From e0182389358424012bf2b4a8b83ce526481cf914 Mon Sep 17 00:00:00 2001 From: lepton Date: Mon, 1 Sep 2025 14:46:34 -0400 Subject: [PATCH] Updated data generation code --- .gitignore | 2 +- __pycache__/config_.cpython-312.pyc | Bin 1509 -> 1509 bytes .../generate_data_consensus.cpython-312.pyc | Bin 8748 -> 7815 bytes __pycache__/model.cpython-312.pyc | Bin 7119 -> 7119 bytes __pycache__/train_and_eval.cpython-312.pyc | Bin 10648 -> 11936 bytes config_.py | 19 +- generate_data_consensus.py | 81 +-- generate_data_kuramoto.py | 4 +- model.py | 3 +- plot_results.py | 88 +-- pyproject.toml | 2 + test.ipynb | 521 +++++++++++++++++- train_and_eval.py | 51 +- uv.lock | 61 ++ 14 files changed, 709 insertions(+), 123 deletions(-) diff --git a/.gitignore b/.gitignore index 6a66263..f04c7c0 100644 --- a/.gitignore +++ b/.gitignore @@ -1,6 +1,6 @@ .venv .env -__pycaches__ +__pycache__ datasets/ temp.* test.* diff --git a/__pycache__/config_.cpython-312.pyc b/__pycache__/config_.cpython-312.pyc 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graph_type == "watts_strogatz": - k = 2 - p = 0.1 + k = 4 + p = 0.5 G = nx.watts_strogatz_graph(num_agents, k, p, seed=rng) elif graph_type == "barabasi_albert": - m = 2 - if m >= num_agents: m = max(1, num_agents - 1) - G = nx.barabasi_albert_graph(num_agents, m, seed=rng) + G = nx.barabasi_albert_graph(num_agents, 2, seed=rng) elif graph_type == "powerlaw_cluster": - m = 3 # Number of random edges to add for each new node - p = 0.1 # Probability of adding a triangle after adding a random edge - if m >= num_agents: m = max(1, num_agents - 1) + m = 2 + p = 0.5 G = nx.powerlaw_cluster_graph(num_agents, m, p, seed=rng) - # Add self-loops, as they are often assumed in consensus algorithms - G.add_edges_from([(i, i) for i in range(num_agents)]) - adj_matrix = nx.to_numpy_array(G, dtype=np.float32) - return G, graph_type, adj_matrix + graph_matrix = nx.adjacency_matrix(G).todense() + + for i in range(num_agents): + graph_matrix[i,i]=1 + + G = nx.Graph(graph_matrix) + + return G, graph_type, graph_matrix + def calculate_graph_metrics(G: nx.Graph) -> dict: """ @@ -91,30 +92,30 @@ def calculate_graph_metrics(G: nx.Graph) -> dict: # --- Spectral & Community Metrics (Potentially Slow) --- # These are also limited to smaller graphs. - if 1 < num_nodes < 500: - # Eigenvalues of the Laplacian matrix - try: - laplacian_eigenvalues = sorted(nx.laplacian_spectrum(G)) - metrics["laplacian_eigenvalues"] = laplacian_eigenvalues - # The second-smallest eigenvalue of the Laplacian matrix - metrics["algebraic_connectivity"] = laplacian_eigenvalues[1] - except Exception: - metrics["laplacian_eigenvalues"] = None - metrics["algebraic_connectivity"] = None + # if 1 < num_nodes < 500: + # # Eigenvalues of the Laplacian matrix + # try: + # laplacian_eigenvalues = sorted(nx.laplacian_spectrum(G)) + # metrics["laplacian_eigenvalues"] = laplacian_eigenvalues + # # The second-smallest eigenvalue of the Laplacian matrix + # metrics["algebraic_connectivity"] = laplacian_eigenvalues[1] + # except Exception: + # metrics["laplacian_eigenvalues"] = None + # metrics["algebraic_connectivity"] = None - # Modularity using the Louvain community detection algorithm - if num_edges > 0: - try: - communities = nx_comm.louvain_communities(G, seed=123) - metrics["modularity"] = nx_comm.modularity(G, communities) - except Exception: - metrics["modularity"] = None # Algorithm may fail on some graphs - else: - metrics["modularity"] = None - else: - metrics["laplacian_eigenvalues"] = None - metrics["algebraic_connectivity"] = None - metrics["modularity"] = None + # # Modularity using the Louvain community detection algorithm + # if num_edges > 0: + # try: + # communities = nx_comm.louvain_communities(G, seed=123) + # metrics["modularity"] = nx_comm.modularity(G, communities) + # except Exception: + # metrics["modularity"] = None # Algorithm may fail on some graphs + # else: + # metrics["modularity"] = None + # else: + # metrics["laplacian_eigenvalues"] = None + # metrics["algebraic_connectivity"] = None + # metrics["modularity"] = None return metrics @@ -132,9 +133,9 @@ def main(): # --- Configuration --- GRAPH_GEN_ALGOS = ["erdos_renyi", "barabasi_albert", "powerlaw_cluster", "watts_strogatz"] AGENT_COUNTS = range(5, 51, 5)# 5, 10, ..., 50 agents - GRAPHS_PER_AGENT_COUNT = 100 + GRAPHS_PER_AGENT_COUNT = 80 GRAPHS_PER_GRAPH_ALGO = GRAPHS_PER_AGENT_COUNT // len(GRAPH_GEN_ALGOS) - SIMS_PER_GRAPH = 100 + SIMS_PER_GRAPH = 400 OUTPUT_DIR = "datasets/consensus_dataset" # --- Setup --- diff --git a/generate_data_kuramoto.py b/generate_data_kuramoto.py index 7cd4524..c9cfeed 100644 --- a/generate_data_kuramoto.py +++ b/generate_data_kuramoto.py @@ -82,9 +82,9 @@ def main(): GRAPH_GEN_ALGOS = ["erdos_renyi", "barabasi_albert", "powerlaw_cluster", "watts_strogatz"] AGENT_COUNTS = range(5, 51, 5) # 5, 10, ..., 50 agents # AGENT_COUNTS = [50] - GRAPHS_PER_AGENT_COUNT = 100 + GRAPHS_PER_AGENT_COUNT = 80 GRAPHS_PER_GRAPH_ALGO = GRAPHS_PER_AGENT_COUNT // len(GRAPH_GEN_ALGOS) - SIMS_PER_GRAPH = 100 + SIMS_PER_GRAPH = 400 OUTPUT_DIR = "datasets/kuramoto_dataset" # --- Setup --- diff --git a/model.py b/model.py index 0cf3e06..ffd7235 100644 --- a/model.py +++ b/model.py @@ -46,7 +46,7 @@ def init_fn(key: jax.Array, config: ModelConfig): def forward(params: dict, input_timesteps: jax.Array, config: ModelConfig): """ - Model's forward function. Takes in the parameters and inptu timesteps, returns predictions + Model's forward function. Takes in the parameters and input timesteps, returns predictions """ batch_size, num_agents, _ = input_timesteps.shape @@ -119,6 +119,7 @@ def train_model(config: ModelConfig, inputs: jax.Array, targets: jax.Array, params, opt_state, loss_val = update_step(params, opt_state, x, y, config) running_loss += loss_val + epoch_loss = running_loss / num_batches loss_history[f"epoch_{epoch}"].append(epoch_loss) diff --git a/plot_results.py b/plot_results.py index 78a152a..a36a5ae 100644 --- a/plot_results.py +++ b/plot_results.py @@ -10,7 +10,7 @@ from train_and_eval import calculate_f1_score from sklearn.metrics import f1_score if len(sys.argv) < 2: - data_dir = "datasets/consensus_dataset" + data_dir = "datasets/kuramoto_dataset" else: data_dir = "datasets/" + sys.argv[1] @@ -22,53 +22,59 @@ for folder in tqdm(os.listdir(data_dir)): folder_path = os.path.join(data_dir, folder) - # Load model config from summary json - with open(os.path.join(folder_path, "results/NoiseType.NONE", "summary_results.json"), "r") as f: - summary_results = json.load(f) + for noise_level in os.listdir(os.path.join(folder_path, "results/NoiseType.NONE")): - - for i, graph in enumerate(os.listdir(folder_path)): - # train_summary_results - summ_results = summary_results[i-1] + # Load model config from summary json + with open(os.path.join(folder_path, "results/NoiseType.NONE", noise_level, "summary_results.json"), "r") as f: + summary_results = json.load(f) - if graph == "results": # ignore the result folder + + for i, graph in enumerate(os.listdir(folder_path)): + + # train_summary_results + summ_results = summary_results[i-1] + + if graph == "results": # ignore the result folder + continue + + graph_path = os.path.join(folder_path, graph) + + # Load run data + with open(os.path.join(folder_path, graph), "r") as f: + run_data = json.load(f) + + true_graph = np.array(run_data["adjacency_matrix"]) + + learned_graph = np.array(summ_results["raw_attention"]) + + predicted_graph = (learned_graph > THRESHOLD).astype(int) + + true_flat = true_graph.flatten() + pred_flat = predicted_graph.flatten() + + calc_f1_score = f1_score(true_flat, pred_flat) + + + datapoints[num_agents] = datapoints.get(num_agents, []) + datapoints[num_agents].append(calc_f1_score) + + + for key in datapoints.keys(): + try: + datapoints[key] = sum(datapoints[key])/len(datapoints[key]) + except: continue - graph_path = os.path.join(folder_path, graph) - # Load run data - with open(os.path.join(folder_path, graph), "r") as f: - run_data = json.load(f) + x = [] + y = [] - true_graph = np.array(run_data["adjacency_matrix"]) - - learned_graph = np.array(summ_results["raw_attention"]) + for item in datapoints.items(): + x.append(item[0]) + y.append(item[1]) - predicted_graph = (learned_graph > THRESHOLD).astype(int) - - true_flat = true_graph.flatten() - pred_flat = predicted_graph.flatten() - - calc_f1_score = f1_score(true_flat, pred_flat) - - - datapoints[num_agents] = datapoints.get(num_agents, []) - datapoints[num_agents].append(calc_f1_score) - - -for key in datapoints.keys(): - datapoints[key] = sum(datapoints[key])/len(datapoints[key]) - - -x = [] -y = [] - -for item in datapoints.items(): - x.append(item[0]) - y.append(item[1]) - -plt.plot(x, y) -plt.show() + plt.plot(x, y) + plt.show() \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index aafb930..771cc92 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -12,6 +12,8 @@ dependencies = [ "matplotlib>=3.10.3", "networkx>=3.5", "optax>=0.2.5", + "pyqt6>=6.9.1", + "python-dotenv>=1.1.1", "scikit-learn>=1.7.1", "seaborn>=0.13.2", "tqdm>=4.67.1", diff --git a/test.ipynb b/test.ipynb index afd8842..c91c608 100644 --- a/test.ipynb +++ b/test.ipynb @@ -584,7 +584,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "a9136787", "metadata": {}, "outputs": [], @@ -594,7 +594,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "742861f5", "metadata": {}, "outputs": [ @@ -629,7 +629,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [00:57<00:00, 5.71s/it]" + "100%|██████████| 10/10 [01:51<00:00, 11.18s/it]" ] }, { @@ -648,7 +648,7 @@ }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -660,7 +660,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [00:57<00:00, 5.72s/it]" + "100%|██████████| 10/10 [01:52<00:00, 11.23s/it]" ] }, { @@ -679,7 +679,7 @@ }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -691,7 +691,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [00:57<00:00, 5.73s/it]" + "100%|██████████| 10/10 [01:52<00:00, 11.29s/it]" ] }, { @@ -710,7 +710,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -722,7 +722,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [00:57<00:00, 5.73s/it]" + "100%|██████████| 10/10 [01:51<00:00, 11.18s/it]" ] }, { @@ -741,7 +741,7 @@ }, { "data": { - "image/png": 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AAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFA/KA0ZZMGTxBGIAiAIxAoyi6qZWVe47otZAT3iZx+mQrzRXC/I8BkcGALGL0zTAKKluatWyHQ0RISJJ/kCPlu1oUHVTq6GRAUBsI0aAURAMWarcd0TWIO/1L6vcd0TB0GBrAEByI0aAUVDX3DHgiMgXWZJaAz2qa+4Yv0EBQJwgRoBR0N41dIiMZD0ASCbECDAKpk92jOp6AJBMiBFgFBTmZMjjdGioCbw2nZlVU5iTMZ7DAoC4QIwAoyA1xSZfaa4kDQiS/q99pbncbwQABkGMAKNkQZ5HW26fJ7cz8lSM2+nQltvncZ8RABgCNz0DRtGCPI9uyHVzB1YAiAIxAoyy1BSbvJdMNT0MAIgbnKYBAABGESMAAMAoYgQAABjFNSMABhUMWVyIC2BcjOjIyObNm5WdnS2Hw6GioiLV1dUNa7tdu3bJZrNp4cKFI/lYAOOkuqlV3/zNP7Ro2z+1clejFm37p775m3/w5GEAYyLqGNm9e7fKy8vl8/nU0NCg/Px8lZSUqL29/Uu3O378uO677z5de+21Ix4sgLFX3dSqZTsaBjz4zx/o0bIdDQQJgFEXdYxs2LBBd999t5YuXarc3Fxt3bpV5557rrZv3z7kNsFgULfddpsqKyt18cUXf+Vn9Pb2qrOzM+IFYOwFQ5Yq9x2RNch7/csq9x1RMDTYGgAwMlHFSF9fn+rr61VcXPz5N0hJUXFxsWpra4fc7le/+pWmT5+uO++8c1ifU1VVJafTGX5lZWVFM0wAI1TX3DHgiMgXWZJaAz2qa+4Yv0EBSHhRxcipU6cUDAblcrkilrtcLvn9/kG3ee211/Tss89q27Ztw/6ciooKBQKB8KulpSWaYQIYofauoUNkJOsBwHCM6Wyarq4u3XHHHdq2bZumTZs27O3sdrvsdvsYjgzAYKZPdnz1SlGsBwDDEVWMTJs2TampqWpra4tY3tbWJrfbPWD9999/X8ePH1dpaWl4WSgUOvPBEybo6NGjuuSSS0YybgBjoDAnQx6nQ/5Az6DXjdh05sF/hTkZ4z00AAksqtM0aWlpKigoUE1NTXhZKBRSTU2NvF7vgPVnzZqlt99+W42NjeHXd7/7XV133XVqbGzkWhAgxqSm2OQrzZV0Jjy+qP9rX2ku9xsBMKqiPk1TXl6uJUuWaP78+SosLNTGjRvV3d2tpUuXSpIWL16szMxMVVVVyeFwKC8vL2L7888/X5IGLAcQGxbkebTl9nmq3Hck4mJWt9MhX2muFuR5DI4OQCKKOkbKysp08uRJrVu3Tn6/X3PmzFF1dXX4otYTJ04oJYW7zAPxbEGeRzfkurkDK4BxYbMsK+ZvGNDZ2Smn06lAIKD09HTTwwEAAMMw3L/fPJsGQELjGTtA7CNGACSs6qbWAde+eLj2BYg5XNwBICHxjB0gfhAjABIOz9gB4gsxAiDh8IwdIL4QIwASDs/YAeILMQIg4fCMHSC+ECMAEk7/M3aGmsBr05lZNTxjB4gNxAiAhMMzdoD4QowASEj9z9hxOyNPxbidDm25fV7c3WckGLJU+/7/6c+NH6r2/f9jJhASCjc9A5CwEuUZO9y8DYmOZ9MAQAzrv3nb//6Puj+n4vEoD5LHcP9+c5oGAGIUN29DsiBGACBGcfM2JAtiBABiFDdvQ7IgRgAgRnHzNiQLZtMAQIzqv3mbP9Az6HUjNp2ZqhxPN28Lhqy4n92E0UeMAECM6r9527IdDbJJEUESjzdvY4oyhsJpGgCIYYly87b+Kcr/e0GuP9CjZTsaVN3UamhkiAUcGQGAGBfvN2/7qinKNp2ZonxDrjtufiaMLmIEAOJAaopN3kummh7GiEQzRTlef0acHU7TAADGFFOU8VU4MgIAGFOJOEWZWUGjixgBAIypRJuizKyg0cdpGgDAmOqfoix9PiW5X7xNUWZW0NggRgAAYy4Rpijz4MKxw2kaAMC4iPcpyswKGjvECABg3MTzFOVEnBUUKxfiEiMAAAxDos0KiqULcblmBACAYeifFTTUcQObzvwxj4dZQbF2IS4xAgDAMCTKrKBYvBCXGAEAYJgSYVZQNBfijheuGQEAIArxPisoFi/EJUYAAIhSPM8KisULcTlNAwBAEonFC3GJEQAAkkgsXohLjAAAkGRi7UJcrhkBACAJxdKFuMQIAABJKlYuxOU0DQAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFEjipHNmzcrOztbDodDRUVFqqurG3Ldbdu26dprr9WUKVM0ZcoUFRcXf+n6AAAguUQdI7t371Z5ebl8Pp8aGhqUn5+vkpIStbe3D7r+oUOHtGjRIr3yyiuqra1VVlaWbrzxRn344YdnPXgAABD/bJZlWdFsUFRUpKuuukqbNm2SJIVCIWVlZWnFihVas2bNV24fDAY1ZcoUbdq0SYsXLx50nd7eXvX29oa/7uzsVFZWlgKBgNLT06MZLgAAMKSzs1NOp/Mr/35HdWSkr69P9fX1Ki4u/vwbpKSouLhYtbW1w/oen3zyiT777DNlZGQMuU5VVZWcTmf4lZWVFc0wAQBAHIkqRk6dOqVgMCiXyxWx3OVyye/3D+t73H///ZoxY0ZE0PyviooKBQKB8KulpSWaYQIAgDgyYTw/bP369dq1a5cOHTokh8Mx5Hp2u112u30cRwYAAEyJKkamTZum1NRUtbW1RSxva2uT2+3+0m1/+9vfav369fr73/+u2bNnRz9SAACQkKI6TZOWlqaCggLV1NSEl4VCIdXU1Mjr9Q653WOPPaaHH35Y1dXVmj9//shHCwAAEk7Up2nKy8u1ZMkSzZ8/X4WFhdq4caO6u7u1dOlSSdLixYuVmZmpqqoqSdJvfvMbrVu3Tjt37lR2dnb42pJJkyZp0qRJo/ijAACAeBR1jJSVlenkyZNat26d/H6/5syZo+rq6vBFrSdOnFBKyucHXLZs2aK+vj796Ec/ivg+Pp9PDz300NmNHgAAxL2o7zNiwnDnKQMAgNgxJvcZAQAAGG3ECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGDUiGJk8+bNys7OlsPhUFFRkerq6r50/T179mjWrFlyOBy68sordeDAgRENFgAAJJ6oY2T37t0qLy+Xz+dTQ0OD8vPzVVJSovb29kHXf/3117Vo0SLdeeed+te//qWFCxdq4cKFampqOuvBAwCA+GezLMuKZoOioiJdddVV2rRpkyQpFAopKytLK1as0Jo1awasX1ZWpu7ubr300kvhZVdffbXmzJmjrVu3DvoZvb296u3tDX8dCAQ0c+ZMtbS0KD09PZrhAgAAQzo7O5WVlaXTp0/L6XQOud6EaL5pX1+f6uvrVVFREV6WkpKi4uJi1dbWDrpNbW2tysvLI5aVlJToxRdfHPJzqqqqVFlZOWB5VlZWNMMFAAAxoKura/Ri5NSpUwoGg3K5XBHLXS6X3n333UG38fv9g67v9/uH/JyKioqIgAmFQuro6NDUqVNls9miGXJS6C9PjhzFDvZJbGF/xBb2R2wZy/1hWZa6uro0Y8aML10vqhgZL3a7XXa7PWLZ+eefb2YwcSQ9PZ1f7BjDPokt7I/Ywv6ILWO1P77siEi/qC5gnTZtmlJTU9XW1haxvK2tTW63e9Bt3G53VOsDAIDkElWMpKWlqaCgQDU1NeFloVBINTU18nq9g27j9Xoj1pekgwcPDrk+AABILlGfpikvL9eSJUs0f/58FRYWauPGjeru7tbSpUslSYsXL1ZmZqaqqqokSStXrtS3vvUtPfHEE7rlllu0a9cuvfXWW3r66adH9ydJYna7XT6fb8CpLZjDPokt7I/Ywv6ILbGwP6Ke2itJmzZt0uOPPy6/3685c+boySefVFFRkSTp29/+trKzs/Xcc8+F19+zZ48efPBBHT9+XJdddpkee+wx3XzzzaP2QwAAgPg1ohgBAAAYLTybBgAAGEWMAAAAo4gRAABgFDECAACMIkbiyKuvvqrS0lLNmDFDNpttwPN9LMvSunXr5PF4NHHiRBUXF+u9994zM9gkUFVVpauuukqTJ0/W9OnTtXDhQh09ejRinZ6eHi1fvlxTp07VpEmT9MMf/nDATQAxOrZs2aLZs2eH7yLp9Xr117/+Nfw++8Ks9evXy2azadWqVeFl7JPx89BDD8lms0W8Zs2aFX7f9L4gRuJId3e38vPztXnz5kHff+yxx/Tkk09q69ateuONN3TeeeeppKREPT094zzS5HD48GEtX75c//znP3Xw4EF99tlnuvHGG9Xd3R1eZ/Xq1dq3b5/27Nmjw4cP66OPPtIPfvADg6NOXBdeeKHWr1+v+vp6vfXWW/rOd76j733ve/r3v/8tiX1h0ptvvqnf//73mj17dsRy9sn4+vrXv67W1tbw67XXXgu/Z3xfWIhLkqy9e/eGvw6FQpbb7bYef/zx8LLTp09bdrvd+uMf/2hghMmnvb3dkmQdPnzYsqwz//7nnHOOtWfPnvA677zzjiXJqq2tNTXMpDJlyhTrmWeeYV8Y1NXVZV122WXWwYMHrW9961vWypUrLcvi92O8+Xw+Kz8/f9D3YmFfcGQkQTQ3N8vv96u4uDi8zOl0qqioSLW1tQZHljwCgYAkKSMjQ5JUX1+vzz77LGKfzJo1SzNnzmSfjLFgMKhdu3apu7tbXq+XfWHQ8uXLdcstt0T820v8fpjw3nvvacaMGbr44ot122236cSJE5JiY1/E5FN7ET2/3y9JcrlcEctdLlf4PYydUCikVatW6ZprrlFeXp6kM/skLS1twBOn2Sdj5+2335bX61VPT48mTZqkvXv3Kjc3V42NjewLA3bt2qWGhga9+eabA97j92N8FRUV6bnnntMVV1yh1tZWVVZW6tprr1VTU1NM7AtiBBgFy5cvV1NTU8Q5WIy/K664Qo2NjQoEAnrhhRe0ZMkSHT582PSwklJLS4tWrlypgwcPyuFwmB5O0rvpppvC/z179mwVFRXpoosu0vPPP6+JEycaHNkZnKZJEG63W5IGXP3c1tYWfg9j495779VLL72kV155RRdeeGF4udvtVl9fn06fPh2xPvtk7KSlpenSSy9VQUGBqqqqlJ+fr9/97nfsCwPq6+vV3t6uefPmacKECZowYYIOHz6sJ598UhMmTJDL5WKfGHT++efr8ssv17Fjx2Li94MYSRA5OTlyu92qqakJL+vs7NQbb7whr9drcGSJy7Is3Xvvvdq7d6/+8Y9/KCcnJ+L9goICnXPOORH75OjRozpx4gT7ZJyEQiH19vayLwy4/vrr9fbbb6uxsTH8mj9/vm677bbwf7NPzPn444/1/vvvy+PxxMTvB6dp4sjHH3+sY8eOhb9ubm5WY2OjMjIyNHPmTK1atUqPPPKILrvsMuXk5Gjt2rWaMWOGFi5caG7QCWz58uXauXOn/vznP2vy5Mnhc6tOp1MTJ06U0+nUnXfeqfLycmVkZCg9PV0rVqyQ1+vV1VdfbXj0iaeiokI33XSTZs6cqa6uLu3cuVOHDh3Syy+/zL4wYPLkyeHrp/qdd955mjp1ang5+2T83HfffSotLdVFF12kjz76SD6fT6mpqVq0aFFs/H6My5wdjIpXXnnFkjTgtWTJEsuyzkzvXbt2reVyuSy73W5df/311tGjR80OOoENti8kWX/4wx/C63z66afWz372M2vKlCnWueeea33/+9+3WltbzQ06gf3kJz+xLrroIistLc264IILrOuvv97629/+Fn6ffWHeF6f2Whb7ZDyVlZVZHo/HSktLszIzM62ysjLr2LFj4fdN7wubZVnW+GQPAADAQFwzAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAw6v8BkGWPg1T8mmcAAAAASUVORK5CYII=", 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", 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" ] @@ -753,7 +753,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [00:57<00:00, 5.74s/it]" + "100%|██████████| 10/10 [01:51<00:00, 11.20s/it]" ] }, { @@ -772,7 +772,7 @@ }, { "data": { - "image/png": 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", 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" ] @@ -784,7 +784,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [00:57<00:00, 5.75s/it]" + "100%|██████████| 10/10 [01:52<00:00, 11.20s/it]" ] }, { @@ -803,7 +803,7 @@ }, { "data": { - "image/png": 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", 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AgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIpP7QVGmD9gqa65Q+1dPUpLdigvK1WJCTbT0wKAiEWMACOouqlVlXsOqdXXE9yW7nSooihbC2elG5wZAEQuLtMAI6S6qVXLtjWEhIgkeX09WratQdVNrYZmBgCRjRgBRoA/YKlyzyFZg3yvf1vlnkPyBwYbAQDxjRgBRkBdc8eAMyL/zZLU6utRXXPH2E0KAKIEMQKMgPauoUNkOOMAIJ4QI8AISEt2jOg4AIgnxAgwAvKyUpXudGioB3htOv1UTV5W6lhOCwCiAjECjIDEBJsqirIlaUCQ9H9dUZTNeiMAMAhiBBghC2ela/Pt8+R2hl6KcTsd2nz7PNYZAYAhsOgZMIIWzkrXDdluVmAFgDAQI8AIS0ywyXPJFNPTAICoMazLNJs2bVJmZqYcDofy8/NVV1d3Tvvt2LFDNptNixYtGs7bAgCAGBR2jOzcuVNlZWWqqKhQQ0ODcnJyVFhYqPb29jPu99FHH+m+++7TNddcM+zJAgCA2BN2jDzxxBO6++67tXTpUmVnZ2vLli0677zz9Nxzzw25j9/v12233abKykpdfPHFZ32P3t5edXZ2hrwAAEBsCitG+vr6VF9fr4KCgq9+QEKCCgoKVFtbO+R+v/rVr5SWlqY777zznN6nqqpKTqcz+MrIyAhnmgAAIIqEFSMnT56U3++Xy+UK2e5yueT1egfd54033tCzzz6rrVu3nvP7lJeXy+fzBV8tLS3hTBPACPAHLNUe+1QvN36s2mOf8iF/AEbNqD5N09XVpTvuuENbt27V1KlTz3k/u90uu90+ijMDcCbVTa2q3HMo5MP/0p0OVRRls14KgBEXVoxMnTpViYmJamtrC9ne1tYmt9s9YPyxY8f00UcfqaioKLgtEAicfuNx43TkyBFdcsklw5k3gFFS3dSqZdsa9L/nQby+Hi3b1sACbgBGXFiXaZKSkpSbm6uamprgtkAgoJqaGnk8ngHjZ86cqXfffVeNjY3B1/e+9z1dd911amxs5F4QIML4A5Yq9xwaECKSgtsq9xzikg2AERX2ZZqysjItWbJE8+fPV15enjZs2KDu7m4tXbpUklRSUqLp06erqqpKDodDs2bNCtl/0qRJkjRgOwDz6po7Qi7N/C9LUquvR3XNHSzsBmDEhB0jxcXFOnHihNatWyev16s5c+aouro6eFPr8ePHlZDAR94A0ai9a+gQGc44ADgXNsuyIv58a2dnp5xOp3w+n1JSUkxPB4hZtcc+1eKt/zjruD/efRVnRgCc1bn+/eYUBoCgvKxUpTsdGupj/Ww6/VRNXlbqWE4LQIwjRgAEJSbYVFGULUkDgqT/64qibD6FGMCIIkYAhFg4K12bb58nt9MRst3tdETlY70s3gZEvlFd9AxAdFo4K103ZLtV19yh9q4epSWfvjQTbWdEWLwNiA7cwAogJg21eFt/TkXjWR4g2nADK4C4xeJtQHQhRgDEnHAWbwNgHjECIOaweBsQXYgRADEnLdlx9kFhjAMwuogRADGHxduA6EKMAIg5LN4GRBdiBEBMirXF24BYxqJnAGJWrCzeBsQ6YgRATEtMsMXEJwz7AxZRhZhFjABAhGNZe8Q67hkBgAjWv6z9/y7i5vX1aNm2BlU3tRqaGTByiBEAiFAsa494QYwAQIRiWXvEC2IEACIUy9ojXhAjABChWNYe8YKnaQAgQvUva+/19Qx634hNpxdxi6Zl7XlEGYMhRgAgQvUva79sW4NsUkiQROOy9jyijKFwmQYAIlisLGvPI8o4E86MAECEi/Zl7c/2iLJNpx9RviHbHTW/E0YWMQIAUSCal7UP5xHlaP0d8fUQIwCAURWLjyhzI+7IIkYAAKMq1h5R5kbckccNrACAUdX/iPJQ5w1sOv3HPBoeUeZG3NFBjAAARlX/I8qSBgRJND2izGcFjR5iBAAw6mLhEeVY/Kwgf8BS7bFP9XLjx6o99qmxkOKeEQDAmIj2R5Rj7UbcSLr3hRgBAIyZaH5EOZZuxO2/9+V/z4P03/sy1meruEwDAMA5iJUbcSPx3hdiBACAcxArN+JG4r0vxAgAAOcoFm7EjcR7X7hnBACAMET7jbiReO8LMQIAQJii+Ubc/ntfvL6eQe8bsen0mZ6xvPeFyzQAAMSRSLz3hRgBACDORNq9L1ymAQAgDkXSvS/ECAAAcSpS7n3hMg0AADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABg1LBiZNOmTcrMzJTD4VB+fr7q6uqGHLt161Zdc801mjx5siZPnqyCgoIzjgcAAPEl7BjZuXOnysrKVFFRoYaGBuXk5KiwsFDt7e2Djj9w4IAWL16s1157TbW1tcrIyNCNN96ojz/++GtPHgAARD+bZVlWODvk5+drwYIF2rhxoyQpEAgoIyNDy5cv15o1a866v9/v1+TJk7Vx40aVlJQMOqa3t1e9vb3Brzs7O5WRkSGfz6eUlJRwpgsAAAzp7OyU0+k869/vsM6M9PX1qb6+XgUFBV/9gIQEFRQUqLa29px+xueff64vv/xSqampQ46pqqqS0+kMvjIyMsKZJgAAiCJhxcjJkyfl9/vlcrlCtrtcLnm93nP6GatXr9a0adNCguZ/lZeXy+fzBV8tLS3hTBMAAESRcWP5ZuvXr9eOHTt04MABORyOIcfZ7XbZ7fYxnBkAADAlrBiZOnWqEhMT1dbWFrK9ra1Nbrf7jPv+5je/0fr16/W3v/1Ns2fPDn+mAAAgJoV1mSYpKUm5ubmqqakJbgsEAqqpqZHH4xlyv0cffVQPPfSQqqurNX/+/OHPFgAAxJywL9OUlZVpyZIlmj9/vvLy8rRhwwZ1d3dr6dKlkqSSkhJNnz5dVVVVkqRf//rXWrdunbZv367MzMzgvSUTJ07UxIkTR/BXAQAA0SjsGCkuLtaJEye0bt06eb1ezZkzR9XV1cGbWo8fP66EhK9OuGzevFl9fX368Y9/HPJzKioq9OCDD3692QMAgKgX9jojJpzrc8oAACByjMo6IwAAACONGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMGlaMbNq0SZmZmXI4HMrPz1ddXd0Zx+/atUszZ86Uw+HQlVdeqX379g1rsgAAIPaEHSM7d+5UWVmZKioq1NDQoJycHBUWFqq9vX3Q8W+++aYWL16sO++8U//85z+1aNEiLVq0SE1NTV978gAAIPrZLMuywtkhPz9fCxYs0MaNGyVJgUBAGRkZWr58udasWTNgfHFxsbq7u/XKK68Et1111VWaM2eOtmzZMuh79Pb2qre3N/i1z+fTjBkz1NLSopSUlHCmCwAADOns7FRGRoZOnTolp9M55Lhx4fzQvr4+1dfXq7y8PLgtISFBBQUFqq2tHXSf2tpalZWVhWwrLCzUSy+9NOT7VFVVqbKycsD2jIyMcKYLAAAiQFdX18jFyMmTJ+X3++VyuUK2u1wuHT58eNB9vF7voOO9Xu+Q71NeXh4SMIFAQB0dHZoyZYpsNls4U44L/eXJmaPIwTGJLByPyMLxiCyjeTwsy1JXV5emTZt2xnFhxchYsdvtstvtIdsmTZpkZjJRJCUlhX/YEYZjElk4HpGF4xFZRut4nOmMSL+wbmCdOnWqEhMT1dbWFrK9ra1Nbrd70H3cbndY4wEAQHwJK0aSkpKUm5urmpqa4LZAIKCamhp5PJ5B9/F4PCHjJWn//v1DjgcAAPEl7Ms0ZWVlWrJkiebPn6+8vDxt2LBB3d3dWrp0qSSppKRE06dPV1VVlSRpxYoVuvbaa/X444/rlltu0Y4dO/TOO+/o6aefHtnfJI7Z7XZVVFQMuLQFczgmkYXjEVk4HpElEo5H2I/2StLGjRv12GOPyev1as6cOXryySeVn58vSfrOd76jzMxMPf/888Hxu3bt0gMPPKCPPvpIl112mR599FHdfPPNI/ZLAACA6DWsGAEAABgpfDYNAAAwihgBAABGESMAAMAoYgQAABhFjESR119/XUVFRZo2bZpsNtuAz/exLEvr1q1Tenq6JkyYoIKCAn3wwQdmJhsHqqqqtGDBAiUnJystLU2LFi3SkSNHQsb09PSotLRUU6ZM0cSJE/WjH/1owCKAGBmbN2/W7Nmzg6tIejwe/eUvfwl+n2Nh1vr162Wz2bRy5crgNo7J2HnwwQdls9lCXjNnzgx+3/SxIEaiSHd3t3JycrRp06ZBv//oo4/qySef1JYtW/TWW2/p/PPPV2FhoXp6esZ4pvHh4MGDKi0t1T/+8Q/t379fX375pW688UZ1d3cHx6xatUp79uzRrl27dPDgQX3yySf64Q9/aHDWsevCCy/U+vXrVV9fr3feeUff/e539f3vf1//+te/JHEsTHr77bf1u9/9TrNnzw7ZzjEZW9/85jfV2toafL3xxhvB7xk/FhaikiRr9+7dwa8DgYDldrutxx57LLjt1KlTlt1ut/74xz8amGH8aW9vtyRZBw8etCzr9P//8ePHW7t27QqOee+99yxJVm1tralpxpXJkydbzzzzDMfCoK6uLuuyyy6z9u/fb1177bXWihUrLMvi38dYq6iosHJycgb9XiQcC86MxIjm5mZ5vV4VFBQEtzmdTuXn56u2ttbgzOKHz+eTJKWmpkqS6uvr9eWXX4Yck5kzZ2rGjBkck1Hm9/u1Y8cOdXd3y+PxcCwMKi0t1S233BLy/17i34cJH3zwgaZNm6aLL75Yt912m44fPy4pMo5FRH5qL8Ln9XolSS6XK2S7y+UKfg+jJxAIaOXKlbr66qs1a9YsSaePSVJS0oBPnOaYjJ53331XHo9HPT09mjhxonbv3q3s7Gw1NjZyLAzYsWOHGhoa9Pbbbw/4Hv8+xlZ+fr6ef/55XXHFFWptbVVlZaWuueYaNTU1RcSxIEaAEVBaWqqmpqaQa7AYe1dccYUaGxvl8/n04osvasmSJTp48KDpacWllpYWrVixQvv375fD4TA9nbh30003Bf979uzZys/P10UXXaQXXnhBEyZMMDiz07hMEyPcbrckDbj7ua2tLfg9jI57771Xr7zyil577TVdeOGFwe1ut1t9fX06depUyHiOyehJSkrSpZdeqtzcXFVVVSknJ0e//e1vORYG1NfXq729XfPmzdO4ceM0btw4HTx4UE8++aTGjRsnl8vFMTFo0qRJuvzyy3X06NGI+PdBjMSIrKwsud1u1dTUBLd1dnbqrbfeksfjMTiz2GVZlu69917t3r1bf//735WVlRXy/dzcXI0fPz7kmBw5ckTHjx/nmIyRQCCg3t5ejoUB119/vd599101NjYGX/Pnz9dtt90W/G+OiTmfffaZjh07pvT09Ij498Flmijy2Wef6ejRo8Gvm5ub1djYqNTUVM2YMUMrV67Uww8/rMsuu0xZWVlau3atpk2bpkWLFpmbdAwrLS3V9u3b9fLLLys5OTl4bdXpdGrChAlyOp268847VVZWptTUVKWkpGj58uXyeDy66qqrDM8+9pSXl+umm27SjBkz1NXVpe3bt+vAgQN69dVXORYGJCcnB++f6nf++edrypQpwe0ck7Fz3333qaioSBdddJE++eQTVVRUKDExUYsXL46Mfx9j8swORsRrr71mSRrwWrJkiWVZpx/vXbt2reVyuSy73W5df/311pEjR8xOOoYNdiwkWb///e+DY7744gvr5z//uTV58mTrvPPOs37wgx9Yra2t5iYdw376059aF110kZWUlGRdcMEF1vXXX2/99a9/DX6fY2Hefz/aa1kck7FUXFxspaenW0lJSdb06dOt4uJi6+jRo8Hvmz4WNsuyrLHJHgAAgIG4ZwQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYNT/A7WanF+zfRnqAAAAAElFTkSuQmCC", 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" ] @@ -815,7 +815,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [00:57<00:00, 5.74s/it]" + "100%|██████████| 10/10 [01:51<00:00, 11.16s/it]" ] }, { @@ -834,7 +834,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -846,8 +846,156 @@ "name": "stderr", "output_type": "stream", "text": [ - " 0%| | 0/10 [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 10/10 [01:51<00:00, 11.14s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-1.0\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "image/png": 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", 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ksd4IACQ4YgRGzZ+RpQ23zJHbGXkpxu10aMMtc1hnBACSAIuewbj5M7J0bZ6bFVgBIEkRI4gJqSk2+S6cbHoYAAADuEwDAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwKghxcj69euVk5Mjh8Mhr9erhoaGszpu69atstlsWrBgwVBeFgAAJKCoY2Tbtm0qLy9XVVWVmpqalJ+fr+LiYnV0dJzxuPfee0933323rrzyyiEPFogHwZCl+sP/0R+b31f94f8oGLJMDwkAYprNsqyo/k/p9Xo1b948rVu3TpIUCoXk8Xi0bNkyrVq1asBjgsGgvv71r+u2227T3//+d508eVLPP//8oK/R29ur3t7e8NednZ3yeDwKBAJKT0+PZrjAqKptaVP1zv1qC3z6ScNZToeqSvJYTRZA0uns7JTT6fzcv99RvTPS19enxsZGFRUVffoNUlJUVFSk+vr6QY/72c9+pszMTN1+++1n9To1NTVyOp3hh8fjiWaYgBG1LW1aurkpIkQkyR/o0dLNTaptaTM0MgCIbVHFyPHjxxUMBuVyuSK2u1wu+f3+AY955ZVX9PTTT2vTpk1n/ToVFRUKBALhR2trazTDBEZdMGSpeud+DfQ24+lt1Tv3c8kGAAYwosvBd3V16dZbb9WmTZs0ZcqUsz7ObrfLbreP4MiA4dVw5ES/d0Q+y5LUFuhRw5ETLHsPAP8jqhiZMmWKUlNT1d7eHrG9vb1dbre73/6HDx/We++9p5KSkvC2UCh06oXHjNHBgwd14YUXDmXcQEzp6Bo8RIayHwAkk6gu06SlpamgoEB1dXXhbaFQSHV1dfL5fP32nz59ut588001NzeHH9/61rd09dVXq7m5mbkgSBiZExzDuh8AJJOoL9OUl5dr8eLFmjt3rgoLC7V27Vp1d3dryZIlkqRFixYpOztbNTU1cjgcmjFjRsTxEydOlKR+24F4VpiboSynQ/5Az4DzRmyS3E6HCnMzRntoABDzoo6R0tJSHTt2TJWVlfL7/Zo1a5Zqa2vDk1qPHj2qlBQWdkVySU2xqaokT0s3N8kmRQSJ7f//WVWSp9QU2wBHA0Byi3qdERPO9j5lwDTWGQGAT53t3+8RvZsGSDbzZ2Tp2jy3Go6cUEdXjzInnLo0wzsiADA4YgQYZqkpNm7fBYAoMLkDAAAYRYwAAACjiBEAAGAUc0YADCgYspiIC2BUECMA+uEWZQCjics0ACLUtrRp6eamfh/85w/0aOnmJtW2tBkaGYBERYwACAuGLFXv3D/gkvant1Xv3K9gKObXSgQQR4gRAGENR070e0fksyxJbYEeNRw5MXqDApDwmDMCIKyja/AQGcp+sYCJuEDsI0YAhGVOcAzrfqYxEReID1ymARBWmJuhLKdDg71vYNOpP+aFuRmjOawhYSIuED+IEQBhqSk2VZXkSVK/IDn9dVVJXsxf5mAiLhBfiBEAEebPyNKGW+bI7Yy8FON2OrThljlxcXmDibhAfGHOCIB+5s/I0rV57rid+JmIE3GBREaMABhQaopNvgsnmx7GkCTaRFwg0XGZBkDCSaSJuEAyIEYAJJxEmYgLJAtiBEBCSoSJuECyYM4IgIQV7xNxP4uVZJHIiBEACS2eJ+KexkqySHRcpgGAGMZKskgGxAgAxChWkkWyIEYAIEaxkiySBTECADGKlWSRLIgRAIhRrCSLZMHdNAAQo06vJOsP9Aw4b8SmU+umxNNKstyijIEQIwAQo06vJLt0c5NsUkSQxONKstyijMFwmQYAYliirCTLLco4E94ZAYAYF+8ryX7eLco2nbpF+do8d9z8TBhexAgAxIF4Xkk2mluU4+VnZO7L8CJGAAAjKtFuUWbuy/BjzggAYEQl0i3KzH0ZGcQIAGBEnb5FebCLGDademch1m9RZnn+kUOMAABG1OlblCX1C5J4ukU5EZfnD4Ys1R/+j/7Y/L7qD//HWEgxZwQAMOJO36L8v3Mt3HE014K5LyOHGAEAjIp4v0U5Eee+/O/7IKfnvoz2GjbECABg1MTzLcqJsjx/LK77wpwRAADOAnNfRg4xAgDAWUqE5fljce4Ll2kAAIgCc1+GHzECAECUmPsyvLhMAwBAEonFuS/ECAAASSbW5r5wmQYAgCQUS3NfiBEAAJJUrMx94TINAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUUOKkfXr1ysnJ0cOh0Ner1cNDQ2D7rtp0yZdeeWVmjRpkiZNmqSioqIz7g8AAJJL1DGybds2lZeXq6qqSk1NTcrPz1dxcbE6OjoG3H/v3r1auHChXnrpJdXX18vj8ei6667T+++//4UHDwAA4p/NsiwrmgO8Xq/mzZundevWSZJCoZA8Ho+WLVumVatWfe7xwWBQkyZN0rp167Ro0aIB9+nt7VVvb2/4687OTnk8HgUCAaWnp0czXAAAYEhnZ6ecTufn/v2O6p2Rvr4+NTY2qqio6NNvkJKioqIi1dfXn9X3+Oijj/TJJ58oIyNj0H1qamrkdDrDD4/HE80wAQBAHIkqRo4fP65gMCiXyxWx3eVyye/3n9X3uOeeezR16tSIoPlfFRUVCgQC4Udra2s0wwQAAHFkzGi+2Jo1a7R161bt3btXDodj0P3sdrvsdvsojgwAAJgSVYxMmTJFqampam9vj9je3t4ut9t9xmN/+ctfas2aNfrrX/+qmTNnRj9SAACQkKK6TJOWlqaCggLV1dWFt4VCIdXV1cnn8w163MMPP6wHHnhAtbW1mjt37tBHCwAAEk7Ul2nKy8u1ePFizZ07V4WFhVq7dq26u7u1ZMkSSdKiRYuUnZ2tmpoaSdIvfvELVVZWasuWLcrJyQnPLRk/frzGjx8/jD8KAACIR1HHSGlpqY4dO6bKykr5/X7NmjVLtbW14UmtR48eVUrKp2+4bNiwQX19ffr+978f8X2qqqp0//33f7HRAwCAuBf1OiMmnO19ygAAIHaMyDojAAAAw40YAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwaUoysX79eOTk5cjgc8nq9amhoOOP+27dv1/Tp0+VwOHTZZZdp9+7dQxosAABIPFHHyLZt21ReXq6qqio1NTUpPz9fxcXF6ujoGHD/V199VQsXLtTtt9+uf/7zn1qwYIEWLFiglpaWLzx4AAAQ/2yWZVnRHOD1ejVv3jytW7dOkhQKheTxeLRs2TKtWrWq3/6lpaXq7u7WCy+8EN52+eWXa9asWdq4ceOAr9Hb26ve3t7w14FAQNOmTVNra6vS09OjGS4AADCks7NTHo9HJ0+elNPpHHS/MdF8076+PjU2NqqioiK8LSUlRUVFRaqvrx/wmPr6epWXl0dsKy4u1vPPPz/o69TU1Ki6urrfdo/HE81wAQBADOjq6hq+GDl+/LiCwaBcLlfEdpfLpQMHDgx4jN/vH3B/v98/6OtUVFREBEwoFNKJEyc0efJk2Wy2aIacFE6XJ+8cxQ7OSWzhfMQWzkdsGcnzYVmWurq6NHXq1DPuF1WMjBa73S673R6xbeLEiWYGE0fS09P5xY4xnJPYwvmILZyP2DJS5+NM74icFtUE1ilTpig1NVXt7e0R29vb2+V2uwc8xu12R7U/AABILlHFSFpamgoKClRXVxfeFgqFVFdXJ5/PN+AxPp8vYn9J2rNnz6D7AwCA5BL1ZZry8nItXrxYc+fOVWFhodauXavu7m4tWbJEkrRo0SJlZ2erpqZGkrR8+XJdddVVevTRR3XjjTdq69ateuONN/Tkk08O70+SxOx2u6qqqvpd2oI5nJPYwvmILZyP2BIL5yPqW3slad26dXrkkUfk9/s1a9YsPf744/J6vZKkb3zjG8rJydEzzzwT3n/79u2677779N577+niiy/Www8/rBtuuGHYfggAABC/hhQjAAAAw4XPpgEAAEYRIwAAwChiBAAAGEWMAAAAo4iROPLyyy+rpKREU6dOlc1m6/f5PpZlqbKyUllZWRo3bpyKior0zjvvmBlsEqipqdG8efM0YcIEZWZmasGCBTp48GDEPj09PSorK9PkyZM1fvx4fe973+u3CCCGx4YNGzRz5szwKpI+n09//vOfw89zLsxas2aNbDabVqxYEd7GORk9999/v2w2W8Rj+vTp4edNnwtiJI50d3crPz9f69evH/D5hx9+WI8//rg2btyo1157Teeee66Ki4vV09MzyiNNDvv27VNZWZn+8Y9/aM+ePfrkk0903XXXqbu7O7zPypUrtXPnTm3fvl379u3TBx98oO9+97sGR524zj//fK1Zs0aNjY1644039M1vflPf/va39a9//UsS58Kk119/Xb/+9a81c+bMiO2ck9H1la98RW1tbeHHK6+8En7O+LmwEJckWTt27Ah/HQqFLLfbbT3yyCPhbSdPnrTsdrv1+9//3sAIk09HR4clydq3b59lWaf++48dO9bavn17eJ+33nrLkmTV19ebGmZSmTRpkvXUU09xLgzq6uqyLr74YmvPnj3WVVddZS1fvtyyLH4/RltVVZWVn58/4HOxcC54ZyRBHDlyRH6/X0VFReFtTqdTXq9X9fX1BkeWPAKBgCQpIyNDktTY2KhPPvkk4pxMnz5d06ZN45yMsGAwqK1bt6q7u1s+n49zYVBZWZluvPHGiP/2Er8fJrzzzjuaOnWqvvSlL+nmm2/W0aNHJcXGuYjJT+1F9Px+vyTJ5XJFbHe5XOHnMHJCoZBWrFihK664QjNmzJB06pykpaX1+8RpzsnIefPNN+Xz+dTT06Px48drx44dysvLU3NzM+fCgK1bt6qpqUmvv/56v+f4/RhdXq9XzzzzjC699FK1tbWpurpaV155pVpaWmLiXBAjwDAoKytTS0tLxDVYjL5LL71Uzc3NCgQCeu6557R48WLt27fP9LCSUmtrq5YvX649e/bI4XCYHk7Su/7668P/PnPmTHm9Xl1wwQV69tlnNW7cOIMjO4XLNAnC7XZLUr/Zz+3t7eHnMDLuuusuvfDCC3rppZd0/vnnh7e73W719fXp5MmTEftzTkZOWlqaLrroIhUUFKimpkb5+fn61a9+xbkwoLGxUR0dHZozZ47GjBmjMWPGaN++fXr88cc1ZswYuVwuzolBEydO1CWXXKJDhw7FxO8HMZIgcnNz5Xa7VVdXF97W2dmp1157TT6fz+DIEpdlWbrrrru0Y8cO/e1vf1Nubm7E8wUFBRo7dmzEOTl48KCOHj3KORkloVBIvb29nAsDrrnmGr355ptqbm4OP+bOnaubb745/O+cE3M+/PBDHT58WFlZWTHx+8Flmjjy4Ycf6tChQ+Gvjxw5oubmZmVkZGjatGlasWKFHnzwQV188cXKzc3V6tWrNXXqVC1YsMDcoBNYWVmZtmzZoj/+8Y+aMGFC+Nqq0+nUuHHj5HQ6dfvtt6u8vFwZGRlKT0/XsmXL5PP5dPnllxsefeKpqKjQ9ddfr2nTpqmrq0tbtmzR3r179eKLL3IuDJgwYUJ4/tRp5557riZPnhzezjkZPXfffbdKSkp0wQUX6IMPPlBVVZVSU1O1cOHC2Pj9GJV7djAsXnrpJUtSv8fixYstyzp1e+/q1astl8tl2e1265prrrEOHjxodtAJbKBzIcn67W9/G97n448/tn784x9bkyZNss455xzrO9/5jtXW1mZu0Anstttusy644AIrLS3NOu+886xrrrnG+stf/hJ+nnNh3mdv7bUszsloKi0ttbKysqy0tDQrOzvbKi0ttQ4dOhR+3vS5sFmWZY1O9gAAAPTHnBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFH/B1mSqRLBmylPAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -867,6 +1015,7 @@ "\n", "for THRESHOLD in np.arange(-5, 1, 0.5):\n", " datapoints = {}\n", + " \n", "\n", " for folder in tqdm(os.listdir(data_dir)):\n", " num_agents = int(folder.split(\"_\")[1]) # Extract num agents\n", @@ -874,7 +1023,7 @@ " folder_path = os.path.join(data_dir, folder)\n", "\n", " # Load model config from summary json\n", - " with open(os.path.join(folder_path, \"results/NoiseType.NONE\", \"summary_results.json\"), \"r\") as f:\n", + " with open(os.path.join(folder_path, \"results/NoiseType.NONE\", \"0.01\", \"summary_results.json\"), \"r\") as f:\n", " summary_results = json.load(f)\n", "\n", " \n", @@ -926,11 +1075,345 @@ "\n", " " ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "7a4fe194", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 10/10 [00:01<00:00, 6.23it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-0.4\n" + ] + }, + { + "data": { + "image/png": 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33HNUVlbG1jv6EcEW2n5bLBbq3bs37dy5ky3v2rWruD7Kzs6mb7/99jh7eOLAjc0JRvutwPFo34ShUIjGjh1Lv//973Xr9+3bt822+vfvT0REmzZtossvv7x1eXp6Oo0ZM4aIDsfhhNvvzz//nC677DI6//zz6bnnnqPOnTtTUlISzZs3j1577bVj79hxtBUDpJTqULsA8dQywccvfvELmjJlim6dwYMHE9HhQP5rr72WrrjiCvrd735H+fn5ZLPZaObMma0XG0c71thyvPdTKBQii8VCH3zwgW5doxJWHj0GDRkypHV5Xl5e6xj06quv6q6rt3/tPUbham8MIkBHDBs2rHVWtLYc/QtCi1AoRPn5+bRgwQLdddr6AjSWYtXHo8eWc845p3V5t27dWmP/Wp500dIbW/785z/TAw88QNdffz09/PDDlJOTQ1arlaZPn37ciZqOBdc2uLE5aWRnZ1NtbS1b5vf7af/+/WxZr169qL6+vvUioD3OO+88crlctHDhQpoxY0aHpzN88803KTk5mZYsWUJOp7N1+bx583Trb9u2TSzbunUrpaamJsQADBBteXl5lJGRQcFg8Ljv4TfeeIN69uxJb731FvuG76GHHjK8X7169SKlFJWUlBzzy5GWR8S2bdvWOnMTEVFzczOVlZWxmxU948ePJ5vNRgsWLGCzE0WqvceorTGoZTIUADPp1asXffzxx3TOOecc84uNo9+3R/+yWl1dfdxfIXv16kVEh28YjjVmtfVYWiz6SER0ySWX0GOPPUYLFixgNzaReuONN+iCCy4Q+bRqa2upU6dOor52bFFK0fbt21u/qIIjEGNzkujVq5eIj3nxxRfFLzZXXXVV67SGWrW1tRQIBNrcRmpqKv3+97+nTZs20b333qv7DUF7vjWw2WxksVhYH3fu3Elvv/22bv0VK1awZ1PLy8vpnXfeoYsuugjfkMJJwWaz0eTJk+nNN9/UnWa4urqa1SXi78lVq1bRihUrDO/XlVdeSTabjf74xz+KMUAp1RpzN3ToUMrLy6MXXniBzVQ0f/588cWMnuLiYrr++uvpgw8+oGeffVa3TnvHIO06xzpGb7/9Nu3du7e1/PXXX9OqVatOntmI4IRy1VVXUTAYpIcfflj8LRAItL4nx4wZQ0lJSfTMM8+w98qxZlFtccYZZ1BJSQnNnj1bvMePbqslp462Tiz6SHT4cdaxY8fSiy++SO+8845unfaOLdr6ixYtYuPH0VpmXGzxxhtv0P79+zG26MAvNieJX//613TLLbfQ5MmTaezYsfTNN9/QkiVLxDcDv/vd7+jf//43XXLJJXTttddSaWkpNTQ00MaNG+mNN96gnTt36n6b0OLee++l77//nmbNmkX//e9/afLkydS1a1eqqamhdevW0aJFiyg/Pz+sBF0TJ06kp556ii6++GL6+c9/TlVVVTR37lzq3bu37vOiAwcOpHHjxrHpnomI/vjHP7bzaAEktr///e+tuZ6Odscdd9Bjjz1Gn376KQ0fPpxuvPFGOvXUU+nQoUO0bt06+vjjj+nQoUNEdPgbyLfeeosmTZpEEydOpLKyMnrhhRfo1FNPFTEqHdWrVy965JFHaMaMGbRz50664oorKCMjg8rKymjx4sV000030d13301JSUn0yCOP0M0330yjR4+mn/3sZ1RWVkbz5s0LK8aG6PCFSllZGd1+++20cOFCuvTSSyk/P58OHDhAX375Jb377rvUr1+/sNpq7zHq3bs3nXvuuXTrrbeSz+ej2bNnU25ubpuP9gIkspEjR9LNN99MM2fOpA0bNtBFF11ESUlJtG3bNlq0aBHNmTOHfvKTn7TmYZo5cyZdcsklNGHCBFq/fj198MEHx7xeIDqcsPP555+nSy+9lE477TS67rrrqHPnzvTDDz/Qd9991/ola8vEQL/5zW9o3LhxZLPZ6Oqrr45JH1u8+uqrdPHFF9MVV1xB48ePpzFjxlB2djZVVFTQxx9/TJ999lnYNxqXXHIJ/elPf6LrrruOzj77bNq4cSMtWLCgzXEuJyeHzj33XLruuuuosrKSZs+eTb1796Ybb7wxrO2dVGI7CRsYpa3pngcMGKBbPxgMqnvuuUd16tRJpaamqnHjxqnt27eL6Z6VUqqurk7NmDFD9e7dWzkcDtWpUyd19tlnqyeeeEL5/f6w+rd48WI1YcIElZeXp+x2u8rKylLnnnuumjVrlpgukYjU1KlTddt5+eWXVZ8+fZTT6VT9+/dX8+bNa51iVq+NV199tbX+6aef3jqlZIuWdaurq9nylmkxy8rKwto/gHhoOU/b+ldeXq6UUqqyslJNnTpVdevWTSUlJanCwkJ14YUXqhdffLG1rVAopP785z+r7t27t75f3nvvPTVlyhTVvXv31notUxnPmjVL9Ke976c333xTnXvuuSotLU2lpaWp/v37q6lTp6otW7awes8995wqKSlRTqdTDR06VH322Wdq5MiRx53uuUUgEFDz5s1To0ePVjk5Ocput6tOnTqpCy+8UL3wwguqqakprP2L5Bg9+eSTqlu3bsrpdKrzzjtPffPNN6zNKVOmqLS0tDaPJYBRwpkeXqm2z8kWL774oiotLVUpKSkqIyNDDRo0SP3+979X+/bta60TDAbVH//4R9W5c2eVkpKiRo0apTZt2iSuMbTTPbf44osv1NixY1VGRoZKS0tTgwcPVs8880zr3wOBgLr99ttVXl6eslgs4r1iZB+PpampSc2ePVuNGDFCZWZmKrvdrgoLC9Ull1yiFixYoAKBgNjXRYsWiXa8Xq/67W9/29qXc845R61YsUKMcy1t/POf/1QzZsxQ+fn5KiUlRU2cOFHt2rWLtdnWNaB2vDrRWZQ6iSKK4IRlsVho6tSpbT5+AgAQLTt37qSSkhKaNWsW3X333fHuDgCcIJYtW0YXXHABLVq0iH7yk5/EuzumgBgbAAAAAAAwPdzYAAAAAACA6eHGBgAAAAAATA8xNgAAAAAAYHr4xQYAAAAAAEwvanls5s6dS7NmzaKKigoaMmQIPfPMMzRs2LDjrhcKhWjfvn2UkZHRZqZZAIgNpRTV1dVRUVERWa2x/R4k0jGECOMIQCIx4ziCMQQgcbRrDInGHNILFy5UDodD/f3vf1ffffeduvHGG1VWVpaqrKw87rrl5eXHzNOAf/iHf7H/15IfJVY6MoYohXEE//AvEf+ZaRzBGIJ/+Jd4/8IZQ6ISYzN8+HA688wzW3OKhEIh6tatG91+++107733HnNdt9tNWVlZtGtdD8pMP3JXNqnvIFZv8daNYl1tnXCE045R2+pInyLZfqz7Hc72tYzqT6T7Gk4fIxXpeaStF06daPHUh6j7GTuptraWXC5XTLZJ1LExhOjIOPLnZcMoOf3ID9OzP57A6qVUyG9+Uqr5kGhrlkPkofGNrJy6Il3U8ebwsq8wIOoULZXfBHt62Pj2faIKuYf4WTllh0PUsfEqlH3hflGnekVnsSxtL9/fg0ODok7qbv5jf/IBeYxqBoVYuWiZrFPbh7fj7STrJLnlMeq0iR/LPWNFFcrcytuu6y33o8tSvr2qoTZRh4J8+2n7ZR/9LtnH9D18/7058lzz9OJ1VLo8R1J/5K+tNy8k6lj9cvshB+9nyn65fbvm3GroIvdN2fmyolMrRZ19mwtY2dbI+xPyeWnnrIdNNY60dS2iFelnWDjj/PHWMcv2jVov3n2MtE4k/QlXJNuL9PohntdU7bkWMfxRNL/fT2vXrqUZM2a0LrNarTRmzBhasWKFqO/z+cjnOzK61tXVERFRZrqVMjOODCZ2SxJb7+i/tVUnHOG0Y9S2OtKnSLYf636Hs30to/oT6b6G08dIRXoeaeuFUyfaYvkoRnvHEKK2x5HkdDulHHVjY01OZuvZnPI42jQXhDaSF3vWVH5xaXMkizo2p2adFHnRak+Sx9Xm1NzY6Hz1ZE3h/bY5dW5sNE3b05yyjlOn35r9t6bIGwKbk390aNc5vB4/RvYkWUfbjjVZp45XHiN7Ej+W1hRRRbatsx/aPlmT5Y2NRXNjo7evNqdeH7XniDzXtMdI6Zwj2tfWmqxzY2PVeX9qz2O9c12zK3rHX3tjo3cead9X1pD+eJHI40i41yJakX6GhTPOH28ds2zfqPXi3cdI60TSn3BFsr1Irx/ifU1FFN4YYngPDhw4QMFgkAoK+Dc4BQUFVFFRIerPnDmTXC5X679u3boZ3SUAMJH2jiFEGEcAgMO1CMDJKe6zos2YMYPcbnfrv/Ly8nh3CQBMBuMIAHQExhCAE4Phj6J16tSJbDYbVVby53ArKyupsLBQ1Hc6neR0yp+2J/UdxH72WrJvA/v7uKLTxDraOuEwqp1w19PbXiR1Iu2jUe0YtR+RiuR80Ktj5Ouf6O2EQ3s8AqqZiHbEbPtE7R9DiNoeR+Y9N5E9JvbNA0+zv4+5Z7pY55r7PmDlFxZMFHUC1fzZp7qe8vEgRy3/3qjoE/k9UuVw+bO6a+ABVrb9M0fUIc1qenE4SQ2aWJmPi0Sdgm/8Ylkoifczfbv8mAik8XLTBI+ok+ts5u3as0WdZE08U/ZW+bhYY558PKwhny+zZnhlna68jqVZHuvdV/Dt2Q/IbaVW83JdiahCzdnyETJl5cdNG3NDRGTR7G6nz+SjHu4J9awcqpGPD6aW1ItlaU7+2lamyvModzXfX9VVHkfLHr69Br987PHGi5ay8us7T2flYKPOCRplsboW0RPOZ8/x1tFbL9LPK6M+iyNtJ5bXNEZed0TyWuvR9incfY1kX2J9TRPN67xIGf6LjcPhoNLSUlq69MhAFwqFaOnSpTRixAijNwcAJxiMIQDQURhHAE5OUcljc9ddd9GUKVNo6NChNGzYMJo9ezY1NDTQddddF43NAcAJBmMIAHQUxhGAk09Ubmx+9rOfUXV1NT344INUUVFBp512Gn344YciiA8AQA/GEADoKIwjACefqOSx6QiPx0Mul4tqtvZk08ZF+oxiJKL5PGgs2w7nechIn8+NVsxTW20Z0XY0+2jUcTRyvXDaOV67nroQZffdQW63mzIzM9u9zXhpGUdOmfpnNqWxRRMKseC3T4p1pzx8FyvXDJBDZMHXvBzUmbY55Zc8b8zu7+Vz/ZYcGXsQquNxFo5DMu6j+394Hp1AhozN2HcuX5b9g9yP7G9qxLLv78rgfdSZb/rUHvv49u+U8Rv1PXluH/cv6kQdn49/t9ZcK+NHrF75xHTqPr4sNNwt6mSk8GNrt8oYl9D8fN4fnXw0XX5exsrblvYUddL36EwB7efLlM6UzIcG8HKgU7Ook1TJX8eg3pTYRY1iWdrn/Pg7J1aJOjV1qaw8qGifqLPjtT6s7Oklt9/9fd5vfxZ/XQPNXvr63w+YahxpGUNG0eXHnOY20s/ZWMad6Ilk++HGU8Tq86kjjLqmjOZxDEcsz5FYXptqBVQzLaN3whpD4j4rGgAAAAAAQEfhxgYAAAAAAEwPNzYAAAAAAGB6uLEBAAAAAADTS9jJA7QBe7EMRotm4F8skxnFMrFjuGIZaBfvwPxIJ1gwKojSiHOtPQF7iaRlHDn1Fj55QMNZPMg69z8yWP3Jh59j5Xt/e6uoM+S+Day87snTRR1/Bg8Wz/5BJj+sK5YJAWsu433s+jcZuFx2LR+2U7+T++F38ToXX7RG1Fn61pliGWk+Ebx5Muhe5fBgcVuFTNro7MuTdtqXuUQdm49vTJtUlIgoqVEuq7yqiZUzPk0TdUI2fvzrz5UB9oEmHuRe+LGcKNSi2f39F8jjoT1mRESWAN++NVdnoogD/PXv8qlsZ88Evj1Lks7robP9vHx+/JNflAlS07fzSRd2XpEr6gTSeOPN2TKJaspeftzyvuGzdASavbTygwdNNY6Eey1i1NgfzYDyaE4AdKIk34zl526sJ4WI9/E34rhh8gAAAAAAADip4MYGAAAAAABMDzc2AAAAAABgevKBYhOLVhJPI59ZjOVzrUa1bVSiz/bUa2870YxdCuc4RjNWK5w+6bUdrbg0M7EoHiOh9vNYlIbO8rudB265iZef+7uo87tnb2Rl3yly2/5cHotQ20/G01i7yriPkid5TEPaE7tFnZz/683Kdd11giw0u7bltv6yzoVyUWNvv1yokZfH4zeqAzrxMxv5soaBMvmkPV0uE3WSZExH3us8sWSzDLGh+t78mBT9U8YBVQ7lH4E1OofI30luX0iWddKz+WtrWS5jXPJX8zrbfyXjqVJ28WVOmVNVPzapgSdN3TMpIOokb+MxNcHB9aKOcy1P9EkWmTDW14nH/SRP1yRwbfARfSBWO2FF8zM0ntuPZoLOWLdrVLxvOH2KZYxLNGO7jbrOieR65XCy8GP3rwV+sQEAAAAAANPDjQ0AAAAAAJgebmwAAAAAAMD0cGMDAAAAAACmd0JNHhCJSBNXJWLCq2gmFo2kTjQD3YyqEw6jjmM0Ay+j9bq2J2AvEQVH1RKlHgnaV3V88oCk7TKx5e6L+LB47xO/FnUWzZjFynee/VNRp/acYl7uJb9HSt4qo97Lx/HEjsn/TBd1Grvxct4GmbSxIZ8HefeZu1XU2f1uqVjm3MOD7Jt7NYk6h9y83869MjB/9IR1rPz9/QNFnZp+fBIAa7MMgk85KJf5XPwYhXQ+yXq+oUk+eXmWqFOwhgfUe7NlYLz9O76t6tPl62jvIyeBqDvAj5H9TFmnpi6FlTO2WESd+iE8sWtKtgzwdzfK87hzNp/godNrnUWdTl8fYOXvu2WJOpnVmkkYxpWLOrs/5+d6+ae8HPTJ5LRmsXjrRsrMaN93wPFO0Kll1PbjnXQ81pPbROtaxKjJp/TaTsQEnUa0HVDNRLQjrLbwiw0AAAAAAJgebmwAAAAAAMD0cGMDAAAAAACml7AxNtrnWo1KSBjNxFlGPWtp1HOMsYzVMer16Mh6kbQTjmg+sxrp9rWMOo+067TnudZEZPski2yOI/EHjjz+97QKmVjR3YfHOdT3kO3edMt0Vn75q6dFnYn/+B0rZ22VcTDBJBlToRVIkXU6Datg5R5jDok6X37Lg6M2z5AxLv4pMn4mbQOP++g5U8aGKBvv05a75XdkX79wOisfmij3v9M6Hr9Ro5Po1N1PLrPma/pdniLq1J6Sycp5a2WsTrcZPO7oq6295MYa+MekrUG+Hs5PMsUyawYvZ+yWH7fVpbxPoXyfbPtHHj+TuUrGAWX75Hns6c5jauq7yX47ruYxRj2elq9R5we3sfKWV2QW06TxPGtoqoMnXg02yP0yi0l9B5HdIhOntkesE2RGwsjP60j6Gc1rEaMkYvxKop030Yo/R4JOAAAAAAA4qeDGBgAAAAAATA83NgAAAAAAYHq4sQEAAAAAANNL2MkDtAF7RiWzimbirFgm3Apn+0Yxcj+MSnhl1LE2aj2jkppGul609sPsCTqbChVZk48EaIc0eSQ9Uzyklbwqm5X92TLo3JvDA7h/8vjvRZ0//OafrDzryatFHV+OTiC6Zh6A2lK/qBP6tJCV11sLRZ3kM+pY+dCpGaJO6kaxiGyauPy9j8rvvxx2Hqye845T1FGaGHflkMfxwAU8qDwlXQaZKyWPUebbPGlpQ2dZp7Ez3171mTIwPv1+PlmA+rnOZA5W3k7392UffdkyuDxQy9tyumWAv6MHP9je/TJha+cV/PW3Ncl2vHkyQWrORn5uV49IFXX2b85n5ZSb60Sd3av47A2h0+X2T/l//Njuu5C3e7Il6DRqYgCjPtOjmaw7lu1E2nak29O2bYZJIKLJqOucSM5HJOgEAAAAAICTCm5sAAAAAADA9HBjAwAAAAAAppewMTaRPNcaTtyFUQmfwmk7UvF+rjWSZ1ZjnTjMiOSTbbUdyXpG7n88Y7VOtASdzRkhsqYcef6/6DP+9/rybNIq3MxjKA7cLhNUpr/PE0I6flUj6jz6v//Dyjfd8R9RZ96zE8SylIM8piOpwC3qhL7qxMr1xaIK2dfymJqmfBnj4hgg225elcXKtk/lMcpay49JXXe9OCQ+flub5Hge0nwENXpl8kk9TefzOI+MH2TbSfU8xiW5WtbZcRXvd/Ie+ZGoDfHZfbHsY3OWjDux8NyXZG2SbWdoEnsGi+Rx3D+Cby+pXlShjN1y+/UlPA6JbLJOKJXHxnjLZByWyuXJNlO3yHiqH27LYmVroybxqFful1lFazw28lokltvXo10vEWNKIvmcNSr5pJHx0LFMUGoUJOgEAAAAAAA4DtzYAAAAAACA6eHGBgAAAAAATA83NgAAAAAAYHoJO3mANkGnViwD7YxMnBXNoDozBI0ZlSA1mvsay+Sb0UxKlogBm7GmHIolhqztrQlWP1UmDiz6gE8EMKxzlajzTY/BfMFrMkFmcy8eMH0oIJMvzr/nabHs6pfuYuWJnbeLOut28KDz1GoZ0B5K4lHvjXnye6zGkEssU6fz6HSrs1nU2T5Esy9emfwy6zu+vcztcvue3rzs6Nog+6MTd144P5mVy8fK7ZNmvaQ6mXzTtZmfD+5TAqJOWgHvU8OhFFFHT1I2T6zpP5Qs6qQc4sfElyuPUfpuzXk0UG7LO1Sex2oXT8hpccjXUXtogy6d13E1nyzA2ixfkMBpPNFoMKA5HxvNm6DzeOJ9nRHN7YdTR2/7Rn0+h3O9ZNRnb7zbMYpRE0sZKdbXIvjFBgAAAAAATA83NgAAAAAAYHq4sQEAAAAAANNr943NZ599RpdeeikVFRWRxWKht99+m/1dKUUPPvggde7cmVJSUmjMmDG0bds2o/oLACaHMQQAOgrjCADoaffkAQ0NDTRkyBC6/vrr6corrxR/f/zxx+mvf/0r/eMf/6CSkhJ64IEHaNy4cbR582ZKTpbBk+EyKtjJqOD1aDIqMDya/Y607UgmeDAqI3K4QZaxfP1jPelAe7ffnmy/4YrlGJL5vZ1sziPDnPs0HtBNfvndjv1lHgi94W+DRR3SxKHXlcjAdJsmXvq190aKOrsvzBHLnrr2ZVa+6x83iDpJgzTlep0Ie02XavvLOimVcv8DW/nEAAG/3Ld0Hy/X95GB6a4dfJm7p5wMpvMXvE/1XTJEnaDOS75rMn8d7SkyON1q44HwrlPrRZ2DdXxfLVWpoo7FwvtoccgAe8shh1imDmj2N0dOTFB5CT+QXf8lj1FdVx6IH8yRxzo1xS+WNffi/bRsSxd1gil839J3yfPBl83LmTvledR8gE+okLOBtxOU3euwWI0j2omMIvmsiTSgO9LA9Gh9hkXzMzQRJ+AxYp1oi/f1qpZR29e2E1DNRLQjrHXbfWMzfvx4Gj9+vO7flFI0e/Zsuv/+++nyyy8nIqJXXnmFCgoK6O2336arr75arOPz+cjnOzK4ezye9nYJAEzE6DGECOMIwMkG1yIAoMfQGJuysjKqqKigMWPGtC5zuVw0fPhwWrFihe46M2fOJJfL1fqvW7duRnYJAEwkkjGECOMIAByBaxGAk5ehNzYVFRVERFRQUMCWFxQUtP5Na8aMGeR2u1v/lZeXG9klADCRSMYQIowjAHAErkUATl5xT9DpdDrJ6XQev2IYzBCbEsnzkOH2J5LnWGP97G2kbUVSJ9JtGXUco5lEM1rneiI+QxyOtsYR79l1ZEs9EpPQdSGPoag6Q36303wnT8j4PyuWiDof3nQeK7v7ydgMX1ceC3FmvzJRZ7hLPjP8+G2/ZOXN858TdUr/eCsr156qE2OjWZS/WlYZdPs3YtnHm/uzssUq207aw491UbeDoo7flc/K9d1kO7UD+bKJQ9eKOlaLjGlZ99gZrFzTR8a4NBUFWdnxsqyTNJAvGzBpq6iz5QDfj6yv5HkWSJVxSE2FfN9SduklnObL9p8jj1Gf5/ewcvaWfFGHSJ5/9noe2LLzUrlWbl/+unn35Ik6vlx+/DOWyXimmlN4jE39WB7PFGz0Es2X208kbY0hi7dupMyMI+NEtOJE9UQzaWQkY7+RSUQjYeTnU7Sul4z83I9WrFYs45L01otkP9oT72voLzaFhYezb1dWVrLllZWVrX8DAGgLxhAA6CiMIwAnL0NvbEpKSqiwsJCWLl3auszj8dCqVatoxIgRRm4KAE5AGEMAoKMwjgCcvNr9KFp9fT1t3769tVxWVkYbNmygnJwcKi4upunTp9MjjzxCffr0aZ1isaioiK644goj+w0AJoUxBAA6CuMIAOhp943NmjVr6IILLmgt33XXXURENGXKFJo/fz79/ve/p4aGBrrpppuotraWzj33XPrwww87lMMGAE4cGEMAoKMwjgCAHotSSifqNH48Hg+5XC4aRZezpFiRiGbwdiy3H27AVrQCwY0MNIukrXgHZ8Y60M6oYxROu8cL6guoZlpG75Db7abMzMx29yteWsaRnvPvI2vqkQuZZi//Lqf4dZt2Vdrzc55Isdv/ye9/uj20hZVXLxko6jgP8XLh525Rp76nTJp4cCDvU+FKmd3wj8+/xMpv1QwVdT7a2Y+VfT45noaq5UWew80D4ZPqZWC8VZMjUo2sEXWam/lxS152/OSbKdXy48jpCYpl3ix+jOq7yj6m7eVtNRbKOs2ZvI5dZ1/zvuXnQ32RPGeSGmS/PSX8SW9vntwPUnx7OvMkiESroXSZ6NOuTQZKRIECft70ni8brzqdB/3nr28SdbZfy/fDWqtzHqVq9k2zX6EmL+2Z/qCpxpGWMaRma082eYBWpAkq451YMZYTxcT7sziazJDQ2yixvhY62uHJA3aENYYYGmMDAAAAAAAQD7ixAQAAAAAA08ONDQAAAAAAmF7cE3RGUywTYBm5/XCSKUUrpkKvjhliXCI9RuGIZnKzSLcfDqNeIzPzNzjIGjqShDF3BY8PqOkjYyose/iwWDFc1in/YgArB7v7RJ1AMk/+6O0skyh6esh4jbR9PF6jpp9MLLnDz5M03pe/XNQZlMoTOz7270mijurULJYlFTeycujrLFEnqMljaAnqJDrdncbbHSvjcBobeJCN7csUUaehSH5MWTQhHd58Gb/S1IMv6/SVjA05VMCPdSBdxqHUV/PXKLVK1nHWyOPYUMj3zRLUOdcKeLJLVSFjnpKr+LFtsuvE+OjEBqVW8hcpZJPnaF0J35cuC/aIOpa6nqzc9ROdWJ0z+LEN2flxDXlln80qWmOmWWNMYinen7NGXdPFWjSvBaKVdL4j12/4xQYAAAAAAEwPNzYAAAAAAGB6uLEBAAAAAADTw40NAAAAAACYXsJOHrB460aWFCuS4KdIA/O1wg1iiiT4LNIAfyPXO14dvf2KZvLPSNo2MnFVtBKd6ollEtdETBIXbbkrk8jmOBLY7M3RJA7UyQEcLORB1radMqA7mMYD0x17ZYC/NsDe3iQD3NP3yqBqpfm6yeeSgeF/3XoBK9f2khMTTEj/jpX/opMf0tIktx8I8GVWuXmyl/KJABrq5TFSuTyg/vo+K0SdBWXDWNlZKY9jvU6wfP1wnkjSvkvnNcrmCSpDSfLFVpog99Q9cls2nyYQXudT05ej07amKUtA50Du5ZMlhDJl8s1Gl2ZZs/w+MrVCJ7Gpmwf5+7Jlx11beVuekT1FnU5rNZMX5Igq1OOdWlY+cLqLlYMyx6xpTOo7KCbJwk828T4m0dp+In6GRvNYGzVZwPHWCahmItoR1rr4xQYAAAAAAEwPNzYAAAAAAGB6uLEBAAAAAADTS9gYmxOBUXEw8X4WVY9Rz5HGO1Yn1kkzwxHP5KfadTx1Icrue9xmEtahwSGyphyJNcjazL/LcXhkbMKkn61m5S9fGy7q1N/uYeXA5k6ijrOWxzhUDtVJvnhAbv/AcB4MU/C5qEKVB9NZec7ei0SdZxsuZuV3f/6kqHPJF1PFMvvqDFZuGOAVdSxlPIZCJcn9IM2il+dPkFU0cSgqR7bTWCiX5WTV8zobZWLPpoM8yElNPCT7WMuTiHrzZBxMuiZn5cFB8vtAXxeZoDN5N985e/d6USc1mQefpL/sEnWqT+fxHd5iGbBy8Ex5jE4/ZScr199bJOpkbuR98gyW57FWk84xqjg7i5XzNjSwciAgzyGzOF68bzhiHd8Y79jJaF3DxDr5ZjjJysPZVqTHw6hzTSvSuOlEjB/Sg19sAAAAAADA9HBjAwAAAAAApocbGwAAAAAAMD3c2AAAAAAAgOlZlFI6UZ/x4/F4yOVy0Si6nCXFimUiw0jaDZcRAd0dWc+ooL5otaPXllFJPI1qpyPbM0qsgjEDqpmW0TvkdrspMzPTkG3GQss40vWpP5E15UjQfv4KHtCd/YMM6N59MQ+et8iciRTS5JH0Fsng8ewNfG6Wuu6ynWBqSCzL3M77qEbXiDr+Zt62K61J1DlQyycYcDplH78a/pJYNnTBXayctkcGi9ub+MfGlb/5RNRZOP9CVg7IHKKUsYu3U3W2ThbRZJ1lQd6nzh/JeXBq+/Dv7bK3ymNd93M3K4dC8rs+tYYH9GtfeyIiZZUfo75Omn4ny+0nVWkSP+p8Ghd9xk/A5gyZRDTjxzqxrLqUv1/zVntEnZ2TeJ2er1aJOlv/wN8PvWbL12PPhbyON4/va8jrpd0z7jfVONIyhtRs7dnhyQPCEc2g83hPQBTptVkkx9rIaxGjtheta9NwxfJaxKiJMvQnMtoR1hiCX2wAAAAAAMD0cGMDAAAAAACmhxsbAAAAAAAwPdzYAAAAAACA6cmIS5OINBjKqCCuSAPGopUxPtz1jAjiCndb0QyYiyQ4MtLgxHgHXkaz3/HOUB1t6TvsZHMeGeZCdh6d/ePkdO0qlKSZT8A54qCoU7sri5ULPpMB3YEUXrZ7ZRB+Sn8Z0J2xjAdG7v9RZqO3NfK2qnvIoTwvlweUV+7KEXXOfOUusWzNr55i5dM+vF3Uue2sT1l5/pazRB1fFx5AnlwiA9yruvEZBew1cj8C8rCRrY4f7wNDZJ1AF57t3uNPFnUa3PxFylgv69T14cHySZ3kRA32DfI8smf5eX+a5L7lr+bHaO8EGZhfPpavl1oiz5maoPyO0ruPt51RLmdvSKrXnEfn5Is6mZ9rFlgbRJ2UKv6+Sj7I2w36dV5Ek5jUdxCbyEjLqKD/cMbeWE+AY5RI+xjLfYv3a2TUepFer4Uj0mvaSK4rtOsEVDMR7QhrXfxiAwAAAAAApocbGwAAAAAAMD3c2AAAAAAAgOklbIzN4q0bWVIsLaOeWTQyxiKStqIZh6MnmjE+4bSjXS8Rk2/GMg4pHPGMVTqcFCuiphOC5ZxasqQ6W8vuzVns78FCP2mlr3aycs0+GeNC6TxpYs6qQ6LK1j9pEjsedIo6loCMzXGX8GXBTJlYM30nf+Y/aYeMDWlO4stso2RsSP5S2aez63/Lyq/++llRZ1HNML795fIYKZ6zkVI3yqRqoUt43I3XKfuT5JQZUns/xQOh9lxSIOr4FG8r/YJKUafwUd7JnZfKDJlJNfxzyLFTxtPU95J9tFbw42+RLzVVDuexJ1lrZaXkWh4rU2mTxzGlq4xfsuTwc7t8nDy2xR/wOodulfEzOS/w/S2bLqpQ8mq+HyFNSErQZ94Ym+Ndi0RToiVtjGa8ZzQTZEa6PW3b0Yynivf1SiTb0tueUXU6Ar/YAAAAAACA6eHGBgAAAAAATA83NgAAAAAAYHq4sQEAAAAAANNL2MkDjpcUS08kgV7RFM2kkZFOjGBUYH6k60UyeUIsg/D1RDOJaCwnTzjRkm+GI7Ami5TzSBB3mibG2pMsx5iGrjyA3Jkjg+5DIR4M3dA/T9Sxb+eB4EoneNzvl4Horv08WNzvksN0xl6eyDGk07anu2YSAp+s5NMJim4q5G3P2TdW1Lmk0zes/Jn/TFHHm8+PY7NLBpAH6zUB7XVyX5OzGsWyH3/JE0k6ZM5KCmmaqj4kg+5rR/MEnWl7ZTt1PTWvR5GczCErt14sq93Pt5d0SB7/1P38mNR3l5MX1JXwOtoEskREjdVpYllSFk9QajskX2tHjY+VQ0q+RvYmPjFCc71D1Mk6wPutPfZBv9wvs4gkQacZkmZGk1H7H83jGK3Px3A+i43cr2hdL4WzrUSFX2wAAAAAAMD0cGMDAAAAAACm164bm5kzZ9KZZ55JGRkZlJ+fT1dccQVt2bKF1fF6vTR16lTKzc2l9PR0mjx5MlVWyvwBAHBywjgCAB2BMQQA2tKuGJvly5fT1KlT6cwzz6RAIED33XcfXXTRRbR582ZKSzv8jO+dd95J//nPf2jRokXkcrlo2rRpdOWVV9KXX37ZoY5G67nBaCaOimbcgxnih6KZuMuoeKJovv7hiGUyq0R57juW44gvP0TW5CMxEo09efxI1w/kdzv7R/A4g+ZamfzSmsrjDnwu2U7qfl4OpMj4hUt+KffnP3vO5ev1kjE+lX143EcoJLcfrONxAXZnUNSpGSvbzs7gMS0b9xeJOmdm7WTlN2fMEnXGz/89K7u2yziLoIPHaxwaEhJ19PbNtZ2Xm2R+Tgom8+2lbEoRdZpO4XEoIZ1koCFtTIlF7od/ZY5YZtG03Sx3jWj/8T+CC1fyFSvO0vk+UqdPNhtfVvxfGZzj6cVjc7L/ITtZdRrvY/Hb8hiVj+frWVw88Weo0Uv0ilgtYrEcQ46XoNPIZIvhtG3UthItDiaW1xThthXOOtF8raPVdrzjcCLZ1/YkC2/Xjc2HH37IyvPnz6f8/Hxau3YtnX/++eR2u+nll1+m1157jUaPHk1ERPPmzaNTTjmFVq5cSWeddVZ7NgcAJyCMIwDQERhDAKAtHYqxcbvdRESUk3P426q1a9dSc3MzjRkzprVO//79qbi4mFasWKHbhs/nI4/Hw/4BwMkD4wgAdATGEABoEfGNTSgUounTp9M555xDAwcOJCKiiooKcjgclJWVxeoWFBRQRUWFbjszZ84kl8vV+q9bt26RdgkATAbjCAB0BMYQADhaxDc2U6dOpU2bNtHChQs71IEZM2aQ2+1u/VdeXt6h9gDAPDCOAEBHYAwBgKNFlKBz2rRp9N5779Fnn31GXbt2bV1eWFhIfr+famtr2TcllZWVVFhYqNuW0+kkp9Op+7eOMip4P5ZJooiMC1aPZYBYNAP2jEpimoivY7wDT48noJqJaEeH29ETi3EklNlMlHIkMaI2gN6fLgPKg5k8ODrpgBwmC0sPsLInp7PctibmPG2/DMx+5/VzxbKUek2ywxqZEDG7Rw0rN/l1Eo16NQkhd8t9VQ4ZdF6/g9fTSyw6f/04Vl49oYeo88DV/2LlR1/5majjy+PHJONHnY3tcMllxPvdlC+PbUoF/96uYK1f1PH9yI9t9SQ5wUKfl3hCTmWTk0BUDZU9zP6Cn4/NGXI99wB+rnX6Wu7/vpG8bJPzPVDyXvn6hzTnbfXpcj2L5rA1FshzPaA5bfadK/toyeQTJVis6phlo5jlWiSazJI0Ucuoz+d4T8gUrcl+wl3PqImUonktEqt2W7TrFxulFE2bNo0WL15Mn3zyCZWUlLC/l5aWUlJSEi1durR12ZYtW2j37t00YsQIY3oMAKaGcQQAOgJjCAC0pV2/2EydOpVee+01eueddygjI6P1WVWXy0UpKSnkcrnohhtuoLvuuotycnIoMzOTbr/9dhoxYgRmIQEAIsI4AgAdgzEEANrSrhub559/noiIRo0axZbPmzePrr32WiIievrpp8lqtdLkyZPJ5/PRuHHj6LnnnjOkswBgfhhHAKAjMIYAQFssSqnoPPwaIY/HQy6Xi0bR5WS3HHlu2KjnCMMRzdiMWMZ9hLP9cMQ6DiiSY2Tkc7XhtB3JepEeR6OSeEZS53BSrB3kdrspMzPzuH1NFC3jSL/f/JlsziMJNnO28JiGil94tauSfUM6KzeWNIs6nVby74RqdRKHBVN5AEOSRz756/DIuAuHmw/JNQNl/IjzII9zsA5yizoji39k5S9fPUPU8cm8kuQv4cckeatMUOrL4X1ybZP7UV/My8/+9CVR5981vE9f/V32MZAq267ry18TS4qMjRnZdxsrf/3OIFGn2cWPdYZOOJk2NiZjt9xW0CH7GHTyZQ1Fso63gLdlaZZ1Qmma7SlZJ2uT/I4yfw1PyLnz0jRRpzmd73/yAZ1zVHNqOWvkJUNyLe+j0jQTaPbSqv88aKpxpK1rEa1ojs/hiOZnSDjbineS7XC2pceoto2K8YlUoiWDjdb+B1QzLaN3whpDOpTHBgAAAAAAIBHgxgYAAAAAAEwPNzYAAAAAAGB6uLEBAAAAAADTiyhBZzxEK9DNyECnSNoyso9GJR/VrhfvJJLhbN/IoLZYBlUalZTMyLZPJP4cRdbkI8HODQU86N5mk4H5Vs1cAUkZMrFjzSl86MzeLLd98ALekHOXDMLXiQMX27d65fdPIRsP4PbVybaX7+7Fyjad3JfZP8j9P5CiSVJ4mkfUUfW8TuZu2Ud3X77BZ/deKOpckv8tK3+eXCrqaI8HEVHB57zthiIZ3L2s8RRWdqTLoPf8NXz/Q3adyRw0CVOVVWcyg+5y/wNpfL3mDDnpgCXA28rcoXMc+/F2kvJlhs76YjkxQFI9X+bPD4g6mZv5cfOcKg92xueaRJ/D5DmTu46/HkHNKRT065x8JrF460bKzDjyukRr4pxYX69E8zM8ks/nWIvk+iiaEymFs/1wGHktEq0EpdE+jvjFBgAAAAAATA83NgAAAAAAYHq4sQEAAAAAANMzTYyNllHPdcY6+aNRSbmi+cxqosUhRfM4RpNRCa+MEsnzsgHVTEQ6WQtNwtKjgSypR2IbrFt43IHaKBN9FazhCSp3lMj4FdcuTfLFrnLbdgePaagvlrEJtiYZr5HzA4/FsP/0oKjj/rKAlZPXO0UdZePLmtNFFaqZ1CD79AOv6G1wyLYbeczE/rNkDEXBSh4bsmdLiagzN6UnK//+ln+JOu9UnyaWbX+VZ0RNqZTxM1Y//3jz6+R0a8jn/faMkPEr6Rn8fPCvzxZ1MnbJ7Xtz+Gubu1G+1odO4d8t+kbJeKZ+j/DzxnpQ1vH1kh/l3lweP5O6Q8Yh1Z/B99dSI1/r0FX8/Ete2UnUIQvff3dfXg55EyoPuKEi/Xw06rMw0rajmWTbqHbMeIyiGe8bzvaiGb9iVPxOJPt1OFn4cVcjIvxiAwAAAAAAJwDc2AAAAAAAgOnhxgYAAAAAAEwPNzYAAAAAAGB6CTt5wPGSYkUasBbLoPN4JwiNNPlmLEUa6GZUgJ5RgZ9GnY96jEp4FevkYomguTqFrClHgv/T9vMEhIFkGVDdUMQDqO25jaJOpibZZt1FblGnpiqDlXVycVJS7zqxTK1MZeXUJJk0sVYzctf1lckfszZpv7eSPUhNl8HydU2833odt2gyi6afJic4SP2ET0Lgy5ITHFh9vNwQknWe6/5vseycrnezckqV7KRngCZB6n75cVc7hE/wcPvpy0WdDyoHsPIOl0tuq6fcvnbfSCd+3penSZrplhNVWA/sZ+XAnr2yoV75YtGh/ppktDLPLKlD/Hhnfyf346DKYeWCH+UkGIcG8PWshXzCBWrUlEGI9wQ4Rn4+mGFyn0gSpEZr220x4+dzrJOV68EvNgAAAAAAYHq4sQEAAAAAANPDjQ0AAAAAAJgebmwAAAAAAMD0EnbygEgkWkB3pG0bJdIgrkj6GO46kbwm0cyQHMtMuuEyKqjRiHbak+03EXV/L0B2+5EA7eZMHlDdlC+DpbN/woOz3Z92FXXqO/NIcIddBu9nr+UTEzTlyW0llWWKZXsu5G2lfiS3H8rk208rkpMQNOXzffXtSxN16vZniWW2gXxCgbwPZUB7gM9vQPU1uaJO/WhePn30FlHn6zX85HrpsctFndld5XH7+w3PsvIvPr5Z1EnJ5vvRfDBD1Lno9E2s/Le3x4k6SfV8+zaXnAXA1iT7qJ0HYf/FchII8vPvFrPXyMksvn+0gJWtVcWijrNGbl9pmko6qNNvL18v5aCcGMC/l59HmT/Kc82fySeKyPycX1oEAnbaKdYyh0l9B5HdIl+XYzHq8yHS9aL1GWLk9sPZVjSvF7Rtx3IiqVhPmhSt675wGXFtHFDNRLQjrO3hFxsAAAAAADA93NgAAAAAAIDp4cYGAAAAAABML2FjbCJ5rjUc0Xz2NZLnGI1MrBjOvkUShxTN50HDWS+aibOi+cxqpPsRy2S0Rj7Xmoh2T0gi61FJOC2afIiWIpl8c/eaLqzs0Ems6PTwhTUNKbKSJn7H20ObsZHIX6szxmm2p/S+ftLUqa9IF1UcBzWxEZUyDiNHhr1Q2RW8Tw1FOvEjPIcpNWfJGCNrE+/4qo29RR27JsZDLw7J21m2/cv3b2Xlry57UtRZ3tSNle+rv1LU+e/aQaycNahG1PE184/JjI9krE5qtexj5oZKVvZ3yRZ1fryBl2tOC4g6Vit/sUMpMg6GetaLRd5KHlPly9GJw8ng2zswWCZITd/Nt19xttz/hmH8fVTXg78fQt4g0cdiNVPQJguPp3gnuoxmLG00xbs/sbzuNOq6K1LRul5sT7xvYrxbAQAAAAAAOgA3NgAAAAAAYHq4sQEAAAAAANPDjQ0AAAAAAJhewk4ecDyxDN7XE82gb6MSZ0W6b0asE+56Ru1rNCcYCGd7Rr4eRiUli2YSUbOw+i1ktR4Jms5bywOhD1yhMzNAdx4Irb6TiS1DPC6fgttk8L5K423bKx2iTiBbBotrOTw2sSyUxAPB7W69OrzsPt0v6qTvk+vZPfz7ruYzZGB6nosv871eIOpk/ehl5f13yO03pfFj4gvKZKCULo+RpYbv3MQNN4g6S0+fx8qe4R+IOs9vPZ+VQ8tyRB3nqEOsfOh0OVFAU7n8KA06Clm5MV9+j5iUwo+jqpDnmnMb39f63vJ4NLrl5BVWH9+e86DcfupGvqxe5oKlYAo/1yxy98m5kWds7bK8gZUDAS+VydVMyajP+XCY9TMsnPWi1U68JwqINMA/lgkyo5m8PlJI0AkAAAAAAHAU3NgAAAAAAIDp4cYGAAAAAABMz7QxNnqi9fyfkbER8Y57MCr5ZaTPbGrXi3VsTDii9cywkc+1RuuZXW077UmKlYhsDRayBY7ECNScwuMFmht0EmRqvu4p/sIrquy6mCcydHiOn8TSlyODE3LWyiHYMamKl9/LFXXsTTw2Jn2fjLuwefn2dt4kEzvafPK7rfRyvi+1Lhn3UvUjjwXpvk0eI28nfgCS35ftODWbd/eTMU+p38ukkSnnHWDlg2Uy+eVZ3/6Wlf981QJRp7aCJ5vMaZDbdzfwfmcXuUWdOo+MzfH04DvX2E2+/o4t/DiG5K5SYxF/3fTiqYIFsu20Et7PelumqKM9j4J9ZMLaQB2Pn/GeIetkfM5jfPzZ/LUPNOskFTWJREoWHus4zUjbjVYcUryPUTTFO2470naimXQ+UvjFBgAAAAAATA83NgAAAAAAYHq4sQEAAAAAANNr143N888/T4MHD6bMzEzKzMykESNG0AcfHMkN4PV6aerUqZSbm0vp6ek0efJkqqysNLzTAGBeGEcAoCMwhgBAWyxKKZ0Mdfreffddstls1KdPH1JK0T/+8Q+aNWsWrV+/ngYMGEC33nor/ec//6H58+eTy+WiadOmkdVqpS+//DLsDnk8HnK5XDSKLmcBe/FMvhlu4FksA6RimSjLyASZsUxuFs3XI5JzJNxtRStBZzjr6U8esIPcbjdlZsrg40jEchw5e8wfyG4/EvxdcRYPau60UQZdN1xby8q+FTJ4XzsxgG2IDCjP/BcPTK/tI79HctaKRVTflQ/J2T/IOgcH8zqhZBmcnaRJ7BlI0wngDslJD+z5Tayc+65M/lh9uma9Ijl5QMYKvp67vzzW+St4O3XF8hgpGStPP/vpMlZe+NYoUcdX4uPt+GXbH497mrf78O9EnYNn8okZrhy6VtRZ/MUwsUxl8PUsjXJHun7MX8e9P2kWdRxO3o76XiaDtfrl6+jtzI93wReyTkNnfkzsjfJyoOYMvv38L+SEF9rzUZsMNOjz0rYn7zNsHInntUg4ojkxgFHbj2XwfLwTquuJ1jEyQ7LwcNrRayue10sB1UzL6J2wxpB2zYp26aWXsvKjjz5Kzz//PK1cuZK6du1KL7/8Mr322ms0evRoIiKaN28enXLKKbRy5Uo666yzdNv0+Xzk8x35APJ4PO3pEgCYDMYRAOgIjCEA0JaIY2yCwSAtXLiQGhoaaMSIEbR27Vpqbm6mMWPGtNbp378/FRcX04oVK9psZ+bMmeRyuVr/devWLdIuAYDJYBwBgI7AGAIAR2v3jc3GjRspPT2dnE4n3XLLLbR48WI69dRTqaKighwOB2VlZbH6BQUFVFFR0WZ7M2bMILfb3fqvvLy83TsBAOaCcQQAOgJjCADoaXeCzn79+tGGDRvI7XbTG2+8QVOmTKHly5dH3AGn00lOp8xKtnjrRsrMOHLfZVTcRziMeo4wnDrRjM0IZ71I64STIDJSRsUKGZXMKppJVI2MX4rW9qMhVuNI5a98ZEs9EltgW8ODY2r6yLgH+0c8psZXLOMOsjfz8oFuMg6l4UJNTImSMSb2ofVimeNrnmwyOPmAqBOq4s8YZ+fViTr13/GkkbYmnfiVLjI2xrmeJ42svkQmZEz+hidtTB8gt+/O5cck5xu5/Zr+vOzPlzEm5wzaJpb9+7mRrOwd7hd1LPX84y1jh3ytf7aax9Q8dd/zos71b97Kyuv+X6mo4+qt9x2hJkmlzE9KKbfvZuWs1+WvBHlr+CNRNafKduq6y2WWZh5T4+4l++jP5nFXnb+Q57rawONLLEEZqxXM4Oe2t4DHN4Ua5XnWUYlyLaInWvG+4YplLGuk249mLG84onVNGc1r03C2l4hJ32OdLLzdNzYOh4N69+5NRESlpaW0evVqmjNnDv3sZz8jv99PtbW17JuSyspKKiwsbO9mAOAEhnEEADoCYwgA6OlwHptQKEQ+n49KS0spKSmJli5d2vq3LVu20O7du2nEiBEd3QwAnMAwjgBAR2AMAQCidv5iM2PGDBo/fjwVFxdTXV0dvfbaa7Rs2TJasmQJuVwuuuGGG+iuu+6inJwcyszMpNtvv51GjBjR5iwkAHDywTgCAB2BMQQA2tKuG5uqqir61a9+Rfv37yeXy0WDBw+mJUuW0NixY4mI6Omnnyar1UqTJ08mn89H48aNo+eeey4qHQcAc8I4AgAdgTEEANrSrgSdsdCRBJ3hMENQXbzFMkAu0QL/wmVUcq9oHqNItqXVnqRYiaRlHDll6p/J5jwSta0N4LbJmHPy5fAhMdBdBj4XvMuDjN1XyeD5pOUu3qe+cvIAR74MzA/s4gkYLTp5NYs+523pJbG0aDZXfbr8HiuQJof/YDJfllwpn1j2DeL9DlXLyPj+c6tZuXJUvqiTt5YHxu9/QO7seV12iGVLtp3CysEaGfRNGXwigiRNoksiop/3X8PK//jiPFHno0ueZOW36oaIOv+3XSborN/FX//OOrkh/Wk8wN9/ea2oY38/i5Wdbvma6SU2bRjIz9uULfI1CqRoEr06RBUiTV7PlAqZ6LOxC3/dlKY7Ia+Xdt97v6nGESMTdOqJVoB9uKKZLDycbUXrMzsRr6mMcqIkeo2knfYkC+9wjA0AAAAAAEC84cYGAAAAAABMDzc2AAAAAABgeu3OYxMvsYxFiGTb0dy+nljGdBiVcEmv7UhF6xnmcLdl1PPRiZ6gsz1JsRJR+t4g2ZOOBJscHMiDUZw1OvEKfXhwirVKxm8cHMzjDJr3p4s6eT/yGA9PqYyxCf0o1wtm83p5K2UAjS+LfyeVXCPbtnl53IMvV36P5aiVy5pdvC1nrYypUJt5gs7USnkc948t0KwkqlBt/wzex2/ltj79WibEzD6Hx+/Qf2WC1EAyf91qSuVx3OfjcTAlb8k4nLH0W1Z+bbwMQt9eJOOHAoV8e6u6ySyanZ/isRs7f8gSdWhUE2+3VicQJkUmNs3J4clf6zLleew8yI93Q1cZ46RSNck3A/KywVrE+2jfxJO8Bn34DlUr3tcLkQj3MzTWMa+RbCuSxJaJ+Hkdy2tjo+LAIjmOAdVMRDLeUg9GGwAAAAAAMD3c2AAAAAAAgOnhxgYAAAAAAEwPNzYAAAAAAGB6CTt5wOKtGykz48h9l1GB4OGINCmWUcHix2u3rXailczKqCSaesuMbDuSdYwKBoxm29E8RmZIGNsRIZuFQrYjAdJ+Fw+Odm2X6yRl8cSGgVQ5TNq28mSHydUyMN3TjX9vZLHKwHTqIRN0WoN8veqz5Gp9/86DtZVNfkelbDwwPJQuA/O9Drle1ka+vzWnycB0UprJE9Ll/uet58c66JTbD9n5soCcA4D8uXJihKaDfNKBfutqRJ3dE3M0G5Ntf7mnJytbSmWAva2Bz3qw1ttD1Lm34COx7P0GnkT0u0OFok5jZz55RNGXcl/d+/hEDb4cUYVIyXP0UFBzvLNk2z3/1cDKW26XL4BrPZ+soL5YzgIROsDfD1anJvFnYuUB75BIgs71xDJ4PprXS9FMLBrLJKInimgmIo+UERMMtGciI/xiAwAAAAAApocbGwAAAAAAMD3c2AAAAAAAgOnhxgYAAAAAAEwvYScP0IpmkHskYh1QHoloHo9I+2jU5AnhtBvrbMvR2n44bYczUUUkfW5Ptt9ElFrlJ7v9yPc3oSxNQL1NZnG3/cADuqlfg6jTVOJn5ZSvk0Qd0sRLq5AMnm9ulOvZD2iWOWTgdc0pvI++LNl2Uj1fL227zuQBnWREvXsADzK3NsiJAexN2qB/2ceK8zXb3yW/R2ss5NvP2iL7aAnK9WpO5a+bxecRdbos46/boQGpok7NQD4JQacKuR85m/nx+PycPqJOrq1eLPtF5lZep5es88qmMbw/p+eKOnXD+EQRDqechMJ7KFksI5tmX2xy8gBPP77/lga5/85avqy+WG5KJfE6/mL+/gg18fKJLlrjc7yFe00TrUz3kV53hdN2OIy6pov1ZAYn0+QJRPjFBgAAAAAATgC4sQEAAAAAANPDjQ0AAAAAAJieaWJsImHU85hGJsiMVhJPvfWMfB71eO1EKlpJVfWE+5pFEs9lZDyVUclHI+mPVnuSYiWiAwOTyeY8En+QvJP/vaFIruPVxAfY9sqkhdYCH6/jk7EyQU2ux6TdMvljIEPGNASyeQxFym7ZtqeXJqZBJ4mlsvI6dpeMc1BVMjYjraiOlRv2ZYg6toP8OzF7g078Th6Pn2kskvE8oVTe7+RD8ru2pAa53sGhfHs1pZ1EHXsT3//GAtlHq+aQWAPy9dAmFl21sbeosy6rq1j2Ra8trPyTnNWizr4xeayc+51P1FGHeDzRkNJdos6aZhn4EvTw9TK/lx/3vky+vznfyGOkTZqavlvWCSbztlMreFxW0B+icrGWOUVrrI2mSD+foimS4xjvPp/sjIotjuQapz3xvvjFBgAAAAAATA83NgAAAAAAYHq4sQEAAAAAANPDjQ0AAAAAAJieaScPCCcYLpxg8UjrhCOcts0QiBjp9qP5GkWrP2bZvlHnzfHaMXuCztB5brKkelvLyUuz2N9rB8hkh6SJVe+0QVbxdOcR1bX9ZdC5TZOQMWNJuqjjy5HfLTV04WWlM0rbBmgSUjbIiQnIxwO4Aw1yEgJbswwET389k5XrR8mJCZLqedvNctcoycP3LZQkj5Gy8TqVw2V/QkkyQWhamWa9i72ijgpq2vLJ7ed/xdv2/qxW1PGvzGHlU+ZUizpNxS6xbPshPuvG3YPPEHVuv/stVn7u6UmiTtFn/ITc/k0/USclRx43pTlseueR9rzVS5Dq7sPrONyyjl2TwzakOdVC8tCbxuKtGykz48j5FsnnQ6zG6/a0FU3xTEgZ7raM6mMkn9dGJmMNZyKjaCZ/jeWkVeHCLzYAAAAAAGB6uLEBAAAAAADTw40NAAAAAACYnkUplVBPv3o8HnK5XFSztSd7rjUc0YqfMTJBZzjtxJKRiSXDaSfWzxob0Z9I247WtsLdnhEOJ+jcQW63mzIzM4+/QoJoGUf63vlnlqCzWZOQkHRGv8wfNVV0hqGDpZq4E506WZt4UENdd7mxHv+RCRkPDuBJM3O+l3Uqh/GYGm2MA5FOnIND1kk+KPvk7sXLBatlgsx9I3k551t5ADw9edkiQ3UofQ8vN3aW8RsWnTCopiK+0NYot29v4MuaM3UShKbxTnVZItvZezFfr7DrIVGn6vs8sSz5AG8rba881pm7+Gt71fMfijrvVw1i5c1f9RR19ART+PYsOvFU1mZebu4sk7haa/iJlNy9TtQJbeQxRt5C/vqEmry0Z/qDphpHWsaQUXQ52S1HjkE8Y2qi+RlmJKPiLqL5uRqtz1Ajk6Ga8ZoyUsc719tzLYJfbAAAAAAAwPRwYwMAAAAAAKaHGxsAAAAAADA93NgAAAAAAIDpJWyCzkl9B7U7YM+oYDSjRHNb0Qzej6TtaAbwGfU6xjtBp55oBhUm2vshHvI2+MhuPxI0XXM7j7KvrcoQ6xScyyPadywtEXVS8htZOekLnWBGTax4xk6dJIpWnYSIp/KA9oKVMvlkUj2fPMDaLAPTtYk+tYHiRETF834Uyxpu7s3KdV1lgkyVxoPMM3fKCP/e15Wx8saKzqJOXW/+EdTn/7lFnUAn+RptvZFPsBDMktsPOXm/lU6CUHsN337mxipRxxLqxMp7R8mJAlS2PLjBej5bQ31X+Vo3p/P9eObvV4g6r099gpUXuIaLOjsbc8WyVTt7sLLFKidPKPgXTzSbO32PqFP1PD//nYPqRZ3dmfw1ytrIj2vQbyfZ8okrks9Ho+pEuv1w2tET64SQWrFO/hiJSK8pjDqPYnktGuk11fH2tT3JwvGLDQAAAAAAmB5ubAAAAAAAwPQ6dGPz2GOPkcVioenTp7cu83q9NHXqVMrNzaX09HSaPHkyVVZWdrSfAHACwhgCAB2FcQQAWkQcY7N69Wr629/+RoMHD2bL77zzTvrPf/5DixYtIpfLRdOmTaMrr7ySvvzyy3a1v3jrxmMm6Ix3gkijxPp50ESLqQjneVCjXkcj9z3REmcl2usajmiPIUREVWc4yeY8Eo/SuJ/HXeglLfxuBw9OsXSSsQmqlsdGJMlmKHMXj/vYPVHW8eY6xTLl5PErDd3TRR1fFi9bAzodsPCYEn8nmSGzuX8XsczbWZP80ic/JpKqeNLGxgIZv7JmZ3dWDvpkrE5SKt9XlSKPhyUoj7+jgvdJ9ZEZSpstmoykOscokKeJjbHIOo15/HNIpekEKwXlej7N8ba55Hqpy/h5pBdztdhzOiv/xLVG1HnfOlgs+yaliJUbd8k4sKZcvr1vvu8u6uSm8Tr7fywQdVK1STt38ISdpHN6GiUW40hHGTU+n0gJOqH9zPL6x1tEv9jU19fTNddcQ//7v/9L2dnZrcvdbje9/PLL9NRTT9Ho0aOptLSU5s2bR1999RWtXLnSsE4DgLlhDAGAjsI4AgBaEd3YTJ06lSZOnEhjxoxhy9euXUvNzc1sef/+/am4uJhWrFih25bP5yOPx8P+AcCJzcgxhAjjCMDJCNciAKDV7kfRFi5cSOvWraPVq1eLv1VUVJDD4aCsrCy2vKCggCoqKnTbmzlzJv3xj39sbzcAwKSMHkOIMI4AnGxwLQIAetr1i015eTndcccdtGDBAkpOTj7+CmGYMWMGud3u1n/l5eWGtAsAiScaYwgRxhGAkwmuRQCgLe36xWbt2rVUVVVFZ5xxRuuyYDBIn332GT377LO0ZMkS8vv9VFtby