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            "Collecting transformers\n",
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            "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1 (from transformers)\n",
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            "\u001b[?25hCollecting safetensors>=0.3.1 (from transformers)\n",
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            "Installing collected packages: tokenizers, safetensors, huggingface-hub, transformers\n",
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        "df = pd.read_csv('/content/essayData.csv')\n",
        "\n",
        "# Initialize the zero-shot classification pipeline\n",
        "classifier = pipeline(\"zero-shot-classification\", model=\"facebook/bart-large-mnli\")\n"
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "# Create an empty list to store the predictions\n",
        "predictions = []\n",
        "word_labels = []\n",
        "num_rows = df.shape[0]\n",
        "# Iterate through each row of the DataFrame\n",
        "for index, row in df.iterrows():\n",
        "    # Get the value from the \"Section\" column\n",
        "    sequence_to_classify = row['ABSTRACT']\n",
        "    # Define the candidate labels\n",
        "    candidate_labels = ['technology', 'business', 'humanities', 'sciences']\n",
        "\n",
        "    # Perform zero-shot classification and get the predicted label\n",
        "    prediction = classifier(sequence_to_classify, candidate_labels)\n",
        "\n",
        "    # Add the predicted label to the list\n",
        "    word_labels.append(prediction['labels'][0])\n",
        "    predictions.append(prediction['scores'])\n",
        "    print(f'row :{index}/{num_rows}')\n",
        "\n",
        "# Add the predictions as a new column in the DataFrame\n",
        "df['Predicted_Label'] = predictions\n",
        "df['Max_Label'] = word_labels\n",
        "\n",
        "# Save the updated DataFrame to a new CSV file\n",
        "df.to_csv('predicted_file_topic_class.csv', index=False)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pyvRAhMCgRE5",
        "outputId": "bf17ddc5-bad6-43ce-81b8-459cc44b4f87"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "# Calculate the accuracy\n",
        "correct_predictions = 0\n",
        "for index,row in df.iterrows():\n",
        "  max_label =row['Max_Label']\n",
        "  terms = row['terms']\n",
        "  if(max_label in terms):\n",
        "    correct_predictions+=1\n",
        "total_predictions = len(df)\n",
        "accuracy = correct_predictions / total_predictions\n",
        "\n",
        "# Print the accuracy\n",
        "print(\"Accuracy:\", accuracy)\n"
      ],
      "metadata": {
        "id": "cWxFlDtvhssC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fb6ad9e5-e65c-4d16-9327-734b310573d1"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy: 0.711864406779661\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Verifying with ChatGPT labellings"
      ],
      "metadata": {
        "id": "6vnqhlYkssY2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install openai"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KR41845Ys6id",
        "outputId": "cc1261ac-1df2-46f2-81e7-2d55aa5b9829"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting openai\n",
            "  Downloading openai-0.27.8-py3-none-any.whl (73 kB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/73.6 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m73.6/73.6 kB\u001b[0m \u001b[31m6.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: requests>=2.20 in /usr/local/lib/python3.10/dist-packages (from openai) (2.27.1)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from openai) (4.65.0)\n",
