBsC8Q81QroadgQy/lneWzJ2V5XZKuDUp0i5SSLI5GiRjhvZccf6pskCy4xxQRQ8Bu57PnsEPXeTBc4+Dbrhmqcp3KrvPECTEGUW6bBfWcdy8zqC8TVdIJlA0KFOOkpoMhzBdUNSiWRkZQRwCllFiCARb9ZK64crkeQMOrFS3PvxQjzES6aN+MYEj0jK7z2B/22B928J0DkcjleH/EMIgTg3cOF0+foOs6jKPLY+fEU5rPSCliHAcQJcQYQUzo+h77iwukFMGRcaJBFNldjxR3orxHMWhSktQ2IMmpeH11BWZgHMU5BNlYAYnxsd/v0O96+DN0xPI4ZyWYxKGl63vsdjuEEHB3d4dxPIsXv52MVo4sSnXSyCXMCFGMWPEJipiGAdMUcDqdMU4Rx9OAEBOiGpigZv7p/aNK5rzZt6gdi8X5dgNBjUrCWfMp+nGj+bXRS9gytzaLjOavCmAJGadFW/15hfEHjs+vfUs5iZizfrxwWG+HRRPzb/WQ3N9rrCtwofLUZw9yi0t2824P8/wQ41UvJVMXyvPBRvZ4iPM8lR8oN+NooYTPd17YM/XvkjSWkTVs5oM169O8unL5Q5p25qCRG/KzdJ2bJb/fpFXXOfKL6N3v4Cay0UYbbbTRRhtttNFGG2200Ub/0VLf9RDMY4lLsQMklWzxzCiLlXVznEKrBCLZSKS0iNehi6VzHCaDPiWSK8tVJZKHWRSnBufhgn+nFME5lQs5gvPU4NXc/DVYUMZ+hY2KpetZ7UmBWjWdDaHBiBQ3JoPlarQMphbBVqkof9URoPIxF1ntMdpfZZf9OgrJphw1IjfXFAxZy0m68K7z6DqXIzhLqvBpmgQXZYmy0R8OObW4wow5InNOsx5jEHSJ1TFEUsAwGJwYAbJ5jr2DT77g6shjr7J1jrDrezAkLXZ18kDpQ+c9nPdwYUA7E2Hwc+mb965g3DEGNPlrFjKsKVSYZWNdShXzYk5IQVI8T1PIjh6yQVGizLQYcpU/G95EdtouG6RsMfq8cjTfQ9bJoESrUQy5qcNgyHOssUw6g8kZkFkhTHX2KB4fCwzZjk9hFOtzddmvBTXwo8UwZ0lY5jzMYUvrwGAXsBqEdfaN5tFD7FitsWqdOajKs5GDfth7+CEMOR//BozdVGq+vQVbbQB3XhZ7CBMGUKNAfSMbMwxZG8kHjTzK1NNN0qTt1HqagNIP9esXpYcA5gX/G2200Ua/OL2zo8d//k//CWKMeP36FtM04ny6RwwBw+mIMA44vf8M5AlhmjBNEyZmDCmVdBfkkfMcOhB1eaEeIKppSGqoPMo78F1RiBksXn4MxKgRPEbElBCmCZzESQBg9P0efZfDrgF43HW4Sgm4BMCM3hM67+Cch/Ndo8wXV2eIowU5hxgixiHnuZsmeQc6cXS4uLqCdx4+R/SA68D6omZG4gCOAYQc6g3idOIdwREwxYgQgyj1efHSOQ/vxMN7igHnaRR+svbsvKtKKoBpGEFOnCNA4lAAIMtavbu5eD+6HJEgQRx1Uunv7L1b9S2Ul6Qp8OTpU/z27/wWxhDw2euXmIYBw+tbhGnCeRjBDFz0e1xdXeL3f//3cXV1ic+/+EucTifc3TGmKeF4/wJhOmN/ecDu4gKnEPDi5gbH4YSJBzy9vsDjiwO+/PoVzucRzz94hPeffIwXr27xyadfA9MIngaJHOG74jREJE4wjgB2omj6iwP6ww67ix28c7h5fY+7u/sc6o7QdSKzvj+g8z2ePH6MR48f4csvv8Dr1y8RxljnapLwfeREiQ9RnIjGYcQ4Tri7O2EKEcfzmJ2R8nUxIuVQgJxY8iqy5HJc1axUf9N7w2xfEGNV7jFxEsjzbkV5YqPciPMFoLlDdZx9jmqQimko6mPKim4Nd2brqsZiZY0A+Nw4G8Mg65jMRmE3EWKMMWhzqFrSX67sLJA2qrNTKzxaXFkncWFFJZQZbA180+finZyqUkhVpiIAB3DNqVhrp+Z3pQjmCnA4rymPOokAE2IjAo7ZaCrGv416pO3MjQRxDlH9fu7gYQ09Ky95Pks6GWIqOwzmErU7VUQUPDPo5grrDDAo2vQDiu1s3tkTjblEQBtxSPtrcsxywjq1ZspytqAaybaM7efMhtloo4022mijjTbaaKONNtpoo28jff+H30dKjPMwIMWIECakjJulGDBdXoAcysa9xEBkWaQva49O09x2GRuu63QAUBdldbE9R2TWxfyM4aQoKFcIsWwWhGLQADrnc0ppob1z2HEC+gMAcTyQILuC3ehGs8wEGi4cIcWEGCTVSMFRSHCJvu+lDo3aS/JZ0nXnFCUEp4haqV/wuVSiM0P3oZGTzY4giUCtmLBy5QS4UrwkhggiwHmf21SZUytWxdkIRfDM1U2g4jGKt8xWS4tgBEw5XBzw3vvvIaaE2/NJ5sV5QIoZ+wKh9x593+Pjjz/Gbtfj7u4GU5gwjkCKjGk6IsUg6Vb6HlNKOA0DpjghIuLQ99j3HvfHM0KIuLzc4/LwCMfTiJvbo0RfDhUzV94I9V/JMJPTwfhOUsIM5wnjKFg3I88JEJzv4JzHYX/Abr/D/f09zudTSf+ieCPJJMiYsm5YjbLmUBw5ItQBRODUVMpXp5AZhorZgOkRZoNFSvtMZrOpOTOHKnntB6XmREndk3FGdXhZLpbXe9pkIgc1oUNsRBiLa2tn7V1gFvNLE3O0Ls9JlVSzwfgh0M7IYS2iRP7TQH9cMdpyVO8Bp6xwvakUQ17IRzFlrWWBSucTnFnTeSvR8nUMkqaYksULqGdS4nfZmFeP2+fsHJ63z7sZa3J0LRqKwU6pqaRGbFrFkBtQVisgrBVt+/DgyXpe5WhK1mAr+iy0T+BZh97SQqnfXLo69WjxZaONNtroF6Z3dvR4+t5TUUCYMQ4jvAfCNMFRwtQRdhcXOJ+GnLtO3okRADlXcu4577OnL0mwvrzL30HjT+jLcf6yYPNgzJE5UpLF9aQKdH15+5znjzMj1InxQORAIHhiiA4vSp2+kxm6qM355U1oXhB5gR8EdM5J37qs+PkuKzSzlybbdBdOnCsAUJIXZ1JnmMRA4pJTkIjgMr+J2+VbDRNGGjmEE5BUijmfGQDy8spvFXEh54CUSLkxxgMV5XGdtBRh1+/w7Okz3J6OOH3xOYbjGaebezFqsjFEzqHrejx7+gzXj65we/clmAecB3F+8I7AToyd3X6HmBinQcLhUXaG8SRpRRIH+I5wcXHA7v4M8g4uefRdV8ZRvZ4BRt/3sljOklpod9hjt9/J3OSEMEnKFNd5ycvY1RyRlMMoEgHDcMbd7R0ceTjySDlaTXKAc4wQI0IICCFgHAYMw4T74xnTFHF/GnI0GZGnemeDSyzEdr6Yb6o4NU6mRbNcKk7cKMPzMSsXQzXLh9WSqkhz8UhmM48XNWMxwYqizU2B9nKG1XBrNL9iKVQqmmBLqrvq2cZUmQmoYgBtZJxmqj/UdPmR+5F3LciNs36vVKW/1tIMkYbdJBtaURi3oTprR5VfLuOhzj1NWZ05pM4rZGwNKdsqq7yQXe2DNQArE7XH72IN5u+Nwa9GSa2GzS6DRRX6fF9rZoWsnVe93deMmJUKzbtG78Gq+lNT/kE+vonBjTbaaKONNtpoo4022mijjTb6j5QOF4eSajnGKE4dUTDh5ADfdwihr5EqKG9CcwTnMh5KFjfQLzUlS4W4VjBk/Q6WzUwpR4TOziQafUMjaDinaQkI3inmI5iwg8V1lCeNoFzbLSknDH6l53WzEjmJMF2dDBQBU3xW+9Bitdq6RoXWxiVVeEZpKW/SKREruMIYJNEzCtbH2oOaBpryf2vonUZXsRhy4WmlvBkNFQi887g4HDCEgHB/hzAFhGEq40FZRs45XBzEaWIY78EICAEFNyMiuLzOwAxMQVJhK4bryvgkOEfoug7eByBvYvLONexq/71zYMelLt/lNvJ4inMGFwcklb1+qpxiCBjHERq1Vze2EjmQOjapo0cICDFhHCekxBinkIc2S1VDiJRNS2sYct26RWQipL9t7fhdzs8wvVXo04Kyc9xvUW4FJl52Z51WMOE5DF3rnCGHJuW4jZ9Rmm9B+FVceA2mfAujpl96d1DLVmFaedQxW+3VrOVlmXmXy2l9SDEkUsoarzBts+1DfkYCRmr666E40PPGM1tFxjP5LBx07HdaF8NaM/NyaxjyW+qy3C6LPXDhrN35dF6UfRttGPJGG230K6B3dvQ43d6AU8KeBux2CVf7x5BH11OEEPDmVcD9cAHyXwH8GiAP6nZ4+vw9vP/972EYGOMITNOAaRrhPMN7iLNH9kgll6N3aG46DcHWdZC30ogYI47HE0KU0GXMLBE1nMdut895E8UT1KEqiXDZyxGqyAMxcYk4wpzy7vXc4azUEEV0nuAvL+TalB//jkVhzN7Ycp3kz2NGjt9BGqgjh1dL0GB9DuLgoioyEQE576NzDoSEmCYwojhDJK7ewFmJV+9rDTQQUzZhgkR46FwHcoQ4e8Wo0QSWqBIaLVEjMiQAMUm9rqxmJ6hjjCOHjjrsuj2uDpcYTwPGV7cYh0HE5lz2HAbGkDBkz2xmxtdff46XL7/C6xvCOBEu9x773R7f+eB9PH32DJ9/dYvPvnyFZ+9d4zvP3senP/1L/NGnn2WHGMZwe48Xn3+JyEDvGI/ef4IPP/ht3N2+wc8++QukNODu9gbOe/zdv/PbOJ0n/PmnL+Ccw6//2gcgAH/+s09xOo2Av8Kjx1d4/ISw2xN83wPO4cvP3+D+7oS/+OSnEnVlCmDyiAmIKeD27oS7uyPOo0QuSammbOGYEJkRgijt0zhlXcZDvLKr+/LSZKuf3vlsBMr5GLJDEKyyUkMfAmoIkDkLgNRz3IR9o1qDVWeiiXZgZ0z9Pgv7aAvYCZT7Rfb84qpszGubxUtnpg7l88XwzY5TTdhKU+tcX24M78qaGGWza1tercJsHK0yi4TqtFOj82ltVg7mkBpqWrue5nwtccmbSNnhy0UJMVkSk+aLUswy9sKAo1bNrt0QhV2mExVwo00QZL9RmR7ar+KcZEAH2w7NDzQVrijqK0UNq3Km8cRZqZ9RdjjocTutV3VkyuZv1vAf1KPX2nugD7ag1v2gj9xGG2200UYbbbTRRhtttNFGG30LaBoH2cxGEd4zer+H2NIHpJRwPidMoQe5e4DPAMQJ4nB5gcdPH+Pi6gr9TtI5xxgFl/GKpSio5gXP1XQXiiiU6BySTnwaQ4nkwcxw5ODI5fTT4uQBFDSkOBwUjIVqtNuy8YbnG25yUeQIIH2PzFQ+wQW/U4cEQCNbK7ZCJVqD8mrhLEUEy+YoZzcJZScWJDjK9SSLq2TnEoP1lI1yGUt03qS5mS0iSxupWX9VDIaBEm2l4nFcCgga7+Bdh77bIYaIeBoRY8jwDBX8LibdKCcY8vF4h9PpHuczISag7xw673F9eYHDxQXu7gec7k84XOxwvb/A7c0Nvrq9E+wLjDBMON7dgyGbCHeXB1xdXmEcz7h98wacQk4lTvjwg/cxxYjXtycQEZ4+vgQBeH17i2mKAO2w2++w3wO+oxKV5f5uwDgGhJs3oBtk7FbHIGEYJ4zjlDcJxhqZA+p0pKnaOUcqBxSxZHCB4ioKuiRXgP0s/ij913Eoc3t18Xy52F42jr2ljHWoWl8Kb3G9uti/Xuc3YsiKnQqDcq7k0lFAkds2yrOira3pWsFszbmmjhb7XDtveV6XxQybbnjIvBdHCy0zw5QNv/rEK48g5yTasqZzKpfqWKHek+UZMGPaCEXgfZefdXXu1Q1x6iZG9frSz1Upz4stT6zNNzs2D108Pz7HdA32vj7HHrqr6jRbLfPA+P/ctGHIG2200a+I3tnRYzyfATAQAxwxXHcAuQ6+6xFDRLc7gLpDVrSRNTyHw8UBF08e4XRMOJ0SnHNglneQIxZnxewVyyEBlCTnHnF9bRCK17KmMwgxImUFiFwnzgddJ9EYkIqSTJmPGqKqPqU1L6OGQXPOSfqK2Uqdo+xsQqKcCsXSx1otl7BqJIlfSh0ako0hyo3kFqwey2pclBBXWeHmbCSkHF6tEGl6G4l6IWKMemEtNh/IrKAXBVzf80TIeTXAkCggRkNvPgniseydR+87eHJI44Q0hSpfko7G7AShqWzCNGEaR4wTYQoEurhE1/fY7/a4OOwBvsUwjgADvfM4Hc/46quX6PsOu65HGBgnYvS7Hvv9Hru+w5Mnj8EcIH4vCcM4Yr/f49HjR+h2E/avT3DO4dH1NVKKOA4j7o8nXLpL9M7jcAHs9wTa7cA56soYJoTjGTEG+K6Hcx4cE1KUlEH3xwHH8xl390eJhmbXwLNHfnXOqQ4bumugUFG0VOnW8aEyxiAgWmeDZjjlfLtjoR13M+PXZkQ2JvV+myn+PL+mmpXt3EBTTp1L5rSmv3C+oMQoobmPNYC82+Bd9B8bn6JEp9GbqnThgbQubHYvUBvTp0TRQOWPWQ1eLfKAX/MsgkrpR6N8t6l36rMrGSWeGgcHaS/X/zaNOSvyjfc8GTtiZnDMw9fVe7o9v2xKn1+GySU3befNmbU5riXrHbIy1/OY8uya2cWFxwdZeKBhlRHZgw3nWBz7ZYiZMcUJQxjQ+16M9o022mijjTbaaKONNtpoo402+htAcQpgMNI4AGB0+4sczcJJKmTfAa5DSdmQNw51XY/9fofdboe+7xECmUgOXNIBayoXIOUqMuZCihoYvJcz5pzs5jlUp4uM05W9Sw8hHlwxvRIFwxnAILdMkOjG0o5ZxNV+Wmg6Y0VutrBZ8Gptms2irsqCaiSJwhsUo0pIqbZDZDCujLmxxciQMZw5sKQYsmF5TTYtEsaLQopzeidYOccIjjaPh/zhxAafzOmvY0RMhJQASXvj0flOUrYzEPLagHMO0xRwf3+C9w7eOSREBGI479D5Dt4RDvs9gCQbNkmcK7z32O33cDGiO08gctjvdoLN5NQqPfXwROh6oPMEAaEJjDNiSpimScYpzyvkFN4hyvVTCBjHKY9nK+Qyr7KTi8lnbaVqVqsNCmUwLo3kwor3rQyWpnBRvHeO8j44yM3JinE2d8uaNwMZPsokso1YZ4K2/ZmYDHw7LzTHfddw2Qe6ZHhrxqXB2R+e3/b2b1rlHPmigJZLDHlx4WIdZp3/Ji4z6X2fKzAOIwsMGTVycTPHmuEg8xzNJ3lRdcMYafqVh6DihXByvWuyaPo24+1tNJsSTT/n/f8Gflc6UCt+6JxpucGQvwl33mijjTb6FdE7O3r8xSc/E+/SSfLR9bsOzjnselF87t98jXh6CU4jmAgpMlJI+OC99/Dxb/4GGD0YPeI0IoyDpHHxHaYwYRjOeH1zh599+hXAEY4jHCV4ihjGEV+/eIVpijgex+xtnNB5wtX+IJ7SXQcicTwQBdRlJTQ7W+SIeKLYZ69Z1GVjUfyrrk3kxAMaKEusmsvQvuZTTBhPEsWi7zsQAdMkSlvqejjnxCElJYQohoX3Do5QQgbqG7ejHRx5RGakMKAsKWava+cI3GVvyhThCOg64SmlIMqChuNykkKGgRxRRF/Stb8Mgu86OO/BK28du64oslVDKYLg0HuHXefQ9R26vke32yMmlrybYECdcMiDOeJ8f8S+7/C3f+f3MYYJr29OGKcAzxOIE17f3eHLN29weXGNH/zaB/jyiy/wZz/+ExzvTtj1fQ6jqDkJAR4DYojSwXECeeCD73wIMOGLr18gJSBMkhLmow+ewXnC119/iSGMAAX0e2CHER6EV68CEiecxglTiHj14gbH4xmn+zPGcUJMKXvZy5iMU8A0SfsxVGNNHIbUHFFFojrvwBpSeTQ0F6Y6gqhBJyepeHVXJ+Ss5aj390LJ0nMzXagYDFwGt6Z6mWuUs0rV4MpOTCaEhTgEFQ1SIsk0evesuqpooRi1hsUS0cLOPRh5PqRb0eyYylAdjJYiYgQ1zMvugTxyuY81r2AdY2THKk0/Jd71Ko+sapfdGWLNtE4r1Z2m8p2PleeQRBYiBrzvwCzRfead1UgfpXdlJ4cUatTlJGymmHIaK3lO1pliFNBVRTc/Ha3hNKMm92eZMyjzZz7Wy8eOUeotH3rIyLVGM7SmVh3zcsfZ++YbDdVaJ2HdYech8dhu/irofrrHv/zJv8TTw1P80x/8U3xw9cGvpuKNNtpoo4022mijjTbaaKONNvorpjc3tzjf3+NP/tW/xnge8Lv/9J/g0QfvwztJsz2dj+BwAnMU/DLjtVcXF3j/vWf46MPn+O53vwOOESkFwYacQ0qSOvk8jLi9vYdsGsr/SDbYHU9nxJgkCkPGhJwDuq6DdcJwBStVfMbgHmgxBoDLxhnrgOEEBKoYhNZpsa0MtjADMUjUX5950A2MnPFsjeSh0UNcjiAt+K6uVjKclmeASmpoxUAERyafD+QNSbqRrEQaboA66XtFhwx+k4Edcg6eDEZmyNm9KaSovKBdDhIR2zuJguG8h/MdHMuGRcHVFK8UbA5it+0AAQAASURBVDVMEzrv8P7zjxFTwnmYEGOSrXnMOI8j7ocz+m6HJ0+ucH93h9cvX2AaA7zPziQFAwc4MjhOAAOvozh5XF1dAQDujnkDX7yD9w5XlxcgBxyP9wgpApTgO8AjwjFwPskYTTn9yuk4YDI4cXFUyRhyjBKhWSKYV5mXjWmNRM3GzObMDOMyC9rFS0LrM/OT1OPDyMIM1HorK3htOyUsOEtlfi8AMeWD59fDYHf1sK2+rY7aAuWcpiiyXaLV9njWh9YJhlFSSVcQcXZxXsMxz4tF5IoSedr+zvdOrpobTwkz6laeM0FxOW67UMfT+szI5moCU2zvb26vmd38dQi11ewkpg5ngsO2aZ1qu7SU2dqBxRSZ4f/2+WPFMK/X1jMfawsrU/tkX+cxz0PWZ2Mu1syp5TUtSYNGkqusvvXyjTbaaKNfAb2zo8eb21tRtgZJl9L3BO8d9v0BYMJ0vkeaTuCUFcysYBz2Bzx9/Bi+P8B3B6QQwGEC+Q7U7TCMA47DEdTv8OLNPZAiPAIICR1NYEqIKYhDyChK2a6X6Be73os3sO/yYq0opqpi1xBS6kldlmbrAueKlyw1C6ZliROq9FoP7ikEgEWpJSKJ2sEsDhQMxOzokZLord5UKnqTVcII4OxUAF2IleMS8UM80DXno3NUlELlk81Llq2Ckt8u+vJm1NyGVQnN9VDVjWwORKhzClgWuzUyiCN0fYcYO4AjJBtOTrvjxJgIYUKKCU+ffQjyHv3hDYZhQBzvkcKIl1/c4s3dHS4vL3F1ucPpdMQXX34JTx6dV6lxcfSIeZF7OJ1wkxIOlwc8+eApphBxc3PENCYcbydcXV3g177/HM4RPn1zj/M4ZCMxARyQGDgeB0xTxM3xhGEMuL+9wziMuLsbMJwnie4RJxB51OgXKAaTCliVdPExUO3d5gKySmxrGlkHEI1gI3XaNkxVqOOjp6tiODMSFhfOtF3iWbkZcZV9ub5MNltXnkczZw1uSy0UyDkf65rVTGLMiyqgSvNCeeVFe9Wgml1v74XiZJIy0848B4yj2Jpc9QYyvDcGk+n24jfyLhXIcy4lZwd3Nn75ipyCyZgQRkGu8rDzyT4rCtuGX6ye0b7V803JZqrSfAgfTr9oD84VdHDbfOF9wXQdkwKA5AKNB3fbXs1fa4/bJ759wmJpoM5qnQ39L0QhBfz0zU/x8vQS/+i7/+iXrG2jjTbaaKONNtpoo4022mijjf766DwMON7f42d/+mcY74/43t/7T9A/ukbnO4Czw0OcAJNCmCHOGIf9HpeXF7i+vsxRHyJADuQ8QoyY4gTyJ5yGCUgJRAkEjc+rETwiYo4Y4XMqW68RPFwGVc3OdcAsXJq0EBaeaBaBK4SXL9GNLjxDWSruI6k5pL8aVFk3AGpEVxt5mgueU7GI5SJtavDESjWSQGHbUYOlVeRI2lmko9EUwRZPbhbSLfJoUSiTAkYXx6nWTSQL0pKGOhW5ARVnTimBE+NwuJLNh91Z0p7EEZwiTvcDhnFE3/fY9R5vwoS7+3vZDGpzsuviNDMSyebEgRld3+FwdUBMCeMwIQXGNCb0uw6PH1+CQLg9jwgxZnybAYhT0jQFSS0+ifPJOEia+XEICCEhpojEqaxMgNnAp4pNGXS4wSZrPPIl3lqHuESUsVhhU1cDlNUSpnmandcyq9iwxaX1Y4b/tRevY7ZN5SqXQmae5/Kz7plPc7KA4qYannEwx39LGW3WymEFQ25OcStenbvlMi71142F+Toz1+uNyKbT9VSLIWcctzlbjxXoNF9Unh1FkFAmcg2Kg5q2zdjpX7bXzPHcxTLFg7Mn99P2ee08zdYL1lzKLPEMgNXf/ED988vrPVXGhmHmVf5Y1MWoDk5tAy2GbNpd7cg3yGujjTba6Oekd3b0mIYjgJqi4nyWkGR36R4cE+7evML5/gacJnhPoJRAU8T5eMKbN7e4vgYuLz36zsHtJMULO4+uc7g49Ljod7i+PMjC/avXOI0Dvr6/xZkkLQyog6M9CEDnPRwRvNed6R2qtgMQYlmKBQMcU3mpJnndwcGBsxHgPBWPX33+JoiTwkXvZDd8EKVXojswQpzAnEpovxSRX5ASOi8xSq49EOC8K8vEnMPNeWLJCwP54BSytGueSE6c8/uJkwg7giMZthCkvIbr05CBupYbQna28C4bNaIwi/MJN7khxTDRhJcEpurQkDhJfzjnSgwRjga8ub3Bz/7ycwAJv/O3fx0pRkzTJBFMpggiQt912PU9djtCiCfswgXilPCjH/0pXrx+iX63g+8cLvcO33n+BC+/+BKf/OinuLm9hYcrsVmIcgobSN9cNtKYCadxwhgTTlPAftfj2ZNH0rfnDuQ97oczhnHEzz75FMfTCa9vjphCxPl+QAwJUxBnnDF/TuOEGKMo6FEMxMQMQjJapqpT2WhiMovo+iHRH5DDROaLdJqWsZLy8sVng7PqPgSowWg0AzVUrH7ZVKz1F82wcmyJCrPKn1VWyPTFHFMZ0OLkKhFmPFbGzBlVeK0yWQVENsxl08+Z5lW8jQErr4e1QzIiS9k2MHWBqxN2fqaY6Je5hmLxZhbrc6RVSwmtQwFXhd92j4qpDUce5BngHNkjhPLMIbbiZ3mueFpttXx3sgtDAiNxYwtJl+s4lP7Ur6VMo7ravK/zwpbmyu3MYWS1vH7NxtDD7khvm4fGSclYifZ+bRXsh5XtGgoRDe/81qs22mijjTbaaKONNtpoo4022ujbQylOSDFAUlInhDBhHAeMPALMGIcTwjSAOcnGucSgmBCmCefzINgHRzhPIJIUL0yEnSP0nUPvPHZdhxAChvMZIQYcxxGBEpzrgM5hn3GkmvZaMZAc9hmAWvMV9uG6AKhYAsm2H0GQGZpCu2BmuSZyOVKHwYM1ModECa7pV2rQYMo4mNlURhnnLXihHCRk3BcZm7DhIUgXlSsm5gDZ1Z6vSRlbLriU4l8s7accVYOcYFcacZdTKtFnLYZkI8py+cxIWMoIGkOccWLEeRhwe3MHEOP950+lXo1gEgVv9U5SrngPJA7wqUdCxMuXL3E8nSRduyf0nnB9ecDp7h5vXrzBMI6oqD5KP9XBgkjwNbCkeonMCCnBe4eL/R60J+BK5skUAkKMuL25wzRNEk0kMcIUkBIXnmPM6wR5w2fS1OUlGrK5IWaYrmKBBUOuI1mwSAsyrVwuY6Xzp0DO7ZxU3K3FCDH7VTFknYu1BSxKtzgerX5duUovXjZtnYtm0G85uFhtpwZDBiALOaWCWXEVYLntZ1i0bfybyGDEDYZs61De1NFpDjk21ZG5eo5RzjbQNRhymxamRBaiHNkDslnYtm2bLo5djcMNNbCu4M8m/QsBjZND4/xWx2ROi9lkp8HK0Na2lnWtzptZRYohvxWlXRuPLM9mijc8rM2vXwxDns+cjTbaaKNflt7Z0SOGCXnpEQDnBf2IOCbEEDEMJ4TpDHDMnskMpIRpGHE6nbHf7cGHPcjv0PUdxNfawXkHjw67zmO/97i/uwePE9g5xNMJyXXouh4ODr2Tx6B3EuGBMQFgEOe8eEkflSk/Q7OKyTnsHeSl6ajmFwRziToB1FBU6ujhfX45QtIqJBalbopRrp09r1XR1fXS4tHsJEKHGg3i4UzyIi51JOQkgdkQQROhIHMIkEOC8EEQRw59oTMBlBXqkNN+kKMSlcMRMKVUnEdczo9IbkUhLPzLv8SMmES+U5xwHga8ef0GF5d7vP/eEwDAFAJSZMRJeNvvJe0KuYQYxxx2kfDy5Ut8/tUXuHj0CLvDHtcXj3B1scend5/ji8++BoiKMaYGi3q8EyR8oXedGIwxIURRvnF9icMHnXh173aIzLgdRtwdT3j9+gbH+yPe3Ejkjtdvjpiyos5GueastFddj40s6jjbV3SNlqC1tBqDRjjRVCQwa8zlMqhCjWKINO7LSbng5vpWX+DmY66w2VM0+145oEVZDdWmpSlzokphJSMXyr/Y1m76Vvpb67bjYLTXJcNFANweghGqoXZY6v00N5Za0rGr1xHmRhI1fC2NEb3WGpuGA+I5q02bmiaGvThnRDVSS5Wtwr2ux9aDMm+1oOXPyl7HzO7mmGvZVs6tss4AaKGpt9RMSW7PqDf8/HzTNzvpq/2T80KacVuKYHluzpP5UeYnr5VaWh3L+2mjjTbaaKONNtpoo4022mijjb5dlPIivmKgMUlaFY6CZcYQEGMASjRcSLkgqVlSjqRA5POipS56UsYDHbwnSZ8dIwBCogAmVza1+WyYuxKtNaeYhknNzZKYtwAtBUfOLIHhdGEz77YhXVBFxmugkEPdsKdYk0bnEFnMMCMuSI3BpngVDxT4p134ZQN0uILTtaTXidOFqYdmi4yMEsGZzEIukYxQMvg3TO+bhozMBDrjsi8opoQQA87DGX3f4fJiX46XjUgAOq8bElnSunCSDX6nE+7u79Dv9/DeY3e1R9953I4T7u+OGZpTYAjQqCIqU4LLeGyOVB0jQojY73p0l3ltIkfmHmLEOAWczwOmUbDmEBPO5ynz1GJKi/QrFi7TaA8zlKg4cmh5ai8uETtW0KXaDq0EFjCLFFxaml1o27T42xz3m+OB6xjyAgErXaNSuMFBmzZnnZtFsFk22GJ0i0jLK9U0dZVLZ3fKWzHkGX0DhtzUaR1tODMy52uVVk7ofLJOL5lHbapcqRuB9YDBjHlRJ5Z9tVi2zhOelXsIQ16TW+P4xLMPe6+ud31BCxmuzJs5hrzSN/ngKqvFvCmA+VtZKFVrRzYMeaONNvr3QO/s6BHOISu2+eWeAMDLIr4n9H2PuNshkAMnxpgY58j48uUt7n/6OfruK3Sdx/P3n+L5+++h3/XY7/fwXhw5ztOAm/MdnAM+/vgDPI8BH370DMM44ubmOyAQLroDmIHTMGEKAa9ev8Q0ThjPQXLehQGcIsI4ilGQc+Ml1hyHEpmBsxOBhsiLkREI8OTQZSeSxIxxDBjO4rjiIM/1EGOO1kFZqcrqvOOiLIP0RafetTk/IqkzCuXUJ1m4zQtDnD1ijAiTRpCwCjvXnG76AiJV9PNLSpJEYrdz1UMTjDHnp/RO+5lDfJHqgOqtrvnjWFJC5OgikcXggnPwDri9v8WP/uIn6LzHft+XFyRn+YhTDmeHFWC32+Hv/N4eF5dXePrxx+BHj/D+1RUOnceLl1/iiy9f4vb+DOc99rsd+r4DaAeiHRJHxBTRd8CuB3a7DofDHjERhkAYTyfcvPwat3d3+NFPgkQtcB7DOOHzr15gOI948+oGYQoYR3HukM9Ud/Zr+MZCXJSlajCoclvTa+hQyFBWL3To7cIMzvOqTKR6K2VZ6w8NoKbhGnOb2VGkpBYpylZNJ9SG6ONWMTNzrPawev8XhVt1rzzHihFHrhp9WrrpwEPqikpL5aOuLDN1Zin6RkZ6ronWYdvk+QXzNlSx5la3WlvxXyM1CPJcVqNV5oErspD8qMqLkV9jrFHTMZ0jtSu6O6T2l8iBHMF3Xc5dK4BJTVEiczjluTpPP1XJdH5mG/DsWynb1ENAdqSr/VjWVw4Y8XIJKWpjJ83KzwwPmYtmxrTDDzEkqpybGueGgt4LpUoyZbi9bs5Xfp6zyqN0OfMMaufmRhtttNFGG2200UYbbbTRRht9SymFhBQiUpR/uuJIlNN25IX1lHGDyIzAwP1pwKvXd/jiq5d48ukXuLw44PLyAt57+M7DkWB9IQUMcQQBuH50hcuUcBUOCDFiGK5BADrXA0CJ4ns6n5BiRAwZJ04ZM45RMJZUNwuiYHKMVDBSZGhAIr06g7sws/RhSAV+YEbddGii0NaUCbDAcP7MGIPiyyxAVAt1zfELkoghqUFSavE1DLkpxzlzcYunxRzhw5FDl/Gf4sRhF2szRlKdSWpK6pQEI3UEjOOIl69fSX2dgyWB6sTBQyEX7z0+/MCj63c4XF+Ddztc7nboiHA83+P+/oRhCuLU00lqd5AH4DMvCY4kdY/3Dl3XCa6fCDFMGE5HDOOIl69uMvDrEGLE3fGEECKG0xkpSqTnGsEjd9rirU1HdASoOS9IbzvS0m+GbnRs6rBY6AI+ZftDfuU/Bd6ym+gUzJw1scBD2fJszy05bzDk+dy094vtSilHRYQzjmodtm+lD4adOW43hyXr7basX+WxuMA0MN9Y9q4w36J8FZAdi9Z/YCYM64RVMGTAzqe2n3bbrsGaAZBzFcs02HyZH4S8Ya7WUuq11dlG8/F1kcwnhBwT6Jha2bj2snLjF5jbPrS+gZrxpNX5UTBk26G1PpbnpD2uJ9zyvnkIQ9Y+NPOBKnvvuh6x0UYbbfSO9M6OHimI5zM7ZOVOnsjiWS0KmPedLANmBXdKjJu7E45fvwFzQEoB0zSi7xwuLy/gEJH6HZiAIYy4H0643O3x/pOnIDCep2uMMeLN+0/hyOHpxSMkBl7dHnEeBlDncT6dcbw9IYSAaQRSCgAnREDCzukCOTS8WkIiV1KTABqpA0WxlfBWEn5tHEc4B+x6B2YgJg09p5Jx8m7IOriu0NboItQo/xqWovp/1wXo+ohPEsIuRJBzcD47ZVSNbbmgaV/2+QXUdQRmgjrRxyiOLv3Oo/NeopOYxUlJz1IXmcG5H56y53NEjJIWJyWH03DC/XASJYU1nY6+Ebv8XpzEaANwuLjAb/7G38L+8gKXT58iXV3hw8MBF87h088+wxcv3sCNEc557Poeh8MOwAVAB0xxAuKE/QG4ugD2+x0uLg+YkoOfPBhASjJer2+PSEwITDiezvjpJz/DOAYgqSYyD8OVo22wMbZU1NCxIp0gUCcetm9+E5lBpkF903M20jiP7cJzHqrPWK1JVZA8ObVNbke/Gn8QJxNQjrmTNYlGmZhr0qo9UWl7YWOWHi35tecbb/TF9fmQ8fZtFKtcob0fZB6vq/2lntnC+kKqWYksBog1RGfaHM+Yb8VQy4rzNGfRmvaznaD2lM4MBkxIz7kzjjV4aMaD8J90t0j2DHPswcT5OWT7U4ST9eOHFeHyjHCwQp2VMnPjLeHuSl1kruK2OjXwanSg1lYxNeWvBCRu55hVjOdimtsRNgRjtXFm88MYAaXudmx4XlZzx+ZjcwNSokH9vFbgu5E6FdXcsBtttNFGG2200UYbbbTRRhtt9B8mcUrgnOYiZSzLmrKyoUySNadsScfEGMaA43HA7d0dXr+5QYoR3hP6rgehA3sPJiCkiDEE9N7jYidpvi95h5gSzpcHEAiHfgdmwnmcyqa1EAKmQVJOp5ySO2R7Oxp8RLAdE1EXKH+0KzMoBswStYRI0jJzOa4VEOyiLxlI0eKJduOOXmY+CoZcHEFI2taNes21q1jdDOPJGLJTTDzl/iXpv/cS8Zqb6w3PhZdadV3ITmDIJsQpThhPk2DI+p/LYBppsvNYWO76Ds+evgff9+gPB/Buh6vOoyOH27s73J3OoChRrL3z6DoPoAOokwjknNB5oO+BrvPo+g6JCRSzfFgiyJzHSZxyQJimgDdvbhBjya1T5kMz2AVjWsGQCwa4RBabalT8aPGqFoPTtixlDNjZMTQYcmlohl1ybiePd4uAGaaKE9KcaXPFPH1HmYv2nJkQizm3IhB7DnV+FQxZ/7D5roivFbXFJ803nvVFWLTCtXLRumf3j+KFCvzaurQlwwOVsvVeVd7nEKfZgtnywtwcbb+Y9hSTbDYDy3hz1Jt6DqjKfFvFkJvhouowtgoPVwz5wZQperw4TdSBspAslRE3T9ny/MTDPDwEg3P7ZXE5U1uwjN28Qj2hc9A81/NjrK3cyGSVfvXY8UYbbfTtpnd29Cgx7/JztqQLSRIho794BMYOp/4VyB2RAARO8GmETyccDhfY769xuLhAcg4J4ixycxrw5s093rx5jc9/9jNcdDs8v3iKrgf2V4z9fo9nz56j73biTALgyfUlri8PuNz3iDFiGsX7OgSJ5HF7d8Iwjnj1+iWO5yNOd2eM5wnn0z3G8SzOHiaXoXeELiuVKQYJKZcjPbjiWevhCHCdLLCGrHzqy5Agz3iXX1qkARzIlRd6SXWhL4H8smaWaBmJAxyJF7JzDt3BQyNJaL6/Zqd+XvwtiTQ45XeKKvVUlToCuk6G27kOIAfmCHVqAWQc5RJ50agjiGMAkFQp+12SRelslXhN/cLWY5dBpNFUGFDP9mnCzd0ZfnfG88Mezy93cOOINJ3xwdMn2PkOd29ucT6dcX3Z42LfgagHEeHNXcT96QSOCXFMGIYJd/cDpsg4jxHDMODu9RvhadcjJpbIL1NAGBM4iJc+AJBzjRLDWY1wxREh5WlulUFdZFWlxRBxNmxkTEp6FgCasiVlvW6mPpQ5WLmYq+9ZKcvhAeuVqvAlaDqRVimUEpzPrbWK5igX4zO5xsSo87StvDEWWm1m2Y569Je8no1KO/dW1oZMuaIYpVKOyvXztow6uOYhaxVyWi+yqJZUBlxZ0PvEqKDFAMv3CAGQDQyqMM5lNO+FPhPkO6lDWrncgYgzuEGy82TOLEuY1JL2SA0CWs6tudMQlzP1vPTDzLsssId2HPBCoJIaSsdQnT5UTo1yn/uqqZPmHNuPRn7vrBsveSsfxot97viDhtdliNO3t/HL05Qm/JvP/g3u6Qv8zv1X+P6vvIWNNtpoo4022mijjTbaaKONNvoVUc3zUbDTFCM++Td/iOPNG3z027+Fy2fPQO4EkC60s+CUPKHzDofDAV3fQ9EuBmGcIobzhPNwxt3NDXrncdkd4Dzgd0DnPQ6HS3jnMx4L7Hc9dn2HvvPZwUPwPd0MOI4BIUacTydMccI0BkkhM02IcZIuGKxK9s0oFpHqJjouS6vQEpQjLpc0NoohNwuxZc9gwQDXNvFYHlJumyCbvYgcXIeSdkUdTOz1LUbEBffQ9VeNOqLpdJ1GKobLGFe+IhlMDWadGbZNlx1efIM1OZDslyxOFPrHbKxhiZiSYsIwBbgx4LLrcEkMihEcJ1we9vDOYTwPCCFg13v0XrB7IsJ5ZIxDAJJg6cf7iHGKiIkRIiOGgOF8Bojg8kbIECNiyPMjVTx3sQiuG7UKaFXQ48y+RZWokVXBlLnOAVvA4tAP79+SOlYx5DL+bKCptn7KDWhkkIq8KoZcSz9IpFgh8tq+YrfqHGXbzDibnShzDHkOKZNEd2HFkO35Ird10bSsV9x6iSG3Y8P2jwV51/DbefMPiKpOERNtJZ9pNsCRbMAs6yrzlNYPVs75WlOU67woa1Y5lQuSwfJNPcVxRZ9Dy5xAD2DIMtYV31Ustw52cQhb7OYrkph1TCMCzeeQFRhgmij343xTatvUbB69jeZtrJ6n9ndTdn7RuzS60UYbbfTL0bs7ejjZ/s1BFT51gBBHhW5/CUYP1/UAuZLDjzmAecRu9wiPrh+h3++RyCGRKKb344TP3tzi1Zdf45Of/BQHt8eb/Q12Fw7Xz4GnT57go/c+xM5LxAiQw9WFLP4/e3KN8iZiSEjAxHh5e4/jeUT3xQ43t6/h/T3O/oyUAmKcEGPOFUmSo88TofMeMUp6EAnNFuX9URwrxEDwLivyMdR3hnH2cFnNFv8OXfQnpJSdDFSXTfLiVd0rMSOkhM4RHCTfZN938sJKOaygWYYlojwmuT4GavQS5UYX5+WIGDqVJ87KnyqA5FiiUEEXWtVTXXomkU16pFTD8akHvssNiy8FQ3NfatmYIkKMOJ5GHE4TPrq6xH7v8GY64RwHPLm6xsXuCl/mlDgXFx0u9w6UjYK7Y8Q4DoguIowTXr26x89+9hJTCDiPA2JMGKeIru9weX2BmBJu7yXMHiZRLGJ29OiIct40GHmpIpzdPFQRMYpcWaBmFX2rjhAxQDb2mKk3X6+6QFUVZ0p5Vqyrur2u/DTfmI0OOFfYSkfa0zMPcc4dVMWzqWXupGTkYVfYiSrXth4iPVbTlBRjhFmuMx60VP6udKnRjJeaNPFaORWBDVMHzJv4ZrWLS5+KEUckDljahvXmgXYrGydUTf5GyNRMCFBxcqAidzWWdQycE8cszs8VqTGPjTpLkIkGUoWSZZGNMdS6YY2x8pGNec7j+zaPCl77QWVQioNYkWA7v4tY7Dw0ijpZZxvD5PJORnO+nuW2mAU86gzNZQhNrmACALfw8Vpt9q+AQgr446//GF9Of4bX57/69jbaaKONNtpoo4022mijjTba6BcmQrG5FRfiGPHFj36CN59+jiff/R4effghSCMYE4OZIEv8ET6ndHZ5kwvnxcwpRtwOI87393jz6g068jh3A3xH2F0Ch8MBVxdXsikt2/G7TjCXw35nmINEHWHGaZwwhQjXewzjGUQjAoV8XtK+FAyDxLHCOVdSQXPSjWG5z4qdkWyQEYcMVIiCKuol/ygXp1ZmFmxgCI6pmBQnSKwMOe4gmG9dWG3xn8qX1kcGQ6ZVXIMcNTwpllMXd1k8VBgyboU37aaD94qJcqlTzkkd1rlDPjg7qSQk5zBNEV0XcX3Zw3eE4RwQOOCw26H3O9zn6/vOo++kt0TAODFiCoKnx4jTecTNzQkpJYQYkBIQU4JzDv2uBzNjmKS8hLuW+SE8u0Z2LR6LsshcpV0dJpgYlDJUnH83g7oGRK5gyGZU2jGaY8gPQKnz+gsMy3MeFKt76GrFHQFF2aidqUUmVWQmQoOFA+1VtskGQ2ZTHu33ppfv1PHlb+tw9GAkE3v9uyzYm3IW/87jLbKjtqjKk8gWnd175jr71TiAMRV3kaaQYslMoXSzdRJ6wCFj1uWFs0eZc7Y9iyEvhPNwf0qliiEjO3u8HYe20VUsZK0bLnkms+ZO1ugcDS8Ge57Ny3nJtjs86xa1DJWy7zqPNtpoo41+PnpnR4/8mBXlhAjdvkPXdXjv0VP0vscXn7/E3c093nRdfZ45wg9/8Gv4we//Z9gfLrE7HND1Xv51Hn3X4VEIeN8TLp8+wfXv/g54msBH8aL+6vM7vH5xj5sXZ3R+h373FPt9h+999wKHQ4/rR8/g/Q7kdxBXA1Horg8HHLoeLj7H6foC948GjMOEMIlX9s39Le5O9zifJgynCSkOSGEAhawiOckXKA4bXvqSlRRZICV0fZ/fCfJS0FSIEhWDzcumvrUZWVFkFm9rR9kRAvDkQL6Hdw6dz3kn87mUlUuXnQh0UVYWeavS3USSyH+qTyhAnD2kNQ0ECCCPhIDEEWOQUIWd8/AkqWqQRFEQRxXRyEqULQY4xzYUz3vN4VhtOu8JznkcLh7jcLjAo8d7XFwQXt+/RryNePHlLY73A27vbnA+n/D69S3ujydIzJeElL2v704D7u4HeMfoXMI4JURH4M7DYQ8HYHch4zeFIGH2YgIlLikq1BvdeseLHHMIsxIhBeZlXt/qdcFZ68iyTrmOvKguV9SUQVYxmHtbW2UKKjmjDOuxKtVV1RSqONtLl5EVzDXVzoIuc6fCpO2vVdh5pqS2fOuivCpiXK5B1W8WRkQ1EIpha/ulN9bSuln5XVtt9LP5FUU5010hbaHiz6JeyYsSM+apKrrMDKdGFql+Wn/X6+bGGUr/OT9QqpNHPa5z2HknoIP3kuaJuXrQqxGVRR9jgneUt4i07c6meO2TnWv2XAYQWqlw6eeKgJrjdSfHsuEyFq1tmp8lGiaUZ4bOvORyfj1Iajw3V7/FgJizvGJvlV0KG2200UYbbbTRRhtttNFGG230baWyiUQ2rLjOwfcdHl1fAU+e4OJwgb7blc1jCgQ8ffIE/PHH+M6Hz/H++0/hnIPzBEcO3jvElHBJQH84YPf8ueCiY0DkiOPdiPNxwnAMcM7DuwN85/D4UYeuc9jtL0DkBecVpAEEYNd16MiDLi8Rdh3GnaStTlHSoQzjgDGMCCEhTEk2NEbd3JaEPzZOEQaY0zTQZZ9ecdao8mEojKxAXV0sNWh8hSFZHEgIEq3Y5UjL8zTHZLAvxfPq73ZBl82fiiErPzmit/aPJRJKAMABNV0513HnpHg4V5yQ5XiFVVIL+WXxOEfo+gt0XYf93qPvCefpjDQyTvcDpjFiGAeEMOF8HjFNU0X3MhY6hohxDFIfMWJK4izkHAgdvAd8TjOh6YWQarRmtvIxzjd2AYALkEcwnaq90ang2sM2qkJNs1PxtdW6ykAtEMwZhvwAGGqrKNVSc3C2lVEPzvDx5mxm6SEM2TZojmrbDbtmSxcz3rq+bzBkW0/BDGsjS9jwIcBwdqu8dQzWLs1/qhPFA9cWXk3n8jwk5X81lMs6D43jhZ27uZ1alXSIsseRFG0xUR3vJtJIFSwAWh+XOc9zHJ5suXmZBwbZ8M+aDmaeAoXQOHnYntZd1rMHjKm7pO1Z3D+0Mm/afq6dXiXrSNLcR1oXYQORN9poo18VvXtEDyA/ycRBwe869PsdPvjgOS73FzgdA+LE6FyuUrQpfO/jj/H3/+7fldxxjhBTQIyh5GgMw4CnjvD48SN88PwDnO7f4OVnP8XNzQkvv75BCBE//fPP4GiH/e5DPHq0x84/xuPHF+j7HXY7hsuh2TRc3eV+D9oDe/8ewnSF89OAEBO828G5Dl+8/Bpfv36Fm9f3ePPqDuP5BuNJInjElMQTGh5EHnAdGAkxabi+HGehsw9j1jSCC+UiZQcAXaBVpwDfUYl0QGCQ8/DkRbZaNiuo+gJx5U2rKRUklQjl/jcLoMwlfxrp2BXFN2ltcETZSSNhChFDTNj7HjvfG31LHD2KjmsUT07qHiB1p1TbdI7gO0Lfezx+/ASXV1e4utphfwF88eIW96czPv/yhPvbEW9efYrT8Q3u7gaczxNO5zPOw4gQIsIUSihE70jyc+522F1cgL2kufHOY991mKYJN3c3iCFKDjqgREKw+QsZALN43yOJdz2zR3H0yGM51x2bdBXFVhKHlBwVsspDFbhitVE1BIASuaEMT1WjZjRXvpaKO69+zjWZ2c+Z/lscYFb0oHKNCMocpKocNaesJNjoc8ZQULWyyGdmGLBGjsm8LQyDWR9miqK1W+YsN0r//JTOk7Jpg5rUe+B1VxfbOqmCnGUKqka3HWeVkK1PjnPhu1RhSjkisHfgJNGTKIMMjFTqZVAJqZkYcA9ZSka2ZU4ujMciivI8sfe95X5hQ82UfgUH9NnXGmPtpYU/MlOvupnDTJpGeuV6y+dK11ujwD4ffg5Fe2FU2LHeaKONNtpoo4022mijjTbaaKNvK2Xs0zu4zuPy6hK4vsZ+v0fX92VDWwYo8fj6GvsPP8Lz99/Ds6ePUVKsCMCCnXeIRNjv97i6vMI0nnG6e4N0TjgdB6TEePPmFgSPzl9ht+/g3R77fQfnZYFfHSQUa+q9B3lC5w5IqUc45M005EHkcH864ng+YziPOJ9GxDAg0gBE2WSTtx3KN3JgpILXcj5D3mDIVPc0VQQpIxc573OJFps3AAreaDAdkmjNAr0bLEMxZMbCkWPdAUS/6eL6YvsVgBYn1PjPKTFCYnTOwZNv+tLiPDZ6ahur2G5CUycP5x32+z36fod+5+E74P40YJwi7u4nTEPE+XyDMA0YBsH7wzQh5OjdKaaKQxLBOcB5D9/3WW6CoXfOI6aAYRjLpswiD0KDNVWcrKBtUAeYAniuYMh1zOqnzA8u+Gcr63Yt2K5tLwMkvA2ZtPjfGhaYeSITbQOmLzAD/k5trDUxx+u0jTy3baRplSNQ7vUlhjxDT031BVte4Nz2swD0aMdk1lWajcbbnBiUd9M9Pc7NlxUq5c2FQMWQm94WaaC5n0oTedy4jmkr3oyrsnHvYK1L/lZ83n6xzM+wWOXVfs67V5cLzFz++TDkUopMX1doLiv7/CrM2NMrWG656qFoJHMMeRF52jS9du+UQVnHsTfaaKONfhn6uRw9nPd4+vQxDhcHfOd738Xl5RXef/wEvfd4eRwx9T0unj/FMLzB4+98iPeePcHhg/eB3Q7TNGIcBkzjiGkYcXt/wpvbI+5v3uD1V1+CyYO7HsNwwu2blxjOI6YQSyi8yBNOwysk7vCjn9xjv+9w8Rev4bs9dodn6HyPx1ceu53Ho+tH2O16dL2H6zx2zqFjwMED5PD08TV2vcN7148wvD8iRvk3DCNOxxNCjBjHCeMYcDyeEaYRp+MtUkqIObKFKuUlj2KOGpGy0pqDD6KE8dMchrk/iNK3HKwDnZMoJwxZX6b8siUyuR+hSoR8c87PVMH6tpKXqc0bqAq0hA2UOlypByDs4EAU0TnxNtd3u6McFINzWhM1NKBRRqSfiUXRV5481Au7R5gm3N/d4k//+EcgR/jyxUsczwNevxpwPgcc719jHM6SGzMkTNOEkD3oxbtauiEGjEeMjOF0FmeY3O+BCClmD/uEEgWgpKd5SEEtEVGynLPyns2xpmjxbG105hzJo1F2sPJZx6jo8827vPLYmBONfl0VllU13eoib1HINR2Idqr4ahhZdH0HR4RJwxcaXtq6jSOHdRpQG6FRqG3n2/434igacXX6WChtM0XSeiovFtpp8aX81Hledc7lGLb3WauULihPEs1Tac0GeyeX6BVW4dTam99VweZGhgA5ST0lzlgJYLkfG7XWROiYMVrqLQq/CqPM1znvqh9TuV9kkGdKMM/G9yGdVXeDZF5aQxelL6V1ml37NiptP6wwW+fqbyaeDf/ceHhrUxtttNFGG2200UYbbbTRRhtt9O0ggmzEuzwgdg4fvP8cTz/4EC+fPIE7jzg8usLu+hL95QEhnLF/dI3Dfofp9ojh5h6RNVpvRIoRwxgwjBPG4Yzz/T1ADuwcYggYzifEEBFz6mgx3ROmcAaD8PLViM47dK/PcK6D7w5wzmPfE7x32O128N7DeSoYi2NAXTgO+x28I1zsdggXEZLOJSKGiCkEwYqj/JumgBQjQhhyyu4c7deukaLiZboxTJf+GKj4MZD7Ihg0mY1ZzskmTAtRCIZMBepR5El3jr8dQVHHl4rt1JQurVMCkYMDwTvZHSURPex50xfoF8V88hnm2legpBbuXS9pcWLCxANefvUScIT740lSd5+jYMbjWVKzB9l4F1OqqXTsBjYCAAdOQJxCg9lEhIylLRd1Gwx5AaktJanpzesBHQODdRmvDVrDswxENz9OtHbuLRjyN2JTGklmtur9NpzN8Fe7UsfcOXGgijGV8W4xZINnsz00x5BneKLKbgnnmvNzXrkeb6C7eT/X8eUlzw+cbhhFe6S0PZ9cULi74ZfJpkLnei/bCx+YNosTOkaL547cg0k37a5h8g9GFVm2yApqPyS+0l0zUdlcM4dVdYwexJBnPK9gyPUIrU2bt9MCC19p/+0HzOE1nHxtsr69yY022mijd6Wfy9HDdw7vf/AeHj9+jN/9nd/D48ePsfMSteJnd2ecOo/L508xnF7j6W/8Gt7/+Du4+PAD0H6HcTrjbjhjvD9jPJ7x2Vev8NNPv8Lx5hVuv/4MYgV4TDHiPI0ARKmWZyMjpYApvMJ5AI4/EbZjDCDyuLz6Dva7A7774Q7XVx2+8/HHuLq+xtNnz3BxeSlpUUhC6nNiPH10hSdXF6VueA84j+F0xv3dHY7nAa/uj7i7vcdXn3+N8+kew+lOMkWmYJwL8kuDCM7lMHohp0fxIjNO4gAB1PckMyOFHC4ge2E716HvOoSUMMUIAksmEVDxcE81uQY0/J+8IlKjRegLTdokuY6BmlJDw9Fl73InqWJ2ROhyJJZSA0uYO1K+s+OKKB1OHC+yXMUhR327AbBDv7tE5z3COGI4BfzlX7zC6Tzg6xdvcDqPOI9BHGumnG6lvNy4yK+QIyQmMDxCiOBhLK/wlBghSiobyuOtHvoxRztQyZUWijAJ6qwBUDYOUzZWXHsNlq9xIjEG1amG7cu8KC1qjZnr3+VFziiGqnU7SatlZzn1yDoWVD3bKlji1JLyVKx5J8kR+l0P51320g8LvnSC6NRbU6Aapest2lWj21kFjxzUxX8pruo1q800ew8Wzh4L7qB3ctMv1ia5Fms8uLXedm4As5lSjB8q48jOFuYyKHPddOmAwGAWZdzuPBEnLQBljj8QJtHql/o8KkaChuBszC7UnRYzAyhXWVIhad+o3QFRCq6QM9Vxvp4Ikvu0KPVLc2XVGF40Y5xSVj0vqiEq0l+bWXYwqhGqTmBSueb8rWDSvI2NNtpoo4022mijjTbaaKONNvo2EjnCxeUFaL/D8+cf4L0PP8Jnz54ApzMO11fYF0ePAw5PH+Pi6grHL1+AOo8IxhgD4hgQp4Db4xlvbu8xDWeMx1voSmlkxQIbJCAv4J8QIjCFjKmmBCKHvr+G9x0eXXnsdoTr60fY7XY4XFxIlBEFRzJkc3A77Pu+YgcZOwshyGbGEHEaJ4zjiOPdEWGaEMOY02CnjMdUnFXTsFhnj4IX57QeNeIDygbCukYtPXXOlQ13uggsdSsSyE27yNhyg1lijl5I+m4baUNlKn8z1kgEz4BbWXwuOKTFRzOoIovXVPpY0D6WjX2u6yXydIyIIeHmzQlTiDgez5iCOHkkFqeaBu/JGGXd0AbAEZgF9+bEJd0OMjuSJt1gpyq3NENcqVZpf6ucNZX5HG9dk669rkRxmS8IEyxg/Y17nGz/l3C0RYXn15h0KRYTLLJszxV+iZvjuVNw3oNc3ogWH8AGDda5hsc1fSXMO9OcKtWuYXG03v68ulKPiSjyMBFqipW27oaPJYQ6461e1wY84SYKOCeuu4tLBzQd1IM3cD6WpavPEUa5b4VSuXg1QoZd/LCd0zWDgqsKVq349tswZHLt4HLBxOdtrXRnVobBZd1jft1DU+gXpxZDLgNe5PoWDHnOXKENQ95oo41+9fTOjh5/7+/+Hfiuw4cfPMfh4gIXh72kD0jiXb3rCYeLHlePH2N89h4OF4+w7y5wPA748uuX+Orzz/Diqy9wPg04n864P55xf3dCmAa43Q4pMuKUsoIrC/XedaL4xQBygPd6XBfYJBJFnO4wxBNevOpxe+9xGiIOhwOuH7/E/rAHsAORB0cACbi8cri4dBDvbId+t0O/28MBuLq6xG6/x+HiEsPjx3jvyWOM44i72+/gdDzhiy+/xDAMuLm5AadUvF81eoZ4Dued9fltKkq5OHZ0XQffdUjZAUTfS4kZIUQk2B3s6vvLqOuIcyWv7vKnoonpm6Z9USRAlFyW76IYpxzBI