74pqayspMLCQt02nU4nOZ0yYFSboFMr0sRRRgkn6D3SREnR3LdIkinpiVaAf7jrRdKOkQlLo5n8MpJkXkZNwhDtSQiiMYYQtT2OJNcosjmOBLY39uKB6K7OMtmgr5kPi6FyGXTtd/Fg+aR6GTxf140HyzurZb99vWXyzYzMJla2+eTkAdaAZhIEGV9PGTs1/emhE7z/zRaxzHIdT9DZ0E82bnPywPjAj/LiUjtZQEqZQ9Tx9uZtN3eSfazpLdt2eHg0uiVZBuYHKlNZOb/PAVHHvTKflavPlsk3/S5N5LvORAG6XxFqloV01qsr5uWczfJYf3WoJyufmrJX1Plt7iaxTFvvrrqrRJ2gQ3NsrfI8zvmBn4+HTpfvs2Y/f89Yed5PChqcWCKW1yKJLt7JF8NhVB/j/TkbTjuxhokapHbd2Fx44YW0ceNGtuy6666j/v370z333EPdunWjpKQkWrp0KU2ePJmIiLZs2UK7d++mESNGGNdrADAljCEA0FEYRwCgLe26scnIyKCBAweyZWlpaZSbm9u6/IYbbqC77rqLcnJyKDMzk26//XYaMWIEnXXWWcb1GgBMCWMIAHQUxhEAaEvEeWza8vTTT5PVaqXJkyeTz+ejcePG0XPPPWf0ZgDgBIUxBAA6CuMIwMmpwzc2y5YtY+Xk5GSaO3cuzZ07t6NNA8BJAGMIAHQUxhEAIIrCLzZGWbx1I2VmtC/iMNJg9Wis05ZIAruMDAaLJOg93tuPpkgD8406JtE8/ggiJGroSmQ9Kj7amsyD3kOf5oh1vKf5WNmlE/Qf6MPbaegiA8Nd23kgeO0pMjDbckAG1Nc183HPUSiH6eYM3laazgROnb5tZOWaYbKdmgmniGVp3/Ht1/cKiDr2PXxil0OD5L6RJg6++MM6UeXQAD4xwr6z5XFszpRth5J448EqOcFC1ha+H54uchICXx5/Hb2FclvJFZrA+FR5PEKN8tham/j2VUBOhmPz8v1tLJD7X7GtKyvf+cPPRZ3XBv4oll2et4GV7ftkYLzNz/fXWi8nbzg4gO+bSpETNRTm8Jwv5b34tkJN8piZxfGuRWI9uYxRovk5H0lgfjSD96M5wUAiTmR1ItAeV09diLL7hreuwXOVAAAAAAAAxB5ubAAAAAAAwPRwYwMAAAAAAKZnUUrpPBwdPx6Ph1wuF42iy1mCTqOeB413jMnxtqW3vXATS0bS71g/5xut5JPRfM45ERN0xuq52oBqpmX0DrndbsrMlIkqE1XLODLgxj+T7agkhO7+PKYivdijXZXS/+li5cpLfKJOr+d4jMfuO2VixVCIx0tYdZIf+g6kiGUWxddTOjEdRR/weA1fpozNSGrk28v5dKeoc3B0D7l9za40Fsrvv3I2+zUrye3X9OF9bOgm9z+Qx9ux6cQcJdXp7Jsmr2pjkTz+zkOafut80qVW8IVuvWe4NZt31Mj++LN14qc0L5vefmjjhxxunbY1yWCdh2SdoE5eyfQ9fL2bZiwWdRZXns7KB5tSRZ0DG3kSU+1rRkRk0ZzbVjsvhxq9tOvXD5tqHAn3WkRPJGN4vD+LzSDWcThGJQsPp914XwuFI55xYYdjbHaENYbgFxsAAAAAADA93NgAAAAAAIDp4cYGAAAAAABMDzc2AAAAAABgeqZN0BnvpEhGBv0fT7iBZrFM/hnNALlI1jEyAVg4xySWAf5GBhoeT0eSYiWipnxFtuQjgcz2Bj6m+P3HHwJte2ViR2+BJtFnyCvqBAM82aFtm5woIClFBp07D/Lg8KZ8OQ7uG823bwnIgHKlSUaatq9I1PH0kG03FfMEjF0+kn2s7cOD/Bu6yDpJmnycgYygqOMs5+34imTyR4uSiS2TD/D9TereIOo0pvLjnbteJp9sLOTthBxyEgJVwCePSN4uz4fidw/Ktkv4JBSOWrlvO67gfcwcXSHqVK8r4O145LFuypOvv72J78ujH10u6jw87g1W/uNbV4k6/UbsZOU9b5WIOvWaiSFCmgkGQgHzfocaSbLwaIn0WiDSxJLhbF+PURMZGfUZGmnbsZxIKpr7mmiinbA2Md6tAAAAAAAAHYAbGwAAAAAAMD3c2AAAAAAAgOklbIyNEWIZBxMuI2NBImknWgmnjFzPqNfIqH7H+zlfo7ZnxoRsHeXwWMjmOxJ/0FjayP4e9MkhsKkT/76nOUsmyKwezNdL+yJd1KkdwmMqvD1kos+MjTKzop+HZlDIKeM++v69iZVtuypFnea+XVjZUyJjQ/LX6cS0rOHxErvHyfgNS5DX6fl2k6gj4ke2ymPd0FWzb83yuzabDF8iiyavtP3rDFHHpVnv0GAZ41P4Bd+3wH6dRKMBftxq+8n+1IxME8ucW3lsUOYOGeOTuYOXDzYViDrNmrgj3yGZxFQvQae7F9/ehBFrRZ1HFvyMlV+9bo6oM2X+Hax84S9lO/9degYrh+o0r3WTeS81JvUd1O4EnZEIJ+4g0mTd4W7PKPFMxB0po+KAIn0dI+2TUYleI70+ScRktPjFBgAAAAAATA83NgAAAAAAYHq4sQEAAAAAANPDjQ0AAAAAAJieRSkls33FkcfjIZfLRTVbe7Y7KVa8JwYIh1GJq6LJqD4ZFQwY64DBWG5fTywneDjee+Zwgs4d5Ha7KTMzM6JtxEPLONJ/2p/J5jwS/O3L1QSdN8hg8aYiHmSes0GOQ0qzqP5CmSDS38iDx/v+TQbq775ITjoQcvI+apNREhFlj9/HynsPZIk6VhsPzHe9LwPcGy/3yGUeHizf41VRhQ4M1kSrn18j6mS+ys+XyqHyOHZZzidmqP51o6jTvEXnvNM0lVIpj5E3hx9HR52sQyNqWdG/2SWqhEr4xAihCjkJQ6835OQJ1afx451yUE4CceB03qeew3bLOv8sZuWczXJb/kyZxDTk5G0Hk+T+D/zdt6y86Ykhos7Tf3mGle+473ZRp6GIvyDaSSFCXi/tvvd+U40jLWPIKLr8mJMHRPoZcrx19BiZINOoBJ1G9duoyZ6M+izUayvekxfoifdEEbF6P7TnWgS/2AAAAAAAgOnhxgYAAAAAAEwPNzYAAAAAAGB6ps2aFc3nEaMp3nFAkTyPalQ8TbjbN2r/I20nms/sasUyViic7WvbCahmItJkETQRfyaR7aiQiJ9O/IL9/Y13zpMraUMRdKIQveN4bEry5zI2o7kXj9U5OEgmViz+b71YtvVaHsNR9LnsQG1zESv3+tIt6vjyeYLMA0NkjEXXP8tlVk8tK5ddLZNGhhy8T90fl/u27Re8TvH7MkFmXTf+EWRdJY9jp10yNsWfoUmsmSKqUNdP/ay88zrZTt4b/Fnt7HrZxwNNqazsLZR1dkyTxzFpKy8fnSi2RfouXt6a2lXUcYzl50hdsYzL0vuKMpDKj3/hKVWizjd/5TE1Vz34X1HnmkW/YeWvH39S1Bn6xl2sHErnxyhkk8fMLBZv3XjMeN9oJoJOtFhOI9uJVmyGkddP0bpe0WsnmgkyY3kexTIJfVvwiw0AAAAAAJgebmwAAAAAAMD0cGMDAAAAAACmhxsbAAAAAAAwPdNOHhBN8Q6GiyRgriPrHY9RQfhExvXRqIC1aG4/3omzjJoEwcwcg2rJlnokmeQ7ZYPY33O/kwHlTbn8+56DZ8vEmo7vedB54xCfqJOxkSexrO0rJwHw9JRJM52aZJP7zpPrBUt4Iktvrgy6z9rG980m8zrSzssy5PZr+L6lVsjtu3bwwPzt18iklRaee5OSGuRxtHttrFzTRb4eloD8/q3zVzygvvxCGVBf049PaJC3RO5HTX9+rK2ByD4Sg245eUKoEw+YT66yiTqWEO9TUp1OMlg33ze9SQgCaXLfbE28XsXmfNn2WXy9F98aJ+qMn7CGlYcumyrqLLh8Lisvdpeysq++mXiazxOHUZPERDP5ZDQ/i6IZ9B7L/oQjmtc0emJ5TRfNcyvW8IsNAAAAAACYHm5sAAAAAADA9HBjAwAAAAAApmeaGJtIEiXFOsbleO2E21akSaFi+cxqOP0xSjSf4Yx1gtRwtq9l1POwkTwL7qkLUXbfdm8qYdRXpJM15Uj8x1Vnfc3+/pn9LLFOygEe51ETkjENShMuYWmQQ2ljkTbGRbbjz5OJC1N38ba8eTJ+QtXw+B17o6hCVk2MS9YOGeNyyJEkt1/J++3pLr//8nbi208u8Ig6/l08NsTukXFINr8mNsUu97WhWMbd2BcdYmVrUMbYODy8rZBdHv/kQ3yZp29A1LEE5HqCVec10qyWXCP3w6p5+T3ne0Ud5yaeINRZI7flFVllifwuTb18neO/j8dG+brKc+T9rQNYuUt+rajzcT2vc032Slaut4dO2BibaDIqObQZEn1GUyzjbhIx5iTSxKaJuC/hwC82AAAAAABgerixAQAAAAAA08ONDQAAAAAAmF7Cxdgodfi5YE89fx45oPizv546+byyto4e7Xp664RTJ5y29YTb1vHajWRfwxXOsY6kP3ptJdp+hLtepG1HIpxzNNJ2jtduy/uw5X1pFi39DXl5zIKvnh+DYLOMaQg1a2IzmuSxDnn50Bmy67wemnwjFq+Mgwg1yRiboE/Ttle2rTT5T4I+mSMl0MzXszTrbUtnmWa9oE/n+y/NrqhGneOoOUaBoIzxCDTzGJ9QkzzP9GJcAiHeVtAntx/08/0I6cRKBTWvUagpjBgbnZAbFdB5/TVBNsFmeRxDmsMf0jmO2uMf9OvkNdLJbRPy8np6rxFpFoWa5BhhCfFjEkiWr6NX876qt/Dj0WDCcaStaxGtaH6GRSqan+HRYlQfI/2cN0qsrwXC2X6k+xrr8/ZY2nMtYlEJNtLs2bOHunXrFu9uAMBRysvLqWvXrvHuRtgwjgAkHjONIxhDABJPOGNIwt3YhEIh2rdvH2VkZFBdXR1169aNysvLKTMz8/grJwCPx2O6PhOZs99m7DORufqtlKK6ujoqKioiq9U8T662jCNKKSouLjbFsT6amc6RFmbsMxH6HQtmHEdwLRIfZuy3GftMZK5+t2cMSbhH0axWa+vdmMVy+Of1zMzMhD/oWmbsM5E5+23GPhOZp98ulyveXWi3lnHE4zk8DbFZjrWWGfttxj4Tod/RZrZxBNci8WXGfpuxz0Tm6Xe4Y4g5vjoBAAAAAAA4BtzYAAAAAACA6SX0jY3T6aSHHnqInE7n8SsnCDP2mcic/TZjn4nM228zMuuxNmO/zdhnIvQbjs+Mx9qMfSYyZ7/N2Gci8/b7eBJu8gAAAAAAAID2SuhfbAAAAAAAAMKBGxsAAAAAADA93NgAAAAAAIDp4cYGAAAAAABMDzc2AAAAAABgegl7YzN37lzq0aMHJScn0/Dhw+nrr7+Od5eYzz77jC699FIqKioii8VCb7/9Nvu7UooefPBB6ty5M6WkpNCYMWNo27Zt8ens/2/mzJl05plnUkZGBuXn59MVV1xBW7ZsYXW8Xi9NnTqVcnNzKT09nSZPnkyVlZVx6vFhzz//PA0ePLg1O+6IESPogw8+aP17IvZZ67HHHiOLxULTp09vXWaGfptdIo8jZhxDiMw5jmAMgUgl8hhCZM5xxIxjCBHGEbNIyBubf/3rX3TXXXfRQw89ROvWraMhQ4bQuHHjqKqqKt5da9XQ0EBDhgyhuXPn6v798ccfp7/+9a/0wgsv0KpVqygtLY3GjRtHXq83xj09Yvny5TR16lRauXIlffTRR9Tc3EwXXXQRNTQ0tNa588476d1336VFixbR8uXLad++fXTllVfGrc9ERF27dqXHHnuM1q5dS2vWrKHRo0fT5ZdfTt99913C9vloq1evpr/97W80ePBgtjzR+212iT6OmHEMITLnOIIxBCKR6GMIkTnHETOOIUQYR0xDJaBhw4apqVOntpaDwaAqKipSM2fOjGOv2kZEavHixa3lUCikCgsL1axZs1qX1dbWKqfTqf75z3/GoYf6qqqqFBGp5cuXK6UO9zEpKUktWrSotc7333+viEitWLEiXt3UlZ2drV566aWE73NdXZ3q06eP+uijj9TIkSPVHXfcoZQy17E2KzONI2YdQ5Qy7ziCMQSOx0xjiFLmHUfMOoYohXEkESXcLzZ+v5/Wrl1LY8aMaV1mtVppzJgxtGLFijj2LHxlZWVUUVHB9sHlctHw4cMTah/cbjcREeXk5BAR0dq1a6m5uZn1u3///lRcXJww/Q4Gg7Rw4UJqaGigESNGJHyfp06dShMnTmT9IzLHsTYzs48jZhlDiMw3jmAMgXCYfQwhMs84YrYxhAjjSCKzx7sDWgcOHKBgMEgFBQVseUFBAf3www9x6lX7VFRUEBHp7kPL3+ItFArR9OnT6ZxzzqGBAwcS0eF+OxwOysrKYnUTod8bN26kESNGkNfrpfT0dFq8eDGdeuqptGHDhoTt88KFC2ndunW0evVq8bdEPtYnArOPI2YYQ4jMNY5gDIH2MPsYQmSOccRMYwgRxhEzSLgbG4iNqVOn0qZNm+iLL76Id1fC0q9fP9qwYQO53W564403aMqUKbR8+fJ4d6tN5eXldMcdd9BHH31EycnJ8e4OQFSYaRzBGAKQeMw0hhBhHDGDhHsUrVOnTmSz2cSMDJWVlVRYWBinXrVPSz8TdR+mTZtG7733Hn366afUtWvX1uWFhYXk9/uptraW1U+EfjscDurduzeVlpbSzJkzaciQITRnzpyE7fPatWupqqqKzjjjDLLb7WS322n58uX017/+lex2OxUUFCRkv08UZh9HEn0MITLfOIIxBNrD7GMIUeKPI2YbQ4gwjphBwt3YOBwOKi0tpaVLl7YuC4VCtHTpUhoxYkQcexa+kpISKiwsZPvg8Xho1apVcd0HpRRNmzaNFi9eTJ988gmVlJSwv5eWllJSUhLr95YtW2j37t0Jd+xDoRD5fL6E7fOFF15IGzdupA0bNrT+Gzp0KF1zzTWt/0/Efp8ozD6OJOoYQnTijCMYQ+BYzD6GECXuOHKijCFEGEcSUpwnL9C1cOFC5XQ61fz589XmzZvVTTfdpLKyslRFRUW8u9aqrq5OrV+/Xq1fv14RkXrqqafU+vXr1a5du5RSSj322GMqKytLvfPOO+rbb79Vl19+uSopKVFNTU1x6/Ott96qXC6XWrZsmdq/f3/rv8bGxtY6t9xyiyouLlaffPKJWrNmjRoxYoQaMWJE3PqslFL33nuvWr58uSorK1Pffvutuvfee5XFYlH//e9/E7bPeo6eiUQp8/TbrBJ9HDHjGKKUOccRjCEQiUQfQ5Qy5zhixjFEKYwjZpGQNzZKKfXMM8+o4uJi5XA41LBhw9TKlSvj3SXm008/VUQk/k2ZMkUpdXiaxQceeEAVFBQop9OpLrzwQrVly5a49lmvv0Sk5s2b11qnqalJ3XbbbSo7O1ulpqaqSZMmqf3798ev00qp66+/XnXv3l05HA6Vl5enLrzwwtaBRKnE7LMe7WBiln6bWSKPI2YcQ5Qy5ziCMQQilchjiFLmHEfMOIYohXHELCxKKRXd34QAAAAAAACiK+FibAAAAAAAANoLNzYAAAAAAGB6uLEBAAAAAADTw40NAAAAAACYHm5sAAAAAADA9HBjAwAAAAAApocbGwAAAAAAMD3c2AAAAAAAgOnhxgYAAAAAAEwPNzYAAAAAAGB6uLEBAAAAAADT+/8Aetuocj8aBtUAAAAASUVORK5CYII=", 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", 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", 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8OG+Px6MePXpo8+bNAdd37ty53vFRWlqaPvvsM8sWth40Nq3Mj98VsPnxk9Dn8+mcc87RLbfc0mB8r169gi6rd+/ekqR169bpwgsv9F+flJSk/Px8SUd+h+M073//+9+64IILdMYZZ+ixxx5TTk6OYmNjNW/ePD3zzDONb5hFsN8AGWOatVygJdWd4OM3v/mNxo0b12BMv379JB35If/48eM1atQo/f73v1dmZqaio6M1ffp0/8HGDzVWW2zPJ5/PJ4/HozfeeKPB2FANrPxhDTrppJP812dkZPhr0FNPPdXg3za0fU3dR0419TeIQHMMGDDAf1a0YH74CUIdn8+nzMxMPf300w3+TbA3QMMpXDn+sLacfvrp/utzc3P9v/2r+6bLjzVUW/70pz/pjjvu0OWXX6777rtP6enpioqK0pQpU6wnamoMxzY0Nm1GWlqaSktLA66rqqrSjh07Aq7r3r27Dh486D8IaIohQ4YoNTVVzz33nKZNm9bs0xm+9NJLio+P15IlS+T1ev3Xz5s3r8H4jRs31rtuw4YNSkxMjIgCDBxtGRkZSk5OVm1trfU5/OKLL6pbt256+eWXA97hu+uuu0KeV/fu3WWMUV5eXqNvjtR9RWzjxo3+MzdJUnV1tYqKigKalYYUFhYqOjpaTz/9dMDZiX6qpu6jYDWo7mQogJt0795dS5cu1emnn97oGxs/fN7+8JPVXbt2WT+F7N69u6QjDUNjNSvY19LCkaMknX/++frzn/+sp59+OqCx+alefPFFnXnmmfXmaZWWlqpjx4714n9cW4wx2rRpk/+NKnyP39i0Ed27d6/3+5i5c+fW+8Tm4osv9p/W8MdKS0tVU1MTdB2JiYm65ZZbtG7dOt12220NvkPQlHcNoqOj5fF4AnLcvHmzFi9e3GD8ypUrA76bunXrVr3yyisaPnw475CiTYiOjtaYMWP00ksvNXia4V27dgXESoHPyVWrVmnlypUhz+uiiy5SdHS07rnnnno1wBjj/83dqaeeqoyMDM2ZMyfgTEXz58+v98ZMQ7p06aLLL79cb7zxhv72t781GNPUGvTjv2lsHy1evFjfffed//8ffvihVq1a1XbORoRW5eKLL1Ztba3uu+++erfV1NT4n5P5+fmKjY3Vo48+GvBcaewsqnV+9rOfKS8vTzNnzqz3HP/hsupm6vw4Jhw5Ske+znrOOedo7ty5euWVVxqMaWpt+XH8woULA+rHD9WdcbHOiy++qB07dlBbGsAnNm3ElVdeqWuuuUZjxozROeeco08//VRLliyp987A73//e/3zn//U+eefr/Hjx6t///46dOiQ1q5dqxdffFGbN29u8N2EOrfddpu+/PJLzZgxQ//61780ZswYde7cWfv27dPHH3+shQsXKjMz09GArvPOO0+PPPKIRowYoV//+tfauXOnZs+erR49ejT4fdETTzxRBQUFAad7lqR77rmniXsLiGxPPvmkf9bTD91www3685//rHfeeUcDBw7UVVddpRNOOEF79+7Vxx9/rKVLl2rv3r2SjrwD+fLLL2v06NE677zzVFRUpDlz5uiEE06o9xuV5urevbvuv/9+TZs2TZs3b9aoUaOUnJysoqIiLVq0SFdffbWmTp2q2NhY3X///Zo4caLOOussXXLJJSoqKtK8efMc/cZGOnKgUlRUpOuvv17PPfecRo4cqczMTO3evVvvv/++Xn31VR133HGOltXUfdSjRw8NHjxY1157rSorKzVz5kx16NAh6Fd7gUg2dOhQTZw4UdOnT9cnn3yi4cOHKzY2Vhs3btTChQs1a9Ys/fKXv/TPYZo+fbrOP/98nXvuuVqzZo3eeOONRo8XpCMDOx9//HGNHDlSJ598siZMmKCcnBx99dVX+vzzz/1vstadGOh3v/udCgoKFB0drbFjx4YlxzpPPfWURowYoVGjRqmwsFD5+flKS0tTcXGxli5dqnfffddxo3H++efr3nvv1YQJE3Taaadp7dq1evrpp4PWufT0dA0ePFgTJkxQSUmJZs6cqR49euiqq65ytL42JbwnYUOoBDvdc58+fRqMr62tNbfeeqvp2LGjSUxMNAUFBWbTpk31TvdsjDEHDhww06ZNMz169DBxcXGmY8eO5rTTTjMPPfSQqaqqcpTfokWLzLnnnmsyMjJMTEyMad++vRk8eLCZMWNGvdMlSjKTJk1qcDlPPPGE6dmzp/F6vaZ3795m3rx5/lPMNrSMp556yh9/yimn+E8pWafub3ft2hVwfd1pMYuKihxtH9AS6h6nwS5bt241xhhTUlJiJk2aZHJzc01sbKzJzs42Z599tpk7d65/WT6fz/zpT38yXbt29T9fXnvtNTNu3DjTtWtXf1zdqYxnzJhRL5+mPp9eeuklM3jwYNOuXTvTrl0707t3bzNp0iSzfv36gLjHHnvM5OXlGa/Xa0499VTz7rvvmqFDh1pP91ynpqbGzJs3z5x11lkmPT3dxMTEmI4dO5qzzz7bzJkzx5SXlzvavp+yjx5++GGTm5trvF6vGTJkiPn0008Dljlu3DjTrl27oPsSCBUnp4c3Jvhjss7cuXNN//79TUJCgklOTjZ9+/Y1t9xyi9m+fbs/pra21txzzz0mJyfHJCQkmGHDhpl169bVO8b48eme67z33nvmnHPOMcnJyaZdu3amX79+5tFHH/XfXlNTY66//nqTkZFhPB5PvedKKHNsTHl5uZk5c6YZNGiQSUlJMTExMSY7O9ucf/755umnnzY1NTX1tnXhwoX1llNRUWFuvvlmfy6nn366WblyZb06V7eMZ5991kybNs1kZmaahIQEc95555lvv/02YJnBjgF/XK9aO48xbegXRWi1PB6PJk2aFPTrJwBwtGzevFl5eXmaMWOGpk6d2tLpAGglli9frjPPPFMLFy7UL3/5y5ZOxxX4jQ0AAAAA16OxAQAAAOB6NDYAAAAAXI/f2AAAAABwPT6xAQAAAOB6ETfHxufzafv27UpOTg46aRZAeBhjdODAAXXq1ElRUe55H4Q6AkQON9YRaggQOZpSQyKusdm+fbtyc3NbOg0AP7B161Z17ty5pdNwjDoCRB431RFqCBB5nNSQo9bYzJ49WzNmzFBxcbFOOukkPfrooxowYID175KTkyVJ3358rFKS3PHOTqQa3auvNWbRhrUhWY5ToVpfOPN2sq5QCuX+trFtW9lBn7r+bLP/eRlOP7WGSN/XkZ5X36nouPigcYk7fdZlnXit/f7//HH7febdW2uNkaSdp8RaY2rb2X8aeX7+h9aYNxcNtMakf1VjjSkZEG2NSdxhf9e7Ms0aIkny2FNS7EF7jJP738kXtg9l24Nqgj8Mv1+Vg+1KLXL2OHKiZJD9Pok5ZI8ZVbCy0dsrD1Vr9vAlrqojdbkO1rmKkf052ZhIfJ0Np3C+pody28P5WuxEqLbNjY+1phyLHJXG5vnnn9dNN92kOXPmaODAgZo5c6YKCgq0fv16ZWZmNvq3dR/5piRFKSWZxqY5Yjz2YuxkHztZjlOhWl848w734zCU+9vG6baF+6sYzakh0vf5RsfFK9ob/IgyOs5+YBuXFGeNiY61H7XGxDo7II322u9/E29vbLxJ9uU0tm/qxMTaj7aj4u2NTbTX/hiKdnDwL0meantMtIOYmFj7/W8cPEWivfYg47UvJ8q+Gx0/jpyIirffJ1G19hgnjzXJXXWkLtcYxTa7Jkfi62w4hfM1PZTbHs7XYidCtW1ufqw5qSFHJaNHHnlEV111lSZMmKATTjhBc+bMUWJiop588smjsToArQw1BEBzUUeAtifkjU1VVZVWr16t/Pz871cSFaX8/HytXFn/4+rKykqVlZUFXAC0XU2tIRJ1BEAgjkWAtinkjc3u3btVW1urrKysgOuzsrJUXFxcL3769OlKTU31X/ixHtC2NbWGSNQRAIE4FgHaphb/Iua0adO0f/9+/2Xr1q0tnRIAl6GOAGgOagjQOoT85AEdO3ZUdHS0SkpKAq4vKSlRdnZ2vXiv1yuv18GvKgG0CU2tIRJ1BEAgjkWAtinkn9jExcWpf//+WrZsmf86n8+nZcuWadCgQaFeHYBWhhoCoLmoI0DbdFRO93zTTTdp3LhxOvXUUzVgwADNnDlThw4d0oQJE47G6oIq6HSyNWbJ9k8ibn3hzjsU63KSc1PiQiFUeYcqZ6f3mRsfI6EWqhqS+XG5YmKCnxq5Mt1+2ssByUXWmHd7nmKNqUq1hkiS2q+3n8p5f3v7chKjqqwxlen2dXkcnF04rsx+Cs5aB6dyTtpiz0eSSo+zx/jiHJxeusoeYxycXjTpO/tpo/ecaF9OjYO3Gn3Rzk6ZXHy6fV+aRPupvC84Y7U15o3HBzd6e21VhaTXrMsJtUg5FnEiEo9F3Mjp67WT7Q/lsY8bhfMxYtuPNaZa0jeOlnVUGptLLrlEu3bt0p133qni4mKdfPLJevPNN+v9iA8AGkINAdBc1BGg7TkqjY0kTZ48WZMnTz5aiwfQylFDADQXdQRoW1r8rGgAAAAA0Fw0NgAAAABcj8YGAAAAgOvR2AAAAABwPRobAAAAAK5HYwMAAADA9Y7a6Z6PtnAOoArlAKZIG5wV7uGT4Rxi6kQ4HyPhHhwG6buhCYqODz4Zsqp7uXUZX5XnWGOSv7UPQzyc5ex9pPh99mGPVSX2ZT3z1anWGNPI8NI624dEW2Nq29mneB7ztjVECSWV9iBJGf/cao359ir7FM9oB6vr8FmZNWbjr5OsMcmb7YM1D+fY74+Ubw5ZYyRp98n2nHzV9pzemzHQGrN3aOP3v6/cwZTXCLVow1qlJB/994DDPegxnMcikfh6FWnHYq15MHco8i474FNaL2fr4xMbAAAAAK5HYwMAAADA9WhsAAAAALgejQ0AAAAA16OxAQAAAOB6NDYAAAAAXI/GBgAAAIDr0dgAAAAAcD3XDuiMtMFJToVykKNNJA5qciLShq+Ge2BmOO9/27pqTLWkb0KST0uIPSBFVwW//ec9vrYuY81Np1hj9hXac7kg/wN7kKSVDw6wxjgZLJn2aqI1prK9/b2t8kz70MjkIvtySuybpawPvfYgSWU/tw/fPNylxhpTeWK1NaYmMcUaE3PYwYDWbHuMxz6bVVtGJNuDJMU4meN50D6gsyLdvpi8lxvf1zU1Pm1zkE4kGt2rr2I8sUFvj8TBiqF6DYmk16JQLieU3DhQPBKPDUN5LMInNgAAAABcj8YGAAAAgOvR2AAAAABwPRobAAAAAK5HYwMAAADA9WhsAAAAALgejQ0AAAAA16OxAQAAAOB6rh3Q6US4h2KFSjiHT4ZKKPdjJA7hsgllPpE08KvsgE9pvUKyqhZRkyiZRmY+vr/qBOsyuldXWGPuuHChNea//jDGGiNJ1/zpRWvMX2f8yhrT4d/fWWM2Xd3ZGhNVaR/imLir1hqTtbLMGrP+RvtQUUlK/b9oa0z7z+0vb4ez7MupTLXn42SwZuome8yuX9j3Y0yZPWdJqkm1DyhN3hB88GSdio72de2JjWv09tpKn7TMvpxItGjDWqUkR8Z7wE7rfiS9hoRSKI/pQjUsPZwDvCPxmDYSB6tGxrMVAAAAAJqBxgYAAACA69HYAAAAAHA9GhsAAAAArkdjAwAAAMD1aGwAAAAAuB6NDQAAAADXo7EBAAAA4Ho0NgAAAABczz6aOUJF2uT5UArntoVzIm4ohXu6rk0o82nNj+2w61smJVYFvTmzXbl1EdGHvNaYP774K2tMls8+VV6SKkzjU9wlKWGffdR9zbdbrTHevbnWmPJMY405eEy0NaYivb01Ju5bjzVGktLWV1pjauPtOZUNrLbGdHzVfv/XxNvz3n2yfT86UZPk7HEkB7uy/aYaa0x0pT3v7UMaP5TwVYRm2xF5QjV5vjUL1Wu6W/djKB4jZQd8SuvlbH0h/8Tm7rvvlsfjCbj07t071KsB0EpRQwA0F3UEaJuOyic2ffr00dKlS79fSYxrPxgC0AKoIQCaizoCtD1H5VkeExOj7OxsR7GVlZWqrPz+awVlZWVHIyUALtKUGiJRRwDUx7EI0PYclZMHbNy4UZ06dVK3bt102WWXacuWLUFjp0+frtTUVP8lN9f+nW8ArVtTaohEHQFQH8ciQNsT8sZm4MCBmj9/vt588009/vjjKioq0pAhQ3TgwIEG46dNm6b9+/f7L1u32n/wCqD1amoNkagjAAJxLAK0TSH/KlphYaH/3/369