            "Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from openai) (3.8.4)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai) (1.26.16)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai) (2023.5.7)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai) (2.0.12)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai) (3.4)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai) (23.1.0)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai) (6.0.4)\n",
            "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai) (4.0.2)\n",
            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai) (1.9.2)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai) (1.3.3)\n",
            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai) (1.3.1)\n",
            "Installing collected packages: openai\n",
            "Successfully installed openai-0.27.8\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import time\n",
        "def get_response(user_prompt, system_prompt=\"You are a classification agent, I will give a few lines of text and your goal is to classify the text on the basis of its content. Your output should be the class you want to classify your text, which is either 'technology', 'science','business' or 'humanities', you can ONLY output one of these fields which you think fits the content of the text best\"\n",
        "):\n",
        "    while True:\n",
        "        try:\n",
        "            response = openai.ChatCompletion.create(\n",
        "                model=\"gpt-3.5-turbo\",\n",
        "                messages=[\n",
        "                    {\"role\": \"system\", \"content\": system_prompt},\n",
        "                    {\"role\": \"user\", \"content\": user_prompt},\n",
        "                ]\n",
        "            )\n",
        "            return response['choices'][0]['message']['content']\n",
        "        except Exception as e:\n",
        "            print(\"An error occurred while generating response: \" + str(e))\n",
        "            time.sleep(3)\n",
        "            continue\n"
      ],
      "metadata": {
        "id": "hPLW2Emsu_J4"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import openai\n",
        "# Load your API key from an environment variable or secret management service\n",
        "openai.api_key = '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'\n",
        "chatgpt_labels = []\n",
        "for index,row in df.iterrows():\n",
        "  chatgpt_label = get_response(row['ABSTRACT'])\n",
        "  chatgpt_labels.append(chatgpt_label)\n",
        "  print(f'row :{index}/{num_rows}')\n",
        "\n",
        "\n",
        "df['ChatGPT_Labels'] = chatgpt_labels\n",
        "\n",
        "df.to_csv('predicted_file_topic_class.csv', index=False)\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s0Fg_pmiP7P8",
        "outputId": "59053d54-f53e-4a32-caa1-65bca3918669"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "# Calculate the accuracy\n",
        "\n",
        "bart_to_human_predictions = 0\n",
        "gpt_to_human_predictions = 0\n",
        "bart_to_gpt_predictions = 0\n",
        "for index,row in df.iterrows():\n",
        "  max_label =row['Max_Label']\n",
        "  gpt_label = row['ChatGPT_Labels']\n",
        "  terms = row['terms']\n",
        "  if(max_label in terms):\n",
        "    bart_to_human_predictions+=1\n",
        "  if(gpt_label in terms):\n",
        "    gpt_to_human_predictions+=1\n",
        "  if(max_label == gpt_label):\n",
        "    bart_to_gpt_predictions+=1\n",
        "\n",
        "\n",
        "total_predictions = len(df)\n",