6dSUDdhoyDq6z+xpLap+kRCjAGckhg4IeL2eEaMCSEmOHK4eX2WBWEOSCnieDwhTBF3p7OkZYlRZJFzXy5e7sWlN/OTEkKYRIHISrkYIdx4wpcoHmCjq2lOS/NCLbpSXsA1IhODK2WlP8vFqkAzw8dGUNF3flXy9Xotizo/sNRBKw/Z8GmsrBoKkU0bVvHh3AHWZtbUG1KuG81S/iYgTBNcdEgpYo2aMJBZyNYYNeyYmvXobKDnCiSbA+Wr0TR1ms50IyuPtsVWwSyDV8RKTVsEw4KNXIFs2K70z7bH2eul5lmVwhKFk7KuXqN6mOobjsu9bRVilj0h6qwFoOS1TTE7mqEE3svzJwFxpghrO3OrMfPIhQdbulJS49eMfR0hK8hWNs2hwk4e0IWimx3H5lNXDePFmGiqH7e812fEM77mxk0TEUnP68SgWUmit7b1q6JpAv7b/xb46U+B/+K/AH7zNzNvDHzxx7+Blz/9Dr7+s+//1TKx0UYbbbTRRhtttNFGG2200UZvoQ8//ADnwwVePHmKOE3ouy5DYIw4Tfj6Rz/Giy++RH/osTtcoOv36HyPJ9/9Li6uH4EuL/Diq68RppgdKgKmaUKKEeR8Xqjngl8AEnGYASBJFGPKWF7ZLOPU4WMEeMLp7DFOhBAEq93tT/CdB9CJjZ/35/U7Qt9TxgIoR//oQAD6vof3nUQy3u9xsd8jxohxvEaYJtzd3yOGiGEYBC8roEnFO+quLLM0mBhMnCN3uIIJ66UM1F35WGLIDTYxw5CtE0E51oCh9UPxSgLyJkaGA1WMShmiiuNZuNVuiqGM42pE2pQYg6bqToJADeeQnUGk3DhNSClhHLWcbmTkBiKsDRtsL+NxSdOyKH5k8G5k5MviQw0G9hCGbOXWnMsRk2eYJs+uL+3Oxuob465QaWaVuLDEaNFLiyi3n4b1OhMWqZ+5Ee1awylGiRT8kMOEgceLPw5zi0k2Xk+zC1fqWsiBzMGFzJfIeMGQZzy/FUNeqanBkL+J5vN2fs6MlEaKaURCs6Krg9zezzwDd1tMNfefdE7KRXk5BBXD5+bapj2DBLeSrAw2TljaBtBGuX4HDBkWkl2ZagWZrpMZjZC4HSvlXMbw58CQZ/1ZYshacI4ho3birxhD3mijjb5d9M6OHv/4H/8jEBEu9heycK+K5RSRYsBu53F11eP6vacI44jLqyc49Je4vzvh08+/wF/8yY/ws5/8BMdxwHE4o/cddv0OruvgDnvwGBCHAQmAIw9yDl2/k4X9FOHAoE4cPfrOlwdxYsY0vMHICcdBUrN8/sUreO9wcXmJfteD+QLMO1AkIBK+8709nn+0A1EPcj0uDxe4vrrG9dUVnjx7KpEq4MRz0hNCTDgNI169egP3h3+E25s3ON3fYUo5goRRdDiJdzG8jaagDhGMvu8lwoUDkAByDMr5+aYQSnQQuVJetqm8heZvIt1Jnl+25eWZ8u8u1yOvOQnEQeXdPgaJonHRd+jhssJWF4JVKdf3TizKt4iGGYhpQowJwxBwHkZ89fUrTFPEeJ6QEnIqF5GB8KYv77obHrDKf114LmaK0UJTkvkmv40RhGqA6LGkzh5rL36Vm1F0UjmGotQWdaCIXjq+WPwmKm1VPcc4UZDHmjcHzZWZcn02fhjNGAs/dUxKv7GSl7NYPQ9okEV+rsiseuAywjjpoVlnUSKmlPaMwr5clZ/9sNPYjGGtDLNjbH7PFLRSXZ0krTqIhfJU7tWZnj6XUvVOr0opr5ac81i1bpuDUKYH1WgWBP31oG6n80dtaKmjzjMdXec94BxSmmptVo4sXtaUQynOWzEXiMHOAMhno2JVc86OHrWtZt7bJqj5QHNL5meONlkU5xKNJu8GsAYJrOFoPk2jRLPTc+ZLW4bNYgzPS7b8PyS/5nm21uyvgMYR+K//a+BwAD78sDp6gAmf/C+/g3/33/3nf0Utb7TRRhtttNFGG2200UYbbbTRu9H3vvc9nK5v8OX772M6nbHrOkGeojh6fPWH/ysGjvj1f/T7uPy176HPjh7v/foP0R12eP3yBb789AtMMWCKAZ4cvPeyMbDvJJpyDHlfmOCYkt6akVg2qMmGNtksqPgIg5HCGREskT6IcHd3lqi2vUS1BfdgeFACwITrRx6X1x6AtN93PXa7HXZ9j8PFAcJBxlIdSsTh02kA5c2C0zQixRxBghV/QMZqOIM+Gf/MUYY5MbzzOXIHDOyR+5H33lSMggymN1uMLRhyPawQRnEK0IgfpMdRNjExZONfYkbvHJzyw1RCthZMR69X7NT0V/sVQkKIEffHE1JMiME4cBSmLf8GS2ywLoMDtVdlcSTZ9GmhxDlgUzYv1e/LxdrlhS2fBkPWCAfNivyc1s6ZYw+G8ZhFBObKR5Gd6ceKNFGivNQwtw1ANot73PJmHHr0Or0ypQTM9wku8F+D+1ke7AUN7NuO+0NS0fMPFpgvp5hfXPryDRjy7LOpp4EkK4a81mIFFx9Co7XK2qE5Hlnx19VLG0zUOh+U9RbnQMyInJ2gSv/nE5/W2zCyLk4oeSxbDNmsG6RmoNuqzHOj+Wx40e/UDtF8vuhGXlN+VkF7jzE02NFbMeRvotXIKPPmmwN/VcjxRhtt9G2ld3b02PWdqK7EAFLxpH19d4vTcMbrF1/h9u4WYTgDEKeF8ziijxN8CogcEBFBDui7ThRtSF05kBqc46IkOACUJOKEuDroQiljDFPmRVKHuF5Cu10/fYJ+v8OzR0+w3+1xeX2F3W6HGDtwIoRJIke4fcDAAcPdEcPxjKvLK5yuB8RnEZeHg3hy73YAJOoHZY/ty4sDvvfxd3B68hhXl3sMw4g3t3eYpgn3t3cIUyhKVUz5HUmyuNr3PQBZjGdWD2jVVcUgIKaiu9aFc1GgmUTZsq90fSeVqHJOFTjKSnXNBclgKcjyBiMieAJMtg4xFCAe5qSOC2DJMxkjQkwl/2SYonhgR/mcJslFOQySQ1PD6D3wHkdxliCriJrFVs6sGi8azpaNOjCIclsbEHHPXvjLZtuzxtFAx0LdZHIMFGPktK9tsnVou6wRBebKNzeKBM+U7nZk8xgSJGrDrD/ahaUBs9pjFIOjKHYoBpRe+zY1w/piFP44AXBmnqBpo3R9fU281Nm0xw8wUJhsL6DZ6bk62TBumTf9XxvPZOS0woUor1q+8KzODa1lwXawlB+rcOc5x2bWtioom3rWxVPuBqrpVDglM96VJ+bcQao8t972VJyldB7reetIJM3leotR0PJXjbhUN6jA3O/UFF50rjFGZmdaA1EP13tF5qedmw9ZJvWzLZnvv/l1iwm7nOC/SlV9ihP++Os/xtXuCjfDTW2ZZ30nxgd/6xPEqcOLP/seXn3y8a+Qi4022mijjTb69lAKDp/+4W/hfHOFj37nz/How1f/vlnaaKONNtpoo79x5J0r0ZjjNOGzf/en2F1e4NXLl7g7n3E+3WOKETHIRq6YZOH/zSef4Hx3B7fvQfseRFIX6QJwxo2JuGAwCkkUINHgDkyMqJv0soVPXjYP7g4HuM7jYreH9x36XQ/vPZgdmAkpCv5IPiFwQhwnhBCw63tMY0C6OKDvOjgnTihCLkOEDn3f4dGja1wc9tj1HiFGDMOImBKmYRTcJl+VIYxcRU3hrTBThpcrfqfRpWcYsmDLuc4VdJQIxkGEm4stNiQYsgJeGR+hZaoWzgv/FX7jksI8JUY0ETw0BQ1zQkyS0jzmVCyafqaFXGrbOrxNGa4yKUPfYG5csNwVdKdcb1g3gvqG37BszeI/FHiLCz5fx00vnFVIpg49NXcWodp7Mg44lfUSU+BhsjAWzz4XBWe/DIb8IFFhdFGfYPwteP0ghrwG5dmBsiEZtE8LeG5WbsnsW3/aui20uyjyTWKZz51SPuPcy1O1T7N5UJ51FlRfm9gPYci2vN3A2dwnpj3UdQnMcVguvQDAVdwPyWM2tg1v2keSBmy3V6enxZBbEH2FNN3Nwxhy4embMORVedtL7P36wIRZY/Rt03SjjTba6B3pnR09DtlRoThdRFHCP3v1Aq9vb/HVp5/g/uYGw/EeQMIwDbg7d+jCAM8jJkxICPAeOLhcVxIHD0oJDgzvWTymo7xIKEYQZ2eP7BiQEmNICUSEq/1BjAe/Q9f3+P4PvofHTx7j17/3a3j86LHkWdzvJT9iDDgOI4ZxwidffYXPX7zAi5df4sUnf4lH14/x9MkzhGHC48tL7C/28DsHYg9KHoBD13V4dH2N3/nN30TkhFP8W7g/n/DjP/9z3Nzc4i/+9M8xTTGvMgIhIhseEqGj70X5TymCOYlnOWVnF0bWLl1+oaqaSHAQZ5aqJKqiXcMShrwyzRoqIB9PMVa9jQFOEeAEch2ICb0DGA4+v6wTi+e7Q7vrP0wTzmfJizhMEcMw4fb2hBiieKUnIIZqeTAAaO7D7ARhlWp5b6a8IJuL5f/YvlxZo4dQWdgsKUz0BZrfyNK0Sm2mVRhNqdHTiyKooRx1ibdYVyiRSAqvtW6uZmJbZ/m0qr52LC/Ec5tPchElYKH41+9s/hWuWSXa6GxgLMPmJTV2rJhM81Vs2kNjQHBtXRKIuJmm9HOQ7Z4J82DzPLZVV6WvZXZu+K1RawzOF8rteLG6+hSXXpQpJ7fqkrkyc3RSFSV5FlUmO07UQ1WFnkc3sbM1pTpYRCsGam7XdR6UndrWNFCN9EIZcKkpgahVlJHTyxhnmHl0PnVaA0zex5WJpPeN9rlJNbXwpuHVrw9tZqj3DTfzPKVZupeZzOqd0k6YIlvScZnLr/yR37Qi51/wdlijIQ7415/861zt2yv+4T/8I/zgH/xv+F/+7//l5uix0UYbbbTRRr8gpdDhT/77f4huF/C//7/9PzZHj4022mijjTb6BajzTtJvgxGGE378P/5/EZnx4s0bnIcBx5sbxBgQpxEAS7qTacInf/S/4dM//mN8/Pd+F9/53d8GOaAjcaKom76yRZ8XSTVOKjWbw7jgYZoWpO86OCIQeTjv8PjJI+wPezx99AT7/R67fieptmNEYtnwFmPCm/t73J1OOJ3ucby5wX63x+FwgRQT9n2Pru9APmNn7AAQnHPY73bYP3smqbr5PYxhwqvXrzEMI16/eC3pqDOkoMijbrD0riuYDSMZzHINyKspFzRVjR5vNhXVXV9y1gCYDG523KsEJX+DBzHgSTDksvk975wvWFBuKuWU2+K8I2M7DJL2O8aY8WmUldyKNaLwU/gtp+qYWsy8nprjczMMt1yr8mpxWAKaDNJ6cIEhmwsWGNMsRcN8o2HFE6usHg7cYbHgjFPOIaH57wbiajFkMMpGs3r5QxgTz35lDNmytoIhl3mWz9fuVxy/DtMSr1z05a1k8XS9wI5xPqYY8jzKyrtiyKZcMxdsJYoLko2WbUeAYLyvZt2zawrcNmTmk0Fmi0glNfdaB+rayry7ZQEh38XkxDFM02AtxaByqGsPy7mZf9HM0WixzJEx5Dwm9UneFCrPA41y35z8pnkx7+/8tMHdaxT0GX6Merz9nI2j7JIuc6GZ0VSPvfXG1ep/hTjyRhtt9O2ld3b0GMYBKSXcH+8QQsDpNGIcAz7//FPc3t/h9tUbjOeTRLVIoshN04QpJkxRg0lw0SmJCM7niABJn93iBazBPmJ28pDnowNDDIX9rkPXd3jvyVPs+h77HDLvow8/wtXVJfaHPZwjpBQQJuDm9h6n8xmvX73C3d0dvr65wc3dPY63d5hCxOl8AjkH5xlECf1+j8PlNS6vLvD8+TN0XYd+dxDlwYvjx8GLo8bHH3yEx5ePkIaI+7sjvvriS4zDIAq7qMoo7hlGoSE4OAISkyjtzJDoFtwoUYwIZnlVFsWfU1HI2bxJUhKvdobkb0wlakZ+7TgxOogIjiTtDYp3OzCFgBAjOKdcCSFimgJCmKrXeUiYQpT8iCkhRVXuYV5MVbkqXvf2tFFcbKQ46CdLnYm5OHnYxVUtt3hxZ92tstH6r6untk0DoY2LslFrreqGQ6PgZXm2jgFzfXq2OGyUBjVElyki5sHxqsFVSlT7pHxR42SZymJuVCzVnMbMMWWt8q5zt/RPxzIf0KgxjZCbNlqe1jmZ1WlmT7miZbQ1Mooix02Rlol59IrWKJiZAo2ypuWZVA3V+W5lo8qh3NuaQ5GMk5JtJaWqEJb27c6TOZfqHKH3gxpo1kiiyrvzDkzIO1CMwHT+Mdc6quUAsDgMuVawmBsKNTUQz8bC3s3yvcpHjpE6g63o6EXn5tkz04w/rV1oZVPamc08e81DSrQaE5l3dXZaXtA8WczRdzA8fk76JgcPwDy6OJVnzEYbbbTRRhtt9IsQAUzgROC37gLcaKONNtpoo40eohgFSzyejri/v8cUImKMuLu7xTiOGM4SDTrlyMOJxQkgpIQYa0TnAmWAZFESaDAWA5llrE8teglf7AB0vaQ/udgf4L1E3/De4+rqGru+h+98xg8SUgoYxkmiVJ9PGMcRx/OAYZowjSNSkgjWGM55cx/DeY+u36Hfdbi8vMgRPjLcTg6OGB0T0BGuL6+x7ydwSBjHCcf7e8QQFpic/LRLxYppZZzC4jvADMtg8xcg5iWGnHFXG2ChsNDAkRqhpOKGKYM1Kacu5yRtpSQRoVOS9OUpaVQPLlGfDYyEupBtMYw1DLmeW+BLqP1i1OivM5Baa/4GslhxxezK4vSsKBtcuGLIIqiSfV3n6aKdBQrZllAMeS6FgsnOMGSL32V+52vkWkGz4P4QS6at1XIPYMjAXPRahlbG5AG8uszth0Ys468NS6udRdMxm5oFivjNqBygWSvrtS+PzpD9PL/nXa8QcYt/142WbeEl/o3ZAFcMs97gqM5SWndpuGLIrJE9dB9nwZCpGYeC1VuHJjbH2wnZDG+zPsEG9S+PLFLfk9k9bip9CG61Q9zsaC3dXOGNDYa8QKZRmbN9WXlQ6tio0xqbZ9DqTTWnXz2GvNFGG3176Z0dPW7vbzFNEz792V/ieDzh5Vd3OJ0GfPHic3GUgETf6FwHR06cHRjYDwE+MKbAQBSFMIGLYs2JkAKDE+BI8imSF2VwnCYAebGfHBgHdH2P5x88xcXlBX7tBz/A5cUFnl5eYt93uH50jb7vENMEcMI4njAOjE8/+xJfv7rBz/78x3jxxaeI7JDYYZwmjFPAGEbc3N/gqxdf4Md//hOQ28P5K3zvu8/xD3//t3F9fY3nzz8COYfUeTgi7GmP6/0lnj8Sr+z33n+ON7e3+Lf/8x/i5vUbhOEeHAOmrPgmhjitEMORLu5mBTC/JLIPtcRMYYa8ZRPAGplDcqi5/Cs68RTXV24q8ffy+ZwygbJi7ryHy4pveU1zKor4aZgwThHn84jhPOJ0HnE8ioOPRCKhmvWhLDwD+mJiQHJJ6qQxUTKsuVI2wefrXHmvVSUl2w3ZCOF6Leqr0pVayTibiPyKQq485nYAWfxuWtP380J3ry/1GiUke6vPPMvrgvS8v3ls8ldP9VhtYa4+GmXBvvSNUVS0Faq6R2ucVeXGeqkXfS3LU8Rrxs8UZKBRxtROqTpjq0iXeVFXnQ0fRnW1elpR+FSR4uYyc2nu46xVq8MVY2OdioKbanKeNZ2KyK0rWlZZY56leLERJRI0PRIVp6Dq5Ib8DCS0fZsTL77I46A4MBgFvzjcZIZ85wAmTBzBkVt5lj7Ir7pLokbdSEBJ8aKOGWV3Rx77lOyOAoINgNL2Yqbk0mwu6fXgdkFFd5mYP5X3Os+sUTQ3IBaRcowMFlNFRaJOMFQOt6XfNmgkeYA32mijjTbaaKONNtpoo4022ujbSsM44jyc8eb1a7x4+QKn+xFhCrg7yeZBIMF7n50cZLMgJ0YICVN2DkDeFMh557QjJ3a77KvLESoA3TSXxOOgRk2ARFa+vBQs+cmTJ+j7Doe+h3cOu/0O3jm5DiwRRgLj9u4ex9OAm9evcLq/QWIHBkma6pQQx4hhGnA83ePl61cg6kCux6NHl/jux+9jt9vh8vJKsBQnmIuHww49LvcXiCni4uIS53HAF599ieF8RgqCY8cMylgcoiIMBYyDbkopyF6BawQv0SvJ7KBPDS5nMCqzSCpOJC5jIg4aqVpI5KRpWEJICCkhhCgRn/NmwbIxqGAsdV7YtVPtokV6WzSFZ1+pYDVl/VmdGgoWBND8OotBIbdXZGSwU9viAhNaYsgKy8Jco50s+/sb0NJWxrOL2n6XDV4ZT7QYb0X17OBZPoww7Dmq/2pfTWdKdQZsbKrgWftzrps/c3bbgg/BZm+VCwzjrUDnd4pti82PgiCabjeX2UlAgpfXqMTrnXhwwxfZysyY2iqQ7+UMENfbg9ohLA4ElvGWlwWXVG4P+d7cY+3oiRMdIcWUceF6k1UcVm++ivc394Y2VrB3y+os2nVhdUUo89A6y+kofBE3z686L3jevVYQqDxaB7b88sCSZpOEYHiEaYtLU+1TY37zt/Q2iHmjjTba6Oehd3b0ePHiK0xTwIuvX+J0OuP+OGAYJ5xOJ5yGEzonDhnUEeCAmAIoEKbpjGk8g3mC8yy5ACMATcmSCCk5yeGXI0swxLGjv7hE5z2uLw7wvsNu/wjdrsfTZ4+wP+zw9NEVdrsddr2Dcyy8nIDb29cYxwEcI1JK+PLFa9zcnXB3d4dxikhIYKYcMq4ukMaUarQHAt688fjkLz/D9fU1xinhcDjg8eNnOc9k7q+TtC6Pr6/hncN3P/4I11cX+PLzL3E+nUHhBIq1jaIgE0k/IV7nLr+MdAGezJuMNd9hvl7eta2aKiddKcOQ1AriNCIe1imHTolZLuMUxFCJCSkmjFkxH6eAaQwYx6mUVc94GGWjvJPzy1B7UMh4jVs2rZJV3r9kZGNessYMaRVEsvrxWnoJNukuaPU9P7MsDJOq4K5po033Vo7ba4y5Yvhq3vlzY2J+rbELcgiYRjlcV6+VD1XE1s8+TMpUWirR1nDhmWGxiIKhPQE0EoNuSGgCmJmqWTtshs7WyCSGajW+sgQYOW9gnhizsHhrtCqahwRDqANulUe06r2d860DulUiZ0zNdEaen5uzp04Oub9NP3QMOJuV1DpyNHcfI0d/YKi9VgCChu+HPdnnCm51luJ2cFWpby/Mjw4Zc+vEtLij8h/imbCQ54SR1XzHwzxWjh5tP9upvjKDV2mRcpGys8qmqG+00UYbbbTRRhtttNFGG230LaXT6Yjj8Yjj8YTT8YRpiggxIkwBY5zg84KgOgUwC+4YU0CKAZJ2OsMeJc2H3UBTMQax4x1cJ5E7dl2Xo2rs4LzD4WIP33kc9r1sOnSCsYYpIAAYxjNiDBlvY9yfzhjGCeM4SnSRkno6L25m2ErYYgABSMBwPuPm5ha73Q4xMrquw35/kJiv6jBBNa0LEeHRtUQVub+7RwgBlCYLNi4cI7IUzELwNyweKnZkFpELSJmBlAa31IVtBjRdiI6RbhJMzBLJm1OJ4iH/xFlHHUYaxm3b9nBxRNExtuXnaGnF5AoO1CwQK8ZFpV8FO64QGuwCdbOf6yGei8zWTitPPMOQV5Det+CTc1pgyKs1t/jz/Hzj70GClS0j1lJ71YMY8mxRfa0OO5bz6ucdyF8eROv44Wi+CwzZLjYsMGRkDLk90Uw326/FdKvYIa/xOx+CRpwzQSiAuJg/7uHp3/C0xEPl6MMA5EPyXWLIBt8vMrONzwZ2LqcHWZidXGDIZtOoFpjLTrHvyjL0XfBg2zrc73DPkf2Wny3r/VjvUgWk1ybRW0gHfcOQN9poo18RvbOjx49+9MeYpohPP/kawzih23dgZtzcvcHpdMJh16HzDnRgoO8xjieEOGJ/uoE/eiQ+o9sn8AjECFH+AiNGjxhdjhoxQR7eDt3+gMtn7+P68go//O53cHVxiY+ef4Ddrsf+sgcRkCZJkTJNA0KY8PVXr3E6Dvizn/wJbl6/wnk8I4SAEGXRX1OZcHYySU3KGIeY5FyKZ4Rwh3F4g5evv8aj6yt8//sf4/n77+M//Xt/H4f9LjsxOjhP2PkeH7/3HsKTJ3h0scft/RH/w//4hxi/egV3nIA4yQJgboeIkCDROKJG+wCXvJIAm0gADikbIQ6qOBolKn/KK8WbhXEGHMExME5BHDkGSc1yd3ePcRpxfxzlXEjiaFOiFJjUFCo3iIep02gHDOhiMgrfqC9kzehBaabsKt/cXCZOKm05gs31SOXlp9WlbHBk8wrOlUyReRyjXOuyzLnWrG3Vv2ouIefJ5JxayMFGC6k11Gssx8Cyu8QEV9LyqHGIpmybm26moJPaYGLIJetRT1mpoxwpBTlUm1WeVnQMAoo3cFWnjLIljBunIsBGRyCooWjmoxqKxfKuMgFn0zgr4cWmtNepVLPVvK6rmbx3JDwRkOep9mumT8+lakKgLGzMlfJFT+eVyBgLu4pUOkgMOBNoY24/rU8fNa7WRkUbIWNEzi0J/S4ph1xmQFIs2WryfE8mxJ7Wl+RZVYwYWnQyG42uGnJapR3XBDApaKPPXWU1zwPkMcz32Xzgyjwle2Qpunpm9mvNwDSA0PySel/MbKlGAnJAs2/OwRXmlWfeRhtttNFGG2200UYbbbTRRht9S+jly69x+/I1Xr58jVev3sB5wesUp+28LG7GFMFIiHECAIRpwDSdwQhwnoEoewUFp2BwcpICmxnMsQBmznv0FxfY9Ts8fXSNvutxfXkpjh29RDnmGMHMSCkgpYj74xlhCnj16gWG0xkh5RTVSaOdcl4ATRlH0LU5aZOTRGvlFJB4RAxnnM5H7HY9Hj9+hMuLC3z00XdA3jewmSeP64sLpP0e+95jGCd88pdf4v54Bk0RGjlDUIaMl0DTAhs+ysKxWRRnyqkYFJmqIGqBLqjUXPG+PG4EceDgkoaFMYwjYoqYRoloUpw52OAhBcpqF4hbaISWOAuZ7xlDaoEly7jyr5e1uI9BC6Eb/mxVrHhlPlHw5ixtif5r27ZttnIq2Jjyxjyrz/Cli7lNx9va2v7maAVN/bVbWnwF1arVWV7YbKK0uGPp24yJORiaf5ToIvrbsgyUeVVlNcOQFyiv8sOmM1VOXDbzcTssFpumjCG3h9s2mr81Hc8yGsTKpTZ9CVtxrTS21v7bMGRo/aboA9OjlH2wrQcw5LJRUE/PMeS2wppuXtvTeVLne43mPJtH9t6btaVPnNVpYLtAFXcvayfNvNNyZuDmMn7gvrLj/VbE9qGFAr1+drHeaw9hyKb35p6GOcbt2G600UYb/YL0zo4e/W4PIMB1HhQCxkkUvZQiCMhOAvlfShK0A8A0jBjuzxhOZwzDgBgdYvIg5wBieE/w3sO5Dl1/ga7rsd9fotvvcfH0KS4PF3j/vWc47Pa4ujyg6zx85xBTxP3xiGkccPvmDcZxxOubM4Zhwv39Pc7DiGEKiDGAs0NCSnWBT/Mbyo/WE1qX5GNKmMYJ5/MZNzc3cM7jiy+/wtXVJT56/xmoc+CU8kKkg3fA5cUFAMLHHz3Hvu/x+c/ucIqjRMRQr+aiWGflmyh7eNeICGXxE+IAUtc620VPzjIX1hMSGCFEJE6YxoCYIsZBjJVxDIgx4XQ6YwoSsWPKTh5sDZnczPLlNFMCCI087bl5ZI9ytb4U23exiQ6BtmzzgrYKn+WvvmlrCSraRznWeIjqMrZ2tCqG6/odN1rjIoWI8jVjtQSMIZGRhltrXAwWiiWVCxe6LqHkJW3Oz5XzBzT+VjHmZdkSjSJ7PK84XKzpncX/iFbKNbzMjIl5FBdeUbiazs6Uuzwudd6+RWtsxqwV0FsVMtPJ4sWOdq6wjiPPr54ro1rl/5+9P2u2LUnSw7DPY621hzPcKW8ONXZVD2hMTaKbaLAxCUQbKeqJNOpJMv0V/hcZH/TAFxpkBjOKEAaTRCNMjUYL6K5mAVVdXUNWZeV0hzPtYa2IcD1EeIRHrLXPPVmZUjWqwjPv2XuvFYOHx+TxhYdHbDFpwaKV3/tItUFVrsLmI/ab8GFABiB2yhuGkgKHsZuIgoeiyLMWeSnN2CaYwFiwYhGjMCBYQc8aqHb7mXk5ZXhxmuTUCSVtvegr6kfZN0lV3Alpax17MchCG4ttA0TZGO4LoI46vHfxHlbdCh/efoi93QMAvAe+/W3g0SPgN34DeO+9Lya/Ro0aNWrUqFGjRo0aNWrU6POSMR0604EMoet7XLz7HKbvcPjBj2BvbcAivMfVhx9jvd3g0dvPsbm8hHcObrSwEc/1nuDZJLyCDNAhHMoyZoAxBn0/wHQ9+s0GQ99ju92g73oMQ/DsYQzBs8c4TfDORmza4nCMV46ME2y8liV4mqa8IVfjiPrqY31CP2IrzjlYSzgejyAi3N3dYVitcLHdBCwkHZYJh9WGfgBAuLgIRim31yOsj9d3s8JLBD+Lm5yUk4FgyBlfLL0jK/bjFScKkI31wAiGHXIli3jwYPaYpmAY45wPV+pwTiNjJwon0cBokk/GjArsUj4KmEXxR0rOmip4S2eRGKthz/sAN41Pxt8lTFX7c1AY8iKcpcq5BL0CAT/THmoJco6xKpPOZBl7TDJbwKLIUCmveTHKNJfwrFN4s/DKBUpX8KWf1FVf96H0mfjkiu+KuQJDjoGKNlnTPZhx/U43O9bvF9r6KVqsK3lxDyu6DaPEjLXRzPKegM6mbNMhHM/jpPFBe/6ZY8jyODonCtwkkPxUWQL/XFaWLmnR9YsvJ9viEi678DgVgeNwtNB+i/HlFIa8zLvkcT+GvFyGbBf1BQHIjRo1+qWnBxt6vPXWuziOE15e7cAd4dNPP8bxeACzRxctsa3ncNciM7wxMORw9+oW49Hj7vo1djdXMGYD6jagocfKGAxDh/VqjfOLSzx75108unyEr3zpyxhWA9ZnWxgQegTPAZ0BGB6jHTFOR/zog5/g6uoK7//Z97G7u4MFwTPBRyvtYLxgYLqwKLBugrUefScLjmjSEY1T9EYhE0Ul3WJ3t8MHP5nw6uU1bnYWb7/1Fh7/3u/grOvBzgbuugEgg0fnF7g8O8Pf/psb3O32+Of/7Brv7w/w3gLs4vUpHobCAsUQwsIjbrTGWaacjNOmf6kwBR49vAt3UbIPhhzXt3uMk8X19S2myeJ4GOFsuOsxyCW43ws24tnYpDxxn9RW6HvgWBYV5XH2uPAIvBOC14m8KOIwqQLoOhP1wnJyZZZJzsfiB0OXUussxKGezxUsYoIxnd7SVkqrfDHQlIxOKW4al3diQK7ByFfZCI8caye0I6KwYAsLV44W+5TSBgBnJE5WIwpWvdJstSW6UqZE+c3GBEkNgah+MyLEa4IkOqXk63sHKfksqNhLi0IuvI2kuCTeIDhZji+sA8o0U3nje1N7eBEjqbmCWRgJJIVvkfXcHj8DsRhSiPCZ4z2nYgk+X3MBugtzbn5FuKwJLjpjpOr3PYsu6X5GukLsY9QFz0vEDJL+rayy5dRCR8HFKTyDje412Tgue8zJeVYcpiGBE1O50NJ/aBYrFi+OLUlmioti8VDEDlelpLYrLCZjjmVtm4hm+bEey/QrbeCl+poY98j4KWNE3/dfmKK+6Tf4/W/+Pp5tn+Ef/bt/hB9e/RAAME3Af/ffAf/9fw/8t/8t8F//119Ido0aNWrUqFGjRo0aNWrUqNHnprOzC9jDhNV6jc3lOX717/xNrC8vcPd//b/heLcDA3DO4Xt/8K/xo3/zJ/it/+If4it/7S9j3I843Oxx2B2wPxxB1Id/XfDU2xmDru+wWq2xPT/HerXG5eVl8NzRB/TYUMAEA1zHcOzAzuHq5hrH4xFXL19hGqeEiQZPDoJ1mXS4Srx7CGZLEQMT/KBGLUIa4cDgjb/FYX/EOHmcnZ1h89UvYTDlYUEQYb1aYTUM+NqX3sFoJ3z/z4+4tjbwRB5yWFBgQMHfMg4RXyg6iUYQAB+uVA/piscOC+c9jodjuoLFO05Ip4A8CUNMmXDAZxOsIzhpiU6e3HyNYcI1OJU040/BybVzgSBnSSI/TMYuWgiCNRVCmGOwchAwwUiLRgL3Ec0wZOEp42oa6w9tKdRzwJI41gtxrtsUuhZlDbTK9UaeirLX0NTP4jigxC5z+gk74zpcGVsDomK4kllUtUi51aT61p9AmbeIlBHA0MqrdYHBChUYepnmonCSkZV+/yYhqg4bf+vaXOSrSDXjtcU+xyyEjlzzdILHqh0ViCmFvTcmBLfQySCkxJDBGd8FI3rhUekkTFWlPod4i9/pdYUhz8Lq+EsYsvTd2jgjhicSD9byGyiMwk5S3RBz+5ttM5wQfYL002AecXxjFuqvUaNGjT47PdjQ4/rmBtM4Yb/f43g4wLrgLUImduccGIwhWop68mGcOh7gCZgmB89dsOoeeqy2m6Dsrre4PH+Es/NLPH3yFOfn59hut+j6DkPfAd7DjROstbi928E5h+N0xPF4wOtXV7i9vcHheAxXkMQNZr0frKdB2YAnPXGAiqHaAwBFLyMEyHYzO49pmnB3e4PNqsPV1Qs4e47z7SW6rg8TJAUllCnct+iZcfn0ER7vn+L66jWOB6cGf55NfkvzlygI4lbMx43ZcA9isBY/HA/BrZ4P9yLe7Y7BwOMY5GYnF8JHQ49knJHypLTVnOw1oBR4zBW2MMVVs6Cy4A7zVu15I+dXVY4qq8y+pep3ikj4FAWWsxtDHXNpi7hO5WSQmb4UZnJSxRDlIAWdtb8T3Jd6aP6udIhUW0rZL0JnnTkrk4WI6wog5GrJNcIqbLZKp1khkrHrUv2p+q/XUsXdeIXSqx/Wbar4mKUzW6+pZPiesJXOHZ6lBcMJfnR4Kt/laqnV91kNLCy2NMO64nQNoRCXVp4R2392PagCSj8yBoa7YNAmHjBSfDEAC63C6IWo6K6k61WVnXIJ69MOheL8Bira09KCuugUWcpav19aKOh6ISXPup0F+ZLysCIvqMi3VO51XefgxtBCP/1s1FGHt8/fxpPNE1yuL7Hu1zBkQCA8P3uO7bCN4Rgf/OAl/tW/uktxP/np58q6UaNGjRo1atSoUaNGjRo1+lx0HI9wzuHs+VNg1WN1foZuNQTvAoZw/uwp+s0a4+trHHd7vP7oY6wuznD3+grOTvDOg5mC0UVn0PU9hmFA3/dYD2sMqzU2my1Ww4ChD+l2Xbhelq2HY49xPwWP097BOhsNL46wNl5BAkBAt6U9voD1lf5XNSaisQhDJhphRBjBB7x2HEf0ncHhsINfrbDqVwCZhCgIFtH1HQYw1ts11naD4+EAZ31mbAGaehNxBGXSNSvxau50QDP+G6fgBdo6H4xbXDwQKaCO3tCsrrFIvNE9GDJV6BpVEUlwxnlFFDj5DMblAgekDKCWCdwrJPWhsKC6bLPPmujE8zqMCibXb+v35HF/OjPcsnxeiEDjccJ7jbGeSH+JKoRyHqcQ4gIY+1kw5EWeqMxeR+Ly9zKsW1ViVWeLGLIqG9VMzhrLUtFOlUrxkJrxCQwZS7jqqYa4/CbtGaj00pUhs34VMWDSuLH2TC4H7sL37Bt6LpwZhqzKUpbxBIZMmkcls5xFmVLRHuoGoXhaaEczDFn2zuhEHZ4cD061Zlr+SnSqKhs1atToM9GDDT3+9NvfgrMOLz55HSyfKVzOwtFV/36/g7UOvNli3ffBYhoegz2gP/RgbwCco9tssX20xdOnz/Hu2+/h6eVjfPmtd7Bar7E9v4yeLcIQb6cRdjri9vULvL66xR/9yfew2x9x3B/AzsG7A9g7OOcA6mEoKOqew4aYIQuieKEJA33fYeh7uGikQjAAmaCQdwiGEt6jMz1W6w7kGeRsslS004QXn3yE4/41/tdvH/D0yVP85d/4W9huLzAMcpo+TGGrfgVDHX71r/0GHn3tOb79h/8Wn36wC8IMvvLAcGGRQwQflW5jgvcHfa8hIXiQ8I5hncc+GnDs73aYxgnX17ew1uFofbDMjpu5zvs0mTEAr9YI0Ju8MNlSEoBYE0M2f0kmu3Jjk2JRyvkr/DDxPkFXed+IxsopAUNZ/S82lONER5FX7THBiNu5aJWSXd1FiSUrn0pjMzJzd7kMaUIVBSYqJyT/slyS0oHomSTyQNE9C1VWLaRYkAVSsegp5vJKCQj3bSy+AnIdB7sdWS1QWnMR5dMLwQNKTsSzT/0WCCcihN9CbLX+K2UpZKKWcoXmSIXBzTwDAzkfEIobXTFU7tCkD8g1Ibm+hGfl6WNJwdK/o7IqHlukbZfrkPJezSUFjQylRbIu77L1emBKjJBmYqjizKztC4s1Kp8pRdXHuN7ndkthhAtroa4HTAdrJzi2szblncfkJ5gunI4Rw7GUBQOk71eUBrFklFEtdqRK84im9e28sAmNV3V03UFY+kyp0ctSQxvvoTpZkxJJgxXnvCuLwGBJnYMJcTJ00Y2T59+Z0PXBNeznofPVOf7LX/sv8e7Fu1h3axzdEQAwdAP+/q/8ffza018DAHh2+J//8T/B//n/8q0U9++8B/zNdz5X9o0aNWrUqFGjRo0aNWrUqNHPTB9/8jG8c/jq3/wbcNai2wywxxHMjK7v8Y3f/W08+eqX8J1//j/j0z/7Pv79v/wDfPdf/evoXcOHa6axgul7DOsBm80ZLs4vsFmtcXl2jq7rMaxWCYlhYnjn4L3FeNjjcBjx049eYrIuGDZ4D2abvRzDRIwjblVyRE4pYxemM8HPrRyYEU+eQPQSyvBgEBl0QzAyIeXiwnuP/e4Wzh7wyScW2+0Gz599Bf2wQqcOcRMQvE73hKdvP8P60Rk++eBD7G6mLFDBG9VBQfYcMS6kZ8GbshzkY3jPmKIBxzRO8M7heByDYYfPnphrb7kFJKLwrLQ3PMOQ47vCQ2qFdwEVVpO4znVRBSh+U4XJUM5CMNaCV4lTZ6xPeZEuN1VhMracICe9KVswp3DoBagoXZ+Sso+Yb8lqhq9iZNIvNIZcX2dT4N+YkT7IhcXiZmCUi0CZF3lyEu6i8ofmXV+rUwTTso9ta54eyeuS34V8eeFbZqQGXN9QhoRDIreTpbLXzwpsOlea7DnEAiwmlTDkBQYXsz6FIauXXHciIDu9kEZB+XL78NyAuuDRnIvNJMR2FMZbMhTw/ISR62IrQVQ4sSrqGzHk1GZm7bYeLGhWf3mQLcDlUm4Fhlw3wKqfLewPLL1KV5nX/Kg8hS8yNKvHRo0aNfpZ6MGGHofDIdw1OI3hnkTIHX4MZl/oO4w42FGHfhiCq77VGTarLbYXG2wvN3jy6CkeP36Cy7OLcH/isELfhY3I2/0uWFsfDpjGI3bXL3F9s8Pt7Q32+xHj4Qj2PhhyqEFXj/kcFcAwZ6ghW00is7mXwgTVdR2GfgV4lzaDDYWNae8d7BSMK7puBWttnPgYbHL+hsIG+sXZGSw7bDdbDMMKbrJgbf0QJ0hWE5pjB8/xnkQO1ufee7gpWFjvxwl2cjgqzx3Oe0w2WGNHq4JkLCIKdtTfE48FLSk4Sp6kpagMKrRRRe2xQewkVERZgqkKyBOx8FQYecw4YSTTS1lkpQ3n+hKTEG5Bzyk1aC0GUXZYSo0iDblTbjl6VoxLeepMOfOs+NEKY5YQQTbYS72s1EqEx3TFDinxaKVSxQgy8ymg1q1K69nM1Fx0sT6Z8nMVLz1VCxDpl7XwSjWWC6WdWRlR6HQx15syz/PrVbJsKLdNSSrKea7USVsoeSRi5UqwPrWQW1/NFykedDtQ2RX5B4MBTguCJbuKlJ90Cw5xmbIRjrQFGePY120092ftgjRKsmZLeXV5s+KLlAYrXuKXSlEv8ktt7rTGuyiPygAlefJQ3aMaiWI0GXcodr15PQonuuyhfeXE5Q7gz0OGDLbDFmfDWfjtDd46ewuePR6vH+N8dQ4AcN5hy8+xHr+UytD7y8+Vd6NGjRo1atQozO23nzzFix98Kf0+3Jz/nLlq1KhRo0aN/sMga4NRRbcaQH3AUxmM7ZNHsHbC5vEl1udnuHzrGaa7XcLa+qFHN/R4/NYzXJxfoF/1GNY9NusN1usN1sMKQ9/DdB0MGXjvMNrgucNaC+ccpuMex3HCOI2YJgcXPVgQRSz21AYvkzL+KB4rjEEDmBTxXwNjuoCxOSR8GUA8tOdwHEcYk72sZoyKwzUzCDjyahjgwRj6AV3XwTufdz5jFH3gTg4+iaFGuJ6Xk5GHZ8YUr2JxU5CPtS6+Vxu9Gm9KoF9+9pkw5BowlfSxjK9UVVBhyOptguw0oJcxnDlAuIRX1bnOd55r+HX5h8TQQpvjTMWv1I5qjLgmmpXl5EbwLAlSGHKVlwB5qu2mNJDD04IcEp45A8Szt+uEYy/wWCC4SxhyygOAPmSW2kCBxpVlKpOY4ec5PmceC6ONReQzv6p/xHqch488UxF6oYa1kce8DGV6XPLwBouAtC8Qc17GkOPb1I3CoDLDkAU/LXDfVJnSrUH1Ybv7eNRCSfX8M2DI96V96vepyPcdYuTQExZruy5n0Q+gRZVEl5JlXb5m6NGoUaMvhh5s6HHc74OxAY9w3uIwTnDO4ziN8Mx4tD3DarXB0HcwhtBvztANPZ4+fxuXT57g13/lG/jmV76KfujRDwOMCa7pOiIMZOCZ4dwBL16/wrf//Hu4ubrFT9//CM5OwLgHM8M6RGvkCWCgN3J/WJxMo4GDMYzg06MLv5EVY5ZNZOqgFRcCYPoO685g6DY4W53D2QkH3IAgXjY8iAE7evzwB1e4uTL4y7++wzCsgqW36dAZA4JB3xuYrsNXnjzH87NH+OitH2O6s7h+/QKH/R1kxGfv4Z0PFpBkghGNC5bWx+OE4zjhdrfHNDkc9kc472Ft9NgRFX7vfS6FWjCoqT3MycqLRy41YhxOixExniEApsvqmIRjAEbykXk5Wfkk23eAgM6oRQcAMsG4gIVl2YyvZrU0GUZjF6LgdSR4GnAgY2BMn+IxAOtLtbK2Qq40ivQryE9NsOiKhRnickQWTkQEGFFATQpSbAxzdgNJBJgupAlt4SrE4c7PIHQTH0XhsvLKojQD6iRcLhtRdFOJJNxQLZ0pvWsonjV12msGRPHIYpPeQtrEmlS74lxerauVi9jEbcwrStfLc1+8z23WFGkZ8QAiUp8tujm1raA/BoO09N5EbxcAyPs4NujLPShpk8SiTJbty5AprM2NUvzE00lZPzG2VlJnlMthjMFq1YOZsT+Eky+hqxVLAqTii8xjPwxebFKLAYiT3Dx5eLjUh6XtOu/hJzkVkt2JihwT20QwMOpUAEPXeZCPGjsUt+kuRyhDsUo+M0P5pDDnOsheaWJ7Uc01yajubpWBDUUe8u+yTuYLdAZSy9FlkuZmMAxD8PjzBdKqW+EffuMfwrHDtt+m54YM/tOv/Kf47fd+O/JBWHfrLzTvRo0aNWrU6JeRvO3wv/5Pfwff+Re/CyDoxdN+83PmqlGjRo0aNfoPg1w09GB2YPbB2ACEX/m9/wTOOVxeXmJYDfiNv/u74N/7HZi+BxmD7dkZVpsN3n33XTx//jwcpOgCHmgiBixekD1b7A57fPrqFY7HEbdXtwHfc8EThveI4QKuZipMRjDkAGcKThAw0XKTliKOljEOAsJ1MWTQmR5DtwoHAzEmiFSAOO8YV68PGDeE588mmK5LmEu4OjeWzTAuN2c4G9a4PbuAmzyOhx3sFD17CObqOWEb4m3EOw9rHazzGKcp/Rbv0EAw/AA0zhbLuLT/yfq5xtu4wJCCODntbsuhl4QhFwmq9BVmw1IvyJ6ys9wXmDzlDYEE+w4Yci6Hj7izURhyPCgJVHV9306ysMLILUNhUeVJx8LYIvFLGSsqMWRdvpjWbGM7tjyOG/Liwlfamtqw1gcYc7b1Ac0S68wsmgqTo1T1RbjkUjr+ri0cHoIhJ+MOKKfWua3M99JpiWVoBrWhUT6bmvt2Wet1fGmXDG1woiDidKhw3lIo/+X6ae6z5fPwjVPd1knS8nchzSKFA8cMBGMu8Cw3qrNhSZeLtCQ/ooCdS/h6TGAGnI/tseqXrJsHlZku1cH8Cmyq3lWXw2jM+Y3dVo19VGO/vJB3ygSz0Hw6/BxDBuZtLfdPonDl2Oe9/rtRo0aNgM9g6BFc4IVNdwaHTU5D6LoOhhl936MfVthsNuiHHmfn51ht1nj67BkuHj3B08dP8Pjx47BBTwTP4cqVo7W4HR2ct7DThJevX+Hq9RVub25xc3MDthbkg1JrqIvzTlYKtEIYnsnklC+VKOwblAWrIQMyHYahw2ro0a+C95Gh22C7Ooe1Iw6HIbi4m6bA7+EY7zD0OBxGvHzxAuwdng8rDCvl0iN+GboePDAuLi5w+fgR9nfXOOyilTUDzgVDD4YDE8FOFnaymCaLcQyGHvvDCDtZHA5HeM9wvnKrV5lY8+y3FF4p1nF2194w0oV06XT6fKKRzeYs0hA+yblWDBQvSuVROhhHfXRu7HH/RK1V8VrjnKvps5KcNGsVTWRpklV3ziWFVHljgciDlZF2pfjOFBFOCosyU1X1UG6wz9Q01dayhwEtD8r5l6wsCIWKz7mxbEyf8hpiUU6yaU6ah9NfZ+UQKtcp6T1VESkxowJGl22pdZBaENQlLgwnllqLrDjKNleEXFxkLCiqSfE90f4Ys7d6EV4vGO5JAmKwla42iv1d/ysW3ko7Trq+LsOCaHJboPi54H1G/0QtkwWFVz3OBj/LZSyzUf1MwjHPwtc1QLmgKoNlId8zoqQuaAwlI5cvigyZ5MWjyJII22GL7bBdiNWoUaNGjRo1+tmJMN6dYbz7efPRqFGjRo0a/YdH6brh+B8RwXQGm4szMCNcX9J1WD/awJh4YKLvsT0/w2q9wcWjR9is13GzEdFoxMM5j9GH79457A97HA4HjOOI43FEOCzlIp6krggGSsxzYcm+hC7qX7L53hmDrgsGKF3Xw5guG3rYLh7MC14z2NqI/XK4gnsfDjKenXfouhKDA/LVyqvVCuv1GnY8wvIY8C1G8tYhG6U+Hh503sNZBxs9dgRDj5C3Twd0UOA+2diCZ7B6wpCrDdE5SFdjs7VQF8AcBTHN4t3ngkDCC2A1w5Dr2mPUtbnIZzJQ4OViaNBMYatFegVQmfOVzXZWSJQuYn3xcE0lui2Y7EIrXYSoCJWNhfpNKFp7jd/W5SyqvK4znMDQdcYpYBVUYeECjSe+54j0cjkkqblcSiZD+ORpeeF1ir2EISdWtXDq9iaRqwTn4HYZTcugoAUMeaFbllVQh13aEKgSSsXhsi4rnLSoSiCNp9obyLxs8YtqSzNxnBg+Agv31WtZC3pIO83LLAOFIUu40/MEaXnO8ijlV4xxuslQzEPj840aNWr0OenBhh7hLsXofYKAy8sLdKZLFsH9sEbfD/jyV7+CR4+f4Gtffg/PnjzGZhuU9PPtFmfbDcZpxDgecXt7g+vXr/Hhyzt876dX8Psd3M0rWDfiOO3grIM7TiCEexGZGePkQAQMwwAC4P0EMAdFmAguXl3ivAMAGNPBEMFxcKSQ1Jg44G82G2y353j2/Bneee8dPH/6GF999x2YrocZ1rB2wuGww/XdHX7wkw9xc73Dj3/4MXg6gsdrXF9f4f/xT/8nPH3yBP+7/+p/j2fPn4PiPYsuzbRA33f4lV//Oh6/+wx/eLzF66tXsNME5yYcjw7T6HE4jjiMEw6HI/a7YEziowcN73ww8LChXHkjPdpVclAO2fuoJIaT+IbEAMPnyQrIqspMl873roVJJhSGU5jg2o8I0epc2R87lSbHPDgYpYS6kInTRD2DleJzz4RNFK/NUZuxygLaew6LOAI6Q9EAZp5OOQUHvoOBTbQ4J4qcZYGkC3ZiwwnXXYS7POODKPN8LU62Fg7RxPGEjxbXxdSdFEQgewkQ9Z1yXSoFNiswDMBD3aIXnibrjBzSRYVCrOzzvr3yBKPSyJ/6Hr5s98wsnj/CfaUwyqKa5+pX0mOorAGtR85Dx1DVAnJRcU0LgGphUgXRC6tTSmIp4VPtMrZkimFimX3sZGIpPosz09vuc0IYgIHxGGQdjO9zuXgWXn5X6UWeGFFxNF0wtrMW5D28kT6k113hh/c+eGfqgmck50IDT/cuimVz7HfKBr2ot9RbKUt2SSFm3Rxniz9JS9WgKMRFauVqh2T8mq0gFoiF/8xfuZxYUrxzWyIEA4++M1+4R49GjRo1atSoUaNGjRo1atToPxTyYujA4bDQerUK2F5cm5uuhzEGl48eYb3e4NHlBbabNfphQNf1WA0Dhr6Hc+Fg4HgccTwecLsf8fLmCJ4m8LiHZwfrpmAA4QQLDqt6533ElLsIc4T32VtCNppg5nAFOQhy020NP/V9j74fsD3b4vziHGfbDR6dn4NMOEQYro+ZcJxGvL6+xXiccH11F2Thjjgej/jBn/8ZtpsNfv03/wr6szMkQ5aI1wEBb33y7DE251t84EYcDvuAC7ODsxyNRhysd/GgYDi9LwYaHA8HFt6fpdwKlYFXnoiL/UkN7KnjZjNjBigcJf+Rg2+Ck+a4XNhUpLQUOKjhJkFlZgfp3kABQ45pKzwVENwpePU1tOCVoU4+YmQJMk9yqswA9CGqJIwaIA2bEyLR2l6GUMB+J270eBOGrBCywsNCxCsr3Dcfns38ejqBIWvjBY1npyRZQWQ1Ao+E39VgH8++SLInMGQdntSnyFsBrHNcscYGdYB52ypsWuaA/gylT+nqqogyqcMmg6rCmAKlbGe8n5Ad1P5Iyjq3f1aHIXUZiu4p6cUOJ4c7iQjwPuKrET9W5UrGHqGQyVgtDD+572Q5Uip2GveUkZXusiWGXHJfHzZePIeq5UR5X4LqgsdQBNUndORZ2mU8PcZmbF0LVZefY/kp4cj0Oa//btSoUSPgMxh6GArbyn0XFKbNao2+79H1Awx1GNZrdP2AJ0+e4vGTJ3jy+AmePH6MYRUMQPrOwDmHw2GP29tb3Fxf4+rVa7x+fYdXr67g9jv4m9dgtmBMccBmMBGY4wa+UnyF9LwChHHTq0memVKYruvQGULfd+h7g/PzRzg/v8SzZ0/x7OkzPH36GE+fPg1Ket/DWov1poc3wLDu0Q0mLQCC+zuL69s7dKaDtRM8e3QwADzYh3y9n+C8g/cOjOA673i0mKYRzgZDj7Ew9BhxOI5ZNxLLa5brVUgpGvGd/oxS0Z4fZsYPeuKMk2VtTXlK0crRZMZlFbBSTnLyZdSFbzPiWYppQSgb6WkTW9zWFYrJAosom08+7Z/VLWKOyivl/Gas5nznha0eLRWGlVhIlNVSAUgpq3ZdKGW6sqSt6wBStqJdaDUu55Jscuu6FreHdaFkAaPkl/ub8FLLANEYQAyEFhQ0KB2LK681cVGobOCzpia8FRbEPOc7fc9CPnELY8lTlco9MU48W1opqrFMZVB0UxLFGMr7RtWR72FDX6ciHjdCVRHk9EPQ2ysvHElRFx6FsaXyLTVqLGvYiSt1RybxQrKUG7wukDyq6mWJZOHNtVAXSsGqimbDlap0PewuMhAXDV1vknFMo0aNGjVq1KhRo0aNGjVq9MtGsuY3Eb/ro2GHMSYcGuo6GNNhs9lgvdlgs95gs1kHr9Hx0J7nYDgxTiOOhyOOhwMO+xGH/RHejuDxgHBtcr6+OGB5mQ/WDPHCuh4K+4kYdIpC8XoVE65WWa3WGIY1tttt+LfZYLvdBGzFmGjoEa747XoDmgSPjv95j+M4wZCJHrM5HIKL2HX49PCcvWl772Fd8F7i2cGKoYezsFaua3EJP8/eSyocUmPIMwhQ4zT1uyzX8HUB5FUh0uY1V+AN1XFPYcgKK0v1kL7N8k3paGAnc1PGS3glR1xd44v0Zgz5FPYrGHIqAs82kAEN4yqcU8uLqvcz5D7zQVWDXkLr7qdy3yC3Gwh4i1SqGqBO8pbnJe+lH3CUYSklHF+d5jwEIyyiu1x/Cj4tMgl4Iy0ZOKQ6U2yT8FLxLo266DNv2JRfgoHr5qAbms52MWkuPsp2QsVXXUXLOG7NSCWcuknUWCkVgijTYpVAkfdsIIISwjJrOmXpTtogpI6T3ut8MavO0xR51MZKqe5TYwWIZnKZJYOFuDWp+BTnl0aNGjX6vPRgQ4+L8w2YgQsObvUuHj3Dar3Fe1/5Os7PL/H08SNs1iusNxv0w4BV36MzXbhfjyfc3O5wPO7xwx/8GD/4/vvYH/bY7XYYJ4v9cQpK6zjCsYN1I4zpsF5tACaMNvAg46N14QFHC1a20cOAMfGYfTCzTafbycMQ4/GTJ7i4uMTXvvYlfOm957g8f4RH54/R9T26fhUMV4YeYAe2I+A9DAjejbjdfYy73Q3s4SOMo8VxdIBndNjggA3244jDYQdaB/k47+C8w8urT7Hb3+F7f/ZDfPrpK3z33/8ZfvKTjzAeJ0yTi272GI7DfYlBsQieOuRkedBRCH0vxiOi1FGhdHSmA1isthnxGsqk35u4uZvPmpOaqOUuRclfvrMKTeg7IM9IpK6FkAkq8MDsAIT7KoHAU6gRv+jxQFt5x+WNeqFnWYIx8RRA9FQSysggl8ub+ClKgKx7yKY5c3RcQRDzbDJKCWcObapejyzkEByDGDA4eXdgxyAy6Ppy0zp5x4jm6uJKUZRNjtY5HA0e5nO+pKDrCtF7S1Z8xL0lSO6jRHKBF9oJAdSlOgptycSqKFVYra8QIZysAIO6DsYQnAsLTkAMh1TLEEMNUZClCSmDlBQMQHDKw4mHtABjWYiV0pQkPXxuKaLkRnc+wfNErZD6fFMRclsCkLyj5HVHsrqIbViDCTk/fV9nSjX20/I+SM56pOjKYlxkgoFboRMSkgel2i4f6heBIF5XwIhGHqGuSSyFyYD7HrAOgF92m4fgSchOUaJGvMvUCnqMkupmtvqI7+uTHqWIUmGlDSQ+KNVneM91A0inPmSBLR5QT60ZU3SVTl5vatlKPwyNUy9PygKET9N3uHx8jtXqwVNro0aNGjVq1KhRo0aNGjVq9AtFq1UPZmCFHkSE1XqLrutxcRkOBG43a/Rdh67vwxUoxsCID0/2OEYvyK9fX+P1q2tYO4Urtb3HZKMhRPQa4tmFQxddWIenAzORl9qzheB10V1xAgYSvkkBY1pvNlitVnj8+BIXF2dYD2usV+vgJdV0wWjFmBDfOQg2xewwTneYphHe3sG5cOVMgIB6WO4xOQdrJ/Rdn7Aqzx77ww6TnfDq5Wvsdge8+PQlrq9v87XfESP0nA9aCTYcEfCIrxFMx5W9h9oIpYgRKwwrYTopScqfEZvRV2ZkdE5joxlkIYhXAKSQmc+YivAQ0zExAPvo/YM5hSk2oYHCWGOO1KhSp81pLqEkbdxQInVlMsXvfLAt+oKJ8lFpC06/mE7mkyJvGcfmdECuvg64Nojw4oE5A5mZJwaoFsdCUaS+irRTuTJveZ9bwhn1u2hduX3pLARSlwOsEVtk1hinjpUbCbEvq5arwAX2Vxx5zc9rGFhkhIzqAoLpRhCYBEsV0BGKD0bxrcKQ1YvMohgpyEuqwhWNB0VYlUooo5JBrisdJsum9pyc8qzC5z0Y6dlZwGEfIWDCAXydmfLkVDh4T09MST4L/HFhmDFvsHOMWpWl/g0tcun38n6OIafocbATTx8zQ5lkDBYf6nROYciaj7oMlRyoM1hvhuYVulGjRl8IPXg3ahjWIAKGrk/K+Xq7xdOnT3Fx8QjPoqEHdV1QUl241uJ4HOGcxW5/i/3+Dq9fvcLLly9xHEccDgd4z8HbhffB8wV7eO+hzRFkbzhoQbKJrgdimdgMwlUfYeO67/twd2JPMAZ49PgRHl0+xrNnT/H8+XNcnl3i4uwCDAJz3qCfpgnHww7WOUyTxe3tHfa7HY6HPZw7pqtUwgRsYD1jv9/h7m6DabQgMrBugvMWr169xm5/i9evr3D1+gp3uwMOxwnHw4RpskHREYMMVCqfVgwKJWCZtFeLEDSkmPXJxRvTZqmIsI1KLmw6lxyGdE3Bs4mLHO9lYo1GKyzzZ6HSl/zGeha9JnjqUGWumK8VXdZh529OPglGlsqrgVhdJgU+T931RRHCGClNmnh2k1+Rcb4CpVTEWRcgGXmwWjBofxXChuYxxknuF1Eq/GLAAqVgK2mwLH6jYYgUqbCeZoCMZBfeGPah/6Q0VX80HZJhBDPCXakczTE4lx2V7lW3fWVZXazFkhyQDAm0wlWsL0T5LpT/U2HK53UbqtueFK82mFhWfvV7KVdppV4qjacoq/ulQlvzirKrxX5IMCAq63rGbTRAC/p5XHRGgzEsBJ+Xr+Y2p7t0h+g8Vk1VmeuEY0MqfLu8gccy3wcHTktZHcMYwvZsjfV6eHA6jRo1avSz0NEecXTH2XxUU296bIctDDXwoFGjRo0aNfpZaHQjDvYwm3OHbsC23yZcqlGjRpmM6aMdRfDisVqt0Q0DNtsNVqsNtptVMnIQd6bM4Qpb9h7TNGKyIw77Pfb7HZzzsNYm3EkONQUMLIKJS441KSMt2jQh/BYclSLPJuCgpgMRsF6vsF4Hrx1nZ1us+zVWq1VAlDhfZ+29S16evWOM44hpmmDtBPY2XaUimI0Hw04TxqmDc+EwnPfhapbD4YBpGnE4HHE4HDBOFtb5cL153EDVmFiJIcdMNPa7BHMkeC0CRQU2qMAjUmEFLyoyLcNTEQEZJKM6nKoefVo+PEj1VgRe2ihGTjr85vK6kxrD5irNe5dRddyl9+qdliPXZT0xR6SiEgojgFk5uUifJY+KsdLLd8hAHyCt+Q7RNeZcFihChwq3zrhs+PDqN+X6qHLLWC9HnkI8wX3tcYQdR/SrFYbNNjaVnI+bLMb9HtQZrDYbVapCSDmHCjDUOPE8Sm7TM9ucVJ+s4lZA7QxDVokV3YG1WHK3vBeGnHd03d+zB+Pcv2bFJPVeeCr4mrdNKVHpeVyMttTeCS0xz2nv5/R+Di88O/kop3vynRozWBeOixBlG1cPaZHJWf6V4Bbe3RdvedghAvqhR983rKZRo0afnx5s6PH4rS9hNQz4+le/hrPtFo+ePMGwWmG12oQrUXqTFHQGsDve4Xjc48/+7Pv48U9+CjeNcJPFfrfDbreH8wwbFXkxCnHOgchgNWxBxiTrvj4ez04Wrh4gYphoZQ0TlF2xph7WF+iHNd55+zEuL7f4yntfwtPHT4JLwOh1ZLVeoaOgYHvn4fyEcTrgcLzDjz98iX/z796HO+zh7q6xHw94cfUKzlq44wQwo49eNyZrcXd3g2/98R9js9ngk+sOx8njcHgN50YQHJgYzjK8YxydAXdreHLh3kc1b8fSpQeixwWDSbEMF4vs7PHDGBMXF/G5AhoYYoohqwpShjN5otI6dWc6dH245qYTDx4MBA8qYZefvbrbEkh39YnFq7VdzDE+Fyt34Sse1zddaDPBmUQUCEcPIOyDRX0yAQ95ZWt8oTxdEoW1HUOd8q8XDDGK3L+ZJt14j1xeHJkotqz4hTUgVTKu1A1C5lm0zHTR5JJSDQTzYAb7WjOLUmQ5WYCoMIl0Z5roTM8iKo2mwtowl11U/mStfUJBkSIkg4ZUH/EO01gtputg+h6bs3OcPXoMMh26rgPcCJruME4jbm5vQ78bs/wkb06KllbF5gs6FLzGMvDMjKPQpsq85inLFSek0mQJNXO9KLIzKaFZ1RXpV0u8igHt6WbB6Q0AQmc6iMvPHBDK2QinyMltJ2c5yYkDidr1HbrOBNBksiFebQCUDI588E4zzNET7eEkL9TL0ieTMA5tPSjgC21tQXvnyEdqybray24dxOHrREJbqtcxVI0JapjM77nsEdL+5wyGK81+/ZvfxPnFdl6IRo0aNfoC6duffht/8JM/eGO4L19+Gf/5r/7n2PSb/z9w1ahRo0aNGv3i0XdefAf/8v1/OVt7f/3x1/H73/x9rLrVz4mzRo3+4tLm7AKd6fD40SMMw4D1ZgPTdehMD2OCp1GNgUxugrUWL1++wvXNLdgFD8h2Cp48PIsn3HwgKhxKiZ48xH0tZY+4AdpTiEwF1gQegK5bwXQ9zs/WWK8GXF5eYLvehMODXYd+CJ8JifMenhnOW1g74fp2jw8/vQJbCz8dYZ3F7rAP4VzwnCt4iPMe43jExx99hL7vcXekgI/bA7x3YfuW4oFAz3BMAHWQ41J67zd8ZgxQUI+MGed94ADPZOwPlHFZ5d40vK+uZykPX2YRcsQmicJVO2So8EacfO8GoUktoNgBjriV99VF09UpqgTrmpBG2h8QXgRPpoRwKkHNwLnIRxGyPPxXh097vIINKpA4xYkYMnH2AFHgfcLSAuglAmYlMymAAhEThkxi9KN5UWVNoKnGIWuDjoqHVCWK19S8chsheZHazTKGzJotQuqLzBT/BVzwo+/+OX74//ljfO0/+uv4zb//d0AmeI2Gd4Af8ekP38cf/5N/gfO3nuE3//7fRb9eJXaJxVM5l2KoaQbEzjpSxauOW8UhHaGUb/irOxPKuOphyqbOrw5XlymGz4d9aV5uqSvBh5cOhxTY+1ImuTTpqTHo4r5P8NyhrsoSD+VAGqeTV+kaxCUkD9+zfqnbWUwrPVySE6u46rOwz5HH9RaD7r4Lezv5q5J1nZ427NJ4eAx/EkNGOJTz1pOnGJpX6EaNGn0B9OCR5OzsAqvVCk+fPsP5+QUuH12iH4Z0st8jKOHOTfDeY3d3i/1hhxcvX+Ljjz+Gtw4s9wp6Cy/KZ239SIAxXbnhKrt79Sl6EMhEAw8iDKsBpuuxOb/AsNrg8ZMnePz4DG+//TbeevoWVkOPvu8gG6HB6jp47RjHCcdxh/3+Ci9fv8ZPP34Bd9jB376GtRZ3xyPAHgYeBKCjcG2IcxbjCLx88RJ9v8KHVx0Ok8d+9xLejRhWBl1nsBo2IDLwTMHdVT2r1EoGskK1sHWdZaB0B18/hMzZc21HqcuVWCkpA4VBA1Fc1BiI1S4ByYhADD0MAZ6DBxVmjuYLSEYEBWNRgdUTXtZl4wIuMFNO8LWCsqSEiTLKYhATFxlJIZJ4uh5KRWzJQ0N2PaaCR81MVA8k6czTSpO9ViYlZuxLi/pdkT9pbTtT/btqWqWWjeK7KJd1q0zvdbssolOSs8Q30f1mNwzoV6tgHND1gGEQOnjuMPQdLABPrki/sAwWK/KZQErNjFK8EF7r0bqd13p1lkYpl5M6/SJREaiQqGYz6aP3JracF5Uc3uMvJmWdkQ3MFjtZyRSFO1ypk9wSFrJXrZoBGFk8zRcpOVDNzP1lPkW5355KvdD81QGIhfZR8UlxENDzzikuCq82Swq6qmhjDM7Pz3B5cX5v2Ro1atToZyFmxuQnTG7Cy/1LfHDzwRvj9KbH7XgLZsa6XzfPHo0aNWrUqNEDaXITRjfi1f4VPrj5YLY5t+k3uBvvMHUTgOC5oM21jRoFGoYVuq7DZrvFalhhtV7BdF1ahDPCRqDncP3KNI6Y7IT9fo+7u7twuMUrzx0hGuTwSonZmLi+52CkUHdBhRGkfXoidJ0BkUG/CoYem80G682A87NzbLfbcJ2MMWrDzkfcW/5NmOwB+8MBt3d7eDuCxyO8d5ici3ikXJkcD+2xh3PAfr+HMR1uDwTrGdO0B3uHrgs4TWf6iNEkhpcFPcPqTgGFCrOi+Lw++FJ8V5hmDT9qzw4JZI2mLBqPTjir8rpaASpyiCzvjyr8aXFzNGI0M/cLmTVaBF9rmgOoCTnWGHqNIc9QUwlAJeSaeC9xK41ZJrSN5GmuE1YczdgtsF5eCFDmFwRWH5hcSHgR61KZqXJwIZgZupzKVaRSYchumuCmCce7HQ43t7DHEabrwtVIZCLuaMDO4Xh7i9V2g+zdpOaeUBganCR97UhVz5qKO7ZR1SHKeFWGRTM5RbGNyrU/RTpKbqfj/wzvHhJnAUPWgeRwYfCipHiXSBpDTk9P9cMTz2aHLMvUltNZziM9kUop7735DKQGgbo9FOON5Kda5j0NgkzYy2xeoRs1avRF0IMNPf76X/01dF2PJ0/fxrBaoe+DKzvnRnh2uL69w+F4xPvf+w5ev/gEL25G3O0nHPYHHMcRHK9nASO4BqCsYFMX72fz0cDDu2gDEKxhnYsDJIXNyL7rg3FHv0LX93j6+BKbzQpf/+qXcHlxjidP38Fmc47NdhUsr02HZNXsGdaF62Tubve4vT3gw59+jB/98AOMdofDeIP9YYS92cN7B2dHeO+xIgeGB3y4tuV2DIr9brcHM+P16x2GYcDT5+9iM6zQna3BPKQFhtyv1xlC3xmYuKAIbgQZ5NXa49TOZppUohzEaCUaBxj4rDxD6d6lFriQdKmJOufh/YhwDQ6psJSshTlazhupx7ixLAYdtdeNZHVcTaSeGXDlZn6oegOIZa7oVXGBB/aAIRjT5SSj9X5a8hHQRR0jOh9JPJYaYZBcLF38DIsRjp5iPIvLOlJ2Hg/QCAp9kYtndZjCRJ7jbw48J08jEkHpJImLWrGMRjrhOpNSwRAVRNqHPPNFYnMlSasuaYkoFtwgDCvCsDYY1pcYNo9hxxE3n7yI3iIcDHkMxmK9GfDu208xjhNevryCtR7Ho8sZsSiHc3nla5qkPMKRj0YKetmkRMNz0UNkECWZjJbeWLeZh6DPVW4DhX2TBXZiKVEyqAqWeM7OQlRwpVBDRdN66mzRqxYOC9YkRATTG7CPVtk0T0Ly9t7G8Vv6jY/PfZInAXF8Kxe/pAQneu8snwXdWA8f2taqksrsWe2aNa2xIxBUDDASUH5SLfclFnM7JQJMZ7Ber7DZrmfcNGrUqNEXQd/6+Fv4tx/+W1wdrx4U/uO7j/GP/t0/wnsX7+H3v/n7OBvO/n/MYaNGjRo1avSLQd/+9Nv41x/8a1wfrxdXGz+9+Sn+h2//D8mw4+3zt9tc26hRpHfefgYig83mHF0fT+gDYATDjuM4wlqHq1cvcNjdYT86jFPwNOq8i9ifBgJCuoI1MBg+nVbP3iIYDFgJL7iliSfLwybydrNG33d4/CgcaNxsztH3A/qhi9e3xMN5ETjzPhh4TOOEcbS4vbnD1dUNnJ9g3YjJOvhxCoYrPpSvQ/DMAQaYPY424KjTNIEBHA4TTNdhe3aO3nSgoQe4y+WUw0SE7AHFUTyrxsXVxwVpbxwkv8N3U2OLzNErR4w6S/AEjpl2ok3CjpxzwaSFKgxGMGSpuwi0ZKgohpfrd3RkniMywfBHUEmNiS2ArQk0jRhe9IZdF0+eGYkiV5EbLAi5RvQUCp8MDRJiqnClBcB/Bg4uIFDL+8PLFAGz0tYwY3Kz66KBVD/JYwGX6Bqpb8UlSAVmuIwhz9KIng+k7X7077+DD7797/D2N7+Jv/N/+j9gdbbFGPdYvA+HNg15XLz9HH/v//jfgLoe3dkaIIK1Wp6nMWTFsvoIGHLcaEBqK9KsIyBIOmKRnhqUSGdyihRuGL/I7kP4ILUnIDEeiCHXwOU92RdUV9epIiy20dBeUv/wIdDJJNJhYeFVvNFkn9vFHoNqT9KHNNI/x5BVK63g3RRd81/Hn3dpPWzGL6YKUKYnB4vL/lLkOssvzGWEvuvQ982jR6NGjT4/PXgk2W7XMCYovWDAOweAMU5HODdht7/Dbr/Hi08/xicffoCXNw63Bx+MGgwVSjpxPJMuCqUM2mmW4KQApGsDEIZJIorXDfToV2sMwwrnF5c4P9vi7bef4/GjSzx79g62mzNQ14EM4XA4YpomTJbhHTCOR0z2iJubHa6vdvjkk5f4yU8+xGT3OE43AMSyPCgX7D2YHeAZ3jk4zxin4A3keBzhPGN/sBiGFR4/tTCrcL8Wc1h8iO0ye7VBLBNY4Sohf+f4e2kPNHm5MCaFJdnkZh22PhMfJ8xaeU6bnznf4AIR0X9JUotD3qk+wiKDiOKdgsoKO1px6jvd3mjIoh4ZBEMFL6pkpY1nBWGmD+Vyopjv05uwEHyTIoZotKIVjvnkrNTchVKUmkJR7JPZVysNyAKmTI6xKDph/NSbFDuv906EPcGgVlqgFp5gxjD02G46mNWAbljBjiOmwxHWWoyHCaYDfM/oe4PV0APMsZ9wZWCuPNgUynbJExWBdOli3c80s4VEZ89xYo0wl0dhlXsiybyclUUpkm1M2Zb4AfW2wIBuJ7M1Yal8JsOe6CmHMlvhuXj38Pe0Tw71QLFs2duFuE9VpZ6vRFJeiV/lyoVTBL3kma/KZC1GhCLETDzpbVVQ9VGGX3BjWYfTYl5YR4rRG5nPWJeNGjVq9EB6fXiNH1798MHhD/aAH1//GJ49dtMOHXVYdasFMLRRo0aNGjVqxMxw7GC9xYvdi3vn3L3d4/3r99Nvxw7Ou5PhGzX6ZaJwODBe8c2IeGi47sR7HzHaCfvdLe5ub7E/eoyWg1FDwkoFY6CIeVKFM1QgWcIIIvZM4ReZ4H3TdD2M6cI15MOAs7MzbNYrbLfB0EOuI7dT4NGBwS4YMThvcRwnHA8T7nZ7XN/cwrsJ1o/IeE/0mMwMjhvJHK8sdy7grNYGQxA7uehFJFxdbgwhHCISLFXhMlLMezBkkcEyhizRI5KztEfMBXKFjEXq/NRj9UjqiqWeUqwyfqjCiI9H0Cij1lzA1UVZagx5AX5NWO9iII23Ke8idSKguQwqEdxHgrOmzeYaQ5akONbFDDOjedjq28nwRRBS78PnafwYKA1qlljRsRcKBSwB89V7FS/KaNrvsX/5AsNf+kt4/o2vw00BQ/bew1kHIqAzwLBa4+nzx3DOYXd3gLUOdjwCIHTDcFqMugExncSQsxxOMq/4X97QqLvqIoasQwiwyQ+r81Mo9pIH98UwM3aoaiZcyoCRMFpakqnuGhK/bkcF8/pCm7LPpyBJvoqRFOm+CuLio5ZWxpBjX1goy0K0e4S+kP8i0F8mr4eU4qV2+t+oUaNGn4MebOjxT//5/wJDPc7WzzD0Kzx7ukLXMT568Ql2hz32hyMma7G/vcV0BKwVjwoe3itd0JhCpQoeHVycU6K1dVSuTbzihBE8R/SrAcNqhbeev4uz7Rl+5etfwdnZFo8vL7EeBpyfbzEMPYZ+AHsP5x08M26vX2G/v8MHP3mJF5/e4vruJW5313CTg7MO+90Bt7d3YLbwfoIod855jOOEcbK4vt3DWodxtGCPYADCHBfyhPV6CyBalSObB3j2YAQZePYYncPBeTgQYDqw9dHTCccbUWSU9+pKv2AAIxOo6QJ/3osRRDQnifcrasvoYnEgCyW9QY9y+mPZSU3xxKWiLAo6AMF7CDh4uwCQDD2CpTxA0cOCq5WWeOqf5FQ/VNsI3CFdH0GANhQhAPBigU0SGN7ldsOqvOJtIVmtL64S5HcphUxGeW4olQcxBjJkACMsUzZOiuXkWdYMdj7piiLsIhxy2RN3alP8oQsNXR45aeSTBLWKlb3OZC8XRXGzRExYrIc+AJgOoA748ntP8I2vPsePfnKF7//wfXgfr2myDuwtGARLBre3e/zohxP6wWC73WDoHY6HHZzOycwzl0VpFhkrfgFdh0FfzAs1vajLn/LMKNkvybbS/uJPL/eZSk7pvklOn0mhrM0IFjfY8vt0ymH2pirnUkO451G9Bgg/w+kW08U+yYF3Zz1AmW9pLd4Fd31dsNWBc6GvG+mzaYwvljH38heec+oHWZGPfIsslryRABBXrd7JGIdiwUqpPcQW5H1dqykfWb+p3CEXV51inxHGtsla3O7vQM0Yu1GjRn/B6MXuBf7xd/4x3j57G//gG/8AF6uLnzdLjRo1atSo0V9I+tbH38KffPQneH14/fNmpVGj/2Dpz7//PogMhm6LznTYboNX6Lv9HSZrMdlo8DGO8DbgKybibsX11UQFvhDwFl/s/8mmOZHGIQimMzBdh7OzCwzDgMePLzEMAzarcK3MauhhOoPOdBFbDGjuOB5gpwk3N3vs7kYcpz3G6QiOHp7tNGEcJzD75E2EEPBtZz2c9ziOU7rmhRkJr/URL+r7IZepwmiknAFTZVifr7WGwhvzniiljVQkbpAP+8RH6QS94JLxM4tNMORlJEoqZYYh6zzleYKepT4yfhcOe8WNW/HyEOPMLhhhjUer8iBH1/xp1DDsoxPAptg/zp6CaSYzgDLfD8Rdk+RTgxRTkgpDRlmWAtmTuoiFSFnLxoBfwqPKg5Fa0il/nse6pyA6oRlmXKNxqU4E+KySKcIRKbkDMMBv/q3/GL/1n/wVTN0G++srpGuaPKd+5ZkwjhOuXjsYQ+iHHrtXV/jTf/r/Qrda4zf+3u9hfXHCi1ZdDtUG5mXPYOniobX0XsmElkp7mjTWnkXGiq8CxZ6Vo0xMP1f9aCnsKQxZ5RsHiCpOTreMEuQQjLYYTD70M88L0ogeeBgwJsG+eQxIPGsE9lTZq8qr5JdRWyr/LoqT0piYBKG8codhVQlZHcSeibg4xJ75XKyK+Jpjmt57jNOEduNfo0aNvgh68HbU++//FIZ6bIcjVv0K02GDvgd+/OEHuN3vME4W3nHYBAZBvK7JxREEUopZVtBlIieouxIRDAY6Y+LA38N0HTbbNVbrDR49eoKLiwt86ctfwuX5GS62Z9FaXAw0HJxzmJyFdR773S12dzf45ONP8cEHr/Dy+hNc3b6CQRzHo9eOwK1Pg76zDtNocTyOuLs7YLIOh4NN+4hhbuO4KAgPZNIC8hZw0MF9UPqZ4Twj5Bbl4ZVFtcyvSXphA16rdCIjsRafTaUz5UxPXqco1lKavHL+oSCysJA9+EphjdfxsFzhIiWoLMzTJrheqpEWmGzUqslYFggshc+GG7lYIkO15EhyoBxQJu2kw5SLjkyU6kcfztflSZb6UYlPjt1S2qJwZOU3bTZ7Vs8KUWoWovLHShZ6GVIaD9TFfYjXkiXNQ6tOui0TgoKe+2kIQJ1BtyKcn63x9NE5fvrTKxzubkEmuJgMhkwOzBQMnuLpjfVmwMXFJi10iBgzlpWuGVXJol3kMi4pb6KAFxpwjluLYEFcrL9Q2VSLl2khpusas9rJo2EBXYSYjNSWUkqFVbxSfNVJjnn7WS6INMXskSPLM3kYIgNjgrJZ3GvKZcG1QVi0UwsGPySemagQUlrDzxhTra04mRJzoarMSgxFuygMeVRbENZJe4lRvaZMsuAqj8V6mVBKuxrdwOxhrcVkp1lJGzVq1OhnpWBY6j/XSeGjO+IHr3+Agz1gcm2MatSoUaNGjTTpufaTu0/wvVff+5nSmPyEyU3oTd+8ZzX6pabrq1sQGfSdQ2c6ONvDGOD69gajndKBETHOWEKvqF6wC6agLBhIhTVisRCvaumHHl3XY73eYLVa4fLyEqthwGoYgucQwYzYw3O4nsUzw04jpnHE3d0ONzd77I87HMd9wjAFCxTEW7b1vAtGHtZajGMwZLF2ZroQvXcglbuEW/IRlYAnC+6rMGQNNlUYMoDknVgJEoJXhyy4BEGWMOR78WOd9EJIDfGkOlKZCDbKAEy+1jfJVidVY5Isf6AgmgUMWb+nSm5JZiVWWOBEJ4t/37guyNECLg2guFbnBBU8Sdl4LpeC35S9AssW2Szzf1h5F5K4h2o+9RVECb/vCKYDnjx9C8+fXOLjT6/x0cfXoX5NTCRe9yHY9jh6dL3BatXDTxNe//RDDJstvLOoqrHMX78rykmqfdxTMHHRosr2IAy5yr/GDsPfosPVXTp+X7iSWrE/+70ki6XuPgs3LwxHLygMVnJU6Gj8Lfh0RruR2+BCZrJvlrssQZf4fprjsvL1JIZchS7GhvykSr5E7HlJrm/ks+KR5ulwNPZwfj5PNGrUqNFnpQcbelg7gWDB/gUOUwf38QqdIdzc7TFGS2xwcEcHBpwPinLfB4MNUUw8B08bolyFzeB4JYvp4j6+wTB02J5tsT07wztf+irONhu8+/wt9MMKw2qDvu9xsd2iNx08O0zWwdkJ1jr86ONXuLnb49VHH2N/ews33YHtEVc3e9ztRthpj54QDT0YjhgWwOE4Ybc/YJrCVRPOx/shncc4Be8ghRVtVDA9AHYO7EIYz3JhC4KrQgLgCYY8jAfgPNhaeDulu8zSRM8MsAuuBTsx6ZNT9rpGsgcITiaR5Zu5PbdE5eKZpGPUJnOZk4rH0T2LKe8nS2pHVMbC5YaRDzWBk9ELuPxC2E8LJ6/KB45XucTglbvBwEp4mRR/REt5zgsPsUo3JPcJxhzSbK81pSBTZsR7PxF/czZ0SLpIvOrGZK8Y+V7KSp4i+y6+l8mcF1S3WI5CGdHqHku5lutNyJCKczIUZyOl2jhHHkW5W8cgl4N96ctv450vP8ftqxv8L3/4PVxf70FG1hiMcPehR7hvNPM5TQ6fvriJzYDRdQQbx4+SUc7VNAPLCs08R5S6TGmxCjeX1Wxdc0pQWlGVz+xCJ38m458k1NxLOJ/AEGDDEEUL6Bid1AkIrspJipmZ7rjEeBaoVipDTxQfcdIBCabvg8cLtghei+YKJyEY7IAIfRynZk5Tah5PXCIrCwSqTJgJuvzIKwFdLgFBfLlAoiqd7CImxJute5T8CsW7ZplytetlAkX+u+h6dbs5nxe0UaNGjT4H/fFHf4zvvPgOPtl98vNmpVGjRo0aNfqFpM87177cv8T/+N3/Ec/PnuPvff3v4XzV1gSNfnnJeweQB/MOlgz4LuC9xykaeSjMDeCIAXJpgIGIn6iDUki4YLjyWXbtus6gH3oMw4Dzy0cYuh7n52cwJlz9bYzBqu8D9hI9T3sfjDuu7g4Yxwn7uzvYcYR3E+AtDqPFNDl4NyXkhBD8iXgA1npMk4XzDs4GTwRiLCKePJZ26AP25iPukrFbwbwESkv4pg9egdm7WXoBDwl4ZDqlxkDhUSKHzE88z97opO/b0ywwSgW9FS8jXj7DWzWsRVEYCQiOfKj8FyFAmotVn21MW846HwmjIbUCSeXiIGH4K/hu+Mc+vyvKJI95jrnKQSsNF2bciWblTIeqqnJTKrcU8gSGrMo6q8Oav4V8UDw6YcQj9YZCXHVWyUiAGSCXsbZHl+c4vzzHeDjiRz95ieNxKmW0iN8Gb967/QizPcNf+9/+Q5iuw+psOy+LFkkFIS4WtgTdq8ZMWLqSZIYhax6KBlznP2uE+VEyBCr7anGIMwo24KiU8c9FDHmpXAo7vWeHQHUm5CZZCUrg9+iqg+S6qqXGl9puNMgjmocpmJ3zoEPIWFnHeDOGrJLTxZ/xoh7UyRTEZTasjnWWYoKqrPgRPND3fY+hG05l0KhRo0YPpgcbenjnACJ43oGI4O/C/d7jNMGzz1pVVNQdB+W2QzmneNk4ZABMMGAYg2Do0XUgQyBD6IcB2+0GF5cXePe9d3FxcY5fee9L6PsOkw3DZBcnBucsAMbxuMc4Tvj45St8+voWH//gfdy+eo2eRhhYWI75OxcH9cBzsKBjTNbhbn/EeJywuzsGa2znEu/idSQ9SJNE9AjCPm3icpo7TZ6AZRKKCxUWPlKS5SSbLNuTAqg243UsMWjgMqWkDCTdqDQHKLxTpIDVhJzCSFyPtDm8pBgkxbHQhKMASaVUztTaIj6lI2sCyrIRjxLMVDzTnCx6tEi/qzs9613dBU0jKSnaGgVA8hKglIis/92/LEpKPCFfy5eULlHqlNUsB4V/plyIwUDSPLLMZzpNKi+A6CWGdBsoZJbrfbYJzvotcHFxjnfee47XL27w/k9enFwspFYW26L3jN1uhCHCetXdozjluMl8YsmcPXG0pITpci2vZEJd1idJFsKnKmL1qAyTYxE4OZ8UDTmWJV7/BEK450pCcZYTF22CAG2MFQaWzMdJmSyUnnN6ehGhr1QyxgRjjpQZivWILFhN1xX9o+CiUGxLRVkvfPISlTJ/emGkE10o5syzy33rlSJiTnB+bVUe46TvzdtGWS5jCH03RDesjRo1avTF0Ud3H+Hbn377581Go0aNGjVq9AtLn3eu3ds9vvvyu7gZb/C3vvK3cI5m6NHol5fkYJVjHw08ehDCoUC5liEGDFgxxDsGxStckLY85bqTAFdy8uYcro0FYADTGQx9j9V6hfOLc6xWKzy5uIQxBBezkzNi4cqVcKDROY+7/R67w4i719cY9wcYciA4eOFhhpMhHYoZ7QRnPabJFVdOCIYM9SsDDpjjnxEACgdgQviML8awvkYkFOarcytw64W6mSE04s05p1eiHfMEU/kyyFSWMWFH8lwwJQEVc5riOaDAcgoobo4hZ3ZUBIUhC35ZoeAhtYRTlaXkiIdnnLfCkGdYk+Kpqt4ZcFrIRKJr0JaqZxVWXcOYpAu7gCFD4Ws11Xwpo437kezQ/4pysn4LCYHalUWWCWG1WuH84gyH/RHXN7s3YsjSvpkZ0+RghhXe/bVvACC4qk/kZqgLGWVUYLkqw3uFNMf9EMsXDDPi3gSrhnNSiHXfyEnndks4ie2ytGndbuKoGdtNNpPKfM+6UV3EBT6zl3llUKTLmNIk9VVkkQpTwsAMEHHCnWfGQsU4UqUxw5CFU91vlspZN67Yiuuy34ch642Zor8tYMiQejgFTWs5ImLvXcDVGzVq1Ohz0oMNPeSKE+vDkXMiB2OCAkqI9+gpPbU3XdpHtDa+iGNZb+KgTsDQDViteqzW5zi7fAuPLs/wlS89w3q9xsXFOVarNR4/eoy+79H1XeTFgZkxWo9xnPDjH/0Yu7s7XF+/wDge8eruiMPocHd1g2k8whkHIo/dfsLhaOGmKbjXHy3GcUrGJ5P1OIw2GHhMNpac8qxDcTJNek1WWyfnYaIFN4C88IjaarhOxoM6Qr8aMB2OADNqg+Ds+kKuZhHr9eoUOoXpulbkQ3bRuEQUnkonr6c48QzhmZNtRu3ySmImy3nKcYsQ0ZND33UhzbiZbbrwgr2+n9KDvVnUtZKXkqTtI8o9Tqgsf5R+kBaI+Z0SVukWjJAWGCLHUkmlLPPIAplSkHnDveQx8V9KDoF7zT9UPE5Kj7xnSRoAxw19X5qpK72epeJKvY1zyylMGJjVE1lkB/eWsrlPunio5IngKcQQwR4nHF7fwh7GqHAWLMZ/PJd/Lj0m69QvbScca4e8ZkaXsExI5BJlyao+80Y9p5SXiRWLy6oZAWEhHlMqg8zrPjVtEmWQg9cemNkigDn3RVOVN9UFmdRgiVG2i9OrivQ+jV8xjbyEyRUnoIkpxqGF1Iy46gvM+7T4wMICJV9DRcVTGYdy+Hz4g1TZyzizh4Uyn72opJ4rC4kEKvgynVreKnJhGU4EfYWUVDAzg90EdiMaNWrUqFGjRo0aNWrUqFGjX0YKmGQw4AhUXg9bY2ZyypsAeJdxHoI4qiDAAJ3p0HUGXTdgWJ9hvRpweblF33VYrVboug7r9SZ4BklXSweszDHDWYfr62tM44jjcQ/nHPaThXWM6XCEdw5MHiDGNIWrV7x3wVNHPAwomI33DOuyJ48MDAAlhqx3IAM5zyA5/CPoVDzYBjbwcPCeAUMwXQdvHRJiU4gupymbrCxY0axSTmz6UoWOVRiyyiDiHio/YsBTwvyWYKlQtaw2Rql4BwCGTEw+XnTeUcoslzkYhWjcM2M9isGC5YD5JshsAX9L4JMG7mJZ5KBaEkA8qUeqmkvRSSKk8prjYjM+i4OK2Wt2cSC0xpBTfnUODDkUtnghRMKQVVCJposrCVP5swhImfd5Ky9rKRyeJXjnYA8j/DS/klQjm0VZCAr8D3sNs2wAhe3pwtZERZXqx+WegMqAqpSEJyWHN2LIRbgy+aU7XhKGrPqpmUUOceJFN1XakhkDUBgyeA7VzrjVn0iplwdVQ3rZ843CbpkXpJDLIXtl0pbUDTk5cZJ8he+K6g7I8+pMMhVRZCsvVLGxOEBI7qljKD5IJyx5Fj9UmSR+GZ4BwLvgralRo0aNPic92NBDlAzvPBgUJ1V9ZQfS5h4hnGwmIjjvg4GDkXcUrnIxQUnvhx6b9QbrswtcPH6Ot54/xq/++tewWa9xfn6Ojgy6OJg676L3EA/2HpO1OBwP+OAnP8Xrl6/w8tWHOB4PAHVgEKwNefsOADF2hyN2uxFumuCmCbv9iN3uCEZQ0BnRQJrzuFvfrZcmhsITQrAiTe4HY5C0SR2VSs8MMgamN9lrXa2gEpLbK++DULXBhiiTYb2gJ1MdJj43et47McUqy3iOym2ylgcnZVu7xNJ6U7kvmvkhY0CcjUWMCQ3AschO8mXZak2yDEoHR+WWyvJxViJZpZ8NVLReRklfl3ZJtXuwQhmryiGzsix6amVXhZU5/7SypNvLXN/PZQoPy+TDooln9agqIhp6ZMMOrVprpbteDqn31Sa3VnHmqiqByMAYgp8sxt0BfpqQrsmRMPPsVBLZe0MaT4rrOxYrquSwbn9JRpXiWonqhO52srQLzCMt4ColNxZNNVlSsQBQtoo+dW+z3MNKSounWpgEQLCEgt+6gEsmLXRSDsFTRzwlQwRjCOwBV8tElHEx9PCRKXaV5yMdhZVcwt/QBkTZzm2RlUzpVIK6Y7IMzXoU4Pw3DzngBXkVdbGwuAp86XfSo1SBmOGdBTuLRo0aNfq8JLqBjx7jvqg0GQzPXulYjRo1atSoUaMvitpc26hRICIGR6MNVlBP9s8b1+KIa+144E0OviC+za7+GaYj9F2HblhhtT7D9myNp88eoe96rIbgedrEtOVabcTDK857WGdxc32Lw36P/eEW1toAniJsHsu1zGBgsvHqFu/ALnjtmCYbl/5zrCHwm6k4u5YCEpgjRuzLiIIfS1w5gKdxoRlURRFHY/HAqzAXknP5Rcr5b8I5Mt5SJr+AQWksPGQPlm1m5tl4VyJTy4KSupeDY3rcnMPZc4RT70tkOWoMllPMAh1TGJEwon0ilEXJ6WXjj6X1GS3AlzQLKl6ZeRGYq8IW0GdsQ+mz5C3DYyd4m3OhGoO0z/AwyZGX4gI18He6JPoQFsNbBzdZsHehJEmUcznVbKdDlFJpBcb/gLm2xpB1hqqPRqBS8bRQus+yPOe6PWk2tOdmwbJLLDjvR1WF0OwzikzKq1YEMAUqS41llk48SVJY7BuU+JXxoAwTLxDXdcYyQmU2y+LVGLKqmtnTKrIEnL0Kc0lqTQsYclG6ahCSvkt1R9d56M97RR29QPGiSVajRo0afSZ6+NUtcbIQrxp6ggoKmEseKIBgKR023QI43VMf3ehtsV5vsT1f4/xyi6dPnuDL776Hrl9j2Fxiu1nhyeU5uq5Db4Ky7ZyFtROub15hv9vh/e//EIfDiIMNxh4vPnmB4+GI3WHCFJ8572EnB+8cjuMEax32hxHH0QavEt7DTh7RlgJZR6BSTxBKE2aYGLW1MIPhnIVz3Qn9Jy5GyKDrOpiuh+kMyABdmrCoUDnDvj2XPBnJOxqlJAMQtXJgPYeUyvpcqdCTmijT4Z5LBsMYEzZxuZpclZaZ58mcuPeMaZwAUPQsqKynRUDKG4JeK8jkbsRlSApablZ7H6zmmdSiJFmhizIWlU0fjJOMkQWTXG0T5Tl3qpDkBiB76dIlLh+m8Hr+Tm+Z0ykGvYDIP4JBDRAWYsBc5jm9sqwsuRLlglRrMaTqKpcAtZIoLibre/fyX+XYkICnTy9weXmG437En3/3A9zc7VIZPQflrrrxEskMZOGOQ8UJuM5PM17LQr+KfZdrxZVTzunPKcX1M2vrKVNJQzfmMsmH7NOF8ccslS71b8ouM2L2sdZiR1u4rXOB78AkQS+3lcQJwTCNAKZwFVfqUyq4mxzIRAM+kvRU5y2UZqh1UkyPyrpOp1iSvEh9r0qRPEzlvi2lmlWwWtvk9lNdTYPlcTIbxGkDomrQAnA8jvjhj36C7dl6zmyjRo0afUZiML718bfww9c/xPvX738haV4fr/Evvv8v8Gz7DL/7ld/FxeriC0m3UaNGjRo1ahSozbWNGsn+HSHCuuU6O57Ukg02jhHChqbgoAadMei6PnjvWHUYVuGK78vzC5Dp0PVr9H2HzWqAMSZtIHrv4b3HcdzDThOuXl3BWgvrw7vd3Q7OWUzWw3mG9zZ46HBh0826EN9ODtZ5iKGI9z5iibqkC1csQ2EOS1gQBUMwI1cHL2wWkiEYpogHR2xW74+ijlhmEmDifPqPi/dlKjlajYnFDdEAQqH0YpChEGLx6KEN20o8s5QZFw2CPeA5ePkVu4d0zmmGA5UIljCUDgiSDqfzr/FyZFxa8DWGNNyIoSucKcFClCDAZSQ5XulRYMi8EFRjlnOwi+u6SdhaLK94mFWeILhOKsHWnORRVHVVn9rbQW0sM2NdMbcIjxclC7y/+v4PcPfJJ3j3N34N9mtfxXGcUiBBGksMWWPZgoVLomUNsLTReeScwRKP0m7qPqCMgySJE0VcynAhn/viSqEIJb6MhSrQYVW6fI/PauayPms5vYn3ghHKYWuZk2CxwfCMHKvYOY730QjWVGUF1Lgw2wBQY1ndOuV3WYYZhrzYQVJBlsvM9fiu6knzVyRBZeb3YMjOOry+usHQt6tbGjVq9Pnp4YYeCEqO6ZUlcDFwiRVa1I1YrmLwIGJ0hrDqemw3Zzi7eIzHT8/x1tuP8aV338Vf+tVfA2CQLTwBQK4A8HDsMNkRNzevcfX6Ct/999/B3d0OB8fxzsSQ6ThZeM/YH0dY62AnC+8cbm8POBxGTDZcnzJjHdWURXOFkJTCI1/SlicD3gV3fkHf0IpJeG+IgM5EA4+opJvs8YARN8cjE7J4EMtm2fxk2ZvUG46FAonZHHVCNUtUqwPB+0rkL3oXSdcopEUKJ/uSmQ7CDBc9pMB0cQ2nmY3yXJi3lc1GuBqDqHgfk088QNYaanOY1CzLyFffwHSpPoJ8YwFmc7pWF3KauZ0sKVD6RMKcxLhEc5jckADK04haVMTkan1T2mjmVcoQLWZL32CpPy3pOJTKJqXLJydqw/JaaTq/2OLZW4/w4x99go8/fBlusqAoc4iyXzZSDx/vMdQWy/m9eMmIy0TFaZZNVTAVRLtQK8PXtgaI4wYVEThHVcp8kYWipeVHeFG3Dq5YVznwQnBod3wl49nGKjcMToNGXchlooXvtW6dWaXkZYXI5TFaxl0wvHMgTzADVfJMzXJOYuQhfXEm/4pTJWK90AouXePVUPrdYik5LTzyk3CaRjpbNhoTdkoJyQmZojep+WKaLD7+5FOs1sNCoRs1atTos9MPXv8Af/TTP/rC0tvbPf7k4z/BW9u38Fvv/lbbfGrUqFGjRr/UpE96f1Hes9pc26hRxgJOeudU6/rwzecDOxTgpY4M+n7AsFpjs11he7bB5cU53nr6FAFDDpRyYDlexPDeYTwecDgc8fLFC4zjBFsc3EDwyszhKuFgHMJg7zCONniI9vl67oSHVtCwwDE1hjzf/VOoKcerus0CUJVFELAGwY4jNlyizSWmzCoeCBlDjp6VT2LIp2hWuIzZcBUueeEQSIV1SC7S0aYaaQROAFnEdjQAnZKqEaxKHum13grOHioErw4i0hheWRZ96DKlXpRnCasMvws8izPLSxjyPI0S+1vEGrm8apuVwE9jyKSw9WxYlfIvMOTakKaiAmvlhcJlpFlj5AzGzYcf4dPv/hlWF5cYnj4r+lIuaZm3PgC53GzLtpXLVNXRAkxbY+cFBKmrR2GRS3hliQ3jxK97MORZ5vEnZ1lmlhfKhiVjBJ1WmVeJtT9Q7ynEvCTzXIzUgnTTVe2SfWhzxGaBt/tGJU71lq6BkkZfjA+nC5D6thwEnuHQ8/Lo9xm7vkcGuQJTQ+LieZaj8x53d3fpUH2jRo0afR56uKGHD/cp9t0AImAaXfSUINt08d67OM4ZY0BksN6eY7Xa4L23H+H5sws8fvI2Hj99B+v1gO1mhfOzM8Qd4hCfPZyfcLvb4f0PP8TxcMTVq3B/4t3ta4yHI/bjBIdo1QzGeBzDPYs3O4zThONxhIt3JwbvEjYo8B4Qy8KZMsVKiVOb8tmowIfFhmx6Gq1QEgwFIw5EK28fJ5ihk/mZlccTUTTU5Frr9oTkgUIeinu/Qqk8ObEK3/NJu/SeEcov10KEacdk7yFOn3jnuFiYX6eiWC/LJrJUltBJOUnpUlZKM2eYT4oxDTUxJ2vRQlRBxulvVERLPa7a1C24LxWpYTWg6zvYycJal0NWineUZEqn4DyVHwWlq0pyhRXFIKCSS0w1u6AJojVB3ydSZYyGH1o11C3f5CpCbjS5PyT2Sb3OSWO7XePxo3N8sn6FpJ8RQJwNFcriSp9darSyKJFymWKZI1f5wJgTpyVkOU9lpol3tWTIf7IxVbEQqASlHhVrhJg2q5XbYnes0i0WByeVwrJ09YLjpMs/ULSfyO2ucB6zlJPy0LPMR7zCpevCKRbHpZYeyfvoxQn1uKPTl15CwZDrlBqvuyLmEkmpRQvwB7tDFtno/qjGmHR6pM4HMQ8jnpT02EE5FFHw2GSakt6oUaNGjRo1atSo0V90YjC+/cm38ePrH+NHVz/6ebPTqNEvDIXNPErXOIu3jCX8ISzPDYgI3bBCZ3pcnK9xth2w2ZxjvT1H3xn0fY/VMADRm0HAkBmeHcZpwvXtLax1OB6OcM5hGg9wk8XkXMI6QQxrHdgzDscJzruAHTsPuULXxe9pk1TAoLT+9xWGXG/kySEshRZUmEUyjOCIk/rw3gi8qTE5jdEl7HCOgZTYU42PZUw3h0EJbSDiJTVMU+DQ4UFZHLXR7KHklLEXEmBKA30l94lvDbgVV+UWjJWYfEEJE9OgJ4Eo108dPn/Ngi5YkbLcu5kccOeu60CGYpvyuRz3lTt9FyxPYY1FCFoKDmlzC6WLBVMYMoCwWR7TqzDkhNvR3HdKSqrA0zljqOo5FbEIX/utv4Kv/frXQRePy3AzuagHRJWHFMVEKv8CSKr3HBaBWslHlV/3B+mbKe4DMOT6+1Jbp4R+ZzbqIMKSGnvyQUmdJ83zIPVc80ML32OE8ljqab5T9PSnykO+xDYmB4eTt5U6isbmdRo0K1D+rmHk9J3m/M5Iya/oQg/Akot2kPNnMODpRBPL/Yd1W5x9hgPW5TX2jRo1avSz0cMNPURhMB2ICM5NsNamCWHoTVDgIxnToes6nJ09wtnFU3zpK2/hG197ireefwlvvf3lMDB6QK52SV4jmOG8xc3dLb73ox/i9voWH/34E7jJwtkjCIw+epww8eJEO3mMo8X1zR0OhxHjOEUjjzygJgtW7a6A8uBaKNIhQNRTKG8yM8BG3NGFeEBQADoyMGQQLMcZLuj96AzQEfLkxoxocRJ54kJnT/MVBReHLEp//MzeRmQm4cSrzMhZD5Gyq1LJYgVUGkOr8ovVfVhscJoICw8MUv5FhbiUo1b2WPGlM1fiTKxnPUGuZyijGl2fRRFKK/0FjTDllw0AGDlHnS6h63sM6yFs8E62TIl1etpdmHY5GdIhXXZpf1rJYE5l1IpAvYDS3kHEIIg9ENesuVo41KMvYqvvqSuoNqO0usIZB9Es7mY94PJ8i2HVA0ZZa1NYdkvryzoYgeLiHRK2WKxlryhUPEU27olPS9001t38eEL6LusxUuJP9a2Ggvt0w7mRjmrTiteSg9wipF60k7liLcRV3OpLlo2ABktMazkuK5uyWMwtP0qzHj+KZE0YjzyDyVWnK8KnTy6J5lzLE8k5Dwmq3aS60fzcQyR1oKWd21aur7LiijFIvHMU4w3AsjCRBqP76byC0kKNQGnua9SoUaNGjRo1atSo0V98+t6r732h3rMaNWqkEA8Kh3W8t/Hqk/CmM5UHiHj1yjCsMaw2uHx0hiePNtieXeDs/FGGfTT2E3EJZo9xHPHy6jXG44S767t43XPA7+SGANm89Z7hnMNxHGGtHAzk8tCM3hhMuKaUTmHIGYBVLHEVhyqshGDiATrZCEw3cyNjKQVWQuKbtESPOXqv0IfxQjkoYV2Z14SwLWDICjfRZeLZwxlWI95GMr5CCq9R4TXwVZSloiQ3Xc9VnhrIQ43XaTRRx5njTBkLXgCgFA81DDTDvxUvZAy63gRsy54owALV3gUElw8vFYasYixhyHMIvDBfielKfwjpZox56WKcsuyY/dZ5LsvSGMK7v/FNPHl8gY8+foVXr2+KdIoYqS/IvslCW6nbYBUinyE8UbdLLjtq0hiy5PAmnFLxptskqecFG2UUFBgykD0435NPCKLa/BJWndqPvJnj5svEKKwcSHmEKfKveVP4L4v1l3zKOKX5EBz4NIacolIt2NLXyn1E98mzoMxbYTcjfakAkBEPMi6kTPUPNU9A5iW9T9KoUaNGPzs92NBDhhzvLMIg68MmcxcMP/q+Q9cZbLdnGFYrvPXWU1xcXODZs7dxefkET59s8eTRFpvNObx3YVTz4XoW7z2ubu7w049ewh6POO6ucbe7xe2nn+BwGOG9hXUWh/0ezjpMxwnec7o38ThOcM5jtz/CWhfuWFQKOjhMJ2GW9cqbBEpljAgwSsll9VxpNmG4V4MwB6trY6JnD2OiNw4C2MNxWEQ453HcH3C43cNNU2FAomWMpKih1CP0wL+g1NxXb9rTBJIscoBCVWQGe69FgOzeLQrzAdaGWlHxWjnVyuvcdLeMXXi4OL0QkMVR+KGtvvOdoKc9F5Tp6wmWwLDTBPYeztp5/kUzyIuqGXMp+H2Tt7SzbB1f6CBFewyGJIYoGHqAoqcBnX9hw76gcERFRG9mQ9UORWulEzxfv7zCh+xxd3M3K2j9rRaJWPYWi1doRa9Q0VOdzNabSuEKixWa8VusN1LY8KbWpRZbWMqbi5czjyuL64M8BtVLzDKxOt5pUnb3y1ToxtmwI2cS4if9WBT9ZAmTW0whn+jRgji2U0+5scWxFUzRVQxlQyxebgP5mRqL4mIzLC6r2zlPri4fStpVafQMc6IaZq1I5pNTrlFSSRhEPvepRo0aNWrUqFGjRo0aNWrU6JeMEgrBLmIS2UsyxU9jCH0fPOhutxusVitst+dYrzfYbHps1gP6foBcEx6W5MGY4HCccHu3h7cWdjpimkaMu13w1sEBK7aTBUejDmZOhwGts2AOV6/6ZOAha/7ItxSEff5Vn5QPu3SqrILhaaCwihOBGIoobcA/TDggGDHkcFt3OERoJws7TvDOKUwiIBYljpvTfwhiMg8T8dCYPKtnRQY1UAJtjFCmmA9eLuFBS8CpQoCSx4YcjoovCjNeAnck4IkN/YRvx3AJPWWFg80w5BphnZeKgLDnMUVcfRkoLOgEagoUqJhg6VUDjLjq6X3iIB+KG9TZQ7c0JY3rocBYNSf6VzIFWTzQebqsx90Bt2BM43iS1WqrReG98TihYHNRPiXqnfsvlY1luRoIuN9DSxl0UTiL1St7C5hjyDU8ewpDxkLrOtWUio2DOYMFgix1vpSwMHgfnDnDkGu+ctrBk7N4tohtuWhrajyTA9X35n9aADmafDmVyD31XZeDtTkXqfH+dI8tk1M4dmqySmbpwzePHo0aNfpC6MGGHkBQfZyLHg2i94G+72C6Dn1v0HcdHj15jIuLC/zqN38F77zzNt55/jaePH6cPVMgKDtyjYn34d7DF6+v8cff+T7GuzscX74E+AjgFpNnOEdw3mK/22McJ7x+vcM0WRyOY1Ic09jJakzX3itifmAPglxboQZSkoml3OQMeiVDrnyRiaPe7zNE6CgaepBBF60LJuuCK0Ab3AGO+yMOtzuws8mYohRyVFALlxbyXBPnySEp3FUYNXmIClQKqwobwy+5lAv6bXCzmBdplOPqz2KmFwVSlNIymL7iI8/38SKOyrAjK1ZcTcCs8ohh1Oa2XIHDYmCUFgGlks8s6au3zMGbjBjm1FQs4O7Th0p5vEnpILU6y/KKtaiiEhE6Y+CTwhtjsy/1RsVmvRzJVvbVoqfMfMbp1csr2Jsb7A7uRFkyFbpN7CcgLvpAoc7WCyqiQiFm6ASV0qqVwgUdPCeX08vjRfiS5FMJzpBcEFMwW9ao6McoH9YLo1zUsu/SrHaWqe66ZepBma6YWEiBqtd5saRP1qRnhgAv7i4Z2ZJbKpCLZEw8oSNgymLJ5o0xj8XCleqXZaO+t8NVZcVszM6GTvFd4rFoeCoZTs1ybi0uiXsQeYA8GjVq1KhRo0aNGjVq1KhRo19mCt5ZMxZoTHBVHw7KEdbbNVarFZ4+eYLz8zOcn51js1mr5b5guYBc2MvM2B+O+OjFK7hxgt3vAbYAjfCMcPCPPabJwjmHw2GCdx42GnwU/M2+yE8NLit4qDB4KK8PmTld1bilSp+ZwlXU0UuH3nz3PnjUZu+D5xEbDD0CdlbyFLItMUnFTklvgiKrcIsY8qnAoVDlKyWE4EVYCeOevdYyjSpNWipG9kBRo06higTo1hgXV2kAesM/X8njFYY8Z7yG4gVDZsdwyN5r7quYkluu3pzApgpakkj5fg6FVThX8uzxpuzm2HHiXBuMnEjgcDjCjyMmewIvq5py2lmgzDODw+EzsKpvtUeQxFECwoVTiqIsqHDGE7TU9paqV22QBLmUOGkKQfPaXkpl9nCGIWPeVBZSSkEWwiXThUVroYVnKTHGsqFMFCoBxJTOFCacvTYMi2nlQ3+1l3aV7gxYplQwXfUzvPshGPJ94wMhg8dp3+ENDUdNFVwMEkA+nSlGWg8Ctxs1atToXnr41S0Uhs0+fg5DDyKDy8dPsN5s8NbzJzg73+KtJ09xvt3i6bNnODs/x7DqwfBw3sE7B2snTG7E1dUNXr58hWnyOB49Xl5d4fqTDzAdjzjc3sK5EcfjHaz1uDtaWOuwv93D2mDg4aM3Dz341wp7noSj5eBMEVfhtEIQY4U0JUwewOvh1xAw9B2GoYubm6IQh81Q+S0LEj2A683hPKfoMGoTtWJcFjvLZ/vriTFfHVM9Ts+S8pT4qRVhKqJpc9TS2wEnOS3ZnsgXBkFuhuGYl1RDMvaI2k+2OI73egJx9p5vvGfyMQ4V8pjdoykNIF2jE8Ia4UUbE0VrU9kIJ5xSQtRisHqGzHXwelCEiKqqWCvPtMmw0c6x0MHlZLhix/usLAtfWb9RvUGaVEo6llvKObOg5SyrJBNgd7SwE3B0S+op5TixjVF0U8Oe4ZPRkM+JAun6J68XWVBtv1Zmc6BFPTMtDhbWG4u6ZTK5nsug6LWpCeXeN9M3ixJo5T67StRlCq99iqO9ciwvLKVdzlYs6g7LUwpy5KpaBKXTG6w926i2TIyOQt92qU+SDpHqmpMrHUppamO5NMZA+IwSXDwJEBtTKotXYZaV6uV1JqmXtTzqK4Gk7OqEyowvqZoQxlmP1y9vMQyfyYayUaNGjRo1atSoUaNGjRo1+oUhVktvQsB6iAir9QZ932N7tsGwGnC22WDoB2y3WwyrAV0XsDAf8SLvPDw7HI5H7PcHeMewlrE/HnC8u4FzDnYcwexg7QjvGaMLRhLBE4aPXj4Yci224rL4qKEVgShKJHSOvyykWMJ4FREFeXTdsvcIQkIzqw3FGQymHlY5zcGNwsPGEucVpDsTT51XwtBSXnO8SqGOcwy54JOwyLSQ4MYLz4vos2JxLtnSpnSRpQZLF65Erh8IhCVl02wUYCTNwfFFRpbxqPBN3tfpLBxYqmSRfwbcLV0Pr65fFgy5jAVVQJSCUEHnGHIuT/rlgcl6eGLYpT5YY8hVPuLNpr4yJxuAaCCYZ81oJn1ScqmbrW6KFb68xLbmXwcofiYMuWo+J5p8ugKp5hUo+hynAYpKB82LtIS1ImPBVaj6iULj53Ja6EcyhhqObSThvrWo8mXYVS8Kda5lDGTcXhLRHe5EG32Ix5kZFWMaVfnFPhMx/vvTpUI+qaxxf+SwG2G65tGjUaNGn58evBvlECyNB0TPFX2Prh/w1ltv4+LRI/ylv/xNPHvrCd66uMTZeg3rAcdA3xM8Ozg3wk4jDoc9Dsc93n//ffz77/wZDgfG7Y2HdwfY6QbWOhzGCeNxwtXVHtM0Yb/fwzmPaQLC6Ogx27wUjx2Ic7FSouJ0kpXQJSqehx3FdJJcB4ufxTYjBcOX1dCnxUvgUVzxhRiegwvBcPdjvgkwpKMmS5naSP+cK1fMVdyYgFaMivv8kF0SSuR0fUwsh5zCB8S6PKRYb0oX8meZsyqFCygtKRdI8ypeFiTPoHMSOJ3uD1cGFeoSqzLO3PVJGfUv4U1pIkofYIrpUdhyJ+UZpFwUUZHaslK+VNrK9VdF2ZBaHDnWnKN4xj5aiuv2H4VoyCRjIC2LVJW1Euq1HNUbnqmoADPuRo9b72EGA9N1Mz5TtswwjGToAYTFelG26B6xC/4q4QsDb60wK+mnAqgesLC4mxs6UFok5EekDF9iIlHrZs3nAjGyyIoak/EjW08U6YhbukWg4cTiLXshWuJHyybzPlsIpYViFTMyLQsN9vU1RjF3AzBTMsaZLepigbzP3nRCbOm76hlFfhjKgKnu0yI6NZYlA6GuUJY1t4vlphwqyz3Xd+EIJbWl0/0vJBfqhBhw1uPlpzfJYKlRo0aNGjVq1KhRo0aNGjX6ZSMfgZIOYS1uunDN9dnZOVbrFd56/hTb7Qbb1RpD30UvHMHjR8C38mFB6yyur67w6YuXsBYYRwZ7C++P8VpvB2c9Dsdwxck02XAQwwGCw81I4VwJSamCPRxDDgkuoYICK2ikhwB0xqDrjPI2q3FXQXK0ccoc4ZByqJ3H8tkpeGkJQ84/42eJp5b4aoXFxT+Vo4g5Kf7mecoBTY0ZzSljz4Jb6wT1W8GrFLsVRqwA+yqPksGUXhU0Y94aNRSAKu8pvGEL+A00Q2MXmBAMWXG8gI2GV5zwVilncZCxNpK4pxkter3O2aQEBH+frMfIwVswmftLTokNLnF/zQ3lw5PF+cPi0JrG5u5D46sXVD+sGu1SAgWGfJoKVFR3Y51X2qTgBDqH9laBz0u8Fz+rfYWie1FZ3pmMy5TehCGntlSHi9k4jgdXl7JgRExeyk4A+wUjD9kKINXHdA+cCbTE4pf4O1nqN/fOdHD5jQHV6KA8envP2O+OM7k1atSo0c9CDzb0GLpwHcnlxWOsV2s8e/sZttst3n7+Ds7OzvD0yVNst1uYrodjYGdHHOyE/ad3OO722O/ucNzvMNoJ0zTik09f4PXrWxwPDne3EyZ7xPFwC+c8xtFisg773QgXra+9DxbdYeIIPGkFM8xJsvmWT2Bz/F2OmfXsRymeKEe1wmLIgClsXqYUVJC+69B3/dyaNKZpTJCfzqMgVu7SYgosz1Xg8pC9ttzluJJCNvoU3U6u8UiTcPRYEQ07lK3HXIayiRsVi7zoKidJEk8XMagYB2QeqvIahCsgWNdgLpp4PtGGCWnxIPKLV0J49srVIScBlMpovrOQCk1KKQIk5UBSULKxTakcFYrZouI9X/TpN9I+FnRoxY7SzKuFScqVGfA+yWzJg0qp74ZrXRDLlPSxmS+1WD91aiIzscjJq7qcW+HyMPxJydZiIfVCv49tVO3Lp/6Q0i3EURp71J5zagVtXl+FtqtUYaVkx8VSFsuSgl0zxkXSRDK+qBg6SlJYl9dkhc+J1Adj36vbdWJ5uYUWbM7KIVmo8VUpo6BwAkV72Kn7eLgXF5XxGMDRFWkSTGZVpVMmxrH/Bo9D2TjmPmU4e9tR4APnzOr2pGt6JptKUFSHVq9lrG/UqFGjRo0aNWrUqFGjRo1+GamLOMBqtUHfddiebdEPA87PzjEMAzbrLfqhBxkDZmDyDtZ72N0IO1nYaYS1E5z38M7hbrfD4TDCWcY4OngfPXgwwzkH7xjT5JK323RgSXAlXoA/eP4jr/Lv2XiLQCFloGFxkzAdJFtIzRDBUKe8F2vMSa50UVhFCXHlPEvgE8VGc+KxjJtOodfl1wfd0u+cT4T3AGRMJl2lEeFsKgBgUrLXIFjmp8CCYp76EFAJt2kMGTEcFalw8VkBa5zxZl13lTXIjGYbviWMPKuC+Zv7aDl2iWemo6unGMwfCopcSitUvWo7qe6RYNkiallBZZJVYN3Pcrur8OL0XePdGoGlMkpBXGHQKpw+jVsgezVQiSIN3XKWwz2QCpz4Hvx1luZnwJCX5KFEOg/DqpQ6iyU5KmBW7w8syeAe2RQYsvT/tMeQw8w8MKe4of8LBk3gsPeT+Mu9oUaNsxDqan5YRabis+DeGvPlYpjQyS6n/gAMWfoc0b3YdqNGjRo9lB5s6LHpCf0w4Nnzd3Hx6DH+6m/9Jh4/eYRnFxdYDwOcbEF6D+s9rg47XB3v8MH3f4xPf/wxrq9e4/b6Gp49PBjjOOJ4CP92dzscjyNu73ZwjqNbPcD7MEgTHOLYDgAwUSnISm15JUp2BRWUF4Ny0Mxf52qYXF2ilSgiAnUmjPbezWRDIPT9gL4fMl+QMZsAGBjToesYhqoNwEJR4urrwrULlW4ceBUPJ5E3Nkgb39GDgpQpyJXD82g9XhhziJ6gM5aJjKLVrc+lSypvzE/+WYnvKw8jiAsVrid1D8AoS1CO0Tnr3VJuCnXhOVzf45lBxOgiH1odllYgCxLZcA6vs2U8qliQkhFF/SZft5HUBkZqV1ohAMorWbJHlOqaD6ljVEQo2mviUelwkp7UVVrM1O2jUqwAVrL3OY2UschYp1AubBiIMicgebCpleSonFE+yaG1oFLhSpymhUG6C1P3Ud2QllQptYIV+VZFL97r8JUqWCaLE94hTrAxV+mlrUQl3Ycrd3J7LFMOUVgPVKr/MMqsF+RBRY2WfU8/LzTjhbLPhoBQcdIXTdcFQyvvIB42yuEsnMIxpgv9IbYBx+puWY69s/IKstQvYUzylMFMM0GH5HzklHI4FTAk69WPHDrNGoVI71O2YyydDhGGrlOeTBo1atSoUaNGjRo1atSoUaNfLuoNwXQdtmfnWK03ePudt7DZrLFdr9CZLu9zcTjUd7QTDnbCzatr7G7ucDwcMB6PEdELxhzOOljrMI0TrHUYpynhK/oAGwkGmiCfClspsMCMIacnVG7tL2LICjtL8WXjDgBMxBJPuLYwXZfxjeKNXINNMAHNLrOukyueL1wXsYgpc4BFSONu2vcrF+mla8PTVeVKElHOpGUZN4oTBpbSoyzMiAvLp48AHoELvCfBM7OyMLRxTNrgLYQpaQqWGzwZzzy5LKB46f3JDdg5hpwqX2Ho4s27DJeTSFvxNRyX2nL4qzHkZUaXM+GIx2rvugn/pIoHXkpCcPXEcPlOqoDKRxq4TDKQfQPVn0rp50O6s1t2FvC50suKn7exYiOh+qy/n+pX+mUdfiktPoEhLzexMmtJU3f5VEcc+4sey5T0lixBWIxmdHuvgfKCgxCO5skVKUu298iDVbBcnjjOUNjDm3fp+Fw8HUVc3IvRiR6ztaVIapY8Y5RoqeIzj7UhHmuG86hWDROkmn7VJ+412FDzhCRD4WB5vVXYqFGjRj8LPdjQ4zf+8m+i6wY8f/4lbM/O8fTRBc63a6x6A0Med7sDxsni5ScvsLvd4fp4g/14wIuPX+L6+ho319e4u7mBdQ6TDa70xuOEaZpwPI6w1sJZH+9h1ANlnlANqBw/gTwDFYYceVIncDZmiMnJ3FgozPI7KpnkQyAiU6g1BcWB3XQGq80a6+0aZCgpX1qhJ6Jg5MHZo0a2di6Lmy91qdRBsSAMmpJKv9zMl6fZK0aekURnyPqDyECecuVFQZVb+NYyTkxnxQ1Qhg6SjleZqlKleZpUXlx9lipClF1U2I2BYVlALKm86jQ/qUkaAPuoCJosieQV5AQRlYY8tSVOKiKpJ0onTNbvQPYeEl8WOcfGoa/WEc1eFK4lRbG2BK1VDObQpkO7yHEyVzqmUpK0EVLFszxN2+Uxquk69L2BnQA32dCHVduaM8+g6DmnksaM6r5VLHjKphfrZEHhQ/b8kxeRy3nep6rViilO/D5ZmnqsU3GzF405J1ni8xVJbumU2k1SVWvdP6WqTgnovipGPfI8KaCxr5sOTBSv41FeeMRYy4crWwyZ2AfndZuVayrbVb2wqMbWpWtodLmEH1GaQzGi0V46/aHGzMUVi+SeR80ikzx0ghmYnINB09IbNWrUqFGjRo0aNWrUqNEvJz17/haM6XB2doG+X2G7WWEYenREIPKYJgfnPPa7HaZxwtGOmJzF/m6P4/GI4/GIaQxXszjvwz/roycPC+8Y7MQMRGNmSN8XXe/rfT8mFS7gIcTqYFDCH2ov0Sp9UlhFBP0ydrFMZAhd36MfujIfHUYBs+n6Fh1AYREa5yyIUTknrjFkRCxWJ1rCWkV0iQvkPWaqfU3wCb4qHIiV6QERCny+LmP6LsBdDfotYccZw9J8JPyzxmBrKoFdZBwqC26ORs0YLjFkVnhcCXOXpKFNxUeNIc+ylwcaY6zzqEVE6sAdMBNfBPpBUFh0DFTidgpDLtqavCrx2uKrRDXBi7j3AJzPYYoOpohYyVcXog7LqRwSNB0MjOnM5LNAyYBDZ7NIuk8koSncuQyrMijqjuPB0zrt1GmLu6c185zGtqorpLory6kw5IX6n23/0AkR1W26Tis2tOwJn5FtOBQyzXJgl6qEdPlLuZ28ZiXJPLYS8T600CkKUUqb1OOAwpBz0qqQVZ+ZCW+pWTKCl/qZZVOjRo0afXZ6sKHH3/0H/yBc3XJ+iaHrsV536AyBfbg38fr6Fa6ub/Bv/vBb+ODHHwH+AOYJlgHHjLvbHe5udzgcJhwOI6bJYZom+Gi9TYiGHMoKN2/OmsIwQ65PkUPTPg6IxphiYDVac5XHlFW8oNMQqCNQFx6yBzgaZRhDYROTGdaGOx71tTCStOkNzh+dY3u2RdeHhAKPOZwhk/YX2flZGvm6EZ9OpS8SA8mDQ0zDmMrQg5W1cmE0ExIIy4VsAFFv0Mv9fJIfxzmUERZSybNHCpCnSFF8uy6rvCzP1eSeamRm3V7KLWu4YYL0PlhgR3008iGV57LiS0Upi8mUOcjfOxfbSbhyR9LMchT2Sh5rFWO5KPM4s2m7WmBIIknJ8cpTDWV5hvSyAl3o6RS9HjByO6p14agsOvF+kDqSGEwsKVMQrhQToiAFvrXHFAbQDx022wHHPTAdp6i0S0qk5KW0QGNi7i6lU5NWrLNSz0pRp/Q+dhcwon1CLQtkw4PkDUKUYN2UABTW0pJryocKUREB+oHITffbQvnVi4UiTqz7k1bB85ZF6m/4mhXhU1fYVHp8nUK0tq41/CB/0/exnU5g7+F8ObY558NBkS4s2kqrrKrQpMalos/G1qgNnxDlqVfKceHA8VqnwhiusjKq7AMVJ7W8tUQW6kENWeEkkgP5e8bwRo0aNWrUqFGjRo0aNWrU6BeYvv6Nb4CIsB5WMMag70xcrjPYexyPexyOIz78yce4ubkF2ALs4RnRC/SUPHdY6+Bc8CYq2CQQsUwuVvL6T8I/8hXViL/j++J8BsEwBaBZrfFZYXGCIYNiXIEnIhYWoI5wxa33gi/NMWQiwmo9oB/65A20xh4DtmaygUcNjqnN0jkwqMIl+CmjP4J/FtifQFLMi2nUaEi62kB2fStAKXkSCEBluWGq4C8RTcYK1fMZpK9wtwyiFlwVGDLKjXmxnaF0MMfHa0wElF3aWM8YpOBRpK7qJSIlY81OltYihlzDrZqiaOfPs5BT207GL4KMyl+pFOkrOe1SYvmwYGEwpcMYIHiHUG1DDt0uYciqbFkmpOoEyVuD8MAUDtH2vYGzgLcBlyN10Gxx+yC1Zc5sVJYIrP6k+hKvPoQS611qYloW4iVD9mVUuGwIU8QovrIGIk80Xc2I5JULI/1tjiEnJnR/XISSqWYrB0zCCgyRxlsVRr+IIZ+Crau8Ke5ZBI/52QO6pOa99FXK40zKqG6cuT7rYS8PERWGrPsGqSBFB6awiaAt5eaQeA5biim1zYIRqt7HD+u5NOJq1KhRo5+RHmzoYbwDvMfd9R3AwDTu4JzFNB1hrcVHL17h7m6Hly9fYre7BfsR7B1G52Cdx35/xOEwYRotrPVwzs8sknn2pRxQ5VUxiQJKKVEu+EVJS6lTHPiDizzqDIa+xxAV67wJSPDew7oJ3jGcdcVmoUx0hScARtBKo0KvN3nriQ+sNu/FgllNLMlSOyWcLSvrdKSEoqTLRrXeQNeyyHKIP41B3uiW1/WkiflklnZd1UKgIjH44PQ9Jxc8FcyiABw2Shkcr9vJkUQ2mReK/5dLDS7KqmxCk6CVV5JKuRGxl4qMXiTI42XtZVlxzvV0kmbmsEq5rrQocXtY2I5HRVEWnHOvFLmyso6o2metXBY/4wOxXNWLiKqPaX3fGEJnCD0B1gRFrusM1qsO3gOTDWmK0ZYYiXTxiiQSBTgKU5dN1pJZXKylltpYJWSlu+fzGjnom5WqEz264KH8eUqwwVVdrFDMND1NUbGlaiHAdcWd0KhTX9FrAC4+SvYKK/tqXFDyX8qPyAT3pN6V42Ma3zhexaQsuJeLXOSdkkrjZrWQYN3iOfcM3a2k4eu0tbFJ8Vxz80BlO6ZP6r9GjRo1+lnJs8cHNx/g9eE1Xu1f/bzZadSoUaNGjRo1atToMxGFU3QYjxMAwNspXr9s4b3H7e6AaZqwP+wxTSPADszh4IhnxjQFAw/vfLyahUv8oP5OUNhauY6nKg5Vb6gOmDBHOWRm4sElg85EgxWTA7NneHbhwMnCoY8ZhhweRgwZER86hT0oDFmXFRk7TvjTEnxZ86LRiiQ3LkPXuCBlDCWi4jrBMi3BkIsiZFC5RO/KIKd4Lndty2di+JOuglbvlw0XNAhMFe4avSgs5J/wwOolawz5ZAN9Az60iEHVGenHJb54H4Ys7XgGO6oTh6c8G5dxNB5/ms26DzJ7vP7px9hfXePxe+/g7MnjWZMBhT11Ez99PBxmDKHvDNgDLvaTdC42gs/ilZsI8ToilXKGs+cwvohE/rCKVxRQZKjkdKqrLlWZlqEA5kEwZYRFXDqPMVSVqTyIqKPEMe1NGPKJNhlgUsoGUCo8lyzdTw+ARMP+BoHYK3EoLLiQt/TVeZlzv1djTMKJ59j0PA2FBc+6MKv6o+WxqE5q1gfnWZUYMhYCNmrUqNFnpwcbeuBwh8kxXr4csd8f8eP3f4Dd3S1e317hOI3YH4KbvXF/hJssnAsK+m63x+EwwnmGdWGTL5y2zsovFQP5TG0ME7BS0rLtbYhtujDgex8m9s7IBqBkEFILp8mB9dkaw2aN87Mtzs636Migi54QTN/jOI642+9w2B9w/eoazPnUPyXrbk4TB0dlkA0B8GCeu3DjVIZYjrx7mRYskmye4H2lUFbKY7SK7hA2/71X3iAkfwIMuoIb6sIvU5tM51jRbVTMWSm6vuAbkMP7Wl+RhUawYo/vo6cGEg5V3Yi+wQgGQJ4ZvTHKK0hoM95z9LJiUj6lPLrIS8jDuSDDzJspytCZ2FCUJTIDYbP6DRO3iRP8zDNLwVl+V6RHSumq14DKGjwpq0rnpKjsJgXGM8Ae2suK9uKSdblYn2IUweoGjkWz6KpASaEs0ynLRvAA+o4w9AbrnrAygOtCv1qtOlyc9Zish91ZlI5rDAwZDH2H7P1lzgeBF+1ipMys2uCsTOmRvi8xK30z/Utkf0qJX6LISxA5R7FV5kiz+2tEWVSLf8rjonbZKXIpeNXvK8Vd1m5sKIEjp1clRdPLv+I4k9YncaBKnmBkIdH34X5dz2DvyjYIgH3wVmRMB0OU1iVzr0MxPJctgIF8Kga1C8xcrrw+KPuxKPuaq9oCPzXvFLY2lqsYnXk4ATrTpVM5jRo1avSzkGePP/zgD/Gtj78F593Pm51GjRo1atSoUaNGjT4b2QneM/b7cH339dVrTNOIw3iAi1d6e/awkwP7bMwxTcGLh+fszXmGvakNz+JAUgWLzE7cx18CoQiMkCCVCkMW3K4fOpihx6ofMKx6EAgmbjKTMfGK8gl2sjjujypXXoQRgHhNL2kuqxA1FpWADs6QHFVh5F0S0xxDjhJAQGCr8JHtmalDgn4kvQWGNTMKQ871xjOMpyxcWeZ8xXSOW6QtmHPE1I3GWVNa0XvJzDohp5U/OMCz7DWolOC6ovz1Jrp6dIoW3z8UQwYygHtK9gorTBBwwXcsi+BcytCjgEcrqFIfrDtdRlWrEkYMexzjR3/0x/jg330Hf/2/+M9w9uTxrNyGgC4eFuwMwD4fFlwNJhh/TdoYIORFROiMiT3IKxxZAZjggi3JNHlpIRT7HyfxUp59WdzDnyGudCKw3gcrDtyl0lVBl/okFaI/HbeOfU9jTbKiLCdg3jaQH2eweP4uVUmRbRyzyQQbmwqnTsFi3yYyqstp0LZkvJQ7pfjyXrM/628SZkk0qkOJB50Sk9cQ+tKB61Mk44954/jRqFGjRg+hBxt6/PBHP4FzjNdXI47HES9fvcThsMfdYY/JWuwPR0zWYTwc4Wy4a9F7xjg5WOuj8oW4MQ3InVuJWDb2smYn27FzY7s4GFYTTRpHRWGJH/3Qo+s7DEOPvuvQb9YYVitsNiushiFc00ImbKJ3Bn3fYTUMAAP+0sM7DztNcNZFpd3PNwglQywxLFOIvkolTjpS9oXwqQALk6XkmKdDQnFCvRYXUdqgFWGL0qsZyPNzVoZKPS++Zf0sK3y1rqFm6Jj2XAsR6cTbWeZ7qoWir+PVM6EUQresvIiTJEl9SYsGaW3MwRWb+p2s4/XCoapjPYefUAsXKdvI5omdiOC5MvKRfBQPyShersOQzBcZUIpjNKRY0CUX1JAoLF2/DJAxYB/6MGtliJCsrgHGZB2cc4lf60O9Db2Bc4yJs0EAiNBHQ49i0bHEz2egpKQW2qfU/H1lz1SE44VnEi590YFSA17OZWHBkH+TaiNV2e89aVCmp+0b8jpb6nX55sNCkWcAlPtVcpFK6rcEMwQDE4wyVB/OHlSyPHJbzp6Q5v06lyXx+ZC2wScDqsIJTwApN5IJYUhVdnp8LVkIhlimM6fDNGrUqNEDyHkH6+3Pm41GjRo1atToF5I8e3x89zGuDle4Pl7/vNlp1OgXjl5fXYM9cDgGr877ww7WWkzWwnmPyVp4z3DWwsfrrZkRr2ipvFXo7wqj4IhT1Ov0Ob6aERX9uMCQ43dCuEKCTNhElgOBpuvQ9x26zoBg0oE4MoSODbzpgB7gdcBavXOhfJMFU8ZQyys5ahCxxCkK7HVxf7MOP/95Pyl8c4atV1fOsGC6ZQZL6BpBV1SFITMKmOY0hqxzKF+kJ0UdYo7TzvAg/bvChHSYdGhrLsoZhgxpgrlh6jpTkPjno1l8KtKXulrCkHNAKZeSQw1sMkoxJSEoec1O350mIsLl82d4/vWvYX1xoRJVxaBgOAWEw6JevJUjHy418aCXSwNCRNJNPJhbV5beAKja95wW8P30/B4MuZYVMJdfEWnpJea83xd28XXZR7QX8DIsLUV+I96dOq3CkAvWT3azh2DIXODCOktOaYV9mgTLimHOEobMOU7B0ikMedY23oQh5zy1NEvs/750qqximagdFmzUqNEXQA829Pgn//f/JzwzjgcLzwwyPrjNQg8GsL/bY5os7nZHjJMN7uqYo9s9QNQeMXSQKzqAeO0Vc3nCnz2YXVSewuhHJmwMesjdhzFoVDRMZ4qpirrg7ePi8Rab7QaPLi5xtj0DmS78I2jVLC4sGKthCN4ezoDnT5+GRcg0Ybfb46c//immKVsF5o3HsMGXNywDiVISDF3mLvzS4iQtPFhNdCaXL4VXCkZ87ERRpi7UiQ0bAyIvMmEREk7UI35yskCXckuBwqQZXYNp5SixmVcYFMteTppqKk8zX1bUsveJaNCAvJHdJQWP4Fntt4onC70OKuZt5cpRza1EFK+oCWEoljtLXFVC4pFAMCl55z3YeZhOvIyIvCI/pFzIsLRWqc1AhXc5RlwkcVJews0/JvBGgJc2pvWEBSpkz5VilEjcqqTVT7EAChflaIGSqufUc1N48ajivAuGW4ZAZEI0Aww9YbMyGCeLu90E6wAwwTrG7sjoDeFs3cO6YETlU7qEzWYV+pDZ586DqqoXtGCieF9ksZjUZVGpLIhINZtkcLRIvBi94mUpGyXbtFbgqr7UoKZdvUh1KUTAVIqjdgNKqjS+YELLLYZhyZMlMmbmI6L4qnEgG0Uh1L2iruvAxgCThWefrLNDnyU4dsE633QwxoDh4ZcuINVDjow1SvktJJett8qX966NePYzX/bECN6AYttWzPBsFZOYAJlgKNgMPRo1atSoUaNGjRo1+otLnj3+4Cd/gD/9+E8x+ennzU6jRr9w9L3v/RAMwE4+YpyCKxgwAXacAtY6BsOP5KW1OLiFhF3lg4HldmWx9odDxuEiskHxeoCl/dUFD51kCKtNj34YsF6tMPRDxLskvZo1DsYfNADDgLPtFswcvJZMFjfXN2DnkXE5+VjiiYri3HulBgBwNrsISUUMORm/SNiMkzAFToqrrNWVyoJLJQ+qglvpA1kae1QYSeE4o4DmFIYcf5/EkKtnkpTEEz/WkqGg1+DgNba4OvwNx+SlPUlG+QCbUexnPKxkWcDqeSkEY8/YN+siImF/mlf1t5RIyXF6YZSnEgLYVVcbLZLIPeOHy1FY4X+EmTHVQrs9mWNn8I3f/W38yu/8xyBjVNKUxNAZoO8JznmM1iXP4N4zJhsw/KEXL8VOtbd4WBCCCZ9gK+GFhSQqDHmpOHQvAKzzW5TALO6ynEjSmrGzwF9hDEFV5Byefdk2y/ZVN9pT2LuKrQ8zVhj7HENeYDvuLGhcOXFiCMQUDP6gDoXLRxy3DOTK+pMj4yzfU2NAruL7x4i6FDX/peTE/OPhaYa9LtMMPRo1avSF0IMNPSY7gRkYo/U14ILCBwsf7120Ntyh6Fy4Q6XceFfeK6JCxAgbhdkEoKT6ZHeeFGSDUiaVoMwSBQWgi9bWw6pH1xtsz7ZYr1cYhhW6rkOxMa8HYtFzieCjAYRzoUyH/QHHwxHeBQOWPD1SsdlOKg0A6V4zRvRqkgtXlywrjxKXZH7MiiErK8qUd0wvqS5KiSk2Q8u5MliZR+OGdFhdSV/PrUkXrV6LkhjqIG/mniZZYEjY3A7kNYEqBbXUEk5O6FoG8QHzwhUlVblq5wukjJASx2mDG7n+lTDKzV9W6ebySmqleAIXzBzuHjJ6g1ibIZUxZg3phFBSWCrTKKzw9WIsF3i+eI5p6Jpg9jDxNEPXEboutF/nwtU5sbukhLwL7hA9Qh/segPyDOeCjDi660xtOnaoZPSiFe77NO6iYKWclt3iLeqrs/fQC+alrLiKcSpsbeShLaOTYUQaEMLiUolgSRRpaKx4Uqp+fKzG5RnfZbwcnhLfRdug8D6Fp/QQCRxYWm0qsACIi7LEl2JMr1dmC7OyAOWQwQU/ur+W8RbXIFkQC0p/OVaWgiMEQyhjmqFHo0aNGjVq1KhRo0Z/kWlyE47u+PNmo1GjX0jy3oMBOPZx01G81sbnNni8kH8J8wRm638xqCjhrxojAkpPA6zW8yWGrPEGWcOTMTCdCR5qhyF474iHUzI2oIEUCsYradNZvFh7eO9hrYW1NpR9BriUAB1pXlkQRV/ioiexpQrPIMTT75yKrYEkAiVPBBnnWkgbc/irMKLAAvQr9SOiXsCQc0DF2CkMuarf5HVZHmscrYAIT6M8S/yqBGPZKqCMy2C1l5UcN4NFxYXuis1Z3rMfcwx5sSiCpZOZ45D3Ulmm3Dcwq5b8XnB6npehwlXnpSH0fQ/0YUzwXg6dIm5yAyCKnjxK/FjgUfEkDULYEE8HhZUH7gV+aoz7zbKpKKb9mWJR/T2PEYthawOKuikUsKd6KQBwDeBKhKW+SWX8uulWKVSRa5o/0xhySOS+fq0YkAEjD1uSUNHpWHm1Dig5z+VwH8v3kcaQ1RhZU9qSWxLcqb76Biqvl2rUqFGjn50ebOixWnVwnsFHwHrG3d0hKK5jdLMXw8m9ilxMMjJSk3ovhiBKUSzupSIwTBoniyGPGYhKdFDKg5WsMR7GMJ48u8Rmu8Xl5SXW63UyxEiKFjO8mwAE7xuGOhgTrANDZgZEwbJ8d3uH/X6PF5+8hHMOLrgnSDx1XQcj3kEI8QqYkEYoffB6YD3DOq/Kyyl/rQ0FQw7hIxsMJGtXBOUnuDYzOSlJDwyKrsvCpikFDyxgaC8BDICdAyzQr4JhDMe82MuGu+QdLbdnG7ZRCc5mzyhmU+1eI76XoOKaUSZRDx+KTF1Kr7ynLU+gCypwQeEEPsM5Gw1hgpy8NraodVsgeZQJhgY+8dF1BmwAZg/vXFjoKS8G7MM7UPC0EOSmlYTSy0etcASDopC56UTWEjnINHcn5RlnSQYLCyldbakfkCgmlJtP+qjscWUzPumLHMvtQhvqQv/Zrnts1wPG0WJ/mGCdD948IMoQw04Wnjug72GIsN0Gq+3d3QT2HtM4pTZIElHxkJtBlg0KCdUrLs4K24LsS7noMgN1Qzu5JjvxdNkmpPTUUijTcVzMhmScy58WCFKnue8Fbz0iB6Q4STqLfKiCxc90Oia1Xd32dH0o13is+qmh0HKiNTaJsUPsH8UahRnsHRyH8YpMDqcN/NJi8iTn1XgTeRdPJsRUjLFUVaKJpytkrEtG1LJYrtdM91II1UeXro0aNWrUqFGjRo0aNWrUqNEvI3UdZQ/HYIxHGzZ6nU/4BaCwswJDhnqfMYd0MCTBJNV25Mx7b/E2JR28HyPip8DmbI2+H7Ber9B1fYKcNIYsHpoFXhAvxekgIgjeOUzThGmasL/bBw+n0dBD8DTxrJygB4o4SkxLcBnPwfNQ4cEioiXFvrF+UDwnxR4vbCYKShZwp4QdJnxa5Suii9c3m86Aokdt2WgvYC5J5xSWo3D/WR3prwqHk6ujJV5xKQQp3heyXMSQi4eCC3H+eYL9GYYsmG+GtwOOFZ+zF08olMqkjRPmUPsC1jvDkJHxO/KzfpDiUDi0JUZIs3TlF5UvhL3s4SXjjwU/VHyt8l5gKYC9CHUWrvTuOwPnPKwNRiAJy4t16Z0HGwqeusWzBzOm0QEe8M5V48dS5QlDpJ4sYcjx9xKGWpVpcYxZbGjLo1HCePXvU8DjUkMU2TMv5pvw0tyFVZ/KOGvCfjk30cxZHNvqTYf4mT0sVRgy5xCF94sMCEdedMvNXoSIVf0UQ5aHZ/HqkcOlq1yAE3tXpyjXdTF21fmqukldmQFw3uP6bJ5BSjKG2mHBRo0afSH0YEOP3e4Yrm45WkzWwU4O1npYG69vUJvzhaFHoRzKhlp5xYZQqexxGvTzXmdU2o2ECcr1erOO12oEhXOz3WC9WWMYenRdl5StbLwgbtQQB3UGew/rHJwNG9THyWIaJ+z3exwPx7BB7b1S7oNxSTf06Ie+GtTzxCL5OedgnQsbnsq1xuL0QxSNK1AqE2rRUk6HKblSfvHpTGmMctUKeZWA3iaXVGb5kVL4dPIpfqGoSPuIwaQOolJZ3/NYpBfNJWuvI/UaJUkniV8tVmKeBS9JKdGFz5vYFPNdKvmswPHrvARcBkt6MaefhR7C5bukuBXlOpnL/BlDGbkrzeSeutYyKLS81F9UYWPXNyb3f8/hyqa5biUnHDgo6xQWJd5zMrRwVhtDPZC00nVvwPlqYyn8ooxP3EGp2+CM64XuUVh/vHFlkJ/NOdf8lhbm4rEiKdGzriW2z3nkCEVONtH66WzBxpKHXj8RJQAh9UTRgElzVacl3nzK8Swv0k+3BU7jBsJVYShFG9kq0i1CzOabKoOqr+Z+NK90XojXqFGjRo0aNWrUqFGjv5hEIDzdPsWXL7+M14fX2E27nzdLjRr9QtE4OTDCgTcx8PARC9LggGBeaU1dYQAZz4sP6g249EXhF1QHzZi1XPcQrtWQ3z26voveOcv1fsFX8vQbgDbx3uE5ljMaejgr+LEYiOQrRqg75QE0Y2xghvceTrs4OOVdNgEfgiFzNHjJOCLd63VZyyhKjTkZKoggMz5Z5Z3knjGm2gdCgaTWrMQ0oh/b3DZqSLKyVKixpTJNXsyswIQ0XkcLuHkBpKmYGkMWGTFFbwMJLYvJVGDcAn7O9QOVX/mmwpB1GpTfFRiyBCkEK6ktVITwm4LWCFv5cxFD1sFje7x7fYVpf8D64hzDdhNkT5qXeN39vCIVrh3riJQXaEL0BoRakGW5QGWZlABpFnY5+nxMqWOVqOy9IG4h21MZStgT/X4Wtq7fBTy6eFulU+x9KEZTP1qSDZWpSb8rtkwY4ke/AHulDWnMWvaqwCDWvqMX6rDGkDUPulz3tMssi6UdKeFTGgoVj8Oz0/11Iff8VMpGVeBGjRo1+pz0YEOPP//BhwADnklZVGdKJ8plsPQ+h1NWHYURiFLO0qYgZLwlGESr496kiZ1A6Lvg6cMbQtd3eOu959hsN1itBnRdh1XfozMm5OXjCXGi5CYM7PO2I0Wrazfh7vYGr169wnicsNsdA+/RA4l4oEjlNgTqOmwfnWGz3cB0HQACiycPtmFCsx7sPQ6HA/bHEc5ZiOG3iKXQV5MYKP02FNRemQ9NWlyEcBLee7cwOYQFAgB08Wi7oWBd7MnHE/RIV2eIgh0m+WBNO1uCELDwtMw61W2pLISN/BC6LKdRCkE+1c/sAe/iqf+4mVy3vSS4mB6LKmBimw3hnVy7E68XEcOjcH2NGBvkxQWHyDFtdSdnkXOsBb3gQ1a+50LiyvqeUniW+LMFRv4ajJLyXY9aWfJe2g8l1sKi0sdaLTWu+R66aFoMbbCVvEbEENkrT0igM8AwBJecu2gINrm5wiP5eecwHUI72HkHQ8B6FQyy9rtjHjfSogkzK/daHzKLwq6vADpRJ1A1yfO09Y9F9fY+c/8lnbt2H6IAg6SN17rpYsKcxoQ5nVBohV2S0xc+GklIn08pV+uU3K9Evy4GchZlXLKlAJCYLowt3gM+e34Ch1YZ0jDRmxKh6zqwR/D0MStbXTOU2rrnMlwaTkzuX+VYy7FN67E0ey+RdMTzVBah9KOyaiWKGDr55Upr1KhRo0aNGjVq1KjRXwAyZPC3v/q38Ttf+h38sz//Z/iTj//k581So0a/UPTq9U1cg5dYGYACn+C8mK4ODKr3C/tpNb4laB5lEBWCG5gIEDCFa1q2F+fohx59Z0Bk0BkTcFIIziV4pPyW64UDdhMwYotxHLE/7OGswzSF6801bpexgmB8QYYwrAf0wxA9oIYyhOIFvFKuM7bWYnIOnn004Aibjhp/EJlkbDXwF3wcKy+lFWYkiIZnjftkhEOw6pAsFemz8OArRhRmtOhhogbjCryHEoZcIylJjsj86DjhKyMBrXEPQl+xPgOroeLpcqd6D7/FiIAE4I3tUjDmBONp3tNBWCnTCRCyYuXEgwUMGSU2eU/yYUM541lJZAoPz3VbYmNzfipQVjMjfEpUVW7vPP78//1H+Oi738Nf+t/8bXz5r/4mooOO4JnDAs77iOmVLSANB56Dd3UGptgf+i7sSdjJZSydVKxaQKmaY72cwJDrDnYfhjyXxRsDlW2+DkAqQN1mJXgAcsvEZHx4U97yfKlMGpdeYrkycjvZ8CrWNOZKuv0U2HcckaSfeRPx5dKAKOPQGZWlONYn45855+WThCHPZUjqfTIGqsZaLgaVefo1ls6S5hJPMX0GkrFWo0aNGn0eerChxzjGOxiyJhX+Jl2Kq08kIw99XUk5RlaDeZFuNjiQ98Rh83C9XoGMAXcGXd9jvdlgtV5jNfRJQRfSRgHh7sdo5MEM512wknYezjrs9wcc90eM0ZuH3pUs9BnxNBJ5Wa2GONfmncSgGHNcKIT7J621wahAT2YU1Ppk/AATJ4Fycjg9G6tNSrWoWArElJcQgFbWJZUYn5K95WL2xhj0wxBFEa6NmKZJKfULDBY6DBf6Q3mVSA7Db7I6F/2NKlFFpVLcIZZ+CrReFd01ctjwFdnkNYzSoOWr1rnumYeL5lwvwqDaZXZXU6jVWSuKbUqYYu3dYUExLBQKrl6IYn5arrpchQ4WjayYQrpJUlGRFhd8nrMhiM6lNM4hZUgSFrwclVXvWNbGBRMLtXfiNxbEkut2sbynqGqzRTzO7Y50hNi3wzvVWJQyr3tceBRrU+p5yXuI9K2Zzh/zyw2oNGZQCwKxo076+9JiQKVd6PlpyOJZHHkeii7jCqd8ZfzmtDCuWmbdxLFYqxXR/KcW0GLYeR2evHixCp8Ufh1Wtw81VAS3e28uQaNGjRrdR483j/HO+Tu4Od5gb/c/b3YaNWrUqFGjXygiImyHLdb9GkM3/LzZadToF46clUW+AEyIWGqF8dT4E3OJdxRECmNQj+OyXjxXaEyPDKHvOsgpOjIGfd+j7zp0nUm4YcFnTDB7Io44WLw+hH0wApjsBDfasFHtyoN3c4wyjDtd36PrTAqV4NIKZBT8OmOHSFiMvoqjwG4LeENhgBVekmpA421LcRNjUoAo44SlCNCsQd85FhKuWu9UOQDnXJLAvcYQSYQlEvozYcgq7BKmlD2fLGCtQMbuKpC7wATB1VdOMcpGX+afIcMKc6MFbkh/LGDIRR5LdbLQUEkjdRUAeR/V4F7so6leCehWA/rNBqbvVaSQhwen/aO6Sxfl5dLjh3h9KI2V6vb4s1CI+zNhyCfSyt+qutIYcp22wpB1cP2l2OmoE/gMGPJJEDjlUo6pp6SQzTIo5V/URW4eSK+KcpVF1th2kU8aB1WyD65yLst9H4Q8E+hS29Jhqj59Kp/0nFO4h3S1Ro0aNXoTPdjQI1jrIil3MpSJFRw7h2IH0bs8yUfSE5AhihbMlR6C6CtCGVPIv37oMKxWeOftt7FarbBeb2BMMPbI1rqMaRzhnENHHYgMODI/WgfrPTowOjBurq5xfXWNcbI4HC28d/DWZU8bwpYat8XFHhFh1fV46+kTrNdrMAGTtTAmnPhO0y4TPHtMxyOOdzs4awtZBGU/iJcZIIPojcSH+xg5b6rLGiktBUyYYF1U/r1zaUNeeNSTvWyqAwwCB4MYEywlawVfzqQnDxFRIAzCarPGs7cfo+s6DF2Hw/6Ijz96CWdd4ldsWdKiJFpCm3hxYSqTgXJwoBcoHgwfrDNNuBpHDFkQlUBmB1CwwI+ZJYEaIpi+S1JmsQQlCvdJUnCZCISwBMBNU/B+kpSoEF4bbQQFNNyzKXWnNfZ076W4YmSKDZqjehRk7ZULguVFTe4UDAaLe0sTeJJazkvOyAjlWLqVEQB4F2WQ20Pg2aTy6XYvhZPripLyFNMwvYGJTcceLTxT9PgjbYmSzPT4IfIMDh/CyQqHsIB2NlqVd6VqLeOMqWSV32eWswKqPu9b2GSHFlX4UtvOuljuK4XhhF5tsVK6K2U8i5fKNBfWYOXYqBc2lfJ9QitMBjpidJf6c+YB1EEv6UI8qfv0BNmiirVYyutaJE912oHIAB1gwPn6rCIvF/sd5YV1beymZFio1NIu0tVB4sUltlmf1yJ6ZE7jqOq7pQxz/6E4ZnSdQXAw5HMwUuUGwxjCdtNjGB4+tTZq1KhRTR11+L2v/h5++73fxj///j/Hn37ypz9vlho1atSoUaNGjRo1+mxUA5/I0FAAcfQmYP07f0Vcz8+9o8bXOlwMQxQOYJi+w/nZObq+Q9/18XnAAgVDdgpLlQNOgIdzARkNoRnHwxHHwxHOe1jrEzYovBTbkYm3zFxHBmebTTQ8CV6Hk6feGEYOC3pn4cYpXVObQ+QvArknbyRRjpxCZt4K1tTBK43baz5SlUQZBbiMsnPn+DLkWSBEM3yq63psL9bJe4qdJtzdHpL3afEOW8pPbYImDnLSJPmmrCLwSIAAzRruyYYClOskgZyx5pPjapFHzDnhvBSLFzwSe++qQ21QGLLIJ1TU3ONAbrykCwaTZJ7Dceo4TFRukKs6yiknQD53J9LXU9R4YhlfMF/Ea4dSuqlOqAianSPovpyxwW/+rd/B1/7Gb2F1tobpTNgnsT7gd1VJS/Fw5gWxliJuG2o7Y4yh7hbw7kW8PfOsodxUhjdhyBVui7o+qkCC90pLK6nu/cvvClGovk9VtZXbcNoLtGrzOumq+RaGYRJAY8hAHBHLiCJtfYgvv+DyK+Wxg3ThUhnjVUgUvK/Px9bgtTwkpQeESlg1ca5avV8m46bIrx4HiwQ8AeTV2FM1BClDnH/CmdhayHlMIwKG3oS9kUaNGjX6nPTg3ahsxJtHWF6YhkpNCnmQBqeBkBYmCk0y4BoTNtiG9QDTEfqhx7AasN6ssRpWWK1W5d2GUTNMSmtUGeTTWovRWnTMMOxxOB5xPB4xTg7jGK5aKfScXKDiGakvvQlW4JMLCjLH6zMMhaWAc9FryOTgJlvPGll5BS8drodWaSmWJvNF0D+XrjS5z/vTKd1kXmaZlHN+xhA6Q+iW7pcUo4qlkhRrDY6XNlQKB5AseoPSq5QjDokkFT3VGeeIyZiFymSX9buiPpPapVdPyApX3r8W6eVaSco55YWDFr/Wr6ioukrd47pmKj2rSjMr8KIsVaohlS2nzqbQaVX8eq+9bnKJs6i4MItBhlrYsIog4ipKBXQdYXO2gneM2/GQjRM0nyn/rBCqhjRLM3zlbAxfaoU5KC/GTErqvBaXqV7bSYJ5vZTb+KIeKvmpBZZqysvrhhkTSw+ykYc8y/Ue2zbJCFNrzzqVMoOl/l3EmS1iZVwXxb82LMnGI8mw7DPRnJ+0PqHcnu7neiHVYjAo+VrkMCr0y24gGzVq1OhhRES4WF3gbDjDul//vNlp1KhRo0aNGjVq1OizkV6AR+DqTTiCUMIOdQJLUWvcziB6zegCLtsZmK5DP/ToTIeu62ab1BEuTpvS2vW+Z5+ulSAwrLNwzsI5DldDq7Az9mj5ezj0qDwReFY4CKWrW7zj8pBJ4vdNWEnGLRaRlRKImb16Yw0pYPNNGHICEGXjM2IlRDWGXOF2b2Bi5sUE4hWiwnCkfKyMPgrvIygKXTRXeVB73C32dwnV1zIVUoekUtloXof6SP9JoCnzW2CKD4HPankKQ1Q8KPlZwJAX03oTAwSsz8+wPgeyMRfSIVHWeOlSBSy0BUPhIDB7xuhsjpNgzXt4Kl5xlvu99AYMmeo2U7w9nWQNNZ7AkOdYOlA2Ok5plM2IgvefU+mcwJCXNg/k8BzwAAx5udreQAv4fmz2s/pU+w0MXsBf78ldt7F6jM7DxYkUVOc/kcV9GPIiLzH8Q7waNWrUqNGb6DMdO2YGnNxRJ/cHAlHhMKBs2gsxuyVDUY8x893K2eYrx9PfBn3fYX2+xna7wdvvvI2u69CbLlwb0gW2PXtYly1ou2KOM8nrA/tgaX3z+hWub27hRgs/OXjv4KKXA7nqQxRn7Z4vOGgwSfnPG7AenhnOeuz2R3jv0bGHAdCv1iBjMI1HWGuxu73D4W4PAmPoejgXPHZ4AN57GDLoTZikvJ+i5hYsAMOdY8KTmnTlrsK4viBjAGZl3HFKS46n3n20TjeUFjTiXk1vMDMzHESNZ7hxwt2rHfo+GN4cxzF4E/EewbJSsslaRDbmkOts/LwJQOnhwWogKbw+aSasFHMT/I44GxZzJnAo3gFMmmB9UFGFBR+UFHZTqGMTrb1rS3nRtWXBEGWqPTVQshLnZCFNxmBY9WAfjIsQXS4CEHc1yQOBryWQLD1VHwKATq70UQuJqBV71gsIRiFzUuq53I3KeREEBmCUdb7kXcghb84XKxTOLLP6VBxmfVOv4+Irkfbl+Rn+xn/0qziOFv/mj76L/X6EtnrKim78onTJmfrE2pChyrPSQQlRQV1Smuu4lTyWFODg+UQyL2+MXVTtYpuZv9QS1IuvnO7MG8s8cWWQlPVHljTTwqGqa/Xpl14sUn5Zp1ZchxTHbzgXTq4kHnNcKRstyqUMV2YlMguNWrpbfV1Nvt4qJ0Ixfi0N4YEBsAcsuxR+vh7i1PYcGxA3a+xGjRo1atSoUaNGjRo1avTLS2H5rTABwQuXNrcIEI+4Iax+RyWGrEAi8TIRrpgORh3n5+cw8VrvYGAQvUkj4mfKW0TOPnunFdzyeDjgeDyCnQ//BH8TFgR4ithLxuQEN0LmO151EvAFxmgdmD1MhHxMNEKRw4LTOMKOEwiMzphwRbLEj5iJkQ15BaxQAjJDOQr8IpVPyVVYS2GwBLhU+BLNIhT2C8mrSPjrncO4n4JH7s5EHN9nUHJp81TJT7xQMxQGW/EHSHoRBy1wcU5phqt3fMR7M0aaeIhx/r/s/Wm7LclxHoa+kVlrrT2c0316bgwEARAEQIKDqenSliVTlC3LluWrK/uDf8L9cf5wHz+SHkm2JWokKMqkRIgAARAEBICNnk73Gffea63KjPshhoysqn2GngA0Kvrps/euysqMjJwi34yMcBxVb4+Zp2UCUM0oZ8HoZnZhLnJr3WVq7EFyiVIMfMw9uSA+AAEAAElEQVQ7LRsEqEko5DbFI0OjkUHm1EDPyEYYkxPuFvBL8r7bX8AL6Sc4q2PZHF/2wB9rnc3WyUU/ZWYiXvtzs9ng1VefQykVP3rtNsZj6eTRf2rt19dR0gQZdn1vwmt4fC1UGceNAJttfF2LIfe5Xwu7hrx58rcLr+sLcW4jn1ofUwqiId5iqmswWgDtkuUjseOYu1Qi1ife+TOcFkRy9hX70aT+hvt2fNI04YQ3H1h6QXQylrovlzDkxWqFdmA9m3qEzOD4tHhHX2mllVZ6v/QUHj1MnQgLdaeYIMx2YRHTv2drz4SIxE1aygnDsMWwydjtttid7HByeoIhD8jxUJPFhb57fmD1oKS8Mqv7vcoSAqVWHA4HHPZ7jIcR9VBkIUmulkZmmsJpvIEkRAHb4k79QSCb1XWRvUktIJYD/soVtUjMxpQ0+sZ1cgB8ASMNVNEUwche24BMBNl0kqkPr0kTVZddYEgVXI/XFhQbhtgp1MoYD6O6nyKMRwvZMtfCrjeOnWttvODJIrzUDK3ftfp0iq79boqtbXqmcrKDWS3XdQDvDeQ6heXMoU+0avRK86x/mxKtcmWeeAzR93GzErcWbbMTvQRYwwSZL4iulw3mCSKTT6KNRa2fW569crp8wN3F/wscgcTQaLfdan8J8rxGH/NaxfQwBQkyBkzJfBry8fwoTawfST4rPvqTnrSfdZs7HyuhPvNd1qOzvW68LQyNecYLHjgeXVqXYjGtT/pho0EJqNWNh6YDx62xr63zZDOgRTxqPp1+Ptn/XPN90OCNtzrZ1HVMTL9dlfSVVlrpJ5MSJZxtznBje8NB75VWWmmllVZa6YOjda1daSVgegje4SzXQVQOJbcQypOz0PArySFdIiTKEm51yBiGAcNmQKKkhhCtTHOh7x6nvUj9T28vVcX+ShlRxhG1yCG/HUbO0JMJvOkYcnhI7WOFEhTDUuMXuyxi2CpriG7DK+YI6pwmiKE/sTqaHCbA0PzjyLVBPyQerB0JiqeglpYwh6iBFgJXX9bCfsj/SOoSLEggGmhMYU2rp4O95Lgbh789sWPI1j8W8kLzSkMWa2YSytgKmUDXoRrUXsxkGP823HOOIXsqsioGvq0MxI/gcujwrGthq9iZlx67IBeaZQHI7caw4fSW4LozgP5Vw5AFVhxS7uo+pSUMeYkptvkm1oUeKZzGW8SQl+rKITFdz1Er8xEU+8wSn/5smvnjqzF7EOdnhnhJZjsTs347L2TZj/LCszDWFjIJ5Vvd1GCtdxHf19nn9AiML5Tr5UzngGt4tvaNaZ8Q7m0XhufZzmiFkFdaaaUPgJ7Y0MNdxi2tw2EebXO1xewin2z7A1TzoMEgYuTtgO3ZFmdnZ3jx+ZeQk8Soyjljkza9KybzSOATrxw2j6oIH/YHlHHEnXfv4OryysNKHI5HjGMBmEE5KtqRNzu4lr9TktAiySx2cxWPDcMG291OrMRTwunpFrVWHK7EuGM/HkFE2GwHZAzImwwk2TA0AwuAKCEPKSj5Jk/15BF0v26LEBZW0o/MowmptwhTsCdqTGg+e2KGDjW8F48Yci5LKCyeTSgllFrx4PISiQg5X7qBRlIrc1HkxfOF8VLN3QNa3eIhvSlGImUJ2cMpiViq8Vo0D3E/Ru0DgKGuEwEJt6meNxjgsQa5NCXZNn2UNROuahmfnD9J21ydmUwT1N0gaY7JeKzgwhj3amxU1SOMxltj8zRg3kfGAgYLz1FFVSUvevHoW7On2d7Bm9g2H4AFnCSw6tZaRnDEY33PKsyAW9qzhiPqFSexUhUjpgE5aWtyBSFdr7wBoMRIW6DUA17/7hs4Hkccj6OViiYR3y51Ol0kH7KESdqQD12vOxP3fSnKMI67Vtjke/+3ByQqZtnCbyKEzZGxuigu6usexNPeu1x6jx+xHe39o8iNYwidS4/JZYOFD8N3vv+YGPj5/JTEYEwN9fqKEcIkCPcKtLRpQpALt5oREXLWelvooKme/yQbH+45A9CMwjQzYbX630SEzSD/r7TSSiv9JNJzJ8/hb/3C38Jzp8/hmd0zP252VlpppZVWWuljR+tau9JKAZO4Bj/obKBomlBx2gkcZsYdgGBseZOx2W5wdnrewoIkQhbAtyuPgXbZhgNOCcY4iofiq6srjMfR8VrxxCxAIKXGY4fvTMiMPATuJnBS7xshdAwRYbPJgmOPUDy7SLqckCF4OPSdIbeOFU9ujnvZKaIVU9hIcfkA6TX8cQkouR488Rv0nXeTBjuyYvTyQH4/HI/qhcQwP4QLQK0Y6xcc8CjDXGdeiKn9oER6EIyAMwVQh1o1O08eVn0CHASrHNK12nmXNfyWmocay9Plbr8YvIXGv18ktbpUoHKRpObJw9rSsU5q+KxjupNOHoWySNf33O4rx9BCfyIEnHry7QRDdkyPTeh9mTKkqmDvnQsUeiT7RABlkdX9Ow9Qi4RWEjHEvhgw5Fmd2p/XYsjcqr+IIVNry9jOjgV3sqM5hmtvIw6tgpmw6dw6hoyGIVN3aXdS5AQjn3aPiBE7huxN1fjgjsHJx5NqIuCvEUef1efaNvZZarIcBFMm1kaJDeh1CxV+FIZsScM80vrhtHNjWqHriee/dhcyfcrsBZiSeKhfaaWVVnq/9FShW4DpXEud8j419mDVym2qbcu7TGSJsnrxAIbdgO3JDicnJzg7OxUDC1eQ+8M6854B96JR9VB9RK2M4/GIchyxv9rj6vJKXNyxKRMhTIXrHL6UoFuBg7Lmf0OMPoYhI+ekCw4hp+SGEL5I6krvIWEQ+Q/yDEqR/dsto2aMoiuEq4ZB4+i8AfiPsLLxQitYsZN10N4527qORivhWlnDzhSvo1kaNxtnuOLfKddT5W22AQzKI1t+Ez8LotW4fJiFJ5OD6XnErT29zUNhLrcog5jHhJoji3m/8H4JPcRG2DikpoxxyMwsxaeL/yKF9ncdeLppeSI3FhpSY5Y0KJUU6voYCvuOEGZI263bGPUZpkTYbhNSIlw8vMJxLH7DYl5CUPhCVsux8+Z5+EaU0KwvNOmi0smTB7NncbQi9JmFhNfwJXr0koZsTb2wE5gphdcVF6VFs3Js8/UIOxwvz+sZO0fkOHbeeKPCE5GOw/CNgTBR0Q2KuvUnTLJyxR79MwAC2ky4mw2JWfOEuXhyZYin89TC/NyRrQ9J3G6utNJKK30QtMs7nG/OsS97jHV83/lt8gYvn7+M506f+wC4W2mllVZaaaWffvqg1tpECSfDCZ7ZPYNXb7yKZ0+e/QC5XGmln35aglrCD8cvHF8K6ckxBMER0iCGHsMwYLMZHD92ihiyg3HNqy9YwoELlihemMfj6IYeEaYISI0bJ/R1meC/oXxFtQUD98t8LZ3hVA1DXkYje7kFsIYmeGKQtCF8FB4LXj1tAMsotgRjdlA/wWi69rH6d88UByXDPdkPwQ0Lmno+6Q5wH0Uc+I4Yd4eZdZ2gAagmPjf0oImA+287BGwJE9PkM3zN+JlhZA1Ddtwu4MWOotqzDivn1vTXiijKZdomAU9+FHw5r8piOR7+ZCmva/jrMGQTfdfuy4wRATkTUCse3n2AyjwLwd5KmGDI+vg9YcjcJ7W26TJ6Eih+WtYjAdmQ1oYn0GGr80K5+/HkPE3TUj9WEMqOU8TS797nlzFkSc+t4Zd4nHRMwXVp0kcs/4Ahz5hp7M1oqewnOk9hZZ+6Z4sV6dptOYmfvT22L6y00korPZ6e2NAjqbuIpvfJpEpJvRqost3m+Tjjt5NVUWwJJ2enOL9xhpPdDudnp3LLexiQc1ajCZK8AbVYBcTTW0U9jmCu4kKvVlxcXGAcC64u9xhLwXiU5+N4BCCLkSz+/UGe8Mu+hjVlg9TLA0CkcfJY0pgl9unJCXYnO/e6MaQERkI6NWVNFppxrBjHgjqK1wNRJsMaaCypAxQLU1gBJDvYpyT1ZkaChH4xybY8muGHWT5bbEauEqZGmwq1yqKYKWEICzhnj2PTFEv0v0Oti5OWOV3sa5WYhdJfGMdRbu036/qkC3+Inxjzt3r5YSuDSNqOkli8m7tAKzaRekoZR1BKyHmA+hMBiJGyeRawzVTrm2wZRf1J/3GbA+OFtfp2QK3yiDp3rQARI5MaIdUCAqEgI2qIbtAQ27JTFnqJ+AbEN0+qPaXU9lyE1pG9MlYhBrhMW1PlqG0QjVIQNz3JlZPGW/srQfjOQ8ZmN6AcZQxOFRXJTschAadnp/jcL7yM437ED7/3Dg6HEYVD/ZpknGU3NuLgWhPqneVavUgt372tZrsleRaMTLoNlvVtz23CW2gAJk0YbwZgsrnwfKa/97FVxQuOblCSc97x3Fx5xs2QbZptU9KPs8h1myt0bmZ0PPD0l+v2FFOXH2xtBJ9PbOObkvSZo97yMJ5sDLBlEVyYEpmHqLkUOmYpsrLErJbWLQUiZ66wRQFTYEWGFU/yUkMZ95QD5JxwenaK7W6zzONKK6200lMQgfCXPvmX8KUXv4R/9+f/Dl9/6+s/bpZWWmmllVZa6WNFH+Ra+8LpC/jtz/02bp3cwvn2/APkcqWVfvqIZjeUuWFeCl9Mdt2ajLtTMcPyhs2A7W6DIQ/YbDaOL6bUgl53oX0h+BxDw65ADDqYGcfDUUJSK6YsF7XkffucHWMwYIN6OKHnPRmGTMGgwTAlwiYPyMPgPCbFa2ljIIbgSbUqn1VxbJ6VJCz28Ha4wCL/+EVH84aMlpWfo04zU5zXM0sGKckHLl8XgGJ39jjgyR1xKNOYpQnuqJBPrWqe4l6cI67F6L0ghHp5fVixcQIoNc8GcDFrWBWVr2HENA2nbX2qk/rsRr4X25oxNIpVNfLZY8iG25F+50ZIKfUFLNzE6w18pggjd3/auT3TBO2awKJ9B/ePJhgadem7+gFNptfwY2MiUUIaEriyepFf+qZ11GEz4Lnnz3H39bfwb/9//xfSdotf/Gv/JbbnZws4reXiaKvL3zDHR2HIkjTk1bOCDnvX990wmnFybTHdfENT2Yd0SxhyTObnG95vlzBk/b6bK/sLpY6XU99ysevr6LATjtkYm51LTCleCg5GHLF7uTxIMORKissHWcdB615JAPF2gnmaBvRj/v5awHvyPSZ9w8YXTZK6sQt1z7u/ibDZbJDFLfVKK6200vuiJ/foMbstjTY5UjdP9e9tEUhisEBJjCi2uw1Ozk5wenKC8/NzMWZQbxhtxbXFVYwFSq3gWjEej+BaUcsRpRTsr/Y4jkdcXu5RxiKGFcxo+4q2wnBYbMiKmujvrudNDgctTdKJeBiGoBNq6py7vA7HgjJWD10yPQ+NNF2AZaWapOksKKMmb8pVOI50ZYv8XzFSkFvxzjPEgpp8c2KhXDjIadrAQfGh4DHA9G4ShdW9l/iGwA6hg5LeRNzxrzsTUV5TKDe0WZSbef6InTL2JDN8abz3cowKazwsNlmwK+ntnaWYSsfDj2h7uYcG119CPecfzxSqR9FUQes0L3vSKS60mG/TS4IC7sp8p9V7OSYzMYASgwT/XzOY7UcIYpAzZJye7IBKuDoecTiOfX0eU/lo+c8IYzB8PM0iepvpPM9MEwcWrk3zJDQdvzHHqAQS9YqipbeNUxypQR/uspn0S7/NMJ20r93MLJW9/Nw3oddYHcc7GcTtRg5D5mWbh4iC5TW3Vuv2U8RuhNSF2Go1Wuy7TzyCGF2uzQXjbEu4VFH9IQM7pYSTkx12J7vHl7vSSiut9BgiIrxw9gKeP30ef/L2n7y/vEDY5i22ebveGFlppZVWWmklpQ9yrd0NO3z6mU/j5u7mB8TdSit9nMhOw/BoWCLAsO6VN8nFokFx2K0aenDANCMZniBhV6obeHAtqFwxlhG1FhyP4lW21towUUD4tHNn7vEGv1Sj6ePBZH/oHnE1Qhoykh3eh7rJ3S0LnwAUru6V+jrRPFJuU2I0uU/SN7zPHvWoSl8d6tqt1TtgyA4+EhYZUizYwyRM2GfqMR/A8OaAsRqoGrN3KLRhu912Z9qOs3ZtCdvluoi3G7t9xrEG7RLRREYLNOUDCPWeejsION+1GHJfzesLnLUN94nCuU/X/6xd5gKb5NNCwc8O/EMr+pOkWKhi5ddiyPp5SgmbYQDXijtvvY1hd4JSyhNgyBw46DOd4ogLqKwmXah4V5kA5McEcYJ4HD2qiKnsHfBdopZY2nLy8aycBfkYSPukvENbd0FOs/F47dfKc5gCGHJM1caLrCOGM8PmhdjfqM+1fdwyn5/jzDpsT0v8xyaPZfhcFR5Nf9qfRBiGAcOwGnqstNJK75+ePnSL3rbnpJOlWjx3se2g3iWIkHJGygNOz85wcnKCzXbAZrvBZthgu91iyNk9d5hikXQFqFW8PnAtOB5H3HlwD8fDEfv7F6ilgGsRa+xRFPeiIVzCvf22mIQ1kOPKRQRGReV2X7+a6wYQzITZWKwAkBPOn72J7XaLRIPcOHdDBPVUQQBXxt137+Dhw0scj3tX4MO1/5BpW8nEKKbxXovUr9aqVoxav+oqlOpq5LI3owRbRBiEovHSzEODLYZjKSiFsd1mbIaEWtHC3Vh8QPKSYKstO9sMWLRC9R5RiqQcfCOjmxjPIWnEHCmnSb8PJ8GT1dDkovu1Jj8iZLPqh/TTPAxgZpTxKBxqOIVStF+5Im15m9WrKQrWj8yARIXKaaKlhC0HpcYxATkPUm9b9EnCWFQ1dKFYL3DzYkAJveFC2DxxK7PTJdDG4fyrXmFhhM2c3TwwNUkVUfPwUJlDXj2ZRwO5Q0FArdgMGdvdgDIyxqMYaVWWEE0py8b87OwEQMW3vvlDjGNBGQuatIFwdaBXvNWdC/mAm2tbLc7njNvWvr6ZQtdeS181BVnarJoBlO+Pwofarm2bs8Qhh39la9G762zP3ZBFOzvHCyYUNmC0vCWf7p9ndSMLL7pg/HONVdqyMjz5LgjTpaGyqtbTMiET+/w222TaDwaqzhDzW0E27qbPJ1q0G5bpF11A4Ol3BMzyC++v2XwxgLPzM/zGX/g1PHtrBXdXWmmlnyx64ewF/Dc//9/ILePNest4pZVWWmmllVZaaaUPn/pw2A2Y9a25b90FH5MLghCjjs0GOSeknJBTRs7ZvQX3ZUDhuoaf1FJxedhLSJb9Qb3BKj5V1QOvXS5zHCBs96k/ZG24gxQmOAw7TAjqw8x2+BIRtrsdcs4g8Ynbnwn6YSRwdXWF4/6IUkfHYVtCxV+62z/kEIanrOoB1+Th8rHDzlBJTOshz/2okrXe1MqsKrucE3JCf8lPP+ox5CbDdtmvr5c52LXzgPllUwfgJufb3OFePP0qtoN9pxiyYMSKo4PUEMcMf8LZRFdgw4qp6zDcvSbFDfsLml0uXq1oYGTGQG1ckOPmTQ7osE3rY60PWF+ceA/B9HA7onARWI44WuPDjD3iOYsnC+OSp/KatGIDU6VuOSXknMB6FuFfkV0qTNhsBgCMt9++hwMN+JX//rdBKWN3dtoMGbQf9NioD95pLbu69R1kQSbTqvSw5zU561xhcpsmC4ODJ3nPsgvzkc9CE2MPHwYMMZ4B3GCNI5fWRxc47jIi6vkKrx1DnsG4PSY9GyKLhYYXbXi1iFI2jxAhJTvviuNq0m7Ti7Ucfga+FmqFWQP1A3X5k0VhxoKXiRnYbDf4xCdewe5ke226lVZaaaUnpafw6GE/VIm0A7fpTXQ7LCdxoZc3GWnI2J7scHJ+it1ui91ui0QJQxrCIg/EyZmZxZiDxc3e8XjE5eUljocDLh4+RB0LoJ4+TH/yxUoPyT3LhXl/VrF4GBkXjYkqxJC6b7ZbbLbbcOBsfLesmBn7/R6Xl5eAW5mGm+iBJ3+mK795f0BUDrV+cug7dSvX16lZZreFxXUfW4NYFvsalKlmYGIKiVDym/fkMu8rjomMLT9q7WtW0e7yI9Q8KBqx2lYfOzvu1ENvYt0QplZvCjwXmILbKt6zz53MmrDsDXsTtGfztJJH1CwneUZFPSrc0XNAMKqIHdfbpNu89Ixca8zrbbmgpOprmj7rPm0mB0tDiayeDKAy0kZuW4AratENBsu4STlh2AzYbLc4Hva4c+ehutF8AuvV0PHEuGnhsL6zrvfBHNo+dJBFRT7KwbzPTNkwHvr2cIOrmAUW+ss0wSNMm03yfTiVpoBerza2fuR8xJsBlhPNGb7Ou0jHaqxcrHebeLpa2CPtTvCxkcTwqbnV406m1ue5e0iPEtms3H5y8sm5vY8bg2uGyPzlMgN5GPDSSy/gueeffRIGV1pppZWemDJlbNIGhUswTn48EQhDGnBjewOfvfXZ9ZbxSiuttNJKK11D73etHdJT36NaaaWPL113KDZ95lAN6UGehGTJmwHDRm46DznDQj3A0gJwtMVg01oVomCUWjEeR5Q64qheoaPHB8QcGjiHyZv5Yz+/ixjCBDjqcCl5nbMYqsxCHIdf5KLaiOM4epjoacThqfxo8ncDx3t8XRIvAbmxESaFdKCz1JEJHnJ8Xm6rLyn25Bf1YtppxWNWE9zOMGSOGHKHBc/ZjTVrxVKzXwguA6Z2SJ3A3YIIEzJ5Au2iU3gGduOaJV6iYGkKGi/2NUK7BDflJOCTHxiGbGmvAd6mbThLFq+tLQ98Fxmze4WugHrzVcycyHHklDNqGXF1dQCQ8PzPfdqZuLYacUjqv7O0074LhDadJKDw3mS7IAuHmmd9vWeN5gzOf+8/eESC8C6GlYkQ8CMx5JazeebgTg5LJdv7BeB8Yeq8dg0AGmDs47/5WBKe9VLzZG5Y7MM8HRfAYyveM2OZTDJdyIAelfljCiTxUnN2forT05PHMbfSSiut9Fh6ip2oLot+juengu4JgYiwO9li2Ay4ceMcJ7sd8naDlAexvM5ZLX6TKuntUNCmxTqOuNhf4bDf4867d1BK9Rvf++NBLIeLKVBJDCKqTPCFGVwZKeti4OEMZbUQt/z6XhetMo5hQbI6EojEWtQsvcciE/AwbDDkjdYnuTxkz8D+P5hRSkEdC+o4gqosFKyeMponBFFcWF0Jyt+AHZqDyN2ZJQT3cYAamTBKqSDIzXwiCY0DQCzWVcPw9VL+lCe6dqUkX5fCuLoaZWMVLCbMQIU8J6kHETwtWVuAYGFhWNOBoWfybfFzFZRaKJm2wVIPLVWsmc2iudb+YFo8TrTF17yFMMQry9FDgUiJtVZVBlK/wbENA1vbWD5BaUH49VG6blBK5tQUVk+SSGUm71KI67lciG6WZmVMNVP7U9sB2h9cHoF8M4ygy6gluSktRCCuyyq0jwEGjwwZkBmbYYPzk1Mgb0CbE9RaMB6PqOOIe+/cRSkFXAAgLeww5O8U/yICJp48lvRmRuun8e3Udl1E2RRST11Dglnu4YZBfMvzMCYzHdx2vJP8WBVY8XzSz0VuFBE3gsBEMLFL9vlzZURjL5NMS8rzGJ2tosvduC9asgpF9NvLJaLuJ6UknopqBRdu41HTxPA8rCFUUxbPOR5D91GM6lzrnZyb0MybSjTs80HQbbT6ubcrktpnqIx6GFEP4/X8rLTSSiu9B/q1V34Nn37m0/jam1/D19/6+hN/99L5S/irP/dX8ezJszjdnH6IHK600korrbTSTzeta+1KK32Q1BBEIG7xAyZIQNaQJtvdFkMeZK+fEkgvDzp2HHELg4QBcK04lopxHHF1eSWYrOG46gWaa/gAjraog2pueXM7How4DBmzzOp5OtbRYMAM2MEjszqNEG8EibIfZnsVAj6haLFedGRwrR6+NuLlwmePozt/EUNWfqlOjQMCVkzt26X7OlPcCIYh6zdJ8xlZD+RD+h5hUubUs4CdHTjGYriTVsLk0nuC6WG1dlenee01Dy3mBULqGSsSvrPuEN4xxNtsrHu85LUYhtlhpIAnUUiwGM4j0OMOn/39QsN4W/TYaA/UoYOgYYfV3qZLfETPwmzDo09n/ad1UanrxGqmodET8jaDj8GEhJwI22GQsZQGMOQ8iGvFXse2eWO5zkqFZn8s47TLCHTE6yd9cJouwpaT+WCa+xRavg5DXiwswqf2fXN1MfO4EXtsx9W031zT93ps1JlFm3DR9ZWexwkjk/y7+3aTcjsYeJaiL9gwcXbv+J1wuj5n1Uka/+VR3mb6omNduHveD58gJ7q+BovFGfxcql6AXWmllVZ6f/TUhh6zX80oQJW1YbvBdrfF+Y1znJ+dYtjskIZBDDRqVYWQ2hphSi0zwBV1LDju97i8uMS9u/cwjgV1rH5GKhadKU7vsFAlQctqjHJ/Hgdi2TAQoXD1w+9YKfe8wS1v+z8lMViJyiOAkKYZe9QqCjpqgcez03S+TKUmu+lC25R5+WmhNNyrAYUyASRzHzcz9Ji0pMpKvpW0KVE4NCUJVTM73GwLWlR4qXtPFgsCBELlAtncLar6Wgdq1t5aa9nk1Famy5l7RTZqs96UVreqdWvfdi72IjfUDtkXjFYnNSQXPi9ZVRtjnReG/jcK/4QnbQPZ1PBesUbfL6a5z8gF13Y0Iu+Jsskm98mnrZEWs/cNFCQPLkBNQC2MNCTsdhvQsEM+OcN4HLEH4VAq9pd7vSUVWxdBEtfVablhvEeYcGb6da/oBTumVu+Z0hdJ+4Zv0lpfWfJeQQttI02woPgzmiIa+GWrhzHnP6b9f6Yiw8d3xz/NOjeHfyh2CLKtwfIccm3r8DJL3Z+TLEksxsSzhxrgcfcVhY+Ef2+/tsNfoMncrpPX7MaE5hMNSqy83hWn5hrWGvPqEuenciwoq6HHSiut9AESEeGVG6/g5fOX8cbDN/DNt7+Jep3xpX0DufV4c3sTv/jCL+Jsc/YRcrzSSiuttNJKP120rrUrrfRh0By/cU8DhnPmjDxkbLdbbDcDUpLw3o4TWy5keKRhMYpv1YoyjoI37fdygaRyV6DhjZjiBxRwBuN1CoEQAxqiuYOdO2DcviWAqvxke5UEN1+QRcNsWjgCwWBqz4Ox1+FdU5yOZxEEHC9xXqxMxTtMLn6RaFr5iKlEvKRdnhSgnJwvw5ubQYFzp0l6PIYaTKt1qn2RU2zJRGsYOmrD1BTvajBan8Ecq+L2IhwQN2isfd8j04ZaxoaJpUzLDbKwA4HIyzJM2GGPiDIKv/a4IDvuuIwh95jfFDKb8mDvvNstpJsaGnh+12GrAUO2ZHIcxOLJJ2dQyqDNBrVUFIwozChjaZfYJnk/GkO+ho1JPbo2cNy09fmuqWiptMmTWXtx+y5ivBHfneTBoV1nXa0f+i39IkT6KID22hqEpwFDNnjVZGR9lCbNPsVRl4v0rngti163ab/3ySbg+MbERFDO55SmY/VRGDJ3SWUuDXMihTl1UsHeC0lfkhn31VKWGFxppZVWeip6YkMPmxcpi5I67MSrxfmNUwzDgJxys7JWq+XDcQQoYWPrsCnWCYBaWF9eXuHB/QcYxyMO+z24VIxjQRkLxrGiVna3mUQa3qGGQ1DAlcumeKhnBlCnyBJJmloLKjflIGwdOs1dWJaKDylhs93g2Wdv4mS3EzaKXi+fLNxgYH84YhxHMItnBInxx3GpAQCUIkqpW3e7tbnwJC7xireBfRtLFW8acKto8xrSDky9FTW9Kn21NQlYbskzm/Ix0RqcJXWdptbqReWetLwyFgCENFhcQTN8oYlUpQa2OavBeFH6T4aH4CGJYokknh+agWncrTTJUMrCsmYqHk/0ead59EqBK98EkPLIgcepdTuHv4yFznUgiXWyt1WnH0lZ1nZNd58qKq1qFHJnmB7RNlBmcOWbrT4HywR+iSBsuFrVyZ6EBLHivXeJyLUYvTDG8YhaC8o44rA/IG/22OwOGMcR+6srV2D8cJ3bVq8d8afu774e9if3bdDE6mm5T95KsY7v85LNcQROLV2oePvB3D+Nxi6PINE3bSy1GndGIb3u6ny1nS/N03SlT5XKqOgiNln3S28oZ1XSMbq4k+ip7Tl07mUEbyT+Etaic+8qMj6JZdCwGojJ2Ir9WfufeefJSQqKXmmcf2NuoR19PPP8VVer5izQpmUzjrO1xm6vMBEuLq7we//Pf8Tp6Qn+t//l/3utvFZaaaWV3it9+cUv4/nT5/HNt7+JP37rj69N98qNV/BXPvVXcOvkFrZ5jfm60korrbTSSk9K61q70krvn3x7rZcDs3rq2G43SOrl2S9xkRhCjKVigHjw6Lfx5FjgOI7Y7w+CORUJcVKrXCysJVwkhOBtACaYgOFoDXOxZ9QZJzSkWELCNOCO+8zQLqzB8blEhJQzTk7EUwkCXzNBMTCWot5C2gWYyHo8GERFk59jpAHb4Ybx2bcRCmqX51p9l1Gflq6HXdlx7GvvSoWCyYFIVmcQhrfqBT8O3k6Mnw6OZOeEtXxvY8X2CAmUG7hnz3vhWbXsPMCkkjqsr6oH6+ZReI5F9qS4VewDE6E2AxWT6LwfgbzproXfovftjrdpH78WQ57mtYCNzcrsi5rz8wj5dO8j6EZeblUP55UrSimglJFHGQ/jOLZLrJ5VB/gt5D191/iKRkUTeL59YRhvKHMWQola1dwgY0mEE/H0c86jE0d0Pg7gDgdewocNA14QyeOciDQeaP4Y7ZX0p0kNKJwoLGQR/453EBe7X8fGtAEsjXi5J59HJFPSjt71DJsTwwXqNsNPWJ3WS+eSxmfoAFPDrWAkxPH7SZ1I5XU8jvjhj17HZhjwq78+r+JKK6200tPQExt6JD1ETimBMmGz3WLYDji/eQO73RZDGpCIxANHrbJA16rKdoGFJqAkB3OyUFcc9wc8uP8Ah/0eVxcXahTgpQY1uq0ATKyGe+2A2Qw9usXAFS3zvGCKsmwECG1ybRNwpz1AXktIjc2QcXqyw3a7BVg9QOgc3lvLMsZScDyOuh4Y7/HWuC48VYpKKlsz0NCS4YYfBD/Id29QvnkxRa8pI70ce2XKjHbYD+1lIazmWcMOa7uVtvFEIFCWs9bKVQzcWb2YFAaIxbuIH4SiW2T7PE1BN37F8CFRCBvCrK4bg7EIh3bWunTy8M2Bum0EkJNnh7ZRaHIS7zSRP3JFuFZRLAi9NGNaq9NUn+n0ANOuw4Y2fi56gQVciQpPML6IijIHPaLfF020JZ4wbjIK4yZoJ+Zir7eJWa65F8P6TRGZl7HieBgxbAqK3rLYX+07JqMVbi/H+PdEcQ8GWv5G5wWLENRXh8LFhKDKLZmeB11t2UBggb0lxdDI56LGVxdbtN9OzPREybcp6BNJ9EXNB9iygu/TxSM25RyTNjeV3Y2awI+UH92yUle9qOBS+KVjSw28yqJ1PrrEzDUYgrV5tL3HZCy3puJJOnvZt2LrXbEHmtGgtkqbo3Re3B+P+O73/xybzRqfe6WVVvrgiYjw6o1X8eqNV3Fvfw/fePsb8Jt/E7q5vYlfevGXsBt2oMVVY6WVVlpppZVWmtJ1a61RXHPjWgvALygBujt4/InKSit9bMkuj9hFs5Qz0pCw2W0xZLkoKF6A5ZCu4ZjqGdnQyriRZ6CMBYfDXi4HHo7oD9QMX1rAkBWjEChmojtH3AaAGRJ0uF7EQvpTQXShgx2XI+REcjEy5x6LnGTCkPmjluroQrvUFcFUuUQHxRUdoeS+zp3HjljSFCOOeA3PxeI1ibiH8a6elN3L7yKG3OoYL8c1wFaxHMP4Z1NmrJP+G72wsOBrDWJtmKFdGvTDfZ7k22HIUQ7KZfSKEQGt8GcXssalhQ5LnfeXa8jxb+ohPBfBdUh0u5w4RaKvg/umSZuX9GmiaWEBUJtgyN661/ShRR5MnjruUYARI3LOMi/UqpdJ2TsQ8yTEBU1x/IVKGobci6fNL4YNB7l3ELj3/4W6NGj90emmH/m/YTxMk/Dim8hh/ydNsconwJBnHbifb6JQDF6+lqxrMGl4mQl+Gv6W6TjMsRPcOvLm5yhTdrWi3PVJDq9jBbmV4ULlxZQzCvNfeBA6kOVvVeuNPJpJCc0KKbXi3Tv3kHPCSiuttNL7pSc+jXrh5edBRNidbJFSRt4MoJSw2QxIlNwie1D3HWLsIcpVZUYZjyil4OryCpeXezFeqIzDYY+ry0uUWuQwvSNTA20SFQ8aydzmzQ5iWbxUuFLeNHUzaWBTjEMJ/rUbRwT3/mxhRwhECcN2AxoSDsc9qCRsNluY9bBlWGvFg7v3cXV5hfF4AMBikZ4AVKjCwm3BU2tt8TwBcVPomxs0wwXL3/hJotCm1PIxnkHQoIlBD6Nm5GF1bta3ZMkn4mdVnFSWqiunIYFrxTiqsqWxL91gvhZE6wMzzp5HyiG3WyBM1jy2H6w39s34Y6L12rctRovIkwGwHB5r6V3GREnqVtsmjiBGHXKQLGVVvSHgFvMTLdLiFoKiNw9qbcdaNpPIZ2Kd70nAoU2assjuHmGqWHDPC/fCZXP3yKG+mCafb0zMxIRrLNE0rKDQLB4uTTuY9PdxLODKyEPqeLKNgO9LJtpo7NJdGWgGRM4ziwS7zVj4g2L+k6pMWHoMRc2w3xj659xadKJr9op62Fwwloqet0583ummCJse7bu0+FUMfdL64BJxV7k662M9f0uC4xmP0kVomsyHdkoJQG7GNmHfY3kxQ1w7koZ3MoOPNtkt1cQK16HDTeghufYuz4ftbx36DYCYr1fj8Yi333hX67DSSiut9OHRF57/Ak6HU3z3znfxn978T7P3bz58E//kO/8EL5+/jL/0yb+03jReaaWVVlpppackW2uNvn/3+/ijN/7I98C21qbJPvvZ3bP4y5/6y2sol5V+pun0/AxEhDxkmNdnECG7Nw/BdZPiho7H2h68jqiVMR5HHMfR9+6ljBiPR8FVGyA0ARQNE2PFQKeADTmGZyBDxGgiZjH1lMwhjWNQk/PEhuGKVw9KhLGOICbknBtOpOmZGYerA8bjiFoLmhGH4VyGdfQAUrvtr7zaJcHJgaL7wzCYw98o+hGylTrb24hDzvyyhjp3yDoa5hRKysJzLe0b8yhtcp5n3ZuOtJfqfSVNgKZolDfBkjogLob0DuU7RhovZwVAq/eAEi46NUBTeNY2hRozzYj1a7v05sKPRguCA/e45QS8shID/sUc010DbsYygjzgfT3inDTJrgNiNT8OZYesaSn9FOBr/Lz9/R/i9W98C8//3Kfwc7/+FQDm6UXa9uG77+L7f/hHGA8HMAOnN2/iM3/x17E9PcWcaPI7O8be43kLc4Mn7PPz9l7EqSflzppggs56v+yB6UdjyGzd4prWvQbYDf2ma4JZPRX0fETOcThdS9N2776gRdH3Gfb9y4y5lgqVogh+UdwnLxFUh0dTfy7QX36kZR4Cv9fd2STlsV027xm8jncAqKXg4uHVahi80korfSD0xIYeN5+9ASLC2fmZHpzLJCQutiAKTCIkiLJeagWpoUKtjHEcMR4PePDgAe7euSeGDgUAVzCPep5HqghhsuCYgg0A0Qijtkk1vOd+TegsjE3p0pQwpRYzxSjOw+z5uJJejiBOGDYDyD2PSJ7MjKuLS1xeXECMC9rmgj0VfNNhmxowAynJRiduWjp9gNCtEASVeKsDBeWfrX5oYROn2XrmvsjZpkG/88Ve/07iHaPCXCqyxq+NGwMWN162iWvszlQGsZ2IZVv5qiy7stkOddvBbmuw1s4clHR0/aVbw6O8ggVM5eYBhjw/TZJiXzLJaXoOirBtbkDBepzd2CJuFaMi3QmFeaJjtTYgNJnNrMxjw8ZbB7FHz4ykel6i/Nx4gvpWbAqT8Mlu2BPCkZgR01hUfmmi9kg5VSL+tGHf1YV68VCTWJwmWLny3qZjbkkekdwofVFJ7yUzt8CdbzzdG0vga6qySZm2uZmYyzyNghf6Bmte9nfcvPm2ZsHafcnVoku4v9owL/YadqZzS7wL46NjtvFpYyxRlrWltMwozO3Vo2ax982wbenrZxnb31puZ2RF7Z3nRKFtwxzW7w77kTyOBffvPphJYKWVVlrp/dCSm+dXzl/BK+ev4FiP+OM3/xiTlQR393fxH17/D/jsrc/i11/5dWzS5gPhZQUhVlpppZVW+jjRYigFJVtrjYgIX3vza/6NrbVL3/3aK7/WGYm8F1rX3JV+mml3sgVA2G43oS9Hgw4AZFfmyHE8QMZlqYxaCg7HA64u94KbONBSG34YfiwhEswNx0P0BhCwCIM7ZrfPHaNcAC9aCXBjj/Csxy5JvCGjYeYdEyyXRsbj0cswHIMbcz3mqg/sQh9HkGU2dfQPOmjP0CKGe0qmLl2sf19Hx7g7w5MFLxckeLRgi3bZS/H4CGhqBXvziB5PivwHP90B2DFwz2RLHTZocuvxrh6VbWKJYFWUI084bEVG78zxkx5DBoAqxipdWaE+lgvZDc5Y/hI1LDZebkXsEtMuzN2nk4f6YrHrz/lwwxp738mL4Gccjt8DHU5HwMO3b+P7f/THYACf+pVfQsqp4ZVE2D98iD//4z/B4fISXIFnXnkRn/61Xwadnc6GfneRL7BrouaQaB4OR59NGy0210wCk7KmP/09oW8Ue9Hy7HBtz8YuLbN360mCR9AUBEbfrku8Bh7nRV0/F/oHE5B9lpr65/PZZZL0uvrpS9IyOV6SDd5JzKZMmqCNfaIpZwvj0IFjzSNYbsSuY3EEbO4myy6h70uhrFqBw9XhmsqttNJKKz0dPbGhx253IhOVLkpxEbcJtZYqnhcq42p/hePxiONhxHgcUUpBHQv26mIPlVXHji7NdIZMcQZnpNTP6HZrvYYJ2xRc13DDmsKQGZ2SLkemJ1UNyUG2x4g33ZtBSBoydqen2Oy2slBQwjBsYHEk7dSSK3B1ucfxcEApI2qtcD8iypNZnYtRavMCYss614rC1fnpV8Opktk/NQOP6ibSCX1ojIkl+szcdjnj6DqRAIxMKOoFoxatH6kXEuU95+T7AQ5KiG3eqgrarPndEwFPqhwURN9k+IJMHefWlv6lKw7eEToNobIdgOtGoxqfcrtALVDARUIQUbLUE01N25Vsk9qJUlOnVqbIQZKYNxZTMlvdCUASuUwUynjo3IJqwJUprq0+Swf7ZmDkbFLPG5BkE5al8Zo3F1N2QiNFd4bmIaUXto4rrVttdZG0CSkRdtsBzMDxMMoY6eqL5vbNNzcyhmyjX3XTnyionG7IYy0VNDvnsU/R/72UbqIFuzjmSlsPzC28t7oFcc30arD3yUcS6ei0TWCcC6+ty+RZ56KP0Fz8mMFRNFp6FE/Rxeo8nQMVNn/Gcl0GYkRWg3y96WMbaP2SurmrNbX2mFV1md/uqQ2M0BZtnpnIcjJ/+kim1ZvHSiut9MHTN29/E9+7873Z89cfvL64Bhm9c/kO/vn3/jmG9P5CSiVK+OWXfhmffubT7yuflVZaaaWVVvpJIgbjG299Az+494PHpn3r4VuPNAwxun+4j3/5n/+lh3R5WiIQvvzil/Hzt37+PX2/0ko/CZTzEEGBhgOgbeslZIvs3Y9lRC0FpWgIE67iRbgUwSO5z6OnHt+Y2UhNcLjZpbAJEGln7vECkz23A0Mv2XGndrGPkmDGKWdPl5Lgsw1DFmzuOBYJd15rm1/CPOO+oA3zaRzLz8oamqZ/P5PNEsxleIuXa9gfh0SRkylZRRYedXUAuBgerE8MczdMxy7VTUs1XMxqQ4FHS3w9NDWTQQsrQTP7letRN2t/61t28a0DjtpPPRehRMuZWnez1x0f3PKxs4RrKVzAU7lML/XNDCoihmy56BhkzafHyBqvxp5j7UG+BBIPKxPc3ToZM/DGN7+NO3/+Ol754i/ghc98Ct0gY8YLP/9pfOVv/nXcfOmFcGGzZXX+3C186a//V6ilIKWE7ekptqenaGHeJ0VPf7e/a8WP/kR4efVLX8ALP/cp8CTJTOqPgWSdvH+Hj6wOj8Ume5nN3/MMQ15m4VGDYsJCMKR5crI+OmGz6yPUT6sTKL3Lih4TOoVDF1+QjTzpzyL6i9NhnlJPH34cx/G5ZRh7U5uvW5aPwZbjuhLZtXJ8PoEamjyN7FdaaaWVrqcnRn23uxPIrFT14F+eNy8K8rweR3ApuLq4wNX+CpcPr3B1uZdDdDOqSPp7bepatPAG4hkd9YsBi/cImehNMdTXqhi2+Zn7nEgOgu2pW4tbismhuC8WKUscye3W9ZCch6ZgKh+VKw77A/b7PUopsDiTZrk69TJhB9WdRwKVYyIJUdNZcBtHS4pKrA9byJfUlLpJXSNfUT6WiLu2qLAGZxDAJH92C7qm1av24pYRKMV4kmR2IG9GBXI+a4snd+0iH+p2Jc12U6o3NYXb+4Iu2IlMpsYrdV4E2P4LvEmIHts4TDYZboihSpC3mynXanfb6R3Kt8tnSUlvET1j6Alr9n5Ds6ynhtK6fmbdZho3s+neOiABiPuENg6sNPKyqVk+m5U9ob0nEncvsUNbaazjkiFtmqzVxXXnbreDeP6oTc5BhqK4N2G4lxitq+cd5BQl5FvuRR0quFzshNrGTSfMxynB1tc8L568syTsOudkiHeZmXFLU2qnfAZy44m+yHktOk15Mse2VG3PJXWmzhgpDIMFwXIvBZepZT+zGzJWtG2rzpG1a/dYGXaZGZ8+v9eJzF25D/UHJrJuzb60/1poGn/Rxj/cxmallVZa6UkOg56Uvnfne/jqD7/61N/d29/Dv3/t37/v8hMlvHD6Aj5181PvO6/1hvJKK6200krvlT7ItdXy+86738Ef/OgPPrA8L44X+MPX//A9f08gPHvyLD7z7Gc+MJ7WtXelj5qGweDm/qKgbJgNn5FLZVyreLQYjxgPo4T+dTAPbTPOSxhyJAMIIj7RPAlMPUM4BsHhYDBu9AMu1jCqHk/rMGRWdIkIachIQ3a8IlFCxL1ZcypjkYuCHA71Hb9l+G2bcABvxiaeyvAaw1a7emAij1B3ntfZcacJhmx/LGLIUSpkCKn9L4BJ7/HBBQgLm+3ejydgZsRaVeR9HTvYrtVzCTcniDi79uYmH8O3Wn7kLeX4Jseewp1X2A5DdgwqYG4uOm4ycWxz8s0Mk5wiv4/8df7J0mPLPjZNkIfnGdddAsIpeXts2L7JcsITE+P2936AH/zH/4SzW8/gpc9+Gh2YB+DWq6/g1quvNOSufQwQ4/SZZ/DZv/DroEQ6vzCOh4L5pT7LtuutnZxuf/f7+MEf/THObj2DFz7zqYmoFPucgYCBJgY13dDrSgKWAcLQNyIgCixiyAhJyGrG07lu+sHjnhrrcyw38rgweyxgyNN37N2hw3u75IRoVDbzYxIw5A6jnUwlPraBCUaNvtX9Yh/P1o9F6N/bb1r5R9BS2lhpNQ5rc7euZauKttJKK30A9MSGHm1eCsoyS0iWWisuLx7ieDyijgW1VBzHI0opGMeqK35RBY4ASvJosiCIQsWoI3dGGU1RUyWg2IE0+kvr3HQhz9oNABiMhGpu4rQsP9SOB/FBmU8krgafffYmNpsNdrutK+h2+O0KRK24f/8Bri7Fm4mE/4ArTy2AgvBQGM6by5lIHfkFLcEXXl32KLwDmmGHP5PD9naxvFdtgs4a8m0y6Vsk9oCln+ysEuxmPaHU5hKx0+dV3jnkUavwQURuxd4pYRz1nCoWl3bbH62PyJrNYkAUeIoLJts/5NuE7sB5Wl37tDIjhZfkdVG3B5W9HzXPMiEPF9ukTX1v0YxFrFauvCnP1l87RW6iBRHg1szq0MM92bTic6dYNQVH6kLecTh8Q/6756b9O6UkZcjQRlWjLu4Gp9ZZ2z8N4jUkJfHoYRYj292AWivGsQYjKAJD3FzOlUvdeAXrW0nnWwPlPcG8inSbwKU9k6cJE8pUcQ3XOMJICMqbxxaZZz5Rm7vnPE1pz2rzcjIxiuuz5/Cj34Ta4xCGFlHZnbornHmws5c0VZin/D9aSZU+2iRTvbXsPXtfYe1vMp1Eg5224QCLNx/rHdN1QcXX1c3mITcCmxi9eRW0gPncKM9bmiifVUlfaaWVhO4f7uNrb3wN+7J/33n94O7jbxp/mMTM+Obtb+Lu/u57zuP50+fxlZe+gk3+YMLIrLTSSiut9LNHty9v4+tvfR1jHT+Q/JgZr91/7QPJ64MiBuPbt7+Ni+PF+87r5vYmfvWVX8XJcPIBcLbSSk9JEXzUfXUtRbDk47FdkKuMWqv+r3iXXoJzfM0PDvvNNjtWZpjAFC+zjf/88Lk/GG4ggmNz7tWU3cusZen3x7sDRcU7c8bJyQ4pJQxDhnvyIEujeAYzDoc9xqN4M/HCnRVqefMUz3LGQzCYKJuG9RKlTiwN2wjfGYZsoJHVJ4rJZMyePeaIUyw/Pp5JX56Iu2u5DOj5hkt2WscgCYfjCObBQtrKvu0L4AnUFs8ZDDQKHiEm+HC8FhbQ58diyOws9f2xRzVbOPeW3yxF+3YSkoUDIGUGJ1338EoF+cwwZG5t6V004eE77+JH3/iW98uTmzfwya98GcN229d/wYgoeuOw+qWU8MoXv4CzZ5/B85/+lPTJgN2xg5WhT1LLQ8KAI+Db8j4P4l281tATGe61ZQnXJEp49ctfwNmtZ/Hcpz/ZSTxOWVbPJfvSizt38aNvfAvlKLrI7sY5PvmVL2Gz2zV5zEUTnoc03S+EzlNMnyhmgNaxFwoKmHWH0U6TTv6ehXnn9qNLy60Ks7FwDc2q1HmVnlfBH4fqOi+zSmhv9jkgMDrhjadtOp+auuZYTKd9bHZK0cD2haa5DkPGSiuttNIHQk/lx7mpiYCcnDGOxyPGccTdd+/i6vISpZgyHq2V4zRnSgq1hTN4IGBmlKIWvTlag4jRhaRRTmyGtCxtE+DM9p4BuFZXjE3Np/DTY0Iqm5QIlAib7QbPPHsTOWcPEQAOC6CbU1c8eHCBi4cXIEgIk5RMMQgrCaO31kZbIJPXkxbmftLb7sml6TaPpiiwKX/xNr7Jo7WHHHpHe+/gQq9vcMxXHZq8hyuHlDMARhnlhbvfC1qze2OAtSX8mdXJCwgiDoJXpZlgFkOmPBLDPb4gN5lEJUo8lAS5PyrSgrYze1WjDFXOiZFQVUntPYKIWFq/p2SdS/Op5lekV6iot24J7ITNazAmsfLIKlXZf4/jkCikm7RtTmZeMlGsu1SRtP+khJzFkEI214yiA407HiWjlBOGjRh4DEm91mhum10G1wSuRzEY8WFDYZzRTNGMXizI69UMmGy35n3MBkXX5+OA0RmLJwJog2nSBLJB4vh97HePo04xtrJDkVE5DVPoVLMmd19JiKYLkea2XFaRNmfMufbOHKbc1q+jGL0143SPJg5juxkQtXnRX/ocDHAhTyftHOYq9S6kjoSQlsQ9FUJnbGXju5tNtRamhDfjwCaN1kdmEnvCJl9ppZU+/nRvfw9f/eFXcf9w/8fNyvsmBuNbt7+Fb93+1nvO4/PPfR5feuFLq6HHSiuttNJK75neuXwH/+b7/+YDMaL8SabvvPsdfOfd77zvfF698Sp+8YVfXA09VvroyQ7yDMvRh2bQcXV5hXE8yiUhsOCccS/dYSQwsCtkHorS8MWpu+xm2GrzSN1hKf2jkCs7dsrmOpapOzel+IXBGYZxECHnJJcE0wQXnxpYMOOwP+J4PMLwq+Y5Gh14I5hEwAzDT0N2J1Lxsv3A2ni20/UGwgbhcMuY+/wc1zSPLGQ8LmHGDVufHWp3kKNYl7jXcPRJG95rLwjx5NfYn0Jv3v3sr3AhsOsIEZtP8V1kxCXXd8NZmoh/euU7qTTstmHD7XnAGyeydjAtwGdzwI/DT5OPXVRcaqdWIff6q0U9fPcOvvN7/w/K4QAAuPWJV/HKL/6CGjJouuihe1Zf7WeGDxLhlS98Dq984XN6WTDKkttQin3KRURIWS8NUjsPAYCUScenhbCfIJUBk3bnOCnhlS98Hi9/4fMBJTbMsROMvPKw1q2Ey7v38Ge/9wc4Xl0BAJ55+UW88oXPdfLxuvl4IINeW96zNsNiM81ocXzqbxx/oYYTL0yw3r86r0Yhzymmz9auAHeh3K9hsMOQr+Nf8lzEkPWP/j7dJDfHkOMYZM12giHre5PRYyH7jgl43mJI1GPIi20ATNr52gJWWmmlld43PbGhx8Orh2JtfHUQxXwcwVWtsKuELClFLLFFw5aZXJQ1XSzt0F+9HzTTTUljE2HOogSkZK7boAu6TpyZZEHRCZEht/9pcsrHptQHPdUVDVMYoGWrJ4+WBWEYMnZnpzg5PVFDBA1ZEhayWvSQsDJKrSCuSJOp3n5Gt1/dgTvgBia24FdmVK2360buHa2CwWrpjuaZxHJzOaNbL6aLtnlnaJbi8wXGFfjp0uX/8PyzoAtUVSxSXJ1j/pOr9hT+DyW0tguLs6zjobCJgkFB1gztasFi1DZKGbL58lA7QRlhJjFIgHqeCJulZuiDJvugjMbbAL2HCXaLe1c0lc8ayicQlva6/k4VXmu/piQDSITk/Z78wy5N906VNADu0cM2hf5TvtCoPBiPI8pYsd0O2J5skRNCOCLpv6UyjocR+6sDhk3CyekG290WN2+eoxl5MUZ1b8O1Sgik3RG1ynNmoKqnl1oqKsPBAFbTb+snraFtbGBOOl7MYrw3+O+1PYoC075mRiJmaOb9QdueWDeqUQ0Nw4u13j77WJ80YycOfasx7RzKTYu+D3qsxut0x1CNfhBrPYMszMSBpp0FUSbsc3v/PtZr8nVQbhlyYyNRP0nRQpaUCIltZ1V1M9Hf8LCQUezIjvLPPNlE6TMdC+xW/xPFmk1pRxOqjTt2IQQxtrGSiKbT3EorrfRTSMyM7935Hn5474fvOY97+3sf+4Oop6E7V3fw1R9+FUN6su3HJm/w5Re/jFsntz5cxlZaaaWVVvpIqHLFt29/G28+fPM953H78vYH5s3jZ4EeHh7i9//899+zoQcR4fPPfR6fvPnJD5izlT7udChHgCU0iYdoYXZsp5TiBhoA5od0aNhDhEMiBhkP6xwTDbCEo4waYbjhcsFlfiQHbicPZ3nCMuz2/ikR8maDYbNxjLCzgyB0OEpV3KFHj+19KNfZiABvw1Yo1Knj0dHIhh07613e1JKDHEydIMiNpQ5kmWK89oZmVfAb/Io/LX3YNXVfmZZHSLkEvfQYcsNzvFgKqWLbTqpj4kAo0h1jWNahvzrWRJNQPV3dOGS8xDwvAGNRrvp3wHGjFRJpH3vzz76L+2+97XJ84bM/h+c++SoAiiLxCjLF3kU4f/4WPv9X/iJ4HAECTp65iWG3nY+ZyJ1dPp3U2w7paxGPPTkn5CF35x3Wf5mBUirKWJAGwjBI2u1uG4Y/q9df9suTw5B1fgljQfHmBhFHjC8YRnHoBDyRPE3xVnl79uwz+Nxf/g3U8QgwsLt54xr5kM+Db3zrO7i8d8/fxK5DAF743M/j2VdfDqJTDHoC9nIQrGHInSVay739Omu2a8b4DOONj8McbbhwLNYwZA6/A3quxGHemJZH3djyt2Ge8EvCS5WZTiVWtvPY5jSfE3k6705H2CR/Y5WvwZA7eXcDDM0KMFxGp1b6GlpvpZVW+qDoiQ097l8+RC0FD+8+RDmOKIcjuFQ/HDcFh2DzOTelnU3xTnpoyzrPBTdHDIAlPIN4B/CcZFEgNGOBLK65UOGLtib0vKIXhmZg0TtV8jWoyqYjJbESNcVnGDa4cfMcu5MTtRqlVp+sCkg1619GKQxiRtJVgNq60tYELdOMLOxYshRV8plRSfylFJZ4f5kAJAtIwWiuDfuFPg9auyS7GBYNZ3YobKIiWPiCoOiZC0GXvj6PGohXiF2ZmPoHIT3xL6p85ZzaRif8Q0G5NwWBOhcbpnwkkIbfgBr2tP1dbW1PaO4GjW9VfgqJPNRew10DUpbDWfNCYcWaEpfMetitgKSudiDfFua4I5goB0FBaXzZ+t76rcnf3FPaBoKmWc0MZuJvosT0ewOC9cmYNMaCc4ePpF5XKDXlw58RcpbHtVYx9NgNOL+xw5CS31ggkvA9Yym4eHiFw/6AzTbhmWe3OD8/xysvvwwwcDyOKKXicCU3OYoaehyLGJTtD9LPi7r3PBwKSqm6QZD5x1z0VYYY/tQ2JxEBtWsKM/LgYGemm5GoYXexf0xe8gF1gu3dwbhCaZsI6x/aJj5VdZsK6xDtTXfTI5bXoQShr4Ys4qzQNTYmf9oYtD+MZxv9NHEAGrR3kW8w0uo1+8eTFld9VxAV78AmEZCATBnV5zz2sSE8qNEJkWxO41gknsWElPJtAxhF0jts7IxtTC+3fGKG4R2ReMZZaaWVPh70rdvfwu/+8Hd/3Gx8bOidy3fwL/7zv3ji9KfDKV45f2U19FhppZVW+phQ5Yqvv/V1/Mc3/uOPm5WfGbp/uI9/84N/856/JxC2v7hdDT1Wemo6HA+C4Vwe5EJPKbCDV2B+FiY0v6jHXdqI2cD+QUr9bt5hsYhTWFiIiCGHvKJH1HghC62YxqUyRTDsU5IkkgPpYRh6XMJgHMOqFcARDKtHYOO/jiEjYA6atLIdVsohvSKl3YW3TqaTenPAiv0Q0i4SxTAonVgnWAeHMDQd11N4h6/5PSCZhs8Z/yEEdf8Fz75dxqEiRtujZDQxpogYcjyEtVDKXS4sl1BFPKGFAoZMoBauPnAzgZhaggjoXQcnRShwihA7rmv5VbzxJ9/CD7/2DU1O+KX819TQw5u7y88/VzZuPP88vvjXfnOCBcYxFV4QFMcnh0jbhUFygw45x5Hzgc0u6yWpZqBlIViOhxGlFKRM2J1kbLZb3Dg/FxxfwzuVsQquxzJySy1qQNYuCwJiNFKrGXywjoPQi/ySF/X9fSIfw5ANDz177ha++F//v7rmifXuAF8i1HHE9//D13D7+8uXSIgSfnm3xbOvvjzB9xcEPzlv8DuxC59dhyEv02Rsxn4S59wJLz5fRgOfaX+NE/kShvwEMCpHmV6LIesIVNx/yYuSTdgC+9OMlUX5MPePefItgCmG7L8s1LV7vULIK6200gdET2zocXH3gXjwuBIDj6reO9qi3RQKU15tMWRmWfL9NvxknQBkgjRPAmhWl03hIFSz5Ku2OPPsoDzo+t2cz/4vdTwT0NyzuSIuB/+bYcDp6Rm2m007ELcCqil8cuD84PIKh8NBwoaoBscVYlXQ6c5BeQZ11sCmZ7LlHddPW4tMefQDzWa17TYKdgDrDyaLLYR9c3imZ+NieEPw7U20VrXPgSY32UiYxCg2v7dd8m6hrq1mFpxB4QubAzcWYOtnFg8xLK6uDLd+BWbnKenqafbr7uHCFc7mFYLN6ndx0zFpwynzVof5Y/Q6xSSMCmSD4COChEfbV7jRAHrFw/oLuryictSMT2zsiIFGlmdJ0ndj13SkcFCesn2XxNglZTWGEpcet998F/eOI26cn+HFF24hBT4JjLEyxlKAAtynh0iUkdMO4Iz9lVg9j2ORmx1VvHUcDkcwGCkn5JyxOxfDkZxk0+BKO5snkCNqrTiOBaUyoMr9OBaUUlBKuzHSlHvdQGgeRcebWn04mYFIvPVhSj14PjJ6XdbmGk3B6C3kOaRngvmpNE8j0QCOvEXnHcw2Kr77cqZqS3ed0jhRSsNk3Oc/+2whw8DCUpax3iZNAoLhfAhBNS+xVUUHBpvBR59E+pJvFHU+t3l3wl7Pami1bmFa4qSvm9XGp2rPZKWVVvpJokM54Fu3v4WHh4dPlJ7BeP3B6x8yVys9isY64htvf+M93fx+9car+Myzn1les1ZaaaWVVnpf9ODwAN++/W0cyuGpvqtc8dbFWx8SVyt9GMQQD2dL+8Lr6LnT5/ALz/0CcsofImcr/aTT8UoMParcamvYRdjfC+mhm5+8TTxT6B8zjc6hDsMuJi6N0XCUiBd2GLJlb6ic4XFouIUV5MhcwBgdCFRsJaWEzbBBzhPXvB2AJHLYH0e/0NTLoRNOKyvAu4L3GY7VUNKl6BwNkzReQyU73rgrYwqgsGY29XCsLdaXZXiYF00ue7021zIPxXeHnn6wOm1Tq0roS/4toc4OBtqvEUNuDd1fyLJLc45QG76keTpubH11hjR5Zlr3R79vFZjT/uEF3vrO9zAej9r/hI282eDlL3wOu/PzlkXMIyW8+LnPYtideN999hOvdF7Qm7fagGzGfhcu+8nf+lUDfUN/09FhWHOy75PieAkgxuWDK9RywHa7wdnpyQTtZvVszkAF9jgobp0BTmrY0bw9m5FHKeLxXLzrJgwbxdYVD7QLnqzjpHKBeRaqFTCAVy6W2aXBYBhiSXReYkDxyNZ/4TWwvsV64GIYMiMPA1798hdw8+UXF9uaQHjm5ZcahhyyvvfGW3j3B3/eitN/zm7dwkuf/4zK15no5kX/dYbxRhQTAVeOn3IbkLGtfR6JMqCWz0Ltugoh/D6ZJ2f+jbj/hUPahVVhUmrDhDujrDgmp/OMn/0tY8gc/8Bsmlzgoc03HIDz6RS8YsgrrbTSB0FPbOjx4La6l9KJvOrBZE4a0kJd5teqh20MNKMGOXxP82wlS6gSoJ4oUEu4vU1IkPhto3kpKLV9TEExCMpc1JX7dUPCHvQeQ5qywiwKQSbCdrPBzbMbSDnp++bmi3WjQlxQy4h3793Hfn+Q8C1EYj2qCgKFhcr9jASDBw7rCWBKg67FwdK09q4JRF7ygeRqC1Rt8nElhNSTBcFvsldXWqJl98Stn1qtTuWVSCzIzV2aLXi1y6vdbq9c9exZFX5V4G2vF5dsIki4BkpuIBKNPLw04993IzDpCq9B1yFmZHsXjHaIpb8WzaczwHzcOqt9b0kRa+E8TJFofY5gy7p9b2kBgoAhKXh4cIMnbwLWMDJoRhqWN0neKRGy9nNKCTknbLdisJSyWE4POXVta7EOTRlPg4ztk21GTglDHsRjR85gIuwvrvDwwUM89+wNfPoTL4OLGGuAK1ALxso4FEY5VryVbiNTxpBOQDXj6qG4si9hLNdSsb8UsPDsxik2Q8azN3fYDBmnJyfIKYOS3IyoSTrQ4XCJUkZcXu1xOI6otUi81/0B+8MR47HgeCjuFaRWKZN1Q1BZvYhURi2Q/m78VO6UYGs1N2aKfcHdyEnaZl8R2tb7CQXbK+u7CaGrgFIO1uaSv+AbVfVCzdfGeuy3QYGdeZpRlqxPhQq0l8ZzDZNn1Ilzs7qf2DQ/FTXFNozfhUFHgFtaJ8qyvvhY7dM3wxf1RpLsBhA3RX1ibBVr329sJhuViQa/uE/hZvy20kor/WTR1XiF3/3B7+K1+6898TfvZ45b6f3TsR7x7/783z0WxFmi3/z0b+Izz37mQ+BqpZVWWmmle/t7+J3v/Q7u7e89PvGE1rX1p4++/tbX8Y23vvHE6b/84pfx2VufRcZq6PGzTIdLDV/o2+mAcyqeAwDupTPguf73Ep4BRxUjiKr7/qpvRHusXvjj5h2apaHpvxGrmGDIBLlolnPCbrMN3iiikQZrWkbhiqv9Xi4+6WEqB7yXOiOKVmP7lQ2viKFQ/NvF6si7ZGhkwHwn8jHM285m42sO3zA3TLd9K/wYfh7bzj2fGL5p+UUclu2AvuUVKxdlPsOQzTBBn/doV0BvGHIJEd0jh4Aift954jUMT4QAvyYYLzMublmmeNzSzib2pwYMXj14iG/966/i6v6D7puTmzfxzCsvYXfjvBlixBSJ8Klf+SV86le+3B7pmGtQV8CUpTiXveDIdlkwYMSGP5t0gtWH4fhEwGCXBS18jfa7chhxOBxwcrLFMzfP3Uu7NKiE6S7MqIW1vIREGxAnjAcJ2VZjX62M8SjPN1sxsDrZZjW4GtzYBER+FlDKEcx6WdC91MslxbEUVMW1mTEx/LCfjJrsb3QYsngKsQEQ+z8hbzf47F/8L1obzcYn+8W2iA0DwLvf/yG+/s/+1WSOBF794i/gxZ//NNI2S1+1ySgOnWuMiAIa3Ty4z+ZcatWgyd89eLo853T1mKGvizw9FU0wWvvbR7vOC+wTBmFqDecGax2PcSXqi3hkLeIENftCeZmy6/P5SiuttNL7pyc29DDyqdwWLpvnXRG0Z4S4vskP6teCsIDZI7GwtDLaOwY0JArCrM1tAVvgTxRPWWiFD1WsOebaf8lg5E3G2dkZtic7MVBggKvw6uE+VK2rVcK31MMRfDjADCPitXBWq2cC9DC9KftuZBGtRZX/ZNn4oW6rv7uCs7VYBUZg1CbtdkiKkM6Ub9181E6GTSOgYNnYbVIqo6CZKkw1CTcU941Xx+SkofTXwEPbRLAvzO2Ffa/175tvdvgaM5w+NyOJznA1bBBYpUhh4Z8avLgEtM9bPknDdCQ99W2GGNHrBVonn+Sbk9hOEeVOeU5J3VJS+x/OM9zAIKUkhh4puaHHbiuKLpMYVJlFtFmYm8WzKf8aLAesYYXGWkBUwVTAALa7Ac/eugEG4/79C1g4JR0wKJUx1orjcewaunJFKWY04VtvjKXgcn8AAdidbpESsN+PGMeKWknDwqiSrjIRjx4F41jBBQAnJCZs8ha0zeCBwdvgyQPmwUZ4q8qfWILbBkPSFPcEohbfOkbHUT2Q2JhlUw4pKN6ht3m35YX+Sa1fh3Hq/UM3TJ29iXQw+2XesS1Gp20UzIDOxq/2sY4XlY3NK9eq3jq4WX/XaTUyPP89imDKqiU35TaMxdm+IWx4l7TribqubZMan1MGQh5RFot118xnbv/8vT5P15kzrrTSSu+X3r54Gz+898MwDp+OLsdLPDw+DDPhSj8t9F7a7M2Hb+I/vP4fnvq7k+EEn3/u89gNu6f+dqWVVlrpp4GYGa/df+09eUsyunN1B/uyX9fUnyF6mra+c3UHf/TGHyHT+zP0SJTw87d+fg3h9rGhDhy2f8JePG7yJ+70Ozyx7fwNQ7a7LnGXvohBTB/a39zKtzwbOwZshw9CeoDlYHmzQR4GmIFCgKw133Y4zMzgsUoMb57gRIqNNDhkGbuB4siKwjsuGXFGP+Akw2enAiGAmqEFKSa0ePDIHMKCL8k1hM11kbG9aofgC2CReFumGNF4CozNaIrheLtNeI4ZTJvxceTdtMO6qHWJAFFZ/+Tw4d3X38SDt2533wLA+QvP4flPvooIahOZdFrG27NTfPKXvojj5RUMTwQRNicn2J2fumEG7PxAvZX34cHh7RZDazTvNPB3ieBh4ykRhpw7vqt7NmfH2TwTHTIEEgMOYlTSi2lV5JKHhJOTLQDgsD82WRleyYI919Jfn7JzIj870fIqV4xjAQAMw4BKFWMhpMp+HmTnEjZkHd+1DFnqkSkDWTyPcIbzY72Ka/MsXdWLSHXe5We19NwwaKD3Lm3t0sZCG6Oxr0XDuBsvvYBP/+ovTScB8dKSYx+iLq/j4Qpvf+/7KPtDPydMiCjh+U9/EqfPPuNnDNY48TLeHFfVHkuBtThHTudaKayNy0eM8ycZoj7XzCoUErD0yXhBeKm86Ys5dj8vYhFDnjzs1xKZb0Mjtxvxqzq90korfQD0xIYefWgIC4uhCwXgC7OnpokrohRnWrgmZAYYZHkwLIpBd/MaXkYrVxJHpRRNuw3qkf3mi3S0WmYGSA7DzV/E5mSLZ156HkMeMNYKYtazUnbe7DxPdHNGvbpC3e9NswkVb4uzuRIjqJVqtA417wF+gA9kVbJAJB4JuAAgJE7qEo271cUtEOPqSz0rpoiIAp/cUpcqo+l8TUaEsA6ZksJi4CIaY9a2001BWM+jsmtEk3PQTjH0NhYFysNFIiokIqNkyiqjtX8nd8lrQYWB94pEEE8JtbUSaaiSRCisiqwqIs2zS+tfbQdDgV993ilFzRCj6/uakxtupARKhO2QkHLCZqNeNFREQ87KXxajIdJ+lYCUrLebF48MooQ8ZORMONkNYEifHY8F9+9eqgIt/ahrGiIMJMFYeARGMLiK682iSuvZ2Q6nN3aoI+Ott95xI4wWXqOCa8FVHBcQLxrHMaiBakRxOBxx/+FDEBHObuwAYtx/KMYKQz40S1xv7EbiWUhNUwg4yQNoIxbog4ascQOZROrJgzGOI672e/27hX1hNWypVfiy8DC1Vuz3o4zdsYCr5MM6Jmpn8BGUc7bQJDLX2QYg1iXMnv2wicp8aCWGGPS0uTdufrQssRZSOVvvjx5HfNrVwu0d+XPbEFmfN0cftMzk01HUtRltcxvnMiBs+IOVeizWfjrwoKFwwrrVe34KFMZtJ2q0ucV46OQ0Y0LXvOm6tdJKK30g9L0738M//tN/7B7l3gu9n29X+umiP3v3z/DdO9996u9eOnsJr9x4ZTX0WGmllT7W9I23v4F/+4N/+77yWNfUla6jHz34Ef7Rt//R+85nkzb4e1/+e6uhx087dTiZ7td9q88OOHQXxqbGFR32MPGI0EHR0714wJAdR5hgyAvf9Rikhdc1XisauCdFpCHLwXtKKCyX5rr7amghTyr0wHgcwWVsoKsBq5ELBV4I5IfMhp1wnxSAOU5o+I/junrAOEMwVK5MrR2mGLLj/Xo7Z4a7Ah1YsoSGeBiMmZzZvZMQMHcDvlSWZ2rYN3udKHzWEB7tVQETmnaXDsPtykDHs4dP93+lH5gnC27FgRl441vfwZ/93v/jXFk5n/mNX8Nzn/yEniv0lwEbEg+cP/sMfvm3/+sFfhU7Dpf/smLJ9tNyaRcFk/fBdlGwnZhAzyvg2CkwDOIXuzKJB+ar0Wvf9RMtLCma6aHR1VuP2IcwNpsBw3YAV8bDi8smPy1fDJMqRh8XAFDBTCg1lKb5l1Kw17A2m90A1ASzaUhU+ktzYbw6ry4nwpAIA6kXkRTlRN6eFvLFPPFUtgvAMiArN+/RFiacWS5ZyrmPhp+xPlubAUrDXfVcKHTElz7783jx539uoW8C5m0ltoMdUxweXuDb/+qruHj3jn/SfmnjJg8Dfu3v/C2cPfdMPygcQ25TcBhymo5bGzLgs0wwaLCp15uAQq7XhTa6jhbw3MhfFIP8Imc+1xbRGcDYvE3t1SOg7se87nleApwpYsjvEVNfaaWVVgr05IYeiXzeYdMqp0qPKdCEZjkck5DaB8dDMjO2ADqlw0qKHhRcQXa1zZRQRijOn5uS1dQwKwe+iYgWlVZ2TgmbwQ7U1QOHK4/sC1utFReXlzgeDihldO8fwmtt65ZlHxTQquEiOjd1Qe+wYCX9XN8sa6Mq2lHYUISHrQCTJ/ffNkXPws5MmKqiR5vSmXqrhs4q1FXK6SIGc1VInY4VaweYvm4Wr+Syc88o3Y6J5vU1hVOVowZCkStCok+IUsFQ1ygWuiS4tDODHpN7DL8SZWqyk//VkIZCelXCs2o3fZxDeNgUMSYhDEOScClq6OGKdjT0SIOUAwCuQLOG3NA2NqWyEg4sFtMjwxVNJ572JVFKSa3ygRbKpNpI0g4xlhHlOGLIG+Q8+AZODD2sf4srynEsICIU1vAbtbqRxXgsaljDuLjYYxhGddVHODnZIqtsprsJk2FVYwpS5ZzU8KLUqm4DtQ0TqXFJCx1D2gYMxpBFbjknVGYMKUs4mCtxrVmSuBTkzB5WqLLIKjH55rvbhFtn151G7LMLBtVtrnJz6X6img2tsJVtu0RCLMiUx861IwPdtQlPHpXtKYNLCqjNcgtK+mwis3ImcwzQ4zkLxZkSnFLyTVYnG570jyXhdpld847IZmAA1FnjS1WpE49tymzzshp7rLTSMpVa8MN7P8T9w/2n/va1+6+JQd66CV7pCYiD7v40dDle4lu3v4Ub2xtPlJ5A+NQzn1oPoVZaaaUfGx3LEd+/+31cjpdP/M1bD99aDTVW+lDpg+hfYx3x/bvf1wtPj6YXz17EK+evrPuwnyDy2+VA0N+nm/CA6dprhCQKcHStakCu7ssV5YAZG3RdoAExmg/32URuCOqhNqAuEdOOMCT330k0c8Ht0uTQjg3/0QtOx3GUsMKKiXns12h9ooyZgYnjS9xLsyfqqxueR6HMv+VeBpNPpxhLjyNruXPweoIxznHbRT19BhEpxmNl+XvrN1q+prVLTy3ctyZXgwrH6CPUFfEzaDea4OFEhDKOeOcHr+F4danwMeG5T31SwqdYWmrcEBGeeflFfOLLX8C0Dz/76svaV1IHw/WhUORFCrw5R9RyNGOFZOFSOgMQdsMFQgohhdDOJya4MJhhAZAKZO6tDD+/iGlnSKHKjuLflm2QQOWKWgoSSZgVnx30A784V8WIgoIL4BZGRc9UqhgLHQ8jitUd4uGjO7cIbUoM1ARQbWcKHs0nVVSdV+ycxDofsxppaPciM8iweUoP7hOJkQvpZUEm9Qlv52oVYCYgqQcdz9IGvlfX25jYg9HPIdZQvdjPhu0WL33uM9i/9ML1CAoDNGScPnMDDMLd117Hxd17fYImOZy/8BxuvvSiPgjjbLb0zibi/s+wPsySL/B47fs5rDzDkH3+8b41n2s9NYfOENM8jg9L2v6Zw+rxXfhAus+qu6y00krvn548