dPAgQPVtWtXvfDCC7riiivqxXu9Xnm99rPOAGgbmlpDJOoIgEAciwBt01GfY9O+fXv16tVLmzZtOtqrAtAKUUMANBd1BGgbjnpjc/DgQX399dfKyck52qsC0ApRQwA0F3UEaBtC/lW0qVOnauTIkeratau2b9+uu+66S9HR0br00ktDuh4ng4qcDAWKxMGSoRp4Fartd7Iup4OjQrW/w7mPInEoViTmFCqhrCEZCxIUExsf9Pb93VKsy1h/uX0gYspG+zTE6x5YaI2RpAXnDbPGfHe9fX0zH9hgjbnrL6dZY7z77OuqdfANnkO/sA9Dbbcy0b4gSUUXO3hPzj7DVD3+0z44cus59nWZaPtyvHvsy/FussdE1Tobdpm2wT7E9OvfOpji6bPHxO5q/HZjn5UacqGqI6N79VWMJ7ZZuYT7tSicr2uRNlDcaT7h3P5wvl5H4jFtuIW8sdm2bZsuvfRS7dmzRxkZGRo8eLA++OADZWRkhHpVAFohagiA5qKOAG1TyBub5557LtSLBNCGUEMANBd1BGibjvpvbAAAAADgaKOxAQAAAOB6NDYAAAAAXI/GBgAAAIDr0dgAAAAAcD0aGwAAAACuF/LTPYdLJA5oDOdATCdCOczKjdw6pCyShrjWmGpJ31iXE6n2HReraG/w4XoVmfZhh9Ed7YMOq3baB0ve87SzwYBx59ljkh3cJf8q7WuNMQ5eATLWVFljyo61DzCM+tC+j6qT7PlIUvtP7evbf7x9sGrJQHtO3n32fJK+s08DLRlgfx8xptzBwMwqBzGSdp0cfDBtnZRP7cs5nGN/jtR2rmj0dt/hxm93s3C+XoeSG18f2/oQ00gchhlpA0olPrEBAAAA0ArQ2AAAAABwPRobAAAAAK5HYwMAAADA9WhsAAAAALgejQ0AAAAA16OxAQAAAOB6NDYAAAAAXM+1AzojcVCRE+HMOxKHYkXa+iJxcFYkDrxyq0N5tYpKCD6oMeG7aOsyMv9hL5Nlx9qHGFakOxusWJVqj0nZbF/fyv/6mTXmmimvWGNeLbQvZ8dpudaY3LfLrTH7etmHSkpS2lf2gY+xh+zLanfZd9aYLety7PlstA/oTN5sf6x1+ucWa0xlj0xrjCR9M9o+xPT4h7dbYzZd2dkaY4q9jd7uqbA/XiPVog1rlZLcvPeAw/06E6ohz5E2CD1UOTsVacci4R6o7tYh73xiAwAAAMD1aGwAAAAAuB6NDQAAAADXo7EBAAAA4Ho0NgAAAABcj8YGAAAAgOvR2AAAAABwPRobAAAAAK4XsQM6R/fqqxiPfcBYc4V7AFGkDbxyIhIHMIVq+8N5/4f7ceSEbfvLDviU1iskq2oR7T+PUnRc8PdvDnS1Dw7c0yfOGlOdYs8lfrc9RpJK+1VbY6Kq7bWx/abgg0nrPLVloDXmwv/51Brz1ScdrTE7DidYYzwO5zjG7LMP++z4/n5rTElcJ2tMuyT7YNUdg+wxtQn2IZ675tj3UeLf7IM+JSmqyp7Tl793sP3fOhgsW9Z4TG2le99DtR2LhOp1NpSvRZH22heJ+yhUIm0fORHKfRSu+6TGVEv6xlGse6sNAAAAAPx/NDYAAAAAXI/GBgAAAIDr0dgAAAAAcD0aGwAAAACuR2MDAAAAwPVobAAAAAC4Ho0NAAAAANeL2AGdizasVUpy8/qucA9qCtWgokgbiBnKwVFuHUIVTq15sGq4lXfwKNobfHigd699GYc72Qcrdn/xsDVmS0GSfWWSjn/QPsnzy6kZ1pjDXezril+ZbY15LDfdGnPraW9YY5Z2Pd4aUzyruzVGkr65NM0ak7HGfr/F77PH7O1vj+nwkf2ltLK9/fUs/Sn7MNj1Ex0MzJTUbaF90Ovuvl5rTPtNNdaYsi6Nb7+nyrqIiGU7FonEodvhHGDtVpE2oDScr9ehfBxFIj6xAQAAAOB6TW5s3n33XY0cOVKdOnWSx+PR4sWLA243xujOO+9UTk6OEhISlJ+fr40bN4YqXwAuRw0B0FzUEQANaXJjc+jQIZ100kmaPXt2g7c/+OCD+utf/6o5c+Zo1apVateunQoKClRRUdHsZAG4HzUEQHNRRwA0pMm/sSksLFRhYWGDtxljNHPmTN1+++268MILJUkLFixQVlaWFi9erLFjx9b7m8rKSlVWVvr/X1ZW1tSUALhIqGuIRB0B2hqORQA0JKS/sSkqKlJxcbHy8/P916WmpmrgwIFauXJlg38zffp0paam+i+5ubmhTAmAi/yUGiJRRwB8j2MRoO0KaWNTXFwsScrKygq4Pisry3/bj02bNk379+/3X7Zu3RrKlAC4yE+pIRJ1BMD3OBYB2q4WP92z1+uV12s/5SQABEMdAdAc1BCgdQjpJzbZ2UdmIpSUlARcX1JS4r8NAIKhhgBoLuoI0HaF9BObvLw8ZWdna9myZTr55JMlHfkB3qpVq3Tttdc2aVmje/VVjCc26O1uHRwVzuGLoRz4FYp1OV1fOIeLhXMfhVK4hsLVmGpJ3zjKKRRCWUMkqTK7VlEJtcHX97J9+GBtnP39nw1X2wcrnnDvNmuMJO2fYy/L0Z87GPb4mX2QY2lvY42J2R28Dtd59L8vtMZkrrEPjJzwl1esMZI0c95F1piKVPs+Ks90MuzSPqCzKsW+nEOd7cvZPCrVGhN9wH6fSVLRhfacMlfZcyr+RbQ1pqZreaO3+w5XSP9lXUzIhLqONFc4h3g6XZYTkfb6GO4hpk6Ec/vDfSwSScdQZQd8SuvlLLbJjc3Bgwe1adMm//+Lior0ySefKD09XV26dNGUKVN0//33q2fPnsrLy9Mdd9yhTp06adSoUU1dFYBWiBoCoLmoIwAa0uTG5qOPPtKZZ57p//9NN90kSRo3bpzmz5+vW265RYcOHdLVV1+t0tJSDR48WG+++abi4+NDlzUA16KGAGgu6giAhjS5sRk2bJiMCf5RuMfj0b333qt77723WYkBaJ2oIQCaizoCoCEhPXkAAAAAALQEGhsAAAAArkdjAwAAAMD1aGwAAAAAuB6NDQAAAADXC+mAznAK5+CoUA58CndOoRBpQ7qkyBviGUrhHOZmW05ThmJFopgDUYqqDv7+TXlH+/DJw5n293+6vmQfPvnVDZ2sMZLUaa59AKNnoH344p6T7cvp9lKFNWZbfqI1JnmLfdDjDY8+a4257ZnfWmMk6c9XLbDG3Pr8f1hjErfb11VRbh9QWZVq39exB+z3WZR9Xqxq0+yPNUnqPfOgNWbjhPbWmLhSB0NMtzR+CmWf/WHW5oV7+GSkDbkO93FGpA0xbc2DwMONT2wAAAAAuB6NDQAAAADXo7EBAAAA4Ho0NgAAAABcj8YGAAAAgOvR2AAAAABwPRobAAAAAK5HYwMAAADA9WhsAAAAALheTEsnEMyiDWuVkhy873IyETXcE+OdiLSc3DoRN1STjEO1rlBya96RyJdbLiUGnwrvXRFrXUZFmn3yelkXeymNLreGHImrrLXG1GTYY6L2O8jJwboSioPvvzqpXx+2xtz43iXWmGEFa60xTp2Wv84as+q1vtaY2P329/+qulZaYzx77Y812R9qivLa7zNJ+q4g3RqTUGJfzsGe1daY+K2Nb5upcrBhaLUi7bgnlNr666yT+zbc+4hPbAAAAAC4Ho0NAAAAANejsQEAAADgejQ2AAAAAFyPxgYAAACA69HYAAAAAHA9GhsAAAAArkdjAwAAAMD1InZA5+hefRXjcTDQrBGhGuIYiQOYwjnwKtzDtSJxf4eC0/0YzsetbTk1plrSN9blRCrfHq902Bv09oOd7O/tRFfZ17P7VAeDLnc4K7c7T7HXvRQHcyzTNtgHK1amB983dXL+tcMaU7tlmzWmw4k/t8a8u7+PNUaStvVtb40pzPrcvpwz7cv5+otO1pjonXHWmNT11hDtPdlnjYkqjrcvSFJ5ln2watw+++DM6P3R1piMT2savb2mukZfW5fStoXydS+cA6zDya3Ha6ES7u0P574M5bEIn9gAAAAAcD0aGwAAAACuR2MDAAAAwPVobAAAAAC4Ho0NAAAAANejsQEAAADgejQ2AAAAAFyPxgYAAACA60XsgM5FG9YqJbl5fVe4hhgejWW11nW15uFZNk63PZyPW9tyyg74lNbLupiIZWKNTGzwQYWHs+wDChN22wcdZr9nr1Vlx1pDJEnJ39qHNFZ0cLC+LvbyHmWf4SlPbQdrzM5f2YdYRjU+w1GSFL/Tfn9I0tdf2df35P4Ua8x5efYhnpsPdbbGpH9hDdGeggprTNq79uGbZUPL7SuTlPh/idaYjp9VWmN297UPca21hNRGtd73UENVi0M5fNGNwzdb61BRpyLpdb8py4pETa427777rkaOHKlOnTrJ4/Fo8eLFAbePHz9eHo8n4DJixIhQ5QvA5aghAJqLOgKgIU1ubA4dOqSTTjpJs2fPDhozYsQI7dixw3959tlnm5UkgNaDGgKguagjABrS5K+iFRYWqrCwsNEYr9er7Ozsn5wUgNaLGgKguagjABpyVL74unz5cmVmZuq4447Ttddeqz179gSNraysVFlZWcAFQNvWlBoiUUcA1MexCND2hLyxGTFihBYsWKBly5bpgQce0IoVK1RYWKja2toG46dPn67U1FT/JTc3N9QpAXCRptYQiToCIBDHIkDbFPKzoo0dO9b/7759+6pfv37q3r27li9frrPPPrte/LRp03TTTTf5/19WVkZBAdqwptYQiToCIBDHIkDbdNTPwditWzd17NhRmzZtavB2r9erlJSUgAsA1LHVEIk6AqBxHIsAbcNRb2y2bdumPXv2KCcn52ivCkArRA0B0FzUEaBtaPJX0Q4ePBjwjkdRUZE++eQTpaenKz09Xffcc4/GjBmj7Oxsff3117rlllvUo0cPFRQUNGk9o3v1VYwnNujtbh306MbBmk6WE4kDn0L1GAnlwCsn3PrYdipcNUSS2m2OUbQ3eJlLcTAMM/XT3daYzb/MtMZ491tDJEnV7exDKsuz7ENDc5fahy9uGW4fvliVYo+pyLDvx7hS+/toNYn27ZKk6AP2Zfm2p1pj/kd9rDETzn3bGvPGh8OsMe3ftg/fjKmwb3/s5/bBm5Lki7bH7DnBft/GlNtzSixp/LFWU2N/LDZVpByLhEq4B1SG8/ggnMc0rZlbB2aGW5Mbm48++khnnnmm//9130kdN26cHn/8cX322Wf6xz/+odLSUnXq1EnDhw/XfffdJ6/XXkABtH7UEADNRR0B0JAmNzbDhg2TMcHfwVmyZEmzEgLQulFDADQXdQRAQ476b2wAAAAA4GijsQEAAADgejQ2AAAAAFyPxgYAAACA69HYAAAAAHA9GhsAAAAArtfk0z1HikgbHOVUOPN264DK1srpYy1U+5L7RCrv5FNUfPDhkdXJ9mGY+/PswzerTii3xtQW2Qc0SpJ3nz0nT419OZ4a+2DF+F32dR04scoa02NerTVmX2/79u/vaQ05wsEcz0oHQ0NjPk+xxvzPc2daYyb+6UVrzKy//MoaEz+u2BpT+1yONUaS9vewx1RnVVtjkr6Ks8ZsOafx+9ZXIek9ez6RaNGGtUpJjoz3gCNxEHakHYtF4utepB33hftYJBR5lx3wKa2Xs/VFxrMVAAAAAJqBxgYAAACA69HYAAAAAHA9GhsAAAAArkdjAwAAAMD1aGwAAAAAuB6NDQAAAADXo7EBAAAA4HoRO6DTNhTLrcOcwrm+cO6jcA98csKtj5FIG+blZr44n+QNPqgxqtpeAivT7NMg0/9lHz4ZXeVgqqSk4uH2gZipH3utMZsui7XGJGxzkFCtfYjnjtMTrDHlWfaBmSbW2T5K+C7aGpO81b6s3afYY6Ir7Xk/efNoa8yY6W9bY/65ra81ptThkLrkzfaY2K/sj5G9J9r3UU37xifG+sodTJRt40I5VNONrw+R+FrUWgehh3vQa7jvWz6xAQAAAOB6NDYAAAAAXI/GBgAAAIDr0dgAAAAAcD0aGwAAAACuR2MDAAAAwPVobAAAAAC4Ho0NAAAAANeL2AGdoRDOQYdOl+VEpA3OcqtI20eRlo9kf6zVmGpJ34Qll6MheUOMor3By1xZP/swzPZr4qwxu8+stMZ4Su3DECXJE20fiBhTbo/Je9k+WHLHIHs+0e2qrTFZ/2dfl7f4oDVm03+k2xOS1OX1fdaY9VemWGNO67/eGrP1HftEzD0n2O/bLw7mWGPu6PWaNWb6k+OsMZKU+Tv78/bzFT2sMTWp9uGaXV+xLKNacjILNhKN7tVXMZ7g968bh2E6FWkDKp0I5fDJSLxPQsGNA9WbcizCJzYAAAAAXI/GBgAAAIDr0dgAAAAAcD0aGwAAAACuR2MDAAAAwPVobAAAAAC4Ho0NAAAAANejsQEAAADgeq4d0BnKwZqtlVu3vzUPBXPCrfdbJMpZsU8x0d7gt79vL4Hrr7S//+Mpsy/HxNqHakpSzqv2YY/bC+xDM/edYM/Ja59zqdoy+4DS6mT7cr75tT3IU2Ef9ClJ5i9l9qDP7QM6P1x+vDWmeox9iKuMPe81r51gjXlq8nJrzOxlG+z5SCrfkGWN+eB/HrbGDFt9hTVm/7Fpjd5eW1VrXYZbReKgx0jMKRRCmXM4t9+N+1py7+OIT2wAAAAAuF6TGpvp06fr5z//uZKTk5WZmalRo0Zp/fr1ATEVFRWaNGmSOnTooKSkJI0ZM0YlJSUhTRqAe1FHADQHNQRAME1qbFasWKFJkybpgw8+0FtvvaXq6moNHz5chw4d8sfceOONevXVV7Vw4UKtWLFC27dv10UXXRTyxAG4E3UEQHNQQwAE06Tf2Lz55psB/58/f74yMzO1evVqnXHGGdq/f7+eeOIJPfPMMzrrrLMkSfPmzdPxxx+vDz74QL/4xS/qLbOyslKVlZX+/5eVOfjuNADXoo4AaA5qCIBgmvUbm/3790uS0tPTJUmrV69WdXW18vPz/TG9e/dWly5dtHLlygaXMX36dKWmpvovubm5zUkJgMtQRwA0BzUEQJ2f3Nj4fD5NmTJFp59+uk488URJUnFxseLi4tS+ffuA2KysLBUXFze4nGnTpmn//v3+y9atW39qSgBchjoCoDmoIQB+6Cef7nnSpElat26d3nvvvWYl4PV65fUGPx0rgNaLOgKgOaghAH7oJ31iM3nyZL322mt655131LlzZ//12dnZqqqqUmlpaUB8SUmJsrOzm5UogNaFOgKgOaghAH6sSY2NMUaTJ0/WokWL9PbbbysvLy/g9v79+ys2NlbLli3zX7d+/Xpt2bJFgwYNCk3GAFyNOgKgOaghAIJp0lfRJk2apGeeeUavvPKKkpOT/d9VTU1NVUJCglJTU3XFFVfopptuUnp6ulJSUnT99ddr0KBBDZ6FpDGje/VVjCf4BG4n006dxIRysmo4p9iHc11OOM0nVPs7VMsJ5752upxwTvIN1bY1RTjrSME/PlBCUvAyN/OTs63LOGHaDmvMxomdrTEe+3B6SVLJ6HJrTMe3EqwxGR/stsZUd0yyxuw4zb6uilRjjYndFW2N8cXalyNJmz62/7A7usZjjalJsd8pGSvirDEHj7Gvq6q9fdtOv2GiNebh1Y9ZYyRp4l+vt8b8+oQCa0xOL/v7n9vOafz22srGb2+qcNaQRRvWKiW5ebPMwz3BPZyva05E4nT6cArn/R/uY9pwHYuWHfAprZezZTWpsXn88cclScOGDQu4ft68eRo/frwk6S9/+YuioqI0ZswYVVZWqqCgQI895qwQA2j9qCMAmoMaAiCYJjU2xtjfcYqPj9fs2bM1e/bsn5wUgNaLOgKgOaghAIJp3uerAAAAABABaGwAAAAAuB6NDQAAAADXo7EBAAAA4Ho0NgAAAABcj8YGAAAAgOs16XTPkSTSBh45Fc7hk+EcLBnKAVzhXl8krSuUQrEfmzIUKxJ9WparOF/wAYvRm+zDJ3eebR++GVdmH9DYYV2NNUaStqZ6rTEVHe3r81RWW2O+PTfeGpNcZD+1rs/BK0nO+7XWmOJf2Id4SlLHT+057evpYB8Z+3t7NfZdJONg+9O+sMckFldZY3792nX2BUm68vJl1pj33uhrjSn5eYo1Jto2UzbEAzrbqkgc8uzWY5FIO85wItwDtSPpvq0x1ZK+cbQsPrEBAAAA4Ho0NgAAAABcj8YGAAAAgOvR2AAAAABwPRobAAAAAK5HYwMAAADA9WhsAAAAALgejQ0AAAAA13PtgM5QDU6KtAFMUnhzCvcwUCfLCudQqHCuK5TcOFysJYztuErtkoMPfXw74wTrMro/9q01ZvOE7taYylRn7yOZJPtgTe8++7J824utMV2WpFtjdp1in1DZbrvPGrN1hH1gZlSabdLjEfuPt++jim1J1hiTbB+aarbZB6ZG2edqqvQ4e4x3f/BhsnUeO3e+fUGSpjxzuTWm68YPrTGpx7a3xuztbc8brVM4Xx9D+ZrmxtdHtx6vhBuf2AAAAABwPRobAAAAAK5HYwMAAADA9WhsAAAAALgejQ0AAAAA16OxAQAAAOB6NDYAAAAAXI/GBgAAAIDrReyAzkUb1iol+ej3XZE46DCcwyedCPc+irT7JNxDsSJt+93snvsmKCY2+IDJhO72GrP+4U7WGO/nTUqrUXHb7MMOq9vZh11u/u+e9pWttQ/fjLLPsNSefvZ84rfb93X0t4n2lUmK32WsMen7aq0xFan2fV3Z3p5PTZI9H+9e+z7acbo95uErfm1PSFJ2O/sdt/WF460xse/b99GI3/5vo7dXHqzWl49bFxORRvfqqxhPbNDbQzV0OhK5Me/WPKAy3APVnQjV+mzLKTvgU1ovZznxiQ0AAAAA16OxAQAAAOB6NDYAAAAAXI/GBgAAAIDr0dgAAAAAcD0aGwAAAACuR2MDAAAAwPUibo6NMUfmAZQd9IVlfTWm2hpTdiA8udRxkpMToco73PsoEu8Tm1DdZ06Fa/vrnod1z0u3qMu3trqi0bjaSvt7O77DjS/jyHLs80dqq5zdZ74KB8tysj4Heasy+HyOOsbBHBtftIPHh4Oc5fBpVFtlX19NtX2OTW1VtD3GQd6+Cns+zpZjf4zU1FRaYySpptr+8u7kMRJV6WDWz8HG77iqQ0dud1Mdqcu1RtVSI2mH87XI6euMk5zc+DrrRLhfi0MlnPdZKPdRuPJuyrGIx0RYpdm2bZtyc3NbOg0AP7B161Z17ty5pdNwjDoCRB431RFqCBB5nNSQiGtsfD6ftm/fruTkZHk8R97hKisrU25urrZu3aqUlJQWztAZN+YskXc4uSFnY4wOHDigTp06KSrKPd9c/XEdccO+bgh5h48bc5bckbcb60hrORaR3Jm3G3OW3Jm3G3JuSg2JuK+iRUVFBe3GUlJSInanB+PGnCXyDqdIzzk1NbWlU2iyYHUk0vd1MOQdPm7MWYr8vN1WR1rbsYjkzrzdmLPkzrwjPWenNcQdb50AAAAAQCNobAAAAAC4nisaG6/Xq7vuukter7elU3HMjTlL5B1ObszZrdy6r8k7fNyYs+TevN3IrfvajXm7MWfJnXm7MefGRNzJAwAAAACgqVzxiQ0AAAAANIbGBgAAAIDr0dgAAAAAcD0aGwAAAACuR2MDAAAAwPUivrGZPXu2jj32WMXHx2vgwIH68MMPWzqlRt19993yeDwBl969e7d0WvW8++67GjlypDp16iSPx6PFixcH3G6M0Z133qmcnBwlJCQoPz9fGzdubJlk/z9bzuPHj6+370eMGNEyyf7A9OnT9fOf/1zJycnKzMzUqFGjtH79+oCYiooKTZo0SR06dFBSUpLGjBmjkpKSFsq49aGOhJ4ba4jkzjpCDWl51JCjw411xI01RGo7dSSiG5vnn39eN910k+666y59/PHHOumkk1RQUKCdO3e2dGqN6tOnj3bs2OG/vPfeey2dUj2HDh3SSSedpNmzZzd4+4MPPqi//vWvmjNnjlatWqV27dqpoKBAFRUVYc70e7acJWnEiBEB+/7ZZ58NY4YNW7FihSZNmqQPPvhAb731lqqrqzV8+HAdOnTIH3PjjTfq1Vdf1cKFC7VixQpt375dF110UQtm3XpQR44ON9YQyZ11hBrSsqghR48b64gba4jUhuqIiWADBgwwkyZN8v+/trbWdOrUyUyfPr0Fs2rcXXfdZU466aSWTqNJJJlFixb5/+/z+Ux2draZMWOG/7rS0lLj9XrNs88+2wIZ1vfjnI0xZty4cebCCy9skXyaYufOnUaSWbFihTHmyL6NjY01Cxcu9Md8+eWXRpJZuXJlS6XZalBHjj431hBj3FtHqCHhRQ0JDzfWEbfWEGNabx2J2E9sqqqqtHr1auXn5/uvi4qKUn5+vlauXNmCmdlt3LhRnTp1Urdu3XTZZZdpy5YtLZ1SkxQVFam4uDhg36empmrgwIERv++XL1+uzMxMHXfccbr22mu1Z8+elk6pnv3790uS0tPTJUmrV69WdXV1wP7u3bu3unTpEvH7O9JRR1qGm2uIFPl1hBoSPtSQluPmOhLpNURqvXUkYhub3bt3q7a2VllZWQHXZ2Vlqbi4uIWyshs4cKDmz5+vN998U48//riKioo0ZMgQHThwoKVTc6xu/7pt348YMUILFizQsmXL9MADD2jFihUqLCxUbW1tS6fm5/P5NGXKFJ1++uk68cQTJR3Z33FxcWrfvn1AbKTvbzegjrQMt9YQKfLrCDUkvKghLcetdSTSa4jUuutITEsn0NoUFhb6/92vXz8NHDhQXbt21QsvvKArrriiBTNr/caOHev/d9++fdWvXz91795dy5cv19lnn92CmX1v0qRJWrduXUR+1xmRgzrSciK9jlBD4AQ1pOVEeg2RWncdidhPbDp27Kjo6Oh6Z2MoKSlRdnZ2C2XVdO3bt1evXr20adOmlk7Fsbr96/Z9361bN3Xs2DFi9v3kyZP12muv6Z133lHnzp3912dnZ6uqqkqlpaUB8W7b35GIOtIyWksNkSKrjlBDwo8a0nJaSx2JpBoitf46ErGNTVxcnPr3769ly5b5r/P5fFq2bJkGDRrUgpk1zcGDB/X1118rJyenpVNxLC8vT9nZ2QH7vqysTKtWrXLVvt+2bZv27NnT4vveGKPJkydr0aJFevvtt5WXlxdwe//+/RUbGxuwv9evX68tW7a4an9HIupIy2gtNUSKjDpCDWk51JCW01rqSCTUEKkN1ZEWPnlBo5577jnj9XrN/PnzzRdffGGuvvpq0759e1NcXNzSqQV18803m+XLl5uioiLz/vvvm/z8fNOxY0ezc+fOlk4twIEDB8yaNWvMmjVrjCTzyCOPmDVr1phvv/3WGGPMn//8Z9O+fXvzyiuvmM8++8xceOGFJi8vz5SXl0dkzgcOHDBTp041K1euNEVFRWbp0qXmZz/7menZs6epqKhosZyNMebaa681qampZvny5WbHjh3+y+HDh/0x11xzjenSpYt5++23zUcffWQGDRpkBg0a1IJZtx7UkaPDjTXElnek1hFqSMuihhw9bqwjbqwhxrSdOhLRjY0xxjz66KOmS5cuJi4uzgwYMMB88MEHLZ1Soy655BKTk5Nj4uLizDHHHGMuueQSs2nTppZOq5533nnHSKp3GTdunDHmyGkW77jjDpOVlWW8Xq85++yzzfr16yM258OHD5vhw4ebjIwMExsba7p27WquuuqqiHjhaShnSWbevHn+mPLycnPdddeZtLQ0k5iYaEaPHm127NjRckm3MtSR0HNjDTHGnXWEGtLyqCFHhxvriBtriDFtp454jDEmlJ8AAQAAAEC4RexvbAAAAADAKRobAAAAAK5HYwMAAADA9WhsAAAAALgejQ0AAAAA16OxAQAAAOB6NDYAAAAAXI/GBgAAAIDr0dgAAAAAcD0aGwAAAACuR2MDAAAAwPX+H4UCpmvkvEFYAAAAAElFTkSuQmCC", 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ELpcL1113HR5++GGv1+/Ro4d0rMsuuwwAsG/fPtx0003uy6Ojo5Gbmwvg3O9wmjvvL7/8EjfeeCOGDh2K119/Henp6QgNDcXChQvx7rvvqg/MB9lvgIQQmsYlCqTGBB+33347Jk2a5PU6ffr0AXDuh/yTJ0/GuHHj8Oc//xkpKSmwWCwoKChwn2ycTxVbfD2fXC4XTCYTPv/8c6/Xba2ClefHoL59+7ovT05Odsegd955x2tfb8fn7xo1l7+/QSTSon///u6saDLnf4LQyOVyISUlBUuWLPHaR/YGaFtqqzmeH1sGDRrkvjwzM9P927/Gb7pcyFts+etf/4rHH38cd9xxB5599lkkJibCbDZj+vTpPhM1qfDchhubDiMhIQHl5eUel9XX1+PkyZMel2VnZ6O6utp9EuCPIUOGIC4uDkuXLsXs2bM1pzP86KOPEB4ejtWrV8NqtbovX7hwodfrHzx4sMllP/74IyIjI4MiABPpLTk5GTExMXA6nT6fwx9++CEuvvhifPzxxx7v8D355JOtPq/s7GwIIZCVlaV8c6TxK2IHDx50Z24CgIaGBhQWFnpsVrwZPXo0LBYLlixZ4pGdqKX8XSNZDGpMhkJkJNnZ2Vi7di0GDRqkfGPj/Oft+Z+slpWV+fwUMjs7G8C5DYMqZsm+ltYWcwSAG264AX/729+wZMkSj41NS3344Ye45pprmtTTKi8vR6dOnZpc/8LYIoTAoUOH3G9U0S/4G5sOIjs7u8nvYxYsWNDkE5tbb73VndbwQuXl5XA4HNLbiIyMxMMPP4x9+/bh0Ucf9foOgT/vGlgsFphMJo85Hj16FCtWrPB6/S1btnh8N7WoqAiffPIJRo4cyXdIqUOwWCyYMGECPvroI69phsvKyjyuC3g+J7dt24YtW7a0+rxuvvlmWCwWPP30001igBDC/Zu7fv36ITk5GfPnz/fIVLRo0aImb8x407VrV9xxxx34/PPP8c9//tPrdfyNQRf2Ua3RihUrcPz4cff/v/nmG2zbtq3jZCOiduXWW2+F0+nEs88+26TN4XC4n5O5ubkIDQ3Fa6+95vFcUWVRbfSb3/wGWVlZmDt3bpPn+PljNdbUufA6bTFH4NzXWa+77josWLAAn3zyidfr+BtbLrz+smXLPOLH+RozLjb68MMPcfLkScYWL/iJTQdx11134d5778WECRNw3XXX4dtvv8Xq1aubvDPw5z//Gf/+979xww03YPLkycjJyUFNTQ327t2LDz/8EEePHvX6bkKjRx99FN9//z3mzJmD//znP5gwYQK6dOmCs2fPYufOnVi2bBlSUlKaVaDr+uuvxyuvvIJRo0bh97//PUpLSzFv3jx0797d6/dFe/Xqhby8PI90zwDw9NNP+7laRMHt7bffdtd6Ot+DDz6Iv/3tb1i/fj0GDBiAu+++G5dffjnOnDmDnTt3Yu3atThz5gyAc+9Afvzxxxg/fjyuv/56FBYWYv78+bj88sub/EZFq+zsbDz33HOYPXs2jh49inHjxiEmJgaFhYVYvnw57rnnHsyaNQuhoaF47rnnMHXqVIwYMQK/+93vUFhYiIULFzbrNzbAuROVwsJCPPDAA1i6dCnGjh2LlJQUnDp1Cl999RU+/fRTXHrppc0ay9816t69OwYPHoz77rsPdrsdc+fORVJSkvSrvUTBbNiwYZg6dSoKCgqwe/dujBw5EqGhoTh48CCWLVuGV199Fbfccou7DlNBQQFuuOEGjBkzBrt27cLnn3+uPF8AzhXsfOONNzB27FhcccUVmDJlCtLT0/HDDz/gu+++c7/J2pgY6E9/+hPy8vJgsVgwceLENpljo3feeQejRo3CuHHjMHr0aOTm5iIhIQHFxcVYu3YtNm3a1OyNxg033IBnnnkGU6ZMwdVXX429e/diyZIl0jiXmJiIwYMHY8qUKSgpKcHcuXPRvXt33H333c26vQ6lbZOwUWuRpXvu2bOn1+s7nU7xyCOPiE6dOonIyEiRl5cnDh061CTdsxBCVFVVidmzZ4vu3buLsLAw0alTJ3H11VeLl156SdTX1zdrfsuXLxdjxowRycnJIiQkRMTHx