        "bart_to_gpt_accuracy = bart_to_gpt_predictions/total_predictions\n",
        "bart_to_human_accuracy = bart_to_human_predictions/total_predictions\n",
        "gpt_to_human_accuracy = gpt_to_human_predictions/total_predictions\n",
        "# Print the accuracy\n",
        "print(\"% of results matching between BART-LARGE-MNLI and ChatGPT:\", bart_to_gpt_accuracy)\n",
        "print(\"% of results matching between BART-LARGE-MNLI and Human Labelled Input:\", bart_to_human_accuracy)\n",
        "print(\"% of results matching between ChatGPT and Human Labelled Input:\", gpt_to_human_accuracy)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "q3uGG6OTt9Nk",
        "outputId": "d503c305-9750-4114-aa93-828c5f1bd70a"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "% of results matching between BART-LARGE-MNLI and ChatGPT: 0.6610169491525424\n",
            "% of results matching between BART-LARGE-MNLI and Human Labelled Input: 0.711864406779661\n",
            "% of results matching between ChatGPT and Human Labelled Input: 0.6949152542372882\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "from sklearn.metrics import confusion_matrix\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Assuming df is your DataFrame and it has 'terms' and 'Max_label' columns\n",
        "\n",
        "# Create a set of all unique labels in 'terms' and 'Max_label'\n",
        "all_labels =set(['technology','science','humanities','business'])\n",
        "print(all_labels)\n",
        "\n",
        "# Create a new column for each label\n",
        "for label in all_labels:\n",
        "    df[label] = df['Max_Label'] == label\n",
        "\n",
        "# Now create confusion matrix for each label\n",
        "for label in all_labels:\n",
        "    df['true'] = df['terms'].apply(lambda x: label in x)\n",
        "    cm = confusion_matrix(df['true'], df[label])\n",
        "    plt.figure(figsize=(5, 5))\n",
        "    sns.heatmap(cm, annot=True, fmt='d', cmap='Blues')\n",
        "    plt.title(f'Confusion matrix for {label}')\n",
        "    plt.xlabel('Predicted')\n",
        "    plt.ylabel('Actual')\n",
        "    plt.show()\n"
      ],
      "metadata": {
        "id": "Vs7JBRd4GFf4",
        "outputId": "b12ee977-4b79-4fcf-8988-33592c4af918",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'science', 'business', 'technology', 'humanities'}\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "for label in all_labels:\n",
        "    df[label] = df['ChatGPT_Labels'] == label\n",
        "\n",
        "# Now create confusion matrix for each label\n",
        "for label in all_labels:\n",
        "    df['true'] = df['terms'].apply(lambda x: label in x)\n",
        "    cm = confusion_matrix(df['true'], df[label])\n",
        "    plt.figure(figsize=(5, 5))\n",
        "    sns.heatmap(cm, annot=True, fmt='d', cmap='Blues')\n",
        "    plt.title(f'Confusion matrix for {label}')\n",
        "    plt.xlabel('Predicted')\n",
        "    plt.ylabel('Actual')\n",
        "    plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "4vg6lalCE8H7",
        "outputId": "e026d550-4105-4e65-ba50-552414d01d19"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 2 Axes>"
            ],