dIsdsNrC216EeY5AWRWKsaDCzRV8cvMYaWrgIUpF1VzkW/EOpgYHgHuBKMWyksPK5Eq/TJRy5EdoMf0a0MtgJF08EwmfpdhCKrzYAd0wZJzuBiBlMITXWkoz9lDF4nA44J133sDhcMDxWFFLWDT04D2l7BscsfSUOo2l6uFwO7x25RC+9ssTXYwsbVLrA1ezOsMHVm8r7FE0OmU4/GRXyIWSWoKyGuR0B5ncyiJTSGGhbFq4nb6xTVbaEqo0MtQjGlEI0xMVKK0LVzX0aN5WPJ3LBOK1gOGGNuZRIiVVhMpRu60+zykonqyas7SFdTgCMJAzJ2s9JcB7Kvu/KYlHDVKvEomAnMR94zBs5P1mQKKEbQpeVMhVc1cikxoiJLPGzmLokXNCzs0AJA9bUB6QKoNqxXgcMR5GjKXgcDxKqJUiSnGpRwCMq8rar6ReNZauyryrQQyMPMIPvAmotbWrJCWgEPb7Ay73FzjbneEs5WboYO7pqiivtQBXVxI/kcfibvZqLTgaz9LJ8M67LQZlTgnPP38T2+3ghi/uWgc2fmro3jqXhH6YyJzjSB/oDuO59X8QkLO8t3iUoIRaCu5VxgFH8LGiiPYOgHE8Spga+696WBfbDKkHD+u3rtdNNcbwm8+zS+r4ddpwmEFokrqTTds8SJVFXtXHqb4Pc1Lb/C2UbWX5YF7Wfs1I7nHaMc9+mRAlDGroMfrY1k+4uXiUmwTSd31jv5B3V6OuSnYrQ8eL9TkDkzqvHprR1BhtpZVW6misI373h7+LP33nT5/6WwdDV1rpQ6R7+3v4P7/zfz7xPJ4p4+988e+shh4rrbTSj42uxiv8i//8L/Da/dee+JtSH39wvtJKP24qXPB7f/57SK89Pjzmb376N/HK5175CLha6akoQh7+gDpIwC+yVQMvpyeWhgHaIadig4AeFpJ7t+XJtxzAhYaTNNzESjO9j7WcVoakcq+14fDOSiQIfrcZzJsqNQxVT3ANsyil4PLiAUoZUarDxg30hSJZwRLBvMHKfbzGyxR36XANw0iIuvy6vRTpV3phChTeRgzZT8DnIV0i5saRnXhmYLi98eC4ep9XlCscm2ovQtaK+7b8oxQaNiR/R53eWTSM3oyD3INDUuHVVgfFDsf9Ht/5N7+HOz96HQAw7Lb4L/7u38bpMzdFzmbQE84jPvWVL+ETv/TFGQ6WcvJLfh7mPRkmrB6ds3jPzu45eSJzLaoL6w00Q49EboBEBKQ0ACkJnyzhR2qpihkXN2Jghnt+Hg82Rmzs9RiyjRdoHUqtoT3k4qb3AW8YwjiOGMcjNsMGKW3VwCN6X1c8j4FRQ46jVsdbmWsLta15Xl4dfEgQEU5Pd3JJMie9QOed2vnv+4/yWtozO3PyNH4YYf1FxntOIhk3pCG5+HjFBxRIP2sXTIECO6ciWD9nlZd7MO4wS+vwPd8+ZnyctPEBAk5unuPLf+OvPdHlh5QzuFZ8/z98DX/+x3/iz6d993N/5TfwzMsvSvt0eHaTU2AnUJz04zM8GkNug/aR/Md6exlhHksC7nof73gIk5Xh4Y+CApYw5JZDS+PrhefHPvd4Imrz/korrbTS+6UnN/TQCWq2QHCvSMmteZvLgrcK0Z7DXNqU3qQLVpuDqSmwoQxL1yZSW45lspRlM06PYaHra9JID/eZGZvtBqdnO+xOTkApe/5RHWgqvywQZWTUMdRzNpEHRZXb72LbYQfOmKwtk4NofWYu1/T0sbWFGSgEjyK2THQXz8mUpaY8RapcRQFiuPEJCEDwyuAy8U3IZJHTlb09Y2NX5REVIpNpT34Wza395RG5MUTzFGEf9ZuiZhBCACW4S7r4rkkJgIbVCUYYyUSQzegiIyVRfixmIEMU8uYtwgw9pI5ZDX0oZ3UNl3QjGBRk5xvY5Cz1MxGo0QC4iFu3WlGIQCNAqUjIHa4oY8U4jqilYiwFlYHRPHCYAUzou95yM+Wrtaj1VVNOWh/QtyytlyhhSIMYP41HlNJc04EZh+MoejkzjqNYQ5nhVK1idpKGjAQNCRXlopuuYxlRD4x0HJuBDJlxUoJFKGmGHMnbmdRQh82givo+6D3BDXuql2/Pa62glDAMGdvdgFqz99xh24zJzD2feFapTYn0TRN34V7YNielaNuo9wi/1WHSjmN2OurCqwVaGGETxRLdRmopp94LCM/kJ2yFTcciV20jsMhTmGllvuBQ3/gzpLTwTdHSzIAD2xFw66szgAbLc1Dr5qzrUXtoc1y7oUSuq9Oc1ZVW+ljT5fESr91/DWMdnyj9sR5xb3/vidOvtNKPgwqX6xfVCVWqeO3+a9jl60O9PH/6PF48e3E1AlxppZWeiB4cHuBH93/0xB4RLsdLPDw8XNfWlT6WVLk+0Vi4fXEb37r9rafOfzfs8Mmbn8Q2b98Leys9Ac0MtYPxg2ET8ewrYhTdvjrAVz1WavlMPuDw1/TCS4+KtfQB325WDRN8wpllpCFjGDLyZuOHvlN8tB2S6yWgys3Aw5ic4DyOIUfeIp7qorQXin2hp4ideX4dcDEVsoND/v5RGLKXH3EbK8uzbrhuV0t9H/HqaSGxzvYxudfnCeuRBxdrMHTp2hbYP3yIO2+8CVTBfDanJ7j1iVfES7EUpOwLk3kYcOtTr2JzsgPAyJsNdudnHU7viLmHSyHHjdxbBVmW7bIjQb1JE+nFTTMAsXyn5yDs3n+zXdjUV95tCqMmgFkuxdVaBOtU4XHRUCPxohqbtwxDpKcUnvnwMDCsjS/v890gC7ic4u8MqHcbDhi/hj7Rz6p6YWYNi9KOQchaV/6O2CZBsWYGlYpuupieCfjLNHtWSTM2w44IpGpftIoyEVLt28EMd3K2+Ua+Ty5jnRf0b8OVm/cSza+aQUs7B+JaPeyRuCjpx4kZh6Qhz5svzq9xmiHCzRdfwEs//3Pzdg746Zt/+t0uuz7jKQosfA/bLW598lWZK6FGQDanLo1lrRv7Wc8s18BUP+/PmPC/bWwtQNexYDXC6dYPM8BBm1sWqj5/0M3LATD2voa+7iuttNJK74Oe2NCjGnDA4tXA57QqYGhFU2q78AX6fRdykMzdVkVKhCEPqFU8EBBBbpkTgdRiudQCAmHIG7SJPi4IphglY7YtkGhzsvFc9R9RLjSMAypOz0/xyidfUqvSjfMIsBwo1rYOVVQUZpQ9oxyanHyddeMLPWyvZqyii70apjhPBeAqdXfDAZUnMyMlQh6SLPRFlRtzM5aXVwVT6lscQc2v2hoVlTSJuceVxbo4ufYpoTq4NkWTGbWWYBRhlq5tfe3UQobGYGveVjp5dTzLs0pJD8jFzF3KEo8ZOREqESpq61Qqc+MxxtJLJJ49/IA220ZISjeDjpwzEhGGbULKhIEyEiVsthl5k3B6coLdbov9/oirq6Mrq9F62gxEhiSbwWJOACam793G1JQ3ELbDBkPOOByPKLW6S0dtBVd82bcQ7Iq0KITsoVtYPeeQ+upIoNnmqVeWwk2ZkK66/ZAa3PihurTLkAakzRkOZcSDy0vsr0ZcXYxeBrMo6cdSMF4dAK6oRbyF5ETIOeHk9ERkl61eTZGuzLi43KOUgnIo3keJCNthQM4ZQzIL+AyYUU6WvjKIGbsab01DGwU5wuYfK9t+qqePTZb/T7YAA1n7PqmFfFX5j9pm4uGHfX4qtaLWiuOx4HAsqEX+H8eCw+Eg/aVIe9pmxmTvgIM1+bUbr9i6fVNyfMHoxx63tM2looW1SX3ahTFMAKBeNq67cW89zmajKbUux7MypjnZRoiSmfcV9CJROZo1thps5EE3dC2y1lQEi1yZZb5tWyJg0g1tmt9yWWmljzO9ffE2/sG3/gEeHh8+8TfHcvwQOVpppY+WKlf8+9f+Pf7gR39wbZrf/PRv4m989m98hFyttNJKP8302v3X8H988//AIYIMj6F1bV3pZ52+dftb+M6733nq7146ewn/6y//r9ieroYeHzRxDKEcnzcATMidcgbMw74Mm2vHpEjD7rJgVXp2p7iLpKpc/TBZUCXFGMIBovwgP4gEzEOB4iIRsiPB9MjOJknwiGEz4MYz53rBK/tlp1htMUxgx3a5CP7bATxkHFHjRcNnG6Yrl6CifFsh5PBtC33tl+REIILzsAXlWCI7/J62F64DS/wik1x6029Jjg24xsubDQPqjE+wAP2w/WgY65zT8DuF9M6s4kDULvExkWDomv7uG2/ij/7h/4k6jgAIz33qE/iN//ffRj4b3GjHy0mE7dkJvvRbfxVcq8t62G4UeyTvlwRCGkT2w7DBMGSMYxHPFM4ptfprORbVgyf1nwFX+pVd5MyKkzeDiarnM3YZzb45omGf4V/DF/3EuQFrSz1l8cC96zfBQAHs/T9WJlEWL+tccShHjGPFeAwGfcp0rRUH/du89ybFbIdhENlNwvJIcrlkWI9Vz0/YDUOyes9uRx4aPkc9oQh8rLJwvLGXQGBU559pCu27Wbxzm7FF6/t2Wcxwy2bEEjFkuyxYS0Up4aJgreKh3qebYFDGky7D4cc0JElfE1BK+Mxf+DX83K9/BdfR9//ga/jD/+MfI3SsBXx33nNuvPA8fuPv/Y84u/Us2lyTFr+eANDSR2mW6ikw5Lh+UNf3Zyns8FANO+zMq58H25XhpbEZhrfn3UkkDG1HmVcceaWVVvoA6Mk9etji4Ifb8ne77azPZx8GRcJd38MVDma1aPZZsykX/c17WYVTIuTNoEqrLJajegcoo4VXaYe2xrOrOcygmnwxtqwTJ+ScNVRGjtoibJK3/2otuLy6xH5/ECtRW4jJBTSRDS9M9EGutimhsDYtKXOm9VkRQYlB/6j/bLLRaM+bPtaUCqBf7LwyPR+BRd2GhCJCjMRqn/dKOvmt+17Jt0yISdb8asp5UkMPcqXHDthNUbLGNO8aQ04q29QUOiIgp6aEh3IHfZ8HMfTIapCTh4w8JAxqVLDZ6KYh1NgNMFTpTyCYz49r9kThO602A6N6uCjqDaL6YTXDLNCj5W9QUSaeLhl2UG9lWCgfDv0xKivmAYHQ96kuzaQ27tYsEVIljUsq8nOLcBvTJm8iZJKwKDlrKBpVtn2sB0qAenFJQAY4tf7s7vqSefypTUlPCZmATBBDD8ogsnmhecihlK2bqC5v/cq22jq+9T1c/gTd4cMVVVIjE07NjaH22UG9eAxDwWZTVVmX+KybTQZXxliqyE2NrsZihmKlG58y7/Sjr820QLtsErV6dL/7FGNzur/qcnL99zF686SQ2Ipt89ckF3vu9Fst390hBl7I5G6KvM2HdleGuvzcyE+fccjqeta7j9rTrrzlWhLUSO/xwlpppZ9ount1F+9cvvOYFQx48+GbuBwvn+owaqWVPm70uFv0ty9u47t3vvvU+W7zFq+cv4JN3rxX1lZaaaWfQLpzdQfvXL5z7fsf3f8Rrsar1UPHSis9BRUuKOXpQxI9PD7ED+79AO9evfvIdIkSXjp7Cefb8/fK4s8ehfOyDt9F3FIH4NOhAfIDSUZtHhzCft6vl0xc/rt3aMcg9AA+ZYUMNQR1FdyFaw24RMN1YjkCnynXCkBasYIdpa48xwwcQxdMZxyPjl1btRseYxVAE9oUQ55BDIqbT0U53b4tYBuzIq9LcB1uoliXZz3Frw1HnxamD2YnBwvdYEoic9ZLhAvvQa3rEOPy3n1c3LmH02dv4sbzt2ACtc+3Jyd47hOvoIwFRMAzLz2PYTMg5+T9z0KWwy7+bLddPZPh+CnJpU20v1NSIwySy20NQ57UkyOW3uNX1x8ktDSdN2H9vsYOiIbbYvo8MtIOTuY82m80+cbGBHqsuIcflzBkqPHS1POJ1sH46AwjFO9Xgw33+G6MxYHg5ytyrkDc0lRmUGU3lAGKvKoVILmQa5ixzBcc/o68+BEE/FJpbKxr2k1awjxa2PfihZytAXWeMQ8hNVWkrF5Pqni5SkUudtqlYq4yrzSvLP15gDxseKm3ik1dOi0NwwBshnZ2MKnI6a1ncOvVlwMuPq/dEu3OznD39TdxcefeJH0/rRARbrz4AnZnpx2Pyxgy9T85tEv4tvVZgtwoX2SxMRHBcqaZrMDX17NjcfHFDClf8eOVVlrpA6OnCN2S4uyoayfJASpEUQ56rx+7JU3r3gbcYEImslLF7XFclNkW+ySTaoIqRZmQNxk3n72BzXaDk7MboES4f3GB4/GIh+/cxbg/qlLQJniCWkeWotbGEm4CWbxE5JyQ84DtdoNh2IBS1jVAF3aP/yYcHg5H/Oi1NzEej8Bx1HL6idm8STCR1CFVP4j0xdt1IrUwHlShrxWs3ilkVRdlqKJ2SjoRoTJcMU0pdcoxV13Y1QMD5eSHkZamAs2oMyzUbH8bnwBaQBEXrCqSTUmorXuIh4JRAtxtt4MoYmY9SS1fOQuPGyOIVxewxiXMYgSQkzMnoVRMEdB/9OA+J0LKCScnG6RE2GzE+OBktxMZZTEU2mUJszKqWF0pJzN2qLKxhMQFyYOEbjk7HZBvMAgDiAaUKl4ZylgwHg6ifJUqXgRUSNYWvrGo1CqvLyoxHu4PYIgrt9CbeqUVgDpua++7t5qvKTBMYJ6bnJgDHPvQjKSWVIzFrWHQxogShs0GuWYQy2Z3LBWHsYoiWqu2WUJOwDabhfsAoHl6aTYto083xMDJsAVngM6kFvvDEWOpKMcRx7GiKv9WVq16u4Ml/iTUaIe03mKwM2DIGZvdRjzFbLLyOIAIGHy8qJJt8WHUy89IWXkXmQ1Z+tmQB/E4MvR9M5Fs9NpwEwOOUiXsTikVx+NRvBuN8ny/P6KUisP+iKoheioD47EG5V2s22WoNuMyM6ZyfXfSiG0TsqCFzsyJ400AbfTYV0L/nKmtYWjLr0nHvtuct81ZV+LkiW2ulD3Li8Aa87Lp4oB4fhLxN8Zrrf1GEvDNZKzXlCIfNuf1xoCSKFHCZhjcK8xKK/200rff+Tb+2Xf/WWf0t0SVK/Zl/xFxtdJKP530zdvfxJ+9+2dP/d1L5y/h7//S38etfOuDZ2qllVb6sRAz4+tvfR3/6j//q2vTFC6rkcdKK31EdPfqLv7Rt//R5Ah2Tpu8wf/0xf8JX3zhix8RZx8Dml2D1p96aO44ZQcqcLCVULSA+4M5ZkKhuIMPe/OFw1bKCbuTLVLOGDZbEID9eEQtFYfLK/BYWuLISm0Ydn+4K9g0UVZ8KzecEw0Ld5yUBBe9f++hhM+o1dMtQjEqlIa/hlAlVlXDFQOmMbucxw1vafUiN3CxuvgnVmdqMGW83saBFz84N1ywOwD1otBA3yZXu7jTsMv+06puWrLica1tuctudjhqZxGJAM5489vfwZ9+9d/j5/+LX8WX/vp/JZicypwIeP7Tn8Bf+P/8jwAEj05DxsnZCVIi9dAh3sfbuYd4C/auAcPJVVLUMFVjJullws2QsNsCgl8l8QBsh/bFvNNKf3NxhbFDEQSLY4GAg34/OZFo4NhU0BPqnwYvPGEMhlz7Dw3TnoF36Nq8pY0ZEVLOSBJnGwRCZQlzbeMuemSxi5vmyd36ZhNT1XMneTNQFgx5AJgkHEyTeTOK8XOqznBJxzzamQPpBUXpHxKi3TxS21lMStTZnllIHwe6yQx+pCC7fJjt/Ce5aFr5cYyynAWI5/uqYcGLHiPVdnmwMoqHS5e6VvUebeOYAsZrw5m6B3MiAK984fN4MYR26ZNOG73Rw3fu4Gv/+P/G1f0Hk1xjOkIeBvzK//A38covfK5NaSF0jo2QGe58zZ8NQ7axIEY10lXi+Aj5hvXFjf3iOqVRCroCYx8PU5a9Es4nczTB+/Rq67HSSit9EPQUhh6BGGrAgMnkyl0i1zuJxFUcT9UES9oUZ1da4+KpVtJ5GDAMGbuTEwzDgM1mAxBht90iJcJ4coKcEspY5LB3rG6AEnlznvX5MAzYnZxIfkHZtoXeD5H1Z60VZRxRxhHJbvMHq8tOj0Y8lJzP3Bzrv/DODGNkIzR5T62wqI+YsmV5z/T9nsXGZ1Dfp3paVO+D6K7JyRixJ7ZYItST/K0Y9ejyS6FsShpWRTZSKVgmpLAYJrOqVyUqqaHHbiuGHlm/zSlLqAdVonJSDzE5STw940yViFpHDZ0hiqe4ThTbaA2sAaKCUqoqjao4MgcrWpFopyYwIdkmqTtEo26MzA7iTYkGOqXCLH+bkqqbtmplBAW922CF7EOapXO9Xt9rOzEzKmh1Dgq0C0D/r6JIVQYKGFwJ4NL1/WboUaTfcws3FDkgSHicknNz28mMWnS6qUVvaYiS6945SBxsFPWUUXJFBUv/qBlECSlLqCgLzWJKnbnyI4vVmQbtR3Dr85QYWWVurgDVT6QAGqwbz6C0ZzU+SlR108jIOaPUCqKEWiqGnGXeqWLFfTyqx5dawFxdiW/u++qkXSd9aWEustct5eM1Te8P12wEZokX5sdHpsVjOYZtrx0Q8hiOYUMURyAHF6Jo857Jqrnym5Q5A6pmrIII2GyHbq5aaaUfN1WueOfyHVweL5/4m7cevoWL48WHyNVKK/3s0FjH93Roe39/H6/dfw339/c/cJ5ubG/g1smt9QbRSiu9Tyq14PblbezHJzd6vH1xG5fjk6/JK6200odHDMbVePXYdMd6xJsP38TpcPrUZZxvz/HcyXM/e2vu5NazH3P5ZtsOQO1vu6xCdpZ2jdE5O8hKlhCAh5ZGxAY1/PMwKCYol3cGrigEDEOWsNDmqbmEA7yAv8WiQYyUsuSZ82K1HXM1PFBxOq61i54wP/yeQiaxz7DieA00nWHIhs85+wvym2AyHJ610DX9qSUvfRgYjk3qzE1AZZMHGej0CAypw5ABcK148M67KIcjzp+7hc3piV+anNbNHu/Oz3DzhedwcvPcDTf8fwCgjO1u61gyaX+QMwjpW4naybud2RMRNBCHHSF7f7QLWMJ0uIQFwzRZMOVql7XaOYNhwYs9XjHJiNvGy1ku//hLJ/+IM7dv3Evw7IA/eF3pjIjm+HXHxALm1+QBq4Dz496qo6FFA9I9I4bYR0n3qk0YrSKhhtyKCcWC5eygUgIlvYBsVWcGa+htO9gHsxttEEHmJmZUTshQ3JkFIzbjJIv4YhiyY93eL6Xvp9BRiRKQ5IKpeaOZjh/ytK2vZUru7ZqtbkkK5sriFZtZPX8zSjLPH3JZsKqxV2XrLn3jyV9xYhDKmwF5M3Tplsdy3+OOZwecP3cLeXj0MWQaBgzbbcuiWzSmI16eXz28wOXd+9ieneL81rPu9Ycm37bqyS+aamF0TCtljEwmSgR8mUIW1o5xjQvtGYcUQTyd/8zpByuttNKHQk9v6KGTosdC5P4Qv4tJCFWQSA52q4Y56G3vJG2CGXYwiIpM7men2G23eO7WsxhyFm8b1G7/m9u9zZnEQjzbnWIsIy7Uw8fFvQeoV3uwWi5ajMJOSWHg/PwUL73yMihlV5xqYbWCHOWGfVW3D1xRywgcC3CssoCQxYZkPxy2MBnU1XaywEAW1QogMavHAQJI1EYu1dQfMJMuvuEQUn2KJXN0YUqSefLQv/NGDCZKFZ2oshwSZ5LwJMYZEcnhux5Ui+GyhuAIXjAZ3Kzvky2NtugZibys/W1VS67sDO17iuEOVOmHGGTkBDfWyCkjZagniIzNZoOcEgZ1w5hUGS0sG7rNRkJyVLMIrtYwRfureBk5Od8i5yxeNhjgIkYdh8MVCiqORayKaawoxDiw+NOotcXMM3lY369T607V04rGV3EXcGHLFBUhJulPrpxWS8Xeb70rEenBfvXxx9rz2DXMyI25qaSmjINRg2s3BsRQhBkFzQuNWwTrWAAzxqKGVWHslDpPWwHUUcrcT6yWksZV9PqGeK7Ww4SkI94422GzyUi7HUAZRKKsHo8jjmPBxcUVLi/3GEcJ7zIfegWXexk7aSB1taghXGJTKu8EeHiZ7SYjpYTtdoOcMvJWPHhsBnk+DFk2/D5PkRuYmNvGPGS4ez+Svp1TxkaVXlaF0Dd+tlnRZ/vjiFor9vs9SinYHw4oY8XlXuJb8jiqdxMyGxtth7AZ67oRTfpUCIIS9NKno/5DHxNhrD+VKsscd65hnbFNDAWL7J5bccDYfdKNC3/oGxwdbUvKts2Z3H0JQkXOA5599iaGzXuzoVxppQ+DxjriX/3nf/VUccuP5fghcrTSSis9Cd3d38U/+NY/aG6jP0D6jVd/A3/jc38D9HQr8UorrTShQzngd773O/j+3e8/1TcrrbTSTxeNdcS//v6/xlfTV5/62195+Vfw333+v0OmuVHAx5vsVEt+N+iJ4mvSg7LwjZyZkYafMAx5mqte5vHwv+JBNm0HDCnj5PREPapmzxMAzGty3mzBDBzzBpXVs2opOO4PKMcSXDYokuAZCE+bzYDzGzfa4ZzBEFVwNeZJCGau6s5a8XCCA29mnBLtYha1M+Xd5WiYfHinaK2L3S6xccjC5BCxEe6AksZTBTlGYpeZkreAXpKp3aeOEUekswOfIuy7gCG3M1PBrygB4/GIP/3Xv4d7b7yFX/3bv40XP/8ZN7OYdijSi1g/96tfxqe+9AUMu4148c3JD1QTNW/XitD6ZUBYW7Dg8B2+NEj+g3msNvkKHCnnByiOFUuIEEaxdtMLbY41GgUcKsok4vwu33iQ7FkEmSv+PuPd8mRtf3Bj3M9pvIOEwRoPtWN2DPM03XUfZjBRV8fmLUPKchzd+qyNF8M8NVMG/Ex9nGJ8sfE7+U37lvC43Qxi8DNkuFcHtIuKgiWP4NJ4sbxNuiOqXgKkgGu6yINo7OKzzD3mjSQPSS8XmncS9VhiB/0qdzMc0OMTv+hqhRHEQETObOx5mCv9p7EjZ1pyOVDOuMpYUFm8SZunE+vz3o987l5CgwOGTNDLz179IH+h02dv4lf+9m/r2cmj0GXC5mTX2nSC3dIkLQC89Z3v4Zv/8t/iE1/+In75t/8ayAzwePJB6LsyB5KOI8KcJ5p8Y49s/lZMmtoY9bm4n5j8m3hMJKzJfLfbbZHyellwpZVWev/0xKdRHFcJmxQxV0B9sQ4TvLmkiwdn9p0vWjljs91oWAUWQ4/dDtvtVg70c8aQJRaCL6JVlNiknA2DhF7YbrdIRBi3W7XQ3KMcSx++kSCut4aMZJbY7Uq4Knu2UqsyUiuOhwMO+0OrYxBAL4vwrb+LC2TT0szQr1uFeL7McPzODsUtG08TlJuJrH2Rx5xcV7RFyRZT/33ClCoXtmA1a0TjK6k1vtbfFJms3llsQ2auylzRsfxbWIxEYtyR3E0aYcgJwyaLoUceYAY1zACqKlSd1ONGRjpjKWISXMYK89gh/Up+L7WiFNYwIK3dTAmtwTo2up1ktEPtuOeIcrfNrIm2V+pbP4heNtoY9D9aOjVIMKMT16mJ0Id5AWwn5ka51X7UvtuqV4iqsjMvEbWyKr5iXFKKhjZyPlk/7T1+IL4PRiW9kavVO7izRFNwmSUEUikFKUGMx8gMZprRCZuBSRwgXf+3MS3tTSyeOADpZ+a5x0I+gRlF42uCWV30ASlVDGCknJSnhDzmFubFgAqCeJAhCQG0KRr/0RV7ixlL3o/kp4ESNjBss2NW4yILEFAGyXMsFfWYxPhGrdKtr3INfUQV5xq6VAxzYuNJ+vSCknsN9WuFsz1N4LWZzFLylKRN2o2Sa4ruxgE3nbsF9YyYR89OWKi6MejjxmfZxp/Oe7zEDEt7DZsBw2azxO1KK30oNNYRd67uXOsx4FiOuHN1Bw8OUzeZK6200k8yVa4fmmeddy7fwRsP3njq20NDGnDr5BaGtBo0rvTxpP24x939XTeAf6L0V3fXNXallX4G6Ek8fyzRu5fv4o2Hbzy14WamjFsnt7DJP517S8ddFFiwkCZzcKa/DKgb6/B3O/T0J4qdZMNRUgKlhJQH5CyXaPxw1HHe9sPySimBmFBzBYFQs4ZBGNG8bxhgpcCOlUV+fb+x3V88YQ+tUMbS4IiI/U6qOceQAy4dwEXBx7qHQebXPWnoBrh9Pw9fEH6tkzLCn96eFOrhB5yhnfvbNgAI4/GAy3v3RcbOl+Bqp88+4/i8HGhLO+7OTnB68wyDXriyS5zUlds88NJwAjpthh+OKZuhhwtYDDGi4QApJtXg++aBojLApaKm5HVjJsAuAlbDPAPuxO3ylYtaw+R0LcXA3BtHT36e3jW2jCHpqj127bnHJvF2sYt5AQ+L/aTnbvanX0iLzEHxQw7vgwGCjIvahX1HZ/Rh/ce+DWW5jJrAwhW1jr3mOUaeWxhnuaxb3FCqGZ30MooGANELsLcBs4b0AaSTtXOBGBrJhwYBGFm8iTCDEqFW7d81eB3Wfmg4svddO2Mge5dmfbZ9bpeIm4wy2aU/8UQNApLyW5nlwqu1g7ad4fcAdf0k4qvxzMN/jecf+ouM4TMsEceE9qwzhGprAoPbvKzv0jBge3qGYbsVhydmgNFlSyEv+bWWERd37oG54vTZZ9zbyHUYMkH7hOHOkzHqaSbfxjOP6bgmAlJOSOlnzRB0pZVW+jDoKQ092kGgKJbmIUMOy+1wldkmKpLwKar8RUtlSqJwpZyRNxnb3Q43zs+x225w4/xMF62kB26ywrlFaJJF9ng8yIZBmRuGAcMwYHs+gLni5OQM++MRd95+Bxf3H4KLWlEr/9vTE5zeOMOw2+EwFvEakiELOgoAlvW6ykK9v7zCm6+/hXEUK1yLtwfoMazH+WoCc8u+rEpoaQsm2AwYzJrWvEO0mT8aLExaRAqy9Y4B5hZbkmDWokAtokT5jfqgnFTmpkDEjYbvWVSJSMHKljSWHKh5QdA9a3JFwxZIa3vZCG2yuEw8P99g2GQQZYASdrsths2A7ZCC2ypCORwwHkdVKEyJt81EQs6EzcYO5sWbBPbiseSgh15e7YnXjaMetj+8OPb7SKRO+e3c6KmsyRV09aYBNRYxsyPTITwVdcYdc829V23cgtiV0t5owowlarF6SZgSM0qpVSyTTQljVs8W4ZDaDDeMC/MfY+PJxnozkomuBbVvu0LMarSj9dcxns1dHFp9GHClnmCGBkHp6uQh49UMconE6OLhRdE6BV6sjVmslWstMsZUOXZJB8XVNq+UEgYChk3G+c0zcGVcXl6hjAWXF6PEiiwyvg616IbzoFbZWQyZTOH0wZNcMaekxklDxjCI94+cM4bNIHLKZsSU9OZJ8rBCzRCkGYZshwwgY7sZdLMpgjBPKuNxRC0Vo4awGYvEoTwejyjjiONYMY5Sp1IKuDJqqWAmFBa3gaim4Gp/MGW50797ZXyJOpy8c5cCRIOKLt84vlScBJmLO/JxpmmsnSuC1s3T5K0TkGUeYwHbN9fsrKeZMbdxRgmb01NxAbrSSh8R3dvfwz/81j/Eu1fvLr5nZjw8PvyIuVpppZV+kunb73wbP7z3w6c29Lh1cgv/85f+Zzx/+vyHxNlKK/146Y2Hb+AfffsfPfGB7odpkLXSSit9POi7d76L1//T60+95t7c3sTf/dLfxcvnL39InH2EpAeO7SILdZdP7OCzYZuCXdl2XbbuesCmB/Z5yNhuxTvvTsN6t3DQdigIwYw146IYkR3GZQ3tnDcJ2DAOwwalFlw9vMTxcHB8SdFS5GEQ7xDDgFI5YE2CLxgcyhBsahxHPHzw0C+O+a19R3nnGHInMxIDgnhg7ditknlujR8+sqc51EEBrFHjEW0DrmrQYKedEUpWXMiOl/tuTa2eLhWEZ4Jn3X/rNv74n/4zjPtD4JVwdutZ/Nrf+W+xfe5Zl1UmwdF+/W//FsAVu7Nz5O0GOYtn3SFR169qKailwFq5P4gmx+BhB9mVNWQPUMKFtP4XocNRYkUfDmWx3hy+cYzS+m+QRQMl/cpi3z5oGHL/YglDbriXtxcMJ22t4HhybViuy4AD3h8O8iv3ZXaeCzSlYMgmBv9loexpfwp4nKF/ZOFJGg7puQQMWeaN6cF931atfaRNj2PF4YhggNPXqVb1UMLtvMv6TNcMfqhFeik1YbvbgBmCw9aK0Y195MPCxm1xfNi9o3PMmNrYotZXUyL3CpL0bMXGqoUjMi/pU0MQMzYZ1DBtSFswGFttBzsnqhoO3AxfqoYNL0XOGoqeK7F6LYLV0WVIC/DwtOM/IS2lbx1AbS1av3r5Fz6L5z75KvJmg3b5uEl1lqn2gasHD/HH//Sfo4xH/Or/8N/i5osv9AmW+PJ4PuzdbrF6zZIsPOszMww5DxvkYTX0WGmlld4/Pf11LIo65qMOw9gnPF8k3dpRjBCyhjhIm4zddiveO7YbbDZbVwJF2egVSvtVjCKqH6sSt0WO1aFcci07zL6aR84Sk28YhqAKy0kmhzXKbveXUjGOI8pYOl5M//ZDyV4K+pPa+hZcqIVSg7eouZIH3Q+0Q+226SFunkJ6JbZl0YwEmkI+I+qf2vaDyU0sXGGPygTIDD8ghjGwtiZktZ6mLMrIbrNFTgknJwOGIYGRQZSw3Qzi6WCTMZhRDAgjNmos0GRmykRhlbnqqBKWpilUnUocNUNTZIKi2yvptpOyj9XAgaB8TENOtA3q1FChKx/RWnrSULahiGzav2xWxvKSwW5UZcoXuIJRxUWgG3oUHzeyaTFFSDc1ttn0WjdDD+nObMMBttlm2xggKK7WlzmpRxbJN1VCRQoKbrQObrLrpDX7RQ7gE0nfsgmllJaReTCxMS59nFuftHHq4weI8TJBFlZFwv+I5Tdba3SGJKFJ9FMGUkKi6v2impEB1Tb3AahDRqkVtSYwV6RSMdbae6tRpX3Qvy1GaM7VDUJMuY8ARtbYoUkNshIBtTByTajMGIrMXzkBY07IuWLMZugxBgOhiuMo4Af0gkKFGrBo32vd3GZ360dxM3dde84fT/X+/pNpT0FX5kyj9jlZb6bYw26+pskn9k59/yxq6ZNifMMXFxXWzVhq7hNXWuk90NV4hYeHh+BZB1+mdy/fxbtX7+LO1Z0Pl7GVVlrpY0OHcnjP4SNuX9x+rLcDAuHG9gZ2w+49lbHSSh80XRwvnsgg4/bFbbx7+S72Zf8RcLXSSiv9LNB7XXNLLbh9cfuxnkAIhPPtOU6Gk/fK4odObQfPsBvRi2R4TgA2BWckNfDQS2RZvHnY/ylnxzmnF0hC1o5rOSqqkAZ5WcFEJOaj/KSUxMBgut/XfAzvcpyK7UINN0yCH4MhG8wSkQvFsECMuSOPCfhLC39EoUo28dx0Rtz9cy2CPKPj5SWOV3vfx+btFtuzU5gBjnnoEO/ag1zGDAfbeTuoN2/16EFw7x3D+U4NNORCaA4YmoWClnOBBAuU7bXhHms1kcRD/85jBPrmd+MNbWRSGfYSo+4nc4+nNqKWZedNpU/SYajOkLSj/Now5FBNZ6MP2cz+ky3OvGHLJgfH0RtPhpl7EcGTtcswSFp+scFgMn2UoYd5pQhCT3om01Uq1DGem4Qm7hJB8eMe1m/5ebYtf1IPHnG6JRIPIz63RA/I5jnGq94a2n/z+aVJiSvLOUoNae0f8wBibZgSOJNcBs4SAl5CAqE35HBDD3gIkEQMqFdpm0OlPPmZbEyq+wrK0gdIvXUnYtQkfV08jyQ5f0gsIcJTw8qrhUunVp9JVwgNGJpqCgbP2jJkMnkfkw3bLYZtuGwXjUIY/YHPJDvKCYnzBCcOE7V+s7//AOPxiN35mYSWCUm7uSBOBdOsaIIhm+GUhyBbaaWVVnp/9MSGHsk0UV0cLMiceCnQg8dEbgVo1rfmGs1Cd2x2G2xONjg/O8PNmzfVWEEPLyFpGaQhFQqQCDkPMjdqzLCiZYx11ElSw4HUCmJGGY8opeDy7n1cXV7hcHGJ43GEBANR9S8RTk5PcOvZZ5VHeWtKTq2m9BQcx4LL44jDOIpSh3DgqVq23OgPrq7MglkztL2EK5LRus8WdCJQYrGMNDWTxRsCQdzLMcsBLiUgh4WACCjqCYRUMxmPo2StBjam9CU31kB3+O3G5bC/LThLEmUqwWPHiYJuseIIOVPzbpAShkHi353uNkhJYljmnPHMzXNsclZLVxZPA4YVV6AeC45j42Oz3WI4PfUQLjxW1GPF/jjiYj9iLBWHq+blojJLH9RKLOnMRvbOtnnBpl7VMK293vY3y1VTZsxi1hQZMUoq+hV7+7suy2Ila3HwmIGxmNKrfZtbuxOawUozdlI9wY0nrJ6Na9t8TGPfzdt4qiF16peH+ahVerxtUGvl7ltWowixqM+eg/QTCwdTu7zB0d1k08PgfdMs6cVKejOQeNuxiKD6T6k1GBeIEi7tIDymBOQw1MQzR/NyIs/N0wkDGHH58B5qZVztK0rl4E1Fyk3a16vmI146spbfYjwSiQzGsWAsFcc6Io8Jh0HCu3jRaF6JrBeK4UnCZiMgQt5IOJjdboOUEoatbnbzIOMrN/ehBHGtjgSktFXFvI0R38xVRqni9UPqT7i62uPe/Yfu4UMMP7TdzcK7VJ8jYz/qNnjWN7BE5O/tx7JOGxJY7FPdSdlIDdustpHAvNymNFP3I/LUj4snU7K7EGYsbZbzgDz8dLrXXekng/7s3T/DP//uP39it/GFC+7v73/IXK200korAff39/EPv/0PkenRt46GNOBvfv5v4osvfPEj4myllR5NX3/r6/jqD7/aG28v0LEe37MR1EorrbTSB0kPjw/xT77zTx675iZK+K3P/ha+8vJXPiLOnowibgNCA7Xs4MvwNG5elwELtZH8Rn3OGWmTsN3I5UAzkHBcUssT+EtucVFK7QydGXJpyTw2NOwl+WWdgloZx714FC7HEaUWQ5/8kG7YDDg52SkeqifCbHhgw/ZKFS+zxcHOCFToBSv1ktwZETh2xZ7cV60p2BJE6/naAbHi1CngvQA7FgzHgnucpB3YUqx5uPAXOOA5jvOjb/4pvvf7fwBDRD/xpS/gF//6fykXmuxgGcDzn3gZf/nv/x3F7ILhxibj5nPPIg8SyiClhN12g5xSwyM54HMsuGV1ryeQC6WbjSCjiuOaZ4JjkfDc48iOF1toYwVaH4khm9zbPSIKbyrseqdjS9WRfTmgV9wpQpFzHC3wwC0Pwx/d+3PIt+NPXzusxf3zWA/DUN2w4Bodiex9qP+idNQNDLMYRXDADPtv5A8Lq9PKYaBQqJ9UQkdMh/lh+rt7D7azCnQGQHL6lSbyoygePctqx1723LFPxzJVuDrex8NezqgK++XTrhHVKMPOhZpXGcPezTBI+oiFS6+lgljSjpwAlK49veraRgTyMxvxQC/jQbxEy9/mmT7r4YCd+yS9PDhoOCzrm1Jau7QpYcGbJ6DxOGJ/OAYP/4qhA3qGBz/XmPYb1gMON5RYxJCfDJt1Yeo4FiDcPo8Lj/1JOLl5A7/y3/82wIzdjRt9qaFfllrwZ7//B3jrO9/DL/71/xKf/PIvwjDka/cVoQ/FKpD3ZzT5UwKtoVtWWmmlD4Ce3KPHktshexIOxqLHBzEAyHILXZW0zW6D7W6D7W6L3W4L1/QY5lGrKcmAORVo5ejq0g7AbbWp6p4NKEcx9DjuDxgPB3lulnIkYRDykD3UC8L2QCMgdHW1UAjjWJZWprYquY4e5AFIDDiExQ2xTpLeNiu+ymnCmbQJC+vc8sJicrRNSbNqbJ4OopIZ/zYF1OJOkm64ZEMgC1GCKE4pEbabQfK10BNq6LHRn9vtBjmLkr5RDyqlVAAFhcQClCv3Ri4kG40oNztgFs8VtYUo4V6pEKk8iYrefjfR1qnySnJoX5g9liAzo6rVrOlwZmAgrJsiHbxYMNzt2TiqwUexfi2dv6j1LFk/h5aFsJkw/TXublxqGj4mjBUpvB2Ud5uxTgjcPTSjFjMSqHXZ0ANkG9VosGD1t9+56cE2UKiVOdeN2nMmMyiCfe2dlSjc2CCAqxgsMMzQgy3Sk9Spttwbq2RTCPwXVdiXVMroDi/+3QxpSI08WttA+0GpFVQJCewuE6kz2tENtvY5ZhmDuYpHD2aJWzrUrAYeBSkl1CE3jyCmxKcEILVNCgxMULgiA5krchU/JqAkYAYRqvyJTAkpZzXwSO7ZSP6Gb7Rh/UJvmFj3W1Z8uxkw/Evx0bQn+HuadxYsj/ZrNgSTxzOAott527NHzSW2me9dJ6600hIxM67Gq0feFH738l3cvnz8jfmVVlpppY+aCpcn8h6UKePdy/fmaWiTNjjbnM3W0rGOeHh4iPuH++v8uFJHzIyL4wWO9Xhtmncu38HbF29/hFyttNJKK70/qlyfaB1NlJ7au991a+0HSoZxPrYIDddgN9Ip+Q1nIkIamucOuWATrQ30R4SnQtEeMzgkinhvsWd6IaseJewHh5tW5oHCQsaIN49mYNLBE826RPDKooYlUzhhEWhqPwxDjgYfhjA7XhjbLmBes7wXMWQXQf+Ow6MOQ5Z3h4tLlHH0s+btyQ6b3VYNTEhx+RrwFO5wKmLBmYa8xenZScD10Lzb6kHzkLP/bR5UBDOWy5B+mM4Qw5aAk07RIcOnzEjEDTAcs50CQMsyivAQx/YyvJNjYwRDEhWYwqddXs0mINahFV/1Ap/js2wYspZZ2Zy9eBkx33jOPQ8Fo98ED9qzSi/JY/JHKzPINODG1xl6gDnMQcqHy4EnzMNDdnQysjMol6uiixGztX8JSP6AWpmh+hSnLJNZomDc45/2eLf+Ppea8UGtTuHwhcBdX+owZO1UzKS4cZBfnNqs/gRwqXIxUWXLKoukRiyZJEwWhzlWznuEJzNuawYRACGJhxBIPpW1FYhQ1cu+WQPZfAlmsIVy1z7M1S7KTgZBaAeK75+WbJz2De9joyMWI7OzZ595oqy5VA977sMjzrnToTXFkLshRahlxOHiEnW3Bb/4/DWXH1daaaWVno6e3tDDFb3kC7isvaVLu9ltkLcDzs/PcXJygiEq51mUY7EQVDd2VQ7RZdHLWpw4XCujeO44HgS8STmpUkZAJRyurlDGggf372McjyhjARfxmlBLRUWVeGQkGu7NZ5/BzWdu4vT0xL1kyGJTxSODWj+KdwBCGY+4e/u2WHWXEu0lrMKycBGDo4cGAoZBlNVxZPVSwq6gxINuVHhoCgZQmSTmY0rIWRQA24QMGrurGRCYBbwujLaYJQBq/SlKtSkWujHRhcfjSmr+lj6nhKxtlXJGzoTNRkKtNCVcwq7cvHEGZsbl1aEpt8ZbIWlrIvEOAPXUQrL4J1QcKrnFKteq1u8MPDwC9NCVLQsxEQ+YXb2yQ/JobIG23poVclElwxVK/a4gWJty9MQhNwAstIX9b94zzKAGtmkIG4WoZFtfATMqzDOIPjXDDs3LWZt83yl2mCjLBLVmr518yMamtosrkdRcIYIZx7H4poitMG4bhGn9yLUw3eRWBpLFdYFstnoN2VvEur673dNyqlpipMQwoyJWI6Oc7JaGNCZpHZrvSgLyVN9Krigyc3NXF3VxyjroNF+ScDNDTiiFca8UlALXyZP2f1N0mSX2qmVIGnJlHMUoIuWMk82A43HE8Thiu8k4227FIConUALSQGHsw8fC8XgUrxoHaZuHF1etL8N8zkDnVGo/N3LrYdgMEstR3VlmHcdiiJV9fyEhlgA+Flzcu0JlmTfPz0/xqU+8CCJgrAWlVuwPRzGwGmVM7Pd7lFKx38tzmwMtPmVskN77xzSISqf5LhCH3x6jBS/tC8KOWvozuSzlBscE4WgfTjNqqYKOL/8TEjLSe4iKttLPDv3Bj/4AX3vza9e+vzxeroeYK6200k81FS743R/+Lv7w9T986m+/8PwX8Fuf/S0M1K+lb1+8jX/6nX+Ku1d38fD48INidaWPAVl/+9N3/vTaNA8ODz5CjlZaaaWVPjqqXPH7f/77+E9v/qcn/ua6tfaDpSmG3DAPP9AMgFbOCZQTtlsJr22Yo+Avih5UxZkcq2p5G0bSQgmwXi4TjCZag5RRsIrDfq+XzqrjUWYEYGGqAcJ2t8PuZIth2DiKYRhZVfyOIJir2DtUXF1cgIvm5wemjaQKtRcD6W1/0vtHDnmyH14Sx4P9kB/a4a557rC7TCne/lFMr2spsjLQQqKHJrQD3e/+/h/irT/7nj4ifP6v/AV88itflvIS8KmvfAkvfvbnnIfd+SnOTneIHlpSIuSUsdttAg7Z+gfA0s4JoCr4LcM8tcgpAVVxMl5Nfnohr1YGjhXAwfFe8dgh+TrO2SGT+ibAlx2GjObRoR2LWF9uN8ni4bQbdvDkfysvAL3t175NTBRmcNMMU5Q3ln/8XABY+D74C5kenmufjN6i2wF8xCKo+1VwWDm8iJcA/d82zHpsuCueHJ+P43LpcLxrqYgh66esGHK7iNfyT6FL+aG/nX2EdL3hTpOXtjrSdMRYX7X20W8SsfbDGtpY5wYicG5519pkIpdsk4dmp5QwENRbdEVOCZshu0GGpG/yMTFyZdQq2HFRg6vDUV52nlPQzn1ayJesBldZ5z4zwCI3cjMvRiZbAnCsjONezuyYGJvNBs/cPAORrE1VeeHgLdvCh/ulXR2ftbCfb1mjcexQNMWQr6HHQcuP+86/l19SSvjsX/kNfPrXvoKTmze8DblLe01+QJfAHj24/S7+5P/+lzi/9Qxe/N/+F2y3a7jTlVZa6f3TE2v1i3MXtZ+uCGq8vGG7wbDdYLPdYrvbqveMLO7YXOFCU2rZJnSC+Vey2+CVZXErYxGFm2WZLWrIMR5GjMcj9ld7HI8H1FEXEVX+xa5BF18ChmEQ45ONKOl2cG0x8Kb1rrViPKgBSViIoV9LOm51iRpiUOajXjVVJJsGI3xGG2QiqS9XjoafcwWdglICOwS3A/2mfJgsLMyD3UK3rGQhRzD0yEiDGOiIoYd4RZGD6ozNdsButxFXh2PbyDAzykgqQ4AobLSspbl5i6jVDD0kvEap1d+bHE15J1102xar/RatsTulThU1U0bd+4wapYhVeFB0Nb3UR8N4FEblooqbGXo0a/LmaWZySDdRANnVsdD0USkOA64ZeZgmHjMN75ibPFVxpLYzDPqzGv5kO5pWOalcCk95CwYloc8xuOnhFCxzZ8OIpg+0qwdlX9mMGwwCZDPr40R5NbmEzUFnsEvc0rPNKPbE2n0aRxLNtFvH2KBfJgIqTdIC3cZRd0jOJYU5zpVowF0Z2ryUE4GyhIMRUAJIYMgwIdCodeUaNgxqZKOGNwSgqHu+IYth11AqUsrYjEXGqirng47jXKoYeyRCJoBzQspAGSvGYxFDJJLbJ7vtIN9yFo8kiVwpr0XMnYqGS6pFlfPKAFeIM6XauZP0MTmRp7VPa5npNntJPe6/tvZY0rPjmOqZ0JJjJ/fGo76f99DMYiFlLCjHcYGDlX4WyDx2jPX6PnD78jZef/D6R8jVSiuttNJHT+/FmwcA3Dq5hQeHBzNX9Xev7uL1B6/j4njxAXC30k8TVa64Gq9Qall8X7jg7Yu317V1pZVW+pmlu/u7uLu/+8Tpr1trjS6OF9OjzaemGYY8faC4i11fSTkjDck9MJv3jGS4DyIOar80UJXtAhJBDDfAfpHIUC87SJUwtaPs3WtBCznBEJeyhvEIPpQ8PLVdJAr8TCpmGKJdYjOYd45RGPbV5NGJnMO7BUxtXm5gymO2zAqdQXWGhzIzjpdXckNfMeTNboc0JC9n3B+wf3ihGHJCHUszwknA6c1znD1zQww7Eqm3Zz0c1nSJEvKQMGS5dFlqxCrZbQysKbhyi8AAw1zZD4jNW4RhoTFcikktGlH0GHKPGRv23P5uZUL58TwMK1Vm7WfDljSMR238NsOLiLEaOhzay3kITMTWs6QRG+bWyRZHLgPRkML51oyi55HeO0jrZ3auQKHeYPWK3UTay3WRoZZnV2/PYyJoxUqnGHKHPVtY8P5UZFJ4A5C78Zh6DBnojakEe+bIdhh6DWRMiYDKXRUitT4c+6GWOxGBnbHZeZmMaw0rY2c4FPp4ZdQE95Tv/cpwY8faBXetnBpWTUCqLJd6M6thFtTQQwztamKkZHMDdIzrZdyifVzDug+KT1cNlUOkYcArt/KT8qPGe1LPgsqpXaCeyjD2sUXQd9o2y8mWPovhY2bjiAhnzzwDPEt9d+r6dyt8MtRCuvawloL9w4fYbDYopaj3p5VWWmml90dPbr5dq+i77jJNJyFZgXBydoLNdsDZ6Rk2my2S3hjPOSOlZuDRFi8KazIDqYUI8NheGFFLwWG/R6mM/X5ELRWHq0tUnQi5Mo56c7yUsR0oukLEqvAzLMTEsMk4Od1JDDIAYk1pwJEquag41orLccTlcVSrSI25R3DPAO4CKtwOBwjDbgNKhHI84jgWtdb0JbsphbpAm6c02+jkLGFRxHJSw0ro96SxKCrH2/LqHitsIHIalCfbGMnRdQuvkkGZsMmEnAg5DR470Y0/rN3cg4L8k8xogRPGQ8Wduxe6cJdOETEPDPWqAETYXx1NAtKtVKkrNbZ7U94n2qvrN36Ab2WBVaym2MNjyjU3YVWtR+WwvHiYHo3LaUYS1ifZ+oMp6c0QZK6pUvskvvX+GPJD/DmnJaXcy+Slt0ApBeNxdKOTKDY19A2bm4phGHB6fiZtW47gUpEKoRbgymXQV2HOpMldNn5cK0owQEhJQogsfevDJiib4GAIRM01Y9tIa0gUBsaiDkRoEO8zVETxDrMKQVmD7NNZjSeY2A1IhA3uNnH2PGcARNhsEigxjkfpk+VYUMX/CwDCdrcRD0Batnl8oUTYbrOE6DkW9SQDXF0dMR4fYLMhbLcp2qAF63OyLo0BhM1Wp2pNm9US3LxippylD+ucuC8FdRxBew7yppaFef5ICYMagGy2G1xdHdTqWuLJHg8jri73GAYx9spION3uVDnXrcmNM+XFxpUYQt2/8xD7/QF37lzg6qqFV/JNyUQ795Ex0Z27FPbdZF4IXasnmrxY6MvsnbHPyQwNQdFNI3ebS9uAWdaH4wGvv/Ya8rDGV/xZpUM54He+9zt47f5ri+8Z/J4PP1daaaWVfhbo+3e/j//96/87JhAs9mWPq/Hqx8TVSj9Oujhe4P/6s/8Lty9uL75nMN65fOcj5mqllVZa6aeXrltrjQ7lgIeH9+k9ixveaX+3U0yIF9IhYTNsBM/QG+Ny8BjwYz90CwfDgBzWurdne8PqfXQEMzDaRbLxqHig4o8e/rkGnMwOlxXfJTiGnDJhGIZwgY7D5S4DcxkFjKN6KLa8Xcb9D4RqABBMByRYu9xsn6AiAVKMx9eWX1JcuV0OJAXB1JsAGh5jlhN2WAwAh4dX+JPf+Td4ePsdwcF2W3zxr/9XeO6TrwoGnAm/+Ff/Mj77F38VWb89f+6WhGBBM8ZBwI+dP798KE9qYVzuj4oJ9t4P/NexoBAkhHqop8E3drHTzRGmBhHajPGxVd0zIfkZjUuA3vgBaB493MNwO8mAG3lE8v7YsM7FQ+v2Y/a84b+PP6rmeBDgDycgWBSg9TMzRJrUwcOA+MOKlBI2m420o8RxRqnWr9AZNvhnsaN2b3QsM7thgkJvXZ8UXgNAGEWicrUzoMR2WVglH/BPkIW8MayZQGTnKY1BCv80lM/YaXxdZwRHUI81WQxGSmn9J/imQM451MuMbORSYs6CP9ZSPfLUWCrq1QEpa95Bts1RR8B7gYbF2/yiZ1iWZ3dxkYGxMphHUHQIHruOeQCBnFElvRg86oVshl6MLRXjOKpHJjXUy4PkZTDpdqO8sLchM+NwdcA4FsHMR/azhSb67o/lBsDkdYchz6nrq9dl6PnAp/ul/KQkxZDRxlFMbDnefOE5/Nrf+VsYthscyoh69+41lVpppZVWenJ6Cj99YeUmaoYOOYmxwHaL7W6Dk7NTbLdbpJR9AQU03IFPsEszIoUVyg7UK0otOB6PKKXicCwoY8H+4lItsM37Q+lujC/Nz3LwnHRhTG7Q0M33gS2z/j4eC8YQrkXWlKAwLHxrbrdI47iZdbhO9Z2rMSAqRG0T0KwkbYMxEVen3VOnpNuib4fl5kHFNiV50Nv/m4yUCZuckBNhyANyHsKBq7VJMNDh5pYQUAWEgXKw28uq+boirF/q3yMHJZ1ZYrbpezfyWBJqMAiwtdJ0Mgm70B60uIutHcWAqAaFidVYoG0Xqxl0hOIpaKbNgCL0tYXO1unlIqWgz+oTDgrjrG0nOsNE+Yxl2PdywK6KULRgJ2oGvc67vMvDgEwAWBSzqn7tor3EbKQS4KbNk5etHa2f0KT+bYPZrIvly2bHElvfxmdscVWdNKwSk9wKaCOHVdltoYmIyPkRjx5om5sg3qmxvFswZ0JigBIDlXwj2nzTNNm4IRCzghUEjG2uAqtBRK0AZNy5IQGxuKEkgrm2NEvqlPS5+sfLg8pTDT3MyMvHUFHgwV3htRBD7s2GSIw81NBjOxYcxuLtwhqe5Xg4gitjYIjhVyK9VSO85aSAhNZfPN4UHK8OAFeZfzhsXnSL01wmhoaI/cw7wlRbn42Q1v+m3z4RTfty3NIh8DwtqL8rAAhgdHVxIe2x0seaKlccymECKAFX4xXeePgGfnDvBz8mzlZaaaWVfrrp4nixeu34GaNSCw7lcO37h4eH+NH9H+GNh298hFyttNJKK3186aNZaxVDbjCy/0JJLp7lnMTgI2f3ImHf2AW0dmI2JcNEqeFLEOMN8xhcLDT04dgunjDaAXfLaZF9C5OQDJ+ZYAX+BzUMpRoWc81BYJdBh4FIWTXgYg1DnmAWXUYBp1/AKDxlYRwP+w5UNc8bw3YDZsbVvXt4+O4dEIDhZAcuo+NQRAnPvPi8e+pIyeSS+sPmcGnJMKoubLbhRnZryQ5CHfM1GbPjkrO6WL9YMrKIAm7ZtjcxTy2bQ7rmfaO1g11KrF0zBIOQUGy71BTLXgJXnYEZ59QZhjiquvwFt2EwpwZ8huMcf1M5yol93LElQPeLHNxrYQzxLlFBEk6oT9raNsJ3U9wPhp+ab19qCQ1D9s/nXlCmeUaf336jzr81GVqe1OTMJhdu77V88xg9NRji7hfNIxk+S6Bql8cav7MuEDFow6zJMGf2sVohOD9AGo6mYe2kdfVLyToG/dxGxZASuvnYO0KBe+LovZU7W8J5kW+joUctCWWC7VuYb87mGCkYfunPRMnxeECwNWZGHYvLIY4vaEgscoZCPWKjGM0Gy2Mw5MU31P/q69ByXp5fOGDgaDSo31sfH7Zb3PrEK3JmUyuOh+v3QSuttNJKT0pPbOhhNhu0SUg5YXdyhjxknJ+dYxgG7DaDxFRMgy7+spq0g0VZWEpV93liDSFrDiXIAb1O7izeOS6vrnA8HPDwzj2UomEAalXr7CrunAC0ZV8XdVOqu5WJcOvWLdy8dQMnu9Pgwk++TGSxHDWOWCm4vLzEnXfuoByP6kGiWSmbgpe0eDtaJ1V6xv1RFi4PtyLyqOq6gwggcy3obDIqycFoThnDZpCwMWrBnLLFNZRFcUP9wpMtploWZX0zDOq5Y2iGI4ArD0kVdBNTotSUgiYcp96aWWMhmr8IU7Rcj2oH/mwtE3Rb37iY3skiN2bZcJlxTGGLXVeBKl4GxKCBWhOzxd1sze6Kui6msZ/4fsH4U+ZMD0zsv2gf8VW5+7YJptdXCTHfoA/ED1wS4UA46KFmSDNLZnKuXYb+4XwT08ficyWLACojKCdsTk+En3RAKgX7h5fqei3UJ7Lo4tBtpAXnM