4vBgweLOXPmNEmXCEDk5+d7Heett94Sl1xyibBareKyyy4TCxcudKeY9TbGO++8477+r3/9a3dKyUaNfcvKyjwub0yLWVhY2KzjIwqExsep7K+oqEgIIURJSYnIz88XmZmZIjQ0VKSlpYlrr71WLFiwwD2Wy+USf/3rX0W3bt3cz5eVK1eKSZMmiW7durmv15jKeM6cOU3m4+/z6aOPPhKDBw8WUVFRIioqSlx22WUiPz9fHDhwwON6r7/+usjKyhJWq1X069dPbNq0SQwbNsxnuudGDodDLFy4UIwYMUIkJiaKkJAQ0alTJ3HttdeK+fPni7q6umYdX0vW6OWXXxaZmZnCarWKIUOGiG+//dZjzEmTJomoqCjpWhK1luakhxdC/phstGDBApGTkyMiIiJETEyM6N27t3j44YfFiRMn3NdxOp3i6aefFunp6SIiIkIMHz5c7Nu3r8k5xoXpnhtt3rxZXHfddSImJkZERUWJPn36iNdee83d7nA4xAMPPCCSk5OFyWRq8lxpzTmq1NXViblz54qBAweK2NhYERISItLS0sQNN9wglixZIhwOR5NjXbZsWZNxbDabeOihh9xzGTRokNiyZUuTONc4xnvvvSdmz54tUlJSREREhLj++uvFTz/95DGm7BzwwnjV3pmE6EC/KKJ2y2QyIT8/X/r1EyIivRw9ehRZWVmYM2cOZs2aFejpEFE7sWHDBlxzzTVYtmwZbrnllkBPxxD4GxsiIiIiIjI8bmyIiIiIiMjwuLEhIiIiIiLD429siIiIiIjI8PiJDRERERERGV7Q1bFxuVw4ceIEYmJipJVmiahtCCFQVVWFjIwMmM3GeR+EcYQoeBgxjjCGEAUPf2JI0G1sTpw4gczMzEBPg4jOU1RUhC5dugR6Gs3GOEIUfIwURxhDiIJPc2KIbhubefPmYc6cOSguLkbfvn3x2muvoX///j77xcTEAAB+2nkRYqO978rG9+jd4nkt/3GvtE3LuL7G9kWvY/I1tpY5++LrmLTcF3qutV5ja7mffNHrfqysdqHbb466n5dtqaUxBPgljvz2379FaFSo1+ts/uZyaf+QGvU7tDFH5W3WSpey74lcdXvcXu/zBQCzQ/2TyKoseVt4mfqYQmvUY9sS5P3tyepjstjkfc2KNgCwpzco2xN3yF/GLOquOH2F/JgtyXXKvjEbI5XttiT5cTmi1WvtiJS3mxzq9fJ1P9uSFcecWa3sKwqjpW1hPSqlbc5aOw7dNddQcaQ55yIqWs8nVAL1WhLIY1LR+poeqNfeYHzNB/Q9R2opf85FdNnYvP/++5g5cybmz5+PAQMGYO7cucjLy8OBAweQkpKi7Nv4kW9stBmxMd6DSYhJ/sLvi2xMreP6GtsXvY7J19ha5uyLr2PScl/oudZ6ja3lfvJFz/sRQJt/FUNLDAF+mW9oVCjCosO8XsccHi7tb3aqj9fifUgAQEio+iTfHOFjExCm2NiY1SfEZvkhwWL1cUwN6rFV/c3hPo4Z8r4WRRsAmCMs6nmFKTY2Ph625nD5MZsVm4tzt6tYbKjXy6W4XV/z8rWx8XU/q8a2RDqUfV2K54wl0q7sCxgrjjTnXERF6/mESqBeSwJ5TCpaX9MD9dobrK/5ep4jadWcGKLL7F555RXcfffdmDJlCi6//HLMnz8fkZGRePvtt5tc1263o7Ky0uOPiDo2f2IIwDhCRE3xXISo42n1jU19fT127NiB3NzcX27EbEZubi62bNnS5PoFBQWIi4tz//E7rUQdm78xBGAcISJPPBch6phafWNz6tQpOJ1OpKamelyempqK4uLiJtefPXs2Kioq3H9FRUWtPSUiMhB/YwjAOEJEnnguQtQxBTwrmtVqhdVqDfQ0iMjAGEeISAvGEKL2odU/senUqRMsFgtKSko8Li8pKUFaWlpr3xwRtTOMIUSkFeMIUcfU6p/YhIWFIScnB+vWrcO4ceMAnCt0tW7dOkybNq3Z44zv0VuamWH1id3SfnkZV/gx2+aPq3VsX331OiatY+vV1xctfbXOS9XfV99gvR9byiEaABzRZWyZ1oohALB5++XS7Ge3X/ultN/Sfw9Vjmu65ZS07fSWZGVfc606q4vJJc9adebXTmXfsDPyDGIuH9He19jWEvkACfvVx1SbKm83qW8Wpgb1+2+1afKxk/arBw+pkY+dEFej7FuZHqVstyfKM8WZ1EnkEKJ4jGR8qc5cdny4+o6OKJWPXZ2o/sSiU+/T0jaLWX5QTke9clw9tGYc0UMg4rmv29V7bNVx6XnMRqXXfRXIc6S2oMtX0WbOnIlJkyahX79+6N+/P+bOnYuamhpMmTJFj5sjonaGMYSItGIcIep4dNnY/O53v0NZWRmeeOIJFBcX44orrsCqVaua/IiPiMgbxhAi0opxhKjj0S15wLRp04Li414iMibGECLSinGEqGMJXPlQIiIiIiKiVsKNDRERERERGR43NkREREREZHgBL9DZElpSzemVyldPWtNQ6zVvrePqmZpbi2BNJ65XisX2nGbTlGSHKdJ7ett3V8tTOuff/Lly3P95Z4y0LaxaPSfrWfX7SaE18nTPoWfl6ZwBQCiyLjv7VSn7RpjktwsAdYiUtl30b3Vq5KrsGGmbpV6d+7iuWH3MkWXy9MdVmeq+DTHy244Pr1P2tfzgK0+1/M4o/536vrAVydfrp9vUt2suVb+s1/aRH1dkpDotc3WdPB10apz8mBwh6hTV7VEgy0foRevrbqBSXBv1NU6v13w978dgwE9siIiIiIjI8LixISIiIiIiw+PGhoiIiIiIDI8bGyIiIiIiMjxubIiIiIiIyPC4sSEiIiIiIsPjxoaIiIiIiAwvaOvYLP9xL2Jj/N936VnTRcvYeua0D1S+/GDNhR6oGjeAvvnyWavGfyGHI2AJD/faFnNlmbTfm4vldWoA4KaJm6VtW05lKfse25eubI8qkse9UB81cpL2y+uFnDRHK/v6KGODyCp5XZbSK2OVfetS5H3tqT5uOMaubD59NkzaJmLVdVlMtfKXwDN18ro9AHDmKkXRIADOaHm9mZBD6vWKKpWPHbs5VNm3rK+yGc5SeS2ahnrvz5VGjkj5fVVUFCVtc9ls6kkFsfE9eiPE5H3NtdRl0fN1SnXbgawfp9frULDXVZEJ1GNAq2Bfb35iQ0REREREhseNDRERERERGR43NkREREREZHjc2BARERERkeFxY0NERERERIbHjQ0RERERERle0KZ7bmmKxUCmoQvWVIZ6rYnW4w3W9MVa5qVnXy2pt7WkJTWysHLAIslue2Z/J2m/UHlGXADAe9uukrbdfOV2Zd8T1RnK9vo4eZvLqk6NXJ4tD+nmBnXfxP3q9tIr5e2OKHXqY5NT3je6c6Wyb8POBHV7jHzshOQqZd/ThxOlbbV2eRppAHBGupTtCJXPS1jUa13TWd5ek6lea1d0g7K909fydNH1ceqxq7vK55X6jbyfowE4phyZ/BGo8hBGfc0PZOrtQAnWVNItPRdxiAYAR5p1G/zEhoiIiIiIDI8bGyIiIiIiMjxubIiIiIiIyPC4sSEiIiIiIsPjxoaIiIiIiAyPGxsiIiIiIjI8bmyIiIiIiMjwgraOjYqWeh565n/XcruBqjOi53r5ouV+DFZGfHy1Z1W962GO8P7+TWiJvJ5H7FF1nRGY5aFz7WJ5jRsAuO72Hcr2vc/0lbbVdrIo+1ZnytvMDeoaJQ3RymZYbPI2Z1adsm/IwUhpm+2HeGXf0L4VynbXCfnETxWpx0aovBaNrU5dx8bkUq9nSIS8nkxUoXpsW7K8zZ7oVPZN2ip/XPsSUqN+3Kd/JW8v+7X8fVKXTb1WwWz5j3sRG9P67wEbtRaNEbXH179APX60aul5X2WVCwk9mncbrf5sfeqpp2AymTz+Lrvssta+GSJqpxhDiEgrxhGijkmXT2x69uyJtWvX/nIjIYb8YIiIAoQxhIi0Yhwh6nh0eZaHhIQgLS2tWde12+2w2+3u/1dWVuoxJSIyEH9iCMA4QkRN8VyEqOPRJXnAwYMHkZGRgYsvvhh/+MMfcOzYMel1CwoKEBcX5/7LzFR8SZyIOgR/YgjAOEJETfFchKjjafWNzYABA7Bo0SKsWrUKb7zxBgoLCzFkyBBUVVV5vf7s2bNRUVHh/isqKmrtKRGRgfgbQwDGESLyxHMRoo6p1b+KNnr0aPe/+/TpgwEDBqBbt2744IMPcOeddza5vtVqhdVqbe1pEJFB+RtDAMYRIvLEcxGijkn3Ojbx8fHo0aMHDh06pPdNEVE7xBhCRFoxjhB1DLqnCKmursbhw4fxxz/+0a9+euWO74j1YgIlULn29cxZH6y549vz46ulMQQAUr8IQUio9zB39lJ5bY2GKHU9j4YYef2T3rkHlX2/LbhC2X73nI+kbU99c6Oyb9S+cGlbSLWyK2yJ6lojMT/J1+RsF3WsNveU/xC7X8bPyr47Vl+ubBdd5PVi4KMcUcJO+UtgrOJ4AaAoz0ddoEp5rZrKS+SPHwCwnpavZ8J36rU+fbViPQDAJu9vqVWPXR4iP+auqxzSNkeDA0fUs9JdS+PI+B69EWJqeW0gmWCtWxaMNUya097S29V7bL1uV8/zq0DV/VHNyyEagGZGkVbfOcyaNQsbN27E0aNH8fXXX2P8+PGwWCy47bbbWvumiKgdYgwhIq0YR4g6plb/xObnn3/GbbfdhtOnTyM5ORmDBw/G1q1bkZysKKVMRPT/MYYQkVaMI0QdU6tvbJYuXdraQxJRB8IYQkRaMY4QdUy6Jw8gIiIiIiLSGzc2RERERERkeNzYEBERERGR4eme7lkPgUqvF6gUeYFM5Ruo9QpUykkgcKkO9bzdlo5dWeVCQo/WnUtbOnuZCeZw7ylqRYgifXGOOmVu/G55Kt8fTlyq7NvQW9mM15+7Rdr2f/7PCmXf5+rGStusxeqUtc4IdXrjTteelLbVfp2h7Gupkaeh3utQp3MOsSibEXlEflydN9Qo+x6cJE9ffLavOp1z1FH1+4Ipu+Tpj08MUvety6qXtl004oSyb/nxVGV72ir5y77JqX4MnOojvzOO3W6XtrlqHcBa5dCG1NHSKgdr2mStgvWcUotgLXuhopqzP+ci/MSGiIiIiIgMjxsbIiIiIiIyPG5siIiIiIjI8LixISIiIiIiw+PGhoiIiIiIDI8bGyIiIiIiMjxubIiIiIiIyPCCto7N+B69EWLyXp8gUHnD9awno+WYAlV3RWtO+0DlrQ/WtQ5UjYBAPX7aQn2iE+YIp9e2qJ/k4S/he3XNF5eiBk5dsrr+SWi1shklV7ukbX/7dLyy723XfSVt2/Jof2XfouvULwclilo15t4Vyr51R2OkbdZT6vfXarvK68EAABTL/fO1UcquMT/K29Jf+VrZtzT/amV7ebb8MZT8rffHZKMTcfL7oqQ6Wtk3+w11LZoj4+QLlrRH/dhN2Sm/L4pD5bWKTDblsEFt+Y97ERvj/TEayNorKsEa0/V6HQpkfZ1gfQxoEaw1CJuLn9gQEREREZHhcWNDRERERESGx40NEREREREZHjc2RERERERkeNzYEBERERGR4XFjQ0REREREhhe06Z5V9EoZGKzpnPUUyGPSKwWjnqkfyVispSGwhHsPc44oeVrc0qvU6Xgjf5aHTmu5ek71cer2iBPysYVF3Xd98SXStgF/3a3sayvtpmwvOdJJ2haxQ31QaQfk6xlRWqfsW93Fqmy3Jcjfn7OlKLuiLkX+GDg8Z6Cyb0SJeuzaDPnYVRep31N0WeXrFRaifmweHRuhbE/8Tt5W1U2d7rkyRP7YdEbK05S7zOoU1MFMVXpCJZDlDvR6XdfzNT9Y18OXYE1TrUWwlupoLn5iQ0REREREhseNDRERERERGR43NkREREREZHjc2BARERERkeFxY0NERERERIbHjQ0RERERERkeNzZERERERGR4QVvHZvmPexEb4/++K1jzggfrvHzRknc+WHOha5l3IPPht8c6SnoLqwAsNu9tVTl2aT9LaZhyXHuvWmmb+C5S2TekWtmM6myHtC3ymDpkq2rNfOVUF8EZlH5E2f75dnlRmARFnRoAqEmX37YrVF2npjpT/TpQ001RI+dn9TFHVsjrtjjV04IjWt1uscnHdkTLa74AQOwB+f1s2pCsvuEr1M1lA+WPLwh1HRuTQ9GuOCRhMm4dGxW96uZpfZ0J1GuYL8Fa/0TLegXrMel5vhDs5xN+7xw2bdqEsWPHIiMjAyaTCStWrPBoF0LgiSeeQHp6OiIiIpCbm4uDBw+21nyJyOAYQ4hIK8YRIvLG741NTU0N+vbti3nz5nltf/HFF/GPf/wD8+fPx7Zt2xAVFYW8vDzYbJK3TYmoQ2EMISKtGEeIyBu/v4o2evRojB492mubEAJz587FY489hptuugkAsHjxYqSmpmLFihWYOHFikz52ux12+y9fCamsrPR3SkRkIK0dQwDGEaKOhuciRORNqyYPKCwsRHFxMXJzc92XxcXFYcCAAdiyZYvXPgUFBYiLi3P/ZWZmtuaUiMhAWhJDAMYRIvoFz0WIOq5W3dgUFxcDAFJTUz0uT01NdbddaPbs2aioqHD/FRUVteaUiMhAWhJDAMYRIvoFz0WIOq6AZ0WzWq2wWn2knyEiUmAcISItGEOI2odW/cQmLS0NAFBSUuJxeUlJibuNiEiGMYSItGIcIeq4WvUTm6ysLKSlpWHdunW44oorAJz7Ad62bdtw3333+TXW+B69EWIK9dqmyqGtpRZIsOfmDgQtudADVS9Gaz0YvfLS6/n4ai+P3daMIQBQ09UFc7j3AhuJX8rfnQ2tVtfdsGyV963sqp5TXap6bHOd/P2m+nh138G/+V7atmVTT2Xf9WvlNXAAwNFNXqjk2ic2K/t+8NEwaVttmrp2iitEfcyqGimOaHVfW4q8PXOtujbPT2N91HxxytvTvlT3PTlcXmum52/VKYvLvrpM2Z62QV7bx5akfq9TKJotdvlaOuvNaMsvdrVmHFHV1AtUDRO96udopWe9vkCdu+k152AeW+tt68EhGgCoa6018ntjU11djUOHDrn/X1hYiN27dyMxMRFdu3bF9OnT8dxzz+GSSy5BVlYWHn/8cWRkZGDcuHH+3hQRtUOMIUSkFeMIEXnj98Zm+/btuOaaa9z/nzlzJgBg0qRJWLRoER5++GHU1NTgnnvuQXl5OQYPHoxVq1YhPDy89WZNRIbFGEJEWjGOEJE3fm9shg8fDiHkHzmbTCY888wzeOaZZzRNjIjaJ8YQItKKcYSIvGnV5AFERERERESBwI0NEREREREZHjc2RERERERkeAEv0CnT3lIsaqHn8QYyJaCW9I2BSgcdyLTKWtJjt7SvPykWg5EwA0KS3daWJE+5a5Jn2wUAVF7U8veEXFZ1CmIVR0q9sn33h72kbeE+phxRJk/nDAB1KfL1+rkuQdnXckWFtK2+JkzZV5xVt4edkacvhjqrMsLL5Itytod6wSxVPtJ2Kx5DVZnqiYWWy9u3FV6k7BvSoGxGiCots3qpYbHJ2+qS5XN22n3cERQ0AnV+5UuwljQI1vXqyPiJDRERERERGR43NkREREREZHjc2BARERERkeFxY0NERERERIbHjQ0RERERERkeNzZERERERGR43NgQEREREZHhBW0dGxUt+cy15BzXs3aKFnrWfNFTsOalVwnWmkJ69a2sciGhR4uHDjhhdUFYvddncYXK39epj/NRd0PRXJupLoITdVQddut618kb7YqaLThXt0cm5pi6Tk34aXUBFFeIvMjJ1eMPKftuOtJd2vbnnP8o+760a6R6XrZwaZsjXn1fuELk90X4aWVXOGOc6nZFmZuoIvVjwBkuf4A12NSPAfgok3S6p7y/LVV9TOEn5X0jixX1cepbXrupI9L6mh6sr63BWiNOCy315fQUqLUOhvNRfmJDRERERESGx40NEREREREZHjc2RERERERkeNzYEBERERGR4XFjQ0REREREhseNDRERERERGZ4h0z1rSWPXHlPzGTWdc7Cmz9brdvW8n4ya/lNvIRUWmCUpkhti5CloI0rV41ZdLE+dHJlSo+xbY4pStkf8ECFts6Wp0/GGVsmPKfaIel7OcPXLga2TPAXx3B9GKPs6bPKx99dmKPtGRdmU7dXp8jbTWXmKagDK1MiVF6u7mm3q9wVFqHxwR6R6bJeib+Rh9TE55dmvAQAmRQbsqGPqVNLOUHlbQ7T88eG0+0ifblBazif0TO/fHtMqG1GwrnUgz0XaAj+xISIiIiIiw+PGhoiIiIiIDI8bGyIiIiIiMjxubIiIiIiIyPC4sSEiIiIiIsPjxoaIiIiIiAyPGxsiIiIiIjK8oK1jM75Hb4SYvCfND9bc4EbMaR/IWjJ63Y/BWo9Iz7H1qhnkEA0AjrSobzBwxDtgjvBeuMNcJ6/ZEX+wQTnu2V7y0Fl7Vl6HBgBMkYpCIgBcYfJ5xRxU1xkxO+T1T2yd1AVObInqsUNq5WOfPa0uzGIKkfc9WpOk7Pv77O3K9q/OZEvbDvyUpezrDFcUstFImOVjh6hL88BSL6/7kralStn3yIRoZbuqzk1otY96M4rlcilq3LjkZZ+ojQVDnREKbsFar6+5/P7EZtOmTRg7diwyMjJgMpmwYsUKj/bJkyfDZDJ5/I0aNaq15ktEBscYQkRaMY4QkTd+b2xqamrQt29fzJs3T3qdUaNG4eTJk+6/9957T9Mkiaj9YAwhIq0YR4jIG7+/ijZ69GiMHj1aeR2r1Yq0tLRmjWe322G3293/r6ys9HdKRGQgrR1DAMYRoo6G5yJE5I0uyQM2bNiAlJQUXHrppbjvvvtw+vRp6XULCgoQFxfn/svMzNRjSkRkIP7EEIBxhIia4rkIUcfT6hubUaNGYfHixVi3bh1eeOEFbNy4EaNHj4bT6fR6/dmzZ6OiosL9V1RU1NpTIiID8TeGAIwjROSJ5yJEHVOrZ0WbOHGi+9+9e/dGnz59kJ2djQ0bNuDaa69tcn2r1Qqr1dra0yAig/I3hgCMI0TkieciRB2T7nVsLr74YnTq1AmHDh3S+6aIqB1iDCEirRhHiDoG3evY/Pzzzzh9+jTS09P96rf8x72IjfF/36WlXozWWiB61RnROi+96uvoWZvHl0DUdGkOPY9Zr7FV41ZWuZDQQ5ebbbaWxhAASNwZAkuY9zBX01les8NpVcceYZUX5rDG2qVtANBwPErZXp8kHzu0Sl1r5mw3eaERe7yi0AiAhlh1TRdVjZOQU+qxzfJvEWKvXf1bhqK0eGX7b1J/lrZ97+MVLqZQfj8LHy8/tk7qdnPPammbPT5W3VlRTsaWoq5H5FI/RBBRKh88skT9GKjuIu8bflre11mvX72g5mppHFHV1AtWgXrN74iMej6hRbA/Dvze2FRXV3u841FYWIjdu3cjMTERiYmJePrppzFhwgSkpaXh8OHDePjhh9G9e3fk5eW16sSJyJgYQ4hIK8YRIvLG743N9u3bcc0117j/P3PmTADApEmT8MYbb2DPnj3417/+hfLycmRkZGDkyJF49tln+d1VIgLAGEJE2jGOEJE3fm9shg8fDiHkHyuvXr1a04SIqH1jDCEirRhHiMgb3ZMHEBERERER6Y0bGyIiIiIiMjxubIiIiIiIyPB0T/fcUqoUi4FKgacljXAg0+NpSY1MnoI1xbVe4zpEA4AjutxuW7AlmWCxek9R64iSfz+/9Dfq9K7hCVXStvjoWmXfilMxynZ7sjzdc/gpddpcYZG/V1XbWT4uAMT/oMgxDMAZJm9zJDiUfS3V8hzEiRkVyr5njyYo2zcdkLf/btRmZd+PPxwibavLUB8TQtX3RWfF46A4Tv0YsNjkbSevUr9sm31MuyFa3nY61cfjK0TeHnlS8fgJfLZnXQQqNbKer0PBWkrBiAJZ/iFQ94Vejz1/8BMbIiIiIiIyPG5siIiIiIjI8LixISIiIiIiw+PGhoiIiIiIDI8bGyIiIiIiMjxubIiIiIiIyPC4sSEiIiIiIsML2jo2y3/ci9gY//ddwZBDu7UFMh++itYc7YG87ZaOrWXOwfr4as+sV52GJdLqta1GVU/GpSjaAiBii7xveay6RonoK6+BAwDdX5HXAzk6NkrZ19yguN3EemXf0Br1MZ8dKO8fvd/7GjcKq5AXMqk700nZV2SqC7PE75S3rds1SNnXlmeXthWOfEvZ96qH71W2Hx+WJG0zhakLu7hS5WttOqO+nyxp6jpK2Q+dkrYV3nGRsm9dpvwBdmqovE6Sq64eeEc5dNDS61xEz9e/YK1FE6i6P4G8L7TcrpaxA1WjUMsxqdoqq1xI6NG8OfATGyIiIiIiMjxubIiIiIiIyPC4sSEiIiIiIsPjxoaIiIiIiAyPGxsiIiIiIjI8bmyIiIiIiMjwgjbds4oR0wRroTUNohHT/ulJz9SPgUrprNda+pNiMRg5nBYIp8Vrm7k8tMXj1qbL0/WG1Kn7WsPU6YuFRZ46OeysPBU0AOVbVfVn1WmCHeHqsS2l8v62RHX64rByeZtJniX4XHuEer1q0+QvY5Z69TF16yxPffxYaW9l37OXqsc2V3t/3AFAeKn6PcVaq+Kl2axe64bycGV7yahu0janVT22yS6fd2icPHW2C4o85B1UoFIfB2vZgUCmoTYio55ftQV+YkNERERERIbHjQ0RERERERkeNzZERERERGR43NgQEREREZHhcWNDRERERESGx40NEREREREZHjc2RERERERkeEFbx2Z8j94IMXmvMxEMebL9pSXnuNb87qr2QK6lXnnpg7VWUbDWI1LNyyEaABzR5XbbgnlDPMxhkroe2fICKhevqFGOe/BeeQ2czl3KlH2PHElVtlfeJZ9X2hp10ZeSkfJ6IfFb1XVsYo/WK9ud4fL6Ovbhlcq+Z2OipG1xXSqUfa0mdW2Visvl7a5qda2iqLfTpW3vjkpS9k0oUjbj6ydfk7b96qNpyr6WGPn9eNGb6vo5h2+T188BgOiT8rpA1V191HaKkfft9FGktM3RYDZsFGnpuYier/m+6DUvra9hWs5FjPi6bsQ5B3Ls1joX8esTm4KCAlx55ZWIiYlBSkoKxo0bhwMHDnhcx2azIT8/H0lJSYiOjsaECRNQUlLiz80QUTvGOEJEWjCGEJGMXxubjRs3Ij8/H1u3bsWaNWvQ0NCAkSNHoqbml3c3Z8yYgU8//RTLli3Dxo0bceLECdx8882tPnEiMibGESLSgjGEiGT8+iraqlWrPP6/aNEipKSkYMeOHRg6dCgqKirw1ltv4d1338WIESMAAAsXLsSvfvUrbN26FVdddVWTMe12O+x2u/v/lZXqrzQQkbExjhCRFowhRCSjKXlARcW570YnJiYCAHbs2IGGhgbk5ua6r3PZZZeha9eu2LJli9cxCgoKEBcX5/7LzMzUMiUiMhjGESLSgjGEiBq1eGPjcrkwffp0DBo0CL169QIAFBcXIywsDPHx8R7XTU1NRXFxsddxZs+ejYqKCvdfUZGPX2QSUbvBOEJEWjCGENH5WpwVLT8/H/v27cPmzZs1TcBqtcJqlWfbIaL2i3GEiLRgDCGi87XoE5tp06Zh5cqVWL9+Pbp06eK+PC0tDfX19SgvL/e4fklJCdLS0jRNlIjaF8YRItKCMYSILuTXJzZCCDzwwANYvnw5NmzYgKysLI/2nJwchIaGYt26dZgwYQIA4MCBAzh27BgGDhzo18SW/7gXsTHe91165Q0P1pzjWsdWrZdetWT0pmeufT3HpraNI/ZYwCJ7E1ZRHqXkymjluKER1dK2Y6WJyr6mBvX7SUJRpsQep65hkrJGXoekdKC6Bk5VlrrOjcsq7+86E6Hsa0mwS9uqayR1hv4/cULd7kqS13x5+pqPlX2fapggbbMeUd/u439erGy//P0HpG2xR9WPgZj18vvi2Eh139BTymYcHy5vM9erawaZT8sfX0IxLVVbS7RlDOlogrXuXbDSq2aQL1rORfSskxQM/NrY5Ofn491338Unn3yCmJgY93dV4+LiEBERgbi4ONx5552YOXMmEhMTERsbiwceeAADBw70moWEiDoexhEi0oIxhIhk/NrYvPHGGwCA4cOHe1y+cOFCTJ48GQDw97//HWazGRMmTIDdbkdeXh5ef/31VpksERkf4wgRacEYQkQyfn8VzZfw8HDMmzcP8+bNa/GkiKj9YhwhIi0YQ4hIppW/+UpERERERNT2uLEhIiIiIiLD48aGiIiIiIgMr8UFOgMpUOn1fAlU+j09bzdQqR99HVOwHnMgUzCqdNQ01Y7LauGK9J6mOHJXpLTf5RO/V467//1fSdvMDerv/5vUWZfREG2Rtp39jTy1MQCYauV9VemtAcAR51S2m2vl74NZqhS3CyB6nzxNsEveBAAIP+Xr9xTy1MjPnL5F2VMkOOS3e0B9TA99eruyvet/5OtZ1lf9nuKpPvLbvv/Gz5R9F/7PGGV7Za96eaNTnU489Iz8lOHkSPlj01XnAD5UDh209Co9EaiYHOypemU64noF6pgDdR6tGreyyoWEHs0bh5/YEBERERGR4XFjQ0REREREhseNDRERERERGR43NkREREREZHjc2BARERERkeFxY0NERERERIbHjQ0RERERERle0NaxGd+jN0JM3gsc6FXzJVjzzhuVllzogarro3XsYK0RoKX2k5HFxdbBIqlj46iR17HZW5quHNdaK6+tUpesrgXijFDXZYn/UV7opspHHn/rGfl7VQ2x6gI6UYfVdVuqfm2TtoVGqOvr1JfHSNscPtZDWNTrGVks7++U3PeNLOHyWjOV2eq+Zod6Xo5I+X0RWq3sivp4+TFdGXFE2fdt9d2IhB3ywkH2BPUxhdTI25wRitMJW9CeatAF9DxHCkT9E6Bj1sAxYl281pozP7EhIiIiIiLD48aGiIiIiIgMjxsbIiIiIiIyPG5siIiIiIjI8LixISIiIiIiw+PGhoiIiIiIDC9oczAu/3EvYmO877u0pCPUkxFT/WoRyDTBWm47WNMbB2NKysoqFxJ8pBgOZuUHEmEOD/fallQtT6lb80OcctyEU/I0wRa7Ot/u2Z7KZtjjVe83yW8XACL7nZK2nTker+zriFC/zxUVK0/3XF0crewbFiZf69Tt6rTKVZ3V69kgz9qNuB/UL3G2pJa/BEYfU6eprsiSz7u6m/p+zOhRJm1bUZ6j7FvTWb2eSXvkKZ1Da9THZEuS9xWKTNHqUclfeqY3DtbzGJVAlngIFD3vp2BNn91c/MSGiIiIiIgMjxsbIiIiIiIyPG5siIiIiIjI8LixISIiIiIiw+PGhoiIiIiIDI8bGyIiIiIiMjxubIiIiIiIyPCCto7N+B69EWIK9bufnvnbteT2NmreeSPmtNeTlvXwdR8HKne8alyHaABwRJfbbQuRJ0ywWL0X2KiPUfVTj1vcX1FbJatW2de6K0rZ3jCiQtpmOqmuF1O9J0nemFGv7Gt2ql8Oaioi5H3r1O+ROaLklUxKf+Pr/TV1FZT6VIe0LWGn+pjqE+Q1X0SMfFwAsKf7mLdTXtjFbFP3Pf6T/H5ctTZN2ffvUxcp25/dO0naVt1VUYwGQL/r90nbdi/rJW1z2o37Hqpe5yKBfC0xokAdU3tc60Aek2rs1joX8SvaFBQU4Morr0RMTAxSUlIwbtw4HDhwwOM6w4cPh8lk8vi79957/bkZImrHGEeISAvGECKS8Wtjs3HjRuTn52Pr1q1Ys2YNGhoaMHLkSNTU1Hhc7+6778bJkyfdfy+++GKrTpqIjItxhIi0YAwhIhm/voq2atUqj/8vWrQIKSkp2LFjB4YOHeq+PDIyEmlp6o/LG9ntdtjtdvf/Kysr/ZkSERkM4wgRacEYQkQymr74WlFx7rvgiYmJHpcvWbIEnTp1Qq9evTB79mzU1sq/c15QUIC4uDj3X2ZmppYpEZHBMI4QkRaMIUTUqMXJA1wuF6ZPn45BgwahV69ffjT4+9//Ht26dUNGRgb27NmDRx55BAcOHMDHH3/sdZzZs2dj5syZ7v9XVlYyoBB1EIwjRKQFYwgRna/FG5v8/Hzs27cPmzdv9rj8