            "image/png": 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FBQVYsWIFli1bhkqVKmHw4MGPXMG8+OKLOHz4MBISEoxjmZmZWLZsGby9veHn5/dI81auXBlA4edcrVo1tG/fHkuXLsXVq1cLPe7+tacAEBoaimPHjhX6uwLKtmJ78cUXkZKSgg0bNhjH7t69iwULFsDOzg7t2rUr8nGWlpZ44YUX8O2335rc9Uev12PdunVo27at8aON4OBgJCQkICkpyXjcrVu38MUXXxQ5d79+/aBSqfDOO+/g/PnzJp9jUsXACrCUatWqhXXr1uGVV16Br6+vyZ1gDhw4gI0bNxrvFdm4cWOEhYVh2bJlSE1NRbt27XD48GGsXr0a3bt3R4cOHRSLq2/fvnjvvffQo0cPjBo1CllZWViyZAnq1q1rsvhjypQp2LdvH7p27QovLy9cu3YNixcvRvXq1U0WXTzoo48+QpcuXRAYGIjBgwcjOzsbCxYsgFarfaLuu/jSSy9hzZo10Gq18PPzQ0JCAn744Qc4OzubHNekSRNYWlpi1qxZSEtLg0ajQceOHVGtWrVSnW/lypXYtm0bVq1aherVqwO4l3BfffVVLFmyBG+//Xapn8O4ceOwfv16dOnSBaNGjYKTkxNWr16N5ORkfP311498kbuNjQ38/PywYcMG1K1bF05OTmjQoAEaNGiARYsWoW3btmjYsCGGDh2KmjVrQq/XIyEhAZcvX8axY8cAAGPGjMGmTZvQu3dvDBo0CP7+/rh16xa2bNmC2NhYNG7c+JFie5hhw4Zh6dKlGDhwIBITE+Ht7Y1Nmzbh559/xrx58/51Ydq0adOwa9cutG3bFm+//TYqVaqEpUuXwmAwYPbs2cbjxo4di7Vr16JTp04YOXIkbG1t8emnn8LT0xO3bt0qVEG7uLigc+fO2LhxIxwcHBR9Q0vlxGzrTyu4P//8UwwdOlR4e3sLtVotqlSpItq0aSMWLFhgspQ8Ly9PTJ48Wfj4+AgrKytRo0aNf70Q/kHt2rUT7dq1M/5c3GUQQty7wL1BgwZCrVaLevXqibVr1xa6DCI+Pl6EhIQId3d3oVarhbu7u+jXr5/4888/C53jwQvhf/jhB9GmTRthY2Mj7O3tRbdu3Yq9EP7ByyzuX/j9z2sGi3L/wugHFff64IHLCG7fvi1ef/11UbVqVWFnZyeCg4PFH3/8UeTlC8uXLxc1a9YUlpaWRV4IX5R/znPp0iWh1WpFt27dCh3Xo0cPYWtr+9Al8Q/Gf9/9C+EdHByEtbW1aNmyZbEXwt+/SUBJHDhwQPj7+wu1Wl3ocoFz586JAQMGCJ1OJ6ysrISHh4d46aWXxKZNm0zmuHnzphgxYoTw8PAQarVaVK9eXYSFhYkbN278a1xF/V0V9/su6rIevV5v/N2q1WrRsGHDQn+jQhR/IXxwcLCws7MTlStXFh06dBAHDhwo9NijR4+KZ599Vmg0GlG9enURHR0tYmJiBADjdaL/9NVXXwkAYtiwYYX20ZNPJcQT/EkzEZGZhYeHY+nSpcjIyCi0YOfbb79F9+7dsW/fPpNLmKhiYAIkIvqv7Oxsk1W1N2/eRN26ddGsWTPs2rWr0PEvvfQSTp06hbNnzyq6sIrKBz8DJCL6r8DAQLRv3x6+vr7Q6/VYsWIF0tPTMX78eJPjvvzyS/z222/Ytm0b5s+fz+RXQbECJCL6r/fffx+bNm3C5cuXoVKp0KxZM0ycOLHQ5SEqlQp2dnZ45ZVXEBsbi0qVWEtURLwMgojov2bMmIE///wTWVlZyMzMxE8//VTktZFCCNy5cweffvopk18p7du3D926dYO7uztUKhXi4uJM9n/zzTd44YUX4OzsDJVKZXJZyn05OTkYPnw4nJ2dYWdnh9DQ0CIvS3sYJkAiIio3mZmZaNy4MRYtWlTs/rZt22LWrFnFzhEREYGtW7di48aN2Lt3L65cuYKePXuWOha2QImIyCxUKhU2b96M7t27F9p34cIF+Pj44OjRoyY3KE9LS4OLiwvWrVuHXr16Abh3Vx9fX18kJCSgVatWJT4/K0AiInosBoMB6enpJltxd5Z6XImJicjLyzNpTdevXx+enp4md08qiaeyef3u1sL3/SMqC4P9q5s7BJKEn7uy99u1aTpCsbneC6mKyZMnm4xNnDixTO4SlZKSArVabfxqt/tcXV2RkpJSqrmeygRIREQPoVKuARgVFVXoe081Go1i85cVJkAiInosGo2m3BKeTqdDbm4uUlNTTapAvV4PnU5Xqrn4GSARkYxUKuW2cuTv7w8rKyvEx8cbx06fPo2LFy+W+ns4WQESEclIwRZoaWRkZJh8x2JycjKSkpLg5ORk/OaNixcv4sqVKwD+9z2kOp0OOp0OWq0WgwcPRmRkJJycnGBvb4+RI0ciMDCwVCtAAVaARERUjn755Rc0bdoUTZs2BQBERkaiadOmmDBhAgBgy5YtaNq0qfHrpfr27YumTZsiNjbWOMfcuXPx0ksvITQ0FM899xx0Oh2++eabUsfyVF4HyFWgVF64CpTKi+KrQFtEPvygEso+MkexucoTW6BERDIyUwv0ScJXgIiIpMQKkIhIRvwKJyZAIiIpsQXKFigREcmJFSARkYzYAmUCJCKSElugbIESEZGcWAESEcmILVAmQCIiKbEFyhYoERHJiRUgEZGM2AJlAiQikhJboGyBEhGRnFgBEhHJiBUgEyARkZQs+Bkg3wIQEZGUWAESEcmILVAmQCIiKfEyCLZAiYhITqwAiYhkxBYoEyARkZTYAmULlIiI5MQKkIhIRmyBMgESEUmJLVC2QImISE6sAImIZMQWKBMgEZGU2AJlC5SIiOTECpCISEZsgTIBEhFJiS1QtkCJiEhOrACJiGTEFigrQCIiKakslNtKYd++fejWrRvc3d2hUqkQFxdnsl8IgQkTJsDNzQ02NjYICgrCmTNnTI65desW+vfvD3t7ezg4OGDw4MHIyMgo9UvABEhEROUmMzMTjRs3xqJFi4rcP3v2bMTExCA2NhaHDh2Cra0tgoODkZOTYzymf//++P3337Fr1y5899132LdvH4YNG1bqWNgCJSKSkZkWwXTp0gVdunQpcp8QAvPmzcOHH36IkJAQAMDnn38OV1dXxMXFoW/fvjh16hR27NiBI0eOoHnz5gCABQsW4MUXX8THH38Md3f3EsfCCpCISEYKtkANBgPS09NNNoPBUOqQkpOTkZKSgqCgIOOYVqtFQEAAEhISAAAJCQlwcHAwJj8ACAoKgoWFBQ4dOlSq8zEBEhHRY4mOjoZWqzXZoqOjSz1PSkoKAMDV1dVk3NXV1bgvJSUF1apVM9lfqVIlODk5GY8pKbZAiYhkpGALNCoqCpGRkSZjGo1GsfnLChMgEZGMFLwMQqPRKJLwdDodAECv18PNzc04rtfr0aRJE+Mx165dM3nc3bt3cevWLePjS4otUCIieiL4+PhAp9MhPj7eOJaeno5Dhw4hMDAQABAYGIjU1FQkJiYaj/nxxx9RUFCAgICAUp2PFSARkYzMtAo0IyMDZ8+eNf6cnJyMpKQkODk5wdPTE+Hh4Zg2bRrq1KkDHx8fjB8/Hu7u7ujevTsAwNfXF507d8bQoUMRGxuLvLw8jBgxAn379i3VClCACZCISEoqMyXAX375BR06dDD+fP+zw7CwMKxatQpjx45FZmYmhg0bhtTUVLRt2xY7duyAtbW18TFffPEFRowYgeeffx4WFhYIDQ1FTExMqWNRCSHE4z+lJ8u7W0+bOwSSxGD/6uYOgSTh526r6HyVQz9TbK6srwcpNld5YgVIRCQhc1WATxImQCIiGTH/cRUoERHJiRUgEZGE2AJlAiQikhITIFugREQkKVaAREQSYgXIBEhEJCUmQLZAiYhIUqwAiYhkxAKQCZCISEZsgbIFSkREkmIFSEQkIVaATIBERFJiAmQLlIiIJMUKkIhIQqwAmQCJiOTE/McWKBERyYkVIBGRhNgCZQIkIpISEyBboEREJClWgEREEmIFyARIRCQn5j+2QImISE6sAImIJMQWKBMgEZGUmADZAiUiIkmxAiQikhArQCZAIiIpMQGyBUpERJJiBUhEJCMWgEyAREQyYguULVAiIpIUEyARkYRUKpViW2nduXMH4eHh