7eJjVV1pajfJp1HmNQVW7gFEfuKGSypAisbjYyK5B50ck7IzplYko9MyImR3dK2eaGhLOM7Wew/Vi85kzpODXdSIpydZJTKyHsxpjkedFxro5trS6v4qIYd4pVHDNEsJmGUYdI5MfbX1hc1NJDJcxxD+8E7lHkpIfPEk2SOON9tkBP55sAMO4qOqVJYbrcUMcq4PIx4cLGX/FNy6/6Liz2+//23xbJcgZjTkw1yTthuN0iJJJxTSsgb8WxCOQHI2A5b0BZI6QEYdmNGOwYBrKCCjZ5+DEV7d+tQ8Ze5Yj3tp90nswezTPtnYex243s6J8IbDYCAFRcXV4sGYCt9vOjB4QH+2Xf/Ge5e3e2eV6548+GbPyauVlpppZVWWumnj966eAv/4nv/4lqPLWMd8e7Vux8xVyuttNJKK70fclgmNcMO8QqwlVAoOV5uaQeB7UhUDR8QvVv01+4MY5E0Bcej4BuHyysN5w3Bmmt1jFKoRw66MK7hQO9kd4Lt6RbDsOmxTcAxZIaFh644HkdcXVx2IWMibBuxQcMa7MyyFrtKzwFPIDd8gHq3jdiiI+F2gJpyh7PFy3v3b7+DP/3Xv4tx3w4UUyKcPHMTX/6tv4rzZ87x63/7b6AcjoLp54xnXn4B29Ott4WHkwit0YUJ7zqAYYEtlIngfu5zuAdSDS92XDA8WyLPImJjikPbSTW3i4AO3USQpzn5bj8jT6H0iHMawN0ZuHQ/qHvPC1YY02Kap5rJu0446EHLDkNGwKbUi7E1goX0mLGh70OBvcFFq5ScYUgmeZCjpJESiCvKgUFcfXRQYKXlxDq+vUvO2xBAdC8du1Zro9gm3PHb0EUNsx6EaR4tfNSwGKm068loZyFWdt9pHm3s0WBobDKhJlJcl1FK/NhwWs+2hZdnwZZl7mL/xnFtCuVyKz8arHAnI5OG2GnEOngYHu1PmyG7N3BD4kF29mVnZQKkMzPGccRBGbDLlcyM47Hg7t0L4TmLYdAwSDjxnPTMSi8fk/5tF+VyykDmJnuti//ph1rzETK7UY345/IsMv/C8p0OFJ502msofsbhQbe8WF7whjwex6UZdKWVVlrpqemJDT2S3jzPQ0bKGduTLYbNgNPzU2w3WwwkRgMVhMrwxcIXmDBX1soan4/9cYWGHVAlfBwLDocDjvsD9pd7tci2RcluqQOAKi1xWuSwGBgRsNttcePGDRAIlWu3QWifqgViKRgPRxzUe0h/yNc0c+6feB5cg+cKV4bNNlaVBa08Efy2v31EqojIYa/9nfwlJY2lFiqYdaOUB/EksN0MEp5hs1F5u4oGgliCEoDC2iZBYew8JIAnSpXFuhTDDH0RFHn4L6ZUm+1sMBgWTvw7aofAMOMObYuq8qwS/mIcxRik2kJubT3ZQLmC6BWnTgl261BLlrQtODQMtT7qewVEl32mCPf5TtbtVgYRomK6pMLHlmp6KfWpTdZk+sZjlA6algJAw4uYS7c0ZBFZ3DgsZOflB14l/JC5vbSxDw+9MteCg3I+tU4JypX1V1fSrUQFBKw/ctVQLrZHiQ1iZVp7kumFasGNaB0MMPXtmQcCVcJQCFQYJTEKo7WIzlm+baisrvnEGMrc10X5NcOrNk8Kl8pPmFlYx+e8qzTNnvQmRc4AZcKQBgxDRjOCkjQji6HUkWQMFS5qRFexP1S/UWOlj2PB/f2lGIZljaNatshDRi0FKSWUIrFqNyxpMqthGUiNx/p5wbcqxL7xIrV0ltiXJqfJWJkNpukv8846GxFLQ2QyJy2TtozfLunfUfhtHMd+DK30U0GlFox1fHxCpYvjBX5w9we4fbnsRn6llVZaaaWVVhJ63Bp7b38P37vzPVyOlx8hVyuttNJKK32Y5Bd41OW/Ycmb7YCcsnoJBex2+uTrHuI1/IUcTfADTTkPFa+9pUoI2zIWx4zt4DLimkunanZB0TMnIG8yttst3CspQw/QLU/Ff5nVm0eRi4m1Ttz2N4BwCXcQ/JK12hPgh+C41Qx4jFlX8Ygt+FbwEK3flcMB9958C8fLZlSZiDDu9+BSMWy2eOHTn1SsOTuO3ZC/YLRimPsU97D6Oq4aZa9YF9f+G+5/cXMard+1OA33ZZgHEOYWEgJc9ZJX6wVeAaAzfliGaSPSY5cke0wqYvLyI5g7NOB7ln/XzjSBqmJaojAA0APOU/K+27xVODcUkGvHkKffTfLC5LmOEffwnghck34/ySSOtSDL+K+329KAnBWuf9MEQ/Y+1+dsODIFowCi1oYyf5i4LM2SEK7zzh78j1ibG+ysXqGT9cdqeKLVSeamNp50fGh/tPmkE4Nd/iRSB9sNyLQLg7EX+fd28bV2r1U2BKQULiLqTUQb69qPZJxVoBIq2XwroWkMKzZeKlccRqkcqdcfZr1cPVQQJSSdO/Kg6wMHHJjkgmcPBdscNMGQJ/MkbN6Icpt5g1roU4tAcWjQaf9cSjrrwo9abPpfudbrh8BKK6200lPQExt6PPfyy0hEODk7Qc4ZWW+O55SByqgJajmsCgwFy1493C6V1SNDRQKQc9IwBgWH/QEPHjzEOI64ujqo544jahGraFEiozt8AovdttzsN3da8ZBUJ3oaCJT1f/v8/9/em+3IkiRZYkdUzdwjbm7VXdULpxdgmnwgAWIeSIAfwTf+9DzMYAA2pvthCuwZ9kpMVWVldd4lwt1MVfggi4qam3t43Hu7qrNKT+JmuJubqelqJnr0qAj769UVv5b/pSx4ev6A5/MzirqOsot69WMzMCxr5iUgJ5u0tPx22meSi5rAWnJj9cZEEE92hEkFGxZyJuv34+RvegCkehdyo8tiWpp3la3ZU93xibxFW/ibdg576giGsynE3VFYqFMph7lucxd31TxwiFrHPBwUbu7BzOCKdzejnHTCUznGVKxwQy/kO5bDVa9myIYOkLTOzRXhF2+OmOcMqKaXwUGPQygaxqesIkQSl5CmbPUm1f4kmUp6Wzf4EgFMvnC/meJsat76jSXSxD1sse1U6DDlhDIlFRWwuFOzVKyvht7IlVGez0BO0hGIwOpyw0Q3W1GOLdJzyKhVa0rWn6LFU2FBQq3vm5iraIiQDsEgs55VmVCZUWtCrRlTBhIxUlbPQZqH87JqmwBrgRqU5voOOq7EAmakbly2EppB7HMjPyMT4+EgdTNNGaUwTmeJnVpqaYMJ8N0b1WJesk4MdCDlTJgnYJrEq86yMk6L9kUwciY8TE0gIaro6nM7N4jJHLuYqKSicgEVQimrh2xqraJ1aRMNmzzomEzmccVbIEHCZ63enKVm0LP043dPzxAxh3qJ0XfClNWjkwpenk+rlGwj6Nk4ZuznrZbnPQO6PbzbRTEhBIc3V2zq+B64wE0Du13dbhFGMVOsxIEfEP72n/8W/+Ef/0OItXwbS1nw9vz2XzhXAwMDAwMDP3z8zXd/g//0T/9pM09o+LB8uBm6ZWBgYGDgh4eHL78ABT7TNoOYN1QLR+JeTCkunQLGBxpPSyRhA9wL9FpwXhbUWrAuJuyw8N7KFe4s2jKEL5NDtojJ4VQCMnwj2JZD9s0rziPL4uaynrGWtdvk01aSQ16c2GlfAbQ8dQvOG1+nJr7wRdFWbz/7b3+Lf/jLv8KP//zP8Of/+7/rwuGknPDjP/1j/B//1/+pnkMaOzwdDvj6xz/CdJgCaxzZ48ZvcKgD+RO4NM1yW1tlL4p5Q9mDptSiQ+u5xunEMCoeqtjvr9du0ouhsp3D3OQz3BwbqmqzcSzURFg0JhLvtjk3nxAdV6q8m4Vxrhpiu5Whb0v/Hu9vn4ngeyxf4qtsIcI4ZO9rfYdjIgmlrp6Z3atOPDV+rkBdCjR2SMsc2QZVhofmsevY2qINJMuK6Vf67LOfRJoQV1tbCOGWrA3D9ZsmhYX7Fu/H7HylnVdKdQFQrRSLE/JgaUYOeQeMLm9S5Ywpyyfhy8WzcidE8ry28dSFbdIMpGThUpQHrsJ7G4dMiTBN5GPIQ7t7UcgcwzeeldSLiImguHYMrefC+6setwFlop/QDqyNWnXTo4WFWVapz/OqubH2Vb7eOGVo+ddS/d59Ne9zyFqArj00+zvHtgNIx+6lC5rtlz6du7HHIW/ySvTSwB4YGBi4C3cLPR7fvEFKCW/ePIohYx4XuLpxay8UeRGQL3pR0seYGjmVRd0s0TgkTMt5OeP56Qnn84IP75/lpWFGkBnKafuQb0YlwXblR/OxGbWki6r9teQv5OihodSK83LGqiFi4hvEX7obFXd7ObQ7NKWHGeiXlk1b/I+Lweb6Su4jL3VZYE45YTpMmFLCw5w87f0XkL2a914aNmnSvG7kxXGRP6YeXRNK9W3Lby4K1ZuBGmOlmnhAhR5LEc8tQezR8uvV4wIQqyfpZ+J3zl+OblhsWl/TSFannas2WfhvYWwSjocJx+MMe+3KPwseQliIQIvmj0XgAS5SD5bHYDREw9XzkmySpAv3puz1rqH1GGeT9oumT9AyQac0LIZdUhEJ19grWlm6KSKzhO1gRrFKmg+tB3B/91vwcls7hMlPqxc1QauJwZrh6CpmtHx7NsEgtokDeTsmFRNk9RhRSgEnxrqq6EYnUbZ7hIhd+HChDO6U5zt512NmpDMBOTPWVY30Yv031AnsWbE5ruM5T9QJK0ppDyAK9WhHa1XBE+SaRgLYmNRr9V42UWnltOPtGiugy8XSxualIM4K9XZeCySOYPFJTJvNAfOk4g+V4aylhvZs9SPftYdaM3R1d8XQ5c1n2h4Ld+k68D61cHHspU5vcRbDjUOvuZbrgd8gjAy8JeL47uk7/PTbn94t9BgYGBgYGBi47x377Ydv8dNvf3rFEhsYGBgY+G3EPIln4XmekGxHFHr+gsM/X+hX/s6OGX9k82z5Lt4r1mVBKQXLeUUjHeIGvcgrRLGBERnCFXV0qHKPxiW1a8NMn3t2oWp+ZNPPDm8ddqxfEAZ2etpyyD3VwbqJKOUkHjc8v3LG8/dv8fP/9nc4vHkD876RUuPPHr98g6+++YsrmejzQrR3TuP95evOO503pQ+UGJvApaN64mKu8kJhYTny1bWq1xS0c7YccsynrJ0a5y83jisCcmHq+4QvQqMRmd0KQ/sri+vpUugRzilFgoNU3RzEVcIM+f10TcDyi831kg39lMIiezhhuzIRSDpvx1Dd3se8eAkdhxzT2jCkMraqhhkiAlLuS02bcXIFpOXipu7xH4y79nDVsf9sCx0/9kO9657G+xORc6lMFSBunuPVjYQk04KYXGKPhNw7R4QZtk4hHKq14R0b21rmfXNl28Ta+GaGLpV1D1EbP7ZWJhukW88LN9CKKiW2fnjucSuD/dSNN+KuOuK4ZAAVFaUql+7rRbGalBt3EQ6Fzbt7IK8jJu8tl6d09wht5u680QbeLof8yjnLzSxfcsiX57zudgMDAwN7uFvo8cXjIwCAS8Fai78i4ovCFpVBhPNSUEvBfJgxpSk8yBkoBR/ef8DT+2fUWlCL7MZ/Pp1V7SpKwpTE6Fptx/TGYiS3iGSp0jQZZsSlJB4wvvnmazx++YiH4wO4MJa6Yq0VU86Y0nTxmF1PC959905c7ulLwWzSlKUkSUUHcOWnCjmm9rsbxyQL/IkASjOQgLKKejSRhlBJUt5pSpgmU14nNNW7vdRt5zwgsQ03CGEnzCAiRjd5YZ+UmOEU3Yhdvteq/66GBPdxDsVFoggXTKVsP1Y3YDYOCKsKhKxcDJ/8dMY3iXLWPTPA3sHJ+4DVi4kozJNDyhmJSJTpRMjmXs6qyutMPs16ftWynE8LlqX4dNAmViBCmjMyMg44BM8NVdT7ROAk5qPtXJi1L06TxMz88HQSDzdFDcAM7fMZAGGt6i2krKoyNgMkxKOh5iMm5YRpziiAL8CbgbXr3YAI6TiJq8ZawCuhlpPck9mq92I6ZIZQFKa40byxTOITwndtWPN32SHkKcmjYV3BJJMfby1rXzJRgLiMYyIUtjimBYkgni6qKpwrgNWKm3SOJmp6iznKkDBNUkrNlY2hK9binAFOhPQo/X1Vjy6lVPU+An9etP8TUibkLN5+coaP/SkDDwegVOC8MNYCnE6qplbl91ra+E0AZk33vJoKXZ87Ie/S/3R8meFMLW82BRMvHPJsY73QwmKlDGSd/IoTHwbXRdpMuhHyNPlzSYxyGT+reu0xF6i86YeSaw7Phf6d0k8wtq1wBTukTky1m+zZ0W2C2xcCXX5ufE801GVMJp99Dfxrwl///K/x029/evX3756+GyKPgYGBgYGBV4LB+Mv//pf4r9/916vnfPvh255UHhgYGBj4rcc8zwAgHjaoXCwix3V/AFg1ZHPOGWnjjRm1YikFy3mBee6otWItxTcbGm/qC4qEtktb0Thk8jzILeS4ca3H4wPm44wpT8JzamiYRElCEUhqnvu6Vpw/nMHKhfhPyvXKvdEtQHsJ4++BzIlcJ3PF3/3ff42f/79/hz/9X/8X/NH/9G/DpjXhQv/kf/4f8dWPvsKbH32DxzfHtnCq50medniKkFdvn80qNG+/dx8ueZvaKha+KGvMqvKCvWdneIeIm8I6MLeFbOOQtX7CSQBS4CsR1m61nnXx3epPvrHXk28WDWlfY3ey8r62+VV4/iDlCBusTDyUkVvZIeIVD0dv7Y7m5UB4bsaylMbDo1FO5vncN9Rx3Ii24asCKBESxCs0obTmwiV3ZzckrZeq6XMtTbil/avnkL2zd/xv+9Rv1owh5OW3lk705gDIGgszNOxFlI7FegxbH32NohXSuFL7uTLJGGE03psB93ji3KgnslO+rpYBCAfMDNCc9D5wIYaHn/KzQ/0QOaebur4hPHJlQinCQZfCknf3tg8fazFvpYYx57+xl0HGTAhjpQPIwsUY85+c9qQ2xvTRKtxyaw7xFtJ8AyUt1NZTvjhiqrsasobLH3dPt4ITPAT3RSsRepLYL7p81tH2lFv33N5D/xKw4ZAh9XCb5R4YGBi4G3cLPeZpAoOxLIsIMeyBqYtbYIiaTo2MUiW8RZ4ymiqS1JVewen5hLfff49aKqoa5yUaJBcGW3v4d4gPRQ7nmCAiJTw+PuKrL78CGDoZqFiq7ErPZCFIYG9alLXg9OHkacn7kYOxbYYDwCb0UEPRw6QkM8qlPqZJf5+zTh4kbmQiXfDNCWnKOMwZx3nSBcO0eeizvw/0nd2cJ5hhEwxw+UhudFoRq36gVrILZba/n9QAKXo+qRFXNFSFiTsWa8NibSDnBedqMDOLNGGpqlY+m3uQCxqsk8UJDocXZatzCWchRmfWRW2ZICYcjgdRW1t/DfnxIgNg98xAQK1YzwXn06IBgppbspRzC6NDGt6iFNRKKMxAEqFHIkLOhJwSDnrN4TBJfa0rUqlI2m7eP5J4FKF1lTFUqbWtGSHcym59NGl5uVbQGssVG7aBCEiThqgpOklWgYupja1vdLZPaAugjYfOaJe5VeuD1pdi/tGEPwQz0tW7CPosW70TEYhZFvC5wtwDWn8jUod6SQxEi0qCKvlJpF5BqnjESDmLOMcDt5rnD4Q+1tWa9k8AxMizpLdUoDCwuoGt0XCsj0MmBFO2doZ7F5Kyy3Fe1SCvjHWBTzrMSPc2CGvRZtT7pNiN7daGREAmasY6bMIJF0MQARMRqk3xrM7RxG0Si5F9MdzHXVJBkww8LEXKUFZ1U2lPK7dnPZM9wrPLG34PF4eDEc7bo/u/Wd/uj3e9uE9oJysEs9H7HyNhMPAvCydHbs8EAQD/9Paf8Fc/+6tfQ64GBgYGBgZ+e/DSu7ZyxT98/w/jHTswMDAw0CHrArWE60YjGJ0P0K0nvtgnvFRKqeOQbYF2XVecTyffTNIWSAPnSP3C8VUyzMmJ4FGCGgkyzzMOh4NzzFU9ESMpH4VIX7CGHl8bt+CLooEzB3pOBJHzbhyznWthmykTmDPe/vzn+O//5f/B7//JHyPRXzThQBKvEt/84Y/xoz/8iXKsl1VgG9ho+xMrO2dUHcc6JL82EMZ9zTLQtnI1vq8y+9UA2gY2tNDugPJZIc2uPbdL30YRMwHdbv69xVP2tYp2vfFfWrep8ZvyXTySW9ibRN3dL+vOwlcrJ1eLcMOtpLCmRbLQISR92jZI2WZCdn5b+eyUPIS71FfVTW1yfnLBivC6VHXjWSldXcXMRGEF6bWUSh9T/Aq1Yn0RAFDiBtBY761NOFQAaZt4OkShxfSTcZXgTau2vtc4ZOPcWOm4uLE09HKKFSAccuj0gRNtYgtmFvIzoQkEtDCkYWvMS4+ls6GNN/VmY13CZTNIwmmziXNa+Bw7z0qZUngOhHTNY7XLW5hRNSIT6cZDDs+Z2KbV72X5suesFCmp94n2yOJGefpDj/w6Dsk38ZH2NP3R5hK2Kc4ftcqLl/Asd8/YYEQPJXuc7E0OOZ5P20RaHV90rsgh792QQuCV2NW2+drlreniUQWGLKMODnlgYOAz4G6hxyoBwNRIzZBgW0CaJlASLwhwlSNhnjISAWUteFpWPH34gKfnJ6AyuFScz4uKRsQolrQV5PYYmjJ0L1e6AGnxCCBGUQ1GikRFYXBhPD2fcDovOBxmHA4zMgjgJkV4fnrG+/fv8fzhBCTydwEh6YO3vQTJQnDMsng6zbOICuYJKSVxT5gSUpbd7vMsAoS1iiG7ns4oSzPAYggRUlWwqxutdNs6CIaIvwvDj0113V4mcsiMaG5GVHypqFWwaqidUuSfKeclMyFvLJMyy6QbCiBke0GrZeDhU9wY0pcrd8nCAkqYYZOzeGCwu6aUupiTlhnz3MGQvBMRUgWIQ5w4M2I0bIoZp+uySF9STyqlrFCLC2BxkZgTIZMGpWARvqzLitPprDH3iniLmIACxsKM43HG7/3kDaZ5wvFwQCkFz+uKdSkoawExMB9nFQAlgAm1ruBakTOpZxobFEnbURTB6yqxSVMiHOYJAItgQ8cZ2QI/yMUUtTIoZ0yHo4QEmifUUvH0vKLWipmyGJ3W5tYu2slafFV4v6oliFHQfQAoIU/ZPVMArIJ1FekEl5gixkDXX8g6CwFIE0Cmwm4T/OgCD1yRCUgTYV1FDEEMDSRCoJRBlAF5AiCxxs5cV+lvD9Tm/m24gPoB5r/nTEhMyCmQDUzehyURajFe1Uq38ZwyMFMGo4J0hlVJnl05WxiWZpg2MZMow+ETBBFlWOxGEFBWEZ6kKpOKKYv3jnOR+IjJvIskwpT0GcNw7z1trBKmzN7vYHVJ4raxmsIFEG80zC6C61RmsRx9L/loXJmHXpz0mntd2OV6YHeNYzsvGPi14VzO+I//9B/x7YdvXzz3H9/+468hRwMDAwMDA79duOdd+/ff//2vMUcDAwMDAz8ERJ7WNqNAeSnYpiUTAxCBE4GQ3WPuuixY1sW3vxsvic3icpuDm7RiZ/Jvk3Wf17P/sKWbfTG8Asu6opSKnIV/TEBHCqzriuV8xnpe4eICX0CN3GfgXLPcM+UsnI7+te9EKjJIsjBale/6i//t3+EP/vTf4Ef/5n/ArF6LAXR8WvOHEKshLmo2Trhba4z1E3ggP4+xQ0hb+ZTv9Q1KDObiAo5W191qcRDYsHO5oZvsrB6zZoHUA3HfyP1mNKiIwQN1wL1jW5qBg3bRgHrLlWgUG88Y3MKumECjFtvYJPe0UOVWTErm/SB4qmBoXy6Nn9W8KWuNnBMeH2aklDHljMqyMa8WBtUq/OaUlVsUjnhZKohVTMBtg2oMVa10qXPlEnaGURPDFuSlq7K2WIKvLSTxQC19U7jiZRWOPSkHamOafcyHuo8r4ox+s2m/Kg97TsQQ2dZuca1EzqSep4tcNbR+YM3CXp4+/LbkMUM0LxUSQpysz+kagcW5IevnVdc/ps2SSiwVh+eRCY9I2OhkogEVgOxxkBSuJRuoSde6Srsbe92gB0v6xkUnAipM4GaCDa8mcG1CFCJdkyHZTFmK9Omkz7Rk3lBaBYdWlPpryz3WWvaMYL+meaPZZP4usnenvOFZb7npTonn9I/HTRl20onfwyONu7ba5GMnD37NK4o2MDAw8BLuFnqYkW6GSlVjgTQkhSw2SrgBgu1YTzgvZ6znBW+/f4u3338vLwOiYACyG6BNICAwxTHCEfu/n8fws7oXmqcpD2KuFafTGR+eTsg54zGZwSKmGjOwnM949/YtylptNbblKwcDEWI0yvtVDILpOEm6D0dMU8bhcBAF7jwjpYTDDOTEOJ0L1rVgTYQ1r+hcmnErhNtk7a24MwVB2O0fVhvtj1sXwYAJL1/W8qeU1Hhphr+o6RnLWlCKCBJqrSjVXCKSZ5JU+CAiD0k/uWFH/duLqClU9XcKZQTaT+YtIGcge0gbMbinacI0zW4wisGqE6aUULnivJwlL9rHirkA039VVchFF6bP5xNqLchZRBe1SBghmAGXkniCAETAwlpPa8VyEpFEYQYlxgSd6JSCeUo4Poi46Hg4YC0V84enljcQDocJKWVZSK/qVYIrsqq0UzL3g+qWz12ziaAl54wpJ5SakfIERnF3elFEJLZUAVFCVjFSnqSsp3MBs3i6IC1zs2FYDWbyiVPS/tKU6GEQdhMnaqGOGJ4nEDZxT3XMeTfv7wdq405cYprIo7oqmap6nklidFaSnRfEySdY4ikn6URExzgzeCngLORC9yzZDjsfTqTPAPmbEeN7Wt+P59voChMcGysZWIMrEUYzFE0gwmyPJRGNmDeg6DWnCTcAEGNZ1OsHA4lFzOEi/NruM4fyXj5lCFDFuJXBDXAdAy1sFjyME0PrGBc2/9XK9TJaJdiDHJpReNfoDGJ/3llFYfvj5pa3fr+G/hEbkup3DV2ZI7wK3rdHKJGbWOqCn377U/zdP//dbzorAwMDAwM/MIx37X0Y79qBgYGBgY9B5ylj870P7RsWKBNQFxF6nJ5POJ9Oeokt5rZNbhcLmsoFOG8aqBcm2+CGniylcCzw0rboXUrBsqygdMBE7URb2KxFvIx4ON2wAA3jsZyvbhkWYYd4j5imSXkcCa0s3LOF+5WQuLUy/ujf/hn+4M//pOeQ/W7No2tYWQ0LrAi/Na/OfSVtknQnHS0xK7ds4IsrpOb9Cy20tYb1rkavBxKHbOPTJvSwN0C3uBqut71U7tEjnAMAZCHToSFtyNNOKWsYFOWQ0cpm4p6iG1qt2TyMjG2WrFIJFqK8lBXM7N64zdsM7BrOLmAhW9lVrrWs1dcjQG2bGNcqG7GmjJzlX60JKS8AqnozEZEGKVFq4ZKtH5h4xetUOXPdViZ51gV7TgmUlNDt4n5TS7/qWk9Oni5XgErknMWrRKSFPR1vR+sraPxwPNeFJiqcsWN+bT+OWt9v301UReGI9WPr8m2Dnno6Z+kzSAAVtHxY2awFjYy0tipVNglvGEDa+RL1Tpandl348YJ3bOPWnlUE5YIJsPUWFy/4GAvHELxoqGDE1pqaFxkAJKHJfcMnhEdOSTayWv1VeMSpnRtuyulPrPBcDs8SBnztweopPqK3z4I9xrpV1YZv97pkrwPPqyVMO+nFe168Z8IJmzr375u/Fxwyk0RECBdtbzMwMDDwMbhb6JHMg4U+faYcwosAeHp+wnk5y2JpKSoQqFjPC8q64nw+N2O8e4a2A/H/YAaX9i6LkAc/qxIcsujI7HEAZXGU8NWPvsTDm0c8PD4g5YQ3bx4wzRMOhxkg8YawqmEGWFgayUKipIup4nEg5WbkEAEJSd8JYuQeHyccDhP+4Cc/wfEwaz1UfDgtWJcFz+cKgqjQaxVxQFcHmgczHMTgUHN5E8PLjFAzIvv4h9S8ZqT2QiW0OIlmu9Ui4oRaQho2OTLDB3CVqogNWBfuTT2s9a0rtGaXT66cljKcFynv4SCGrr7O/XXW3o3REORmdIBAqgivYKy1oK56TwaQElLKkp9asSwr3n7/BDAwz2KMejxDM1rUejCF/PPzCetawLSAQSr0aFbIAzOYZlSuKLUZeafzguezxNqgOPdgeDiUQ55wzBMOOWNKGT/++iuclxW/+PYtSqkgEkHQ+Sw7BsRTR3DnBxFhzEm8OUhvkrbO8wROhIXFA8iXjzNKyVjOq4bQKPDJNKB9mVGenoGckeYZQHJ/EnI/Uq82Gh4FBFSZiLgXFZ04ESWkJP20NjWCN2rOhHlOAKq71bNnQc5mWEnfyjm1iZT95BNjqBKZvV3M20utjFptBwCp95Aq7utYnhHVyk86v7IPavFyInGYEuxUGSjowPEDx5EpF7nLPT9pa7z3lmpnP+qXWs1zh/b7YDCbyCZpXSQCSrSZ1RDPmXBOxftiLUCdJMwMWz2whFsC9xMDm3jZ88XDywBYVhXIcWtHAtzt5aRKklKaG7/ebA5PdDPsYy2ZvY3XIFTA3eff/8tlslduJDOu0Hk+Dk/rE/793/97vJnffFI6v+1Y6oLvnr77TWdjYGBgYOAHiPGuvQ/jXTswMDAw8DGIHi0AdIvsALCsC0otGgZCedLKqKuE+y61tMu30+/dSTv33EM8RzegNC8HkmjH3STC4eGA6TBhmiZQgntqzjkDJLxhLUYQsXo+DrczTjTZZqVLltN4rjxLyJUv3rzBpGGYURnn0oQSCLwv1yschHJwXNkra59DtjriRi9pPbhwg8IV1C++yt8iPNG63ZQp3FFHySiPq7S9esVuvHG3wEnR64X8UoqkJIKGtl6wWcLXC6xubWOmkVrwPFWu7rHDCDFfcCfxsnE+LbIekE0MwpGKa/1Gy7vqhkgoPxu9FIAZ0wSAErj2G9pKKViL8rTgNlYYvmEvU9J/sh7x5nhEKRUfygmVGROEW4+eQVpYo5bd7KIJa1cJHc8k/C8RcJiziE8Ktb5Gvjzg+eN1BdRTiqVvi+gShkkJQusHruZAGwux/beDlVp7pExAYayxKxvVFjhnC6fiyXQcciiHHpa9g1bOtiLR6rD1KfY8W9PZOPGKke5k/GXswIHk7MYKb/6S8u+edfa6agti4RhJ3ryo8VRqXrLLhkOWTZSSVhvm1nZKYyZ/UjiPzsnWkHRE2PqAEcuB+4waJ1kXkrvVKIBCyIOJknQRxR5hlREd0Wygzxntbq2Q6E/uifptIleOvfyTnxDydvGOCl2ynXeDQ7b30sDAwMAn4m6hB+XULTZa2AxADJzTcsLT8xPW9yfU84LzUrCuFXVdUWtRg9rEIlvfFLrwH99naIZsM9SCtWLHCBZFphnYScIhPH71iK++/lp2zDNwPB4wH2a/a6nmxaAAUEOL5fVlxhBNyXfJy/0yQOLSi6BurDLwcMw4PMz4/R9/g8fjA87fv8N6XnB6XnBeVpRaPLyNizo2ddwp1K0OQoGj7QKGvywZNrmQyktmb6RgKLDNZ9iFunWtokBfRJSjlep3MXEH0FTBZhhmiy+YzCyQ3JmXgdmFMfBFdwZjnhNySmq8cninNZVsXyHhe2nK30JF1NaKlCdMB5k4MjPOa8G7d2cwVxyPKfTV1k+Sv2ylHp+fFyxLwRqM69b/JBRInnNQpAvO64qzhk/JObuxIep1SWfOGbOKPADgmy+/wOm84BfffUBZGYkyEhJqXcSN31qbKIgZS1FjJwOHLKIEZHHrkFNW8UnFnAkPU8K6imKhrCI4MovXBTsA6ukMyhPSdIDqmKHZ1aoPlpVZxYBPHHw4k4wNqZdo6ajniUzImVBKa19TE1tcSZkUEVLuJyat79l1DI8vAnY3cqYgN9eC5VzEk4UKt8zzTZzgmMXfvNOYccV9A++hDWN4fEMXSVkaYcxhm2Tftyn8q4BLpIOTj77e/B+jBuvWum1K3j1afrV9i946JfHqIZ5t5LeUGDl7U7tABAxx+1HZ69XEYVnrP6sILKuXFq7NUA+dYluNem9u1W+NZO4i+4CQO4hysctzrl21/e0id/vJdQdbXwqXqUjwU3AuZ/znn/3nT0tkYGBgYGBg4CrGu3ZgYGBgYOBfDt0CLJSzUZJEPOsWLMuCuqzgYvwXg6t4HDD+0TiabnruC4Ftkdw4Zb+fnWhLl4HDCvSWn0wEzMcJh+ODcDMsvHfK2U9jrihFOFigKserjIRxpomcs2kL0s1jg3E600TIU8LjmwfMeUI5nVGL8OilVFSEjWfOxaGnH5y36blyWyDumAtG4No2PkmVm0UK9Rbqx3gbrgBX4R6b8KRfpOzCyDjHox6BnVf2pnG+P3t9wRfdAUZWbtlDTbS7bioDuIiFUEP+Qz0CAHHytuUqnp7PZxFNTL4hrVUnLHu2+G5Cj8K6Ya4njwgyBoiThtxotVm0Ds3zcltbb1xoShI63DbXPhwOWEvBh+cFvFYfT8LZyfpJWyMQL9Cs3GYmCIfs3TH5pq5M4vnXNsbVyqhcrARNX0AAr0U2lKY4JigsylOoH6t5/X9lUG51SqReDbpxaAv/GtaEtE1jnTpHSk2EQrH+g/ceUMcfC79s2SNwagPKPH6bpwum9ht740uakq1Wn5453nzH5ph+b/4yqHWucLR5P4rXdYS2121f1dGLi46X0H5Sf9zai8mTtWcWbcrhSyPUmpcroyrna5uf27NHnhMSO10u0Ohb3VoMQ/hs6BoTxXuF8nTCl/BTN6SsjD6QLrnnm9h7rl5Jwm9rXWvb3tvrt4+oixTbe3FgYGDgU3G30EPe2U15WcuCyox3795jWRZ8eP8ey3JGPcvC8lrEcAHUiNBEqhuY4WVkRnxQeMqDubbvMKPUVg5JXO3q9ewGPuH45hHzYcY0HUCQsBTQiUTR1VkrxzwlLOcVp9MZZS2Ypgxb1JSFaPEckucMIlFcTznh8fGInAiTvqGWWoCa8Ktf/ApvU8Z6XlBLwem8oNbSQoCYyKObWUSldHT1hmCcWL3oicTNwAkvMWbGuqiil0tTVbtN0N42tazigo2a8QwyrxyyYCvHpW0SiQAmTxnH40E9nSSZ7CziHWQ9LyAAD5N57hBXg796u2ItjON8QJrQGzPeFy5fedGQb+pQm7SwvRKBDDE29f2YSDxEtLq+BvJJihtv3E8iN3bn5aKy1qurcNXLgo+ZlDBNE3KeXEAxTYRSs7dNrRU5Ed68OaJyxfPzE5aFYQIMO9GUuTnNSCocoZRxXhacTisoZ6Q0gXnBqvFEi7pMbPUofWcFULmgfHhCBcR1YNVJCrDZQSAH42QqJ+kLxCwTF2YsXNUwT0hZyv1wnPDmiwMoLXh6/tBEPiFsi+WJQ+gVwNwtJk1vQiLpr4UX1ILW13Viw11n0ZiBsxqia5HJTTJVMoFrAS8rgIo8q3BJJ0xNtBImwbEzVf1HCc1ANzd40mZsRrQZ7WYYM0CdVSi/TZlQGFiL1Ekp5G4hQSaaQZsAWy90o9kfED7nSORhbVGKxVgkHGbCeRHhRiIhGkxUw9yS0hC66vlHPYNYzkmEboC4+ENlHKCuH3fGT3eAwgG+rGMm23nAoTRtEnKROFmd9s3UzYU22BvnMVu7+e+u3sONWcHAwMDAwMDAwMDAwMDAwG85jP/w72whk88otWI5i7CBdYE17vp2TiJM2LsFwG7lHbro1kKqOs9Uw5UuFoBzazZtz/Msoo40yeJ5Nc8XvedoQLzK1iKL/Fy5eb9OjasQHrDxKykR5nmCeSwG2+YywvP7Z5wTiScTrrpJLnj0iOVGK3tkXC45z8jcbX7RPZzdBjX1nsGrbNDbXyiVEB7OLSZbVBbCxcrdNiuZx2MCZQlF4hutWEIwC5dXQAxM2VUmqBV4LtJfcmbk1Pg2K/leiB65GD3Rs6mryDEThbbz9YuQZJe21UurB6/kSCpROPVKG7RfNhyX1iPIwne3HUQpERInL7KtgczzBJ4Za1kheyH7QcNgVBKv5KRxbcQTiHg4lzZJYASvOhXo3CWYeAQEqgxeFvnu48RO4/Y39skwXEXY0nxYVN9zqt7Uk6y5zIcMLBVpXRA3BkdhF8G6RRN8+fhTLl63Faq3bMa6tHWCrTjHedSsvK2KcawuOOk1RVhz0vUSK4s9jrpUYz26t2hfzIEuKDhZ7EPPRDCxm3dKL/GwkdTjhomNavTKrfWqzpQu2qM9Sfpe6rw15BlatYw5E1CAojv6koo5zPuNt7MOZVtnsaU7CukD8H6WSTj6TVNc9qGuDNx0XdWq0Q50PlK6e27TI2ag39d+k87thnscsyHNrv1558Jt+nTZBgMDAwMfg7uFHoA8k0S3SVhLwVoW/POvfoWnpyeU0+ou7EysYCZUEyiwv8S7uHWapj+IXVASXAYghBfR3LhbtHA4JcLx8RGHhwdM+QAL41BLwVpXFG7u/3LKIvQ4VZxPZ31xyaIyUUIiRkJBygn5cEBKhMOUMM8Tfu/3vhLjIyXUwvjVr56xLAX//Mvv1djZ1JwZQFb2YK13pWKZAPnKrrx54B4vbNGY5eW5NcCZq7qPKzJxquyhWmyikdz6YK0zeWGbUWU2wDQlTHqcEmFKCVNKOBxnPH7xKOdOIqRZns9YlxUfSgEBeJyzG8gnAMu54LwU1C8q2CZCVnadqLlRaIUhdWPnYof2o/cvYiQQwOTu46ysYhhx7GK+ON3NA6p5R7H38qb9aHO9H6PWfzcrz+J+Tz4lSpjyhJwzShWDI08Juaq7u8rS5iA8PB5BCfjuO/WwATGmzVCp0pVUcCMuJadpAteCc2X1lCctWNaCUrm5bFPXgABQmLAyI9UKrCdUNOOwWt+wcVytPzYLxpTnU0pIYBBX1EpYbfeCurk8HA94eJjx8PiAWgk5P4HMyCM3o0VVzPCW7ibHWUMFhXEJXlAr43yqTUVvw4oI8yT/VPuDsrAQCOabMAFcVeihqvR0sHAoJvLQsib0/cg7DkJwQlI7vBlo3rdJDEe3e1k/229WpxqGBpWxannW0C8BFWnYhNo7YhCKofVhayeLBSqCIgkLM2kollIrsEjfCsOnU33bbYo+S6w7qHMjpKzxTM+sXkHEq9B2Ym0jo/9n7wJu9eMXqeEeJmytzCGj4eHQJlYUKvsS2znDNfDOiZeHyFshtszAwMDAwMDAwMDAwMDAwO8khIZwTxbirbbg+fkZ67K6sME5jTDJJv9fo9yc9eBwDvcnX/IkGw45XA/nPAjTNCPPExJlP5OrLg4HtxCJxMtCLYyi3GfSbfDk/CXLQqd6wc5JPCI/Ph5lsZ5ESPL8vKLUiufn086CM3s+pA4uVjnR+BSrbC0Uhe+UuvRc5EHGegqnWZWTrBoGxEUUYSNgV/fUPJYYr2d14Yu/pCGHdbPgPM/O8TFLiOlaChaNlTEHbw8rgGqb1mYO3hV6778m/rjgfJ1Pb3luwgxdqTBS0i61BX1Ps5W/55AZYc+p9qnYKXf+xs9WFFN26I8Eo/elNhMlJPWGTRC+0PdTOX/OmGchPZ+fWvJ9rw9dI0maKcmGTVpt+EjmPPyL9R/bMQrjolk2V9kCPtso07JYX4xhhmxZw8ulgghmCR9DrTpSSshTxpQTpmkG1xUpLcLdemj6UJmkWyMZzRuNdk5StQFR0nOqbqZTkVEN9UTSd3OiNmQqg4v2GyKAqrc1q1KKVNzV1rCMu9w8a2JjhPqO4jRvJN3YenGND/G+sxOJtyDbIBi9kwtHSrGbw2OeNMI6ZJPDuY3lZG48f2UGqnH2Id1G8Xofr9Y/nNDWU9WJTVWOnjJpyPLLYnek9PbXvqh+3FZQCFaX28HnJ4WxSsDFc/gObOrAHz3bW3WP8MYhDwwMDHxOvM6jR/dXF4G5qvHbL+WxX2VHtgbohX2NIIVEk0XAjQQ3Ru36YLy5EZkS3jw84PHNG2T1NmHXEgik4SxqKSipIFEGV+AwzZjmCYfjjEwSeoTVcKwwpaE8jmsF3r97dqOVmfGsQpfoKi3WgS2We7g3Ncp8B31XE3SxmsjMKO6hQ+6xluI2gCziVjeYmcUrQk7ApC/2nDMSEaYsKmsT4Zh7rhTU1eAmAFnWivPzijRnTMcZk06Eylrw9ldPIC7IdcG6FLz/cEIiwjFLTMEKgEvxF2Z1EVCbLDVDvL1Xq54rXkTi+1aMhGUtOJ8XTFPG48MBFcETCqCeISSmnrUDmUs5TymkadXvRgB3Sm7pPylM4MQ4Yqg4hkQkNB+yqo8TqDCWwkg5eWzPd09PMpGcm3u+lBO+/PpLPDzMIIJMGImAxJjSBBBhOa+oXNwgKoWBc8E8zzgeJ5zPMiFdF4nZuJaCNGXUtQAeP7NVZAXjbP0imQ3fzmOz2iEGr/QzrRf3xCFjtNYKiys5ZULK2b2+PDweMU1Z2oFsAtxq3twx2u1MLDap6iAliUkZJ/nSNxIYCdDJc+UioYj0HF4ZhQk5MaYk9VWK7L4QK7iCeQW4ilAlSWgeCzXTm5Dy3PCdHDo+ODWxkQsLVFJsRr7p3uVEub5UbT+bxCXpO6CKaSKgALTKNevang1JxRkivurtydippR37Cb0/m61Pp4TszwF79LZZsXnNIYgHEWkbHb/U+m0iYLKwVlzlUa0qcgq1EM3qbcabG84NdNJiA5Pt3GAsx3EaS9seLCExS2V7q+2zdicfdvBiYqlXDPN8YGBgYGBgYGBgYGBgYEDg61r6wSkmVq63W2y8uKp9vWe2rec12nCfQ94mZXzsPE2Y5tlFCPKbZpHVgwNXMFUQErjKxkFZmE5IEK8dWkr5f+CQGcD5vIbNTox1rb5J8oJT0AVSuOiiXwBuHDJafbXbB/6stvIzKx8bTlVuqza3Cs4NQ8tEykUZo+L0nHPKrV6JZBG3FkZZxeNBmjIShNurVbhlQpXNYkXCpRABk95XPCm0BmvLCJsSb9YVrH8RWjrxjFJFnJNSwjxlTTcwSNw2Gbq+gRG8BiMUXDeRtY7UpWVtZORgxzAmgGoT0AivRkiZgCprD7YJjIiwLuJ145jIM0NEOD4cxEuKtrPlK1ECKKFAYinbOnllAEW8o0xTQinCGdbCWGpB5Sr9H9Cw6TZwW7mKliPRdiNcP5bJOWQ9FsQG1q/tXFmPSOq9OGOaJ+GgvbhSLm+GcB8ZZ5qOEIa2r89awRfYdXsbkGQMV3DzXg2oZyHhqxNBhV6yydLLp57ajeMkJVQDZa356hfy/TcTWnXPuT1mVzuecsiV2/PEvFckvbeJL0woUUO/NG8eKQWxx4b/bA9mq/C9hyXDNg1Td9yePe0ZK/WiV8U9zLDnrYnEpIztndDXwzabuPNXCv9n57ltWx71V3e3DA9Gij/ucMgI5/Gm2jbN6rfY3GvzeBoYGBj4LHi1R4/2Sf5ViNBj+3Sii+u2bxI7Swzvy/P100bWTTpD6BYGfQGZkEmEHl9+8QbnImFT/JVO8jpe1oLltIiyM4m/hON8wPHxiMev3uCQgIcsUoSVdfH8w8lzVgvj3dtTezTb6jPaVzOam/Fcu5359hIR9eV25VOPmEcKyIu7WvyFKjEbn5cVgDoLYGBdi7cLQTxyECXMs7oKzBNySjhMIuCYSIQf6ldCXOpBFt8lXiBAxKhLxfK0YGbGdMyYiDBPByynZ3z/yw/IVPDlYUVZCt6/PyEnwtfHDNI6rMWDgahgRV0h6JvVjd5QnUUFNkjRSGt1uiwr3r074eFhxvE4IzGaxxdWI5YoGEdqSm1evmwv5Rieo5uoNANclMCpKWLJVOtJ1L+ZMM3iJWY+JmBlpIWRchZ3egw8PZ8BInzx5uh2RMqEr370Jd68ecDz+2cs58UNRmnDLOGQuNqQQakVdZEJ0fE44elJvHgsy4rntYoidkpIGzWvoQI4sRhYsyu0q5na3XAl8yDB2lpuKLJ4xLB7kLhbnA4T8jzh4eGAN4/HztCxerO2rMEKZQZKqTqhSkG81aZFFqK0glCRxMVQIvDCWMMYKxWgwpgywJMp06t4R6EE5gJwAYGRk9RDmslDxnh9MWQib5MFbpm1UDHNMO2NypZKsP5I+ula2nMxZ5ncUSLMsxRQHYBgLaEdiFzokbau5TxbMjmxsWVP6n6yA1djm8G/zbHdz8I6cWWcl+Y1xdyP5gwcJpvYyG6D01nqOycb2wzXqd+ay2xgoaTiReaar58w9ZOoy2nJxgNK81F6ce22DvYzuxUChc/DSB8YGBgYGBgYGBgYGBj4XUejJRAXgW3T4M7pu0uMjrg2at+N5Njco0+38U/dqpvyy4kk/MVhnlHYvIyg8V8Q3qqsLYwDMTCljDxPmA8zMgFT8m0+sni+FM8PV+Bc1pYHxkVWJfvRE0Cspw3/vVt76BZcxSsJjLBCrYy1tPAksijcZySZF+hkm8KE/8zKHSWQc6SwpVOWe5nnCRBwXivKWpAgXqCF18sohXF6WkCoOE5V62kV4UJOIhIBPGyNLUJX9aDQk7btr3uWYAg/GPuXUnEmKpkyY8qpT86qaZt8V/XxXnBu9qLLETnlZF4smscHeL8TTk42DlrYdBBA1fg24WWXVTwzH+bcbpEIh4cD5nnCel5RCzl1JoKjJEKFsGAt3iwq5oNtApX1hFJq2+hlgoCOvGvVsKL3Yhs3C3YnpthC5GsfpJXu7eOcr4X+zpin3DevUnisYprts6N9V3YwiEqs7X2NRvlgWUCovoZgIopaJBSKCTK6zZC2PsXs4a1Jvdf0hW/rVh7T3X4LCxJeBZvnWrdNTglQCcnS+qgFpCEAObNsFtS7140Aybzs7GiRYJxxPP9CUBW+kLUjtrIMLZ4etEhL5mXEimgUb/aQL9BNzPLXBGawuo53uYtDRt8eLCFhIut7i0P2+3hMGPvcP3vkFAY2WdzNo55D4bsLQ0JTDwwMDHwOvEroscUVOxrXD9/z9OoNhHvSeel5HzWHF89RfxlpKIppAkF3+8NCRrC+XC1TrMroKzY2bMGVL18YboC7yafZYLgYRI1ZqPqabUHSBC1TBhJhVg8elkKiJMZKEfHK4zwh54TDpCpOEBIxMsR4TFTgsS/BYEpu1NkLt6rKutaCymJYLmvB9++e8Px0wvP5GXMCMMsE6c2DiEfAFbVKiJDCQSWrJoG5KXw8zJhSM1jtvPOy4rwUPBxn5EPrpqx1ZRMJqx83utwwYV/MNs8lXTNADZQETJRRU8KySJ7NeOF4HokXjuODqItTFkM0Txn0/Qe8fzrh8c0RP/mDbzDnhOMh4+l5wbq8w2GekPOEUipOS/HymUFd14rvfvkO79894+nDE9ZlwbquEocSpIaFCE24iuAjTQlZDdHlXFBsNwDEW0eGuIfkxKCpn8S4YWMxQ1Wen9VjyTTNfi8GQCbkUqV0zqRxSYsroGNPzznheBR1uXlrqLWgaogV9+gSDXzIeVb3ZvXknJtKvVas2ucJCZPWgdhdZ6ScsZyLCp5gmigsxYXXAIApkfejnAhpJqRJVO2unAdg4WSY9XxSi1kT40knT5zknGJtIO1mdVMR7EQiTBO8XhjmIlDylzKhVnKXmlatlp+s57qAgtq0yk63+LbFyo1mrPuYsMdQIuRJ2t8i+5DuRCGweqohEY1TlUmIdIqwk0MmUlOGxIOcJUQXhzpvs4pmSEsLR29GFzNkJHU3I0ObQDlp3kQQNKU2aTWvKvb4BGs+wN34t77RdhTYRGzHyA/Ztx/cHt8zykmEX71gaGBgYGBgYGBgYGBgYGDgdxQX0/3LWTd3n3Ym29sVUbr4sAO7hu9aKERkJ4wzCeSxeHtttyT1xECAECAknoCJauCQ9dqLVdZNOePaplNiYcVbSYiuGFydBzEymQltI6JvipQF9Rw5amLxVsDCtQHA7OFmZBGbLGQDJH1lutpigG/dD5yUceGBB6614nResa4r1rIihSaZJ9v62BaznQcnYX9AwLrKwvysni68CvQeRUO9TMrV+u9kbdc81wq/11gprxVq1R/J/m4tNwGJJZxFLcbJWTp9c6UsfJtxyhIuXX48ryumOePNFw8SmjsnrKWgljNyls2EtUo4Z0A2e1Zr48p4ejpjOa9YlhW1FPG0bJsdLQ/UPKSYiIMroxp3aXVcm7dxIpbQJ9tFbEbjuZQMNLlBUkGQ9/HN3xTubWGIIoeckoT3iemwba5THto3GLpgK3rfaRk14Yhl2jbMknHgfmYBJUIp7P3fki/GZWodRL2GhBeHC6KEAzSWvQ0NWcaxCmaI9wptP1aphIXJsZHFDLJ1DmqiGgsxHr0NWZ4IImboN7RZF4ihW9xfTd+oxqMyAr/fCmPiDBujzhkTvC1pe74qPcjCnXfPTOhzUj2nECGj1fclh9zVbEtoWwb9zfoC2+OJWttYW9plJlchuz9UHBfq3v704gzxGG91zuG8Vvdd9V5/XTkHPzjkgYGBT8dHCz1u2eh7C2WvTvSVidzzWHzpd3HhNoGqxItEysgpo6ZgWKhxWKNB0Vvack6NZkv7JC81M0zDi1aV4+J5wMKwVDFqmJFSxjTNIjI4JLDEf0BlRlGDe8pixC1Pooj+8jBjnjOOkxoBtQQjqbodUC2yRKpiQehbimtF4Yq1FpRaxDsKi0jh/fIe5+cT3j894WFO4McH5JTw9ZtJX84VpTAWZKzu9k3Kzkh4/2HBeVkwfZMxHczdnC2sM06nBR+ezkgEHFW53CuHRdAQY76x/sA6Y6AEoIoAJVjrOqEgJDXOcs5gBk7nBdCQGnFdmFRlfThkPDxKWJKcMw4PBxwfDqjM+OV37/HFl2/wZ3/2h5hyxnHK+OfvP+DduxWH4wHTdEDhFc+nVct3Rq22M6DgZz/7DgDw9OE9Slkxz9DQQ+ryjhIoiavBslZMGlZnXSvOz4u484viIiJMKYEzI81ZDEZzCKIGPNSIpiyK6ZwBSglfaNijsqoRXhZwraAqi/+TTjqen044n8/9BJaAKU94PB51ckXgWlCXBXWV8EYmxOGdAd8tkBMwTZMIRiDeQ5bziloZh4cjpmlCnrNMCijjvCwATi6gYRaPGIUl7IhM5nRypQZemoD0mJCTCEdSSjgeswsiABFAMBjIOlY1bmnViESVSeJVlub6r1b7J7s9KsN3PuScUGdJqlYTt4iEnFOScxOBzOmN/o9AmJKMc4IZpTqxDDsEGBoahhml6r3RPLFEt305E+ZDQinAsooy3V4KNnmYM6GAsRBam3GbNCTziKIzjZw1nNWzhagxd4k2SHtsBXFuoocJmlwvYYFs+pwIOBzk3FrInwHdBEUPtvHMzdg2t5f6v2bkbyee2wkFNxeAoG7+QRAxylZYMjAwMDAwMDAwMDAwMDAwAPQLd3u/3XncVtCu8sfX5+X7v2wWFHnDVHQrdsonpgzbtAdY6ON+hZy58V/kbkojg2N885WyEG04Bl0wBjxMuN9DvXgQCW8nC9NJ0tfNXFUXvm2x2EKVH1QkMZlHhlCuthIL514S1Y3oovHlbCIUAGupWMoZZV2FB84E1hAdRwtrrdcWpAuvBAzCeSkopSI9zLC9glZnzCIEWdYCOsiGR2vNCOOLvArbUeeBOSwWdySbcmrCHyXl3QpQ2omRyyIVb0yzeDShJBsFJw0b8/S04HA44JtvvpQQ6ynh+bTgfKrI04SUJlSuWFdZKV/XovkXHvn9uyep22VB5aqeiqnjppiSrwMkXVCulTWcvaTLKg6y0BxIwj23chufRjDREGlF2KL9wcIeWSgULt5JZEFf6mNdVxQNQR+RUhKRkfHBrN6jN5tb+wX1sCbjfcU8bovPC+FtpQ+7kCSJ5xiihFLF0zOb4ILNO3jrJ+ztqRxoAmiOnm9MzNN4R+m/3NxCa/pcSccPeVtGgYP983UL422RlBZuGySFC5Zz2dqI0YcRgXK1ZF4oYocOogiodx+Chltp4o22GVN7lURQR2X1pE29YyWCeOyo1TY9cuhH5P3JvNq0/sVY1/Ac7Adfd2yfQbb89mOXtC/YoezPDoRngHHHhEo7/Yyxqb/+r6V/8egOWeNwdvf493E1OOSBgYFPx/1Cj82z9ofyCOIrnwV7paD+065leO2aWxOVnbv7Zdvf9gx8fqHSt/e4lhebXOydE8vefksqhsjJdtdLaBdTDIv+OkFi2Zlloy/HZLFXZOE0qru9SGTFI8vY7aLqG7J3K6cvZlWkg4FE4tEipd4ItfArWcNl2AL10/MzStJQJGokU5KJW8oJX371Br//42+Q1XCcpoxpnvHueMI0iWE65wNyIjfOzHhby4pSVvFKsa749pdvJT7leRFhgrrNW1fxxGBVR2CAVABkkzdmMBdUJp14cdeUZsyezyuYCPM0NzMkJfXYYerj5lemQNozUwJxAlXJL5uAoYpqIKsFax5wotq6VlYPFcnTrUXV+6V2bvOs4aPw2IyfKsWWiZP2GyKS0CsqvJGJRFV3k2LQy0Qqo6yiePe+pfmhTFaxIvTJqsRnEYUkdRHJkMkPm6EPIKtgyiZQpsgnVgWyq7jFvK1aJ8XyGN30wQxLDp/NuCZ8UcW7zLpam1bxpDLJpCSBgMo6iZHfbEICMNbgTcNEK4mAbJ5L5HKknHGcEs7ngnVd+2cemwFuzwDV66u7z7ZDQ8rLXhCtBWr5gR9tbe3HovI/wPpUu7A9lZJPMPUnM9Zr619Vn3FsJAe150vRGDTWjnG3CQMqsNt7bsfZnn7wIuvEn8T7zsDAwMDAwMDAwMDAwMDA7ySurMVdpSpvXf/a89uq2u1jO9d1VOk+lfvx+bI0X4Pd850EvXGvlzjknSR3y8r9x2tpcvtgYoBk/Czg/BgZB8lt8bxLImymlLZQbsaooZAdUp65LbJv+Zo+b85RtdXdjkP2MCP619c/9ELz4EB6zZqScrVt0V00EMJXHo4z3jw+uPDDQrWcc/FNWJlyt3nIymybP+VzwYfns26o1A2h6ralVkakzaweOLSneVWWe6SdJQjlLsWXL7KvhsM3PjaOr3n7qNzak9xjhazwO9/JLKHFtR5TSs3LCkP7BFq/0PyW0rje0LUuxmQ8JJvsWAVNBA8yYm1qZS3s7UqJ1LOyrSmENk/UvEJYuye4kMtp3rWJriI9r9Sz9gmtP11/kCqIEgnrAyaU2j5AWe8b6oRbv5lnKauLpFhFKR6uWzqZeW3xcOBtCae7mw1DWzMh2HBRr9C6cTXqFYxDbnXLoNr8OBuvb43WPWstEbtRSHMLG/cXYLR6C+Q2h6++hqTju0VgCWkaFx5EI6qD0XTIuXw5X59D194VVtEbftzGFPmDaWBgYODT8EmhW35zj6FXWNvc/XnhOmp/g3F5s6CfavS/NuHdom8P7i9SdsaRWrJxCdZeLdsrU0qY50mMPTU4l3VFWSsyJQlvo3KPTKrCruoyMGU1XuQtXmtwncZV79devjGnLfZjLITkToyLZnDYhIzUqkrQ0CXMSFN2lSkRIU2zCh5EQT5NYuG8//CEdS0alxOY5yzCgUk8u/z+j3+EP/3TPwaxKVYJQML7dyfMhwmHwwGP8yMYjLUsIsQg8TxyPp8lXEtd8Xw64Re/+E4X9UV0MqmRsCxVvFCs0gXzVJGSeHiptfokgmsRkbS6qjB70dwoipq9Yp4nvPni0VX8OU84PHwh5c5a1VUmCudlVWW/GG1lKeI1poobQC4FqOIqEUk8UyBN3kZlLShLwZSzK+hF5FLx9LxobEltRmvHYEz5XAtNAb0sC0ohpDRJmx8OSDkjqfCorIuosEFIlDHNE6r6hit+O+0n2l+YCDQl5DkhUZtw1irXnRagrIx3b0+uaiYCHg4Tcia8eUyYMuHwMCMnm7AASYVDU4aHYgEYy1pF5ILoprBNwGqVc5jFA8bMjPkoSvvzWYz8tWo/mcjV2CARfiQAkxqeFqJmLYBqRJAzIWeZZBzmhHkW94SlAvMh4/HxAfT+jPOzVVicJWq/SsA0Z4AqTov8bN5IzEiWNiO0//ej2s17mwgSxdtszicXLIHIJ4YeO5QSUrLYmOTu99hCA1UJgXPWyWxOSVyq+nkipLFQOJXJ49MyACZCWTeTSmpiEOvbrWzQSaCIPIYae2BgYGBgYGBgYGBgYOB3HtupsX3/3FxqJDIvpuO6onftuvi5hrQ+No+fk0PuVrLjDUyk8EKCu3nZ4ZB9IfJWVjeLlLtJNm8WsgFGvd5q6BHjgtrufl00t5XmZKuxupjqi7cS1mK3bQOHfFFm7xPUNgvGUmv9ERoHbZ67/ZjGP7bQIkljzyzLgprESwoztMwq6KCEx8cHfP31l2EBXMq1LAU5JwlVnSctf3FRAkO9OdeKyhKe+sOHZ+cTQWQ+HlBqC50MACmxdou2IU8Ky3JS7XksY+WMq09ZPZ2r0CFRQp4OsuHMx27b1GaL/0Joapjrqvyncv+ZCMgqdolhdSqjoiKp9xnLpnGktbbNe6xjeK9pbYmjgiXEOBGo2ga/LBxdsnA4xbk8QkLK5m1HQv9YzZgogwjuGdrD3+j1pbDdWDj1U+nEIuYNe57EE3IOaxMgeDh18zgtzcvapsZHdgMfPp66zaASjlwEMnKsWtglF3oAYC0DEhKjeRGB9KFqwye1YZiT8Mm671P67TRhWcTbuHek8Nc58iTj3+q1jeXW1g2XDyqydrffd59lgUO2hSEE7peDkCg8Wvw5oOG+RSSioXxg4z6Ij6odt7ayDb7qEYfJPf9f5I5CeeMjitqHQSEPDAx8Dtwt9Ni+Wvz5aV8/m5HOm78Nr54PhBMvHpoU/1E4HB+wH/+kjXOCq6nsFeSlycRLhefdjx8BDgvTwWD2n7epbycKduyefFz0rhdAux/79Di0q00gbIE4i9u8PKmIRVx5pZT1d7ncXb65elcmKqoJFrGCG9rquq8WMIvXDvEIwa2umDV2YnEvDx6awnIqSXlMRuYqxrO5rGN1gVhJFd7cFr+TeFUBqllEIso5n9U9XUJJFVXD2bi6WMdyDHnCzCiLhmzRkB/mRk1EH82IYoYLbDyU0XbCSaFdrrQnYXt+MzxlQigPrOgrQUqrEx2deE15QsmMlJsLS5tsMosIhgiAhgRq92rPHjGMK4rtHiDCaa3IlcDEyAmY1mY0A1AhAanHD+gzUsQKtbIayzrpy8mNTWaIF5VEOMzyvc4yCV6OKpzSucKU9RmlQghKhFIZa1HXeXqvWsMDWj3tJA37In1LjG0iRlklpiejj0Moym142NWJAdZ4s9IP4JsfgDbB9HbZNnV4tLehqf1k7/GB+GRovUNO5X7MmOGcADDBImwmIteZ9Q8LSSVlEYRF36AyjjV01t400qz7iCBKkx0lw0ofGBgYGBgYGBgYGBgYGNjDR/GVuxfx5dePnY7fylRHL/bcAl2c9EJaV0665JADeWKcyUtlu8bD3HE++//p8oemCriRUGBqbi0g+Anbe9zLId97UrjXi/XCgZ9qHLJwiSr0IAkvkrPknaKnC9hiMgUOmZwr8tJyX5msHG9V3ne70OK/m3cMIhWnGFPWODHfTGbcsSfDzq2ykbgI/C3YiWFW3hpEIOU/mc9d+tSFHmHLqvPWkix5b3DRR2xyp+2vcMjbdtrp+xfd0buZJq6eYDp6zs9pni5SSuJZRL1tmLiCrFwsYcxlI6t1DO7y64IJuy+UI9XjiYBU+7WV6OmDWgfx9oK3LYJISfuebXhTwnbSTaElWx+QM5OqSqwsIHI+17j2JsAIdav39bUDal6Tva/GNtIubf2EwX5vZ3G9D+qREK48OO0Jie61tVbUHofc9RG6+hPF30n7s/Vtah5ILjLAbYx7H/OyWU+/wSFTOBw/f9JLa2BgYKDhVR49ePuZzYxj7D2E2T99BDpL6DU5vHFB/x7ev+XFPbf5jw9xu+DXhI0NbGab5Dlk/CPfEc1+ulZJzeiuN87qzg1Zun3X10G6h1sSl2u41KZbzU0eQGQCj4x5PiDnjMeHCQBrSJMzppxQmTVcjYUJSc3SsYIxa6gIBlICg7EuZ1SueD6dsZwXD3eSGCBmrOuKZV2xlAKuwARucRQJoEzIRDg+zMg54enpA8q6QK1DWZCv4rovqRcKVss15YykggKr1lJWfPiwgJCQaNK6ed8mA1C3fKpSZ2bUdYXF9yQCjo8H5JzAZxFol1KRKfSBwm3Xgxs9+lkNpSAhtp8uxmK3+K9pi5MFAjRMEFjq0iY8lcTtn4lW5mlCooRaRAFfi4SeMXFOKRXruYB4Aj3EDiO9WtqWUFGxoqAwo7IIQpaqMXWeJOMpLbBwMgwgQYQTxOLKkHVilcFIYBzmjMM84XBIOB5JBTRwhfc8Zzy8OWg3k/5VWT3jQPqXxdGE6ve/VjHRUiV0y7KsUsaF3UNFm8m0CQfr5O98ZpyenrEuGp9TJwQpiSeQlAlp1klOghjB2l/dYwpL+JvzUlGK3Jdh6m0L6XJ9pF8ep81fmQD40NMJANs7gljEGmiTprJK/8w5AcRgohBPUZ8JSdT9eUrAChAXf4OsgIh8wGgRHUMOdfKqMv/WhdjeiB/3XBsYGBgYGBgYGBgYGBgY+O1EW/i9ziHvHOArx/Z4z1tc6MU1L8/bb83t23L95ui2IMx9GboUXsEd3OR5uZ1zpY5Y/+/hE/au7/iYkOZOPlvyt8vA+0unPbqFz2sphoLtlmGTs/B7ayvabziizoNAEzao19aUhHNNhHkS0tU9fIB0fxh5eGBQvGsoFBuHLHVim67WVTwk2AY/y14t1UOnK/UM59kI4nWCxXsEJcK6Lu75We6lXB8bja09WjlgYvGaQUoXci3KfYaQxNT3iiZwUTGHClSMQ86T1BObd4nKoBTCmlTe78q2yN5x/IFDvjh/0+bGravIhJSRJXvqMIQX5MYv5pxE0JLYvT0btwciD1FOOYGmzT09Drncr6Ki7bkjVPP4sVoZbEsa+f+t7q0Izi3DvGkk8dI82WZB+PpGzoRpzmFZioPXCGubNq4ZwFE9WZeq/U83oVZtq1jnkUPW1FEKZLNg8Ihsqy/uPSRxGz9k/D+pGMjSIvVY0+673TC3+4i69QwM19t+wniZe0fRzZDxGhGdEIiqelwhrzN4larARkP9xN2N7euVvm0c8s4a1mCPBwYGPhc+KXQLgLDa1mBmzGVIDux+f/keF7e444KWl7170tZ2CBfsBAx5IdMvlOilvIf12JfSvXqnaMy/pq745teQLdr5YX/Kc1kMs3T2M3Y5tdmfLr0atyZ92s6dtiAY4Z3LvovkrvUqPXZjYhK9pHB3fGe+ZwvbVn8bZYQphptRtHPDeGcWNYYbyCrOaJpTVgtTZgCsq+sJQCYNe5Js0mKTIO5GeZz/kWbKj6lnDL9VsKuoXdH+UGyh7ieHGWCmeG42rLgYlPiJYuGZ20CtDff0YfM/KamUPxFwmDLWxDgvsepJJlLQyQ0B5IavxshkaExK9kkUad1WFY+sbAIYUUhPE5BPFceFNQSPt1qYIMoRAiFlqR+u5tFF8jRRQs5Ahhq2KfbtkIrmazlUnJeC86kiTyvqCiyL5mlOOEzA4ShX1cJAqpiPFWWVfwxgKYxUAVCSfGVu/cues9pG18GxB+mnMCpo559f6g0ItavhnbC1GmxW/u/aYgAAFkRJREFULIp57pIhqNAp7KCI0xnTdJs46rKj63kETJMKwwYGBgYGBgYGBgYGBgYGftcR+RTnBi/5gY5DDj9zo0PiyS/ca+ec3Wv2OacLVjlwWBcXMF0e+xTQxYdtpna+a53ucLwdM68hpi93X1G4dsNQ8t75L6HV29X8XxzerHhfrIYar/WScCTwSHfz5LzfLQNxFGmgnpwKbJYviIQb3qw7fiGPd9Z5xyGjq8r2Lx68A8FziISnaN2nH6D6P25+gt1bOjUO2TJ2cf2mHF09B4UHbc+JZfc22BvPO2w+939h/LOnRei7o3K74SfysaTCDEqgrOFTukxQ91e3RMIaplWffK8+llVoAqCqIAfKSdqmwdwOa1b3OWQTXaDR4uKxA7oJDgBzOK+rueZhpGSWUOBFPKBwBWrRtDQ0dp7Uc3lioEg4IBPMMKDeoRuPLYIhhEqzfrd5eBCF3+N5oVG3D+nLjrI9eH04GNce+GzrHqQVKOs1ktdrjxi6yHe7sYV6+nXuIR8YGPjtxacLPYCbhvrNS157j1c8+G7uqN781IyFqLzdOf/FTL+6VHck1Zu8N6uAGC4FvXWiN9X9bbYV1JoaeAvefHl5b/tHvs2iTf3RKd/fXvtpXdbf1XmjehQwTxn33THGmGshWuKdXJHNrd3N2OobiNVcJJhrNzdUNNYgqHUfgDWuIjARYc4ZJVcQAzmLu0Jii5FZunqw/IiZnNw4BQAK7kZiTE43xs14td87e8g6HcNUKlnV86e1YDUhB4vhm1VdT4lQ1+qhdEgts1KKKvD1PGRNtyIn4Is3M9bCKGVFsdCDBKR5UmMs9QIGFvV9WSoqJOxLFA6cawEtVRXOaGpmrYeURLFNUGObAAtfabsDDlNGzgmPD5MY0RBhSD6IUX2YJNxQmuVZNh0m5CmLap0s9qM+SQhYS8VaVjw/r3j/tODd2xXf/uyEnAmPX8w4zglff6EeTdaK+VxwKozlXPH0dgFX4OmpStiZh1nCvWQpz/K0asxGNXqtrnbm+w2bEVQZnNo8w8O1xv6P4DVE279Nl9rDShTlEosmgUG1NiNd27NWUbQTS3gbaVb255+MFbk/165zSu61HnLOu6UbGBgYGBgYGBgYGBgYGPidArHuizHuBHiRj9z7+R4K83XU9P7J917vC7hXro8L+Fuy9KWMbgngOy6Re3FXzRdL3JHYtY1edtwIkraa31/zktgj/NStF1fjaF6Gn0Po73Wtjq+mcoURfoEofnHBNdbfjXM+jum+TDNIAdqBi8TtIG1oYN6cayFX0OpWOTaGtW0vQGiebOUI+TVNCGAOxs0bSaIJORGYEipVtHAXdvE2RA2UQxYut+ssZEFgrCjGXVPrI4Ej7Dhk68/+j1z0sGpYFeMMiWXDm0RoN2FC7dJki1/topC4WZAxH9JOKG1omHXjw/v2YTC4qHdlz65cXLiCCrU2asWwqmmbVDXJZHkl48WFE5/V44tJTGTzoHgFIRBokvvklEA5enKRjXJ2h8qMUivWtWJZCs7nig/vC1IiTIeMKRGOBzm3VEYqjJVX1MJYTqKAWdbm+cXKAAB1reopZMMhW2b00YSurwbos0bcgFMbh+G05vEltsOGQ7aDQaRE6jknrslYmzCrZ2+re193gKZhxzccsqaXp4SUNmUZGBgY+Ah8HqHHTVx5+G4Vz3fhcmHt2h2vXXk1V7eyQ6+cJ9zE5Y3uNXivJ6cx+l6VkBlvt9uhS+6KQXvtlh5N5kXV907/+JR33NXbvZwoRSv19plXzrl9rXiSeDEbF9dc3CJ8uPCUEAwhM8dvwYzp62eZyhaga7Meavf0W16t7j6GZfsbJ3FmwlM/kYjH1ahqC/99uQnNiI2Fte+1iis/zmawqTAFIthIKoxwvYkaeXJvCnkz9XFQP4c5B+xvzEjTHzQPLz65IQ8NUqKRTiLgSam5bMxqNOa1glQokggav5EwzRUpi7gBBBV6wCdalSsqi5GeuDUjs3jw4AnISV4TNDEIGV88AudccPog3klY2+/h8YBpzpjmBALwdv2AcxWlt6QZZyTX+kaooJsnSZrRmI5tfPsZQP7+EbFNbcI1bm1mkwrrmgyZ/NFFGdgnBkSE4+EBeR5Cj4GBgYGBgYGBgYGBgYEBALoId2WObwuuLxEFn0LMXk1+hwsjRL3EfmK0IXg21+9f2xbkX8SG9/Pvzk/s3PcatquazovEQsaV6bsytvuThWboT+XN3/08WliN66dFznDnPN7+uMM1X018p1w3q5c2n/vF2/3zr2b4eh6w6Yi0d4MtD7uT8e6SLYds97mPC+/p3xvnmyv1eNrVBYRbedzxu94Nv348Uv+/dpyMX9+uLd3u87ZZsGljev7Z+UnlqQlVmGgKnHb4/7ZkrA+bjkNG8CwMdpEAh2elFJu9GahRncpPatWo8KQThtiGttU8VktuUpYwO/D8GydO+shQUUpt93V+2zbqkfChOUneDxNQqGI911B2wjRlCReuIodzFXfatj02bmjt/gJw9zIXuPUe4dAe9yJyyMb9Ng6/6wZ6+8Yh69uFqDvFc6P1OuVpeIUeGBj4LPh4oYfbphz+fU7cMJo/Z9Kb47aYbO7Grhvo/1KZ2DsvrL528dHiKyysMH+UiOYSzUY2BWf/YydAiP2BuNmZLHHurqT8yZDb3vmq3jH0up8/T7Xt3tiMKdaQKHyx8v+5wN2fj7z6OnbHA+9/3qzrm4EImB3e3LQ1sYYoohkwa7KrJjtfrNAEIu7VspsJnW1QsORd+sLAuqzgnEF5BhJpjL4KsKnUyYURnBhIGUSitPUeF5tR3XQQVTeECb0CmVKCxYeMOTVbvVZo/7A6NANSzn8mM7bPkmLW2CxsWyTCrJoAQurKYVqZKSdMWcqSM+EwJzweMrAwKhilVJyeVkyUMOGAnBPSnMFH4KvHiqenBW+/X1B5BUO8vPzkj77Bmy+PePMwgxj42+X/w/elYF0ZpesvNmovJzkXfciV/3zlNWPHKQiRGCspSWD3sUej1bMSGuK9AzBnMLVWrUubqElLsarWARKPNn73pvnmCmTK+PpHv4fD8XBRqoGBgYGBgYGBgYGBgYGB3z1Q9+dick+4j8fcJxDuOyGu7Xa3eokF2/u9JUC6uho55Nv5+0hsFxT9y55YYIeXc6qQNufq3y2tt+WA782ik287YoKrSRppJyd1u/gvE7+Orn/tn9vYvM3v15r56i1f6Gd3kbLXWDFy8tS9OF/eoN3mYrE5dvaXYB2D7hhfm2wjMpt7yYbfLgjQvaxQKJ6xcej0J8Yd9xyw3W77nImZTTB+kNE2dO1xyBwvtcSZhD8k0jDekasMQgo2/p8BstDRjZvsYMImGy9dveg1caHCs9mOsa7NXITrgXGaUqcnZWUphT4Xzuvv27hju10iCzEi/HLOhCknodCJwRUoa0VCRjpmPTeBGThMjHUtOJ0qShGxR0qEN18eMR8mzJNsFvxVfYfT84K69VAe+kXrClcGJoXytU66qTdG1x5kt2vXdiPI1r/COljvVfqy7Vq4ePHYvX0k2wcC4fj4OLxCDwwMfBZ8pNBj+xC74/zu0y3j7DUGySuwvaXbs3QzO3Tz4h735/jaC+nyQKctv3dOcDFpCS+3G/UbbVhz5bZnYLv9sE2CN3/RXoKvyrdPQD5zH3gVrs4C77juxvmvLdJFRX9snbxUhtely9Ey2bs6VNvenfdENWZ3bSPbvSzi2c/7xrTTCXg7cGGLxfsEg3Yv3e2kwscpXebdash7hol+4uldO4fJAtA8fthntvRamBSf3FSg9/Ai4oSUeqFHVU8bJvRgVXif1+p1UytjXRlP54KcuAtlcl6CdEPFXOfziuk54ZgyEgDU3kNKK2isI5sW7rdym6f1ZxDQ8QbNC8dmgtNdsZkrBLFVnGu25xuH37gLV9XcSsaiyMxumiZM07xTmoGBgYGBgYGBgYGBgYGB3zV8PLfXUU+71NArOeQd3vX2eVti6zaHvJ9mZBzuRFfe7T03i+fx2CeD9xdLr3DIgcDdI9nuvqWl2K29X95s/xh3f66c/AJec0lH5l1L4CPycA33LKEYGDuigc990839bl4ufehFDvmlm+yRyHEBv6PNb5DRfTY6xB7fSQECh0zXhgVt/qL/3q67/bxqgWo2R4m9af3qTsCwv27QwsHbeZsMmlhhe0fjj/UyG95EjEoWPrui1MhXyya6tTCoAkS6EZGbp2fPFRNKqUhrEU/Vnu2dwb/37NsWYtNWtD2+k8xtbdPt/k9AdPKxqWe9BV9/bHn4JIKEX09D6DEwMPDp+ITQLbLqde/L+bOYnHcZ01dWZu9Yr5erL4I9bF4L+wu6Ebw9d/f7x+DahGLHstuGwvgINDtsYyTsWTDRGopnm9EQmmY3dMnOtdgeejU+s2F9R/9r0UU2i9L6qfKV0C2Xq8bhH15RER9Z5heN889yyQ8U2/5++Xzo7NFdocE2NesrcmIFYCFg3OgD0IQQ+wlNU5LQLGp5L6cTyhr9Z1hmMiR8i0R+PK8VpRYkU6NDbmp9l5mwVuD984rTz9+37qnJlVKwrhrypFQsXPGzf/ol5jnjD776GnPOWE4M8AS4P48opXi5lxAQ6sgM//bZp0fMqKyCFs2kC178HUXQYJtgVBG2WPpJ07OxGV2NbmACGHOqRwQkSqhgrFxBYByOM44Pw6PHwMDAwMDAwMDAwMDAwEDDJzB8H0s03aRG7yCJ78ryHZl7kVvb3Oxmkq/ge29yyIGjuVjBvhcxL5EUuzMzHZesPPAmG/f3mtdxTvv5u+Nu9yZ9T7eg/Tsab+ibvS7X/jfgzd978Qkc8h5PfpFcO/Dxo/9KHumOz7eSfE2Gbt3rGmG75ZDDn057gStpaB33XkzCGkGKw+aOAhHcK4ehrmUj9LDPKaTJKMxY1ypsbBCrWD8FichjWSu+f3/uigYWr8rVRCGVUbng/dsnpJTwxfGIRISyAmDZLLhbES/Aa9w5ZGp1GJLw8DfuKYTdSfaeWoPjYYJ6GdffLhYELnNuGwW9TrT+qh7POSNPQ+gxMDDw6fgEocctXH/AfcLlr7r7i7CH/dUf97R/zfy+fuetuAPo3ggfjc+8fH5nHfPFh00aeClnFlvt/qzt4zXl/yyyojvu0e4TxRz7CMbtKyrD6o782y3Ee+/1wxs3+dTudWM8fa7W+OyhdT4hPQ8BQ5vvPjG9NgtrlW0GnoWe2dVKvZiR5gaw3WenH5hqAt6ZwBWoCUhV8i35IOTUnnQMuDEek6os6SUiFE1WvIRUPJ8WrEm8gVQXWuw9Uy21K2KWMH/w0lEL0bIdE23TiabGfcpE1MQf/q/dxA1uraet+nrrlGSvP9Za8eH9e6zrevnjwMDAwMDAwMDAwMDAwMDvEu5ef75kC/j2zw1RKLClwj5l3b5b/xQxxH4OA99xcT++08FCLODOwuuLoTXaomz7vpPV3fvG+9w4uSOIQ175yikXSVn+buWN+1O3J96qyBj+5+I2e5nc5mtz6Fp9382hxvJeLiCT53l7E375W1ikbiSfJx34slCfNwnblzjkTf2RLZR/CuMbttnutdetB8C1pRerTuIWWmXb77yP35N3vW6v/vYH/KYMdJk/GIfc86X798Zm7Pe8btd77uyXvjnVL7zy3NmokNjqlanLeaLW59jOC6UDWkjzmF/WsC/rWmQDXZXg2C3lTd2zZb5uRlQotFVPoMgp/o0V5cXWflzDz5A2Yi24h2gJUQHiPS4bgS+G/oVHbwaYGctyljDiAwMDA5+IjxJ67NppmxfEvrupz4Xr6b4kOrh1uRTj0sjdW7P93GvOH4OtscfbF6G3y325fcG06EGXS8q71+qLaxc7F3/Oet0VBmimaXPCLRPvpXLSlTGwlxeufFPo0XsEuaeGX8J9Y/Dls7biAYrW225aL9uYd8+Oeh3D58SLHRi3O8e/GmyeWxfYKCbiZWHOEH8mEhdy0yyviVoqQEBOWRTYpaKs1dXJ0zQh54Tv3p1Q6wmlFDmvvpCni0mvxX3sleYEdWlHwJRYQtFoPrPFpbF5VOWmbUkSSzIlgNcCMKOsBbVWTNNB7pdEQJLUW8e2D/NF9caYoFVtdMLTh2f8zV//lz6O5sDAwMDAwMDAwMDAwMDA7yKuTfsvTvhMN9uqKroJ/WuT45s8X79Yul1IvpGnPnP76XtygRfcLBxeyfTVE/Y5ZL1ml9O8zeVIdi7LdxG5t0uXLpMN54gDC75S3Ttc624T7ZH2tPsxHqRAc245SIrH7sY+p0vh/yAAdXtO+G4r515HfZoUMxo3gXVrAVfqc3Or27jk7Vql7PWTexK+1Sbar66dsNdFuzaLXzbtQEAnCrpGau/lkbY/7Yxb+xtEAfuITOxOHcb+vlfFFyTurXvtXXwtP+HeFxwyNQ55I6iQy0i9Tsv6h3RLAlKSsV2bn/iUE4gIT+cC5gLm2oXMvmzz6y8T3xS4Gfu2SdAoY4D1WDiPAKpo7ZlaelxFVFKrcN8pZ1gFEAiUKqhIumxt7vW0eTh5c7P3j2VZ8cuf/QJbCeHAwMDAxyC9fEqPz7XeSZt/vz68rgQX7/crBuG/bCnuT5v9fx+HK1OM/sfXpvdJnebj6vb2LX8zL9B/fa9tqduPa56XRVM3fr5+wWfAv3pNxr80rgyZl7QHPk/i/hiZ4MIMWYr/zJAmN6BLZaylolbz6HHZIm77ut17PXOk/20ns115NpOLi+Pxq3v1QJt8deXtr7mnPzVPLhWn5xNOz893XDUwMDAwMDAwMDAwMDAw8NuLz7X1qJ/b85XPm2NXk+X+4+XOjp1z9+65XUDfXB9pjN28bA9uyJh43NPa7ETyrFxVV2h6r2bpNiKWeP9NPnbPu4Fr2oCL+26+765Nv0BK7v7GOydcE+Ps3fPGzWJ/urjPlc+0PX6DJbsg2W/0oY9iR69d01QF+1352tjZNN4L4413PrW24Yvkbva1rRDiJq6NPf3NlA172buRVHfgal54t6q6/HTjfy+fr2zrOGa36d6bPIWfzGPHllAGXMSwR9sSWMNxc9govGn78BzlFxt+vx4uVj/2Lt/pL84ho3XBTiDCYVTspbn3HO+yKhsRh1fogYGBzwHi18SRGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgY+I3h1R49BgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGfjMYQo+BgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgR8IhtBjYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYOAHgiH0GBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBj4gWAIPQYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGfiAYQo+BgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgR8IhtBjYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYOAHgiH0GBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBj4gWAIPQYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGBgYGfiD4/wGljAwuF6UlJQAAAABJRU5ErkJggg==\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["\n","📊 Statistiques du masque prédit:\n"," flat: 19730 pixels (39.3%)\n"," human: 87 pixels (0.2%)\n"," vehicle: 2887 pixels (5.8%)\n"," construction: 19259 pixels (38.4%)\n"," object: 484 pixels (1.0%)\n"," nature: 1001 pixels (2.0%)\n"," sky: 883 pixels (1.8%)\n"," void: 5845 pixels (11.6%)\n","\n","📊 Statistiques du masque de vérité:\n"," flat: 18943 pixels (37.8%)\n"," human: 165 pixels (0.3%)\n"," vehicle: 2759 pixels (5.5%)\n"," construction: 19632 pixels (39.1%)\n"," object: 873 pixels (1.7%)\n"," nature: 1013 pixels (2.0%)\n"," sky: 883 pixels (1.8%)\n"," void: 5908 pixels (11.8%)\n"]}]},{"cell_type":"markdown","source":["# Rapport"],"metadata":{"id":"5S5RqKBPbFQU"}},{"cell_type":"markdown","source":["De nombreux modèles ont été testés. Le meilleur modèle s'est avéré être `FPN` avec un backbone `efficientnetb0` (features extraction) aux poids **ajustables** le tout dans un contexte de données augmentées aléatoirement."],"metadata":{"id":"rEs5z5n0bGo5"}},{"cell_type":"markdown","source":["Limites du travail :\n","- Le prétraitement reste générique, en particulier la division par 255 pour placer les valeurs des pixels entre 0 et 1. Appliquer un prétraitement plus adapté à chaque backbone permettrait peut-être un entraînement plus efficace et une meilleure performance\n","- Généralisation au-delà de Cityscapes ? Globalement toujours les mêmes conditions de météo, mêmes environnements (urbains)... Modèle pas général\n","- Quid des performances en temps réel ?\n","- Taille fixe des images (224x224) pour faciliter l'apprentissage mais généralisation faible\n","- Backbone pré-entrainés sur imagenet... Mappilary Vistas serait plus pertinent (jeu de données orienté prises de vue sur la route, villes, campagnes, etc.) --> potentiel gain de transfer learning (feature extraction)\n","- IoU perfectible sur les humains, qui sont pourtant le plus important --> piste de travail à privilégier. Pour ce faire, data augmentation avec augmentation nombre d'humains (IA générative d'images, par exemple ?)\n","- Globalement performances assez proches pour tous les modèles : nous sommes probablement limités par le jeu de données"],"metadata":{"id":"PkOuVBcdctg4"}},{"cell_type":"code","metadata":{"id":"0qXyX6entBG","executionInfo":{"status":"ok","timestamp":1754981578829,"user_tz":-120,"elapsed":3949,"user":{"displayName":"Grégoire","userId":"01249298206117462766"}}},"source":["!pip freeze > requirements.txt"],"execution_count":39,"outputs":[]},{"cell_type":"code","source":[],"metadata":{"id":"FOlElVf7DagG"},"execution_count":null,"outputs":[]}],"metadata":{"colab":{"toc_visible":true,"provenance":[]},"kernelspec":{"display_name":"Python 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\ No newline at end of file diff --git a/utils/__init__.py b/utils/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/utils/utils.py b/utils/utils.py new file mode 100644 index 0000000..37787af --- /dev/null +++ b/utils/utils.py @@ -0,0 +1,311 @@ +import os +import json +import tempfile +import numpy as np +import tensorflow as tf +import matplotlib.pyplot as plt + +import mlflow + + + +def load_cityscapes_config(config_path="../cityscapes_config.json", verbose=True): + """ + Charge la configuration Cityscapes depuis un fichier JSON. + """ + with open(config_path, "r", encoding="utf-8") as f: + config = json.load(f) + + class_groups = config["class_groups"] + cityscapes_mapping = {int(k): v for k, v in config["cityscapes_mapping"].items()} + id_to_label = {int(k): v for k, v in config["id_to_label"].items()} + group_colors = np.array(config["group_colors"], dtype=np.uint8) + group_names = config["group_names"] + + id_to_group = np.zeros(256, dtype=np.uint8) + for id_, group_id in cityscapes_mapping.items(): + id_to_group[id_] = group_id + + num_classes = len(group_names) + + if verbose: + print("== Groupes de classes Cityscapes ==") + for group, classes in class_groups.items(): + print(f" - {group} : {classes}") + + print("\n== Mapping ID Cityscapes → Groupe ==") + for id_ in sorted(cityscapes_mapping.keys()): + label = id_to_label.get(id_, "Label inconnu") + group_id = cityscapes_mapping[id_] + print(f" ID {id_:2d} ('{label}') → groupe '{group_names[group_id]}' ({group_id})") + + print("\n== Liste des groupes et couleurs associées ==") + for i, (name, color) in enumerate(zip(group_names, group_colors)): + print(f" Groupe {i}: {name} - Couleur RGB : {color}") + + print(f"\nNombre total de groupes/classes : {num_classes}") + + return { + "class_groups": class_groups, + "cityscapes_mapping": cityscapes_mapping, + "id_to_label": id_to_label, + "group_colors": group_colors, + "group_names": group_names, + "id_to_group": id_to_group, + "num_classes": num_classes + } + + +def get_preprocessing_fn(encoder_name=None): + """ + Retourne la fonction de prétraitement adaptée au backbone utilisé. + Si encoder_name est None (modèle vanilla), on normalise à la main. + """ + print("ℹ️ Modèle vanilla - pas de preprocessing") + return lambda x: x / 255.0 + # Peut être rajouté dans le cas d'un entraînement plus poussé avec un traitement particulier pour chaque feature encoder + # if encoder_name is None: + # print("ℹ️ Modèle vanilla - pas de preprocessing") + # return lambda x: x / 255.0 + # else: + # print(f"ℹ️ Préprocessing du backbone {encoder_name}") + # return sm.get_preprocessing(encoder_name) + + +def load_best_model_from_registry(model_name): + """ + Charge le meilleur modèle depuis le MLflow Model Registry + """ + client = mlflow.tracking.MlflowClient() + + # Récupérer la dernière version en Production (votre logique) + versions = client.search_model_versions(f"name='{model_name}'") + prod_versions = [v for v in versions if v.current_stage == "Production"] + if not prod_versions: + raise RuntimeError(f"Aucune version en Production trouvée pour {model_name}") + latest_prod = max(prod_versions, key=lambda v: int(v.version)) + + # Récupérer le tag source_run_id + source_run_id = latest_prod.tags.get("source_run_id") + if not source_run_id: + raise RuntimeError(f"Tag 'source_run_id' absent pour la version {latest_prod.version}") + + print(f"📦 Téléchargement du modèle {model_name} (run: {source_run_id})") + + # Télécharger le fichier best_model.keras (VOTRE approche) + with tempfile.TemporaryDirectory() as tmpdir: + local_path = mlflow.artifacts.download_artifacts( + run_id=source_run_id, + artifact_path="best_model.keras", + dst_path=tmpdir + ) + + # ✅ SOLUTION : Charger SANS compiler d'abord + print("🔄 Chargement sans compilation...") + model = tf.keras.models.load_model(local_path, compile=False) + + # Puis recompiler avec la bonne métrique + print("🔄 Recompilation avec MeanIoU...") + model.compile( + optimizer='adam', + loss='sparse_categorical_crossentropy', + metrics=[tf.keras.metrics.MeanIoU(num_classes=8)] + ) + print("✅ Modèle chargé et recompilé !") + + # Récupérer les paramètres (votre logique) + run = mlflow.get_run(source_run_id) + encoder_name = run.data.params.get("encoder", None) + + script_img_size_str = run.data.params.get("script_img_size", None) + script_img_size = None + if script_img_size_str: + try: + script_img_size = tuple(int(x.replace(' ','').replace('(','').replace(')','').strip()) for x in script_img_size_str.split(",")) + except Exception as e: + print(f"⚠️ Impossible de parser 'script_img_size': {e}") + + return model, source_run_id, encoder_name, script_img_size + + +def map_mask_ids(mask, id_to_group_mapping): + """ + Applique le mapping des IDs Cityscapes vers les groupes + """ + if isinstance(id_to_group_mapping, np.ndarray): + # Vérifier que le mapping a bien 256 éléments + if len(id_to_group_mapping) != 256: + raise ValueError(f"id_to_group_mapping doit avoir 256 éléments, reçu: {len(id_to_group_mapping)}") + mapping_tensor = tf.constant(id_to_group_mapping, dtype=tf.int32) + else: + mapping_tensor = tf.constant(list(id_to_group_mapping), dtype=tf.int32) + + # S'assurer que les valeurs du masque sont dans la plage valide [0, 255] + mask_clipped = tf.clip_by_value(mask, 0, 255) + mapped_mask = tf.gather(mapping_tensor, mask_clipped) + return mapped_mask + + +def preprocess_image_and_mask(image_path, mask_path=None, img_size=(224, 224), + encoder_name=None, id_to_group_mapping=None): + """ + Préprocesse une image (et optionnellement un masque) avec le même pipeline que l'entraînement + + Args: + image_path (str): Chemin vers l'image + mask_path (str, optional): Chemin vers le masque de vérité + img_size (tuple): Taille de redimensionnement (H, W) + encoder_name (str): Nom du backbone pour le preprocessing + id_to_group_mapping: Mapping des IDs Cityscapes vers les groupes + + Returns: + tuple: (image_preprocessed, mask_preprocessed) ou (image_preprocessed, None) + """ + print(f"🔄 Préprocessing de l'image: {os.path.basename(image_path)}") + + # Preprocessing de l'image (même logique que l'entraînement) + img = tf.io.read_file(image_path) + img = tf.image.decode_image(img, channels=3) # Support PNG et JPG automatique + img_original = tf.image.resize(img, img_size, method='bilinear') # Pour affichage + img = tf.cast(img_original, tf.float32) + + # Appliquer le preprocessing du backbone + preprocessing_fn = get_preprocessing_fn(encoder_name) + img_preprocessed = preprocessing_fn(img) + + # Preprocessing du masque si fourni + mask_preprocessed = None + if mask_path and os.path.exists(mask_path): + print(f"🔄 Préprocessing du masque: {os.path.basename(mask_path)}") + + mask = tf.io.read_file(mask_path) + mask = tf.image.decode_image(mask, channels=1) # Support PNG et JPG pour les masques aussi + mask = tf.image.resize(mask, img_size, method='nearest') + mask = tf.cast(mask, tf.int32) + + print(f" Valeurs uniques avant mapping: {tf.unique(tf.reshape(mask, [-1]))[0][:10].numpy()}...") # Debug + + # Appliquer le mapping si fourni + if id_to_group_mapping is not None: + mask = map_mask_ids(mask, id_to_group_mapping) + print(f" Valeurs uniques après mapping: {tf.unique(tf.reshape(mask, [-1]))[0].numpy()}") # Debug + + mask_preprocessed = tf.squeeze(mask, axis=-1) + + return img_preprocessed, img_original, mask_preprocessed + + +def colorize_mask(mask, group_colors): + """ + Applique la colorisation du masque avec les couleurs définies + + Args: + mask (np.ndarray): Masque avec les IDs de classes + group_colors (np.ndarray): Couleurs RGB pour chaque classe + + Returns: + np.ndarray: Masque colorisé RGB + """ + colored_mask = np.zeros((mask.shape[0], mask.shape[1], 3), dtype=np.uint8) + num_classes = len(group_colors) + + for group_id in range(num_classes): + colored_mask[mask == group_id] = group_colors[group_id] + + return colored_mask + + +def run_inference_and_visualize(image_path, model, encoder_name, img_size, mapping_config, + mask_path=None, save_dir=None, show_stats=True): + print(f"=== INFÉRENCE SUR {os.path.basename(image_path)} ===") + + img_preprocessed, img_display, mask_gt = preprocess_image_and_mask( + image_path=image_path, + mask_path=mask_path, + img_size=img_size or (224, 224), + encoder_name=encoder_name, + id_to_group_mapping=mapping_config.get('id_to_group') + ) + + print("🔮 Exécution de l'inférence...") + img_batch = tf.expand_dims(img_preprocessed, axis=0) + predictions = model.predict(img_batch, verbose=0) + predicted_mask = tf.argmax(predictions[0], axis=-1).numpy() + print(f"✅ Inférence terminée - Shape: {predicted_mask.shape}") + + # Nombre de plots : 2 si pas de masque, sinon 4 (image, prédiction, vérité, erreurs) + num_plots = 2 if mask_gt is None else 4 + fig, axes = plt.subplots(1, num_plots, figsize=(5*num_plots, 5)) + if num_plots == 1: + axes = [axes] + + axes[0].imshow(img_display.numpy().astype(np.uint8)) + axes[0].set_title("Image Originale") + axes[0].axis('off') + + predicted_colored = colorize_mask(predicted_mask, mapping_config['group_colors']) + axes[1].imshow(predicted_colored) + axes[1].set_title("Masque Prédit") + axes[1].axis('off') + + if mask_gt is not None: + gt_colored = colorize_mask(mask_gt.numpy(), mapping_config['group_colors']) + axes[2].imshow(gt_colored) + axes[2].set_title("Masque de Vérité") + axes[2].axis('off') + + # Visualisation des erreurs en rouge translucide + diff_mask = (mask_gt.numpy() != predicted_mask).astype(float) + axes[3].imshow(img_display.numpy().astype(np.uint8)) + axes[3].imshow(diff_mask, alpha=0.5, cmap='Reds') + axes[3].set_title("Erreurs (en rouge)") + axes[3].axis('off') + + # Légende colorée + from matplotlib.colors import ListedColormap + import matplotlib.patches as mpatches + + colors_normalized = mapping_config['group_colors'] / 255.0 + custom_cmap = ListedColormap(colors_normalized) + + legend_elements = [] + for i, (name, color) in enumerate(zip(mapping_config['group_names'], colors_normalized)): + legend_elements.append(mpatches.Patch(color=color, label=f'{i}: {name}')) + + fig.legend(handles=legend_elements, + loc='center left', + bbox_to_anchor=(1.01, 0.5), + fontsize=9, + frameon=True, + fancybox=True, + shadow=True) + + plt.tight_layout() + fig.subplots_adjust(right=0.95) + + if save_dir: + os.makedirs(save_dir, exist_ok=True) + img_name = os.path.splitext(os.path.basename(image_path))[0] + fig_path = os.path.join(save_dir, f'{img_name}_inference.png') + fig.savefig(fig_path, dpi=150, bbox_inches='tight') + print(f"💾 Résultat sauvegardé: {fig_path}") + + plt.show() + + if show_stats: + print("\n📊 Statistiques du masque prédit:") + unique_classes, counts = np.unique(predicted_mask, return_counts=True) + for class_id, count in zip(unique_classes, counts): + if class_id < len(mapping_config['group_names']): + percentage = (count / predicted_mask.size) * 100 + print(f" {mapping_config['group_names'][class_id]}: {count} pixels ({percentage:.1f}%)") + + if mask_gt is not None: + print("\n📊 Statistiques du masque de vérité:") + unique_classes, counts = np.unique(mask_gt.numpy(), return_counts=True) + for class_id, count in zip(unique_classes, counts): + if class_id < len(mapping_config['group_names']): + percentage = (count / mask_gt.numpy().size) * 100 + print(f" {mapping_config['group_names'][class_id]}: {count} pixels ({percentage:.1f}%)") + + return predicted_mask \ No newline at end of file