nnvucf+7d+/eSE9Px7XXXovDhw8jOzu7yThWqxVWq7Wl0yAiA2McISItGEOI6Hwt+iratGnTsHLlSqxfvx5dunRRXnfAgAEAgEOHDrXkpoionWIcISItGEOI6EJ+fWIjhMADDzyA5cuXY8OGDcjKyvLZZ/fu3QCA9PT0Fk3Qm5bmwdbaV0965rTX63Z9Cdb7IljzzgfrerW2towjNV1dMId7r1UiLPL6KCJMXTslOrVa2uZyqWuBmBuUzQgJlV8hYof6vagQm3zepj3qWhxneqqPOfmLMGlbTYb6mOt61UnbUpPLlX2Pl8Yr22GX1xRqGCmvCQQApp9ipW0JW+XHCwDlg23KdleVfL0tNvV6JX0rf2lO2nlG2ffR8MnK9v95/J/Stn9X/EbZ99PD8lo1kJc5grOVy9i0ZQxZ/uNexMYYtw7PhQL5WhGs5yp63W4g68VoWWuj1+7xa2OTn5+Pd999F5988gliYmJQXFwMAIiLi0NERAQOHz6Md999F2PGjEFSUhL27NmDGTNmYOjQoejTp48uB0BExsI4QkRaMIYQkYxfG5s33ngDwLnCV+dbuHAhJk+ejLCwMKxduxZz585FTU0NMjMzMWHCBDz22GOtNmEiMjbGESLSgjGEiGT8/iqaSmZmJjZu3KhpQkTUvjGOEJEWjCFEJNN+vjhKREREREQdFjc2RERERERkeNzYEBERERGR4bW4QKfeVCkWVanotKSh89XXqCnwApUe24jpGYOZlsd9S/tWVrmQ0EM9r2AWkl4DS6TTa5sqLbNJnY0XNcdjpG2RRfL0wwAgfIxdVRMuHzvKR1rlZMUxec967VYfp75Cfaz8fTBzvXpsUSFPnXyiJFXZN/yU+v23iDL57y1qusQr+0JxzOWXqn/H4apX388Rx+Uvr/Zk9Vrb4+XHfLZ3vLJvfZx63ovKhkjbhsf/oOx7JjNK2rbeLg8Urlp1amzyZKT0/efTeg6ll0CVj9B6LqLXua4vwXju5s+5CD+xISIiIiIiw+PGhoiIiIiIDI8bGyIiIiIiMjxubIiIiIiIyPC4sSEiIiIiIsPjxoaIiIiIiAyPGxsiIiIiIjK8oK1joxctecH1qhXiq68vetbu0dLXqLn4VYK1dk+wzivQuiWdRUiU1WvbwW8zpf1EqLoWiNkmrxdTk92g7JuxRv1+Uk1mpLJdpT5ePm9LnboGTswR9bwc8vI6qEtVr5e1VF7zpT5BXdOl9iL1elrqQ6Vt4aeUXVEfK29zxXivf9QoaYv8dgGg6iL5mpjt6vuipot8TRwR6vvJGader43r+0jbivrHK/sOTCqU326d/D522dQ1f8hTIF9btdSu0/M8JlDnbnrS83Vby/1odPzEhoiIiIiIDI8bGyIiIiIiMjxubIiIiIiIyPC4sSEiIiIiIsPjxoaIiIiIiAyPGxsiIiIiIjK8dpfuWUsau0CmwOuIaYIDlY4wUGMHa8rv9iwqtB6hkqy8Iqle2k/4SE8bViJP9Zv+uTrd7pHfqlP9dvmPvK3kSnVaZUeUPE2w9bT6mKouUac3Djsjfx8s+pj6mFTStqlv9/hw9ctUZLH8mKNPyO9jACi/XDG2Wb3W4WfVaaqjT8rby/qqU0XXx8nbarPVx9Tpa/XYZ38lb/txfxdl36IT3aRtd09cJ22zVTfgeeXIHU+wpkbWQsu89Dx3M+rro16PEa3nIlrWsy0em/zEhoiIiIiIDI8bGyIiIiIiMjxubIiIiIiIyPC4sSEiIiIiIsPjxoaIiIiIiAyPGxsiIiIiIjK8oEv3LMS5FJuV1fJUmQ6hTqcajCqr1KlBA8XXWmqZt5axtdzHvuYcqMePnvPS6/HV+DxsfF4aReN8G2rkqXFddTZ5fx/pnp12eYpih8Ou7OuqU4/taJCnTnbZ1O9Fuczyx4HTrr5dV5067bJTcdtOe8vTPTsa1I97l039MuWslz82HQ51amRXnWJsl4/na4N6PdGgui/Ua+2yyY/JVadeL2e9r7EVbVAfs+oxZKuWz8te4wBgrDjSnHMRLQL1Gheo1/Tm9NdLsL726rkegbyfWzq2alx/zkVMIsgizc8//4zMzMxAT4OIzlNUVIQuXdQ1LoIJ4whR8DFSHGEMIQo+zYkhQbexcblcOHHiBGJiYmAymVBZWYnMzEwUFRUhNjY20NMLelwv/3C91IQQqKqqQkZGBsxm43xzlXFEG66Xf7heakaMI4wh2nC9/MP1UvMnhgTdV9HMZrPX3VhsbCzvbD9wvfzD9ZKLi1OUQQ9SjCOtg+vlH66XnNHiCGNI6+B6+YfrJdfcGGKMt06IiIiIiIgUuLEhIiIiIiLDC/qNjdVqxZNPPgmr1RroqRgC18s/XK+Ogfezf7he/uF6tX+8j/3D9fIP16v1BF3yACIiIiIiIn8F/Sc2REREREREvnBjQ0REREREhseNDRERERERGR43NkREREREZHjc2BARERERkeEF/cZm3rx5uOiiixAeHo4BAwbgm2++CfSUgsKmTZswduxYZGRkwGQyYcWKFR7tQgg88cQTSE9PR0REBHJzc3Hw4MHATDbACgoKcOWVVyImJgYpKSkYN24cDhw44HEdm82G/Px8JCUlITo6GhMmTEBJSUmAZkytiTHEO8YQ/zCOdGyMI94xjjQfY0jbCOqNzfvvv4+ZM2fiySefxM6dO9G3b1/k5eWhtLQ00FMLuJqaGvTt2xfz5s3z2v7iiy/iH//4B+bPn49t27YhKioKeXl5sNlsbTzTwNu4cSPy8/OxdetWrFmzBg0NDRg5ciRqamrc15kxYwY+/fRTLFu2DBs3bsSJEydw8803B3DW1BoYQ+QYQ/zDONJxMY7IMY40H2NIGxFBrH///iI/P9/9f6fTKTIyMkRBQUEAZxV8AIjly5e7/+9yuURaWpqYM2eO+7Ly8nJhtVrFe++9F4AZBpfS0lIBQGzcuFEIcW5tQkNDxbJly9zX+f777wUAsWXLlkBNk1oBY0jzMIb4j3Gk42AcaR7GEf8whugjaD+xqa+vx44dO5Cbm+u+zGw2Izc3F1u2bAngzIJfYWEhiouLPdYuLi4OAwYM4NoBqKioAAAkJiYCAHbs2IGGhgaP9brsssvQtWtXrpeBMYa0HGOIb4wjHQPjSMsxjqgxhugjaDc2p06dgtPpRGpqqsflqampKC4uDtCsjKFxfbh2TblcLkyfPh2DBg1Cr169AJxbr7CwMMTHx3tcl+tlbIwhLccYosY40nEwjrQc44gcY4h+QgI9AaK2lJ+fj3379mHz5s2BngoRGRTjCBFpwRiin6D9xKZTp06wWCxNskGUlJQgLS0tQLMyhsb14dp5mjZtGlauXIn169ejS5cu7svT0tJQX1+P8vJyj+t39PUyOsaQlmMMkWMc6VgYR1qOccQ7xhB9Be3GJiwsDDk5OVi3bp37MpfLhXXr1mHgwIEBnFnwy8rKQlpamsfaVVZWYtu2bR1y7YQQmDZtGpYvX44vvvgCWVlZHu05OTkIDQ31WK8DBw7g2LFjHXK92gvGkJZjDGmKcaRjYhxpOcYRT4whbSTAyQuUli5dKqxWq1i0aJHYv3+/uOeee0R8fLwoLi4O9NQCrqqqSuzatUvs2rVLABCvvPKK2LVrl/jpp5+EEEL87W9/E/Hx8eKTTz4Re/bsETfddJPIysoSdXV1AZ5527vvvvtEXFyc2LBhgzh58qT7r7a21n2de++9V3Tt2lV88cUXYvv27WLgwIFi4MCBAZw1tQbGEDnGEP8wjnRcjCNyjCPNxxjSNoJ6YyOEEK+99pro2rWrCAsLE/379xdbt24N9JSCwvr16wWAJn+TJk0SQpxLs/j444+L1NRUYbVaxbXXXisOHDgQ2EkHiLd1AiAWLlzovk5dXZ24//77RUJCgoiMjBTjx48XJ0+eDNykqdUwhnjHGOIfxpGOjXHEO8aR5mMMaRsmIYTQ9zMhIiIiIiIifQXtb2yIiIiIiIiaixsbIiIiIiIyPG5siIiIiIjI8LixISIiIiIiw+PGhoiIiIiIDI8bGyIiIiIiMjxubIiIiIiIyPC4sSEiIiIiIsPjxoaIiIiIiAyPGxsiIiIiIjI8bmyIiIiIiMjw/h+//a0dpUjD+wAAAABJRU5ErkJggg==", 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", 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", 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import os\n", + "import sys\n", + "import json\n", + "import pickle\n", + "import matplotlib.pyplot as plt\n", + "from tqdm import tqdm\n", + "import numpy as np\n", + "from config_ import ModelConfig\n", + "from train_and_eval import calculate_f1_score\n", + "from sklearn.metrics import f1_score\n", + "\n", + "\n", + "data_dir = \"datasets/consensus_dataset\"\n", + "\n", + "THRESHOLD = -0.4\n", + "datapoints = {}\n", + "\n", + "\n", + "for folder in tqdm(os.listdir(data_dir)):\n", + " num_agents = int(folder.split(\"_\")[1]) # Extract num agents\n", + " \n", + " folder_path = os.path.join(data_dir, folder)\n", + "\n", + " # Load model config from summary json\n", + " with open(os.path.join(folder_path, \"results/NoiseType.NONE\", \"0.01\", \"summary_results.json\"), \"r\") as f:\n", + " summary_results = json.load(f)\n", + "\n", + " \n", + " for i, graph in enumerate(os.listdir(folder_path)):\n", + "\n", + " # train_summary_results\n", + " summ_results = summary_results[i-1]\n", + "\n", + " if graph == \"results\": # ignore the result folder\n", + " continue\n", + "\n", + " graph_path = os.path.join(folder_path, graph)\n", + "\n", + " # Load run data\n", + " with open(os.path.join(folder_path, graph), \"r\") as f:\n", + " run_data = json.load(f)\n", + "\n", + " true_graph = np.array(run_data[\"adjacency_matrix\"])\n", + " \n", + " learned_graph = np.array(summ_results[\"raw_attention\"])\n", + "\n", + " predicted_graph = (learned_graph > THRESHOLD).astype(int)\n", + "\n", + " fig, ax = plt.subplots(1,3, figsize=(10, 8))\n", + "\n", + " ax[0].imshow(true_graph)\n", + " ax[0].set_title(\"True Graph\")\n", + " ax[1].imshow(learned_graph)\n", + " ax[1].set_title(\"Learned Graph\")\n", + " ax[2].imshow(predicted_graph)\n", + " ax[2].set_title(\"Predicted Graph\")\n", + "\n", + " break\n", + "\n", + "\n", + "for key in datapoints.keys():\n", + " datapoints[key] = sum(datapoints[key])/len(datapoints[key])\n", + "\n", + "\n", + "x = []\n", + "y = []\n", + "\n", + "for item in datapoints.items():\n", + " x.append(item[0])\n", + " y.append(item[1])\n", + "\n", + "print(THRESHOLD)\n", + "plt.ylim(0, 1)\n", + "plt.scatter(x, y)\n", + "plt.show() \n", + "\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "764558cb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Starting training pipeline for 'datasets/consensus_dataset' data.\n", + "\n", + "Processing 100 graphs for agents_5...\n", + "0.8571428571428571\n" + ] + } + ], + "source": [ + "from train_and_eval import *\n", + "\n", + "train_config = TrainConfig()\n", + "train_config.epochs = 10_000\n", + "train_config.f1_threshold = -2\n", + "train_config.data_directory = \"datasets/consensus_dataset\"\n", + "\n", + "print(f\"Starting training pipeline for '{train_config.data_directory}' data.\")\n", + "\n", + "# Get sorted list of agent directories\n", + "agent_dirs = sorted(\n", + " [d for d in os.listdir(train_config.data_directory) if d.startswith(\"agents_\")],\n", + " key=lambda x: int(x.split('_')[1])\n", + ")\n", + "\n", + "starter_key = jax.random.PRNGKey(49)\n", + "agent_dir_name = agent_dirs[0]\n", + "agent_dir_path = os.path.join(train_config.data_directory, agent_dir_name)\n", + "\n", + "all_results_for_agent = []\n", + "\n", + "graph_files = sorted([f for f in os.listdir(agent_dir_path) if f.endswith(\".json\")])\n", + "\n", + "results_dir = os.path.join(agent_dir_path, \"results\")\n", + "os.makedirs(results_dir, exist_ok=True)\n", + "\n", + "subdir = str(train_config.noise_type)\n", + "subsubdir = str(train_config.noise_level)\n", + "sub_results_dir = os.path.join(results_dir, subdir, subsubdir)\n", + "os.makedirs(sub_results_dir, exist_ok=True)\n", + "\n", + "print(f\"\\nProcessing {len(graph_files)} graphs for {agent_dir_name}...\")\n", + "graph_file_name = graph_files[0]\n", + "file_path = os.path.join(agent_dir_path, graph_file_name)\n", + "\n", + "with open(file_path, 'r') as f:\n", + " data = json.load(f)\n", + "\n", + "# 1. Load and Prepare Data\n", + "trajectories = np.array(data['trajectories'])*10\n", + "s, l, n = trajectories.shape\n", + "# trajectories = trajectories.T\n", + "# np.random.shuffle(trajectories)\n", + "# trajectories = np.random.shuffle(trajectories)\n", + "true_graph = np.array(data['adjacency_matrix'])\n", + "starter_key, data_key = jax.random.split(starter_key)\n", + "inputs, targets = prepare_data_for_model(data_key, trajectories, train_config, train_config.batch_size)\n", + "\n", + "# 2. Configure Model\n", + "num_agents = trajectories.shape[-1]\n", + "model_config = ModelConfig(\n", + ")\n", + "\n", + "model_config.num_agents=num_agents\n", + "model_config.input_dim=1 # Each agent has a single state value at time t\n", + "model_config.output_dim=1\n", + "model_config.embedding_dim=32 \n", + "\n", + "# 3. Train the Model\n", + "# This relies on the modified train_model that returns final params\n", + "final_params, train_logs = train_model(\n", + " config=model_config,\n", + " inputs=inputs,\n", + " targets=targets,\n", + " true_graph=true_graph,\n", + " train_config=train_config\n", + ")\n", + "\n", + "# 4. Evaluate\n", + "f1 = calculate_f1_score(\n", + " final_params, \n", + " model_config, \n", + " true_graph, \n", + " train_config.f1_threshold\n", + ")\n", + "\n", + "loss_history_serializable = {\n", + " epoch: [loss.item() for loss in losses] \n", + " for epoch, losses in train_logs['loss_history'].items()\n", + "}\n", + "\n", + "\n", + "print(f1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1335db3f", + "metadata": {}, + "outputs": [ + { + "ename": "KeyError", + "evalue": "0", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mKeyError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[28]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[43mdata\u001b[49m\u001b[43m[\u001b[49m\u001b[32;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n", + "\u001b[31mKeyError\u001b[39m: 0" + ] + } + ], + "source": [ + "data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c5ca08df", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "graph-recognition-w-attn (3.12.3)", + "display_name": "graph-recognition-w-attn", "language": "python", "name": "python3" }, diff --git a/train_and_eval.py b/train_and_eval.py index 3f36f0f..cf78a96 100644 --- a/train_and_eval.py +++ b/train_and_eval.py @@ -51,7 +51,7 @@ def prepare_data_for_model(key: jax.Array, trajectories: np.ndarray, train_confi all_targets = all_targets[all_indices] if train_config.noise_type != NoiseType.NONE and train_config.noise_level > 0: - noise_shape = full_dataset_inputs.shape + noise_shape = all_inputs.shape if train_config.noise_type == NoiseType.NORMAL: noise = jax.random.normal(key, noise_shape) * train_config.noise_level elif train_config.noise_type == NoiseType.UNIFORM: @@ -60,18 +60,18 @@ def prepare_data_for_model(key: jax.Array, trajectories: np.ndarray, train_confi minval=-train_config.noise_level, maxval=train_config.noise_level ) - full_dataset_inputs += np.array(noise) # Add noise to inputs + all_inputs += np.array(noise) # Add noise to inputs - full_dataset_inputs = np.expand_dims(all_inputs, axis=-1) + all_inputs = np.expand_dims(all_inputs, axis=-1) full_dataset_targets = np.expand_dims(all_targets, axis=-1) # Create batches - num_samples = full_dataset_inputs.shape[0] + num_samples = all_inputs.shape[0] num_batches = num_samples // batch_size # Truncate to full batches - truncated_inputs = full_dataset_inputs[:num_batches * batch_size] + truncated_inputs = all_inputs[:num_batches * batch_size] truncated_targets = full_dataset_targets[:num_batches * batch_size] # Reshape into batches @@ -81,6 +81,40 @@ def prepare_data_for_model(key: jax.Array, trajectories: np.ndarray, train_confi return batched_inputs, batched_targets +def f1_score_np(y_true: np.ndarray, y_pred: np.ndarray) -> float: + """ + Compute the F1 score between two numpy arrays. + + Parameters + ---------- + y_true : np.ndarray + Ground truth (correct) labels. + y_pred : np.ndarray + Predicted labels. + + Returns + ------- + float + The F1 score. + """ + # Ensure binary arrays (0 or 1) + y_true = np.asarray(y_true).astype(int) + y_pred = np.asarray(y_pred).astype(int) + + # Compute True Positives, False Positives, and False Negatives + tp = np.sum((y_true == 1) & (y_pred == 1)) + fp = np.sum((y_true == 0) & (y_pred == 1)) + fn = np.sum((y_true == 1) & (y_pred == 0)) + + # Precision and Recall + precision = tp / (tp + fp) if (tp + fp) > 0 else 0.0 + recall = tp / (tp + fn) if (tp + fn) > 0 else 0.0 + + # F1 Score + if precision + recall == 0: + return 0.0 + return 2 * (precision * recall) / (precision + recall) + def calculate_f1_score( params: dict, model_config: ModelConfig, @@ -111,7 +145,7 @@ def calculate_f1_score( true_flat = true_graph.flatten() pred_flat = predicted_graph.flatten() - return f1_score(true_flat, pred_flat) + return f1_score_np(true_flat, pred_flat) def main(): """Main script to run the training and evaluation pipeline.""" @@ -125,7 +159,7 @@ def main(): print(f"Please run the data generation script for '{train_config.data_directory}' first.") return - print(f"🚀 Starting training pipeline for '{train_config.data_directory}' data.") + print(f"Starting training pipeline for '{train_config.data_directory}' data.") # Get sorted list of agent directories agent_dirs = sorted( @@ -146,7 +180,8 @@ def main(): os.makedirs(results_dir, exist_ok=True) subdir = str(train_config.noise_type) - sub_results_dir = os.path.join(results_dir, subdir) + subsubdir = str(train_config.noise_level) + sub_results_dir = os.path.join(results_dir, subdir, subsubdir) os.makedirs(sub_results_dir, exist_ok=True) print(f"\nProcessing {len(graph_files)} graphs for {agent_dir_name}...") diff --git a/uv.lock b/uv.lock index 5987ef0..4253836 100644 --- 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