8PLygo2NDVq3bo0jR44Y9wshMGHCBLi5ucHGxgZBQUE4c+aMkk8fABMgEZGUzJkAhwwZgl27dmHNmjU4fvw4XnjhBQQFBeHvv/8GAMyePRsxMTGIjY3FoUOHYGtri+DgYOTk5Cj6GjABEhFRucnOzsbXX3+N2bNn47nnnkPt2rUxadIk1K5dG0uWLIEQAvPmzcOHH36IkJAQNGrUCJ9//jmuXLmCuLg4RWNhAiQikpFKuc1gMCA9Pd1kMxgMRZ727t27yM/Ph7W1tcm4jY0N9u/fj+TkZKSkpCAoKMi4T6vVIiAgAAkJCQq+AEyARERSUrIFGh0dDa1Wa7JFR0cXed4qVaogMDAQU6dOxZUrV5Cfn4+1a9ciISEBV69eRUpKCgDA1dXV5HGurq7GfUphAiQioscSFRWFtLQ0ky0qKqrY49esWQMhBDw8PKDRaBATE4N+/frBwqJ8UxITIBGRhJSsADUaDezt7U02jUZT7Llr1aqFvXv3IiMjA5cuXcLhw4eRl5eHmjVrQqfTAQD0er3JY/R6vXGfUnghvGTsrSvhJV8X1K9mC7WlCjcy8/Bl0lVcTrvXr+/bRIcWNbQmj/njWiaWH7psjnCpgtrx7Ubs2LIR11KuAgBqeNdEnwHD4B/QBgBw+9YNrI6dh2O/HEJ2diY8anijV//BCGz3vDnDlsqTcCG8ra0tbG1tcfv2bezcuROzZ8+Gj48PdDod4uPj0aRJEwBAeno6Dh06hLfeekvR8zMBSsTGygIj23ji7I0sLD90GZmGfFS1s0J2XoHJcaeuZWBD0v967XcLRHmHShWcs0s1vDZ0FNyqe0IIgd07t2LmhxH4ZNl6ePrUwvzoCcjMuIOo6XNhr3XAT/E78PGU9/BR7FrUrFPf3OFTGdu5cyeEEKhXrx7Onj2LMWPGoH79+nj99dehUqkQHh6OadOmoU6dOvDx8cH48ePh7u6O7t27KxoHE6BEOtZyQmp2HjYc+19yu5WdV+i4/AKBO4b88gyNnjItWrcz+fnVISOwc8sm/HnyODx9auH0iWN4IyIKdX0bAAB6vzYEWzZ9gXN/nmICLCfmrADvf0Z4+fJlODk5ITQ0FNOnT4eVlRUAYOzYscjMzMSwYcOQmpqKtm3bYseOHYVWjj4usybAGzdu4LPPPkNCQoJxdY9Op0Pr1q0xcOBAuLi4mDO8p46fzg6nr2digL87ajrbID3nLn6+kIpDF9NMjqvlXBmTXqiF7LwCnL2Rhf/8cR1ZD1SJRCWVn5+PA3t/QE5ONuo90wgAUK9BY+zf/T38Wz0LW7sq+HnPLuTlGtCgib+Zo5WIGTugffr0QZ8+fYrdr1KpMGXKFEyZMqVM4zBbAjxy5AiCg4NRuXJlBAUFoW7dugDufdAZExODmTNnYufOnWjevPm/zmMwGApdb3I3LxeVrNRlFntF5VzZCq29HLD3/G3En7mJGg7W6NGgGvILBH65nA7g3ud9x6/ewc2sPFS1VaNL/aoYGlAdMfsvgo1QKo2/zp/BuOEDkZubC2sbG4yb8glqeNcEAIyZOAsfT34PA0I6wNKyEjTW1hg35RO4eXiaOWqSidkS4MiRI9G7d2/ExsYWKsWFEHjzzTcxcuTIh174GB0djcmTJ5uMteo7HK3/b6TiMVd0KpUKl1Nz8J8/bgAA/k43QFdFg0AvB2MCTLpyx3h8yp1cXEk34IPna6J21co4cyPLLHFTxeRewxtzPl2PrIwMHNgXj5iZEzBt3qeo4V0T6z5bjMyMDEz+eAmqaB1x+Ofd+Gjye5gRswJeNeuYO3QpPAmLYMzNbJdBHDt2DBEREUX+ElQqFSIiIpCUlPTQeYq6/qRl7zfKIOKKLz3nLvR3TKtlfUYuHG2Kfx90KysPGYa7cLa1Kuvw6CljZWUFNw9P1Krnh9eGjoR3rbr47ut1uPr3JWzfvAEjxk5EI/8A+NSui1fC3kDten7YHveVucOWhjnvBfqkMFsFqNPpcPjwYdSvX/QH3ocPHy50J4CiaDSaQtebsP1ZtAu3suFiZ/rauNhZ4Xb23WIfo7WuhMpqS9zJKf4YopIoEAXIy8tDruHeDY1VFqb/cFpYWEAU8LNmKj9mS4CjR4/GsGHDkJiYiOeff96Y7PR6PeLj47F8+XJ8/PHH5grvqbTv/G2MbOuJ52s7IenKHXg6WqOVpwM2/XZvAZLaUoUX6lbFb1fv4I7hLqraqtHV1wU3M/Pwx3W2P6nk1ixfgGYtW8PF1Q3ZWZnYF78DvyclYsLsRfDw9IabRw3EzpmOsDcjUMVei8M/78GxxEP4YMZ8c4cujQpcuCnGbAlw+PDhqFq1KubOnYvFixcjP//esntLS0v4+/tj1apV/7pKiErvUloOVh75G119XdCprjNuZeXh29+v4de/733uVyAAd3sNmtewh42VJdJz7uL09Uzs+OMG8nktIJVC2u1bmB89Abdv3UBlWzt416yDCbMXoUnzVgCAD2cuwJplMZjxQThysrPg5l4Do8ZNhn+rtmaOXB4VuXWpFJUQwuz/suXl5eHGjXsLM6pWrWq8FuRRvbv1tBJhET3UYP/q5g6BJOHnbqvofHXG7FBsrjMfdVZsrvL0RFwIb2VlBTc3N3OHQUQkDRaAT0gCJCKi8sUWKL8NgoiIJMUKkIhIQiwAmQCJiKRkYcEMyBYoERFJiRUgEZGE2AJlBUhERJJiBUhEJCFeBsEESEQkJeY/tkCJiEhSrACJiCTEFigTIBGRlJgA2QIlIiJJsQIkIpIQC0AmQCIiKbEFyhYoERFJihUgEZGEWAAyARIRSYktULZAiYhIUqwAiYgkxAKQCZCISEpsgbIFSkREkmIFSEQkIRaATIBERFJiC5QtUCIikhQrQCIiCbEAZAVIRCQllUql2FYa+fn5GD9+PHx8fGBjY4NatWph6tSpEEIYjxFCYMKECXBzc4ONjQ2CgoJw5swZpV8CJkAiIio/s2bNwpIlS7Bw4UKcOnUKs2bNwuzZs7FgwQLjMbNnz0ZMTAxiY2Nx6NAh2NraIjg4GDk5OYrGwhYoEZGElGyBGgwGGAwGkzGNRgONRlPo2AMHDiAkJARdu3YFAHh7e2P9+vU4fPgwgHvV37x58/Dhhx8iJCQEAPD555/D1dUVcXFx6Nu3r2JxswIkIpKQki3Q6OhoaLVaky06OrrI87Zu3Rrx8fH4888/AQDHjh3D/v370aVLFwBAcnIyUlJSEBQUZHyMVqtFQEAAEhISFH0NWAESEdFjiYqKQmRkpMlYUdUfAIwbNw7p6emoX78+LC0tkZ+fj+nTp6N///4AgJSUFACAq6uryeNcXV2N+5TCBEhEJCElW6DFtTuL8tVXX+GLL77AunXr8MwzzyApKQnh4eFwd3dHWFiYckGVABMgEZGEzHUh/JgxYzBu3DjjZ3kNGzbEX3/9hejoaISFhUGn0wEA9Ho93NzcjI/T6/Vo0qSJorHwM0AiIio3WVlZsLAwTT2WlpYoKCgAAPj4+ECn0yE+Pt64Pz09HYcOHUJgYKCisbACJCKSkLkqwG7dumH69Onw9PTEM888g6NHj2LOnDkYNGiQMa7w8HBMmzYNderUgY+PD8aPHw93d3d0795d0ViYAImIJGSuO8EsWLAA48ePx9tvv41r167B3d0db7zxBiZMmGA8ZuzYscjMzMSwYcOQmpqKtm3bYseOHbC2tlY0FpX45+X3T4l3t542dwgkicH+1c0dAknCz91W0fnazf1Zsbn2RrRRbK7yxAqQiEhC/DYIJkAiIikx/3EVKBERSYoVIBGRhNgCZQIkIpIS8x9boEREJClWgEREErJgCcgESEQkI+Y/tkCJiEhSrACJiCTEVaBMgEREUrJg/mMLlIiI5MQKkIhIQmyBMgESEUmJ+Y8tUCIikhQrQCIiCanAEpAJkIhIQlwFyhYoERFJihUgEZGEuAqUCZCISErMf2yBEhGRpFgBEhFJiF+HxARIRCQl5j+2QImISFKsAImIJMRVoEyARERSYv5jC5SIiCTFCpCISEJcBcoESEQkJaY/tkCJiEhSrACJiCTEVaBMgEREUuLXIbEFSkREkmICJCKSkEqlUmwrDW9v7yLnGD58OAAgJycHw4cPh7OzM+zs7BAaGgq9Xl8WL0HJWqBbtmwp8YQvv/zyIwdDRETlw1wfAR45cgT5+fnGn0+cOIFOnTqhd+/eAICIiAhs27YNGzduhFarxYgRI9CzZ0/8/PPPisdSogTYvXv3Ek2mUqlMnhgREdE/ubi4mPw8c+ZM1KpVC+3atUNaWhpWrFiBdevWoWPHjgCAlStXwtfXFwcPHkSrVq0UjaVECbCgoEDRkxIRkXkpuQrUYDDAYDCYjGk0Gmg0mn99XG5uLtauXYvIyEioVCokJiYiLy8PQUFBxmPq168PT09PJCQkKJ4A+RkgEZGELFTKbdHR0dBqtSZbdHT0Q2OIi4tDamoqBg4cCABISUmBWq2Gg4ODyXGurq5ISUlR/DV4pMsgMjMzsXfvXly8eBG5ubkm+0aNGqVIYEREVDFERUUhMjLSZOxh1R8ArFixAl26dIG7u3tZhfavSp0Ajx49ihdffBFZWVnIzMyEk5MTbty4gcqVK6NatWpMgEREFYCSLdCStDsf9Ndff+GHH37AN998YxzT6XTIzc1FamqqSRWo1+uh0+mUCteo1C3QiIgIdOvWDbdv34aNjQ0OHjyIv/76C/7+/vj4448VD5CIiJSnUnB7FCtXrkS1atXQtWtX45i/vz+srKwQHx9vHDt9+jQuXryIwMDARzxT8UpdASYlJWHp0qWwsLCApaUlDAYDatasidmzZyMsLAw9e/ZUPEgiInp6FBQUYOXKlQgLC0OlSv9LQ1qtFoMHD0ZkZCScnJxgb2+PkSNHIjAwUPEFMMAjJEArKytYWNwrHKtVq4aLFy/C19cXWq0Wly5dUjxAIiJSnjm/DumHH37AxYsXMWjQoEL75s6dCwsLC4SGhsJgMCA4OBiLFy8ukzhKnQCbNm2KI0eOoE6dOmjXrh0mTJiAGzduYM2aNWjQoEFZxEhERAoz572wX3jhBQghitxnbW2NRYsWYdGiRWUeR6k/A5wxYwbc3NwAANOnT4ejoyPeeustXL9+HcuWLVM8QCIiorJQ6gqwefPmxv+uVq0aduzYoWhARERU9vh1SPw6JCIiKTH/PUIC9PHx+dd3DufPn3+sgIiIiMpDqRNgeHi4yc95eXk4evQoduzYgTFjxigVFxERlSFzrgJ9UpQ6Ab7zzjtFji9atAi//PLLYwdERERlj/lPwZthd+nSBV9//bVS0xEREZUpxRbBbNq0CU5OTkpNR0REZYirQB/xQvh/vnBCCKSkpOD69etldrV+aU3vUs/cIZAkHFuMMHcIJInsowsVnY/fhfcICTAkJMQkAVpYWMDFxQXt27dH/fr1FQ2OiIiorJQ6AU6aNKkMwiAiovLEFugjVMGWlpa4du1aofGbN2/C0tJSkaCIiKhsKfmN8BVVqRNgcTcwNRgMUKvVjx0QERFReShxCzQmJgbAvbL5008/hZ2dnXFffn4+9u3bx88AiYgqiIpcuSmlxAlw7ty5AO5VgLGxsSbtTrVaDW9vb8TGxiofIRERKY6fAZYiASYnJwMAOnTogG+++QaOjo5lFhQREVFZK/Uq0N27d5dFHEREVI7YAn2ERTChoaGYNWtWofHZs2ejd+/eigRFRERlS6VSbquoSp0A9+3bhxdffLHQeJcuXbBv3z5FgiIiIiprpW6BZmRkFHm5g5WVFdLT0xUJioiIyha/DukRKsCGDRtiw4YNhca//PJL+Pn5KRIUERGVLQsFt4qq1BXg+PHj0bNnT5w7dw4dO3YEAMTHx2PdunXYtGmT4gESERGVhVInwG7duiEuLg4zZszApk2bYGNjg8aNG+PHH3/k1yEREVUQ7IA+4vcBdu3aFV27dgUApKenY/369Rg9ejQSExORn5+vaIBERKQ8fgb4GO3bffv2ISwsDO7u7vjkk0/QsWNHHDx4UMnYiIiIykypKsCUlBSsWrUKK1asQHp6Ovr06QODwYC4uDgugCEiqkBYAJaiAuzWrRvq1auH3377DfPmzcOVK1ewYMGCsoyNiIjKCL8OqRQV4H/+8x+MGjUKb731FurUqVOWMREREZW5EleA+/fvx507d+Dv74+AgAAsXLgQN27cKMvYiIiojFioVIptFVWJE2CrVq2wfPlyXL16FW+88Qa+/PJLuLu7o6CgALt27cKdO3fKMk4iIlIQ7wX6CKtAbW1tMWjQIOzfvx/Hjx/Hu+++i5kzZ6JatWp4+eWXyyJGIiIixT3WXWzq1auH2bNn4/Lly1i/fr1SMRERURnjIphHvBD+QZaWlujevTu6d++uxHRERFTGVKjAmUshFfk+pkREVAH9/fffePXVV+Hs7AwbGxs0bNgQv/zyi3G/EAITJkyAm5sbbGxsEBQUhDNnzigeBxMgEZGEzNUCvX37Ntq0aQMrKyv85z//wcmTJ/HJJ5/A0dHReMzs2bMRExOD2NhYHDp0CLa2tggODkZOTo6ir4EiLVAiIqpYzPXZ3axZs1CjRg2sXLnSOObj42P8byEE5s2bhw8//BAhISEAgM8//xyurq6Ii4tD3759FYuFFSARET0Wg8GA9PR0k81gMBR57JYtW9C8eXP07t0b1apVQ9OmTbF8+XLj/uTkZKSkpCAoKMg4ptVqERAQgISEBEXjZgIkIpKQSqVSbIuOjoZWqzXZoqOjizzv+fPnsWTJEtSpUwc7d+7EW2+9hVGjRmH16tUA7t1zGgBcXV1NHufq6mrcpxS2QImIJKRkCzQqKgqRkZEmYxqNpshjCwoK0Lx5c8yYMQMA0LRpU5w4cQKxsbEICwtTLqgSYAVIRESPRaPRwN7e3mQrLgG6ubkV+vYgX19fXLx4EQCg0+kAAHq93uQYvV5v3KcUJkAiIgmZ61Zobdq0wenTp03G/vzzT3h5eQG4tyBGp9MhPj7euD89PR2HDh1CYGDgYz/vf2ILlIhIQua6iXVERARat26NGTNmoE+fPjh8+DCWLVuGZcuWAbj32WR4eDimTZuGOnXqwMfHB+PHj4e7u7viN1thAiQionLTokULbN68GVFRUZgyZQp8fHwwb9489O/f33jM2LFjkZmZiWHDhiE1NRVt27bFjh07YG1trWgsKiGEUHTGJ0DOXXNHQLJwbDHC3CGQJLKPLlR0vpj9yYrNNaqtz8MPegKxAiQiklBF/hojpXARDBERSYkVIBGRhCz4bRBMgEREMmILlC1QIiKSFCtAIiIJVeRvclcKEyARkYTMdSH8k4QtUCIikhIrQCIiCbEAZAIkIpISW6BsgRIRkaRYARIRSYgFIBMgEZGU2P7ja0BERJJiBUhEJCEVe6BMgEREMmL6YwuUiIgkxQqQiEhCvA6QCZCISEpMf2yBEhGRpFgBEhFJiB1QJkAiIinxMgi2QImISFKsAImIJMTqhwmQiEhKbIHyTQAREUmKFSARkYRY/zEBEhFJiS1QtkCJiEhSrACJiCTE6ocJkIhISmyB8k0AERFJihUgEZGEWP+xAiQikpJKpdxWGpMmTYJKpTLZ6tevb9yfk5OD4cOHw9nZGXZ2dggNDYVer1f42d/DBEhEROXqmWeewdWrV43b/v37jfsiIiKwdetWbNy4EXv37sWVK1fQs2fPMomDLVAiIglZmLEJWqlSJeh0ukLjaWlpWLFiBdatW4eOHTsCAFauXAlfX18cPHgQrVq1UjQOVoBERBJSsgVqMBiQnp5ushkMhmLPfebMGbi7u6NmzZro378/Ll68CABITExEXl4egoKCjMfWr18fnp6eSEhIUPw1YAIkIqLHEh0dDa1Wa7JFR0cXeWxAQABWrVqFHTt2YMmSJUhOTsazzz6LO3fuICUlBWq1Gg4ODiaPcXV1RUpKiuJxswVKRCQhlYIt0KioKERGRpqMaTSaIo/t0qWL8b8bNWqEgIAAeHl54auvvoKNjY1iMZUEEyARkYSUvA5eo9EUm/AexsHBAXXr1sXZs2fRqVMn5ObmIjU11aQK1Ov1RX5m+LjYAiUiIrPJyMjAuXPn4ObmBn9/f1hZWSE+Pt64//Tp07h48SICAwMVPzcrQCIiCZlrFejo0aPRrVs3eHl54cqVK5g4cSIsLS3Rr18/aLVaDB48GJGRkXBycoK9vT1GjhyJwMBAxVeAAkyARERSMtetQC9fvox+/frh5s2bcHFxQdu2bXHw4EG4uLgAAObOnQsLCwuEhobCYDAgODgYixcvLpNYVEIIUSYzm1HOXXNHQLJwbDHC3CGQJLKPLlR0vp0nrys2V7Cfi2JzlSdWgEREEuKXQTABEhFJScnLICoqrgIlIiIpsQIkIpKQBQtAJkAiIhmxBcoWKBERSYoVIBGRhLgKlAmQiEhKbIGyBUpERJJiBUhEJCGuAmUCJCKSElugTIBSWbF8KeJ3fY/k5PPQWFujSZOmCI8cDW+fmsZjpkyagEMHD+D6tWuoXLkyGv/3GJ+atcwYOT3p2jSrhYgBQWjm5wk3Fy36RCzD1j2/GfeHdGyMIb3aoqmvJ5wdbBHwSjR++/Nvkzk06kqYGdkTvYP9oVFXwg8Jp/DOjA24dutOeT8dkgQ/A5TIL0cO45V+/bFm/VdYunwl7t69izeHDkZWVpbxGD+/ZzBlWjQ2b92OJctWQAiBN4cORn5+vhkjpyedrY0Gx//8G+HRG4rcX9lGjQNJ5/BhTFyxc8weHYquzzVA/7Er8MKQeXBz0eLLT4aUUcSkUim3VVSsACWyZNkKk5+nTJ+JDs8G4tTJ3+HfvAUAoFefV4z7PTyqY8SocPTuGYIrf/+NGp6e5RovVRzf/3wS3/98stj967cdAQB4ujkVud/ezhoDuwdi4PursPfInwCAYRPX4tjm8WjZ0BuHj19QPGbZVeC8pRhWgBLLuHOvtWSv1Ra5PysrC99u/gYe1atDp9OVZ2gkmaa+nlBbVcKPB08bx/68oMfFq7cQ0MjHjJHR06zCV4AGgwEGg8FkTFhqoNFozBRRxVBQUIDZs2agSdNmqFOnrsm+Deu/wNxPPkZ2dha8fXywdPlKWKnVZoqUZKBztochNw9pGdkm49dupsPV2d5MUT3dLCpy71IhT3QFeOnSJQwaNOhfj4mOjoZWqzXZPpoVXU4RVlwzpk3GuTNnMPvjuYX2vfjSy9jw9WZ8tnotvLy8Mebd8EJvMoioYlMpuFVUT3QCvHXrFlavXv2vx0RFRSEtLc1kG/NeVDlFWDHNmDYF+/buwfKVq+FaRGuzSpUq8PLyhn/zFvhkbgySk8/jxx92mSFSkkXKzXRo1FbQ2tmYjFdztof+ZrqZoqKnnVlboFu2bPnX/efPn3/oHBpN4XZnzt3HCuupJYRA9PSp+DF+F1asWoPq1Ws8/DH3Hojc3Nwyj4/kdfTUReTm3UWHgHqIi08CANTxqgZPNycc+i3ZvME9rSpy6aYQsybA7t27Q6VSQQhR7DEq9qkVM2PqZPxn+3eYt2AxbCvb4sb16wAAuypVYG1tjcuXLmHnju0IbN0Gjo5O0OtT8Nmny6DRWKPtc+3MHD09yWxt1KhVw8X4s7eHMxrV9cDt9CxcSrkNR/vKqKFzhFu1ewuu6nq7AgD0N9Ohv3kH6Rk5WBWXgFnv9sSttEzcyczBnPd64+Cx81wBWkZ4ITygEv+WfcqYh4cHFi9ejJCQkCL3JyUlwd/fv9TXoLECLFrjZ+oVOT5lWjRCevTEtWt6TJ7wIU6e/B3paelwruoMf//meOOt4SYXy9P/OLYYYe4QngjP+tfB95++U2h8zZaDGDZxLV7tFoDlU14rtH9a7HZMX7odwP8uhO/T+b8Xwh84hXeiN0B/kxfCA0D20YWKznfoXJpicwXUKnol+ZPOrAnw5ZdfRpMmTTBlypQi9x87dgxNmzZFQUFBqeZlAqTywgRI5UXpBHj4vHIJsGXNipkAzdoCHTNmDDIzM4vdX7t2bezevbscIyIikgMboGZOgM8+++y/7re1tUW7dvzsiYiIlFfhL4QnIqJHwBKQCZCISEZcBfqEXwhPRERUVlgBEhFJiJdYswIkIiJJsQIkIpIQC0AmQCIiOTEDsgVKRERyYgVIRCQhXgbBBEhEJCWuAmULlIiIzGTmzJlQqVQIDw83juXk5GD48OFwdnaGnZ0dQkNDodfry+T8TIBERBJSKbg9iiNHjmDp0qVo1KiRyXhERAS2bt2KjRs3Yu/evbhy5Qp69uz5iGf5d0yAREQyUjADGgwGpKenm2wGg6HYU2dkZKB///5Yvnw5HB0djeNpaWlYsWIF5syZg44dO8Lf3x8rV67EgQMHcPDgQcVfAiZAIiJ6LNHR0dBqtSZbdHR0sccPHz4cXbt2RVBQkMl4YmIi8vLyTMbr168PT09PJCQkKB43F8EQEUlIyVWgUVFRiIyMNBnTaDRFHvvll1/i119/xZEjRwrtS0lJgVqthoODg8m4q6srUlJSFIv3PiZAIiIJKbkKVKPRFJvw/unSpUt45513sGvXLlhbWysXwCNiC5SIiMpFYmIirl27hmbNmqFSpUqoVKkS9u7di5iYGFSqVAmurq7Izc1FamqqyeP0ej10Op3i8bACJCKSkDkuA3z++edx/Phxk7HXX38d9evXx3vvvYcaNWrAysoK8fHxCA0NBQCcPn0aFy9eRGBgoOLxMAESEcnIDBmwSpUqaNCggcmYra0tnJ2djeODBw9GZGQknJycYG9vj5EjRyIwMBCtWrVSPB4mQCIiemLMnTsXFhYWCA0NhcFgQHBwMBYvXlwm51IJIUSZzGxGOXfNHQHJwrHFCHOHQJLIPrpQ0fl+/ztTsbme8bBVbK7yxAqQiEhCvBcoV4ESEZGkWAESEUmIBSATIBGRnJgB2QIlIiI5sQIkIpIQvxGeCZCISEpcBcoWKBERSYoVIBGRhFgAMgESEcmJGZAtUCIikhMrQCIiCXEVKBMgEZGUuAqULVAiIpIUK0AiIgmxAGQCJCKSEzMgW6BERCQnVoBERBLiKlAmQCIiKXEVKFugREQkKVaAREQSYgHIBEhEJCdmQLZAiYhITqwAiYgkxFWgTIBERFLiKlC2QImISFKsAImIJMQCkAmQiEhKbIGyBUpERJJiBUhEJCWWgEyAREQSYguULVAiIpIUK0AiIgmxAGQFSEQkJZVKua00lixZgkaNGsHe3h729vYIDAzEf/7zH+P+nJwcDB8+HM7OzrCzs0NoaCj0er3Cz/4eJkAiIio31atXx8yZM5GYmIhffvkFHTt2REhICH7//XcAQEREBLZu3YqNGzdi7969uHLlCnr27FkmsaiEEKJMZjajnLvmjoBk4dhihLlDIElkH12o6HwpaXmKzaXTWj3W452cnPDRRx+hV69ecHFxwbp169CrVy8AwB9//AFfX18kJCSgVatWSoRrxAqQiEhGKuU2g8GA9PR0k81gMDw0hPz8fHz55ZfIzMxEYGAgEhMTkZeXh6CgIOMx9evXh6enJxISEpR77v/FBEhERI8lOjoaWq3WZIuOji72+OPHj8POzg4ajQZvvvkmNm/eDD8/P6SkpECtVsPBwcHkeFdXV6SkpCgeN1eBEhFJSMlVoFFRUYiMjDQZ02g0xR5fr149JCUlIS0tDZs2bUJYWBj27t2rYEQlwwRIRCQhJS+E12g0/5rwHqRWq1G7dm0AgL+/P44cOYL58+fjlVdeQW5uLlJTU02qQL1eD51Op1zA/8UWKBERmVVBQQEMBgP8/f1hZWWF+Ph4477Tp0/j4sWLCAwMVPy8rACJiCRkrm+Ej4qKQpcuXeDp6Yk7d+5g3bp12LNnD3bu3AmtVovBgwcjMjISTk5OsLe3x8iRIxEYGKj4ClCACZCISE5muhXMtWvXMGDAAFy9ehVarRaNGjXCzp070alTJwDA3LlzYWFhgdDQUBgMBgQHB2Px4sVlEguvAyR6DLwOkMqL0tcBXs9Q7h9KF7uKWUtVzKiJiOix8F6gTIBERFLi1yFxFSgREUmKFSARkYTMtQr0ScIESEQkIbZA2QIlIiJJMQESEZGU2AIlIpIQW6CsAImISFKsAImIJMRVoEyARERSYguULVAiIpIUK0AiIgmxAGQCJCKSEzMgW6BERCQnVoBERBLiKlAmQCIiKXEVKFugREQkKVaAREQSYgHIBEhEJCdmQLZAiYhITqwAiYgkxFWgTIBERFLiKlC2QImISFIqIYQwdxBkfgaDAdHR0YiKioJGozF3OPQU498aPSmYAAkAkJ6eDq1Wi7S0NNjb25s7HHqK8W+NnhRsgRIRkZSYAImISEpMgEREJCUmQAIAaDQaTJw4kYsSqMzxb42eFFwEQ0REUmIFSEREUmICJCIiKTEBEhGRlJgAiYhISkyAhEWLFsHb2xvW1tYICAjA4cOHzR0SPYX27duHbt26wd3dHSqVCnFxceYOiSTHBCi5DRs2IDIyEhMnTsSvv/6Kxo0bIzg4GNeuXTN3aPSUyczMROPGjbFo0SJzh0IEgJdBSC8gIAAtWrTAwoULAQAFBQWoUaMGRo4ciXHjxpk5OnpaqVQqbN68Gd27dzd3KCQxVoASy83NRWJiIoKCgoxjFhYWCAoKQkJCghkjIyIqe0yAErtx4wby8/Ph6upqMu7q6oqUlBQzRUVEVD6YAImISEpMgBKrWrUqLC0todfrTcb1ej10Op2ZoiIiKh9MgBJTq9Xw9/dHfHy8caygoADx8fEIDAw0Y2RERGWvkrkDIPOKjIxEWFgYmjdvjpYtW2LevHnIzMzE66+/bu7Q6CmTkZGBs2fPGn9OTk5GUlISnJyc4OnpacbISFa8DIKwcOFCfPTRR0hJSUGTJk0QExODgIAAc4dFT5k9e/agQ4cOhcbDwsKwatWq8g+IpMcESEREUuJngEREJCUmQCIikhITIBERSYkJkIiIpMQESEREUmICJCIiKTEBEhGRlJgAiYhISkyARCU0cOBAky9wbd++PcLDw8s9jj179kClUiE1NbXcz030NGECpApv4MCBUKlUUKlUUKvVqF27NqZMmYK7d++W6Xm/+eYbTJ06tUTHMmkRPXl4M2x6KnTu3BkrV66EwWDA9u3bMXz4cFhZWSEqKsrkuNzcXKjVakXO6eTkpMg8RGQerADpqaDRaKDT6eDl5YW33noLQUFB2LJli7FtOX36dLi7u6NevXoAgEuXLqFPnz5wcHCAk5MTQkJCcOHCBeN8+fn5iIyMhIODA5ydnTF27Fg8eNvcB1ugBoMB7733HmrUqAGNRoPatWtjxYoVuHDhgvEm0I6OjlCpVBg4cCCAe18/FR0dDR8fH9jY2KBx48bYtGmTyXm2b9+OunXrwsbGBh06dDCJk4geHRMgPZVsbGyQm5sLAIiPj8fp06exa9cufPfdd8jLy0NwcDCqVKmCn376CT///DPs7OzQuXNn42M++eQTrFq1Cp999hn279+PW7duYfPmzf96zgEDBmD9+vWIiYnBqVOnsHTpUtjZ2aFGjRr4+uuvAQCnT5/G1atXMX/+fABAdHQ0Pv/8c8TGxuL3339HREQEXn31VezduxfAvUTds2dPdOvWDUlJSRgyZAjGjRtXVi8bkVwEUQUXFhYmQkJChBBCFBQUiF27dgmNRiNGjx4twsLChKurqzAYDMbj16xZI+rVqycKCgqMYwaDQdjY2IidO3cKIYRwc3MTs2fPNu7Py8sT1atXN55HCCHatWsn3nnnHSGEEKdPnxYAxK5du4qMcffu3QKAuH37tnEsJydHVK5cWRw4cMDk2MGDB4t+/foJIYSIiooSfn5+Jvvfe++9QnMRUenxM0B6Knz33Xews7NDXl4eCgoK8H//93+YNGkShg8fjoYNG5p87nfs2DGcPXsWVapUMZkjJycH586dQ1paGq5evWrynYiVKlVC8+bNC7VB70tKSoKlpSXatWtX4pjPnj2LrKwsdOrUyWQ8NzcXTZs2BQCcOnWq0HczBgYGlvgcRFQ8JkB6KnTo0AFLliyBWq2Gu7s7KlX635+2ra2tybEZGRnw9/fHF198UWgeFxeXRzq/jY1NqR+TkZEBANi2bRs8PDxM9mk0mkeKg4hKjgmQngq2traoXbt2iY5t1qwZNmzYgGrVqsHe3r7IY9zc3HDo0CE899xzAIC7d+8iMTERzZo1K/L4hg0boqCgAHv37kVQUFCh/fcr0Pz8fOOYn58fNBoNLl68WGzl6Ovriy1btpiMHTx48OFPkogeiotgSDr9+/dH1apVERISgp9++gnJycnYs2cPRo0ahcuXLwMA3nnnHcycORNxcXH4448/8Pbbb//rNXze3t4ICwvDoEGDEBcXZ5zzq6++AgB4eXlBpVLhu+++w/Xr15GRkYEqVapg9OjRiIiIwOrVq3Hu3Dn8+uuvWLBgAVavXg0AePPNN3HmzBmMGTMGp0+fxrp167Bq1aqyfomIpMAESNKpXLky9u3bB09PT/Ts2RO+vr4YPHgwcnJyjBXhu+++i9deew1hYWEIDAxElSpV0KNHj3+dd8mSJejVqxfefvtt1K9fH0OHDkVmZiYAwMPDA5MnT8a4cePg6uqKESNGAACmTp2K8ePHIzo6Gr6+vujcuTO2bdsGHx8fAICnpye+/vprxMXFoXHjxoiNjcWMGTPK8NUhkodKFPepPhER0VOMFSAREUmJCZCIiKTEBEhERFJiAiQiIikxARIRkZSYAImISEpMgEREJCUmQCIikhITIBERSYkJkIiIpMQESEREUvp/55loDk4SLWgAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "y_64CFS4HGoO"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}